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--- |
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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: Flaubert_1619 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# Flaubert_1619 |
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This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.2458 |
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- Validation Loss: 0.5339 |
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- Train Accuracy: 0.8170 |
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- Epoch: 19 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 1.0000 | 0.5841 | 0.7769 | 0 | |
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| 0.5526 | 0.5284 | 0.7845 | 1 | |
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| 0.3909 | 0.4806 | 0.8221 | 2 | |
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| 0.2798 | 0.5339 | 0.8170 | 3 | |
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| 0.2378 | 0.5339 | 0.8170 | 4 | |
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| 0.2514 | 0.5339 | 0.8170 | 5 | |
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| 0.2403 | 0.5339 | 0.8170 | 6 | |
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| 0.2373 | 0.5339 | 0.8170 | 7 | |
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| 0.2441 | 0.5339 | 0.8170 | 8 | |
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| 0.2529 | 0.5339 | 0.8170 | 9 | |
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| 0.2400 | 0.5339 | 0.8170 | 10 | |
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| 0.2337 | 0.5339 | 0.8170 | 11 | |
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| 0.2394 | 0.5339 | 0.8170 | 12 | |
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| 0.2383 | 0.5339 | 0.8170 | 13 | |
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| 0.2464 | 0.5339 | 0.8170 | 14 | |
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| 0.2464 | 0.5339 | 0.8170 | 15 | |
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| 0.2468 | 0.5339 | 0.8170 | 16 | |
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| 0.2427 | 0.5339 | 0.8170 | 17 | |
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| 0.2546 | 0.5339 | 0.8170 | 18 | |
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| 0.2458 | 0.5339 | 0.8170 | 19 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- TensorFlow 2.12.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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