The following values were not passed to `accelerate launch` and had defaults used instead:
	`--num_processes` was set to a value of `4`
		More than one GPU was found, enabling multi-GPU training.
		If this was unintended please pass in `--num_processes=1`.
	`--num_machines` was set to a value of `1`
	`--mixed_precision` was set to a value of `'no'`
	`--dynamo_backend` was set to a value of `'no'`
To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
gradient_accumulation_steps:  4
gradient_accumulation_steps:  4
Params using prompt template alpaca:
base_model: baichuan-inc/Baichuan2-7B-Base
data_path: ../../data/belle_dolphine/p19.jsonl
output_dir: ../out/lora/p19
batch_size: 32
micro_batch_size: 2
num_epochs: 1
learning_rate: 0.0004
cutoff_len: 4096
val_set_size: 0
lr_scheduler: cosine
warmup_steps: 100
lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules: ['gate_proj', 'down_proj', 'up_proj']
train_on_inputs: False
add_eos_token: False
group_by_length: False
wandb_project: lora-moe
wandb_run_name: belle_dolphine-p19
wandb_watch: 
wandb_log_model: 
resume_from_checkpoint: False

gradient_accumulation_steps:  4
gradient_accumulation_steps:  4

Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards:  50%|█████     | 1/2 [00:10<00:10, 10.53s/it]
Loading checkpoint shards:  50%|█████     | 1/2 [00:11<00:11, 11.67s/it]
Loading checkpoint shards:  50%|█████     | 1/2 [00:11<00:11, 11.77s/it]
Loading checkpoint shards:  50%|█████     | 1/2 [00:12<00:12, 12.08s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:15<00:00,  7.52s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:15<00:00,  7.98s/it]

Loading checkpoint shards: 100%|██████████| 2/2 [00:16<00:00,  7.90s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:16<00:00,  8.47s/it]
pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None

Loading checkpoint shards: 100%|██████████| 2/2 [00:17<00:00,  8.05s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:17<00:00,  8.65s/it]

Loading checkpoint shards: 100%|██████████| 2/2 [00:17<00:00,  8.08s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:17<00:00,  8.63s/it]
pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
pre-trained model's BOS EOS and PAD token id: 1 2 0  => It should be 1 2 None
trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183

Map:   0%|          | 0/114105 [00:00<?, ? examples/s]
Map:   0%|          | 69/114105 [00:00<02:49, 672.47 examples/s]
Map:   0%|          | 147/114105 [00:00<02:36, 730.24 examples/s]
Map:   0%|          | 222/114105 [00:00<02:34, 734.80 examples/s]
Map:   0%|          | 300/114105 [00:00<02:31, 749.63 examples/s]
Map:   0%|          | 381/114105 [00:00<02:27, 768.52 examples/s]
Map:   0%|          | 490/114105 [00:00<02:32, 744.71 examples/s]
Map:   1%|          | 571/114105 [00:00<02:29, 757.25 examples/s]trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183

Map:   1%|          | 677/114105 [00:00<02:34, 734.28 examples/s]
Map:   0%|          | 0/114105 [00:00<?, ? examples/s]
Map:   1%|          | 757/114105 [00:01<02:31, 749.12 examples/s]trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183

Map:   0%|          | 65/114105 [00:00<02:59, 635.29 examples/s]
Map:   0%|          | 0/114105 [00:00<?, ? examples/s]
Map:   1%|          | 838/114105 [00:01<02:28, 760.46 examples/s]
Map:   0%|          | 132/114105 [00:00<02:55, 651.23 examples/s]
Map:   0%|          | 59/114105 [00:00<03:19, 572.75 examples/s]trainable params: 23,199,744 || all params: 7,529,172,992 || trainable%: 0.30813137146205183

