Chukwuneke, CI and Rayson, Paul and Ezeani, Ignatius and El-Haj, Mahmoud (2022) IgboBERT Models : Building and Training Transformer Models for the Igbo Language. In: LREC 2022 Conference Proceedings :. European Language Resources Association (ELRA), FRA, 5114–5122. ISBN 9781095546726
Full text not available from this repository.Abstract
This work presents a standard Igbo named entity recognition (IgboNER) dataset as well as the results from training and fine-tuning state-of-the-art transformer IgboNER models. We discuss the process of our dataset creation - data collection and annotation and quality checking. We also present experimental processes involved in building an IgboBERT language model from scratch as well as fine-tuning it along with other non-Igbo pre-trained models for the downstream IgboNER task. Our results show that, although the IgboNER task benefited hugely from fine-tuning large transformer model, fine-tuning a transformer model built from scratch with comparatively little Igbo text data seems to yield quite decent results for the IgboNER task. This work will contribute immensely to IgboNLP in particular as well as the wider African and low-resource NLP efforts.