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hi welcome to the video were going to be covering how we can train a s better model or a sentence transformer or sentence better model using the what is kind of like the original way of training these models of fine-tuning these models which is using softmax loss so lets start with just a quick overview of the the training approach [Music] [Applause] [Music] [Applause] [Music] now using the softmax training approach is part of what we could call the natural language inference approach to fine-tuning these models and of or within that sort of category of training we have two approaches we have uh softmax loss or softmax classification loss which were going to cover and then we also have something called a multiple negatives ranking loss now in reality you probably wouldnt use softmax loss because its just nowhere near as good as using the the other form of loss of multiple negatives ranking im going to call it m r from from now on so m r is more effective but softmax loss is sort