Map:   1%|          | 916/114105 [00:01<02:28, 762.48 examples/s]
Map:   0%|          | 231/114105 [00:00<02:54, 653.56 examples/s]
Map:   0%|          | 0/114105 [00:00<?, ? examples/s]
Map:   0%|          | 136/114105 [00:00<02:46, 686.36 examples/s]
Map:   0%|          | 304/114105 [00:00<02:48, 677.36 examples/s]
Map:   0%|          | 53/114105 [00:00<03:39, 519.36 examples/s]
Map:   0%|          | 207/114105 [00:00<02:45, 689.69 examples/s]
Map:   1%|          | 1000/114105 [00:01<03:12, 588.84 examples/s]
Map:   0%|          | 376/114105 [00:00<02:44, 689.82 examples/s]
Map:   0%|          | 109/114105 [00:00<03:33, 534.79 examples/s]
Map:   0%|          | 284/114105 [00:00<02:38, 717.10 examples/s]
Map:   1%|          | 1074/114105 [00:01<03:01, 623.43 examples/s]
Map:   0%|          | 448/114105 [00:00<02:43, 696.61 examples/s]
Map:   0%|          | 167/114105 [00:00<03:26, 551.67 examples/s]
Map:   0%|          | 356/114105 [00:00<02:39, 715.24 examples/s]
Map:   1%|          | 1156/114105 [00:01<02:48, 669.94 examples/s]
Map:   0%|          | 520/114105 [00:00<02:42, 699.19 examples/s]
Map:   0%|          | 229/114105 [00:00<03:18, 573.18 examples/s]
Map:   1%|          | 1232/114105 [00:01<02:43, 690.13 examples/s]
Map:   0%|          | 465/114105 [00:00<02:38, 717.11 examples/s]
Map:   0%|          | 310/114105 [00:00<02:54, 652.93 examples/s]
Map:   1%|          | 626/114105 [00:00<02:42, 699.78 examples/s]
Map:   1%|          | 1317/114105 [00:01<02:34, 731.50 examples/s]
Map:   0%|          | 386/114105 [00:00<02:45, 686.46 examples/s]
Map:   0%|          | 567/114105 [00:00<02:42, 698.78 examples/s]
Map:   1%|          | 698/114105 [00:01<02:41, 703.06 examples/s]
Map:   1%|          | 1394/114105 [00:01<02:32, 738.00 examples/s]
Map:   0%|          | 470/114105 [00:00<02:34, 734.56 examples/s]
Map:   1%|▏         | 1472/114105 [00:02<02:31, 745.00 examples/s]
Map:   1%|          | 669/114105 [00:00<02:45, 687.35 examples/s]
Map:   1%|          | 801/114105 [00:01<02:43, 693.51 examples/s]
Map:   0%|          | 551/114105 [00:00<02:30, 753.33 examples/s]
Map:   1%|▏         | 1555/114105 [00:02<02:27, 763.76 examples/s]
Map:   1%|          | 631/114105 [00:00<02:29, 761.46 examples/s]
Map:   1%|          | 766/114105 [00:01<02:49, 668.23 examples/s]
Map:   1%|          | 908/114105 [00:01<02:42, 697.59 examples/s]
Map:   1%|▏         | 1636/114105 [00:02<02:25, 772.50 examples/s]
Map:   1%|          | 980/114105 [00:01<02:41, 699.10 examples/s]
Map:   2%|▏         | 1717/114105 [00:02<02:24, 778.83 examples/s]
Map:   1%|          | 745/114105 [00:01<02:30, 755.08 examples/s]
Map:   1%|          | 864/114105 [00:01<02:51, 662.15 examples/s]
Map:   2%|▏         | 1796/114105 [00:02<02:23, 781.41 examples/s]
Map:   1%|          | 825/114105 [00:01<02:27, 766.02 examples/s]
Map:   1%|          | 934/114105 [00:01<02:49, 668.46 examples/s]
Map:   2%|▏         | 1875/114105 [00:02<02:23, 782.56 examples/s]
Map:   1%|          | 905/114105 [00:01<02:26, 771.93 examples/s]
Map:   1%|          | 1063/114105 [00:01<03:26, 546.23 examples/s]
Map:   1%|          | 1136/114105 [00:01<03:13, 584.72 examples/s]
Map:   2%|▏         | 1987/114105 [00:02<02:26, 763.81 examples/s]
Map:   1%|          | 1032/114105 [00:01<03:38, 517.49 examples/s]
Map:   1%|          | 1207/114105 [00:01<03:04, 611.61 examples/s]
Map:   1%|          | 1000/114105 [00:01<03:09, 597.04 examples/s]
Map:   1%|          | 1107/114105 [00:01<03:20, 562.35 examples/s]
Map:   1%|          | 1282/114105 [00:01<02:55, 644.34 examples/s]
Map:   1%|          | 1081/114105 [00:01<02:55, 643.85 examples/s]
Map:   2%|▏         | 2082/114105 [00:02<03:04, 608.03 examples/s]
Map:   1%|          | 1188/114105 [00:01<03:03, 614.17 examples/s]
Map:   1%|          | 1360/114105 [00:02<02:46, 677.54 examples/s]
Map:   1%|          | 1158/114105 [00:01<02:48, 671.36 examples/s]
Map:   2%|▏         | 2163/114105 [00:03<02:52, 649.27 examples/s]
Map:   1%|          | 1272/114105 [00:01<02:49, 664.93 examples/s]
Map:   1%|▏         | 1435/114105 [00:02<02:42, 694.74 examples/s]
Map:   1%|          | 1238/114105 [00:01<02:41, 700.40 examples/s]
Map:   2%|▏         | 2247/114105 [00:03<02:41, 691.27 examples/s]
Map:   1%|          | 1355/114105 [00:02<02:40, 703.61 examples/s]
Map:   1%|▏         | 1513/114105 [00:02<02:37, 714.25 examples/s]
Map:   1%|          | 1316/114105 [00:01<02:37, 717.29 examples/s]
Map:   2%|▏         | 2323/114105 [00:03<02:38, 707.21 examples/s]
Map:   1%|▏         | 1438/114105 [00:02<02:33, 735.72 examples/s]
Map:   1%|▏         | 1588/114105 [00:02<02:36, 720.42 examples/s]
Map:   1%|          | 1397/114105 [00:02<02:32, 738.74 examples/s]
Map:   2%|▏         | 2403/114105 [00:03<02:33, 728.57 examples/s]
Map:   1%|▏         | 1520/114105 [00:02<02:29, 754.78 examples/s]
Map:   1%|▏         | 1663/114105 [00:02<02:35, 724.53 examples/s]
Map:   1%|▏         | 1477/114105 [00:02<02:29, 754.05 examples/s]
Map:   2%|▏         | 2484/114105 [00:03<02:28, 750.18 examples/s]
Map:   1%|▏         | 1606/114105 [00:02<02:23, 782.29 examples/s]
Map:   2%|▏         | 1772/114105 [00:02<02:35, 723.21 examples/s]
Map:   1%|▏         | 1691/114105 [00:02<02:20, 797.88 examples/s]
Map:   1%|▏         | 1592/114105 [00:02<02:29, 755.00 examples/s]
Map:   2%|▏         | 2604/114105 [00:03<02:25, 765.64 examples/s]
Map:   2%|▏         | 1851/114105 [00:02<02:32, 737.70 examples/s]
Map:   1%|▏         | 1669/114105 [00:02<02:28, 756.38 examples/s]
Map:   2%|▏         | 2689/114105 [00:03<02:21, 785.31 examples/s]
Map:   2%|▏         | 1815/114105 [00:02<02:19, 804.33 examples/s]
Map:   2%|▏         | 1928/114105 [00:02<02:30, 744.73 examples/s]
Map:   2%|▏         | 2773/114105 [00:03<02:19, 797.69 examples/s]
Map:   2%|▏         | 1779/114105 [00:02<02:30, 744.20 examples/s]
Map:   2%|▏         | 1935/114105 [00:02<02:20, 799.83 examples/s]
Map:   2%|▏         | 1863/114105 [00:02<02:26, 765.66 examples/s]
Map:   3%|▎         | 2891/114105 [00:03<02:20, 792.06 examples/s]
Map:   2%|▏         | 2040/114105 [00:03<03:08, 594.90 examples/s]
Map:   2%|▏         | 1944/114105 [00:02<02:24, 774.35 examples/s]
Map:   3%|▎         | 2974/114105 [00:04<02:19, 797.94 examples/s]
Map:   2%|▏         | 2119/114105 [00:03<02:56, 635.53 examples/s]
Map:   2%|▏         | 2039/114105 [00:03<02:55, 639.50 examples/s]
Map:   2%|▏         | 2202/114105 [00:03<02:44, 679.59 examples/s]
Map:   2%|▏         | 2119/114105 [00:03<02:46, 671.84 examples/s]
Map:   2%|▏         | 2037/114105 [00:02<03:08, 593.49 examples/s]
Map:   3%|▎         | 3082/114105 [00:04<02:52, 641.83 examples/s]
Map:   2%|▏         | 2284/114105 [00:03<02:37, 711.25 examples/s]
Map:   2%|▏         | 2200/114105 [00:03<02:39, 702.68 examples/s]
Map:   2%|▏         | 2117/114105 [00:03<02:55, 638.59 examples/s]
Map:   3%|▎         | 3168/114105 [00:04<02:41, 687.19 examples/s]
Map:   2%|▏         | 2365/114105 [00:03<02:31, 736.20 examples/s]
Map:   2%|▏         | 2280/114105 [00:03<02:34, 723.55 examples/s]
Map:   2%|▏         | 2206/114105 [00:03<02:40, 696.39 examples/s]
Map:   3%|▎         | 3259/114105 [00:04<02:30, 738.17 examples/s]
Map:   2%|▏         | 2443/114105 [00:03<02:30, 743.89 examples/s]
Map:   2%|▏         | 2362/114105 [00:03<02:29, 746.22 examples/s]
Map:   2%|▏         | 2296/114105 [00:03<02:30, 744.46 examples/s]
Map:   3%|▎         | 3345/114105 [00:04<02:24, 766.34 examples/s]
Map:   2%|▏         | 2524/114105 [00:03<02:26, 760.63 examples/s]
Map:   2%|▏         | 2443/114105 [00:03<02:26, 761.93 examples/s]
Map:   2%|▏         | 2381/114105 [00:03<02:25, 768.67 examples/s]
Map:   3%|▎         | 3431/114105 [00:04<02:20, 789.00 examples/s]
Map:   2%|▏         | 2605/114105 [00:03<02:24, 771.03 examples/s]
Map:   2%|▏         | 2526/114105 [00:03<02:23, 776.47 examples/s]
Map:   2%|▏         | 2463/114105 [00:03<02:23, 779.59 examples/s]
Map:   3%|▎         | 3514/114105 [00:04<02:18, 795.69 examples/s]
Map:   2%|▏         | 2610/114105 [00:03<02:20, 792.81 examples/s]
Map:   2%|▏         | 2721/114105 [00:03<02:24, 770.23 examples/s]
Map:   2%|▏         | 2544/114105 [00:03<02:21, 786.69 examples/s]
Map:   2%|▏         | 2695/114105 [00:03<02:17, 807.48 examples/s]
Map:   3%|▎         | 3640/114105 [00:04<02:16, 808.85 examples/s]
Map:   2%|▏         | 2803/114105 [00:04<02:22, 781.95 examples/s]
Map:   2%|▏         | 2630/114105 [00:03<02:18, 804.41 examples/s]
Map:   3%|▎         | 2886/114105 [00:04<02:20, 789.71 examples/s]
Map:   2%|▏         | 2818/114105 [00:03<02:18, 805.14 examples/s]
Map:   2%|▏         | 2713/114105 [00:03<02:17, 808.18 examples/s]
Map:   3%|▎         | 3765/114105 [00:05<02:15, 815.54 examples/s]
Map:   3%|▎         | 2997/114105 [00:04<02:24, 766.59 examples/s]
Map:   3%|▎         | 2932/114105 [00:04<02:21, 787.21 examples/s]
Map:   2%|▏         | 2828/114105 [00:03<02:20, 789.65 examples/s]
Map:   3%|▎         | 3887/114105 [00:05<02:16, 807.28 examples/s]
Map:   3%|▎         | 2912/114105 [00:04<02:18, 801.15 examples/s]
Map:   3%|▎         | 3975/114105 [00:05<02:13, 823.15 examples/s]
Map:   3%|▎         | 3077/114105 [00:04<03:01, 610.83 examples/s]
Map:   3%|▎         | 2996/114105 [00:04<02:17, 809.49 examples/s]
Map:   3%|▎         | 3037/114105 [00:04<03:00, 614.34 examples/s]
Map:   3%|▎         | 3165/114105 [00:04<02:45, 668.81 examples/s]
Map:   3%|▎         | 3118/114105 [00:04<02:49, 652.95 examples/s]
Map:   4%|▎         | 4085/114105 [00:05<02:43, 674.03 examples/s]
Map:   3%|▎         | 3246/114105 [00:04<02:38, 700.07 examples/s]
Map:   3%|▎         | 3078/114105 [00:04<02:58, 623.20 examples/s]
Map:   3%|▎         | 3204/114105 [00:04<02:39, 696.13 examples/s]
Map:   4%|▎         | 4177/114105 [00:05<02:31, 724.73 examples/s]
Map:   3%|▎         | 3335/114105 [00:04<02:28, 746.19 examples/s]
Map:   3%|▎         | 3173/114105 [00:04<02:38, 698.31 examples/s]
Map:   3%|▎         | 3287/114105 [00:04<02:32, 726.70 examples/s]
Map:   4%|▎         | 4260/114105 [00:05<02:27, 745.68 examples/s]
Map:   3%|▎         | 3417/114105 [00:04<02:24, 764.92 examples/s]
Map:   3%|▎         | 3259/114105 [00:04<02:30, 735.95 examples/s]
Map:   3%|▎         | 3370/114105 [00:04<02:27, 751.61 examples/s]
Map:   4%|▍         | 4345/114105 [00:05<02:22, 770.13 examples/s]
Map:   3%|▎         | 3501/114105 [00:04<02:21, 783.01 examples/s]
Map:   3%|▎         | 3348/114105 [00:04<02:23, 773.27 examples/s]
Map:   3%|▎         | 3454/114105 [00:04<02:22, 774.18 examples/s]
Map:   4%|▍         | 4427/114105 [00:05<02:20, 781.17 examples/s]
Map:   3%|▎         | 3584/114105 [00:05<02:19, 790.40 examples/s]
Map:   3%|▎         | 3434/114105 [00:04<02:19, 792.82 examples/s]
Map:   3%|▎         | 3535/114105 [00:04<02:21, 780.97 examples/s]
Map:   4%|▍         | 4516/114105 [00:06<02:15, 807.40 examples/s]
Map:   3%|▎         | 3667/114105 [00:05<02:18, 795.83 examples/s]
Map:   3%|▎         | 3616/114105 [00:05<02:20, 788.62 examples/s]
Map:   4%|▍         | 4600/114105 [00:06<02:14, 812.92 examples/s]
Map:   3%|▎         | 3557/114105 [00:04<02:18, 797.02 examples/s]
Map:   3%|▎         | 3755/114105 [00:05<02:14, 817.48 examples/s]
Map:   3%|▎         | 3699/114105 [00:05<02:19, 794.26 examples/s]
Map:   4%|▍         | 4686/114105 [00:06<02:12, 824.01 examples/s]
Map:   3%|▎         | 3642/114105 [00:04<02:16, 807.70 examples/s]
Map:   3%|▎         | 3841/114105 [00:05<02:13, 827.53 examples/s]
Map:   3%|▎         | 3783/114105 [00:05<02:17, 803.34 examples/s]
Map:   4%|▍         | 4770/114105 [00:06<02:12, 824.41 examples/s]
Map:   3%|▎         | 3728/114105 [00:05<02:14, 818.62 examples/s]
Map:   3%|▎         | 3960/114105 [00:05<02:16, 808.18 examples/s]
Map:   3%|▎         | 3870/114105 [00:05<02:14, 818.16 examples/s]
Map:   4%|▍         | 4855/114105 [00:06<02:11, 828.76 examples/s]
Map:   3%|▎         | 3815/114105 [00:05<02:13, 828.37 examples/s]
Map:   4%|▍         | 4941/114105 [00:06<02:10, 833.64 examples/s]
Map:   3%|▎         | 3993/114105 [00:05<02:15, 814.73 examples/s]
Map:   3%|▎         | 3923/114105 [00:05<02:21, 781.12 examples/s]
Map:   4%|▎         | 4082/114105 [00:05<02:51, 641.53 examples/s]
Map:   4%|▍         | 5040/114105 [00:06<02:47, 651.84 examples/s]
Map:   4%|▎         | 4081/114105 [00:05<02:50, 645.45 examples/s]
Map:   4%|▎         | 4166/114105 [00:05<02:41, 680.40 examples/s]
Map:   4%|▎         | 4039/114105 [00:05<02:56, 622.19 examples/s]
Map:   4%|▍         | 5127/114105 [00:06<02:35, 700.69 examples/s]
Map:   4%|▎         | 4162/114105 [00:05<02:41, 681.76 examples/s]
Map:   4%|▎         | 4249/114105 [00:06<02:34, 713.04 examples/s]
Map:   4%|▎         | 4122/114105 [00:05<02:45, 663.93 examples/s]
Map:   5%|▍         | 5212/114105 [00:07<02:28, 735.11 examples/s]
Map:   4%|▎         | 4247/114105 [00:05<02:32, 721.07 examples/s]
Map:   4%|▍         | 4334/114105 [00:06<02:27, 743.34 examples/s]
Map:   4%|▎         | 4208/114105 [00:05<02:35, 705.87 examples/s]
Map:   5%|▍         | 5300/114105 [00:07<02:20, 772.72 examples/s]
Map:   4%|▍         | 4329/114105 [00:06<02:27, 744.72 examples/s]
Map:   4%|▍         | 4419/114105 [00:06<02:23, 766.46 examples/s]
Map:   5%|▍         | 5382/114105 [00:07<02:18, 782.56 examples/s]
Map:   4%|▍         | 4412/114105 [00:06<02:23, 766.90 examples/s]
Map:   4%|▍         | 4503/114105 [00:06<02:19, 784.09 examples/s]
Map:   4%|▍         | 4324/114105 [00:05<02:31, 725.95 examples/s]
Map:   5%|▍         | 5468/114105 [00:07<02:15, 802.59 examples/s]
Map:   4%|▍         | 4493/114105 [00:06<02:21, 777.35 examples/s]
Map:   4%|▍         | 4404/114105 [00:06<02:28, 739.82 examples/s]
Map:   4%|▍         | 4622/114105 [00:06<02:19, 785.16 examples/s]
Map:   5%|▍         | 5556/114105 [00:07<02:12, 820.83 examples/s]
Map:   4%|▍         | 4577/114105 [00:06<02:18, 793.07 examples/s]
Map:   4%|▍         | 4482/114105 [00:06<02:26, 746.52 examples/s]
Map:   4%|▍         | 4713/114105 [00:06<02:14, 815.20 examples/s]
Map:   5%|▍         | 5643/114105 [00:07<02:10, 833.75 examples/s]
Map:   4%|▍         | 4663/114105 [00:06<02:15, 808.42 examples/s]
Map:   4%|▍         | 4797/114105 [00:06<02:14, 814.63 examples/s]
Map:   4%|▍         | 4594/114105 [00:06<02:27, 740.83 examples/s]
Map:   5%|▌         | 5729/114105 [00:07<02:09, 837.89 examples/s]
Map:   4%|▍         | 4785/114105 [00:06<02:15, 806.98 examples/s]
Map:   5%|▌         | 5815/114105 [00:07<02:08, 843.79 examples/s]
Map:   4%|▍         | 4920/114105 [00:06<02:14, 811.82 examples/s]
Map:   4%|▍         | 4705/114105 [00:06<02:28, 737.90 examples/s]
Map:   4%|▍         | 4906/114105 [00:06<02:16, 802.07 examples/s]
Map:   5%|▌         | 5940/114105 [00:07<02:09, 836.27 examples/s]
Map:   4%|▍         | 4783/114105 [00:06<02:26, 745.66 examples/s]
Map:   4%|▍         | 4988/114105 [00:06<02:15, 805.19 examples/s]
Map:   4%|▍         | 5032/114105 [00:07<02:50, 640.09 examples/s]
Map:   4%|▍         | 4892/114105 [00:06<02:28, 734.36 examples/s]
Map:   4%|▍         | 5113/114105 [00:07<02:41, 673.59 examples/s]
Map:   4%|▍         | 4970/114105 [00:06<02:26, 743.71 examples/s]
Map:   5%|▌         | 6040/114105 [00:08<02:56, 613.51 examples/s]
Map:   4%|▍         | 5074/114105 [00:07<02:55, 619.93 examples/s]
Map:   5%|▍         | 5194/114105 [00:07<02:35, 700.45 examples/s]
Map:   5%|▌         | 6126/114105 [00:08<02:42, 663.38 examples/s]
Map:   5%|▍         | 5272/114105 [00:07<02:31, 718.80 examples/s]
Map:   5%|▍         | 5167/114105 [00:07<02:55, 618.99 examples/s]
Map:   5%|▌         | 6209/114105 [00:08<02:33, 701.33 examples/s]
Map:   4%|▍         | 5081/114105 [00:07<03:00, 603.77 examples/s]
Map:   5%|▍         | 5359/114105 [00:07<02:23, 755.36 examples/s]
Map:   5%|▍         | 5243/114105 [00:07<02:47, 649.66 examples/s]
Map:   6%|▌         | 6294/114105 [00:08<02:26, 734.43 examples/s]
Map:   5%|▍         | 5161/114105 [00:07<02:49, 642.79 examples/s]
Map:   5%|▍         | 5321/114105 [00:07<02:39, 679.91 examples/s]
Map:   6%|▌         | 6380/114105 [00:08<02:21, 762.73 examples/s]
Map:   5%|▍         | 5479/114105 [00:07<02:21, 767.35 examples/s]
Map:   5%|▍         | 5238/114105 [00:07<02:42, 670.42 examples/s]
Map:   5%|▍         | 5404/114105 [00:07<02:32, 714.61 examples/s]
Map:   5%|▍         | 5561/114105 [00:07<02:19, 777.42 examples/s]
Map:   5%|▍         | 5312/114105 [00:07<02:39, 683.91 examples/s]
Map:   6%|▌         | 6500/114105 [00:08<02:19, 771.77 examples/s]
Map:   5%|▍         | 5484/114105 [00:07<02:27, 735.18 examples/s]
Map:   5%|▍         | 5646/114105 [00:07<02:16, 791.99 examples/s]
Map:   5%|▍         | 5386/114105 [00:07<02:36, 695.34 examples/s]
Map:   6%|▌         | 6581/114105 [00:08<02:18, 776.39 examples/s]
Map:   5%|▍         | 5561/114105 [00:07<02:26, 740.97 examples/s]
Map:   5%|▌         | 5728/114105 [00:07<02:15, 798.72 examples/s]
Map:   5%|▍         | 5468/114105 [00:07<02:30, 724.06 examples/s]
Map:   5%|▍         | 5642/114105 [00:07<02:23, 756.26 examples/s]
Map:   6%|▌         | 6700/114105 [00:08<02:17, 779.84 examples/s]
Map:   5%|▌         | 5809/114105 [00:08<02:15, 800.10 examples/s]
Map:   5%|▍         | 5544/114105 [00:07<02:28, 731.00 examples/s]
Map:   5%|▌         | 5724/114105 [00:07<02:20, 768.69 examples/s]
Map:   6%|▌         | 6785/114105 [00:09<02:15, 794.41 examples/s]
Map:   5%|▌         | 5892/114105 [00:08<02:14, 806.56 examples/s]
Map:   5%|▍         | 5624/114105 [00:07<02:24, 748.48 examples/s]
Map:   5%|▌         | 5808/114105 [00:08<02:17, 787.71 examples/s]
Map:   6%|▌         | 6872/114105 [00:09<02:11, 812.95 examples/s]
Map:   5%|▌         | 5974/114105 [00:08<02:14, 806.20 examples/s]
Map:   5%|▌         | 5740/114105 [00:07<02:23, 755.20 examples/s]
Map:   5%|▌         | 5891/114105 [00:08<02:15, 796.19 examples/s]
Map:   6%|▌         | 6995/114105 [00:09<02:11, 812.43 examples/s]
Map:   5%|▌         | 5825/114105 [00:08<02:19, 777.86 examples/s]
Map:   5%|▌         | 6078/114105 [00:08<02:48, 639.47 examples/s]
Map:   5%|▌         | 5904/114105 [00:08<02:19, 778.16 examples/s]
Map:   5%|▌         | 6000/114105 [00:08<02:54, 619.00 examples/s]
Map:   5%|▌         | 6149/114105 [00:08<02:45, 651.91 examples/s]
Map:   5%|▌         | 5986/114105 [00:08<02:17, 787.46 examples/s]
Map:   6%|▌         | 7112/114105 [00:09<02:46, 643.08 examples/s]
Map:   5%|▌         | 6081/114105 [00:08<02:43, 661.21 examples/s]
Map:   5%|▌         | 6231/114105 [00:08<02:35, 691.63 examples/s]
Map:   6%|▋         | 7194/114105 [00:09<02:37, 676.95 examples/s]
Map:   5%|▌         | 6167/114105 [00:08<02:32, 707.34 examples/s]
Map:   6%|▌         | 6318/114105 [00:08<02:26, 735.05 examples/s]
Map:   6%|▋         | 7273/114105 [00:09<02:32, 700.78 examples/s]
Map:   5%|▌         | 6083/114105 [00:08<02:54, 617.40 examples/s]
Map:   5%|▌         | 6249/114105 [00:08<02:27, 732.33 examples/s]
Map:   6%|▌         | 6399/114105 [00:08<02:23, 752.23 examples/s]
Map:   6%|▋         | 7354/114105 [00:09<02:26, 726.62 examples/s]
Map:   5%|▌         | 6167/114105 [00:08<02:41, 667.71 examples/s]
Map:   6%|▌         | 6332/114105 [00:08<02:22, 756.41 examples/s]
Map:   6%|▌         | 6483/114105 [00:08<02:19, 773.00 examples/s]
Map:   7%|▋         | 7440/114105 [00:09<02:20, 758.94 examples/s]
Map:   5%|▌         | 6249/114105 [00:08<02:33, 703.05 examples/s]
Map:   6%|▌         | 6416/114105 [00:08<02:18, 776.27 examples/s]
Map:   6%|▌         | 6565/114105 [00:09<02:17, 784.10 examples/s]
Map:   7%|▋         | 7520/114105 [00:10<02:18, 768.95 examples/s]
Map:   6%|▌         | 6334/114105 [00:08<02:25, 739.20 examples/s]
Map:   6%|▌         | 6533/114105 [00:09<02:18, 774.86 examples/s]
Map:   7%|▋         | 7603/114105 [00:10<02:15, 783.81 examples/s]
Map:   6%|▌         | 6686/114105 [00:09<02:16, 789.25 examples/s]
Map:   6%|▌         | 6421/114105 [00:08<02:19, 770.49 examples/s]
Map:   6%|▌         | 6768/114105 [00:09<02:15, 792.85 examples/s]
Map:   6%|▌         | 6645/114105 [00:09<02:20, 762.49 examples/s]
Map:   7%|▋         | 7719/114105 [00:10<02:16, 778.69 examples/s]
Map:   6%|▌         | 6520/114105 [00:09<02:27, 727.07 examples/s]
Map:   6%|▌         | 6851/114105 [00:09<02:13, 802.27 examples/s]
Map:   6%|▌         | 6729/114105 [00:09<02:17, 778.48 examples/s]
Map:   7%|▋         | 7835/114105 [00:10<02:17, 772.16 examples/s]
Map:   6%|▌         | 6939/114105 [00:09<02:10, 821.19 examples/s]
Map:   6%|▌         | 6600/114105 [00:09<02:43, 657.66 examples/s]
Map:   6%|▌         | 6810/114105 [00:09<02:16, 785.89 examples/s]
Map:   7%|▋         | 7914/114105 [00:10<02:17, 774.63 examples/s]
Map:   6%|▌         | 6673/114105 [00:09<02:39, 673.65 examples/s]
Map:   6%|▌         | 6893/114105 [00:09<02:14, 796.36 examples/s]
Map:   7%|▋         | 7993/114105 [00:10<02:17, 772.98 examples/s]
Map:   6%|▌         | 6751/114105 [00:09<02:33, 698.96 examples/s]
Map:   6%|▌         | 7035/114105 [00:09<02:46, 644.52 examples/s]
Map:   6%|▌         | 6979/114105 [00:09<02:12, 810.82 examples/s]
Map:   6%|▌         | 6832/114105 [00:09<02:27, 725.32 examples/s]
Map:   6%|▌         | 7119/114105 [00:09<02:35, 688.97 examples/s]
Map:   6%|▌         | 6909/114105 [00:09<02:25, 735.56 examples/s]
Map:   7%|▋         | 8087/114105 [00:10<02:51, 618.64 examples/s]
Map:   6%|▋         | 7204/114105 [00:09<02:27, 725.31 examples/s]
Map:   6%|▌         | 7070/114105 [00:09<02:56, 604.91 examples/s]
Map:   7%|▋         | 8165/114105 [00:10<02:42, 652.85 examples/s]
Map:   6%|▋         | 7319/114105 [00:10<02:25, 735.08 examples/s]
Map:   7%|▋         | 8246/114105 [00:11<02:33, 690.04 examples/s]
Map:   6%|▋         | 7180/114105 [00:09<02:46, 641.75 examples/s]
Map:   6%|▋         | 7403/114105 [00:10<02:20, 760.09 examples/s]
Map:   6%|▌         | 7000/114105 [00:09<03:24, 524.54 examples/s]
Map:   6%|▋         | 7259/114105 [00:10<02:38, 673.92 examples/s]
Map:   7%|▋         | 8334/114105 [00:11<02:24, 734.46 examples/s]
Map:   6%|▌         | 7076/114105 [00:09<03:06, 573.67 examples/s]
Map:   6%|▋         | 7342/114105 [00:10<02:30, 709.31 examples/s]
Map:   7%|▋         | 8421/114105 [00:11<02:17, 766.24 examples/s]
Map:   7%|▋         | 7518/114105 [00:10<02:20, 756.46 examples/s]
Map:   6%|▋         | 7159/114105 [00:10<02:49, 631.11 examples/s]
Map:   7%|▋         | 7432/114105 [00:10<02:21, 755.64 examples/s]
Map:   7%|▋         | 8506/114105 [00:11<02:13, 788.30 examples/s]
Map:   7%|▋         | 7596/114105 [00:10<02:19, 761.53 examples/s]
Map:   6%|▋         | 7231/114105 [00:10<02:44, 649.63 examples/s]
Map:   7%|▋         | 7515/114105 [00:10<02:17, 774.32 examples/s]
Map:   8%|▊         | 8590/114105 [00:11<02:11, 799.44 examples/s]
Map:   7%|▋         | 7683/114105 [00:10<02:15, 787.86 examples/s]
Map:   6%|▋         | 7310/114105 [00:10<02:36, 681.74 examples/s]
Map:   7%|▋         | 7599/114105 [00:10<02:14, 790.99 examples/s]
Map:   8%|▊         | 8676/114105 [00:11<02:09, 814.37 examples/s]
Map:   7%|▋         | 7806/114105 [00:10<02:13, 798.80 examples/s]
Map:   6%|▋         | 7384/114105 [00:10<02:33, 693.15 examples/s]
Map:   7%|▋         | 7686/114105 [00:10<02:11, 809.76 examples/s]
Map:   8%|▊         | 8760/114105 [00:11<02:08, 816.67 examples/s]
Map:   7%|▋         | 7891/114105 [00:10<02:11, 809.55 examples/s]
Map:   7%|▋         | 7459/114105 [00:10<02:31, 706.26 examples/s]
Map:   7%|▋         | 7771/114105 [00:10<02:10, 816.98 examples/s]
Map:   8%|▊         | 8848/114105 [00:11<02:06, 832.04 examples/s]
Map:   7%|▋         | 7975/114105 [00:10<02:10, 814.82 examples/s]
Map:   7%|▋         | 7537/114105 [00:10<02:27, 724.61 examples/s]
Map:   7%|▋         | 7858/114105 [00:10<02:08, 827.77 examples/s]
Map:   8%|▊         | 8966/114105 [00:11<02:11, 798.37 examples/s]
Map:   7%|▋         | 7613/114105 [00:10<02:26, 729.36 examples/s]
Map:   7%|▋         | 7981/114105 [00:10<02:08, 822.91 examples/s]
Map:   7%|▋         | 7692/114105 [00:10<02:22, 744.29 examples/s]
Map:   7%|▋         | 8079/114105 [00:11<02:45, 639.62 examples/s]
Map:   7%|▋         | 8162/114105 [00:11<02:35, 679.60 examples/s]
Map:   8%|▊         | 9088/114105 [00:12<02:38, 661.19 examples/s]
Map:   7%|▋         | 7799/114105 [00:10<02:25, 728.44 examples/s]
Map:   7%|▋         | 8079/114105 [00:11<02:43, 649.71 examples/s]
Map:   7%|▋         | 8245/114105 [00:11<02:28, 714.55 examples/s]
Map:   8%|▊         | 9175/114105 [00:12<02:29, 703.53 examples/s]
Map:   7%|▋         | 7873/114105 [00:11<02:25, 730.11 examples/s]
Map:   7%|▋         | 8160/114105 [00:11<02:35, 682.76 examples/s]
Map:   7%|▋         | 8326/114105 [00:11<02:23, 736.99 examples/s]
Map:   8%|▊         | 9263/114105 [00:12<02:21, 743.37 examples/s]
Map:   7%|▋         | 7953/114105 [00:11<02:22, 745.82 examples/s]
Map:   7%|▋         | 8272/114105 [00:11<02:31, 699.26 examples/s]
Map:   7%|▋         | 8440/114105 [00:11<02:22, 740.39 examples/s]
Map:   8%|▊         | 9376/114105 [00:12<02:20, 744.74 examples/s]
Map:   7%|▋         | 8355/114105 [00:11<02:25, 727.22 examples/s]
Map:   7%|▋         | 8520/114105 [00:11<02:20, 752.33 examples/s]
Map:   7%|▋         | 8037/114105 [00:11<03:05, 570.96 examples/s]
Map:   8%|▊         | 9464/114105 [00:12<02:15, 774.55 examples/s]
Map:   7%|▋         | 8438/114105 [00:11<02:20, 749.92 examples/s]
Map:   8%|▊         | 8603/114105 [00:11<02:17, 769.82 examples/s]
Map:   7%|▋         | 8110/114105 [00:11<02:55, 604.96 examples/s]
Map:   8%|▊         | 9549/114105 [00:12<02:11, 793.49 examples/s]
Map:   7%|▋         | 8522/114105 [00:11<02:17, 770.62 examples/s]
Map:   8%|▊         | 8689/114105 [00:11<02:13, 791.91 examples/s]
Map:   7%|▋         | 8191/114105 [00:11<02:42, 653.22 examples/s]
Map:   8%|▊         | 9636/114105 [00:12<02:09, 809.73 examples/s]
Map:   8%|▊         | 8603/114105 [00:11<02:15, 779.45 examples/s]
Map:   7%|▋         | 8268/114105 [00:11<02:35, 680.46 examples/s]
Map:   8%|▊         | 8806/114105 [00:12<02:14, 782.89 examples/s]
Map:   9%|▊         | 9757/114105 [00:13<02:10, 802.25 examples/s]
Map:   8%|▊         | 8686/114105 [00:11<02:13, 791.58 examples/s]
Map:   7%|▋         | 8348/114105 [00:11<02:29, 708.04 examples/s]
Map:   9%|▊         | 9841/114105 [00:13<02:08, 808.73 examples/s]
Map:   8%|▊         | 8926/114105 [00:12<02:15, 779.09 examples/s]
Map:   7%|▋         | 8425/114105 [00:11<02:26, 720.95 examples/s]
Map:   8%|▊         | 8804/114105 [00:12<02:13, 786.65 examples/s]
Map:   7%|▋         | 8504/114105 [00:11<02:22, 739.36 examples/s]
Map:   9%|▊         | 9966/114105 [00:13<02:07, 815.85 examples/s]
Map:   8%|▊         | 8886/114105 [00:12<02:12, 792.28 examples/s]
Map:   8%|▊         | 8580/114105 [00:12<02:22, 741.71 examples/s]
Map:   8%|▊         | 9036/114105 [00:12<02:44, 637.02 examples/s]
Map:   8%|▊         | 8657/114105 [00:12<02:20, 748.33 examples/s]
Map:   8%|▊         | 9116/114105 [00:12<02:36, 668.84 examples/s]
Map:   9%|▉         | 10084/114105 [00:13<02:35, 667.37 examples/s]
Map:   8%|▊         | 9000/114105 [00:12<02:46, 631.02 examples/s]
Map:   8%|▊         | 8737/114105 [00:12<02:18, 761.80 examples/s]
Map:   8%|▊         | 9195/114105 [00:12<02:31, 694.73 examples/s]
Map:   9%|▉         | 10173/114105 [00:13<02:25, 712.18 examples/s]
Map:   8%|▊         | 9082/114105 [00:12<02:36, 671.30 examples/s]
Map:   8%|▊         | 8814/114105 [00:12<02:18, 761.46 examples/s]
Map:   8%|▊         | 9280/114105 [00:12<02:23, 730.71 examples/s]
Map:   9%|▉         | 10264/114105 [00:13<02:17, 756.13 examples/s]
Map:   8%|▊         | 9164/114105 [00:12<02:29, 703.27 examples/s]
Map:   8%|▊         | 9364/114105 [00:12<02:18, 755.68 examples/s]
Map:   9%|▉         | 10345/114105 [00:13<02:15, 767.99 examples/s]
Map:   8%|▊         | 8929/114105 [00:12<02:18, 759.77 examples/s]
Map:   8%|▊         | 9240/114105 [00:12<02:26, 715.51 examples/s]
Map:   8%|▊         | 9477/114105 [00:13<02:19, 750.57 examples/s]
Map:   9%|▉         | 10458/114105 [00:13<02:17, 755.83 examples/s]
Map:   8%|▊         | 9349/114105 [00:12<02:26, 713.20 examples/s]
Map:   8%|▊         | 9555/114105 [00:13<02:18, 756.51 examples/s]
Map:   9%|▉         | 10538/114105 [00:14<02:15, 763.13 examples/s]
Map:   8%|▊         | 9043/114105 [00:12<02:55, 599.95 examples/s]
Map:   8%|▊         | 9435/114105 [00:12<02:19, 747.81 examples/s]
Map:   8%|▊         | 9638/114105 [00:13<02:14, 774.84 examples/s]
Map:   9%|▉         | 10623/114105 [00:14<02:11, 784.32 examples/s]
Map:   8%|▊         | 9121/114105 [00:12<02:45, 635.76 examples/s]
Map:   8%|▊         | 9516/114105 [00:13<02:17, 759.49 examples/s]
Map:   9%|▊         | 9719/114105 [00:13<02:13, 779.99 examples/s]
Map:   9%|▉         | 10709/114105 [00:14<02:09, 800.69 examples/s]
Map:   8%|▊         | 9198/114105 [00:12<02:37, 664.97 examples/s]
Map:   8%|▊         | 9598/114105 [00:13<02:15, 771.60 examples/s]
Map:   9%|▊         | 9804/114105 [00:13<02:11, 795.61 examples/s]
Map:   9%|▉         | 10793/114105 [00:14<02:07, 808.31 examples/s]
Map:   8%|▊         | 9277/114105 [00:13<02:30, 695.08 examples/s]
Map:   8%|▊         | 9681/114105 [00:13<02:13, 782.38 examples/s]
Map:   9%|▊         | 9888/114105 [00:13<02:09, 807.30 examples/s]
Map:  10%|▉         | 10879/114105 [00:14<02:05, 821.47 examples/s]
Map:   8%|▊         | 9353/114105 [00:13<02:27, 708.86 examples/s]
Map:   9%|▊         | 9766/114105 [00:13<02:10, 799.19 examples/s]
Map:   8%|▊         | 9429/114105 [00:13<02:25, 717.58 examples/s]
Map:   9%|▊         | 9848/114105 [00:13<02:09, 803.59 examples/s]
Map:   8%|▊         | 9512/114105 [00:13<02:20, 745.44 examples/s]
Map:   9%|▉         | 10000/114105 [00:13<02:42, 640.53 examples/s]
Map:  10%|▉         | 11000/114105 [00:14<02:38, 650.72 examples/s]
Map:   9%|▊         | 9967/114105 [00:13<02:10, 796.36 examples/s]
Map:   9%|▉         | 10084/114105 [00:13<02:32, 682.76 examples/s]
Map:  10%|▉         | 11083/114105 [00:14<02:29, 687.96 examples/s]
Map:   8%|▊         | 9623/114105 [00:13<02:21, 739.43 examples/s]
Map:   9%|▉         | 10169/114105 [00:13<02:23, 722.34 examples/s]
Map:  10%|▉         | 11169/114105 [00:14<02:21, 727.50 examples/s]
Map:   9%|▊         | 9702/114105 [00:13<02:19, 748.29 examples/s]
Map:   9%|▉         | 10249/114105 [00:14<02:20, 741.56 examples/s]
Map:   9%|▉         | 10083/114105 [00:13<02:42, 641.41 examples/s]
Map:  10%|▉         | 11256/114105 [00:15<02:14, 761.96 examples/s]
Map:   9%|▊         | 9782/114105 [00:13<02:17, 758.94 examples/s]
Map:   9%|▉         | 10334/114105 [00:14<02:15, 767.80 examples/s]
Map:   9%|▉         | 10165/114105 [00:14<02:33, 678.31 examples/s]
Map:  10%|▉         | 11342/114105 [00:15<02:10, 786.48 examples/s]
Map:   9%|▊         | 9864/114105 [00:13<02:14, 773.41 examples/s]
Map:   9%|▉         | 10245/114105 [00:14<02:27, 704.70 examples/s]
Map:   9%|▉         | 10418/114105 [00:14<02:12, 781.40 examples/s]
Map:  10%|█         | 11429/114105 [00:15<02:07, 807.78 examples/s]
Map:   9%|▊         | 9972/114105 [00:14<02:19, 748.62 examples/s]
Map:   9%|▉         | 10327/114105 [00:14<02:21, 730.84 examples/s]
Map:   9%|▉         | 10499/114105 [00:14<02:11, 787.22 examples/s]
Map:  10%|█         | 11550/114105 [00:15<02:07, 803.50 examples/s]
Map:   9%|▉         | 10580/114105 [00:14<02:10, 791.71 examples/s]
Map:   9%|▉         | 10406/114105 [00:14<02:19, 741.63 examples/s]
Map:  10%|█         | 11635/114105 [00:15<02:06, 812.82 examples/s]
Map:   9%|▉         | 10663/114105 [00:14<02:09, 801.79 examples/s]
Map:   9%|▉         | 10489/114105 [00:14<02:15, 762.01 examples/s]
Map:   9%|▉         | 10075/114105 [00:14<02:59, 581.01 examples/s]
Map:  10%|█         | 11722/114105 [00:15<02:04, 825.62 examples/s]
Map:   9%|▉         | 10744/114105 [00:14<02:09, 800.96 examples/s]
Map:   9%|▉         | 10572/114105 [00:14<02:13, 777.03 examples/s]
Map:   9%|▉         | 10152/114105 [00:14<02:48, 617.97 examples/s]
Map:  10%|█         | 11809/114105 [00:15<02:02, 834.45 examples/s]
Map:   9%|▉         | 10827/114105 [00:14<02:08, 806.23 examples/s]
Map:   9%|▉         | 10655/114105 [00:14<02:11, 788.08 examples/s]
Map:   9%|▉         | 10225/114105 [00:14<02:41, 642.13 examples/s]
Map:  10%|▉         | 10915/114105 [00:14<02:05, 824.80 examples/s]
Map:   9%|▉         | 10741/114105 [00:14<02:08, 806.70 examples/s]
Map:  10%|█         | 11934/114105 [00:15<02:02, 831.49 examples/s]
Map:   9%|▉         | 10306/114105 [00:14<02:32, 679.69 examples/s]
Map:   9%|▉         | 10828/114105 [00:14<02:05, 821.32 examples/s]
Map:   9%|▉         | 10383/114105 [00:14<02:28, 698.00 examples/s]
Map:  10%|▉         | 11000/114105 [00:15<02:42, 636.32 examples/s]
Map:  10%|▉         | 10915/114105 [00:14<02:03, 833.65 examples/s]
Map:  11%|█         | 12043/114105 [00:16<02:31, 672.82 examples/s]
Map:   9%|▉         | 10464/114105 [00:14<02:23, 722.64 examples/s]
Map:  10%|▉         | 11083/114105 [00:15<02:31, 680.57 examples/s]
Map:  11%|█         | 12131/114105 [00:16<02:22, 716.56 examples/s]
Map:   9%|▉         | 10541/114105 [00:14<02:20, 735.38 examples/s]
Map:  10%|▉         | 11165/114105 [00:15<02:23, 714.92 examples/s]
Map:  10%|▉         | 11000/114105 [00:15<02:43, 629.12 examples/s]
Map:  11%|█         | 12217/114105 [00:16<02:16, 748.42 examples/s]
Map:   9%|▉         | 10617/114105 [00:14<02:19, 740.51 examples/s]
Map:  10%|▉         | 11250/114105 [00:15<02:17, 748.12 examples/s]
Map:  10%|▉         | 11081/114105 [00:15<02:33, 670.70 examples/s]
Map:  11%|█         | 12300/114105 [00:16<02:12, 767.47 examples/s]
Map:   9%|▉         | 10693/114105 [00:15<02:19, 743.47 examples/s]
Map:  10%|▉         | 11336/114105 [00:15<02:12, 776.97 examples/s]
Map:  10%|▉         | 11169/114105 [00:15<02:22, 721.09 examples/s]
Map:  11%|█         | 12386/114105 [00:16<02:08, 789.48 examples/s]
Map:   9%|▉         | 10774/114105 [00:15<02:16, 759.69 examples/s]
Map:  10%|▉         | 11248/114105 [00:15<02:19, 737.99 examples/s]
Map:  11%|█         | 12469/114105 [00:16<02:07, 798.48 examples/s]
Map:  10%|▉         | 10854/114105 [00:15<02:14, 769.76 examples/s]
Map:  10%|█         | 11458/114105 [00:15<02:10, 785.14 examples/s]
Map:  10%|▉         | 11327/114105 [00:15<02:17, 749.13 examples/s]
Map:  11%|█         | 12551/114105 [00:16<02:06, 800.04 examples/s]
Map:  10%|█         | 11541/114105 [00:15<02:09, 793.78 examples/s]
Map:  10%|▉         | 10964/114105 [00:15<02:17, 751.10 examples/s]
Map:  10%|█         | 11437/114105 [00:15<02:19, 738.09 examples/s]
Map:  11%|█         | 12673/114105 [00:16<02:06, 799.29 examples/s]
Map:  10%|█         | 11661/114105 [00:15<02:09, 791.51 examples/s]
Map:  10%|█         | 11526/114105 [00:15<02:12, 773.66 examples/s]
Map:  11%|█         | 12758/114105 [00:16<02:05, 810.63 examples/s]
Map:  10%|█         | 11744/114105 [00:16<02:08, 799.13 examples/s]
Map:  10%|▉         | 11076/114105 [00:15<02:54, 590.39 examples/s]
Map:  10%|█         | 11606/114105 [00:15<02:11, 777.26 examples/s]
Map:  11%|█▏        | 12845/114105 [00:17<02:02, 823.80 examples/s]
Map:  10%|█         | 11830/114105 [00:16<02:06, 810.76 examples/s]
Map:  10%|▉         | 11155/114105 [00:15<02:43, 630.96 examples/s]
Map:  10%|█         | 11686/114105 [00:15<02:11, 779.75 examples/s]
Map:  11%|█▏        | 12933/114105 [00:17<02:00, 838.26 examples/s]
Map:  10%|█         | 11917/114105 [00:16<02:04, 822.12 examples/s]
Map:  10%|▉         | 11231/114105 [00:15<02:36, 659.09 examples/s]
Map:  10%|█         | 11769/114105 [00:16<02:09, 792.36 examples/s]
Map:  10%|█         | 11856/114105 [00:16<02:05, 812.03 examples/s]
Map:  11%|█         | 12000/114105 [00:16<02:39, 639.91 examples/s]
Map:  10%|▉         | 11328/114105 [00:16<02:38, 650.45 examples/s]
Map:  11%|█▏        | 13039/114105 [00:17<02:32, 662.17 examples/s]
Map:  10%|█         | 11938/114105 [00:16<02:06, 810.63 examples/s]
Map:  11%|█         | 12085/114105 [00:16<02:28, 688.76 examples/s]
Map:  12%|█▏        | 13125/114105 [00:17<02:22, 706.83 examples/s]
Map:  10%|▉         | 11409/114105 [00:16<02:47, 613.58 examples/s]
Map:  11%|█         | 12167/114105 [00:16<02:21, 719.62 examples/s]
Map:  12%|█▏        | 13208/114105 [00:17<02:17, 735.03 examples/s]
Map:  11%|█         | 12043/114105 [00:16<02:40, 637.56 examples/s]
Map:  11%|█         | 12247/114105 [00:16<02:18, 737.27 examples/s]
Map:  10%|█         | 11494/114105 [00:16<02:52, 595.21 examples/s]
Map:  12%|█▏        | 13296/114105 [00:17<02:10, 771.05 examples/s]
Map:  11%|█         | 12123/114105 [00:16<02:31, 671.11 examples/s]
Map:  11%|█         | 12332/114105 [00:16<02:13, 764.68 examples/s]
Map:  10%|█         | 11566/114105 [00:16<02:45, 619.65 examples/s]
Map:  12%|█▏        | 13380/114105 [00:17<02:08, 785.83 examples/s]
Map:  11%|█         | 12210/114105 [00:16<02:21, 718.57 examples/s]
Map:  11%|█         | 12416/114105 [00:16<02:10, 781.35 examples/s]
Map:  10%|█         | 11642/114105 [00:16<02:37, 651.90 examples/s]
Map:  12%|█▏        | 13463/114105 [00:17<02:06, 796.53 examples/s]
Map:  11%|█         | 12293/114105 [00:16<02:16, 745.24 examples/s]
Map:  11%|█         | 12498/114105 [00:17<02:08, 790.88 examples/s]
Map:  10%|█         | 11715/114105 [00:16<02:33, 668.89 examples/s]
Map:  12%|█▏        | 13550/114105 [00:17<02:03, 815.81 examples/s]
Map:  11%|█         | 12379/114105 [00:16<02:11, 773.45 examples/s]
Map:  11%|█         | 12582/114105 [00:17<02:06, 801.96 examples/s]
Map:  10%|█         | 11819/114105 [00:16<02:32, 670.95 examples/s]
Map:  12%|█▏        | 13669/114105 [00:18<02:04, 803.71 examples/s]
Map:  11%|█         | 12487/114105 [00:17<02:15, 748.94 examples/s]
Map:  11%|█         | 12695/114105 [00:17<02:10, 779.30 examples/s]
Map:  10%|█         | 11891/114105 [00:16<02:30, 681.16 examples/s]
Map:  12%|█▏        | 13787/114105 [00:18<02:06, 794.23 examples/s]
Map:  11%|█         | 12570/114105 [00:17<02:12, 767.30 examples/s]
Map:  11%|█         | 12775/114105 [00:17<02:09, 782.81 examples/s]
Map:  10%|█         | 11965/114105 [00:17<02:27, 693.94 examples/s]
Map:  12%|█▏        | 13874/114105 [00:18<02:03, 810.29 examples/s]
Map:  11%|█         | 12653/114105 [00:17<02:09, 781.83 examples/s]
Map:  11%|█▏        | 12862/114105 [00:17<02:06, 803.22 examples/s]
Map:  12%|█▏        | 13958/114105 [00:18<02:02, 814.91 examples/s]
Map:  11%|█         | 12735/114105 [00:17<02:08, 787.98 examples/s]
Map:  11%|█▏        | 12946/114105 [00:17<02:04, 811.22 examples/s]
Map:  11%|█         | 12038/114105 [00:17<03:12, 531.34 examples/s]
Map:  11%|█         | 12816/114105 [00:17<02:08, 788.28 examples/s]
Map:  11%|█         | 12117/114105 [00:17<02:52, 589.53 examples/s]
Map:  12%|█▏        | 14042/114105 [00:18<02:36, 641.33 examples/s]
Map:  11%|█▏        | 12896/114105 [00:17<02:08, 787.81 examples/s]
Map:  11%|█▏        | 13037/114105 [00:17<02:40, 629.77 examples/s]
Map:  11%|█         | 12197/114105 [00:17<02:39, 639.09 examples/s]
Map:  12%|█▏        | 14130/114105 [00:18<02:23, 694.38 examples/s]
Map:  11%|█▏        | 12976/114105 [00:17<02:08, 787.82 examples/s]
Map:  11%|█▏        | 13118/114105 [00:17<02:30, 669.50 examples/s]
Map:  11%|█         | 12277/114105 [00:17<02:30, 678.72 examples/s]
Map:  12%|█▏        | 14212/114105 [00:18<02:18, 723.37 examples/s]
Map:  12%|█▏        | 13201/114105 [00:17<02:22, 707.11 examples/s]
Map:  11%|█         | 12362/114105 [00:17<02:21, 721.53 examples/s]
Map:  13%|█▎        | 14294/114105 [00:18<02:13, 747.32 examples/s]
Map:  12%|█▏        | 13286/114105 [00:18<02:16, 739.91 examples/s]
Map:  11%|█▏        | 13077/114105 [00:17<02:45, 611.05 examples/s]
Map:  11%|█         | 12442/114105 [00:17<02:17, 740.44 examples/s]
Map:  13%|█▎        | 14377/114105 [00:19<02:09, 767.23 examples/s]
Map:  12%|█▏        | 13368/114105 [00:18<02:12, 758.51 examples/s]
Map:  12%|█▏        | 13160/114105 [00:18<02:32, 659.94 examples/s]
Map:  11%|█         | 12522/114105 [00:17<02:14, 756.22 examples/s]
Map:  13%|█▎        | 14459/114105 [00:19<02:07, 778.84 examples/s]
Map:  12%|█▏        | 13455/114105 [00:18<02:08, 786.01 examples/s]
Map:  12%|█▏        | 13241/114105 [00:18<02:25, 694.83 examples/s]
Map:  13%|█▎        | 14548/114105 [00:19<02:03, 807.19 examples/s]
Map:  11%|█         | 12640/114105 [00:17<02:12, 763.38 examples/s]
Map:  12%|█▏        | 13537/114105 [00:18<02:06, 793.78 examples/s]
Map:  12%|█▏        | 13324/114105 [00:18<02:18, 727.76 examples/s]
Map:  13%|█▎        | 14668/114105 [00:19<02:03, 802.88 examples/s]
Map:  12%|█▏        | 13623/114105 [00:18<02:04, 806.35 examples/s]
Map:  12%|█▏        | 13410/114105 [00:18<02:12, 759.02 examples/s]
Map:  11%|█         | 12754/114105 [00:18<02:13, 757.21 examples/s]
Map:  13%|█▎        | 14780/114105 [00:19<02:08, 775.48 examples/s]
Map:  12%|█▏        | 13730/114105 [00:18<02:10, 766.32 examples/s]
Map:  12%|█▏        | 13518/114105 [00:18<02:15, 742.79 examples/s]
Map:  11%|█▏        | 12863/114105 [00:18<02:16, 743.61 examples/s]
Map:  13%|█▎        | 14893/114105 [00:19<02:09, 765.65 examples/s]
Map:  12%|█▏        | 13840/114105 [00:18<02:13, 749.88 examples/s]
Map:  12%|█▏        | 13624/114105 [00:18<02:17, 728.54 examples/s]
Map:  11%|█▏        | 12971/114105 [00:18<02:18, 731.10 examples/s]
Map:  13%|█▎        | 14977/114105 [00:19<02:07, 780.30 examples/s]
Map:  12%|█▏        | 13925/114105 [00:18<02:10, 769.85 examples/s]
Map:  12%|█▏        | 13705/114105 [00:18<02:14, 746.36 examples/s]
Map:  12%|█▏        | 13783/114105 [00:18<02:13, 752.06 examples/s]
Map:  11%|█▏        | 13081/114105 [00:18<02:43, 616.45 examples/s]
Map:  12%|█▏        | 13867/114105 [00:18<02:09, 772.74 examples/s]
Map:  13%|█▎        | 15082/114105 [00:20<02:35, 635.15 examples/s]
Map:  12%|█▏        | 14040/114105 [00:19<02:37, 636.41 examples/s]
Map:  12%|█▏        | 13155/114105 [00:18<02:38, 638.79 examples/s]
Map:  12%|█▏        | 13948/114105 [00:19<02:08, 779.11 examples/s]
Map:  13%|█▎        | 15170/114105 [00:20<02:24, 686.55 examples/s]
Map:  12%|█▏        | 14126/114105 [00:19<02:26, 682.26 examples/s]
Map:  12%|█▏        | 13235/114105 [00:18<02:47, 602.01 examples/s]
Map:  13%|█▎        | 15253/114105 [00:20<02:17, 716.34 examples/s]
Map:  12%|█▏        | 14210/114105 [00:19<02:19, 716.87 examples/s]
Map:  12%|█▏        | 13306/114105 [00:19<02:41, 625.60 examples/s]
Map:  13%|█▎        | 15339/114105 [00:20<02:11, 751.00 examples/s]
Map:  12%|█▏        | 14037/114105 [00:19<02:46, 599.42 examples/s]
Map:  13%|█▎        | 14289/114105 [00:19<02:15, 734.46 examples/s]
Map:  12%|█▏        | 13382/114105 [00:19<02:33, 655.79 examples/s]
Map:  14%|█▎        | 15422/114105 [00:20<02:08, 770.38 examples/s]
Map:  12%|█▏        | 14118/114105 [00:19<02:34, 646.69 examples/s]
Map:  13%|█▎        | 14367/114105 [00:19<02:13, 745.14 examples/s]
Map:  12%|█▏        | 13459/114105 [00:19<02:27, 683.05 examples/s]
Map:  14%|█▎        | 15506/114105 [00:20<02:05, 786.15 examples/s]
Map:  12%|█▏        | 14200/114105 [00:19<02:25, 686.02 examples/s]
Map:  13%|█▎        | 14447/114105 [00:19<02:11, 756.10 examples/s]
Map:  12%|█▏        | 13534/114105 [00:19<02:24, 698.22 examples/s]
Map:  14%|█▎        | 15591/114105 [00:20<02:03, 800.59 examples/s]
Map:  13%|█▎        | 14278/114105 [00:19<02:20, 709.45 examples/s]
Map:  13%|█▎        | 14531/114105 [00:19<02:08, 777.21 examples/s]
Map:  12%|█▏        | 13610/114105 [00:19<02:20, 715.07 examples/s]
Map:  14%|█▎        | 15678/114105 [00:20<02:00, 819.72 examples/s]
Map:  13%|█▎        | 14365/114105 [00:19<02:13, 748.67 examples/s]
Map:  13%|█▎        | 14618/114105 [00:19<02:04, 798.96 examples/s]
Map:  12%|█▏        | 13688/114105 [00:19<02:17, 731.63 examples/s]
Map:  13%|█▎        | 14448/114105 [00:19<02:09, 767.31 examples/s]
Map:  13%|█▎        | 14702/114105 [00:19<02:03, 807.57 examples/s]
Map:  14%|█▍        | 15803/114105 [00:20<01:59, 820.32 examples/s]
Map:  13%|█▎        | 14529/114105 [00:19<02:08, 775.67 examples/s]
Map:  12%|█▏        | 13778/114105 [00:19<02:27, 678.52 examples/s]
Map:  13%|█▎        | 14812/114105 [00:20<02:08, 774.34 examples/s]
Map:  14%|█▍        | 15912/114105 [00:21<02:05, 783.62 examples/s]
Map:  13%|█▎        | 14645/114105 [00:20<02:09, 768.88 examples/s]
Map:  13%|█▎        | 14894/114105 [00:20<02:06, 784.41 examples/s]
Map:  12%|█▏        | 13889/114105 [00:19<02:24, 695.44 examples/s]
Map:  14%|█▍        | 15998/114105 [00:21<02:02, 798.04 examples/s]
Map:  13%|█▎        | 14978/114105 [00:20<02:04, 797.42 examples/s]
Map:  12%|█▏        | 13966/114105 [00:19<02:20, 710.50 examples/s]
Map:  13%|█▎        | 14758/114105 [00:20<02:11, 757.58 examples/s]
Map:  13%|█▎        | 14838/114105 [00:20<02:09, 766.75 examples/s]
Map:  14%|█▍        | 16083/114105 [00:21<02:35, 631.57 examples/s]
Map:  13%|█▎        | 15082/114105 [00:20<02:34, 640.41 examples/s]
Map:  13%|█▎        | 14919/114105 [00:20<02:07, 775.70 examples/s]
Map:  14%|█▍        | 16167/114105 [00:21<02:24, 676.37 examples/s]
Map:  12%|█▏        | 14079/114105 [00:20<02:52, 581.12 examples/s]
Map:  13%|█▎        | 15160/114105 [00:20<02:27, 669.33 examples/s]
Map:  14%|█▍        | 16250/114105 [00:21<02:17, 713.32 examples/s]
Map:  12%|█▏        | 14157/114105 [00:20<02:40, 621.53 examples/s]
Map:  13%|█▎        | 15242/114105 [00:20<02:20, 705.72 examples/s]
Map:  14%|█▍        | 16333/114105 [00:21<02:11, 743.18 examples/s]
Map:  13%|█▎        | 15000/114105 [00:20<02:43, 604.98 examples/s]
Map:  12%|█▏        | 14232/114105 [00:20<02:33, 648.96 examples/s]
Map:  13%|█▎        | 15325/114105 [00:20<02:14, 736.60 examples/s]
Map:  14%|█▍        | 16420/114105 [00:21<02:05, 776.04 examples/s]
Map:  13%|█▎        | 15079/114105 [00:20<02:32, 647.32 examples/s]
Map:  13%|█▎        | 14309/114105 [00:20<02:27, 676.12 examples/s]
Map:  14%|█▎        | 15406/114105 [00:20<02:10, 754.77 examples/s]
Map:  13%|█▎        | 15161/114105 [00:20<02:23, 688.05 examples/s]
Map:  13%|█▎        | 14388/114105 [00:20<02:21, 703.64 examples/s]
Map:  14%|█▍        | 16541/114105 [00:21<02:04, 784.09 examples/s]
Map:  14%|█▎        | 15492/114105 [00:21<02:05, 782.67 examples/s]
Map:  13%|█▎        | 15240/114105 [00:20<02:19, 710.18 examples/s]
Map:  13%|█▎        | 14463/114105 [00:20<02:19, 713.56 examples/s]
Map:  15%|█▍        | 16624/114105 [00:22<02:02, 793.73 examples/s]
Map:  13%|█▎        | 15325/114105 [00:21<02:12, 743.88 examples/s]
Map:  13%|█▎        | 14539/114105 [00:20<02:17, 723.84 examples/s]
Map:  14%|█▎        | 15614/114105 [00:21<02:04, 791.64 examples/s]
Map:  15%|█▍        | 16709/114105 [00:22<02:00, 806.44 examples/s]
Map:  13%|█▎        | 15404/114105 [00:21<02:10, 756.01 examples/s]
Map:  13%|█▎        | 14616/114105 [00:20<02:16, 731.35 examples/s]
Map:  14%|█▍        | 15698/114105 [00:21<02:02, 801.47 examples/s]
Map:  15%|█▍        | 16797/114105 [00:22<01:57, 825.11 examples/s]
Map:  14%|█▎        | 15482/114105 [00:21<02:10, 758.07 examples/s]
Map:  13%|█▎        | 14727/114105 [00:21<02:15, 732.47 examples/s]
Map:  14%|█▍        | 15808/114105 [00:21<02:07, 773.76 examples/s]
Map:  15%|█▍        | 16916/114105 [00:22<02:00, 807.61 examples/s]
Map:  14%|█▎        | 15594/114105 [00:21<02:10, 752.02 examples/s]
Map:  13%|█▎        | 14805/114105 [00:21<02:14, 741.01 examples/s]
Map:  14%|█▍        | 15890/114105 [00:21<02:05, 783.06 examples/s]
Map:  15%|█▍        | 16999/114105 [00:22<01:59, 810.22 examples/s]
Map:  14%|█▎        | 15673/114105 [00:21<02:09, 758.41 examples/s]
Map:  13%|█▎        | 14883/114105 [00:21<02:13, 743.10 examples/s]
Map:  14%|█▍        | 15974/114105 [00:21<02:03, 792.70 examples/s]
Map:  14%|█▍        | 15757/114105 [00:21<02:06, 776.92 examples/s]
Map:  13%|█▎        | 14962/114105 [00:21<02:11, 752.64 examples/s]
Map:  15%|█▌        | 17118/114105 [00:22<02:31, 642.05 examples/s]
Map:  14%|█▍        | 15840/114105 [00:21<02:04, 789.17 examples/s]
Map:  14%|█▍        | 16082/114105 [00:21<02:32, 641.56 examples/s]
Map:  15%|█▌        | 17205/114105 [00:22<02:20, 689.28 examples/s]
Map:  14%|█▍        | 15923/114105 [00:21<02:02, 799.26 examples/s]
Map:  13%|█▎        | 15041/114105 [00:21<02:49, 583.70 examples/s]
Map:  14%|█▍        | 16166/114105 [00:21<02:23, 684.53 examples/s]
Map:  15%|█▌        | 17290/114105 [00:22<02:13, 724.06 examples/s]
Map:  13%|█▎        | 15122/114105 [00:21<02:35, 635.02 examples/s]
Map:  14%|█▍        | 16247/114105 [00:22<02:17, 711.06 examples/s]
Map:  15%|█▌        | 17374/114105 [00:23<02:09, 749.80 examples/s]
Map:  13%|█▎        | 15201/114105 [00:21<02:26, 672.94 examples/s]
Map:  14%|█▍        | 16037/114105 [00:22<02:35, 630.85 examples/s]
Map:  14%|█▍        | 16330/114105 [00:22<02:12, 739.05 examples/s]
Map:  15%|█▌        | 17462/114105 [00:23<02:03, 781.05 examples/s]
Map:  13%|█▎        | 15279/114105 [00:21<02:21, 700.59 examples/s]
Map:  14%|█▍        | 16123/114105 [00:22<02:23, 681.20 examples/s]
Map:  14%|█▍        | 16413/114105 [00:22<02:08, 761.36 examples/s]
Map:  13%|█▎        | 15357/114105 [00:22<02:17, 719.59 examples/s]
Map:  14%|█▍        | 16210/114105 [00:22<02:15, 723.37 examples/s]
Map:  15%|█▌        | 17582/114105 [00:23<02:02, 785.08 examples/s]
Map:  14%|█▍        | 16497/114105 [00:22<02:05, 778.65 examples/s]
Map:  14%|█▎        | 15433/114105 [00:22<02:15, 728.25 examples/s]
Map:  15%|█▌        | 17666/114105 [00:23<02:01, 796.46 examples/s]
Map:  14%|█▍        | 16294/114105 [00:22<02:10, 749.10 examples/s]
Map:  15%|█▍        | 16578/114105 [00:22<02:04, 785.54 examples/s]
Map:  14%|█▎        | 15512/114105 [00:22<02:12, 742.94 examples/s]
Map:  16%|█▌        | 17755/114105 [00:23<01:57, 818.81 examples/s]
Map:  14%|█▍        | 16379/114105 [00:22<02:06, 774.17 examples/s]
Map:  15%|█▍        | 16661/114105 [00:22<02:02, 797.36 examples/s]
Map:  14%|█▎        | 15625/114105 [00:22<02:12, 741.68 examples/s]
Map:  16%|█▌        | 17872/114105 [00:23<02:00, 798.59 examples/s]
Map:  14%|█▍        | 16494/114105 [00:22<02:07, 765.20 examples/s]
Map:  15%|█▍        | 16769/114105 [00:22<02:07, 763.35 examples/s]
Map:  14%|█▍        | 15706/114105 [00:22<02:09, 757.80 examples/s]
Map:  15%|█▍        | 16578/114105 [00:22<02:04, 782.62 examples/s]
Map:  16%|█▌        | 17959/114105 [00:23<01:58, 812.93 examples/s]
Map:  15%|█▍        | 16850/114105 [00:22<02:06, 771.69 examples/s]
Map:  14%|█▍        | 15788/114105 [00:22<02:07, 772.66 examples/s]
Map:  15%|█▍        | 16668/114105 [00:22<02:00, 806.86 examples/s]
Map:  15%|█▍        | 16935/114105 [00:22<02:02, 791.03 examples/s]
Map:  14%|█▍        | 15871/114105 [00:22<02:04, 787.74 examples/s]
Map:  16%|█▌        | 18082/114105 [00:24<02:24, 664.63 examples/s]
Map:  15%|█▍        | 16788/114105 [00:22<02:01, 800.28 examples/s]
Map:  14%|█▍        | 15953/114105 [00:22<02:03, 793.68 examples/s]
Map:  15%|█▍        | 17034/114105 [00:23<02:35, 626.06 examples/s]
Map:  16%|█▌        | 18165/114105 [00:24<02:17, 697.73 examples/s]
Map:  15%|█▍        | 16875/114105 [00:23<01:59, 815.08 examples/s]
Map:  15%|█▌        | 17116/114105 [00:23<02:25, 668.88 examples/s]
Map:  16%|█▌        | 18251/114105 [00:24<02:10, 733.12 examples/s]
Map:  15%|█▍        | 16961/114105 [00:23<01:57, 826.17 examples/s]
Map:  14%|█▍        | 16041/114105 [00:22<02:42, 602.24 examples/s]
Map:  15%|█▌        | 17199/114105 [00:23<02:17, 706.37 examples/s]
Map:  16%|█▌        | 18341/114105 [00:24<02:04, 772.25 examples/s]
Map:  14%|█▍        | 16123/114105 [00:23<02:30, 650.50 examples/s]
Map:  15%|█▌        | 17277/114105 [00:23<02:13, 724.92 examples/s]
Map:  16%|█▌        | 18428/114105 [00:24<02:00, 795.01 examples/s]
Map:  14%|█▍        | 16205/114105 [00:23<02:21, 691.93 examples/s]
Map:  15%|█▍        | 17078/114105 [00:23<02:29, 647.29 examples/s]
Map:  15%|█▌        | 17359/114105 [00:23<02:09, 749.01 examples/s]
Map:  16%|█▌        | 18513/114105 [00:24<01:58, 808.02 examples/s]
Map:  14%|█▍        | 16287/114105 [00:23<02:15, 722.65 examples/s]
Map:  15%|█▌        | 17161/114105 [00:23<02:21, 684.60 examples/s]
Map:  15%|█▌        | 17444/114105 [00:23<02:04, 773.73 examples/s]
Map:  16%|█▋        | 18629/114105 [00:24<02:00, 791.86 examples/s]
Map:  14%|█▍        | 16374/114105 [00:23<02:08, 759.49 examples/s]
Map:  15%|█▌        | 17243/114105 [00:23<02:16, 711.98 examples/s]
Map:  15%|█▌        | 17529/114105 [00:23<02:01, 793.70 examples/s]
Map:  16%|█▋        | 18712/114105 [00:24<01:59, 799.95 examples/s]
Map:  14%|█▍        | 16457/114105 [00:23<02:05, 776.35 examples/s]
Map:  15%|█▌        | 17327/114105 [00:23<02:10, 740.75 examples/s]
Map:  15%|█▌        | 17612/114105 [00:23<02:00, 799.23 examples/s]
Map:  16%|█▋        | 18794/114105 [00:24<01:58, 801.61 examples/s]
Map:  15%|█▍        | 16571/114105 [00:23<02:07, 766.71 examples/s]
Map:  15%|█▌        | 17440/114105 [00:23<02:10, 741.13 examples/s]
Map:  16%|█▌        | 17730/114105 [00:24<02:01, 792.25 examples/s]
Map:  17%|█▋        | 18914/114105 [00:25<01:59, 798.77 examples/s]
Map:  15%|█▍        | 16655/114105 [00:23<02:04, 781.60 examples/s]
Map:  15%|█▌        | 17522/114105 [00:23<02:07, 759.49 examples/s]
Map:  16%|█▌        | 17851/114105 [00:24<02:01, 794.66 examples/s]
Map:  17%|█▋        | 18997/114105 [00:25<01:58, 804.29 examples/s]
Map:  15%|█▍        | 16735/114105 [00:23<02:04, 783.50 examples/s]
Map:  15%|█▌        | 17606/114105 [00:24<02:04, 776.29 examples/s]
Map:  16%|█▌        | 17934/114105 [00:24<01:59, 801.97 examples/s]
Map:  15%|█▍        | 16818/114105 [00:23<02:02, 792.99 examples/s]
Map:  16%|█▌        | 17695/114105 [00:24<01:59, 804.34 examples/s]
Map:  17%|█▋        | 19087/114105 [00:25<02:28, 638.17 examples/s]
Map:  15%|█▍        | 16899/114105 [00:24<02:02, 793.48 examples/s]
Map:  16%|█▌        | 17779/114105 [00:24<01:58, 810.12 examples/s]
Map:  17%|█▋        | 19169/114105 [00:25<02:19, 678.58 examples/s]
Map:  16%|█▌        | 17863/114105 [00:24<01:57, 818.25 examples/s]
Map:  16%|█▌        | 18041/114105 [00:24<02:29, 643.88 examples/s]
Map:  17%|█▋        | 19255/114105 [00:25<02:11, 722.42 examples/s]
Map:  16%|█▌        | 17947/114105 [00:24<01:56, 823.52 examples/s]
Map:  16%|█▌        | 18125/114105 [00:24<02:20, 683.21 examples/s]
Map:  15%|█▍        | 17000/114105 [00:24<02:37, 616.49 examples/s]
Map:  17%|█▋        | 19342/114105 [00:25<02:04, 758.11 examples/s]
Map:  16%|█▌        | 18206/114105 [00:24<02:14, 711.07 examples/s]
Map:  15%|█▍        | 17086/114105 [00:24<02:24, 670.59 examples/s]
Map:  17%|█▋        | 19429/114105 [00:25<02:00, 785.82 examples/s]
Map:  16%|█▌        | 18286/114105 [00:24<02:10, 733.01 examples/s]
Map:  16%|█▌        | 18042/114105 [00:24<02:31, 632.50 examples/s]
Map:  15%|█▌        | 17169/114105 [00:24<02:16, 707.58 examples/s]
Map:  17%|█▋        | 19518/114105 [00:25<01:56, 810.22 examples/s]
Map:  16%|█▌        | 18371/114105 [00:24<02:05, 760.60 examples/s]
Map:  16%|█▌        | 18128/114105 [00:24<02:20, 683.87 examples/s]
Map:  15%|█▌        | 17251/114105 [00:24<02:11, 736.14 examples/s]
Map:  16%|█▌        | 18455/114105 [00:25<02:02, 779.45 examples/s]
Map:  16%|█▌        | 18211/114105 [00:24<02:13, 717.27 examples/s]
Map:  15%|█▌        | 17333/114105 [00:24<02:07, 756.06 examples/s]
Map:  17%|█▋        | 19646/114105 [00:26<01:55, 820.71 examples/s]
Map:  16%|█▋        | 18566/114105 [00:25<02:05, 761.22 examples/s]
Map:  16%|█▌        | 18323/114105 [00:25<02:11, 725.80 examples/s]
Map:  15%|█▌        | 17451/114105 [00:24<02:07, 760.94 examples/s]
Map:  17%|█▋        | 19763/114105 [00:26<01:58, 796.34 examples/s]
Map:  16%|█▋        | 18647/114105 [00:25<02:03, 770.79 examples/s]
Map:  16%|█▌        | 18407/114105 [00:25<02:07, 749.87 examples/s]
Map:  15%|█▌        | 17536/114105 [00:24<02:03, 781.27 examples/s]
Map:  17%|█▋        | 19856/114105 [00:26<01:54, 824.98 examples/s]
Map:  16%|█▋        | 18734/114105 [00:25<01:59, 796.89 examples/s]
Map:  15%|█▌        | 17622/114105 [00:25<02:00, 799.67 examples/s]
Map:  16%|█▌        | 18521/114105 [00:25<02:07, 748.79 examples/s]
Map:  16%|█▋        | 18820/114105 [00:25<01:57, 812.75 examples/s]
Map:  18%|█▊        | 19980/114105 [00:26<01:54, 821.14 examples/s]
Map:  16%|█▌        | 17739/114105 [00:25<02:02, 789.36 examples/s]
Map:  17%|█▋        | 18904/114105 [00:25<01:56, 816.13 examples/s]
Map:  16%|█▋        | 18630/114105 [00:25<02:09, 736.38 examples/s]
Map:  16%|█▌        | 17825/114105 [00:25<01:59, 804.94 examples/s]
Map:  17%|█▋        | 18992/114105 [00:25<01:54, 829.37 examples/s]
Map:  16%|█▋        | 18710/114105 [00:25<02:07, 749.75 examples/s]
Map:  18%|█▊        | 20089/114105 [00:26<02:19, 674.63 examples/s]
Map:  16%|█▋        | 18802/114105 [00:25<02:00, 791.15 examples/s]
Map:  18%|█▊        | 20177/114105 [00:26<02:11, 715.64 examples/s]
Map:  16%|█▌        | 17952/114105 [00:25<01:57, 814.91 examples/s]
Map:  17%|█▋        | 19076/114105 [00:25<02:31, 628.43 examples/s]
Map:  17%|█▋        | 18891/114105 [00:25<01:56, 814.06 examples/s]
Map:  18%|█▊        | 20263/114105 [00:26<02:05, 747.07 examples/s]
Map:  17%|█▋        | 19158/114105 [00:26<02:21, 672.69 examples/s]
Map:  18%|█▊        | 20345/114105 [00:26<02:02, 762.99 examples/s]
Map:  16%|█▌        | 18038/114105 [00:25<02:28, 646.26 examples/s]
Map:  17%|█▋        | 19245/114105 [00:26<02:11, 719.39 examples/s]
Map:  18%|█▊        | 20426/114105 [00:27<02:01, 772.49 examples/s]
Map:  16%|█▌        | 18123/114105 [00:25<02:19, 689.13 examples/s]
Map:  17%|█▋        | 19000/114105 [00:25<02:28, 638.51 examples/s]
Map:  17%|█▋        | 19330/114105 [00:26<02:06, 750.42 examples/s]
Map:  18%|█▊        | 20508/114105 [00:27<01:59, 782.84 examples/s]
Map:  16%|█▌        | 18209/114105 [00:25<02:11, 727.58 examples/s]
Map:  17%|█▋        | 19079/114105 [00:26<02:21, 669.88 examples/s]
Map:  17%|█▋        | 19416/114105 [00:26<02:01, 776.66 examples/s]
Map:  18%|█▊        | 20593/114105 [00:27<01:57, 797.25 examples/s]
Map:  16%|█▌        | 18291/114105 [00:25<02:07, 749.05 examples/s]
Map:  17%|█▋        | 19167/114105 [00:26<02:12, 716.86 examples/s]
Map:  17%|█▋        | 19252/114105 [00:26<02:06, 749.78 examples/s]
Map:  17%|█▋        | 19528/114105 [00:26<02:04, 761.76 examples/s]
Map:  18%|█▊        | 20712/114105 [00:27<01:57, 791.79 examples/s]
Map:  16%|█▌        | 18402/114105 [00:26<02:09, 738.87 examples/s]
Map:  17%|█▋        | 19615/114105 [00:26<02:00, 785.40 examples/s]
Map:  18%|█▊        | 20800/114105 [00:27<01:54, 812.54 examples/s]
Map:  16%|█▌        | 18484/114105 [00:26<02:06, 756.26 examples/s]
Map:  17%|█▋        | 19376/114105 [00:26<02:02, 774.17 examples/s]
Map:  17%|█▋        | 19696/114105 [00:26<01:59, 791.01 examples/s]
Map:  18%|█▊        | 20884/114105 [00:27<01:55, 808.43 examples/s]
Map:  16%|█▋        | 18563/114105 [00:26<02:04, 764.64 examples/s]
Map:  17%|█▋        | 19460/114105 [00:26<01:59, 789.10 examples/s]
Map:  17%|█▋        | 19783/114105 [00:26<01:56, 809.84 examples/s]
Map:  18%|█▊        | 20969/114105 [00:27<01:54, 816.37 examples/s]
Map:  16%|█▋        | 18648/114105 [00:26<02:01, 785.48 examples/s]
Map:  17%|█▋        | 19546/114105 [00:26<01:57, 805.39 examples/s]
Map:  17%|█▋        | 19906/114105 [00:26<01:56, 809.91 examples/s]
Map:  16%|█▋        | 18764/114105 [00:26<02:02, 779.03 examples/s]
Map:  17%|█▋        | 19650/114105 [00:26<02:04, 761.16 examples/s]
Map:  18%|█▊        | 19988/114105 [00:27<01:56, 810.09 examples/s]
Map:  18%|█▊        | 21082/114105 [00:27<02:23, 647.38 examples/s]
Map:  17%|█▋        | 18846/114105 [00:26<02:00, 789.43 examples/s]
Map:  17%|█▋        | 19766/114105 [00:26<02:03, 762.03 examples/s]
Map:  19%|█▊        | 21170/114105 [00:28<02:13, 696.86 examples/s]
Map:  17%|█▋        | 18961/114105 [00:26<02:02, 777.18 examples/s]
Map:  19%|█▊        | 21252/114105 [00:28<02:07, 726.11 examples/s]
Map:  18%|█▊        | 20082/114105 [00:27<02:26, 643.85 examples/s]
Map:  17%|█▋        | 19878/114105 [00:27<02:04, 755.11 examples/s]
Map:  19%|█▊        | 21332/114105 [00:28<02:04, 742.33 examples/s]
Map:  18%|█▊        | 20164/114105 [00:27<02:17, 682.32 examples/s]
Map:  17%|█▋        | 19960/114105 [00:27<02:02, 768.90 examples/s]
Map:  17%|█▋        | 19042/114105 [00:27<02:37, 605.48 examples/s]
Map:  19%|█▉        | 21416/114105 [00:28<02:01, 766.02 examples/s]
Map:  18%|█▊        | 20249/114105 [00:27<02:10, 720.72 examples/s]
Map:  17%|█▋        | 19119/114105 [00:27<02:28, 641.04 examples/s]
Map:  19%|█▉        | 21504/114105 [00:28<01:56, 793.95 examples/s]
Map:  18%|█▊        | 20333/114105 [00:27<02:05, 746.92 examples/s]
Map:  17%|█▋        | 19196/114105 [00:27<02:21, 670.23 examples/s]
Map:  18%|█▊        | 20073/114105 [00:27<02:34, 608.14 examples/s]
Map:  19%|█▉        | 21588/114105 [00:28<01:55, 802.93 examples/s]
Map:  18%|█▊        | 20414/114105 [00:27<02:02, 762.20 examples/s]
Map:  17%|█▋        | 19273/114105 [00:27<02:16, 692.65 examples/s]
Map:  18%|█▊        | 20155/114105 [00:27<02:24, 648.74 examples/s]
Map:  19%|█▉        | 21714/114105 [00:28<01:54, 807.41 examples/s]
Map:  18%|█▊        | 20533/114105 [00:27<02:01, 769.70 examples/s]
Map:  17%|█▋        | 19350/114105 [00:27<02:13, 712.09 examples/s]
Map:  18%|█▊        | 20233/114105 [00:27<02:18, 676.90 examples/s]
Map:  19%|█▉        | 21797/114105 [00:28<01:53, 810.29 examples/s]
Map:  18%|█▊        | 20618/114105 [00:27<01:58, 786.24 examples/s]
Map:  17%|█▋        | 19427/114105 [00:27<02:10, 724.37 examples/s]
Map:  18%|█▊        | 20314/114105 [00:27<02:12, 705.71 examples/s]
Map:  19%|█▉        | 21884/114105 [00:28<01:52, 821.91 examples/s]
Map:  18%|█▊        | 20703/114105 [00:27<01:56, 801.86 examples/s]
Map:  17%|█▋        | 19510/114105 [00:27<02:05, 751.88 examples/s]
Map:  18%|█▊        | 20391/114105 [00:27<02:09, 721.79 examples/s]
Map:  19%|█▉        | 21974/114105 [00:29<01:49, 840.64 examples/s]
Map:  18%|█▊        | 20786/114105 [00:28<01:55, 808.79 examples/s]
Map:  17%|█▋        | 19589/114105 [00:27<02:04, 761.62 examples/s]
Map:  18%|█▊        | 20469/114105 [00:27<02:07, 736.24 examples/s]
Map:  17%|█▋        | 19671/114105 [00:27<02:02, 772.56 examples/s]
Map:  18%|█▊        | 20902/114105 [00:28<01:57, 790.56 examples/s]
Map:  18%|█▊        | 20583/114105 [00:28<02:05, 743.45 examples/s]
Map:  19%|█▉        | 22081/114105 [00:29<02:19, 657.31 examples/s]
Map:  17%|█▋        | 19786/114105 [00:28<02:02, 767.18 examples/s]
Map:  18%|█▊        | 20661/114105 [00:28<02:04, 751.15 examples/s]
Map:  19%|█▉        | 22166/114105 [00:29<02:11, 698.87 examples/s]
Map:  18%|█▊        | 21000/114105 [00:28<02:26, 633.96 examples/s]
Map:  18%|█▊        | 20739/114105 [00:28<02:03, 756.14 examples/s]
Map:  17%|█▋        | 19903/114105 [00:28<02:02, 768.94 examples/s]
Map:  20%|█▉        | 22252/114105 [00:29<02:04, 735.36 examples/s]
Map:  18%|█▊        | 21078/114105 [00:28<02:20, 664.10 examples/s]
Map:  18%|█▊        | 20819/114105 [00:28<02:01, 765.39 examples/s]
Map:  20%|█▉        | 22341/114105 [00:29<01:59, 770.63 examples/s]
Map:  19%|█▊        | 21159/114105 [00:28<02:13, 696.29 examples/s]
Map:  20%|█▉        | 22430/114105 [00:29<01:54, 801.09 examples/s]
Map:  18%|█▊        | 20928/114105 [00:28<02:04, 745.89 examples/s]
Map:  18%|█▊        | 20000/114105 [00:28<02:35, 606.85 examples/s]
Map:  19%|█▊        | 21241/114105 [00:28<02:08, 722.23 examples/s]
Map:  20%|█▉        | 22519/114105 [00:29<01:51, 821.66 examples/s]
Map:  18%|█▊        | 20082/114105 [00:28<02:24, 649.45 examples/s]
Map:  19%|█▊        | 21330/114105 [00:28<02:01, 762.71 examples/s]
Map:  18%|█▊        | 20162/114105 [00:28<02:17, 683.61 examples/s]
Map:  19%|█▉        | 21413/114105 [00:28<01:59, 778.80 examples/s]
Map:  20%|█▉        | 22647/114105 [00:29<01:50, 829.68 examples/s]
Map:  18%|█▊        | 21042/114105 [00:28<02:34, 603.36 examples/s]
Map:  18%|█▊        | 20241/114105 [00:28<02:12, 708.99 examples/s]
Map:  19%|█▉        | 21495/114105 [00:29<01:57, 788.96 examples/s]
Map:  19%|█▊        | 21124/114105 [00:28<02:23, 646.90 examples/s]
Map:  20%|█▉        | 22775/114105 [00:30<01:49, 835.20 examples/s]
Map:  18%|█▊        | 20322/114105 [00:28<02:08, 732.16 examples/s]
Map:  19%|█▉        | 21578/114105 [00:29<01:56, 797.21 examples/s]
Map:  19%|█▊        | 21204/114105 [00:29<02:16, 679.65 examples/s]
Map:  20%|██        | 22863/114105 [00:30<01:48, 842.66 examples/s]
Map:  18%|█▊        | 20411/114105 [00:28<02:01, 768.15 examples/s]
Map:  19%|█▊        | 21287/114105 [00:29<02:09, 715.62 examples/s]
Map:  19%|█▉        | 21704/114105 [00:29<01:53, 810.93 examples/s]
Map:  18%|█▊        | 20493/114105 [00:29<02:00, 779.00 examples/s]
Map:  20%|██        | 22992/114105 [00:30<01:48, 841.96 examples/s]
Map:  19%|█▊        | 21365/114105 [00:29<02:07, 728.51 examples/s]
Map:  19%|█▉        | 21787/114105 [00:29<01:53, 813.75 examples/s]
Map:  18%|█▊        | 20576/114105 [00:29<01:58, 789.81 examples/s]
Map:  19%|█▉        | 21445/114105 [00:29<02:04, 746.85 examples/s]
Map:  19%|█▉        | 21872/114105 [00:29<01:52, 820.76 examples/s]
Map:  18%|█▊        | 20657/114105 [00:29<01:57, 793.08 examples/s]
Map:  20%|██        | 23086/114105 [00:30<02:14, 679.13 examples/s]
Map:  19%|█▉        | 21531/114105 [00:29<01:59, 774.79 examples/s]
Map:  18%|█▊        | 20744/114105 [00:29<01:54, 811.93 examples/s]
Map:  19%|█▉        | 21993/114105 [00:29<01:53, 810.39 examples/s]
Map:  20%|██        | 23170/114105 [00:30<02:07, 711.96 examples/s]
Map:  19%|█▉        | 21614/114105 [00:29<01:57, 788.71 examples/s]
Map:  20%|██        | 23251/114105 [00:30<02:04, 731.00 examples/s]
Map:  18%|█▊        | 20864/114105 [00:29<01:55, 804.55 examples/s]
Map:  19%|█▉        | 21731/114105 [00:29<01:58, 781.47 examples/s]
Map:  19%|█▉        | 22086/114105 [00:29<02:21, 651.21 examples/s]
Map:  20%|██        | 23336/114105 [00:30<01:59, 757.82 examples/s]
Map:  19%|█▉        | 21816/114105 [00:29<01:55, 796.17 examples/s]
Map:  18%|█▊        | 20988/114105 [00:29<01:55, 806.59 examples/s]
Map:  19%|█▉        | 22168/114105 [00:30<02:14, 685.83 examples/s]
Map:  21%|██        | 23419/114105 [00:30<01:57, 774.43 examples/s]
Map:  19%|█▉        | 21899/114105 [00:29<01:55, 799.97 examples/s]
Map:  20%|█▉        | 22252/114105 [00:30<02:07, 721.02 examples/s]
Map:  21%|██        | 23506/114105 [00:31<01:53, 798.01 examples/s]
Map:  19%|█▉        | 21982/114105 [00:29<01:54, 805.90 examples/s]
Map:  18%|█▊        | 21081/114105 [00:29<02:25, 641.54 examples/s]
Map:  20%|█▉        | 22339/114105 [00:30<02:01, 755.78 examples/s]
Map:  21%|██        | 23627/114105 [00:31<01:53, 798.73 examples/s]
Map:  19%|█▊        | 21169/114105 [00:29<02:14, 691.01 examples/s]
Map:  20%|█▉        | 22420/114105 [00:30<01:59, 768.21 examples/s]
Map:  21%|██        | 23711/114105 [00:31<01:51, 808.01 examples/s]
Map:  19%|█▉        | 22080/114105 [00:30<02:27, 623.86 examples/s]
Map:  19%|█▊        | 21252/114105 [00:30<02:08, 720.93 examples/s]
Map:  20%|█▉        | 22505/114105 [00:30<01:56, 787.72 examples/s]
Map:  19%|█▉        | 22166/114105 [00:30<02:15, 676.52 examples/s]
Map:  19%|█▊        | 21338/114105 [00:30<02:03, 753.91 examples/s]
Map:  20%|█▉        | 22589/114105 [00:30<01:54, 801.14 examples/s]
Map:  21%|██        | 23835/114105 [00:31<01:51, 810.34 examples/s]
Map:  19%|█▉        | 22250/114105 [00:30<02:08, 714.35 examples/s]
Map:  19%|█▉        | 21419/114105 [00:30<02:01, 764.65 examples/s]
Map:  20%|█▉        | 22671/114105 [00:30<01:53, 803.98 examples/s]
Map:  21%|██        | 23923/114105 [00:31<01:49, 824.24 examples/s]
Map:  20%|█▉        | 22331/114105 [00:30<02:04, 738.13 examples/s]
Map:  19%|█▉        | 21506/114105 [00:30<01:57, 790.27 examples/s]
Map:  20%|█▉        | 22760/114105 [00:30<01:50, 827.10 examples/s]
Map:  20%|█▉        | 22414/114105 [00:30<02:00, 761.93 examples/s]
Map:  19%|█▉        | 21590/114105 [00:30<01:55, 802.02 examples/s]
Map:  20%|██        | 22844/114105 [00:30<01:50, 827.11 examples/s]
Map:  21%|██        | 24043/114105 [00:31<02:14, 667.50 examples/s]
Map:  20%|█▉        | 22498/114105 [00:30<01:57, 782.42 examples/s]
Map:  19%|█▉        | 21679/114105 [00:30<01:52, 822.18 examples/s]
Map:  20%|██        | 22928/114105 [00:30<01:50, 827.95 examples/s]
Map:  21%|██        | 24130/114105 [00:31<02:06, 709.71 examples/s]
Map:  20%|█▉        | 22584/114105 [00:30<01:54, 801.80 examples/s]
Map:  19%|█▉        | 21763/114105 [00:30<01:51, 826.44 examples/s]
Map:  21%|██        | 24216/114105 [00:31<02:00, 743.21 examples/s]
Map:  20%|█▉        | 22672/114105 [00:30<01:51, 822.69 examples/s]
Map:  19%|█▉        | 21847/114105 [00:30<01:51, 824.54 examples/s]
Map:  20%|██        | 23042/114105 [00:31<02:19, 651.44 examples/s]
Map:  21%|██▏       | 24297/114105 [00:32<01:58, 757.73 examples/s]
Map:  20%|█▉        | 22759/114105 [00:31<01:49, 830.91 examples/s]
Map:  20%|██        | 23125/114105 [00:31<02:11, 690.76 examples/s]
Map:  21%|██▏       | 24385/114105 [00:32<01:53, 787.85 examples/s]
Map:  19%|█▉        | 21972/114105 [00:30<01:52, 817.60 examples/s]
Map:  20%|██        | 22885/114105 [00:31<01:49, 832.02 examples/s]
Map:  20%|██        | 23203/114105 [00:31<02:08, 710.01 examples/s]
Map:  21%|██▏       | 24501/114105 [00:32<01:54, 779.27 examples/s]
Map:  20%|██        | 22970/114105 [00:31<01:49, 833.40 examples/s]
Map:  20%|██        | 23284/114105 [00:31<02:04, 732.01 examples/s]
Map:  22%|██▏       | 24590/114105 [00:32<01:51, 805.54 examples/s]
Map:  19%|█▉        | 22080/114105 [00:31<02:24, 635.20 examples/s]
Map:  20%|██        | 23367/114105 [00:31<02:00, 755.13 examples/s]
Map:  22%|██▏       | 24673/114105 [00:32<01:50, 808.18 examples/s]
Map:  19%|█▉        | 22170/114105 [00:31<02:13, 688.95 examples/s]
Map:  20%|██        | 23087/114105 [00:31<02:18, 658.57 examples/s]
Map:  21%|██        | 23489/114105 [00:31<01:57, 771.25 examples/s]
Map:  22%|██▏       | 24757/114105 [00:32<01:49, 815.78 examples/s]
Map:  20%|█▉        | 22253/114105 [00:31<02:07, 719.51 examples/s]
Map:  20%|██        | 23172/114105 [00:31<02:10, 699.43 examples/s]
Map:  21%|██        | 23572/114105 [00:31<01:55, 783.86 examples/s]
Map:  20%|█▉        | 22337/114105 [00:31<02:02, 748.11 examples/s]
Map:  22%|██▏       | 24879/114105 [00:32<01:49, 812.64 examples/s]
Map:  20%|██        | 23256/114105 [00:31<02:04, 730.44 examples/s]
Map:  21%|██        | 23653/114105 [00:31<01:54, 790.70 examples/s]
Map:  20%|█▉        | 22422/114105 [00:31<01:58, 772.45 examples/s]
Map:  22%|██▏       | 24966/114105 [00:32<01:48, 823.08 examples/s]
Map:  20%|██        | 23342/114105 [00:31<01:59, 761.74 examples/s]
Map:  21%|██        | 23738/114105 [00:32<01:52, 805.28 examples/s]
Map:  20%|█▉        | 22507/114105 [00:31<01:55, 791.45 examples/s]
Map:  21%|██        | 23426/114105 [00:31<01:56, 779.08 examples/s]
Map:  20%|█▉        | 22590/114105 [00:31<01:54, 800.96 examples/s]
Map:  21%|██        | 23857/114105 [00:32<01:53, 796.24 examples/s]
Map:  22%|██▏       | 25077/114105 [00:33<02:18, 644.57 examples/s]
Map:  20%|█▉        | 22673/114105 [00:31<01:53, 805.42 examples/s]
Map:  21%|██        | 23551/114105 [00:32<01:53, 796.21 examples/s]
Map:  21%|██        | 23978/114105 [00:32<01:53, 794.38 examples/s]
Map:  22%|██▏       | 25153/114105 [00:33<02:13, 664.16 examples/s]
Map:  20%|█▉        | 22757/114105 [00:31<01:52, 811.01 examples/s]
Map:  21%|██        | 23673/114105 [00:32<01:53, 796.61 examples/s]
Map:  22%|██▏       | 25231/114105 [00:33<02:08, 690.85 examples/s]
Map:  20%|██        | 22872/114105 [00:32<01:55, 788.11 examples/s]
Map:  21%|██        | 23756/114105 [00:32<01:52, 802.60 examples/s]
Map:  22%|██▏       | 25306/114105 [00:33<02:06, 704.13 examples/s]
Map:  21%|██        | 24071/114105 [00:32<02:23, 626.50 examples/s]
Map:  22%|██▏       | 25382/114105 [00:33<02:04, 710.91 examples/s]
Map:  20%|██        | 22980/114105 [00:32<01:59, 760.75 examples/s]
Map:  21%|██        | 24141/114105 [00:32<02:20, 638.37 examples/s]
Map:  21%|██        | 23871/114105 [00:32<01:54, 786.35 examples/s]
Map:  22%|██▏       | 25460/114105 [00:33<02:01, 727.00 examples/s]
Map:  21%|██        | 24214/114105 [00:32<02:16, 657.08 examples/s]
Map:  21%|██        | 23957/114105 [00:32<01:52, 802.53 examples/s]
Map:  22%|██▏       | 25541/114105 [00:33<01:58, 747.54 examples/s]
Map:  21%|██▏       | 24296/114105 [00:32<02:08, 696.27 examples/s]
Map:  20%|██        | 23084/114105 [00:32<02:28, 611.35 examples/s]
Map:  22%|██▏       | 25621/114105 [00:33<01:56, 756.70 examples/s]
Map:  21%|██▏       | 24375/114105 [00:32<02:04, 718.98 examples/s]
Map:  20%|██        | 23168/114105 [00:32<02:18, 656.76 examples/s]
Map:  21%|██        | 24042/114105 [00:32<02:23, 626.85 examples/s]
Map:  23%|██▎       | 25701/114105 [00:33<01:55, 766.39 examples/s]
Map:  21%|██▏       | 24457/114105 [00:33<02:00, 743.40 examples/s]
Map:  20%|██        | 23251/114105 [00:32<02:11, 692.90 examples/s]
Map:  21%|██        | 24122/114105 [00:32<02:15, 664.54 examples/s]
Map:  23%|██▎       | 25782/114105 [00:34<01:53, 776.04 examples/s]
Map:  22%|██▏       | 24540/114105 [00:33<01:57, 762.24 examples/s]
Map:  20%|██        | 23337/114105 [00:32<02:03, 733.31 examples/s]
Map:  21%|██        | 24204/114105 [00:33<02:08, 698.67 examples/s]
Map:  21%|██        | 23422/114105 [00:32<01:59, 761.41 examples/s]
Map:  21%|██▏       | 24287/114105 [00:33<02:03, 728.34 examples/s]
Map:  23%|██▎       | 25900/114105 [00:34<01:53, 777.64 examples/s]
Map:  22%|██▏       | 24656/114105 [00:33<01:57, 761.69 examples/s]
Map:  21%|██        | 23507/114105 [00:33<01:55, 783.21 examples/s]
Map:  21%|██▏       | 24368/114105 [00:33<02:00, 746.24 examples/s]
Map:  23%|██▎       | 25989/114105 [00:34<01:49, 804.58 examples/s]
Map:  22%|██▏       | 24737/114105 [00:33<01:55, 771.20 examples/s]
Map:  21%|██        | 23591/114105 [00:33<01:53, 796.22 examples/s]
Map:  21%|██▏       | 24454/114105 [00:33<01:55, 774.53 examples/s]
Map:  22%|██▏       | 24821/114105 [00:33<01:53, 787.45 examples/s]
Map:  21%|██        | 23676/114105 [00:33<01:51, 810.32 examples/s]
Map:  22%|██▏       | 24537/114105 [00:33<01:53, 787.43 examples/s]
Map:  23%|██▎       | 26084/114105 [00:34<02:18, 634.76 examples/s]
Map:  22%|██▏       | 24941/114105 [00:33<01:53, 786.46 examples/s]
Map:  22%|██▏       | 24622/114105 [00:33<01:51, 801.87 examples/s]
Map:  23%|██▎       | 26165/114105 [00:34<02:10, 673.14 examples/s]
Map:  21%|██        | 23799/114105 [00:33<01:51, 811.45 examples/s]
Map:  22%|██▏       | 24707/114105 [00:33<01:49, 814.77 examples/s]
Map:  23%|██▎       | 26244/114105 [00:34<02:05, 699.46 examples/s]
Map:  21%|██        | 23886/114105 [00:33<01:49, 822.05 examples/s]
Map:  22%|██▏       | 25033/114105 [00:33<02:25, 610.69 examples/s]
Map:  23%|██▎       | 26319/114105 [00:34<02:03, 709.47 examples/s]
Map:  22%|██▏       | 24823/114105 [00:33<01:52, 794.35 examples/s]
Map:  21%|██        | 23985/114105 [00:33<01:58, 761.28 examples/s]
Map:  22%|██▏       | 25114/114105 [00:34<02:16, 651.52 examples/s]
Map:  23%|██▎       | 26399/114105 [00:34<02:00, 729.82 examples/s]
Map:  22%|██▏       | 24907/114105 [00:33<01:51, 800.78 examples/s]
Map:  22%|██▏       | 25199/114105 [00:34<02:08, 694.03 examples/s]
Map:  23%|██▎       | 26481/114105 [00:35<01:56, 750.77 examples/s]
Map:  22%|██▏       | 24994/114105 [00:33<01:48, 818.06 examples/s]
Map:  22%|██▏       | 25277/114105 [00:34<02:04, 712.65 examples/s]
Map:  23%|██▎       | 26561/114105 [00:35<01:54, 761.72 examples/s]
Map:  21%|██        | 24081/114105 [00:33<02:27, 609.62 examples/s]
Map:  22%|██▏       | 25358/114105 [00:34<02:00, 735.79 examples/s]
Map:  23%|██▎       | 26643/114105 [00:35<01:52, 776.84 examples/s]
Map:  21%|██        | 24164/114105 [00:33<02:17, 655.80 examples/s]
Map:  22%|██▏       | 25080/114105 [00:34<02:21, 628.25 examples/s]
Map:  22%|██▏       | 25441/114105 [00:34<01:56, 758.32 examples/s]
Map:  23%|██▎       | 26724/114105 [00:35<01:51, 782.01 examples/s]
Map:  21%|██        | 24245/114105 [00:34<02:10, 689.16 examples/s]
Map:  22%|██▏       | 25163/114105 [00:34<02:12, 671.55 examples/s]
Map:  21%|██▏       | 24330/114105 [00:34<02:03, 727.57 examples/s]
Map:  22%|██▏       | 25556/114105 [00:34<01:56, 759.67 examples/s]
Map:  22%|██▏       | 25245/114105 [00:34<02:05, 707.07 examples/s]
Map:  24%|██▎       | 26841/114105 [00:35<01:52, 778.79 examples/s]
Map:  21%|██▏       | 24412/114105 [00:34<01:59, 750.37 examples/s]
Map:  22%|██▏       | 25635/114105 [00:34<01:55, 763.11 examples/s]
Map:  22%|██▏       | 25326/114105 [00:34<02:01, 733.13 examples/s]
Map:  24%|██▎       | 26957/114105 [00:35<01:53, 771.12 examples/s]
Map:  21%|██▏       | 24496/114105 [00:34<01:55, 772.53 examples/s]
Map:  23%|██▎       | 25715/114105 [00:34<01:54, 771.46 examples/s]
Map:  22%|██▏       | 25411/114105 [00:34<01:56, 762.03 examples/s]
Map:  22%|██▏       | 24579/114105 [00:34<01:53, 785.65 examples/s]
Map:  22%|██▏       | 25495/114105 [00:34<01:53, 782.65 examples/s]
Map:  23%|██▎       | 25830/114105 [00:34<01:55, 763.32 examples/s]
Map:  22%|██▏       | 24662/114105 [00:34<01:52, 797.01 examples/s]
Map:  24%|██▎       | 27039/114105 [00:35<02:23, 605.71 examples/s]
Map:  22%|██▏       | 25576/114105 [00:34<01:52, 788.91 examples/s]
Map:  23%|██▎       | 25909/114105 [00:35<01:54, 768.10 examples/s]
Map:  22%|██▏       | 24744/114105 [00:34<01:51, 800.11 examples/s]
Map:  24%|██▍       | 27122/114105 [00:35<02:13, 650.67 examples/s]
Map:  22%|██▏       | 25662/114105 [00:34<01:49, 806.48 examples/s]
Map:  23%|██▎       | 25990/114105 [00:35<01:53, 775.40 examples/s]
Map:  22%|██▏       | 24833/114105 [00:34<01:48, 822.59 examples/s]
Map:  24%|██▍       | 27204/114105 [00:36<02:06, 684.85 examples/s]
Map:  23%|██▎       | 25769/114105 [00:35<01:54, 768.54 examples/s]
Map:  22%|██▏       | 24947/114105 [00:34<01:52, 793.72 examples/s]
Map:  24%|██▍       | 27318/114105 [00:36<02:03, 704.73 examples/s]
Map:  23%|██▎       | 25851/114105 [00:35<01:52, 782.02 examples/s]
Map:  23%|██▎       | 26077/114105 [00:35<02:30, 585.38 examples/s]
Map:  24%|██▍       | 27399/114105 [00:36<01:59, 728.45 examples/s]
Map:  23%|██▎       | 25931/114105 [00:35<01:52, 785.71 examples/s]
Map:  23%|██▎       | 26155/114105 [00:35<02:20, 627.39 examples/s]
Map:  22%|██▏       | 25040/114105 [00:35<02:20, 632.93 examples/s]
Map:  24%|██▍       | 27480/114105 [00:36<01:56, 745.77 examples/s]
Map:  23%|██▎       | 26234/114105 [00:35<02:12, 665.63 examples/s]
Map:  22%|██▏       | 25127/114105 [00:35<02:10, 683.97 examples/s]
Map:  24%|██▍       | 27559/114105 [00:36<01:54, 755.14 examples/s]
Map:  23%|██▎       | 26313/114105 [00:35<02:06, 695.94 examples/s]
Map:  23%|██▎       | 26042/114105 [00:35<02:24, 609.10 examples/s]
Map:  22%|██▏       | 25210/114105 [00:35<02:04, 714.38 examples/s]
Map:  24%|██▍       | 27637/114105 [00:36<01:53, 758.62 examples/s]
Map:  23%|██▎       | 26391/114105 [00:35<02:02, 716.95 examples/s]
Map:  23%|██▎       | 26121/114105 [00:35<02:16, 646.67 examples/s]
Map:  22%|██▏       | 25296/114105 [00:35<01:58, 749.91 examples/s]
Map:  23%|██▎       | 26470/114105 [00:35<01:59, 733.52 examples/s]
Map:  24%|██▍       | 27751/114105 [00:36<01:54, 754.52 examples/s]
Map:  23%|██▎       | 26203/114105 [00:35<02:08, 684.79 examples/s]
Map:  22%|██▏       | 25378/114105 [00:35<01:55, 765.29 examples/s]
Map:  23%|██▎       | 26287/114105 [00:35<02:01, 721.25 examples/s]
Map:  23%|██▎       | 26583/114105 [00:36<01:58, 738.10 examples/s]
Map:  22%|██▏       | 25461/114105 [00:35<01:53, 779.27 examples/s]
Map:  24%|██▍       | 27865/114105 [00:36<01:54, 752.44 examples/s]
Map:  23%|██▎       | 26369/114105 [00:35<01:57, 744.46 examples/s]
Map:  23%|██▎       | 26660/114105 [00:36<01:57, 743.69 examples/s]
Map:  24%|██▍       | 27945/114105 [00:37<01:53, 759.11 examples/s]
Map:  22%|██▏       | 25580/114105 [00:35<01:53, 781.74 examples/s]
Map:  23%|██▎       | 26450/114105 [00:36<01:55, 757.27 examples/s]
Map:  23%|██▎       | 26777/114105 [00:36<01:56, 748.63 examples/s]
Map:  23%|██▎       | 26535/114105 [00:36<01:52, 778.64 examples/s]
Map:  23%|██▎       | 25697/114105 [00:35<01:53, 776.64 examples/s]
Map:  25%|██▍       | 28038/114105 [00:37<02:23, 598.78 examples/s]
Map:  24%|██▎       | 26854/114105 [00:36<01:56, 749.84 examples/s]
Map:  23%|██▎       | 26615/114105 [00:36<01:52, 780.87 examples/s]
Map:  25%|██▍       | 28118/114105 [00:37<02:14, 641.22 examples/s]
Map:  23%|██▎       | 25816/114105 [00:36<01:53, 779.25 examples/s]
Map:  24%|██▎       | 26931/114105 [00:36<01:55, 752.26 examples/s]
Map:  23%|██▎       | 26726/114105 [00:36<01:54, 759.99 examples/s]
Map:  25%|██▍       | 28193/114105 [00:37<02:09, 664.67 examples/s]
Map:  23%|██▎       | 25928/114105 [00:36<01:55, 764.99 examples/s]
Map:  24%|██▎       | 26844/114105 [00:36<01:54, 763.85 examples/s]
Map:  25%|██▍       | 28302/114105 [00:37<02:05, 681.41 examples/s]
Map:  24%|██▎       | 27033/114105 [00:36<02:30, 578.37 examples/s]
Map:  24%|██▎       | 26928/114105 [00:36<01:51, 779.49 examples/s]
Map:  25%|██▍       | 28375/114105 [00:37<02:04, 690.27 examples/s]
Map:  24%|██▍       | 27112/114105 [00:36<02:19, 622.09 examples/s]
Map:  23%|██▎       | 26037/114105 [00:36<02:21, 621.45 examples/s]
Map:  25%|██▍       | 28454/114105 [00:37<02:00, 712.43 examples/s]
Map:  24%|██▍       | 27193/114105 [00:36<02:11, 661.35 examples/s]
Map:  23%|██▎       | 26121/114105 [00:36<02:12, 663.19 examples/s]
Map:  25%|██▌       | 28530/114105 [00:37<01:58, 722.33 examples/s]
Map:  24%|██▍       | 27272/114105 [00:37<02:05, 690.40 examples/s]
Map:  24%|██▎       | 27044/114105 [00:36<02:18, 627.87 examples/s]
Map:  23%|██▎       | 26204/114105 [00:36<02:05, 697.95 examples/s]
Map:  25%|██▌       | 28607/114105 [00:38<01:56, 733.01 examples/s]
Map:  24%|██▍       | 27355/114105 [00:37<01:59, 725.54 examples/s]
Map:  24%|██▍       | 27122/114105 [00:36<02:12, 658.11 examples/s]
Map:  23%|██▎       | 26289/114105 [00:36<02:00, 730.04 examples/s]
Map:  25%|██▌       | 28684/114105 [00:38<01:55, 739.08 examples/s]
Map:  24%|██▍       | 27436/114105 [00:37<01:56, 747.11 examples/s]
Map:  24%|██▍       | 27200/114105 [00:37<02:07, 682.97 examples/s]
Map:  23%|██▎       | 26372/114105 [00:36<01:56, 754.18 examples/s]
Map:  25%|██▌       | 28764/114105 [00:38<01:53, 754.38 examples/s]
Map:  24%|██▍       | 27514/114105 [00:37<01:54, 754.13 examples/s]
Map:  24%|██▍       | 27279/114105 [00:37<02:02, 707.31 examples/s]
Map:  23%|██▎       | 26452/114105 [00:37<01:54, 763.75 examples/s]
Map:  24%|██▍       | 27358/114105 [00:37<01:59, 726.41 examples/s]
Map:  25%|██▌       | 28879/114105 [00:38<01:53, 753.74 examples/s]
Map:  23%|██▎       | 26537/114105 [00:37<01:51, 783.06 examples/s]
Map:  24%|██▍       | 27630/114105 [00:37<01:53, 758.62 examples/s]
Map:  24%|██▍       | 27437/114105 [00:37<01:56, 741.76 examples/s]
Map:  25%|██▌       | 28955/114105 [00:38<01:53, 750.69 examples/s]
Map:  23%|██▎       | 26655/114105 [00:37<01:51, 781.68 examples/s]
Map:  24%|██▍       | 27745/114105 [00:37<01:53, 760.90 examples/s]
Map:  24%|██▍       | 27521/114105 [00:37<01:53, 762.86 examples/s]
Map:  23%|██▎       | 26736/114105 [00:37<01:51, 783.21 examples/s]
Map:  24%|██▍       | 27823/114105 [00:37<01:53, 762.76 examples/s]
Map:  24%|██▍       | 27606/114105 [00:37<01:50, 783.87 examples/s]
Map:  25%|██▌       | 29038/114105 [00:38<02:28, 574.60 examples/s]
Map:  24%|██▍       | 27900/114105 [00:37<01:53, 761.57 examples/s]
Map:  24%|██▎       | 26850/114105 [00:37<01:53, 771.69 examples/s]
Map:  26%|██▌       | 29114/114105 [00:38<02:18, 615.42 examples/s]
Map:  24%|██▍       | 27720/114105 [00:37<01:52, 769.10 examples/s]
Map:  26%|██▌       | 29191/114105 [00:38<02:10, 648.98 examples/s]
Map:  24%|██▍       | 27799/114105 [00:37<01:51, 772.13 examples/s]
Map:  24%|██▎       | 26964/114105 [00:37<01:54, 763.92 examples/s]
Map:  25%|██▍       | 28000/114105 [00:38<02:25, 592.27 examples/s]
Map:  26%|██▌       | 29264/114105 [00:39<02:07, 667.68 examples/s]
Map:  24%|██▍       | 27881/114105 [00:37<01:50, 782.72 examples/s]
Map:  25%|██▍       | 28077/114105 [00:38<02:16, 628.54 examples/s]
Map:  26%|██▌       | 29345/114105 [00:39<02:00, 702.18 examples/s]
Map:  25%|██▍       | 28157/114105 [00:38<02:08, 667.54 examples/s]
Map:  24%|██▎       | 27084/114105 [00:37<02:17, 634.59 examples/s]
Map:  26%|██▌       | 29422/114105 [00:39<01:57, 718.04 examples/s]
Map:  25%|██▍       | 28000/114105 [00:38<02:19, 619.10 examples/s]
Map:  25%|██▍       | 28233/114105 [00:38<02:04, 690.37 examples/s]
Map:  24%|██▍       | 27166/114105 [00:38<02:09, 670.21 examples/s]
Map:  26%|██▌       | 29497/114105 [00:39<01:56, 726.27 examples/s]
Map:  25%|██▍       | 28083/114105 [00:38<02:10, 660.71 examples/s]
Map:  25%|██▍       | 28314/114105 [00:38<01:58, 721.45 examples/s]
Map:  24%|██▍       | 27250/114105 [00:38<02:02, 707.01 examples/s]
Map:  26%|██▌       | 29610/114105 [00:39<01:55, 731.42 examples/s]
Map:  25%|██▍       | 28167/114105 [00:38<02:02, 700.12 examples/s]
Map:  24%|██▍       | 27336/114105 [00:38<01:57, 741.01 examples/s]
Map:  25%|██▍       | 28427/114105 [00:38<01:57, 730.62 examples/s]
Map:  26%|██▌       | 29687/114105 [00:39<01:53, 740.96 examples/s]
Map:  25%|██▍       | 28247/114105 [00:38<01:59, 721.49 examples/s]
Map:  24%|██▍       | 27418/114105 [00:38<01:54, 757.49 examples/s]
Map:  25%|██▍       | 28507/114105 [00:38<01:54, 744.53 examples/s]
Map:  26%|██▌       | 29764/114105 [00:39<01:52, 747.64 examples/s]
Map:  25%|██▍       | 28329/114105 [00:38<01:54, 746.02 examples/s]
Map:  24%|██▍       | 27502/114105 [00:38<01:51, 775.51 examples/s]
Map:  25%|██▌       | 28588/114105 [00:38<01:52, 758.37 examples/s]
Map:  26%|██▌       | 29842/114105 [00:39<01:51, 756.03 examples/s]
Map:  25%|██▍       | 28413/114105 [00:38<01:51, 768.73 examples/s]
Map:  24%|██▍       | 27582/114105 [00:38<01:50, 780.98 examples/s]
Map:  25%|██▌       | 28666/114105 [00:38<01:52, 759.64 examples/s]
Map:  26%|██▌       | 29919/114105 [00:39<01:51, 757.30 examples/s]
Map:  25%|██▍       | 28501/114105 [00:38<01:47, 795.86 examples/s]
Map:  24%|██▍       | 27666/114105 [00:38<01:48, 794.05 examples/s]
Map:  25%|██▌       | 28747/114105 [00:39<01:50, 771.00 examples/s]
Map:  24%|██▍       | 27748/114105 [00:38<01:48, 795.17 examples/s]
Map:  25%|██▌       | 28619/114105 [00:38<01:48, 791.18 examples/s]
Map:  25%|██▌       | 28826/114105 [00:39<01:50, 774.46 examples/s]
Map:  26%|██▋       | 30000/114105 [00:40<02:26, 572.39 examples/s]
Map:  24%|██▍       | 27831/114105 [00:38<01:47, 801.14 examples/s]
Map:  25%|██▌       | 28727/114105 [00:39<01:52, 761.44 examples/s]
Map:  25%|██▌       | 28931/114105 [00:39<01:54, 743.43 examples/s]
Map:  26%|██▋       | 30104/114105 [00:40<02:17, 609.31 examples/s]
Map:  24%|██▍       | 27948/114105 [00:38<01:49, 790.02 examples/s]
Map:  25%|██▌       | 28805/114105 [00:39<01:51, 765.15 examples/s]
Map:  26%|██▋       | 30181/114105 [00:40<02:10, 643.22 examples/s]
Map:  25%|██▌       | 28892/114105 [00:39<01:47, 790.11 examples/s]
Map:  27%|██▋       | 30256/114105 [00:40<02:05, 668.33 examples/s]
Map:  25%|██▌       | 29038/114105 [00:39<02:20, 603.46 examples/s]
Map:  25%|██▍       | 28044/114105 [00:39<02:15, 636.13 examples/s]
Map:  25%|██▌       | 28977/114105 [00:39<01:45, 803.64 examples/s]
Map:  27%|██▋       | 30338/114105 [00:40<01:58, 706.43 examples/s]
Map:  26%|██▌       | 29118/114105 [00:39<02:12, 643.19 examples/s]
Map:  25%|██▍       | 28128/114105 [00:39<02:06, 680.38 examples/s]
Map:  27%|██▋       | 30416/114105 [00:40<01:55, 722.41 examples/s]
Map:  26%|██▌       | 29200/114105 [00:39<02:04, 682.07 examples/s]
Map:  25%|██▍       | 28214/114105 [00:39<01:59, 721.22 examples/s]
Map:  27%|██▋       | 30492/114105 [00:40<01:54, 729.22 examples/s]
Map:  25%|██▌       | 29077/114105 [00:39<02:18, 615.19 examples/s]
Map:  26%|██▌       | 29278/114105 [00:39<02:00, 703.83 examples/s]
Map:  25%|██▍       | 28297/114105 [00:39<01:55, 744.41 examples/s]
Map:  27%|██▋       | 30568/114105 [00:40<01:54, 731.78 examples/s]
Map:  26%|██▌       | 29163/114105 [00:39<02:07, 666.78 examples/s]
Map:  26%|██▌       | 29356/114105 [00:39<01:57, 722.75 examples/s]
Map:  25%|██▍       | 28381/114105 [00:39<01:51, 767.31 examples/s]
Map:  26%|██▌       | 29240/114105 [00:39<02:02, 690.62 examples/s]
Map:  26%|██▌       | 29433/114105 [00:40<01:55, 732.90 examples/s]
Map:  27%|██▋       | 30680/114105 [00:41<01:53, 734.90 examples/s]
Map:  25%|██▍       | 28497/114105 [00:39<01:51, 765.58 examples/s]
Map:  26%|██▌       | 29321/114105 [00:39<01:58, 716.84 examples/s]
Map:  26%|██▌       | 29509/114105 [00:40<01:54, 736.93 examples/s]
Map:  25%|██▌       | 28582/114105 [00:39<01:49, 783.29 examples/s]
Map:  27%|██▋       | 30793/114105 [00:41<01:53, 737.08 examples/s]
Map:  26%|██▌       | 29408/114105 [00:40<01:52, 754.27 examples/s]
Map:  26%|██▌       | 29586/114105 [00:40<01:53, 742.75 examples/s]
Map:  25%|██▌       | 28663/114105 [00:39<01:48, 788.65 examples/s]
Map:  26%|██▌       | 29493/114105 [00:40<01:49, 774.59 examples/s]
Map:  26%|██▌       | 29663/114105 [00:40<01:53, 747.27 examples/s]
Map:  27%|██▋       | 30898/114105 [00:41<01:55, 718.25 examples/s]
Map:  25%|██▌       | 28748/114105 [00:40<01:46, 801.94 examples/s]
Map:  26%|██▌       | 29577/114105 [00:40<01:46, 790.29 examples/s]
Map:  26%|██▌       | 29741/114105 [00:40<01:52, 753.10 examples/s]
Map:  25%|██▌       | 28864/114105 [00:40<01:48, 786.04 examples/s]
Map:  26%|██▌       | 29688/114105 [00:40<01:49, 769.74 examples/s]
Map:  26%|██▌       | 29846/114105 [00:40<01:55, 731.48 examples/s]
Map:  27%|██▋       | 31000/114105 [00:41<02:26, 566.58 examples/s]
Map:  25%|██▌       | 28949/114105 [00:40<01:46, 799.78 examples/s]
Map:  26%|██▌       | 29767/114105 [00:40<01:49, 773.02 examples/s]
Map:  26%|██▌       | 29923/114105 [00:40<01:53, 738.91 examples/s]
Map:  27%|██▋       | 31079/114105 [00:41<02:16, 608.93 examples/s]
Map:  26%|██▌       | 29850/114105 [00:40<01:47, 785.44 examples/s]
Map:  27%|██▋       | 31159/114105 [00:41<02:07, 649.21 examples/s]
Map:  26%|██▌       | 29933/114105 [00:40<01:45, 794.83 examples/s]
Map:  25%|██▌       | 29043/114105 [00:40<02:13, 638.10 examples/s]
Map:  26%|██▋       | 30000/114105 [00:40<02:24, 580.86 examples/s]
Map:  27%|██▋       | 31238/114105 [00:41<02:01, 679.77 examples/s]
Map:  26%|██▌       | 29126/114105 [00:40<02:04, 680.57 examples/s]
Map:  26%|██▋       | 30078/114105 [00:41<02:14, 624.90 examples/s]
Map:  27%|██▋       | 31313/114105 [00:41<01:59, 693.22 examples/s]
Map:  26%|██▌       | 29214/114105 [00:40<01:56, 726.97 examples/s]
Map:  26%|██▋       | 30156/114105 [00:41<02:06, 662.30 examples/s]
Map:  26%|██▋       | 30042/114105 [00:40<02:13, 631.72 examples/s]
Map:  28%|██▊       | 31393/114105 [00:42<01:54, 719.26 examples/s]
Map:  26%|██▌       | 29298/114105 [00:40<01:52, 752.45 examples/s]
Map:  26%|██▋       | 30234/114105 [00:41<02:02, 686.40 examples/s]
Map:  26%|██▋       | 30125/114105 [00:41<02:04, 674.51 examples/s]
Map:  28%|██▊       | 31471/114105 [00:42<01:52, 731.91 examples/s]
Map:  26%|██▌       | 29382/114105 [00:40<01:49, 773.61 examples/s]
Map:  27%|██▋       | 30309/114105 [00:41<01:59, 702.82 examples/s]
Map:  26%|██▋       | 30207/114105 [00:41<01:58, 706.13 examples/s]
Map:  28%|██▊       | 31549/114105 [00:42<01:51, 742.70 examples/s]
Map:  26%|██▌       | 29467/114105 [00:41<01:47, 790.25 examples/s]
Map:  27%|██▋       | 30388/114105 [00:41<01:55, 723.43 examples/s]
Map:  27%|██▋       | 30292/114105 [00:41<01:53, 740.88 examples/s]
Map:  28%|██▊       | 31627/114105 [00:42<01:50, 745.69 examples/s]
Map:  27%|██▋       | 30469/114105 [00:41<01:52, 744.63 examples/s]
Map:  27%|██▋       | 30374/114105 [00:41<01:50, 757.26 examples/s]
Map:  26%|██▌       | 29588/114105 [00:41<01:46, 792.26 examples/s]
Map:  26%|██▌       | 29670/114105 [00:41<01:45, 797.49 examples/s]
Map:  27%|██▋       | 30580/114105 [00:41<01:53, 735.32 examples/s]
Map:  28%|██▊       | 31731/114105 [00:42<02:13, 618.73 examples/s]
Map:  27%|██▋       | 30456/114105 [00:41<02:03, 677.40 examples/s]
Map:  28%|██▊       | 31803/114105 [00:42<02:08, 640.92 examples/s]
Map:  27%|██▋       | 30528/114105 [00:41<02:01, 686.67 examples/s]
Map:  26%|██▌       | 29781/114105 [00:41<01:49, 773.25 examples/s]
Map:  27%|██▋       | 30684/114105 [00:41<01:56, 718.71 examples/s]
Map:  27%|██▋       | 30607/114105 [00:41<01:57, 711.96 examples/s]
Map:  26%|██▌       | 29867/114105 [00:41<01:46, 793.15 examples/s]
Map:  27%|██▋       | 30761/114105 [00:41<01:54, 729.34 examples/s]
Map:  28%|██▊       | 31881/114105 [00:42<02:30, 546.43 examples/s]
Map:  27%|██▋       | 30692/114105 [00:41<01:51, 746.98 examples/s]
Map:  26%|██▌       | 29952/114105 [00:41<01:44, 807.22 examples/s]
Map:  27%|██▋       | 30837/114105 [00:42<01:53, 734.02 examples/s]
Map:  27%|██▋       | 30771/114105 [00:41<01:50, 755.76 examples/s]
Map:  27%|██▋       | 30914/114105 [00:42<01:52, 741.25 examples/s]
Map:  28%|██▊       | 31941/114105 [00:43<02:44, 500.88 examples/s]
Map:  27%|██▋       | 30855/114105 [00:42<01:47, 775.83 examples/s]
Map:  26%|██▋       | 30044/114105 [00:41<02:11, 639.87 examples/s]
Map:  27%|██▋       | 30996/114105 [00:42<01:49, 758.92 examples/s]
Map:  27%|██▋       | 30935/114105 [00:42<01:46, 779.18 examples/s]
Map:  28%|██▊       | 32000/114105 [00:43<03:07, 438.00 examples/s]
Map:  26%|██▋       | 30127/114105 [00:41<02:02, 683.08 examples/s]
Map:  28%|██▊       | 32082/114105 [00:43<02:38, 517.59 examples/s]
Map:  26%|██▋       | 30210/114105 [00:42<01:57, 716.37 examples/s]
Map:  27%|██▋       | 31076/114105 [00:42<02:21, 587.01 examples/s]
Map:  28%|██▊       | 32160/114105 [00:43<02:22, 575.18 examples/s]
Map:  27%|██▋       | 30292/114105 [00:42<01:53, 741.01 examples/s]
Map:  27%|██▋       | 31155/114105 [00:42<02:11, 632.21 examples/s]
Map:  27%|██▋       | 31040/114105 [00:42<02:15, 613.05 examples/s]
Map:  28%|██▊       | 32242/114105 [00:43<02:09, 634.10 examples/s]
Map:  27%|██▋       | 30374/114105 [00:42<01:50, 758.40 examples/s]
Map:  27%|██▋       | 31232/114105 [00:42<02:04, 664.35 examples/s]
Map:  27%|██▋       | 31123/114105 [00:42<02:05, 659.59 examples/s]
Map:  28%|██▊       | 32322/114105 [00:43<02:01, 674.99 examples/s]
Map:  27%|██▋       | 30461/114105 [00:42<01:46, 787.34 examples/s]
Map:  27%|██▋       | 31310/114105 [00:42<01:59, 690.09 examples/s]
Map:  27%|██▋       | 31201/114105 [00:42<02:00, 686.20 examples/s]
Map:  28%|██▊       | 32400/114105 [00:43<01:56, 700.20 examples/s]
Map:  27%|██▋       | 30545/114105 [00:42<01:44, 797.80 examples/s]
Map:  28%|██▊       | 31386/114105 [00:42<01:56, 707.52 examples/s]
Map:  27%|██▋       | 31282/114105 [00:42<01:55, 715.53 examples/s]
Map:  28%|██▊       | 32484/114105 [00:43<01:50, 738.08 examples/s]
Map:  28%|██▊       | 31465/114105 [00:42<01:53, 727.40 examples/s]
Map:  27%|██▋       | 31366/114105 [00:42<01:50, 747.49 examples/s]
Map:  27%|██▋       | 30666/114105 [00:42<01:44, 797.26 examples/s]
Map:  28%|██▊       | 31453/114105 [00:42<01:45, 780.00 examples/s]
Map:  29%|██▊       | 32594/114105 [00:44<01:51, 731.36 examples/s]
Map:  28%|██▊       | 31569/114105 [00:43<01:55, 711.64 examples/s]
Map:  27%|██▋       | 30781/114105 [00:42<01:46, 783.46 examples/s]
Map:  28%|██▊       | 31536/114105 [00:42<01:44, 789.78 examples/s]
Map:  29%|██▊       | 32677/114105 [00:44<01:48, 753.53 examples/s]
Map:  28%|██▊       | 31648/114105 [00:43<01:52, 730.54 examples/s]
Map:  27%|██▋       | 30863/114105 [00:42<01:45, 787.65 examples/s]
Map:  28%|██▊       | 31617/114105 [00:43<01:44, 792.89 examples/s]
Map:  29%|██▊       | 32755/114105 [00:44<01:47, 759.96 examples/s]
Map:  28%|██▊       | 31732/114105 [00:43<01:48, 759.72 examples/s]
Map:  27%|██▋       | 30949/114105 [00:42<01:43, 803.70 examples/s]
Map:  28%|██▊       | 31702/114105 [00:43<01:42, 805.64 examples/s]
Map:  29%|██▉       | 32835/114105 [00:44<01:45, 770.12 examples/s]
Map:  28%|██▊       | 31815/114105 [00:43<01:46, 775.79 examples/s]
Map:  28%|██▊       | 31786/114105 [00:43<01:41, 809.76 examples/s]
Map:  28%|██▊       | 31897/114105 [00:43<01:44, 785.61 examples/s]
Map:  29%|██▉       | 32951/114105 [00:44<01:45, 768.92 examples/s]
Map:  28%|██▊       | 31869/114105 [00:43<01:41, 812.97 examples/s]
Map:  27%|██▋       | 31042/114105 [00:43<02:12, 627.18 examples/s]
Map:  28%|██▊       | 31983/114105 [00:43<01:42, 803.86 examples/s]
Map:  27%|██▋       | 31128/114105 [00:43<02:02, 676.96 examples/s]
Map:  28%|██▊       | 31992/114105 [00:43<01:41, 810.36 examples/s]
Map:  29%|██▉       | 33039/114105 [00:44<02:14, 602.93 examples/s]
Map:  27%|██▋       | 31209/114105 [00:43<01:57, 706.95 examples/s]
Map:  28%|██▊       | 32082/114105 [00:43<02:09, 633.69 examples/s]
Map:  29%|██▉       | 33120/114105 [00:44<02:05, 646.27 examples/s]
Map:  27%|██▋       | 31290/114105 [00:43<01:53, 732.29 examples/s]
Map:  28%|██▊       | 32162/114105 [00:43<02:02, 670.15 examples/s]
Map:  28%|██▊       | 32083/114105 [00:43<02:10, 630.01 examples/s]
Map:  29%|██▉       | 33201/114105 [00:44<01:58, 684.02 examples/s]
Map:  27%|██▋       | 31369/114105 [00:43<01:51, 745.29 examples/s]
Map:  28%|██▊       | 32241/114105 [00:44<01:57, 698.58 examples/s]
Map:  28%|██▊       | 32164/114105 [00:43<02:02, 669.38 examples/s]
Map:  29%|██▉       | 33281/114105 [00:44<01:53, 711.45 examples/s]
Map:  28%|██▊       | 31450/114105 [00:43<01:48, 760.90 examples/s]
Map:  28%|██▊       | 32322/114105 [00:44<01:52, 726.91 examples/s]
Map:  28%|██▊       | 32247/114105 [00:43<01:55, 706.23 examples/s]
Map:  29%|██▉       | 33367/114105 [00:45<01:48, 745.96 examples/s]
Map:  28%|██▊       | 31533/114105 [00:43<01:46, 777.98 examples/s]
Map:  28%|██▊       | 32400/114105 [00:44<01:50, 739.29 examples/s]
Map:  28%|██▊       | 32332/114105 [00:44<01:50, 741.19 examples/s]
Map:  29%|██▉       | 33469/114105 [00:45<01:51, 720.48 examples/s]
Map:  28%|██▊       | 31644/114105 [00:43<01:48, 758.16 examples/s]
Map:  28%|██▊       | 32415/114105 [00:44<01:47, 761.75 examples/s]
Map:  28%|██▊       | 32506/114105 [00:44<01:52, 722.31 examples/s]
Map:  28%|██▊       | 32498/114105 [00:44<01:45, 776.87 examples/s]
Map:  29%|██▉       | 33577/114105 [00:45<01:52, 716.76 examples/s]
Map:  28%|██▊       | 31752/114105 [00:44<01:51, 740.00 examples/s]
Map:  29%|██▊       | 32581/114105 [00:44<01:52, 726.60 examples/s]
Map:  30%|██▉       | 33661/114105 [00:45<01:47, 745.70 examples/s]
Map:  28%|██▊       | 31838/114105 [00:44<01:47, 763.98 examples/s]
Map:  29%|██▊       | 32662/114105 [00:44<01:49, 745.41 examples/s]
Map:  29%|██▊       | 32613/114105 [00:44<01:46, 768.14 examples/s]
Map:  30%|██▉       | 33747/114105 [00:45<01:43, 773.52 examples/s]
Map:  28%|██▊       | 31918/114105 [00:44<01:46, 771.88 examples/s]
Map:  29%|██▊       | 32740/114105 [00:44<01:48, 752.06 examples/s]
Map:  29%|██▊       | 32697/114105 [00:44<01:43, 785.87 examples/s]
Map:  30%|██▉       | 33827/114105 [00:45<01:43, 777.65 examples/s]
Map:  29%|██▉       | 32818/114105 [00:44<01:47, 756.82 examples/s]
Map:  29%|██▉       | 32820/114105 [00:44<01:42, 794.53 examples/s]
Map:  30%|██▉       | 33909/114105 [00:45<01:42, 785.23 examples/s]
Map:  29%|██▉       | 32898/114105 [00:44<01:45, 767.74 examples/s]
Map:  28%|██▊       | 32000/114105 [00:44<02:15, 606.65 examples/s]
Map:  30%|██▉       | 33995/114105 [00:45<01:40, 799.02 examples/s]
Map:  29%|██▉       | 32976/114105 [00:44<01:45, 769.20 examples/s]
Map:  28%|██▊       | 32081/114105 [00:44<02:05, 652.69 examples/s]
Map:  29%|██▉       | 32942/114105 [00:44<01:42, 795.31 examples/s]
Map:  28%|██▊       | 32164/114105 [00:44<01:58, 692.87 examples/s]
Map:  30%|██▉       | 34083/114105 [00:46<02:08, 622.29 examples/s]
Map:  28%|██▊       | 32247/114105 [00:44<01:52, 727.31 examples/s]
Map:  29%|██▉       | 33080/114105 [00:45<02:11, 617.54 examples/s]
Map:  29%|██▉       | 33038/114105 [00:45<02:07, 637.97 examples/s]
Map:  30%|██▉       | 34164/114105 [00:46<02:00, 662.51 examples/s]
Map:  28%|██▊       | 32335/114105 [00:44<01:47, 763.69 examples/s]
Map:  29%|██▉       | 33166/114105 [00:45<02:00, 671.64 examples/s]
Map:  29%|██▉       | 33120/114105 [00:45<02:00, 674.40 examples/s]
Map:  30%|███       | 34244/114105 [00:46<01:54, 694.89 examples/s]
Map:  28%|██▊       | 32417/114105 [00:45<01:45, 773.67 examples/s]
Map:  29%|██▉       | 33248/114105 [00:45<01:54, 705.37 examples/s]
Map:  29%|██▉       | 33205/114105 [00:45<01:53, 712.97 examples/s]
Map:  30%|███       | 34330/114105 [00:46<01:48, 737.56 examples/s]
Map:  28%|██▊       | 32497/114105 [00:45<01:44, 780.41 examples/s]
Map:  29%|██▉       | 33331/114105 [00:45<01:49, 736.67 examples/s]
Map:  29%|██▉       | 33288/114105 [00:45<01:49, 740.64 examples/s]
Map:  30%|███       | 34414/114105 [00:46<01:44, 763.48 examples/s]
Map:  29%|██▊       | 32580/114105 [00:45<01:42, 792.85 examples/s]
Map:  29%|██▉       | 33447/114105 [00:45<01:48, 746.05 examples/s]
Map:  29%|██▉       | 33404/114105 [00:45<01:47, 748.90 examples/s]
Map:  30%|███       | 34531/114105 [00:46<01:44, 763.00 examples/s]
Map:  29%|██▊       | 32693/114105 [00:45<01:45, 774.03 examples/s]
Map:  29%|██▉       | 33529/114105 [00:45<01:45, 762.47 examples/s]
Map:  29%|██▉       | 33485/114105 [00:45<01:45, 762.32 examples/s]
Map:  30%|███       | 34617/114105 [00:46<01:41, 784.89 examples/s]
Map:  29%|██▊       | 32775/114105 [00:45<01:43, 782.67 examples/s]
Map:  29%|██▉       | 33613/114105 [00:45<01:42, 781.82 examples/s]
Map:  29%|██▉       | 33571/114105 [00:45<01:42, 783.22 examples/s]
Map:  30%|███       | 34701/114105 [00:46<01:39, 798.00 examples/s]
Map:  29%|██▉       | 32856/114105 [00:45<01:42, 788.93 examples/s]
Map:  30%|██▉       | 33698/114105 [00:45<01:40, 796.23 examples/s]
Map:  29%|██▉       | 33659/114105 [00:45<01:39, 805.54 examples/s]
Map:  30%|██▉       | 33780/114105 [00:46<01:41, 795.15 examples/s]
Map:  30%|██▉       | 33743/114105 [00:45<01:38, 812.10 examples/s]
Map:  31%|███       | 34823/114105 [00:47<01:39, 799.38 examples/s]
Map:  29%|██▉       | 32976/114105 [00:45<01:42, 789.30 examples/s]
Map:  30%|██▉       | 33866/114105 [00:46<01:38, 811.33 examples/s]
Map:  31%|███       | 34911/114105 [00:47<01:36, 817.81 examples/s]
Map:  30%|██▉       | 33871/114105 [00:46<01:37, 822.37 examples/s]
Map:  31%|███       | 34996/114105 [00:47<01:36, 823.20 examples/s]
Map:  30%|██▉       | 33991/114105 [00:46<01:38, 814.96 examples/s]
Map:  29%|██▉       | 33086/114105 [00:45<02:06, 641.84 examples/s]
Map:  30%|██▉       | 33997/114105 [00:46<01:37, 823.54 examples/s]
Map:  29%|██▉       | 33167/114105 [00:46<01:59, 674.88 examples/s]
Map:  31%|███       | 35080/114105 [00:47<02:04, 634.65 examples/s]
Map:  30%|██▉       | 34081/114105 [00:46<02:03, 648.56 examples/s]
Map:  29%|██▉       | 33252/114105 [00:46<01:53, 714.80 examples/s]
Map:  30%|██▉       | 34085/114105 [00:46<02:03, 647.14 examples/s]
Map:  31%|███       | 35162/114105 [00:47<01:56, 675.17 examples/s]
Map:  29%|██▉       | 33334/114105 [00:46<01:49, 737.82 examples/s]
Map:  30%|██▉       | 34170/114105 [00:46<02:07, 627.92 examples/s]
Map:  30%|██▉       | 34170/114105 [00:46<01:55, 689.83 examples/s]
Map:  31%|███       | 35243/114105 [00:47<01:51, 706.42 examples/s]
Map:  29%|██▉       | 33418/114105 [00:46<01:46, 760.76 examples/s]
Map:  30%|███       | 34252/114105 [00:46<01:59, 667.89 examples/s]
Map:  30%|███       | 34250/114105 [00:46<01:51, 713.80 examples/s]
Map:  31%|███       | 35323/114105 [00:47<01:48, 727.99 examples/s]
Map:  29%|██▉       | 33503/114105 [00:46<01:43, 777.56 examples/s]
Map:  30%|███       | 34328/114105 [00:46<01:56, 686.80 examples/s]
Map:  30%|███       | 34333/114105 [00:46<01:48, 737.84 examples/s]
Map:  31%|███       | 35401/114105 [00:47<01:46, 741.00 examples/s]
Map:  29%|██▉       | 33585/114105 [00:46<01:42, 787.24 examples/s]
Map:  30%|███       | 34404/114105 [00:47<01:53, 703.97 examples/s]
Map:  30%|███       | 34420/114105 [00:46<01:43, 770.71 examples/s]
Map:  31%|███       | 35485/114105 [00:47<01:42, 765.70 examples/s]
Map:  30%|██▉       | 33669/114105 [00:46<01:40, 800.58 examples/s]
Map:  30%|███       | 34485/114105 [00:47<01:49, 727.46 examples/s]
Map:  30%|███       | 34509/114105 [00:46<01:39, 801.13 examples/s]
Map:  31%|███       | 35567/114105 [00:48<01:40, 778.75 examples/s]
Map:  30%|██▉       | 33751/114105 [00:46<01:40, 802.91 examples/s]
Map:  30%|███       | 34569/114105 [00:47<01:45, 755.07 examples/s]
Map:  31%|███       | 35647/114105 [00:48<01:40, 781.05 examples/s]
Map:  30%|██▉       | 33834/114105 [00:46<01:39, 809.71 examples/s]
Map:  30%|███       | 34632/114105 [00:47<01:38, 804.37 examples/s]
Map:  30%|███       | 34652/114105 [00:47<01:42, 773.13 examples/s]
Map:  31%|███▏      | 35729/114105 [00:48<01:38, 792.14 examples/s]
Map:  30%|██▉       | 33917/114105 [00:46<01:38, 812.34 examples/s]
Map:  30%|███       | 34718/114105 [00:47<01:37, 815.98 examples/s]
Map:  31%|███▏      | 35809/114105 [00:48<01:38, 791.35 examples/s]
Map:  30%|███       | 34769/114105 [00:47<01:42, 773.38 examples/s]
Map:  31%|███       | 34804/114105 [00:47<01:36, 824.86 examples/s]
Map:  31%|███▏      | 35889/114105 [00:48<01:38, 793.09 examples/s]
Map:  31%|███       | 34849/114105 [00:47<01:41, 777.93 examples/s]
Map:  30%|██▉       | 34000/114105 [00:47<02:08, 625.80 examples/s]
Map:  31%|███       | 34925/114105 [00:47<01:37, 813.74 examples/s]
Map:  32%|███▏      | 35974/114105 [00:48<01:36, 806.09 examples/s]
Map:  30%|██▉       | 34081/114105 [00:47<01:59, 668.67 examples/s]
Map:  31%|███       | 34964/114105 [00:47<01:42, 770.12 examples/s]
Map:  30%|██▉       | 34168/114105 [00:47<01:51, 718.54 examples/s]
Map:  31%|███       | 35041/114105 [00:47<01:58, 664.50 examples/s]
Map:  30%|███       | 34246/114105 [00:47<01:48, 733.68 examples/s]
Map:  32%|███▏      | 36079/114105 [00:48<02:06, 618.04 examples/s]
Map:  31%|███       | 35074/114105 [00:47<02:07, 619.98 examples/s]
Map:  31%|███       | 35123/114105 [00:47<01:53, 695.37 examples/s]
Map:  30%|███       | 34330/114105 [00:47<01:45, 759.26 examples/s]
Map:  32%|███▏      | 36161/114105 [00:48<01:57, 662.18 examples/s]
Map:  31%|███       | 35151/114105 [00:48<02:01, 650.05 examples/s]
Map:  31%|███       | 35203/114105 [00:47<01:49, 718.35 examples/s]
Map:  30%|███       | 34411/114105 [00:47<01:43, 772.24 examples/s]
Map:  32%|███▏      | 36243/114105 [00:49<01:51, 699.66 examples/s]
Map:  31%|███       | 35283/114105 [00:47<01:46, 737.16 examples/s]
Map:  30%|███       | 34494/114105 [00:47<01:41, 786.95 examples/s]
Map:  32%|███▏      | 36328/114105 [00:49<01:45, 734.80 examples/s]
Map:  31%|███       | 35256/114105 [00:48<01:58, 662.77 examples/s]
Map:  30%|███       | 34575/114105 [00:47<01:40, 790.44 examples/s]
Map:  31%|███       | 35398/114105 [00:48<01:45, 743.85 examples/s]
Map:  31%|███       | 35340/114105 [00:48<01:52, 698.94 examples/s]
Map:  32%|███▏      | 36435/114105 [00:49<01:47, 721.83 examples/s]
Map:  30%|███       | 34658/114105 [00:48<01:39, 798.63 examples/s]
Map:  31%|███       | 35478/114105 [00:48<01:44, 753.09 examples/s]
Map:  31%|███       | 35418/114105 [00:48<01:49, 715.64 examples/s]
Map:  32%|███▏      | 36519/114105 [00:49<01:43, 748.94 examples/s]
Map:  30%|███       | 34744/114105 [00:48<01:37, 812.65 examples/s]
Map:  31%|███       | 35562/114105 [00:48<01:41, 774.78 examples/s]
Map:  31%|███       | 35500/114105 [00:48<01:46, 738.63 examples/s]
Map:  32%|███▏      | 36602/114105 [00:49<01:40, 767.59 examples/s]
Map:  31%|███       | 34829/114105 [00:48<01:36, 820.34 examples/s]
Map:  31%|███       | 35650/114105 [00:48<01:38, 800.36 examples/s]
Map:  31%|███       | 35577/114105 [00:48<01:45, 743.19 examples/s]
Map:  32%|███▏      | 36689/114105 [00:49<01:37, 794.10 examples/s]
Map:  31%|███▏      | 35732/114105 [00:48<01:37, 803.84 examples/s]
Map:  31%|███       | 35656/114105 [00:48<01:43, 755.06 examples/s]
Map:  31%|███       | 34951/114105 [00:48<01:37, 809.06 examples/s]
Map:  32%|███▏      | 36776/114105 [00:49<01:35, 811.05 examples/s]
Map:  31%|███▏      | 35816/114105 [00:48<01:36, 812.61 examples/s]
Map:  31%|███▏      | 35737/114105 [00:48<01:42, 766.64 examples/s]
Map:  32%|███▏      | 36862/114105 [00:49<01:34, 821.46 examples/s]
Map:  31%|███▏      | 35819/114105 [00:48<01:40, 779.77 examples/s]
Map:  32%|███▏      | 36947/114105 [00:49<01:33, 827.09 examples/s]
Map:  31%|███       | 35041/114105 [00:48<02:05, 631.31 examples/s]
Map:  31%|███▏      | 35939/114105 [00:48<01:36, 812.55 examples/s]
Map:  31%|███▏      | 35899/114105 [00:49<01:39, 782.48 examples/s]
Map:  31%|███       | 35124/114105 [00:48<01:57, 674.57 examples/s]
Map:  31%|███       | 35210/114105 [00:48<01:49, 718.27 examples/s]
Map:  32%|███▏      | 37033/114105 [00:50<02:03, 623.94 examples/s]
Map:  32%|███▏      | 36036/114105 [00:49<02:07, 613.08 examples/s]
Map:  31%|███       | 35288/114105 [00:48<01:47, 733.32 examples/s]
Map:  33%|███▎      | 37111/114105 [00:50<01:57, 656.40 examples/s]
Map:  32%|███▏      | 36000/114105 [00:49<02:11, 594.74 examples/s]
Map:  32%|███▏      | 36124/114105 [00:49<01:56, 669.06 examples/s]
Map:  31%|███       | 35374/114105 [00:48<01:43, 761.72 examples/s]
Map:  33%|███▎      | 37195/114105 [00:50<01:49, 700.48 examples/s]
Map:  32%|███▏      | 36079/114105 [00:49<02:02, 635.03 examples/s]
Map:  32%|███▏      | 36205/114105 [00:49<01:51, 699.31 examples/s]
Map:  31%|███       | 35458/114105 [00:49<01:40, 781.10 examples/s]
Map:  33%|███▎      | 37276/114105 [00:50<01:45, 727.12 examples/s]
Map:  32%|███▏      | 36158/114105 [00:49<01:56, 671.43 examples/s]
Map:  32%|███▏      | 36293/114105 [00:49<01:44, 742.89 examples/s]
Map:  31%|███       | 35540/114105 [00:49<01:39, 789.36 examples/s]
Map:  33%|███▎      | 37363/114105 [00:50<01:40, 763.04 examples/s]
Map:  32%|███▏      | 36239/114105 [00:49<01:50, 705.16 examples/s]
Map:  32%|███▏      | 36377/114105 [00:49<01:41, 763.36 examples/s]
Map:  31%|███       | 35622/114105 [00:49<01:38, 796.45 examples/s]
Map:  32%|███▏      | 36320/114105 [00:49<01:46, 729.44 examples/s]
Map:  33%|███▎      | 37485/114105 [00:50<01:38, 778.09 examples/s]
Map:  32%|███▏      | 36464/114105 [00:49<01:38, 787.01 examples/s]
Map:  31%|███▏      | 35703/114105 [00:49<01:38, 799.22 examples/s]
Map:  32%|███▏      | 36402/114105 [00:49<01:43, 751.49 examples/s]
Map:  33%|███▎      | 37571/114105 [00:50<01:36, 795.84 examples/s]
Map:  32%|███▏      | 36546/114105 [00:49<01:37, 793.95 examples/s]
Map:  31%|███▏      | 35788/114105 [00:49<01:36, 810.83 examples/s]
Map:  32%|███▏      | 36482/114105 [00:49<01:41, 762.59 examples/s]
Map:  32%|███▏      | 36634/114105 [00:49<01:35, 812.41 examples/s]
Map:  33%|███▎      | 37691/114105 [00:50<01:36, 793.11 examples/s]
Map:  32%|███▏      | 36568/114105 [00:49<01:38, 787.80 examples/s]
Map:  31%|███▏      | 35908/114105 [00:49<01:37, 804.64 examples/s]
Map:  32%|███▏      | 36756/114105 [00:49<01:35, 809.79 examples/s]
Map:  32%|███▏      | 36651/114105 [00:50<01:37, 795.55 examples/s]
Map:  33%|███▎      | 37812/114105 [00:51<01:35, 794.76 examples/s]
Map:  32%|███▏      | 36845/114105 [00:50<01:33, 827.65 examples/s]
Map:  32%|███▏      | 36733/114105 [00:50<01:36, 797.83 examples/s]
Map:  33%|███▎      | 37894/114105 [00:51<01:35, 800.14 examples/s]
Map:  32%|███▏      | 36000/114105 [00:49<02:11, 593.83 examples/s]
Map:  32%|███▏      | 36817/114105 [00:50<01:35, 808.88 examples/s]
Map:  33%|███▎      | 37979/114105 [00:51<01:34, 809.40 examples/s]
Map:  32%|███▏      | 36972/114105 [00:50<01:32, 830.18 examples/s]
Map:  32%|███▏      | 36070/114105 [00:50<02:06, 615.47 examples/s]
Map:  32%|███▏      | 36899/114105 [00:50<01:35, 809.43 examples/s]
Map:  32%|███▏      | 36144/114105 [00:50<02:01, 642.43 examples/s]
Map:  32%|███▏      | 36981/114105 [00:50<01:35, 807.58 examples/s]
Map:  32%|███▏      | 36224/114105 [00:50<01:54, 680.13 examples/s]
Map:  33%|███▎      | 38084/114105 [00:51<02:00, 628.41 examples/s]
Map:  32%|███▏      | 37083/114105 [00:50<01:59, 644.56 examples/s]
Map:  33%|███▎      | 38166/114105 [00:51<01:53, 668.25 examples/s]
Map:  32%|███▏      | 36307/114105 [00:50<01:48, 716.45 examples/s]
Map:  33%|███▎      | 37168/114105 [00:50<01:52, 685.02 examples/s]
Map:  32%|███▏      | 37078/114105 [00:50<02:02, 626.70 examples/s]
Map:  34%|███▎      | 38246/114105 [00:51<01:48, 697.44 examples/s]
Map:  32%|███▏      | 36385/114105 [00:50<01:46, 732.66 examples/s]
Map:  33%|███▎      | 37249/114105 [00:50<01:48, 710.79 examples/s]
Map:  33%|███▎      | 37155/114105 [00:50<01:56, 659.62 examples/s]
Map:  34%|███▎      | 38331/114105 [00:51<01:43, 733.35 examples/s]
Map:  32%|███▏      | 36468/114105 [00:50<01:42, 754.33 examples/s]
Map:  33%|███▎      | 37333/114105 [00:50<01:43, 738.27 examples/s]
Map:  33%|███▎      | 37238/114105 [00:50<01:49, 699.96 examples/s]
Map:  34%|███▎      | 38415/114105 [00:51<01:39, 758.18 examples/s]
Map:  32%|███▏      | 36547/114105 [00:50<01:42, 760.11 examples/s]
Map:  33%|███▎      | 37418/114105 [00:50<01:40, 762.19 examples/s]
Map:  33%|███▎      | 37320/114105 [00:51<01:45, 728.72 examples/s]
Map:  34%|███▎      | 38496/114105 [00:52<01:38, 770.75 examples/s]
Map:  32%|███▏      | 36631/114105 [00:50<01:39, 778.84 examples/s]
Map:  33%|███▎      | 37499/114105 [00:50<01:39, 770.99 examples/s]
Map:  33%|███▎      | 37408/114105 [00:51<01:40, 766.81 examples/s]
Map:  34%|███▍      | 38583/114105 [00:52<01:34, 796.64 examples/s]
Map:  32%|███▏      | 36714/114105 [00:50<01:37, 790.59 examples/s]
Map:  33%|███▎      | 37582/114105 [00:51<01:37, 785.10 examples/s]
Map:  33%|███▎      | 37489/114105 [00:51<01:38, 775.04 examples/s]
Map:  34%|███▍      | 38667/114105 [00:52<01:33, 807.90 examples/s]
Map:  32%|███▏      | 36794/114105 [00:50<01:38, 788.08 examples/s]
Map:  33%|███▎      | 37666/114105 [00:51<01:35, 799.31 examples/s]
Map:  33%|███▎      | 37571/114105 [00:51<01:37, 785.31 examples/s]
Map:  34%|███▍      | 38753/114105 [00:52<01:32, 818.52 examples/s]
Map:  32%|███▏      | 36876/114105 [00:51<01:37, 794.61 examples/s]
Map:  33%|███▎      | 37658/114105 [00:51<01:34, 804.77 examples/s]
Map:  33%|███▎      | 37785/114105 [00:51<01:36, 793.85 examples/s]
Map:  34%|███▍      | 38838/114105 [00:52<01:31, 824.68 examples/s]
Map:  32%|███▏      | 36956/114105 [00:51<01:37, 794.18 examples/s]
Map:  33%|███▎      | 37779/114105 [00:51<01:35, 802.39 examples/s]
Map:  34%|███▍      | 38925/114105 [00:52<01:30, 834.53 examples/s]
Map:  33%|███▎      | 37899/114105 [00:51<01:38, 777.40 examples/s]
Map:  32%|███▏      | 37036/114105 [00:51<02:12, 580.85 examples/s]
Map:  33%|███▎      | 37979/114105 [00:51<01:37, 780.19 examples/s]
Map:  33%|███▎      | 37898/114105 [00:51<01:35, 796.97 examples/s]
Map:  33%|███▎      | 37116/114105 [00:51<02:02, 627.85 examples/s]
Map:  33%|███▎      | 37979/114105 [00:51<01:35, 797.58 examples/s]
Map:  34%|███▍      | 39041/114105 [00:52<01:58, 635.82 examples/s]
Map:  33%|███▎      | 37199/114105 [00:51<01:53, 676.98 examples/s]
Map:  34%|███▍      | 39125/114105 [00:52<01:50, 680.28 examples/s]
Map:  33%|███▎      | 38083/114105 [00:51<02:00, 628.79 examples/s]
Map:  33%|███▎      | 37284/114105 [00:51<01:46, 721.48 examples/s]
Map:  34%|███▍      | 39207/114105 [00:52<01:45, 709.53 examples/s]
Map:  33%|███▎      | 38170/114105 [00:51<01:51, 679.95 examples/s]
Map:  33%|███▎      | 38080/114105 [00:52<01:59, 637.15 examples/s]
Map:  33%|███▎      | 37368/114105 [00:51<01:41, 752.38 examples/s]
Map:  34%|███▎      | 38254/114105 [00:51<01:46, 713.83 examples/s]
Map:  33%|███▎      | 38162/114105 [00:52<01:52, 674.58 examples/s]
Map:  34%|███▍      | 39318/114105 [00:53<01:44, 717.95 examples/s]
Map:  34%|███▎      | 38335/114105 [00:52<01:43, 734.28 examples/s]
Map:  34%|███▎      | 38241/114105 [00:52<01:48, 700.98 examples/s]
Map:  33%|███▎      | 37486/114105 [00:51<01:40, 760.34 examples/s]
Map:  35%|███▍      | 39401/114105 [00:53<01:40, 743.81 examples/s]
Map:  34%|███▎      | 38418/114105 [00:52<01:40, 755.61 examples/s]
Map:  34%|███▎      | 38325/114105 [00:52<01:43, 733.59 examples/s]
Map:  33%|███▎      | 37566/114105 [00:52<01:39, 769.08 examples/s]
Map:  35%|███▍      | 39484/114105 [00:53<01:37, 763.51 examples/s]
Map:  34%|███▎      | 38501/114105 [00:52<01:37, 774.80 examples/s]
Map:  34%|███▎      | 38409/114105 [00:52<01:39, 759.51 examples/s]
Map:  33%|███▎      | 37647/114105 [00:52<01:38, 778.83 examples/s]
Map:  35%|███▍      | 39565/114105 [00:53<01:36, 773.57 examples/s]
Map:  34%|███▍      | 38586/114105 [00:52<01:35, 793.29 examples/s]
Map:  34%|███▎      | 38498/114105 [00:52<01:35, 792.05 examples/s]
Map:  35%|███▍      | 39648/114105 [00:53<01:34, 784.69 examples/s]
Map:  33%|███▎      | 37762/114105 [00:52<01:38, 772.13 examples/s]
Map:  34%|███▍      | 38669/114105 [00:52<01:34, 801.60 examples/s]
Map:  35%|███▍      | 39728/114105 [00:53<01:35, 780.04 examples/s]
Map:  34%|███▍      | 38616/114105 [00:52<01:35, 787.02 examples/s]
Map:  33%|███▎      | 37844/114105 [00:52<01:37, 781.94 examples/s]
Map:  34%|███▍      | 38751/114105 [00:52<01:33, 805.19 examples/s]
Map:  35%|███▍      | 39812/114105 [00:53<01:33, 796.12 examples/s]
Map:  34%|███▍      | 38698/114105 [00:52<01:35, 791.67 examples/s]
Map:  33%|███▎      | 37932/114105 [00:52<01:34, 803.12 examples/s]
Map:  34%|███▍      | 38833/114105 [00:52<01:33, 804.29 examples/s]
Map:  34%|███▍      | 38783/114105 [00:52<01:33, 805.54 examples/s]
Map:  35%|███▍      | 39923/114105 [00:53<01:36, 770.67 examples/s]
Map:  34%|███▍      | 38949/114105 [00:52<01:35, 788.65 examples/s]
Map:  34%|███▍      | 38866/114105 [00:53<01:33, 808.93 examples/s]
Map:  33%|███▎      | 38037/114105 [00:52<02:06, 600.89 examples/s]
Map:  34%|███▍      | 38982/114105 [00:53<01:34, 792.13 examples/s]
Map:  33%|███▎      | 38119/114105 [00:52<01:57, 646.96 examples/s]
Map:  35%|███▌      | 40040/114105 [00:54<01:58, 624.31 examples/s]
Map:  34%|███▍      | 39039/114105 [00:53<02:02, 612.90 examples/s]
Map:  33%|███▎      | 38201/114105 [00:52<01:50, 687.23 examples/s]
Map:  35%|███▌      | 40124/114105 [00:54<01:50, 668.86 examples/s]
Map:  34%|███▍      | 39123/114105 [00:53<01:53, 661.35 examples/s]
Map:  34%|███▎      | 38278/114105 [00:53<01:47, 705.94 examples/s]
Map:  34%|███▍      | 39079/114105 [00:53<01:58, 630.55 examples/s]
Map:  35%|███▌      | 40208/114105 [00:54<01:44, 707.13 examples/s]
Map:  34%|███▍      | 39207/114105 [00:53<01:46, 700.40 examples/s]
Map:  34%|███▎      | 38357/114105 [00:53<01:44, 724.72 examples/s]
Map:  34%|███▍      | 39157/114105 [00:53<01:53, 661.06 examples/s]
Map:  35%|███▌      | 40290/114105 [00:54<01:40, 732.79 examples/s]
Map:  34%|███▍      | 39293/114105 [00:53<01:41, 737.43 examples/s]
Map:  34%|███▎      | 38438/114105 [00:53<01:41, 743.69 examples/s]
Map:  34%|███▍      | 39232/114105 [00:53<01:50, 679.14 examples/s]
Map:  35%|███▌      | 40371/114105 [00:54<01:38, 751.48 examples/s]
Map:  35%|███▍      | 39375/114105 [00:53<01:38, 757.13 examples/s]
Map:  34%|███▍      | 38516/114105 [00:53<01:40, 750.51 examples/s]
Map:  34%|███▍      | 39316/114105 [00:53<01:44, 716.42 examples/s]
Map:  35%|███▌      | 40453/114105 [00:54<01:35, 768.96 examples/s]
Map:  35%|███▍      | 39457/114105 [00:53<01:36, 771.93 examples/s]
Map:  34%|███▍      | 38597/114105 [00:53<01:39, 762.40 examples/s]
Map:  35%|███▍      | 39398/114105 [00:53<01:40, 740.11 examples/s]
Map:  36%|███▌      | 40533/114105 [00:54<01:35, 774.10 examples/s]
Map:  35%|███▍      | 39544/114105 [00:53<01:33, 794.72 examples/s]
Map:  34%|███▍      | 38682/114105 [00:53<01:36, 785.43 examples/s]
Map:  35%|███▍      | 39478/114105 [00:53<01:38, 753.81 examples/s]
Map:  36%|███▌      | 40616/114105 [00:54<01:33, 788.42 examples/s]
Map:  35%|███▍      | 39633/114105 [00:53<01:30, 819.40 examples/s]
Map:  35%|███▍      | 39561/114105 [00:54<01:36, 774.26 examples/s]
Map:  36%|███▌      | 40697/114105 [00:54<01:32, 791.56 examples/s]
Map:  34%|███▍      | 38798/114105 [00:53<01:37, 775.87 examples/s]
Map:  35%|███▍      | 39752/114105 [00:53<01:32, 808.10 examples/s]
Map:  35%|███▍      | 39642/114105 [00:54<01:35, 780.79 examples/s]
Map:  36%|███▌      | 40781/114105 [00:55<01:31, 802.90 examples/s]
Map:  34%|███▍      | 38881/114105 [00:53<01:35, 787.42 examples/s]
Map:  35%|███▍      | 39834/114105 [00:54<01:31, 808.58 examples/s]
Map:  35%|███▍      | 39723/114105 [00:54<01:34, 787.51 examples/s]
Map:  36%|███▌      | 40894/114105 [00:55<01:33, 779.18 examples/s]
Map:  34%|███▍      | 38990/114105 [00:53<01:38, 762.78 examples/s]
Map:  35%|███▍      | 39804/114105 [00:54<01:33, 792.43 examples/s]
Map:  35%|███▌      | 39945/114105 [00:54<01:35, 780.57 examples/s]
Map:  36%|███▌      | 40973/114105 [00:55<01:33, 779.68 examples/s]
Map:  35%|███▍      | 39885/114105 [00:54<01:33, 795.87 examples/s]
Map:  35%|███▌      | 39965/114105 [00:54<01:33, 794.82 examples/s]
Map:  34%|███▍      | 39083/114105 [00:54<02:03, 608.90 examples/s]
Map:  35%|███▌      | 40043/114105 [00:54<01:58, 627.21 examples/s]
Map:  36%|███▌      | 41087/114105 [00:55<01:55, 634.05 examples/s]
Map:  34%|███▍      | 39166/114105 [00:54<01:54, 655.05 examples/s]
Map:  35%|███▌      | 40127/114105 [00:54<01:50, 671.18 examples/s]
Map:  36%|███▌      | 41171/114105 [00:55<01:47, 678.35 examples/s]
Map:  34%|███▍      | 39248/114105 [00:54<01:48, 689.07 examples/s]
Map:  35%|███▌      | 40076/114105 [00:54<01:59, 621.94 examples/s]
Map:  35%|███▌      | 40208/114105 [00:54<01:45, 702.14 examples/s]
Map:  36%|███▌      | 41251/114105 [00:55<01:43, 705.92 examples/s]
Map:  34%|███▍      | 39333/114105 [00:54<01:43, 725.37 examples/s]
Map:  35%|███▌      | 40161/114105 [00:54<01:49, 672.42 examples/s]
Map:  35%|███▌      | 40294/114105 [00:54<01:39, 739.57 examples/s]
Map:  36%|███▌      | 41339/114105 [00:55<01:37, 745.73 examples/s]
Map:  35%|███▍      | 39412/114105 [00:54<01:41, 739.37 examples/s]
Map:  35%|███▌      | 40245/114105 [00:54<01:43, 712.11 examples/s]
Map:  35%|███▌      | 40372/114105 [00:54<01:38, 748.54 examples/s]
Map:  36%|███▋      | 41418/114105 [00:55<01:36, 755.94 examples/s]
Map:  35%|███▍      | 39501/114105 [00:54<01:36, 775.91 examples/s]
Map:  35%|███▌      | 40325/114105 [00:55<01:40, 732.03 examples/s]
Map:  35%|███▌      | 40454/114105 [00:54<01:36, 764.99 examples/s]
Map:  36%|███▋      | 41499/114105 [00:56<01:34, 769.46 examples/s]
Map:  35%|███▍      | 39587/114105 [00:54<01:33, 794.79 examples/s]
Map:  35%|███▌      | 40405/114105 [00:55<01:38, 746.68 examples/s]
Map:  36%|███▌      | 40535/114105 [00:55<01:34, 776.06 examples/s]
Map:  35%|███▌      | 40489/114105 [00:55<01:35, 769.92 examples/s]
Map:  36%|███▋      | 41619/114105 [00:56<01:33, 778.67 examples/s]
Map:  36%|███▌      | 40619/114105 [00:55<01:32, 790.49 examples/s]
Map:  35%|███▍      | 39712/114105 [00:54<01:32, 806.02 examples/s]
Map:  36%|███▌      | 40569/114105 [00:55<01:34, 776.86 examples/s]
Map:  37%|███▋      | 41703/114105 [00:56<01:31, 791.73 examples/s]
Map:  36%|███▌      | 40706/114105 [00:55<01:30, 810.00 examples/s]
Map:  35%|███▍      | 39798/114105 [00:55<01:31, 812.97 examples/s]
Map:  36%|███▌      | 40656/114105 [00:55<01:31, 800.72 examples/s]
Map:  37%|███▋      | 41818/114105 [00:56<01:32, 780.00 examples/s]
Map:  36%|███▌      | 40824/114105 [00:55<01:32, 796.06 examples/s]
Map:  35%|███▍      | 39917/114105 [00:55<01:32, 804.68 examples/s]
Map:  36%|███▌      | 40777/114105 [00:55<01:31, 798.29 examples/s]
Map:  37%|███▋      | 41901/114105 [00:56<01:31, 785.69 examples/s]
Map:  36%|███▌      | 40907/114105 [00:55<01:31, 801.40 examples/s]
Map:  36%|███▌      | 40862/114105 [00:55<01:30, 808.96 examples/s]
Map:  37%|███▋      | 41985/114105 [00:56<01:30, 796.89 examples/s]
Map:  35%|███▌      | 40000/114105 [00:55<01:57, 628.84 examples/s]
Map:  36%|███▌      | 40945/114105 [00:55<01:30, 810.92 examples/s]
Map:  35%|███▌      | 40079/114105 [00:55<01:51, 662.54 examples/s]
Map:  36%|███▌      | 41000/114105 [00:55<01:58, 618.33 examples/s]
Map:  37%|███▋      | 42082/114105 [00:56<01:54, 630.02 examples/s]
Map:  35%|███▌      | 40162/114105 [00:55<01:45, 698.29 examples/s]
Map:  36%|███▌      | 41086/114105 [00:55<01:48, 671.84 examples/s]
Map:  36%|███▌      | 41042/114105 [00:56<01:53, 641.97 examples/s]
Map:  37%|███▋      | 42169/114105 [00:56<01:45, 680.78 examples/s]
Map:  35%|███▌      | 40249/114105 [00:55<01:39, 738.56 examples/s]
Map:  36%|███▌      | 41174/114105 [00:55<01:41, 719.71 examples/s]
Map:  36%|███▌      | 41127/114105 [00:56<01:46, 687.05 examples/s]
Map:  37%|███▋      | 42252/114105 [00:57<01:40, 713.55 examples/s]
Map:  35%|███▌      | 40336/114105 [00:55<01:35, 771.82 examples/s]
Map:  36%|███▌      | 41257/114105 [00:56<01:37, 744.36 examples/s]
Map:  36%|███▌      | 41209/114105 [00:56<01:41, 716.66 examples/s]
Map:  37%|███▋      | 42339/114105 [00:57<01:35, 750.21 examples/s]
Map:  35%|███▌      | 40421/114105 [00:55<01:33, 790.41 examples/s]
Map:  36%|███▌      | 41344/114105 [00:56<01:33, 775.74 examples/s]
Map:  36%|███▌      | 41294/114105 [00:56<01:37, 744.87 examples/s]
Map:  37%|███▋      | 42426/114105 [00:57<01:31, 780.78 examples/s]
Map:  36%|███▌      | 40511/114105 [00:56<01:29, 817.79 examples/s]
Map:  36%|███▋      | 41428/114105 [00:56<01:31, 790.80 examples/s]
Map:  36%|███▋      | 41377/114105 [00:56<01:34, 766.43 examples/s]
Map:  37%|███▋      | 42512/114105 [00:57<01:29, 797.80 examples/s]
Map:  36%|███▌      | 40602/114105 [00:56<01:27, 839.44 examples/s]
Map:  36%|███▋      | 41514/114105 [00:56<01:29, 808.90 examples/s]
Map:  36%|███▋      | 41461/114105 [00:56<01:33, 780.99 examples/s]
Map:  36%|███▌      | 40690/114105 [00:56<01:26, 846.84 examples/s]
Map:  37%|███▋      | 42634/114105 [00:57<01:29, 798.50 examples/s]
Map:  36%|███▋      | 41638/114105 [00:56<01:29, 811.43 examples/s]
Map:  36%|███▋      | 41546/114105 [00:56<01:31, 795.85 examples/s]
Map:  36%|███▌      | 40776/114105 [00:56<01:26, 846.47 examples/s]
Map:  37%|███▋      | 41726/114105 [00:56<01:27, 827.77 examples/s]
Map:  36%|███▋      | 41630/114105 [00:56<01:30, 804.46 examples/s]
Map:  37%|███▋      | 42755/114105 [00:57<01:29, 795.06 examples/s]
Map:  36%|███▌      | 40864/114105 [00:56<01:26, 851.52 examples/s]
Map:  37%|███▋      | 41716/114105 [00:56<01:28, 815.57 examples/s]
Map:  38%|███▊      | 42842/114105 [00:57<01:27, 810.82 examples/s]
Map:  37%|███▋      | 41848/114105 [00:56<01:27, 821.29 examples/s]
Map:  36%|███▌      | 40990/114105 [00:56<01:26, 844.71 examples/s]
Map:  38%|███▊      | 42927/114105 [00:57<01:26, 818.43 examples/s]
Map:  37%|███▋      | 41841/114105 [00:57<01:28, 818.04 examples/s]
Map:  37%|███▋      | 41969/114105 [00:56<01:28, 812.65 examples/s]
Map:  37%|███▋      | 41924/114105 [00:57<01:28, 818.12 examples/s]
Map:  36%|███▌      | 41087/114105 [00:56<01:49, 665.81 examples/s]
Map:  38%|███▊      | 43042/114105 [00:58<01:48, 657.48 examples/s]
Map:  36%|███▌      | 41171/114105 [00:56<01:43, 702.09 examples/s]
Map:  37%|███▋      | 42087/114105 [00:57<01:47, 669.88 examples/s]
Map:  38%|███▊      | 43128/114105 [00:58<01:41, 700.62 examples/s]
Map:  36%|███▌      | 41256/114105 [00:56<01:38, 735.87 examples/s]
Map:  37%|███▋      | 42036/114105 [00:57<01:52, 642.50 examples/s]
Map:  37%|███▋      | 42167/114105 [00:57<01:43, 695.21 examples/s]
Map:  38%|███▊      | 43210/114105 [00:58<01:37, 726.02 examples/s]
Map:  36%|███▌      | 41345/114105 [00:57<01:34, 773.18 examples/s]
Map:  37%|███▋      | 42121/114105 [00:57<01:45, 684.37 examples/s]
Map:  37%|███▋      | 42254/114105 [00:57<01:37, 733.78 examples/s]
Map:  38%|███▊      | 43296/114105 [00:58<01:33, 757.36 examples/s]
Map:  36%|███▋      | 41431/114105 [00:57<01:31, 793.49 examples/s]
Map:  37%|███▋      | 42204/114105 [00:57<01:40, 715.38 examples/s]
Map:  37%|███▋      | 42343/114105 [00:57<01:33, 770.79 examples/s]
Map:  38%|███▊      | 43383/114105 [00:58<01:30, 782.47 examples/s]
Map:  36%|███▋      | 41516/114105 [00:57<01:30, 805.28 examples/s]
Map:  37%|███▋      | 42427/114105 [00:57<01:31, 786.66 examples/s]
Map:  37%|███▋      | 42320/114105 [00:57<01:38, 731.87 examples/s]
Map:  38%|███▊      | 43497/114105 [00:58<01:31, 772.79 examples/s]
Map:  36%|███▋      | 41627/114105 [00:57<01:33, 776.21 examples/s]
Map:  37%|███▋      | 42403/114105 [00:57<01:35, 752.35 examples/s]
Map:  37%|███▋      | 42544/114105 [00:57<01:31, 780.58 examples/s]
Map:  38%|███▊      | 43580/114105 [00:58<01:29, 784.33 examples/s]
Map:  37%|███▋      | 41710/114105 [00:57<01:31, 788.64 examples/s]
Map:  37%|███▋      | 42482/114105 [00:57<01:34, 760.38 examples/s]
Map:  37%|███▋      | 42630/114105 [00:57<01:29, 800.29 examples/s]
Map:  38%|███▊      | 43665/114105 [00:58<01:28, 798.46 examples/s]
Map:  37%|███▋      | 41795/114105 [00:57<01:30, 801.55 examples/s]
Map:  37%|███▋      | 42714/114105 [00:57<01:28, 807.16 examples/s]
Map:  38%|███▊      | 43747/114105 [00:58<01:27, 802.07 examples/s]
Map:  37%|███▋      | 42600/114105 [00:58<01:33, 766.82 examples/s]
Map:  37%|███▋      | 41882/114105 [00:57<01:28, 815.84 examples/s]
Map:  38%|███▊      | 42800/114105 [00:57<01:27, 817.40 examples/s]
Map:  37%|███▋      | 42685/114105 [00:58<01:30, 785.50 examples/s]
Map:  38%|███▊      | 43834/114105 [00:59<01:26, 816.61 examples/s]
Map:  38%|███▊      | 43920/114105 [00:59<01:24, 827.00 examples/s]
Map:  38%|███▊      | 42925/114105 [00:58<01:26, 819.41 examples/s]
Map:  38%|███▊      | 42797/114105 [00:58<01:32, 769.77 examples/s]
Map:  37%|███▋      | 42000/114105 [00:57<01:51, 644.36 examples/s]
Map:  37%|███▋      | 42083/114105 [00:58<01:45, 683.07 examples/s]
Map:  38%|███▊      | 42908/114105 [00:58<01:34, 756.87 examples/s]
Map:  39%|███▊      | 44040/114105 [00:59<01:46, 658.66 examples/s]
Map:  38%|███▊      | 43040/114105 [00:58<01:47, 658.80 examples/s]
Map:  37%|███▋      | 42167/114105 [00:58<01:40, 719.03 examples/s]
Map:  38%|███▊      | 42986/114105 [00:58<01:33, 758.38 examples/s]
Map:  39%|███▊      | 44127/114105 [00:59<01:39, 704.02 examples/s]
Map:  38%|███▊      | 43121/114105 [00:58<01:43, 688.65 examples/s]
Map:  37%|███▋      | 42249/114105 [00:58<01:36, 743.14 examples/s]
Map:  39%|███▊      | 44214/114105 [00:59<01:34, 743.30 examples/s]
Map:  38%|███▊      | 43198/114105 [00:58<01:40, 706.00 examples/s]
Map:  37%|███▋      | 42337/114105 [00:58<01:32, 776.81 examples/s]
Map:  38%|███▊      | 43079/114105 [00:58<01:57, 606.92 examples/s]
Map:  39%|███▉      | 44298/114105 [00:59<01:31, 764.21 examples/s]
Map:  38%|███▊      | 43278/114105 [00:58<01:37, 726.99 examples/s]
Map:  37%|███▋      | 42422/114105 [00:58<01:30, 794.28 examples/s]
Map:  38%|███▊      | 43161/114105 [00:58<01:48, 652.10 examples/s]
Map:  38%|███▊      | 43356/114105 [00:58<01:35, 737.36 examples/s]
Map:  39%|███▉      | 44413/114105 [00:59<01:31, 759.61 examples/s]
Map:  38%|███▊      | 43247/114105 [00:59<01:41, 698.44 examples/s]
Map:  37%|███▋      | 42539/114105 [00:58<01:30, 786.93 examples/s]
Map:  39%|███▉      | 44501/114105 [01:00<01:28, 788.34 examples/s]
Map:  38%|███▊      | 43469/114105 [00:58<01:35, 740.53 examples/s]
Map:  38%|███▊      | 43326/114105 [00:59<01:38, 719.27 examples/s]
Map:  37%|███▋      | 42661/114105 [00:58<01:30, 793.63 examples/s]
Map:  39%|███▉      | 44584/114105 [01:00<01:27, 794.10 examples/s]
Map:  38%|███▊      | 43552/114105 [00:59<01:32, 761.60 examples/s]
Map:  38%|███▊      | 43405/114105 [00:59<01:35, 736.80 examples/s]
Map:  37%|███▋      | 42748/114105 [00:58<01:28, 808.80 examples/s]
Map:  39%|███▉      | 44670/114105 [01:00<01:25, 807.92 examples/s]
Map:  38%|███▊      | 43637/114105 [00:59<01:30, 782.78 examples/s]
Map:  38%|███▊      | 43486/114105 [00:59<01:33, 754.50 examples/s]
Map:  39%|███▉      | 44755/114105 [01:00<01:24, 817.42 examples/s]
Map:  38%|███▊      | 43720/114105 [00:59<01:28, 792.62 examples/s]
Map:  38%|███▊      | 42872/114105 [00:59<01:27, 810.32 examples/s]
Map:  38%|███▊      | 43605/114105 [00:59<01:32, 765.19 examples/s]
Map:  39%|███▉      | 44841/114105 [01:00<01:23, 827.86 examples/s]
Map:  38%|███▊      | 43803/114105 [00:59<01:27, 802.15 examples/s]
Map:  38%|███▊      | 42958/114105 [00:59<01:26, 820.44 examples/s]
Map:  38%|███▊      | 43685/114105 [00:59<01:31, 772.14 examples/s]
Map:  38%|███▊      | 43886/114105 [00:59<01:26, 809.60 examples/s]
Map:  39%|███▉      | 44960/114105 [01:00<01:25, 808.73 examples/s]
Map:  39%|███▊      | 43971/114105 [00:59<01:25, 816.81 examples/s]
Map:  38%|███▊      | 43799/114105 [00:59<01:31, 764.27 examples/s]
Map:  38%|███▊      | 43081/114105 [00:59<01:47, 660.62 examples/s]
Map:  38%|███▊      | 43877/114105 [00:59<01:31, 765.83 examples/s]
Map:  39%|███▉      | 45042/114105 [01:00<01:47, 640.08 examples/s]
Map:  38%|███▊      | 43166/114105 [00:59<01:41, 698.19 examples/s]
Map:  40%|███▉      | 45127/114105 [01:00<01:40, 685.81 examples/s]
Map:  39%|███▊      | 44087/114105 [00:59<01:49, 639.52 examples/s]
Map:  39%|███▊      | 43993/114105 [00:59<01:31, 767.55 examples/s]
Map:  38%|███▊      | 43247/114105 [00:59<01:37, 723.71 examples/s]
Map:  40%|███▉      | 45215/114105 [01:00<01:34, 730.94 examples/s]
Map:  39%|███▊      | 44170/114105 [00:59<01:42, 679.94 examples/s]
Map:  38%|███▊      | 43330/114105 [00:59<01:34, 746.02 examples/s]
Map:  40%|███▉      | 45295/114105 [01:01<01:31, 748.05 examples/s]
Map:  39%|███▉      | 44252/114105 [00:59<01:38, 710.78 examples/s]
Map:  39%|███▊      | 44078/114105 [01:00<01:53, 614.37 examples/s]
Map:  38%|███▊      | 43410/114105 [00:59<01:33, 758.82 examples/s]
Map:  40%|███▉      | 45381/114105 [01:01<01:28, 777.04 examples/s]
Map:  39%|███▉      | 44340/114105 [01:00<01:32, 750.94 examples/s]
Map:  39%|███▊      | 44159/114105 [01:00<01:46, 655.45 examples/s]
Map:  38%|███▊      | 43492/114105 [00:59<01:31, 772.49 examples/s]
Map:  40%|███▉      | 45469/114105 [01:01<01:25, 800.94 examples/s]
Map:  39%|███▉      | 44424/114105 [01:00<01:30, 771.65 examples/s]
Map:  39%|███▉      | 44237/114105 [01:00<01:42, 684.57 examples/s]
Map:  38%|███▊      | 43579/114105 [01:00<01:28, 797.76 examples/s]
Map:  40%|███▉      | 45554/114105 [01:01<01:24, 814.04 examples/s]
Map:  39%|███▉      | 44509/114105 [01:00<01:27, 791.75 examples/s]
Map:  39%|███▉      | 44315/114105 [01:00<01:38, 707.87 examples/s]
Map:  38%|███▊      | 43664/114105 [01:00<01:27, 806.59 examples/s]
Map:  40%|███▉      | 45640/114105 [01:01<01:22, 824.91 examples/s]
Map:  39%|███▉      | 44593/114105 [01:00<01:26, 800.69 examples/s]
Map:  39%|███▉      | 44395/114105 [01:00<01:35, 730.74 examples/s]
Map:  38%|███▊      | 43747/114105 [01:00<01:26, 812.15 examples/s]
Map:  40%|████      | 45725/114105 [01:01<01:22, 830.36 examples/s]
Map:  39%|███▉      | 44680/114105 [01:00<01:25, 816.30 examples/s]
Map:  39%|███▉      | 44474/114105 [01:00<01:33, 744.91 examples/s]
Map:  38%|███▊      | 43831/114105 [01:00<01:25, 818.39 examples/s]
Map:  39%|███▉      | 44556/114105 [01:00<01:30, 764.85 examples/s]
Map:  38%|███▊      | 43923/114105 [01:00<01:23, 844.95 examples/s]
Map:  40%|████      | 45848/114105 [01:01<01:23, 818.05 examples/s]
Map:  39%|███▉      | 44808/114105 [01:00<01:23, 827.84 examples/s]
Map:  39%|███▉      | 44638/114105 [01:00<01:29, 779.36 examples/s]
Map:  40%|████      | 45931/114105 [01:01<01:23, 820.04 examples/s]
Map:  39%|███▉      | 44925/114105 [01:00<01:25, 807.96 examples/s]
Map:  39%|███▉      | 44750/114105 [01:01<01:30, 763.18 examples/s]
Map:  39%|███▊      | 44041/114105 [01:00<01:46, 657.88 examples/s]
Map:  40%|████      | 46045/114105 [01:02<01:42, 662.07 examples/s]
Map:  39%|███▉      | 44832/114105 [01:01<01:29, 774.01 examples/s]
Map:  39%|███▊      | 44124/114105 [01:00<01:40, 693.56 examples/s]
Map:  39%|███▉      | 45039/114105 [01:01<01:45, 652.58 examples/s]
Map:  40%|████      | 46133/114105 [01:02<01:35, 709.57 examples/s]
Map:  39%|███▊      | 44201/114105 [01:00<01:38, 708.37 examples/s]
Map:  39%|███▉      | 44943/114105 [01:01<01:31, 757.14 examples/s]
Map:  40%|███▉      | 45116/114105 [01:01<01:42, 675.72 examples/s]
Map:  41%|████      | 46255/114105 [01:02<01:31, 740.38 examples/s]
Map:  39%|███▉      | 44314/114105 [01:01<01:36, 721.83 examples/s]
Map:  40%|███▉      | 45198/114105 [01:01<01:37, 707.28 examples/s]
Map:  41%|████      | 46342/114105 [01:02<01:28, 766.74 examples/s]
Map:  39%|███▉      | 44402/114105 [01:01<01:31, 757.69 examples/s]
Map:  40%|███▉      | 45284/114105 [01:01<01:32, 741.03 examples/s]
Map:  39%|███▉      | 45038/114105 [01:01<01:52, 613.18 examples/s]
Map:  41%|████      | 46429/114105 [01:02<01:25, 788.31 examples/s]
Map:  39%|███▉      | 44483/114105 [01:01<01:30, 768.56 examples/s]
Map:  40%|███▉      | 45371/114105 [01:01<01:29, 771.78 examples/s]
Map:  40%|███▉      | 45120/114105 [01:01<01:45, 654.97 examples/s]
Map:  41%|████      | 46513/114105 [01:02<01:24, 801.09 examples/s]
Map:  39%|███▉      | 44569/114105 [01:01<01:27, 790.99 examples/s]
Map:  40%|███▉      | 45458/114105 [01:01<01:26, 796.12 examples/s]
Map:  40%|███▉      | 45199/114105 [01:01<01:40, 684.64 examples/s]
Map:  41%|████      | 46600/114105 [01:02<01:22, 816.66 examples/s]
Map:  39%|███▉      | 44656/114105 [01:01<01:25, 808.86 examples/s]
Map:  40%|███▉      | 45281/114105 [01:01<01:36, 715.47 examples/s]
Map:  40%|███▉      | 45582/114105 [01:01<01:25, 803.85 examples/s]
Map:  41%|████      | 46684/114105 [01:02<01:22, 820.64 examples/s]
Map:  39%|███▉      | 44739/114105 [01:01<01:25, 812.38 examples/s]
Map:  40%|████      | 45666/114105 [01:01<01:24, 811.24 examples/s]
Map:  40%|███▉      | 45391/114105 [01:01<01:35, 717.32 examples/s]
Map:  41%|████      | 46768/114105 [01:02<01:21, 823.08 examples/s]
Map:  39%|███▉      | 44822/114105 [01:01<01:25, 811.27 examples/s]
Map:  40%|███▉      | 45470/114105 [01:02<01:33, 734.25 examples/s]
Map:  41%|████      | 46855/114105 [01:03<01:20, 832.94 examples/s]
Map:  39%|███▉      | 44907/114105 [01:01<01:24, 819.58 examples/s]
Map:  40%|████      | 45785/114105 [01:01<01:25, 799.91 examples/s]
Map:  40%|███▉      | 45553/114105 [01:02<01:30, 757.45 examples/s]
Map:  41%|████      | 46939/114105 [01:03<01:20, 832.51 examples/s]
Map:  40%|████      | 45875/114105 [01:02<01:22, 823.06 examples/s]
Map:  40%|████      | 45668/114105 [01:02<01:30, 755.25 examples/s]
Map:  39%|███▉      | 45000/114105 [01:01<01:51, 621.08 examples/s]
Map:  40%|████      | 45997/114105 [01:02<01:23, 817.68 examples/s]
Map:  41%|████      | 47042/114105 [01:03<01:42, 655.72 examples/s]
Map:  40%|███▉      | 45078/114105 [01:02<01:45, 654.50 examples/s]
Map:  40%|████      | 45781/114105 [01:02<01:31, 748.86 examples/s]
Map:  41%|████▏     | 47123/114105 [01:03<01:37, 689.35 examples/s]
Map:  40%|███▉      | 45163/114105 [01:02<01:38, 701.79 examples/s]
Map:  40%|████      | 45859/114105 [01:02<01:30, 753.97 examples/s]
Map:  41%|████▏     | 47201/114105 [01:03<01:34, 709.56 examples/s]
Map:  40%|████      | 46114/114105 [01:02<01:45, 645.87 examples/s]
Map:  40%|███▉      | 45242/114105 [01:02<01:35, 723.30 examples/s]
Map:  40%|████      | 45936/114105 [01:02<01:30, 752.28 examples/s]
Map:  41%|████▏     | 47283/114105 [01:03<01:30, 738.20 examples/s]
Map:  40%|████      | 46199/114105 [01:02<01:39, 685.57 examples/s]
Map:  40%|███▉      | 45322/114105 [01:02<01:32, 740.00 examples/s]
Map:  42%|████▏     | 47373/114105 [01:03<01:25, 780.38 examples/s]
Map:  41%|████      | 46282/114105 [01:02<01:34, 715.90 examples/s]
Map:  40%|███▉      | 45407/114105 [01:02<01:29, 768.26 examples/s]
Map:  40%|████      | 46037/114105 [01:02<01:52, 606.81 examples/s]
Map:  42%|████▏     | 47456/114105 [01:03<01:24, 791.15 examples/s]
Map:  41%|████      | 46366/114105 [01:02<01:30, 744.45 examples/s]
Map:  40%|███▉      | 45491/114105 [01:02<01:27, 786.15 examples/s]
Map:  40%|████      | 46122/114105 [01:03<01:43, 658.00 examples/s]
Map:  41%|████      | 46451/114105 [01:02<01:27, 769.34 examples/s]
Map:  40%|███▉      | 45577/114105 [01:02<01:25, 805.80 examples/s]
Map:  42%|████▏     | 47576/114105 [01:04<01:24, 788.17 examples/s]
Map:  40%|████      | 46201/114105 [01:03<01:38, 686.85 examples/s]
Map:  41%|████      | 46533/114105 [01:02<01:26, 779.46 examples/s]
Map:  40%|████      | 45661/114105 [01:02<01:24, 810.80 examples/s]
Map:  42%|████▏     | 47657/114105 [01:04<01:24, 790.96 examples/s]
Map:  41%|████      | 46280/114105 [01:03<01:35, 711.23 examples/s]
Map:  41%|████      | 46614/114105 [01:03<01:25, 786.24 examples/s]
Map:  42%|████▏     | 47741/114105 [01:04<01:22, 800.22 examples/s]
Map:  40%|████      | 45783/114105 [01:02<01:24, 810.06 examples/s]
Map:  41%|████      | 46359/114105 [01:03<01:32, 729.81 examples/s]
Map:  41%|████      | 46697/114105 [01:03<01:25, 792.96 examples/s]
Map:  42%|████▏     | 47826/114105 [01:04<01:21, 811.47 examples/s]
Map:  41%|████      | 46435/114105 [01:03<01:32, 735.24 examples/s]
Map:  40%|████      | 45901/114105 [01:03<01:25, 800.19 examples/s]
Map:  41%|████      | 46816/114105 [01:03<01:25, 788.26 examples/s]
Map:  41%|████      | 46517/114105 [01:03<01:29, 754.88 examples/s]
Map:  42%|████▏     | 47947/114105 [01:04<01:21, 807.39 examples/s]
Map:  40%|████      | 45985/114105 [01:03<01:24, 808.26 examples/s]
Map:  41%|████      | 46896/114105 [01:03<01:25, 790.24 examples/s]
Map:  41%|████      | 46633/114105 [01:03<01:29, 756.98 examples/s]
Map:  41%|████      | 46980/114105 [01:03<01:23, 801.57 examples/s]
Map:  42%|████▏     | 48038/114105 [01:04<01:44, 631.92 examples/s]
Map:  40%|████      | 46083/114105 [01:03<01:46, 640.39 examples/s]
Map:  41%|████      | 46714/114105 [01:03<01:27, 767.69 examples/s]
Map:  42%|████▏     | 48126/114105 [01:04<01:36, 683.01 examples/s]
Map:  40%|████      | 46171/114105 [01:03<01:38, 691.27 examples/s]
Map:  41%|████      | 46792/114105 [01:03<01:27, 769.00 examples/s]
Map:  41%|████▏     | 47084/114105 [01:03<01:46, 626.51 examples/s]
Map:  42%|████▏     | 48214/114105 [01:04<01:30, 727.99 examples/s]
Map:  41%|████      | 46259/114105 [01:03<01:32, 733.24 examples/s]
Map:  41%|████      | 46873/114105 [01:03<01:26, 777.88 examples/s]
Map:  41%|████▏     | 47170/114105 [01:03<01:38, 676.66 examples/s]
Map:  42%|████▏     | 48298/114105 [01:04<01:27, 753.59 examples/s]
Map:  41%|████      | 46342/114105 [01:03<01:29, 755.05 examples/s]
Map:  41%|████      | 46952/114105 [01:04<01:26, 778.48 examples/s]
Map:  41%|████▏     | 47256/114105 [01:03<01:33, 717.43 examples/s]
Map:  42%|████▏     | 48381/114105 [01:05<01:25, 772.39 examples/s]
Map:  41%|████      | 46429/114105 [01:03<01:26, 783.46 examples/s]
Map:  41%|████▏     | 47341/114105 [01:04<01:29, 747.91 examples/s]
Map:  42%|████▏     | 48464/114105 [01:05<01:23, 785.76 examples/s]
Map:  41%|████      | 46519/114105 [01:03<01:23, 810.65 examples/s]
Map:  41%|████      | 47038/114105 [01:04<01:50, 605.28 examples/s]
Map:  42%|████▏     | 47423/114105 [01:04<01:27, 764.58 examples/s]
Map:  43%|████▎     | 48548/114105 [01:05<01:21, 800.12 examples/s]
Map:  41%|████▏     | 47119/114105 [01:04<01:42, 651.50 examples/s]
Map:  41%|████      | 46639/114105 [01:04<01:23, 803.41 examples/s]
Map:  42%|████▏     | 47508/114105 [01:04<01:24, 783.51 examples/s]
Map:  41%|████▏     | 47198/114105 [01:04<01:37, 682.80 examples/s]
Map:  43%|████▎     | 48671/114105 [01:05<01:21, 806.86 examples/s]
Map:  42%|████▏     | 47592/114105 [01:04<01:23, 795.61 examples/s]
Map:  41%|████      | 46757/114105 [01:04<01:24, 795.21 examples/s]
Map:  41%|████▏     | 47282/114105 [01:04<01:32, 720.15 examples/s]
Map:  43%|████▎     | 48754/114105 [01:05<01:20, 811.41 examples/s]
Map:  41%|████      | 46839/114105 [01:04<01:24, 800.02 examples/s]
Map:  42%|████▏     | 47712/114105 [01:04<01:23, 793.05 examples/s]
Map:  42%|████▏     | 47360/114105 [01:04<01:30, 733.88 examples/s]
Map:  43%|████▎     | 48838/114105 [01:05<01:19, 815.88 examples/s]
Map:  41%|████      | 46926/114105 [01:04<01:22, 817.12 examples/s]
Map:  42%|████▏     | 47794/114105 [01:04<01:23, 796.82 examples/s]
Map:  43%|████▎     | 48922/114105 [01:05<01:19, 820.30 examples/s]
Map:  42%|████▏     | 47474/114105 [01:04<01:29, 741.39 examples/s]
Map:  42%|████▏     | 47876/114105 [01:04<01:22, 800.71 examples/s]
Map:  42%|████▏     | 47557/114105 [01:04<01:27, 761.85 examples/s]
Map:  42%|████▏     | 47957/114105 [01:04<01:22, 799.47 examples/s]
Map:  41%|████      | 47038/114105 [01:04<01:43, 645.31 examples/s]
Map:  42%|████▏     | 47641/114105 [01:05<01:25, 781.48 examples/s]
Map:  43%|████▎     | 49043/114105 [01:05<01:39, 652.08 examples/s]
Map:  41%|████▏     | 47119/114105 [01:04<01:38, 680.30 examples/s]
Map:  43%|████▎     | 49132/114105 [01:06<01:32, 701.98 examples/s]
Map:  42%|████▏     | 47757/114105 [01:05<01:25, 774.05 examples/s]
Map:  42%|████▏     | 48040/114105 [01:05<01:48, 610.00 examples/s]
Map:  41%|████▏     | 47202/114105 [01:04<01:33, 713.70 examples/s]
Map:  43%|████▎     | 49215/114105 [01:06<01:28, 730.99 examples/s]
Map:  42%|████▏     | 47838/114105 [01:05<01:24, 780.44 examples/s]
Map:  42%|████▏     | 48128/114105 [01:05<01:38, 671.37 examples/s]
Map:  41%|████▏     | 47286/114105 [01:04<01:30, 742.24 examples/s]
Map:  43%|████▎     | 49294/114105 [01:06<01:27, 744.05 examples/s]
Map:  42%|████▏     | 47919/114105 [01:05<01:24, 786.33 examples/s]
Map:  42%|████▏     | 48210/114105 [01:05<01:33, 706.85 examples/s]
Map:  42%|████▏     | 47370/114105 [01:05<01:27, 766.72 examples/s]
Map:  43%|████▎     | 49375/114105 [01:06<01:25, 760.81 examples/s]
Map:  42%|████▏     | 48297/114105 [01:05<01:28, 745.87 examples/s]
Map:  43%|████▎     | 49458/114105 [01:06<01:23, 777.43 examples/s]
Map:  42%|████▏     | 47491/114105 [01:05<01:25, 779.00 examples/s]
Map:  42%|████▏     | 48000/114105 [01:05<01:45, 625.18 examples/s]
Map:  42%|████▏     | 48383/114105 [01:05<01:25, 769.96 examples/s]
Map:  43%|████▎     | 49542/114105 [01:06<01:21, 790.60 examples/s]
Map:  42%|████▏     | 48081/114105 [01:05<01:39, 666.14 examples/s]
Map:  42%|████▏     | 47611/114105 [01:05<01:25, 780.43 examples/s]
Map:  43%|████▎     | 48503/114105 [01:05<01:24, 776.90 examples/s]
Map:  43%|████▎     | 49625/114105 [01:06<01:20, 798.93 examples/s]
Map:  42%|████▏     | 48166/114105 [01:05<01:32, 710.66 examples/s]
Map:  42%|████▏     | 47693/114105 [01:05<01:24, 785.34 examples/s]
Map:  44%|████▎     | 49707/114105 [01:06<01:20, 804.32 examples/s]
Map:  42%|████▏     | 48251/114105 [01:05<01:28, 745.16 examples/s]
Map:  43%|████▎     | 48622/114105 [01:05<01:24, 778.27 examples/s]
Map:  42%|████▏     | 47812/114105 [01:05<01:24, 783.48 examples/s]
Map:  42%|████▏     | 48332/114105 [01:06<01:26, 759.16 examples/s]
Map:  44%|████▎     | 49823/114105 [01:06<01:21, 789.47 examples/s]
Map:  43%|████▎     | 48730/114105 [01:05<01:26, 755.44 examples/s]
Map:  42%|████▏     | 47895/114105 [01:05<01:23, 792.47 examples/s]
Map:  42%|████▏     | 48413/114105 [01:06<01:25, 772.22 examples/s]
Map:  43%|████▎     | 48811/114105 [01:06<01:25, 766.62 examples/s]
Map:  42%|████▏     | 47976/114105 [01:05<01:23, 794.14 examples/s]
Map:  43%|████▎     | 48499/114105 [01:06<01:22, 795.04 examples/s]
Map:  44%|████▍     | 49926/114105 [01:07<01:44, 613.80 examples/s]
Map:  43%|████▎     | 48892/114105 [01:06<01:24, 772.05 examples/s]
Map:  43%|████▎     | 48582/114105 [01:06<01:21, 802.21 examples/s]
Map:  43%|████▎     | 48977/114105 [01:06<01:22, 789.30 examples/s]
Map:  43%|████▎     | 48664/114105 [01:06<01:21, 803.55 examples/s]
Map:  42%|████▏     | 48076/114105 [01:06<01:47, 616.47 examples/s]
Map:  44%|████▍     | 50000/114105 [01:07<01:59, 536.34 examples/s]
Map:  43%|████▎     | 48747/114105 [01:06<01:21, 805.36 examples/s]
Map:  42%|████▏     | 48156/114105 [01:06<01:40, 654.81 examples/s]
Map:  44%|████▍     | 50083/114105 [01:07<01:47, 594.57 examples/s]
Map:  43%|████▎     | 48829/114105 [01:06<01:20, 806.03 examples/s]
Map:  43%|████▎     | 49082/114105 [01:06<01:44, 619.70 examples/s]
Map:  42%|████▏     | 48240/114105 [01:06<01:34, 694.99 examples/s]
Map:  44%|████▍     | 50165/114105 [01:07<01:39, 643.73 examples/s]
Map:  43%|████▎     | 48912/114105 [01:06<01:20, 809.65 examples/s]
Map:  43%|████▎     | 49168/114105 [01:06<01:36, 670.18 examples/s]
Map:  42%|████▏     | 48320/114105 [01:06<01:31, 719.66 examples/s]
Map:  44%|████▍     | 50247/114105 [01:07<01:33, 683.99 examples/s]
Map:  43%|████▎     | 49247/114105 [01:06<01:33, 696.27 examples/s]
Map:  42%|████▏     | 48400/114105 [01:06<01:29, 736.12 examples/s]
Map:  44%|████▍     | 50335/114105 [01:07<01:27, 732.47 examples/s]
Map:  43%|████▎     | 49332/114105 [01:06<01:28, 730.26 examples/s]
Map:  43%|████▎     | 49000/114105 [01:06<01:45, 619.26 examples/s]
Map:  42%|████▏     | 48484/114105 [01:06<01:26, 758.49 examples/s]
Map:  44%|████▍     | 50420/114105 [01:07<01:23, 760.70 examples/s]
Map:  43%|████▎     | 49413/114105 [01:06<01:26, 748.24 examples/s]
Map:  43%|████▎     | 49081/114105 [01:07<01:37, 663.81 examples/s]
Map:  44%|████▍     | 50509/114105 [01:08<01:20, 794.57 examples/s]
Map:  43%|████▎     | 48602/114105 [01:06<01:25, 764.38 examples/s]
Map:  43%|████▎     | 49492/114105 [01:06<01:25, 758.51 examples/s]
Map:  43%|████▎     | 49167/114105 [01:07<01:31, 711.29 examples/s]
Map:  44%|████▍     | 50597/114105 [01:08<01:17, 815.34 examples/s]
Map:  43%|████▎     | 48683/114105 [01:06<01:24, 773.96 examples/s]
Map:  43%|████▎     | 49571/114105 [01:07<01:24, 762.75 examples/s]
Map:  43%|████▎     | 49250/114105 [01:07<01:27, 739.94 examples/s]
Map:  43%|████▎     | 48766/114105 [01:06<01:22, 787.80 examples/s]
Map:  44%|████▍     | 50716/114105 [01:08<01:19, 798.69 examples/s]
Map:  43%|████▎     | 49333/114105 [01:07<01:25, 760.89 examples/s]
Map:  44%|████▎     | 49682/114105 [01:07<01:25, 749.90 examples/s]
Map:  43%|████▎     | 48847/114105 [01:07<01:22, 789.91 examples/s]
Map:  45%|████▍     | 50802/114105 [01:08<01:17, 812.84 examples/s]
Map:  43%|████▎     | 49415/114105 [01:07<01:23, 773.23 examples/s]
Map:  44%|████▎     | 49762/114105 [01:07<01:24, 759.96 examples/s]
Map:  43%|████▎     | 49495/114105 [01:07<01:23, 775.20 examples/s]
Map:  43%|████▎     | 48962/114105 [01:07<01:23, 776.91 examples/s]
Map:  45%|████▍     | 50927/114105 [01:08<01:17, 816.61 examples/s]
Map:  44%|████▎     | 49844/114105 [01:07<01:23, 773.59 examples/s]
Map:  43%|████▎     | 49577/114105 [01:07<01:22, 783.95 examples/s]
Map:  44%|████▎     | 49662/114105 [01:07<01:20, 801.50 examples/s]
Map:  43%|████▎     | 49077/114105 [01:07<01:44, 622.69 examples/s]
Map:  45%|████▍     | 51042/114105 [01:08<01:35, 662.99 examples/s]
Map:  44%|████▎     | 49744/114105 [01:07<01:20, 803.24 examples/s]
Map:  44%|████▍     | 49923/114105 [01:07<02:08, 501.15 examples/s]
Map:  43%|████▎     | 49157/114105 [01:07<01:38, 657.70 examples/s]
Map:  45%|████▍     | 51127/114105 [01:08<01:29, 700.92 examples/s]
Map:  44%|████▎     | 49827/114105 [01:07<01:19, 808.08 examples/s]
Map:  43%|████▎     | 49239/114105 [01:07<01:33, 692.52 examples/s]
Map:  45%|████▍     | 51210/114105 [01:08<01:26, 729.68 examples/s]
Map:  44%|████▍     | 50000/114105 [01:07<02:19, 458.17 examples/s]
Map:  43%|████▎     | 49316/114105 [01:07<01:31, 706.46 examples/s]
Map:  45%|████▍     | 51301/114105 [01:09<01:31, 685.74 examples/s]
Map:  44%|████▍     | 50083/114105 [01:08<02:01, 528.51 examples/s]
Map:  44%|████▍     | 49924/114105 [01:08<01:47, 598.14 examples/s]
Map:  43%|████▎     | 49400/114105 [01:07<01:27, 737.25 examples/s]
Map:  44%|████▍     | 50165/114105 [01:08<01:48, 589.47 examples/s]
Map:  43%|████▎     | 49477/114105 [01:07<01:27, 741.68 examples/s]
Map:  45%|████▌     | 51415/114105 [01:09<01:28, 705.57 examples/s]
Map:  44%|████▍     | 50000/114105 [01:08<02:01, 527.02 examples/s]
Map:  44%|████▍     | 50246/114105 [01:08<01:39, 639.84 examples/s]
Map:  45%|████▌     | 51494/114105 [01:09<01:26, 724.08 examples/s]
Map:  43%|████▎     | 49591/114105 [01:08<01:26, 745.72 examples/s]
Map:  44%|████▍     | 50070/114105 [01:08<01:53, 562.30 examples/s]
Map:  44%|████▍     | 50329/114105 [01:08<01:33, 684.28 examples/s]
Map:  45%|████▌     | 51572/114105 [01:09<01:24, 736.61 examples/s]
Map:  44%|████▎     | 49669/114105 [01:08<01:25, 752.57 examples/s]
Map:  44%|████▍     | 50143/114105 [01:08<01:46, 599.63 examples/s]
Map:  44%|████▍     | 50431/114105 [01:08<01:33, 681.61 examples/s]
Map:  45%|████▌     | 51684/114105 [01:09<01:24, 736.40 examples/s]
Map:  44%|████▍     | 50224/114105 [01:08<01:38, 650.25 examples/s]
Map:  44%|████▎     | 49775/114105 [01:08<01:27, 731.49 examples/s]
Map:  44%|████▍     | 50510/114105 [01:08<01:30, 705.16 examples/s]
Map:  45%|████▌     | 51770/114105 [01:09<01:21, 764.37 examples/s]
Map:  44%|████▍     | 50302/114105 [01:08<01:33, 682.10 examples/s]
Map:  44%|████▎     | 49853/114105 [01:08<01:26, 742.05 examples/s]
Map:  44%|████▍     | 50592/114105 [01:08<01:26, 731.61 examples/s]
Map:  45%|████▌     | 51853/114105 [01:09<01:20, 776.69 examples/s]
Map:  44%|████▍     | 50387/114105 [01:08<01:27, 724.50 examples/s]
Map:  44%|████▍     | 50674/114105 [01:08<01:24, 750.43 examples/s]
Map:  46%|████▌     | 51934/114105 [01:09<01:19, 783.44 examples/s]
Map:  44%|████▍     | 50464/114105 [01:08<01:26, 734.88 examples/s]
Map:  44%|████▍     | 50755/114105 [01:08<01:22, 765.87 examples/s]
Map:  44%|████▍     | 50547/114105 [01:09<01:23, 761.07 examples/s]
Map:  44%|████▍     | 49963/114105 [01:08<02:01, 525.87 examples/s]
Map:  45%|████▍     | 50835/114105 [01:08<01:21, 772.99 examples/s]
Map:  44%|████▍     | 50628/114105 [01:09<01:22, 768.84 examples/s]
Map:  46%|████▌     | 52040/114105 [01:10<01:40, 618.72 examples/s]
Map:  45%|████▍     | 50914/114105 [01:09<01:21, 773.39 examples/s]
Map:  44%|████▍     | 50710/114105 [01:09<01:21, 776.24 examples/s]
Map:  46%|████▌     | 52120/114105 [01:10<01:34, 657.73 examples/s]
Map:  44%|████▍     | 50038/114105 [01:08<02:15, 471.40 examples/s]
Map:  45%|████▍     | 50998/114105 [01:09<01:19, 790.46 examples/s]
Map:  46%|████▌     | 52203/114105 [01:10<01:28, 697.75 examples/s]
Map:  45%|████▍     | 50829/114105 [01:09<01:21, 779.33 examples/s]
Map:  44%|████▍     | 50120/114105 [01:09<01:59, 534.03 examples/s]
Map:  46%|████▌     | 52287/114105 [01:10<01:24, 730.59 examples/s]
Map:  45%|████▍     | 50908/114105 [01:09<01:21, 777.32 examples/s]
Map:  44%|████▍     | 50204/114105 [01:09<01:47, 593.90 examples/s]
Map:  45%|████▍     | 51078/114105 [01:09<01:45, 597.41 examples/s]
Map:  46%|████▌     | 52373/114105 [01:10<01:20, 762.78 examples/s]
Map:  45%|████▍     | 50988/114105 [01:09<01:21, 777.51 examples/s]
Map:  44%|████▍     | 50286/114105 [01:09<01:39, 643.32 examples/s]
Map:  45%|████▍     | 51161/114105 [01:09<01:36, 651.22 examples/s]
Map:  46%|████▌     | 52453/114105 [01:10<01:20, 769.38 examples/s]
Map:  44%|████▍     | 50365/114105 [01:09<01:33, 678.21 examples/s]
Map:  45%|████▍     | 51242/114105 [01:09<01:31, 688.65 examples/s]
Map:  46%|████▌     | 52536/114105 [01:10<01:18, 784.00 examples/s]
Map:  44%|████▍     | 50446/114105 [01:09<01:29, 707.91 examples/s]
Map:  45%|████▍     | 51084/114105 [01:09<01:40, 624.90 examples/s]
Map:  45%|████▍     | 51320/114105 [01:09<01:28, 712.02 examples/s]
Map:  46%|████▌     | 52618/114105 [01:10<01:17, 790.53 examples/s]
Map:  44%|████▍     | 50529/114105 [01:09<01:26, 737.40 examples/s]
Map:  45%|████▍     | 51168/114105 [01:09<01:33, 672.91 examples/s]
Map:  45%|████▌     | 51403/114105 [01:09<01:24, 742.93 examples/s]
Map:  44%|████▍     | 50612/114105 [01:09<01:23, 761.82 examples/s]
Map:  45%|████▌     | 51483/114105 [01:09<01:22, 756.03 examples/s]
Map:  45%|████▍     | 51250/114105 [01:10<01:28, 706.34 examples/s]
Map:  46%|████▌     | 52736/114105 [01:11<01:18, 784.29 examples/s]
Map:  44%|████▍     | 50694/114105 [01:09<01:21, 776.41 examples/s]
Map:  45%|████▌     | 51567/114105 [01:10<01:20, 777.32 examples/s]
Map:  45%|████▍     | 51329/114105 [01:10<01:26, 725.10 examples/s]
Map:  46%|████▋     | 52856/114105 [01:11<01:17, 786.10 examples/s]
Map:  44%|████▍     | 50776/114105 [01:09<01:20, 783.87 examples/s]
Map:  45%|████▌     | 51412/114105 [01:10<01:23, 750.06 examples/s]
Map:  45%|████▌     | 51681/114105 [01:10<01:21, 765.54 examples/s]
Map:  46%|████▋     | 52943/114105 [01:11<01:16, 804.75 examples/s]
Map:  45%|████▍     | 50857/114105 [01:10<01:20, 789.08 examples/s]
Map:  45%|████▌     | 51503/114105 [01:10<01:19, 790.61 examples/s]
Map:  45%|████▌     | 51794/114105 [01:10<01:22, 758.92 examples/s]
Map:  45%|████▌     | 51587/114105 [01:10<01:18, 800.14 examples/s]
Map:  45%|████▍     | 50973/114105 [01:10<01:21, 778.52 examples/s]
Map:  46%|████▋     | 53045/114105 [01:11<01:34, 644.66 examples/s]
Map:  45%|████▌     | 51875/114105 [01:10<01:20, 769.35 examples/s]
Map:  45%|████▌     | 51669/114105 [01:10<01:17, 804.17 examples/s]
Map:  47%|████▋     | 53129/114105 [01:11<01:29, 684.85 examples/s]
Map:  46%|████▌     | 51955/114105 [01:10<01:20, 773.38 examples/s]
Map:  45%|████▌     | 51754/114105 [01:10<01:16, 814.47 examples/s]
Map:  45%|████▍     | 51080/114105 [01:10<01:41, 621.05 examples/s]
Map:  47%|████▋     | 53213/114105 [01:11<01:24, 719.97 examples/s]
Map:  45%|████▌     | 51877/114105 [01:10<01:16, 810.63 examples/s]
Map:  45%|████▍     | 51163/114105 [01:10<01:34, 665.60 examples/s]
Map:  47%|████▋     | 53298/114105 [01:11<01:21, 750.00 examples/s]
Map:  46%|████▌     | 52039/114105 [01:10<01:44, 592.52 examples/s]
Map:  46%|████▌     | 51963/114105 [01:10<01:15, 821.36 examples/s]
Map:  45%|████▍     | 51246/114105 [01:10<01:29, 700.56 examples/s]
Map:  47%|████▋     | 53379/114105 [01:11<01:19, 762.52 examples/s]
Map:  46%|████▌     | 52120/114105 [01:10<01:36, 640.26 examples/s]
Map:  45%|████▍     | 51326/114105 [01:10<01:26, 723.10 examples/s]
Map:  47%|████▋     | 53462/114105 [01:12<01:17, 778.13 examples/s]
Map:  46%|████▌     | 52201/114105 [01:10<01:31, 679.92 examples/s]
Map:  45%|████▌     | 51405/114105 [01:10<01:25, 736.98 examples/s]
Map:  47%|████▋     | 53544/114105 [01:12<01:16, 789.32 examples/s]
Map:  46%|████▌     | 52085/114105 [01:11<01:33, 665.90 examples/s]
Map:  46%|████▌     | 52280/114105 [01:11<01:27, 707.02 examples/s]
Map:  45%|████▌     | 51490/114105 [01:10<01:21, 764.03 examples/s]
Map:  47%|████▋     | 53627/114105 [01:12<01:15, 798.10 examples/s]
Map:  46%|████▌     | 52168/114105 [01:11<01:28, 698.67 examples/s]
Map:  46%|████▌     | 52362/114105 [01:11<01:23, 735.51 examples/s]
Map:  47%|████▋     | 53711/114105 [01:12<01:14, 806.55 examples/s]
Map:  46%|████▌     | 52246/114105 [01:11<01:26, 713.74 examples/s]
Map:  46%|████▌     | 52443/114105 [01:11<01:21, 754.75 examples/s]
Map:  45%|████▌     | 51609/114105 [01:11<01:21, 770.46 examples/s]
Map:  47%|████▋     | 53800/114105 [01:12<01:12, 826.18 examples/s]
Map:  46%|████▌     | 52325/114105 [01:11<01:24, 730.89 examples/s]
Map:  46%|████▌     | 52525/114105 [01:11<01:19, 770.52 examples/s]
Map:  45%|████▌     | 51689/114105 [01:11<01:20, 776.28 examples/s]
Map:  47%|████▋     | 53884/114105 [01:12<01:12, 825.73 examples/s]
Map:  46%|████▌     | 52403/114105 [01:11<01:23, 742.15 examples/s]
Map:  46%|████▌     | 52607/114105 [01:11<01:18, 778.79 examples/s]
Map:  45%|████▌     | 51771/114105 [01:11<01:19, 786.80 examples/s]
Map:  47%|████▋     | 53967/114105 [01:12<01:13, 820.45 examples/s]
Map:  46%|████▌     | 52486/114105 [01:11<01:20, 763.82 examples/s]
Map:  46%|████▌     | 52689/114105 [01:11<01:17, 789.34 examples/s]
Map:  45%|████▌     | 51854/114105 [01:11<01:18, 797.40 examples/s]
Map:  46%|████▌     | 52570/114105 [01:11<01:18, 781.98 examples/s]
Map:  46%|████▋     | 52775/114105 [01:11<01:15, 808.29 examples/s]
Map:  46%|████▌     | 51935/114105 [01:11<01:17, 798.86 examples/s]
Map:  46%|████▌     | 52659/114105 [01:11<01:16, 807.15 examples/s]
Map:  47%|████▋     | 54085/114105 [01:12<01:32, 649.25 examples/s]
Map:  46%|████▋     | 52895/114105 [01:11<01:16, 798.71 examples/s]
Map:  46%|████▌     | 52742/114105 [01:12<01:15, 811.58 examples/s]
Map:  47%|████▋     | 54172/114105 [01:12<01:25, 697.23 examples/s]
Map:  46%|████▌     | 52041/114105 [01:11<01:38, 632.50 examples/s]
Map:  46%|████▋     | 52978/114105 [01:11<01:15, 805.61 examples/s]
Map:  46%|████▋     | 52830/114105 [01:12<01:14, 827.82 examples/s]
Map:  48%|████▊     | 54257/114105 [01:13<01:21, 730.45 examples/s]
Map:  46%|████▌     | 52128/114105 [01:11<01:30, 684.59 examples/s]
Map:  48%|████▊     | 54340/114105 [01:13<01:19, 755.85 examples/s]
Map:  46%|████▋     | 52954/114105 [01:12<01:14, 824.72 examples/s]
Map:  46%|████▌     | 52212/114105 [01:11<01:25, 721.26 examples/s]
Map:  47%|████▋     | 53086/114105 [01:12<01:35, 639.96 examples/s]
Map:  48%|████▊     | 54420/114105 [01:13<01:18, 764.95 examples/s]
Map:  46%|████▌     | 52292/114105 [01:12<01:23, 740.79 examples/s]
Map:  47%|████▋     | 53168/114105 [01:12<01:30, 676.26 examples/s]
Map:  48%|████▊     | 54505/114105 [01:13<01:15, 784.82 examples/s]
Map:  46%|████▋     | 53042/114105 [01:12<01:33, 654.47 examples/s]
Map:  46%|████▌     | 52379/114105 [01:12<01:19, 773.22 examples/s]
Map:  47%|████▋     | 53252/114105 [01:12<01:25, 712.04 examples/s]
Map:  48%|████▊     | 54586/114105 [01:13<01:15, 790.45 examples/s]
Map:  47%|████▋     | 53125/114105 [01:12<01:27, 692.96 examples/s]
Map:  46%|████▌     | 52466/114105 [01:12<01:17, 797.39 examples/s]
Map:  47%|████▋     | 53335/114105 [01:12<01:22, 739.88 examples/s]
Map:  48%|████▊     | 54673/114105 [01:13<01:13, 811.52 examples/s]
Map:  47%|████▋     | 53207/114105 [01:12<01:24, 722.39 examples/s]
Map:  46%|████▌     | 52553/114105 [01:12<01:15, 815.43 examples/s]
Map:  47%|████▋     | 53422/114105 [01:12<01:18, 773.50 examples/s]
Map:  47%|████▋     | 53292/114105 [01:12<01:20, 752.97 examples/s]
Map:  46%|████▌     | 52641/114105 [01:12<01:13, 832.17 examples/s]
Map:  48%|████▊     | 54795/114105 [01:13<01:13, 801.73 examples/s]
Map:  47%|████▋     | 53509/114105 [01:12<01:16, 796.89 examples/s]
Map:  47%|████▋     | 53377/114105 [01:12<01:18, 775.00 examples/s]
Map:  46%|████▌     | 52728/114105 [01:12<01:13, 840.76 examples/s]
Map:  48%|████▊     | 54877/114105 [01:13<01:13, 803.72 examples/s]
Map:  47%|████▋     | 53593/114105 [01:12<01:14, 807.01 examples/s]
Map:  47%|████▋     | 53464/114105 [01:12<01:15, 800.52 examples/s]
Map:  46%|████▋     | 52813/114105 [01:12<01:12, 840.08 examples/s]
Map:  48%|████▊     | 54998/114105 [01:13<01:13, 800.61 examples/s]
Map:  47%|████▋     | 53548/114105 [01:13<01:14, 807.89 examples/s]
Map:  47%|████▋     | 53716/114105 [01:12<01:14, 808.66 examples/s]
Map:  46%|████▋     | 52937/114105 [01:12<01:13, 830.86 examples/s]
Map:  47%|████▋     | 53631/114105 [01:13<01:14, 810.92 examples/s]
Map:  47%|████▋     | 53799/114105 [01:13<01:14, 813.13 examples/s]
Map:  48%|████▊     | 55082/114105 [01:14<01:33, 630.11 examples/s]
Map:  47%|████▋     | 53882/114105 [01:13<01:13, 816.84 examples/s]
Map:  47%|████▋     | 53745/114105 [01:13<01:16, 790.34 examples/s]
Map:  46%|████▋     | 53041/114105 [01:12<01:31, 666.09 examples/s]
Map:  48%|████▊     | 55168/114105 [01:14<01:27, 677.40 examples/s]
Map:  47%|████▋     | 53123/114105 [01:13<01:27, 699.40 examples/s]
Map:  48%|████▊     | 55249/114105 [01:14<01:23, 704.70 examples/s]
Map:  47%|████▋     | 53866/114105 [01:13<01:15, 793.23 examples/s]
Map:  47%|████▋     | 54000/114105 [01:13<01:34, 639.41 examples/s]
Map:  47%|████▋     | 53203/114105 [01:13<01:24, 721.81 examples/s]
Map:  48%|████▊     | 55329/114105 [01:14<01:20, 727.89 examples/s]
Map:  47%|████▋     | 53985/114105 [01:13<01:16, 789.19 examples/s]
Map:  47%|████▋     | 54082/114105 [01:13<01:29, 673.98 examples/s]
Map:  47%|████▋     | 53286/114105 [01:13<01:21, 747.80 examples/s]
Map:  49%|████▊     | 55411/114105 [01:14<01:18, 748.74 examples/s]
Map:  47%|████▋     | 54167/114105 [01:13<01:24, 713.28 examples/s]
Map:  47%|████▋     | 53377/114105 [01:13<01:16, 789.01 examples/s]
Map:  49%|████▊     | 55494/114105 [01:14<01:16, 770.12 examples/s]
Map:  48%|████▊     | 54252/114105 [01:13<01:20, 746.71 examples/s]
Map:  47%|████▋     | 54079/114105 [01:13<01:34, 638.36 examples/s]
Map:  49%|████▊     | 55576/114105 [01:14<01:14, 780.81 examples/s]
Map:  47%|████▋     | 53501/114105 [01:13<01:15, 799.03 examples/s]
Map:  48%|████▊     | 54335/114105 [01:13<01:17, 767.33 examples/s]
Map:  47%|████▋     | 54156/114105 [01:13<01:30, 662.41 examples/s]
Map:  49%|████▉     | 55663/114105 [01:14<01:12, 802.48 examples/s]
Map:  47%|████▋     | 53584/114105 [01:13<01:15, 805.21 examples/s]
Map:  48%|████▊     | 54419/114105 [01:13<01:16, 781.50 examples/s]
Map:  48%|████▊     | 54239/114105 [01:14<01:25, 699.57 examples/s]
Map:  49%|████▉     | 55746/114105 [01:15<01:12, 807.46 examples/s]
Map:  47%|████▋     | 53669/114105 [01:13<01:14, 807.16 examples/s]
Map:  48%|████▊     | 54503/114105 [01:13<01:15, 788.81 examples/s]
Map:  48%|████▊     | 54317/114105 [01:14<01:23, 716.75 examples/s]
Map:  49%|████▉     | 55834/114105 [01:15<01:10, 825.61 examples/s]
Map:  47%|████▋     | 53751/114105 [01:13<01:14, 809.57 examples/s]
Map:  48%|████▊     | 54587/114105 [01:14<01:14, 802.56 examples/s]
Map:  48%|████▊     | 54401/114105 [01:14<01:19, 746.94 examples/s]
Map:  49%|████▉     | 55918/114105 [01:15<01:10, 824.21 examples/s]
Map:  47%|████▋     | 53838/114105 [01:13<01:13, 822.51 examples/s]
Map:  48%|████▊     | 54677/114105 [01:14<01:11, 826.92 examples/s]
Map:  48%|████▊     | 54480/114105 [01:14<01:18, 756.09 examples/s]
Map:  47%|████▋     | 53923/114105 [01:14<01:12, 828.97 examples/s]
Map:  48%|████▊     | 54762/114105 [01:14<01:11, 832.28 examples/s]
Map:  48%|████▊     | 54600/114105 [01:14<01:17, 770.65 examples/s]
Map:  49%|████▉     | 56039/114105 [01:15<01:30, 642.31 examples/s]
Map:  48%|████▊     | 54847/114105 [01:14<01:10, 835.63 examples/s]
Map:  49%|████▉     | 56118/114105 [01:15<01:25, 674.93 examples/s]
Map:  48%|████▊     | 54935/114105 [01:14<01:10, 844.03 examples/s]
Map:  48%|████▊     | 54714/114105 [01:14<01:18, 756.41 examples/s]
Map:  47%|████▋     | 54041/114105 [01:14<01:45, 571.57 examples/s]
Map:  49%|████▉     | 56204/114105 [01:15<01:20, 718.01 examples/s]
Map:  48%|████▊     | 54832/114105 [01:14<01:17, 764.32 examples/s]
Map:  47%|████▋     | 54121/114105 [01:14<01:37, 614.50 examples/s]
Map:  49%|████▉     | 56293/114105 [01:15<01:16, 760.14 examples/s]
Map:  48%|████▊     | 55040/114105 [01:14<01:31, 647.36 examples/s]
Map:  48%|████▊     | 54918/114105 [01:14<01:15, 785.36 examples/s]
Map:  48%|████▊     | 54204/114105 [01:14<01:30, 659.28 examples/s]
Map:  49%|████▉     | 56379/114105 [01:15<01:13, 783.99 examples/s]
Map:  48%|████▊     | 55126/114105 [01:14<01:24, 694.28 examples/s]
Map:  48%|████▊     | 54998/114105 [01:15<01:15, 787.50 examples/s]
Map:  48%|████▊     | 54285/114105 [01:14<01:26, 693.00 examples/s]
Map:  49%|████▉     | 56466/114105 [01:15<01:11, 804.39 examples/s]
Map:  48%|████▊     | 55207/114105 [01:14<01:21, 721.75 examples/s]
Map:  48%|████▊     | 54366/114105 [01:14<01:23, 719.40 examples/s]
Map:  50%|████▉     | 56577/114105 [01:16<01:14, 775.56 examples/s]
Map:  48%|████▊     | 55320/114105 [01:15<01:20, 728.95 examples/s]
Map:  48%|████▊     | 54448/114105 [01:14<01:20, 743.86 examples/s]
Map:  48%|████▊     | 55108/114105 [01:15<01:35, 615.86 examples/s]
Map:  49%|████▊     | 55404/114105 [01:15<01:18, 750.56 examples/s]
Map:  48%|████▊     | 54528/114105 [01:14<01:19, 754.00 examples/s]
Map:  50%|████▉     | 56698/114105 [01:16<01:13, 781.02 examples/s]
Map:  48%|████▊     | 55191/114105 [01:15<01:29, 658.38 examples/s]
Map:  49%|████▊     | 55488/114105 [01:15<01:15, 771.56 examples/s]
Map:  48%|████▊     | 54607/114105 [01:15<01:17, 762.86 examples/s]
Map:  50%|████▉     | 56780/114105 [01:16<01:12, 786.90 examples/s]
Map:  48%|████▊     | 55270/114105 [01:15<01:25, 688.36 examples/s]
Map:  49%|████▊     | 55571/114105 [01:15<01:14, 784.97 examples/s]
Map:  48%|████▊     | 54686/114105 [01:15<01:17, 763.47 examples/s]
Map:  50%|████▉     | 56863/114105 [01:16<01:11, 796.72 examples/s]
Map:  49%|████▊     | 55351/114105 [01:15<01:21, 718.14 examples/s]
Map:  50%|████▉     | 56945/114105 [01:16<01:11, 799.86 examples/s]
Map:  49%|████▊     | 55432/114105 [01:15<01:19, 736.54 examples/s]
Map:  49%|████▉     | 55695/114105 [01:15<01:13, 796.29 examples/s]
Map:  48%|████▊     | 54804/114105 [01:15<01:17, 769.29 examples/s]
Map:  49%|████▊     | 55518/114105 [01:15<01:16, 765.56 examples/s]
Map:  48%|████▊     | 54887/114105 [01:15<01:15, 781.03 examples/s]
Map:  49%|████▉     | 55811/114105 [01:15<01:14, 785.70 examples/s]
Map:  50%|████▉     | 57042/114105 [01:16<01:29, 638.08 examples/s]
Map:  49%|████▊     | 55600/114105 [01:15<01:15, 777.63 examples/s]
Map:  48%|████▊     | 54969/114105 [01:15<01:14, 789.63 examples/s]
Map:  49%|████▉     | 55894/114105 [01:15<01:13, 795.52 examples/s]
Map:  50%|█████     | 57128/114105 [01:16<01:22, 687.93 examples/s]
Map:  49%|████▉     | 55720/114105 [01:16<01:14, 780.63 examples/s]
Map:  49%|████▉     | 55977/114105 [01:15<01:12, 802.69 examples/s]
Map:  50%|█████     | 57213/114105 [01:16<01:18, 725.58 examples/s]
Map:  49%|████▉     | 55804/114105 [01:16<01:13, 794.27 examples/s]
Map:  48%|████▊     | 55080/114105 [01:15<01:35, 616.12 examples/s]
Map:  50%|█████     | 57297/114105 [01:17<01:15, 752.57 examples/s]
Map:  49%|████▉     | 55890/114105 [01:16<01:12, 807.35 examples/s]
Map:  48%|████▊     | 55163/114105 [01:15<01:29, 660.97 examples/s]
Map:  49%|████▉     | 56079/114105 [01:16<01:33, 619.77 examples/s]
Map:  50%|█████     | 57416/114105 [01:17<01:14, 762.88 examples/s]
Map:  48%|████▊     | 55244/114105 [01:15<01:25, 692.45 examples/s]
Map:  49%|████▉     | 56158/114105 [01:16<01:28, 652.79 examples/s]
Map:  50%|█████     | 57496/114105 [01:17<01:13, 769.56 examples/s]
Map:  48%|████▊     | 55328/114105 [01:16<01:20, 726.74 examples/s]
Map:  49%|████▉     | 56000/114105 [01:16<01:30, 643.86 examples/s]
Map:  49%|████▉     | 56236/114105 [01:16<01:24, 681.52 examples/s]
Map:  50%|█████     | 57575/114105 [01:17<01:14, 759.05 examples/s]
Map:  49%|████▉     | 56076/114105 [01:16<01:27, 665.73 examples/s]
Map:  49%|████▊     | 55437/114105 [01:16<01:21, 723.92 examples/s]
Map:  49%|████▉     | 56346/114105 [01:16<01:23, 695.61 examples/s]
Map:  49%|████▉     | 56154/114105 [01:16<01:23, 690.85 examples/s]
Map:  51%|█████     | 57694/114105 [01:17<01:13, 766.27 examples/s]
Map:  49%|████▊     | 55518/114105 [01:16<01:18, 743.78 examples/s]
Map:  49%|████▉     | 56430/114105 [01:16<01:19, 728.47 examples/s]
Map:  49%|████▉     | 56241/114105 [01:16<01:19, 732.38 examples/s]
Map:  51%|█████     | 57777/114105 [01:17<01:12, 779.08 examples/s]
Map:  49%|████▊     | 55595/114105 [01:16<01:18, 745.17 examples/s]
Map:  50%|████▉     | 56514/114105 [01:16<01:16, 753.44 examples/s]
Map:  49%|████▉     | 56326/114105 [01:16<01:15, 762.05 examples/s]
Map:  51%|█████     | 57858/114105 [01:17<01:11, 786.24 examples/s]
Map:  49%|████▉     | 55675/114105 [01:16<01:17, 758.62 examples/s]
Map:  50%|████▉     | 56595/114105 [01:16<01:14, 767.40 examples/s]
Map:  51%|█████     | 57941/114105 [01:17<01:10, 796.85 examples/s]
Map:  49%|████▉     | 55755/114105 [01:16<01:16, 765.76 examples/s]
Map:  49%|████▉     | 56448/114105 [01:17<01:13, 779.23 examples/s]
Map:  50%|████▉     | 56679/114105 [01:16<01:13, 781.63 examples/s]
Map:  49%|████▉     | 55835/114105 [01:16<01:15, 774.51 examples/s]
Map:  50%|████▉     | 56529/114105 [01:17<01:13, 784.28 examples/s]
Map:  50%|████▉     | 56759/114105 [01:16<01:13, 784.78 examples/s]
Map:  49%|████▉     | 55918/114105 [01:16<01:13, 788.50 examples/s]
Map:  51%|█████     | 58039/114105 [01:18<01:30, 616.39 examples/s]
Map:  50%|████▉     | 56610/114105 [01:17<01:12, 788.97 examples/s]
Map:  50%|████▉     | 56840/114105 [01:17<01:12, 788.55 examples/s]
Map:  51%|█████     | 58118/114105 [01:18<01:25, 654.15 examples/s]
Map:  50%|████▉     | 56693/114105 [01:17<01:11, 797.48 examples/s]
Map:  50%|████▉     | 56924/114105 [01:17<01:11, 800.67 examples/s]
Map:  51%|█████     | 58201/114105 [01:18<01:20, 693.01 examples/s]
Map:  50%|████▉     | 56774/114105 [01:17<01:11, 798.27 examples/s]
Map:  49%|████▉     | 56000/114105 [01:17<01:37, 595.77 examples/s]
Map:  51%|█████     | 58280/114105 [01:18<01:18, 715.28 examples/s]
Map:  50%|████▉     | 56856/114105 [01:17<01:11, 803.01 examples/s]
Map:  49%|████▉     | 56084/114105 [01:17<01:28, 652.07 examples/s]
Map:  50%|████▉     | 57040/114105 [01:17<01:32, 620.10 examples/s]
Map:  51%|█████     | 58363/114105 [01:18<01:14, 745.20 examples/s]
Map:  49%|████▉     | 56165/114105 [01:17<01:24, 689.62 examples/s]
Map:  50%|████▉     | 56976/114105 [01:17<01:11, 795.57 examples/s]
Map:  50%|█████     | 57123/114105 [01:17<01:25, 663.83 examples/s]
Map:  51%|█████     | 58447/114105 [01:18<01:12, 768.28 examples/s]
Map:  49%|████▉     | 56245/114105 [01:17<01:20, 716.14 examples/s]
Map:  50%|█████     | 57206/114105 [01:17<01:21, 702.21 examples/s]
Map:  51%|█████▏    | 58531/114105 [01:18<01:10, 786.90 examples/s]
Map:  49%|████▉     | 56327/114105 [01:17<01:18, 740.51 examples/s]
Map:  50%|█████     | 57079/114105 [01:17<01:28, 642.50 examples/s]
Map:  50%|█████     | 57290/114105 [01:17<01:17, 732.78 examples/s]
Map:  49%|████▉     | 56406/114105 [01:17<01:16, 751.26 examples/s]
Map:  51%|█████▏    | 58649/114105 [01:18<01:10, 783.64 examples/s]
Map:  50%|█████     | 57166/114105 [01:18<01:22, 690.32 examples/s]
Map:  50%|█████     | 57371/114105 [01:17<01:15, 750.54 examples/s]
Map:  50%|████▉     | 56490/114105 [01:17<01:14, 773.75 examples/s]
Map:  51%|█████▏    | 58733/114105 [01:19<01:09, 795.92 examples/s]
Map:  50%|█████     | 57248/114105 [01:18<01:19, 719.26 examples/s]
Map:  50%|████▉     | 56573/114105 [01:17<01:12, 789.17 examples/s]
Map:  50%|█████     | 57492/114105 [01:18<01:13, 765.19 examples/s]
Map:  52%|█████▏    | 58820/114105 [01:19<01:07, 815.15 examples/s]
Map:  50%|█████     | 57328/114105 [01:18<01:16, 737.50 examples/s]
Map:  50%|████▉     | 56658/114105 [01:17<01:11, 804.81 examples/s]
Map:  50%|█████     | 57572/114105 [01:18<01:13, 773.76 examples/s]
Map:  50%|█████     | 57410/114105 [01:18<01:14, 758.40 examples/s]
Map:  52%|█████▏    | 58941/114105 [01:19<01:08, 808.52 examples/s]
Map:  50%|████▉     | 56740/114105 [01:17<01:10, 808.04 examples/s]
Map:  50%|█████     | 57495/114105 [01:18<01:12, 780.25 examples/s]
Map:  51%|█████     | 57696/114105 [01:18<01:11, 790.04 examples/s]
Map:  50%|████▉     | 56822/114105 [01:18<01:10, 810.86 examples/s]
Map:  51%|█████     | 57779/114105 [01:18<01:10, 798.18 examples/s]
Map:  52%|█████▏    | 59040/114105 [01:19<01:25, 647.47 examples/s]
Map:  50%|█████     | 57616/114105 [01:18<01:11, 787.09 examples/s]
Map:  50%|████▉     | 56941/114105 [01:18<01:11, 800.74 examples/s]
Map:  51%|█████     | 57861/114105 [01:18<01:10, 799.19 examples/s]
Map:  52%|█████▏    | 59122/114105 [01:19<01:20, 684.21 examples/s]
Map:  51%|█████     | 57699/114105 [01:18<01:10, 794.73 examples/s]
Map:  52%|█████▏    | 59203/114105 [01:19<01:17, 711.35 examples/s]
Map:  51%|█████     | 57781/114105 [01:18<01:10, 800.55 examples/s]
Map:  51%|█████     | 57981/114105 [01:18<01:10, 795.41 examples/s]
Map:  50%|████▉     | 57040/114105 [01:18<01:31, 622.82 examples/s]
Map:  52%|█████▏    | 59285/114105 [01:19<01:14, 736.43 examples/s]
Map:  51%|█████     | 57866/114105 [01:18<01:09, 811.42 examples/s]
Map:  50%|█████     | 57121/114105 [01:18<01:26, 661.53 examples/s]
Map:  52%|█████▏    | 59369/114105 [01:19<01:11, 762.73 examples/s]
Map:  51%|█████     | 58078/114105 [01:18<01:30, 619.91 examples/s]
Map:  51%|█████     | 57989/114105 [01:19<01:09, 809.75 examples/s]
Map:  50%|█████     | 57203/114105 [01:18<01:21, 697.55 examples/s]
Map:  52%|█████▏    | 59451/114105 [01:19<01:10, 773.53 examples/s]
Map:  51%|█████     | 58160/114105 [01:18<01:24, 660.83 examples/s]
Map:  50%|█████     | 57282/114105 [01:18<01:19, 718.06 examples/s]
Map:  52%|█████▏    | 59533/114105 [01:20<01:09, 784.03 examples/s]
Map:  51%|█████     | 58237/114105 [01:19<01:21, 683.77 examples/s]
Map:  51%|█████     | 58077/114105 [01:19<01:27, 638.53 examples/s]
Map:  50%|█████     | 57361/114105 [01:18<01:17, 735.61 examples/s]
Map:  52%|█████▏    | 59654/114105 [01:20<01:09, 787.03 examples/s]
Map:  51%|█████     | 58318/114105 [01:19<01:18, 712.44 examples/s]
Map:  50%|█████     | 57442/114105 [01:18<01:15, 754.36 examples/s]
Map:  51%|█████     | 58163/114105 [01:19<01:21, 684.92 examples/s]
Map:  52%|█████▏    | 59737/114105 [01:20<01:08, 795.32 examples/s]
Map:  51%|█████     | 58398/114105 [01:19<01:15, 733.25 examples/s]
Map:  50%|█████     | 57523/114105 [01:19<01:13, 768.17 examples/s]
Map:  51%|█████     | 58246/114105 [01:19<01:17, 718.83 examples/s]
Map:  51%|█████▏    | 58486/114105 [01:19<01:12, 770.60 examples/s]
Map:  51%|█████     | 58327/114105 [01:19<01:15, 739.10 examples/s]
Map:  50%|█████     | 57604/114105 [01:19<01:13, 773.50 examples/s]
Map:  52%|█████▏    | 59856/114105 [01:20<01:08, 790.58 examples/s]
Map:  51%|█████     | 57684/114105 [01:19<01:12, 779.32 examples/s]
Map:  51%|█████     | 58409/114105 [01:19<01:13, 756.66 examples/s]
Map:  53%|█████▎    | 59938/114105 [01:20<01:08, 795.64 examples/s]
Map:  51%|█████▏    | 58604/114105 [01:19<01:11, 775.29 examples/s]
Map:  51%|█████     | 57765/114105 [01:19<01:11, 786.30 examples/s]
Map:  51%|█████▏    | 58492/114105 [01:19<01:11, 774.86 examples/s]
Map:  51%|█████▏    | 58687/114105 [01:19<01:10, 787.98 examples/s]
Map:  51%|█████     | 57849/114105 [01:19<01:10, 801.01 examples/s]
Map:  51%|█████▏    | 58577/114105 [01:19<01:10, 792.38 examples/s]
Map:  53%|█████▎    | 60040/114105 [01:20<01:24, 637.50 examples/s]
Map:  52%|█████▏    | 58806/114105 [01:19<01:10, 784.82 examples/s]
Map:  51%|█████     | 57931/114105 [01:19<01:09, 804.45 examples/s]
Map:  51%|█████▏    | 58694/114105 [01:20<01:10, 784.51 examples/s]
Map:  53%|█████▎    | 60127/114105 [01:20<01:18, 686.97 examples/s]
Map:  52%|█████▏    | 58888/114105 [01:19<01:09, 790.68 examples/s]
Map:  52%|█████▏    | 58778/114105 [01:20<01:09, 796.35 examples/s]
Map:  53%|█████▎    | 60210/114105 [01:21<01:15, 717.13 examples/s]
Map:  52%|█████▏    | 58970/114105 [01:19<01:09, 797.46 examples/s]
Map:  51%|█████     | 58043/114105 [01:19<01:28, 631.11 examples/s]
Map:  52%|█████▏    | 58864/114105 [01:20<01:08, 810.92 examples/s]
Map:  53%|█████▎    | 60295/114105 [01:21<01:11, 748.95 examples/s]
Map:  51%|█████     | 58126/114105 [01:19<01:23, 671.88 examples/s]
Map:  53%|█████▎    | 60376/114105 [01:21<01:10, 762.23 examples/s]
Map:  52%|█████▏    | 58983/114105 [01:20<01:08, 800.86 examples/s]
Map:  52%|█████▏    | 59082/114105 [01:20<01:28, 621.95 examples/s]
Map:  51%|█████     | 58204/114105 [01:20<01:20, 697.41 examples/s]
Map:  53%|█████▎    | 60456/114105 [01:21<01:09, 771.06 examples/s]
Map:  52%|█████▏    | 59160/114105 [01:20<01:23, 654.80 examples/s]
Map:  51%|█████     | 58284/114105 [01:20<01:17, 723.19 examples/s]
Map:  53%|█████▎    | 60537/114105 [01:21<01:08, 778.09 examples/s]
Map:  52%|█████▏    | 59077/114105 [01:20<01:26, 634.63 examples/s]
Map:  52%|█████▏    | 59243/114105 [01:20<01:18, 694.54 examples/s]
Map:  51%|█████     | 58368/114105 [01:20<01:14, 752.42 examples/s]
Map:  53%|█████▎    | 60620/114105 [01:21<01:07, 790.96 examples/s]
Map:  52%|█████▏    | 59161/114105 [01:20<01:21, 676.67 examples/s]
Map:  52%|█████▏    | 59325/114105 [01:20<01:15, 723.65 examples/s]
Map:  51%|█████     | 58449/114105 [01:20<01:12, 765.67 examples/s]
Map:  53%|█████▎    | 60704/114105 [01:21<01:06, 803.21 examples/s]
Map:  52%|█████▏    | 59242/114105 [01:20<01:17, 706.76 examples/s]
Map:  51%|█████▏    | 58535/114105 [01:20<01:10, 788.42 examples/s]
Map:  53%|█████▎    | 60788/114105 [01:21<01:05, 810.56 examples/s]
Map:  52%|█████▏    | 59443/114105 [01:20<01:13, 742.39 examples/s]
Map:  52%|█████▏    | 59324/114105 [01:20<01:14, 732.23 examples/s]
Map:  51%|█████▏    | 58618/114105 [01:20<01:09, 799.98 examples/s]
Map:  53%|█████▎    | 60871/114105 [01:21<01:05, 813.56 examples/s]
Map:  52%|█████▏    | 59525/114105 [01:20<01:11, 758.59 examples/s]
Map:  52%|█████▏    | 59407/114105 [01:20<01:12, 756.35 examples/s]
Map:  51%|█████▏    | 58704/114105 [01:20<01:08, 812.07 examples/s]
Map:  52%|█████▏    | 59609/114105 [01:20<01:09, 779.33 examples/s]
Map:  53%|█████▎    | 60990/114105 [01:21<01:06, 802.94 examples/s]
Map:  52%|█████▏    | 59487/114105 [01:21<01:11, 764.16 examples/s]
Map:  52%|█████▏    | 58788/114105 [01:20<01:07, 816.30 examples/s]
Map:  52%|█████▏    | 59694/114105 [01:20<01:08, 793.68 examples/s]
Map:  52%|█████▏    | 59570/114105 [01:21<01:09, 779.76 examples/s]
Map:  52%|█████▏    | 58876/114105 [01:20<01:06, 829.40 examples/s]
Map:  52%|█████▏    | 59779/114105 [01:21<01:07, 804.60 examples/s]
Map:  54%|█████▎    | 61087/114105 [01:22<01:22, 643.61 examples/s]
Map:  52%|█████▏    | 59653/114105 [01:21<01:08, 791.84 examples/s]
Map:  52%|█████▏    | 59865/114105 [01:21<01:06, 817.53 examples/s]
Map:  54%|█████▎    | 61170/114105 [01:22<01:17, 682.80 examples/s]
Map:  52%|█████▏    | 59737/114105 [01:21<01:07, 801.33 examples/s]
Map:  53%|█████▎    | 59951/114105 [01:21<01:05, 825.54 examples/s]
Map:  52%|█████▏    | 59000/114105 [01:21<01:25, 646.12 examples/s]
Map:  54%|█████▎    | 61248/114105 [01:22<01:15, 704.19 examples/s]
Map:  52%|█████▏    | 59856/114105 [01:21<01:08, 791.85 examples/s]
Map:  52%|█████▏    | 59084/114105 [01:21<01:20, 686.78 examples/s]
Map:  54%|█████▍    | 61336/114105 [01:22<01:10, 747.16 examples/s]
Map:  53%|█████▎    | 59937/114105 [01:21<01:08, 791.17 examples/s]
Map:  52%|█████▏    | 59166/114105 [01:21<01:16, 717.13 examples/s]
Map:  53%|█████▎    | 60045/114105 [01:21<01:25, 630.10 examples/s]
Map:  54%|█████▍    | 61456/114105 [01:22<01:09, 761.98 examples/s]
Map:  52%|█████▏    | 59250/114105 [01:21<01:13, 746.76 examples/s]
Map:  53%|█████▎    | 60135/114105 [01:21<01:18, 691.43 examples/s]
Map:  54%|█████▍    | 61541/114105 [01:22<01:07, 780.76 examples/s]
Map:  52%|█████▏    | 59331/114105 [01:21<01:11, 761.67 examples/s]
Map:  53%|█████▎    | 60038/114105 [01:21<01:26, 623.25 examples/s]
Map:  53%|█████▎    | 60214/114105 [01:21<01:15, 712.48 examples/s]
Map:  54%|█████▍    | 61626/114105 [01:22<01:06, 794.95 examples/s]
Map:  52%|█████▏    | 59415/114105 [01:21<01:09, 781.45 examples/s]
Map:  53%|█████▎    | 60121/114105 [01:21<01:20, 667.84 examples/s]
Map:  53%|█████▎    | 60299/114105 [01:21<01:12, 746.01 examples/s]
Map:  54%|█████▍    | 61712/114105 [01:22<01:04, 810.83 examples/s]
Map:  52%|█████▏    | 59504/114105 [01:21<01:07, 808.20 examples/s]
Map:  53%|█████▎    | 60204/114105 [01:22<01:16, 703.79 examples/s]
Map:  53%|█████▎    | 60383/114105 [01:21<01:09, 768.83 examples/s]
Map:  54%|█████▍    | 61798/114105 [01:23<01:03, 821.49 examples/s]
Map:  53%|█████▎    | 60466/114105 [01:22<01:08, 783.64 examples/s]
Map:  53%|█████▎    | 60289/114105 [01:22<01:13, 736.63 examples/s]
Map:  52%|█████▏    | 59629/114105 [01:21<01:07, 810.28 examples/s]
Map:  54%|█████▍    | 61884/114105 [01:23<01:03, 819.64 examples/s]
Map:  53%|█████▎    | 60550/114105 [01:22<01:07, 796.85 examples/s]
Map:  53%|█████▎    | 60372/114105 [01:22<01:10, 759.99 examples/s]
Map:  52%|█████▏    | 59715/114105 [01:21<01:06, 818.17 examples/s]
Map:  53%|█████▎    | 60455/114105 [01:22<01:08, 778.06 examples/s]
Map:  53%|█████▎    | 60636/114105 [01:22<01:05, 812.16 examples/s]
Map:  52%|█████▏    | 59799/114105 [01:22<01:06, 820.77 examples/s]
Map:  53%|█████▎    | 60537/114105 [01:22<01:08, 787.48 examples/s]
Map:  53%|█████▎    | 60719/114105 [01:22<01:05, 813.05 examples/s]
Map:  54%|█████▍    | 62000/114105 [01:23<01:20, 645.98 examples/s]
Map:  52%|█████▏    | 59884/114105 [01:22<01:05, 825.58 examples/s]
Map:  53%|█████▎    | 60624/114105 [01:22<01:06, 808.01 examples/s]
Map:  53%|█████▎    | 60804/114105 [01:22<01:04, 820.15 examples/s]
Map:  54%|█████▍    | 62083/114105 [01:23<01:16, 683.43 examples/s]
Map:  53%|█████▎    | 60707/114105 [01:22<01:05, 810.88 examples/s]
Map:  53%|█████▎    | 60891/114105 [01:22<01:03, 832.90 examples/s]
Map:  54%|█████▍    | 62171/114105 [01:23<01:11, 727.64 examples/s]
Map:  53%|█████▎    | 60000/114105 [01:22<01:22, 654.77 examples/s]
Map:  53%|█████▎    | 60975/114105 [01:22<01:03, 832.18 examples/s]
Map:  55%|█████▍    | 62253/114105 [01:23<01:09, 748.41 examples/s]
Map:  53%|█████▎    | 60826/114105 [01:22<01:06, 799.67 examples/s]
Map:  53%|█████▎    | 60087/114105 [01:22<01:17, 699.98 examples/s]
Map:  55%|█████▍    | 62338/114105 [01:23<01:07, 770.92 examples/s]
Map:  53%|█████▎    | 60909/114105 [01:22<01:06, 804.42 examples/s]
Map:  53%|█████▎    | 60175/114105 [01:22<01:12, 741.16 examples/s]
Map:  55%|█████▍    | 62424/114105 [01:23<01:05, 792.90 examples/s]
Map:  54%|█████▎    | 61085/114105 [01:22<01:21, 651.92 examples/s]
Map:  53%|█████▎    | 60995/114105 [01:23<01:04, 817.33 examples/s]
Map:  53%|█████▎    | 60255/114105 [01:22<01:11, 753.77 examples/s]
Map:  55%|█████▍    | 62507/114105 [01:24<01:04, 800.29 examples/s]
Map:  54%|█████▎    | 61166/114105 [01:22<01:17, 686.35 examples/s]
Map:  53%|█████▎    | 60343/114105 [01:22<01:08, 782.90 examples/s]
Map:  54%|█████▎    | 61248/114105 [01:23<01:13, 715.20 examples/s]
Map:  55%|█████▍    | 62629/114105 [01:24<01:04, 800.19 examples/s]
Map:  53%|█████▎    | 60426/114105 [01:22<01:07, 794.31 examples/s]
Map:  54%|█████▎    | 61115/114105 [01:23<01:22, 641.67 examples/s]
Map:  54%|█████▍    | 61335/114105 [01:23<01:10, 753.54 examples/s]
Map:  55%|█████▍    | 62714/114105 [01:24<01:03, 807.40 examples/s]
Map:  53%|█████▎    | 60513/114105 [01:23<01:05, 815.29 examples/s]
Map:  54%|█████▎    | 61198/114105 [01:23<01:17, 680.46 examples/s]
Map:  54%|█████▍    | 61418/114105 [01:23<01:08, 769.48 examples/s]
Map:  55%|█████▌    | 62796/114105 [01:24<01:03, 809.70 examples/s]
Map:  54%|█████▎    | 61276/114105 [01:23<01:15, 701.49 examples/s]
Map:  54%|█████▍    | 61504/114105 [01:23<01:06, 793.58 examples/s]
Map:  53%|█████▎    | 60631/114105 [01:23<01:06, 799.87 examples/s]
Map:  55%|█████▌    | 62879/114105 [01:24<01:03, 811.57 examples/s]
Map:  54%|█████▍    | 61358/114105 [01:23<01:12, 728.69 examples/s]
Map:  54%|█████▍    | 61588/114105 [01:23<01:05, 803.05 examples/s]
Map:  55%|█████▌    | 62965/114105 [01:24<01:02, 823.21 examples/s]
Map:  53%|█████▎    | 60751/114105 [01:23<01:06, 796.90 examples/s]
Map:  54%|█████▍    | 61435/114105 [01:23<01:11, 736.32 examples/s]
Map:  54%|█████▍    | 61674/114105 [01:23<01:04, 817.18 examples/s]
Map:  54%|█████▍    | 61516/114105 [01:23<01:09, 754.16 examples/s]
Map:  54%|█████▍    | 61760/114105 [01:23<01:03, 827.05 examples/s]
Map:  53%|█████▎    | 60870/114105 [01:23<01:07, 793.38 examples/s]
Map:  54%|█████▍    | 61598/114105 [01:23<01:08, 769.39 examples/s]
Map:  55%|█████▌    | 63088/114105 [01:24<01:17, 659.41 examples/s]
Map:  53%|█████▎    | 60956/114105 [01:23<01:05, 807.53 examples/s]
Map:  54%|█████▍    | 61884/114105 [01:23<01:04, 811.52 examples/s]
Map:  54%|█████▍    | 61678/114105 [01:24<01:07, 776.03 examples/s]
Map:  55%|█████▌    | 63168/114105 [01:24<01:13, 688.43 examples/s]
Map:  54%|█████▍    | 61967/114105 [01:23<01:04, 814.48 examples/s]
Map:  54%|█████▍    | 61757/114105 [01:24<01:07, 778.79 examples/s]
Map:  55%|█████▌    | 63251/114105 [01:25<01:10, 721.16 examples/s]
Map:  53%|█████▎    | 61041/114105 [01:23<01:23, 638.71 examples/s]
Map:  54%|█████▍    | 61836/114105 [01:24<01:07, 778.67 examples/s]
Map:  56%|█████▌    | 63333/114105 [01:25<01:08, 744.08 examples/s]
Map:  54%|█████▎    | 61126/114105 [01:23<01:17, 683.37 examples/s]
Map:  56%|█████▌    | 63418/114105 [01:25<01:05, 770.97 examples/s]
Map:  54%|█████▍    | 62082/114105 [01:24<01:21, 640.60 examples/s]
Map:  54%|█████▎    | 61208/114105 [01:23<01:14, 714.25 examples/s]
Map:  54%|█████▍    | 61947/114105 [01:24<01:08, 757.67 examples/s]
Map:  56%|█████▌    | 63501/114105 [01:25<01:04, 785.28 examples/s]
Map:  54%|█████▍    | 62168/114105 [01:24<01:15, 686.44 examples/s]
Map:  54%|█████▎    | 61290/114105 [01:24<01:11, 739.06 examples/s]
Map:  56%|█████▌    | 63582/114105 [01:25<01:04, 788.00 examples/s]
Map:  55%|█████▍    | 62251/114105 [01:24<01:12, 717.52 examples/s]
Map:  54%|█████▍    | 61377/114105 [01:24<01:08, 771.30 examples/s]
Map:  54%|█████▍    | 62035/114105 [01:24<01:27, 594.79 examples/s]
Map:  56%|█████▌    | 63663/114105 [01:25<01:03, 793.54 examples/s]
Map:  55%|█████▍    | 62334/114105 [01:24<01:09, 743.92 examples/s]
Map:  54%|█████▍    | 61464/114105 [01:24<01:06, 796.19 examples/s]
Map:  54%|█████▍    | 62110/114105 [01:24<01:22, 628.36 examples/s]
Map:  56%|█████▌    | 63747/114105 [01:25<01:02, 799.42 examples/s]
Map:  55%|█████▍    | 62416/114105 [01:24<01:08, 759.53 examples/s]
Map:  55%|█████▍    | 62194/114105 [01:24<01:16, 678.23 examples/s]
Map:  54%|█████▍    | 61589/114105 [01:24<01:05, 806.90 examples/s]
Map:  56%|█████▌    | 63831/114105 [01:25<01:02, 810.47 examples/s]
Map:  55%|█████▍    | 62499/114105 [01:24<01:06, 774.84 examples/s]
Map:  55%|█████▍    | 62278/114105 [01:24<01:12, 717.00 examples/s]
Map:  54%|█████▍    | 61675/114105 [01:24<01:04, 816.66 examples/s]
Map:  56%|█████▌    | 63956/114105 [01:25<01:01, 816.18 examples/s]
Map:  55%|█████▍    | 62362/114105 [01:24<01:09, 745.33 examples/s]
Map:  55%|█████▍    | 62619/114105 [01:24<01:05, 781.44 examples/s]
Map:  54%|█████▍    | 61759/114105 [01:24<01:03, 818.48 examples/s]
Map:  55%|█████▍    | 62448/114105 [01:25<01:06, 773.99 examples/s]
Map:  55%|█████▍    | 62700/114105 [01:24<01:05, 785.13 examples/s]
Map:  54%|█████▍    | 61848/114105 [01:24<01:02, 836.93 examples/s]
Map:  56%|█████▌    | 64044/114105 [01:26<01:17, 642.15 examples/s]
Map:  55%|█████▍    | 62533/114105 [01:25<01:05, 792.87 examples/s]
Map:  55%|█████▌    | 62782/114105 [01:25<01:04, 792.82 examples/s]
Map:  54%|█████▍    | 61967/114105 [01:24<01:03, 818.07 examples/s]
Map:  56%|█████▌    | 64129/114105 [01:26<01:12, 687.66 examples/s]
Map:  55%|█████▌    | 62864/114105 [01:25<01:04, 794.63 examples/s]
Map:  55%|█████▍    | 62651/114105 [01:25<01:05, 785.79 examples/s]
Map:  56%|█████▋    | 64212/114105 [01:26<01:09, 719.62 examples/s]
Map:  55%|█████▌    | 62947/114105 [01:25<01:03, 802.33 examples/s]
Map:  55%|█████▍    | 62732/114105 [01:25<01:05, 788.59 examples/s]
Map:  56%|█████▋    | 64299/114105 [01:26<01:05, 754.96 examples/s]
Map:  54%|█████▍    | 62084/114105 [01:25<01:18, 662.60 examples/s]
Map:  55%|█████▌    | 62816/114105 [01:25<01:04, 799.75 examples/s]
Map:  56%|█████▋    | 64383/114105 [01:26<01:04, 773.41 examples/s]
Map:  54%|█████▍    | 62169/114105 [01:25<01:14, 701.35 examples/s]
Map:  55%|█████▌    | 63039/114105 [01:25<01:22, 621.82 examples/s]
Map:  55%|█████▌    | 62935/114105 [01:25<01:04, 792.97 examples/s]
Map:  55%|█████▍    | 62254/114105 [01:25<01:10, 734.84 examples/s]
Map:  55%|█████▌    | 63121/114105 [01:25<01:16, 666.54 examples/s]
Map:  57%|█████▋    | 64504/114105 [01:26<01:03, 783.63 examples/s]
Map:  55%|█████▍    | 62344/114105 [01:25<01:06, 774.30 examples/s]
Map:  55%|█████▌    | 63206/114105 [01:25<01:11, 711.48 examples/s]
Map:  57%|█████▋    | 64589/114105 [01:26<01:01, 799.44 examples/s]
Map:  55%|█████▍    | 62427/114105 [01:25<01:05, 785.97 examples/s]
Map:  55%|█████▌    | 63294/114105 [01:25<01:07, 753.59 examples/s]
Map:  55%|█████▌    | 63040/114105 [01:25<01:19, 642.20 examples/s]
Map:  57%|█████▋    | 64676/114105 [01:26<01:00, 817.90 examples/s]
Map:  55%|█████▍    | 62511/114105 [01:25<01:04, 798.42 examples/s]
Map:  56%|█████▌    | 63384/114105 [01:25<01:04, 792.07 examples/s]
Map:  55%|█████▌    | 63125/114105 [01:26<01:14, 684.36 examples/s]
Map:  57%|█████▋    | 64760/114105 [01:26<01:00, 821.72 examples/s]
Map:  55%|█████▍    | 62595/114105 [01:25<01:03, 806.78 examples/s]
Map:  56%|█████▌    | 63470/114105 [01:25<01:02, 810.20 examples/s]
Map:  55%|█████▌    | 63212/114105 [01:26<01:10, 726.48 examples/s]
Map:  57%|█████▋    | 64844/114105 [01:27<00:59, 824.59 examples/s]
Map:  55%|█████▍    | 62682/114105 [01:25<01:02, 823.60 examples/s]
Map:  55%|█████▌    | 63297/114105 [01:26<01:07, 756.33 examples/s]
Map:  57%|█████▋    | 64929/114105 [01:27<00:59, 827.41 examples/s]
Map:  56%|█████▌    | 63596/114105 [01:26<01:01, 815.91 examples/s]
Map:  56%|█████▌    | 63380/114105 [01:26<01:05, 770.72 examples/s]
Map:  55%|█████▌    | 62807/114105 [01:25<01:02, 824.13 examples/s]
Map:  56%|█████▌    | 63681/114105 [01:26<01:01, 820.50 examples/s]
Map:  57%|█████▋    | 65042/114105 [01:27<01:15, 653.34 examples/s]
Map:  56%|█████▌    | 63767/114105 [01:26<01:00, 828.18 examples/s]
Map:  56%|█████▌    | 63500/114105 [01:26<01:05, 777.21 examples/s]
Map:  55%|█████▌    | 62925/114105 [01:26<01:03, 808.31 examples/s]
Map:  57%|█████▋    | 65127/114105 [01:27<01:10, 697.21 examples/s]
Map:  56%|█████▌    | 63854/114105 [01:26<01:00, 836.89 examples/s]
Map:  56%|█████▌    | 63619/114105 [01:26<01:04, 780.88 examples/s]
Map:  57%|█████▋    | 65205/114105 [01:27<01:08, 715.33 examples/s]
Map:  56%|█████▌    | 63977/114105 [01:26<01:00, 825.20 examples/s]
Map:  56%|█████▌    | 63705/114105 [01:26<01:03, 798.21 examples/s]
Map:  55%|█████▌    | 63038/114105 [01:26<01:18, 646.98 examples/s]
Map:  57%|█████▋    | 65291/114105 [01:27<01:05, 750.85 examples/s]
Map:  56%|█████▌    | 63787/114105 [01:26<01:02, 801.44 examples/s]
Map:  55%|█████▌    | 63125/114105 [01:26<01:13, 691.76 examples/s]
Map:  57%|█████▋    | 65375/114105 [01:27<01:03, 772.43 examples/s]
Map:  55%|█████▌    | 63204/114105 [01:26<01:11, 712.62 examples/s]
Map:  56%|█████▌    | 64083/114105 [01:26<01:16, 650.67 examples/s]
Map:  57%|█████▋    | 65462/114105 [01:27<01:01, 794.68 examples/s]
Map:  56%|█████▌    | 63906/114105 [01:27<01:03, 792.13 examples/s]
Map:  55%|█████▌    | 63284/114105 [01:26<01:09, 732.54 examples/s]
Map:  56%|█████▌    | 64164/114105 [01:26<01:12, 684.35 examples/s]
Map:  57%|█████▋    | 65548/114105 [01:28<00:59, 811.91 examples/s]
Map:  56%|█████▌    | 63370/114105 [01:26<01:06, 763.96 examples/s]
Map:  56%|█████▋    | 64252/114105 [01:27<01:08, 729.11 examples/s]
Map:  56%|█████▌    | 64000/114105 [01:27<01:18, 639.29 examples/s]
Map:  58%|█████▊    | 65668/114105 [01:28<01:00, 805.55 examples/s]
Map:  56%|█████▌    | 63450/114105 [01:26<01:05, 772.38 examples/s]
Map:  56%|█████▋    | 64334/114105 [01:27<01:06, 745.04 examples/s]
Map:  56%|█████▌    | 64082/114105 [01:27<01:13, 676.38 examples/s]
Map:  58%|█████▊    | 65756/114105 [01:28<00:58, 820.81 examples/s]
Map:  56%|█████▌    | 63533/114105 [01:27<01:04, 785.33 examples/s]
Map:  56%|█████▋    | 64419/114105 [01:27<01:04, 770.51 examples/s]
Map:  56%|█████▌    | 64162/114105 [01:27<01:10, 703.67 examples/s]
Map:  58%|█████▊    | 65844/114105 [01:28<00:57, 833.49 examples/s]
Map:  56%|█████▌    | 63618/114105 [01:27<01:03, 800.42 examples/s]
Map:  57%|█████▋    | 64504/114105 [01:27<01:02, 789.35 examples/s]
Map:  56%|█████▋    | 64246/114105 [01:27<01:07, 735.67 examples/s]
Map:  58%|█████▊    | 65931/114105 [01:28<00:57, 840.57 examples/s]
Map:  56%|█████▌    | 63701/114105 [01:27<01:02, 805.68 examples/s]
Map:  57%|█████▋    | 64589/114105 [01:27<01:01, 801.52 examples/s]
Map:  56%|█████▋    | 64330/114105 [01:27<01:05, 760.94 examples/s]
Map:  56%|█████▌    | 63825/114105 [01:27<01:02, 810.84 examples/s]
Map:  57%|█████▋    | 64710/114105 [01:27<01:01, 799.32 examples/s]
Map:  56%|█████▋    | 64448/114105 [01:27<01:04, 767.24 examples/s]
Map:  58%|█████▊    | 66044/114105 [01:28<01:12, 660.71 examples/s]
Map:  56%|█████▌    | 63907/114105 [01:27<01:01, 812.10 examples/s]
Map:  57%|█████▋    | 64793/114105 [01:27<01:01, 803.36 examples/s]
Map:  57%|█████▋    | 64527/114105 [01:27<01:04, 770.22 examples/s]
Map:  58%|█████▊    | 66128/114105 [01:28<01:08, 698.26 examples/s]
Map:  56%|█████▌    | 63990/114105 [01:27<01:01, 815.49 examples/s]
Map:  57%|█████▋    | 64878/114105 [01:27<01:00, 814.87 examples/s]
Map:  57%|█████▋    | 64607/114105 [01:27<01:03, 776.48 examples/s]
Map:  58%|█████▊    | 66214/114105 [01:28<01:05, 735.04 examples/s]
Map:  57%|█████▋    | 64962/114105 [01:27<00:59, 819.58 examples/s]
Map:  57%|█████▋    | 64688/114105 [01:28<01:03, 783.24 examples/s]
Map:  58%|█████▊    | 66302/114105 [01:29<01:02, 768.21 examples/s]
Map:  56%|█████▌    | 64075/114105 [01:27<01:21, 613.96 examples/s]
Map:  57%|█████▋    | 64769/114105 [01:28<01:02, 788.34 examples/s]
Map:  56%|█████▌    | 64155/114105 [01:27<01:16, 655.75 examples/s]
Map:  58%|█████▊    | 66425/114105 [01:29<01:00, 782.87 examples/s]
Map:  57%|█████▋    | 65082/114105 [01:28<01:16, 639.44 examples/s]
Map:  57%|█████▋    | 64889/114105 [01:28<01:02, 790.08 examples/s]
Map:  56%|█████▋    | 64242/114105 [01:27<01:10, 704.47 examples/s]
Map:  58%|█████▊    | 66511/114105 [01:29<00:59, 800.26 examples/s]
Map:  57%|█████▋    | 65167/114105 [01:28<01:11, 683.28 examples/s]
Map:  57%|█████▋    | 64974/114105 [01:28<01:01, 803.61 examples/s]
Map:  56%|█████▋    | 64327/114105 [01:28<01:07, 739.17 examples/s]
Map:  58%|█████▊    | 66633/114105 [01:29<00:59, 803.00 examples/s]
Map:  57%|█████▋    | 65249/114105 [01:28<01:08, 714.14 examples/s]
Map:  56%|█████▋    | 64407/114105 [01:28<01:05, 754.96 examples/s]
Map:  57%|█████▋    | 65334/114105 [01:28<01:05, 745.70 examples/s]
Map:  57%|█████▋    | 64487/114105 [01:28<01:04, 764.61 examples/s]
Map:  59%|█████▊    | 66754/114105 [01:29<00:59, 797.73 examples/s]
Map:  57%|█████▋    | 65079/114105 [01:28<01:16, 637.28 examples/s]
Map:  57%|█████▋    | 65415/114105 [01:28<01:04, 759.54 examples/s]
Map:  57%|█████▋    | 64570/114105 [01:28<01:03, 778.13 examples/s]
Map:  59%|█████▊    | 66838/114105 [01:29<00:58, 804.49 examples/s]
Map:  57%|█████▋    | 65161/114105 [01:28<01:12, 673.30 examples/s]
Map:  57%|█████▋    | 65497/114105 [01:28<01:02, 775.47 examples/s]
Map:  57%|█████▋    | 64656/114105 [01:28<01:01, 797.69 examples/s]
Map:  59%|█████▊    | 66924/114105 [01:29<00:57, 818.30 examples/s]
Map:  57%|█████▋    | 65578/114105 [01:28<01:01, 783.17 examples/s]
Map:  57%|█████▋    | 65268/114105 [01:28<01:11, 685.07 examples/s]
Map:  57%|█████▋    | 64738/114105 [01:28<01:01, 801.59 examples/s]
Map:  58%|█████▊    | 65660/114105 [01:28<01:01, 792.17 examples/s]
Map:  57%|█████▋    | 65348/114105 [01:29<01:08, 709.04 examples/s]
Map:  57%|█████▋    | 64820/114105 [01:28<01:01, 803.27 examples/s]
Map:  59%|█████▉    | 67043/114105 [01:30<01:10, 667.47 examples/s]
Map:  58%|█████▊    | 65741/114105 [01:28<01:00, 793.25 examples/s]
Map:  57%|█████▋    | 65431/114105 [01:29<01:05, 738.88 examples/s]
Map:  57%|█████▋    | 64903/114105 [01:28<01:00, 809.25 examples/s]
Map:  59%|█████▉    | 67127/114105 [01:30<01:06, 703.03 examples/s]
Map:  58%|█████▊    | 65824/114105 [01:29<01:00, 801.57 examples/s]
Map:  57%|█████▋    | 65515/114105 [01:29<01:03, 761.80 examples/s]
Map:  57%|█████▋    | 64987/114105 [01:28<01:00, 814.80 examples/s]
Map:  59%|█████▉    | 67215/114105 [01:30<01:03, 743.04 examples/s]
Map:  58%|█████▊    | 65907/114105 [01:29<00:59, 806.53 examples/s]
Map:  57%|█████▋    | 65595/114105 [01:29<01:03, 768.48 examples/s]
Map:  59%|█████▉    | 67301/114105 [01:30<01:00, 770.87 examples/s]
Map:  58%|█████▊    | 65992/114105 [01:29<00:58, 817.84 examples/s]
Map:  58%|█████▊    | 65682/114105 [01:29<01:00, 794.79 examples/s]
Map:  57%|█████▋    | 65076/114105 [01:29<01:20, 611.10 examples/s]
Map:  59%|█████▉    | 67416/114105 [01:30<01:01, 763.96 examples/s]
Map:  58%|█████▊    | 65799/114105 [01:29<01:01, 785.54 examples/s]
Map:  57%|█████▋    | 65154/114105 [01:29<01:15, 649.75 examples/s]
Map:  58%|█████▊    | 66080/114105 [01:29<01:21, 592.51 examples/s]
Map:  58%|█████▊    | 65885/114105 [01:29<01:00, 801.21 examples/s]
Map:  57%|█████▋    | 65238/114105 [01:29<01:10, 695.00 examples/s]
Map:  59%|█████▉    | 67537/114105 [01:30<00:59, 776.18 examples/s]
Map:  58%|█████▊    | 66168/114105 [01:29<01:12, 656.77 examples/s]
Map:  57%|█████▋    | 65319/114105 [01:29<01:07, 723.57 examples/s]
Map:  59%|█████▉    | 67654/114105 [01:30<00:59, 774.66 examples/s]
Map:  58%|█████▊    | 66251/114105 [01:29<01:08, 697.30 examples/s]
Map:  57%|█████▋    | 65402/114105 [01:29<01:05, 749.19 examples/s]
Map:  58%|█████▊    | 66000/114105 [01:29<01:14, 647.24 examples/s]
Map:  59%|█████▉    | 67738/114105 [01:30<00:58, 789.20 examples/s]
Map:  58%|█████▊    | 66335/114105 [01:29<01:05, 732.72 examples/s]
Map:  57%|█████▋    | 65484/114105 [01:29<01:03, 768.53 examples/s]
Map:  58%|█████▊    | 66083/114105 [01:30<01:10, 684.61 examples/s]
Map:  59%|█████▉    | 67826/114105 [01:30<00:57, 809.96 examples/s]
Map:  58%|█████▊    | 66422/114105 [01:29<01:02, 764.93 examples/s]
Map:  57%|█████▋    | 65565/114105 [01:29<01:02, 779.05 examples/s]
Map:  58%|█████▊    | 66168/114105 [01:30<01:06, 719.96 examples/s]
Map:  60%|█████▉    | 67910/114105 [01:31<00:56, 815.87 examples/s]
Map:  58%|█████▊    | 66509/114105 [01:29<01:00, 792.68 examples/s]
Map:  58%|█████▊    | 65655/114105 [01:29<00:59, 808.73 examples/s]
Map:  58%|█████▊    | 66252/114105 [01:30<01:04, 746.27 examples/s]
Map:  60%|█████▉    | 67994/114105 [01:31<00:56, 819.56 examples/s]
Map:  58%|█████▊    | 66596/114105 [01:30<00:58, 812.21 examples/s]
Map:  58%|█████▊    | 66340/114105 [01:30<01:01, 778.62 examples/s]
Map:  58%|█████▊    | 65774/114105 [01:29<01:00, 799.36 examples/s]
Map:  58%|█████▊    | 66685/114105 [01:30<00:56, 832.25 examples/s]
Map:  58%|█████▊    | 66424/114105 [01:30<01:00, 791.39 examples/s]
Map:  60%|█████▉    | 68078/114105 [01:31<01:13, 628.83 examples/s]
Map:  58%|█████▊    | 65891/114105 [01:30<01:00, 790.41 examples/s]
Map:  59%|█████▊    | 66804/114105 [01:30<00:57, 816.43 examples/s]
Map:  58%|█████▊    | 66513/114105 [01:30<00:58, 814.11 examples/s]
Map:  60%|█████▉    | 68168/114105 [01:31<01:06, 691.67 examples/s]
Map:  58%|█████▊    | 65972/114105 [01:30<01:00, 794.53 examples/s]
Map:  59%|█████▊    | 66924/114105 [01:30<00:58, 808.42 examples/s]
Map:  60%|█████▉    | 68250/114105 [01:31<01:03, 720.54 examples/s]
Map:  58%|█████▊    | 66634/114105 [01:30<00:58, 807.64 examples/s]
Map:  60%|█████▉    | 68337/114105 [01:31<01:00, 757.32 examples/s]
Map:  59%|█████▊    | 66758/114105 [01:30<00:58, 811.94 examples/s]
Map:  58%|█████▊    | 66081/114105 [01:30<01:15, 635.21 examples/s]
Map:  60%|█████▉    | 68421/114105 [01:31<00:58, 776.01 examples/s]
Map:  59%|█████▉    | 67039/114105 [01:30<01:13, 638.96 examples/s]
Map:  58%|█████▊    | 66162/114105 [01:30<01:11, 670.67 examples/s]
Map:  60%|██████    | 68506/114105 [01:31<00:57, 795.16 examples/s]
Map:  59%|█████▊    | 66881/114105 [01:30<00:58, 809.11 examples/s]
Map:  59%|█████▉    | 67122/114105 [01:30<01:09, 675.80 examples/s]
Map:  58%|█████▊    | 66242/114105 [01:30<01:08, 699.43 examples/s]
Map:  60%|██████    | 68596/114105 [01:32<00:55, 823.12 examples/s]
Map:  59%|█████▉    | 67204/114105 [01:30<01:06, 705.05 examples/s]
Map:  58%|█████▊    | 66326/114105 [01:30<01:05, 732.08 examples/s]
Map:  60%|██████    | 68681/114105 [01:32<00:54, 828.31 examples/s]
Map:  59%|█████▉    | 67287/114105 [01:31<01:04, 731.45 examples/s]
Map:  59%|█████▊    | 67000/114105 [01:31<01:10, 667.16 examples/s]
Map:  58%|█████▊    | 66408/114105 [01:30<01:03, 752.30 examples/s]
Map:  60%|██████    | 68808/114105 [01:32<00:54, 831.26 examples/s]
Map:  59%|█████▉    | 67368/114105 [01:31<01:02, 748.56 examples/s]
Map:  59%|█████▉    | 67082/114105 [01:31<01:07, 697.22 examples/s]
Map:  58%|█████▊    | 66489/114105 [01:30<01:02, 762.73 examples/s]
Map:  60%|██████    | 68895/114105 [01:32<00:53, 839.34 examples/s]
Map:  59%|█████▉    | 67449/114105 [01:31<01:01, 763.32 examples/s]
Map:  59%|█████▉    | 67164/114105 [01:31<01:04, 723.28 examples/s]
Map:  58%|█████▊    | 66570/114105 [01:31<01:01, 772.81 examples/s]
Map:  59%|█████▉    | 67536/114105 [01:31<00:59, 789.04 examples/s]
Map:  59%|█████▉    | 67246/114105 [01:31<01:02, 744.37 examples/s]
Map:  58%|█████▊    | 66652/114105 [01:31<01:00, 782.04 examples/s]
Map:  59%|█████▉    | 67331/114105 [01:31<01:00, 768.93 examples/s]
Map:  59%|█████▉    | 67622/114105 [01:31<00:57, 803.85 examples/s]
Map:  60%|██████    | 69000/114105 [01:32<01:08, 661.98 examples/s]
Map:  59%|█████▊    | 66772/114105 [01:31<01:00, 783.38 examples/s]
Map:  59%|█████▉    | 67413/114105 [01:31<00:59, 779.93 examples/s]
Map:  59%|█████▉    | 67710/114105 [01:31<00:56, 820.21 examples/s]
Map:  61%|██████    | 69084/114105 [01:32<01:04, 700.00 examples/s]
Map:  59%|█████▉    | 67497/114105 [01:31<00:58, 793.69 examples/s]
Map:  59%|█████▊    | 66889/114105 [01:31<01:00, 779.85 examples/s]
Map:  61%|██████    | 69167/114105 [01:32<01:01, 728.65 examples/s]
Map:  59%|█████▉    | 67839/114105 [01:31<00:55, 830.50 examples/s]
Map:  59%|█████▉    | 67580/114105 [01:31<00:58, 800.90 examples/s]
Map:  59%|█████▊    | 66973/114105 [01:31<00:59, 793.71 examples/s]
Map:  61%|██████    | 69250/114105 [01:32<00:59, 751.09 examples/s]
Map:  60%|█████▉    | 67958/114105 [01:31<00:56, 814.74 examples/s]
Map:  61%|██████    | 69338/114105 [01:32<00:57, 781.35 examples/s]
Map:  59%|█████▉    | 67698/114105 [01:32<00:58, 792.64 examples/s]
Map:  59%|█████▉    | 67075/114105 [01:31<01:15, 620.96 examples/s]
Map:  61%|██████    | 69452/114105 [01:33<00:57, 771.16 examples/s]
Map:  59%|█████▉    | 67807/114105 [01:32<01:00, 766.27 examples/s]
Map:  59%|█████▉    | 67159/114105 [01:31<01:10, 666.91 examples/s]
Map:  61%|██████    | 69534/114105 [01:33<00:57, 781.85 examples/s]
Map:  60%|█████▉    | 68084/114105 [01:32<01:11, 643.81 examples/s]
Map:  59%|█████▉    | 67888/114105 [01:32<00:59, 775.66 examples/s]
Map:  59%|█████▉    | 67239/114105 [01:32<01:07, 694.25 examples/s]
Map:  61%|██████    | 69618/114105 [01:33<00:55, 795.93 examples/s]
Map:  60%|█████▉    | 68169/114105 [01:32<01:07, 682.91 examples/s]
Map:  59%|█████▉    | 67323/114105 [01:32<01:04, 728.91 examples/s]
Map:  61%|██████    | 69709/114105 [01:33<00:53, 822.51 examples/s]
Map:  60%|█████▉    | 68254/114105 [01:32<01:04, 716.33 examples/s]
Map:  60%|█████▉    | 68000/114105 [01:32<01:13, 625.30 examples/s]
Map:  59%|█████▉    | 67403/114105 [01:32<01:02, 745.49 examples/s]
Map:  61%|██████    | 69793/114105 [01:33<00:53, 825.67 examples/s]
Map:  60%|█████▉    | 68333/114105 [01:32<01:02, 732.80 examples/s]
Map:  60%|█████▉    | 68080/114105 [01:32<01:09, 661.00 examples/s]
Map:  59%|█████▉    | 67486/114105 [01:32<01:00, 766.54 examples/s]
Map:  60%|█████▉    | 68418/114105 [01:32<01:00, 761.35 examples/s]
Map:  61%|██████▏   | 69918/114105 [01:33<00:53, 825.49 examples/s]
Map:  60%|█████▉    | 68161/114105 [01:32<01:06, 692.35 examples/s]
Map:  59%|█████▉    | 67569/114105 [01:32<00:59, 780.87 examples/s]
Map:  60%|██████    | 68502/114105 [01:32<00:58, 780.33 examples/s]
Map:  60%|█████▉    | 68241/114105 [01:32<01:04, 716.19 examples/s]
Map:  59%|█████▉    | 67656/114105 [01:32<00:57, 804.77 examples/s]
Map:  60%|██████    | 68584/114105 [01:32<00:57, 787.44 examples/s]
Map:  60%|█████▉    | 68325/114105 [01:33<01:01, 747.31 examples/s]
Map:  61%|██████▏   | 70040/114105 [01:33<01:06, 663.09 examples/s]
Map:  60%|██████    | 68669/114105 [01:32<00:56, 803.47 examples/s]
Map:  59%|█████▉    | 67774/114105 [01:32<00:58, 791.98 examples/s]
Map:  61%|██████▏   | 70127/114105 [01:34<01:02, 705.70 examples/s]
Map:  60%|██████    | 68751/114105 [01:32<00:56, 800.32 examples/s]
Map:  60%|█████▉    | 68442/114105 [01:33<01:00, 756.94 examples/s]
Map:  59%|█████▉    | 67860/114105 [01:32<00:57, 807.50 examples/s]
Map:  62%|██████▏   | 70215/114105 [01:34<00:58, 744.44 examples/s]
Map:  60%|██████    | 68833/114105 [01:33<00:56, 802.84 examples/s]
Map:  60%|██████    | 68522/114105 [01:33<00:59, 767.07 examples/s]
Map:  60%|█████▉    | 67981/114105 [01:32<00:57, 802.77 examples/s]
Map:  62%|██████▏   | 70298/114105 [01:34<00:57, 762.34 examples/s]
Map:  60%|██████    | 68917/114105 [01:33<00:55, 808.59 examples/s]
Map:  60%|██████    | 68606/114105 [01:33<00:58, 783.18 examples/s]
Map:  62%|██████▏   | 70384/114105 [01:34<00:55, 784.82 examples/s]
Map:  60%|██████    | 68691/114105 [01:33<00:56, 799.79 examples/s]
Map:  62%|██████▏   | 70467/114105 [01:34<00:55, 793.09 examples/s]
Map:  60%|█████▉    | 68080/114105 [01:33<01:12, 632.90 examples/s]
Map:  60%|██████    | 69000/114105 [01:33<01:15, 598.30 examples/s]
Map:  60%|██████    | 68802/114105 [01:33<00:58, 774.00 examples/s]
Map:  60%|█████▉    | 68155/114105 [01:33<01:09, 656.56 examples/s]
Map:  61%|██████    | 69078/114105 [01:33<01:10, 640.13 examples/s]
Map:  62%|██████▏   | 70584/114105 [01:34<00:55, 785.14 examples/s]
Map:  60%|██████    | 68882/114105 [01:33<00:58, 778.82 examples/s]
Map:  60%|█████▉    | 68235/114105 [01:33<01:06, 688.86 examples/s]
Map:  61%|██████    | 69159/114105 [01:33<01:06, 680.93 examples/s]
Map:  62%|██████▏   | 70667/114105 [01:34<00:54, 794.42 examples/s]
Map:  60%|██████    | 68961/114105 [01:33<00:57, 781.02 examples/s]
Map:  60%|█████▉    | 68319/114105 [01:33<01:03, 725.46 examples/s]
Map:  61%|██████    | 69239/114105 [01:33<01:03, 709.36 examples/s]
Map:  62%|██████▏   | 70749/114105 [01:34<00:54, 798.71 examples/s]
Map:  60%|█████▉    | 68407/114105 [01:33<00:59, 761.98 examples/s]
Map:  61%|██████    | 69320/114105 [01:33<01:00, 734.91 examples/s]
Map:  62%|██████▏   | 70835/114105 [01:34<00:53, 811.22 examples/s]
Map:  61%|██████    | 69041/114105 [01:34<01:13, 613.78 examples/s]
Map:  60%|██████    | 68490/114105 [01:33<00:58, 776.86 examples/s]
Map:  61%|██████    | 69405/114105 [01:33<00:58, 763.64 examples/s]
Map:  62%|██████▏   | 70920/114105 [01:35<00:52, 818.55 examples/s]
Map:  61%|██████    | 69126/114105 [01:34<01:07, 667.52 examples/s]
Map:  60%|██████    | 68572/114105 [01:33<00:57, 787.35 examples/s]
Map:  61%|██████    | 69484/114105 [01:33<00:58, 767.04 examples/s]
Map:  61%|██████    | 69211/114105 [01:34<01:03, 712.53 examples/s]
Map:  60%|██████    | 68656/114105 [01:33<00:56, 798.70 examples/s]
Map:  61%|██████    | 69568/114105 [01:34<00:56, 785.02 examples/s]
Map:  61%|██████    | 69293/114105 [01:34<01:00, 739.86 examples/s]
Map:  62%|██████▏   | 71041/114105 [01:35<01:05, 657.32 examples/s]
Map:  60%|██████    | 68740/114105 [01:33<00:56, 806.70 examples/s]
Map:  61%|██████    | 69649/114105 [01:34<00:56, 790.62 examples/s]
Map:  61%|██████    | 69378/114105 [01:34<00:58, 769.31 examples/s]
Map:  62%|██████▏   | 71130/114105 [01:35<01:00, 707.95 examples/s]
Map:  60%|██████    | 68825/114105 [01:34<00:55, 818.62 examples/s]
Map:  61%|██████    | 69734/114105 [01:34<00:55, 806.61 examples/s]
Map:  62%|██████▏   | 71216/114105 [01:35<00:57, 741.80 examples/s]
Map:  60%|██████    | 68909/114105 [01:34<00:55, 820.63 examples/s]
Map:  61%|██████    | 69504/114105 [01:34<00:56, 793.23 examples/s]
Map:  61%|██████    | 69818/114105 [01:34<00:54, 811.35 examples/s]
Map:  62%|██████▏   | 71297/114105 [01:35<00:56, 757.09 examples/s]
Map:  61%|██████    | 69586/114105 [01:34<00:55, 798.80 examples/s]
Map:  61%|██████▏   | 69904/114105 [01:34<00:53, 821.58 examples/s]
Map:  63%|██████▎   | 71385/114105 [01:35<00:54, 787.05 examples/s]
Map:  61%|██████    | 69668/114105 [01:34<00:55, 801.61 examples/s]
Map:  60%|██████    | 69000/114105 [01:34<01:11, 630.73 examples/s]
Map:  61%|██████▏   | 69992/114105 [01:34<00:52, 832.39 examples/s]
Map:  61%|██████    | 69751/114105 [01:34<00:55, 806.22 examples/s]
Map:  61%|██████    | 69080/114105 [01:34<01:07, 669.68 examples/s]
Map:  63%|██████▎   | 71509/114105 [01:35<00:53, 797.95 examples/s]
Map:  61%|██████    | 69159/114105 [01:34<01:04, 696.06 examples/s]
Map:  61%|██████    | 69864/114105 [01:35<00:56, 782.78 examples/s]
Map:  63%|██████▎   | 71627/114105 [01:35<00:53, 790.28 examples/s]
Map:  61%|██████▏   | 70116/114105 [01:34<01:10, 628.02 examples/s]
Map:  61%|██████    | 69240/114105 [01:34<01:01, 723.92 examples/s]
Map:  61%|██████▏   | 69952/114105 [01:35<00:54, 804.10 examples/s]
Map:  63%|██████▎   | 71712/114105 [01:36<00:52, 802.37 examples/s]
Map:  62%|██████▏   | 70198/114105 [01:34<01:05, 668.83 examples/s]
Map:  61%|██████    | 69323/114105 [01:34<00:59, 751.68 examples/s]
Map:  63%|██████▎   | 71796/114105 [01:36<00:52, 807.97 examples/s]
Map:  62%|██████▏   | 70282/114105 [01:35<01:01, 708.10 examples/s]
Map:  61%|██████    | 69402/114105 [01:34<00:58, 759.67 examples/s]
Map:  61%|██████▏   | 70042/114105 [01:35<01:08, 645.62 examples/s]
Map:  63%|██████▎   | 71882/114105 [01:36<00:51, 819.35 examples/s]
Map:  62%|██████▏   | 70364/114105 [01:35<00:59, 733.86 examples/s]
Map:  61%|██████    | 69484/114105 [01:35<00:57, 773.47 examples/s]
Map:  61%|██████▏   | 70125/114105 [01:35<01:04, 685.55 examples/s]
Map:  63%|██████▎   | 71965/114105 [01:36<00:51, 818.92 examples/s]
Map:  62%|██████▏   | 70449/114105 [01:35<00:57, 762.24 examples/s]
Map:  61%|██████    | 69567/114105 [01:35<00:56, 785.18 examples/s]
Map:  62%|██████▏   | 70207/114105 [01:35<01:01, 716.26 examples/s]
Map:  62%|██████▏   | 70536/114105 [01:35<00:55, 787.71 examples/s]
Map:  61%|██████    | 69653/114105 [01:35<00:55, 803.86 examples/s]
Map:  62%|██████▏   | 70292/114105 [01:35<00:58, 750.24 examples/s]
Map:  63%|██████▎   | 72087/114105 [01:36<01:03, 657.59 examples/s]
Map:  62%|██████▏   | 70658/114105 [01:35<00:54, 793.97 examples/s]
Map:  62%|██████▏   | 70373/114105 [01:35<00:57, 764.33 examples/s]
Map:  61%|██████    | 69772/114105 [01:35<00:55, 794.32 examples/s]
Map:  63%|██████▎   | 72171/114105 [01:36<01:00, 695.62 examples/s]
Map:  62%|██████▏   | 70453/114105 [01:35<00:56, 771.98 examples/s]
Map:  61%|██████    | 69857/114105 [01:35<00:54, 806.58 examples/s]
Map:  62%|██████▏   | 70781/114105 [01:35<00:54, 800.56 examples/s]
Map:  63%|██████▎   | 72253/114105 [01:36<00:57, 724.51 examples/s]
Map:  62%|██████▏   | 70537/114105 [01:35<00:55, 789.15 examples/s]
Map:  62%|██████▏   | 70863/114105 [01:35<00:53, 801.08 examples/s]
Map:  61%|██████▏   | 69978/114105 [01:35<00:55, 800.53 examples/s]
Map:  63%|██████▎   | 72334/114105 [01:36<00:56, 743.90 examples/s]
Map:  62%|██████▏   | 70620/114105 [01:36<00:54, 796.98 examples/s]
Map:  62%|██████▏   | 70975/114105 [01:35<00:55, 778.33 examples/s]
Map:  63%|██████▎   | 72450/114105 [01:37<00:55, 749.40 examples/s]
Map:  62%|██████▏   | 70730/114105 [01:36<00:56, 770.53 examples/s]
Map:  61%|██████▏   | 70080/114105 [01:35<01:10, 620.96 examples/s]
Map:  64%|██████▎   | 72533/114105 [01:37<00:54, 766.33 examples/s]
Map:  62%|██████▏   | 70816/114105 [01:36<00:54, 791.15 examples/s]
Map:  61%|██████▏   | 70163/114105 [01:35<01:06, 662.78 examples/s]
Map:  64%|██████▎   | 72621/114105 [01:37<00:52, 793.21 examples/s]
Map:  62%|██████▏   | 71089/114105 [01:36<01:07, 639.52 examples/s]
Map:  62%|██████▏   | 70899/114105 [01:36<00:53, 800.36 examples/s]
Map:  62%|██████▏   | 70251/114105 [01:36<01:01, 710.04 examples/s]
Map:  62%|██████▏   | 71176/114105 [01:36<01:02, 685.93 examples/s]
Map:  64%|██████▎   | 72708/114105 [01:37<00:51, 810.29 examples/s]
Map:  62%|██████▏   | 70980/114105 [01:36<00:53, 799.76 examples/s]
Map:  62%|██████▏   | 70334/114105 [01:36<00:59, 735.15 examples/s]
Map:  62%|██████▏   | 71257/114105 [01:36<01:00, 711.92 examples/s]
Map:  64%|██████▍   | 72830/114105 [01:37<00:51, 808.70 examples/s]
Map:  62%|██████▏   | 70416/114105 [01:36<00:57, 754.71 examples/s]
Map:  63%|██████▎   | 71342/114105 [01:36<00:57, 742.59 examples/s]
Map:  62%|██████▏   | 71082/114105 [01:36<01:07, 635.54 examples/s]
Map:  64%|██████▍   | 72915/114105 [01:37<00:50, 817.98 examples/s]
Map:  62%|██████▏   | 70500/114105 [01:36<00:56, 776.26 examples/s]
Map:  63%|██████▎   | 71423/114105 [01:36<00:56, 759.47 examples/s]
Map:  62%|██████▏   | 71169/114105 [01:36<01:02, 688.18 examples/s]
Map:  64%|██████▍   | 72999/114105 [01:37<00:50, 821.42 examples/s]
Map:  62%|██████▏   | 70587/114105 [01:36<00:54, 798.01 examples/s]
Map:  63%|██████▎   | 71510/114105 [01:36<00:54, 784.48 examples/s]
Map:  62%|██████▏   | 71255/114105 [01:36<00:58, 726.92 examples/s]
Map:  62%|██████▏   | 70701/114105 [01:36<00:55, 779.93 examples/s]
Map:  63%|██████▎   | 71342/114105 [01:37<00:56, 762.72 examples/s]
Map:  64%|██████▍   | 73088/114105 [01:37<01:02, 653.35 examples/s]
Map:  63%|██████▎   | 71631/114105 [01:36<00:54, 784.72 examples/s]
Map:  62%|██████▏   | 70784/114105 [01:36<00:54, 790.61 examples/s]
Map:  63%|██████▎   | 71430/114105 [01:37<00:53, 792.07 examples/s]
Map:  64%|██████▍   | 73170/114105 [01:38<00:59, 691.12 examples/s]
Map:  63%|██████▎   | 71714/114105 [01:36<00:53, 790.81 examples/s]
Map:  62%|██████▏   | 70866/114105 [01:36<00:54, 797.56 examples/s]
Map:  64%|██████▍   | 73250/114105 [01:38<00:57, 715.41 examples/s]
Map:  63%|██████▎   | 71797/114105 [01:37<00:52, 799.76 examples/s]
Map:  63%|██████▎   | 71549/114105 [01:37<00:53, 790.06 examples/s]
Map:  64%|██████▍   | 73329/114105 [01:38<00:55, 730.17 examples/s]
Map:  62%|██████▏   | 70978/114105 [01:36<00:55, 777.14 examples/s]
Map:  63%|██████▎   | 71916/114105 [01:37<00:53, 795.33 examples/s]
Map:  63%|██████▎   | 71664/114105 [01:37<00:54, 777.97 examples/s]
Map:  64%|██████▍   | 73415/114105 [01:38<00:53, 764.27 examples/s]
Map:  63%|██████▎   | 71997/114105 [01:37<00:52, 796.09 examples/s]
Map:  63%|██████▎   | 71748/114105 [01:37<00:53, 789.53 examples/s]
Map:  64%|██████▍   | 73496/114105 [01:38<00:52, 771.43 examples/s]
Map:  62%|██████▏   | 71085/114105 [01:37<01:08, 629.86 examples/s]
Map:  63%|██████▎   | 71832/114105 [01:37<00:52, 800.94 examples/s]
Map:  64%|██████▍   | 73579/114105 [01:38<00:51, 784.57 examples/s]
Map:  63%|██████▎   | 72084/114105 [01:37<01:07, 623.47 examples/s]
Map:  62%|██████▏   | 71169/114105 [01:37<01:03, 673.62 examples/s]
Map:  63%|██████▎   | 71916/114105 [01:37<00:52, 810.48 examples/s]
Map:  65%|██████▍   | 73661/114105 [01:38<00:51, 791.56 examples/s]
Map:  63%|██████▎   | 72167/114105 [01:37<01:02, 668.83 examples/s]
Map:  62%|██████▏   | 71248/114105 [01:37<01:01, 700.80 examples/s]
Map:  65%|██████▍   | 73745/114105 [01:38<00:50, 804.08 examples/s]
Map:  63%|██████▎   | 72251/114105 [01:37<00:59, 706.33 examples/s]
Map:  63%|██████▎   | 71334/114105 [01:37<00:58, 736.07 examples/s]
Map:  63%|██████▎   | 72000/114105 [01:37<01:05, 640.38 examples/s]
Map:  65%|██████▍   | 73832/114105 [01:38<00:49, 819.38 examples/s]
Map:  63%|██████▎   | 72341/114105 [01:37<00:55, 754.48 examples/s]
Map:  63%|██████▎   | 71417/114105 [01:37<00:56, 759.05 examples/s]
Map:  63%|██████▎   | 72080/114105 [01:38<01:02, 674.48 examples/s]
Map:  65%|██████▍   | 73953/114105 [01:39<00:49, 810.12 examples/s]
Map:  63%|██████▎   | 72423/114105 [01:37<00:54, 771.45 examples/s]
Map:  63%|██████▎   | 71498/114105 [01:37<00:55, 771.78 examples/s]
Map:  63%|██████▎   | 72163/114105 [01:38<00:58, 710.96 examples/s]
Map:  64%|██████▎   | 72507/114105 [01:38<00:52, 788.95 examples/s]
Map:  63%|██████▎   | 72250/114105 [01:38<00:55, 751.23 examples/s]
Map:  63%|██████▎   | 71616/114105 [01:37<00:54, 773.67 examples/s]
Map:  64%|██████▎   | 72594/114105 [01:38<00:51, 809.41 examples/s]
Map:  65%|██████▍   | 74044/114105 [01:39<01:03, 635.77 examples/s]
Map:  63%|██████▎   | 71703/114105 [01:37<00:53, 794.56 examples/s]
Map:  63%|██████▎   | 72372/114105 [01:38<00:54, 767.80 examples/s]
Map:  64%|██████▎   | 72682/114105 [01:38<00:50, 827.43 examples/s]
Map:  65%|██████▍   | 74129/114105 [01:39<00:58, 681.49 examples/s]
Map:  63%|██████▎   | 71814/114105 [01:38<00:54, 772.12 examples/s]
Map:  65%|██████▌   | 74204/114105 [01:39<00:57, 693.96 examples/s]
Map:  64%|██████▎   | 72483/114105 [01:38<00:55, 754.68 examples/s]
Map:  64%|██████▍   | 72795/114105 [01:38<00:51, 797.10 examples/s]
Map:  63%|██████▎   | 71895/114105 [01:38<00:54, 776.99 examples/s]
Map:  65%|██████▌   | 74294/114105 [01:39<00:53, 744.71 examples/s]
Map:  64%|██████▎   | 72561/114105 [01:38<00:54, 757.25 examples/s]
Map:  64%|██████▍   | 72877/114105 [01:38<00:51, 801.67 examples/s]
Map:  63%|██████▎   | 71978/114105 [01:38<00:53, 788.49 examples/s]
Map:  65%|██████▌   | 74375/114105 [01:39<00:52, 761.64 examples/s]
Map:  64%|██████▎   | 72645/114105 [01:38<00:53, 772.52 examples/s]
Map:  64%|██████▍   | 72959/114105 [01:38<00:51, 804.28 examples/s]
Map:  65%|██████▌   | 74462/114105 [01:39<00:50, 786.93 examples/s]
Map:  64%|██████▎   | 72730/114105 [01:38<00:52, 790.10 examples/s]
Map:  63%|██████▎   | 72080/114105 [01:38<01:06, 627.26 examples/s]
Map:  64%|██████▍   | 72811/114105 [01:38<00:51, 794.69 examples/s]
Map:  64%|██████▍   | 73041/114105 [01:38<01:05, 625.85 examples/s]
Map:  65%|██████▌   | 74581/114105 [01:39<00:50, 783.40 examples/s]
Map:  63%|██████▎   | 72164/114105 [01:38<01:02, 671.67 examples/s]
Map:  64%|██████▍   | 72897/114105 [01:39<00:50, 811.37 examples/s]
Map:  64%|██████▍   | 73127/114105 [01:38<01:00, 678.58 examples/s]
Map:  65%|██████▌   | 74662/114105 [01:39<00:50, 787.34 examples/s]
Map:  63%|██████▎   | 72248/114105 [01:38<00:58, 709.81 examples/s]
Map:  64%|██████▍   | 73210/114105 [01:38<00:57, 714.02 examples/s]
Map:  66%|██████▌   | 74744/114105 [01:40<00:49, 793.49 examples/s]
Map:  63%|██████▎   | 72337/114105 [01:38<00:55, 752.48 examples/s]
Map:  64%|██████▍   | 73298/114105 [01:39<00:54, 754.63 examples/s]
Map:  66%|██████▌   | 74830/114105 [01:40<00:48, 810.90 examples/s]
Map:  64%|██████▍   | 73000/114105 [01:39<01:05, 632.34 examples/s]
Map:  63%|██████▎   | 72422/114105 [01:38<00:53, 775.19 examples/s]
Map:  64%|██████▍   | 73384/114105 [01:39<00:52, 781.47 examples/s]
Map:  66%|██████▌   | 74918/114105 [01:40<00:47, 824.97 examples/s]
Map:  64%|██████▍   | 73079/114105 [01:39<01:01, 666.64 examples/s]
Map:  64%|██████▎   | 72506/114105 [01:39<00:52, 789.16 examples/s]
Map:  64%|██████▍   | 73468/114105 [01:39<00:51, 793.56 examples/s]
Map:  64%|██████▍   | 73164/114105 [01:39<00:57, 709.01 examples/s]
Map:  64%|██████▍   | 73551/114105 [01:39<00:50, 799.35 examples/s]
Map:  64%|██████▍   | 73246/114105 [01:39<00:55, 735.55 examples/s]
Map:  64%|██████▎   | 72624/114105 [01:39<00:52, 785.97 examples/s]
Map:  66%|██████▌   | 75040/114105 [01:40<00:59, 655.38 examples/s]
Map:  65%|██████▍   | 73667/114105 [01:39<00:51, 784.41 examples/s]
Map:  66%|██████▌   | 75121/114105 [01:40<00:56, 686.09 examples/s]
Map:  64%|██████▍   | 73362/114105 [01:39<00:54, 742.44 examples/s]
Map:  64%|██████▍   | 72744/114105 [01:39<00:52, 782.43 examples/s]
Map:  65%|██████▍   | 73750/114105 [01:39<00:50, 795.77 examples/s]
Map:  66%|██████▌   | 75205/114105 [01:40<00:53, 721.58 examples/s]
Map:  64%|██████▍   | 73448/114105 [01:39<00:52, 771.42 examples/s]
Map:  64%|██████▍   | 72825/114105 [01:39<00:52, 788.49 examples/s]
Map:  65%|██████▍   | 73832/114105 [01:39<00:50, 800.34 examples/s]
Map:  66%|██████▌   | 75289/114105 [01:40<00:51, 749.39 examples/s]
Map:  64%|██████▍   | 73531/114105 [01:39<00:51, 782.42 examples/s]
Map:  64%|██████▍   | 72909/114105 [01:39<00:51, 801.01 examples/s]
Map:  66%|██████▌   | 75373/114105 [01:40<00:50, 771.93 examples/s]
Map:  64%|██████▍   | 72994/114105 [01:39<00:50, 810.88 examples/s]
Map:  65%|██████▍   | 73955/114105 [01:39<00:49, 804.38 examples/s]
Map:  65%|██████▍   | 73650/114105 [01:40<00:51, 783.20 examples/s]
Map:  66%|██████▌   | 75458/114105 [01:41<00:48, 790.73 examples/s]
Map:  65%|██████▍   | 73734/114105 [01:40<00:50, 796.21 examples/s]
Map:  66%|██████▌   | 75540/114105 [01:41<00:48, 795.10 examples/s]
Map:  64%|██████▍   | 73078/114105 [01:39<01:06, 621.19 examples/s]
Map:  65%|██████▍   | 74041/114105 [01:40<01:03, 634.82 examples/s]
Map:  65%|██████▍   | 73815/114105 [01:40<00:50, 796.51 examples/s]
Map:  64%|██████▍   | 73161/114105 [01:40<01:01, 668.11 examples/s]
Map:  66%|██████▋   | 75660/114105 [01:41<00:48, 793.57 examples/s]
Map:  65%|██████▍   | 74127/114105 [01:40<00:58, 684.57 examples/s]
Map:  65%|██████▍   | 73931/114105 [01:40<00:51, 784.11 examples/s]
Map:  64%|██████▍   | 73247/114105 [01:40<00:57, 712.88 examples/s]
Map:  66%|██████▋   | 75746/114105 [01:41<00:47, 807.47 examples/s]
Map:  65%|██████▌   | 74207/114105 [01:40<00:56, 711.31 examples/s]
Map:  64%|██████▍   | 73333/114105 [01:40<00:54, 750.41 examples/s]
Map:  66%|██████▋   | 75833/114105 [01:41<00:46, 822.64 examples/s]
Map:  65%|██████▌   | 74288/114105 [01:40<00:54, 734.66 examples/s]
Map:  64%|██████▍   | 73414/114105 [01:40<00:53, 762.87 examples/s]
Map:  67%|██████▋   | 75920/114105 [01:41<00:46, 830.02 examples/s]
Map:  65%|██████▍   | 74041/114105 [01:40<01:03, 633.90 examples/s]
Map:  65%|██████▌   | 74370/114105 [01:40<00:52, 756.53 examples/s]
Map:  64%|██████▍   | 73499/114105 [01:40<00:51, 782.49 examples/s]
Map:  65%|██████▍   | 74126/114105 [01:40<00:59, 677.05 examples/s]
Map:  65%|██████▌   | 74458/114105 [01:40<00:50, 787.66 examples/s]
Map:  65%|██████▌   | 74204/114105 [01:40<00:57, 698.06 examples/s]
Map:  65%|██████▌   | 74541/114105 [01:40<00:49, 794.76 examples/s]
Map:  65%|██████▍   | 73623/114105 [01:40<00:50, 794.42 examples/s]
Map:  67%|██████▋   | 76040/114105 [01:41<00:57, 657.22 examples/s]
Map:  65%|██████▌   | 74288/114105 [01:40<00:54, 731.42 examples/s]
Map:  65%|██████▌   | 74622/114105 [01:40<00:49, 796.75 examples/s]
Map:  65%|██████▍   | 73706/114105 [01:40<00:50, 793.73 examples/s]
Map:  67%|██████▋   | 76122/114105 [01:41<00:54, 690.72 examples/s]
Map:  65%|██████▌   | 74374/114105 [01:41<00:52, 760.48 examples/s]
Map:  65%|██████▌   | 74706/114105 [01:40<00:48, 806.35 examples/s]
Map:  65%|██████▍   | 73790/114105 [01:40<00:50, 801.41 examples/s]
Map:  67%|██████▋   | 76204/114105 [01:42<00:52, 718.61 examples/s]
Map:  65%|██████▌   | 74459/114105 [01:41<00:50, 782.02 examples/s]
Map:  66%|██████▌   | 74793/114105 [01:41<00:47, 822.37 examples/s]
Map:  65%|██████▍   | 73877/114105 [01:40<00:49, 818.09 examples/s]
Map:  67%|██████▋   | 76293/114105 [01:42<00:49, 757.74 examples/s]
Map:  66%|██████▌   | 74881/114105 [01:41<00:46, 836.81 examples/s]
Map:  67%|██████▋   | 76374/114105 [01:42<00:49, 767.00 examples/s]
Map:  65%|██████▌   | 74580/114105 [01:41<00:50, 783.49 examples/s]
Map:  65%|██████▍   | 73995/114105 [01:41<00:49, 804.33 examples/s]
Map:  66%|██████▌   | 74967/114105 [01:41<00:46, 840.83 examples/s]
Map:  67%|██████▋   | 76454/114105 [01:42<00:48, 772.22 examples/s]
Map:  65%|██████▌   | 74664/114105 [01:41<00:49, 796.24 examples/s]
Map:  67%|██████▋   | 76536/114105 [01:42<00:47, 784.42 examples/s]
Map:  66%|██████▌   | 74747/114105 [01:41<00:49, 801.52 examples/s]
Map:  65%|██████▍   | 74080/114105 [01:41<01:03, 634.08 examples/s]
Map:  66%|██████▌   | 75085/114105 [01:41<00:59, 659.05 examples/s]
Map:  67%|██████▋   | 76622/114105 [01:42<00:46, 801.90 examples/s]
Map:  66%|██████▌   | 74832/114105 [01:41<00:48, 812.20 examples/s]
Map:  65%|██████▍   | 74162/114105 [01:41<00:59, 674.39 examples/s]
Map:  66%|██████▌   | 75169/114105 [01:41<00:55, 698.03 examples/s]
Map:  67%|██████▋   | 76707/114105 [01:42<00:46, 812.28 examples/s]
Map:  65%|██████▌   | 74242/114105 [01:41<00:56, 703.64 examples/s]
Map:  66%|██████▌   | 74956/114105 [01:41<00:47, 816.28 examples/s]
Map:  66%|██████▌   | 75254/114105 [01:41<00:53, 731.65 examples/s]
Map:  67%|██████▋   | 76791/114105 [01:42<00:45, 819.67 examples/s]
Map:  65%|██████▌   | 74330/114105 [01:41<00:53, 744.24 examples/s]
Map:  66%|██████▌   | 75339/114105 [01:41<00:51, 758.69 examples/s]
Map:  67%|██████▋   | 76878/114105 [01:42<00:44, 831.53 examples/s]
Map:  65%|██████▌   | 74413/114105 [01:41<00:52, 763.23 examples/s]
Map:  66%|██████▌   | 75428/114105 [01:41<00:48, 791.80 examples/s]
Map:  66%|██████▌   | 75082/114105 [01:42<00:59, 657.04 examples/s]
Map:  65%|██████▌   | 74497/114105 [01:41<00:50, 782.44 examples/s]
Map:  66%|██████▌   | 75168/114105 [01:42<00:55, 696.09 examples/s]
Map:  66%|██████▌   | 75550/114105 [01:42<00:48, 794.34 examples/s]
Map:  67%|██████▋   | 77000/114105 [01:43<00:56, 651.20 examples/s]
Map:  65%|██████▌   | 74620/114105 [01:41<00:49, 792.45 examples/s]
Map:  66%|██████▌   | 75251/114105 [01:42<00:53, 722.59 examples/s]
Map:  66%|██████▋   | 75636/114105 [01:42<00:47, 808.03 examples/s]
Map:  68%|██████▊   | 77077/114105 [01:43<00:54, 676.54 examples/s]
Map:  65%|██████▌   | 74706/114105 [01:41<00:48, 807.75 examples/s]
Map:  66%|██████▌   | 75335/114105 [01:42<00:51, 750.01 examples/s]
Map:  68%|██████▊   | 77160/114105 [01:43<00:51, 710.95 examples/s]
Map:  66%|██████▋   | 75758/114105 [01:42<00:47, 804.19 examples/s]
Map:  66%|██████▌   | 74788/114105 [01:42<00:48, 806.78 examples/s]
Map:  66%|██████▌   | 75418/114105 [01:42<00:50, 767.94 examples/s]
Map:  68%|██████▊   | 77245/114105 [01:43<00:49, 741.72 examples/s]
Map:  66%|██████▋   | 75842/114105 [01:42<00:47, 812.08 examples/s]
Map:  66%|██████▌   | 74876/114105 [01:42<00:47, 825.22 examples/s]
Map:  66%|██████▌   | 75502/114105 [01:42<00:49, 784.84 examples/s]
Map:  68%|██████▊   | 77328/114105 [01:43<00:48, 763.90 examples/s]
Map:  66%|██████▌   | 75583/114105 [01:42<00:48, 789.27 examples/s]
Map:  67%|██████▋   | 75968/114105 [01:42<00:46, 814.76 examples/s]
Map:  68%|██████▊   | 77450/114105 [01:43<00:47, 778.70 examples/s]
Map:  66%|██████▋   | 75666/114105 [01:42<00:48, 797.96 examples/s]
Map:  66%|██████▌   | 75000/114105 [01:42<01:00, 650.83 examples/s]
Map:  68%|██████▊   | 77535/114105 [01:43<00:46, 793.61 examples/s]
Map:  66%|██████▋   | 75751/114105 [01:42<00:47, 809.11 examples/s]
Map:  66%|██████▌   | 75081/114105 [01:42<00:56, 685.14 examples/s]
Map:  67%|██████▋   | 76079/114105 [01:42<00:58, 646.86 examples/s]
Map:  68%|██████▊   | 77623/114105 [01:43<00:44, 814.70 examples/s]
Map:  66%|██████▋   | 75834/114105 [01:42<00:47, 809.66 examples/s]
Map:  66%|██████▌   | 75164/114105 [01:42<00:54, 714.31 examples/s]
Map:  67%|██████▋   | 76161/114105 [01:42<00:55, 681.20 examples/s]
Map:  68%|██████▊   | 77746/114105 [01:44<00:44, 814.50 examples/s]
Map:  66%|██████▌   | 75254/114105 [01:42<00:51, 757.49 examples/s]
Map:  67%|██████▋   | 75953/114105 [01:43<00:47, 801.20 examples/s]
Map:  67%|██████▋   | 76243/114105 [01:42<00:53, 711.12 examples/s]
Map:  68%|██████▊   | 77832/114105 [01:44<00:43, 825.24 examples/s]
Map:  66%|██████▌   | 75342/114105 [01:42<00:49, 787.23 examples/s]
Map:  67%|██████▋   | 76329/114105 [01:43<00:50, 744.80 examples/s]
Map:  67%|██████▋   | 76042/114105 [01:43<00:59, 641.53 examples/s]
Map:  68%|██████▊   | 77958/114105 [01:44<00:43, 825.76 examples/s]
Map:  66%|██████▌   | 75468/114105 [01:43<00:47, 804.95 examples/s]
Map:  67%|██████▋   | 76447/114105 [01:43<00:49, 755.78 examples/s]
Map:  67%|██████▋   | 76130/114105 [01:43<00:54, 694.46 examples/s]
Map:  66%|██████▌   | 75552/114105 [01:43<00:47, 812.83 examples/s]
Map:  67%|██████▋   | 76532/114105 [01:43<00:48, 776.61 examples/s]
Map:  67%|██████▋   | 76214/114105 [01:43<00:51, 729.81 examples/s]
Map:  66%|██████▋   | 75635/114105 [01:43<00:47, 815.04 examples/s]
Map:  67%|██████▋   | 76619/114105 [01:43<00:46, 800.51 examples/s]
Map:  68%|██████▊   | 78081/114105 [01:44<00:53, 670.50 examples/s]
Map:  67%|██████▋   | 76299/114105 [01:43<00:49, 758.91 examples/s]
Map:  66%|██████▋   | 75720/114105 [01:43<00:46, 821.60 examples/s]
Map:  67%|██████▋   | 76706/114105 [01:43<00:45, 816.10 examples/s]
Map:  69%|██████▊   | 78169/114105 [01:44<00:50, 711.49 examples/s]
Map:  67%|██████▋   | 76383/114105 [01:43<00:48, 778.14 examples/s]
Map:  67%|██████▋   | 76790/114105 [01:43<00:45, 817.75 examples/s]
Map:  69%|██████▊   | 78258/114105 [01:44<00:47, 749.69 examples/s]
Map:  66%|██████▋   | 75847/114105 [01:43<00:46, 825.96 examples/s]
Map:  67%|██████▋   | 76464/114105 [01:43<00:47, 784.20 examples/s]
Map:  67%|██████▋   | 76877/114105 [01:43<00:44, 828.32 examples/s]
Map:  69%|██████▊   | 78343/114105 [01:44<00:46, 771.40 examples/s]
Map:  67%|██████▋   | 76550/114105 [01:43<00:46, 802.78 examples/s]
Map:  67%|██████▋   | 75971/114105 [01:43<00:46, 823.89 examples/s]
Map:  69%|██████▊   | 78429/114105 [01:44<00:45, 791.05 examples/s]
Map:  67%|██████▋   | 76632/114105 [01:44<00:46, 802.64 examples/s]
Map:  67%|██████▋   | 76999/114105 [01:43<00:45, 817.28 examples/s]
Map:  69%|██████▉   | 78519/114105 [01:45<00:43, 816.18 examples/s]
Map:  67%|██████▋   | 76752/114105 [01:44<00:46, 795.61 examples/s]
Map:  67%|██████▋   | 76086/114105 [01:43<00:56, 670.11 examples/s]
Map:  69%|██████▉   | 78641/114105 [01:45<00:43, 811.46 examples/s]
Map:  67%|██████▋   | 76835/114105 [01:44<00:46, 801.15 examples/s]
Map:  67%|██████▋   | 76174/114105 [01:43<00:53, 711.83 examples/s]
Map:  68%|██████▊   | 77122/114105 [01:44<00:56, 652.45 examples/s]
Map:  69%|██████▉   | 78725/114105 [01:45<00:43, 817.66 examples/s]
Map:  67%|██████▋   | 76921/114105 [01:44<00:45, 813.25 examples/s]
Map:  67%|██████▋   | 76260/114105 [01:44<00:50, 742.30 examples/s]
Map:  68%|██████▊   | 77207/114105 [01:44<00:53, 690.79 examples/s]
Map:  69%|██████▉   | 78812/114105 [01:45<00:42, 827.39 examples/s]
Map:  67%|██████▋   | 76343/114105 [01:44<00:49, 761.18 examples/s]
Map:  68%|██████▊   | 77290/114105 [01:44<00:51, 721.34 examples/s]
Map:  67%|██████▋   | 76425/114105 [01:44<00:48, 774.51 examples/s]
Map:  69%|██████▉   | 78938/114105 [01:45<00:42, 829.36 examples/s]
Map:  68%|██████▊   | 77377/114105 [01:44<00:48, 755.14 examples/s]
Map:  68%|██████▊   | 77036/114105 [01:44<00:57, 648.46 examples/s]
Map:  67%|██████▋   | 76513/114105 [01:44<00:46, 799.94 examples/s]
Map:  68%|██████▊   | 77463/114105 [01:44<00:47, 779.31 examples/s]
Map:  68%|██████▊   | 77109/114105 [01:44<00:55, 665.00 examples/s]
Map:  67%|██████▋   | 76597/114105 [01:44<00:46, 809.22 examples/s]
Map:  68%|██████▊   | 77193/114105 [01:44<00:52, 703.43 examples/s]
Map:  69%|██████▉   | 79039/114105 [01:45<00:53, 659.21 examples/s]
Map:  68%|██████▊   | 77586/114105 [01:44<00:46, 791.09 examples/s]
Map:  67%|██████▋   | 76682/114105 [01:44<00:45, 816.78 examples/s]
Map:  68%|██████▊   | 77271/114105 [01:44<00:51, 720.39 examples/s]
Map:  69%|██████▉   | 79124/114105 [01:45<00:50, 696.89 examples/s]
Map:  67%|██████▋   | 76766/114105 [01:44<00:45, 819.83 examples/s]
Map:  68%|██████▊   | 77710/114105 [01:44<00:45, 799.72 examples/s]
Map:  69%|██████▉   | 79205/114105 [01:45<00:48, 720.46 examples/s]
Map:  68%|██████▊   | 77390/114105 [01:45<00:49, 742.51 examples/s]
Map:  67%|██████▋   | 76851/114105 [01:44<00:45, 824.53 examples/s]
Map:  68%|██████▊   | 77792/114105 [01:44<00:45, 802.28 examples/s]
Map:  69%|██████▉   | 79287/114105 [01:46<00:46, 743.63 examples/s]
Map:  68%|██████▊   | 77507/114105 [01:45<00:48, 752.09 examples/s]
Map:  67%|██████▋   | 76970/114105 [01:44<00:45, 810.22 examples/s]
Map:  68%|██████▊   | 77903/114105 [01:45<00:46, 776.94 examples/s]
Map:  70%|██████▉   | 79403/114105 [01:46<00:46, 750.64 examples/s]
Map:  68%|██████▊   | 77591/114105 [01:45<00:47, 771.47 examples/s]
Map:  68%|██████▊   | 77985/114105 [01:45<00:46, 784.64 examples/s]
Map:  70%|██████▉   | 79487/114105 [01:46<00:44, 771.84 examples/s]
Map:  68%|██████▊   | 77674/114105 [01:45<00:46, 785.98 examples/s]
Map:  70%|██████▉   | 79570/114105 [01:46<00:44, 783.20 examples/s]
Map:  68%|██████▊   | 77080/114105 [01:45<00:57, 640.95 examples/s]
Map:  68%|██████▊   | 77756/114105 [01:45<00:45, 791.51 examples/s]
Map:  70%|██████▉   | 79655/114105 [01:46<00:43, 798.68 examples/s]
Map:  68%|██████▊   | 78085/114105 [01:45<00:57, 628.34 examples/s]
Map:  68%|██████▊   | 77166/114105 [01:45<00:53, 685.70 examples/s]
Map:  68%|██████▊   | 77841/114105 [01:45<00:45, 802.36 examples/s]
Map:  70%|██████▉   | 79740/114105 [01:46<00:42, 809.35 examples/s]
Map:  69%|██████▊   | 78169/114105 [01:45<00:53, 673.25 examples/s]
Map:  68%|██████▊   | 77249/114105 [01:45<00:51, 717.52 examples/s]
Map:  68%|██████▊   | 77926/114105 [01:45<00:44, 813.21 examples/s]
Map:  70%|██████▉   | 79825/114105 [01:46<00:42, 815.39 examples/s]
Map:  69%|██████▊   | 78256/114105 [01:45<00:49, 718.44 examples/s]
Map:  68%|██████▊   | 77339/114105 [01:45<00:48, 762.42 examples/s]
Map:  70%|███████   | 79913/114105 [01:46<00:41, 829.29 examples/s]
Map:  69%|██████▊   | 78340/114105 [01:45<00:47, 746.55 examples/s]
Map:  68%|██████▊   | 77425/114105 [01:45<00:46, 787.05 examples/s]
Map:  68%|██████▊   | 78039/114105 [01:45<00:55, 647.52 examples/s]
Map:  70%|███████   | 79998/114105 [01:46<00:41, 829.26 examples/s]
Map:  69%|██████▊   | 78422/114105 [01:45<00:46, 765.13 examples/s]
Map:  68%|██████▊   | 77508/114105 [01:45<00:46, 795.48 examples/s]
Map:  68%|██████▊   | 78119/114105 [01:46<00:53, 678.66 examples/s]
Map:  69%|██████▉   | 78506/114105 [01:45<00:45, 780.67 examples/s]
Map:  68%|██████▊   | 77594/114105 [01:45<00:45, 810.01 examples/s]
Map:  69%|██████▊   | 78208/114105 [01:46<00:49, 727.07 examples/s]
Map:  70%|███████   | 80085/114105 [01:47<00:53, 638.04 examples/s]
Map:  69%|██████▉   | 78630/114105 [01:46<00:44, 792.03 examples/s]
Map:  68%|██████▊   | 77715/114105 [01:45<00:45, 804.00 examples/s]
Map:  69%|██████▊   | 78289/114105 [01:46<00:47, 747.27 examples/s]
Map:  70%|███████   | 80165/114105 [01:47<00:50, 675.88 examples/s]
Map:  69%|██████▉   | 78743/114105 [01:46<00:45, 777.20 examples/s]
Map:  70%|███████   | 80243/114105 [01:47<00:48, 700.78 examples/s]
Map:  68%|██████▊   | 77834/114105 [01:46<00:45, 796.05 examples/s]
Map:  69%|██████▊   | 78406/114105 [01:46<00:47, 753.02 examples/s]
Map:  69%|██████▉   | 78826/114105 [01:46<00:44, 788.82 examples/s]
Map:  70%|███████   | 80330/114105 [01:47<00:45, 740.54 examples/s]
Map:  68%|██████▊   | 77917/114105 [01:46<00:45, 802.41 examples/s]
Map:  69%|██████▉   | 78493/114105 [01:46<00:45, 779.03 examples/s]
Map:  69%|██████▉   | 78907/114105 [01:46<00:44, 791.52 examples/s]
Map:  70%|███████   | 80413/114105 [01:47<00:44, 762.93 examples/s]
Map:  69%|██████▉   | 78574/114105 [01:46<00:45, 785.37 examples/s]
Map:  69%|██████▉   | 78988/114105 [01:46<00:44, 793.87 examples/s]
Map:  71%|███████   | 80500/114105 [01:47<00:42, 792.04 examples/s]
Map:  68%|██████▊   | 78000/114105 [01:46<00:56, 635.56 examples/s]
Map:  69%|██████▉   | 78660/114105 [01:46<00:44, 804.08 examples/s]
Map:  68%|██████▊   | 78084/114105 [01:46<00:52, 679.87 examples/s]
Map:  69%|██████▉   | 78742/114105 [01:46<00:43, 807.19 examples/s]
Map:  71%|███████   | 80622/114105 [01:47<00:41, 797.54 examples/s]
Map:  69%|██████▊   | 78172/114105 [01:46<00:49, 724.98 examples/s]
Map:  69%|██████▉   | 79083/114105 [01:46<00:56, 624.06 examples/s]
Map:  71%|███████   | 80704/114105 [01:47<00:41, 801.70 examples/s]
Map:  69%|██████▉   | 78863/114105 [01:47<00:43, 805.24 examples/s]
Map:  69%|██████▊   | 78254/114105 [01:46<00:47, 747.46 examples/s]
Map:  69%|██████▉   | 79166/114105 [01:46<00:52, 667.81 examples/s]
Map:  71%|███████   | 80787/114105 [01:48<00:41, 808.80 examples/s]
Map:  69%|██████▊   | 78338/114105 [01:46<00:46, 767.85 examples/s]
Map:  69%|██████▉   | 78982/114105 [01:47<00:44, 796.80 examples/s]
Map:  69%|██████▉   | 79250/114105 [01:46<00:49, 709.02 examples/s]
Map:  71%|███████   | 80871/114105 [01:48<00:40, 816.73 examples/s]
Map:  69%|██████▊   | 78426/114105 [01:46<00:44, 795.87 examples/s]
Map:  70%|██████▉   | 79333/114105 [01:47<00:47, 737.36 examples/s]
Map:  71%|███████   | 80958/114105 [01:48<00:39, 829.46 examples/s]
Map:  70%|██████▉   | 79412/114105 [01:47<00:46, 747.55 examples/s]
Map:  69%|██████▉   | 79079/114105 [01:47<00:54, 644.47 examples/s]
Map:  69%|██████▉   | 78547/114105 [01:47<00:44, 794.99 examples/s]
Map:  70%|██████▉   | 79496/114105 [01:47<00:44, 772.38 examples/s]
Map:  69%|██████▉   | 79162/114105 [01:47<00:51, 681.95 examples/s]
Map:  71%|███████   | 81077/114105 [01:48<00:51, 644.86 examples/s]
Map:  69%|██████▉   | 78661/114105 [01:47<00:45, 778.62 examples/s]
Map:  70%|██████▉   | 79603/114105 [01:47<00:46, 745.61 examples/s]
Map:  69%|██████▉   | 79276/114105 [01:47<00:49, 703.22 examples/s]
Map:  71%|███████   | 81160/114105 [01:48<00:48, 684.53 examples/s]
Map:  69%|██████▉   | 78784/114105 [01:47<00:44, 790.98 examples/s]
Map:  70%|██████▉   | 79688/114105 [01:47<00:44, 770.27 examples/s]
Map:  70%|██████▉   | 79358/114105 [01:47<00:47, 728.06 examples/s]
Map:  71%|███████   | 81243/114105 [01:48<00:45, 717.44 examples/s]
Map:  69%|██████▉   | 78869/114105 [01:47<00:43, 802.09 examples/s]
Map:  70%|██████▉   | 79771/114105 [01:47<00:43, 783.58 examples/s]
Map:  70%|██████▉   | 79440/114105 [01:47<00:46, 747.50 examples/s]
Map:  71%|███████▏  | 81326/114105 [01:48<00:44, 744.32 examples/s]
Map:  70%|██████▉   | 79858/114105 [01:47<00:42, 805.47 examples/s]
Map:  70%|██████▉   | 79526/114105 [01:47<00:44, 775.18 examples/s]
Map:  71%|███████▏  | 81407/114105 [01:48<00:43, 760.31 examples/s]
Map:  69%|██████▉   | 78989/114105 [01:47<00:43, 798.12 examples/s]
Map:  70%|██████▉   | 79614/114105 [01:48<00:43, 801.12 examples/s]
Map:  71%|███████▏  | 81490/114105 [01:48<00:41, 777.20 examples/s]
Map:  70%|███████   | 79984/114105 [01:47<00:41, 815.74 examples/s]
Map:  70%|██████▉   | 79697/114105 [01:48<00:42, 807.59 examples/s]
Map:  71%|███████▏  | 81575/114105 [01:49<00:41, 791.41 examples/s]
Map:  69%|██████▉   | 79084/114105 [01:47<00:54, 646.71 examples/s]
Map:  70%|██████▉   | 79782/114105 [01:48<00:42, 816.37 examples/s]
Map:  69%|██████▉   | 79166/114105 [01:47<00:51, 681.58 examples/s]
Map:  70%|███████   | 80080/114105 [01:48<00:53, 639.45 examples/s]
Map:  72%|███████▏  | 81695/114105 [01:49<00:40, 790.62 examples/s]
Map:  70%|██████▉   | 79866/114105 [01:48<00:41, 820.04 examples/s]
Map:  69%|██████▉   | 79255/114105 [01:48<00:47, 727.26 examples/s]
Map:  70%|███████   | 80166/114105 [01:48<00:49, 686.29 examples/s]
Map:  72%|███████▏  | 81778/114105 [01:49<00:40, 798.61 examples/s]
Map:  70%|███████   | 79949/114105 [01:48<00:41, 820.82 examples/s]
Map:  70%|██████▉   | 79341/114105 [01:48<00:45, 758.32 examples/s]
Map:  70%|███████   | 80245/114105 [01:48<00:47, 708.01 examples/s]
Map:  72%|███████▏  | 81861/114105 [01:49<00:40, 805.51 examples/s]
Map:  70%|██████▉   | 79425/114105 [01:48<00:44, 776.65 examples/s]
Map:  70%|███████   | 80330/114105 [01:48<00:45, 739.73 examples/s]
Map:  72%|███████▏  | 81946/114105 [01:49<00:39, 814.58 examples/s]
Map:  70%|███████   | 80042/114105 [01:48<00:53, 642.16 examples/s]
Map:  70%|██████▉   | 79510/114105 [01:48<00:43, 793.96 examples/s]
Map:  70%|███████   | 80412/114105 [01:48<00:44, 758.10 examples/s]
Map:  70%|███████   | 80125/114105 [01:48<00:49, 684.59 examples/s]
Map:  70%|██████▉   | 79593/114105 [01:48<00:43, 799.75 examples/s]
Map:  71%|███████   | 80496/114105 [01:48<00:43, 777.68 examples/s]
Map:  72%|███████▏  | 82042/114105 [01:49<00:50, 629.55 examples/s]
Map:  70%|███████   | 80209/114105 [01:48<00:46, 721.22 examples/s]
Map:  70%|██████▉   | 79676/114105 [01:48<00:42, 806.56 examples/s]
Map:  71%|███████   | 80581/114105 [01:48<00:42, 796.71 examples/s]
Map:  72%|███████▏  | 82121/114105 [01:49<00:48, 664.91 examples/s]
Map:  70%|███████   | 80292/114105 [01:48<00:45, 748.09 examples/s]
Map:  71%|███████   | 80665/114105 [01:48<00:41, 804.86 examples/s]
Map:  72%|███████▏  | 82205/114105 [01:49<00:45, 706.13 examples/s]
Map:  70%|██████▉   | 79798/114105 [01:48<00:42, 806.34 examples/s]
Map:  70%|███████   | 80374/114105 [01:49<00:44, 764.80 examples/s]
Map:  72%|███████▏  | 82288/114105 [01:50<00:43, 737.81 examples/s]
Map:  70%|███████   | 79884/114105 [01:48<00:42, 812.22 examples/s]
Map:  71%|███████   | 80455/114105 [01:49<00:43, 774.67 examples/s]
Map:  71%|███████   | 80788/114105 [01:48<00:41, 807.58 examples/s]
Map:  70%|███████   | 79967/114105 [01:48<00:41, 813.67 examples/s]
Map:  71%|███████   | 80535/114105 [01:49<00:43, 780.31 examples/s]
Map:  71%|███████   | 80871/114105 [01:49<00:40, 812.18 examples/s]
Map:  72%|███████▏  | 82398/114105 [01:50<00:43, 731.67 examples/s]
Map:  71%|███████   | 80621/114105 [01:49<00:41, 802.23 examples/s]
Map:  71%|███████   | 80956/114105 [01:49<00:40, 819.77 examples/s]
Map:  72%|███████▏  | 82483/114105 [01:50<00:41, 758.21 examples/s]
Map:  71%|███████   | 80703/114105 [01:49<00:41, 804.76 examples/s]
Map:  72%|███████▏  | 82567/114105 [01:50<00:40, 776.83 examples/s]
Map:  70%|███████   | 80076/114105 [01:49<00:54, 630.14 examples/s]
Map:  71%|███████   | 81039/114105 [01:49<00:52, 627.64 examples/s]
Map:  72%|███████▏  | 82659/114105 [01:50<00:38, 811.42 examples/s]
Map:  70%|███████   | 80159/114105 [01:49<00:50, 673.36 examples/s]
Map:  71%|███████   | 80825/114105 [01:49<00:41, 804.15 examples/s]
Map:  71%|███████   | 81124/114105 [01:49<00:48, 677.26 examples/s]
Map:  70%|███████   | 80242/114105 [01:49<00:47, 709.71 examples/s]
Map:  71%|███████   | 80910/114105 [01:49<00:40, 811.65 examples/s]
Map:  73%|███████▎  | 82782/114105 [01:50<00:38, 810.30 examples/s]
Map:  71%|███████   | 81203/114105 [01:49<00:46, 701.67 examples/s]
Map:  70%|███████   | 80325/114105 [01:49<00:45, 739.56 examples/s]
Map:  71%|███████   | 80993/114105 [01:49<00:40, 813.92 examples/s]
Map:  73%|███████▎  | 82867/114105 [01:50<00:38, 818.09 examples/s]
Map:  71%|███████   | 81283/114105 [01:49<00:45, 726.24 examples/s]
Map:  70%|███████   | 80406/114105 [01:49<00:44, 756.14 examples/s]
Map:  73%|███████▎  | 82952/114105 [01:50<00:37, 825.26 examples/s]
Map:  71%|███████▏  | 81369/114105 [01:49<00:43, 759.25 examples/s]
Map:  71%|███████   | 80488/114105 [01:49<00:43, 771.86 examples/s]
Map:  71%|███████   | 81081/114105 [01:50<00:51, 638.68 examples/s]
Map:  71%|███████▏  | 81454/114105 [01:49<00:41, 780.89 examples/s]
Map:  71%|███████   | 80568/114105 [01:49<00:43, 776.50 examples/s]
Map:  71%|███████   | 81165/114105 [01:50<00:48, 685.57 examples/s]
Map:  73%|███████▎  | 83044/114105 [01:51<00:47, 648.72 examples/s]
Map:  71%|███████▏  | 81542/114105 [01:50<00:40, 808.35 examples/s]
Map:  71%|███████   | 80653/114105 [01:49<00:42, 793.31 examples/s]
Map:  71%|███████   | 81249/114105 [01:50<00:45, 720.18 examples/s]
Map:  73%|███████▎  | 83128/114105 [01:51<00:44, 692.09 examples/s]
Map:  71%|███████   | 80739/114105 [01:49<00:41, 808.63 examples/s]
Map:  71%|███████▏  | 81330/114105 [01:50<00:44, 740.82 examples/s]
Map:  72%|███████▏  | 81665/114105 [01:50<00:40, 809.41 examples/s]
Map:  73%|███████▎  | 83215/114105 [01:51<00:42, 733.71 examples/s]
Map:  71%|███████▏  | 81417/114105 [01:50<00:42, 774.81 examples/s]
Map:  72%|███████▏  | 81750/114105 [01:50<00:39, 815.55 examples/s]
Map:  71%|███████   | 80863/114105 [01:50<00:40, 810.79 examples/s]
Map:  73%|███████▎  | 83299/114105 [01:51<00:40, 756.44 examples/s]
Map:  71%|███████▏  | 81503/114105 [01:50<00:41, 795.16 examples/s]
Map:  72%|███████▏  | 81836/114105 [01:50<00:39, 826.76 examples/s]
Map:  71%|███████   | 80948/114105 [01:50<00:40, 816.27 examples/s]
Map:  73%|███████▎  | 83385/114105 [01:51<00:39, 781.96 examples/s]
Map:  72%|███████▏  | 81920/114105 [01:50<00:38, 826.20 examples/s]
Map:  73%|███████▎  | 83469/114105 [01:51<00:38, 794.06 examples/s]
Map:  72%|███████▏  | 81620/114105 [01:50<00:41, 785.89 examples/s]
Map:  71%|███████   | 81042/114105 [01:50<00:51, 642.04 examples/s]
Map:  73%|███████▎  | 83586/114105 [01:51<00:38, 784.52 examples/s]
Map:  72%|███████▏  | 81740/114105 [01:50<00:41, 787.36 examples/s]
Map:  71%|███████   | 81126/114105 [01:50<00:48, 684.74 examples/s]
Map:  72%|███████▏  | 82041/114105 [01:50<00:49, 651.29 examples/s]
Map:  73%|███████▎  | 83699/114105 [01:51<00:39, 770.33 examples/s]
Map:  71%|███████   | 81203/114105 [01:50<00:46, 702.60 examples/s]
Map:  72%|███████▏  | 81855/114105 [01:50<00:41, 778.35 examples/s]
Map:  72%|███████▏  | 82118/114105 [01:50<00:47, 675.57 examples/s]
Map:  73%|███████▎  | 83780/114105 [01:52<00:38, 777.74 examples/s]
Map:  71%|███████   | 81292/114105 [01:50<00:43, 749.05 examples/s]
Map:  72%|███████▏  | 81936/114105 [01:51<00:41, 784.46 examples/s]
Map:  72%|███████▏  | 82200/114105 [01:50<00:45, 708.25 examples/s]
Map:  73%|███████▎  | 83865/114105 [01:52<00:38, 795.18 examples/s]
Map:  71%|███████▏  | 81372/114105 [01:50<00:43, 760.44 examples/s]
Map:  72%|███████▏  | 82283/114105 [01:51<00:43, 736.49 examples/s]
Map:  74%|███████▎  | 83949/114105 [01:52<00:37, 806.05 examples/s]
Map:  71%|███████▏  | 81454/114105 [01:50<00:42, 776.66 examples/s]
Map:  72%|███████▏  | 82363/114105 [01:51<00:42, 751.43 examples/s]
Map:  72%|███████▏  | 82040/114105 [01:51<00:49, 643.36 examples/s]
Map:  71%|███████▏  | 81538/114105 [01:51<00:41, 789.92 examples/s]
Map:  72%|███████▏  | 82445/114105 [01:51<00:41, 767.05 examples/s]
Map:  72%|███████▏  | 82122/114105 [01:51<00:47, 679.02 examples/s]
Map:  72%|███████▏  | 81625/114105 [01:51<00:40, 811.94 examples/s]
Map:  74%|███████▎  | 84039/114105 [01:52<00:47, 628.30 examples/s]
Map:  72%|███████▏  | 82527/114105 [01:51<00:40, 779.11 examples/s]
Map:  72%|███████▏  | 82204/114105 [01:51<00:44, 710.20 examples/s]
Map:  72%|███████▏  | 81711/114105 [01:51<00:39, 821.83 examples/s]
Map:  74%|███████▎  | 84124/114105 [01:52<00:44, 677.57 examples/s]
Map:  72%|███████▏  | 82612/114105 [01:51<00:39, 796.05 examples/s]
Map:  72%|███████▏  | 82288/114105 [01:51<00:42, 741.98 examples/s]
Map:  72%|███████▏  | 81797/114105 [01:51<00:38, 829.39 examples/s]
Map:  74%|███████▍  | 84205/114105 [01:52<00:42, 707.73 examples/s]
Map:  72%|███████▏  | 82696/114105 [01:51<00:39, 804.10 examples/s]
Map:  72%|███████▏  | 82376/114105 [01:51<00:40, 776.20 examples/s]
Map:  72%|███████▏  | 81882/114105 [01:51<00:38, 834.15 examples/s]
Map:  74%|███████▍  | 84285/114105 [01:52<00:40, 731.03 examples/s]
Map:  73%|███████▎  | 82781/114105 [01:51<00:38, 814.43 examples/s]
Map:  72%|███████▏  | 82457/114105 [01:51<00:40, 783.70 examples/s]
Map:  74%|███████▍  | 84370/114105 [01:52<00:39, 761.97 examples/s]
Map:  73%|███████▎  | 82864/114105 [01:51<00:38, 817.07 examples/s]
Map:  72%|███████▏  | 82540/114105 [01:51<00:39, 793.88 examples/s]
Map:  74%|███████▍  | 84454/114105 [01:52<00:38, 778.26 examples/s]
Map:  73%|███████▎  | 82947/114105 [01:51<00:38, 818.03 examples/s]
Map:  72%|███████▏  | 82000/114105 [01:51<00:50, 642.05 examples/s]
Map:  72%|███████▏  | 82653/114105 [01:52<00:40, 774.69 examples/s]
Map:  72%|███████▏  | 82080/114105 [01:51<00:47, 676.82 examples/s]
Map:  74%|███████▍  | 84576/114105 [01:53<00:37, 785.93 examples/s]
Map:  73%|███████▎  | 82732/114105 [01:52<00:40, 777.37 examples/s]
Map:  73%|███████▎  | 83042/114105 [01:52<00:49, 626.94 examples/s]
Map:  72%|███████▏  | 82163/114105 [01:51<00:44, 711.04 examples/s]
Map:  74%|███████▍  | 84662/114105 [01:53<00:36, 804.20 examples/s]
Map:  73%|███████▎  | 82816/114105 [01:52<00:39, 789.48 examples/s]
Map:  73%|███████▎  | 83128/114105 [01:52<00:45, 678.26 examples/s]
Map:  72%|███████▏  | 82249/114105 [01:51<00:42, 741.36 examples/s]
Map:  74%|███████▍  | 84785/114105 [01:53<00:36, 807.73 examples/s]
Map:  73%|███████▎  | 82923/114105 [01:52<00:41, 757.77 examples/s]
Map:  73%|███████▎  | 83212/114105 [01:52<00:43, 715.85 examples/s]
Map:  72%|███████▏  | 82335/114105 [01:52<00:41, 770.83 examples/s]
Map:  74%|███████▍  | 84869/114105 [01:53<00:35, 813.22 examples/s]
Map:  73%|███████▎  | 83295/114105 [01:52<00:41, 744.82 examples/s]
Map:  72%|███████▏  | 82417/114105 [01:52<00:40, 781.38 examples/s]
Map:  74%|███████▍  | 84954/114105 [01:53<00:35, 819.45 examples/s]
Map:  73%|███████▎  | 83379/114105 [01:52<00:40, 768.05 examples/s]
Map:  72%|███████▏  | 82503/114105 [01:52<00:39, 800.78 examples/s]
Map:  73%|███████▎  | 83000/114105 [01:52<01:00, 511.11 examples/s]
Map:  73%|███████▎  | 83462/114105 [01:52<00:39, 782.19 examples/s]
Map:  72%|███████▏  | 82589/114105 [01:52<00:38, 814.74 examples/s]
Map:  75%|███████▍  | 85041/114105 [01:53<00:45, 636.69 examples/s]
Map:  73%|███████▎  | 83543/114105 [01:52<00:38, 787.96 examples/s]
Map:  72%|███████▏  | 82675/114105 [01:52<00:38, 826.18 examples/s]
Map:  73%|███████▎  | 83097/114105 [01:52<00:56, 546.41 examples/s]
Map:  75%|███████▍  | 85125/114105 [01:53<00:42, 679.98 examples/s]
Map:  73%|███████▎  | 83179/114105 [01:52<00:51, 600.71 examples/s]
Map:  73%|███████▎  | 83665/114105 [01:52<00:38, 795.11 examples/s]
Map:  73%|███████▎  | 82796/114105 [01:52<00:38, 815.83 examples/s]
Map:  75%|███████▍  | 85210/114105 [01:53<00:40, 719.86 examples/s]
Map:  73%|███████▎  | 83257/114105 [01:53<00:48, 639.38 examples/s]
Map:  73%|███████▎  | 83749/114105 [01:52<00:37, 802.29 examples/s]
Map:  73%|███████▎  | 82883/114105 [01:52<00:37, 828.06 examples/s]
Map:  75%|███████▍  | 85297/114105 [01:54<00:38, 755.86 examples/s]
Map:  73%|███████▎  | 83329/114105 [01:53<00:46, 658.43 examples/s]
Map:  73%|███████▎  | 83866/114105 [01:53<00:38, 790.57 examples/s]
Map:  73%|███████▎  | 82996/114105 [01:52<00:38, 797.74 examples/s]
Map:  75%|███████▍  | 85413/114105 [01:54<00:37, 758.09 examples/s]
Map:  73%|███████▎  | 83443/114105 [01:53<00:44, 690.89 examples/s]
Map:  74%|███████▎  | 83946/114105 [01:53<00:38, 789.65 examples/s]
Map:  75%|███████▍  | 85493/114105 [01:54<00:37, 768.22 examples/s]
Map:  73%|███████▎  | 83524/114105 [01:53<00:42, 718.04 examples/s]
Map:  73%|███████▎  | 83083/114105 [01:53<00:48, 634.24 examples/s]
Map:  75%|███████▍  | 85574/114105 [01:54<00:36, 776.16 examples/s]
Map:  73%|███████▎  | 83606/114105 [01:53<00:41, 742.66 examples/s]
Map:  74%|███████▎  | 84041/114105 [01:53<00:48, 623.72 examples/s]
Map:  73%|███████▎  | 83166/114105 [01:53<00:45, 675.89 examples/s]
Map:  75%|███████▌  | 85658/114105 [01:54<00:35, 790.29 examples/s]
Map:  73%|███████▎  | 83688/114105 [01:53<00:40, 759.89 examples/s]
Map:  74%|███████▎  | 84121/114105 [01:53<00:45, 661.75 examples/s]
Map:  73%|███████▎  | 83248/114105 [01:53<00:43, 707.10 examples/s]
Map:  75%|███████▌  | 85741/114105 [01:54<00:35, 799.20 examples/s]
Map:  73%|███████▎  | 83767/114105 [01:53<00:39, 766.41 examples/s]
Map:  74%|███████▍  | 84203/114105 [01:53<00:42, 697.27 examples/s]
Map:  73%|███████▎  | 83334/114105 [01:53<00:41, 744.42 examples/s]
Map:  75%|███████▌  | 85825/114105 [01:54<00:35, 807.87 examples/s]
Map:  73%|███████▎  | 83850/114105 [01:53<00:38, 784.06 examples/s]
Map:  74%|███████▍  | 84290/114105 [01:53<00:40, 739.07 examples/s]
Map:  73%|███████▎  | 83415/114105 [01:53<00:40, 756.88 examples/s]
Map:  75%|███████▌  | 85947/114105 [01:54<00:34, 804.54 examples/s]
Map:  74%|███████▍  | 84380/114105 [01:53<00:38, 780.81 examples/s]
Map:  74%|███████▎  | 83970/114105 [01:53<00:38, 784.44 examples/s]
Map:  73%|███████▎  | 83500/114105 [01:53<00:39, 780.73 examples/s]
Map:  74%|███████▍  | 84466/114105 [01:53<00:37, 798.72 examples/s]
Map:  73%|███████▎  | 83586/114105 [01:53<00:38, 797.99 examples/s]
Map:  75%|███████▌  | 86043/114105 [01:55<00:43, 638.35 examples/s]
Map:  74%|███████▍  | 84553/114105 [01:54<00:36, 813.91 examples/s]
Map:  73%|███████▎  | 83671/114105 [01:53<00:37, 807.47 examples/s]
Map:  74%|███████▎  | 84074/114105 [01:54<00:48, 619.94 examples/s]
Map:  75%|███████▌  | 86124/114105 [01:55<00:41, 675.11 examples/s]
Map:  74%|███████▍  | 84639/114105 [01:54<00:35, 821.77 examples/s]
Map:  74%|███████▎  | 84152/114105 [01:54<00:46, 649.84 examples/s]
Map:  73%|███████▎  | 83791/114105 [01:53<00:37, 799.32 examples/s]
Map:  76%|███████▌  | 86231/114105 [01:55<00:40, 686.20 examples/s]
Map:  74%|███████▍  | 84223/114105 [01:54<00:45, 662.72 examples/s]
Map:  74%|███████▍  | 84748/114105 [01:54<00:37, 784.02 examples/s]
Map:  74%|███████▎  | 83909/114105 [01:54<00:38, 790.88 examples/s]
Map:  76%|███████▌  | 86311/114105 [01:55<00:39, 710.41 examples/s]
Map:  74%|███████▍  | 84302/114105 [01:54<00:43, 692.04 examples/s]
Map:  74%|███████▍  | 84868/114105 [01:54<00:37, 786.85 examples/s]
Map:  74%|███████▎  | 83993/114105 [01:54<00:37, 800.42 examples/s]
Map:  76%|███████▌  | 86393/114105 [01:55<00:37, 733.70 examples/s]
Map:  74%|███████▍  | 84380/114105 [01:54<00:41, 711.02 examples/s]
Map:  74%|███████▍  | 84954/114105 [01:54<00:36, 803.14 examples/s]
Map:  76%|███████▌  | 86480/114105 [01:55<00:36, 765.43 examples/s]
Map:  74%|███████▍  | 84462/114105 [01:54<00:40, 739.28 examples/s]
Map:  74%|███████▎  | 84084/114105 [01:54<00:47, 635.12 examples/s]
Map:  76%|███████▌  | 86563/114105 [01:55<00:35, 781.36 examples/s]
Map:  74%|███████▍  | 84578/114105 [01:54<00:39, 748.44 examples/s]
Map:  75%|███████▍  | 85042/114105 [01:54<00:45, 634.07 examples/s]
Map:  74%|███████▍  | 84164/114105 [01:54<00:44, 671.20 examples/s]
Map:  76%|███████▌  | 86646/114105 [01:55<00:34, 792.13 examples/s]
Map:  74%|███████▍  | 84664/114105 [01:54<00:38, 773.53 examples/s]
Map:  75%|███████▍  | 85130/114105 [01:54<00:42, 687.45 examples/s]
Map:  74%|███████▍  | 84249/114105 [01:54<00:41, 712.12 examples/s]
Map:  76%|███████▌  | 86731/114105 [01:55<00:34, 804.95 examples/s]
Map:  75%|███████▍  | 85214/114105 [01:54<00:40, 721.27 examples/s]
Map:  74%|███████▍  | 84332/114105 [01:54<00:40, 740.15 examples/s]
Map:  76%|███████▌  | 86815/114105 [01:56<00:33, 812.47 examples/s]
Map:  74%|███████▍  | 84780/114105 [01:55<00:38, 771.41 examples/s]
Map:  75%|███████▍  | 85301/114105 [01:55<00:38, 756.87 examples/s]
Map:  74%|███████▍  | 84417/114105 [01:54<00:38, 766.90 examples/s]
Map:  76%|███████▌  | 86898/114105 [01:56<00:33, 815.76 examples/s]
Map:  74%|███████▍  | 84899/114105 [01:55<00:37, 775.72 examples/s]
Map:  74%|███████▍  | 84503/114105 [01:54<00:37, 790.28 examples/s]
Map:  76%|███████▌  | 86985/114105 [01:56<00:32, 828.84 examples/s]
Map:  75%|███████▍  | 85423/114105 [01:55<00:37, 772.94 examples/s]
Map:  74%|███████▍  | 84981/114105 [01:55<00:37, 783.71 examples/s]
Map:  74%|███████▍  | 84589/114105 [01:55<00:36, 807.47 examples/s]
Map:  75%|███████▍  | 85508/114105 [01:55<00:36, 789.15 examples/s]
Map:  76%|███████▋  | 87080/114105 [01:56<00:42, 632.96 examples/s]
Map:  74%|███████▍  | 84711/114105 [01:55<00:36, 803.85 examples/s]
Map:  75%|███████▌  | 85630/114105 [01:55<00:35, 794.04 examples/s]
Map:  75%|███████▍  | 85078/114105 [01:55<00:46, 619.64 examples/s]
Map:  76%|███████▋  | 87160/114105 [01:56<00:40, 670.86 examples/s]
Map:  74%|███████▍  | 84796/114105 [01:55<00:35, 814.18 examples/s]
Map:  75%|███████▌  | 85715/114105 [01:55<00:35, 804.23 examples/s]
Map:  75%|███████▍  | 85160/114105 [01:55<00:43, 660.81 examples/s]
Map:  76%|███████▋  | 87246/114105 [01:56<00:37, 717.27 examples/s]
Map:  74%|███████▍  | 84882/114105 [01:55<00:35, 824.32 examples/s]
Map:  75%|███████▌  | 85801/114105 [01:55<00:34, 816.70 examples/s]
Map:  75%|███████▍  | 85234/114105 [01:55<00:42, 677.84 examples/s]
Map:  77%|███████▋  | 87334/114105 [01:56<00:35, 756.63 examples/s]
Map:  74%|███████▍  | 84968/114105 [01:55<00:34, 833.39 examples/s]
Map:  75%|███████▌  | 85884/114105 [01:55<00:35, 805.54 examples/s]
Map:  75%|███████▍  | 85317/114105 [01:55<00:40, 714.06 examples/s]
Map:  77%|███████▋  | 87417/114105 [01:56<00:34, 773.29 examples/s]
Map:  75%|███████▌  | 85966/114105 [01:55<00:34, 807.34 examples/s]
Map:  75%|███████▍  | 85402/114105 [01:56<00:38, 747.08 examples/s]
Map:  77%|███████▋  | 87498/114105 [01:56<00:33, 782.58 examples/s]
Map:  75%|███████▍  | 85084/114105 [01:55<00:43, 661.34 examples/s]
Map:  75%|███████▍  | 85486/114105 [01:56<00:37, 770.75 examples/s]
Map:  77%|███████▋  | 87623/114105 [01:57<00:33, 795.69 examples/s]
Map:  75%|███████▍  | 85166/114105 [01:55<00:41, 694.87 examples/s]
Map:  75%|███████▍  | 85573/114105 [01:56<00:35, 794.93 examples/s]
Map:  75%|███████▌  | 86085/114105 [01:56<00:43, 645.72 examples/s]
Map:  75%|███████▍  | 85248/114105 [01:55<00:39, 724.19 examples/s]
Map:  77%|███████▋  | 87740/114105 [01:57<00:33, 786.12 examples/s]
Map:  76%|███████▌  | 86173/114105 [01:56<00:40, 694.97 examples/s]
Map:  75%|███████▌  | 85696/114105 [01:56<00:35, 800.07 examples/s]
Map:  75%|███████▍  | 85338/114105 [01:56<00:37, 764.22 examples/s]
Map:  77%|███████▋  | 87826/114105 [01:57<00:32, 801.62 examples/s]
Map:  76%|███████▌  | 86257/114105 [01:56<00:38, 727.78 examples/s]
Map:  75%|███████▌  | 85781/114105 [01:56<00:34, 809.80 examples/s]
Map:  75%|███████▍  | 85420/114105 [01:56<00:36, 777.86 examples/s]
Map:  77%|███████▋  | 87911/114105 [01:57<00:32, 810.14 examples/s]
Map:  76%|███████▌  | 86338/114105 [01:56<00:37, 745.23 examples/s]
Map:  75%|███████▌  | 85865/114105 [01:56<00:34, 816.11 examples/s]
Map:  75%|███████▍  | 85544/114105 [01:56<00:36, 791.04 examples/s]
Map:  76%|███████▌  | 86422/114105 [01:56<00:35, 769.36 examples/s]
Map:  75%|███████▌  | 85980/114105 [01:56<00:35, 796.86 examples/s]
Map:  75%|███████▌  | 85626/114105 [01:56<00:35, 795.33 examples/s]
Map:  76%|███████▌  | 86507/114105 [01:56<00:34, 789.75 examples/s]
Map:  77%|███████▋  | 88000/114105 [01:57<00:41, 633.97 examples/s]
Map:  75%|███████▌  | 85708/114105 [01:56<00:35, 800.60 examples/s]
Map:  77%|███████▋  | 88085/114105 [01:57<00:38, 681.76 examples/s]
Map:  76%|███████▌  | 86634/114105 [01:56<00:33, 808.12 examples/s]
Map:  75%|███████▌  | 86080/114105 [01:56<00:43, 642.94 examples/s]
Map:  75%|███████▌  | 85794/114105 [01:56<00:34, 816.25 examples/s]
Map:  77%|███████▋  | 88172/114105 [01:57<00:35, 724.79 examples/s]
Map:  76%|███████▌  | 86720/114105 [01:56<00:33, 818.51 examples/s]
Map:  76%|███████▌  | 86168/114105 [01:57<00:40, 690.73 examples/s]
Map:  75%|███████▌  | 85877/114105 [01:56<00:34, 817.96 examples/s]
Map:  77%|███████▋  | 88254/114105 [01:58<00:34, 748.45 examples/s]
Map:  76%|███████▌  | 86807/114105 [01:56<00:32, 829.17 examples/s]
Map:  76%|███████▌  | 86249/114105 [01:57<00:38, 717.18 examples/s]
Map:  77%|███████▋  | 88340/114105 [01:58<00:33, 776.26 examples/s]
Map:  75%|███████▌  | 85996/114105 [01:56<00:34, 804.90 examples/s]
Map:  76%|███████▌  | 86335/114105 [01:57<00:37, 749.87 examples/s]
Map:  76%|███████▌  | 86929/114105 [01:57<00:33, 818.66 examples/s]
Map:  77%|███████▋  | 88424/114105 [01:58<00:32, 792.04 examples/s]
Map:  76%|███████▌  | 86416/114105 [01:57<00:36, 763.74 examples/s]
Map:  78%|███████▊  | 88510/114105 [01:58<00:31, 808.57 examples/s]
Map:  75%|███████▌  | 86081/114105 [01:57<00:44, 628.68 examples/s]
Map:  76%|███████▌  | 86501/114105 [01:57<00:35, 783.67 examples/s]
Map:  78%|███████▊  | 88597/114105 [01:58<00:31, 821.11 examples/s]
Map:  76%|███████▋  | 87041/114105 [01:57<00:41, 655.72 examples/s]
Map:  76%|███████▌  | 86168/114105 [01:57<00:41, 681.27 examples/s]
Map:  76%|███████▌  | 86586/114105 [01:57<00:34, 801.18 examples/s]
Map:  78%|███████▊  | 88682/114105 [01:58<00:30, 825.10 examples/s]
Map:  76%|███████▋  | 87125/114105 [01:57<00:39, 691.73 examples/s]
Map:  76%|███████▌  | 86248/114105 [01:57<00:39, 705.65 examples/s]
Map:  76%|███████▌  | 86671/114105 [01:57<00:33, 809.96 examples/s]
Map:  76%|███████▋  | 87210/114105 [01:57<00:37, 725.02 examples/s]
Map:  78%|███████▊  | 88805/114105 [01:58<00:30, 819.29 examples/s]
Map:  76%|███████▌  | 86336/114105 [01:57<00:37, 748.11 examples/s]
Map:  76%|███████▌  | 86793/114105 [01:57<00:33, 805.60 examples/s]
Map:  77%|███████▋  | 87298/114105 [01:57<00:35, 762.18 examples/s]
Map:  78%|███████▊  | 88892/114105 [01:58<00:30, 830.38 examples/s]
Map:  76%|███████▌  | 86422/114105 [01:57<00:35, 775.61 examples/s]
Map:  76%|███████▌  | 86882/114105 [01:57<00:33, 824.46 examples/s]
Map:  77%|███████▋  | 87379/114105 [01:57<00:34, 772.28 examples/s]
Map:  78%|███████▊  | 88976/114105 [01:58<00:30, 830.75 examples/s]
Map:  76%|███████▌  | 86508/114105 [01:57<00:34, 798.31 examples/s]
Map:  77%|███████▋  | 87463/114105 [01:57<00:33, 787.43 examples/s]
Map:  76%|███████▌  | 86594/114105 [01:57<00:33, 811.96 examples/s]
Map:  77%|███████▋  | 87545/114105 [01:57<00:33, 795.63 examples/s]
Map:  76%|███████▌  | 86681/114105 [01:57<00:33, 823.16 examples/s]
Map:  76%|███████▌  | 87000/114105 [01:58<00:41, 659.10 examples/s]
Map:  78%|███████▊  | 89084/114105 [01:59<00:38, 653.23 examples/s]
Map:  77%|███████▋  | 87631/114105 [01:58<00:32, 812.87 examples/s]
Map:  76%|███████▋  | 87081/114105 [01:58<00:39, 689.99 examples/s]
Map:  78%|███████▊  | 89170/114105 [01:59<00:35, 698.82 examples/s]
Map:  76%|███████▌  | 86803/114105 [01:57<00:33, 817.80 examples/s]
Map:  76%|███████▋  | 87159/114105 [01:58<00:37, 710.14 examples/s]
Map:  78%|███████▊  | 89256/114105 [01:59<00:33, 735.89 examples/s]
Map:  77%|███████▋  | 87756/114105 [01:58<00:32, 815.00 examples/s]
Map:  76%|███████▌  | 86892/114105 [01:58<00:32, 833.78 examples/s]
Map:  76%|███████▋  | 87244/114105 [01:58<00:36, 742.84 examples/s]
Map:  78%|███████▊  | 89339/114105 [01:59<00:32, 755.90 examples/s]
Map:  77%|███████▋  | 87840/114105 [01:58<00:32, 819.00 examples/s]
Map:  76%|███████▌  | 86979/114105 [01:58<00:32, 837.69 examples/s]
Map:  77%|███████▋  | 87329/114105 [01:58<00:34, 768.75 examples/s]
Map:  78%|███████▊  | 89427/114105 [01:59<00:31, 786.82 examples/s]
Map:  77%|███████▋  | 87925/114105 [01:58<00:31, 820.41 examples/s]
Map:  77%|███████▋  | 87413/114105 [01:58<00:33, 786.69 examples/s]
Map:  78%|███████▊  | 89510/114105 [01:59<00:30, 798.20 examples/s]
Map:  76%|███████▋  | 87087/114105 [01:58<00:40, 660.69 examples/s]
Map:  79%|███████▊  | 89595/114105 [01:59<00:30, 809.77 examples/s]
Map:  77%|███████▋  | 87535/114105 [01:58<00:33, 796.10 examples/s]
Map:  76%|███████▋  | 87173/114105 [01:58<00:38, 704.14 examples/s]
Map:  77%|███████▋  | 88043/114105 [01:58<00:40, 642.86 examples/s]
Map:  79%|███████▊  | 89680/114105 [01:59<00:29, 817.73 examples/s]
Map:  76%|███████▋  | 87254/114105 [01:58<00:36, 726.70 examples/s]
Map:  77%|███████▋  | 88123/114105 [01:58<00:38, 673.56 examples/s]
Map:  77%|███████▋  | 87656/114105 [01:58<00:33, 794.95 examples/s]
Map:  79%|███████▊  | 89803/114105 [01:59<00:29, 813.82 examples/s]
Map:  77%|███████▋  | 87340/114105 [01:58<00:35, 757.92 examples/s]
Map:  77%|███████▋  | 88211/114105 [01:58<00:35, 719.58 examples/s]
Map:  77%|███████▋  | 87779/114105 [01:59<00:32, 800.05 examples/s]
Map:  79%|███████▉  | 89891/114105 [02:00<00:29, 827.53 examples/s]
Map:  77%|███████▋  | 87424/114105 [01:58<00:34, 778.12 examples/s]
Map:  77%|███████▋  | 88298/114105 [01:58<00:34, 752.76 examples/s]
Map:  77%|███████▋  | 87860/114105 [01:59<00:32, 799.60 examples/s]
Map:  79%|███████▉  | 89977/114105 [02:00<00:29, 831.38 examples/s]
Map:  77%|███████▋  | 87509/114105 [01:58<00:33, 794.54 examples/s]
Map:  77%|███████▋  | 88381/114105 [01:59<00:33, 770.66 examples/s]
Map:  77%|███████▋  | 87942/114105 [01:59<00:32, 802.74 examples/s]
Map:  78%|███████▊  | 88467/114105 [01:59<00:32, 792.76 examples/s]
Map:  77%|███████▋  | 87629/114105 [01:59<00:33, 794.45 examples/s]
Map:  78%|███████▊  | 88554/114105 [01:59<00:31, 812.05 examples/s]
Map:  79%|███████▉  | 90080/114105 [02:00<00:37, 635.38 examples/s]
Map:  77%|███████▋  | 87713/114105 [01:59<00:32, 803.87 examples/s]
Map:  78%|███████▊  | 88638/114105 [01:59<00:31, 816.23 examples/s]
Map:  77%|███████▋  | 88037/114105 [01:59<00:41, 634.72 examples/s]
Map:  79%|███████▉  | 90161/114105 [02:00<00:35, 673.21 examples/s]
Map:  77%|███████▋  | 87800/114105 [01:59<00:32, 818.83 examples/s]
Map:  77%|███████▋  | 88123/114105 [01:59<00:38, 681.42 examples/s]
Map:  79%|███████▉  | 90249/114105 [02:00<00:33, 721.83 examples/s]
Map:  77%|███████▋  | 87884/114105 [01:59<00:32, 818.73 examples/s]
Map:  78%|███████▊  | 88760/114105 [01:59<00:31, 808.65 examples/s]
Map:  77%|███████▋  | 88205/114105 [01:59<00:36, 711.95 examples/s]
Map:  79%|███████▉  | 90329/114105 [02:00<00:32, 741.32 examples/s]
Map:  77%|███████▋  | 87968/114105 [01:59<00:31, 822.19 examples/s]
Map:  78%|███████▊  | 88844/114105 [01:59<00:31, 812.99 examples/s]
Map:  77%|███████▋  | 88286/114105 [01:59<00:35, 735.93 examples/s]
Map:  79%|███████▉  | 90414/114105 [02:00<00:30, 767.77 examples/s]
Map:  78%|███████▊  | 88928/114105 [01:59<00:30, 816.62 examples/s]
Map:  77%|███████▋  | 88367/114105 [01:59<00:34, 754.02 examples/s]
Map:  79%|███████▉  | 90499/114105 [02:00<00:29, 788.85 examples/s]
Map:  77%|███████▋  | 88081/114105 [01:59<00:40, 650.18 examples/s]
Map:  78%|███████▊  | 88447/114105 [02:00<00:33, 763.84 examples/s]
Map:  79%|███████▉  | 90583/114105 [02:01<00:29, 801.06 examples/s]
Map:  77%|███████▋  | 88166/114105 [01:59<00:37, 693.35 examples/s]
Map:  78%|███████▊  | 89042/114105 [01:59<00:38, 644.31 examples/s]
Map:  78%|███████▊  | 88533/114105 [02:00<00:32, 787.49 examples/s]
Map:  79%|███████▉  | 90666/114105 [02:01<00:29, 806.67 examples/s]
Map:  77%|███████▋  | 88252/114105 [01:59<00:35, 729.36 examples/s]
Map:  78%|███████▊  | 89125/114105 [02:00<00:36, 683.18 examples/s]
Map:  78%|███████▊  | 88616/114105 [02:00<00:31, 797.10 examples/s]
Map:  80%|███████▉  | 90788/114105 [02:01<00:28, 806.03 examples/s]
Map:  77%|███████▋  | 88339/114105 [01:59<00:33, 763.99 examples/s]
Map:  78%|███████▊  | 89205/114105 [02:00<00:35, 707.64 examples/s]
Map:  78%|███████▊  | 88699/114105 [02:00<00:31, 802.32 examples/s]
Map:  80%|███████▉  | 90871/114105 [02:01<00:28, 809.66 examples/s]
Map:  77%|███████▋  | 88421/114105 [02:00<00:33, 776.47 examples/s]
Map:  78%|███████▊  | 89288/114105 [02:00<00:33, 735.74 examples/s]
Map:  78%|███████▊  | 88822/114105 [02:00<00:31, 806.96 examples/s]
Map:  78%|███████▊  | 88505/114105 [02:00<00:32, 792.19 examples/s]
Map:  78%|███████▊  | 89371/114105 [02:00<00:32, 757.27 examples/s]
Map:  80%|███████▉  | 90995/114105 [02:01<00:28, 813.93 examples/s]
Map:  78%|███████▊  | 88904/114105 [02:00<00:31, 808.75 examples/s]
Map:  78%|███████▊  | 88589/114105 [02:00<00:31, 801.43 examples/s]
Map:  78%|███████▊  | 89453/114105 [02:00<00:32, 769.72 examples/s]
Map:  78%|███████▊  | 88990/114105 [02:00<00:30, 820.56 examples/s]
Map:  78%|███████▊  | 88678/114105 [02:00<00:30, 821.73 examples/s]
Map:  78%|███████▊  | 89538/114105 [02:00<00:31, 788.96 examples/s]
Map:  80%|███████▉  | 91083/114105 [02:01<00:35, 645.74 examples/s]
Map:  78%|███████▊  | 88763/114105 [02:00<00:30, 826.49 examples/s]
Map:  79%|███████▊  | 89620/114105 [02:00<00:30, 795.74 examples/s]
Map:  80%|███████▉  | 91169/114105 [02:01<00:33, 691.19 examples/s]
Map:  78%|███████▊  | 89081/114105 [02:00<00:39, 641.09 examples/s]
Map:  79%|███████▊  | 89709/114105 [02:00<00:29, 818.09 examples/s]
Map:  78%|███████▊  | 88887/114105 [02:00<00:30, 823.29 examples/s]
Map:  80%|███████▉  | 91251/114105 [02:01<00:31, 720.57 examples/s]
Map:  78%|███████▊  | 89165/114105 [02:01<00:36, 685.12 examples/s]
Map:  79%|███████▊  | 89793/114105 [02:00<00:29, 820.81 examples/s]
Map:  80%|████████  | 91339/114105 [02:02<00:29, 759.19 examples/s]
Map:  78%|███████▊  | 89247/114105 [02:01<00:34, 716.18 examples/s]
Map:  79%|███████▉  | 89881/114105 [02:01<00:29, 835.08 examples/s]
Map:  80%|████████  | 91429/114105 [02:02<00:28, 794.80 examples/s]
Map:  78%|███████▊  | 89329/114105 [02:01<00:33, 742.54 examples/s]
Map:  78%|███████▊  | 89000/114105 [02:00<00:38, 656.09 examples/s]
Map:  79%|███████▉  | 89968/114105 [02:01<00:28, 844.90 examples/s]
Map:  80%|████████  | 91516/114105 [02:02<00:27, 812.23 examples/s]
Map:  78%|███████▊  | 89084/114105 [02:00<00:36, 694.81 examples/s]
Map:  78%|███████▊  | 89446/114105 [02:01<00:32, 753.10 examples/s]
Map:  80%|████████  | 91605/114105 [02:02<00:27, 828.79 examples/s]
Map:  78%|███████▊  | 89168/114105 [02:01<00:34, 728.44 examples/s]
Map:  78%|███████▊  | 89529/114105 [02:01<00:31, 770.76 examples/s]
Map:  79%|███████▉  | 90073/114105 [02:01<00:37, 633.07 examples/s]
Map:  78%|███████▊  | 89247/114105 [02:01<00:33, 741.49 examples/s]
Map:  80%|████████  | 91723/114105 [02:02<00:27, 808.53 examples/s]
Map:  79%|███████▉  | 90159/114105 [02:01<00:35, 682.15 examples/s]
Map:  79%|███████▊  | 89648/114105 [02:01<00:31, 775.35 examples/s]
Map:  78%|███████▊  | 89330/114105 [02:01<00:32, 762.87 examples/s]
Map:  80%|████████  | 91809/114105 [02:02<00:27, 821.40 examples/s]
Map:  79%|███████▉  | 90247/114105 [02:01<00:32, 723.94 examples/s]
Map:  79%|███████▊  | 89730/114105 [02:01<00:31, 783.14 examples/s]
Map:  78%|███████▊  | 89412/114105 [02:01<00:31, 775.67 examples/s]
Map:  81%|████████  | 91933/114105 [02:02<00:27, 820.88 examples/s]
Map:  79%|███████▉  | 90332/114105 [02:01<00:31, 753.78 examples/s]
Map:  79%|███████▊  | 89814/114105 [02:01<00:30, 793.20 examples/s]
Map:  78%|███████▊  | 89495/114105 [02:01<00:31, 785.90 examples/s]
Map:  79%|███████▉  | 90420/114105 [02:01<00:30, 783.82 examples/s]
Map:  79%|███████▉  | 89897/114105 [02:01<00:30, 801.26 examples/s]
Map:  79%|███████▊  | 89578/114105 [02:01<00:30, 795.41 examples/s]
Map:  79%|███████▉  | 89982/114105 [02:02<00:29, 808.45 examples/s]
Map:  81%|████████  | 92040/114105 [02:02<00:33, 660.16 examples/s]
Map:  79%|███████▊  | 89661/114105 [02:01<00:30, 801.26 examples/s]
Map:  79%|███████▉  | 90544/114105 [02:01<00:29, 793.40 examples/s]
Map:  81%|████████  | 92124/114105 [02:03<00:31, 695.04 examples/s]
Map:  79%|███████▊  | 89742/114105 [02:01<00:30, 800.45 examples/s]
Map:  79%|███████▉  | 90665/114105 [02:02<00:29, 794.38 examples/s]
Map:  81%|████████  | 92206/114105 [02:03<00:30, 722.13 examples/s]
Map:  79%|███████▊  | 89829/114105 [02:01<00:29, 816.36 examples/s]
Map:  79%|███████▉  | 90081/114105 [02:02<00:37, 634.96 examples/s]
Map:  81%|████████  | 92287/114105 [02:03<00:29, 742.36 examples/s]
Map:  79%|███████▉  | 89913/114105 [02:02<00:29, 817.61 examples/s]
Map:  79%|███████▉  | 90165/114105 [02:02<00:35, 681.25 examples/s]
Map:  80%|███████▉  | 90786/114105 [02:02<00:29, 794.44 examples/s]
Map:  81%|████████  | 92372/114105 [02:03<00:28, 768.15 examples/s]
Map:  79%|███████▉  | 90244/114105 [02:02<00:33, 705.20 examples/s]
Map:  80%|███████▉  | 90873/114105 [02:02<00:28, 810.01 examples/s]
Map:  81%|████████  | 92457/114105 [02:03<00:27, 787.65 examples/s]
Map:  79%|███████▉  | 90327/114105 [02:02<00:32, 735.88 examples/s]
Map:  79%|███████▉  | 90000/114105 [02:02<00:38, 619.50 examples/s]
Map:  80%|███████▉  | 90992/114105 [02:02<00:28, 801.37 examples/s]
Map:  81%|████████  | 92540/114105 [02:03<00:27, 796.89 examples/s]
Map:  79%|███████▉  | 90412/114105 [02:02<00:31, 760.59 examples/s]
Map:  79%|███████▉  | 90082/114105 [02:02<00:36, 664.27 examples/s]
Map:  81%|████████  | 92624/114105 [02:03<00:26, 808.31 examples/s]
Map:  79%|███████▉  | 90494/114105 [02:02<00:30, 773.84 examples/s]
Map:  79%|███████▉  | 90170/114105 [02:02<00:33, 716.36 examples/s]
Map:  81%|████████▏ | 92712/114105 [02:03<00:25, 825.82 examples/s]
Map:  80%|███████▉  | 91086/114105 [02:02<00:35, 641.97 examples/s]
Map:  79%|███████▉  | 90574/114105 [02:02<00:30, 778.58 examples/s]
Map:  79%|███████▉  | 90255/114105 [02:02<00:31, 748.98 examples/s]
Map:  81%|████████▏ | 92798/114105 [02:03<00:25, 832.08 examples/s]
Map:  80%|███████▉  | 91171/114105 [02:02<00:33, 684.51 examples/s]
Map:  79%|███████▉  | 90656/114105 [02:02<00:29, 788.10 examples/s]
Map:  79%|███████▉  | 90374/114105 [02:02<00:31, 764.30 examples/s]
Map:  81%|████████▏ | 92884/114105 [02:03<00:25, 837.50 examples/s]
Map:  80%|███████▉  | 91250/114105 [02:02<00:32, 708.31 examples/s]
Map:  80%|███████▉  | 90774/114105 [02:03<00:29, 784.30 examples/s]
Map:  79%|███████▉  | 90460/114105 [02:02<00:30, 784.97 examples/s]
Map:  80%|████████  | 91337/114105 [02:02<00:30, 745.77 examples/s]
Map:  80%|███████▉  | 90859/114105 [02:03<00:29, 796.90 examples/s]
Map:  79%|███████▉  | 90544/114105 [02:02<00:29, 794.51 examples/s]
Map:  80%|████████  | 91419/114105 [02:03<00:29, 762.16 examples/s]
Map:  82%|████████▏ | 93000/114105 [02:04<00:32, 649.81 examples/s]
Map:  79%|███████▉  | 90630/114105 [02:02<00:28, 809.74 examples/s]
Map:  80%|████████  | 91503/114105 [02:03<00:28, 781.30 examples/s]
Map:  80%|███████▉  | 90980/114105 [02:03<00:28, 797.53 examples/s]
Map:  82%|████████▏ | 93083/114105 [02:04<00:30, 688.53 examples/s]
Map:  80%|████████  | 91590/114105 [02:03<00:27, 805.93 examples/s]
Map:  80%|███████▉  | 90747/114105 [02:03<00:29, 796.38 examples/s]
Map:  82%|████████▏ | 93165/114105 [02:04<00:29, 716.59 examples/s]
Map:  80%|████████  | 91676/114105 [02:03<00:27, 817.03 examples/s]
Map:  80%|███████▉  | 90831/114105 [02:03<00:28, 804.29 examples/s]
Map:  80%|███████▉  | 91083/114105 [02:03<00:35, 648.88 examples/s]
Map:  82%|████████▏ | 93253/114105 [02:04<00:27, 756.09 examples/s]
Map:  80%|████████  | 91762/114105 [02:03<00:27, 826.91 examples/s]
Map:  80%|███████▉  | 90917/114105 [02:03<00:28, 816.09 examples/s]
Map:  80%|███████▉  | 91168/114105 [02:03<00:33, 689.86 examples/s]
Map:  82%|████████▏ | 93339/114105 [02:04<00:26, 782.33 examples/s]
Map:  81%|████████  | 91875/114105 [02:03<00:27, 795.92 examples/s]
Map:  80%|███████▉  | 91266/114105 [02:03<00:33, 676.17 examples/s]
Map:  82%|████████▏ | 93442/114105 [02:04<00:27, 743.63 examples/s]
Map:  81%|████████  | 91958/114105 [02:03<00:27, 802.20 examples/s]
Map:  80%|███████▉  | 91000/114105 [02:03<00:38, 604.11 examples/s]
Map:  80%|████████  | 91351/114105 [02:04<00:35, 637.88 examples/s]
Map:  82%|████████▏ | 93526/114105 [02:04<00:30, 674.21 examples/s]
Map:  80%|███████▉  | 91080/114105 [02:03<00:39, 579.44 examples/s]
Map:  80%|████████  | 91419/114105 [02:04<00:35, 645.39 examples/s]
Map:  82%|████████▏ | 93609/114105 [02:05<00:32, 631.91 examples/s]
Map:  81%|████████  | 92076/114105 [02:04<00:36, 608.01 examples/s]
Map:  80%|███████▉  | 91160/114105 [02:03<00:40, 562.24 examples/s]
Map:  80%|████████  | 91513/114105 [02:04<00:35, 635.65 examples/s]
Map:  81%|████████  | 92153/114105 [02:04<00:34, 639.74 examples/s]
Map:  82%|████████▏ | 93699/114105 [02:05<00:33, 617.28 examples/s]
Map:  80%|███████▉  | 91224/114105 [02:03<00:39, 576.95 examples/s]
Map:  81%|████████  | 92231/114105 [02:04<00:32, 670.44 examples/s]
Map:  80%|████████  | 91614/114105 [02:04<00:34, 644.51 examples/s]
Map:  80%|████████  | 91291/114105 [02:04<00:38, 597.40 examples/s]
Map:  82%|████████▏ | 93787/114105 [02:05<00:33, 602.52 examples/s]
Map:  81%|████████  | 92307/114105 [02:04<00:31, 687.01 examples/s]
Map:  80%|████████  | 91685/114105 [02:04<00:34, 656.11 examples/s]
Map:  80%|████████  | 91359/114105 [02:04<00:36, 616.47 examples/s]
Map:  82%|████████▏ | 93855/114105 [02:05<00:32, 619.29 examples/s]
Map:  81%|████████  | 92402/114105 [02:04<00:32, 667.29 examples/s]
Map:  80%|████████  | 91778/114105 [02:04<00:34, 642.37 examples/s]
Map:  80%|████████  | 91450/114105 [02:04<00:37, 607.08 examples/s]
Map:  82%|████████▏ | 93953/114105 [02:05<00:31, 629.87 examples/s]
Map:  80%|████████  | 91845/114105 [02:04<00:34, 646.95 examples/s]
Map:  81%|████████  | 92490/114105 [02:04<00:33, 638.47 examples/s]
Map:  80%|████████  | 91547/114105 [02:04<00:36, 617.83 examples/s]
Map:  81%|████████  | 91929/114105 [02:04<00:36, 610.81 examples/s]
Map:  80%|████████  | 91622/114105 [02:04<00:34, 648.54 examples/s]
Map:  81%|████████  | 92576/114105 [02:04<00:34, 615.51 examples/s]
Map:  81%|████████  | 91995/114105 [02:05<00:35, 620.24 examples/s]
Map:  82%|████████▏ | 94025/114105 [02:05<00:45, 437.73 examples/s]
Map:  80%|████████  | 91691/114105 [02:04<00:34, 654.38 examples/s]
Map:  81%|████████  | 92642/114105 [02:04<00:34, 623.16 examples/s]
Map:  81%|████████  | 92708/114105 [02:04<00:34, 627.46 examples/s]
Map:  82%|████████▏ | 94085/114105 [02:06<00:47, 424.12 examples/s]
Map:  80%|████████  | 91764/114105 [02:04<00:37, 590.14 examples/s]
Map:  81%|████████  | 92067/114105 [02:05<00:50, 440.26 examples/s]
Map:  83%|████████▎ | 94156/114105 [02:06<00:45, 435.48 examples/s]
Map:  80%|████████  | 91832/114105 [02:04<00:41, 538.98 examples/s]
Map:  81%|████████▏ | 92789/114105 [02:05<00:40, 528.98 examples/s]
Map:  81%|████████  | 92130/114105 [02:05<00:46, 476.33 examples/s]
Map:  83%|████████▎ | 94227/114105 [02:06<00:44, 443.86 examples/s]
Map:  81%|████████  | 91900/114105 [02:05<00:43, 506.97 examples/s]
Map:  81%|████████  | 92194/114105 [02:05<00:42, 512.07 examples/s]
Map:  81%|████████▏ | 92854/114105 [02:05<00:43, 493.57 examples/s]
Map:  83%|████████▎ | 94294/114105 [02:06<00:40, 488.33 examples/s]
Map:  81%|████████  | 91957/114105 [02:05<00:42, 519.28 examples/s]
Map:  81%|████████  | 92266/114105 [02:05<00:38, 560.49 examples/s]
Map:  81%|████████▏ | 92908/114105 [02:05<00:42, 502.91 examples/s]
Map:  83%|████████▎ | 94362/114105 [02:06<00:37, 529.24 examples/s]
Map:  81%|████████  | 92345/114105 [02:05<00:35, 616.51 examples/s]
Map:  81%|████████▏ | 92970/114105 [02:05<00:39, 529.80 examples/s]
Map:  83%|████████▎ | 94437/114105 [02:06<00:33, 580.48 examples/s]
Map:  81%|████████  | 92417/114105 [02:05<00:33, 641.47 examples/s]
Map:  81%|████████  | 92036/114105 [02:05<00:49, 442.10 examples/s]
Map:  83%|████████▎ | 94519/114105 [02:06<00:30, 640.31 examples/s]
Map:  81%|████████  | 92104/114105 [02:05<00:44, 491.86 examples/s]
Map:  82%|████████▏ | 93033/114105 [02:05<00:49, 423.96 examples/s]
Map:  81%|████████  | 92513/114105 [02:05<00:33, 637.93 examples/s]
Map:  83%|████████▎ | 94601/114105 [02:06<00:28, 685.57 examples/s]
Map:  81%|████████  | 92178/114105 [02:05<00:39, 548.47 examples/s]
Map:  82%|████████▏ | 93114/114105 [02:05<00:41, 507.35 examples/s]
Map:  81%|████████  | 92598/114105 [02:06<00:31, 690.90 examples/s]
Map:  83%|████████▎ | 94687/114105 [02:07<00:26, 728.75 examples/s]
Map:  81%|████████  | 92259/114105 [02:05<00:35, 611.64 examples/s]
Map:  82%|████████▏ | 93204/114105 [02:05<00:35, 595.94 examples/s]
Map:  81%|████████  | 92684/114105 [02:06<00:29, 733.52 examples/s]
Map:  83%|████████▎ | 94770/114105 [02:07<00:25, 754.41 examples/s]
Map:  81%|████████  | 92342/114105 [02:05<00:32, 664.66 examples/s]
Map:  82%|████████▏ | 93289/114105 [02:06<00:31, 657.07 examples/s]
Map:  83%|████████▎ | 94853/114105 [02:07<00:24, 770.54 examples/s]
Map:  81%|████████▏ | 92796/114105 [02:06<00:29, 733.18 examples/s]
Map:  81%|████████  | 92422/114105 [02:05<00:30, 700.18 examples/s]
Map:  82%|████████▏ | 93373/114105 [02:06<00:29, 703.96 examples/s]
Map:  83%|████████▎ | 94937/114105 [02:07<00:24, 786.25 examples/s]
Map:  81%|████████▏ | 92881/114105 [02:06<00:27, 760.60 examples/s]
Map:  81%|████████  | 92507/114105 [02:06<00:29, 738.48 examples/s]
Map:  82%|████████▏ | 93451/114105 [02:06<00:28, 721.30 examples/s]
Map:  81%|████████▏ | 92979/114105 [02:06<00:29, 717.27 examples/s]
Map:  81%|████████  | 92610/114105 [02:06<00:30, 712.73 examples/s]
Map:  82%|████████▏ | 93550/114105 [02:06<00:29, 697.28 examples/s]
Map:  83%|████████▎ | 95041/114105 [02:07<00:30, 626.47 examples/s]
Map:  81%|████████  | 92690/114105 [02:06<00:29, 733.42 examples/s]
Map:  82%|████████▏ | 93636/114105 [02:06<00:27, 738.62 examples/s]
Map:  83%|████████▎ | 95125/114105 [02:07<00:28, 673.34 examples/s]
Map:  81%|████████▏ | 92773/114105 [02:06<00:28, 757.62 examples/s]
Map:  82%|████████▏ | 93719/114105 [02:06<00:26, 762.31 examples/s]
Map:  82%|████████▏ | 93078/114105 [02:06<00:35, 586.90 examples/s]
Map:  83%|████████▎ | 95210/114105 [02:07<00:26, 714.41 examples/s]
Map:  81%|████████▏ | 92860/114105 [02:06<00:26, 788.40 examples/s]
Map:  82%|████████▏ | 93801/114105 [02:06<00:26, 777.38 examples/s]
Map:  82%|████████▏ | 93159/114105 [02:06<00:33, 631.23 examples/s]
Map:  84%|████████▎ | 95298/114105 [02:07<00:24, 754.63 examples/s]
Map:  81%|████████▏ | 92944/114105 [02:06<00:26, 798.88 examples/s]
Map:  82%|████████▏ | 93886/114105 [02:06<00:25, 796.02 examples/s]
Map:  82%|████████▏ | 93239/114105 [02:07<00:31, 668.95 examples/s]
Map:  84%|████████▎ | 95383/114105 [02:07<00:24, 777.57 examples/s]
Map:  82%|████████▏ | 93312/114105 [02:07<00:30, 681.14 examples/s]
Map:  84%|████████▎ | 95466/114105 [02:08<00:23, 786.81 examples/s]
Map:  82%|████████▏ | 93998/114105 [02:06<00:25, 773.37 examples/s]
Map:  82%|████████▏ | 93030/114105 [02:06<00:36, 580.47 examples/s]
Map:  82%|████████▏ | 93413/114105 [02:07<00:30, 677.12 examples/s]
Map:  84%|████████▍ | 95587/114105 [02:08<00:23, 783.38 examples/s]
Map:  82%|████████▏ | 93113/114105 [02:06<00:33, 634.82 examples/s]
Map:  82%|████████▏ | 93496/114105 [02:07<00:28, 712.62 examples/s]
Map:  82%|████████▏ | 94085/114105 [02:07<00:33, 594.22 examples/s]
Map:  84%|████████▍ | 95669/114105 [02:08<00:23, 789.85 examples/s]
Map:  82%|████████▏ | 93198/114105 [02:07<00:30, 684.59 examples/s]
Map:  82%|████████▏ | 93572/114105 [02:07<00:28, 723.16 examples/s]
Map:  83%|████████▎ | 94155/114105 [02:07<00:32, 614.05 examples/s]
Map:  82%|████████▏ | 93284/114105 [02:07<00:28, 725.97 examples/s]
Map:  84%|████████▍ | 95788/114105 [02:08<00:23, 787.07 examples/s]
Map:  82%|████████▏ | 93651/114105 [02:07<00:27, 739.98 examples/s]
Map:  83%|████████▎ | 94237/114105 [02:07<00:30, 662.15 examples/s]
Map:  83%|████████▎ | 94312/114105 [02:07<00:29, 680.36 examples/s]
Map:  82%|████████▏ | 93397/114105 [02:07<00:28, 733.41 examples/s]
Map:  84%|████████▍ | 95899/114105 [02:08<00:23, 766.95 examples/s]
Map:  82%|████████▏ | 93761/114105 [02:07<00:27, 732.74 examples/s]
Map:  84%|████████▍ | 95983/114105 [02:08<00:23, 780.58 examples/s]
Map:  82%|████████▏ | 93504/114105 [02:07<00:28, 722.95 examples/s]
Map:  83%|████████▎ | 94411/114105 [02:07<00:29, 667.44 examples/s]
Map:  82%|████████▏ | 93859/114105 [02:07<00:28, 702.99 examples/s]
Map:  83%|████████▎ | 94486/114105 [02:07<00:28, 683.27 examples/s]
Map:  82%|████████▏ | 93934/114105 [02:07<00:28, 713.26 examples/s]
Map:  82%|████████▏ | 93619/114105 [02:07<00:27, 734.60 examples/s]
Map:  83%|████████▎ | 94573/114105 [02:07<00:26, 730.19 examples/s]
Map:  84%|████████▍ | 96083/114105 [02:08<00:29, 608.28 examples/s]
Map:  82%|████████▏ | 93703/114105 [02:07<00:26, 758.41 examples/s]
Map:  83%|████████▎ | 94661/114105 [02:07<00:25, 769.25 examples/s]
Map:  84%|████████▍ | 96165/114105 [02:09<00:27, 650.67 examples/s]
Map:  82%|████████▏ | 93787/114105 [02:07<00:26, 774.80 examples/s]
Map:  82%|████████▏ | 94038/114105 [02:08<00:33, 602.08 examples/s]
Map:  84%|████████▍ | 96246/114105 [02:09<00:26, 685.39 examples/s]
Map:  82%|████████▏ | 93875/114105 [02:07<00:25, 798.67 examples/s]
Map:  83%|████████▎ | 94781/114105 [02:08<00:24, 773.81 examples/s]
Map:  82%|████████▏ | 94119/114105 [02:08<00:30, 646.94 examples/s]
Map:  84%|████████▍ | 96331/114105 [02:09<00:24, 721.26 examples/s]
Map:  83%|████████▎ | 94197/114105 [02:08<00:29, 677.93 examples/s]
Map:  82%|████████▏ | 93985/114105 [02:08<00:26, 773.69 examples/s]
Map:  83%|████████▎ | 94890/114105 [02:08<00:25, 754.71 examples/s]
Map:  85%|████████▍ | 96437/114105 [02:09<00:24, 710.53 examples/s]
Map:  83%|████████▎ | 94296/114105 [02:08<00:29, 665.86 examples/s]
Map:  83%|████████▎ | 94989/114105 [02:08<00:26, 720.31 examples/s]
Map:  83%|████████▎ | 94378/114105 [02:08<00:28, 701.28 examples/s]
Map:  85%|████████▍ | 96552/114105 [02:09<00:24, 724.91 examples/s]
Map:  82%|████████▏ | 94084/114105 [02:08<00:33, 598.73 examples/s]
Map:  83%|████████▎ | 94466/114105 [02:08<00:26, 745.82 examples/s]
Map:  85%|████████▍ | 96638/114105 [02:09<00:23, 755.69 examples/s]
Map:  83%|████████▎ | 94169/114105 [02:08<00:30, 649.54 examples/s]
Map:  83%|████████▎ | 95081/114105 [02:08<00:31, 597.82 examples/s]
Map:  83%|████████▎ | 94554/114105 [02:08<00:25, 778.12 examples/s]
Map:  85%|████████▍ | 96721/114105 [02:09<00:22, 771.47 examples/s]
Map:  83%|████████▎ | 94252/114105 [02:08<00:28, 689.20 examples/s]
Map:  83%|████████▎ | 95160/114105 [02:08<00:29, 636.23 examples/s]
Map:  83%|████████▎ | 94331/114105 [02:08<00:27, 712.02 examples/s]
Map:  83%|████████▎ | 94677/114105 [02:09<00:24, 790.08 examples/s]
Map:  85%|████████▍ | 96843/114105 [02:09<00:22, 782.94 examples/s]
Map:  83%|████████▎ | 95246/114105 [02:08<00:27, 685.38 examples/s]
Map:  84%|████████▎ | 95324/114105 [02:08<00:26, 705.95 examples/s]
Map:  83%|████████▎ | 94441/114105 [02:08<00:27, 716.72 examples/s]
Map:  83%|████████▎ | 94788/114105 [02:09<00:25, 769.03 examples/s]
Map:  85%|████████▍ | 96955/114105 [02:10<00:22, 762.43 examples/s]
Map:  83%|████████▎ | 94521/114105 [02:08<00:26, 732.96 examples/s]
Map:  83%|████████▎ | 94870/114105 [02:09<00:24, 779.92 examples/s]
Map:  84%|████████▎ | 95440/114105 [02:09<00:25, 724.97 examples/s]
Map:  83%|████████▎ | 94600/114105 [02:09<00:26, 744.83 examples/s]
Map:  83%|████████▎ | 94956/114105 [02:09<00:24, 797.48 examples/s]
Map:  84%|████████▎ | 95520/114105 [02:09<00:25, 740.02 examples/s]
Map:  85%|████████▌ | 97042/114105 [02:10<00:27, 613.40 examples/s]
Map:  83%|████████▎ | 94682/114105 [02:09<00:25, 761.34 examples/s]
Map:  84%|████████▍ | 95602/114105 [02:09<00:24, 758.11 examples/s]
Map:  85%|████████▌ | 97128/114105 [02:10<00:25, 663.09 examples/s]
Map:  83%|████████▎ | 94771/114105 [02:09<00:24, 792.45 examples/s]
Map:  83%|████████▎ | 95037/114105 [02:09<00:30, 626.29 examples/s]
Map:  84%|████████▍ | 95686/114105 [02:09<00:23, 775.69 examples/s]
Map:  85%|████████▌ | 97208/114105 [02:10<00:24, 692.96 examples/s]
Map:  83%|████████▎ | 94855/114105 [02:09<00:24, 800.60 examples/s]
Map:  83%|████████▎ | 95119/114105 [02:09<00:28, 667.58 examples/s]
Map:  84%|████████▍ | 95769/114105 [02:09<00:23, 788.25 examples/s]
Map:  85%|████████▌ | 97288/114105 [02:10<00:23, 717.78 examples/s]
Map:  83%|████████▎ | 94940/114105 [02:09<00:23, 811.07 examples/s]
Map:  83%|████████▎ | 95203/114105 [02:09<00:26, 708.42 examples/s]
Map:  84%|████████▍ | 95853/114105 [02:09<00:22, 799.12 examples/s]
Map:  85%|████████▌ | 97392/114105 [02:10<00:23, 705.89 examples/s]
Map:  84%|████████▎ | 95284/114105 [02:09<00:25, 733.40 examples/s]
Map:  84%|████████▍ | 95963/114105 [02:09<00:23, 767.88 examples/s]
Map:  85%|████████▌ | 97468/114105 [02:10<00:23, 716.48 examples/s]
Map:  84%|████████▎ | 95366/114105 [02:09<00:24, 756.23 examples/s]
Map:  83%|████████▎ | 95042/114105 [02:09<00:29, 638.21 examples/s]
Map:  85%|████████▌ | 97554/114105 [02:10<00:22, 750.77 examples/s]
Map:  83%|████████▎ | 95128/114105 [02:09<00:27, 687.91 examples/s]
Map:  84%|████████▎ | 95484/114105 [02:10<00:24, 762.48 examples/s]
Map:  86%|████████▌ | 97639/114105 [02:11<00:21, 774.42 examples/s]
Map:  84%|████████▍ | 96081/114105 [02:10<00:28, 629.83 examples/s]
Map:  83%|████████▎ | 95212/114105 [02:09<00:26, 723.45 examples/s]
Map:  86%|████████▌ | 97721/114105 [02:11<00:20, 782.70 examples/s]
Map:  84%|████████▍ | 95602/114105 [02:10<00:24, 767.34 examples/s]
Map:  84%|████████▍ | 96170/114105 [02:10<00:26, 683.48 examples/s]
Map:  84%|████████▎ | 95297/114105 [02:09<00:24, 752.37 examples/s]
Map:  86%|████████▌ | 97805/114105 [02:11<00:20, 797.98 examples/s]
Map:  84%|████████▍ | 95682/114105 [02:10<00:23, 774.93 examples/s]
Map:  84%|████████▍ | 96250/114105 [02:10<00:25, 708.82 examples/s]
Map:  84%|████████▎ | 95382/114105 [02:10<00:24, 777.01 examples/s]
Map:  84%|████████▍ | 95761/114105 [02:10<00:23, 777.44 examples/s]
Map:  84%|████████▎ | 95470/114105 [02:10<00:23, 801.08 examples/s]
Map:  86%|████████▌ | 97906/114105 [02:11<00:21, 747.24 examples/s]
Map:  84%|████████▍ | 96347/114105 [02:10<00:26, 681.07 examples/s]
Map:  84%|████████▍ | 95840/114105 [02:10<00:23, 777.38 examples/s]
Map:  85%|████████▍ | 96432/114105 [02:10<00:24, 720.00 examples/s]
Map:  84%|████████▍ | 95582/114105 [02:10<00:23, 776.37 examples/s]
Map:  84%|████████▍ | 95952/114105 [02:10<00:23, 758.01 examples/s]
Map:  86%|████████▌ | 98000/114105 [02:11<00:27, 589.22 examples/s]
Map:  85%|████████▍ | 96508/114105 [02:10<00:24, 729.15 examples/s]
Map:  84%|████████▍ | 95702/114105 [02:10<00:23, 780.83 examples/s]
Map:  86%|████████▌ | 98086/114105 [02:11<00:24, 646.27 examples/s]
Map:  85%|████████▍ | 96589/114105 [02:10<00:23, 747.80 examples/s]
Map:  84%|████████▍ | 95787/114105 [02:10<00:23, 794.91 examples/s]
Map:  86%|████████▌ | 98173/114105 [02:11<00:22, 695.11 examples/s]
Map:  84%|████████▍ | 96035/114105 [02:10<00:30, 600.79 examples/s]
Map:  85%|████████▍ | 96710/114105 [02:10<00:22, 767.52 examples/s]
Map:  84%|████████▍ | 95869/114105 [02:10<00:22, 798.34 examples/s]
Map:  86%|████████▌ | 98249/114105 [02:11<00:22, 708.34 examples/s]
Map:  84%|████████▍ | 96114/114105 [02:11<00:28, 640.47 examples/s]
Map:  84%|████████▍ | 96187/114105 [02:11<00:27, 659.36 examples/s]
Map:  85%|████████▍ | 96810/114105 [02:11<00:23, 727.72 examples/s]
Map:  84%|████████▍ | 95977/114105 [02:10<00:23, 767.99 examples/s]
Map:  86%|████████▌ | 98341/114105 [02:12<00:23, 673.35 examples/s]
Map:  84%|████████▍ | 96261/114105 [02:11<00:26, 678.49 examples/s]
Map:  85%|████████▍ | 96885/114105 [02:11<00:23, 729.57 examples/s]
Map:  86%|████████▋ | 98423/114105 [02:12<00:22, 705.90 examples/s]
Map:  84%|████████▍ | 96336/114105 [02:11<00:25, 694.58 examples/s]
Map:  85%|████████▍ | 96970/114105 [02:11<00:22, 757.19 examples/s]
Map:  84%|████████▍ | 96082/114105 [02:11<00:29, 617.46 examples/s]
Map:  86%|████████▋ | 98508/114105 [02:12<00:21, 741.92 examples/s]
Map:  84%|████████▍ | 96413/114105 [02:11<00:24, 712.56 examples/s]
Map:  84%|████████▍ | 96164/114105 [02:11<00:27, 658.70 examples/s]
Map:  86%|████████▋ | 98586/114105 [02:12<00:20, 749.22 examples/s]
Map:  84%|████████▍ | 96251/114105 [02:11<00:25, 705.70 examples/s]
Map:  86%|████████▋ | 98668/114105 [02:12<00:20, 764.50 examples/s]
Map:  85%|████████▍ | 96519/114105 [02:11<00:24, 706.77 examples/s]
Map:  85%|████████▌ | 97083/114105 [02:11<00:27, 608.51 examples/s]
Map:  85%|████████▍ | 96596/114105 [02:11<00:24, 722.30 examples/s]
Map:  85%|████████▌ | 97154/114105 [02:11<00:26, 628.27 examples/s]
Map:  84%|████████▍ | 96359/114105 [02:11<00:25, 706.92 examples/s]
Map:  87%|████████▋ | 98770/114105 [02:12<00:21, 726.62 examples/s]
Map:  85%|████████▍ | 96675/114105 [02:11<00:23, 738.13 examples/s]
Map:  85%|████████▌ | 97255/114105 [02:11<00:26, 640.69 examples/s]
Map:  85%|████████▍ | 96468/114105 [02:11<00:24, 712.46 examples/s]
Map:  87%|████████▋ | 98875/114105 [02:12<00:21, 714.38 examples/s]
Map:  85%|████████▍ | 96757/114105 [02:11<00:22, 759.12 examples/s]
Map:  85%|████████▌ | 97339/114105 [02:11<00:24, 684.58 examples/s]
Map:  85%|████████▍ | 96551/114105 [02:11<00:23, 737.52 examples/s]
Map:  87%|████████▋ | 98956/114105 [02:12<00:20, 735.62 examples/s]
Map:  85%|████████▍ | 96834/114105 [02:12<00:22, 759.11 examples/s]
Map:  85%|████████▌ | 97421/114105 [02:11<00:23, 715.90 examples/s]
Map:  85%|████████▍ | 96634/114105 [02:11<00:23, 756.82 examples/s]
Map:  85%|████████▍ | 96913/114105 [02:12<00:22, 762.94 examples/s]
Map:  85%|████████▌ | 97503/114105 [02:12<00:22, 740.36 examples/s]
Map:  85%|████████▍ | 96716/114105 [02:11<00:22, 770.02 examples/s]
Map:  87%|████████▋ | 99040/114105 [02:13<00:25, 587.92 examples/s]
Map:  86%|████████▌ | 97586/114105 [02:12<00:21, 761.62 examples/s]
Map:  85%|████████▍ | 96796/114105 [02:11<00:22, 775.96 examples/s]
Map:  87%|████████▋ | 99117/114105 [02:13<00:23, 627.86 examples/s]
Map:  85%|████████▌ | 97000/114105 [02:12<00:29, 570.35 examples/s]
Map:  86%|████████▌ | 97692/114105 [02:12<00:22, 736.77 examples/s]
Map:  85%|████████▌ | 97076/114105 [02:12<00:27, 613.05 examples/s]
Map:  85%|████████▍ | 96915/114105 [02:12<00:22, 777.40 examples/s]
Map:  87%|████████▋ | 99216/114105 [02:13<00:23, 633.32 examples/s]
Map:  86%|████████▌ | 97774/114105 [02:12<00:21, 756.77 examples/s]
Map:  85%|████████▌ | 97153/114105 [02:12<00:26, 650.00 examples/s]
Map:  87%|████████▋ | 99295/114105 [02:13<00:22, 668.72 examples/s]
Map:  86%|████████▌ | 97853/114105 [02:12<00:21, 762.17 examples/s]
Map:  85%|████████▌ | 97229/114105 [02:12<00:24, 677.74 examples/s]
Map:  85%|████████▌ | 97000/114105 [02:12<00:27, 629.90 examples/s]
Map:  87%|████████▋ | 99374/114105 [02:13<00:21, 695.94 examples/s]
Map:  86%|████████▌ | 97935/114105 [02:12<00:20, 773.19 examples/s]
Map:  85%|████████▌ | 97307/114105 [02:12<00:23, 703.18 examples/s]
Map:  85%|████████▌ | 97081/114105 [02:12<00:25, 669.57 examples/s]
Map:  87%|████████▋ | 99451/114105 [02:13<00:20, 711.73 examples/s]
Map:  85%|████████▌ | 97386/114105 [02:12<00:23, 724.71 examples/s]
Map:  85%|████████▌ | 97172/114105 [02:12<00:23, 726.64 examples/s]
Map:  87%|████████▋ | 99536/114105 [02:13<00:19, 748.70 examples/s]
Map:  85%|████████▌ | 97464/114105 [02:12<00:22, 737.48 examples/s]
Map:  86%|████████▌ | 98040/114105 [02:12<00:26, 609.35 examples/s]
Map:  85%|████████▌ | 97250/114105 [02:12<00:22, 737.42 examples/s]
Map:  87%|████████▋ | 99614/114105 [02:13<00:19, 755.63 examples/s]
Map:  85%|████████▌ | 97543/114105 [02:13<00:22, 749.91 examples/s]
Map:  85%|████████▌ | 97334/114105 [02:12<00:21, 763.68 examples/s]
Map:  86%|████████▌ | 98139/114105 [02:12<00:25, 621.88 examples/s]
Map:  87%|████████▋ | 99709/114105 [02:14<00:20, 707.76 examples/s]
Map:  86%|████████▌ | 97620/114105 [02:13<00:21, 753.79 examples/s]
Map:  86%|████████▌ | 98217/114105 [02:13<00:24, 655.88 examples/s]
Map:  85%|████████▌ | 97455/114105 [02:12<00:21, 775.32 examples/s]
Map:  87%|████████▋ | 99791/114105 [02:14<00:19, 734.47 examples/s]
Map:  86%|████████▌ | 97700/114105 [02:13<00:21, 761.10 examples/s]
Map:  86%|████████▌ | 98300/114105 [02:13<00:22, 695.88 examples/s]
Map:  85%|████████▌ | 97536/114105 [02:12<00:21, 782.93 examples/s]
Map:  88%|████████▊ | 99905/114105 [02:14<00:19, 740.45 examples/s]
Map:  86%|████████▌ | 97812/114105 [02:13<00:21, 754.04 examples/s]
Map:  86%|████████▌ | 98384/114105 [02:13<00:21, 730.42 examples/s]
Map:  86%|████████▌ | 97617/114105 [02:13<00:20, 787.50 examples/s]
Map:  88%|████████▊ | 99984/114105 [02:14<00:18, 749.57 examples/s]
Map:  86%|████████▌ | 97699/114105 [02:13<00:20, 795.69 examples/s]
Map:  86%|████████▋ | 98470/114105 [02:13<00:20, 761.13 examples/s]
Map:  86%|████████▌ | 97924/114105 [02:13<00:21, 748.92 examples/s]
Map:  86%|████████▌ | 97782/114105 [02:13<00:20, 803.14 examples/s]
Map:  86%|████████▋ | 98555/114105 [02:13<00:19, 782.96 examples/s]
Map:  88%|████████▊ | 100066/114105 [02:14<00:24, 568.66 examples/s]
Map:  86%|████████▌ | 98000/114105 [02:13<00:26, 603.19 examples/s]
Map:  86%|████████▋ | 98660/114105 [02:13<00:20, 749.84 examples/s]
Map:  86%|████████▌ | 97884/114105 [02:13<00:21, 746.60 examples/s]
Map:  88%|████████▊ | 100130/114105 [02:14<00:24, 580.79 examples/s]
Map:  86%|████████▌ | 98069/114105 [02:13<00:25, 620.21 examples/s]
Map:  88%|████████▊ | 100203/114105 [02:14<00:22, 614.20 examples/s]
Map:  87%|████████▋ | 98771/114105 [02:13<00:20, 743.45 examples/s]
Map:  86%|████████▌ | 97997/114105 [02:13<00:21, 745.95 examples/s]
Map:  86%|████████▌ | 98142/114105 [02:13<00:24, 645.03 examples/s]
Map:  88%|████████▊ | 100286/114105 [02:14<00:20, 665.82 examples/s]
Map:  87%|████████▋ | 98859/114105 [02:13<00:19, 774.38 examples/s]
Map:  86%|████████▌ | 98222/114105 [02:14<00:23, 683.51 examples/s]
Map:  87%|████████▋ | 98940/114105 [02:13<00:19, 782.75 examples/s]
Map:  88%|████████▊ | 100374/114105 [02:15<00:19, 719.07 examples/s]
Map:  86%|████████▌ | 98083/114105 [02:13<00:26, 608.63 examples/s]
Map:  86%|████████▌ | 98307/114105 [02:14<00:21, 724.29 examples/s]
Map:  88%|████████▊ | 100454/114105 [02:15<00:18, 740.02 examples/s]
Map:  86%|████████▌ | 98171/114105 [02:13<00:23, 665.52 examples/s]
Map:  86%|████████▌ | 98387/114105 [02:14<00:21, 742.54 examples/s]
Map:  86%|████████▋ | 98465/114105 [02:14<00:20, 749.27 examples/s]
Map:  87%|████████▋ | 99033/114105 [02:14<00:25, 594.87 examples/s]
Map:  88%|████████▊ | 100561/114105 [02:15<00:18, 724.22 examples/s]
Map:  86%|████████▌ | 98272/114105 [02:14<00:23, 664.57 examples/s]
Map:  86%|████████▋ | 98542/114105 [02:14<00:20, 752.64 examples/s]
Map:  86%|████████▌ | 98344/114105 [02:14<00:23, 675.49 examples/s]
Map:  87%|████████▋ | 99142/114105 [02:14<00:23, 629.69 examples/s]
Map:  88%|████████▊ | 100677/114105 [02:15<00:18, 737.02 examples/s]
Map:  86%|████████▋ | 98623/114105 [02:14<00:20, 759.61 examples/s]
Map:  86%|████████▋ | 98431/114105 [02:14<00:21, 721.67 examples/s]
Map:  87%|████████▋ | 99223/114105 [02:14<00:22, 666.42 examples/s]
Map:  88%|████████▊ | 100760/114105 [02:15<00:17, 757.06 examples/s]
Map:  86%|████████▋ | 98517/114105 [02:14<00:20, 755.67 examples/s]
Map:  87%|████████▋ | 98739/114105 [02:14<00:20, 761.30 examples/s]
Map:  87%|████████▋ | 99305/114105 [02:14<00:21, 699.44 examples/s]
Map:  88%|████████▊ | 100876/114105 [02:15<00:17, 760.49 examples/s]
Map:  86%|████████▋ | 98603/114105 [02:14<00:19, 779.39 examples/s]
Map:  87%|████████▋ | 99386/114105 [02:14<00:20, 725.35 examples/s]
Map:  87%|████████▋ | 98855/114105 [02:14<00:19, 762.90 examples/s]
Map:  88%|████████▊ | 100958/114105 [02:15<00:17, 772.28 examples/s]
Map:  86%|████████▋ | 98687/114105 [02:14<00:19, 794.51 examples/s]
Map:  87%|████████▋ | 99471/114105 [02:14<00:19, 755.50 examples/s]
Map:  87%|████████▋ | 98934/114105 [02:14<00:19, 765.97 examples/s]
Map:  87%|████████▋ | 98794/114105 [02:14<00:20, 761.21 examples/s]
Map:  87%|████████▋ | 99574/114105 [02:14<00:19, 729.58 examples/s]
Map:  89%|████████▊ | 101041/114105 [02:16<00:21, 611.86 examples/s]
Map:  87%|████████▋ | 99653/114105 [02:15<00:19, 740.84 examples/s]
Map:  89%|████████▊ | 101122/114105 [02:16<00:19, 655.57 examples/s]
Map:  87%|████████▋ | 98899/114105 [02:14<00:20, 736.44 examples/s]
Map:  87%|████████▋ | 99039/114105 [02:15<00:24, 622.08 examples/s]
Map:  87%|████████▋ | 99738/114105 [02:15<00:18, 768.52 examples/s]
Map:  89%|████████▊ | 101204/114105 [02:16<00:18, 690.58 examples/s]
Map:  87%|████████▋ | 98978/114105 [02:14<00:20, 747.65 examples/s]
Map:  87%|████████▋ | 99117/114105 [02:15<00:22, 652.81 examples/s]
Map:  87%|████████▋ | 99823/114105 [02:15<00:18, 788.21 examples/s]
Map:  89%|████████▉ | 101286/114105 [02:16<00:17, 721.64 examples/s]
Map:  87%|████████▋ | 99196/114105 [02:15<00:21, 684.29 examples/s]
Map:  88%|████████▊ | 99909/114105 [02:15<00:17, 804.33 examples/s]
Map:  89%|████████▉ | 101374/114105 [02:16<00:16, 760.67 examples/s]
Map:  87%|████████▋ | 99272/114105 [02:15<00:21, 700.29 examples/s]
Map:  87%|████████▋ | 99087/114105 [02:15<00:24, 622.42 examples/s]
Map:  88%|████████▊ | 99993/114105 [02:15<00:17, 809.21 examples/s]
Map:  89%|████████▉ | 101458/114105 [02:16<00:16, 780.54 examples/s]
Map:  87%|████████▋ | 99347/114105 [02:15<00:20, 710.70 examples/s]
Map:  87%|████████▋ | 99160/114105 [02:15<00:23, 643.38 examples/s]
Map:  89%|████████▉ | 101542/114105 [02:16<00:15, 795.97 examples/s]
Map:  87%|████████▋ | 99423/114105 [02:15<00:20, 722.04 examples/s]
Map:  87%|████████▋ | 99231/114105 [02:15<00:22, 657.04 examples/s]
Map:  88%|████████▊ | 100082/114105 [02:15<00:23, 587.33 examples/s]
Map:  87%|████████▋ | 99310/114105 [02:15<00:21, 688.73 examples/s]
Map:  89%|████████▉ | 101663/114105 [02:16<00:15, 796.67 examples/s]
Map:  87%|████████▋ | 99535/114105 [02:15<00:20, 728.19 examples/s]
Map:  88%|████████▊ | 100166/114105 [02:15<00:21, 643.09 examples/s]
Map:  87%|████████▋ | 99393/114105 [02:15<00:20, 724.22 examples/s]
Map:  89%|████████▉ | 101745/114105 [02:16<00:15, 800.57 examples/s]
Map:  87%|████████▋ | 99616/114105 [02:15<00:19, 747.25 examples/s]
Map:  88%|████████▊ | 100255/114105 [02:15<00:19, 701.22 examples/s]
Map:  87%|████████▋ | 99476/114105 [02:15<00:19, 752.56 examples/s]
Map:  89%|████████▉ | 101826/114105 [02:17<00:15, 800.36 examples/s]
Map:  87%|████████▋ | 99700/114105 [02:16<00:18, 769.05 examples/s]
Map:  88%|████████▊ | 100336/114105 [02:15<00:18, 728.37 examples/s]
Map:  87%|████████▋ | 99558/114105 [02:15<00:18, 771.33 examples/s]
Map:  89%|████████▉ | 101909/114105 [02:17<00:15, 804.52 examples/s]
Map:  87%|████████▋ | 99789/114105 [02:16<00:17, 799.37 examples/s]
Map:  87%|████████▋ | 99640/114105 [02:15<00:18, 781.93 examples/s]
Map:  89%|████████▉ | 101991/114105 [02:17<00:15, 802.19 examples/s]
Map:  88%|████████▊ | 99874/114105 [02:16<00:17, 808.80 examples/s]
Map:  88%|████████▊ | 100442/114105 [02:16<00:19, 717.52 examples/s]
Map:  88%|████████▊ | 99961/114105 [02:16<00:17, 819.15 examples/s]
Map:  87%|████████▋ | 99745/114105 [02:16<00:19, 746.78 examples/s]
Map:  88%|████████▊ | 100545/114105 [02:16<00:19, 704.43 examples/s]
Map:  89%|████████▉ | 102082/114105 [02:17<00:19, 621.76 examples/s]
Map:  87%|████████▋ | 99825/114105 [02:16<00:18, 758.41 examples/s]
Map:  88%|████████▊ | 100631/114105 [02:16<00:18, 740.33 examples/s]
Map:  90%|████████▉ | 102163/114105 [02:17<00:17, 665.09 examples/s]
Map:  88%|████████▊ | 99909/114105 [02:16<00:18, 780.03 examples/s]
Map:  88%|████████▊ | 100076/114105 [02:16<00:22, 632.15 examples/s]
Map:  88%|████████▊ | 100714/114105 [02:16<00:17, 759.18 examples/s]
Map:  90%|████████▉ | 102249/114105 [02:17<00:16, 711.36 examples/s]
Map:  88%|████████▊ | 99992/114105 [02:16<00:17, 791.79 examples/s]
Map:  88%|████████▊ | 100151/114105 [02:16<00:21, 655.73 examples/s]
Map:  88%|████████▊ | 100799/114105 [02:16<00:17, 780.74 examples/s]
Map:  90%|████████▉ | 102328/114105 [02:17<00:16, 730.13 examples/s]
Map:  88%|████████▊ | 100885/114105 [02:16<00:16, 800.89 examples/s]
Map:  88%|████████▊ | 100258/114105 [02:16<00:20, 670.79 examples/s]
Map:  90%|████████▉ | 102408/114105 [02:17<00:15, 747.15 examples/s]
Map:  88%|████████▊ | 100079/114105 [02:16<00:22, 610.82 examples/s]
Map:  90%|████████▉ | 102488/114105 [02:17<00:15, 761.58 examples/s]
Map:  88%|████████▊ | 100333/114105 [02:17<00:20, 686.95 examples/s]
Map:  89%|████████▊ | 100995/114105 [02:16<00:17, 766.85 examples/s]
Map:  88%|████████▊ | 100179/114105 [02:16<00:22, 624.99 examples/s]
Map:  90%|████████▉ | 102571/114105 [02:18<00:14, 778.89 examples/s]
Map:  88%|████████▊ | 100407/114105 [02:17<00:19, 697.87 examples/s]
Map:  88%|████████▊ | 100264/114105 [02:16<00:20, 674.99 examples/s]
Map:  90%|████████▉ | 102655/114105 [02:18<00:14, 794.53 examples/s]
Map:  88%|████████▊ | 100488/114105 [02:17<00:18, 724.95 examples/s]
Map:  89%|████████▊ | 101082/114105 [02:17<00:21, 594.14 examples/s]
Map:  88%|████████▊ | 100349/114105 [02:16<00:19, 716.75 examples/s]
Map:  88%|████████▊ | 100568/114105 [02:17<00:18, 743.44 examples/s]
Map:  89%|████████▊ | 101168/114105 [02:17<00:19, 649.22 examples/s]
Map:  90%|█████████ | 102774/114105 [02:18<00:14, 791.90 examples/s]
Map:  88%|████████▊ | 100432/114105 [02:17<00:18, 744.67 examples/s]
Map:  89%|████████▊ | 101250/114105 [02:17<00:18, 686.16 examples/s]
Map:  90%|█████████ | 102861/114105 [02:18<00:13, 810.38 examples/s]
Map:  88%|████████▊ | 100684/114105 [02:17<00:17, 750.48 examples/s]
Map:  88%|████████▊ | 100520/114105 [02:17<00:17, 774.47 examples/s]
Map:  89%|████████▉ | 101337/114105 [02:17<00:17, 728.87 examples/s]
Map:  90%|█████████ | 102945/114105 [02:18<00:13, 815.37 examples/s]
Map:  88%|████████▊ | 100603/114105 [02:17<00:17, 786.18 examples/s]
Map:  88%|████████▊ | 100797/114105 [02:17<00:17, 748.29 examples/s]
Map:  89%|████████▉ | 101440/114105 [02:17<00:17, 709.37 examples/s]
Map:  88%|████████▊ | 100875/114105 [02:17<00:17, 753.94 examples/s]
Map:  88%|████████▊ | 100711/114105 [02:17<00:17, 758.55 examples/s]
Map:  90%|█████████ | 103040/114105 [02:18<00:17, 626.26 examples/s]
Map:  89%|████████▉ | 101518/114105 [02:17<00:17, 724.48 examples/s]
Map:  88%|████████▊ | 100954/114105 [02:17<00:17, 762.30 examples/s]
Map:  88%|████████▊ | 100795/114105 [02:17<00:17, 778.13 examples/s]
Map:  90%|█████████ | 103119/114105 [02:18<00:16, 662.10 examples/s]
Map:  89%|████████▉ | 101601/114105 [02:17<00:16, 746.67 examples/s]
Map:  90%|█████████ | 103204/114105 [02:18<00:15, 703.05 examples/s]
Map:  88%|████████▊ | 100913/114105 [02:17<00:16, 776.87 examples/s]
Map:  89%|████████▉ | 101679/114105 [02:17<00:16, 752.98 examples/s]
Map:  89%|████████▊ | 101037/114105 [02:18<00:22, 588.29 examples/s]
Map:  91%|█████████ | 103287/114105 [02:19<00:14, 733.03 examples/s]
Map:  89%|████████▊ | 100997/114105 [02:17<00:16, 787.55 examples/s]
Map:  89%|████████▉ | 101760/114105 [02:17<00:16, 763.59 examples/s]
Map:  89%|████████▊ | 101120/114105 [02:18<00:20, 639.34 examples/s]
Map:  91%|█████████ | 103371/114105 [02:19<00:14, 758.70 examples/s]
Map:  89%|████████▉ | 101839/114105 [02:18<00:16, 765.84 examples/s]
Map:  89%|████████▊ | 101202/114105 [02:18<00:18, 681.05 examples/s]
Map:  91%|█████████ | 103456/114105 [02:19<00:13, 780.00 examples/s]
Map:  89%|████████▉ | 101280/114105 [02:18<00:18, 703.72 examples/s]
Map:  89%|████████▊ | 101103/114105 [02:17<00:21, 604.51 examples/s]
Map:  89%|████████▉ | 101937/114105 [02:18<00:16, 717.91 examples/s]
Map:  91%|█████████ | 103541/114105 [02:19<00:13, 795.63 examples/s]
Map:  89%|████████▉ | 101361/114105 [02:18<00:17, 731.98 examples/s]
Map:  89%|████████▊ | 101180/114105 [02:18<00:20, 637.55 examples/s]
Map:  91%|█████████ | 103659/114105 [02:19<00:13, 789.53 examples/s]
Map:  89%|████████▉ | 101269/114105 [02:18<00:18, 694.25 examples/s]
Map:  89%|████████▉ | 101477/114105 [02:18<00:16, 743.94 examples/s]
Map:  89%|████████▉ | 102041/114105 [02:18<00:20, 576.56 examples/s]
Map:  91%|█████████ | 103742/114105 [02:19<00:12, 798.76 examples/s]
Map:  89%|████████▉ | 101352/114105 [02:18<00:17, 726.23 examples/s]
Map:  89%|████████▉ | 101557/114105 [02:18<00:16, 756.76 examples/s]
Map:  90%|████████▉ | 102124/114105 [02:18<00:19, 628.23 examples/s]
Map:  91%|█████████ | 103827/114105 [02:19<00:12, 811.74 examples/s]
Map:  89%|████████▉ | 101436/114105 [02:18<00:16, 751.28 examples/s]
Map:  90%|████████▉ | 102204/114105 [02:18<00:17, 666.42 examples/s]
Map:  89%|████████▉ | 101673/114105 [02:18<00:16, 759.07 examples/s]
Map:  89%|████████▉ | 101521/114105 [02:18<00:16, 776.03 examples/s]
Map:  91%|█████████ | 103950/114105 [02:19<00:12, 809.43 examples/s]
Map:  90%|████████▉ | 102282/114105 [02:18<00:17, 690.40 examples/s]
Map:  89%|████████▉ | 101752/114105 [02:18<00:16, 763.62 examples/s]
Map:  89%|████████▉ | 101624/114105 [02:18<00:16, 737.23 examples/s]
Map:  89%|████████▉ | 101830/114105 [02:19<00:16, 766.27 examples/s]
Map:  90%|████████▉ | 102376/114105 [02:18<00:17, 664.41 examples/s]
Map:  91%|█████████ | 104040/114105 [02:20<00:15, 637.64 examples/s]
Map:  89%|████████▉ | 101742/114105 [02:18<00:16, 750.87 examples/s]
Map:  90%|████████▉ | 102456/114105 [02:19<00:16, 695.77 examples/s]
Map:  89%|████████▉ | 101945/114105 [02:19<00:15, 761.32 examples/s]
Map:  91%|█████████▏| 104125/114105 [02:20<00:14, 683.09 examples/s]
Map:  89%|████████▉ | 101828/114105 [02:18<00:15, 776.49 examples/s]
Map:  90%|████████▉ | 102537/114105 [02:19<00:15, 723.83 examples/s]
Map:  91%|█████████▏| 104207/114105 [02:20<00:13, 715.18 examples/s]
Map:  89%|████████▉ | 101911/114105 [02:19<00:15, 787.72 examples/s]
Map:  90%|████████▉ | 102617/114105 [02:19<00:15, 744.05 examples/s]
Map:  89%|████████▉ | 102041/114105 [02:19<00:19, 616.37 examples/s]
Map:  91%|█████████▏| 104293/114105 [02:20<00:13, 749.40 examples/s]
Map:  89%|████████▉ | 101994/114105 [02:19<00:15, 796.82 examples/s]
Map:  90%|█████████ | 102703/114105 [02:19<00:14, 775.83 examples/s]
Map:  89%|████████▉ | 102119/114105 [02:19<00:18, 649.95 examples/s]
Map:  92%|█████████▏| 104410/114105 [02:20<00:12, 758.46 examples/s]
Map:  90%|████████▉ | 102197/114105 [02:19<00:17, 679.23 examples/s]
Map:  90%|█████████ | 102805/114105 [02:19<00:15, 732.60 examples/s]
Map:  92%|█████████▏| 104498/114105 [02:20<00:12, 784.72 examples/s]
Map:  90%|████████▉ | 102269/114105 [02:19<00:17, 683.11 examples/s]
Map:  89%|████████▉ | 102105/114105 [02:19<00:20, 587.52 examples/s]
Map:  92%|█████████▏| 104579/114105 [02:20<00:12, 785.49 examples/s]
Map:  90%|█████████ | 102913/114105 [02:19<00:15, 725.12 examples/s]
Map:  90%|████████▉ | 102342/114105 [02:19<00:17, 691.25 examples/s]
Map:  90%|████████▉ | 102188/114105 [02:19<00:18, 636.40 examples/s]
Map:  92%|█████████▏| 104664/114105 [02:20<00:11, 800.49 examples/s]
Map:  90%|█████████ | 102998/114105 [02:19<00:14, 754.22 examples/s]
Map:  90%|████████▉ | 102425/114105 [02:19<00:16, 725.47 examples/s]
Map:  90%|████████▉ | 102270/114105 [02:19<00:17, 676.90 examples/s]
Map:  92%|█████████▏| 104752/114105 [02:20<00:11, 820.14 examples/s]
Map:  90%|████████▉ | 102509/114105 [02:20<00:15, 755.79 examples/s]
Map:  90%|████████▉ | 102361/114105 [02:19<00:16, 731.90 examples/s]
Map:  90%|█████████ | 103086/114105 [02:19<00:18, 605.49 examples/s]
Map:  92%|█████████▏| 104876/114105 [02:21<00:11, 818.65 examples/s]
Map:  90%|████████▉ | 102444/114105 [02:19<00:15, 755.33 examples/s]
Map:  90%|████████▉ | 102627/114105 [02:20<00:15, 764.08 examples/s]
Map:  90%|█████████ | 103166/114105 [02:20<00:16, 647.23 examples/s]
Map:  92%|█████████▏| 104966/114105 [02:21<00:10, 838.11 examples/s]
Map:  90%|█████████ | 102708/114105 [02:20<00:14, 774.55 examples/s]
Map:  90%|████████▉ | 102542/114105 [02:19<00:16, 717.36 examples/s]
Map:  90%|█████████ | 103265/114105 [02:20<00:16, 647.48 examples/s]
Map:  90%|█████████ | 102821/114105 [02:20<00:14, 765.55 examples/s]
Map:  91%|█████████ | 103346/114105 [02:20<00:15, 682.48 examples/s]
Map:  90%|████████▉ | 102658/114105 [02:20<00:15, 733.29 examples/s]
Map:  92%|█████████▏| 105078/114105 [02:21<00:13, 659.68 examples/s]
Map:  90%|█████████ | 102903/114105 [02:20<00:14, 776.26 examples/s]
Map:  91%|█████████ | 103432/114105 [02:20<00:14, 725.52 examples/s]
Map:  90%|█████████ | 102737/114105 [02:20<00:15, 745.85 examples/s]
Map:  92%|█████████▏| 105160/114105 [02:21<00:12, 692.55 examples/s]
Map:  90%|█████████ | 102986/114105 [02:20<00:14, 789.49 examples/s]
Map:  91%|█████████ | 103518/114105 [02:20<00:13, 757.00 examples/s]
Map:  90%|█████████ | 102821/114105 [02:20<00:14, 769.47 examples/s]
Map:  92%|█████████▏| 105251/114105 [02:21<00:11, 740.59 examples/s]
Map:  91%|█████████ | 103604/114105 [02:20<00:13, 781.19 examples/s]
Map:  90%|█████████ | 102906/114105 [02:20<00:14, 790.43 examples/s]
Map:  92%|█████████▏| 105336/114105 [02:21<00:11, 767.14 examples/s]
Map:  90%|█████████ | 103077/114105 [02:20<00:17, 616.97 examples/s]
Map:  92%|█████████▏| 105422/114105 [02:21<00:11, 787.30 examples/s]
Map:  91%|█████████ | 103725/114105 [02:20<00:13, 786.80 examples/s]
Map:  90%|█████████ | 103150/114105 [02:20<00:17, 642.07 examples/s]
Map:  92%|█████████▏| 105507/114105 [02:21<00:10, 800.45 examples/s]
Map:  90%|█████████ | 103000/114105 [02:20<00:18, 605.57 examples/s]
Map:  91%|█████████ | 103807/114105 [02:20<00:12, 794.47 examples/s]
Map:  90%|█████████ | 103236/114105 [02:21<00:15, 692.34 examples/s]
Map:  93%|█████████▎| 105593/114105 [02:22<00:10, 812.78 examples/s]
Map:  90%|█████████ | 103085/114105 [02:20<00:16, 658.61 examples/s]
Map:  91%|█████████ | 103890/114105 [02:20<00:12, 802.30 examples/s]
Map:  91%|█████████ | 103317/114105 [02:21<00:14, 721.25 examples/s]
Map:  93%|█████████▎| 105683/114105 [02:22<00:10, 831.98 examples/s]
Map:  90%|█████████ | 103173/114105 [02:20<00:15, 709.34 examples/s]
Map:  91%|█████████ | 103973/114105 [02:21<00:12, 808.31 examples/s]
Map:  91%|█████████ | 103400/114105 [02:21<00:14, 745.74 examples/s]
Map:  90%|█████████ | 103258/114105 [02:20<00:14, 742.54 examples/s]
Map:  93%|█████████▎| 105803/114105 [02:22<00:10, 816.54 examples/s]
Map:  91%|█████████ | 103483/114105 [02:21<00:13, 768.70 examples/s]
Map:  91%|█████████ | 103343/114105 [02:21<00:14, 768.06 examples/s]
Map:  93%|█████████▎| 105887/114105 [02:22<00:10, 819.98 examples/s]
Map:  91%|█████████ | 104083/114105 [02:21<00:15, 633.00 examples/s]
Map:  91%|█████████ | 103427/114105 [02:21<00:13, 786.08 examples/s]
Map:  91%|█████████ | 103602/114105 [02:21<00:13, 773.53 examples/s]
Map:  93%|█████████▎| 105970/114105 [02:22<00:09, 820.27 examples/s]
Map:  91%|█████████▏| 104171/114105 [02:21<00:14, 685.75 examples/s]
Map:  91%|█████████ | 103509/114105 [02:21<00:13, 792.78 examples/s]
Map:  91%|█████████ | 103681/114105 [02:21<00:13, 775.48 examples/s]
Map:  91%|█████████▏| 104258/114105 [02:21<00:13, 726.53 examples/s]
Map:  91%|█████████ | 103594/114105 [02:21<00:13, 803.29 examples/s]
Map:  91%|█████████▏| 104338/114105 [02:21<00:13, 744.37 examples/s]
Map:  91%|█████████ | 103794/114105 [02:21<00:13, 764.56 examples/s]
Map:  93%|█████████▎| 106083/114105 [02:22<00:12, 647.14 examples/s]
Map:  91%|█████████ | 103680/114105 [02:21<00:12, 819.16 examples/s]
Map:  92%|█████████▏| 104420/114105 [02:21<00:12, 759.91 examples/s]
Map:  91%|█████████ | 103874/114105 [02:21<00:13, 770.57 examples/s]
Map:  93%|█████████▎| 106163/114105 [02:22<00:11, 680.08 examples/s]
Map:  91%|█████████ | 103765/114105 [02:21<00:12, 826.58 examples/s]
Map:  92%|█████████▏| 104506/114105 [02:21<00:12, 786.73 examples/s]
Map:  93%|█████████▎| 106242/114105 [02:22<00:11, 704.01 examples/s]
Map:  91%|█████████ | 103852/114105 [02:21<00:12, 835.80 examples/s]
Map:  91%|█████████ | 103988/114105 [02:22<00:13, 763.19 examples/s]
Map:  92%|█████████▏| 104590/114105 [02:21<00:11, 798.30 examples/s]
Map:  93%|█████████▎| 106322/114105 [02:23<00:10, 726.09 examples/s]
Map:  91%|█████████ | 103941/114105 [02:21<00:11, 847.98 examples/s]
Map:  92%|█████████▏| 104697/114105 [02:22<00:12, 760.78 examples/s]
Map:  93%|█████████▎| 106431/114105 [02:23<00:10, 721.72 examples/s]
Map:  91%|█████████ | 104070/114105 [02:22<00:16, 592.66 examples/s]
Map:  93%|█████████▎| 106509/114105 [02:23<00:10, 734.97 examples/s]
Map:  91%|█████████ | 104044/114105 [02:21<00:15, 644.55 examples/s]
Map:  91%|█████████▏| 104153/114105 [02:22<00:15, 642.38 examples/s]
Map:  92%|█████████▏| 104787/114105 [02:22<00:13, 702.13 examples/s]
Map:  93%|█████████▎| 106592/114105 [02:23<00:09, 756.31 examples/s]
Map:  91%|█████████▏| 104133/114105 [02:22<00:14, 698.09 examples/s]
Map:  91%|█████████▏| 104238/114105 [02:22<00:14, 689.31 examples/s]
Map:  92%|█████████▏| 104869/114105 [02:22<00:12, 727.06 examples/s]
Map:  91%|█████████▏| 104217/114105 [02:22<00:13, 731.72 examples/s]
Map:  93%|█████████▎| 106677/114105 [02:23<00:09, 777.28 examples/s]
Map:  91%|█████████▏| 104320/114105 [02:22<00:13, 720.95 examples/s]
Map:  92%|█████████▏| 104951/114105 [02:22<00:12, 746.24 examples/s]
Map:  91%|█████████▏| 104302/114105 [02:22<00:12, 760.68 examples/s]
Map:  94%|█████████▎| 106760/114105 [02:23<00:09, 787.12 examples/s]
Map:  91%|█████████▏| 104401/114105 [02:22<00:13, 743.54 examples/s]
Map:  94%|█████████▎| 106843/114105 [02:23<00:09, 797.04 examples/s]
Map:  91%|█████████▏| 104384/114105 [02:22<00:12, 771.47 examples/s]
Map:  92%|█████████▏| 104486/114105 [02:22<00:12, 769.25 examples/s]
Map:  92%|█████████▏| 105041/114105 [02:22<00:15, 600.56 examples/s]
Map:  92%|█████████▏| 104467/114105 [02:22<00:12, 785.10 examples/s]
Map:  94%|█████████▎| 106929/114105 [02:23<00:08, 809.50 examples/s]
Map:  92%|█████████▏| 105113/114105 [02:22<00:14, 626.93 examples/s]
Map:  92%|█████████▏| 104608/114105 [02:22<00:12, 783.25 examples/s]
Map:  92%|█████████▏| 104549/114105 [02:22<00:12, 794.39 examples/s]
Map:  92%|█████████▏| 105191/114105 [02:22<00:13, 659.71 examples/s]
Map:  92%|█████████▏| 104695/114105 [02:23<00:11, 802.02 examples/s]
Map:  92%|█████████▏| 104635/114105 [02:22<00:11, 810.49 examples/s]
Map:  92%|█████████▏| 105273/114105 [02:22<00:12, 699.45 examples/s]
Map:  94%|█████████▍| 107046/114105 [02:24<00:10, 645.00 examples/s]
Map:  92%|█████████▏| 104778/114105 [02:23<00:11, 806.36 examples/s]
Map:  92%|█████████▏| 104719/114105 [02:22<00:11, 815.56 examples/s]
Map:  92%|█████████▏| 105355/114105 [02:23<00:11, 730.66 examples/s]
Map:  94%|█████████▍| 107130/114105 [02:24<00:10, 687.49 examples/s]
Map:  92%|█████████▏| 104860/114105 [02:23<00:11, 808.89 examples/s]
Map:  92%|█████████▏| 104808/114105 [02:22<00:11, 835.69 examples/s]
Map:  92%|█████████▏| 105435/114105 [02:23<00:11, 747.19 examples/s]
Map:  94%|█████████▍| 107216/114105 [02:24<00:09, 726.69 examples/s]
Map:  92%|█████████▏| 104943/114105 [02:23<00:11, 814.31 examples/s]
Map:  92%|█████████▏| 105518/114105 [02:23<00:11, 767.57 examples/s]
Map:  94%|█████████▍| 107299/114105 [02:24<00:09, 750.44 examples/s]
Map:  92%|█████████▏| 104934/114105 [02:23<00:10, 834.79 examples/s]
Map:  94%|█████████▍| 107383/114105 [02:24<00:08, 770.46 examples/s]
Map:  92%|█████████▏| 105033/114105 [02:23<00:14, 614.05 examples/s]
Map:  93%|█████████▎| 105620/114105 [02:23<00:11, 730.05 examples/s]
Map:  93%|█████████▎| 105696/114105 [02:23<00:11, 736.59 examples/s]
Map:  92%|█████████▏| 105028/114105 [02:23<00:14, 622.45 examples/s]
Map:  94%|█████████▍| 107497/114105 [02:24<00:08, 765.38 examples/s]
Map:  92%|█████████▏| 105139/114105 [02:23<00:14, 639.00 examples/s]
Map:  93%|█████████▎| 105781/114105 [02:23<00:10, 765.28 examples/s]
Map:  92%|█████████▏| 105099/114105 [02:23<00:14, 640.76 examples/s]
Map:  92%|█████████▏| 105221/114105 [02:23<00:13, 677.77 examples/s]
Map:  94%|█████████▍| 107613/114105 [02:24<00:08, 762.82 examples/s]
Map:  93%|█████████▎| 105866/114105 [02:23<00:10, 786.35 examples/s]
Map:  92%|█████████▏| 105182/114105 [02:23<00:13, 682.77 examples/s]
Map:  92%|█████████▏| 105307/114105 [02:23<00:12, 720.17 examples/s]
Map:  94%|█████████▍| 107697/114105 [02:24<00:08, 779.05 examples/s]
Map:  93%|█████████▎| 105951/114105 [02:23<00:10, 800.70 examples/s]
Map:  92%|█████████▏| 105263/114105 [02:23<00:12, 714.29 examples/s]
Map:  92%|█████████▏| 105393/114105 [02:24<00:11, 754.30 examples/s]
Map:  94%|█████████▍| 107778/114105 [02:24<00:08, 783.48 examples/s]
Map:  92%|█████████▏| 105350/114105 [02:23<00:11, 754.20 examples/s]
Map:  95%|█████████▍| 107869/114105 [02:25<00:07, 811.89 examples/s]
Map:  92%|█████████▏| 105501/114105 [02:24<00:11, 739.22 examples/s]
Map:  92%|█████████▏| 105434/114105 [02:23<00:11, 775.06 examples/s]
Map:  93%|█████████▎| 106059/114105 [02:24<00:13, 577.31 examples/s]
Map:  92%|█████████▏| 105520/114105 [02:23<00:10, 794.46 examples/s]
Map:  95%|█████████▍| 107992/114105 [02:25<00:07, 807.87 examples/s]
Map:  93%|█████████▎| 105608/114105 [02:24<00:11, 728.37 examples/s]
Map:  93%|█████████▎| 106135/114105 [02:24<00:12, 614.27 examples/s]
Map:  93%|█████████▎| 105603/114105 [02:23<00:10, 804.31 examples/s]
Map:  93%|█████████▎| 105691/114105 [02:24<00:11, 750.52 examples/s]
Map:  93%|█████████▎| 106218/114105 [02:24<00:11, 662.69 examples/s]
Map:  95%|█████████▍| 108083/114105 [02:25<00:09, 646.06 examples/s]
Map:  93%|█████████▎| 105774/114105 [02:24<00:10, 769.24 examples/s]
Map:  93%|█████████▎| 105724/114105 [02:24<00:10, 804.03 examples/s]
Map:  93%|█████████▎| 106302/114105 [02:24<00:11, 704.54 examples/s]
Map:  95%|█████████▍| 108167/114105 [02:25<00:08, 684.41 examples/s]
Map:  93%|█████████▎| 105858/114105 [02:24<00:10, 784.01 examples/s]
Map:  93%|█████████▎| 106387/114105 [02:24<00:10, 740.29 examples/s]
Map:  93%|█████████▎| 105845/114105 [02:24<00:10, 801.88 examples/s]
Map:  95%|█████████▍| 108253/114105 [02:25<00:08, 722.03 examples/s]
Map:  93%|█████████▎| 105942/114105 [02:24<00:10, 794.61 examples/s]
Map:  93%|█████████▎| 106466/114105 [02:24<00:10, 752.40 examples/s]
Map:  93%|█████████▎| 105927/114105 [02:24<00:10, 802.40 examples/s]
Map:  95%|█████████▍| 108335/114105 [02:25<00:07, 745.67 examples/s]
Map:  95%|█████████▌| 108419/114105 [02:25<00:07, 768.19 examples/s]
Map:  93%|█████████▎| 106564/114105 [02:24<00:10, 713.68 examples/s]
Map:  93%|█████████▎| 106043/114105 [02:24<00:13, 590.07 examples/s]
Map:  95%|█████████▌| 108501/114105 [02:25<00:07, 780.11 examples/s]
Map:  93%|█████████▎| 106645/114105 [02:24<00:10, 736.35 examples/s]
Map:  93%|█████████▎| 106042/114105 [02:24<00:12, 650.36 examples/s]
Map:  93%|█████████▎| 106123/114105 [02:25<00:12, 633.04 examples/s]
Map:  95%|█████████▌| 108583/114105 [02:26<00:07, 787.25 examples/s]
Map:  94%|█████████▎| 106733/114105 [02:24<00:09, 772.61 examples/s]
Map:  93%|█████████▎| 106125/114105 [02:24<00:11, 685.93 examples/s]
Map:  93%|█████████▎| 106208/114105 [02:25<00:11, 680.56 examples/s]
Map:  95%|█████████▌| 108668/114105 [02:26<00:06, 801.16 examples/s]
Map:  94%|█████████▎| 106818/114105 [02:25<00:09, 790.20 examples/s]
Map:  93%|█████████▎| 106211/114105 [02:24<00:10, 722.45 examples/s]
Map:  93%|█████████▎| 106292/114105 [02:25<00:10, 717.46 examples/s]
Map:  95%|█████████▌| 108752/114105 [02:26<00:06, 809.03 examples/s]
Map:  94%|█████████▎| 106902/114105 [02:25<00:08, 803.16 examples/s]
Map:  93%|█████████▎| 106296/114105 [02:24<00:10, 750.50 examples/s]
Map:  93%|█████████▎| 106373/114105 [02:25<00:10, 740.19 examples/s]
Map:  95%|█████████▌| 108835/114105 [02:26<00:06, 809.88 examples/s]
Map:  93%|█████████▎| 106380/114105 [02:25<00:09, 772.66 examples/s]
Map:  95%|█████████▌| 108918/114105 [02:26<00:06, 814.50 examples/s]
Map:  93%|█████████▎| 106467/114105 [02:25<00:09, 795.80 examples/s]
Map:  93%|█████████▎| 106469/114105 [02:25<00:10, 701.32 examples/s]
Map:  94%|█████████▍| 107000/114105 [02:25<00:12, 579.28 examples/s]
Map:  93%|█████████▎| 106550/114105 [02:25<00:09, 803.19 examples/s]
Map:  93%|█████████▎| 106544/114105 [02:25<00:10, 711.30 examples/s]
Map:  94%|█████████▍| 107085/114105 [02:25<00:11, 636.10 examples/s]
Map:  96%|█████████▌| 109000/114105 [02:26<00:08, 621.64 examples/s]
Map:  93%|█████████▎| 106634/114105 [02:25<00:09, 809.83 examples/s]
Map:  93%|█████████▎| 106628/114105 [02:25<00:10, 743.15 examples/s]
Map:  96%|█████████▌| 109081/114105 [02:26<00:07, 663.11 examples/s]
Map:  94%|█████████▍| 107182/114105 [02:25<00:10, 635.98 examples/s]
Map:  94%|█████████▎| 106710/114105 [02:25<00:09, 761.82 examples/s]
Map:  94%|█████████▎| 106756/114105 [02:25<00:09, 808.25 examples/s]
Map:  96%|█████████▌| 109167/114105 [02:26<00:06, 712.05 examples/s]
Map:  94%|█████████▎| 106795/114105 [02:25<00:09, 782.72 examples/s]
Map:  94%|█████████▎| 106843/114105 [02:25<00:08, 822.94 examples/s]
Map:  94%|█████████▍| 107292/114105 [02:25<00:10, 661.72 examples/s]
Map:  96%|█████████▌| 109254/114105 [02:26<00:06, 749.56 examples/s]
Map:  94%|█████████▍| 107363/114105 [02:25<00:10, 668.87 examples/s]
Map:  94%|█████████▎| 106905/114105 [02:26<00:09, 758.53 examples/s]
Map:  96%|█████████▌| 109338/114105 [02:27<00:06, 771.81 examples/s]
Map:  94%|█████████▎| 106970/114105 [02:25<00:08, 828.40 examples/s]
Map:  96%|█████████▌| 109419/114105 [02:27<00:05, 781.71 examples/s]
Map:  94%|█████████▍| 107466/114105 [02:26<00:09, 671.86 examples/s]
Map:  94%|█████████▍| 107000/114105 [02:26<00:11, 598.33 examples/s]
Map:  94%|█████████▍| 107546/114105 [02:26<00:09, 698.98 examples/s]
Map:  94%|█████████▍| 107086/114105 [02:26<00:10, 672.44 examples/s]
Map:  96%|█████████▌| 109530/114105 [02:27<00:06, 760.64 examples/s]
Map:  94%|█████████▍| 107072/114105 [02:26<00:11, 623.53 examples/s]
Map:  94%|█████████▍| 107622/114105 [02:26<00:09, 710.49 examples/s]
Map:  94%|█████████▍| 107168/114105 [02:26<00:09, 702.37 examples/s]
Map:  96%|█████████▌| 109649/114105 [02:27<00:05, 769.90 examples/s]
Map:  94%|█████████▍| 107158/114105 [02:26<00:10, 677.91 examples/s]
Map:  94%|█████████▍| 107705/114105 [02:26<00:08, 739.17 examples/s]
Map:  94%|█████████▍| 107250/114105 [02:26<00:09, 727.74 examples/s]
Map:  96%|█████████▌| 109734/114105 [02:27<00:05, 788.11 examples/s]
Map:  94%|█████████▍| 107242/114105 [02:26<00:09, 715.43 examples/s]
Map:  94%|█████████▍| 107782/114105 [02:26<00:08, 744.88 examples/s]
Map:  94%|█████████▍| 107336/114105 [02:26<00:08, 757.32 examples/s]
Map:  96%|█████████▌| 109818/114105 [02:27<00:05, 798.73 examples/s]
Map:  94%|█████████▍| 107420/114105 [02:26<00:08, 776.80 examples/s]
Map:  94%|█████████▍| 107344/114105 [02:26<00:09, 701.26 examples/s]
Map:  95%|█████████▍| 107879/114105 [02:26<00:08, 705.39 examples/s]
Map:  94%|█████████▍| 107501/114105 [02:26<00:08, 785.38 examples/s]
Map:  96%|█████████▋| 109934/114105 [02:27<00:05, 786.07 examples/s]
Map:  95%|█████████▍| 107955/114105 [02:26<00:08, 716.90 examples/s]
Map:  94%|█████████▍| 107457/114105 [02:26<00:09, 715.66 examples/s]
Map:  94%|█████████▍| 107583/114105 [02:26<00:08, 791.10 examples/s]
Map:  94%|█████████▍| 107539/114105 [02:27<00:08, 738.46 examples/s]
Map:  94%|█████████▍| 107669/114105 [02:26<00:07, 807.93 examples/s]
Map:  95%|█████████▍| 108039/114105 [02:26<00:10, 574.14 examples/s]
Map:  96%|█████████▋| 110041/114105 [02:28<00:06, 634.08 examples/s]
Map:  94%|█████████▍| 107619/114105 [02:27<00:08, 751.73 examples/s]
Map:  94%|█████████▍| 107752/114105 [02:26<00:07, 810.46 examples/s]
Map:  95%|█████████▍| 108126/114105 [02:27<00:09, 639.36 examples/s]
Map:  97%|█████████▋| 110127/114105 [02:28<00:05, 680.74 examples/s]
Map:  94%|█████████▍| 107704/114105 [02:27<00:08, 774.80 examples/s]
Map:  95%|█████████▍| 107836/114105 [02:26<00:07, 816.34 examples/s]
Map:  95%|█████████▍| 108212/114105 [02:27<00:08, 691.14 examples/s]
Map:  97%|█████████▋| 110210/114105 [02:28<00:05, 714.11 examples/s]
Map:  94%|█████████▍| 107810/114105 [02:27<00:08, 746.11 examples/s]
Map:  97%|█████████▋| 110293/114105 [02:28<00:05, 741.19 examples/s]
Map:  95%|█████████▍| 107960/114105 [02:27<00:07, 817.27 examples/s]
Map:  95%|█████████▍| 108307/114105 [02:27<00:08, 670.36 examples/s]
Map:  97%|█████████▋| 110378/114105 [02:28<00:04, 767.02 examples/s]
Map:  95%|█████████▍| 107923/114105 [02:27<00:08, 742.71 examples/s]
Map:  95%|█████████▍| 108389/114105 [02:27<00:08, 705.49 examples/s]
Map:  97%|█████████▋| 110462/114105 [02:28<00:04, 785.25 examples/s]
Map:  95%|█████████▌| 108465/114105 [02:27<00:07, 719.01 examples/s]
Map:  95%|█████████▍| 108079/114105 [02:27<00:09, 645.59 examples/s]
Map:  95%|█████████▍| 108000/114105 [02:27<00:10, 594.13 examples/s]
Map:  95%|█████████▌| 108550/114105 [02:27<00:07, 750.78 examples/s]
Map:  97%|█████████▋| 110580/114105 [02:28<00:04, 781.44 examples/s]
Map:  95%|█████████▍| 108164/114105 [02:27<00:08, 687.87 examples/s]
Map:  95%|█████████▍| 108081/114105 [02:27<00:09, 639.66 examples/s]
Map:  95%|█████████▌| 108632/114105 [02:27<00:07, 766.56 examples/s]
Map:  97%|█████████▋| 110662/114105 [02:28<00:04, 786.71 examples/s]
Map:  95%|█████████▍| 108245/114105 [02:27<00:08, 713.63 examples/s]
Map:  95%|█████████▍| 108164/114105 [02:27<00:08, 681.47 examples/s]
Map:  95%|█████████▌| 108718/114105 [02:27<00:06, 791.06 examples/s]
Map:  97%|█████████▋| 110745/114105 [02:28<00:04, 795.17 examples/s]
Map:  95%|█████████▍| 108326/114105 [02:27<00:07, 733.74 examples/s]
Map:  97%|█████████▋| 110831/114105 [02:29<00:04, 810.80 examples/s]
Map:  95%|█████████▌| 108407/114105 [02:27<00:07, 751.85 examples/s]
Map:  95%|█████████▍| 108259/114105 [02:28<00:08, 659.03 examples/s]
Map:  95%|█████████▌| 108816/114105 [02:27<00:07, 732.06 examples/s]
Map:  95%|█████████▌| 108493/114105 [02:27<00:07, 778.87 examples/s]
Map:  95%|█████████▍| 108334/114105 [02:28<00:08, 679.75 examples/s]
Map:  95%|█████████▌| 108898/114105 [02:28<00:06, 754.25 examples/s]
Map:  97%|█████████▋| 110951/114105 [02:29<00:03, 804.06 examples/s]
Map:  95%|█████████▌| 108577/114105 [02:27<00:06, 792.04 examples/s]
Map:  95%|█████████▌| 108421/114105 [02:28<00:07, 727.10 examples/s]
Map:  96%|█████████▌| 108979/114105 [02:28<00:06, 768.85 examples/s]
Map:  95%|█████████▌| 108663/114105 [02:28<00:06, 807.60 examples/s]
Map:  95%|█████████▌| 108504/114105 [02:28<00:07, 752.55 examples/s]
Map:  97%|█████████▋| 111041/114105 [02:29<00:04, 636.33 examples/s]
Map:  95%|█████████▌| 108746/114105 [02:28<00:06, 810.63 examples/s]
Map:  95%|█████████▌| 108584/114105 [02:28<00:07, 762.57 examples/s]
Map:  97%|█████████▋| 111126/114105 [02:29<00:04, 683.13 examples/s]
Map:  96%|█████████▌| 109077/114105 [02:28<00:08, 604.03 examples/s]
Map:  95%|█████████▌| 108833/114105 [02:28<00:06, 825.12 examples/s]
Map:  95%|█████████▌| 108666/114105 [02:28<00:07, 771.80 examples/s]
Map:  97%|█████████▋| 111209/114105 [02:29<00:04, 715.17 examples/s]
Map:  96%|█████████▌| 109151/114105 [02:28<00:07, 632.31 examples/s]
Map:  98%|█████████▊| 111291/114105 [02:29<00:03, 738.10 examples/s]
Map:  95%|█████████▌| 108956/114105 [02:28<00:06, 818.35 examples/s]
Map:  95%|█████████▌| 108764/114105 [02:28<00:07, 723.74 examples/s]
Map:  96%|█████████▌| 109250/114105 [02:28<00:07, 637.32 examples/s]
Map:  98%|█████████▊| 111375/114105 [02:29<00:03, 762.50 examples/s]
Map:  95%|█████████▌| 108845/114105 [02:28<00:07, 745.13 examples/s]
Map:  96%|█████████▌| 109337/114105 [02:28<00:06, 689.55 examples/s]
Map:  98%|█████████▊| 111461/114105 [02:29<00:03, 783.82 examples/s]
Map:  96%|█████████▌| 109040/114105 [02:28<00:07, 636.62 examples/s]
Map:  96%|█████████▌| 109422/114105 [02:28<00:06, 727.22 examples/s]
Map:  95%|█████████▌| 108961/114105 [02:29<00:06, 753.71 examples/s]
Map:  98%|█████████▊| 111552/114105 [02:29<00:03, 813.59 examples/s]
Map:  96%|█████████▌| 109121/114105 [02:28<00:07, 674.04 examples/s]
Map:  96%|█████████▌| 109508/114105 [02:28<00:06, 760.68 examples/s]
Map:  96%|█████████▌| 109203/114105 [02:28<00:06, 706.12 examples/s]
Map:  98%|█████████▊| 111674/114105 [02:30<00:03, 809.84 examples/s]
Map:  96%|█████████▌| 109038/114105 [02:29<00:08, 610.22 examples/s]
Map:  96%|█████████▌| 109590/114105 [02:29<00:05, 773.06 examples/s]
Map:  96%|█████████▌| 109289/114105 [02:28<00:06, 741.92 examples/s]
Map:  96%|█████████▌| 109112/114105 [02:29<00:07, 637.14 examples/s]
Map:  98%|█████████▊| 111798/114105 [02:30<00:02, 812.81 examples/s]
Map:  96%|█████████▌| 109699/114105 [02:29<00:05, 751.61 examples/s]
Map:  96%|█████████▌| 109374/114105 [02:29<00:06, 766.00 examples/s]
Map:  96%|█████████▌| 109216/114105 [02:29<00:07, 653.92 examples/s]
Map:  96%|█████████▌| 109455/114105 [02:29<00:06, 774.32 examples/s]
Map:  98%|█████████▊| 111917/114105 [02:30<00:02, 802.76 examples/s]
Map:  96%|█████████▌| 109809/114105 [02:29<00:05, 744.23 examples/s]
Map:  96%|█████████▌| 109299/114105 [02:29<00:06, 694.67 examples/s]
Map:  96%|█████████▌| 109538/114105 [02:29<00:05, 788.61 examples/s]
Map:  96%|█████████▋| 109891/114105 [02:29<00:05, 759.71 examples/s]
Map:  96%|█████████▌| 109383/114105 [02:29<00:06, 729.55 examples/s]
Map:  96%|█████████▌| 109619/114105 [02:29<00:05, 791.30 examples/s]
Map:  98%|█████████▊| 112000/114105 [02:30<00:03, 655.04 examples/s]
Map:  96%|█████████▋| 109974/114105 [02:29<00:05, 777.23 examples/s]
Map:  96%|█████████▌| 109460/114105 [02:29<00:06, 736.96 examples/s]
Map:  96%|█████████▌| 109702/114105 [02:29<00:05, 799.95 examples/s]
Map:  98%|█████████▊| 112084/114105 [02:30<00:02, 692.08 examples/s]
Map:  96%|█████████▌| 109546/114105 [02:29<00:05, 767.99 examples/s]
Map:  96%|█████████▌| 109783/114105 [02:29<00:05, 797.87 examples/s]
Map:  98%|█████████▊| 112163/114105 [02:30<00:02, 711.20 examples/s]
Map:  96%|█████████▋| 110075/114105 [02:29<00:06, 608.18 examples/s]
Map:  96%|█████████▌| 109644/114105 [02:30<00:06, 718.72 examples/s]
Map:  96%|█████████▋| 109896/114105 [02:29<00:05, 776.17 examples/s]
Map:  98%|█████████▊| 112276/114105 [02:30<00:02, 722.32 examples/s]
Map:  97%|█████████▋| 110179/114105 [02:29<00:06, 629.08 examples/s]
Map:  96%|█████████▌| 109718/114105 [02:30<00:06, 720.52 examples/s]
Map:  96%|█████████▋| 109978/114105 [02:29<00:05, 785.41 examples/s]
Map:  98%|█████████▊| 112358/114105 [02:31<00:02, 743.86 examples/s]
Map:  97%|█████████▋| 110266/114105 [02:30<00:05, 680.96 examples/s]
Map:  96%|█████████▌| 109802/114105 [02:30<00:05, 752.24 examples/s]
Map:  99%|█████████▊| 112441/114105 [02:31<00:02, 763.68 examples/s]
Map:  97%|█████████▋| 110351/114105 [02:30<00:05, 719.13 examples/s]
Map:  96%|█████████▋| 109884/114105 [02:30<00:05, 764.98 examples/s]
Map:  96%|█████████▋| 110085/114105 [02:30<00:06, 628.51 examples/s]
Map:  99%|█████████▊| 112525/114105 [02:31<00:02, 781.06 examples/s]
Map:  97%|█████████▋| 110438/114105 [02:30<00:04, 752.77 examples/s]
Map:  96%|█████████▋| 109966/114105 [02:30<00:05, 775.86 examples/s]
Map:  97%|█████████▋| 110175/114105 [02:30<00:05, 685.84 examples/s]
Map:  99%|█████████▊| 112606/114105 [02:31<00:01, 784.38 examples/s]
Map:  97%|█████████▋| 110526/114105 [02:30<00:04, 781.96 examples/s]
Map:  97%|█████████▋| 110256/114105 [02:30<00:05, 713.79 examples/s]
Map:  99%|█████████▉| 112691/114105 [02:31<00:01, 798.75 examples/s]
Map:  97%|█████████▋| 110630/114105 [02:30<00:04, 745.28 examples/s]
Map:  97%|█████████▋| 110336/114105 [02:30<00:05, 734.55 examples/s]
Map:  96%|█████████▋| 110067/114105 [02:30<00:06, 595.94 examples/s]
Map:  99%|█████████▉| 112778/114105 [02:31<00:01, 815.06 examples/s]
Map:  97%|█████████▋| 110421/114105 [02:30<00:04, 764.12 examples/s]
Map:  97%|█████████▋| 110143/114105 [02:30<00:06, 631.58 examples/s]
Map:  97%|█████████▋| 110745/114105 [02:30<00:04, 748.60 examples/s]
Map:  99%|█████████▉| 112899/114105 [02:31<00:01, 808.96 examples/s]
Map:  97%|█████████▋| 110504/114105 [02:30<00:04, 778.61 examples/s]
Map:  97%|█████████▋| 110227/114105 [02:30<00:05, 679.92 examples/s]
Map:  97%|█████████▋| 110827/114105 [02:30<00:04, 763.67 examples/s]
Map:  99%|█████████▉| 112985/114105 [02:31<00:01, 817.77 examples/s]
Map:  97%|█████████▋| 110590/114105 [02:30<00:04, 798.45 examples/s]
Map:  97%|█████████▋| 110311/114105 [02:30<00:05, 717.44 examples/s]
Map:  97%|█████████▋| 110909/114105 [02:30<00:04, 776.42 examples/s]
Map:  97%|█████████▋| 110394/114105 [02:31<00:04, 745.51 examples/s]
Map:  97%|█████████▋| 110992/114105 [02:30<00:03, 786.28 examples/s]
Map:  97%|█████████▋| 110713/114105 [02:30<00:04, 800.22 examples/s]
Map:  99%|█████████▉| 113083/114105 [02:32<00:01, 647.36 examples/s]
Map:  97%|█████████▋| 110478/114105 [02:31<00:04, 767.89 examples/s]
Map:  97%|█████████▋| 110797/114105 [02:30<00:04, 808.48 examples/s]
Map:  99%|█████████▉| 113166/114105 [02:32<00:01, 687.96 examples/s]
Map:  97%|█████████▋| 110578/114105 [02:31<00:04, 722.87 examples/s]
Map:  99%|█████████▉| 113242/114105 [02:32<00:01, 702.84 examples/s]
Map:  97%|█████████▋| 110912/114105 [02:31<00:04, 787.65 examples/s]
Map:  97%|█████████▋| 111109/114105 [02:31<00:05, 593.37 examples/s]
Map:  99%|█████████▉| 113324/114105 [02:32<00:01, 731.07 examples/s]
Map:  97%|█████████▋| 110693/114105 [02:31<00:04, 734.24 examples/s]
Map:  97%|█████████▋| 111193/114105 [02:31<00:04, 643.13 examples/s]
Map:  99%|█████████▉| 113411/114105 [02:32<00:00, 764.32 examples/s]
Map:  97%|█████████▋| 110775/114105 [02:31<00:04, 753.07 examples/s]
Map:  97%|█████████▋| 111000/114105 [02:31<00:05, 620.65 examples/s]
Map:  98%|█████████▊| 111277/114105 [02:31<00:04, 687.96 examples/s]
Map:  99%|█████████▉| 113496/114105 [02:32<00:00, 784.70 examples/s]
Map:  97%|█████████▋| 110862/114105 [02:31<00:04, 780.92 examples/s]
Map:  97%|█████████▋| 111083/114105 [02:31<00:04, 665.29 examples/s]
Map:  98%|█████████▊| 111360/114105 [02:31<00:03, 719.89 examples/s]
Map: 100%|█████████▉| 113580/114105 [02:32<00:00, 796.00 examples/s]
Map:  97%|█████████▋| 110944/114105 [02:31<00:03, 790.60 examples/s]
Map:  97%|█████████▋| 111171/114105 [02:31<00:04, 713.80 examples/s]
Map:  98%|█████████▊| 111445/114105 [02:31<00:03, 752.23 examples/s]
Map: 100%|█████████▉| 113662/114105 [02:32<00:00, 798.00 examples/s]
Map:  98%|█████████▊| 111256/114105 [02:31<00:03, 745.66 examples/s]
Map:  98%|█████████▊| 111545/114105 [02:31<00:03, 717.30 examples/s]
Map:  97%|█████████▋| 111041/114105 [02:32<00:04, 631.19 examples/s]
Map:  98%|█████████▊| 111339/114105 [02:31<00:03, 765.51 examples/s]
Map: 100%|█████████▉| 113779/114105 [02:32<00:00, 789.81 examples/s]
Map:  98%|█████████▊| 111622/114105 [02:31<00:03, 729.33 examples/s]
Map:  97%|█████████▋| 111126/114105 [02:32<00:04, 679.11 examples/s]
Map:  98%|█████████▊| 111423/114105 [02:31<00:03, 780.64 examples/s]
Map: 100%|█████████▉| 113865/114105 [02:33<00:00, 805.80 examples/s]
Map:  98%|█████████▊| 111706/114105 [02:31<00:03, 757.00 examples/s]
Map:  97%|█████████▋| 111211/114105 [02:32<00:04, 719.32 examples/s]
Map:  98%|█████████▊| 111509/114105 [02:31<00:03, 801.00 examples/s]
Map: 100%|█████████▉| 113956/114105 [02:33<00:00, 827.76 examples/s]
Map:  98%|█████████▊| 111785/114105 [02:32<00:03, 763.95 examples/s]
Map:  98%|█████████▊| 111290/114105 [02:32<00:03, 735.23 examples/s]
Map:  98%|█████████▊| 111594/114105 [02:31<00:03, 812.24 examples/s]
Map:  98%|█████████▊| 111867/114105 [02:32<00:02, 779.12 examples/s]
Map:  98%|█████████▊| 111373/114105 [02:32<00:03, 756.28 examples/s]
Map:  98%|█████████▊| 111681/114105 [02:32<00:02, 823.43 examples/s]
Map: 100%|█████████▉| 114042/114105 [02:33<00:00, 644.39 examples/s]
Map:  98%|█████████▊| 111950/114105 [02:32<00:02, 791.03 examples/s]
Map:  98%|█████████▊| 111458/114105 [02:32<00:03, 778.45 examples/s]
Map:  98%|█████████▊| 111765/114105 [02:32<00:02, 827.01 examples/s]
Map:  98%|█████████▊| 111543/114105 [02:32<00:03, 796.20 examples/s]
Map:  98%|█████████▊| 111849/114105 [02:32<00:02, 826.66 examples/s]
Map: 100%|██████████| 114105/114105 [02:33<00:00, 742.80 examples/s]

