Arabert Sentiment Model with Farasa Preprocessing

This is a fine-tuned version of AraBERT using the ArSAS dataset for sentiment analysis. The text was preprocessed using Farasa for optimal tokenization of Arabic text.

Model Details

  • Base Model: AraBERT v2
  • Dataset: ArSAS (Arabic Sentiment Analysis)
  • Preprocessing: Farasa Tokenization
  • Tasks: Sentiment Classification (negative, neutral, positive , mixed)

Usage

from transformers import pipeline

sentiment_pipeline = pipeline(
    task="text-classification",
    model="Abdo36/Arabert-Sentiment-Analysis-ArSAS"
)

result = sentiment_pipeline("هذا المنتج رائع للغاية")
print(result)

Training Details

  • Number of Epochs: 2

  • Training Loss: 0.6

  • Validation Accuracy: 0.5

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