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--- |
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language: |
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- ar |
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widget: |
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- text: "لقد كان الاحتفال رائع" |
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- text: "هناك بعض القوانين التي يجب تغيرها" |
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- text: "الخدمة كانت سيئة" |
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tags: |
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- text classification |
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- Sentiment |
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--- |
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## Arabic-MARBERT-Sentiment Model |
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#### Model description |
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**Arabic-MARBERT-Sentiment Model** is a Sentiment analysis model that was built by fine-tuning the [MARBERT](https://huggingface.co/UBC-NLP/MARBERT) model. For the fine-tuning, I used [KAUST dataset](https://www.kaggle.com/competitions/arabic-sentiment-analysis-2021-kaust), which includes 3 labels(positive,negative,and neutral). |
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#### How to use |
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To use the model with a transformers pipeline: |
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```python |
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>>>from transformers import pipeline |
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>>>model = pipeline('text-classification', model='Ammar-alhaj-ali/arabic-MARBERT-sentiment') |
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>>>sentences = ['لقد استمتعت بالحفلة', 'خدمة المطعم كانت محبطة'] |
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>>>model(sentences) |
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[{'label': 'positive', 'score': 0.9577557444572449}, |
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{'label': 'negative', 'score': 0.9158180952072144}] |
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