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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: maxime7770/model |
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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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# maxime7770/model |
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This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1211 |
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- Validation Loss: 0.4812 |
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- Epoch: 49 |
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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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 650, '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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 1.5966 | 1.5898 | 0 | |
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| 1.5577 | 1.5576 | 1 | |
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| 1.5034 | 1.4761 | 2 | |
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| 1.4034 | 1.3538 | 3 | |
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| 1.2864 | 1.2163 | 4 | |
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| 1.1502 | 1.0980 | 5 | |
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| 1.0085 | 0.9988 | 6 | |
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| 0.8828 | 0.9130 | 7 | |
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| 0.7863 | 0.8445 | 8 | |
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| 0.7036 | 0.7871 | 9 | |
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| 0.6322 | 0.7399 | 10 | |
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| 0.5731 | 0.7030 | 11 | |
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| 0.5180 | 0.6714 | 12 | |
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| 0.4757 | 0.6432 | 13 | |
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| 0.4366 | 0.6204 | 14 | |
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| 0.4057 | 0.6006 | 15 | |
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| 0.3743 | 0.5827 | 16 | |
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| 0.3475 | 0.5689 | 17 | |
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| 0.3221 | 0.5577 | 18 | |
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| 0.2971 | 0.5467 | 19 | |
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| 0.2815 | 0.5372 | 20 | |
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| 0.2700 | 0.5297 | 21 | |
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| 0.2521 | 0.5225 | 22 | |
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| 0.2343 | 0.5168 | 23 | |
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| 0.2265 | 0.5117 | 24 | |
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| 0.2143 | 0.5074 | 25 | |
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| 0.2063 | 0.5038 | 26 | |
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| 0.1941 | 0.5001 | 27 | |
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| 0.1843 | 0.4976 | 28 | |
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| 0.1782 | 0.4949 | 29 | |
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| 0.2012 | 0.4938 | 30 | |
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| 0.1691 | 0.4930 | 31 | |
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| 0.1626 | 0.4910 | 32 | |
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| 0.1884 | 0.4886 | 33 | |
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| 0.1547 | 0.4870 | 34 | |
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| 0.1492 | 0.4858 | 35 | |
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| 0.1445 | 0.4850 | 36 | |
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| 0.1415 | 0.4842 | 37 | |
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| 0.1383 | 0.4836 | 38 | |
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| 0.1374 | 0.4832 | 39 | |
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| 0.1336 | 0.4826 | 40 | |
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| 0.1322 | 0.4823 | 41 | |
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| 0.1295 | 0.4820 | 42 | |
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| 0.1268 | 0.4818 | 43 | |
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| 0.1261 | 0.4816 | 44 | |
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| 0.1253 | 0.4815 | 45 | |
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| 0.1275 | 0.4814 | 46 | |
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| 0.1247 | 0.4812 | 47 | |
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| 0.1256 | 0.4812 | 48 | |
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| 0.1211 | 0.4812 | 49 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- TensorFlow 2.8.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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