Map:  98%|█████████▊| 112040/114105 [02:32<00:03, 562.62 examples/s]
Map:  98%|█████████▊| 111658/114105 [02:32<00:03, 779.87 examples/s]
Map:  98%|█████████▊| 111965/114105 [02:32<00:02, 801.27 examples/s]
Map:  98%|█████████▊| 112119/114105 [02:32<00:03, 612.43 examples/s]
Map:  98%|█████████▊| 111746/114105 [02:32<00:02, 801.77 examples/s]
Map:  98%|█████████▊| 112202/114105 [02:32<00:02, 663.73 examples/s]
Map:  98%|█████████▊| 111833/114105 [02:32<00:02, 816.05 examples/s]
Map:  98%|█████████▊| 112079/114105 [02:32<00:03, 637.96 examples/s]
Map:  98%|█████████▊| 112284/114105 [02:32<00:02, 700.00 examples/s]
Map:  98%|█████████▊| 111916/114105 [02:33<00:02, 814.85 examples/s]
Map:  98%|█████████▊| 112164/114105 [02:32<00:02, 680.06 examples/s]
Map:  98%|█████████▊| 112369/114105 [02:32<00:02, 739.63 examples/s]
Map:  98%|█████████▊| 112250/114105 [02:32<00:02, 720.14 examples/s]
Map:  98%|█████████▊| 112000/114105 [02:33<00:03, 646.95 examples/s]
Map:  99%|█████████▊| 112468/114105 [02:33<00:02, 705.54 examples/s]
Map:  98%|█████████▊| 112335/114105 [02:32<00:02, 749.96 examples/s]
Map:  98%|█████████▊| 112081/114105 [02:33<00:02, 684.82 examples/s]
Map:  99%|█████████▊| 112547/114105 [02:33<00:02, 724.23 examples/s]
Map:  99%|█████████▊| 112416/114105 [02:33<00:02, 760.94 examples/s]
Map:  98%|█████████▊| 112164/114105 [02:33<00:02, 718.82 examples/s]
Map:  99%|█████████▊| 112633/114105 [02:33<00:01, 757.51 examples/s]
Map:  99%|█████████▊| 112503/114105 [02:33<00:02, 786.81 examples/s]
Map:  98%|█████████▊| 112246/114105 [02:33<00:02, 743.11 examples/s]
Map:  99%|█████████▉| 112716/114105 [02:33<00:01, 774.04 examples/s]
Map:  99%|█████████▊| 112585/114105 [02:33<00:01, 792.99 examples/s]
Map:  98%|█████████▊| 112330/114105 [02:33<00:02, 767.75 examples/s]
Map:  99%|█████████▉| 112803/114105 [02:33<00:01, 797.36 examples/s]
Map:  99%|█████████▊| 112667/114105 [02:33<00:01, 796.90 examples/s]
Map:  99%|█████████▊| 112414/114105 [02:33<00:02, 785.59 examples/s]
Map:  99%|█████████▉| 112751/114105 [02:33<00:01, 803.86 examples/s]
Map:  99%|█████████▉| 112912/114105 [02:33<00:01, 767.00 examples/s]
Map:  99%|█████████▊| 112496/114105 [02:33<00:02, 791.97 examples/s]
Map:  99%|█████████▉| 112869/114105 [02:33<00:01, 793.35 examples/s]
Map:  99%|█████████▊| 112606/114105 [02:34<00:01, 768.75 examples/s]
Map:  99%|█████████▉| 113000/114105 [02:33<00:01, 584.05 examples/s]
Map:  99%|█████████▉| 112689/114105 [02:34<00:01, 782.03 examples/s]
Map:  99%|█████████▉| 112988/114105 [02:33<00:01, 788.55 examples/s]
Map:  99%|█████████▉| 113079/114105 [02:34<00:01, 628.17 examples/s]
Map:  99%|█████████▉| 112774/114105 [02:34<00:01, 798.29 examples/s]
Map:  99%|█████████▉| 113167/114105 [02:34<00:01, 684.11 examples/s]
Map:  99%|█████████▉| 112855/114105 [02:34<00:01, 797.88 examples/s]
Map:  99%|█████████▉| 113085/114105 [02:33<00:01, 639.72 examples/s]
Map:  99%|█████████▉| 113255/114105 [02:34<00:01, 730.77 examples/s]
Map:  99%|█████████▉| 112937/114105 [02:34<00:01, 799.61 examples/s]
Map:  99%|█████████▉| 113169/114105 [02:34<00:01, 679.13 examples/s]
Map:  99%|█████████▉| 113359/114105 [02:34<00:01, 715.30 examples/s]
Map:  99%|█████████▉| 113253/114105 [02:34<00:01, 715.74 examples/s]
Map:  99%|█████████▉| 113039/114105 [02:34<00:01, 633.76 examples/s]
Map:  99%|█████████▉| 113335/114105 [02:34<00:01, 741.09 examples/s]
Map:  99%|█████████▉| 113467/114105 [02:34<00:00, 713.58 examples/s]
Map:  99%|█████████▉| 113118/114105 [02:34<00:01, 668.70 examples/s]
Map:  99%|█████████▉| 113414/114105 [02:34<00:00, 752.76 examples/s]
Map: 100%|█████████▉| 113548/114105 [02:34<00:00, 735.50 examples/s]
Map:  99%|█████████▉| 113197/114105 [02:34<00:01, 695.45 examples/s]
Map:  99%|█████████▉| 113494/114105 [02:34<00:00, 764.06 examples/s]
Map: 100%|█████████▉| 113633/114105 [02:34<00:00, 761.16 examples/s]
Map:  99%|█████████▉| 113276/114105 [02:34<00:01, 718.29 examples/s]
Map: 100%|█████████▉| 113578/114105 [02:34<00:00, 782.46 examples/s]
Map: 100%|█████████▉| 113718/114105 [02:34<00:00, 780.63 examples/s]
Map:  99%|█████████▉| 113355/114105 [02:35<00:01, 734.13 examples/s]
Map: 100%|█████████▉| 113660/114105 [02:34<00:00, 790.34 examples/s]
Map: 100%|█████████▉| 113798/114105 [02:34<00:00, 783.21 examples/s]
Map:  99%|█████████▉| 113465/114105 [02:35<00:00, 729.88 examples/s]
Map: 100%|█████████▉| 113765/114105 [02:34<00:00, 751.21 examples/s]
Map: 100%|█████████▉| 113897/114105 [02:35<00:00, 730.98 examples/s]
Map: 100%|█████████▉| 113984/114105 [02:35<00:00, 764.95 examples/s]
Map: 100%|█████████▉| 113873/114105 [02:35<00:00, 738.24 examples/s]
Map: 100%|█████████▉| 113572/114105 [02:35<00:00, 719.97 examples/s]
Map: 100%|█████████▉| 113953/114105 [02:35<00:00, 753.07 examples/s]
Map: 100%|█████████▉| 113647/114105 [02:35<00:00, 725.03 examples/s]
Map: 100%|█████████▉| 113728/114105 [02:35<00:00, 745.40 examples/s]
Map: 100%|█████████▉| 114081/114105 [02:35<00:00, 607.15 examples/s]
Map: 100%|█████████▉| 113808/114105 [02:35<00:00, 754.81 examples/s]
Map: 100%|█████████▉| 114043/114105 [02:35<00:00, 604.99 examples/s]
Map: 100%|█████████▉| 113885/114105 [02:35<00:00, 754.96 examples/s]
Map: 100%|██████████| 114105/114105 [02:35<00:00, 733.12 examples/s]

Map: 100%|█████████▉| 113963/114105 [02:35<00:00, 761.23 examples/s]
Map: 100%|██████████| 114105/114105 [02:35<00:00, 733.21 examples/s]

Map: 100%|█████████▉| 114040/114105 [02:36<00:00, 578.32 examples/s]
Map: 100%|██████████| 114105/114105 [02:36<00:00, 729.74 examples/s]
Detected kernel version 5.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
wandb: Currently logged in as: k-duan (nus_keyu). Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.16.1
wandb: Run data is saved locally in /home/aiops/duanky/lora-moe/experiments/launch_scripts/wandb/run-20231230_053311-nnsx4ee7
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run belle_dolphine-p19
wandb: ⭐️ View project at https://wandb.ai/nus_keyu/lora-moe
wandb: 🚀 View run at https://wandb.ai/nus_keyu/lora-moe/runs/nnsx4ee7

  0%|          | 0/3566 [00:00<?, ?it/s]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(

  0%|          | 1/3566 [00:03<3:06:11,  3.13s/it]
                                                  
{'loss': 1.9918, 'learning_rate': 4.000000000000001e-06, 'epoch': 0.0}

  0%|          | 1/3566 [00:03<3:06:11,  3.13s/it]
  0%|          | 2/3566 [00:05<2:43:25,  2.75s/it]
                                                  
{'loss': 2.0258, 'learning_rate': 8.000000000000001e-06, 'epoch': 0.0}

  0%|          | 2/3566 [00:05<2:43:25,  2.75s/it]
  0%|          | 3/3566 [00:08<2:34:42,  2.61s/it]
                                                  
{'loss': 2.0756, 'learning_rate': 1.2e-05, 'epoch': 0.0}

  0%|          | 3/3566 [00:08<2:34:42,  2.61s/it]
  0%|          | 4/3566 [00:10<2:39:34,  2.69s/it]
                                                  
{'loss': 2.2086, 'learning_rate': 1.6000000000000003e-05, 'epoch': 0.0}

  0%|          | 4/3566 [00:10<2:39:34,  2.69s/it]
  0%|          | 5/3566 [00:13<2:31:09,  2.55s/it]
                                                  
{'loss': 2.075, 'learning_rate': 2e-05, 'epoch': 0.0}

  0%|          | 5/3566 [00:13<2:31:09,  2.55s/it]
  0%|          | 6/3566 [00:15<2:25:15,  2.45s/it]
                                                  
{'loss': 2.0893, 'learning_rate': 2.4e-05, 'epoch': 0.0}

  0%|          | 6/3566 [00:15<2:25:15,  2.45s/it]
  0%|          | 7/3566 [00:17<2:24:50,  2.44s/it]
                                                  
{'loss': 2.0577, 'learning_rate': 2.8000000000000003e-05, 'epoch': 0.0}

  0%|          | 7/3566 [00:17<2:24:50,  2.44s/it]
  0%|          | 8/3566 [00:20<2:28:16,  2.50s/it]
                                                  
{'loss': 1.9745, 'learning_rate': 3.2000000000000005e-05, 'epoch': 0.0}

  0%|          | 8/3566 [00:20<2:28:16,  2.50s/it]
  0%|          | 9/3566 [00:22<2:27:25,  2.49s/it]
                                                  
{'loss': 1.9442, 'learning_rate': 3.6e-05, 'epoch': 0.0}

  0%|          | 9/3566 [00:22<2:27:25,  2.49s/it]
  0%|          | 10/3566 [00:25<2:30:34,  2.54s/it]
                                                   
{'loss': 1.9246, 'learning_rate': 4e-05, 'epoch': 0.0}

  0%|          | 10/3566 [00:25<2:30:34,  2.54s/it]
  0%|          | 11/3566 [00:27<2:27:17,  2.49s/it]
                                                   
{'loss': 1.9296, 'learning_rate': 4.4000000000000006e-05, 'epoch': 0.0}

  0%|          | 11/3566 [00:27<2:27:17,  2.49s/it]
  0%|          | 12/3566 [00:30<2:28:05,  2.50s/it]
                                                   
{'loss': 1.9183, 'learning_rate': 4.8e-05, 'epoch': 0.0}

  0%|          | 12/3566 [00:30<2:28:05,  2.50s/it]
  0%|          | 13/3566 [00:33<2:28:41,  2.51s/it]
                                                   
{'loss': 1.9778, 'learning_rate': 5.2000000000000004e-05, 'epoch': 0.0}

  0%|          | 13/3566 [00:33<2:28:41,  2.51s/it]
  0%|          | 14/3566 [00:35<2:25:25,  2.46s/it]
                                                   
{'loss': 1.8426, 'learning_rate': 5.6000000000000006e-05, 'epoch': 0.0}

  0%|          | 14/3566 [00:35<2:25:25,  2.46s/it]
  0%|          | 15/3566 [00:37<2:23:21,  2.42s/it]
                                                   
{'loss': 1.8825, 'learning_rate': 6e-05, 'epoch': 0.0}

  0%|          | 15/3566 [00:37<2:23:21,  2.42s/it]
  0%|          | 16/3566 [00:39<2:20:34,  2.38s/it]
                                                   
{'loss': 1.7846, 'learning_rate': 6.400000000000001e-05, 'epoch': 0.0}

  0%|          | 16/3566 [00:39<2:20:34,  2.38s/it]
  0%|          | 17/3566 [00:42<2:21:48,  2.40s/it]
                                                   
{'loss': 1.8535, 'learning_rate': 6.800000000000001e-05, 'epoch': 0.0}

  0%|          | 17/3566 [00:42<2:21:48,  2.40s/it]
  1%|          | 18/3566 [00:44<2:22:47,  2.41s/it]
                                                   
{'loss': 1.6916, 'learning_rate': 7.2e-05, 'epoch': 0.01}

  1%|          | 18/3566 [00:44<2:22:47,  2.41s/it]
  1%|          | 19/3566 [00:47<2:24:18,  2.44s/it]
                                                   
{'loss': 1.7672, 'learning_rate': 7.6e-05, 'epoch': 0.01}

  1%|          | 19/3566 [00:47<2:24:18,  2.44s/it]
  1%|          | 20/3566 [00:49<2:23:27,  2.43s/it]
                                                   
{'loss': 1.8477, 'learning_rate': 8e-05, 'epoch': 0.01}

  1%|          | 20/3566 [00:49<2:23:27,  2.43s/it]
  1%|          | 21/3566 [00:51<2:18:07,  2.34s/it]
                                                   
{'loss': 1.8787, 'learning_rate': 8.4e-05, 'epoch': 0.01}

  1%|          | 21/3566 [00:51<2:18:07,  2.34s/it]
  1%|          | 22/3566 [00:54<2:17:06,  2.32s/it]
                                                   
{'loss': 1.8734, 'learning_rate': 8.800000000000001e-05, 'epoch': 0.01}

  1%|          | 22/3566 [00:54<2:17:06,  2.32s/it]
  1%|          | 23/3566 [00:56<2:22:54,  2.42s/it]
                                                   
{'loss': 1.8889, 'learning_rate': 9.200000000000001e-05, 'epoch': 0.01}

  1%|          | 23/3566 [00:56<2:22:54,  2.42s/it]
  1%|          | 24/3566 [00:59<2:20:16,  2.38s/it]
                                                   
{'loss': 1.8299, 'learning_rate': 9.6e-05, 'epoch': 0.01}

  1%|          | 24/3566 [00:59<2:20:16,  2.38s/it]
  1%|          | 25/3566 [01:01<2:20:41,  2.38s/it]
                                                   
{'loss': 1.7827, 'learning_rate': 0.0001, 'epoch': 0.01}

  1%|          | 25/3566 [01:01<2:20:41,  2.38s/it]
  1%|          | 26/3566 [01:03<2:20:04,  2.37s/it]
                                                   
{'loss': 1.8557, 'learning_rate': 0.00010400000000000001, 'epoch': 0.01}

  1%|          | 26/3566 [01:03<2:20:04,  2.37s/it]
  1%|          | 27/3566 [01:06<2:28:44,  2.52s/it]
                                                   
{'loss': 1.9838, 'learning_rate': 0.00010800000000000001, 'epoch': 0.01}

  1%|          | 27/3566 [01:06<2:28:44,  2.52s/it]
  1%|          | 28/3566 [01:09<2:28:12,  2.51s/it]
                                                   
{'loss': 1.8365, 'learning_rate': 0.00011200000000000001, 'epoch': 0.01}

  1%|          | 28/3566 [01:09<2:28:12,  2.51s/it]
  1%|          | 29/3566 [01:11<2:26:54,  2.49s/it]
                                                   
{'loss': 1.7932, 'learning_rate': 0.000116, 'epoch': 0.01}

  1%|          | 29/3566 [01:11<2:26:54,  2.49s/it]
  1%|          | 30/3566 [01:13<2:22:42,  2.42s/it]
                                                   
{'loss': 1.7293, 'learning_rate': 0.00012, 'epoch': 0.01}

  1%|          | 30/3566 [01:13<2:22:42,  2.42s/it]
  1%|          | 31/3566 [01:16<2:22:46,  2.42s/it]
                                                   
{'loss': 1.712, 'learning_rate': 0.000124, 'epoch': 0.01}

  1%|          | 31/3566 [01:16<2:22:46,  2.42s/it]
  1%|          | 32/3566 [01:18<2:23:31,  2.44s/it]
                                                   
{'loss': 1.7439, 'learning_rate': 0.00012800000000000002, 'epoch': 0.01}

  1%|          | 32/3566 [01:18<2:23:31,  2.44s/it]
  1%|          | 33/3566 [01:21<2:28:59,  2.53s/it]
                                                   
{'loss': 1.7217, 'learning_rate': 0.000132, 'epoch': 0.01}

  1%|          | 33/3566 [01:21<2:28:59,  2.53s/it]
  1%|          | 34/3566 [01:23<2:24:21,  2.45s/it]
                                                   
{'loss': 1.7385, 'learning_rate': 0.00013600000000000003, 'epoch': 0.01}

  1%|          | 34/3566 [01:23<2:24:21,  2.45s/it]
  1%|          | 35/3566 [01:26<2:25:14,  2.47s/it]
                                                   
{'loss': 1.842, 'learning_rate': 0.00014, 'epoch': 0.01}

  1%|          | 35/3566 [01:26<2:25:14,  2.47s/it]
  1%|          | 36/3566 [01:28<2:19:47,  2.38s/it]
                                                   
{'loss': 1.8133, 'learning_rate': 0.000144, 'epoch': 0.01}

  1%|          | 36/3566 [01:28<2:19:47,  2.38s/it]
  1%|          | 37/3566 [01:30<2:20:33,  2.39s/it]
                                                   
{'loss': 1.7923, 'learning_rate': 0.000148, 'epoch': 0.01}

  1%|          | 37/3566 [01:30<2:20:33,  2.39s/it]
  1%|          | 38/3566 [01:33<2:22:23,  2.42s/it]
                                                   
{'loss': 1.8135, 'learning_rate': 0.000152, 'epoch': 0.01}

  1%|          | 38/3566 [01:33<2:22:23,  2.42s/it]
  1%|          | 39/3566 [01:35<2:21:35,  2.41s/it]
                                                   
{'loss': 1.8485, 'learning_rate': 0.00015600000000000002, 'epoch': 0.01}

  1%|          | 39/3566 [01:35<2:21:35,  2.41s/it]
  1%|          | 40/3566 [01:37<2:17:23,  2.34s/it]
                                                   
{'loss': 1.9182, 'learning_rate': 0.00016, 'epoch': 0.01}

  1%|          | 40/3566 [01:37<2:17:23,  2.34s/it]
  1%|          | 41/3566 [01:40<2:15:50,  2.31s/it]
                                                   
{'loss': 1.7354, 'learning_rate': 0.000164, 'epoch': 0.01}

  1%|          | 41/3566 [01:40<2:15:50,  2.31s/it]
  1%|          | 42/3566 [01:42<2:13:59,  2.28s/it]
                                                   
{'loss': 1.5868, 'learning_rate': 0.000168, 'epoch': 0.01}

  1%|          | 42/3566 [01:42<2:13:59,  2.28s/it]
  1%|          | 43/3566 [01:44<2:13:43,  2.28s/it]
                                                   
{'loss': 1.7228, 'learning_rate': 0.000172, 'epoch': 0.01}

  1%|          | 43/3566 [01:44<2:13:43,  2.28s/it]
  1%|          | 44/3566 [01:47<2:15:32,  2.31s/it]
                                                   
{'loss': 1.6714, 'learning_rate': 0.00017600000000000002, 'epoch': 0.01}

  1%|          | 44/3566 [01:47<2:15:32,  2.31s/it]
  1%|▏         | 45/3566 [01:49<2:12:14,  2.25s/it]
                                                   
{'loss': 1.7548, 'learning_rate': 0.00018, 'epoch': 0.01}

  1%|▏         | 45/3566 [01:49<2:12:14,  2.25s/it]
  1%|▏         | 46/3566 [01:51<2:16:40,  2.33s/it]
                                                   
{'loss': 1.7708, 'learning_rate': 0.00018400000000000003, 'epoch': 0.01}

  1%|▏         | 46/3566 [01:51<2:16:40,  2.33s/it]
  1%|▏         | 47/3566 [01:54<2:17:23,  2.34s/it]
                                                   
{'loss': 1.6132, 'learning_rate': 0.000188, 'epoch': 0.01}

  1%|▏         | 47/3566 [01:54<2:17:23,  2.34s/it]
  1%|▏         | 48/3566 [01:56<2:15:39,  2.31s/it]
                                                   
{'loss': 1.6484, 'learning_rate': 0.000192, 'epoch': 0.01}

  1%|▏         | 48/3566 [01:56<2:15:39,  2.31s/it]
  1%|▏         | 49/3566 [01:58<2:17:29,  2.35s/it]
                                                   
{'loss': 1.8452, 'learning_rate': 0.000196, 'epoch': 0.01}

  1%|▏         | 49/3566 [01:58<2:17:29,  2.35s/it]
  1%|▏         | 50/3566 [02:01<2:16:43,  2.33s/it]
                                                   
{'loss': 1.7226, 'learning_rate': 0.0002, 'epoch': 0.01}

  1%|▏         | 50/3566 [02:01<2:16:43,  2.33s/it]
  1%|▏         | 51/3566 [02:03<2:19:56,  2.39s/it]
                                                   
{'loss': 1.7263, 'learning_rate': 0.00020400000000000003, 'epoch': 0.01}

  1%|▏         | 51/3566 [02:03<2:19:56,  2.39s/it]
  1%|▏         | 52/3566 [02:06<2:20:58,  2.41s/it]
                                                   
{'loss': 1.7683, 'learning_rate': 0.00020800000000000001, 'epoch': 0.01}

  1%|▏         | 52/3566 [02:06<2:20:58,  2.41s/it]
  1%|▏         | 53/3566 [02:08<2:20:45,  2.40s/it]
                                                   
{'loss': 1.5194, 'learning_rate': 0.00021200000000000003, 'epoch': 0.01}

  1%|▏         | 53/3566 [02:08<2:20:45,  2.40s/it]
  2%|▏         | 54/3566 [02:10<2:21:25,  2.42s/it]
                                                   
{'loss': 1.8621, 'learning_rate': 0.00021600000000000002, 'epoch': 0.02}

  2%|▏         | 54/3566 [02:10<2:21:25,  2.42s/it]
  2%|▏         | 55/3566 [02:13<2:19:41,  2.39s/it]
                                                   
{'loss': 1.6884, 'learning_rate': 0.00022000000000000003, 'epoch': 0.02}

  2%|▏         | 55/3566 [02:13<2:19:41,  2.39s/it]
  2%|▏         | 56/3566 [02:15<2:18:39,  2.37s/it]
                                                   
{'loss': 1.6589, 'learning_rate': 0.00022400000000000002, 'epoch': 0.02}

  2%|▏         | 56/3566 [02:15<2:18:39,  2.37s/it]
  2%|▏         | 57/3566 [02:17<2:18:28,  2.37s/it]
                                                   
{'loss': 1.7475, 'learning_rate': 0.00022799999999999999, 'epoch': 0.02}

  2%|▏         | 57/3566 [02:17<2:18:28,  2.37s/it]
  2%|▏         | 58/3566 [02:20<2:20:48,  2.41s/it]
                                                   
{'loss': 1.5911, 'learning_rate': 0.000232, 'epoch': 0.02}

  2%|▏         | 58/3566 [02:20<2:20:48,  2.41s/it]
  2%|▏         | 59/3566 [02:22<2:19:29,  2.39s/it]
                                                   
{'loss': 1.6961, 'learning_rate': 0.000236, 'epoch': 0.02}

  2%|▏         | 59/3566 [02:22<2:19:29,  2.39s/it]
  2%|▏         | 60/3566 [02:25<2:21:50,  2.43s/it]
                                                   
{'loss': 1.7497, 'learning_rate': 0.00024, 'epoch': 0.02}

  2%|▏         | 60/3566 [02:25<2:21:50,  2.43s/it]
  2%|▏         | 61/3566 [02:27<2:22:00,  2.43s/it]
                                                   
{'loss': 1.7571, 'learning_rate': 0.000244, 'epoch': 0.02}

  2%|▏         | 61/3566 [02:27<2:22:00,  2.43s/it]
  2%|▏         | 62/3566 [02:30<2:22:04,  2.43s/it]
                                                   
{'loss': 1.7656, 'learning_rate': 0.000248, 'epoch': 0.02}

  2%|▏         | 62/3566 [02:30<2:22:04,  2.43s/it]
  2%|▏         | 63/3566 [02:32<2:23:57,  2.47s/it]
                                                   
{'loss': 1.6999, 'learning_rate': 0.000252, 'epoch': 0.02}

  2%|▏         | 63/3566 [02:32<2:23:57,  2.47s/it]
  2%|▏         | 64/3566 [02:35<2:22:58,  2.45s/it]
                                                   
{'loss': 1.6289, 'learning_rate': 0.00025600000000000004, 'epoch': 0.02}

  2%|▏         | 64/3566 [02:35<2:22:58,  2.45s/it]
  2%|▏         | 65/3566 [02:37<2:25:28,  2.49s/it]
                                                   
{'loss': 1.7333, 'learning_rate': 0.00026000000000000003, 'epoch': 0.02}

  2%|▏         | 65/3566 [02:37<2:25:28,  2.49s/it]
  2%|▏         | 66/3566 [02:40<2:23:06,  2.45s/it]
                                                   
{'loss': 1.8245, 'learning_rate': 0.000264, 'epoch': 0.02}

  2%|▏         | 66/3566 [02:40<2:23:06,  2.45s/it]
  2%|▏         | 67/3566 [02:42<2:23:05,  2.45s/it]
                                                   
{'loss': 1.7294, 'learning_rate': 0.000268, 'epoch': 0.02}

  2%|▏         | 67/3566 [02:42<2:23:05,  2.45s/it]
  2%|▏         | 68/3566 [02:44<2:23:36,  2.46s/it]
                                                   
{'loss': 1.8249, 'learning_rate': 0.00027200000000000005, 'epoch': 0.02}

  2%|▏         | 68/3566 [02:44<2:23:36,  2.46s/it]
  2%|▏         | 69/3566 [02:47<2:18:50,  2.38s/it]
                                                   
{'loss': 1.7929, 'learning_rate': 0.000276, 'epoch': 0.02}

  2%|▏         | 69/3566 [02:47<2:18:50,  2.38s/it]
  2%|▏         | 70/3566 [02:49<2:14:23,  2.31s/it]
                                                   
{'loss': 1.6111, 'learning_rate': 0.00028, 'epoch': 0.02}

  2%|▏         | 70/3566 [02:49<2:14:23,  2.31s/it]
  2%|▏         | 71/3566 [02:51<2:18:31,  2.38s/it]
                                                   
{'loss': 1.775, 'learning_rate': 0.000284, 'epoch': 0.02}

  2%|▏         | 71/3566 [02:51<2:18:31,  2.38s/it]
  2%|▏         | 72/3566 [02:54<2:18:20,  2.38s/it]
                                                   
{'loss': 1.6014, 'learning_rate': 0.000288, 'epoch': 0.02}

  2%|▏         | 72/3566 [02:54<2:18:20,  2.38s/it]
  2%|▏         | 73/3566 [02:56<2:19:47,  2.40s/it]
                                                   
{'loss': 1.6855, 'learning_rate': 0.000292, 'epoch': 0.02}

  2%|▏         | 73/3566 [02:56<2:19:47,  2.40s/it]
  2%|▏         | 74/3566 [02:59<2:19:32,  2.40s/it]
                                                   
{'loss': 1.8239, 'learning_rate': 0.000296, 'epoch': 0.02}

  2%|▏         | 74/3566 [02:59<2:19:32,  2.40s/it]
  2%|▏         | 75/3566 [03:01<2:19:40,  2.40s/it]
                                                   
{'loss': 1.7535, 'learning_rate': 0.00030000000000000003, 'epoch': 0.02}

  2%|▏         | 75/3566 [03:01<2:19:40,  2.40s/it]
  2%|▏         | 76/3566 [03:04<2:22:50,  2.46s/it]
                                                   
{'loss': 1.6055, 'learning_rate': 0.000304, 'epoch': 0.02}

  2%|▏         | 76/3566 [03:04<2:22:50,  2.46s/it]
  2%|▏         | 77/3566 [03:06<2:27:49,  2.54s/it]
                                                   
{'loss': 1.8036, 'learning_rate': 0.000308, 'epoch': 0.02}

  2%|▏         | 77/3566 [03:06<2:27:49,  2.54s/it]
  2%|▏         | 78/3566 [03:09<2:25:41,  2.51s/it]
                                                   
{'loss': 1.6589, 'learning_rate': 0.00031200000000000005, 'epoch': 0.02}

  2%|▏         | 78/3566 [03:09<2:25:41,  2.51s/it]
  2%|▏         | 79/3566 [03:11<2:25:03,  2.50s/it]
                                                   
{'loss': 1.7957, 'learning_rate': 0.00031600000000000004, 'epoch': 0.02}

  2%|▏         | 79/3566 [03:11<2:25:03,  2.50s/it]
  2%|▏         | 80/3566 [03:14<2:27:30,  2.54s/it]
                                                   
{'loss': 1.7978, 'learning_rate': 0.00032, 'epoch': 0.02}

  2%|▏         | 80/3566 [03:14<2:27:30,  2.54s/it]
  2%|▏         | 81/3566 [03:16<2:21:59,  2.44s/it]
                                                   
{'loss': 1.6027, 'learning_rate': 0.000324, 'epoch': 0.02}

  2%|▏         | 81/3566 [03:16<2:21:59,  2.44s/it]
  2%|▏         | 82/3566 [03:18<2:18:38,  2.39s/it]
                                                   
{'loss': 1.6281, 'learning_rate': 0.000328, 'epoch': 0.02}

  2%|▏         | 82/3566 [03:18<2:18:38,  2.39s/it]
  2%|▏         | 83/3566 [03:21<2:22:51,  2.46s/it]
                                                   
{'loss': 1.6942, 'learning_rate': 0.000332, 'epoch': 0.02}

  2%|▏         | 83/3566 [03:21<2:22:51,  2.46s/it]
  2%|▏         | 84/3566 [03:23<2:21:58,  2.45s/it]
                                                   
{'loss': 1.7232, 'learning_rate': 0.000336, 'epoch': 0.02}

  2%|▏         | 84/3566 [03:23<2:21:58,  2.45s/it]
  2%|▏         | 85/3566 [03:26<2:20:19,  2.42s/it]
                                                   
{'loss': 1.605, 'learning_rate': 0.00034, 'epoch': 0.02}

  2%|▏         | 85/3566 [03:26<2:20:19,  2.42s/it]
  2%|▏         | 86/3566 [03:28<2:22:16,  2.45s/it]
                                                   
{'loss': 1.696, 'learning_rate': 0.000344, 'epoch': 0.02}

  2%|▏         | 86/3566 [03:28<2:22:16,  2.45s/it]
  2%|▏         | 87/3566 [03:30<2:18:46,  2.39s/it]
                                                   
{'loss': 1.5277, 'learning_rate': 0.000348, 'epoch': 0.02}

  2%|▏         | 87/3566 [03:30<2:18:46,  2.39s/it]
  2%|▏         | 88/3566 [03:33<2:19:43,  2.41s/it]
                                                   
{'loss': 1.746, 'learning_rate': 0.00035200000000000005, 'epoch': 0.02}

  2%|▏         | 88/3566 [03:33<2:19:43,  2.41s/it]
  2%|▏         | 89/3566 [03:35<2:21:57,  2.45s/it]
                                                   
{'loss': 1.7568, 'learning_rate': 0.00035600000000000003, 'epoch': 0.02}

  2%|▏         | 89/3566 [03:35<2:21:57,  2.45s/it]
  3%|▎         | 90/3566 [03:38<2:22:04,  2.45s/it]
                                                   
{'loss': 1.8807, 'learning_rate': 0.00036, 'epoch': 0.03}

  3%|▎         | 90/3566 [03:38<2:22:04,  2.45s/it]
  3%|▎         | 91/3566 [03:40<2:21:50,  2.45s/it]
                                                   
{'loss': 1.7793, 'learning_rate': 0.000364, 'epoch': 0.03}

  3%|▎         | 91/3566 [03:40<2:21:50,  2.45s/it]
  3%|▎         | 92/3566 [03:43<2:23:51,  2.48s/it]
                                                   
{'loss': 1.7317, 'learning_rate': 0.00036800000000000005, 'epoch': 0.03}

  3%|▎         | 92/3566 [03:43<2:23:51,  2.48s/it]
  3%|▎         | 93/3566 [03:46<2:28:02,  2.56s/it]
                                                   
{'loss': 1.7291, 'learning_rate': 0.00037200000000000004, 'epoch': 0.03}

  3%|▎         | 93/3566 [03:46<2:28:02,  2.56s/it]
  3%|▎         | 94/3566 [03:49<2:33:09,  2.65s/it]
                                                   
{'loss': 1.6806, 'learning_rate': 0.000376, 'epoch': 0.03}

  3%|▎         | 94/3566 [03:49<2:33:09,  2.65s/it]
  3%|▎         | 95/3566 [03:51<2:27:11,  2.54s/it]
                                                   
{'loss': 1.7072, 'learning_rate': 0.00038, 'epoch': 0.03}

  3%|▎         | 95/3566 [03:51<2:27:11,  2.54s/it]
  3%|▎         | 96/3566 [03:53<2:27:18,  2.55s/it]
                                                   
{'loss': 1.692, 'learning_rate': 0.000384, 'epoch': 0.03}

  3%|▎         | 96/3566 [03:53<2:27:18,  2.55s/it]
  3%|▎         | 97/3566 [03:56<2:29:01,  2.58s/it]
                                                   
{'loss': 1.6635, 'learning_rate': 0.000388, 'epoch': 0.03}

  3%|▎         | 97/3566 [03:56<2:29:01,  2.58s/it]
  3%|▎         | 98/3566 [03:59<2:34:01,  2.66s/it]
                                                   
{'loss': 1.7166, 'learning_rate': 0.000392, 'epoch': 0.03}

  3%|▎         | 98/3566 [03:59<2:34:01,  2.66s/it]
  3%|▎         | 99/3566 [04:01<2:32:32,  2.64s/it]
                                                   
{'loss': 1.6075, 'learning_rate': 0.00039600000000000003, 'epoch': 0.03}

  3%|▎         | 99/3566 [04:01<2:32:32,  2.64s/it]
  3%|▎         | 100/3566 [04:04<2:25:26,  2.52s/it]
                                                    
{'loss': 1.6545, 'learning_rate': 0.0004, 'epoch': 0.03}

  3%|▎         | 100/3566 [04:04<2:25:26,  2.52s/it]
  3%|▎         | 101/3566 [04:07<2:41:54,  2.80s/it]
                                                    
{'loss': 1.5775, 'learning_rate': 0.00039999991784337336, 'epoch': 0.03}

  3%|▎         | 101/3566 [04:07<2:41:54,  2.80s/it]
  3%|▎         | 102/3566 [04:10<2:33:38,  2.66s/it]
                                                    
{'loss': 1.8225, 'learning_rate': 0.0003999996713735609, 'epoch': 0.03}

  3%|▎         | 102/3566 [04:10<2:33:38,  2.66s/it]
  3%|▎         | 103/3566 [04:12<2:37:07,  2.72s/it]
                                                    
{'loss': 1.6641, 'learning_rate': 0.000399999260590765, 'epoch': 0.03}

  3%|▎         | 103/3566 [04:12<2:37:07,  2.72s/it]
  3%|▎         | 104/3566 [04:15<2:30:08,  2.60s/it]
                                                    
{'loss': 1.6713, 'learning_rate': 0.00039999868549532336, 'epoch': 0.03}

  3%|▎         | 104/3566 [04:15<2:30:08,  2.60s/it]
  3%|▎         | 105/3566 [04:17<2:26:29,  2.54s/it]
                                                    
{'loss': 1.7508, 'learning_rate': 0.0003999979460877083, 'epoch': 0.03}

  3%|▎         | 105/3566 [04:17<2:26:29,  2.54s/it]
  3%|▎         | 106/3566 [04:20<2:24:31,  2.51s/it]
                                                    
{'loss': 1.6184, 'learning_rate': 0.00039999704236852733, 'epoch': 0.03}

  3%|▎         | 106/3566 [04:20<2:24:31,  2.51s/it]
  3%|▎         | 107/3566 [04:22<2:20:40,  2.44s/it]
                                                    
{'loss': 1.7434, 'learning_rate': 0.00039999597433852294, 'epoch': 0.03}

  3%|▎         | 107/3566 [04:22<2:20:40,  2.44s/it]
  3%|▎         | 108/3566 [04:24<2:17:21,  2.38s/it]
                                                    
{'loss': 1.8389, 'learning_rate': 0.0003999947419985726, 'epoch': 0.03}

  3%|▎         | 108/3566 [04:24<2:17:21,  2.38s/it]
  3%|▎         | 109/3566 [04:26<2:16:47,  2.37s/it]
                                                    
{'loss': 1.8842, 'learning_rate': 0.0003999933453496887, 'epoch': 0.03}

  3%|▎         | 109/3566 [04:26<2:16:47,  2.37s/it]
  3%|▎         | 110/3566 [04:29<2:14:38,  2.34s/it]
                                                    
{'loss': 1.821, 'learning_rate': 0.0003999917843930187, 'epoch': 0.03}

  3%|▎         | 110/3566 [04:29<2:14:38,  2.34s/it]
  3%|▎         | 111/3566 [04:31<2:16:57,  2.38s/it]
                                                    
{'loss': 1.6944, 'learning_rate': 0.00039999005912984503, 'epoch': 0.03}

  3%|▎         | 111/3566 [04:31<2:16:57,  2.38s/it]
  3%|▎         | 112/3566 [04:34<2:21:12,  2.45s/it]
                                                    
{'loss': 1.6341, 'learning_rate': 0.00039998816956158514, 'epoch': 0.03}

  3%|▎         | 112/3566 [04:34<2:21:12,  2.45s/it]
  3%|▎         | 113/3566 [04:36<2:18:08,  2.40s/it]
                                                    
{'loss': 1.8067, 'learning_rate': 0.0003999861156897914, 'epoch': 0.03}

  3%|▎         | 113/3566 [04:36<2:18:08,  2.40s/it]
  3%|▎         | 114/3566 [04:38<2:18:33,  2.41s/it]
                                                    
{'loss': 1.7007, 'learning_rate': 0.0003999838975161512, 'epoch': 0.03}

  3%|▎         | 114/3566 [04:38<2:18:33,  2.41s/it]
  3%|▎         | 115/3566 [04:41<2:21:58,  2.47s/it]
                                                    
{'loss': 1.6112, 'learning_rate': 0.000399981515042487, 'epoch': 0.03}

  3%|▎         | 115/3566 [04:41<2:21:58,  2.47s/it]
  3%|▎         | 116/3566 [04:43<2:18:51,  2.41s/it]
                                                    
{'loss': 1.6086, 'learning_rate': 0.00039997896827075605, 'epoch': 0.03}

  3%|▎         | 116/3566 [04:43<2:18:51,  2.41s/it]
  3%|▎         | 117/3566 [04:45<2:13:33,  2.32s/it]
                                                    
{'loss': 1.7449, 'learning_rate': 0.0003999762572030507, 'epoch': 0.03}

  3%|▎         | 117/3566 [04:45<2:13:33,  2.32s/it]
  3%|▎         | 118/3566 [04:48<2:12:05,  2.30s/it]
                                                    
{'loss': 1.6054, 'learning_rate': 0.0003999733818415983, 'epoch': 0.03}

  3%|▎         | 118/3566 [04:48<2:12:05,  2.30s/it]
  3%|▎         | 119/3566 [04:50<2:12:34,  2.31s/it]
                                                    
{'loss': 1.6986, 'learning_rate': 0.00039997034218876125, 'epoch': 0.03}

  3%|▎         | 119/3566 [04:50<2:12:34,  2.31s/it]
  3%|▎         | 120/3566 [04:53<2:16:48,  2.38s/it]
                                                    
{'loss': 1.7209, 'learning_rate': 0.00039996713824703664, 'epoch': 0.03}

  3%|▎         | 120/3566 [04:53<2:16:48,  2.38s/it]
  3%|▎         | 121/3566 [04:55<2:18:48,  2.42s/it]
                                                    
{'loss': 1.6468, 'learning_rate': 0.00039996377001905685, 'epoch': 0.03}

  3%|▎         | 121/3566 [04:55<2:18:48,  2.42s/it]
  3%|▎         | 122/3566 [04:58<2:23:04,  2.49s/it]
                                                    
{'loss': 1.6012, 'learning_rate': 0.00039996023750758905, 'epoch': 0.03}

  3%|▎         | 122/3566 [04:58<2:23:04,  2.49s/it]
  3%|▎         | 123/3566 [05:00<2:20:54,  2.46s/it]
                                                    
{'loss': 1.7693, 'learning_rate': 0.0003999565407155355, 'epoch': 0.03}

  3%|▎         | 123/3566 [05:00<2:20:54,  2.46s/it]
  3%|▎         | 124/3566 [05:03<2:22:21,  2.48s/it]
                                                    
{'loss': 1.6956, 'learning_rate': 0.0003999526796459332, 'epoch': 0.03}

  3%|▎         | 124/3566 [05:03<2:22:21,  2.48s/it]
  4%|▎         | 125/3566 [05:05<2:22:10,  2.48s/it]
                                                    
{'loss': 1.6959, 'learning_rate': 0.00039994865430195443, 'epoch': 0.04}

  4%|▎         | 125/3566 [05:05<2:22:10,  2.48s/it]
  4%|▎         | 126/3566 [05:07<2:18:47,  2.42s/it]
                                                    
{'loss': 1.6999, 'learning_rate': 0.00039994446468690625, 'epoch': 0.04}

  4%|▎         | 126/3566 [05:07<2:18:47,  2.42s/it]
  4%|▎         | 127/3566 [05:10<2:18:42,  2.42s/it]
                                                    
{'loss': 1.6748, 'learning_rate': 0.00039994011080423064, 'epoch': 0.04}

  4%|▎         | 127/3566 [05:10<2:18:42,  2.42s/it]
  4%|▎         | 128/3566 [05:12<2:15:58,  2.37s/it]
                                                    
{'loss': 1.6957, 'learning_rate': 0.00039993559265750464, 'epoch': 0.04}

  4%|▎         | 128/3566 [05:12<2:15:58,  2.37s/it]
  4%|▎         | 129/3566 [05:14<2:12:13,  2.31s/it]
                                                    
{'loss': 1.6667, 'learning_rate': 0.0003999309102504403, 'epoch': 0.04}

  4%|▎         | 129/3566 [05:14<2:12:13,  2.31s/it]
  4%|▎         | 130/3566 [05:17<2:12:24,  2.31s/it]
                                                    
{'loss': 1.8012, 'learning_rate': 0.00039992606358688434, 'epoch': 0.04}

  4%|▎         | 130/3566 [05:17<2:12:24,  2.31s/it]
  4%|▎         | 131/3566 [05:19<2:12:04,  2.31s/it]
                                                    
{'loss': 1.702, 'learning_rate': 0.0003999210526708188, 'epoch': 0.04}

  4%|▎         | 131/3566 [05:19<2:12:04,  2.31s/it]
  4%|▎         | 132/3566 [05:21<2:15:33,  2.37s/it]
                                                    
{'loss': 1.8419, 'learning_rate': 0.00039991587750636036, 'epoch': 0.04}

  4%|▎         | 132/3566 [05:21<2:15:33,  2.37s/it]
  4%|▎         | 133/3566 [05:24<2:16:19,  2.38s/it]
                                                    
{'loss': 1.6793, 'learning_rate': 0.0003999105380977608, 'epoch': 0.04}

  4%|▎         | 133/3566 [05:24<2:16:19,  2.38s/it]
  4%|▍         | 134/3566 [05:26<2:14:49,  2.36s/it]
                                                    
{'loss': 1.7067, 'learning_rate': 0.0003999050344494068, 'epoch': 0.04}

  4%|▍         | 134/3566 [05:26<2:14:49,  2.36s/it]
  4%|▍         | 135/3566 [05:28<2:14:07,  2.35s/it]
                                                    
{'loss': 1.5846, 'learning_rate': 0.00039989936656581996, 'epoch': 0.04}

  4%|▍         | 135/3566 [05:28<2:14:07,  2.35s/it]
  4%|▍         | 136/3566 [05:31<2:17:04,  2.40s/it]
                                                    
{'loss': 1.8016, 'learning_rate': 0.0003998935344516569, 'epoch': 0.04}

  4%|▍         | 136/3566 [05:31<2:17:04,  2.40s/it]
  4%|▍         | 137/3566 [05:34<2:20:07,  2.45s/it]
                                                    
{'loss': 1.6084, 'learning_rate': 0.0003998875381117089, 'epoch': 0.04}

  4%|▍         | 137/3566 [05:34<2:20:07,  2.45s/it]
  4%|▍         | 138/3566 [05:36<2:16:47,  2.39s/it]
                                                    
{'loss': 1.7251, 'learning_rate': 0.0003998813775509025, 'epoch': 0.04}

  4%|▍         | 138/3566 [05:36<2:16:47,  2.39s/it]
  4%|▍         | 139/3566 [05:38<2:20:44,  2.46s/it]
                                                    
{'loss': 1.6121, 'learning_rate': 0.00039987505277429904, 'epoch': 0.04}

  4%|▍         | 139/3566 [05:38<2:20:44,  2.46s/it]
  4%|▍         | 140/3566 [05:41<2:19:21,  2.44s/it]
                                                    
{'loss': 1.673, 'learning_rate': 0.00039986856378709454, 'epoch': 0.04}

  4%|▍         | 140/3566 [05:41<2:19:21,  2.44s/it]
  4%|▍         | 141/3566 [05:43<2:16:59,  2.40s/it]
                                                    
{'loss': 1.5884, 'learning_rate': 0.0003998619105946204, 'epoch': 0.04}

  4%|▍         | 141/3566 [05:43<2:16:59,  2.40s/it]
  4%|▍         | 142/3566 [05:45<2:16:21,  2.39s/it]
                                                    
{'loss': 1.6651, 'learning_rate': 0.00039985509320234245, 'epoch': 0.04}

  4%|▍         | 142/3566 [05:45<2:16:21,  2.39s/it]
  4%|▍         | 143/3566 [05:48<2:18:20,  2.42s/it]
                                                    
{'loss': 1.787, 'learning_rate': 0.0003998481116158618, 'epoch': 0.04}

  4%|▍         | 143/3566 [05:48<2:18:20,  2.42s/it]
  4%|▍         | 144/3566 [05:50<2:17:17,  2.41s/it]
                                                    
{'loss': 1.7694, 'learning_rate': 0.00039984096584091413, 'epoch': 0.04}

  4%|▍         | 144/3566 [05:50<2:17:17,  2.41s/it]
  4%|▍         | 145/3566 [05:53<2:17:56,  2.42s/it]
                                                    
{'loss': 1.8221, 'learning_rate': 0.0003998336558833703, 'epoch': 0.04}

  4%|▍         | 145/3566 [05:53<2:17:56,  2.42s/it]
  4%|▍         | 146/3566 [05:55<2:18:52,  2.44s/it]
                                                    
{'loss': 1.7721, 'learning_rate': 0.00039982618174923577, 'epoch': 0.04}

  4%|▍         | 146/3566 [05:55<2:18:52,  2.44s/it]
  4%|▍         | 147/3566 [05:58<2:16:58,  2.40s/it]
                                                    
{'loss': 1.7399, 'learning_rate': 0.0003998185434446512, 'epoch': 0.04}

  4%|▍         | 147/3566 [05:58<2:16:58,  2.40s/it]
  4%|▍         | 148/3566 [06:00<2:16:52,  2.40s/it]
                                                    
{'loss': 1.6257, 'learning_rate': 0.0003998107409758919, 'epoch': 0.04}

  4%|▍         | 148/3566 [06:00<2:16:52,  2.40s/it]
  4%|▍         | 149/3566 [06:02<2:14:24,  2.36s/it]
                                                    
{'loss': 1.7065, 'learning_rate': 0.000399802774349368, 'epoch': 0.04}

  4%|▍         | 149/3566 [06:02<2:14:24,  2.36s/it]
  4%|▍         | 150/3566 [06:05<2:14:10,  2.36s/it]
                                                    
{'loss': 1.6701, 'learning_rate': 0.0003997946435716248, 'epoch': 0.04}

  4%|▍         | 150/3566 [06:05<2:14:10,  2.36s/it]
  4%|▍         | 151/3566 [06:07<2:14:22,  2.36s/it]
                                                    
{'loss': 1.6728, 'learning_rate': 0.00039978634864934215, 'epoch': 0.04}

  4%|▍         | 151/3566 [06:07<2:14:22,  2.36s/it]
  4%|▍         | 152/3566 [06:10<2:22:40,  2.51s/it]
                                                    
{'loss': 1.7849, 'learning_rate': 0.00039977788958933495, 'epoch': 0.04}

  4%|▍         | 152/3566 [06:10<2:22:40,  2.51s/it]
  4%|▍         | 153/3566 [06:12<2:24:13,  2.54s/it]
                                                    
{'loss': 1.6676, 'learning_rate': 0.0003997692663985528, 'epoch': 0.04}

  4%|▍         | 153/3566 [06:12<2:24:13,  2.54s/it]
  4%|▍         | 154/3566 [06:15<2:18:14,  2.43s/it]
                                                    
{'loss': 1.845, 'learning_rate': 0.0003997604790840803, 'epoch': 0.04}

  4%|▍         | 154/3566 [06:15<2:18:14,  2.43s/it]
  4%|▍         | 155/3566 [06:17<2:21:20,  2.49s/it]
                                                    
{'loss': 1.6801, 'learning_rate': 0.0003997515276531368, 'epoch': 0.04}

  4%|▍         | 155/3566 [06:17<2:21:20,  2.49s/it]
  4%|▍         | 156/3566 [06:20<2:19:19,  2.45s/it]
                                                    
{'loss': 1.6767, 'learning_rate': 0.0003997424121130764, 'epoch': 0.04}

  4%|▍         | 156/3566 [06:20<2:19:19,  2.45s/it]
  4%|▍         | 157/3566 [06:22<2:17:39,  2.42s/it]
                                                    
{'loss': 1.7125, 'learning_rate': 0.00039973313247138823, 'epoch': 0.04}

  4%|▍         | 157/3566 [06:22<2:17:39,  2.42s/it]
  4%|▍         | 158/3566 [06:24<2:14:56,  2.38s/it]
                                                    
{'loss': 1.6456, 'learning_rate': 0.0003997236887356961, 'epoch': 0.04}

  4%|▍         | 158/3566 [06:24<2:14:56,  2.38s/it]
  4%|▍         | 159/3566 [06:26<2:09:49,  2.29s/it]
                                                    
{'loss': 1.5806, 'learning_rate': 0.0003997140809137586, 'epoch': 0.04}

  4%|▍         | 159/3566 [06:26<2:09:49,  2.29s/it]
  4%|▍         | 160/3566 [06:29<2:13:14,  2.35s/it]
                                                    
{'loss': 1.669, 'learning_rate': 0.00039970430901346935, 'epoch': 0.04}

  4%|▍         | 160/3566 [06:29<2:13:14,  2.35s/it]
  5%|▍         | 161/3566 [06:31<2:09:35,  2.28s/it]
                                                    
{'loss': 1.754, 'learning_rate': 0.0003996943730428565, 'epoch': 0.05}

  5%|▍         | 161/3566 [06:31<2:09:35,  2.28s/it]
  5%|▍         | 162/3566 [06:33<2:11:09,  2.31s/it]
                                                    
{'loss': 1.6931, 'learning_rate': 0.00039968427301008305, 'epoch': 0.05}

  5%|▍         | 162/3566 [06:33<2:11:09,  2.31s/it]
  5%|▍         | 163/3566 [06:36<2:15:32,  2.39s/it]
                                                    
{'loss': 1.7199, 'learning_rate': 0.000399674008923447, 'epoch': 0.05}

  5%|▍         | 163/3566 [06:36<2:15:32,  2.39s/it]
  5%|▍         | 164/3566 [06:38<2:09:47,  2.29s/it]
                                                    
{'loss': 1.6193, 'learning_rate': 0.00039966358079138083, 'epoch': 0.05}

  5%|▍         | 164/3566 [06:38<2:09:47,  2.29s/it]
  5%|▍         | 165/3566 [06:40<2:10:59,  2.31s/it]
                                                    
{'loss': 1.5771, 'learning_rate': 0.00039965298862245204, 'epoch': 0.05}

  5%|▍         | 165/3566 [06:40<2:10:59,  2.31s/it]
  5%|▍         | 166/3566 [06:43<2:10:17,  2.30s/it]
                                                    
{'loss': 1.7107, 'learning_rate': 0.0003996422324253628, 'epoch': 0.05}

  5%|▍         | 166/3566 [06:43<2:10:17,  2.30s/it]
  5%|▍         | 167/3566 [06:45<2:11:28,  2.32s/it]
                                                    
{'loss': 1.6894, 'learning_rate': 0.0003996313122089499, 'epoch': 0.05}

  5%|▍         | 167/3566 [06:45<2:11:28,  2.32s/it]
  5%|▍         | 168/3566 [06:47<2:13:51,  2.36s/it]
                                                    
{'loss': 1.6656, 'learning_rate': 0.0003996202279821852, 'epoch': 0.05}

  5%|▍         | 168/3566 [06:47<2:13:51,  2.36s/it]
  5%|▍         | 169/3566 [06:50<2:15:01,  2.38s/it]
                                                    
{'loss': 1.8858, 'learning_rate': 0.000399608979754175, 'epoch': 0.05}

  5%|▍         | 169/3566 [06:50<2:15:01,  2.38s/it]
  5%|▍         | 170/3566 [06:52<2:13:43,  2.36s/it]
                                                    
{'loss': 1.7983, 'learning_rate': 0.0003995975675341606, 'epoch': 0.05}

  5%|▍         | 170/3566 [06:52<2:13:43,  2.36s/it]
  5%|▍         | 171/3566 [06:55<2:16:55,  2.42s/it]
                                                    
{'loss': 1.5216, 'learning_rate': 0.0003995859913315178, 'epoch': 0.05}

  5%|▍         | 171/3566 [06:55<2:16:55,  2.42s/it]
  5%|▍         | 172/3566 [06:57<2:14:08,  2.37s/it]
                                                    
{'loss': 1.6359, 'learning_rate': 0.00039957425115575714, 'epoch': 0.05}

  5%|▍         | 172/3566 [06:57<2:14:08,  2.37s/it]
  5%|▍         | 173/3566 [07:00<2:17:53,  2.44s/it]
                                                    
{'loss': 1.6685, 'learning_rate': 0.00039956234701652414, 'epoch': 0.05}

  5%|▍         | 173/3566 [07:00<2:17:53,  2.44s/it]
  5%|▍         | 174/3566 [07:02<2:13:30,  2.36s/it]
                                                    
{'loss': 1.8074, 'learning_rate': 0.00039955027892359866, 'epoch': 0.05}

  5%|▍         | 174/3566 [07:02<2:13:30,  2.36s/it]
  5%|▍         | 175/3566 [07:04<2:12:34,  2.35s/it]
                                                    
{'loss': 1.6036, 'learning_rate': 0.0003995380468868956, 'epoch': 0.05}

  5%|▍         | 175/3566 [07:04<2:12:34,  2.35s/it]
  5%|▍         | 176/3566 [07:07<2:14:27,  2.38s/it]
                                                    
{'loss': 1.733, 'learning_rate': 0.00039952565091646425, 'epoch': 0.05}

  5%|▍         | 176/3566 [07:07<2:14:27,  2.38s/it]
  5%|▍         | 177/3566 [07:09<2:14:57,  2.39s/it]
                                                    
{'loss': 1.7479, 'learning_rate': 0.0003995130910224888, 'epoch': 0.05}

  5%|▍         | 177/3566 [07:09<2:14:57,  2.39s/it]
  5%|▍         | 178/3566 [07:11<2:12:50,  2.35s/it]
                                                    
{'loss': 1.6784, 'learning_rate': 0.00039950036721528797, 'epoch': 0.05}

  5%|▍         | 178/3566 [07:11<2:12:50,  2.35s/it]
  5%|▌         | 179/3566 [07:14<2:13:19,  2.36s/it]
                                                    
{'loss': 1.8141, 'learning_rate': 0.00039948747950531536, 'epoch': 0.05}

  5%|▌         | 179/3566 [07:14<2:13:19,  2.36s/it]
  5%|▌         | 180/3566 [07:16<2:13:18,  2.36s/it]
                                                    
{'loss': 1.7042, 'learning_rate': 0.0003994744279031589, 'epoch': 0.05}

  5%|▌         | 180/3566 [07:16<2:13:18,  2.36s/it]
  5%|▌         | 181/3566 [07:19<2:18:55,  2.46s/it]
                                                    
{'loss': 1.6995, 'learning_rate': 0.0003994612124195414, 'epoch': 0.05}

  5%|▌         | 181/3566 [07:19<2:18:55,  2.46s/it]
  5%|▌         | 182/3566 [07:21<2:15:59,  2.41s/it]
                                                    
{'loss': 1.7261, 'learning_rate': 0.0003994478330653203, 'epoch': 0.05}

  5%|▌         | 182/3566 [07:21<2:15:59,  2.41s/it]
  5%|▌         | 183/3566 [07:23<2:16:43,  2.42s/it]
                                                    
{'loss': 1.58, 'learning_rate': 0.00039943428985148764, 'epoch': 0.05}

  5%|▌         | 183/3566 [07:23<2:16:43,  2.42s/it]
  5%|▌         | 184/3566 [07:26<2:15:33,  2.41s/it]
                                                    
{'loss': 1.7264, 'learning_rate': 0.00039942058278917, 'epoch': 0.05}

  5%|▌         | 184/3566 [07:26<2:15:33,  2.41s/it]
  5%|▌         | 185/3566 [07:28<2:15:47,  2.41s/it]
                                                    
{'loss': 1.8242, 'learning_rate': 0.00039940671188962867, 'epoch': 0.05}

  5%|▌         | 185/3566 [07:28<2:15:47,  2.41s/it]
  5%|▌         | 186/3566 [07:31<2:16:39,  2.43s/it]
                                                    
{'loss': 1.6811, 'learning_rate': 0.0003993926771642595, 'epoch': 0.05}

  5%|▌         | 186/3566 [07:31<2:16:39,  2.43s/it]
  5%|▌         | 187/3566 [07:33<2:13:16,  2.37s/it]
                                                    
{'loss': 1.6755, 'learning_rate': 0.00039937847862459296, 'epoch': 0.05}

  5%|▌         | 187/3566 [07:33<2:13:16,  2.37s/it]
  5%|▌         | 188/3566 [07:35<2:13:00,  2.36s/it]
                                                    
{'loss': 1.6586, 'learning_rate': 0.0003993641162822941, 'epoch': 0.05}

  5%|▌         | 188/3566 [07:35<2:13:00,  2.36s/it]
  5%|▌         | 189/3566 [07:37<2:10:36,  2.32s/it]
                                                    
{'loss': 1.6002, 'learning_rate': 0.00039934959014916246, 'epoch': 0.05}

  5%|▌         | 189/3566 [07:37<2:10:36,  2.32s/it]
  5%|▌         | 190/3566 [07:40<2:15:15,  2.40s/it]
                                                    
{'loss': 1.6485, 'learning_rate': 0.0003993349002371324, 'epoch': 0.05}

  5%|▌         | 190/3566 [07:40<2:15:15,  2.40s/it]
  5%|▌         | 191/3566 [07:42<2:14:36,  2.39s/it]
                                                    
{'loss': 1.7832, 'learning_rate': 0.0003993200465582725, 'epoch': 0.05}

  5%|▌         | 191/3566 [07:42<2:14:36,  2.39s/it]
  5%|▌         | 192/3566 [07:45<2:12:30,  2.36s/it]
                                                    
{'loss': 1.6417, 'learning_rate': 0.0003993050291247861, 'epoch': 0.05}

  5%|▌         | 192/3566 [07:45<2:12:30,  2.36s/it]
  5%|▌         | 193/3566 [07:47<2:14:28,  2.39s/it]
                                                    
{'loss': 1.6637, 'learning_rate': 0.00039928984794901097, 'epoch': 0.05}

  5%|▌         | 193/3566 [07:47<2:14:28,  2.39s/it]
  5%|▌         | 194/3566 [07:49<2:09:39,  2.31s/it]
                                                    
{'loss': 1.6483, 'learning_rate': 0.00039927450304341945, 'epoch': 0.05}

  5%|▌         | 194/3566 [07:49<2:09:39,  2.31s/it]
  5%|▌         | 195/3566 [07:51<2:08:02,  2.28s/it]
                                                    
{'loss': 1.7407, 'learning_rate': 0.0003992589944206185, 'epoch': 0.05}

  5%|▌         | 195/3566 [07:51<2:08:02,  2.28s/it]
  5%|▌         | 196/3566 [07:54<2:11:22,  2.34s/it]
                                                    
{'loss': 1.663, 'learning_rate': 0.00039924332209334936, 'epoch': 0.05}

  5%|▌         | 196/3566 [07:54<2:11:22,  2.34s/it]
  6%|▌         | 197/3566 [07:56<2:12:18,  2.36s/it]
                                                    
{'loss': 1.747, 'learning_rate': 0.00039922748607448794, 'epoch': 0.06}

  6%|▌         | 197/3566 [07:56<2:12:18,  2.36s/it]
  6%|▌         | 198/3566 [07:59<2:13:29,  2.38s/it]
                                                    
{'loss': 1.7124, 'learning_rate': 0.0003992114863770446, 'epoch': 0.06}

  6%|▌         | 198/3566 [07:59<2:13:29,  2.38s/it]
  6%|▌         | 199/3566 [08:01<2:10:34,  2.33s/it]
                                                    
{'loss': 1.7536, 'learning_rate': 0.0003991953230141641, 'epoch': 0.06}

  6%|▌         | 199/3566 [08:01<2:10:34,  2.33s/it]
  6%|▌         | 200/3566 [08:03<2:13:17,  2.38s/it]
                                                    
{'loss': 1.6898, 'learning_rate': 0.0003991789959991258, 'epoch': 0.06}

  6%|▌         | 200/3566 [08:03<2:13:17,  2.38s/it]
  6%|▌         | 201/3566 [08:06<2:21:15,  2.52s/it]
                                                    
{'loss': 1.7433, 'learning_rate': 0.0003991625053453433, 'epoch': 0.06}

  6%|▌         | 201/3566 [08:06<2:21:15,  2.52s/it]
  6%|▌         | 202/3566 [08:09<2:20:30,  2.51s/it]
                                                    
{'loss': 1.7718, 'learning_rate': 0.00039914585106636484, 'epoch': 0.06}

  6%|▌         | 202/3566 [08:09<2:20:30,  2.51s/it]
  6%|▌         | 203/3566 [08:11<2:16:20,  2.43s/it]
                                                    
{'loss': 1.6753, 'learning_rate': 0.00039912903317587304, 'epoch': 0.06}

  6%|▌         | 203/3566 [08:11<2:16:20,  2.43s/it]
  6%|▌         | 204/3566 [08:13<2:14:42,  2.40s/it]
                                                    
{'loss': 1.8652, 'learning_rate': 0.00039911205168768486, 'epoch': 0.06}

  6%|▌         | 204/3566 [08:13<2:14:42,  2.40s/it]
  6%|▌         | 205/3566 [08:16<2:13:47,  2.39s/it]
                                                    
{'loss': 1.6869, 'learning_rate': 0.0003990949066157518, 'epoch': 0.06}

  6%|▌         | 205/3566 [08:16<2:13:47,  2.39s/it]
  6%|▌         | 206/3566 [08:18<2:12:10,  2.36s/it]
                                                    
{'loss': 1.7137, 'learning_rate': 0.00039907759797415946, 'epoch': 0.06}

  6%|▌         | 206/3566 [08:18<2:12:10,  2.36s/it]
  6%|▌         | 207/3566 [08:20<2:11:53,  2.36s/it]
                                                    
{'loss': 1.6232, 'learning_rate': 0.00039906012577712826, 'epoch': 0.06}

  6%|▌         | 207/3566 [08:20<2:11:53,  2.36s/it]
  6%|▌         | 208/3566 [08:24<2:25:44,  2.60s/it]
                                                    
{'loss': 1.6791, 'learning_rate': 0.0003990424900390127, 'epoch': 0.06}

  6%|▌         | 208/3566 [08:24<2:25:44,  2.60s/it]
  6%|▌         | 209/3566 [08:26<2:22:18,  2.54s/it]
                                                    
{'loss': 1.7531, 'learning_rate': 0.0003990246907743017, 'epoch': 0.06}

  6%|▌         | 209/3566 [08:26<2:22:18,  2.54s/it]
  6%|▌         | 210/3566 [08:28<2:20:13,  2.51s/it]
                                                    
{'loss': 1.7844, 'learning_rate': 0.0003990067279976185, 'epoch': 0.06}

  6%|▌         | 210/3566 [08:28<2:20:13,  2.51s/it]
  6%|▌         | 211/3566 [08:31<2:23:12,  2.56s/it]
                                                    
{'loss': 1.6868, 'learning_rate': 0.0003989886017237208, 'epoch': 0.06}

  6%|▌         | 211/3566 [08:31<2:23:12,  2.56s/it]
  6%|▌         | 212/3566 [08:34<2:24:10,  2.58s/it]
                                                    
{'loss': 1.678, 'learning_rate': 0.0003989703119675004, 'epoch': 0.06}

  6%|▌         | 212/3566 [08:34<2:24:10,  2.58s/it]
  6%|▌         | 213/3566 [08:36<2:17:33,  2.46s/it]
                                                    
{'loss': 1.6909, 'learning_rate': 0.0003989518587439837, 'epoch': 0.06}

  6%|▌         | 213/3566 [08:36<2:17:33,  2.46s/it]
  6%|▌         | 214/3566 [08:38<2:15:46,  2.43s/it]
                                                    
{'loss': 1.6467, 'learning_rate': 0.0003989332420683311, 'epoch': 0.06}

  6%|▌         | 214/3566 [08:38<2:15:46,  2.43s/it]
  6%|▌         | 215/3566 [08:41<2:15:30,  2.43s/it]
                                                    
{'loss': 1.6644, 'learning_rate': 0.00039891446195583757, 'epoch': 0.06}

  6%|▌         | 215/3566 [08:41<2:15:30,  2.43s/it]
  6%|▌         | 216/3566 [08:43<2:13:32,  2.39s/it]
                                                    
{'loss': 1.6828, 'learning_rate': 0.0003988955184219321, 'epoch': 0.06}

  6%|▌         | 216/3566 [08:43<2:13:32,  2.39s/it]
  6%|▌         | 217/3566 [08:45<2:14:00,  2.40s/it]
                                                    
{'loss': 1.5632, 'learning_rate': 0.00039887641148217813, 'epoch': 0.06}

  6%|▌         | 217/3566 [08:45<2:14:00,  2.40s/it]
  6%|▌         | 218/3566 [08:48<2:20:23,  2.52s/it]
                                                    
{'loss': 1.6232, 'learning_rate': 0.00039885714115227327, 'epoch': 0.06}

  6%|▌         | 218/3566 [08:48<2:20:23,  2.52s/it]
  6%|▌         | 219/3566 [08:50<2:16:32,  2.45s/it]
                                                    
{'loss': 1.5412, 'learning_rate': 0.0003988377074480494, 'epoch': 0.06}

  6%|▌         | 219/3566 [08:50<2:16:32,  2.45s/it]
  6%|▌         | 220/3566 [08:53<2:16:26,  2.45s/it]
                                                    
{'loss': 1.8423, 'learning_rate': 0.0003988181103854725, 'epoch': 0.06}

  6%|▌         | 220/3566 [08:53<2:16:26,  2.45s/it]
  6%|▌         | 221/3566 [08:55<2:11:42,  2.36s/it]
                                                    
{'loss': 1.6867, 'learning_rate': 0.0003987983499806429, 'epoch': 0.06}

  6%|▌         | 221/3566 [08:55<2:11:42,  2.36s/it]
  6%|▌         | 222/3566 [08:58<2:14:29,  2.41s/it]
                                                    
{'loss': 1.6369, 'learning_rate': 0.0003987784262497951, 'epoch': 0.06}

  6%|▌         | 222/3566 [08:58<2:14:29,  2.41s/it]
  6%|▋         | 223/3566 [09:00<2:11:43,  2.36s/it]
                                                    
{'loss': 1.5102, 'learning_rate': 0.00039875833920929784, 'epoch': 0.06}

  6%|▋         | 223/3566 [09:00<2:11:43,  2.36s/it]
  6%|▋         | 224/3566 [09:02<2:11:59,  2.37s/it]
                                                    
{'loss': 1.7809, 'learning_rate': 0.0003987380888756538, 'epoch': 0.06}

  6%|▋         | 224/3566 [09:02<2:11:59,  2.37s/it]
  6%|▋         | 225/3566 [09:05<2:14:58,  2.42s/it]
                                                    
{'loss': 1.7746, 'learning_rate': 0.0003987176752655001, 'epoch': 0.06}

  6%|▋         | 225/3566 [09:05<2:14:58,  2.42s/it]
  6%|▋         | 226/3566 [09:07<2:15:45,  2.44s/it]
                                                    
{'loss': 1.679, 'learning_rate': 0.00039869709839560774, 'epoch': 0.06}

  6%|▋         | 226/3566 [09:07<2:15:45,  2.44s/it]
  6%|▋         | 227/3566 [09:09<2:10:53,  2.35s/it]
                                                    
{'loss': 1.6352, 'learning_rate': 0.0003986763582828821, 'epoch': 0.06}

  6%|▋         | 227/3566 [09:09<2:10:53,  2.35s/it]
  6%|▋         | 228/3566 [09:12<2:08:35,  2.31s/it]
                                                    
{'loss': 1.6803, 'learning_rate': 0.0003986554549443625, 'epoch': 0.06}

  6%|▋         | 228/3566 [09:12<2:08:35,  2.31s/it]
  6%|▋         | 229/3566 [09:15<2:18:58,  2.50s/it]
                                                    
{'loss': 1.5693, 'learning_rate': 0.0003986343883972224, 'epoch': 0.06}

  6%|▋         | 229/3566 [09:15<2:18:58,  2.50s/it]
  6%|▋         | 230/3566 [09:17<2:14:04,  2.41s/it]
                                                    
{'loss': 1.6777, 'learning_rate': 0.00039861315865876947, 'epoch': 0.06}

  6%|▋         | 230/3566 [09:17<2:14:04,  2.41s/it]
  6%|▋         | 231/3566 [09:19<2:19:06,  2.50s/it]
                                                    
{'loss': 1.6464, 'learning_rate': 0.00039859176574644526, 'epoch': 0.06}

  6%|▋         | 231/3566 [09:19<2:19:06,  2.50s/it]
  7%|▋         | 232/3566 [09:22<2:19:09,  2.50s/it]
                                                    
{'loss': 1.4862, 'learning_rate': 0.0003985702096778255, 'epoch': 0.07}

  7%|▋         | 232/3566 [09:22<2:19:09,  2.50s/it]
  7%|▋         | 233/3566 [09:24<2:13:33,  2.40s/it]
                                                    
{'loss': 1.7875, 'learning_rate': 0.0003985484904706199, 'epoch': 0.07}

  7%|▋         | 233/3566 [09:24<2:13:33,  2.40s/it]
  7%|▋         | 234/3566 [09:27<2:13:00,  2.40s/it]
                                                    
{'loss': 1.7406, 'learning_rate': 0.00039852660814267225, 'epoch': 0.07}

  7%|▋         | 234/3566 [09:27<2:13:00,  2.40s/it]
  7%|▋         | 235/3566 [09:29<2:11:18,  2.37s/it]
                                                    
{'loss': 1.6427, 'learning_rate': 0.00039850456271196024, 'epoch': 0.07}

  7%|▋         | 235/3566 [09:29<2:11:18,  2.37s/it]
  7%|▋         | 236/3566 [09:31<2:07:38,  2.30s/it]
                                                    
{'loss': 1.6792, 'learning_rate': 0.0003984823541965958, 'epoch': 0.07}

  7%|▋         | 236/3566 [09:31<2:07:38,  2.30s/it]
  7%|▋         | 237/3566 [09:33<2:08:23,  2.31s/it]
                                                    
{'loss': 1.6694, 'learning_rate': 0.0003984599826148246, 'epoch': 0.07}

  7%|▋         | 237/3566 [09:33<2:08:23,  2.31s/it]
  7%|▋         | 238/3566 [09:36<2:10:49,  2.36s/it]
                                                    
{'loss': 1.6611, 'learning_rate': 0.00039843744798502643, 'epoch': 0.07}

  7%|▋         | 238/3566 [09:36<2:10:49,  2.36s/it]
  7%|▋         | 239/3566 [09:38<2:09:23,  2.33s/it]
                                                    
{'loss': 1.779, 'learning_rate': 0.000398414750325715, 'epoch': 0.07}

  7%|▋         | 239/3566 [09:38<2:09:23,  2.33s/it]
  7%|▋         | 240/3566 [09:40<2:07:35,  2.30s/it]
                                                    
{'loss': 1.7927, 'learning_rate': 0.0003983918896555379, 'epoch': 0.07}

  7%|▋         | 240/3566 [09:40<2:07:35,  2.30s/it]
  7%|▋         | 241/3566 [09:43<2:08:39,  2.32s/it]
                                                    
{'loss': 1.5586, 'learning_rate': 0.0003983688659932766, 'epoch': 0.07}

  7%|▋         | 241/3566 [09:43<2:08:39,  2.32s/it]
  7%|▋         | 242/3566 [09:45<2:08:25,  2.32s/it]
                                                    
{'loss': 1.7038, 'learning_rate': 0.00039834567935784676, 'epoch': 0.07}

  7%|▋         | 242/3566 [09:45<2:08:25,  2.32s/it]
  7%|▋         | 243/3566 [09:47<2:08:45,  2.32s/it]
                                                    
{'loss': 1.5733, 'learning_rate': 0.0003983223297682975, 'epoch': 0.07}

  7%|▋         | 243/3566 [09:47<2:08:45,  2.32s/it]
  7%|▋         | 244/3566 [09:50<2:07:45,  2.31s/it]
                                                    
{'loss': 1.5646, 'learning_rate': 0.00039829881724381223, 'epoch': 0.07}

  7%|▋         | 244/3566 [09:50<2:07:45,  2.31s/it]
  7%|▋         | 245/3566 [09:52<2:10:03,  2.35s/it]
                                                    
{'loss': 1.639, 'learning_rate': 0.000398275141803708, 'epoch': 0.07}

  7%|▋         | 245/3566 [09:52<2:10:03,  2.35s/it]
  7%|▋         | 246/3566 [09:54<2:10:49,  2.36s/it]
                                                    
{'loss': 1.6839, 'learning_rate': 0.0003982513034674358, 'epoch': 0.07}

  7%|▋         | 246/3566 [09:54<2:10:49,  2.36s/it]
  7%|▋         | 247/3566 [09:57<2:11:46,  2.38s/it]
                                                    
{'loss': 1.606, 'learning_rate': 0.0003982273022545803, 'epoch': 0.07}

  7%|▋         | 247/3566 [09:57<2:11:46,  2.38s/it]
  7%|▋         | 248/3566 [09:59<2:07:09,  2.30s/it]
                                                    
{'loss': 1.6646, 'learning_rate': 0.00039820313818486017, 'epoch': 0.07}

  7%|▋         | 248/3566 [09:59<2:07:09,  2.30s/it]
  7%|▋         | 249/3566 [10:01<2:11:01,  2.37s/it]
                                                    
{'loss': 1.6461, 'learning_rate': 0.0003981788112781278, 'epoch': 0.07}

  7%|▋         | 249/3566 [10:01<2:11:01,  2.37s/it]
  7%|▋         | 250/3566 [10:04<2:11:46,  2.38s/it]
                                                    
{'loss': 1.734, 'learning_rate': 0.0003981543215543693, 'epoch': 0.07}

  7%|▋         | 250/3566 [10:04<2:11:46,  2.38s/it]
  7%|▋         | 251/3566 [10:07<2:18:21,  2.50s/it]
                                                    
{'loss': 1.6804, 'learning_rate': 0.00039812966903370457, 'epoch': 0.07}

  7%|▋         | 251/3566 [10:07<2:18:21,  2.50s/it]
  7%|▋         | 252/3566 [10:09<2:13:33,  2.42s/it]
                                                    
{'loss': 1.5808, 'learning_rate': 0.0003981048537363874, 'epoch': 0.07}

  7%|▋         | 252/3566 [10:09<2:13:33,  2.42s/it]
  7%|▋         | 253/3566 [10:11<2:12:20,  2.40s/it]
                                                    
{'loss': 1.5425, 'learning_rate': 0.0003980798756828051, 'epoch': 0.07}

  7%|▋         | 253/3566 [10:11<2:12:20,  2.40s/it]
  7%|▋         | 254/3566 [10:14<2:15:07,  2.45s/it]
                                                    
{'loss': 1.6667, 'learning_rate': 0.0003980547348934789, 'epoch': 0.07}

  7%|▋         | 254/3566 [10:14<2:15:07,  2.45s/it]
  7%|▋         | 255/3566 [10:16<2:14:46,  2.44s/it]
                                                    
{'loss': 1.7531, 'learning_rate': 0.0003980294313890635, 'epoch': 0.07}

  7%|▋         | 255/3566 [10:16<2:14:46,  2.44s/it]
  7%|▋         | 256/3566 [10:19<2:15:58,  2.46s/it]
                                                    
{'loss': 1.7476, 'learning_rate': 0.00039800396519034753, 'epoch': 0.07}

  7%|▋         | 256/3566 [10:19<2:15:58,  2.46s/it]
  7%|▋         | 257/3566 [10:21<2:13:29,  2.42s/it]
                                                    
{'loss': 1.7341, 'learning_rate': 0.0003979783363182531, 'epoch': 0.07}

  7%|▋         | 257/3566 [10:21<2:13:29,  2.42s/it]
  7%|▋         | 258/3566 [10:23<2:09:17,  2.35s/it]
                                                    
{'loss': 1.7615, 'learning_rate': 0.000397952544793836, 'epoch': 0.07}

  7%|▋         | 258/3566 [10:23<2:09:17,  2.35s/it]
  7%|▋         | 259/3566 [10:26<2:12:38,  2.41s/it]
                                                    
{'loss': 1.6179, 'learning_rate': 0.0003979265906382857, 'epoch': 0.07}

  7%|▋         | 259/3566 [10:26<2:12:38,  2.41s/it]
  7%|▋         | 260/3566 [10:28<2:08:18,  2.33s/it]
                                                    
{'loss': 1.6777, 'learning_rate': 0.0003979004738729253, 'epoch': 0.07}

  7%|▋         | 260/3566 [10:28<2:08:18,  2.33s/it]
  7%|▋         | 261/3566 [10:30<2:07:21,  2.31s/it]
                                                    
{'loss': 1.5358, 'learning_rate': 0.00039787419451921133, 'epoch': 0.07}

  7%|▋         | 261/3566 [10:30<2:07:21,  2.31s/it]
  7%|▋         | 262/3566 [10:33<2:14:23,  2.44s/it]
                                                    
{'loss': 1.6684, 'learning_rate': 0.00039784775259873415, 'epoch': 0.07}

  7%|▋         | 262/3566 [10:33<2:14:23,  2.44s/it]
  7%|▋         | 263/3566 [10:35<2:12:07,  2.40s/it]
                                                    
{'loss': 1.8019, 'learning_rate': 0.0003978211481332175, 'epoch': 0.07}

  7%|▋         | 263/3566 [10:35<2:12:07,  2.40s/it]
  7%|▋         | 264/3566 [10:38<2:09:59,  2.36s/it]
                                                    
{'loss': 1.6875, 'learning_rate': 0.00039779438114451876, 'epoch': 0.07}

  7%|▋         | 264/3566 [10:38<2:09:59,  2.36s/it]
  7%|▋         | 265/3566 [10:40<2:11:58,  2.40s/it]
                                                    
{'loss': 1.7118, 'learning_rate': 0.0003977674516546287, 'epoch': 0.07}

  7%|▋         | 265/3566 [10:40<2:11:58,  2.40s/it]
  7%|▋         | 266/3566 [10:42<2:11:59,  2.40s/it]
                                                    
{'loss': 1.5797, 'learning_rate': 0.00039774035968567176, 'epoch': 0.07}

  7%|▋         | 266/3566 [10:42<2:11:59,  2.40s/it]
  7%|▋         | 267/3566 [10:45<2:11:06,  2.38s/it]
                                                    
{'loss': 1.6126, 'learning_rate': 0.0003977131052599058, 'epoch': 0.07}

  7%|▋         | 267/3566 [10:45<2:11:06,  2.38s/it]
  8%|▊         | 268/3566 [10:47<2:10:45,  2.38s/it]
                                                    
{'loss': 1.6258, 'learning_rate': 0.00039768568839972194, 'epoch': 0.08}

  8%|▊         | 268/3566 [10:47<2:10:45,  2.38s/it]
  8%|▊         | 269/3566 [10:50<2:11:14,  2.39s/it]
                                                    
{'loss': 1.4715, 'learning_rate': 0.0003976581091276452, 'epoch': 0.08}

  8%|▊         | 269/3566 [10:50<2:11:14,  2.39s/it]
  8%|▊         | 270/3566 [10:52<2:11:49,  2.40s/it]
                                                    
{'loss': 1.5902, 'learning_rate': 0.0003976303674663337, 'epoch': 0.08}

  8%|▊         | 270/3566 [10:52<2:11:49,  2.40s/it]
  8%|▊         | 271/3566 [10:54<2:08:57,  2.35s/it]
                                                    
{'loss': 1.595, 'learning_rate': 0.0003976024634385789, 'epoch': 0.08}

  8%|▊         | 271/3566 [10:54<2:08:57,  2.35s/it]
  8%|▊         | 272/3566 [10:57<2:14:06,  2.44s/it]
                                                    
{'loss': 1.7204, 'learning_rate': 0.000397574397067306, 'epoch': 0.08}

  8%|▊         | 272/3566 [10:57<2:14:06,  2.44s/it]
  8%|▊         | 273/3566 [10:59<2:10:41,  2.38s/it]
                                                    
{'loss': 1.7199, 'learning_rate': 0.00039754616837557334, 'epoch': 0.08}

  8%|▊         | 273/3566 [10:59<2:10:41,  2.38s/it]
  8%|▊         | 274/3566 [11:01<2:10:43,  2.38s/it]
                                                    
{'loss': 1.6953, 'learning_rate': 0.00039751777738657266, 'epoch': 0.08}

  8%|▊         | 274/3566 [11:02<2:10:43,  2.38s/it]
  8%|▊         | 275/3566 [11:04<2:12:16,  2.41s/it]
                                                    
{'loss': 1.7156, 'learning_rate': 0.00039748922412362895, 'epoch': 0.08}

  8%|▊         | 275/3566 [11:04<2:12:16,  2.41s/it]
  8%|▊         | 276/3566 [11:06<2:13:21,  2.43s/it]
                                                    
{'loss': 1.5859, 'learning_rate': 0.0003974605086102007, 'epoch': 0.08}

  8%|▊         | 276/3566 [11:06<2:13:21,  2.43s/it]
  8%|▊         | 277/3566 [11:09<2:11:00,  2.39s/it]
                                                    
{'loss': 1.7613, 'learning_rate': 0.0003974316308698796, 'epoch': 0.08}

  8%|▊         | 277/3566 [11:09<2:11:00,  2.39s/it]
  8%|▊         | 278/3566 [11:11<2:08:37,  2.35s/it]
                                                    
{'loss': 1.6515, 'learning_rate': 0.00039740259092639065, 'epoch': 0.08}

  8%|▊         | 278/3566 [11:11<2:08:37,  2.35s/it]
  8%|▊         | 279/3566 [11:14<2:15:26,  2.47s/it]
                                                    
{'loss': 1.6348, 'learning_rate': 0.000397373388803592, 'epoch': 0.08}

  8%|▊         | 279/3566 [11:14<2:15:26,  2.47s/it]
  8%|▊         | 280/3566 [11:16<2:12:24,  2.42s/it]
                                                    
{'loss': 1.4916, 'learning_rate': 0.0003973440245254752, 'epoch': 0.08}

  8%|▊         | 280/3566 [11:16<2:12:24,  2.42s/it]
  8%|▊         | 281/3566 [11:18<2:10:17,  2.38s/it]
                                                    
{'loss': 1.5288, 'learning_rate': 0.0003973144981161649, 'epoch': 0.08}

  8%|▊         | 281/3566 [11:18<2:10:17,  2.38s/it]
  8%|▊         | 282/3566 [11:21<2:10:19,  2.38s/it]
                                                    
{'loss': 1.7296, 'learning_rate': 0.00039728480959991903, 'epoch': 0.08}

  8%|▊         | 282/3566 [11:21<2:10:19,  2.38s/it]
  8%|▊         | 283/3566 [11:23<2:09:06,  2.36s/it]
                                                    
{'loss': 1.6089, 'learning_rate': 0.0003972549590011287, 'epoch': 0.08}

  8%|▊         | 283/3566 [11:23<2:09:06,  2.36s/it]
  8%|▊         | 284/3566 [11:25<2:10:42,  2.39s/it]
                                                    
{'loss': 1.8133, 'learning_rate': 0.0003972249463443181, 'epoch': 0.08}

  8%|▊         | 284/3566 [11:25<2:10:42,  2.39s/it]
  8%|▊         | 285/3566 [11:28<2:08:19,  2.35s/it]
                                                    
{'loss': 1.6188, 'learning_rate': 0.0003971947716541447, 'epoch': 0.08}

  8%|▊         | 285/3566 [11:28<2:08:19,  2.35s/it]
  8%|▊         | 286/3566 [11:30<2:09:55,  2.38s/it]
                                                    
{'loss': 1.6767, 'learning_rate': 0.0003971644349553989, 'epoch': 0.08}

  8%|▊         | 286/3566 [11:30<2:09:55,  2.38s/it]
  8%|▊         | 287/3566 [11:33<2:09:01,  2.36s/it]
                                                    
{'loss': 1.5592, 'learning_rate': 0.0003971339362730044, 'epoch': 0.08}

  8%|▊         | 287/3566 [11:33<2:09:01,  2.36s/it]
  8%|▊         | 288/3566 [11:35<2:18:32,  2.54s/it]
                                                    
{'loss': 1.7247, 'learning_rate': 0.00039710327563201786, 'epoch': 0.08}

  8%|▊         | 288/3566 [11:35<2:18:32,  2.54s/it]
  8%|▊         | 289/3566 [11:38<2:14:02,  2.45s/it]
                                                    
{'loss': 1.5534, 'learning_rate': 0.00039707245305762895, 'epoch': 0.08}

  8%|▊         | 289/3566 [11:38<2:14:02,  2.45s/it]
  8%|▊         | 290/3566 [11:40<2:09:08,  2.37s/it]
                                                    
{'loss': 1.5649, 'learning_rate': 0.0003970414685751606, 'epoch': 0.08}

  8%|▊         | 290/3566 [11:40<2:09:08,  2.37s/it]
  8%|▊         | 291/3566 [11:42<2:08:52,  2.36s/it]
                                                    
{'loss': 1.6316, 'learning_rate': 0.00039701032221006846, 'epoch': 0.08}

  8%|▊         | 291/3566 [11:42<2:08:52,  2.36s/it]
  8%|▊         | 292/3566 [11:44<2:06:20,  2.32s/it]
                                                    
{'loss': 1.6102, 'learning_rate': 0.00039697901398794144, 'epoch': 0.08}

  8%|▊         | 292/3566 [11:44<2:06:20,  2.32s/it]
  8%|▊         | 293/3566 [11:47<2:04:06,  2.28s/it]
                                                    
{'loss': 1.6398, 'learning_rate': 0.00039694754393450137, 'epoch': 0.08}

  8%|▊         | 293/3566 [11:47<2:04:06,  2.28s/it]
  8%|▊         | 294/3566 [11:49<2:06:16,  2.32s/it]
                                                    
{'loss': 1.6802, 'learning_rate': 0.0003969159120756028, 'epoch': 0.08}

  8%|▊         | 294/3566 [11:49<2:06:16,  2.32s/it]
  8%|▊         | 295/3566 [11:51<2:03:35,  2.27s/it]
                                                    
{'loss': 1.7493, 'learning_rate': 0.00039688411843723356, 'epoch': 0.08}

  8%|▊         | 295/3566 [11:51<2:03:35,  2.27s/it]
  8%|▊         | 296/3566 [11:53<2:03:33,  2.27s/it]
                                                    
{'loss': 1.7303, 'learning_rate': 0.00039685216304551416, 'epoch': 0.08}

  8%|▊         | 296/3566 [11:53<2:03:33,  2.27s/it]
  8%|▊         | 297/3566 [11:56<2:03:04,  2.26s/it]
                                                    
{'loss': 1.7573, 'learning_rate': 0.00039682004592669814, 'epoch': 0.08}

  8%|▊         | 297/3566 [11:56<2:03:04,  2.26s/it]
  8%|▊         | 298/3566 [11:58<2:09:20,  2.37s/it]
                                                    
{'loss': 1.7138, 'learning_rate': 0.00039678776710717174, 'epoch': 0.08}

  8%|▊         | 298/3566 [11:58<2:09:20,  2.37s/it]
  8%|▊         | 299/3566 [12:01<2:06:24,  2.32s/it]
                                                    
{'loss': 1.6963, 'learning_rate': 0.00039675532661345416, 'epoch': 0.08}

  8%|▊         | 299/3566 [12:01<2:06:24,  2.32s/it]
  8%|▊         | 300/3566 [12:03<2:12:27,  2.43s/it]
                                                    
{'loss': 1.5269, 'learning_rate': 0.0003967227244721976, 'epoch': 0.08}

  8%|▊         | 300/3566 [12:03<2:12:27,  2.43s/it]
  8%|▊         | 301/3566 [12:05<2:07:49,  2.35s/it]
                                                    
{'loss': 1.5682, 'learning_rate': 0.00039668996071018657, 'epoch': 0.08}

  8%|▊         | 301/3566 [12:05<2:07:49,  2.35s/it]
  8%|▊         | 302/3566 [12:08<2:05:52,  2.31s/it]
                                                    
{'loss': 1.668, 'learning_rate': 0.00039665703535433894, 'epoch': 0.08}

  8%|▊         | 302/3566 [12:08<2:05:52,  2.31s/it]
  8%|▊         | 303/3566 [12:10<2:05:29,  2.31s/it]
                                                    
{'loss': 1.7288, 'learning_rate': 0.0003966239484317049, 'epoch': 0.08}

  8%|▊         | 303/3566 [12:10<2:05:29,  2.31s/it]
  9%|▊         | 304/3566 [12:12<2:05:55,  2.32s/it]
                                                    
