readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - null
  metrics:
  - accuracy
  model-index:
  - name: biobert-base-cased-v1.1-finetuned-pubmedqa
    results:
    - task:
        name: Text Classification
        type: text-classification
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.5
  ---
  
  <!-- 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. -->
  
  # biobert-base-cased-v1.1-finetuned-pubmedqa
  
  This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3182
  - Accuracy: 0.5
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 57   | 0.8591          | 0.58     |
  | No log        | 2.0   | 114  | 0.9120          | 0.58     |
  | No log        | 3.0   | 171  | 0.8159          | 0.62     |
  | No log        | 4.0   | 228  | 1.1651          | 0.54     |
  | No log        | 5.0   | 285  | 1.2350          | 0.6      |
  | No log        | 6.0   | 342  | 1.5563          | 0.68     |
  | No log        | 7.0   | 399  | 2.0233          | 0.58     |
  | No log        | 8.0   | 456  | 2.2054          | 0.5      |
  | 0.4463        | 9.0   | 513  | 2.2434          | 0.5      |
  | 0.4463        | 10.0  | 570  | 2.3182          | 0.5      |
  
  
  ### Framework versions
  
  - Transformers 4.10.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  