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README.md
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The AraRoBERTa models are mono-dialectal Arabic models trained on a country-level dialect. AraRoBERTa uses RoBERTa base config. More details are available in the paper (
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The following are the AraRoBERTa seven dialectal variations:
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AraRoBERTa-SA: Saudi Arabia (SA).
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AraRoBERTa-
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AraRoBERTa-KU: Kuwait (KU).
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AraRoBERTa-OM: Oman (OM).
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AraRoBERTa-LB: Lebanon (LB).
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AraRoBERTa-JO: Jordan (JO).
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AraRoBERTa-DZ: Algeria (DZ)
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The **AraRoBERTa** models are mono-dialectal Arabic models trained on a country-level dialect. AraRoBERTa uses RoBERTa base config. More details are available in the paper [click](https://aclanthology.org/2022.wanlp-1.24/).
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The following are the AraRoBERTa seven dialectal variations:
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* [AraRoBERTa-SA](https://huggingface.co/reemalyami/AraRoBERTa-SA): Saudi Arabia (SA) dialect.
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* [AraRoBERTa-EGY](https://huggingface.co/reemalyami/AraRoBERTa-EGY): Egypt (EGY) dialect.
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* [AraRoBERTa-KU](https://huggingface.co/reemalyami/AraRoBERTa-KU): Kuwait (KU) dialect.
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* [AraRoBERTa-OM](https://huggingface.co/reemalyami/AraRoBERTa-OM): Oman (OM) dialect.
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* [AraRoBERTa-LB](https://huggingface.co/reemalyami/AraRoBERTa-LB): Lebanon (LB) dialect.
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* [AraRoBERTa-JO](https://huggingface.co/reemalyami/AraRoBERTa-JO): Jordan (JO) dialect.
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* [AraRoBERTa-DZ](https://huggingface.co/reemalyami/AraRoBERTa-DZ): Algeria (DZ) dialect
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# When using the model, please cite our paper:
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```python
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@inproceedings{alyami-al-zaidy-2022-weakly,
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title = "Weakly and Semi-Supervised Learning for {A}rabic Text Classification using Monodialectal Language Models",
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author = "AlYami, Reem and Al-Zaidy, Rabah",
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booktitle = "Proceedings of the The Seventh Arabic Natural Language Processing Workshop (WANLP)",
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month = dec,
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year = "2022",
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address = "Abu Dhabi, United Arab Emirates (Hybrid)",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2022.wanlp-1.24",
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pages = "260--272",
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}
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```
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# Contact
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**Reem AlYami**: [Linkedin](https://www.linkedin.com/in/reem-alyami/) | <reem.yami@kfupm.edu.sa> | <yami.m.reem@gmail.com>
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