# Change rate of cross validation data, after training

Say we have N of labeled data, and we need to take some part for the cross validation (we will skip test part for this case). We chose, 0.6 part for the training and 0.4 for validation.

After training neural Network with early stop, we have found 8 epochs, as optimal to stop, and have received good enough results.

Q. In case, we have very limited N training samples. May we use all samples in new model training, and just stop it's training after discovered epochs? Without separating it to train and cross validation, and testing it, at all (or even, change rate of separating, to 0.9 train, 0.1 cross validation).

Maybe there is known technologies for such cases? Thanks.