MMEngine 快速上手#
构建模型#
首先，需要构建 MMEngine 模型，约定这个模型应当继承 BaseModel，并且其 forward 方法除了接受来自数据集的若干参数外，还需要接受额外的参数 mode：对于训练，需要 mode 接受字符串 "loss"，并返回包含 "loss" 字段的字典；对于验证，需要 mode 接受字符串 "predict"，并返回同时包含预测信息和真实信息的结果。
import torch.nn.functional as F
import torch
from torch import nn
import torchvision
from mmengine.model import BaseModel
class MMResNet50(BaseModel):
def __init__(self, data_preprocessor: dict|nn.Module|None = None,
init_cfg: dict|None = None):
super().__init__(data_preprocessor=data_preprocessor, init_cfg=init_cfg)
self.resnet = torchvision.models.resnet50()
def forward(self, inputs: torch.Tensor,
data_samples: list|list = None,
mode: str = 'tensor') -> dict[str, torch.Tensor] | list:
x = self.resnet(inputs)
if mode == 'loss':
return {'loss': F.cross_entropy(x, data_samples)}
elif mode == 'predict':
return x, data_samples
else:
return x
构建数据集和数据加载器#
其次，需要构建训练和验证所需要的数据集 (Dataset)和数据加载器 (DataLoader)。 对于基础的训练和验证功能，可以直接使用符合 PyTorch 标准的数据加载器和数据集。
from pathlib import Path
temp_dir = Path(".temp")
temp_dir.mkdir(exist_ok=True) # 创建缓存目录
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
norm_cfg = dict(mean=[0.491, 0.482, 0.447], std=[0.202, 0.199, 0.201])
train_dataloader = DataLoader(
batch_size=32,
shuffle=True,
dataset=torchvision.datasets.CIFAR10(
temp_dir/'data/cifar10',
train=True,
download=True,
transform=transforms.Compose([
transforms.RandomCrop(32, padding=4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize(**norm_cfg)
]))
)
val_dataloader = DataLoader(
batch_size=32,
shuffle=False,
dataset=torchvision.datasets.CIFAR10(
temp_dir/'data/cifar10',
train=False,
download=True,
transform=transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(**norm_cfg)
]))
)
Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to .temp/data/cifar10/cifar-10-python.tar.gz
Extracting .temp/data/cifar10/cifar-10-python.tar.gz to .temp/data/cifar10
Files already downloaded and verified
100%|██████████| 170M/170M [04:18<00:00, 659kB/s]
构建评测指标#
为了进行验证和测试，需要定义模型推理结果的评测指标。
约定评测指标需要继承 BaseMetric，并实现 process 和 compute_metrics 方法。其中 process 方法接受数据集的输出和模型 mode="predict" 时的输出，此时的数据为单个批次的数据，对这一批次的数据进行处理后，保存信息至 self.results 属性。而 compute_metrics 接受 results 参数，这一参数的输入为 process 中保存的所有信息（如果是分布式环境，results 中为已收集的，包括各个进程 process 保存信息的结果），利用这些信息计算并返回保存有评测指标结果的字典
from typing import Any, Sequence
from mmengine.evaluator import BaseMetric
class Accuracy(BaseMetric):
def process(self, data_batch: Any, data_samples: Sequence[dict])->None:
"""
处理一批数据样本及其预测结果。处理后的结果应存储在`self.results`中，这将在所有批次处理完毕后用于计算指标。
Args:
data_batch: 从数据加载器获取的一批数据。
data_samples: 模型输出的一批结果。
"""
score, gt = data_samples
# 将一个批次的中间结果保存至 `self.results`
self.results.append({
'batch_size': len(gt),
'correct': (score.argmax(dim=1) == gt).sum().cpu(),
})
def compute_metrics(self, results):
total_correct = sum(item['correct'] for item in results)
total_size = sum(item['batch_size'] for item in results)
# 返回保存有评测指标结果的字典，其中键为指标名称
return dict(accuracy=100 * total_correct / total_size)
构建执行器并执行任务#
最后，利用构建好的模型，数据加载器，评测指标构建执行器 (Runner)，同时在其中配置 优化器、工作路径、训练与验证配置等选项，即可通过调用执行器的 train() 方法启动训练：
from torch.optim import SGD
from mmengine.runner import Runner
runner = Runner(
# 用以训练和验证的模型，需要满足特定的接口需求
model=MMResNet50(),
# 工作路径，用以保存训练日志、权重文件信息
work_dir=temp_dir/'./work_dir',
# 训练数据加载器，需要满足 PyTorch 数据加载器协议
train_dataloader=train_dataloader,
# 优化器包装，用于模型优化，并提供 AMP、梯度累积等附加功能
optim_wrapper=dict(optimizer=dict(type=SGD, lr=0.001, momentum=0.9)),
# 训练配置，用于指定训练周期、验证间隔等信息
train_cfg=dict(by_epoch=True, max_epochs=5, val_interval=1),
# 验证数据加载器，需要满足 PyTorch 数据加载器协议
val_dataloader=val_dataloader,
# 验证配置，用于指定验证所需要的额外参数
val_cfg=dict(),
# 用于验证的评测器，这里使用默认评测器，并评测指标
val_evaluator=dict(type=Accuracy),
)
runner.train()
Show code cell output
11/16 19:30:32 - mmengine - INFO -
------------------------------------------------------------
System environment:
sys.platform: linux
Python: 3.12.2 | packaged by conda-forge | (main, Feb 16 2024, 20:50:58) [GCC 12.3.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 798167336
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 2080 Ti
CUDA_HOME: /media/pc/data/lxw/envs/anaconda3x/envs/xxx
NVCC: Cuda compilation tools, release 12.6, V12.6.20
GCC: gcc (conda-forge gcc 12.4.0-0) 12.4.0
PyTorch: 2.5.0
PyTorch compiling details: PyTorch built with:
- GCC 9.3
- C++ Version: 201703
- Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 for Intel(R) 64 architecture applications
- Intel(R) MKL-DNN v3.5.3 (Git Hash 66f0cb9eb66affd2da3bf5f8d897376f04aae6af)
- OpenMP 201511 (a.k.a. OpenMP 4.5)
- LAPACK is enabled (usually provided by MKL)
- NNPACK is enabled
- CPU capability usage: AVX2
- CUDA Runtime 12.4
- NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
- CuDNN 90.1
- Magma 2.6.1
- Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.4, CUDNN_VERSION=9.1.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.5.0, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,
TorchVision: 0.20.0
OpenCV: 4.10.0
MMEngine: 0.10.5
Runtime environment:
dist_cfg: {'backend': 'nccl'}
seed: 798167336
Distributed launcher: none
Distributed training: False
GPU number: 1
------------------------------------------------------------
11/16 19:30:32 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used.
11/16 19:30:32 - mmengine - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH ) RuntimeInfoHook
(BELOW_NORMAL) LoggerHook
--------------------
before_train:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(VERY_LOW ) CheckpointHook
--------------------
before_train_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(NORMAL ) DistSamplerSeedHook
--------------------
before_train_iter:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
--------------------
after_train_iter:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
--------------------
after_train_epoch:
(NORMAL ) IterTimerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
--------------------
before_val:
(VERY_HIGH ) RuntimeInfoHook
--------------------
before_val_epoch:
(NORMAL ) IterTimerHook
--------------------
before_val_iter:
(NORMAL ) IterTimerHook
--------------------
after_val_iter:
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
--------------------
after_val_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
(LOW ) ParamSchedulerHook
(VERY_LOW ) CheckpointHook
--------------------
after_val:
(VERY_HIGH ) RuntimeInfoHook
--------------------
after_train:
(VERY_HIGH ) RuntimeInfoHook
(VERY_LOW ) CheckpointHook
--------------------
before_test:
(VERY_HIGH ) RuntimeInfoHook
--------------------
before_test_epoch:
(NORMAL ) IterTimerHook
--------------------
before_test_iter:
(NORMAL ) IterTimerHook
--------------------
after_test_iter:
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
--------------------
after_test_epoch:
(VERY_HIGH ) RuntimeInfoHook
(NORMAL ) IterTimerHook
(BELOW_NORMAL) LoggerHook
--------------------
after_test:
(VERY_HIGH ) RuntimeInfoHook
--------------------
after_run:
(BELOW_NORMAL) LoggerHook
--------------------
11/16 19:30:32 - mmengine - WARNING - Dataset CIFAR10 has no metainfo. ``dataset_meta`` in visualizer will be None.
11/16 19:30:32 - mmengine - WARNING - The prefix is not set in metric class Accuracy.
11/16 19:30:32 - mmengine - WARNING - Dataset CIFAR10 has no metainfo. ``dataset_meta`` in evaluator, metric and visualizer will be None.
11/16 19:30:32 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io
11/16 19:30:32 - mmengine - INFO - Checkpoints will be saved to /media/pc/data/lxw/ai/torch-book/doc/mmengine/.temp/work_dir.
11/16 19:30:32 - mmengine - INFO - Epoch(train) [1][ 10/1563] lr: 1.0000e-03 eta: 0:06:52 time: 0.0528 data_time: 0.0136 memory: 583 loss: 5.2429
11/16 19:30:33 - mmengine - INFO - Epoch(train) [1][ 20/1563] lr: 1.0000e-03 eta: 0:07:47 time: 0.0672 data_time: 0.0246 memory: 583 loss: 2.7109
11/16 19:30:33 - mmengine - INFO - Epoch(train) [1][ 30/1563] lr: 1.0000e-03 eta: 0:07:38 time: 0.0566 data_time: 0.0156 memory: 583 loss: 2.8172
11/16 19:30:34 - mmengine - INFO - Epoch(train) [1][ 40/1563] lr: 1.0000e-03 eta: 0:07:33 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.7161
11/16 19:30:35 - mmengine - INFO - Epoch(train) [1][ 50/1563] lr: 1.0000e-03 eta: 0:07:30 time: 0.0570 data_time: 0.0157 memory: 583 loss: 2.5933
11/16 19:30:35 - mmengine - INFO - Epoch(train) [1][ 60/1563] lr: 1.0000e-03 eta: 0:07:28 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.5723
11/16 19:30:36 - mmengine - INFO - Epoch(train) [1][ 70/1563] lr: 1.0000e-03 eta: 0:07:26 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.6657
11/16 19:30:36 - mmengine - INFO - Epoch(train) [1][ 80/1563] lr: 1.0000e-03 eta: 0:07:25 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.8928
11/16 19:30:37 - mmengine - INFO - Epoch(train) [1][ 90/1563] lr: 1.0000e-03 eta: 0:07:24 time: 0.0568 data_time: 0.0157 memory: 583 loss: 2.7148
11/16 19:30:37 - mmengine - INFO - Epoch(train) [1][ 100/1563] lr: 1.0000e-03 eta: 0:07:22 time: 0.0566 data_time: 0.0156 memory: 583 loss: 2.6429
11/16 19:30:38 - mmengine - INFO - Epoch(train) [1][ 110/1563] lr: 1.0000e-03 eta: 0:07:22 time: 0.0572 data_time: 0.0159 memory: 583 loss: 2.4578
11/16 19:30:39 - mmengine - INFO - Epoch(train) [1][ 120/1563] lr: 1.0000e-03 eta: 0:07:21 time: 0.0572 data_time: 0.0159 memory: 583 loss: 2.5217
11/16 19:30:39 - mmengine - INFO - Epoch(train) [1][ 130/1563] lr: 1.0000e-03 eta: 0:07:20 time: 0.0569 data_time: 0.0157 memory: 583 loss: 2.4902
11/16 19:30:40 - mmengine - INFO - Epoch(train) [1][ 140/1563] lr: 1.0000e-03 eta: 0:07:19 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.5046
11/16 19:30:40 - mmengine - INFO - Epoch(train) [1][ 150/1563] lr: 1.0000e-03 eta: 0:07:19 time: 0.0570 data_time: 0.0156 memory: 583 loss: 2.5468
11/16 19:30:41 - mmengine - INFO - Epoch(train) [1][ 160/1563] lr: 1.0000e-03 eta: 0:07:18 time: 0.0569 data_time: 0.0157 memory: 583 loss: 2.5345
11/16 19:30:41 - mmengine - INFO - Epoch(train) [1][ 170/1563] lr: 1.0000e-03 eta: 0:07:17 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.5123
11/16 19:30:42 - mmengine - INFO - Epoch(train) [1][ 180/1563] lr: 1.0000e-03 eta: 0:07:16 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.4850
11/16 19:30:43 - mmengine - INFO - Epoch(train) [1][ 190/1563] lr: 1.0000e-03 eta: 0:07:16 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.4499
11/16 19:30:43 - mmengine - INFO - Epoch(train) [1][ 200/1563] lr: 1.0000e-03 eta: 0:07:15 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.6277
11/16 19:30:44 - mmengine - INFO - Epoch(train) [1][ 210/1563] lr: 1.0000e-03 eta: 0:07:14 time: 0.0572 data_time: 0.0158 memory: 583 loss: 2.4470
11/16 19:30:44 - mmengine - INFO - Epoch(train) [1][ 220/1563] lr: 1.0000e-03 eta: 0:07:14 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.5172
11/16 19:30:45 - mmengine - INFO - Epoch(train) [1][ 230/1563] lr: 1.0000e-03 eta: 0:07:13 time: 0.0571 data_time: 0.0157 memory: 583 loss: 2.4071
11/16 19:30:45 - mmengine - INFO - Epoch(train) [1][ 240/1563] lr: 1.0000e-03 eta: 0:07:12 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.3784
11/16 19:30:46 - mmengine - INFO - Epoch(train) [1][ 250/1563] lr: 1.0000e-03 eta: 0:07:12 time: 0.0571 data_time: 0.0157 memory: 583 loss: 2.3364
11/16 19:30:46 - mmengine - INFO - Epoch(train) [1][ 260/1563] lr: 1.0000e-03 eta: 0:07:11 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.4262
11/16 19:30:47 - mmengine - INFO - Epoch(train) [1][ 270/1563] lr: 1.0000e-03 eta: 0:07:10 time: 0.0570 data_time: 0.0157 memory: 583 loss: 2.4239
11/16 19:30:48 - mmengine - INFO - Epoch(train) [1][ 280/1563] lr: 1.0000e-03 eta: 0:07:10 time: 0.0569 data_time: 0.0157 memory: 583 loss: 2.6525
11/16 19:30:48 - mmengine - INFO - Epoch(train) [1][ 290/1563] lr: 1.0000e-03 eta: 0:07:09 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.5649
11/16 19:30:49 - mmengine - INFO - Epoch(train) [1][ 300/1563] lr: 1.0000e-03 eta: 0:07:09 time: 0.0568 data_time: 0.0155 memory: 583 loss: 2.4449
11/16 19:30:49 - mmengine - INFO - Epoch(train) [1][ 310/1563] lr: 1.0000e-03 eta: 0:07:08 time: 0.0570 data_time: 0.0157 memory: 583 loss: 2.4234
11/16 19:30:50 - mmengine - INFO - Epoch(train) [1][ 320/1563] lr: 1.0000e-03 eta: 0:07:07 time: 0.0569 data_time: 0.0155 memory: 583 loss: 2.4709
11/16 19:30:50 - mmengine - INFO - Epoch(train) [1][ 330/1563] lr: 1.0000e-03 eta: 0:07:07 time: 0.0570 data_time: 0.0156 memory: 583 loss: 2.3999
11/16 19:30:51 - mmengine - INFO - Epoch(train) [1][ 340/1563] lr: 1.0000e-03 eta: 0:07:06 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.3403
11/16 19:30:52 - mmengine - INFO - Epoch(train) [1][ 350/1563] lr: 1.0000e-03 eta: 0:07:05 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.4029
11/16 19:30:52 - mmengine - INFO - Epoch(train) [1][ 360/1563] lr: 1.0000e-03 eta: 0:07:05 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1956
11/16 19:30:53 - mmengine - INFO - Epoch(train) [1][ 370/1563] lr: 1.0000e-03 eta: 0:07:04 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.3607
11/16 19:30:53 - mmengine - INFO - Epoch(train) [1][ 380/1563] lr: 1.0000e-03 eta: 0:07:04 time: 0.0568 data_time: 0.0155 memory: 583 loss: 2.2534
11/16 19:30:54 - mmengine - INFO - Epoch(train) [1][ 390/1563] lr: 1.0000e-03 eta: 0:07:04 time: 0.0622 data_time: 0.0205 memory: 583 loss: 2.3954
11/16 19:30:55 - mmengine - INFO - Epoch(train) [1][ 400/1563] lr: 1.0000e-03 eta: 0:07:03 time: 0.0569 data_time: 0.0155 memory: 583 loss: 2.4549
11/16 19:30:55 - mmengine - INFO - Epoch(train) [1][ 410/1563] lr: 1.0000e-03 eta: 0:07:03 time: 0.0572 data_time: 0.0159 memory: 583 loss: 2.3724
11/16 19:30:56 - mmengine - INFO - Epoch(train) [1][ 420/1563] lr: 1.0000e-03 eta: 0:07:02 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.3348
11/16 19:30:56 - mmengine - INFO - Epoch(train) [1][ 430/1563] lr: 1.0000e-03 eta: 0:07:02 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.2779
11/16 19:30:57 - mmengine - INFO - Epoch(train) [1][ 440/1563] lr: 1.0000e-03 eta: 0:07:01 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2766
11/16 19:30:57 - mmengine - INFO - Epoch(train) [1][ 450/1563] lr: 1.0000e-03 eta: 0:07:00 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.4431
11/16 19:30:58 - mmengine - INFO - Epoch(train) [1][ 460/1563] lr: 1.0000e-03 eta: 0:07:00 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.3707
11/16 19:30:58 - mmengine - INFO - Epoch(train) [1][ 470/1563] lr: 1.0000e-03 eta: 0:06:59 time: 0.0574 data_time: 0.0159 memory: 583 loss: 2.3774
11/16 19:30:59 - mmengine - INFO - Epoch(train) [1][ 480/1563] lr: 1.0000e-03 eta: 0:06:59 time: 0.0565 data_time: 0.0155 memory: 583 loss: 2.2470
11/16 19:31:00 - mmengine - INFO - Epoch(train) [1][ 490/1563] lr: 1.0000e-03 eta: 0:06:58 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2287
11/16 19:31:00 - mmengine - INFO - Epoch(train) [1][ 500/1563] lr: 1.0000e-03 eta: 0:06:57 time: 0.0570 data_time: 0.0156 memory: 583 loss: 2.2841
11/16 19:31:01 - mmengine - INFO - Epoch(train) [1][ 510/1563] lr: 1.0000e-03 eta: 0:06:57 time: 0.0568 data_time: 0.0157 memory: 583 loss: 2.2093
11/16 19:31:01 - mmengine - INFO - Epoch(train) [1][ 520/1563] lr: 1.0000e-03 eta: 0:06:56 time: 0.0570 data_time: 0.0157 memory: 583 loss: 2.3259
11/16 19:31:02 - mmengine - INFO - Epoch(train) [1][ 530/1563] lr: 1.0000e-03 eta: 0:06:56 time: 0.0572 data_time: 0.0157 memory: 583 loss: 2.1771
11/16 19:31:02 - mmengine - INFO - Epoch(train) [1][ 540/1563] lr: 1.0000e-03 eta: 0:06:55 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2184
11/16 19:31:03 - mmengine - INFO - Epoch(train) [1][ 550/1563] lr: 1.0000e-03 eta: 0:06:54 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1943
11/16 19:31:04 - mmengine - INFO - Epoch(train) [1][ 560/1563] lr: 1.0000e-03 eta: 0:06:54 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2307
11/16 19:31:04 - mmengine - INFO - Epoch(train) [1][ 570/1563] lr: 1.0000e-03 eta: 0:06:53 time: 0.0570 data_time: 0.0156 memory: 583 loss: 2.1997
11/16 19:31:05 - mmengine - INFO - Epoch(train) [1][ 580/1563] lr: 1.0000e-03 eta: 0:06:53 time: 0.0575 data_time: 0.0158 memory: 583 loss: 2.3196
11/16 19:31:05 - mmengine - INFO - Epoch(train) [1][ 590/1563] lr: 1.0000e-03 eta: 0:06:52 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.4100
11/16 19:31:06 - mmengine - INFO - Epoch(train) [1][ 600/1563] lr: 1.0000e-03 eta: 0:06:51 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.3546
11/16 19:31:06 - mmengine - INFO - Epoch(train) [1][ 610/1563] lr: 1.0000e-03 eta: 0:06:51 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2251
11/16 19:31:07 - mmengine - INFO - Epoch(train) [1][ 620/1563] lr: 1.0000e-03 eta: 0:06:50 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1233
11/16 19:31:08 - mmengine - INFO - Epoch(train) [1][ 630/1563] lr: 1.0000e-03 eta: 0:06:50 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.3149
11/16 19:31:08 - mmengine - INFO - Epoch(train) [1][ 640/1563] lr: 1.0000e-03 eta: 0:06:49 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.0781
11/16 19:31:09 - mmengine - INFO - Epoch(train) [1][ 650/1563] lr: 1.0000e-03 eta: 0:06:48 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.5079
11/16 19:31:09 - mmengine - INFO - Epoch(train) [1][ 660/1563] lr: 1.0000e-03 eta: 0:06:48 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.4047
11/16 19:31:10 - mmengine - INFO - Epoch(train) [1][ 670/1563] lr: 1.0000e-03 eta: 0:06:47 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2861
11/16 19:31:10 - mmengine - INFO - Epoch(train) [1][ 680/1563] lr: 1.0000e-03 eta: 0:06:47 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.3053
11/16 19:31:11 - mmengine - INFO - Epoch(train) [1][ 690/1563] lr: 1.0000e-03 eta: 0:06:46 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.2480
11/16 19:31:12 - mmengine - INFO - Epoch(train) [1][ 700/1563] lr: 1.0000e-03 eta: 0:06:45 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1948
11/16 19:31:12 - mmengine - INFO - Epoch(train) [1][ 710/1563] lr: 1.0000e-03 eta: 0:06:45 time: 0.0566 data_time: 0.0155 memory: 583 loss: 2.3047
