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--- |
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license: mit |
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--- |
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This model is ANCE-Tele trained on MS MARCO. The training details and evaluation results are as follows: |
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|Model|Pretrain Model|Train w/ Marco Title|Marco Dev MRR@10|BEIR Avg NDCG@10| |
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|:----|:----|:----|:----|:----| |
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|ANCE-Tele|[cocodr-base](https://huggingface.co/OpenMatch/cocodr-base)|w/o|37.3|44.2| |
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|BERI Dataset|NDCG@10| |
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|:----|:----| |
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|TREC-COVID|77.4| |
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|NFCorpus|34.4 | |
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|FiQA|29.0 | |
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|ArguAna|45.6 | |
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|Touché-2020|22.3 | |
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|Quora|85.8 | |
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|SCIDOCS|14.6 | |
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|SciFact|71.0 | |
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|NQ|50.5 | |
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|HotpotQA|58.8 | |
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|Signal-1M|27.2 | |
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|TREC-NEWS|34.7 | |
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|DBPedia-entity|36.2 | |
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|Fever|71.4 | |
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|Climate-Fever|17.9 | |
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|BioASQ|42.1 | |
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|Robust04|41.4 | |
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|CQADupStack|34.9 | |
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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. |
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``` |
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@inproceedings{sun2022ancetele, |
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title={Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives}, |
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author={Si, Sun and Chenyan, Xiong and Yue, Yu and Arnold, Overwijk and Zhiyuan, Liu and Jie, Bao}, |
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booktitle={Proceedings of EMNLP 2022}, |
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year={2022} |
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} |
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``` |
