Update README.md

README.md

@@ -18,4 +18,90 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+
+language: ba
+license: mit
+tags:
+- bashkir
+- low-resource-language
+- topic-classification
+- news
+- task-specific-tuning
+pretty_name: Bashqort Topic Classification
+size_categories:
+- 100<n<1000
 ---
+
+# Bashqort Topic Classification
+
+## Description
+
+A **topic classification** dataset for Bashkir news headlines. This dataset was created because no publicly available topic classification benchmark exists for Bashkir. It is intended for **task‑specific fine‑tuning** and evaluation of LLMs adapted to Bashkir.
+
+## Data Creation
+
+- **Source**: Random sampling of headlines from [bash.news](https://bash.news)
+- **Annotation**: Manual labeling by **Ilyas Khatipov** (native speaker of Bashkir)
+- **Cleaning**: Removed categories with fewer than 17 samples to improve class balance
+
+## Class Distribution (after cleaning)
+
+| Topic | Count | Proportion |
+|-------|-------|-------------|
+| Culture (Мәҙәниәт) | 58 | 21.7% |
+| Healthcare (Һаулыҡ һаҡлау) | 35 | 13.1% |
+| Education (Мәғариф) | 32 | 12.0% |
+| Social sphere (Социаль өлкә) | 25 | 9.4% |
+| Politics (Сәйәсәт) | 25 | 9.4% |
+| Sports (Спорт) | 21 | 7.9% |
+| Military service (Хәрби хеҙмәт) | 18 | 6.7% |
+| Economy (Иҡтисад) | 18 | 6.7% |
+| Incidents (Ваҡиғалар) | 18 | 6.7% |
+| Security (Хәүефһеҙлек) | 17 | 6.4% |
+
+**Total**: 267 headlines (10 classes)
+
+
+## Format
+
+The dataset is provided in CSV/JSON format with the following columns:
+
+- `title`: Bashkir news headline (string)
+- `topic`: topic label (string, one of the 10 classes)
+
+```json
+{
+  "title": "Өфөлә мәктәптәрҙә яңы уҡыу йылы башланды",
+  "topic": "Education"
+}
+```
+
+## Splits
+
+No fixed train/test split. Users are encouraged to create their own splits (e.g., 80/20) for reproducibility.
+## Intended Use
+
+    Task‑specific fine‑tuning of LLMs for topic classification
+
+    Zero‑shot and few‑shot evaluation of Bashkir language understanding
+
+    Benchmark for future Bashkir NLP work
+
+## Licensing
+
+MIT License
+## Citation
+```bibtex
+
+@misc{khudiakova2025bashqorttask,
+  author       = {Khudiakova, Kseniia and Khatipov, Ilyas},
+  title        = {Bashqort Topic Classification: News Headlines with 10 Topics},
+  year         = {2025},
+  howpublished = {Hugging Face Datasets},
+  url          = {https://huggingface.co/datasets/metuKKhud/bashqort-task}
+}
+```
+
+## Acknowledgements
+
+Thanks to Ilyas Khatipov for native speaker validation and annotation.