Computer Science > Computation and Language
arXiv:2304.06459 (cs)
[Submitted on 13 Apr 2023]
Title:Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages
Authors:Israel Abebe Azime,Sana Sabah Al-Azzawi,Atnafu Lambebo Tonja,Iyanuoluwa Shode,Jesujoba Alabi,Ayodele Awokoya,Mardiyyah Oduwole,Tosin Adewumi,Samuel Fanijo,Oyinkansola Awosan,Oreen Yousuf
View a PDF of the paper titled Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages, by Israel Abebe Azime and 10 other authors
View PDFAbstract:AfriSenti-SemEval Shared Task 12 of SemEval-2023. The task aims to perform monolingual sentiment classification (sub-task A) for 12 African languages, multilingual sentiment classification (sub-task B), and zero-shot sentiment classification (task C). For sub-task A, we conducted experiments using classical machine learning classifiers, Afro-centric language models, and language-specific models. For task B, we fine-tuned multilingual pre-trained language models that support many of the languages in the task. For task C, we used we make use of a parameter-efficient Adapter approach that leverages monolingual texts in the target language for effective zero-shot transfer. Our findings suggest that using pre-trained Afro-centric language models improves performance for low-resource African languages. We also ran experiments using adapters for zero-shot tasks, and the results suggest that we can obtain promising results by using adapters with a limited amount of resources.
| Comments: | SemEval 2023 |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2304.06459 [cs.CL] |
| (orarXiv:2304.06459v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2304.06459 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages, by Israel Abebe Azime and 10 other authors
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