| 2022-02-05 01:08:47,419 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:08:47,461 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): RobertaModel( | |
| (embeddings): RobertaEmbeddings( | |
| (word_embeddings): Embedding(32768, 768, padding_idx=1) | |
| (position_embeddings): Embedding(514, 768, padding_idx=1) | |
| (token_type_embeddings): Embedding(1, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): RobertaEncoder( | |
| (layer): ModuleList( | |
| (0): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (1): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (2): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (3): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (4): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (5): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (6): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (7): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (8): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (9): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (10): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (11): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): RobertaPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (word_dropout): WordDropout(p=0.05) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=18, bias=True) | |
| (beta): 1.0 | |
| (weights): None | |
| (weight_tensor) None | |
| )" | |
| 2022-02-05 01:08:47,466 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:08:47,466 Corpus: "Corpus: 126973 train + 7037 dev + 7090 test sentences" | |
| 2022-02-05 01:08:47,466 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:08:47,466 Parameters: | |
| 2022-02-05 01:08:47,466 - learning_rate: "5e-05" | |
| 2022-02-05 01:08:47,466 - mini_batch_size: "16" | |
| 2022-02-05 01:08:47,466 - patience: "3" | |
| 2022-02-05 01:08:47,466 - anneal_factor: "0.5" | |
| 2022-02-05 01:08:47,466 - max_epochs: "10" | |
| 2022-02-05 01:08:47,466 - shuffle: "True" | |
| 2022-02-05 01:08:47,466 - train_with_dev: "False" | |
| 2022-02-05 01:08:47,466 - batch_growth_annealing: "False" | |
| 2022-02-05 01:08:47,466 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:08:47,466 Model training base path: "resources/taggers/ner-dalembert-2ndtry" | |
| 2022-02-05 01:08:47,466 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:08:47,466 Device: cuda:0 | |
| 2022-02-05 01:08:47,466 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:08:47,467 Embeddings storage mode: none | |
| 2022-02-05 01:08:47,469 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 01:15:08,771 epoch 1 - iter 793/7936 - loss 0.78007372 - samples/sec: 33.28 - lr: 0.000005 | |
| 2022-02-05 01:22:45,940 epoch 1 - iter 1586/7936 - loss 0.41932043 - samples/sec: 27.76 - lr: 0.000010 | |
| 2022-02-05 01:29:23,897 epoch 1 - iter 2379/7936 - loss 0.33514542 - samples/sec: 31.89 - lr: 0.000015 | |
| 2022-02-05 01:35:24,915 epoch 1 - iter 3172/7936 - loss 0.30212998 - samples/sec: 35.15 - lr: 0.000020 | |
