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Natural language processing model training method and device

A technology for natural language processing and training methods, applied in the field of natural language processing model training, can solve problems such as poor execution effect and limited application scenarios of natural language processing models, and achieve the effect of improving performance and accurately processing results

Active Publication Date: 2020-11-13
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In the field of natural language processing technology, in some scenarios, the model is trained so that the model can complete tasks such as semantic understanding, translation, and question answering for a specific language. Once the language is switched for training, the execution effect is not good; in other scenarios Under this circumstance, the model can be used to complete tasks such as semantic understanding, translation, and question answering in specific fields. If the model is trained for similar tasks in other fields and used in other fields to perform such tasks, the problem of poor performance also occurs.
It can be seen that the existing natural language processing model application scenarios are limited

Method used

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  • Natural language processing model training method and device
  • Natural language processing model training method and device

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Embodiment Construction

[0021] Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0022] The method and device for training a natural language processing model in the embodiments of the present application are described below with reference to the accompanying drawings.

[0023] figure 1 is a schematic diagram according to the first embodiment of the present application. Wherein, it should be noted that the execution subject of the embodiment of...

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Abstract

The invention discloses a natural language processing model training method and device, and relates to the technical field of deep learning and natural language processing. The specific implementationscheme is as follows: generating derivative models according to an obtained meta-model set of natural language processing, and adding the plurality of derivative models into the meta-model set as meta-models to increase the number of models in the meta-model set for subsequent meta-training of the meta-model set; and then, screening the meta-models in the meta-model set according to the performance parameters of the trained meta-models to obtain the meta-models with good performance for adaptive training of natural language processing tasks. Due to the fact that the scheme adopts the mode that the meta-models are enriched and then screened, the performance of the screened and reserved meta-models is improved, and no matter what fields or languages are involved in adaptive training, accurate processing results can be obtained on subsequent natural language processing tasks of the corresponding fields or languages.

Description

technical field [0001] This application relates to the technical field of artificial intelligence, specifically to the technical fields of deep learning and natural language processing, and in particular to a training method and device for a natural language processing model. Background technique [0002] In the field of natural language processing technology, in some scenarios, the model is trained so that the model can complete tasks such as semantic understanding, translation, and question answering for a specific language. Once the language is switched for training, the execution effect is not good; in other scenarios Under this circumstance, the model can be used to complete tasks such as semantic understanding, translation, and question answering in specific fields. If the model is trained for similar tasks in other fields and used in other fields to perform such tasks, the problem of poor performance also occurs. . It can be seen that the application scenarios of exi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/56G06F40/30
CPCG06F40/30G06F40/56
Inventor 王凡田浩方晓敏何径舟
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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