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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: LovenOO/distilBERT_without_preprocessing_grid_search |
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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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# LovenOO/distilBERT_without_preprocessing_grid_search |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0863 |
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- Validation Loss: 0.5369 |
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- Train Precision: 0.7209 |
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- Train Recall: 0.6880 |
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- Train F1: 0.6970 |
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- Train Accuracy: 0.8654 |
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- Epoch: 8 |
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 5140, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
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| 1.1440 | 0.6108 | 0.5739 | 0.5788 | 0.5727 | 0.8367 | 0 | |
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| 0.5050 | 0.5447 | 0.6506 | 0.6243 | 0.6325 | 0.8489 | 1 | |
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| 0.3584 | 0.4823 | 0.6518 | 0.6619 | 0.6558 | 0.8620 | 2 | |
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| 0.2612 | 0.4890 | 0.7183 | 0.6777 | 0.6902 | 0.8654 | 3 | |
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| 0.1901 | 0.4922 | 0.7137 | 0.6880 | 0.6937 | 0.8639 | 4 | |
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| 0.1566 | 0.5050 | 0.7220 | 0.6838 | 0.6953 | 0.8703 | 5 | |
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| 0.1189 | 0.5284 | 0.7088 | 0.6911 | 0.6920 | 0.8712 | 6 | |
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| 0.1059 | 0.5285 | 0.7113 | 0.6835 | 0.6900 | 0.8635 | 7 | |
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| 0.0863 | 0.5369 | 0.7209 | 0.6880 | 0.6970 | 0.8654 | 8 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- TensorFlow 2.13.0 |
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- Datasets 2.14.2 |
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- Tokenizers 0.11.0 |
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