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This model is ANCE-Tele 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
ANCE-Tele cocodr-base w/o 37.3 44.2
BERI Dataset NDCG@10
TREC-COVID 77.4
NFCorpus 34.4
FiQA 29.0
ArguAna 45.6
Touché-2020 22.3
Quora 85.8
SCIDOCS 14.6
SciFact 71.0
NQ 50.5
HotpotQA 58.8
Signal-1M 27.2
TREC-NEWS 34.7
DBPedia-entity 36.2
Fever 71.4
Climate-Fever 17.9
BioASQ 42.1
Robust04 41.4
CQADupStack 34.9

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}
}
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