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飞桨常规赛：中文场景文字识别 - 5月第2名方案

该内容主要介绍了PaddleOCR相关操作，包括下载安装PaddleOCR及依赖库，解压训练集和测试集文件，对训练集进行预处理（含数据增强、字符处理、切分数据集等），还说明了模型调优和配置，使用CRNN_CTC模型，修改配置文件，下载预训练模型用于迁移学习。

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飞桨常规赛：中文场景文字识别 - 5月第2名方案 -

一、下载安装PaddleOCR及其依赖库

下载PaddleOCR套件，可通过运行命令 git clone https://gitee.com/paddlepaddle/PaddleOCR.git 的方式，直接克隆整个PaddleOCR的代码库到本地
安装本项目需要各种python包，注意选好合适的链接下载，否则速度很慢。

In [1]

!mkdir /home/aistudio/external-librariesimport sys
sys.path.append('/home/aistudio/external-libraries')

! pip install tqdm imgaug lmdb matplotlib opencv-python Pillow python-Levenshtein PyYAML trdg anyconfig -i https://mirror.baidu.com/pypi/simple

mkdir: cannot create directory ‘/home/aistudio/external-libraries’: File exists
Looking in indexes: https://mirror.baidu.com/pypi/simple
Requirement already satisfied: tqdm in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (4.36.1)
Collecting imgaug
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Collecting lmdb
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Requirement already satisfied: matplotlib in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (2.2.3)
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Requirement already satisfied: Pillow in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (7.1.2)
Collecting python-Levenshtein
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  Preparing metadata (setup.py) ... done
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Collecting trdg
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Collecting anyconfig
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Collecting scikit-image>=0.14.2
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Collecting diffimg==0.2.3
  Downloading https://mirror.baidu.com/pypi/packages/3d/fa/de925a7c2203b52f007ad6b9cce343c21dbe389a221a4f51f25960c83d8b/diffimg-0.2.3.tar.gz (4.1 kB)
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Collecting numpy>=1.15
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Requirement already satisfied: networkx>=2.2 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from scikit-image>=0.14.2->imgaug) (2.4)
Collecting PyW*elets>=1.1.1
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Collecting scikit-image>=0.14.2
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Collecting tifffile>=2019.7.26
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Collecting PyW*elets>=1.1.1
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Building wheels for collected packages: python-Levenshtein, diffimg
  Building wheel for python-Levenshtein (setup.py) ... done
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  Stored in directory: /home/aistudio/.cache/pip/wheels/2c/3e/2a/1bbb6d64b0ec37b336d3739e277f9c0006eaf61c10f2e3e141
  Building wheel for diffimg (setup.py) ... done
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  Stored in directory: /home/aistudio/.cache/pip/wheels/9e/74/a8/86b7dd9ae1d06c4ad6c444c3d215dd44f97f8c2f747d38273e
Successfully built python-Levenshtein diffimg
Installing collected packages: lmdb, Shapely, python-Levenshtein, numpy, diffimg, anyconfig, tifffile, PyW*elets, opencv-python, trdg, scikit-image, imgaug
  Attempting uninstall: numpy
    Found existing installation: numpy 1.20.3
    Uninstalling numpy-1.20.3:
      Successfully uninstalled numpy-1.20.3
  Attempting uninstall: opencv-python
    Found existing installation: opencv-python 4.1.1.26
    Uninstalling opencv-python-4.1.1.26:
      Successfully uninstalled opencv-python-4.1.1.26ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This beh*iour is the source of the following dependency conflicts.
parl 1.4.1 requires pyzmq==18.1.1, but you h*e pyzmq 22.3.0 which is incompatible.Successfully installed PyW*elets-1.1.1 Shapely-1.8.2 anyconfig-0.13.0 diffimg-0.2.3 imgaug-0.4.0 lmdb-1.3.0 numpy-1.16.6 opencv-python-4.6.0.66 python-Levenshtein-0.12.2 scikit-image-0.18.3 tifffile-2025.11.2 trdg-1.7.0WARNING: You are using pip version 22.0.4; however, version 22.1.2 is *ailable.
You should consider upgrading via the '/opt/conda/envs/python35-paddle120-env/bin/python -m pip install --upgrade pip' command.

二、解压训练集和测试集文件

压缩包内含训练集图片，使用了外部的训练集共包含21万图片，以及原始的训练集标注文件train.list，使用tar -zxf train_img.tar.gz将其解压，此时在data/data10879之下会出现train_images文件夹

In [1]

import os
os.chdir('/home/aistudio/data/data10879')
! tar -zxf train_img.tar.gz

为了和现有的测试集区分，将比赛测试集压缩文件夹命名为test_images2.zip，解压测试集压缩文件夹，

In [ ]

!unzip -oq /home/aistudio/test_images2.zip

三、训练集数据预处理

在模型搭建和训练之前，需要做的第一件事就是对数据进行必要的预处理，主要是做了数据增强，对字符列表进行处理能使模型更加快速的收敛，切分训练数据为训练集和验证集，方便模型验证，切分比例为19：1
文件 langconv(language convert)，这个文件用来把繁体字转成简体字
函数 read_ims_list：读取train.list文件，生成图片的信息字典
函数 modify_ch：对标签label进行修改，进行四项操作，分别是“繁体->简体”、“大写->小写”、“删除空格”、“删除符号”。
函数 pipeline：调用定义的函数，对训练数据进行初步处理。
在pipeline函数进行数据集最大长度计算，算出最长的数据集长度；结果如下
label的最大长度为83
字符数量class num: 3827
训练集数量: 200342, 验证集数量: 10544
class num表示文字的数量：生成三个文件dict.txt是字符文件，用于存储所有的中英文字符
train.txt.是训练集图片，200342张，test.txt是测试集图片10544张

In [4]

from work.langconv import Converterimport codecsimport randomimport sysimport osfrom os.path import join as pjoin

os.chdir('/home/aistudio')
sys.path.append('/home/aistudio/work')def read_ims_list(path_ims_list):
    """
    读取 train.list 文件
    """
    ims_info_dic = {}    with open(path_ims_list, 'r', encoding='utf-8') as f:        for line in f:
            parts = line.strip().split(maxsplit=3)
            w, h, file, label = parts[0], parts[1], parts[2], parts[3]
            ims_info_dic[file] = {'label': label, 'w': int(w)}    return ims_info_dic    

def modify_ch(label):
    # 繁体 -> 简体
    label = Converter("zh-hans").convert(label)    # 大写 -> 小写
    label = label.lower()    # 删除空格
    label = label.replace(' ', '')    # 删除符号
    for ch in label:        if (not '\u4e00' <= ch <= '\u9fff') and (not ch.isalnum()):
            label = label.replace(ch, '')    return labeldef s*e_txt(data, file_path):
    """
    将一个list的数组写入txt文件里
    :param data:
    :param file_path:
    :return:
    """
    if not isinstance(data, list):
        data = [data]    with open(file_path, mode='w', encoding='utf8') as f:
        f.write('\n'.join(data))def pipeline(dataset_dir):
    path_ims        = pjoin(dataset_dir, "train_images")
    path_ims_list   = pjoin(dataset_dir, "train.list")
    path_train_list = pjoin('/home/aistudio/work', "train.txt")
    path_test_list  = pjoin('/home/aistudio/work', "test.txt")
    path_label_list = pjoin('/home/aistudio/work', "dict.txt")    # 读取数据信息
    file_info_dic = read_ims_list(path_ims_list)    # 创建 train.txt
    class_set = set()
    data_list = []    #maxlen计算训练集数据的最大长度
    maxlen = 0

    for file, info in file_info_dic.items():
        label = info['label']
        label = modify_ch(label)        # 异常: 标签为空
        if label == '':            continue

        if len(label)>maxlen:
            maxlen=len(label)        for e in label:
            class_set.add(e)
        data_list.append("{0}\t{1}".format(pjoin('/home/aistudio/',path_ims, file), label))    print('label的最大长度为{}'.format(maxlen))    # 创建 label_list.txt
    class_list = list(class_set)
    class_list.sort()    print("class num: {0}".format(len(class_list)))    with codecs.open(path_label_list, "w", encoding='utf-8') as label_list:        for id, c in enumerate(class_list):            # label_list.write("{0}\t{1}\n".format(c, id))
            label_list.write("{0}\n".format(c))    # 随机切分
    random.shuffle(data_list)
    val_len = int(len(data_list) * 0.05)
    val_list = data_list[-val_len:]
    train_list = data_list[:-val_len]    print('训练集数量: {}, 验证集数量: {}'.format(len(train_list),len(val_list)))
    s*e_txt(train_list,path_train_list)
    s*e_txt(val_list,path_test_list)
    
random.seed(0)
pipeline(dataset_dir="data/data10879")

label的最大长度为83
class num: 3827
训练集数量: 200342, 验证集数量: 10544

将/home/aistudio/work/PaddleOCR设置为当前工作的文件夹

In [5]

os.chdir('/home/aistudio/work/PaddleOCR/')
!pwd

/home/aistudio/work/PaddleOCR

四，模型调优和配置说明

本次项目使用的文本识别模型为CRNN_CTC，一个非常经典的文本识别模型，CRNN即CNN+RNN：通过CNN Backbone提取图像的特征，然后通过RNN网络提取图像文本序列的特征，CTC即Connectionist Temporal Classification：是一种常用于序列的损失函数，模型架构图如下：飞桨常规赛：中文场景文字识别 - 5月第2名方案 -

在work/PaddleOCR/configs/rec之下创建rec_this_bilstm_ctc.yml和rec_this_reader.yml两个文件，在基于PaddleOCR提供的配置文件的基础之上做了修改

algorithm: CRNN # 模型名称，PaddleOCR目前包含Rosetta、CRNN、STAR-Net、RARE和SRN五种识别算法
epoch_num: 120
s*e_model_dir: output/this_train
eval_batch_step: 1800
train_batch_size_per_card: 256
test_batch_size_per_card: 128
max_text_length: 84
character_type: ch
character_dict_path: /home/aistudio/work/dict.txt # 字符集文件位置，中文识别时需要，使用上面生成的字符集作为字符集
loss_type: ctc # 损失函数类型，PaddleOCR包含ctc、attn和srn三种损失函数，本文选择CTC作为损失函数
reader_yml: ./configs/rec/rec_this_reader.yml
function: ppocr.modeling.backbones.rec_resnet_vd,ResNet # 骨干网络，PaddleOCR目前包含ResNet和MobileNet两种
layers: 34
function: ppocr.optimizer,AdamDecay #优化器AdamDecay
base_lr: 0.00001
beta1: 0.9
beta2: 0.999

经测试这样能提高精度

下载并解压预训练模型：选择好使用的模型，可以通过迁移学习的方式加快模型训练的收敛速度，即使用训练好的预训练模型作为初始权重，并在此基础上使用新的数据对模型进行微调，要使用预训练模型，就需要先将其下载到本地，你可以在PaddleOCR的gitee主页上找到所有官方提供的预训练模型的下载链接，然后通过 wget -P ./pretrain_models/ 下载链接这个指令即可下载对应的预训练模型了。下载完成之后、解压并在配置文件pretrain_weights处设置对应的路径，即可正常的使用这个预训练模型进行迁移学习了。
下载预训练模型
%cd ~/work/PaddleOCR
!wget -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/ch_models/ch_rec_r34_vd_crnn.tar
解压预训练模型
Openflow
一键极速绘图，赋能行业工作流
88 查看详情
%cd pretrain_models
!tar -xf ch_rec_r34_vd_crnn.tar

五、模型训练

进入work/PaddleOcr文件夹，进行模型训练 ! export PYTHONPATH=$PYTHONPATH:. ! python tools/train.py -c configs/rec/rec_this_bilstm_ctc.yml

In [6]

! export PYTHONPATH=$PYTHONPATH:.
! python tools/train.py -c configs/rec/rec_this_bilstm_ctc.yml

