Classification network training method and device, computer equipment and storage medium

The invention relates to a classification network training method and a device, computer equipment and a storage medium. The method comprises the steps of determining a first weight factor of each category of sample data in a sample set according to the number of each category of sample data in the sample set; determining a second weight factor of each piece of sample data according to the gradient value of each piece of sample data in the sample set; and determining a loss value of the classification network according to the first weight factor, the second weight factor, the label corresponding to each piece of sample data and the classification result corresponding to each piece of sample data, and updating parameters in the classification network according to the loss value. According to the method, the value of the loss function containing the first weight factor and the second weight factor is adopted to train the classification network; and meanwhile, the problems of class imbalance of the training samp