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Method and device for generating model

A technology for generating models and models, applied in the computer field, can solve problems such as lack of data and poor reliability of models

Pending Publication Date: 2020-04-10
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, some industries in real applications often have the problem of lack of data, resulting in poor reliability of the model generated by traditional model training methods
For example, in the machine translation industry, there are less sample data in industries such as medicine and law, resulting in poor reliability of models trained using traditional model training methods based on large amounts of data

Method used

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  • Method and device for generating model

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Embodiment Construction

[0024] The present disclosure will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0025] It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

[0026] figure 1 An exemplary system architecture 100 of a method for generating a model or an apparatus for generating a model to which embodiments of the present disclosure can be applied is shown.

[0027] like figure 1 As shown, the system architecture 100 may incl...

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Abstract

The embodiment of the invention discloses a method and device for generating a model. One specific embodiment of the method comprises the steps of obtaining a universal corpus pair sample set in response to a received corpus model generation request, and obtaining a basic model by utilizing the universal corpus pair sample set, obtaining a domain corpus pair sample set, and iteratively executing abasic model parameter updating step comprising substeps of respectively obtaining a first preset number of general corpus pair samples and a second preset number of domain corpus pair samples from the obtained general corpus pair sample set and the domain corpus pair sample set, training model parameters of a basic model by sequentially utilizing the obtained universal corpus pair samples and domain corpus pair samples, and updating the basic model, and in response to the determined basic model parameter updating step, iteratively executing K times, and determining the basic model updated bythe Kth iteration as a corpus model. According to the embodiment of the invention, the corpus model with better reliability is obtained by training the sample with fewer domain corpora.

Description

technical field [0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to methods and devices for generating models. Background technique [0002] With the development of machine learning, existing AI technologies are widely used in various industries, such as machine translation, machine question answering, image recognition, etc. When applying A1 technology to various industries, it is necessary to obtain a large amount of sample data for model training. However, some industries in practical applications often have the problem of lack of data, resulting in poor reliability of the models generated by traditional model training methods. For example, in the machine translation industry, there are less sample data in industries such as medicine and law, resulting in poor reliability of models trained by traditional model training methods based on large amounts of data. Contents of the invention [0003] Embodiments of the...

Claims

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Application Information

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IPC IPC(8): G06N20/20G06N3/08G06N3/04
CPCG06N20/20G06N3/084G06N3/045
Inventor 熊皓何中军李芝吴华王海峰
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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