readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: bert-small-finetuned-glue-rte
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        config: rte
        split: train
        args: rte
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.631768953068592
  ---
  
  <!-- 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. -->
  
  # bert-small-finetuned-glue-rte
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8715
  - Accuracy: 0.6318
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 128
  - 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 | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 2.62  | 50   | 1.8285          | 0.6318   |
  | No log        | 5.26  | 100  | 2.0806          | 0.6462   |
  | No log        | 7.87  | 150  | 2.1598          | 0.6282   |
  | No log        | 10.51 | 200  | 2.2774          | 0.6318   |
  | No log        | 13.15 | 250  | 2.3676          | 0.6245   |
  | No log        | 15.77 | 300  | 2.4581          | 0.6462   |
  | No log        | 18.41 | 350  | 2.6175          | 0.6354   |
  | No log        | 21.05 | 400  | 2.6697          | 0.6354   |
  | No log        | 23.67 | 450  | 2.7717          | 0.6354   |
  | 0.0101        | 26.31 | 500  | 2.7975          | 0.6462   |
  | 0.0101        | 28.92 | 550  | 2.8532          | 0.6390   |
  | 0.0101        | 31.56 | 600  | 2.9054          | 0.6209   |
  | 0.0101        | 34.21 | 650  | 2.8715          | 0.6318   |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  