11/16 19:31:13 - mmengine - INFO - Epoch(train) [1][ 720/1563] lr: 1.0000e-03 eta: 0:06:44 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.2473
11/16 19:31:13 - mmengine - INFO - Epoch(train) [1][ 730/1563] lr: 1.0000e-03 eta: 0:06:44 time: 0.0569 data_time: 0.0155 memory: 583 loss: 2.2633
11/16 19:31:14 - mmengine - INFO - Epoch(train) [1][ 740/1563] lr: 1.0000e-03 eta: 0:06:43 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1047
11/16 19:31:14 - mmengine - INFO - Epoch(train) [1][ 750/1563] lr: 1.0000e-03 eta: 0:06:42 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.3204
11/16 19:31:15 - mmengine - INFO - Epoch(train) [1][ 760/1563] lr: 1.0000e-03 eta: 0:06:42 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.2244
11/16 19:31:16 - mmengine - INFO - Epoch(train) [1][ 770/1563] lr: 1.0000e-03 eta: 0:06:41 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1751
11/16 19:31:16 - mmengine - INFO - Epoch(train) [1][ 780/1563] lr: 1.0000e-03 eta: 0:06:41 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.3935
11/16 19:31:17 - mmengine - INFO - Epoch(train) [1][ 790/1563] lr: 1.0000e-03 eta: 0:06:40 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1178
11/16 19:31:17 - mmengine - INFO - Epoch(train) [1][ 800/1563] lr: 1.0000e-03 eta: 0:06:40 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.2400
11/16 19:31:18 - mmengine - INFO - Epoch(train) [1][ 810/1563] lr: 1.0000e-03 eta: 0:06:39 time: 0.0568 data_time: 0.0155 memory: 583 loss: 2.2427
11/16 19:31:18 - mmengine - INFO - Epoch(train) [1][ 820/1563] lr: 1.0000e-03 eta: 0:06:38 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.1875
11/16 19:31:19 - mmengine - INFO - Epoch(train) [1][ 830/1563] lr: 1.0000e-03 eta: 0:06:38 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.1405
11/16 19:31:20 - mmengine - INFO - Epoch(train) [1][ 840/1563] lr: 1.0000e-03 eta: 0:06:37 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1878
11/16 19:31:20 - mmengine - INFO - Epoch(train) [1][ 850/1563] lr: 1.0000e-03 eta: 0:06:37 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0904
11/16 19:31:21 - mmengine - INFO - Epoch(train) [1][ 860/1563] lr: 1.0000e-03 eta: 0:06:36 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1568
11/16 19:31:21 - mmengine - INFO - Epoch(train) [1][ 870/1563] lr: 1.0000e-03 eta: 0:06:35 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0799
11/16 19:31:22 - mmengine - INFO - Epoch(train) [1][ 880/1563] lr: 1.0000e-03 eta: 0:06:35 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1147
11/16 19:31:22 - mmengine - INFO - Epoch(train) [1][ 890/1563] lr: 1.0000e-03 eta: 0:06:34 time: 0.0567 data_time: 0.0156 memory: 583 loss: 1.9687
11/16 19:31:23 - mmengine - INFO - Epoch(train) [1][ 900/1563] lr: 1.0000e-03 eta: 0:06:34 time: 0.0570 data_time: 0.0156 memory: 583 loss: 2.1428
11/16 19:31:24 - mmengine - INFO - Epoch(train) [1][ 910/1563] lr: 1.0000e-03 eta: 0:06:33 time: 0.0569 data_time: 0.0157 memory: 583 loss: 2.1266
11/16 19:31:24 - mmengine - INFO - Epoch(train) [1][ 920/1563] lr: 1.0000e-03 eta: 0:06:32 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.1522
11/16 19:31:25 - mmengine - INFO - Epoch(train) [1][ 930/1563] lr: 1.0000e-03 eta: 0:06:32 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.0761
11/16 19:31:25 - mmengine - INFO - Epoch(train) [1][ 940/1563] lr: 1.0000e-03 eta: 0:06:31 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1860
11/16 19:31:26 - mmengine - INFO - Epoch(train) [1][ 950/1563] lr: 1.0000e-03 eta: 0:06:31 time: 0.0570 data_time: 0.0156 memory: 583 loss: 2.0426
11/16 19:31:26 - mmengine - INFO - Epoch(train) [1][ 960/1563] lr: 1.0000e-03 eta: 0:06:30 time: 0.0570 data_time: 0.0157 memory: 583 loss: 2.2578
11/16 19:31:27 - mmengine - INFO - Epoch(train) [1][ 970/1563] lr: 1.0000e-03 eta: 0:06:30 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1935
11/16 19:31:28 - mmengine - INFO - Epoch(train) [1][ 980/1563] lr: 1.0000e-03 eta: 0:06:29 time: 0.0569 data_time: 0.0156 memory: 583 loss: 1.9832
11/16 19:31:28 - mmengine - INFO - Epoch(train) [1][ 990/1563] lr: 1.0000e-03 eta: 0:06:28 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.1283
11/16 19:31:29 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:31:29 - mmengine - INFO - Epoch(train) [1][1000/1563] lr: 1.0000e-03 eta: 0:06:28 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1035
11/16 19:31:29 - mmengine - INFO - Epoch(train) [1][1010/1563] lr: 1.0000e-03 eta: 0:06:27 time: 0.0577 data_time: 0.0161 memory: 583 loss: 2.0732
11/16 19:31:30 - mmengine - INFO - Epoch(train) [1][1020/1563] lr: 1.0000e-03 eta: 0:06:27 time: 0.0569 data_time: 0.0156 memory: 583 loss: 1.9369
11/16 19:31:30 - mmengine - INFO - Epoch(train) [1][1030/1563] lr: 1.0000e-03 eta: 0:06:26 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.0293
11/16 19:31:31 - mmengine - INFO - Epoch(train) [1][1040/1563] lr: 1.0000e-03 eta: 0:06:26 time: 0.0572 data_time: 0.0156 memory: 583 loss: 2.0615
11/16 19:31:31 - mmengine - INFO - Epoch(train) [1][1050/1563] lr: 1.0000e-03 eta: 0:06:25 time: 0.0569 data_time: 0.0157 memory: 583 loss: 2.1302
11/16 19:31:32 - mmengine - INFO - Epoch(train) [1][1060/1563] lr: 1.0000e-03 eta: 0:06:24 time: 0.0569 data_time: 0.0155 memory: 583 loss: 2.1177
11/16 19:31:33 - mmengine - INFO - Epoch(train) [1][1070/1563] lr: 1.0000e-03 eta: 0:06:24 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.1026
11/16 19:31:33 - mmengine - INFO - Epoch(train) [1][1080/1563] lr: 1.0000e-03 eta: 0:06:23 time: 0.0569 data_time: 0.0155 memory: 583 loss: 2.0996
11/16 19:31:34 - mmengine - INFO - Epoch(train) [1][1090/1563] lr: 1.0000e-03 eta: 0:06:23 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0525
11/16 19:31:34 - mmengine - INFO - Epoch(train) [1][1100/1563] lr: 1.0000e-03 eta: 0:06:22 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0588
11/16 19:31:35 - mmengine - INFO - Epoch(train) [1][1110/1563] lr: 1.0000e-03 eta: 0:06:22 time: 0.0570 data_time: 0.0156 memory: 583 loss: 1.9882
11/16 19:31:35 - mmengine - INFO - Epoch(train) [1][1120/1563] lr: 1.0000e-03 eta: 0:06:21 time: 0.0573 data_time: 0.0159 memory: 583 loss: 2.0403
11/16 19:31:36 - mmengine - INFO - Epoch(train) [1][1130/1563] lr: 1.0000e-03 eta: 0:06:20 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.0466
11/16 19:31:37 - mmengine - INFO - Epoch(train) [1][1140/1563] lr: 1.0000e-03 eta: 0:06:20 time: 0.0572 data_time: 0.0157 memory: 583 loss: 1.9862
11/16 19:31:37 - mmengine - INFO - Epoch(train) [1][1150/1563] lr: 1.0000e-03 eta: 0:06:19 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0484
11/16 19:31:38 - mmengine - INFO - Epoch(train) [1][1160/1563] lr: 1.0000e-03 eta: 0:06:19 time: 0.0569 data_time: 0.0156 memory: 583 loss: 1.9743
11/16 19:31:38 - mmengine - INFO - Epoch(train) [1][1170/1563] lr: 1.0000e-03 eta: 0:06:18 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.0298
11/16 19:31:39 - mmengine - INFO - Epoch(train) [1][1180/1563] lr: 1.0000e-03 eta: 0:06:18 time: 0.0571 data_time: 0.0156 memory: 583 loss: 2.0166
11/16 19:31:39 - mmengine - INFO - Epoch(train) [1][1190/1563] lr: 1.0000e-03 eta: 0:06:17 time: 0.0568 data_time: 0.0156 memory: 583 loss: 1.8625
11/16 19:31:40 - mmengine - INFO - Epoch(train) [1][1200/1563] lr: 1.0000e-03 eta: 0:06:16 time: 0.0573 data_time: 0.0159 memory: 583 loss: 1.9544
11/16 19:31:41 - mmengine - INFO - Epoch(train) [1][1210/1563] lr: 1.0000e-03 eta: 0:06:16 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0050
11/16 19:31:41 - mmengine - INFO - Epoch(train) [1][1220/1563] lr: 1.0000e-03 eta: 0:06:15 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.0514
11/16 19:31:42 - mmengine - INFO - Epoch(train) [1][1230/1563] lr: 1.0000e-03 eta: 0:06:15 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0199
11/16 19:31:42 - mmengine - INFO - Epoch(train) [1][1240/1563] lr: 1.0000e-03 eta: 0:06:14 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0691
11/16 19:31:43 - mmengine - INFO - Epoch(train) [1][1250/1563] lr: 1.0000e-03 eta: 0:06:14 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0770
11/16 19:31:43 - mmengine - INFO - Epoch(train) [1][1260/1563] lr: 1.0000e-03 eta: 0:06:13 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.0407
11/16 19:31:44 - mmengine - INFO - Epoch(train) [1][1270/1563] lr: 1.0000e-03 eta: 0:06:12 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.0224
11/16 19:31:45 - mmengine - INFO - Epoch(train) [1][1280/1563] lr: 1.0000e-03 eta: 0:06:12 time: 0.0569 data_time: 0.0156 memory: 583 loss: 2.0722
11/16 19:31:45 - mmengine - INFO - Epoch(train) [1][1290/1563] lr: 1.0000e-03 eta: 0:06:11 time: 0.0569 data_time: 0.0156 memory: 583 loss: 1.9250
11/16 19:31:46 - mmengine - INFO - Epoch(train) [1][1300/1563] lr: 1.0000e-03 eta: 0:06:11 time: 0.0567 data_time: 0.0156 memory: 583 loss: 1.9272
11/16 19:31:46 - mmengine - INFO - Epoch(train) [1][1310/1563] lr: 1.0000e-03 eta: 0:06:10 time: 0.0568 data_time: 0.0156 memory: 583 loss: 2.1550
11/16 19:31:47 - mmengine - INFO - Epoch(train) [1][1320/1563] lr: 1.0000e-03 eta: 0:06:10 time: 0.0572 data_time: 0.0157 memory: 583 loss: 1.9615
11/16 19:31:47 - mmengine - INFO - Epoch(train) [1][1330/1563] lr: 1.0000e-03 eta: 0:06:09 time: 0.0568 data_time: 0.0157 memory: 583 loss: 2.0335
11/16 19:31:48 - mmengine - INFO - Epoch(train) [1][1340/1563] lr: 1.0000e-03 eta: 0:06:08 time: 0.0574 data_time: 0.0157 memory: 583 loss: 2.0045
11/16 19:31:49 - mmengine - INFO - Epoch(train) [1][1350/1563] lr: 1.0000e-03 eta: 0:06:08 time: 0.0567 data_time: 0.0156 memory: 583 loss: 1.9513
11/16 19:31:49 - mmengine - INFO - Epoch(train) [1][1360/1563] lr: 1.0000e-03 eta: 0:06:07 time: 0.0568 data_time: 0.0155 memory: 583 loss: 2.0505
11/16 19:31:50 - mmengine - INFO - Epoch(train) [1][1370/1563] lr: 1.0000e-03 eta: 0:06:07 time: 0.0567 data_time: 0.0156 memory: 583 loss: 1.9027
11/16 19:31:50 - mmengine - INFO - Epoch(train) [1][1380/1563] lr: 1.0000e-03 eta: 0:06:06 time: 0.0567 data_time: 0.0156 memory: 583 loss: 1.8259
11/16 19:31:51 - mmengine - INFO - Epoch(train) [1][1390/1563] lr: 1.0000e-03 eta: 0:06:06 time: 0.0572 data_time: 0.0156 memory: 583 loss: 2.0147
11/16 19:31:51 - mmengine - INFO - Epoch(train) [1][1400/1563] lr: 1.0000e-03 eta: 0:06:05 time: 0.0576 data_time: 0.0157 memory: 583 loss: 2.1101
11/16 19:31:52 - mmengine - INFO - Epoch(train) [1][1410/1563] lr: 1.0000e-03 eta: 0:06:04 time: 0.0576 data_time: 0.0157 memory: 583 loss: 1.8542
11/16 19:31:53 - mmengine - INFO - Epoch(train) [1][1420/1563] lr: 1.0000e-03 eta: 0:06:04 time: 0.0570 data_time: 0.0156 memory: 583 loss: 1.7707
11/16 19:31:53 - mmengine - INFO - Epoch(train) [1][1430/1563] lr: 1.0000e-03 eta: 0:06:03 time: 0.0568 data_time: 0.0156 memory: 583 loss: 1.9122
11/16 19:31:54 - mmengine - INFO - Epoch(train) [1][1440/1563] lr: 1.0000e-03 eta: 0:06:03 time: 0.0566 data_time: 0.0155 memory: 583 loss: 1.9640
11/16 19:31:54 - mmengine - INFO - Epoch(train) [1][1450/1563] lr: 1.0000e-03 eta: 0:06:02 time: 0.0568 data_time: 0.0156 memory: 583 loss: 1.9841
11/16 19:31:55 - mmengine - INFO - Epoch(train) [1][1460/1563] lr: 1.0000e-03 eta: 0:06:02 time: 0.0571 data_time: 0.0156 memory: 583 loss: 1.9097
11/16 19:31:55 - mmengine - INFO - Epoch(train) [1][1470/1563] lr: 1.0000e-03 eta: 0:06:01 time: 0.0569 data_time: 0.0157 memory: 583 loss: 1.8479
11/16 19:31:56 - mmengine - INFO - Epoch(train) [1][1480/1563] lr: 1.0000e-03 eta: 0:06:00 time: 0.0576 data_time: 0.0159 memory: 583 loss: 1.9360
11/16 19:31:57 - mmengine - INFO - Epoch(train) [1][1490/1563] lr: 1.0000e-03 eta: 0:06:00 time: 0.0575 data_time: 0.0157 memory: 583 loss: 1.9871
11/16 19:31:57 - mmengine - INFO - Epoch(train) [1][1500/1563] lr: 1.0000e-03 eta: 0:05:59 time: 0.0570 data_time: 0.0156 memory: 583 loss: 1.9939
11/16 19:31:58 - mmengine - INFO - Epoch(train) [1][1510/1563] lr: 1.0000e-03 eta: 0:05:59 time: 0.0567 data_time: 0.0155 memory: 583 loss: 2.0558
11/16 19:31:58 - mmengine - INFO - Epoch(train) [1][1520/1563] lr: 1.0000e-03 eta: 0:05:58 time: 0.0567 data_time: 0.0156 memory: 583 loss: 1.9977
11/16 19:31:59 - mmengine - INFO - Epoch(train) [1][1530/1563] lr: 1.0000e-03 eta: 0:05:58 time: 0.0569 data_time: 0.0156 memory: 583 loss: 1.9616
11/16 19:31:59 - mmengine - INFO - Epoch(train) [1][1540/1563] lr: 1.0000e-03 eta: 0:05:57 time: 0.0569 data_time: 0.0156 memory: 583 loss: 1.9128
11/16 19:32:00 - mmengine - INFO - Epoch(train) [1][1550/1563] lr: 1.0000e-03 eta: 0:05:56 time: 0.0568 data_time: 0.0156 memory: 583 loss: 1.9564
11/16 19:32:01 - mmengine - INFO - Epoch(train) [1][1560/1563] lr: 1.0000e-03 eta: 0:05:56 time: 0.0567 data_time: 0.0156 memory: 583 loss: 2.1554
11/16 19:32:01 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:32:01 - mmengine - INFO - Saving checkpoint at 1 epochs
11/16 19:32:01 - mmengine - WARNING - `save_param_scheduler` is True but `self.param_schedulers` is None, so skip saving parameter schedulers
11/16 19:32:02 - mmengine - INFO - Epoch(val) [1][ 10/313] eta: 0:00:23 time: 0.0761 data_time: 0.0110 memory: 583
11/16 19:32:02 - mmengine - INFO - Epoch(val) [1][ 20/313] eta: 0:00:14 time: 0.0195 data_time: 0.0097 memory: 424
11/16 19:32:03 - mmengine - INFO - Epoch(val) [1][ 30/313] eta: 0:00:10 time: 0.0194 data_time: 0.0096 memory: 424
11/16 19:32:03 - mmengine - INFO - Epoch(val) [1][ 40/313] eta: 0:00:08 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:32:03 - mmengine - INFO - Epoch(val) [1][ 50/313] eta: 0:00:07 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:03 - mmengine - INFO - Epoch(val) [1][ 60/313] eta: 0:00:06 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:03 - mmengine - INFO - Epoch(val) [1][ 70/313] eta: 0:00:06 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:03 - mmengine - INFO - Epoch(val) [1][ 80/313] eta: 0:00:05 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:32:04 - mmengine - INFO - Epoch(val) [1][ 90/313] eta: 0:00:05 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:04 - mmengine - INFO - Epoch(val) [1][100/313] eta: 0:00:04 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:04 - mmengine - INFO - Epoch(val) [1][110/313] eta: 0:00:04 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:04 - mmengine - INFO - Epoch(val) [1][120/313] eta: 0:00:04 time: 0.0165 data_time: 0.0083 memory: 424
11/16 19:32:04 - mmengine - INFO - Epoch(val) [1][130/313] eta: 0:00:03 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:04 - mmengine - INFO - Epoch(val) [1][140/313] eta: 0:00:03 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:32:05 - mmengine - INFO - Epoch(val) [1][150/313] eta: 0:00:03 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:05 - mmengine - INFO - Epoch(val) [1][160/313] eta: 0:00:03 time: 0.0165 data_time: 0.0083 memory: 424
11/16 19:32:05 - mmengine - INFO - Epoch(val) [1][170/313] eta: 0:00:02 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:32:05 - mmengine - INFO - Epoch(val) [1][180/313] eta: 0:00:02 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:32:05 - mmengine - INFO - Epoch(val) [1][190/313] eta: 0:00:02 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:32:05 - mmengine - INFO - Epoch(val) [1][200/313] eta: 0:00:02 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:32:06 - mmengine - INFO - Epoch(val) [1][210/313] eta: 0:00:02 time: 0.0165 data_time: 0.0083 memory: 424
11/16 19:32:06 - mmengine - INFO - Epoch(val) [1][220/313] eta: 0:00:01 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:06 - mmengine - INFO - Epoch(val) [1][230/313] eta: 0:00:01 time: 0.0165 data_time: 0.0083 memory: 424
11/16 19:32:06 - mmengine - INFO - Epoch(val) [1][240/313] eta: 0:00:01 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:32:06 - mmengine - INFO - Epoch(val) [1][250/313] eta: 0:00:01 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:32:06 - mmengine - INFO - Epoch(val) [1][260/313] eta: 0:00:01 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:07 - mmengine - INFO - Epoch(val) [1][270/313] eta: 0:00:00 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:32:07 - mmengine - INFO - Epoch(val) [1][280/313] eta: 0:00:00 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:07 - mmengine - INFO - Epoch(val) [1][290/313] eta: 0:00:00 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:32:07 - mmengine - INFO - Epoch(val) [1][300/313] eta: 0:00:00 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:32:07 - mmengine - INFO - Epoch(val) [1][310/313] eta: 0:00:00 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:32:07 - mmengine - INFO - Epoch(val) [1][313/313] accuracy: 35.3700 data_time: 0.0085 time: 0.0187
11/16 19:32:08 - mmengine - INFO - Epoch(train) [2][ 10/1563] lr: 1.0000e-03 eta: 0:05:55 time: 0.0514 data_time: 0.0131 memory: 583 loss: 1.8511
11/16 19:32:08 - mmengine - INFO - Epoch(train) [2][ 20/1563] lr: 1.0000e-03 eta: 0:05:54 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.9076
11/16 19:32:09 - mmengine - INFO - Epoch(train) [2][ 30/1563] lr: 1.0000e-03 eta: 0:05:53 time: 0.0515 data_time: 0.0132 memory: 583 loss: 1.9955
11/16 19:32:09 - mmengine - INFO - Epoch(train) [2][ 40/1563] lr: 1.0000e-03 eta: 0:05:53 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.8968
11/16 19:32:10 - mmengine - INFO - Epoch(train) [2][ 50/1563] lr: 1.0000e-03 eta: 0:05:52 time: 0.0509 data_time: 0.0132 memory: 583 loss: 2.0139
11/16 19:32:10 - mmengine - INFO - Epoch(train) [2][ 60/1563] lr: 1.0000e-03 eta: 0:05:51 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.9494
11/16 19:32:11 - mmengine - INFO - Epoch(train) [2][ 70/1563] lr: 1.0000e-03 eta: 0:05:50 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.9847
11/16 19:32:11 - mmengine - INFO - Epoch(train) [2][ 80/1563] lr: 1.0000e-03 eta: 0:05:50 time: 0.0520 data_time: 0.0135 memory: 583 loss: 2.0855
11/16 19:32:12 - mmengine - INFO - Epoch(train) [2][ 90/1563] lr: 1.0000e-03 eta: 0:05:49 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.9568
11/16 19:32:13 - mmengine - INFO - Epoch(train) [2][ 100/1563] lr: 1.0000e-03 eta: 0:05:48 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.9868
11/16 19:32:13 - mmengine - INFO - Epoch(train) [2][ 110/1563] lr: 1.0000e-03 eta: 0:05:47 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.9593
