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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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<!-- 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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# cva-quant-weighted-classifier |
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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: 0.1539 |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-06 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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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| 0.6832 | 1.0 | 4 | 0.6577 | 0.6786 | 0.7097 | 0.6111 | 0.8462 | |
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| 0.6332 | 2.0 | 8 | 0.6121 | 0.8571 | 0.8462 | 0.8462 | 0.8462 | |
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| 0.587 | 3.0 | 12 | 0.5636 | 0.8571 | 0.8462 | 0.8462 | 0.8462 | |
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| 0.5308 | 4.0 | 16 | 0.5053 | 0.8571 | 0.8462 | 0.8462 | 0.8462 | |
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| 0.4738 | 5.0 | 20 | 0.4425 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.3972 | 6.0 | 24 | 0.3848 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.3347 | 7.0 | 28 | 0.3371 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.2769 | 8.0 | 32 | 0.2950 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.2321 | 9.0 | 36 | 0.2621 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.1847 | 10.0 | 40 | 0.2343 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.1524 | 11.0 | 44 | 0.2120 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.1374 | 12.0 | 48 | 0.1935 | 0.8929 | 0.8800 | 0.9167 | 0.8462 | |
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| 0.1112 | 13.0 | 52 | 0.1792 | 0.9286 | 0.9231 | 0.9231 | 0.9231 | |
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| 0.0881 | 14.0 | 56 | 0.1687 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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| 0.0785 | 15.0 | 60 | 0.1623 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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| 0.065 | 16.0 | 64 | 0.1585 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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| 0.0625 | 17.0 | 68 | 0.1570 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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| 0.0566 | 18.0 | 72 | 0.1554 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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| 0.0587 | 19.0 | 76 | 0.1544 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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| 0.0537 | 20.0 | 80 | 0.1539 | 0.9643 | 0.9630 | 0.9286 | 1.0 | |
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### Framework versions |
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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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