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arabert_c19: An Arabert model pretrained on 1.5 million COVID-19 multi-dialect Arabic tweets

ARABERT COVID-19 is a pretrained (fine-tuned) version of the AraBERT v2 model (https://huggingface.co/aubmindlab/bert-base-arabertv02). The pretraining was done using 1.5 million multi-dialect Arabic tweets regarding the COVID-19 pandemic from the “Large Arabic Twitter Dataset on COVID-19” (https://arxiv.org/abs/2004.04315). The model can achieve better results for the tasks that deal with multi-dialect Arabic tweets in relation to the COVID-19 pandemic.

Classification results for multiple tasks including fake-news and hate speech detection when using arabert_c19 and mbert_ar_c19:

For more details refer to the paper (link)

arabert mbert distilbert multi arabert Covid-19 mbert Covid-19
Contains hate (Binary) 0.8346 0.6675 0.7145 0.8649 0.8492
Talk about a cure (Binary) 0.8193 0.7406 0.7127 0.9055 0.9176
News or opinion (Binary) 0.8987 0.8332 0.8099 0.9163 0.9116
Contains fake information (Binary) 0.6415 0.5428 0.4743 0.7739 0.7228


from arabert.preprocess import ArabertPreprocessor
arabert_prep = ArabertPreprocessor(model_name=model_name)
text = "للوقايه من عدم انتشار كورونا عليك اولا غسل اليدين بالماء والصابون وتكون عملية الغسل دقيقه تشمل راحة اليد الأصابع التركيز على الإبهام"


Hadj Ameur: Github | mohamedhadjameur@gmail.com | mhadjameur@cerist.dz

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