readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: bert-tiny-target-cola
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        config: cola
        split: train
        args: cola
      metrics:
      - name: Matthews Correlation
        type: matthews_correlation
        value: 0.14578167065086653
  ---
  
  <!-- 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-tiny-target-cola
  
  This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6626
  - Matthews Correlation: 0.1458
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: constant
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.6124        | 1.87  | 500  | 0.6192          | 0.0                  |
  | 0.6016        | 3.73  | 1000 | 0.6167          | 0.0                  |
  | 0.5838        | 5.6   | 1500 | 0.6166          | 0.0149               |
  | 0.5555        | 7.46  | 2000 | 0.6344          | 0.0465               |
  | 0.5272        | 9.33  | 2500 | 0.6542          | 0.1399               |
  | 0.5058        | 11.19 | 3000 | 0.6626          | 0.1458               |
  | 0.4791        | 13.06 | 3500 | 0.6868          | 0.1192               |
  | 0.4577        | 14.93 | 4000 | 0.7215          | 0.1230               |
  | 0.4425        | 16.79 | 4500 | 0.7322          | 0.1243               |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  