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).
Please check the
official repository for
more details and updates.
This is the LUKE base model with 12 hidden layers, 768 hidden size. The total number
of parameters in this model is 253M. It is trained using December 2018 version of
Wikipedia.
1@inproceedings{yamada2020luke,
2 title={LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention},
3 author={Ikuya Yamada and Akari Asai and Hiroyuki Shindo and Hideaki Takeda and Yuji Matsumoto},
4 booktitle={EMNLP},
5 year={2020}
6}