language:ja license:cc-by-sa-4.0 region:us
---
license: cc-by-sa-4.0
language:
- ja
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 1954209746
    num_examples: 745392
  - name: validation
    num_bytes: 107186201
    num_examples: 41576
  - name: test
    num_bytes: 107509760
    num_examples: 41268
  download_size: 420085060
  dataset_size: 2168905707
---
This dataset is a reformatted version of the Japanese portion of [wiki40b](https://aclanthology.org/2020.lrec-1.297/) dataset.
When you use this dataset, please cite the original paper:
```
@inproceedings{guo-etal-2020-wiki,
    title = "{W}iki-40{B}: Multilingual Language Model Dataset",
    author = "Guo, Mandy  and
      Dai, Zihang  and
      Vrande{\v{c}}i{\'c}, Denny  and
      Al-Rfou, Rami",
    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2020.lrec-1.297",
    pages = "2440--2452",
    abstract = "We propose a new multilingual language model benchmark that is composed of 40+ languages spanning several scripts and linguistic families. With around 40 billion characters, we hope this new resource will accelerate the research of multilingual modeling. We train monolingual causal language models using a state-of-the-art model (Transformer-XL) establishing baselines for many languages. We also introduce the task of multilingual causal language modeling where we train our model on the combined text of 40+ languages from Wikipedia with different vocabulary sizes and evaluate on the languages individually. We released the cleaned-up text of 40+ Wikipedia language editions, the corresponding trained monolingual language models, and several multilingual language models with different fixed vocabulary sizes.",
    language = "English",
    ISBN = "979-10-95546-34-4",
}
```
