Fine-tuning Multilingual Transformers for Hausa-English Sentiment Analysis

Investigating the Impact of Language-Adaptive Fine-Tuning on Sentiment Analysis in Hausa Language Using AfriBERTa

Sentiment analysis (SA) plays a vital role in Natural Language Processing (NLP) by ~identifying sent

MULTILINGUAL ADAPTIVE FINE-TUNING (MAFT)

We introduce MAFT as an approach to adapt a multi-lingual PLM to a new set of languages. Adapting PLMs has been shown to be effective when adapting to a new domain (Gururangan et al., 2020) or language (Pfeiffer et al., 2020; Alabi et al., 2020; Adelani et al., 202

Harnessing Ensemble and Transformers for Sentiment Analysis and Emotion Detection in Hausa Text

Understanding emotional tone and sentiment in text has driven significant advancements in Natural La

Fine-Tuning Transformers and LLMs for Fake News Detection in Algerian Dialect

Overview of monolingual and multilingual PLM-based fine-tuning for Sentiment Analysis. The SAfriSenti is utilised for training and evaluation purposes.

Overview of monolingual and multilingual PLM-based fine-tuning for Sentiment Analysis. The SAfriS

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

Our contribution to the 2023 AfriSenti-SemEval shared task 12: Sentiment Analysis for African Langua