update README

README.md

@@ -1,3 +1,59 @@
 ---
+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-large
+
+**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-large-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-large-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) is shown as follows:
+
+| Model                         | MARC-ja   | JSTS                | JNLI      | JCommonsenseQA |
+| ----------------------------- | --------- | ------------------- | --------- | -------------- |
+|                               | acc       | Pearson/Spearman    | acc       | acc            |
+| **LUKE Japanese large**       | **0.965** | **0.932**/**0.902** | **0.927** | 0.893          |
+| _Baselines:_                  |           |
+| Tohoku BERT large             | 0.955     | 0.913/0.872         | 0.900     | 0.816          |
+| Waseda RoBERTa large (seq128) | 0.954     | 0.930/0.896         | 0.924     | **0.907**      |
+| Waseda RoBERTa large (seq512) | 0.961     | 0.926/0.892         | 0.926     | 0.891          |
+| XLM RoBERTa large             | 0.964     | 0.918/0.884         | 0.919     | 0.840          |
+
+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}
+}
+```