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This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.7623
- Loss: 1.5465
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: 160
- eval_batch_size: 160
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 36
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.4968 | 1.0 | 1041 | 0.7587 | 0.6138 |
| 0.4174 | 2.0 | 2082 | 0.7695 | 0.6211 |
| 0.4036 | 3.0 | 3123 | 0.7733 | 0.6181 |
| 0.3415 | 4.0 | 4164 | 0.7772 | 0.6450 |
| 0.2868 | 5.0 | 5205 | 0.7738 | 0.6896 |
| 0.2453 | 6.0 | 6246 | 0.7763 | 0.7119 |
| 0.2003 | 7.0 | 7287 | 0.7728 | 0.8254 |
| 0.1683 | 8.0 | 8328 | 0.7712 | 0.9288 |
| 0.1439 | 9.0 | 9369 | 0.7764 | 0.8993 |
| 0.1197 | 10.0 | 10410 | 0.7729 | 0.9819 |
| 0.102 | 11.0 | 11451 | 0.7709 | 1.0478 |
| 0.088 | 12.0 | 12492 | 0.7692 | 1.1574 |
| 0.087 | 13.0 | 13533 | 0.7709 | 1.0969 |
| 0.0779 | 14.0 | 14574 | 0.7661 | 1.2575 |
| 0.0695 | 15.0 | 15615 | 0.7658 | 1.3540 |
| 0.0664 | 16.0 | 16656 | 0.7719 | 1.2155 |
| 0.058 | 17.0 | 17697 | 0.7654 | 1.3065 |
| 0.0533 | 18.0 | 18738 | 0.7674 | 1.3535 |
| 0.0496 | 19.0 | 19779 | 0.7663 | 1.3327 |
| 0.0459 | 20.0 | 20820 | 0.7686 | 1.3893 |
| 0.0432 | 21.0 | 21861 | 0.7691 | 1.4211 |
| 0.0396 | 22.0 | 22902 | 0.7682 | 1.4810 |
| 0.0371 | 23.0 | 23943 | 0.7705 | 1.4926 |
| 0.0338 | 24.0 | 24984 | 0.7633 | 1.5058 |
| 0.037 | 25.0 | 26025 | 0.7604 | 1.4986 |
| 0.034 | 26.0 | 27066 | 0.7611 | 1.5314 |
| 0.0317 | 27.0 | 28107 | 0.7659 | 1.4636 |
| 0.0312 | 28.0 | 29148 | 0.7658 | 1.5006 |
| 0.0282 | 29.0 | 30189 | 0.7672 | 1.4250 |
| 0.0282 | 30.0 | 31230 | 0.7662 | 1.4904 |
| 0.0264 | 31.0 | 32271 | 0.7669 | 1.5415 |
| 0.0253 | 32.0 | 33312 | 0.7679 | 1.6110 |
| 0.0257 | 33.0 | 34353 | 0.7645 | 1.6097 |
| 0.0233 | 34.0 | 35394 | 0.7614 | 1.6646 |
| 0.0251 | 35.0 | 36435 | 0.7651 | 1.6080 |
| 0.0236 | 36.0 | 37476 | 0.7699 | 1.5824 |
| 0.025 | 37.0 | 38517 | 0.7623 | 1.5465 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
