Update README.md

README.md

@@ -11,7 +11,17 @@ This could be able to distinguish between positive and negative content.
 This model was fine-tuned by using Natsume Souseki's documents
 For example Kokoro, Bocchan and Sanshiro and so on...
 
-# how to use 使い方
+# what is Luke?[1] 
+LUKE (Language Understanding with Knowledge-based Embeddings) is a new pre-trained contextualized representation of words and entities based on transformer. LUKE treats words and entities in a given text as independent tokens, and outputs contextualized representations of them. LUKE adopts an entity-aware self-attention mechanism that is an extension of the self-attention mechanism of the transformer, and considers the types of tokens (words or entities) when computing attention scores.
 
+LUKE achieves state-of-the-art results on five popular NLP benchmarks including SQuAD v1.1 (extractive question answering), CoNLL-2003 (named entity recognition), ReCoRD (cloze-style question answering), TACRED (relation classification), and Open Entity (entity typing).
 
+# how to use 使い方
 
+# Citation
+[1]@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}
+}