--- license: mit tags: - generated_from_keras_callback model-index: - name: huynhdoo/camembert-base-finetuned-jva-missions-report results: [] --- # huynhdoo/camembert-base-finetuned-jva-missions-report This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.1724 - Train Accuracy: 0.9446 - Validation Loss: 0.4132 - Validation Accuracy: 0.8436 - Epoch: 2 ## 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: - optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 603, '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 ### Training results | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| | 0.4575 | 0.7934 | 0.4093 | 0.8492 | 0 | | 0.2709 | 0.9073 | 0.4132 | 0.8603 | 1 | | 0.1724 | 0.9446 | 0.4132 | 0.8436 | 2 | ### Framework versions - Transformers 4.26.1 - TensorFlow 2.9.2 - Datasets 2.9.0 - Tokenizers 0.13.2