readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: tiny-bert-sst2-distilled
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        args: sst2
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8325688073394495
  ---
  
  <!-- 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-bert-sst2-distilled
  
  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 glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7305
  - Accuracy: 0.8326
  
  ## 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: 0.0007199555649276667
  - train_batch_size: 1024
  - eval_batch_size: 1024
  - seed: 33
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 7
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.77          | 1.0   | 66   | 1.6939          | 0.8165   |
  | 0.729         | 2.0   | 132  | 1.5090          | 0.8326   |
  | 0.5242        | 3.0   | 198  | 1.5369          | 0.8257   |
  | 0.4017        | 4.0   | 264  | 1.7025          | 0.8326   |
  | 0.327         | 5.0   | 330  | 1.6743          | 0.8245   |
  | 0.2749        | 6.0   | 396  | 1.7305          | 0.8337   |
  | 0.2521        | 7.0   | 462  | 1.7305          | 0.8326   |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.1
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  