PaddleClas/configs/quick_start/ResNet50_vd.yaml

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YAML

mode: 'train'
ARCHITECTURE:
name: 'ResNet50_vd'
pretrained_model: ""
model_save_dir: "./output/"
classes_num: 102
total_images: 1020
save_interval: 1
validate: True
valid_interval: 1
epochs: 20
topk: 5
image_shape: [3, 224, 224]
LEARNING_RATE:
function: 'Cosine'
params:
lr: 0.0125
OPTIMIZER:
function: 'Momentum'
params:
momentum: 0.9
regularizer:
function: 'L2'
factor: 0.00001
TRAIN:
batch_size: 32
num_workers: 4
file_list: "./dataset/flowers102/train_list.txt"
data_dir: "./dataset/flowers102/"
shuffle_seed: 0
transforms:
- DecodeImage:
to_rgb: True
to_np: False
channel_first: False
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 1./255.
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
- ToCHWImage:
VALID:
batch_size: 20
num_workers: 4
file_list: "./dataset/flowers102/val_list.txt"
data_dir: "./dataset/flowers102/"
shuffle_seed: 0
transforms:
- DecodeImage:
to_rgb: True
to_np: False
channel_first: False
- ResizeImage:
resize_short: 256
- CropImage:
size: 224
- NormalizeImage:
scale: 1.0/255.0
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
- ToCHWImage: