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--- |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Pavan-124/lwin_winery_roberta |
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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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# Pavan-124/lwin_winery_roberta |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1539 |
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- Validation Loss: 0.0875 |
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- Train Precision: 0.8705 |
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- Train Recall: 0.8780 |
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- Train F1: 0.8742 |
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- Train Accuracy: 0.9661 |
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- Epoch: 0 |
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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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1908, '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, 'weight_decay_rate': 0.01} |
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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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| 0.1539 | 0.0875 | 0.8705 | 0.8780 | 0.8742 | 0.9661 | 0 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.14.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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