English

UIO at SemEval-2023 Task 12: Multilingual fine-tuning for sentiment classification in low-resource languages

Computation and Language 2023-04-28 v1

Abstract

Our contribution to the 2023 AfriSenti-SemEval shared task 12: Sentiment Analysis for African Languages, provides insight into how a multilingual large language model can be a resource for sentiment analysis in languages not seen during pretraining. The shared task provides datasets of a variety of African languages from different language families. The languages are to various degrees related to languages used during pretraining, and the language data contain various degrees of code-switching. We experiment with both monolingual and multilingual datasets for the final fine-tuning, and find that with the provided datasets that contain samples in the thousands, monolingual fine-tuning yields the best results.

Keywords

Cite

@article{arxiv.2304.14189,
  title  = {UIO at SemEval-2023 Task 12: Multilingual fine-tuning for sentiment classification in low-resource languages},
  author = {Egil Rønningstad},
  journal= {arXiv preprint arXiv:2304.14189},
  year   = {2023}
}

Comments

Submitted to SemEval-2023, The 17th International Workshop on Semantic Evaluation