metadata
license: mit
base_model: facebook/m2m100_1.2B
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: cs_m2m_2e-5_100_v0.2
results: []
cs_m2m_2e-5_100_v0.2
This model is a fine-tuned version of facebook/m2m100_1.2B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3369
- Bleu: 48.2659
- Gen Len: 20.4286
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: 2e-05
- 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 |
|---|---|---|---|---|---|
| 0.0 | 1.0 | 6 | 2.3719 | 49.7748 | 20.619 |
| 0.0001 | 2.0 | 12 | 2.4619 | 52.8954 | 20.0952 |
| 0.0242 | 3.0 | 18 | 2.5621 | 49.1697 | 19.9524 |
| 0.0 | 4.0 | 24 | 2.4757 | 48.7512 | 20.2857 |
| 0.0001 | 5.0 | 30 | 2.5652 | 43.0006 | 22.619 |
| 0.0001 | 6.0 | 36 | 2.5258 | 40.1532 | 22.2381 |
| 0.0 | 7.0 | 42 | 2.4040 | 49.8751 | 20.1905 |
| 0.0002 | 8.0 | 48 | 2.4212 | 49.541 | 19.4286 |
| 0.0001 | 9.0 | 54 | 2.3373 | 50.7267 | 21.619 |
| 0.0002 | 10.0 | 60 | 2.3222 | 49.2808 | 20.9524 |
| 0.0002 | 11.0 | 66 | 2.3240 | 50.4615 | 20.0 |
| 0.0008 | 12.0 | 72 | 2.3064 | 49.0688 | 20.1429 |
| 0.0006 | 13.0 | 78 | 2.2857 | 47.8241 | 19.7619 |
| 0.0001 | 14.0 | 84 | 2.2707 | 48.1756 | 19.8095 |
| 0.0001 | 15.0 | 90 | 2.2770 | 47.4155 | 20.0 |
| 0.0002 | 16.0 | 96 | 2.3248 | 46.9435 | 20.5238 |
| 0.0001 | 17.0 | 102 | 2.3505 | 47.3096 | 20.9048 |
| 0.0001 | 18.0 | 108 | 2.3525 | 48.5449 | 20.7619 |
| 0.0 | 19.0 | 114 | 2.3462 | 48.5449 | 20.7619 |
| 0.0001 | 20.0 | 120 | 2.3439 | 48.6822 | 20.7143 |
| 0.0001 | 21.0 | 126 | 2.3570 | 49.1326 | 20.5238 |
| 0.0 | 22.0 | 132 | 2.3656 | 48.5247 | 20.7143 |
| 0.0 | 23.0 | 138 | 2.3684 | 48.5247 | 20.7143 |
| 0.0001 | 24.0 | 144 | 2.3738 | 49.3527 | 20.5714 |
| 0.0 | 25.0 | 150 | 2.3793 | 48.2079 | 20.8571 |
| 0.0001 | 26.0 | 156 | 2.3854 | 47.8381 | 21.0476 |
| 0.0 | 27.0 | 162 | 2.3897 | 48.0223 | 21.0476 |
| 0.0001 | 28.0 | 168 | 2.3947 | 47.8029 | 21.0 |
| 0.0 | 29.0 | 174 | 2.3994 | 48.1359 | 20.8571 |
| 0.0002 | 30.0 | 180 | 2.3992 | 48.7452 | 20.8095 |
| 0.0001 | 31.0 | 186 | 2.3984 | 48.0307 | 20.5714 |
| 0.0001 | 32.0 | 192 | 2.3991 | 48.2877 | 20.5238 |
| 0.0 | 33.0 | 198 | 2.3979 | 49.5262 | 20.619 |
| 0.0001 | 34.0 | 204 | 2.3998 | 49.7465 | 20.6667 |
| 0.0001 | 35.0 | 210 | 2.4019 | 49.5488 | 20.619 |
| 0.0001 | 36.0 | 216 | 2.4056 | 49.7465 | 20.6667 |
| 0.0001 | 37.0 | 222 | 2.4108 | 50.1467 | 20.4762 |
| 0.0001 | 38.0 | 228 | 2.4150 | 50.1467 | 20.4762 |
| 0.0 | 39.0 | 234 | 2.4182 | 50.707 | 20.5714 |
| 0.0 | 40.0 | 240 | 2.4189 | 50.503 | 20.5238 |
| 0.0 | 41.0 | 246 | 2.4151 | 48.2877 | 20.5238 |
| 0.0001 | 42.0 | 252 | 2.4511 | 48.7331 | 20.4762 |
| 0.0 | 43.0 | 258 | 2.4614 | 49.1268 | 20.2857 |
| 0.0 | 44.0 | 264 | 2.4134 | 48.6628 | 20.381 |
| 0.0 | 45.0 | 270 | 2.4117 | 48.6628 | 20.381 |
| 0.0001 | 46.0 | 276 | 2.4130 | 48.2745 | 20.4286 |
