metadata
tags:
- aspect identification
- aspect extraction
- multi-label classification
- tagalog
- filipino
- taglish
inference: false
language:
- tl
- en
base_model:
- google/gemma-3-1b-pt
Citations
All model details and training setups can be found in our papers. If you use our model or find it useful in your projects, please cite our work:
@article{dionela2025aspectextraction,
title={Aspect Extraction from E-Commerce Product and Service Reviews},
author={Valiant Lance Dionela, Fatima Kriselle Dy, Robin James Hombrebueno, Aaron Rae Nicolas, and Charibeth Cheng},
journal={ },
year={2025}
}
Data and Other Resources
The training and evaluation datasets, as well as label definitions, can be found in the respective CSV files under the datasets/ directory. Additional resources and related benchmark data may be available on the project website.