paddleocr项目训练检测模型训练不动

[yingying0601]

配置文件如下：
Global:
debug: false
use_gpu: false
epoch_num: 50
log_smooth_window: 20
print_batch_step: 1
save_model_dir: ./output/rec_ppocr_v3
save_epoch_step: 15
eval_batch_step: [0, 2000]
cal_metric_during_train: true
pretrained_model: ./pretrain_models/ch_PP-OCRv4_rec_train/student.pdparams # 识别训练模型路径
checkpoints:
save_inference_dir:
use_visualdl: false
infer_img: doc/imgs_words/ch/word_1.jpg
character_dict_path: ppocr/utils/ppocr_keys_v1.txt
max_text_length: &max_text_length 25
infer_mode: false
use_space_char: true
distributed: true
save_res_path: ./output/rec/predicts_ppocrv4.txt

Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
name: Cosine
learning_rate: 0.001
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: *max_text_length

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: ./train_data/
ext_op_transform_idx: 1
label_file_list:
- ./train_data/train.txt # 识别训练数据集标签路径
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- RecConAug:
prob: 0.5
ext_data_num: 2
image_shape: [48, 320, 3]
max_text_length: *max_text_length
- RecAug:
- MultiLabelEncode:
- RecResizeImg:
image_shape: [3, 48, 320]
- KeepKeys:
keep_keys:
- image
- label_ctc
- label_sar
- length
- valid_ratio
loader:
shuffle: true
batch_size_per_card: 2
drop_last: true
num_workers: 2
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/
label_file_list:
- ./train_data/test.txt # 识别数据集中的评估标签路径
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- MultiLabelEncode:
- RecResizeImg:
image_shape: [3, 48, 320]
- KeepKeys:
keep_keys:
- image
- label_ctc
- label_sar
- length
- valid_ratio
loader:
shuffle: false
drop_last: false
batch_size_per_card: 1
num_workers: 1
结果[2025/05/15 13:03:59] ppocr INFO: load pretrain successful from ./pretrain_models/ch_PP-OCRv4_rec_train/student
[2025/05/15 13:03:59] ppocr INFO: During the training process, after the 0th iteration, an evaluation is run every 2000 iterations一直不动，求大佬解答

[cuicheng01]

一直不动的意思是？