readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - matthews_correlation
  model-index:
  - name: tiny-vanilla-target-glue-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. -->
  
  # tiny-vanilla-target-glue-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 None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8745
  - Matthews Correlation: 0.0651
  
  ## 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  | 0.6204          | 0.0                  |
  | 0.603         | 3.73  | 1000 | 0.6181          | 0.0                  |
  | 0.5927        | 5.6   | 1500 | 0.6231          | 0.0194               |
  | 0.5707        | 7.46  | 2000 | 0.6366          | 0.0149               |
  | 0.5399        | 9.33  | 2500 | 0.6549          | 0.0646               |
  | 0.5169        | 11.19 | 3000 | 0.6769          | 0.0736               |
  | 0.4954        | 13.06 | 3500 | 0.6856          | 0.0742               |
  | 0.4724        | 14.93 | 4000 | 0.7246          | 0.0777               |
  | 0.4552        | 16.79 | 4500 | 0.7517          | 0.0767               |
  | 0.434         | 18.66 | 5000 | 0.7868          | 0.0832               |
  | 0.4192        | 20.52 | 5500 | 0.8144          | 0.0664               |
  | 0.4092        | 22.39 | 6000 | 0.8025          | 0.0670               |
  | 0.3874        | 24.25 | 6500 | 0.8745          | 0.0651               |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  