rifkybujana/IndoBERT-QA
🧠 AI Modelrifkybujana
A fine-tuned IndoBERT model for Indonesian language question answering based on the SQuAD v2.0 dataset.
IndoBERT-QA represents a specialized application of the BERT architecture, optimized for the Indonesian language. The project utilizes the IndoBERT Base-Uncased model as its foundation, which has been fine-tuned on the translated version of the Stanford Question Answering Dataset (SQuAD) v2.0. This allows the model to perform extractive question answering, where it identifies the correct span of text within a given passage to answer a user's query. The repository provides the necessary implementation details and Jupyter Notebooks to facilitate the training and inference process. It serves as a practical resource for those looking to build Indonesian-centric NLP pipelines, offering a pre-trained solution that understands the nuances of the language compared to standard multilingual models. The project is built using the Hugging Face ecosystem, ensuring compatibility with modern deep learning workflows and ease of deployment for developers working on Indonesian language AI solutions.
💡Highlights
- ├─Fine-tuned IndoBERT Base-Uncased
- ├─Trained on translated SQuAD v2.0
- └─Extractive QA for Indonesian
🎯For
- ├─NLP Researchers
- └─Indonesian AI Developers