masakhane-io/masakhane-news

MasakhaNEWS: News Topic Classification for African Languages # MasakhaNEWS: News Topic Classification for African Languages paper | dataset >African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks (e.g. named entity recognition and machine translation) have standardized benchmark datasets covering several geographical and typologically-diverse African languages. In this paper, we develop MasakhaNEWS -- a new benchmark dataset for news topic classification covering 16 languages widely spoken in Africa. We provide an evaluation of baseline models by training classical machine learning models and fine-tuning several language models. Furthermore, we explore several alternatives to full fine-tuning of language models that are better suited for zero-shot and few-shot learning such as cross-lingual parameter-efficient fine-tuning (like MAD-X), pattern exploiting training (PET), prompting language models (like ChatGPT), and prompt-free sentence transformer fine-tuning (SetFit and Cohere Embedding API). Our evaluation in zero-shot setting shows the potential of prompting ChatGPT for news topic classification in low-resource African languages, achieving an average performance of 70 F1 points without leveraging additional supervision like MAD-X. In few-shot setting, we show that with as little as 10 examples per label, we achieved more than 90\% (i.e. 86.0 F1 points) of the performance of full supervised training (92.6 F1 points) leveraging the PET approach. ## Languages There are 16 languages available : - Amharic (amh) - English (eng) - French (fra) - Hausa (hau) - Igbo (ibo) - Lingala (lin) - Luganda (lug) - Oromo (orm) - Nigerian Pidgin (pcm) - Rundi (run) - chiShona (sna) - Somali (som) - Kiswahili (swą) - Tigrinya (tir) - isiXhosa (xho) - Yorùbá (yor) ### Monolingual Corpus We obtained the data mostly from BBC news, and a few other websites …