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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distilbert-base-uncased-finetuned-pfe-projectt |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilbert-base-uncased-finetuned-pfe-projectt |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6986 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 6 | 2.5604 | |
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| No log | 2.0 | 12 | 2.8128 | |
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| No log | 3.0 | 18 | 2.5817 | |
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| No log | 4.0 | 24 | 2.8479 | |
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| No log | 5.0 | 30 | 2.8753 | |
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| No log | 6.0 | 36 | 3.0051 | |
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| No log | 7.0 | 42 | 2.9990 | |
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| No log | 8.0 | 48 | 3.1331 | |
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| No log | 9.0 | 54 | 3.0289 | |
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| No log | 10.0 | 60 | 3.1572 | |
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| No log | 11.0 | 66 | 3.1695 | |
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| No log | 12.0 | 72 | 3.0457 | |
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| No log | 13.0 | 78 | 3.2199 | |
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| No log | 14.0 | 84 | 3.0475 | |
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| No log | 15.0 | 90 | 2.8916 | |
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| No log | 16.0 | 96 | 3.0530 | |
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| No log | 17.0 | 102 | 3.2559 | |
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| No log | 18.0 | 108 | 3.0997 | |
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| No log | 19.0 | 114 | 3.0878 | |
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| No log | 20.0 | 120 | 3.1099 | |
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| No log | 21.0 | 126 | 3.2060 | |
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| No log | 22.0 | 132 | 3.2004 | |
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| No log | 23.0 | 138 | 3.5195 | |
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| No log | 24.0 | 144 | 3.2190 | |
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| No log | 25.0 | 150 | 3.1644 | |
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| No log | 26.0 | 156 | 3.4342 | |
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| No log | 27.0 | 162 | 3.2915 | |
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| No log | 28.0 | 168 | 3.2673 | |
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| No log | 29.0 | 174 | 3.1651 | |
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| No log | 30.0 | 180 | 3.1639 | |
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| No log | 31.0 | 186 | 3.1415 | |
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| No log | 32.0 | 192 | 3.2468 | |
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| No log | 33.0 | 198 | 3.3137 | |
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| No log | 34.0 | 204 | 3.3605 | |
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| No log | 35.0 | 210 | 3.3658 | |
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| No log | 36.0 | 216 | 3.3332 | |
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| No log | 37.0 | 222 | 3.4058 | |
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| No log | 38.0 | 228 | 3.3871 | |
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| No log | 39.0 | 234 | 3.5490 | |
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| No log | 40.0 | 240 | 3.5084 | |
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| No log | 41.0 | 246 | 3.3001 | |
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| No log | 42.0 | 252 | 3.4091 | |
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| No log | 43.0 | 258 | 3.4617 | |
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| No log | 44.0 | 264 | 3.3954 | |
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| No log | 45.0 | 270 | 3.4649 | |
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| No log | 46.0 | 276 | 3.5548 | |
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| No log | 47.0 | 282 | 3.4694 | |
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| No log | 48.0 | 288 | 3.5323 | |
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| No log | 49.0 | 294 | 3.6298 | |
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| No log | 50.0 | 300 | 3.5810 | |
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| No log | 51.0 | 306 | 3.5994 | |
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| No log | 52.0 | 312 | 3.5456 | |
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| No log | 53.0 | 318 | 3.5188 | |
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| No log | 54.0 | 324 | 3.3893 | |
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| No log | 55.0 | 330 | 3.4129 | |
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| No log | 56.0 | 336 | 3.5145 | |
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| No log | 57.0 | 342 | 3.4143 | |
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| No log | 58.0 | 348 | 3.4388 | |
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| No log | 59.0 | 354 | 3.4903 | |
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| No log | 60.0 | 360 | 3.5829 | |
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| No log | 61.0 | 366 | 3.5710 | |
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| No log | 62.0 | 372 | 3.6743 | |
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| No log | 63.0 | 378 | 3.6255 | |
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| No log | 64.0 | 384 | 3.6043 | |
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| No log | 65.0 | 390 | 3.6279 | |
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| No log | 66.0 | 396 | 3.6332 | |
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| No log | 67.0 | 402 | 3.7761 | |
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| No log | 68.0 | 408 | 3.7641 | |
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| No log | 69.0 | 414 | 3.7318 | |
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| No log | 70.0 | 420 | 3.6692 | |
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| No log | 71.0 | 426 | 3.6632 | |
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| No log | 72.0 | 432 | 3.7541 | |
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| No log | 73.0 | 438 | 3.8217 | |
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| No log | 74.0 | 444 | 3.7746 | |
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| No log | 75.0 | 450 | 3.6729 | |
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| No log | 76.0 | 456 | 3.6182 | |
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| No log | 77.0 | 462 | 3.6192 | |
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| No log | 78.0 | 468 | 3.5641 | |
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| No log | 79.0 | 474 | 3.5862 | |
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| No log | 80.0 | 480 | 3.5692 | |
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| No log | 81.0 | 486 | 3.5628 | |
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| No log | 82.0 | 492 | 3.5613 | |
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| No log | 83.0 | 498 | 3.5187 | |
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| 0.1491 | 84.0 | 504 | 3.5166 | |
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| 0.1491 | 85.0 | 510 | 3.5846 | |
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| 0.1491 | 86.0 | 516 | 3.6448 | |
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| 0.1491 | 87.0 | 522 | 3.6829 | |
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| 0.1491 | 88.0 | 528 | 3.6796 | |
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| 0.1491 | 89.0 | 534 | 3.6635 | |
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| 0.1491 | 90.0 | 540 | 3.6570 | |
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| 0.1491 | 91.0 | 546 | 3.6742 | |
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| 0.1491 | 92.0 | 552 | 3.7069 | |
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| 0.1491 | 93.0 | 558 | 3.6936 | |
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| 0.1491 | 94.0 | 564 | 3.6882 | |
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| 0.1491 | 95.0 | 570 | 3.6864 | |
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| 0.1491 | 96.0 | 576 | 3.6779 | |
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| 0.1491 | 97.0 | 582 | 3.6845 | |
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| 0.1491 | 98.0 | 588 | 3.6930 | |
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| 0.1491 | 99.0 | 594 | 3.6972 | |
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| 0.1491 | 100.0 | 600 | 3.6986 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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