net: "TestNetTrain.proto"
type: "SGD"
base_lr: 1e-3    # begin training at a learning rate of 0.01 = 1e-2

lr_policy: "step" # learning rate policy: drop the learning rate in "steps"
                  # by a factor of gamma every stepsize iterations

gamma: 0.1        # drop the learning rate by a factor of 10
                  # (i.e., multiply it by a factor of gamma = 0.1)

stepsize: 10000  # drop the learning rate every 100K iterations

max_iter: 35000  # train for 350K iterations total

momentum: 0.9
display: 100
weight_decay: 1e-5
snapshot: 2500
snapshot_prefix: "F:/caffe_snapshots/imagenet_5_gen_fntng"
solver_mode: GPU