| --- |
| pretty_name: test strict shuffled |
| task_categories: |
| - text-generation |
| tags: |
| - parquet |
| license: odc-by |
| language: |
| - ja |
| --- |
| |
| # ClimbLab-Ja |
|
|
| ClimbLab-Ja is a filtered 300-billion-token Japanese corpus with 20 clusters. It is a Japanese adaptation of the [nvidia/Nemotron-ClimbLab](https://huggingface.co/datasets/nvidia/Nemotron-ClimbLab) approach. Based on [LLM-jp Corpus v4](https://gitlab.llm-jp.nii.ac.jp/datasets/llm-jp-corpus-v4), we semantically reorganized and filtered the dataset into 20 distinct clusters, resulting in a high-quality 300-billion-token corpus. Specifically, we first grouped the data into 1,000 groups based on topic information. Then we assigned six scores from 0 to 5 to each group and document: quality, advertisement, informational value, educational value, cultural value, and creative value. Low-quality clusters and documents were removed based on these scores. |
|
|
| This dataset is for research and development only. |
|
|
| ## Dataset Details |
|
|
| - Intended Usage: Pre-training language models. |
| - Format: Text in parquet format. |
| - Size: 300 billion tokens. |
|
|
| ## Filtering |
|
|
| We removed clusters using the following rule: |
|
|
| `quality_mean >= 2 && advertisement_mean >= 2 && any(value_mean >= 3)` |
|
|
| where `value_mean` refers to informational value, educational value, cultural value, or creative value. |
|
|
| We also removed documents using the following rule: |
|
|
| `quality >= 2 && advertisement >= 2 && any(value >= 3)` |
|
|
| where `value` refers to informational value, educational value, cultural value, or creative value. |
|
|
| ## License |
|
|
| The dataset structure, record IDs, filtering scores, mixture weights, and other metadata newly added in this release are licensed under [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). |
| By using this dataset, you are also bound by any license agreements and terms of use of the original data sources listed in the [LICENSES.md](LICENSES.md). |
|
|
| This dataset was created using the Supermicro ARS-111GL-DNHR-LCC and FUJITSU Server PRIMERGY CX2550 M7 (Miyabi) at the Joint Center for Advanced High Performance Computing (JCAHPC). |
