2025
ACL
ACL 2025
indiDataMiner at SemEval-2025 Task 11: From Text to Emotion: Transformer-Based Models for Emotions Detection in Indian Languages
Abstract
AbstractEmotion detection is essential for applications like mental health monitoring and social media analysis, yet remains underexplored for Indian languages. This paper presents our system for SemEval-2025 Task 11 (Track A), focusing on multilabel emotion detection in Hindi and Marathi, two widely spoken Indian languages. We fine-tune IndicBERT v2 on the BRIGHTER dataset, achieving F1 scores of 87.37 (Hindi) and 88.32 (Marathi), outperforming baseline models. Our results highlight the effectiveness of fine-tuning a language-specific pretrained model for emotion detection, contributing to advancements in multilingual NLP research.
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
Authors
Topics
Natural Language Processing > Understanding > Sentiment Analysis
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Resources & Methods > Multilingual NLP
Natural Language Processing > Applications > Sentiment Analysis
Machine Learning > Learning Types > Fine-Tuning
Machine Learning > Learning Types > Multi-Label Classification
Deep Learning > Learning Types > Fine-Tuning