Why there is Different accuracy for two same trained model?
Somewhere in the code there should be some parameter that is initialised randomly, this is usually called the random seed. It could be the different initialisation of your neural network weights that is affecting the results, or maybe the k-fold being different if done at random.
The extent of the difference between the performance suggests that you might not have enough data to reliably learn a good model, or your model is underspecified and gets stuck at different local minima. Consider, changing the learning rate and other hyperparameters and see if the effect stays.