The invention provides a
mask feature progressive knowledge
distillation completion method for a user portrait of a
nasopharyngeal carcinoma patient, and relates to the technical field of image
data processing, and the method comprises the following steps: a pre-
distillation stage: carrying out the pre-
distillation of a pre-training
language model, so as to obtain a high-quality teacher model, generating feature distillation through a
mask, and carrying out the feature distillation; applying a
mask operation in the input data, and setting a mask proportion according to the number of student
model parameters; and S2, mask generation feature distillation: the teacher model and the student model perform mask operation on input data including the triad and text description thereof in a
data input stage. In the masking generation characteristic distillation, masking operation is applied to input marks, and a proper masking rate is set in a pre-distillation stage according to student
model parameter counting, so that the performance of an initial model is improved. In the progressive distillation stage, a multi-grade student model is designed, and the parameter count and the mask rate are gradually reduced. Each student model is trained under the three kinds of supervision described above.