Does adding of many FC layers during re-training increase the model size ? Are there any ways to optimize the size of model?
You can change the type of your weight, you will loose precision but reduce the size of the weights. You can also do some regularisation during training to learn sparse weight matrix

You can read these two articles : 


Deep compression optimisation techniques for inference
Model quantisation for production level nn inference