@inproceedings{abyan-2025-aghna,
title = "{AGHNA} at {S}em{E}val-2025 Task 11: Predicting Emotion and Its Intensity within a Text with {E}mo{BERT}a",
author = "Abyan, Moh.",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.140/",
pages = "1057--1063",
ISBN = "979-8-89176-273-2",
abstract = "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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%0 Conference Proceedings
%T AGHNA at SemEval-2025 Task 11: Predicting Emotion and Its Intensity within a Text with EmoBERTa
%A Abyan, Moh.
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F abyan-2025-aghna
%X 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.
%U https://aclanthology.org/2025.semeval-1.140/
%P 1057-1063
Markdown (Informal)
[AGHNA at SemEval-2025 Task 11: Predicting Emotion and Its Intensity within a Text with EmoBERTa](https://aclanthology.org/2025.semeval-1.140/) (Abyan, SemEval 2025)
ACL