readme: ---
  language: fr
  license: mit
  tags:
  - generated_from_keras_callback
  model-index:
  - name: camembert-sentiment-allocine
    results: []
  datasets:
  - allocine
  metrics:
  - accuracy
  ---
  
  # camembert-sentiment-allocine
  
  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the [allocine](https://huggingface.co/datasets/allocine) dataset.
  
  ## Intended uses & limitations
  
  This model has been trained for a single epoch for testing purposes.
  
  ## Training procedure
  
  This model has been created by fine-tuning the TensorFlow version [camembert-base](https://huggingface.co/camembert-base) **after freezing the encoder part**:
  
  ```python
  model.roberta.trainable = False
  ```
  
  Therefore, only the classifier head parameters have been updated during training.
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  ```
  - optimizer: {
       'name': 'Adam', 
       'learning_rate': {
           'class_name': 'PolynomialDecay', 
           'config': {'initial_learning_rate': 5e-05, 'decay_steps': 15000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}
        }, 
        'decay': 0.0, 
        'beta_1': 0.9, 
        'beta_2': 0.999, 
        'epsilon': 1e-07, 
        'amsgrad': False
  }
  - training_precision: float32
  - epochs: 1
  ```
  
  ### Training results
  
  The model achieves the following results on the test set:
  
  | Accuracy  |
  |---|
  | 0.918  |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - TensorFlow 2.8.2
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  