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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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metrics:
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- accuracy
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- f1
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model-index:
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- name: Bio_ClinicalBERT-finetuned-20pc
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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-20pc
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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: 1.3213
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- Accuracy: 0.8580
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- F1: 0.4390
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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: 16
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- eval_batch_size: 16
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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 | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 41 | 1.0399 | 0.8642 | 0.45 |
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| No log | 2.0 | 82 | 1.1412 | 0.8519 | 0.4 |
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| No log | 3.0 | 123 | 1.2759 | 0.8642 | 0.45 |
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| No log | 4.0 | 164 | 1.2953 | 0.8519 | 0.5385 |
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| No log | 5.0 | 205 | 1.3213 | 0.8580 | 0.4390 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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