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README.md
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- **Test Set**: 10%
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## Model Training
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- **Optimizer**: AdamW
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- **Learning Rate**: 3e-5
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- **Batch Size**: 64
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- **Loss Function**: Focal Loss to handle class imbalance
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- **Frameworks**: PyTorch, Hugging Face Transformers, SimpleTransformers
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## How to Use
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You can easily use this model with the Hugging Face `transformers` library. Here's an example of how to load and use the model for inference:
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- **Test Set**: 10%
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## Model Training
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**Training Configuration**:
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- **Optimizer**: AdamW
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- **Learning Rate**: 3e-5
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- **Batch Size**: 64
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- **Loss Function**: Focal Loss to handle class imbalance
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- **Frameworks**: PyTorch, Hugging Face Transformers, SimpleTransformers
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## Evaluation metrics
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- eval_loss = 0.4112480320792267
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- f1_score = 0.6910085729376871
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- precision = 0.7068717096148518
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- recall = 0.675841788751424
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## How to Use
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You can easily use this model with the Hugging Face `transformers` library. Here's an example of how to load and use the model for inference:
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