11/16 19:32:14 - mmengine - INFO - Epoch(train) [2][ 120/1563] lr: 1.0000e-03 eta: 0:05:47 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7831
11/16 19:32:14 - mmengine - INFO - Epoch(train) [2][ 130/1563] lr: 1.0000e-03 eta: 0:05:46 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.9188
11/16 19:32:15 - mmengine - INFO - Epoch(train) [2][ 140/1563] lr: 1.0000e-03 eta: 0:05:45 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.8471
11/16 19:32:15 - mmengine - INFO - Epoch(train) [2][ 150/1563] lr: 1.0000e-03 eta: 0:05:44 time: 0.0521 data_time: 0.0137 memory: 583 loss: 1.8796
11/16 19:32:16 - mmengine - INFO - Epoch(train) [2][ 160/1563] lr: 1.0000e-03 eta: 0:05:44 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8865
11/16 19:32:16 - mmengine - INFO - Epoch(train) [2][ 170/1563] lr: 1.0000e-03 eta: 0:05:43 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8872
11/16 19:32:17 - mmengine - INFO - Epoch(train) [2][ 180/1563] lr: 1.0000e-03 eta: 0:05:42 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.9043
11/16 19:32:17 - mmengine - INFO - Epoch(train) [2][ 190/1563] lr: 1.0000e-03 eta: 0:05:41 time: 0.0512 data_time: 0.0134 memory: 583 loss: 2.0034
11/16 19:32:18 - mmengine - INFO - Epoch(train) [2][ 200/1563] lr: 1.0000e-03 eta: 0:05:41 time: 0.0513 data_time: 0.0133 memory: 583 loss: 1.8433
11/16 19:32:18 - mmengine - INFO - Epoch(train) [2][ 210/1563] lr: 1.0000e-03 eta: 0:05:40 time: 0.0522 data_time: 0.0135 memory: 583 loss: 2.0625
11/16 19:32:19 - mmengine - INFO - Epoch(train) [2][ 220/1563] lr: 1.0000e-03 eta: 0:05:39 time: 0.0520 data_time: 0.0134 memory: 583 loss: 2.0319
11/16 19:32:19 - mmengine - INFO - Epoch(train) [2][ 230/1563] lr: 1.0000e-03 eta: 0:05:39 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.8396
11/16 19:32:20 - mmengine - INFO - Epoch(train) [2][ 240/1563] lr: 1.0000e-03 eta: 0:05:38 time: 0.0519 data_time: 0.0132 memory: 583 loss: 1.9666
11/16 19:32:20 - mmengine - INFO - Epoch(train) [2][ 250/1563] lr: 1.0000e-03 eta: 0:05:37 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.8276
11/16 19:32:21 - mmengine - INFO - Epoch(train) [2][ 260/1563] lr: 1.0000e-03 eta: 0:05:36 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.8790
11/16 19:32:21 - mmengine - INFO - Epoch(train) [2][ 270/1563] lr: 1.0000e-03 eta: 0:05:36 time: 0.0515 data_time: 0.0132 memory: 583 loss: 1.7974
11/16 19:32:22 - mmengine - INFO - Epoch(train) [2][ 280/1563] lr: 1.0000e-03 eta: 0:05:35 time: 0.0514 data_time: 0.0132 memory: 583 loss: 1.8357
11/16 19:32:22 - mmengine - INFO - Epoch(train) [2][ 290/1563] lr: 1.0000e-03 eta: 0:05:34 time: 0.0515 data_time: 0.0131 memory: 583 loss: 1.8770
11/16 19:32:23 - mmengine - INFO - Epoch(train) [2][ 300/1563] lr: 1.0000e-03 eta: 0:05:34 time: 0.0515 data_time: 0.0132 memory: 583 loss: 1.9502
11/16 19:32:23 - mmengine - INFO - Epoch(train) [2][ 310/1563] lr: 1.0000e-03 eta: 0:05:33 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.9055
11/16 19:32:24 - mmengine - INFO - Epoch(train) [2][ 320/1563] lr: 1.0000e-03 eta: 0:05:32 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.9013
11/16 19:32:24 - mmengine - INFO - Epoch(train) [2][ 330/1563] lr: 1.0000e-03 eta: 0:05:32 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.8961
11/16 19:32:25 - mmengine - INFO - Epoch(train) [2][ 340/1563] lr: 1.0000e-03 eta: 0:05:31 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.9397
11/16 19:32:25 - mmengine - INFO - Epoch(train) [2][ 350/1563] lr: 1.0000e-03 eta: 0:05:30 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.9173
11/16 19:32:26 - mmengine - INFO - Epoch(train) [2][ 360/1563] lr: 1.0000e-03 eta: 0:05:29 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.8247
11/16 19:32:26 - mmengine - INFO - Epoch(train) [2][ 370/1563] lr: 1.0000e-03 eta: 0:05:29 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.8350
11/16 19:32:27 - mmengine - INFO - Epoch(train) [2][ 380/1563] lr: 1.0000e-03 eta: 0:05:28 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.8715
11/16 19:32:28 - mmengine - INFO - Epoch(train) [2][ 390/1563] lr: 1.0000e-03 eta: 0:05:27 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.7986
11/16 19:32:28 - mmengine - INFO - Epoch(train) [2][ 400/1563] lr: 1.0000e-03 eta: 0:05:27 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.9252
11/16 19:32:29 - mmengine - INFO - Epoch(train) [2][ 410/1563] lr: 1.0000e-03 eta: 0:05:26 time: 0.0523 data_time: 0.0134 memory: 583 loss: 1.8617
11/16 19:32:29 - mmengine - INFO - Epoch(train) [2][ 420/1563] lr: 1.0000e-03 eta: 0:05:25 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.8652
11/16 19:32:30 - mmengine - INFO - Epoch(train) [2][ 430/1563] lr: 1.0000e-03 eta: 0:05:25 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.8999
11/16 19:32:30 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:32:30 - mmengine - INFO - Epoch(train) [2][ 440/1563] lr: 1.0000e-03 eta: 0:05:24 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.7591
11/16 19:32:31 - mmengine - INFO - Epoch(train) [2][ 450/1563] lr: 1.0000e-03 eta: 0:05:23 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.8833
11/16 19:32:31 - mmengine - INFO - Epoch(train) [2][ 460/1563] lr: 1.0000e-03 eta: 0:05:23 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.7220
11/16 19:32:32 - mmengine - INFO - Epoch(train) [2][ 470/1563] lr: 1.0000e-03 eta: 0:05:22 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.9039
11/16 19:32:32 - mmengine - INFO - Epoch(train) [2][ 480/1563] lr: 1.0000e-03 eta: 0:05:21 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.8110
11/16 19:32:33 - mmengine - INFO - Epoch(train) [2][ 490/1563] lr: 1.0000e-03 eta: 0:05:21 time: 0.0521 data_time: 0.0133 memory: 583 loss: 1.7856
11/16 19:32:33 - mmengine - INFO - Epoch(train) [2][ 500/1563] lr: 1.0000e-03 eta: 0:05:20 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.8020
11/16 19:32:34 - mmengine - INFO - Epoch(train) [2][ 510/1563] lr: 1.0000e-03 eta: 0:05:19 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.8469
11/16 19:32:34 - mmengine - INFO - Epoch(train) [2][ 520/1563] lr: 1.0000e-03 eta: 0:05:19 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.8006
11/16 19:32:35 - mmengine - INFO - Epoch(train) [2][ 530/1563] lr: 1.0000e-03 eta: 0:05:18 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.7958
11/16 19:32:35 - mmengine - INFO - Epoch(train) [2][ 540/1563] lr: 1.0000e-03 eta: 0:05:17 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.7669
11/16 19:32:36 - mmengine - INFO - Epoch(train) [2][ 550/1563] lr: 1.0000e-03 eta: 0:05:17 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.8769
11/16 19:32:36 - mmengine - INFO - Epoch(train) [2][ 560/1563] lr: 1.0000e-03 eta: 0:05:16 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.7606
11/16 19:32:37 - mmengine - INFO - Epoch(train) [2][ 570/1563] lr: 1.0000e-03 eta: 0:05:15 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.8220
11/16 19:32:37 - mmengine - INFO - Epoch(train) [2][ 580/1563] lr: 1.0000e-03 eta: 0:05:15 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7862
11/16 19:32:38 - mmengine - INFO - Epoch(train) [2][ 590/1563] lr: 1.0000e-03 eta: 0:05:14 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.8417
11/16 19:32:38 - mmengine - INFO - Epoch(train) [2][ 600/1563] lr: 1.0000e-03 eta: 0:05:13 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.9000
11/16 19:32:39 - mmengine - INFO - Epoch(train) [2][ 610/1563] lr: 1.0000e-03 eta: 0:05:13 time: 0.0527 data_time: 0.0138 memory: 583 loss: 1.7480
11/16 19:32:39 - mmengine - INFO - Epoch(train) [2][ 620/1563] lr: 1.0000e-03 eta: 0:05:12 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.8431
11/16 19:32:40 - mmengine - INFO - Epoch(train) [2][ 630/1563] lr: 1.0000e-03 eta: 0:05:12 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8513
11/16 19:32:41 - mmengine - INFO - Epoch(train) [2][ 640/1563] lr: 1.0000e-03 eta: 0:05:11 time: 0.0521 data_time: 0.0133 memory: 583 loss: 1.8626
11/16 19:32:41 - mmengine - INFO - Epoch(train) [2][ 650/1563] lr: 1.0000e-03 eta: 0:05:10 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.7403
11/16 19:32:42 - mmengine - INFO - Epoch(train) [2][ 660/1563] lr: 1.0000e-03 eta: 0:05:10 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6988
11/16 19:32:42 - mmengine - INFO - Epoch(train) [2][ 670/1563] lr: 1.0000e-03 eta: 0:05:09 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8228
11/16 19:32:43 - mmengine - INFO - Epoch(train) [2][ 680/1563] lr: 1.0000e-03 eta: 0:05:08 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8248
11/16 19:32:43 - mmengine - INFO - Epoch(train) [2][ 690/1563] lr: 1.0000e-03 eta: 0:05:08 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.8048
11/16 19:32:44 - mmengine - INFO - Epoch(train) [2][ 700/1563] lr: 1.0000e-03 eta: 0:05:07 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.7265
11/16 19:32:44 - mmengine - INFO - Epoch(train) [2][ 710/1563] lr: 1.0000e-03 eta: 0:05:06 time: 0.0523 data_time: 0.0133 memory: 583 loss: 1.9501
11/16 19:32:45 - mmengine - INFO - Epoch(train) [2][ 720/1563] lr: 1.0000e-03 eta: 0:05:06 time: 0.0502 data_time: 0.0134 memory: 583 loss: 1.8235
11/16 19:32:45 - mmengine - INFO - Epoch(train) [2][ 730/1563] lr: 1.0000e-03 eta: 0:05:05 time: 0.0514 data_time: 0.0132 memory: 583 loss: 1.6962
11/16 19:32:46 - mmengine - INFO - Epoch(train) [2][ 740/1563] lr: 1.0000e-03 eta: 0:05:04 time: 0.0510 data_time: 0.0134 memory: 583 loss: 1.7234
11/16 19:32:46 - mmengine - INFO - Epoch(train) [2][ 750/1563] lr: 1.0000e-03 eta: 0:05:04 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.8508
11/16 19:32:47 - mmengine - INFO - Epoch(train) [2][ 760/1563] lr: 1.0000e-03 eta: 0:05:03 time: 0.0514 data_time: 0.0132 memory: 583 loss: 1.8899
11/16 19:32:47 - mmengine - INFO - Epoch(train) [2][ 770/1563] lr: 1.0000e-03 eta: 0:05:02 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.8178
11/16 19:32:48 - mmengine - INFO - Epoch(train) [2][ 780/1563] lr: 1.0000e-03 eta: 0:05:02 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.5996
11/16 19:32:48 - mmengine - INFO - Epoch(train) [2][ 790/1563] lr: 1.0000e-03 eta: 0:05:01 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.8101
11/16 19:32:49 - mmengine - INFO - Epoch(train) [2][ 800/1563] lr: 1.0000e-03 eta: 0:05:01 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7247
11/16 19:32:49 - mmengine - INFO - Epoch(train) [2][ 810/1563] lr: 1.0000e-03 eta: 0:05:00 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.7869
11/16 19:32:50 - mmengine - INFO - Epoch(train) [2][ 820/1563] lr: 1.0000e-03 eta: 0:04:59 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7606
11/16 19:32:50 - mmengine - INFO - Epoch(train) [2][ 830/1563] lr: 1.0000e-03 eta: 0:04:59 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.9957
11/16 19:32:51 - mmengine - INFO - Epoch(train) [2][ 840/1563] lr: 1.0000e-03 eta: 0:04:58 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.7821
11/16 19:32:51 - mmengine - INFO - Epoch(train) [2][ 850/1563] lr: 1.0000e-03 eta: 0:04:57 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8700
11/16 19:32:52 - mmengine - INFO - Epoch(train) [2][ 860/1563] lr: 1.0000e-03 eta: 0:04:57 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7949
11/16 19:32:52 - mmengine - INFO - Epoch(train) [2][ 870/1563] lr: 1.0000e-03 eta: 0:04:56 time: 0.0517 data_time: 0.0134 memory: 583 loss: 1.7867
11/16 19:32:53 - mmengine - INFO - Epoch(train) [2][ 880/1563] lr: 1.0000e-03 eta: 0:04:56 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.8850
11/16 19:32:53 - mmengine - INFO - Epoch(train) [2][ 890/1563] lr: 1.0000e-03 eta: 0:04:55 time: 0.0516 data_time: 0.0134 memory: 583 loss: 1.8644
11/16 19:32:54 - mmengine - INFO - Epoch(train) [2][ 900/1563] lr: 1.0000e-03 eta: 0:04:54 time: 0.0514 data_time: 0.0132 memory: 583 loss: 1.8152
11/16 19:32:54 - mmengine - INFO - Epoch(train) [2][ 910/1563] lr: 1.0000e-03 eta: 0:04:54 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.8192
11/16 19:32:55 - mmengine - INFO - Epoch(train) [2][ 920/1563] lr: 1.0000e-03 eta: 0:04:53 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.6881
11/16 19:32:56 - mmengine - INFO - Epoch(train) [2][ 930/1563] lr: 1.0000e-03 eta: 0:04:52 time: 0.0514 data_time: 0.0136 memory: 583 loss: 1.7314
11/16 19:32:56 - mmengine - INFO - Epoch(train) [2][ 940/1563] lr: 1.0000e-03 eta: 0:04:52 time: 0.0514 data_time: 0.0134 memory: 583 loss: 1.7789
11/16 19:32:57 - mmengine - INFO - Epoch(train) [2][ 950/1563] lr: 1.0000e-03 eta: 0:04:51 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.8036
11/16 19:32:57 - mmengine - INFO - Epoch(train) [2][ 960/1563] lr: 1.0000e-03 eta: 0:04:51 time: 0.0509 data_time: 0.0133 memory: 583 loss: 1.8447
11/16 19:32:58 - mmengine - INFO - Epoch(train) [2][ 970/1563] lr: 1.0000e-03 eta: 0:04:50 time: 0.0515 data_time: 0.0133 memory: 583 loss: 1.8573
11/16 19:32:58 - mmengine - INFO - Epoch(train) [2][ 980/1563] lr: 1.0000e-03 eta: 0:04:49 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7953
11/16 19:32:59 - mmengine - INFO - Epoch(train) [2][ 990/1563] lr: 1.0000e-03 eta: 0:04:49 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6438
11/16 19:32:59 - mmengine - INFO - Epoch(train) [2][1000/1563] lr: 1.0000e-03 eta: 0:04:48 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.8462
11/16 19:33:00 - mmengine - INFO - Epoch(train) [2][1010/1563] lr: 1.0000e-03 eta: 0:04:47 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7599
11/16 19:33:00 - mmengine - INFO - Epoch(train) [2][1020/1563] lr: 1.0000e-03 eta: 0:04:47 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.7938
11/16 19:33:01 - mmengine - INFO - Epoch(train) [2][1030/1563] lr: 1.0000e-03 eta: 0:04:46 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.8831
11/16 19:33:01 - mmengine - INFO - Epoch(train) [2][1040/1563] lr: 1.0000e-03 eta: 0:04:46 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7699
11/16 19:33:02 - mmengine - INFO - Epoch(train) [2][1050/1563] lr: 1.0000e-03 eta: 0:04:45 time: 0.0511 data_time: 0.0133 memory: 583 loss: 1.7876
11/16 19:33:02 - mmengine - INFO - Epoch(train) [2][1060/1563] lr: 1.0000e-03 eta: 0:04:44 time: 0.0501 data_time: 0.0133 memory: 583 loss: 1.8230
11/16 19:33:03 - mmengine - INFO - Epoch(train) [2][1070/1563] lr: 1.0000e-03 eta: 0:04:44 time: 0.0499 data_time: 0.0132 memory: 583 loss: 1.8396
11/16 19:33:03 - mmengine - INFO - Epoch(train) [2][1080/1563] lr: 1.0000e-03 eta: 0:04:43 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.7037
11/16 19:33:04 - mmengine - INFO - Epoch(train) [2][1090/1563] lr: 1.0000e-03 eta: 0:04:43 time: 0.0520 data_time: 0.0136 memory: 583 loss: 1.6823
11/16 19:33:04 - mmengine - INFO - Epoch(train) [2][1100/1563] lr: 1.0000e-03 eta: 0:04:42 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.8701
11/16 19:33:05 - mmengine - INFO - Epoch(train) [2][1110/1563] lr: 1.0000e-03 eta: 0:04:41 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8504
11/16 19:33:05 - mmengine - INFO - Epoch(train) [2][1120/1563] lr: 1.0000e-03 eta: 0:04:41 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.8349
11/16 19:33:06 - mmengine - INFO - Epoch(train) [2][1130/1563] lr: 1.0000e-03 eta: 0:04:40 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.7067
11/16 19:33:06 - mmengine - INFO - Epoch(train) [2][1140/1563] lr: 1.0000e-03 eta: 0:04:39 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.8023
11/16 19:33:07 - mmengine - INFO - Epoch(train) [2][1150/1563] lr: 1.0000e-03 eta: 0:04:39 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6927
11/16 19:33:07 - mmengine - INFO - Epoch(train) [2][1160/1563] lr: 1.0000e-03 eta: 0:04:38 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6391
11/16 19:33:08 - mmengine - INFO - Epoch(train) [2][1170/1563] lr: 1.0000e-03 eta: 0:04:38 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.7171
11/16 19:33:08 - mmengine - INFO - Epoch(train) [2][1180/1563] lr: 1.0000e-03 eta: 0:04:37 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.7668
11/16 19:33:09 - mmengine - INFO - Epoch(train) [2][1190/1563] lr: 1.0000e-03 eta: 0:04:36 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7758
11/16 19:33:09 - mmengine - INFO - Epoch(train) [2][1200/1563] lr: 1.0000e-03 eta: 0:04:36 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.7493
11/16 19:33:10 - mmengine - INFO - Epoch(train) [2][1210/1563] lr: 1.0000e-03 eta: 0:04:35 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.7973
11/16 19:33:11 - mmengine - INFO - Epoch(train) [2][1220/1563] lr: 1.0000e-03 eta: 0:04:35 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.8105
11/16 19:33:11 - mmengine - INFO - Epoch(train) [2][1230/1563] lr: 1.0000e-03 eta: 0:04:34 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.8216
11/16 19:33:12 - mmengine - INFO - Epoch(train) [2][1240/1563] lr: 1.0000e-03 eta: 0:04:33 time: 0.0508 data_time: 0.0132 memory: 583 loss: 1.8057
11/16 19:33:12 - mmengine - INFO - Epoch(train) [2][1250/1563] lr: 1.0000e-03 eta: 0:04:33 time: 0.0514 data_time: 0.0132 memory: 583 loss: 1.7161
11/16 19:33:13 - mmengine - INFO - Epoch(train) [2][1260/1563] lr: 1.0000e-03 eta: 0:04:32 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7758
11/16 19:33:13 - mmengine - INFO - Epoch(train) [2][1270/1563] lr: 1.0000e-03 eta: 0:04:32 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.7466
11/16 19:33:14 - mmengine - INFO - Epoch(train) [2][1280/1563] lr: 1.0000e-03 eta: 0:04:31 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.7950
11/16 19:33:14 - mmengine - INFO - Epoch(train) [2][1290/1563] lr: 1.0000e-03 eta: 0:04:30 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.8379
11/16 19:33:15 - mmengine - INFO - Epoch(train) [2][1300/1563] lr: 1.0000e-03 eta: 0:04:30 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.7630
11/16 19:33:15 - mmengine - INFO - Epoch(train) [2][1310/1563] lr: 1.0000e-03 eta: 0:04:29 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.7248
11/16 19:33:16 - mmengine - INFO - Epoch(train) [2][1320/1563] lr: 1.0000e-03 eta: 0:04:29 time: 0.0513 data_time: 0.0132 memory: 583 loss: 1.6909
