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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ncbi_disease |
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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: biobert_v1.1_pubmed-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: ncbi_disease |
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type: ncbi_disease |
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args: ncbi_disease |
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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.9827274990663513 |
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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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# biobert_v1.1_pubmed-finetuned-ner |
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This model is a fine-tuned version of [monologg/biobert_v1.1_pubmed](https://huggingface.co/monologg/biobert_v1.1_pubmed) on the ncbi_disease dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0657 |
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- Precision: 0.8338 |
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- Recall: 0.8933 |
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- F1: 0.8625 |
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- Accuracy: 0.9827 |
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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: 3 |
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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 | 340 | 0.0612 | 0.8268 | 0.85 | 0.8382 | 0.9806 | |
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| 0.0987 | 2.0 | 680 | 0.0604 | 0.8397 | 0.8848 | 0.8616 | 0.9829 | |
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| 0.0272 | 3.0 | 1020 | 0.0657 | 0.8338 | 0.8933 | 0.8625 | 0.9827 | |
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### Framework versions |
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- Transformers 4.8.1 |
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- Pytorch 1.9.0 |
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- Datasets 1.6.2 |
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- Tokenizers 0.10.3 |
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