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4d-addition-3000

Text2Text Generation
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t5
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4d-addition-3000 / README.md
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metadata
license: apache-2.0
base_model: google/byt5-small
tags:
  - generated_from_trainer
model-index:
  - name: byt5_3k_4d
    results: []

byt5_3k_4d

This model is a fine-tuned version of google/byt5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0348

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 800
  • eval_batch_size: 800
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 4 0.4702
No log 2.0 8 0.4366
0.8301 3.0 12 0.4202
0.8301 4.0 16 0.3843
0.7703 5.0 20 0.3898
0.7703 6.0 24 0.3573
0.7703 7.0 28 0.3422
0.7169 8.0 32 0.3304
0.7169 9.0 36 0.3049
0.6727 10.0 40 0.3067
0.6727 11.0 44 0.2965
0.6727 12.0 48 0.2693
0.6394 13.0 52 0.2711
0.6394 14.0 56 0.2561
0.6047 15.0 60 0.2454
0.6047 16.0 64 0.2368
0.6047 17.0 68 0.2250
0.565 18.0 72 0.2110
0.565 19.0 76 0.2109
0.5368 20.0 80 0.1950
0.5368 21.0 84 0.1974
0.5368 22.0 88 0.1819
0.518 23.0 92 0.1795
0.518 24.0 96 0.1648
0.4862 25.0 100 0.1675
0.4862 26.0 104 0.1550
0.4862 27.0 108 0.1530
0.4628 28.0 112 0.1447
0.4628 29.0 116 0.1442
0.4408 30.0 120 0.1310
0.4408 31.0 124 0.1336
0.4408 32.0 128 0.1235
0.4192 33.0 132 0.1191
0.4192 34.0 136 0.1193
0.4133 35.0 140 0.1123
0.4133 36.0 144 0.1156
0.4133 37.0 148 0.1051
0.3922 38.0 152 0.0999
0.3922 39.0 156 0.0991
0.3778 40.0 160 0.0995
0.3778 41.0 164 0.0912
0.3778 42.0 168 0.0903
0.3655 43.0 172 0.0841
0.3655 44.0 176 0.0790
0.3526 45.0 180 0.0827
0.3526 46.0 184 0.0756
0.3526 47.0 188 0.0747
0.3378 48.0 192 0.0737
0.3378 49.0 196 0.0747
0.3308 50.0 200 0.0729
0.3308 51.0 204 0.0665
0.3308 52.0 208 0.0663
0.321 53.0 212 0.0642
0.321 54.0 216 0.0640
0.3084 55.0 220 0.0632
0.3084 56.0 224 0.0599
0.3084 57.0 228 0.0580
0.2967 58.0 232 0.0567
0.2967 59.0 236 0.0525
0.2928 60.0 240 0.0522
0.2928 61.0 244 0.0536
0.2928 62.0 248 0.0524
0.2929 63.0 252 0.0568
0.2929 64.0 256 0.0530
0.283 65.0 260 0.0476
0.283 66.0 264 0.0479
0.283 67.0 268 0.0507
0.2766 68.0 272 0.0461
0.2766 69.0 276 0.0444
0.2677 70.0 280 0.0456
0.2677 71.0 284 0.0437
0.2677 72.0 288 0.0428
0.2614 73.0 292 0.0419
0.2614 74.0 296 0.0414
0.2595 75.0 300 0.0418
0.2595 76.0 304 0.0412
0.2595 77.0 308 0.0396
0.2582 78.0 312 0.0382
0.2582 79.0 316 0.0381
0.2511 80.0 320 0.0387
0.2511 81.0 324 0.0388
0.2511 82.0 328 0.0372
0.2481 83.0 332 0.0360
0.2481 84.0 336 0.0366
0.2474 85.0 340 0.0365
0.2474 86.0 344 0.0357
0.2474 87.0 348 0.0355
0.2537 88.0 352 0.0360
0.2537 89.0 356 0.0359
0.2438 90.0 360 0.0355
0.2438 91.0 364 0.0353
0.2438 92.0 368 0.0349
0.2461 93.0 372 0.0343
0.2461 94.0 376 0.0342
0.2395 95.0 380 0.0344
0.2395 96.0 384 0.0347
0.2395 97.0 388 0.0350
0.2439 98.0 392 0.0349
0.2439 99.0 396 0.0348
0.2432 100.0 400 0.0348

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2