DiTy/bi encoder russian msmarco This is a sentence transformers model based on a pre trained DeepPavlov/rubert base cased and finetuned with MS MARCO Russian passage ranking dataset: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for asymmetric semantic search in the Russian language. Usage (Sentence Transformers) Using this model becomes easy when you have sentence transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) 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. Training The model was trained with the parameters: DataLoader : torch.utils.data.dataloader.DataLoader of length 1989041 with parameters: Loss : sentence transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss with parameters: Parameters of the fit() Method: Full Model Architecture
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