metadata
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: cs_mT5_0.01_100_v0.1
results: []
cs_mT5_0.01_100_v0.1
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 7.2340
- Bleu: 0.3036
- Gen Len: 19.0
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: 0.01
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Bleu | Gen Len |
|---|---|---|---|---|---|
| 6.6837 | 1.0 | 6 | 11.3036 | 0.2013 | 19.0 |
| 8.0402 | 2.0 | 12 | 7.6042 | 0.0 | 19.0 |
| 5.7261 | 3.0 | 18 | 6.2715 | 0.1442 | 19.0 |
| 5.3416 | 4.0 | 24 | 6.1049 | 0.0 | 19.0 |
| 5.8512 | 5.0 | 30 | 5.9636 | 0.7212 | 19.0 |
| 5.5121 | 6.0 | 36 | 6.1024 | 0.0 | 19.0 |
| 5.4593 | 7.0 | 42 | 5.8880 | 0.0 | 19.0 |
| 5.9207 | 8.0 | 48 | 5.7795 | 0.1689 | 19.0 |
| 4.8391 | 9.0 | 54 | 5.8944 | 0.7212 | 19.0 |
| 5.0744 | 10.0 | 60 | 5.8163 | 0.7212 | 19.0 |
| 4.3596 | 11.0 | 66 | 5.6633 | 0.7212 | 19.0 |
| 4.4986 | 12.0 | 72 | 5.7046 | 0.7212 | 19.0 |
| 3.7398 | 13.0 | 78 | 5.7036 | 0.1689 | 19.0 |
| 4.3772 | 14.0 | 84 | 5.6193 | 0.7212 | 19.0 |
| 4.3643 | 15.0 | 90 | 5.6598 | 0.7212 | 19.0 |
| 4.1574 | 16.0 | 96 | 5.7247 | 0.7212 | 19.0 |
| 4.1304 | 17.0 | 102 | 5.7906 | 0.7212 | 19.0 |
| 4.1503 | 18.0 | 108 | 5.6421 | 0.1689 | 19.0 |
| 4.769 | 19.0 | 114 | 5.5631 | 0.7212 | 19.0 |
| 4.7648 | 20.0 | 120 | 5.9913 | 0.0 | 19.0 |
| 4.076 | 21.0 | 126 | 5.8300 | 0.7212 | 19.0 |
| 4.5435 | 22.0 | 132 | 5.7988 | 0.7212 | 19.0 |
| 4.2224 | 23.0 | 138 | 5.7900 | 0.7212 | 19.0 |
| 3.7953 | 24.0 | 144 | 6.0687 | 0.011 | 19.0 |
| 4.0312 | 25.0 | 150 | 5.8321 | 0.1689 | 19.0 |
| 3.4781 | 26.0 | 156 | 5.8820 | 0.7984 | 19.0 |
| 4.0509 | 27.0 | 162 | 5.9177 | 0.7212 | 19.0 |
| 3.8217 | 28.0 | 168 | 5.7663 | 0.7861 | 19.0 |
| 4.1972 | 29.0 | 174 | 6.0547 | 0.9173 | 19.0 |
| 3.9588 | 30.0 | 180 | 5.7790 | 0.7212 | 19.0 |
| 3.8624 | 31.0 | 186 | 5.8604 | 0.1916 | 19.0 |
| 3.7053 | 32.0 | 192 | 5.9171 | 0.7212 | 19.0 |
| 4.03 | 33.0 | 198 | 5.8490 | 0.7212 | 19.0 |
| 3.3214 | 34.0 | 204 | 6.3967 | 0.7212 | 19.0 |
| 3.8343 | 35.0 | 210 | 5.7936 | 0.0 | 19.0 |
| 3.3124 | 36.0 | 216 | 5.8793 | 0.7663 | 19.0 |
| 3.7071 | 37.0 | 222 | 6.1326 | 0.0957 | 8.0 |
| 3.6547 | 38.0 | 228 | 5.9072 | 0.8029 | 19.0 |
| 3.4187 | 39.0 | 234 | 5.8807 | 0.5047 | 19.0 |
| 3.953 | 40.0 | 240 | 5.8663 | 0.7923 | 19.0 |
| 4.0113 | 41.0 | 246 | 6.1256 | 0.7212 | 19.0 |
| 4.2969 | 42.0 | 252 | 6.0113 | 0.1689 | 19.0 |
| 3.9081 | 43.0 | 258 | 5.9222 | 0.0 | 15.9048 |
| 3.7646 | 44.0 | 264 | 5.9990 | 0.7212 | 19.0 |
| 3.5407 | 45.0 | 270 | 6.2920 | 0.0945 | 7.0 |
| 2.8075 | 46.0 | 276 | 6.1092 | 0.4815 | 19.0 |
| 3.9057 | 47.0 | 282 | 6.1175 | 1.0006 | 19.0 |