2025-05-30 04:24:15,117-INFO: epoch: 12, iter: 9700, lr: 0.000010, 'loss': 723.173, 'acc': 0.767578, time: 1.503
2025-05-30 04:26:45,589-INFO: epoch: 12, iter: 9800, lr: 0.000010, 'loss': 769.6999, 'acc': 0.765625, time: 1.501
2025-05-30 04:29:16,109-INFO: epoch: 12, iter: 9900, lr: 0.000010, 'loss': 811.43665, 'acc': 0.759766, time: 1.504
2025-05-30 04:31:46,621-INFO: epoch: 12, iter: 10000, lr: 0.000010, 'loss': 787.0708, 'acc': 0.759766, time: 1.504
2025-05-30 04:34:17,087-INFO: epoch: 12, iter: 10100, lr: 0.000010, 'loss': 806.48535, 'acc': 0.746094, time: 1.509
2025-05-30 04:36:34,642-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 04:36:51,164-INFO: epoch: 13, iter: 10200, lr: 0.000010, 'loss': 684.36206, 'acc': 0.78125, time: 1.633
2025-05-30 04:39:29,025-INFO: epoch: 13, iter: 10300, lr: 0.000010, 'loss': 818.61914, 'acc': 0.757812, time: 1.504
2025-05-30 04:41:59,470-INFO: epoch: 13, iter: 10400, lr: 0.000010, 'loss': 818.8104, 'acc': 0.751953, time: 1.510
2025-05-30 04:44:29,968-INFO: epoch: 13, iter: 10500, lr: 0.000010, 'loss': 838.57385, 'acc': 0.757812, time: 1.507
2025-05-30 04:47:00,467-INFO: epoch: 13, iter: 10600, lr: 0.000010, 'loss': 814.1988, 'acc': 0.763672, time: 1.503
2025-05-30 04:49:30,945-INFO: epoch: 13, iter: 10700, lr: 0.000010, 'loss': 760.9939, 'acc': 0.765625, time: 1.507
2025-05-30 04:52:01,476-INFO: epoch: 13, iter: 10800, lr: 0.000010, 'loss': 928.49084, 'acc': 0.75, time: 1.503
2025-05-30 04:52:44,260-INFO: Test iter: 10800, acc:0.747060, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 04:55:14,458-INFO: epoch: 13, iter: 10900, lr: 0.000010, 'loss': 779.18713, 'acc': 0.767578, time: 1.504
2025-05-30 04:57:07,950-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 04:57:50,128-INFO: epoch: 14, iter: 11000, lr: 0.000010, 'loss': 856.6353, 'acc': 0.755859, time: 1.600
2025-05-30 05:00:26,479-INFO: epoch: 14, iter: 11100, lr: 0.000010, 'loss': 816.2085, 'acc': 0.755859, time: 1.502
2025-05-30 05:02:57,012-INFO: epoch: 14, iter: 11200, lr: 0.000010, 'loss': 886.43225, 'acc': 0.753906, time: 1.509
2025-05-30 05:05:27,536-INFO: epoch: 14, iter: 11300, lr: 0.000010, 'loss': 874.2769, 'acc': 0.761719, time: 1.508
2025-05-30 05:07:57,995-INFO: epoch: 14, iter: 11400, lr: 0.000010, 'loss': 874.1431, 'acc': 0.753906, time: 1.507
2025-05-30 05:10:28,520-INFO: epoch: 14, iter: 11500, lr: 0.000010, 'loss': 758.8789, 'acc': 0.751953, time: 1.502
2025-05-30 05:12:58,986-INFO: epoch: 14, iter: 11600, lr: 0.000010, 'loss': 852.7044, 'acc': 0.753906, time: 1.503
2025-05-30 05:15:29,452-INFO: epoch: 14, iter: 11700, lr: 0.000010, 'loss': 773.8209, 'acc': 0.763672, time: 1.504
2025-05-30 05:16:59,375-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 05:18:07,228-INFO: epoch: 15, iter: 11800, lr: 0.000010, 'loss': 841.5386, 'acc': 0.746094, time: 1.600
2025-05-30 05:20:42,068-INFO: epoch: 15, iter: 11900, lr: 0.000010, 'loss': 799.64795, 'acc': 0.765625, time: 1.505
2025-05-30 05:23:12,559-INFO: epoch: 15, iter: 12000, lr: 0.000010, 'loss': 875.5138, 'acc': 0.740234, time: 1.504
2025-05-30 05:25:43,072-INFO: epoch: 15, iter: 12100, lr: 0.000010, 'loss': 789.30273, 'acc': 0.759766, time: 1.503
2025-05-30 05:28:13,534-INFO: epoch: 15, iter: 12200, lr: 0.000010, 'loss': 769.7068, 'acc': 0.753906, time: 1.502
2025-05-30 05:30:44,029-INFO: epoch: 15, iter: 12300, lr: 0.000010, 'loss': 746.8828, 'acc': 0.755859, time: 1.507
2025-05-30 05:33:14,533-INFO: epoch: 15, iter: 12400, lr: 0.000010, 'loss': 782.2943, 'acc': 0.761719, time: 1.504
2025-05-30 05:35:45,055-INFO: epoch: 15, iter: 12500, lr: 0.000010, 'loss': 841.0609, 'acc': 0.748047, time: 1.504
2025-05-30 05:36:50,391-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 05:38:23,828-INFO: epoch: 16, iter: 12600, lr: 0.000010, 'loss': 869.9346, 'acc': 0.765625, time: 1.600
2025-05-30 05:39:26,626-INFO: Test iter: 12600, acc:0.748008, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 05:41:56,617-INFO: epoch: 16, iter: 12700, lr: 0.000010, 'loss': 754.7243, 'acc': 0.753906, time: 1.507
2025-05-30 05:44:27,079-INFO: epoch: 16, iter: 12800, lr: 0.000010, 'loss': 872.2932, 'acc': 0.753906, time: 1.505
2025-05-30 05:46:57,576-INFO: epoch: 16, iter: 12900, lr: 0.000010, 'loss': 853.4508, 'acc': 0.757812, time: 1.508
2025-05-30 05:49:28,014-INFO: epoch: 16, iter: 13000, lr: 0.000010, 'loss': 765.9165, 'acc': 0.761719, time: 1.504
2025-05-30 05:51:58,497-INFO: epoch: 16, iter: 13100, lr: 0.000010, 'loss': 722.2091, 'acc': 0.759766, time: 1.508
2025-05-30 05:54:28,941-INFO: epoch: 16, iter: 13200, lr: 0.000010, 'loss': 850.30365, 'acc': 0.75, time: 1.504
2025-05-30 05:56:59,339-INFO: epoch: 16, iter: 13300, lr: 0.000010, 'loss': 933.8229, 'acc': 0.753906, time: 1.509
2025-05-30 05:57:40,518-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 05:59:39,628-INFO: epoch: 17, iter: 13400, lr: 0.000010, 'loss': 768.1283, 'acc': 0.753906, time: 1.600
2025-05-30 06:02:11,312-INFO: epoch: 17, iter: 13500, lr: 0.000010, 'loss': 802.87427, 'acc': 0.753906, time: 1.505
2025-05-30 06:04:41,815-INFO: epoch: 17, iter: 13600, lr: 0.000010, 'loss': 809.30457, 'acc': 0.761719, time: 1.506
2025-05-30 06:07:12,335-INFO: epoch: 17, iter: 13700, lr: 0.000010, 'loss': 771.8013, 'acc': 0.769531, time: 1.505
2025-05-30 06:09:42,818-INFO: epoch: 17, iter: 13800, lr: 0.000010, 'loss': 824.9247, 'acc': 0.759766, time: 1.503
2025-05-30 06:12:13,261-INFO: epoch: 17, iter: 13900, lr: 0.000010, 'loss': 771.58746, 'acc': 0.75, time: 1.505
2025-05-30 06:14:43,776-INFO: epoch: 17, iter: 14000, lr: 0.000010, 'loss': 793.6093, 'acc': 0.763672, time: 1.505
2025-05-30 06:17:14,297-INFO: epoch: 17, iter: 14100, lr: 0.000010, 'loss': 824.89404, 'acc': 0.75, time: 1.507
2025-05-30 06:17:31,564-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 06:19:56,078-INFO: epoch: 18, iter: 14200, lr: 0.000010, 'loss': 782.80444, 'acc': 0.763672, time: 1.501
2025-05-30 06:22:26,557-INFO: epoch: 18, iter: 14300, lr: 0.000010, 'loss': 803.5506, 'acc': 0.757812, time: 1.504
2025-05-30 06:24:57,050-INFO: epoch: 18, iter: 14400, lr: 0.000010, 'loss': 774.2059, 'acc': 0.765625, time: 1.506
2025-05-30 06:25:39,794-INFO: Test iter: 14400, acc:0.748767, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 06:28:10,036-INFO: epoch: 18, iter: 14500, lr: 0.000010, 'loss': 876.0082, 'acc': 0.75, time: 1.507
2025-05-30 06:30:40,532-INFO: epoch: 18, iter: 14600, lr: 0.000010, 'loss': 690.56006, 'acc': 0.761719, time: 1.501
2025-05-30 06:33:10,981-INFO: epoch: 18, iter: 14700, lr: 0.000010, 'loss': 791.61414, 'acc': 0.771484, time: 1.507
2025-05-30 06:35:41,575-INFO: epoch: 18, iter: 14800, lr: 0.000010, 'loss': 765.9193, 'acc': 0.755859, time: 1.504
2025-05-30 06:38:05,205-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 06:38:15,228-INFO: epoch: 19, iter: 14900, lr: 0.000010, 'loss': 739.0075, 'acc': 0.753555, time: 1.600
2025-05-30 06:40:53,367-INFO: epoch: 19, iter: 15000, lr: 0.000010, 'loss': 837.3982, 'acc': 0.751953, time: 1.507
2025-05-30 06:43:23,783-INFO: epoch: 19, iter: 15100, lr: 0.000010, 'loss': 783.0751, 'acc': 0.757812, time: 1.503
2025-05-30 06:45:54,274-INFO: epoch: 19, iter: 15200, lr: 0.000010, 'loss': 848.4093, 'acc': 0.757812, time: 1.502
2025-05-30 06:48:24,738-INFO: epoch: 19, iter: 15300, lr: 0.000010, 'loss': 887.7626, 'acc': 0.748047, time: 1.504
2025-05-30 06:50:55,221-INFO: epoch: 19, iter: 15400, lr: 0.000010, 'loss': 881.8578, 'acc': 0.765625, time: 1.503
2025-05-30 06:53:25,632-INFO: epoch: 19, iter: 15500, lr: 0.000010, 'loss': 824.89105, 'acc': 0.761719, time: 1.502
2025-05-30 06:55:56,047-INFO: epoch: 19, iter: 15600, lr: 0.000010, 'loss': 823.55524, 'acc': 0.75, time: 1.503
2025-05-30 06:57:55,671-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 06:58:31,328-INFO: epoch: 20, iter: 15700, lr: 0.000010, 'loss': 837.07825, 'acc': 0.744141, time: 1.600
2025-05-30 07:01:07,976-INFO: epoch: 20, iter: 15800, lr: 0.000010, 'loss': 756.35474, 'acc': 0.759766, time: 1.501
2025-05-30 07:03:38,474-INFO: epoch: 20, iter: 15900, lr: 0.000010, 'loss': 822.7643, 'acc': 0.759766, time: 1.505
2025-05-30 07:06:08,965-INFO: epoch: 20, iter: 16000, lr: 0.000010, 'loss': 764.1765, 'acc': 0.757812, time: 1.504
2025-05-30 07:08:39,418-INFO: epoch: 20, iter: 16100, lr: 0.000010, 'loss': 787.92236, 'acc': 0.753906, time: 1.506
2025-05-30 07:11:09,226-INFO: epoch: 20, iter: 16200, lr: 0.000010, 'loss': 836.1673, 'acc': 0.755859, time: 1.499
2025-05-30 07:11:52,108-INFO: Test iter: 16200, acc:0.750190, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 07:14:21,231-INFO: epoch: 20, iter: 16300, lr: 0.000010, 'loss': 750.805, 'acc': 0.765625, time: 1.494
2025-05-30 07:16:50,518-INFO: epoch: 20, iter: 16400, lr: 0.000010, 'loss': 862.2168, 'acc': 0.763672, time: 1.491
2025-05-30 07:18:25,212-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 07:19:26,428-INFO: epoch: 21, iter: 16500, lr: 0.000010, 'loss': 753.6105, 'acc': 0.765625, time: 1.599
2025-05-30 07:22:00,954-INFO: epoch: 21, iter: 16600, lr: 0.000010, 'loss': 770.70856, 'acc': 0.757812, time: 1.490
2025-05-30 07:24:30,221-INFO: epoch: 21, iter: 16700, lr: 0.000010, 'loss': 905.1117, 'acc': 0.751953, time: 1.492
2025-05-30 07:26:59,563-INFO: epoch: 21, iter: 16800, lr: 0.000010, 'loss': 812.08997, 'acc': 0.753906, time: 1.494
2025-05-30 07:29:28,872-INFO: epoch: 21, iter: 16900, lr: 0.000010, 'loss': 846.0322, 'acc': 0.761719, time: 1.491
2025-05-30 07:31:58,209-INFO: epoch: 21, iter: 17000, lr: 0.000010, 'loss': 757.8638, 'acc': 0.755859, time: 1.495
2025-05-30 07:34:27,568-INFO: epoch: 21, iter: 17100, lr: 0.000010, 'loss': 811.0347, 'acc': 0.751953, time: 1.494
2025-05-30 07:36:56,895-INFO: epoch: 21, iter: 17200, lr: 0.000010, 'loss': 757.6428, 'acc': 0.757812, time: 1.495
2025-05-30 07:38:07,734-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 07:39:34,728-INFO: epoch: 22, iter: 17300, lr: 0.000010, 'loss': 800.1118, 'acc': 0.771484, time: 1.600
2025-05-30 07:42:07,551-INFO: epoch: 22, iter: 17400, lr: 0.000010, 'loss': 755.39453, 'acc': 0.767578, time: 1.491
2025-05-30 07:44:36,869-INFO: epoch: 22, iter: 17500, lr: 0.000010, 'loss': 777.39325, 'acc': 0.761719, time: 1.491
2025-05-30 07:47:06,201-INFO: epoch: 22, iter: 17600, lr: 0.000010, 'loss': 856.5044, 'acc': 0.755859, time: 1.494
2025-05-30 07:49:35,548-INFO: epoch: 22, iter: 17700, lr: 0.000010, 'loss': 781.6309, 'acc': 0.757812, time: 1.497
2025-05-30 07:52:04,836-INFO: epoch: 22, iter: 17800, lr: 0.000010, 'loss': 908.0542, 'acc': 0.761719, time: 1.492
2025-05-30 07:54:34,162-INFO: epoch: 22, iter: 17900, lr: 0.000010, 'loss': 765.9068, 'acc': 0.761719, time: 1.493
2025-05-30 07:57:03,504-INFO: epoch: 22, iter: 18000, lr: 0.000010, 'loss': 758.1658, 'acc': 0.751953, time: 1.491
2025-05-30 07:57:46,784-INFO: Test iter: 18000, acc:0.747819, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 07:58:33,911-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 08:00:26,328-INFO: epoch: 23, iter: 18100, lr: 0.000010, 'loss': 845.06366, 'acc': 0.769531, time: 1.601
2025-05-30 08:02:57,462-INFO: epoch: 23, iter: 18200, lr: 0.000010, 'loss': 885.7156, 'acc': 0.755859, time: 1.493
2025-05-30 08:05:26,835-INFO: epoch: 23, iter: 18300, lr: 0.000010, 'loss': 830.87537, 'acc': 0.755859, time: 1.493
2025-05-30 08:07:56,219-INFO: epoch: 23, iter: 18400, lr: 0.000010, 'loss': 797.00305, 'acc': 0.773438, time: 1.493
2025-05-30 08:10:25,645-INFO: epoch: 23, iter: 18500, lr: 0.000010, 'loss': 781.5936, 'acc': 0.746094, time: 1.495
2025-05-30 08:12:55,037-INFO: epoch: 23, iter: 18600, lr: 0.000010, 'loss': 826.2796, 'acc': 0.761719, time: 1.490
2025-05-30 08:15:24,411-INFO: epoch: 23, iter: 18700, lr: 0.000010, 'loss': 836.5994, 'acc': 0.75, time: 1.493
2025-05-30 08:17:53,795-INFO: epoch: 23, iter: 18800, lr: 0.000010, 'loss': 783.86597, 'acc': 0.755859, time: 1.493
2025-05-30 08:18:16,918-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 08:20:35,028-INFO: epoch: 24, iter: 18900, lr: 0.000010, 'loss': 868.2908, 'acc': 0.757812, time: 1.600
2025-05-30 08:23:04,480-INFO: epoch: 24, iter: 19000, lr: 0.000010, 'loss': 813.59674, 'acc': 0.75, time: 1.496
2025-05-30 08:25:33,823-INFO: epoch: 24, iter: 19100, lr: 0.000010, 'loss': 796.53625, 'acc': 0.759766, time: 1.492
2025-05-30 08:28:03,231-INFO: epoch: 24, iter: 19200, lr: 0.000010, 'loss': 793.2433, 'acc': 0.753906, time: 1.495
2025-05-30 08:30:32,677-INFO: epoch: 24, iter: 19300, lr: 0.000010, 'loss': 813.9197, 'acc': 0.761719, time: 1.494
2025-05-30 08:33:02,181-INFO: epoch: 24, iter: 19400, lr: 0.000010, 'loss': 811.4301, 'acc': 0.761719, time: 1.494
2025-05-30 08:35:31,687-INFO: epoch: 24, iter: 19500, lr: 0.000010, 'loss': 814.62115, 'acc': 0.761719, time: 1.496
2025-05-30 08:38:00,327-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 08:38:03,922-INFO: epoch: 25, iter: 19600, lr: 0.000010, 'loss': 713.3778, 'acc': 0.762376, time: 3.592
2025-05-30 08:40:42,355-INFO: epoch: 25, iter: 19700, lr: 0.000010, 'loss': 830.9636, 'acc': 0.777344, time: 1.494
2025-05-30 08:43:11,741-INFO: epoch: 25, iter: 19800, lr: 0.000010, 'loss': 834.72015, 'acc': 0.761719, time: 1.495
2025-05-30 08:43:54,616-INFO: Test iter: 19800, acc:0.744310, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 08:46:23,674-INFO: epoch: 25, iter: 19900, lr: 0.000010, 'loss': 798.6936, 'acc': 0.765625, time: 1.493
2025-05-30 08:48:53,014-INFO: epoch: 25, iter: 20000, lr: 0.000010, 'loss': 807.82275, 'acc': 0.767578, time: 1.494
2025-05-30 08:51:22,355-INFO: epoch: 25, iter: 20100, lr: 0.000010, 'loss': 751.64966, 'acc': 0.773438, time: 1.494
2025-05-30 08:53:51,639-INFO: epoch: 25, iter: 20250, lr: 0.000010, 'loss': 793.99194, 'acc': 0.769531, time: 1.495
2025-05-30 08:56:20,960-INFO: epoch: 25, iter: 20300, lr: 0.000010, 'loss': 775.62915, 'acc': 0.759766, time: 1.490
2025-05-30 08:58:25,474-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 08:58:54,828-INFO: epoch: 26, iter: 20400, lr: 0.000010, 'loss': 724.44946, 'acc': 0.761719, time: 1.600
2025-05-30 09:01:31,527-INFO: epoch: 26, iter: 20500, lr: 0.000010, 'loss': 796.36084, 'acc': 0.759766, time: 1.498
2025-05-30 09:04:00,840-INFO: epoch: 26, iter: 20600, lr: 0.000010, 'loss': 837.9087, 'acc': 0.757812, time: 1.491
2025-05-30 09:06:30,190-INFO: epoch: 26, iter: 20700, lr: 0.000010, 'loss': 723.84143, 'acc': 0.761719, time: 1.491
2025-05-30 09:08:59,541-INFO: epoch: 26, iter: 20800, lr: 0.000010, 'loss': 700.9664, 'acc': 0.761719, time: 1.493
2025-05-30 09:11:28,875-INFO: epoch: 26, iter: 20900, lr: 0.000010, 'loss': 847.1577, 'acc': 0.757812, time: 1.491
2025-05-30 09:13:58,237-INFO: epoch: 26, iter: 21000, lr: 0.000010, 'loss': 796.8728, 'acc': 0.767578, time: 1.496
2025-05-30 09:16:27,576-INFO: epoch: 26, iter: 21100, lr: 0.000010, 'loss': 803.3621, 'acc': 0.761719, time: 1.490
2025-05-30 09:18:08,304-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 09:19:03,328-INFO: epoch: 27, iter: 21200, lr: 0.000010, 'loss': 768.6195, 'acc': 0.763672, time: 1.600
2025-05-30 09:21:38,435-INFO: epoch: 27, iter: 21300, lr: 0.000010, 'loss': 768.867, 'acc': 0.751953, time: 1.498
2025-05-30 09:24:07,781-INFO: epoch: 27, iter: 21400, lr: 0.000010, 'loss': 792.67285, 'acc': 0.771484, time: 1.498
2025-05-30 09:26:37,184-INFO: epoch: 27, iter: 21500, lr: 0.000010, 'loss': 788.47253, 'acc': 0.767578, time: 1.491
2025-05-30 09:29:06,612-INFO: epoch: 27, iter: 21600, lr: 0.000010, 'loss': 815.10754, 'acc': 0.765625, time: 1.498
2025-05-30 09:29:49,630-INFO: Test iter: 21600, acc:0.744404, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 09:32:18,874-INFO: epoch: 27, iter: 21700, lr: 0.000010, 'loss': 727.9241, 'acc': 0.777344, time: 1.493
2025-05-30 09:34:48,323-INFO: epoch: 27, iter: 21800, lr: 0.000010, 'loss': 791.48914, 'acc': 0.759766, time: 1.493
2025-05-30 09:37:17,815-INFO: epoch: 27, iter: 21900, lr: 0.000010, 'loss': 844.42505, 'acc': 0.75, time: 1.493
2025-05-30 09:38:34,607-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 09:39:55,228-INFO: epoch: 28, iter: 22000, lr: 0.000010, 'loss': 773.29736, 'acc': 0.763672, time: 1.600
2025-05-30 09:42:28,636-INFO: epoch: 28, iter: 22100, lr: 0.000010, 'loss': 758.2311, 'acc': 0.775391, time: 1.494
2025-05-30 09:44:58,131-INFO: epoch: 28, iter: 22200, lr: 0.000010, 'loss': 810.0912, 'acc': 0.757812, time: 1.494
2025-05-30 09:47:27,618-INFO: epoch: 28, iter: 22300, lr: 0.000010, 'loss': 811.84546, 'acc': 0.763672, time: 1.493
2025-05-30 09:49:57,085-INFO: epoch: 28, iter: 22400, lr: 0.000010, 'loss': 800.67163, 'acc': 0.765625, time: 1.495
2025-05-30 09:52:26,560-INFO: epoch: 28, iter: 22500, lr: 0.000010, 'loss': 803.2442, 'acc': 0.763672, time: 1.498
2025-05-30 09:54:56,004-INFO: epoch: 28, iter: 22600, lr: 0.000010, 'loss': 806.6989, 'acc': 0.744141, time: 1.495
2025-05-30 09:57:25,443-INFO: epoch: 28, iter: 22700, lr: 0.000010, 'loss': 895.87994, 'acc': 0.761719, time: 1.494
2025-05-30 09:58:18,361-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 10:00:04,528-INFO: epoch: 29, iter: 22800, lr: 0.000010, 'loss': 806.8021, 'acc': 0.753906, time: 1.604
2025-05-30 10:02:36,163-INFO: epoch: 29, iter: 22900, lr: 0.000010, 'loss': 758.1184, 'acc': 0.777344, time: 1.497
2025-05-30 10:05:05,601-INFO: epoch: 29, iter: 23000, lr: 0.000010, 'loss': 883.3495, 'acc': 0.769531, time: 1.494
2025-05-30 10:07:35,078-INFO: epoch: 29, iter: 23100, lr: 0.000010, 'loss': 762.5336, 'acc': 0.769531, time: 1.494
2025-05-30 10:10:04,567-INFO: epoch: 29, iter: 23200, lr: 0.000010, 'loss': 789.8906, 'acc': 0.771484, time: 1.500
2025-05-30 10:12:34,023-INFO: epoch: 29, iter: 23300, lr: 0.000010, 'loss': 841.5648, 'acc': 0.759766, time: 1.493
2025-05-30 10:15:03,455-INFO: epoch: 29, iter: 23400, lr: 0.000010, 'loss': 796.6923, 'acc': 0.765625, time: 1.496
2025-05-30 10:15:46,108-INFO: Test iter: 23400, acc:0.745637, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 10:18:15,566-INFO: epoch: 29, iter: 23500, lr: 0.000010, 'loss': 800.1649, 'acc': 0.769531, time: 1.499
2025-05-30 10:18:45,046-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 10:20:56,827-INFO: epoch: 30, iter: 23600, lr: 0.000010, 'loss': 892.2462, 'acc': 0.746094, time: 1.600
2025-05-30 10:23:27,750-INFO: epoch: 30, iter: 23700, lr: 0.000010, 'loss': 762.2878, 'acc': 0.769531, time: 1.508
