YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/model-cards#model-card-metadata)
language: en
tags:
- sentence-embeddings
- sentence-similarity
cambridgeltl/mirror-roberta-base-sentence-drophead
An unsupervised sentence encoder proposed by Liu et al. (2021), using drophead instead of dropout as feature space augmentation. The model is trained with unlabelled raw sentences, using roberta-base as the base model. Please use [CLS] (before pooler) as the representation of the input.
Note the model does not replicate the exact numbers in the paper since the reported numbers in the paper are average of three runs.
Citation
@inproceedings{
liu2021fast,
title={Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders},
author={Liu, Fangyu and Vuli{\'c}, Ivan and Korhonen, Anna and Collier, Nigel},
booktitle={EMNLP 2021},
year={2021}
}
- Downloads last month
- 17
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.