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--- |
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library_name: transformers |
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base_model: medicalai/ClinicalBERT |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: section-classification-v2 |
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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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# section-classification-v2 |
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This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9439 |
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- Accuracy: 0.7473 |
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- Precision: 0.6549 |
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- Recall: 0.7473 |
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- F1: 0.6918 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 434 | 1.1859 | 0.6909 | 0.6054 | 0.6909 | 0.6422 | |
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| 1.2827 | 2.0 | 868 | 1.1446 | 0.7258 | 0.6268 | 0.7258 | 0.6721 | |
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| 1.1164 | 3.0 | 1302 | 1.0256 | 0.75 | 0.6546 | 0.75 | 0.6946 | |
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| 1.0728 | 4.0 | 1736 | 0.9982 | 0.7473 | 0.6517 | 0.7473 | 0.6921 | |
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| 1.0206 | 5.0 | 2170 | 0.9582 | 0.7446 | 0.6530 | 0.7446 | 0.6891 | |
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| 0.9745 | 6.0 | 2604 | 0.9439 | 0.7473 | 0.6549 | 0.7473 | 0.6918 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Tokenizers 0.21.1 |
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