{'loss': 1.6777, 'learning_rate': 0.0003965906999694677, 'epoch': 0.09}

  9%|▊         | 304/3566 [12:12<2:05:55,  2.32s/it]
  9%|▊         | 305/3566 [12:15<2:08:21,  2.36s/it]
                                                    
{'loss': 1.614, 'learning_rate': 0.00039655728999494295, 'epoch': 0.09}

  9%|▊         | 305/3566 [12:15<2:08:21,  2.36s/it]
  9%|▊         | 306/3566 [12:17<2:07:33,  2.35s/it]
                                                    
{'loss': 1.7444, 'learning_rate': 0.00039652371853557937, 'epoch': 0.09}

  9%|▊         | 306/3566 [12:17<2:07:33,  2.35s/it]
  9%|▊         | 307/3566 [12:19<2:04:01,  2.28s/it]
                                                    
{'loss': 1.6656, 'learning_rate': 0.000396489985618958, 'epoch': 0.09}

  9%|▊         | 307/3566 [12:19<2:04:01,  2.28s/it]
  9%|▊         | 308/3566 [12:21<2:04:34,  2.29s/it]
                                                    
{'loss': 1.467, 'learning_rate': 0.00039645609127279276, 'epoch': 0.09}

  9%|▊         | 308/3566 [12:21<2:04:34,  2.29s/it]
  9%|▊         | 309/3566 [12:24<2:04:36,  2.30s/it]
                                                    
{'loss': 1.7377, 'learning_rate': 0.00039642203552493006, 'epoch': 0.09}

  9%|▊         | 309/3566 [12:24<2:04:36,  2.30s/it]
  9%|▊         | 310/3566 [12:26<2:11:26,  2.42s/it]
                                                    
{'loss': 1.6204, 'learning_rate': 0.00039638781840334894, 'epoch': 0.09}

  9%|▊         | 310/3566 [12:26<2:11:26,  2.42s/it]
  9%|▊         | 311/3566 [12:29<2:07:31,  2.35s/it]
                                                    
{'loss': 1.5772, 'learning_rate': 0.00039635343993616096, 'epoch': 0.09}

  9%|▊         | 311/3566 [12:29<2:07:31,  2.35s/it]
  9%|▊         | 312/3566 [12:31<2:07:10,  2.35s/it]
                                                    
{'loss': 1.7176, 'learning_rate': 0.0003963189001516105, 'epoch': 0.09}

  9%|▊         | 312/3566 [12:31<2:07:10,  2.35s/it]
  9%|▉         | 313/3566 [12:33<2:02:37,  2.26s/it]
                                                    
{'loss': 1.527, 'learning_rate': 0.0003962841990780741, 'epoch': 0.09}

  9%|▉         | 313/3566 [12:33<2:02:37,  2.26s/it]
  9%|▉         | 314/3566 [12:35<2:00:24,  2.22s/it]
                                                    
{'loss': 1.6117, 'learning_rate': 0.0003962493367440612, 'epoch': 0.09}

  9%|▉         | 314/3566 [12:35<2:00:24,  2.22s/it]
  9%|▉         | 315/3566 [12:38<2:03:55,  2.29s/it]
                                                    
{'loss': 1.716, 'learning_rate': 0.0003962143131782132, 'epoch': 0.09}

  9%|▉         | 315/3566 [12:38<2:03:55,  2.29s/it]
  9%|▉         | 316/3566 [12:40<2:01:33,  2.24s/it]
                                                    
{'loss': 1.648, 'learning_rate': 0.00039617912840930454, 'epoch': 0.09}

  9%|▉         | 316/3566 [12:40<2:01:33,  2.24s/it]
  9%|▉         | 317/3566 [12:42<2:06:27,  2.34s/it]
                                                    
{'loss': 1.6771, 'learning_rate': 0.00039614378246624176, 'epoch': 0.09}

  9%|▉         | 317/3566 [12:42<2:06:27,  2.34s/it]
  9%|▉         | 318/3566 [12:45<2:07:37,  2.36s/it]
                                                    
{'loss': 1.6652, 'learning_rate': 0.00039610827537806394, 'epoch': 0.09}

  9%|▉         | 318/3566 [12:45<2:07:37,  2.36s/it]
  9%|▉         | 319/3566 [12:47<2:06:09,  2.33s/it]
                                                    
{'loss': 1.6864, 'learning_rate': 0.0003960726071739424, 'epoch': 0.09}

  9%|▉         | 319/3566 [12:47<2:06:09,  2.33s/it]
  9%|▉         | 320/3566 [12:49<2:06:58,  2.35s/it]
                                                    
{'loss': 1.6546, 'learning_rate': 0.00039603677788318105, 'epoch': 0.09}

  9%|▉         | 320/3566 [12:49<2:06:58,  2.35s/it]
  9%|▉         | 321/3566 [12:52<2:06:16,  2.33s/it]
                                                    
{'loss': 1.6717, 'learning_rate': 0.0003960007875352159, 'epoch': 0.09}

  9%|▉         | 321/3566 [12:52<2:06:16,  2.33s/it]
  9%|▉         | 322/3566 [12:54<2:06:23,  2.34s/it]
                                                    
{'loss': 1.5745, 'learning_rate': 0.0003959646361596155, 'epoch': 0.09}

  9%|▉         | 322/3566 [12:54<2:06:23,  2.34s/it]
  9%|▉         | 323/3566 [12:56<2:04:25,  2.30s/it]
                                                    
{'loss': 1.5425, 'learning_rate': 0.00039592832378608066, 'epoch': 0.09}

  9%|▉         | 323/3566 [12:56<2:04:25,  2.30s/it]
  9%|▉         | 324/3566 [12:59<2:07:16,  2.36s/it]
                                                    
{'loss': 1.5907, 'learning_rate': 0.00039589185044444425, 'epoch': 0.09}

  9%|▉         | 324/3566 [12:59<2:07:16,  2.36s/it]
  9%|▉         | 325/3566 [13:01<2:04:57,  2.31s/it]
                                                    
{'loss': 1.5331, 'learning_rate': 0.0003958552161646716, 'epoch': 0.09}

  9%|▉         | 325/3566 [13:01<2:04:57,  2.31s/it]
  9%|▉         | 326/3566 [13:04<2:18:19,  2.56s/it]
                                                    
{'loss': 1.5927, 'learning_rate': 0.00039581842097686023, 'epoch': 0.09}

  9%|▉         | 326/3566 [13:04<2:18:19,  2.56s/it]
  9%|▉         | 327/3566 [13:06<2:13:53,  2.48s/it]
                                                    
{'loss': 1.6573, 'learning_rate': 0.00039578146491123977, 'epoch': 0.09}

  9%|▉         | 327/3566 [13:06<2:13:53,  2.48s/it]
  9%|▉         | 328/3566 [13:09<2:10:32,  2.42s/it]
                                                    
{'loss': 1.6798, 'learning_rate': 0.0003957443479981722, 'epoch': 0.09}

  9%|▉         | 328/3566 [13:09<2:10:32,  2.42s/it]
  9%|▉         | 329/3566 [13:11<2:08:32,  2.38s/it]
                                                    
{'loss': 1.7501, 'learning_rate': 0.0003957070702681513, 'epoch': 0.09}

  9%|▉         | 329/3566 [13:11<2:08:32,  2.38s/it]
  9%|▉         | 330/3566 [13:13<2:03:44,  2.29s/it]
                                                    
{'loss': 1.6227, 'learning_rate': 0.0003956696317518034, 'epoch': 0.09}

  9%|▉         | 330/3566 [13:13<2:03:44,  2.29s/it]
  9%|▉         | 331/3566 [13:16<2:06:23,  2.34s/it]
                                                    
{'loss': 1.5463, 'learning_rate': 0.0003956320324798866, 'epoch': 0.09}

  9%|▉         | 331/3566 [13:16<2:06:23,  2.34s/it]
  9%|▉         | 332/3566 [13:18<2:07:52,  2.37s/it]
                                                    
{'loss': 1.7951, 'learning_rate': 0.00039559427248329134, 'epoch': 0.09}

  9%|▉         | 332/3566 [13:18<2:07:52,  2.37s/it]
  9%|▉         | 333/3566 [13:20<2:07:29,  2.37s/it]
                                                    
{'loss': 1.6577, 'learning_rate': 0.00039555635179303977, 'epoch': 0.09}

  9%|▉         | 333/3566 [13:20<2:07:29,  2.37s/it]
  9%|▉         | 334/3566 [13:23<2:04:49,  2.32s/it]
                                                    
{'loss': 1.6136, 'learning_rate': 0.00039551827044028635, 'epoch': 0.09}

  9%|▉         | 334/3566 [13:23<2:04:49,  2.32s/it]
  9%|▉         | 335/3566 [13:25<2:03:55,  2.30s/it]
                                                    
{'loss': 1.584, 'learning_rate': 0.00039548002845631746, 'epoch': 0.09}

  9%|▉         | 335/3566 [13:25<2:03:55,  2.30s/it]
  9%|▉         | 336/3566 [13:28<2:11:01,  2.43s/it]
                                                    
{'loss': 1.559, 'learning_rate': 0.00039544162587255133, 'epoch': 0.09}

  9%|▉         | 336/3566 [13:28<2:11:01,  2.43s/it]
  9%|▉         | 337/3566 [13:30<2:13:56,  2.49s/it]
                                                    
{'loss': 1.5896, 'learning_rate': 0.00039540306272053835, 'epoch': 0.09}

  9%|▉         | 337/3566 [13:30<2:13:56,  2.49s/it]
  9%|▉         | 338/3566 [13:33<2:19:07,  2.59s/it]
                                                    
{'loss': 1.6262, 'learning_rate': 0.00039536433903196065, 'epoch': 0.09}

  9%|▉         | 338/3566 [13:33<2:19:07,  2.59s/it]
 10%|▉         | 339/3566 [13:36<2:21:42,  2.63s/it]
                                                    
{'loss': 1.4847, 'learning_rate': 0.0003953254548386323, 'epoch': 0.1}

 10%|▉         | 339/3566 [13:36<2:21:42,  2.63s/it]
 10%|▉         | 340/3566 [13:38<2:19:32,  2.60s/it]
                                                    
{'loss': 1.6229, 'learning_rate': 0.0003952864101724992, 'epoch': 0.1}

 10%|▉         | 340/3566 [13:38<2:19:32,  2.60s/it]
 10%|▉         | 341/3566 [13:41<2:15:35,  2.52s/it]
                                                    
{'loss': 1.6223, 'learning_rate': 0.00039524720506563916, 'epoch': 0.1}

 10%|▉         | 341/3566 [13:41<2:15:35,  2.52s/it]
 10%|▉         | 342/3566 [13:43<2:11:30,  2.45s/it]
                                                    
{'loss': 1.6402, 'learning_rate': 0.0003952078395502618, 'epoch': 0.1}

 10%|▉         | 342/3566 [13:43<2:11:30,  2.45s/it]
 10%|▉         | 343/3566 [13:45<2:06:40,  2.36s/it]
                                                    
{'loss': 1.6644, 'learning_rate': 0.0003951683136587085, 'epoch': 0.1}

 10%|▉         | 343/3566 [13:45<2:06:40,  2.36s/it]
 10%|▉         | 344/3566 [13:47<2:05:39,  2.34s/it]
                                                    
{'loss': 1.6631, 'learning_rate': 0.0003951286274234524, 'epoch': 0.1}

 10%|▉         | 344/3566 [13:47<2:05:39,  2.34s/it]
 10%|▉         | 345/3566 [13:49<2:03:12,  2.30s/it]
                                                    
{'loss': 1.6568, 'learning_rate': 0.0003950887808770983, 'epoch': 0.1}

 10%|▉         | 345/3566 [13:49<2:03:12,  2.30s/it]
 10%|▉         | 346/3566 [13:52<2:03:27,  2.30s/it]
                                                    
{'loss': 1.6874, 'learning_rate': 0.0003950487740523829, 'epoch': 0.1}

 10%|▉         | 346/3566 [13:52<2:03:27,  2.30s/it]
 10%|▉         | 347/3566 [13:54<2:03:01,  2.29s/it]
                                                    
{'loss': 1.5275, 'learning_rate': 0.0003950086069821743, 'epoch': 0.1}

 10%|▉         | 347/3566 [13:54<2:03:01,  2.29s/it]
 10%|▉         | 348/3566 [13:56<2:01:53,  2.27s/it]
                                                    
{'loss': 1.5334, 'learning_rate': 0.00039496827969947256, 'epoch': 0.1}

 10%|▉         | 348/3566 [13:56<2:01:53,  2.27s/it]
 10%|▉         | 349/3566 [13:58<1:59:16,  2.22s/it]
                                                    
{'loss': 1.7514, 'learning_rate': 0.00039492779223740913, 'epoch': 0.1}

 10%|▉         | 349/3566 [13:58<1:59:16,  2.22s/it]
 10%|▉         | 350/3566 [14:01<2:04:45,  2.33s/it]
                                                    
{'loss': 1.5748, 'learning_rate': 0.00039488714462924723, 'epoch': 0.1}

 10%|▉         | 350/3566 [14:01<2:04:45,  2.33s/it]
 10%|▉         | 351/3566 [14:03<2:03:50,  2.31s/it]
                                                    
{'loss': 1.6717, 'learning_rate': 0.0003948463369083815, 'epoch': 0.1}

 10%|▉         | 351/3566 [14:03<2:03:50,  2.31s/it]
 10%|▉         | 352/3566 [14:06<2:03:11,  2.30s/it]
                                                    
{'loss': 1.6801, 'learning_rate': 0.0003948053691083381, 'epoch': 0.1}

 10%|▉         | 352/3566 [14:06<2:03:11,  2.30s/it]
 10%|▉         | 353/3566 [14:08<2:04:06,  2.32s/it]
                                                    
{'loss': 1.5303, 'learning_rate': 0.0003947642412627749, 'epoch': 0.1}

 10%|▉         | 353/3566 [14:08<2:04:06,  2.32s/it]
 10%|▉         | 354/3566 [14:10<2:08:59,  2.41s/it]
                                                    
{'loss': 1.5768, 'learning_rate': 0.0003947229534054812, 'epoch': 0.1}

 10%|▉         | 354/3566 [14:10<2:08:59,  2.41s/it]
 10%|▉         | 355/3566 [14:13<2:10:18,  2.43s/it]
                                                    
{'loss': 1.6292, 'learning_rate': 0.0003946815055703776, 'epoch': 0.1}

 10%|▉         | 355/3566 [14:13<2:10:18,  2.43s/it]
 10%|▉         | 356/3566 [14:15<2:09:57,  2.43s/it]
                                                    
{'loss': 1.6216, 'learning_rate': 0.00039463989779151633, 'epoch': 0.1}

 10%|▉         | 356/3566 [14:15<2:09:57,  2.43s/it]
 10%|█         | 357/3566 [14:18<2:05:20,  2.34s/it]
                                                    
{'loss': 1.4513, 'learning_rate': 0.00039459813010308083, 'epoch': 0.1}

 10%|█         | 357/3566 [14:18<2:05:20,  2.34s/it]
 10%|█         | 358/3566 [14:20<2:05:11,  2.34s/it]
                                                    
{'loss': 1.6213, 'learning_rate': 0.0003945562025393861, 'epoch': 0.1}

 10%|█         | 358/3566 [14:20<2:05:11,  2.34s/it]
 10%|█         | 359/3566 [14:22<2:05:53,  2.36s/it]
                                                    
{'loss': 1.5435, 'learning_rate': 0.00039451411513487846, 'epoch': 0.1}

 10%|█         | 359/3566 [14:22<2:05:53,  2.36s/it]
 10%|█         | 360/3566 [14:25<2:06:21,  2.36s/it]
                                                    
{'loss': 1.8213, 'learning_rate': 0.0003944718679241354, 'epoch': 0.1}

 10%|█         | 360/3566 [14:25<2:06:21,  2.36s/it]
 10%|█         | 361/3566 [14:27<2:02:48,  2.30s/it]
                                                    
{'loss': 1.6161, 'learning_rate': 0.0003944294609418658, 'epoch': 0.1}

 10%|█         | 361/3566 [14:27<2:02:48,  2.30s/it]
 10%|█         | 362/3566 [14:29<2:01:01,  2.27s/it]
                                                    
{'loss': 1.7734, 'learning_rate': 0.0003943868942229099, 'epoch': 0.1}

 10%|█         | 362/3566 [14:29<2:01:01,  2.27s/it]
 10%|█         | 363/3566 [14:31<1:59:06,  2.23s/it]
                                                    
{'loss': 1.5545, 'learning_rate': 0.00039434416780223904, 'epoch': 0.1}

 10%|█         | 363/3566 [14:31<1:59:06,  2.23s/it]
 10%|█         | 364/3566 [14:34<2:07:40,  2.39s/it]
                                                    
{'loss': 1.6179, 'learning_rate': 0.0003943012817149558, 'epoch': 0.1}

 10%|█         | 364/3566 [14:34<2:07:40,  2.39s/it]
 10%|█         | 365/3566 [14:36<2:05:13,  2.35s/it]
                                                    
{'loss': 1.6104, 'learning_rate': 0.0003942582359962939, 'epoch': 0.1}

 10%|█         | 365/3566 [14:36<2:05:13,  2.35s/it]
 10%|█         | 366/3566 [14:39<2:12:35,  2.49s/it]
                                                    
{'loss': 1.6037, 'learning_rate': 0.00039421503068161833, 'epoch': 0.1}

 10%|█         | 366/3566 [14:39<2:12:35,  2.49s/it]
 10%|█         | 367/3566 [14:42<2:14:23,  2.52s/it]
                                                    
{'loss': 1.6444, 'learning_rate': 0.0003941716658064251, 'epoch': 0.1}

 10%|█         | 367/3566 [14:42<2:14:23,  2.52s/it]
 10%|█         | 368/3566 [14:44<2:11:50,  2.47s/it]
                                                    
{'loss': 1.7601, 'learning_rate': 0.0003941281414063412, 'epoch': 0.1}

 10%|█         | 368/3566 [14:44<2:11:50,  2.47s/it]
 10%|█         | 369/3566 [14:46<2:07:22,  2.39s/it]
                                                    
{'loss': 1.7248, 'learning_rate': 0.000394084457517125, 'epoch': 0.1}

 10%|█         | 369/3566 [14:46<2:07:22,  2.39s/it]
 10%|█         | 370/3566 [14:48<2:07:00,  2.38s/it]
                                                    
{'loss': 1.5837, 'learning_rate': 0.0003940406141746656, 'epoch': 0.1}

 10%|█         | 370/3566 [14:48<2:07:00,  2.38s/it]
 10%|█         | 371/3566 [14:51<2:04:51,  2.34s/it]
                                                    
{'loss': 1.7561, 'learning_rate': 0.0003939966114149833, 'epoch': 0.1}

 10%|█         | 371/3566 [14:51<2:04:51,  2.34s/it]
 10%|█         | 372/3566 [14:53<2:05:32,  2.36s/it]
                                                    
{'loss': 1.7232, 'learning_rate': 0.00039395244927422913, 'epoch': 0.1}

 10%|█         | 372/3566 [14:53<2:05:32,  2.36s/it]
 10%|█         | 373/3566 [14:56<2:15:44,  2.55s/it]
                                                    
{'loss': 1.623, 'learning_rate': 0.00039390812778868534, 'epoch': 0.1}

 10%|█         | 373/3566 [14:56<2:15:44,  2.55s/it]
 10%|█         | 374/3566 [14:58<2:11:34,  2.47s/it]
                                                    
{'loss': 1.5596, 'learning_rate': 0.000393863646994765, 'epoch': 0.1}

 10%|█         | 374/3566 [14:58<2:11:34,  2.47s/it]
 11%|█         | 375/3566 [15:01<2:08:37,  2.42s/it]
                                                    
{'loss': 1.5719, 'learning_rate': 0.00039381900692901184, 'epoch': 0.11}

 11%|█         | 375/3566 [15:01<2:08:37,  2.42s/it]
 11%|█         | 376/3566 [15:03<2:12:27,  2.49s/it]
                                                    
{'loss': 1.5753, 'learning_rate': 0.00039377420762810086, 'epoch': 0.11}

 11%|█         | 376/3566 [15:03<2:12:27,  2.49s/it]
 11%|█         | 377/3566 [15:06<2:11:15,  2.47s/it]
                                                    
{'loss': 1.6194, 'learning_rate': 0.0003937292491288375, 'epoch': 0.11}

 11%|█         | 377/3566 [15:06<2:11:15,  2.47s/it]
 11%|█         | 378/3566 [15:08<2:09:13,  2.43s/it]
                                                    
{'loss': 1.5417, 'learning_rate': 0.0003936841314681582, 'epoch': 0.11}

 11%|█         | 378/3566 [15:08<2:09:13,  2.43s/it]
 11%|█         | 379/3566 [15:11<2:13:36,  2.52s/it]
                                                    
{'loss': 1.6827, 'learning_rate': 0.00039363885468313007, 'epoch': 0.11}

 11%|█         | 379/3566 [15:11<2:13:36,  2.52s/it]
 11%|█         | 380/3566 [15:13<2:09:40,  2.44s/it]
                                                    
{'loss': 1.6674, 'learning_rate': 0.0003935934188109511, 'epoch': 0.11}

 11%|█         | 380/3566 [15:13<2:09:40,  2.44s/it]
 11%|█         | 381/3566 [15:16<2:13:55,  2.52s/it]
                                                    
{'loss': 1.639, 'learning_rate': 0.00039354782388894974, 'epoch': 0.11}

 11%|█         | 381/3566 [15:16<2:13:55,  2.52s/it]
 11%|█         | 382/3566 [15:18<2:09:56,  2.45s/it]
                                                    
{'loss': 1.5754, 'learning_rate': 0.0003935020699545853, 'epoch': 0.11}

 11%|█         | 382/3566 [15:18<2:09:56,  2.45s/it]
 11%|█         | 383/3566 [15:21<2:13:02,  2.51s/it]
                                                    
{'loss': 1.8751, 'learning_rate': 0.00039345615704544765, 'epoch': 0.11}

 11%|█         | 383/3566 [15:21<2:13:02,  2.51s/it]
 11%|█         | 384/3566 [15:23<2:09:15,  2.44s/it]
                                                    
{'loss': 1.5544, 'learning_rate': 0.00039341008519925733, 'epoch': 0.11}

 11%|█         | 384/3566 [15:23<2:09:15,  2.44s/it]
 11%|█         | 385/3566 [15:25<2:08:44,  2.43s/it]
                                                    
{'loss': 1.6666, 'learning_rate': 0.0003933638544538654, 'epoch': 0.11}

 11%|█         | 385/3566 [15:25<2:08:44,  2.43s/it]
 11%|█         | 386/3566 [15:28<2:06:19,  2.38s/it]
                                                    
{'loss': 1.5579, 'learning_rate': 0.0003933174648472534, 'epoch': 0.11}

 11%|█         | 386/3566 [15:28<2:06:19,  2.38s/it]
 11%|█         | 387/3566 [15:31<2:16:10,  2.57s/it]
                                                    
{'loss': 1.4627, 'learning_rate': 0.0003932709164175336, 'epoch': 0.11}

 11%|█         | 387/3566 [15:31<2:16:10,  2.57s/it]
 11%|█         | 388/3566 [15:33<2:18:29,  2.61s/it]
                                                    
{'loss': 1.5594, 'learning_rate': 0.0003932242092029485, 'epoch': 0.11}

 11%|█         | 388/3566 [15:33<2:18:29,  2.61s/it]
 11%|█         | 389/3566 [15:36<2:14:49,  2.55s/it]
                                                    
{'loss': 1.7023, 'learning_rate': 0.0003931773432418712, 'epoch': 0.11}

 11%|█         | 389/3566 [15:36<2:14:49,  2.55s/it]
 11%|█         | 390/3566 [15:38<2:09:43,  2.45s/it]
                                                    
{'loss': 1.7923, 'learning_rate': 0.00039313031857280534, 'epoch': 0.11}

 11%|█         | 390/3566 [15:38<2:09:43,  2.45s/it]
 11%|█         | 391/3566 [15:41<2:11:27,  2.48s/it]
                                                    
{'loss': 1.5627, 'learning_rate': 0.0003930831352343845, 'epoch': 0.11}

 11%|█         | 391/3566 [15:41<2:11:27,  2.48s/it]
 11%|█         | 392/3566 [15:43<2:12:49,  2.51s/it]
                                                    
{'loss': 1.6565, 'learning_rate': 0.0003930357932653733, 'epoch': 0.11}

 11%|█         | 392/3566 [15:43<2:12:49,  2.51s/it]
 11%|█         | 393/3566 [15:46<2:09:48,  2.45s/it]
                                                    
{'loss': 1.6148, 'learning_rate': 0.00039298829270466594, 'epoch': 0.11}

 11%|█         | 393/3566 [15:46<2:09:48,  2.45s/it]
 11%|█         | 394/3566 [15:48<2:14:34,  2.55s/it]
                                                    
{'loss': 1.745, 'learning_rate': 0.0003929406335912875, 'epoch': 0.11}

 11%|█         | 394/3566 [15:48<2:14:34,  2.55s/it]
 11%|█         | 395/3566 [15:51<2:11:01,  2.48s/it]
                                                    
{'loss': 1.7138, 'learning_rate': 0.00039289281596439305, 'epoch': 0.11}

 11%|█         | 395/3566 [15:51<2:11:01,  2.48s/it]
 11%|█         | 396/3566 [15:53<2:14:25,  2.54s/it]
                                                    
{'loss': 1.642, 'learning_rate': 0.00039284483986326785, 'epoch': 0.11}

 11%|█         | 396/3566 [15:53<2:14:25,  2.54s/it]
 11%|█         | 397/3566 [15:56<2:10:18,  2.47s/it]
                                                    
{'loss': 1.7352, 'learning_rate': 0.0003927967053273276, 'epoch': 0.11}

 11%|█         | 397/3566 [15:56<2:10:18,  2.47s/it]
 11%|█         | 398/3566 [15:58<2:06:08,  2.39s/it]
                                                    
{'loss': 1.7875, 'learning_rate': 0.0003927484123961179, 'epoch': 0.11}

 11%|█         | 398/3566 [15:58<2:06:08,  2.39s/it]
 11%|█         | 399/3566 [16:01<2:15:13,  2.56s/it]
                                                    
{'loss': 1.4313, 'learning_rate': 0.00039269996110931463, 'epoch': 0.11}

 11%|█         | 399/3566 [16:01<2:15:13,  2.56s/it]
 11%|█         | 400/3566 [16:03<2:11:28,  2.49s/it]
                                                    
{'loss': 1.7059, 'learning_rate': 0.0003926513515067238, 'epoch': 0.11}

 11%|█         | 400/3566 [16:03<2:11:28,  2.49s/it]
 11%|█         | 401/3566 [16:05<2:10:16,  2.47s/it]
                                                    
{'loss': 1.6339, 'learning_rate': 0.00039260258362828126, 'epoch': 0.11}

 11%|█         | 401/3566 [16:05<2:10:16,  2.47s/it]
 11%|█▏        | 402/3566 [16:08<2:06:02,  2.39s/it]
                                                    
{'loss': 1.7316, 'learning_rate': 0.0003925536575140532, 'epoch': 0.11}

 11%|█▏        | 402/3566 [16:08<2:06:02,  2.39s/it]
 11%|█▏        | 403/3566 [16:10<2:06:36,  2.40s/it]
                                                    
{'loss': 1.4714, 'learning_rate': 0.00039250457320423555, 'epoch': 0.11}

 11%|█▏        | 403/3566 [16:10<2:06:36,  2.40s/it]
 11%|█▏        | 404/3566 [16:13<2:08:01,  2.43s/it]
                                                    
{'loss': 1.8578, 'learning_rate': 0.0003924553307391545, 'epoch': 0.11}

 11%|█▏        | 404/3566 [16:13<2:08:01,  2.43s/it]
 11%|█▏        | 405/3566 [16:15<2:06:33,  2.40s/it]
                                                    
{'loss': 1.6047, 'learning_rate': 0.00039240593015926577, 'epoch': 0.11}

 11%|█▏        | 405/3566 [16:15<2:06:33,  2.40s/it]
 11%|█▏        | 406/3566 [16:17<2:05:32,  2.38s/it]
                                                    
{'loss': 1.6092, 'learning_rate': 0.00039235637150515537, 'epoch': 0.11}

 11%|█▏        | 406/3566 [16:17<2:05:32,  2.38s/it]
 11%|█▏        | 407/3566 [16:20<2:04:10,  2.36s/it]
                                                    
{'loss': 1.709, 'learning_rate': 0.00039230665481753893, 'epoch': 0.11}

 11%|█▏        | 407/3566 [16:20<2:04:10,  2.36s/it]
 11%|█▏        | 408/3566 [16:22<1:59:22,  2.27s/it]
                                                    
{'loss': 1.5493, 'learning_rate': 0.0003922567801372621, 'epoch': 0.11}

 11%|█▏        | 408/3566 [16:22<1:59:22,  2.27s/it]
 11%|█▏        | 409/3566 [16:25<2:09:56,  2.47s/it]
                                                    
{'loss': 1.6283, 'learning_rate': 0.00039220674750530015, 'epoch': 0.11}

 11%|█▏        | 409/3566 [16:25<2:09:56,  2.47s/it]
 11%|█▏        | 410/3566 [16:27<2:10:44,  2.49s/it]
                                                    
{'loss': 1.5762, 'learning_rate': 0.0003921565569627582, 'epoch': 0.11}

 11%|█▏        | 410/3566 [16:27<2:10:44,  2.49s/it]
 12%|█▏        | 411/3566 [16:29<2:06:53,  2.41s/it]
                                                    
{'loss': 1.4162, 'learning_rate': 0.00039210620855087116, 'epoch': 0.12}

 12%|█▏        | 411/3566 [16:29<2:06:53,  2.41s/it]
 12%|█▏        | 412/3566 [16:32<2:06:54,  2.41s/it]
                                                    
{'loss': 1.6104, 'learning_rate': 0.0003920557023110036, 'epoch': 0.12}

 12%|█▏        | 412/3566 [16:32<2:06:54,  2.41s/it]
 12%|█▏        | 413/3566 [16:34<2:08:03,  2.44s/it]
                                                    
{'loss': 1.5302, 'learning_rate': 0.00039200503828464966, 'epoch': 0.12}

 12%|█▏        | 413/3566 [16:34<2:08:03,  2.44s/it]
 12%|█▏        | 414/3566 [16:37<2:06:33,  2.41s/it]
                                                    
{'loss': 1.6919, 'learning_rate': 0.0003919542165134333, 'epoch': 0.12}

 12%|█▏        | 414/3566 [16:37<2:06:33,  2.41s/it]
 12%|█▏        | 415/3566 [16:39<2:03:51,  2.36s/it]
                                                    
{'loss': 1.6932, 'learning_rate': 0.00039190323703910783, 'epoch': 0.12}

 12%|█▏        | 415/3566 [16:39<2:03:51,  2.36s/it]
 12%|█▏        | 416/3566 [16:41<2:03:53,  2.36s/it]
                                                    
{'loss': 1.6851, 'learning_rate': 0.0003918520999035564, 'epoch': 0.12}

 12%|█▏        | 416/3566 [16:41<2:03:53,  2.36s/it]
 12%|█▏        | 417/3566 [16:44<2:05:09,  2.38s/it]
                                                    
{'loss': 1.6587, 'learning_rate': 0.0003918008051487915, 'epoch': 0.12}

 12%|█▏        | 417/3566 [16:44<2:05:09,  2.38s/it]
 12%|█▏        | 418/3566 [16:46<2:05:18,  2.39s/it]
                                                    
{'loss': 1.6301, 'learning_rate': 0.0003917493528169552, 'epoch': 0.12}

 12%|█▏        | 418/3566 [16:46<2:05:18,  2.39s/it]
 12%|█▏        | 419/3566 [16:48<2:03:11,  2.35s/it]
                                                    
{'loss': 1.5199, 'learning_rate': 0.000391697742950319, 'epoch': 0.12}

 12%|█▏        | 419/3566 [16:48<2:03:11,  2.35s/it]
 12%|█▏        | 420/3566 [16:50<1:59:30,  2.28s/it]
                                                    
{'loss': 1.6334, 'learning_rate': 0.0003916459755912837, 'epoch': 0.12}

 12%|█▏        | 420/3566 [16:50<1:59:30,  2.28s/it]
 12%|█▏        | 421/3566 [16:53<2:01:46,  2.32s/it]
                                                    
{'loss': 1.474, 'learning_rate': 0.00039159405078237976, 'epoch': 0.12}

 12%|█▏        | 421/3566 [16:53<2:01:46,  2.32s/it]
 12%|█▏        | 422/3566 [16:55<2:00:54,  2.31s/it]
                                                    
{'loss': 1.6662, 'learning_rate': 0.0003915419685662669, 'epoch': 0.12}

 12%|█▏        | 422/3566 [16:55<2:00:54,  2.31s/it]
 12%|█▏        | 423/3566 [16:58<2:03:44,  2.36s/it]
                                                    
{'loss': 1.6301, 'learning_rate': 0.0003914897289857339, 'epoch': 0.12}

 12%|█▏        | 423/3566 [16:58<2:03:44,  2.36s/it]
 12%|█▏        | 424/3566 [17:00<2:06:56,  2.42s/it]
                                                    
{'loss': 1.4839, 'learning_rate': 0.0003914373320836992, 'epoch': 0.12}

 12%|█▏        | 424/3566 [17:00<2:06:56,  2.42s/it]
 12%|█▏        | 425/3566 [17:03<2:16:02,  2.60s/it]
                                                    
{'loss': 1.9532, 'learning_rate': 0.0003913847779032103, 'epoch': 0.12}

 12%|█▏        | 425/3566 [17:03<2:16:02,  2.60s/it]
 12%|█▏        | 426/3566 [17:05<2:09:59,  2.48s/it]
                                                    
{'loss': 1.6305, 'learning_rate': 0.00039133206648744395, 'epoch': 0.12}

 12%|█▏        | 426/3566 [17:05<2:09:59,  2.48s/it]
 12%|█▏        | 427/3566 [17:08<2:07:19,  2.43s/it]
                                                    
{'loss': 1.6361, 'learning_rate': 0.000391279197879706, 'epoch': 0.12}

 12%|█▏        | 427/3566 [17:08<2:07:19,  2.43s/it]
 12%|█▏        | 428/3566 [17:10<2:11:17,  2.51s/it]
                                                    
{'loss': 1.5287, 'learning_rate': 0.0003912261721234316, 'epoch': 0.12}

 12%|█▏        | 428/3566 [17:10<2:11:17,  2.51s/it]
 12%|█▏        | 429/3566 [17:13<2:10:28,  2.50s/it]
                                                    
{'loss': 1.5012, 'learning_rate': 0.0003911729892621849, 'epoch': 0.12}

 12%|█▏        | 429/3566 [17:13<2:10:28,  2.50s/it]
 12%|█▏        | 430/3566 [17:15<2:09:01,  2.47s/it]
                                                    
{'loss': 1.6288, 'learning_rate': 0.0003911196493396591, 'epoch': 0.12}

 12%|█▏        | 430/3566 [17:15<2:09:01,  2.47s/it]
 12%|█▏        | 431/3566 [17:18<2:11:07,  2.51s/it]
                                                    
{'loss': 1.7189, 'learning_rate': 0.0003910661523996765, 'epoch': 0.12}

 12%|█▏        | 431/3566 [17:18<2:11:07,  2.51s/it]
 12%|█▏        | 432/3566 [17:20<2:06:13,  2.42s/it]
                                                    
{'loss': 1.5912, 'learning_rate': 0.0003910124984861884, 'epoch': 0.12}

 12%|█▏        | 432/3566 [17:20<2:06:13,  2.42s/it]
 12%|█▏        | 433/3566 [17:24<2:23:34,  2.75s/it]
                                                    
{'loss': 1.5301, 'learning_rate': 0.00039095868764327506, 'epoch': 0.12}

 12%|█▏        | 433/3566 [17:24<2:23:34,  2.75s/it]
 12%|█▏        | 434/3566 [17:26<2:19:21,  2.67s/it]
                                                    
{'loss': 1.5542, 'learning_rate': 0.0003909047199151456, 'epoch': 0.12}

 12%|█▏        | 434/3566 [17:26<2:19:21,  2.67s/it]
 12%|█▏        | 435/3566 [17:28<2:14:55,  2.59s/it]
                                                    
{'loss': 1.6419, 'learning_rate': 0.00039085059534613815, 'epoch': 0.12}

 12%|█▏        | 435/3566 [17:28<2:14:55,  2.59s/it]
 12%|█▏        | 436/3566 [17:31<2:09:50,  2.49s/it]
                                                    
{'loss': 1.4787, 'learning_rate': 0.0003907963139807196, 'epoch': 0.12}

 12%|█▏        | 436/3566 [17:31<2:09:50,  2.49s/it]
 12%|█▏        | 437/3566 [17:33<2:07:59,  2.45s/it]
                                                    
{'loss': 1.6225, 'learning_rate': 0.00039074187586348564, 'epoch': 0.12}

 12%|█▏        | 437/3566 [17:33<2:07:59,  2.45s/it]
 12%|█▏        | 438/3566 [17:36<2:07:04,  2.44s/it]
                                                    
{'loss': 1.674, 'learning_rate': 0.0003906872810391609, 'epoch': 0.12}

 12%|█▏        | 438/3566 [17:36<2:07:04,  2.44s/it]
 12%|█▏        | 439/3566 [17:39<2:19:09,  2.67s/it]
                                                    
{'loss': 1.4997, 'learning_rate': 0.0003906325295525985, 'epoch': 0.12}

 12%|█▏        | 439/3566 [17:39<2:19:09,  2.67s/it]
 12%|█▏        | 440/3566 [17:41<2:14:33,  2.58s/it]
                                                    
{'loss': 1.6527, 'learning_rate': 0.0003905776214487806, 'epoch': 0.12}

 12%|█▏        | 440/3566 [17:41<2:14:33,  2.58s/it]
 12%|█▏        | 441/3566 [17:44<2:13:07,  2.56s/it]
                                                    
{'loss': 1.7466, 'learning_rate': 0.00039052255677281766, 'epoch': 0.12}

 12%|█▏        | 441/3566 [17:44<2:13:07,  2.56s/it]
 12%|█▏        | 442/3566 [17:46<2:12:50,  2.55s/it]
                                                    
{'loss': 1.5778, 'learning_rate': 0.0003904673355699491, 'epoch': 0.12}

 12%|█▏        | 442/3566 [17:46<2:12:50,  2.55s/it]
 12%|█▏        | 443/3566 [17:49<2:13:52,  2.57s/it]
                                                    
{'loss': 1.6379, 'learning_rate': 0.0003904119578855427, 'epoch': 0.12}

 12%|█▏        | 443/3566 [17:49<2:13:52,  2.57s/it]
 12%|█▏        | 444/3566 [17:52<2:18:59,  2.67s/it]
                                                    
{'loss': 1.6003, 'learning_rate': 0.00039035642376509497, 'epoch': 0.12}

 12%|█▏        | 444/3566 [17:52<2:18:59,  2.67s/it]
 12%|█▏        | 445/3566 [17:54<2:12:22,  2.54s/it]
                                                    
{'loss': 1.6279, 'learning_rate': 0.0003903007332542308, 'epoch': 0.12}

 12%|█▏        | 445/3566 [17:54<2:12:22,  2.54s/it]
 13%|█▎        | 446/3566 [17:56<2:11:03,  2.52s/it]
                                                    
{'loss': 1.8208, 'learning_rate': 0.0003902448863987037, 'epoch': 0.13}

 13%|█▎        | 446/3566 [17:56<2:11:03,  2.52s/it]
 13%|█▎        | 447/3566 [17:59<2:08:16,  2.47s/it]
                                                    
{'loss': 1.6746, 'learning_rate': 0.0003901888832443955, 'epoch': 0.13}

 13%|█▎        | 447/3566 [17:59<2:08:16,  2.47s/it]
 13%|█▎        | 448/3566 [18:01<2:08:53,  2.48s/it]
                                                    
{'loss': 1.5868, 'learning_rate': 0.0003901327238373166, 'epoch': 0.13}

 13%|█▎        | 448/3566 [18:01<2:08:53,  2.48s/it]
 13%|█▎        | 449/3566 [18:04<2:07:51,  2.46s/it]
                                                    
{'loss': 1.7086, 'learning_rate': 0.0003900764082236056, 'epoch': 0.13}

 13%|█▎        | 449/3566 [18:04<2:07:51,  2.46s/it]
 13%|█▎        | 450/3566 [18:06<2:09:49,  2.50s/it]
                                                    
{'loss': 1.6933, 'learning_rate': 0.00039001993644952943, 'epoch': 0.13}

 13%|█▎        | 450/3566 [18:06<2:09:49,  2.50s/it]
 13%|█▎        | 451/3566 [18:09<2:06:14,  2.43s/it]
                                                    
{'loss': 1.727, 'learning_rate': 0.0003899633085614836, 'epoch': 0.13}

 13%|█▎        | 451/3566 [18:09<2:06:14,  2.43s/it]
 13%|█▎        | 452/3566 [18:11<2:13:30,  2.57s/it]
                                                    
{'loss': 1.6483, 'learning_rate': 0.0003899065246059915, 'epoch': 0.13}

 13%|█▎        | 452/3566 [18:11<2:13:30,  2.57s/it]
 13%|█▎        | 453/3566 [18:13<2:05:33,  2.42s/it]
                                                    
{'loss': 1.6562, 'learning_rate': 0.000389849584629705, 'epoch': 0.13}

 13%|█▎        | 453/3566 [18:13<2:05:33,  2.42s/it]
 13%|█▎        | 454/3566 [18:16<2:07:31,  2.46s/it]
                                                    
{'loss': 1.6298, 'learning_rate': 0.000389792488679404, 'epoch': 0.13}

 13%|█▎        | 454/3566 [18:16<2:07:31,  2.46s/it]
 13%|█▎        | 455/3566 [18:18<2:06:36,  2.44s/it]
                                                    
{'loss': 1.7358, 'learning_rate': 0.0003897352368019966, 'epoch': 0.13}

 13%|█▎        | 455/3566 [18:18<2:06:36,  2.44s/it]
 13%|█▎        | 456/3566 [18:21<2:07:10,  2.45s/it]
                                                    
{'loss': 1.4379, 'learning_rate': 0.0003896778290445192, 'epoch': 0.13}

 13%|█▎        | 456/3566 [18:21<2:07:10,  2.45s/it]
 13%|█▎        | 457/3566 [18:23<2:08:31,  2.48s/it]
                                                    
{'loss': 1.7434, 'learning_rate': 0.00038962026545413586, 'epoch': 0.13}

 13%|█▎        | 457/3566 [18:23<2:08:31,  2.48s/it]
 13%|█▎        | 458/3566 [18:26<2:08:56,  2.49s/it]
                                                    
{'loss': 1.8016, 'learning_rate': 0.0003895625460781389, 'epoch': 0.13}

 13%|█▎        | 458/3566 [18:26<2:08:56,  2.49s/it]
 13%|█▎        | 459/3566 [18:28<2:02:27,  2.36s/it]
                                                    
{'loss': 1.6085, 'learning_rate': 0.00038950467096394867, 'epoch': 0.13}

 13%|█▎        | 459/3566 [18:28<2:02:27,  2.36s/it]
 13%|█▎        | 460/3566 [18:30<2:00:16,  2.32s/it]
                                                    
{'loss': 1.6858, 'learning_rate': 0.0003894466401591135, 'epoch': 0.13}

 13%|█▎        | 460/3566 [18:30<2:00:16,  2.32s/it]
 13%|█▎        | 461/3566 [18:33<2:02:28,  2.37s/it]
                                                    
{'loss': 1.6548, 'learning_rate': 0.00038938845371130936, 'epoch': 0.13}

 13%|█▎        | 461/3566 [18:33<2:02:28,  2.37s/it]
 13%|█▎        | 462/3566 [18:35<2:03:29,  2.39s/it]
                                                    
{'loss': 1.717, 'learning_rate': 0.0003893301116683404, 'epoch': 0.13}

 13%|█▎        | 462/3566 [18:35<2:03:29,  2.39s/it]
 13%|█▎        | 463/3566 [18:38<2:03:28,  2.39s/it]
                                                    
{'loss': 1.6933, 'learning_rate': 0.0003892716140781384, 'epoch': 0.13}

 13%|█▎        | 463/3566 [18:38<2:03:28,  2.39s/it]
 13%|█▎        | 464/3566 [18:40<2:02:02,  2.36s/it]
                                                    
{'loss': 1.7293, 'learning_rate': 0.0003892129609887631, 'epoch': 0.13}

 13%|█▎        | 464/3566 [18:40<2:02:02,  2.36s/it]
 13%|█▎        | 465/3566 [18:42<1:59:33,  2.31s/it]
                                                    
{'loss': 1.6544, 'learning_rate': 0.0003891541524484018, 'epoch': 0.13}

 13%|█▎        | 465/3566 [18:42<1:59:33,  2.31s/it]
 13%|█▎        | 466/3566 [18:44<2:01:09,  2.35s/it]
                                                    
{'loss': 1.67, 'learning_rate': 0.0003890951885053697, 'epoch': 0.13}

 13%|█▎        | 466/3566 [18:44<2:01:09,  2.35s/it]
 13%|█▎        | 467/3566 [18:47<2:03:13,  2.39s/it]
                                                    
{'loss': 1.5251, 'learning_rate': 0.0003890360692081094, 'epoch': 0.13}

 13%|█▎        | 467/3566 [18:47<2:03:13,  2.39s/it]
 13%|█▎        | 468/3566 [18:49<2:01:38,  2.36s/it]
                                                    
{'loss': 1.6306, 'learning_rate': 0.0003889767946051916, 'epoch': 0.13}

 13%|█▎        | 468/3566 [18:49<2:01:38,  2.36s/it]
 13%|█▎        | 469/3566 [18:51<1:58:10,  2.29s/it]
                                                    
{'loss': 1.6507, 'learning_rate': 0.00038891736474531416, 'epoch': 0.13}

 13%|█▎        | 469/3566 [18:51<1:58:10,  2.29s/it]
 13%|█▎        | 470/3566 [18:54<2:00:22,  2.33s/it]
                                                    
{'loss': 1.735, 'learning_rate': 0.00038885777967730264, 'epoch': 0.13}

 13%|█▎        | 470/3566 [18:54<2:00:22,  2.33s/it]
 13%|█▎        | 471/3566 [18:56<1:58:10,  2.29s/it]
                                                    
{'loss': 1.5742, 'learning_rate': 0.00038879803945011016, 'epoch': 0.13}

 13%|█▎        | 471/3566 [18:56<1:58:10,  2.29s/it]
 13%|█▎        | 472/3566 [18:59<2:03:56,  2.40s/it]
                                                    
{'loss': 1.7325, 'learning_rate': 0.0003887381441128173, 'epoch': 0.13}

 13%|█▎        | 472/3566 [18:59<2:03:56,  2.40s/it]
 13%|█▎        | 473/3566 [19:01<2:01:32,  2.36s/it]
                                                    
{'loss': 1.5972, 'learning_rate': 0.00038867809371463186, 'epoch': 0.13}

 13%|█▎        | 473/3566 [19:01<2:01:32,  2.36s/it]
 13%|█▎        | 474/3566 [19:03<1:59:19,  2.32s/it]
                                                    
{'loss': 1.6424, 'learning_rate': 0.00038861788830488956, 'epoch': 0.13}

 13%|█▎        | 474/3566 [19:03<1:59:19,  2.32s/it]
 13%|█▎        | 475/3566 [19:06<2:03:47,  2.40s/it]
                                                    
{'loss': 1.7426, 'learning_rate': 0.00038855752793305284, 'epoch': 0.13}

 13%|█▎        | 475/3566 [19:06<2:03:47,  2.40s/it]
 13%|█▎        | 476/3566 [19:08<2:05:02,  2.43s/it]
                                                    
{'loss': 1.7686, 'learning_rate': 0.0003884970126487119, 'epoch': 0.13}

 13%|█▎        | 476/3566 [19:08<2:05:02,  2.43s/it]
 13%|█▎        | 477/3566 [19:11<2:08:26,  2.49s/it]
                                                    
{'loss': 1.5441, 'learning_rate': 0.000388436342501584, 'epoch': 0.13}

 13%|█▎        | 477/3566 [19:11<2:08:26,  2.49s/it]
 13%|█▎        | 478/3566 [19:13<2:04:48,  2.42s/it]
                                                    
{'loss': 1.6817, 'learning_rate': 0.0003883755175415136, 'epoch': 0.13}

 13%|█▎        | 478/3566 [19:13<2:04:48,  2.42s/it]
 13%|█▎        | 479/3566 [19:16<2:11:24,  2.55s/it]
                                                    
{'loss': 1.7718, 'learning_rate': 0.0003883145378184726, 'epoch': 0.13}

 13%|█▎        | 479/3566 [19:16<2:11:24,  2.55s/it]
 13%|█▎        | 480/3566 [19:18<2:08:15,  2.49s/it]
                                                    
{'loss': 1.5555, 'learning_rate': 0.0003882534033825598, 'epoch': 0.13}

 13%|█▎        | 480/3566 [19:18<2:08:15,  2.49s/it]
 13%|█▎        | 481/3566 [19:21<2:10:11,  2.53s/it]
                                                    
{'loss': 1.6318, 'learning_rate': 0.00038819211428400125, 'epoch': 0.13}

 13%|█▎        | 481/3566 [19:21<2:10:11,  2.53s/it]
 14%|█▎        | 482/3566 [19:23<2:10:03,  2.53s/it]
                                                    
{'loss': 1.6014, 'learning_rate': 0.00038813067057314994, 'epoch': 0.14}

 14%|█▎        | 482/3566 [19:24<2:10:03,  2.53s/it]
 14%|█▎        | 483/3566 [19:26<2:11:44,  2.56s/it]
                                                    
{'loss': 1.7192, 'learning_rate': 0.0003880690723004859, 'epoch': 0.14}

 14%|█▎        | 483/3566 [19:26<2:11:44,  2.56s/it]
 14%|█▎        | 484/3566 [19:29<2:12:38,  2.58s/it]
                                                    
{'loss': 1.5524, 'learning_rate': 0.0003880073195166164, 'epoch': 0.14}

 14%|█▎        | 484/3566 [19:29<2:12:38,  2.58s/it]
 14%|█▎        | 485/3566 [19:31<2:10:31,  2.54s/it]
                                                    
{'loss': 1.6834, 'learning_rate': 0.0003879454122722752, 'epoch': 0.14}

 14%|█▎        | 485/3566 [19:31<2:10:31,  2.54s/it]
 14%|█▎        | 486/3566 [19:34<2:06:38,  2.47s/it]
                                                    
{'loss': 1.7585, 'learning_rate': 0.00038788335061832333, 'epoch': 0.14}

 14%|█▎        | 486/3566 [19:34<2:06:38,  2.47s/it]
 14%|█▎        | 487/3566 [19:36<2:08:04,  2.50s/it]
                                                    
{'loss': 1.5802, 'learning_rate': 0.00038782113460574853, 'epoch': 0.14}

 14%|█▎        | 487/3566 [19:36<2:08:04,  2.50s/it]
 14%|█▎        | 488/3566 [19:38<2:04:43,  2.43s/it]
                                                    
{'loss': 1.8165, 'learning_rate': 0.00038775876428566534, 'epoch': 0.14}

 14%|█▎        | 488/3566 [19:38<2:04:43,  2.43s/it]
 14%|█▎        | 489/3566 [19:41<2:03:10,  2.40s/it]
                                                    
{'loss': 1.6848, 'learning_rate': 0.0003876962397093152, 'epoch': 0.14}

 14%|█▎        | 489/3566 [19:41<2:03:10,  2.40s/it]
 14%|█▎        | 490/3566 [19:43<1:58:38,  2.31s/it]
                                                    
{'loss': 1.6112, 'learning_rate': 0.0003876335609280661, 'epoch': 0.14}

 14%|█▎        | 490/3566 [19:43<1:58:38,  2.31s/it]
 14%|█▍        | 491/3566 [19:45<1:56:10,  2.27s/it]
                                                    
{'loss': 1.5237, 'learning_rate': 0.0003875707279934129, 'epoch': 0.14}

 14%|█▍        | 491/3566 [19:45<1:56:10,  2.27s/it]
 14%|█▍        | 492/3566 [19:47<1:59:24,  2.33s/it]
                                                    
{'loss': 1.7105, 'learning_rate': 0.00038750774095697697, 'epoch': 0.14}

 14%|█▍        | 492/3566 [19:47<1:59:24,  2.33s/it]
 14%|█▍        | 493/3566 [19:50<2:00:30,  2.35s/it]
                                                    
{'loss': 1.4533, 'learning_rate': 0.0003874445998705063, 'epoch': 0.14}

 14%|█▍        | 493/3566 [19:50<2:00:30,  2.35s/it]
 14%|█▍        | 494/3566 [19:52<2:02:02,  2.38s/it]
                                                    
{'loss': 1.6991, 'learning_rate': 0.00038738130478587553, 'epoch': 0.14}

 14%|█▍        | 494/3566 [19:52<2:02:02,  2.38s/it]
 14%|█▍        | 495/3566 [19:55<2:06:45,  2.48s/it]
                                                    
{'loss': 1.6408, 'learning_rate': 0.0003873178557550858, 'epoch': 0.14}

 14%|█▍        | 495/3566 [19:55<2:06:45,  2.48s/it]
 14%|█▍        | 496/3566 [19:57<2:04:47,  2.44s/it]
                                                    
{'loss': 1.548, 'learning_rate': 0.0003872542528302646, 'epoch': 0.14}

 14%|█▍        | 496/3566 [19:57<2:04:47,  2.44s/it]
 14%|█▍        | 497/3566 [20:00<2:06:01,  2.46s/it]
                                                    
{'loss': 1.6202, 'learning_rate': 0.000387190496063666, 'epoch': 0.14}

 14%|█▍        | 497/3566 [20:00<2:06:01,  2.46s/it]
 14%|█▍        | 498/3566 [20:02<2:01:01,  2.37s/it]
                                                    
{'loss': 1.6177, 'learning_rate': 0.0003871265855076704, 'epoch': 0.14}

 14%|█▍        | 498/3566 [20:02<2:01:01,  2.37s/it]
 14%|█▍        | 499/3566 [20:04<1:58:14,  2.31s/it]
                                                    
{'loss': 1.689, 'learning_rate': 0.0003870625212147845, 'epoch': 0.14}

 14%|█▍        | 499/3566 [20:04<1:58:14,  2.31s/it]
 14%|█▍        | 500/3566 [20:07<2:03:42,  2.42s/it]
                                                    
{'loss': 1.7346, 'learning_rate': 0.0003869983032376415, 'epoch': 0.14}

 14%|█▍        | 500/3566 [20:07<2:03:42,  2.42s/it]
 14%|█▍        | 501/3566 [20:10<2:09:36,  2.54s/it]
                                                    
{'loss': 1.6023, 'learning_rate': 0.0003869339316290006, 'epoch': 0.14}

 14%|█▍        | 501/3566 [20:10<2:09:36,  2.54s/it]
 14%|█▍        | 502/3566 [20:12<2:07:00,  2.49s/it]
                                                    
{'loss': 1.5982, 'learning_rate': 0.00038686940644174736, 'epoch': 0.14}

 14%|█▍        | 502/3566 [20:12<2:07:00,  2.49s/it]
 14%|█▍        | 503/3566 [20:15<2:06:56,  2.49s/it]
                                                    
{'loss': 1.6136, 'learning_rate': 0.00038680472772889356, 'epoch': 0.14}

 14%|█▍        | 503/3566 [20:15<2:06:56,  2.49s/it]
 14%|█▍        | 504/3566 [20:17<2:08:19,  2.51s/it]
                                                    
{'loss': 1.5158, 'learning_rate': 0.00038673989554357705, 'epoch': 0.14}

 14%|█▍        | 504/3566 [20:17<2:08:19,  2.51s/it]
 14%|█▍        | 505/3566 [20:19<2:03:53,  2.43s/it]
                                                    
{'loss': 1.5937, 'learning_rate': 0.0003866749099390617, 'epoch': 0.14}

 14%|█▍        | 505/3566 [20:19<2:03:53,  2.43s/it]
 14%|█▍        | 506/3566 [20:22<2:01:16,  2.38s/it]
                                                    
{'loss': 1.5731, 'learning_rate': 0.00038660977096873747, 'epoch': 0.14}

 14%|█▍        | 506/3566 [20:22<2:01:16,  2.38s/it]
 14%|█▍        | 507/3566 [20:24<1:59:40,  2.35s/it]
                                                    
{'loss': 1.5614, 'learning_rate': 0.0003865444786861204, 'epoch': 0.14}

 14%|█▍        | 507/3566 [20:24<1:59:40,  2.35s/it]
 14%|█▍        | 508/3566 [20:26<1:59:07,  2.34s/it]
                                                    
{'loss': 1.6313, 'learning_rate': 0.0003864790331448525, 'epoch': 0.14}

 14%|█▍        | 508/3566 [20:26<1:59:07,  2.34s/it]
 14%|█▍        | 509/3566 [20:29<2:00:09,  2.36s/it]
                                                    
{'loss': 1.6973, 'learning_rate': 0.0003864134343987014, 'epoch': 0.14}

 14%|█▍        | 509/3566 [20:29<2:00:09,  2.36s/it]
 14%|█▍        | 510/3566 [20:31<2:03:27,  2.42s/it]
                                                    
{'loss': 1.7273, 'learning_rate': 0.00038634768250156106, 'epoch': 0.14}

 14%|█▍        | 510/3566 [20:31<2:03:27,  2.42s/it]
 14%|█▍        | 511/3566 [20:33<2:01:36,  2.39s/it]
                                                    
{'loss': 1.7, 'learning_rate': 0.0003862817775074509, 'epoch': 0.14}

 14%|█▍        | 511/3566 [20:33<2:01:36,  2.39s/it]
 14%|█▍        | 512/3566 [20:36<2:01:08,  2.38s/it]
                                                    
{'loss': 1.4817, 'learning_rate': 0.00038621571947051623, 'epoch': 0.14}

 14%|█▍        | 512/3566 [20:36<2:01:08,  2.38s/it]
 14%|█▍        | 513/3566 [20:38<1:57:04,  2.30s/it]
                                                    
{'loss': 1.6953, 'learning_rate': 0.00038614950844502807, 'epoch': 0.14}

 14%|█▍        | 513/3566 [20:38<1:57:04,  2.30s/it]
 14%|█▍        | 514/3566 [20:40<1:56:26,  2.29s/it]
                                                    
{'loss': 1.6213, 'learning_rate': 0.0003860831444853833, 'epoch': 0.14}

 14%|█▍        | 514/3566 [20:40<1:56:26,  2.29s/it]
 14%|█▍        | 515/3566 [20:43<2:02:16,  2.40s/it]
                                                    
{'loss': 1.696, 'learning_rate': 0.00038601662764610424, 'epoch': 0.14}

 14%|█▍        | 515/3566 [20:43<2:02:16,  2.40s/it]
 14%|█▍        | 516/3566 [20:45<2:04:54,  2.46s/it]
                                                    
{'loss': 1.6227, 'learning_rate': 0.0003859499579818388, 'epoch': 0.14}

 14%|█▍        | 516/3566 [20:45<2:04:54,  2.46s/it]
 14%|█▍        | 517/3566 [20:48<1:59:46,  2.36s/it]
                                                    
{'loss': 1.7682, 'learning_rate': 0.00038588313554736067, 'epoch': 0.14}

 14%|█▍        | 517/3566 [20:48<1:59:46,  2.36s/it]
 15%|█▍        | 518/3566 [20:50<1:55:55,  2.28s/it]
                                                    
{'loss': 1.5169, 'learning_rate': 0.0003858161603975688, 'epoch': 0.15}

 15%|█▍        | 518/3566 [20:50<1:55:55,  2.28s/it]
 15%|█▍        | 519/3566 [20:52<1:56:36,  2.30s/it]
                                                    
{'loss': 1.5868, 'learning_rate': 0.00038574903258748773, 'epoch': 0.15}

 15%|█▍        | 519/3566 [20:52<1:56:36,  2.30s/it]
 15%|█▍        | 520/3566 [20:54<1:55:02,  2.27s/it]
                                                    
{'loss': 1.4486, 'learning_rate': 0.0003856817521722675, 'epoch': 0.15}

 15%|█▍        | 520/3566 [20:54<1:55:02,  2.27s/it]
 15%|█▍        | 521/3566 [20:57<1:57:23,  2.31s/it]
                                                    
{'loss': 1.684, 'learning_rate': 0.00038561431920718325, 'epoch': 0.15}

 15%|█▍        | 521/3566 [20:57<1:57:23,  2.31s/it]
 15%|█▍        | 522/3566 [20:59<2:04:30,  2.45s/it]
                                                    
{'loss': 1.7448, 'learning_rate': 0.0003855467337476358, 'epoch': 0.15}

 15%|█▍        | 522/3566 [20:59<2:04:30,  2.45s/it]
 15%|█▍        | 523/3566 [21:02<2:00:03,  2.37s/it]
                                                    
{'loss': 1.3673, 'learning_rate': 0.00038547899584915105, 'epoch': 0.15}

 15%|█▍        | 523/3566 [21:02<2:00:03,  2.37s/it]
 15%|█▍        | 524/3566 [21:04<2:03:07,  2.43s/it]
                                                    
{'loss': 1.6268, 'learning_rate': 0.00038541110556738014, 'epoch': 0.15}

 15%|█▍        | 524/3566 [21:04<2:03:07,  2.43s/it]
 15%|█▍        | 525/3566 [21:07<2:02:16,  2.41s/it]
                                                    
{'loss': 1.6764, 'learning_rate': 0.0003853430629580994, 'epoch': 0.15}

 15%|█▍        | 525/3566 [21:07<2:02:16,  2.41s/it]
 15%|█▍        | 526/3566 [21:09<2:00:18,  2.37s/it]
                                                    
{'loss': 1.6594, 'learning_rate': 0.0003852748680772104, 'epoch': 0.15}

 15%|█▍        | 526/3566 [21:09<2:00:18,  2.37s/it]
 15%|█▍        | 527/3566 [21:11<1:57:09,  2.31s/it]
                                                    
{'loss': 1.5929, 'learning_rate': 0.0003852065209807397, 'epoch': 0.15}

 15%|█▍        | 527/3566 [21:11<1:57:09,  2.31s/it]
 15%|█▍        | 528/3566 [21:13<2:00:00,  2.37s/it]
                                                    
{'loss': 1.7438, 'learning_rate': 0.000385138021724839, 'epoch': 0.15}

 15%|█▍        | 528/3566 [21:13<2:00:00,  2.37s/it]
 15%|█▍        | 529/3566 [21:16<2:03:37,  2.44s/it]
                                                    
{'loss': 1.5752, 'learning_rate': 0.000385069370365785, 'epoch': 0.15}

 15%|█▍        | 529/3566 [21:16<2:03:37,  2.44s/it]
 15%|█▍        | 530/3566 [21:18<2:01:57,  2.41s/it]
                                                    
{'loss': 1.5398, 'learning_rate': 0.0003850005669599793, 'epoch': 0.15}

 15%|█▍        | 530/3566 [21:18<2:01:57,  2.41s/it]
 15%|█▍        | 531/3566 [21:21<2:00:31,  2.38s/it]
                                                    
{'loss': 1.7006, 'learning_rate': 0.00038493161156394855, 'epoch': 0.15}

 15%|█▍        | 531/3566 [21:21<2:00:31,  2.38s/it]
 15%|█▍        | 532/3566 [21:23<1:55:45,  2.29s/it]
                                                    
{'loss': 1.5635, 'learning_rate': 0.00038486250423434403, 'epoch': 0.15}

 15%|█▍        | 532/3566 [21:23<1:55:45,  2.29s/it]
 15%|█▍        | 533/3566 [21:26<2:05:04,  2.47s/it]
                                                    
{'loss': 1.5738, 'learning_rate': 0.00038479324502794214, 'epoch': 0.15}

 15%|█▍        | 533/3566 [21:26<2:05:04,  2.47s/it]
 15%|█▍        | 534/3566 [21:28<2:04:22,  2.46s/it]
                                                    
{'loss': 1.652, 'learning_rate': 0.00038472383400164374, 'epoch': 0.15}

 15%|█▍        | 534/3566 [21:28<2:04:22,  2.46s/it]
 15%|█▌        | 535/3566 [21:31<2:04:58,  2.47s/it]
                                                    
{'loss': 1.6429, 'learning_rate': 0.00038465427121247474, 'epoch': 0.15}

 15%|█▌        | 535/3566 [21:31<2:04:58,  2.47s/it]
 15%|█▌        | 536/3566 [21:33<2:03:09,  2.44s/it]
                                                    
{'loss': 1.6968, 'learning_rate': 0.0003845845567175855, 'epoch': 0.15}

 15%|█▌        | 536/3566 [21:33<2:03:09,  2.44s/it]
 15%|█▌        | 537/3566 [21:36<2:04:09,  2.46s/it]
                                                    
{'loss': 1.6771, 'learning_rate': 0.00038451469057425113, 'epoch': 0.15}

 15%|█▌        | 537/3566 [21:36<2:04:09,  2.46s/it]
 15%|█▌        | 538/3566 [21:38<2:00:05,  2.38s/it]
                                                    
{'loss': 1.6604, 'learning_rate': 0.00038444467283987134, 'epoch': 0.15}

 15%|█▌        | 538/3566 [21:38<2:00:05,  2.38s/it]
 15%|█▌        | 539/3566 [21:40<1:59:01,  2.36s/it]
                                                    
{'loss': 1.663, 'learning_rate': 0.00038437450357197025, 'epoch': 0.15}

 15%|█▌        | 539/3566 [21:40<1:59:01,  2.36s/it]
 15%|█▌        | 540/3566 [21:42<1:58:51,  2.36s/it]
                                                    
{'loss': 1.5601, 'learning_rate': 0.0003843041828281965, 'epoch': 0.15}

 15%|█▌        | 540/3566 [21:42<1:58:51,  2.36s/it]
 15%|█▌        | 541/3566 [21:45<1:56:19,  2.31s/it]
                                                    
{'loss': 1.568, 'learning_rate': 0.00038423371066632347, 'epoch': 0.15}

 15%|█▌        | 541/3566 [21:45<1:56:19,  2.31s/it]
 15%|█▌        | 542/3566 [21:47<1:57:31,  2.33s/it]
                                                    
{'loss': 1.5334, 'learning_rate': 0.0003841630871442485, 'epoch': 0.15}

 15%|█▌        | 542/3566 [21:47<1:57:31,  2.33s/it]
 15%|█▌        | 543/3566 [21:50<2:02:43,  2.44s/it]
                                                    
{'loss': 1.5218, 'learning_rate': 0.0003840923123199936, 'epoch': 0.15}

 15%|█▌        | 543/3566 [21:50<2:02:43,  2.44s/it]
 15%|█▌        | 544/3566 [21:52<2:01:48,  2.42s/it]
                                                    
{'loss': 1.6451, 'learning_rate': 0.00038402138625170495, 'epoch': 0.15}

 15%|█▌        | 544/3566 [21:52<2:01:48,  2.42s/it]
 15%|█▌        | 545/3566 [21:55<2:04:31,  2.47s/it]
                                                    
{'loss': 1.5404, 'learning_rate': 0.000383950308997653, 'epoch': 0.15}

 15%|█▌        | 545/3566 [21:55<2:04:31,  2.47s/it]
 15%|█▌        | 546/3566 [21:57<1:59:41,  2.38s/it]
                                                    
{'loss': 1.4505, 'learning_rate': 0.0003838790806162325, 'epoch': 0.15}

 15%|█▌        | 546/3566 [21:57<1:59:41,  2.38s/it]
 15%|█▌        | 547/3566 [21:59<1:59:51,  2.38s/it]
                                                    
{'loss': 1.6547, 'learning_rate': 0.0003838077011659622, 'epoch': 0.15}

 15%|█▌        | 547/3566 [21:59<1:59:51,  2.38s/it]
 15%|█▌        | 548/3566 [22:02<2:02:26,  2.43s/it]
                                                    
{'loss': 1.7092, 'learning_rate': 0.00038373617070548504, 'epoch': 0.15}

 15%|█▌        | 548/3566 [22:02<2:02:26,  2.43s/it]
 15%|█▌        | 549/3566 [22:04<2:04:35,  2.48s/it]
                                                    
{'loss': 1.6728, 'learning_rate': 0.0003836644892935681, 'epoch': 0.15}

 15%|█▌        | 549/3566 [22:04<2:04:35,  2.48s/it]
 15%|█▌        | 550/3566 [22:07<2:04:23,  2.47s/it]
                                                    
{'loss': 1.488, 'learning_rate': 0.00038359265698910237, 'epoch': 0.15}

 15%|█▌        | 550/3566 [22:07<2:04:23,  2.47s/it]
 15%|█▌        | 551/3566 [22:09<2:04:28,  2.48s/it]
                                                    
{'loss': 1.5505, 'learning_rate': 0.0003835206738511029, 'epoch': 0.15}

 15%|█▌        | 551/3566 [22:09<2:04:28,  2.48s/it]
 15%|█▌        | 552/3566 [22:12<2:01:02,  2.41s/it]
                                                    
{'loss': 1.6329, 'learning_rate': 0.0003834485399387085, 'epoch': 0.15}

 15%|█▌        | 552/3566 [22:12<2:01:02,  2.41s/it]
 16%|█▌        | 553/3566 [22:14<2:02:27,  2.44s/it]
                                                    
{'loss': 1.7233, 'learning_rate': 0.000383376255311182, 'epoch': 0.16}

 16%|█▌        | 553/3566 [22:14<2:02:27,  2.44s/it]
 16%|█▌        | 554/3566 [22:16<2:00:43,  2.40s/it]
                                                    
{'loss': 1.6345, 'learning_rate': 0.00038330382002791014, 'epoch': 0.16}

 16%|█▌        | 554/3566 [22:16<2:00:43,  2.40s/it]
 16%|█▌        | 555/3566 [22:19<2:03:59,  2.47s/it]
                                                    
{'loss': 1.7528, 'learning_rate': 0.00038323123414840313, 'epoch': 0.16}

 16%|█▌        | 555/3566 [22:19<2:03:59,  2.47s/it]
 16%|█▌        | 556/3566 [22:21<2:03:16,  2.46s/it]
                                                    
{'loss': 1.6351, 'learning_rate': 0.00038315849773229514, 'epoch': 0.16}

 16%|█▌        | 556/3566 [22:21<2:03:16,  2.46s/it]
 16%|█▌        | 557/3566 [22:24<2:01:19,  2.42s/it]
                                                    
{'loss': 1.7131, 'learning_rate': 0.000383085610839344, 'epoch': 0.16}

 16%|█▌        | 557/3566 [22:24<2:01:19,  2.42s/it]
 16%|█▌        | 558/3566 [22:26<2:04:43,  2.49s/it]
                                                    
{'loss': 1.609, 'learning_rate': 0.0003830125735294311, 'epoch': 0.16}

 16%|█▌        | 558/3566 [22:26<2:04:43,  2.49s/it]
 16%|█▌        | 559/3566 [22:29<2:02:35,  2.45s/it]
                                                    
{'loss': 1.5494, 'learning_rate': 0.0003829393858625614, 'epoch': 0.16}

 16%|█▌        | 559/3566 [22:29<2:02:35,  2.45s/it]
 16%|█▌        | 560/3566 [22:31<1:58:53,  2.37s/it]
                                                    
{'loss': 1.7247, 'learning_rate': 0.0003828660478988634, 'epoch': 0.16}

 16%|█▌        | 560/3566 [22:31<1:58:53,  2.37s/it]
 16%|█▌        | 561/3566 [22:34<2:02:15,  2.44s/it]
                                                    
{'loss': 1.5116, 'learning_rate': 0.00038279255969858914, 'epoch': 0.16}

 16%|█▌        | 561/3566 [22:34<2:02:15,  2.44s/it]
 16%|█▌        | 562/3566 [22:36<2:01:53,  2.43s/it]
                                                    
{'loss': 1.5377, 'learning_rate': 0.00038271892132211413, 'epoch': 0.16}

 16%|█▌        | 562/3566 [22:36<2:01:53,  2.43s/it]
 16%|█▌        | 563/3566 [22:38<2:00:11,  2.40s/it]
                                                    
{'loss': 1.6662, 'learning_rate': 0.00038264513282993697, 'epoch': 0.16}

 16%|█▌        | 563/3566 [22:38<2:00:11,  2.40s/it]
 16%|█▌        | 564/3566 [22:41<2:00:43,  2.41s/it]
                                                    
{'loss': 1.5916, 'learning_rate': 0.00038257119428268, 'epoch': 0.16}

 16%|█▌        | 564/3566 [22:41<2:00:43,  2.41s/it]
 16%|█▌        | 565/3566 [22:43<1:58:05,  2.36s/it]
                                                    
{'loss': 1.6098, 'learning_rate': 0.0003824971057410885, 'epoch': 0.16}

 16%|█▌        | 565/3566 [22:43<1:58:05,  2.36s/it]
 16%|█▌        | 566/3566 [22:45<2:00:55,  2.42s/it]
                                                    
{'loss': 1.6052, 'learning_rate': 0.00038242286726603117, 'epoch': 0.16}

 16%|█▌        | 566/3566 [22:46<2:00:55,  2.42s/it]
 16%|█▌        | 567/3566 [22:48<1:58:53,  2.38s/it]
                                                    
{'loss': 1.6702, 'learning_rate': 0.0003823484789184999, 'epoch': 0.16}

 16%|█▌        | 567/3566 [22:48<1:58:53,  2.38s/it]
 16%|█▌        | 568/3566 [22:50<2:00:38,  2.41s/it]
                                                    
{'loss': 1.7043, 'learning_rate': 0.00038227394075960946, 'epoch': 0.16}

 16%|█▌        | 568/3566 [22:50<2:00:38,  2.41s/it]
 16%|█▌        | 569/3566 [22:53<1:58:53,  2.38s/it]
                                                    
{'loss': 1.7048, 'learning_rate': 0.0003821992528505981, 'epoch': 0.16}

 16%|█▌        | 569/3566 [22:53<1:58:53,  2.38s/it]
 16%|█▌        | 570/3566 [22:55<2:00:28,  2.41s/it]
                                                    
{'loss': 1.6, 'learning_rate': 0.00038212441525282677, 'epoch': 0.16}

 16%|█▌        | 570/3566 [22:55<2:00:28,  2.41s/it]
 16%|█▌        | 571/3566 [22:57<1:57:00,  2.34s/it]
                                                    
{'loss': 1.6999, 'learning_rate': 0.0003820494280277795, 'epoch': 0.16}

 16%|█▌        | 571/3566 [22:57<1:57:00,  2.34s/it]
 16%|█▌        | 572/3566 [23:00<1:58:30,  2.38s/it]
                                                    
{'loss': 1.5814, 'learning_rate': 0.0003819742912370633, 'epoch': 0.16}

 16%|█▌        | 572/3566 [23:00<1:58:30,  2.38s/it]
 16%|█▌        | 573/3566 [23:02<1:59:59,  2.41s/it]
                                                    
{'loss': 1.5547, 'learning_rate': 0.0003818990049424081, 'epoch': 0.16}

 16%|█▌        | 573/3566 [23:02<1:59:59,  2.41s/it]
 16%|█▌        | 574/3566 [23:05<2:00:02,  2.41s/it]
                                                    
{'loss': 1.6049, 'learning_rate': 0.0003818235692056664, 'epoch': 0.16}

 16%|█▌        | 574/3566 [23:05<2:00:02,  2.41s/it]
 16%|█▌        | 575/3566 [23:07<2:00:45,  2.42s/it]
                                                    
{'loss': 1.5417, 'learning_rate': 0.00038174798408881385, 'epoch': 0.16}

 16%|█▌        | 575/3566 [23:07<2:00:45,  2.42s/it]
 16%|█▌        | 576/3566 [23:09<1:59:30,  2.40s/it]
                                                    
{'loss': 1.6171, 'learning_rate': 0.00038167224965394856, 'epoch': 0.16}

 16%|█▌        | 576/3566 [23:09<1:59:30,  2.40s/it]
 16%|█▌        | 577/3566 [23:12<1:58:49,  2.39s/it]
                                                    
{'loss': 1.7906, 'learning_rate': 0.0003815963659632913, 'epoch': 0.16}

 16%|█▌        | 577/3566 [23:12<1:58:49,  2.39s/it]
 16%|█▌        | 578/3566 [23:14<2:02:05,  2.45s/it]
                                                    
{'loss': 1.4961, 'learning_rate': 0.00038152033307918564, 'epoch': 0.16}

 16%|█▌        | 578/3566 [23:14<2:02:05,  2.45s/it]
 16%|█▌        | 579/3566 [23:17<2:08:43,  2.59s/it]
                                                    
{'loss': 1.6419, 'learning_rate': 0.00038144415106409763, 'epoch': 0.16}

 16%|█▌        | 579/3566 [23:17<2:08:43,  2.59s/it]
 16%|█▋        | 580/3566 [23:20<2:04:53,  2.51s/it]
                                                    
{'loss': 1.6146, 'learning_rate': 0.0003813678199806159, 'epoch': 0.16}

 16%|█▋        | 580/3566 [23:20<2:04:53,  2.51s/it]
 16%|█▋        | 581/3566 [23:22<2:00:24,  2.42s/it]
                                                    
{'loss': 1.5949, 'learning_rate': 0.0003812913398914513, 'epoch': 0.16}

 16%|█▋        | 581/3566 [23:22<2:00:24,  2.42s/it]
 16%|█▋        | 582/3566 [23:24<2:00:18,  2.42s/it]
                                                    
{'loss': 1.6703, 'learning_rate': 0.00038121471085943745, 'epoch': 0.16}

 16%|█▋        | 582/3566 [23:24<2:00:18,  2.42s/it]
 16%|█▋        | 583/3566 [23:27<1:59:11,  2.40s/it]
                                                    
{'loss': 1.6016, 'learning_rate': 0.00038113793294753014, 'epoch': 0.16}

 16%|█▋        | 583/3566 [23:27<1:59:11,  2.40s/it]
 16%|█▋        | 584/3566 [23:29<2:02:38,  2.47s/it]
                                                    
{'loss': 1.714, 'learning_rate': 0.00038106100621880756, 'epoch': 0.16}

 16%|█▋        | 584/3566 [23:29<2:02:38,  2.47s/it]
 16%|█▋        | 585/3566 [23:32<2:01:03,  2.44s/it]
                                                    
{'loss': 1.6146, 'learning_rate': 0.00038098393073647004, 'epoch': 0.16}

 16%|█▋        | 585/3566 [23:32<2:01:03,  2.44s/it]
 16%|█▋        | 586/3566 [23:34<2:00:38,  2.43s/it]
                                                    
{'loss': 1.629, 'learning_rate': 0.00038090670656384023, 'epoch': 0.16}

 16%|█▋        | 586/3566 [23:34<2:00:38,  2.43s/it]
 16%|█▋        | 587/3566 [23:36<1:59:07,  2.40s/it]
                                                    
{'loss': 1.6082, 'learning_rate': 0.0003808293337643629, 'epoch': 0.16}

 16%|█▋        | 587/3566 [23:36<1:59:07,  2.40s/it]
 16%|█▋        | 588/3566 [23:39<2:00:44,  2.43s/it]
                                                    
{'loss': 1.5346, 'learning_rate': 0.0003807518124016049, 'epoch': 0.16}

 16%|█▋        | 588/3566 [23:39<2:00:44,  2.43s/it]
 17%|█▋        | 589/3566 [23:41<2:01:20,  2.45s/it]
                                                    
{'loss': 1.6732, 'learning_rate': 0.0003806741425392552, 'epoch': 0.17}

 17%|█▋        | 589/3566 [23:41<2:01:20,  2.45s/it]
 17%|█▋        | 590/3566 [23:43<1:56:55,  2.36s/it]
                                                    
{'loss': 1.5394, 'learning_rate': 0.0003805963242411247, 'epoch': 0.17}

 17%|█▋        | 590/3566 [23:43<1:56:55,  2.36s/it]
 17%|█▋        | 591/3566 [23:46<1:55:13,  2.32s/it]
                                                    
{'loss': 1.6558, 'learning_rate': 0.0003805183575711464, 'epoch': 0.17}

 17%|█▋        | 591/3566 [23:46<1:55:13,  2.32s/it]
 17%|█▋        | 592/3566 [23:48<1:54:43,  2.31s/it]
                                                    
{'loss': 1.5871, 'learning_rate': 0.00038044024259337503, 'epoch': 0.17}

 17%|█▋        | 592/3566 [23:48<1:54:43,  2.31s/it]
 17%|█▋        | 593/3566 [23:50<1:52:39,  2.27s/it]
                                                    
{'loss': 1.8108, 'learning_rate': 0.00038036197937198717, 'epoch': 0.17}

 17%|█▋        | 593/3566 [23:50<1:52:39,  2.27s/it]
 17%|█▋        | 594/3566 [23:53<1:56:52,  2.36s/it]
                                                    
{'loss': 1.5756, 'learning_rate': 0.00038028356797128126, 'epoch': 0.17}

 17%|█▋        | 594/3566 [23:53<1:56:52,  2.36s/it]
 17%|█▋        | 595/3566 [23:55<1:56:05,  2.34s/it]
                                                    
{'loss': 1.6226, 'learning_rate': 0.00038020500845567745, 'epoch': 0.17}

 17%|█▋        | 595/3566 [23:55<1:56:05,  2.34s/it]
 17%|█▋        | 596/3566 [23:57<1:54:16,  2.31s/it]
                                                    
{'loss': 1.7574, 'learning_rate': 0.00038012630088971765, 'epoch': 0.17}

 17%|█▋        | 596/3566 [23:57<1:54:16,  2.31s/it]
 17%|█▋        | 597/3566 [23:59<1:53:08,  2.29s/it]
                                                    
{'loss': 1.5721, 'learning_rate': 0.0003800474453380653, 'epoch': 0.17}

 17%|█▋        | 597/3566 [23:59<1:53:08,  2.29s/it]
 17%|█▋        | 598/3566 [24:02<1:55:55,  2.34s/it]
                                                    
{'loss': 1.6086, 'learning_rate': 0.0003799684418655055, 'epoch': 0.17}

 17%|█▋        | 598/3566 [24:02<1:55:55,  2.34s/it]
 17%|█▋        | 599/3566 [24:04<1:53:13,  2.29s/it]
                                                    
{'loss': 1.4927, 'learning_rate': 0.00037988929053694477, 'epoch': 0.17}

 17%|█▋        | 599/3566 [24:04<1:53:13,  2.29s/it]
 17%|█▋        | 600/3566 [24:07<2:03:01,  2.49s/it]
                                                    
{'loss': 1.7234, 'learning_rate': 0.0003798099914174112, 'epoch': 0.17}

 17%|█▋        | 600/3566 [24:07<2:03:01,  2.49s/it]
 17%|█▋        | 601/3566 [24:09<1:59:10,  2.41s/it]
                                                    
{'loss': 1.7057, 'learning_rate': 0.0003797305445720543, 'epoch': 0.17}

 17%|█▋        | 601/3566 [24:09<1:59:10,  2.41s/it]
 17%|█▋        | 602/3566 [24:12<2:01:18,  2.46s/it]
                                                    
{'loss': 1.7821, 'learning_rate': 0.0003796509500661449, 'epoch': 0.17}

 17%|█▋        | 602/3566 [24:12<2:01:18,  2.46s/it]
 17%|█▋        | 603/3566 [24:14<2:00:00,  2.43s/it]
                                                    
{'loss': 1.7239, 'learning_rate': 0.00037957120796507516, 'epoch': 0.17}

 17%|█▋        | 603/3566 [24:14<2:00:00,  2.43s/it]
 17%|█▋        | 604/3566 [24:17<1:57:47,  2.39s/it]
                                                    
{'loss': 1.5739, 'learning_rate': 0.00037949131833435847, 'epoch': 0.17}

 17%|█▋        | 604/3566 [24:17<1:57:47,  2.39s/it]
 17%|█▋        | 605/3566 [24:19<2:03:30,  2.50s/it]
                                                    
{'loss': 1.6795, 'learning_rate': 0.0003794112812396295, 'epoch': 0.17}

 17%|█▋        | 605/3566 [24:19<2:03:30,  2.50s/it]
 17%|█▋        | 606/3566 [24:22<2:01:24,  2.46s/it]
                                                    
{'loss': 1.5626, 'learning_rate': 0.000379331096746644, 'epoch': 0.17}

 17%|█▋        | 606/3566 [24:22<2:01:24,  2.46s/it]
 17%|█▋        | 607/3566 [24:24<2:04:40,  2.53s/it]
                                                    
{'loss': 1.6654, 'learning_rate': 0.00037925076492127885, 'epoch': 0.17}

 17%|█▋        | 607/3566 [24:24<2:04:40,  2.53s/it]
 17%|█▋        | 608/3566 [24:27<2:02:25,  2.48s/it]
                                                    
{'loss': 1.7856, 'learning_rate': 0.00037917028582953204, 'epoch': 0.17}

 17%|█▋        | 608/3566 [24:27<2:02:25,  2.48s/it]
 17%|█▋        | 609/3566 [24:29<1:59:08,  2.42s/it]
                                                    
{'loss': 1.5479, 'learning_rate': 0.0003790896595375223, 'epoch': 0.17}

 17%|█▋        | 609/3566 [24:29<1:59:08,  2.42s/it]
 17%|█▋        | 610/3566 [24:31<1:58:13,  2.40s/it]
                                                    
{'loss': 1.6803, 'learning_rate': 0.0003790088861114897, 'epoch': 0.17}

 17%|█▋        | 610/3566 [24:31<1:58:13,  2.40s/it]
 17%|█▋        | 611/3566 [24:34<1:59:19,  2.42s/it]
                                                    
{'loss': 1.7133, 'learning_rate': 0.00037892796561779475, 'epoch': 0.17}

 17%|█▋        | 611/3566 [24:34<1:59:19,  2.42s/it]
 17%|█▋        | 612/3566 [24:36<1:55:28,  2.35s/it]
                                                    
{'loss': 1.6756, 'learning_rate': 0.00037884689812291915, 'epoch': 0.17}

 17%|█▋        | 612/3566 [24:36<1:55:28,  2.35s/it]
 17%|█▋        | 613/3566 [24:39<2:01:20,  2.47s/it]
                                                    
{'loss': 1.6747, 'learning_rate': 0.00037876568369346505, 'epoch': 0.17}

 17%|█▋        | 613/3566 [24:39<2:01:20,  2.47s/it]
 17%|█▋        | 614/3566 [24:41<2:00:31,  2.45s/it]
                                                    
{'loss': 1.6242, 'learning_rate': 0.00037868432239615573, 'epoch': 0.17}

 17%|█▋        | 614/3566 [24:41<2:00:31,  2.45s/it]
 17%|█▋        | 615/3566 [24:44<1:59:54,  2.44s/it]
                                                    
{'loss': 1.5968, 'learning_rate': 0.0003786028142978347, 'epoch': 0.17}

 17%|█▋        | 615/3566 [24:44<1:59:54,  2.44s/it]
 17%|█▋        | 616/3566 [24:46<2:02:48,  2.50s/it]
                                                    
{'loss': 1.7603, 'learning_rate': 0.00037852115946546627, 'epoch': 0.17}

 17%|█▋        | 616/3566 [24:46<2:02:48,  2.50s/it]
 17%|█▋        | 617/3566 [24:49<2:02:07,  2.48s/it]
                                                    
{'loss': 1.5431, 'learning_rate': 0.0003784393579661354, 'epoch': 0.17}

 17%|█▋        | 617/3566 [24:49<2:02:07,  2.48s/it]
 17%|█▋        | 618/3566 [24:51<2:01:42,  2.48s/it]
                                                    
{'loss': 1.5807, 'learning_rate': 0.00037835740986704743, 'epoch': 0.17}

 17%|█▋        | 618/3566 [24:51<2:01:42,  2.48s/it]
 17%|█▋        | 619/3566 [24:54<2:14:01,  2.73s/it]
                                                    
{'loss': 1.6421, 'learning_rate': 0.0003782753152355281, 'epoch': 0.17}

 17%|█▋        | 619/3566 [24:54<2:14:01,  2.73s/it]
 17%|█▋        | 620/3566 [24:57<2:11:02,  2.67s/it]
                                                    
{'loss': 1.5383, 'learning_rate': 0.00037819307413902345, 'epoch': 0.17}

 17%|█▋        | 620/3566 [24:57<2:11:02,  2.67s/it]
 17%|█▋        | 621/3566 [24:59<2:05:20,  2.55s/it]
                                                    
{'loss': 1.5435, 'learning_rate': 0.0003781106866451003, 'epoch': 0.17}

 17%|█▋        | 621/3566 [24:59<2:05:20,  2.55s/it]
 17%|█▋        | 622/3566 [25:02<2:01:52,  2.48s/it]
                                                    
{'loss': 1.6208, 'learning_rate': 0.00037802815282144526, 'epoch': 0.17}

 17%|█▋        | 622/3566 [25:02<2:01:52,  2.48s/it]
 17%|█▋        | 623/3566 [25:04<2:01:05,  2.47s/it]
                                                    
{'loss': 1.6295, 'learning_rate': 0.0003779454727358653, 'epoch': 0.17}

 17%|█▋        | 623/3566 [25:04<2:01:05,  2.47s/it]
 17%|█▋        | 624/3566 [25:06<1:59:00,  2.43s/it]
                                                    
{'loss': 1.5912, 'learning_rate': 0.00037786264645628767, 'epoch': 0.17}

 17%|█▋        | 624/3566 [25:06<1:59:00,  2.43s/it]
 18%|█▊        | 625/3566 [25:09<1:57:30,  2.40s/it]
                                                    
{'loss': 1.5793, 'learning_rate': 0.00037777967405075956, 'epoch': 0.18}

 18%|█▊        | 625/3566 [25:09<1:57:30,  2.40s/it]
 18%|█▊        | 626/3566 [25:11<1:56:03,  2.37s/it]
                                                    
{'loss': 1.7148, 'learning_rate': 0.0003776965555874484, 'epoch': 0.18}

 18%|█▊        | 626/3566 [25:11<1:56:03,  2.37s/it]
 18%|█▊        | 627/3566 [25:13<1:57:25,  2.40s/it]
                                                    
{'loss': 1.6304, 'learning_rate': 0.0003776132911346415, 'epoch': 0.18}

 18%|█▊        | 627/3566 [25:13<1:57:25,  2.40s/it]
 18%|█▊        | 628/3566 [25:16<1:57:12,  2.39s/it]
                                                    
{'loss': 1.6453, 'learning_rate': 0.00037752988076074606, 'epoch': 0.18}

 18%|█▊        | 628/3566 [25:16<1:57:12,  2.39s/it]
 18%|█▊        | 629/3566 [25:18<1:57:04,  2.39s/it]
                                                    
{'loss': 1.7158, 'learning_rate': 0.0003774463245342893, 'epoch': 0.18}

 18%|█▊        | 629/3566 [25:18<1:57:04,  2.39s/it]
 18%|█▊        | 630/3566 [25:21<1:56:13,  2.38s/it]
                                                    
{'loss': 1.4112, 'learning_rate': 0.00037736262252391817, 'epoch': 0.18}

 18%|█▊        | 630/3566 [25:21<1:56:13,  2.38s/it]
 18%|█▊        | 631/3566 [25:23<1:55:52,  2.37s/it]
                                                    
{'loss': 1.6531, 'learning_rate': 0.0003772787747983993, 'epoch': 0.18}

 18%|█▊        | 631/3566 [25:23<1:55:52,  2.37s/it]
 18%|█▊        | 632/3566 [25:25<1:56:29,  2.38s/it]
                                                    
{'loss': 1.5022, 'learning_rate': 0.0003771947814266194, 'epoch': 0.18}

 18%|█▊        | 632/3566 [25:25<1:56:29,  2.38s/it]
 18%|█▊        | 633/3566 [25:28<2:02:43,  2.51s/it]
                                                    
{'loss': 1.7515, 'learning_rate': 0.0003771106424775844, 'epoch': 0.18}

 18%|█▊        | 633/3566 [25:28<2:02:43,  2.51s/it]
 18%|█▊        | 634/3566 [25:31<2:03:38,  2.53s/it]
                                                    
{'loss': 1.684, 'learning_rate': 0.00037702635802042015, 'epoch': 0.18}

 18%|█▊        | 634/3566 [25:31<2:03:38,  2.53s/it]
 18%|█▊        | 635/3566 [25:33<2:01:01,  2.48s/it]
                                                    
{'loss': 1.5281, 'learning_rate': 0.00037694192812437173, 'epoch': 0.18}

 18%|█▊        | 635/3566 [25:33<2:01:01,  2.48s/it]
 18%|█▊        | 636/3566 [25:35<1:59:12,  2.44s/it]
                                                    
{'loss': 1.8032, 'learning_rate': 0.0003768573528588041, 'epoch': 0.18}

 18%|█▊        | 636/3566 [25:35<1:59:12,  2.44s/it]
 18%|█▊        | 637/3566 [25:38<1:59:38,  2.45s/it]
                                                    
{'loss': 1.457, 'learning_rate': 0.0003767726322932013, 'epoch': 0.18}

 18%|█▊        | 637/3566 [25:38<1:59:38,  2.45s/it]
 18%|█▊        | 638/3566 [25:40<1:57:18,  2.40s/it]
                                                    
{'loss': 1.584, 'learning_rate': 0.00037668776649716696, 'epoch': 0.18}

 18%|█▊        | 638/3566 [25:40<1:57:18,  2.40s/it]
 18%|█▊        | 639/3566 [25:42<1:55:45,  2.37s/it]
                                                    
{'loss': 1.5261, 'learning_rate': 0.0003766027555404239, 'epoch': 0.18}

 18%|█▊        | 639/3566 [25:42<1:55:45,  2.37s/it]
 18%|█▊        | 640/3566 [25:45<1:56:10,  2.38s/it]
                                                    
{'loss': 1.7317, 'learning_rate': 0.00037651759949281437, 'epoch': 0.18}

 18%|█▊        | 640/3566 [25:45<1:56:10,  2.38s/it]
 18%|█▊        | 641/3566 [25:47<1:57:03,  2.40s/it]
                                                    
{'loss': 1.5849, 'learning_rate': 0.0003764322984242996, 'epoch': 0.18}

 18%|█▊        | 641/3566 [25:47<1:57:03,  2.40s/it]
 18%|█▊        | 642/3566 [25:50<1:55:59,  2.38s/it]
                                                    
{'loss': 1.4775, 'learning_rate': 0.0003763468524049601, 'epoch': 0.18}

 18%|█▊        | 642/3566 [25:50<1:55:59,  2.38s/it]
 18%|█▊        | 643/3566 [25:52<1:56:26,  2.39s/it]
                                                    
{'loss': 1.7729, 'learning_rate': 0.00037626126150499547, 'epoch': 0.18}

 18%|█▊        | 643/3566 [25:52<1:56:26,  2.39s/it]
 18%|█▊        | 644/3566 [25:55<1:58:17,  2.43s/it]
                                                    
{'loss': 1.7641, 'learning_rate': 0.00037617552579472424, 'epoch': 0.18}

 18%|█▊        | 644/3566 [25:55<1:58:17,  2.43s/it]
 18%|█▊        | 645/3566 [25:57<1:54:58,  2.36s/it]
                                                    
{'loss': 1.6569, 'learning_rate': 0.000376089645344584, 'epoch': 0.18}

 18%|█▊        | 645/3566 [25:57<1:54:58,  2.36s/it]
 18%|█▊        | 646/3566 [25:59<1:51:27,  2.29s/it]
                                                    
{'loss': 1.6777, 'learning_rate': 0.0003760036202251312, 'epoch': 0.18}

 18%|█▊        | 646/3566 [25:59<1:51:27,  2.29s/it]
 18%|█▊        | 647/3566 [26:01<1:52:16,  2.31s/it]
                                                    
{'loss': 1.5653, 'learning_rate': 0.0003759174505070413, 'epoch': 0.18}

 18%|█▊        | 647/3566 [26:01<1:52:16,  2.31s/it]
 18%|█▊        | 648/3566 [26:04<1:52:52,  2.32s/it]
                                                    
{'loss': 1.6499, 'learning_rate': 0.0003758311362611083, 'epoch': 0.18}

 18%|█▊        | 648/3566 [26:04<1:52:52,  2.32s/it]
 18%|█▊        | 649/3566 [26:06<1:53:07,  2.33s/it]
                                                    
{'loss': 1.6806, 'learning_rate': 0.00037574467755824515, 'epoch': 0.18}

 18%|█▊        | 649/3566 [26:06<1:53:07,  2.33s/it]
 18%|█▊        | 650/3566 [26:09<1:56:36,  2.40s/it]
                                                    
{'loss': 1.5205, 'learning_rate': 0.00037565807446948344, 'epoch': 0.18}

 18%|█▊        | 650/3566 [26:09<1:56:36,  2.40s/it]
 18%|█▊        | 651/3566 [26:11<1:57:31,  2.42s/it]
                                                    
{'loss': 1.6806, 'learning_rate': 0.0003755713270659732, 'epoch': 0.18}

 18%|█▊        | 651/3566 [26:11<1:57:31,  2.42s/it]
 18%|█▊        | 652/3566 [26:13<1:55:30,  2.38s/it]
                                                    
{'loss': 1.7035, 'learning_rate': 0.00037548443541898324, 'epoch': 0.18}

 18%|█▊        | 652/3566 [26:13<1:55:30,  2.38s/it]
 18%|█▊        | 653/3566 [26:15<1:53:01,  2.33s/it]
                                                    
{'loss': 1.6304, 'learning_rate': 0.0003753973995999009, 'epoch': 0.18}

 18%|█▊        | 653/3566 [26:15<1:53:01,  2.33s/it]
 18%|█▊        | 654/3566 [26:18<1:59:03,  2.45s/it]
                                                    
{'loss': 1.6656, 'learning_rate': 0.00037531021968023175, 'epoch': 0.18}

 18%|█▊        | 654/3566 [26:18<1:59:03,  2.45s/it]
 18%|█▊        | 655/3566 [26:21<2:01:05,  2.50s/it]
                                                    
{'loss': 1.5005, 'learning_rate': 0.0003752228957315999, 'epoch': 0.18}

 18%|█▊        | 655/3566 [26:21<2:01:05,  2.50s/it]
 18%|█▊        | 656/3566 [26:23<1:58:11,  2.44s/it]
                                                    
{'loss': 1.5847, 'learning_rate': 0.0003751354278257478, 'epoch': 0.18}

 18%|█▊        | 656/3566 [26:23<1:58:11,  2.44s/it]
 18%|█▊        | 657/3566 [26:25<1:56:45,  2.41s/it]
                                                    
{'loss': 1.5535, 'learning_rate': 0.0003750478160345361, 'epoch': 0.18}

 18%|█▊        | 657/3566 [26:25<1:56:45,  2.41s/it]
 18%|█▊        | 658/3566 [26:28<1:56:32,  2.40s/it]
                                                    
{'loss': 1.544, 'learning_rate': 0.0003749600604299437, 'epoch': 0.18}

 18%|█▊        | 658/3566 [26:28<1:56:32,  2.40s/it]
 18%|█▊        | 659/3566 [26:30<1:59:16,  2.46s/it]
                                                    
{'loss': 1.7352, 'learning_rate': 0.00037487216108406763, 'epoch': 0.18}

 18%|█▊        | 659/3566 [26:30<1:59:16,  2.46s/it]
 19%|█▊        | 660/3566 [26:33<1:55:43,  2.39s/it]
                                                    
{'loss': 1.5405, 'learning_rate': 0.000374784118069123, 'epoch': 0.19}

 19%|█▊        | 660/3566 [26:33<1:55:43,  2.39s/it]
 19%|█▊        | 661/3566 [26:35<1:57:17,  2.42s/it]
                                                    
{'loss': 1.7449, 'learning_rate': 0.0003746959314574431, 'epoch': 0.19}

 19%|█▊        | 661/3566 [26:35<1:57:17,  2.42s/it]
 19%|█▊        | 662/3566 [26:38<1:56:38,  2.41s/it]
                                                    
{'loss': 1.5527, 'learning_rate': 0.000374607601321479, 'epoch': 0.19}

 19%|█▊        | 662/3566 [26:38<1:56:38,  2.41s/it]
 19%|█▊        | 663/3566 [26:40<1:57:33,  2.43s/it]
                                                    
{'loss': 1.6157, 'learning_rate': 0.00037451912773379974, 'epoch': 0.19}

 19%|█▊        | 663/3566 [26:40<1:57:33,  2.43s/it]
 19%|█▊        | 664/3566 [26:42<1:55:18,  2.38s/it]
                                                    
{'loss': 1.5348, 'learning_rate': 0.0003744305107670922, 'epoch': 0.19}

 19%|█▊        | 664/3566 [26:42<1:55:18,  2.38s/it]
 19%|█▊        | 665/3566 [26:45<1:56:02,  2.40s/it]
                                                    
{'loss': 1.5841, 'learning_rate': 0.00037434175049416116, 'epoch': 0.19}

 19%|█▊        | 665/3566 [26:45<1:56:02,  2.40s/it]
 19%|█▊        | 666/3566 [26:47<1:55:05,  2.38s/it]
                                                    
{'loss': 1.5098, 'learning_rate': 0.00037425284698792906, 'epoch': 0.19}

 19%|█▊        | 666/3566 [26:47<1:55:05,  2.38s/it]
 19%|█▊        | 667/3566 [26:49<1:51:44,  2.31s/it]
                                                    
{'loss': 1.6932, 'learning_rate': 0.0003741638003214361, 'epoch': 0.19}

 19%|█▊        | 667/3566 [26:49<1:51:44,  2.31s/it]
 19%|█▊        | 668/3566 [26:52<1:56:41,  2.42s/it]
                                                    
{'loss': 1.6092, 'learning_rate': 0.0003740746105678398, 'epoch': 0.19}

 19%|█▊        | 668/3566 [26:52<1:56:41,  2.42s/it]
 19%|█▉        | 669/3566 [26:54<1:55:28,  2.39s/it]
                                                    
{'loss': 1.6698, 'learning_rate': 0.0003739852778004156, 'epoch': 0.19}

 19%|█▉        | 669/3566 [26:54<1:55:28,  2.39s/it]
 19%|█▉        | 670/3566 [26:56<1:52:29,  2.33s/it]
                                                    
{'loss': 1.5511, 'learning_rate': 0.0003738958020925563, 'epoch': 0.19}

 19%|█▉        | 670/3566 [26:56<1:52:29,  2.33s/it]
 19%|█▉        | 671/3566 [26:59<1:56:44,  2.42s/it]
                                                    
{'loss': 1.5249, 'learning_rate': 0.0003738061835177721, 'epoch': 0.19}

 19%|█▉        | 671/3566 [26:59<1:56:44,  2.42s/it]
 19%|█▉        | 672/3566 [27:01<1:56:26,  2.41s/it]
                                                    
{'loss': 1.6848, 'learning_rate': 0.0003737164221496906, 'epoch': 0.19}

 19%|█▉        | 672/3566 [27:01<1:56:26,  2.41s/it]
 19%|█▉        | 673/3566 [27:04<1:53:40,  2.36s/it]
                                                    
{'loss': 1.6778, 'learning_rate': 0.00037362651806205664, 'epoch': 0.19}

 19%|█▉        | 673/3566 [27:04<1:53:40,  2.36s/it]
 19%|█▉        | 674/3566 [27:06<1:52:47,  2.34s/it]
                                                    
{'loss': 1.6821, 'learning_rate': 0.0003735364713287325, 'epoch': 0.19}

 19%|█▉        | 674/3566 [27:06<1:52:47,  2.34s/it]
 19%|█▉        | 675/3566 [27:08<1:52:37,  2.34s/it]
                                                    
{'loss': 1.6008, 'learning_rate': 0.00037344628202369746, 'epoch': 0.19}

 19%|█▉        | 675/3566 [27:08<1:52:37,  2.34s/it]
 19%|█▉        | 676/3566 [27:11<1:53:55,  2.37s/it]
                                                    
{'loss': 1.6035, 'learning_rate': 0.0003733559502210481, 'epoch': 0.19}

 19%|█▉        | 676/3566 [27:11<1:53:55,  2.37s/it]
 19%|█▉        | 677/3566 [27:13<1:54:53,  2.39s/it]
                                                    
{'loss': 1.6969, 'learning_rate': 0.0003732654759949978, 'epoch': 0.19}

 19%|█▉        | 677/3566 [27:13<1:54:53,  2.39s/it]
 19%|█▉        | 678/3566 [27:15<1:51:46,  2.32s/it]
                                                    
{'loss': 1.5471, 'learning_rate': 0.0003731748594198774, 'epoch': 0.19}

 19%|█▉        | 678/3566 [27:15<1:51:46,  2.32s/it]
 19%|█▉        | 679/3566 [27:18<1:51:12,  2.31s/it]
                                                    
{'loss': 1.5921, 'learning_rate': 0.0003730841005701342, 'epoch': 0.19}

 19%|█▉        | 679/3566 [27:18<1:51:12,  2.31s/it]
 19%|█▉        | 680/3566 [27:20<1:57:24,  2.44s/it]
                                                    
{'loss': 1.7005, 'learning_rate': 0.00037299319952033256, 'epoch': 0.19}

 19%|█▉        | 680/3566 [27:20<1:57:24,  2.44s/it]
 19%|█▉        | 681/3566 [27:23<1:54:18,  2.38s/it]
                                                    
{'loss': 1.6051, 'learning_rate': 0.00037290215634515404, 'epoch': 0.19}

 19%|█▉        | 681/3566 [27:23<1:54:18,  2.38s/it]
 19%|█▉        | 682/3566 [27:25<1:54:46,  2.39s/it]
                                                    
{'loss': 1.6601, 'learning_rate': 0.00037281097111939633, 'epoch': 0.19}

 19%|█▉        | 682/3566 [27:25<1:54:46,  2.39s/it]
 19%|█▉        | 683/3566 [27:27<1:55:42,  2.41s/it]
                                                    
{'loss': 1.6737, 'learning_rate': 0.0003727196439179742, 'epoch': 0.19}

 19%|█▉        | 683/3566 [27:27<1:55:42,  2.41s/it]
 19%|█▉        | 684/3566 [27:30<1:54:29,  2.38s/it]
                                                    
{'loss': 1.6409, 'learning_rate': 0.00037262817481591913, 'epoch': 0.19}

 19%|█▉        | 684/3566 [27:30<1:54:29,  2.38s/it]
 19%|█▉        | 685/3566 [27:32<1:55:09,  2.40s/it]
                                                    
{'loss': 1.6214, 'learning_rate': 0.00037253656388837894, 'epoch': 0.19}

 19%|█▉        | 685/3566 [27:32<1:55:09,  2.40s/it]
 19%|█▉        | 686/3566 [27:35<1:54:56,  2.39s/it]
                                                    
{'loss': 1.663, 'learning_rate': 0.00037244481121061814, 'epoch': 0.19}

 19%|█▉        | 686/3566 [27:35<1:54:56,  2.39s/it]
 19%|█▉        | 687/3566 [27:37<1:51:05,  2.32s/it]
                                                    
{'loss': 1.5129, 'learning_rate': 0.0003723529168580175, 'epoch': 0.19}

 19%|█▉        | 687/3566 [27:37<1:51:05,  2.32s/it]
 19%|█▉        | 688/3566 [27:39<1:49:41,  2.29s/it]
                                                    
{'loss': 1.6899, 'learning_rate': 0.0003722608809060745, 'epoch': 0.19}

 19%|█▉        | 688/3566 [27:39<1:49:41,  2.29s/it]
 19%|█▉        | 689/3566 [27:41<1:51:50,  2.33s/it]
                                                    
{'loss': 1.6275, 'learning_rate': 0.00037216870343040266, 'epoch': 0.19}

 19%|█▉        | 689/3566 [27:41<1:51:50,  2.33s/it]
 19%|█▉        | 690/3566 [27:44<1:55:52,  2.42s/it]
                                                    
{'loss': 1.6723, 'learning_rate': 0.00037207638450673184, 'epoch': 0.19}

 19%|█▉        | 690/3566 [27:44<1:55:52,  2.42s/it]
 19%|█▉        | 691/3566 [27:46<1:54:27,  2.39s/it]
                                                    
{'loss': 1.6748, 'learning_rate': 0.0003719839242109083, 'epoch': 0.19}

 19%|█▉        | 691/3566 [27:46<1:54:27,  2.39s/it]
 19%|█▉        | 692/3566 [27:49<1:52:47,  2.35s/it]
                                                    
{'loss': 1.5452, 'learning_rate': 0.0003718913226188942, 'epoch': 0.19}

 19%|█▉        | 692/3566 [27:49<1:52:47,  2.35s/it]
 19%|█▉        | 693/3566 [27:51<1:50:02,  2.30s/it]
                                                    
{'loss': 1.572, 'learning_rate': 0.0003717985798067679, 'epoch': 0.19}

 19%|█▉        | 693/3566 [27:51<1:50:02,  2.30s/it]
 19%|█▉        | 694/3566 [27:53<1:53:17,  2.37s/it]
                                                    
{'loss': 1.6967, 'learning_rate': 0.00037170569585072384, 'epoch': 0.19}

 19%|█▉        | 694/3566 [27:53<1:53:17,  2.37s/it]
 19%|█▉        | 695/3566 [27:56<1:51:41,  2.33s/it]
                                                    
{'loss': 1.555, 'learning_rate': 0.00037161267082707223, 'epoch': 0.19}

 19%|█▉        | 695/3566 [27:56<1:51:41,  2.33s/it]
 20%|█▉        | 696/3566 [27:58<1:55:08,  2.41s/it]
                                                    
{'loss': 1.6263, 'learning_rate': 0.0003715195048122394, 'epoch': 0.2}

 20%|█▉        | 696/3566 [27:58<1:55:08,  2.41s/it]
 20%|█▉        | 697/3566 [28:00<1:54:11,  2.39s/it]
                                                    
{'loss': 1.604, 'learning_rate': 0.0003714261978827673, 'epoch': 0.2}

 20%|█▉        | 697/3566 [28:00<1:54:11,  2.39s/it]
 20%|█▉        | 698/3566 [28:03<2:02:06,  2.55s/it]
                                                    
{'loss': 1.5761, 'learning_rate': 0.00037133275011531376, 'epoch': 0.2}

 20%|█▉        | 698/3566 [28:03<2:02:06,  2.55s/it]
 20%|█▉        | 699/3566 [28:06<1:59:57,  2.51s/it]
                                                    
{'loss': 1.747, 'learning_rate': 0.0003712391615866524, 'epoch': 0.2}

 20%|█▉        | 699/3566 [28:06<1:59:57,  2.51s/it]
 20%|█▉        | 700/3566 [28:08<1:55:39,  2.42s/it]
                                                    
{'loss': 1.4509, 'learning_rate': 0.00037114543237367237, 'epoch': 0.2}

 20%|█▉        | 700/3566 [28:08<1:55:39,  2.42s/it]
 20%|█▉        | 701/3566 [28:10<1:54:22,  2.40s/it]
                                                    
{'loss': 1.4426, 'learning_rate': 0.00037105156255337835, 'epoch': 0.2}

 20%|█▉        | 701/3566 [28:10<1:54:22,  2.40s/it]
 20%|█▉        | 702/3566 [28:13<1:53:09,  2.37s/it]
                                                    
{'loss': 1.5841, 'learning_rate': 0.0003709575522028907, 'epoch': 0.2}

 20%|█▉        | 702/3566 [28:13<1:53:09,  2.37s/it]
 20%|█▉        | 703/3566 [28:15<1:58:04,  2.47s/it]
                                                    
{'loss': 1.6263, 'learning_rate': 0.0003708634013994452, 'epoch': 0.2}

 20%|█▉        | 703/3566 [28:15<1:58:04,  2.47s/it]
 20%|█▉        | 704/3566 [28:18<1:59:28,  2.50s/it]
                                                    
{'loss': 1.6031, 'learning_rate': 0.0003707691102203929, 'epoch': 0.2}

 20%|█▉        | 704/3566 [28:18<1:59:28,  2.50s/it]
 20%|█▉        | 705/3566 [28:20<1:56:53,  2.45s/it]
                                                    
{'loss': 1.583, 'learning_rate': 0.00037067467874320024, 'epoch': 0.2}

 20%|█▉        | 705/3566 [28:20<1:56:53,  2.45s/it]
 20%|█▉        | 706/3566 [28:23<1:53:44,  2.39s/it]
                                                    
{'loss': 1.6128, 'learning_rate': 0.0003705801070454489, 'epoch': 0.2}

 20%|█▉        | 706/3566 [28:23<1:53:44,  2.39s/it]
 20%|█▉        | 707/3566 [28:25<1:51:05,  2.33s/it]
                                                    
{'loss': 1.3901, 'learning_rate': 0.0003704853952048359, 'epoch': 0.2}

 20%|█▉        | 707/3566 [28:25<1:51:05,  2.33s/it]
 20%|█▉        | 708/3566 [28:27<1:50:23,  2.32s/it]
                                                    
{'loss': 1.5793, 'learning_rate': 0.00037039054329917324, 'epoch': 0.2}

 20%|█▉        | 708/3566 [28:27<1:50:23,  2.32s/it]
 20%|█▉        | 709/3566 [28:29<1:49:37,  2.30s/it]
                                                    
{'loss': 1.5687, 'learning_rate': 0.0003702955514063881, 'epoch': 0.2}

 20%|█▉        | 709/3566 [28:29<1:49:37,  2.30s/it]
 20%|█▉        | 710/3566 [28:32<1:50:16,  2.32s/it]
                                                    
{'loss': 1.6644, 'learning_rate': 0.0003702004196045225, 'epoch': 0.2}

 20%|█▉        | 710/3566 [28:32<1:50:16,  2.32s/it]
 20%|█▉        | 711/3566 [28:34<1:49:38,  2.30s/it]
                                                    
{'loss': 1.5907, 'learning_rate': 0.0003701051479717336, 'epoch': 0.2}

 20%|█▉        | 711/3566 [28:34<1:49:38,  2.30s/it]
 20%|█▉        | 712/3566 [28:36<1:51:55,  2.35s/it]
                                                    
{'loss': 1.5606, 'learning_rate': 0.00037000973658629334, 'epoch': 0.2}

 20%|█▉        | 712/3566 [28:36<1:51:55,  2.35s/it]
 20%|█▉        | 713/3566 [28:39<1:50:18,  2.32s/it]
                                                    
{'loss': 1.6814, 'learning_rate': 0.0003699141855265886, 'epoch': 0.2}

 20%|█▉        | 713/3566 [28:39<1:50:18,  2.32s/it]
 20%|██        | 714/3566 [28:41<1:53:12,  2.38s/it]
                                                    
{'loss': 1.6013, 'learning_rate': 0.0003698184948711207, 'epoch': 0.2}

 20%|██        | 714/3566 [28:41<1:53:12,  2.38s/it]
 20%|██        | 715/3566 [28:44<1:54:05,  2.40s/it]
                                                    
{'loss': 1.6585, 'learning_rate': 0.00036972266469850593, 'epoch': 0.2}

 20%|██        | 715/3566 [28:44<1:54:05,  2.40s/it]
 20%|██        | 716/3566 [28:46<1:51:36,  2.35s/it]
                                                    
{'loss': 1.6623, 'learning_rate': 0.0003696266950874753, 'epoch': 0.2}

 20%|██        | 716/3566 [28:46<1:51:36,  2.35s/it]
 20%|██        | 717/3566 [28:48<1:53:16,  2.39s/it]
                                                    
{'loss': 1.5937, 'learning_rate': 0.00036953058611687397, 'epoch': 0.2}

 20%|██        | 717/3566 [28:48<1:53:16,  2.39s/it]
 20%|██        | 718/3566 [28:51<1:51:14,  2.34s/it]
                                                    
{'loss': 1.6727, 'learning_rate': 0.0003694343378656619, 'epoch': 0.2}

 20%|██        | 718/3566 [28:51<1:51:14,  2.34s/it]
 20%|██        | 719/3566 [28:53<1:50:30,  2.33s/it]
                                                    
{'loss': 1.7429, 'learning_rate': 0.00036933795041291354, 'epoch': 0.2}

 20%|██        | 719/3566 [28:53<1:50:30,  2.33s/it]
 20%|██        | 720/3566 [28:55<1:47:09,  2.26s/it]
                                                    
{'loss': 1.772, 'learning_rate': 0.00036924142383781735, 'epoch': 0.2}

 20%|██        | 720/3566 [28:55<1:47:09,  2.26s/it]
 20%|██        | 721/3566 [28:57<1:45:26,  2.22s/it]
                                                    
{'loss': 1.6947, 'learning_rate': 0.0003691447582196765, 'epoch': 0.2}

 20%|██        | 721/3566 [28:57<1:45:26,  2.22s/it]
 20%|██        | 722/3566 [28:59<1:45:16,  2.22s/it]
                                                    
{'loss': 1.8246, 'learning_rate': 0.00036904795363790807, 'epoch': 0.2}

 20%|██        | 722/3566 [28:59<1:45:16,  2.22s/it]
 20%|██        | 723/3566 [29:01<1:44:30,  2.21s/it]
                                                    
{'loss': 1.7672, 'learning_rate': 0.00036895101017204345, 'epoch': 0.2}

 20%|██        | 723/3566 [29:01<1:44:30,  2.21s/it]
 20%|██        | 724/3566 [29:04<1:45:20,  2.22s/it]
                                                    
{'loss': 1.5733, 'learning_rate': 0.00036885392790172826, 'epoch': 0.2}

 20%|██        | 724/3566 [29:04<1:45:20,  2.22s/it]
 20%|██        | 725/3566 [29:06<1:45:57,  2.24s/it]
                                                    
{'loss': 1.5593, 'learning_rate': 0.00036875670690672183, 'epoch': 0.2}

 20%|██        | 725/3566 [29:06<1:45:57,  2.24s/it]
 20%|██        | 726/3566 [29:09<1:49:58,  2.32s/it]
                                                    
{'loss': 1.8336, 'learning_rate': 0.0003686593472668978, 'epoch': 0.2}

 20%|██        | 726/3566 [29:09<1:49:58,  2.32s/it]
 20%|██        | 727/3566 [29:11<1:48:16,  2.29s/it]
                                                    
{'loss': 1.5559, 'learning_rate': 0.00036856184906224347, 'epoch': 0.2}

 20%|██        | 727/3566 [29:11<1:48:16,  2.29s/it]
 20%|██        | 728/3566 [29:13<1:46:50,  2.26s/it]
                                                    
{'loss': 1.6823, 'learning_rate': 0.0003684642123728601, 'epoch': 0.2}

 20%|██        | 728/3566 [29:13<1:46:50,  2.26s/it]
 20%|██        | 729/3566 [29:15<1:45:58,  2.24s/it]
                                                    
{'loss': 1.442, 'learning_rate': 0.00036836643727896273, 'epoch': 0.2}

 20%|██        | 729/3566 [29:15<1:45:58,  2.24s/it]
 20%|██        | 730/3566 [29:20<2:17:12,  2.90s/it]
                                                    
{'loss': 1.7233, 'learning_rate': 0.00036826852386088007, 'epoch': 0.2}

 20%|██        | 730/3566 [29:20<2:17:12,  2.90s/it]
 20%|██        | 731/3566 [29:22<2:13:58,  2.84s/it]
                                                    
{'loss': 1.6053, 'learning_rate': 0.00036817047219905446, 'epoch': 0.2}

 20%|██        | 731/3566 [29:22<2:13:58,  2.84s/it]
 21%|██        | 732/3566 [29:24<2:05:40,  2.66s/it]
                                                    
{'loss': 1.6173, 'learning_rate': 0.00036807228237404184, 'epoch': 0.21}

 21%|██        | 732/3566 [29:24<2:05:40,  2.66s/it]
 21%|██        | 733/3566 [29:27<2:05:31,  2.66s/it]
                                                    
{'loss': 1.6574, 'learning_rate': 0.00036797395446651164, 'epoch': 0.21}

 21%|██        | 733/3566 [29:27<2:05:31,  2.66s/it]
 21%|██        | 734/3566 [29:29<2:00:59,  2.56s/it]
                                                    
{'loss': 1.6933, 'learning_rate': 0.00036787548855724683, 'epoch': 0.21}

 21%|██        | 734/3566 [29:29<2:00:59,  2.56s/it]
 21%|██        | 735/3566 [29:32<1:55:06,  2.44s/it]
                                                    
{'loss': 1.5255, 'learning_rate': 0.00036777688472714365, 'epoch': 0.21}

 21%|██        | 735/3566 [29:32<1:55:06,  2.44s/it]
 21%|██        | 736/3566 [29:34<1:55:24,  2.45s/it]
                                                    
{'loss': 1.6014, 'learning_rate': 0.0003676781430572116, 'epoch': 0.21}

 21%|██        | 736/3566 [29:34<1:55:24,  2.45s/it]
 21%|██        | 737/3566 [29:37<1:55:56,  2.46s/it]
                                                    
{'loss': 1.6, 'learning_rate': 0.00036757926362857355, 'epoch': 0.21}

 21%|██        | 737/3566 [29:37<1:55:56,  2.46s/it]
 21%|██        | 738/3566 [29:39<1:52:57,  2.40s/it]
                                                    
{'loss': 1.6416, 'learning_rate': 0.0003674802465224655, 'epoch': 0.21}

 21%|██        | 738/3566 [29:39<1:52:57,  2.40s/it]
 21%|██        | 739/3566 [29:41<1:55:01,  2.44s/it]
                                                    
{'loss': 1.6506, 'learning_rate': 0.00036738109182023665, 'epoch': 0.21}

 21%|██        | 739/3566 [29:41<1:55:01,  2.44s/it]
 21%|██        | 740/3566 [29:44<1:54:07,  2.42s/it]
                                                    
{'loss': 1.5477, 'learning_rate': 0.0003672817996033491, 'epoch': 0.21}

 21%|██        | 740/3566 [29:44<1:54:07,  2.42s/it]
 21%|██        | 741/3566 [29:46<1:58:17,  2.51s/it]
                                                    
{'loss': 1.3591, 'learning_rate': 0.0003671823699533779, 'epoch': 0.21}

 21%|██        | 741/3566 [29:46<1:58:17,  2.51s/it]
 21%|██        | 742/3566 [29:49<1:55:59,  2.46s/it]
                                                    
{'loss': 1.5883, 'learning_rate': 0.0003670828029520112, 'epoch': 0.21}

 21%|██        | 742/3566 [29:49<1:55:59,  2.46s/it]
 21%|██        | 743/3566 [29:51<1:52:20,  2.39s/it]
                                                    
{'loss': 1.6689, 'learning_rate': 0.00036698309868104986, 'epoch': 0.21}

 21%|██        | 743/3566 [29:51<1:52:20,  2.39s/it]
 21%|██        | 744/3566 [29:53<1:51:26,  2.37s/it]
                                                    
{'loss': 1.6483, 'learning_rate': 0.0003668832572224076, 'epoch': 0.21}

 21%|██        | 744/3566 [29:53<1:51:26,  2.37s/it]
 21%|██        | 745/3566 [29:56<1:51:46,  2.38s/it]
                                                    
{'loss': 1.5851, 'learning_rate': 0.00036678327865811067, 'epoch': 0.21}

 21%|██        | 745/3566 [29:56<1:51:46,  2.38s/it]
 21%|██        | 746/3566 [29:59<1:58:28,  2.52s/it]
                                                    
{'loss': 1.577, 'learning_rate': 0.0003666831630702982, 'epoch': 0.21}

 21%|██        | 746/3566 [29:59<1:58:28,  2.52s/it]
 21%|██        | 747/3566 [30:01<1:59:58,  2.55s/it]
                                                    
{'loss': 1.5954, 'learning_rate': 0.00036658291054122164, 'epoch': 0.21}

 21%|██        | 747/3566 [30:01<1:59:58,  2.55s/it]
 21%|██        | 748/3566 [30:04<1:58:43,  2.53s/it]
                                                    
{'loss': 1.4855, 'learning_rate': 0.00036648252115324524, 'epoch': 0.21}

 21%|██        | 748/3566 [30:04<1:58:43,  2.53s/it]
 21%|██        | 749/3566 [30:06<1:56:52,  2.49s/it]
                                                    
{'loss': 1.6042, 'learning_rate': 0.00036638199498884553, 'epoch': 0.21}

 21%|██        | 749/3566 [30:06<1:56:52,  2.49s/it]
 21%|██        | 750/3566 [30:09<1:56:18,  2.48s/it]
                                                    
{'loss': 1.6123, 'learning_rate': 0.00036628133213061136, 'epoch': 0.21}

 21%|██        | 750/3566 [30:09<1:56:18,  2.48s/it]
 21%|██        | 751/3566 [30:11<1:56:46,  2.49s/it]
                                                    
{'loss': 1.7188, 'learning_rate': 0.00036618053266124386, 'epoch': 0.21}

 21%|██        | 751/3566 [30:11<1:56:46,  2.49s/it]
 21%|██        | 752/3566 [30:13<1:55:10,  2.46s/it]
                                                    
{'loss': 1.6181, 'learning_rate': 0.0003660795966635566, 'epoch': 0.21}

 21%|██        | 752/3566 [30:13<1:55:10,  2.46s/it]
 21%|██        | 753/3566 [30:16<1:52:50,  2.41s/it]
                                                    
{'loss': 1.5388, 'learning_rate': 0.0003659785242204752, 'epoch': 0.21}

 21%|██        | 753/3566 [30:16<1:52:50,  2.41s/it]
 21%|██        | 754/3566 [30:18<1:53:47,  2.43s/it]
                                                    
{'loss': 1.6865, 'learning_rate': 0.0003658773154150372, 'epoch': 0.21}

 21%|██        | 754/3566 [30:18<1:53:47,  2.43s/it]
 21%|██        | 755/3566 [30:22<2:12:03,  2.82s/it]
                                                    
{'loss': 1.7088, 'learning_rate': 0.0003657759703303926, 'epoch': 0.21}

 21%|██        | 755/3566 [30:22<2:12:03,  2.82s/it]
 21%|██        | 756/3566 [30:24<2:03:49,  2.64s/it]
                                                    
{'loss': 1.6922, 'learning_rate': 0.0003656744890498028, 'epoch': 0.21}

 21%|██        | 756/3566 [30:24<2:03:49,  2.64s/it]
 21%|██        | 757/3566 [30:27<2:03:16,  2.63s/it]
                                                    
{'loss': 1.6053, 'learning_rate': 0.00036557287165664166, 'epoch': 0.21}

 21%|██        | 757/3566 [30:27<2:03:16,  2.63s/it]
 21%|██▏       | 758/3566 [30:29<1:54:56,  2.46s/it]
                                                    
{'loss': 1.6599, 'learning_rate': 0.00036547111823439447, 'epoch': 0.21}

 21%|██▏       | 758/3566 [30:29<1:54:56,  2.46s/it]
 21%|██▏       | 759/3566 [30:31<1:56:41,  2.49s/it]
                                                    
{'loss': 1.8624, 'learning_rate': 0.00036536922886665847, 'epoch': 0.21}

 21%|██▏       | 759/3566 [30:31<1:56:41,  2.49s/it]
 21%|██▏       | 760/3566 [30:33<1:50:11,  2.36s/it]
                                                    
{'loss': 1.5775, 'learning_rate': 0.0003652672036371424, 'epoch': 0.21}

 21%|██▏       | 760/3566 [30:33<1:50:11,  2.36s/it]
 21%|██▏       | 761/3566 [30:36<1:47:30,  2.30s/it]
                                                    
{'loss': 1.7386, 'learning_rate': 0.0003651650426296669, 'epoch': 0.21}

 21%|██▏       | 761/3566 [30:36<1:47:30,  2.30s/it]
 21%|██▏       | 762/3566 [30:38<1:47:45,  2.31s/it]
                                                    
{'loss': 1.7108, 'learning_rate': 0.00036506274592816395, 'epoch': 0.21}

 21%|██▏       | 762/3566 [30:38<1:47:45,  2.31s/it]
 21%|██▏       | 763/3566 [30:40<1:47:54,  2.31s/it]
                                                    
{'loss': 1.5253, 'learning_rate': 0.0003649603136166771, 'epoch': 0.21}

 21%|██▏       | 763/3566 [30:40<1:47:54,  2.31s/it]
 21%|██▏       | 764/3566 [30:43<1:48:44,  2.33s/it]
                                                    
{'loss': 1.4999, 'learning_rate': 0.00036485774577936123, 'epoch': 0.21}

 21%|██▏       | 764/3566 [30:43<1:48:44,  2.33s/it]
 21%|██▏       | 765/3566 [30:45<1:47:37,  2.31s/it]
                                                    
{'loss': 1.5671, 'learning_rate': 0.0003647550425004826, 'epoch': 0.21}

 21%|██▏       | 765/3566 [30:45<1:47:37,  2.31s/it]
 21%|██▏       | 766/3566 [30:47<1:49:53,  2.35s/it]
                                                    
{'loss': 1.6967, 'learning_rate': 0.00036465220386441887, 'epoch': 0.21}

 21%|██▏       | 766/3566 [30:47<1:49:53,  2.35s/it]
 22%|██▏       | 767/3566 [30:50<1:50:08,  2.36s/it]
                                                    
{'loss': 1.5612, 'learning_rate': 0.0003645492299556586, 'epoch': 0.22}

 22%|██▏       | 767/3566 [30:50<1:50:08,  2.36s/it]
 22%|██▏       | 768/3566 [30:52<1:51:37,  2.39s/it]
                                                    
{'loss': 1.7352, 'learning_rate': 0.0003644461208588019, 'epoch': 0.22}

 22%|██▏       | 768/3566 [30:52<1:51:37,  2.39s/it]
 22%|██▏       | 769/3566 [30:55<1:52:43,  2.42s/it]
                                                    
{'loss': 1.7234, 'learning_rate': 0.0003643428766585596, 'epoch': 0.22}

 22%|██▏       | 769/3566 [30:55<1:52:43,  2.42s/it]
 22%|██▏       | 770/3566 [30:57<1:48:17,  2.32s/it]
                                                    
{'loss': 1.4075, 'learning_rate': 0.00036423949743975365, 'epoch': 0.22}

 22%|██▏       | 770/3566 [30:57<1:48:17,  2.32s/it]
 22%|██▏       | 771/3566 [30:59<1:51:29,  2.39s/it]
                                                    
{'loss': 1.6601, 'learning_rate': 0.000364135983287317, 'epoch': 0.22}

 22%|██▏       | 771/3566 [30:59<1:51:29,  2.39s/it]
 22%|██▏       | 772/3566 [31:02<1:53:14,  2.43s/it]
                                                    
{'loss': 1.6162, 'learning_rate': 0.0003640323342862932, 'epoch': 0.22}

 22%|██▏       | 772/3566 [31:02<1:53:14,  2.43s/it]
 22%|██▏       | 773/3566 [31:05<1:59:09,  2.56s/it]
                                                    
{'loss': 1.4388, 'learning_rate': 0.0003639285505218371, 'epoch': 0.22}

 22%|██▏       | 773/3566 [31:05<1:59:09,  2.56s/it]
 22%|██▏       | 774/3566 [31:07<1:57:01,  2.51s/it]
                                                    
{'loss': 1.5171, 'learning_rate': 0.0003638246320792137, 'epoch': 0.22}

 22%|██▏       | 774/3566 [31:07<1:57:01,  2.51s/it]
 22%|██▏       | 775/3566 [31:10<1:57:35,  2.53s/it]
                                                    
{'loss': 1.6289, 'learning_rate': 0.0003637205790437989, 'epoch': 0.22}

 22%|██▏       | 775/3566 [31:10<1:57:35,  2.53s/it]
 22%|██▏       | 776/3566 [31:12<1:58:43,  2.55s/it]
                                                    
{'loss': 1.6994, 'learning_rate': 0.0003636163915010792, 'epoch': 0.22}

 22%|██▏       | 776/3566 [31:12<1:58:43,  2.55s/it]
 22%|██▏       | 777/3566 [31:14<1:52:43,  2.43s/it]
                                                    
{'loss': 1.7473, 'learning_rate': 0.00036351206953665164, 'epoch': 0.22}

 22%|██▏       | 777/3566 [31:14<1:52:43,  2.43s/it]
 22%|██▏       | 778/3566 [31:17<1:52:37,  2.42s/it]
                                                    
{'loss': 1.7608, 'learning_rate': 0.00036340761323622346, 'epoch': 0.22}

 22%|██▏       | 778/3566 [31:17<1:52:37,  2.42s/it]
 22%|██▏       | 779/3566 [31:24<2:51:27,  3.69s/it]
                                                    
{'loss': 1.6271, 'learning_rate': 0.00036330302268561265, 'epoch': 0.22}

 22%|██▏       | 779/3566 [31:24<2:51:27,  3.69s/it]
 22%|██▏       | 780/3566 [31:26<2:32:16,  3.28s/it]
                                                    
{'loss': 1.6581, 'learning_rate': 0.00036319829797074705, 'epoch': 0.22}

 22%|██▏       | 780/3566 [31:26<2:32:16,  3.28s/it]
 22%|██▏       | 781/3566 [31:29<2:29:06,  3.21s/it]
                                                    
{'loss': 1.6611, 'learning_rate': 0.00036309343917766514, 'epoch': 0.22}

 22%|██▏       | 781/3566 [31:29<2:29:06,  3.21s/it]
 22%|██▏       | 782/3566 [31:31<2:15:07,  2.91s/it]
                                                    
{'loss': 1.3999, 'learning_rate': 0.00036298844639251525, 'epoch': 0.22}

 22%|██▏       | 782/3566 [31:31<2:15:07,  2.91s/it]
 22%|██▏       | 783/3566 [31:33<2:05:25,  2.70s/it]
                                                    
{'loss': 1.5234, 'learning_rate': 0.00036288331970155596, 'epoch': 0.22}

 22%|██▏       | 783/3566 [31:33<2:05:25,  2.70s/it]
 22%|██▏       | 784/3566 [31:36<1:59:32,  2.58s/it]
                                                    
{'loss': 1.7755, 'learning_rate': 0.00036277805919115584, 'epoch': 0.22}

 22%|██▏       | 784/3566 [31:36<1:59:32,  2.58s/it]
 22%|██▏       | 785/3566 [31:38<1:55:40,  2.50s/it]
                                                    
{'loss': 1.5381, 'learning_rate': 0.00036267266494779336, 'epoch': 0.22}

 22%|██▏       | 785/3566 [31:38<1:55:40,  2.50s/it]
 22%|██▏       | 786/3566 [31:41<2:04:52,  2.70s/it]
                                                    
{'loss': 1.6635, 'learning_rate': 0.0003625671370580568, 'epoch': 0.22}

 22%|██▏       | 786/3566 [31:41<2:04:52,  2.70s/it]
 22%|██▏       | 787/3566 [31:44<2:02:37,  2.65s/it]
                                                    
{'loss': 1.6698, 'learning_rate': 0.0003624614756086444, 'epoch': 0.22}

 22%|██▏       | 787/3566 [31:44<2:02:37,  2.65s/it]
 22%|██▏       | 788/3566 [31:46<1:57:09,  2.53s/it]
                                                    
{'loss': 1.5536, 'learning_rate': 0.00036235568068636396, 'epoch': 0.22}

 22%|██▏       | 788/3566 [31:46<1:57:09,  2.53s/it]
 22%|██▏       | 789/3566 [31:48<1:56:57,  2.53s/it]
                                                    
{'loss': 1.6996, 'learning_rate': 0.00036224975237813314, 'epoch': 0.22}

 22%|██▏       | 789/3566 [31:48<1:56:57,  2.53s/it]
 22%|██▏       | 790/3566 [31:51<1:55:58,  2.51s/it]
                                                    
{'loss': 1.6837, 'learning_rate': 0.000362143690770979, 'epoch': 0.22}

 22%|██▏       | 790/3566 [31:51<1:55:58,  2.51s/it]
 22%|██▏       | 791/3566 [31:53<1:53:33,  2.46s/it]
                                                    
{'loss': 1.6303, 'learning_rate': 0.0003620374959520382, 'epoch': 0.22}

 22%|██▏       | 791/3566 [31:53<1:53:33,  2.46s/it]
 22%|██▏       | 792/3566 [31:56<1:52:07,  2.43s/it]
                                                    
{'loss': 1.6647, 'learning_rate': 0.0003619311680085567, 'epoch': 0.22}

 22%|██▏       | 792/3566 [31:56<1:52:07,  2.43s/it]
 22%|██▏       | 793/3566 [31:58<1:50:20,  2.39s/it]
                                                    
{'loss': 1.6499, 'learning_rate': 0.00036182470702789, 'epoch': 0.22}

 22%|██▏       | 793/3566 [31:58<1:50:20,  2.39s/it]
 22%|██▏       | 794/3566 [32:00<1:50:29,  2.39s/it]
                                                    
{'loss': 1.6702, 'learning_rate': 0.00036171811309750306, 'epoch': 0.22}

 22%|██▏       | 794/3566 [32:00<1:50:29,  2.39s/it]
 22%|██▏       | 795/3566 [32:04<2:04:21,  2.69s/it]
                                                    
{'loss': 1.6315, 'learning_rate': 0.00036161138630496964, 'epoch': 0.22}

 22%|██▏       | 795/3566 [32:04<2:04:21,  2.69s/it]
 22%|██▏       | 796/3566 [32:06<2:00:05,  2.60s/it]
                                                    
{'loss': 1.6463, 'learning_rate': 0.0003615045267379729, 'epoch': 0.22}

 22%|██▏       | 796/3566 [32:06<2:00:05,  2.60s/it]
 22%|██▏       | 797/3566 [32:08<1:53:32,  2.46s/it]
                                                    
{'loss': 1.6804, 'learning_rate': 0.00036139753448430513, 'epoch': 0.22}

 22%|██▏       | 797/3566 [32:08<1:53:32,  2.46s/it]
 22%|██▏       | 798/3566 [32:10<1:51:09,  2.41s/it]
                                                    
{'loss': 1.6333, 'learning_rate': 0.00036129040963186744, 'epoch': 0.22}

 22%|██▏       | 798/3566 [32:10<1:51:09,  2.41s/it]
 22%|██▏       | 799/3566 [32:13<1:50:50,  2.40s/it]
                                                    
{'loss': 1.7529, 'learning_rate': 0.0003611831522686701, 'epoch': 0.22}

 22%|██▏       | 799/3566 [32:13<1:50:50,  2.40s/it]
 22%|██▏       | 800/3566 [32:15<1:52:53,  2.45s/it]
                                                    
{'loss': 1.5498, 'learning_rate': 0.0003610757624828321, 'epoch': 0.22}

 22%|██▏       | 800/3566 [32:15<1:52:53,  2.45s/it]
 22%|██▏       | 801/3566 [32:18<1:52:22,  2.44s/it]
                                                    
{'loss': 1.6344, 'learning_rate': 0.0003609682403625813, 'epoch': 0.22}

 22%|██▏       | 801/3566 [32:18<1:52:22,  2.44s/it]
 22%|██▏       | 802/3566 [32:20<1:54:29,  2.49s/it]
                                                    
{'loss': 1.5093, 'learning_rate': 0.0003608605859962542, 'epoch': 0.22}

 22%|██▏       | 802/3566 [32:20<1:54:29,  2.49s/it]
 23%|██▎       | 803/3566 [32:23<1:53:34,  2.47s/it]
                                                    
{'loss': 1.6603, 'learning_rate': 0.00036075279947229603, 'epoch': 0.23}

 23%|██▎       | 803/3566 [32:23<1:53:34,  2.47s/it]
 23%|██▎       | 804/3566 [32:25<1:52:30,  2.44s/it]
                                                    
{'loss': 1.6719, 'learning_rate': 0.0003606448808792605, 'epoch': 0.23}

 23%|██▎       | 804/3566 [32:25<1:52:30,  2.44s/it]
 23%|██▎       | 805/3566 [32:27<1:50:30,  2.40s/it]
                                                    
{'loss': 1.5757, 'learning_rate': 0.00036053683030581, 'epoch': 0.23}

 23%|██▎       | 805/3566 [32:28<1:50:30,  2.40s/it]
 23%|██▎       | 806/3566 [32:30<1:51:12,  2.42s/it]
                                                    
{'loss': 1.6758, 'learning_rate': 0.00036042864784071514, 'epoch': 0.23}

 23%|██▎       | 806/3566 [32:30<1:51:12,  2.42s/it]
 23%|██▎       | 807/3566 [32:32<1:49:42,  2.39s/it]
                                                    
{'loss': 1.6227, 'learning_rate': 0.00036032033357285496, 'epoch': 0.23}

 23%|██▎       | 807/3566 [32:32<1:49:42,  2.39s/it]
 23%|██▎       | 808/3566 [32:34<1:46:01,  2.31s/it]
                                                    
{'loss': 1.4965, 'learning_rate': 0.000360211887591217, 'epoch': 0.23}

 23%|██▎       | 808/3566 [32:34<1:46:01,  2.31s/it]
 23%|██▎       | 809/3566 [32:37<1:50:28,  2.40s/it]
                                                    
{'loss': 1.6304, 'learning_rate': 0.00036010330998489655, 'epoch': 0.23}

 23%|██▎       | 809/3566 [32:37<1:50:28,  2.40s/it]
 23%|██▎       | 810/3566 [32:39<1:50:44,  2.41s/it]
                                                    
{'loss': 1.7211, 'learning_rate': 0.0003599946008430974, 'epoch': 0.23}

 23%|██▎       | 810/3566 [32:39<1:50:44,  2.41s/it]
 23%|██▎       | 811/3566 [32:42<1:50:06,  2.40s/it]
                                                    
{'loss': 1.6257, 'learning_rate': 0.00035988576025513153, 'epoch': 0.23}

 23%|██▎       | 811/3566 [32:42<1:50:06,  2.40s/it]
 23%|██▎       | 812/3566 [32:44<1:51:35,  2.43s/it]
                                                    
{'loss': 1.6938, 'learning_rate': 0.00035977678831041837, 'epoch': 0.23}

 23%|██▎       | 812/3566 [32:44<1:51:35,  2.43s/it]
 23%|██▎       | 813/3566 [32:47<1:50:37,  2.41s/it]
                                                    
{'loss': 1.5939, 'learning_rate': 0.00035966768509848585, 'epoch': 0.23}

 23%|██▎       | 813/3566 [32:47<1:50:37,  2.41s/it]
 23%|██▎       | 814/3566 [32:50<1:57:02,  2.55s/it]
                                                    
{'loss': 1.6475, 'learning_rate': 0.00035955845070896933, 'epoch': 0.23}

 23%|██▎       | 814/3566 [32:50<1:57:02,  2.55s/it]
 23%|██▎       | 815/3566 [32:52<1:51:24,  2.43s/it]
                                                    
{'loss': 1.7269, 'learning_rate': 0.00035944908523161215, 'epoch': 0.23}

 23%|██▎       | 815/3566 [32:52<1:51:24,  2.43s/it]
 23%|██▎       | 816/3566 [32:54<1:50:47,  2.42s/it]
                                                    
{'loss': 1.6109, 'learning_rate': 0.0003593395887562653, 'epoch': 0.23}

 23%|██▎       | 816/3566 [32:54<1:50:47,  2.42s/it]
 23%|██▎       | 817/3566 [32:57<1:54:51,  2.51s/it]
                                                    
{'loss': 1.6085, 'learning_rate': 0.00035922996137288736, 'epoch': 0.23}

 23%|██▎       | 817/3566 [32:57<1:54:51,  2.51s/it]
 23%|██▎       | 818/3566 [32:59<1:57:10,  2.56s/it]
                                                    
{'loss': 1.6714, 'learning_rate': 0.0003591202031715446, 'epoch': 0.23}

 23%|██▎       | 818/3566 [33:00<1:57:10,  2.56s/it]
 23%|██▎       | 819/3566 [33:02<1:57:09,  2.56s/it]
                                                    
{'loss': 1.5724, 'learning_rate': 0.00035901031424241046, 'epoch': 0.23}

 23%|██▎       | 819/3566 [33:02<1:57:09,  2.56s/it]
 23%|██▎       | 820/3566 [33:04<1:54:53,  2.51s/it]
                                                    
{'loss': 1.5815, 'learning_rate': 0.0003589002946757662, 'epoch': 0.23}

 23%|██▎       | 820/3566 [33:04<1:54:53,  2.51s/it]
 23%|██▎       | 821/3566 [33:07<1:51:47,  2.44s/it]
                                                    
{'loss': 1.5851, 'learning_rate': 0.000358790144562, 'epoch': 0.23}

 23%|██▎       | 821/3566 [33:07<1:51:47,  2.44s/it]
 23%|██▎       | 822/3566 [33:09<1:48:50,  2.38s/it]
                                                    
{'loss': 1.5545, 'learning_rate': 0.0003586798639916076, 'epoch': 0.23}

 23%|██▎       | 822/3566 [33:09<1:48:50,  2.38s/it]
 23%|██▎       | 823/3566 [33:11<1:47:46,  2.36s/it]
                                                    
{'loss': 1.5106, 'learning_rate': 0.00035856945305519177, 'epoch': 0.23}

 23%|██▎       | 823/3566 [33:11<1:47:46,  2.36s/it]
 23%|██▎       | 824/3566 [33:14<1:47:46,  2.36s/it]
                                                    
{'loss': 1.6366, 'learning_rate': 0.00035845891184346237, 'epoch': 0.23}

 23%|██▎       | 824/3566 [33:14<1:47:46,  2.36s/it]
 23%|██▎       | 825/3566 [33:16<1:49:17,  2.39s/it]
                                                    
{'loss': 1.4399, 'learning_rate': 0.0003583482404472363, 'epoch': 0.23}

 23%|██▎       | 825/3566 [33:16<1:49:17,  2.39s/it]
 23%|██▎       | 826/3566 [33:19<1:53:04,  2.48s/it]
                                                    
{'loss': 1.6289, 'learning_rate': 0.00035823743895743753, 'epoch': 0.23}

 23%|██▎       | 826/3566 [33:19<1:53:04,  2.48s/it]
 23%|██▎       | 827/3566 [33:21<1:53:45,  2.49s/it]
                                                    
{'loss': 1.6164, 'learning_rate': 0.00035812650746509686, 'epoch': 0.23}

 23%|██▎       | 827/3566 [33:21<1:53:45,  2.49s/it]
 23%|██▎       | 828/3566 [33:24<1:50:39,  2.42s/it]
                                                    
{'loss': 1.5382, 'learning_rate': 0.00035801544606135164, 'epoch': 0.23}

 23%|██▎       | 828/3566 [33:24<1:50:39,  2.42s/it]
 23%|██▎       | 829/3566 [33:26<1:51:34,  2.45s/it]
                                                    
{'loss': 1.7615, 'learning_rate': 0.0003579042548374465, 'epoch': 0.23}

 23%|██▎       | 829/3566 [33:26<1:51:34,  2.45s/it]
 23%|██▎       | 830/3566 [33:28<1:48:28,  2.38s/it]
                                                    
{'loss': 1.6598, 'learning_rate': 0.00035779293388473214, 'epoch': 0.23}

 23%|██▎       | 830/3566 [33:28<1:48:28,  2.38s/it]
 23%|██▎       | 831/3566 [33:31<1:47:20,  2.35s/it]
                                                    
{'loss': 1.3605, 'learning_rate': 0.0003576814832946662, 'epoch': 0.23}

 23%|██▎       | 831/3566 [33:31<1:47:20,  2.35s/it]
 23%|██▎       | 832/3566 [33:33<1:47:32,  2.36s/it]
                                                    
{'loss': 1.6997, 'learning_rate': 0.00035756990315881273, 'epoch': 0.23}

 23%|██▎       | 832/3566 [33:33<1:47:32,  2.36s/it]
 23%|██▎       | 833/3566 [33:35<1:48:19,  2.38s/it]
                                                    
{'loss': 1.6884, 'learning_rate': 0.00035745819356884217, 'epoch': 0.23}

 23%|██▎       | 833/3566 [33:35<1:48:19,  2.38s/it]
 23%|██▎       | 834/3566 [33:38<1:45:56,  2.33s/it]
                                                    
{'loss': 1.5922, 'learning_rate': 0.0003573463546165314, 'epoch': 0.23}

 23%|██▎       | 834/3566 [33:38<1:45:56,  2.33s/it]
 23%|██▎       | 835/3566 [33:40<1:44:13,  2.29s/it]
                                                    
{'loss': 1.5222, 'learning_rate': 0.00035723438639376345, 'epoch': 0.23}

 23%|██▎       | 835/3566 [33:40<1:44:13,  2.29s/it]
 23%|██▎       | 836/3566 [33:42<1:49:22,  2.40s/it]
                                                    
{'loss': 1.6046, 'learning_rate': 0.00035712228899252774, 'epoch': 0.23}

 23%|██▎       | 836/3566 [33:42<1:49:22,  2.40s/it]
 23%|██▎       | 837/3566 [33:45<1:46:12,  2.34s/it]
                                                    
{'loss': 1.5822, 'learning_rate': 0.00035701006250491964, 'epoch': 0.23}

 23%|██▎       | 837/3566 [33:45<1:46:12,  2.34s/it]
 23%|██▎       | 838/3566 [33:47<1:46:04,  2.33s/it]
                                                    
{'loss': 1.7044, 'learning_rate': 0.0003568977070231406, 'epoch': 0.23}

 23%|██▎       | 838/3566 [33:47<1:46:04,  2.33s/it]
 24%|██▎       | 839/3566 [33:49<1:48:17,  2.38s/it]
                                                    
{'loss': 1.6725, 'learning_rate': 0.00035678522263949823, 'epoch': 0.24}

 24%|██▎       | 839/3566 [33:49<1:48:17,  2.38s/it]
 24%|██▎       | 840/3566 [33:52<1:49:03,  2.40s/it]
                                                    
{'loss': 1.6955, 'learning_rate': 0.0003566726094464058, 'epoch': 0.24}

 24%|██▎       | 840/3566 [33:52<1:49:03,  2.40s/it]
 24%|██▎       | 841/3566 [33:54<1:48:03,  2.38s/it]
                                                    
{'loss': 1.5768, 'learning_rate': 0.0003565598675363826, 'epoch': 0.24}

 24%|██▎       | 841/3566 [33:54<1:48:03,  2.38s/it]
 24%|██▎       | 842/3566 [33:57<1:46:55,  2.36s/it]
                                                    
{'loss': 1.4117, 'learning_rate': 0.0003564469970020534, 'epoch': 0.24}

 24%|██▎       | 842/3566 [33:57<1:46:55,  2.36s/it]
 24%|██▎       | 843/3566 [33:59<1:46:09,  2.34s/it]
                                                    
{'loss': 1.5941, 'learning_rate': 0.0003563339979361491, 'epoch': 0.24}

 24%|██▎       | 843/3566 [33:59<1:46:09,  2.34s/it]
 24%|██▎       | 844/3566 [34:01<1:44:07,  2.30s/it]
                                                    
{'loss': 1.623, 'learning_rate': 0.0003562208704315057, 'epoch': 0.24}

 24%|██▎       | 844/3566 [34:01<1:44:07,  2.30s/it]
 24%|██▎       | 845/3566 [34:03<1:44:42,  2.31s/it]
                                                    
{'loss': 1.4523, 'learning_rate': 0.000356107614581065, 'epoch': 0.24}

 24%|██▎       | 845/3566 [34:03<1:44:42,  2.31s/it]
 24%|██▎       | 846/3566 [34:05<1:41:34,  2.24s/it]
                                                    
{'loss': 1.6319, 'learning_rate': 0.0003559942304778742, 'epoch': 0.24}

 24%|██▎       | 846/3566 [34:05<1:41:34,  2.24s/it]
 24%|██▍       | 847/3566 [34:08<1:42:17,  2.26s/it]
                                                    
{'loss': 1.551, 'learning_rate': 0.00035588071821508586, 'epoch': 0.24}

 24%|██▍       | 847/3566 [34:08<1:42:17,  2.26s/it]
 24%|██▍       | 848/3566 [34:10<1:46:24,  2.35s/it]
                                                    
{'loss': 1.711, 'learning_rate': 0.00035576707788595777, 'epoch': 0.24}

 24%|██▍       | 848/3566 [34:10<1:46:24,  2.35s/it]
 24%|██▍       | 849/3566 [34:12<1:44:11,  2.30s/it]
                                                    
{'loss': 1.6893, 'learning_rate': 0.0003556533095838531, 'epoch': 0.24}

 24%|██▍       | 849/3566 [34:13<1:44:11,  2.30s/it]
 24%|██▍       | 850/3566 [34:15<1:51:38,  2.47s/it]
                                                    
{'loss': 1.5213, 'learning_rate': 0.00035553941340223994, 'epoch': 0.24}

 24%|██▍       | 850/3566 [34:15<1:51:38,  2.47s/it]
 24%|██▍       | 851/3566 [34:18<1:48:20,  2.39s/it]
                                                    
{'loss': 1.724, 'learning_rate': 0.0003554253894346916, 'epoch': 0.24}

 24%|██▍       | 851/3566 [34:18<1:48:20,  2.39s/it]
 24%|██▍       | 852/3566 [34:20<1:51:10,  2.46s/it]
                                                    
{'loss': 1.7319, 'learning_rate': 0.0003553112377748864, 'epoch': 0.24}

 24%|██▍       | 852/3566 [34:20<1:51:10,  2.46s/it]
 24%|██▍       | 853/3566 [34:23<1:52:07,  2.48s/it]
                                                    
{'loss': 1.6992, 'learning_rate': 0.00035519695851660735, 'epoch': 0.24}

 24%|██▍       | 853/3566 [34:23<1:52:07,  2.48s/it]
 24%|██▍       | 854/3566 [34:25<1:50:31,  2.45s/it]
                                                    
{'loss': 1.6182, 'learning_rate': 0.0003550825517537425, 'epoch': 0.24}

 24%|██▍       | 854/3566 [34:25<1:50:31,  2.45s/it]
 24%|██▍       | 855/3566 [34:27<1:46:13,  2.35s/it]
                                                    
{'loss': 1.4842, 'learning_rate': 0.00035496801758028455, 'epoch': 0.24}

 24%|██▍       | 855/3566 [34:27<1:46:13,  2.35s/it]
 24%|██▍       | 856/3566 [34:30<1:47:17,  2.38s/it]
                                                    
{'loss': 1.6117, 'learning_rate': 0.0003548533560903311, 'epoch': 0.24}

 24%|██▍       | 856/3566 [34:30<1:47:17,  2.38s/it]
 24%|██▍       | 857/3566 [34:33<2:06:27,  2.80s/it]
                                                    
{'loss': 1.527, 'learning_rate': 0.0003547385673780838, 'epoch': 0.24}

 24%|██▍       | 857/3566 [34:33<2:06:27,  2.80s/it]
 24%|██▍       | 858/3566 [34:36<1:58:43,  2.63s/it]
                                                    
{'loss': 1.5368, 'learning_rate': 0.00035462365153784953, 'epoch': 0.24}

 24%|██▍       | 858/3566 [34:36<1:58:43,  2.63s/it]
 24%|██▍       | 859/3566 [34:38<1:56:50,  2.59s/it]
                                                    
{'loss': 1.5789, 'learning_rate': 0.0003545086086640391, 'epoch': 0.24}

 24%|██▍       | 859/3566 [34:38<1:56:50,  2.59s/it]
 24%|██▍       | 860/3566 [34:41<1:59:32,  2.65s/it]
                                                    
{'loss': 1.7224, 'learning_rate': 0.00035439343885116786, 'epoch': 0.24}

 24%|██▍       | 860/3566 [34:41<1:59:32,  2.65s/it]
 24%|██▍       | 861/3566 [34:43<1:53:43,  2.52s/it]
                                                    
{'loss': 1.6041, 'learning_rate': 0.0003542781421938555, 'epoch': 0.24}

 24%|██▍       | 861/3566 [34:43<1:53:43,  2.52s/it]
 24%|██▍       | 862/3566 [34:45<1:50:12,  2.45s/it]
                                                    
{'loss': 1.4644, 'learning_rate': 0.00035416271878682584, 'epoch': 0.24}

 24%|██▍       | 862/3566 [34:45<1:50:12,  2.45s/it]
 24%|██▍       | 863/3566 [34:48<1:47:14,  2.38s/it]
                                                    
{'loss': 1.6175, 'learning_rate': 0.00035404716872490684, 'epoch': 0.24}

 24%|██▍       | 863/3566 [34:48<1:47:14,  2.38s/it]
 24%|██▍       | 864/3566 [34:50<1:51:53,  2.48s/it]
                                                    
{'loss': 1.6211, 'learning_rate': 0.00035393149210303056, 'epoch': 0.24}

 24%|██▍       | 864/3566 [34:50<1:51:53,  2.48s/it]
 24%|██▍       | 865/3566 [34:53<1:56:46,  2.59s/it]
                                                    
{'loss': 1.5742, 'learning_rate': 0.000353815689016233, 'epoch': 0.24}

 24%|██▍       | 865/3566 [34:53<1:56:46,  2.59s/it]
 24%|██▍       | 866/3566 [34:56<1:55:55,  2.58s/it]
                                                    
{'loss': 1.6979, 'learning_rate': 0.00035369975955965407, 'epoch': 0.24}

 24%|██▍       | 866/3566 [34:56<1:55:55,  2.58s/it]
 24%|██▍       | 867/3566 [34:58<1:53:26,  2.52s/it]
                                                    
{'loss': 1.6021, 'learning_rate': 0.0003535837038285375, 'epoch': 0.24}

 24%|██▍       | 867/3566 [34:58<1:53:26,  2.52s/it]
 24%|██▍       | 868/3566 [35:01<1:55:20,  2.56s/it]
                                                    
{'loss': 1.7332, 'learning_rate': 0.0003534675219182307, 'epoch': 0.24}

 24%|██▍       | 868/3566 [35:01<1:55:20,  2.56s/it]
 24%|██▍       | 869/3566 [35:04<1:57:10,  2.61s/it]
                                                    
{'loss': 1.601, 'learning_rate': 0.0003533512139241849, 'epoch': 0.24}

 24%|██▍       | 869/3566 [35:04<1:57:10,  2.61s/it]
 24%|██▍       | 870/3566 [35:06<1:55:46,  2.58s/it]
                                                    
{'loss': 1.7034, 'learning_rate': 0.00035323477994195484, 'epoch': 0.24}

 24%|██▍       | 870/3566 [35:06<1:55:46,  2.58s/it]
 24%|██▍       | 871/3566 [35:09<1:57:53,  2.62s/it]
                                                    
{'loss': 1.5706, 'learning_rate': 0.00035311822006719865, 'epoch': 0.24}

 24%|██▍       | 871/3566 [35:09<1:57:53,  2.62s/it]
 24%|██▍       | 872/3566 [35:11<1:57:09,  2.61s/it]
                                                    
{'loss': 1.5292, 'learning_rate': 0.0003530015343956781, 'epoch': 0.24}

 24%|██▍       | 872/3566 [35:11<1:57:09,  2.61s/it]
 24%|██▍       | 873/3566 [35:14<1:57:16,  2.61s/it]
                                                    
{'loss': 1.672, 'learning_rate': 0.00035288472302325805, 'epoch': 0.24}

 24%|██▍       | 873/3566 [35:14<1:57:16,  2.61s/it]
 25%|██▍       | 874/3566 [35:16<1:52:45,  2.51s/it]
                                                    
{'loss': 1.3831, 'learning_rate': 0.00035276778604590695, 'epoch': 0.25}

 25%|██▍       | 874/3566 [35:16<1:52:45,  2.51s/it]
 25%|██▍       | 875/3566 [35:19<1:50:12,  2.46s/it]
                                                    
{'loss': 1.6969, 'learning_rate': 0.00035265072355969624, 'epoch': 0.25}

 25%|██▍       | 875/3566 [35:19<1:50:12,  2.46s/it]
 25%|██▍       | 876/3566 [35:21<1:49:17,  2.44s/it]
                                                    
{'loss': 1.572, 'learning_rate': 0.0003525335356608004, 'epoch': 0.25}

 25%|██▍       | 876/3566 [35:21<1:49:17,  2.44s/it]
 25%|██▍       | 877/3566 [35:23<1:46:40,  2.38s/it]
                                                    
{'loss': 1.5844, 'learning_rate': 0.00035241622244549717, 'epoch': 0.25}

 25%|██▍       | 877/3566 [35:23<1:46:40,  2.38s/it]
 25%|██▍       | 878/3566 [35:26<1:45:33,  2.36s/it]
                                                    
{'loss': 1.4933, 'learning_rate': 0.00035229878401016714, 'epoch': 0.25}

 25%|██▍       | 878/3566 [35:26<1:45:33,  2.36s/it]
 25%|██▍       | 879/3566 [35:28<1:48:13,  2.42s/it]
                                                    
{'loss': 1.5196, 'learning_rate': 0.00035218122045129363, 'epoch': 0.25}

 25%|██▍       | 879/3566 [35:28<1:48:13,  2.42s/it]
 25%|██▍       | 880/3566 [35:30<1:46:19,  2.38s/it]
                                                    
{'loss': 1.4318, 'learning_rate': 0.00035206353186546303, 'epoch': 0.25}

 25%|██▍       | 880/3566 [35:30<1:46:19,  2.38s/it]
 25%|██▍       | 881/3566 [35:33<1:46:27,  2.38s/it]
                                                    
{'loss': 1.5611, 'learning_rate': 0.00035194571834936425, 'epoch': 0.25}

 25%|██▍       | 881/3566 [35:33<1:46:27,  2.38s/it]
 25%|██▍       | 882/3566 [35:35<1:47:20,  2.40s/it]
                                                    
{'loss': 1.5781, 'learning_rate': 0.0003518277799997889, 'epoch': 0.25}

 25%|██▍       | 882/3566 [35:35<1:47:20,  2.40s/it]
 25%|██▍       | 883/3566 [35:38<1:46:21,  2.38s/it]
                                                    
{'loss': 1.628, 'learning_rate': 0.0003517097169136312, 'epoch': 0.25}

 25%|██▍       | 883/3566 [35:38<1:46:21,  2.38s/it]
 25%|██▍       | 884/3566 [35:40<1:45:41,  2.36s/it]
                                                    
{'loss': 1.5709, 'learning_rate': 0.00035159152918788774, 'epoch': 0.25}

 25%|██▍       | 884/3566 [35:40<1:45:41,  2.36s/it]
 25%|██▍       | 885/3566 [35:42<1:44:31,  2.34s/it]
                                                    
{'loss': 1.5126, 'learning_rate': 0.0003514732169196576, 'epoch': 0.25}

 25%|██▍       | 885/3566 [35:42<1:44:31,  2.34s/it]
 25%|██▍       | 886/3566 [35:45<1:50:13,  2.47s/it]
                                                    
{'loss': 1.5469, 'learning_rate': 0.00035135478020614216, 'epoch': 0.25}

 25%|██▍       | 886/3566 [35:45<1:50:13,  2.47s/it]
 25%|██▍       | 887/3566 [35:47<1:47:27,  2.41s/it]
                                                    
{'loss': 1.5261, 'learning_rate': 0.00035123621914464497, 'epoch': 0.25}

 25%|██▍       | 887/3566 [35:47<1:47:27,  2.41s/it]
 25%|██▍       | 888/3566 [35:50<1:46:23,  2.38s/it]
                                                    
{'loss': 1.5995, 'learning_rate': 0.00035111753383257186, 'epoch': 0.25}

 25%|██▍       | 888/3566 [35:50<1:46:23,  2.38s/it]
 25%|██▍       | 889/3566 [35:52<1:45:19,  2.36s/it]
                                                    
{'loss': 1.7705, 'learning_rate': 0.00035099872436743066, 'epoch': 0.25}

 25%|██▍       | 889/3566 [35:52<1:45:19,  2.36s/it]
 25%|██▍       | 890/3566 [35:54<1:44:46,  2.35s/it]
                                                    
{'loss': 1.6683, 'learning_rate': 0.0003508797908468312, 'epoch': 0.25}

 25%|██▍       | 890/3566 [35:54<1:44:46,  2.35s/it]
 25%|██▍       | 891/3566 [35:56<1:44:20,  2.34s/it]
                                                    
{'loss': 1.5466, 'learning_rate': 0.0003507607333684852, 'epoch': 0.25}

 25%|██▍       | 891/3566 [35:56<1:44:20,  2.34s/it]
 25%|██▌       | 892/3566 [35:59<1:45:45,  2.37s/it]
                                                    
{'loss': 1.7457, 'learning_rate': 0.0003506415520302065, 'epoch': 0.25}

 25%|██▌       | 892/3566 [35:59<1:45:45,  2.37s/it]
 25%|██▌       | 893/3566 [36:01<1:44:22,  2.34s/it]
                                                    
{'loss': 1.6789, 'learning_rate': 0.0003505222469299102, 'epoch': 0.25}

 25%|██▌       | 893/3566 [36:01<1:44:22,  2.34s/it]
 25%|██▌       | 894/3566 [36:03<1:42:51,  2.31s/it]
                                                    
{'loss': 1.5042, 'learning_rate': 0.0003504028181656135, 'epoch': 0.25}

 25%|██▌       | 894/3566 [36:03<1:42:51,  2.31s/it]
 25%|██▌       | 895/3566 [36:06<1:48:04,  2.43s/it]
                                                    
{'loss': 1.6736, 'learning_rate': 0.0003502832658354349, 'epoch': 0.25}

 25%|██▌       | 895/3566 [36:06<1:48:04,  2.43s/it]
 25%|██▌       | 896/3566 [36:09<1:55:15,  2.59s/it]
                                                    
{'loss': 1.6903, 'learning_rate': 0.00035016359003759464, 'epoch': 0.25}

 25%|██▌       | 896/3566 [36:09<1:55:15,  2.59s/it]
 25%|██▌       | 897/3566 [36:11<1:50:58,  2.49s/it]
                                                    
{'loss': 1.5225, 'learning_rate': 0.0003500437908704144, 'epoch': 0.25}

 25%|██▌       | 897/3566 [36:11<1:50:58,  2.49s/it]
 25%|██▌       | 898/3566 [36:14<1:52:10,  2.52s/it]
                                                    
{'loss': 1.5269, 'learning_rate': 0.00034992386843231703, 'epoch': 0.25}

 25%|██▌       | 898/3566 [36:14<1:52:10,  2.52s/it]
 25%|██▌       | 899/3566 [36:16<1:52:08,  2.52s/it]
                                                    
{'loss': 1.5159, 'learning_rate': 0.0003498038228218268, 'epoch': 0.25}

 25%|██▌       | 899/3566 [36:16<1:52:08,  2.52s/it]
 25%|██▌       | 900/3566 [36:19<1:49:29,  2.46s/it]
                                                    
{'loss': 1.7589, 'learning_rate': 0.00034968365413756914, 'epoch': 0.25}

 25%|██▌       | 900/3566 [36:19<1:49:29,  2.46s/it]
 25%|██▌       | 901/3566 [36:21<1:45:44,  2.38s/it]
                                                    
{'loss': 1.7051, 'learning_rate': 0.00034956336247827054, 'epoch': 0.25}

 25%|██▌       | 901/3566 [36:21<1:45:44,  2.38s/it]
 25%|██▌       | 902/3566 [36:23<1:43:23,  2.33s/it]
                                                    
{'loss': 1.4743, 'learning_rate': 0.0003494429479427586, 'epoch': 0.25}

 25%|██▌       | 902/3566 [36:23<1:43:23,  2.33s/it]
 25%|██▌       | 903/3566 [36:26<1:48:52,  2.45s/it]
                                                    
{'loss': 1.7536, 'learning_rate': 0.0003493224106299619, 'epoch': 0.25}

 25%|██▌       | 903/3566 [36:26<1:48:52,  2.45s/it]
 25%|██▌       | 904/3566 [36:29<1:52:37,  2.54s/it]
                                                    
{'loss': 1.5885, 'learning_rate': 0.00034920175063890975, 'epoch': 0.25}

 25%|██▌       | 904/3566 [36:29<1:52:37,  2.54s/it]
 25%|██▌       | 905/3566 [36:31<1:48:44,  2.45s/it]
                                                    
{'loss': 1.5361, 'learning_rate': 0.00034908096806873237, 'epoch': 0.25}

 25%|██▌       | 905/3566 [36:31<1:48:44,  2.45s/it]
 25%|██▌       | 906/3566 [36:33<1:42:56,  2.32s/it]
                                                    
{'loss': 1.5788, 'learning_rate': 0.00034896006301866065, 'epoch': 0.25}

 25%|██▌       | 906/3566 [36:33<1:42:56,  2.32s/it]
 25%|██▌       | 907/3566 [36:36<1:47:03,  2.42s/it]
                                                    
{'loss': 1.7757, 'learning_rate': 0.000348839035588026, 'epoch': 0.25}

 25%|██▌       | 907/3566 [36:36<1:47:03,  2.42s/it]
 25%|██▌       | 908/3566 [36:38<1:49:27,  2.47s/it]
                                                    
{'loss': 1.4703, 'learning_rate': 0.0003487178858762606, 'epoch': 0.25}

 25%|██▌       | 908/3566 [36:38<1:49:27,  2.47s/it]
 25%|██▌       | 909/3566 [36:41<1:49:59,  2.48s/it]
                                                    
{'loss': 1.6324, 'learning_rate': 0.00034859661398289687, 'epoch': 0.25}

 25%|██▌       | 909/3566 [36:41<1:49:59,  2.48s/it]
 26%|██▌       | 910/3566 [36:44<2:04:16,  2.81s/it]
                                                    
{'loss': 1.5308, 'learning_rate': 0.00034847522000756783, 'epoch': 0.26}

 26%|██▌       | 910/3566 [36:44<2:04:16,  2.81s/it]
 26%|██▌       | 911/3566 [36:47<2:01:22,  2.74s/it]
                                                    
{'loss': 1.6901, 'learning_rate': 0.0003483537040500066, 'epoch': 0.26}

 26%|██▌       | 911/3566 [36:47<2:01:22,  2.74s/it]
 26%|██▌       | 912/3566 [36:50<2:00:21,  2.72s/it]
                                                    
{'loss': 1.5897, 'learning_rate': 0.0003482320662100465, 'epoch': 0.26}

 26%|██▌       | 912/3566 [36:50<2:00:21,  2.72s/it]
 26%|██▌       | 913/3566 [36:52<1:54:14,  2.58s/it]
                                                    
{'loss': 1.7772, 'learning_rate': 0.00034811030658762123, 'epoch': 0.26}

 26%|██▌       | 913/3566 [36:52<1:54:14,  2.58s/it]
 26%|██▌       | 914/3566 [36:54<1:50:03,  2.49s/it]
                                                    
{'loss': 1.6363, 'learning_rate': 0.0003479884252827644, 'epoch': 0.26}

 26%|██▌       | 914/3566 [36:54<1:50:03,  2.49s/it]
 26%|██▌       | 915/3566 [36:56<1:46:57,  2.42s/it]
                                                    
{'loss': 1.5437, 'learning_rate': 0.0003478664223956094, 'epoch': 0.26}

 26%|██▌       | 915/3566 [36:56<1:46:57,  2.42s/it]
 26%|██▌       | 916/3566 [36:59<1:49:46,  2.49s/it]
                                                    
{'loss': 1.6354, 'learning_rate': 0.0003477442980263898, 'epoch': 0.26}

 26%|██▌       | 916/3566 [36:59<1:49:46,  2.49s/it]
 26%|██▌       | 917/3566 [37:01<1:49:18,  2.48s/it]
                                                    
{'loss': 1.6113, 'learning_rate': 0.0003476220522754389, 'epoch': 0.26}

 26%|██▌       | 917/3566 [37:01<1:49:18,  2.48s/it]
 26%|██▌       | 918/3566 [37:04<1:52:25,  2.55s/it]
                                                    
{'loss': 1.5946, 'learning_rate': 0.0003474996852431896, 'epoch': 0.26}

 26%|██▌       | 918/3566 [37:04<1:52:25,  2.55s/it]
 26%|██▌       | 919/3566 [37:06<1:49:17,  2.48s/it]
                                                    
{'loss': 1.7754, 'learning_rate': 0.00034737719703017457, 'epoch': 0.26}

 26%|██▌       | 919/3566 [37:06<1:49:17,  2.48s/it]
 26%|██▌       | 920/3566 [37:09<1:49:26,  2.48s/it]
                                                    
{'loss': 1.6842, 'learning_rate': 0.000347254587737026, 'epoch': 0.26}

 26%|██▌       | 920/3566 [37:09<1:49:26,  2.48s/it]
 26%|██▌       | 921/3566 [37:11<1:49:59,  2.50s/it]
                                                    
{'loss': 1.6545, 'learning_rate': 0.00034713185746447554, 'epoch': 0.26}

 26%|██▌       | 921/3566 [37:11<1:49:59,  2.50s/it]
 26%|██▌       | 922/3566 [37:14<1:46:43,  2.42s/it]
                                                    
{'loss': 1.7102, 'learning_rate': 0.00034700900631335426, 'epoch': 0.26}

 26%|██▌       | 922/3566 [37:14<1:46:43,  2.42s/it]
 26%|██▌       | 923/3566 [37:16<1:46:39,  2.42s/it]
                                                    
{'loss': 1.8011, 'learning_rate': 0.0003468860343845925, 'epoch': 0.26}

 26%|██▌       | 923/3566 [37:16<1:46:39,  2.42s/it]
 26%|██▌       | 924/3566 [37:18<1:43:59,  2.36s/it]
                                                    
{'loss': 1.656, 'learning_rate': 0.0003467629417792198, 'epoch': 0.26}

 26%|██▌       | 924/3566 [37:18<1:43:59,  2.36s/it]
 26%|██▌       | 925/3566 [37:21<1:42:04,  2.32s/it]
                                                    
{'loss': 1.6627, 'learning_rate': 0.000346639728598365, 'epoch': 0.26}

 26%|██▌       | 925/3566 [37:21<1:42:04,  2.32s/it]
 26%|██▌       | 926/3566 [37:23<1:45:37,  2.40s/it]
                                                    
{'loss': 1.4086, 'learning_rate': 0.0003465163949432558, 'epoch': 0.26}

 26%|██▌       | 926/3566 [37:23<1:45:37,  2.40s/it]
 26%|██▌       | 927/3566 [37:26<1:45:25,  2.40s/it]
                                                    
{'loss': 1.5241, 'learning_rate': 0.000346392940915219, 'epoch': 0.26}

 26%|██▌       | 927/3566 [37:26<1:45:25,  2.40s/it]
 26%|██▌       | 928/3566 [37:28<1:44:54,  2.39s/it]
                                                    
{'loss': 1.6476, 'learning_rate': 0.0003462693666156803, 'epoch': 0.26}

 26%|██▌       | 928/3566 [37:28<1:44:54,  2.39s/it]
 26%|██▌       | 929/3566 [37:30<1:46:10,  2.42s/it]
                                                    
{'loss': 1.5162, 'learning_rate': 0.00034614567214616415, 'epoch': 0.26}

 26%|██▌       | 929/3566 [37:30<1:46:10,  2.42s/it]
 26%|██▌       | 930/3566 [37:33<1:43:45,  2.36s/it]
                                                    
{'loss': 1.6194, 'learning_rate': 0.00034602185760829375, 'epoch': 0.26}

 26%|██▌       | 930/3566 [37:33<1:43:45,  2.36s/it]
 26%|██▌       | 931/3566 [37:35<1:42:49,  2.34s/it]
                                                    
{'loss': 1.6278, 'learning_rate': 0.0003458979231037909, 'epoch': 0.26}

 26%|██▌       | 931/3566 [37:35<1:42:49,  2.34s/it]
 26%|██▌       | 932/3566 [37:37<1:41:44,  2.32s/it]
                                                    
{'loss': 1.4978, 'learning_rate': 0.0003457738687344761, 'epoch': 0.26}

 26%|██▌       | 932/3566 [37:37<1:41:44,  2.32s/it]
 26%|██▌       | 933/3566 [37:40<1:47:13,  2.44s/it]
                                                    
{'loss': 1.5282, 'learning_rate': 0.00034564969460226824, 'epoch': 0.26}

 26%|██▌       | 933/3566 [37:40<1:47:13,  2.44s/it]
 26%|██▌       | 934/3566 [37:42<1:46:36,  2.43s/it]
                                                    
{'loss': 1.6575, 'learning_rate': 0.0003455254008091844, 'epoch': 0.26}

 26%|██▌       | 934/3566 [37:42<1:46:36,  2.43s/it]
 26%|██▌       | 935/3566 [37:44<1:42:54,  2.35s/it]
                                                    
{'loss': 1.8001, 'learning_rate': 0.00034540098745734044, 'epoch': 0.26}

 26%|██▌       | 935/3566 [37:44<1:42:54,  2.35s/it]
 26%|██▌       | 936/3566 [37:47<1:48:38,  2.48s/it]
                                                    
{'loss': 1.639, 'learning_rate': 0.00034527645464895004, 'epoch': 0.26}

 26%|██▌       | 936/3566 [37:47<1:48:38,  2.48s/it]
 26%|██▋       | 937/3566 [37:50<1:49:04,  2.49s/it]
                                                    
{'loss': 1.729, 'learning_rate': 0.00034515180248632514, 'epoch': 0.26}

 26%|██▋       | 937/3566 [37:50<1:49:04,  2.49s/it]
 26%|██▋       | 938/3566 [37:52<1:48:34,  2.48s/it]
                                                    
{'loss': 1.728, 'learning_rate': 0.0003450270310718758, 'epoch': 0.26}

 26%|██▋       | 938/3566 [37:52<1:48:34,  2.48s/it]
 26%|██▋       | 939/3566 [37:54<1:45:35,  2.41s/it]
                                                    
{'loss': 1.549, 'learning_rate': 0.00034490214050811, 'epoch': 0.26}

 26%|██▋       | 939/3566 [37:54<1:45:35,  2.41s/it]
 26%|██▋       | 940/3566 [37:57<1:44:24,  2.39s/it]
                                                    
{'loss': 1.6194, 'learning_rate': 0.0003447771308976335, 'epoch': 0.26}

 26%|██▋       | 940/3566 [37:57<1:44:24,  2.39s/it]
 26%|██▋       | 941/3566 [37:59<1:44:45,  2.39s/it]
                                                    
{'loss': 1.6228, 'learning_rate': 0.00034465200234315007, 'epoch': 0.26}

 26%|██▋       | 941/3566 [37:59<1:44:45,  2.39s/it]
 26%|██▋       | 942/3566 [38:02<1:44:06,  2.38s/it]
                                                    
{'loss': 1.4906, 'learning_rate': 0.00034452675494746126, 'epoch': 0.26}

 26%|██▋       | 942/3566 [38:02<1:44:06,  2.38s/it]
 26%|██▋       | 943/3566 [38:04<1:42:04,  2.34s/it]
                                                    
{'loss': 1.5751, 'learning_rate': 0.00034440138881346584, 'epoch': 0.26}

 26%|██▋       | 943/3566 [38:04<1:42:04,  2.34s/it]
 26%|██▋       | 944/3566 [38:06<1:40:50,  2.31s/it]
                                                    
{'loss': 1.4345, 'learning_rate': 0.00034427590404416056, 'epoch': 0.26}

 26%|██▋       | 944/3566 [38:06<1:40:50,  2.31s/it]
 27%|██▋       | 945/3566 [38:09<1:43:15,  2.36s/it]
                                                    
{'loss': 1.6488, 'learning_rate': 0.00034415030074263944, 'epoch': 0.27}

 27%|██▋       | 945/3566 [38:09<1:43:15,  2.36s/it]
 27%|██▋       | 946/3566 [38:11<1:45:36,  2.42s/it]
                                                    
{'loss': 1.6703, 'learning_rate': 0.00034402457901209387, 'epoch': 0.27}

 27%|██▋       | 946/3566 [38:11<1:45:36,  2.42s/it]
 27%|██▋       | 947/3566 [38:13<1:41:52,  2.33s/it]
                                                    
{'loss': 1.687, 'learning_rate': 0.00034389873895581264, 'epoch': 0.27}

 27%|██▋       | 947/3566 [38:13<1:41:52,  2.33s/it]
 27%|██▋       | 948/3566 [38:16<1:42:32,  2.35s/it]
                                                    
{'loss': 1.5687, 'learning_rate': 0.00034377278067718165, 'epoch': 0.27}

 27%|██▋       | 948/3566 [38:16<1:42:32,  2.35s/it]
 27%|██▋       | 949/3566 [38:18<1:42:39,  2.35s/it]
                                                    
{'loss': 1.7186, 'learning_rate': 0.000343646704279684, 'epoch': 0.27}

 27%|██▋       | 949/3566 [38:18<1:42:39,  2.35s/it]
 27%|██▋       | 950/3566 [38:20<1:41:45,  2.33s/it]
                                                    
{'loss': 1.6859, 'learning_rate': 0.00034352050986689983, 'epoch': 0.27}

 27%|██▋       | 950/3566 [38:20<1:41:45,  2.33s/it]
 27%|██▋       | 951/3566 [38:22<1:39:32,  2.28s/it]
                                                    
{'loss': 1.5446, 'learning_rate': 0.0003433941975425062, 'epoch': 0.27}

 27%|██▋       | 951/3566 [38:22<1:39:32,  2.28s/it]
 27%|██▋       | 952/3566 [38:25<1:41:38,  2.33s/it]
                                                    
{'loss': 1.5113, 'learning_rate': 0.000343267767410277, 'epoch': 0.27}

 27%|██▋       | 952/3566 [38:25<1:41:38,  2.33s/it]
 27%|██▋       | 953/3566 [38:27<1:38:45,  2.27s/it]
                                                    
{'loss': 1.6428, 'learning_rate': 0.00034314121957408297, 'epoch': 0.27}

 27%|██▋       | 953/3566 [38:27<1:38:45,  2.27s/it]
 27%|██▋       | 954/3566 [38:30<1:42:37,  2.36s/it]
                                                    
{'loss': 1.5125, 'learning_rate': 0.00034301455413789165, 'epoch': 0.27}

 27%|██▋       | 954/3566 [38:30<1:42:37,  2.36s/it]
 27%|██▋       | 955/3566 [38:32<1:41:28,  2.33s/it]
                                                    
{'loss': 1.5916, 'learning_rate': 0.000342887771205767, 'epoch': 0.27}

 27%|██▋       | 955/3566 [38:32<1:41:28,  2.33s/it]
 27%|██▋       | 956/3566 [38:34<1:39:03,  2.28s/it]
                                                    
{'loss': 1.583, 'learning_rate': 0.00034276087088186955, 'epoch': 0.27}

 27%|██▋       | 956/3566 [38:34<1:39:03,  2.28s/it]
 27%|██▋       | 957/3566 [38:36<1:39:08,  2.28s/it]
                                                    
{'loss': 1.3318, 'learning_rate': 0.00034263385327045647, 'epoch': 0.27}

 27%|██▋       | 957/3566 [38:36<1:39:08,  2.28s/it]
 27%|██▋       | 958/3566 [38:39<1:41:25,  2.33s/it]
                                                    
{'loss': 1.7858, 'learning_rate': 0.00034250671847588097, 'epoch': 0.27}

 27%|██▋       | 958/3566 [38:39<1:41:25,  2.33s/it]
 27%|██▋       | 959/3566 [38:41<1:41:42,  2.34s/it]
                                                    
{'loss': 1.5554, 'learning_rate': 0.0003423794666025929, 'epoch': 0.27}

 27%|██▋       | 959/3566 [38:41<1:41:42,  2.34s/it]
 27%|██▋       | 960/3566 [38:43<1:39:07,  2.28s/it]
                                                    
{'loss': 1.4468, 'learning_rate': 0.0003422520977551379, 'epoch': 0.27}

 27%|██▋       | 960/3566 [38:43<1:39:07,  2.28s/it]
 27%|██▋       | 961/3566 [38:46<1:42:40,  2.36s/it]
                                                    
{'loss': 1.6589, 'learning_rate': 0.00034212461203815813, 'epoch': 0.27}

 27%|██▋       | 961/3566 [38:46<1:42:40,  2.36s/it]
 27%|██▋       | 962/3566 [38:48<1:41:59,  2.35s/it]
                                                    
{'loss': 1.6757, 'learning_rate': 0.0003419970095563914, 'epoch': 0.27}

 27%|██▋       | 962/3566 [38:48<1:41:59,  2.35s/it]
 27%|██▋       | 963/3566 [38:51<1:43:55,  2.40s/it]
                                                    
{'loss': 1.6794, 'learning_rate': 0.00034186929041467166, 'epoch': 0.27}

 27%|██▋       | 963/3566 [38:51<1:43:55,  2.40s/it]
 27%|██▋       | 964/3566 [38:53<1:46:36,  2.46s/it]
                                                    
{'loss': 1.6412, 'learning_rate': 0.00034174145471792863, 'epoch': 0.27}

 27%|██▋       | 964/3566 [38:53<1:46:36,  2.46s/it]
 27%|██▋       | 965/3566 [38:55<1:43:36,  2.39s/it]
                                                    
{'loss': 1.562, 'learning_rate': 0.0003416135025711879, 'epoch': 0.27}

 27%|██▋       | 965/3566 [38:55<1:43:36,  2.39s/it]
 27%|██▋       | 966/3566 [38:58<1:50:00,  2.54s/it]
                                                    
{'loss': 1.6078, 'learning_rate': 0.00034148543407957045, 'epoch': 0.27}

 27%|██▋       | 966/3566 [38:58<1:50:00,  2.54s/it]
 27%|██▋       | 967/3566 [39:01<1:48:46,  2.51s/it]
                                                    
{'loss': 1.7199, 'learning_rate': 0.0003413572493482932, 'epoch': 0.27}

 27%|██▋       | 967/3566 [39:01<1:48:46,  2.51s/it]
 27%|██▋       | 968/3566 [39:03<1:47:57,  2.49s/it]
                                                    
{'loss': 1.6804, 'learning_rate': 0.00034122894848266833, 'epoch': 0.27}

 27%|██▋       | 968/3566 [39:03<1:47:57,  2.49s/it]
 27%|██▋       | 969/3566 [39:06<1:46:17,  2.46s/it]
                                                    
{'loss': 1.6861, 'learning_rate': 0.0003411005315881035, 'epoch': 0.27}

 27%|██▋       | 969/3566 [39:06<1:46:17,  2.46s/it]
 27%|██▋       | 970/3566 [39:08<1:45:04,  2.43s/it]
                                                    
{'loss': 1.6702, 'learning_rate': 0.0003409719987701017, 'epoch': 0.27}

 27%|██▋       | 970/3566 [39:08<1:45:04,  2.43s/it]
 27%|██▋       | 971/3566 [39:10<1:41:15,  2.34s/it]
                                                    
{'loss': 1.6035, 'learning_rate': 0.00034084335013426123, 'epoch': 0.27}

 27%|██▋       | 971/3566 [39:10<1:41:15,  2.34s/it]
 27%|██▋       | 972/3566 [39:13<1:45:28,  2.44s/it]
                                                    
{'loss': 1.5438, 'learning_rate': 0.0003407145857862754, 'epoch': 0.27}

 27%|██▋       | 972/3566 [39:13<1:45:28,  2.44s/it]
 27%|██▋       | 973/3566 [39:15<1:41:13,  2.34s/it]
                                                    
{'loss': 1.6954, 'learning_rate': 0.00034058570583193263, 'epoch': 0.27}

 27%|██▋       | 973/3566 [39:15<1:41:13,  2.34s/it]
 27%|██▋       | 974/3566 [39:17<1:43:42,  2.40s/it]
                                                    
{'loss': 1.7222, 'learning_rate': 0.00034045671037711634, 'epoch': 0.27}

 27%|██▋       | 974/3566 [39:17<1:43:42,  2.40s/it]
 27%|██▋       | 975/3566 [39:20<1:43:01,  2.39s/it]
                                                    
{'loss': 1.6006, 'learning_rate': 0.00034032759952780503, 'epoch': 0.27}

 27%|██▋       | 975/3566 [39:20<1:43:01,  2.39s/it]
 27%|██▋       | 976/3566 [39:23<1:52:02,  2.60s/it]
                                                    
{'loss': 1.7374, 'learning_rate': 0.0003401983733900715, 'epoch': 0.27}

 27%|██▋       | 976/3566 [39:23<1:52:02,  2.60s/it]
 27%|██▋       | 977/3566 [39:25<1:47:00,  2.48s/it]
                                                    
{'loss': 1.6048, 'learning_rate': 0.00034006903207008387, 'epoch': 0.27}

 27%|██▋       | 977/3566 [39:25<1:47:00,  2.48s/it]
 27%|██▋       | 978/3566 [39:28<1:47:38,  2.50s/it]
                                                    
{'loss': 1.6602, 'learning_rate': 0.00033993957567410445, 'epoch': 0.27}

 27%|██▋       | 978/3566 [39:28<1:47:38,  2.50s/it]
 27%|██▋       | 979/3566 [39:30<1:44:31,  2.42s/it]
                                                    
{'loss': 1.474, 'learning_rate': 0.00033981000430849027, 'epoch': 0.27}

 27%|██▋       | 979/3566 [39:30<1:44:31,  2.42s/it]
 27%|██▋       | 980/3566 [39:32<1:41:21,  2.35s/it]
                                                    
{'loss': 1.4518, 'learning_rate': 0.0003396803180796928, 'epoch': 0.27}

 27%|██▋       | 980/3566 [39:32<1:41:21,  2.35s/it]
 28%|██▊       | 981/3566 [39:34<1:41:37,  2.36s/it]
                                                    
