debug: False
apex: False
print_freq: 100
num_workers: 8
model_name: 'seresnext26d_32x4d' #['seresnext26d_32x4d', 'seresnext26t_32x4d', 'seresnext26tn_32x4d', 
# 'seresnext50_32x4d', 'seresnext101_32x4d', 'seresnext101_32x8d']
size: 512
scheduler: 'CosineAnnealingWarmRestarts' # ['ReduceLROnPlateau', 'CosineAnnealingLR', 'CosineAnnealingWarmRestarts']
criterion: 'TaylorCrossEntropyLoss' # ['CrossEntropyLoss', LabelSmoothing', 'FocalLoss' 'FocalCosineLoss', 
# 'SymmetricCrossEntropyLoss', 'BiTemperedLoss', 'TaylorCrossEntropyLoss']
epochs: 15
factor: 0.2 # ReduceLROnPlateau
patience: 4 # ReduceLROnPlateau
eps: 1e-6 # ReduceLROnPlateau
T_max: 10 # CosineAnnealingLR
T_0: 10 # CosineAnnealingWarmRestarts
lr: 0.0001
min_lr: 0.000001
batch_size: 4
weight_decay: 0.000001
gradient_accumulation_steps: 1
max_grad_norm: 1000
seed: 123
target_size: 2 #NUMBER OF OUTPUT
target_col: 'label'
n_fold: 5
trn_fold: [0, 1, 2, 3, 4]
train: True
inference: False
smoothing: 0.05
t1: 0.3 
t2: 1.0 
##TTA
tta: 5