使用en_PP-OCRv3_rec版本，训练Rec模型，每一轮次的准确率acc都为0，配置文件如下

[jasonlamsz]

使用en_PP-OCRv3_rec版本，训练Rec模型，每一轮次的准确率acc都为0，配置文件如下，请大神指导一下。

Global:
  debug: false
  use_gpu: true
  epoch_num: 500
  log_smooth_window: 20
  print_batch_step: 10
  save_model_dir: ./user/train_models/en_PP-OCRv3_rec_train/checkpoints
  save_epoch_step: 10
  eval_batch_step: [0, 10]
  cal_metric_during_train: true
  pretrained_model: ./user/pretrain_models/en_PP-OCRv3_rec_train/best_accuracy.pdparams
  checkpoints:
  save_inference_dir:
  use_visualdl: false
  infer_img: doc/imgs_words/ch/word_1.jpg
  character_dict_path: ppocr/utils/en_dict.txt
  max_text_length: 44
  infer_mode: false
  use_space_char: false
  distributed: true
  save_res_path: ./user/train_models/en_PP-OCRv3_rec_train/checkpoints/det_db/predicts_db.txt


Optimizer:
  name: Adam
  beta1: 0.9
  beta2: 0.999
  lr:
    name: Cosine
    learning_rate: 0.00000125
    warmup_epoch: 5
  regularizer:
    name: L2
    factor: 3.0e-05


Architecture:
  model_type: rec
  algorithm: SVTR_LCNet
  Transform:
  Backbone:
    name: MobileNetV1Enhance
    scale: 0.5
    last_conv_stride: [1, 2]
    last_pool_type: avg
    last_pool_kernel_size: [2, 2]
  Head:
    name: MultiHead
    head_list:
      - CTCHead:
          Neck:
            name: svtr
            dims: 64
            depth: 2
            hidden_dims: 120
            use_guide: True
          Head:
            fc_decay: 0.00001
      - SARHead:
          enc_dim: 512
          max_text_length: 44

Loss:
  name: MultiLoss
  loss_config_list:
    - CTCLoss:
    - SARLoss:

PostProcess:  
  name: CTCLabelDecode

Metric:
  name: RecMetric
  main_indicator: acc
  ignore_space: False

Train:
  dataset:
    name: SimpleDataSet
    data_dir: ./user/train_data/OCR_Rec_Train_Data_20240624a/train/
    ext_op_transform_idx: 1
    label_file_list:
    - ./user/train_data/OCR_Rec_Train_Data_20240624a/train/Label.txt
    transforms:
    - DecodeImage:
        img_mode: BGR
        channel_first: false
    - RecConAug:
        prob: 0.5
        ext_data_num: 2
        image_shape: [48, 960, 3]
        max_text_length: 44
    - RecAug:
    - MultiLabelEncode:
    - RecResizeImg:
        image_shape: [3, 48, 960]
    - KeepKeys:
        keep_keys:
        - image
        - label_ctc
        - label_sar
        - length
        - valid_ratio
  loader:
    shuffle: true
    batch_size_per_card: 8
    drop_last: true
    num_workers: 4
Eval:
  dataset:
    name: SimpleDataSet
    data_dir: ./user/train_data/OCR_Rec_Train_Data_20240624a/eval/
    label_file_list:
    - ./user/train_data/OCR_Rec_Train_Data_20240624a/eval/Label.txt
    transforms:
    - DecodeImage:
        img_mode: BGR
        channel_first: false
    - MultiLabelEncode:
    - RecResizeImg:
        image_shape: [3, 48, 960]
    - KeepKeys:
        keep_keys:
        - image
        - label_ctc
        - label_sar
        - length
        - valid_ratio
  loader:
    shuffle: false
    drop_last: false
    batch_size_per_card: 8
    num_workers: 4

[GreatV]

多训几轮看看

[jasonlamsz]

不管训练轮次多久，acc都是0

[GreatV]

多几个 epoch 再看看，增加数据量，检查数据标注是否有问题

[jasonlamsz]

都检查过了，训练数据集大概500张，数据标注都是正确的，郁闷

[GreatV]

一般得等norm_edit_dis 零点几的时候 acc才会增长