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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: 0.2317 |
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- Validation Loss: 0.5081 |
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- Train Precision: 0.6613 |
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- Train Recall: 0.6531 |
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- Train F1: 0.6566 |
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- Train Accuracy: 0.8581 |
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- Epoch: 4 |
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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': 2e-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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| 1.2437 | 0.6349 | 0.5675 | 0.5420 | 0.5499 | 0.8343 | 0 | |
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| 0.5456 | 0.5544 | 0.6316 | 0.6172 | 0.6214 | 0.8435 | 1 | |
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| 0.3904 | 0.5303 | 0.6384 | 0.6191 | 0.6239 | 0.8523 | 2 | |
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| 0.3005 | 0.5042 | 0.6594 | 0.6486 | 0.6531 | 0.8610 | 3 | |
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| 0.2317 | 0.5081 | 0.6613 | 0.6531 | 0.6566 | 0.8581 | 4 | |
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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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