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README.md

@@ -1,50 +1,199 @@
 ---
-dataset_info:
-  - config_name: ces_Latn
-    features:
-      - name: text
-        dtype: string
-      - name: id
-        dtype: string
-      - name: url
-        dtype: string
-      - name: dump
-        dtype: string
-      - name: date
-        dtype: string
-      - name: language
-        dtype: string
-      - name: language_score
-        dtype: float64
 license: odc-by
 task_categories:
   - text-generation
 language:
-  - ces
+  - da
+  - sv
+  - "no"
+  - fi
+  - nl
+  - pl
+  - tr
+  - vi
+  - cs
 tags:
   - fineweb
   - autocurate
-  - autoresearch
+  - data-quality
+  - multilingual
+pretty_name: fineweb-2-autocurate
+configs:
+  - config_name: dan_Latn
+    data_files:
+      - split: train
+        path: data/dan_Latn/train/*
+  - config_name: swe_Latn
+    data_files:
+      - split: train
+        path: swe_Latn/train/*
+  - config_name: nob_Latn
+    data_files:
+      - split: train
+        path: nob_Latn/train/*
+  - config_name: fin_Latn
+    data_files:
+      - split: train
+        path: fin_Latn/train/*
+  - config_name: nld_Latn
+    data_files:
+      - split: train
+        path: nld_Latn/train/*
+  - config_name: pol_Latn
+    data_files:
+      - split: train
+        path: pol_Latn/train/*
+  - config_name: ces_Latn
+    data_files:
+      - split: train
+        path: ces_Latn/train/*
+  - config_name: tur_Latn
+    data_files:
+      - split: train
+        path: tur_Latn/train/*
+  - config_name: vie_Latn
+    data_files:
+      - split: train
+        path: vie_Latn/train/*
 ---
 
 # fineweb-2-autocurate
 
 Autonomously curated subsets of [HuggingFaceFW/fineweb-2](https://huggingface.co/datasets/HuggingFaceFW/fineweb-2).
 
-An AI agent (Qwen3.5-35B-A3B) iteratively analyzed random samples of web documents,
-identified quality problems, and proposed heuristic fixes (regex, string operations).
-Each fix was validated by training a small language model and measuring BPB improvement
-on a Wikipedia eval set. Only fixes that improved BPB were kept.
+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](https://github.com/bwang-pplx/autocurate).
 
 ## Subsets
 
-| Language | Original docs | Kept docs | Kept % |
-|---|---|---|---|
-| ces_Latn | 66,067,904 | 32,493,428 | 49.2% |
-| nob_Latn | 38,144,343 | 30,561,546 | 80.1% |
-| nld_Latn | 147,301,270 | 126,021,987 | 85.6% |
-| swe_Latn | 59,485,306 | 53,887,025 | 90.6% |
-| fin_Latn | 36,710,816 | 33,010,774 | 89.9% |
-| pol_Latn | 151,966,724 | 100,254,080 | 66.0% |
-| tur_Latn | 95,129,129 | 83,878,413 | 88.2% |
-| vie_Latn | 61,064,248 | 61,027,548 | 99.9% |
+| 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
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("bowang0911/fineweb-2-autocurate", "dan_Latn", split="train")
+```
+
+## Filters applied per language
+
+<details>
+<summary>Vietnamese (vie_Latn) — 1 filter</summary>
+
+- **Drop gambling/casino spam** — keyword density filter for betting and casino spam injected into articles
+
+</details>
+
+<details>
+<summary>Turkish (tur_Latn) — 2 cleaners, 3 filters</summary>
+
+- 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
+
+</details>
+
+<details>
+<summary>Czech (ces_Latn) — 2 cleaners, 4 filters</summary>
+
+- 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`)
+
+</details>
+
+<details>
+<summary>Polish (pol_Latn) — 2 cleaners, 3 filters</summary>
+
+- 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
+
+</details>
+
+<details>
+<summary>Finnish (fin_Latn) — 1 cleaner, 5 filters</summary>
+
+- 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
+
+</details>
+
+<details>
+<summary>Dutch (nld_Latn) — 2 cleaners, 3 filters</summary>
+
+- 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
+
+</details>
+
+<details>
+<summary>Swedish (swe_Latn) — 1 cleaner, 3 filters</summary>
+
+- Strip truncated document endings
+- Drop adult content and SEO spam
+- Drop truncated/incomplete paragraphs (scraping errors, paywalls)
+- Drop adult content keyword stuffing (density filter)
+
+</details>
+
+<details>
+<summary>Norwegian Bokmål (nob_Latn) — 1 cleaner, 2 filters</summary>
+
+- Strip boilerplate/footer artifacts and platform noise
+- Drop boilerplate interface elements
+- Drop SEO spam keyword stuffing
+
+</details>
+
+<details>
+<summary>Danish (dan_Latn) — 5 rules</summary>
+
+- 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
+
+</details>
+
+## 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](https://github.com/bwang-pplx/autocurate) for details.
+
+## License
+
+Same as fineweb-2: [ODC-BY](https://opendatacommons.org/licenses/by/1-0/).