readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: bert-base-cased-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: 0.5794528111058918
  ---
  
  <!-- 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. -->
  
  # bert-base-cased-cola
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE COLA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3976
  - Matthews Correlation: 0.5795
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.5733        | 0.93  | 500  | 0.4877          | 0.5001               |
  | 0.3426        | 1.87  | 1000 | 0.3976          | 0.5795               |
  | 0.2321        | 2.8   | 1500 | 0.6284          | 0.6034               |
  | 0.1599        | 3.74  | 2000 | 0.6997          | 0.5718               |
  | 0.123         | 4.67  | 2500 | 0.8962          | 0.5624               |
  | 0.0888        | 5.61  | 3000 | 0.8743          | 0.5857               |
  | 0.0659        | 6.54  | 3500 | 0.9159          | 0.5962               |
  | 0.0385        | 7.48  | 4000 | 1.2283          | 0.5704               |
  | 0.0299        | 8.41  | 4500 | 1.2601          | 0.5662               |
  | 0.0211        | 9.35  | 5000 | 1.2885          | 0.5629               |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.7.1
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  