Okay so many people like tensorboard(x) for plotting loss and accuracy. I prefer visdom as it offers you to plot richer data, but is a bit complex. Look into those!
8 images per class is simply too little. Either get more validation images or possible take some training images out of the training set and put it in the validation set. A normal amount is 80% training and 20% validation (more complicated than that but lets not get into it)
Good that you did the calculations  What do you mean with “thing goes wrong”? Which images that get misclassified? Thats some old school programming ya know. You have to keep track of the image id / paths but don’t worry too much about that for now if that’s difficult. There are a TON of image classification projects out there. Simply google for “image classification deep learning medium” for more info