2023/04/13 17:27:38 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.16 (default, Jan 17 2023, 22:20:44) [GCC 11.2.0] CUDA available: True numpy_random_seed: 1785764901 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: None GCC: gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44) PyTorch: 1.13.1+cu116 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.6 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-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 - CuDNN 8.3.2 (built against CUDA 11.5) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.6, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.14.1+cu116 OpenCV: 4.7.0 MMEngine: 0.7.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None deterministic: False Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/04/13 17:27:39 - mmengine - INFO - Config: model = dict( _scope_='mmrazor', type='MMArchitectureQuant', data_preprocessor=dict( type='mmcls.ClsDataPreprocessor', num_classes=1000, mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), architecture=dict( type='ImageClassifier', backbone=dict( type='ResNet', depth=18, num_stages=4, out_indices=(3, ), style='pytorch'), neck=dict(type='GlobalAveragePooling'), head=dict( type='LinearClsHead', num_classes=1000, in_channels=512, loss=dict(type='CrossEntropyLoss', loss_weight=1.0), topk=(1, 5)), _scope_='mmcls'), float_checkpoint= 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet18_8xb32_in1k_20210831-fbbb1da6.pth', quantizer=dict( type='mmrazor.OpenVINOQuantizer', global_qconfig=dict( w_observer=dict(type='mmrazor.PerChannelMinMaxObserver'), a_observer=dict(type='mmrazor.MovingAverageMinMaxObserver'), w_fake_quant=dict(type='mmrazor.FakeQuantize'), a_fake_quant=dict(type='mmrazor.FakeQuantize'), w_qscheme=dict( qdtype='qint8', bit=8, is_symmetry=True, is_symmetric_range=True), a_qscheme=dict(qdtype='quint8', bit=8, is_symmetry=True)), tracer=dict( type='mmrazor.CustomTracer', skipped_methods=[ 'mmcls.models.heads.ClsHead._get_loss', 'mmcls.models.heads.ClsHead._get_predictions' ]))) dataset_type = 'ImageNet' data_preprocessor = dict( num_classes=1000, mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile', _scope_='mmcls'), dict(type='RandomResizedCrop', scale=224, _scope_='mmcls'), dict(type='RandomFlip', prob=0.5, direction='horizontal', _scope_='mmcls'), dict(type='PackClsInputs', _scope_='mmcls') ] test_pipeline = [ dict(type='LoadImageFromFile', _scope_='mmcls'), dict(type='ResizeEdge', scale=256, edge='short', _scope_='mmcls'), dict(type='CenterCrop', crop_size=224, _scope_='mmcls'), dict(type='PackClsInputs', _scope_='mmcls') ] train_dataloader = dict( batch_size=32, num_workers=5, dataset=dict( type='ImageNet', data_root='data/imagenet', ann_file='meta/train.txt', data_prefix='train', pipeline=[ dict(type='LoadImageFromFile'), dict(type='RandomResizedCrop', scale=224), dict(type='RandomFlip', prob=0.5, direction='horizontal'), dict(type='PackClsInputs') ], _scope_='mmcls'), sampler=dict(type='DefaultSampler', shuffle=True, _scope_='mmcls')) val_dataloader = dict( batch_size=32, num_workers=5, dataset=dict( type='ImageNet', data_root='data/imagenet', ann_file='meta/val.txt', data_prefix='val', pipeline=[ dict(type='LoadImageFromFile'), dict(type='ResizeEdge', scale=256, edge='short'), dict(type='CenterCrop', crop_size=224), dict(type='PackClsInputs') ], _scope_='mmcls'), sampler=dict(type='DefaultSampler', shuffle=False, _scope_='mmcls')) val_evaluator = dict(type='Accuracy', topk=(1, 5), _scope_='mmcls') test_dataloader = dict( batch_size=32, num_workers=5, dataset=dict( type='ImageNet', data_root='data/imagenet', ann_file='meta/val.txt', data_prefix='val', pipeline=[ dict(type='LoadImageFromFile'), dict(type='ResizeEdge', scale=256, edge='short'), dict(type='CenterCrop', crop_size=224), dict(type='PackClsInputs') ], _scope_='mmcls'), sampler=dict(type='DefaultSampler', shuffle=False, _scope_='mmcls')) test_evaluator = dict(type='Accuracy', topk=(1, 5), _scope_='mmcls') optim_wrapper = dict( optimizer=dict( type='SGD', lr=0.0001, momentum=0.9, weight_decay=0.0001, _scope_='mmcls')) param_scheduler = dict(type='ConstantLR', by_epoch=True) train_cfg = dict( type='mmrazor.QATEpochBasedLoop', max_epochs=10, val_interval=1) val_cfg = dict(type='mmrazor.QATValLoop') test_cfg = dict(type='mmrazor.QATValLoop') auto_scale_lr = dict(base_batch_size=256) default_scope = 'mmcls' default_hooks = dict( timer=dict(type='IterTimerHook', _scope_='mmcls'), logger=dict(type='LoggerHook', interval=100, _scope_='mmcls'), param_scheduler=dict(type='ParamSchedulerHook', _scope_='mmcls'), checkpoint=dict(type='CheckpointHook', interval=1, _scope_='mmcls'), sampler_seed=dict(type='DistSamplerSeedHook', _scope_='mmcls'), visualization=dict( type='VisualizationHook', enable=False, _scope_='mmcls'), sync=dict(type='SyncBuffersHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) vis_backends = [dict(type='LocalVisBackend', _scope_='mmcls')] visualizer = dict( type='ClsVisualizer', vis_backends=[dict(type='LocalVisBackend')], _scope_='mmcls') log_level = 'INFO' load_from = None resume = False randomness = dict(seed=None, deterministic=False) resnet = dict( type='ImageClassifier', backbone=dict( type='ResNet', depth=18, num_stages=4, out_indices=(3, ), style='pytorch'), neck=dict(type='GlobalAveragePooling'), head=dict( type='LinearClsHead', num_classes=1000, in_channels=512, loss=dict(type='CrossEntropyLoss', loss_weight=1.0), topk=(1, 5)), _scope_='mmcls') float_checkpoint = 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet18_8xb32_in1k_20210831-fbbb1da6.pth' global_qconfig = dict( w_observer=dict(type='mmrazor.PerChannelMinMaxObserver'), a_observer=dict(type='mmrazor.MovingAverageMinMaxObserver'), w_fake_quant=dict(type='mmrazor.FakeQuantize'), a_fake_quant=dict(type='mmrazor.FakeQuantize'), w_qscheme=dict( qdtype='qint8', bit=8, is_symmetry=True, is_symmetric_range=True), a_qscheme=dict(qdtype='quint8', bit=8, is_symmetry=True)) model_wrapper_cfg = dict( type='mmrazor.MMArchitectureQuantDDP', broadcast_buffers=False, find_unused_parameters=False) launcher = 'pytorch' work_dir = 'qat_r18_test' 2023/04/13 17:27:39 - mmengine - WARNING - The "task util" registry in mmrazor did not set import location. Fallback to call `mmrazor.utils.register_all_modules` instead. 2023/04/13 17:27:41 - mmengine - WARNING - The "model_wrapper" registry in mmrazor did not set import location. Fallback to call `mmrazor.utils.register_all_modules` instead. 2023/04/13 17:27:47 - 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 (NORMAL ) SyncBuffersHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) VisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) VisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/04/13 17:27:47 - mmengine - WARNING - The "loop" registry in mmrazor did not set import location. Fallback to call `mmrazor.utils.register_all_modules` instead. 2023/04/13 17:27:55 - mmengine - WARNING - init_weights of ImageClassifier has been called more than once. Name of parameter - Initialization information architecture.backbone.conv1.weight - torch.Size([64, 3, 7, 7]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.0.conv1.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.0.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.0.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.0.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.0.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.1.conv1.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.1.bn1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.1.bn1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.1.bn2.