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program: training/run_sweep.py
method: bayes
metric:
name: val_accuracy
goal: maximize
parameters:
dataset:
value: EmnistDataset
model:
value: CharacterModel
network:
value: ResidualNetwork
network_args.block_sizes:
distribution: q_uniform
min: 16
max: 256
q: 8
network_args.depths:
distribution: int_uniform
min: 1
max: 3
network_args.levels:
distribution: int_uniform
min: 1
max: 2
network_args.activation:
distribution: categorical
values:
- gelu
- leaky_relu
- relu
- selu
optimizer_args.lr:
distribution: uniform
min: 1.e-5
max: 1.e-1
lr_scheduler_args.max_lr:
distribution: uniform
min: 1.e-5
max: 1.e-1
train_args.batch_size:
distribution: q_uniform
min: 32
max: 256
q: 8
train_args.epochs:
value: 5
early_terminate:
type: hyperband
min_iter: 2
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