---
dataset_info:
  features:
  - name: id
    dtype: int64
  - name: title
    dtype: string
  - name: topic
    dtype: string
  splits:
  - name: train
    num_bytes: 40302
    num_examples: 267
  download_size: 20514
  dataset_size: 40302
configs:
- config_name: default
  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.