huynhdoo/flaubert_base_uncased-finetuned-CLS
This model is a fine-tuned version of flaubert/flaubert_base_uncased on FLUE/CLS dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1491
- Validation Loss: 0.2361
- Train Accuracy: 0.9270
- Epoch: 2
Model description
More information needed
Intended uses & limitations
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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': 2e-05, 'decay_steps': 669, '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-08, 'amsgrad': False}
- training_precision: float32
Training results
Train Loss | Validation Loss | Train Accuracy | Epoch |
---|---|---|---|
0.5561 | 0.3184 | 0.8589 | 0 |
0.2343 | 0.2487 | 0.9118 | 1 |
0.1491 | 0.2361 | 0.9270 | 2 |
Framework versions
- Transformers 4.26.0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2
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