| --- |
| license: mit |
| task_categories: |
| - question-answering |
| - text-generation |
| - table-question-answering |
| - sentence-similarity |
| - feature-extraction |
| language: |
| - vi |
| tags: |
| - question-generation |
| - nlp |
| - faq |
| - low-resource |
| - code |
| pretty_name: HVU_QA |
| size_categories: |
| - 10K<n<100K |
| --- |
| # HVU_QA |
| |
| **HVU_QA** is an open-source Vietnamese Question–Context–Answer (QCA) corpus, accompanied by supporting tools, created to facilitate the development of FAQ-style question generation and question answering systems, particularly for low-resource language settings. The dataset is developed by a research team at Hung Vuong University, Phu Tho, Vietnam, led by Dr. Ha Nguyen, Deputy Head of the Department of Engineering Technology. HVU_QA was constructed using a fully automated data-building pipeline that combines web crawling from reliable sources, semantic tag-based extraction, and AI-assisted filtering, helping ensure high factual accuracy, consistent structure, and practical usability for real-world applications. |
|
|
| ## 📋 Dataset Description |
|
|
| - **Language:** Vietnamese |
| - **Format:** SQuAD-style JSON |
| - **Total samples:** 39,000 QCA triples (full corpus released) |
| - **Domains covered:** Social services, labor law, administrative processes, and other public service topics. |
| - **Structure of each sample:** |
| - **Question:** Generated or extracted question |
| - **Context:** Supporting text passage from which the answer is derived |
| - **Answer:** Answer span within the context |
|
|
| ## ⚙️ Creation Pipeline |
|
|
| The dataset was built using a 4-stage automated process: |
| 1. **Selecting relevant QA websites** from trusted sources. |
| 2. **Automated data crawling** to collect raw QA webpages. |
| 3. **Extraction via semantic tags** to obtain clean Question–Context–Answer triples. |
| 4. **AI-assisted filtering** to remove noisy or factually inconsistent samples. |
|
|
| ## 📊 Quality Evaluation |
| A fine-tuned `vit5-base` model trained on HVU_QA achieved: |
| |
| | Metric | Score | |
| |-------------------------|----------------| |
| | BLEU | 89.1 | |
| | Semantic similarity | 91.5% (cos ≥ 0.8) | |
| | Human grammar score | 4.58 / 5 | |
| | Human usefulness score | 4.29 / 5 | |
| |
| These results confirm that HVU_QA is a high-quality resource for developing robust FAQ-style question generation models. |
|
|
| ## 📁 Dataset Structure |
| ``` |
| .HVU_QA |
| ├── t5-viet-qg-finetuned/ |
| ├── fine_tune_qg.py |
| ├── generate_question.py |
| ├── 39k_train.json |
| └── README.md |
| ``` |
| ## 📁 Vietnamese Question Generation Tool |
|
|
| ## 🛠️ Requirements |
|
|
| * Python 3.8+ |
| * PyTorch >= 1.9 |
| * Transformers >= 4.30 |
| * scikit-learn |
|
|
| ### 📦 Install Required Libraries |
|
|
| ```bash |
| pip install datasets transformers sentencepiece safetensors accelerate evaluate sacrebleu rouge-score nltk scikit-learn |
| ``` |
|
|
| *(Install PyTorch separately from [pytorch.org](https://pytorch.org) if not installed yet.)* |
|
|
| ### 📥 Load Dataset from Hugging Face Hub |
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("DANGDOCAO/GeneratingQuestions", split="train") |
| print(ds[0]) |
| ``` |
| ## 📚 Usage |
|
|
| * Train and evaluate a question generation model. |
| * Develop Vietnamese NLP tools. |
| * Conduct linguistic research. |
|
|
| ### 🔹 Fine-tuning |
|
|
| ```bash |
