# Solver for SqueezeNet Model
test_iter: 1000
test_interval: 1000
base_lr: 0.03
display: 1
max_iter: 1500000
lr_policy: "step"
gamma: 0.5
stepsize: 100000
momentum: 0.9
weight_decay: 0.0002
snapshot: 1000
snapshot_prefix: "snapshot"
solver_mode: GPU
net: "SqueezeNet_train_test.prototxt"
random_seed: 42
average_loss: 80