| 2022-02-05 01:42:28,297 epoch 1 - iter 3965/7936 - loss 0.27341208 - samples/sec: 29.97 - lr: 0.000025 | |
| 2022-02-05 01:49:23,543 epoch 1 - iter 4758/7936 - loss 0.25403588 - samples/sec: 30.56 - lr: 0.000030 | |
| 2022-02-05 01:55:46,783 epoch 1 - iter 5551/7936 - loss 0.24241496 - samples/sec: 33.11 - lr: 0.000035 | |
| 2022-02-05 02:01:45,654 epoch 1 - iter 6344/7936 - loss 0.23381719 - samples/sec: 35.36 - lr: 0.000040 | |
| 2022-02-05 02:07:29,407 epoch 1 - iter 7137/7936 - loss 0.22586308 - samples/sec: 36.92 - lr: 0.000045 | |
| 2022-02-05 02:13:54,603 epoch 1 - iter 7930/7936 - loss 0.21834611 - samples/sec: 32.94 - lr: 0.000050 | |
| 2022-02-05 02:13:57,692 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 02:13:57,693 EPOCH 1 done: loss 0.2183 - lr 0.0000500 | |
| 2022-02-05 02:16:47,190 DEV : loss 0.0355144739151001 - f1-score (micro avg) 0.8254 | |
| 2022-02-05 02:16:47,244 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 02:16:47,244 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 02:23:15,435 epoch 2 - iter 793/7936 - loss 0.14903310 - samples/sec: 32.69 - lr: 0.000049 | |
| 2022-02-05 02:30:06,605 epoch 2 - iter 1586/7936 - loss 0.14777394 - samples/sec: 30.86 - lr: 0.000049 | |
| 2022-02-05 02:36:48,570 epoch 2 - iter 2379/7936 - loss 0.14637300 - samples/sec: 31.57 - lr: 0.000048 | |
| 2022-02-05 02:43:37,172 epoch 2 - iter 3172/7936 - loss 0.14491485 - samples/sec: 31.06 - lr: 0.000048 | |
| 2022-02-05 02:50:13,040 epoch 2 - iter 3965/7936 - loss 0.14361996 - samples/sec: 32.06 - lr: 0.000047 | |
| 2022-02-05 02:56:49,904 epoch 2 - iter 4758/7936 - loss 0.14232123 - samples/sec: 31.98 - lr: 0.000047 | |
| 2022-02-05 03:03:34,383 epoch 2 - iter 5551/7936 - loss 0.14116820 - samples/sec: 31.38 - lr: 0.000046 | |
| 2022-02-05 03:10:09,778 epoch 2 - iter 6344/7936 - loss 0.14001072 - samples/sec: 32.10 - lr: 0.000046 | |
| 2022-02-05 03:16:43,847 epoch 2 - iter 7137/7936 - loss 0.13868572 - samples/sec: 32.20 - lr: 0.000045 | |
| 2022-02-05 03:23:28,994 epoch 2 - iter 7930/7936 - loss 0.13731517 - samples/sec: 31.33 - lr: 0.000044 | |
| 2022-02-05 03:23:31,622 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 03:23:31,623 EPOCH 2 done: loss 0.1373 - lr 0.0000444 | |
| 2022-02-05 03:26:13,727 DEV : loss 0.015243684872984886 - f1-score (micro avg) 0.9132 | |
| 2022-02-05 03:26:13,788 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 03:26:13,806 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 03:32:57,765 epoch 3 - iter 793/7936 - loss 0.11924788 - samples/sec: 31.42 - lr: 0.000044 | |
| 2022-02-05 03:39:33,229 epoch 3 - iter 1586/7936 - loss 0.11867811 - samples/sec: 32.09 - lr: 0.000043 | |
| 2022-02-05 03:46:09,619 epoch 3 - iter 2379/7936 - loss 0.11819415 - samples/sec: 32.01 - lr: 0.000043 | |
| 2022-02-05 03:52:49,510 epoch 3 - iter 3172/7936 - loss 0.11779082 - samples/sec: 31.74 - lr: 0.000042 | |
| 2022-02-05 03:59:27,917 epoch 3 - iter 3965/7936 - loss 0.11691604 - samples/sec: 31.85 - lr: 0.000042 | |
