metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-pfe-projectt
results: []
distilbert-base-uncased-finetuned-pfe-projectt
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.6986
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: 32
- eval_batch_size: 32
- 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 | 6 | 2.5604 |
| No log | 2.0 | 12 | 2.8128 |
| No log | 3.0 | 18 | 2.5817 |
| No log | 4.0 | 24 | 2.8479 |
| No log | 5.0 | 30 | 2.8753 |
| No log | 6.0 | 36 | 3.0051 |
| No log | 7.0 | 42 | 2.9990 |
| No log | 8.0 | 48 | 3.1331 |
| No log | 9.0 | 54 | 3.0289 |
| No log | 10.0 | 60 | 3.1572 |
| No log | 11.0 | 66 | 3.1695 |
| No log | 12.0 | 72 | 3.0457 |
| No log | 13.0 | 78 | 3.2199 |
| No log | 14.0 | 84 | 3.0475 |
| No log | 15.0 | 90 | 2.8916 |
| No log | 16.0 | 96 | 3.0530 |
| No log | 17.0 | 102 | 3.2559 |
| No log | 18.0 | 108 | 3.0997 |
| No log | 19.0 | 114 | 3.0878 |
| No log | 20.0 | 120 | 3.1099 |
| No log | 21.0 | 126 | 3.2060 |
| No log | 22.0 | 132 | 3.2004 |
| No log | 23.0 | 138 | 3.5195 |
| No log | 24.0 | 144 | 3.2190 |
| No log | 25.0 | 150 | 3.1644 |
| No log | 26.0 | 156 | 3.4342 |
| No log | 27.0 | 162 | 3.2915 |
| No log | 28.0 | 168 | 3.2673 |
| No log | 29.0 | 174 | 3.1651 |
| No log | 30.0 | 180 | 3.1639 |
| No log | 31.0 | 186 | 3.1415 |
| No log | 32.0 | 192 | 3.2468 |
| No log | 33.0 | 198 | 3.3137 |
| No log | 34.0 | 204 | 3.3605 |
| No log | 35.0 | 210 | 3.3658 |
| No log | 36.0 | 216 | 3.3332 |
| No log | 37.0 | 222 | 3.4058 |
| No log | 38.0 | 228 | 3.3871 |
| No log | 39.0 | 234 | 3.5490 |
| No log | 40.0 | 240 | 3.5084 |
| No log | 41.0 | 246 | 3.3001 |
| No log | 42.0 | 252 | 3.4091 |
| No log | 43.0 | 258 | 3.4617 |
| No log | 44.0 | 264 | 3.3954 |
| No log | 45.0 | 270 | 3.4649 |
| No log | 46.0 | 276 | 3.5548 |
| No log | 47.0 | 282 | 3.4694 |
| No log | 48.0 | 288 | 3.5323 |
| No log | 49.0 | 294 | 3.6298 |
| No log | 50.0 | 300 | 3.5810 |
| No log | 51.0 | 306 | 3.5994 |
| No log | 52.0 | 312 | 3.5456 |
| No log | 53.0 | 318 | 3.5188 |
| No log | 54.0 | 324 | 3.3893 |
| No log | 55.0 | 330 | 3.4129 |
| No log | 56.0 | 336 | 3.5145 |
| No log | 57.0 | 342 | 3.4143 |
| No log | 58.0 | 348 | 3.4388 |
| No log | 59.0 | 354 | 3.4903 |
| No log | 60.0 | 360 | 3.5829 |
| No log | 61.0 | 366 | 3.5710 |
| No log | 62.0 | 372 | 3.6743 |
| No log | 63.0 | 378 | 3.6255 |
| No log | 64.0 | 384 | 3.6043 |
| No log | 65.0 | 390 | 3.6279 |
| No log | 66.0 | 396 | 3.6332 |
| No log | 67.0 | 402 | 3.7761 |
| No log | 68.0 | 408 | 3.7641 |
| No log | 69.0 | 414 | 3.7318 |
| No log | 70.0 | 420 | 3.6692 |
| No log | 71.0 | 426 | 3.6632 |
| No log | 72.0 | 432 | 3.7541 |
| No log | 73.0 | 438 | 3.8217 |
| No log | 74.0 | 444 | 3.7746 |
| No log | 75.0 | 450 | 3.6729 |
| No log | 76.0 | 456 | 3.6182 |
| No log | 77.0 | 462 | 3.6192 |
| No log | 78.0 | 468 | 3.5641 |
| No log | 79.0 | 474 | 3.5862 |
| No log | 80.0 | 480 | 3.5692 |
| No log | 81.0 | 486 | 3.5628 |
| No log | 82.0 | 492 | 3.5613 |
| No log | 83.0 | 498 | 3.5187 |
| 0.1491 | 84.0 | 504 | 3.5166 |
| 0.1491 | 85.0 | 510 | 3.5846 |
| 0.1491 | 86.0 | 516 | 3.6448 |
| 0.1491 | 87.0 | 522 | 3.6829 |
| 0.1491 | 88.0 | 528 | 3.6796 |
| 0.1491 | 89.0 | 534 | 3.6635 |
| 0.1491 | 90.0 | 540 | 3.6570 |
| 0.1491 | 91.0 | 546 | 3.6742 |
| 0.1491 | 92.0 | 552 | 3.7069 |
| 0.1491 | 93.0 | 558 | 3.6936 |
| 0.1491 | 94.0 | 564 | 3.6882 |
| 0.1491 | 95.0 | 570 | 3.6864 |
| 0.1491 | 96.0 | 576 | 3.6779 |
| 0.1491 | 97.0 | 582 | 3.6845 |
| 0.1491 | 98.0 | 588 | 3.6930 |
| 0.1491 | 99.0 | 594 | 3.6972 |
| 0.1491 | 100.0 | 600 | 3.6986 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2