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Datasets:
UCLNLP
/
monoweb-dataset

Tasks:
Text Generation
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
German
Spanish
Size:
100M - 1B
ArXiv:
Tags:
pretraining
multilingual
monolingual
web-corpus
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monoweb-dataset
File size: 2,136 Bytes
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---
language:
  - en
  - de
  - es
  - fr
task_categories:
  - text-generation
pretty_name: MonoWeb Dataset
tags:
  - pretraining
  - multilingual
  - monolingual
  - web-corpus
---

# MonoWeb Dataset

MonoWeb is a multilingual pretraining corpus derived from [FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) (English) and [FineWeb2](https://huggingface.co/datasets/HuggingFaceFW/fineweb-2) (German, Spanish, French) by systematically removing all mixed-language documents.

Released alongside the paper:

> **[The Role of Mixed-Language Documents for Multilingual Large Language Model Pretraining](https://arxiv.org/pdf/2601.00364)**

## Dataset Structure

```
monoweb-dataset/
├── eng/                                     # Full English corpus (FineWeb-Edu)
├── deu/                                     # Full German corpus (FineWeb2)
├── fra/                                     # Full French corpus (FineWeb2)
├── spa/                                     # Full Spanish corpus (FineWeb2)
├── finewebedu-en-de-parallel-codeswitch/    # Removed en-de bilingual docs (English side)
├── finewebedu-en-es-parallel-codeswitch/    # Removed en-es bilingual docs (English side)
├── finewebedu-en-fr-parallel-codeswitch/    # Removed en-fr bilingual docs (English side)
├── fineweb2-de-en-parallel-codeswitch/      # Removed en-de bilingual docs (German side)
├── fineweb2-es-en-parallel-codeswitch/      # Removed en-es bilingual docs (Spanish side)
└── fineweb2-fr-en-parallel-codeswitch/      # Removed en-fr bilingual docs (French side)
```

The four folders (`eng`, `deu`, `fra`, `spa`) contain the full source corpora (FineWeb-Edu / FineWeb2), 60B tokens per language (240B total). The `parallel-codeswitch` folders contain the parallel and code-switching documents identified and removed from the full corpus (miscellaneous documents are excluded). The MonoWeb corpus is obtained by excluding the `parallel-codeswitch` documents from the full set.



## Associated Models

Pretrained models are available at: https://huggingface.co/UCLNLP/monoweb