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README.md
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- **Learning Rate**: 3e-5
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- **Batch Size**: 64
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- **Epochs**: 200
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- **Loss Function
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- **Frameworks**: PyTorch, Hugging Face Transformers, SimpleTransformers
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## Evaluation metrics
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- precision = 0.759089632772006
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- recall = 0.7528393482105897
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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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- **Learning Rate**: 3e-5
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- **Batch Size**: 64
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- **Epochs**: 200
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- **Loss Function**
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: 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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- precision = 0.759089632772006
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- recall = 0.7528393482105897
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Visit [HUMADEX/Weekly-Supervised-NER-pipline](https://github.com/HUMADEX/Weekly-Supervised-NER-pipline) for more info.
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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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