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