metadata

license: apache-2.0
language:
  - ar
pretty_name: 101 Billion Arabic Words Dataset
size_categories:
  - 100B<n<1T
task_categories:
  - text-generation

Dataset Card for 101 Billion Arabic Words Dataset

Dataset Details

Dataset Description

The 101 Billion Arabic Words Dataset is curated by the Clusterlab team and consists of 101 billion words extracted and cleaned from web content, specifically targeting Arabic text. This dataset is intended for use in natural language processing applications, particularly in training and fine-tuning Large Language Models (LLMs) capable of understanding and generating Arabic text.

Curated by: Clusterlab Team
Language(s) (NLP): Mix of Modern Standard Arabic (MSA) & Arabic Dialects
License: Apache 2.0
Repository: HuggingFace Dataset Page
Paper [101 Billion Arabic Words Dataset]*(https://arxiv.org/abs/2405.01590): [Published on Arxiv]

Uses

Direct Use

The dataset is suitable for training and fine-tuning models that perform a variety of NLP tasks in Arabic, including text classification, sentiment analysis, and machine translation. Its vast size and comprehensive coverage of Arabic text make it a valuable resource for developing robust language models.

Out-of-Scope Use

The dataset is not intended for uses that require personal or sensitive data as it consists of general web text. Uses requiring fine-grained dialectal understanding or specific cultural nuances without further processing and adaptation might find limitations in this dataset.

Dataset Structure

{
  "text": "content...",
  "date": "YYYY-MM-DDTHH:MM:SSZ",
  "url": "URL"
}

Dataset Creation

Curation Rationale

This dataset was created to address the significant lack of large-scale, high-quality datasets for the Arabic language in NLP research and application development. It aims to provide a robust foundation for developing more accurate and efficient Arabic language models.

Source Data

Data Collection and Processing

Data was collected from the Common Crawl archive, focusing on Arabic content within a specified time frame. The data underwent extensive cleaning and deduplication processes to ensure quality and relevance.

Who are the source data producers?

The data was produced by web content creators worldwide and collected through the Common Crawl project, which provides an extensive archive of the web's content.

Bias, Risks, and Limitations

The dataset primarily consists of web text that may include biases present in online content. Users should be aware of these potential biases when training models with this dataset. Further research and adjustment may be necessary to mitigate these biases for specific applications.

Recommendations

Users should critically evaluate the dataset for any potential biases or misrepresentations of the Arabic language and culture due to its web-derived nature.