Feature extraction model training method and device, equipment, medium and program product

Abstract

The invention provides a feature extraction model training method and device, equipment, a storage medium and a computer program product. The method comprises the steps of performing feature extraction on a plurality of training samples carrying sample tags through a feature extraction model of at least one historical version obtained through training to obtain a plurality of sample features corresponding to each historical version; determining a sample similarity between any two training samples based on a plurality of sample features corresponding to each historical version; based on the determined sample similarity, at least one training sample pair is selected from the multiple training samples, and the training sample pair comprises a first training sample and a second training sample; training a target feature extraction model based on the selected at least one training sample pair to obtain a trained feature extraction model; according to the invention, the training efficiency of the feature extraction model can be improved, and the feature extraction precision of the feature extraction model obtained through training can be improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular, to a training method, apparatus, device, storage medium and computer program product for a feature extraction model. Background technique [0002] Artificial intelligence (AI, Artificial Intelligence) is the theory, method, technology and application system that use 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 a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have th...

AI Technical Summary

Problems solved by technology

However, during the training process of some training samples, the predicted results and sample labels are very different. Such training samples will lead to a decrease in the accuracy of model learning. However, if the full amount of training samples are used in each iteration process in related technologies, It is difficult to pay attention to such training samples, which not only reduces the efficiency of model training, but also makes the model learning effect poor

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