2025-05-30 10:25:58,080-INFO: epoch: 30, iter: 23800, lr: 0.000010, 'loss': 816.3321, 'acc': 0.753906, time: 1.501
2025-05-30 10:28:28,404-INFO: epoch: 30, iter: 23900, lr: 0.000010, 'loss': 771.4009, 'acc': 0.759766, time: 1.502
2025-05-30 10:30:58,681-INFO: epoch: 30, iter: 24000, lr: 0.000010, 'loss': 879.38855, 'acc': 0.757812, time: 1.504
2025-05-30 10:33:28,982-INFO: epoch: 30, iter: 24100, lr: 0.000010, 'loss': 861.6743, 'acc': 0.773438, time: 1.502
2025-05-30 10:35:59,431-INFO: epoch: 30, iter: 24200, lr: 0.000010, 'loss': 845.1192, 'acc': 0.763672, time: 1.500
2025-05-30 10:38:28,539-INFO: epoch: 30, iter: 24300, lr: 0.000010, 'loss': 708.26294, 'acc': 0.771022, time: 1.247
2025-05-30 10:38:34,942-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 10:41:11,337-INFO: epoch: 31, iter: 24400, lr: 0.000010, 'loss': 846.96497, 'acc': 0.751953, time: 1.503
2025-05-30 10:43:41,773-INFO: epoch: 31, iter: 24500, lr: 0.000010, 'loss': 815.39813, 'acc': 0.769531, time: 1.504
2025-05-30 10:46:12,180-INFO: epoch: 31, iter: 24600, lr: 0.000010, 'loss': 738.178, 'acc': 0.773438, time: 1.502
2025-05-30 10:48:42,615-INFO: epoch: 31, iter: 24700, lr: 0.000010, 'loss': 885.26294, 'acc': 0.757812, time: 1.505
2025-05-30 10:51:13,058-INFO: epoch: 31, iter: 24800, lr: 0.000010, 'loss': 737.80286, 'acc': 0.761719, time: 1.504
2025-05-30 10:53:43,595-INFO: epoch: 31, iter: 24900, lr: 0.000010, 'loss': 818.4972, 'acc': 0.755859, time: 1.504
2025-05-30 10:56:13,994-INFO: epoch: 31, iter: 25000, lr: 0.000010, 'loss': 839.1698, 'acc': 0.765625, time: 1.502
2025-05-30 10:58:25,356-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 10:58:48,334-INFO: epoch: 32, iter: 25100, lr: 0.000010, 'loss': 765.9391, 'acc': 0.7561, time: 1.603
2025-05-30 11:01:25,735-INFO: epoch: 32, iter: 25200, lr: 0.000010, 'loss': 832.3977, 'acc': 0.759766, time: 1.501
2025-05-30 11:02:08,670-INFO: Test iter: 25200, acc:0.746396, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 11:04:38,874-INFO: epoch: 32, iter: 25300, lr: 0.000010, 'loss': 701.14905, 'acc': 0.757812, time: 1.503
2025-05-30 11:07:09,086-INFO: epoch: 32, iter: 25400, lr: 0.000010, 'loss': 790.56024, 'acc': 0.763672, time: 1.501
2025-05-30 11:09:39,322-INFO: epoch: 32, iter: 25500, lr: 0.000010, 'loss': 887.37964, 'acc': 0.761719, time: 1.503
2025-05-30 11:12:09,697-INFO: epoch: 32, iter: 25600, lr: 0.000010, 'loss': 784.1081, 'acc': 0.779297, time: 1.506
2025-05-30 11:14:40,117-INFO: epoch: 32, iter: 25700, lr: 0.000010, 'loss': 839.022, 'acc': 0.769531, time: 1.504
2025-05-30 11:17:10,555-INFO: epoch: 32, iter: 25800, lr: 0.000010, 'loss': 752.19305, 'acc': 0.761719, time: 1.504
2025-05-30 11:18:58,068-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 11:19:46,528-INFO: epoch: 33, iter: 25900, lr: 0.000010, 'loss': 744.72534, 'acc': 0.761719, time: 1.600
2025-05-30 11:22:22,391-INFO: epoch: 33, iter: 26000, lr: 0.000010, 'loss': 749.1394, 'acc': 0.769531, time: 1.506
2025-05-30 11:24:52,633-INFO: epoch: 33, iter: 26100, lr: 0.000010, 'loss': 845.954, 'acc': 0.765625, time: 1.503
2025-05-30 11:27:22,903-INFO: epoch: 33, iter: 26200, lr: 0.000010, 'loss': 863.6808, 'acc': 0.769531, time: 1.504
2025-05-30 11:29:53,241-INFO: epoch: 33, iter: 26300, lr: 0.000010, 'loss': 828.85425, 'acc': 0.769531, time: 1.504
2025-05-30 11:32:22,991-INFO: epoch: 33, iter: 26400, lr: 0.000010, 'loss': 816.9681, 'acc': 0.763672, time: 1.496
2025-05-30 11:34:52,712-INFO: epoch: 33, iter: 26500, lr: 0.000010, 'loss': 785.428, 'acc': 0.761719, time: 1.499
2025-05-30 11:37:22,249-INFO: epoch: 33, iter: 26600, lr: 0.000010, 'loss': 832.95593, 'acc': 0.773438, time: 1.494
2025-05-30 11:38:45,151-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 11:39:59,428-INFO: epoch: 34, iter: 26700, lr: 0.000010, 'loss': 825.64343, 'acc': 0.757812, time: 1.602
2025-05-30 11:42:33,205-INFO: epoch: 34, iter: 26800, lr: 0.000010, 'loss': 992.4359, 'acc': 0.757812, time: 1.492
2025-05-30 11:45:03,004-INFO: epoch: 34, iter: 26900, lr: 0.000010, 'loss': 775.7558, 'acc': 0.765625, time: 1.499
2025-05-30 11:47:32,929-INFO: epoch: 34, iter: 27000, lr: 0.000010, 'loss': 775.61615, 'acc': 0.767578, time: 1.500
2025-05-30 11:48:15,881-INFO: Test iter: 27000, acc:0.747724, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 11:50:45,573-INFO: epoch: 34, iter: 27100, lr: 0.000010, 'loss': 745.1616, 'acc': 0.759766, time: 1.499
2025-05-30 11:53:15,472-INFO: epoch: 34, iter: 27200, lr: 0.000010, 'loss': 809.11084, 'acc': 0.761719, time: 1.496
2025-05-30 11:55:45,403-INFO: epoch: 34, iter: 27300, lr: 0.000010, 'loss': 824.917, 'acc': 0.755859, time: 1.499
2025-05-30 11:58:15,385-INFO: epoch: 34, iter: 27400, lr: 0.000010, 'loss': 801.7388, 'acc': 0.773438, time: 1.501
2025-05-30 11:59:14,482-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 12:00:54,328-INFO: epoch: 35, iter: 27500, lr: 0.000010, 'loss': 707.3496, 'acc': 0.771484, time: 1.600
2025-05-30 12:03:26,850-INFO: epoch: 35, iter: 27600, lr: 0.000010, 'loss': 860.7188, 'acc': 0.763672, time: 1.497
2025-05-30 12:05:56,789-INFO: epoch: 35, iter: 27700, lr: 0.000010, 'loss': 812.0786, 'acc': 0.771484, time: 1.504
2025-05-30 12:08:26,736-INFO: epoch: 35, iter: 27800, lr: 0.000010, 'loss': 862.25964, 'acc': 0.767578, time: 1.497
2025-05-30 12:10:56,628-INFO: epoch: 35, iter: 27900, lr: 0.000010, 'loss': 806.14087, 'acc': 0.765625, time: 1.496
2025-05-30 12:13:26,402-INFO: epoch: 35, iter: 28000, lr: 0.000010, 'loss': 817.3717, 'acc': 0.761719, time: 1.496
2025-05-30 12:15:56,149-INFO: epoch: 35, iter: 28100, lr: 0.000010, 'loss': 767.0642, 'acc': 0.757812, time: 1.495
2025-05-30 12:18:25,833-INFO: epoch: 35, iter: 28200, lr: 0.000010, 'loss': 739.8462, 'acc': 0.777344, time: 1.500
2025-05-30 12:19:00,889-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 12:21:06,828-INFO: epoch: 36, iter: 28300, lr: 0.000010, 'loss': 831.9491, 'acc': 0.761719, time: 1.602
2025-05-30 12:23:37,402-INFO: epoch: 36, iter: 28400, lr: 0.000010, 'loss': 853.7959, 'acc': 0.763672, time: 1.491
2025-05-30 12:26:06,965-INFO: epoch: 36, iter: 28500, lr: 0.000010, 'loss': 865.27515, 'acc': 0.763672, time: 1.493
2025-05-30 12:28:36,409-INFO: epoch: 36, iter: 28600, lr: 0.000010, 'loss': 812.99585, 'acc': 0.761719, time: 1.496
2025-05-30 12:31:05,909-INFO: epoch: 36, iter: 28700, lr: 0.000010, 'loss': 775.9178, 'acc': 0.759766, time: 1.496
2025-05-30 12:33:35,425-INFO: epoch: 36, iter: 28800, lr: 0.000010, 'loss': 790.19727, 'acc': 0.761719, time: 1.497
2025-05-30 12:34:18,399-INFO: Test iter: 28800, acc:0.746017, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 12:36:47,724-INFO: epoch: 36, iter: 28900, lr: 0.000010, 'loss': 794.9398, 'acc': 0.748047, time: 1.500
2025-05-30 12:39:16,767-INFO: epoch: 36, iter: 29000, lr: 0.000010, 'loss': 762.34705, 'acc': 0.759766, time: 1.499
2025-05-30 12:39:28,381-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 12:41:58,629-INFO: epoch: 37, iter: 29100, lr: 0.000010, 'loss': 730.57416, 'acc': 0.773438, time: 1.490
2025-05-30 12:44:28,210-INFO: epoch: 37, iter: 29200, lr: 0.000010, 'loss': 832.48517, 'acc': 0.769531, time: 1.497
2025-05-30 12:46:57,817-INFO: epoch: 37, iter: 29300, lr: 0.000010, 'loss': 845.1477, 'acc': 0.763672, time: 1.494
2025-05-30 12:49:27,377-INFO: epoch: 37, iter: 29400, lr: 0.000010, 'loss': 833.0525, 'acc': 0.761719, time: 1.489
2025-05-30 12:51:57,025-INFO: epoch: 37, iter: 29500, lr: 0.000010, 'loss': 797.1345, 'acc': 0.769531, time: 1.496
2025-05-30 12:54:26,733-INFO: epoch: 37, iter: 29600, lr: 0.000010, 'loss': 775.8845, 'acc': 0.759766, time: 1.495
2025-05-30 12:56:56,522-INFO: epoch: 37, iter: 29700, lr: 0.000010, 'loss': 778.73315, 'acc': 0.757812, time: 1.499
2025-05-30 12:59:13,610-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 12:59:30,540-INFO: epoch: 38, iter: 29800, lr: 0.000010, 'loss': 738.98566, 'acc': 0.766699, time: 1.677
2025-05-30 13:02:08,297-INFO: epoch: 38, iter: 29900, lr: 0.000010, 'loss': 784.23535, 'acc': 0.761719, time: 1.499
2025-05-30 13:04:38,104-INFO: epoch: 38, iter: 30000, lr: 0.000010, 'loss': 814.1173, 'acc': 0.755859, time: 1.496
2025-05-30 13:07:07,914-INFO: epoch: 38, iter: 30100, lr: 0.000010, 'loss': 787.648, 'acc': 0.767578, time: 1.494
2025-05-30 13:09:37,602-INFO: epoch: 38, iter: 30200, lr: 0.000010, 'loss': 793.02747, 'acc': 0.763672, time: 1.500
2025-05-30 13:12:07,256-INFO: epoch: 38, iter: 30300, lr: 0.000010, 'loss': 797.619, 'acc': 0.757812, time: 1.496
2025-05-30 13:14:36,961-INFO: epoch: 38, iter: 30400, lr: 0.000010, 'loss': 809.0262, 'acc': 0.765625, time: 1.498
2025-05-30 13:17:06,760-INFO: epoch: 38, iter: 30500, lr: 0.000010, 'loss': 782.70447, 'acc': 0.769531, time: 1.500
2025-05-30 13:18:59,785-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 13:19:42,428-INFO: epoch: 39, iter: 30600, lr: 0.000010, 'loss': 816.80597, 'acc': 0.765625, time: 1.598
2025-05-30 13:21:02,339-INFO: Test iter: 30600, acc:0.747250, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 13:23:32,615-INFO: epoch: 39, iter: 30700, lr: 0.000010, 'loss': 873.92847, 'acc': 0.765625, time: 1.494
2025-05-30 13:26:02,237-INFO: epoch: 39, iter: 30800, lr: 0.000010, 'loss': 774.24774, 'acc': 0.763672, time: 1.495
2025-05-30 13:28:31,946-INFO: epoch: 39, iter: 30900, lr: 0.000010, 'loss': 919.71594, 'acc': 0.769531, time: 1.496
2025-05-30 13:31:01,625-INFO: epoch: 39, iter: 31000, lr: 0.000010, 'loss': 648.636, 'acc': 0.775391, time: 1.496
2025-05-30 13:33:31,347-INFO: epoch: 39, iter: 31100, lr: 0.000010, 'loss': 725.8932, 'acc': 0.767578, time: 1.498
2025-05-30 13:36:01,068-INFO: epoch: 39, iter: 31200, lr: 0.000010, 'loss': 770.2261, 'acc': 0.777344, time: 1.496
2025-05-30 13:38:30,731-INFO: epoch: 39, iter: 31300, lr: 0.000010, 'loss': 750.8507, 'acc': 0.761719, time: 1.496
2025-05-30 13:39:59,792-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 13:41:07,528-INFO: epoch: 40, iter: 31400, lr: 0.000010, 'loss': 871.4826, 'acc': 0.765625, time: 1.600
2025-05-30 13:43:41,831-INFO: epoch: 40, iter: 31500, lr: 0.000010, 'loss': 791.89417, 'acc': 0.773438, time: 1.497
2025-05-30 13:46:11,536-INFO: epoch: 40, iter: 31600, lr: 0.000010, 'loss': 797.7447, 'acc': 0.757812, time: 1.498
2025-05-30 13:48:41,227-INFO: epoch: 40, iter: 31700, lr: 0.000010, 'loss': 818.7768, 'acc': 0.755859, time: 1.499
2025-05-30 13:51:10,886-INFO: epoch: 40, iter: 31800, lr: 0.000010, 'loss': 779.5845, 'acc': 0.769531, time: 1.494
2025-05-30 13:53:40,610-INFO: epoch: 40, iter: 31900, lr: 0.000010, 'loss': 831.41504, 'acc': 0.767578, time: 1.498
2025-05-30 13:56:10,344-INFO: epoch: 40, iter: 32000, lr: 0.000010, 'loss': 826.5134, 'acc': 0.761719, time: 1.498
2025-05-30 13:58:40,065-INFO: epoch: 40, iter: 32100, lr: 0.000010, 'loss': 677.40845, 'acc': 0.775391, time: 1.496
2025-05-30 13:59:45,201-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 14:01:18,528-INFO: epoch: 41, iter: 32200, lr: 0.000010, 'loss': 688.8986, 'acc': 0.767578, time: 1.600
2025-05-30 14:03:51,216-INFO: epoch: 41, iter: 32300, lr: 0.000010, 'loss': 858.4071, 'acc': 0.759766, time: 1.497
2025-05-30 14:06:20,955-INFO: epoch: 41, iter: 32400, lr: 0.000010, 'loss': 709.80286, 'acc': 0.775391, time: 1.497
2025-05-30 14:07:03,918-INFO: Test iter: 32400, acc:0.747344, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 14:09:33,278-INFO: epoch: 41, iter: 32500, lr: 0.000010, 'loss': 846.2653, 'acc': 0.771484, time: 1.493
2025-05-30 14:12:02,925-INFO: epoch: 41, iter: 32600, lr: 0.000010, 'loss': 774.6905, 'acc': 0.746094, time: 1.498
2025-05-30 14:14:32,556-INFO: epoch: 41, iter: 32700, lr: 0.000010, 'loss': 643.87476, 'acc': 0.777344, time: 1.496
2025-05-30 14:17:02,142-INFO: epoch: 41, iter: 32800, lr: 0.000010, 'loss': 814.66187, 'acc': 0.765625, time: 1.494
2025-05-30 14:19:31,738-INFO: epoch: 41, iter: 32900, lr: 0.000010, 'loss': 809.1865, 'acc': 0.757812, time: 1.512
2025-05-30 14:20:12,688-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 14:22:11,728-INFO: epoch: 42, iter: 33000, lr: 0.000010, 'loss': 759.80457, 'acc': 0.767578, time: 1.601
2025-05-30 14:24:42,633-INFO: epoch: 42, iter: 33100, lr: 0.000010, 'loss': 772.23596, 'acc': 0.751953, time: 1.491
2025-05-30 14:27:12,139-INFO: epoch: 42, iter: 33200, lr: 0.000010, 'loss': 719.0503, 'acc': 0.767578, time: 1.493
2025-05-30 14:29:41,640-INFO: epoch: 42, iter: 33300, lr: 0.000010, 'loss': 767.4442, 'acc': 0.746094, time: 1.496
2025-05-30 14:32:11,178-INFO: epoch: 42, iter: 33400, lr: 0.000010, 'loss': 813.94556, 'acc': 0.755859, time: 1.492
2025-05-30 14:34:40,753-INFO: epoch: 42, iter: 33500, lr: 0.000010, 'loss': 749.19025, 'acc': 0.767578, time: 1.496
2025-05-30 14:37:10,289-INFO: epoch: 42, iter: 33600, lr: 0.000010, 'loss': 763.5924, 'acc': 0.773438, time: 1.495
2025-05-30 14:39:39,489-INFO: epoch: 42, iter: 33700, lr: 0.000010, 'loss': 728.84546, 'acc': 0.759766, time: 1.234
2025-05-30 14:39:56,806-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 14:42:20,862-INFO: epoch: 43, iter: 33800, lr: 0.000010, 'loss': 762.76843, 'acc': 0.769531, time: 1.491
2025-05-30 14:44:50,369-INFO: epoch: 43, iter: 33900, lr: 0.000010, 'loss': 807.6052, 'acc': 0.771484, time: 1.493
2025-05-30 14:47:19,891-INFO: epoch: 43, iter: 34000, lr: 0.000010, 'loss': 820.8777, 'acc': 0.765625, time: 1.492
2025-05-30 14:49:49,465-INFO: epoch: 43, iter: 34100, lr: 0.000010, 'loss': 699.48254, 'acc': 0.763672, time: 1.494
2025-05-30 14:52:18,912-INFO: epoch: 43, iter: 34200, lr: 0.000010, 'loss': 729.0989, 'acc': 0.775391, time: 1.497
2025-05-30 14:53:02,332-INFO: Test iter: 34200, acc:0.747724, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 14:55:31,525-INFO: epoch: 43, iter: 34300, lr: 0.000010, 'loss': 749.0641, 'acc': 0.767578, time: 1.495
2025-05-30 14:58:01,053-INFO: epoch: 43, iter: 34400, lr: 0.000010, 'loss': 807.9845, 'acc': 0.761719, time: 1.497
2025-05-30 15:00:23,739-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 15:00:33,932-INFO: epoch: 44, iter: 34500, lr: 0.000010, 'loss': 698.7145, 'acc': 0.757812, time: 1.704
2025-05-30 15:03:12,372-INFO: epoch: 44, iter: 34600, lr: 0.000010, 'loss': 798.28265, 'acc': 0.769531, time: 1.497
2025-05-30 15:05:41,973-INFO: epoch: 44, iter: 34700, lr: 0.000010, 'loss': 778.844, 'acc': 0.757812, time: 1.494
2025-05-30 15:08:11,586-INFO: epoch: 44, iter: 34800, lr: 0.000010, 'loss': 812.72394, 'acc': 0.763672, time: 1.494
2025-05-30 15:10:41,136-INFO: epoch: 44, iter: 34900, lr: 0.000010, 'loss': 672.2686, 'acc': 0.78125, time: 1.497
2025-05-30 15:13:10,718-INFO: epoch: 44, iter: 35000, lr: 0.000010, 'loss': 764.0675, 'acc': 0.771484, time: 1.496
2025-05-30 15:15:40,291-INFO: epoch: 44, iter: 35100, lr: 0.000010, 'loss': 824.64124, 'acc': 0.767578, time: 1.497
2025-05-30 15:18:09,849-INFO: epoch: 44, iter: 35200, lr: 0.000010, 'loss': 810.9432, 'acc': 0.767578, time: 1.495
2025-05-30 15:20:08,579-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 15:20:44,423-INFO: epoch: 45, iter: 35300, lr: 0.000010, 'loss': 760.1756, 'acc': 0.759766, time: 1.595
2025-05-30 15:23:20,886-INFO: epoch: 45, iter: 35400, lr: 0.000010, 'loss': 891.94543, 'acc': 0.767578, time: 1.495
2025-05-30 15:25:50,487-INFO: epoch: 45, iter: 35500, lr: 0.000010, 'loss': 828.6175, 'acc': 0.765625, time: 1.496
2025-05-30 15:28:20,762-INFO: epoch: 45, iter: 35600, lr: 0.000010, 'loss': 822.4815, 'acc': 0.765625, time: 1.508
2025-05-30 15:30:51,290-INFO: epoch: 45, iter: 35700, lr: 0.000010, 'loss': 765.68286, 'acc': 0.769531, time: 1.504
2025-05-30 15:33:21,904-INFO: epoch: 45, iter: 35800, lr: 0.000010, 'loss': 814.37335, 'acc': 0.769531, time: 1.503
2025-05-30 15:35:52,462-INFO: epoch: 45, iter: 35900, lr: 0.000010, 'loss': 790.8864, 'acc': 0.765625, time: 1.502
2025-05-30 15:38:22,968-INFO: epoch: 45, iter: 36000, lr: 0.000010, 'loss': 771.67694, 'acc': 0.763672, time: 1.509
2025-05-30 15:39:05,699-INFO: Test iter: 36000, acc:0.749905, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 15:40:41,581-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 15:41:42,928-INFO: epoch: 46, iter: 36100, lr: 0.000010, 'loss': 852.6521, 'acc': 0.763672, time: 1.600
2025-05-30 15:44:18,324-INFO: epoch: 46, iter: 36200, lr: 0.000010, 'loss': 690.95044, 'acc': 0.773438, time: 1.502
2025-05-30 15:46:49,020-INFO: epoch: 46, iter: 36300, lr: 0.000010, 'loss': 802.2465, 'acc': 0.779297, time: 1.509
2025-05-30 15:49:19,651-INFO: epoch: 46, iter: 36400, lr: 0.000010, 'loss': 771.6051, 'acc': 0.769531, time: 1.500
2025-05-30 15:51:50,392-INFO: epoch: 46, iter: 36500, lr: 0.000010, 'loss': 813.5723, 'acc': 0.761719, time: 1.508
2025-05-30 15:54:20,940-INFO: epoch: 46, iter: 36600, lr: 0.000010, 'loss': 766.5608, 'acc': 0.769531, time: 1.510
2025-05-30 15:56:51,496-INFO: epoch: 46, iter: 36700, lr: 0.000010, 'loss': 784.6614, 'acc': 0.773438, time: 1.508
2025-05-30 15:59:22,174-INFO: epoch: 46, iter: 36800, lr: 0.000010, 'loss': 748.14734, 'acc': 0.769531, time: 1.506
2025-05-30 16:00:33,465-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 16:02:00,928-INFO: epoch: 47, iter: 36900, lr: 0.000010, 'loss': 738.58234, 'acc': 0.761719, time: 1.601
2025-05-30 16:04:34,709-INFO: epoch: 47, iter: 37000, lr: 0.000010, 'loss': 808.3149, 'acc': 0.767578, time: 1.500
2025-05-30 16:07:04,877-INFO: epoch: 47, iter: 37100, lr: 0.000010, 'loss': 821.7324, 'acc': 0.771484, time: 1.501
2025-05-30 16:09:35,074-INFO: epoch: 47, iter: 37200, lr: 0.000010, 'loss': 826.7959, 'acc': 0.763672, time: 1.503
2025-05-30 16:12:05,271-INFO: epoch: 47, iter: 37300, lr: 0.000010, 'loss': 781.4752, 'acc': 0.763672, time: 1.504
2025-05-30 16:14:35,429-INFO: epoch: 47, iter: 37400, lr: 0.000010, 'loss': 774.58136, 'acc': 0.773438, time: 1.502
2025-05-30 16:17:05,691-INFO: epoch: 47, iter: 37500, lr: 0.000010, 'loss': 713.0936, 'acc': 0.765625, time: 1.503
2025-05-30 16:19:35,874-INFO: epoch: 47, iter: 37600, lr: 0.000010, 'loss': 828.3831, 'acc': 0.767578, time: 1.502
2025-05-30 16:20:23,078-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 16:22:15,828-INFO: epoch: 48, iter: 37700, lr: 0.000010, 'loss': 791.9916, 'acc': 0.759766, time: 1.600
2025-05-30 16:24:47,789-INFO: epoch: 48, iter: 37800, lr: 0.000010, 'loss': 657.7782, 'acc': 0.777344, time: 1.495