| 0.0002 | 47.0 | 282 | 2.3939 | 47.9864 | 20.4286 |
| 0.0 | 48.0 | 288 | 2.3937 | 48.6253 | 20.2857 |
| 0.0 | 49.0 | 294 | 2.4062 | 49.3153 | 20.0476 |
| 0.0 | 50.0 | 300 | 2.4131 | 49.9443 | 20.0476 |
| 0.0001 | 51.0 | 306 | 2.4164 | 50.9445 | 20.0476 |
| 0.0 | 52.0 | 312 | 2.4129 | 50.7412 | 20.1905 |
| 0.0001 | 53.0 | 318 | 2.4178 | 50.693 | 20.1905 |
| 0.0 | 54.0 | 324 | 2.4051 | 49.2945 | 20.381 |
| 0.0002 | 55.0 | 330 | 2.4062 | 49.3592 | 20.381 |
| 0.0001 | 56.0 | 336 | 2.3274 | 49.7531 | 20.3333 |
| 0.0002 | 57.0 | 342 | 2.2969 | 50.5601 | 20.2857 |
| 0.0 | 58.0 | 348 | 2.2919 | 50.9648 | 20.1429 |
| 0.0 | 59.0 | 354 | 2.2730 | 50.1805 | 20.2381 |
| 0.0 | 60.0 | 360 | 2.2660 | 50.1805 | 20.2857 |
| 0.0001 | 61.0 | 366 | 2.2664 | 50.1805 | 20.2857 |
| 0.0001 | 62.0 | 372 | 2.2620 | 49.064 | 20.1905 |
| 0.0001 | 63.0 | 378 | 2.2576 | 50.8497 | 20.2857 |
| 0.0002 | 64.0 | 384 | 2.2808 | 50.5765 | 20.0476 |
| 0.0 | 65.0 | 390 | 2.2962 | 46.8674 | 20.381 |
| 0.0 | 66.0 | 396 | 2.3097 | 46.4579 | 20.3333 |
| 0.0001 | 67.0 | 402 | 2.3109 | 50.015 | 20.0 |
| 0.0 | 68.0 | 408 | 2.3189 | 49.5925 | 20.0 |
| 0.0 | 69.0 | 414 | 2.3080 | 49.5925 | 20.0 |
| 0.0 | 70.0 | 420 | 2.3065 | 49.5925 | 20.0 |
| 0.0 | 71.0 | 426 | 2.3102 | 50.3721 | 19.9048 |
| 0.0 | 72.0 | 432 | 2.3129 | 50.3721 | 19.9048 |
| 0.0 | 73.0 | 438 | 2.3154 | 48.9649 | 19.8571 |
| 0.0 | 74.0 | 444 | 2.3178 | 48.3266 | 20.0476 |
| 0.0001 | 75.0 | 450 | 2.3205 | 49.9671 | 20.1905 |
| 0.0 | 76.0 | 456 | 2.3218 | 49.746 | 20.0952 |
| 0.0 | 77.0 | 462 | 2.3216 | 49.746 | 20.2381 |
| 0.0 | 78.0 | 468 | 2.3218 | 49.746 | 20.2381 |
| 0.0 | 79.0 | 474 | 2.3174 | 50.1689 | 20.0952 |
| 0.0 | 80.0 | 480 | 2.3154 | 50.5016 | 20.1905 |
| 0.0001 | 81.0 | 486 | 2.3215 | 48.6113 | 20.2381 |
| 0.0001 | 82.0 | 492 | 2.3330 | 48.6113 | 20.2381 |
| 0.0003 | 83.0 | 498 | 2.3391 | 48.6113 | 20.2381 |
| 0.0 | 84.0 | 504 | 2.3418 | 48.4616 | 20.2857 |
| 0.0 | 85.0 | 510 | 2.3408 | 48.53 | 20.1429 |
| 0.0031 | 86.0 | 516 | 2.3392 | 48.4848 | 20.2857 |
| 0.0 | 87.0 | 522 | 2.3401 | 48.4848 | 20.2857 |
| 0.0001 | 88.0 | 528 | 2.3410 | 48.4848 | 20.2857 |
| 0.0 | 89.0 | 534 | 2.3416 | 48.8708 | 20.2381 |
| 0.0002 | 90.0 | 540 | 2.3417 | 48.8244 | 20.381 |
| 0.0 | 91.0 | 546 | 2.3407 | 48.2659 | 20.4286 |
| 0.0 | 92.0 | 552 | 2.3394 | 48.2659 | 20.4286 |
| 0.0001 | 93.0 | 558 | 2.3388 | 48.2659 | 20.4286 |
| 0.0001 | 94.0 | 564 | 2.3386 | 48.2659 | 20.4286 |
| 0.0 | 95.0 | 570 | 2.3385 | 48.2659 | 20.4286 |
| 0.0 | 96.0 | 576 | 2.3383 | 48.2659 | 20.4286 |
| 0.0001 | 97.0 | 582 | 2.3376 | 48.2659 | 20.4286 |
| 0.0001 | 98.0 | 588 | 2.3371 | 48.2659 | 20.4286 |
| 0.0 | 99.0 | 594 | 2.3369 | 48.2659 | 20.4286 |
| 0.0001 | 100.0 | 600 | 2.3369 | 48.2659 | 20.4286 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2