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

• URL: http://arxiv.org/abs/2304.12569v1
• Date: Tue, 25 Apr 2023 04:30:03 GMT
• Title: KINLP at SemEval-2023 Task 12: Kinyarwanda Tweet Sentiment Analysis
• Authors: Antoine Nzeyimana
• Abstract summary: 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.
• Score: 1.2183405753834562
• License: http://creativecommons.org/licenses/by/4.0/
• 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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