11/16 19:33:16 - mmengine - INFO - Epoch(train) [2][1330/1563] lr: 1.0000e-03 eta: 0:04:28 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.7019
11/16 19:33:17 - mmengine - INFO - Epoch(train) [2][1340/1563] lr: 1.0000e-03 eta: 0:04:27 time: 0.0517 data_time: 0.0134 memory: 583 loss: 1.8237
11/16 19:33:17 - mmengine - INFO - Epoch(train) [2][1350/1563] lr: 1.0000e-03 eta: 0:04:27 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7761
11/16 19:33:18 - mmengine - INFO - Epoch(train) [2][1360/1563] lr: 1.0000e-03 eta: 0:04:26 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.7088
11/16 19:33:18 - mmengine - INFO - Epoch(train) [2][1370/1563] lr: 1.0000e-03 eta: 0:04:26 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7784
11/16 19:33:19 - mmengine - INFO - Epoch(train) [2][1380/1563] lr: 1.0000e-03 eta: 0:04:25 time: 0.0526 data_time: 0.0138 memory: 583 loss: 1.8132
11/16 19:33:19 - mmengine - INFO - Epoch(train) [2][1390/1563] lr: 1.0000e-03 eta: 0:04:25 time: 0.0528 data_time: 0.0140 memory: 583 loss: 1.7568
11/16 19:33:20 - mmengine - INFO - Epoch(train) [2][1400/1563] lr: 1.0000e-03 eta: 0:04:24 time: 0.0527 data_time: 0.0138 memory: 583 loss: 1.7457
11/16 19:33:20 - mmengine - INFO - Epoch(train) [2][1410/1563] lr: 1.0000e-03 eta: 0:04:23 time: 0.0525 data_time: 0.0135 memory: 583 loss: 1.6736
11/16 19:33:21 - mmengine - INFO - Epoch(train) [2][1420/1563] lr: 1.0000e-03 eta: 0:04:23 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.7935
11/16 19:33:21 - mmengine - INFO - Epoch(train) [2][1430/1563] lr: 1.0000e-03 eta: 0:04:22 time: 0.0528 data_time: 0.0138 memory: 583 loss: 1.7187
11/16 19:33:22 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:33:22 - mmengine - INFO - Epoch(train) [2][1440/1563] lr: 1.0000e-03 eta: 0:04:22 time: 0.0532 data_time: 0.0142 memory: 583 loss: 1.7448
11/16 19:33:22 - mmengine - INFO - Epoch(train) [2][1450/1563] lr: 1.0000e-03 eta: 0:04:21 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.6961
11/16 19:33:23 - mmengine - INFO - Epoch(train) [2][1460/1563] lr: 1.0000e-03 eta: 0:04:21 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.6872
11/16 19:33:24 - mmengine - INFO - Epoch(train) [2][1470/1563] lr: 1.0000e-03 eta: 0:04:20 time: 0.0526 data_time: 0.0138 memory: 583 loss: 1.9040
11/16 19:33:24 - mmengine - INFO - Epoch(train) [2][1480/1563] lr: 1.0000e-03 eta: 0:04:19 time: 0.0524 data_time: 0.0135 memory: 583 loss: 1.8377
11/16 19:33:25 - mmengine - INFO - Epoch(train) [2][1490/1563] lr: 1.0000e-03 eta: 0:04:19 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.7021
11/16 19:33:25 - mmengine - INFO - Epoch(train) [2][1500/1563] lr: 1.0000e-03 eta: 0:04:18 time: 0.0525 data_time: 0.0135 memory: 583 loss: 1.8644
11/16 19:33:26 - mmengine - INFO - Epoch(train) [2][1510/1563] lr: 1.0000e-03 eta: 0:04:18 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.7350
11/16 19:33:26 - mmengine - INFO - Epoch(train) [2][1520/1563] lr: 1.0000e-03 eta: 0:04:17 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.8119
11/16 19:33:27 - mmengine - INFO - Epoch(train) [2][1530/1563] lr: 1.0000e-03 eta: 0:04:17 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.7103
11/16 19:33:27 - mmengine - INFO - Epoch(train) [2][1540/1563] lr: 1.0000e-03 eta: 0:04:16 time: 0.0526 data_time: 0.0137 memory: 583 loss: 1.6662
11/16 19:33:28 - mmengine - INFO - Epoch(train) [2][1550/1563] lr: 1.0000e-03 eta: 0:04:15 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.6727
11/16 19:33:28 - mmengine - INFO - Epoch(train) [2][1560/1563] lr: 1.0000e-03 eta: 0:04:15 time: 0.0528 data_time: 0.0139 memory: 583 loss: 1.8069
11/16 19:33:28 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:33:28 - mmengine - INFO - Saving checkpoint at 2 epochs
11/16 19:33:29 - mmengine - INFO - Epoch(val) [2][ 10/313] eta: 0:00:05 time: 0.0182 data_time: 0.0097 memory: 583
11/16 19:33:29 - mmengine - INFO - Epoch(val) [2][ 20/313] eta: 0:00:05 time: 0.0171 data_time: 0.0086 memory: 424
11/16 19:33:29 - mmengine - INFO - Epoch(val) [2][ 30/313] eta: 0:00:04 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:30 - mmengine - INFO - Epoch(val) [2][ 40/313] eta: 0:00:04 time: 0.0173 data_time: 0.0086 memory: 424
11/16 19:33:30 - mmengine - INFO - Epoch(val) [2][ 50/313] eta: 0:00:04 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:33:30 - mmengine - INFO - Epoch(val) [2][ 60/313] eta: 0:00:04 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:30 - mmengine - INFO - Epoch(val) [2][ 70/313] eta: 0:00:04 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:33:30 - mmengine - INFO - Epoch(val) [2][ 80/313] eta: 0:00:04 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:30 - mmengine - INFO - Epoch(val) [2][ 90/313] eta: 0:00:03 time: 0.0170 data_time: 0.0084 memory: 424
11/16 19:33:31 - mmengine - INFO - Epoch(val) [2][100/313] eta: 0:00:03 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:33:31 - mmengine - INFO - Epoch(val) [2][110/313] eta: 0:00:03 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:33:31 - mmengine - INFO - Epoch(val) [2][120/313] eta: 0:00:03 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:33:31 - mmengine - INFO - Epoch(val) [2][130/313] eta: 0:00:03 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:33:31 - mmengine - INFO - Epoch(val) [2][140/313] eta: 0:00:02 time: 0.0172 data_time: 0.0085 memory: 424
11/16 19:33:31 - mmengine - INFO - Epoch(val) [2][150/313] eta: 0:00:02 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:32 - mmengine - INFO - Epoch(val) [2][160/313] eta: 0:00:02 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:32 - mmengine - INFO - Epoch(val) [2][170/313] eta: 0:00:02 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:32 - mmengine - INFO - Epoch(val) [2][180/313] eta: 0:00:02 time: 0.0171 data_time: 0.0086 memory: 424
11/16 19:33:32 - mmengine - INFO - Epoch(val) [2][190/313] eta: 0:00:02 time: 0.0171 data_time: 0.0086 memory: 424
11/16 19:33:32 - mmengine - INFO - Epoch(val) [2][200/313] eta: 0:00:01 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:33 - mmengine - INFO - Epoch(val) [2][210/313] eta: 0:00:01 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:33:33 - mmengine - INFO - Epoch(val) [2][220/313] eta: 0:00:01 time: 0.0173 data_time: 0.0086 memory: 424
11/16 19:33:33 - mmengine - INFO - Epoch(val) [2][230/313] eta: 0:00:01 time: 0.0175 data_time: 0.0087 memory: 424
11/16 19:33:33 - mmengine - INFO - Epoch(val) [2][240/313] eta: 0:00:01 time: 0.0173 data_time: 0.0086 memory: 424
11/16 19:33:33 - mmengine - INFO - Epoch(val) [2][250/313] eta: 0:00:01 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:33 - mmengine - INFO - Epoch(val) [2][260/313] eta: 0:00:00 time: 0.0172 data_time: 0.0085 memory: 424
11/16 19:33:34 - mmengine - INFO - Epoch(val) [2][270/313] eta: 0:00:00 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:34 - mmengine - INFO - Epoch(val) [2][280/313] eta: 0:00:00 time: 0.0172 data_time: 0.0085 memory: 424
11/16 19:33:34 - mmengine - INFO - Epoch(val) [2][290/313] eta: 0:00:00 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:34 - mmengine - INFO - Epoch(val) [2][300/313] eta: 0:00:00 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:34 - mmengine - INFO - Epoch(val) [2][310/313] eta: 0:00:00 time: 0.0172 data_time: 0.0086 memory: 424
11/16 19:33:34 - mmengine - INFO - Epoch(val) [2][313/313] accuracy: 43.0100 data_time: 0.0086 time: 0.0172
11/16 19:33:35 - mmengine - INFO - Epoch(train) [3][ 10/1563] lr: 1.0000e-03 eta: 0:04:14 time: 0.0533 data_time: 0.0139 memory: 583 loss: 1.7525
11/16 19:33:35 - mmengine - INFO - Epoch(train) [3][ 20/1563] lr: 1.0000e-03 eta: 0:04:14 time: 0.0540 data_time: 0.0148 memory: 583 loss: 1.7308
11/16 19:33:36 - mmengine - INFO - Epoch(train) [3][ 30/1563] lr: 1.0000e-03 eta: 0:04:13 time: 0.0527 data_time: 0.0139 memory: 583 loss: 1.6290
11/16 19:33:36 - mmengine - INFO - Epoch(train) [3][ 40/1563] lr: 1.0000e-03 eta: 0:04:12 time: 0.0529 data_time: 0.0136 memory: 583 loss: 1.6476
11/16 19:33:37 - mmengine - INFO - Epoch(train) [3][ 50/1563] lr: 1.0000e-03 eta: 0:04:12 time: 0.0561 data_time: 0.0164 memory: 583 loss: 1.7265
11/16 19:33:38 - mmengine - INFO - Epoch(train) [3][ 60/1563] lr: 1.0000e-03 eta: 0:04:11 time: 0.0553 data_time: 0.0149 memory: 583 loss: 1.8372
11/16 19:33:38 - mmengine - INFO - Epoch(train) [3][ 70/1563] lr: 1.0000e-03 eta: 0:04:11 time: 0.0595 data_time: 0.0171 memory: 583 loss: 1.6949
11/16 19:33:39 - mmengine - INFO - Epoch(train) [3][ 80/1563] lr: 1.0000e-03 eta: 0:04:10 time: 0.0533 data_time: 0.0144 memory: 583 loss: 1.7641
11/16 19:33:39 - mmengine - INFO - Epoch(train) [3][ 90/1563] lr: 1.0000e-03 eta: 0:04:10 time: 0.0552 data_time: 0.0153 memory: 583 loss: 1.6955
11/16 19:33:40 - mmengine - INFO - Epoch(train) [3][ 100/1563] lr: 1.0000e-03 eta: 0:04:09 time: 0.0544 data_time: 0.0144 memory: 583 loss: 1.6036
11/16 19:33:40 - mmengine - INFO - Epoch(train) [3][ 110/1563] lr: 1.0000e-03 eta: 0:04:09 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.7715
11/16 19:33:41 - mmengine - INFO - Epoch(train) [3][ 120/1563] lr: 1.0000e-03 eta: 0:04:08 time: 0.0567 data_time: 0.0158 memory: 583 loss: 1.6335
11/16 19:33:41 - mmengine - INFO - Epoch(train) [3][ 130/1563] lr: 1.0000e-03 eta: 0:04:08 time: 0.0527 data_time: 0.0136 memory: 583 loss: 1.7649
11/16 19:33:42 - mmengine - INFO - Epoch(train) [3][ 140/1563] lr: 1.0000e-03 eta: 0:04:07 time: 0.0543 data_time: 0.0151 memory: 583 loss: 1.5909
11/16 19:33:42 - mmengine - INFO - Epoch(train) [3][ 150/1563] lr: 1.0000e-03 eta: 0:04:06 time: 0.0529 data_time: 0.0137 memory: 583 loss: 1.6598
11/16 19:33:43 - mmengine - INFO - Epoch(train) [3][ 160/1563] lr: 1.0000e-03 eta: 0:04:06 time: 0.0535 data_time: 0.0139 memory: 583 loss: 1.6848
11/16 19:33:44 - mmengine - INFO - Epoch(train) [3][ 170/1563] lr: 1.0000e-03 eta: 0:04:05 time: 0.0534 data_time: 0.0139 memory: 583 loss: 1.7333
11/16 19:33:44 - mmengine - INFO - Epoch(train) [3][ 180/1563] lr: 1.0000e-03 eta: 0:04:05 time: 0.0530 data_time: 0.0135 memory: 583 loss: 1.6091
11/16 19:33:45 - mmengine - INFO - Epoch(train) [3][ 190/1563] lr: 1.0000e-03 eta: 0:04:04 time: 0.0541 data_time: 0.0144 memory: 583 loss: 1.7022
11/16 19:33:45 - mmengine - INFO - Epoch(train) [3][ 200/1563] lr: 1.0000e-03 eta: 0:04:04 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.8573
11/16 19:33:46 - mmengine - INFO - Epoch(train) [3][ 210/1563] lr: 1.0000e-03 eta: 0:04:03 time: 0.0550 data_time: 0.0152 memory: 583 loss: 1.6577
11/16 19:33:46 - mmengine - INFO - Epoch(train) [3][ 220/1563] lr: 1.0000e-03 eta: 0:04:03 time: 0.0540 data_time: 0.0145 memory: 583 loss: 1.8743
11/16 19:33:47 - mmengine - INFO - Epoch(train) [3][ 230/1563] lr: 1.0000e-03 eta: 0:04:02 time: 0.0589 data_time: 0.0169 memory: 583 loss: 1.8006
11/16 19:33:47 - mmengine - INFO - Epoch(train) [3][ 240/1563] lr: 1.0000e-03 eta: 0:04:02 time: 0.0542 data_time: 0.0150 memory: 583 loss: 1.7756
11/16 19:33:48 - mmengine - INFO - Epoch(train) [3][ 250/1563] lr: 1.0000e-03 eta: 0:04:01 time: 0.0537 data_time: 0.0143 memory: 583 loss: 1.6863
11/16 19:33:48 - mmengine - INFO - Epoch(train) [3][ 260/1563] lr: 1.0000e-03 eta: 0:04:00 time: 0.0552 data_time: 0.0155 memory: 583 loss: 1.7039
11/16 19:33:49 - mmengine - INFO - Epoch(train) [3][ 270/1563] lr: 1.0000e-03 eta: 0:04:00 time: 0.0548 data_time: 0.0155 memory: 583 loss: 1.6986
11/16 19:33:50 - mmengine - INFO - Epoch(train) [3][ 280/1563] lr: 1.0000e-03 eta: 0:03:59 time: 0.0552 data_time: 0.0153 memory: 583 loss: 1.7122
11/16 19:33:50 - mmengine - INFO - Epoch(train) [3][ 290/1563] lr: 1.0000e-03 eta: 0:03:59 time: 0.0536 data_time: 0.0147 memory: 583 loss: 1.7163
11/16 19:33:51 - mmengine - INFO - Epoch(train) [3][ 300/1563] lr: 1.0000e-03 eta: 0:03:58 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.6804
11/16 19:33:51 - mmengine - INFO - Epoch(train) [3][ 310/1563] lr: 1.0000e-03 eta: 0:03:58 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.6541
11/16 19:33:52 - mmengine - INFO - Epoch(train) [3][ 320/1563] lr: 1.0000e-03 eta: 0:03:57 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.5949
11/16 19:33:52 - mmengine - INFO - Epoch(train) [3][ 330/1563] lr: 1.0000e-03 eta: 0:03:57 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6530
11/16 19:33:53 - mmengine - INFO - Epoch(train) [3][ 340/1563] lr: 1.0000e-03 eta: 0:03:56 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.6009
11/16 19:33:53 - mmengine - INFO - Epoch(train) [3][ 350/1563] lr: 1.0000e-03 eta: 0:03:55 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7795
11/16 19:33:54 - mmengine - INFO - Epoch(train) [3][ 360/1563] lr: 1.0000e-03 eta: 0:03:55 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.7391
11/16 19:33:54 - mmengine - INFO - Epoch(train) [3][ 370/1563] lr: 1.0000e-03 eta: 0:03:54 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.7473
11/16 19:33:55 - mmengine - INFO - Epoch(train) [3][ 380/1563] lr: 1.0000e-03 eta: 0:03:54 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.7001
11/16 19:33:55 - mmengine - INFO - Epoch(train) [3][ 390/1563] lr: 1.0000e-03 eta: 0:03:53 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.8269
11/16 19:33:56 - mmengine - INFO - Epoch(train) [3][ 400/1563] lr: 1.0000e-03 eta: 0:03:53 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6615
11/16 19:33:56 - mmengine - INFO - Epoch(train) [3][ 410/1563] lr: 1.0000e-03 eta: 0:03:52 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.7525
11/16 19:33:57 - mmengine - INFO - Epoch(train) [3][ 420/1563] lr: 1.0000e-03 eta: 0:03:51 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6632
11/16 19:33:57 - mmengine - INFO - Epoch(train) [3][ 430/1563] lr: 1.0000e-03 eta: 0:03:51 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.7096
11/16 19:33:58 - mmengine - INFO - Epoch(train) [3][ 440/1563] lr: 1.0000e-03 eta: 0:03:50 time: 0.0509 data_time: 0.0133 memory: 583 loss: 1.7796
11/16 19:33:58 - mmengine - INFO - Epoch(train) [3][ 450/1563] lr: 1.0000e-03 eta: 0:03:50 time: 0.0503 data_time: 0.0133 memory: 583 loss: 1.7139
11/16 19:33:59 - mmengine - INFO - Epoch(train) [3][ 460/1563] lr: 1.0000e-03 eta: 0:03:49 time: 0.0518 data_time: 0.0135 memory: 583 loss: 1.6882
11/16 19:33:59 - mmengine - INFO - Epoch(train) [3][ 470/1563] lr: 1.0000e-03 eta: 0:03:49 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.7111
11/16 19:34:00 - mmengine - INFO - Epoch(train) [3][ 480/1563] lr: 1.0000e-03 eta: 0:03:48 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.7213
11/16 19:34:00 - mmengine - INFO - Epoch(train) [3][ 490/1563] lr: 1.0000e-03 eta: 0:03:47 time: 0.0517 data_time: 0.0134 memory: 583 loss: 1.5724
11/16 19:34:01 - mmengine - INFO - Epoch(train) [3][ 500/1563] lr: 1.0000e-03 eta: 0:03:47 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7341
11/16 19:34:01 - mmengine - INFO - Epoch(train) [3][ 510/1563] lr: 1.0000e-03 eta: 0:03:46 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6678
11/16 19:34:02 - mmengine - INFO - Epoch(train) [3][ 520/1563] lr: 1.0000e-03 eta: 0:03:46 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7692
11/16 19:34:03 - mmengine - INFO - Epoch(train) [3][ 530/1563] lr: 1.0000e-03 eta: 0:03:45 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7251
11/16 19:34:03 - mmengine - INFO - Epoch(train) [3][ 540/1563] lr: 1.0000e-03 eta: 0:03:45 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7397
11/16 19:34:04 - mmengine - INFO - Epoch(train) [3][ 550/1563] lr: 1.0000e-03 eta: 0:03:44 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6523
11/16 19:34:04 - mmengine - INFO - Epoch(train) [3][ 560/1563] lr: 1.0000e-03 eta: 0:03:43 time: 0.0530 data_time: 0.0138 memory: 583 loss: 1.6658
11/16 19:34:05 - mmengine - INFO - Epoch(train) [3][ 570/1563] lr: 1.0000e-03 eta: 0:03:43 time: 0.0502 data_time: 0.0134 memory: 583 loss: 1.7000
11/16 19:34:05 - mmengine - INFO - Epoch(train) [3][ 580/1563] lr: 1.0000e-03 eta: 0:03:42 time: 0.0511 data_time: 0.0134 memory: 583 loss: 1.6418
11/16 19:34:06 - mmengine - INFO - Epoch(train) [3][ 590/1563] lr: 1.0000e-03 eta: 0:03:42 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6751
11/16 19:34:06 - mmengine - INFO - Epoch(train) [3][ 600/1563] lr: 1.0000e-03 eta: 0:03:41 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.6219
11/16 19:34:07 - mmengine - INFO - Epoch(train) [3][ 610/1563] lr: 1.0000e-03 eta: 0:03:41 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.8199
11/16 19:34:07 - mmengine - INFO - Epoch(train) [3][ 620/1563] lr: 1.0000e-03 eta: 0:03:40 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.6300
11/16 19:34:08 - mmengine - INFO - Epoch(train) [3][ 630/1563] lr: 1.0000e-03 eta: 0:03:39 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6875
11/16 19:34:08 - mmengine - INFO - Epoch(train) [3][ 640/1563] lr: 1.0000e-03 eta: 0:03:39 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.8230
11/16 19:34:09 - mmengine - INFO - Epoch(train) [3][ 650/1563] lr: 1.0000e-03 eta: 0:03:38 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.7262
11/16 19:34:09 - mmengine - INFO - Epoch(train) [3][ 660/1563] lr: 1.0000e-03 eta: 0:03:38 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.7142
11/16 19:34:10 - mmengine - INFO - Epoch(train) [3][ 670/1563] lr: 1.0000e-03 eta: 0:03:37 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6989
11/16 19:34:10 - mmengine - INFO - Epoch(train) [3][ 680/1563] lr: 1.0000e-03 eta: 0:03:37 time: 0.0513 data_time: 0.0135 memory: 583 loss: 1.7242
11/16 19:34:11 - mmengine - INFO - Epoch(train) [3][ 690/1563] lr: 1.0000e-03 eta: 0:03:36 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.6707
11/16 19:34:11 - mmengine - INFO - Epoch(train) [3][ 700/1563] lr: 1.0000e-03 eta: 0:03:35 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6199
11/16 19:34:12 - mmengine - INFO - Epoch(train) [3][ 710/1563] lr: 1.0000e-03 eta: 0:03:35 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.7296
11/16 19:34:12 - mmengine - INFO - Epoch(train) [3][ 720/1563] lr: 1.0000e-03 eta: 0:03:34 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.6454
