readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - sibyl
  datasets:
  - imdb
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-imdb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: imdb
        type: imdb
        args: plain_text
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.91264
  ---
  
  <!-- 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-imdb
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4942
  - Accuracy: 0.9126
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1546
  - training_steps: 15468
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.3952        | 0.65  | 2000  | 0.4012          | 0.86     |
  | 0.2954        | 1.29  | 4000  | 0.4535          | 0.892    |
  | 0.2595        | 1.94  | 6000  | 0.4320          | 0.892    |
  | 0.1516        | 2.59  | 8000  | 0.5309          | 0.896    |
  | 0.1167        | 3.23  | 10000 | 0.4070          | 0.928    |
  | 0.0624        | 3.88  | 12000 | 0.5055          | 0.908    |
  | 0.0329        | 4.52  | 14000 | 0.4342          | 0.92     |
  
  
  ### Framework versions
  
  - Transformers 4.10.2
  - Pytorch 1.7.1
  - Datasets 1.6.1
  - Tokenizers 0.10.3
  