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer1.1.bn2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.conv1.weight - torch.Size([128, 64, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.downsample.0.weight - torch.Size([128, 64, 1, 1]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.downsample.1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.0.downsample.1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.1.conv1.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.1.bn1.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.1.bn1.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.1.bn2.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer2.1.bn2.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.conv1.weight - torch.Size([256, 128, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.downsample.0.weight - torch.Size([256, 128, 1, 1]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.downsample.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.0.downsample.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.1.conv1.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.1.bn1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.1.bn1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.1.bn2.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer3.1.bn2.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.conv1.weight - torch.Size([512, 256, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.bn1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.bn1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.bn2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.bn2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.downsample.0.weight - torch.Size([512, 256, 1, 1]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.downsample.1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.0.downsample.1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.1.conv1.weight - torch.Size([512, 512, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.1.bn1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.1.bn1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.1.bn2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.backbone.layer4.1.bn2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.head.fc.weight - torch.Size([1000, 512]): The value is the same before and after calling `init_weights` of MMArchitectureQuant architecture.head.fc.bias - torch.Size([1000]): The value is the same before and after calling `init_weights` of MMArchitectureQuant 2023/04/13 17:27:55 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/04/13 17:27:55 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/04/13 17:27:55 - mmengine - INFO - Checkpoints will be saved to /nvme/caoweihan.p/projects/mmrazor/qat_r18_test. 2023/04/13 17:28:14 - mmengine - INFO - Epoch(train) [1][ 100/5005] lr: 3.3333e-05 eta: 2:36:18 time: 0.1855 data_time: 0.0075 memory: 1637 loss: 1.5115 2023/04/13 17:28:31 - mmengine - INFO - Epoch(train) [1][ 200/5005] lr: 3.3333e-05 eta: 2:29:37 time: 0.1641 data_time: 0.0074 memory: 1637 loss: 1.3895 2023/04/13 17:28:49 - mmengine - INFO - Epoch(train) [1][ 300/5005] lr: 3.3333e-05 eta: 2:28:25 time: 0.1733 data_time: 0.0073 memory: 1637 loss: 1.2250 2023/04/13 17:29:06 - mmengine - INFO - Epoch(train) [1][ 400/5005] lr: 3.3333e-05 eta: 2:26:35 time: 0.1577 data_time: 0.0077 memory: 1637 loss: 1.2913 2023/04/13 17:29:24 - mmengine - INFO - Epoch(train) [1][ 500/5005] lr: 3.3333e-05 eta: 2:26:24 time: 0.1747 data_time: 0.0076 memory: 1637 loss: 1.3106 2023/04/13 17:29:42 - mmengine - INFO - Epoch(train) [1][ 600/5005] lr: 3.3333e-05 eta: 2:27:35 time: 0.2000 data_time: 0.0079 memory: 1637 loss: 1.4104 2023/04/13 17:30:00 - mmengine - INFO - Epoch(train) [1][ 700/5005] lr: 3.3333e-05 eta: 2:26:27 time: 0.1654 data_time: 0.0082 memory: 1637 loss: 1.2439 2023/04/13 17:30:17 - mmengine - INFO - Epoch(train) [1][ 800/5005] lr: 