| language: | |
| - en | |
| tags: | |
| - text reranking | |
| license: apache-2.0 | |
| datasets: | |
| - MS MARCO document ranking | |
| # BERT Reranker for MS-MARCO Document Ranking | |
| ## Model description | |
| A text reranker trained for BM25 retriever on MS MARCO document dataset. | |
| ## Intended uses & limitations | |
| It is possible to work with other retrievers like but using aligned BM25 works the best. | |
| We used anserini toolkit's BM25 implementation and indexed with tuned parameters (k1=3.8, b=0.87) following [this instruction](https://github.com/castorini/anserini/blob/master/docs/experiments-msmarco-doc.md). | |
| #### How to use | |
| See our [project repo page](https://github.com/luyug/Reranker). | |
| ## Eval results | |
| MRR @10: 0.423 on Dev. | |
| ### BibTeX entry and citation info | |
| ```bibtex | |
| @inproceedings{gao2021lce, | |
| title={Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline}, | |
| author={Luyu Gao and Zhuyun Dai and Jamie Callan}, | |
| year={2021}, | |
| booktitle={The 43rd European Conference On Information Retrieval (ECIR)}, | |
| } | |
| ``` |