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---
license: apache-2.0
language:
- en
tags:
- text-classification
- web-corpus
- balanced-dataset
size_categories:
- 100k<n<1M
---
# Unofficial m-a-p/FineFineWeb Equal Weighted Sample
A balanced, class-weighted subset of [m-a-p/FineFineWeb](https://huggingface.co/datasets/m-a-p/FineFineWeb) optimized for multi-class text classification tasks.
## ๐Ÿ“Š Dataset Overview
To prevent class imbalance issues during model training, this dataset extracts an equal-weighted sample across all fine-grained domain classes.
* **Original Dataset:** `m-a-p/FineFineWeb`
* **Total Samples:** 134,000 (0 duplicates)
* **Training Set (85%):** 113,900 rows
* **Validation Set (15%):** 20,100 rows
* **Classes:** 67 balanced domains (2,000 samples per class)
## ๐Ÿš€ Quick Start
Load the dataset easily using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
dataset = load_dataset("agentlans/finefineweb-equal-weighted")
print(dataset["train"][0])
```
## ๐Ÿ“‚ Data Structure
Each row contains text metadata, source tracking information, and the assigned domain label (`domain`).
### Example Row
```json
{
"url": "https://lothbury.exchange/parson-desires-cure-fund-for-local-utilities/",
"date": "2023-03-27T13:42:03Z",
"file_path": "s3://commoncrawl/crawl-data/CC-MAIN-2023-14/segments/1679296948632.20/warc/CC-MAIN-20230327123514-20230327153514-00428.warc.gz",
"language_score": 0.93825,
"token_count": 894,
"dump": "CC-MAIN-2023-14",
"global_id": "webtext-fineweb__CC-MAIN-2023-14__0__10195829",
"lang": "en",
"text": "Mike Parson is actually asking for an emergency therapy account...",
"domain": "journalism_and_media_communication",
"round": 1,
"source": "journalism_and_media_communication/journalism_and_media_communication_001222.jsonl"
}
```
> **Note:** The `source` field indicates the exact origin file from which the row was pulled.
## ๐Ÿ“‹ Class Distribution
All 67 categories maintain a strict 1:1 balance of **1,700 training samples** and **300 validation samples** (2,000 total per class).
| Label | Train | Validation | Total |
| --- | --- | --- | --- |
| aerospace | 1700 | 300 | 2000 |
| agronomy | 1700 | 300 | 2000 |
| artistic | 1700 | 300 | 2000 |
| astronomy | 1700 | 300 | 2000 |
| atmospheric_science | 1700 | 300 | 2000 |
| automotive | 1700 | 300 | 2000 |
| beauty | 1700 | 300 | 2000 |
| biology | 1700 | 300 | 2000 |
| celebrity | 1700 | 300 | 2000 |
| chemistry | 1700 | 300 | 2000 |
| christianity | 1700 | 300 | 2000 |
| civil_engineering | 1700 | 300 | 2000 |
| communication_engineering | 1700 | 300 | 2000 |
| computer_science_and_technology | 1700 | 300 | 2000 |
| design | 1700 | 300 | 2000 |
| drama_and_film | 1700 | 300 | 2000 |
| economics | 1700 | 300 | 2000 |
| electronic_science | 1700 | 300 | 2000 |
| entertainment | 1700 | 300 | 2000 |
| environmental_science | 1700 | 300 | 2000 |
| fashion | 1700 | 300 | 2000 |
| finance | 1700 | 300 | 2000 |
| food | 1700 | 300 | 2000 |
| gamble | 1700 | 300 | 2000 |
| game | 1700 | 300 | 2000 |
| geography | 1700 | 300 | 2000 |
| health | 1700 | 300 | 2000 |
| history | 1700 | 300 | 2000 |
| hobby | 1700 | 300 | 2000 |
| hydraulic_engineering | 1700 | 300 | 2000 |
| instrument_science | 1700 | 300 | 2000 |
| journalism_and_media_communication | 1700 | 300 | 2000 |
| landscape_architecture | 1700 | 300 | 2000 |
| law | 1700 | 300 | 2000 |
| library | 1700 | 300 | 2000 |
| literature | 1700 | 300 | 2000 |
| materials_science | 1700 | 300 | 2000 |
| mathematics | 1700 | 300 | 2000 |
| mechanical_engineering | 1700 | 300 | 2000 |
| medical | 1700 | 300 | 2000 |
| mining_engineering | 1700 | 300 | 2000 |
| movie | 1700 | 300 | 2000 |
| music_and_dance | 1700 | 300 | 2000 |
| news | 1700 | 300 | 2000 |
| nuclear_science | 1700 | 300 | 2000 |
| ocean_science | 1700 | 300 | 2000 |
| optical_engineering | 1700 | 300 | 2000 |
| painting | 1700 | 300 | 2000 |
| pet | 1700 | 300 | 2000 |
| petroleum_and_natural_gas_engineering | 1700 | 300 | 2000 |
| philosophy | 1700 | 300 | 2000 |
| photo | 1700 | 300 | 2000 |
| physics | 1700 | 300 | 2000 |
| politics | 1700 | 300 | 2000 |
| psychology | 1700 | 300 | 2000 |
| public_administration | 1700 | 300 | 2000 |
| relationship | 1700 | 300 | 2000 |
| sociology | 1700 | 300 | 2000 |
| sports | 1700 | 300 | 2000 |
| statistics | 1700 | 300 | 2000 |
| systems_science | 1700 | 300 | 2000 |
| textile_science | 1700 | 300 | 2000 |
| topicality | 1700 | 300 | 2000 |
| transportation_engineering | 1700 | 300 | 2000 |
| travel | 1700 | 300 | 2000 |
| urban_planning | 1700 | 300 | 2000 |
| weapons_science | 1700 | 300 | 2000 |
| **Total** | **113900** | **20100** | **134000** |
## ๐Ÿ“ License & Citation
This sample is distributed under the **Apache 2.0 License**.
If you use this balanced dataset in your research or applications, please cite the original FineFineWeb authors:
```bibtex
@misc{map2024finefineweb,
title={FineFineWeb: A Comprehensive Study on Fine-grained Domain Web Corpus},
url={https://huggingface.co/datasets/m-a-p/FineFineWeb},
author={Zhang, Ge and Du, Xinrun and Yu, Zhimiao and Wang, Zili and Wang, Zekun and Guo, Shuyue and Zheng, Tianyu and Zhu, Kang and Liu, Jerry and Yue, Shawn and Liu, Binbin and Peng, Zhongyuan and Yao, Yifan and Yang, Jack and Li, Ziming and Zhang, Bingni and Liu, Minghao and Liu, Tianyu and Gao, Yang and Chen, Wenhu and Zhou, Xiaohuan and Liu, Qian and Wang, Taifeng and Huang, Wenhao},
publisher={Hugging Face},
version={v0.1.0},
month={December},
year={2024}
}
```
## See Also
[agentlans/m-a-p-FineFineWeb-sample](https://huggingface.co/datasets/agentlans/m-a-p-FineFineWeb-sample) which is unbalanced but has more rows