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msislam
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code-mixed-language-detection-XLMRoberta

Token Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Model card Files
xet
Community
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@@ -27,16 +27,24 @@ The training dataset is based on [The Multilingual Amazon Reviews Corpus](https:
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  ## Results
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- ```
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- 'DE': {'precision': 0.9870741390453328, 'recall': 0.9883516686696866, 'f1': 0.9877124907612713}
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- 'EN': {'precision': 0.9901617633147289, 'recall': 0.9914748508098892, 'f1': 0.9908178720181748}
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- 'ES': {'precision': 0.9912407007439404, 'recall': 0.9912407007439404, 'f1': 0.9912407007439406}
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- 'FR': {'precision': 0.9872469872469872, 'recall': 0.9871314927468414, 'f1': 0.9871892366188945}
 
 
 
 
 
 
 
 
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  'overall_precision': 0.9888723454274744
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  'overall_recall': 0.9895702634880803
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  'overall_f1': 0.9892211813585232
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- 'overall_accuracy': 0.9993651810717168
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  ```
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  ## Usage
 
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  ## Results
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+ ```python
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+ {'DE': {'precision': 0.9870741390453328,
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+ 'recall': 0.9883516686696866,
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+ 'f1': 0.9877124907612713}
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+ 'EN': {'precision': 0.9901617633147289,
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+ 'recall': 0.9914748508098892,
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+ 'f1': 0.9908178720181748}
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+ 'ES': {'precision': 0.9912407007439404,
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+ 'recall': 0.9912407007439404,
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+ 'f1': 0.9912407007439406}
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+ 'FR': {'precision': 0.9872469872469872,
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+ 'recall': 0.9871314927468414,
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+ 'f1': 0.9871892366188945}
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  'overall_precision': 0.9888723454274744
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  'overall_recall': 0.9895702634880803
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  'overall_f1': 0.9892211813585232
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+ 'overall_accuracy': 0.9993651810717168}
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  ```
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  ## Usage