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--- |
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license: mit |
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base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext |
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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: PubMedBERT_BC5CDR_NER_new |
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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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# PubMedBERT_BC5CDR_NER_new |
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0805 |
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- Precision: 0.9857 |
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- Recall: 0.9821 |
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- F1: 0.9839 |
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- Accuracy: 0.9769 |
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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 | 286 | 0.0837 | 0.9831 | 0.9782 | 0.9806 | 0.9725 | |
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| 0.126 | 2.0 | 572 | 0.0824 | 0.9847 | 0.9784 | 0.9815 | 0.9740 | |
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| 0.126 | 3.0 | 858 | 0.0805 | 0.9857 | 0.9821 | 0.9839 | 0.9769 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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