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README.md
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@@ -43,7 +43,8 @@ PROBLEM`: Diseases, symptoms, and medical conditions.
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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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@@ -58,7 +59,6 @@ You can easily use this model with the Hugging Face `transformers` library. Here
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```python
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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import torch
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model_name = "rigonsallauka/polish_medical_ner"
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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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**Epochs**: 200
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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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```python
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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model_name = "rigonsallauka/polish_medical_ner"
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