Retrain your CNN model successifely with two different datasets
It is quite possible if you have not provided the seed number set.seed( ) in the R language or tf.random.set_seed(any_no.) in python
I had implemented a CNN with 3 Convolutional layers with Maxpooling and dropout after each layer
I had noticed that when I trained the model for the first time it gave me 88% as testing accuracy but after retraining it for the second time successively, with the same training dataset it gave me 92% as testing accuracy.
I could not understand this behavior, is it possible that the model had overfitting in the second training process?
Thank you in advance for any help!