11/16 19:34:13 - mmengine - INFO - Epoch(train) [3][ 730/1563] lr: 1.0000e-03 eta: 0:03:34 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.7502
11/16 19:34:13 - mmengine - INFO - Epoch(train) [3][ 740/1563] lr: 1.0000e-03 eta: 0:03:33 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6429
11/16 19:34:14 - mmengine - INFO - Epoch(train) [3][ 750/1563] lr: 1.0000e-03 eta: 0:03:33 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7218
11/16 19:34:14 - mmengine - INFO - Epoch(train) [3][ 760/1563] lr: 1.0000e-03 eta: 0:03:32 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.7305
11/16 19:34:15 - mmengine - INFO - Epoch(train) [3][ 770/1563] lr: 1.0000e-03 eta: 0:03:31 time: 0.0524 data_time: 0.0137 memory: 583 loss: 1.6878
11/16 19:34:15 - mmengine - INFO - Epoch(train) [3][ 780/1563] lr: 1.0000e-03 eta: 0:03:31 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.7743
11/16 19:34:16 - mmengine - INFO - Epoch(train) [3][ 790/1563] lr: 1.0000e-03 eta: 0:03:30 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.6877
11/16 19:34:17 - mmengine - INFO - Epoch(train) [3][ 800/1563] lr: 1.0000e-03 eta: 0:03:30 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6350
11/16 19:34:17 - mmengine - INFO - Epoch(train) [3][ 810/1563] lr: 1.0000e-03 eta: 0:03:29 time: 0.0515 data_time: 0.0132 memory: 583 loss: 1.6308
11/16 19:34:18 - mmengine - INFO - Epoch(train) [3][ 820/1563] lr: 1.0000e-03 eta: 0:03:29 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6440
11/16 19:34:18 - mmengine - INFO - Epoch(train) [3][ 830/1563] lr: 1.0000e-03 eta: 0:03:28 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.5148
11/16 19:34:19 - mmengine - INFO - Epoch(train) [3][ 840/1563] lr: 1.0000e-03 eta: 0:03:28 time: 0.0522 data_time: 0.0136 memory: 583 loss: 1.6309
11/16 19:34:19 - mmengine - INFO - Epoch(train) [3][ 850/1563] lr: 1.0000e-03 eta: 0:03:27 time: 0.0521 data_time: 0.0136 memory: 583 loss: 1.6781
11/16 19:34:20 - mmengine - INFO - Epoch(train) [3][ 860/1563] lr: 1.0000e-03 eta: 0:03:26 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.5909
11/16 19:34:20 - mmengine - INFO - Epoch(train) [3][ 870/1563] lr: 1.0000e-03 eta: 0:03:26 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.5640
11/16 19:34:20 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:34:21 - mmengine - INFO - Epoch(train) [3][ 880/1563] lr: 1.0000e-03 eta: 0:03:25 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.8019
11/16 19:34:21 - mmengine - INFO - Epoch(train) [3][ 890/1563] lr: 1.0000e-03 eta: 0:03:25 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6269
11/16 19:34:22 - mmengine - INFO - Epoch(train) [3][ 900/1563] lr: 1.0000e-03 eta: 0:03:24 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6528
11/16 19:34:22 - mmengine - INFO - Epoch(train) [3][ 910/1563] lr: 1.0000e-03 eta: 0:03:24 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5432
11/16 19:34:23 - mmengine - INFO - Epoch(train) [3][ 920/1563] lr: 1.0000e-03 eta: 0:03:23 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.5577
11/16 19:34:23 - mmengine - INFO - Epoch(train) [3][ 930/1563] lr: 1.0000e-03 eta: 0:03:22 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.6203
11/16 19:34:24 - mmengine - INFO - Epoch(train) [3][ 940/1563] lr: 1.0000e-03 eta: 0:03:22 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.6583
11/16 19:34:24 - mmengine - INFO - Epoch(train) [3][ 950/1563] lr: 1.0000e-03 eta: 0:03:21 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.7277
11/16 19:34:25 - mmengine - INFO - Epoch(train) [3][ 960/1563] lr: 1.0000e-03 eta: 0:03:21 time: 0.0516 data_time: 0.0133 memory: 583 loss: 1.6505
11/16 19:34:25 - mmengine - INFO - Epoch(train) [3][ 970/1563] lr: 1.0000e-03 eta: 0:03:20 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.7238
11/16 19:34:26 - mmengine - INFO - Epoch(train) [3][ 980/1563] lr: 1.0000e-03 eta: 0:03:20 time: 0.0515 data_time: 0.0132 memory: 583 loss: 1.6329
11/16 19:34:26 - mmengine - INFO - Epoch(train) [3][ 990/1563] lr: 1.0000e-03 eta: 0:03:19 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.6117
11/16 19:34:27 - mmengine - INFO - Epoch(train) [3][1000/1563] lr: 1.0000e-03 eta: 0:03:19 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6176
11/16 19:34:27 - mmengine - INFO - Epoch(train) [3][1010/1563] lr: 1.0000e-03 eta: 0:03:18 time: 0.0512 data_time: 0.0135 memory: 583 loss: 1.5579
11/16 19:34:28 - mmengine - INFO - Epoch(train) [3][1020/1563] lr: 1.0000e-03 eta: 0:03:17 time: 0.0501 data_time: 0.0133 memory: 583 loss: 1.6778
11/16 19:34:28 - mmengine - INFO - Epoch(train) [3][1030/1563] lr: 1.0000e-03 eta: 0:03:17 time: 0.0504 data_time: 0.0135 memory: 583 loss: 1.5413
11/16 19:34:29 - mmengine - INFO - Epoch(train) [3][1040/1563] lr: 1.0000e-03 eta: 0:03:16 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.6044
11/16 19:34:29 - mmengine - INFO - Epoch(train) [3][1050/1563] lr: 1.0000e-03 eta: 0:03:16 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.6741
11/16 19:34:30 - mmengine - INFO - Epoch(train) [3][1060/1563] lr: 1.0000e-03 eta: 0:03:15 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6769
11/16 19:34:30 - mmengine - INFO - Epoch(train) [3][1070/1563] lr: 1.0000e-03 eta: 0:03:15 time: 0.0513 data_time: 0.0131 memory: 583 loss: 1.5650
11/16 19:34:31 - mmengine - INFO - Epoch(train) [3][1080/1563] lr: 1.0000e-03 eta: 0:03:14 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.6365
11/16 19:34:32 - mmengine - INFO - Epoch(train) [3][1090/1563] lr: 1.0000e-03 eta: 0:03:14 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.6537
11/16 19:34:32 - mmengine - INFO - Epoch(train) [3][1100/1563] lr: 1.0000e-03 eta: 0:03:13 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6805
11/16 19:34:33 - mmengine - INFO - Epoch(train) [3][1110/1563] lr: 1.0000e-03 eta: 0:03:12 time: 0.0522 data_time: 0.0136 memory: 583 loss: 1.6337
11/16 19:34:33 - mmengine - INFO - Epoch(train) [3][1120/1563] lr: 1.0000e-03 eta: 0:03:12 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5570
11/16 19:34:34 - mmengine - INFO - Epoch(train) [3][1130/1563] lr: 1.0000e-03 eta: 0:03:11 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.6492
11/16 19:34:34 - mmengine - INFO - Epoch(train) [3][1140/1563] lr: 1.0000e-03 eta: 0:03:11 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5469
11/16 19:34:35 - mmengine - INFO - Epoch(train) [3][1150/1563] lr: 1.0000e-03 eta: 0:03:10 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6229
11/16 19:34:35 - mmengine - INFO - Epoch(train) [3][1160/1563] lr: 1.0000e-03 eta: 0:03:10 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.5561
11/16 19:34:36 - mmengine - INFO - Epoch(train) [3][1170/1563] lr: 1.0000e-03 eta: 0:03:09 time: 0.0521 data_time: 0.0133 memory: 583 loss: 1.5947
11/16 19:34:36 - mmengine - INFO - Epoch(train) [3][1180/1563] lr: 1.0000e-03 eta: 0:03:09 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6452
11/16 19:34:37 - mmengine - INFO - Epoch(train) [3][1190/1563] lr: 1.0000e-03 eta: 0:03:08 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6300
11/16 19:34:37 - mmengine - INFO - Epoch(train) [3][1200/1563] lr: 1.0000e-03 eta: 0:03:07 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6517
11/16 19:34:38 - mmengine - INFO - Epoch(train) [3][1210/1563] lr: 1.0000e-03 eta: 0:03:07 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.6739
11/16 19:34:38 - mmengine - INFO - Epoch(train) [3][1220/1563] lr: 1.0000e-03 eta: 0:03:06 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.6970
11/16 19:34:39 - mmengine - INFO - Epoch(train) [3][1230/1563] lr: 1.0000e-03 eta: 0:03:06 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.6927
11/16 19:34:39 - mmengine - INFO - Epoch(train) [3][1240/1563] lr: 1.0000e-03 eta: 0:03:05 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6417
11/16 19:34:40 - mmengine - INFO - Epoch(train) [3][1250/1563] lr: 1.0000e-03 eta: 0:03:05 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5887
11/16 19:34:40 - mmengine - INFO - Epoch(train) [3][1260/1563] lr: 1.0000e-03 eta: 0:03:04 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.6255
11/16 19:34:41 - mmengine - INFO - Epoch(train) [3][1270/1563] lr: 1.0000e-03 eta: 0:03:04 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.6591
11/16 19:34:41 - mmengine - INFO - Epoch(train) [3][1280/1563] lr: 1.0000e-03 eta: 0:03:03 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.6132
11/16 19:34:42 - mmengine - INFO - Epoch(train) [3][1290/1563] lr: 1.0000e-03 eta: 0:03:02 time: 0.0513 data_time: 0.0134 memory: 583 loss: 1.7146
11/16 19:34:42 - mmengine - INFO - Epoch(train) [3][1300/1563] lr: 1.0000e-03 eta: 0:03:02 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6319
11/16 19:34:43 - mmengine - INFO - Epoch(train) [3][1310/1563] lr: 1.0000e-03 eta: 0:03:01 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6219
11/16 19:34:43 - mmengine - INFO - Epoch(train) [3][1320/1563] lr: 1.0000e-03 eta: 0:03:01 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4518
11/16 19:34:44 - mmengine - INFO - Epoch(train) [3][1330/1563] lr: 1.0000e-03 eta: 0:03:00 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5846
11/16 19:34:45 - mmengine - INFO - Epoch(train) [3][1340/1563] lr: 1.0000e-03 eta: 0:03:00 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.6854
11/16 19:34:45 - mmengine - INFO - Epoch(train) [3][1350/1563] lr: 1.0000e-03 eta: 0:02:59 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5629
11/16 19:34:46 - mmengine - INFO - Epoch(train) [3][1360/1563] lr: 1.0000e-03 eta: 0:02:59 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.7074
11/16 19:34:46 - mmengine - INFO - Epoch(train) [3][1370/1563] lr: 1.0000e-03 eta: 0:02:58 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7023
11/16 19:34:47 - mmengine - INFO - Epoch(train) [3][1380/1563] lr: 1.0000e-03 eta: 0:02:57 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5691
11/16 19:34:47 - mmengine - INFO - Epoch(train) [3][1390/1563] lr: 1.0000e-03 eta: 0:02:57 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6268
11/16 19:34:48 - mmengine - INFO - Epoch(train) [3][1400/1563] lr: 1.0000e-03 eta: 0:02:56 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5882
11/16 19:34:48 - mmengine - INFO - Epoch(train) [3][1410/1563] lr: 1.0000e-03 eta: 0:02:56 time: 0.0526 data_time: 0.0136 memory: 583 loss: 1.5840
11/16 19:34:49 - mmengine - INFO - Epoch(train) [3][1420/1563] lr: 1.0000e-03 eta: 0:02:55 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.5812
11/16 19:34:49 - mmengine - INFO - Epoch(train) [3][1430/1563] lr: 1.0000e-03 eta: 0:02:55 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.8222
11/16 19:34:50 - mmengine - INFO - Epoch(train) [3][1440/1563] lr: 1.0000e-03 eta: 0:02:54 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6268
11/16 19:34:50 - mmengine - INFO - Epoch(train) [3][1450/1563] lr: 1.0000e-03 eta: 0:02:54 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6789
11/16 19:34:51 - mmengine - INFO - Epoch(train) [3][1460/1563] lr: 1.0000e-03 eta: 0:02:53 time: 0.0512 data_time: 0.0133 memory: 583 loss: 1.6895
11/16 19:34:51 - mmengine - INFO - Epoch(train) [3][1470/1563] lr: 1.0000e-03 eta: 0:02:53 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.8220
11/16 19:34:52 - mmengine - INFO - Epoch(train) [3][1480/1563] lr: 1.0000e-03 eta: 0:02:52 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6938
11/16 19:34:52 - mmengine - INFO - Epoch(train) [3][1490/1563] lr: 1.0000e-03 eta: 0:02:51 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.6710
11/16 19:34:53 - mmengine - INFO - Epoch(train) [3][1500/1563] lr: 1.0000e-03 eta: 0:02:51 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.4810
11/16 19:34:53 - mmengine - INFO - Epoch(train) [3][1510/1563] lr: 1.0000e-03 eta: 0:02:50 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.6855
11/16 19:34:54 - mmengine - INFO - Epoch(train) [3][1520/1563] lr: 1.0000e-03 eta: 0:02:50 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.6499
11/16 19:34:54 - mmengine - INFO - Epoch(train) [3][1530/1563] lr: 1.0000e-03 eta: 0:02:49 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.6791
11/16 19:34:55 - mmengine - INFO - Epoch(train) [3][1540/1563] lr: 1.0000e-03 eta: 0:02:49 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.6281
11/16 19:34:55 - mmengine - INFO - Epoch(train) [3][1550/1563] lr: 1.0000e-03 eta: 0:02:48 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.5941
11/16 19:34:56 - mmengine - INFO - Epoch(train) [3][1560/1563] lr: 1.0000e-03 eta: 0:02:48 time: 0.0511 data_time: 0.0132 memory: 583 loss: 1.5869
11/16 19:34:56 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:34:56 - mmengine - INFO - Saving checkpoint at 3 epochs
11/16 19:34:57 - mmengine - INFO - Epoch(val) [3][ 10/313] eta: 0:00:05 time: 0.0167 data_time: 0.0083 memory: 583
11/16 19:34:57 - mmengine - INFO - Epoch(val) [3][ 20/313] eta: 0:00:04 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:34:57 - mmengine - INFO - Epoch(val) [3][ 30/313] eta: 0:00:04 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:34:57 - mmengine - INFO - Epoch(val) [3][ 40/313] eta: 0:00:04 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:34:57 - mmengine - INFO - Epoch(val) [3][ 50/313] eta: 0:00:04 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:34:58 - mmengine - INFO - Epoch(val) [3][ 60/313] eta: 0:00:04 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:34:58 - mmengine - INFO - Epoch(val) [3][ 70/313] eta: 0:00:04 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:34:58 - mmengine - INFO - Epoch(val) [3][ 80/313] eta: 0:00:03 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:34:58 - mmengine - INFO - Epoch(val) [3][ 90/313] eta: 0:00:03 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:34:58 - mmengine - INFO - Epoch(val) [3][100/313] eta: 0:00:03 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:34:58 - mmengine - INFO - Epoch(val) [3][110/313] eta: 0:00:03 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:34:59 - mmengine - INFO - Epoch(val) [3][120/313] eta: 0:00:03 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:34:59 - mmengine - INFO - Epoch(val) [3][130/313] eta: 0:00:03 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:34:59 - mmengine - INFO - Epoch(val) [3][140/313] eta: 0:00:02 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:34:59 - mmengine - INFO - Epoch(val) [3][150/313] eta: 0:00:02 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:34:59 - mmengine - INFO - Epoch(val) [3][160/313] eta: 0:00:02 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:34:59 - mmengine - INFO - Epoch(val) [3][170/313] eta: 0:00:02 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:35:00 - mmengine - INFO - Epoch(val) [3][180/313] eta: 0:00:02 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:35:00 - mmengine - INFO - Epoch(val) [3][190/313] eta: 0:00:02 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:35:00 - mmengine - INFO - Epoch(val) [3][200/313] eta: 0:00:01 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:35:00 - mmengine - INFO - Epoch(val) [3][210/313] eta: 0:00:01 time: 0.0171 data_time: 0.0086 memory: 424
11/16 19:35:00 - mmengine - INFO - Epoch(val) [3][220/313] eta: 0:00:01 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:35:00 - mmengine - INFO - Epoch(val) [3][230/313] eta: 0:00:01 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:35:01 - mmengine - INFO - Epoch(val) [3][240/313] eta: 0:00:01 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:35:01 - mmengine - INFO - Epoch(val) [3][250/313] eta: 0:00:01 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:35:01 - mmengine - INFO - Epoch(val) [3][260/313] eta: 0:00:00 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:35:01 - mmengine - INFO - Epoch(val) [3][270/313] eta: 0:00:00 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:35:01 - mmengine - INFO - Epoch(val) [3][280/313] eta: 0:00:00 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:35:01 - mmengine - INFO - Epoch(val) [3][290/313] eta: 0:00:00 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:35:02 - mmengine - INFO - Epoch(val) [3][300/313] eta: 0:00:00 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:35:02 - mmengine - INFO - Epoch(val) [3][310/313] eta: 0:00:00 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:35:02 - mmengine - INFO - Epoch(val) [3][313/313] accuracy: 45.5000 data_time: 0.0084 time: 0.0168
11/16 19:35:02 - mmengine - INFO - Epoch(train) [4][ 10/1563] lr: 1.0000e-03 eta: 0:02:47 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.5607
11/16 19:35:03 - mmengine - INFO - Epoch(train) [4][ 20/1563] lr: 1.0000e-03 eta: 0:02:46 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6224
11/16 19:35:03 - mmengine - INFO - Epoch(train) [4][ 30/1563] lr: 1.0000e-03 eta: 0:02:46 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.5670
11/16 19:35:04 - mmengine - INFO - Epoch(train) [4][ 40/1563] lr: 1.0000e-03 eta: 0:02:45 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5347
11/16 19:35:04 - mmengine - INFO - Epoch(train) [4][ 50/1563] lr: 1.0000e-03 eta: 0:02:45 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.5120
11/16 19:35:05 - mmengine - INFO - Epoch(train) [4][ 60/1563] lr: 1.0000e-03 eta: 0:02:44 time: 0.0522 data_time: 0.0134 memory: 583 loss: 1.5437
11/16 19:35:06 - mmengine - INFO - Epoch(train) [4][ 70/1563] lr: 1.0000e-03 eta: 0:02:44 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.7087
11/16 19:35:06 - mmengine - INFO - Epoch(train) [4][ 80/1563] lr: 1.0000e-03 eta: 0:02:43 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6404
11/16 19:35:07 - mmengine - INFO - Epoch(train) [4][ 90/1563] lr: 1.0000e-03 eta: 0:02:42 time: 0.0508 data_time: 0.0131 memory: 583 loss: 1.4498
11/16 19:35:07 - mmengine - INFO - Epoch(train) [4][ 100/1563] lr: 1.0000e-03 eta: 0:02:42 time: 0.0517 data_time: 0.0135 memory: 583 loss: 1.6266
11/16 19:35:08 - mmengine - INFO - Epoch(train) [4][ 110/1563] lr: 1.0000e-03 eta: 0:02:41 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6001