2025-05-30 16:25:31,288-INFO: Test iter: 37800, acc:0.748293, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 16:28:01,116-INFO: epoch: 48, iter: 37900, lr: 0.000010, 'loss': 654.9749, 'acc': 0.769531, time: 1.499
2025-05-30 16:30:31,428-INFO: epoch: 48, iter: 38000, lr: 0.000010, 'loss': 783.9652, 'acc': 0.775391, time: 1.503
2025-05-30 16:33:02,168-INFO: epoch: 48, iter: 38100, lr: 0.000010, 'loss': 848.30115, 'acc': 0.763672, time: 1.506
2025-05-30 16:35:32,856-INFO: epoch: 48, iter: 38200, lr: 0.000010, 'loss': 822.49756, 'acc': 0.769531, time: 1.510
2025-05-30 16:38:03,420-INFO: epoch: 48, iter: 38300, lr: 0.000010, 'loss': 730.25305, 'acc': 0.769531, time: 1.504
2025-05-30 16:40:34,027-INFO: epoch: 48, iter: 38400, lr: 0.000010, 'loss': 679.0596, 'acc': 0.777344, time: 1.505
2025-05-30 16:40:57,459-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 16:43:16,227-INFO: epoch: 49, iter: 38500, lr: 0.000010, 'loss': 775.8943, 'acc': 0.761719, time: 1.599
2025-05-30 16:45:47,175-INFO: epoch: 49, iter: 38600, lr: 0.000010, 'loss': 824.65015, 'acc': 0.771484, time: 1.505
2025-05-30 16:48:17,728-INFO: epoch: 49, iter: 38700, lr: 0.000010, 'loss': 750.0271, 'acc': 0.761719, time: 1.506
2025-05-30 16:50:48,148-INFO: epoch: 49, iter: 38800, lr: 0.000010, 'loss': 730.2977, 'acc': 0.773438, time: 1.503
2025-05-30 16:53:18,341-INFO: epoch: 49, iter: 38900, lr: 0.000010, 'loss': 733.90924, 'acc': 0.771484, time: 1.501
2025-05-30 16:55:48,490-INFO: epoch: 49, iter: 39000, lr: 0.000010, 'loss': 840.0241, 'acc': 0.761719, time: 1.500
2025-05-30 16:58:18,551-INFO: epoch: 49, iter: 39100, lr: 0.000010, 'loss': 867.83014, 'acc': 0.757812, time: 1.498
2025-05-30 17:00:47,839-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 17:00:51,632-INFO: epoch: 50, iter: 39200, lr: 0.000010, 'loss': 699.5686, 'acc': 0.777344, time: 3.790
2025-05-30 17:03:30,908-INFO: epoch: 50, iter: 39300, lr: 0.000010, 'loss': 662.6245, 'acc': 0.769531, time: 1.498
2025-05-30 17:06:00,908-INFO: epoch: 50, iter: 39400, lr: 0.000010, 'loss': 784.9778, 'acc': 0.763672, time: 1.500
2025-05-30 17:08:31,050-INFO: epoch: 50, iter: 39500, lr: 0.000010, 'loss': 833.7151, 'acc': 0.767578, time: 1.504
2025-05-30 17:11:01,606-INFO: epoch: 50, iter: 39600, lr: 0.000010, 'loss': 809.7446, 'acc': 0.767578, time: 1.502
2025-05-30 17:11:44,517-INFO: Test iter: 39600, acc:0.748103, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 17:14:15,024-INFO: epoch: 50, iter: 39700, lr: 0.000010, 'loss': 825.30646, 'acc': 0.761719, time: 1.509
2025-05-30 17:16:45,585-INFO: epoch: 50, iter: 39800, lr: 0.000010, 'loss': 775.84186, 'acc': 0.773438, time: 1.502
2025-05-30 17:19:15,895-INFO: epoch: 50, iter: 39900, lr: 0.000010, 'loss': 773.841, 'acc': 0.78125, time: 1.497
2025-05-30 17:21:21,277-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 17:21:50,928-INFO: epoch: 51, iter: 40000, lr: 0.000010, 'loss': 750.48425, 'acc': 0.768099, time: 1.600
2025-05-30 17:24:27,849-INFO: epoch: 51, iter: 40100, lr: 0.000010, 'loss': 782.947, 'acc': 0.775391, time: 1.494
2025-05-30 17:26:57,455-INFO: epoch: 51, iter: 40200, lr: 0.000010, 'loss': 665.24304, 'acc': 0.765625, time: 1.496
2025-05-30 17:29:26,982-INFO: epoch: 51, iter: 40300, lr: 0.000010, 'loss': 863.0307, 'acc': 0.765625, time: 1.493
2025-05-30 17:31:56,503-INFO: epoch: 51, iter: 40400, lr: 0.000010, 'loss': 771.4785, 'acc': 0.765625, time: 1.493
2025-05-30 17:34:26,082-INFO: epoch: 51, iter: 40500, lr: 0.000010, 'loss': 805.5956, 'acc': 0.777344, time: 1.494
2025-05-30 17:36:56,097-INFO: epoch: 51, iter: 40600, lr: 0.000010, 'loss': 762.447, 'acc': 0.773438, time: 1.501
2025-05-30 17:39:25,861-INFO: epoch: 51, iter: 40700, lr: 0.000010, 'loss': 823.7523, 'acc': 0.763672, time: 1.495
2025-05-30 17:41:06,779-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 17:42:01,942-INFO: epoch: 52, iter: 40800, lr: 0.000010, 'loss': 804.1991, 'acc': 0.767578, time: 1.598
2025-05-30 17:44:37,119-INFO: epoch: 52, iter: 40900, lr: 0.000010, 'loss': 785.7146, 'acc': 0.765625, time: 1.496
2025-05-30 17:47:06,556-INFO: epoch: 52, iter: 41000, lr: 0.000010, 'loss': 868.68555, 'acc': 0.753906, time: 1.497
2025-05-30 17:49:36,761-INFO: epoch: 52, iter: 41100, lr: 0.000010, 'loss': 805.3978, 'acc': 0.769531, time: 1.507
2025-05-30 17:52:07,198-INFO: epoch: 52, iter: 41200, lr: 0.000010, 'loss': 814.76544, 'acc': 0.769531, time: 1.506
2025-05-30 17:54:37,734-INFO: epoch: 52, iter: 41300, lr: 0.000010, 'loss': 743.2091, 'acc': 0.773438, time: 1.506
2025-05-30 17:57:08,240-INFO: epoch: 52, iter: 41400, lr: 0.000010, 'loss': 790.0695, 'acc': 0.78125, time: 1.508
2025-05-30 17:57:51,073-INFO: Test iter: 41400, acc:0.748672, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 18:00:21,448-INFO: epoch: 52, iter: 41500, lr: 0.000010, 'loss': 825.02014, 'acc': 0.759766, time: 1.504
2025-05-30 18:01:38,915-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 18:03:00,128-INFO: epoch: 53, iter: 41600, lr: 0.000010, 'loss': 733.7169, 'acc': 0.767578, time: 1.600
2025-05-30 18:05:34,749-INFO: epoch: 53, iter: 41700, lr: 0.000010, 'loss': 857.08606, 'acc': 0.761719, time: 1.504
2025-05-30 18:08:05,282-INFO: epoch: 53, iter: 41800, lr: 0.000010, 'loss': 742.28613, 'acc': 0.769531, time: 1.505
2025-05-30 18:10:35,794-INFO: epoch: 53, iter: 41900, lr: 0.000010, 'loss': 709.46106, 'acc': 0.771484, time: 1.505
2025-05-30 18:13:06,375-INFO: epoch: 53, iter: 42000, lr: 0.000010, 'loss': 739.46387, 'acc': 0.769531, time: 1.506
2025-05-30 18:15:36,917-INFO: epoch: 53, iter: 42100, lr: 0.000010, 'loss': 850.21497, 'acc': 0.765625, time: 1.501
2025-05-30 18:18:07,813-INFO: epoch: 53, iter: 42200, lr: 0.000010, 'loss': 809.76056, 'acc': 0.769531, time: 1.513
2025-05-30 18:20:38,892-INFO: epoch: 53, iter: 42300, lr: 0.000010, 'loss': 702.8702, 'acc': 0.771484, time: 1.511
2025-05-30 18:21:32,320-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 18:23:19,028-INFO: epoch: 54, iter: 42400, lr: 0.000010, 'loss': 742.78955, 'acc': 0.773438, time: 1.597
2025-05-30 18:25:52,166-INFO: epoch: 54, iter: 42500, lr: 0.000010, 'loss': 820.32666, 'acc': 0.779297, time: 1.508
2025-05-30 18:28:23,211-INFO: epoch: 54, iter: 42600, lr: 0.000010, 'loss': 688.5978, 'acc': 0.78125, time: 1.509
2025-05-30 18:30:54,095-INFO: epoch: 54, iter: 42700, lr: 0.000010, 'loss': 717.23145, 'acc': 0.75, time: 1.506
2025-05-30 18:33:24,941-INFO: epoch: 54, iter: 42800, lr: 0.000010, 'loss': 783.5393, 'acc': 0.773438, time: 1.510
2025-05-30 18:35:55,662-INFO: epoch: 54, iter: 42900, lr: 0.000010, 'loss': 743.9623, 'acc': 0.789062, time: 1.511
2025-05-30 18:38:26,466-INFO: epoch: 54, iter: 43000, lr: 0.000010, 'loss': 772.53485, 'acc': 0.763672, time: 1.506
2025-05-30 18:40:57,094-INFO: epoch: 54, iter: 43100, lr: 0.000010, 'loss': 782.74304, 'acc': 0.765625, time: 1.504
2025-05-30 18:41:26,390-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 18:43:38,228-INFO: epoch: 55, iter: 43200, lr: 0.000010, 'loss': 821.728, 'acc': 0.763672, time: 1.600
2025-05-30 18:44:25,907-INFO: Test iter: 43200, acc:0.747629, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 18:46:56,533-INFO: epoch: 55, iter: 43300, lr: 0.000010, 'loss': 754.2859, 'acc': 0.773438, time: 1.506
2025-05-30 18:49:27,216-INFO: epoch: 55, iter: 43400, lr: 0.000010, 'loss': 785.3016, 'acc': 0.779297, time: 1.505
2025-05-30 18:51:57,882-INFO: epoch: 55, iter: 43500, lr: 0.000010, 'loss': 762.8927, 'acc': 0.777344, time: 1.507
2025-05-30 18:54:28,558-INFO: epoch: 55, iter: 43600, lr: 0.000010, 'loss': 793.6015, 'acc': 0.771484, time: 1.508
2025-05-30 18:56:59,094-INFO: epoch: 55, iter: 43700, lr: 0.000010, 'loss': 736.89624, 'acc': 0.775391, time: 1.506
2025-05-30 18:59:29,660-INFO: epoch: 55, iter: 43800, lr: 0.000010, 'loss': 767.3441, 'acc': 0.769531, time: 1.512
2025-05-30 19:01:59,087-INFO: epoch: 55, iter: 43900, lr: 0.000010, 'loss': 731.8158, 'acc': 0.751777, time: 1.245
2025-05-30 19:02:05,507-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 19:04:42,188-INFO: epoch: 56, iter: 44000, lr: 0.000010, 'loss': 791.6061, 'acc': 0.767578, time: 1.505
2025-05-30 19:07:12,766-INFO: epoch: 56, iter: 44100, lr: 0.000010, 'loss': 793.8723, 'acc': 0.773438, time: 1.507
2025-05-30 19:09:43,300-INFO: epoch: 56, iter: 44200, lr: 0.000010, 'loss': 755.6627, 'acc': 0.775391, time: 1.505
2025-05-30 19:12:13,961-INFO: epoch: 56, iter: 44300, lr: 0.000010, 'loss': 779.50006, 'acc': 0.763672, time: 1.507
2025-05-30 19:14:44,642-INFO: epoch: 56, iter: 44400, lr: 0.000010, 'loss': 723.55383, 'acc': 0.773438, time: 1.507
2025-05-30 19:17:15,270-INFO: epoch: 56, iter: 44500, lr: 0.000010, 'loss': 797.66754, 'acc': 0.755859, time: 1.509
2025-05-30 19:19:45,936-INFO: epoch: 56, iter: 44600, lr: 0.000010, 'loss': 783.27783, 'acc': 0.765625, time: 1.503
2025-05-30 19:21:57,700-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 19:22:20,828-INFO: epoch: 57, iter: 44700, lr: 0.000010, 'loss': 742.8301, 'acc': 0.769531, time: 1.600
2025-05-30 19:24:58,317-INFO: epoch: 57, iter: 44800, lr: 0.000010, 'loss': 722.5408, 'acc': 0.783203, time: 1.507
2025-05-30 19:27:28,826-INFO: epoch: 57, iter: 44900, lr: 0.000010, 'loss': 819.4166, 'acc': 0.761719, time: 1.503
2025-05-30 19:29:59,345-INFO: epoch: 57, iter: 45000, lr: 0.000010, 'loss': 789.27747, 'acc': 0.777344, time: 1.505
2025-05-30 19:30:53,698-INFO: Test iter: 45000, acc:0.744973, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 19:33:24,084-INFO: epoch: 57, iter: 45100, lr: 0.000010, 'loss': 721.0781, 'acc': 0.777344, time: 1.504
2025-05-30 19:35:54,608-INFO: epoch: 57, iter: 45200, lr: 0.000010, 'loss': 739.7223, 'acc': 0.767578, time: 1.508
2025-05-30 19:38:25,177-INFO: epoch: 57, iter: 45300, lr: 0.000010, 'loss': 867.28467, 'acc': 0.771484, time: 1.507
2025-05-30 19:40:55,790-INFO: epoch: 57, iter: 45400, lr: 0.000010, 'loss': 670.3572, 'acc': 0.783203, time: 1.503
2025-05-30 19:42:43,308-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 19:43:32,133-INFO: epoch: 58, iter: 45500, lr: 0.000010, 'loss': 805.8157, 'acc': 0.773438, time: 1.604
2025-05-30 19:46:08,077-INFO: epoch: 58, iter: 45600, lr: 0.000010, 'loss': 729.41815, 'acc': 0.771484, time: 1.502
2025-05-30 19:48:38,666-INFO: epoch: 58, iter: 45700, lr: 0.000010, 'loss': 844.6998, 'acc': 0.755859, time: 1.510
2025-05-30 19:51:09,098-INFO: epoch: 58, iter: 45800, lr: 0.000010, 'loss': 808.4137, 'acc': 0.757812, time: 1.507
2025-05-30 19:53:39,658-INFO: epoch: 58, iter: 45900, lr: 0.000010, 'loss': 772.73975, 'acc': 0.761719, time: 1.510
2025-05-30 19:56:10,183-INFO: epoch: 58, iter: 46000, lr: 0.000010, 'loss': 783.66406, 'acc': 0.773438, time: 1.506
2025-05-30 19:58:40,715-INFO: epoch: 58, iter: 46100, lr: 0.000010, 'loss': 761.038, 'acc': 0.769531, time: 1.505
2025-05-30 20:01:11,275-INFO: epoch: 58, iter: 46200, lr: 0.000010, 'loss': 766.69446, 'acc': 0.759766, time: 1.507
2025-05-30 20:02:34,704-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 20:03:49,028-INFO: epoch: 59, iter: 46300, lr: 0.000010, 'loss': 884.06604, 'acc': 0.759766, time: 1.600
2025-05-30 20:06:23,571-INFO: epoch: 59, iter: 46400, lr: 0.000010, 'loss': 815.8745, 'acc': 0.771484, time: 1.506
2025-05-30 20:08:54,099-INFO: epoch: 59, iter: 46500, lr: 0.000010, 'loss': 830.31793, 'acc': 0.775391, time: 1.503
2025-05-30 20:11:24,590-INFO: epoch: 59, iter: 46600, lr: 0.000010, 'loss': 766.4379, 'acc': 0.765625, time: 1.502
2025-05-30 20:13:55,170-INFO: epoch: 59, iter: 46700, lr: 0.000010, 'loss': 795.0852, 'acc': 0.765625, time: 1.500
2025-05-30 20:16:25,724-INFO: epoch: 59, iter: 46800, lr: 0.000010, 'loss': 724.80164, 'acc': 0.777344, time: 1.506
2025-05-30 20:17:08,885-INFO: Test iter: 46800, acc:0.751897, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 20:19:39,434-INFO: epoch: 59, iter: 46900, lr: 0.000010, 'loss': 848.3589, 'acc': 0.767578, time: 1.504
2025-05-30 20:22:10,076-INFO: epoch: 59, iter: 47000, lr: 0.000010, 'loss': 800.5083, 'acc': 0.761719, time: 1.506
2025-05-30 20:23:09,382-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 20:24:49,528-INFO: epoch: 60, iter: 47100, lr: 0.000010, 'loss': 845.0459, 'acc': 0.769531, time: 1.600
2025-05-30 20:27:22,708-INFO: epoch: 60, iter: 47200, lr: 0.000010, 'loss': 890.1496, 'acc': 0.765625, time: 1.506
2025-05-30 20:29:53,337-INFO: epoch: 60, iter: 47300, lr: 0.000010, 'loss': 769.9689, 'acc': 0.773438, time: 1.507
2025-05-30 20:32:23,998-INFO: epoch: 60, iter: 47400, lr: 0.000010, 'loss': 771.6892, 'acc': 0.765625, time: 1.504
2025-05-30 20:34:54,661-INFO: epoch: 60, iter: 47500, lr: 0.000010, 'loss': 795.43005, 'acc': 0.767578, time: 1.509
2025-05-30 20:37:25,322-INFO: epoch: 60, iter: 47600, lr: 0.000010, 'loss': 890.20184, 'acc': 0.767578, time: 1.504
2025-05-30 20:39:56,040-INFO: epoch: 60, iter: 47700, lr: 0.000010, 'loss': 723.6571, 'acc': 0.771484, time: 1.507
2025-05-30 20:42:26,693-INFO: epoch: 60, iter: 47800, lr: 0.000010, 'loss': 765.61395, 'acc': 0.765625, time: 1.504
2025-05-30 20:43:02,020-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 20:45:07,328-INFO: epoch: 61, iter: 47900, lr: 0.000010, 'loss': 799.6328, 'acc': 0.78125, time: 1.600
2025-05-30 20:47:38,930-INFO: epoch: 61, iter: 48000, lr: 0.000010, 'loss': 791.80493, 'acc': 0.777344, time: 1.500
2025-05-30 20:50:09,519-INFO: epoch: 61, iter: 48100, lr: 0.000010, 'loss': 779.4253, 'acc': 0.767578, time: 1.501
2025-05-30 20:52:40,191-INFO: epoch: 61, iter: 48200, lr: 0.000010, 'loss': 760.9438, 'acc': 0.767578, time: 1.509
2025-05-30 20:55:10,853-INFO: epoch: 61, iter: 48300, lr: 0.000010, 'loss': 759.773, 'acc': 0.779297, time: 1.506
2025-05-30 20:57:41,407-INFO: epoch: 61, iter: 48400, lr: 0.000010, 'loss': 699.77234, 'acc': 0.773438, time: 1.508
2025-05-30 21:00:12,017-INFO: epoch: 61, iter: 48500, lr: 0.000010, 'loss': 747.1356, 'acc': 0.769531, time: 1.505
2025-05-30 21:02:42,215-INFO: epoch: 61, iter: 48600, lr: 0.000010, 'loss': 810.0222, 'acc': 0.766699, time: 1.504
2025-05-30 21:03:25,537-INFO: Test iter: 48600, acc:0.745258, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 21:03:37,253-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 21:06:08,029-INFO: epoch: 62, iter: 48700, lr: 0.000010, 'loss': 801.1719, 'acc': 0.771484, time: 1.510
2025-05-30 21:08:39,320-INFO: epoch: 62, iter: 48800, lr: 0.000010, 'loss': 828.29443, 'acc': 0.765625, time: 1.514
2025-05-30 21:11:10,271-INFO: epoch: 62, iter: 48900, lr: 0.000010, 'loss': 757.786, 'acc': 0.787109, time: 1.509
2025-05-30 21:13:41,072-INFO: epoch: 62, iter: 49000, lr: 0.000010, 'loss': 775.18866, 'acc': 0.767578, time: 1.516
2025-05-30 21:16:12,377-INFO: epoch: 62, iter: 49100, lr: 0.000010, 'loss': 704.4737, 'acc': 0.767578, time: 1.514
2025-05-30 21:18:43,715-INFO: epoch: 62, iter: 49200, lr: 0.000010, 'loss': 718.5282, 'acc': 0.775391, time: 1.520
2025-05-30 21:21:15,149-INFO: epoch: 62, iter: 49300, lr: 0.000010, 'loss': 776.56396, 'acc': 0.765625, time: 1.513
2025-05-30 21:23:33,463-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 21:23:50,228-INFO: epoch: 63, iter: 49400, lr: 0.000010, 'loss': 767.34766, 'acc': 0.768652, time: 1.672
2025-05-30 21:26:28,626-INFO: epoch: 63, iter: 49500, lr: 0.000010, 'loss': 744.98926, 'acc': 0.771484, time: 1.517
2025-05-30 21:28:59,993-INFO: epoch: 63, iter: 49600, lr: 0.000010, 'loss': 769.6802, 'acc': 0.777344, time: 1.514
2025-05-30 21:31:31,348-INFO: epoch: 63, iter: 49700, lr: 0.000010, 'loss': 806.0011, 'acc': 0.775391, time: 1.512
2025-05-30 21:34:02,696-INFO: epoch: 63, iter: 49800, lr: 0.000010, 'loss': 680.3314, 'acc': 0.783203, time: 1.515
2025-05-30 21:36:34,099-INFO: epoch: 63, iter: 49900, lr: 0.000010, 'loss': 748.2019, 'acc': 0.771484, time: 1.515
2025-05-30 21:39:05,442-INFO: epoch: 63, iter: 50000, lr: 0.000010, 'loss': 820.6935, 'acc': 0.771484, time: 1.514
2025-05-30 21:41:36,818-INFO: epoch: 63, iter: 50100, lr: 0.000010, 'loss': 799.0313, 'acc': 0.773438, time: 1.514
2025-05-30 21:43:31,021-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 21:44:13,131-INFO: epoch: 64, iter: 50200, lr: 0.000010, 'loss': 767.1228, 'acc': 0.779297, time: 1.600
2025-05-30 21:46:49,982-INFO: epoch: 64, iter: 50300, lr: 0.000010, 'loss': 723.42957, 'acc': 0.777344, time: 1.511
2025-05-30 21:49:21,209-INFO: epoch: 64, iter: 50400, lr: 0.000010, 'loss': 762.67676, 'acc': 0.771484, time: 1.515
2025-05-30 21:50:04,325-INFO: Test iter: 50400, acc:0.746491, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 21:52:35,371-INFO: epoch: 64, iter: 50500, lr: 0.000010, 'loss': 787.7898, 'acc': 0.785156, time: 1.510
2025-05-30 21:55:06,723-INFO: epoch: 64, iter: 50600, lr: 0.000010, 'loss': 812.2639, 'acc': 0.773438, time: 1.515
2025-05-30 21:57:38,100-INFO: epoch: 64, iter: 50700, lr: 0.000010, 'loss': 789.1388, 'acc': 0.775391, time: 1.516
2025-05-30 22:00:09,369-INFO: epoch: 64, iter: 50800, lr: 0.000010, 'loss': 814.13696, 'acc': 0.773438, time: 1.511
2025-05-30 22:02:39,670-INFO: epoch: 64, iter: 50900, lr: 0.000010, 'loss': 722.03937, 'acc': 0.761719, time: 1.499
2025-05-30 22:04:18,640-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 22:05:26,428-INFO: epoch: 65, iter: 51000, lr: 0.000010, 'loss': 774.2773, 'acc': 0.777344, time: 1.599
2025-05-30 22:08:01,194-INFO: epoch: 65, iter: 51100, lr: 0.000010, 'loss': 746.4785, 'acc': 0.765625, time: 1.499
2025-05-30 22:10:30,823-INFO: epoch: 65, iter: 51200, lr: 0.000010, 'loss': 813.70654, 'acc': 0.777344, time: 1.496
2025-05-30 22:13:00,355-INFO: epoch: 65, iter: 51300, lr: 0.000010, 'loss': 735.434, 'acc': 0.763672, time: 1.492
2025-05-30 22:15:29,762-INFO: epoch: 65, iter: 51400, lr: 0.000010, 'loss': 706.8122, 'acc': 0.767578, time: 1.499
2025-05-30 22:17:59,206-INFO: epoch: 65, iter: 51500, lr: 0.000010, 'loss': 680.2599, 'acc': 0.777344, time: 1.497
2025-05-30 22:20:28,571-INFO: epoch: 65, iter: 51600, lr: 0.000010, 'loss': 787.93713, 'acc': 0.779297, time: 1.495
2025-05-30 22:22:58,017-INFO: epoch: 65, iter: 51700, lr: 0.000010, 'loss': 776.1387, 'acc': 0.767578, time: 1.492
2025-05-30 22:24:02,927-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 22:25:36,426-INFO: epoch: 66, iter: 51800, lr: 0.000010, 'loss': 800.229, 'acc': 0.773438, time: 1.599
2025-05-30 22:28:09,016-INFO: epoch: 66, iter: 51900, lr: 0.000010, 'loss': 842.6061, 'acc': 0.763672, time: 1.495
