| # HVU_QA | |
| **HVU_QA** is a project dedicated to sharing datasets and tools for **Question Generation Processing (NLP)**, developed and maintained by the research team at **Hung Vuong University (HVU), Phu Tho, Vietnam**. | |
| This project is supported by **Hung Vuong University, Phu Tho, Vietnam**, with the aim of advancing research and applications in low-resource language processing, particularly for the Vietnamese language. | |
| --- | |
| ## 📚 Overview | |
| This repository enables you to: | |
| 1. Fine-tune the [VietAI/vit5-base](https://huggingface.co/datasets/DANGDOCAO/GeneratingQuestions) model on your own GQ dataset. | |
| 2. Generate multiple, diverse questions given a user-provided text passage (context). | |
| --- | |
| ## 📁 Datasets | |
| * Built following the **SQuAD v2.0 standard**, ensuring compatibility with NLP pipelines. | |
| * Includes tens of thousands of high-quality **Question–Context–Answer triples (QCA)**. | |
| * Suitable for both **training** and **evaluation**. | |
| --- | |
| ## 📁 Vietnamese Question Generation Tool | |
| A **command-line tool** for: | |
| * **Fine-tuning** a question generation model. | |
| * **Automatically generating questions** from Vietnamese text. | |
| Built on **Hugging Face Transformers (VietAI/vit5-base)** and **PyTorch**. | |
| --- | |
| ## Features | |
| * Fine-tune a question generation model with SQuAD v2.0 format data. | |
| * Generate diverse and creative questions from text passages. | |
| * Flexible generation parameters (`top-k`, `top-p`, `temperature`, etc.). | |
| * Simple command-line usage. | |
| * GPU support if available. | |
| --- | |
| ## 📊 Evaluation Results | |
| We conducted both **manual evaluation** (500 samples) and **automatic evaluation** (1,000 samples). | |
| | Evaluation Type | Precision | Recall | F1-Score | | |
| |------------------|-----------|--------|----------| | |
| | Automatic (1000) | 0.85 | 0.83 | 0.84 | | |
| | Manual (500) | 0.88 | 0.86 | 0.87 | | |
| ➡️ The model generates diverse, grammatically correct, and contextually appropriate questions. | |
| --- | |
| ## Creation Process | |
| The dataset was built using a **4-stage automated pipeline**: | |
| 1. Select relevant QA websites from trusted sources. | |
| 2. Automatic crawling to collect raw QA pages. | |
| 3. Semantic tag extraction to obtain clean Question–Context–Answer triples. | |
| 4. AI-assisted filtering to remove noisy or inconsistent samples. | |
| --- | |
| ## 📝 Quality Evaluation | |
| A fine-tuned model trained on **HVU_QA (VietAI/vit5-base)** achieved: | |
| * **BLEU Score**: 90.61 | |
| * **Semantic similarity**: 97.0% (cosine ≥ 0.8) | |
| * **Human evaluation**: | |
| * Grammar: **4.58 / 5** | |
| * Usefulness: **4.29 / 5** | |
| ➡️ These results confirm that **HVU_QA is a high-quality resource** for developing robust FAQ-style question generation models. | |
| --- | |
| ## 📂 Project Structure | |
| ``` | |
| .HVU_QA | |
| ├── t5-viet-qg-finetuned/ | |
| ├── fine_tune_qg.py | |
| ├── generate_question.py | |
| ├── 30ktrain.json | |
| └── README.md | |
| ``` | |
| > All data files are UTF-8 encoded and ready for use in NLP pipelines. | |
| --- | |
| ## 🛠️ Requirements | |
| * Python 3.8+ | |
| * PyTorch >= 1.9 | |
| * Transformers >= 4.30 | |
| * scikit-learn | |
| * Fine-tuned model (download at: [link](https://huggingface.co/datasets/DANGDOCAO/GeneratingQuestions/tree/main)) | |
| --- | |
| ## ⚙️ Setup | |
| ### 🛠️ Step 1: Download and Extract | |
| 1. Download `HVU_QA.zip` | |
| 2. Extract into a folder, e.g.: | |
| ``` | |
| D:\your\HVU_QA | |
| ``` | |
| ### 🛠️ Step 2: Add to Environment Path (if needed) | |
| 1. Open **System Properties → Environment Variables** | |
| 2. Select `Path` → **Edit** → **New** | |
| 3. Add the path, e.g.: | |
| ``` | |
| D:\your\HVU_QA | |
| ``` | |
| ### 🛠️ Step 3: Open in Visual Studio Code | |
| ``` | |
| File > Open Folder > D:\HVU_QA | |
| ``` | |
| ### 🛠️ Step 4: Install Required Libraries | |
| Open **Terminal** and run: | |
| #### Windows (PowerShell) | |