| 2022-02-05 04:06:01,365 epoch 3 - iter 4758/7936 - loss 0.11592267 - samples/sec: 32.26 - lr: 0.000041 | |
| 2022-02-05 04:12:41,174 epoch 3 - iter 5551/7936 - loss 0.11480043 - samples/sec: 31.74 - lr: 0.000041 | |
| 2022-02-05 04:19:14,243 epoch 3 - iter 6344/7936 - loss 0.11389582 - samples/sec: 32.29 - lr: 0.000040 | |
| 2022-02-05 04:25:45,192 epoch 3 - iter 7137/7936 - loss 0.11289267 - samples/sec: 32.46 - lr: 0.000039 | |
| 2022-02-05 04:32:26,310 epoch 3 - iter 7930/7936 - loss 0.11196899 - samples/sec: 31.64 - lr: 0.000039 | |
| 2022-02-05 04:32:29,352 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 04:32:29,353 EPOCH 3 done: loss 0.1120 - lr 0.0000389 | |
| 2022-02-05 04:35:09,639 DEV : loss 0.016585879027843475 - f1-score (micro avg) 0.9229 | |
| 2022-02-05 04:35:09,698 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 04:35:09,698 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 04:41:46,821 epoch 4 - iter 793/7936 - loss 0.09739851 - samples/sec: 31.96 - lr: 0.000038 | |
| 2022-02-05 04:48:23,504 epoch 4 - iter 1586/7936 - loss 0.09750632 - samples/sec: 31.99 - lr: 0.000038 | |
| 2022-02-05 04:55:05,833 epoch 4 - iter 2379/7936 - loss 0.09636659 - samples/sec: 31.54 - lr: 0.000037 | |
| 2022-02-05 05:01:34,951 epoch 4 - iter 3172/7936 - loss 0.09583742 - samples/sec: 32.61 - lr: 0.000037 | |
| 2022-02-05 05:08:07,163 epoch 4 - iter 3965/7936 - loss 0.09518243 - samples/sec: 32.36 - lr: 0.000036 | |
| 2022-02-05 05:14:50,781 epoch 4 - iter 4758/7936 - loss 0.09444265 - samples/sec: 31.44 - lr: 0.000036 | |
| 2022-02-05 05:21:24,983 epoch 4 - iter 5551/7936 - loss 0.09374740 - samples/sec: 32.19 - lr: 0.000035 | |
| 2022-02-05 05:27:54,052 epoch 4 - iter 6344/7936 - loss 0.09321236 - samples/sec: 32.62 - lr: 0.000034 | |
| 2022-02-05 05:34:32,228 epoch 4 - iter 7137/7936 - loss 0.09231997 - samples/sec: 31.87 - lr: 0.000034 | |
| 2022-02-05 05:41:08,580 epoch 4 - iter 7930/7936 - loss 0.09147929 - samples/sec: 32.02 - lr: 0.000033 | |
| 2022-02-05 05:41:11,479 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 05:41:11,479 EPOCH 4 done: loss 0.0915 - lr 0.0000333 | |
| 2022-02-05 05:44:00,197 DEV : loss 0.016923826187849045 - f1-score (micro avg) 0.9213 | |
| 2022-02-05 05:44:00,256 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 05:44:00,270 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 05:50:27,537 epoch 5 - iter 793/7936 - loss 0.07986125 - samples/sec: 32.77 - lr: 0.000033 | |
| 2022-02-05 05:56:56,203 epoch 5 - iter 1586/7936 - loss 0.08031745 - samples/sec: 32.65 - lr: 0.000032 | |
| 2022-02-05 06:03:34,109 epoch 5 - iter 2379/7936 - loss 0.07984185 - samples/sec: 31.89 - lr: 0.000032 | |
| 2022-02-05 06:10:03,550 epoch 5 - iter 3172/7936 - loss 0.07905074 - samples/sec: 32.59 - lr: 0.000031 | |
| 2022-02-05 06:16:30,085 epoch 5 - iter 3965/7936 - loss 0.07843193 - samples/sec: 32.83 - lr: 0.000031 | |
| 2022-02-05 06:23:10,671 epoch 5 - iter 4758/7936 - loss 0.07785540 - samples/sec: 31.68 - lr: 0.000030 | |