3.3333e-05 eta: 2:25:48 time: 0.1725 data_time: 0.0073 memory: 1637 loss: 1.3777 2023/04/13 17:30:35 - mmengine - INFO - Epoch(train) [1][ 900/5005] lr: 3.3333e-05 eta: 2:25:36 time: 0.2025 data_time: 0.0080 memory: 1637 loss: 1.3352 2023/04/13 17:30:52 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 17:30:52 - mmengine - INFO - Epoch(train) [1][1000/5005] lr: 3.3333e-05 eta: 2:24:57 time: 0.1434 data_time: 0.0074 memory: 1637 loss: 1.2744 2023/04/13 17:31:14 - mmengine - INFO - Epoch(train) [1][1100/5005] lr: 3.3333e-05 eta: 2:27:42 time: 0.2129 data_time: 0.0077 memory: 1637 loss: 1.5348 2023/04/13 17:31:32 - mmengine - INFO - Epoch(train) [1][1200/5005] lr: 3.3333e-05 eta: 2:27:27 time: 0.2044 data_time: 0.0074 memory: 1637 loss: 1.3925 2023/04/13 17:31:50 - mmengine - INFO - Epoch(train) [1][1300/5005] lr: 3.3333e-05 eta: 2:26:36 time: 0.1633 data_time: 0.0080 memory: 1637 loss: 1.3044 2023/04/13 17:32:06 - mmengine - INFO - Epoch(train) [1][1400/5005] lr: 3.3333e-05 eta: 2:25:33 time: 0.1845 data_time: 0.0075 memory: 1637 loss: 1.4979 2023/04/13 17:32:24 - mmengine - INFO - Epoch(train) [1][1500/5005] lr: 3.3333e-05 eta: 2:25:12 time: 0.1788 data_time: 0.0075 memory: 1637 loss: 1.2620 2023/04/13 17:32:42 - mmengine - INFO - Epoch(train) [1][1600/5005] lr: 3.3333e-05 eta: 2:24:56 time: 0.1852 data_time: 0.0075 memory: 1637 loss: 1.1791 2023/04/13 17:33:00 - mmengine - INFO - Epoch(train) [1][1700/5005] lr: 3.3333e-05 eta: 2:24:19 time: 0.1603 data_time: 0.0076 memory: 1637 loss: 1.4786 2023/04/13 17:33:17 - mmengine - INFO - Epoch(train) [1][1800/5005] lr: 3.3333e-05 eta: 2:24:00 time: 0.1794 data_time: 0.0075 memory: 1637 loss: 1.3707 2023/04/13 17:33:35 - mmengine - INFO - Epoch(train) [1][1900/5005] lr: 3.3333e-05 eta: 2:23:25 time: 0.1902 data_time: 0.0075 memory: 1637 loss: 1.3765 2023/04/13 17:33:51 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 17:33:51 - mmengine - INFO - Epoch(train) [1][2000/5005] lr: 3.3333e-05 eta: 2:22:38 time: 0.1583 data_time: 0.0075 memory: 1637 loss: 1.4928 2023/04/13 17:34:09 - mmengine - INFO - Epoch(train) [1][2100/5005] lr: 3.3333e-05 eta: 2:22:14 time: 0.1922 data_time: 0.0183 memory: 1637 loss: 1.3240 2023/04/13 17:34:27 - mmengine - INFO - Epoch(train) [1][2200/5005] lr: 3.3333e-05 eta: 2:22:07 time: 0.1868 data_time: 0.0083 memory: 1637 loss: 1.2921 2023/04/13 17:34:45 - mmengine - INFO - Epoch(train) [1][2300/5005] lr: 3.3333e-05 eta: 2:21:44 time: 0.1666 data_time: 0.0074 memory: 1637 loss: 1.3112 2023/04/13 17:35:02 - mmengine - INFO - Epoch(train) [1][2400/5005] lr: 3.3333e-05 eta: 2:21:20 time: 0.1708 data_time: 0.0081 memory: 1637 loss: 1.3781 2023/04/13 17:35:20 - mmengine - INFO - Epoch(train) [1][2500/5005] lr: 3.3333e-05 eta: 2:20:54 time: 0.1619 data_time: 0.0075 memory: 1637 loss: 1.3538 2023/04/13 17:35:37 - mmengine - INFO - Epoch(train) [1][2600/5005] lr: 3.3333e-05 eta: 2:20:25 time: 0.1655 data_time: 0.0077 memory: 1637 loss: 1.4208 2023/04/13 17:35:54 - mmengine - INFO - Epoch(train) [1][2700/5005] lr: 3.3333e-05 eta: 2:20:07 time: 0.1859 data_time: 0.0076 memory: 1637 loss: 1.4353 2023/04/13 17:36:18 - mmengine - INFO - Epoch(train) [1][2800/5005] lr: 3.3333e-05 eta: 2:21:33 time: 0.2097 data_time: 0.0076 memory: 1637 loss: 1.2605 2023/04/13 17:36:56 - mmengine - INFO - Epoch(train) [1][2900/5005] lr: 3.3333e-05 eta: 2:26:34 time: 0.5742 data_time: 0.0077 memory: 1637 loss: 1.3690 2023/04/13 17:37:52 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 17:37:52 - mmengine - INFO - Epoch(train) [1][3000/5005] lr: 3.3333e-05 eta: 2:35:54 time: 0.5559 data_time: 0.0080 memory: 1637 loss: 1.4776 2023/04/13 17:38:47 - mmengine - INFO - Epoch(train) [1][3100/5005] lr: 3.3333e-05 eta: 2:44:37 time: 0.5740 data_time: 0.0076 memory: 1637 loss: 1.2890 2023/04/13 17:39:47 - mmengine - INFO - Epoch(train) [1][3200/5005] lr: 