基于论文ESimCSE进行复现，基于STS-B训练集进行训练，在中文STS-B的验证集spermanr相关性得分为0.7226.


论文参考：

@inproceedings{Wu2021ESimCSEES,

title={ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence Embedding},

author={Xing Wu and Chaochen Gao and Liangjun Zang and Jizhong Han and Zhongyuan Wang and Songlin Hu},

booktitle={International Conference on Computational Linguistics},

year={2021}

}
{"language": ["zh"], "metrics": ["spearmanr"]}
transformers pytorch bert feature-extraction zh endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #feature-extraction #zh #endpoints_compatible #region-us 

基于论文ESimCSE进行复现，基于STS-B训练集进行训练，在中文STS-B的验证集spermanr相关性得分为0.7226.


论文参考：

@inproceedings{Wu2021ESimCSEES,

title={ESimCSE: Enhanced Sample Building Method for Contrastive Learning of Unsupervised Sentence Embedding},

author={Xing Wu and Chaochen Gao and Liangjun Zang and Jizhong Han and Zhongyuan Wang and Songlin Hu},

booktitle={International Conference on Computational Linguistics},

year={2021}

}
TAGS
#transformers #pytorch #bert #feature-extraction #zh #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #bert #feature-extraction #zh #endpoints_compatible #region-us 
