Faster RCNN訓練1: faster_rcnn_end2end/solver.prototxt

train_net: "models/pascal_voc/VGG16/faster_rcnn_end2end/train.prototxt"
base_lr: 0.001     # 學習率，begin training at a learning rate of 0.001 = 1e-3，
                   #且在訓練過程中間隔一定的迭代次數減小學習率
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: 50000   # drop the learning rate every 50K iterations
display: 20   # 每迭代20次在屏幕上輸出一次結果
average_loss: 100
# iter_size: 1
momentum: 0.9
weight_decay: 0.0005
# We disable standard caffe solver snapshotting and implement our own snapshot
# function
snapshot: 0
# We still use the snapshot prefix, though
snapshot_prefix: "vgg16_faster_rcnn"
iter_size: 2

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