test5_balanced_60ep
This model is a fine-tuned version of ibaucells/RoBERTa-ca-CaWikiTC on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8209
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: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 60
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.8299 | 1.0 | 63 | 2.8361 |
| 2.8512 | 2.0 | 126 | 2.8253 |
| 2.8118 | 3.0 | 189 | 2.8376 |
| 2.7238 | 4.0 | 252 | 2.7157 |
| 2.5914 | 5.0 | 315 | 2.6045 |
| 2.5527 | 6.0 | 378 | 2.5580 |
| 2.4197 | 7.0 | 441 | 2.6009 |
| 2.2561 | 8.0 | 504 | 2.3989 |
| 1.9213 | 9.0 | 567 | 2.2129 |
| 1.8147 | 10.0 | 630 | 2.1155 |
| 1.4336 | 11.0 | 693 | 2.0509 |
| 1.2948 | 12.0 | 756 | 1.8276 |
| 0.9833 | 13.0 | 819 | 1.8245 |
| 0.8577 | 14.0 | 882 | 1.7360 |
| 0.665 | 15.0 | 945 | 1.8072 |
| 0.5397 | 16.0 | 1008 | 1.8583 |
| 0.2861 | 17.0 | 1071 | 1.9073 |
| 0.3394 | 18.0 | 1134 | 2.0320 |
| 0.2941 | 19.0 | 1197 | 2.1608 |
| 0.1868 | 20.0 | 1260 | 2.1440 |
| 0.175 | 21.0 | 1323 | 2.2099 |
| 0.3357 | 22.0 | 1386 | 2.3903 |
| 0.1311 | 23.0 | 1449 | 2.4006 |
| 0.103 | 24.0 | 1512 | 2.4874 |
| 0.1323 | 25.0 | 1575 | 2.5191 |
| 0.0928 | 26.0 | 1638 | 2.3582 |
| 0.0872 | 27.0 | 1701 | 2.4494 |
| 0.1271 | 28.0 | 1764 | 2.5821 |
| 0.1796 | 29.0 | 1827 | 2.6190 |
| 0.0479 | 30.0 | 1890 | 2.5549 |
| 0.0197 | 31.0 | 1953 | 2.8739 |
| 0.0222 | 32.0 | 2016 | 2.7927 |
| 0.019 | 33.0 | 2079 | 2.8467 |
| 0.0946 | 34.0 | 2142 | 2.9086 |
| 0.0084 | 35.0 | 2205 | 2.7976 |
| 0.0539 | 36.0 | 2268 | 2.8300 |
| 0.0553 | 37.0 | 2331 | 2.9293 |
| 0.0124 | 38.0 | 2394 | 3.0047 |
| 0.0447 | 39.0 | 2457 | 2.9724 |
| 0.0363 | 40.0 | 2520 | 2.9775 |
| 0.0056 | 41.0 | 2583 | 2.9972 |
| 0.0072 | 42.0 | 2646 | 3.0162 |
| 0.0091 | 43.0 | 2709 | 3.0348 |
| 0.031 | 44.0 | 2772 | 3.0490 |
| 0.0091 | 45.0 | 2835 | 3.0648 |
| 0.029 | 46.0 | 2898 | 3.0730 |
| 0.0076 | 47.0 | 2961 | 3.0866 |
| 0.0115 | 48.0 | 3024 | 3.0979 |
| 0.0047 | 49.0 | 3087 | 3.1102 |
| 0.0079 | 50.0 | 3150 | 3.1242 |
| 0.0039 | 51.0 | 3213 | 3.1299 |
| 0.0043 | 52.0 | 3276 | 3.1386 |
| 0.0322 | 53.0 | 3339 | 3.1478 |
| 0.0041 | 54.0 | 3402 | 3.1478 |
| 0.0289 | 55.0 | 3465 | 3.1570 |
| 0.0038 | 56.0 | 3528 | 3.1661 |
| 0.004 | 57.0 | 3591 | 3.1546 |
| 0.0037 | 58.0 | 3654 | 3.1575 |
| 0.0069 | 59.0 | 3717 | 3.1587 |
| 0.0135 | 60.0 | 3780 | 3.1626 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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