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