readme: ---
  language:
  - en
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: roberta-base-cola
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE COLA
        type: glue
        args: cola
      metrics:
      - name: Matthews Correlation
        type: matthews_correlation
        value: 0.5960380981891474
  ---
  
  <!-- 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. -->
  
  # roberta-base-cola
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE COLA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3829
  - Matthews Correlation: 0.5960
  
  ## 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: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.06
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.5446        | 0.93  | 500  | 0.4946          | 0.5260               |
  | 0.3638        | 1.87  | 1000 | 0.3829          | 0.5960               |
  | 0.2658        | 2.8   | 1500 | 0.6063          | 0.6018               |
  | 0.2097        | 3.74  | 2000 | 0.7701          | 0.5931               |
  | 0.1806        | 4.67  | 2500 | 0.8445          | 0.6181               |
  | 0.1405        | 5.61  | 3000 | 0.8823          | 0.5978               |
  | 0.1091        | 6.54  | 3500 | 1.0399          | 0.5806               |
  | 0.0758        | 7.48  | 4000 | 1.0440          | 0.6220               |
  | 0.0625        | 8.41  | 4500 | 1.1968          | 0.5981               |
  | 0.0456        | 9.35  | 5000 | 1.2408          | 0.6008               |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.7.1
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  