Question answering model training method, computer device and readable storage medium

Abstract

The application discloses a question-answering model training method, computer equipment and a computer-readable storage medium. The training method of the question answering model includes: establishing a text matching model and a meta-learning model, the text matching model and the meta-learning model have the same deep neural network structure; obtaining test tasks and multiple different training tasks; The first matching loss of each task is used to update the meta-network parameters of the meta-learning model, and the first matching loss is used to represent the matching errors of the respective text matching models of multiple different training tasks; the text matching model is generated by using the updated meta-network parameters , and use the test task to train the text matching model to update the initial parameters of the text matching model, and use the text matching model obtained after training as the question answering model. Through the above method, the question answering model of the present application can be applied to the field of question answering with few samples, and the accuracy of question answer pair matching can be improved.

Description

technical field [0001] The present application relates to the technical field of machine learning, in particular to a question answering model training method, computer equipment and computer-readable storage media. Background technique [0002] Question answering system is an important branch of information retrieval and natural language processing. In recent years, with the rise of the Internet, a large amount of user-generated content has been accumulated on the Internet, resulting in a wealth of open domain question answering and vertical domain question answering data. [0003] In the community question answering scenario, a common application is to select the answer that best matches the current user question among the candidate answers, that is, answer sorting and selection. A question answering model with high accuracy can quickly locate the answer that best matches the new question among the candidate answers, improve the question answering rate, and improve user ex...

AI Technical Summary

Problems solved by technology

[0005] The technical problem mainly solved by this application is to provide a question answering model training method, computer equipment and computer-readable storage medium, which can solve the problem of difficult model training due to small sample size

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