cls_mv3.yml

Global:
  algorithm: CLS
  use_gpu: false
  epoch_num: 30
  log_smooth_window: 20
  print_batch_step: 10
  save_model_dir: output/cls_mb3
  save_epoch_step: 3
  eval_batch_step: 100
  train_batch_size_per_card: 256
  test_batch_size_per_card: 256
  image_shape: [3, 32, 100]
  label_list: [0,180]
  reader_yml: ./configs/cls/cls_reader.yml
  pretrain_weights:
  checkpoints: /Users/zhoujun20/Desktop/code/class_model/cls_mb3_ultra_small_0.35/best_accuracy
  save_inference_dir:
  infer_img: /Users/zhoujun20/Desktop/code/PaddleOCR/doc/imgs_words/ch/word_1.jpg
  
Architecture:
  function: ppocr.modeling.architectures.cls_model,ClsModel

Backbone:
  function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3
  scale: 0.35
  model_name: Ultra_small
 
Head:
  function: ppocr.modeling.heads.cls_head,ClsHead
  class_dim: 2

Loss:
  function: ppocr.modeling.losses.cls_loss,ClsLoss

Optimizer:
  function: ppocr.optimizer,AdamDecay
  base_lr: 0.001
  beta1: 0.9
  beta2: 0.999
  decay:
    function: piecewise_decay
    boundaries: [20,30]
    decay_rate: 0.1