3.3333e-05 eta: 2:53:42 time: 0.5273 data_time: 0.0082 memory: 1637 loss: 1.5245 2023/04/13 17:40:43 - mmengine - INFO - Epoch(train) [1][3300/5005] lr: 3.3333e-05 eta: 3:01:22 time: 0.5823 data_time: 0.0075 memory: 1637 loss: 1.2314 2023/04/13 17:41:38 - mmengine - INFO - Epoch(train) [1][3400/5005] lr: 3.3333e-05 eta: 3:08:13 time: 0.5802 data_time: 0.0075 memory: 1637 loss: 1.3811 2023/04/13 17:42:34 - mmengine - INFO - Epoch(train) [1][3500/5005] lr: 3.3333e-05 eta: 3:14:49 time: 0.5309 data_time: 0.0080 memory: 1637 loss: 1.4471 2023/04/13 17:43:31 - mmengine - INFO - Epoch(train) [1][3600/5005] lr: 3.3333e-05 eta: 3:21:16 time: 0.5907 data_time: 0.0081 memory: 1637 loss: 1.3128 2023/04/13 17:44:29 - mmengine - INFO - Epoch(train) [1][3700/5005] lr: 3.3333e-05 eta: 3:27:26 time: 0.5815 data_time: 0.0074 memory: 1637 loss: 1.4412 2023/04/13 17:45:25 - mmengine - INFO - Epoch(train) [1][3800/5005] lr: 3.3333e-05 eta: 3:32:53 time: 0.5699 data_time: 0.0190 memory: 1637 loss: 1.3372 2023/04/13 17:46:21 - mmengine - INFO - Epoch(train) [1][3900/5005] lr: 3.3333e-05 eta: 3:38:12 time: 0.6116 data_time: 0.0079 memory: 1637 loss: 1.2346 2023/04/13 17:47:17 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 17:47:17 - mmengine - INFO - Epoch(train) [1][4000/5005] lr: 3.3333e-05 eta: 3:43:01 time: 0.5378 data_time: 0.0079 memory: 1637 loss: 1.3941 2023/04/13 17:48:14 - mmengine - INFO - Epoch(train) [1][4100/5005] lr: 3.3333e-05 eta: 3:47:38 time: 0.5477 data_time: 0.0075 memory: 1637 loss: 1.5608 2023/04/13 17:49:14 - mmengine - INFO - Epoch(train) [1][4200/5005] lr: 3.3333e-05 eta: 3:52:38 time: 0.6003 data_time: 0.0077 memory: 1637 loss: 1.4346 2023/04/13 17:50:08 - mmengine - INFO - Epoch(train) [1][4300/5005] lr: 3.3333e-05 eta: 3:56:24 time: 0.5237 data_time: 0.0079 memory: 1637 loss: 1.4684 2023/04/13 17:51:06 - mmengine - INFO - Epoch(train) [1][4400/5005] lr: 3.3333e-05 eta: 4:00:29 time: 0.5519 data_time: 0.0075 memory: 1637 loss: 1.3708 2023/04/13 17:52:01 - mmengine - INFO - Epoch(train) [1][4500/5005] lr: 3.3333e-05 eta: 4:03:54 time: 0.5272 data_time: 0.0085 memory: 1637 loss: 1.4103 2023/04/13 17:52:56 - mmengine - INFO - Epoch(train) [1][4600/5005] lr: 3.3333e-05 eta: 4:07:12 time: 0.5436 data_time: 0.0074 memory: 1637 loss: 1.4235 2023/04/13 17:53:52 - mmengine - INFO - Epoch(train) [1][4700/5005] lr: 3.3333e-05 eta: 4:10:26 time: 0.5230 data_time: 0.0080 memory: 1637 loss: 1.4453 2023/04/13 17:54:49 - mmengine - INFO - Epoch(train) [1][4800/5005] lr: 3.3333e-05 eta: 4:13:33 time: 0.5175 data_time: 0.0075 memory: 1637 loss: 1.5433 2023/04/13 17:55:45 - mmengine - INFO - Epoch(train) [1][4900/5005] lr: 3.3333e-05 eta: 4:16:28 time: 0.6325 data_time: 0.0079 memory: 1637 loss: 1.2871 2023/04/13 17:56:42 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 17:56:42 - mmengine - INFO - Epoch(train) [1][5000/5005] lr: 3.3333e-05 eta: 4:19:18 time: 0.5992 data_time: 0.0085 memory: 1637 loss: 1.4284 2023/04/13 17:56:45 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 17:56:45 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/04/13 17:57:09 - mmengine - INFO - Epoch(val) [1][100/196] eta: 0:00:21 time: 0.2128 data_time: 0.0073 memory: 1637 2023/04/13 17:58:55 - mmengine - INFO - Epoch(val) [1][196/196] qat.accuracy/top1: 69.8800 qat.accuracy/top5: 89.4080data_time: 0.0210 time: 0.3805 2023/04/13 17:58:59 - mmengine - INFO - Epoch(val) [1][100/196] eta: 0:00:04 time: 0.0305 data_time: 0.0135 memory: 967 2023/04/13 17:59:55 - mmengine - INFO - Epoch(val) [1][196/196] original.accuracy/top1: 69.9600 original.accuracy/top5: 89.4360data_time: 0.0118 time: 0.0285 2023/04/13 18:00:53 - mmengine - INFO - Epoch(train) [2][ 100/5005] lr: 3.3333e-05 eta: 4:22:16 time: 0.5808 data_time: 0.0080 memory: 1637 loss: 1.2780 2023/04/13 18:01:51 - mmengine - INFO - Epoch(train) [2][ 200/5005] lr: 