########## Model ##########

# Using cuda or cpu for training
device: cuda

# If train with arcface loss, options: 'True', 'False'
cos_layer: false

# If train with multi-gpu ddp mode, options: 'True', 'False'
dist_train: false

# Transformer settings
drop_path: 0.1
drop_out: 0.0
att_drop_rate: 0.0

# SIE parameters
sie_coe: 3.0


########## Solver ##########

optimizer_name: Adam

max_epochs: 100

# Base learning rate
base_lr: 3e-4

# Whether using larger learning rate for fc layer
large_fc_lr: false

# Factor of learning bias
bias_lr_factor: 1

momentum: 0.9

# Settings of weight decay
weight_decay: 0.0005
weight_decay_bias: 0.0005

# Warm up epochs
warmup_epochs: 5

# Epoch number of saving checkpoints
checkpoint_period: 10

# Iteration of display training log
log_period: 100

########## Test ##########

# Whether feature is normalized before test, if yes, it is equivalent to cosine distance
feat_norm: yes