Moh. Abyan

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2025

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AGHNA at SemEval-2025 Task 11: Predicting Emotion and Its Intensity within a Text with EmoBERTa
Moh. Abyan
Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)

This paper presents our system that have been developed for SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection. The system is able to do two sub-tasks: Track A, related to detecting emotion(s) in a given text; Track B, related to calculate intensity of emotion(s) in a given text. The system will have EmoBERTa as the model baseline, despite some minor differences used in the system approach between these tracks. With the system designed above, Track A achieved a Macro-F1 Score of 0.7372, while Track B achieved Average Pearson r Score of 0.7618.
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