readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: electra-base-discriminator-CoLA
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: GLUE COLA
        type: glue
        config: cola
        split: validation
        args: cola
      metrics:
      - name: Matthews Correlation
        type: matthews_correlation
        value: 0.6579677841732349
  widget:
    - text: The cat sat on the mat.
      example_title: Correct grammatical sentence
    - text: Me and my friend going to the store.
      example_title: Incorrect subject-verb agreement
    - text: I ain't got no money.
      example_title: Incorrect verb conjugation and double negative
    - text: She don't like pizza no more.
      example_title: Incorrect verb conjugation and double negative
    - text: They is arriving tomorrow.
      example_title: Incorrect verb conjugation
  ---
  
  # electra-base-discriminator-CoLA
  
  This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the GLUE COLA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3542
  - Matthews Correlation: 0.6580
  
  ## Model description
  
  Trying to find a decent optimum between accuracy/quality and inference speed.
  
  
  ```json
  {
      "epoch": 8.0,
      "eval_loss": 0.3541961908340454,
      "eval_matthews_correlation": 0.6579677841732349,
      "eval_runtime": 1.9552,
      "eval_samples": 1043,
      "eval_samples_per_second": 533.451,
      "eval_steps_per_second": 33.756
  }
  ```
  ## 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: 8e-05
  - train_batch_size: 128
  - eval_batch_size: 16
  - seed: 22165
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.03
  - num_epochs: 8.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.4004        | 1.0   | 67   | 0.3569          | 0.6340               |
  | 0.2843        | 2.0   | 134  | 0.3542          | 0.6580               |
  | 0.1228        | 3.0   | 201  | 0.4201          | 0.6412               |
  | 0.0989        | 4.0   | 268  | 0.4780          | 0.6757               |
  | 0.0681        | 5.0   | 335  | 0.4900          | 0.6925               |
  | 0.0506        | 6.0   | 402  | 0.5837          | 0.6785               |
  | 0.0093        | 7.0   | 469  | 0.6298          | 0.6652               |
  | 0.0244        | 8.0   | 536  | 0.6292          | 0.6750               |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.1
  