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HausaNLP at SemEval-2025 Task 11: Hausa Text Emotion Detection

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arxiv 2506.16388 v2 pith:HMDHTW5M submitted 2025-06-19 cs.CL

HausaNLP at SemEval-2025 Task 11: Hausa Text Emotion Detection

Sani Abdullahi Sani , Salim Abubakar , Falalu Ibrahim Lawan , Abdulhamid Abubakar , Maryam Bala This is my paper
classification cs.CL
keywords detectionemotionhausaafricanlanguageslow-resourcemodeltext
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper presents our approach to multi-label emotion detection in Hausa, a low-resource African language, for SemEval Track A. We fine-tuned AfriBERTa, a transformer-based model pre-trained on African languages, to classify Hausa text into six emotions: anger, disgust, fear, joy, sadness, and surprise. Our methodology involved data preprocessing, tokenization, and model fine-tuning using the Hugging Face Trainer API. The system achieved a validation accuracy of 74.00%, with an F1-score of 73.50%, demonstrating the effectiveness of transformer-based models for emotion detection in low-resource languages.

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