readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: distilbert_add_GLUE_Experiment_logit_kd_cola_384
    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: 0.11335189203790383
  ---
  
  <!-- 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_add_GLUE_Experiment_logit_kd_cola_384
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE COLA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6805
  - Matthews Correlation: 0.1134
  
  ## 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: 5e-05
  - train_batch_size: 256
  - eval_batch_size: 256
  - seed: 10
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.8052        | 1.0   | 34   | 0.6842          | 0.0                  |
  | 0.7982        | 2.0   | 68   | 0.6842          | 0.0                  |
  | 0.7961        | 3.0   | 102  | 0.6841          | 0.0                  |
  | 0.7965        | 4.0   | 136  | 0.6846          | 0.0                  |
  | 0.799         | 5.0   | 170  | 0.6841          | 0.0                  |
  | 0.7956        | 6.0   | 204  | 0.6840          | 0.0                  |
  | 0.798         | 7.0   | 238  | 0.6860          | 0.0                  |
  | 0.7984        | 8.0   | 272  | 0.6839          | 0.0                  |
  | 0.7962        | 9.0   | 306  | 0.6875          | 0.0                  |
  | 0.797         | 10.0  | 340  | 0.6834          | 0.0                  |
  | 0.7951        | 11.0  | 374  | 0.6813          | 0.0                  |
  | 0.7771        | 12.0  | 408  | 0.6849          | 0.0257               |
  | 0.7055        | 13.0  | 442  | 0.7093          | 0.0764               |
  | 0.6664        | 14.0  | 476  | 0.6957          | 0.1007               |
  | 0.654         | 15.0  | 510  | 0.6805          | 0.1134               |
  | 0.6345        | 16.0  | 544  | 0.6966          | 0.1176               |
  | 0.6176        | 17.0  | 578  | 0.7439          | 0.1155               |
  | 0.6156        | 18.0  | 612  | 0.7178          | 0.1406               |
  | 0.5938        | 19.0  | 646  | 0.7192          | 0.1212               |
  | 0.582         | 20.0  | 680  | 0.7765          | 0.1506               |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  