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train_configs.yaml
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cifar-10:
conv-default:
epochs: 200
batch_size: 128
scheduler: 'cosine'
optim: 'sgd'
lr: 0.1
weight_decay: 5.0e-4
is_nesterov: False
steps: ~
gamma: ~
rand_aug_m: ~
rand_aug_n: ~
label_smoothing: ~
closed:
epochs: 600
batch_size: 128
scheduler: 'cosine_warm_restarts_warmup'
optim: 'sgd'
lr: 0.1
weight_decay: 1.0e-4
is_nesterov: False
steps: ~
gamma: ~
rand_aug_m: 6
rand_aug_n: 1
label_smoothing: ~
oe-default:
epochs: 100
batch_size: 128
scheduler: 'oe_opt'
optim: 'sgd'
lr: 0.1
weight_decay: 5.0e-4
is_nesterov: True
steps: ~
gamma: ~
rand_aug_m: ~
rand_aug_n: ~
label_smoothing: ~
cifar-100:
conv-default:
epochs: 200
batch_size: 128
scheduler: 'multi_step'
optim: 'sgd'
lr: 0.1
weight_decay: 5.0e-4
is_nesterov: True
steps: [60, 120, 160]
gamma: 0.2
rand_aug_m: ~
rand_aug_n: ~
label_smoothing: ~
conv-cifar10-default:
epochs: 200
batch_size: 128
scheduler: 'cosine'
optim: 'sgd'
lr: 0.1
weight_decay: 5.0e-4
is_nesterov: False
steps: ~
gamma: ~
rand_aug_m: ~
rand_aug_n: ~
label_smoothing: ~
closed:
epochs: 600
batch_size: 128
scheduler: 'cosine_warm_restarts_warmup'
optim: 'sgd'
lr: 0.1
weight_decay: 1.0e-4
is_nesterov: False
steps: ~
gamma: ~
rand_aug_m: 6
rand_aug_n: 1
label_smoothing: ~
oe-default:
epochs: 100
batch_size: 128
scheduler: 'oe_opt'
optim: 'sgd'
lr: 0.1
weight_decay: 5.0e-4
is_nesterov: True
steps: ~
gamma: ~
rand_aug_m: ~
rand_aug_n: ~
label_smoothing: ~
tinyimagenet:
closed:
epochs: 600
batch_size: 128
scheduler: 'cosine_warm_restarts_warmup'
optim: 'adam'
lr: 0.001
weight_decay: ~
is_nesterov: ~
steps: ~
gamma: ~
rand_aug_m: 9
rand_aug_n: 1
label_smoothing: 0.9