coat_tiny_ascend.yaml

# system
mode: 0
distribute: True
num_parallel_workers: 8
val_while_train: True
val_interval: 1

# dataset
dataset: 'imagenet'
data_dir: '/path/to/imagenet'
shuffle: True
dataset_download: False
batch_size: 32
drop_remainder: True

# augmentation
image_resize: 224
scale: [0.08, 1.0]
ratio: [0.75, 1.333]
hflip: 0.5
interpolation: 'bicubic'
auto_augment: 'randaug-m7-mstd0.5-inc1'
re_prob: 0.1
mixup: 0.2
cutmix: 1.0
cutmix_prob: 1.0
crop_pct: 0.9
color_jitter: 0.4

# model
model: 'coat_tiny'
drop_rate: 0.0
drop_path_rate: 0.0
num_classes: 1000
pretrained: False
ckpt_path: ''
keep_checkpoint_max: 10
ckpt_save_policy: 'top_k'
ckpt_save_dir: './ckpt/'
dataset_sink_mode: True
amp_level: 'O2'
ema: True
ema_decay: 0.9995

# loss
loss: 'CE'
label_smoothing: 0.1

# lr scheduler
scheduler: 'cosine_decay'
lr: 0.00025
min_lr: 0.000001
warmup_epochs: 20
decay_epochs: 280
epoch_size: 300

# optimizer
opt: 'lion'
weight_decay: 0.15
filter_bias_and_bn: True
loss_scale: 4096
use_nesterov: False
loss_scale_type: dynamic
drop_overflow_update: True