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--- |
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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model |
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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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# NLP-HIBA_DisTEMIST_fine_tuned_ClinicalBERT-pretrained-model |
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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: 0.2644 |
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- Precision: 0.5331 |
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- Recall: 0.5170 |
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- F1: 0.5249 |
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- Accuracy: 0.9319 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 71 | 0.2155 | 0.4953 | 0.4904 | 0.4929 | 0.9230 | |
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| No log | 2.0 | 142 | 0.2250 | 0.5350 | 0.4910 | 0.5121 | 0.9314 | |
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| No log | 3.0 | 213 | 0.2293 | 0.5373 | 0.5071 | 0.5218 | 0.9327 | |
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| No log | 4.0 | 284 | 0.2374 | 0.5562 | 0.4978 | 0.5254 | 0.9344 | |
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| No log | 5.0 | 355 | 0.2644 | 0.5331 | 0.5170 | 0.5249 | 0.9319 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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