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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 |
|---|---|---|---|---|---|---|---|
| 1.1723 | 1.0 | 664 | 0.9597 | 0.1022 | 0.0284 | 0.0445 | 0.7705 |
| 1.0015 | 2.0 | 1328 | 0.9761 | 0.0908 | 0.0906 | 0.0907 | 0.7382 |
| 0.8659 | 3.0 | 1992 | 0.9519 | 0.1174 | 0.0808 | 0.0957 | 0.7578 |
| 0.6297 | 4.0 | 2656 | 1.0252 | 0.0920 | 0.0995 | 0.0956 | 0.7285 |
| 0.5716 | 5.0 | 3320 | 1.0423 | 0.1004 | 0.0879 | 0.0938 | 0.7402 |
| 0.5236 | 6.0 | 3984 | 1.0918 | 0.1041 | 0.0906 | 0.0969 | 0.7435 |
| 0.3943 | 7.0 | 4648 | 1.1581 | 0.0911 | 0.1030 | 0.0967 | 0.7060 |
| 0.3713 | 8.0 | 5312 | 1.2021 | 0.0902 | 0.0933 | 0.0917 | 0.7099 |
| 0.3525 | 9.0 | 5976 | 1.2281 | 0.0918 | 0.0986 | 0.0951 | 0.7148 |
| 0.296 | 10.0 | 6640 | 1.2455 | 0.0809 | 0.0915 | 0.0859 | 0.7099 |