Research

Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning

Research
NLP methods
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This paper introduces multilingual adaptive fine-tuning (MAFT) applied to 17 of the most-resourced African languages, producing the AfroXLMR family of models. Removing non-African-script tokens cuts model size by roughly 50 percent while matching the accuracy of single-language adaptation on named entity recognition, topic classification and sentiment analysis.

Category
Research
Pricing
Free / open
Country
馃實 Pan-African
Last verified
5 Jul 2026

Tags

nlp
african-languages
fine-tuning
language-models