11/16 19:35:08 - mmengine - INFO - Epoch(train) [4][ 120/1563] lr: 1.0000e-03 eta: 0:02:41 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5924
11/16 19:35:09 - mmengine - INFO - Epoch(train) [4][ 130/1563] lr: 1.0000e-03 eta: 0:02:40 time: 0.0522 data_time: 0.0136 memory: 583 loss: 1.6669
11/16 19:35:09 - mmengine - INFO - Epoch(train) [4][ 140/1563] lr: 1.0000e-03 eta: 0:02:40 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5858
11/16 19:35:10 - mmengine - INFO - Epoch(train) [4][ 150/1563] lr: 1.0000e-03 eta: 0:02:39 time: 0.0520 data_time: 0.0136 memory: 583 loss: 1.7140
11/16 19:35:10 - mmengine - INFO - Epoch(train) [4][ 160/1563] lr: 1.0000e-03 eta: 0:02:39 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5863
11/16 19:35:11 - mmengine - INFO - Epoch(train) [4][ 170/1563] lr: 1.0000e-03 eta: 0:02:38 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.4617
11/16 19:35:11 - mmengine - INFO - Epoch(train) [4][ 180/1563] lr: 1.0000e-03 eta: 0:02:38 time: 0.0521 data_time: 0.0133 memory: 583 loss: 1.6065
11/16 19:35:12 - mmengine - INFO - Epoch(train) [4][ 190/1563] lr: 1.0000e-03 eta: 0:02:37 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.4972
11/16 19:35:12 - mmengine - INFO - Epoch(train) [4][ 200/1563] lr: 1.0000e-03 eta: 0:02:36 time: 0.0513 data_time: 0.0130 memory: 583 loss: 1.5356
11/16 19:35:13 - mmengine - INFO - Epoch(train) [4][ 210/1563] lr: 1.0000e-03 eta: 0:02:36 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.5422
11/16 19:35:13 - mmengine - INFO - Epoch(train) [4][ 220/1563] lr: 1.0000e-03 eta: 0:02:35 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.4797
11/16 19:35:14 - mmengine - INFO - Epoch(train) [4][ 230/1563] lr: 1.0000e-03 eta: 0:02:35 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5629
11/16 19:35:14 - mmengine - INFO - Epoch(train) [4][ 240/1563] lr: 1.0000e-03 eta: 0:02:34 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6657
11/16 19:35:15 - mmengine - INFO - Epoch(train) [4][ 250/1563] lr: 1.0000e-03 eta: 0:02:34 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5348
11/16 19:35:15 - mmengine - INFO - Epoch(train) [4][ 260/1563] lr: 1.0000e-03 eta: 0:02:33 time: 0.0519 data_time: 0.0132 memory: 583 loss: 1.5266
11/16 19:35:16 - mmengine - INFO - Epoch(train) [4][ 270/1563] lr: 1.0000e-03 eta: 0:02:33 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.5891
11/16 19:35:16 - mmengine - INFO - Epoch(train) [4][ 280/1563] lr: 1.0000e-03 eta: 0:02:32 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.6362
11/16 19:35:17 - mmengine - INFO - Epoch(train) [4][ 290/1563] lr: 1.0000e-03 eta: 0:02:32 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.7368
11/16 19:35:17 - mmengine - INFO - Epoch(train) [4][ 300/1563] lr: 1.0000e-03 eta: 0:02:31 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6271
11/16 19:35:18 - mmengine - INFO - Epoch(train) [4][ 310/1563] lr: 1.0000e-03 eta: 0:02:30 time: 0.0514 data_time: 0.0134 memory: 583 loss: 1.5836
11/16 19:35:18 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:35:18 - mmengine - INFO - Epoch(train) [4][ 320/1563] lr: 1.0000e-03 eta: 0:02:30 time: 0.0526 data_time: 0.0139 memory: 583 loss: 1.5767
11/16 19:35:19 - mmengine - INFO - Epoch(train) [4][ 330/1563] lr: 1.0000e-03 eta: 0:02:29 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5190
11/16 19:35:20 - mmengine - INFO - Epoch(train) [4][ 340/1563] lr: 1.0000e-03 eta: 0:02:29 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.4818
11/16 19:35:20 - mmengine - INFO - Epoch(train) [4][ 350/1563] lr: 1.0000e-03 eta: 0:02:28 time: 0.0521 data_time: 0.0136 memory: 583 loss: 1.5604
11/16 19:35:21 - mmengine - INFO - Epoch(train) [4][ 360/1563] lr: 1.0000e-03 eta: 0:02:28 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.7209
11/16 19:35:21 - mmengine - INFO - Epoch(train) [4][ 370/1563] lr: 1.0000e-03 eta: 0:02:27 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.6530
11/16 19:35:22 - mmengine - INFO - Epoch(train) [4][ 380/1563] lr: 1.0000e-03 eta: 0:02:27 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6377
11/16 19:35:22 - mmengine - INFO - Epoch(train) [4][ 390/1563] lr: 1.0000e-03 eta: 0:02:26 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5516
11/16 19:35:23 - mmengine - INFO - Epoch(train) [4][ 400/1563] lr: 1.0000e-03 eta: 0:02:26 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.5795
11/16 19:35:23 - mmengine - INFO - Epoch(train) [4][ 410/1563] lr: 1.0000e-03 eta: 0:02:25 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.7536
11/16 19:35:24 - mmengine - INFO - Epoch(train) [4][ 420/1563] lr: 1.0000e-03 eta: 0:02:24 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.6067
11/16 19:35:24 - mmengine - INFO - Epoch(train) [4][ 430/1563] lr: 1.0000e-03 eta: 0:02:24 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5970
11/16 19:35:25 - mmengine - INFO - Epoch(train) [4][ 440/1563] lr: 1.0000e-03 eta: 0:02:23 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5953
11/16 19:35:25 - mmengine - INFO - Epoch(train) [4][ 450/1563] lr: 1.0000e-03 eta: 0:02:23 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.6145
11/16 19:35:26 - mmengine - INFO - Epoch(train) [4][ 460/1563] lr: 1.0000e-03 eta: 0:02:22 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5111
11/16 19:35:26 - mmengine - INFO - Epoch(train) [4][ 470/1563] lr: 1.0000e-03 eta: 0:02:22 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.6105
11/16 19:35:27 - mmengine - INFO - Epoch(train) [4][ 480/1563] lr: 1.0000e-03 eta: 0:02:21 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.6430
11/16 19:35:27 - mmengine - INFO - Epoch(train) [4][ 490/1563] lr: 1.0000e-03 eta: 0:02:21 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.5662
11/16 19:35:28 - mmengine - INFO - Epoch(train) [4][ 500/1563] lr: 1.0000e-03 eta: 0:02:20 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5906
11/16 19:35:28 - mmengine - INFO - Epoch(train) [4][ 510/1563] lr: 1.0000e-03 eta: 0:02:20 time: 0.0516 data_time: 0.0131 memory: 583 loss: 1.6394
11/16 19:35:29 - mmengine - INFO - Epoch(train) [4][ 520/1563] lr: 1.0000e-03 eta: 0:02:19 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5032
11/16 19:35:29 - mmengine - INFO - Epoch(train) [4][ 530/1563] lr: 1.0000e-03 eta: 0:02:18 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.6482
11/16 19:35:30 - mmengine - INFO - Epoch(train) [4][ 540/1563] lr: 1.0000e-03 eta: 0:02:18 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.6914
11/16 19:35:30 - mmengine - INFO - Epoch(train) [4][ 550/1563] lr: 1.0000e-03 eta: 0:02:17 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6061
11/16 19:35:31 - mmengine - INFO - Epoch(train) [4][ 560/1563] lr: 1.0000e-03 eta: 0:02:17 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5547
11/16 19:35:31 - mmengine - INFO - Epoch(train) [4][ 570/1563] lr: 1.0000e-03 eta: 0:02:16 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.5621
11/16 19:35:32 - mmengine - INFO - Epoch(train) [4][ 580/1563] lr: 1.0000e-03 eta: 0:02:16 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5626
11/16 19:35:33 - mmengine - INFO - Epoch(train) [4][ 590/1563] lr: 1.0000e-03 eta: 0:02:15 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.5019
11/16 19:35:33 - mmengine - INFO - Epoch(train) [4][ 600/1563] lr: 1.0000e-03 eta: 0:02:15 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.6926
11/16 19:35:34 - mmengine - INFO - Epoch(train) [4][ 610/1563] lr: 1.0000e-03 eta: 0:02:14 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.4765
11/16 19:35:34 - mmengine - INFO - Epoch(train) [4][ 620/1563] lr: 1.0000e-03 eta: 0:02:14 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.6460
11/16 19:35:35 - mmengine - INFO - Epoch(train) [4][ 630/1563] lr: 1.0000e-03 eta: 0:02:13 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.5182
11/16 19:35:35 - mmengine - INFO - Epoch(train) [4][ 640/1563] lr: 1.0000e-03 eta: 0:02:12 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.6307
11/16 19:35:36 - mmengine - INFO - Epoch(train) [4][ 650/1563] lr: 1.0000e-03 eta: 0:02:12 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.6553
11/16 19:35:36 - mmengine - INFO - Epoch(train) [4][ 660/1563] lr: 1.0000e-03 eta: 0:02:11 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5777
11/16 19:35:37 - mmengine - INFO - Epoch(train) [4][ 670/1563] lr: 1.0000e-03 eta: 0:02:11 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5607
11/16 19:35:37 - mmengine - INFO - Epoch(train) [4][ 680/1563] lr: 1.0000e-03 eta: 0:02:10 time: 0.0522 data_time: 0.0134 memory: 583 loss: 1.5438
11/16 19:35:38 - mmengine - INFO - Epoch(train) [4][ 690/1563] lr: 1.0000e-03 eta: 0:02:10 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.6494
11/16 19:35:38 - mmengine - INFO - Epoch(train) [4][ 700/1563] lr: 1.0000e-03 eta: 0:02:09 time: 0.0512 data_time: 0.0133 memory: 583 loss: 1.5733
11/16 19:35:39 - mmengine - INFO - Epoch(train) [4][ 710/1563] lr: 1.0000e-03 eta: 0:02:09 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.6367
11/16 19:35:39 - mmengine - INFO - Epoch(train) [4][ 720/1563] lr: 1.0000e-03 eta: 0:02:08 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5514
11/16 19:35:40 - mmengine - INFO - Epoch(train) [4][ 730/1563] lr: 1.0000e-03 eta: 0:02:08 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.6155
11/16 19:35:40 - mmengine - INFO - Epoch(train) [4][ 740/1563] lr: 1.0000e-03 eta: 0:02:07 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5856
11/16 19:35:41 - mmengine - INFO - Epoch(train) [4][ 750/1563] lr: 1.0000e-03 eta: 0:02:07 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5818
11/16 19:35:41 - mmengine - INFO - Epoch(train) [4][ 760/1563] lr: 1.0000e-03 eta: 0:02:06 time: 0.0526 data_time: 0.0136 memory: 583 loss: 1.5806
11/16 19:35:42 - mmengine - INFO - Epoch(train) [4][ 770/1563] lr: 1.0000e-03 eta: 0:02:05 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5392
11/16 19:35:42 - mmengine - INFO - Epoch(train) [4][ 780/1563] lr: 1.0000e-03 eta: 0:02:05 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5545
11/16 19:35:43 - mmengine - INFO - Epoch(train) [4][ 790/1563] lr: 1.0000e-03 eta: 0:02:04 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.4785
11/16 19:35:43 - mmengine - INFO - Epoch(train) [4][ 800/1563] lr: 1.0000e-03 eta: 0:02:04 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.6271
11/16 19:35:44 - mmengine - INFO - Epoch(train) [4][ 810/1563] lr: 1.0000e-03 eta: 0:02:03 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.6067
11/16 19:35:44 - mmengine - INFO - Epoch(train) [4][ 820/1563] lr: 1.0000e-03 eta: 0:02:03 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.7234
11/16 19:35:45 - mmengine - INFO - Epoch(train) [4][ 830/1563] lr: 1.0000e-03 eta: 0:02:02 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.4992
11/16 19:35:46 - mmengine - INFO - Epoch(train) [4][ 840/1563] lr: 1.0000e-03 eta: 0:02:02 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.5843
11/16 19:35:46 - mmengine - INFO - Epoch(train) [4][ 850/1563] lr: 1.0000e-03 eta: 0:02:01 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.8102
11/16 19:35:47 - mmengine - INFO - Epoch(train) [4][ 860/1563] lr: 1.0000e-03 eta: 0:02:01 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5565
11/16 19:35:47 - mmengine - INFO - Epoch(train) [4][ 870/1563] lr: 1.0000e-03 eta: 0:02:00 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.5670
11/16 19:35:48 - mmengine - INFO - Epoch(train) [4][ 880/1563] lr: 1.0000e-03 eta: 0:02:00 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.6017
11/16 19:35:48 - mmengine - INFO - Epoch(train) [4][ 890/1563] lr: 1.0000e-03 eta: 0:01:59 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5105
11/16 19:35:49 - mmengine - INFO - Epoch(train) [4][ 900/1563] lr: 1.0000e-03 eta: 0:01:58 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.6366
11/16 19:35:49 - mmengine - INFO - Epoch(train) [4][ 910/1563] lr: 1.0000e-03 eta: 0:01:58 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.4760
11/16 19:35:50 - mmengine - INFO - Epoch(train) [4][ 920/1563] lr: 1.0000e-03 eta: 0:01:57 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.5833
11/16 19:35:50 - mmengine - INFO - Epoch(train) [4][ 930/1563] lr: 1.0000e-03 eta: 0:01:57 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5323
11/16 19:35:51 - mmengine - INFO - Epoch(train) [4][ 940/1563] lr: 1.0000e-03 eta: 0:01:56 time: 0.0517 data_time: 0.0132 memory: 583 loss: 1.5967
11/16 19:35:51 - mmengine - INFO - Epoch(train) [4][ 950/1563] lr: 1.0000e-03 eta: 0:01:56 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.6286
11/16 19:35:52 - mmengine - INFO - Epoch(train) [4][ 960/1563] lr: 1.0000e-03 eta: 0:01:55 time: 0.0517 data_time: 0.0134 memory: 583 loss: 1.5687
11/16 19:35:52 - mmengine - INFO - Epoch(train) [4][ 970/1563] lr: 1.0000e-03 eta: 0:01:55 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5091
11/16 19:35:53 - mmengine - INFO - Epoch(train) [4][ 980/1563] lr: 1.0000e-03 eta: 0:01:54 time: 0.0524 data_time: 0.0137 memory: 583 loss: 1.5775
11/16 19:35:53 - mmengine - INFO - Epoch(train) [4][ 990/1563] lr: 1.0000e-03 eta: 0:01:54 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5355
11/16 19:35:54 - mmengine - INFO - Epoch(train) [4][1000/1563] lr: 1.0000e-03 eta: 0:01:53 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.5327
11/16 19:35:54 - mmengine - INFO - Epoch(train) [4][1010/1563] lr: 1.0000e-03 eta: 0:01:52 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.5377
11/16 19:35:55 - mmengine - INFO - Epoch(train) [4][1020/1563] lr: 1.0000e-03 eta: 0:01:52 time: 0.0527 data_time: 0.0138 memory: 583 loss: 1.5830
11/16 19:35:55 - mmengine - INFO - Epoch(train) [4][1030/1563] lr: 1.0000e-03 eta: 0:01:51 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.5977
11/16 19:35:56 - mmengine - INFO - Epoch(train) [4][1040/1563] lr: 1.0000e-03 eta: 0:01:51 time: 0.0525 data_time: 0.0138 memory: 583 loss: 1.5331
11/16 19:35:56 - mmengine - INFO - Epoch(train) [4][1050/1563] lr: 1.0000e-03 eta: 0:01:50 time: 0.0528 data_time: 0.0139 memory: 583 loss: 1.5030
11/16 19:35:57 - mmengine - INFO - Epoch(train) [4][1060/1563] lr: 1.0000e-03 eta: 0:01:50 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.6630
11/16 19:35:58 - mmengine - INFO - Epoch(train) [4][1070/1563] lr: 1.0000e-03 eta: 0:01:49 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.5678
11/16 19:35:58 - mmengine - INFO - Epoch(train) [4][1080/1563] lr: 1.0000e-03 eta: 0:01:49 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.6587
11/16 19:35:59 - mmengine - INFO - Epoch(train) [4][1090/1563] lr: 1.0000e-03 eta: 0:01:48 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5858
11/16 19:35:59 - mmengine - INFO - Epoch(train) [4][1100/1563] lr: 1.0000e-03 eta: 0:01:48 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.6455
11/16 19:36:00 - mmengine - INFO - Epoch(train) [4][1110/1563] lr: 1.0000e-03 eta: 0:01:47 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.4323
11/16 19:36:00 - mmengine - INFO - Epoch(train) [4][1120/1563] lr: 1.0000e-03 eta: 0:01:47 time: 0.0690 data_time: 0.0277 memory: 583 loss: 1.5821
11/16 19:36:01 - mmengine - INFO - Epoch(train) [4][1130/1563] lr: 1.0000e-03 eta: 0:01:46 time: 0.0565 data_time: 0.0156 memory: 583 loss: 1.4582
11/16 19:36:01 - mmengine - INFO - Epoch(train) [4][1140/1563] lr: 1.0000e-03 eta: 0:01:46 time: 0.0564 data_time: 0.0154 memory: 583 loss: 1.5141
11/16 19:36:02 - mmengine - INFO - Epoch(train) [4][1150/1563] lr: 1.0000e-03 eta: 0:01:45 time: 0.0562 data_time: 0.0153 memory: 583 loss: 1.5818
11/16 19:36:03 - mmengine - INFO - Epoch(train) [4][1160/1563] lr: 1.0000e-03 eta: 0:01:45 time: 0.0562 data_time: 0.0153 memory: 583 loss: 1.5350
11/16 19:36:03 - mmengine - INFO - Epoch(train) [4][1170/1563] lr: 1.0000e-03 eta: 0:01:44 time: 0.0563 data_time: 0.0155 memory: 583 loss: 1.4803
11/16 19:36:04 - mmengine - INFO - Epoch(train) [4][1180/1563] lr: 1.0000e-03 eta: 0:01:43 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.4910
11/16 19:36:04 - mmengine - INFO - Epoch(train) [4][1190/1563] lr: 1.0000e-03 eta: 0:01:43 time: 0.0563 data_time: 0.0155 memory: 583 loss: 1.4926
11/16 19:36:05 - mmengine - INFO - Epoch(train) [4][1200/1563] lr: 1.0000e-03 eta: 0:01:42 time: 0.0565 data_time: 0.0155 memory: 583 loss: 1.6220
11/16 19:36:05 - mmengine - INFO - Epoch(train) [4][1210/1563] lr: 1.0000e-03 eta: 0:01:42 time: 0.0565 data_time: 0.0155 memory: 583 loss: 1.4857
11/16 19:36:06 - mmengine - INFO - Epoch(train) [4][1220/1563] lr: 1.0000e-03 eta: 0:01:41 time: 0.0562 data_time: 0.0154 memory: 583 loss: 1.4314
11/16 19:36:06 - mmengine - INFO - Epoch(train) [4][1230/1563] lr: 1.0000e-03 eta: 0:01:41 time: 0.0562 data_time: 0.0153 memory: 583 loss: 1.6568
11/16 19:36:07 - mmengine - INFO - Epoch(train) [4][1240/1563] lr: 1.0000e-03 eta: 0:01:40 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.5729
11/16 19:36:08 - mmengine - INFO - Epoch(train) [4][1250/1563] lr: 1.0000e-03 eta: 0:01:40 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.5035
11/16 19:36:08 - mmengine - INFO - Epoch(train) [4][1260/1563] lr: 1.0000e-03 eta: 0:01:39 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.5118
11/16 19:36:09 - mmengine - INFO - Epoch(train) [4][1270/1563] lr: 1.0000e-03 eta: 0:01:39 time: 0.0562 data_time: 0.0154 memory: 583 loss: 1.5899
11/16 19:36:09 - mmengine - INFO - Epoch(train) [4][1280/1563] lr: 1.0000e-03 eta: 0:01:38 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.5077
11/16 19:36:10 - mmengine - INFO - Epoch(train) [4][1290/1563] lr: 1.0000e-03 eta: 0:01:38 time: 0.0564 data_time: 0.0154 memory: 583 loss: 1.5095
11/16 19:36:10 - mmengine - INFO - Epoch(train) [4][1300/1563] lr: 1.0000e-03 eta: 0:01:37 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.6233
11/16 19:36:11 - mmengine - INFO - Epoch(train) [4][1310/1563] lr: 1.0000e-03 eta: 0:01:37 time: 0.0562 data_time: 0.0154 memory: 583 loss: 1.5511
11/16 19:36:11 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:36:12 - mmengine - INFO - Epoch(train) [4][1320/1563] lr: 1.0000e-03 eta: 0:01:36 time: 0.0569 data_time: 0.0159 memory: 583 loss: 1.4975
