README.md

---
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