| --- |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: text |
| dtype: string |
| - name: url |
| dtype: string |
| - name: date |
| dtype: string |
| - name: dump |
| dtype: string |
| - name: file_path |
| dtype: string |
| - name: detected_lang |
| dtype: string |
| - name: word_count |
| dtype: int64 |
| - name: title |
| dtype: string |
| - name: source |
| dtype: string |
| - name: language |
| dtype: string |
| - name: token_count |
| dtype: int64 |
| - name: content_hash |
| dtype: string |
| - name: crawled_at |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 167232715.0 |
| num_examples: 41767 |
| - name: test |
| num_bytes: 10732830.0 |
| num_examples: 3769 |
| download_size: 73712640 |
| dataset_size: 177965545.0 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| --- |
| |
| # halohalo |
|
|
| ## Dataset Summary |
|
|
| `halohalo` is a Pretraining text corpus for Philippine languages, |
| assembled from web-scraped data. It is compatible with [Fineweb](https://huggingface.co/datasets/HuggingFaceFW/fineweb) for LLM Pretraining. |
|
|
| ## Source Data |
|
|
| Derived from the following cleaned datasets: |
|
|
| | Source | Documents | |
| |---|---| |
| | `halo-hil` | 8,874 | |
| | `halo-tgl` | 6,589 | |
| | `halo-bcl` | 1,264 | |
|
|
|
|
| Each source dataset was cleaned using `clean_halo.py` to remove web boilerplate, navigation menus, |
| markdown noise, HTML artifacts, and low-quality documents before being included here. |
|
|
| ## Processing |
|
|
| 1. **Cleaning** (`clean_halo.py`) — strips boilerplate, HTML, markdown noise; filters documents |
| with fewer than 30 words or less than 40% Latin characters |
| 2. **FineWeb formatting** (`prep_halohalo.py`) — adds `source`, `language`, `token_count`, |
| `content_hash`; deduplicates against existing documents using MD5 content hashing |
|
|
| Processing code is available at [github.com/sapinsapin/halohalo](https://github.com/sapinsapin/halohalo). |
|
|
| ## Statistics |
|
|
| | Metric | Value | |
| |---|---| |
| | Total documents | 16,727 | |
| | Total tokens | 19,178,582 | |
| | Avg tokens per document | 1,146.6 | |
| | Min tokens | 30 | |
| | Max tokens | 10,552 | |
|
|
| ### Languages |
|
|
| | Language | Documents | Word Count | |
| |---|---|---| |
| | `hil` | 8,874 | 9,332,784 | |
| | `tgl` | 6,589 | 8,208,749 | |
| | `bcl` | 1,264 | 1,637,049 | |
| | **Total** | **16,727** | **19,178,582** | |
|
|
| ## Schema |
|
|
| | Field | Type | Description | |
| |---|---|---| |
| | `text` | `str` | Cleaned document text | |
| | `id` | `str` | Unique document identifier | |
| | `source` | `str` | Source dataset name | |
| | `language` | `str` | ISO 639-3 language code | |
| | `token_count` | `int` | Whitespace-tokenized word count | |
| | `content_hash` | `str` | MD5 hash of text for deduplication | |
| | `url` | `str` | Source URL | |
| | `date` | `str` | Crawl date | |
| | `dump` | `str` | CommonCrawl dump identifier | |
| | `title` | `str` | Page title | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("sapinsapin/halohalo") |
| print(ds["train"][0]) |
| ``` |
|
|
