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--- |
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license: apache-2.0 |
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language: |
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- ar |
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--- |
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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: Saudi Arabia (SA) dialect. |
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* AraRoBERTa-EGY: Egypt (EGY) dialect. |
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* AraRoBERTa-KU: Kuwait (KU) dialect. |
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* AraRoBERTa-OM: Oman (OM) dialect. |
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* AraRoBERTa-LB: Lebanon (LB) dialect. |
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* AraRoBERTa-JO: Jordan (JO) dialect. |
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* 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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