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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 |
|---|---|---|---|---|---|---|---|
| 1.1758 | 1.0 | 664 | 0.9597 | 0.0604 | 0.0169 | 0.0264 | 0.7783 |
| 1.0125 | 2.0 | 1328 | 0.9865 | 0.0674 | 0.0677 | 0.0676 | 0.7377 |
| 0.8824 | 3.0 | 1992 | 0.9705 | 0.0801 | 0.0553 | 0.0654 | 0.7506 |
| 0.6425 | 4.0 | 2656 | 1.0209 | 0.0755 | 0.0732 | 0.0744 | 0.7298 |
| 0.582 | 5.0 | 3320 | 1.0497 | 0.0780 | 0.0672 | 0.0722 | 0.7478 |
| 0.5384 | 6.0 | 3984 | 1.0894 | 0.0777 | 0.0672 | 0.0721 | 0.7360 |
| 0.404 | 7.0 | 4648 | 1.1506 | 0.0767 | 0.0807 | 0.0786 | 0.7103 |
| 0.3884 | 8.0 | 5312 | 1.1851 | 0.0752 | 0.0782 | 0.0767 | 0.7121 |
| 0.3699 | 9.0 | 5976 | 1.2204 | 0.0789 | 0.0772 | 0.0780 | 0.7158 |
| 0.2998 | 10.0 | 6640 | 1.2426 | 0.0806 | 0.0817 | 0.0811 | 0.7135 |