{'loss': 1.8245, 'learning_rate': 0.0003395505170942579, 'epoch': 0.28}

 28%|██▊       | 981/3566 [39:34<1:41:37,  2.36s/it]
 28%|██▊       | 982/3566 [39:37<1:43:46,  2.41s/it]
                                                    
{'loss': 1.5936, 'learning_rate': 0.0003394206014588257, 'epoch': 0.28}

 28%|██▊       | 982/3566 [39:37<1:43:46,  2.41s/it]
 28%|██▊       | 983/3566 [39:39<1:43:32,  2.41s/it]
                                                    
{'loss': 1.5189, 'learning_rate': 0.00033929057128013053, 'epoch': 0.28}

 28%|██▊       | 983/3566 [39:39<1:43:32,  2.41s/it]
 28%|██▊       | 984/3566 [39:41<1:39:54,  2.32s/it]
                                                    
{'loss': 1.632, 'learning_rate': 0.0003391604266650006, 'epoch': 0.28}

 28%|██▊       | 984/3566 [39:41<1:39:54,  2.32s/it]
 28%|██▊       | 985/3566 [39:44<1:44:07,  2.42s/it]
                                                    
{'loss': 1.5355, 'learning_rate': 0.00033903016772035853, 'epoch': 0.28}

 28%|██▊       | 985/3566 [39:44<1:44:07,  2.42s/it]
 28%|██▊       | 986/3566 [39:46<1:42:06,  2.37s/it]
                                                    
{'loss': 1.5453, 'learning_rate': 0.0003388997945532206, 'epoch': 0.28}

 28%|██▊       | 986/3566 [39:46<1:42:06,  2.37s/it]
 28%|██▊       | 987/3566 [39:49<1:41:37,  2.36s/it]
                                                    
{'loss': 1.5479, 'learning_rate': 0.0003387693072706971, 'epoch': 0.28}

 28%|██▊       | 987/3566 [39:49<1:41:37,  2.36s/it]
 28%|██▊       | 988/3566 [39:51<1:46:57,  2.49s/it]
                                                    
{'loss': 1.6015, 'learning_rate': 0.0003386387059799918, 'epoch': 0.28}

 28%|██▊       | 988/3566 [39:51<1:46:57,  2.49s/it]
 28%|██▊       | 989/3566 [39:54<1:43:47,  2.42s/it]
                                                    
{'loss': 1.709, 'learning_rate': 0.0003385079907884025, 'epoch': 0.28}

 28%|██▊       | 989/3566 [39:54<1:43:47,  2.42s/it]
 28%|██▊       | 990/3566 [39:56<1:41:34,  2.37s/it]
                                                    
{'loss': 1.6344, 'learning_rate': 0.0003383771618033203, 'epoch': 0.28}

 28%|██▊       | 990/3566 [39:56<1:41:34,  2.37s/it]
 28%|██▊       | 991/3566 [39:59<1:43:51,  2.42s/it]
                                                    
{'loss': 1.709, 'learning_rate': 0.0003382462191322298, 'epoch': 0.28}

 28%|██▊       | 991/3566 [39:59<1:43:51,  2.42s/it]
 28%|██▊       | 992/3566 [40:01<1:43:03,  2.40s/it]
                                                    
{'loss': 1.5598, 'learning_rate': 0.0003381151628827092, 'epoch': 0.28}

 28%|██▊       | 992/3566 [40:01<1:43:03,  2.40s/it]
 28%|██▊       | 993/3566 [40:03<1:45:25,  2.46s/it]
                                                    
{'loss': 1.6272, 'learning_rate': 0.00033798399316242993, 'epoch': 0.28}

 28%|██▊       | 993/3566 [40:03<1:45:25,  2.46s/it]
 28%|██▊       | 994/3566 [40:06<1:43:14,  2.41s/it]
                                                    
{'loss': 1.5783, 'learning_rate': 0.00033785271007915653, 'epoch': 0.28}

 28%|██▊       | 994/3566 [40:06<1:43:14,  2.41s/it]
 28%|██▊       | 995/3566 [40:08<1:41:59,  2.38s/it]
                                                    
{'loss': 1.5724, 'learning_rate': 0.00033772131374074674, 'epoch': 0.28}

 28%|██▊       | 995/3566 [40:08<1:41:59,  2.38s/it]
 28%|██▊       | 996/3566 [40:10<1:41:22,  2.37s/it]
                                                    
{'loss': 1.6668, 'learning_rate': 0.00033758980425515136, 'epoch': 0.28}

 28%|██▊       | 996/3566 [40:10<1:41:22,  2.37s/it]
 28%|██▊       | 997/3566 [40:13<1:45:43,  2.47s/it]
                                                    
{'loss': 1.5015, 'learning_rate': 0.0003374581817304142, 'epoch': 0.28}

 28%|██▊       | 997/3566 [40:13<1:45:43,  2.47s/it]
 28%|██▊       | 998/3566 [40:16<1:49:14,  2.55s/it]
                                                    
{'loss': 1.5056, 'learning_rate': 0.0003373264462746719, 'epoch': 0.28}

 28%|██▊       | 998/3566 [40:16<1:49:14,  2.55s/it]
 28%|██▊       | 999/3566 [40:18<1:47:51,  2.52s/it]
                                                    
{'loss': 1.561, 'learning_rate': 0.0003371945979961537, 'epoch': 0.28}

 28%|██▊       | 999/3566 [40:18<1:47:51,  2.52s/it]
 28%|██▊       | 1000/3566 [40:21<1:44:05,  2.43s/it]
                                                     
{'loss': 1.5886, 'learning_rate': 0.0003370626370031819, 'epoch': 0.28}

 28%|██▊       | 1000/3566 [40:21<1:44:05,  2.43s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(

 28%|██▊       | 1001/3566 [40:23<1:45:26,  2.47s/it]
                                                     
{'loss': 1.7004, 'learning_rate': 0.0003369305634041712, 'epoch': 0.28}

 28%|██▊       | 1001/3566 [40:23<1:45:26,  2.47s/it]
 28%|██▊       | 1002/3566 [40:25<1:42:15,  2.39s/it]
                                                     
{'loss': 1.5864, 'learning_rate': 0.00033679837730762863, 'epoch': 0.28}

 28%|██▊       | 1002/3566 [40:25<1:42:15,  2.39s/it]
 28%|██▊       | 1003/3566 [40:28<1:40:16,  2.35s/it]
                                                     
{'loss': 1.6418, 'learning_rate': 0.000336666078822154, 'epoch': 0.28}

 28%|██▊       | 1003/3566 [40:28<1:40:16,  2.35s/it]
 28%|██▊       | 1004/3566 [40:30<1:41:09,  2.37s/it]
                                                     
{'loss': 1.6663, 'learning_rate': 0.0003365336680564392, 'epoch': 0.28}

 28%|██▊       | 1004/3566 [40:30<1:41:09,  2.37s/it]
 28%|██▊       | 1005/3566 [40:32<1:41:27,  2.38s/it]
                                                     
{'loss': 1.4919, 'learning_rate': 0.00033640114511926844, 'epoch': 0.28}

 28%|██▊       | 1005/3566 [40:32<1:41:27,  2.38s/it]
 28%|██▊       | 1006/3566 [40:35<1:40:22,  2.35s/it]
                                                     
{'loss': 1.5652, 'learning_rate': 0.0003362685101195181, 'epoch': 0.28}

 28%|██▊       | 1006/3566 [40:35<1:40:22,  2.35s/it]
 28%|██▊       | 1007/3566 [40:37<1:41:09,  2.37s/it]
                                                     
{'loss': 1.685, 'learning_rate': 0.0003361357631661567, 'epoch': 0.28}

 28%|██▊       | 1007/3566 [40:37<1:41:09,  2.37s/it]
 28%|██▊       | 1008/3566 [40:40<1:42:28,  2.40s/it]
                                                     
{'loss': 1.7768, 'learning_rate': 0.00033600290436824453, 'epoch': 0.28}

 28%|██▊       | 1008/3566 [40:40<1:42:28,  2.40s/it]
 28%|██▊       | 1009/3566 [40:42<1:40:59,  2.37s/it]
                                                     
{'loss': 1.4661, 'learning_rate': 0.00033586993383493406, 'epoch': 0.28}

 28%|██▊       | 1009/3566 [40:42<1:40:59,  2.37s/it]
 28%|██▊       | 1010/3566 [40:44<1:38:48,  2.32s/it]
                                                     
{'loss': 1.4692, 'learning_rate': 0.00033573685167546924, 'epoch': 0.28}

 28%|██▊       | 1010/3566 [40:44<1:38:48,  2.32s/it]
 28%|██▊       | 1011/3566 [40:48<1:55:08,  2.70s/it]
                                                     
{'loss': 1.6077, 'learning_rate': 0.00033560365799918597, 'epoch': 0.28}

 28%|██▊       | 1011/3566 [40:48<1:55:08,  2.70s/it]
 28%|██▊       | 1012/3566 [40:50<1:49:08,  2.56s/it]
                                                     
{'loss': 1.562, 'learning_rate': 0.00033547035291551163, 'epoch': 0.28}

 28%|██▊       | 1012/3566 [40:50<1:49:08,  2.56s/it]
 28%|██▊       | 1013/3566 [40:52<1:46:28,  2.50s/it]
                                                     
{'loss': 1.7198, 'learning_rate': 0.00033533693653396517, 'epoch': 0.28}

 28%|██▊       | 1013/3566 [40:52<1:46:28,  2.50s/it]
 28%|██▊       | 1014/3566 [40:55<1:44:13,  2.45s/it]
                                                     
{'loss': 1.5849, 'learning_rate': 0.00033520340896415704, 'epoch': 0.28}

 28%|██▊       | 1014/3566 [40:55<1:44:13,  2.45s/it]
 28%|██▊       | 1015/3566 [40:57<1:43:00,  2.42s/it]
                                                     
{'loss': 1.6759, 'learning_rate': 0.00033506977031578903, 'epoch': 0.28}

 28%|██▊       | 1015/3566 [40:57<1:43:00,  2.42s/it]
 28%|██▊       | 1016/3566 [41:00<1:47:04,  2.52s/it]
                                                     
{'loss': 1.5835, 'learning_rate': 0.0003349360206986541, 'epoch': 0.28}

 28%|██▊       | 1016/3566 [41:00<1:47:04,  2.52s/it]
 29%|██▊       | 1017/3566 [41:02<1:43:19,  2.43s/it]
                                                     
{'loss': 1.5427, 'learning_rate': 0.0003348021602226363, 'epoch': 0.29}

 29%|██▊       | 1017/3566 [41:02<1:43:19,  2.43s/it]
 29%|██▊       | 1018/3566 [41:05<1:56:28,  2.74s/it]
                                                     
{'loss': 1.6485, 'learning_rate': 0.00033466818899771113, 'epoch': 0.29}

 29%|██▊       | 1018/3566 [41:05<1:56:28,  2.74s/it]
 29%|██▊       | 1019/3566 [41:08<1:52:17,  2.65s/it]
                                                     
{'loss': 1.507, 'learning_rate': 0.0003345341071339446, 'epoch': 0.29}

 29%|██▊       | 1019/3566 [41:08<1:52:17,  2.65s/it]
 29%|██▊       | 1020/3566 [41:10<1:48:27,  2.56s/it]
                                                     
{'loss': 1.6952, 'learning_rate': 0.00033439991474149396, 'epoch': 0.29}

 29%|██▊       | 1020/3566 [41:10<1:48:27,  2.56s/it]
 29%|██▊       | 1021/3566 [41:13<1:49:26,  2.58s/it]
                                                     
{'loss': 1.6469, 'learning_rate': 0.0003342656119306072, 'epoch': 0.29}

 29%|██▊       | 1021/3566 [41:13<1:49:26,  2.58s/it]
 29%|██▊       | 1022/3566 [41:15<1:47:51,  2.54s/it]
                                                     
{'loss': 1.6973, 'learning_rate': 0.0003341311988116228, 'epoch': 0.29}

 29%|██▊       | 1022/3566 [41:15<1:47:51,  2.54s/it]
 29%|██▊       | 1023/3566 [41:18<1:46:45,  2.52s/it]
                                                     
{'loss': 1.5268, 'learning_rate': 0.00033399667549497016, 'epoch': 0.29}

 29%|██▊       | 1023/3566 [41:18<1:46:45,  2.52s/it]
 29%|██▊       | 1024/3566 [41:20<1:44:28,  2.47s/it]
                                                     
{'loss': 1.484, 'learning_rate': 0.0003338620420911692, 'epoch': 0.29}

 29%|██▊       | 1024/3566 [41:20<1:44:28,  2.47s/it]
 29%|██▊       | 1025/3566 [41:22<1:41:27,  2.40s/it]
                                                     
{'loss': 1.5406, 'learning_rate': 0.00033372729871082997, 'epoch': 0.29}

 29%|██▊       | 1025/3566 [41:22<1:41:27,  2.40s/it]
 29%|██▉       | 1026/3566 [41:25<1:43:21,  2.44s/it]
                                                     
{'loss': 1.6968, 'learning_rate': 0.00033359244546465324, 'epoch': 0.29}

 29%|██▉       | 1026/3566 [41:25<1:43:21,  2.44s/it]
 29%|██▉       | 1027/3566 [41:27<1:41:56,  2.41s/it]
                                                     
{'loss': 1.5439, 'learning_rate': 0.0003334574824634298, 'epoch': 0.29}

 29%|██▉       | 1027/3566 [41:27<1:41:56,  2.41s/it]
 29%|██▉       | 1028/3566 [41:29<1:40:33,  2.38s/it]
                                                     
{'loss': 1.7706, 'learning_rate': 0.00033332240981804077, 'epoch': 0.29}

 29%|██▉       | 1028/3566 [41:29<1:40:33,  2.38s/it]
 29%|██▉       | 1029/3566 [41:32<1:39:02,  2.34s/it]
                                                     
{'loss': 1.5416, 'learning_rate': 0.0003331872276394572, 'epoch': 0.29}

 29%|██▉       | 1029/3566 [41:32<1:39:02,  2.34s/it]
 29%|██▉       | 1030/3566 [41:34<1:41:27,  2.40s/it]
                                                     
{'loss': 1.5297, 'learning_rate': 0.00033305193603874034, 'epoch': 0.29}

 29%|██▉       | 1030/3566 [41:34<1:41:27,  2.40s/it]
 29%|██▉       | 1031/3566 [41:36<1:39:10,  2.35s/it]
                                                     
{'loss': 1.6227, 'learning_rate': 0.0003329165351270411, 'epoch': 0.29}

 29%|██▉       | 1031/3566 [41:36<1:39:10,  2.35s/it]
 29%|██▉       | 1032/3566 [41:39<1:37:51,  2.32s/it]
                                                     
{'loss': 1.5251, 'learning_rate': 0.0003327810250156002, 'epoch': 0.29}

 29%|██▉       | 1032/3566 [41:39<1:37:51,  2.32s/it]
 29%|██▉       | 1033/3566 [41:41<1:42:39,  2.43s/it]
                                                     
{'loss': 1.5749, 'learning_rate': 0.0003326454058157484, 'epoch': 0.29}

 29%|██▉       | 1033/3566 [41:41<1:42:39,  2.43s/it]
 29%|██▉       | 1034/3566 [41:44<1:42:42,  2.43s/it]
                                                     
{'loss': 1.5676, 'learning_rate': 0.0003325096776389058, 'epoch': 0.29}

 29%|██▉       | 1034/3566 [41:44<1:42:42,  2.43s/it]
 29%|██▉       | 1035/3566 [41:46<1:43:18,  2.45s/it]
                                                     
{'loss': 1.6995, 'learning_rate': 0.000332373840596582, 'epoch': 0.29}

 29%|██▉       | 1035/3566 [41:46<1:43:18,  2.45s/it]
 29%|██▉       | 1036/3566 [41:49<1:43:57,  2.47s/it]
                                                     
{'loss': 1.6477, 'learning_rate': 0.0003322378948003762, 'epoch': 0.29}

 29%|██▉       | 1036/3566 [41:49<1:43:57,  2.47s/it]
 29%|██▉       | 1037/3566 [41:51<1:41:36,  2.41s/it]
                                                     
{'loss': 1.5012, 'learning_rate': 0.00033210184036197685, 'epoch': 0.29}

 29%|██▉       | 1037/3566 [41:51<1:41:36,  2.41s/it]
 29%|██▉       | 1038/3566 [41:54<1:42:24,  2.43s/it]
                                                     
{'loss': 1.7402, 'learning_rate': 0.0003319656773931617, 'epoch': 0.29}

 29%|██▉       | 1038/3566 [41:54<1:42:24,  2.43s/it]
 29%|██▉       | 1039/3566 [41:56<1:41:34,  2.41s/it]
                                                     
{'loss': 1.6674, 'learning_rate': 0.0003318294060057976, 'epoch': 0.29}

 29%|██▉       | 1039/3566 [41:56<1:41:34,  2.41s/it]
 29%|██▉       | 1040/3566 [41:59<1:44:08,  2.47s/it]
                                                     
{'loss': 1.6402, 'learning_rate': 0.00033169302631184066, 'epoch': 0.29}

 29%|██▉       | 1040/3566 [41:59<1:44:08,  2.47s/it]
 29%|██▉       | 1041/3566 [42:01<1:42:24,  2.43s/it]
                                                     
{'loss': 1.6748, 'learning_rate': 0.0003315565384233357, 'epoch': 0.29}

 29%|██▉       | 1041/3566 [42:01<1:42:24,  2.43s/it]
 29%|██▉       | 1042/3566 [42:03<1:41:34,  2.41s/it]
                                                     
{'loss': 1.6319, 'learning_rate': 0.0003314199424524167, 'epoch': 0.29}

 29%|██▉       | 1042/3566 [42:03<1:41:34,  2.41s/it]
 29%|██▉       | 1043/3566 [42:06<1:41:23,  2.41s/it]
                                                     
{'loss': 1.7178, 'learning_rate': 0.0003312832385113061, 'epoch': 0.29}

 29%|██▉       | 1043/3566 [42:06<1:41:23,  2.41s/it]
 29%|██▉       | 1044/3566 [42:09<1:47:26,  2.56s/it]
                                                     
{'loss': 1.6806, 'learning_rate': 0.0003311464267123154, 'epoch': 0.29}

 29%|██▉       | 1044/3566 [42:09<1:47:26,  2.56s/it]
 29%|██▉       | 1045/3566 [42:11<1:46:15,  2.53s/it]
                                                     
{'loss': 1.4169, 'learning_rate': 0.00033100950716784456, 'epoch': 0.29}

 29%|██▉       | 1045/3566 [42:11<1:46:15,  2.53s/it]
 29%|██▉       | 1046/3566 [42:14<1:48:41,  2.59s/it]
                                                     
{'loss': 1.3883, 'learning_rate': 0.000330872479990382, 'epoch': 0.29}

 29%|██▉       | 1046/3566 [42:14<1:48:41,  2.59s/it]
 29%|██▉       | 1047/3566 [42:17<1:52:41,  2.68s/it]
                                                     
{'loss': 1.4829, 'learning_rate': 0.00033073534529250463, 'epoch': 0.29}

 29%|██▉       | 1047/3566 [42:17<1:52:41,  2.68s/it]
 29%|██▉       | 1048/3566 [42:19<1:48:37,  2.59s/it]
                                                     
{'loss': 1.5919, 'learning_rate': 0.0003305981031868777, 'epoch': 0.29}

 29%|██▉       | 1048/3566 [42:19<1:48:37,  2.59s/it]
 29%|██▉       | 1049/3566 [42:21<1:44:39,  2.49s/it]
                                                     
{'loss': 1.6668, 'learning_rate': 0.00033046075378625475, 'epoch': 0.29}

 29%|██▉       | 1049/3566 [42:21<1:44:39,  2.49s/it]
 29%|██▉       | 1050/3566 [42:24<1:45:04,  2.51s/it]
                                                     
{'loss': 1.3224, 'learning_rate': 0.00033032329720347737, 'epoch': 0.29}

 29%|██▉       | 1050/3566 [42:24<1:45:04,  2.51s/it]
 29%|██▉       | 1051/3566 [42:27<1:47:03,  2.55s/it]
                                                     
{'loss': 1.5624, 'learning_rate': 0.00033018573355147524, 'epoch': 0.29}

 29%|██▉       | 1051/3566 [42:27<1:47:03,  2.55s/it]
 30%|██▉       | 1052/3566 [42:29<1:41:42,  2.43s/it]
                                                     
{'loss': 1.3918, 'learning_rate': 0.00033004806294326605, 'epoch': 0.3}

 30%|██▉       | 1052/3566 [42:29<1:41:42,  2.43s/it]
 30%|██▉       | 1053/3566 [42:31<1:42:21,  2.44s/it]
                                                     
{'loss': 1.7946, 'learning_rate': 0.00032991028549195526, 'epoch': 0.3}

 30%|██▉       | 1053/3566 [42:31<1:42:21,  2.44s/it]
 30%|██▉       | 1054/3566 [42:34<1:43:04,  2.46s/it]
                                                     
{'loss': 1.9143, 'learning_rate': 0.0003297724013107363, 'epoch': 0.3}

 30%|██▉       | 1054/3566 [42:34<1:43:04,  2.46s/it]
 30%|██▉       | 1055/3566 [42:36<1:43:58,  2.48s/it]
                                                     
{'loss': 1.4799, 'learning_rate': 0.00032963441051288994, 'epoch': 0.3}

 30%|██▉       | 1055/3566 [42:36<1:43:58,  2.48s/it]
 30%|██▉       | 1056/3566 [42:39<1:43:12,  2.47s/it]
                                                     
{'loss': 1.3832, 'learning_rate': 0.00032949631321178504, 'epoch': 0.3}

 30%|██▉       | 1056/3566 [42:39<1:43:12,  2.47s/it]
 30%|██▉       | 1057/3566 [42:41<1:42:45,  2.46s/it]
                                                     
{'loss': 1.6206, 'learning_rate': 0.0003293581095208775, 'epoch': 0.3}

 30%|██▉       | 1057/3566 [42:41<1:42:45,  2.46s/it]
 30%|██▉       | 1058/3566 [42:44<1:44:53,  2.51s/it]
                                                     
{'loss': 1.6049, 'learning_rate': 0.0003292197995537109, 'epoch': 0.3}

 30%|██▉       | 1058/3566 [42:44<1:44:53,  2.51s/it]
 30%|██▉       | 1059/3566 [42:46<1:44:36,  2.50s/it]
                                                     
{'loss': 1.6862, 'learning_rate': 0.000329081383423916, 'epoch': 0.3}

 30%|██▉       | 1059/3566 [42:46<1:44:36,  2.50s/it]
 30%|██▉       | 1060/3566 [42:49<1:43:39,  2.48s/it]
                                                     
{'loss': 1.5244, 'learning_rate': 0.00032894286124521076, 'epoch': 0.3}

 30%|██▉       | 1060/3566 [42:49<1:43:39,  2.48s/it]
 30%|██▉       | 1061/3566 [42:51<1:43:20,  2.48s/it]
                                                     
{'loss': 1.7469, 'learning_rate': 0.00032880423313140045, 'epoch': 0.3}

 30%|██▉       | 1061/3566 [42:51<1:43:20,  2.48s/it]
 30%|██▉       | 1062/3566 [42:54<1:45:22,  2.52s/it]
                                                     
{'loss': 1.708, 'learning_rate': 0.00032866549919637717, 'epoch': 0.3}

 30%|██▉       | 1062/3566 [42:54<1:45:22,  2.52s/it]
 30%|██▉       | 1063/3566 [42:56<1:43:02,  2.47s/it]
                                                     
{'loss': 1.6796, 'learning_rate': 0.0003285266595541201, 'epoch': 0.3}

 30%|██▉       | 1063/3566 [42:56<1:43:02,  2.47s/it]
 30%|██▉       | 1064/3566 [42:59<1:45:12,  2.52s/it]
                                                     
{'loss': 1.5523, 'learning_rate': 0.00032838771431869515, 'epoch': 0.3}

 30%|██▉       | 1064/3566 [42:59<1:45:12,  2.52s/it]
 30%|██▉       | 1065/3566 [43:01<1:47:22,  2.58s/it]
                                                     
{'loss': 1.7482, 'learning_rate': 0.0003282486636042551, 'epoch': 0.3}

 30%|██▉       | 1065/3566 [43:01<1:47:22,  2.58s/it]
 30%|██▉       | 1066/3566 [43:04<1:46:02,  2.54s/it]
                                                     
{'loss': 1.7665, 'learning_rate': 0.00032810950752503923, 'epoch': 0.3}

 30%|██▉       | 1066/3566 [43:04<1:46:02,  2.54s/it]
 30%|██▉       | 1067/3566 [43:06<1:46:08,  2.55s/it]
                                                     
{'loss': 1.6417, 'learning_rate': 0.0003279702461953736, 'epoch': 0.3}

 30%|██▉       | 1067/3566 [43:06<1:46:08,  2.55s/it]
 30%|██▉       | 1068/3566 [43:09<1:44:39,  2.51s/it]
                                                     
{'loss': 1.6071, 'learning_rate': 0.0003278308797296706, 'epoch': 0.3}

 30%|██▉       | 1068/3566 [43:09<1:44:39,  2.51s/it]
 30%|██▉       | 1069/3566 [43:11<1:44:24,  2.51s/it]
                                                     
{'loss': 1.49, 'learning_rate': 0.0003276914082424289, 'epoch': 0.3}

 30%|██▉       | 1069/3566 [43:11<1:44:24,  2.51s/it]
 30%|███       | 1070/3566 [43:14<1:42:01,  2.45s/it]
                                                     
{'loss': 1.5762, 'learning_rate': 0.00032755183184823367, 'epoch': 0.3}

 30%|███       | 1070/3566 [43:14<1:42:01,  2.45s/it]
 30%|███       | 1071/3566 [43:16<1:37:51,  2.35s/it]
                                                     
{'loss': 1.5535, 'learning_rate': 0.0003274121506617562, 'epoch': 0.3}

 30%|███       | 1071/3566 [43:16<1:37:51,  2.35s/it]
 30%|███       | 1072/3566 [43:19<1:43:06,  2.48s/it]
                                                     
{'loss': 1.6236, 'learning_rate': 0.0003272723647977538, 'epoch': 0.3}

 30%|███       | 1072/3566 [43:19<1:43:06,  2.48s/it]
 30%|███       | 1073/3566 [43:21<1:39:16,  2.39s/it]
                                                     
{'loss': 1.4387, 'learning_rate': 0.0003271324743710697, 'epoch': 0.3}

 30%|███       | 1073/3566 [43:21<1:39:16,  2.39s/it]
 30%|███       | 1074/3566 [43:23<1:36:51,  2.33s/it]
                                                     
{'loss': 1.7215, 'learning_rate': 0.00032699247949663333, 'epoch': 0.3}

 30%|███       | 1074/3566 [43:23<1:36:51,  2.33s/it]
 30%|███       | 1075/3566 [43:25<1:36:05,  2.31s/it]
                                                     
{'loss': 1.5572, 'learning_rate': 0.0003268523802894596, 'epoch': 0.3}

 30%|███       | 1075/3566 [43:25<1:36:05,  2.31s/it]
 30%|███       | 1076/3566 [43:28<1:39:29,  2.40s/it]
                                                     
{'loss': 1.7069, 'learning_rate': 0.0003267121768646495, 'epoch': 0.3}

 30%|███       | 1076/3566 [43:28<1:39:29,  2.40s/it]
 30%|███       | 1077/3566 [43:30<1:37:03,  2.34s/it]
                                                     
{'loss': 1.6241, 'learning_rate': 0.00032657186933738935, 'epoch': 0.3}

 30%|███       | 1077/3566 [43:30<1:37:03,  2.34s/it]
 30%|███       | 1078/3566 [43:33<1:41:21,  2.44s/it]
                                                     
{'loss': 1.556, 'learning_rate': 0.00032643145782295096, 'epoch': 0.3}

 30%|███       | 1078/3566 [43:33<1:41:21,  2.44s/it]
 30%|███       | 1079/3566 [43:35<1:40:58,  2.44s/it]
                                                     
{'loss': 1.802, 'learning_rate': 0.00032629094243669175, 'epoch': 0.3}

 30%|███       | 1079/3566 [43:35<1:40:58,  2.44s/it]
 30%|███       | 1080/3566 [43:37<1:38:50,  2.39s/it]
                                                     
{'loss': 1.5444, 'learning_rate': 0.00032615032329405454, 'epoch': 0.3}

 30%|███       | 1080/3566 [43:37<1:38:50,  2.39s/it]
 30%|███       | 1081/3566 [43:40<1:38:01,  2.37s/it]
                                                     
{'loss': 1.5606, 'learning_rate': 0.00032600960051056715, 'epoch': 0.3}

 30%|███       | 1081/3566 [43:40<1:38:01,  2.37s/it]
 30%|███       | 1082/3566 [43:42<1:37:35,  2.36s/it]
                                                     
{'loss': 1.5156, 'learning_rate': 0.0003258687742018427, 'epoch': 0.3}

 30%|███       | 1082/3566 [43:42<1:37:35,  2.36s/it]
 30%|███       | 1083/3566 [43:44<1:38:14,  2.37s/it]
                                                     
{'loss': 1.5738, 'learning_rate': 0.0003257278444835793, 'epoch': 0.3}

 30%|███       | 1083/3566 [43:44<1:38:14,  2.37s/it]
 30%|███       | 1084/3566 [43:47<1:38:38,  2.38s/it]
                                                     
{'loss': 1.7141, 'learning_rate': 0.00032558681147156014, 'epoch': 0.3}

 30%|███       | 1084/3566 [43:47<1:38:38,  2.38s/it]
 30%|███       | 1085/3566 [43:49<1:36:20,  2.33s/it]
                                                     
{'loss': 1.6297, 'learning_rate': 0.0003254456752816532, 'epoch': 0.3}

 30%|███       | 1085/3566 [43:49<1:36:20,  2.33s/it]
 30%|███       | 1086/3566 [43:51<1:35:16,  2.30s/it]
                                                     
{'loss': 1.5697, 'learning_rate': 0.00032530443602981105, 'epoch': 0.3}

 30%|███       | 1086/3566 [43:51<1:35:16,  2.30s/it]
 30%|███       | 1087/3566 [43:54<1:34:09,  2.28s/it]
                                                     
{'loss': 1.5531, 'learning_rate': 0.0003251630938320713, 'epoch': 0.3}

 30%|███       | 1087/3566 [43:54<1:34:09,  2.28s/it]
 31%|███       | 1088/3566 [43:56<1:37:10,  2.35s/it]
                                                     
{'loss': 1.457, 'learning_rate': 0.0003250216488045558, 'epoch': 0.31}

 31%|███       | 1088/3566 [43:56<1:37:10,  2.35s/it]
 31%|███       | 1089/3566 [43:59<1:38:33,  2.39s/it]
                                                     
{'loss': 1.4773, 'learning_rate': 0.000324880101063471, 'epoch': 0.31}

 31%|███       | 1089/3566 [43:59<1:38:33,  2.39s/it]
 31%|███       | 1090/3566 [44:01<1:38:33,  2.39s/it]
                                                     
{'loss': 1.4973, 'learning_rate': 0.0003247384507251078, 'epoch': 0.31}

 31%|███       | 1090/3566 [44:01<1:38:33,  2.39s/it]
 31%|███       | 1091/3566 [44:03<1:39:54,  2.42s/it]
                                                     
{'loss': 1.5522, 'learning_rate': 0.0003245966979058413, 'epoch': 0.31}

 31%|███       | 1091/3566 [44:03<1:39:54,  2.42s/it]
 31%|███       | 1092/3566 [44:06<1:39:16,  2.41s/it]
                                                     
{'loss': 1.5904, 'learning_rate': 0.00032445484272213096, 'epoch': 0.31}

 31%|███       | 1092/3566 [44:06<1:39:16,  2.41s/it]
 31%|███       | 1093/3566 [44:08<1:39:25,  2.41s/it]
                                                     
{'loss': 1.6103, 'learning_rate': 0.0003243128852905201, 'epoch': 0.31}

 31%|███       | 1093/3566 [44:08<1:39:25,  2.41s/it]
 31%|███       | 1094/3566 [44:11<1:40:48,  2.45s/it]
                                                     
{'loss': 1.5589, 'learning_rate': 0.00032417082572763615, 'epoch': 0.31}

 31%|███       | 1094/3566 [44:11<1:40:48,  2.45s/it]
 31%|███       | 1095/3566 [44:13<1:40:05,  2.43s/it]
                                                     
{'loss': 1.6806, 'learning_rate': 0.00032402866415019043, 'epoch': 0.31}

 31%|███       | 1095/3566 [44:13<1:40:05,  2.43s/it]
 31%|███       | 1096/3566 [44:16<1:39:55,  2.43s/it]
                                                     
{'loss': 1.6955, 'learning_rate': 0.0003238864006749783, 'epoch': 0.31}

 31%|███       | 1096/3566 [44:16<1:39:55,  2.43s/it]
 31%|███       | 1097/3566 [44:18<1:39:14,  2.41s/it]
                                                     
{'loss': 1.5308, 'learning_rate': 0.00032374403541887833, 'epoch': 0.31}

 31%|███       | 1097/3566 [44:18<1:39:14,  2.41s/it]
 31%|███       | 1098/3566 [44:20<1:36:33,  2.35s/it]
                                                     
{'loss': 1.5559, 'learning_rate': 0.0003236015684988532, 'epoch': 0.31}

 31%|███       | 1098/3566 [44:20<1:36:33,  2.35s/it]
 31%|███       | 1099/3566 [44:22<1:34:13,  2.29s/it]
                                                     
{'loss': 1.531, 'learning_rate': 0.00032345900003194895, 'epoch': 0.31}

 31%|███       | 1099/3566 [44:22<1:34:13,  2.29s/it]
 31%|███       | 1100/3566 [44:25<1:33:31,  2.28s/it]
                                                     
{'loss': 1.5571, 'learning_rate': 0.0003233163301352949, 'epoch': 0.31}

 31%|███       | 1100/3566 [44:25<1:33:31,  2.28s/it]
 31%|███       | 1101/3566 [44:27<1:34:48,  2.31s/it]
                                                     
{'loss': 1.4935, 'learning_rate': 0.00032317355892610386, 'epoch': 0.31}

 31%|███       | 1101/3566 [44:27<1:34:48,  2.31s/it]
 31%|███       | 1102/3566 [44:29<1:35:14,  2.32s/it]
                                                     
{'loss': 1.6009, 'learning_rate': 0.00032303068652167195, 'epoch': 0.31}

 31%|███       | 1102/3566 [44:29<1:35:14,  2.32s/it]
 31%|███       | 1103/3566 [44:32<1:40:06,  2.44s/it]
                                                     
{'loss': 1.7522, 'learning_rate': 0.0003228877130393782, 'epoch': 0.31}

 31%|███       | 1103/3566 [44:32<1:40:06,  2.44s/it]
 31%|███       | 1104/3566 [44:34<1:38:58,  2.41s/it]
                                                     
{'loss': 1.5671, 'learning_rate': 0.0003227446385966848, 'epoch': 0.31}

 31%|███       | 1104/3566 [44:34<1:38:58,  2.41s/it]
 31%|███       | 1105/3566 [44:37<1:38:19,  2.40s/it]
                                                     
{'loss': 1.468, 'learning_rate': 0.000322601463311137, 'epoch': 0.31}

 31%|███       | 1105/3566 [44:37<1:38:19,  2.40s/it]
 31%|███       | 1106/3566 [44:39<1:37:16,  2.37s/it]
                                                     
{'loss': 1.4573, 'learning_rate': 0.00032245818730036263, 'epoch': 0.31}

 31%|███       | 1106/3566 [44:39<1:37:16,  2.37s/it]
 31%|███       | 1107/3566 [44:41<1:38:09,  2.39s/it]
                                                     
{'loss': 1.7848, 'learning_rate': 0.0003223148106820725, 'epoch': 0.31}

 31%|███       | 1107/3566 [44:41<1:38:09,  2.39s/it]
 31%|███       | 1108/3566 [44:44<1:36:59,  2.37s/it]
                                                     
{'loss': 1.7604, 'learning_rate': 0.00032217133357406003, 'epoch': 0.31}

 31%|███       | 1108/3566 [44:44<1:36:59,  2.37s/it]
 31%|███       | 1109/3566 [44:46<1:35:50,  2.34s/it]
                                                     
{'loss': 1.7273, 'learning_rate': 0.00032202775609420115, 'epoch': 0.31}

 31%|███       | 1109/3566 [44:46<1:35:50,  2.34s/it]
 31%|███       | 1110/3566 [44:48<1:35:21,  2.33s/it]
                                                     
{'loss': 1.6537, 'learning_rate': 0.00032188407836045423, 'epoch': 0.31}

 31%|███       | 1110/3566 [44:48<1:35:21,  2.33s/it]
 31%|███       | 1111/3566 [44:51<1:40:15,  2.45s/it]
                                                     
{'loss': 1.4706, 'learning_rate': 0.00032174030049086016, 'epoch': 0.31}

 31%|███       | 1111/3566 [44:51<1:40:15,  2.45s/it]
 31%|███       | 1112/3566 [44:53<1:38:36,  2.41s/it]
                                                     
{'loss': 1.472, 'learning_rate': 0.00032159642260354184, 'epoch': 0.31}

 31%|███       | 1112/3566 [44:53<1:38:36,  2.41s/it]
 31%|███       | 1113/3566 [44:56<1:37:42,  2.39s/it]
                                                     
{'loss': 1.605, 'learning_rate': 0.00032145244481670464, 'epoch': 0.31}

 31%|███       | 1113/3566 [44:56<1:37:42,  2.39s/it]
 31%|███       | 1114/3566 [44:58<1:36:38,  2.36s/it]
                                                     
{'loss': 1.6392, 'learning_rate': 0.00032130836724863577, 'epoch': 0.31}

 31%|███       | 1114/3566 [44:58<1:36:38,  2.36s/it]
 31%|███▏      | 1115/3566 [45:01<1:38:31,  2.41s/it]
                                                     
{'loss': 1.747, 'learning_rate': 0.00032116419001770446, 'epoch': 0.31}

 31%|███▏      | 1115/3566 [45:01<1:38:31,  2.41s/it]
 31%|███▏      | 1116/3566 [45:03<1:37:59,  2.40s/it]
                                                     
{'loss': 1.6071, 'learning_rate': 0.0003210199132423619, 'epoch': 0.31}

 31%|███▏      | 1116/3566 [45:03<1:37:59,  2.40s/it]
 31%|███▏      | 1117/3566 [45:05<1:37:58,  2.40s/it]
                                                     
{'loss': 1.6046, 'learning_rate': 0.0003208755370411411, 'epoch': 0.31}

 31%|███▏      | 1117/3566 [45:05<1:37:58,  2.40s/it]
 31%|███▏      | 1118/3566 [45:08<1:42:57,  2.52s/it]
                                                     
{'loss': 1.5948, 'learning_rate': 0.00032073106153265656, 'epoch': 0.31}

 31%|███▏      | 1118/3566 [45:08<1:42:57,  2.52s/it]
 31%|███▏      | 1119/3566 [45:11<1:42:23,  2.51s/it]
                                                     
{'loss': 1.5413, 'learning_rate': 0.00032058648683560453, 'epoch': 0.31}

 31%|███▏      | 1119/3566 [45:11<1:42:23,  2.51s/it]
 31%|███▏      | 1120/3566 [45:13<1:39:35,  2.44s/it]
                                                     
{'loss': 1.5848, 'learning_rate': 0.0003204418130687627, 'epoch': 0.31}

 31%|███▏      | 1120/3566 [45:13<1:39:35,  2.44s/it]
 31%|███▏      | 1121/3566 [45:15<1:36:48,  2.38s/it]
                                                     
{'loss': 1.5756, 'learning_rate': 0.00032029704035099017, 'epoch': 0.31}

 31%|███▏      | 1121/3566 [45:15<1:36:48,  2.38s/it]
 31%|███▏      | 1122/3566 [45:17<1:34:24,  2.32s/it]
                                                     
{'loss': 1.4922, 'learning_rate': 0.0003201521688012273, 'epoch': 0.31}

 31%|███▏      | 1122/3566 [45:17<1:34:24,  2.32s/it]
 31%|███▏      | 1123/3566 [45:20<1:35:13,  2.34s/it]
                                                     
{'loss': 1.6451, 'learning_rate': 0.00032000719853849573, 'epoch': 0.31}

 31%|███▏      | 1123/3566 [45:20<1:35:13,  2.34s/it]
 32%|███▏      | 1124/3566 [45:22<1:38:29,  2.42s/it]
                                                     
{'loss': 1.6512, 'learning_rate': 0.00031986212968189805, 'epoch': 0.32}

 32%|███▏      | 1124/3566 [45:22<1:38:29,  2.42s/it]
 32%|███▏      | 1125/3566 [45:25<1:39:36,  2.45s/it]
                                                     
{'loss': 1.8236, 'learning_rate': 0.000319716962350618, 'epoch': 0.32}

 32%|███▏      | 1125/3566 [45:25<1:39:36,  2.45s/it]
 32%|███▏      | 1126/3566 [45:27<1:40:29,  2.47s/it]
                                                     
{'loss': 1.7257, 'learning_rate': 0.00031957169666392007, 'epoch': 0.32}

 32%|███▏      | 1126/3566 [45:27<1:40:29,  2.47s/it]
 32%|███▏      | 1127/3566 [45:30<1:39:40,  2.45s/it]
                                                     
{'loss': 1.6207, 'learning_rate': 0.0003194263327411497, 'epoch': 0.32}

 32%|███▏      | 1127/3566 [45:30<1:39:40,  2.45s/it]
 32%|███▏      | 1128/3566 [45:32<1:37:47,  2.41s/it]
                                                     
{'loss': 1.6075, 'learning_rate': 0.0003192808707017331, 'epoch': 0.32}

 32%|███▏      | 1128/3566 [45:32<1:37:47,  2.41s/it]
 32%|███▏      | 1129/3566 [45:34<1:37:26,  2.40s/it]
                                                     
{'loss': 1.506, 'learning_rate': 0.00031913531066517687, 'epoch': 0.32}

 32%|███▏      | 1129/3566 [45:34<1:37:26,  2.40s/it]
 32%|███▏      | 1130/3566 [45:37<1:36:31,  2.38s/it]
                                                     
{'loss': 1.4684, 'learning_rate': 0.00031898965275106825, 'epoch': 0.32}

 32%|███▏      | 1130/3566 [45:37<1:36:31,  2.38s/it]
 32%|███▏      | 1131/3566 [45:39<1:39:13,  2.44s/it]
                                                     
{'loss': 1.5826, 'learning_rate': 0.0003188438970790748, 'epoch': 0.32}

 32%|███▏      | 1131/3566 [45:39<1:39:13,  2.44s/it]
 32%|███▏      | 1132/3566 [45:42<1:38:03,  2.42s/it]
                                                     
{'loss': 1.5985, 'learning_rate': 0.0003186980437689445, 'epoch': 0.32}

 32%|███▏      | 1132/3566 [45:42<1:38:03,  2.42s/it]
 32%|███▏      | 1133/3566 [45:44<1:35:31,  2.36s/it]
                                                     
{'loss': 1.501, 'learning_rate': 0.00031855209294050555, 'epoch': 0.32}

 32%|███▏      | 1133/3566 [45:44<1:35:31,  2.36s/it]
 32%|███▏      | 1134/3566 [45:46<1:35:12,  2.35s/it]
                                                     
{'loss': 1.5743, 'learning_rate': 0.0003184060447136662, 'epoch': 0.32}

 32%|███▏      | 1134/3566 [45:46<1:35:12,  2.35s/it]
 32%|███▏      | 1135/3566 [45:48<1:33:17,  2.30s/it]
                                                     
{'loss': 1.5378, 'learning_rate': 0.00031825989920841475, 'epoch': 0.32}

 32%|███▏      | 1135/3566 [45:48<1:33:17,  2.30s/it]
 32%|███▏      | 1136/3566 [45:51<1:33:45,  2.32s/it]
                                                     
{'loss': 1.6063, 'learning_rate': 0.00031811365654481935, 'epoch': 0.32}

 32%|███▏      | 1136/3566 [45:51<1:33:45,  2.32s/it]
 32%|███▏      | 1137/3566 [45:53<1:33:08,  2.30s/it]
                                                     
{'loss': 1.6827, 'learning_rate': 0.0003179673168430282, 'epoch': 0.32}

 32%|███▏      | 1137/3566 [45:53<1:33:08,  2.30s/it]
 32%|███▏      | 1138/3566 [45:56<1:35:55,  2.37s/it]
                                                     
{'loss': 1.6636, 'learning_rate': 0.00031782088022326896, 'epoch': 0.32}

 32%|███▏      | 1138/3566 [45:56<1:35:55,  2.37s/it]
 32%|███▏      | 1139/3566 [45:59<1:48:47,  2.69s/it]
                                                     
{'loss': 1.4996, 'learning_rate': 0.000317674346805849, 'epoch': 0.32}

 32%|███▏      | 1139/3566 [45:59<1:48:47,  2.69s/it]
 32%|███▏      | 1140/3566 [46:01<1:41:54,  2.52s/it]
                                                     
{'loss': 1.5111, 'learning_rate': 0.0003175277167111552, 'epoch': 0.32}

 32%|███▏      | 1140/3566 [46:01<1:41:54,  2.52s/it]
 32%|███▏      | 1141/3566 [46:04<1:39:48,  2.47s/it]
                                                     
{'loss': 1.6358, 'learning_rate': 0.000317380990059654, 'epoch': 0.32}

 32%|███▏      | 1141/3566 [46:04<1:39:48,  2.47s/it]
 32%|███▏      | 1142/3566 [46:06<1:38:22,  2.44s/it]
                                                     
{'loss': 1.6654, 'learning_rate': 0.0003172341669718911, 'epoch': 0.32}

 32%|███▏      | 1142/3566 [46:06<1:38:22,  2.44s/it]
 32%|███▏      | 1143/3566 [46:08<1:37:36,  2.42s/it]
                                                     
{'loss': 1.5866, 'learning_rate': 0.00031708724756849123, 'epoch': 0.32}

 32%|███▏      | 1143/3566 [46:08<1:37:36,  2.42s/it]
 32%|███▏      | 1144/3566 [46:11<1:36:56,  2.40s/it]
                                                     
{'loss': 1.5739, 'learning_rate': 0.0003169402319701585, 'epoch': 0.32}

 32%|███▏      | 1144/3566 [46:11<1:36:56,  2.40s/it]
 32%|███▏      | 1145/3566 [46:13<1:35:01,  2.35s/it]
                                                     
{'loss': 1.5787, 'learning_rate': 0.000316793120297676, 'epoch': 0.32}

 32%|███▏      | 1145/3566 [46:13<1:35:01,  2.35s/it]
 32%|███▏      | 1146/3566 [46:15<1:36:53,  2.40s/it]
                                                     
{'loss': 1.6545, 'learning_rate': 0.0003166459126719057, 'epoch': 0.32}

 32%|███▏      | 1146/3566 [46:15<1:36:53,  2.40s/it]
 32%|███▏      | 1147/3566 [46:18<1:36:01,  2.38s/it]
                                                     
{'loss': 1.7071, 'learning_rate': 0.0003164986092137884, 'epoch': 0.32}

 32%|███▏      | 1147/3566 [46:18<1:36:01,  2.38s/it]
 32%|███▏      | 1148/3566 [46:20<1:35:22,  2.37s/it]
                                                     
{'loss': 1.5618, 'learning_rate': 0.00031635121004434366, 'epoch': 0.32}

 32%|███▏      | 1148/3566 [46:20<1:35:22,  2.37s/it]
 32%|███▏      | 1149/3566 [46:23<1:37:05,  2.41s/it]
                                                     
{'loss': 1.3392, 'learning_rate': 0.00031620371528466964, 'epoch': 0.32}

 32%|███▏      | 1149/3566 [46:23<1:37:05,  2.41s/it]
 32%|███▏      | 1150/3566 [46:25<1:37:31,  2.42s/it]
                                                     
{'loss': 1.6128, 'learning_rate': 0.00031605612505594314, 'epoch': 0.32}

 32%|███▏      | 1150/3566 [46:25<1:37:31,  2.42s/it]
 32%|███▏      | 1151/3566 [46:28<1:39:29,  2.47s/it]
                                                     
{'loss': 1.5969, 'learning_rate': 0.0003159084394794192, 'epoch': 0.32}

 32%|███▏      | 1151/3566 [46:28<1:39:29,  2.47s/it]
 32%|███▏      | 1152/3566 [46:30<1:38:25,  2.45s/it]
                                                     
{'loss': 1.5725, 'learning_rate': 0.00031576065867643143, 'epoch': 0.32}

 32%|███▏      | 1152/3566 [46:30<1:38:25,  2.45s/it]
 32%|███▏      | 1153/3566 [46:33<1:42:32,  2.55s/it]
                                                     
{'loss': 1.5855, 'learning_rate': 0.0003156127827683914, 'epoch': 0.32}

 32%|███▏      | 1153/3566 [46:33<1:42:32,  2.55s/it]
 32%|███▏      | 1154/3566 [46:36<1:45:51,  2.63s/it]
                                                     
{'loss': 1.558, 'learning_rate': 0.0003154648118767891, 'epoch': 0.32}

 32%|███▏      | 1154/3566 [46:36<1:45:51,  2.63s/it]
 32%|███▏      | 1155/3566 [46:38<1:41:09,  2.52s/it]
                                                     
{'loss': 1.5026, 'learning_rate': 0.00031531674612319237, 'epoch': 0.32}

 32%|███▏      | 1155/3566 [46:38<1:41:09,  2.52s/it]
 32%|███▏      | 1156/3566 [46:40<1:39:11,  2.47s/it]
                                                     
{'loss': 1.5938, 'learning_rate': 0.0003151685856292471, 'epoch': 0.32}

 32%|███▏      | 1156/3566 [46:40<1:39:11,  2.47s/it]
 32%|███▏      | 1157/3566 [46:43<1:37:16,  2.42s/it]
                                                     
{'loss': 1.5771, 'learning_rate': 0.00031502033051667686, 'epoch': 0.32}

 32%|███▏      | 1157/3566 [46:43<1:37:16,  2.42s/it]
 32%|███▏      | 1158/3566 [46:45<1:36:24,  2.40s/it]
                                                     
{'loss': 1.564, 'learning_rate': 0.00031487198090728307, 'epoch': 0.32}

 32%|███▏      | 1158/3566 [46:45<1:36:24,  2.40s/it]
 33%|███▎      | 1159/3566 [46:47<1:35:06,  2.37s/it]
                                                     
{'loss': 1.551, 'learning_rate': 0.00031472353692294484, 'epoch': 0.33}

 33%|███▎      | 1159/3566 [46:47<1:35:06,  2.37s/it]
 33%|███▎      | 1160/3566 [46:50<1:39:11,  2.47s/it]
                                                     
{'loss': 1.7344, 'learning_rate': 0.00031457499868561866, 'epoch': 0.33}

 33%|███▎      | 1160/3566 [46:50<1:39:11,  2.47s/it]
 33%|███▎      | 1161/3566 [46:52<1:38:24,  2.45s/it]
                                                     
{'loss': 1.6058, 'learning_rate': 0.0003144263663173385, 'epoch': 0.33}

 33%|███▎      | 1161/3566 [46:52<1:38:24,  2.45s/it]
 33%|███▎      | 1162/3566 [46:55<1:39:18,  2.48s/it]
                                                     
{'loss': 1.6153, 'learning_rate': 0.00031427763994021585, 'epoch': 0.33}

 33%|███▎      | 1162/3566 [46:55<1:39:18,  2.48s/it]
 33%|███▎      | 1163/3566 [46:57<1:40:07,  2.50s/it]
                                                     
{'loss': 1.6389, 'learning_rate': 0.0003141288196764392, 'epoch': 0.33}

 33%|███▎      | 1163/3566 [46:57<1:40:07,  2.50s/it]
 33%|███▎      | 1164/3566 [47:00<1:37:12,  2.43s/it]
                                                     
{'loss': 1.6039, 'learning_rate': 0.00031397990564827424, 'epoch': 0.33}

 33%|███▎      | 1164/3566 [47:00<1:37:12,  2.43s/it]
 33%|███▎      | 1165/3566 [47:02<1:34:34,  2.36s/it]
                                                     
{'loss': 1.5565, 'learning_rate': 0.0003138308979780637, 'epoch': 0.33}

 33%|███▎      | 1165/3566 [47:02<1:34:34,  2.36s/it]
 33%|███▎      | 1166/3566 [47:05<1:39:27,  2.49s/it]
                                                     
{'loss': 1.453, 'learning_rate': 0.00031368179678822726, 'epoch': 0.33}

 33%|███▎      | 1166/3566 [47:05<1:39:27,  2.49s/it]
 33%|███▎      | 1167/3566 [47:07<1:35:12,  2.38s/it]
                                                     
{'loss': 1.6155, 'learning_rate': 0.0003135326022012614, 'epoch': 0.33}

 33%|███▎      | 1167/3566 [47:07<1:35:12,  2.38s/it]
 33%|███▎      | 1168/3566 [47:09<1:33:22,  2.34s/it]
                                                     
{'loss': 1.5345, 'learning_rate': 0.0003133833143397395, 'epoch': 0.33}

 33%|███▎      | 1168/3566 [47:09<1:33:22,  2.34s/it]
 33%|███▎      | 1169/3566 [47:12<1:38:48,  2.47s/it]
                                                     
{'loss': 1.5031, 'learning_rate': 0.0003132339333263113, 'epoch': 0.33}

 33%|███▎      | 1169/3566 [47:12<1:38:48,  2.47s/it]
 33%|███▎      | 1170/3566 [47:14<1:35:38,  2.40s/it]
                                                     
{'loss': 1.5716, 'learning_rate': 0.0003130844592837033, 'epoch': 0.33}

 33%|███▎      | 1170/3566 [47:14<1:35:38,  2.40s/it]
 33%|███▎      | 1171/3566 [47:16<1:35:40,  2.40s/it]
                                                     
{'loss': 1.5669, 'learning_rate': 0.0003129348923347182, 'epoch': 0.33}

 33%|███▎      | 1171/3566 [47:16<1:35:40,  2.40s/it]
 33%|███▎      | 1172/3566 [47:19<1:32:58,  2.33s/it]
                                                     
{'loss': 1.6134, 'learning_rate': 0.0003127852326022353, 'epoch': 0.33}

 33%|███▎      | 1172/3566 [47:19<1:32:58,  2.33s/it]
 33%|███▎      | 1173/3566 [47:21<1:32:51,  2.33s/it]
                                                     
{'loss': 1.5915, 'learning_rate': 0.00031263548020920987, 'epoch': 0.33}

 33%|███▎      | 1173/3566 [47:21<1:32:51,  2.33s/it]
 33%|███▎      | 1174/3566 [47:23<1:34:12,  2.36s/it]
                                                     
{'loss': 1.7203, 'learning_rate': 0.0003124856352786735, 'epoch': 0.33}

 33%|███▎      | 1174/3566 [47:23<1:34:12,  2.36s/it]
 33%|███▎      | 1175/3566 [47:26<1:34:13,  2.36s/it]
                                                     
{'loss': 1.6924, 'learning_rate': 0.00031233569793373366, 'epoch': 0.33}

 33%|███▎      | 1175/3566 [47:26<1:34:13,  2.36s/it]
 33%|███▎      | 1176/3566 [47:28<1:37:49,  2.46s/it]
                                                     
{'loss': 1.4656, 'learning_rate': 0.0003121856682975739, 'epoch': 0.33}

 33%|███▎      | 1176/3566 [47:28<1:37:49,  2.46s/it]
 33%|███▎      | 1177/3566 [47:31<1:36:34,  2.43s/it]
                                                     
{'loss': 1.5214, 'learning_rate': 0.00031203554649345347, 'epoch': 0.33}

 33%|███▎      | 1177/3566 [47:31<1:36:34,  2.43s/it]
 33%|███▎      | 1178/3566 [47:33<1:39:43,  2.51s/it]
                                                     
{'loss': 1.6814, 'learning_rate': 0.0003118853326447074, 'epoch': 0.33}

 33%|███▎      | 1178/3566 [47:33<1:39:43,  2.51s/it]
 33%|███▎      | 1179/3566 [47:36<1:39:23,  2.50s/it]
                                                     
{'loss': 1.5776, 'learning_rate': 0.00031173502687474624, 'epoch': 0.33}

 33%|███▎      | 1179/3566 [47:36<1:39:23,  2.50s/it]
 33%|███▎      | 1180/3566 [47:38<1:35:56,  2.41s/it]
                                                     
{'loss': 1.6242, 'learning_rate': 0.00031158462930705623, 'epoch': 0.33}

 33%|███▎      | 1180/3566 [47:38<1:35:56,  2.41s/it]
 33%|███▎      | 1181/3566 [47:41<1:36:18,  2.42s/it]
                                                     
{'loss': 1.5993, 'learning_rate': 0.0003114341400651989, 'epoch': 0.33}

 33%|███▎      | 1181/3566 [47:41<1:36:18,  2.42s/it]
 33%|███▎      | 1182/3566 [47:43<1:36:03,  2.42s/it]
                                                     
{'loss': 1.6489, 'learning_rate': 0.0003112835592728111, 'epoch': 0.33}

 33%|███▎      | 1182/3566 [47:43<1:36:03,  2.42s/it]
 33%|███▎      | 1183/3566 [47:46<1:42:13,  2.57s/it]
                                                     
{'loss': 1.5243, 'learning_rate': 0.000311132887053605, 'epoch': 0.33}

 33%|███▎      | 1183/3566 [47:46<1:42:13,  2.57s/it]
 33%|███▎      | 1184/3566 [47:48<1:38:41,  2.49s/it]
                                                     
{'loss': 1.6148, 'learning_rate': 0.0003109821235313678, 'epoch': 0.33}

 33%|███▎      | 1184/3566 [47:48<1:38:41,  2.49s/it]
 33%|███▎      | 1185/3566 [47:51<1:38:14,  2.48s/it]
                                                     
{'loss': 1.5741, 'learning_rate': 0.00031083126882996173, 'epoch': 0.33}

 33%|███▎      | 1185/3566 [47:51<1:38:14,  2.48s/it]
 33%|███▎      | 1186/3566 [47:53<1:33:37,  2.36s/it]
                                                     
{'loss': 1.6274, 'learning_rate': 0.00031068032307332387, 'epoch': 0.33}

 33%|███▎      | 1186/3566 [47:53<1:33:37,  2.36s/it]
 33%|███▎      | 1187/3566 [47:55<1:31:20,  2.30s/it]
                                                     
{'loss': 1.4296, 'learning_rate': 0.0003105292863854662, 'epoch': 0.33}

 33%|███▎      | 1187/3566 [47:55<1:31:20,  2.30s/it]
 33%|███▎      | 1188/3566 [47:57<1:32:09,  2.33s/it]
                                                     
{'loss': 1.6334, 'learning_rate': 0.00031037815889047536, 'epoch': 0.33}

 33%|███▎      | 1188/3566 [47:57<1:32:09,  2.33s/it]
 33%|███▎      | 1189/3566 [48:00<1:33:33,  2.36s/it]
                                                     
{'loss': 1.7279, 'learning_rate': 0.00031022694071251253, 'epoch': 0.33}

 33%|███▎      | 1189/3566 [48:00<1:33:33,  2.36s/it]
 33%|███▎      | 1190/3566 [48:02<1:36:26,  2.44s/it]
                                                     
{'loss': 1.6015, 'learning_rate': 0.0003100756319758137, 'epoch': 0.33}

 33%|███▎      | 1190/3566 [48:02<1:36:26,  2.44s/it]
 33%|███▎      | 1191/3566 [48:05<1:43:54,  2.63s/it]
                                                     
{'loss': 1.5406, 'learning_rate': 0.0003099242328046887, 'epoch': 0.33}

 33%|███▎      | 1191/3566 [48:05<1:43:54,  2.63s/it]
 33%|███▎      | 1192/3566 [48:08<1:39:27,  2.51s/it]
                                                     
{'loss': 1.6772, 'learning_rate': 0.00030977274332352224, 'epoch': 0.33}

 33%|███▎      | 1192/3566 [48:08<1:39:27,  2.51s/it]
 33%|███▎      | 1193/3566 [48:10<1:36:32,  2.44s/it]
                                                     
{'loss': 1.634, 'learning_rate': 0.00030962116365677286, 'epoch': 0.33}

 33%|███▎      | 1193/3566 [48:10<1:36:32,  2.44s/it]
 33%|███▎      | 1194/3566 [48:13<1:41:07,  2.56s/it]
                                                     
{'loss': 1.5997, 'learning_rate': 0.0003094694939289733, 'epoch': 0.33}

 33%|███▎      | 1194/3566 [48:13<1:41:07,  2.56s/it]
 34%|███▎      | 1195/3566 [48:15<1:39:40,  2.52s/it]
                                                     
{'loss': 1.6244, 'learning_rate': 0.00030931773426473027, 'epoch': 0.34}

 34%|███▎      | 1195/3566 [48:15<1:39:40,  2.52s/it]
 34%|███▎      | 1196/3566 [48:18<1:37:38,  2.47s/it]
                                                     
{'loss': 1.6461, 'learning_rate': 0.0003091658847887244, 'epoch': 0.34}

 34%|███▎      | 1196/3566 [48:18<1:37:38,  2.47s/it]
 34%|███▎      | 1197/3566 [48:20<1:39:20,  2.52s/it]
                                                     
{'loss': 1.7696, 'learning_rate': 0.00030901394562571024, 'epoch': 0.34}

 34%|███▎      | 1197/3566 [48:20<1:39:20,  2.52s/it]
 34%|███▎      | 1198/3566 [48:23<1:40:13,  2.54s/it]
                                                     
{'loss': 1.6668, 'learning_rate': 0.00030886191690051565, 'epoch': 0.34}

 34%|███▎      | 1198/3566 [48:23<1:40:13,  2.54s/it]
 34%|███▎      | 1199/3566 [48:25<1:38:47,  2.50s/it]
                                                     
{'loss': 1.5908, 'learning_rate': 0.00030870979873804245, 'epoch': 0.34}

 34%|███▎      | 1199/3566 [48:25<1:38:47,  2.50s/it]
 34%|███▎      | 1200/3566 [48:28<1:39:23,  2.52s/it]
                                                     
{'loss': 1.6645, 'learning_rate': 0.0003085575912632658, 'epoch': 0.34}

 34%|███▎      | 1200/3566 [48:28<1:39:23,  2.52s/it]
 34%|███▎      | 1201/3566 [48:30<1:39:22,  2.52s/it]
                                                     
{'loss': 1.5892, 'learning_rate': 0.0003084052946012341, 'epoch': 0.34}

 34%|███▎      | 1201/3566 [48:30<1:39:22,  2.52s/it]
 34%|███▎      | 1202/3566 [48:33<1:38:36,  2.50s/it]
                                                     
{'loss': 1.5513, 'learning_rate': 0.0003082529088770693, 'epoch': 0.34}

 34%|███▎      | 1202/3566 [48:33<1:38:36,  2.50s/it]
 34%|███▎      | 1203/3566 [48:35<1:38:35,  2.50s/it]
                                                     
{'loss': 1.5125, 'learning_rate': 0.00030810043421596625, 'epoch': 0.34}

 34%|███▎      | 1203/3566 [48:35<1:38:35,  2.50s/it]
 34%|███▍      | 1204/3566 [48:37<1:34:13,  2.39s/it]
                                                     
{'loss': 1.5175, 'learning_rate': 0.00030794787074319303, 'epoch': 0.34}

 34%|███▍      | 1204/3566 [48:37<1:34:13,  2.39s/it]
 34%|███▍      | 1205/3566 [48:40<1:33:29,  2.38s/it]
                                                     
{'loss': 1.549, 'learning_rate': 0.0003077952185840907, 'epoch': 0.34}

 34%|███▍      | 1205/3566 [48:40<1:33:29,  2.38s/it]
 34%|███▍      | 1206/3566 [48:42<1:36:36,  2.46s/it]
                                                     
{'loss': 1.5469, 'learning_rate': 0.0003076424778640731, 'epoch': 0.34}

 34%|███▍      | 1206/3566 [48:42<1:36:36,  2.46s/it]
 34%|███▍      | 1207/3566 [48:45<1:35:16,  2.42s/it]
                                                     
{'loss': 1.6703, 'learning_rate': 0.0003074896487086268, 'epoch': 0.34}

 34%|███▍      | 1207/3566 [48:45<1:35:16,  2.42s/it]
 34%|███▍      | 1208/3566 [48:47<1:36:14,  2.45s/it]
                                                     
{'loss': 1.5375, 'learning_rate': 0.0003073367312433111, 'epoch': 0.34}

 34%|███▍      | 1208/3566 [48:47<1:36:14,  2.45s/it]
 34%|███▍      | 1209/3566 [48:49<1:33:13,  2.37s/it]
                                                     
{'loss': 1.4652, 'learning_rate': 0.0003071837255937578, 'epoch': 0.34}

 34%|███▍      | 1209/3566 [48:49<1:33:13,  2.37s/it]
 34%|███▍      | 1210/3566 [48:52<1:33:17,  2.38s/it]
                                                     
{'loss': 1.5613, 'learning_rate': 0.00030703063188567125, 'epoch': 0.34}

 34%|███▍      | 1210/3566 [48:52<1:33:17,  2.38s/it]
 34%|███▍      | 1211/3566 [48:54<1:30:46,  2.31s/it]
                                                     
{'loss': 1.7065, 'learning_rate': 0.00030687745024482807, 'epoch': 0.34}

 34%|███▍      | 1211/3566 [48:54<1:30:46,  2.31s/it]
 34%|███▍      | 1212/3566 [48:56<1:29:31,  2.28s/it]
                                                     
{'loss': 1.4361, 'learning_rate': 0.0003067241807970771, 'epoch': 0.34}

 34%|███▍      | 1212/3566 [48:56<1:29:31,  2.28s/it]
 34%|███▍      | 1213/3566 [48:58<1:27:26,  2.23s/it]
                                                     
{'loss': 1.5132, 'learning_rate': 0.00030657082366833936, 'epoch': 0.34}

 34%|███▍      | 1213/3566 [48:58<1:27:26,  2.23s/it]
 34%|███▍      | 1214/3566 [49:01<1:30:10,  2.30s/it]
                                                     
{'loss': 1.5481, 'learning_rate': 0.0003064173789846079, 'epoch': 0.34}

 34%|███▍      | 1214/3566 [49:01<1:30:10,  2.30s/it]
 34%|███▍      | 1215/3566 [49:03<1:30:04,  2.30s/it]
                                                     
{'loss': 1.6849, 'learning_rate': 0.00030626384687194765, 'epoch': 0.34}

 34%|███▍      | 1215/3566 [49:03<1:30:04,  2.30s/it]
 34%|███▍      | 1216/3566 [49:05<1:29:03,  2.27s/it]
                                                     
{'loss': 1.3907, 'learning_rate': 0.0003061102274564954, 'epoch': 0.34}

 34%|███▍      | 1216/3566 [49:05<1:29:03,  2.27s/it]
 34%|███▍      | 1217/3566 [49:08<1:30:30,  2.31s/it]
                                                     
{'loss': 1.5077, 'learning_rate': 0.00030595652086445977, 'epoch': 0.34}

 34%|███▍      | 1217/3566 [49:08<1:30:30,  2.31s/it]
 34%|███▍      | 1218/3566 [49:10<1:31:59,  2.35s/it]
                                                     
{'loss': 1.4581, 'learning_rate': 0.00030580272722212094, 'epoch': 0.34}

 34%|███▍      | 1218/3566 [49:10<1:31:59,  2.35s/it]
 34%|███▍      | 1219/3566 [49:13<1:33:12,  2.38s/it]
                                                     
{'loss': 1.6817, 'learning_rate': 0.0003056488466558304, 'epoch': 0.34}

 34%|███▍      | 1219/3566 [49:13<1:33:12,  2.38s/it]
 34%|███▍      | 1220/3566 [49:15<1:29:28,  2.29s/it]
                                                     
{'loss': 1.5937, 'learning_rate': 0.0003054948792920114, 'epoch': 0.34}

 34%|███▍      | 1220/3566 [49:15<1:29:28,  2.29s/it]
 34%|███▍      | 1221/3566 [49:17<1:31:40,  2.35s/it]
                                                     
{'loss': 1.5329, 'learning_rate': 0.00030534082525715826, 'epoch': 0.34}

 34%|███▍      | 1221/3566 [49:17<1:31:40,  2.35s/it]
 34%|███▍      | 1222/3566 [49:19<1:30:29,  2.32s/it]
                                                     
{'loss': 1.6112, 'learning_rate': 0.0003051866846778366, 'epoch': 0.34}

 34%|███▍      | 1222/3566 [49:19<1:30:29,  2.32s/it]
 34%|███▍      | 1223/3566 [49:22<1:30:39,  2.32s/it]
                                                     
{'loss': 1.5885, 'learning_rate': 0.0003050324576806831, 'epoch': 0.34}

 34%|███▍      | 1223/3566 [49:22<1:30:39,  2.32s/it]
 34%|███▍      | 1224/3566 [49:24<1:36:05,  2.46s/it]
                                                     
{'loss': 1.5476, 'learning_rate': 0.0003048781443924054, 'epoch': 0.34}

 34%|███▍      | 1224/3566 [49:24<1:36:05,  2.46s/it]
 34%|███▍      | 1225/3566 [49:27<1:33:20,  2.39s/it]
                                                     
{'loss': 1.6249, 'learning_rate': 0.00030472374493978224, 'epoch': 0.34}

 34%|███▍      | 1225/3566 [49:27<1:33:20,  2.39s/it]
 34%|███▍      | 1226/3566 [49:29<1:32:12,  2.36s/it]
                                                     
{'loss': 1.6615, 'learning_rate': 0.00030456925944966296, 'epoch': 0.34}

 34%|███▍      | 1226/3566 [49:29<1:32:12,  2.36s/it]
 34%|███▍      | 1227/3566 [49:32<1:35:04,  2.44s/it]
                                                     
{'loss': 1.5339, 'learning_rate': 0.00030441468804896755, 'epoch': 0.34}

 34%|███▍      | 1227/3566 [49:32<1:35:04,  2.44s/it]
 34%|███▍      | 1228/3566 [49:34<1:37:17,  2.50s/it]
                                                     
{'loss': 1.5914, 'learning_rate': 0.00030426003086468667, 'epoch': 0.34}

 34%|███▍      | 1228/3566 [49:34<1:37:17,  2.50s/it]
 34%|███▍      | 1229/3566 [49:37<1:37:20,  2.50s/it]
                                                     
{'loss': 1.642, 'learning_rate': 0.0003041052880238815, 'epoch': 0.34}

 34%|███▍      | 1229/3566 [49:37<1:37:20,  2.50s/it]
 34%|███▍      | 1230/3566 [49:40<1:45:32,  2.71s/it]
                                                     
{'loss': 1.6709, 'learning_rate': 0.0003039504596536835, 'epoch': 0.34}

 34%|███▍      | 1230/3566 [49:40<1:45:32,  2.71s/it]
 35%|███▍      | 1231/3566 [49:42<1:40:20,  2.58s/it]
                                                     
{'loss': 1.5091, 'learning_rate': 0.0003037955458812944, 'epoch': 0.35}

 35%|███▍      | 1231/3566 [49:42<1:40:20,  2.58s/it]
 35%|███▍      | 1232/3566 [49:45<1:37:12,  2.50s/it]
                                                     
{'loss': 1.7787, 'learning_rate': 0.00030364054683398623, 'epoch': 0.35}

 35%|███▍      | 1232/3566 [49:45<1:37:12,  2.50s/it]
 35%|███▍      | 1233/3566 [49:47<1:36:11,  2.47s/it]
                                                     
{'loss': 1.5264, 'learning_rate': 0.0003034854626391009, 'epoch': 0.35}

 35%|███▍      | 1233/3566 [49:47<1:36:11,  2.47s/it]
 35%|███▍      | 1234/3566 [49:49<1:34:23,  2.43s/it]
                                                     
{'loss': 1.5762, 'learning_rate': 0.0003033302934240504, 'epoch': 0.35}

 35%|███▍      | 1234/3566 [49:49<1:34:23,  2.43s/it]
 35%|███▍      | 1235/3566 [49:51<1:32:07,  2.37s/it]
                                                     
{'loss': 1.6442, 'learning_rate': 0.00030317503931631657, 'epoch': 0.35}

 35%|███▍      | 1235/3566 [49:52<1:32:07,  2.37s/it]
 35%|███▍      | 1236/3566 [49:54<1:38:50,  2.55s/it]
                                                     
{'loss': 1.3079, 'learning_rate': 0.00030301970044345077, 'epoch': 0.35}

 35%|███▍      | 1236/3566 [49:54<1:38:50,  2.55s/it]
 35%|███▍      | 1237/3566 [49:57<1:36:12,  2.48s/it]
                                                     
{'loss': 1.6531, 'learning_rate': 0.0003028642769330743, 'epoch': 0.35}

 35%|███▍      | 1237/3566 [49:57<1:36:12,  2.48s/it]
 35%|███▍      | 1238/3566 [50:00<1:40:45,  2.60s/it]
                                                     
{'loss': 1.6456, 'learning_rate': 0.00030270876891287787, 'epoch': 0.35}

 35%|███▍      | 1238/3566 [50:00<1:40:45,  2.60s/it]
 35%|███▍      | 1239/3566 [50:02<1:37:38,  2.52s/it]
                                                     
{'loss': 1.7472, 'learning_rate': 0.00030255317651062166, 'epoch': 0.35}

 35%|███▍      | 1239/3566 [50:02<1:37:38,  2.52s/it]
 35%|███▍      | 1240/3566 [50:04<1:33:20,  2.41s/it]
                                                     
{'loss': 1.7043, 'learning_rate': 0.0003023974998541351, 'epoch': 0.35}

 35%|███▍      | 1240/3566 [50:04<1:33:20,  2.41s/it]
 35%|███▍      | 1241/3566 [50:06<1:32:23,  2.38s/it]
                                                     
{'loss': 1.5712, 'learning_rate': 0.0003022417390713168, 'epoch': 0.35}

 35%|███▍      | 1241/3566 [50:06<1:32:23,  2.38s/it]
 35%|███▍      | 1242/3566 [50:09<1:33:08,  2.40s/it]
                                                     
{'loss': 1.5013, 'learning_rate': 0.0003020858942901347, 'epoch': 0.35}

 35%|███▍      | 1242/3566 [50:09<1:33:08,  2.40s/it]
 35%|███▍      | 1243/3566 [50:11<1:31:50,  2.37s/it]
                                                     
{'loss': 1.6338, 'learning_rate': 0.00030192996563862553, 'epoch': 0.35}

 35%|███▍      | 1243/3566 [50:11<1:31:50,  2.37s/it]
 35%|███▍      | 1244/3566 [50:14<1:32:00,  2.38s/it]
                                                     
{'loss': 1.5967, 'learning_rate': 0.00030177395324489505, 'epoch': 0.35}

 35%|███▍      | 1244/3566 [50:14<1:32:00,  2.38s/it]
 35%|███▍      | 1245/3566 [50:16<1:30:57,  2.35s/it]
                                                     
{'loss': 1.464, 'learning_rate': 0.0003016178572371177, 'epoch': 0.35}

 35%|███▍      | 1245/3566 [50:16<1:30:57,  2.35s/it]
 35%|███▍      | 1246/3566 [50:18<1:32:07,  2.38s/it]
                                                     
{'loss': 1.6075, 'learning_rate': 0.0003014616777435368, 'epoch': 0.35}

 35%|███▍      | 1246/3566 [50:18<1:32:07,  2.38s/it]
 35%|███▍      | 1247/3566 [50:21<1:32:41,  2.40s/it]
                                                     
{'loss': 1.5623, 'learning_rate': 0.0003013054148924641, 'epoch': 0.35}

 35%|███▍      | 1247/3566 [50:21<1:32:41,  2.40s/it]
 35%|███▍      | 1248/3566 [50:23<1:32:14,  2.39s/it]
                                                     
{'loss': 1.5102, 'learning_rate': 0.0003011490688122799, 'epoch': 0.35}

 35%|███▍      | 1248/3566 [50:23<1:32:14,  2.39s/it]
 35%|███▌      | 1249/3566 [50:26<1:36:21,  2.50s/it]
                                                     
{'loss': 1.6834, 'learning_rate': 0.0003009926396314329, 'epoch': 0.35}

 35%|███▌      | 1249/3566 [50:26<1:36:21,  2.50s/it]
 35%|███▌      | 1250/3566 [50:28<1:33:34,  2.42s/it]
                                                     
{'loss': 1.553, 'learning_rate': 0.00030083612747844, 'epoch': 0.35}

 35%|███▌      | 1250/3566 [50:28<1:33:34,  2.42s/it]
 35%|███▌      | 1251/3566 [50:31<1:33:19,  2.42s/it]
                                                     
{'loss': 1.4659, 'learning_rate': 0.00030067953248188626, 'epoch': 0.35}

 35%|███▌      | 1251/3566 [50:31<1:33:19,  2.42s/it]
 35%|███▌      | 1252/3566 [50:33<1:29:49,  2.33s/it]
                                                     
{'loss': 1.4358, 'learning_rate': 0.0003005228547704249, 'epoch': 0.35}

 35%|███▌      | 1252/3566 [50:33<1:29:49,  2.33s/it]
 35%|███▌      | 1253/3566 [50:35<1:26:14,  2.24s/it]
                                                     
{'loss': 1.5063, 'learning_rate': 0.00030036609447277703, 'epoch': 0.35}

 35%|███▌      | 1253/3566 [50:35<1:26:14,  2.24s/it]
 35%|███▌      | 1254/3566 [50:37<1:26:39,  2.25s/it]
                                                     
{'loss': 1.496, 'learning_rate': 0.00030020925171773163, 'epoch': 0.35}

 35%|███▌      | 1254/3566 [50:37<1:26:39,  2.25s/it]
 35%|███▌      | 1255/3566 [50:39<1:28:49,  2.31s/it]
                                                     
{'loss': 1.3668, 'learning_rate': 0.00030005232663414544, 'epoch': 0.35}

 35%|███▌      | 1255/3566 [50:39<1:28:49,  2.31s/it]
 35%|███▌      | 1256/3566 [50:42<1:29:45,  2.33s/it]
                                                     
{'loss': 1.5428, 'learning_rate': 0.00029989531935094277, 'epoch': 0.35}

 35%|███▌      | 1256/3566 [50:42<1:29:45,  2.33s/it]
 35%|███▌      | 1257/3566 [50:44<1:31:27,  2.38s/it]
                                                     
{'loss': 1.5547, 'learning_rate': 0.00029973822999711556, 'epoch': 0.35}

 35%|███▌      | 1257/3566 [50:44<1:31:27,  2.38s/it]
 35%|███▌      | 1258/3566 [50:47<1:31:30,  2.38s/it]
                                                     
{'loss': 1.5979, 'learning_rate': 0.00029958105870172305, 'epoch': 0.35}

 35%|███▌      | 1258/3566 [50:47<1:31:30,  2.38s/it]
 35%|███▌      | 1259/3566 [50:50<1:39:18,  2.58s/it]
                                                     
{'loss': 1.6185, 'learning_rate': 0.0002994238055938919, 'epoch': 0.35}

 35%|███▌      | 1259/3566 [50:50<1:39:18,  2.58s/it]
 35%|███▌      | 1260/3566 [50:52<1:38:21,  2.56s/it]
                                                     
{'loss': 1.6565, 'learning_rate': 0.00029926647080281597, 'epoch': 0.35}

 35%|███▌      | 1260/3566 [50:52<1:38:21,  2.56s/it]
 35%|███▌      | 1261/3566 [50:55<1:44:35,  2.72s/it]
                                                     
{'loss': 1.6531, 'learning_rate': 0.0002991090544577563, 'epoch': 0.35}

 35%|███▌      | 1261/3566 [50:55<1:44:35,  2.72s/it]
 35%|███▌      | 1262/3566 [50:58<1:42:42,  2.67s/it]
                                                     
{'loss': 1.6557, 'learning_rate': 0.0002989515566880407, 'epoch': 0.35}

 35%|███▌      | 1262/3566 [50:58<1:42:42,  2.67s/it]
 35%|███▌      | 1263/3566 [51:00<1:39:09,  2.58s/it]
                                                     
{'loss': 1.5383, 'learning_rate': 0.00029879397762306415, 'epoch': 0.35}

 35%|███▌      | 1263/3566 [51:00<1:39:09,  2.58s/it]
 35%|███▌      | 1264/3566 [51:03<1:36:10,  2.51s/it]
                                                     
{'loss': 1.7664, 'learning_rate': 0.0002986363173922882, 'epoch': 0.35}

 35%|███▌      | 1264/3566 [51:03<1:36:10,  2.51s/it]
 35%|███▌      | 1265/3566 [51:05<1:32:10,  2.40s/it]
                                                     
{'loss': 1.5882, 'learning_rate': 0.00029847857612524123, 'epoch': 0.35}

 35%|███▌      | 1265/3566 [51:05<1:32:10,  2.40s/it]
 36%|███▌      | 1266/3566 [51:07<1:29:55,  2.35s/it]
                                                     
{'loss': 1.6038, 'learning_rate': 0.0002983207539515181, 'epoch': 0.36}

 36%|███▌      | 1266/3566 [51:07<1:29:55,  2.35s/it]
 36%|███▌      | 1267/3566 [51:09<1:30:01,  2.35s/it]
                                                     
{'loss': 1.6021, 'learning_rate': 0.0002981628510007802, 'epoch': 0.36}

 36%|███▌      | 1267/3566 [51:09<1:30:01,  2.35s/it]
 36%|███▌      | 1268/3566 [51:12<1:31:59,  2.40s/it]
                                                     
{'loss': 1.6582, 'learning_rate': 0.00029800486740275535, 'epoch': 0.36}

 36%|███▌      | 1268/3566 [51:12<1:31:59,  2.40s/it]
 36%|███▌      | 1269/3566 [51:14<1:31:40,  2.39s/it]
                                                     
{'loss': 1.5992, 'learning_rate': 0.00029784680328723745, 'epoch': 0.36}

 36%|███▌      | 1269/3566 [51:14<1:31:40,  2.39s/it]
 36%|███▌      | 1270/3566 [51:17<1:34:41,  2.47s/it]
                                                     
{'loss': 1.506, 'learning_rate': 0.0002976886587840867, 'epoch': 0.36}

 36%|███▌      | 1270/3566 [51:17<1:34:41,  2.47s/it]
 36%|███▌      | 1271/3566 [51:19<1:34:02,  2.46s/it]
                                                     
{'loss': 1.4982, 'learning_rate': 0.0002975304340232292, 'epoch': 0.36}

 36%|███▌      | 1271/3566 [51:19<1:34:02,  2.46s/it]
 36%|███▌      | 1272/3566 [51:22<1:37:12,  2.54s/it]
                                                     
{'loss': 1.5145, 'learning_rate': 0.00029737212913465714, 'epoch': 0.36}

 36%|███▌      | 1272/3566 [51:22<1:37:12,  2.54s/it]
 36%|███▌      | 1273/3566 [51:25<1:38:07,  2.57s/it]
                                                     
{'loss': 1.526, 'learning_rate': 0.0002972137442484285, 'epoch': 0.36}

 36%|███▌      | 1273/3566 [51:25<1:38:07,  2.57s/it]
 36%|███▌      | 1274/3566 [51:27<1:38:46,  2.59s/it]
                                                     
{'loss': 1.5751, 'learning_rate': 0.0002970552794946669, 'epoch': 0.36}

 36%|███▌      | 1274/3566 [51:27<1:38:46,  2.59s/it]
 36%|███▌      | 1275/3566 [51:30<1:35:37,  2.50s/it]
                                                     
{'loss': 1.7251, 'learning_rate': 0.0002968967350035617, 'epoch': 0.36}

 36%|███▌      | 1275/3566 [51:30<1:35:37,  2.50s/it]
 36%|███▌      | 1276/3566 [51:32<1:32:09,  2.41s/it]
                                                     
{'loss': 1.6145, 'learning_rate': 0.0002967381109053677, 'epoch': 0.36}

 36%|███▌      | 1276/3566 [51:32<1:32:09,  2.41s/it]
 36%|███▌      | 1277/3566 [51:34<1:29:37,  2.35s/it]
                                                     
{'loss': 1.654, 'learning_rate': 0.000296579407330405, 'epoch': 0.36}

 36%|███▌      | 1277/3566 [51:34<1:29:37,  2.35s/it]
 36%|███▌      | 1278/3566 [51:36<1:27:25,  2.29s/it]
                                                     
{'loss': 1.5621, 'learning_rate': 0.0002964206244090593, 'epoch': 0.36}

 36%|███▌      | 1278/3566 [51:36<1:27:25,  2.29s/it]
 36%|███▌      | 1279/3566 [51:39<1:28:47,  2.33s/it]
                                                     
{'loss': 1.6457, 'learning_rate': 0.0002962617622717811, 'epoch': 0.36}

 36%|███▌      | 1279/3566 [51:39<1:28:47,  2.33s/it]
 36%|███▌      | 1280/3566 [51:41<1:28:03,  2.31s/it]
                                                     
{'loss': 1.5072, 'learning_rate': 0.00029610282104908627, 'epoch': 0.36}

 36%|███▌      | 1280/3566 [51:41<1:28:03,  2.31s/it]
 36%|███▌      | 1281/3566 [51:43<1:29:43,  2.36s/it]
                                                     
{'loss': 1.4819, 'learning_rate': 0.0002959438008715555, 'epoch': 0.36}

 36%|███▌      | 1281/3566 [51:43<1:29:43,  2.36s/it]
 36%|███▌      | 1282/3566 [51:46<1:29:45,  2.36s/it]
                                                     
{'loss': 1.5347, 'learning_rate': 0.00029578470186983455, 'epoch': 0.36}

 36%|███▌      | 1282/3566 [51:46<1:29:45,  2.36s/it]
 36%|███▌      | 1283/3566 [51:48<1:28:21,  2.32s/it]
                                                     
{'loss': 1.586, 'learning_rate': 0.00029562552417463354, 'epoch': 0.36}

 36%|███▌      | 1283/3566 [51:48<1:28:21,  2.32s/it]
 36%|███▌      | 1284/3566 [51:50<1:31:10,  2.40s/it]
                                                     
{'loss': 1.4968, 'learning_rate': 0.00029546626791672774, 'epoch': 0.36}

 36%|███▌      | 1284/3566 [51:50<1:31:10,  2.40s/it]
 36%|███▌      | 1285/3566 [51:53<1:29:08,  2.34s/it]
                                                     
{'loss': 1.6464, 'learning_rate': 0.0002953069332269566, 'epoch': 0.36}

 36%|███▌      | 1285/3566 [51:53<1:29:08,  2.34s/it]
 36%|███▌      | 1286/3566 [51:55<1:31:21,  2.40s/it]
                                                     
{'loss': 1.5809, 'learning_rate': 0.0002951475202362241, 'epoch': 0.36}

 36%|███▌      | 1286/3566 [51:55<1:31:21,  2.40s/it]
 36%|███▌      | 1287/3566 [51:58<1:31:39,  2.41s/it]
                                                     
{'loss': 1.582, 'learning_rate': 0.0002949880290754987, 'epoch': 0.36}

 36%|███▌      | 1287/3566 [51:58<1:31:39,  2.41s/it]
 36%|███▌      | 1288/3566 [52:01<1:38:54,  2.60s/it]
                                                     
{'loss': 1.8617, 'learning_rate': 0.0002948284598758128, 'epoch': 0.36}

 36%|███▌      | 1288/3566 [52:01<1:38:54,  2.60s/it]
 36%|███▌      | 1289/3566 [52:04<1:41:11,  2.67s/it]
                                                     
{'loss': 1.553, 'learning_rate': 0.00029466881276826317, 'epoch': 0.36}

 36%|███▌      | 1289/3566 [52:04<1:41:11,  2.67s/it]
 36%|███▌      | 1290/3566 [52:06<1:39:11,  2.61s/it]
                                                     
{'loss': 1.6381, 'learning_rate': 0.0002945090878840105, 'epoch': 0.36}

 36%|███▌      | 1290/3566 [52:06<1:39:11,  2.61s/it]
 36%|███▌      | 1291/3566 [52:08<1:32:43,  2.45s/it]
                                                     
{'loss': 1.6688, 'learning_rate': 0.0002943492853542793, 'epoch': 0.36}

 36%|███▌      | 1291/3566 [52:08<1:32:43,  2.45s/it]
 36%|███▌      | 1292/3566 [52:11<1:32:41,  2.45s/it]
                                                     
{'loss': 1.661, 'learning_rate': 0.000294189405310358, 'epoch': 0.36}

 36%|███▌      | 1292/3566 [52:11<1:32:41,  2.45s/it]
 36%|███▋      | 1293/3566 [52:13<1:31:43,  2.42s/it]
                                                     
{'loss': 1.4943, 'learning_rate': 0.0002940294478835986, 'epoch': 0.36}

 36%|███▋      | 1293/3566 [52:13<1:31:43,  2.42s/it]
 36%|███▋      | 1294/3566 [52:15<1:32:03,  2.43s/it]
                                                     
{'loss': 1.6113, 'learning_rate': 0.00029386941320541676, 'epoch': 0.36}

 36%|███▋      | 1294/3566 [52:15<1:32:03,  2.43s/it]
 36%|███▋      | 1295/3566 [52:18<1:29:09,  2.36s/it]
                                                     
{'loss': 1.5637, 'learning_rate': 0.00029370930140729156, 'epoch': 0.36}

 36%|███▋      | 1295/3566 [52:18<1:29:09,  2.36s/it]
 36%|███▋      | 1296/3566 [52:20<1:28:17,  2.33s/it]
                                                     
{'loss': 1.6185, 'learning_rate': 0.00029354911262076546, 'epoch': 0.36}

 36%|███▋      | 1296/3566 [52:20<1:28:17,  2.33s/it]
 36%|███▋      | 1297/3566 [52:22<1:27:56,  2.33s/it]
                                                     
{'loss': 1.6038, 'learning_rate': 0.00029338884697744413, 'epoch': 0.36}

 36%|███▋      | 1297/3566 [52:22<1:27:56,  2.33s/it]
 36%|███▋      | 1298/3566 [52:24<1:28:07,  2.33s/it]
                                                     
{'loss': 1.5863, 'learning_rate': 0.0002932285046089965, 'epoch': 0.36}

 36%|███▋      | 1298/3566 [52:24<1:28:07,  2.33s/it]
 36%|███▋      | 1299/3566 [52:27<1:33:25,  2.47s/it]
                                                     
{'loss': 1.4783, 'learning_rate': 0.00029306808564715436, 'epoch': 0.36}

 36%|███▋      | 1299/3566 [52:27<1:33:25,  2.47s/it]
 36%|███▋      | 1300/3566 [52:30<1:32:28,  2.45s/it]
                                                     
{'loss': 1.8249, 'learning_rate': 0.00029290759022371253, 'epoch': 0.36}

 36%|███▋      | 1300/3566 [52:30<1:32:28,  2.45s/it]
 36%|███▋      | 1301/3566 [52:32<1:30:19,  2.39s/it]
                                                     
{'loss': 1.5068, 'learning_rate': 0.0002927470184705287, 'epoch': 0.36}

 36%|███▋      | 1301/3566 [52:32<1:30:19,  2.39s/it]
 37%|███▋      | 1302/3566 [52:35<1:32:50,  2.46s/it]
                                                     
{'loss': 1.4926, 'learning_rate': 0.0002925863705195231, 'epoch': 0.37}

 37%|███▋      | 1302/3566 [52:35<1:32:50,  2.46s/it]
 37%|███▋      | 1303/3566 [52:37<1:31:30,  2.43s/it]
                                                     
{'loss': 1.8286, 'learning_rate': 0.0002924256465026788, 'epoch': 0.37}

 37%|███▋      | 1303/3566 [52:37<1:31:30,  2.43s/it]
 37%|███▋      | 1304/3566 [52:39<1:30:19,  2.40s/it]
                                                     
{'loss': 1.585, 'learning_rate': 0.0002922648465520411, 'epoch': 0.37}

 37%|███▋      | 1304/3566 [52:39<1:30:19,  2.40s/it]
 37%|███▋      | 1305/3566 [52:42<1:29:06,  2.36s/it]
                                                     
{'loss': 1.4951, 'learning_rate': 0.00029210397079971795, 'epoch': 0.37}

 37%|███▋      | 1305/3566 [52:42<1:29:06,  2.36s/it]
 37%|███▋      | 1306/3566 [52:44<1:28:19,  2.35s/it]
                                                     
{'loss': 1.6094, 'learning_rate': 0.0002919430193778793, 'epoch': 0.37}

 37%|███▋      | 1306/3566 [52:44<1:28:19,  2.35s/it]
 37%|███▋      | 1307/3566 [52:46<1:29:52,  2.39s/it]
                                                     
{'loss': 1.6628, 'learning_rate': 0.00029178199241875754, 'epoch': 0.37}

 37%|███▋      | 1307/3566 [52:46<1:29:52,  2.39s/it]
 37%|███▋      | 1308/3566 [52:49<1:29:51,  2.39s/it]
                                                     
{'loss': 1.6924, 'learning_rate': 0.00029162089005464693, 'epoch': 0.37}

 37%|███▋      | 1308/3566 [52:49<1:29:51,  2.39s/it]
 37%|███▋      | 1309/3566 [52:51<1:31:03,  2.42s/it]
                                                     
{'loss': 1.4482, 'learning_rate': 0.0002914597124179037, 'epoch': 0.37}

 37%|███▋      | 1309/3566 [52:51<1:31:03,  2.42s/it]
 37%|███▋      | 1310/3566 [52:54<1:38:13,  2.61s/it]
                                                     
{'loss': 1.5083, 'learning_rate': 0.00029129845964094597, 'epoch': 0.37}

 37%|███▋      | 1310/3566 [52:54<1:38:13,  2.61s/it]
 37%|███▋      | 1311/3566 [52:57<1:37:49,  2.60s/it]
                                                     
{'loss': 1.6582, 'learning_rate': 0.0002911371318562536, 'epoch': 0.37}

 37%|███▋      | 1311/3566 [52:57<1:37:49,  2.60s/it]
 37%|███▋      | 1312/3566 [52:59<1:36:49,  2.58s/it]
                                                     
{'loss': 1.5422, 'learning_rate': 0.00029097572919636807, 'epoch': 0.37}

 37%|███▋      | 1312/3566 [52:59<1:36:49,  2.58s/it]
 37%|███▋      | 1313/3566 [53:02<1:33:21,  2.49s/it]
                                                     
{'loss': 1.5767, 'learning_rate': 0.00029081425179389235, 'epoch': 0.37}

 37%|███▋      | 1313/3566 [53:02<1:33:21,  2.49s/it]
 37%|███▋      | 1314/3566 [53:04<1:32:06,  2.45s/it]
                                                     
{'loss': 1.6507, 'learning_rate': 0.00029065269978149086, 'epoch': 0.37}

 37%|███▋      | 1314/3566 [53:04<1:32:06,  2.45s/it]
 37%|███▋      | 1315/3566 [53:07<1:33:04,  2.48s/it]
                                                     
{'loss': 1.5284, 'learning_rate': 0.0002904910732918892, 'epoch': 0.37}

 37%|███▋      | 1315/3566 [53:07<1:33:04,  2.48s/it]
 37%|███▋      | 1316/3566 [53:09<1:30:40,  2.42s/it]
                                                     
{'loss': 1.6317, 'learning_rate': 0.00029032937245787436, 'epoch': 0.37}

 37%|███▋      | 1316/3566 [53:09<1:30:40,  2.42s/it]
 37%|███▋      | 1317/3566 [53:11<1:28:18,  2.36s/it]
                                                     
{'loss': 1.5418, 'learning_rate': 0.00029016759741229414, 'epoch': 0.37}

 37%|███▋      | 1317/3566 [53:11<1:28:18,  2.36s/it]
 37%|███▋      | 1318/3566 [53:14<1:32:10,  2.46s/it]
                                                     
{'loss': 1.6465, 'learning_rate': 0.0002900057482880576, 'epoch': 0.37}

 37%|███▋      | 1318/3566 [53:14<1:32:10,  2.46s/it]
 37%|███▋      | 1319/3566 [53:16<1:29:22,  2.39s/it]
                                                     
{'loss': 1.4781, 'learning_rate': 0.00028984382521813446, 'epoch': 0.37}

 37%|███▋      | 1319/3566 [53:16<1:29:22,  2.39s/it]
 37%|███▋      | 1320/3566 [53:19<1:31:39,  2.45s/it]
                                                     
{'loss': 1.6437, 'learning_rate': 0.0002896818283355552, 'epoch': 0.37}

 37%|███▋      | 1320/3566 [53:19<1:31:39,  2.45s/it]
 37%|███▋      | 1321/3566 [53:21<1:27:27,  2.34s/it]
                                                     
{'loss': 1.4823, 'learning_rate': 0.0002895197577734112, 'epoch': 0.37}

 37%|███▋      | 1321/3566 [53:21<1:27:27,  2.34s/it]
 37%|███▋      | 1322/3566 [53:23<1:25:44,  2.29s/it]
                                                     
{'loss': 1.5966, 'learning_rate': 0.00028935761366485386, 'epoch': 0.37}

 37%|███▋      | 1322/3566 [53:23<1:25:44,  2.29s/it]
 37%|███▋      | 1323/3566 [53:25<1:27:58,  2.35s/it]
                                                     
{'loss': 1.6798, 'learning_rate': 0.0002891953961430955, 'epoch': 0.37}

 37%|███▋      | 1323/3566 [53:25<1:27:58,  2.35s/it]
 37%|███▋      | 1324/3566 [53:28<1:28:57,  2.38s/it]
                                                     
{'loss': 1.6863, 'learning_rate': 0.00028903310534140857, 'epoch': 0.37}

 37%|███▋      | 1324/3566 [53:28<1:28:57,  2.38s/it]
 37%|███▋      | 1325/3566 [53:30<1:28:23,  2.37s/it]
                                                     
{'loss': 1.6297, 'learning_rate': 0.00028887074139312565, 'epoch': 0.37}

 37%|███▋      | 1325/3566 [53:30<1:28:23,  2.37s/it]
 37%|███▋      | 1326/3566 [53:32<1:27:51,  2.35s/it]
                                                     
{'loss': 1.5969, 'learning_rate': 0.0002887083044316395, 'epoch': 0.37}

 37%|███▋      | 1326/3566 [53:32<1:27:51,  2.35s/it]
 37%|███▋      | 1327/3566 [53:35<1:27:03,  2.33s/it]
                                                     
{'loss': 1.7106, 'learning_rate': 0.0002885457945904029, 'epoch': 0.37}

 37%|███▋      | 1327/3566 [53:35<1:27:03,  2.33s/it]
 37%|███▋      | 1328/3566 [53:37<1:32:02,  2.47s/it]
                                                     
{'loss': 1.4536, 'learning_rate': 0.00028838321200292836, 'epoch': 0.37}

 37%|███▋      | 1328/3566 [53:37<1:32:02,  2.47s/it]
 37%|███▋      | 1329/3566 [53:40<1:28:20,  2.37s/it]
                                                     
{'loss': 1.5529, 'learning_rate': 0.00028822055680278834, 'epoch': 0.37}

 37%|███▋      | 1329/3566 [53:40<1:28:20,  2.37s/it]
 37%|███▋      | 1330/3566 [53:42<1:28:11,  2.37s/it]
                                                     
{'loss': 1.6485, 'learning_rate': 0.0002880578291236148, 'epoch': 0.37}

 37%|███▋      | 1330/3566 [53:42<1:28:11,  2.37s/it]
 37%|███▋      | 1331/3566 [53:44<1:28:36,  2.38s/it]
                                                     
{'loss': 1.562, 'learning_rate': 0.00028789502909909936, 'epoch': 0.37}

 37%|███▋      | 1331/3566 [53:44<1:28:36,  2.38s/it]
 37%|███▋      | 1332/3566 [53:47<1:29:43,  2.41s/it]
                                                     
{'loss': 1.7625, 'learning_rate': 0.00028773215686299304, 'epoch': 0.37}

 37%|███▋      | 1332/3566 [53:47<1:29:43,  2.41s/it]
 37%|███▋      | 1333/3566 [53:49<1:29:57,  2.42s/it]
                                                     
{'loss': 1.5392, 'learning_rate': 0.0002875692125491061, 'epoch': 0.37}

 37%|███▋      | 1333/3566 [53:49<1:29:57,  2.42s/it]
 37%|███▋      | 1334/3566 [53:51<1:27:27,  2.35s/it]
                                                     
{'loss': 1.4792, 'learning_rate': 0.0002874061962913081, 'epoch': 0.37}

 37%|███▋      | 1334/3566 [53:51<1:27:27,  2.35s/it]
 37%|███▋      | 1335/3566 [53:54<1:27:04,  2.34s/it]
                                                     
{'loss': 1.6575, 'learning_rate': 0.0002872431082235278, 'epoch': 0.37}

 37%|███▋      | 1335/3566 [53:54<1:27:04,  2.34s/it]
 37%|███▋      | 1336/3566 [53:56<1:29:05,  2.40s/it]
                                                     
{'loss': 1.661, 'learning_rate': 0.0002870799484797527, 'epoch': 0.37}

 37%|███▋      | 1336/3566 [53:56<1:29:05,  2.40s/it]
 37%|███▋      | 1337/3566 [53:59<1:29:16,  2.40s/it]
                                                     
{'loss': 1.5613, 'learning_rate': 0.0002869167171940295, 'epoch': 0.37}

 37%|███▋      | 1337/3566 [53:59<1:29:16,  2.40s/it]
 38%|███▊      | 1338/3566 [54:02<1:37:44,  2.63s/it]
                                                     
{'loss': 1.5619, 'learning_rate': 0.00028675341450046346, 'epoch': 0.38}

 38%|███▊      | 1338/3566 [54:02<1:37:44,  2.63s/it]
 38%|███▊      | 1339/3566 [54:04<1:33:35,  2.52s/it]
                                                     
{'loss': 1.6638, 'learning_rate': 0.0002865900405332186, 'epoch': 0.38}

 38%|███▊      | 1339/3566 [54:04<1:33:35,  2.52s/it]
 38%|███▊      | 1340/3566 [54:07<1:31:35,  2.47s/it]
                                                     
{'loss': 1.6187, 'learning_rate': 0.0002864265954265173, 'epoch': 0.38}

 38%|███▊      | 1340/3566 [54:07<1:31:35,  2.47s/it]
 38%|███▊      | 1341/3566 [54:09<1:30:03,  2.43s/it]
                                                     
{'loss': 1.4234, 'learning_rate': 0.00028626307931464066, 'epoch': 0.38}

 38%|███▊      | 1341/3566 [54:09<1:30:03,  2.43s/it]
 38%|███▊      | 1342/3566 [54:11<1:28:04,  2.38s/it]
                                                     
{'loss': 1.5031, 'learning_rate': 0.00028609949233192805, 'epoch': 0.38}

 38%|███▊      | 1342/3566 [54:11<1:28:04,  2.38s/it]
 38%|███▊      | 1343/3566 [54:14<1:28:50,  2.40s/it]
                                                     
{'loss': 1.3451, 'learning_rate': 0.000285935834612777, 'epoch': 0.38}

 38%|███▊      | 1343/3566 [54:14<1:28:50,  2.40s/it]
 38%|███▊      | 1344/3566 [54:16<1:29:39,  2.42s/it]
                                                     
{'loss': 1.401, 'learning_rate': 0.000285772106291643, 'epoch': 0.38}

 38%|███▊      | 1344/3566 [54:16<1:29:39,  2.42s/it]
 38%|███▊      | 1345/3566 [54:18<1:28:22,  2.39s/it]
                                                     
{'loss': 1.5241, 'learning_rate': 0.00028560830750304, 'epoch': 0.38}

 38%|███▊      | 1345/3566 [54:18<1:28:22,  2.39s/it]
 38%|███▊      | 1346/3566 [54:21<1:32:11,  2.49s/it]
                                                     
{'loss': 1.6803, 'learning_rate': 0.00028544443838153933, 'epoch': 0.38}

 38%|███▊      | 1346/3566 [54:21<1:32:11,  2.49s/it]
 38%|███▊      | 1347/3566 [54:23<1:28:35,  2.40s/it]
                                                     
{'loss': 1.5534, 'learning_rate': 0.0002852804990617705, 'epoch': 0.38}

 38%|███▊      | 1347/3566 [54:23<1:28:35,  2.40s/it]
 38%|███▊      | 1348/3566 [54:26<1:28:40,  2.40s/it]
                                                     
{'loss': 1.6425, 'learning_rate': 0.00028511648967842034, 'epoch': 0.38}

 38%|███▊      | 1348/3566 [54:26<1:28:40,  2.40s/it]
 38%|███▊      | 1349/3566 [54:28<1:26:24,  2.34s/it]
                                                     
{'loss': 1.5895, 'learning_rate': 0.00028495241036623355, 'epoch': 0.38}

 38%|███▊      | 1349/3566 [54:28<1:26:24,  2.34s/it]
 38%|███▊      | 1350/3566 [54:30<1:27:47,  2.38s/it]
                                                     
{'loss': 1.607, 'learning_rate': 0.00028478826126001217, 'epoch': 0.38}

 38%|███▊      | 1350/3566 [54:30<1:27:47,  2.38s/it]
 38%|███▊      | 1351/3566 [54:33<1:27:53,  2.38s/it]
                                                     
{'loss': 1.5567, 'learning_rate': 0.0002846240424946155, 'epoch': 0.38}

 38%|███▊      | 1351/3566 [54:33<1:27:53,  2.38s/it]
 38%|███▊      | 1352/3566 [54:35<1:29:33,  2.43s/it]
                                                     
{'loss': 1.6499, 'learning_rate': 0.0002844597542049602, 'epoch': 0.38}

 38%|███▊      | 1352/3566 [54:35<1:29:33,  2.43s/it]
 38%|███▊      | 1353/3566 [54:38<1:29:59,  2.44s/it]
                                                     
{'loss': 1.4521, 'learning_rate': 0.0002842953965260199, 'epoch': 0.38}

 38%|███▊      | 1353/3566 [54:38<1:29:59,  2.44s/it]
 38%|███▊      | 1354/3566 [54:40<1:30:36,  2.46s/it]
                                                     
{'loss': 1.6268, 'learning_rate': 0.0002841309695928254, 'epoch': 0.38}

 38%|███▊      | 1354/3566 [54:40<1:30:36,  2.46s/it]
 38%|███▊      | 1355/3566 [54:42<1:27:39,  2.38s/it]
                                                     
{'loss': 1.4933, 'learning_rate': 0.0002839664735404644, 'epoch': 0.38}

 38%|███▊      | 1355/3566 [54:42<1:27:39,  2.38s/it]
 38%|███▊      | 1356/3566 [54:45<1:28:14,  2.40s/it]
                                                     
{'loss': 1.6719, 'learning_rate': 0.00028380190850408113, 'epoch': 0.38}

 38%|███▊      | 1356/3566 [54:45<1:28:14,  2.40s/it]
 38%|███▊      | 1357/3566 [54:48<1:39:14,  2.70s/it]
                                                     
{'loss': 1.2667, 'learning_rate': 0.0002836372746188768, 'epoch': 0.38}

 38%|███▊      | 1357/3566 [54:48<1:39:14,  2.70s/it]
 38%|███▊      | 1358/3566 [54:51<1:37:40,  2.65s/it]
                                                     
{'loss': 1.5909, 'learning_rate': 0.0002834725720201089, 'epoch': 0.38}

 38%|███▊      | 1358/3566 [54:51<1:37:40,  2.65s/it]
 38%|███▊      | 1359/3566 [54:53<1:33:54,  2.55s/it]
                                                     
{'loss': 1.7232, 'learning_rate': 0.0002833078008430917, 'epoch': 0.38}

 38%|███▊      | 1359/3566 [54:53<1:33:54,  2.55s/it]
 38%|███▊      | 1360/3566 [54:56<1:32:08,  2.51s/it]
                                                     
{'loss': 1.546, 'learning_rate': 0.0002831429612231956, 'epoch': 0.38}

 38%|███▊      | 1360/3566 [54:56<1:32:08,  2.51s/it]
 38%|███▊      | 1361/3566 [54:58<1:29:36,  2.44s/it]
                                                     
{'loss': 1.5954, 'learning_rate': 0.00028297805329584725, 'epoch': 0.38}

 38%|███▊      | 1361/3566 [54:58<1:29:36,  2.44s/it]
 38%|███▊      | 1362/3566 [55:00<1:28:06,  2.40s/it]
                                                     
{'loss': 1.5687, 'learning_rate': 0.0002828130771965294, 'epoch': 0.38}

 38%|███▊      | 1362/3566 [55:00<1:28:06,  2.40s/it]
 38%|███▊      | 1363/3566 [55:03<1:29:05,  2.43s/it]
                                                     
{'loss': 1.5193, 'learning_rate': 0.00028264803306078093, 'epoch': 0.38}

 38%|███▊      | 1363/3566 [55:03<1:29:05,  2.43s/it]
 38%|███▊      | 1364/3566 [55:05<1:31:57,  2.51s/it]
                                                     
{'loss': 1.6457, 'learning_rate': 0.00028248292102419655, 'epoch': 0.38}

 38%|███▊      | 1364/3566 [55:05<1:31:57,  2.51s/it]
 38%|███▊      | 1365/3566 [55:08<1:33:21,  2.55s/it]
                                                     
{'loss': 1.699, 'learning_rate': 0.00028231774122242656, 'epoch': 0.38}

 38%|███▊      | 1365/3566 [55:08<1:33:21,  2.55s/it]
 38%|███▊      | 1366/3566 [55:10<1:33:16,  2.54s/it]
                                                     
{'loss': 1.5789, 'learning_rate': 0.0002821524937911773, 'epoch': 0.38}

 38%|███▊      | 1366/3566 [55:10<1:33:16,  2.54s/it]
 38%|███▊      | 1367/3566 [55:13<1:28:41,  2.42s/it]
                                                     
{'loss': 1.7219, 'learning_rate': 0.0002819871788662104, 'epoch': 0.38}

 38%|███▊      | 1367/3566 [55:13<1:28:41,  2.42s/it]
 38%|███▊      | 1368/3566 [55:15<1:30:16,  2.46s/it]
                                                     
{'loss': 1.538, 'learning_rate': 0.0002818217965833431, 'epoch': 0.38}

 38%|███▊      | 1368/3566 [55:15<1:30:16,  2.46s/it]
 38%|███▊      | 1369/3566 [55:18<1:29:23,  2.44s/it]
                                                     
{'loss': 1.5908, 'learning_rate': 0.0002816563470784478, 'epoch': 0.38}

 38%|███▊      | 1369/3566 [55:18<1:29:23,  2.44s/it]
 38%|███▊      | 1370/3566 [55:20<1:28:59,  2.43s/it]
                                                     
{'loss': 1.5928, 'learning_rate': 0.0002814908304874523, 'epoch': 0.38}

 38%|███▊      | 1370/3566 [55:20<1:28:59,  2.43s/it]
 38%|███▊      | 1371/3566 [55:23<1:34:01,  2.57s/it]
                                                     
{'loss': 1.5533, 'learning_rate': 0.00028132524694633943, 'epoch': 0.38}

 38%|███▊      | 1371/3566 [55:23<1:34:01,  2.57s/it]
 38%|███▊      | 1372/3566 [55:25<1:33:29,  2.56s/it]
                                                     
{'loss': 1.4639, 'learning_rate': 0.00028115959659114704, 'epoch': 0.38}

 38%|███▊      | 1372/3566 [55:25<1:33:29,  2.56s/it]
 39%|███▊      | 1373/3566 [55:28<1:35:42,  2.62s/it]
                                                     
{'loss': 1.5845, 'learning_rate': 0.0002809938795579679, 'epoch': 0.39}

 39%|███▊      | 1373/3566 [55:28<1:35:42,  2.62s/it]
 39%|███▊      | 1374/3566 [55:30<1:31:39,  2.51s/it]
                                                     
{'loss': 1.6648, 'learning_rate': 0.00028082809598294946, 'epoch': 0.39}

 39%|███▊      | 1374/3566 [55:30<1:31:39,  2.51s/it]
 39%|███▊      | 1375/3566 [55:33<1:30:12,  2.47s/it]
                                                     
{'loss': 1.6132, 'learning_rate': 0.000280662246002294, 'epoch': 0.39}

 39%|███▊      | 1375/3566 [55:33<1:30:12,  2.47s/it]
 39%|███▊      | 1376/3566 [55:35<1:28:04,  2.41s/it]
                                                     
{'loss': 1.5049, 'learning_rate': 0.00028049632975225825, 'epoch': 0.39}

 39%|███▊      | 1376/3566 [55:35<1:28:04,  2.41s/it]
 39%|███▊      | 1377/3566 [55:38<1:29:52,  2.46s/it]
                                                     
{'loss': 1.6983, 'learning_rate': 0.0002803303473691534, 'epoch': 0.39}

 39%|███▊      | 1377/3566 [55:38<1:29:52,  2.46s/it]
 39%|███▊      | 1378/3566 [55:40<1:28:16,  2.42s/it]
                                                     
{'loss': 1.529, 'learning_rate': 0.00028016429898934496, 'epoch': 0.39}

 39%|███▊      | 1378/3566 [55:40<1:28:16,  2.42s/it]
 39%|███▊      | 1379/3566 [55:42<1:26:40,  2.38s/it]
                                                     
{'loss': 1.5246, 'learning_rate': 0.00027999818474925257, 'epoch': 0.39}

 39%|███▊      | 1379/3566 [55:42<1:26:40,  2.38s/it]
 39%|███▊      | 1380/3566 [55:45<1:28:04,  2.42s/it]
                                                     
{'loss': 1.6582, 'learning_rate': 0.0002798320047853503, 'epoch': 0.39}

 39%|███▊      | 1380/3566 [55:45<1:28:04,  2.42s/it]
 39%|███▊      | 1381/3566 [55:47<1:26:16,  2.37s/it]
                                                     
{'loss': 1.6139, 'learning_rate': 0.0002796657592341659, 'epoch': 0.39}

 39%|███▊      | 1381/3566 [55:47<1:26:16,  2.37s/it]
 39%|███▉      | 1382/3566 [55:50<1:29:47,  2.47s/it]
                                                     
{'loss': 1.6289, 'learning_rate': 0.0002794994482322811, 'epoch': 0.39}

 39%|███▉      | 1382/3566 [55:50<1:29:47,  2.47s/it]
 39%|███▉      | 1383/3566 [55:52<1:25:43,  2.36s/it]
                                                     
{'loss': 1.512, 'learning_rate': 0.0002793330719163314, 'epoch': 0.39}

 39%|███▉      | 1383/3566 [55:52<1:25:43,  2.36s/it]
 39%|███▉      | 1384/3566 [55:54<1:24:48,  2.33s/it]
                                                     
{'loss': 1.6038, 'learning_rate': 0.000279166630423006, 'epoch': 0.39}

 39%|███▉      | 1384/3566 [55:54<1:24:48,  2.33s/it]
 39%|███▉      | 1385/3566 [55:57<1:27:35,  2.41s/it]
                                                     
{'loss': 1.8598, 'learning_rate': 0.00027900012388904757, 'epoch': 0.39}

 39%|███▉      | 1385/3566 [55:57<1:27:35,  2.41s/it]
 39%|███▉      | 1386/3566 [55:59<1:30:37,  2.49s/it]
                                                     
{'loss': 1.6253, 'learning_rate': 0.0002788335524512523, 'epoch': 0.39}

 39%|███▉      | 1386/3566 [55:59<1:30:37,  2.49s/it]
 39%|███▉      | 1387/3566 [56:02<1:28:53,  2.45s/it]
                                                     
{'loss': 1.4944, 'learning_rate': 0.0002786669162464697, 'epoch': 0.39}

 39%|███▉      | 1387/3566 [56:02<1:28:53,  2.45s/it]
 39%|███▉      | 1388/3566 [56:04<1:27:00,  2.40s/it]
                                                     
{'loss': 1.8054, 'learning_rate': 0.0002785002154116024, 'epoch': 0.39}

 39%|███▉      | 1388/3566 [56:04<1:27:00,  2.40s/it]
 39%|███▉      | 1389/3566 [56:06<1:23:22,  2.30s/it]
                                                     
{'loss': 1.5125, 'learning_rate': 0.00027833345008360615, 'epoch': 0.39}

 39%|███▉      | 1389/3566 [56:06<1:23:22,  2.30s/it]
 39%|███▉      | 1390/3566 [56:08<1:22:17,  2.27s/it]
                                                     
{'loss': 1.5585, 'learning_rate': 0.0002781666203994899, 'epoch': 0.39}

 39%|███▉      | 1390/3566 [56:08<1:22:17,  2.27s/it]
 39%|███▉      | 1391/3566 [56:11<1:23:04,  2.29s/it]
                                                     
{'loss': 1.6857, 'learning_rate': 0.000277999726496315, 'epoch': 0.39}

 39%|███▉      | 1391/3566 [56:11<1:23:04,  2.29s/it]
 39%|███▉      | 1392/3566 [56:13<1:26:46,  2.39s/it]
                                                     
{'loss': 1.6913, 'learning_rate': 0.0002778327685111961, 'epoch': 0.39}

 39%|███▉      | 1392/3566 [56:13<1:26:46,  2.39s/it]
 39%|███▉      | 1393/3566 [56:16<1:26:32,  2.39s/it]
                                                     
{'loss': 1.4969, 'learning_rate': 0.00027766574658130006, 'epoch': 0.39}

 39%|███▉      | 1393/3566 [56:16<1:26:32,  2.39s/it]
 39%|███▉      | 1394/3566 [56:18<1:25:40,  2.37s/it]
                                                     
{'loss': 1.6242, 'learning_rate': 0.0002774986608438466, 'epoch': 0.39}

 39%|███▉      | 1394/3566 [56:18<1:25:40,  2.37s/it]
 39%|███▉      | 1395/3566 [56:20<1:24:49,  2.34s/it]
                                                     
{'loss': 1.5628, 'learning_rate': 0.0002773315114361077, 'epoch': 0.39}

 39%|███▉      | 1395/3566 [56:20<1:24:49,  2.34s/it]
 39%|███▉      | 1396/3566 [56:23<1:25:09,  2.35s/it]
                                                     
{'loss': 1.5391, 'learning_rate': 0.00027716429849540764, 'epoch': 0.39}

 39%|███▉      | 1396/3566 [56:23<1:25:09,  2.35s/it]
 39%|███▉      | 1397/3566 [56:25<1:26:23,  2.39s/it]
                                                     
{'loss': 1.4453, 'learning_rate': 0.0002769970221591229, 'epoch': 0.39}

 39%|███▉      | 1397/3566 [56:25<1:26:23,  2.39s/it]
 39%|███▉      | 1398/3566 [56:27<1:24:21,  2.33s/it]
                                                     
{'loss': 1.5723, 'learning_rate': 0.00027682968256468227, 'epoch': 0.39}

 39%|███▉      | 1398/3566 [56:27<1:24:21,  2.33s/it]
 39%|███▉      | 1399/3566 [56:29<1:22:59,  2.30s/it]
                                                     
{'loss': 1.4469, 'learning_rate': 0.00027666227984956605, 'epoch': 0.39}

 39%|███▉      | 1399/3566 [56:29<1:22:59,  2.30s/it]
 39%|███▉      | 1400/3566 [56:32<1:22:20,  2.28s/it]
                                                     
{'loss': 1.6614, 'learning_rate': 0.00027649481415130677, 'epoch': 0.39}

 39%|███▉      | 1400/3566 [56:32<1:22:20,  2.28s/it]
 39%|███▉      | 1401/3566 [56:34<1:23:42,  2.32s/it]
                                                     
{'loss': 1.6085, 'learning_rate': 0.0002763272856074886, 'epoch': 0.39}

 39%|███▉      | 1401/3566 [56:34<1:23:42,  2.32s/it]
 39%|███▉      | 1402/3566 [56:36<1:23:39,  2.32s/it]
                                                     
{'loss': 1.4628, 'learning_rate': 0.00027615969435574743, 'epoch': 0.39}

 39%|███▉      | 1402/3566 [56:36<1:23:39,  2.32s/it]
 39%|███▉      | 1403/3566 [56:39<1:22:53,  2.30s/it]
                                                     
{'loss': 1.6109, 'learning_rate': 0.0002759920405337705, 'epoch': 0.39}

 39%|███▉      | 1403/3566 [56:39<1:22:53,  2.30s/it]
 39%|███▉      | 1404/3566 [56:41<1:24:44,  2.35s/it]
                                                     
{'loss': 1.6735, 'learning_rate': 0.0002758243242792965, 'epoch': 0.39}

 39%|███▉      | 1404/3566 [56:41<1:24:44,  2.35s/it]
 39%|███▉      | 1405/3566 [56:44<1:27:23,  2.43s/it]
                                                     
{'loss': 1.644, 'learning_rate': 0.00027565654573011544, 'epoch': 0.39}

 39%|███▉      | 1405/3566 [56:44<1:27:23,  2.43s/it]
 39%|███▉      | 1406/3566 [56:46<1:26:31,  2.40s/it]
                                                     
{'loss': 1.6833, 'learning_rate': 0.0002754887050240686, 'epoch': 0.39}

 39%|███▉      | 1406/3566 [56:46<1:26:31,  2.40s/it]
 39%|███▉      | 1407/3566 [56:48<1:24:54,  2.36s/it]
                                                     
{'loss': 1.6676, 'learning_rate': 0.0002753208022990482, 'epoch': 0.39}

 39%|███▉      | 1407/3566 [56:48<1:24:54,  2.36s/it]
 39%|███▉      | 1408/3566 [56:51<1:27:03,  2.42s/it]
                                                     
{'loss': 1.5092, 'learning_rate': 0.00027515283769299746, 'epoch': 0.39}

 39%|███▉      | 1408/3566 [56:51<1:27:03,  2.42s/it]
 40%|███▉      | 1409/3566 [56:53<1:26:40,  2.41s/it]
                                                     
{'loss': 1.5241, 'learning_rate': 0.0002749848113439104, 'epoch': 0.4}

 40%|███▉      | 1409/3566 [56:53<1:26:40,  2.41s/it]
 40%|███▉      | 1410/3566 [56:56<1:27:38,  2.44s/it]
                                                     
{'loss': 1.5969, 'learning_rate': 0.00027481672338983186, 'epoch': 0.4}

 40%|███▉      | 1410/3566 [56:56<1:27:38,  2.44s/it]
 40%|███▉      | 1411/3566 [56:58<1:28:42,  2.47s/it]
                                                     
{'loss': 1.7649, 'learning_rate': 0.00027464857396885726, 'epoch': 0.4}

 40%|███▉      | 1411/3566 [56:58<1:28:42,  2.47s/it]
 40%|███▉      | 1412/3566 [57:01<1:27:17,  2.43s/it]
                                                     
{'loss': 1.5747, 'learning_rate': 0.00027448036321913236, 'epoch': 0.4}

 40%|███▉      | 1412/3566 [57:01<1:27:17,  2.43s/it]
 40%|███▉      | 1413/3566 [57:03<1:24:14,  2.35s/it]
                                                     
{'loss': 1.4058, 'learning_rate': 0.00027431209127885353, 'epoch': 0.4}

 40%|███▉      | 1413/3566 [57:03<1:24:14,  2.35s/it]
 40%|███▉      | 1414/3566 [57:05<1:26:20,  2.41s/it]
                                                     
{'loss': 1.7127, 'learning_rate': 0.00027414375828626724, 'epoch': 0.4}

 40%|███▉      | 1414/3566 [57:05<1:26:20,  2.41s/it]
 40%|███▉      | 1415/3566 [57:08<1:23:43,  2.34s/it]
                                                     
{'loss': 1.573, 'learning_rate': 0.00027397536437967035, 'epoch': 0.4}

 40%|███▉      | 1415/3566 [57:08<1:23:43,  2.34s/it]
 40%|███▉      | 1416/3566 [57:10<1:22:53,  2.31s/it]
                                                     
{'loss': 1.531, 'learning_rate': 0.0002738069096974095, 'epoch': 0.4}

 40%|███▉      | 1416/3566 [57:10<1:22:53,  2.31s/it]
 40%|███▉      | 1417/3566 [57:12<1:23:28,  2.33s/it]
                                                     
{'loss': 1.6098, 'learning_rate': 0.0002736383943778814, 'epoch': 0.4}

 40%|███▉      | 1417/3566 [57:12<1:23:28,  2.33s/it]
 40%|███▉      | 1418/3566 [57:14<1:21:58,  2.29s/it]
                                                     
{'loss': 1.6464, 'learning_rate': 0.00027346981855953253, 'epoch': 0.4}

 40%|███▉      | 1418/3566 [57:14<1:21:58,  2.29s/it]
 40%|███▉      | 1419/3566 [57:17<1:22:51,  2.32s/it]
                                                     
{'loss': 1.5938, 'learning_rate': 0.00027330118238085916, 'epoch': 0.4}

 40%|███▉      | 1419/3566 [57:17<1:22:51,  2.32s/it]
 40%|███▉      | 1420/3566 [57:20<1:29:36,  2.51s/it]
                                                     
{'loss': 1.4606, 'learning_rate': 0.000273132485980407, 'epoch': 0.4}

 40%|███▉      | 1420/3566 [57:20<1:29:36,  2.51s/it]
 40%|███▉      | 1421/3566 [57:22<1:30:29,  2.53s/it]
                                                     
{'loss': 1.6626, 'learning_rate': 0.00027296372949677135, 'epoch': 0.4}

 40%|███▉      | 1421/3566 [57:22<1:30:29,  2.53s/it]
 40%|███▉      | 1422/3566 [57:24<1:26:28,  2.42s/it]
                                                     
{'loss': 1.5812, 'learning_rate': 0.00027279491306859684, 'epoch': 0.4}

 40%|███▉      | 1422/3566 [57:24<1:26:28,  2.42s/it]
 40%|███▉      | 1423/3566 [57:27<1:23:33,  2.34s/it]
                                                     
{'loss': 1.5507, 'learning_rate': 0.0002726260368345774, 'epoch': 0.4}

 40%|███▉      | 1423/3566 [57:27<1:23:33,  2.34s/it]
 40%|███▉      | 1424/3566 [57:29<1:23:02,  2.33s/it]
                                                     
{'loss': 1.6078, 'learning_rate': 0.00027245710093345613, 'epoch': 0.4}

 40%|███▉      | 1424/3566 [57:29<1:23:02,  2.33s/it]
 40%|███▉      | 1425/3566 [57:31<1:24:46,  2.38s/it]
                                                     
{'loss': 1.5539, 'learning_rate': 0.0002722881055040248, 'epoch': 0.4}

 40%|███▉      | 1425/3566 [57:31<1:24:46,  2.38s/it]
 40%|███▉      | 1426/3566 [57:34<1:28:07,  2.47s/it]
                                                     
{'loss': 1.6483, 'learning_rate': 0.0002721190506851246, 'epoch': 0.4}

 40%|███▉      | 1426/3566 [57:34<1:28:07,  2.47s/it]
 40%|████      | 1427/3566 [57:37<1:28:22,  2.48s/it]
                                                     
{'loss': 1.678, 'learning_rate': 0.00027194993661564513, 'epoch': 0.4}

 40%|████      | 1427/3566 [57:37<1:28:22,  2.48s/it]
 40%|████      | 1428/3566 [57:39<1:27:30,  2.46s/it]
                                                     
{'loss': 1.6343, 'learning_rate': 0.00027178076343452486, 'epoch': 0.4}

 40%|████      | 1428/3566 [57:39<1:27:30,  2.46s/it]
 40%|████      | 1429/3566 [57:42<1:28:53,  2.50s/it]
                                                     
{'loss': 1.536, 'learning_rate': 0.00027161153128075073, 'epoch': 0.4}

 40%|████      | 1429/3566 [57:42<1:28:53,  2.50s/it]
 40%|████      | 1430/3566 [57:44<1:27:20,  2.45s/it]
                                                     
{'loss': 1.4717, 'learning_rate': 0.00027144224029335823, 'epoch': 0.4}

 40%|████      | 1430/3566 [57:44<1:27:20,  2.45s/it]
 40%|████      | 1431/3566 [57:46<1:23:16,  2.34s/it]
                                                     
{'loss': 1.5653, 'learning_rate': 0.0002712728906114311, 'epoch': 0.4}

 40%|████      | 1431/3566 [57:46<1:23:16,  2.34s/it]
 40%|████      | 1432/3566 [57:49<1:25:36,  2.41s/it]
                                                     
{'loss': 1.6074, 'learning_rate': 0.00027110348237410135, 'epoch': 0.4}

 40%|████      | 1432/3566 [57:49<1:25:36,  2.41s/it]
 40%|████      | 1433/3566 [57:51<1:28:22,  2.49s/it]
                                                     
{'loss': 1.577, 'learning_rate': 0.000270934015720549, 'epoch': 0.4}

 40%|████      | 1433/3566 [57:51<1:28:22,  2.49s/it]
 40%|████      | 1434/3566 [57:54<1:29:03,  2.51s/it]
                                                     
{'loss': 1.5222, 'learning_rate': 0.00027076449079000217, 'epoch': 0.4}

 40%|████      | 1434/3566 [57:54<1:29:03,  2.51s/it]
 40%|████      | 1435/3566 [57:56<1:28:45,  2.50s/it]
                                                     
{'loss': 1.5487, 'learning_rate': 0.00027059490772173684, 'epoch': 0.4}

 40%|████      | 1435/3566 [57:56<1:28:45,  2.50s/it]
 40%|████      | 1436/3566 [57:59<1:27:00,  2.45s/it]
                                                     
{'loss': 1.6224, 'learning_rate': 0.00027042526665507674, 'epoch': 0.4}

 40%|████      | 1436/3566 [57:59<1:27:00,  2.45s/it]
 40%|████      | 1437/3566 [58:01<1:25:15,  2.40s/it]
                                                     
{'loss': 1.5369, 'learning_rate': 0.00027025556772939323, 'epoch': 0.4}

 40%|████      | 1437/3566 [58:01<1:25:15,  2.40s/it]
 40%|████      | 1438/3566 [58:03<1:26:24,  2.44s/it]
                                                     
{'loss': 1.7217, 'learning_rate': 0.00027008581108410525, 'epoch': 0.4}

 40%|████      | 1438/3566 [58:03<1:26:24,  2.44s/it]
 40%|████      | 1439/3566 [58:06<1:28:17,  2.49s/it]
                                                     
{'loss': 1.6173, 'learning_rate': 0.000269915996858679, 'epoch': 0.4}

 40%|████      | 1439/3566 [58:06<1:28:17,  2.49s/it]
 40%|████      | 1440/3566 [58:09<1:30:03,  2.54s/it]
                                                     
{'loss': 1.5546, 'learning_rate': 0.00026974612519262836, 'epoch': 0.4}

 40%|████      | 1440/3566 [58:09<1:30:03,  2.54s/it]
 40%|████      | 1441/3566 [58:11<1:28:50,  2.51s/it]
                                                     
{'loss': 1.5914, 'learning_rate': 0.0002695761962255141, 'epoch': 0.4}

 40%|████      | 1441/3566 [58:11<1:28:50,  2.51s/it]
 40%|████      | 1442/3566 [58:14<1:32:18,  2.61s/it]
                                                     
{'loss': 1.7928, 'learning_rate': 0.0002694062100969439, 'epoch': 0.4}

 40%|████      | 1442/3566 [58:14<1:32:18,  2.61s/it]
 40%|████      | 1443/3566 [58:16<1:27:39,  2.48s/it]
                                                     
{'loss': 1.4734, 'learning_rate': 0.0002692361669465728, 'epoch': 0.4}

 40%|████      | 1443/3566 [58:16<1:27:39,  2.48s/it]
 40%|████      | 1444/3566 [58:18<1:26:00,  2.43s/it]
                                                     
{'loss': 1.6999, 'learning_rate': 0.00026906606691410256, 'epoch': 0.4}

 40%|████      | 1444/3566 [58:18<1:26:00,  2.43s/it]
 41%|████      | 1445/3566 [58:21<1:24:31,  2.39s/it]
                                                     
{'loss': 1.6739, 'learning_rate': 0.00026889591013928155, 'epoch': 0.41}

 41%|████      | 1445/3566 [58:21<1:24:31,  2.39s/it]
 41%|████      | 1446/3566 [58:23<1:26:01,  2.43s/it]
                                                     
{'loss': 1.4526, 'learning_rate': 0.0002687256967619049, 'epoch': 0.41}

 41%|████      | 1446/3566 [58:23<1:26:01,  2.43s/it]
 41%|████      | 1447/3566 [58:26<1:25:51,  2.43s/it]
                                                     
{'loss': 1.5046, 'learning_rate': 0.00026855542692181416, 'epoch': 0.41}

 41%|████      | 1447/3566 [58:26<1:25:51,  2.43s/it]
 41%|████      | 1448/3566 [58:28<1:28:12,  2.50s/it]
                                                     
{'loss': 1.5466, 'learning_rate': 0.0002683851007588972, 'epoch': 0.41}

 41%|████      | 1448/3566 [58:28<1:28:12,  2.50s/it]
 41%|████      | 1449/3566 [58:31<1:24:49,  2.40s/it]
                                                     
{'loss': 1.4806, 'learning_rate': 0.00026821471841308837, 'epoch': 0.41}

 41%|████      | 1449/3566 [58:31<1:24:49,  2.40s/it]
 41%|████      | 1450/3566 [58:33<1:23:53,  2.38s/it]
                                                     
{'loss': 1.4408, 'learning_rate': 0.00026804428002436795, 'epoch': 0.41}

 41%|████      | 1450/3566 [58:33<1:23:53,  2.38s/it]
 41%|████      | 1451/3566 [58:35<1:23:19,  2.36s/it]
                                                     
{'loss': 1.675, 'learning_rate': 0.00026787378573276245, 'epoch': 0.41}

 41%|████      | 1451/3566 [58:35<1:23:19,  2.36s/it]
 41%|████      | 1452/3566 [58:37<1:20:49,  2.29s/it]
                                                     
{'loss': 1.6464, 'learning_rate': 0.0002677032356783442, 'epoch': 0.41}

 41%|████      | 1452/3566 [58:37<1:20:49,  2.29s/it]
 41%|████      | 1453/3566 [58:40<1:26:57,  2.47s/it]
                                                     
{'loss': 1.4288, 'learning_rate': 0.00026753263000123137, 'epoch': 0.41}

 41%|████      | 1453/3566 [58:40<1:26:57,  2.47s/it]
 41%|████      | 1454/3566 [58:43<1:25:12,  2.42s/it]
                                                     
{'loss': 1.5308, 'learning_rate': 0.0002673619688415879, 'epoch': 0.41}

 41%|████      | 1454/3566 [58:43<1:25:12,  2.42s/it]
 41%|████      | 1455/3566 [58:45<1:24:19,  2.40s/it]
                                                     
{'loss': 1.6454, 'learning_rate': 0.00026719125233962306, 'epoch': 0.41}

 41%|████      | 1455/3566 [58:45<1:24:19,  2.40s/it]
 41%|████      | 1456/3566 [58:47<1:22:58,  2.36s/it]
                                                     
{'loss': 1.5972, 'learning_rate': 0.00026702048063559196, 'epoch': 0.41}

 41%|████      | 1456/3566 [58:47<1:22:58,  2.36s/it]
 41%|████      | 1457/3566 [58:49<1:22:05,  2.34s/it]
                                                     
{'loss': 1.6361, 'learning_rate': 0.00026684965386979473, 'epoch': 0.41}

 41%|████      | 1457/3566 [58:49<1:22:05,  2.34s/it]
 41%|████      | 1458/3566 [58:52<1:23:01,  2.36s/it]
                                                     
{'loss': 1.7033, 'learning_rate': 0.000266678772182577, 'epoch': 0.41}

 41%|████      | 1458/3566 [58:52<1:23:01,  2.36s/it]
 41%|████      | 1459/3566 [58:54<1:20:56,  2.30s/it]
                                                     
{'loss': 1.5109, 'learning_rate': 0.0002665078357143294, 'epoch': 0.41}

 41%|████      | 1459/3566 [58:54<1:20:56,  2.30s/it]
 41%|████      | 1460/3566 [58:56<1:20:07,  2.28s/it]
                                                     
{'loss': 1.6466, 'learning_rate': 0.00026633684460548743, 'epoch': 0.41}

 41%|████      | 1460/3566 [58:56<1:20:07,  2.28s/it]
 41%|████      | 1461/3566 [58:59<1:23:14,  2.37s/it]
                                                     
{'loss': 1.4888, 'learning_rate': 0.0002661657989965317, 'epoch': 0.41}

 41%|████      | 1461/3566 [58:59<1:23:14,  2.37s/it]
 41%|████      | 1462/3566 [59:01<1:22:35,  2.36s/it]
                                                     
{'loss': 1.4921, 'learning_rate': 0.00026599469902798754, 'epoch': 0.41}

 41%|████      | 1462/3566 [59:01<1:22:35,  2.36s/it]
 41%|████      | 1463/3566 [59:04<1:23:24,  2.38s/it]
                                                     
{'loss': 1.7685, 'learning_rate': 0.0002658235448404249, 'epoch': 0.41}

 41%|████      | 1463/3566 [59:04<1:23:24,  2.38s/it]
 41%|████      | 1464/3566 [59:06<1:23:02,  2.37s/it]
                                                     
{'loss': 1.6959, 'learning_rate': 0.0002656523365744582, 'epoch': 0.41}

 41%|████      | 1464/3566 [59:06<1:23:02,  2.37s/it]
 41%|████      | 1465/3566 [59:08<1:22:48,  2.36s/it]
                                                     
{'loss': 1.6365, 'learning_rate': 0.0002654810743707465, 'epoch': 0.41}

 41%|████      | 1465/3566 [59:08<1:22:48,  2.36s/it]
 41%|████      | 1466/3566 [59:11<1:22:18,  2.35s/it]
                                                     
{'loss': 1.6566, 'learning_rate': 0.0002653097583699929, 'epoch': 0.41}

 41%|████      | 1466/3566 [59:11<1:22:18,  2.35s/it]
 41%|████      | 1467/3566 [59:13<1:22:25,  2.36s/it]
                                                     
{'loss': 1.5456, 'learning_rate': 0.0002651383887129451, 'epoch': 0.41}

 41%|████      | 1467/3566 [59:13<1:22:25,  2.36s/it]
 41%|████      | 1468/3566 [59:16<1:24:23,  2.41s/it]
                                                     
{'loss': 1.5749, 'learning_rate': 0.0002649669655403944, 'epoch': 0.41}

 41%|████      | 1468/3566 [59:16<1:24:23,  2.41s/it]
 41%|████      | 1469/3566 [59:18<1:25:07,  2.44s/it]
                                                     
{'loss': 1.393, 'learning_rate': 0.00026479548899317637, 'epoch': 0.41}

 41%|████      | 1469/3566 [59:18<1:25:07,  2.44s/it]
 41%|████      | 1470/3566 [59:20<1:23:22,  2.39s/it]
                                                     
{'loss': 1.4978, 'learning_rate': 0.00026462395921217027, 'epoch': 0.41}

 41%|████      | 1470/3566 [59:20<1:23:22,  2.39s/it]
 41%|████▏     | 1471/3566 [59:22<1:21:05,  2.32s/it]
                                                     
{'loss': 1.5108, 'learning_rate': 0.00026445237633829937, 'epoch': 0.41}

 41%|████▏     | 1471/3566 [59:22<1:21:05,  2.32s/it]
 41%|████▏     | 1472/3566 [59:25<1:20:50,  2.32s/it]
                                                     
{'loss': 1.4914, 'learning_rate': 0.00026428074051253024, 'epoch': 0.41}

 41%|████▏     | 1472/3566 [59:25<1:20:50,  2.32s/it]
 41%|████▏     | 1473/3566 [59:27<1:18:51,  2.26s/it]
                                                     
{'loss': 1.5146, 'learning_rate': 0.0002641090518758731, 'epoch': 0.41}

 41%|████▏     | 1473/3566 [59:27<1:18:51,  2.26s/it]
 41%|████▏     | 1474/3566 [59:29<1:18:38,  2.26s/it]
                                                     
{'loss': 1.6586, 'learning_rate': 0.0002639373105693815, 'epoch': 0.41}

 41%|████▏     | 1474/3566 [59:29<1:18:38,  2.26s/it]
 41%|████▏     | 1475/3566 [59:32<1:22:11,  2.36s/it]
                                                     
{'loss': 1.6137, 'learning_rate': 0.0002637655167341525, 'epoch': 0.41}

 41%|████▏     | 1475/3566 [59:32<1:22:11,  2.36s/it]
 41%|████▏     | 1476/3566 [59:34<1:20:58,  2.32s/it]
                                                     
{'loss': 1.5716, 'learning_rate': 0.0002635936705113259, 'epoch': 0.41}

 41%|████▏     | 1476/3566 [59:34<1:20:58,  2.32s/it]
 41%|████▏     | 1477/3566 [59:37<1:23:43,  2.40s/it]
                                                     
{'loss': 1.4816, 'learning_rate': 0.0002634217720420848, 'epoch': 0.41}

 41%|████▏     | 1477/3566 [59:37<1:23:43,  2.40s/it]
 41%|████▏     | 1478/3566 [59:39<1:23:38,  2.40s/it]
                                                     
{'loss': 1.4983, 'learning_rate': 0.0002632498214676552, 'epoch': 0.41}

 41%|████▏     | 1478/3566 [59:39<1:23:38,  2.40s/it]
 41%|████▏     | 1479/3566 [59:41<1:22:41,  2.38s/it]
                                                     
{'loss': 1.57, 'learning_rate': 0.000263077818929306, 'epoch': 0.41}

 41%|████▏     | 1479/3566 [59:41<1:22:41,  2.38s/it]
 42%|████▏     | 1480/3566 [59:44<1:20:52,  2.33s/it]
                                                     
{'loss': 1.3983, 'learning_rate': 0.0002629057645683485, 'epoch': 0.42}

 42%|████▏     | 1480/3566 [59:44<1:20:52,  2.33s/it]
 42%|████▏     | 1481/3566 [59:46<1:24:15,  2.42s/it]
                                                     
{'loss': 1.588, 'learning_rate': 0.00026273365852613696, 'epoch': 0.42}

 42%|████▏     | 1481/3566 [59:46<1:24:15,  2.42s/it]
 42%|████▏     | 1482/3566 [59:48<1:22:15,  2.37s/it]
                                                     
{'loss': 1.7071, 'learning_rate': 0.0002625615009440677, 'epoch': 0.42}

 42%|████▏     | 1482/3566 [59:48<1:22:15,  2.37s/it]
 42%|████▏     | 1483/3566 [59:51<1:20:31,  2.32s/it]
                                                     
{'loss': 1.5111, 'learning_rate': 0.0002623892919635797, 'epoch': 0.42}

 42%|████▏     | 1483/3566 [59:51<1:20:31,  2.32s/it]
 42%|████▏     | 1484/3566 [59:53<1:21:14,  2.34s/it]
                                                     
{'loss': 1.6639, 'learning_rate': 0.00026221703172615407, 'epoch': 0.42}

 42%|████▏     | 1484/3566 [59:53<1:21:14,  2.34s/it]
 42%|████▏     | 1485/3566 [59:56<1:28:45,  2.56s/it]
                                                     
{'loss': 1.6503, 'learning_rate': 0.0002620447203733139, 'epoch': 0.42}

 42%|████▏     | 1485/3566 [59:56<1:28:45,  2.56s/it]
 42%|████▏     | 1486/3566 [59:58<1:24:50,  2.45s/it]
                                                     
{'loss': 1.8411, 'learning_rate': 0.0002618723580466245, 'epoch': 0.42}

 42%|████▏     | 1486/3566 [59:58<1:24:50,  2.45s/it]
 42%|████▏     | 1487/3566 [1:00:01<1:23:03,  2.40s/it]
                                                       
{'loss': 1.5682, 'learning_rate': 0.00026169994488769283, 'epoch': 0.42}

 42%|████▏     | 1487/3566 [1:00:01<1:23:03,  2.40s/it]
 42%|████▏     | 1488/3566 [1:00:03<1:23:49,  2.42s/it]
                                                       
{'loss': 1.7213, 'learning_rate': 0.00026152748103816785, 'epoch': 0.42}

 42%|████▏     | 1488/3566 [1:00:03<1:23:49,  2.42s/it]
 42%|████▏     | 1489/3566 [1:00:06<1:26:41,  2.50s/it]
                                                       
{'loss': 1.5409, 'learning_rate': 0.00026135496663974, 'epoch': 0.42}

 42%|████▏     | 1489/3566 [1:00:06<1:26:41,  2.50s/it]
 42%|████▏     | 1490/3566 [1:00:08<1:27:58,  2.54s/it]
                                                       
{'loss': 1.5094, 'learning_rate': 0.0002611824018341412, 'epoch': 0.42}

 42%|████▏     | 1490/3566 [1:00:08<1:27:58,  2.54s/it]
 42%|████▏     | 1491/3566 [1:00:11<1:25:15,  2.47s/it]
                                                       
{'loss': 1.7543, 'learning_rate': 0.00026100978676314496, 'epoch': 0.42}

 42%|████▏     | 1491/3566 [1:00:11<1:25:15,  2.47s/it]
 42%|████▏     | 1492/3566 [1:00:13<1:26:50,  2.51s/it]
                                                       
{'loss': 1.6379, 'learning_rate': 0.00026083712156856596, 'epoch': 0.42}

 42%|████▏     | 1492/3566 [1:00:13<1:26:50,  2.51s/it]
 42%|████▏     | 1493/3566 [1:00:16<1:27:32,  2.53s/it]
                                                       
{'loss': 1.6939, 'learning_rate': 0.0002606644063922602, 'epoch': 0.42}

 42%|████▏     | 1493/3566 [1:00:16<1:27:32,  2.53s/it]
 42%|████▏     | 1494/3566 [1:00:18<1:26:37,  2.51s/it]
                                                       
{'loss': 1.6746, 'learning_rate': 0.0002604916413761245, 'epoch': 0.42}

 42%|████▏     | 1494/3566 [1:00:18<1:26:37,  2.51s/it]
 42%|████▏     | 1495/3566 [1:00:21<1:24:36,  2.45s/it]
                                                       
{'loss': 1.5731, 'learning_rate': 0.00026031882666209685, 'epoch': 0.42}

 42%|████▏     | 1495/3566 [1:00:21<1:24:36,  2.45s/it]
 42%|████▏     | 1496/3566 [1:00:23<1:23:02,  2.41s/it]
                                                       
{'loss': 1.5194, 'learning_rate': 0.0002601459623921559, 'epoch': 0.42}

 42%|████▏     | 1496/3566 [1:00:23<1:23:02,  2.41s/it]
 42%|████▏     | 1497/3566 [1:00:25<1:22:05,  2.38s/it]
                                                       
{'loss': 1.5836, 'learning_rate': 0.0002599730487083213, 'epoch': 0.42}

 42%|████▏     | 1497/3566 [1:00:25<1:22:05,  2.38s/it]
 42%|████▏     | 1498/3566 [1:00:28<1:22:24,  2.39s/it]
                                                       
{'loss': 1.6906, 'learning_rate': 0.00025980008575265294, 'epoch': 0.42}

 42%|████▏     | 1498/3566 [1:00:28<1:22:24,  2.39s/it]
 42%|████▏     | 1499/3566 [1:00:30<1:21:03,  2.35s/it]
                                                       
{'loss': 1.5943, 'learning_rate': 0.0002596270736672513, 'epoch': 0.42}

 42%|████▏     | 1499/3566 [1:00:30<1:21:03,  2.35s/it]
 42%|████▏     | 1500/3566 [1:00:32<1:18:56,  2.29s/it]
                                                       
{'loss': 1.5434, 'learning_rate': 0.0002594540125942574, 'epoch': 0.42}

 42%|████▏     | 1500/3566 [1:00:32<1:18:56,  2.29s/it]
 42%|████▏     | 1501/3566 [1:00:34<1:19:43,  2.32s/it]
                                                       
{'loss': 1.5649, 'learning_rate': 0.0002592809026758524, 'epoch': 0.42}

 42%|████▏     | 1501/3566 [1:00:34<1:19:43,  2.32s/it]
 42%|████▏     | 1502/3566 [1:00:37<1:22:49,  2.41s/it]
                                                       
{'loss': 1.5539, 'learning_rate': 0.00025910774405425745, 'epoch': 0.42}

 42%|████▏     | 1502/3566 [1:00:37<1:22:49,  2.41s/it]
 42%|████▏     | 1503/3566 [1:00:39<1:20:30,  2.34s/it]
                                                       
{'loss': 1.7896, 'learning_rate': 0.00025893453687173386, 'epoch': 0.42}

 42%|████▏     | 1503/3566 [1:00:39<1:20:30,  2.34s/it]
 42%|████▏     | 1504/3566 [1:00:42<1:21:52,  2.38s/it]
                                                       
{'loss': 1.6039, 'learning_rate': 0.0002587612812705829, 'epoch': 0.42}

 42%|████▏     | 1504/3566 [1:00:42<1:21:52,  2.38s/it]
 42%|████▏     | 1505/3566 [1:00:44<1:20:12,  2.33s/it]
                                                       
{'loss': 1.6795, 'learning_rate': 0.00025858797739314543, 'epoch': 0.42}

 42%|████▏     | 1505/3566 [1:00:44<1:20:12,  2.33s/it]
 42%|████▏     | 1506/3566 [1:00:47<1:31:51,  2.68s/it]
                                                       
{'loss': 1.6231, 'learning_rate': 0.0002584146253818021, 'epoch': 0.42}

 42%|████▏     | 1506/3566 [1:00:47<1:31:51,  2.68s/it]
 42%|████▏     | 1507/3566 [1:00:50<1:28:55,  2.59s/it]
                                                       
{'loss': 1.566, 'learning_rate': 0.00025824122537897306, 'epoch': 0.42}

 42%|████▏     | 1507/3566 [1:00:50<1:28:55,  2.59s/it]
 42%|████▏     | 1508/3566 [1:00:52<1:28:59,  2.59s/it]
                                                       
{'loss': 1.5596, 'learning_rate': 0.000258067777527118, 'epoch': 0.42}

 42%|████▏     | 1508/3566 [1:00:52<1:28:59,  2.59s/it]
 42%|████▏     | 1509/3566 [1:00:55<1:26:36,  2.53s/it]
                                                       
{'loss': 1.5003, 'learning_rate': 0.0002578942819687357, 'epoch': 0.42}

 42%|████▏     | 1509/3566 [1:00:55<1:26:36,  2.53s/it]
 42%|████▏     | 1510/3566 [1:00:57<1:23:22,  2.43s/it]
                                                       
{'loss': 1.4594, 'learning_rate': 0.0002577207388463643, 'epoch': 0.42}

 42%|████▏     | 1510/3566 [1:00:57<1:23:22,  2.43s/it]
 42%|████▏     | 1511/3566 [1:01:00<1:28:22,  2.58s/it]
                                                       
{'loss': 1.6117, 'learning_rate': 0.000257547148302581, 'epoch': 0.42}

 42%|████▏     | 1511/3566 [1:01:00<1:28:22,  2.58s/it]
 42%|████▏     | 1512/3566 [1:01:02<1:26:14,  2.52s/it]
                                                       
{'loss': 1.6485, 'learning_rate': 0.0002573735104800019, 'epoch': 0.42}

 42%|████▏     | 1512/3566 [1:01:02<1:26:14,  2.52s/it]
 42%|████▏     | 1513/3566 [1:01:05<1:24:02,  2.46s/it]
                                                       
{'loss': 1.5471, 'learning_rate': 0.0002571998255212819, 'epoch': 0.42}

 42%|████▏     | 1513/3566 [1:01:05<1:24:02,  2.46s/it]
 42%|████▏     | 1514/3566 [1:01:07<1:22:09,  2.40s/it]
                                                       
{'loss': 1.7916, 'learning_rate': 0.00025702609356911496, 'epoch': 0.42}

 42%|████▏     | 1514/3566 [1:01:07<1:22:09,  2.40s/it]
 42%|████▏     | 1515/3566 [1:01:09<1:21:59,  2.40s/it]
                                                       
{'loss': 1.5788, 'learning_rate': 0.0002568523147662331, 'epoch': 0.42}

 42%|████▏     | 1515/3566 [1:01:09<1:21:59,  2.40s/it]
 43%|████▎     | 1516/3566 [1:01:12<1:20:29,  2.36s/it]
                                                       
{'loss': 1.5992, 'learning_rate': 0.0002566784892554073, 'epoch': 0.43}

 43%|████▎     | 1516/3566 [1:01:12<1:20:29,  2.36s/it]
 43%|████▎     | 1517/3566 [1:01:14<1:19:33,  2.33s/it]
                                                       
{'loss': 1.6932, 'learning_rate': 0.00025650461717944666, 'epoch': 0.43}

 43%|████▎     | 1517/3566 [1:01:14<1:19:33,  2.33s/it]
 43%|████▎     | 1518/3566 [1:01:16<1:20:00,  2.34s/it]
                                                       
{'loss': 1.5534, 'learning_rate': 0.00025633069868119865, 'epoch': 0.43}

 43%|████▎     | 1518/3566 [1:01:16<1:20:00,  2.34s/it]
 43%|████▎     | 1519/3566 [1:01:19<1:20:26,  2.36s/it]
                                                       
{'loss': 1.6099, 'learning_rate': 0.0002561567339035489, 'epoch': 0.43}

 43%|████▎     | 1519/3566 [1:01:19<1:20:26,  2.36s/it]
 43%|████▎     | 1520/3566 [1:01:21<1:19:44,  2.34s/it]
                                                       
{'loss': 1.5029, 'learning_rate': 0.0002559827229894208, 'epoch': 0.43}

 43%|████▎     | 1520/3566 [1:01:21<1:19:44,  2.34s/it]
 43%|████▎     | 1521/3566 [1:01:23<1:18:46,  2.31s/it]
                                                       
{'loss': 1.4537, 'learning_rate': 0.000255808666081776, 'epoch': 0.43}

 43%|████▎     | 1521/3566 [1:01:23<1:18:46,  2.31s/it]
 43%|████▎     | 1522/3566 [1:01:25<1:18:47,  2.31s/it]
                                                       
{'loss': 1.6383, 'learning_rate': 0.00025563456332361386, 'epoch': 0.43}

 43%|████▎     | 1522/3566 [1:01:25<1:18:47,  2.31s/it]
 43%|████▎     | 1523/3566 [1:01:28<1:22:14,  2.42s/it]
                                                       
{'loss': 1.5842, 'learning_rate': 0.00025546041485797116, 'epoch': 0.43}

 43%|████▎     | 1523/3566 [1:01:28<1:22:14,  2.42s/it]
 43%|████▎     | 1524/3566 [1:01:30<1:22:22,  2.42s/it]
                                                       
{'loss': 1.7171, 'learning_rate': 0.00025528622082792254, 'epoch': 0.43}

 43%|████▎     | 1524/3566 [1:01:30<1:22:22,  2.42s/it]
 43%|████▎     | 1525/3566 [1:01:33<1:20:08,  2.36s/it]
                                                       
{'loss': 1.6149, 'learning_rate': 0.0002551119813765798, 'epoch': 0.43}

 43%|████▎     | 1525/3566 [1:01:33<1:20:08,  2.36s/it]
 43%|████▎     | 1526/3566 [1:01:35<1:19:36,  2.34s/it]
                                                       
{'loss': 1.4452, 'learning_rate': 0.0002549376966470923, 'epoch': 0.43}

 43%|████▎     | 1526/3566 [1:01:35<1:19:36,  2.34s/it]
 43%|████▎     | 1527/3566 [1:01:37<1:18:52,  2.32s/it]
                                                       
{'loss': 1.531, 'learning_rate': 0.0002547633667826465, 'epoch': 0.43}

 43%|████▎     | 1527/3566 [1:01:37<1:18:52,  2.32s/it]
 43%|████▎     | 1528/3566 [1:01:40<1:18:11,  2.30s/it]
                                                       
{'loss': 1.4827, 'learning_rate': 0.00025458899192646586, 'epoch': 0.43}

 43%|████▎     | 1528/3566 [1:01:40<1:18:11,  2.30s/it]
 43%|████▎     | 1529/3566 [1:01:42<1:19:16,  2.34s/it]
                                                       
{'loss': 1.5782, 'learning_rate': 0.00025441457222181096, 'epoch': 0.43}

 43%|████▎     | 1529/3566 [1:01:42<1:19:16,  2.34s/it]
 43%|████▎     | 1530/3566 [1:01:44<1:21:03,  2.39s/it]
                                                       
{'loss': 1.5321, 'learning_rate': 0.00025424010781197905, 'epoch': 0.43}

 43%|████▎     | 1530/3566 [1:01:44<1:21:03,  2.39s/it]
 43%|████▎     | 1531/3566 [1:01:47<1:20:12,  2.36s/it]
                                                       
{'loss': 1.6408, 'learning_rate': 0.0002540655988403043, 'epoch': 0.43}

 43%|████▎     | 1531/3566 [1:01:47<1:20:12,  2.36s/it]
 43%|████▎     | 1532/3566 [1:01:49<1:19:35,  2.35s/it]
                                                       
{'loss': 1.507, 'learning_rate': 0.0002538910454501574, 'epoch': 0.43}

 43%|████▎     | 1532/3566 [1:01:49<1:19:35,  2.35s/it]
 43%|████▎     | 1533/3566 [1:01:51<1:19:27,  2.34s/it]
                                                       
{'loss': 1.5447, 'learning_rate': 0.00025371644778494543, 'epoch': 0.43}

 43%|████▎     | 1533/3566 [1:01:51<1:19:27,  2.34s/it]
 43%|████▎     | 1534/3566 [1:01:54<1:21:10,  2.40s/it]
                                                       
{'loss': 1.5883, 'learning_rate': 0.00025354180598811195, 'epoch': 0.43}

 43%|████▎     | 1534/3566 [1:01:54<1:21:10,  2.40s/it]
 43%|████▎     | 1535/3566 [1:01:56<1:20:24,  2.38s/it]
                                                       
{'loss': 1.6542, 'learning_rate': 0.00025336712020313694, 'epoch': 0.43}

 43%|████▎     | 1535/3566 [1:01:56<1:20:24,  2.38s/it]
 43%|████▎     | 1536/3566 [1:01:59<1:21:58,  2.42s/it]
                                                       
{'loss': 1.4731, 'learning_rate': 0.0002531923905735362, 'epoch': 0.43}

 43%|████▎     | 1536/3566 [1:01:59<1:21:58,  2.42s/it]
 43%|████▎     | 1537/3566 [1:02:01<1:20:19,  2.38s/it]
                                                       
{'loss': 1.4463, 'learning_rate': 0.00025301761724286166, 'epoch': 0.43}

 43%|████▎     | 1537/3566 [1:02:01<1:20:19,  2.38s/it]
 43%|████▎     | 1538/3566 [1:02:03<1:18:24,  2.32s/it]
                                                       
{'loss': 1.5595, 'learning_rate': 0.00025284280035470127, 'epoch': 0.43}

 43%|████▎     | 1538/3566 [1:02:03<1:18:24,  2.32s/it]
 43%|████▎     | 1539/3566 [1:02:06<1:19:21,  2.35s/it]
                                                       
{'loss': 1.6009, 'learning_rate': 0.00025266794005267864, 'epoch': 0.43}

 43%|████▎     | 1539/3566 [1:02:06<1:19:21,  2.35s/it]
 43%|████▎     | 1540/3566 [1:02:08<1:23:14,  2.47s/it]
                                                       
{'loss': 1.6186, 'learning_rate': 0.00025249303648045327, 'epoch': 0.43}

 43%|████▎     | 1540/3566 [1:02:08<1:23:14,  2.47s/it]
 43%|████▎     | 1541/3566 [1:02:11<1:25:06,  2.52s/it]
                                                       
{'loss': 1.4711, 'learning_rate': 0.0002523180897817198, 'epoch': 0.43}

 43%|████▎     | 1541/3566 [1:02:11<1:25:06,  2.52s/it]
 43%|████▎     | 1542/3566 [1:02:13<1:23:10,  2.47s/it]
                                                       
{'loss': 1.5344, 'learning_rate': 0.0002521431001002086, 'epoch': 0.43}

 43%|████▎     | 1542/3566 [1:02:13<1:23:10,  2.47s/it]
 43%|████▎     | 1543/3566 [1:02:16<1:21:09,  2.41s/it]
                                                       
{'loss': 1.7139, 'learning_rate': 0.0002519680675796853, 'epoch': 0.43}

 43%|████▎     | 1543/3566 [1:02:16<1:21:09,  2.41s/it]
 43%|████▎     | 1544/3566 [1:02:18<1:25:07,  2.53s/it]
                                                       
{'loss': 1.703, 'learning_rate': 0.00025179299236395086, 'epoch': 0.43}

 43%|████▎     | 1544/3566 [1:02:18<1:25:07,  2.53s/it]
 43%|████▎     | 1545/3566 [1:02:21<1:24:17,  2.50s/it]
                                                       
{'loss': 1.624, 'learning_rate': 0.000251617874596841, 'epoch': 0.43}

 43%|████▎     | 1545/3566 [1:02:21<1:24:17,  2.50s/it]
 43%|████▎     | 1546/3566 [1:02:23<1:22:08,  2.44s/it]
                                                       
{'loss': 1.5383, 'learning_rate': 0.00025144271442222656, 'epoch': 0.43}

 43%|████▎     | 1546/3566 [1:02:23<1:22:08,  2.44s/it]
 43%|████▎     | 1547/3566 [1:02:26<1:20:54,  2.40s/it]
                                                       
{'loss': 1.3363, 'learning_rate': 0.0002512675119840133, 'epoch': 0.43}

 43%|████▎     | 1547/3566 [1:02:26<1:20:54,  2.40s/it]
 43%|████▎     | 1548/3566 [1:02:28<1:24:13,  2.50s/it]
                                                       
{'loss': 1.5917, 'learning_rate': 0.00025109226742614163, 'epoch': 0.43}

 43%|████▎     | 1548/3566 [1:02:28<1:24:13,  2.50s/it]
 43%|████▎     | 1549/3566 [1:02:30<1:20:25,  2.39s/it]
                                                       
{'loss': 1.5101, 'learning_rate': 0.00025091698089258656, 'epoch': 0.43}

 43%|████▎     | 1549/3566 [1:02:30<1:20:25,  2.39s/it]
 43%|████▎     | 1550/3566 [1:02:33<1:21:30,  2.43s/it]
                                                       
{'loss': 1.588, 'learning_rate': 0.0002507416525273576, 'epoch': 0.43}

 43%|████▎     | 1550/3566 [1:02:33<1:21:30,  2.43s/it]
 43%|████▎     | 1551/3566 [1:02:36<1:23:23,  2.48s/it]
                                                       
{'loss': 1.6409, 'learning_rate': 0.00025056628247449857, 'epoch': 0.43}

 43%|████▎     | 1551/3566 [1:02:36<1:23:23,  2.48s/it]
 44%|████▎     | 1552/3566 [1:02:38<1:20:57,  2.41s/it]
                                                       
{'loss': 1.4405, 'learning_rate': 0.00025039087087808765, 'epoch': 0.44}

 44%|████▎     | 1552/3566 [1:02:38<1:20:57,  2.41s/it]
 44%|████▎     | 1553/3566 [1:02:40<1:21:07,  2.42s/it]
                                                       
{'loss': 1.5421, 'learning_rate': 0.00025021541788223714, 'epoch': 0.44}

 44%|████▎     | 1553/3566 [1:02:40<1:21:07,  2.42s/it]
 44%|████▎     | 1554/3566 [1:02:43<1:24:33,  2.52s/it]
                                                       
{'loss': 1.5258, 'learning_rate': 0.0002500399236310932, 'epoch': 0.44}

 44%|████▎     | 1554/3566 [1:02:43<1:24:33,  2.52s/it]
 44%|████▎     | 1555/3566 [1:02:45<1:20:43,  2.41s/it]
                                                       
{'loss': 1.5296, 'learning_rate': 0.00024986438826883595, 'epoch': 0.44}

 44%|████▎     | 1555/3566 [1:02:45<1:20:43,  2.41s/it]
 44%|████▎     | 1556/3566 [1:02:47<1:19:57,  2.39s/it]
                                                       
{'loss': 1.5543, 'learning_rate': 0.0002496888119396794, 'epoch': 0.44}

 44%|████▎     | 1556/3566 [1:02:47<1:19:57,  2.39s/it]
 44%|████▎     | 1557/3566 [1:02:50<1:18:26,  2.34s/it]
                                                       
{'loss': 1.5746, 'learning_rate': 0.00024951319478787125, 'epoch': 0.44}

 44%|████▎     | 1557/3566 [1:02:50<1:18:26,  2.34s/it]
 44%|████▎     | 1558/3566 [1:02:52<1:19:31,  2.38s/it]
                                                       
{'loss': 1.7266, 'learning_rate': 0.00024933753695769237, 'epoch': 0.44}

 44%|████▎     | 1558/3566 [1:02:52<1:19:31,  2.38s/it]
 44%|████▎     | 1559/3566 [1:02:55<1:22:00,  2.45s/it]
                                                       
{'loss': 1.7363, 'learning_rate': 0.00024916183859345756, 'epoch': 0.44}

 44%|████▎     | 1559/3566 [1:02:55<1:22:00,  2.45s/it]
 44%|████▎     | 1560/3566 [1:02:57<1:22:13,  2.46s/it]
                                                       
{'loss': 1.6904, 'learning_rate': 0.00024898609983951445, 'epoch': 0.44}

 44%|████▎     | 1560/3566 [1:02:57<1:22:13,  2.46s/it]
 44%|████▍     | 1561/3566 [1:03:00<1:20:46,  2.42s/it]
                                                       
{'loss': 1.6837, 'learning_rate': 0.00024881032084024426, 'epoch': 0.44}

 44%|████▍     | 1561/3566 [1:03:00<1:20:46,  2.42s/it]
 44%|████▍     | 1562/3566 [1:03:02<1:24:07,  2.52s/it]
                                                       
{'loss': 1.5852, 'learning_rate': 0.000248634501740061, 'epoch': 0.44}

 44%|████▍     | 1562/3566 [1:03:02<1:24:07,  2.52s/it]
 44%|████▍     | 1563/3566 [1:03:04<1:19:58,  2.40s/it]
                                                       
{'loss': 1.5069, 'learning_rate': 0.00024845864268341166, 'epoch': 0.44}

 44%|████▍     | 1563/3566 [1:03:04<1:19:58,  2.40s/it]
 44%|████▍     | 1564/3566 [1:03:07<1:18:52,  2.36s/it]
                                                       
{'loss': 1.6916, 'learning_rate': 0.00024828274381477616, 'epoch': 0.44}

 44%|████▍     | 1564/3566 [1:03:07<1:18:52,  2.36s/it]
 44%|████▍     | 1565/3566 [1:03:09<1:18:26,  2.35s/it]
                                                       
{'loss': 1.5812, 'learning_rate': 0.00024810680527866715, 'epoch': 0.44}

 44%|████▍     | 1565/3566 [1:03:09<1:18:26,  2.35s/it]
 44%|████▍     | 1566/3566 [1:03:11<1:17:34,  2.33s/it]
                                                       
{'loss': 1.5797, 'learning_rate': 0.0002479308272196297, 'epoch': 0.44}

 44%|████▍     | 1566/3566 [1:03:11<1:17:34,  2.33s/it]
 44%|████▍     | 1567/3566 [1:03:14<1:20:38,  2.42s/it]
                                                       
{'loss': 1.6729, 'learning_rate': 0.00024775480978224147, 'epoch': 0.44}

 44%|████▍     | 1567/3566 [1:03:14<1:20:38,  2.42s/it]
 44%|████▍     | 1568/3566 [1:03:17<1:22:33,  2.48s/it]
                                                       
{'loss': 1.5456, 'learning_rate': 0.00024757875311111246, 'epoch': 0.44}

 44%|████▍     | 1568/3566 [1:03:17<1:22:33,  2.48s/it]
 44%|████▍     | 1569/3566 [1:03:19<1:20:39,  2.42s/it]
                                                       
{'loss': 1.6212, 'learning_rate': 0.00024740265735088485, 'epoch': 0.44}

 44%|████▍     | 1569/3566 [1:03:19<1:20:39,  2.42s/it]
 44%|████▍     | 1570/3566 [1:03:21<1:21:19,  2.44s/it]
                                                       
{'loss': 1.5198, 'learning_rate': 0.00024722652264623306, 'epoch': 0.44}

 44%|████▍     | 1570/3566 [1:03:21<1:21:19,  2.44s/it]
 44%|████▍     | 1571/3566 [1:03:24<1:19:50,  2.40s/it]
                                                       
{'loss': 1.4736, 'learning_rate': 0.00024705034914186333, 'epoch': 0.44}

 44%|████▍     | 1571/3566 [1:03:24<1:19:50,  2.40s/it]
 44%|████▍     | 1572/3566 [1:03:26<1:17:41,  2.34s/it]
                                                       
{'loss': 1.3715, 'learning_rate': 0.00024687413698251394, 'epoch': 0.44}

 44%|████▍     | 1572/3566 [1:03:26<1:17:41,  2.34s/it]
 44%|████▍     | 1573/3566 [1:03:28<1:17:35,  2.34s/it]
                                                       
{'loss': 1.6873, 'learning_rate': 0.0002466978863129548, 'epoch': 0.44}

 44%|████▍     | 1573/3566 [1:03:28<1:17:35,  2.34s/it]
 44%|████▍     | 1574/3566 [1:03:30<1:16:13,  2.30s/it]
                                                       
{'loss': 1.5421, 'learning_rate': 0.00024652159727798763, 'epoch': 0.44}

 44%|████▍     | 1574/3566 [1:03:30<1:16:13,  2.30s/it]
 44%|████▍     | 1575/3566 [1:03:33<1:15:23,  2.27s/it]
                                                       
{'loss': 1.5436, 'learning_rate': 0.0002463452700224454, 'epoch': 0.44}

 44%|████▍     | 1575/3566 [1:03:33<1:15:23,  2.27s/it]
 44%|████▍     | 1576/3566 [1:03:35<1:20:36,  2.43s/it]
                                                       
{'loss': 1.6014, 'learning_rate': 0.0002461689046911926, 'epoch': 0.44}

 44%|████▍     | 1576/3566 [1:03:35<1:20:36,  2.43s/it]
 44%|████▍     | 1577/3566 [1:03:38<1:19:32,  2.40s/it]
                                                       
{'loss': 1.5805, 'learning_rate': 0.00024599250142912527, 'epoch': 0.44}

 44%|████▍     | 1577/3566 [1:03:38<1:19:32,  2.40s/it]
 44%|████▍     | 1578/3566 [1:03:41<1:23:29,  2.52s/it]
                                                       
{'loss': 1.4851, 'learning_rate': 0.0002458160603811702, 'epoch': 0.44}

 44%|████▍     | 1578/3566 [1:03:41<1:23:29,  2.52s/it]
 44%|████▍     | 1579/3566 [1:03:43<1:21:53,  2.47s/it]
                                                       
{'loss': 1.7865, 'learning_rate': 0.0002456395816922855, 'epoch': 0.44}

 44%|████▍     | 1579/3566 [1:03:43<1:21:53,  2.47s/it]
 44%|████▍     | 1580/3566 [1:03:45<1:22:03,  2.48s/it]
                                                       
{'loss': 1.6202, 'learning_rate': 0.00024546306550746004, 'epoch': 0.44}

 44%|████▍     | 1580/3566 [1:03:45<1:22:03,  2.48s/it]
 44%|████▍     | 1581/3566 [1:03:48<1:19:34,  2.41s/it]
                                                       
{'loss': 1.6061, 'learning_rate': 0.0002452865119717136, 'epoch': 0.44}

 44%|████▍     | 1581/3566 [1:03:48<1:19:34,  2.41s/it]
 44%|████▍     | 1582/3566 [1:03:50<1:18:58,  2.39s/it]
                                                       
{'loss': 1.6226, 'learning_rate': 0.0002451099212300966, 'epoch': 0.44}

 44%|████▍     | 1582/3566 [1:03:50<1:18:58,  2.39s/it]
 44%|████▍     | 1583/3566 [1:03:52<1:18:10,  2.37s/it]
                                                       
{'loss': 1.5634, 'learning_rate': 0.00024493329342768994, 'epoch': 0.44}

 44%|████▍     | 1583/3566 [1:03:52<1:18:10,  2.37s/it]
 44%|████▍     | 1584/3566 [1:03:54<1:16:14,  2.31s/it]
                                                       
{'loss': 1.5307, 'learning_rate': 0.00024475662870960516, 'epoch': 0.44}

 44%|████▍     | 1584/3566 [1:03:54<1:16:14,  2.31s/it]
 44%|████▍     | 1585/3566 [1:03:57<1:18:22,  2.37s/it]
                                                       
{'loss': 1.7258, 'learning_rate': 0.00024457992722098405, 'epoch': 0.44}

 44%|████▍     | 1585/3566 [1:03:57<1:18:22,  2.37s/it]
 44%|████▍     | 1586/3566 [1:03:59<1:18:11,  2.37s/it]
                                                       
{'loss': 1.5549, 'learning_rate': 0.0002444031891069986, 'epoch': 0.44}

 44%|████▍     | 1586/3566 [1:03:59<1:18:11,  2.37s/it]
 45%|████▍     | 1587/3566 [1:04:02<1:19:49,  2.42s/it]
                                                       
{'loss': 1.5448, 'learning_rate': 0.00024422641451285086, 'epoch': 0.45}

 45%|████▍     | 1587/3566 [1:04:02<1:19:49,  2.42s/it]
 45%|████▍     | 1588/3566 [1:04:04<1:20:44,  2.45s/it]
                                                       
{'loss': 1.6417, 'learning_rate': 0.00024404960358377284, 'epoch': 0.45}

 45%|████▍     | 1588/3566 [1:04:04<1:20:44,  2.45s/it]
 45%|████▍     | 1589/3566 [1:04:07<1:23:37,  2.54s/it]
                                                       
{'loss': 1.5272, 'learning_rate': 0.00024387275646502646, 'epoch': 0.45}

 45%|████▍     | 1589/3566 [1:04:07<1:23:37,  2.54s/it]
 45%|████▍     | 1590/3566 [1:04:09<1:20:57,  2.46s/it]
                                                       
{'loss': 1.6629, 'learning_rate': 0.00024369587330190325, 'epoch': 0.45}

 45%|████▍     | 1590/3566 [1:04:09<1:20:57,  2.46s/it]
 45%|████▍     | 1591/3566 [1:04:12<1:26:29,  2.63s/it]
                                                       
{'loss': 1.3826, 'learning_rate': 0.00024351895423972467, 'epoch': 0.45}

 45%|████▍     | 1591/3566 [1:04:12<1:26:29,  2.63s/it]
 45%|████▍     | 1592/3566 [1:04:15<1:25:57,  2.61s/it]
                                                       
{'loss': 1.4844, 'learning_rate': 0.0002433419994238413, 'epoch': 0.45}

 45%|████▍     | 1592/3566 [1:04:15<1:25:57,  2.61s/it]
 45%|████▍     | 1593/3566 [1:04:17<1:22:44,  2.52s/it]
                                                       
{'loss': 1.5749, 'learning_rate': 0.00024316500899963323, 'epoch': 0.45}

 45%|████▍     | 1593/3566 [1:04:17<1:22:44,  2.52s/it]
 45%|████▍     | 1594/3566 [1:04:20<1:22:19,  2.50s/it]
                                                       
{'loss': 1.4315, 'learning_rate': 0.00024298798311250987, 'epoch': 0.45}

 45%|████▍     | 1594/3566 [1:04:20<1:22:19,  2.50s/it]
 45%|████▍     | 1595/3566 [1:04:22<1:22:13,  2.50s/it]
                                                       
{'loss': 1.5369, 'learning_rate': 0.00024281092190790978, 'epoch': 0.45}

 45%|████▍     | 1595/3566 [1:04:22<1:22:13,  2.50s/it]
 45%|████▍     | 1596/3566 [1:04:25<1:21:44,  2.49s/it]
                                                       
{'loss': 1.5281, 'learning_rate': 0.0002426338255313004, 'epoch': 0.45}

 45%|████▍     | 1596/3566 [1:04:25<1:21:44,  2.49s/it]
 45%|████▍     | 1597/3566 [1:04:27<1:21:31,  2.48s/it]
                                                       
{'loss': 1.4906, 'learning_rate': 0.0002424566941281781, 'epoch': 0.45}

 45%|████▍     | 1597/3566 [1:04:27<1:21:31,  2.48s/it]
 45%|████▍     | 1598/3566 [1:04:30<1:24:04,  2.56s/it]
                                                       
{'loss': 1.5724, 'learning_rate': 0.00024227952784406807, 'epoch': 0.45}

 45%|████▍     | 1598/3566 [1:04:30<1:24:04,  2.56s/it]
 45%|████▍     | 1599/3566 [1:04:32<1:22:54,  2.53s/it]
                                                       
{'loss': 1.6224, 'learning_rate': 0.00024210232682452424, 'epoch': 0.45}

 45%|████▍     | 1599/3566 [1:04:32<1:22:54,  2.53s/it]
 45%|████▍     | 1600/3566 [1:04:35<1:19:50,  2.44s/it]
                                                       
{'loss': 1.6724, 'learning_rate': 0.000241925091215129, 'epoch': 0.45}

 45%|████▍     | 1600/3566 [1:04:35<1:19:50,  2.44s/it]
 45%|████▍     | 1601/3566 [1:04:37<1:18:04,  2.38s/it]
                                                       
{'loss': 1.5638, 'learning_rate': 0.00024174782116149303, 'epoch': 0.45}

 45%|████▍     | 1601/3566 [1:04:37<1:18:04,  2.38s/it]
 45%|████▍     | 1602/3566 [1:04:39<1:17:26,  2.37s/it]
                                                       
{'loss': 1.5348, 'learning_rate': 0.0002415705168092555, 'epoch': 0.45}

 45%|████▍     | 1602/3566 [1:04:39<1:17:26,  2.37s/it]
 45%|████▍     | 1603/3566 [1:04:42<1:17:48,  2.38s/it]
                                                       
{'loss': 1.5205, 'learning_rate': 0.00024139317830408367, 'epoch': 0.45}

 45%|████▍     | 1603/3566 [1:04:42<1:17:48,  2.38s/it]
 45%|████▍     | 1604/3566 [1:04:44<1:19:42,  2.44s/it]
                                                       
{'loss': 1.5838, 'learning_rate': 0.00024121580579167292, 'epoch': 0.45}

 45%|████▍     | 1604/3566 [1:04:44<1:19:42,  2.44s/it]
 45%|████▌     | 1605/3566 [1:04:47<1:20:40,  2.47s/it]
                                                       
{'loss': 1.4553, 'learning_rate': 0.0002410383994177464, 'epoch': 0.45}

 45%|████▌     | 1605/3566 [1:04:47<1:20:40,  2.47s/it]
 45%|████▌     | 1606/3566 [1:04:49<1:20:22,  2.46s/it]
                                                       
{'loss': 1.561, 'learning_rate': 0.00024086095932805536, 'epoch': 0.45}

 45%|████▌     | 1606/3566 [1:04:49<1:20:22,  2.46s/it]
 45%|████▌     | 1607/3566 [1:04:52<1:19:21,  2.43s/it]
                                                       
{'loss': 1.4977, 'learning_rate': 0.00024068348566837845, 'epoch': 0.45}

 45%|████▌     | 1607/3566 [1:04:52<1:19:21,  2.43s/it]
 45%|████▌     | 1608/3566 [1:04:54<1:19:06,  2.42s/it]
                                                       
{'loss': 1.5353, 'learning_rate': 0.00024050597858452216, 'epoch': 0.45}

 45%|████▌     | 1608/3566 [1:04:54<1:19:06,  2.42s/it]
 45%|████▌     | 1609/3566 [1:04:56<1:18:33,  2.41s/it]
                                                       
{'loss': 1.371, 'learning_rate': 0.00024032843822232024, 'epoch': 0.45}

 45%|████▌     | 1609/3566 [1:04:56<1:18:33,  2.41s/it]
 45%|████▌     | 1610/3566 [1:04:59<1:16:28,  2.35s/it]
                                                       
{'loss': 1.576, 'learning_rate': 0.0002401508647276339, 'epoch': 0.45}

 45%|████▌     | 1610/3566 [1:04:59<1:16:28,  2.35s/it]
 45%|████▌     | 1611/3566 [1:05:01<1:15:54,  2.33s/it]
                                                       
{'loss': 1.5715, 'learning_rate': 0.0002399732582463515, 'epoch': 0.45}

 45%|████▌     | 1611/3566 [1:05:01<1:15:54,  2.33s/it]
 45%|████▌     | 1612/3566 [1:05:03<1:17:21,  2.38s/it]
                                                       
{'loss': 1.6734, 'learning_rate': 0.00023979561892438858, 'epoch': 0.45}

 45%|████▌     | 1612/3566 [1:05:03<1:17:21,  2.38s/it]
 45%|████▌     | 1613/3566 [1:05:06<1:18:13,  2.40s/it]
                                                       
{'loss': 1.6044, 'learning_rate': 0.00023961794690768756, 'epoch': 0.45}

 45%|████▌     | 1613/3566 [1:05:06<1:18:13,  2.40s/it]
 45%|████▌     | 1614/3566 [1:05:08<1:18:21,  2.41s/it]
                                                       
{'loss': 1.4774, 'learning_rate': 0.00023944024234221788, 'epoch': 0.45}

 45%|████▌     | 1614/3566 [1:05:08<1:18:21,  2.41s/it]
 45%|████▌     | 1615/3566 [1:05:10<1:17:14,  2.38s/it]
                                                       
{'loss': 1.5756, 'learning_rate': 0.00023926250537397548, 'epoch': 0.45}

 45%|████▌     | 1615/3566 [1:05:10<1:17:14,  2.38s/it]
 45%|████▌     | 1616/3566 [1:05:13<1:17:13,  2.38s/it]
                                                       
{'loss': 1.6889, 'learning_rate': 0.0002390847361489831, 'epoch': 0.45}

 45%|████▌     | 1616/3566 [1:05:13<1:17:13,  2.38s/it]
 45%|████▌     | 1617/3566 [1:05:15<1:15:57,  2.34s/it]
                                                       
{'loss': 1.7233, 'learning_rate': 0.00023890693481329006, 'epoch': 0.45}

 45%|████▌     | 1617/3566 [1:05:15<1:15:57,  2.34s/it]
 45%|████▌     | 1618/3566 [1:05:17<1:15:58,  2.34s/it]
                                                       
{'loss': 1.4928, 'learning_rate': 0.0002387291015129718, 'epoch': 0.45}

 45%|████▌     | 1618/3566 [1:05:17<1:15:58,  2.34s/it]
 45%|████▌     | 1619/3566 [1:05:20<1:17:48,  2.40s/it]
                                                       
{'loss': 1.6063, 'learning_rate': 0.00023855123639413011, 'epoch': 0.45}

 45%|████▌     | 1619/3566 [1:05:20<1:17:48,  2.40s/it]
 45%|████▌     | 1620/3566 [1:05:22<1:17:08,  2.38s/it]
                                                       
{'loss': 1.5051, 'learning_rate': 0.0002383733396028931, 'epoch': 0.45}

 45%|████▌     | 1620/3566 [1:05:22<1:17:08,  2.38s/it]
 45%|████▌     | 1621/3566 [1:05:24<1:15:17,  2.32s/it]
                                                       
{'loss': 1.6827, 'learning_rate': 0.00023819541128541482, 'epoch': 0.45}

 45%|████▌     | 1621/3566 [1:05:25<1:15:17,  2.32s/it]
 45%|████▌     | 1622/3566 [1:05:27<1:13:09,  2.26s/it]
                                                       
{'loss': 1.5971, 'learning_rate': 0.00023801745158787504, 'epoch': 0.45}

 45%|████▌     | 1622/3566 [1:05:27<1:13:09,  2.26s/it]
 46%|████▌     | 1623/3566 [1:05:30<1:19:50,  2.47s/it]
                                                       
{'loss': 1.4289, 'learning_rate': 0.00023783946065647946, 'epoch': 0.46}

 46%|████▌     | 1623/3566 [1:05:30<1:19:50,  2.47s/it]
 46%|████▌     | 1624/3566 [1:05:32<1:18:45,  2.43s/it]
                                                       
{'loss': 1.7191, 'learning_rate': 0.00023766143863745946, 'epoch': 0.46}

 46%|████▌     | 1624/3566 [1:05:32<1:18:45,  2.43s/it]
 46%|████▌     | 1625/3566 [1:05:35<1:22:57,  2.56s/it]
                                                       
{'loss': 1.4261, 'learning_rate': 0.00023748338567707196, 'epoch': 0.46}

 46%|████▌     | 1625/3566 [1:05:35<1:22:57,  2.56s/it]
 46%|████▌     | 1626/3566 [1:05:37<1:22:03,  2.54s/it]
                                                       
{'loss': 1.5713, 'learning_rate': 0.0002373053019215992, 'epoch': 0.46}

 46%|████▌     | 1626/3566 [1:05:37<1:22:03,  2.54s/it]
 46%|████▌     | 1627/3566 [1:05:40<1:22:33,  2.55s/it]
                                                       
{'loss': 1.5689, 'learning_rate': 0.00023712718751734882, 'epoch': 0.46}

 46%|████▌     | 1627/3566 [1:05:40<1:22:33,  2.55s/it]
 46%|████▌     | 1628/3566 [1:05:42<1:19:31,  2.46s/it]
                                                       
{'loss': 1.5209, 'learning_rate': 0.00023694904261065364, 'epoch': 0.46}

 46%|████▌     | 1628/3566 [1:05:42<1:19:31,  2.46s/it]
 46%|████▌     | 1629/3566 [1:05:44<1:18:01,  2.42s/it]
                                                       
{'loss': 1.4496, 'learning_rate': 0.00023677086734787142, 'epoch': 0.46}

 46%|████▌     | 1629/3566 [1:05:44<1:18:01,  2.42s/it]
 46%|████▌     | 1630/3566 [1:05:47<1:18:59,  2.45s/it]
                                                       
{'loss': 1.4943, 'learning_rate': 0.00023659266187538505, 'epoch': 0.46}

 46%|████▌     | 1630/3566 [1:05:47<1:18:59,  2.45s/it]
 46%|████▌     | 1631/3566 [1:05:49<1:19:50,  2.48s/it]
                                                       
{'loss': 1.5836, 'learning_rate': 0.00023641442633960203, 'epoch': 0.46}

 46%|████▌     | 1631/3566 [1:05:49<1:19:50,  2.48s/it]
 46%|████▌     | 1632/3566 [1:05:52<1:19:58,  2.48s/it]
                                                       
{'loss': 1.686, 'learning_rate': 0.00023623616088695468, 'epoch': 0.46}

 46%|████▌     | 1632/3566 [1:05:52<1:19:58,  2.48s/it]
 46%|████▌     | 1633/3566 [1:05:54<1:17:48,  2.42s/it]
                                                       
{'loss': 1.4795, 'learning_rate': 0.0002360578656638999, 'epoch': 0.46}

 46%|████▌     | 1633/3566 [1:05:54<1:17:48,  2.42s/it]
 46%|████▌     | 1634/3566 [1:05:57<1:17:31,  2.41s/it]
                                                       
{'loss': 1.6373, 'learning_rate': 0.00023587954081691917, 'epoch': 0.46}

 46%|████▌     | 1634/3566 [1:05:57<1:17:31,  2.41s/it]
 46%|████▌     | 1635/3566 [1:05:59<1:17:19,  2.40s/it]
                                                       
{'loss': 1.4847, 'learning_rate': 0.00023570118649251796, 'epoch': 0.46}

 46%|████▌     | 1635/3566 [1:05:59<1:17:19,  2.40s/it]
 46%|████▌     | 1636/3566 [1:06:01<1:15:31,  2.35s/it]
                                                       
{'loss': 1.6384, 'learning_rate': 0.00023552280283722622, 'epoch': 0.46}

 46%|████▌     | 1636/3566 [1:06:01<1:15:31,  2.35s/it]
 46%|████▌     | 1637/3566 [1:06:03<1:14:22,  2.31s/it]
                                                       
{'loss': 1.5915, 'learning_rate': 0.000235344389997598, 'epoch': 0.46}

 46%|████▌     | 1637/3566 [1:06:03<1:14:22,  2.31s/it]
 46%|████▌     | 1638/3566 [1:06:06<1:15:51,  2.36s/it]
                                                       
{'loss': 1.5623, 'learning_rate': 0.00023516594812021126, 'epoch': 0.46}

 46%|████▌     | 1638/3566 [1:06:06<1:15:51,  2.36s/it]
 46%|████▌     | 1639/3566 [1:06:08<1:14:57,  2.33s/it]
                                                       
{'loss': 1.4261, 'learning_rate': 0.00023498747735166783, 'epoch': 0.46}

 46%|████▌     | 1639/3566 [1:06:08<1:14:57,  2.33s/it]
 46%|████▌     | 1640/3566 [1:06:11<1:16:11,  2.37s/it]
                                                       
