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DeBERTaV3_model_V4

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deberta-v2
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  1. README.md +17 -17
  2. model.safetensors +1 -1
  3. runs/Jun11_10-51-42_0417-111206-hkgnini8-10-45-16-10/events.out.tfevents.1718103103.0417-111206-hkgnini8-10-45-16-10.1902.4 +3 -0
  4. runs/Jun11_10-57-31_0417-111206-hkgnini8-10-45-16-10/events.out.tfevents.1718103452.0417-111206-hkgnini8-10-45-16-10.1902.5 +3 -0
  5. runs/Jun11_10-57-31_0417-111206-hkgnini8-10-45-16-10/events.out.tfevents.1718106172.0417-111206-hkgnini8-10-45-16-10.1902.6 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1536
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- - Accuracy: 0.9511
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- - F1: 0.7447
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- - Precision: 0.7799
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- - Recall: 0.7126
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  ## Model description
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@@ -55,18 +55,18 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 1.0 | 140 | 0.2890 | 0.9 | 0.0 | 0.0 | 0.0 |
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- | No log | 2.0 | 280 | 0.2285 | 0.9109 | 0.2791 | 0.7317 | 0.1724 |
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- | No log | 3.0 | 420 | 0.1791 | 0.9420 | 0.6456 | 0.8288 | 0.5287 |
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- | 0.2695 | 4.0 | 560 | 0.1662 | 0.9460 | 0.7117 | 0.7632 | 0.6667 |
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- | 0.2695 | 5.0 | 700 | 0.1536 | 0.9511 | 0.7447 | 0.7799 | 0.7126 |
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- | 0.2695 | 6.0 | 840 | 0.1536 | 0.9494 | 0.7396 | 0.7622 | 0.7184 |
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- | 0.2695 | 7.0 | 980 | 0.1569 | 0.95 | 0.7418 | 0.7669 | 0.7184 |
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- | 0.0905 | 8.0 | 1120 | 0.1656 | 0.9489 | 0.7405 | 0.7515 | 0.7299 |
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- | 0.0905 | 9.0 | 1260 | 0.1640 | 0.9489 | 0.7420 | 0.7485 | 0.7356 |
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- | 0.0905 | 10.0 | 1400 | 0.1745 | 0.9460 | 0.7235 | 0.7410 | 0.7069 |
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- | 0.0386 | 11.0 | 1540 | 0.1679 | 0.95 | 0.7464 | 0.7574 | 0.7356 |
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- | 0.0386 | 12.0 | 1680 | 0.1683 | 0.9511 | 0.7507 | 0.7665 | 0.7356 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1557
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+ - Accuracy: 0.9485
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+ - F1: 0.7248
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+ - Precision: 0.7778
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+ - Recall: 0.6786
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 159 | 0.2879 | 0.9 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 318 | 0.2226 | 0.9189 | 0.3457 | 0.8936 | 0.2143 |
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+ | No log | 3.0 | 477 | 0.1883 | 0.9347 | 0.5975 | 0.7787 | 0.4847 |
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+ | 0.2618 | 4.0 | 636 | 0.1557 | 0.9485 | 0.7248 | 0.7778 | 0.6786 |
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+ | 0.2618 | 5.0 | 795 | 0.1593 | 0.9480 | 0.7273 | 0.7640 | 0.6939 |
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+ | 0.2618 | 6.0 | 954 | 0.1564 | 0.9505 | 0.7413 | 0.7765 | 0.7092 |
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+ | 0.0829 | 7.0 | 1113 | 0.1636 | 0.9520 | 0.7552 | 0.7713 | 0.7398 |
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+ | 0.0829 | 8.0 | 1272 | 0.1761 | 0.9485 | 0.7363 | 0.7540 | 0.7194 |
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+ | 0.0829 | 9.0 | 1431 | 0.1686 | 0.9536 | 0.7599 | 0.7869 | 0.7347 |
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+ | 0.0297 | 10.0 | 1590 | 0.1807 | 0.9526 | 0.7584 | 0.7725 | 0.7449 |
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+ | 0.0297 | 11.0 | 1749 | 0.1765 | 0.9531 | 0.7629 | 0.7708 | 0.7551 |
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+ | 0.0297 | 12.0 | 1908 | 0.1790 | 0.9536 | 0.7649 | 0.7749 | 0.7551 |
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  ### Framework versions
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