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arXiv · 2304.12569

KINLP at SemEval-2023 Task 12: Kinyarwanda Tweet Sentiment Analysis

Antoine Nzeyimana
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Abstract

This paper describes the system entered by the author to the SemEval-2023 Task 12: Sentiment analysis for African languages. The system focuses on the Kinyarwanda language and uses a language-specific model. Kinyarwanda morphology is modeled in a two tier transformer architecture and the transformer model is pre-trained on a large text corpus using multi-task masked morphology prediction. The model is deployed on an experimental platform that allows users to experiment with the pre-trained language model fine-tuning without the need to write machine learning code. Our final submission to the shared task achieves second ranking out of 34 teams in the competition, achieving 72.50% weighted F1 score. Our analysis of the evaluation results highlights challenges in achieving high accuracy on the task and identifies areas for improvement.

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BibTeXRIS

Antoine Nzeyimana. 2023-04-25. KINLP at SemEval-2023 Task 12: Kinyarwanda Tweet Sentiment Analysis. https://arxiv.org/abs/2304.12569

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