2025-05-30 22:30:38,426-INFO: epoch: 66, iter: 52000, lr: 0.000010, 'loss': 698.17285, 'acc': 0.771484, time: 1.493
2025-05-30 22:33:07,857-INFO: epoch: 66, iter: 52100, lr: 0.000010, 'loss': 759.3546, 'acc': 0.773438, time: 1.496
2025-05-30 22:35:37,307-INFO: epoch: 66, iter: 52200, lr: 0.000010, 'loss': 922.1255, 'acc': 0.763672, time: 1.495
2025-05-30 22:36:19,831-INFO: Test iter: 52200, acc:0.748293, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 22:38:49,045-INFO: epoch: 66, iter: 52300, lr: 0.000010, 'loss': 823.65466, 'acc': 0.773438, time: 1.495
2025-05-30 22:41:18,452-INFO: epoch: 66, iter: 52400, lr: 0.000010, 'loss': 776.2611, 'acc': 0.753906, time: 1.495
2025-05-30 22:43:47,848-INFO: epoch: 66, iter: 52500, lr: 0.000010, 'loss': 816.5613, 'acc': 0.775391, time: 1.491
2025-05-30 22:44:28,805-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 22:46:27,928-INFO: epoch: 67, iter: 52600, lr: 0.000010, 'loss': 727.2331, 'acc': 0.759766, time: 1.601
2025-05-30 22:48:58,667-INFO: epoch: 67, iter: 52700, lr: 0.000010, 'loss': 820.74744, 'acc': 0.769531, time: 1.494
2025-05-30 22:51:28,095-INFO: epoch: 67, iter: 52800, lr: 0.000010, 'loss': 727.22327, 'acc': 0.771484, time: 1.493
2025-05-30 22:53:57,497-INFO: epoch: 67, iter: 52900, lr: 0.000010, 'loss': 823.5492, 'acc': 0.769531, time: 1.493
2025-05-30 22:56:26,929-INFO: epoch: 67, iter: 53000, lr: 0.000010, 'loss': 845.49786, 'acc': 0.773438, time: 1.499
2025-05-30 22:58:56,371-INFO: epoch: 67, iter: 53100, lr: 0.000010, 'loss': 786.07935, 'acc': 0.769531, time: 1.495
2025-05-30 23:01:25,832-INFO: epoch: 67, iter: 53200, lr: 0.000010, 'loss': 794.3812, 'acc': 0.765625, time: 1.496
2025-05-30 23:03:55,095-INFO: epoch: 67, iter: 53300, lr: 0.000010, 'loss': 766.2962, 'acc': 0.779297, time: 1.494
2025-05-30 23:04:12,438-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 23:06:37,254-INFO: epoch: 68, iter: 53400, lr: 0.000010, 'loss': 804.2832, 'acc': 0.775391, time: 1.491
2025-05-30 23:09:06,737-INFO: epoch: 68, iter: 53500, lr: 0.000010, 'loss': 794.60754, 'acc': 0.767578, time: 1.496
2025-05-30 23:11:36,243-INFO: epoch: 68, iter: 53600, lr: 0.000010, 'loss': 817.6123, 'acc': 0.771484, time: 1.500
2025-05-30 23:14:05,803-INFO: epoch: 68, iter: 53700, lr: 0.000010, 'loss': 774.62537, 'acc': 0.771484, time: 1.495
2025-05-30 23:16:35,397-INFO: epoch: 68, iter: 53800, lr: 0.000010, 'loss': 702.11206, 'acc': 0.779297, time: 1.497
2025-05-30 23:19:04,972-INFO: epoch: 68, iter: 53900, lr: 0.000010, 'loss': 857.22107, 'acc': 0.771484, time: 1.494
2025-05-30 23:21:34,495-INFO: epoch: 68, iter: 54000, lr: 0.000010, 'loss': 814.2201, 'acc': 0.779297, time: 1.495
2025-05-30 23:22:17,523-INFO: Test iter: 54000, acc:0.742413, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-30 23:24:39,958-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 23:24:50,128-INFO: epoch: 69, iter: 54100, lr: 0.000010, 'loss': 776.6543, 'acc': 0.766699, time: 1.690
2025-05-30 23:27:28,447-INFO: epoch: 69, iter: 54200, lr: 0.000010, 'loss': 821.983, 'acc': 0.773438, time: 1.502
2025-05-30 23:29:57,992-INFO: epoch: 69, iter: 54300, lr: 0.000010, 'loss': 764.8248, 'acc': 0.777344, time: 1.497
2025-05-30 23:32:27,565-INFO: epoch: 69, iter: 54400, lr: 0.000010, 'loss': 852.8922, 'acc': 0.773438, time: 1.499
2025-05-30 23:34:57,171-INFO: epoch: 69, iter: 54500, lr: 0.000010, 'loss': 810.3157, 'acc': 0.785156, time: 1.497
2025-05-30 23:37:26,774-INFO: epoch: 69, iter: 54600, lr: 0.000010, 'loss': 792.3468, 'acc': 0.771484, time: 1.497
2025-05-30 23:39:56,341-INFO: epoch: 69, iter: 54700, lr: 0.000010, 'loss': 708.3982, 'acc': 0.779297, time: 1.496
2025-05-30 23:42:25,915-INFO: epoch: 69, iter: 54800, lr: 0.000010, 'loss': 811.6311, 'acc': 0.773438, time: 1.498
2025-05-30 23:44:24,941-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-30 23:45:00,928-INFO: epoch: 70, iter: 54900, lr: 0.000010, 'loss': 693.35095, 'acc': 0.775391, time: 1.600
2025-05-30 23:47:37,381-INFO: epoch: 70, iter: 55000, lr: 0.000010, 'loss': 762.7894, 'acc': 0.771484, time: 1.495
2025-05-30 23:50:06,941-INFO: epoch: 70, iter: 55100, lr: 0.000010, 'loss': 678.0182, 'acc': 0.78125, time: 1.496
2025-05-30 23:52:36,474-INFO: epoch: 70, iter: 55200, lr: 0.000010, 'loss': 721.34125, 'acc': 0.771484, time: 1.497
2025-05-30 23:55:06,044-INFO: epoch: 70, iter: 55300, lr: 0.000010, 'loss': 742.0408, 'acc': 0.787109, time: 1.496
2025-05-30 23:57:35,624-INFO: epoch: 70, iter: 55400, lr: 0.000010, 'loss': 826.8546, 'acc': 0.771484, time: 1.494
2025-05-31 00:00:05,236-INFO: epoch: 70, iter: 55500, lr: 0.000010, 'loss': 742.03375, 'acc': 0.771484, time: 1.494
2025-05-31 00:02:34,829-INFO: epoch: 70, iter: 55600, lr: 0.000010, 'loss': 820.8894, 'acc': 0.759766, time: 1.496
2025-05-31 00:04:09,761-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 00:05:11,128-INFO: epoch: 71, iter: 55700, lr: 0.000010, 'loss': 756.5916, 'acc': 0.777344, time: 1.600
2025-05-31 00:07:46,000-INFO: epoch: 71, iter: 55800, lr: 0.000010, 'loss': 781.4601, 'acc': 0.777344, time: 1.499
2025-05-31 00:08:28,607-INFO: Test iter: 55800, acc:0.745542, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 00:10:57,836-INFO: epoch: 71, iter: 55900, lr: 0.000010, 'loss': 689.89294, 'acc': 0.78125, time: 1.492
2025-05-31 00:13:27,288-INFO: epoch: 71, iter: 56000, lr: 0.000010, 'loss': 834.9049, 'acc': 0.775391, time: 1.494
2025-05-31 00:15:56,714-INFO: epoch: 71, iter: 56100, lr: 0.000010, 'loss': 828.0934, 'acc': 0.759766, time: 1.494
2025-05-31 00:18:26,176-INFO: epoch: 71, iter: 56200, lr: 0.000010, 'loss': 701.272, 'acc': 0.759766, time: 1.496
2025-05-31 00:20:55,608-INFO: epoch: 71, iter: 56300, lr: 0.000010, 'loss': 830.4695, 'acc': 0.753906, time: 1.500
2025-05-31 00:23:25,017-INFO: epoch: 71, iter: 56400, lr: 0.000010, 'loss': 738.24146, 'acc': 0.771484, time: 1.494
2025-05-31 00:24:35,837-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 00:26:02,627-INFO: epoch: 72, iter: 56500, lr: 0.000010, 'loss': 754.9024, 'acc': 0.773438, time: 1.600
2025-05-31 00:28:35,752-INFO: epoch: 72, iter: 56600, lr: 0.000010, 'loss': 693.2995, 'acc': 0.767578, time: 1.497
2025-05-31 00:31:05,139-INFO: epoch: 72, iter: 56700, lr: 0.000010, 'loss': 705.3039, 'acc': 0.771484, time: 1.494
2025-05-31 00:33:34,571-INFO: epoch: 72, iter: 56800, lr: 0.000010, 'loss': 825.5765, 'acc': 0.769531, time: 1.492
2025-05-31 00:36:03,987-INFO: epoch: 72, iter: 56900, lr: 0.000010, 'loss': 747.27795, 'acc': 0.777344, time: 1.494
2025-05-31 00:38:33,395-INFO: epoch: 72, iter: 57000, lr: 0.000010, 'loss': 822.45776, 'acc': 0.761719, time: 1.492
2025-05-31 00:41:02,812-INFO: epoch: 72, iter: 57100, lr: 0.000010, 'loss': 811.50146, 'acc': 0.767578, time: 1.492
2025-05-31 00:43:32,260-INFO: epoch: 72, iter: 57200, lr: 0.000010, 'loss': 783.7479, 'acc': 0.775391, time: 1.494
2025-05-31 00:44:19,304-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 00:46:12,127-INFO: epoch: 73, iter: 57300, lr: 0.000010, 'loss': 817.4159, 'acc': 0.769531, time: 1.600
2025-05-31 00:48:43,574-INFO: epoch: 73, iter: 57400, lr: 0.000010, 'loss': 775.1251, 'acc': 0.763672, time: 1.497
2025-05-31 00:51:13,081-INFO: epoch: 73, iter: 57500, lr: 0.000010, 'loss': 728.0471, 'acc': 0.777344, time: 1.495
2025-05-31 00:53:42,587-INFO: epoch: 73, iter: 57600, lr: 0.000010, 'loss': 647.15515, 'acc': 0.78125, time: 1.498
2025-05-31 00:54:25,394-INFO: Test iter: 57600, acc:0.747534, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 00:56:54,643-INFO: epoch: 73, iter: 57700, lr: 0.000010, 'loss': 794.51587, 'acc': 0.769531, time: 1.494
2025-05-31 00:59:24,127-INFO: epoch: 73, iter: 57800, lr: 0.000010, 'loss': 818.994, 'acc': 0.759766, time: 1.494
2025-05-31 01:01:53,611-INFO: epoch: 73, iter: 57900, lr: 0.000010, 'loss': 761.4164, 'acc': 0.771484, time: 1.495
2025-05-31 01:04:23,140-INFO: epoch: 73, iter: 58000, lr: 0.000010, 'loss': 721.1012, 'acc': 0.777344, time: 1.495
2025-05-31 01:04:46,176-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 01:07:04,327-INFO: epoch: 74, iter: 58100, lr: 0.000010, 'loss': 780.0078, 'acc': 0.769531, time: 1.599
2025-05-31 01:09:34,106-INFO: epoch: 74, iter: 58200, lr: 0.000010, 'loss': 792.4292, 'acc': 0.78125, time: 1.493
2025-05-31 01:12:03,642-INFO: epoch: 74, iter: 58300, lr: 0.000010, 'loss': 695.92035, 'acc': 0.773438, time: 1.494
2025-05-31 01:14:33,132-INFO: epoch: 74, iter: 58400, lr: 0.000010, 'loss': 763.14026, 'acc': 0.769531, time: 1.493
2025-05-31 01:17:02,657-INFO: epoch: 74, iter: 58500, lr: 0.000010, 'loss': 690.87195, 'acc': 0.779297, time: 1.495
2025-05-31 01:19:32,199-INFO: epoch: 74, iter: 58600, lr: 0.000010, 'loss': 827.9093, 'acc': 0.777344, time: 1.492
2025-05-31 01:22:01,702-INFO: epoch: 74, iter: 58700, lr: 0.000010, 'loss': 765.29565, 'acc': 0.769531, time: 1.496
2025-05-31 01:24:30,333-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 01:24:33,931-INFO: epoch: 75, iter: 58800, lr: 0.000010, 'loss': 840.12964, 'acc': 0.78125, time: 3.596
2025-05-31 01:27:12,451-INFO: epoch: 75, iter: 58900, lr: 0.000010, 'loss': 761.45984, 'acc': 0.777344, time: 1.498
2025-05-31 01:29:41,904-INFO: epoch: 75, iter: 59000, lr: 0.000010, 'loss': 723.88635, 'acc': 0.78125, time: 1.494
2025-05-31 01:32:11,397-INFO: epoch: 75, iter: 59100, lr: 0.000010, 'loss': 664.396, 'acc': 0.773438, time: 1.494
2025-05-31 01:34:40,897-INFO: epoch: 75, iter: 59200, lr: 0.000010, 'loss': 797.1874, 'acc': 0.763672, time: 1.492
2025-05-31 01:37:10,386-INFO: epoch: 75, iter: 59300, lr: 0.000010, 'loss': 769.12946, 'acc': 0.757812, time: 1.493
2025-05-31 01:39:39,883-INFO: epoch: 75, iter: 59400, lr: 0.000010, 'loss': 686.20685, 'acc': 0.787109, time: 1.495
2025-05-31 01:40:22,784-INFO: Test iter: 59400, acc:0.750664, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 01:42:52,048-INFO: epoch: 75, iter: 59500, lr: 0.000010, 'loss': 709.3624, 'acc': 0.773438, time: 1.496
2025-05-31 01:44:56,718-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 01:45:26,228-INFO: epoch: 76, iter: 59600, lr: 0.000010, 'loss': 752.20325, 'acc': 0.777344, time: 1.600
2025-05-31 01:48:03,090-INFO: epoch: 76, iter: 59700, lr: 0.000010, 'loss': 795.32227, 'acc': 0.777344, time: 1.493
2025-05-31 01:50:32,578-INFO: epoch: 76, iter: 59800, lr: 0.000010, 'loss': 734.6292, 'acc': 0.769531, time: 1.494
2025-05-31 01:53:02,082-INFO: epoch: 76, iter: 59900, lr: 0.000010, 'loss': 805.59186, 'acc': 0.771484, time: 1.495
2025-05-31 01:55:31,586-INFO: epoch: 76, iter: 60000, lr: 0.000010, 'loss': 776.79706, 'acc': 0.767578, time: 1.491
2025-05-31 01:58:01,080-INFO: epoch: 76, iter: 60100, lr: 0.000010, 'loss': 712.6255, 'acc': 0.775391, time: 1.495
2025-05-31 02:00:30,543-INFO: epoch: 76, iter: 60200, lr: 0.000010, 'loss': 788.83734, 'acc': 0.779297, time: 1.494
2025-05-31 02:03:00,073-INFO: epoch: 76, iter: 60300, lr: 0.000010, 'loss': 798.0568, 'acc': 0.775391, time: 1.498
2025-05-31 02:04:40,894-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 02:05:36,027-INFO: epoch: 77, iter: 60400, lr: 0.000010, 'loss': 736.4961, 'acc': 0.755859, time: 1.599
2025-05-31 02:08:11,724-INFO: epoch: 77, iter: 60500, lr: 0.000010, 'loss': 792.7007, 'acc': 0.771484, time: 1.510
2025-05-31 02:10:42,309-INFO: epoch: 77, iter: 60600, lr: 0.000010, 'loss': 765.3669, 'acc': 0.767578, time: 1.506
2025-05-31 02:13:12,856-INFO: epoch: 77, iter: 60700, lr: 0.000010, 'loss': 835.8453, 'acc': 0.775391, time: 1.504
2025-05-31 02:15:43,415-INFO: epoch: 77, iter: 60800, lr: 0.000010, 'loss': 726.92236, 'acc': 0.777344, time: 1.507
2025-05-31 02:18:14,029-INFO: epoch: 77, iter: 60900, lr: 0.000010, 'loss': 759.6417, 'acc': 0.773438, time: 1.509
2025-05-31 02:20:44,603-INFO: epoch: 77, iter: 61000, lr: 0.000010, 'loss': 745.365, 'acc': 0.777344, time: 1.509
2025-05-31 02:23:15,104-INFO: epoch: 77, iter: 61100, lr: 0.000010, 'loss': 751.50745, 'acc': 0.777344, time: 1.506
2025-05-31 02:24:32,528-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 02:25:53,327-INFO: epoch: 78, iter: 61200, lr: 0.000010, 'loss': 738.3429, 'acc': 0.771484, time: 1.600
2025-05-31 02:27:02,491-INFO: Test iter: 61200, acc:0.744689, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 02:29:32,902-INFO: epoch: 78, iter: 61300, lr: 0.000010, 'loss': 705.45483, 'acc': 0.777344, time: 1.504
2025-05-31 02:32:03,460-INFO: epoch: 78, iter: 61400, lr: 0.000010, 'loss': 775.5167, 'acc': 0.779297, time: 1.505
2025-05-31 02:34:34,057-INFO: epoch: 78, iter: 61500, lr: 0.000010, 'loss': 673.3287, 'acc': 0.767578, time: 1.503
2025-05-31 02:37:04,601-INFO: epoch: 78, iter: 61600, lr: 0.000010, 'loss': 702.29675, 'acc': 0.773438, time: 1.505
2025-05-31 02:39:35,163-INFO: epoch: 78, iter: 61700, lr: 0.000010, 'loss': 710.6393, 'acc': 0.771484, time: 1.504
2025-05-31 02:42:05,799-INFO: epoch: 78, iter: 61800, lr: 0.000010, 'loss': 673.1873, 'acc': 0.783203, time: 1.509
2025-05-31 02:44:36,389-INFO: epoch: 78, iter: 61900, lr: 0.000010, 'loss': 809.42395, 'acc': 0.763672, time: 1.504
2025-05-31 02:45:29,672-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 02:47:16,028-INFO: epoch: 79, iter: 62000, lr: 0.000010, 'loss': 689.90656, 'acc': 0.771484, time: 1.600
2025-05-31 02:49:48,578-INFO: epoch: 79, iter: 62100, lr: 0.000010, 'loss': 729.7644, 'acc': 0.767578, time: 1.501
2025-05-31 02:52:19,113-INFO: epoch: 79, iter: 62200, lr: 0.000010, 'loss': 807.3106, 'acc': 0.775391, time: 1.503
2025-05-31 02:54:49,773-INFO: epoch: 79, iter: 62300, lr: 0.000010, 'loss': 728.7843, 'acc': 0.78125, time: 1.509
2025-05-31 02:57:20,441-INFO: epoch: 79, iter: 62400, lr: 0.000010, 'loss': 741.4131, 'acc': 0.773438, time: 1.505
2025-05-31 02:59:51,026-INFO: epoch: 79, iter: 62500, lr: 0.000010, 'loss': 787.77844, 'acc': 0.769531, time: 1.507
2025-05-31 03:02:21,701-INFO: epoch: 79, iter: 62600, lr: 0.000010, 'loss': 814.5587, 'acc': 0.765625, time: 1.507
2025-05-31 03:04:52,318-INFO: epoch: 79, iter: 62700, lr: 0.000010, 'loss': 706.17725, 'acc': 0.771484, time: 1.510
2025-05-31 03:05:21,551-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 03:07:33,628-INFO: epoch: 80, iter: 62800, lr: 0.000010, 'loss': 768.55115, 'acc': 0.78125, time: 1.600
2025-05-31 03:10:04,810-INFO: epoch: 80, iter: 62900, lr: 0.000010, 'loss': 841.73914, 'acc': 0.769531, time: 1.503
2025-05-31 03:12:35,459-INFO: epoch: 80, iter: 63000, lr: 0.000010, 'loss': 746.8823, 'acc': 0.777344, time: 1.505
2025-05-31 03:13:18,623-INFO: Test iter: 63000, acc:0.745922, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 03:15:49,138-INFO: epoch: 80, iter: 63100, lr: 0.000010, 'loss': 714.2982, 'acc': 0.78125, time: 1.504
2025-05-31 03:18:19,715-INFO: epoch: 80, iter: 63200, lr: 0.000010, 'loss': 727.84644, 'acc': 0.777344, time: 1.507
2025-05-31 03:20:50,282-INFO: epoch: 80, iter: 63300, lr: 0.000010, 'loss': 769.99603, 'acc': 0.763672, time: 1.506
2025-05-31 03:23:20,899-INFO: epoch: 80, iter: 63400, lr: 0.000010, 'loss': 707.43164, 'acc': 0.775391, time: 1.510
2025-05-31 03:25:50,120-INFO: epoch: 80, iter: 63500, lr: 0.000010, 'loss': 696.65765, 'acc': 0.775391, time: 1.240
2025-05-31 03:25:56,771-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 03:28:33,404-INFO: epoch: 81, iter: 63600, lr: 0.000010, 'loss': 728.9532, 'acc': 0.769531, time: 1.502
2025-05-31 03:31:03,940-INFO: epoch: 81, iter: 63700, lr: 0.000010, 'loss': 751.874, 'acc': 0.777344, time: 1.506
2025-05-31 03:33:34,500-INFO: epoch: 81, iter: 63800, lr: 0.000010, 'loss': 733.67017, 'acc': 0.78125, time: 1.502
2025-05-31 03:36:05,110-INFO: epoch: 81, iter: 63900, lr: 0.000010, 'loss': 828.97064, 'acc': 0.761719, time: 1.502
2025-05-31 03:38:35,710-INFO: epoch: 81, iter: 64000, lr: 0.000010, 'loss': 710.41284, 'acc': 0.775391, time: 1.508
2025-05-31 03:41:06,387-INFO: epoch: 81, iter: 64100, lr: 0.000010, 'loss': 787.9204, 'acc': 0.773438, time: 1.505
2025-05-31 03:43:36,953-INFO: epoch: 81, iter: 64200, lr: 0.000010, 'loss': 832.98865, 'acc': 0.759766, time: 1.506
2025-05-31 03:45:48,624-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 03:46:11,728-INFO: epoch: 82, iter: 64300, lr: 0.000010, 'loss': 760.4878, 'acc': 0.773438, time: 1.586
2025-05-31 03:48:49,268-INFO: epoch: 82, iter: 64400, lr: 0.000010, 'loss': 733.4469, 'acc': 0.767578, time: 1.506
2025-05-31 03:51:19,846-INFO: epoch: 82, iter: 64500, lr: 0.000010, 'loss': 676.6207, 'acc': 0.777344, time: 1.503
2025-05-31 03:53:50,437-INFO: epoch: 82, iter: 64600, lr: 0.000010, 'loss': 727.2194, 'acc': 0.78125, time: 1.503
2025-05-31 03:56:21,005-INFO: epoch: 82, iter: 64700, lr: 0.000010, 'loss': 761.69434, 'acc': 0.771484, time: 1.508
2025-05-31 03:58:51,480-INFO: epoch: 82, iter: 64800, lr: 0.000010, 'loss': 807.6964, 'acc': 0.773438, time: 1.507
2025-05-31 03:59:34,412-INFO: Test iter: 64800, acc:0.744594, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 04:02:04,987-INFO: epoch: 82, iter: 64900, lr: 0.000010, 'loss': 808.7843, 'acc': 0.775391, time: 1.504
2025-05-31 04:04:35,618-INFO: epoch: 82, iter: 65000, lr: 0.000010, 'loss': 751.0137, 'acc': 0.78125, time: 1.506
2025-05-31 04:06:23,083-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 04:07:11,928-INFO: epoch: 83, iter: 65100, lr: 0.000010, 'loss': 752.9244, 'acc': 0.773438, time: 1.600
2025-05-31 04:09:47,920-INFO: epoch: 83, iter: 65200, lr: 0.000010, 'loss': 796.0821, 'acc': 0.785156, time: 1.509
2025-05-31 04:12:18,486-INFO: epoch: 83, iter: 65300, lr: 0.000010, 'loss': 787.99365, 'acc': 0.775391, time: 1.505
2025-05-31 04:14:49,003-INFO: epoch: 83, iter: 65400, lr: 0.000010, 'loss': 750.2649, 'acc': 0.789062, time: 1.504
2025-05-31 04:17:19,564-INFO: epoch: 83, iter: 65500, lr: 0.000010, 'loss': 702.50024, 'acc': 0.777344, time: 1.509
2025-05-31 04:19:50,142-INFO: epoch: 83, iter: 65600, lr: 0.000010, 'loss': 824.801, 'acc': 0.779297, time: 1.510
2025-05-31 04:22:20,817-INFO: epoch: 83, iter: 65700, lr: 0.000010, 'loss': 841.41064, 'acc': 0.763672, time: 1.505
2025-05-31 04:24:51,420-INFO: epoch: 83, iter: 65800, lr: 0.000010, 'loss': 789.2965, 'acc': 0.789062, time: 1.505
2025-05-31 04:26:14,911-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 04:27:29,228-INFO: epoch: 84, iter: 65900, lr: 0.000010, 'loss': 771.3669, 'acc': 0.777344, time: 1.600
2025-05-31 04:30:03,811-INFO: epoch: 84, iter: 66000, lr: 0.000010, 'loss': 727.2678, 'acc': 0.775391, time: 1.506
