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January 1, 2021Open Access

ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic

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Authors

MAMuhammad Abdul-MageedAEAbdelRahim ElmadanyENEl Moatez Billah Nagoudi

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Overview

Research presents two deep learning models for Arabic language processing, suggesting advancements in NLP applications.

Key Points

  • This research aims to create and evaluate two deep bidirectional transformer models, ARBERT and MARBERT, for Arabic natural language processing.
  • Developed ARBERT and MARBERT models based on transformer architecture.
  • Utilized Arabic textual data for training and evaluation.
  • Compared performance against existing language models for Arabic.
  • ARBERT achieved improved performance over current models on Arabic NLP tasks.
  • MARBERT demonstrated enhanced contextual understanding of Arabic text in various applications.

Cite This Study

Abdul-Mageed et al. (2021) studied this question.

synapsesocial.com/papers/6a01c72b1adb974501caf7a9https://doi.org/10.18653/v1/2021.acl-long.551
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