readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: distilbert-base-uncased-finetuned-cola
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        args: cola
      metrics:
      - name: Matthews Correlation
        type: matthews_correlation
        value: 0.5439723028804963
  ---
  
  <!-- 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. -->
  
  # distilbert-base-uncased-finetuned-cola
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8336
  - Matthews Correlation: 0.5440
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.5211        | 1.0   | 535  | 0.5317          | 0.4158               |
  | 0.3505        | 2.0   | 1070 | 0.5131          | 0.4542               |
  | 0.2383        | 3.0   | 1605 | 0.5371          | 0.5335               |
  | 0.1772        | 4.0   | 2140 | 0.7725          | 0.5376               |
  | 0.1241        | 5.0   | 2675 | 0.8336          | 0.5440               |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.1+cpu
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  