| # MS MARCO - Multilingual Training | |
| This folder demonstrates how to train a multi-lingual SBERT model for [semantic search](https://www.sbert.net/examples/applications/semantic-search/README.html) / [information retrieval](https://www.sbert.net/examples/applications/retrieve_rerank/README.html). | |
| As dataset, we use the [MS Marco Passage Ranking dataset](https://github.com/microsoft/MSMARCO-Passage-Ranking). It is a large dataset consisting of search queries from Bing search engine with the relevant text passage that answers the query. | |
| Sadly this dataset is only available in English. As there are no large, multi-lingual datasets available suitable to train a semantic search model, we will use **machine translation** to translate the training data. | |
| ## Translating Data | |
| We will translate the queries and the passages using [EasyNMT](https://github.com/UKPLab/EasyNMT), which provides state-of-the-art machine translation to 150+ languages. | |
| Then, we will use [Multilingual Knowledge Distillation](https://www.sbert.net/examples/training/multilingual/README.html) and transform the English model trained on MS MARCO to a multi-lingual model. | |