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mstsb-paraphrase-multilingual-mpnet-base-v2

AIDA-UPM

This is a fine-tuned version of `paraphrase-multilingual-mpnet-base-v2` from sentence-transformers model with Semantic Textual Similarity Benchmark extended to 15 languages: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering, semantic search and measuring the similarity between two sentences. This model is fine-tuned version of `paraphrase-multilingual-mpnet-base-v2` for semantic textual similarity with multilingual data. The dataset used for this fine-tuning is STSb extended to 15 languages with Google Translator. For mantaining data quality the sentence pairs with a confidence value below 0.7 were dropped. The extended dataset is available at GitHub. The languages included in the extended version are: ar, cs, de, en, es, fr, hi, it, ja, nl, pl, pt, ru, tr, zh-CN, zh-TW. The pooling operation used to condense the word embeddings into a sentence embedding is mean pooling (more info below). Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.

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