metadata
tags:
- generated_from_trainer
model-index:
- name: calculator_model_test_third_version
results: []
calculator_model_test_third_version
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2789
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: 0.001
- train_batch_size: 512
- eval_batch_size: 512
- 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 |
|---|---|---|---|
| 3.4163 | 1.0 | 6 | 2.7578 |
| 2.3764 | 2.0 | 12 | 1.9673 |
| 1.794 | 3.0 | 18 | 1.6871 |
| 1.682 | 4.0 | 24 | 1.6571 |
| 1.6127 | 5.0 | 30 | 1.5569 |
| 1.5398 | 6.0 | 36 | 1.5012 |
| 1.5125 | 7.0 | 42 | 1.5110 |
| 1.521 | 8.0 | 48 | 1.4432 |
| 1.4421 | 9.0 | 54 | 1.3939 |
| 1.3958 | 10.0 | 60 | 1.3717 |
| 1.3615 | 11.0 | 66 | 1.2885 |
| 1.2466 | 12.0 | 72 | 1.2391 |
| 1.2277 | 13.0 | 78 | 1.1908 |
| 1.1821 | 14.0 | 84 | 1.2211 |
| 1.1512 | 15.0 | 90 | 1.1313 |
| 1.1268 | 16.0 | 96 | 1.0571 |
| 1.0752 | 17.0 | 102 | 1.0546 |
| 1.0988 | 18.0 | 108 | 1.0526 |
| 1.0499 | 19.0 | 114 | 1.0063 |
| 0.9957 | 20.0 | 120 | 0.9662 |
| 1.0018 | 21.0 | 126 | 0.9062 |
| 0.9747 | 22.0 | 132 | 0.9273 |
| 0.9545 | 23.0 | 138 | 1.0973 |
| 1.0842 | 24.0 | 144 | 1.1854 |
| 1.0838 | 25.0 | 150 | 1.0031 |
| 0.9812 | 26.0 | 156 | 1.0129 |
| 1.0154 | 27.0 | 162 | 0.9693 |
| 0.9441 | 28.0 | 168 | 0.8257 |
| 0.863 | 29.0 | 174 | 0.8138 |
| 0.8591 | 30.0 | 180 | 0.8746 |
| 0.8913 | 31.0 | 186 | 0.8592 |
| 0.8719 | 32.0 | 192 | 0.7773 |
| 0.8187 | 33.0 | 198 | 0.7999 |
| 0.8013 | 34.0 | 204 | 0.7491 |
| 0.7976 | 35.0 | 210 | 0.7171 |
| 0.8033 | 36.0 | 216 | 0.7610 |
| 0.7785 | 37.0 | 222 | 0.8047 |
| 0.8141 | 38.0 | 228 | 0.7245 |
| 0.7726 | 39.0 | 234 | 0.6725 |
| 0.7832 | 40.0 | 240 | 0.8410 |
| 0.8625 | 41.0 | 246 | 0.7093 |
| 0.7307 | 42.0 | 252 | 0.6675 |
| 0.6832 | 43.0 | 258 | 0.6891 |
| 0.7126 | 44.0 | 264 | 0.7927 |
| 0.7808 | 45.0 | 270 | 0.7757 |
| 0.8031 | 46.0 | 276 | 0.6749 |
| 0.728 | 47.0 | 282 | 0.7299 |
| 0.741 | 48.0 | 288 | 0.6062 |
| 0.6772 | 49.0 | 294 | 0.6449 |
| 0.6505 | 50.0 | 300 | 0.6041 |
| 0.6315 | 51.0 | 306 | 0.5769 |
| 0.6339 | 52.0 | 312 | 0.6003 |
| 0.6388 | 53.0 | 318 | 0.6115 |
| 0.6436 | 54.0 | 324 | 0.5778 |
| 0.5993 | 55.0 | 330 | 0.5777 |
| 0.5936 | 56.0 | 336 | 0.5614 |
| 0.5873 | 57.0 | 342 | 0.5445 |
| 0.5819 | 58.0 | 348 | 0.5437 |
| 0.5523 | 59.0 | 354 | 0.4961 |
| 0.5527 | 60.0 | 360 | 0.4939 |
| 0.5622 | 61.0 | 366 | 0.4922 |
| 0.5603 | 62.0 | 372 | 0.5252 |
| 0.612 | 63.0 | 378 | 0.5024 |
| 0.6284 | 64.0 | 384 | 0.5152 |
| 0.573 | 65.0 | 390 | 0.5300 |
| 0.5407 | 66.0 | 396 | 0.4879 |
| 0.5266 | 67.0 | 402 | 0.4813 |
| 0.526 | 68.0 | 408 | 0.4341 |
| 0.5306 | 69.0 | 414 | 0.4817 |
| 0.5108 | 70.0 | 420 | 0.4127 |
| 0.5079 | 71.0 | 426 | 0.5083 |
| 0.5237 | 72.0 | 432 | 0.4423 |
| 0.5049 | 73.0 | 438 | 0.4948 |
| 0.491 | 74.0 | 444 | 0.4121 |
| 0.484 | 75.0 | 450 | 0.4047 |
| 0.4668 | 76.0 | 456 | 0.4041 |
| 0.4669 | 77.0 | 462 | 0.3987 |
| 0.4524 | 78.0 | 468 | 0.4115 |
| 0.4604 | 79.0 | 474 | 0.3926 |
| 0.4536 | 80.0 | 480 | 0.3970 |
| 0.4747 | 81.0 | 486 | 0.3674 |
| 0.4417 | 82.0 | 492 | 0.3905 |
| 0.458 | 83.0 | 498 | 0.4045 |
| 0.4393 | 84.0 | 504 | 0.3889 |
| 0.431 | 85.0 | 510 | 0.3427 |
| 0.4076 | 86.0 | 516 | 0.3621 |
| 0.4239 | 87.0 | 522 | 0.3368 |
| 0.4089 | 88.0 | 528 | 0.3353 |
| 0.3936 | 89.0 | 534 | 0.3253 |
| 0.3899 | 90.0 | 540 | 0.3173 |
| 0.3792 | 91.0 | 546 | 0.3065 |
| 0.3774 | 92.0 | 552 | 0.3060 |
| 0.3677 | 93.0 | 558 | 0.3063 |
| 0.3655 | 94.0 | 564 | 0.2909 |
| 0.3608 | 95.0 | 570 | 0.2944 |
| 0.3561 | 96.0 | 576 | 0.2842 |
| 0.3593 | 97.0 | 582 | 0.2906 |
| 0.357 | 98.0 | 588 | 0.2800 |
| 0.3558 | 99.0 | 594 | 0.2751 |
| 0.3456 | 100.0 | 600 | 0.2789 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2