fineweb-2-autocurate

Autonomously curated subsets of HuggingFaceFW/fineweb-2.

An LLM agent iteratively samples documents, identifies quality problems, and proposes heuristic fixes. Each fix is validated by training a small language model for 5 minutes and measuring BPB improvement on a Wikipedia eval set. Only fixes that improve BPB are kept.

Built with autocurate.

Subsets

Language	Subset	Original Docs	Kept Docs	Kept %	BPB Before → After	Improvement
Danish	dan_Latn	45.4M	39.5M	87%	1.448 → 1.422	-1.8%
Swedish	swe_Latn	59.5M	53.9M	91%	1.443 → 1.437	-0.4%
Norwegian Bokmål	nob_Latn	38.1M	30.6M	80%	1.447 → 1.439	-0.5%
Finnish	fin_Latn	36.7M	33.0M	90%	1.386 → 1.374	-0.8%
Dutch	nld_Latn	147.3M	126.0M	86%	1.405 → 1.391	-1.0%
Polish	pol_Latn	152.0M	100.3M	66%	1.196 → 1.176	-1.7%
Czech	ces_Latn	66.1M	32.5M	49%	1.167 → 1.153	-1.1%
Turkish	tur_Latn	95.1M	83.9M	88%	1.117 → 1.111	-0.6%
Vietnamese	vie_Latn	61.1M	61.0M	99.9%	0.863 → 0.808	-6.4%

Usage

from datasets import load_dataset

ds = load_dataset("bowang0911/fineweb-2-autocurate", "dan_Latn", split="train")

Filters applied per language

Vietnamese (vie_Latn) — 1 filter

• Drop gambling/casino spam — keyword density filter for betting and casino spam injected into articles

Turkish (tur_Latn) — 2 cleaners, 3 filters

• Strip aggregated unrelated content (news tickers, sidebars)
• Strip truncated line endings
• Drop incomplete/truncated text ending mid-sentence (2 rules)
• Drop SEO spam keyword stuffing

Czech (ces_Latn) — 2 cleaners, 4 filters

• Strip truncated line endings (...splňuje, ...Pokračovat ve čtení)
• Strip boilerplate footers (Můžete také zajímat, Zaregistrovat se, více »)
• Drop truncated articles containing ...
• Drop e-commerce pages (Skladem, PPL, Koupit, Poštovné)
• Drop cookie/boilerplate pages (využíváme soubory cookies, Copyright)
• Drop incomplete text (číst dále, zobrazit více)

Polish (pol_Latn) — 2 cleaners, 3 filters

• Strip footer boilerplate (Ostatnie wiadomości, Newsletter, Zaloguj się)
• Strip cookie/UI noise (Ta strona używa plików cookies)
• Drop truncated text (..., czytaj dalej, zobacz więcej)
• Drop truncated text with abrupt cutoffs
• Drop cookie banner documents

Finnish (fin_Latn) — 1 cleaner, 5 filters

• Strip link farm / footer leakage
• Drop CLI flags and ellipsis patterns
• Drop machine translation errors and gibberish
• Drop OCR errors and garbled text
• Drop grammar/syntax errors and morphological breakdowns
• Drop SEO spam keyword stuffing

Dutch (nld_Latn) — 2 cleaners, 3 filters

• Strip incomplete sentence endings and text cutoffs
• Strip boilerplate/navigation artifacts (footers, sidebars)
• Drop machine translation artifacts and nonsensical syntax
• Drop structural noise (UI artifacts, footer leakage)
• Drop aggressive filter patterns

Swedish (swe_Latn) — 1 cleaner, 3 filters

• Strip truncated document endings
• Drop adult content and SEO spam
• Drop truncated/incomplete paragraphs (scraping errors, paywalls)
• Drop adult content keyword stuffing (density filter)

Norwegian Bokmål (nob_Latn) — 1 cleaner, 2 filters

• Strip boilerplate/footer artifacts and platform noise
• Drop boilerplate interface elements
• Drop SEO spam keyword stuffing

Danish (dan_Latn) — 5 rules

• Drop short documents (< 500 chars / 50 words)
• Drop documents with high adult/spam keyword density
• Remove lines containing adult/NSFW keywords
• Strip truncation artifacts ("Læs mere")
• Drop SEO spam pages

Schema

Same as fineweb-2 — all original columns preserved. The text column contains cleaned text.

Method

Sample docs → LLM identifies problems → Propose fix → Train 5 min → BPB improved? → Keep / Revert

See autocurate for details.

License

Same as fineweb-2: ODC-BY.