11/16 19:36:12 - mmengine - INFO - Epoch(train) [4][1330/1563] lr: 1.0000e-03 eta: 0:01:36 time: 0.0560 data_time: 0.0152 memory: 583 loss: 1.5573
11/16 19:36:13 - mmengine - INFO - Epoch(train) [4][1340/1563] lr: 1.0000e-03 eta: 0:01:35 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.5318
11/16 19:36:13 - mmengine - INFO - Epoch(train) [4][1350/1563] lr: 1.0000e-03 eta: 0:01:35 time: 0.0562 data_time: 0.0153 memory: 583 loss: 1.4151
11/16 19:36:14 - mmengine - INFO - Epoch(train) [4][1360/1563] lr: 1.0000e-03 eta: 0:01:34 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.6054
11/16 19:36:14 - mmengine - INFO - Epoch(train) [4][1370/1563] lr: 1.0000e-03 eta: 0:01:33 time: 0.0562 data_time: 0.0154 memory: 583 loss: 1.6002
11/16 19:36:15 - mmengine - INFO - Epoch(train) [4][1380/1563] lr: 1.0000e-03 eta: 0:01:33 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.5828
11/16 19:36:16 - mmengine - INFO - Epoch(train) [4][1390/1563] lr: 1.0000e-03 eta: 0:01:32 time: 0.0566 data_time: 0.0155 memory: 583 loss: 1.3907
11/16 19:36:16 - mmengine - INFO - Epoch(train) [4][1400/1563] lr: 1.0000e-03 eta: 0:01:32 time: 0.0564 data_time: 0.0155 memory: 583 loss: 1.5694
11/16 19:36:17 - mmengine - INFO - Epoch(train) [4][1410/1563] lr: 1.0000e-03 eta: 0:01:31 time: 0.0563 data_time: 0.0153 memory: 583 loss: 1.5473
11/16 19:36:17 - mmengine - INFO - Epoch(train) [4][1420/1563] lr: 1.0000e-03 eta: 0:01:31 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.6656
11/16 19:36:18 - mmengine - INFO - Epoch(train) [4][1430/1563] lr: 1.0000e-03 eta: 0:01:30 time: 0.0563 data_time: 0.0153 memory: 583 loss: 1.6371
11/16 19:36:18 - mmengine - INFO - Epoch(train) [4][1440/1563] lr: 1.0000e-03 eta: 0:01:30 time: 0.0562 data_time: 0.0154 memory: 583 loss: 1.5560
11/16 19:36:19 - mmengine - INFO - Epoch(train) [4][1450/1563] lr: 1.0000e-03 eta: 0:01:29 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.4844
11/16 19:36:19 - mmengine - INFO - Epoch(train) [4][1460/1563] lr: 1.0000e-03 eta: 0:01:29 time: 0.0561 data_time: 0.0154 memory: 583 loss: 1.5168
11/16 19:36:20 - mmengine - INFO - Epoch(train) [4][1470/1563] lr: 1.0000e-03 eta: 0:01:28 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.4785
11/16 19:36:21 - mmengine - INFO - Epoch(train) [4][1480/1563] lr: 1.0000e-03 eta: 0:01:28 time: 0.0564 data_time: 0.0156 memory: 583 loss: 1.5309
11/16 19:36:21 - mmengine - INFO - Epoch(train) [4][1490/1563] lr: 1.0000e-03 eta: 0:01:27 time: 0.0565 data_time: 0.0155 memory: 583 loss: 1.5986
11/16 19:36:22 - mmengine - INFO - Epoch(train) [4][1500/1563] lr: 1.0000e-03 eta: 0:01:27 time: 0.0566 data_time: 0.0155 memory: 583 loss: 1.5646
11/16 19:36:22 - mmengine - INFO - Epoch(train) [4][1510/1563] lr: 1.0000e-03 eta: 0:01:26 time: 0.0562 data_time: 0.0154 memory: 583 loss: 1.6112
11/16 19:36:23 - mmengine - INFO - Epoch(train) [4][1520/1563] lr: 1.0000e-03 eta: 0:01:26 time: 0.0563 data_time: 0.0153 memory: 583 loss: 1.5362
11/16 19:36:23 - mmengine - INFO - Epoch(train) [4][1530/1563] lr: 1.0000e-03 eta: 0:01:25 time: 0.0561 data_time: 0.0153 memory: 583 loss: 1.6157
11/16 19:36:24 - mmengine - INFO - Epoch(train) [4][1540/1563] lr: 1.0000e-03 eta: 0:01:25 time: 0.0563 data_time: 0.0153 memory: 583 loss: 1.5889
11/16 19:36:25 - mmengine - INFO - Epoch(train) [4][1550/1563] lr: 1.0000e-03 eta: 0:01:24 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.5280
11/16 19:36:25 - mmengine - INFO - Epoch(train) [4][1560/1563] lr: 1.0000e-03 eta: 0:01:23 time: 0.0563 data_time: 0.0154 memory: 583 loss: 1.5604
11/16 19:36:25 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:36:25 - mmengine - INFO - Saving checkpoint at 4 epochs
11/16 19:36:26 - mmengine - INFO - Epoch(val) [4][ 10/313] eta: 0:00:05 time: 0.0197 data_time: 0.0097 memory: 583
11/16 19:36:26 - mmengine - INFO - Epoch(val) [4][ 20/313] eta: 0:00:05 time: 0.0181 data_time: 0.0091 memory: 424
11/16 19:36:26 - mmengine - INFO - Epoch(val) [4][ 30/313] eta: 0:00:05 time: 0.0170 data_time: 0.0086 memory: 424
11/16 19:36:27 - mmengine - INFO - Epoch(val) [4][ 40/313] eta: 0:00:04 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:36:27 - mmengine - INFO - Epoch(val) [4][ 50/313] eta: 0:00:04 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:36:27 - mmengine - INFO - Epoch(val) [4][ 60/313] eta: 0:00:04 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:36:27 - mmengine - INFO - Epoch(val) [4][ 70/313] eta: 0:00:04 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:36:27 - mmengine - INFO - Epoch(val) [4][ 80/313] eta: 0:00:04 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:36:27 - mmengine - INFO - Epoch(val) [4][ 90/313] eta: 0:00:03 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:36:28 - mmengine - INFO - Epoch(val) [4][100/313] eta: 0:00:03 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:36:28 - mmengine - INFO - Epoch(val) [4][110/313] eta: 0:00:03 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:36:28 - mmengine - INFO - Epoch(val) [4][120/313] eta: 0:00:03 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:36:28 - mmengine - INFO - Epoch(val) [4][130/313] eta: 0:00:03 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:36:28 - mmengine - INFO - Epoch(val) [4][140/313] eta: 0:00:02 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:36:28 - mmengine - INFO - Epoch(val) [4][150/313] eta: 0:00:02 time: 0.0173 data_time: 0.0087 memory: 424
11/16 19:36:29 - mmengine - INFO - Epoch(val) [4][160/313] eta: 0:00:02 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:36:29 - mmengine - INFO - Epoch(val) [4][170/313] eta: 0:00:02 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:36:29 - mmengine - INFO - Epoch(val) [4][180/313] eta: 0:00:02 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:36:29 - mmengine - INFO - Epoch(val) [4][190/313] eta: 0:00:02 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:36:29 - mmengine - INFO - Epoch(val) [4][200/313] eta: 0:00:01 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:36:29 - mmengine - INFO - Epoch(val) [4][210/313] eta: 0:00:01 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:36:30 - mmengine - INFO - Epoch(val) [4][220/313] eta: 0:00:01 time: 0.0168 data_time: 0.0084 memory: 424
11/16 19:36:30 - mmengine - INFO - Epoch(val) [4][230/313] eta: 0:00:01 time: 0.0171 data_time: 0.0085 memory: 424
11/16 19:36:30 - mmengine - INFO - Epoch(val) [4][240/313] eta: 0:00:01 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:36:30 - mmengine - INFO - Epoch(val) [4][250/313] eta: 0:00:01 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:36:30 - mmengine - INFO - Epoch(val) [4][260/313] eta: 0:00:00 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:36:30 - mmengine - INFO - Epoch(val) [4][270/313] eta: 0:00:00 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:36:31 - mmengine - INFO - Epoch(val) [4][280/313] eta: 0:00:00 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:36:31 - mmengine - INFO - Epoch(val) [4][290/313] eta: 0:00:00 time: 0.0169 data_time: 0.0085 memory: 424
11/16 19:36:31 - mmengine - INFO - Epoch(val) [4][300/313] eta: 0:00:00 time: 0.0168 data_time: 0.0085 memory: 424
11/16 19:36:31 - mmengine - INFO - Epoch(val) [4][310/313] eta: 0:00:00 time: 0.0170 data_time: 0.0085 memory: 424
11/16 19:36:31 - mmengine - INFO - Epoch(val) [4][313/313] accuracy: 48.1000 data_time: 0.0085 time: 0.0170
11/16 19:36:32 - mmengine - INFO - Epoch(train) [5][ 10/1563] lr: 1.0000e-03 eta: 0:01:23 time: 0.0515 data_time: 0.0131 memory: 583 loss: 1.4898
11/16 19:36:32 - mmengine - INFO - Epoch(train) [5][ 20/1563] lr: 1.0000e-03 eta: 0:01:22 time: 0.0516 data_time: 0.0132 memory: 583 loss: 1.4765
11/16 19:36:33 - mmengine - INFO - Epoch(train) [5][ 30/1563] lr: 1.0000e-03 eta: 0:01:22 time: 0.0551 data_time: 0.0149 memory: 583 loss: 1.6208
11/16 19:36:33 - mmengine - INFO - Epoch(train) [5][ 40/1563] lr: 1.0000e-03 eta: 0:01:21 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.5789
11/16 19:36:34 - mmengine - INFO - Epoch(train) [5][ 50/1563] lr: 1.0000e-03 eta: 0:01:21 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.5925
11/16 19:36:34 - mmengine - INFO - Epoch(train) [5][ 60/1563] lr: 1.0000e-03 eta: 0:01:20 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.6478
11/16 19:36:35 - mmengine - INFO - Epoch(train) [5][ 70/1563] lr: 1.0000e-03 eta: 0:01:20 time: 0.0527 data_time: 0.0136 memory: 583 loss: 1.4172
11/16 19:36:35 - mmengine - INFO - Epoch(train) [5][ 80/1563] lr: 1.0000e-03 eta: 0:01:19 time: 0.0532 data_time: 0.0141 memory: 583 loss: 1.5051
11/16 19:36:36 - mmengine - INFO - Epoch(train) [5][ 90/1563] lr: 1.0000e-03 eta: 0:01:18 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.5325
11/16 19:36:36 - mmengine - INFO - Epoch(train) [5][ 100/1563] lr: 1.0000e-03 eta: 0:01:18 time: 0.0526 data_time: 0.0137 memory: 583 loss: 1.5734
11/16 19:36:37 - mmengine - INFO - Epoch(train) [5][ 110/1563] lr: 1.0000e-03 eta: 0:01:17 time: 0.0526 data_time: 0.0136 memory: 583 loss: 1.5382
11/16 19:36:38 - mmengine - INFO - Epoch(train) [5][ 120/1563] lr: 1.0000e-03 eta: 0:01:17 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.5414
11/16 19:36:38 - mmengine - INFO - Epoch(train) [5][ 130/1563] lr: 1.0000e-03 eta: 0:01:16 time: 0.0529 data_time: 0.0138 memory: 583 loss: 1.4464
11/16 19:36:39 - mmengine - INFO - Epoch(train) [5][ 140/1563] lr: 1.0000e-03 eta: 0:01:16 time: 0.0529 data_time: 0.0138 memory: 583 loss: 1.4153
11/16 19:36:39 - mmengine - INFO - Epoch(train) [5][ 150/1563] lr: 1.0000e-03 eta: 0:01:15 time: 0.0529 data_time: 0.0137 memory: 583 loss: 1.5358
11/16 19:36:40 - mmengine - INFO - Epoch(train) [5][ 160/1563] lr: 1.0000e-03 eta: 0:01:15 time: 0.0528 data_time: 0.0138 memory: 583 loss: 1.5253
11/16 19:36:40 - mmengine - INFO - Epoch(train) [5][ 170/1563] lr: 1.0000e-03 eta: 0:01:14 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.5026
11/16 19:36:41 - mmengine - INFO - Epoch(train) [5][ 180/1563] lr: 1.0000e-03 eta: 0:01:14 time: 0.0528 data_time: 0.0138 memory: 583 loss: 1.5032
11/16 19:36:41 - mmengine - INFO - Epoch(train) [5][ 190/1563] lr: 1.0000e-03 eta: 0:01:13 time: 0.0526 data_time: 0.0136 memory: 583 loss: 1.5401
11/16 19:36:42 - mmengine - INFO - Epoch(train) [5][ 200/1563] lr: 1.0000e-03 eta: 0:01:13 time: 0.0535 data_time: 0.0140 memory: 583 loss: 1.5001
11/16 19:36:42 - mmengine - INFO - Epoch(train) [5][ 210/1563] lr: 1.0000e-03 eta: 0:01:12 time: 0.0538 data_time: 0.0142 memory: 583 loss: 1.6214
11/16 19:36:43 - mmengine - INFO - Epoch(train) [5][ 220/1563] lr: 1.0000e-03 eta: 0:01:11 time: 0.0527 data_time: 0.0136 memory: 583 loss: 1.3950
11/16 19:36:43 - mmengine - INFO - Epoch(train) [5][ 230/1563] lr: 1.0000e-03 eta: 0:01:11 time: 0.0530 data_time: 0.0136 memory: 583 loss: 1.6352
11/16 19:36:44 - mmengine - INFO - Epoch(train) [5][ 240/1563] lr: 1.0000e-03 eta: 0:01:10 time: 0.0543 data_time: 0.0144 memory: 583 loss: 1.4896
11/16 19:36:44 - mmengine - INFO - Epoch(train) [5][ 250/1563] lr: 1.0000e-03 eta: 0:01:10 time: 0.0543 data_time: 0.0144 memory: 583 loss: 1.4954
11/16 19:36:45 - mmengine - INFO - Epoch(train) [5][ 260/1563] lr: 1.0000e-03 eta: 0:01:09 time: 0.0530 data_time: 0.0138 memory: 583 loss: 1.5834
11/16 19:36:45 - mmengine - INFO - Epoch(train) [5][ 270/1563] lr: 1.0000e-03 eta: 0:01:09 time: 0.0526 data_time: 0.0138 memory: 583 loss: 1.6811
11/16 19:36:46 - mmengine - INFO - Epoch(train) [5][ 280/1563] lr: 1.0000e-03 eta: 0:01:08 time: 0.0529 data_time: 0.0138 memory: 583 loss: 1.5205
11/16 19:36:47 - mmengine - INFO - Epoch(train) [5][ 290/1563] lr: 1.0000e-03 eta: 0:01:08 time: 0.0526 data_time: 0.0137 memory: 583 loss: 1.5678
11/16 19:36:47 - mmengine - INFO - Epoch(train) [5][ 300/1563] lr: 1.0000e-03 eta: 0:01:07 time: 0.0530 data_time: 0.0138 memory: 583 loss: 1.4220
11/16 19:36:48 - mmengine - INFO - Epoch(train) [5][ 310/1563] lr: 1.0000e-03 eta: 0:01:07 time: 0.0527 data_time: 0.0136 memory: 583 loss: 1.4808
11/16 19:36:48 - mmengine - INFO - Epoch(train) [5][ 320/1563] lr: 1.0000e-03 eta: 0:01:06 time: 0.0528 data_time: 0.0138 memory: 583 loss: 1.5319
11/16 19:36:49 - mmengine - INFO - Epoch(train) [5][ 330/1563] lr: 1.0000e-03 eta: 0:01:06 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.5735
11/16 19:36:49 - mmengine - INFO - Epoch(train) [5][ 340/1563] lr: 1.0000e-03 eta: 0:01:05 time: 0.0529 data_time: 0.0137 memory: 583 loss: 1.4347
11/16 19:36:50 - mmengine - INFO - Epoch(train) [5][ 350/1563] lr: 1.0000e-03 eta: 0:01:04 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4799
11/16 19:36:50 - mmengine - INFO - Epoch(train) [5][ 360/1563] lr: 1.0000e-03 eta: 0:01:04 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.4012
11/16 19:36:51 - mmengine - INFO - Epoch(train) [5][ 370/1563] lr: 1.0000e-03 eta: 0:01:03 time: 0.0530 data_time: 0.0137 memory: 583 loss: 1.4668
11/16 19:36:51 - mmengine - INFO - Epoch(train) [5][ 380/1563] lr: 1.0000e-03 eta: 0:01:03 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.4760
11/16 19:36:52 - mmengine - INFO - Epoch(train) [5][ 390/1563] lr: 1.0000e-03 eta: 0:01:02 time: 0.0527 data_time: 0.0138 memory: 583 loss: 1.6199
11/16 19:36:52 - mmengine - INFO - Epoch(train) [5][ 400/1563] lr: 1.0000e-03 eta: 0:01:02 time: 0.0527 data_time: 0.0137 memory: 583 loss: 1.5602
11/16 19:36:53 - mmengine - INFO - Epoch(train) [5][ 410/1563] lr: 1.0000e-03 eta: 0:01:01 time: 0.0529 data_time: 0.0139 memory: 583 loss: 1.5030
11/16 19:36:53 - mmengine - INFO - Epoch(train) [5][ 420/1563] lr: 1.0000e-03 eta: 0:01:01 time: 0.0527 data_time: 0.0137 memory: 583 loss: 1.5223
11/16 19:36:54 - mmengine - INFO - Epoch(train) [5][ 430/1563] lr: 1.0000e-03 eta: 0:01:00 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.4740
11/16 19:36:54 - mmengine - INFO - Epoch(train) [5][ 440/1563] lr: 1.0000e-03 eta: 0:01:00 time: 0.0530 data_time: 0.0138 memory: 583 loss: 1.5722
11/16 19:36:55 - mmengine - INFO - Epoch(train) [5][ 450/1563] lr: 1.0000e-03 eta: 0:00:59 time: 0.0529 data_time: 0.0137 memory: 583 loss: 1.5297
11/16 19:36:56 - mmengine - INFO - Epoch(train) [5][ 460/1563] lr: 1.0000e-03 eta: 0:00:59 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.5597
11/16 19:36:56 - mmengine - INFO - Epoch(train) [5][ 470/1563] lr: 1.0000e-03 eta: 0:00:58 time: 0.0529 data_time: 0.0140 memory: 583 loss: 1.5702
11/16 19:36:57 - mmengine - INFO - Epoch(train) [5][ 480/1563] lr: 1.0000e-03 eta: 0:00:58 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.6565
11/16 19:36:57 - mmengine - INFO - Epoch(train) [5][ 490/1563] lr: 1.0000e-03 eta: 0:00:57 time: 0.0526 data_time: 0.0137 memory: 583 loss: 1.4949
11/16 19:36:58 - mmengine - INFO - Epoch(train) [5][ 500/1563] lr: 1.0000e-03 eta: 0:00:56 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.5098
11/16 19:36:58 - mmengine - INFO - Epoch(train) [5][ 510/1563] lr: 1.0000e-03 eta: 0:00:56 time: 0.0531 data_time: 0.0140 memory: 583 loss: 1.5387
11/16 19:36:59 - mmengine - INFO - Epoch(train) [5][ 520/1563] lr: 1.0000e-03 eta: 0:00:55 time: 0.0529 data_time: 0.0138 memory: 583 loss: 1.5758
11/16 19:36:59 - mmengine - INFO - Epoch(train) [5][ 530/1563] lr: 1.0000e-03 eta: 0:00:55 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.5320
11/16 19:37:00 - mmengine - INFO - Epoch(train) [5][ 540/1563] lr: 1.0000e-03 eta: 0:00:54 time: 0.0529 data_time: 0.0138 memory: 583 loss: 1.6817
11/16 19:37:00 - mmengine - INFO - Epoch(train) [5][ 550/1563] lr: 1.0000e-03 eta: 0:00:54 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.3118
11/16 19:37:01 - mmengine - INFO - Epoch(train) [5][ 560/1563] lr: 1.0000e-03 eta: 0:00:53 time: 0.0526 data_time: 0.0137 memory: 583 loss: 1.5294
11/16 19:37:01 - mmengine - INFO - Epoch(train) [5][ 570/1563] lr: 1.0000e-03 eta: 0:00:53 time: 0.0524 data_time: 0.0135 memory: 583 loss: 1.5879
11/16 19:37:02 - mmengine - INFO - Epoch(train) [5][ 580/1563] lr: 1.0000e-03 eta: 0:00:52 time: 0.0528 data_time: 0.0137 memory: 583 loss: 1.5371
11/16 19:37:02 - mmengine - INFO - Epoch(train) [5][ 590/1563] lr: 1.0000e-03 eta: 0:00:52 time: 0.0526 data_time: 0.0137 memory: 583 loss: 1.5631
11/16 19:37:03 - mmengine - INFO - Epoch(train) [5][ 600/1563] lr: 1.0000e-03 eta: 0:00:51 time: 0.0529 data_time: 0.0138 memory: 583 loss: 1.5269
11/16 19:37:03 - mmengine - INFO - Epoch(train) [5][ 610/1563] lr: 1.0000e-03 eta: 0:00:51 time: 0.0525 data_time: 0.0136 memory: 583 loss: 1.4735
11/16 19:37:04 - mmengine - INFO - Epoch(train) [5][ 620/1563] lr: 1.0000e-03 eta: 0:00:50 time: 0.0530 data_time: 0.0138 memory: 583 loss: 1.6116
11/16 19:37:05 - mmengine - INFO - Epoch(train) [5][ 630/1563] lr: 1.0000e-03 eta: 0:00:49 time: 0.0530 data_time: 0.0139 memory: 583 loss: 1.5450
11/16 19:37:05 - mmengine - INFO - Epoch(train) [5][ 640/1563] lr: 1.0000e-03 eta: 0:00:49 time: 0.0530 data_time: 0.0138 memory: 583 loss: 1.5807
11/16 19:37:06 - mmengine - INFO - Epoch(train) [5][ 650/1563] lr: 1.0000e-03 eta: 0:00:48 time: 0.0531 data_time: 0.0139 memory: 583 loss: 1.6075
11/16 19:37:06 - mmengine - INFO - Epoch(train) [5][ 660/1563] lr: 1.0000e-03 eta: 0:00:48 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4707
11/16 19:37:07 - mmengine - INFO - Epoch(train) [5][ 670/1563] lr: 1.0000e-03 eta: 0:00:47 time: 0.0532 data_time: 0.0141 memory: 583 loss: 1.4897
11/16 19:37:07 - mmengine - INFO - Epoch(train) [5][ 680/1563] lr: 1.0000e-03 eta: 0:00:47 time: 0.0525 data_time: 0.0137 memory: 583 loss: 1.5033
11/16 19:37:08 - mmengine - INFO - Epoch(train) [5][ 690/1563] lr: 1.0000e-03 eta: 0:00:46 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.4563
11/16 19:37:08 - mmengine - INFO - Epoch(train) [5][ 700/1563] lr: 1.0000e-03 eta: 0:00:46 time: 0.0524 data_time: 0.0135 memory: 583 loss: 1.4896
11/16 19:37:09 - mmengine - INFO - Epoch(train) [5][ 710/1563] lr: 1.0000e-03 eta: 0:00:45 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.4151
11/16 19:37:09 - mmengine - INFO - Epoch(train) [5][ 720/1563] lr: 1.0000e-03 eta: 0:00:45 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5665
11/16 19:37:10 - mmengine - INFO - Epoch(train) [5][ 730/1563] lr: 1.0000e-03 eta: 0:00:44 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.5743
