604.yaml

AUTO_RESUME: False
DATA_DIR: './data/imagenet'
MODEL: '604m_retrain'
RESUME_PATH: './experiments/workspace/retrain/resume.pth.tar'
SAVE_PATH: './experiments/workspace/retrain'
SEED: 42
LOG_INTERVAL: 50
RECOVERY_INTERVAL: 0
WORKERS: 8
NUM_GPU: 8
SAVE_IMAGES: False
AMP: False
OUTPUT: 'None'
EVAL_METRICS: 'prec1'
TTA: 0
LOCAL_RANK: 0

DATASET:
  NUM_CLASSES: 1000
  IMAGE_SIZE: 224 # image patch size
  INTERPOLATION: 'random' # Image resize interpolation type
  BATCH_SIZE: 128 # batch size
  NO_PREFECHTER: False

NET:
  GP: 'avg'
  DROPOUT_RATE: 0.2
  SELECTION: 604

  EMA:
    USE: True
    FORCE_CPU: False # force model ema to be tracked on CPU
    DECAY: 0.9999


LR: 0.064
EPOCHS: 500
OPT_EPS: 1e-3
SCHED: 'cosine'
OPT: 'rmsproptf'
WARMUP_LR: 1e-6
DECAY_EPOCHS: 2.4
DECAY_RATE: 0.973
WARMUP_EPOCHS: 3
WEIGHT_DECAY: 1e-5

AUGMENTATION:
  AA: 'rand-m9-mstd0.5'
  RE_PROB: 0.2  # random erase prob
  RE_MODE: 'pixel'  # random erase mode