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As it is marked here, an overfitting is achieved when your prediction is getting worse. So testing on the same unknown data (it should be big enough for detecting the case), if your prediction is less good as the prediction of the model trained on less data, then there is an overfitting. Tell me mode about the number of images you use (test and train)
