Model training method and related equipment

Abstract

The embodiment of the invention provides a model training method which is applied to the field of artificial intelligence, and the method comprises the steps: obtaining a first neural network model and M batches of batch training samples, M being a positive integer greater than 1; then determining a target incremental training method according to sample distribution characteristics between batches of batch training samples in the M batches of batch training samples, wherein the sample distribution characteristics are related to the degree of catastrophic forgetting generated by the model when incremental training is carried out based on the batches of batch training samples; and using the target incremental training method for realizing catastrophic forgetting resistance when incremental training is performed on the model; and according to the M batches of batch training samples, performing self-supervised training on the first neural network model through a target incremental training method to obtain a second neural network model. According to the method, on the premise that the training time is shortened and the data storage space is saved, the balance between efficiency and performance is realized.

Description

technical field [0001] This application relates to the field of artificial intelligence, in particular to a model training method and related equipment. Background technique [0002] Artificial intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is the branch of computer science that attempts to understand the nature of intelligence and produce a new class of intelligent machines that respond in ways similar to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and decision-making. [0003] In the existing computer vision and natural language processing ta...

AI Technical Summary

Problems solved by technology

Compared to joint training, incremental training can significantly save computing and storage resources, but may cause model performance degradation due to catastrophic forgetting

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