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cva-quant-weighted-classifier

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  2. model.safetensors +1 -1
  3. runs/Aug02_13-23-53_a0ae54856f2b/events.out.tfevents.1722605034.a0ae54856f2b.778.1 +2 -2
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 [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5278
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- - Accuracy: 0.8214
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- - F1: 0.8148
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- - Precision: 0.7857
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- - Recall: 0.8462
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  ## Model description
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@@ -43,28 +43,38 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-06
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.6851 | 1.0 | 7 | 0.6688 | 0.5 | 0.5882 | 0.4762 | 0.7692 |
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- | 0.6626 | 2.0 | 14 | 0.6466 | 0.6786 | 0.7097 | 0.6111 | 0.8462 |
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- | 0.6353 | 3.0 | 21 | 0.6255 | 0.75 | 0.7586 | 0.6875 | 0.8462 |
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- | 0.6157 | 4.0 | 28 | 0.6029 | 0.7857 | 0.7857 | 0.7333 | 0.8462 |
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- | 0.5949 | 5.0 | 35 | 0.5822 | 0.8214 | 0.8148 | 0.7857 | 0.8462 |
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- | 0.5808 | 6.0 | 42 | 0.5638 | 0.8214 | 0.8148 | 0.7857 | 0.8462 |
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- | 0.5585 | 7.0 | 49 | 0.5493 | 0.8214 | 0.8148 | 0.7857 | 0.8462 |
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- | 0.5464 | 8.0 | 56 | 0.5376 | 0.8214 | 0.8148 | 0.7857 | 0.8462 |
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- | 0.5326 | 9.0 | 63 | 0.5304 | 0.8214 | 0.8148 | 0.7857 | 0.8462 |
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- | 0.5236 | 10.0 | 70 | 0.5278 | 0.8214 | 0.8148 | 0.7857 | 0.8462 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2017
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+ - Accuracy: 0.9643
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+ - F1: 0.9630
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+ - Precision: 0.9286
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+ - Recall: 1.0
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 20
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.6608 | 1.0 | 7 | 0.5726 | 0.7857 | 0.7857 | 0.7333 | 0.8462 |
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+ | 0.5107 | 2.0 | 14 | 0.4116 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
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+ | 0.35 | 3.0 | 21 | 0.3056 | 0.8929 | 0.8800 | 0.9167 | 0.8462 |
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+ | 0.2166 | 4.0 | 28 | 0.2485 | 0.8571 | 0.8462 | 0.8462 | 0.8462 |
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+ | 0.1356 | 5.0 | 35 | 0.1940 | 0.9286 | 0.9231 | 0.9231 | 0.9231 |
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+ | 0.0705 | 6.0 | 42 | 0.1848 | 0.9286 | 0.9231 | 0.9231 | 0.9231 |
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+ | 0.0491 | 7.0 | 49 | 0.1728 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0229 | 8.0 | 56 | 0.1725 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0129 | 9.0 | 63 | 0.1744 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0092 | 10.0 | 70 | 0.1793 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0075 | 11.0 | 77 | 0.1847 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0061 | 12.0 | 84 | 0.1890 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0058 | 13.0 | 91 | 0.1928 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0049 | 14.0 | 98 | 0.1954 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0045 | 15.0 | 105 | 0.1975 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0042 | 16.0 | 112 | 0.1990 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.004 | 17.0 | 119 | 0.2001 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0038 | 18.0 | 126 | 0.2010 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0038 | 19.0 | 133 | 0.2015 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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+ | 0.0038 | 20.0 | 140 | 0.2017 | 0.9643 | 0.9630 | 0.9286 | 1.0 |
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  ### Framework versions
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