readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  model-index:
  - name: distilbert-imdb-demo
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: imdb
        type: imdb
        args: plain_text
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.928
  ---
  
  <!-- 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-imdb-demo
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4328
  - Accuracy: 0.928
  
  ## 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: 1337
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 5.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.3459        | 1.0   | 2657  | 0.2362          | 0.9091   |
  | 0.1612        | 2.0   | 5314  | 0.2668          | 0.9248   |
  | 0.0186        | 3.0   | 7971  | 0.3274          | 0.9323   |
  | 0.1005        | 4.0   | 10628 | 0.3978          | 0.9277   |
  | 0.0006        | 5.0   | 13285 | 0.4328          | 0.928    |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  