11/16 19:37:10 - mmengine - INFO - Epoch(train) [5][ 740/1563] lr: 1.0000e-03 eta: 0:00:44 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4464
11/16 19:37:11 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:37:11 - mmengine - INFO - Epoch(train) [5][ 750/1563] lr: 1.0000e-03 eta: 0:00:43 time: 0.0532 data_time: 0.0141 memory: 583 loss: 1.4977
11/16 19:37:11 - mmengine - INFO - Epoch(train) [5][ 760/1563] lr: 1.0000e-03 eta: 0:00:42 time: 0.0519 data_time: 0.0132 memory: 583 loss: 1.5969
11/16 19:37:12 - mmengine - INFO - Epoch(train) [5][ 770/1563] lr: 1.0000e-03 eta: 0:00:42 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.4688
11/16 19:37:12 - mmengine - INFO - Epoch(train) [5][ 780/1563] lr: 1.0000e-03 eta: 0:00:41 time: 0.0519 data_time: 0.0135 memory: 583 loss: 1.4980
11/16 19:37:13 - mmengine - INFO - Epoch(train) [5][ 790/1563] lr: 1.0000e-03 eta: 0:00:41 time: 0.0522 data_time: 0.0134 memory: 583 loss: 1.4763
11/16 19:37:13 - mmengine - INFO - Epoch(train) [5][ 800/1563] lr: 1.0000e-03 eta: 0:00:40 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.3775
11/16 19:37:14 - mmengine - INFO - Epoch(train) [5][ 810/1563] lr: 1.0000e-03 eta: 0:00:40 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5056
11/16 19:37:14 - mmengine - INFO - Epoch(train) [5][ 820/1563] lr: 1.0000e-03 eta: 0:00:39 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5930
11/16 19:37:15 - mmengine - INFO - Epoch(train) [5][ 830/1563] lr: 1.0000e-03 eta: 0:00:39 time: 0.0522 data_time: 0.0134 memory: 583 loss: 1.5652
11/16 19:37:15 - mmengine - INFO - Epoch(train) [5][ 840/1563] lr: 1.0000e-03 eta: 0:00:38 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4322
11/16 19:37:16 - mmengine - INFO - Epoch(train) [5][ 850/1563] lr: 1.0000e-03 eta: 0:00:38 time: 0.0523 data_time: 0.0137 memory: 583 loss: 1.3475
11/16 19:37:17 - mmengine - INFO - Epoch(train) [5][ 860/1563] lr: 1.0000e-03 eta: 0:00:37 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5206
11/16 19:37:17 - mmengine - INFO - Epoch(train) [5][ 870/1563] lr: 1.0000e-03 eta: 0:00:37 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.4609
11/16 19:37:18 - mmengine - INFO - Epoch(train) [5][ 880/1563] lr: 1.0000e-03 eta: 0:00:36 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5457
11/16 19:37:18 - mmengine - INFO - Epoch(train) [5][ 890/1563] lr: 1.0000e-03 eta: 0:00:36 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5227
11/16 19:37:19 - mmengine - INFO - Epoch(train) [5][ 900/1563] lr: 1.0000e-03 eta: 0:00:35 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.4527
11/16 19:37:19 - mmengine - INFO - Epoch(train) [5][ 910/1563] lr: 1.0000e-03 eta: 0:00:34 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4892
11/16 19:37:20 - mmengine - INFO - Epoch(train) [5][ 920/1563] lr: 1.0000e-03 eta: 0:00:34 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.6151
11/16 19:37:20 - mmengine - INFO - Epoch(train) [5][ 930/1563] lr: 1.0000e-03 eta: 0:00:33 time: 0.0523 data_time: 0.0137 memory: 583 loss: 1.5074
11/16 19:37:21 - mmengine - INFO - Epoch(train) [5][ 940/1563] lr: 1.0000e-03 eta: 0:00:33 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.5901
11/16 19:37:21 - mmengine - INFO - Epoch(train) [5][ 950/1563] lr: 1.0000e-03 eta: 0:00:32 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.6118
11/16 19:37:22 - mmengine - INFO - Epoch(train) [5][ 960/1563] lr: 1.0000e-03 eta: 0:00:32 time: 0.0512 data_time: 0.0135 memory: 583 loss: 1.4956
11/16 19:37:22 - mmengine - INFO - Epoch(train) [5][ 970/1563] lr: 1.0000e-03 eta: 0:00:31 time: 0.0516 data_time: 0.0134 memory: 583 loss: 1.4863
11/16 19:37:23 - mmengine - INFO - Epoch(train) [5][ 980/1563] lr: 1.0000e-03 eta: 0:00:31 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.4141
11/16 19:37:23 - mmengine - INFO - Epoch(train) [5][ 990/1563] lr: 1.0000e-03 eta: 0:00:30 time: 0.0520 data_time: 0.0132 memory: 583 loss: 1.5219
11/16 19:37:24 - mmengine - INFO - Epoch(train) [5][1000/1563] lr: 1.0000e-03 eta: 0:00:30 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4401
11/16 19:37:24 - mmengine - INFO - Epoch(train) [5][1010/1563] lr: 1.0000e-03 eta: 0:00:29 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5296
11/16 19:37:25 - mmengine - INFO - Epoch(train) [5][1020/1563] lr: 1.0000e-03 eta: 0:00:29 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5026
11/16 19:37:25 - mmengine - INFO - Epoch(train) [5][1030/1563] lr: 1.0000e-03 eta: 0:00:28 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.4996
11/16 19:37:26 - mmengine - INFO - Epoch(train) [5][1040/1563] lr: 1.0000e-03 eta: 0:00:27 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.5231
11/16 19:37:26 - mmengine - INFO - Epoch(train) [5][1050/1563] lr: 1.0000e-03 eta: 0:00:27 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4268
11/16 19:37:27 - mmengine - INFO - Epoch(train) [5][1060/1563] lr: 1.0000e-03 eta: 0:00:26 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5333
11/16 19:37:27 - mmengine - INFO - Epoch(train) [5][1070/1563] lr: 1.0000e-03 eta: 0:00:26 time: 0.0523 data_time: 0.0134 memory: 583 loss: 1.3655
11/16 19:37:28 - mmengine - INFO - Epoch(train) [5][1080/1563] lr: 1.0000e-03 eta: 0:00:25 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.5330
11/16 19:37:29 - mmengine - INFO - Epoch(train) [5][1090/1563] lr: 1.0000e-03 eta: 0:00:25 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.5190
11/16 19:37:29 - mmengine - INFO - Epoch(train) [5][1100/1563] lr: 1.0000e-03 eta: 0:00:24 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5310
11/16 19:37:30 - mmengine - INFO - Epoch(train) [5][1110/1563] lr: 1.0000e-03 eta: 0:00:24 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.6061
11/16 19:37:30 - mmengine - INFO - Epoch(train) [5][1120/1563] lr: 1.0000e-03 eta: 0:00:23 time: 0.0524 data_time: 0.0137 memory: 583 loss: 1.4444
11/16 19:37:31 - mmengine - INFO - Epoch(train) [5][1130/1563] lr: 1.0000e-03 eta: 0:00:23 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.3861
11/16 19:37:31 - mmengine - INFO - Epoch(train) [5][1140/1563] lr: 1.0000e-03 eta: 0:00:22 time: 0.0524 data_time: 0.0137 memory: 583 loss: 1.4380
11/16 19:37:32 - mmengine - INFO - Epoch(train) [5][1150/1563] lr: 1.0000e-03 eta: 0:00:22 time: 0.0523 data_time: 0.0136 memory: 583 loss: 1.5193
11/16 19:37:32 - mmengine - INFO - Epoch(train) [5][1160/1563] lr: 1.0000e-03 eta: 0:00:21 time: 0.0518 data_time: 0.0133 memory: 583 loss: 1.5001
11/16 19:37:33 - mmengine - INFO - Epoch(train) [5][1170/1563] lr: 1.0000e-03 eta: 0:00:21 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.4448
11/16 19:37:33 - mmengine - INFO - Epoch(train) [5][1180/1563] lr: 1.0000e-03 eta: 0:00:20 time: 0.0521 data_time: 0.0135 memory: 583 loss: 1.5808
11/16 19:37:34 - mmengine - INFO - Epoch(train) [5][1190/1563] lr: 1.0000e-03 eta: 0:00:19 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.5503
11/16 19:37:34 - mmengine - INFO - Epoch(train) [5][1200/1563] lr: 1.0000e-03 eta: 0:00:19 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.4549
11/16 19:37:35 - mmengine - INFO - Epoch(train) [5][1210/1563] lr: 1.0000e-03 eta: 0:00:18 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5404
11/16 19:37:35 - mmengine - INFO - Epoch(train) [5][1220/1563] lr: 1.0000e-03 eta: 0:00:18 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.6810
11/16 19:37:36 - mmengine - INFO - Epoch(train) [5][1230/1563] lr: 1.0000e-03 eta: 0:00:17 time: 0.0521 data_time: 0.0136 memory: 583 loss: 1.4515
11/16 19:37:36 - mmengine - INFO - Epoch(train) [5][1240/1563] lr: 1.0000e-03 eta: 0:00:17 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.5025
11/16 19:37:37 - mmengine - INFO - Epoch(train) [5][1250/1563] lr: 1.0000e-03 eta: 0:00:16 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.5501
11/16 19:37:37 - mmengine - INFO - Epoch(train) [5][1260/1563] lr: 1.0000e-03 eta: 0:00:16 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4776
11/16 19:37:38 - mmengine - INFO - Epoch(train) [5][1270/1563] lr: 1.0000e-03 eta: 0:00:15 time: 0.0518 data_time: 0.0132 memory: 583 loss: 1.4217
11/16 19:37:38 - mmengine - INFO - Epoch(train) [5][1280/1563] lr: 1.0000e-03 eta: 0:00:15 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.4721
11/16 19:37:39 - mmengine - INFO - Epoch(train) [5][1290/1563] lr: 1.0000e-03 eta: 0:00:14 time: 0.0522 data_time: 0.0135 memory: 583 loss: 1.4576
11/16 19:37:39 - mmengine - INFO - Epoch(train) [5][1300/1563] lr: 1.0000e-03 eta: 0:00:14 time: 0.0513 data_time: 0.0133 memory: 583 loss: 1.3825
11/16 19:37:40 - mmengine - INFO - Epoch(train) [5][1310/1563] lr: 1.0000e-03 eta: 0:00:13 time: 0.0525 data_time: 0.0138 memory: 583 loss: 1.4888
11/16 19:37:41 - mmengine - INFO - Epoch(train) [5][1320/1563] lr: 1.0000e-03 eta: 0:00:12 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.3870
11/16 19:37:41 - mmengine - INFO - Epoch(train) [5][1330/1563] lr: 1.0000e-03 eta: 0:00:12 time: 0.0529 data_time: 0.0137 memory: 583 loss: 1.6107
11/16 19:37:42 - mmengine - INFO - Epoch(train) [5][1340/1563] lr: 1.0000e-03 eta: 0:00:11 time: 0.0555 data_time: 0.0146 memory: 583 loss: 1.5175
11/16 19:37:42 - mmengine - INFO - Epoch(train) [5][1350/1563] lr: 1.0000e-03 eta: 0:00:11 time: 0.0556 data_time: 0.0144 memory: 583 loss: 1.4579
11/16 19:37:43 - mmengine - INFO - Epoch(train) [5][1360/1563] lr: 1.0000e-03 eta: 0:00:10 time: 0.0554 data_time: 0.0144 memory: 583 loss: 1.4369
11/16 19:37:43 - mmengine - INFO - Epoch(train) [5][1370/1563] lr: 1.0000e-03 eta: 0:00:10 time: 0.0557 data_time: 0.0145 memory: 583 loss: 1.3232
11/16 19:37:44 - mmengine - INFO - Epoch(train) [5][1380/1563] lr: 1.0000e-03 eta: 0:00:09 time: 0.0556 data_time: 0.0146 memory: 583 loss: 1.4291
11/16 19:37:44 - mmengine - INFO - Epoch(train) [5][1390/1563] lr: 1.0000e-03 eta: 0:00:09 time: 0.0546 data_time: 0.0143 memory: 583 loss: 1.5174
11/16 19:37:45 - mmengine - INFO - Epoch(train) [5][1400/1563] lr: 1.0000e-03 eta: 0:00:08 time: 0.0534 data_time: 0.0138 memory: 583 loss: 1.5390
11/16 19:37:45 - mmengine - INFO - Epoch(train) [5][1410/1563] lr: 1.0000e-03 eta: 0:00:08 time: 0.0518 data_time: 0.0134 memory: 583 loss: 1.5225
11/16 19:37:46 - mmengine - INFO - Epoch(train) [5][1420/1563] lr: 1.0000e-03 eta: 0:00:07 time: 0.0521 data_time: 0.0134 memory: 583 loss: 1.3912
11/16 19:37:46 - mmengine - INFO - Epoch(train) [5][1430/1563] lr: 1.0000e-03 eta: 0:00:07 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5429
11/16 19:37:47 - mmengine - INFO - Epoch(train) [5][1440/1563] lr: 1.0000e-03 eta: 0:00:06 time: 0.0520 data_time: 0.0133 memory: 583 loss: 1.5281
11/16 19:37:48 - mmengine - INFO - Epoch(train) [5][1450/1563] lr: 1.0000e-03 eta: 0:00:06 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.5734
11/16 19:37:48 - mmengine - INFO - Epoch(train) [5][1460/1563] lr: 1.0000e-03 eta: 0:00:05 time: 0.0524 data_time: 0.0135 memory: 583 loss: 1.4923
11/16 19:37:49 - mmengine - INFO - Epoch(train) [5][1470/1563] lr: 1.0000e-03 eta: 0:00:04 time: 0.0520 data_time: 0.0135 memory: 583 loss: 1.4860
11/16 19:37:49 - mmengine - INFO - Epoch(train) [5][1480/1563] lr: 1.0000e-03 eta: 0:00:04 time: 0.0517 data_time: 0.0133 memory: 583 loss: 1.3867
11/16 19:37:50 - mmengine - INFO - Epoch(train) [5][1490/1563] lr: 1.0000e-03 eta: 0:00:03 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5023
11/16 19:37:50 - mmengine - INFO - Epoch(train) [5][1500/1563] lr: 1.0000e-03 eta: 0:00:03 time: 0.0519 data_time: 0.0134 memory: 583 loss: 1.5159
11/16 19:37:51 - mmengine - INFO - Epoch(train) [5][1510/1563] lr: 1.0000e-03 eta: 0:00:02 time: 0.0515 data_time: 0.0133 memory: 583 loss: 1.5236
11/16 19:37:51 - mmengine - INFO - Epoch(train) [5][1520/1563] lr: 1.0000e-03 eta: 0:00:02 time: 0.0520 data_time: 0.0134 memory: 583 loss: 1.4562
11/16 19:37:52 - mmengine - INFO - Epoch(train) [5][1530/1563] lr: 1.0000e-03 eta: 0:00:01 time: 0.0524 data_time: 0.0136 memory: 583 loss: 1.3925
11/16 19:37:52 - mmengine - INFO - Epoch(train) [5][1540/1563] lr: 1.0000e-03 eta: 0:00:01 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.4927
11/16 19:37:53 - mmengine - INFO - Epoch(train) [5][1550/1563] lr: 1.0000e-03 eta: 0:00:00 time: 0.0523 data_time: 0.0135 memory: 583 loss: 1.4950
11/16 19:37:53 - mmengine - INFO - Epoch(train) [5][1560/1563] lr: 1.0000e-03 eta: 0:00:00 time: 0.0519 data_time: 0.0133 memory: 583 loss: 1.5727
11/16 19:37:53 - mmengine - INFO - Exp name: 20241116_193032
11/16 19:37:53 - mmengine - INFO - Saving checkpoint at 5 epochs
11/16 19:37:54 - mmengine - INFO - Epoch(val) [5][ 10/313] eta: 0:00:05 time: 0.0180 data_time: 0.0097 memory: 583
11/16 19:37:54 - mmengine - INFO - Epoch(val) [5][ 20/313] eta: 0:00:05 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:37:54 - mmengine - INFO - Epoch(val) [5][ 30/313] eta: 0:00:04 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:37:55 - mmengine - INFO - Epoch(val) [5][ 40/313] eta: 0:00:04 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:55 - mmengine - INFO - Epoch(val) [5][ 50/313] eta: 0:00:04 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:37:55 - mmengine - INFO - Epoch(val) [5][ 60/313] eta: 0:00:04 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:55 - mmengine - INFO - Epoch(val) [5][ 70/313] eta: 0:00:04 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:37:55 - mmengine - INFO - Epoch(val) [5][ 80/313] eta: 0:00:03 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:37:55 - mmengine - INFO - Epoch(val) [5][ 90/313] eta: 0:00:03 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:56 - mmengine - INFO - Epoch(val) [5][100/313] eta: 0:00:03 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:56 - mmengine - INFO - Epoch(val) [5][110/313] eta: 0:00:03 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:37:56 - mmengine - INFO - Epoch(val) [5][120/313] eta: 0:00:03 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:56 - mmengine - INFO - Epoch(val) [5][130/313] eta: 0:00:03 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:56 - mmengine - INFO - Epoch(val) [5][140/313] eta: 0:00:02 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:56 - mmengine - INFO - Epoch(val) [5][150/313] eta: 0:00:02 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:57 - mmengine - INFO - Epoch(val) [5][160/313] eta: 0:00:02 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:57 - mmengine - INFO - Epoch(val) [5][170/313] eta: 0:00:02 time: 0.0164 data_time: 0.0082 memory: 424
11/16 19:37:57 - mmengine - INFO - Epoch(val) [5][180/313] eta: 0:00:02 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:37:57 - mmengine - INFO - Epoch(val) [5][190/313] eta: 0:00:02 time: 0.0167 data_time: 0.0084 memory: 424
11/16 19:37:57 - mmengine - INFO - Epoch(val) [5][200/313] eta: 0:00:01 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:57 - mmengine - INFO - Epoch(val) [5][210/313] eta: 0:00:01 time: 0.0166 data_time: 0.0082 memory: 424
11/16 19:37:58 - mmengine - INFO - Epoch(val) [5][220/313] eta: 0:00:01 time: 0.0166 data_time: 0.0083 memory: 424
11/16 19:37:58 - mmengine - INFO - Epoch(val) [5][230/313] eta: 0:00:01 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:37:58 - mmengine - INFO - Epoch(val) [5][240/313] eta: 0:00:01 time: 0.0166 data_time: 0.0082 memory: 424
11/16 19:37:58 - mmengine - INFO - Epoch(val) [5][250/313] eta: 0:00:01 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:37:58 - mmengine - INFO - Epoch(val) [5][260/313] eta: 0:00:00 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:58 - mmengine - INFO - Epoch(val) [5][270/313] eta: 0:00:00 time: 0.0169 data_time: 0.0084 memory: 424
11/16 19:37:59 - mmengine - INFO - Epoch(val) [5][280/313] eta: 0:00:00 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:59 - mmengine - INFO - Epoch(val) [5][290/313] eta: 0:00:00 time: 0.0164 data_time: 0.0082 memory: 424
11/16 19:37:59 - mmengine - INFO - Epoch(val) [5][300/313] eta: 0:00:00 time: 0.0165 data_time: 0.0082 memory: 424
11/16 19:37:59 - mmengine - INFO - Epoch(val) [5][310/313] eta: 0:00:00 time: 0.0167 data_time: 0.0083 memory: 424
11/16 19:37:59 - mmengine - INFO - Epoch(val) [5][313/313] accuracy: 50.1800 data_time: 0.0083 time: 0.0166
MMResNet50(
(data_preprocessor): BaseDataPreprocessor()
(resnet): ResNet(
(conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
(bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
(layer1): Sequential(
(0): Bottleneck(
(conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): Bottleneck(
(conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): Bottleneck(
(conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
)
(layer2): Sequential(
(0): Bottleneck(
(conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
(1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): Bottleneck(
(conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): Bottleneck(
(conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(3): Bottleneck(
(conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
)
(layer3): Sequential(
(0): Bottleneck(
(conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False)
(1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): Bottleneck(
(conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): Bottleneck(
(conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(3): Bottleneck(
(conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(4): Bottleneck(
(conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(5): Bottleneck(
(conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
)
(layer4): Sequential(
(0): Bottleneck(
(conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
(downsample): Sequential(
(0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False)
(1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
)
)
(1): Bottleneck(
(conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
(2): Bottleneck(
(conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False)
(bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(relu): ReLU(inplace=True)
)
)
(avgpool): AdaptiveAvgPool2d(output_size=(1, 1))
(fc): Linear(in_features=2048, out_features=1000, bias=True)
)
)