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This model is a fine-tuned version of roberta-base 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.0794 | 1.0 | 1022 | 1.1888 | 0.1440 | 0.0203 | 0.0356 | 0.7435 |
| 0.9242 | 2.0 | 2044 | 1.1341 | 0.1719 | 0.0313 | 0.0529 | 0.7451 |
| 0.8462 | 3.0 | 3066 | 1.1380 | 0.1444 | 0.0606 | 0.0853 | 0.7282 |
| 0.7496 | 4.0 | 4088 | 1.1755 | 0.1349 | 0.0535 | 0.0766 | 0.7219 |
| 0.6526 | 5.0 | 5110 | 1.2087 | 0.1337 | 0.0649 | 0.0873 | 0.7270 |
| 0.5841 | 6.0 | 6132 | 1.2208 | 0.1323 | 0.0676 | 0.0895 | 0.7178 |
| 0.5311 | 7.0 | 7154 | 1.2532 | 0.1345 | 0.0801 | 0.1004 | 0.7088 |
| 0.4749 | 8.0 | 8176 | 1.3047 | 0.1459 | 0.0727 | 0.0970 | 0.7184 |
| 0.4393 | 9.0 | 9198 | 1.3341 | 0.1473 | 0.0801 | 0.1038 | 0.7187 |
| 0.4015 | 10.0 | 10220 | 1.3465 | 0.1454 | 0.0813 | 0.1043 | 0.7143 |