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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: bert-section-classification-v5 |
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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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# bert-section-classification-v5 |
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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: 0.9710 |
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- Accuracy: 0.8644 |
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- Precision: 0.8671 |
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- Recall: 0.8644 |
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- F1: 0.8642 |
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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: 3e-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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- lr_scheduler_warmup_steps: 300 |
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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 | 370 | 1.3245 | 0.2555 | 0.3090 | 0.2555 | 0.1199 | |
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| 1.3542 | 2.0 | 740 | 1.2024 | 0.7319 | 0.8115 | 0.7319 | 0.7163 | |
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| 1.2122 | 3.0 | 1110 | 1.1008 | 0.8675 | 0.8756 | 0.8675 | 0.8678 | |
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| 1.2122 | 4.0 | 1480 | 1.0275 | 0.8770 | 0.8834 | 0.8770 | 0.8773 | |
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| 1.082 | 5.0 | 1850 | 0.9855 | 0.8707 | 0.8751 | 0.8707 | 0.8706 | |
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| 1.003 | 6.0 | 2220 | 0.9710 | 0.8644 | 0.8671 | 0.8644 | 0.8642 | |
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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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