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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: Bio_ClinicalBERT-finetuned-medicalcondition
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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_ClinicalBERT-finetuned-medicalcondition
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This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7201
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- F1 Score: 0.8254
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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: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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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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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.8002 | 1.0 | 1772 | 0.6327 | 0.7759 |
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| 0.5933 | 2.0 | 3544 | 0.5906 | 0.7934 |
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| 0.5015 | 3.0 | 5316 | 0.5768 | 0.8033 |
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| 0.4265 | 4.0 | 7088 | 0.5792 | 0.8099 |
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| 0.3698 | 5.0 | 8860 | 0.6030 | 0.8109 |
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| 0.3229 | 6.0 | 10632 | 0.6366 | 0.8167 |
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| 0.2907 | 7.0 | 12404 | 0.6671 | 0.8198 |
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| 0.2649 | 8.0 | 14176 | 0.6850 | 0.8237 |
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| 0.2477 | 9.0 | 15948 | 0.7072 | 0.8247 |
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| 0.2348 | 10.0 | 17720 | 0.7201 | 0.8254 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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