3.3333e-05 eta: 4:25:01 time: 0.5857 data_time: 0.0084 memory: 1637 loss: 1.3331 2023/04/13 18:02:49 - mmengine - INFO - Epoch(train) [2][ 300/5005] lr: 3.3333e-05 eta: 4:27:35 time: 0.5643 data_time: 0.0083 memory: 1637 loss: 1.1708 2023/04/13 18:03:49 - mmengine - INFO - Epoch(train) [2][ 400/5005] lr: 3.3333e-05 eta: 4:30:18 time: 0.5509 data_time: 0.0087 memory: 1637 loss: 1.4642 2023/04/13 18:04:48 - mmengine - INFO - Epoch(train) [2][ 500/5005] lr: 3.3333e-05 eta: 4:32:40 time: 0.5670 data_time: 0.0088 memory: 1637 loss: 1.4278 2023/04/13 18:05:45 - mmengine - INFO - Epoch(train) [2][ 600/5005] lr: 3.3333e-05 eta: 4:34:49 time: 0.5907 data_time: 0.0087 memory: 1637 loss: 1.5120 2023/04/13 18:06:42 - mmengine - INFO - Epoch(train) [2][ 700/5005] lr: 3.3333e-05 eta: 4:36:46 time: 0.5445 data_time: 0.0084 memory: 1637 loss: 1.3378 2023/04/13 18:07:42 - mmengine - INFO - Epoch(train) [2][ 800/5005] lr: 3.3333e-05 eta: 4:38:58 time: 0.5684 data_time: 0.0082 memory: 1637 loss: 1.5098 2023/04/13 18:08:43 - mmengine - INFO - Epoch(train) [2][ 900/5005] lr: 3.3333e-05 eta: 4:41:11 time: 0.5349 data_time: 0.0084 memory: 1637 loss: 1.4845 2023/04/13 18:09:39 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 18:09:42 - mmengine - INFO - Epoch(train) [2][1000/5005] lr: 3.3333e-05 eta: 4:43:06 time: 0.6063 data_time: 0.0085 memory: 1637 loss: 1.3233 2023/04/13 18:10:39 - mmengine - INFO - Epoch(train) [2][1100/5005] lr: 3.3333e-05 eta: 4:44:41 time: 0.5895 data_time: 0.0086 memory: 1637 loss: 1.2646 2023/04/13 18:11:38 - mmengine - INFO - Epoch(train) [2][1200/5005] lr: 3.3333e-05 eta: 4:46:24 time: 0.5823 data_time: 0.0084 memory: 1637 loss: 1.4524 2023/04/13 18:12:36 - mmengine - INFO - Epoch(train) [2][1300/5005] lr: 3.3333e-05 eta: 4:47:57 time: 0.5599 data_time: 0.0079 memory: 1637 loss: 1.3431 2023/04/13 18:13:34 - mmengine - INFO - Epoch(train) [2][1400/5005] lr: 3.3333e-05 eta: 4:49:25 time: 0.6078 data_time: 0.0080 memory: 1637 loss: 1.4173 2023/04/13 18:14:32 - mmengine - INFO - Epoch(train) [2][1500/5005] lr: 3.3333e-05 eta: 4:50:46 time: 0.6342 data_time: 0.0090 memory: 1637 loss: 1.3218 2023/04/13 18:15:31 - mmengine - INFO - Epoch(train) [2][1600/5005] lr: 3.3333e-05 eta: 4:52:09 time: 0.6015 data_time: 0.0081 memory: 1637 loss: 1.2594 2023/04/13 18:16:29 - mmengine - INFO - Epoch(train) [2][1700/5005] lr: 3.3333e-05 eta: 4:53:23 time: 0.5571 data_time: 0.0083 memory: 1637 loss: 1.4946 2023/04/13 18:17:27 - mmengine - INFO - Epoch(train) [2][1800/5005] lr: 3.3333e-05 eta: 4:54:33 time: 0.5965 data_time: 0.0198 memory: 1637 loss: 1.3985 2023/04/13 18:18:29 - mmengine - INFO - Epoch(train) [2][1900/5005] lr: 3.3333e-05 eta: 4:56:01 time: 0.6021 data_time: 0.0082 memory: 1637 loss: 1.3551 2023/04/13 18:19:24 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 18:19:28 - mmengine - INFO - Epoch(train) [2][2000/5005] lr: 3.3333e-05 eta: 4:57:11 time: 0.6418 data_time: 0.0094 memory: 1637 loss: 1.2063 2023/04/13 18:20:26 - mmengine - INFO - Epoch(train) [2][2100/5005] lr: 3.3333e-05 eta: 4:58:11 time: 0.5621 data_time: 0.0082 memory: 1637 loss: 1.3649 2023/04/13 18:21:24 - mmengine - INFO - Epoch(train) [2][2200/5005] lr: 3.3333e-05 eta: 4:59:05 time: 0.5782 data_time: 0.0085 memory: 1637 loss: 1.3944 2023/04/13 18:22:23 - mmengine - INFO - Epoch(train) [2][2300/5005] lr: 3.3333e-05 eta: 5:00:06 time: 0.6007 data_time: 0.0092 memory: 1637 loss: 1.4232 2023/04/13 18:23:23 - mmengine - INFO - Epoch(train) [2][2400/5005] lr: 3.3333e-05 eta: 5:01:04 time: 0.5753 data_time: 0.0088 memory: 1637 loss: 1.2637 2023/04/13 18:24:22 - mmengine - INFO - Epoch(train) [2][2500/5005] lr: 3.3333e-05 eta: 5:01:58 time: 0.6055 data_time: 0.0085 memory: 1637 loss: 1.3317 2023/04/13 18:25:21 - mmengine - INFO - Epoch(train) [2][2600/5005] lr: 3.3333e-05 eta: 5:02:48 time: 0.6197 data_time: 0.0091 memory: 