readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - matthews_correlation
  model_index:
  - name: distilbert-base-uncased-finetuned-cola
    results:
    - task:
        name: Text Classification
        type: text-classification
      metric:
        name: Matthews Correlation
        type: matthews_correlation
        value: 0.9719066462260881
  ---
  
  <!-- 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 an unkown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1037
  - Matthews Correlation: 0.9719
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.2094        | 1.0   | 525  | 0.1069          | 0.9607               |
  | 0.0483        | 2.0   | 1050 | 0.0878          | 0.9719               |
  | 0.0296        | 3.0   | 1575 | 0.1263          | 0.9664               |
  | 0.0108        | 4.0   | 2100 | 0.1037          | 0.9719               |
  | 0.0096        | 5.0   | 2625 | 0.1065          | 0.9719               |
  
  
  ### Framework versions
  
  - Transformers 4.9.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  