| --- |
| license: mit |
| --- |
| |
| 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| |
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| The implementation is the same as our EMNLP 2022 paper ["Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives"](https://arxiv.org/pdf/2210.17167.pdf). 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} |
| } |
| ``` |
