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---
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library_name: transformers
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license: mit
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base_model: emilyalsentzer/Bio_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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model-index:
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- name: bio-mqa
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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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# bio-mqa
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This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1830
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- Accuracy: 0.6185
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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: 1e-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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.0695 | 1.0 | 18387 | 0.9820 | 0.5833 |
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| 0.8957 | 2.0 | 36774 | 0.9734 | 0.6154 |
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| 0.7079 | 3.0 | 55161 | 1.1830 | 0.6185 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.6.0+cu118
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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