1637 loss: 1.4452 2023/04/13 18:26:20 - mmengine - INFO - Epoch(train) [2][2700/5005] lr: 3.3333e-05 eta: 5:03:34 time: 0.6055 data_time: 0.0100 memory: 1637 loss: 1.3987 2023/04/13 18:27:19 - mmengine - INFO - Epoch(train) [2][2800/5005] lr: 3.3333e-05 eta: 5:04:18 time: 0.5616 data_time: 0.0087 memory: 1637 loss: 1.3590 2023/04/13 18:28:22 - mmengine - INFO - Epoch(train) [2][2900/5005] lr: 3.3333e-05 eta: 5:05:19 time: 0.5553 data_time: 0.0086 memory: 1637 loss: 1.3520 2023/04/13 18:29:17 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 18:29:21 - mmengine - INFO - Epoch(train) [2][3000/5005] lr: 3.3333e-05 eta: 5:05:54 time: 0.5992 data_time: 0.0096 memory: 1637 loss: 1.2759 2023/04/13 18:30:18 - mmengine - INFO - Epoch(train) [2][3100/5005] lr: 3.3333e-05 eta: 5:06:23 time: 0.5684 data_time: 0.0086 memory: 1637 loss: 1.3786 2023/04/13 18:31:16 - mmengine - INFO - Epoch(train) [2][3200/5005] lr: 3.3333e-05 eta: 5:06:49 time: 0.5976 data_time: 0.0085 memory: 1637 loss: 1.3129 2023/04/13 18:32:15 - mmengine - INFO - Epoch(train) [2][3300/5005] lr: 3.3333e-05 eta: 5:07:21 time: 0.6311 data_time: 0.0084 memory: 1637 loss: 1.3176 2023/04/13 18:33:14 - mmengine - INFO - Epoch(train) [2][3400/5005] lr: 3.3333e-05 eta: 5:07:50 time: 0.5720 data_time: 0.0087 memory: 1637 loss: 1.2559 2023/04/13 18:34:13 - mmengine - INFO - Epoch(train) [2][3500/5005] lr: 3.3333e-05 eta: 5:08:16 time: 0.5898 data_time: 0.0087 memory: 1637 loss: 1.4886 2023/04/13 18:35:11 - mmengine - INFO - Epoch(train) [2][3600/5005] lr: 3.3333e-05 eta: 5:08:40 time: 0.5655 data_time: 0.0088 memory: 1637 loss: 1.3686 2023/04/13 18:36:10 - mmengine - INFO - Epoch(train) [2][3700/5005] lr: 3.3333e-05 eta: 5:09:02 time: 0.5955 data_time: 0.0084 memory: 1637 loss: 1.3852 2023/04/13 18:37:07 - mmengine - INFO - Epoch(train) [2][3800/5005] lr: 3.3333e-05 eta: 5:09:15 time: 0.5492 data_time: 0.0134 memory: 1637 loss: 1.3350 2023/04/13 18:38:10 - mmengine - INFO - Epoch(train) [2][3900/5005] lr: 3.3333e-05 eta: 5:09:52 time: 0.6243 data_time: 0.0085 memory: 1637 loss: 1.4470 2023/04/13 18:39:07 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 18:39:10 - mmengine - INFO - Epoch(train) [2][4000/5005] lr: 3.3333e-05 eta: 5:10:15 time: 0.5861 data_time: 0.0092 memory: 1637 loss: 1.2542 2023/04/13 18:40:11 - mmengine - INFO - Epoch(train) [2][4100/5005] lr: 3.3333e-05 eta: 5:10:37 time: 0.6319 data_time: 0.0092 memory: 1637 loss: 1.3358 2023/04/13 18:41:14 - mmengine - INFO - Epoch(train) [2][4200/5005] lr: 3.3333e-05 eta: 5:11:10 time: 0.6355 data_time: 0.0090 memory: 1637 loss: 1.4463 2023/04/13 18:42:15 - mmengine - INFO - Epoch(train) [2][4300/5005] lr: 3.3333e-05 eta: 5:11:33 time: 0.6053 data_time: 0.0105 memory: 1637 loss: 1.3103 2023/04/13 18:43:17 - mmengine - INFO - Epoch(train) [2][4400/5005] lr: 3.3333e-05 eta: 5:11:57 time: 0.6192 data_time: 0.0112 memory: 1637 loss: 1.5930 2023/04/13 18:44:19 - mmengine - INFO - Epoch(train) [2][4500/5005] lr: 3.3333e-05 eta: 5:12:18 time: 0.6118 data_time: 0.0112 memory: 1637 loss: 1.4088 2023/04/13 18:45:22 - mmengine - INFO - Epoch(train) [2][4600/5005] lr: 3.3333e-05 eta: 5:12:41 time: 0.5880 data_time: 0.0111 memory: 1637 loss: 1.4433 2023/04/13 18:46:23 - mmengine - INFO - Epoch(train) [2][4700/5005] lr: 3.3333e-05 eta: 5:12:58 time: 0.6306 data_time: 0.0119 memory: 1637 loss: 1.3118 2023/04/13 18:47:24 - mmengine - INFO - Epoch(train) [2][4800/5005] lr: 3.3333e-05 eta: 5:13:11 time: 0.6380 data_time: 0.0114 memory: 1637 loss: 1.4441 2023/04/13 18:48:23 - mmengine - INFO - Epoch(train) [2][4900/5005] lr: 3.3333e-05 eta: 5:13:13 time: 0.4092 data_time: 0.0125 memory: 1637 loss: 1.4982 2023/04/13 18:49:03 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 18:49:05 - mmengine - INFO - Epoch(train) [2][5000/5005] lr: 3.3333e-05 eta: 5:12:07 time: 0.4383 data_time: 0.0121 memory: 1637 