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**DarijaBERT** is the first BERT model for the Moroccan Arabic dialect called “Darija”. It is based on the same architecture as BERT-base, but without the Next Sentence Prediction (NSP) objective. This model was trained on a total of ~3 Million sequences of Darija dialect representing 691MB of text or a total of ~100M tokens.
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The model was trained on a dataset issued from three different sources:
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language: ar
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datasets:
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- wikipedia
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- OSIAN
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- 1.5B Arabic Corpus
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- OSCAR Arabic Unshuffled
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widget:
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- text: " جاب ليا [MASK] ."
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**DarijaBERT** is the first BERT model for the Moroccan Arabic dialect called “Darija”. It is based on the same architecture as BERT-base, but without the Next Sentence Prediction (NSP) objective. This model was trained on a total of ~3 Million sequences of Darija dialect representing 691MB of text or a total of ~100M tokens.
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The model was trained on a dataset issued from three different sources:
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