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- # 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
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