| 2022-02-05 06:29:45,063 epoch 5 - iter 5551/7936 - loss 0.07709413 - samples/sec: 32.18 - lr: 0.000029 | |
| 2022-02-05 06:36:23,513 epoch 5 - iter 6344/7936 - loss 0.07634510 - samples/sec: 31.85 - lr: 0.000029 | |
| 2022-02-05 06:42:51,615 epoch 5 - iter 7137/7936 - loss 0.07566508 - samples/sec: 32.70 - lr: 0.000028 | |
| 2022-02-05 06:49:23,409 epoch 5 - iter 7930/7936 - loss 0.07495508 - samples/sec: 32.39 - lr: 0.000028 | |
| 2022-02-05 06:49:26,372 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 06:49:26,373 EPOCH 5 done: loss 0.0750 - lr 0.0000278 | |
| 2022-02-05 06:52:15,459 DEV : loss 0.017464155331254005 - f1-score (micro avg) 0.9311 | |
| 2022-02-05 06:52:15,518 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 06:52:15,518 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 06:58:49,072 epoch 6 - iter 793/7936 - loss 0.06552824 - samples/sec: 32.25 - lr: 0.000027 | |
| 2022-02-05 07:05:27,796 epoch 6 - iter 1586/7936 - loss 0.06569517 - samples/sec: 31.83 - lr: 0.000027 | |
| 2022-02-05 07:11:58,162 epoch 6 - iter 2379/7936 - loss 0.06536467 - samples/sec: 32.51 - lr: 0.000026 | |
| 2022-02-05 07:18:25,878 epoch 6 - iter 3172/7936 - loss 0.06467146 - samples/sec: 32.73 - lr: 0.000026 | |
| 2022-02-05 07:25:10,562 epoch 6 - iter 3965/7936 - loss 0.06426965 - samples/sec: 31.36 - lr: 0.000025 | |
| 2022-02-05 07:31:39,437 epoch 6 - iter 4758/7936 - loss 0.06371305 - samples/sec: 32.63 - lr: 0.000024 | |
| 2022-02-05 07:38:08,323 epoch 6 - iter 5551/7936 - loss 0.06328229 - samples/sec: 32.63 - lr: 0.000024 | |
| 2022-02-05 07:44:52,176 epoch 6 - iter 6344/7936 - loss 0.06272143 - samples/sec: 31.42 - lr: 0.000023 | |
| 2022-02-05 07:51:20,507 epoch 6 - iter 7137/7936 - loss 0.06218937 - samples/sec: 32.68 - lr: 0.000023 | |
| 2022-02-05 07:57:52,828 epoch 6 - iter 7930/7936 - loss 0.06175113 - samples/sec: 32.35 - lr: 0.000022 | |
| 2022-02-05 07:57:55,686 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 07:57:55,687 EPOCH 6 done: loss 0.0617 - lr 0.0000222 | |
| 2022-02-05 08:00:45,565 DEV : loss 0.01982131227850914 - f1-score (micro avg) 0.9358 | |
| 2022-02-05 08:00:45,625 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 08:00:45,644 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 08:07:26,967 epoch 7 - iter 793/7936 - loss 0.05520420 - samples/sec: 31.62 - lr: 0.000022 | |
| 2022-02-05 08:13:58,782 epoch 7 - iter 1586/7936 - loss 0.05522964 - samples/sec: 32.39 - lr: 0.000021 | |
| 2022-02-05 08:20:32,705 epoch 7 - iter 2379/7936 - loss 0.05482898 - samples/sec: 32.21 - lr: 0.000021 | |
| 2022-02-05 08:27:14,353 epoch 7 - iter 3172/7936 - loss 0.05433105 - samples/sec: 31.59 - lr: 0.000020 | |
| 2022-02-05 08:33:45,236 epoch 7 - iter 3965/7936 - loss 0.05397125 - samples/sec: 32.47 - lr: 0.000019 | |
| 2022-02-05 08:40:14,072 epoch 7 - iter 4758/7936 - loss 0.05348281 - samples/sec: 32.64 - lr: 0.000019 | |
| 2022-02-05 08:46:52,674 epoch 7 - iter 5551/7936 - loss 0.05316673 - samples/sec: 31.84 - lr: 0.000018 | |
