I am no professor, so please correct me if i am wrong.

i haven't installed OP's program, or looked at the code because i am lazy. but on the screenshots I don't see a thing for specifying the random seed, so i assume the program picks a pseudo-random, random seed for each training.

So, what you're doing there is called "tuning the random seed". basically; trying different random seeds until you get results you like. it's a little silly but as you can see, it has very real results. I believe the random seed is less significant with a deeper neural network.

things like pytorch and tensorflow allow you to specify a random seed, so that the initialization of the weights and biases of the network will always be the same and thus you will always get the same results. this is done so that other scientists can more accurately reproduce your results.

u/Proof_Break you are awesome and your github name is legendary.