MODEL PROFILE

ARBERTv2

UBC-NLP · ARBERTv2

**ARBERTv2** is the updated version of ARBERT model described in our **ACL 2021 paper** **"ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic"**. **ARBERTv2** is presented in our paper "ORCA: A Challenging Benchmark for Arabic Language Understanding" **ARBERTv2** is trained on MSA data **243 GB** of text and **27.8B tokens**. If you use our models (ARBERTv2) for your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows (to be updated): We gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, Canadian Foundation for Innovation, ComputeCanada and UBC ARC-Sockeye. We also thank the Google TensorFlow Research Cloud (TFRC) program for providing us with free TPU access.

Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/11/2 19:15:36
OVERVIEW

Model overview

**ARBERTv2** is the updated version of ARBERT model described in our **ACL 2021 paper** **"ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic"**. **ARBERTv2** is presented in our paper "ORCA: A Challenging Benchmark for Arabic Language Understanding" **ARBERTv2** is trained on MSA data **243 GB** of text and **27.8B tokens**. If you use our models (ARBERTv2) for your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows (to be updated): We gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, Canadian Foundation for Innovation, ComputeCanada and UBC ARC-Sockeye. We also thank the Google TensorFlow Research Cloud (TFRC) program for providing us with free TPU access.

Key features

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

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