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This model is a fine-tuned version of bert-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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6808 | 1.0 | 1839 | 1.0655 | 0.0257 | 0.0169 | 0.0204 | 0.7448 |
| 0.3777 | 2.0 | 3678 | 1.2309 | 0.0273 | 0.0234 | 0.0252 | 0.7075 |
| 0.2877 | 3.0 | 5517 | 1.2290 | 0.0383 | 0.0383 | 0.0383 | 0.7303 |
| 0.2232 | 4.0 | 7356 | 1.2724 | 0.0454 | 0.0458 | 0.0456 | 0.7317 |
| 0.19 | 5.0 | 9195 | 1.2874 | 0.0422 | 0.0448 | 0.0435 | 0.7337 |
| 0.1594 | 6.0 | 11034 | 1.3996 | 0.0412 | 0.0413 | 0.0413 | 0.7146 |
| 0.1438 | 7.0 | 12873 | 1.4436 | 0.0376 | 0.0403 | 0.0389 | 0.7128 |
| 0.131 | 8.0 | 14712 | 1.5348 | 0.0410 | 0.0528 | 0.0462 | 0.7001 |
| 0.1177 | 9.0 | 16551 | 1.5470 | 0.0407 | 0.0513 | 0.0454 | 0.7066 |
| 0.0935 | 10.0 | 18390 | 1.5875 | 0.0410 | 0.0528 | 0.0462 | 0.7097 |