{'loss': 1.7279, 'learning_rate': 0.00023480897783859317, 'epoch': 0.46}

 46%|████▌     | 1640/3566 [1:06:11<1:16:11,  2.37s/it]
 46%|████▌     | 1641/3566 [1:06:13<1:15:58,  2.37s/it]
                                                       
{'loss': 1.4415, 'learning_rate': 0.00023463044972763658, 'epoch': 0.46}

 46%|████▌     | 1641/3566 [1:06:13<1:15:58,  2.37s/it]
 46%|████▌     | 1642/3566 [1:06:15<1:16:27,  2.38s/it]
                                                       
{'loss': 1.6595, 'learning_rate': 0.00023445189316547072, 'epoch': 0.46}

 46%|████▌     | 1642/3566 [1:06:15<1:16:27,  2.38s/it]
 46%|████▌     | 1643/3566 [1:06:18<1:17:00,  2.40s/it]
                                                       
{'loss': 1.4856, 'learning_rate': 0.00023427330829879167, 'epoch': 0.46}

 46%|████▌     | 1643/3566 [1:06:18<1:17:00,  2.40s/it]
 46%|████▌     | 1644/3566 [1:06:20<1:16:02,  2.37s/it]
                                                       
{'loss': 1.5011, 'learning_rate': 0.00023409469527431855, 'epoch': 0.46}

 46%|████▌     | 1644/3566 [1:06:20<1:16:02,  2.37s/it]
 46%|████▌     | 1645/3566 [1:06:23<1:22:54,  2.59s/it]
                                                       
{'loss': 1.5571, 'learning_rate': 0.000233916054238794, 'epoch': 0.46}

 46%|████▌     | 1645/3566 [1:06:23<1:22:54,  2.59s/it]
 46%|████▌     | 1646/3566 [1:06:26<1:19:32,  2.49s/it]
                                                       
{'loss': 1.4625, 'learning_rate': 0.0002337373853389834, 'epoch': 0.46}

 46%|████▌     | 1646/3566 [1:06:26<1:19:32,  2.49s/it]
 46%|████▌     | 1647/3566 [1:06:28<1:19:32,  2.49s/it]
                                                       
{'loss': 1.5243, 'learning_rate': 0.00023355868872167502, 'epoch': 0.46}

 46%|████▌     | 1647/3566 [1:06:28<1:19:32,  2.49s/it]
 46%|████▌     | 1648/3566 [1:06:30<1:17:05,  2.41s/it]
                                                       
{'loss': 1.5997, 'learning_rate': 0.00023337996453368006, 'epoch': 0.46}

 46%|████▌     | 1648/3566 [1:06:30<1:17:05,  2.41s/it]
 46%|████▌     | 1649/3566 [1:06:32<1:15:24,  2.36s/it]
                                                       
{'loss': 1.5089, 'learning_rate': 0.00023320121292183226, 'epoch': 0.46}

 46%|████▌     | 1649/3566 [1:06:33<1:15:24,  2.36s/it]
 46%|████▋     | 1650/3566 [1:06:35<1:14:07,  2.32s/it]
                                                       
{'loss': 1.5961, 'learning_rate': 0.00023302243403298793, 'epoch': 0.46}

 46%|████▋     | 1650/3566 [1:06:35<1:14:07,  2.32s/it]
 46%|████▋     | 1651/3566 [1:06:37<1:13:46,  2.31s/it]
                                                       
{'loss': 1.5106, 'learning_rate': 0.00023284362801402576, 'epoch': 0.46}

 46%|████▋     | 1651/3566 [1:06:37<1:13:46,  2.31s/it]
 46%|████▋     | 1652/3566 [1:06:39<1:14:08,  2.32s/it]
                                                       
{'loss': 1.5099, 'learning_rate': 0.0002326647950118467, 'epoch': 0.46}

 46%|████▋     | 1652/3566 [1:06:39<1:14:08,  2.32s/it]
 46%|████▋     | 1653/3566 [1:06:42<1:15:06,  2.36s/it]
                                                       
{'loss': 1.4402, 'learning_rate': 0.000232485935173374, 'epoch': 0.46}

 46%|████▋     | 1653/3566 [1:06:42<1:15:06,  2.36s/it]
 46%|████▋     | 1654/3566 [1:06:44<1:14:43,  2.35s/it]
                                                       
{'loss': 1.4325, 'learning_rate': 0.00023230704864555274, 'epoch': 0.46}

 46%|████▋     | 1654/3566 [1:06:44<1:14:43,  2.35s/it]
 46%|████▋     | 1655/3566 [1:06:46<1:13:36,  2.31s/it]
                                                       
{'loss': 1.4983, 'learning_rate': 0.00023212813557535022, 'epoch': 0.46}

 46%|████▋     | 1655/3566 [1:06:46<1:13:36,  2.31s/it]
 46%|████▋     | 1656/3566 [1:06:49<1:13:58,  2.32s/it]
                                                       
{'loss': 1.6445, 'learning_rate': 0.0002319491961097553, 'epoch': 0.46}

 46%|████▋     | 1656/3566 [1:06:49<1:13:58,  2.32s/it]
 46%|████▋     | 1657/3566 [1:06:51<1:13:27,  2.31s/it]
                                                       
{'loss': 1.3986, 'learning_rate': 0.00023177023039577859, 'epoch': 0.46}

 46%|████▋     | 1657/3566 [1:06:51<1:13:27,  2.31s/it]
 46%|████▋     | 1658/3566 [1:06:53<1:13:20,  2.31s/it]
                                                       
{'loss': 1.6527, 'learning_rate': 0.00023159123858045225, 'epoch': 0.46}

 46%|████▋     | 1658/3566 [1:06:53<1:13:20,  2.31s/it]
 47%|████▋     | 1659/3566 [1:06:56<1:14:39,  2.35s/it]
                                                       
{'loss': 1.7511, 'learning_rate': 0.00023141222081083003, 'epoch': 0.47}

 47%|████▋     | 1659/3566 [1:06:56<1:14:39,  2.35s/it]
 47%|████▋     | 1660/3566 [1:06:58<1:16:11,  2.40s/it]
                                                       
{'loss': 1.5593, 'learning_rate': 0.00023123317723398689, 'epoch': 0.47}

 47%|████▋     | 1660/3566 [1:06:58<1:16:11,  2.40s/it]
 47%|████▋     | 1661/3566 [1:07:01<1:17:56,  2.45s/it]
                                                       
{'loss': 1.5734, 'learning_rate': 0.0002310541079970188, 'epoch': 0.47}

 47%|████▋     | 1661/3566 [1:07:01<1:17:56,  2.45s/it]
 47%|████▋     | 1662/3566 [1:07:03<1:15:24,  2.38s/it]
                                                       
{'loss': 1.5429, 'learning_rate': 0.00023087501324704318, 'epoch': 0.47}

 47%|████▋     | 1662/3566 [1:07:03<1:15:24,  2.38s/it]
 47%|████▋     | 1663/3566 [1:07:06<1:16:59,  2.43s/it]
                                                       
{'loss': 1.6887, 'learning_rate': 0.00023069589313119826, 'epoch': 0.47}

 47%|████▋     | 1663/3566 [1:07:06<1:16:59,  2.43s/it]
 47%|████▋     | 1664/3566 [1:07:08<1:19:51,  2.52s/it]
                                                       
{'loss': 1.6576, 'learning_rate': 0.000230516747796643, 'epoch': 0.47}

 47%|████▋     | 1664/3566 [1:07:08<1:19:51,  2.52s/it]
 47%|████▋     | 1665/3566 [1:07:11<1:18:57,  2.49s/it]
                                                       
{'loss': 1.79, 'learning_rate': 0.00023033757739055716, 'epoch': 0.47}

 47%|████▋     | 1665/3566 [1:07:11<1:18:57,  2.49s/it]
 47%|████▋     | 1666/3566 [1:07:13<1:18:28,  2.48s/it]
                                                       
{'loss': 1.5351, 'learning_rate': 0.00023015838206014112, 'epoch': 0.47}

 47%|████▋     | 1666/3566 [1:07:13<1:18:28,  2.48s/it]
 47%|████▋     | 1667/3566 [1:07:16<1:17:43,  2.46s/it]
                                                       
{'loss': 1.7071, 'learning_rate': 0.00022997916195261576, 'epoch': 0.47}

 47%|████▋     | 1667/3566 [1:07:16<1:17:43,  2.46s/it]
 47%|████▋     | 1668/3566 [1:07:18<1:18:37,  2.49s/it]
                                                       
{'loss': 1.4834, 'learning_rate': 0.0002297999172152222, 'epoch': 0.47}

 47%|████▋     | 1668/3566 [1:07:18<1:18:37,  2.49s/it]
 47%|████▋     | 1669/3566 [1:07:21<1:18:50,  2.49s/it]
                                                       
{'loss': 1.5708, 'learning_rate': 0.00022962064799522192, 'epoch': 0.47}

 47%|████▋     | 1669/3566 [1:07:21<1:18:50,  2.49s/it]
 47%|████▋     | 1670/3566 [1:07:23<1:20:19,  2.54s/it]
                                                       
{'loss': 1.4445, 'learning_rate': 0.00022944135443989642, 'epoch': 0.47}

 47%|████▋     | 1670/3566 [1:07:23<1:20:19,  2.54s/it]
 47%|████▋     | 1671/3566 [1:07:26<1:18:10,  2.48s/it]
                                                       
{'loss': 1.5581, 'learning_rate': 0.00022926203669654732, 'epoch': 0.47}

 47%|████▋     | 1671/3566 [1:07:26<1:18:10,  2.48s/it]
 47%|████▋     | 1672/3566 [1:07:28<1:16:28,  2.42s/it]
                                                       
{'loss': 1.6432, 'learning_rate': 0.00022908269491249593, 'epoch': 0.47}

 47%|████▋     | 1672/3566 [1:07:28<1:16:28,  2.42s/it]
 47%|████▋     | 1673/3566 [1:07:31<1:21:17,  2.58s/it]
                                                       
{'loss': 1.5703, 'learning_rate': 0.0002289033292350835, 'epoch': 0.47}

 47%|████▋     | 1673/3566 [1:07:31<1:21:17,  2.58s/it]
 47%|████▋     | 1674/3566 [1:07:33<1:18:11,  2.48s/it]
                                                       
{'loss': 1.5786, 'learning_rate': 0.00022872393981167077, 'epoch': 0.47}

 47%|████▋     | 1674/3566 [1:07:33<1:18:11,  2.48s/it]
 47%|████▋     | 1675/3566 [1:07:36<1:20:40,  2.56s/it]
                                                       
{'loss': 1.5684, 'learning_rate': 0.000228544526789638, 'epoch': 0.47}

 47%|████▋     | 1675/3566 [1:07:36<1:20:40,  2.56s/it]
 47%|████▋     | 1676/3566 [1:07:38<1:17:03,  2.45s/it]
                                                       
{'loss': 1.5308, 'learning_rate': 0.00022836509031638495, 'epoch': 0.47}

 47%|████▋     | 1676/3566 [1:07:38<1:17:03,  2.45s/it]
 47%|████▋     | 1677/3566 [1:07:41<1:18:49,  2.50s/it]
                                                       
{'loss': 1.7682, 'learning_rate': 0.00022818563053933057, 'epoch': 0.47}

 47%|████▋     | 1677/3566 [1:07:41<1:18:49,  2.50s/it]
 47%|████▋     | 1678/3566 [1:07:43<1:17:34,  2.47s/it]
                                                       
{'loss': 1.4572, 'learning_rate': 0.00022800614760591295, 'epoch': 0.47}

 47%|████▋     | 1678/3566 [1:07:43<1:17:34,  2.47s/it]
 47%|████▋     | 1679/3566 [1:07:45<1:15:35,  2.40s/it]
                                                       
{'loss': 1.5774, 'learning_rate': 0.00022782664166358916, 'epoch': 0.47}

 47%|████▋     | 1679/3566 [1:07:45<1:15:35,  2.40s/it]
 47%|████▋     | 1680/3566 [1:07:48<1:21:47,  2.60s/it]
                                                       
{'loss': 1.5223, 'learning_rate': 0.00022764711285983523, 'epoch': 0.47}

 47%|████▋     | 1680/3566 [1:07:48<1:21:47,  2.60s/it]
 47%|████▋     | 1681/3566 [1:07:51<1:19:27,  2.53s/it]
                                                       
{'loss': 1.677, 'learning_rate': 0.00022746756134214607, 'epoch': 0.47}

 47%|████▋     | 1681/3566 [1:07:51<1:19:27,  2.53s/it]
 47%|████▋     | 1682/3566 [1:07:53<1:18:05,  2.49s/it]
                                                       
{'loss': 1.5746, 'learning_rate': 0.00022728798725803504, 'epoch': 0.47}

 47%|████▋     | 1682/3566 [1:07:53<1:18:05,  2.49s/it]
 47%|████▋     | 1683/3566 [1:07:56<1:17:30,  2.47s/it]
                                                       
{'loss': 1.5622, 'learning_rate': 0.00022710839075503421, 'epoch': 0.47}

 47%|████▋     | 1683/3566 [1:07:56<1:17:30,  2.47s/it]
 47%|████▋     | 1684/3566 [1:07:58<1:17:47,  2.48s/it]
                                                       
{'loss': 1.5781, 'learning_rate': 0.00022692877198069402, 'epoch': 0.47}

 47%|████▋     | 1684/3566 [1:07:58<1:17:47,  2.48s/it]
 47%|████▋     | 1685/3566 [1:08:00<1:14:47,  2.39s/it]
                                                       
{'loss': 1.5514, 'learning_rate': 0.00022674913108258315, 'epoch': 0.47}

 47%|████▋     | 1685/3566 [1:08:00<1:14:47,  2.39s/it]
 47%|████▋     | 1686/3566 [1:08:03<1:16:20,  2.44s/it]
                                                       
{'loss': 1.426, 'learning_rate': 0.00022656946820828852, 'epoch': 0.47}

 47%|████▋     | 1686/3566 [1:08:03<1:16:20,  2.44s/it]
 47%|████▋     | 1687/3566 [1:08:05<1:15:07,  2.40s/it]
                                                       
{'loss': 1.65, 'learning_rate': 0.00022638978350541508, 'epoch': 0.47}

 47%|████▋     | 1687/3566 [1:08:05<1:15:07,  2.40s/it]
 47%|████▋     | 1688/3566 [1:08:08<1:15:22,  2.41s/it]
                                                       
{'loss': 1.7149, 'learning_rate': 0.00022621007712158577, 'epoch': 0.47}

 47%|████▋     | 1688/3566 [1:08:08<1:15:22,  2.41s/it]
 47%|████▋     | 1689/3566 [1:08:10<1:13:33,  2.35s/it]
                                                       
{'loss': 1.6595, 'learning_rate': 0.0002260303492044412, 'epoch': 0.47}

 47%|████▋     | 1689/3566 [1:08:10<1:13:33,  2.35s/it]
 47%|████▋     | 1690/3566 [1:08:12<1:14:30,  2.38s/it]
                                                       
{'loss': 1.6742, 'learning_rate': 0.00022585059990163983, 'epoch': 0.47}

 47%|████▋     | 1690/3566 [1:08:12<1:14:30,  2.38s/it]
 47%|████▋     | 1691/3566 [1:08:14<1:13:02,  2.34s/it]
                                                       
{'loss': 1.6686, 'learning_rate': 0.0002256708293608576, 'epoch': 0.47}

 47%|████▋     | 1691/3566 [1:08:14<1:13:02,  2.34s/it]
 47%|████▋     | 1692/3566 [1:08:17<1:14:30,  2.39s/it]
                                                       
{'loss': 1.4319, 'learning_rate': 0.00022549103772978794, 'epoch': 0.47}

 47%|████▋     | 1692/3566 [1:08:17<1:14:30,  2.39s/it]
 47%|████▋     | 1693/3566 [1:08:20<1:16:24,  2.45s/it]
                                                       
{'loss': 1.6116, 'learning_rate': 0.00022531122515614155, 'epoch': 0.47}

 47%|████▋     | 1693/3566 [1:08:20<1:16:24,  2.45s/it]
 48%|████▊     | 1694/3566 [1:08:22<1:15:13,  2.41s/it]
                                                       
{'loss': 1.3789, 'learning_rate': 0.00022513139178764648, 'epoch': 0.48}

 48%|████▊     | 1694/3566 [1:08:22<1:15:13,  2.41s/it]
 48%|████▊     | 1695/3566 [1:08:24<1:15:06,  2.41s/it]
                                                       
{'loss': 1.4669, 'learning_rate': 0.00022495153777204766, 'epoch': 0.48}

 48%|████▊     | 1695/3566 [1:08:24<1:15:06,  2.41s/it]
 48%|████▊     | 1696/3566 [1:08:27<1:13:41,  2.36s/it]
                                                       
{'loss': 1.6649, 'learning_rate': 0.00022477166325710703, 'epoch': 0.48}

 48%|████▊     | 1696/3566 [1:08:27<1:13:41,  2.36s/it]
 48%|████▊     | 1697/3566 [1:08:29<1:13:25,  2.36s/it]
                                                       
{'loss': 1.6541, 'learning_rate': 0.00022459176839060354, 'epoch': 0.48}

 48%|████▊     | 1697/3566 [1:08:29<1:13:25,  2.36s/it]
 48%|████▊     | 1698/3566 [1:08:31<1:11:14,  2.29s/it]
                                                       
{'loss': 1.671, 'learning_rate': 0.00022441185332033276, 'epoch': 0.48}

 48%|████▊     | 1698/3566 [1:08:31<1:11:14,  2.29s/it]
 48%|████▊     | 1699/3566 [1:08:33<1:11:08,  2.29s/it]
                                                       
{'loss': 1.5792, 'learning_rate': 0.00022423191819410674, 'epoch': 0.48}

 48%|████▊     | 1699/3566 [1:08:33<1:11:08,  2.29s/it]
 48%|████▊     | 1700/3566 [1:08:36<1:13:17,  2.36s/it]
                                                       
{'loss': 1.3773, 'learning_rate': 0.00022405196315975414, 'epoch': 0.48}

 48%|████▊     | 1700/3566 [1:08:36<1:13:17,  2.36s/it]
 48%|████▊     | 1701/3566 [1:08:38<1:13:38,  2.37s/it]
                                                       
{'loss': 1.3891, 'learning_rate': 0.00022387198836512, 'epoch': 0.48}

 48%|████▊     | 1701/3566 [1:08:38<1:13:38,  2.37s/it]
 48%|████▊     | 1702/3566 [1:08:41<1:13:22,  2.36s/it]
                                                       
{'loss': 1.4892, 'learning_rate': 0.00022369199395806547, 'epoch': 0.48}

 48%|████▊     | 1702/3566 [1:08:41<1:13:22,  2.36s/it]
 48%|████▊     | 1703/3566 [1:08:43<1:13:38,  2.37s/it]
                                                       
{'loss': 1.4984, 'learning_rate': 0.00022351198008646792, 'epoch': 0.48}

 48%|████▊     | 1703/3566 [1:08:43<1:13:38,  2.37s/it]
 48%|████▊     | 1704/3566 [1:08:45<1:14:33,  2.40s/it]
                                                       
{'loss': 1.6368, 'learning_rate': 0.00022333194689822067, 'epoch': 0.48}

 48%|████▊     | 1704/3566 [1:08:45<1:14:33,  2.40s/it]
 48%|████▊     | 1705/3566 [1:08:48<1:13:35,  2.37s/it]
                                                       
{'loss': 1.4427, 'learning_rate': 0.00022315189454123294, 'epoch': 0.48}

 48%|████▊     | 1705/3566 [1:08:48<1:13:35,  2.37s/it]
 48%|████▊     | 1706/3566 [1:08:50<1:12:53,  2.35s/it]
                                                       
{'loss': 1.5146, 'learning_rate': 0.0002229718231634296, 'epoch': 0.48}

 48%|████▊     | 1706/3566 [1:08:50<1:12:53,  2.35s/it]
 48%|████▊     | 1707/3566 [1:08:52<1:12:08,  2.33s/it]
                                                       
{'loss': 1.4817, 'learning_rate': 0.00022279173291275134, 'epoch': 0.48}

 48%|████▊     | 1707/3566 [1:08:52<1:12:08,  2.33s/it]
 48%|████▊     | 1708/3566 [1:08:54<1:11:03,  2.29s/it]
                                                       
{'loss': 1.5236, 'learning_rate': 0.0002226116239371541, 'epoch': 0.48}

 48%|████▊     | 1708/3566 [1:08:54<1:11:03,  2.29s/it]
 48%|████▊     | 1709/3566 [1:08:57<1:10:15,  2.27s/it]
                                                       
{'loss': 1.3901, 'learning_rate': 0.00022243149638460943, 'epoch': 0.48}

 48%|████▊     | 1709/3566 [1:08:57<1:10:15,  2.27s/it]
 48%|████▊     | 1710/3566 [1:08:59<1:13:02,  2.36s/it]
                                                       
{'loss': 1.5693, 'learning_rate': 0.00022225135040310394, 'epoch': 0.48}

 48%|████▊     | 1710/3566 [1:08:59<1:13:02,  2.36s/it]
 48%|████▊     | 1711/3566 [1:09:02<1:11:56,  2.33s/it]
                                                       
{'loss': 1.4913, 'learning_rate': 0.00022207118614063967, 'epoch': 0.48}

 48%|████▊     | 1711/3566 [1:09:02<1:11:56,  2.33s/it]
 48%|████▊     | 1712/3566 [1:09:04<1:11:32,  2.32s/it]
                                                       
{'loss': 1.5038, 'learning_rate': 0.0002218910037452334, 'epoch': 0.48}

 48%|████▊     | 1712/3566 [1:09:04<1:11:32,  2.32s/it]
 48%|████▊     | 1713/3566 [1:09:06<1:12:00,  2.33s/it]
                                                       
{'loss': 1.5641, 'learning_rate': 0.00022171080336491684, 'epoch': 0.48}

 48%|████▊     | 1713/3566 [1:09:06<1:12:00,  2.33s/it]
 48%|████▊     | 1714/3566 [1:09:09<1:14:11,  2.40s/it]
                                                       
{'loss': 1.5131, 'learning_rate': 0.0002215305851477367, 'epoch': 0.48}

 48%|████▊     | 1714/3566 [1:09:09<1:14:11,  2.40s/it]
 48%|████▊     | 1715/3566 [1:09:11<1:11:57,  2.33s/it]
                                                       
{'loss': 1.4212, 'learning_rate': 0.000221350349241754, 'epoch': 0.48}

 48%|████▊     | 1715/3566 [1:09:11<1:11:57,  2.33s/it]
 48%|████▊     | 1716/3566 [1:09:13<1:11:12,  2.31s/it]
                                                       
{'loss': 1.5201, 'learning_rate': 0.00022117009579504467, 'epoch': 0.48}

 48%|████▊     | 1716/3566 [1:09:13<1:11:12,  2.31s/it]
 48%|████▊     | 1717/3566 [1:09:15<1:10:02,  2.27s/it]
                                                       
{'loss': 1.4989, 'learning_rate': 0.00022098982495569872, 'epoch': 0.48}

 48%|████▊     | 1717/3566 [1:09:15<1:10:02,  2.27s/it]
 48%|████▊     | 1718/3566 [1:09:18<1:11:11,  2.31s/it]
                                                       
{'loss': 1.4331, 'learning_rate': 0.00022080953687182063, 'epoch': 0.48}

 48%|████▊     | 1718/3566 [1:09:18<1:11:11,  2.31s/it]
 48%|████▊     | 1719/3566 [1:09:20<1:09:18,  2.25s/it]
                                                       
{'loss': 1.4991, 'learning_rate': 0.00022062923169152904, 'epoch': 0.48}

 48%|████▊     | 1719/3566 [1:09:20<1:09:18,  2.25s/it]
 48%|████▊     | 1720/3566 [1:09:22<1:11:19,  2.32s/it]
                                                       
{'loss': 1.5306, 'learning_rate': 0.00022044890956295668, 'epoch': 0.48}

 48%|████▊     | 1720/3566 [1:09:22<1:11:19,  2.32s/it]
 48%|████▊     | 1721/3566 [1:09:25<1:13:41,  2.40s/it]
                                                       
{'loss': 1.3076, 'learning_rate': 0.00022026857063424995, 'epoch': 0.48}

 48%|████▊     | 1721/3566 [1:09:25<1:13:41,  2.40s/it]
 48%|████▊     | 1722/3566 [1:09:27<1:14:30,  2.42s/it]
                                                       
{'loss': 1.4638, 'learning_rate': 0.00022008821505356928, 'epoch': 0.48}

 48%|████▊     | 1722/3566 [1:09:27<1:14:30,  2.42s/it]
 48%|████▊     | 1723/3566 [1:09:30<1:12:52,  2.37s/it]
                                                       
{'loss': 1.5505, 'learning_rate': 0.00021990784296908883, 'epoch': 0.48}

 48%|████▊     | 1723/3566 [1:09:30<1:12:52,  2.37s/it]
 48%|████▊     | 1724/3566 [1:09:32<1:16:18,  2.49s/it]
                                                       
{'loss': 1.7054, 'learning_rate': 0.0002197274545289961, 'epoch': 0.48}

 48%|████▊     | 1724/3566 [1:09:32<1:16:18,  2.49s/it]
 48%|████▊     | 1725/3566 [1:09:35<1:14:02,  2.41s/it]
                                                       
{'loss': 1.4317, 'learning_rate': 0.00021954704988149225, 'epoch': 0.48}

 48%|████▊     | 1725/3566 [1:09:35<1:14:02,  2.41s/it]
 48%|████▊     | 1726/3566 [1:09:37<1:12:59,  2.38s/it]
                                                       
{'loss': 1.6565, 'learning_rate': 0.00021936662917479156, 'epoch': 0.48}

 48%|████▊     | 1726/3566 [1:09:37<1:12:59,  2.38s/it]
 48%|████▊     | 1727/3566 [1:09:39<1:10:57,  2.31s/it]
                                                       
{'loss': 1.4403, 'learning_rate': 0.00021918619255712168, 'epoch': 0.48}

 48%|████▊     | 1727/3566 [1:09:39<1:10:57,  2.31s/it]
 48%|████▊     | 1728/3566 [1:09:41<1:11:01,  2.32s/it]
                                                       
{'loss': 1.4818, 'learning_rate': 0.00021900574017672325, 'epoch': 0.48}

 48%|████▊     | 1728/3566 [1:09:41<1:11:01,  2.32s/it]
 48%|████▊     | 1729/3566 [1:09:44<1:10:57,  2.32s/it]
                                                       
{'loss': 1.493, 'learning_rate': 0.00021882527218184975, 'epoch': 0.48}

 48%|████▊     | 1729/3566 [1:09:44<1:10:57,  2.32s/it]
 49%|████▊     | 1730/3566 [1:09:46<1:11:56,  2.35s/it]
                                                       
{'loss': 1.4143, 'learning_rate': 0.00021864478872076767, 'epoch': 0.49}

 49%|████▊     | 1730/3566 [1:09:46<1:11:56,  2.35s/it]
 49%|████▊     | 1731/3566 [1:09:48<1:11:12,  2.33s/it]
                                                       
{'loss': 1.5277, 'learning_rate': 0.00021846428994175612, 'epoch': 0.49}

 49%|████▊     | 1731/3566 [1:09:48<1:11:12,  2.33s/it]
 49%|████▊     | 1732/3566 [1:09:51<1:10:54,  2.32s/it]
                                                       
{'loss': 1.6244, 'learning_rate': 0.00021828377599310685, 'epoch': 0.49}

 49%|████▊     | 1732/3566 [1:09:51<1:10:54,  2.32s/it]
 49%|████▊     | 1733/3566 [1:09:53<1:14:02,  2.42s/it]
                                                       
{'loss': 1.4557, 'learning_rate': 0.000218103247023124, 'epoch': 0.49}

 49%|████▊     | 1733/3566 [1:09:53<1:14:02,  2.42s/it]
 49%|████▊     | 1734/3566 [1:09:56<1:15:24,  2.47s/it]
                                                       
{'loss': 1.5642, 'learning_rate': 0.00021792270318012405, 'epoch': 0.49}

 49%|████▊     | 1734/3566 [1:09:56<1:15:24,  2.47s/it]
 49%|████▊     | 1735/3566 [1:09:58<1:15:09,  2.46s/it]
                                                       
{'loss': 1.6224, 'learning_rate': 0.00021774214461243579, 'epoch': 0.49}

 49%|████▊     | 1735/3566 [1:09:58<1:15:09,  2.46s/it]
 49%|████▊     | 1736/3566 [1:10:01<1:15:06,  2.46s/it]
                                                       
{'loss': 1.5405, 'learning_rate': 0.00021756157146839996, 'epoch': 0.49}

 49%|████▊     | 1736/3566 [1:10:01<1:15:06,  2.46s/it]
 49%|████▊     | 1737/3566 [1:10:03<1:13:53,  2.42s/it]
                                                       
{'loss': 1.5319, 'learning_rate': 0.00021738098389636955, 'epoch': 0.49}

 49%|████▊     | 1737/3566 [1:10:03<1:13:53,  2.42s/it]
 49%|████▊     | 1738/3566 [1:10:06<1:13:49,  2.42s/it]
                                                       
{'loss': 1.38, 'learning_rate': 0.0002172003820447089, 'epoch': 0.49}

 49%|████▊     | 1738/3566 [1:10:06<1:13:49,  2.42s/it]
 49%|████▉     | 1739/3566 [1:10:08<1:13:29,  2.41s/it]
                                                       
{'loss': 1.6056, 'learning_rate': 0.0002170197660617947, 'epoch': 0.49}

 49%|████▉     | 1739/3566 [1:10:08<1:13:29,  2.41s/it]
 49%|████▉     | 1740/3566 [1:10:10<1:11:16,  2.34s/it]
                                                       
{'loss': 1.5819, 'learning_rate': 0.00021683913609601483, 'epoch': 0.49}

 49%|████▉     | 1740/3566 [1:10:10<1:11:16,  2.34s/it]
 49%|████▉     | 1741/3566 [1:10:12<1:09:20,  2.28s/it]
                                                       
{'loss': 1.5213, 'learning_rate': 0.00021665849229576885, 'epoch': 0.49}

 49%|████▉     | 1741/3566 [1:10:12<1:09:20,  2.28s/it]
 49%|████▉     | 1742/3566 [1:10:15<1:11:33,  2.35s/it]
                                                       
{'loss': 1.5423, 'learning_rate': 0.00021647783480946745, 'epoch': 0.49}

 49%|████▉     | 1742/3566 [1:10:15<1:11:33,  2.35s/it]
 49%|████▉     | 1743/3566 [1:10:17<1:11:27,  2.35s/it]
                                                       
{'loss': 1.4778, 'learning_rate': 0.00021629716378553289, 'epoch': 0.49}

 49%|████▉     | 1743/3566 [1:10:17<1:11:27,  2.35s/it]
 49%|████▉     | 1744/3566 [1:10:20<1:11:29,  2.35s/it]
                                                       
{'loss': 1.5397, 'learning_rate': 0.00021611647937239825, 'epoch': 0.49}

 49%|████▉     | 1744/3566 [1:10:20<1:11:29,  2.35s/it]
 49%|████▉     | 1745/3566 [1:10:22<1:10:29,  2.32s/it]
                                                       
{'loss': 1.4801, 'learning_rate': 0.00021593578171850788, 'epoch': 0.49}

 49%|████▉     | 1745/3566 [1:10:22<1:10:29,  2.32s/it]
 49%|████▉     | 1746/3566 [1:10:25<1:17:25,  2.55s/it]
                                                       
{'loss': 1.5704, 'learning_rate': 0.0002157550709723168, 'epoch': 0.49}

 49%|████▉     | 1746/3566 [1:10:25<1:17:25,  2.55s/it]
 49%|████▉     | 1747/3566 [1:10:28<1:18:37,  2.59s/it]
                                                       
{'loss': 1.4853, 'learning_rate': 0.00021557434728229088, 'epoch': 0.49}

 49%|████▉     | 1747/3566 [1:10:28<1:18:37,  2.59s/it]
 49%|████▉     | 1748/3566 [1:10:30<1:17:52,  2.57s/it]
                                                       
{'loss': 1.5793, 'learning_rate': 0.00021539361079690657, 'epoch': 0.49}

 49%|████▉     | 1748/3566 [1:10:30<1:17:52,  2.57s/it]
 49%|████▉     | 1749/3566 [1:10:32<1:15:37,  2.50s/it]
                                                       
{'loss': 1.7272, 'learning_rate': 0.00021521286166465093, 'epoch': 0.49}

 49%|████▉     | 1749/3566 [1:10:32<1:15:37,  2.50s/it]
 49%|████▉     | 1750/3566 [1:10:35<1:15:55,  2.51s/it]
                                                       
{'loss': 1.678, 'learning_rate': 0.00021503210003402141, 'epoch': 0.49}

 49%|████▉     | 1750/3566 [1:10:35<1:15:55,  2.51s/it]
 49%|████▉     | 1751/3566 [1:10:37<1:14:15,  2.45s/it]
                                                       
{'loss': 1.5371, 'learning_rate': 0.00021485132605352552, 'epoch': 0.49}

 49%|████▉     | 1751/3566 [1:10:37<1:14:15,  2.45s/it]
 49%|████▉     | 1752/3566 [1:10:40<1:12:30,  2.40s/it]
                                                       
{'loss': 1.4413, 'learning_rate': 0.00021467053987168105, 'epoch': 0.49}

 49%|████▉     | 1752/3566 [1:10:40<1:12:30,  2.40s/it]
 49%|████▉     | 1753/3566 [1:10:42<1:15:40,  2.50s/it]
                                                       
{'loss': 1.6737, 'learning_rate': 0.000214489741637016, 'epoch': 0.49}

 49%|████▉     | 1753/3566 [1:10:42<1:15:40,  2.50s/it]
 49%|████▉     | 1754/3566 [1:10:45<1:15:48,  2.51s/it]
                                                       
{'loss': 1.5311, 'learning_rate': 0.00021430893149806802, 'epoch': 0.49}

 49%|████▉     | 1754/3566 [1:10:45<1:15:48,  2.51s/it]
 49%|████▉     | 1755/3566 [1:10:47<1:14:35,  2.47s/it]
                                                       
{'loss': 1.5138, 'learning_rate': 0.00021412810960338456, 'epoch': 0.49}

 49%|████▉     | 1755/3566 [1:10:47<1:14:35,  2.47s/it]
 49%|████▉     | 1756/3566 [1:10:50<1:17:38,  2.57s/it]
                                                       
{'loss': 1.5867, 'learning_rate': 0.0002139472761015229, 'epoch': 0.49}

 49%|████▉     | 1756/3566 [1:10:50<1:17:38,  2.57s/it]
 49%|████▉     | 1757/3566 [1:10:53<1:17:53,  2.58s/it]
                                                       
{'loss': 1.5229, 'learning_rate': 0.00021376643114104962, 'epoch': 0.49}

 49%|████▉     | 1757/3566 [1:10:53<1:17:53,  2.58s/it]
 49%|████▉     | 1758/3566 [1:10:55<1:19:54,  2.65s/it]
                                                       
{'loss': 1.5251, 'learning_rate': 0.00021358557487054092, 'epoch': 0.49}

 49%|████▉     | 1758/3566 [1:10:56<1:19:54,  2.65s/it]
 49%|████▉     | 1759/3566 [1:10:58<1:17:22,  2.57s/it]
                                                       
{'loss': 1.6136, 'learning_rate': 0.00021340470743858223, 'epoch': 0.49}

 49%|████▉     | 1759/3566 [1:10:58<1:17:22,  2.57s/it]
 49%|████▉     | 1760/3566 [1:11:01<1:18:06,  2.59s/it]
                                                       
{'loss': 1.3991, 'learning_rate': 0.00021322382899376802, 'epoch': 0.49}

 49%|████▉     | 1760/3566 [1:11:01<1:18:06,  2.59s/it]
 49%|████▉     | 1761/3566 [1:11:03<1:14:49,  2.49s/it]
                                                       
{'loss': 1.4122, 'learning_rate': 0.00021304293968470205, 'epoch': 0.49}

 49%|████▉     | 1761/3566 [1:11:03<1:14:49,  2.49s/it]
 49%|████▉     | 1762/3566 [1:11:05<1:13:18,  2.44s/it]
                                                       
{'loss': 1.5702, 'learning_rate': 0.00021286203965999677, 'epoch': 0.49}

 49%|████▉     | 1762/3566 [1:11:05<1:13:18,  2.44s/it]
 49%|████▉     | 1763/3566 [1:11:07<1:10:41,  2.35s/it]
                                                       
{'loss': 1.613, 'learning_rate': 0.00021268112906827367, 'epoch': 0.49}

 49%|████▉     | 1763/3566 [1:11:07<1:10:41,  2.35s/it]
 49%|████▉     | 1764/3566 [1:11:10<1:11:44,  2.39s/it]
                                                       
{'loss': 1.5842, 'learning_rate': 0.00021250020805816267, 'epoch': 0.49}

 49%|████▉     | 1764/3566 [1:11:10<1:11:44,  2.39s/it]
 49%|████▉     | 1765/3566 [1:11:13<1:17:48,  2.59s/it]
                                                       
{'loss': 1.48, 'learning_rate': 0.00021231927677830238, 'epoch': 0.49}

 49%|████▉     | 1765/3566 [1:11:13<1:17:48,  2.59s/it]
 50%|████▉     | 1766/3566 [1:11:15<1:16:30,  2.55s/it]
                                                       
{'loss': 1.6922, 'learning_rate': 0.00021213833537733984, 'epoch': 0.5}

 50%|████▉     | 1766/3566 [1:11:15<1:16:30,  2.55s/it]
 50%|████▉     | 1767/3566 [1:11:18<1:15:49,  2.53s/it]
                                                       
{'loss': 1.4609, 'learning_rate': 0.0002119573840039305, 'epoch': 0.5}

 50%|████▉     | 1767/3566 [1:11:18<1:15:49,  2.53s/it]
 50%|████▉     | 1768/3566 [1:11:20<1:12:32,  2.42s/it]
                                                       
{'loss': 1.6187, 'learning_rate': 0.00021177642280673773, 'epoch': 0.5}

 50%|████▉     | 1768/3566 [1:11:20<1:12:32,  2.42s/it]
 50%|████▉     | 1769/3566 [1:11:22<1:11:30,  2.39s/it]
                                                       
{'loss': 1.6393, 'learning_rate': 0.00021159545193443329, 'epoch': 0.5}

 50%|████▉     | 1769/3566 [1:11:22<1:11:30,  2.39s/it]
 50%|████▉     | 1770/3566 [1:11:25<1:13:32,  2.46s/it]
                                                       
{'loss': 1.5765, 'learning_rate': 0.0002114144715356967, 'epoch': 0.5}

 50%|████▉     | 1770/3566 [1:11:25<1:13:32,  2.46s/it]
 50%|████▉     | 1771/3566 [1:11:27<1:13:28,  2.46s/it]
                                                       
{'loss': 1.5726, 'learning_rate': 0.00021123348175921538, 'epoch': 0.5}

 50%|████▉     | 1771/3566 [1:11:27<1:13:28,  2.46s/it]
 50%|████▉     | 1772/3566 [1:11:30<1:11:36,  2.40s/it]
                                                       
{'loss': 1.6218, 'learning_rate': 0.00021105248275368434, 'epoch': 0.5}

 50%|████▉     | 1772/3566 [1:11:30<1:11:36,  2.40s/it]
 50%|████▉     | 1773/3566 [1:11:32<1:10:39,  2.36s/it]
                                                       
{'loss': 1.6118, 'learning_rate': 0.0002108714746678063, 'epoch': 0.5}

 50%|████▉     | 1773/3566 [1:11:32<1:10:39,  2.36s/it]
 50%|████▉     | 1774/3566 [1:11:34<1:11:56,  2.41s/it]
                                                       
{'loss': 1.53, 'learning_rate': 0.00021069045765029137, 'epoch': 0.5}

 50%|████▉     | 1774/3566 [1:11:34<1:11:56,  2.41s/it]
 50%|████▉     | 1775/3566 [1:11:37<1:11:01,  2.38s/it]
                                                       
{'loss': 1.4516, 'learning_rate': 0.00021050943184985714, 'epoch': 0.5}

 50%|████▉     | 1775/3566 [1:11:37<1:11:01,  2.38s/it]
 50%|████▉     | 1776/3566 [1:11:39<1:09:55,  2.34s/it]
                                                       
{'loss': 1.6388, 'learning_rate': 0.0002103283974152282, 'epoch': 0.5}

 50%|████▉     | 1776/3566 [1:11:39<1:09:55,  2.34s/it]
 50%|████▉     | 1777/3566 [1:11:41<1:10:00,  2.35s/it]
                                                       
{'loss': 1.6348, 'learning_rate': 0.0002101473544951363, 'epoch': 0.5}

 50%|████▉     | 1777/3566 [1:11:41<1:10:00,  2.35s/it]
 50%|████▉     | 1778/3566 [1:11:44<1:09:29,  2.33s/it]
                                                       
{'loss': 1.5979, 'learning_rate': 0.0002099663032383203, 'epoch': 0.5}

 50%|████▉     | 1778/3566 [1:11:44<1:09:29,  2.33s/it]
 50%|████▉     | 1779/3566 [1:11:46<1:11:53,  2.41s/it]
                                                       
{'loss': 1.5776, 'learning_rate': 0.00020978524379352574, 'epoch': 0.5}

 50%|████▉     | 1779/3566 [1:11:46<1:11:53,  2.41s/it]
 50%|████▉     | 1780/3566 [1:11:48<1:09:44,  2.34s/it]
                                                       
{'loss': 1.5778, 'learning_rate': 0.00020960417630950504, 'epoch': 0.5}

 50%|████▉     | 1780/3566 [1:11:48<1:09:44,  2.34s/it]
 50%|████▉     | 1781/3566 [1:11:51<1:08:10,  2.29s/it]
                                                       
{'loss': 1.7426, 'learning_rate': 0.00020942310093501694, 'epoch': 0.5}

 50%|████▉     | 1781/3566 [1:11:51<1:08:10,  2.29s/it]
 50%|████▉     | 1782/3566 [1:11:53<1:08:08,  2.29s/it]
                                                       
{'loss': 1.5134, 'learning_rate': 0.00020924201781882706, 'epoch': 0.5}

 50%|████▉     | 1782/3566 [1:11:53<1:08:08,  2.29s/it]
 50%|█████     | 1783/3566 [1:11:55<1:06:37,  2.24s/it]
                                                       
{'loss': 1.555, 'learning_rate': 0.00020906092710970707, 'epoch': 0.5}

 50%|█████     | 1783/3566 [1:11:55<1:06:37,  2.24s/it]
 50%|█████     | 1784/3566 [1:11:57<1:05:58,  2.22s/it]
                                                       
{'loss': 1.577, 'learning_rate': 0.0002088798289564351, 'epoch': 0.5}

 50%|█████     | 1784/3566 [1:11:57<1:05:58,  2.22s/it]
 50%|█████     | 1785/3566 [1:12:00<1:08:40,  2.31s/it]
                                                       
{'loss': 1.4946, 'learning_rate': 0.00020869872350779512, 'epoch': 0.5}

 50%|█████     | 1785/3566 [1:12:00<1:08:40,  2.31s/it]
 50%|█████     | 1786/3566 [1:12:02<1:11:00,  2.39s/it]
                                                       
{'loss': 1.6802, 'learning_rate': 0.0002085176109125774, 'epoch': 0.5}

 50%|█████     | 1786/3566 [1:12:02<1:11:00,  2.39s/it]
 50%|█████     | 1787/3566 [1:12:05<1:11:22,  2.41s/it]
                                                       
{'loss': 1.6832, 'learning_rate': 0.00020833649131957781, 'epoch': 0.5}

 50%|█████     | 1787/3566 [1:12:05<1:11:22,  2.41s/it]
 50%|█████     | 1788/3566 [1:12:07<1:11:14,  2.40s/it]
                                                       
{'loss': 1.543, 'learning_rate': 0.00020815536487759823, 'epoch': 0.5}

 50%|█████     | 1788/3566 [1:12:07<1:11:14,  2.40s/it]
 50%|█████     | 1789/3566 [1:12:10<1:15:35,  2.55s/it]
                                                       
{'loss': 1.4706, 'learning_rate': 0.00020797423173544598, 'epoch': 0.5}

 50%|█████     | 1789/3566 [1:12:10<1:15:35,  2.55s/it]
 50%|█████     | 1790/3566 [1:12:12<1:14:09,  2.51s/it]
                                                       
{'loss': 1.5107, 'learning_rate': 0.0002077930920419339, 'epoch': 0.5}

 50%|█████     | 1790/3566 [1:12:12<1:14:09,  2.51s/it]
 50%|█████     | 1791/3566 [1:12:15<1:14:56,  2.53s/it]
                                                       
{'loss': 1.4211, 'learning_rate': 0.0002076119459458803, 'epoch': 0.5}

 50%|█████     | 1791/3566 [1:12:15<1:14:56,  2.53s/it]
 50%|█████     | 1792/3566 [1:12:17<1:14:16,  2.51s/it]
                                                       
{'loss': 1.6153, 'learning_rate': 0.00020743079359610865, 'epoch': 0.5}

 50%|█████     | 1792/3566 [1:12:17<1:14:16,  2.51s/it]
 50%|█████     | 1793/3566 [1:12:20<1:12:22,  2.45s/it]
                                                       
{'loss': 1.5399, 'learning_rate': 0.00020724963514144772, 'epoch': 0.5}

 50%|█████     | 1793/3566 [1:12:20<1:12:22,  2.45s/it]
 50%|█████     | 1794/3566 [1:12:22<1:15:10,  2.55s/it]
                                                       
{'loss': 1.5471, 'learning_rate': 0.0002070684707307311, 'epoch': 0.5}

 50%|█████     | 1794/3566 [1:12:22<1:15:10,  2.55s/it]
 50%|█████     | 1795/3566 [1:12:25<1:13:26,  2.49s/it]
                                                       
{'loss': 1.6296, 'learning_rate': 0.0002068873005127973, 'epoch': 0.5}

 50%|█████     | 1795/3566 [1:12:25<1:13:26,  2.49s/it]
 50%|█████     | 1796/3566 [1:12:28<1:16:34,  2.60s/it]
                                                       
{'loss': 1.6471, 'learning_rate': 0.00020670612463648976, 'epoch': 0.5}

 50%|█████     | 1796/3566 [1:12:28<1:16:34,  2.60s/it]
 50%|█████     | 1797/3566 [1:12:30<1:13:18,  2.49s/it]
                                                       
{'loss': 1.4332, 'learning_rate': 0.00020652494325065649, 'epoch': 0.5}

 50%|█████     | 1797/3566 [1:12:30<1:13:18,  2.49s/it]
 50%|█████     | 1798/3566 [1:12:32<1:12:20,  2.46s/it]
                                                       
{'loss': 1.5291, 'learning_rate': 0.00020634375650414993, 'epoch': 0.5}

 50%|█████     | 1798/3566 [1:12:32<1:12:20,  2.46s/it]
 50%|█████     | 1799/3566 [1:12:35<1:11:38,  2.43s/it]
                                                       
{'loss': 1.5962, 'learning_rate': 0.000206162564545827, 'epoch': 0.5}

 50%|█████     | 1799/3566 [1:12:35<1:11:38,  2.43s/it]
 50%|█████     | 1800/3566 [1:12:37<1:08:47,  2.34s/it]
                                                       
{'loss': 1.5381, 'learning_rate': 0.00020598136752454895, 'epoch': 0.5}

 50%|█████     | 1800/3566 [1:12:37<1:08:47,  2.34s/it]
 51%|█████     | 1801/3566 [1:12:39<1:10:01,  2.38s/it]
                                                       
{'loss': 1.5404, 'learning_rate': 0.00020580016558918108, 'epoch': 0.51}

 51%|█████     | 1801/3566 [1:12:39<1:10:01,  2.38s/it]
 51%|█████     | 1802/3566 [1:12:41<1:07:50,  2.31s/it]
                                                       
{'loss': 1.6397, 'learning_rate': 0.00020561895888859285, 'epoch': 0.51}

 51%|█████     | 1802/3566 [1:12:41<1:07:50,  2.31s/it]
 51%|█████     | 1803/3566 [1:12:44<1:07:57,  2.31s/it]
                                                       
{'loss': 1.556, 'learning_rate': 0.00020543774757165754, 'epoch': 0.51}

 51%|█████     | 1803/3566 [1:12:44<1:07:57,  2.31s/it]
 51%|█████     | 1804/3566 [1:12:46<1:10:26,  2.40s/it]
                                                       
{'loss': 1.439, 'learning_rate': 0.00020525653178725222, 'epoch': 0.51}

 51%|█████     | 1804/3566 [1:12:46<1:10:26,  2.40s/it]
 51%|█████     | 1805/3566 [1:12:49<1:09:53,  2.38s/it]
                                                       
{'loss': 1.6438, 'learning_rate': 0.00020507531168425773, 'epoch': 0.51}

 51%|█████     | 1805/3566 [1:12:49<1:09:53,  2.38s/it]
 51%|█████     | 1806/3566 [1:12:51<1:08:15,  2.33s/it]
                                                       
{'loss': 1.5649, 'learning_rate': 0.00020489408741155844, 'epoch': 0.51}

 51%|█████     | 1806/3566 [1:12:51<1:08:15,  2.33s/it]
 51%|█████     | 1807/3566 [1:12:53<1:09:26,  2.37s/it]
                                                       
{'loss': 1.5187, 'learning_rate': 0.0002047128591180419, 'epoch': 0.51}

 51%|█████     | 1807/3566 [1:12:53<1:09:26,  2.37s/it]
 51%|█████     | 1808/3566 [1:12:56<1:07:58,  2.32s/it]
                                                       
{'loss': 1.5315, 'learning_rate': 0.00020453162695259938, 'epoch': 0.51}

 51%|█████     | 1808/3566 [1:12:56<1:07:58,  2.32s/it]
 51%|█████     | 1809/3566 [1:12:58<1:09:43,  2.38s/it]
                                                       
{'loss': 1.5905, 'learning_rate': 0.00020435039106412494, 'epoch': 0.51}

 51%|█████     | 1809/3566 [1:12:58<1:09:43,  2.38s/it]
 51%|█████     | 1810/3566 [1:13:01<1:11:32,  2.44s/it]
                                                       
{'loss': 1.622, 'learning_rate': 0.00020416915160151607, 'epoch': 0.51}

 51%|█████     | 1810/3566 [1:13:01<1:11:32,  2.44s/it]
 51%|█████     | 1811/3566 [1:13:03<1:11:30,  2.44s/it]
                                                       
{'loss': 1.7464, 'learning_rate': 0.00020398790871367281, 'epoch': 0.51}

 51%|█████     | 1811/3566 [1:13:03<1:11:30,  2.44s/it]
 51%|█████     | 1812/3566 [1:13:06<1:11:56,  2.46s/it]
                                                       
{'loss': 1.5899, 'learning_rate': 0.00020380666254949826, 'epoch': 0.51}

 51%|█████     | 1812/3566 [1:13:06<1:11:56,  2.46s/it]
 51%|█████     | 1813/3566 [1:13:08<1:09:33,  2.38s/it]
                                                       
{'loss': 1.5067, 'learning_rate': 0.0002036254132578982, 'epoch': 0.51}

 51%|█████     | 1813/3566 [1:13:08<1:09:33,  2.38s/it]
 51%|█████     | 1814/3566 [1:13:10<1:08:27,  2.34s/it]
                                                       
{'loss': 1.5302, 'learning_rate': 0.00020344416098778094, 'epoch': 0.51}

 51%|█████     | 1814/3566 [1:13:10<1:08:27,  2.34s/it]
 51%|█████     | 1815/3566 [1:13:12<1:08:10,  2.34s/it]
                                                       
{'loss': 1.5828, 'learning_rate': 0.00020326290588805717, 'epoch': 0.51}

 51%|█████     | 1815/3566 [1:13:12<1:08:10,  2.34s/it]
 51%|█████     | 1816/3566 [1:13:15<1:08:53,  2.36s/it]
                                                       
{'loss': 1.5656, 'learning_rate': 0.00020308164810763993, 'epoch': 0.51}

 51%|█████     | 1816/3566 [1:13:15<1:08:53,  2.36s/it]
 51%|█████     | 1817/3566 [1:13:18<1:12:18,  2.48s/it]
                                                       
{'loss': 1.5036, 'learning_rate': 0.0002029003877954446, 'epoch': 0.51}

 51%|█████     | 1817/3566 [1:13:18<1:12:18,  2.48s/it]
 51%|█████     | 1818/3566 [1:13:20<1:09:48,  2.40s/it]
                                                       
{'loss': 1.5446, 'learning_rate': 0.00020271912510038854, 'epoch': 0.51}

 51%|█████     | 1818/3566 [1:13:20<1:09:48,  2.40s/it]
 51%|█████     | 1819/3566 [1:13:23<1:14:14,  2.55s/it]
                                                       
{'loss': 1.5783, 'learning_rate': 0.000202537860171391, 'epoch': 0.51}

 51%|█████     | 1819/3566 [1:13:23<1:14:14,  2.55s/it]
 51%|█████     | 1820/3566 [1:13:25<1:11:11,  2.45s/it]
                                                       
{'loss': 1.4605, 'learning_rate': 0.00020235659315737315, 'epoch': 0.51}

 51%|█████     | 1820/3566 [1:13:25<1:11:11,  2.45s/it]
 51%|█████     | 1821/3566 [1:13:27<1:10:05,  2.41s/it]
                                                       
{'loss': 1.5527, 'learning_rate': 0.00020217532420725785, 'epoch': 0.51}

 51%|█████     | 1821/3566 [1:13:27<1:10:05,  2.41s/it]
 51%|█████     | 1822/3566 [1:13:29<1:09:05,  2.38s/it]
                                                       
{'loss': 1.469, 'learning_rate': 0.00020199405346996955, 'epoch': 0.51}

 51%|█████     | 1822/3566 [1:13:29<1:09:05,  2.38s/it]
 51%|█████     | 1823/3566 [1:13:32<1:08:46,  2.37s/it]
                                                       
{'loss': 1.5489, 'learning_rate': 0.00020181278109443417, 'epoch': 0.51}

 51%|█████     | 1823/3566 [1:13:32<1:08:46,  2.37s/it]
 51%|█████     | 1824/3566 [1:13:34<1:11:07,  2.45s/it]
                                                       
{'loss': 1.5781, 'learning_rate': 0.00020163150722957905, 'epoch': 0.51}

 51%|█████     | 1824/3566 [1:13:34<1:11:07,  2.45s/it]
 51%|█████     | 1825/3566 [1:13:37<1:10:46,  2.44s/it]
                                                       
{'loss': 1.5845, 'learning_rate': 0.0002014502320243326, 'epoch': 0.51}

 51%|█████     | 1825/3566 [1:13:37<1:10:46,  2.44s/it]
 51%|█████     | 1826/3566 [1:13:39<1:11:21,  2.46s/it]
                                                       
{'loss': 1.4641, 'learning_rate': 0.00020126895562762442, 'epoch': 0.51}

 51%|█████     | 1826/3566 [1:13:39<1:11:21,  2.46s/it]
 51%|█████     | 1827/3566 [1:13:42<1:11:27,  2.47s/it]
                                                       
{'loss': 1.4895, 'learning_rate': 0.00020108767818838516, 'epoch': 0.51}

 51%|█████     | 1827/3566 [1:13:42<1:11:27,  2.47s/it]
 51%|█████▏    | 1828/3566 [1:13:44<1:11:15,  2.46s/it]
                                                       
{'loss': 1.5249, 'learning_rate': 0.00020090639985554613, 'epoch': 0.51}

 51%|█████▏    | 1828/3566 [1:13:44<1:11:15,  2.46s/it]
 51%|█████▏    | 1829/3566 [1:13:46<1:08:24,  2.36s/it]
                                                       
{'loss': 1.476, 'learning_rate': 0.00020072512077803957, 'epoch': 0.51}

 51%|█████▏    | 1829/3566 [1:13:46<1:08:24,  2.36s/it]
 51%|█████▏    | 1830/3566 [1:13:49<1:09:34,  2.40s/it]
                                                       
{'loss': 1.592, 'learning_rate': 0.00020054384110479822, 'epoch': 0.51}

 51%|█████▏    | 1830/3566 [1:13:49<1:09:34,  2.40s/it]
 51%|█████▏    | 1831/3566 [1:13:51<1:10:01,  2.42s/it]
                                                       
{'loss': 1.6337, 'learning_rate': 0.00020036256098475544, 'epoch': 0.51}

 51%|█████▏    | 1831/3566 [1:13:51<1:10:01,  2.42s/it]
 51%|█████▏    | 1832/3566 [1:13:54<1:08:25,  2.37s/it]
                                                       
{'loss': 1.4726, 'learning_rate': 0.00020018128056684473, 'epoch': 0.51}

 51%|█████▏    | 1832/3566 [1:13:54<1:08:25,  2.37s/it]
 51%|█████▏    | 1833/3566 [1:13:56<1:09:37,  2.41s/it]
                                                       
{'loss': 1.5201, 'learning_rate': 0.0002, 'epoch': 0.51}

 51%|█████▏    | 1833/3566 [1:13:56<1:09:37,  2.41s/it]
 51%|█████▏    | 1834/3566 [1:13:59<1:09:57,  2.42s/it]
                                                       
{'loss': 1.6322, 'learning_rate': 0.00019981871943315532, 'epoch': 0.51}

 51%|█████▏    | 1834/3566 [1:13:59<1:09:57,  2.42s/it]
 51%|█████▏    | 1835/3566 [1:14:01<1:11:56,  2.49s/it]
                                                       
{'loss': 1.7281, 'learning_rate': 0.0001996374390152446, 'epoch': 0.51}

 51%|█████▏    | 1835/3566 [1:14:01<1:11:56,  2.49s/it]
 51%|█████▏    | 1836/3566 [1:14:04<1:10:58,  2.46s/it]
                                                       
{'loss': 1.4793, 'learning_rate': 0.00019945615889520183, 'epoch': 0.51}

 51%|█████▏    | 1836/3566 [1:14:04<1:10:58,  2.46s/it]
 52%|█████▏    | 1837/3566 [1:14:06<1:10:41,  2.45s/it]
                                                       
{'loss': 1.5181, 'learning_rate': 0.0001992748792219605, 'epoch': 0.52}

 52%|█████▏    | 1837/3566 [1:14:06<1:10:41,  2.45s/it]
 52%|█████▏    | 1838/3566 [1:14:09<1:11:34,  2.48s/it]
                                                       
{'loss': 1.5796, 'learning_rate': 0.00019909360014445392, 'epoch': 0.52}

 52%|█████▏    | 1838/3566 [1:14:09<1:11:34,  2.48s/it]
 52%|█████▏    | 1839/3566 [1:14:11<1:10:28,  2.45s/it]
                                                       
{'loss': 1.4726, 'learning_rate': 0.0001989123218116149, 'epoch': 0.52}

 52%|█████▏    | 1839/3566 [1:14:11<1:10:28,  2.45s/it]
 52%|█████▏    | 1840/3566 [1:14:13<1:08:14,  2.37s/it]
                                                       
{'loss': 1.454, 'learning_rate': 0.00019873104437237563, 'epoch': 0.52}

 52%|█████▏    | 1840/3566 [1:14:13<1:08:14,  2.37s/it]
 52%|█████▏    | 1841/3566 [1:14:15<1:07:13,  2.34s/it]
                                                       
{'loss': 1.6595, 'learning_rate': 0.00019854976797566742, 'epoch': 0.52}

 52%|█████▏    | 1841/3566 [1:14:15<1:07:13,  2.34s/it]
 52%|█████▏    | 1842/3566 [1:14:18<1:11:53,  2.50s/it]
                                                       
{'loss': 1.5598, 'learning_rate': 0.00019836849277042097, 'epoch': 0.52}

 52%|█████▏    | 1842/3566 [1:14:18<1:11:53,  2.50s/it]
 52%|█████▏    | 1843/3566 [1:14:21<1:09:54,  2.43s/it]
                                                       
{'loss': 1.676, 'learning_rate': 0.0001981872189055658, 'epoch': 0.52}

 52%|█████▏    | 1843/3566 [1:14:21<1:09:54,  2.43s/it]
 52%|█████▏    | 1844/3566 [1:14:23<1:07:45,  2.36s/it]
                                                       
{'loss': 1.5567, 'learning_rate': 0.00019800594653003047, 'epoch': 0.52}

 52%|█████▏    | 1844/3566 [1:14:23<1:07:45,  2.36s/it]
 52%|█████▏    | 1845/3566 [1:14:26<1:12:10,  2.52s/it]
                                                       
{'loss': 1.5302, 'learning_rate': 0.0001978246757927422, 'epoch': 0.52}

 52%|█████▏    | 1845/3566 [1:14:26<1:12:10,  2.52s/it]
 52%|█████▏    | 1846/3566 [1:14:28<1:11:35,  2.50s/it]
                                                       
{'loss': 1.5436, 'learning_rate': 0.0001976434068426269, 'epoch': 0.52}

 52%|█████▏    | 1846/3566 [1:14:28<1:11:35,  2.50s/it]
 52%|█████▏    | 1847/3566 [1:14:31<1:11:10,  2.48s/it]
                                                       
{'loss': 1.6026, 'learning_rate': 0.00019746213982860903, 'epoch': 0.52}

 52%|█████▏    | 1847/3566 [1:14:31<1:11:10,  2.48s/it]
 52%|█████▏    | 1848/3566 [1:14:33<1:10:01,  2.45s/it]
                                                       
{'loss': 1.5056, 'learning_rate': 0.00019728087489961148, 'epoch': 0.52}

 52%|█████▏    | 1848/3566 [1:14:33<1:10:01,  2.45s/it]
 52%|█████▏    | 1849/3566 [1:14:35<1:10:17,  2.46s/it]
                                                       
{'loss': 1.5773, 'learning_rate': 0.00019709961220455545, 'epoch': 0.52}

 52%|█████▏    | 1849/3566 [1:14:35<1:10:17,  2.46s/it]
 52%|█████▏    | 1850/3566 [1:14:38<1:12:15,  2.53s/it]
                                                       
{'loss': 1.5341, 'learning_rate': 0.0001969183518923601, 'epoch': 0.52}

 52%|█████▏    | 1850/3566 [1:14:38<1:12:15,  2.53s/it]
 52%|█████▏    | 1851/3566 [1:14:41<1:12:09,  2.52s/it]
                                                       
{'loss': 1.5715, 'learning_rate': 0.00019673709411194293, 'epoch': 0.52}

 52%|█████▏    | 1851/3566 [1:14:41<1:12:09,  2.52s/it]
 52%|█████▏    | 1852/3566 [1:14:43<1:10:15,  2.46s/it]
                                                       
{'loss': 1.4446, 'learning_rate': 0.00019655583901221913, 'epoch': 0.52}

 52%|█████▏    | 1852/3566 [1:14:43<1:10:15,  2.46s/it]
 52%|█████▏    | 1853/3566 [1:14:45<1:08:30,  2.40s/it]
                                                       
{'loss': 1.6097, 'learning_rate': 0.00019637458674210182, 'epoch': 0.52}

 52%|█████▏    | 1853/3566 [1:14:45<1:08:30,  2.40s/it]
 52%|█████▏    | 1854/3566 [1:14:48<1:10:25,  2.47s/it]
                                                       
{'loss': 1.361, 'learning_rate': 0.0001961933374505018, 'epoch': 0.52}

 52%|█████▏    | 1854/3566 [1:14:48<1:10:25,  2.47s/it]
 52%|█████▏    | 1855/3566 [1:14:50<1:09:04,  2.42s/it]
                                                       
{'loss': 1.7158, 'learning_rate': 0.0001960120912863272, 'epoch': 0.52}

 52%|█████▏    | 1855/3566 [1:14:50<1:09:04,  2.42s/it]
 52%|█████▏    | 1856/3566 [1:14:53<1:10:02,  2.46s/it]
                                                       
{'loss': 1.4089, 'learning_rate': 0.00019583084839848398, 'epoch': 0.52}

 52%|█████▏    | 1856/3566 [1:14:53<1:10:02,  2.46s/it]
 52%|█████▏    | 1857/3566 [1:14:55<1:05:23,  2.30s/it]
                                                       
{'loss': 1.395, 'learning_rate': 0.00019564960893587505, 'epoch': 0.52}

 52%|█████▏    | 1857/3566 [1:14:55<1:05:23,  2.30s/it]
 52%|█████▏    | 1858/3566 [1:14:57<1:05:35,  2.30s/it]
                                                       
{'loss': 1.583, 'learning_rate': 0.00019546837304740066, 'epoch': 0.52}

 52%|█████▏    | 1858/3566 [1:14:57<1:05:35,  2.30s/it]
 52%|█████▏    | 1859/3566 [1:14:59<1:04:24,  2.26s/it]
                                                       
{'loss': 1.5671, 'learning_rate': 0.0001952871408819581, 'epoch': 0.52}

 52%|█████▏    | 1859/3566 [1:14:59<1:04:24,  2.26s/it]
 52%|█████▏    | 1860/3566 [1:15:01<1:04:40,  2.27s/it]
                                                       
{'loss': 1.5786, 'learning_rate': 0.0001951059125884416, 'epoch': 0.52}

 52%|█████▏    | 1860/3566 [1:15:01<1:04:40,  2.27s/it]
 52%|█████▏    | 1861/3566 [1:15:04<1:06:31,  2.34s/it]
                                                       
{'loss': 1.6128, 'learning_rate': 0.0001949246883157423, 'epoch': 0.52}

 52%|█████▏    | 1861/3566 [1:15:04<1:06:31,  2.34s/it]
 52%|█████▏    | 1862/3566 [1:15:06<1:05:53,  2.32s/it]
                                                       
{'loss': 1.6966, 'learning_rate': 0.00019474346821274783, 'epoch': 0.52}

 52%|█████▏    | 1862/3566 [1:15:06<1:05:53,  2.32s/it]
 52%|█████▏    | 1863/3566 [1:15:09<1:08:31,  2.41s/it]
                                                       
{'loss': 1.5539, 'learning_rate': 0.0001945622524283425, 'epoch': 0.52}

 52%|█████▏    | 1863/3566 [1:15:09<1:08:31,  2.41s/it]
 52%|█████▏    | 1864/3566 [1:15:11<1:09:20,  2.44s/it]
                                                       
{'loss': 1.545, 'learning_rate': 0.0001943810411114072, 'epoch': 0.52}

 52%|█████▏    | 1864/3566 [1:15:11<1:09:20,  2.44s/it]
 52%|█████▏    | 1865/3566 [1:15:14<1:07:32,  2.38s/it]
                                                       
{'loss': 1.6414, 'learning_rate': 0.00019419983441081897, 'epoch': 0.52}

 52%|█████▏    | 1865/3566 [1:15:14<1:07:32,  2.38s/it]
 52%|█████▏    | 1866/3566 [1:15:16<1:06:45,  2.36s/it]
                                                       
{'loss': 1.5608, 'learning_rate': 0.00019401863247545115, 'epoch': 0.52}

 52%|█████▏    | 1866/3566 [1:15:16<1:06:45,  2.36s/it]
 52%|█████▏    | 1867/3566 [1:15:18<1:06:30,  2.35s/it]
                                                       
{'loss': 1.4859, 'learning_rate': 0.00019383743545417308, 'epoch': 0.52}

 52%|█████▏    | 1867/3566 [1:15:18<1:06:30,  2.35s/it]
 52%|█████▏    | 1868/3566 [1:15:21<1:07:59,  2.40s/it]
                                                       
{'loss': 1.6858, 'learning_rate': 0.00019365624349585017, 'epoch': 0.52}

 52%|█████▏    | 1868/3566 [1:15:21<1:07:59,  2.40s/it]
 52%|█████▏    | 1869/3566 [1:15:23<1:09:58,  2.47s/it]
                                                       
{'loss': 1.6128, 'learning_rate': 0.00019347505674934353, 'epoch': 0.52}

 52%|█████▏    | 1869/3566 [1:15:23<1:09:58,  2.47s/it]
 52%|█████▏    | 1870/3566 [1:15:26<1:08:50,  2.44s/it]
                                                       
{'loss': 1.5808, 'learning_rate': 0.00019329387536351026, 'epoch': 0.52}

 52%|█████▏    | 1870/3566 [1:15:26<1:08:50,  2.44s/it]
 52%|█████▏    | 1871/3566 [1:15:28<1:08:22,  2.42s/it]
                                                       
{'loss': 1.3536, 'learning_rate': 0.0001931126994872027, 'epoch': 0.52}

 52%|█████▏    | 1871/3566 [1:15:28<1:08:22,  2.42s/it]
 52%|█████▏    | 1872/3566 [1:15:30<1:08:04,  2.41s/it]
                                                       
{'loss': 1.3789, 'learning_rate': 0.00019293152926926896, 'epoch': 0.52}

 52%|█████▏    | 1872/3566 [1:15:30<1:08:04,  2.41s/it]
 53%|█████▎    | 1873/3566 [1:15:33<1:06:33,  2.36s/it]
                                                       
{'loss': 1.541, 'learning_rate': 0.0001927503648585523, 'epoch': 0.53}

 53%|█████▎    | 1873/3566 [1:15:33<1:06:33,  2.36s/it]
 53%|█████▎    | 1874/3566 [1:15:35<1:06:33,  2.36s/it]
                                                       
{'loss': 1.5438, 'learning_rate': 0.00019256920640389137, 'epoch': 0.53}

 53%|█████▎    | 1874/3566 [1:15:35<1:06:33,  2.36s/it]
 53%|█████▎    | 1875/3566 [1:15:37<1:06:30,  2.36s/it]
                                                       
{'loss': 1.7398, 'learning_rate': 0.00019238805405411978, 'epoch': 0.53}

 53%|█████▎    | 1875/3566 [1:15:37<1:06:30,  2.36s/it]
 53%|█████▎    | 1876/3566 [1:15:40<1:06:07,  2.35s/it]
                                                       
{'loss': 1.4853, 'learning_rate': 0.00019220690795806615, 'epoch': 0.53}

 53%|█████▎    | 1876/3566 [1:15:40<1:06:07,  2.35s/it]
 53%|█████▎    | 1877/3566 [1:15:43<1:17:19,  2.75s/it]
                                                       
{'loss': 1.5107, 'learning_rate': 0.0001920257682645541, 'epoch': 0.53}

 53%|█████▎    | 1877/3566 [1:15:43<1:17:19,  2.75s/it]
 53%|█████▎    | 1878/3566 [1:15:46<1:17:02,  2.74s/it]
                                                       
{'loss': 1.5052, 'learning_rate': 0.00019184463512240182, 'epoch': 0.53}

 53%|█████▎    | 1878/3566 [1:15:46<1:17:02,  2.74s/it]
 53%|█████▎    | 1879/3566 [1:15:49<1:14:59,  2.67s/it]
                                                       
{'loss': 1.5421, 'learning_rate': 0.00019166350868042223, 'epoch': 0.53}

 53%|█████▎    | 1879/3566 [1:15:49<1:14:59,  2.67s/it]
 53%|█████▎    | 1880/3566 [1:15:51<1:11:30,  2.54s/it]
                                                       
{'loss': 1.4841, 'learning_rate': 0.00019148238908742272, 'epoch': 0.53}

 53%|█████▎    | 1880/3566 [1:15:51<1:11:30,  2.54s/it]
 53%|█████▎    | 1881/3566 [1:15:53<1:09:29,  2.47s/it]
                                                       
{'loss': 1.5578, 'learning_rate': 0.00019130127649220495, 'epoch': 0.53}

 53%|█████▎    | 1881/3566 [1:15:53<1:09:29,  2.47s/it]
 53%|█████▎    | 1882/3566 [1:15:56<1:08:12,  2.43s/it]
                                                       
{'loss': 1.5659, 'learning_rate': 0.000191120171043565, 'epoch': 0.53}

 53%|█████▎    | 1882/3566 [1:15:56<1:08:12,  2.43s/it]
 53%|█████▎    | 1883/3566 [1:15:58<1:07:01,  2.39s/it]
                                                       
{'loss': 1.6815, 'learning_rate': 0.00019093907289029295, 'epoch': 0.53}

 53%|█████▎    | 1883/3566 [1:15:58<1:07:01,  2.39s/it]
 53%|█████▎    | 1884/3566 [1:16:00<1:05:36,  2.34s/it]
                                                       
{'loss': 1.5356, 'learning_rate': 0.00019075798218117296, 'epoch': 0.53}

 53%|█████▎    | 1884/3566 [1:16:00<1:05:36,  2.34s/it]
 53%|█████▎    | 1885/3566 [1:16:02<1:05:22,  2.33s/it]
                                                       
{'loss': 1.5597, 'learning_rate': 0.00019057689906498305, 'epoch': 0.53}

 53%|█████▎    | 1885/3566 [1:16:02<1:05:22,  2.33s/it]
 53%|█████▎    | 1886/3566 [1:16:05<1:04:37,  2.31s/it]
                                                       
{'loss': 1.6631, 'learning_rate': 0.000190395823690495, 'epoch': 0.53}

 53%|█████▎    | 1886/3566 [1:16:05<1:04:37,  2.31s/it]
 53%|█████▎    | 1887/3566 [1:16:07<1:03:34,  2.27s/it]
                                                       
{'loss': 1.6313, 'learning_rate': 0.00019021475620647428, 'epoch': 0.53}

 53%|█████▎    | 1887/3566 [1:16:07<1:03:34,  2.27s/it]
 53%|█████▎    | 1888/3566 [1:16:09<1:05:34,  2.34s/it]
                                                       
{'loss': 1.4553, 'learning_rate': 0.00019003369676167975, 'epoch': 0.53}

 53%|█████▎    | 1888/3566 [1:16:09<1:05:34,  2.34s/it]
 53%|█████▎    | 1889/3566 [1:16:12<1:05:21,  2.34s/it]
                                                       
{'loss': 1.6443, 'learning_rate': 0.0001898526455048637, 'epoch': 0.53}

 53%|█████▎    | 1889/3566 [1:16:12<1:05:21,  2.34s/it]
 53%|█████▎    | 1890/3566 [1:16:14<1:04:44,  2.32s/it]
                                                       
{'loss': 1.5262, 'learning_rate': 0.00018967160258477186, 'epoch': 0.53}

 53%|█████▎    | 1890/3566 [1:16:14<1:04:44,  2.32s/it]
 53%|█████▎    | 1891/3566 [1:16:17<1:06:46,  2.39s/it]
                                                       
{'loss': 1.4328, 'learning_rate': 0.0001894905681501429, 'epoch': 0.53}

 53%|█████▎    | 1891/3566 [1:16:17<1:06:46,  2.39s/it]
 53%|█████▎    | 1892/3566 [1:16:19<1:04:34,  2.31s/it]
                                                       
{'loss': 1.4888, 'learning_rate': 0.00018930954234970868, 'epoch': 0.53}

 53%|█████▎    | 1892/3566 [1:16:19<1:04:34,  2.31s/it]
 53%|█████▎    | 1893/3566 [1:16:21<1:05:45,  2.36s/it]
                                                       
{'loss': 1.4733, 'learning_rate': 0.0001891285253321938, 'epoch': 0.53}

 53%|█████▎    | 1893/3566 [1:16:21<1:05:45,  2.36s/it]
 53%|█████▎    | 1894/3566 [1:16:24<1:06:56,  2.40s/it]
                                                       
{'loss': 1.5523, 'learning_rate': 0.00018894751724631576, 'epoch': 0.53}

 53%|█████▎    | 1894/3566 [1:16:24<1:06:56,  2.40s/it]
 53%|█████▎    | 1895/3566 [1:16:26<1:08:42,  2.47s/it]
                                                       
{'loss': 1.4814, 'learning_rate': 0.00018876651824078472, 'epoch': 0.53}

 53%|█████▎    | 1895/3566 [1:16:26<1:08:42,  2.47s/it]
 53%|█████▎    | 1896/3566 [1:16:29<1:08:22,  2.46s/it]
                                                       
{'loss': 1.5552, 'learning_rate': 0.00018858552846430336, 'epoch': 0.53}

 53%|█████▎    | 1896/3566 [1:16:29<1:08:22,  2.46s/it]
 53%|█████▎    | 1897/3566 [1:16:31<1:07:07,  2.41s/it]
                                                       
{'loss': 1.5165, 'learning_rate': 0.0001884045480655667, 'epoch': 0.53}

 53%|█████▎    | 1897/3566 [1:16:31<1:07:07,  2.41s/it]
 53%|█████▎    | 1898/3566 [1:16:33<1:07:36,  2.43s/it]
                                                       
{'loss': 1.6468, 'learning_rate': 0.00018822357719326224, 'epoch': 0.53}

 53%|█████▎    | 1898/3566 [1:16:33<1:07:36,  2.43s/it]
 53%|█████▎    | 1899/3566 [1:16:36<1:06:13,  2.38s/it]
                                                       
{'loss': 1.5167, 'learning_rate': 0.00018804261599606958, 'epoch': 0.53}

 53%|█████▎    | 1899/3566 [1:16:36<1:06:13,  2.38s/it]
 53%|█████▎    | 1900/3566 [1:16:38<1:04:38,  2.33s/it]
                                                       
{'loss': 1.5326, 'learning_rate': 0.00018786166462266018, 'epoch': 0.53}

 53%|█████▎    | 1900/3566 [1:16:38<1:04:38,  2.33s/it]
 53%|█████▎    | 1901/3566 [1:16:41<1:07:05,  2.42s/it]
                                                       
{'loss': 1.6156, 'learning_rate': 0.00018768072322169766, 'epoch': 0.53}

 53%|█████▎    | 1901/3566 [1:16:41<1:07:05,  2.42s/it]
 53%|█████▎    | 1902/3566 [1:16:43<1:05:18,  2.35s/it]
                                                       
{'loss': 1.4218, 'learning_rate': 0.00018749979194183737, 'epoch': 0.53}

 53%|█████▎    | 1902/3566 [1:16:43<1:05:18,  2.35s/it]
 53%|█████▎    | 1903/3566 [1:16:45<1:06:41,  2.41s/it]
                                                       
{'loss': 1.611, 'learning_rate': 0.00018731887093172635, 'epoch': 0.53}

 53%|█████▎    | 1903/3566 [1:16:45<1:06:41,  2.41s/it]
 53%|█████▎    | 1904/3566 [1:16:48<1:07:03,  2.42s/it]
                                                       
{'loss': 1.4635, 'learning_rate': 0.00018713796034000325, 'epoch': 0.53}

 53%|█████▎    | 1904/3566 [1:16:48<1:07:03,  2.42s/it]
 53%|█████▎    | 1905/3566 [1:16:50<1:06:49,  2.41s/it]
                                                       
{'loss': 1.5552, 'learning_rate': 0.000186957060315298, 'epoch': 0.53}

 53%|█████▎    | 1905/3566 [1:16:50<1:06:49,  2.41s/it]
 53%|█████▎    | 1906/3566 [1:16:52<1:04:57,  2.35s/it]
                                                       
{'loss': 1.5173, 'learning_rate': 0.000186776171006232, 'epoch': 0.53}

 53%|█████▎    | 1906/3566 [1:16:52<1:04:57,  2.35s/it]
 53%|█████▎    | 1907/3566 [1:16:55<1:06:26,  2.40s/it]
                                                       
{'loss': 1.4805, 'learning_rate': 0.00018659529256141784, 'epoch': 0.53}

 53%|█████▎    | 1907/3566 [1:16:55<1:06:26,  2.40s/it]
 54%|█████▎    | 1908/3566 [1:16:57<1:04:54,  2.35s/it]
                                                       
{'loss': 1.4122, 'learning_rate': 0.00018641442512945912, 'epoch': 0.54}

 54%|█████▎    | 1908/3566 [1:16:57<1:04:54,  2.35s/it]
 54%|█████▎    | 1909/3566 [1:16:59<1:05:26,  2.37s/it]
                                                       
{'loss': 1.4841, 'learning_rate': 0.00018623356885895048, 'epoch': 0.54}

 54%|█████▎    | 1909/3566 [1:17:00<1:05:26,  2.37s/it]
 54%|█████▎    | 1910/3566 [1:17:02<1:07:22,  2.44s/it]
                                                       
{'loss': 1.6319, 'learning_rate': 0.0001860527238984772, 'epoch': 0.54}

 54%|█████▎    | 1910/3566 [1:17:02<1:07:22,  2.44s/it]
 54%|█████▎    | 1911/3566 [1:17:04<1:06:04,  2.40s/it]
                                                       
{'loss': 1.5003, 'learning_rate': 0.0001858718903966154, 'epoch': 0.54}

 54%|█████▎    | 1911/3566 [1:17:04<1:06:04,  2.40s/it]
 54%|█████▎    | 1912/3566 [1:17:07<1:04:52,  2.35s/it]
                                                       
{'loss': 1.5432, 'learning_rate': 0.00018569106850193203, 'epoch': 0.54}

 54%|█████▎    | 1912/3566 [1:17:07<1:04:52,  2.35s/it]
 54%|█████▎    | 1913/3566 [1:17:09<1:04:23,  2.34s/it]
                                                       
{'loss': 1.3749, 'learning_rate': 0.000185510258362984, 'epoch': 0.54}

 54%|█████▎    | 1913/3566 [1:17:09<1:04:23,  2.34s/it]
 54%|█████▎    | 1914/3566 [1:17:12<1:08:01,  2.47s/it]
                                                       
{'loss': 1.6482, 'learning_rate': 0.00018532946012831894, 'epoch': 0.54}

 54%|█████▎    | 1914/3566 [1:17:12<1:08:01,  2.47s/it]
 54%|█████▎    | 1915/3566 [1:17:14<1:04:54,  2.36s/it]
                                                       
{'loss': 1.5161, 'learning_rate': 0.00018514867394647455, 'epoch': 0.54}

 54%|█████▎    | 1915/3566 [1:17:14<1:04:54,  2.36s/it]
 54%|█████▎    | 1916/3566 [1:17:16<1:05:51,  2.39s/it]
                                                       
{'loss': 1.5298, 'learning_rate': 0.00018496789996597866, 'epoch': 0.54}

 54%|█████▎    | 1916/3566 [1:17:16<1:05:51,  2.39s/it]
 54%|█████▍    | 1917/3566 [1:17:19<1:08:29,  2.49s/it]
                                                       
{'loss': 1.5455, 'learning_rate': 0.0001847871383353491, 'epoch': 0.54}

 54%|█████▍    | 1917/3566 [1:17:19<1:08:29,  2.49s/it]
 54%|█████▍    | 1918/3566 [1:17:21<1:06:28,  2.42s/it]
                                                       
{'loss': 1.5383, 'learning_rate': 0.00018460638920309345, 'epoch': 0.54}

 54%|█████▍    | 1918/3566 [1:17:21<1:06:28,  2.42s/it]
 54%|█████▍    | 1919/3566 [1:17:24<1:04:52,  2.36s/it]
                                                       
{'loss': 1.373, 'learning_rate': 0.0001844256527177092, 'epoch': 0.54}

 54%|█████▍    | 1919/3566 [1:17:24<1:04:52,  2.36s/it]
 54%|█████▍    | 1920/3566 [1:17:26<1:05:20,  2.38s/it]
                                                       
{'loss': 1.4938, 'learning_rate': 0.00018424492902768325, 'epoch': 0.54}

 54%|█████▍    | 1920/3566 [1:17:26<1:05:20,  2.38s/it]
 54%|█████▍    | 1921/3566 [1:17:28<1:03:35,  2.32s/it]
                                                       
{'loss': 1.4049, 'learning_rate': 0.00018406421828149217, 'epoch': 0.54}

 54%|█████▍    | 1921/3566 [1:17:28<1:03:35,  2.32s/it]
 54%|█████▍    | 1922/3566 [1:17:31<1:05:06,  2.38s/it]
                                                       
{'loss': 1.6455, 'learning_rate': 0.00018388352062760182, 'epoch': 0.54}

 54%|█████▍    | 1922/3566 [1:17:31<1:05:06,  2.38s/it]
 54%|█████▍    | 1923/3566 [1:17:33<1:05:24,  2.39s/it]
                                                       
{'loss': 1.5405, 'learning_rate': 0.00018370283621446722, 'epoch': 0.54}

 54%|█████▍    | 1923/3566 [1:17:33<1:05:24,  2.39s/it]
 54%|█████▍    | 1924/3566 [1:17:36<1:07:39,  2.47s/it]
                                                       
{'loss': 1.5581, 'learning_rate': 0.00018352216519053262, 'epoch': 0.54}

 54%|█████▍    | 1924/3566 [1:17:36<1:07:39,  2.47s/it]
 54%|█████▍    | 1925/3566 [1:17:38<1:07:00,  2.45s/it]
                                                       
{'loss': 1.558, 'learning_rate': 0.0001833415077042312, 'epoch': 0.54}

 54%|█████▍    | 1925/3566 [1:17:38<1:07:00,  2.45s/it]
 54%|█████▍    | 1926/3566 [1:17:40<1:06:32,  2.43s/it]
                                                       
{'loss': 1.43, 'learning_rate': 0.00018316086390398513, 'epoch': 0.54}

 54%|█████▍    | 1926/3566 [1:17:40<1:06:32,  2.43s/it]
 54%|█████▍    | 1927/3566 [1:17:43<1:06:47,  2.45s/it]
                                                       
{'loss': 1.5956, 'learning_rate': 0.00018298023393820527, 'epoch': 0.54}

 54%|█████▍    | 1927/3566 [1:17:43<1:06:47,  2.45s/it]
 54%|█████▍    | 1928/3566 [1:17:46<1:08:05,  2.49s/it]
                                                       
{'loss': 1.6198, 'learning_rate': 0.0001827996179552911, 'epoch': 0.54}

 54%|█████▍    | 1928/3566 [1:17:46<1:08:05,  2.49s/it]
 54%|█████▍    | 1929/3566 [1:17:48<1:06:40,  2.44s/it]
                                                       
{'loss': 1.3946, 'learning_rate': 0.00018261901610363052, 'epoch': 0.54}

 54%|█████▍    | 1929/3566 [1:17:48<1:06:40,  2.44s/it]
 54%|█████▍    | 1930/3566 [1:17:50<1:04:56,  2.38s/it]
                                                       
{'loss': 1.5476, 'learning_rate': 0.00018243842853160006, 'epoch': 0.54}

 54%|█████▍    | 1930/3566 [1:17:50<1:04:56,  2.38s/it]
 54%|█████▍    | 1931/3566 [1:17:52<1:04:11,  2.36s/it]
                                                       
{'loss': 1.4229, 'learning_rate': 0.0001822578553875643, 'epoch': 0.54}

 54%|█████▍    | 1931/3566 [1:17:52<1:04:11,  2.36s/it]
 54%|█████▍    | 1932/3566 [1:17:55<1:03:12,  2.32s/it]
                                                       
{'loss': 1.5386, 'learning_rate': 0.000182077296819876, 'epoch': 0.54}

 54%|█████▍    | 1932/3566 [1:17:55<1:03:12,  2.32s/it]
 54%|█████▍    | 1933/3566 [1:17:57<1:02:01,  2.28s/it]
                                                       
{'loss': 1.2868, 'learning_rate': 0.00018189675297687605, 'epoch': 0.54}

 54%|█████▍    | 1933/3566 [1:17:57<1:02:01,  2.28s/it]
 54%|█████▍    | 1934/3566 [1:17:59<1:02:52,  2.31s/it]
                                                       
{'loss': 1.472, 'learning_rate': 0.0001817162240068932, 'epoch': 0.54}

 54%|█████▍    | 1934/3566 [1:17:59<1:02:52,  2.31s/it]
 54%|█████▍    | 1935/3566 [1:18:02<1:05:42,  2.42s/it]
                                                       
{'loss': 1.5035, 'learning_rate': 0.00018153571005824395, 'epoch': 0.54}

 54%|█████▍    | 1935/3566 [1:18:02<1:05:42,  2.42s/it]
 54%|█████▍    | 1936/3566 [1:18:04<1:04:24,  2.37s/it]
                                                       
{'loss': 1.4659, 'learning_rate': 0.0001813552112792324, 'epoch': 0.54}

 54%|█████▍    | 1936/3566 [1:18:04<1:04:24,  2.37s/it]
 54%|█████▍    | 1937/3566 [1:18:07<1:04:12,  2.37s/it]
                                                       
{'loss': 1.6429, 'learning_rate': 0.00018117472781815035, 'epoch': 0.54}

 54%|█████▍    | 1937/3566 [1:18:07<1:04:12,  2.37s/it]
 54%|█████▍    | 1938/3566 [1:18:09<1:06:47,  2.46s/it]
                                                       
{'loss': 1.5322, 'learning_rate': 0.00018099425982327685, 'epoch': 0.54}

 54%|█████▍    | 1938/3566 [1:18:09<1:06:47,  2.46s/it]
 54%|█████▍    | 1939/3566 [1:18:11<1:04:34,  2.38s/it]
                                                       
{'loss': 1.5729, 'learning_rate': 0.00018081380744287834, 'epoch': 0.54}

 54%|█████▍    | 1939/3566 [1:18:11<1:04:34,  2.38s/it]
 54%|█████▍    | 1940/3566 [1:18:14<1:03:55,  2.36s/it]
                                                       
{'loss': 1.461, 'learning_rate': 0.0001806333708252084, 'epoch': 0.54}

 54%|█████▍    | 1940/3566 [1:18:14<1:03:55,  2.36s/it]
 54%|█████▍    | 1941/3566 [1:18:16<1:01:59,  2.29s/it]
                                                       
{'loss': 1.5112, 'learning_rate': 0.00018045295011850777, 'epoch': 0.54}

 54%|█████▍    | 1941/3566 [1:18:16<1:01:59,  2.29s/it]
 54%|█████▍    | 1942/3566 [1:18:18<1:04:51,  2.40s/it]
                                                       
{'loss': 1.4506, 'learning_rate': 0.0001802725454710039, 'epoch': 0.54}

 54%|█████▍    | 1942/3566 [1:18:18<1:04:51,  2.40s/it]
 54%|█████▍    | 1943/3566 [1:18:21<1:05:52,  2.44s/it]
                                                       
{'loss': 1.6647, 'learning_rate': 0.00018009215703091122, 'epoch': 0.54}

 54%|█████▍    | 1943/3566 [1:18:21<1:05:52,  2.44s/it]
 55%|█████▍    | 1944/3566 [1:18:23<1:05:56,  2.44s/it]
                                                       
{'loss': 1.6595, 'learning_rate': 0.00017991178494643076, 'epoch': 0.55}

 55%|█████▍    | 1944/3566 [1:18:23<1:05:56,  2.44s/it]
 55%|█████▍    | 1945/3566 [1:18:26<1:05:07,  2.41s/it]
                                                       
{'loss': 1.4811, 'learning_rate': 0.00017973142936575013, 'epoch': 0.55}

 55%|█████▍    | 1945/3566 [1:18:26<1:05:07,  2.41s/it]
 55%|█████▍    | 1946/3566 [1:18:28<1:04:13,  2.38s/it]
                                                       
{'loss': 1.628, 'learning_rate': 0.0001795510904370434, 'epoch': 0.55}

 55%|█████▍    | 1946/3566 [1:18:28<1:04:13,  2.38s/it]
 55%|█████▍    | 1947/3566 [1:18:31<1:05:25,  2.42s/it]
                                                       
{'loss': 1.5668, 'learning_rate': 0.00017937076830847097, 'epoch': 0.55}

 55%|█████▍    | 1947/3566 [1:18:31<1:05:25,  2.42s/it]
 55%|█████▍    | 1948/3566 [1:18:33<1:03:00,  2.34s/it]
                                                       
{'loss': 1.6493, 'learning_rate': 0.00017919046312817939, 'epoch': 0.55}

 55%|█████▍    | 1948/3566 [1:18:33<1:03:00,  2.34s/it]
 55%|█████▍    | 1949/3566 [1:18:35<1:01:45,  2.29s/it]
                                                       
{'loss': 1.5995, 'learning_rate': 0.00017901017504430133, 'epoch': 0.55}

 55%|█████▍    | 1949/3566 [1:18:35<1:01:45,  2.29s/it]
 55%|█████▍    | 1950/3566 [1:18:37<1:00:57,  2.26s/it]
                                                       
{'loss': 1.6209, 'learning_rate': 0.0001788299042049554, 'epoch': 0.55}

 55%|█████▍    | 1950/3566 [1:18:37<1:00:57,  2.26s/it]
 55%|█████▍    | 1951/3566 [1:18:40<1:04:55,  2.41s/it]
                                                       
{'loss': 1.6038, 'learning_rate': 0.00017864965075824605, 'epoch': 0.55}

 55%|█████▍    | 1951/3566 [1:18:40<1:04:55,  2.41s/it]
 55%|█████▍    | 1952/3566 [1:18:42<1:04:51,  2.41s/it]
                                                       
{'loss': 1.6302, 'learning_rate': 0.00017846941485226344, 'epoch': 0.55}

 55%|█████▍    | 1952/3566 [1:18:42<1:04:51,  2.41s/it]
 55%|█████▍    | 1953/3566 [1:18:45<1:05:41,  2.44s/it]
                                                       
{'loss': 1.6829, 'learning_rate': 0.00017828919663508315, 'epoch': 0.55}

 55%|█████▍    | 1953/3566 [1:18:45<1:05:41,  2.44s/it]
 55%|█████▍    | 1954/3566 [1:18:48<1:08:51,  2.56s/it]
                                                       
{'loss': 1.5378, 'learning_rate': 0.00017810899625476663, 'epoch': 0.55}

 55%|█████▍    | 1954/3566 [1:18:48<1:08:51,  2.56s/it]
 55%|█████▍    | 1955/3566 [1:18:50<1:07:32,  2.52s/it]
                                                       
{'loss': 1.4865, 'learning_rate': 0.00017792881385936035, 'epoch': 0.55}

 55%|█████▍    | 1955/3566 [1:18:50<1:07:32,  2.52s/it]
 55%|█████▍    | 1956/3566 [1:18:52<1:05:54,  2.46s/it]
                                                       
{'loss': 1.6057, 'learning_rate': 0.00017774864959689606, 'epoch': 0.55}

 55%|█████▍    | 1956/3566 [1:18:52<1:05:54,  2.46s/it]
 55%|█████▍    | 1957/3566 [1:18:55<1:03:31,  2.37s/it]
                                                       
{'loss': 1.6124, 'learning_rate': 0.00017756850361539062, 'epoch': 0.55}

 55%|█████▍    | 1957/3566 [1:18:55<1:03:31,  2.37s/it]
 55%|█████▍    | 1958/3566 [1:18:57<1:03:52,  2.38s/it]
                                                       
{'loss': 1.6264, 'learning_rate': 0.00017738837606284593, 'epoch': 0.55}

 55%|█████▍    | 1958/3566 [1:18:57<1:03:52,  2.38s/it]
 55%|█████▍    | 1959/3566 [1:19:00<1:05:54,  2.46s/it]
                                                       
{'loss': 1.53, 'learning_rate': 0.00017720826708724868, 'epoch': 0.55}

 55%|█████▍    | 1959/3566 [1:19:00<1:05:54,  2.46s/it]
 55%|█████▍    | 1960/3566 [1:19:02<1:03:30,  2.37s/it]
                                                       
{'loss': 1.5987, 'learning_rate': 0.00017702817683657042, 'epoch': 0.55}

 55%|█████▍    | 1960/3566 [1:19:02<1:03:30,  2.37s/it]
 55%|█████▍    | 1961/3566 [1:19:04<1:03:03,  2.36s/it]
                                                       
{'loss': 1.6489, 'learning_rate': 0.0001768481054587671, 'epoch': 0.55}

 55%|█████▍    | 1961/3566 [1:19:04<1:03:03,  2.36s/it]
 55%|█████▌    | 1962/3566 [1:19:06<1:02:19,  2.33s/it]
                                                       
{'loss': 1.5588, 'learning_rate': 0.00017666805310177937, 'epoch': 0.55}

 55%|█████▌    | 1962/3566 [1:19:06<1:02:19,  2.33s/it]
 55%|█████▌    | 1963/3566 [1:19:09<1:04:21,  2.41s/it]
                                                       
{'loss': 1.4548, 'learning_rate': 0.00017648801991353212, 'epoch': 0.55}

 55%|█████▌    | 1963/3566 [1:19:09<1:04:21,  2.41s/it]
 55%|█████▌    | 1964/3566 [1:19:11<1:03:08,  2.36s/it]
                                                       
{'loss': 1.4823, 'learning_rate': 0.00017630800604193455, 'epoch': 0.55}

 55%|█████▌    | 1964/3566 [1:19:11<1:03:08,  2.36s/it]
 55%|█████▌    | 1965/3566 [1:19:14<1:05:46,  2.46s/it]
                                                       
{'loss': 1.6019, 'learning_rate': 0.00017612801163488008, 'epoch': 0.55}

 55%|█████▌    | 1965/3566 [1:19:14<1:05:46,  2.46s/it]
 55%|█████▌    | 1966/3566 [1:19:17<1:09:11,  2.59s/it]
                                                       
{'loss': 1.6656, 'learning_rate': 0.00017594803684024593, 'epoch': 0.55}

 55%|█████▌    | 1966/3566 [1:19:17<1:09:11,  2.59s/it]
 55%|█████▌    | 1967/3566 [1:19:19<1:08:59,  2.59s/it]
                                                       
{'loss': 1.5728, 'learning_rate': 0.00017576808180589325, 'epoch': 0.55}

 55%|█████▌    | 1967/3566 [1:19:19<1:08:59,  2.59s/it]
 55%|█████▌    | 1968/3566 [1:19:22<1:07:06,  2.52s/it]
                                                       
{'loss': 1.5393, 'learning_rate': 0.0001755881466796673, 'epoch': 0.55}

 55%|█████▌    | 1968/3566 [1:19:22<1:07:06,  2.52s/it]
 55%|█████▌    | 1969/3566 [1:19:24<1:04:35,  2.43s/it]
                                                       
{'loss': 1.5718, 'learning_rate': 0.00017540823160939645, 'epoch': 0.55}

 55%|█████▌    | 1969/3566 [1:19:24<1:04:35,  2.43s/it]
 55%|█████▌    | 1970/3566 [1:19:26<1:04:41,  2.43s/it]
                                                       
{'loss': 1.6284, 'learning_rate': 0.000175228336742893, 'epoch': 0.55}

 55%|█████▌    | 1970/3566 [1:19:26<1:04:41,  2.43s/it]
 55%|█████▌    | 1971/3566 [1:19:29<1:04:51,  2.44s/it]
                                                       
{'loss': 1.6717, 'learning_rate': 0.0001750484622279524, 'epoch': 0.55}

 55%|█████▌    | 1971/3566 [1:19:29<1:04:51,  2.44s/it]
 55%|█████▌    | 1972/3566 [1:19:31<1:02:58,  2.37s/it]
                                                       
{'loss': 1.3874, 'learning_rate': 0.00017486860821235353, 'epoch': 0.55}

 55%|█████▌    | 1972/3566 [1:19:31<1:02:58,  2.37s/it]
 55%|█████▌    | 1973/3566 [1:19:34<1:04:58,  2.45s/it]
                                                       
{'loss': 1.4552, 'learning_rate': 0.00017468877484385847, 'epoch': 0.55}

 55%|█████▌    | 1973/3566 [1:19:34<1:04:58,  2.45s/it]
 55%|█████▌    | 1974/3566 [1:19:36<1:02:36,  2.36s/it]
                                                       
{'loss': 1.5111, 'learning_rate': 0.0001745089622702121, 'epoch': 0.55}

 55%|█████▌    | 1974/3566 [1:19:36<1:02:36,  2.36s/it]
 55%|█████▌    | 1975/3566 [1:19:38<1:03:35,  2.40s/it]
                                                       
{'loss': 1.5682, 'learning_rate': 0.00017432917063914244, 'epoch': 0.55}

 55%|█████▌    | 1975/3566 [1:19:38<1:03:35,  2.40s/it]
 55%|█████▌    | 1976/3566 [1:19:41<1:04:25,  2.43s/it]
                                                       
{'loss': 1.5648, 'learning_rate': 0.00017414940009836022, 'epoch': 0.55}

 55%|█████▌    | 1976/3566 [1:19:41<1:04:25,  2.43s/it]
 55%|█████▌    | 1977/3566 [1:19:43<1:03:10,  2.39s/it]
                                                       
{'loss': 1.4998, 'learning_rate': 0.00017396965079555886, 'epoch': 0.55}

 55%|█████▌    | 1977/3566 [1:19:43<1:03:10,  2.39s/it]
 55%|█████▌    | 1978/3566 [1:19:46<1:03:13,  2.39s/it]
                                                       
{'loss': 1.6988, 'learning_rate': 0.00017378992287841433, 'epoch': 0.55}

 55%|█████▌    | 1978/3566 [1:19:46<1:03:13,  2.39s/it]
 55%|█████▌    | 1979/3566 [1:19:48<1:05:04,  2.46s/it]
                                                       
{'loss': 1.5206, 'learning_rate': 0.00017361021649458497, 'epoch': 0.55}

 55%|█████▌    | 1979/3566 [1:19:48<1:05:04,  2.46s/it]
 56%|█████▌    | 1980/3566 [1:19:51<1:05:04,  2.46s/it]
                                                       
{'loss': 1.5095, 'learning_rate': 0.00017343053179171155, 'epoch': 0.56}

 56%|█████▌    | 1980/3566 [1:19:51<1:05:04,  2.46s/it]
 56%|█████▌    | 1981/3566 [1:19:53<1:03:52,  2.42s/it]
                                                       
{'loss': 1.4581, 'learning_rate': 0.00017325086891741687, 'epoch': 0.56}

 56%|█████▌    | 1981/3566 [1:19:53<1:03:52,  2.42s/it]
 56%|█████▌    | 1982/3566 [1:19:55<1:01:56,  2.35s/it]
                                                       
{'loss': 1.5087, 'learning_rate': 0.000173071228019306, 'epoch': 0.56}

 56%|█████▌    | 1982/3566 [1:19:55<1:01:56,  2.35s/it]
 56%|█████▌    | 1983/3566 [1:19:57<1:01:11,  2.32s/it]
                                                       
{'loss': 1.5442, 'learning_rate': 0.00017289160924496578, 'epoch': 0.56}

 56%|█████▌    | 1983/3566 [1:19:57<1:01:11,  2.32s/it]
 56%|█████▌    | 1984/3566 [1:20:00<1:02:17,  2.36s/it]
                                                       
{'loss': 1.5898, 'learning_rate': 0.00017271201274196495, 'epoch': 0.56}

 56%|█████▌    | 1984/3566 [1:20:00<1:02:17,  2.36s/it]
 56%|█████▌    | 1985/3566 [1:20:02<1:00:27,  2.29s/it]
                                                       
{'loss': 1.4531, 'learning_rate': 0.00017253243865785397, 'epoch': 0.56}

 56%|█████▌    | 1985/3566 [1:20:02<1:00:27,  2.29s/it]
 56%|█████▌    | 1986/3566 [1:20:04<1:00:11,  2.29s/it]
                                                       
{'loss': 1.5352, 'learning_rate': 0.0001723528871401648, 'epoch': 0.56}

 56%|█████▌    | 1986/3566 [1:20:04<1:00:11,  2.29s/it]
 56%|█████▌    | 1987/3566 [1:20:07<1:02:47,  2.39s/it]
                                                       
{'loss': 1.4362, 'learning_rate': 0.0001721733583364109, 'epoch': 0.56}

 56%|█████▌    | 1987/3566 [1:20:07<1:02:47,  2.39s/it]
 56%|█████▌    | 1988/3566 [1:20:09<1:02:29,  2.38s/it]
                                                       
{'loss': 1.422, 'learning_rate': 0.00017199385239408712, 'epoch': 0.56}

 56%|█████▌    | 1988/3566 [1:20:09<1:02:29,  2.38s/it]
 56%|█████▌    | 1989/3566 [1:20:12<1:01:53,  2.35s/it]
                                                       
{'loss': 1.5783, 'learning_rate': 0.00017181436946066947, 'epoch': 0.56}

 56%|█████▌    | 1989/3566 [1:20:12<1:01:53,  2.35s/it]
 56%|█████▌    | 1990/3566 [1:20:14<1:01:08,  2.33s/it]
                                                       
{'loss': 1.5079, 'learning_rate': 0.0001716349096836151, 'epoch': 0.56}

 56%|█████▌    | 1990/3566 [1:20:14<1:01:08,  2.33s/it]
 56%|█████▌    | 1991/3566 [1:20:16<1:00:00,  2.29s/it]
                                                       
{'loss': 1.6901, 'learning_rate': 0.00017145547321036205, 'epoch': 0.56}

 56%|█████▌    | 1991/3566 [1:20:16<1:00:00,  2.29s/it]
 56%|█████▌    | 1992/3566 [1:20:18<1:00:01,  2.29s/it]
                                                       
{'loss': 1.764, 'learning_rate': 0.0001712760601883293, 'epoch': 0.56}

 56%|█████▌    | 1992/3566 [1:20:18<1:00:01,  2.29s/it]
 56%|█████▌    | 1993/3566 [1:20:21<1:00:44,  2.32s/it]
                                                       
{'loss': 1.6544, 'learning_rate': 0.00017109667076491657, 'epoch': 0.56}

 56%|█████▌    | 1993/3566 [1:20:21<1:00:44,  2.32s/it]
 56%|█████▌    | 1994/3566 [1:20:23<1:04:09,  2.45s/it]
                                                       
{'loss': 1.5159, 'learning_rate': 0.00017091730508750412, 'epoch': 0.56}

 56%|█████▌    | 1994/3566 [1:20:23<1:04:09,  2.45s/it]
 56%|█████▌    | 1995/3566 [1:20:26<1:03:05,  2.41s/it]
                                                       
{'loss': 1.573, 'learning_rate': 0.0001707379633034528, 'epoch': 0.56}

 56%|█████▌    | 1995/3566 [1:20:26<1:03:05,  2.41s/it]
 56%|█████▌    | 1996/3566 [1:20:29<1:07:29,  2.58s/it]
                                                       
{'loss': 1.6284, 'learning_rate': 0.00017055864556010357, 'epoch': 0.56}

 56%|█████▌    | 1996/3566 [1:20:29<1:07:29,  2.58s/it]
 56%|█████▌    | 1997/3566 [1:20:31<1:07:08,  2.57s/it]
                                                       
{'loss': 1.5416, 'learning_rate': 0.0001703793520047781, 'epoch': 0.56}

 56%|█████▌    | 1997/3566 [1:20:31<1:07:08,  2.57s/it]
 56%|█████▌    | 1998/3566 [1:20:34<1:07:35,  2.59s/it]
                                                       
{'loss': 1.4663, 'learning_rate': 0.00017020008278477786, 'epoch': 0.56}

 56%|█████▌    | 1998/3566 [1:20:34<1:07:35,  2.59s/it]
 56%|█████▌    | 1999/3566 [1:20:37<1:07:54,  2.60s/it]
                                                       
{'loss': 1.6156, 'learning_rate': 0.0001700208380473843, 'epoch': 0.56}

 56%|█████▌    | 1999/3566 [1:20:37<1:07:54,  2.60s/it]
 56%|█████▌    | 2000/3566 [1:20:39<1:04:02,  2.45s/it]
                                                       
{'loss': 1.4967, 'learning_rate': 0.0001698416179398589, 'epoch': 0.56}

 56%|█████▌    | 2000/3566 [1:20:39<1:04:02,  2.45s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(

 56%|█████▌    | 2001/3566 [1:20:41<1:05:49,  2.52s/it]
                                                       
{'loss': 1.351, 'learning_rate': 0.00016966242260944286, 'epoch': 0.56}

 56%|█████▌    | 2001/3566 [1:20:41<1:05:49,  2.52s/it]
 56%|█████▌    | 2002/3566 [1:20:43<1:01:57,  2.38s/it]
                                                       
{'loss': 1.4819, 'learning_rate': 0.00016948325220335702, 'epoch': 0.56}

 56%|█████▌    | 2002/3566 [1:20:43<1:01:57,  2.38s/it]
 56%|█████▌    | 2003/3566 [1:20:46<1:05:33,  2.52s/it]
                                                       
{'loss': 1.5242, 'learning_rate': 0.00016930410686880182, 'epoch': 0.56}

 56%|█████▌    | 2003/3566 [1:20:46<1:05:33,  2.52s/it]
 56%|█████▌    | 2004/3566 [1:20:48<1:02:28,  2.40s/it]
                                                       
{'loss': 1.4244, 'learning_rate': 0.00016912498675295684, 'epoch': 0.56}

 56%|█████▌    | 2004/3566 [1:20:48<1:02:28,  2.40s/it]
 56%|█████▌    | 2005/3566 [1:20:51<1:01:50,  2.38s/it]
                                                       
{'loss': 1.4183, 'learning_rate': 0.00016894589200298123, 'epoch': 0.56}

 56%|█████▌    | 2005/3566 [1:20:51<1:01:50,  2.38s/it]
 56%|█████▋    | 2006/3566 [1:20:53<1:02:22,  2.40s/it]
                                                       
{'loss': 1.6765, 'learning_rate': 0.00016876682276601321, 'epoch': 0.56}

 56%|█████▋    | 2006/3566 [1:20:53<1:02:22,  2.40s/it]
 56%|█████▋    | 2007/3566 [1:20:56<1:02:34,  2.41s/it]
                                                       
{'loss': 1.5431, 'learning_rate': 0.00016858777918917, 'epoch': 0.56}

 56%|█████▋    | 2007/3566 [1:20:56<1:02:34,  2.41s/it]
 56%|█████▋    | 2008/3566 [1:20:58<1:02:28,  2.41s/it]
                                                       
{'loss': 1.5091, 'learning_rate': 0.0001684087614195478, 'epoch': 0.56}

 56%|█████▋    | 2008/3566 [1:20:58<1:02:28,  2.41s/it]
 56%|█████▋    | 2009/3566 [1:21:01<1:07:25,  2.60s/it]
                                                       
{'loss': 1.5176, 'learning_rate': 0.00016822976960422152, 'epoch': 0.56}

 56%|█████▋    | 2009/3566 [1:21:01<1:07:25,  2.60s/it]
 56%|█████▋    | 2010/3566 [1:21:03<1:06:39,  2.57s/it]
                                                       
{'loss': 1.5882, 'learning_rate': 0.00016805080389024473, 'epoch': 0.56}

 56%|█████▋    | 2010/3566 [1:21:03<1:06:39,  2.57s/it]
 56%|█████▋    | 2011/3566 [1:21:06<1:06:25,  2.56s/it]
                                                       
{'loss': 1.4128, 'learning_rate': 0.0001678718644246498, 'epoch': 0.56}

 56%|█████▋    | 2011/3566 [1:21:06<1:06:25,  2.56s/it]
 56%|█████▋    | 2012/3566 [1:21:08<1:04:28,  2.49s/it]
                                                       
{'loss': 1.5414, 'learning_rate': 0.00016769295135444725, 'epoch': 0.56}

 56%|█████▋    | 2012/3566 [1:21:08<1:04:28,  2.49s/it]
 56%|█████▋    | 2013/3566 [1:21:11<1:04:16,  2.48s/it]
                                                       
{'loss': 1.4527, 'learning_rate': 0.00016751406482662606, 'epoch': 0.56}

 56%|█████▋    | 2013/3566 [1:21:11<1:04:16,  2.48s/it]
 56%|█████▋    | 2014/3566 [1:21:13<1:03:18,  2.45s/it]
                                                       
{'loss': 1.5438, 'learning_rate': 0.0001673352049881533, 'epoch': 0.56}

 56%|█████▋    | 2014/3566 [1:21:13<1:03:18,  2.45s/it]
 57%|█████▋    | 2015/3566 [1:21:15<1:02:16,  2.41s/it]
                                                       
{'loss': 1.6425, 'learning_rate': 0.00016715637198597426, 'epoch': 0.57}

 57%|█████▋    | 2015/3566 [1:21:15<1:02:16,  2.41s/it]
 57%|█████▋    | 2016/3566 [1:21:18<1:00:20,  2.34s/it]
                                                       
{'loss': 1.5259, 'learning_rate': 0.00016697756596701212, 'epoch': 0.57}

 57%|█████▋    | 2016/3566 [1:21:18<1:00:20,  2.34s/it]
 57%|█████▋    | 2017/3566 [1:21:20<1:00:15,  2.33s/it]
                                                       
{'loss': 1.5631, 'learning_rate': 0.0001667987870781678, 'epoch': 0.57}

 57%|█████▋    | 2017/3566 [1:21:20<1:00:15,  2.33s/it]
 57%|█████▋    | 2018/3566 [1:21:22<1:01:22,  2.38s/it]
                                                       
{'loss': 1.5013, 'learning_rate': 0.00016662003546631996, 'epoch': 0.57}

 57%|█████▋    | 2018/3566 [1:21:22<1:01:22,  2.38s/it]
 57%|█████▋    | 2019/3566 [1:21:25<59:58,  2.33s/it]  
                                                     
{'loss': 1.5068, 'learning_rate': 0.00016644131127832503, 'epoch': 0.57}

 57%|█████▋    | 2019/3566 [1:21:25<59:58,  2.33s/it]
 57%|█████▋    | 2020/3566 [1:21:27<1:00:25,  2.34s/it]
                                                       
{'loss': 1.5089, 'learning_rate': 0.00016626261466101667, 'epoch': 0.57}

 57%|█████▋    | 2020/3566 [1:21:27<1:00:25,  2.34s/it]
 57%|█████▋    | 2021/3566 [1:21:29<59:24,  2.31s/it]  
                                                     
{'loss': 1.3908, 'learning_rate': 0.0001660839457612061, 'epoch': 0.57}

 57%|█████▋    | 2021/3566 [1:21:29<59:24,  2.31s/it]
 57%|█████▋    | 2022/3566 [1:21:32<1:00:06,  2.34s/it]
                                                       
{'loss': 1.5975, 'learning_rate': 0.0001659053047256815, 'epoch': 0.57}

 57%|█████▋    | 2022/3566 [1:21:32<1:00:06,  2.34s/it]
 57%|█████▋    | 2023/3566 [1:21:34<1:00:48,  2.36s/it]
                                                       
{'loss': 1.4961, 'learning_rate': 0.00016572669170120846, 'epoch': 0.57}

 57%|█████▋    | 2023/3566 [1:21:34<1:00:48,  2.36s/it]
 57%|█████▋    | 2024/3566 [1:21:36<1:00:20,  2.35s/it]
                                                       
{'loss': 1.5883, 'learning_rate': 0.00016554810683452927, 'epoch': 0.57}

 57%|█████▋    | 2024/3566 [1:21:36<1:00:20,  2.35s/it]
 57%|█████▋    | 2025/3566 [1:21:39<59:17,  2.31s/it]  
                                                     
{'loss': 1.5551, 'learning_rate': 0.0001653695502723634, 'epoch': 0.57}

 57%|█████▋    | 2025/3566 [1:21:39<59:17,  2.31s/it]
 57%|█████▋    | 2026/3566 [1:21:41<1:00:20,  2.35s/it]
                                                       
{'loss': 1.5881, 'learning_rate': 0.00016519102216140682, 'epoch': 0.57}

 57%|█████▋    | 2026/3566 [1:21:41<1:00:20,  2.35s/it]
 57%|█████▋    | 2027/3566 [1:21:43<1:00:17,  2.35s/it]
                                                       
{'loss': 1.4807, 'learning_rate': 0.00016501252264833222, 'epoch': 0.57}

 57%|█████▋    | 2027/3566 [1:21:43<1:00:17,  2.35s/it]
 57%|█████▋    | 2028/3566 [1:21:46<1:02:03,  2.42s/it]
                                                       
{'loss': 1.5498, 'learning_rate': 0.0001648340518797888, 'epoch': 0.57}

 57%|█████▋    | 2028/3566 [1:21:46<1:02:03,  2.42s/it]
 57%|█████▋    | 2029/3566 [1:21:49<1:02:42,  2.45s/it]
                                                       
{'loss': 1.6116, 'learning_rate': 0.00016465561000240204, 'epoch': 0.57}

 57%|█████▋    | 2029/3566 [1:21:49<1:02:42,  2.45s/it]
 57%|█████▋    | 2030/3566 [1:21:51<1:01:37,  2.41s/it]
                                                       
{'loss': 1.5286, 'learning_rate': 0.00016447719716277382, 'epoch': 0.57}

 57%|█████▋    | 2030/3566 [1:21:51<1:01:37,  2.41s/it]
 57%|█████▋    | 2031/3566 [1:21:53<1:00:59,  2.38s/it]
                                                       
{'loss': 1.4174, 'learning_rate': 0.0001642988135074821, 'epoch': 0.57}

 57%|█████▋    | 2031/3566 [1:21:53<1:00:59,  2.38s/it]
 57%|█████▋    | 2032/3566 [1:21:56<1:00:47,  2.38s/it]
                                                       
{'loss': 1.5826, 'learning_rate': 0.0001641204591830809, 'epoch': 0.57}

 57%|█████▋    | 2032/3566 [1:21:56<1:00:47,  2.38s/it]
 57%|█████▋    | 2033/3566 [1:21:58<1:01:07,  2.39s/it]
                                                       
{'loss': 1.5428, 'learning_rate': 0.00016394213433610012, 'epoch': 0.57}

 57%|█████▋    | 2033/3566 [1:21:58<1:01:07,  2.39s/it]
 57%|█████▋    | 2034/3566 [1:22:00<1:00:54,  2.39s/it]
                                                       
{'loss': 1.4801, 'learning_rate': 0.0001637638391130454, 'epoch': 0.57}

 57%|█████▋    | 2034/3566 [1:22:00<1:00:54,  2.39s/it]
 57%|█████▋    | 2035/3566 [1:22:03<1:01:17,  2.40s/it]
                                                       
{'loss': 1.6449, 'learning_rate': 0.00016358557366039807, 'epoch': 0.57}

 57%|█████▋    | 2035/3566 [1:22:03<1:01:17,  2.40s/it]
 57%|█████▋    | 2036/3566 [1:22:05<1:00:53,  2.39s/it]
                                                       
{'loss': 1.5617, 'learning_rate': 0.00016340733812461507, 'epoch': 0.57}

 57%|█████▋    | 2036/3566 [1:22:05<1:00:53,  2.39s/it]
 57%|█████▋    | 2037/3566 [1:22:08<1:02:25,  2.45s/it]
                                                       
{'loss': 1.4804, 'learning_rate': 0.00016322913265212865, 'epoch': 0.57}

 57%|█████▋    | 2037/3566 [1:22:08<1:02:25,  2.45s/it]
 57%|█████▋    | 2038/3566 [1:22:10<1:01:43,  2.42s/it]
                                                       
{'loss': 1.5622, 'learning_rate': 0.00016305095738934638, 'epoch': 0.57}

 57%|█████▋    | 2038/3566 [1:22:10<1:01:43,  2.42s/it]
 57%|█████▋    | 2039/3566 [1:22:12<1:00:44,  2.39s/it]
                                                       
{'loss': 1.6346, 'learning_rate': 0.00016287281248265117, 'epoch': 0.57}

 57%|█████▋    | 2039/3566 [1:22:12<1:00:44,  2.39s/it]
 57%|█████▋    | 2040/3566 [1:22:15<1:01:26,  2.42s/it]
                                                       
{'loss': 1.3748, 'learning_rate': 0.0001626946980784008, 'epoch': 0.57}

 57%|█████▋    | 2040/3566 [1:22:15<1:01:26,  2.42s/it]
 57%|█████▋    | 2041/3566 [1:22:17<59:51,  2.35s/it]  
                                                     
{'loss': 1.6151, 'learning_rate': 0.00016251661432292809, 'epoch': 0.57}

 57%|█████▋    | 2041/3566 [1:22:17<59:51,  2.35s/it]
 57%|█████▋    | 2042/3566 [1:22:20<1:02:00,  2.44s/it]
                                                       
{'loss': 1.5742, 'learning_rate': 0.00016233856136254056, 'epoch': 0.57}

 57%|█████▋    | 2042/3566 [1:22:20<1:02:00,  2.44s/it]
 57%|█████▋    | 2043/3566 [1:22:22<1:03:42,  2.51s/it]
                                                       
{'loss': 1.566, 'learning_rate': 0.0001621605393435206, 'epoch': 0.57}

 57%|█████▋    | 2043/3566 [1:22:22<1:03:42,  2.51s/it]
 57%|█████▋    | 2044/3566 [1:22:25<1:03:57,  2.52s/it]
                                                       
{'loss': 1.5973, 'learning_rate': 0.000161982548412125, 'epoch': 0.57}

 57%|█████▋    | 2044/3566 [1:22:25<1:03:57,  2.52s/it]
 57%|█████▋    | 2045/3566 [1:22:27<1:02:38,  2.47s/it]
                                                       
{'loss': 1.6233, 'learning_rate': 0.00016180458871458523, 'epoch': 0.57}

 57%|█████▋    | 2045/3566 [1:22:27<1:02:38,  2.47s/it]
 57%|█████▋    | 2046/3566 [1:22:30<1:03:09,  2.49s/it]
                                                       
{'loss': 1.6623, 'learning_rate': 0.00016162666039710693, 'epoch': 0.57}

 57%|█████▋    | 2046/3566 [1:22:30<1:03:09,  2.49s/it]
 57%|█████▋    | 2047/3566 [1:22:32<1:02:40,  2.48s/it]
                                                       
{'loss': 1.662, 'learning_rate': 0.00016144876360586996, 'epoch': 0.57}

 57%|█████▋    | 2047/3566 [1:22:32<1:02:40,  2.48s/it]
 57%|█████▋    | 2048/3566 [1:22:34<1:00:04,  2.37s/it]
                                                       
{'loss': 1.3829, 'learning_rate': 0.00016127089848702833, 'epoch': 0.57}

 57%|█████▋    | 2048/3566 [1:22:34<1:00:04,  2.37s/it]
 57%|█████▋    | 2049/3566 [1:22:37<58:57,  2.33s/it]  
                                                     
{'loss': 1.5952, 'learning_rate': 0.00016109306518671004, 'epoch': 0.57}

 57%|█████▋    | 2049/3566 [1:22:37<58:57,  2.33s/it]
 57%|█████▋    | 2050/3566 [1:22:39<58:20,  2.31s/it]
                                                     
{'loss': 1.5162, 'learning_rate': 0.0001609152638510169, 'epoch': 0.57}

 57%|█████▋    | 2050/3566 [1:22:39<58:20,  2.31s/it]
 58%|█████▊    | 2051/3566 [1:22:41<57:12,  2.27s/it]
                                                     
{'loss': 1.5544, 'learning_rate': 0.00016073749462602464, 'epoch': 0.58}

 58%|█████▊    | 2051/3566 [1:22:41<57:12,  2.27s/it]
 58%|█████▊    | 2052/3566 [1:22:44<58:36,  2.32s/it]
                                                     
{'loss': 1.5731, 'learning_rate': 0.00016055975765778214, 'epoch': 0.58}

 58%|█████▊    | 2052/3566 [1:22:44<58:36,  2.32s/it]
 58%|█████▊    | 2053/3566 [1:22:46<59:14,  2.35s/it]
                                                     
{'loss': 1.5027, 'learning_rate': 0.00016038205309231243, 'epoch': 0.58}

 58%|█████▊    | 2053/3566 [1:22:46<59:14,  2.35s/it]
 58%|█████▊    | 2054/3566 [1:22:49<1:03:45,  2.53s/it]
                                                       
{'loss': 1.5698, 'learning_rate': 0.00016020438107561147, 'epoch': 0.58}

 58%|█████▊    | 2054/3566 [1:22:49<1:03:45,  2.53s/it]
 58%|█████▊    | 2055/3566 [1:22:51<1:03:33,  2.52s/it]
                                                       
{'loss': 1.55, 'learning_rate': 0.00016002674175364854, 'epoch': 0.58}

 58%|█████▊    | 2055/3566 [1:22:51<1:03:33,  2.52s/it]
 58%|█████▊    | 2056/3566 [1:22:54<1:01:52,  2.46s/it]
                                                       
{'loss': 1.5245, 'learning_rate': 0.00015984913527236616, 'epoch': 0.58}

 58%|█████▊    | 2056/3566 [1:22:54<1:01:52,  2.46s/it]
 58%|█████▊    | 2057/3566 [1:22:56<59:52,  2.38s/it]  
                                                     
{'loss': 1.3925, 'learning_rate': 0.00015967156177767978, 'epoch': 0.58}

 58%|█████▊    | 2057/3566 [1:22:56<59:52,  2.38s/it]
 58%|█████▊    | 2058/3566 [1:22:58<1:01:27,  2.45s/it]
                                                       
{'loss': 1.4424, 'learning_rate': 0.00015949402141547786, 'epoch': 0.58}

 58%|█████▊    | 2058/3566 [1:22:59<1:01:27,  2.45s/it]
 58%|█████▊    | 2059/3566 [1:23:01<1:00:08,  2.39s/it]
                                                       
{'loss': 1.3824, 'learning_rate': 0.0001593165143316216, 'epoch': 0.58}

 58%|█████▊    | 2059/3566 [1:23:01<1:00:08,  2.39s/it]
 58%|█████▊    | 2060/3566 [1:23:03<1:00:05,  2.39s/it]
                                                       
{'loss': 1.4309, 'learning_rate': 0.00015913904067194472, 'epoch': 0.58}

 58%|█████▊    | 2060/3566 [1:23:03<1:00:05,  2.39s/it]
 58%|█████▊    | 2061/3566 [1:23:06<59:42,  2.38s/it]  
                                                     
{'loss': 1.6169, 'learning_rate': 0.00015896160058225363, 'epoch': 0.58}

 58%|█████▊    | 2061/3566 [1:23:06<59:42,  2.38s/it]
 58%|█████▊    | 2062/3566 [1:23:08<59:27,  2.37s/it]
                                                     
{'loss': 1.4269, 'learning_rate': 0.00015878419420832716, 'epoch': 0.58}

 58%|█████▊    | 2062/3566 [1:23:08<59:27,  2.37s/it]
 58%|█████▊    | 2063/3566 [1:23:10<57:12,  2.28s/it]
                                                     
{'loss': 1.5658, 'learning_rate': 0.00015860682169591635, 'epoch': 0.58}

 58%|█████▊    | 2063/3566 [1:23:10<57:12,  2.28s/it]
 58%|█████▊    | 2064/3566 [1:23:13<1:00:32,  2.42s/it]
                                                       
{'loss': 1.6094, 'learning_rate': 0.00015842948319074457, 'epoch': 0.58}

 58%|█████▊    | 2064/3566 [1:23:13<1:00:32,  2.42s/it]
 58%|█████▊    | 2065/3566 [1:23:15<1:01:34,  2.46s/it]
                                                       
{'loss': 1.6853, 'learning_rate': 0.00015825217883850705, 'epoch': 0.58}

 58%|█████▊    | 2065/3566 [1:23:15<1:01:34,  2.46s/it]
 58%|█████▊    | 2066/3566 [1:23:18<1:01:33,  2.46s/it]
                                                       
{'loss': 1.4805, 'learning_rate': 0.00015807490878487105, 'epoch': 0.58}

 58%|█████▊    | 2066/3566 [1:23:18<1:01:33,  2.46s/it]
 58%|█████▊    | 2067/3566 [1:23:21<1:06:43,  2.67s/it]
                                                       
{'loss': 1.5545, 'learning_rate': 0.00015789767317547575, 'epoch': 0.58}

 58%|█████▊    | 2067/3566 [1:23:21<1:06:43,  2.67s/it]
 58%|█████▊    | 2068/3566 [1:23:23<1:03:31,  2.54s/it]
                                                       
{'loss': 1.5423, 'learning_rate': 0.00015772047215593192, 'epoch': 0.58}

 58%|█████▊    | 2068/3566 [1:23:23<1:03:31,  2.54s/it]
 58%|█████▊    | 2069/3566 [1:23:26<1:02:31,  2.51s/it]
                                                       
{'loss': 1.5624, 'learning_rate': 0.00015754330587182196, 'epoch': 0.58}

 58%|█████▊    | 2069/3566 [1:23:26<1:02:31,  2.51s/it]
 58%|█████▊    | 2070/3566 [1:23:28<1:02:15,  2.50s/it]
                                                       
{'loss': 1.5615, 'learning_rate': 0.00015736617446869964, 'epoch': 0.58}

 58%|█████▊    | 2070/3566 [1:23:28<1:02:15,  2.50s/it]
 58%|█████▊    | 2071/3566 [1:23:30<1:01:40,  2.47s/it]
                                                       
{'loss': 1.511, 'learning_rate': 0.0001571890780920903, 'epoch': 0.58}

 58%|█████▊    | 2071/3566 [1:23:30<1:01:40,  2.47s/it]
 58%|█████▊    | 2072/3566 [1:23:33<1:01:28,  2.47s/it]
                                                       
{'loss': 1.5807, 'learning_rate': 0.00015701201688749015, 'epoch': 0.58}

 58%|█████▊    | 2072/3566 [1:23:33<1:01:28,  2.47s/it]
 58%|█████▊    | 2073/3566 [1:23:35<59:33,  2.39s/it]  
                                                     
{'loss': 1.5503, 'learning_rate': 0.0001568349910003668, 'epoch': 0.58}

 58%|█████▊    | 2073/3566 [1:23:35<59:33,  2.39s/it]
 58%|█████▊    | 2074/3566 [1:23:38<1:00:36,  2.44s/it]
                                                       
{'loss': 1.4604, 'learning_rate': 0.00015665800057615875, 'epoch': 0.58}

 58%|█████▊    | 2074/3566 [1:23:38<1:00:36,  2.44s/it]
 58%|█████▊    | 2075/3566 [1:23:40<59:23,  2.39s/it]  
                                                     
{'loss': 1.5833, 'learning_rate': 0.00015648104576027538, 'epoch': 0.58}

 58%|█████▊    | 2075/3566 [1:23:40<59:23,  2.39s/it]
 58%|█████▊    | 2076/3566 [1:23:42<1:00:26,  2.43s/it]
                                                       
{'loss': 1.5526, 'learning_rate': 0.00015630412669809677, 'epoch': 0.58}

 58%|█████▊    | 2076/3566 [1:23:42<1:00:26,  2.43s/it]
 58%|█████▊    | 2077/3566 [1:23:46<1:06:47,  2.69s/it]
                                                       
{'loss': 1.5452, 'learning_rate': 0.00015612724353497365, 'epoch': 0.58}

 58%|█████▊    | 2077/3566 [1:23:46<1:06:47,  2.69s/it]
 58%|█████▊    | 2078/3566 [1:23:48<1:05:13,  2.63s/it]
                                                       
{'loss': 1.4504, 'learning_rate': 0.00015595039641622726, 'epoch': 0.58}

 58%|█████▊    | 2078/3566 [1:23:48<1:05:13,  2.63s/it]
 58%|█████▊    | 2079/3566 [1:23:51<1:02:42,  2.53s/it]
                                                       
{'loss': 1.5726, 'learning_rate': 0.00015577358548714922, 'epoch': 0.58}

 58%|█████▊    | 2079/3566 [1:23:51<1:02:42,  2.53s/it]
 58%|█████▊    | 2080/3566 [1:23:53<1:01:31,  2.48s/it]
                                                       
{'loss': 1.5934, 'learning_rate': 0.0001555968108930014, 'epoch': 0.58}

 58%|█████▊    | 2080/3566 [1:23:53<1:01:31,  2.48s/it]
 58%|█████▊    | 2081/3566 [1:23:55<1:00:49,  2.46s/it]
                                                       
{'loss': 1.5744, 'learning_rate': 0.00015542007277901594, 'epoch': 0.58}

 58%|█████▊    | 2081/3566 [1:23:55<1:00:49,  2.46s/it]
 58%|█████▊    | 2082/3566 [1:23:58<1:02:35,  2.53s/it]
                                                       
{'loss': 1.577, 'learning_rate': 0.00015524337129039484, 'epoch': 0.58}

 58%|█████▊    | 2082/3566 [1:23:58<1:02:35,  2.53s/it]
 58%|█████▊    | 2083/3566 [1:24:00<1:00:56,  2.47s/it]
                                                       
{'loss': 1.5272, 'learning_rate': 0.00015506670657231008, 'epoch': 0.58}

 58%|█████▊    | 2083/3566 [1:24:00<1:00:56,  2.47s/it]
 58%|█████▊    | 2084/3566 [1:24:03<1:01:24,  2.49s/it]
                                                       
{'loss': 1.4203, 'learning_rate': 0.00015489007876990353, 'epoch': 0.58}

 58%|█████▊    | 2084/3566 [1:24:03<1:01:24,  2.49s/it]
 58%|█████▊    | 2085/3566 [1:24:05<1:00:29,  2.45s/it]
                                                       
{'loss': 1.5214, 'learning_rate': 0.00015471348802828646, 'epoch': 0.58}

 58%|█████▊    | 2085/3566 [1:24:05<1:00:29,  2.45s/it]
 58%|█████▊    | 2086/3566 [1:24:07<58:44,  2.38s/it]  
                                                     
{'loss': 1.4917, 'learning_rate': 0.00015453693449253998, 'epoch': 0.58}

 58%|█████▊    | 2086/3566 [1:24:07<58:44,  2.38s/it]
 59%|█████▊    | 2087/3566 [1:24:10<56:46,  2.30s/it]
                                                     
{'loss': 1.5142, 'learning_rate': 0.00015436041830771454, 'epoch': 0.59}

 59%|█████▊    | 2087/3566 [1:24:10<56:46,  2.30s/it]
 59%|█████▊    | 2088/3566 [1:24:12<57:12,  2.32s/it]
                                                     
{'loss': 1.4514, 'learning_rate': 0.00015418393961882978, 'epoch': 0.59}

 59%|█████▊    | 2088/3566 [1:24:12<57:12,  2.32s/it]
 59%|█████▊    | 2089/3566 [1:24:14<57:22,  2.33s/it]
                                                     
{'loss': 1.5344, 'learning_rate': 0.00015400749857087478, 'epoch': 0.59}

 59%|█████▊    | 2089/3566 [1:24:14<57:22,  2.33s/it]
 59%|█████▊    | 2090/3566 [1:24:17<56:40,  2.30s/it]
                                                     
{'loss': 1.6419, 'learning_rate': 0.00015383109530880742, 'epoch': 0.59}

 59%|█████▊    | 2090/3566 [1:24:17<56:40,  2.30s/it]
 59%|█████▊    | 2091/3566 [1:24:19<57:18,  2.33s/it]
                                                     
{'loss': 1.5666, 'learning_rate': 0.0001536547299775547, 'epoch': 0.59}

 59%|█████▊    | 2091/3566 [1:24:19<57:18,  2.33s/it]
 59%|█████▊    | 2092/3566 [1:24:22<1:03:19,  2.58s/it]
                                                       
{'loss': 1.6822, 'learning_rate': 0.00015347840272201247, 'epoch': 0.59}

 59%|█████▊    | 2092/3566 [1:24:22<1:03:19,  2.58s/it]
 59%|█████▊    | 2093/3566 [1:24:25<1:06:24,  2.71s/it]
                                                       
{'loss': 1.7507, 'learning_rate': 0.00015330211368704523, 'epoch': 0.59}

 59%|█████▊    | 2093/3566 [1:24:25<1:06:24,  2.71s/it]
 59%|█████▊    | 2094/3566 [1:24:28<1:05:55,  2.69s/it]
                                                       
{'loss': 1.4784, 'learning_rate': 0.00015312586301748606, 'epoch': 0.59}

 59%|█████▊    | 2094/3566 [1:24:28<1:05:55,  2.69s/it]
 59%|█████▊    | 2095/3566 [1:24:30<1:02:18,  2.54s/it]
                                                       
{'loss': 1.5543, 'learning_rate': 0.0001529496508581367, 'epoch': 0.59}

 59%|█████▊    | 2095/3566 [1:24:30<1:02:18,  2.54s/it]
 59%|█████▉    | 2096/3566 [1:24:32<1:01:50,  2.52s/it]
                                                       
{'loss': 1.588, 'learning_rate': 0.00015277347735376696, 'epoch': 0.59}

 59%|█████▉    | 2096/3566 [1:24:32<1:01:50,  2.52s/it]
 59%|█████▉    | 2097/3566 [1:24:35<59:19,  2.42s/it]  
                                                     
{'loss': 1.4743, 'learning_rate': 0.0001525973426491152, 'epoch': 0.59}

 59%|█████▉    | 2097/3566 [1:24:35<59:19,  2.42s/it]
 59%|█████▉    | 2098/3566 [1:24:38<1:05:10,  2.66s/it]
                                                       
{'loss': 1.5636, 'learning_rate': 0.0001524212468888876, 'epoch': 0.59}

 59%|█████▉    | 2098/3566 [1:24:38<1:05:10,  2.66s/it]
 59%|█████▉    | 2099/3566 [1:24:40<1:03:17,  2.59s/it]
                                                       
{'loss': 1.5454, 'learning_rate': 0.00015224519021775858, 'epoch': 0.59}

 59%|█████▉    | 2099/3566 [1:24:40<1:03:17,  2.59s/it]
 59%|█████▉    | 2100/3566 [1:24:43<1:04:21,  2.63s/it]
                                                       
{'loss': 1.5721, 'learning_rate': 0.00015206917278037034, 'epoch': 0.59}

 59%|█████▉    | 2100/3566 [1:24:43<1:04:21,  2.63s/it]
 59%|█████▉    | 2101/3566 [1:24:45<1:03:16,  2.59s/it]
                                                       
{'loss': 1.5926, 'learning_rate': 0.00015189319472133287, 'epoch': 0.59}

 59%|█████▉    | 2101/3566 [1:24:45<1:03:16,  2.59s/it]
 59%|█████▉    | 2102/3566 [1:24:48<1:03:37,  2.61s/it]
                                                       
{'loss': 1.5108, 'learning_rate': 0.00015171725618522388, 'epoch': 0.59}

 59%|█████▉    | 2102/3566 [1:24:48<1:03:37,  2.61s/it]
 59%|█████▉    | 2103/3566 [1:24:51<1:02:05,  2.55s/it]
                                                       
{'loss': 1.5511, 'learning_rate': 0.00015154135731658842, 'epoch': 0.59}

 59%|█████▉    | 2103/3566 [1:24:51<1:02:05,  2.55s/it]
 59%|█████▉    | 2104/3566 [1:24:53<59:25,  2.44s/it]  
                                                     
{'loss': 1.3536, 'learning_rate': 0.0001513654982599391, 'epoch': 0.59}

 59%|█████▉    | 2104/3566 [1:24:53<59:25,  2.44s/it]
 59%|█████▉    | 2105/3566 [1:24:55<57:47,  2.37s/it]
                                                     
{'loss': 1.58, 'learning_rate': 0.00015118967915975578, 'epoch': 0.59}

 59%|█████▉    | 2105/3566 [1:24:55<57:47,  2.37s/it]
 59%|█████▉    | 2106/3566 [1:24:57<56:27,  2.32s/it]
                                                     
{'loss': 1.4712, 'learning_rate': 0.00015101390016048556, 'epoch': 0.59}

 59%|█████▉    | 2106/3566 [1:24:57<56:27,  2.32s/it]
 59%|█████▉    | 2107/3566 [1:25:00<57:49,  2.38s/it]
                                                     
{'loss': 1.3741, 'learning_rate': 0.00015083816140654257, 'epoch': 0.59}

 59%|█████▉    | 2107/3566 [1:25:00<57:49,  2.38s/it]
 59%|█████▉    | 2108/3566 [1:25:02<59:51,  2.46s/it]
                                                     
{'loss': 1.524, 'learning_rate': 0.0001506624630423076, 'epoch': 0.59}

 59%|█████▉    | 2108/3566 [1:25:02<59:51,  2.46s/it]
 59%|█████▉    | 2109/3566 [1:25:05<59:20,  2.44s/it]
                                                     
{'loss': 1.5013, 'learning_rate': 0.00015048680521212882, 'epoch': 0.59}

 59%|█████▉    | 2109/3566 [1:25:05<59:20,  2.44s/it]
 59%|█████▉    | 2110/3566 [1:25:07<1:00:31,  2.49s/it]
                                                       
{'loss': 1.4526, 'learning_rate': 0.00015031118806032058, 'epoch': 0.59}

 59%|█████▉    | 2110/3566 [1:25:07<1:00:31,  2.49s/it]
 59%|█████▉    | 2111/3566 [1:25:10<58:36,  2.42s/it]  
                                                     
{'loss': 1.4385, 'learning_rate': 0.0001501356117311641, 'epoch': 0.59}

 59%|█████▉    | 2111/3566 [1:25:10<58:36,  2.42s/it]
 59%|█████▉    | 2112/3566 [1:25:12<57:47,  2.38s/it]
                                                     
{'loss': 1.6339, 'learning_rate': 0.00014996007636890687, 'epoch': 0.59}

 59%|█████▉    | 2112/3566 [1:25:12<57:47,  2.38s/it]
 59%|█████▉    | 2113/3566 [1:25:14<58:28,  2.41s/it]
                                                     
{'loss': 1.5147, 'learning_rate': 0.0001497845821177629, 'epoch': 0.59}

 59%|█████▉    | 2113/3566 [1:25:14<58:28,  2.41s/it]
 59%|█████▉    | 2114/3566 [1:25:17<57:57,  2.40s/it]
                                                     
{'loss': 1.5197, 'learning_rate': 0.0001496091291219124, 'epoch': 0.59}

 59%|█████▉    | 2114/3566 [1:25:17<57:57,  2.40s/it]
 59%|█████▉    | 2115/3566 [1:25:19<57:36,  2.38s/it]
                                                     
{'loss': 1.7313, 'learning_rate': 0.00014943371752550145, 'epoch': 0.59}

 59%|█████▉    | 2115/3566 [1:25:19<57:36,  2.38s/it]
 59%|█████▉    | 2116/3566 [1:25:21<57:26,  2.38s/it]
                                                     
{'loss': 1.5696, 'learning_rate': 0.00014925834747264247, 'epoch': 0.59}

 59%|█████▉    | 2116/3566 [1:25:21<57:26,  2.38s/it]
 59%|█████▉    | 2117/3566 [1:25:24<59:19,  2.46s/it]
                                                     
{'loss': 1.5896, 'learning_rate': 0.00014908301910741348, 'epoch': 0.59}

 59%|█████▉    | 2117/3566 [1:25:24<59:19,  2.46s/it]
 59%|█████▉    | 2118/3566 [1:25:26<57:13,  2.37s/it]
                                                     
{'loss': 1.4597, 'learning_rate': 0.00014890773257385842, 'epoch': 0.59}

 59%|█████▉    | 2118/3566 [1:25:26<57:13,  2.37s/it]
 59%|█████▉    | 2119/3566 [1:25:29<57:33,  2.39s/it]
                                                     
{'loss': 1.6866, 'learning_rate': 0.00014873248801598678, 'epoch': 0.59}

 59%|█████▉    | 2119/3566 [1:25:29<57:33,  2.39s/it]
 59%|█████▉    | 2120/3566 [1:25:31<55:23,  2.30s/it]
                                                     
{'loss': 1.5581, 'learning_rate': 0.00014855728557777354, 'epoch': 0.59}

 59%|█████▉    | 2120/3566 [1:25:31<55:23,  2.30s/it]
 59%|█████▉    | 2121/3566 [1:25:33<56:24,  2.34s/it]
                                                     
{'loss': 1.5604, 'learning_rate': 0.00014838212540315912, 'epoch': 0.59}

 59%|█████▉    | 2121/3566 [1:25:33<56:24,  2.34s/it]
 60%|█████▉    | 2122/3566 [1:25:36<58:23,  2.43s/it]
                                                     
{'loss': 1.4501, 'learning_rate': 0.0001482070076360492, 'epoch': 0.6}

 60%|█████▉    | 2122/3566 [1:25:36<58:23,  2.43s/it]
 60%|█████▉    | 2123/3566 [1:25:38<57:36,  2.40s/it]
                                                     
{'loss': 1.491, 'learning_rate': 0.00014803193242031467, 'epoch': 0.6}

 60%|█████▉    | 2123/3566 [1:25:38<57:36,  2.40s/it]
 60%|█████▉    | 2124/3566 [1:25:41<58:08,  2.42s/it]
                                                     
{'loss': 1.5932, 'learning_rate': 0.00014785689989979143, 'epoch': 0.6}

 60%|█████▉    | 2124/3566 [1:25:41<58:08,  2.42s/it]
 60%|█████▉    | 2125/3566 [1:25:43<58:04,  2.42s/it]
                                                     
{'loss': 1.6409, 'learning_rate': 0.00014768191021828026, 'epoch': 0.6}

 60%|█████▉    | 2125/3566 [1:25:43<58:04,  2.42s/it]
 60%|█████▉    | 2126/3566 [1:25:45<57:37,  2.40s/it]
                                                     
{'loss': 1.4849, 'learning_rate': 0.00014750696351954678, 'epoch': 0.6}

 60%|█████▉    | 2126/3566 [1:25:45<57:37,  2.40s/it]
 60%|█████▉    | 2127/3566 [1:25:48<57:17,  2.39s/it]
                                                     
{'loss': 1.5199, 'learning_rate': 0.00014733205994732135, 'epoch': 0.6}

 60%|█████▉    | 2127/3566 [1:25:48<57:17,  2.39s/it]
 60%|█████▉    | 2128/3566 [1:25:50<58:23,  2.44s/it]
                                                     
{'loss': 1.4459, 'learning_rate': 0.00014715719964529877, 'epoch': 0.6}

 60%|█████▉    | 2128/3566 [1:25:50<58:23,  2.44s/it]
 60%|█████▉    | 2129/3566 [1:25:53<56:58,  2.38s/it]
                                                     
{'loss': 1.4676, 'learning_rate': 0.00014698238275713839, 'epoch': 0.6}

 60%|█████▉    | 2129/3566 [1:25:53<56:58,  2.38s/it]
 60%|█████▉    | 2130/3566 [1:25:55<54:57,  2.30s/it]
                                                     
{'loss': 1.6114, 'learning_rate': 0.00014680760942646388, 'epoch': 0.6}

 60%|█████▉    | 2130/3566 [1:25:55<54:57,  2.30s/it]
 60%|█████▉    | 2131/3566 [1:25:57<55:18,  2.31s/it]
                                                     
{'loss': 1.4208, 'learning_rate': 0.00014663287979686308, 'epoch': 0.6}

 60%|█████▉    | 2131/3566 [1:25:57<55:18,  2.31s/it]
 60%|█████▉    | 2132/3566 [1:25:59<55:53,  2.34s/it]
                                                     
{'loss': 1.7883, 'learning_rate': 0.00014645819401188804, 'epoch': 0.6}

 60%|█████▉    | 2132/3566 [1:25:59<55:53,  2.34s/it]
 60%|█████▉    | 2133/3566 [1:26:02<55:38,  2.33s/it]
                                                     
{'loss': 1.4648, 'learning_rate': 0.00014628355221505464, 'epoch': 0.6}

 60%|█████▉    | 2133/3566 [1:26:02<55:38,  2.33s/it]
 60%|█████▉    | 2134/3566 [1:26:04<56:13,  2.36s/it]
                                                     
{'loss': 1.5138, 'learning_rate': 0.00014610895454984267, 'epoch': 0.6}

 60%|█████▉    | 2134/3566 [1:26:04<56:13,  2.36s/it]
 60%|█████▉    | 2135/3566 [1:26:06<56:11,  2.36s/it]
                                                     
{'loss': 1.617, 'learning_rate': 0.00014593440115969576, 'epoch': 0.6}

 60%|█████▉    | 2135/3566 [1:26:06<56:11,  2.36s/it]
 60%|█████▉    | 2136/3566 [1:26:09<57:44,  2.42s/it]
                                                     
{'loss': 1.4877, 'learning_rate': 0.00014575989218802094, 'epoch': 0.6}

 60%|█████▉    | 2136/3566 [1:26:09<57:44,  2.42s/it]
 60%|█████▉    | 2137/3566 [1:26:12<59:54,  2.52s/it]
                                                     
{'loss': 1.5244, 'learning_rate': 0.0001455854277781891, 'epoch': 0.6}

 60%|█████▉    | 2137/3566 [1:26:12<59:54,  2.52s/it]
 60%|█████▉    | 2138/3566 [1:26:14<58:20,  2.45s/it]
                                                     
{'loss': 1.662, 'learning_rate': 0.00014541100807353416, 'epoch': 0.6}

 60%|█████▉    | 2138/3566 [1:26:14<58:20,  2.45s/it]
 60%|█████▉    | 2139/3566 [1:26:16<57:16,  2.41s/it]
                                                     
{'loss': 1.4268, 'learning_rate': 0.00014523663321735356, 'epoch': 0.6}

 60%|█████▉    | 2139/3566 [1:26:16<57:16,  2.41s/it]
 60%|██████    | 2140/3566 [1:26:19<57:08,  2.40s/it]
                                                     
{'loss': 1.6587, 'learning_rate': 0.00014506230335290776, 'epoch': 0.6}

 60%|██████    | 2140/3566 [1:26:19<57:08,  2.40s/it]
 60%|██████    | 2141/3566 [1:26:21<56:43,  2.39s/it]
                                                     
{'loss': 1.2935, 'learning_rate': 0.00014488801862342024, 'epoch': 0.6}

 60%|██████    | 2141/3566 [1:26:21<56:43,  2.39s/it]
 60%|██████    | 2142/3566 [1:26:24<57:12,  2.41s/it]
                                                     
{'loss': 1.4157, 'learning_rate': 0.00014471377917207753, 'epoch': 0.6}

 60%|██████    | 2142/3566 [1:26:24<57:12,  2.41s/it]
 60%|██████    | 2143/3566 [1:26:26<57:14,  2.41s/it]
                                                     
{'loss': 1.6749, 'learning_rate': 0.00014453958514202886, 'epoch': 0.6}

 60%|██████    | 2143/3566 [1:26:26<57:14,  2.41s/it]
 60%|██████    | 2144/3566 [1:26:29<59:15,  2.50s/it]
                                                     
{'loss': 1.6559, 'learning_rate': 0.0001443654366763862, 'epoch': 0.6}

 60%|██████    | 2144/3566 [1:26:29<59:15,  2.50s/it]
 60%|██████    | 2145/3566 [1:26:31<56:58,  2.41s/it]
                                                     
{'loss': 1.4405, 'learning_rate': 0.00014419133391822402, 'epoch': 0.6}

 60%|██████    | 2145/3566 [1:26:31<56:58,  2.41s/it]
 60%|██████    | 2146/3566 [1:26:34<58:38,  2.48s/it]
                                                     
{'loss': 1.6115, 'learning_rate': 0.00014401727701057924, 'epoch': 0.6}

 60%|██████    | 2146/3566 [1:26:34<58:38,  2.48s/it]
 60%|██████    | 2147/3566 [1:26:36<56:45,  2.40s/it]
                                                     
{'loss': 1.5387, 'learning_rate': 0.00014384326609645121, 'epoch': 0.6}

 60%|██████    | 2147/3566 [1:26:36<56:45,  2.40s/it]
 60%|██████    | 2148/3566 [1:26:38<57:28,  2.43s/it]
                                                     
{'loss': 1.6267, 'learning_rate': 0.0001436693013188014, 'epoch': 0.6}

 60%|██████    | 2148/3566 [1:26:38<57:28,  2.43s/it]
 60%|██████    | 2149/3566 [1:26:40<55:58,  2.37s/it]
                                                     
{'loss': 1.3372, 'learning_rate': 0.00014349538282055338, 'epoch': 0.6}

 60%|██████    | 2149/3566 [1:26:40<55:58,  2.37s/it]
 60%|██████    | 2150/3566 [1:26:43<55:06,  2.34s/it]
                                                     
{'loss': 1.5288, 'learning_rate': 0.0001433215107445928, 'epoch': 0.6}

 60%|██████    | 2150/3566 [1:26:43<55:06,  2.34s/it]
 60%|██████    | 2151/3566 [1:26:45<55:28,  2.35s/it]
                                                     
{'loss': 1.4841, 'learning_rate': 0.00014314768523376688, 'epoch': 0.6}

 60%|██████    | 2151/3566 [1:26:45<55:28,  2.35s/it]
 60%|██████    | 2152/3566 [1:26:48<56:05,  2.38s/it]
                                                     
{'loss': 1.5663, 'learning_rate': 0.00014297390643088512, 'epoch': 0.6}

 60%|██████    | 2152/3566 [1:26:48<56:05,  2.38s/it]
 60%|██████    | 2153/3566 [1:26:50<55:08,  2.34s/it]
                                                     
{'loss': 1.563, 'learning_rate': 0.0001428001744787181, 'epoch': 0.6}

 60%|██████    | 2153/3566 [1:26:50<55:08,  2.34s/it]
 60%|██████    | 2154/3566 [1:26:52<54:48,  2.33s/it]
                                                     
{'loss': 1.5424, 'learning_rate': 0.00014262648951999816, 'epoch': 0.6}

 60%|██████    | 2154/3566 [1:26:52<54:48,  2.33s/it]
 60%|██████    | 2155/3566 [1:26:55<55:55,  2.38s/it]
                                                     
{'loss': 1.5066, 'learning_rate': 0.00014245285169741908, 'epoch': 0.6}

 60%|██████    | 2155/3566 [1:26:55<55:55,  2.38s/it]
 60%|██████    | 2156/3566 [1:26:57<54:53,  2.34s/it]
                                                     
{'loss': 1.6066, 'learning_rate': 0.00014227926115363573, 'epoch': 0.6}

 60%|██████    | 2156/3566 [1:26:57<54:53,  2.34s/it]
 60%|██████    | 2157/3566 [1:26:59<54:32,  2.32s/it]
                                                     
{'loss': 1.6894, 'learning_rate': 0.00014210571803126437, 'epoch': 0.6}

 60%|██████    | 2157/3566 [1:26:59<54:32,  2.32s/it]
 61%|██████    | 2158/3566 [1:27:02<55:53,  2.38s/it]
                                                     
{'loss': 1.5813, 'learning_rate': 0.00014193222247288207, 'epoch': 0.61}

 61%|██████    | 2158/3566 [1:27:02<55:53,  2.38s/it]
 61%|██████    | 2159/3566 [1:27:04<56:01,  2.39s/it]
                                                     
{'loss': 1.544, 'learning_rate': 0.00014175877462102693, 'epoch': 0.61}

 61%|██████    | 2159/3566 [1:27:04<56:01,  2.39s/it]
 61%|██████    | 2160/3566 [1:27:06<55:48,  2.38s/it]
                                                     
{'loss': 1.4414, 'learning_rate': 0.0001415853746181979, 'epoch': 0.61}

 61%|██████    | 2160/3566 [1:27:06<55:48,  2.38s/it]
 61%|██████    | 2161/3566 [1:27:09<57:53,  2.47s/it]
                                                     
{'loss': 1.4898, 'learning_rate': 0.00014141202260685461, 'epoch': 0.61}

 61%|██████    | 2161/3566 [1:27:09<57:53,  2.47s/it]
 61%|██████    | 2162/3566 [1:27:12<57:58,  2.48s/it]
                                                     
{'loss': 1.4828, 'learning_rate': 0.00014123871872941717, 'epoch': 0.61}

 61%|██████    | 2162/3566 [1:27:12<57:58,  2.48s/it]
 61%|██████    | 2163/3566 [1:27:14<55:07,  2.36s/it]
                                                     
{'loss': 1.6092, 'learning_rate': 0.00014106546312826618, 'epoch': 0.61}

 61%|██████    | 2163/3566 [1:27:14<55:07,  2.36s/it]
 61%|██████    | 2164/3566 [1:27:16<55:58,  2.40s/it]
                                                     
{'loss': 1.6373, 'learning_rate': 0.00014089225594574262, 'epoch': 0.61}

 61%|██████    | 2164/3566 [1:27:16<55:58,  2.40s/it]
 61%|██████    | 2165/3566 [1:27:18<55:20,  2.37s/it]
                                                     
{'loss': 1.5327, 'learning_rate': 0.00014071909732414763, 'epoch': 0.61}

 61%|██████    | 2165/3566 [1:27:18<55:20,  2.37s/it]
 61%|██████    | 2166/3566 [1:27:21<57:45,  2.48s/it]
                                                     
{'loss': 1.6808, 'learning_rate': 0.0001405459874057426, 'epoch': 0.61}

 61%|██████    | 2166/3566 [1:27:21<57:45,  2.48s/it]
 61%|██████    | 2167/3566 [1:27:24<58:21,  2.50s/it]
                                                     
{'loss': 1.5245, 'learning_rate': 0.0001403729263327487, 'epoch': 0.61}

 61%|██████    | 2167/3566 [1:27:24<58:21,  2.50s/it]
 61%|██████    | 2168/3566 [1:27:27<1:00:38,  2.60s/it]
                                                       
{'loss': 1.5383, 'learning_rate': 0.00014019991424734713, 'epoch': 0.61}

 61%|██████    | 2168/3566 [1:27:27<1:00:38,  2.60s/it]
 61%|██████    | 2169/3566 [1:27:30<1:03:50,  2.74s/it]
                                                       
{'loss': 1.603, 'learning_rate': 0.00014002695129167872, 'epoch': 0.61}

 61%|██████    | 2169/3566 [1:27:30<1:03:50,  2.74s/it]
 61%|██████    | 2170/3566 [1:27:33<1:05:20,  2.81s/it]
                                                       
{'loss': 1.6375, 'learning_rate': 0.0001398540376078441, 'epoch': 0.61}

 61%|██████    | 2170/3566 [1:27:33<1:05:20,  2.81s/it]
 61%|██████    | 2171/3566 [1:27:35<1:02:51,  2.70s/it]
                                                       
{'loss': 1.4463, 'learning_rate': 0.00013968117333790323, 'epoch': 0.61}

 61%|██████    | 2171/3566 [1:27:35<1:02:51,  2.70s/it]
 61%|██████    | 2172/3566 [1:27:38<1:01:13,  2.63s/it]
                                                       
{'loss': 1.5305, 'learning_rate': 0.00013950835862387554, 'epoch': 0.61}

 61%|██████    | 2172/3566 [1:27:38<1:01:13,  2.63s/it]
 61%|██████    | 2173/3566 [1:27:40<59:28,  2.56s/it]  
                                                     
{'loss': 1.6198, 'learning_rate': 0.00013933559360773987, 'epoch': 0.61}

 61%|██████    | 2173/3566 [1:27:40<59:28,  2.56s/it]
 61%|██████    | 2174/3566 [1:27:42<58:28,  2.52s/it]
                                                     
{'loss': 1.6037, 'learning_rate': 0.00013916287843143406, 'epoch': 0.61}

 61%|██████    | 2174/3566 [1:27:42<58:28,  2.52s/it]
 61%|██████    | 2175/3566 [1:27:45<57:12,  2.47s/it]
                                                     
{'loss': 1.5595, 'learning_rate': 0.00013899021323685512, 'epoch': 0.61}

 61%|██████    | 2175/3566 [1:27:45<57:12,  2.47s/it]
 61%|██████    | 2176/3566 [1:27:47<57:20,  2.48s/it]
                                                     
{'loss': 1.7285, 'learning_rate': 0.00013881759816585887, 'epoch': 0.61}

 61%|██████    | 2176/3566 [1:27:47<57:20,  2.48s/it]
 61%|██████    | 2177/3566 [1:27:50<56:23,  2.44s/it]
                                                     
{'loss': 1.633, 'learning_rate': 0.00013864503336026012, 'epoch': 0.61}

 61%|██████    | 2177/3566 [1:27:50<56:23,  2.44s/it]
 61%|██████    | 2178/3566 [1:27:52<55:49,  2.41s/it]
                                                     
{'loss': 1.5056, 'learning_rate': 0.0001384725189618322, 'epoch': 0.61}

 61%|██████    | 2178/3566 [1:27:52<55:49,  2.41s/it]
 61%|██████    | 2179/3566 [1:27:54<55:05,  2.38s/it]
                                                     
{'loss': 1.429, 'learning_rate': 0.00013830005511230716, 'epoch': 0.61}

 61%|██████    | 2179/3566 [1:27:54<55:05,  2.38s/it]
 61%|██████    | 2180/3566 [1:27:57<54:31,  2.36s/it]
                                                     
{'loss': 1.6825, 'learning_rate': 0.0001381276419533755, 'epoch': 0.61}

 61%|██████    | 2180/3566 [1:27:57<54:31,  2.36s/it]
 61%|██████    | 2181/3566 [1:27:59<57:11,  2.48s/it]
                                                     
{'loss': 1.5693, 'learning_rate': 0.00013795527962668608, 'epoch': 0.61}

 61%|██████    | 2181/3566 [1:27:59<57:11,  2.48s/it]
 61%|██████    | 2182/3566 [1:28:02<55:44,  2.42s/it]
                                                     
{'loss': 1.5604, 'learning_rate': 0.00013778296827384595, 'epoch': 0.61}

 61%|██████    | 2182/3566 [1:28:02<55:44,  2.42s/it]
 61%|██████    | 2183/3566 [1:28:04<55:48,  2.42s/it]
                                                     
{'loss': 1.5696, 'learning_rate': 0.00013761070803642033, 'epoch': 0.61}

 61%|██████    | 2183/3566 [1:28:04<55:48,  2.42s/it]
 61%|██████    | 2184/3566 [1:28:07<58:19,  2.53s/it]
                                                     
{'loss': 1.6523, 'learning_rate': 0.00013743849905593233, 'epoch': 0.61}

 61%|██████    | 2184/3566 [1:28:07<58:19,  2.53s/it]
 61%|██████▏   | 2185/3566 [1:28:09<58:25,  2.54s/it]
                                                     
{'loss': 1.5832, 'learning_rate': 0.0001372663414738631, 'epoch': 0.61}

 61%|██████▏   | 2185/3566 [1:28:09<58:25,  2.54s/it]
 61%|██████▏   | 2186/3566 [1:28:12<58:12,  2.53s/it]
                                                     
{'loss': 1.4978, 'learning_rate': 0.0001370942354316515, 'epoch': 0.61}

 61%|██████▏   | 2186/3566 [1:28:12<58:12,  2.53s/it]
 61%|██████▏   | 2187/3566 [1:28:14<57:26,  2.50s/it]
                                                     
{'loss': 1.7184, 'learning_rate': 0.00013692218107069407, 'epoch': 0.61}

 61%|██████▏   | 2187/3566 [1:28:14<57:26,  2.50s/it]
 61%|██████▏   | 2188/3566 [1:28:17<57:08,  2.49s/it]
                                                     
{'loss': 1.5224, 'learning_rate': 0.00013675017853234488, 'epoch': 0.61}

 61%|██████▏   | 2188/3566 [1:28:17<57:08,  2.49s/it]
 61%|██████▏   | 2189/3566 [1:28:19<57:56,  2.52s/it]
                                                     
{'loss': 1.6035, 'learning_rate': 0.0001365782279579153, 'epoch': 0.61}

 61%|██████▏   | 2189/3566 [1:28:19<57:56,  2.52s/it]
 61%|██████▏   | 2190/3566 [1:28:22<55:27,  2.42s/it]
                                                     
{'loss': 1.6017, 'learning_rate': 0.0001364063294886742, 'epoch': 0.61}

 61%|██████▏   | 2190/3566 [1:28:22<55:27,  2.42s/it]
 61%|██████▏   | 2191/3566 [1:28:24<55:22,  2.42s/it]
                                                     
{'loss': 1.4599, 'learning_rate': 0.0001362344832658476, 'epoch': 0.61}

 61%|██████▏   | 2191/3566 [1:28:24<55:22,  2.42s/it]
 61%|██████▏   | 2192/3566 [1:28:26<56:06,  2.45s/it]
                                                     
{'loss': 1.6399, 'learning_rate': 0.0001360626894306185, 'epoch': 0.61}

 61%|██████▏   | 2192/3566 [1:28:26<56:06,  2.45s/it]
 61%|██████▏   | 2193/3566 [1:28:29<55:10,  2.41s/it]
                                                     
{'loss': 1.5574, 'learning_rate': 0.00013589094812412693, 'epoch': 0.61}

 61%|██████▏   | 2193/3566 [1:28:29<55:10,  2.41s/it]
 62%|██████▏   | 2194/3566 [1:28:31<55:13,  2.42s/it]
                                                     
{'loss': 1.5488, 'learning_rate': 0.0001357192594874698, 'epoch': 0.62}

 62%|██████▏   | 2194/3566 [1:28:31<55:13,  2.42s/it]
 62%|██████▏   | 2195/3566 [1:28:33<52:45,  2.31s/it]
                                                     
{'loss': 1.4774, 'learning_rate': 0.00013554762366170067, 'epoch': 0.62}

 62%|██████▏   | 2195/3566 [1:28:33<52:45,  2.31s/it]
 62%|██████▏   | 2196/3566 [1:28:36<54:04,  2.37s/it]
                                                     
{'loss': 1.7236, 'learning_rate': 0.00013537604078782972, 'epoch': 0.62}

 62%|██████▏   | 2196/3566 [1:28:36<54:04,  2.37s/it]
 62%|██████▏   | 2197/3566 [1:28:38<52:11,  2.29s/it]
                                                     
{'loss': 1.4355, 'learning_rate': 0.00013520451100682373, 'epoch': 0.62}

 62%|██████▏   | 2197/3566 [1:28:38<52:11,  2.29s/it]
 62%|██████▏   | 2198/3566 [1:28:40<54:09,  2.38s/it]
                                                     
{'loss': 1.563, 'learning_rate': 0.00013503303445960567, 'epoch': 0.62}

 62%|██████▏   | 2198/3566 [1:28:40<54:09,  2.38s/it]
 62%|██████▏   | 2199/3566 [1:28:43<53:45,  2.36s/it]
                                                     
{'loss': 1.5843, 'learning_rate': 0.00013486161128705495, 'epoch': 0.62}

 62%|██████▏   | 2199/3566 [1:28:43<53:45,  2.36s/it]
 62%|██████▏   | 2200/3566 [1:28:45<54:43,  2.40s/it]
                                                     
{'loss': 1.5718, 'learning_rate': 0.0001346902416300071, 'epoch': 0.62}

 62%|██████▏   | 2200/3566 [1:28:45<54:43,  2.40s/it]
 62%|██████▏   | 2201/3566 [1:28:48<56:21,  2.48s/it]
                                                     
{'loss': 1.5387, 'learning_rate': 0.00013451892562925356, 'epoch': 0.62}

 62%|██████▏   | 2201/3566 [1:28:48<56:21,  2.48s/it]
 62%|██████▏   | 2202/3566 [1:28:50<55:23,  2.44s/it]
                                                     
{'loss': 1.4863, 'learning_rate': 0.00013434766342554184, 'epoch': 0.62}

 62%|██████▏   | 2202/3566 [1:28:50<55:23,  2.44s/it]
 62%|██████▏   | 2203/3566 [1:28:53<56:37,  2.49s/it]
                                                     
{'loss': 1.5296, 'learning_rate': 0.0001341764551595752, 'epoch': 0.62}

 62%|██████▏   | 2203/3566 [1:28:53<56:37,  2.49s/it]
 62%|██████▏   | 2204/3566 [1:28:55<55:49,  2.46s/it]
                                                     
{'loss': 1.4098, 'learning_rate': 0.0001340053009720125, 'epoch': 0.62}

 62%|██████▏   | 2204/3566 [1:28:55<55:49,  2.46s/it]
 62%|██████▏   | 2205/3566 [1:28:58<56:14,  2.48s/it]
                                                     
{'loss': 1.5501, 'learning_rate': 0.00013383420100346837, 'epoch': 0.62}

 62%|██████▏   | 2205/3566 [1:28:58<56:14,  2.48s/it]
 62%|██████▏   | 2206/3566 [1:29:00<56:54,  2.51s/it]
                                                     
{'loss': 1.5727, 'learning_rate': 0.00013366315539451267, 'epoch': 0.62}

 62%|██████▏   | 2206/3566 [1:29:00<56:54,  2.51s/it]
 62%|██████▏   | 2207/3566 [1:29:03<54:10,  2.39s/it]
                                                     
{'loss': 1.5295, 'learning_rate': 0.00013349216428567063, 'epoch': 0.62}

 62%|██████▏   | 2207/3566 [1:29:03<54:10,  2.39s/it]
 62%|██████▏   | 2208/3566 [1:29:05<53:11,  2.35s/it]
                                                     
{'loss': 1.3267, 'learning_rate': 0.000133321227817423, 'epoch': 0.62}

 62%|██████▏   | 2208/3566 [1:29:05<53:11,  2.35s/it]
 62%|██████▏   | 2209/3566 [1:29:08<56:21,  2.49s/it]
                                                     
{'loss': 1.5707, 'learning_rate': 0.00013315034613020526, 'epoch': 0.62}

 62%|██████▏   | 2209/3566 [1:29:08<56:21,  2.49s/it]
 62%|██████▏   | 2210/3566 [1:29:10<55:59,  2.48s/it]
                                                     
{'loss': 1.5994, 'learning_rate': 0.00013297951936440806, 'epoch': 0.62}

 62%|██████▏   | 2210/3566 [1:29:10<55:59,  2.48s/it]
 62%|██████▏   | 2211/3566 [1:29:12<55:34,  2.46s/it]
                                                     
{'loss': 1.6535, 'learning_rate': 0.00013280874766037693, 'epoch': 0.62}

 62%|██████▏   | 2211/3566 [1:29:12<55:34,  2.46s/it]
 62%|██████▏   | 2212/3566 [1:29:14<52:21,  2.32s/it]
                                                     
{'loss': 1.4918, 'learning_rate': 0.00013263803115841217, 'epoch': 0.62}

 62%|██████▏   | 2212/3566 [1:29:14<52:21,  2.32s/it]
 62%|██████▏   | 2213/3566 [1:29:17<54:08,  2.40s/it]
                                                     
{'loss': 1.6237, 'learning_rate': 0.00013246736999876867, 'epoch': 0.62}

 62%|██████▏   | 2213/3566 [1:29:17<54:08,  2.40s/it]
 62%|██████▏   | 2214/3566 [1:29:19<53:29,  2.37s/it]
                                                     
{'loss': 1.5126, 'learning_rate': 0.00013229676432165586, 'epoch': 0.62}

 62%|██████▏   | 2214/3566 [1:29:19<53:29,  2.37s/it]
 62%|██████▏   | 2215/3566 [1:29:22<52:06,  2.31s/it]
                                                     
{'loss': 1.5032, 'learning_rate': 0.00013212621426723762, 'epoch': 0.62}

 62%|██████▏   | 2215/3566 [1:29:22<52:06,  2.31s/it]
 62%|██████▏   | 2216/3566 [1:29:24<51:02,  2.27s/it]
                                                     
{'loss': 1.5657, 'learning_rate': 0.0001319557199756321, 'epoch': 0.62}

 62%|██████▏   | 2216/3566 [1:29:24<51:02,  2.27s/it]
 62%|██████▏   | 2217/3566 [1:29:26<52:44,  2.35s/it]
                                                     
{'loss': 1.6054, 'learning_rate': 0.0001317852815869117, 'epoch': 0.62}

 62%|██████▏   | 2217/3566 [1:29:26<52:44,  2.35s/it]
 62%|██████▏   | 2218/3566 [1:29:29<52:22,  2.33s/it]
                                                     
{'loss': 1.51, 'learning_rate': 0.0001316148992411029, 'epoch': 0.62}

 62%|██████▏   | 2218/3566 [1:29:29<52:22,  2.33s/it]
 62%|██████▏   | 2219/3566 [1:29:31<52:20,  2.33s/it]
                                                     
{'loss': 1.5919, 'learning_rate': 0.00013144457307818596, 'epoch': 0.62}

 62%|██████▏   | 2219/3566 [1:29:31<52:20,  2.33s/it]
 62%|██████▏   | 2220/3566 [1:29:33<51:49,  2.31s/it]
                                                     
{'loss': 1.5377, 'learning_rate': 0.00013127430323809516, 'epoch': 0.62}

 62%|██████▏   | 2220/3566 [1:29:33<51:49,  2.31s/it]
 62%|██████▏   | 2221/3566 [1:29:36<53:30,  2.39s/it]
                                                     
{'loss': 1.3796, 'learning_rate': 0.00013110408986071845, 'epoch': 0.62}

 62%|██████▏   | 2221/3566 [1:29:36<53:30,  2.39s/it]
 62%|██████▏   | 2222/3566 [1:29:38<52:17,  2.33s/it]
                                                     
{'loss': 1.6229, 'learning_rate': 0.00013093393308589746, 'epoch': 0.62}

 62%|██████▏   | 2222/3566 [1:29:38<52:17,  2.33s/it]
 62%|██████▏   | 2223/3566 [1:29:40<51:45,  2.31s/it]
                                                     
{'loss': 1.4188, 'learning_rate': 0.00013076383305342718, 'epoch': 0.62}

 62%|██████▏   | 2223/3566 [1:29:40<51:45,  2.31s/it]
 62%|██████▏   | 2224/3566 [1:29:43<52:52,  2.36s/it]
                                                     
{'loss': 1.5611, 'learning_rate': 0.00013059378990305613, 'epoch': 0.62}

 62%|██████▏   | 2224/3566 [1:29:43<52:52,  2.36s/it]
 62%|██████▏   | 2225/3566 [1:29:45<53:25,  2.39s/it]
                                                     
{'loss': 1.3778, 'learning_rate': 0.000130423803774486, 'epoch': 0.62}

 62%|██████▏   | 2225/3566 [1:29:45<53:25,  2.39s/it]
 62%|██████▏   | 2226/3566 [1:29:47<52:27,  2.35s/it]
                                                     
{'loss': 1.4106, 'learning_rate': 0.00013025387480737169, 'epoch': 0.62}

 62%|██████▏   | 2226/3566 [1:29:47<52:27,  2.35s/it]
 62%|██████▏   | 2227/3566 [1:29:50<52:06,  2.33s/it]
                                                     
{'loss': 1.7085, 'learning_rate': 0.00013008400314132098, 'epoch': 0.62}

 62%|██████▏   | 2227/3566 [1:29:50<52:06,  2.33s/it]
 62%|██████▏   | 2228/3566 [1:29:52<52:48,  2.37s/it]
                                                     
{'loss': 1.623, 'learning_rate': 0.00012991418891589485, 'epoch': 0.62}

 62%|██████▏   | 2228/3566 [1:29:52<52:48,  2.37s/it]
 63%|██████▎   | 2229/3566 [1:29:54<53:02,  2.38s/it]
                                                     
{'loss': 1.4744, 'learning_rate': 0.0001297444322706068, 'epoch': 0.63}

 63%|██████▎   | 2229/3566 [1:29:54<53:02,  2.38s/it]
 63%|██████▎   | 2230/3566 [1:29:57<55:43,  2.50s/it]
                                                     
{'loss': 1.4807, 'learning_rate': 0.0001295747333449233, 'epoch': 0.63}

 63%|██████▎   | 2230/3566 [1:29:57<55:43,  2.50s/it]
 63%|██████▎   | 2231/3566 [1:30:00<55:07,  2.48s/it]
                                                     
{'loss': 1.5594, 'learning_rate': 0.00012940509227826326, 'epoch': 0.63}

 63%|██████▎   | 2231/3566 [1:30:00<55:07,  2.48s/it]
 63%|██████▎   | 2232/3566 [1:30:03<57:27,  2.58s/it]
                                                     
{'loss': 1.5275, 'learning_rate': 0.0001292355092099979, 'epoch': 0.63}

 63%|██████▎   | 2232/3566 [1:30:03<57:27,  2.58s/it]
 63%|██████▎   | 2233/3566 [1:30:05<58:25,  2.63s/it]
                                                     
{'loss': 1.5324, 'learning_rate': 0.0001290659842794511, 'epoch': 0.63}

 63%|██████▎   | 2233/3566 [1:30:05<58:25,  2.63s/it]
 63%|██████▎   | 2234/3566 [1:30:08<57:30,  2.59s/it]
                                                     
{'loss': 1.5576, 'learning_rate': 0.00012889651762589872, 'epoch': 0.63}

 63%|██████▎   | 2234/3566 [1:30:08<57:30,  2.59s/it]
 63%|██████▎   | 2235/3566 [1:30:10<54:47,  2.47s/it]
                                                     
{'loss': 1.4737, 'learning_rate': 0.0001287271093885689, 'epoch': 0.63}

 63%|██████▎   | 2235/3566 [1:30:10<54:47,  2.47s/it]
 63%|██████▎   | 2236/3566 [1:30:13<56:21,  2.54s/it]
                                                     
{'loss': 1.5425, 'learning_rate': 0.00012855775970664173, 'epoch': 0.63}

 63%|██████▎   | 2236/3566 [1:30:13<56:21,  2.54s/it]
 63%|██████▎   | 2237/3566 [1:30:15<56:07,  2.53s/it]
                                                     
{'loss': 1.4445, 'learning_rate': 0.00012838846871924924, 'epoch': 0.63}

 63%|██████▎   | 2237/3566 [1:30:15<56:07,  2.53s/it]
 63%|██████▎   | 2238/3566 [1:30:18<54:58,  2.48s/it]
                                                     
{'loss': 1.3467, 'learning_rate': 0.00012821923656547516, 'epoch': 0.63}

 63%|██████▎   | 2238/3566 [1:30:18<54:58,  2.48s/it]
 63%|██████▎   | 2239/3566 [1:30:21<59:30,  2.69s/it]
                                                     
{'loss': 1.5208, 'learning_rate': 0.0001280500633843549, 'epoch': 0.63}

 63%|██████▎   | 2239/3566 [1:30:21<59:30,  2.69s/it]
 63%|██████▎   | 2240/3566 [1:30:23<57:23,  2.60s/it]
                                                     
{'loss': 1.5119, 'learning_rate': 0.00012788094931487544, 'epoch': 0.63}

 63%|██████▎   | 2240/3566 [1:30:23<57:23,  2.60s/it]
 63%|██████▎   | 2241/3566 [1:30:25<56:01,  2.54s/it]
                                                     
{'loss': 1.5536, 'learning_rate': 0.0001277118944959752, 'epoch': 0.63}

 63%|██████▎   | 2241/3566 [1:30:25<56:01,  2.54s/it]
 63%|██████▎   | 2242/3566 [1:30:28<55:08,  2.50s/it]
                                                     
{'loss': 1.7005, 'learning_rate': 0.00012754289906654394, 'epoch': 0.63}

 63%|██████▎   | 2242/3566 [1:30:28<55:08,  2.50s/it]
 63%|██████▎   | 2243/3566 [1:30:30<54:51,  2.49s/it]
                                                     
{'loss': 1.4239, 'learning_rate': 0.0001273739631654226, 'epoch': 0.63}

 63%|██████▎   | 2243/3566 [1:30:30<54:51,  2.49s/it]
 63%|██████▎   | 2244/3566 [1:30:33<53:53,  2.45s/it]
                                                     
{'loss': 1.5431, 'learning_rate': 0.00012720508693140316, 'epoch': 0.63}

 63%|██████▎   | 2244/3566 [1:30:33<53:53,  2.45s/it]
 63%|██████▎   | 2245/3566 [1:30:35<52:59,  2.41s/it]
                                                     
{'loss': 1.6499, 'learning_rate': 0.00012703627050322867, 'epoch': 0.63}

 63%|██████▎   | 2245/3566 [1:30:35<52:59,  2.41s/it]
 63%|██████▎   | 2246/3566 [1:30:37<52:28,  2.39s/it]
                                                     
{'loss': 1.6058, 'learning_rate': 0.00012686751401959305, 'epoch': 0.63}

 63%|██████▎   | 2246/3566 [1:30:37<52:28,  2.39s/it]
 63%|██████▎   | 2247/3566 [1:30:40<52:09,  2.37s/it]
                                                     
{'loss': 1.576, 'learning_rate': 0.00012669881761914092, 'epoch': 0.63}

 63%|██████▎   | 2247/3566 [1:30:40<52:09,  2.37s/it]
 63%|██████▎   | 2248/3566 [1:30:42<52:29,  2.39s/it]
                                                     
{'loss': 1.5469, 'learning_rate': 0.00012653018144046752, 'epoch': 0.63}

 63%|██████▎   | 2248/3566 [1:30:42<52:29,  2.39s/it]
 63%|██████▎   | 2249/3566 [1:30:44<51:54,  2.36s/it]
                                                     
{'loss': 1.5721, 'learning_rate': 0.0001263616056221186, 'epoch': 0.63}

 63%|██████▎   | 2249/3566 [1:30:44<51:54,  2.36s/it]
 63%|██████▎   | 2250/3566 [1:30:47<52:31,  2.40s/it]
                                                     
{'loss': 1.6357, 'learning_rate': 0.00012619309030259047, 'epoch': 0.63}

 63%|██████▎   | 2250/3566 [1:30:47<52:31,  2.40s/it]
 63%|██████▎   | 2251/3566 [1:30:50<54:42,  2.50s/it]
                                                     
{'loss': 1.5661, 'learning_rate': 0.00012602463562032967, 'epoch': 0.63}

 63%|██████▎   | 2251/3566 [1:30:50<54:42,  2.50s/it]
 63%|██████▎   | 2252/3566 [1:30:52<54:34,  2.49s/it]
                                                     
{'loss': 1.424, 'learning_rate': 0.00012585624171373272, 'epoch': 0.63}

 63%|██████▎   | 2252/3566 [1:30:52<54:34,  2.49s/it]
 63%|██████▎   | 2253/3566 [1:30:55<55:05,  2.52s/it]
                                                     
{'loss': 1.519, 'learning_rate': 0.00012568790872114654, 'epoch': 0.63}

 63%|██████▎   | 2253/3566 [1:30:55<55:05,  2.52s/it]
 63%|██████▎   | 2254/3566 [1:30:57<53:54,  2.47s/it]
                                                     
{'loss': 1.3909, 'learning_rate': 0.0001255196367808677, 'epoch': 0.63}

 63%|██████▎   | 2254/3566 [1:30:57<53:54,  2.47s/it]
 63%|██████▎   | 2255/3566 [1:30:59<53:18,  2.44s/it]
                                                     
{'loss': 1.6044, 'learning_rate': 0.00012535142603114282, 'epoch': 0.63}

 63%|██████▎   | 2255/3566 [1:30:59<53:18,  2.44s/it]
 63%|██████▎   | 2256/3566 [1:31:03<57:32,  2.64s/it]
                                                     
{'loss': 1.4342, 'learning_rate': 0.00012518327661016819, 'epoch': 0.63}

 63%|██████▎   | 2256/3566 [1:31:03<57:32,  2.64s/it]
 63%|██████▎   | 2257/3566 [1:31:05<54:48,  2.51s/it]
                                                     
{'loss': 1.4537, 'learning_rate': 0.0001250151886560896, 'epoch': 0.63}

 63%|██████▎   | 2257/3566 [1:31:05<54:48,  2.51s/it]
 63%|██████▎   | 2258/3566 [1:31:07<53:44,  2.46s/it]
                                                     
{'loss': 1.6241, 'learning_rate': 0.00012484716230700256, 'epoch': 0.63}

 63%|██████▎   | 2258/3566 [1:31:07<53:44,  2.46s/it]
 63%|██████▎   | 2259/3566 [1:31:10<54:13,  2.49s/it]
                                                     
{'loss': 1.51, 'learning_rate': 0.00012467919770095185, 'epoch': 0.63}

 63%|██████▎   | 2259/3566 [1:31:10<54:13,  2.49s/it]
 63%|██████▎   | 2260/3566 [1:31:12<53:40,  2.47s/it]
                                                     
{'loss': 1.4775, 'learning_rate': 0.00012451129497593143, 'epoch': 0.63}

 63%|██████▎   | 2260/3566 [1:31:12<53:40,  2.47s/it]
 63%|██████▎   | 2261/3566 [1:31:14<53:12,  2.45s/it]
                                                     
{'loss': 1.5267, 'learning_rate': 0.00012434345426988466, 'epoch': 0.63}

 63%|██████▎   | 2261/3566 [1:31:14<53:12,  2.45s/it]
 63%|██████▎   | 2262/3566 [1:31:17<51:41,  2.38s/it]
                                                     
{'loss': 1.5038, 'learning_rate': 0.00012417567572070364, 'epoch': 0.63}

 63%|██████▎   | 2262/3566 [1:31:17<51:41,  2.38s/it]
 63%|██████▎   | 2263/3566 [1:31:19<51:46,  2.38s/it]
                                                     
{'loss': 1.6827, 'learning_rate': 0.0001240079594662295, 'epoch': 0.63}

 63%|██████▎   | 2263/3566 [1:31:19<51:46,  2.38s/it]
 63%|██████▎   | 2264/3566 [1:31:21<51:07,  2.36s/it]
                                                     
{'loss': 1.3979, 'learning_rate': 0.00012384030564425262, 'epoch': 0.63}

 63%|██████▎   | 2264/3566 [1:31:21<51:07,  2.36s/it]
 64%|██████▎   | 2265/3566 [1:31:24<54:19,  2.51s/it]
                                                     
{'loss': 1.5716, 'learning_rate': 0.0001236727143925114, 'epoch': 0.64}

 64%|██████▎   | 2265/3566 [1:31:24<54:19,  2.51s/it]
 64%|██████▎   | 2266/3566 [1:31:27<54:00,  2.49s/it]
                                                     
{'loss': 1.4923, 'learning_rate': 0.00012350518584869325, 'epoch': 0.64}

 64%|██████▎   | 2266/3566 [1:31:27<54:00,  2.49s/it]
 64%|██████▎   | 2267/3566 [1:31:29<53:15,  2.46s/it]
                                                     
{'loss': 1.3879, 'learning_rate': 0.00012333772015043403, 'epoch': 0.64}

 64%|██████▎   | 2267/3566 [1:31:29<53:15,  2.46s/it]
 64%|██████▎   | 2268/3566 [1:31:31<52:15,  2.42s/it]
                                                     
{'loss': 1.4465, 'learning_rate': 0.0001231703174353178, 'epoch': 0.64}

 64%|██████▎   | 2268/3566 [1:31:31<52:15,  2.42s/it]
 64%|██████▎   | 2269/3566 [1:31:34<52:03,  2.41s/it]
                                                     
{'loss': 1.7336, 'learning_rate': 0.00012300297784087713, 'epoch': 0.64}

 64%|██████▎   | 2269/3566 [1:31:34<52:03,  2.41s/it]
 64%|██████▎   | 2270/3566 [1:31:36<52:46,  2.44s/it]
                                                     
{'loss': 1.6306, 'learning_rate': 0.00012283570150459244, 'epoch': 0.64}

 64%|██████▎   | 2270/3566 [1:31:36<52:46,  2.44s/it]
 64%|██████▎   | 2271/3566 [1:31:39<52:53,  2.45s/it]
                                                     
{'loss': 1.5269, 'learning_rate': 0.00012266848856389237, 'epoch': 0.64}

 64%|██████▎   | 2271/3566 [1:31:39<52:53,  2.45s/it]
 64%|██████▎   | 2272/3566 [1:31:41<53:46,  2.49s/it]
                                                     
{'loss': 1.4058, 'learning_rate': 0.00012250133915615345, 'epoch': 0.64}

 64%|██████▎   | 2272/3566 [1:31:41<53:46,  2.49s/it]
 64%|██████▎   | 2273/3566 [1:31:44<53:54,  2.50s/it]
                                                     
{'loss': 1.6563, 'learning_rate': 0.00012233425341869996, 'epoch': 0.64}

 64%|██████▎   | 2273/3566 [1:31:44<53:54,  2.50s/it]
 64%|██████▍   | 2274/3566 [1:31:47<55:27,  2.58s/it]
                                                     
{'loss': 1.5, 'learning_rate': 0.00012216723148880402, 'epoch': 0.64}

 64%|██████▍   | 2274/3566 [1:31:47<55:27,  2.58s/it]
 64%|██████▍   | 2275/3566 [1:31:49<54:51,  2.55s/it]
                                                     
{'loss': 1.6219, 'learning_rate': 0.00012200027350368508, 'epoch': 0.64}

 64%|██████▍   | 2275/3566 [1:31:49<54:51,  2.55s/it]
 64%|██████▍   | 2276/3566 [1:31:52<54:51,  2.55s/it]
                                                     
{'loss': 1.5293, 'learning_rate': 0.00012183337960051022, 'epoch': 0.64}

 64%|██████▍   | 2276/3566 [1:31:52<54:51,  2.55s/it]
 64%|██████▍   | 2277/3566 [1:31:54<54:37,  2.54s/it]
                                                     
{'loss': 1.6608, 'learning_rate': 0.00012166654991639382, 'epoch': 0.64}

 64%|██████▍   | 2277/3566 [1:31:54<54:37,  2.54s/it]
 64%|██████▍   | 2278/3566 [1:31:58<59:57,  2.79s/it]
                                                     
{'loss': 1.375, 'learning_rate': 0.00012149978458839761, 'epoch': 0.64}

 64%|██████▍   | 2278/3566 [1:31:58<59:57,  2.79s/it]
 64%|██████▍   | 2279/3566 [1:32:00<57:01,  2.66s/it]
                                                     
{'loss': 1.43, 'learning_rate': 0.0001213330837535303, 'epoch': 0.64}

 64%|██████▍   | 2279/3566 [1:32:00<57:01,  2.66s/it]
 64%|██████▍   | 2280/3566 [1:32:02<55:23,  2.58s/it]
                                                     
{'loss': 1.5436, 'learning_rate': 0.00012116644754874767, 'epoch': 0.64}

 64%|██████▍   | 2280/3566 [1:32:02<55:23,  2.58s/it]
 64%|██████▍   | 2281/3566 [1:32:05<53:48,  2.51s/it]
                                                     
