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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 |
|---|---|---|---|
| 2.5054 | 1.0 | 383 | 2.3043 |
| 2.3885 | 2.0 | 766 | 2.2447 |
| 2.3418 | 3.0 | 1149 | 2.2319 |
| 2.3045 | 4.0 | 1532 | 2.1883 |
| 2.2772 | 5.0 | 1915 | 2.1893 |
| 2.2543 | 6.0 | 2298 | 2.1683 |
| 2.2308 | 7.0 | 2681 | 2.1454 |
| 2.2139 | 8.0 | 3064 | 2.1403 |
| 2.2008 | 9.0 | 3447 | 2.1165 |
| 2.1937 | 10.0 | 3830 | 2.1281 |
| 2.1778 | 11.0 | 4213 | 2.1189 |
| 2.1742 | 12.0 | 4596 | 2.1218 |
| 2.1611 | 13.0 | 4979 | 2.0996 |
| 2.1562 | 14.0 | 5362 | 2.0992 |
| 2.1508 | 15.0 | 5745 | 2.1013 |
| 2.1469 | 16.0 | 6128 | 2.0945 |
| 2.1437 | 17.0 | 6511 | 2.0899 |
| 2.1436 | 18.0 | 6894 | 2.0827 |
| 2.1443 | 19.0 | 7277 | 2.0935 |
| 2.1389 | 20.0 | 7660 | 2.0939 |