mixing of training/validation weights
wheatpennymaster opened this issue · comments
wheatpennymaster commented
The model weights are not re-instantiated before each call of run_model() in the folds loop. Therefore, the model has seen images from fold 0 (i.e. training set of fold 0) which are included in the validation set for fold 1. This results in an increase in validation performance after each fold is trained.
wheatpennymaster commented
Heads up, the training code for sarscovid2, pneuomina, hemorrhage, covid19 are also still bugged. Thanks for correcting the others.