Cross Encoder for MS MARCO EN DE This is a cross lingual Cross Encoder model for EN DE that can be used for passage re ranking. It was trained on the MS Marco Passage Ranking task. The model can be used for Information Retrieval: See SBERT.net Retrieve & Re rank. The training code is available in this repository, see train script.py . Usage with SentenceTransformers When you have SentenceTransformers installed, you can use the model like this: Usage with Transformers With the transformers library, you can use the model like this: Performance The performance was evaluated on three datasets: TREC DL19 EN EN : The original TREC 2019 Deep Learning Track: Given an English query and 1000 documents (retrieved by BM25 lexical search), rank documents with according to their relevance. We compute NDCG@10. BM25 achieves a score of 45.46, a perfect re ranker can achieve a score of 95.47. TREC DL19 DE EN : The English queries of TREC DL19 have been translated by a German native speaker to German. We rank the German queries versus the English passages from the original TREC DL19 setup. We compute NDCG@10. GermanDPR DE DE : The GermanDPR dataset provides German queries and German passages from Wi…
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