| 2022-02-05 08:53:20,653 epoch 7 - iter 6344/7936 - loss 0.05275831 - samples/sec: 32.71 - lr: 0.000018 | |
| 2022-02-05 08:59:52,741 epoch 7 - iter 7137/7936 - loss 0.05230036 - samples/sec: 32.37 - lr: 0.000017 | |
| 2022-02-05 09:06:38,983 epoch 7 - iter 7930/7936 - loss 0.05190552 - samples/sec: 31.24 - lr: 0.000017 | |
| 2022-02-05 09:06:41,639 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 09:06:41,639 EPOCH 7 done: loss 0.0519 - lr 0.0000167 | |
| 2022-02-05 09:09:20,864 DEV : loss 0.02467426098883152 - f1-score (micro avg) 0.9355 | |
| 2022-02-05 09:09:20,924 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 09:09:20,939 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 09:16:05,134 epoch 8 - iter 793/7936 - loss 0.04726178 - samples/sec: 31.40 - lr: 0.000016 | |
| 2022-02-05 09:22:33,870 epoch 8 - iter 1586/7936 - loss 0.04719666 - samples/sec: 32.64 - lr: 0.000016 | |
| 2022-02-05 09:29:02,929 epoch 8 - iter 2379/7936 - loss 0.04663752 - samples/sec: 32.62 - lr: 0.000015 | |
| 2022-02-05 09:35:42,369 epoch 8 - iter 3172/7936 - loss 0.04634901 - samples/sec: 31.77 - lr: 0.000014 | |
| 2022-02-05 09:42:14,843 epoch 8 - iter 3965/7936 - loss 0.04602895 - samples/sec: 32.33 - lr: 0.000014 | |
| 2022-02-05 09:48:48,062 epoch 8 - iter 4758/7936 - loss 0.04582764 - samples/sec: 32.27 - lr: 0.000013 | |
| 2022-02-05 09:55:28,863 epoch 8 - iter 5551/7936 - loss 0.04566599 - samples/sec: 31.66 - lr: 0.000013 | |
| 2022-02-05 10:01:52,699 epoch 8 - iter 6344/7936 - loss 0.04545939 - samples/sec: 33.06 - lr: 0.000012 | |
| 2022-02-05 10:08:33,137 epoch 8 - iter 7137/7936 - loss 0.04526206 - samples/sec: 31.69 - lr: 0.000012 | |
| 2022-02-05 10:15:07,241 epoch 8 - iter 7930/7936 - loss 0.04503385 - samples/sec: 32.20 - lr: 0.000011 | |
| 2022-02-05 10:15:10,600 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 10:15:10,600 EPOCH 8 done: loss 0.0450 - lr 0.0000111 | |
| 2022-02-05 10:18:00,280 DEV : loss 0.02364770695567131 - f1-score (micro avg) 0.9371 | |
| 2022-02-05 10:18:00,339 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 10:18:00,358 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 10:24:31,011 epoch 9 - iter 793/7936 - loss 0.04122325 - samples/sec: 32.48 - lr: 0.000011 | |
| 2022-02-05 10:31:00,279 epoch 9 - iter 1586/7936 - loss 0.04130931 - samples/sec: 32.60 - lr: 0.000010 | |
| 2022-02-05 10:37:40,369 epoch 9 - iter 2379/7936 - loss 0.04131112 - samples/sec: 31.72 - lr: 0.000009 | |
| 2022-02-05 10:44:11,067 epoch 9 - iter 3172/7936 - loss 0.04141124 - samples/sec: 32.48 - lr: 0.000009 | |
| 2022-02-05 10:50:41,270 epoch 9 - iter 3965/7936 - loss 0.04120608 - samples/sec: 32.52 - lr: 0.000008 | |
| 2022-02-05 10:57:24,718 epoch 9 - iter 4758/7936 - loss 0.04108655 - samples/sec: 31.45 - lr: 0.000008 | |
| 2022-02-05 11:04:00,581 epoch 9 - iter 5551/7936 - loss 0.04093370 - samples/sec: 32.06 - lr: 0.000007 | |
| 2022-02-05 11:10:31,042 epoch 9 - iter 6344/7936 - loss 0.04078404 - samples/sec: 32.50 - lr: 0.000007 | |
