NLPeople at NADI 2023 Shared Task: Arabic Dialect Identification with Augmented Context and Multi-Stage Tuning

Mohab Elkaref, Movina Moses, Shinnosuke Tanaka, James Barry, Geeth R. de Mel · 2023

This paper presents the approach of the NLPeople team to the Nuanced Arabic Dialect Identification (NADI) 2023 shared task.Subtask 1 involves identifying the dialect of a source text at the country level.Our approach to Subtask 1 makes use of language-specific language models, a clustering and retrieval method to provide additional context to a target sentence, a fine-tuning strategy which makes use of the provided data from the 2020 and 2021 shared tasks, and finally, ensembling over the predictions of multiple models.Our submission achieves a macro-averaged F1 score of 87.27, ranking 1st among the other participants in the task.

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