LRSA-IndoBERT-Sentiment-ID

Model Description

LRSA-IndoBERT-Sentiment-ID is a fine-tuned IndoBERT model for Indonesian sentiment analysis developed as part of the study:

Stress-Testing Large Language Models (LLMs) against Code-Mixing and Distributional Shifts in Low-Resource NLP

The model was trained and evaluated on a large Indonesian sentiment corpus containing approximately 75,000 samples collected from social media and news domains.

Task

Sentiment Classification

Labels:

• Negative
• Neutral
• Positive

Dataset

Sources:

• YouTube comments
• Indonesian news articles and comments

Domains:

• Politics
• Economics
• Social issues
• Public policy

Repository

Code, results, and supplementary materials:

https://github.com/mziarehman4353/LRSA-LLM

Citation

If you use this model, please cite the associated publication:

Zafar, Z. U. R., Gunawan, D., Pamungkas, E. W., Widayat, W., & Imaduddin, H.

Stress-Testing Large Language Models (LLMs) against Code-Mixing and Distributional Shifts in Low-Resource NLP.