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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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- 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: ADE-Bio_ClinicalBERT-NER |
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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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# ADE-Bio_ClinicalBERT-NER |
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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: 0.1926 |
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- Precision: 0.7830 |
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- Recall: 0.8811 |
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- F1: 0.8291 |
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- Accuracy: 0.9437 |
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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: 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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.2389 | 1.0 | 201 | 0.2100 | 0.7155 | 0.8292 | 0.7681 | 0.9263 | |
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| 0.0648 | 2.0 | 402 | 0.1849 | 0.7716 | 0.8711 | 0.8183 | 0.9392 | |
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| 0.2825 | 3.0 | 603 | 0.1856 | 0.7834 | 0.8788 | 0.8284 | 0.9422 | |
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| 0.199 | 4.0 | 804 | 0.1875 | 0.7796 | 0.8781 | 0.8259 | 0.9430 | |
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| 0.0404 | 5.0 | 1005 | 0.1926 | 0.7830 | 0.8811 | 0.8291 | 0.9437 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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