Abstract: A neural network training method, apparatus, a storage medium, and a computer device are provided. The method includes: obtaining a training sample set, each training sample including a standard label; inputting the each training sample into a neural network model including n attention networks, the n attention networks respectively mapping the each training sample to n subspaces, each of the n subspaces including a query vector sequence, a key vector sequence, and a value vector sequence; calculating a space difference degree between the n subspaces by using the neural network model; calculating an output similarity degree according to an output of the neural network model and the standard label corresponding to the each training sample; and adjusting a model parameter of the neural network model according to the space difference degree and the output similarity degree until a convergence condition is satisfied to obtain a target neural network model.