readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - sst2
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-sst2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: sst2
        type: sst2
        config: default
        split: train
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.876
  ---
  
  <!-- 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-base-uncased-sst2
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the sst2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9312
  - Accuracy: 0.876
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 125  | 1.0209          | 0.836    |
  | No log        | 2.0   | 250  | 1.0430          | 0.85     |
  | No log        | 3.0   | 375  | 0.9312          | 0.876    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  