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This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5049 | 1.0 | 383 | 2.3056 |
| 2.3896 | 2.0 | 766 | 2.2460 |
| 2.3458 | 3.0 | 1149 | 2.2351 |
| 2.3097 | 4.0 | 1532 | 2.1917 |
| 2.2839 | 5.0 | 1915 | 2.1935 |
| 2.2611 | 6.0 | 2298 | 2.1741 |
| 2.2397 | 7.0 | 2681 | 2.1516 |
| 2.2234 | 8.0 | 3064 | 2.1464 |
| 2.2121 | 9.0 | 3447 | 2.1242 |
| 2.2041 | 10.0 | 3830 | 2.1361 |
| 2.1883 | 11.0 | 4213 | 2.1251 |
| 2.185 | 12.0 | 4596 | 2.1297 |
| 2.1712 | 13.0 | 4979 | 2.1062 |
| 2.1648 | 14.0 | 5362 | 2.1049 |
| 2.1587 | 15.0 | 5745 | 2.1066 |
| 2.1532 | 16.0 | 6128 | 2.0981 |
| 2.1472 | 17.0 | 6511 | 2.0926 |
| 2.1462 | 18.0 | 6894 | 2.0832 |
| 2.1437 | 19.0 | 7277 | 2.0937 |
| 2.1386 | 20.0 | 7660 | 2.0927 |