2025-05-31 04:32:34,421-INFO: epoch: 84, iter: 66100, lr: 0.000010, 'loss': 769.8502, 'acc': 0.779297, time: 1.504
2025-05-31 04:35:05,049-INFO: epoch: 84, iter: 66200, lr: 0.000010, 'loss': 853.0419, 'acc': 0.777344, time: 1.509
2025-05-31 04:37:35,702-INFO: epoch: 84, iter: 66300, lr: 0.000010, 'loss': 796.86523, 'acc': 0.769531, time: 1.506
2025-05-31 04:40:06,213-INFO: epoch: 84, iter: 66400, lr: 0.000010, 'loss': 693.38916, 'acc': 0.777344, time: 1.505
2025-05-31 04:42:36,866-INFO: epoch: 84, iter: 66500, lr: 0.000010, 'loss': 795.24414, 'acc': 0.773438, time: 1.509
2025-05-31 04:45:07,487-INFO: epoch: 84, iter: 66600, lr: 0.000010, 'loss': 687.3568, 'acc': 0.771484, time: 1.504
2025-05-31 04:45:50,255-INFO: Test iter: 66600, acc:0.744215, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 04:46:49,507-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 04:48:29,528-INFO: epoch: 85, iter: 66700, lr: 0.000010, 'loss': 791.8745, 'acc': 0.769531, time: 1.599
2025-05-31 04:51:02,668-INFO: epoch: 85, iter: 66800, lr: 0.000010, 'loss': 782.7244, 'acc': 0.775391, time: 1.506
2025-05-31 04:53:33,290-INFO: epoch: 85, iter: 66900, lr: 0.000010, 'loss': 704.7214, 'acc': 0.779297, time: 1.507
2025-05-31 04:56:03,843-INFO: epoch: 85, iter: 67000, lr: 0.000010, 'loss': 708.36475, 'acc': 0.783203, time: 1.509
2025-05-31 04:58:34,399-INFO: epoch: 85, iter: 67100, lr: 0.000010, 'loss': 750.5251, 'acc': 0.777344, time: 1.506
2025-05-31 05:01:05,005-INFO: epoch: 85, iter: 67200, lr: 0.000010, 'loss': 785.9284, 'acc': 0.767578, time: 1.506
2025-05-31 05:03:35,629-INFO: epoch: 85, iter: 67300, lr: 0.000010, 'loss': 737.22296, 'acc': 0.771484, time: 1.505
2025-05-31 05:06:06,216-INFO: epoch: 85, iter: 67400, lr: 0.000010, 'loss': 782.5618, 'acc': 0.775391, time: 1.511
2025-05-31 05:06:41,654-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 05:08:47,328-INFO: epoch: 86, iter: 67500, lr: 0.000010, 'loss': 829.0638, 'acc': 0.763672, time: 1.599
2025-05-31 05:11:18,787-INFO: epoch: 86, iter: 67600, lr: 0.000010, 'loss': 822.75854, 'acc': 0.775391, time: 1.504
2025-05-31 05:13:49,402-INFO: epoch: 86, iter: 67700, lr: 0.000010, 'loss': 870.10815, 'acc': 0.787109, time: 1.508
2025-05-31 05:16:20,076-INFO: epoch: 86, iter: 67800, lr: 0.000010, 'loss': 669.44006, 'acc': 0.775391, time: 1.507
2025-05-31 05:18:50,797-INFO: epoch: 86, iter: 67900, lr: 0.000010, 'loss': 783.9906, 'acc': 0.777344, time: 1.508
2025-05-31 05:21:21,345-INFO: epoch: 86, iter: 68000, lr: 0.000010, 'loss': 732.573, 'acc': 0.779297, time: 1.504
2025-05-31 05:23:51,908-INFO: epoch: 86, iter: 68100, lr: 0.000010, 'loss': 769.8691, 'acc': 0.777344, time: 1.503
2025-05-31 05:26:21,712-INFO: epoch: 86, iter: 68200, lr: 0.000010, 'loss': 782.65186, 'acc': 0.763672, time: 1.241
2025-05-31 05:26:33,660-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 05:29:04,131-INFO: epoch: 87, iter: 68300, lr: 0.000010, 'loss': 756.3049, 'acc': 0.78125, time: 1.509
2025-05-31 05:31:34,803-INFO: epoch: 87, iter: 68400, lr: 0.000010, 'loss': 656.74023, 'acc': 0.783203, time: 1.508
2025-05-31 05:32:17,915-INFO: Test iter: 68400, acc:0.745068, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 05:34:48,602-INFO: epoch: 87, iter: 68500, lr: 0.000010, 'loss': 681.04736, 'acc': 0.765625, time: 1.506
2025-05-31 05:37:19,275-INFO: epoch: 87, iter: 68600, lr: 0.000010, 'loss': 690.78375, 'acc': 0.785156, time: 1.507
2025-05-31 05:39:49,862-INFO: epoch: 87, iter: 68700, lr: 0.000010, 'loss': 743.69934, 'acc': 0.769531, time: 1.510
2025-05-31 05:42:20,488-INFO: epoch: 87, iter: 68800, lr: 0.000010, 'loss': 768.17303, 'acc': 0.765625, time: 1.505
2025-05-31 05:44:51,019-INFO: epoch: 87, iter: 68900, lr: 0.000010, 'loss': 852.24817, 'acc': 0.783203, time: 1.505
2025-05-31 05:47:08,655-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 05:47:25,428-INFO: epoch: 88, iter: 69000, lr: 0.000010, 'loss': 758.3657, 'acc': 0.76722, time: 1.584
2025-05-31 05:50:03,459-INFO: epoch: 88, iter: 69100, lr: 0.000010, 'loss': 821.5426, 'acc': 0.757812, time: 1.507
2025-05-31 05:52:34,063-INFO: epoch: 88, iter: 69200, lr: 0.000010, 'loss': 699.592, 'acc': 0.779297, time: 1.508
2025-05-31 05:55:04,560-INFO: epoch: 88, iter: 69300, lr: 0.000010, 'loss': 774.34393, 'acc': 0.78125, time: 1.510
2025-05-31 05:57:35,163-INFO: epoch: 88, iter: 69400, lr: 0.000010, 'loss': 817.7196, 'acc': 0.761719, time: 1.507
2025-05-31 06:00:05,771-INFO: epoch: 88, iter: 69500, lr: 0.000010, 'loss': 786.5346, 'acc': 0.771484, time: 1.510
2025-05-31 06:02:36,299-INFO: epoch: 88, iter: 69600, lr: 0.000010, 'loss': 652.66565, 'acc': 0.78125, time: 1.508
2025-05-31 06:05:06,897-INFO: epoch: 88, iter: 69700, lr: 0.000010, 'loss': 845.5615, 'acc': 0.765625, time: 1.503
2025-05-31 06:07:00,695-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 06:07:42,932-INFO: epoch: 89, iter: 69800, lr: 0.000010, 'loss': 762.2389, 'acc': 0.773438, time: 1.600
2025-05-31 06:10:19,290-INFO: epoch: 89, iter: 69900, lr: 0.000010, 'loss': 758.52454, 'acc': 0.769531, time: 1.504
2025-05-31 06:12:49,936-INFO: epoch: 89, iter: 70000, lr: 0.000010, 'loss': 713.919, 'acc': 0.775391, time: 1.501
2025-05-31 06:15:20,462-INFO: epoch: 89, iter: 70100, lr: 0.000010, 'loss': 738.21814, 'acc': 0.769531, time: 1.501
2025-05-31 06:17:51,099-INFO: epoch: 89, iter: 70200, lr: 0.000010, 'loss': 754.43097, 'acc': 0.777344, time: 1.503
2025-05-31 06:18:34,113-INFO: Test iter: 70200, acc:0.745732, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 06:21:04,761-INFO: epoch: 89, iter: 70300, lr: 0.000010, 'loss': 702.9273, 'acc': 0.777344, time: 1.508
2025-05-31 06:23:35,422-INFO: epoch: 89, iter: 70400, lr: 0.000010, 'loss': 733.7002, 'acc': 0.767578, time: 1.507
2025-05-31 06:26:06,079-INFO: epoch: 89, iter: 70500, lr: 0.000010, 'loss': 825.9903, 'acc': 0.771484, time: 1.503
2025-05-31 06:27:35,459-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 06:28:43,228-INFO: epoch: 90, iter: 70600, lr: 0.000010, 'loss': 686.6317, 'acc': 0.777344, time: 1.600
2025-05-31 06:31:18,162-INFO: epoch: 90, iter: 70700, lr: 0.000010, 'loss': 707.29126, 'acc': 0.78125, time: 1.507
2025-05-31 06:33:48,837-INFO: epoch: 90, iter: 70800, lr: 0.000010, 'loss': 820.9489, 'acc': 0.769531, time: 1.507
2025-05-31 06:36:19,350-INFO: epoch: 90, iter: 70900, lr: 0.000010, 'loss': 735.0083, 'acc': 0.777344, time: 1.509
2025-05-31 06:38:49,987-INFO: epoch: 90, iter: 71000, lr: 0.000010, 'loss': 787.82983, 'acc': 0.771484, time: 1.508
2025-05-31 06:41:20,552-INFO: epoch: 90, iter: 71100, lr: 0.000010, 'loss': 736.17896, 'acc': 0.769531, time: 1.504
2025-05-31 06:43:51,199-INFO: epoch: 90, iter: 71200, lr: 0.000010, 'loss': 756.745, 'acc': 0.785156, time: 1.504
2025-05-31 06:46:21,779-INFO: epoch: 90, iter: 71300, lr: 0.000010, 'loss': 776.6343, 'acc': 0.777344, time: 1.511
2025-05-31 06:47:27,191-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 06:49:00,827-INFO: epoch: 91, iter: 71400, lr: 0.000010, 'loss': 812.8438, 'acc': 0.777344, time: 1.600
2025-05-31 06:51:34,312-INFO: epoch: 91, iter: 71500, lr: 0.000010, 'loss': 672.1523, 'acc': 0.775391, time: 1.504
2025-05-31 06:54:04,957-INFO: epoch: 91, iter: 71600, lr: 0.000010, 'loss': 764.4419, 'acc': 0.785156, time: 1.506
2025-05-31 06:56:35,556-INFO: epoch: 91, iter: 71700, lr: 0.000010, 'loss': 775.03265, 'acc': 0.767578, time: 1.507
2025-05-31 06:59:06,166-INFO: epoch: 91, iter: 71800, lr: 0.000010, 'loss': 812.4837, 'acc': 0.785156, time: 1.502
2025-05-31 07:01:36,923-INFO: epoch: 91, iter: 71900, lr: 0.000010, 'loss': 720.36914, 'acc': 0.767578, time: 1.504
2025-05-31 07:04:07,522-INFO: epoch: 91, iter: 72000, lr: 0.000010, 'loss': 802.402, 'acc': 0.785156, time: 1.503
2025-05-31 07:04:50,953-INFO: Test iter: 72000, acc:0.749715, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 07:07:21,450-INFO: epoch: 91, iter: 72100, lr: 0.000010, 'loss': 773.5663, 'acc': 0.773438, time: 1.506
2025-05-31 07:08:02,692-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 07:10:01,928-INFO: epoch: 92, iter: 72200, lr: 0.000010, 'loss': 757.82874, 'acc': 0.777344, time: 1.600
2025-05-31 07:12:33,776-INFO: epoch: 92, iter: 72300, lr: 0.000010, 'loss': 772.2261, 'acc': 0.773438, time: 1.505
2025-05-31 07:15:04,563-INFO: epoch: 92, iter: 72400, lr: 0.000010, 'loss': 832.2197, 'acc': 0.771484, time: 1.506
2025-05-31 07:17:35,189-INFO: epoch: 92, iter: 72500, lr: 0.000010, 'loss': 799.5083, 'acc': 0.785156, time: 1.503
2025-05-31 07:20:05,866-INFO: epoch: 92, iter: 72600, lr: 0.000010, 'loss': 765.4785, 'acc': 0.769531, time: 1.506
2025-05-31 07:22:36,458-INFO: epoch: 92, iter: 72700, lr: 0.000010, 'loss': 789.4176, 'acc': 0.777344, time: 1.505
2025-05-31 07:25:07,185-INFO: epoch: 92, iter: 72800, lr: 0.000010, 'loss': 720.50146, 'acc': 0.767578, time: 1.507
2025-05-31 07:27:37,533-INFO: epoch: 92, iter: 72900, lr: 0.000010, 'loss': 662.4402, 'acc': 0.783203, time: 1.506
2025-05-31 07:27:54,966-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 07:30:19,450-INFO: epoch: 93, iter: 73000, lr: 0.000010, 'loss': 734.2639, 'acc': 0.773438, time: 1.507
2025-05-31 07:32:50,176-INFO: epoch: 93, iter: 73100, lr: 0.000010, 'loss': 757.0546, 'acc': 0.779297, time: 1.510
2025-05-31 07:35:20,787-INFO: epoch: 93, iter: 73200, lr: 0.000010, 'loss': 786.3181, 'acc': 0.769531, time: 1.503
2025-05-31 07:37:51,375-INFO: epoch: 93, iter: 73300, lr: 0.000010, 'loss': 856.0951, 'acc': 0.763672, time: 1.504
2025-05-31 07:40:21,968-INFO: epoch: 93, iter: 73400, lr: 0.000010, 'loss': 770.1427, 'acc': 0.775391, time: 1.509
2025-05-31 07:42:52,538-INFO: epoch: 93, iter: 73500, lr: 0.000010, 'loss': 800.14874, 'acc': 0.785156, time: 1.504
2025-05-31 07:45:23,175-INFO: epoch: 93, iter: 73600, lr: 0.000010, 'loss': 762.60657, 'acc': 0.765625, time: 1.507
2025-05-31 07:47:47,115-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 07:47:57,228-INFO: epoch: 94, iter: 73700, lr: 0.000010, 'loss': 634.64404, 'acc': 0.783573, time: 1.599
2025-05-31 07:50:35,665-INFO: epoch: 94, iter: 73800, lr: 0.000010, 'loss': 776.74646, 'acc': 0.769531, time: 1.505
2025-05-31 07:51:18,702-INFO: Test iter: 73800, acc:0.744499, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 07:53:49,217-INFO: epoch: 94, iter: 73900, lr: 0.000010, 'loss': 786.5563, 'acc': 0.785156, time: 1.505
2025-05-31 07:56:19,794-INFO: epoch: 94, iter: 74000, lr: 0.000010, 'loss': 810.491, 'acc': 0.78125, time: 1.506
2025-05-31 07:58:50,334-INFO: epoch: 94, iter: 74100, lr: 0.000010, 'loss': 750.77985, 'acc': 0.785156, time: 1.511
2025-05-31 08:01:20,981-INFO: epoch: 94, iter: 74200, lr: 0.000010, 'loss': 760.8955, 'acc': 0.777344, time: 1.506
2025-05-31 08:03:51,506-INFO: epoch: 94, iter: 74300, lr: 0.000010, 'loss': 778.546, 'acc': 0.783203, time: 1.505
2025-05-31 08:06:22,021-INFO: epoch: 94, iter: 74400, lr: 0.000010, 'loss': 707.06, 'acc': 0.783203, time: 1.504
2025-05-31 08:08:21,549-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 08:08:57,429-INFO: epoch: 95, iter: 74500, lr: 0.000010, 'loss': 762.2744, 'acc': 0.767578, time: 1.601
2025-05-31 08:11:34,039-INFO: epoch: 95, iter: 74600, lr: 0.000010, 'loss': 718.3966, 'acc': 0.777344, time: 1.501
2025-05-31 08:14:04,077-INFO: epoch: 95, iter: 74700, lr: 0.000010, 'loss': 726.4803, 'acc': 0.777344, time: 1.499
2025-05-31 08:16:33,930-INFO: epoch: 95, iter: 74800, lr: 0.000010, 'loss': 650.1878, 'acc': 0.785156, time: 1.502
2025-05-31 08:19:03,705-INFO: epoch: 95, iter: 74900, lr: 0.000010, 'loss': 781.8801, 'acc': 0.777344, time: 1.494
2025-05-31 08:21:33,464-INFO: epoch: 95, iter: 75000, lr: 0.000010, 'loss': 744.2808, 'acc': 0.769531, time: 1.496
2025-05-31 08:24:03,225-INFO: epoch: 95, iter: 75100, lr: 0.000010, 'loss': 743.3024, 'acc': 0.78125, time: 1.498
2025-05-31 08:26:33,006-INFO: epoch: 95, iter: 75200, lr: 0.000010, 'loss': 805.4026, 'acc': 0.769531, time: 1.502
2025-05-31 08:28:08,071-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 08:29:09,323-INFO: epoch: 96, iter: 75300, lr: 0.000010, 'loss': 786.3525, 'acc': 0.769531, time: 1.599
2025-05-31 08:31:44,063-INFO: epoch: 96, iter: 75400, lr: 0.000010, 'loss': 793.8599, 'acc': 0.78125, time: 1.494
2025-05-31 08:34:13,520-INFO: epoch: 96, iter: 75500, lr: 0.000010, 'loss': 747.10913, 'acc': 0.767578, time: 1.496
2025-05-31 08:36:42,946-INFO: epoch: 96, iter: 75600, lr: 0.000010, 'loss': 772.25684, 'acc': 0.779297, time: 1.495
2025-05-31 08:37:25,792-INFO: Test iter: 75600, acc:0.747534, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 08:39:54,982-INFO: epoch: 96, iter: 75700, lr: 0.000010, 'loss': 684.5333, 'acc': 0.785156, time: 1.497
2025-05-31 08:42:24,405-INFO: epoch: 96, iter: 75800, lr: 0.000010, 'loss': 762.86566, 'acc': 0.787109, time: 1.497
2025-05-31 08:44:53,831-INFO: epoch: 96, iter: 75900, lr: 0.000010, 'loss': 813.5812, 'acc': 0.773438, time: 1.493
2025-05-31 08:47:23,255-INFO: epoch: 96, iter: 76000, lr: 0.000010, 'loss': 862.90674, 'acc': 0.779297, time: 1.494
2025-05-31 08:48:34,155-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 08:50:01,328-INFO: epoch: 97, iter: 76100, lr: 0.000010, 'loss': 779.16895, 'acc': 0.767578, time: 1.601
2025-05-31 08:52:35,018-INFO: epoch: 97, iter: 76200, lr: 0.000010, 'loss': 720.7589, 'acc': 0.771484, time: 1.507
2025-05-31 08:55:05,568-INFO: epoch: 97, iter: 76300, lr: 0.000010, 'loss': 743.00525, 'acc': 0.775391, time: 1.509
2025-05-31 08:57:36,048-INFO: epoch: 97, iter: 76400, lr: 0.000010, 'loss': 667.4888, 'acc': 0.775391, time: 1.505
2025-05-31 09:00:06,582-INFO: epoch: 97, iter: 76500, lr: 0.000010, 'loss': 678.5835, 'acc': 0.771484, time: 1.505
2025-05-31 09:02:37,138-INFO: epoch: 97, iter: 76600, lr: 0.000010, 'loss': 720.9004, 'acc': 0.78125, time: 1.503
2025-05-31 09:05:07,637-INFO: epoch: 97, iter: 76700, lr: 0.000010, 'loss': 683.0383, 'acc': 0.777344, time: 1.506
2025-05-31 09:07:38,278-INFO: epoch: 97, iter: 76800, lr: 0.000010, 'loss': 792.67175, 'acc': 0.779297, time: 1.506
2025-05-31 09:08:25,535-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 09:10:18,428-INFO: epoch: 98, iter: 76900, lr: 0.000010, 'loss': 734.9844, 'acc': 0.767578, time: 1.597
2025-05-31 09:12:50,620-INFO: epoch: 98, iter: 77000, lr: 0.000010, 'loss': 712.31305, 'acc': 0.773438, time: 1.510
2025-05-31 09:15:21,119-INFO: epoch: 98, iter: 77100, lr: 0.000010, 'loss': 771.02026, 'acc': 0.792969, time: 1.504
2025-05-31 09:17:51,633-INFO: epoch: 98, iter: 77200, lr: 0.000010, 'loss': 720.03186, 'acc': 0.779297, time: 1.506
2025-05-31 09:20:22,199-INFO: epoch: 98, iter: 77300, lr: 0.000010, 'loss': 790.9592, 'acc': 0.777344, time: 1.504
2025-05-31 09:22:52,782-INFO: epoch: 98, iter: 77400, lr: 0.000010, 'loss': 634.83734, 'acc': 0.771484, time: 1.503
2025-05-31 09:23:35,918-INFO: Test iter: 77400, acc:0.743266, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 09:26:06,384-INFO: epoch: 98, iter: 77500, lr: 0.000010, 'loss': 725.41705, 'acc': 0.777344, time: 1.505
2025-05-31 09:28:36,820-INFO: epoch: 98, iter: 77600, lr: 0.000010, 'loss': 798.948, 'acc': 0.771484, time: 1.506
2025-05-31 09:29:00,159-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 09:31:18,325-INFO: epoch: 99, iter: 77700, lr: 0.000010, 'loss': 738.0316, 'acc': 0.773438, time: 1.597
2025-05-31 09:33:48,934-INFO: epoch: 99, iter: 77800, lr: 0.000010, 'loss': 751.62, 'acc': 0.767578, time: 1.505
2025-05-31 09:36:19,461-INFO: epoch: 99, iter: 77900, lr: 0.000010, 'loss': 757.50006, 'acc': 0.771484, time: 1.503
2025-05-31 09:38:49,967-INFO: epoch: 99, iter: 78000, lr: 0.000010, 'loss': 742.39355, 'acc': 0.773438, time: 1.502
2025-05-31 09:41:20,445-INFO: epoch: 99, iter: 78100, lr: 0.000010, 'loss': 763.15674, 'acc': 0.779297, time: 1.502
2025-05-31 09:43:50,914-INFO: epoch: 99, iter: 78200, lr: 0.000010, 'loss': 706.4013, 'acc': 0.771484, time: 1.510
2025-05-31 09:46:21,478-INFO: epoch: 99, iter: 78300, lr: 0.000010, 'loss': 684.69403, 'acc': 0.792969, time: 1.511
2025-05-31 09:48:51,140-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 09:48:54,831-INFO: epoch: 100, iter: 78400, lr: 0.000010, 'loss': 654.5953, 'acc': 0.773438, time: 3.689
2025-05-31 09:51:33,636-INFO: epoch: 100, iter: 78500, lr: 0.000010, 'loss': 787.89514, 'acc': 0.771484, time: 1.508
2025-05-31 09:54:04,203-INFO: epoch: 100, iter: 78600, lr: 0.000010, 'loss': 794.891, 'acc': 0.783203, time: 1.503
2025-05-31 09:56:34,773-INFO: epoch: 100, iter: 78700, lr: 0.000010, 'loss': 717.28925, 'acc': 0.792969, time: 1.506
2025-05-31 09:59:05,276-INFO: epoch: 100, iter: 78800, lr: 0.000010, 'loss': 720.94604, 'acc': 0.78125, time: 1.505
2025-05-31 10:01:35,825-INFO: epoch: 100, iter: 78900, lr: 0.000010, 'loss': 711.34186, 'acc': 0.78125, time: 1.507
2025-05-31 10:04:06,375-INFO: epoch: 100, iter: 79000, lr: 0.000010, 'loss': 708.94507, 'acc': 0.777344, time: 1.505
2025-05-31 10:06:36,897-INFO: epoch: 100, iter: 79100, lr: 0.000010, 'loss': 842.1647, 'acc': 0.765625, time: 1.506
2025-05-31 10:08:42,465-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 10:09:11,929-INFO: epoch: 101, iter: 79200, lr: 0.000010, 'loss': 689.8788, 'acc': 0.776767, time: 1.602
2025-05-31 10:10:31,623-INFO: Test iter: 79200, acc:0.744973, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 10:13:03,795-INFO: epoch: 101, iter: 79300, lr: 0.000010, 'loss': 647.0427, 'acc': 0.783203, time: 1.509
2025-05-31 10:15:34,421-INFO: epoch: 101, iter: 79400, lr: 0.000010, 'loss': 786.0249, 'acc': 0.761719, time: 1.502
2025-05-31 10:18:05,001-INFO: epoch: 101, iter: 79500, lr: 0.000010, 'loss': 774.34033, 'acc': 0.791016, time: 1.503
2025-05-31 10:20:35,505-INFO: epoch: 101, iter: 79600, lr: 0.000010, 'loss': 778.6283, 'acc': 0.775391, time: 1.506
2025-05-31 10:23:06,060-INFO: epoch: 101, iter: 79700, lr: 0.000010, 'loss': 752.6593, 'acc': 0.777344, time: 1.510
2025-05-31 10:25:36,615-INFO: epoch: 101, iter: 79800, lr: 0.000010, 'loss': 686.3369, 'acc': 0.791016, time: 1.505
2025-05-31 10:28:07,101-INFO: epoch: 101, iter: 79900, lr: 0.000010, 'loss': 751.3617, 'acc': 0.78125, time: 1.505
2025-05-31 10:29:48,717-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 10:30:43,832-INFO: epoch: 102, iter: 80000, lr: 0.000010, 'loss': 767.90356, 'acc': 0.779297, time: 1.603
2025-05-31 10:33:19,510-INFO: epoch: 102, iter: 80100, lr: 0.000010, 'loss': 801.8423, 'acc': 0.773438, time: 1.506
