Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages

Israel Abebe Azime, Sana Al-azzawi, Atnafu Lambebo Tonja, Iyanuoluwa Shode, Jesujoba Alabi, Ayodele Awokoya, Mardiyyah Oduwole, Tosin Adewumi, Samuel Fanijo, Awosan Oyinkansola


Abstract
Detecting harmful content on social media plat-forms is crucial in preventing the negative ef-fects these posts can have on social media users. This paper presents our methodology for tack-ling task 10 from SemEval23, which focuseson detecting and classifying online sexism insocial media posts. We constructed our solu-tion using an ensemble of transformer-basedmodels (that have been fine-tuned; BERTweet,RoBERTa, and DeBERTa). To alleviate the var-ious issues caused by the class imbalance inthe dataset provided and improve the general-ization of our model, our framework employsdata augmentation and semi-supervised learn-ing. Specifically, we use back-translation fordata augmentation in two scenarios: augment-ing the underrepresented class and augment-ing all classes. In this study, we analyze theimpact of these different strategies on the sys-tem’s overall performance and determine whichtechnique is the most effective. Extensive ex-periments demonstrate the efficacy of our ap-proach. For sub-task A, the system achievedan F1-score of 0.8613. The source code to re-produce the proposed solutions is available onGithub
Anthology ID:
2023.semeval-1.182
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1311–1316
Language:
URL:
https://aclanthology.org/2023.semeval-1.182
DOI:
10.18653/v1/2023.semeval-1.182
Bibkey:
Cite (ACL):
Israel Abebe Azime, Sana Al-azzawi, Atnafu Lambebo Tonja, Iyanuoluwa Shode, Jesujoba Alabi, Ayodele Awokoya, Mardiyyah Oduwole, Tosin Adewumi, Samuel Fanijo, and Awosan Oyinkansola. 2023. Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1311–1316, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Masakhane-Afrisenti at SemEval-2023 Task 12: Sentiment Analysis using Afro-centric Language Models and Adapters for Low-resource African Languages (Azime et al., SemEval 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-3/2023.semeval-1.182.pdf