{'loss': 1.542, 'learning_rate': 0.00012099987611095245, 'epoch': 0.64}

 64%|██████▍   | 2281/3566 [1:32:05<53:48,  2.51s/it]
 64%|██████▍   | 2282/3566 [1:32:07<52:23,  2.45s/it]
                                                     
{'loss': 1.5556, 'learning_rate': 0.00012083336957699405, 'epoch': 0.64}

 64%|██████▍   | 2282/3566 [1:32:07<52:23,  2.45s/it]
 64%|██████▍   | 2283/3566 [1:32:09<51:56,  2.43s/it]
                                                     
{'loss': 1.5163, 'learning_rate': 0.00012066692808366865, 'epoch': 0.64}

 64%|██████▍   | 2283/3566 [1:32:09<51:56,  2.43s/it]
 64%|██████▍   | 2284/3566 [1:32:12<53:34,  2.51s/it]
                                                     
{'loss': 1.5947, 'learning_rate': 0.00012050055176771895, 'epoch': 0.64}

 64%|██████▍   | 2284/3566 [1:32:12<53:34,  2.51s/it]
 64%|██████▍   | 2285/3566 [1:32:14<52:55,  2.48s/it]
                                                     
{'loss': 1.4247, 'learning_rate': 0.00012033424076583413, 'epoch': 0.64}

 64%|██████▍   | 2285/3566 [1:32:14<52:55,  2.48s/it]
 64%|██████▍   | 2286/3566 [1:32:17<53:24,  2.50s/it]
                                                     
{'loss': 1.5281, 'learning_rate': 0.00012016799521464976, 'epoch': 0.64}

 64%|██████▍   | 2286/3566 [1:32:17<53:24,  2.50s/it]
 64%|██████▍   | 2287/3566 [1:32:20<53:45,  2.52s/it]
                                                     
{'loss': 1.5534, 'learning_rate': 0.00012000181525074748, 'epoch': 0.64}

 64%|██████▍   | 2287/3566 [1:32:20<53:45,  2.52s/it]
 64%|██████▍   | 2288/3566 [1:32:22<54:45,  2.57s/it]
                                                     
{'loss': 1.535, 'learning_rate': 0.00011983570101065516, 'epoch': 0.64}

 64%|██████▍   | 2288/3566 [1:32:22<54:45,  2.57s/it]
 64%|██████▍   | 2289/3566 [1:32:24<52:23,  2.46s/it]
                                                     
{'loss': 1.5631, 'learning_rate': 0.00011966965263084669, 'epoch': 0.64}

 64%|██████▍   | 2289/3566 [1:32:24<52:23,  2.46s/it]
 64%|██████▍   | 2290/3566 [1:32:27<53:08,  2.50s/it]
                                                     
{'loss': 1.3464, 'learning_rate': 0.0001195036702477418, 'epoch': 0.64}

 64%|██████▍   | 2290/3566 [1:32:27<53:08,  2.50s/it]
 64%|██████▍   | 2291/3566 [1:32:29<52:12,  2.46s/it]
                                                     
{'loss': 1.5753, 'learning_rate': 0.00011933775399770599, 'epoch': 0.64}

 64%|██████▍   | 2291/3566 [1:32:29<52:12,  2.46s/it]
 64%|██████▍   | 2292/3566 [1:32:32<52:21,  2.47s/it]
                                                     
{'loss': 1.5603, 'learning_rate': 0.00011917190401705052, 'epoch': 0.64}

 64%|██████▍   | 2292/3566 [1:32:32<52:21,  2.47s/it]
 64%|██████▍   | 2293/3566 [1:32:34<50:42,  2.39s/it]
                                                     
{'loss': 1.6505, 'learning_rate': 0.00011900612044203213, 'epoch': 0.64}

 64%|██████▍   | 2293/3566 [1:32:34<50:42,  2.39s/it]
 64%|██████▍   | 2294/3566 [1:32:36<50:11,  2.37s/it]
                                                     
{'loss': 1.5396, 'learning_rate': 0.000118840403408853, 'epoch': 0.64}

 64%|██████▍   | 2294/3566 [1:32:36<50:11,  2.37s/it]
 64%|██████▍   | 2295/3566 [1:32:39<48:39,  2.30s/it]
                                                     
{'loss': 1.4766, 'learning_rate': 0.0001186747530536606, 'epoch': 0.64}

 64%|██████▍   | 2295/3566 [1:32:39<48:39,  2.30s/it]
 64%|██████▍   | 2296/3566 [1:32:41<48:42,  2.30s/it]
                                                     
{'loss': 1.3901, 'learning_rate': 0.00011850916951254773, 'epoch': 0.64}

 64%|██████▍   | 2296/3566 [1:32:41<48:42,  2.30s/it]
 64%|██████▍   | 2297/3566 [1:32:43<48:44,  2.30s/it]
                                                     
{'loss': 1.6858, 'learning_rate': 0.00011834365292155223, 'epoch': 0.64}

 64%|██████▍   | 2297/3566 [1:32:43<48:44,  2.30s/it]
 64%|██████▍   | 2298/3566 [1:32:46<49:39,  2.35s/it]
                                                     
{'loss': 1.6253, 'learning_rate': 0.00011817820341665692, 'epoch': 0.64}

 64%|██████▍   | 2298/3566 [1:32:46<49:39,  2.35s/it]
 64%|██████▍   | 2299/3566 [1:32:48<51:15,  2.43s/it]
                                                     
{'loss': 1.4976, 'learning_rate': 0.00011801282113378965, 'epoch': 0.64}

 64%|██████▍   | 2299/3566 [1:32:48<51:15,  2.43s/it]
 64%|██████▍   | 2300/3566 [1:32:51<51:08,  2.42s/it]
                                                     
{'loss': 1.4978, 'learning_rate': 0.00011784750620882277, 'epoch': 0.64}

 64%|██████▍   | 2300/3566 [1:32:51<51:08,  2.42s/it]
 65%|██████▍   | 2301/3566 [1:32:53<50:59,  2.42s/it]
                                                     
{'loss': 1.6493, 'learning_rate': 0.00011768225877757348, 'epoch': 0.65}

 65%|██████▍   | 2301/3566 [1:32:53<50:59,  2.42s/it]
 65%|██████▍   | 2302/3566 [1:32:56<52:56,  2.51s/it]
                                                     
{'loss': 1.4257, 'learning_rate': 0.00011751707897580355, 'epoch': 0.65}

 65%|██████▍   | 2302/3566 [1:32:56<52:56,  2.51s/it]
 65%|██████▍   | 2303/3566 [1:32:58<52:02,  2.47s/it]
                                                     
{'loss': 1.5828, 'learning_rate': 0.0001173519669392191, 'epoch': 0.65}

 65%|██████▍   | 2303/3566 [1:32:58<52:02,  2.47s/it]
 65%|██████▍   | 2304/3566 [1:33:01<51:52,  2.47s/it]
                                                     
{'loss': 1.4727, 'learning_rate': 0.00011718692280347065, 'epoch': 0.65}

 65%|██████▍   | 2304/3566 [1:33:01<51:52,  2.47s/it]
 65%|██████▍   | 2305/3566 [1:33:03<52:47,  2.51s/it]
                                                     
{'loss': 1.5215, 'learning_rate': 0.00011702194670415276, 'epoch': 0.65}

 65%|██████▍   | 2305/3566 [1:33:03<52:47,  2.51s/it]
 65%|██████▍   | 2306/3566 [1:33:06<52:53,  2.52s/it]
                                                     
{'loss': 1.5279, 'learning_rate': 0.00011685703877680438, 'epoch': 0.65}

 65%|██████▍   | 2306/3566 [1:33:06<52:53,  2.52s/it]
 65%|██████▍   | 2307/3566 [1:33:09<55:00,  2.62s/it]
                                                     
{'loss': 1.4682, 'learning_rate': 0.00011669219915690828, 'epoch': 0.65}

 65%|██████▍   | 2307/3566 [1:33:09<55:00,  2.62s/it]
 65%|██████▍   | 2308/3566 [1:33:11<53:53,  2.57s/it]
                                                     
{'loss': 1.5838, 'learning_rate': 0.00011652742797989109, 'epoch': 0.65}

 65%|██████▍   | 2308/3566 [1:33:11<53:53,  2.57s/it]
 65%|██████▍   | 2309/3566 [1:33:13<51:47,  2.47s/it]
                                                     
{'loss': 1.5881, 'learning_rate': 0.00011636272538112334, 'epoch': 0.65}

 65%|██████▍   | 2309/3566 [1:33:13<51:47,  2.47s/it]
 65%|██████▍   | 2310/3566 [1:33:16<52:18,  2.50s/it]
                                                     
{'loss': 1.7722, 'learning_rate': 0.00011619809149591896, 'epoch': 0.65}

 65%|██████▍   | 2310/3566 [1:33:16<52:18,  2.50s/it]
 65%|██████▍   | 2311/3566 [1:33:18<50:22,  2.41s/it]
                                                     
{'loss': 1.4385, 'learning_rate': 0.0001160335264595357, 'epoch': 0.65}

 65%|██████▍   | 2311/3566 [1:33:18<50:22,  2.41s/it]
 65%|██████▍   | 2312/3566 [1:33:20<48:51,  2.34s/it]
                                                     
{'loss': 1.507, 'learning_rate': 0.0001158690304071746, 'epoch': 0.65}

 65%|██████▍   | 2312/3566 [1:33:20<48:51,  2.34s/it]
 65%|██████▍   | 2313/3566 [1:33:23<53:02,  2.54s/it]
                                                     
{'loss': 1.5585, 'learning_rate': 0.00011570460347398013, 'epoch': 0.65}

 65%|██████▍   | 2313/3566 [1:33:23<53:02,  2.54s/it]
 65%|██████▍   | 2314/3566 [1:33:25<49:48,  2.39s/it]
                                                     
{'loss': 1.2838, 'learning_rate': 0.00011554024579503986, 'epoch': 0.65}

 65%|██████▍   | 2314/3566 [1:33:25<49:48,  2.39s/it]
 65%|██████▍   | 2315/3566 [1:33:28<53:55,  2.59s/it]
                                                     
{'loss': 1.3636, 'learning_rate': 0.00011537595750538455, 'epoch': 0.65}

 65%|██████▍   | 2315/3566 [1:33:28<53:55,  2.59s/it]
 65%|██████▍   | 2316/3566 [1:33:31<52:39,  2.53s/it]
                                                     
{'loss': 1.4372, 'learning_rate': 0.0001152117387399879, 'epoch': 0.65}

 65%|██████▍   | 2316/3566 [1:33:31<52:39,  2.53s/it]
 65%|██████▍   | 2317/3566 [1:33:33<50:52,  2.44s/it]
                                                     
{'loss': 1.619, 'learning_rate': 0.00011504758963376647, 'epoch': 0.65}

 65%|██████▍   | 2317/3566 [1:33:33<50:52,  2.44s/it]
 65%|██████▌   | 2318/3566 [1:33:35<49:57,  2.40s/it]
                                                     
{'loss': 1.4386, 'learning_rate': 0.00011488351032157969, 'epoch': 0.65}

 65%|██████▌   | 2318/3566 [1:33:35<49:57,  2.40s/it]
 65%|██████▌   | 2319/3566 [1:33:38<49:14,  2.37s/it]
                                                     
{'loss': 1.5817, 'learning_rate': 0.00011471950093822966, 'epoch': 0.65}

 65%|██████▌   | 2319/3566 [1:33:38<49:14,  2.37s/it]
 65%|██████▌   | 2320/3566 [1:33:40<49:24,  2.38s/it]
                                                     
{'loss': 1.5485, 'learning_rate': 0.00011455556161846068, 'epoch': 0.65}

 65%|██████▌   | 2320/3566 [1:33:40<49:24,  2.38s/it]
 65%|██████▌   | 2321/3566 [1:33:42<48:38,  2.34s/it]
                                                     
{'loss': 1.5227, 'learning_rate': 0.00011439169249696004, 'epoch': 0.65}

 65%|██████▌   | 2321/3566 [1:33:42<48:38,  2.34s/it]
 65%|██████▌   | 2322/3566 [1:33:45<48:31,  2.34s/it]
                                                     
{'loss': 1.4357, 'learning_rate': 0.00011422789370835696, 'epoch': 0.65}

 65%|██████▌   | 2322/3566 [1:33:45<48:31,  2.34s/it]
 65%|██████▌   | 2323/3566 [1:33:47<48:12,  2.33s/it]
                                                     
{'loss': 1.3976, 'learning_rate': 0.00011406416538722307, 'epoch': 0.65}

 65%|██████▌   | 2323/3566 [1:33:47<48:12,  2.33s/it]
 65%|██████▌   | 2324/3566 [1:33:49<48:11,  2.33s/it]
                                                     
{'loss': 1.6117, 'learning_rate': 0.00011390050766807196, 'epoch': 0.65}

 65%|██████▌   | 2324/3566 [1:33:49<48:11,  2.33s/it]
 65%|██████▌   | 2325/3566 [1:33:52<48:40,  2.35s/it]
                                                     
{'loss': 1.5457, 'learning_rate': 0.00011373692068535933, 'epoch': 0.65}

 65%|██████▌   | 2325/3566 [1:33:52<48:40,  2.35s/it]
 65%|██████▌   | 2326/3566 [1:33:54<48:14,  2.33s/it]
                                                     
{'loss': 1.4333, 'learning_rate': 0.00011357340457348274, 'epoch': 0.65}

 65%|██████▌   | 2326/3566 [1:33:54<48:14,  2.33s/it]
 65%|██████▌   | 2327/3566 [1:33:56<47:27,  2.30s/it]
                                                     
{'loss': 1.5637, 'learning_rate': 0.00011340995946678155, 'epoch': 0.65}

 65%|██████▌   | 2327/3566 [1:33:56<47:27,  2.30s/it]
 65%|██████▌   | 2328/3566 [1:33:58<47:14,  2.29s/it]
                                                     
{'loss': 1.5422, 'learning_rate': 0.0001132465854995366, 'epoch': 0.65}

 65%|██████▌   | 2328/3566 [1:33:58<47:14,  2.29s/it]
 65%|██████▌   | 2329/3566 [1:34:01<48:40,  2.36s/it]
                                                     
{'loss': 1.5266, 'learning_rate': 0.00011308328280597054, 'epoch': 0.65}

 65%|██████▌   | 2329/3566 [1:34:01<48:40,  2.36s/it]
 65%|██████▌   | 2330/3566 [1:34:03<48:11,  2.34s/it]
                                                     
{'loss': 1.5926, 'learning_rate': 0.00011292005152024732, 'epoch': 0.65}

 65%|██████▌   | 2330/3566 [1:34:03<48:11,  2.34s/it]
 65%|██████▌   | 2331/3566 [1:34:06<50:44,  2.46s/it]
                                                     
{'loss': 1.3729, 'learning_rate': 0.00011275689177647226, 'epoch': 0.65}

 65%|██████▌   | 2331/3566 [1:34:06<50:44,  2.46s/it]
 65%|██████▌   | 2332/3566 [1:34:08<49:04,  2.39s/it]
                                                     
{'loss': 1.4828, 'learning_rate': 0.00011259380370869195, 'epoch': 0.65}

 65%|██████▌   | 2332/3566 [1:34:08<49:04,  2.39s/it]
 65%|██████▌   | 2333/3566 [1:34:11<50:16,  2.45s/it]
                                                     
{'loss': 1.3943, 'learning_rate': 0.000112430787450894, 'epoch': 0.65}

 65%|██████▌   | 2333/3566 [1:34:11<50:16,  2.45s/it]
 65%|██████▌   | 2334/3566 [1:34:13<49:11,  2.40s/it]
                                                     
{'loss': 1.5332, 'learning_rate': 0.00011226784313700695, 'epoch': 0.65}

 65%|██████▌   | 2334/3566 [1:34:13<49:11,  2.40s/it]
 65%|██████▌   | 2335/3566 [1:34:15<49:21,  2.41s/it]
                                                     
{'loss': 1.5428, 'learning_rate': 0.00011210497090090069, 'epoch': 0.65}

 65%|██████▌   | 2335/3566 [1:34:15<49:21,  2.41s/it]
 66%|██████▌   | 2336/3566 [1:34:18<49:02,  2.39s/it]
                                                     
{'loss': 1.633, 'learning_rate': 0.00011194217087638523, 'epoch': 0.66}

 66%|██████▌   | 2336/3566 [1:34:18<49:02,  2.39s/it]
 66%|██████▌   | 2337/3566 [1:34:20<48:21,  2.36s/it]
                                                     
{'loss': 1.4996, 'learning_rate': 0.00011177944319721172, 'epoch': 0.66}

 66%|██████▌   | 2337/3566 [1:34:20<48:21,  2.36s/it]
 66%|██████▌   | 2338/3566 [1:34:23<48:32,  2.37s/it]
                                                     
{'loss': 1.4582, 'learning_rate': 0.00011161678799707167, 'epoch': 0.66}

 66%|██████▌   | 2338/3566 [1:34:23<48:32,  2.37s/it]
 66%|██████▌   | 2339/3566 [1:34:25<48:06,  2.35s/it]
                                                     
{'loss': 1.6072, 'learning_rate': 0.00011145420540959715, 'epoch': 0.66}

 66%|██████▌   | 2339/3566 [1:34:25<48:06,  2.35s/it]
 66%|██████▌   | 2340/3566 [1:34:27<48:39,  2.38s/it]
                                                     
{'loss': 1.6378, 'learning_rate': 0.00011129169556836055, 'epoch': 0.66}

 66%|██████▌   | 2340/3566 [1:34:27<48:39,  2.38s/it]
 66%|██████▌   | 2341/3566 [1:34:30<51:10,  2.51s/it]
                                                     
{'loss': 1.5633, 'learning_rate': 0.0001111292586068744, 'epoch': 0.66}

 66%|██████▌   | 2341/3566 [1:34:30<51:10,  2.51s/it]
 66%|██████▌   | 2342/3566 [1:34:32<49:52,  2.45s/it]
                                                     
{'loss': 1.4772, 'learning_rate': 0.00011096689465859147, 'epoch': 0.66}

 66%|██████▌   | 2342/3566 [1:34:32<49:52,  2.45s/it]
 66%|██████▌   | 2343/3566 [1:34:35<49:32,  2.43s/it]
                                                     
{'loss': 1.4045, 'learning_rate': 0.00011080460385690452, 'epoch': 0.66}

 66%|██████▌   | 2343/3566 [1:34:35<49:32,  2.43s/it]
 66%|██████▌   | 2344/3566 [1:34:38<52:06,  2.56s/it]
                                                     
{'loss': 1.5064, 'learning_rate': 0.00011064238633514625, 'epoch': 0.66}

 66%|██████▌   | 2344/3566 [1:34:38<52:06,  2.56s/it]
 66%|██████▌   | 2345/3566 [1:34:40<51:11,  2.52s/it]
                                                     
{'loss': 1.6639, 'learning_rate': 0.00011048024222658897, 'epoch': 0.66}

 66%|██████▌   | 2345/3566 [1:34:40<51:11,  2.52s/it]
 66%|██████▌   | 2346/3566 [1:34:42<49:03,  2.41s/it]
                                                     
{'loss': 1.5347, 'learning_rate': 0.00011031817166444485, 'epoch': 0.66}

 66%|██████▌   | 2346/3566 [1:34:42<49:03,  2.41s/it]
 66%|██████▌   | 2347/3566 [1:34:44<47:44,  2.35s/it]
                                                     
{'loss': 1.5482, 'learning_rate': 0.00011015617478186562, 'epoch': 0.66}

 66%|██████▌   | 2347/3566 [1:34:44<47:44,  2.35s/it]
 66%|██████▌   | 2348/3566 [1:34:47<48:32,  2.39s/it]
                                                     
{'loss': 1.4676, 'learning_rate': 0.0001099942517119424, 'epoch': 0.66}

 66%|██████▌   | 2348/3566 [1:34:47<48:32,  2.39s/it]
 66%|██████▌   | 2349/3566 [1:34:49<48:25,  2.39s/it]
                                                     
{'loss': 1.5455, 'learning_rate': 0.00010983240258770584, 'epoch': 0.66}

 66%|██████▌   | 2349/3566 [1:34:49<48:25,  2.39s/it]
 66%|██████▌   | 2350/3566 [1:34:52<49:31,  2.44s/it]
                                                     
{'loss': 1.5, 'learning_rate': 0.00010967062754212567, 'epoch': 0.66}

 66%|██████▌   | 2350/3566 [1:34:52<49:31,  2.44s/it]
 66%|██████▌   | 2351/3566 [1:34:54<49:00,  2.42s/it]
                                                     
{'loss': 1.603, 'learning_rate': 0.00010950892670811077, 'epoch': 0.66}

 66%|██████▌   | 2351/3566 [1:34:54<49:00,  2.42s/it]
 66%|██████▌   | 2352/3566 [1:34:57<49:22,  2.44s/it]
                                                     
{'loss': 1.4492, 'learning_rate': 0.00010934730021850921, 'epoch': 0.66}

 66%|██████▌   | 2352/3566 [1:34:57<49:22,  2.44s/it]
 66%|██████▌   | 2353/3566 [1:34:59<47:55,  2.37s/it]
                                                     
{'loss': 1.4355, 'learning_rate': 0.0001091857482061077, 'epoch': 0.66}

 66%|██████▌   | 2353/3566 [1:34:59<47:55,  2.37s/it]
 66%|██████▌   | 2354/3566 [1:35:01<48:27,  2.40s/it]
                                                     
{'loss': 1.4848, 'learning_rate': 0.00010902427080363198, 'epoch': 0.66}

 66%|██████▌   | 2354/3566 [1:35:01<48:27,  2.40s/it]
 66%|██████▌   | 2355/3566 [1:35:04<48:33,  2.41s/it]
                                                     
{'loss': 1.4396, 'learning_rate': 0.00010886286814374647, 'epoch': 0.66}

 66%|██████▌   | 2355/3566 [1:35:04<48:33,  2.41s/it]
 66%|██████▌   | 2356/3566 [1:35:06<49:39,  2.46s/it]
                                                     
{'loss': 1.6875, 'learning_rate': 0.00010870154035905411, 'epoch': 0.66}

 66%|██████▌   | 2356/3566 [1:35:06<49:39,  2.46s/it]
 66%|██████▌   | 2357/3566 [1:35:09<49:59,  2.48s/it]
                                                     
{'loss': 1.459, 'learning_rate': 0.0001085402875820964, 'epoch': 0.66}

 66%|██████▌   | 2357/3566 [1:35:09<49:59,  2.48s/it]
 66%|██████▌   | 2358/3566 [1:35:11<50:07,  2.49s/it]
                                                     
{'loss': 1.669, 'learning_rate': 0.00010837910994535314, 'epoch': 0.66}

 66%|██████▌   | 2358/3566 [1:35:11<50:07,  2.49s/it]
 66%|██████▌   | 2359/3566 [1:35:14<50:43,  2.52s/it]
                                                     
{'loss': 1.4651, 'learning_rate': 0.00010821800758124249, 'epoch': 0.66}

 66%|██████▌   | 2359/3566 [1:35:14<50:43,  2.52s/it]
 66%|██████▌   | 2360/3566 [1:35:16<48:54,  2.43s/it]
                                                     
{'loss': 1.5951, 'learning_rate': 0.0001080569806221207, 'epoch': 0.66}

 66%|██████▌   | 2360/3566 [1:35:16<48:54,  2.43s/it]
 66%|██████▌   | 2361/3566 [1:35:19<49:31,  2.47s/it]
                                                     
{'loss': 1.4874, 'learning_rate': 0.0001078960292002821, 'epoch': 0.66}

 66%|██████▌   | 2361/3566 [1:35:19<49:31,  2.47s/it]
 66%|██████▌   | 2362/3566 [1:35:21<49:14,  2.45s/it]
                                                     
{'loss': 1.5791, 'learning_rate': 0.0001077351534479589, 'epoch': 0.66}

 66%|██████▌   | 2362/3566 [1:35:21<49:14,  2.45s/it]
 66%|██████▋   | 2363/3566 [1:35:24<50:43,  2.53s/it]
                                                     
{'loss': 1.4951, 'learning_rate': 0.00010757435349732123, 'epoch': 0.66}

 66%|██████▋   | 2363/3566 [1:35:24<50:43,  2.53s/it]
 66%|██████▋   | 2364/3566 [1:35:26<49:11,  2.46s/it]
                                                     
{'loss': 1.4869, 'learning_rate': 0.00010741362948047691, 'epoch': 0.66}

 66%|██████▋   | 2364/3566 [1:35:26<49:11,  2.46s/it]
 66%|██████▋   | 2365/3566 [1:35:29<48:48,  2.44s/it]
                                                     
{'loss': 1.4771, 'learning_rate': 0.00010725298152947134, 'epoch': 0.66}

 66%|██████▋   | 2365/3566 [1:35:29<48:48,  2.44s/it]
 66%|██████▋   | 2366/3566 [1:35:31<47:09,  2.36s/it]
                                                     
{'loss': 1.5272, 'learning_rate': 0.0001070924097762875, 'epoch': 0.66}

 66%|██████▋   | 2366/3566 [1:35:31<47:09,  2.36s/it]
 66%|██████▋   | 2367/3566 [1:35:33<46:05,  2.31s/it]
                                                     
{'loss': 1.4979, 'learning_rate': 0.00010693191435284569, 'epoch': 0.66}

 66%|██████▋   | 2367/3566 [1:35:33<46:05,  2.31s/it]
 66%|██████▋   | 2368/3566 [1:35:35<45:56,  2.30s/it]
                                                     
{'loss': 1.4052, 'learning_rate': 0.00010677149539100355, 'epoch': 0.66}

 66%|██████▋   | 2368/3566 [1:35:35<45:56,  2.30s/it]
 66%|██████▋   | 2369/3566 [1:35:38<47:39,  2.39s/it]
                                                     
{'loss': 1.6622, 'learning_rate': 0.00010661115302255586, 'epoch': 0.66}

 66%|██████▋   | 2369/3566 [1:35:38<47:39,  2.39s/it]
 66%|██████▋   | 2370/3566 [1:35:40<48:44,  2.45s/it]
                                                     
{'loss': 1.5022, 'learning_rate': 0.00010645088737923463, 'epoch': 0.66}

 66%|██████▋   | 2370/3566 [1:35:40<48:44,  2.45s/it]
 66%|██████▋   | 2371/3566 [1:35:43<50:19,  2.53s/it]
                                                     
{'loss': 1.4967, 'learning_rate': 0.00010629069859270853, 'epoch': 0.66}

 66%|██████▋   | 2371/3566 [1:35:43<50:19,  2.53s/it]
 67%|██████▋   | 2372/3566 [1:35:46<50:13,  2.52s/it]
                                                     
{'loss': 1.5952, 'learning_rate': 0.00010613058679458332, 'epoch': 0.67}

 67%|██████▋   | 2372/3566 [1:35:46<50:13,  2.52s/it]
 67%|██████▋   | 2373/3566 [1:35:48<49:47,  2.50s/it]
                                                     
{'loss': 1.5528, 'learning_rate': 0.00010597055211640148, 'epoch': 0.67}

 67%|██████▋   | 2373/3566 [1:35:48<49:47,  2.50s/it]
 67%|██████▋   | 2374/3566 [1:35:50<48:27,  2.44s/it]
                                                     
{'loss': 1.5309, 'learning_rate': 0.00010581059468964207, 'epoch': 0.67}

 67%|██████▋   | 2374/3566 [1:35:50<48:27,  2.44s/it]
 67%|██████▋   | 2375/3566 [1:35:53<48:50,  2.46s/it]
                                                     
{'loss': 1.6464, 'learning_rate': 0.00010565071464572075, 'epoch': 0.67}

 67%|██████▋   | 2375/3566 [1:35:53<48:50,  2.46s/it]
 67%|██████▋   | 2376/3566 [1:35:56<50:12,  2.53s/it]
                                                     
{'loss': 1.5134, 'learning_rate': 0.00010549091211598949, 'epoch': 0.67}

 67%|██████▋   | 2376/3566 [1:35:56<50:12,  2.53s/it]
 67%|██████▋   | 2377/3566 [1:35:58<47:55,  2.42s/it]
                                                     
{'loss': 1.5439, 'learning_rate': 0.0001053311872317368, 'epoch': 0.67}

 67%|██████▋   | 2377/3566 [1:35:58<47:55,  2.42s/it]
 67%|██████▋   | 2378/3566 [1:36:00<46:25,  2.34s/it]
                                                     
{'loss': 1.5316, 'learning_rate': 0.00010517154012418724, 'epoch': 0.67}

 67%|██████▋   | 2378/3566 [1:36:00<46:25,  2.34s/it]
 67%|██████▋   | 2379/3566 [1:36:02<47:07,  2.38s/it]
                                                     
{'loss': 1.59, 'learning_rate': 0.00010501197092450136, 'epoch': 0.67}

 67%|██████▋   | 2379/3566 [1:36:02<47:07,  2.38s/it]
 67%|██████▋   | 2380/3566 [1:36:05<47:21,  2.40s/it]
                                                     
{'loss': 1.676, 'learning_rate': 0.00010485247976377593, 'epoch': 0.67}

 67%|██████▋   | 2380/3566 [1:36:05<47:21,  2.40s/it]
 67%|██████▋   | 2381/3566 [1:36:08<49:40,  2.52s/it]
                                                     
{'loss': 1.5727, 'learning_rate': 0.00010469306677304347, 'epoch': 0.67}

 67%|██████▋   | 2381/3566 [1:36:08<49:40,  2.52s/it]
 67%|██████▋   | 2382/3566 [1:36:10<51:21,  2.60s/it]
                                                     
{'loss': 1.521, 'learning_rate': 0.00010453373208327231, 'epoch': 0.67}

 67%|██████▋   | 2382/3566 [1:36:10<51:21,  2.60s/it]
 67%|██████▋   | 2383/3566 [1:36:13<50:20,  2.55s/it]
                                                     
{'loss': 1.4959, 'learning_rate': 0.00010437447582536645, 'epoch': 0.67}

 67%|██████▋   | 2383/3566 [1:36:13<50:20,  2.55s/it]
 67%|██████▋   | 2384/3566 [1:36:15<50:10,  2.55s/it]
                                                     
{'loss': 1.5256, 'learning_rate': 0.00010421529813016552, 'epoch': 0.67}

 67%|██████▋   | 2384/3566 [1:36:15<50:10,  2.55s/it]
 67%|██████▋   | 2385/3566 [1:36:18<50:40,  2.57s/it]
                                                     
{'loss': 1.5452, 'learning_rate': 0.00010405619912844451, 'epoch': 0.67}

 67%|██████▋   | 2385/3566 [1:36:18<50:40,  2.57s/it]
 67%|██████▋   | 2386/3566 [1:36:21<51:41,  2.63s/it]
                                                     
{'loss': 1.4568, 'learning_rate': 0.00010389717895091375, 'epoch': 0.67}

 67%|██████▋   | 2386/3566 [1:36:21<51:41,  2.63s/it]
 67%|██████▋   | 2387/3566 [1:36:23<48:06,  2.45s/it]
                                                     
{'loss': 1.4616, 'learning_rate': 0.000103738237728219, 'epoch': 0.67}

 67%|██████▋   | 2387/3566 [1:36:23<48:06,  2.45s/it]
 67%|██████▋   | 2388/3566 [1:36:25<47:29,  2.42s/it]
                                                     
{'loss': 1.5238, 'learning_rate': 0.0001035793755909408, 'epoch': 0.67}

 67%|██████▋   | 2388/3566 [1:36:25<47:29,  2.42s/it]
 67%|██████▋   | 2389/3566 [1:36:27<45:12,  2.30s/it]
                                                     
{'loss': 1.4172, 'learning_rate': 0.00010342059266959502, 'epoch': 0.67}

 67%|██████▋   | 2389/3566 [1:36:27<45:12,  2.30s/it]
 67%|██████▋   | 2390/3566 [1:36:30<46:19,  2.36s/it]
                                                     
{'loss': 1.5053, 'learning_rate': 0.00010326188909463232, 'epoch': 0.67}

 67%|██████▋   | 2390/3566 [1:36:30<46:19,  2.36s/it]
 67%|██████▋   | 2391/3566 [1:36:32<45:38,  2.33s/it]
                                                     
{'loss': 1.474, 'learning_rate': 0.0001031032649964383, 'epoch': 0.67}

 67%|██████▋   | 2391/3566 [1:36:32<45:38,  2.33s/it]
 67%|██████▋   | 2392/3566 [1:36:34<45:22,  2.32s/it]
                                                     
{'loss': 1.5216, 'learning_rate': 0.00010294472050533306, 'epoch': 0.67}

 67%|██████▋   | 2392/3566 [1:36:34<45:22,  2.32s/it]
 67%|██████▋   | 2393/3566 [1:36:37<45:42,  2.34s/it]
                                                     
{'loss': 1.5045, 'learning_rate': 0.00010278625575157148, 'epoch': 0.67}

 67%|██████▋   | 2393/3566 [1:36:37<45:42,  2.34s/it]
 67%|██████▋   | 2394/3566 [1:36:40<50:51,  2.60s/it]
                                                     
{'loss': 1.2639, 'learning_rate': 0.00010262787086534284, 'epoch': 0.67}

 67%|██████▋   | 2394/3566 [1:36:40<50:51,  2.60s/it]
 67%|██████▋   | 2395/3566 [1:36:42<49:18,  2.53s/it]
                                                     
{'loss': 1.5139, 'learning_rate': 0.00010246956597677089, 'epoch': 0.67}

 67%|██████▋   | 2395/3566 [1:36:42<49:18,  2.53s/it]
 67%|██████▋   | 2396/3566 [1:36:45<47:49,  2.45s/it]
                                                     
{'loss': 1.4366, 'learning_rate': 0.0001023113412159134, 'epoch': 0.67}

 67%|██████▋   | 2396/3566 [1:36:45<47:49,  2.45s/it]
 67%|██████▋   | 2397/3566 [1:36:47<47:21,  2.43s/it]
                                                     
{'loss': 1.6278, 'learning_rate': 0.0001021531967127626, 'epoch': 0.67}

 67%|██████▋   | 2397/3566 [1:36:47<47:21,  2.43s/it]
 67%|██████▋   | 2398/3566 [1:36:49<47:55,  2.46s/it]
                                                     
{'loss': 1.4398, 'learning_rate': 0.00010199513259724471, 'epoch': 0.67}

 67%|██████▋   | 2398/3566 [1:36:49<47:55,  2.46s/it]
 67%|██████▋   | 2399/3566 [1:36:52<46:53,  2.41s/it]
                                                     
{'loss': 1.5639, 'learning_rate': 0.00010183714899921982, 'epoch': 0.67}

 67%|██████▋   | 2399/3566 [1:36:52<46:53,  2.41s/it]
 67%|██████▋   | 2400/3566 [1:36:55<51:05,  2.63s/it]
                                                     
{'loss': 1.5194, 'learning_rate': 0.00010167924604848194, 'epoch': 0.67}

 67%|██████▋   | 2400/3566 [1:36:55<51:05,  2.63s/it]
 67%|██████▋   | 2401/3566 [1:36:57<49:01,  2.52s/it]
                                                     
{'loss': 1.6078, 'learning_rate': 0.00010152142387475883, 'epoch': 0.67}

 67%|██████▋   | 2401/3566 [1:36:57<49:01,  2.52s/it]
 67%|██████▋   | 2402/3566 [1:37:00<49:22,  2.54s/it]
                                                     
{'loss': 1.5933, 'learning_rate': 0.00010136368260771185, 'epoch': 0.67}

 67%|██████▋   | 2402/3566 [1:37:00<49:22,  2.54s/it]
 67%|██████▋   | 2403/3566 [1:37:02<49:42,  2.56s/it]
                                                     
{'loss': 1.4253, 'learning_rate': 0.00010120602237693591, 'epoch': 0.67}

 67%|██████▋   | 2403/3566 [1:37:02<49:42,  2.56s/it]
 67%|██████▋   | 2404/3566 [1:37:05<48:46,  2.52s/it]
                                                     
{'loss': 1.5834, 'learning_rate': 0.00010104844331195931, 'epoch': 0.67}

 67%|██████▋   | 2404/3566 [1:37:05<48:46,  2.52s/it]
 67%|██████▋   | 2405/3566 [1:37:07<47:48,  2.47s/it]
                                                     
{'loss': 1.5484, 'learning_rate': 0.00010089094554224372, 'epoch': 0.67}

 67%|██████▋   | 2405/3566 [1:37:07<47:48,  2.47s/it]
 67%|██████▋   | 2406/3566 [1:37:10<47:39,  2.47s/it]
                                                     
{'loss': 1.5717, 'learning_rate': 0.00010073352919718401, 'epoch': 0.67}

 67%|██████▋   | 2406/3566 [1:37:10<47:39,  2.47s/it]
 67%|██████▋   | 2407/3566 [1:37:13<52:21,  2.71s/it]
                                                     
{'loss': 1.5063, 'learning_rate': 0.00010057619440610811, 'epoch': 0.67}

 67%|██████▋   | 2407/3566 [1:37:13<52:21,  2.71s/it]
 68%|██████▊   | 2408/3566 [1:37:15<50:50,  2.63s/it]
                                                     
{'loss': 1.4809, 'learning_rate': 0.00010041894129827698, 'epoch': 0.68}

 68%|██████▊   | 2408/3566 [1:37:15<50:50,  2.63s/it]
 68%|██████▊   | 2409/3566 [1:37:18<49:31,  2.57s/it]
                                                     
{'loss': 1.5223, 'learning_rate': 0.00010026177000288449, 'epoch': 0.68}

 68%|██████▊   | 2409/3566 [1:37:18<49:31,  2.57s/it]
 68%|██████▊   | 2410/3566 [1:37:20<48:20,  2.51s/it]
                                                     
{'loss': 1.5235, 'learning_rate': 0.00010010468064905725, 'epoch': 0.68}

 68%|██████▊   | 2410/3566 [1:37:20<48:20,  2.51s/it]
 68%|██████▊   | 2411/3566 [1:37:22<46:02,  2.39s/it]
                                                     
{'loss': 1.5308, 'learning_rate': 9.994767336585458e-05, 'epoch': 0.68}

 68%|██████▊   | 2411/3566 [1:37:22<46:02,  2.39s/it]
 68%|██████▊   | 2412/3566 [1:37:25<47:22,  2.46s/it]
                                                     
{'loss': 1.4919, 'learning_rate': 9.979074828226837e-05, 'epoch': 0.68}

 68%|██████▊   | 2412/3566 [1:37:25<47:22,  2.46s/it]
 68%|██████▊   | 2413/3566 [1:37:27<47:22,  2.47s/it]
                                                     
{'loss': 1.4253, 'learning_rate': 9.963390552722304e-05, 'epoch': 0.68}

 68%|██████▊   | 2413/3566 [1:37:27<47:22,  2.47s/it]
 68%|██████▊   | 2414/3566 [1:37:30<46:20,  2.41s/it]
                                                     
{'loss': 1.4384, 'learning_rate': 9.947714522957519e-05, 'epoch': 0.68}

 68%|██████▊   | 2414/3566 [1:37:30<46:20,  2.41s/it]
 68%|██████▊   | 2415/3566 [1:37:32<45:55,  2.39s/it]
                                                     
{'loss': 1.4003, 'learning_rate': 9.932046751811384e-05, 'epoch': 0.68}

 68%|██████▊   | 2415/3566 [1:37:32<45:55,  2.39s/it]
 68%|██████▊   | 2416/3566 [1:37:35<47:36,  2.48s/it]
                                                     
{'loss': 1.5228, 'learning_rate': 9.91638725215601e-05, 'epoch': 0.68}

 68%|██████▊   | 2416/3566 [1:37:35<47:36,  2.48s/it]
 68%|██████▊   | 2417/3566 [1:37:37<47:09,  2.46s/it]
                                                     
{'loss': 1.5091, 'learning_rate': 9.900736036856718e-05, 'epoch': 0.68}

 68%|██████▊   | 2417/3566 [1:37:37<47:09,  2.46s/it]
 68%|██████▊   | 2418/3566 [1:37:39<46:01,  2.41s/it]
                                                     
{'loss': 1.5672, 'learning_rate': 9.885093118772006e-05, 'epoch': 0.68}

 68%|██████▊   | 2418/3566 [1:37:39<46:01,  2.41s/it]
 68%|██████▊   | 2419/3566 [1:37:42<46:14,  2.42s/it]
                                                     
{'loss': 1.5597, 'learning_rate': 9.869458510753587e-05, 'epoch': 0.68}

 68%|██████▊   | 2419/3566 [1:37:42<46:14,  2.42s/it]
 68%|██████▊   | 2420/3566 [1:37:44<45:58,  2.41s/it]
                                                     
{'loss': 1.3927, 'learning_rate': 9.853832225646318e-05, 'epoch': 0.68}

 68%|██████▊   | 2420/3566 [1:37:44<45:58,  2.41s/it]
 68%|██████▊   | 2421/3566 [1:37:47<47:43,  2.50s/it]
                                                     
{'loss': 1.6494, 'learning_rate': 9.838214276288233e-05, 'epoch': 0.68}

 68%|██████▊   | 2421/3566 [1:37:47<47:43,  2.50s/it]
 68%|██████▊   | 2422/3566 [1:37:50<49:16,  2.58s/it]
                                                     
{'loss': 1.5582, 'learning_rate': 9.822604675510503e-05, 'epoch': 0.68}

 68%|██████▊   | 2422/3566 [1:37:50<49:16,  2.58s/it]
 68%|██████▊   | 2423/3566 [1:37:52<49:47,  2.61s/it]
                                                     
{'loss': 1.6884, 'learning_rate': 9.807003436137452e-05, 'epoch': 0.68}

 68%|██████▊   | 2423/3566 [1:37:52<49:47,  2.61s/it]
 68%|██████▊   | 2424/3566 [1:37:55<48:16,  2.54s/it]
                                                     
{'loss': 1.4817, 'learning_rate': 9.791410570986534e-05, 'epoch': 0.68}

 68%|██████▊   | 2424/3566 [1:37:55<48:16,  2.54s/it]
 68%|██████▊   | 2425/3566 [1:37:57<47:43,  2.51s/it]
                                                     
{'loss': 1.4094, 'learning_rate': 9.775826092868321e-05, 'epoch': 0.68}

 68%|██████▊   | 2425/3566 [1:37:57<47:43,  2.51s/it]
 68%|██████▊   | 2426/3566 [1:38:00<50:56,  2.68s/it]
                                                     
{'loss': 1.5131, 'learning_rate': 9.760250014586495e-05, 'epoch': 0.68}

 68%|██████▊   | 2426/3566 [1:38:00<50:56,  2.68s/it]
 68%|██████▊   | 2427/3566 [1:38:03<49:30,  2.61s/it]
                                                     
{'loss': 1.3778, 'learning_rate': 9.744682348937835e-05, 'epoch': 0.68}

 68%|██████▊   | 2427/3566 [1:38:03<49:30,  2.61s/it]
 68%|██████▊   | 2428/3566 [1:38:05<49:15,  2.60s/it]
                                                     
{'loss': 1.5111, 'learning_rate': 9.729123108712212e-05, 'epoch': 0.68}

 68%|██████▊   | 2428/3566 [1:38:05<49:15,  2.60s/it]
 68%|██████▊   | 2429/3566 [1:38:07<46:38,  2.46s/it]
                                                     
{'loss': 1.4977, 'learning_rate': 9.713572306692571e-05, 'epoch': 0.68}

 68%|██████▊   | 2429/3566 [1:38:07<46:38,  2.46s/it]
 68%|██████▊   | 2430/3566 [1:38:10<44:59,  2.38s/it]
                                                     
{'loss': 1.4208, 'learning_rate': 9.698029955654932e-05, 'epoch': 0.68}

 68%|██████▊   | 2430/3566 [1:38:10<44:59,  2.38s/it]
 68%|██████▊   | 2431/3566 [1:38:12<43:49,  2.32s/it]
                                                     
{'loss': 1.477, 'learning_rate': 9.682496068368356e-05, 'epoch': 0.68}

 68%|██████▊   | 2431/3566 [1:38:12<43:49,  2.32s/it]
 68%|██████▊   | 2432/3566 [1:38:14<43:35,  2.31s/it]
                                                     
{'loss': 1.5122, 'learning_rate': 9.666970657594958e-05, 'epoch': 0.68}

 68%|██████▊   | 2432/3566 [1:38:14<43:35,  2.31s/it]
 68%|██████▊   | 2433/3566 [1:38:16<43:40,  2.31s/it]
                                                     
{'loss': 1.491, 'learning_rate': 9.651453736089908e-05, 'epoch': 0.68}

 68%|██████▊   | 2433/3566 [1:38:16<43:40,  2.31s/it]
 68%|██████▊   | 2434/3566 [1:38:19<43:48,  2.32s/it]
                                                     
{'loss': 1.3928, 'learning_rate': 9.635945316601378e-05, 'epoch': 0.68}

 68%|██████▊   | 2434/3566 [1:38:19<43:48,  2.32s/it]
 68%|██████▊   | 2435/3566 [1:38:21<45:17,  2.40s/it]
                                                     
{'loss': 1.6135, 'learning_rate': 9.62044541187056e-05, 'epoch': 0.68}

 68%|██████▊   | 2435/3566 [1:38:21<45:17,  2.40s/it]
 68%|██████▊   | 2436/3566 [1:38:24<45:24,  2.41s/it]
                                                     
{'loss': 1.5173, 'learning_rate': 9.604954034631655e-05, 'epoch': 0.68}

 68%|██████▊   | 2436/3566 [1:38:24<45:24,  2.41s/it]
 68%|██████▊   | 2437/3566 [1:38:27<48:03,  2.55s/it]
                                                     
{'loss': 1.4699, 'learning_rate': 9.589471197611852e-05, 'epoch': 0.68}

 68%|██████▊   | 2437/3566 [1:38:27<48:03,  2.55s/it]
 68%|██████▊   | 2438/3566 [1:38:29<47:04,  2.50s/it]
                                                     
{'loss': 1.5679, 'learning_rate': 9.573996913531342e-05, 'epoch': 0.68}

 68%|██████▊   | 2438/3566 [1:38:29<47:04,  2.50s/it]
 68%|██████▊   | 2439/3566 [1:38:31<45:18,  2.41s/it]
                                                     
{'loss': 1.5441, 'learning_rate': 9.558531195103255e-05, 'epoch': 0.68}

 68%|██████▊   | 2439/3566 [1:38:31<45:18,  2.41s/it]
 68%|██████▊   | 2440/3566 [1:38:33<44:07,  2.35s/it]
                                                     
{'loss': 1.5289, 'learning_rate': 9.543074055033712e-05, 'epoch': 0.68}

 68%|██████▊   | 2440/3566 [1:38:33<44:07,  2.35s/it]
 68%|██████▊   | 2441/3566 [1:38:36<44:42,  2.38s/it]
                                                     
{'loss': 1.6738, 'learning_rate': 9.52762550602178e-05, 'epoch': 0.68}

 68%|██████▊   | 2441/3566 [1:38:36<44:42,  2.38s/it]
 68%|██████▊   | 2442/3566 [1:38:39<46:38,  2.49s/it]
                                                     
{'loss': 1.3932, 'learning_rate': 9.512185560759461e-05, 'epoch': 0.68}

 68%|██████▊   | 2442/3566 [1:38:39<46:38,  2.49s/it]
 69%|██████▊   | 2443/3566 [1:38:41<45:34,  2.44s/it]
                                                     
{'loss': 1.5253, 'learning_rate': 9.496754231931698e-05, 'epoch': 0.69}

 69%|██████▊   | 2443/3566 [1:38:41<45:34,  2.44s/it]
 69%|██████▊   | 2444/3566 [1:38:43<44:57,  2.40s/it]
                                                     
{'loss': 1.5823, 'learning_rate': 9.481331532216347e-05, 'epoch': 0.69}

 69%|██████▊   | 2444/3566 [1:38:43<44:57,  2.40s/it]
 69%|██████▊   | 2445/3566 [1:38:46<44:35,  2.39s/it]
                                                     
{'loss': 1.3889, 'learning_rate': 9.465917474284178e-05, 'epoch': 0.69}

 69%|██████▊   | 2445/3566 [1:38:46<44:35,  2.39s/it]
 69%|██████▊   | 2446/3566 [1:38:48<43:45,  2.34s/it]
                                                     
{'loss': 1.4834, 'learning_rate': 9.450512070798865e-05, 'epoch': 0.69}

 69%|██████▊   | 2446/3566 [1:38:48<43:45,  2.34s/it]
 69%|██████▊   | 2447/3566 [1:38:50<43:17,  2.32s/it]
                                                     
{'loss': 1.3755, 'learning_rate': 9.435115334416962e-05, 'epoch': 0.69}

 69%|██████▊   | 2447/3566 [1:38:50<43:17,  2.32s/it]
 69%|██████▊   | 2448/3566 [1:38:53<44:15,  2.37s/it]
                                                     
{'loss': 1.49, 'learning_rate': 9.419727277787913e-05, 'epoch': 0.69}

 69%|██████▊   | 2448/3566 [1:38:53<44:15,  2.37s/it]
 69%|██████▊   | 2449/3566 [1:38:55<43:51,  2.36s/it]
                                                     
{'loss': 1.5251, 'learning_rate': 9.404347913554024e-05, 'epoch': 0.69}

 69%|██████▊   | 2449/3566 [1:38:55<43:51,  2.36s/it]
 69%|██████▊   | 2450/3566 [1:38:58<46:23,  2.49s/it]
                                                     
{'loss': 1.543, 'learning_rate': 9.388977254350461e-05, 'epoch': 0.69}

 69%|██████▊   | 2450/3566 [1:38:58<46:23,  2.49s/it]
 69%|██████▊   | 2451/3566 [1:39:00<44:01,  2.37s/it]
                                                     
{'loss': 1.4452, 'learning_rate': 9.373615312805242e-05, 'epoch': 0.69}

 69%|██████▊   | 2451/3566 [1:39:00<44:01,  2.37s/it]
 69%|██████▉   | 2452/3566 [1:39:02<44:59,  2.42s/it]
                                                     
{'loss': 1.5157, 'learning_rate': 9.358262101539217e-05, 'epoch': 0.69}

 69%|██████▉   | 2452/3566 [1:39:02<44:59,  2.42s/it]
 69%|██████▉   | 2453/3566 [1:39:05<44:14,  2.38s/it]
                                                     
{'loss': 1.5573, 'learning_rate': 9.342917633166066e-05, 'epoch': 0.69}

 69%|██████▉   | 2453/3566 [1:39:05<44:14,  2.38s/it]
 69%|██████▉   | 2454/3566 [1:39:07<43:14,  2.33s/it]
                                                     
{'loss': 1.588, 'learning_rate': 9.327581920292292e-05, 'epoch': 0.69}

 69%|██████▉   | 2454/3566 [1:39:07<43:14,  2.33s/it]
 69%|██████▉   | 2455/3566 [1:39:09<43:01,  2.32s/it]
                                                     
{'loss': 1.4344, 'learning_rate': 9.312254975517194e-05, 'epoch': 0.69}

 69%|██████▉   | 2455/3566 [1:39:09<43:01,  2.32s/it]
 69%|██████▉   | 2456/3566 [1:39:12<43:55,  2.37s/it]
                                                     
{'loss': 1.4057, 'learning_rate': 9.296936811432881e-05, 'epoch': 0.69}

 69%|██████▉   | 2456/3566 [1:39:12<43:55,  2.37s/it]
 69%|██████▉   | 2457/3566 [1:39:14<44:05,  2.39s/it]
                                                     
{'loss': 1.3291, 'learning_rate': 9.281627440624228e-05, 'epoch': 0.69}

 69%|██████▉   | 2457/3566 [1:39:14<44:05,  2.39s/it]
 69%|██████▉   | 2458/3566 [1:39:17<45:22,  2.46s/it]
                                                     
{'loss': 1.5251, 'learning_rate': 9.2663268756689e-05, 'epoch': 0.69}

 69%|██████▉   | 2458/3566 [1:39:17<45:22,  2.46s/it]
 69%|██████▉   | 2459/3566 [1:39:19<46:37,  2.53s/it]
                                                     
{'loss': 1.5803, 'learning_rate': 9.25103512913733e-05, 'epoch': 0.69}

 69%|██████▉   | 2459/3566 [1:39:19<46:37,  2.53s/it]
 69%|██████▉   | 2460/3566 [1:39:22<44:37,  2.42s/it]
                                                     
{'loss': 1.417, 'learning_rate': 9.235752213592693e-05, 'epoch': 0.69}

 69%|██████▉   | 2460/3566 [1:39:22<44:37,  2.42s/it]
 69%|██████▉   | 2461/3566 [1:39:24<44:16,  2.40s/it]
                                                     
{'loss': 1.5755, 'learning_rate': 9.220478141590927e-05, 'epoch': 0.69}

 69%|██████▉   | 2461/3566 [1:39:24<44:16,  2.40s/it]
 69%|██████▉   | 2462/3566 [1:39:26<43:54,  2.39s/it]
                                                     
{'loss': 1.508, 'learning_rate': 9.205212925680692e-05, 'epoch': 0.69}

 69%|██████▉   | 2462/3566 [1:39:26<43:54,  2.39s/it]
 69%|██████▉   | 2463/3566 [1:39:28<42:42,  2.32s/it]
                                                     
{'loss': 1.5722, 'learning_rate': 9.189956578403374e-05, 'epoch': 0.69}

 69%|██████▉   | 2463/3566 [1:39:28<42:42,  2.32s/it]
 69%|██████▉   | 2464/3566 [1:39:31<43:49,  2.39s/it]
                                                     
{'loss': 1.5893, 'learning_rate': 9.174709112293079e-05, 'epoch': 0.69}

 69%|██████▉   | 2464/3566 [1:39:31<43:49,  2.39s/it]
 69%|██████▉   | 2465/3566 [1:39:33<43:34,  2.37s/it]
                                                     
{'loss': 1.4371, 'learning_rate': 9.159470539876596e-05, 'epoch': 0.69}

 69%|██████▉   | 2465/3566 [1:39:33<43:34,  2.37s/it]
 69%|██████▉   | 2466/3566 [1:39:36<43:10,  2.35s/it]
                                                     
{'loss': 1.5099, 'learning_rate': 9.144240873673429e-05, 'epoch': 0.69}

 69%|██████▉   | 2466/3566 [1:39:36<43:10,  2.35s/it]
 69%|██████▉   | 2467/3566 [1:39:38<45:24,  2.48s/it]
                                                     
{'loss': 1.6186, 'learning_rate': 9.129020126195758e-05, 'epoch': 0.69}

 69%|██████▉   | 2467/3566 [1:39:38<45:24,  2.48s/it]
 69%|██████▉   | 2468/3566 [1:39:41<45:29,  2.49s/it]
                                                     
{'loss': 1.6048, 'learning_rate': 9.11380830994844e-05, 'epoch': 0.69}

 69%|██████▉   | 2468/3566 [1:39:41<45:29,  2.49s/it]
 69%|██████▉   | 2469/3566 [1:39:43<44:30,  2.43s/it]
                                                     
{'loss': 1.4751, 'learning_rate': 9.098605437428982e-05, 'epoch': 0.69}

 69%|██████▉   | 2469/3566 [1:39:43<44:30,  2.43s/it]
 69%|██████▉   | 2470/3566 [1:39:45<43:02,  2.36s/it]
                                                     
{'loss': 1.5798, 'learning_rate': 9.083411521127558e-05, 'epoch': 0.69}

 69%|██████▉   | 2470/3566 [1:39:45<43:02,  2.36s/it]
 69%|██████▉   | 2471/3566 [1:39:48<42:42,  2.34s/it]
                                                     
{'loss': 1.5071, 'learning_rate': 9.068226573526976e-05, 'epoch': 0.69}

 69%|██████▉   | 2471/3566 [1:39:48<42:42,  2.34s/it]
 69%|██████▉   | 2472/3566 [1:39:50<41:20,  2.27s/it]
                                                     
{'loss': 1.4278, 'learning_rate': 9.053050607102676e-05, 'epoch': 0.69}

 69%|██████▉   | 2472/3566 [1:39:50<41:20,  2.27s/it]
 69%|██████▉   | 2473/3566 [1:39:52<41:30,  2.28s/it]
                                                     
{'loss': 1.6747, 'learning_rate': 9.037883634322725e-05, 'epoch': 0.69}

 69%|██████▉   | 2473/3566 [1:39:52<41:30,  2.28s/it]
 69%|██████▉   | 2474/3566 [1:39:54<40:24,  2.22s/it]
                                                     
{'loss': 1.3934, 'learning_rate': 9.022725667647784e-05, 'epoch': 0.69}

 69%|██████▉   | 2474/3566 [1:39:54<40:24,  2.22s/it]
 69%|██████▉   | 2475/3566 [1:39:57<41:09,  2.26s/it]
                                                     
{'loss': 1.3874, 'learning_rate': 9.007576719531127e-05, 'epoch': 0.69}

 69%|██████▉   | 2475/3566 [1:39:57<41:09,  2.26s/it]
 69%|██████▉   | 2476/3566 [1:39:59<41:18,  2.27s/it]
                                                     
{'loss': 1.5141, 'learning_rate': 8.992436802418635e-05, 'epoch': 0.69}

 69%|██████▉   | 2476/3566 [1:39:59<41:18,  2.27s/it]
 69%|██████▉   | 2477/3566 [1:40:01<41:26,  2.28s/it]
                                                     
{'loss': 1.6001, 'learning_rate': 8.977305928748743e-05, 'epoch': 0.69}

 69%|██████▉   | 2477/3566 [1:40:01<41:26,  2.28s/it]
 69%|██████▉   | 2478/3566 [1:40:04<43:43,  2.41s/it]
                                                     
{'loss': 1.5519, 'learning_rate': 8.962184110952466e-05, 'epoch': 0.69}

 69%|██████▉   | 2478/3566 [1:40:04<43:43,  2.41s/it]
 70%|██████▉   | 2479/3566 [1:40:06<43:45,  2.42s/it]
                                                     
{'loss': 1.4319, 'learning_rate': 8.947071361453381e-05, 'epoch': 0.7}

 70%|██████▉   | 2479/3566 [1:40:06<43:45,  2.42s/it]
 70%|██████▉   | 2480/3566 [1:40:09<46:42,  2.58s/it]
                                                     
{'loss': 1.3896, 'learning_rate': 8.931967692667613e-05, 'epoch': 0.7}

 70%|██████▉   | 2480/3566 [1:40:09<46:42,  2.58s/it]
 70%|██████▉   | 2481/3566 [1:40:11<44:50,  2.48s/it]
                                                     
{'loss': 1.5239, 'learning_rate': 8.916873117003834e-05, 'epoch': 0.7}

 70%|██████▉   | 2481/3566 [1:40:11<44:50,  2.48s/it]
 70%|██████▉   | 2482/3566 [1:40:14<44:20,  2.45s/it]
                                                     
{'loss': 1.5354, 'learning_rate': 8.916873117003834e-05, 'epoch': 0.7}

 70%|██████▉   | 2482/3566 [1:40:14<44:20,  2.45s/it]
 70%|██████▉   | 2483/3566 [1:40:16<43:42,  2.42s/it]
                                                     
{'loss': 1.4435, 'learning_rate': 8.901787646863224e-05, 'epoch': 0.7}

 70%|██████▉   | 2483/3566 [1:40:16<43:42,  2.42s/it]
 70%|██████▉   | 2484/3566 [1:40:19<43:51,  2.43s/it]
                                                     
{'loss': 1.6518, 'learning_rate': 8.886711294639505e-05, 'epoch': 0.7}

 70%|██████▉   | 2484/3566 [1:40:19<43:51,  2.43s/it]
 70%|██████▉   | 2485/3566 [1:40:21<42:05,  2.34s/it]
                                                     
{'loss': 1.3866, 'learning_rate': 8.871644072718894e-05, 'epoch': 0.7}

 70%|██████▉   | 2485/3566 [1:40:21<42:05,  2.34s/it]
 70%|██████▉   | 2486/3566 [1:40:23<42:17,  2.35s/it]
                                                     
{'loss': 1.5002, 'learning_rate': 8.856585993480117e-05, 'epoch': 0.7}

 70%|██████▉   | 2486/3566 [1:40:23<42:17,  2.35s/it]
 70%|██████▉   | 2487/3566 [1:40:26<42:47,  2.38s/it]
                                                     
{'loss': 1.4174, 'learning_rate': 8.841537069294386e-05, 'epoch': 0.7}

 70%|██████▉   | 2487/3566 [1:40:26<42:47,  2.38s/it]
 70%|██████▉   | 2488/3566 [1:40:28<42:25,  2.36s/it]
                                                     
{'loss': 1.5096, 'learning_rate': 8.826497312525383e-05, 'epoch': 0.7}

 70%|██████▉   | 2488/3566 [1:40:28<42:25,  2.36s/it]
 70%|██████▉   | 2489/3566 [1:40:31<45:05,  2.51s/it]
                                                     
{'loss': 1.6723, 'learning_rate': 8.811466735529271e-05, 'epoch': 0.7}

 70%|██████▉   | 2489/3566 [1:40:31<45:05,  2.51s/it]
 70%|██████▉   | 2490/3566 [1:40:33<43:53,  2.45s/it]
                                                     
{'loss': 1.4855, 'learning_rate': 8.796445350654658e-05, 'epoch': 0.7}

 70%|██████▉   | 2490/3566 [1:40:33<43:53,  2.45s/it]
 70%|██████▉   | 2491/3566 [1:40:35<42:26,  2.37s/it]
                                                     
{'loss': 1.4255, 'learning_rate': 8.781433170242614e-05, 'epoch': 0.7}

 70%|██████▉   | 2491/3566 [1:40:35<42:26,  2.37s/it]
 70%|██████▉   | 2492/3566 [1:40:38<43:17,  2.42s/it]
                                                     
{'loss': 1.5642, 'learning_rate': 8.766430206626637e-05, 'epoch': 0.7}

 70%|██████▉   | 2492/3566 [1:40:38<43:17,  2.42s/it]
 70%|██████▉   | 2493/3566 [1:40:40<43:16,  2.42s/it]
                                                     
{'loss': 1.6323, 'learning_rate': 8.751436472132655e-05, 'epoch': 0.7}

 70%|██████▉   | 2493/3566 [1:40:40<43:16,  2.42s/it]
 70%|██████▉   | 2494/3566 [1:40:42<41:20,  2.31s/it]
                                                     
{'loss': 1.4955, 'learning_rate': 8.736451979079016e-05, 'epoch': 0.7}

 70%|██████▉   | 2494/3566 [1:40:42<41:20,  2.31s/it]
 70%|██████▉   | 2495/3566 [1:40:45<43:25,  2.43s/it]
                                                     
{'loss': 1.4444, 'learning_rate': 8.721476739776475e-05, 'epoch': 0.7}

 70%|██████▉   | 2495/3566 [1:40:45<43:25,  2.43s/it]
 70%|██████▉   | 2496/3566 [1:40:47<42:16,  2.37s/it]
                                                     
{'loss': 1.2431, 'learning_rate': 8.70651076652818e-05, 'epoch': 0.7}

 70%|██████▉   | 2496/3566 [1:40:47<42:16,  2.37s/it]
 70%|███████   | 2497/3566 [1:40:49<40:54,  2.30s/it]
                                                     
{'loss': 1.5567, 'learning_rate': 8.691554071629673e-05, 'epoch': 0.7}

 70%|███████   | 2497/3566 [1:40:49<40:54,  2.30s/it]
 70%|███████   | 2498/3566 [1:40:52<40:52,  2.30s/it]
                                                     
{'loss': 1.6115, 'learning_rate': 8.67660666736887e-05, 'epoch': 0.7}

 70%|███████   | 2498/3566 [1:40:52<40:52,  2.30s/it]
 70%|███████   | 2499/3566 [1:40:54<43:03,  2.42s/it]
                                                     
{'loss': 1.5559, 'learning_rate': 8.661668566026051e-05, 'epoch': 0.7}

 70%|███████   | 2499/3566 [1:40:54<43:03,  2.42s/it]
 70%|███████   | 2500/3566 [1:40:57<43:20,  2.44s/it]
                                                     
{'loss': 1.6122, 'learning_rate': 8.646739779873865e-05, 'epoch': 0.7}

 70%|███████   | 2500/3566 [1:40:57<43:20,  2.44s/it]
 70%|███████   | 2501/3566 [1:41:00<45:19,  2.55s/it]
                                                     
{'loss': 1.5122, 'learning_rate': 8.631820321177286e-05, 'epoch': 0.7}

 70%|███████   | 2501/3566 [1:41:00<45:19,  2.55s/it]
 70%|███████   | 2502/3566 [1:41:02<43:54,  2.48s/it]
                                                     
{'loss': 1.543, 'learning_rate': 8.616910202193644e-05, 'epoch': 0.7}

 70%|███████   | 2502/3566 [1:41:02<43:54,  2.48s/it]
 70%|███████   | 2503/3566 [1:41:04<42:27,  2.40s/it]
                                                     
{'loss': 1.5318, 'learning_rate': 8.602009435172589e-05, 'epoch': 0.7}

 70%|███████   | 2503/3566 [1:41:04<42:27,  2.40s/it]
 70%|███████   | 2504/3566 [1:41:07<42:04,  2.38s/it]
                                                     
{'loss': 1.7923, 'learning_rate': 8.587118032356083e-05, 'epoch': 0.7}

 70%|███████   | 2504/3566 [1:41:07<42:04,  2.38s/it]
 70%|███████   | 2505/3566 [1:41:09<41:06,  2.33s/it]
                                                     
{'loss': 1.4695, 'learning_rate': 8.572236005978413e-05, 'epoch': 0.7}

 70%|███████   | 2505/3566 [1:41:09<41:06,  2.33s/it]
 70%|███████   | 2506/3566 [1:41:11<43:10,  2.44s/it]
                                                     
{'loss': 1.594, 'learning_rate': 8.557363368266144e-05, 'epoch': 0.7}

 70%|███████   | 2506/3566 [1:41:11<43:10,  2.44s/it]
 70%|███████   | 2507/3566 [1:41:14<43:31,  2.47s/it]
                                                     
{'loss': 1.4904, 'learning_rate': 8.542500131438133e-05, 'epoch': 0.7}

 70%|███████   | 2507/3566 [1:41:14<43:31,  2.47s/it]
 70%|███████   | 2508/3566 [1:41:17<45:22,  2.57s/it]
                                                     
{'loss': 1.5393, 'learning_rate': 8.527646307705522e-05, 'epoch': 0.7}

 70%|███████   | 2508/3566 [1:41:17<45:22,  2.57s/it]
 70%|███████   | 2509/3566 [1:41:19<44:23,  2.52s/it]
                                                     
{'loss': 1.616, 'learning_rate': 8.512801909271695e-05, 'epoch': 0.7}

 70%|███████   | 2509/3566 [1:41:19<44:23,  2.52s/it]
 70%|███████   | 2510/3566 [1:41:22<44:19,  2.52s/it]
                                                     
{'loss': 1.5029, 'learning_rate': 8.497966948332319e-05, 'epoch': 0.7}

 70%|███████   | 2510/3566 [1:41:22<44:19,  2.52s/it]
 70%|███████   | 2511/3566 [1:41:24<44:02,  2.50s/it]
                                                     
{'loss': 1.6116, 'learning_rate': 8.483141437075295e-05, 'epoch': 0.7}

 70%|███████   | 2511/3566 [1:41:24<44:02,  2.50s/it]
 70%|███████   | 2512/3566 [1:41:27<43:53,  2.50s/it]
                                                     
{'loss': 1.5275, 'learning_rate': 8.468325387680764e-05, 'epoch': 0.7}

 70%|███████   | 2512/3566 [1:41:27<43:53,  2.50s/it]
 70%|███████   | 2513/3566 [1:41:29<44:48,  2.55s/it]
                                                     
{'loss': 1.7031, 'learning_rate': 8.45351881232109e-05, 'epoch': 0.7}

 70%|███████   | 2513/3566 [1:41:29<44:48,  2.55s/it]
 70%|███████   | 2514/3566 [1:41:32<44:04,  2.51s/it]
                                                     
{'loss': 1.4223, 'learning_rate': 8.43872172316086e-05, 'epoch': 0.7}

 70%|███████   | 2514/3566 [1:41:32<44:04,  2.51s/it]
 71%|███████   | 2515/3566 [1:41:34<45:15,  2.58s/it]
                                                     
{'loss': 1.5525, 'learning_rate': 8.423934132356863e-05, 'epoch': 0.71}

 71%|███████   | 2515/3566 [1:41:35<45:15,  2.58s/it]
 71%|███████   | 2516/3566 [1:41:37<43:46,  2.50s/it]
                                                     
{'loss': 1.608, 'learning_rate': 8.409156052058083e-05, 'epoch': 0.71}

 71%|███████   | 2516/3566 [1:41:37<43:46,  2.50s/it]
 71%|███████   | 2517/3566 [1:41:39<42:48,  2.45s/it]
                                                     
{'loss': 1.4686, 'learning_rate': 8.394387494405698e-05, 'epoch': 0.71}

 71%|███████   | 2517/3566 [1:41:39<42:48,  2.45s/it]
 71%|███████   | 2518/3566 [1:41:42<43:16,  2.48s/it]
                                                     
{'loss': 1.5268, 'learning_rate': 8.379628471533037e-05, 'epoch': 0.71}

 71%|███████   | 2518/3566 [1:41:42<43:16,  2.48s/it]
 71%|███████   | 2519/3566 [1:41:44<42:25,  2.43s/it]
                                                     
{'loss': 1.3577, 'learning_rate': 8.364878995565637e-05, 'epoch': 0.71}

 71%|███████   | 2519/3566 [1:41:44<42:25,  2.43s/it]
 71%|███████   | 2520/3566 [1:41:46<41:04,  2.36s/it]
                                                     
{'loss': 1.4323, 'learning_rate': 8.350139078621162e-05, 'epoch': 0.71}

 71%|███████   | 2520/3566 [1:41:46<41:04,  2.36s/it]
 71%|███████   | 2521/3566 [1:41:48<40:15,  2.31s/it]
                                                     
{'loss': 1.4828, 'learning_rate': 8.335408732809432e-05, 'epoch': 0.71}

 71%|███████   | 2521/3566 [1:41:48<40:15,  2.31s/it]
 71%|███████   | 2522/3566 [1:41:51<39:57,  2.30s/it]
                                                     
{'loss': 1.3806, 'learning_rate': 8.3206879702324e-05, 'epoch': 0.71}

 71%|███████   | 2522/3566 [1:41:51<39:57,  2.30s/it]
 71%|███████   | 2523/3566 [1:41:53<39:00,  2.24s/it]
                                                     
{'loss': 1.4505, 'learning_rate': 8.305976802984147e-05, 'epoch': 0.71}

 71%|███████   | 2523/3566 [1:41:53<39:00,  2.24s/it]
 71%|███████   | 2524/3566 [1:41:55<40:03,  2.31s/it]
                                                     
{'loss': 1.5215, 'learning_rate': 8.291275243150878e-05, 'epoch': 0.71}

 71%|███████   | 2524/3566 [1:41:55<40:03,  2.31s/it]
 71%|███████   | 2525/3566 [1:41:58<43:06,  2.48s/it]
                                                     
{'loss': 1.4442, 'learning_rate': 8.2765833028109e-05, 'epoch': 0.71}

 71%|███████   | 2525/3566 [1:41:58<43:06,  2.48s/it]
 71%|███████   | 2526/3566 [1:42:00<42:14,  2.44s/it]
                                                     
{'loss': 1.6594, 'learning_rate': 8.261900994034603e-05, 'epoch': 0.71}

 71%|███████   | 2526/3566 [1:42:00<42:14,  2.44s/it]
 71%|███████   | 2527/3566 [1:42:03<42:55,  2.48s/it]
                                                     
{'loss': 1.5444, 'learning_rate': 8.247228328884485e-05, 'epoch': 0.71}

 71%|███████   | 2527/3566 [1:42:03<42:55,  2.48s/it]
 71%|███████   | 2528/3566 [1:42:05<41:57,  2.42s/it]
                                                     
{'loss': 1.5256, 'learning_rate': 8.23256531941511e-05, 'epoch': 0.71}

 71%|███████   | 2528/3566 [1:42:05<41:57,  2.42s/it]
 71%|███████   | 2529/3566 [1:42:08<41:59,  2.43s/it]
                                                     
{'loss': 1.5025, 'learning_rate': 8.217911977673112e-05, 'epoch': 0.71}

 71%|███████   | 2529/3566 [1:42:08<41:59,  2.43s/it]
 71%|███████   | 2530/3566 [1:42:10<42:07,  2.44s/it]
                                                     
{'loss': 1.5899, 'learning_rate': 8.203268315697183e-05, 'epoch': 0.71}

 71%|███████   | 2530/3566 [1:42:10<42:07,  2.44s/it]
 71%|███████   | 2531/3566 [1:42:12<41:11,  2.39s/it]
                                                     
{'loss': 1.6606, 'learning_rate': 8.188634345518065e-05, 'epoch': 0.71}

 71%|███████   | 2531/3566 [1:42:13<41:11,  2.39s/it]
 71%|███████   | 2532/3566 [1:42:15<42:03,  2.44s/it]
                                                     
{'loss': 1.4018, 'learning_rate': 8.174010079158526e-05, 'epoch': 0.71}

 71%|███████   | 2532/3566 [1:42:15<42:03,  2.44s/it]
 71%|███████   | 2533/3566 [1:42:18<42:47,  2.49s/it]
                                                     
{'loss': 1.5491, 'learning_rate': 8.159395528633387e-05, 'epoch': 0.71}

 71%|███████   | 2533/3566 [1:42:18<42:47,  2.49s/it]
 71%|███████   | 2534/3566 [1:42:20<43:37,  2.54s/it]
                                                     
{'loss': 1.4123, 'learning_rate': 8.14479070594945e-05, 'epoch': 0.71}

 71%|███████   | 2534/3566 [1:42:20<43:37,  2.54s/it]
 71%|███████   | 2535/3566 [1:42:23<43:08,  2.51s/it]
                                                     
{'loss': 1.5169, 'learning_rate': 8.130195623105555e-05, 'epoch': 0.71}

 71%|███████   | 2535/3566 [1:42:23<43:08,  2.51s/it]
 71%|███████   | 2536/3566 [1:42:25<42:31,  2.48s/it]
                                                     
{'loss': 1.4217, 'learning_rate': 8.115610292092526e-05, 'epoch': 0.71}

 71%|███████   | 2536/3566 [1:42:25<42:31,  2.48s/it]
 71%|███████   | 2537/3566 [1:42:28<42:31,  2.48s/it]
                                                     
{'loss': 1.5012, 'learning_rate': 8.101034724893182e-05, 'epoch': 0.71}

 71%|███████   | 2537/3566 [1:42:28<42:31,  2.48s/it]
 71%|███████   | 2538/3566 [1:42:32<49:56,  2.92s/it]
                                                     
{'loss': 1.4005, 'learning_rate': 8.086468933482317e-05, 'epoch': 0.71}

 71%|███████   | 2538/3566 [1:42:32<49:56,  2.92s/it]
 71%|███████   | 2539/3566 [1:42:34<47:41,  2.79s/it]
                                                     
{'loss': 1.4098, 'learning_rate': 8.07191292982669e-05, 'epoch': 0.71}

 71%|███████   | 2539/3566 [1:42:34<47:41,  2.79s/it]
 71%|███████   | 2540/3566 [1:42:36<45:36,  2.67s/it]
                                                     
{'loss': 1.4843, 'learning_rate': 8.057366725885025e-05, 'epoch': 0.71}

 71%|███████   | 2540/3566 [1:42:36<45:36,  2.67s/it]
 71%|███████▏  | 2541/3566 [1:42:39<43:18,  2.54s/it]
                                                     
{'loss': 1.5633, 'learning_rate': 8.042830333607995e-05, 'epoch': 0.71}

 71%|███████▏  | 2541/3566 [1:42:39<43:18,  2.54s/it]
 71%|███████▏  | 2542/3566 [1:42:41<41:41,  2.44s/it]
                                                     
{'loss': 1.5756, 'learning_rate': 8.028303764938206e-05, 'epoch': 0.71}

 71%|███████▏  | 2542/3566 [1:42:41<41:41,  2.44s/it]
 71%|███████▏  | 2543/3566 [1:42:44<42:55,  2.52s/it]
                                                     
{'loss': 1.4689, 'learning_rate': 8.013787031810207e-05, 'epoch': 0.71}

 71%|███████▏  | 2543/3566 [1:42:44<42:55,  2.52s/it]
 71%|███████▏  | 2544/3566 [1:42:46<42:03,  2.47s/it]
                                                     
{'loss': 1.4426, 'learning_rate': 7.999280146150438e-05, 'epoch': 0.71}

 71%|███████▏  | 2544/3566 [1:42:46<42:03,  2.47s/it]
 71%|███████▏  | 2545/3566 [1:42:48<41:31,  2.44s/it]
                                                     
{'loss': 1.497, 'learning_rate': 7.984783119877277e-05, 'epoch': 0.71}

 71%|███████▏  | 2545/3566 [1:42:48<41:31,  2.44s/it]
 71%|███████▏  | 2546/3566 [1:42:51<40:21,  2.37s/it]
                                                     
{'loss': 1.7186, 'learning_rate': 7.970295964900985e-05, 'epoch': 0.71}

 71%|███████▏  | 2546/3566 [1:42:51<40:21,  2.37s/it]
 71%|███████▏  | 2547/3566 [1:42:53<40:47,  2.40s/it]
                                                     
{'loss': 1.5018, 'learning_rate': 7.955818693123731e-05, 'epoch': 0.71}

 71%|███████▏  | 2547/3566 [1:42:53<40:47,  2.40s/it]
 71%|███████▏  | 2548/3566 [1:42:56<41:18,  2.43s/it]
                                                     
{'loss': 1.5186, 'learning_rate': 7.941351316439546e-05, 'epoch': 0.71}

 71%|███████▏  | 2548/3566 [1:42:56<41:18,  2.43s/it]
 71%|███████▏  | 2549/3566 [1:42:58<41:14,  2.43s/it]
                                                     
{'loss': 1.6613, 'learning_rate': 7.926893846734344e-05, 'epoch': 0.71}

 71%|███████▏  | 2549/3566 [1:42:58<41:14,  2.43s/it]
 72%|███████▏  | 2550/3566 [1:43:00<40:19,  2.38s/it]
                                                     
{'loss': 1.3293, 'learning_rate': 7.912446295885891e-05, 'epoch': 0.72}

 72%|███████▏  | 2550/3566 [1:43:00<40:19,  2.38s/it]
 72%|███████▏  | 2551/3566 [1:43:02<39:02,  2.31s/it]
                                                     
{'loss': 1.3611, 'learning_rate': 7.898008675763815e-05, 'epoch': 0.72}

 72%|███████▏  | 2551/3566 [1:43:02<39:02,  2.31s/it]
 72%|███████▏  | 2552/3566 [1:43:05<39:01,  2.31s/it]
                                                     
{'loss': 1.485, 'learning_rate': 7.88358099822956e-05, 'epoch': 0.72}

 72%|███████▏  | 2552/3566 [1:43:05<39:01,  2.31s/it]
 72%|███████▏  | 2553/3566 [1:43:07<38:07,  2.26s/it]
                                                     
{'loss': 1.4546, 'learning_rate': 7.869163275136431e-05, 'epoch': 0.72}

 72%|███████▏  | 2553/3566 [1:43:07<38:07,  2.26s/it]
 72%|███████▏  | 2554/3566 [1:43:10<41:03,  2.43s/it]
                                                     
{'loss': 1.4953, 'learning_rate': 7.854755518329542e-05, 'epoch': 0.72}

 72%|███████▏  | 2554/3566 [1:43:10<41:03,  2.43s/it]
 72%|███████▏  | 2555/3566 [1:43:12<39:44,  2.36s/it]
                                                     
{'loss': 1.311, 'learning_rate': 7.840357739645819e-05, 'epoch': 0.72}

 72%|███████▏  | 2555/3566 [1:43:12<39:44,  2.36s/it]
 72%|███████▏  | 2556/3566 [1:43:14<39:56,  2.37s/it]
                                                     
{'loss': 1.5108, 'learning_rate': 7.82596995091399e-05, 'epoch': 0.72}

 72%|███████▏  | 2556/3566 [1:43:14<39:56,  2.37s/it]
 72%|███████▏  | 2557/3566 [1:43:17<39:44,  2.36s/it]
                                                     
{'loss': 1.4789, 'learning_rate': 7.811592163954578e-05, 'epoch': 0.72}

 72%|███████▏  | 2557/3566 [1:43:17<39:44,  2.36s/it]
 72%|███████▏  | 2558/3566 [1:43:20<42:51,  2.55s/it]
                                                     
{'loss': 1.5899, 'learning_rate': 7.79722439057989e-05, 'epoch': 0.72}

 72%|███████▏  | 2558/3566 [1:43:20<42:51,  2.55s/it]
 72%|███████▏  | 2559/3566 [1:43:22<42:08,  2.51s/it]
                                                     
{'loss': 1.5532, 'learning_rate': 7.782866642594e-05, 'epoch': 0.72}

 72%|███████▏  | 2559/3566 [1:43:22<42:08,  2.51s/it]
 72%|███████▏  | 2560/3566 [1:43:24<41:52,  2.50s/it]
                                                     
{'loss': 1.4495, 'learning_rate': 7.768518931792752e-05, 'epoch': 0.72}

 72%|███████▏  | 2560/3566 [1:43:24<41:52,  2.50s/it]
 72%|███████▏  | 2561/3566 [1:43:28<46:50,  2.80s/it]
                                                     
{'loss': 1.4506, 'learning_rate': 7.75418126996374e-05, 'epoch': 0.72}

 72%|███████▏  | 2561/3566 [1:43:28<46:50,  2.80s/it]
 72%|███████▏  | 2562/3566 [1:43:30<43:25,  2.60s/it]
                                                     
{'loss': 1.4508, 'learning_rate': 7.739853668886305e-05, 'epoch': 0.72}

 72%|███████▏  | 2562/3566 [1:43:30<43:25,  2.60s/it]
 72%|███████▏  | 2563/3566 [1:43:33<43:40,  2.61s/it]
                                                     
{'loss': 1.6751, 'learning_rate': 7.72553614033152e-05, 'epoch': 0.72}

 72%|███████▏  | 2563/3566 [1:43:33<43:40,  2.61s/it]
 72%|███████▏  | 2564/3566 [1:43:35<42:36,  2.55s/it]
                                                     
{'loss': 1.5392, 'learning_rate': 7.711228696062183e-05, 'epoch': 0.72}

 72%|███████▏  | 2564/3566 [1:43:35<42:36,  2.55s/it]
 72%|███████▏  | 2565/3566 [1:43:38<43:13,  2.59s/it]
                                                     
{'loss': 1.6416, 'learning_rate': 7.696931347832808e-05, 'epoch': 0.72}

 72%|███████▏  | 2565/3566 [1:43:38<43:13,  2.59s/it]
 72%|███████▏  | 2566/3566 [1:43:40<41:05,  2.47s/it]
                                                     
{'loss': 1.515, 'learning_rate': 7.682644107389612e-05, 'epoch': 0.72}

 72%|███████▏  | 2566/3566 [1:43:40<41:05,  2.47s/it]
 72%|███████▏  | 2567/3566 [1:43:42<40:42,  2.45s/it]
                                                     
{'loss': 1.5707, 'learning_rate': 7.668366986470513e-05, 'epoch': 0.72}

 72%|███████▏  | 2567/3566 [1:43:42<40:42,  2.45s/it]
 72%|███████▏  | 2568/3566 [1:43:45<41:22,  2.49s/it]
                                                     
{'loss': 1.6533, 'learning_rate': 7.654099996805115e-05, 'epoch': 0.72}

 72%|███████▏  | 2568/3566 [1:43:45<41:22,  2.49s/it]
 72%|███████▏  | 2569/3566 [1:43:47<40:17,  2.42s/it]
                                                     
{'loss': 1.5242, 'learning_rate': 7.639843150114685e-05, 'epoch': 0.72}

 72%|███████▏  | 2569/3566 [1:43:47<40:17,  2.42s/it]
 72%|███████▏  | 2570/3566 [1:43:50<39:51,  2.40s/it]
                                                     
{'loss': 1.6532, 'learning_rate': 7.625596458112174e-05, 'epoch': 0.72}

 72%|███████▏  | 2570/3566 [1:43:50<39:51,  2.40s/it]
 72%|███████▏  | 2571/3566 [1:43:52<40:15,  2.43s/it]
                                                     
{'loss': 1.5206, 'learning_rate': 7.611359932502183e-05, 'epoch': 0.72}

 72%|███████▏  | 2571/3566 [1:43:52<40:15,  2.43s/it]
 72%|███████▏  | 2572/3566 [1:43:55<40:59,  2.47s/it]
                                                     
{'loss': 1.3837, 'learning_rate': 7.59713358498096e-05, 'epoch': 0.72}

 72%|███████▏  | 2572/3566 [1:43:55<40:59,  2.47s/it]
 72%|███████▏  | 2573/3566 [1:43:57<41:03,  2.48s/it]
                                                     
{'loss': 1.5387, 'learning_rate': 7.582917427236394e-05, 'epoch': 0.72}

 72%|███████▏  | 2573/3566 [1:43:57<41:03,  2.48s/it]
 72%|███████▏  | 2574/3566 [1:43:59<40:07,  2.43s/it]
                                                     
{'loss': 1.4843, 'learning_rate': 7.56871147094799e-05, 'epoch': 0.72}

 72%|███████▏  | 2574/3566 [1:43:59<40:07,  2.43s/it]
 72%|███████▏  | 2575/3566 [1:44:02<39:20,  2.38s/it]
                                                     
{'loss': 1.4855, 'learning_rate': 7.554515727786901e-05, 'epoch': 0.72}

 72%|███████▏  | 2575/3566 [1:44:02<39:20,  2.38s/it]
 72%|███████▏  | 2576/3566 [1:44:04<39:44,  2.41s/it]
                                                     
{'loss': 1.5612, 'learning_rate': 7.540330209415871e-05, 'epoch': 0.72}

 72%|███████▏  | 2576/3566 [1:44:04<39:44,  2.41s/it]
 72%|███████▏  | 2577/3566 [1:44:07<40:28,  2.46s/it]
                                                     
{'loss': 1.4995, 'learning_rate': 7.526154927489224e-05, 'epoch': 0.72}

 72%|███████▏  | 2577/3566 [1:44:07<40:28,  2.46s/it]
 72%|███████▏  | 2578/3566 [1:44:09<39:09,  2.38s/it]
                                                     
{'loss': 1.363, 'learning_rate': 7.511989893652907e-05, 'epoch': 0.72}

 72%|███████▏  | 2578/3566 [1:44:09<39:09,  2.38s/it]
 72%|███████▏  | 2579/3566 [1:44:12<40:59,  2.49s/it]
                                                     
{'loss': 1.5173, 'learning_rate': 7.497835119544428e-05, 'epoch': 0.72}

 72%|███████▏  | 2579/3566 [1:44:12<40:59,  2.49s/it]
 72%|███████▏  | 2580/3566 [1:44:14<40:22,  2.46s/it]
                                                     
{'loss': 1.6067, 'learning_rate': 7.483690616792875e-05, 'epoch': 0.72}

 72%|███████▏  | 2580/3566 [1:44:14<40:22,  2.46s/it]
 72%|███████▏  | 2581/3566 [1:44:17<40:48,  2.49s/it]
                                                     
{'loss': 1.6989, 'learning_rate': 7.469556397018895e-05, 'epoch': 0.72}

 72%|███████▏  | 2581/3566 [1:44:17<40:48,  2.49s/it]
 72%|███████▏  | 2582/3566 [1:44:19<40:44,  2.48s/it]
                                                     
{'loss': 1.5934, 'learning_rate': 7.455432471834685e-05, 'epoch': 0.72}

 72%|███████▏  | 2582/3566 [1:44:19<40:44,  2.48s/it]
 72%|███████▏  | 2583/3566 [1:44:21<39:32,  2.41s/it]
                                                     
{'loss': 1.4007, 'learning_rate': 7.441318852843986e-05, 'epoch': 0.72}

 72%|███████▏  | 2583/3566 [1:44:21<39:32,  2.41s/it]
 72%|███████▏  | 2584/3566 [1:44:24<38:53,  2.38s/it]
                                                     
{'loss': 1.5135, 'learning_rate': 7.42721555164207e-05, 'epoch': 0.72}

 72%|███████▏  | 2584/3566 [1:44:24<38:53,  2.38s/it]
 72%|███████▏  | 2585/3566 [1:44:26<38:20,  2.35s/it]
                                                     
{'loss': 1.4185, 'learning_rate': 7.413122579815734e-05, 'epoch': 0.72}

 72%|███████▏  | 2585/3566 [1:44:26<38:20,  2.35s/it]
 73%|███████▎  | 2586/3566 [1:44:28<38:36,  2.36s/it]
                                                     
{'loss': 1.4516, 'learning_rate': 7.399039948943296e-05, 'epoch': 0.73}

 73%|███████▎  | 2586/3566 [1:44:28<38:36,  2.36s/it]
 73%|███████▎  | 2587/3566 [1:44:31<38:05,  2.33s/it]
                                                     
{'loss': 1.5716, 'learning_rate': 7.384967670594556e-05, 'epoch': 0.73}

 73%|███████▎  | 2587/3566 [1:44:31<38:05,  2.33s/it]
 73%|███████▎  | 2588/3566 [1:44:33<37:54,  2.33s/it]
                                                     
{'loss': 1.5257, 'learning_rate': 7.370905756330824e-05, 'epoch': 0.73}

 73%|███████▎  | 2588/3566 [1:44:33<37:54,  2.33s/it]
 73%|███████▎  | 2589/3566 [1:44:35<38:02,  2.34s/it]
                                                     
{'loss': 1.5366, 'learning_rate': 7.356854217704908e-05, 'epoch': 0.73}

 73%|███████▎  | 2589/3566 [1:44:35<38:02,  2.34s/it]
 73%|███████▎  | 2590/3566 [1:44:37<37:02,  2.28s/it]
                                                     
{'loss': 1.5768, 'learning_rate': 7.34281306626107e-05, 'epoch': 0.73}

 73%|███████▎  | 2590/3566 [1:44:37<37:02,  2.28s/it]
 73%|███████▎  | 2591/3566 [1:44:40<38:12,  2.35s/it]
                                                     
{'loss': 1.4908, 'learning_rate': 7.328782313535048e-05, 'epoch': 0.73}

 73%|███████▎  | 2591/3566 [1:44:40<38:12,  2.35s/it]
 73%|███████▎  | 2592/3566 [1:44:42<38:16,  2.36s/it]
                                                     
{'loss': 1.5331, 'learning_rate': 7.314761971054034e-05, 'epoch': 0.73}

 73%|███████▎  | 2592/3566 [1:44:42<38:16,  2.36s/it]
 73%|███████▎  | 2593/3566 [1:44:45<40:14,  2.48s/it]
                                                     
{'loss': 1.4567, 'learning_rate': 7.300752050336667e-05, 'epoch': 0.73}

 73%|███████▎  | 2593/3566 [1:44:45<40:14,  2.48s/it]
 73%|███████▎  | 2594/3566 [1:44:47<38:40,  2.39s/it]
                                                     
{'loss': 1.543, 'learning_rate': 7.286752562893036e-05, 'epoch': 0.73}

 73%|███████▎  | 2594/3566 [1:44:47<38:40,  2.39s/it]
 73%|███████▎  | 2595/3566 [1:44:50<38:21,  2.37s/it]
                                                     
{'loss': 1.4948, 'learning_rate': 7.272763520224632e-05, 'epoch': 0.73}

 73%|███████▎  | 2595/3566 [1:44:50<38:21,  2.37s/it]
 73%|███████▎  | 2596/3566 [1:44:52<38:40,  2.39s/it]
                                                     
{'loss': 1.3793, 'learning_rate': 7.258784933824385e-05, 'epoch': 0.73}

 73%|███████▎  | 2596/3566 [1:44:52<38:40,  2.39s/it]
 73%|███████▎  | 2597/3566 [1:44:55<39:46,  2.46s/it]
                                                     
{'loss': 1.608, 'learning_rate': 7.244816815176634e-05, 'epoch': 0.73}

 73%|███████▎  | 2597/3566 [1:44:55<39:46,  2.46s/it]
 73%|███████▎  | 2598/3566 [1:44:57<39:33,  2.45s/it]
                                                     
{'loss': 1.6223, 'learning_rate': 7.230859175757113e-05, 'epoch': 0.73}

 73%|███████▎  | 2598/3566 [1:44:57<39:33,  2.45s/it]
 73%|███████▎  | 2599/3566 [1:44:59<38:44,  2.40s/it]
                                                     
{'loss': 1.6029, 'learning_rate': 7.216912027032946e-05, 'epoch': 0.73}

 73%|███████▎  | 2599/3566 [1:44:59<38:44,  2.40s/it]
 73%|███████▎  | 2600/3566 [1:45:02<37:33,  2.33s/it]
                                                     
{'loss': 1.3352, 'learning_rate': 7.202975380462642e-05, 'epoch': 0.73}

 73%|███████▎  | 2600/3566 [1:45:02<37:33,  2.33s/it]
 73%|███████▎  | 2601/3566 [1:45:04<38:03,  2.37s/it]
                                                     
{'loss': 1.5475, 'learning_rate': 7.189049247496076e-05, 'epoch': 0.73}

 73%|███████▎  | 2601/3566 [1:45:04<38:03,  2.37s/it]
 73%|███████▎  | 2602/3566 [1:45:07<39:44,  2.47s/it]
                                                     
{'loss': 1.6023, 'learning_rate': 7.175133639574494e-05, 'epoch': 0.73}

 73%|███████▎  | 2602/3566 [1:45:07<39:44,  2.47s/it]
 73%|███████▎  | 2603/3566 [1:45:09<39:51,  2.48s/it]
                                                     
{'loss': 1.5833, 'learning_rate': 7.161228568130487e-05, 'epoch': 0.73}

 73%|███████▎  | 2603/3566 [1:45:09<39:51,  2.48s/it]
 73%|███████▎  | 2604/3566 [1:45:11<38:29,  2.40s/it]
                                                     
{'loss': 1.3923, 'learning_rate': 7.147334044587994e-05, 'epoch': 0.73}

 73%|███████▎  | 2604/3566 [1:45:11<38:29,  2.40s/it]
 73%|███████▎  | 2605/3566 [1:45:14<38:26,  2.40s/it]
                                                     
{'loss': 1.6753, 'learning_rate': 7.133450080362287e-05, 'epoch': 0.73}

 73%|███████▎  | 2605/3566 [1:45:14<38:26,  2.40s/it]
 73%|███████▎  | 2606/3566 [1:45:16<37:21,  2.34s/it]
                                                     
{'loss': 1.3064, 'learning_rate': 7.119576686859959e-05, 'epoch': 0.73}

 73%|███████▎  | 2606/3566 [1:45:16<37:21,  2.34s/it]
 73%|███████▎  | 2607/3566 [1:45:18<36:54,  2.31s/it]
                                                     
{'loss': 1.4073, 'learning_rate': 7.105713875478928e-05, 'epoch': 0.73}

 73%|███████▎  | 2607/3566 [1:45:18<36:54,  2.31s/it]
 73%|███████▎  | 2608/3566 [1:45:21<37:43,  2.36s/it]
                                                     
{'loss': 1.5841, 'learning_rate': 7.091861657608407e-05, 'epoch': 0.73}

 73%|███████▎  | 2608/3566 [1:45:21<37:43,  2.36s/it]
 73%|███████▎  | 2609/3566 [1:45:23<36:21,  2.28s/it]
                                                     
{'loss': 1.3198, 'learning_rate': 7.078020044628915e-05, 'epoch': 0.73}

 73%|███████▎  | 2609/3566 [1:45:23<36:21,  2.28s/it]
 73%|███████▎  | 2610/3566 [1:45:25<36:53,  2.31s/it]
                                                     
{'loss': 1.5818, 'learning_rate': 7.06418904791225e-05, 'epoch': 0.73}

 73%|███████▎  | 2610/3566 [1:45:25<36:53,  2.31s/it]
 73%|███████▎  | 2611/3566 [1:45:28<37:49,  2.38s/it]
                                                     
{'loss': 1.632, 'learning_rate': 7.050368678821504e-05, 'epoch': 0.73}

 73%|███████▎  | 2611/3566 [1:45:28<37:49,  2.38s/it]
 73%|███████▎  | 2612/3566 [1:45:30<36:52,  2.32s/it]
                                                     
{'loss': 1.5025, 'learning_rate': 7.03655894871101e-05, 'epoch': 0.73}

 73%|███████▎  | 2612/3566 [1:45:30<36:52,  2.32s/it]
 73%|███████▎  | 2613/3566 [1:45:32<37:28,  2.36s/it]
                                                     
{'loss': 1.5489, 'learning_rate': 7.022759868926383e-05, 'epoch': 0.73}

 73%|███████▎  | 2613/3566 [1:45:32<37:28,  2.36s/it]
 73%|███████▎  | 2614/3566 [1:45:35<37:10,  2.34s/it]
                                                     
{'loss': 1.5314, 'learning_rate': 7.00897145080448e-05, 'epoch': 0.73}

 73%|███████▎  | 2614/3566 [1:45:35<37:10,  2.34s/it]
 73%|███████▎  | 2615/3566 [1:45:37<37:26,  2.36s/it]
                                                     
{'loss': 1.5517, 'learning_rate': 6.995193705673401e-05, 'epoch': 0.73}

 73%|███████▎  | 2615/3566 [1:45:37<37:26,  2.36s/it]
 73%|███████▎  | 2616/3566 [1:45:39<37:30,  2.37s/it]
                                                     
{'loss': 1.504, 'learning_rate': 6.981426644852474e-05, 'epoch': 0.73}

 73%|███████▎  | 2616/3566 [1:45:39<37:30,  2.37s/it]
 73%|███████▎  | 2617/3566 [1:45:42<37:31,  2.37s/it]
                                                     
{'loss': 1.4491, 'learning_rate': 6.967670279652261e-05, 'epoch': 0.73}

 73%|███████▎  | 2617/3566 [1:45:42<37:31,  2.37s/it]
 73%|███████▎  | 2618/3566 [1:45:44<37:45,  2.39s/it]
                                                     
{'loss': 1.3491, 'learning_rate': 6.953924621374522e-05, 'epoch': 0.73}

 73%|███████▎  | 2618/3566 [1:45:44<37:45,  2.39s/it]
 73%|███████▎  | 2619/3566 [1:45:47<38:19,  2.43s/it]
                                                     
{'loss': 1.5795, 'learning_rate': 6.940189681312232e-05, 'epoch': 0.73}

 73%|███████▎  | 2619/3566 [1:45:47<38:19,  2.43s/it]
 73%|███████▎  | 2620/3566 [1:45:49<38:58,  2.47s/it]
                                                     
{'loss': 1.575, 'learning_rate': 6.926465470749542e-05, 'epoch': 0.73}

 73%|███████▎  | 2620/3566 [1:45:49<38:58,  2.47s/it]
 73%|███████▎  | 2621/3566 [1:45:52<38:23,  2.44s/it]
                                                     
{'loss': 1.4323, 'learning_rate': 6.912752000961807e-05, 'epoch': 0.73}

 73%|███████▎  | 2621/3566 [1:45:52<38:23,  2.44s/it]
 74%|███████▎  | 2622/3566 [1:45:54<38:25,  2.44s/it]
                                                     
{'loss': 1.553, 'learning_rate': 6.899049283215551e-05, 'epoch': 0.74}

 74%|███████▎  | 2622/3566 [1:45:54<38:25,  2.44s/it]
 74%|███████▎  | 2623/3566 [1:45:56<37:29,  2.39s/it]
                                                     
{'loss': 1.5586, 'learning_rate': 6.885357328768463e-05, 'epoch': 0.74}

 74%|███████▎  | 2623/3566 [1:45:56<37:29,  2.39s/it]
 74%|███████▎  | 2624/3566 [1:45:59<37:55,  2.42s/it]
                                                     
{'loss': 1.5644, 'learning_rate': 6.871676148869394e-05, 'epoch': 0.74}

 74%|███████▎  | 2624/3566 [1:45:59<37:55,  2.42s/it]
 74%|███████▎  | 2625/3566 [1:46:01<36:58,  2.36s/it]
                                                     
{'loss': 1.4739, 'learning_rate': 6.858005754758338e-05, 'epoch': 0.74}

 74%|███████▎  | 2625/3566 [1:46:01<36:58,  2.36s/it]
 74%|███████▎  | 2626/3566 [1:46:04<37:16,  2.38s/it]
                                                     
{'loss': 1.4833, 'learning_rate': 6.844346157666432e-05, 'epoch': 0.74}

 74%|███████▎  | 2626/3566 [1:46:04<37:16,  2.38s/it]
 74%|███████▎  | 2627/3566 [1:46:06<36:40,  2.34s/it]
                                                     
{'loss': 1.461, 'learning_rate': 6.830697368815938e-05, 'epoch': 0.74}

 74%|███████▎  | 2627/3566 [1:46:06<36:40,  2.34s/it]
 74%|███████▎  | 2628/3566 [1:46:08<37:54,  2.43s/it]
                                                     
{'loss': 1.4319, 'learning_rate': 6.817059399420238e-05, 'epoch': 0.74}

 74%|███████▎  | 2628/3566 [1:46:08<37:54,  2.43s/it]
 74%|███████▎  | 2629/3566 [1:46:11<37:35,  2.41s/it]
                                                     
{'loss': 1.4639, 'learning_rate': 6.80343226068384e-05, 'epoch': 0.74}

 74%|███████▎  | 2629/3566 [1:46:11<37:35,  2.41s/it]
 74%|███████▍  | 2630/3566 [1:46:13<36:57,  2.37s/it]
                                                     
{'loss': 1.4626, 'learning_rate': 6.789815963802324e-05, 'epoch': 0.74}

 74%|███████▍  | 2630/3566 [1:46:13<36:57,  2.37s/it]
 74%|███████▍  | 2631/3566 [1:46:16<37:02,  2.38s/it]
                                                     
{'loss': 1.4975, 'learning_rate': 6.776210519962383e-05, 'epoch': 0.74}

 74%|███████▍  | 2631/3566 [1:46:16<37:02,  2.38s/it]
 74%|███████▍  | 2632/3566 [1:46:18<37:47,  2.43s/it]
                                                     
{'loss': 1.554, 'learning_rate': 6.762615940341802e-05, 'epoch': 0.74}

 74%|███████▍  | 2632/3566 [1:46:18<37:47,  2.43s/it]
 74%|███████▍  | 2633/3566 [1:46:20<37:01,  2.38s/it]
                                                     
{'loss': 1.3772, 'learning_rate': 6.74903223610942e-05, 'epoch': 0.74}

 74%|███████▍  | 2633/3566 [1:46:20<37:01,  2.38s/it]
 74%|███████▍  | 2634/3566 [1:46:23<37:04,  2.39s/it]
                                                     
{'loss': 1.6687, 'learning_rate': 6.735459418425156e-05, 'epoch': 0.74}

 74%|███████▍  | 2634/3566 [1:46:23<37:04,  2.39s/it]
 74%|███████▍  | 2635/3566 [1:46:25<36:56,  2.38s/it]
                                                     
{'loss': 1.5878, 'learning_rate': 6.721897498439975e-05, 'epoch': 0.74}

 74%|███████▍  | 2635/3566 [1:46:25<36:56,  2.38s/it]
 74%|███████▍  | 2636/3566 [1:46:28<37:05,  2.39s/it]
                                                     
{'loss': 1.5222, 'learning_rate': 6.708346487295896e-05, 'epoch': 0.74}

 74%|███████▍  | 2636/3566 [1:46:28<37:05,  2.39s/it]
 74%|███████▍  | 2637/3566 [1:46:30<36:42,  2.37s/it]
                                                     
{'loss': 1.5502, 'learning_rate': 6.694806396125975e-05, 'epoch': 0.74}

 74%|███████▍  | 2637/3566 [1:46:30<36:42,  2.37s/it]
 74%|███████▍  | 2638/3566 [1:46:32<36:10,  2.34s/it]
                                                     
{'loss': 1.5566, 'learning_rate': 6.681277236054284e-05, 'epoch': 0.74}

 74%|███████▍  | 2638/3566 [1:46:32<36:10,  2.34s/it]
 74%|███████▍  | 2639/3566 [1:46:35<36:26,  2.36s/it]
                                                     
{'loss': 1.4009, 'learning_rate': 6.667759018195929e-05, 'epoch': 0.74}

 74%|███████▍  | 2639/3566 [1:46:35<36:26,  2.36s/it]
 74%|███████▍  | 2640/3566 [1:46:37<35:54,  2.33s/it]
                                                     
{'loss': 1.4149, 'learning_rate': 6.654251753657025e-05, 'epoch': 0.74}

 74%|███████▍  | 2640/3566 [1:46:37<35:54,  2.33s/it]
 74%|███████▍  | 2641/3566 [1:46:39<37:10,  2.41s/it]
                                                     
{'loss': 1.6468, 'learning_rate': 6.640755453534684e-05, 'epoch': 0.74}

 74%|███████▍  | 2641/3566 [1:46:39<37:10,  2.41s/it]
 74%|███████▍  | 2642/3566 [1:46:42<36:18,  2.36s/it]
                                                     
{'loss': 1.4961, 'learning_rate': 6.627270128917009e-05, 'epoch': 0.74}

 74%|███████▍  | 2642/3566 [1:46:42<36:18,  2.36s/it]
 74%|███████▍  | 2643/3566 [1:46:44<36:27,  2.37s/it]
                                                     
{'loss': 1.5241, 'learning_rate': 6.61379579088309e-05, 'epoch': 0.74}

 74%|███████▍  | 2643/3566 [1:46:44<36:27,  2.37s/it]
 74%|███████▍  | 2644/3566 [1:46:47<37:52,  2.47s/it]
                                                     
{'loss': 1.3589, 'learning_rate': 6.600332450502986e-05, 'epoch': 0.74}

 74%|███████▍  | 2644/3566 [1:46:47<37:52,  2.47s/it]
 74%|███████▍  | 2645/3566 [1:46:49<38:30,  2.51s/it]
                                                     
{'loss': 1.6239, 'learning_rate': 6.586880118837727e-05, 'epoch': 0.74}

 74%|███████▍  | 2645/3566 [1:46:49<38:30,  2.51s/it]
 74%|███████▍  | 2646/3566 [1:46:52<37:29,  2.44s/it]
                                                     
{'loss': 1.541, 'learning_rate': 6.57343880693929e-05, 'epoch': 0.74}

 74%|███████▍  | 2646/3566 [1:46:52<37:29,  2.44s/it]
 74%|███████▍  | 2647/3566 [1:46:54<36:03,  2.35s/it]
                                                     
{'loss': 1.6375, 'learning_rate': 6.560008525850605e-05, 'epoch': 0.74}

 74%|███████▍  | 2647/3566 [1:46:54<36:03,  2.35s/it]
 74%|███████▍  | 2648/3566 [1:46:56<35:50,  2.34s/it]
                                                     
{'loss': 1.4853, 'learning_rate': 6.546589286605542e-05, 'epoch': 0.74}

 74%|███████▍  | 2648/3566 [1:46:56<35:50,  2.34s/it]
 74%|███████▍  | 2649/3566 [1:46:59<36:26,  2.38s/it]
                                                     
{'loss': 1.6852, 'learning_rate': 6.533181100228891e-05, 'epoch': 0.74}

 74%|███████▍  | 2649/3566 [1:46:59<36:26,  2.38s/it]
 74%|███████▍  | 2650/3566 [1:47:01<36:59,  2.42s/it]
                                                     
{'loss': 1.5717, 'learning_rate': 6.519783977736366e-05, 'epoch': 0.74}

 74%|███████▍  | 2650/3566 [1:47:01<36:59,  2.42s/it]
 74%|███████▍  | 2651/3566 [1:47:04<40:28,  2.65s/it]
                                                     
{'loss': 1.5837, 'learning_rate': 6.506397930134593e-05, 'epoch': 0.74}

 74%|███████▍  | 2651/3566 [1:47:04<40:28,  2.65s/it]
 74%|███████▍  | 2652/3566 [1:47:07<39:20,  2.58s/it]
                                                     
{'loss': 1.5535, 'learning_rate': 6.493022968421096e-05, 'epoch': 0.74}

 74%|███████▍  | 2652/3566 [1:47:07<39:20,  2.58s/it]
 74%|███████▍  | 2653/3566 [1:47:09<37:50,  2.49s/it]
                                                     
{'loss': 1.4543, 'learning_rate': 6.479659103584293e-05, 'epoch': 0.74}

 74%|███████▍  | 2653/3566 [1:47:09<37:50,  2.49s/it]
 74%|███████▍  | 2654/3566 [1:47:11<36:38,  2.41s/it]
                                                     
{'loss': 1.3809, 'learning_rate': 6.46630634660349e-05, 'epoch': 0.74}

 74%|███████▍  | 2654/3566 [1:47:11<36:38,  2.41s/it]
 74%|███████▍  | 2655/3566 [1:47:13<36:18,  2.39s/it]
                                                     
{'loss': 1.4963, 'learning_rate': 6.452964708448848e-05, 'epoch': 0.74}

 74%|███████▍  | 2655/3566 [1:47:13<36:18,  2.39s/it]
 74%|███████▍  | 2656/3566 [1:47:16<36:55,  2.43s/it]
                                                     
{'loss': 1.6194, 'learning_rate': 6.439634200081414e-05, 'epoch': 0.74}

 74%|███████▍  | 2656/3566 [1:47:16<36:55,  2.43s/it]
 75%|███████▍  | 2657/3566 [1:47:18<36:36,  2.42s/it]
                                                     
{'loss': 1.4795, 'learning_rate': 6.426314832453086e-05, 'epoch': 0.75}

 75%|███████▍  | 2657/3566 [1:47:18<36:36,  2.42s/it]
 75%|███████▍  | 2658/3566 [1:47:21<35:28,  2.34s/it]
                                                     
{'loss': 1.4258, 'learning_rate': 6.413006616506605e-05, 'epoch': 0.75}

 75%|███████▍  | 2658/3566 [1:47:21<35:28,  2.34s/it]
 75%|███████▍  | 2659/3566 [1:47:23<36:41,  2.43s/it]
                                                     
{'loss': 1.5875, 'learning_rate': 6.399709563175546e-05, 'epoch': 0.75}

 75%|███████▍  | 2659/3566 [1:47:23<36:41,  2.43s/it]
 75%|███████▍  | 2660/3566 [1:47:26<36:10,  2.40s/it]
                                                     
{'loss': 1.3821, 'learning_rate': 6.386423683384333e-05, 'epoch': 0.75}

 75%|███████▍  | 2660/3566 [1:47:26<36:10,  2.40s/it]
 75%|███████▍  | 2661/3566 [1:47:28<35:58,  2.38s/it]
                                                     
{'loss': 1.4784, 'learning_rate': 6.37314898804819e-05, 'epoch': 0.75}

 75%|███████▍  | 2661/3566 [1:47:28<35:58,  2.38s/it]
 75%|███████▍  | 2662/3566 [1:47:30<36:04,  2.39s/it]
                                                     
{'loss': 1.6146, 'learning_rate': 6.359885488073164e-05, 'epoch': 0.75}

 75%|███████▍  | 2662/3566 [1:47:30<36:04,  2.39s/it]
 75%|███████▍  | 2663/3566 [1:47:33<35:41,  2.37s/it]
                                                     
{'loss': 1.4967, 'learning_rate': 6.346633194356089e-05, 'epoch': 0.75}

 75%|███████▍  | 2663/3566 [1:47:33<35:41,  2.37s/it]
 75%|███████▍  | 2664/3566 [1:47:35<35:07,  2.34s/it]
                                                     
{'loss': 1.4024, 'learning_rate': 6.333392117784606e-05, 'epoch': 0.75}

 75%|███████▍  | 2664/3566 [1:47:35<35:07,  2.34s/it]
 75%|███████▍  | 2665/3566 [1:47:37<34:22,  2.29s/it]
                                                     
{'loss': 1.5244, 'learning_rate': 6.32016226923714e-05, 'epoch': 0.75}

 75%|███████▍  | 2665/3566 [1:47:37<34:22,  2.29s/it]
 75%|███████▍  | 2666/3566 [1:47:39<34:10,  2.28s/it]
                                                     
{'loss': 1.5112, 'learning_rate': 6.306943659582887e-05, 'epoch': 0.75}

 75%|███████▍  | 2666/3566 [1:47:39<34:10,  2.28s/it]
 75%|███████▍  | 2667/3566 [1:47:41<33:13,  2.22s/it]
                                                     
{'loss': 1.3496, 'learning_rate': 6.29373629968181e-05, 'epoch': 0.75}

 75%|███████▍  | 2667/3566 [1:47:41<33:13,  2.22s/it]
 75%|███████▍  | 2668/3566 [1:47:44<35:48,  2.39s/it]
                                                     
{'loss': 1.49, 'learning_rate': 6.280540200384629e-05, 'epoch': 0.75}

 75%|███████▍  | 2668/3566 [1:47:44<35:48,  2.39s/it]
 75%|███████▍  | 2669/3566 [1:47:47<37:49,  2.53s/it]
                                                     
{'loss': 1.518, 'learning_rate': 6.267355372532818e-05, 'epoch': 0.75}

 75%|███████▍  | 2669/3566 [1:47:47<37:49,  2.53s/it]
 75%|███████▍  | 2670/3566 [1:47:50<37:49,  2.53s/it]
                                                     
{'loss': 1.5731, 'learning_rate': 6.254181826958583e-05, 'epoch': 0.75}

 75%|███████▍  | 2670/3566 [1:47:50<37:49,  2.53s/it]
 75%|███████▍  | 2671/3566 [1:47:52<37:01,  2.48s/it]
                                                     
{'loss': 1.4931, 'learning_rate': 6.241019574484865e-05, 'epoch': 0.75}

 75%|███████▍  | 2671/3566 [1:47:52<37:01,  2.48s/it]
 75%|███████▍  | 2672/3566 [1:47:55<39:16,  2.64s/it]
                                                     
{'loss': 1.3783, 'learning_rate': 6.227868625925337e-05, 'epoch': 0.75}

 75%|███████▍  | 2672/3566 [1:47:55<39:16,  2.64s/it]
 75%|███████▍  | 2673/3566 [1:47:57<37:13,  2.50s/it]
                                                     
{'loss': 1.5754, 'learning_rate': 6.21472899208435e-05, 'epoch': 0.75}

 75%|███████▍  | 2673/3566 [1:47:57<37:13,  2.50s/it]
 75%|███████▍  | 2674/3566 [1:47:59<36:19,  2.44s/it]
                                                     
{'loss': 1.4664, 'learning_rate': 6.20160068375701e-05, 'epoch': 0.75}

 75%|███████▍  | 2674/3566 [1:47:59<36:19,  2.44s/it]
 75%|███████▌  | 2675/3566 [1:48:02<35:00,  2.36s/it]
                                                     
{'loss': 1.6091, 'learning_rate': 6.188483711729079e-05, 'epoch': 0.75}

 75%|███████▌  | 2675/3566 [1:48:02<35:00,  2.36s/it]
 75%|███████▌  | 2676/3566 [1:48:04<36:10,  2.44s/it]
                                                     
{'loss': 1.5564, 'learning_rate': 6.175378086777021e-05, 'epoch': 0.75}

 75%|███████▌  | 2676/3566 [1:48:04<36:10,  2.44s/it]
 75%|███████▌  | 2677/3566 [1:48:07<36:31,  2.47s/it]
                                                     
{'loss': 1.4729, 'learning_rate': 6.162283819667975e-05, 'epoch': 0.75}

 75%|███████▌  | 2677/3566 [1:48:07<36:31,  2.47s/it]
 75%|███████▌  | 2678/3566 [1:48:09<36:38,  2.48s/it]
                                                     
{'loss': 1.524, 'learning_rate': 6.149200921159752e-05, 'epoch': 0.75}

 75%|███████▌  | 2678/3566 [1:48:09<36:38,  2.48s/it]
 75%|███████▌  | 2679/3566 [1:48:12<37:14,  2.52s/it]
                                                     
{'loss': 1.5324, 'learning_rate': 6.136129402000818e-05, 'epoch': 0.75}

 75%|███████▌  | 2679/3566 [1:48:12<37:14,  2.52s/it]
 75%|███████▌  | 2680/3566 [1:48:14<36:39,  2.48s/it]
                                                     
{'loss': 1.5627, 'learning_rate': 6.123069272930299e-05, 'epoch': 0.75}

 75%|███████▌  | 2680/3566 [1:48:14<36:39,  2.48s/it]
 75%|███████▌  | 2681/3566 [1:48:17<37:20,  2.53s/it]
                                                     
{'loss': 1.5361, 'learning_rate': 6.110020544677943e-05, 'epoch': 0.75}

 75%|███████▌  | 2681/3566 [1:48:17<37:20,  2.53s/it]
 75%|███████▌  | 2682/3566 [1:48:19<37:03,  2.52s/it]
                                                     
{'loss': 1.5748, 'learning_rate': 6.0969832279641505e-05, 'epoch': 0.75}

 75%|███████▌  | 2682/3566 [1:48:19<37:03,  2.52s/it]
 75%|███████▌  | 2683/3566 [1:48:22<38:45,  2.63s/it]
                                                     
{'loss': 1.4336, 'learning_rate': 6.0839573334999436e-05, 'epoch': 0.75}

 75%|███████▌  | 2683/3566 [1:48:22<38:45,  2.63s/it]
 75%|███████▌  | 2684/3566 [1:48:25<38:09,  2.60s/it]
                                                     
{'loss': 1.4365, 'learning_rate': 6.070942871986955e-05, 'epoch': 0.75}

 75%|███████▌  | 2684/3566 [1:48:25<38:09,  2.60s/it]
 75%|███████▌  | 2685/3566 [1:48:27<36:44,  2.50s/it]
                                                     
{'loss': 1.6381, 'learning_rate': 6.0579398541174316e-05, 'epoch': 0.75}

 75%|███████▌  | 2685/3566 [1:48:27<36:44,  2.50s/it]
 75%|███████▌  | 2686/3566 [1:48:29<36:00,  2.45s/it]
                                                     
{'loss': 1.4889, 'learning_rate': 6.0449482905742084e-05, 'epoch': 0.75}

 75%|███████▌  | 2686/3566 [1:48:29<36:00,  2.45s/it]
 75%|███████▌  | 2687/3566 [1:48:32<34:51,  2.38s/it]
                                                     
{'loss': 1.5368, 'learning_rate': 6.031968192030719e-05, 'epoch': 0.75}

 75%|███████▌  | 2687/3566 [1:48:32<34:51,  2.38s/it]
 75%|███████▌  | 2688/3566 [1:48:34<34:33,  2.36s/it]
                                                     
{'loss': 1.5797, 'learning_rate': 6.018999569150976e-05, 'epoch': 0.75}

 75%|███████▌  | 2688/3566 [1:48:34<34:33,  2.36s/it]
 75%|███████▌  | 2689/3566 [1:48:36<35:16,  2.41s/it]
                                                     
{'loss': 1.5719, 'learning_rate': 6.0060424325895605e-05, 'epoch': 0.75}

 75%|███████▌  | 2689/3566 [1:48:36<35:16,  2.41s/it]
 75%|███████▌  | 2690/3566 [1:48:39<34:58,  2.40s/it]
                                                     
{'loss': 1.6305, 'learning_rate': 5.9930967929916174e-05, 'epoch': 0.75}

 75%|███████▌  | 2690/3566 [1:48:39<34:58,  2.40s/it]
 75%|███████▌  | 2691/3566 [1:48:41<34:43,  2.38s/it]
                                                     
{'loss': 1.6027, 'learning_rate': 5.980162660992852e-05, 'epoch': 0.75}

 75%|███████▌  | 2691/3566 [1:48:41<34:43,  2.38s/it]
 75%|███████▌  | 2692/3566 [1:48:44<35:16,  2.42s/it]
                                                     
{'loss': 1.6328, 'learning_rate': 5.9672400472195045e-05, 'epoch': 0.75}

 75%|███████▌  | 2692/3566 [1:48:44<35:16,  2.42s/it]
 76%|███████▌  | 2693/3566 [1:48:46<35:40,  2.45s/it]
                                                     
{'loss': 1.4518, 'learning_rate': 5.954328962288365e-05, 'epoch': 0.76}

 76%|███████▌  | 2693/3566 [1:48:46<35:40,  2.45s/it]
 76%|███████▌  | 2694/3566 [1:48:48<34:41,  2.39s/it]
                                                     
{'loss': 1.5656, 'learning_rate': 5.9414294168067405e-05, 'epoch': 0.76}

 76%|███████▌  | 2694/3566 [1:48:48<34:41,  2.39s/it]
 76%|███████▌  | 2695/3566 [1:48:51<35:22,  2.44s/it]
                                                     
{'loss': 1.4268, 'learning_rate': 5.9285414213724646e-05, 'epoch': 0.76}

 76%|███████▌  | 2695/3566 [1:48:51<35:22,  2.44s/it]
 76%|███████▌  | 2696/3566 [1:48:53<35:06,  2.42s/it]
                                                     
{'loss': 1.6436, 'learning_rate': 5.915664986573879e-05, 'epoch': 0.76}

 76%|███████▌  | 2696/3566 [1:48:53<35:06,  2.42s/it]
 76%|███████▌  | 2697/3566 [1:48:56<36:40,  2.53s/it]
                                                     
{'loss': 1.5753, 'learning_rate': 5.9028001229898356e-05, 'epoch': 0.76}

 76%|███████▌  | 2697/3566 [1:48:56<36:40,  2.53s/it]
 76%|███████▌  | 2698/3566 [1:48:59<36:40,  2.53s/it]
                                                     
{'loss': 1.586, 'learning_rate': 5.889946841189658e-05, 'epoch': 0.76}

 76%|███████▌  | 2698/3566 [1:48:59<36:40,  2.53s/it]
 76%|███████▌  | 2699/3566 [1:49:01<35:15,  2.44s/it]
                                                     
{'loss': 1.488, 'learning_rate': 5.877105151733175e-05, 'epoch': 0.76}

 76%|███████▌  | 2699/3566 [1:49:01<35:15,  2.44s/it]
 76%|███████▌  | 2700/3566 [1:49:03<35:07,  2.43s/it]
                                                     
{'loss': 1.4152, 'learning_rate': 5.864275065170688e-05, 'epoch': 0.76}

 76%|███████▌  | 2700/3566 [1:49:03<35:07,  2.43s/it]
 76%|███████▌  | 2701/3566 [1:49:05<33:43,  2.34s/it]
                                                     
{'loss': 1.4079, 'learning_rate': 5.851456592042954e-05, 'epoch': 0.76}

 76%|███████▌  | 2701/3566 [1:49:05<33:43,  2.34s/it]
 76%|███████▌  | 2702/3566 [1:49:08<34:31,  2.40s/it]
                                                     
{'loss': 1.5461, 'learning_rate': 5.838649742881215e-05, 'epoch': 0.76}

 76%|███████▌  | 2702/3566 [1:49:08<34:31,  2.40s/it]
 76%|███████▌  | 2703/3566 [1:49:10<34:16,  2.38s/it]
                                                     
{'loss': 1.5212, 'learning_rate': 5.825854528207135e-05, 'epoch': 0.76}

 76%|███████▌  | 2703/3566 [1:49:10<34:16,  2.38s/it]
 76%|███████▌  | 2704/3566 [1:49:13<34:38,  2.41s/it]
                                                     
{'loss': 1.2518, 'learning_rate': 5.8130709585328336e-05, 'epoch': 0.76}

 76%|███████▌  | 2704/3566 [1:49:13<34:38,  2.41s/it]
 76%|███████▌  | 2705/3566 [1:49:16<37:35,  2.62s/it]
                                                     
{'loss': 1.4946, 'learning_rate': 5.8002990443608664e-05, 'epoch': 0.76}

 76%|███████▌  | 2705/3566 [1:49:16<37:35,  2.62s/it]
 76%|███████▌  | 2706/3566 [1:49:18<35:50,  2.50s/it]
                                                     
{'loss': 1.5324, 'learning_rate': 5.787538796184193e-05, 'epoch': 0.76}

 76%|███████▌  | 2706/3566 [1:49:18<35:50,  2.50s/it]
 76%|███████▌  | 2707/3566 [1:49:21<35:38,  2.49s/it]
                                                     
{'loss': 1.4748, 'learning_rate': 5.774790224486213e-05, 'epoch': 0.76}

 76%|███████▌  | 2707/3566 [1:49:21<35:38,  2.49s/it]
 76%|███████▌  | 2708/3566 [1:49:23<35:17,  2.47s/it]
                                                     
{'loss': 1.5349, 'learning_rate': 5.762053339740718e-05, 'epoch': 0.76}

 76%|███████▌  | 2708/3566 [1:49:23<35:17,  2.47s/it]
 76%|███████▌  | 2709/3566 [1:49:25<33:57,  2.38s/it]
                                                     
{'loss': 1.597, 'learning_rate': 5.749328152411906e-05, 'epoch': 0.76}

 76%|███████▌  | 2709/3566 [1:49:25<33:57,  2.38s/it]
 76%|███████▌  | 2710/3566 [1:49:28<33:43,  2.36s/it]
                                                     
{'loss': 1.3769, 'learning_rate': 5.7366146729543615e-05, 'epoch': 0.76}

 76%|███████▌  | 2710/3566 [1:49:28<33:43,  2.36s/it]
 76%|███████▌  | 2711/3566 [1:49:30<33:02,  2.32s/it]
                                                     
{'loss': 1.5258, 'learning_rate': 5.723912911813047e-05, 'epoch': 0.76}

 76%|███████▌  | 2711/3566 [1:49:30<33:02,  2.32s/it]
 76%|███████▌  | 2712/3566 [1:49:32<32:51,  2.31s/it]
                                                     
{'loss': 1.5964, 'learning_rate': 5.7112228794233055e-05, 'epoch': 0.76}

 76%|███████▌  | 2712/3566 [1:49:32<32:51,  2.31s/it]
 76%|███████▌  | 2713/3566 [1:49:35<34:06,  2.40s/it]
                                                     
{'loss': 1.4543, 'learning_rate': 5.698544586210839e-05, 'epoch': 0.76}

 76%|███████▌  | 2713/3566 [1:49:35<34:06,  2.40s/it]
 76%|███████▌  | 2714/3566 [1:49:37<34:04,  2.40s/it]
                                                     
{'loss': 1.5211, 'learning_rate': 5.6858780425917016e-05, 'epoch': 0.76}

 76%|███████▌  | 2714/3566 [1:49:37<34:04,  2.40s/it]
 76%|███████▌  | 2715/3566 [1:49:39<32:41,  2.31s/it]
                                                     
{'loss': 1.5465, 'learning_rate': 5.673223258972302e-05, 'epoch': 0.76}

 76%|███████▌  | 2715/3566 [1:49:39<32:41,  2.31s/it]
 76%|███████▌  | 2716/3566 [1:49:42<33:04,  2.33s/it]
                                                     
{'loss': 1.6447, 'learning_rate': 5.660580245749383e-05, 'epoch': 0.76}

 76%|███████▌  | 2716/3566 [1:49:42<33:04,  2.33s/it]
 76%|███████▌  | 2717/3566 [1:49:44<33:09,  2.34s/it]
                                                     
{'loss': 1.3552, 'learning_rate': 5.647949013310017e-05, 'epoch': 0.76}

 76%|███████▌  | 2717/3566 [1:49:44<33:09,  2.34s/it]
 76%|███████▌  | 2718/3566 [1:49:46<33:04,  2.34s/it]
                                                     
{'loss': 1.335, 'learning_rate': 5.635329572031598e-05, 'epoch': 0.76}

 76%|███████▌  | 2718/3566 [1:49:46<33:04,  2.34s/it]
 76%|███████▌  | 2719/3566 [1:49:49<34:17,  2.43s/it]
                                                     
{'loss': 1.4357, 'learning_rate': 5.622721932281834e-05, 'epoch': 0.76}

 76%|███████▌  | 2719/3566 [1:49:49<34:17,  2.43s/it]
 76%|███████▋  | 2720/3566 [1:49:51<34:18,  2.43s/it]
                                                     
{'loss': 1.472, 'learning_rate': 5.610126104418738e-05, 'epoch': 0.76}

 76%|███████▋  | 2720/3566 [1:49:51<34:18,  2.43s/it]
 76%|███████▋  | 2721/3566 [1:49:54<33:40,  2.39s/it]
                                                     
{'loss': 1.4811, 'learning_rate': 5.5975420987906135e-05, 'epoch': 0.76}

 76%|███████▋  | 2721/3566 [1:49:54<33:40,  2.39s/it]
 76%|███████▋  | 2722/3566 [1:49:56<34:27,  2.45s/it]
                                                     
{'loss': 1.5568, 'learning_rate': 5.584969925736063e-05, 'epoch': 0.76}

 76%|███████▋  | 2722/3566 [1:49:56<34:27,  2.45s/it]
 76%|███████▋  | 2723/3566 [1:49:59<34:00,  2.42s/it]
                                                     
{'loss': 1.4332, 'learning_rate': 5.5724095955839497e-05, 'epoch': 0.76}

 76%|███████▋  | 2723/3566 [1:49:59<34:00,  2.42s/it]
 76%|███████▋  | 2724/3566 [1:50:01<33:58,  2.42s/it]
                                                     
{'loss': 1.657, 'learning_rate': 5.559861118653422e-05, 'epoch': 0.76}

 76%|███████▋  | 2724/3566 [1:50:01<33:58,  2.42s/it]
 76%|███████▋  | 2725/3566 [1:50:03<33:03,  2.36s/it]
                                                     
{'loss': 1.6332, 'learning_rate': 5.547324505253884e-05, 'epoch': 0.76}

 76%|███████▋  | 2725/3566 [1:50:03<33:03,  2.36s/it]
 76%|███████▋  | 2726/3566 [1:50:06<33:20,  2.38s/it]
                                                     
{'loss': 1.4438, 'learning_rate': 5.5347997656849925e-05, 'epoch': 0.76}

 76%|███████▋  | 2726/3566 [1:50:06<33:20,  2.38s/it]
 76%|███████▋  | 2727/3566 [1:50:08<33:14,  2.38s/it]
                                                     
{'loss': 1.5934, 'learning_rate': 5.522286910236656e-05, 'epoch': 0.76}

 76%|███████▋  | 2727/3566 [1:50:08<33:14,  2.38s/it]
 77%|███████▋  | 2728/3566 [1:50:11<33:51,  2.42s/it]
                                                     
{'loss': 1.5027, 'learning_rate': 5.5097859491890126e-05, 'epoch': 0.77}

 77%|███████▋  | 2728/3566 [1:50:11<33:51,  2.42s/it]
 77%|███████▋  | 2729/3566 [1:50:13<33:24,  2.39s/it]
                                                     
{'loss': 1.5381, 'learning_rate': 5.4972968928124225e-05, 'epoch': 0.77}

 77%|███████▋  | 2729/3566 [1:50:13<33:24,  2.39s/it]
 77%|███████▋  | 2730/3566 [1:50:15<33:14,  2.39s/it]
                                                     
{'loss': 1.5463, 'learning_rate': 5.484819751367492e-05, 'epoch': 0.77}

 77%|███████▋  | 2730/3566 [1:50:15<33:14,  2.39s/it]
 77%|███████▋  | 2731/3566 [1:50:18<34:04,  2.45s/it]
                                                     
{'loss': 1.4411, 'learning_rate': 5.472354535105002e-05, 'epoch': 0.77}

 77%|███████▋  | 2731/3566 [1:50:18<34:04,  2.45s/it]
 77%|███████▋  | 2732/3566 [1:50:21<37:12,  2.68s/it]
                                                     
{'loss': 1.4449, 'learning_rate': 5.45990125426596e-05, 'epoch': 0.77}

 77%|███████▋  | 2732/3566 [1:50:21<37:12,  2.68s/it]
 77%|███████▋  | 2733/3566 [1:50:24<36:46,  2.65s/it]
                                                     
{'loss': 1.7017, 'learning_rate': 5.447459919081559e-05, 'epoch': 0.77}

 77%|███████▋  | 2733/3566 [1:50:24<36:46,  2.65s/it]
 77%|███████▋  | 2734/3566 [1:50:26<35:26,  2.56s/it]
                                                     
{'loss': 1.4643, 'learning_rate': 5.435030539773185e-05, 'epoch': 0.77}

 77%|███████▋  | 2734/3566 [1:50:26<35:26,  2.56s/it]
 77%|███████▋  | 2735/3566 [1:50:28<33:56,  2.45s/it]
                                                     
{'loss': 1.5071, 'learning_rate': 5.422613126552394e-05, 'epoch': 0.77}

 77%|███████▋  | 2735/3566 [1:50:28<33:56,  2.45s/it]
 77%|███████▋  | 2736/3566 [1:50:31<33:44,  2.44s/it]
                                                     
{'loss': 1.4499, 'learning_rate': 5.410207689620912e-05, 'epoch': 0.77}

 77%|███████▋  | 2736/3566 [1:50:31<33:44,  2.44s/it]
 77%|███████▋  | 2737/3566 [1:50:33<33:06,  2.40s/it]
                                                     
{'loss': 1.3849, 'learning_rate': 5.397814239170631e-05, 'epoch': 0.77}

 77%|███████▋  | 2737/3566 [1:50:33<33:06,  2.40s/it]
 77%|███████▋  | 2738/3566 [1:50:35<33:46,  2.45s/it]
                                                     
{'loss': 1.5164, 'learning_rate': 5.3854327853835887e-05, 'epoch': 0.77}

 77%|███████▋  | 2738/3566 [1:50:35<33:46,  2.45s/it]
 77%|███████▋  | 2739/3566 [1:50:38<33:37,  2.44s/it]
                                                     
{'loss': 1.6806, 'learning_rate': 5.373063338431972e-05, 'epoch': 0.77}

 77%|███████▋  | 2739/3566 [1:50:38<33:37,  2.44s/it]
 77%|███████▋  | 2740/3566 [1:50:40<33:33,  2.44s/it]
                                                     
{'loss': 1.5676, 'learning_rate': 5.360705908478108e-05, 'epoch': 0.77}

 77%|███████▋  | 2740/3566 [1:50:40<33:33,  2.44s/it]
 77%|███████▋  | 2741/3566 [1:50:43<34:36,  2.52s/it]
                                                     
{'loss': 1.5182, 'learning_rate': 5.348360505674428e-05, 'epoch': 0.77}

 77%|███████▋  | 2741/3566 [1:50:43<34:36,  2.52s/it]
 77%|███████▋  | 2742/3566 [1:50:45<34:15,  2.49s/it]
                                                     
{'loss': 1.6033, 'learning_rate': 5.3360271401635084e-05, 'epoch': 0.77}

 77%|███████▋  | 2742/3566 [1:50:45<34:15,  2.49s/it]
 77%|███████▋  | 2743/3566 [1:50:48<34:36,  2.52s/it]
                                                     
{'loss': 1.733, 'learning_rate': 5.32370582207802e-05, 'epoch': 0.77}

 77%|███████▋  | 2743/3566 [1:50:48<34:36,  2.52s/it]
 77%|███████▋  | 2744/3566 [1:50:51<34:35,  2.53s/it]
                                                     
{'loss': 1.5312, 'learning_rate': 5.311396561540754e-05, 'epoch': 0.77}

 77%|███████▋  | 2744/3566 [1:50:51<34:35,  2.53s/it]
 77%|███████▋  | 2745/3566 [1:50:53<34:39,  2.53s/it]
                                                     
{'loss': 1.6029, 'learning_rate': 5.299099368664575e-05, 'epoch': 0.77}

 77%|███████▋  | 2745/3566 [1:50:53<34:39,  2.53s/it]
 77%|███████▋  | 2746/3566 [1:50:56<36:14,  2.65s/it]
                                                     
{'loss': 1.4828, 'learning_rate': 5.2868142535524456e-05, 'epoch': 0.77}

 77%|███████▋  | 2746/3566 [1:50:56<36:14,  2.65s/it]
 77%|███████▋  | 2747/3566 [1:50:59<36:14,  2.66s/it]
                                                     
{'loss': 1.5396, 'learning_rate': 5.274541226297398e-05, 'epoch': 0.77}

 77%|███████▋  | 2747/3566 [1:50:59<36:14,  2.66s/it]
 77%|███████▋  | 2748/3566 [1:51:01<34:53,  2.56s/it]
                                                     
{'loss': 1.4052, 'learning_rate': 5.262280296982547e-05, 'epoch': 0.77}

 77%|███████▋  | 2748/3566 [1:51:01<34:53,  2.56s/it]
 77%|███████▋  | 2749/3566 [1:51:03<33:38,  2.47s/it]
                                                     
{'loss': 1.411, 'learning_rate': 5.2500314756810455e-05, 'epoch': 0.77}

 77%|███████▋  | 2749/3566 [1:51:03<33:38,  2.47s/it]
 77%|███████▋  | 2750/3566 [1:51:06<32:44,  2.41s/it]
                                                     
{'loss': 1.5356, 'learning_rate': 5.237794772456117e-05, 'epoch': 0.77}

 77%|███████▋  | 2750/3566 [1:51:06<32:44,  2.41s/it]
 77%|███████▋  | 2751/3566 [1:51:08<32:54,  2.42s/it]
                                                     
{'loss': 1.5258, 'learning_rate': 5.225570197361025e-05, 'epoch': 0.77}

 77%|███████▋  | 2751/3566 [1:51:08<32:54,  2.42s/it]
 77%|███████▋  | 2752/3566 [1:51:10<32:50,  2.42s/it]
                                                     
{'loss': 1.6235, 'learning_rate': 5.213357760439066e-05, 'epoch': 0.77}

 77%|███████▋  | 2752/3566 [1:51:10<32:50,  2.42s/it]
 77%|███████▋  | 2753/3566 [1:51:13<32:32,  2.40s/it]
                                                     
{'loss': 1.5066, 'learning_rate': 5.20115747172357e-05, 'epoch': 0.77}

 77%|███████▋  | 2753/3566 [1:51:13<32:32,  2.40s/it]
 77%|███████▋  | 2754/3566 [1:51:15<32:33,  2.41s/it]
                                                     
{'loss': 1.5161, 'learning_rate': 5.188969341237879e-05, 'epoch': 0.77}

 77%|███████▋  | 2754/3566 [1:51:15<32:33,  2.41s/it]
 77%|███████▋  | 2755/3566 [1:51:17<31:49,  2.35s/it]
                                                     
{'loss': 1.3714, 'learning_rate': 5.1767933789953504e-05, 'epoch': 0.77}

 77%|███████▋  | 2755/3566 [1:51:17<31:49,  2.35s/it]
 77%|███████▋  | 2756/3566 [1:51:20<32:21,  2.40s/it]
                                                     
{'loss': 1.4717, 'learning_rate': 5.164629594999346e-05, 'epoch': 0.77}

 77%|███████▋  | 2756/3566 [1:51:20<32:21,  2.40s/it]
 77%|███████▋  | 2757/3566 [1:51:22<32:55,  2.44s/it]
                                                     
{'loss': 1.4804, 'learning_rate': 5.152477999243222e-05, 'epoch': 0.77}

 77%|███████▋  | 2757/3566 [1:51:22<32:55,  2.44s/it]
 77%|███████▋  | 2758/3566 [1:51:25<32:52,  2.44s/it]
                                                     
{'loss': 1.6051, 'learning_rate': 5.1403386017103125e-05, 'epoch': 0.77}

 77%|███████▋  | 2758/3566 [1:51:25<32:52,  2.44s/it]
 77%|███████▋  | 2759/3566 [1:51:27<32:02,  2.38s/it]
                                                     
{'loss': 1.4314, 'learning_rate': 5.1282114123739445e-05, 'epoch': 0.77}

 77%|███████▋  | 2759/3566 [1:51:27<32:02,  2.38s/it]
 77%|███████▋  | 2760/3566 [1:51:30<32:29,  2.42s/it]
                                                     
{'loss': 1.4866, 'learning_rate': 5.116096441197402e-05, 'epoch': 0.77}

 77%|███████▋  | 2760/3566 [1:51:30<32:29,  2.42s/it]
 77%|███████▋  | 2761/3566 [1:51:32<33:51,  2.52s/it]
                                                     
{'loss': 1.4774, 'learning_rate': 5.10399369813394e-05, 'epoch': 0.77}

 77%|███████▋  | 2761/3566 [1:51:32<33:51,  2.52s/it]
 77%|███████▋  | 2762/3566 [1:51:35<33:06,  2.47s/it]
                                                     
{'loss': 1.5134, 'learning_rate': 5.091903193126763e-05, 'epoch': 0.77}

 77%|███████▋  | 2762/3566 [1:51:35<33:06,  2.47s/it]
 77%|███████▋  | 2763/3566 [1:51:37<32:37,  2.44s/it]
                                                     
{'loss': 1.4556, 'learning_rate': 5.079824936109023e-05, 'epoch': 0.77}

 77%|███████▋  | 2763/3566 [1:51:37<32:37,  2.44s/it]
 78%|███████▊  | 2764/3566 [1:51:40<32:27,  2.43s/it]
                                                     
{'loss': 1.6267, 'learning_rate': 5.067758937003808e-05, 'epoch': 0.78}

 78%|███████▊  | 2764/3566 [1:51:40<32:27,  2.43s/it]
 78%|███████▊  | 2765/3566 [1:51:42<32:36,  2.44s/it]
                                                     
{'loss': 1.4596, 'learning_rate': 5.0557052057241415e-05, 'epoch': 0.78}

 78%|███████▊  | 2765/3566 [1:51:42<32:36,  2.44s/it]
 78%|███████▊  | 2766/3566 [1:51:45<32:45,  2.46s/it]
                                                     
{'loss': 1.4653, 'learning_rate': 5.043663752172949e-05, 'epoch': 0.78}

 78%|███████▊  | 2766/3566 [1:51:45<32:45,  2.46s/it]
 78%|███████▊  | 2767/3566 [1:51:48<35:43,  2.68s/it]
                                                     
{'loss': 1.5473, 'learning_rate': 5.031634586243092e-05, 'epoch': 0.78}

 78%|███████▊  | 2767/3566 [1:51:48<35:43,  2.68s/it]
 78%|███████▊  | 2768/3566 [1:51:50<34:56,  2.63s/it]
                                                     
{'loss': 1.5767, 'learning_rate': 5.019617717817324e-05, 'epoch': 0.78}

 78%|███████▊  | 2768/3566 [1:51:50<34:56,  2.63s/it]
 78%|███████▊  | 2769/3566 [1:51:53<33:57,  2.56s/it]
                                                     
{'loss': 1.5406, 'learning_rate': 5.0076131567683024e-05, 'epoch': 0.78}

 78%|███████▊  | 2769/3566 [1:51:53<33:57,  2.56s/it]
 78%|███████▊  | 2770/3566 [1:51:55<33:28,  2.52s/it]
                                                     
{'loss': 1.5407, 'learning_rate': 4.995620912958565e-05, 'epoch': 0.78}

 78%|███████▊  | 2770/3566 [1:51:55<33:28,  2.52s/it]
 78%|███████▊  | 2771/3566 [1:51:57<32:44,  2.47s/it]
                                                     
{'loss': 1.4921, 'learning_rate': 4.983640996240533e-05, 'epoch': 0.78}

 78%|███████▊  | 2771/3566 [1:51:57<32:44,  2.47s/it]
 78%|███████▊  | 2772/3566 [1:52:00<32:00,  2.42s/it]
                                                     
{'loss': 1.4848, 'learning_rate': 4.971673416456513e-05, 'epoch': 0.78}

 78%|███████▊  | 2772/3566 [1:52:00<32:00,  2.42s/it]
 78%|███████▊  | 2773/3566 [1:52:02<32:02,  2.42s/it]
                                                     
{'loss': 1.5582, 'learning_rate': 4.959718183438662e-05, 'epoch': 0.78}

 78%|███████▊  | 2773/3566 [1:52:02<32:02,  2.42s/it]
 78%|███████▊  | 2774/3566 [1:52:04<30:28,  2.31s/it]
                                                     
{'loss': 1.3446, 'learning_rate': 4.947775307008986e-05, 'epoch': 0.78}

 78%|███████▊  | 2774/3566 [1:52:04<30:28,  2.31s/it]
 78%|███████▊  | 2775/3566 [1:52:07<30:53,  2.34s/it]
                                                     
{'loss': 1.6742, 'learning_rate': 4.935844796979356e-05, 'epoch': 0.78}

 78%|███████▊  | 2775/3566 [1:52:07<30:53,  2.34s/it]
 78%|███████▊  | 2776/3566 [1:52:09<31:16,  2.38s/it]
                                                     
{'loss': 1.5862, 'learning_rate': 4.923926663151477e-05, 'epoch': 0.78}

 78%|███████▊  | 2776/3566 [1:52:09<31:16,  2.38s/it]
 78%|███████▊  | 2777/3566 [1:52:11<31:10,  2.37s/it]
                                                     
{'loss': 1.5215, 'learning_rate': 4.912020915316884e-05, 'epoch': 0.78}

 78%|███████▊  | 2777/3566 [1:52:11<31:10,  2.37s/it]
 78%|███████▊  | 2778/3566 [1:52:14<32:12,  2.45s/it]
                                                     
{'loss': 1.571, 'learning_rate': 4.9001275632569375e-05, 'epoch': 0.78}

 78%|███████▊  | 2778/3566 [1:52:14<32:12,  2.45s/it]
 78%|███████▊  | 2779/3566 [1:52:16<31:45,  2.42s/it]
                                                     
{'loss': 1.5794, 'learning_rate': 4.8882466167428177e-05, 'epoch': 0.78}

 78%|███████▊  | 2779/3566 [1:52:16<31:45,  2.42s/it]
 78%|███████▊  | 2780/3566 [1:52:19<31:34,  2.41s/it]
                                                     
{'loss': 1.5793, 'learning_rate': 4.876378085535505e-05, 'epoch': 0.78}

 78%|███████▊  | 2780/3566 [1:52:19<31:34,  2.41s/it]
 78%|███████▊  | 2781/3566 [1:52:21<31:02,  2.37s/it]
                                                     
{'loss': 1.6267, 'learning_rate': 4.864521979385788e-05, 'epoch': 0.78}

 78%|███████▊  | 2781/3566 [1:52:21<31:02,  2.37s/it]
 78%|███████▊  | 2782/3566 [1:52:24<32:43,  2.50s/it]
                                                     
{'loss': 1.5685, 'learning_rate': 4.852678308034242e-05, 'epoch': 0.78}

 78%|███████▊  | 2782/3566 [1:52:24<32:43,  2.50s/it]
 78%|███████▊  | 2783/3566 [1:52:26<32:46,  2.51s/it]
                                                     
{'loss': 1.6074, 'learning_rate': 4.840847081211233e-05, 'epoch': 0.78}

 78%|███████▊  | 2783/3566 [1:52:26<32:46,  2.51s/it]
 78%|███████▊  | 2784/3566 [1:52:29<31:29,  2.42s/it]
                                                     
{'loss': 1.2377, 'learning_rate': 4.829028308636887e-05, 'epoch': 0.78}

 78%|███████▊  | 2784/3566 [1:52:29<31:29,  2.42s/it]
 78%|███████▊  | 2785/3566 [1:52:31<30:55,  2.38s/it]
                                                     
{'loss': 1.4252, 'learning_rate': 4.8172220000211156e-05, 'epoch': 0.78}

 78%|███████▊  | 2785/3566 [1:52:31<30:55,  2.38s/it]
 78%|███████▊  | 2786/3566 [1:52:33<31:29,  2.42s/it]
                                                     
{'loss': 1.3445, 'learning_rate': 4.805428165063577e-05, 'epoch': 0.78}

 78%|███████▊  | 2786/3566 [1:52:33<31:29,  2.42s/it]
 78%|███████▊  | 2787/3566 [1:52:36<31:13,  2.41s/it]
                                                     
{'loss': 1.5329, 'learning_rate': 4.7936468134536984e-05, 'epoch': 0.78}

 78%|███████▊  | 2787/3566 [1:52:36<31:13,  2.41s/it]
 78%|███████▊  | 2788/3566 [1:52:38<31:00,  2.39s/it]
                                                     
{'loss': 1.4256, 'learning_rate': 4.781877954870637e-05, 'epoch': 0.78}

 78%|███████▊  | 2788/3566 [1:52:38<31:00,  2.39s/it]
 78%|███████▊  | 2789/3566 [1:52:41<31:12,  2.41s/it]
                                                     
{'loss': 1.7576, 'learning_rate': 4.77012159898329e-05, 'epoch': 0.78}

 78%|███████▊  | 2789/3566 [1:52:41<31:12,  2.41s/it]
 78%|███████▊  | 2790/3566 [1:52:43<30:28,  2.36s/it]
                                                     
{'loss': 1.4922, 'learning_rate': 4.758377755450281e-05, 'epoch': 0.78}

 78%|███████▊  | 2790/3566 [1:52:43<30:28,  2.36s/it]
 78%|███████▊  | 2791/3566 [1:52:45<30:42,  2.38s/it]
                                                     
{'loss': 1.5241, 'learning_rate': 4.7466464339199634e-05, 'epoch': 0.78}

 78%|███████▊  | 2791/3566 [1:52:45<30:42,  2.38s/it]
 78%|███████▊  | 2792/3566 [1:52:47<30:03,  2.33s/it]
                                                     
{'loss': 1.508, 'learning_rate': 4.7349276440303825e-05, 'epoch': 0.78}

 78%|███████▊  | 2792/3566 [1:52:47<30:03,  2.33s/it]
 78%|███████▊  | 2793/3566 [1:52:50<29:54,  2.32s/it]
                                                     
{'loss': 1.4288, 'learning_rate': 4.7232213954093074e-05, 'epoch': 0.78}

 78%|███████▊  | 2793/3566 [1:52:50<29:54,  2.32s/it]
 78%|███████▊  | 2794/3566 [1:52:52<30:02,  2.33s/it]
                                                     
{'loss': 1.5138, 'learning_rate': 4.711527697674196e-05, 'epoch': 0.78}

 78%|███████▊  | 2794/3566 [1:52:52<30:02,  2.33s/it]
 78%|███████▊  | 2795/3566 [1:52:55<31:29,  2.45s/it]
                                                     
{'loss': 1.392, 'learning_rate': 4.699846560432197e-05, 'epoch': 0.78}

 78%|███████▊  | 2795/3566 [1:52:55<31:29,  2.45s/it]
 78%|███████▊  | 2796/3566 [1:52:57<31:35,  2.46s/it]
                                                     
{'loss': 1.4227, 'learning_rate': 4.688177993280138e-05, 'epoch': 0.78}

 78%|███████▊  | 2796/3566 [1:52:57<31:35,  2.46s/it]
 78%|███████▊  | 2797/3566 [1:53:00<30:40,  2.39s/it]
                                                     
{'loss': 1.4752, 'learning_rate': 4.67652200580452e-05, 'epoch': 0.78}

 78%|███████▊  | 2797/3566 [1:53:00<30:40,  2.39s/it]
 78%|███████▊  | 2798/3566 [1:53:02<30:49,  2.41s/it]
                                                     
{'loss': 1.4767, 'learning_rate': 4.664878607581511e-05, 'epoch': 0.78}

 78%|███████▊  | 2798/3566 [1:53:02<30:49,  2.41s/it]
 78%|███████▊  | 2799/3566 [1:53:04<30:37,  2.40s/it]
                                                     
{'loss': 1.6231, 'learning_rate': 4.6532478081769324e-05, 'epoch': 0.78}

 78%|███████▊  | 2799/3566 [1:53:04<30:37,  2.40s/it]
 79%|███████▊  | 2800/3566 [1:53:07<30:47,  2.41s/it]
                                                     
{'loss': 1.4021, 'learning_rate': 4.641629617146255e-05, 'epoch': 0.79}

 79%|███████▊  | 2800/3566 [1:53:07<30:47,  2.41s/it]
 79%|███████▊  | 2801/3566 [1:53:10<31:57,  2.51s/it]
                                                     
{'loss': 1.3017, 'learning_rate': 4.630024044034595e-05, 'epoch': 0.79}

 79%|███████▊  | 2801/3566 [1:53:10<31:57,  2.51s/it]
 79%|███████▊  | 2802/3566 [1:53:12<30:50,  2.42s/it]
                                                     
{'loss': 1.3501, 'learning_rate': 4.618431098376701e-05, 'epoch': 0.79}

 79%|███████▊  | 2802/3566 [1:53:12<30:50,  2.42s/it]
 79%|███████▊  | 2803/3566 [1:53:14<29:54,  2.35s/it]
                                                     
{'loss': 1.4858, 'learning_rate': 4.6068507896969436e-05, 'epoch': 0.79}

 79%|███████▊  | 2803/3566 [1:53:14<29:54,  2.35s/it]
 79%|███████▊  | 2804/3566 [1:53:17<30:39,  2.41s/it]
                                                     
{'loss': 1.5612, 'learning_rate': 4.595283127509316e-05, 'epoch': 0.79}

 79%|███████▊  | 2804/3566 [1:53:17<30:39,  2.41s/it]
 79%|███████▊  | 2805/3566 [1:53:19<30:57,  2.44s/it]
                                                     
{'loss': 1.71, 'learning_rate': 4.583728121317417e-05, 'epoch': 0.79}

 79%|███████▊  | 2805/3566 [1:53:19<30:57,  2.44s/it]
 79%|███████▊  | 2806/3566 [1:53:22<31:53,  2.52s/it]
                                                     
{'loss': 1.4055, 'learning_rate': 4.572185780614449e-05, 'epoch': 0.79}

 79%|███████▊  | 2806/3566 [1:53:22<31:53,  2.52s/it]
 79%|███████▊  | 2807/3566 [1:53:24<31:19,  2.48s/it]
                                                     
{'loss': 1.5303, 'learning_rate': 4.560656114883213e-05, 'epoch': 0.79}

 79%|███████▊  | 2807/3566 [1:53:24<31:19,  2.48s/it]
 79%|███████▊  | 2808/3566 [1:53:26<30:38,  2.43s/it]
                                                     
{'loss': 1.5672, 'learning_rate': 4.5491391335960966e-05, 'epoch': 0.79}

 79%|███████▊  | 2808/3566 [1:53:26<30:38,  2.43s/it]
 79%|███████▉  | 2809/3566 [1:53:29<30:17,  2.40s/it]
                                                     
{'loss': 1.5164, 'learning_rate': 4.537634846215053e-05, 'epoch': 0.79}

 79%|███████▉  | 2809/3566 [1:53:29<30:17,  2.40s/it]
 79%|███████▉  | 2810/3566 [1:53:31<30:15,  2.40s/it]
                                                     
{'loss': 1.5765, 'learning_rate': 4.526143262191624e-05, 'epoch': 0.79}

 79%|███████▉  | 2810/3566 [1:53:31<30:15,  2.40s/it]
 79%|███████▉  | 2811/3566 [1:53:34<31:04,  2.47s/it]
                                                     
{'loss': 1.5381, 'learning_rate': 4.514664390966903e-05, 'epoch': 0.79}

 79%|███████▉  | 2811/3566 [1:53:34<31:04,  2.47s/it]
 79%|███████▉  | 2812/3566 [1:53:36<31:36,  2.52s/it]
                                                     
{'loss': 1.5177, 'learning_rate': 4.503198241971547e-05, 'epoch': 0.79}

 79%|███████▉  | 2812/3566 [1:53:36<31:36,  2.52s/it]
 79%|███████▉  | 2813/3566 [1:53:39<31:42,  2.53s/it]
                                                     
{'loss': 1.5218, 'learning_rate': 4.4917448246257566e-05, 'epoch': 0.79}

 79%|███████▉  | 2813/3566 [1:53:39<31:42,  2.53s/it]
 79%|███████▉  | 2814/3566 [1:53:41<30:53,  2.47s/it]
                                                     
{'loss': 1.5207, 'learning_rate': 4.4803041483392674e-05, 'epoch': 0.79}

 79%|███████▉  | 2814/3566 [1:53:41<30:53,  2.47s/it]
 79%|███████▉  | 2815/3566 [1:53:44<31:09,  2.49s/it]
                                                     
{'loss': 1.5246, 'learning_rate': 4.468876222511362e-05, 'epoch': 0.79}

 79%|███████▉  | 2815/3566 [1:53:44<31:09,  2.49s/it]
 79%|███████▉  | 2816/3566 [1:53:47<31:59,  2.56s/it]
                                                     
{'loss': 1.6633, 'learning_rate': 4.4574610565308406e-05, 'epoch': 0.79}

 79%|███████▉  | 2816/3566 [1:53:47<31:59,  2.56s/it]
 79%|███████▉  | 2817/3566 [1:53:49<32:01,  2.56s/it]
                                                     
{'loss': 1.5655, 'learning_rate': 4.446058659776009e-05, 'epoch': 0.79}

 79%|███████▉  | 2817/3566 [1:53:49<32:01,  2.56s/it]
 79%|███████▉  | 2818/3566 [1:53:51<30:50,  2.47s/it]
                                                     
{'loss': 1.4372, 'learning_rate': 4.434669041614694e-05, 'epoch': 0.79}

 79%|███████▉  | 2818/3566 [1:53:51<30:50,  2.47s/it]
 79%|███████▉  | 2819/3566 [1:53:54<31:09,  2.50s/it]
                                                     
{'loss': 1.5311, 'learning_rate': 4.423292211404224e-05, 'epoch': 0.79}

 79%|███████▉  | 2819/3566 [1:53:54<31:09,  2.50s/it]
 79%|███████▉  | 2820/3566 [1:53:56<29:34,  2.38s/it]
                                                     
{'loss': 1.5286, 'learning_rate': 4.4119281784914205e-05, 'epoch': 0.79}

 79%|███████▉  | 2820/3566 [1:53:56<29:34,  2.38s/it]
 79%|███████▉  | 2821/3566 [1:53:59<30:13,  2.43s/it]
                                                     
{'loss': 1.4962, 'learning_rate': 4.400576952212585e-05, 'epoch': 0.79}

 79%|███████▉  | 2821/3566 [1:53:59<30:13,  2.43s/it]
 79%|███████▉  | 2822/3566 [1:54:01<29:31,  2.38s/it]
                                                     
{'loss': 1.537, 'learning_rate': 4.3892385418935054e-05, 'epoch': 0.79}

 79%|███████▉  | 2822/3566 [1:54:01<29:31,  2.38s/it]
 79%|███████▉  | 2823/3566 [1:54:03<30:03,  2.43s/it]
                                                     
{'loss': 1.3638, 'learning_rate': 4.377912956849435e-05, 'epoch': 0.79}

 79%|███████▉  | 2823/3566 [1:54:03<30:03,  2.43s/it]
 79%|███████▉  | 2824/3566 [1:54:06<29:32,  2.39s/it]
                                                     
{'loss': 1.6476, 'learning_rate': 4.366600206385094e-05, 'epoch': 0.79}

 79%|███████▉  | 2824/3566 [1:54:06<29:32,  2.39s/it]
 79%|███████▉  | 2825/3566 [1:54:08<29:27,  2.39s/it]
                                                     
{'loss': 1.6887, 'learning_rate': 4.355300299794658e-05, 'epoch': 0.79}

 79%|███████▉  | 2825/3566 [1:54:08<29:27,  2.39s/it]
 79%|███████▉  | 2826/3566 [1:54:11<29:46,  2.41s/it]
                                                     
{'loss': 1.4977, 'learning_rate': 4.344013246361751e-05, 'epoch': 0.79}

 79%|███████▉  | 2826/3566 [1:54:11<29:46,  2.41s/it]
 79%|███████▉  | 2827/3566 [1:54:13<29:36,  2.40s/it]
                                                     
{'loss': 1.5364, 'learning_rate': 4.3327390553594246e-05, 'epoch': 0.79}

 79%|███████▉  | 2827/3566 [1:54:13<29:36,  2.40s/it]
 79%|███████▉  | 2828/3566 [1:54:15<29:20,  2.39s/it]
                                                     
{'loss': 1.513, 'learning_rate': 4.321477736050179e-05, 'epoch': 0.79}

 79%|███████▉  | 2828/3566 [1:54:15<29:20,  2.39s/it]
 79%|███████▉  | 2829/3566 [1:54:18<30:03,  2.45s/it]
                                                     
{'loss': 1.4781, 'learning_rate': 4.3102292976859395e-05, 'epoch': 0.79}

 79%|███████▉  | 2829/3566 [1:54:18<30:03,  2.45s/it]
 79%|███████▉  | 2830/3566 [1:54:20<29:28,  2.40s/it]
                                                     
{'loss': 1.6047, 'learning_rate': 4.2989937495080405e-05, 'epoch': 0.79}

 79%|███████▉  | 2830/3566 [1:54:20<29:28,  2.40s/it]
 79%|███████▉  | 2831/3566 [1:54:22<28:42,  2.34s/it]
                                                     
{'loss': 1.5189, 'learning_rate': 4.287771100747229e-05, 'epoch': 0.79}

 79%|███████▉  | 2831/3566 [1:54:22<28:42,  2.34s/it]
 79%|███████▉  | 2832/3566 [1:54:25<28:21,  2.32s/it]
                                                     
{'loss': 1.5343, 'learning_rate': 4.276561360623654e-05, 'epoch': 0.79}

 79%|███████▉  | 2832/3566 [1:54:25<28:21,  2.32s/it]
 79%|███████▉  | 2833/3566 [1:54:27<28:51,  2.36s/it]
                                                     
{'loss': 1.6105, 'learning_rate': 4.265364538346861e-05, 'epoch': 0.79}

 79%|███████▉  | 2833/3566 [1:54:27<28:51,  2.36s/it]
 79%|███████▉  | 2834/3566 [1:54:30<29:05,  2.38s/it]
                                                     
{'loss': 1.5185, 'learning_rate': 4.254180643115788e-05, 'epoch': 0.79}

 79%|███████▉  | 2834/3566 [1:54:30<29:05,  2.38s/it]
 80%|███████▉  | 2835/3566 [1:54:32<29:32,  2.42s/it]
                                                     
{'loss': 1.7152, 'learning_rate': 4.243009684118733e-05, 'epoch': 0.8}

 80%|███████▉  | 2835/3566 [1:54:32<29:32,  2.42s/it]
 80%|███████▉  | 2836/3566 [1:54:35<29:38,  2.44s/it]
                                                     
{'loss': 1.5322, 'learning_rate': 4.2318516705333844e-05, 'epoch': 0.8}

 80%|███████▉  | 2836/3566 [1:54:35<29:38,  2.44s/it]
 80%|███████▉  | 2837/3566 [1:54:37<29:58,  2.47s/it]
                                                     
{'loss': 1.6431, 'learning_rate': 4.22070661152679e-05, 'epoch': 0.8}

 80%|███████▉  | 2837/3566 [1:54:37<29:58,  2.47s/it]
 80%|███████▉  | 2838/3566 [1:54:40<30:11,  2.49s/it]
                                                     
{'loss': 1.5051, 'learning_rate': 4.2095745162553545e-05, 'epoch': 0.8}

 80%|███████▉  | 2838/3566 [1:54:40<30:11,  2.49s/it]
 80%|███████▉  | 2839/3566 [1:54:42<29:26,  2.43s/it]
                                                     
{'loss': 1.4275, 'learning_rate': 4.198455393864835e-05, 'epoch': 0.8}

 80%|███████▉  | 2839/3566 [1:54:42<29:26,  2.43s/it]
 80%|███████▉  | 2840/3566 [1:54:44<29:02,  2.40s/it]
                                                     
{'loss': 1.3369, 'learning_rate': 4.187349253490323e-05, 'epoch': 0.8}

 80%|███████▉  | 2840/3566 [1:54:44<29:02,  2.40s/it]
 80%|███████▉  | 2841/3566 [1:54:47<30:55,  2.56s/it]
                                                     
{'loss': 1.3158, 'learning_rate': 4.176256104256249e-05, 'epoch': 0.8}

 80%|███████▉  | 2841/3566 [1:54:47<30:55,  2.56s/it]
 80%|███████▉  | 2842/3566 [1:54:49<29:38,  2.46s/it]
                                                     
{'loss': 1.4289, 'learning_rate': 4.165175955276373e-05, 'epoch': 0.8}

 80%|███████▉  | 2842/3566 [1:54:49<29:38,  2.46s/it]
 80%|███████▉  | 2843/3566 [1:54:52<29:07,  2.42s/it]
                                                     
{'loss': 1.6288, 'learning_rate': 4.15410881565377e-05, 'epoch': 0.8}

 80%|███████▉  | 2843/3566 [1:54:52<29:07,  2.42s/it]
 80%|███████▉  | 2844/3566 [1:54:54<28:56,  2.41s/it]
                                                     
{'loss': 1.6367, 'learning_rate': 4.143054694480828e-05, 'epoch': 0.8}

 80%|███████▉  | 2844/3566 [1:54:54<28:56,  2.41s/it]
 80%|███████▉  | 2845/3566 [1:54:57<28:59,  2.41s/it]
                                                     
{'loss': 1.5206, 'learning_rate': 4.132013600839242e-05, 'epoch': 0.8}

 80%|███████▉  | 2845/3566 [1:54:57<28:59,  2.41s/it]
 80%|███████▉  | 2846/3566 [1:54:59<29:29,  2.46s/it]
                                                     
{'loss': 1.5096, 'learning_rate': 4.1209855438e-05, 'epoch': 0.8}

 80%|███████▉  | 2846/3566 [1:54:59<29:29,  2.46s/it]
 80%|███████▉  | 2847/3566 [1:55:02<29:47,  2.49s/it]
                                                     
{'loss': 1.5294, 'learning_rate': 4.109970532423384e-05, 'epoch': 0.8}

 80%|███████▉  | 2847/3566 [1:55:02<29:47,  2.49s/it]
 80%|███████▉  | 2848/3566 [1:55:04<29:50,  2.49s/it]
                                                     
{'loss': 1.4854, 'learning_rate': 4.0989685757589525e-05, 'epoch': 0.8}

 80%|███████▉  | 2848/3566 [1:55:04<29:50,  2.49s/it]
 80%|███████▉  | 2849/3566 [1:55:07<30:06,  2.52s/it]
                                                     
{'loss': 1.7426, 'learning_rate': 4.0879796828455465e-05, 'epoch': 0.8}

 80%|███████▉  | 2849/3566 [1:55:07<30:06,  2.52s/it]
 80%|███████▉  | 2850/3566 [1:55:10<32:58,  2.76s/it]
                                                     
{'loss': 1.3822, 'learning_rate': 4.077003862711264e-05, 'epoch': 0.8}

 80%|███████▉  | 2850/3566 [1:55:10<32:58,  2.76s/it]
 80%|███████▉  | 2851/3566 [1:55:12<30:41,  2.58s/it]
                                                     
{'loss': 1.5503, 'learning_rate': 4.0660411243734786e-05, 'epoch': 0.8}

 80%|███████▉  | 2851/3566 [1:55:12<30:41,  2.58s/it]
 80%|███████▉  | 2852/3566 [1:55:14<29:21,  2.47s/it]
                                                     
{'loss': 1.4344, 'learning_rate': 4.055091476838793e-05, 'epoch': 0.8}

 80%|███████▉  | 2852/3566 [1:55:14<29:21,  2.47s/it]
 80%|████████  | 2853/3566 [1:55:17<29:52,  2.51s/it]
                                                     
{'loss': 1.4241, 'learning_rate': 4.0441549291030746e-05, 'epoch': 0.8}

 80%|████████  | 2853/3566 [1:55:17<29:52,  2.51s/it]
 80%|████████  | 2854/3566 [1:55:20<30:05,  2.54s/it]
                                                     
{'loss': 1.6192, 'learning_rate': 4.0332314901514234e-05, 'epoch': 0.8}

 80%|████████  | 2854/3566 [1:55:20<30:05,  2.54s/it]
 80%|████████  | 2855/3566 [1:55:23<31:40,  2.67s/it]
                                                     
{'loss': 1.5255, 'learning_rate': 4.022321168958165e-05, 'epoch': 0.8}

 80%|████████  | 2855/3566 [1:55:23<31:40,  2.67s/it]
 80%|████████  | 2856/3566 [1:55:25<31:07,  2.63s/it]
                                                     
{'loss': 1.4838, 'learning_rate': 4.01142397448685e-05, 'epoch': 0.8}

 80%|████████  | 2856/3566 [1:55:25<31:07,  2.63s/it]
 80%|████████  | 2857/3566 [1:55:27<29:44,  2.52s/it]
                                                     
{'loss': 1.493, 'learning_rate': 4.000539915690253e-05, 'epoch': 0.8}

 80%|████████  | 2857/3566 [1:55:27<29:44,  2.52s/it]
 80%|████████  | 2858/3566 [1:55:30<29:07,  2.47s/it]
                                                     
{'loss': 1.4214, 'learning_rate': 3.989669001510346e-05, 'epoch': 0.8}

 80%|████████  | 2858/3566 [1:55:30<29:07,  2.47s/it]
 80%|████████  | 2859/3566 [1:55:32<28:19,  2.40s/it]
                                                     
{'loss': 1.6094, 'learning_rate': 3.978811240878311e-05, 'epoch': 0.8}

 80%|████████  | 2859/3566 [1:55:32<28:19,  2.40s/it]
 80%|████████  | 2860/3566 [1:55:34<28:32,  2.43s/it]
                                                     
{'loss': 1.4703, 'learning_rate': 3.967966642714505e-05, 'epoch': 0.8}

 80%|████████  | 2860/3566 [1:55:34<28:32,  2.43s/it]
 80%|████████  | 2861/3566 [1:55:37<28:54,  2.46s/it]
                                                     
{'loss': 1.5696, 'learning_rate': 3.957135215928491e-05, 'epoch': 0.8}

 80%|████████  | 2861/3566 [1:55:37<28:54,  2.46s/it]
 80%|████████  | 2862/3566 [1:55:39<28:27,  2.43s/it]
                                                     
{'loss': 1.4994, 'learning_rate': 3.946316969419004e-05, 'epoch': 0.8}

 80%|████████  | 2862/3566 [1:55:39<28:27,  2.43s/it]
 80%|████████  | 2863/3566 [1:55:42<27:50,  2.38s/it]
                                                     
{'loss': 1.5138, 'learning_rate': 3.93551191207395e-05, 'epoch': 0.8}

 80%|████████  | 2863/3566 [1:55:42<27:50,  2.38s/it]
 80%|████████  | 2864/3566 [1:55:44<27:07,  2.32s/it]
                                                     
{'loss': 1.4514, 'learning_rate': 3.924720052770401e-05, 'epoch': 0.8}

 80%|████████  | 2864/3566 [1:55:44<27:07,  2.32s/it]
 80%|████████  | 2865/3566 [1:55:46<26:27,  2.26s/it]
                                                     
{'loss': 1.6211, 'learning_rate': 3.9139414003745835e-05, 'epoch': 0.8}

 80%|████████  | 2865/3566 [1:55:46<26:27,  2.26s/it]
 80%|████████  | 2866/3566 [1:55:48<26:50,  2.30s/it]
                                                     
{'loss': 1.561, 'learning_rate': 3.9031759637418716e-05, 'epoch': 0.8}

 80%|████████  | 2866/3566 [1:55:48<26:50,  2.30s/it]
 80%|████████  | 2867/3566 [1:55:50<26:14,  2.25s/it]
                                                     
{'loss': 1.5925, 'learning_rate': 3.8924237517167916e-05, 'epoch': 0.8}

 80%|████████  | 2867/3566 [1:55:50<26:14,  2.25s/it]
 80%|████████  | 2868/3566 [1:55:53<26:35,  2.29s/it]
                                                     
{'loss': 1.5652, 'learning_rate': 3.881684773132992e-05, 'epoch': 0.8}

 80%|████████  | 2868/3566 [1:55:53<26:35,  2.29s/it]
 80%|████████  | 2869/3566 [1:55:55<27:36,  2.38s/it]
                                                     
{'loss': 1.3362, 'learning_rate': 3.870959036813262e-05, 'epoch': 0.8}

 80%|████████  | 2869/3566 [1:55:55<27:36,  2.38s/it]
 80%|████████  | 2870/3566 [1:55:58<27:29,  2.37s/it]
                                                     
{'loss': 1.4931, 'learning_rate': 3.860246551569493e-05, 'epoch': 0.8}

 80%|████████  | 2870/3566 [1:55:58<27:29,  2.37s/it]
 81%|████████  | 2871/3566 [1:56:00<27:33,  2.38s/it]
                                                     
{'loss': 1.4719, 'learning_rate': 3.849547326202712e-05, 'epoch': 0.81}

 81%|████████  | 2871/3566 [1:56:00<27:33,  2.38s/it]
 81%|████████  | 2872/3566 [1:56:02<27:07,  2.35s/it]
                                                     
{'loss': 1.4975, 'learning_rate': 3.8388613695030394e-05, 'epoch': 0.81}

 81%|████████  | 2872/3566 [1:56:02<27:07,  2.35s/it]
 81%|████████  | 2873/3566 [1:56:05<27:11,  2.35s/it]
                                                     
{'loss': 1.6008, 'learning_rate': 3.828188690249694e-05, 'epoch': 0.81}

 81%|████████  | 2873/3566 [1:56:05<27:11,  2.35s/it]
 81%|████████  | 2874/3566 [1:56:07<27:13,  2.36s/it]
                                                     
{'loss': 1.408, 'learning_rate': 3.817529297210993e-05, 'epoch': 0.81}

 81%|████████  | 2874/3566 [1:56:07<27:13,  2.36s/it]
 81%|████████  | 2875/3566 [1:56:10<27:24,  2.38s/it]
                                                     
{'loss': 1.6894, 'learning_rate': 3.806883199144333e-05, 'epoch': 0.81}

 81%|████████  | 2875/3566 [1:56:10<27:24,  2.38s/it]
 81%|████████  | 2876/3566 [1:56:12<27:30,  2.39s/it]
                                                     
{'loss': 1.5417, 'learning_rate': 3.7962504047961864e-05, 'epoch': 0.81}

 81%|████████  | 2876/3566 [1:56:12<27:30,  2.39s/it]
 81%|████████  | 2877/3566 [1:56:14<27:22,  2.38s/it]
                                                     
{'loss': 1.4405, 'learning_rate': 3.7856309229021083e-05, 'epoch': 0.81}

 81%|████████  | 2877/3566 [1:56:14<27:22,  2.38s/it]
 81%|████████  | 2878/3566 [1:56:17<27:05,  2.36s/it]
                                                     
{'loss': 1.4441, 'learning_rate': 3.7750247621866896e-05, 'epoch': 0.81}

 81%|████████  | 2878/3566 [1:56:17<27:05,  2.36s/it]
 81%|████████  | 2879/3566 [1:56:19<27:01,  2.36s/it]
                                                     
{'loss': 1.4824, 'learning_rate': 3.764431931363605e-05, 'epoch': 0.81}

 81%|████████  | 2879/3566 [1:56:19<27:01,  2.36s/it]
 81%|████████  | 2880/3566 [1:56:21<27:09,  2.38s/it]
                                                     
{'loss': 1.624, 'learning_rate': 3.7538524391355655e-05, 'epoch': 0.81}

 81%|████████  | 2880/3566 [1:56:21<27:09,  2.38s/it]
 81%|████████  | 2881/3566 [1:56:24<27:53,  2.44s/it]
                                                     
{'loss': 1.4276, 'learning_rate': 3.7432862941943234e-05, 'epoch': 0.81}

 81%|████████  | 2881/3566 [1:56:24<27:53,  2.44s/it]
 81%|████████  | 2882/3566 [1:56:27<29:09,  2.56s/it]
                                                     
{'loss': 1.4608, 'learning_rate': 3.732733505220669e-05, 'epoch': 0.81}

 81%|████████  | 2882/3566 [1:56:27<29:09,  2.56s/it]
 81%|████████  | 2883/3566 [1:56:29<27:45,  2.44s/it]
                                                     
{'loss': 1.3405, 'learning_rate': 3.722194080884418e-05, 'epoch': 0.81}

 81%|████████  | 2883/3566 [1:56:29<27:45,  2.44s/it]
 81%|████████  | 2884/3566 [1:56:32<28:01,  2.47s/it]
                                                     
{'loss': 1.4681, 'learning_rate': 3.7116680298444e-05, 'epoch': 0.81}

 81%|████████  | 2884/3566 [1:56:32<28:01,  2.47s/it]
 81%|████████  | 2885/3566 [1:56:34<26:50,  2.37s/it]
                                                     
{'loss': 1.5053, 'learning_rate': 3.701155360748476e-05, 'epoch': 0.81}

 81%|████████  | 2885/3566 [1:56:34<26:50,  2.37s/it]
 81%|████████  | 2886/3566 [1:56:36<26:59,  2.38s/it]
                                                     
{'loss': 1.61, 'learning_rate': 3.6906560822334904e-05, 'epoch': 0.81}

 81%|████████  | 2886/3566 [1:56:36<26:59,  2.38s/it]
 81%|████████  | 2887/3566 [1:56:38<26:41,  2.36s/it]
                                                     
{'loss': 1.4223, 'learning_rate': 3.680170202925297e-05, 'epoch': 0.81}

 81%|████████  | 2887/3566 [1:56:38<26:41,  2.36s/it]
 81%|████████  | 2888/3566 [1:56:41<26:44,  2.37s/it]
                                                     
{'loss': 1.4884, 'learning_rate': 3.669697731438741e-05, 'epoch': 0.81}

 81%|████████  | 2888/3566 [1:56:41<26:44,  2.37s/it]
 81%|████████  | 2889/3566 [1:56:43<27:11,  2.41s/it]
                                                     
{'loss': 1.5391, 'learning_rate': 3.659238676377654e-05, 'epoch': 0.81}

 81%|████████  | 2889/3566 [1:56:43<27:11,  2.41s/it]
 81%|████████  | 2890/3566 [1:56:46<27:09,  2.41s/it]
                                                     
{'loss': 1.6644, 'learning_rate': 3.648793046334842e-05, 'epoch': 0.81}

 81%|████████  | 2890/3566 [1:56:46<27:09,  2.41s/it]
 81%|████████  | 2891/3566 [1:56:48<26:13,  2.33s/it]
                                                     
{'loss': 1.5201, 'learning_rate': 3.638360849892082e-05, 'epoch': 0.81}

 81%|████████  | 2891/3566 [1:56:48<26:13,  2.33s/it]
 81%|████████  | 2892/3566 [1:56:50<25:29,  2.27s/it]
                                                     
{'loss': 1.5313, 'learning_rate': 3.627942095620114e-05, 'epoch': 0.81}

 81%|████████  | 2892/3566 [1:56:50<25:29,  2.27s/it]
 81%|████████  | 2893/3566 [1:56:53<27:19,  2.44s/it]
                                                     
{'loss': 1.6214, 'learning_rate': 3.617536792078635e-05, 'epoch': 0.81}

 81%|████████  | 2893/3566 [1:56:53<27:19,  2.44s/it]
 81%|████████  | 2894/3566 [1:56:55<27:32,  2.46s/it]
                                                     
{'loss': 1.3895, 'learning_rate': 3.607144947816297e-05, 'epoch': 0.81}

 81%|████████  | 2894/3566 [1:56:55<27:32,  2.46s/it]
 81%|████████  | 2895/3566 [1:56:58<27:59,  2.50s/it]
                                                     
{'loss': 1.5951, 'learning_rate': 3.59676657137068e-05, 'epoch': 0.81}

 81%|████████  | 2895/3566 [1:56:58<27:59,  2.50s/it]
 81%|████████  | 2896/3566 [1:57:00<27:30,  2.46s/it]
                                                     
{'loss': 1.5363, 'learning_rate': 3.586401671268311e-05, 'epoch': 0.81}

 81%|████████  | 2896/3566 [1:57:00<27:30,  2.46s/it]
 81%|████████  | 2897/3566 [1:57:03<27:11,  2.44s/it]
                                                     
{'loss': 1.4176, 'learning_rate': 3.576050256024641e-05, 'epoch': 0.81}

 81%|████████  | 2897/3566 [1:57:03<27:11,  2.44s/it]
 81%|████████▏ | 2898/3566 [1:57:05<26:18,  2.36s/it]
                                                     
{'loss': 1.4399, 'learning_rate': 3.565712334144042e-05, 'epoch': 0.81}

 81%|████████▏ | 2898/3566 [1:57:05<26:18,  2.36s/it]
 81%|████████▏ | 2899/3566 [1:57:08<28:38,  2.58s/it]
                                                     
{'loss': 1.4571, 'learning_rate': 3.555387914119812e-05, 'epoch': 0.81}

 81%|████████▏ | 2899/3566 [1:57:08<28:38,  2.58s/it]
 81%|████████▏ | 2900/3566 [1:57:10<27:02,  2.44s/it]
                                                     
{'loss': 1.5811, 'learning_rate': 3.545077004434138e-05, 'epoch': 0.81}

 81%|████████▏ | 2900/3566 [1:57:10<27:02,  2.44s/it]
 81%|████████▏ | 2901/3566 [1:57:12<26:33,  2.40s/it]
                                                     
{'loss': 1.3783, 'learning_rate': 3.5347796135581165e-05, 'epoch': 0.81}

 81%|████████▏ | 2901/3566 [1:57:12<26:33,  2.40s/it]
 81%|████████▏ | 2902/3566 [1:57:15<26:04,  2.36s/it]
                                                     
{'loss': 1.4157, 'learning_rate': 3.524495749951744e-05, 'epoch': 0.81}

 81%|████████▏ | 2902/3566 [1:57:15<26:04,  2.36s/it]
 81%|████████▏ | 2903/3566 [1:57:17<25:46,  2.33s/it]
                                                     
{'loss': 1.4323, 'learning_rate': 3.514225422063884e-05, 'epoch': 0.81}

 81%|████████▏ | 2903/3566 [1:57:17<25:46,  2.33s/it]
 81%|████████▏ | 2904/3566 [1:57:19<25:45,  2.33s/it]
                                                     
{'loss': 1.4874, 'learning_rate': 3.5039686383322935e-05, 'epoch': 0.81}

 81%|████████▏ | 2904/3566 [1:57:19<25:45,  2.33s/it]
 81%|████████▏ | 2905/3566 [1:57:22<25:19,  2.30s/it]
                                                     
{'loss': 1.4969, 'learning_rate': 3.4937254071836054e-05, 'epoch': 0.81}

 81%|████████▏ | 2905/3566 [1:57:22<25:19,  2.30s/it]
 81%|████████▏ | 2906/3566 [1:57:24<26:01,  2.37s/it]
                                                     
{'loss': 1.5267, 'learning_rate': 3.483495737033311e-05, 'epoch': 0.81}

 81%|████████▏ | 2906/3566 [1:57:24<26:01,  2.37s/it]
 82%|████████▏ | 2907/3566 [1:57:26<25:55,  2.36s/it]
                                                     
{'loss': 1.7283, 'learning_rate': 3.47327963628576e-05, 'epoch': 0.82}

 82%|████████▏ | 2907/3566 [1:57:26<25:55,  2.36s/it]
 82%|████████▏ | 2908/3566 [1:57:29<26:59,  2.46s/it]
                                                     
{'loss': 1.5255, 'learning_rate': 3.463077113334159e-05, 'epoch': 0.82}

 82%|████████▏ | 2908/3566 [1:57:29<26:59,  2.46s/it]
 82%|████████▏ | 2909/3566 [1:57:31<26:18,  2.40s/it]
                                                     
{'loss': 1.5527, 'learning_rate': 3.452888176560556e-05, 'epoch': 0.82}

 82%|████████▏ | 2909/3566 [1:57:31<26:18,  2.40s/it]
 82%|████████▏ | 2910/3566 [1:57:34<25:51,  2.36s/it]
                                                     
{'loss': 1.6928, 'learning_rate': 3.4427128343358376e-05, 'epoch': 0.82}

 82%|████████▏ | 2910/3566 [1:57:34<25:51,  2.36s/it]
 82%|████████▏ | 2911/3566 [1:57:36<25:29,  2.33s/it]
                                                     
{'loss': 1.5024, 'learning_rate': 3.4325510950197206e-05, 'epoch': 0.82}

 82%|████████▏ | 2911/3566 [1:57:36<25:29,  2.33s/it]
 82%|████████▏ | 2912/3566 [1:57:38<25:06,  2.30s/it]
                                                     
{'loss': 1.5279, 'learning_rate': 3.422402966960747e-05, 'epoch': 0.82}

 82%|████████▏ | 2912/3566 [1:57:38<25:06,  2.30s/it]
 82%|████████▏ | 2913/3566 [1:57:40<25:12,  2.32s/it]
                                                     
{'loss': 1.5407, 'learning_rate': 3.41226845849628e-05, 'epoch': 0.82}

 82%|████████▏ | 2913/3566 [1:57:40<25:12,  2.32s/it]
 82%|████████▏ | 2914/3566 [1:57:43<25:30,  2.35s/it]
                                                     
{'loss': 1.305, 'learning_rate': 3.402147577952484e-05, 'epoch': 0.82}

 82%|████████▏ | 2914/3566 [1:57:43<25:30,  2.35s/it]
 82%|████████▏ | 2915/3566 [1:57:45<25:43,  2.37s/it]
                                                     
{'loss': 1.629, 'learning_rate': 3.3920403336443394e-05, 'epoch': 0.82}

 82%|████████▏ | 2915/3566 [1:57:45<25:43,  2.37s/it]
 82%|████████▏ | 2916/3566 [1:57:48<25:41,  2.37s/it]
                                                     
{'loss': 1.629, 'learning_rate': 3.3819467338756136e-05, 'epoch': 0.82}

 82%|████████▏ | 2916/3566 [1:57:48<25:41,  2.37s/it]
 82%|████████▏ | 2917/3566 [1:57:51<28:06,  2.60s/it]
                                                     
{'loss': 1.413, 'learning_rate': 3.3718667869388663e-05, 'epoch': 0.82}

 82%|████████▏ | 2917/3566 [1:57:51<28:06,  2.60s/it]
 82%|████████▏ | 2918/3566 [1:57:53<27:02,  2.50s/it]
                                                     
{'loss': 1.5077, 'learning_rate': 3.3618005011154464e-05, 'epoch': 0.82}

 82%|████████▏ | 2918/3566 [1:57:53<27:02,  2.50s/it]
 82%|████████▏ | 2919/3566 [1:57:55<26:21,  2.44s/it]
                                                     
{'loss': 1.5147, 'learning_rate': 3.351747884675471e-05, 'epoch': 0.82}

 82%|████████▏ | 2919/3566 [1:57:55<26:21,  2.44s/it]
 82%|████████▏ | 2920/3566 [1:57:58<26:08,  2.43s/it]
                                                     
{'loss': 1.5329, 'learning_rate': 3.341708945877837e-05, 'epoch': 0.82}

 82%|████████▏ | 2920/3566 [1:57:58<26:08,  2.43s/it]
 82%|████████▏ | 2921/3566 [1:58:00<26:07,  2.43s/it]
                                                     
{'loss': 1.4794, 'learning_rate': 3.331683692970189e-05, 'epoch': 0.82}

 82%|████████▏ | 2921/3566 [1:58:00<26:07,  2.43s/it]
 82%|████████▏ | 2922/3566 [1:58:03<26:18,  2.45s/it]
                                                     
{'loss': 1.5778, 'learning_rate': 3.32167213418894e-05, 'epoch': 0.82}

 82%|████████▏ | 2922/3566 [1:58:03<26:18,  2.45s/it]
 82%|████████▏ | 2923/3566 [1:58:05<27:04,  2.53s/it]
                                                     
{'loss': 1.5636, 'learning_rate': 3.311674277759249e-05, 'epoch': 0.82}

 82%|████████▏ | 2923/3566 [1:58:05<27:04,  2.53s/it]
 82%|████████▏ | 2924/3566 [1:58:08<26:27,  2.47s/it]
                                                     
{'loss': 1.6192, 'learning_rate': 3.301690131895016e-05, 'epoch': 0.82}

 82%|████████▏ | 2924/3566 [1:58:08<26:27,  2.47s/it]
 82%|████████▏ | 2925/3566 [1:58:10<26:19,  2.46s/it]
                                                     
{'loss': 1.5076, 'learning_rate': 3.291719704798884e-05, 'epoch': 0.82}

 82%|████████▏ | 2925/3566 [1:58:10<26:19,  2.46s/it]
 82%|████████▏ | 2926/3566 [1:58:12<25:28,  2.39s/it]
                                                     
{'loss': 1.3965, 'learning_rate': 3.281763004662208e-05, 'epoch': 0.82}

 82%|████████▏ | 2926/3566 [1:58:12<25:28,  2.39s/it]
 82%|████████▏ | 2927/3566 [1:58:15<25:28,  2.39s/it]
                                                     
{'loss': 1.4415, 'learning_rate': 3.271820039665092e-05, 'epoch': 0.82}

 82%|████████▏ | 2927/3566 [1:58:15<25:28,  2.39s/it]
 82%|████████▏ | 2928/3566 [1:58:17<25:33,  2.40s/it]
                                                     
{'loss': 1.4371, 'learning_rate': 3.2618908179763386e-05, 'epoch': 0.82}

 82%|████████▏ | 2928/3566 [1:58:17<25:33,  2.40s/it]
 82%|████████▏ | 2929/3566 [1:58:20<26:40,  2.51s/it]
                                                     
