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# Model settings
model = dict(
type='ImageClassifier',
backbone=dict(
type='ConvNeXt',
arch='base',
out_indices=(3, ),
drop_path_rate=0.5,
gap_before_final_norm=True,
init_cfg=[
dict(
type='TruncNormal',
layer=['Conv2d', 'Linear'],
std=.02,
bias=0.),
dict(type='Constant', layer=['LayerNorm'], val=1., bias=0.),
]),
head=dict(
type='LinearClsHead',
num_classes=1000,
in_channels=1024,
loss=dict(
type='LabelSmoothLoss', label_smooth_val=0.1, mode='original'),
),
train_cfg=dict(augments=[
dict(type='Mixup', alpha=0.8),
dict(type='CutMix', alpha=1.0),
]),
)
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