r/deeplearning - 100% accuracy on test set, much lower on the training set

I am currently having a problem with my thesis project and I would like to ask you for help: I basically need to examine a dataset made of images of cells through a siamese network and evaluate their similarity through a contrastive loss. I have managed to run the code, but the weird thing is that I obtain like 61% of accuracy on the training set (I have to improve it) and 100% of accuracy on the test set after 3 epochs and I have no idea why. About my syste, I have divided the data in 80/20, my dataset is made of more or less 115000 images and for my network I have used a margin of 0.2.