This is the situation. I'm training a model to recognize letters of the Alphabet. There are 26 classes. When writing the code for 26 classes, and loading nearly 100,000 images to train, I'm having a lot of issues. However, I was able to successfully train the model to work on 10 letter increments. As in, A-J, K-T, and then U-Z. These three work perfectly fine (A-Z does not).
Question: Can I train my A-J model, save the H5. Then, train the K-T, and U-Z after and then MERGE the H5 files together? I understand it's possible to train all A-Z using fewer images and then retrain the model with a different image set, but the issues are coming when I'm doing a 26 class system - hence I'm asking if I can do it in increments of 10 and merge it after.