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

Domain:

natural language processing

Record type:

papermodel
Creator:
Nze
Host:avatar
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.

Visit

arxiv.org

Tasks

sentiment analysistext classification

Languages

Kinyarwanda

Tags

Computation and LanguageI.2.7

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