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

Egil Rønningstad
4/27/2023
cs.CL

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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.

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Cite this paper

@article{rnningstad2023semeval,
  title  = {UIO at SemEval-2023 Task 12: Multilingual fine-tuning for sentiment classification in low-resource languages},
  author = {Egil Rønningstad},
  year   = {2023},
  eprint = {2304.14189},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2304.14189v1}
}

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