readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - matthews_correlation
  model-index:
  - name: distilbert-base-uncased-finetuned-cola-4
    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. -->
  
  # distilbert-base-uncased-finetuned-cola-4
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0011
  - Matthews Correlation: 1.0
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | No log        | 1.0   | 104  | 0.0243          | 1.0                  |
  | No log        | 2.0   | 208  | 0.0074          | 1.0                  |
  | No log        | 3.0   | 312  | 0.0041          | 1.0                  |
  | No log        | 4.0   | 416  | 0.0028          | 1.0                  |
  | 0.0929        | 5.0   | 520  | 0.0021          | 1.0                  |
  | 0.0929        | 6.0   | 624  | 0.0016          | 1.0                  |
  | 0.0929        | 7.0   | 728  | 0.0014          | 1.0                  |
  | 0.0929        | 8.0   | 832  | 0.0012          | 1.0                  |
  | 0.0929        | 9.0   | 936  | 0.0012          | 1.0                  |
  | 0.0021        | 10.0  | 1040 | 0.0011          | 1.0                  |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  