README.md

---
license: mit
language:
- ro
tags:
- legal
- finance
- biology
- chemistry
- medical
- code
- climate
size_categories:
- 100K<n<1M
---
# Romanian Wikipedia - Processed Dataset

This is a processed version of the Romanian Wikipedia subset from the [FineWiki dataset](https://huggingface.co/datasets/HuggingFaceFW/finewiki), optimized for language model training and analysis. The dataset has been filtered to essential fields and enriched with token counts using tiktoken's cl100k_base encoding.

## Dataset Overview

- **Total Pages**: 493,462
- **Total Size**: ~669 MB (compressed parquet)
- **Language**: Romanian (ro)
- **Total Tokens**: ~395 million tokens (cl100k_base encoding)
- **Source**: FineWiki - An updated and better extracted version of the wikimedia/Wikipedia dataset originally released in 2023

## Dataset Structure

### Data Instances

Example from the Romanian subset (values truncated for readability):

```json
{
  "id": "rowiki/3217840",
  "title": "Melba (film)",
  "url": "https://ro.wikipedia.org/wiki/Melba_(film)",
  "date_modified": "2023-08-15T10:22:31Z",
  "text": "# Melba (film)\nMelba este un film biografic muzical britanic din 1953 regizat de Lewis Milestone...",
  "token_count": 2145
}
```

### Data Fields

- **id** (string): dataset-unique identifier; format: `rowiki/<page_id>`
- **title** (string): article title
- **url** (string): canonical article URL
- **date_modified** (string): ISO-8601 timestamp of the last page revision
- **text** (string): cleaned, structured article text preserving headings, lists, code/pre blocks, tables and math. Has markdown formatting (headings, tables, lists)
- **token_count** (int64): number of tokens in the text field, calculated using tiktoken's cl100k_base encoding (used by GPT-4 and similar models)

## Tokenization

Token counts are computed using [tiktoken](https://github.com/openai/tiktoken) with the **cl100k_base** encoding, which is the same tokenizer used by:
- GPT-4
- GPT-3.5-turbo
- text-embedding-ada-002

This makes the dataset particularly useful for training or fine-tuning models compatible with OpenAI's tokenization scheme.

## Processing Details

This dataset was created from the original FineWiki Romanian subset by:
1. Filtering from 14 columns down to 6 essential fields
2. Computing token counts for each article's text using tiktoken (cl100k_base)
3. Processing in batches of 10,000 rows for efficient computation
4. Saving as compressed parquet files with snappy compression

## Files

- `000_00000_processed.parquet`: 249,533 articles (~327 MB)
- `000_00001_processed.parquet`: 243,929 articles (~342 MB)

## Use Cases

- Training or fine-tuning Romanian language models
- Token budget analysis and dataset planning
- Information retrieval and semantic search
- Question answering systems
- Text summarization and generation tasks

## Citation Information

```bibtex
@dataset{penedo2025finewiki,
  author    = {Guilherme Penedo},
  title     = {FineWiki},
  year      = {2025},
  publisher = {Hugging Face Datasets},
  url       = {https://huggingface.co/datasets/HuggingFaceFW/finewiki},
  urldate   = {2025-10-20},
  note      = {Source: Wikimedia Enterprise Snapshot API (https://api.enterprise.wikimedia.com/v2/snapshots). Text licensed under CC BY-SA 4.0 with attribution to Wikipedia contributors.}
}
```

## License

The text content is licensed under **CC BY-SA 4.0** with attribution to Wikipedia contributors, as per the original Wikipedia content license.

## Dataset Creator

Processed and uploaded by [Yxanul](https://huggingface.co/Yxanul)