cambridgeltl/trans-encoder-bi-simcse-bert-base

---

language: en

tags:

• sentence-embeddings
• sentence-similarity
• dual-encoder

cambridgeltl/trans-encoder-bi-simcse-bert-base

An unsupervised sentence encoder (bi-encoder) proposed by Liu et al. (2021). The model is trained with unlabelled sentence pairs sampled from STS2012-2016, STS-b, and SICK-R, using princeton-nlp/unsup-simcse-bert-base-uncased as the base model. Please use [CLS] (before pooler) as the representation of the input.

Citation

@article{liu2021trans,
  title={Trans-Encoder: Unsupervised sentence-pair modelling through self-and mutual-distillations},
  author={Liu, Fangyu and Jiao, Yunlong and Massiah, Jordan and Yilmaz, Emine and Havrylov, Serhii},
  journal={arXiv preprint arXiv:2109.13059},
  year={2021}
}