README.md

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# 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

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### Direct Use

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[More Information Needed]

### Out-of-Scope Use

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## Dataset Structure

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## Dataset Creation

### Curation Rationale

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### Source Data

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

#### Data Collection and Processing

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#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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#### Who are the annotators?

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#### Personal and Sensitive Information

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## Bias, Risks, and Limitations

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### Recommendations

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

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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