UIO at SemEval-2023 Task 12: Multilingual fine-tuning for sentiment classification in low-resource languages
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 7 of its 12 references that are in the map. First posted on arXiv 27 Apr 2023.
Builds on
7 of 12 references.
References · 7
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
- 2022Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuningcited by 149
- 2021XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyondcited by 114
- 2023AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languagescited by 68
- 2022NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysiscited by 64
- 2023SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)cited by 41
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.