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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: alex-miller/ODABert
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: cva-quant-weighted-classifier
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # cva-quant-weighted-classifier
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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