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--- |
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license: mit |
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base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: test |
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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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# test |
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This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4018 |
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- Accuracy: 0.8207 |
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- Precision: 0.8202 |
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- Recall: 0.8207 |
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- F1: 0.8202 |
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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: 3e-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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.4749 | 1.0 | 417 | 0.4018 | 0.8207 | 0.8202 | 0.8207 | 0.8202 | |
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| 0.0976 | 2.0 | 834 | 0.4443 | 0.8189 | 0.8234 | 0.8189 | 0.8197 | |
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| 0.0061 | 3.0 | 1251 | 0.7378 | 0.8213 | 0.8233 | 0.8213 | 0.8219 | |
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| 0.3159 | 4.0 | 1668 | 0.9154 | 0.8094 | 0.8092 | 0.8094 | 0.8092 | |
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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 2.15.0 |
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- Tokenizers 0.15.0 |
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