readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-sst2-finetuned-sst2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: glue
        type: glue
        config: sst2
        split: train
        args: sst2
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9071100917431193
  ---
  
  <!-- 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-base-uncased-finetuned-sst2-finetuned-sst2
  
  This model was trained from scratch on the glue dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3156
  - Accuracy: 0.9071
  
  ## 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: 256
  - eval_batch_size: 256
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 264  | 0.2830          | 0.9014   |
  | 0.111         | 2.0   | 528  | 0.3156          | 0.9071   |
  | 0.111         | 3.0   | 792  | 0.3351          | 0.8979   |
  | 0.0688        | 4.0   | 1056 | 0.3377          | 0.9037   |
  | 0.0688        | 5.0   | 1320 | 0.3526          | 0.9048   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  