Finetuning Alex-Net for Semantic Segmentation

[seragENTp]

I'm trying to reproduce FCN paper results using Alex-Net (imagenet-matconvnet-alex.mat) which
doesn't contain Local response normalization layer as in Alex-Net (imagene-caffe-ref.mat).
This the results (shown in the pdf attached) i obtained using :
minibatch size = 1 ;
learning rate = 1e-5 ;
after 100 epoch i got meanIU = 25 on validation dataset (1111 images) and it seems that there is some sort of saturation in meanIU value for validation dataset , so what i should do next !

1-train for more epochs ?
2- decrease the learning rate and train from the start ?
3- add local response normalization layer like the paper ?

net-train.pdf