2025-05-31 10:35:50,074-INFO: epoch: 102, iter: 80200, lr: 0.000010, 'loss': 749.049, 'acc': 0.777344, time: 1.507
2025-05-31 10:38:20,629-INFO: epoch: 102, iter: 80300, lr: 0.000010, 'loss': 818.3783, 'acc': 0.769531, time: 1.502
2025-05-31 10:40:51,166-INFO: epoch: 102, iter: 80400, lr: 0.000010, 'loss': 740.281, 'acc': 0.787109, time: 1.506
2025-05-31 10:43:21,715-INFO: epoch: 102, iter: 80500, lr: 0.000010, 'loss': 724.90717, 'acc': 0.779297, time: 1.510
2025-05-31 10:45:52,235-INFO: epoch: 102, iter: 80600, lr: 0.000010, 'loss': 791.6231, 'acc': 0.791016, time: 1.502
2025-05-31 10:48:22,766-INFO: epoch: 102, iter: 80700, lr: 0.000010, 'loss': 702.6991, 'acc': 0.789062, time: 1.508
2025-05-31 10:49:40,251-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 10:51:01,128-INFO: epoch: 103, iter: 80800, lr: 0.000010, 'loss': 745.4491, 'acc': 0.78125, time: 1.600
2025-05-31 10:53:35,127-INFO: epoch: 103, iter: 80900, lr: 0.000010, 'loss': 758.3841, 'acc': 0.777344, time: 1.506
2025-05-31 10:56:05,694-INFO: epoch: 103, iter: 81000, lr: 0.000010, 'loss': 728.9217, 'acc': 0.779297, time: 1.502
2025-05-31 10:56:48,515-INFO: Test iter: 81000, acc:0.745827, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 10:59:19,019-INFO: epoch: 103, iter: 81100, lr: 0.000010, 'loss': 770.4907, 'acc': 0.773438, time: 1.503
2025-05-31 11:01:49,545-INFO: epoch: 103, iter: 81200, lr: 0.000010, 'loss': 738.6574, 'acc': 0.783203, time: 1.509
2025-05-31 11:04:20,077-INFO: epoch: 103, iter: 81300, lr: 0.000010, 'loss': 827.229, 'acc': 0.769531, time: 1.505
2025-05-31 11:06:50,601-INFO: epoch: 103, iter: 81400, lr: 0.000010, 'loss': 810.6865, 'acc': 0.777344, time: 1.508
2025-05-31 11:09:21,045-INFO: epoch: 103, iter: 81500, lr: 0.000010, 'loss': 733.6402, 'acc': 0.773438, time: 1.510
2025-05-31 11:10:14,456-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 11:12:00,928-INFO: epoch: 104, iter: 81600, lr: 0.000010, 'loss': 836.1894, 'acc': 0.775391, time: 1.600
2025-05-31 11:14:33,452-INFO: epoch: 104, iter: 81700, lr: 0.000010, 'loss': 716.20276, 'acc': 0.763672, time: 1.502
2025-05-31 11:17:03,983-INFO: epoch: 104, iter: 81800, lr: 0.000010, 'loss': 759.4098, 'acc': 0.78125, time: 1.505
2025-05-31 11:19:34,522-INFO: epoch: 104, iter: 81900, lr: 0.000010, 'loss': 710.24097, 'acc': 0.779297, time: 1.504
2025-05-31 11:22:05,018-INFO: epoch: 104, iter: 82000, lr: 0.000010, 'loss': 700.3512, 'acc': 0.791016, time: 1.506
2025-05-31 11:24:35,555-INFO: epoch: 104, iter: 82100, lr: 0.000010, 'loss': 817.2369, 'acc': 0.78125, time: 1.502
2025-05-31 11:27:06,031-INFO: epoch: 104, iter: 82200, lr: 0.000010, 'loss': 735.25793, 'acc': 0.777344, time: 1.509
2025-05-31 11:29:36,663-INFO: epoch: 104, iter: 82300, lr: 0.000010, 'loss': 778.7717, 'acc': 0.775391, time: 1.506
2025-05-31 11:30:06,133-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 11:32:18,028-INFO: epoch: 105, iter: 82400, lr: 0.000010, 'loss': 797.82153, 'acc': 0.779297, time: 1.601
2025-05-31 11:34:49,053-INFO: epoch: 105, iter: 82500, lr: 0.000010, 'loss': 815.9928, 'acc': 0.773438, time: 1.505
2025-05-31 11:37:19,611-INFO: epoch: 105, iter: 82600, lr: 0.000010, 'loss': 769.0526, 'acc': 0.779297, time: 1.507
2025-05-31 11:39:50,029-INFO: epoch: 105, iter: 82700, lr: 0.000010, 'loss': 787.18695, 'acc': 0.775391, time: 1.501
2025-05-31 11:42:20,540-INFO: epoch: 105, iter: 82800, lr: 0.000010, 'loss': 718.734, 'acc': 0.767578, time: 1.508
2025-05-31 11:43:03,546-INFO: Test iter: 82800, acc:0.745258, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 11:45:33,984-INFO: epoch: 105, iter: 82900, lr: 0.000010, 'loss': 731.97205, 'acc': 0.789062, time: 1.503
2025-05-31 11:48:04,526-INFO: epoch: 105, iter: 83000, lr: 0.000010, 'loss': 775.74774, 'acc': 0.775391, time: 1.503
2025-05-31 11:50:33,729-INFO: epoch: 105, iter: 83100, lr: 0.000010, 'loss': 686.9553, 'acc': 0.783203, time: 1.245
2025-05-31 11:50:40,309-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 11:53:16,762-INFO: epoch: 106, iter: 83200, lr: 0.000010, 'loss': 735.6865, 'acc': 0.773438, time: 1.505
2025-05-31 11:55:47,291-INFO: epoch: 106, iter: 83300, lr: 0.000010, 'loss': 690.4821, 'acc': 0.78125, time: 1.503
2025-05-31 11:58:17,825-INFO: epoch: 106, iter: 83400, lr: 0.000010, 'loss': 721.96814, 'acc': 0.787109, time: 1.505
2025-05-31 12:00:48,273-INFO: epoch: 106, iter: 83500, lr: 0.000010, 'loss': 687.9638, 'acc': 0.787109, time: 1.502
2025-05-31 12:03:18,769-INFO: epoch: 106, iter: 83600, lr: 0.000010, 'loss': 755.6626, 'acc': 0.765625, time: 1.508
2025-05-31 12:05:49,308-INFO: epoch: 106, iter: 83700, lr: 0.000010, 'loss': 709.4296, 'acc': 0.783203, time: 1.507
2025-05-31 12:08:19,857-INFO: epoch: 106, iter: 83800, lr: 0.000010, 'loss': 755.9047, 'acc': 0.789062, time: 1.502
2025-05-31 12:10:31,508-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 12:10:54,550-INFO: epoch: 107, iter: 83900, lr: 0.000010, 'loss': 639.81195, 'acc': 0.787109, time: 1.621
2025-05-31 12:13:32,010-INFO: epoch: 107, iter: 84000, lr: 0.000010, 'loss': 656.662, 'acc': 0.796875, time: 1.504
2025-05-31 12:16:02,558-INFO: epoch: 107, iter: 84100, lr: 0.000010, 'loss': 729.3135, 'acc': 0.773438, time: 1.502
2025-05-31 12:18:33,057-INFO: epoch: 107, iter: 84200, lr: 0.000010, 'loss': 725.31573, 'acc': 0.789062, time: 1.507
2025-05-31 12:21:03,626-INFO: epoch: 107, iter: 84300, lr: 0.000010, 'loss': 754.9436, 'acc': 0.785156, time: 1.500
2025-05-31 12:23:34,116-INFO: epoch: 107, iter: 84400, lr: 0.000010, 'loss': 720.1361, 'acc': 0.78125, time: 1.507
2025-05-31 12:26:04,634-INFO: epoch: 107, iter: 84500, lr: 0.000010, 'loss': 718.4946, 'acc': 0.767578, time: 1.503
2025-05-31 12:28:35,212-INFO: epoch: 107, iter: 84600, lr: 0.000010, 'loss': 717.5338, 'acc': 0.773438, time: 1.506
2025-05-31 12:29:18,102-INFO: Test iter: 84600, acc:0.743266, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 12:31:05,500-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 12:31:54,728-INFO: epoch: 108, iter: 84700, lr: 0.000010, 'loss': 699.2783, 'acc': 0.771484, time: 1.600
2025-05-31 12:34:30,742-INFO: epoch: 108, iter: 84800, lr: 0.000010, 'loss': 806.93884, 'acc': 0.773438, time: 1.506
2025-05-31 12:37:01,253-INFO: epoch: 108, iter: 84900, lr: 0.000010, 'loss': 665.06335, 'acc': 0.775391, time: 1.506
2025-05-31 12:39:31,797-INFO: epoch: 108, iter: 85000, lr: 0.000010, 'loss': 765.65173, 'acc': 0.783203, time: 1.504
2025-05-31 12:42:02,296-INFO: epoch: 108, iter: 85100, lr: 0.000010, 'loss': 807.5587, 'acc': 0.783203, time: 1.500
2025-05-31 12:44:32,887-INFO: epoch: 108, iter: 85200, lr: 0.000010, 'loss': 707.85675, 'acc': 0.789062, time: 1.505
2025-05-31 12:47:03,768-INFO: epoch: 108, iter: 85300, lr: 0.000010, 'loss': 747.6273, 'acc': 0.791016, time: 1.511
2025-05-31 12:49:35,108-INFO: epoch: 108, iter: 85400, lr: 0.000010, 'loss': 799.57526, 'acc': 0.777344, time: 1.514
2025-05-31 12:50:58,973-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 12:52:13,228-INFO: epoch: 109, iter: 85500, lr: 0.000010, 'loss': 749.0958, 'acc': 0.773438, time: 1.600
2025-05-31 12:54:48,120-INFO: epoch: 109, iter: 85600, lr: 0.000010, 'loss': 742.2565, 'acc': 0.783203, time: 1.512
2025-05-31 12:57:19,485-INFO: epoch: 109, iter: 85700, lr: 0.000010, 'loss': 765.98096, 'acc': 0.769531, time: 1.514
2025-05-31 12:59:50,808-INFO: epoch: 109, iter: 85800, lr: 0.000010, 'loss': 748.8552, 'acc': 0.783203, time: 1.509
2025-05-31 13:02:22,052-INFO: epoch: 109, iter: 85900, lr: 0.000010, 'loss': 720.9272, 'acc': 0.783203, time: 1.509
2025-05-31 13:04:53,393-INFO: epoch: 109, iter: 86000, lr: 0.000010, 'loss': 774.6081, 'acc': 0.773438, time: 1.519
2025-05-31 13:07:24,764-INFO: epoch: 109, iter: 86100, lr: 0.000010, 'loss': 734.9338, 'acc': 0.771484, time: 1.513
2025-05-31 13:09:56,086-INFO: epoch: 109, iter: 86200, lr: 0.000010, 'loss': 749.68616, 'acc': 0.775391, time: 1.512
2025-05-31 13:10:56,790-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 13:12:36,828-INFO: epoch: 110, iter: 86300, lr: 0.000010, 'loss': 766.793, 'acc': 0.777344, time: 1.599
2025-05-31 13:15:10,420-INFO: epoch: 110, iter: 86400, lr: 0.000010, 'loss': 737.38196, 'acc': 0.78125, time: 1.512
2025-05-31 13:15:53,448-INFO: Test iter: 86400, acc:0.740326, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 13:18:24,402-INFO: epoch: 110, iter: 86500, lr: 0.000010, 'loss': 744.6538, 'acc': 0.779297, time: 1.516
2025-05-31 13:20:55,460-INFO: epoch: 110, iter: 86600, lr: 0.000010, 'loss': 702.1681, 'acc': 0.779297, time: 1.507
2025-05-31 13:23:26,316-INFO: epoch: 110, iter: 86700, lr: 0.000010, 'loss': 770.31995, 'acc': 0.787109, time: 1.508
2025-05-31 13:25:57,067-INFO: epoch: 110, iter: 86800, lr: 0.000010, 'loss': 715.5343, 'acc': 0.777344, time: 1.511
2025-05-31 13:28:27,805-INFO: epoch: 110, iter: 86900, lr: 0.000010, 'loss': 772.28253, 'acc': 0.775391, time: 1.508
2025-05-31 13:30:58,680-INFO: epoch: 110, iter: 87000, lr: 0.000010, 'loss': 831.5389, 'acc': 0.773438, time: 1.508
2025-05-31 13:31:33,985-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 13:33:39,328-INFO: epoch: 111, iter: 87100, lr: 0.000010, 'loss': 702.5831, 'acc': 0.777344, time: 1.600
2025-05-31 13:36:11,009-INFO: epoch: 111, iter: 87200, lr: 0.000010, 'loss': 714.77936, 'acc': 0.773438, time: 1.507
2025-05-31 13:38:41,675-INFO: epoch: 111, iter: 87300, lr: 0.000010, 'loss': 800.1779, 'acc': 0.771484, time: 1.506
2025-05-31 13:41:12,343-INFO: epoch: 111, iter: 87400, lr: 0.000010, 'loss': 715.327, 'acc': 0.791016, time: 1.507
2025-05-31 13:43:43,043-INFO: epoch: 111, iter: 87500, lr: 0.000010, 'loss': 820.1315, 'acc': 0.775391, time: 1.512
2025-05-31 13:46:13,691-INFO: epoch: 111, iter: 87600, lr: 0.000010, 'loss': 733.7456, 'acc': 0.777344, time: 1.505
2025-05-31 13:48:44,392-INFO: epoch: 111, iter: 87700, lr: 0.000010, 'loss': 722.5994, 'acc': 0.783203, time: 1.506
2025-05-31 13:51:14,475-INFO: epoch: 111, iter: 87800, lr: 0.000010, 'loss': 688.6823, 'acc': 0.789062, time: 1.503
2025-05-31 13:51:26,788-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 13:53:57,422-INFO: epoch: 112, iter: 87900, lr: 0.000010, 'loss': 772.8824, 'acc': 0.777344, time: 1.510
2025-05-31 13:56:28,014-INFO: epoch: 112, iter: 88000, lr: 0.000010, 'loss': 740.9795, 'acc': 0.783203, time: 1.509
2025-05-31 13:58:58,689-INFO: epoch: 112, iter: 88100, lr: 0.000010, 'loss': 669.8073, 'acc': 0.789062, time: 1.504
2025-05-31 14:01:29,340-INFO: epoch: 112, iter: 88200, lr: 0.000010, 'loss': 749.3363, 'acc': 0.769531, time: 1.513
2025-05-31 14:02:12,851-INFO: Test iter: 88200, acc:0.743930, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 14:04:43,268-INFO: epoch: 112, iter: 88300, lr: 0.000010, 'loss': 840.53735, 'acc': 0.779297, time: 1.505
2025-05-31 14:07:13,869-INFO: epoch: 112, iter: 88400, lr: 0.000010, 'loss': 640.32526, 'acc': 0.800781, time: 1.509
2025-05-31 14:09:44,462-INFO: epoch: 112, iter: 88500, lr: 0.000010, 'loss': 671.3767, 'acc': 0.785156, time: 1.504
2025-05-31 14:12:02,292-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 14:12:19,228-INFO: epoch: 113, iter: 88600, lr: 0.000010, 'loss': 739.70825, 'acc': 0.763033, time: 1.672
2025-05-31 14:14:57,198-INFO: epoch: 113, iter: 88700, lr: 0.000010, 'loss': 756.7597, 'acc': 0.785156, time: 1.507
2025-05-31 14:17:27,777-INFO: epoch: 113, iter: 88800, lr: 0.000010, 'loss': 738.22437, 'acc': 0.777344, time: 1.507
2025-05-31 14:19:58,435-INFO: epoch: 113, iter: 88900, lr: 0.000010, 'loss': 826.0126, 'acc': 0.779297, time: 1.507
2025-05-31 14:22:29,140-INFO: epoch: 113, iter: 89000, lr: 0.000010, 'loss': 694.5654, 'acc': 0.775391, time: 1.507
2025-05-31 14:24:59,748-INFO: epoch: 113, iter: 89100, lr: 0.000010, 'loss': 770.29443, 'acc': 0.767578, time: 1.503
2025-05-31 14:27:30,425-INFO: epoch: 113, iter: 89200, lr: 0.000010, 'loss': 668.3689, 'acc': 0.783203, time: 1.506
2025-05-31 14:30:01,055-INFO: epoch: 113, iter: 89300, lr: 0.000010, 'loss': 709.6771, 'acc': 0.787109, time: 1.507
2025-05-31 14:31:54,917-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 14:32:37,329-INFO: epoch: 114, iter: 89400, lr: 0.000010, 'loss': 793.5533, 'acc': 0.787109, time: 1.601
2025-05-31 14:35:13,821-INFO: epoch: 114, iter: 89500, lr: 0.000010, 'loss': 785.9336, 'acc': 0.769531, time: 1.507
2025-05-31 14:37:44,409-INFO: epoch: 114, iter: 89600, lr: 0.000010, 'loss': 710.5088, 'acc': 0.779297, time: 1.507
2025-05-31 14:40:14,981-INFO: epoch: 114, iter: 89700, lr: 0.000010, 'loss': 802.39935, 'acc': 0.779297, time: 1.506
2025-05-31 14:42:45,665-INFO: epoch: 114, iter: 89800, lr: 0.000010, 'loss': 638.2144, 'acc': 0.791016, time: 1.507
2025-05-31 14:45:16,318-INFO: epoch: 114, iter: 89900, lr: 0.000010, 'loss': 808.4333, 'acc': 0.779297, time: 1.507
2025-05-31 14:47:46,949-INFO: epoch: 114, iter: 90000, lr: 0.000010, 'loss': 831.43304, 'acc': 0.759766, time: 1.505
2025-05-31 14:48:30,287-INFO: Test iter: 90000, acc:0.742223, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 14:51:00,676-INFO: epoch: 114, iter: 90100, lr: 0.000010, 'loss': 725.48303, 'acc': 0.777344, time: 1.506
2025-05-31 14:52:30,347-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 14:53:38,228-INFO: epoch: 115, iter: 90200, lr: 0.000010, 'loss': 708.12756, 'acc': 0.773438, time: 1.600
2025-05-31 14:56:13,289-INFO: epoch: 115, iter: 90300, lr: 0.000010, 'loss': 760.2054, 'acc': 0.78125, time: 1.506
2025-05-31 14:58:43,905-INFO: epoch: 115, iter: 90400, lr: 0.000010, 'loss': 846.70984, 'acc': 0.78125, time: 1.509
2025-05-31 15:01:14,553-INFO: epoch: 115, iter: 90500, lr: 0.000010, 'loss': 799.3527, 'acc': 0.777344, time: 1.504
2025-05-31 15:03:45,253-INFO: epoch: 115, iter: 90600, lr: 0.000010, 'loss': 689.0614, 'acc': 0.78125, time: 1.505
2025-05-31 15:06:15,988-INFO: epoch: 115, iter: 90700, lr: 0.000010, 'loss': 830.7285, 'acc': 0.765625, time: 1.508
2025-05-31 15:08:46,690-INFO: epoch: 115, iter: 90800, lr: 0.000010, 'loss': 782.3959, 'acc': 0.777344, time: 1.508
2025-05-31 15:11:17,408-INFO: epoch: 115, iter: 90900, lr: 0.000010, 'loss': 840.95734, 'acc': 0.765625, time: 1.507
2025-05-31 15:12:22,914-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 15:13:56,928-INFO: epoch: 116, iter: 91000, lr: 0.000010, 'loss': 762.3522, 'acc': 0.791016, time: 1.600
2025-05-31 15:16:30,516-INFO: epoch: 116, iter: 91100, lr: 0.000010, 'loss': 838.7588, 'acc': 0.777344, time: 1.509
2025-05-31 15:19:01,308-INFO: epoch: 116, iter: 91200, lr: 0.000010, 'loss': 798.1638, 'acc': 0.775391, time: 1.507
2025-05-31 15:21:32,004-INFO: epoch: 116, iter: 91300, lr: 0.000010, 'loss': 777.4186, 'acc': 0.779297, time: 1.503
2025-05-31 15:24:02,839-INFO: epoch: 116, iter: 91400, lr: 0.000010, 'loss': 702.73914, 'acc': 0.775391, time: 1.507
2025-05-31 15:26:33,628-INFO: epoch: 116, iter: 91500, lr: 0.000010, 'loss': 708.0011, 'acc': 0.791016, time: 1.506
2025-05-31 15:29:04,332-INFO: epoch: 116, iter: 91600, lr: 0.000010, 'loss': 811.1213, 'acc': 0.769531, time: 1.505
2025-05-31 15:31:35,104-INFO: epoch: 116, iter: 91700, lr: 0.000010, 'loss': 764.50757, 'acc': 0.787109, time: 1.510
2025-05-31 15:32:16,387-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 15:34:15,628-INFO: epoch: 117, iter: 91800, lr: 0.000010, 'loss': 817.8839, 'acc': 0.775391, time: 1.601
2025-05-31 15:35:10,352-INFO: Test iter: 91800, acc:0.746017, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 15:37:40,663-INFO: epoch: 117, iter: 91900, lr: 0.000010, 'loss': 744.3956, 'acc': 0.789062, time: 1.508
2025-05-31 15:40:11,251-INFO: epoch: 117, iter: 92000, lr: 0.000010, 'loss': 758.4287, 'acc': 0.777344, time: 1.506
2025-05-31 15:42:41,933-INFO: epoch: 117, iter: 92100, lr: 0.000010, 'loss': 716.6971, 'acc': 0.775391, time: 1.505
2025-05-31 15:45:12,545-INFO: epoch: 117, iter: 92200, lr: 0.000010, 'loss': 712.7052, 'acc': 0.783203, time: 1.504
2025-05-31 15:47:43,239-INFO: epoch: 117, iter: 92300, lr: 0.000010, 'loss': 695.9932, 'acc': 0.779297, time: 1.506
2025-05-31 15:50:13,891-INFO: epoch: 117, iter: 92400, lr: 0.000010, 'loss': 763.3002, 'acc': 0.78125, time: 1.506
2025-05-31 15:52:44,261-INFO: epoch: 117, iter: 92500, lr: 0.000010, 'loss': 742.28674, 'acc': 0.792219, time: 1.244
2025-05-31 15:53:01,684-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 15:55:26,249-INFO: epoch: 118, iter: 92600, lr: 0.000010, 'loss': 723.02454, 'acc': 0.777344, time: 1.505
2025-05-31 15:57:56,885-INFO: epoch: 118, iter: 92700, lr: 0.000010, 'loss': 771.7685, 'acc': 0.769531, time: 1.510
2025-05-31 16:00:27,591-INFO: epoch: 118, iter: 92800, lr: 0.000010, 'loss': 606.2634, 'acc': 0.785156, time: 1.508
2025-05-31 16:02:58,197-INFO: epoch: 118, iter: 92900, lr: 0.000010, 'loss': 716.8702, 'acc': 0.78125, time: 1.510
2025-05-31 16:05:28,926-INFO: epoch: 118, iter: 93000, lr: 0.000010, 'loss': 851.57056, 'acc': 0.775391, time: 1.506
2025-05-31 16:07:59,614-INFO: epoch: 118, iter: 93100, lr: 0.000010, 'loss': 726.327, 'acc': 0.779297, time: 1.507
2025-05-31 16:10:30,316-INFO: epoch: 118, iter: 93200, lr: 0.000010, 'loss': 697.4546, 'acc': 0.787109, time: 1.506
2025-05-31 16:12:54,082-INFO: Already s*e model in output/rec_CRNN_aug_341/latest
2025-05-31 16:13:04,329-INFO: epoch: 119, iter: 93300, lr: 0.000010, 'loss': 783.4164, 'acc': 0.766699, time: 1.593
2025-05-31 16:15:42,990-INFO: epoch: 119, iter: 93400, lr: 0.000010, 'loss': 736.87744, 'acc': 0.763672, time: 1.507
2025-05-31 16:18:13,663-INFO: epoch: 119, iter: 93500, lr: 0.000010, 'loss': 806.32886, 'acc': 0.773438, time: 1.505
2025-05-31 16:20:44,382-INFO: epoch: 119, iter: 93600, lr: 0.000010, 'loss': 694.41315, 'acc': 0.783203, time: 1.502
2025-05-31 16:21:27,256-INFO: Test iter: 93600, acc:0.745637, best_acc:0.753414, best_epoch:11, best_batch_id:9000, eval_sample_num:10544
2025-05-31 16:23:57,705-INFO: epoch: 119, iter: 93700, lr: 0.000010, 'loss': 692.7659, 'acc': 0.773438, time: 1.506
2025-05-31 16:26:28,362-INFO: epoch: 119, iter: 93800, lr: 0.000010, 'loss': 730.4896, 'acc': 0.771484, time: 1.505
2025-05-31 16:28:59,074-INFO: epoch: 119, iter: 93900, lr: 0.000010, 'loss': 681.943, 'acc': 0.787109, time: 1.504
2025-05-31 16:31:29,793-INFO: epoch: 119, iter: 94000, lr: 0.000010, 'loss': 718.77905, 'acc': 0.779297, time: 1.508
2025-05-31 16:33:29,577-INFO: Already s*e model in output/rec_CRNN_aug_341/latest

