Question and answer reading understanding model acquisition method and device, electronic equipment and storage medium

Abstract

The invention discloses a question and answer reading understanding model acquisition method and device, electronic equipment and a storage medium, and relates to the field of deep learning. The method can comprise: for N models with different structures, N being a positive integer greater than 1, carrying out pre-training by using unsupervised training data to obtain N pre-training models, wherein different models correspond to different pre-training tasks respectively; taking a question and answer reading understanding task as a main task, taking other predetermined natural language processing tasks as auxiliary tasks, and performing fine adjustment on each pre-training model by utilizing supervised training data to obtain N fine adjustment models; and determining a finally required question-answer reading understanding model according to the N fine adjustment models. By applying the scheme of the invention, the generalization ability and the like of the model can be improved.

Description

technical field [0001] This application relates to computer application technology, in particular to a method, device, electronic device and storage medium for acquiring a question-and-answer reading comprehension model in the field of deep learning. Background technique [0002] Question and answer reading comprehension technology refers to given one or more paragraphs (P) and a question (Q), using machine learning methods to let the model predict the answer (A). [0003] The current question-and-answer reading comprehension models are mostly obtained based on pre-training-fine-tuning methods, that is, first select a model structure, then pre-train on a large number of unsupervised training data from a single source, and then use supervised training data, in a single The Q&A reading comprehension task is fine-tuned to obtain the final required Q&A reading comprehension model. [0004] However, the model structure and training tasks of the above method are single, which mak...

AI Technical Summary

Problems solved by technology

[0004] However, the model structure and training tasks of the above method are single, which makes it difficult for the model to learn some common features, which leads to weak generalization ability of the model, etc.

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