Upload README.md

README.md

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+---
+dataset_name: HVU_GQ
+language: 
+  - vi
+license: mit
+task_categories:
+  - text-generation
+  - question-generation
+task_ids:
+  - question-answering
+  - text-generation
+pretty_name: HVU Question Generation Dataset
+size_categories:
+  - 10K<n<100K
+source_datasets:
+  - original
+tags:
+  - vietnamese
+  - t5
+  - nlp
+  - question-generation
+---
+
+# HVU_GQ
+
+**HHVU_GQ** 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 QA dataset.
+2. Generate multiple, diverse questions given a user-provided text passage (context).
+
+---
+
+## 📁 Dataset Format
+
+Your dataset must follow the **SQuAD v2.0** JSON structure:
+
+```json
+{
+  "version": "v2.0",
+  "data": [
+    {
+      "title": "Đồ uống nào của Việt Nam từng lọt top ngon nhất thế giới?",
+      "paragraphs": [
+        {
+          "qas": [
+            {
+              "id": "q1_1",
+              "question": "Đồ uống nào của Việt Nam từng lọt top ngon nhất thế giới?",
+              "answers": [
+                {
+                  "text": "Theo bản đánh giá tháng 2/2023 của Taste Atlas...",
+                  "answer_start": "Theo bản đánh giá tháng 2/2023 của Taste Atlas..."
+                }
+              ],
+              "is_impossible": false
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
+```
+
+**Required fields:**
+- `title` → used as context
+- `question` → target question
+- `answers[0].text` → seed answer for training
+- `is_impossible` → filter for valid QAs
+
+**File name:** `30ktrain.json` (UTF-8)
+
+---
+
+## 📁 Datasets
+
+This repository provides datasets for **training** and **evaluating** Vietnamese question generation models.
+
+### 🔹 `DataTotalQCAtriples30k/`
+- **`30ktrain.json`** → 30,000 QCA triples for training.
+
+### 🔹 `Datatest1k/`
+- **`testorgin1k.json`** → 1,000 examples for manual & automatic evaluation.
+
+### 🔹 `Datatrain29k/`
+- **`29kcorpustag.json`** → 29,000 preprocessed QCA triples.
+
+> All files are UTF-8 encoded and ready for direct use in NLP pipelines.
+
+---
+
+## 📊 Evaluation Results
+
+We performed **manual evaluation on 500 samples** and **automatic evaluation on 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     |
+
+---
+
+## 🔧 Installation
+
+Create a virtual environment and install dependencies:
+
+### Windows (PowerShell)
+```powershell
+python -m venv .venv
+.venv\Scripts\Activate.ps1
+python -m pip install --upgrade pip
+pip install torch transformers datasets scikit-learn
+```
+
+### Linux / macOS
+```bash
+python3 -m venv .venv
+source .venv/bin/activate
+python -m pip install --upgrade pip
+pip install torch transformers datasets scikit-learn
+```
+
+---
+
+## 🚀 Training (Fine-tuning)
+
+Make sure `30ktrain.json` is in the same folder as `fine_tune_qg.py`.
+
+Run:
+```bash
+python fine_tune_qg.py
+```
+
+**What happens:**
+- Loads `30ktrain.json`
+- Splits into 80% train / 20% validation
+- Tokenizes using `T5Tokenizer`
+- Fine-tunes `VietAI/vit5-base` for 3 epochs
+- Saves model + tokenizer to `t5-viet-qg-finetuned/`
+
+**Key training parameters** (edit in `fine_tune_qg.py` if needed):
+- `per_device_train_batch_size`: 1
+- `learning_rate`: 2e-4
+- `num_train_epochs`: 3
+- `max_input_length`: 512
+- `max_target_length`: 64
+
+---
+
+## 💡 Generating Questions
+
+Once training is done, use `generate_question.py` to generate new questions.
+
+Ensure:
+- `MODEL_DIR` → `t5-viet-qg-finetuned/`
+- `DATA_PATH` → `30ktrain.json`
+
+Run:
+```bash
+python generate_question.py
+```
+
+Steps:
+1. Enter a context passage (Vietnamese)
+2. Enter number of questions (default 20, max 200)
+3. Script will:
+   - Find best match in dataset by title similarity
+   - Use matched answer + your context
+   - Generate multiple unique questions with top-k & top-p sampling
+4. Output lists generated questions.
+
+---
+
+## ⚙️ Generation Settings
+
+In `generate_question.py`, tweak:
+- `top_k` (default 60)
+- `top_p` (default 0.95)
+- `temperature` (default 0.9)
+- `no_repeat_ngram_size` (default 3)
+- `repetition_penalty` (default 1.12)
+
+---
+
+## 📂 Project Structure
+
+```
+.
+├── fine_tune_qg.py
+├── generate_question.py
+├── 30ktrain.json
+├── t5-viet-qg-finetuned/
+├── README.md
+└── LICENSE
+```
+
+---
+
+## 🔍 Example Usage
+
+**Training**
+```bash
+python fine_tune_qg.py
+```
+
+**Generating**
+```bash
+python generate_question.py
+```
+
+Example:
+```
+Nhập đoạn văn bản:
+ Cà phê sữa đá là đồ uống nổi tiếng ở Việt Nam.
+
+Nhập vào số lượng câu hỏi bạn cần: 5
+
+✅ Các câu hỏi mới được sinh ra:
+1. Loại cà phê nào nổi tiếng ở Việt Nam?
+2. Tại sao cà phê sữa đá được yêu thích?
+3. Cà phê sữa đá gồm những nguyên liệu gì?
+4. Nguồn gốc của cà phê sữa đá là từ đâu?
+5. Cà phê sữa đá Việt Nam được pha chế như thế nào?
+```
+
+---
+
+## 🤝 Contribution
+
+You’re welcome to:
+- Open issues
+- Submit pull requests
+- Suggest new datasets
+
+---
+
+## 📄 License
+
+Licensed under the MIT License – see the `LICENSE` file for details.
+
+---
+
+## 📬 Contact
+
+- **Ha Nguyen-Tien** (Corresponding author)  
+  Email: nguyentienha@hvu.edu.vn  
+
+- **Phuc Le-Hong**  
+  Email: Lehongphuc20021408@gmail.com
+
+- **DANG DO CAO**  
+  Email: docaodang532001@gmail.com
+
+---
+
+*This repository is part of an effort to advance Vietnamese NLP by making question generation more accessible for researchers and developers.*