Q8BERTA-SA

Fine-Tuned SA-Q8BERTA Model for Sentiment Analysis

This model is a fine-tuned version of Kalmundi/Q8BERTA, which was trained on a customized dataset for sentiment analysis. This model mainly focuses on Sentiment Analysis for the Kuwaiti Dialect.

Model Details

• Base Model: The original model is Kalmundi/Q8BERTA, a transformer-based model pre-trained on a sufficient size Kuwaiti Dialect dataset.
• Fine-Tuning: This model was fine-tuned on a dataset for sentiment analysis related to Kuwaiti Dialect, and it can classify text as either positive or negative.
• Fine-Tuning Task: The model was fine-tuned for 5 epochs with a learning rate of 2e-5.

Model Usage

To use the model for sentiment analysis:

from transformers import pipeline

# Load the fine-tuned model
classifier = pipeline("text-classification", model="Kalmundi/Q8BERTA-SA")

# Test the classifier
result = classifier("الجو اليوم وايد حلو")
print(result)