bi-encoder_msmarco_bert-base_german

This model can be used for **semantic search** and **documents retrieval** to find relevant passages based on a query. It was trained on a machine translated **MSMARCO dataset** for _german_ with **hard negatives** and **Margin MSE loss**. Combining these elements results in a SOTA transformer for asymmetric search. Details are presented below. The model is based on training with samples from **MSMARCO Passage Ranking** dataset. It contains about 500.000 questions and 8.8 million passages. The training objective is to identify the relevant passages or answers for an input question. In terms of content, the texts deal with diverse domains. Questions are available as sentences but also keyword-based variants can be found. Consequently, models trained on MSMARCO can be used in a variety of domains. The dataset was originally published in English, but has been translated into other languages by researchers with the help of machine translation. To be more specific, **"mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset"** is used, which contains 13 Google based translations, German is one of them.

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