| --- |
| license: mit |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: Flaubert_1619 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should |
| probably proofread and complete it, then remove this comment. --> |
|
|
| # Flaubert_1619 |
| |
| This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.2458 |
| - Validation Loss: 0.5339 |
| - Train Accuracy: 0.8170 |
| - Epoch: 19 |
| |
| ## 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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1432, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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 | |
| |:----------:|:---------------:|:--------------:|:-----:| |
| | 1.0000 | 0.5841 | 0.7769 | 0 | |
| | 0.5526 | 0.5284 | 0.7845 | 1 | |
| | 0.3909 | 0.4806 | 0.8221 | 2 | |
| | 0.2798 | 0.5339 | 0.8170 | 3 | |
| | 0.2378 | 0.5339 | 0.8170 | 4 | |
| | 0.2514 | 0.5339 | 0.8170 | 5 | |
| | 0.2403 | 0.5339 | 0.8170 | 6 | |
| | 0.2373 | 0.5339 | 0.8170 | 7 | |
| | 0.2441 | 0.5339 | 0.8170 | 8 | |
| | 0.2529 | 0.5339 | 0.8170 | 9 | |
| | 0.2400 | 0.5339 | 0.8170 | 10 | |
| | 0.2337 | 0.5339 | 0.8170 | 11 | |
| | 0.2394 | 0.5339 | 0.8170 | 12 | |
| | 0.2383 | 0.5339 | 0.8170 | 13 | |
| | 0.2464 | 0.5339 | 0.8170 | 14 | |
| | 0.2464 | 0.5339 | 0.8170 | 15 | |
| | 0.2468 | 0.5339 | 0.8170 | 16 | |
| | 0.2427 | 0.5339 | 0.8170 | 17 | |
| | 0.2546 | 0.5339 | 0.8170 | 18 | |
| | 0.2458 | 0.5339 | 0.8170 | 19 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - TensorFlow 2.12.0 |
| - Datasets 2.12.0 |
| - Tokenizers 0.13.3 |
|
|
