swinv2-base-w24_in21k-pre_16xb64_in1k-384px.py

_base_ = [
    '../_base_/models/swin_transformer_v2/base_384.py',
    '../_base_/datasets/imagenet_bs64_swin_384.py',
    '../_base_/schedules/imagenet_bs1024_adamw_swin.py',
    '../_base_/default_runtime.py'
]

model = dict(
    type='ImageClassifier',
    backbone=dict(
        img_size=384,
        window_size=[24, 24, 24, 12],
        drop_path_rate=0.2,
        pretrained_window_sizes=[12, 12, 12, 6]))