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@@ -85,17 +85,6 @@ Accuracy (overall correct predictions), Macro F1-score (average F1 across classe
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  - Macro F1-Score: 66.35%
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  Detailed per-class metrics and confusion matrix available in the repository.
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- #### Summary
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- The model shows robust performance on unseen Persian tweet data, with good generalization across emotions.
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- ## Technical Specifications
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- ### Model Architecture and Objective
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- BERT base model with a sequence classification head for multi-class emotion prediction.
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- #### Hardware
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- T4.
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- #### Software
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- Hugging Face Transformers library, Python.
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  **BibTeX:**
 
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  - Macro F1-Score: 66.35%
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  Detailed per-class metrics and confusion matrix available in the repository.
 
 
 
 
 
 
 
 
 
 
 
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  **BibTeX:**