OpenMatch/dpr_bert-base_msmarco_qry-psg-encoder

This model is DPR trained on MS MARCO. The training details and evaluation results are as follows:

Model	Pretrain Model	Train w/ Marco Title	Marco Dev MRR@10	BEIR Avg NDCG@10
DPR	bert-base-uncased	w/	32.4	35.5

BERI Dataset	NDCG@10
TREC-COVID	58.8
NFCorpus	23.4
FiQA	20.6
ArguAna	39.4
Touché-2020	22.3
Quora	78.0
SCIDOCS	11.9
SciFact	49.4
NQ	43.9
HotpotQA	45.3
Signal-1M	20.2
TREC-NEWS	31.8
DBPedia-entity	28.7
Fever	65.0
Climate-Fever	14.9
BioASQ	24.1
Robust04	32.3
CQADupStack	28.3

The implementation is the same as our EMNLP 2022 paper "Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives". The associated GitHub repository is available at https://github.com/OpenMatch/ANCE-Tele.

@inproceedings{sun2022ancetele,
  title={Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives},
  author={Si, Sun and Chenyan, Xiong and Yue, Yu and Arnold, Overwijk and Zhiyuan, Liu and Jie, Bao},
  booktitle={Proceedings of EMNLP 2022},
  year={2022}
}