readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: roberta-base-finetuned-cola
    results: []
  ---
  
  <!-- 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-finetuned-cola
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4211
  - Matthews Correlation: 0.6279
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - distributed_type: IPU
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 64
  - total_eval_batch_size: 20
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - training precision: Mixed Precision
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.4218        | 1.0   | 133  | 0.4236          | 0.5243               |
  | 0.2077        | 2.0   | 266  | 0.3970          | 0.5930               |
  | 0.184         | 3.0   | 399  | 0.4211          | 0.6279               |
  | 0.1807        | 4.0   | 532  | 0.4854          | 0.6197               |
  | 0.1405        | 5.0   | 665  | 0.5693          | 0.5968               |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.0+cpu
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  