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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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datasets: |
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- bc2gm_corpus |
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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: bc2gm_corpus-Bio_ClinicalBERT-finetuned-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: bc2gm_corpus |
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type: bc2gm_corpus |
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args: bc2gm_corpus |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7853881278538812 |
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- name: Recall |
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type: recall |
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value: 0.8158102766798419 |
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- name: F1 |
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type: f1 |
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value: 0.8003101977510663 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9758965601366187 |
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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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# bc2gm_corpus-Bio_ClinicalBERT-finetuned-ner |
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This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the bc2gm_corpus dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1505 |
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- Precision: 0.7854 |
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- Recall: 0.8158 |
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- F1: 0.8003 |
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- Accuracy: 0.9759 |
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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: 10 |
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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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| 0.0981 | 1.0 | 782 | 0.0712 | 0.7228 | 0.7948 | 0.7571 | 0.9724 | |
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| 0.0509 | 2.0 | 1564 | 0.0687 | 0.7472 | 0.8199 | 0.7818 | 0.9746 | |
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| 0.0121 | 3.0 | 2346 | 0.0740 | 0.7725 | 0.8011 | 0.7866 | 0.9747 | |
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| 0.0001 | 4.0 | 3128 | 0.1009 | 0.7618 | 0.8251 | 0.7922 | 0.9741 | |
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| 0.0042 | 5.0 | 3910 | 0.1106 | 0.7757 | 0.8185 | 0.7965 | 0.9754 | |
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| 0.0015 | 6.0 | 4692 | 0.1182 | 0.7812 | 0.8111 | 0.7958 | 0.9758 | |
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| 0.0001 | 7.0 | 5474 | 0.1283 | 0.7693 | 0.8275 | 0.7973 | 0.9753 | |
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| 0.0072 | 8.0 | 6256 | 0.1376 | 0.7863 | 0.8158 | 0.8008 | 0.9762 | |
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| 0.0045 | 9.0 | 7038 | 0.1468 | 0.7856 | 0.8180 | 0.8015 | 0.9761 | |
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| 0.0 | 10.0 | 7820 | 0.1505 | 0.7854 | 0.8158 | 0.8003 | 0.9759 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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