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---
language: ja
thumbnail: https://github.com/studio-ousia/luke/raw/master/resources/luke_logo.png
tags:
- luke
- named entity recognition
- entity typing
- relation classification
- question answering
license: apache-2.0
---
## luke-japanese
**luke-japanese** is the Japanese version of **LUKE** (**L**anguage **U**nderstanding with **K**nowledge-based **E**mbeddings), a pre-trained _knowledge-enhanced_ contextualized representation of words and entities. LUKE treats words and entities in a given text as independent tokens, and outputs contextualized representations of them. Please refer to our [GitHub repository](https://github.com/studio-ousia/luke) for more details and updates.
This model contains Wikipedia entity embeddings which are not used in general NLP tasks. Please use the [lite version](https://huggingface.co/studio-ousia/luke-japanese-base-lite/) for tasks that do not use Wikipedia entities as inputs.
**luke-japanese**は、単語とエンティティの知識拡張型訓練済みTransformerモデル**LUKE**の日本語版です。LUKEは単語とエンティティを独立したトークンとして扱い、これらの文脈を考慮した表現を出力します。詳細については、[GitHub リポジトリ](https://github.com/studio-ousia/luke)を参照してください。
このモデルは、通常のNLPタスクでは使われないWikipediaエンティティのエンベディングを含んでいます。単語の入力のみを使うタスクには、[lite version](https://huggingface.co/studio-ousia/luke-japanese-base-lite/)を使用してください。
### Experimental results on JGLUE
The experimental results evaluated on the dev set of
[JGLUE](https://github.com/yahoojapan/JGLUE) are shown as follows:
| Model | MARC-ja | JSTS | JNLI | JCommonsenseQA |
| ---------------------- | --------- | ------------------- | --------- | -------------- |
| | acc | Pearson/Spearman | acc | acc |
| **LUKE Japanese base** | **0.965** | **0.916**/**0.877** | **0.912** | **0.842** |
| _Baselines:_ | |
| Tohoku BERT base | 0.958 | 0.909/0.868 | 0.899 | 0.808 |
| NICT BERT base | 0.958 | 0.910/0.871 | 0.902 | 0.823 |
| Waseda RoBERTa base | 0.962 | 0.913/0.873 | 0.895 | 0.840 |
| XLM RoBERTa base | 0.961 | 0.877/0.831 | 0.893 | 0.687 |
The baseline scores are obtained from
[here](https://github.com/yahoojapan/JGLUE/blob/a6832af23895d6faec8ecf39ec925f1a91601d62/README.md).
### Citation
```latex
@inproceedings{yamada2020luke,
title={LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention},
author={Ikuya Yamada and Akari Asai and Hiroyuki Shindo and Hideaki Takeda and Yuji Matsumoto},
booktitle={EMNLP},
year={2020}
}
```
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