A method and device for adjusting configuration parameters during model training
A technology for configuration parameters and model training, applied in the field of machine learning, can solve problems such as inability to adjust, affect model training efficiency and performance, and achieve the effect of improving efficiency and performance
Active Publication Date: 2021-10-01
ZHEJIANG UNIV +1
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These parameters greatly affect the efficiency and performance of model training
However, once the model training task starts running, if some parameters are found to be unreasonable, these parameters cannot be adjusted during the training process of the model.
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[0070] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with this specification. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present specification as recited in the appended claims.
[0071] The terminology used in the specification is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and the appended claims, the singular forms "a", "said" and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the t...
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This specification provides a method and device for adjusting configuration parameters during model training. According to the method for adjusting configuration parameters, during the model training process, at least one node metric index and at least one system metric index of a working node are collected; based on the node The metric indicator determines the first configuration parameter to be adjusted; determines the first adjustment strategy corresponding to the first configuration parameter to be adjusted; adjusts the first configuration parameter to be adjusted according to the first adjustment strategy; and sends the system metric indicator to the target device , make the target device determine the second configuration parameter to be adjusted, and determine the second adjustment strategy corresponding to the second configuration parameter to be adjusted; receive the second adjustment strategy returned by the target device; adjust the second adjustment strategy according to the second adjustment strategy configuration parameters. In this way, the purpose of adaptively adjusting the configuration parameters during the model training process is realized, and the efficiency and performance of the model training are improved.
Description
technical field [0001] One or more embodiments of this specification relate to the technical field of machine learning, and in particular to a method and device for adjusting configuration parameters during model training. Background technique [0002] Currently, when training a model through a distributed machine learning system, a large number of parameters need to be configured in advance. These parameters greatly affect the efficiency and performance of model training. However, once the model training task starts running, if some parameters are found to be unreasonable, these parameters cannot be adjusted during the training process of the model. Contents of the invention [0003] In order to solve one of the above technical problems, one or more embodiments of this specification provide a method and device for adjusting configuration parameters during model training. [0004] According to the first aspect, a method for adjusting configuration parameters during model...
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IPC IPC(8): G06N20/00G06F9/50H04L29/08
CPCG06F9/5072G06N20/00H04L67/10
Inventor 朱海洋周俊陈为严凡钱中昊毛科添
Owner ZHEJIANG UNIV