Multi-task model training method, information recommendation method, device and equipment
The invention provides a multi-task model training method, and relates to the technical field of artificial intelligence, in particular to the technical field of deep learning, cloud computing, multi-task parallel processing and data search. According to the specific implementation scheme, sample be...
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Main Authors | , , , |
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Format | Patent |
Language | Chinese English |
Published |
20.09.2022
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Subjects | |
Online Access | Get full text |
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Summary: | The invention provides a multi-task model training method, and relates to the technical field of artificial intelligence, in particular to the technical field of deep learning, cloud computing, multi-task parallel processing and data search. According to the specific implementation scheme, sample behavior data of a sample object is input into a shared sub-model, behavior feature information of the sample object is obtained, and the behavior feature information comprises multiple pieces of behavior feature sub-information; according to the behavior feature sub-information related to the task processing sub-model, obtaining a sub-loss value of the task processing sub-model; determining a target gradient value corresponding to the sub-loss value according to the sub-loss value of the task processing sub-model; determining a weight value corresponding to the sub-loss value according to the plurality of target gradient values; and training the multi-task model according to the plurality of sub-loss values and the |
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Bibliography: | Application Number: CN202211015938 |