| 4.1845 | 48.0 | 288 | 6.2553 | 0.8147 | 19.0 |
| 3.4686 | 49.0 | 294 | 6.1979 | 0.7796 | 19.0 |
| 3.029 | 50.0 | 300 | 6.1064 | 0.7771 | 19.0 |
| 3.62 | 51.0 | 306 | 5.9443 | 0.7212 | 19.0 |
| 3.719 | 52.0 | 312 | 6.3162 | 0.7212 | 19.0 |
| 3.4713 | 53.0 | 318 | 5.9465 | 0.7212 | 19.0 |
| 3.675 | 54.0 | 324 | 6.1606 | 0.3501 | 19.0 |
| 3.518 | 55.0 | 330 | 6.1223 | 0.1689 | 19.0 |
| 3.3729 | 56.0 | 336 | 6.0394 | 1.3618 | 19.0 |
| 2.7827 | 57.0 | 342 | 6.3169 | 0.7212 | 19.0 |
| 3.7061 | 58.0 | 348 | 6.4504 | 1.694 | 19.0 |
| 3.4929 | 59.0 | 354 | 6.3042 | 0.7475 | 19.0 |
| 2.1424 | 60.0 | 360 | 6.3536 | 0.8628 | 19.0 |
| 2.787 | 61.0 | 366 | 6.3339 | 0.0 | 19.0 |
| 3.6486 | 62.0 | 372 | 6.4380 | 0.1023 | 19.0 |
| 3.8631 | 63.0 | 378 | 6.3261 | 0.7212 | 19.0 |
| 3.4476 | 64.0 | 384 | 6.2478 | 1.2825 | 19.0 |
| 3.256 | 65.0 | 390 | 6.4766 | 0.5017 | 19.0 |
| 3.6114 | 66.0 | 396 | 6.4519 | 0.7212 | 19.0 |
| 3.8405 | 67.0 | 402 | 6.3538 | 0.4744 | 19.0 |
| 3.3164 | 68.0 | 408 | 6.0134 | 0.3725 | 19.0 |
| 3.4129 | 69.0 | 414 | 6.5988 | 0.2135 | 19.0 |
| 3.693 | 70.0 | 420 | 6.4498 | 0.1689 | 19.0 |
| 2.9521 | 71.0 | 426 | 6.2916 | 1.3636 | 19.0 |
| 3.6362 | 72.0 | 432 | 6.3040 | 0.3063 | 19.0 |
| 3.6713 | 73.0 | 438 | 6.3731 | 0.8106 | 19.0 |
| 3.2562 | 74.0 | 444 | 6.3822 | 0.9407 | 19.0 |
| 2.4132 | 75.0 | 450 | 6.5435 | 0.9407 | 19.0 |
| 3.4504 | 76.0 | 456 | 6.7828 | 0.8829 | 19.0 |
| 3.282 | 77.0 | 462 | 6.6479 | 1.4788 | 19.0 |
| 3.4199 | 78.0 | 468 | 6.6536 | 0.0761 | 6.0 |
| 3.4234 | 79.0 | 474 | 6.5193 | 0.4172 | 19.0 |
| 3.0937 | 80.0 | 480 | 6.7476 | 0.5603 | 19.0 |
| 2.9563 | 81.0 | 486 | 6.6885 | 1.5178 | 19.0 |
| 3.1052 | 82.0 | 492 | 6.6320 | 1.3064 | 19.0 |
| 2.7674 | 83.0 | 498 | 6.6363 | 0.7892 | 19.0 |
| 2.6265 | 84.0 | 504 | 6.6629 | 1.5199 | 19.0 |
| 2.3116 | 85.0 | 510 | 6.6467 | 0.0 | 19.0 |
| 3.0439 | 86.0 | 516 | 6.7820 | 0.9326 | 19.0 |
| 2.7406 | 87.0 | 522 | 6.9067 | 1.2025 | 19.0 |
| 2.4509 | 88.0 | 528 | 6.9738 | 1.0657 | 19.0 |
| 2.8186 | 89.0 | 534 | 7.1507 | 0.4574 | 19.0 |
| 2.6713 | 90.0 | 540 | 7.0799 | 0.4527 | 19.0 |
| 2.6231 | 91.0 | 546 | 7.0459 | 0.646 | 19.0 |
| 3.2357 | 92.0 | 552 | 7.0238 | 0.525 | 19.0 |
| 2.8834 | 93.0 | 558 | 7.0185 | 0.5206 | 19.0 |
| 1.7973 | 94.0 | 564 | 7.0711 | 0.8153 | 19.0 |
| 1.9995 | 95.0 | 570 | 7.1263 | 0.3015 | 19.0 |
| 2.2875 | 96.0 | 576 | 7.1877 | 0.3025 | 19.0 |
| 1.8547 | 97.0 | 582 | 7.2062 | 0.3025 | 19.0 |
| 1.5572 | 98.0 | 588 | 7.2270 | 0.5076 | 19.0 |
| 1.7653 | 99.0 | 594 | 7.2347 | 0.3025 | 19.0 |
| 2.6411 | 100.0 | 600 | 7.2340 | 0.3036 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0