I am trying to classify my dataset into two categories using transfer learning with vgg and finetuning the very last layer (fully-connected). When I plot the graph of value vs epochs, I get the following graph:
Each graph shows a unique, different learning rate. It seems like the validation accuracy / loss always plateaus regardless of which learning rate I set; is this the sign of overfitting? What could potentially be the cause of this?