readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  model-index:
  - name: distilbert-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: 0.9214
  ---
  
  <!-- 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-imdb
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an imdb dataset where an evaluation of 5000 samples was created by splitting the training set.
  It achieves the following results on the evaluation set:
  - Loss: 0.6252
  - Accuracy: 0.9214
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  This model was trained for the introduction to Natural language processing course of [EPITA](https://www.epita.fr/).
  
  ## Training and evaluation data
  
  The training/evaluation split was generated using a `seed` of 42 and a `test_size` of 0.2.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 128
  - seed: 1337
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.2875        | 1.0   | 625  | 0.2286          | 0.9102   |
  | 0.1685        | 2.0   | 1250 | 0.2416          | 0.9128   |
  | 0.1171        | 3.0   | 1875 | 0.3223          | 0.917    |
  | 0.0493        | 4.0   | 2500 | 0.3667          | 0.9162   |
  | 0.023         | 5.0   | 3125 | 0.4074          | 0.92     |
  | 0.015         | 6.0   | 3750 | 0.4291          | 0.9236   |
  | 0.0129        | 7.0   | 4375 | 0.5452          | 0.9194   |
  | 0.0051        | 8.0   | 5000 | 0.5886          | 0.9146   |
  | 0.0027        | 9.0   | 5625 | 0.6310          | 0.9186   |
  | 0.002         | 10.0  | 6250 | 0.6252          | 0.9214   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  