{'loss': 1.5952, 'learning_rate': 3.251975347753451e-05, 'epoch': 0.82}

 82%|████████▏ | 2929/3566 [1:58:20<26:40,  2.51s/it]
 82%|████████▏ | 2930/3566 [1:58:23<27:05,  2.56s/it]
                                                     
{'loss': 1.6255, 'learning_rate': 3.2420736371426486e-05, 'epoch': 0.82}

 82%|████████▏ | 2930/3566 [1:58:23<27:05,  2.56s/it]
 82%|████████▏ | 2931/3566 [1:58:25<26:26,  2.50s/it]
                                                     
{'loss': 1.6084, 'learning_rate': 3.232185694278846e-05, 'epoch': 0.82}

 82%|████████▏ | 2931/3566 [1:58:25<26:26,  2.50s/it]
 82%|████████▏ | 2932/3566 [1:58:28<27:18,  2.58s/it]
                                                     
{'loss': 1.5345, 'learning_rate': 3.222311527285642e-05, 'epoch': 0.82}

 82%|████████▏ | 2932/3566 [1:58:28<27:18,  2.58s/it]
 82%|████████▏ | 2933/3566 [1:58:30<27:23,  2.60s/it]
                                                     
{'loss': 1.5229, 'learning_rate': 3.212451144275319e-05, 'epoch': 0.82}

 82%|████████▏ | 2933/3566 [1:58:30<27:23,  2.60s/it]
 82%|████████▏ | 2934/3566 [1:58:33<26:56,  2.56s/it]
                                                     
{'loss': 1.4737, 'learning_rate': 3.202604553348836e-05, 'epoch': 0.82}

 82%|████████▏ | 2934/3566 [1:58:33<26:56,  2.56s/it]
 82%|████████▏ | 2935/3566 [1:58:35<25:38,  2.44s/it]
                                                     
{'loss': 1.5007, 'learning_rate': 3.1927717625958184e-05, 'epoch': 0.82}

 82%|████████▏ | 2935/3566 [1:58:35<25:38,  2.44s/it]
 82%|████████▏ | 2936/3566 [1:58:38<26:36,  2.53s/it]
                                                     
{'loss': 1.5044, 'learning_rate': 3.182952780094557e-05, 'epoch': 0.82}

 82%|████████▏ | 2936/3566 [1:58:38<26:36,  2.53s/it]
 82%|████████▏ | 2937/3566 [1:58:40<25:46,  2.46s/it]
                                                     
{'loss': 1.4093, 'learning_rate': 3.173147613912e-05, 'epoch': 0.82}

 82%|████████▏ | 2937/3566 [1:58:40<25:46,  2.46s/it]
 82%|████████▏ | 2938/3566 [1:58:43<26:24,  2.52s/it]
                                                     
{'loss': 1.331, 'learning_rate': 3.163356272103732e-05, 'epoch': 0.82}

 82%|████████▏ | 2938/3566 [1:58:43<26:24,  2.52s/it]
 82%|████████▏ | 2939/3566 [1:58:45<26:08,  2.50s/it]
                                                     
{'loss': 1.4292, 'learning_rate': 3.153578762713996e-05, 'epoch': 0.82}

 82%|████████▏ | 2939/3566 [1:58:45<26:08,  2.50s/it]
 82%|████████▏ | 2940/3566 [1:58:47<25:06,  2.41s/it]
                                                     
{'loss': 1.5713, 'learning_rate': 3.1438150937756596e-05, 'epoch': 0.82}

 82%|████████▏ | 2940/3566 [1:58:47<25:06,  2.41s/it]
 82%|████████▏ | 2941/3566 [1:58:50<25:20,  2.43s/it]
                                                     
{'loss': 1.5599, 'learning_rate': 3.134065273310223e-05, 'epoch': 0.82}

 82%|████████▏ | 2941/3566 [1:58:50<25:20,  2.43s/it]
 83%|████████▎ | 2942/3566 [1:58:52<25:23,  2.44s/it]
                                                     
{'loss': 1.5376, 'learning_rate': 3.124329309327816e-05, 'epoch': 0.83}

 83%|████████▎ | 2942/3566 [1:58:52<25:23,  2.44s/it]
 83%|████████▎ | 2943/3566 [1:58:55<24:43,  2.38s/it]
                                                     
{'loss': 1.4192, 'learning_rate': 3.114607209827176e-05, 'epoch': 0.83}

 83%|████████▎ | 2943/3566 [1:58:55<24:43,  2.38s/it]
 83%|████████▎ | 2944/3566 [1:58:57<24:21,  2.35s/it]
                                                     
{'loss': 1.7012, 'learning_rate': 3.104898982795652e-05, 'epoch': 0.83}

 83%|████████▎ | 2944/3566 [1:58:57<24:21,  2.35s/it]
 83%|████████▎ | 2945/3566 [1:58:59<23:44,  2.29s/it]
                                                     
{'loss': 1.4337, 'learning_rate': 3.095204636209199e-05, 'epoch': 0.83}

 83%|████████▎ | 2945/3566 [1:58:59<23:44,  2.29s/it]
 83%|████████▎ | 2946/3566 [1:59:02<24:11,  2.34s/it]
                                                     
{'loss': 1.6364, 'learning_rate': 3.0855241780323574e-05, 'epoch': 0.83}

 83%|████████▎ | 2946/3566 [1:59:02<24:11,  2.34s/it]
 83%|████████▎ | 2947/3566 [1:59:04<24:34,  2.38s/it]
                                                     
{'loss': 1.5152, 'learning_rate': 3.0758576162182694e-05, 'epoch': 0.83}

 83%|████████▎ | 2947/3566 [1:59:04<24:34,  2.38s/it]
 83%|████████▎ | 2948/3566 [1:59:06<24:17,  2.36s/it]
                                                     
{'loss': 1.6497, 'learning_rate': 3.066204958708654e-05, 'epoch': 0.83}

 83%|████████▎ | 2948/3566 [1:59:06<24:17,  2.36s/it]
 83%|████████▎ | 2949/3566 [1:59:09<23:48,  2.32s/it]
                                                     
{'loss': 1.4281, 'learning_rate': 3.056566213433811e-05, 'epoch': 0.83}

 83%|████████▎ | 2949/3566 [1:59:09<23:48,  2.32s/it]
 83%|████████▎ | 2950/3566 [1:59:11<23:10,  2.26s/it]
                                                     
{'loss': 1.526, 'learning_rate': 3.0469413883126074e-05, 'epoch': 0.83}

 83%|████████▎ | 2950/3566 [1:59:11<23:10,  2.26s/it]
 83%|████████▎ | 2951/3566 [1:59:13<23:33,  2.30s/it]
                                                     
{'loss': 1.5543, 'learning_rate': 3.037330491252477e-05, 'epoch': 0.83}

 83%|████████▎ | 2951/3566 [1:59:13<23:33,  2.30s/it]
 83%|████████▎ | 2952/3566 [1:59:15<23:45,  2.32s/it]
                                                     
{'loss': 1.6115, 'learning_rate': 3.0277335301494057e-05, 'epoch': 0.83}

 83%|████████▎ | 2952/3566 [1:59:15<23:45,  2.32s/it]
 83%|████████▎ | 2953/3566 [1:59:18<24:04,  2.36s/it]
                                                     
{'loss': 1.3965, 'learning_rate': 3.0181505128879362e-05, 'epoch': 0.83}

 83%|████████▎ | 2953/3566 [1:59:18<24:04,  2.36s/it]
 83%|████████▎ | 2954/3566 [1:59:21<25:16,  2.48s/it]
                                                     
{'loss': 1.4513, 'learning_rate': 3.008581447341148e-05, 'epoch': 0.83}

 83%|████████▎ | 2954/3566 [1:59:21<25:16,  2.48s/it]
 83%|████████▎ | 2955/3566 [1:59:23<24:51,  2.44s/it]
                                                     
{'loss': 1.5136, 'learning_rate': 2.9990263413706655e-05, 'epoch': 0.83}

 83%|████████▎ | 2955/3566 [1:59:23<24:51,  2.44s/it]
 83%|████████▎ | 2956/3566 [1:59:25<24:09,  2.38s/it]
                                                     
{'loss': 1.5729, 'learning_rate': 2.9894852028266407e-05, 'epoch': 0.83}

 83%|████████▎ | 2956/3566 [1:59:25<24:09,  2.38s/it]
 83%|████████▎ | 2957/3566 [1:59:27<23:27,  2.31s/it]
                                                     
{'loss': 1.4587, 'learning_rate': 2.9799580395477522e-05, 'epoch': 0.83}

 83%|████████▎ | 2957/3566 [1:59:27<23:27,  2.31s/it]
 83%|████████▎ | 2958/3566 [1:59:30<23:20,  2.30s/it]
                                                     
{'loss': 1.1967, 'learning_rate': 2.9704448593611946e-05, 'epoch': 0.83}

 83%|████████▎ | 2958/3566 [1:59:30<23:20,  2.30s/it]
 83%|████████▎ | 2959/3566 [1:59:32<23:33,  2.33s/it]
                                                     
{'loss': 1.5435, 'learning_rate': 2.9609456700826754e-05, 'epoch': 0.83}

 83%|████████▎ | 2959/3566 [1:59:32<23:33,  2.33s/it]
 83%|████████▎ | 2960/3566 [1:59:34<23:55,  2.37s/it]
                                                     
{'loss': 1.32, 'learning_rate': 2.9514604795164103e-05, 'epoch': 0.83}

 83%|████████▎ | 2960/3566 [1:59:34<23:55,  2.37s/it]
 83%|████████▎ | 2961/3566 [1:59:37<24:11,  2.40s/it]
                                                     
{'loss': 1.4174, 'learning_rate': 2.94198929545511e-05, 'epoch': 0.83}

 83%|████████▎ | 2961/3566 [1:59:37<24:11,  2.40s/it]
 83%|████████▎ | 2962/3566 [1:59:39<24:27,  2.43s/it]
                                                     
{'loss': 1.5801, 'learning_rate': 2.932532125679981e-05, 'epoch': 0.83}

 83%|████████▎ | 2962/3566 [1:59:39<24:27,  2.43s/it]
 83%|████████▎ | 2963/3566 [1:59:42<24:37,  2.45s/it]
                                                     
{'loss': 1.489, 'learning_rate': 2.9230889779607175e-05, 'epoch': 0.83}

 83%|████████▎ | 2963/3566 [1:59:42<24:37,  2.45s/it]
 83%|████████▎ | 2964/3566 [1:59:45<25:34,  2.55s/it]
                                                     
{'loss': 1.419, 'learning_rate': 2.9136598600554843e-05, 'epoch': 0.83}

 83%|████████▎ | 2964/3566 [1:59:45<25:34,  2.55s/it]
 83%|████████▎ | 2965/3566 [1:59:47<24:57,  2.49s/it]
                                                     
{'loss': 1.3829, 'learning_rate': 2.9042447797109296e-05, 'epoch': 0.83}

 83%|████████▎ | 2965/3566 [1:59:47<24:57,  2.49s/it]
 83%|████████▎ | 2966/3566 [1:59:49<24:30,  2.45s/it]
                                                     
{'loss': 1.42, 'learning_rate': 2.894843744662168e-05, 'epoch': 0.83}

 83%|████████▎ | 2966/3566 [1:59:49<24:30,  2.45s/it]
 83%|████████▎ | 2967/3566 [1:59:52<24:38,  2.47s/it]
                                                     
{'loss': 1.6965, 'learning_rate': 2.88545676263277e-05, 'epoch': 0.83}

 83%|████████▎ | 2967/3566 [1:59:52<24:38,  2.47s/it]
 83%|████████▎ | 2968/3566 [1:59:54<24:35,  2.47s/it]
                                                     
{'loss': 1.6632, 'learning_rate': 2.8760838413347645e-05, 'epoch': 0.83}

 83%|████████▎ | 2968/3566 [1:59:54<24:35,  2.47s/it]
 83%|████████▎ | 2969/3566 [1:59:57<24:01,  2.42s/it]
                                                     
{'loss': 1.4283, 'learning_rate': 2.866724988468623e-05, 'epoch': 0.83}

 83%|████████▎ | 2969/3566 [1:59:57<24:01,  2.42s/it]
 83%|████████▎ | 2970/3566 [1:59:59<24:04,  2.42s/it]
                                                     
{'loss': 1.5621, 'learning_rate': 2.8573802117232727e-05, 'epoch': 0.83}

 83%|████████▎ | 2970/3566 [1:59:59<24:04,  2.42s/it]
 83%|████████▎ | 2971/3566 [2:00:02<24:02,  2.42s/it]
                                                     
{'loss': 1.5678, 'learning_rate': 2.848049518776068e-05, 'epoch': 0.83}

 83%|████████▎ | 2971/3566 [2:00:02<24:02,  2.42s/it]
 83%|████████▎ | 2972/3566 [2:00:04<24:22,  2.46s/it]
                                                     
{'loss': 1.5593, 'learning_rate': 2.838732917292779e-05, 'epoch': 0.83}

 83%|████████▎ | 2972/3566 [2:00:04<24:22,  2.46s/it]
 83%|████████▎ | 2973/3566 [2:00:07<24:46,  2.51s/it]
                                                     
{'loss': 1.3675, 'learning_rate': 2.8294304149276186e-05, 'epoch': 0.83}

 83%|████████▎ | 2973/3566 [2:00:07<24:46,  2.51s/it]
 83%|████████▎ | 2974/3566 [2:00:09<23:56,  2.43s/it]
                                                     
{'loss': 1.4717, 'learning_rate': 2.8201420193232087e-05, 'epoch': 0.83}

 83%|████████▎ | 2974/3566 [2:00:09<23:56,  2.43s/it]
 83%|████████▎ | 2975/3566 [2:00:11<23:11,  2.35s/it]
                                                     
{'loss': 1.383, 'learning_rate': 2.810867738110581e-05, 'epoch': 0.83}

 83%|████████▎ | 2975/3566 [2:00:11<23:11,  2.35s/it]
 83%|████████▎ | 2976/3566 [2:00:14<24:56,  2.54s/it]
                                                     
{'loss': 1.4145, 'learning_rate': 2.8016075789091712e-05, 'epoch': 0.83}

 83%|████████▎ | 2976/3566 [2:00:14<24:56,  2.54s/it]
 83%|████████▎ | 2977/3566 [2:00:16<23:38,  2.41s/it]
                                                     
{'loss': 1.2939, 'learning_rate': 2.7923615493268162e-05, 'epoch': 0.83}

 83%|████████▎ | 2977/3566 [2:00:16<23:38,  2.41s/it]
 84%|████████▎ | 2978/3566 [2:00:18<23:02,  2.35s/it]
                                                     
{'loss': 1.3699, 'learning_rate': 2.7831296569597397e-05, 'epoch': 0.84}

 84%|████████▎ | 2978/3566 [2:00:18<23:02,  2.35s/it]
 84%|████████▎ | 2979/3566 [2:00:21<23:08,  2.37s/it]
                                                     
{'loss': 1.4519, 'learning_rate': 2.7739119093925548e-05, 'epoch': 0.84}

 84%|████████▎ | 2979/3566 [2:00:21<23:08,  2.37s/it]
 84%|████████▎ | 2980/3566 [2:00:23<22:47,  2.33s/it]
                                                     
{'loss': 1.5443, 'learning_rate': 2.7647083141982544e-05, 'epoch': 0.84}

 84%|████████▎ | 2980/3566 [2:00:23<22:47,  2.33s/it]
 84%|████████▎ | 2981/3566 [2:00:25<22:54,  2.35s/it]
                                                     
{'loss': 1.5174, 'learning_rate': 2.7555188789381968e-05, 'epoch': 0.84}

 84%|████████▎ | 2981/3566 [2:00:26<22:54,  2.35s/it]
 84%|████████▎ | 2982/3566 [2:00:28<22:53,  2.35s/it]
                                                     
{'loss': 1.5687, 'learning_rate': 2.746343611162112e-05, 'epoch': 0.84}

 84%|████████▎ | 2982/3566 [2:00:28<22:53,  2.35s/it]
 84%|████████▎ | 2983/3566 [2:00:30<23:24,  2.41s/it]
                                                     
{'loss': 1.5241, 'learning_rate': 2.737182518408088e-05, 'epoch': 0.84}

 84%|████████▎ | 2983/3566 [2:00:30<23:24,  2.41s/it]
 84%|████████▎ | 2984/3566 [2:00:33<22:56,  2.36s/it]
                                                     
{'loss': 1.4496, 'learning_rate': 2.728035608202577e-05, 'epoch': 0.84}

 84%|████████▎ | 2984/3566 [2:00:33<22:56,  2.36s/it]
 84%|████████▎ | 2985/3566 [2:00:35<23:09,  2.39s/it]
                                                     
{'loss': 1.5648, 'learning_rate': 2.7189028880603706e-05, 'epoch': 0.84}

 84%|████████▎ | 2985/3566 [2:00:35<23:09,  2.39s/it]
 84%|████████▎ | 2986/3566 [2:00:38<23:45,  2.46s/it]
                                                     
{'loss': 1.642, 'learning_rate': 2.7097843654846e-05, 'epoch': 0.84}

 84%|████████▎ | 2986/3566 [2:00:38<23:45,  2.46s/it]
 84%|████████▍ | 2987/3566 [2:00:41<25:46,  2.67s/it]
                                                     
{'loss': 1.485, 'learning_rate': 2.7006800479667393e-05, 'epoch': 0.84}

 84%|████████▍ | 2987/3566 [2:00:41<25:46,  2.67s/it]
 84%|████████▍ | 2988/3566 [2:00:43<25:24,  2.64s/it]
                                                     
{'loss': 1.4646, 'learning_rate': 2.6915899429865922e-05, 'epoch': 0.84}

 84%|████████▍ | 2988/3566 [2:00:43<25:24,  2.64s/it]
 84%|████████▍ | 2989/3566 [2:00:46<24:24,  2.54s/it]
                                                     
{'loss': 1.489, 'learning_rate': 2.682514058012271e-05, 'epoch': 0.84}

 84%|████████▍ | 2989/3566 [2:00:46<24:24,  2.54s/it]
 84%|████████▍ | 2990/3566 [2:00:48<23:46,  2.48s/it]
                                                     
{'loss': 1.5544, 'learning_rate': 2.6734524005002226e-05, 'epoch': 0.84}

 84%|████████▍ | 2990/3566 [2:00:48<23:46,  2.48s/it]
 84%|████████▍ | 2991/3566 [2:00:50<23:18,  2.43s/it]
                                                     
{'loss': 1.6067, 'learning_rate': 2.6644049778951985e-05, 'epoch': 0.84}

 84%|████████▍ | 2991/3566 [2:00:50<23:18,  2.43s/it]
 84%|████████▍ | 2992/3566 [2:00:53<23:06,  2.42s/it]
                                                     
{'loss': 1.6649, 'learning_rate': 2.655371797630257e-05, 'epoch': 0.84}

 84%|████████▍ | 2992/3566 [2:00:53<23:06,  2.42s/it]
 84%|████████▍ | 2993/3566 [2:00:55<22:37,  2.37s/it]
                                                     
{'loss': 1.4564, 'learning_rate': 2.6463528671267534e-05, 'epoch': 0.84}

 84%|████████▍ | 2993/3566 [2:00:55<22:37,  2.37s/it]
 84%|████████▍ | 2994/3566 [2:00:58<22:59,  2.41s/it]
                                                     
{'loss': 1.5772, 'learning_rate': 2.637348193794338e-05, 'epoch': 0.84}

 84%|████████▍ | 2994/3566 [2:00:58<22:59,  2.41s/it]
 84%|████████▍ | 2995/3566 [2:01:00<22:57,  2.41s/it]
                                                     
{'loss': 1.505, 'learning_rate': 2.628357785030946e-05, 'epoch': 0.84}

 84%|████████▍ | 2995/3566 [2:01:00<22:57,  2.41s/it]
 84%|████████▍ | 2996/3566 [2:01:02<22:43,  2.39s/it]
                                                     
{'loss': 1.2686, 'learning_rate': 2.619381648222794e-05, 'epoch': 0.84}

 84%|████████▍ | 2996/3566 [2:01:02<22:43,  2.39s/it]
 84%|████████▍ | 2997/3566 [2:01:05<22:54,  2.42s/it]
                                                     
{'loss': 1.4693, 'learning_rate': 2.6104197907443718e-05, 'epoch': 0.84}

 84%|████████▍ | 2997/3566 [2:01:05<22:54,  2.42s/it]
 84%|████████▍ | 2998/3566 [2:01:08<23:48,  2.52s/it]
                                                     
{'loss': 1.5805, 'learning_rate': 2.601472219958441e-05, 'epoch': 0.84}

 84%|████████▍ | 2998/3566 [2:01:08<23:48,  2.52s/it]
 84%|████████▍ | 2999/3566 [2:01:10<23:22,  2.47s/it]
                                                     
{'loss': 1.593, 'learning_rate': 2.592538943216023e-05, 'epoch': 0.84}

 84%|████████▍ | 2999/3566 [2:01:10<23:22,  2.47s/it]
 84%|████████▍ | 3000/3566 [2:01:12<23:31,  2.49s/it]
                                                     
{'loss': 1.4186, 'learning_rate': 2.5836199678563965e-05, 'epoch': 0.84}

 84%|████████▍ | 3000/3566 [2:01:12<23:31,  2.49s/it]/home/aiops/duanky/miniconda3/envs/lora/lib/python3.11/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(

 84%|████████▍ | 3001/3566 [2:01:16<26:01,  2.76s/it]
                                                     
{'loss': 1.565, 'learning_rate': 2.5747153012070936e-05, 'epoch': 0.84}

 84%|████████▍ | 3001/3566 [2:01:16<26:01,  2.76s/it]
 84%|████████▍ | 3002/3566 [2:01:18<24:49,  2.64s/it]
                                                     
{'loss': 1.4785, 'learning_rate': 2.565824950583884e-05, 'epoch': 0.84}

 84%|████████▍ | 3002/3566 [2:01:18<24:49,  2.64s/it]
 84%|████████▍ | 3003/3566 [2:01:20<23:38,  2.52s/it]
                                                     
{'loss': 1.5113, 'learning_rate': 2.5569489232907805e-05, 'epoch': 0.84}

 84%|████████▍ | 3003/3566 [2:01:20<23:38,  2.52s/it]
 84%|████████▍ | 3004/3566 [2:01:23<22:21,  2.39s/it]
                                                     
{'loss': 1.4555, 'learning_rate': 2.5480872266200306e-05, 'epoch': 0.84}

 84%|████████▍ | 3004/3566 [2:01:23<22:21,  2.39s/it]
 84%|████████▍ | 3005/3566 [2:01:25<22:10,  2.37s/it]
                                                     
{'loss': 1.6278, 'learning_rate': 2.5392398678521034e-05, 'epoch': 0.84}

 84%|████████▍ | 3005/3566 [2:01:25<22:10,  2.37s/it]
 84%|████████▍ | 3006/3566 [2:01:27<21:15,  2.28s/it]
                                                     
{'loss': 1.573, 'learning_rate': 2.5304068542556935e-05, 'epoch': 0.84}

 84%|████████▍ | 3006/3566 [2:01:27<21:15,  2.28s/it]
 84%|████████▍ | 3007/3566 [2:01:29<21:11,  2.28s/it]
                                                     
{'loss': 1.4051, 'learning_rate': 2.5215881930877007e-05, 'epoch': 0.84}

 84%|████████▍ | 3007/3566 [2:01:29<21:11,  2.28s/it]
 84%|████████▍ | 3008/3566 [2:01:31<20:57,  2.25s/it]
                                                     
{'loss': 1.66, 'learning_rate': 2.512783891593242e-05, 'epoch': 0.84}

 84%|████████▍ | 3008/3566 [2:01:31<20:57,  2.25s/it]
 84%|████████▍ | 3009/3566 [2:01:34<21:03,  2.27s/it]
                                                     
{'loss': 1.4142, 'learning_rate': 2.503993957005637e-05, 'epoch': 0.84}

 84%|████████▍ | 3009/3566 [2:01:34<21:03,  2.27s/it]
 84%|████████▍ | 3010/3566 [2:01:36<20:46,  2.24s/it]
                                                     
{'loss': 1.483, 'learning_rate': 2.495218396546395e-05, 'epoch': 0.84}

 84%|████████▍ | 3010/3566 [2:01:36<20:46,  2.24s/it]
 84%|████████▍ | 3011/3566 [2:01:38<21:00,  2.27s/it]
                                                     
{'loss': 1.6582, 'learning_rate': 2.48645721742522e-05, 'epoch': 0.84}

 84%|████████▍ | 3011/3566 [2:01:38<21:00,  2.27s/it]
 84%|████████▍ | 3012/3566 [2:01:41<21:57,  2.38s/it]
                                                     
{'loss': 1.5771, 'learning_rate': 2.4777104268400097e-05, 'epoch': 0.84}

 84%|████████▍ | 3012/3566 [2:01:41<21:57,  2.38s/it]
 84%|████████▍ | 3013/3566 [2:01:43<21:48,  2.37s/it]
                                                     
{'loss': 1.4514, 'learning_rate': 2.4689780319768254e-05, 'epoch': 0.84}

 84%|████████▍ | 3013/3566 [2:01:43<21:48,  2.37s/it]
 85%|████████▍ | 3014/3566 [2:01:46<22:35,  2.46s/it]
                                                     
{'loss': 1.601, 'learning_rate': 2.460260040009914e-05, 'epoch': 0.85}

 85%|████████▍ | 3014/3566 [2:01:46<22:35,  2.46s/it]
 85%|████████▍ | 3015/3566 [2:01:48<22:17,  2.43s/it]
                                                     
{'loss': 1.5912, 'learning_rate': 2.451556458101676e-05, 'epoch': 0.85}

 85%|████████▍ | 3015/3566 [2:01:48<22:17,  2.43s/it]
 85%|████████▍ | 3016/3566 [2:01:51<22:06,  2.41s/it]
                                                     
{'loss': 1.4685, 'learning_rate': 2.442867293402684e-05, 'epoch': 0.85}

 85%|████████▍ | 3016/3566 [2:01:51<22:06,  2.41s/it]
 85%|████████▍ | 3017/3566 [2:01:53<21:28,  2.35s/it]
                                                     
{'loss': 1.4211, 'learning_rate': 2.434192553051662e-05, 'epoch': 0.85}

 85%|████████▍ | 3017/3566 [2:01:53<21:28,  2.35s/it]
 85%|████████▍ | 3018/3566 [2:01:55<21:29,  2.35s/it]
                                                     
{'loss': 1.4651, 'learning_rate': 2.4255322441754836e-05, 'epoch': 0.85}

 85%|████████▍ | 3018/3566 [2:01:55<21:29,  2.35s/it]
 85%|████████▍ | 3019/3566 [2:01:57<21:13,  2.33s/it]
                                                     
{'loss': 1.5291, 'learning_rate': 2.416886373889169e-05, 'epoch': 0.85}

 85%|████████▍ | 3019/3566 [2:01:57<21:13,  2.33s/it]
 85%|████████▍ | 3020/3566 [2:02:01<23:44,  2.61s/it]
                                                     
{'loss': 1.5784, 'learning_rate': 2.4082549492958717e-05, 'epoch': 0.85}

 85%|████████▍ | 3020/3566 [2:02:01<23:44,  2.61s/it]
 85%|████████▍ | 3021/3566 [2:02:03<22:26,  2.47s/it]
                                                     
{'loss': 1.4323, 'learning_rate': 2.399637977486877e-05, 'epoch': 0.85}

 85%|████████▍ | 3021/3566 [2:02:03<22:26,  2.47s/it]
 85%|████████▍ | 3022/3566 [2:02:05<22:26,  2.48s/it]
                                                     
{'loss': 1.5692, 'learning_rate': 2.3910354655416024e-05, 'epoch': 0.85}

 85%|████████▍ | 3022/3566 [2:02:05<22:26,  2.48s/it]
 85%|████████▍ | 3023/3566 [2:02:08<22:07,  2.44s/it]
                                                     
{'loss': 1.401, 'learning_rate': 2.3824474205275847e-05, 'epoch': 0.85}

 85%|████████▍ | 3023/3566 [2:02:08<22:07,  2.44s/it]
 85%|████████▍ | 3024/3566 [2:02:10<22:05,  2.45s/it]
                                                     
{'loss': 1.5544, 'learning_rate': 2.373873849500461e-05, 'epoch': 0.85}

 85%|████████▍ | 3024/3566 [2:02:10<22:05,  2.45s/it]
 85%|████████▍ | 3025/3566 [2:02:13<22:05,  2.45s/it]
                                                     
{'loss': 1.5991, 'learning_rate': 2.3653147595039914e-05, 'epoch': 0.85}

 85%|████████▍ | 3025/3566 [2:02:13<22:05,  2.45s/it]
 85%|████████▍ | 3026/3566 [2:02:15<21:30,  2.39s/it]
                                                     
{'loss': 1.354, 'learning_rate': 2.3567701575700407e-05, 'epoch': 0.85}

 85%|████████▍ | 3026/3566 [2:02:15<21:30,  2.39s/it]
 85%|████████▍ | 3027/3566 [2:02:17<21:45,  2.42s/it]
                                                     
{'loss': 1.365, 'learning_rate': 2.348240050718562e-05, 'epoch': 0.85}

 85%|████████▍ | 3027/3566 [2:02:17<21:45,  2.42s/it]
 85%|████████▍ | 3028/3566 [2:02:20<21:35,  2.41s/it]
                                                     
{'loss': 1.5945, 'learning_rate': 2.3397244459576073e-05, 'epoch': 0.85}

 85%|████████▍ | 3028/3566 [2:02:20<21:35,  2.41s/it]
 85%|████████▍ | 3029/3566 [2:02:22<21:22,  2.39s/it]
                                                     
{'loss': 1.5735, 'learning_rate': 2.3312233502833046e-05, 'epoch': 0.85}

 85%|████████▍ | 3029/3566 [2:02:22<21:22,  2.39s/it]
 85%|████████▍ | 3030/3566 [2:02:24<20:51,  2.34s/it]
                                                     
{'loss': 1.4846, 'learning_rate': 2.3227367706798718e-05, 'epoch': 0.85}

 85%|████████▍ | 3030/3566 [2:02:24<20:51,  2.34s/it]
 85%|████████▍ | 3031/3566 [2:02:27<21:29,  2.41s/it]
                                                     
{'loss': 1.5843, 'learning_rate': 2.3142647141195984e-05, 'epoch': 0.85}

 85%|████████▍ | 3031/3566 [2:02:27<21:29,  2.41s/it]
 85%|████████▌ | 3032/3566 [2:02:29<21:27,  2.41s/it]
                                                     
{'loss': 1.6677, 'learning_rate': 2.3058071875628318e-05, 'epoch': 0.85}

 85%|████████▌ | 3032/3566 [2:02:29<21:27,  2.41s/it]
 85%|████████▌ | 3033/3566 [2:02:32<21:48,  2.46s/it]
                                                     
{'loss': 1.5742, 'learning_rate': 2.297364197957994e-05, 'epoch': 0.85}

 85%|████████▌ | 3033/3566 [2:02:32<21:48,  2.46s/it]
 85%|████████▌ | 3034/3566 [2:02:34<22:04,  2.49s/it]
                                                     
{'loss': 1.6377, 'learning_rate': 2.2889357522415634e-05, 'epoch': 0.85}

 85%|████████▌ | 3034/3566 [2:02:34<22:04,  2.49s/it]
 85%|████████▌ | 3035/3566 [2:02:37<21:25,  2.42s/it]
                                                     
{'loss': 1.3794, 'learning_rate': 2.280521857338065e-05, 'epoch': 0.85}

 85%|████████▌ | 3035/3566 [2:02:37<21:25,  2.42s/it]
 85%|████████▌ | 3036/3566 [2:02:40<24:05,  2.73s/it]
                                                     
{'loss': 1.437, 'learning_rate': 2.2721225201600693e-05, 'epoch': 0.85}

 85%|████████▌ | 3036/3566 [2:02:40<24:05,  2.73s/it]
 85%|████████▌ | 3037/3566 [2:02:42<23:06,  2.62s/it]
                                                     
{'loss': 1.5489, 'learning_rate': 2.26373774760819e-05, 'epoch': 0.85}

 85%|████████▌ | 3037/3566 [2:02:42<23:06,  2.62s/it]
 85%|████████▌ | 3038/3566 [2:02:45<22:43,  2.58s/it]
                                                     
{'loss': 1.478, 'learning_rate': 2.2553675465710744e-05, 'epoch': 0.85}

 85%|████████▌ | 3038/3566 [2:02:45<22:43,  2.58s/it]
 85%|████████▌ | 3039/3566 [2:02:47<21:24,  2.44s/it]
                                                     
{'loss': 1.4078, 'learning_rate': 2.2470119239253972e-05, 'epoch': 0.85}

 85%|████████▌ | 3039/3566 [2:02:47<21:24,  2.44s/it]
 85%|████████▌ | 3040/3566 [2:02:49<21:22,  2.44s/it]
                                                     
{'loss': 1.4991, 'learning_rate': 2.238670886535854e-05, 'epoch': 0.85}

 85%|████████▌ | 3040/3566 [2:02:50<21:22,  2.44s/it]
 85%|████████▌ | 3041/3566 [2:02:52<21:11,  2.42s/it]
                                                     
{'loss': 1.5524, 'learning_rate': 2.230344441255161e-05, 'epoch': 0.85}

 85%|████████▌ | 3041/3566 [2:02:52<21:11,  2.42s/it]
 85%|████████▌ | 3042/3566 [2:02:54<20:56,  2.40s/it]
                                                     
{'loss': 1.5441, 'learning_rate': 2.2220325949240462e-05, 'epoch': 0.85}

 85%|████████▌ | 3042/3566 [2:02:54<20:56,  2.40s/it]
 85%|████████▌ | 3043/3566 [2:02:57<20:42,  2.38s/it]
                                                     
{'loss': 1.3048, 'learning_rate': 2.213735354371238e-05, 'epoch': 0.85}

 85%|████████▌ | 3043/3566 [2:02:57<20:42,  2.38s/it]
 85%|████████▌ | 3044/3566 [2:02:59<20:48,  2.39s/it]
                                                     
{'loss': 1.4664, 'learning_rate': 2.2054527264134727e-05, 'epoch': 0.85}

 85%|████████▌ | 3044/3566 [2:02:59<20:48,  2.39s/it]
 85%|████████▌ | 3045/3566 [2:03:02<22:19,  2.57s/it]
                                                     
{'loss': 1.5122, 'learning_rate': 2.1971847178554783e-05, 'epoch': 0.85}

 85%|████████▌ | 3045/3566 [2:03:02<22:19,  2.57s/it]
 85%|████████▌ | 3046/3566 [2:03:04<22:04,  2.55s/it]
                                                     
{'loss': 1.2752, 'learning_rate': 2.188931335489972e-05, 'epoch': 0.85}

 85%|████████▌ | 3046/3566 [2:03:04<22:04,  2.55s/it]
 85%|████████▌ | 3047/3566 [2:03:07<21:19,  2.47s/it]
                                                     
{'loss': 1.6498, 'learning_rate': 2.18069258609765e-05, 'epoch': 0.85}

 85%|████████▌ | 3047/3566 [2:03:07<21:19,  2.47s/it]
 85%|████████▌ | 3048/3566 [2:03:09<20:59,  2.43s/it]
                                                     
{'loss': 1.6345, 'learning_rate': 2.172468476447196e-05, 'epoch': 0.85}

 85%|████████▌ | 3048/3566 [2:03:09<20:59,  2.43s/it]
 86%|████████▌ | 3049/3566 [2:03:11<20:03,  2.33s/it]
                                                     
{'loss': 1.4348, 'learning_rate': 2.1642590132952644e-05, 'epoch': 0.86}

 86%|████████▌ | 3049/3566 [2:03:11<20:03,  2.33s/it]
 86%|████████▌ | 3050/3566 [2:03:14<20:11,  2.35s/it]
                                                     
{'loss': 1.4081, 'learning_rate': 2.1560642033864607e-05, 'epoch': 0.86}

 86%|████████▌ | 3050/3566 [2:03:14<20:11,  2.35s/it]
 86%|████████▌ | 3051/3566 [2:03:16<20:17,  2.36s/it]
                                                     
{'loss': 1.5559, 'learning_rate': 2.147884053453373e-05, 'epoch': 0.86}

 86%|████████▌ | 3051/3566 [2:03:16<20:17,  2.36s/it]
 86%|████████▌ | 3052/3566 [2:03:19<20:42,  2.42s/it]
                                                     
{'loss': 1.6582, 'learning_rate': 2.1397185702165358e-05, 'epoch': 0.86}

 86%|████████▌ | 3052/3566 [2:03:19<20:42,  2.42s/it]
 86%|████████▌ | 3053/3566 [2:03:21<20:39,  2.42s/it]
                                                     
{'loss': 1.4421, 'learning_rate': 2.1315677603844276e-05, 'epoch': 0.86}

 86%|████████▌ | 3053/3566 [2:03:21<20:39,  2.42s/it]
 86%|████████▌ | 3054/3566 [2:03:23<20:19,  2.38s/it]
                                                     
{'loss': 1.6913, 'learning_rate': 2.123431630653492e-05, 'epoch': 0.86}

 86%|████████▌ | 3054/3566 [2:03:23<20:19,  2.38s/it]
 86%|████████▌ | 3055/3566 [2:03:26<20:58,  2.46s/it]
                                                     
{'loss': 1.5518, 'learning_rate': 2.1153101877080884e-05, 'epoch': 0.86}

 86%|████████▌ | 3055/3566 [2:03:26<20:58,  2.46s/it]
 86%|████████▌ | 3056/3566 [2:03:28<20:09,  2.37s/it]
                                                     
{'loss': 1.5152, 'learning_rate': 2.1072034382205264e-05, 'epoch': 0.86}

 86%|████████▌ | 3056/3566 [2:03:28<20:09,  2.37s/it]
 86%|████████▌ | 3057/3566 [2:03:30<19:42,  2.32s/it]
                                                     
{'loss': 1.4277, 'learning_rate': 2.0991113888510384e-05, 'epoch': 0.86}

 86%|████████▌ | 3057/3566 [2:03:30<19:42,  2.32s/it]
 86%|████████▌ | 3058/3566 [2:03:33<20:28,  2.42s/it]
                                                     
{'loss': 1.5838, 'learning_rate': 2.0910340462477727e-05, 'epoch': 0.86}

 86%|████████▌ | 3058/3566 [2:03:33<20:28,  2.42s/it]
 86%|████████▌ | 3059/3566 [2:03:35<20:23,  2.41s/it]
                                                     
{'loss': 1.5948, 'learning_rate': 2.082971417046804e-05, 'epoch': 0.86}

 86%|████████▌ | 3059/3566 [2:03:35<20:23,  2.41s/it]
 86%|████████▌ | 3060/3566 [2:03:37<19:33,  2.32s/it]
                                                     
{'loss': 1.2582, 'learning_rate': 2.0749235078721176e-05, 'epoch': 0.86}

 86%|████████▌ | 3060/3566 [2:03:37<19:33,  2.32s/it]
 86%|████████▌ | 3061/3566 [2:03:40<20:20,  2.42s/it]
                                                     
{'loss': 1.4868, 'learning_rate': 2.066890325335602e-05, 'epoch': 0.86}

 86%|████████▌ | 3061/3566 [2:03:40<20:20,  2.42s/it]
 86%|████████▌ | 3062/3566 [2:03:42<19:59,  2.38s/it]
                                                     
{'loss': 1.5304, 'learning_rate': 2.058871876037054e-05, 'epoch': 0.86}

 86%|████████▌ | 3062/3566 [2:03:42<19:59,  2.38s/it]
 86%|████████▌ | 3063/3566 [2:03:45<20:14,  2.41s/it]
                                                     
{'loss': 1.5917, 'learning_rate': 2.050868166564157e-05, 'epoch': 0.86}

 86%|████████▌ | 3063/3566 [2:03:45<20:14,  2.41s/it]
 86%|████████▌ | 3064/3566 [2:03:47<19:56,  2.38s/it]
                                                     
{'loss': 1.5686, 'learning_rate': 2.0428792034924894e-05, 'epoch': 0.86}

 86%|████████▌ | 3064/3566 [2:03:47<19:56,  2.38s/it]
 86%|████████▌ | 3065/3566 [2:03:50<20:47,  2.49s/it]
                                                     
{'loss': 1.651, 'learning_rate': 2.0349049933855134e-05, 'epoch': 0.86}

 86%|████████▌ | 3065/3566 [2:03:50<20:47,  2.49s/it]
 86%|████████▌ | 3066/3566 [2:03:52<20:12,  2.42s/it]
                                                     
{'loss': 1.505, 'learning_rate': 2.026945542794576e-05, 'epoch': 0.86}

 86%|████████▌ | 3066/3566 [2:03:52<20:12,  2.42s/it]
 86%|████████▌ | 3067/3566 [2:03:54<19:41,  2.37s/it]
                                                     
{'loss': 1.4168, 'learning_rate': 2.0190008582588814e-05, 'epoch': 0.86}

 86%|████████▌ | 3067/3566 [2:03:54<19:41,  2.37s/it]
 86%|████████▌ | 3068/3566 [2:03:57<19:45,  2.38s/it]
                                                     
{'loss': 1.3979, 'learning_rate': 2.0110709463055245e-05, 'epoch': 0.86}

 86%|████████▌ | 3068/3566 [2:03:57<19:45,  2.38s/it]
 86%|████████▌ | 3069/3566 [2:03:59<19:36,  2.37s/it]
                                                     
{'loss': 1.5507, 'learning_rate': 2.0031558134494532e-05, 'epoch': 0.86}

 86%|████████▌ | 3069/3566 [2:03:59<19:36,  2.37s/it]
 86%|████████▌ | 3070/3566 [2:04:03<22:10,  2.68s/it]
                                                     
{'loss': 1.4588, 'learning_rate': 1.9952554661934707e-05, 'epoch': 0.86}

 86%|████████▌ | 3070/3566 [2:04:03<22:10,  2.68s/it]
 86%|████████▌ | 3071/3566 [2:04:05<21:19,  2.59s/it]
                                                     
{'loss': 1.3466, 'learning_rate': 1.987369911028236e-05, 'epoch': 0.86}

 86%|████████▌ | 3071/3566 [2:04:05<21:19,  2.59s/it]
 86%|████████▌ | 3072/3566 [2:04:07<20:59,  2.55s/it]
                                                     
{'loss': 1.4798, 'learning_rate': 1.979499154432256e-05, 'epoch': 0.86}

 86%|████████▌ | 3072/3566 [2:04:07<20:59,  2.55s/it]
 86%|████████▌ | 3073/3566 [2:04:10<20:50,  2.54s/it]
                                                     
{'loss': 1.5032, 'learning_rate': 1.9716432028718778e-05, 'epoch': 0.86}

 86%|████████▌ | 3073/3566 [2:04:10<20:50,  2.54s/it]
 86%|████████▌ | 3074/3566 [2:04:13<21:10,  2.58s/it]
                                                     
{'loss': 1.4521, 'learning_rate': 1.963802062801292e-05, 'epoch': 0.86}

 86%|████████▌ | 3074/3566 [2:04:13<21:10,  2.58s/it]
 86%|████████▌ | 3075/3566 [2:04:15<20:30,  2.51s/it]
                                                     
{'loss': 1.5781, 'learning_rate': 1.9559757406625035e-05, 'epoch': 0.86}

 86%|████████▌ | 3075/3566 [2:04:15<20:30,  2.51s/it]
 86%|████████▋ | 3076/3566 [2:04:17<20:16,  2.48s/it]
                                                     
{'loss': 1.5631, 'learning_rate': 1.948164242885364e-05, 'epoch': 0.86}

 86%|████████▋ | 3076/3566 [2:04:17<20:16,  2.48s/it]
 86%|████████▋ | 3077/3566 [2:04:20<19:51,  2.44s/it]
                                                     
{'loss': 1.4027, 'learning_rate': 1.9403675758875317e-05, 'epoch': 0.86}

 86%|████████▋ | 3077/3566 [2:04:20<19:51,  2.44s/it]
 86%|████████▋ | 3078/3566 [2:04:22<19:36,  2.41s/it]
                                                     
{'loss': 1.5275, 'learning_rate': 1.9325857460744866e-05, 'epoch': 0.86}

 86%|████████▋ | 3078/3566 [2:04:22<19:36,  2.41s/it]
 86%|████████▋ | 3079/3566 [2:04:24<19:08,  2.36s/it]
                                                     
{'loss': 1.5799, 'learning_rate': 1.9248187598395175e-05, 'epoch': 0.86}

 86%|████████▋ | 3079/3566 [2:04:24<19:08,  2.36s/it]
 86%|████████▋ | 3080/3566 [2:04:26<18:45,  2.32s/it]
                                                     
{'loss': 1.5143, 'learning_rate': 1.9170666235637193e-05, 'epoch': 0.86}

 86%|████████▋ | 3080/3566 [2:04:26<18:45,  2.32s/it]
 86%|████████▋ | 3081/3566 [2:04:29<18:39,  2.31s/it]
                                                     
{'loss': 1.4743, 'learning_rate': 1.90932934361598e-05, 'epoch': 0.86}

 86%|████████▋ | 3081/3566 [2:04:29<18:39,  2.31s/it]
 86%|████████▋ | 3082/3566 [2:04:31<19:22,  2.40s/it]
                                                     
{'loss': 1.4548, 'learning_rate': 1.9016069263530013e-05, 'epoch': 0.86}

 86%|████████▋ | 3082/3566 [2:04:31<19:22,  2.40s/it]
 86%|████████▋ | 3083/3566 [2:04:34<19:20,  2.40s/it]
                                                     
{'loss': 1.5033, 'learning_rate': 1.8938993781192484e-05, 'epoch': 0.86}

 86%|████████▋ | 3083/3566 [2:04:34<19:20,  2.40s/it]
 86%|████████▋ | 3084/3566 [2:04:36<19:52,  2.47s/it]
                                                     
{'loss': 1.5316, 'learning_rate': 1.8862067052469866e-05, 'epoch': 0.86}

 86%|████████▋ | 3084/3566 [2:04:36<19:52,  2.47s/it]
 87%|████████▋ | 3085/3566 [2:04:39<19:53,  2.48s/it]
                                                     
{'loss': 1.6469, 'learning_rate': 1.8785289140562567e-05, 'epoch': 0.87}

 87%|████████▋ | 3085/3566 [2:04:39<19:53,  2.48s/it]
 87%|████████▋ | 3086/3566 [2:04:41<19:14,  2.40s/it]
                                                     
{'loss': 1.5238, 'learning_rate': 1.8708660108548726e-05, 'epoch': 0.87}

 87%|████████▋ | 3086/3566 [2:04:41<19:14,  2.40s/it]
 87%|████████▋ | 3087/3566 [2:04:44<19:32,  2.45s/it]
                                                     
{'loss': 1.5827, 'learning_rate': 1.863218001938416e-05, 'epoch': 0.87}

 87%|████████▋ | 3087/3566 [2:04:44<19:32,  2.45s/it]
 87%|████████▋ | 3088/3566 [2:04:46<19:14,  2.42s/it]
                                                     
{'loss': 1.4911, 'learning_rate': 1.8555848935902364e-05, 'epoch': 0.87}

 87%|████████▋ | 3088/3566 [2:04:46<19:14,  2.42s/it]
 87%|████████▋ | 3089/3566 [2:04:49<19:27,  2.45s/it]
                                                     
{'loss': 1.6104, 'learning_rate': 1.8479666920814354e-05, 'epoch': 0.87}

 87%|████████▋ | 3089/3566 [2:04:49<19:27,  2.45s/it]
 87%|████████▋ | 3090/3566 [2:04:51<19:16,  2.43s/it]
                                                     
{'loss': 1.6973, 'learning_rate': 1.8403634036708705e-05, 'epoch': 0.87}

 87%|████████▋ | 3090/3566 [2:04:51<19:16,  2.43s/it]
 87%|████████▋ | 3091/3566 [2:04:53<19:27,  2.46s/it]
                                                     
{'loss': 1.5458, 'learning_rate': 1.8327750346051476e-05, 'epoch': 0.87}

 87%|████████▋ | 3091/3566 [2:04:53<19:27,  2.46s/it]
 87%|████████▋ | 3092/3566 [2:04:56<20:44,  2.63s/it]
                                                     
{'loss': 1.5847, 'learning_rate': 1.825201591118617e-05, 'epoch': 0.87}

 87%|████████▋ | 3092/3566 [2:04:56<20:44,  2.63s/it]
 87%|████████▋ | 3093/3566 [2:04:59<20:01,  2.54s/it]
                                                     
{'loss': 1.5903, 'learning_rate': 1.81764307943336e-05, 'epoch': 0.87}

 87%|████████▋ | 3093/3566 [2:04:59<20:01,  2.54s/it]
 87%|████████▋ | 3094/3566 [2:05:01<19:11,  2.44s/it]
                                                     
{'loss': 1.4493, 'learning_rate': 1.8100995057591953e-05, 'epoch': 0.87}

 87%|████████▋ | 3094/3566 [2:05:01<19:11,  2.44s/it]
 87%|████████▋ | 3095/3566 [2:05:03<19:12,  2.45s/it]
                                                     
{'loss': 1.4984, 'learning_rate': 1.8025708762936722e-05, 'epoch': 0.87}

 87%|████████▋ | 3095/3566 [2:05:03<19:12,  2.45s/it]
 87%|████████▋ | 3096/3566 [2:05:06<18:46,  2.40s/it]
                                                     
{'loss': 1.4328, 'learning_rate': 1.7950571972220498e-05, 'epoch': 0.87}

 87%|████████▋ | 3096/3566 [2:05:06<18:46,  2.40s/it]
 87%|████████▋ | 3097/3566 [2:05:08<18:31,  2.37s/it]
                                                     
{'loss': 1.3343, 'learning_rate': 1.7875584747173257e-05, 'epoch': 0.87}

 87%|████████▋ | 3097/3566 [2:05:08<18:31,  2.37s/it]
 87%|████████▋ | 3098/3566 [2:05:11<18:45,  2.40s/it]
                                                     
{'loss': 1.5043, 'learning_rate': 1.780074714940192e-05, 'epoch': 0.87}

 87%|████████▋ | 3098/3566 [2:05:11<18:45,  2.40s/it]
 87%|████████▋ | 3099/3566 [2:05:15<23:51,  3.06s/it]
                                                     
{'loss': 1.3565, 'learning_rate': 1.7726059240390526e-05, 'epoch': 0.87}

 87%|████████▋ | 3099/3566 [2:05:15<23:51,  3.06s/it]
 87%|████████▋ | 3100/3566 [2:05:17<21:37,  2.78s/it]
                                                     
{'loss': 1.5053, 'learning_rate': 1.7651521081500188e-05, 'epoch': 0.87}

 87%|████████▋ | 3100/3566 [2:05:17<21:37,  2.78s/it]
 87%|████████▋ | 3101/3566 [2:05:20<20:33,  2.65s/it]
                                                     
{'loss': 1.4689, 'learning_rate': 1.757713273396886e-05, 'epoch': 0.87}

 87%|████████▋ | 3101/3566 [2:05:20<20:33,  2.65s/it]
 87%|████████▋ | 3102/3566 [2:05:22<19:43,  2.55s/it]
                                                     
{'loss': 1.5751, 'learning_rate': 1.750289425891154e-05, 'epoch': 0.87}

 87%|████████▋ | 3102/3566 [2:05:22<19:43,  2.55s/it]
 87%|████████▋ | 3103/3566 [2:05:24<18:32,  2.40s/it]
                                                     
{'loss': 1.4489, 'learning_rate': 1.742880571732004e-05, 'epoch': 0.87}

 87%|████████▋ | 3103/3566 [2:05:24<18:32,  2.40s/it]
 87%|████████▋ | 3104/3566 [2:05:26<18:11,  2.36s/it]
                                                     
{'loss': 1.2822, 'learning_rate': 1.735486717006305e-05, 'epoch': 0.87}

 87%|████████▋ | 3104/3566 [2:05:26<18:11,  2.36s/it]
 87%|████████▋ | 3105/3566 [2:05:29<19:04,  2.48s/it]
                                                     
{'loss': 1.4984, 'learning_rate': 1.7281078677885932e-05, 'epoch': 0.87}

 87%|████████▋ | 3105/3566 [2:05:29<19:04,  2.48s/it]
 87%|████████▋ | 3106/3566 [2:05:31<18:43,  2.44s/it]
                                                     
{'loss': 1.5215, 'learning_rate': 1.720744030141086e-05, 'epoch': 0.87}

 87%|████████▋ | 3106/3566 [2:05:31<18:43,  2.44s/it]
 87%|████████▋ | 3107/3566 [2:05:34<18:55,  2.47s/it]
                                                     
{'loss': 1.5953, 'learning_rate': 1.713395210113664e-05, 'epoch': 0.87}

 87%|████████▋ | 3107/3566 [2:05:34<18:55,  2.47s/it]
 87%|████████▋ | 3108/3566 [2:05:36<18:49,  2.47s/it]
                                                     
{'loss': 1.5102, 'learning_rate': 1.7060614137438667e-05, 'epoch': 0.87}

 87%|████████▋ | 3108/3566 [2:05:36<18:49,  2.47s/it]
 87%|████████▋ | 3109/3566 [2:05:39<18:28,  2.43s/it]
                                                     
{'loss': 1.5496, 'learning_rate': 1.6987426470568992e-05, 'epoch': 0.87}

 87%|████████▋ | 3109/3566 [2:05:39<18:28,  2.43s/it]
 87%|████████▋ | 3110/3566 [2:05:42<19:18,  2.54s/it]
                                                     
{'loss': 1.582, 'learning_rate': 1.691438916065604e-05, 'epoch': 0.87}

 87%|████████▋ | 3110/3566 [2:05:42<19:18,  2.54s/it]
 87%|████████▋ | 3111/3566 [2:05:44<18:49,  2.48s/it]
                                                     
{'loss': 1.4474, 'learning_rate': 1.6841502267704868e-05, 'epoch': 0.87}

 87%|████████▋ | 3111/3566 [2:05:44<18:49,  2.48s/it]
 87%|████████▋ | 3112/3566 [2:05:46<19:04,  2.52s/it]
                                                     
{'loss': 1.5635, 'learning_rate': 1.6768765851596902e-05, 'epoch': 0.87}

 87%|████████▋ | 3112/3566 [2:05:46<19:04,  2.52s/it]
 87%|████████▋ | 3113/3566 [2:05:49<18:14,  2.42s/it]
                                                     
{'loss': 1.4487, 'learning_rate': 1.6696179972089898e-05, 'epoch': 0.87}

 87%|████████▋ | 3113/3566 [2:05:49<18:14,  2.42s/it]
 87%|████████▋ | 3114/3566 [2:05:51<18:53,  2.51s/it]
                                                     
{'loss': 1.664, 'learning_rate': 1.6623744688818e-05, 'epoch': 0.87}

 87%|████████▋ | 3114/3566 [2:05:51<18:53,  2.51s/it]
 87%|████████▋ | 3115/3566 [2:05:54<18:15,  2.43s/it]
                                                     
{'loss': 1.4614, 'learning_rate': 1.6551460061291534e-05, 'epoch': 0.87}

 87%|████████▋ | 3115/3566 [2:05:54<18:15,  2.43s/it]
 87%|████████▋ | 3116/3566 [2:05:56<18:06,  2.41s/it]
                                                     
{'loss': 1.4789, 'learning_rate': 1.6479326148897155e-05, 'epoch': 0.87}

 87%|████████▋ | 3116/3566 [2:05:56<18:06,  2.41s/it]
 87%|████████▋ | 3117/3566 [2:05:58<17:46,  2.37s/it]
                                                     
{'loss': 1.3286, 'learning_rate': 1.640734301089768e-05, 'epoch': 0.87}

 87%|████████▋ | 3117/3566 [2:05:58<17:46,  2.37s/it]
 87%|████████▋ | 3118/3566 [2:06:01<17:30,  2.34s/it]
                                                     
{'loss': 1.4432, 'learning_rate': 1.6335510706431957e-05, 'epoch': 0.87}

 87%|████████▋ | 3118/3566 [2:06:01<17:30,  2.34s/it]
 87%|████████▋ | 3119/3566 [2:06:03<17:06,  2.30s/it]
                                                     
{'loss': 1.5637, 'learning_rate': 1.6263829294515e-05, 'epoch': 0.87}

 87%|████████▋ | 3119/3566 [2:06:03<17:06,  2.30s/it]
 87%|████████▋ | 3120/3566 [2:06:05<16:44,  2.25s/it]
                                                     
{'loss': 1.3861, 'learning_rate': 1.6192298834037855e-05, 'epoch': 0.87}

 87%|████████▋ | 3120/3566 [2:06:05<16:44,  2.25s/it]
 88%|████████▊ | 3121/3566 [2:06:07<16:29,  2.22s/it]
                                                     
{'loss': 1.3861, 'learning_rate': 1.612091938376754e-05, 'epoch': 0.88}

 88%|████████▊ | 3121/3566 [2:06:07<16:29,  2.22s/it]
 88%|████████▊ | 3122/3566 [2:06:09<16:37,  2.25s/it]
                                                     
{'loss': 1.4166, 'learning_rate': 1.604969100234701e-05, 'epoch': 0.88}

 88%|████████▊ | 3122/3566 [2:06:09<16:37,  2.25s/it]
 88%|████████▊ | 3123/3566 [2:06:12<18:00,  2.44s/it]
                                                     
{'loss': 1.5924, 'learning_rate': 1.597861374829508e-05, 'epoch': 0.88}

 88%|████████▊ | 3123/3566 [2:06:12<18:00,  2.44s/it]
 88%|████████▊ | 3124/3566 [2:06:15<18:12,  2.47s/it]
                                                     
{'loss': 1.3881, 'learning_rate': 1.590768768000639e-05, 'epoch': 0.88}

 88%|████████▊ | 3124/3566 [2:06:15<18:12,  2.47s/it]
 88%|████████▊ | 3125/3566 [2:06:17<18:16,  2.49s/it]
                                                     
{'loss': 1.4583, 'learning_rate': 1.583691285575153e-05, 'epoch': 0.88}

 88%|████████▊ | 3125/3566 [2:06:17<18:16,  2.49s/it]
 88%|████████▊ | 3126/3566 [2:06:20<17:58,  2.45s/it]
                                                     
{'loss': 1.6022, 'learning_rate': 1.5766289333676587e-05, 'epoch': 0.88}

 88%|████████▊ | 3126/3566 [2:06:20<17:58,  2.45s/it]
 88%|████████▊ | 3127/3566 [2:06:22<17:32,  2.40s/it]
                                                     
{'loss': 1.3567, 'learning_rate': 1.5695817171803506e-05, 'epoch': 0.88}

 88%|████████▊ | 3127/3566 [2:06:22<17:32,  2.40s/it]
 88%|████████▊ | 3128/3566 [2:06:24<17:21,  2.38s/it]
                                                     
{'loss': 1.6229, 'learning_rate': 1.562549642802984e-05, 'epoch': 0.88}

 88%|████████▊ | 3128/3566 [2:06:24<17:21,  2.38s/it]
 88%|████████▊ | 3129/3566 [2:06:27<17:01,  2.34s/it]
                                                     
{'loss': 1.3261, 'learning_rate': 1.555532716012873e-05, 'epoch': 0.88}

 88%|████████▊ | 3129/3566 [2:06:27<17:01,  2.34s/it]
 88%|████████▊ | 3130/3566 [2:06:29<16:57,  2.33s/it]
                                                     
{'loss': 1.5368, 'learning_rate': 1.5485309425748883e-05, 'epoch': 0.88}

 88%|████████▊ | 3130/3566 [2:06:29<16:57,  2.33s/it]
 88%|████████▊ | 3131/3566 [2:06:31<17:18,  2.39s/it]
                                                     
{'loss': 1.3636, 'learning_rate': 1.541544328241451e-05, 'epoch': 0.88}

 88%|████████▊ | 3131/3566 [2:06:31<17:18,  2.39s/it]
 88%|████████▊ | 3132/3566 [2:06:34<17:31,  2.42s/it]
                                                     
{'loss': 1.5518, 'learning_rate': 1.5345728787525272e-05, 'epoch': 0.88}

 88%|████████▊ | 3132/3566 [2:06:34<17:31,  2.42s/it]
 88%|████████▊ | 3133/3566 [2:06:36<17:06,  2.37s/it]
                                                     
{'loss': 1.5042, 'learning_rate': 1.5276165998356263e-05, 'epoch': 0.88}

 88%|████████▊ | 3133/3566 [2:06:36<17:06,  2.37s/it]
 88%|████████▊ | 3134/3566 [2:06:39<17:35,  2.44s/it]
                                                     
{'loss': 1.6386, 'learning_rate': 1.5206754972057901e-05, 'epoch': 0.88}

 88%|████████▊ | 3134/3566 [2:06:39<17:35,  2.44s/it]
 88%|████████▊ | 3135/3566 [2:06:41<18:05,  2.52s/it]
                                                     
{'loss': 1.6081, 'learning_rate': 1.5137495765656019e-05, 'epoch': 0.88}

 88%|████████▊ | 3135/3566 [2:06:41<18:05,  2.52s/it]
 88%|████████▊ | 3136/3566 [2:06:44<17:47,  2.48s/it]
                                                     
{'loss': 1.4396, 'learning_rate': 1.5068388436051518e-05, 'epoch': 0.88}

 88%|████████▊ | 3136/3566 [2:06:44<17:47,  2.48s/it]
 88%|████████▊ | 3137/3566 [2:06:46<17:52,  2.50s/it]
                                                     
{'loss': 1.6211, 'learning_rate': 1.4999433040020715e-05, 'epoch': 0.88}

 88%|████████▊ | 3137/3566 [2:06:46<17:52,  2.50s/it]
 88%|████████▊ | 3138/3566 [2:06:49<17:21,  2.43s/it]
                                                     
{'loss': 1.5851, 'learning_rate': 1.493062963421501e-05, 'epoch': 0.88}

 88%|████████▊ | 3138/3566 [2:06:49<17:21,  2.43s/it]
 88%|████████▊ | 3139/3566 [2:06:51<17:11,  2.42s/it]
                                                     
{'loss': 1.5891, 'learning_rate': 1.4861978275161003e-05, 'epoch': 0.88}

 88%|████████▊ | 3139/3566 [2:06:51<17:11,  2.42s/it]
 88%|████████▊ | 3140/3566 [2:06:53<16:36,  2.34s/it]
                                                     
{'loss': 1.404, 'learning_rate': 1.4793479019260315e-05, 'epoch': 0.88}

 88%|████████▊ | 3140/3566 [2:06:53<16:36,  2.34s/it]
 88%|████████▊ | 3141/3566 [2:06:55<16:28,  2.33s/it]
                                                     
{'loss': 1.6932, 'learning_rate': 1.4725131922789637e-05, 'epoch': 0.88}

 88%|████████▊ | 3141/3566 [2:06:55<16:28,  2.33s/it]
 88%|████████▊ | 3142/3566 [2:06:58<16:54,  2.39s/it]
                                                     
{'loss': 1.5689, 'learning_rate': 1.4656937041900631e-05, 'epoch': 0.88}

 88%|████████▊ | 3142/3566 [2:06:58<16:54,  2.39s/it]
 88%|████████▊ | 3143/3566 [2:07:01<17:26,  2.47s/it]
                                                     
{'loss': 1.465, 'learning_rate': 1.4588894432619927e-05, 'epoch': 0.88}

 88%|████████▊ | 3143/3566 [2:07:01<17:26,  2.47s/it]
 88%|████████▊ | 3144/3566 [2:07:03<17:00,  2.42s/it]
                                                     
{'loss': 1.6221, 'learning_rate': 1.4521004150848983e-05, 'epoch': 0.88}

 88%|████████▊ | 3144/3566 [2:07:03<17:00,  2.42s/it]
 88%|████████▊ | 3145/3566 [2:07:06<17:19,  2.47s/it]
                                                     
{'loss': 1.4774, 'learning_rate': 1.4453266252364207e-05, 'epoch': 0.88}

 88%|████████▊ | 3145/3566 [2:07:06<17:19,  2.47s/it]
 88%|████████▊ | 3146/3566 [2:07:08<17:34,  2.51s/it]
                                                     
{'loss': 1.7321, 'learning_rate': 1.4385680792816747e-05, 'epoch': 0.88}

 88%|████████▊ | 3146/3566 [2:07:08<17:34,  2.51s/it]
 88%|████████▊ | 3147/3566 [2:07:11<17:19,  2.48s/it]
                                                     
{'loss': 1.4188, 'learning_rate': 1.4318247827732568e-05, 'epoch': 0.88}

 88%|████████▊ | 3147/3566 [2:07:11<17:19,  2.48s/it]
 88%|████████▊ | 3148/3566 [2:07:13<17:30,  2.51s/it]
                                                     
{'loss': 1.5599, 'learning_rate': 1.4250967412512283e-05, 'epoch': 0.88}

 88%|████████▊ | 3148/3566 [2:07:13<17:30,  2.51s/it]
 88%|████████▊ | 3149/3566 [2:07:16<17:16,  2.48s/it]
                                                     
{'loss': 1.2599, 'learning_rate': 1.418383960243126e-05, 'epoch': 0.88}

 88%|████████▊ | 3149/3566 [2:07:16<17:16,  2.48s/it]
 88%|████████▊ | 3150/3566 [2:07:18<16:40,  2.40s/it]
                                                     
{'loss': 1.5307, 'learning_rate': 1.4116864452639377e-05, 'epoch': 0.88}

 88%|████████▊ | 3150/3566 [2:07:18<16:40,  2.40s/it]
 88%|████████▊ | 3151/3566 [2:07:20<16:44,  2.42s/it]
                                                     
{'loss': 1.5446, 'learning_rate': 1.4050042018161224e-05, 'epoch': 0.88}

 88%|████████▊ | 3151/3566 [2:07:20<16:44,  2.42s/it]
 88%|████████▊ | 3152/3566 [2:07:23<16:28,  2.39s/it]
                                                     
{'loss': 1.5337, 'learning_rate': 1.3983372353895818e-05, 'epoch': 0.88}

 88%|████████▊ | 3152/3566 [2:07:23<16:28,  2.39s/it]
 88%|████████▊ | 3153/3566 [2:07:25<16:20,  2.37s/it]
                                                     
{'loss': 1.5386, 'learning_rate': 1.3916855514616723e-05, 'epoch': 0.88}

 88%|████████▊ | 3153/3566 [2:07:25<16:20,  2.37s/it]
 88%|████████▊ | 3154/3566 [2:07:27<16:15,  2.37s/it]
                                                     
{'loss': 1.4712, 'learning_rate': 1.3850491554971934e-05, 'epoch': 0.88}

 88%|████████▊ | 3154/3566 [2:07:27<16:15,  2.37s/it]
 88%|████████▊ | 3155/3566 [2:07:30<16:01,  2.34s/it]
                                                     
{'loss': 1.3755, 'learning_rate': 1.3784280529483817e-05, 'epoch': 0.88}

 88%|████████▊ | 3155/3566 [2:07:30<16:01,  2.34s/it]
 89%|████████▊ | 3156/3566 [2:07:32<16:08,  2.36s/it]
                                                     
{'loss': 1.4053, 'learning_rate': 1.371822249254915e-05, 'epoch': 0.89}

 89%|████████▊ | 3156/3566 [2:07:32<16:08,  2.36s/it]
 89%|████████▊ | 3157/3566 [2:07:35<16:31,  2.43s/it]
                                                     
{'loss': 1.6371, 'learning_rate': 1.365231749843896e-05, 'epoch': 0.89}

 89%|████████▊ | 3157/3566 [2:07:35<16:31,  2.43s/it]
 89%|████████▊ | 3158/3566 [2:07:37<16:25,  2.42s/it]
                                                     
{'loss': 1.5657, 'learning_rate': 1.3586565601298585e-05, 'epoch': 0.89}

 89%|████████▊ | 3158/3566 [2:07:37<16:25,  2.42s/it]
 89%|████████▊ | 3159/3566 [2:07:39<16:15,  2.40s/it]
                                                     
{'loss': 1.4533, 'learning_rate': 1.3520966855147543e-05, 'epoch': 0.89}

 89%|████████▊ | 3159/3566 [2:07:39<16:15,  2.40s/it]
 89%|████████▊ | 3160/3566 [2:07:42<15:56,  2.36s/it]
                                                     
{'loss': 1.5085, 'learning_rate': 1.3455521313879615e-05, 'epoch': 0.89}

 89%|████████▊ | 3160/3566 [2:07:42<15:56,  2.36s/it]
 89%|████████▊ | 3161/3566 [2:07:44<15:17,  2.27s/it]
                                                     
{'loss': 1.343, 'learning_rate': 1.3390229031262568e-05, 'epoch': 0.89}

 89%|████████▊ | 3161/3566 [2:07:44<15:17,  2.27s/it]
 89%|████████▊ | 3162/3566 [2:07:46<15:33,  2.31s/it]
                                                     
{'loss': 1.5923, 'learning_rate': 1.332509006093836e-05, 'epoch': 0.89}

 89%|████████▊ | 3162/3566 [2:07:46<15:33,  2.31s/it]
 89%|████████▊ | 3163/3566 [2:07:49<16:06,  2.40s/it]
                                                     
{'loss': 1.5959, 'learning_rate': 1.3260104456423005e-05, 'epoch': 0.89}

 89%|████████▊ | 3163/3566 [2:07:49<16:06,  2.40s/it]
 89%|████████▊ | 3164/3566 [2:07:51<16:15,  2.43s/it]
                                                     
{'loss': 1.5922, 'learning_rate': 1.319527227110644e-05, 'epoch': 0.89}

 89%|████████▊ | 3164/3566 [2:07:51<16:15,  2.43s/it]
 89%|████████▉ | 3165/3566 [2:07:53<15:54,  2.38s/it]
                                                     
{'loss': 1.5603, 'learning_rate': 1.3130593558252636e-05, 'epoch': 0.89}

 89%|████████▉ | 3165/3566 [2:07:53<15:54,  2.38s/it]
 89%|████████▉ | 3166/3566 [2:07:56<15:47,  2.37s/it]
                                                     
{'loss': 1.5838, 'learning_rate': 1.3066068370999395e-05, 'epoch': 0.89}

 89%|████████▉ | 3166/3566 [2:07:56<15:47,  2.37s/it]
 89%|████████▉ | 3167/3566 [2:07:59<17:02,  2.56s/it]
                                                     
{'loss': 1.3399, 'learning_rate': 1.3001696762358518e-05, 'epoch': 0.89}

 89%|████████▉ | 3167/3566 [2:07:59<17:02,  2.56s/it]
 89%|████████▉ | 3168/3566 [2:08:01<17:08,  2.58s/it]
                                                     
{'loss': 1.5241, 'learning_rate': 1.2937478785215518e-05, 'epoch': 0.89}

 89%|████████▉ | 3168/3566 [2:08:01<17:08,  2.58s/it]
 89%|████████▉ | 3169/3566 [2:08:04<16:31,  2.50s/it]
                                                     
{'loss': 1.4202, 'learning_rate': 1.287341449232966e-05, 'epoch': 0.89}

 89%|████████▉ | 3169/3566 [2:08:04<16:31,  2.50s/it]
 89%|████████▉ | 3170/3566 [2:08:06<16:15,  2.46s/it]
                                                     
{'loss': 1.5595, 'learning_rate': 1.2809503936334043e-05, 'epoch': 0.89}

 89%|████████▉ | 3170/3566 [2:08:06<16:15,  2.46s/it]
 89%|████████▉ | 3171/3566 [2:08:09<16:21,  2.48s/it]
                                                     
{'loss': 1.5936, 'learning_rate': 1.2745747169735444e-05, 'epoch': 0.89}

 89%|████████▉ | 3171/3566 [2:08:09<16:21,  2.48s/it]
 89%|████████▉ | 3172/3566 [2:08:11<15:54,  2.42s/it]
                                                     
{'loss': 1.3427, 'learning_rate': 1.2682144244914251e-05, 'epoch': 0.89}

 89%|████████▉ | 3172/3566 [2:08:11<15:54,  2.42s/it]
 89%|████████▉ | 3173/3566 [2:08:13<15:51,  2.42s/it]
                                                     
{'loss': 1.2929, 'learning_rate': 1.2618695214124465e-05, 'epoch': 0.89}

 89%|████████▉ | 3173/3566 [2:08:13<15:51,  2.42s/it]
 89%|████████▉ | 3174/3566 [2:08:16<16:13,  2.48s/it]
                                                     
{'loss': 1.5191, 'learning_rate': 1.2555400129493699e-05, 'epoch': 0.89}

 89%|████████▉ | 3174/3566 [2:08:16<16:13,  2.48s/it]
 89%|████████▉ | 3175/3566 [2:08:19<16:50,  2.59s/it]
                                                     
{'loss': 1.536, 'learning_rate': 1.2492259043023046e-05, 'epoch': 0.89}

 89%|████████▉ | 3175/3566 [2:08:19<16:50,  2.59s/it]
 89%|████████▉ | 3176/3566 [2:08:21<16:31,  2.54s/it]
                                                     
{'loss': 1.4688, 'learning_rate': 1.24292720065871e-05, 'epoch': 0.89}

 89%|████████▉ | 3176/3566 [2:08:21<16:31,  2.54s/it]
 89%|████████▉ | 3177/3566 [2:08:23<16:02,  2.47s/it]
                                                     
{'loss': 1.58, 'learning_rate': 1.236643907193389e-05, 'epoch': 0.89}

 89%|████████▉ | 3177/3566 [2:08:23<16:02,  2.47s/it]
 89%|████████▉ | 3178/3566 [2:08:26<16:02,  2.48s/it]
                                                     
{'loss': 1.5167, 'learning_rate': 1.2303760290684829e-05, 'epoch': 0.89}

 89%|████████▉ | 3178/3566 [2:08:26<16:02,  2.48s/it]
 89%|████████▉ | 3179/3566 [2:08:28<15:14,  2.36s/it]
                                                     
{'loss': 1.4663, 'learning_rate': 1.2241235714334687e-05, 'epoch': 0.89}

 89%|████████▉ | 3179/3566 [2:08:28<15:14,  2.36s/it]
 89%|████████▉ | 3180/3566 [2:08:31<15:58,  2.48s/it]
                                                     
{'loss': 1.5905, 'learning_rate': 1.2178865394251504e-05, 'epoch': 0.89}

 89%|████████▉ | 3180/3566 [2:08:31<15:58,  2.48s/it]
 89%|████████▉ | 3181/3566 [2:08:33<15:41,  2.44s/it]
                                                     
{'loss': 1.5592, 'learning_rate': 1.2116649381676693e-05, 'epoch': 0.89}

 89%|████████▉ | 3181/3566 [2:08:33<15:41,  2.44s/it]
 89%|████████▉ | 3182/3566 [2:08:36<15:26,  2.41s/it]
                                                     
{'loss': 1.3906, 'learning_rate': 1.205458772772483e-05, 'epoch': 0.89}

 89%|████████▉ | 3182/3566 [2:08:36<15:26,  2.41s/it]
 89%|████████▉ | 3183/3566 [2:08:38<15:05,  2.37s/it]
                                                     
{'loss': 1.4964, 'learning_rate': 1.1992680483383644e-05, 'epoch': 0.89}

 89%|████████▉ | 3183/3566 [2:08:38<15:05,  2.37s/it]
 89%|████████▉ | 3184/3566 [2:08:41<16:33,  2.60s/it]
                                                     
{'loss': 1.4898, 'learning_rate': 1.193092769951405e-05, 'epoch': 0.89}

 89%|████████▉ | 3184/3566 [2:08:41<16:33,  2.60s/it]
 89%|████████▉ | 3185/3566 [2:08:43<16:13,  2.56s/it]
                                                     
{'loss': 1.4816, 'learning_rate': 1.1869329426850063e-05, 'epoch': 0.89}

 89%|████████▉ | 3185/3566 [2:08:43<16:13,  2.56s/it]
 89%|████████▉ | 3186/3566 [2:08:46<15:49,  2.50s/it]
                                                     
{'loss': 1.7403, 'learning_rate': 1.1807885715998778e-05, 'epoch': 0.89}

 89%|████████▉ | 3186/3566 [2:08:46<15:49,  2.50s/it]
 89%|████████▉ | 3187/3566 [2:08:48<15:45,  2.49s/it]
                                                     
{'loss': 1.4307, 'learning_rate': 1.1746596617440197e-05, 'epoch': 0.89}

 89%|████████▉ | 3187/3566 [2:08:48<15:45,  2.49s/it]
 89%|████████▉ | 3188/3566 [2:08:51<16:26,  2.61s/it]
                                                     
{'loss': 1.4857, 'learning_rate': 1.1685462181527395e-05, 'epoch': 0.89}

 89%|████████▉ | 3188/3566 [2:08:51<16:26,  2.61s/it]
 89%|████████▉ | 3189/3566 [2:08:54<16:45,  2.67s/it]
                                                     
{'loss': 1.6633, 'learning_rate': 1.1624482458486418e-05, 'epoch': 0.89}

 89%|████████▉ | 3189/3566 [2:08:54<16:45,  2.67s/it]
 89%|████████▉ | 3190/3566 [2:08:56<16:17,  2.60s/it]
                                                     
{'loss': 1.4406, 'learning_rate': 1.156365749841608e-05, 'epoch': 0.89}

 89%|████████▉ | 3190/3566 [2:08:56<16:17,  2.60s/it]
 89%|████████▉ | 3191/3566 [2:08:59<15:56,  2.55s/it]
                                                     
{'loss': 1.5097, 'learning_rate': 1.1502987351288164e-05, 'epoch': 0.89}

 89%|████████▉ | 3191/3566 [2:08:59<15:56,  2.55s/it]
 90%|████████▉ | 3192/3566 [2:09:01<16:03,  2.58s/it]
                                                     
{'loss': 1.6095, 'learning_rate': 1.1442472066947197e-05, 'epoch': 0.9}

 90%|████████▉ | 3192/3566 [2:09:01<16:03,  2.58s/it]
 90%|████████▉ | 3193/3566 [2:09:04<15:54,  2.56s/it]
                                                     
{'loss': 1.5109, 'learning_rate': 1.1382111695110498e-05, 'epoch': 0.9}

 90%|████████▉ | 3193/3566 [2:09:04<15:54,  2.56s/it]
 90%|████████▉ | 3194/3566 [2:09:06<15:40,  2.53s/it]
                                                     
{'loss': 1.4365, 'learning_rate': 1.1321906285368111e-05, 'epoch': 0.9}

 90%|████████▉ | 3194/3566 [2:09:06<15:40,  2.53s/it]
 90%|████████▉ | 3195/3566 [2:09:09<15:19,  2.48s/it]
                                                     
{'loss': 1.4392, 'learning_rate': 1.1261855887182782e-05, 'epoch': 0.9}

 90%|████████▉ | 3195/3566 [2:09:09<15:19,  2.48s/it]
 90%|████████▉ | 3196/3566 [2:09:11<15:15,  2.47s/it]
                                                     
{'loss': 1.5434, 'learning_rate': 1.1201960549889867e-05, 'epoch': 0.9}

 90%|████████▉ | 3196/3566 [2:09:11<15:15,  2.47s/it]
 90%|████████▉ | 3197/3566 [2:09:13<14:45,  2.40s/it]
                                                     
{'loss': 1.4459, 'learning_rate': 1.1142220322697384e-05, 'epoch': 0.9}

 90%|████████▉ | 3197/3566 [2:09:13<14:45,  2.40s/it]
 90%|████████▉ | 3198/3566 [2:09:16<14:42,  2.40s/it]
                                                     
{'loss': 1.4994, 'learning_rate': 1.1082635254685869e-05, 'epoch': 0.9}

 90%|████████▉ | 3198/3566 [2:09:16<14:42,  2.40s/it]
 90%|████████▉ | 3199/3566 [2:09:18<14:41,  2.40s/it]
                                                     
{'loss': 1.5538, 'learning_rate': 1.1023205394808411e-05, 'epoch': 0.9}

 90%|████████▉ | 3199/3566 [2:09:18<14:41,  2.40s/it]
 90%|████████▉ | 3200/3566 [2:09:21<15:26,  2.53s/it]
                                                     
{'loss': 1.6174, 'learning_rate': 1.0963930791890576e-05, 'epoch': 0.9}

 90%|████████▉ | 3200/3566 [2:09:21<15:26,  2.53s/it]
 90%|████████▉ | 3201/3566 [2:09:24<15:47,  2.60s/it]
                                                     
{'loss': 1.5427, 'learning_rate': 1.0904811494630385e-05, 'epoch': 0.9}

 90%|████████▉ | 3201/3566 [2:09:24<15:47,  2.60s/it]
 90%|████████▉ | 3202/3566 [2:09:26<15:00,  2.47s/it]
                                                     
{'loss': 1.4279, 'learning_rate': 1.0845847551598232e-05, 'epoch': 0.9}

 90%|████████▉ | 3202/3566 [2:09:26<15:00,  2.47s/it]
 90%|████████▉ | 3203/3566 [2:09:28<14:20,  2.37s/it]
                                                     
{'loss': 1.5317, 'learning_rate': 1.0787039011236966e-05, 'epoch': 0.9}

 90%|████████▉ | 3203/3566 [2:09:28<14:20,  2.37s/it]
 90%|████████▉ | 3204/3566 [2:09:30<13:59,  2.32s/it]
                                                     
{'loss': 1.4326, 'learning_rate': 1.0728385921861628e-05, 'epoch': 0.9}

 90%|████████▉ | 3204/3566 [2:09:30<13:59,  2.32s/it]
 90%|████████▉ | 3205/3566 [2:09:33<13:44,  2.28s/it]
                                                     
{'loss': 1.4741, 'learning_rate': 1.066988833165965e-05, 'epoch': 0.9}

 90%|████████▉ | 3205/3566 [2:09:33<13:44,  2.28s/it]
 90%|████████▉ | 3206/3566 [2:09:35<13:55,  2.32s/it]
                                                     
{'loss': 1.5682, 'learning_rate': 1.0611546288690678e-05, 'epoch': 0.9}

 90%|████████▉ | 3206/3566 [2:09:35<13:55,  2.32s/it]
 90%|████████▉ | 3207/3566 [2:09:37<13:50,  2.31s/it]
                                                     
{'loss': 1.5388, 'learning_rate': 1.0553359840886567e-05, 'epoch': 0.9}

 90%|████████▉ | 3207/3566 [2:09:37<13:50,  2.31s/it]
 90%|████████▉ | 3208/3566 [2:09:40<13:56,  2.34s/it]
                                                     
{'loss': 1.6032, 'learning_rate': 1.0495329036051305e-05, 'epoch': 0.9}

 90%|████████▉ | 3208/3566 [2:09:40<13:56,  2.34s/it]
 90%|████████▉ | 3209/3566 [2:09:42<13:56,  2.34s/it]
                                                     
{'loss': 1.3131, 'learning_rate': 1.0437453921861106e-05, 'epoch': 0.9}

 90%|████████▉ | 3209/3566 [2:09:42<13:56,  2.34s/it]
 90%|█████████ | 3210/3566 [2:09:45<14:34,  2.46s/it]
                                                     
{'loss': 1.5921, 'learning_rate': 1.0379734545864184e-05, 'epoch': 0.9}

 90%|█████████ | 3210/3566 [2:09:45<14:34,  2.46s/it]
 90%|█████████ | 3211/3566 [2:09:47<14:11,  2.40s/it]
                                                     
{'loss': 1.5438, 'learning_rate': 1.0322170955480848e-05, 'epoch': 0.9}

 90%|█████████ | 3211/3566 [2:09:47<14:11,  2.40s/it]
 90%|█████████ | 3212/3566 [2:09:49<14:22,  2.44s/it]
                                                     
{'loss': 1.5403, 'learning_rate': 1.0264763198003358e-05, 'epoch': 0.9}

 90%|█████████ | 3212/3566 [2:09:50<14:22,  2.44s/it]
 90%|█████████ | 3213/3566 [2:09:52<14:30,  2.47s/it]
                                                     
{'loss': 1.551, 'learning_rate': 1.0207511320596008e-05, 'epoch': 0.9}

 90%|█████████ | 3213/3566 [2:09:52<14:30,  2.47s/it]
 90%|█████████ | 3214/3566 [2:09:55<14:49,  2.53s/it]
                                                     
{'loss': 1.6377, 'learning_rate': 1.0150415370295042e-05, 'epoch': 0.9}

 90%|█████████ | 3214/3566 [2:09:55<14:49,  2.53s/it]
 90%|█████████ | 3215/3566 [2:09:58<15:32,  2.66s/it]
                                                     
{'loss': 1.4479, 'learning_rate': 1.0093475394008511e-05, 'epoch': 0.9}

 90%|█████████ | 3215/3566 [2:09:58<15:32,  2.66s/it]
 90%|█████████ | 3216/3566 [2:10:00<15:02,  2.58s/it]
                                                     
{'loss': 1.5886, 'learning_rate': 1.0036691438516443e-05, 'epoch': 0.9}

 90%|█████████ | 3216/3566 [2:10:00<15:02,  2.58s/it]
 90%|█████████ | 3217/3566 [2:10:03<15:17,  2.63s/it]
                                                     
{'loss': 1.4589, 'learning_rate': 9.980063550470565e-06, 'epoch': 0.9}

 90%|█████████ | 3217/3566 [2:10:03<15:17,  2.63s/it]
 90%|█████████ | 3218/3566 [2:10:05<14:42,  2.54s/it]
                                                     
{'loss': 1.3886, 'learning_rate': 9.923591776394458e-06, 'epoch': 0.9}

 90%|█████████ | 3218/3566 [2:10:05<14:42,  2.54s/it]
 90%|█████████ | 3219/3566 [2:10:08<14:49,  2.56s/it]
                                                     
{'loss': 1.4234, 'learning_rate': 9.867276162683437e-06, 'epoch': 0.9}

 90%|█████████ | 3219/3566 [2:10:08<14:49,  2.56s/it]
 90%|█████████ | 3220/3566 [2:10:10<14:05,  2.44s/it]
                                                     
{'loss': 1.5419, 'learning_rate': 9.81111675560451e-06, 'epoch': 0.9}

 90%|█████████ | 3220/3566 [2:10:10<14:05,  2.44s/it]
 90%|█████████ | 3221/3566 [2:10:12<14:04,  2.45s/it]
                                                     
{'loss': 1.5004, 'learning_rate': 9.755113601296351e-06, 'epoch': 0.9}

 90%|█████████ | 3221/3566 [2:10:12<14:04,  2.45s/it]
 90%|█████████ | 3222/3566 [2:10:15<13:55,  2.43s/it]
                                                     
{'loss': 1.606, 'learning_rate': 9.69926674576922e-06, 'epoch': 0.9}

 90%|█████████ | 3222/3566 [2:10:15<13:55,  2.43s/it]
 90%|█████████ | 3223/3566 [2:10:17<13:51,  2.42s/it]
                                                     
{'loss': 1.6012, 'learning_rate': 9.64357623490506e-06, 'epoch': 0.9}

 90%|█████████ | 3223/3566 [2:10:17<13:51,  2.42s/it]
 90%|█████████ | 3224/3566 [2:10:20<14:01,  2.46s/it]
                                                     
{'loss': 1.5003, 'learning_rate': 9.588042114457318e-06, 'epoch': 0.9}

 90%|█████████ | 3224/3566 [2:10:20<14:01,  2.46s/it]
 90%|█████████ | 3225/3566 [2:10:22<13:53,  2.45s/it]
                                                     
{'loss': 1.4689, 'learning_rate': 9.53266443005094e-06, 'epoch': 0.9}

 90%|█████████ | 3225/3566 [2:10:22<13:53,  2.45s/it]
 90%|█████████ | 3226/3566 [2:10:24<13:28,  2.38s/it]
                                                     
{'loss': 1.5421, 'learning_rate': 9.477443227182337e-06, 'epoch': 0.9}

 90%|█████████ | 3226/3566 [2:10:24<13:28,  2.38s/it]
 90%|█████████ | 3227/3566 [2:10:27<13:32,  2.40s/it]
                                                     
{'loss': 1.7116, 'learning_rate': 9.422378551219434e-06, 'epoch': 0.9}

 90%|█████████ | 3227/3566 [2:10:27<13:32,  2.40s/it]
 91%|█████████ | 3228/3566 [2:10:29<13:17,  2.36s/it]
                                                     
{'loss': 1.5041, 'learning_rate': 9.367470447401472e-06, 'epoch': 0.91}

 91%|█████████ | 3228/3566 [2:10:29<13:17,  2.36s/it]
 91%|█████████ | 3229/3566 [2:10:31<13:13,  2.35s/it]
                                                     
{'loss': 1.4639, 'learning_rate': 9.312718960839161e-06, 'epoch': 0.91}

 91%|█████████ | 3229/3566 [2:10:31<13:13,  2.35s/it]
 91%|█████████ | 3230/3566 [2:10:34<12:56,  2.31s/it]
                                                     
{'loss': 1.3777, 'learning_rate': 9.25812413651439e-06, 'epoch': 0.91}

 91%|█████████ | 3230/3566 [2:10:34<12:56,  2.31s/it]
 91%|█████████ | 3231/3566 [2:10:36<12:53,  2.31s/it]
                                                     
{'loss': 1.5377, 'learning_rate': 9.203686019280455e-06, 'epoch': 0.91}

 91%|█████████ | 3231/3566 [2:10:36<12:53,  2.31s/it]
 91%|█████████ | 3232/3566 [2:10:38<12:59,  2.33s/it]
                                                     
{'loss': 1.424, 'learning_rate': 9.149404653861893e-06, 'epoch': 0.91}

 91%|█████████ | 3232/3566 [2:10:38<12:59,  2.33s/it]
 91%|█████████ | 3233/3566 [2:10:41<13:14,  2.39s/it]
                                                     
{'loss': 1.3922, 'learning_rate': 9.09528008485443e-06, 'epoch': 0.91}

 91%|█████████ | 3233/3566 [2:10:41<13:14,  2.39s/it]
 91%|█████████ | 3234/3566 [2:10:43<13:13,  2.39s/it]
                                                     
{'loss': 1.6023, 'learning_rate': 9.041312356724985e-06, 'epoch': 0.91}

 91%|█████████ | 3234/3566 [2:10:43<13:13,  2.39s/it]
 91%|█████████ | 3235/3566 [2:10:45<12:58,  2.35s/it]
                                                     
{'loss': 1.4872, 'learning_rate': 8.987501513811625e-06, 'epoch': 0.91}

 91%|█████████ | 3235/3566 [2:10:45<12:58,  2.35s/it]
 91%|█████████ | 3236/3566 [2:10:48<12:58,  2.36s/it]
                                                     
{'loss': 1.6268, 'learning_rate': 8.933847600323542e-06, 'epoch': 0.91}

 91%|█████████ | 3236/3566 [2:10:48<12:58,  2.36s/it]
 91%|█████████ | 3237/3566 [2:10:50<12:57,  2.36s/it]
                                                     
{'loss': 1.5175, 'learning_rate': 8.880350660340942e-06, 'epoch': 0.91}

 91%|█████████ | 3237/3566 [2:10:50<12:57,  2.36s/it]
 91%|█████████ | 3238/3566 [2:10:53<13:10,  2.41s/it]
                                                     
{'loss': 1.5395, 'learning_rate': 8.827010737815156e-06, 'epoch': 0.91}

 91%|█████████ | 3238/3566 [2:10:53<13:10,  2.41s/it]
 91%|█████████ | 3239/3566 [2:10:55<13:00,  2.39s/it]
                                                     
{'loss': 1.6375, 'learning_rate': 8.77382787656842e-06, 'epoch': 0.91}

 91%|█████████ | 3239/3566 [2:10:55<13:00,  2.39s/it]
 91%|█████████ | 3240/3566 [2:10:58<13:12,  2.43s/it]
                                                     
{'loss': 1.6174, 'learning_rate': 8.720802120294003e-06, 'epoch': 0.91}

 91%|█████████ | 3240/3566 [2:10:58<13:12,  2.43s/it]
 91%|█████████ | 3241/3566 [2:11:00<12:41,  2.34s/it]
                                                     
{'loss': 1.4514, 'learning_rate': 8.667933512556081e-06, 'epoch': 0.91}

 91%|█████████ | 3241/3566 [2:11:00<12:41,  2.34s/it]
 91%|█████████ | 3242/3566 [2:11:02<12:34,  2.33s/it]
                                                     
{'loss': 1.5983, 'learning_rate': 8.61522209678971e-06, 'epoch': 0.91}

 91%|█████████ | 3242/3566 [2:11:02<12:34,  2.33s/it]
 91%|█████████ | 3243/3566 [2:11:04<12:29,  2.32s/it]
                                                     
{'loss': 1.5748, 'learning_rate': 8.562667916300805e-06, 'epoch': 0.91}

 91%|█████████ | 3243/3566 [2:11:04<12:29,  2.32s/it]
 91%|█████████ | 3244/3566 [2:11:07<12:15,  2.28s/it]
                                                     
{'loss': 1.6983, 'learning_rate': 8.510271014266113e-06, 'epoch': 0.91}

 91%|█████████ | 3244/3566 [2:11:07<12:15,  2.28s/it]
 91%|█████████ | 3245/3566 [2:11:09<12:45,  2.39s/it]
                                                     
{'loss': 1.7032, 'learning_rate': 8.45803143373316e-06, 'epoch': 0.91}

 91%|█████████ | 3245/3566 [2:11:09<12:45,  2.39s/it]
 91%|█████████ | 3246/3566 [2:11:12<13:36,  2.55s/it]
                                                     
{'loss': 1.6123, 'learning_rate': 8.405949217620256e-06, 'epoch': 0.91}

 91%|█████████ | 3246/3566 [2:11:12<13:36,  2.55s/it]
 91%|█████████ | 3247/3566 [2:11:14<13:10,  2.48s/it]
                                                     
{'loss': 1.4013, 'learning_rate': 8.354024408716332e-06, 'epoch': 0.91}

 91%|█████████ | 3247/3566 [2:11:14<13:10,  2.48s/it]
 91%|█████████ | 3248/3566 [2:11:16<12:23,  2.34s/it]
                                                     
{'loss': 1.4655, 'learning_rate': 8.302257049681084e-06, 'epoch': 0.91}

 91%|█████████ | 3248/3566 [2:11:16<12:23,  2.34s/it]
 91%|█████████ | 3249/3566 [2:11:19<12:14,  2.32s/it]
                                                     
{'loss': 1.4169, 'learning_rate': 8.250647183044847e-06, 'epoch': 0.91}

 91%|█████████ | 3249/3566 [2:11:19<12:14,  2.32s/it]
 91%|█████████ | 3250/3566 [2:11:21<11:59,  2.28s/it]
                                                     
{'loss': 1.4577, 'learning_rate': 8.199194851208503e-06, 'epoch': 0.91}

 91%|█████████ | 3250/3566 [2:11:21<11:59,  2.28s/it]
 91%|█████████ | 3251/3566 [2:11:23<12:08,  2.31s/it]
                                                     
{'loss': 1.5864, 'learning_rate': 8.147900096443595e-06, 'epoch': 0.91}

 91%|█████████ | 3251/3566 [2:11:23<12:08,  2.31s/it]
 91%|█████████ | 3252/3566 [2:11:26<11:59,  2.29s/it]
                                                     
{'loss': 1.4822, 'learning_rate': 8.096762960892168e-06, 'epoch': 0.91}

 91%|█████████ | 3252/3566 [2:11:26<11:59,  2.29s/it]
 91%|█████████ | 3253/3566 [2:11:28<12:24,  2.38s/it]
                                                     
{'loss': 1.4007, 'learning_rate': 8.045783486566749e-06, 'epoch': 0.91}

 91%|█████████ | 3253/3566 [2:11:28<12:24,  2.38s/it]
 91%|█████████▏| 3254/3566 [2:11:31<12:32,  2.41s/it]
                                                     
{'loss': 1.4482, 'learning_rate': 7.994961715350368e-06, 'epoch': 0.91}

 91%|█████████▏| 3254/3566 [2:11:31<12:32,  2.41s/it]
 91%|█████████▏| 3255/3566 [2:11:33<12:52,  2.49s/it]
                                                     
{'loss': 1.4935, 'learning_rate': 7.94429768899645e-06, 'epoch': 0.91}

 91%|█████████▏| 3255/3566 [2:11:33<12:52,  2.49s/it]
 91%|█████████▏| 3256/3566 [2:11:36<12:41,  2.46s/it]
                                                     
{'loss': 1.4751, 'learning_rate': 7.893791449128852e-06, 'epoch': 0.91}

 91%|█████████▏| 3256/3566 [2:11:36<12:41,  2.46s/it]
 91%|█████████▏| 3257/3566 [2:11:38<12:43,  2.47s/it]
                                                     
{'loss': 1.613, 'learning_rate': 7.843443037241827e-06, 'epoch': 0.91}

 91%|█████████▏| 3257/3566 [2:11:38<12:43,  2.47s/it]
 91%|█████████▏| 3258/3566 [2:11:40<12:21,  2.41s/it]
                                                     
{'loss': 1.5742, 'learning_rate': 7.793252494699888e-06, 'epoch': 0.91}

 91%|█████████▏| 3258/3566 [2:11:40<12:21,  2.41s/it]
 91%|█████████▏| 3259/3566 [2:11:43<12:11,  2.38s/it]
                                                     
{'loss': 1.652, 'learning_rate': 7.743219862737939e-06, 'epoch': 0.91}

 91%|█████████▏| 3259/3566 [2:11:43<12:11,  2.38s/it]
 91%|█████████▏| 3260/3566 [2:11:45<12:24,  2.43s/it]
                                                     
{'loss': 1.5164, 'learning_rate': 7.693345182461076e-06, 'epoch': 0.91}

 91%|█████████▏| 3260/3566 [2:11:45<12:24,  2.43s/it]
 91%|█████████▏| 3261/3566 [2:11:48<12:57,  2.55s/it]
                                                     
{'loss': 1.508, 'learning_rate': 7.643628494844678e-06, 'epoch': 0.91}

 91%|█████████▏| 3261/3566 [2:11:48<12:57,  2.55s/it]
 91%|█████████▏| 3262/3566 [2:11:51<12:42,  2.51s/it]
                                                     
{'loss': 1.4034, 'learning_rate': 7.594069840734253e-06, 'epoch': 0.91}

 91%|█████████▏| 3262/3566 [2:11:51<12:42,  2.51s/it]
 92%|█████████▏| 3263/3566 [2:11:53<12:37,  2.50s/it]
                                                     
{'loss': 1.5903, 'learning_rate': 7.544669260845561e-06, 'epoch': 0.92}

 92%|█████████▏| 3263/3566 [2:11:53<12:37,  2.50s/it]
 92%|█████████▏| 3264/3566 [2:11:55<12:10,  2.42s/it]
                                                     
{'loss': 1.5578, 'learning_rate': 7.495426795764471e-06, 'epoch': 0.92}

 92%|█████████▏| 3264/3566 [2:11:55<12:10,  2.42s/it]
 92%|█████████▏| 3265/3566 [2:11:58<12:28,  2.49s/it]
                                                     
{'loss': 1.5893, 'learning_rate': 7.446342485946822e-06, 'epoch': 0.92}

 92%|█████████▏| 3265/3566 [2:11:58<12:28,  2.49s/it]
 92%|█████████▏| 3266/3566 [2:12:00<12:20,  2.47s/it]
                                                     
{'loss': 1.6135, 'learning_rate': 7.397416371718757e-06, 'epoch': 0.92}

 92%|█████████▏| 3266/3566 [2:12:00<12:20,  2.47s/it]
 92%|█████████▏| 3267/3566 [2:12:02<11:52,  2.38s/it]
                                                     
{'loss': 1.3993, 'learning_rate': 7.348648493276233e-06, 'epoch': 0.92}

 92%|█████████▏| 3267/3566 [2:12:02<11:52,  2.38s/it]
 92%|█████████▏| 3268/3566 [2:12:05<12:04,  2.43s/it]
                                                     
{'loss': 1.4906, 'learning_rate': 7.300038890685357e-06, 'epoch': 0.92}

 92%|█████████▏| 3268/3566 [2:12:05<12:04,  2.43s/it]
 92%|█████████▏| 3269/3566 [2:12:07<12:03,  2.44s/it]
                                                     
{'loss': 1.542, 'learning_rate': 7.251587603882093e-06, 'epoch': 0.92}

 92%|█████████▏| 3269/3566 [2:12:07<12:03,  2.44s/it]
 92%|█████████▏| 3270/3566 [2:12:10<11:33,  2.34s/it]
                                                     
{'loss': 1.5471, 'learning_rate': 7.2032946726724225e-06, 'epoch': 0.92}

 92%|█████████▏| 3270/3566 [2:12:10<11:33,  2.34s/it]
 92%|█████████▏| 3271/3566 [2:12:12<11:23,  2.32s/it]
                                                     
{'loss': 1.3896, 'learning_rate': 7.155160136732142e-06, 'epoch': 0.92}

 92%|█████████▏| 3271/3566 [2:12:12<11:23,  2.32s/it]
 92%|█████████▏| 3272/3566 [2:12:14<11:37,  2.37s/it]
                                                     
{'loss': 1.3804, 'learning_rate': 7.107184035607018e-06, 'epoch': 0.92}

 92%|█████████▏| 3272/3566 [2:12:14<11:37,  2.37s/it]
 92%|█████████▏| 3273/3566 [2:12:17<11:26,  2.34s/it]
                                                     
{'loss': 1.484, 'learning_rate': 7.0593664087125426e-06, 'epoch': 0.92}

 92%|█████████▏| 3273/3566 [2:12:17<11:26,  2.34s/it]
 92%|█████████▏| 3274/3566 [2:12:19<11:18,  2.32s/it]
                                                     
{'loss': 1.4983, 'learning_rate': 7.011707295334091e-06, 'epoch': 0.92}

 92%|█████████▏| 3274/3566 [2:12:19<11:18,  2.32s/it]
 92%|█████████▏| 3275/3566 [2:12:21<11:28,  2.37s/it]
                                                     
{'loss': 1.4814, 'learning_rate': 6.964206734626788e-06, 'epoch': 0.92}

 92%|█████████▏| 3275/3566 [2:12:21<11:28,  2.37s/it]
 92%|█████████▏| 3276/3566 [2:12:24<12:16,  2.54s/it]
                                                     
{'loss': 1.4635, 'learning_rate': 6.916864765615483e-06, 'epoch': 0.92}

 92%|█████████▏| 3276/3566 [2:12:24<12:16,  2.54s/it]
 92%|█████████▏| 3277/3566 [2:12:27<12:07,  2.52s/it]
                                                     
{'loss': 1.4415, 'learning_rate': 6.86968142719473e-06, 'epoch': 0.92}

 92%|█████████▏| 3277/3566 [2:12:27<12:07,  2.52s/it]
 92%|█████████▏| 3278/3566 [2:12:29<11:53,  2.48s/it]
                                                     
{'loss': 1.5367, 'learning_rate': 6.822656758128787e-06, 'epoch': 0.92}

 92%|█████████▏| 3278/3566 [2:12:29<11:53,  2.48s/it]
 92%|█████████▏| 3279/3566 [2:12:31<11:21,  2.38s/it]
                                                     
{'loss': 1.5089, 'learning_rate': 6.775790797051529e-06, 'epoch': 0.92}

 92%|█████████▏| 3279/3566 [2:12:31<11:21,  2.38s/it]
 92%|█████████▏| 3280/3566 [2:12:34<11:19,  2.38s/it]
                                                     
{'loss': 1.341, 'learning_rate': 6.7290835824664446e-06, 'epoch': 0.92}

 92%|█████████▏| 3280/3566 [2:12:34<11:19,  2.38s/it]
 92%|█████████▏| 3281/3566 [2:12:36<11:10,  2.35s/it]
                                                     
{'loss': 1.5257, 'learning_rate': 6.682535152746594e-06, 'epoch': 0.92}

 92%|█████████▏| 3281/3566 [2:12:36<11:10,  2.35s/it]
 92%|█████████▏| 3282/3566 [2:12:39<11:54,  2.52s/it]
                                                     
{'loss': 1.5688, 'learning_rate': 6.636145546134631e-06, 'epoch': 0.92}

 92%|█████████▏| 3282/3566 [2:12:39<11:54,  2.52s/it]
 92%|█████████▏| 3283/3566 [2:12:42<12:14,  2.59s/it]
                                                     
{'loss': 1.5537, 'learning_rate': 6.589914800742669e-06, 'epoch': 0.92}

 92%|█████████▏| 3283/3566 [2:12:42<12:14,  2.59s/it]
 92%|█████████▏| 3284/3566 [2:12:44<12:10,  2.59s/it]
                                                     
{'loss': 1.3294, 'learning_rate': 6.543842954552348e-06, 'epoch': 0.92}

 92%|█████████▏| 3284/3566 [2:12:44<12:10,  2.59s/it]
 92%|█████████▏| 3285/3566 [2:12:46<11:37,  2.48s/it]
                                                     
{'loss': 1.5439, 'learning_rate': 6.497930045414724e-06, 'epoch': 0.92}

 92%|█████████▏| 3285/3566 [2:12:46<11:37,  2.48s/it]
 92%|█████████▏| 3286/3566 [2:12:49<11:40,  2.50s/it]
                                                     
{'loss': 1.5416, 'learning_rate': 6.45217611105029e-06, 'epoch': 0.92}

 92%|█████████▏| 3286/3566 [2:12:49<11:40,  2.50s/it]
 92%|█████████▏| 3287/3566 [2:12:51<11:05,  2.39s/it]
                                                     
{'loss': 1.4641, 'learning_rate': 6.406581189048932e-06, 'epoch': 0.92}

 92%|█████████▏| 3287/3566 [2:12:51<11:05,  2.39s/it]
 92%|█████████▏| 3288/3566 [2:12:53<10:58,  2.37s/it]
                                                     
{'loss': 1.4569, 'learning_rate': 6.361145316869932e-06, 'epoch': 0.92}

 92%|█████████▏| 3288/3566 [2:12:53<10:58,  2.37s/it]
 92%|█████████▏| 3289/3566 [2:12:56<11:14,  2.43s/it]
                                                     
{'loss': 1.4389, 'learning_rate': 6.315868531841851e-06, 'epoch': 0.92}

 92%|█████████▏| 3289/3566 [2:12:56<11:14,  2.43s/it]
 92%|█████████▏| 3290/3566 [2:12:58<11:03,  2.41s/it]
                                                     
{'loss': 1.4516, 'learning_rate': 6.270750871162556e-06, 'epoch': 0.92}

 92%|█████████▏| 3290/3566 [2:12:58<11:03,  2.41s/it]
 92%|█████████▏| 3291/3566 [2:13:01<11:40,  2.55s/it]
                                                     
{'loss': 1.4031, 'learning_rate': 6.225792371899198e-06, 'epoch': 0.92}

 92%|█████████▏| 3291/3566 [2:13:01<11:40,  2.55s/it]
 92%|█████████▏| 3292/3566 [2:13:04<12:06,  2.65s/it]
                                                     
{'loss': 1.4873, 'learning_rate': 6.180993070988184e-06, 'epoch': 0.92}

 92%|█████████▏| 3292/3566 [2:13:04<12:06,  2.65s/it]
 92%|█████████▏| 3293/3566 [2:13:07<11:56,  2.63s/it]
                                                     
{'loss': 1.5406, 'learning_rate': 6.1363530052350516e-06, 'epoch': 0.92}

 92%|█████████▏| 3293/3566 [2:13:07<11:56,  2.63s/it]
 92%|█████████▏| 3294/3566 [2:13:09<11:30,  2.54s/it]
                                                     
{'loss': 1.6214, 'learning_rate': 6.0918722113146644e-06, 'epoch': 0.92}

 92%|█████████▏| 3294/3566 [2:13:09<11:30,  2.54s/it]
 92%|█████████▏| 3295/3566 [2:13:11<11:07,  2.46s/it]
                                                     
{'loss': 1.654, 'learning_rate': 6.047550725770879e-06, 'epoch': 0.92}

 92%|█████████▏| 3295/3566 [2:13:11<11:07,  2.46s/it]
 92%|█████████▏| 3296/3566 [2:13:14<11:22,  2.53s/it]
                                                     
{'loss': 1.4409, 'learning_rate': 6.0033885850167445e-06, 'epoch': 0.92}

 92%|█████████▏| 3296/3566 [2:13:14<11:22,  2.53s/it]
 92%|█████████▏| 3297/3566 [2:13:16<10:53,  2.43s/it]
                                                     
{'loss': 1.5185, 'learning_rate': 5.9593858253344186e-06, 'epoch': 0.92}

 92%|█████████▏| 3297/3566 [2:13:16<10:53,  2.43s/it]
 92%|█████████▏| 3298/3566 [2:13:19<10:55,  2.45s/it]
                                                     
{'loss': 1.4461, 'learning_rate': 5.915542482875025e-06, 'epoch': 0.92}

 92%|█████████▏| 3298/3566 [2:13:19<10:55,  2.45s/it]
 93%|█████████▎| 3299/3566 [2:13:21<10:45,  2.42s/it]
                                                     
{'loss': 1.5493, 'learning_rate': 5.8718585936588185e-06, 'epoch': 0.93}

 93%|█████████▎| 3299/3566 [2:13:21<10:45,  2.42s/it]
 93%|█████████▎| 3300/3566 [2:13:23<10:37,  2.40s/it]
                                                     
{'loss': 1.4187, 'learning_rate': 5.82833419357498e-06, 'epoch': 0.93}

 93%|█████████▎| 3300/3566 [2:13:23<10:37,  2.40s/it]
 93%|█████████▎| 3301/3566 [2:13:26<10:41,  2.42s/it]
                                                     
{'loss': 1.4147, 'learning_rate': 5.784969318381706e-06, 'epoch': 0.93}

 93%|█████████▎| 3301/3566 [2:13:26<10:41,  2.42s/it]
 93%|█████████▎| 3302/3566 [2:13:28<10:34,  2.40s/it]
                                                     
{'loss': 1.4351, 'learning_rate': 5.741764003706119e-06, 'epoch': 0.93}

 93%|█████████▎| 3302/3566 [2:13:28<10:34,  2.40s/it]
 93%|█████████▎| 3303/3566 [2:13:31<10:23,  2.37s/it]
                                                     
{'loss': 1.4193, 'learning_rate': 5.698718285044247e-06, 'epoch': 0.93}

 93%|█████████▎| 3303/3566 [2:13:31<10:23,  2.37s/it]
 93%|█████████▎| 3304/3566 [2:13:33<10:20,  2.37s/it]
                                                     
{'loss': 1.3579, 'learning_rate': 5.655832197760979e-06, 'epoch': 0.93}

 93%|█████████▎| 3304/3566 [2:13:33<10:20,  2.37s/it]
 93%|█████████▎| 3305/3566 [2:13:35<10:05,  2.32s/it]
                                                     
{'loss': 1.5996, 'learning_rate': 5.6131057770901105e-06, 'epoch': 0.93}

 93%|█████████▎| 3305/3566 [2:13:35<10:05,  2.32s/it]
 93%|█████████▎| 3306/3566 [2:13:37<10:07,  2.34s/it]
                                                     
{'loss': 1.4784, 'learning_rate': 5.570539058134205e-06, 'epoch': 0.93}

 93%|█████████▎| 3306/3566 [2:13:37<10:07,  2.34s/it]
 93%|█████████▎| 3307/3566 [2:13:40<10:13,  2.37s/it]
                                                     
{'loss': 1.372, 'learning_rate': 5.5281320758646445e-06, 'epoch': 0.93}

 93%|█████████▎| 3307/3566 [2:13:40<10:13,  2.37s/it]
 93%|█████████▎| 3308/3566 [2:13:43<11:03,  2.57s/it]
                                                     
{'loss': 1.6313, 'learning_rate': 5.485884865121582e-06, 'epoch': 0.93}

 93%|█████████▎| 3308/3566 [2:13:43<11:03,  2.57s/it]
 93%|█████████▎| 3309/3566 [2:13:45<10:42,  2.50s/it]
                                                     
{'loss': 1.5011, 'learning_rate': 5.443797460613897e-06, 'epoch': 0.93}

 93%|█████████▎| 3309/3566 [2:13:45<10:42,  2.50s/it]
 93%|█████████▎| 3310/3566 [2:13:48<10:25,  2.45s/it]
                                                     
{'loss': 1.4486, 'learning_rate': 5.401869896919176e-06, 'epoch': 0.93}

 93%|█████████▎| 3310/3566 [2:13:48<10:25,  2.45s/it]
 93%|█████████▎| 3311/3566 [2:13:50<10:16,  2.42s/it]
                                                     
{'loss': 1.6164, 'learning_rate': 5.3601022084837084e-06, 'epoch': 0.93}

 93%|█████████▎| 3311/3566 [2:13:50<10:16,  2.42s/it]
 93%|█████████▎| 3312/3566 [2:13:52<10:08,  2.40s/it]
                                                     
{'loss': 1.4808, 'learning_rate': 5.318494429622401e-06, 'epoch': 0.93}

 93%|█████████▎| 3312/3566 [2:13:52<10:08,  2.40s/it]
 93%|█████████▎| 3313/3566 [2:13:55<09:58,  2.36s/it]
                                                     
{'loss': 1.5668, 'learning_rate': 5.277046594518797e-06, 'epoch': 0.93}

 93%|█████████▎| 3313/3566 [2:13:55<09:58,  2.36s/it]
 93%|█████████▎| 3314/3566 [2:13:57<10:00,  2.38s/it]
                                                     
{'loss': 1.613, 'learning_rate': 5.2357587372250825e-06, 'epoch': 0.93}

 93%|█████████▎| 3314/3566 [2:13:57<10:00,  2.38s/it]
 93%|█████████▎| 3315/3566 [2:13:59<09:48,  2.34s/it]
                                                     
{'loss': 1.4627, 'learning_rate': 5.194630891661922e-06, 'epoch': 0.93}

 93%|█████████▎| 3315/3566 [2:13:59<09:48,  2.34s/it]
 93%|█████████▎| 3316/3566 [2:14:02<10:00,  2.40s/it]
                                                     
{'loss': 1.5025, 'learning_rate': 5.153663091618577e-06, 'epoch': 0.93}

 93%|█████████▎| 3316/3566 [2:14:02<10:00,  2.40s/it]
 93%|█████████▎| 3317/3566 [2:14:05<10:24,  2.51s/it]
                                                     
{'loss': 1.6127, 'learning_rate': 5.112855370752812e-06, 'epoch': 0.93}

 93%|█████████▎| 3317/3566 [2:14:05<10:24,  2.51s/it]
 93%|█████████▎| 3318/3566 [2:14:07<10:05,  2.44s/it]
                                                     
{'loss': 1.4373, 'learning_rate': 5.072207762590852e-06, 'epoch': 0.93}

 93%|█████████▎| 3318/3566 [2:14:07<10:05,  2.44s/it]
 93%|█████████▎| 3319/3566 [2:14:09<09:55,  2.41s/it]
                                                     
{'loss': 1.4911, 'learning_rate': 5.031720300527454e-06, 'epoch': 0.93}

 93%|█████████▎| 3319/3566 [2:14:09<09:55,  2.41s/it]
 93%|█████████▎| 3320/3566 [2:14:12<09:47,  2.39s/it]
                                                     
{'loss': 1.5377, 'learning_rate': 4.991393017825696e-06, 'epoch': 0.93}

 93%|█████████▎| 3320/3566 [2:14:12<09:47,  2.39s/it]
 93%|█████████▎| 3321/3566 [2:14:14<10:01,  2.45s/it]
                                                     
{'loss': 1.4105, 'learning_rate': 4.951225947617144e-06, 'epoch': 0.93}

 93%|█████████▎| 3321/3566 [2:14:14<10:01,  2.45s/it]
 93%|█████████▎| 3322/3566 [2:14:17<10:02,  2.47s/it]
                                                     
{'loss': 1.4628, 'learning_rate': 4.911219122901712e-06, 'epoch': 0.93}

 93%|█████████▎| 3322/3566 [2:14:17<10:02,  2.47s/it]
 93%|█████████▎| 3323/3566 [2:14:19<10:04,  2.49s/it]
                                                     
{'loss': 1.4954, 'learning_rate': 4.871372576547639e-06, 'epoch': 0.93}

 93%|█████████▎| 3323/3566 [2:14:19<10:04,  2.49s/it]
 93%|█████████▎| 3324/3566 [2:14:21<09:49,  2.44s/it]
                                                     
{'loss': 1.4045, 'learning_rate': 4.831686341291519e-06, 'epoch': 0.93}

 93%|█████████▎| 3324/3566 [2:14:22<09:49,  2.44s/it]
 93%|█████████▎| 3325/3566 [2:14:24<09:33,  2.38s/it]
                                                     
{'loss': 1.5601, 'learning_rate': 4.792160449738203e-06, 'epoch': 0.93}

 93%|█████████▎| 3325/3566 [2:14:24<09:33,  2.38s/it]
 93%|█████████▎| 3326/3566 [2:14:26<09:17,  2.32s/it]
                                                     
{'loss': 1.4732, 'learning_rate': 4.752794934360872e-06, 'epoch': 0.93}

 93%|█████████▎| 3326/3566 [2:14:26<09:17,  2.32s/it]
 93%|█████████▎| 3327/3566 [2:14:28<09:04,  2.28s/it]
                                                     
{'loss': 1.6577, 'learning_rate': 4.713589827500853e-06, 'epoch': 0.93}

 93%|█████████▎| 3327/3566 [2:14:28<09:04,  2.28s/it]
 93%|█████████▎| 3328/3566 [2:14:30<08:59,  2.26s/it]
                                                     
{'loss': 1.556, 'learning_rate': 4.67454516136776e-06, 'epoch': 0.93}

 93%|█████████▎| 3328/3566 [2:14:30<08:59,  2.26s/it]
 93%|█████████▎| 3329/3566 [2:14:33<09:05,  2.30s/it]
                                                     
{'loss': 1.5989, 'learning_rate': 4.63566096803938e-06, 'epoch': 0.93}

 93%|█████████▎| 3329/3566 [2:14:33<09:05,  2.30s/it]
 93%|█████████▎| 3330/3566 [2:14:35<09:11,  2.34s/it]
                                                     
{'loss': 1.4657, 'learning_rate': 4.596937279461644e-06, 'epoch': 0.93}

 93%|█████████▎| 3330/3566 [2:14:35<09:11,  2.34s/it]
 93%|█████████▎| 3331/3566 [2:14:37<09:07,  2.33s/it]
                                                     
{'loss': 1.5205, 'learning_rate': 4.558374127448662e-06, 'epoch': 0.93}

 93%|█████████▎| 3331/3566 [2:14:37<09:07,  2.33s/it]
 93%|█████████▎| 3332/3566 [2:14:40<09:02,  2.32s/it]
                                                     
{'loss': 1.5932, 'learning_rate': 4.519971543682577e-06, 'epoch': 0.93}

 93%|█████████▎| 3332/3566 [2:14:40<09:02,  2.32s/it]
 93%|█████████▎| 3333/3566 [2:14:42<08:50,  2.28s/it]
                                                     
{'loss': 1.5974, 'learning_rate': 4.481729559713688e-06, 'epoch': 0.93}

 93%|█████████▎| 3333/3566 [2:14:42<08:50,  2.28s/it]
 93%|█████████▎| 3334/3566 [2:14:44<08:40,  2.24s/it]
                                                     
{'loss': 1.366, 'learning_rate': 4.443648206960283e-06, 'epoch': 0.93}

 93%|█████████▎| 3334/3566 [2:14:44<08:40,  2.24s/it]
 94%|█████████▎| 3335/3566 [2:14:46<08:43,  2.27s/it]
                                                     
{'loss': 1.506, 'learning_rate': 4.405727516708713e-06, 'epoch': 0.94}

 94%|█████████▎| 3335/3566 [2:14:46<08:43,  2.27s/it]
 94%|█████████▎| 3336/3566 [2:14:49<08:58,  2.34s/it]
                                                     
{'loss': 1.5559, 'learning_rate': 4.367967520113392e-06, 'epoch': 0.94}

 94%|█████████▎| 3336/3566 [2:14:49<08:58,  2.34s/it]
 94%|█████████▎| 3337/3566 [2:14:51<08:55,  2.34s/it]
                                                     
{'loss': 1.5742, 'learning_rate': 4.330368248196614e-06, 'epoch': 0.94}

 94%|█████████▎| 3337/3566 [2:14:51<08:55,  2.34s/it]
 94%|█████████▎| 3338/3566 [2:14:54<09:04,  2.39s/it]
                                                     
{'loss': 1.6169, 'learning_rate': 4.292929731848716e-06, 'epoch': 0.94}

 94%|█████████▎| 3338/3566 [2:14:54<09:04,  2.39s/it]
 94%|█████████▎| 3339/3566 [2:14:56<09:19,  2.47s/it]
                                                     
{'loss': 1.5297, 'learning_rate': 4.25565200182787e-06, 'epoch': 0.94}

 94%|█████████▎| 3339/3566 [2:14:56<09:19,  2.47s/it]
 94%|█████████▎| 3340/3566 [2:14:59<09:12,  2.44s/it]
                                                     
{'loss': 1.5329, 'learning_rate': 4.218535088760245e-06, 'epoch': 0.94}

 94%|█████████▎| 3340/3566 [2:14:59<09:12,  2.44s/it]
 94%|█████████▎| 3341/3566 [2:15:01<09:07,  2.43s/it]
                                                     
{'loss': 1.6579, 'learning_rate': 4.181579023139803e-06, 'epoch': 0.94}

 94%|█████████▎| 3341/3566 [2:15:01<09:07,  2.43s/it]
 94%|█████████▎| 3342/3566 [2:15:03<08:44,  2.34s/it]
                                                     
{'loss': 1.4703, 'learning_rate': 4.144783835328414e-06, 'epoch': 0.94}

 94%|█████████▎| 3342/3566 [2:15:03<08:44,  2.34s/it]
 94%|█████████▎| 3343/3566 [2:15:06<08:40,  2.33s/it]
                                                     
{'loss': 1.3892, 'learning_rate': 4.108149555555785e-06, 'epoch': 0.94}

 94%|█████████▎| 3343/3566 [2:15:06<08:40,  2.33s/it]
 94%|█████████▍| 3344/3566 [2:15:08<08:28,  2.29s/it]
                                                     
{'loss': 1.6183, 'learning_rate': 4.071676213919373e-06, 'epoch': 0.94}

 94%|█████████▍| 3344/3566 [2:15:08<08:28,  2.29s/it]
 94%|█████████▍| 3345/3566 [2:15:10<08:14,  2.24s/it]
                                                     
{'loss': 1.6091, 'learning_rate': 4.035363840384476e-06, 'epoch': 0.94}

 94%|█████████▍| 3345/3566 [2:15:10<08:14,  2.24s/it]
 94%|█████████▍| 3346/3566 [2:15:12<08:26,  2.30s/it]
                                                     
{'loss': 1.4104, 'learning_rate': 3.999212464784097e-06, 'epoch': 0.94}

 94%|█████████▍| 3346/3566 [2:15:12<08:26,  2.30s/it]
 94%|█████████▍| 3347/3566 [2:15:15<08:35,  2.36s/it]
                                                     
{'loss': 1.5015, 'learning_rate': 3.9632221168189875e-06, 'epoch': 0.94}

 94%|█████████▍| 3347/3566 [2:15:15<08:35,  2.36s/it]
 94%|█████████▍| 3348/3566 [2:15:17<08:16,  2.28s/it]
                                                     
{'loss': 1.5712, 'learning_rate': 3.9273928260576075e-06, 'epoch': 0.94}

 94%|█████████▍| 3348/3566 [2:15:17<08:16,  2.28s/it]
 94%|█████████▍| 3349/3566 [2:15:19<08:07,  2.25s/it]
                                                     
{'loss': 1.5075, 'learning_rate': 3.891724621936099e-06, 'epoch': 0.94}

 94%|█████████▍| 3349/3566 [2:15:19<08:07,  2.25s/it]
 94%|█████████▍| 3350/3566 [2:15:21<08:00,  2.22s/it]
                                                     
{'loss': 1.4962, 'learning_rate': 3.856217533758222e-06, 'epoch': 0.94}

 94%|█████████▍| 3350/3566 [2:15:21<08:00,  2.22s/it]
 94%|█████████▍| 3351/3566 [2:15:24<08:05,  2.26s/it]
                                                     
{'loss': 1.5411, 'learning_rate': 3.820871590695463e-06, 'epoch': 0.94}

 94%|█████████▍| 3351/3566 [2:15:24<08:05,  2.26s/it]
 94%|█████████▍| 3352/3566 [2:15:26<07:59,  2.24s/it]
                                                     
{'loss': 1.4467, 'learning_rate': 3.7856868217867936e-06, 'epoch': 0.94}

 94%|█████████▍| 3352/3566 [2:15:26<07:59,  2.24s/it]
 94%|█████████▍| 3353/3566 [2:15:28<08:08,  2.29s/it]
                                                     
{'loss': 1.6727, 'learning_rate': 3.750663255938869e-06, 'epoch': 0.94}

 94%|█████████▍| 3353/3566 [2:15:28<08:08,  2.29s/it]
 94%|█████████▍| 3354/3566 [2:15:31<08:36,  2.44s/it]
                                                     
{'loss': 1.4978, 'learning_rate': 3.7158009219258717e-06, 'epoch': 0.94}

 94%|█████████▍| 3354/3566 [2:15:31<08:36,  2.44s/it]
 94%|█████████▍| 3355/3566 [2:15:33<08:18,  2.36s/it]
                                                     
{'loss': 1.4307, 'learning_rate': 3.6810998483895133e-06, 'epoch': 0.94}

 94%|█████████▍| 3355/3566 [2:15:33<08:18,  2.36s/it]
 94%|█████████▍| 3356/3566 [2:15:36<08:13,  2.35s/it]
                                                     
{'loss': 1.5942, 'learning_rate': 3.6465600638390107e-06, 'epoch': 0.94}

 94%|█████████▍| 3356/3566 [2:15:36<08:13,  2.35s/it]
 94%|█████████▍| 3357/3566 [2:15:38<08:07,  2.33s/it]
                                                     
{'loss': 1.3019, 'learning_rate': 3.6121815966511096e-06, 'epoch': 0.94}

 94%|█████████▍| 3357/3566 [2:15:38<08:07,  2.33s/it]
 94%|█████████▍| 3358/3566 [2:15:41<08:37,  2.49s/it]
                                                     
{'loss': 1.5688, 'learning_rate': 3.5779644750699724e-06, 'epoch': 0.94}

 94%|█████████▍| 3358/3566 [2:15:41<08:37,  2.49s/it]
 94%|█████████▍| 3359/3566 [2:15:43<08:23,  2.43s/it]
                                                     
{'loss': 1.4394, 'learning_rate': 3.5439087272072457e-06, 'epoch': 0.94}

 94%|█████████▍| 3359/3566 [2:15:43<08:23,  2.43s/it]
 94%|█████████▍| 3360/3566 [2:15:45<08:23,  2.45s/it]
                                                     
{'loss': 1.4718, 'learning_rate': 3.5100143810419927e-06, 'epoch': 0.94}

 94%|█████████▍| 3360/3566 [2:15:45<08:23,  2.45s/it]
 94%|█████████▍| 3361/3566 [2:15:47<07:50,  2.29s/it]
                                                     
{'loss': 1.6131, 'learning_rate': 3.47628146442065e-06, 'epoch': 0.94}

 94%|█████████▍| 3361/3566 [2:15:47<07:50,  2.29s/it]
 94%|█████████▍| 3362/3566 [2:15:50<07:47,  2.29s/it]
                                                     
{'loss': 1.5313, 'learning_rate': 3.4427100050570484e-06, 'epoch': 0.94}

 94%|█████████▍| 3362/3566 [2:15:50<07:47,  2.29s/it]
 94%|█████████▍| 3363/3566 [2:15:52<07:43,  2.28s/it]
                                                     
{'loss': 1.5403, 'learning_rate': 3.4093000305323475e-06, 'epoch': 0.94}

 94%|█████████▍| 3363/3566 [2:15:52<07:43,  2.28s/it]
 94%|█████████▍| 3364/3566 [2:15:54<07:48,  2.32s/it]
                                                     
{'loss': 1.3468, 'learning_rate': 3.3760515682951023e-06, 'epoch': 0.94}

 94%|█████████▍| 3364/3566 [2:15:54<07:48,  2.32s/it]
 94%|█████████▍| 3365/3566 [2:15:57<07:52,  2.35s/it]
                                                     
{'loss': 1.5298, 'learning_rate': 3.3429646456611062e-06, 'epoch': 0.94}

 94%|█████████▍| 3365/3566 [2:15:57<07:52,  2.35s/it]
 94%|█████████▍| 3366/3566 [2:16:00<08:12,  2.46s/it]
                                                     
{'loss': 1.5932, 'learning_rate': 3.310039289813438e-06, 'epoch': 0.94}

 94%|█████████▍| 3366/3566 [2:16:00<08:12,  2.46s/it]
 94%|█████████▍| 3367/3566 [2:16:02<08:07,  2.45s/it]
                                                     
{'loss': 1.513, 'learning_rate': 3.2772755278024813e-06, 'epoch': 0.94}

 94%|█████████▍| 3367/3566 [2:16:02<08:07,  2.45s/it]
 94%|█████████▍| 3368/3566 [2:16:05<08:13,  2.49s/it]
                                                     
{'loss': 1.5569, 'learning_rate': 3.2446733865458156e-06, 'epoch': 0.94}

 94%|█████████▍| 3368/3566 [2:16:05<08:13,  2.49s/it]
 94%|█████████▍| 3369/3566 [2:16:07<08:04,  2.46s/it]
                                                     
{'loss': 1.6224, 'learning_rate': 3.212232892828282e-06, 'epoch': 0.94}

 94%|█████████▍| 3369/3566 [2:16:07<08:04,  2.46s/it]
 95%|█████████▍| 3370/3566 [2:16:09<07:47,  2.38s/it]
                                                     
{'loss': 1.5352, 'learning_rate': 3.179954073301894e-06, 'epoch': 0.95}

 95%|█████████▍| 3370/3566 [2:16:09<07:47,  2.38s/it]
 95%|█████████▍| 3371/3566 [2:16:12<07:46,  2.39s/it]
                                                     
{'loss': 1.4018, 'learning_rate': 3.147836954485839e-06, 'epoch': 0.95}

 95%|█████████▍| 3371/3566 [2:16:12<07:46,  2.39s/it]
 95%|█████████▍| 3372/3566 [2:16:15<08:19,  2.57s/it]
                                                     
{'loss': 1.474, 'learning_rate': 3.1158815627664318e-06, 'epoch': 0.95}

 95%|█████████▍| 3372/3566 [2:16:15<08:19,  2.57s/it]
 95%|█████████▍| 3373/3566 [2:16:17<08:00,  2.49s/it]
                                                     
{'loss': 1.4249, 'learning_rate': 3.0840879243972056e-06, 'epoch': 0.95}

 95%|█████████▍| 3373/3566 [2:16:17<08:00,  2.49s/it]
 95%|█████████▍| 3374/3566 [2:16:19<07:52,  2.46s/it]
                                                     
{'loss': 1.5811, 'learning_rate': 3.0524560654986654e-06, 'epoch': 0.95}

 95%|█████████▍| 3374/3566 [2:16:19<07:52,  2.46s/it]
 95%|█████████▍| 3375/3566 [2:16:22<07:49,  2.46s/it]
                                                     
{'loss': 1.4264, 'learning_rate': 3.0209860120585575e-06, 'epoch': 0.95}

 95%|█████████▍| 3375/3566 [2:16:22<07:49,  2.46s/it]
 95%|█████████▍| 3376/3566 [2:16:24<07:43,  2.44s/it]
                                                     
{'loss': 1.4768, 'learning_rate': 2.989677789931555e-06, 'epoch': 0.95}

 95%|█████████▍| 3376/3566 [2:16:24<07:43,  2.44s/it]
 95%|█████████▍| 3377/3566 [2:16:26<07:38,  2.43s/it]
                                                     
{'loss': 1.3373, 'learning_rate': 2.958531424839439e-06, 'epoch': 0.95}

 95%|█████████▍| 3377/3566 [2:16:26<07:38,  2.43s/it]
 95%|█████████▍| 3378/3566 [2:16:29<07:37,  2.43s/it]
                                                     
{'loss': 1.5234, 'learning_rate': 2.927546942371051e-06, 'epoch': 0.95}

 95%|█████████▍| 3378/3566 [2:16:29<07:37,  2.43s/it]
 95%|█████████▍| 3379/3566 [2:16:31<07:32,  2.42s/it]
                                                     
{'loss': 1.4248, 'learning_rate': 2.8967243679821844e-06, 'epoch': 0.95}

 95%|█████████▍| 3379/3566 [2:16:31<07:32,  2.42s/it]
 95%|█████████▍| 3380/3566 [2:16:34<07:22,  2.38s/it]
                                                     
{'loss': 1.5532, 'learning_rate': 2.866063726995627e-06, 'epoch': 0.95}

 95%|█████████▍| 3380/3566 [2:16:34<07:22,  2.38s/it]
 95%|█████████▍| 3381/3566 [2:16:36<07:42,  2.50s/it]
                                                     
{'loss': 1.4802, 'learning_rate': 2.8355650446010963e-06, 'epoch': 0.95}

 95%|█████████▍| 3381/3566 [2:16:36<07:42,  2.50s/it]
 95%|█████████▍| 3382/3566 [2:16:39<07:31,  2.45s/it]
                                                     
{'loss': 1.6671, 'learning_rate': 2.8052283458553263e-06, 'epoch': 0.95}

 95%|█████████▍| 3382/3566 [2:16:39<07:31,  2.45s/it]
 95%|█████████▍| 3383/3566 [2:16:41<07:27,  2.44s/it]
                                                     
{'loss': 1.539, 'learning_rate': 2.7750536556818916e-06, 'epoch': 0.95}

 95%|█████████▍| 3383/3566 [2:16:41<07:27,  2.44s/it]
 95%|█████████▍| 3384/3566 [2:16:44<07:22,  2.43s/it]
                                                     
{'loss': 1.6825, 'learning_rate': 2.7450409988713176e-06, 'epoch': 0.95}

 95%|█████████▍| 3384/3566 [2:16:44<07:22,  2.43s/it]
 95%|█████████▍| 3385/3566 [2:16:46<07:14,  2.40s/it]
                                                     
{'loss': 1.491, 'learning_rate': 2.7151904000809693e-06, 'epoch': 0.95}

 95%|█████████▍| 3385/3566 [2:16:46<07:14,  2.40s/it]
 95%|█████████▍| 3386/3566 [2:16:48<07:04,  2.36s/it]
                                                     
{'loss': 1.4988, 'learning_rate': 2.6855018838351174e-06, 'epoch': 0.95}

 95%|█████████▍| 3386/3566 [2:16:48<07:04,  2.36s/it]
 95%|█████████▍| 3387/3566 [2:16:50<07:00,  2.35s/it]
                                                     
{'loss': 1.4134, 'learning_rate': 2.65597547452483e-06, 'epoch': 0.95}

 95%|█████████▍| 3387/3566 [2:16:50<07:00,  2.35s/it]
 95%|█████████▌| 3388/3566 [2:16:53<07:02,  2.37s/it]
                                                     
{'loss': 1.5256, 'learning_rate': 2.626611196408035e-06, 'epoch': 0.95}

 95%|█████████▌| 3388/3566 [2:16:53<07:02,  2.37s/it]
 95%|█████████▌| 3389/3566 [2:16:56<07:22,  2.50s/it]
                                                     
{'loss': 1.4155, 'learning_rate': 2.5974090736093916e-06, 'epoch': 0.95}

 95%|█████████▌| 3389/3566 [2:16:56<07:22,  2.50s/it]
 95%|█████████▌| 3390/3566 [2:16:58<07:19,  2.50s/it]
                                                     
{'loss': 1.6288, 'learning_rate': 2.568369130120396e-06, 'epoch': 0.95}

 95%|█████████▌| 3390/3566 [2:16:58<07:19,  2.50s/it]
 95%|█████████▌| 3391/3566 [2:17:01<07:15,  2.49s/it]
                                                     
{'loss': 1.5962, 'learning_rate': 2.539491389799298e-06, 'epoch': 0.95}

 95%|█████████▌| 3391/3566 [2:17:01<07:15,  2.49s/it]
 95%|█████████▌| 3392/3566 [2:17:03<07:16,  2.51s/it]
                                                     
{'loss': 1.3867, 'learning_rate': 2.510775876371052e-06, 'epoch': 0.95}

 95%|█████████▌| 3392/3566 [2:17:03<07:16,  2.51s/it]
 95%|█████████▌| 3393/3566 [2:17:05<07:02,  2.44s/it]
                                                     
{'loss': 1.518, 'learning_rate': 2.4822226134273873e-06, 'epoch': 0.95}

 95%|█████████▌| 3393/3566 [2:17:05<07:02,  2.44s/it]
 95%|█████████▌| 3394/3566 [2:17:08<06:53,  2.40s/it]
                                                     
{'loss': 1.4695, 'learning_rate': 2.453831624426672e-06, 'epoch': 0.95}

 95%|█████████▌| 3394/3566 [2:17:08<06:53,  2.40s/it]
 95%|█████████▌| 3395/3566 [2:17:10<06:46,  2.38s/it]
                                                     
{'loss': 1.5608, 'learning_rate': 2.4256029326940043e-06, 'epoch': 0.95}

 95%|█████████▌| 3395/3566 [2:17:10<06:46,  2.38s/it]
 95%|█████████▌| 3396/3566 [2:17:12<06:34,  2.32s/it]
                                                     
{'loss': 1.4986, 'learning_rate': 2.397536561421121e-06, 'epoch': 0.95}

 95%|█████████▌| 3396/3566 [2:17:12<06:34,  2.32s/it]
 95%|█████████▌| 3397/3566 [2:17:15<06:28,  2.30s/it]
                                                     
{'loss': 1.4895, 'learning_rate': 2.3696325336663772e-06, 'epoch': 0.95}

 95%|█████████▌| 3397/3566 [2:17:15<06:28,  2.30s/it]
 95%|█████████▌| 3398/3566 [2:17:17<06:38,  2.37s/it]
                                                     
{'loss': 1.485, 'learning_rate': 2.341890872354835e-06, 'epoch': 0.95}

 95%|█████████▌| 3398/3566 [2:17:17<06:38,  2.37s/it]
 95%|█████████▌| 3399/3566 [2:17:19<06:29,  2.33s/it]
                                                     
{'loss': 1.5695, 'learning_rate': 2.314311600278063e-06, 'epoch': 0.95}

 95%|█████████▌| 3399/3566 [2:17:19<06:29,  2.33s/it]
 95%|█████████▌| 3400/3566 [2:17:22<06:36,  2.39s/it]
                                                     
{'loss': 1.5533, 'learning_rate': 2.2868947400942918e-06, 'epoch': 0.95}

 95%|█████████▌| 3400/3566 [2:17:22<06:36,  2.39s/it]
 95%|█████████▌| 3401/3566 [2:17:24<06:24,  2.33s/it]
                                                     
{'loss': 1.5704, 'learning_rate': 2.2596403143282594e-06, 'epoch': 0.95}

 95%|█████████▌| 3401/3566 [2:17:24<06:24,  2.33s/it]
 95%|█████████▌| 3402/3566 [2:17:28<07:19,  2.68s/it]
                                                     
{'loss': 1.5421, 'learning_rate': 2.232548345371299e-06, 'epoch': 0.95}

 95%|█████████▌| 3402/3566 [2:17:28<07:19,  2.68s/it]
 95%|█████████▌| 3403/3566 [2:17:30<07:02,  2.59s/it]
                                                     
{'loss': 1.5783, 'learning_rate': 2.2056188554812507e-06, 'epoch': 0.95}

 95%|█████████▌| 3403/3566 [2:17:30<07:02,  2.59s/it]
 95%|█████████▌| 3404/3566 [2:17:32<06:46,  2.51s/it]
                                                     
{'loss': 1.4199, 'learning_rate': 2.178851866782483e-06, 'epoch': 0.95}

 95%|█████████▌| 3404/3566 [2:17:32<06:46,  2.51s/it]
 95%|█████████▌| 3405/3566 [2:17:35<06:32,  2.44s/it]
                                                     
{'loss': 1.3821, 'learning_rate': 2.152247401265828e-06, 'epoch': 0.95}

 95%|█████████▌| 3405/3566 [2:17:35<06:32,  2.44s/it]
 96%|█████████▌| 3406/3566 [2:17:37<06:20,  2.38s/it]
                                                     
{'loss': 1.6316, 'learning_rate': 2.1258054807886673e-06, 'epoch': 0.96}

 96%|█████████▌| 3406/3566 [2:17:37<06:20,  2.38s/it]
 96%|█████████▌| 3407/3566 [2:17:39<06:34,  2.48s/it]
                                                     
{'loss': 1.4645, 'learning_rate': 2.099526127074736e-06, 'epoch': 0.96}

 96%|█████████▌| 3407/3566 [2:17:39<06:34,  2.48s/it]
 96%|█████████▌| 3408/3566 [2:17:42<06:22,  2.42s/it]
                                                     
{'loss': 1.5031, 'learning_rate': 2.073409361714318e-06, 'epoch': 0.96}

 96%|█████████▌| 3408/3566 [2:17:42<06:22,  2.42s/it]
 96%|█████████▌| 3409/3566 [2:17:44<06:18,  2.41s/it]
                                                     
{'loss': 1.4487, 'learning_rate': 2.0474552061640286e-06, 'epoch': 0.96}

 96%|█████████▌| 3409/3566 [2:17:44<06:18,  2.41s/it]
 96%|█████████▌| 3410/3566 [2:17:47<06:24,  2.47s/it]
                                                     
{'loss': 1.4165, 'learning_rate': 2.0216636817469216e-06, 'epoch': 0.96}

 96%|█████████▌| 3410/3566 [2:17:47<06:24,  2.47s/it]
 96%|█████████▌| 3411/3566 [2:17:49<06:15,  2.42s/it]
                                                     
{'loss': 1.449, 'learning_rate': 1.9960348096524695e-06, 'epoch': 0.96}

 96%|█████████▌| 3411/3566 [2:17:49<06:15,  2.42s/it]
 96%|█████████▌| 3412/3566 [2:17:51<06:13,  2.42s/it]
                                                     
{'loss': 1.6267, 'learning_rate': 1.970568610936474e-06, 'epoch': 0.96}

 96%|█████████▌| 3412/3566 [2:17:51<06:13,  2.42s/it]
 96%|█████████▌| 3413/3566 [2:17:54<06:04,  2.38s/it]
                                                     
{'loss': 1.3642, 'learning_rate': 1.9452651065211104e-06, 'epoch': 0.96}

 96%|█████████▌| 3413/3566 [2:17:54<06:04,  2.38s/it]
 96%|█████████▌| 3414/3566 [2:17:56<06:05,  2.41s/it]
                                                     
{'loss': 1.518, 'learning_rate': 1.9201243171948824e-06, 'epoch': 0.96}

 96%|█████████▌| 3414/3566 [2:17:56<06:05,  2.41s/it]
 96%|█████████▌| 3415/3566 [2:17:59<06:16,  2.49s/it]
                                                     
{'loss': 1.5459, 'learning_rate': 1.8951462636126016e-06, 'epoch': 0.96}

 96%|█████████▌| 3415/3566 [2:17:59<06:16,  2.49s/it]
 96%|█████████▌| 3416/3566 [2:18:01<06:05,  2.44s/it]
                                                     
{'loss': 1.5164, 'learning_rate': 1.8703309662954082e-06, 'epoch': 0.96}

 96%|█████████▌| 3416/3566 [2:18:01<06:05,  2.44s/it]
 96%|█████████▌| 3417/3566 [2:18:04<06:04,  2.44s/it]
                                                     
{'loss': 1.5386, 'learning_rate': 1.8456784456307274e-06, 'epoch': 0.96}

 96%|█████████▌| 3417/3566 [2:18:04<06:04,  2.44s/it]
 96%|█████████▌| 3418/3566 [2:18:06<05:52,  2.38s/it]
                                                     
{'loss': 1.5744, 'learning_rate': 1.8211887218722246e-06, 'epoch': 0.96}

 96%|█████████▌| 3418/3566 [2:18:06<05:52,  2.38s/it]
 96%|█████████▌| 3419/3566 [2:18:08<05:55,  2.42s/it]
                                                     
{'loss': 1.4023, 'learning_rate': 1.7968618151398275e-06, 'epoch': 0.96}

 96%|█████████▌| 3419/3566 [2:18:08<05:55,  2.42s/it]
 96%|█████████▌| 3420/3566 [2:18:11<06:03,  2.49s/it]
                                                     
{'loss': 1.5878, 'learning_rate': 1.7726977454196825e-06, 'epoch': 0.96}

 96%|█████████▌| 3420/3566 [2:18:11<06:03,  2.49s/it]
 96%|█████████▌| 3421/3566 [2:18:14<06:01,  2.49s/it]
                                                     
{'loss': 1.6652, 'learning_rate': 1.748696532564198e-06, 'epoch': 0.96}

 96%|█████████▌| 3421/3566 [2:18:14<06:01,  2.49s/it]
 96%|█████████▌| 3422/3566 [2:18:16<06:12,  2.59s/it]
                                                     
{'loss': 1.6165, 'learning_rate': 1.7248581962919563e-06, 'epoch': 0.96}

 96%|█████████▌| 3422/3566 [2:18:16<06:12,  2.59s/it]
 96%|█████████▌| 3423/3566 [2:18:19<05:59,  2.51s/it]
                                                     
{'loss': 1.4265, 'learning_rate': 1.701182756187758e-06, 'epoch': 0.96}

 96%|█████████▌| 3423/3566 [2:18:19<05:59,  2.51s/it]
 96%|█████████▌| 3424/3566 [2:18:21<05:50,  2.47s/it]
                                                     
{'loss': 1.6058, 'learning_rate': 1.6776702317024884e-06, 'epoch': 0.96}

 96%|█████████▌| 3424/3566 [2:18:21<05:50,  2.47s/it]
 96%|█████████▌| 3425/3566 [2:18:23<05:42,  2.43s/it]
                                                     
{'loss': 1.633, 'learning_rate': 1.6543206421532953e-06, 'epoch': 0.96}

 96%|█████████▌| 3425/3566 [2:18:23<05:42,  2.43s/it]
 96%|█████████▌| 3426/3566 [2:18:26<05:35,  2.40s/it]
                                                     
{'loss': 1.5334, 'learning_rate': 1.6311340067234115e-06, 'epoch': 0.96}

 96%|█████████▌| 3426/3566 [2:18:26<05:35,  2.40s/it]
 96%|█████████▌| 3427/3566 [2:18:28<05:35,  2.41s/it]
                                                     
{'loss': 1.3873, 'learning_rate': 1.6081103444621549e-06, 'epoch': 0.96}

 96%|█████████▌| 3427/3566 [2:18:28<05:35,  2.41s/it]
 96%|█████████▌| 3428/3566 [2:18:30<05:26,  2.37s/it]
                                                     
{'loss': 1.6249, 'learning_rate': 1.5852496742850165e-06, 'epoch': 0.96}

 96%|█████████▌| 3428/3566 [2:18:30<05:26,  2.37s/it]
 96%|█████████▌| 3429/3566 [2:18:33<05:27,  2.39s/it]
                                                     
{'loss': 1.3975, 'learning_rate': 1.5625520149735507e-06, 'epoch': 0.96}

 96%|█████████▌| 3429/3566 [2:18:33<05:27,  2.39s/it]
 96%|█████████▌| 3430/3566 [2:18:35<05:21,  2.37s/it]
                                                     
{'loss': 1.4826, 'learning_rate': 1.540017385175374e-06, 'epoch': 0.96}

 96%|█████████▌| 3430/3566 [2:18:35<05:21,  2.37s/it]
 96%|█████████▌| 3431/3566 [2:18:38<05:28,  2.43s/it]
                                                     
{'loss': 1.4882, 'learning_rate': 1.5176458034042108e-06, 'epoch': 0.96}

 96%|█████████▌| 3431/3566 [2:18:38<05:28,  2.43s/it]
 96%|█████████▌| 3432/3566 [2:18:40<05:28,  2.45s/it]
                                                     
{'loss': 1.6543, 'learning_rate': 1.4954372880397583e-06, 'epoch': 0.96}

 96%|█████████▌| 3432/3566 [2:18:40<05:28,  2.45s/it]
 96%|█████████▋| 3433/3566 [2:18:43<05:23,  2.44s/it]
                                                     
{'loss': 1.5112, 'learning_rate': 1.4733918573277994e-06, 'epoch': 0.96}

 96%|█████████▋| 3433/3566 [2:18:43<05:23,  2.44s/it]
 96%|█████████▋| 3434/3566 [2:18:45<05:32,  2.52s/it]
                                                     
{'loss': 1.4708, 'learning_rate': 1.451509529380135e-06, 'epoch': 0.96}

 96%|█████████▋| 3434/3566 [2:18:45<05:32,  2.52s/it]
 96%|█████████▋| 3435/3566 [2:18:48<05:23,  2.47s/it]
                                                     
{'loss': 1.489, 'learning_rate': 1.429790322174518e-06, 'epoch': 0.96}

 96%|█████████▋| 3435/3566 [2:18:48<05:23,  2.47s/it]
 96%|█████████▋| 3436/3566 [2:18:50<05:09,  2.38s/it]
                                                     
{'loss': 1.4459, 'learning_rate': 1.4082342535547411e-06, 'epoch': 0.96}

 96%|█████████▋| 3436/3566 [2:18:50<05:09,  2.38s/it]
 96%|█████████▋| 3437/3566 [2:18:52<05:11,  2.42s/it]
                                                     
{'loss': 1.6749, 'learning_rate': 1.386841341230527e-06, 'epoch': 0.96}

 96%|█████████▋| 3437/3566 [2:18:52<05:11,  2.42s/it]
 96%|█████████▋| 3438/3566 [2:18:55<05:01,  2.36s/it]
                                                     
{'loss': 1.4901, 'learning_rate': 1.3656116027775723e-06, 'epoch': 0.96}

 96%|█████████▋| 3438/3566 [2:18:55<05:01,  2.36s/it]
 96%|█████████▋| 3439/3566 [2:18:57<04:58,  2.35s/it]
                                                     
{'loss': 1.4459, 'learning_rate': 1.344545055637525e-06, 'epoch': 0.96}

 96%|█████████▋| 3439/3566 [2:18:57<04:58,  2.35s/it]
 96%|█████████▋| 3440/3566 [2:18:59<04:51,  2.32s/it]
                                                     
{'loss': 1.4213, 'learning_rate': 1.3236417171179406e-06, 'epoch': 0.96}

 96%|█████████▋| 3440/3566 [2:18:59<04:51,  2.32s/it]
 96%|█████████▋| 3441/3566 [2:19:02<04:52,  2.34s/it]
                                                     
{'loss': 1.4448, 'learning_rate': 1.3029016043923037e-06, 'epoch': 0.96}

 96%|█████████▋| 3441/3566 [2:19:02<04:52,  2.34s/it]
 97%|█████████▋| 3442/3566 [2:19:04<05:03,  2.45s/it]
                                                     
{'loss': 1.3505, 'learning_rate': 1.2823247344999844e-06, 'epoch': 0.97}

 97%|█████████▋| 3442/3566 [2:19:04<05:03,  2.45s/it]
 97%|█████████▋| 3443/3566 [2:19:07<04:58,  2.43s/it]
                                                     
{'loss': 1.4386, 'learning_rate': 1.261911124346238e-06, 'epoch': 0.97}

 97%|█████████▋| 3443/3566 [2:19:07<04:58,  2.43s/it]
 97%|█████████▋| 3444/3566 [2:19:09<04:48,  2.36s/it]
                                                     
{'loss': 1.4924, 'learning_rate': 1.2416607907022038e-06, 'epoch': 0.97}

 97%|█████████▋| 3444/3566 [2:19:09<04:48,  2.36s/it]
 97%|█████████▋| 3445/3566 [2:19:11<04:41,  2.32s/it]
                                                     
{'loss': 1.3862, 'learning_rate': 1.2215737502048851e-06, 'epoch': 0.97}

 97%|█████████▋| 3445/3566 [2:19:11<04:41,  2.32s/it]
 97%|█████████▋| 3446/3566 [2:19:14<04:44,  2.37s/it]
                                                     
{'loss': 1.6755, 'learning_rate': 1.2016500193571035e-06, 'epoch': 0.97}

 97%|█████████▋| 3446/3566 [2:19:14<04:44,  2.37s/it]
 97%|█████████▋| 3447/3566 [2:19:16<04:40,  2.36s/it]
                                                     
{'loss': 1.462, 'learning_rate': 1.1818896145275426e-06, 'epoch': 0.97}

 97%|█████████▋| 3447/3566 [2:19:16<04:40,  2.36s/it]
 97%|█████████▋| 3448/3566 [2:19:18<04:28,  2.27s/it]
                                                     
{'loss': 1.4361, 'learning_rate': 1.162292551950639e-06, 'epoch': 0.97}

 97%|█████████▋| 3448/3566 [2:19:18<04:28,  2.27s/it]
 97%|█████████▋| 3449/3566 [2:19:21<04:34,  2.34s/it]
                                                     
{'loss': 1.4704, 'learning_rate': 1.1428588477267354e-06, 'epoch': 0.97}

 97%|█████████▋| 3449/3566 [2:19:21<04:34,  2.34s/it]
 97%|█████████▋| 3450/3566 [2:19:23<04:41,  2.42s/it]
                                                     
{'loss': 1.3827, 'learning_rate': 1.123588517821861e-06, 'epoch': 0.97}

 97%|█████████▋| 3450/3566 [2:19:23<04:41,  2.42s/it]
 97%|█████████▋| 3451/3566 [2:19:26<04:37,  2.41s/it]
                                                     
{'loss': 1.6365, 'learning_rate': 1.1044815780679063e-06, 'epoch': 0.97}

 97%|█████████▋| 3451/3566 [2:19:26<04:37,  2.41s/it]
 97%|█████████▋| 3452/3566 [2:19:28<04:33,  2.40s/it]
                                                     
{'loss': 1.5484, 'learning_rate': 1.0855380441624708e-06, 'epoch': 0.97}

 97%|█████████▋| 3452/3566 [2:19:28<04:33,  2.40s/it]
 97%|█████████▋| 3453/3566 [2:19:30<04:27,  2.37s/it]
                                                     
{'loss': 1.4412, 'learning_rate': 1.066757931668927e-06, 'epoch': 0.97}

 97%|█████████▋| 3453/3566 [2:19:30<04:27,  2.37s/it]
 97%|█████████▋| 3454/3566 [2:19:33<04:26,  2.38s/it]
                                                     
{'loss': 1.5537, 'learning_rate': 1.048141256016355e-06, 'epoch': 0.97}

 97%|█████████▋| 3454/3566 [2:19:33<04:26,  2.38s/it]
 97%|█████████▋| 3455/3566 [2:19:35<04:22,  2.36s/it]
                                                     
{'loss': 1.5172, 'learning_rate': 1.0296880324996316e-06, 'epoch': 0.97}

 97%|█████████▋| 3455/3566 [2:19:35<04:22,  2.36s/it]
 97%|█████████▋| 3456/3566 [2:19:37<04:25,  2.41s/it]
                                                     
{'loss': 1.6135, 'learning_rate': 1.011398276279274e-06, 'epoch': 0.97}

 97%|█████████▋| 3456/3566 [2:19:37<04:25,  2.41s/it]
 97%|█████████▋| 3457/3566 [2:19:40<04:27,  2.45s/it]
                                                     
{'loss': 1.6054, 'learning_rate': 9.93272002381529e-07, 'epoch': 0.97}

 97%|█████████▋| 3457/3566 [2:19:40<04:27,  2.45s/it]
 97%|█████████▋| 3458/3566 [2:19:43<04:29,  2.49s/it]
                                                     
{'loss': 1.5247, 'learning_rate': 9.753092256983508e-07, 'epoch': 0.97}

 97%|█████████▋| 3458/3566 [2:19:43<04:29,  2.49s/it]
 97%|█████████▋| 3459/3566 [2:19:46<04:50,  2.71s/it]
                                                     
{'loss': 1.5779, 'learning_rate': 9.575099609873351e-07, 'epoch': 0.97}

 97%|█████████▋| 3459/3566 [2:19:46<04:50,  2.71s/it]
 97%|█████████▋| 3460/3566 [2:19:48<04:37,  2.62s/it]
                                                     
{'loss': 1.5372, 'learning_rate': 9.398742228717616e-07, 'epoch': 0.97}

 97%|█████████▋| 3460/3566 [2:19:48<04:37,  2.62s/it]
 97%|█████████▋| 3461/3566 [2:19:50<04:22,  2.50s/it]
                                                     
{'loss': 1.5427, 'learning_rate': 9.224020258405741e-07, 'epoch': 0.97}

 97%|█████████▋| 3461/3566 [2:19:50<04:22,  2.50s/it]
 97%|█████████▋| 3462/3566 [2:19:53<04:20,  2.51s/it]
                                                     
{'loss': 1.4192, 'learning_rate': 9.050933842482901e-07, 'epoch': 0.97}

 97%|█████████▋| 3462/3566 [2:19:53<04:20,  2.51s/it]
 97%|█████████▋| 3463/3566 [2:19:56<04:19,  2.52s/it]
                                                     
{'loss': 1.4422, 'learning_rate': 8.879483123151789e-07, 'epoch': 0.97}

 97%|█████████▋| 3463/3566 [2:19:56<04:19,  2.52s/it]
 97%|█████████▋| 3464/3566 [2:19:58<04:13,  2.48s/it]
                                                     
{'loss': 1.5037, 'learning_rate': 8.709668241269953e-07, 'epoch': 0.97}

 97%|█████████▋| 3464/3566 [2:19:58<04:13,  2.48s/it]
 97%|█████████▋| 3465/3566 [2:20:00<04:04,  2.42s/it]
                                                     
{'loss': 1.5843, 'learning_rate': 8.541489336351571e-07, 'epoch': 0.97}

 97%|█████████▋| 3465/3566 [2:20:00<04:04,  2.42s/it]
 97%|█████████▋| 3466/3566 [2:20:03<04:01,  2.41s/it]
                                                     
{'loss': 1.6583, 'learning_rate': 8.374946546567231e-07, 'epoch': 0.97}

 97%|█████████▋| 3466/3566 [2:20:03<04:01,  2.41s/it]
 97%|█████████▋| 3467/3566 [2:20:05<04:00,  2.43s/it]
                                                     
{'loss': 1.3924, 'learning_rate': 8.210040008742371e-07, 'epoch': 0.97}

 97%|█████████▋| 3467/3566 [2:20:05<04:00,  2.43s/it]
 97%|█████████▋| 3468/3566 [2:20:08<04:02,  2.47s/it]
                                                     
{'loss': 1.6724, 'learning_rate': 8.046769858359061e-07, 'epoch': 0.97}

 97%|█████████▋| 3468/3566 [2:20:08<04:02,  2.47s/it]
 97%|█████████▋| 3469/3566 [2:20:10<03:57,  2.45s/it]
                                                     
{'loss': 1.3547, 'learning_rate': 7.885136229554224e-07, 'epoch': 0.97}

 97%|█████████▋| 3469/3566 [2:20:10<03:57,  2.45s/it]
 97%|█████████▋| 3470/3566 [2:20:13<03:59,  2.50s/it]
                                                     
{'loss': 1.5561, 'learning_rate': 7.725139255120751e-07, 'epoch': 0.97}

 97%|█████████▋| 3470/3566 [2:20:13<03:59,  2.50s/it]
 97%|█████████▋| 3471/3566 [2:20:15<03:47,  2.39s/it]
                                                     
{'loss': 1.4845, 'learning_rate': 7.566779066506823e-07, 'epoch': 0.97}

 97%|█████████▋| 3471/3566 [2:20:15<03:47,  2.39s/it]
 97%|█████████▋| 3472/3566 [2:20:17<03:50,  2.45s/it]
                                                     
{'loss': 1.4361, 'learning_rate': 7.410055793815484e-07, 'epoch': 0.97}

 97%|█████████▋| 3472/3566 [2:20:17<03:50,  2.45s/it]
 97%|█████████▋| 3473/3566 [2:20:20<03:42,  2.39s/it]
                                                     
{'loss': 1.7652, 'learning_rate': 7.254969565805736e-07, 'epoch': 0.97}

 97%|█████████▋| 3473/3566 [2:20:20<03:42,  2.39s/it]
 97%|█████████▋| 3474/3566 [2:20:22<03:43,  2.43s/it]
                                                     
{'loss': 1.4927, 'learning_rate': 7.101520509890991e-07, 'epoch': 0.97}

 97%|█████████▋| 3474/3566 [2:20:22<03:43,  2.43s/it]
 97%|█████████▋| 3475/3566 [2:20:25<03:44,  2.47s/it]
                                                     
{'loss': 1.446, 'learning_rate': 6.949708752139739e-07, 'epoch': 0.97}

 97%|█████████▋| 3475/3566 [2:20:25<03:44,  2.47s/it]
 97%|█████████▋| 3476/3566 [2:20:27<03:34,  2.38s/it]
                                                     
{'loss': 1.581, 'learning_rate': 6.799534417275322e-07, 'epoch': 0.97}

 97%|█████████▋| 3476/3566 [2:20:27<03:34,  2.38s/it]
 98%|█████████▊| 3477/3566 [2:20:30<03:43,  2.52s/it]
                                                     
{'loss': 1.5517, 'learning_rate': 6.650997628676159e-07, 'epoch': 0.98}

 98%|█████████▊| 3477/3566 [2:20:30<03:43,  2.52s/it]
 98%|█████████▊| 3478/3566 [2:20:32<03:42,  2.52s/it]
                                                     
{'loss': 1.4101, 'learning_rate': 6.504098508375078e-07, 'epoch': 0.98}

 98%|█████████▊| 3478/3566 [2:20:32<03:42,  2.52s/it]
 98%|█████████▊| 3479/3566 [2:20:35<03:44,  2.58s/it]
                                                     
{'loss': 1.616, 'learning_rate': 6.358837177059318e-07, 'epoch': 0.98}

 98%|█████████▊| 3479/3566 [2:20:35<03:44,  2.58s/it]
 98%|█████████▊| 3480/3566 [2:20:37<03:31,  2.46s/it]
                                                     
{'loss': 1.4319, 'learning_rate': 6.215213754070748e-07, 'epoch': 0.98}

 98%|█████████▊| 3480/3566 [2:20:37<03:31,  2.46s/it]
 98%|█████████▊| 3481/3566 [2:20:39<03:20,  2.36s/it]
                                                     
{'loss': 1.3664, 'learning_rate': 6.073228357405425e-07, 'epoch': 0.98}

 98%|█████████▊| 3481/3566 [2:20:39<03:20,  2.36s/it]
 98%|█████████▊| 3482/3566 [2:20:42<03:22,  2.41s/it]
                                                     
{'loss': 1.6087, 'learning_rate': 5.932881103713594e-07, 'epoch': 0.98}

 98%|█████████▊| 3482/3566 [2:20:42<03:22,  2.41s/it]
 98%|█████████▊| 3483/3566 [2:20:44<03:18,  2.39s/it]
                                                     
{'loss': 1.2862, 'learning_rate': 5.794172108300355e-07, 'epoch': 0.98}

 98%|█████████▊| 3483/3566 [2:20:44<03:18,  2.39s/it]
 98%|█████████▊| 3484/3566 [2:20:46<03:12,  2.35s/it]
                                                     
{'loss': 1.5419, 'learning_rate': 5.657101485123883e-07, 'epoch': 0.98}

 98%|█████████▊| 3484/3566 [2:20:46<03:12,  2.35s/it]
 98%|█████████▊| 3485/3566 [2:20:49<03:13,  2.39s/it]
                                                     
{'loss': 1.6036, 'learning_rate': 5.521669346796987e-07, 'epoch': 0.98}

 98%|█████████▊| 3485/3566 [2:20:49<03:13,  2.39s/it]
 98%|█████████▊| 3486/3566 [2:20:51<03:12,  2.40s/it]
                                                     
{'loss': 1.4694, 'learning_rate': 5.387875804585996e-07, 'epoch': 0.98}

 98%|█████████▊| 3486/3566 [2:20:51<03:12,  2.40s/it]
 98%|█████████▊| 3487/3566 [2:20:54<03:08,  2.38s/it]
                                                     
{'loss': 1.579, 'learning_rate': 5.255720968411426e-07, 'epoch': 0.98}

 98%|█████████▊| 3487/3566 [2:20:54<03:08,  2.38s/it]
 98%|█████████▊| 3488/3566 [2:20:56<03:08,  2.42s/it]
                                                     
{'loss': 1.4756, 'learning_rate': 5.125204946846873e-07, 'epoch': 0.98}

 98%|█████████▊| 3488/3566 [2:20:56<03:08,  2.42s/it]
 98%|█████████▊| 3489/3566 [2:20:58<03:03,  2.38s/it]
                                                     
{'loss': 1.4366, 'learning_rate': 4.996327847120119e-07, 'epoch': 0.98}

 98%|█████████▊| 3489/3566 [2:20:58<03:03,  2.38s/it]
 98%|█████████▊| 3490/3566 [2:21:01<02:57,  2.33s/it]
                                                     
{'loss': 1.4537, 'learning_rate': 4.869089775112245e-07, 'epoch': 0.98}

 98%|█████████▊| 3490/3566 [2:21:01<02:57,  2.33s/it]
 98%|█████████▊| 3491/3566 [2:21:03<02:56,  2.36s/it]
                                                     
{'loss': 1.574, 'learning_rate': 4.7434908353578557e-07, 'epoch': 0.98}

 98%|█████████▊| 3491/3566 [2:21:03<02:56,  2.36s/it]
 98%|█████████▊| 3492/3566 [2:21:05<02:50,  2.31s/it]
                                                     
{'loss': 1.5245, 'learning_rate': 4.619531131044408e-07, 'epoch': 0.98}

 98%|█████████▊| 3492/3566 [2:21:05<02:50,  2.31s/it]
 98%|█████████▊| 3493/3566 [2:21:08<02:51,  2.35s/it]
                                                     
{'loss': 1.5708, 'learning_rate': 4.497210764013549e-07, 'epoch': 0.98}

 98%|█████████▊| 3493/3566 [2:21:08<02:51,  2.35s/it]
 98%|█████████▊| 3494/3566 [2:21:10<02:54,  2.42s/it]
                                                     
{'loss': 1.4172, 'learning_rate': 4.376529834759113e-07, 'epoch': 0.98}

 98%|█████████▊| 3494/3566 [2:21:10<02:54,  2.42s/it]
 98%|█████████▊| 3495/3566 [2:21:13<02:59,  2.53s/it]
                                                     
{'loss': 1.5128, 'learning_rate': 4.257488442428681e-07, 'epoch': 0.98}

 98%|█████████▊| 3495/3566 [2:21:13<02:59,  2.53s/it]
 98%|█████████▊| 3496/3566 [2:21:15<02:47,  2.39s/it]
                                                     
{'loss': 1.3207, 'learning_rate': 4.140086684822686e-07, 'epoch': 0.98}

 98%|█████████▊| 3496/3566 [2:21:15<02:47,  2.39s/it]
 98%|█████████▊| 3497/3566 [2:21:17<02:40,  2.32s/it]
                                                     
{'loss': 1.4167, 'learning_rate': 4.024324658394418e-07, 'epoch': 0.98}

 98%|█████████▊| 3497/3566 [2:21:17<02:40,  2.32s/it]
 98%|█████████▊| 3498/3566 [2:21:20<02:40,  2.36s/it]
                                                     
{'loss': 1.6103, 'learning_rate': 3.910202458250023e-07, 'epoch': 0.98}

 98%|█████████▊| 3498/3566 [2:21:20<02:40,  2.36s/it]
 98%|█████████▊| 3499/3566 [2:21:22<02:39,  2.38s/it]
                                                     
{'loss': 1.3836, 'learning_rate': 3.7977201781482783e-07, 'epoch': 0.98}

 98%|█████████▊| 3499/3566 [2:21:22<02:39,  2.38s/it]
 98%|█████████▊| 3500/3566 [2:21:25<02:37,  2.39s/it]
                                                     
{'loss': 1.5531, 'learning_rate': 3.686877910501263e-07, 'epoch': 0.98}

 98%|█████████▊| 3500/3566 [2:21:25<02:37,  2.39s/it]
 98%|█████████▊| 3501/3566 [2:21:27<02:32,  2.34s/it]
                                                     
{'loss': 1.515, 'learning_rate': 3.5776757463727995e-07, 'epoch': 0.98}

 98%|█████████▊| 3501/3566 [2:21:27<02:32,  2.34s/it]
 98%|█████████▊| 3502/3566 [2:21:29<02:25,  2.28s/it]
                                                     
{'loss': 1.3906, 'learning_rate': 3.4701137754800104e-07, 'epoch': 0.98}

 98%|█████████▊| 3502/3566 [2:21:29<02:25,  2.28s/it]
 98%|█████████▊| 3503/3566 [2:21:31<02:28,  2.35s/it]
                                                     
{'loss': 1.583, 'learning_rate': 3.3641920861919864e-07, 'epoch': 0.98}

 98%|█████████▊| 3503/3566 [2:21:31<02:28,  2.35s/it]
 98%|█████████▊| 3504/3566 [2:21:34<02:27,  2.38s/it]
                                                     
{'loss': 1.5643, 'learning_rate': 3.2599107655304497e-07, 'epoch': 0.98}

 98%|█████████▊| 3504/3566 [2:21:34<02:27,  2.38s/it]
 98%|█████████▊| 3505/3566 [2:21:36<02:22,  2.33s/it]
                                                     
{'loss': 1.6637, 'learning_rate': 3.1572698991695347e-07, 'epoch': 0.98}

 98%|█████████▊| 3505/3566 [2:21:36<02:22,  2.33s/it]
 98%|█████████▊| 3506/3566 [2:21:38<02:17,  2.29s/it]
                                                     
{'loss': 1.4715, 'learning_rate': 3.056269571435566e-07, 'epoch': 0.98}

 98%|█████████▊| 3506/3566 [2:21:38<02:17,  2.29s/it]
 98%|█████████▊| 3507/3566 [2:21:41<02:19,  2.36s/it]
                                                     
{'loss': 1.5305, 'learning_rate': 2.9569098653066116e-07, 'epoch': 0.98}

 98%|█████████▊| 3507/3566 [2:21:41<02:19,  2.36s/it]
 98%|█████████▊| 3508/3566 [2:21:43<02:17,  2.37s/it]
                                                     
{'loss': 1.3692, 'learning_rate': 2.8591908624138187e-07, 'epoch': 0.98}

 98%|█████████▊| 3508/3566 [2:21:43<02:17,  2.37s/it]
 98%|█████████▊| 3509/3566 [2:21:46<02:15,  2.37s/it]
                                                     
{'loss': 1.5654, 'learning_rate': 2.8591908624138187e-07, 'epoch': 0.98}

 98%|█████████▊| 3509/3566 [2:21:46<02:15,  2.37s/it]
 98%|█████████▊| 3510/3566 [2:21:50<02:38,  2.83s/it]
                                                     
{'loss': 1.5345, 'learning_rate': 2.7631126430391896e-07, 'epoch': 0.98}

 98%|█████████▊| 3510/3566 [2:21:50<02:38,  2.83s/it]
 98%|█████████▊| 3511/3566 [2:21:52<02:22,  2.60s/it]
                                                     
{'loss': 1.4294, 'learning_rate': 2.668675286118028e-07, 'epoch': 0.98}

 98%|█████████▊| 3511/3566 [2:21:52<02:22,  2.60s/it]
 98%|█████████▊| 3512/3566 [2:21:54<02:14,  2.49s/it]
                                                     
{'loss': 1.4049, 'learning_rate': 2.57587886923627e-07, 'epoch': 0.98}

 98%|█████████▊| 3512/3566 [2:21:54<02:14,  2.49s/it]
 99%|█████████▊| 3513/3566 [2:21:56<02:10,  2.47s/it]
                                                     
{'loss': 1.6169, 'learning_rate': 2.4847234686327103e-07, 'epoch': 0.99}

 99%|█████████▊| 3513/3566 [2:21:56<02:10,  2.47s/it]
 99%|█████████▊| 3514/3566 [2:21:59<02:08,  2.46s/it]
                                                     
{'loss': 1.5927, 'learning_rate': 2.395209159197442e-07, 'epoch': 0.99}

 99%|█████████▊| 3514/3566 [2:21:59<02:08,  2.46s/it]
 99%|█████████▊| 3515/3566 [2:22:01<02:05,  2.46s/it]
                                                     
{'loss': 1.4435, 'learning_rate': 2.3073360144723055e-07, 'epoch': 0.99}

 99%|█████████▊| 3515/3566 [2:22:01<02:05,  2.46s/it]
 99%|█████████▊| 3516/3566 [2:22:03<01:59,  2.40s/it]
                                                     
{'loss': 1.5409, 'learning_rate': 2.2211041066511063e-07, 'epoch': 0.99}

 99%|█████████▊| 3516/3566 [2:22:03<01:59,  2.40s/it]
 99%|█████████▊| 3517/3566 [2:22:06<01:56,  2.38s/it]
                                                     
{'loss': 1.6436, 'learning_rate': 2.136513506578952e-07, 'epoch': 0.99}

 99%|█████████▊| 3517/3566 [2:22:06<01:56,  2.38s/it]
 99%|█████████▊| 3518/3566 [2:22:08<01:52,  2.35s/it]
                                                     
{'loss': 1.5028, 'learning_rate': 2.0535642837524737e-07, 'epoch': 0.99}

 99%|█████████▊| 3518/3566 [2:22:08<01:52,  2.35s/it]
 99%|█████████▊| 3519/3566 [2:22:10<01:49,  2.34s/it]
                                                     
{'loss': 1.5051, 'learning_rate': 1.9722565063202692e-07, 'epoch': 0.99}

 99%|█████████▊| 3519/3566 [2:22:10<01:49,  2.34s/it]
 99%|█████████▊| 3520/3566 [2:22:13<01:49,  2.37s/it]
                                                     
{'loss': 1.4315, 'learning_rate': 1.892590241081793e-07, 'epoch': 0.99}

 99%|█████████▊| 3520/3566 [2:22:13<01:49,  2.37s/it]
 99%|█████████▊| 3521/3566 [2:22:15<01:48,  2.42s/it]
                                                     
{'loss': 1.5972, 'learning_rate': 1.8145655534884677e-07, 'epoch': 0.99}

 99%|█████████▊| 3521/3566 [2:22:15<01:48,  2.42s/it]
 99%|█████████▉| 3522/3566 [2:22:18<01:47,  2.44s/it]
                                                     
{'loss': 1.6682, 'learning_rate': 1.7381825076423496e-07, 'epoch': 0.99}

 99%|█████████▉| 3522/3566 [2:22:18<01:47,  2.44s/it]
 99%|█████████▉| 3523/3566 [2:22:20<01:46,  2.48s/it]
                                                     
{'loss': 1.5304, 'learning_rate': 1.6634411662974636e-07, 'epoch': 0.99}

 99%|█████████▉| 3523/3566 [2:22:20<01:46,  2.48s/it]
 99%|█████████▉| 3524/3566 [2:22:22<01:39,  2.38s/it]
                                                     
{'loss': 1.4766, 'learning_rate': 1.5903415908586904e-07, 'epoch': 0.99}

 99%|█████████▉| 3524/3566 [2:22:22<01:39,  2.38s/it]
 99%|█████████▉| 3525/3566 [2:22:25<01:38,  2.41s/it]
                                                     
{'loss': 1.5359, 'learning_rate': 1.5188838413822125e-07, 'epoch': 0.99}

 99%|█████████▉| 3525/3566 [2:22:25<01:38,  2.41s/it]
 99%|█████████▉| 3526/3566 [2:22:27<01:35,  2.40s/it]
                                                     
{'loss': 1.571, 'learning_rate': 1.4490679765752912e-07, 'epoch': 0.99}

 99%|█████████▉| 3526/3566 [2:22:27<01:35,  2.40s/it]
 99%|█████████▉| 3527/3566 [2:22:30<01:34,  2.41s/it]
                                                     
{'loss': 1.4588, 'learning_rate': 1.3808940537962667e-07, 'epoch': 0.99}

 99%|█████████▉| 3527/3566 [2:22:30<01:34,  2.41s/it]
 99%|█████████▉| 3528/3566 [2:22:32<01:31,  2.41s/it]
                                                     
{'loss': 1.4271, 'learning_rate': 1.314362129054336e-07, 'epoch': 0.99}

 99%|█████████▉| 3528/3566 [2:22:32<01:31,  2.41s/it]
 99%|█████████▉| 3529/3566 [2:22:35<01:28,  2.39s/it]
                                                     
{'loss': 1.3924, 'learning_rate': 1.2494722570102203e-07, 'epoch': 0.99}

 99%|█████████▉| 3529/3566 [2:22:35<01:28,  2.39s/it]
 99%|█████████▉| 3530/3566 [2:22:37<01:28,  2.45s/it]
                                                     
{'loss': 1.4746, 'learning_rate': 1.186224490975274e-07, 'epoch': 0.99}

 99%|█████████▉| 3530/3566 [2:22:37<01:28,  2.45s/it]
 99%|█████████▉| 3531/3566 [2:22:40<01:32,  2.64s/it]
                                                     
{'loss': 1.5209, 'learning_rate': 1.1246188829112658e-07, 'epoch': 0.99}

 99%|█████████▉| 3531/3566 [2:22:40<01:32,  2.64s/it]
 99%|█████████▉| 3532/3566 [2:22:43<01:27,  2.58s/it]
                                                     
{'loss': 1.6361, 'learning_rate': 1.0646554834317091e-07, 'epoch': 0.99}

 99%|█████████▉| 3532/3566 [2:22:43<01:27,  2.58s/it]
 99%|█████████▉| 3533/3566 [2:22:45<01:25,  2.59s/it]
                                                     
{'loss': 1.4542, 'learning_rate': 1.00633434180053e-07, 'epoch': 0.99}

 99%|█████████▉| 3533/3566 [2:22:45<01:25,  2.59s/it]
 99%|█████████▉| 3534/3566 [2:22:48<01:20,  2.53s/it]
                                                     
{'loss': 1.5201, 'learning_rate': 9.496555059320678e-08, 'epoch': 0.99}

 99%|█████████▉| 3534/3566 [2:22:48<01:20,  2.53s/it]
 99%|█████████▉| 3535/3566 [2:22:50<01:15,  2.45s/it]
                                                     
{'loss': 1.4941, 'learning_rate': 8.946190223919625e-08, 'epoch': 0.99}

 99%|█████████▉| 3535/3566 [2:22:50<01:15,  2.45s/it]
 99%|█████████▉| 3536/3566 [2:22:52<01:11,  2.37s/it]
                                                     
{'loss': 1.372, 'learning_rate': 8.412249363964897e-08, 'epoch': 0.99}

 99%|█████████▉| 3536/3566 [2:22:52<01:11,  2.37s/it]
 99%|█████████▉| 3537/3566 [2:22:55<01:10,  2.42s/it]
                                                     
{'loss': 1.4338, 'learning_rate': 7.89473291812115e-08, 'epoch': 0.99}

 99%|█████████▉| 3537/3566 [2:22:55<01:10,  2.42s/it]
 99%|█████████▉| 3538/3566 [2:22:57<01:08,  2.43s/it]
                                                     
{'loss': 1.5457, 'learning_rate': 7.393641311563836e-08, 'epoch': 0.99}

 99%|█████████▉| 3538/3566 [2:22:57<01:08,  2.43s/it]
 99%|█████████▉| 3539/3566 [2:23:00<01:12,  2.67s/it]
                                                     
{'loss': 1.4418, 'learning_rate': 6.908974955972536e-08, 'epoch': 0.99}

 99%|█████████▉| 3539/3566 [2:23:00<01:12,  2.67s/it]
 99%|█████████▉| 3540/3566 [2:23:03<01:07,  2.61s/it]
                                                     
{'loss': 1.525, 'learning_rate': 6.440734249533176e-08, 'epoch': 0.99}

 99%|█████████▉| 3540/3566 [2:23:03<01:07,  2.61s/it]
 99%|█████████▉| 3541/3566 [2:23:05<01:03,  2.53s/it]
                                                     
{'loss': 1.5667, 'learning_rate': 5.988919576935814e-08, 'epoch': 0.99}

 99%|█████████▉| 3541/3566 [2:23:05<01:03,  2.53s/it]
 99%|█████████▉| 3542/3566 [2:23:07<00:59,  2.48s/it]
                                                     
{'loss': 1.7043, 'learning_rate': 5.553531309376858e-08, 'epoch': 0.99}

 99%|█████████▉| 3542/3566 [2:23:07<00:59,  2.48s/it]
 99%|█████████▉| 3543/3566 [2:23:10<00:57,  2.51s/it]
                                                     
{'loss': 1.4271, 'learning_rate': 5.134569804559064e-08, 'epoch': 0.99}

 99%|█████████▉| 3543/3566 [2:23:10<00:57,  2.51s/it]
 99%|█████████▉| 3544/3566 [2:23:12<00:52,  2.39s/it]
                                                     
{'loss': 1.4136, 'learning_rate': 4.7320354066826555e-08, 'epoch': 0.99}

 99%|█████████▉| 3544/3566 [2:23:12<00:52,  2.39s/it]
 99%|█████████▉| 3545/3566 [2:23:15<00:52,  2.49s/it]
                                                     
{'loss': 1.6156, 'learning_rate': 4.345928446456426e-08, 'epoch': 0.99}

 99%|█████████▉| 3545/3566 [2:23:15<00:52,  2.49s/it]
 99%|█████████▉| 3546/3566 [2:23:18<00:50,  2.54s/it]
                                                     
{'loss': 1.5119, 'learning_rate': 3.97624924109774e-08, 'epoch': 0.99}

 99%|█████████▉| 3546/3566 [2:23:18<00:50,  2.54s/it]
 99%|█████████▉| 3547/3566 [2:23:20<00:47,  2.50s/it]
                                                     
{'loss': 1.6061, 'learning_rate': 3.622998094316987e-08, 'epoch': 0.99}

 99%|█████████▉| 3547/3566 [2:23:20<00:47,  2.50s/it]
 99%|█████████▉| 3548/3566 [2:23:22<00:44,  2.45s/it]
                                                     
{'loss': 1.5301, 'learning_rate': 3.286175296337568e-08, 'epoch': 0.99}

 99%|█████████▉| 3548/3566 [2:23:22<00:44,  2.45s/it]
100%|█████████▉| 3549/3566 [2:23:25<00:40,  2.41s/it]
                                                     
{'loss': 1.546, 'learning_rate': 2.9657811238803512e-08, 'epoch': 1.0}

100%|█████████▉| 3549/3566 [2:23:25<00:40,  2.41s/it]
100%|█████████▉| 3550/3566 [2:23:27<00:37,  2.36s/it]
                                                     
{'loss': 1.4117, 'learning_rate': 2.6618158401681137e-08, 'epoch': 1.0}

100%|█████████▉| 3550/3566 [2:23:27<00:37,  2.36s/it]
100%|█████████▉| 3551/3566 [2:23:29<00:36,  2.41s/it]
                                                     
{'loss': 1.5575, 'learning_rate': 2.3742796949322023e-08, 'epoch': 1.0}

100%|█████████▉| 3551/3566 [2:23:29<00:36,  2.41s/it]
100%|█████████▉| 3552/3566 [2:23:32<00:33,  2.39s/it]
                                                     
{'loss': 1.4982, 'learning_rate': 2.1031729243992104e-08, 'epoch': 1.0}

100%|█████████▉| 3552/3566 [2:23:32<00:33,  2.39s/it]
100%|█████████▉| 3553/3566 [2:23:34<00:32,  2.50s/it]
                                                     
{'loss': 1.3424, 'learning_rate': 1.848495751304302e-08, 'epoch': 1.0}

100%|█████████▉| 3553/3566 [2:23:34<00:32,  2.50s/it]
100%|█████████▉| 3554/3566 [2:23:37<00:28,  2.40s/it]
                                                     
{'loss': 1.5036, 'learning_rate': 1.6102483848801088e-08, 'epoch': 1.0}

100%|█████████▉| 3554/3566 [2:23:37<00:28,  2.40s/it]
100%|█████████▉| 3555/3566 [2:23:39<00:26,  2.41s/it]
                                                     
{'loss': 1.6478, 'learning_rate': 1.3884310208611695e-08, 'epoch': 1.0}

100%|█████████▉| 3555/3566 [2:23:39<00:26,  2.41s/it]
100%|█████████▉| 3556/3566 [2:23:41<00:23,  2.39s/it]
                                                     
{'loss': 1.5889, 'learning_rate': 1.1830438414883739e-08, 'epoch': 1.0}

100%|█████████▉| 3556/3566 [2:23:41<00:23,  2.39s/it]
100%|█████████▉| 3557/3566 [2:23:44<00:21,  2.35s/it]
                                                     
{'loss': 1.474, 'learning_rate': 9.94087015500078e-09, 'epoch': 1.0}

100%|█████████▉| 3557/3566 [2:23:44<00:21,  2.35s/it]
100%|█████████▉| 3558/3566 [2:23:46<00:18,  2.35s/it]
                                                     
{'loss': 1.42, 'learning_rate': 8.215606981343272e-09, 'epoch': 1.0}

100%|█████████▉| 3558/3566 [2:23:46<00:18,  2.35s/it]
100%|█████████▉| 3559/3566 [2:23:48<00:16,  2.32s/it]
                                                     
{'loss': 1.5487, 'learning_rate': 6.654650311355148e-09, 'epoch': 1.0}

100%|█████████▉| 3559/3566 [2:23:48<00:16,  2.32s/it]
100%|█████████▉| 3560/3566 [2:23:50<00:13,  2.23s/it]
                                                     
{'loss': 1.5105, 'learning_rate': 5.258001427455028e-09, 'epoch': 1.0}

100%|█████████▉| 3560/3566 [2:23:50<00:13,  2.23s/it]
100%|█████████▉| 3561/3566 [2:23:53<00:11,  2.25s/it]
                                                     
{'loss': 1.55, 'learning_rate': 4.0256614770806115e-09, 'epoch': 1.0}

100%|█████████▉| 3561/3566 [2:23:53<00:11,  2.25s/it]
100%|█████████▉| 3562/3566 [2:23:55<00:09,  2.27s/it]
                                                     
{'loss': 1.5311, 'learning_rate': 2.9576314726886823e-09, 'epoch': 1.0}

100%|█████████▉| 3562/3566 [2:23:55<00:09,  2.27s/it]
100%|█████████▉| 3563/3566 [2:23:57<00:06,  2.27s/it]
                                                     
{'loss': 1.3907, 'learning_rate': 2.0539122917329066e-09, 'epoch': 1.0}

100%|█████████▉| 3563/3566 [2:23:57<00:06,  2.27s/it]
100%|█████████▉| 3564/3566 [2:24:00<00:04,  2.35s/it]
                                                     
{'loss': 1.4404, 'learning_rate': 1.3145046766638302e-09, 'epoch': 1.0}

100%|█████████▉| 3564/3566 [2:24:00<00:04,  2.35s/it]
100%|█████████▉| 3565/3566 [2:24:02<00:02,  2.39s/it]
                                                     
{'loss': 1.4876, 'learning_rate': 7.394092349954918e-10, 'epoch': 1.0}

100%|█████████▉| 3565/3566 [2:24:02<00:02,  2.39s/it]
100%|██████████| 3566/3566 [2:24:05<00:00,  2.42s/it]
                                                     
{'loss': 1.5456, 'learning_rate': 3.286264391499927e-10, 'epoch': 1.0}

100%|██████████| 3566/3566 [2:24:05<00:00,  2.42s/it]
                                                     
{'train_runtime': 8652.9663, 'train_samples_per_second': 13.187, 'train_steps_per_second': 0.412, 'train_loss': 1.5701122180304363, 'epoch': 1.0}

100%|██████████| 3566/3566 [2:24:05<00:00,  2.42s/it]
100%|██████████| 3566/3566 [2:24:05<00:00,  2.42s/it]
wandb: 
wandb: Run history:
wandb:                    train/epoch ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
wandb:              train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███
wandb:            train/learning_rate ▃███████▇▇▇▇▇▆▆▆▆▅▅▅▅▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁
wandb:                     train/loss █▇▆█▄▄▆█▅▇▆▃▂▅▃▃▃▂▇▃▅▃▃▅█▁▁▅▃▄▂▆▄▆▃▃▄▂▅▃
wandb:               train/total_flos ▁
wandb:               train/train_loss ▁
wandb:            train/train_runtime ▁
wandb: train/train_samples_per_second ▁
wandb:   train/train_steps_per_second ▁
wandb: 
wandb: Run summary:
wandb:                    train/epoch 1.0
wandb:              train/global_step 3566
wandb:            train/learning_rate 0.0
wandb:                     train/loss 1.5456
wandb:               train/total_flos 9.196674453738619e+17
wandb:               train/train_loss 1.57011
wandb:            train/train_runtime 8652.9663
wandb: train/train_samples_per_second 13.187
wandb:   train/train_steps_per_second 0.412
wandb: 
wandb: 🚀 View run belle_dolphine-p19 at: https://wandb.ai/nus_keyu/lora-moe/runs/nnsx4ee7
wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
wandb: Find logs at: ./wandb/run-20231230_053311-nnsx4ee7/logs