RevCol / training /configs /revcol_base_1k_224_finetune.yaml
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PRINT_FREQ: 100
SAVE_FREQ: 1
MODEL_EMA: False
DATA:
IMG_SIZE: 224
DATASET: imagenet
MODEL:
TYPE: revcol_base
NAME: revcol_base_1k_Finetune_224
LABEL_SMOOTHING: 0.1
NUM_CLASSES: 1000
REVCOL:
INTER_SUPV: False
SAVEMM: True
FCOE: 3.0
CCOE: 0.7
DROP_PATH: 0.2
HEAD_INIT_SCALE: 0.001
TRAIN:
EPOCHS: 30
BASE_LR: 1e-4
WARMUP_EPOCHS: 0
WEIGHT_DECAY: 1e-8
WARMUP_LR: 4e-6
MIN_LR: 2e-7
OPTIMIZER:
NAME: 'adamw'
LAYER_DECAY: 0.9
AUG:
COLOR_JITTER: 0.0
# Use AutoAugment policy. "v0" or "original"
AUTO_AUGMENT: 'rand-m9-mstd0.5-inc1'
# Random erase prob
REPROB: 0.25
# Random erase mode
REMODE: 'pixel'
# Random erase count
RECOUNT: 1
# Mixup alpha, mixup enabled if > 0
MIXUP: 0.0
# Cutmix alpha, cutmix enabled if > 0
CUTMIX: 0.0
# Cutmix min/max ratio, overrides alpha and enables cutmix if set
CUTMIX_MINMAX: None
# Probability of performing mixup or cutmix when either/both is enabled
MIXUP_PROB: 0.0
# Probability of switching to cutmix when both mixup and cutmix enabled
MIXUP_SWITCH_PROB: 0.0
# How to apply mixup/cutmix params. Per "batch", "pair", or "elem"
MIXUP_MODE: 'batch'