| 2022-02-05 11:17:13,751 epoch 9 - iter 7137/7936 - loss 0.04061073 - samples/sec: 31.51 - lr: 0.000006 | |
| 2022-02-05 11:23:44,231 epoch 9 - iter 7930/7936 - loss 0.04050638 - samples/sec: 32.50 - lr: 0.000006 | |
| 2022-02-05 11:23:47,941 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 11:23:47,942 EPOCH 9 done: loss 0.0405 - lr 0.0000056 | |
| 2022-02-05 11:26:37,114 DEV : loss 0.026182951405644417 - f1-score (micro avg) 0.9361 | |
| 2022-02-05 11:26:37,173 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 11:26:37,186 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 11:33:05,778 epoch 10 - iter 793/7936 - loss 0.03876526 - samples/sec: 32.66 - lr: 0.000005 | |
| 2022-02-05 11:39:45,501 epoch 10 - iter 1586/7936 - loss 0.03871561 - samples/sec: 31.75 - lr: 0.000004 | |
| 2022-02-05 11:46:18,242 epoch 10 - iter 2379/7936 - loss 0.03842790 - samples/sec: 32.31 - lr: 0.000004 | |
| 2022-02-05 11:52:48,370 epoch 10 - iter 3172/7936 - loss 0.03820246 - samples/sec: 32.53 - lr: 0.000003 | |
| 2022-02-05 11:59:28,420 epoch 10 - iter 3965/7936 - loss 0.03807900 - samples/sec: 31.72 - lr: 0.000003 | |
| 2022-02-05 12:05:57,882 epoch 10 - iter 4758/7936 - loss 0.03798954 - samples/sec: 32.58 - lr: 0.000002 | |
| 2022-02-05 12:12:25,766 epoch 10 - iter 5551/7936 - loss 0.03803371 - samples/sec: 32.72 - lr: 0.000002 | |
| 2022-02-05 12:19:03,411 epoch 10 - iter 6344/7936 - loss 0.03805844 - samples/sec: 31.91 - lr: 0.000001 | |
| 2022-02-05 12:25:27,539 epoch 10 - iter 7137/7936 - loss 0.03799490 - samples/sec: 33.04 - lr: 0.000001 | |
| 2022-02-05 12:31:55,442 epoch 10 - iter 7930/7936 - loss 0.03798541 - samples/sec: 32.71 - lr: 0.000000 | |
| 2022-02-05 12:31:58,461 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 12:31:58,462 EPOCH 10 done: loss 0.0380 - lr 0.0000000 | |
| 2022-02-05 12:34:45,700 DEV : loss 0.027400659397244453 - f1-score (micro avg) 0.9368 | |
| 2022-02-05 12:34:45,760 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 12:34:46,755 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 12:34:46,757 Testing using last state of model ... | |
| 2022-02-05 12:37:34,421 0.9329 0.9323 0.9326 0.8893 | |
| 2022-02-05 12:37:34,422 | |
| Results: | |
| - F-score (micro) 0.9326 | |
| - F-score (macro) 0.9111 | |
| - Accuracy 0.8893 | |
| By class: | |
| precision recall f1-score support | |
| pers 0.9355 0.9279 0.9317 2734 | |
| loc 0.9242 0.9335 0.9288 1384 | |
| amount 0.9800 0.9800 0.9800 250 | |
| time 0.9456 0.9576 0.9516 236 | |
| func 0.9333 0.9000 0.9164 140 | |
| org 0.8148 0.8980 0.8544 49 | |
| prod 0.8621 0.9259 0.8929 27 | |
| event 0.8333 0.8333 0.8333 12 | |
| micro avg 0.9329 0.9323 0.9326 4832 | |
| macro avg 0.9036 0.9195 0.9111 4832 | |
| weighted avg 0.9331 0.9323 0.9327 4832 | |
| samples avg 0.8893 0.8893 0.8893 4832 | |
| 2022-02-05 12:37:34,422 ---------------------------------------------------------------------------------------------------- | |