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This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown 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 | Accuracy |
|---|---|---|---|---|
| 0.5335 | 1.0 | 5 | 0.2744 | 0.95 |
| 0.1607 | 2.0 | 10 | 0.0485 | 1.0 |
| 0.0358 | 3.0 | 15 | 0.0136 | 1.0 |
| 0.0092 | 4.0 | 20 | 0.0055 | 1.0 |
| 0.0049 | 5.0 | 25 | 0.0033 | 1.0 |
| 0.0041 | 6.0 | 30 | 0.0020 | 1.0 |
| 0.0019 | 7.0 | 35 | 0.0015 | 1.0 |
| 0.0013 | 8.0 | 40 | 0.0013 | 1.0 |
| 0.0015 | 9.0 | 45 | 0.0011 | 1.0 |
| 0.0017 | 10.0 | 50 | 0.0010 | 1.0 |
| 0.0007 | 11.0 | 55 | 0.0010 | 1.0 |
| 0.0010 | 12.0 | 60 | 0.0009 | 1.0 |
| 0.0006 | 13.0 | 65 | 0.0009 | 1.0 |
| 0.0008 | 14.0 | 70 | 0.0009 | 1.0 |
| 0.0005 | 15.0 | 75 | 0.0009 | 1.0 |