@KFrank
Thanks for your input! I do agree that accuracy data does look fishy, I am only a novice at deep learning and machine learning overall so I don’t have any ideas on how to check if the model is training correctly. The way my code is written, it checks the validation set every training batch, whereas the training set’s metrics are measured for every batch, thus the training batch’s acc/loss will fluctuate more than the test set’s (bc they are measured over the whole set and averaged, not recorded for each test batch). This only explains the fluctuation in the training set’s loss, and why its not in the testing set’s loss. Any tips?