Abstract: An optimization method comprises determining jump ratios of embedding layer parameters of a trained quantization model in a predetermined time range. The quantization model comprises a neural network model obtained after quantization processing on the embedding layer parameters. The method also comprises determining a jump curve in the predetermined time range according to the jump ratios, and fitting the jump curve to obtain a corresponding time scaling parameter. The method also comprises optimizing an initial algorithm of the quantization model based on the time scaling parameter to obtain an optimized target optimization algorithm, and training the quantization model based on the target optimization algorithm.