This is Roformer model pretrained on texts in the Japanese language.

3.45GB wikipedia text

trained 125M step

use the BERT BPE tokenizer.

If you want to fine-tune model. Please use



from transformers import BertTokenizer, RoFormerModel
BertTokenizer.from_pretrained('Roformer-base-japanese')
RoFormerModel.from_pretrained('Roformer-base-japanese')

The accuracy in JGLUE-marc-ja-v1.0 binary sentiment classification 95.12%

Contribute by Yokohama Nationaly University Mori Lab

@article{su2021roformer, title={Roformer: Enhanced transformer with rotary position embedding}, author={Su, Jianlin and Lu, Yu and Pan, Shengfeng and Wen, Bo and Liu, Yunfeng}, journal={arXiv preprint arXiv:2104.09864}, year={2021} }

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