METHOD, ELECTRONIC DEVICE, AND COMPUTER PROGRAM PRODUCT FOR TRAINING MODEL

Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for training a model. The method includes: acquiring a test set and a training set for training models, the test set and the training set each including workload data associated with normal storage devices and workload data associated with exceptional storage devices; training a device detection model using the training set, the device detection model being used to classify storage devices as normal storage devices or exceptional storage devices according to a threshold degree, with the threshold degree being within a range; determining a test result by applying the test set to the device detection model; and updating the range of the threshold degree if it is determined that the test result indicates that the performance of the device detection model does not reach a threshold performance. With this method, storage devices can be accurately detected by the trained model.