MS MARCO Passages Hard Negatives

MS MARCO is a large scale information retrieval corpus that was created based on real user search queries using Bing search engine.

This dataset repository contains files that are helpful to train bi-encoder models e.g. using sentence-transformers.

msmarco-hard-negatives.jsonl.gz

This is a jsonl file: Each line is a JSON object. It has the following format:

{"qid": 867436, "pos": [5238393], "neg": {"bm25": [...], ...}}

qid is the query-ID from MS MARCO, pos is a list with paragraph IDs for positive passages. neg is a dictionary where we mined hard negatives using different (mainly dense retrieval) systems.

cross-encoder-ms-marco-MiniLM-L-6-v2-scores.pkl.gz

This is a pickled dictionary in the format: scores[qid][pid] -> cross_encoder_score

It contains 160 million cross-encoder scores for (query, paragraph) pairs using the cross-encoder/ms-marco-MiniLM-L-6-v2 model.