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alex-miller/cva-quant-weighted-classifier
cva-quant-weighted-classifier is a machine learning model from alex-miller. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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From the Hugging Face model README
This model is a fine-tuned version of alex-miller/ODABert on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6832 | 1.0 | 4 | 0.6577 | 0.6786 | 0.7097 | 0.6111 | 0.8462 |
| 0.6332 | 2.0 | 8 | 0.6121 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
| 0.587 | 3.0 | 12 | 0.5636 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
| 0.5308 | 4.0 | 16 | 0.5053 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
| 0.4738 | 5.0 | 20 | 0.4425 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.3972 | 6.0 | 24 | 0.3848 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.3347 | 7.0 | 28 | 0.3371 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.2769 | 8.0 | 32 | 0.2950 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.2321 | 9.0 | 36 | 0.2621 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1847 | 10.0 | 40 | 0.2343 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1524 | 11.0 | 44 | 0.2120 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1374 | 12.0 | 48 | 0.1935 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
| 0.1112 | 13.0 | 52 | 0.1792 | 0.9286 | 0.9231 | 0.9231 | 0.9231 |
| 0.0881 | 14.0 | 56 | 0.1687 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0785 | 15.0 | 60 | 0.1623 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.065 | 16.0 | 64 | 0.1585 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0625 | 17.0 | 68 | 0.1570 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0566 | 18.0 | 72 | 0.1554 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0587 | 19.0 | 76 | 0.1544 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
| 0.0537 | 20.0 | 80 | 0.1539 | 0.9643 | 0.9630 | 0.9286 | 1.0 |