readme: ---
  license: cc0-1.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: BlueBERT
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # BlueBERT
  
  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.
  It achieves the following results on the evaluation set:
  - Loss: 0.6525
  - Accuracy: 0.83
  - Precision: 0.8767
  - Recall: 0.8889
  - F1: 0.8828
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.6839        | 1.0   | 50   | 0.7208          | 0.39     | 0.9231    | 0.1667 | 0.2824 |
  | 0.6594        | 2.0   | 100  | 0.5862          | 0.6      | 0.9211    | 0.4861 | 0.6364 |
  | 0.539         | 3.0   | 150  | 0.5940          | 0.66     | 0.9318    | 0.5694 | 0.7069 |
  | 0.4765        | 4.0   | 200  | 0.5675          | 0.65     | 0.9512    | 0.5417 | 0.6903 |
  | 0.3805        | 5.0   | 250  | 0.4494          | 0.79     | 0.9322    | 0.7639 | 0.8397 |
  | 0.279         | 6.0   | 300  | 0.4760          | 0.84     | 0.8784    | 0.9028 | 0.8904 |
  | 0.2016        | 7.0   | 350  | 0.5514          | 0.82     | 0.8553    | 0.9028 | 0.8784 |
  | 0.1706        | 8.0   | 400  | 0.5353          | 0.84     | 0.8889    | 0.8889 | 0.8889 |
  | 0.1164        | 9.0   | 450  | 0.7676          | 0.82     | 0.8462    | 0.9167 | 0.8800 |
  | 0.1054        | 10.0  | 500  | 0.6525          | 0.83     | 0.8767    | 0.8889 | 0.8828 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  