Abstract: A target sample including a sample feature, a first label, and a second label is obtained, where a user corresponds to the target sample, the first label indicates whether a target object is clicked on by the user, and the second label indicates whether the user implements a target behavior related to the target object. Model processing is performed on the sample feature using a prediction model with a first branch and first probability and a second branch and second probability. A first loss is determined based on a first label value and the first probability. When a predetermined condition is satisfied, the second loss is determined based on a second label value of the second label and the second probability, and a predicted loss of the target sample is determined based on the first loss and the second loss. Training the prediction model based on the predicted loss.