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README.md

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-**Model uncertainty estimation**
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+**Model uncertainty quantification on GoEmotions test set**
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+The distribution demonstrates strong calibration, as the highest error density correlates with increased epistemic uncertainty. While most high-probability predictions are correct, a small fragment of overconfident incorrects remains likely due to dataset bias or linguistic nuances like sarcasm. These outliers identify a clear opportunity for further refinement using **temperature scaling**.
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 ![epistemic_unc](outputs/epistemic_unc_scatter.png)
 
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 **Confusion matrix**
 ![multi_label_confusion_matrix](outputs/confusion_matrix.png)