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---
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license: cc0-1.0
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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: BlueBERT
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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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# BlueBERT
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This model is a fine-tuned version of [bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12](https://huggingface.co/bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6525
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- Accuracy: 0.83
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- Precision: 0.8767
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- Recall: 0.8889
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- F1: 0.8828
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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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- mixed_precision_training: Native AMP
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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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| 0.6839 | 1.0 | 50 | 0.7208 | 0.39 | 0.9231 | 0.1667 | 0.2824 |
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| 0.6594 | 2.0 | 100 | 0.5862 | 0.6 | 0.9211 | 0.4861 | 0.6364 |
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| 0.539 | 3.0 | 150 | 0.5940 | 0.66 | 0.9318 | 0.5694 | 0.7069 |
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| 0.4765 | 4.0 | 200 | 0.5675 | 0.65 | 0.9512 | 0.5417 | 0.6903 |
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| 0.3805 | 5.0 | 250 | 0.4494 | 0.79 | 0.9322 | 0.7639 | 0.8397 |
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| 0.279 | 6.0 | 300 | 0.4760 | 0.84 | 0.8784 | 0.9028 | 0.8904 |
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| 0.2016 | 7.0 | 350 | 0.5514 | 0.82 | 0.8553 | 0.9028 | 0.8784 |
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| 0.1706 | 8.0 | 400 | 0.5353 | 0.84 | 0.8889 | 0.8889 | 0.8889 |
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| 0.1164 | 9.0 | 450 | 0.7676 | 0.82 | 0.8462 | 0.9167 | 0.8800 |
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| 0.1054 | 10.0 | 500 | 0.6525 | 0.83 | 0.8767 | 0.8889 | 0.8828 |
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### Framework versions
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- Transformers 4.21.2
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- Pytorch 1.12.1+cu113
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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