| **Required only** | |
| ```powershell | |
| python -m pip install --upgrade pip | |
| pip install torch transformers datasets scikit-learn sentencepiece safetensors | |
| ``` | |
| **Required + Optional** | |
| ```powershell | |
| python -m pip install --upgrade pip | |
| pip install torch transformers datasets scikit-learn sentencepiece safetensors accelerate tensorboard evaluate sacrebleu rouge-score nltk | |
| ``` | |
| #### Linux / macOS (bash/zsh) | |
| **Required only** | |
| ```bash | |
| python3 -m pip install --upgrade pip | |
| pip install torch transformers datasets scikit-learn sentencepiece safetensors | |
| ``` | |
| **Required + Optional** | |
| ```bash | |
| python3 -m pip install --upgrade pip | |
| pip install torch transformers datasets scikit-learn sentencepiece safetensors accelerate tensorboard evaluate sacrebleu rouge-score nltk | |
| ``` | |
| ✅ Verify installation: | |
| * Windows (PowerShell) | |
| ```powershell | |
| python -c "import torch, transformers, datasets, sklearn, sentencepiece, safetensors, accelerate, tensorboard, evaluate, sacrebleu, rouge_score, nltk; print('✅ All dependencies installed correctly!')" | |
| ``` | |
| * Linux/macOS | |
| ```bash | |
| python3 -c "import torch, transformers, datasets, sklearn, sentencepiece, safetensors, accelerate, tensorboard, evaluate, sacrebleu, rouge_score, nltk; print('✅ All dependencies installed correctly!')" | |
| ``` | |
| --- | |
| ## Usage | |
| * Train and evaluate a question generation model. | |
| * Develop Vietnamese NLP tools. | |
| * Conduct linguistic research. | |
| ### Training (Fine-tuning) | |
| When you run `fine_tune_qg.py`, the script will: | |
| 1. Load the dataset from **`30ktrain.json`** | |
| 2. Fine-tune the `VietAI/vit5-base` model | |
| 3. Save the trained model into a new folder named **`t5-viet-qg-finetuned/`** | |
| Run: | |
| ```bash | |
| python fine_tune_qg.py | |
| ``` | |
| ### Generating Questions | |
| ```bash | |
| python generate_question.py | |
| ``` | |
| **Example:** | |
| ``` | |
| Input passage: | |
| Iced milk coffee (Cà phê sữa đá) is a famous drink in Vietnam. | |
| Number of questions: 5 | |
| ``` | |
| ✅ Output: | |
| 1. What type of coffee is famous in Vietnam? | |
| 2. Why is iced milk coffee popular? | |
| 3. What ingredients are included in iced milk coffee? | |
| 4. Where does iced milk coffee originate from? | |
| 5. How is Vietnamese iced milk coffee prepared? | |
| --- | |
| ## ⚙️ Generation Settings | |
| In `generate_question.py`, you can adjust: | |
| * `top_k`, `top_p`, `temperature`, `no_repeat_ngram_size`, `repetition_penalty` | |
| --- | |
| ## 🤝 Contribution | |
| We welcome contributions: | |
| * Open issues | |
| * Submit pull requests | |
| * Suggest improvements or add datasets | |
| --- | |
| ## 📄 Citation | |
| If you use this repository or datasets in research, please cite: | |
| **Ha Nguyen-Tien, Phuc Le-Hong, Dang Do-Cao, Cuong Nguyen-Hung, Chung Mai-Van. 2025. A Method to Build QA Corpora for Low-Resource Languages. Proceedings of KSE 2025. ACM TALLIP.** | |
| ### 📚 BibTeX | |
| ```bibtex | |
| @inproceedings{nguyen2025hvuqa, | |
| title={A Method to Build QA Corpora for Low-Resource Languages}, | |
| author={Ha Nguyen-Tien and Phuc Le-Hong and Dang Do-Cao and Cuong Nguyen-Hung and Chung Mai-Van}, | |
| booktitle={Proceedings of KSE 2025}, | |
| year={2025} | |
| } | |
| ``` | |
| --- | |
| ## 📬 Contact | |
| * **Ha Nguyen-Tien** (Corresponding author) | |
| 📧 [nguyentienha@hvu.edu.vn](mailto:nguyentienha@hvu.edu.vn) | |
| * **Phuc Le-Hong** | |
| 📧 [Lehongphuc20021408@gmail.com](mailto:Lehongphuc20021408@gmail.com) | |
| * **Dang Do-Cao** | |
| 📧 [docaodang532001@gmail.com](mailto:docaodang532001@gmail.com) | |
| 📍 Faculty of Engineering and Technology, Hung Vuong University, Phu Tho, Vietnam | |
| 🌐 [https://hvu.edu.vn](https://hvu.edu.vn) | |
| --- | |
| *This repository is part of our ongoing effort to support Vietnamese NLP and make language technology more accessible for low-resource and underrepresented languages.* | |