A short-term confidence-based size model parallel cooperative evaluation method

Abstract

This invention discloses a parallel collaborative evaluation method for large and small models based on short-term confidence scores, belonging to the field of federated learning outcome quality evaluation in computing power networks. The method includes the following steps: generating short-term evaluation confidence scores based on the short-term evaluation of the small model; having the large model evaluate the evaluation indicators with low confidence scores in the short-term evaluation confidence scores; and simultaneously, having the small model supplement the remaining content of the short-term evaluation, thus achieving parallel collaborative evaluation of large and small models. This invention, through parallel collaboration between large and small models, can fully utilize the high accuracy of the large model and the low resource consumption of the small model, solving the resource idleness problem of serial collaboration between large and small models and improving the efficiency and accuracy of the evaluation.

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