六、模型预测

使用训练好的Global.checkpoints=output/this_train/best_accuracy文件模型进行测试集数据预测，在PaddleOcr之下生成test2.txt文件，就是所得的最后结果，上传test2.txt文件得到最后的分数85.86

In [8]

! python3 tools/infer_rec.py -c configs/rec/rec_this_bilstm_ctc.yml -o Global.checkpoints=output/this_train/best_accuracy

2025-06-10 14:57:55,158-INFO: {'Global': {'algorithm': 'CRNN', 'use_gpu': True, 'epoch_num': 120, 'log_smooth_window': 20, 'print_batch_step': 100, 's*e_model_dir': 'output/this_train', 's*e_epoch_step': 3, 'eval_batch_step': 1800, 'train_batch_size_per_card': 256, 'test_batch_size_per_card': 128, 'image_shape': [3, 32, 256], 'max_text_length': 84, 'character_type': 'ch', 'character_dict_path': '/home/aistudio/work/dict.txt', 'loss_type': 'ctc', 'reader_yml': './configs/rec/rec_this_reader.yml', 'pretrain_weights': '/home/aistudio/work/PaddleOCR/model/latest', 'checkpoints': 'output/this_train/best_accuracy', 's*e_inference_dir': '/home/aistudio/work/test', 'infer_img': '/home/aistudio/test_images2'}, 'Architecture': {'function': 'ppocr.modeling.architectures.rec_model,RecModel'}, 'Backbone': {'function': 'ppocr.modeling.backbones.rec_resnet_vd,ResNet', 'layers': 34}, 'Head': {'function': 'ppocr.modeling.heads.rec_ctc_head,CTCPredict', 'encoder_type': 'rnn', 'SeqRNN': {'hidden_size': 256}}, 'Loss': {'function': 'ppocr.modeling.losses.rec_ctc_loss,CTCLoss'}, 'Optimizer': {'function': 'ppocr.optimizer,AdamDecay', 'base_lr': 1e-05, 'beta1': 0.9, 'beta2': 0.999}, 'TrainReader': {'reader_function': 'ppocr.data.rec.dataset_tr*ersal,SimpleReader', 'num_workers': 8, 'img_set_dir': '/', 'label_file_path': '/home/aistudio/work/train.txt'}, 'EvalReader': {'reader_function': 'ppocr.data.rec.dataset_tr*ersal,SimpleReader', 'img_set_dir': '/', 'label_file_path': '/home/aistudio/work/test.txt'}, 'TestReader': {'reader_function': 'ppocr.data.rec.dataset_tr*ersal,SimpleReader', 'img_set_dir': '/', 'infer_img': '/home/aistudio/test_images2'}}
W0610 14:57:55.426496   506 device_context.cc:404] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 11.2, Runtime API Version: 10.1
W0610 14:57:55.431546   506 device_context.cc:422] device: 0, cuDNN Version: 7.6.
2025-06-10 14:57:58,860-INFO: Finish initing model from output/this_train/best_accuracy
100%|█████████████████████████████████████| 10000/10000 [05:43<00:00, 29.10it/s]

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