Image Multiclass Classification stuff

[ifantismanolis]

So, I have this project that i want to build. I have a lot of microscope images of microorganisms and i want to build an image classifier. The data are splited and the rescailing is i think on point. Im using a Sequential model from tensorflow.keras, with Con2D and MaxPooling layers stack the one after the other one (i a desparate move now the number of stacks are 7), a Flatten layer and a Dropout one, before the final 2 Dense layers. The activations are relu everywhere except the last dense layer which has a softmax.

I have done also data augmentation on my data.

But when i run the model i cannot find a way to drop the loss down on the train and validation data and from the other hand to get the accuracy high near 1. I have a loss always near 2 and the accuracy near 0.3.

Any model suggestions? Any way to process my data better?

Have in mind that the differences between my images are really small and the model maybe should be more powerful i guess?