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--- |
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language: ar |
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widget: |
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- text: "ممتاز" |
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- text: "أنا حزين" |
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- text: "لا شيء" |
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--- |
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# Model description |
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This model is an Arabic language sentiment analysis pretrained model. |
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The model is built on top of the CAMelBERT_msa_sixteenth BERT-based model. |
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We used the HARD dataset of hotels review to fine tune the model. |
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The dataset original labels based on a five-star rating were modified to a 3 label data: |
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- POSITIVE: for ratings > 3 stars |
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- NEUTRAL: for a 3 star rating |
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- NEGATIVE: for ratings < 3 stars |
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This first prototype was trained on 3 epochs for 1 hours using Colab and a TPU acceleration. |
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# Examples |
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Here are some examples in Arabic to test : |
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- Excellent -> ممتاز(Happy) |
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- I'am sad -> أنا حزين (Sad) |
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- Nothing -> لا شيء (Neutral) |
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# Contact |
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If you have questions or improvement remarks, feel free to contact me on my LinkedIn profile: https://www.linkedin.com/in/yahya-ghrab/ |
