---
language:
- so
license: mit
task_categories:
- text-generation
size_categories:
- 1K<n<10K
tags:
- somali
- bbc
- news
- educational
- low-resource-language
pretty_name: FineWeb Somali - BBC Somali Content
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
dataset_info:
  features:
  - name: text
    dtype: string
  - name: id
    dtype: string
  - name: token_count
    dtype: int64
  splits:
  - name: train
    num_bytes: 21949333.254534338
    num_examples: 4808
  - name: validation
    num_bytes: 451951.7454656613
    num_examples: 99
  download_size: 13256325
  dataset_size: 22401285.0
---

# FineWeb Somali Dataset

A curated collection of Somali language content from BBC Somali, designed for training and evaluating small language models on low-resource languages.

## Dataset Description

This dataset contains 4,910 high-quality Somali language articles scraped from BBC Somali's website. The content covers diverse topics including news, culture, technology, sports, and human interest stories, providing a rich corpus for Somali language model training.

### Dataset Summary

- **Language**: Somali (so)
- **Total Records**: 4,910 articles
- **Source**: BBC Somali (bbc.com/somali)
- **Collection Date**: January 25, 2026
- **License**: MIT (for educational and research purposes only)
- **Purpose**: Educational - for building and experimenting with small language models for low-resource languages

### Key Features

- ✅ **High-Quality Content**: Professional journalism from BBC Somali
- ✅ **Diverse Topics**: News, sports, culture, technology, health, and more
- ✅ **Clean Text**: Pre-processed and validated Somali text
- ✅ **Metadata Rich**: Includes URLs, dates, file paths, and token counts
- ✅ **Language Verified**: All content has language_score of 1.0

## Dataset Structure

### Data Fields

| Field | Type | Description |
|-------|------|-------------|
| `text` | string | Main article content (136-26,800 characters) |
| `id` | string | Unique identifier (UUID format, 36 chars) |
| `dump` | string | Dataset dump identifier (CC-MAIN-2026-SOMALI) |
| `url` | string | Source article URL (35-431 characters) |
| `date` | timestamp | Collection timestamp (2026-01-25 16:56:04) |
| `file_path` | string | Source file path (238 unique sources) |
| `language` | string | Language code (always "so") |
| `language_score` | float | Language detection confidence (always 1.0) |
| `token_count` | int | Number of tokens per article (17-4,160 tokens) |

### Data Splits

| Split | Records |
|-------|---------|
| train | 4,910 |

## Usage

### Loading the Dataset
```python
from datasets import load_dataset

# Load the full dataset
dataset = load_dataset("IbraahimLab/fineweb-somali")

# Access the training split
train_data = dataset['train']

# Example: Print first article
print(train_data[0]['text'][:500])
```

### Example Use Cases

**1. Training a Small Language Model**
```python
from transformers import AutoTokenizer, AutoModelForCausalLM, TrainingArguments, Trainer

# Load dataset
dataset = load_dataset("IbraahimLab/fineweb-somali")

# Initialize tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("your-base-model")
model = AutoModelForCausalLM.from_pretrained("your-base-model")

# Your training code here...
```

**2. Text Analysis**
```python
import pandas as pd

# Convert to pandas for analysis
df = dataset['train'].to_pandas()

# Analyze token distribution
print(df['token_count'].describe())

# Check content sources
print(df['file_path'].value_counts())
```

**3. Data Exploration**
```python
# Filter by token count
long_articles = dataset['train'].filter(lambda x: x['token_count'] > 1000)

# Sample random articles
sample = dataset['train'].shuffle(seed=42).select(range(10))
```

## Dataset Statistics

- **Total Articles**: 4,910
- **Total Characters**: ~40M (estimated)
- **Average Article Length**: ~8,150 characters
- **Token Count Range**: 17 - 4,160 tokens
- **Unique Sources**: 238 file paths
- **Language Purity**: 100% (all articles scored 1.0)

## Source Information

All content is sourced from **BBC Somali** (https://www.bbc.com/somali), which provides:
- Professional journalism in Somali language
- Wide topic coverage (news, sports, culture, tech, health)
- High-quality, edited content
- Diverse vocabulary and writing styles

### Content Categories
Based on file paths, content includes articles from various BBC Somali journalists and sections covering:
- Breaking news and current events
- Sports coverage
- Cultural stories
- Technology and science
- Health and lifestyle
- Human interest stories

## Intended Use

### Primary Use Cases
- 🎓 **Educational**: Learning to build language models for low-resource languages
- 🔬 **Research**: Somali NLP research and experimentation
- 🤖 **Model Training**: Pre-training or fine-tuning small language models
- 📊 **Linguistic Analysis**: Studying Somali language patterns and structures

### Out-of-Scope Use
- ❌ Commercial applications without proper licensing
- ❌ Creating misinformation or fake news in Somali
- ❌ Any use that violates BBC's terms of service

## Limitations

- **Single Source**: All content is from BBC Somali only
- **Temporal Scope**: Single collection date (January 25, 2026)
- **Domain**: Primarily news/journalism style, may not represent conversational Somali
- **Size**: Moderate dataset, may not be sufficient for large model training
- **License**: Educational/research purposes only

## Ethical Considerations

- This dataset is provided **for educational and research purposes only**
- Original content belongs to BBC and should be used in accordance with fair use principles
- Users should respect copyright and only use this for non-commercial learning purposes
- Researchers should cite both this dataset and BBC Somali as the original source

## Citation

If you use this dataset, please cite:
```bibtex
@dataset{fineweb_somali_2026,
  author = {IbraahimLab},
  title = {FineWeb Somali: BBC Somali Content for Language Model Training},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/IbraahimLab/fineweb-somali}
}
```

Also acknowledge the original source:
```
Content sourced from BBC Somali (https://www.bbc.com/somali)
```

## Dataset Creation

### Collection Process
- **Method**: Web scraping from BBC Somali website
- **Date**: January 25, 2026
- **Processing**: Text extraction, cleaning, and validation
- **Quality Control**: Language detection (all articles scored 1.0 for Somali)

### Preprocessing
- Text extracted from HTML content
- Character encoding standardized
- Token counts computed
- Metadata preserved (URLs, dates, sources)

## Maintenance

- **Version**: 1.0
- **Last Updated**: January 2026
- **Status**: Static dataset (snapshot from single date)

## Contact

For questions or issues regarding this dataset:
- **Creator**: IbraahimLab
- **Platform**: Hugging Face Datasets

## Acknowledgments

- **BBC Somali**: Original content creators
- **Somali Language Community**: For preserving and developing the language
- **Low-Resource Language Research Community**: For supporting Somali NLP development

---

**Disclaimer**: This dataset is intended solely for educational and research purposes. All content rights belong to BBC. Users must comply with applicable copyright laws and BBC's terms of service.