In this iteration I have worked on multiple models of the CNN by first just training it with the basic layer with no global average pooling and no augmentation of data to allow me to see which model is the best for this data set, I got a validation accuracy of around 53.13% however its not really good as I really want it to get as high as 65% as according to the thesis paper research done on the FER2013 dataset for facial expression people have reached up to 72% accuracy with a refined and tuned model

Afterward I tried out Augmented data without global average pooling which got 55% and improved one which uses everything and got 57% which is fair enough

Next step will probably be trying out class weight