README.md

---
language:
- ja
license: other
size_categories:
- 1M<n<10M
task_categories:
- text-generation
pretty_name: Washi
dataset_info:
- config_name: 200k
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 5315275997
    num_examples: 200000
  download_size: 2841685460
  dataset_size: 5315275997
- config_name: 20m
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 105176099351.0
    num_examples: 20000000
  download_size: 60214844912
  dataset_size: 105176099351.0
- config_name: 400m
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 24693584215
    num_examples: 4000000
  download_size: 14134783813
  dataset_size: 24693584215
- config_name: 4m
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 24693584215
    num_examples: 4000000
  download_size: 14134783813
  dataset_size: 24693584215
configs:
- config_name: 200k
  data_files:
  - split: train
    path: 200k/train-*
- config_name: 20m
  data_files:
  - split: train
    path: 20m/train-*
- config_name: 400m
  data_files:
  - split: train
    path: 400m/train-*
- config_name: 4m
  data_files:
  - split: train
    path: 4m/train-*
tags:
- nlp
- pretrain
- llm
---

# Washi (a kind of traditional Japanese paper)

This dataset is sampled from a subset of ja (Japanese) sourced from [uonlp/CulturaX](https://huggingface.co/datasets/uonlp/CulturaX). 
Utilizing DSIR (Data Selection for Language Models via Importance Resampling), 
documents closest to the Japanese subset of csebuetnlp/xlsum and systemk/aozorabunko_chunked 
(cleaned data from the Aozora Bunko collection, containing modern Japanese literature in the public domain) were selected, 
comprising approximately 5% of the corpus.

We have noted a qualitative leap in the quantity of low-quality Japanese datasets with the release of several multilingual datasets. 
However, traditional data cleaning methods for Japanese, based on blacklists and rules, continue to produce significant noise.

We speculate that, particularly in cases where fine-tune from predominantly English-focused Large Language Model (LLM), 
the quality of data outweighs its quantity. Hence, we have created this dataset to validate this hypothesis.

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->

- **Language(s) (NLP):** Japanese
- **License:** ocd-by / cc0-1.0

### License Information

The licence terms for Washi strictly follows uonlp/CulturaX. 
Please refer to both below licenses when using this dataset.

- [mC4 license](https://huggingface.co/datasets/allenai/c4#license)
- [OSCAR license](https://huggingface.co/datasets/oscar-corpus/OSCAR-2301#licensing-information)


## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

[More Information Needed]

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

[More Information Needed]

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->

#### Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

[More Information Needed]

#### Who are the source data producers?

<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->

[More Information Needed]

### Annotations [optional]

<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->

#### Annotation process

<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->

[More Information Needed]

#### Who are the annotators?

<!-- This section describes the people or systems who created the annotations. -->

[More Information Needed]

#### Personal and Sensitive Information

<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->

[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Dataset Card Authors [optional]

[More Information Needed]

## Dataset Card Contact

[More Information Needed]