| python fine_tune_qg.py |
| ``` |
|
|
| This will: |
|
|
| 1. Load the dataset from `39k_train.json`. |
| 2. Fine-tune `VietAI/vit5-base`. |
| 3. Save the trained model into `t5-viet-qg-finetuned/`. |
|
|
| *(Or download the pre-trained model: [t5-viet-qg-finetuned](https://huggingface.co/datasets/DANGDOCAO/GeneratingQuestions/tree/main).)* |
|
|
| ### 🔹 Generating Questions |
| ```bash |
| python generate_question.py |
| ``` |
|
|
| **Example:** |
| ``` |
| Input passage: |
| Cà phê sữa đá là một loại đồ uống nổi tiếng ở Việt Nam |
| (Iced milk coffee is a famous drink in Vietnam) |
| |
| Number of questions: 5 |
| ``` |
| **Output:** |
| ``` |
| 1. Loại cà phê nào nổi tiếng ở Việt Nam? |
| (What type of coffee is famous in Vietnam?) |
| 2. Tại sao cà phê sữa đá lại phổ biến? |
| (Why is iced milk coffee popular?) |
| 3. Cà phê sữa đá bao gồm những nguyên liệu gì? |
| (What ingredients are included in iced milk coffee?) |
| 4. Cà phê sữa đá có nguồn gốc từ đâu? |
| (Where does iced milk coffee originate from?) |
| 5. Cà phê sữa đá Việt Nam được pha chế như thế nào? |
| (How is Vietnamese iced milk coffee prepared?) |
| ``` |
| **You can adjust** in `generate_question.py`: |
|
|
| - `top_k`, `top_p`, `temperature`, `no_repeat_ngram_size`, `repetition_penalty` |
|
|
| ## 📌 Citation |
| If you use **HVU_QA** in your research, please cite: |
| |
| ```bibtex |
| @inproceedings{nguyen2025method, |
| author = {Ha Nguyen and Phuc Le and Dang Do and Cuong Nguyen and Chung Mai}, |
| title = {A Method for Building QA Corpora for Low-Resource Languages}, |
| booktitle = {Proceedings of the 2025 International Symposium on Information and Communication Technology (SOICT 2025)}, |
| year = {2025}, |
| publisher = {Springer}, |
| series = {Communications in Computer and Information Science (CCIS)}, |
| address = {Nha Trang, Vietnam}, |
| note = {To appear} |
| } |
| ``` |
| ## ❤️ Support / Funding |
| |
| If you find **HVU_QA** useful, please consider supporting our work. |
| Your contributions help us maintain the dataset, improve quality, and release new versions (cleaning, expansion, benchmarks, and tools). |
|
|
| ### 🇻🇳 Donate via VietQR (scan to support) |
| This **VietQR / NAPAS 247** code can be scanned by Vietnamese banking apps and some international payment apps that support QR bank transfers. |
|
|
| <img src="QRtk.jpg" alt="VietQR Support" width="320"/> |
|
|
| **Bank:** VietinBank (Vietnam) |
| **Account name:** NGUYEN TIEN HA |
| **Account number:** 103004492490 |
| **Branch:** VietinBank CN PHU THO - HOI SO |
|
|
| ### 🌍 International Support (Quick card payment) |
| If you are outside Vietnam, you can support this project via **Buy Me a Coffee** |
| (no PayPal account needed — pay directly with a credit/debit card): |
| - BuyMeACoffee: https://buymeacoffee.com/hanguyen0408 |
|
|
| ### 🌍 International Support (PayPal) |
| If you prefer PayPal, you can also support us here: |
| - PayPal.me: https://paypal.me/HaNguyen0408 |
|
|
| ### ✨ Other ways to support |
| - ⭐ Star this repository / dataset on Hugging Face |
| - 📌 Cite our paper if you use it in your research |
| - 🐛 Open issues / pull requests to improve the dataset and tools |
| - |
| 📬 Contact / Maintainers |
| For questions, feedback, collaborations, or issue reports related to HVU_QA, please contact: |
| Dr. Ha Nguyen (Project Lead) |
| Hung Vuong University, Phu Tho, Vietnam |
| Email: nguyentienha@hvu.edu.vn |