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hi welcome to the video here were going to have a look at using net sentence prediction or nsp for fine-tuning our birth models now a few of the previous videos we covered mass language modeling and how we use mass language modeling to fine-tune our models nsp is like the other half of fine-tuning for bert so both of those techniques during the actual training of bert so when google train bert initially they use both of these methods and whereas mlm is identifying or almost training on the relationships between words next sentence prediction is training on more long-term relationships between sentences rather than words and in the original paper it was found that without nsp because they tried training but without nsp as well but performed worse on every single metric so it is pretty important and obviously if we take this approach we take mass language modeling and nsp and apply both those to our training our models fine-tuning our models were going to get better results and if we
