readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - matthews_correlation
  model-index:
  - name: mobilebert_add_GLUE_Experiment_logit_kd_cola_256
    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: 0.0
  ---
  
  <!-- 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. -->
  
  # mobilebert_add_GLUE_Experiment_logit_kd_cola_256
  
  This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE COLA dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6707
  - Matthews Correlation: 0.0
  
  ## 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: 5e-05
  - train_batch_size: 128
  - eval_batch_size: 128
  - 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
  |:-------------:|:-----:|:----:|:---------------:|:--------------------:|
  | 0.8133        | 1.0   | 67   | 0.6864          | 0.0                  |
  | 0.797         | 2.0   | 134  | 0.6866          | 0.0                  |
  | 0.7964        | 3.0   | 201  | 0.6832          | 0.0                  |
  | 0.7948        | 4.0   | 268  | 0.6827          | 0.0                  |
  | 0.7934        | 5.0   | 335  | 0.6787          | 0.0                  |
  | 0.7759        | 6.0   | 402  | 0.6742          | 0.0                  |
  | 0.761         | 7.0   | 469  | 0.6777          | 0.0                  |
  | 0.756         | 8.0   | 536  | 0.6754          | 0.0                  |
  | 0.7471        | 9.0   | 603  | 0.6772          | 0.0                  |
  | 0.7457        | 10.0  | 670  | 0.6760          | 0.0                  |
  | 0.7419        | 11.0  | 737  | 0.6707          | 0.0                  |
  | 0.741         | 12.0  | 804  | 0.6729          | 0.0                  |
  | 0.7351        | 13.0  | 871  | 0.6836          | 0.0758               |
  | 0.7349        | 14.0  | 938  | 0.6769          | 0.0795               |
  | 0.7357        | 15.0  | 1005 | 0.6715          | 0.0315               |
  | 0.7333        | 16.0  | 1072 | 0.6813          | 0.0894               |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.14.0a0+410ce96
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  