simple-neural-networks | Simple neural networks based only on Numpy | Machine Learning library

I am trying to learn the correct procedure for training a neural network for classification. Many tutorials are there but they never explain how to report for the generalization performance. Can somebody please tell me if the following is the correct method or not. I am using first 100 examples from the fisheriris data set that has labels 1,2 and call them as X and Y respectively. Then I split X into trainData and Xtest with a 90/10 split ratio. Using trainData I trained the NN model. Now the NN internally further splits trainData into tr,val,test subsets. My confusion is which one is usually used for generalization purpose when reporting the performance of the model to unseen data in conferences/Journals? The dataset can be found in the link: https://www.mathworks.com/matlabcentral/fileexchange/71468-simple-neural-networks-with-k-fold-cross-validation-manner