loss: 1.5112 2023/04/13 18:49:08 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 18:49:09 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/04/13 18:49:28 - mmengine - INFO - Epoch(val) [2][100/196] eta: 0:00:15 time: 0.1461 data_time: 0.0095 memory: 1637 2023/04/13 18:51:32 - mmengine - INFO - Epoch(val) [2][196/196] qat.accuracy/top1: 69.8500 qat.accuracy/top5: 89.3840data_time: 0.0103 time: 0.1489 2023/04/13 18:51:37 - mmengine - INFO - Epoch(val) [2][100/196] eta: 0:00:04 time: 0.0495 data_time: 0.0314 memory: 967 2023/04/13 18:52:38 - mmengine - INFO - Epoch(val) [2][196/196] original.accuracy/top1: 69.9260 original.accuracy/top5: 89.4280data_time: 0.0230 time: 0.0386 2023/04/13 18:53:38 - mmengine - INFO - Epoch(train) [3][ 100/5005] lr: 3.3333e-05 eta: 5:12:14 time: 0.6244 data_time: 0.0124 memory: 1637 loss: 1.3390 2023/04/13 18:54:40 - mmengine - INFO - Epoch(train) [3][ 200/5005] lr: 3.3333e-05 eta: 5:12:26 time: 0.6880 data_time: 0.0110 memory: 1637 loss: 1.5801 2023/04/13 18:55:42 - mmengine - INFO - Epoch(train) [3][ 300/5005] lr: 3.3333e-05 eta: 5:12:35 time: 0.6264 data_time: 0.0107 memory: 1637 loss: 1.2049 2023/04/13 18:56:43 - mmengine - INFO - Epoch(train) [3][ 400/5005] lr: 3.3333e-05 eta: 5:12:41 time: 0.6431 data_time: 0.0115 memory: 1637 loss: 1.3054 2023/04/13 18:57:43 - mmengine - INFO - Epoch(train) [3][ 500/5005] lr: 3.3333e-05 eta: 5:12:41 time: 0.5786 data_time: 0.0119 memory: 1637 loss: 1.3590 2023/04/13 18:58:46 - mmengine - INFO - Epoch(train) [3][ 600/5005] lr: 3.3333e-05 eta: 5:12:54 time: 0.6442 data_time: 0.0105 memory: 1637 loss: 1.5198 2023/04/13 18:59:47 - mmengine - INFO - Epoch(train) [3][ 700/5005] lr: 3.3333e-05 eta: 5:12:56 time: 0.5956 data_time: 0.0115 memory: 1637 loss: 1.2808 2023/04/13 19:00:49 - mmengine - INFO - Epoch(train) [3][ 800/5005] lr: 3.3333e-05 eta: 5:12:59 time: 0.6107 data_time: 0.0116 memory: 1637 loss: 1.4779 2023/04/13 19:01:49 - mmengine - INFO - Epoch(train) [3][ 900/5005] lr: 3.3333e-05 eta: 5:12:54 time: 0.6026 data_time: 0.0109 memory: 1637 loss: 1.4987 2023/04/13 19:02:44 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:02:50 - mmengine - INFO - Epoch(train) [3][1000/5005] lr: 3.3333e-05 eta: 5:12:53 time: 0.6261 data_time: 0.0103 memory: 1637 loss: 1.2484 2023/04/13 19:03:50 - mmengine - INFO - Epoch(train) [3][1100/5005] lr: 3.3333e-05 eta: 5:12:47 time: 0.5879 data_time: 0.0129 memory: 1637 loss: 1.3587 2023/04/13 19:04:51 - mmengine - INFO - Epoch(train) [3][1200/5005] lr: 3.3333e-05 eta: 5:12:43 time: 0.6370 data_time: 0.0114 memory: 1637 loss: 1.3389 2023/04/13 19:05:55 - mmengine - INFO - Epoch(train) [3][1300/5005] lr: 3.3333e-05 eta: 5:12:48 time: 0.6420 data_time: 0.0119 memory: 1637 loss: 1.3850 2023/04/13 19:06:57 - mmengine - INFO - Epoch(train) [3][1400/5005] lr: 3.3333e-05 eta: 5:12:45 time: 0.5810 data_time: 0.0117 memory: 1637 loss: 1.4197 2023/04/13 19:08:00 - mmengine - INFO - Epoch(train) [3][1500/5005] lr: 3.3333e-05 eta: 5:12:44 time: 0.6002 data_time: 0.0098 memory: 1637 loss: 1.4212 2023/04/13 19:09:04 - mmengine - INFO - Epoch(train) [3][1600/5005] lr: 3.3333e-05 eta: 5:12:48 time: 0.6610 data_time: 0.0103 memory: 1637 loss: 1.2536 2023/04/13 19:10:06 - mmengine - INFO - Epoch(train) [3][1700/5005] lr: 3.3333e-05 eta: 5:12:42 time: 0.6229 data_time: 0.0110 memory: 1637 loss: 1.3611 2023/04/13 19:11:07 - mmengine - INFO - Epoch(train) [3][1800/5005] lr: 3.3333e-05 eta: 5:12:33 time: 0.5715 data_time: 0.0113 memory: 1637 loss: 1.2924 2023/04/13 19:12:08 - mmengine - INFO - Epoch(train) [3][1900/5005] lr: 3.3333e-05 eta: 5:12:19 time: 0.5791 data_time: 0.0104 memory: 1637 loss: 1.2983 2023/04/13 19:13:01 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:13:06 - mmengine - INFO - Epoch(train) [3][2000/5005] lr: 3.3333e-05 eta: 5:12:00 time: 0.5730 data_time: 0.0110 memory: 1637 loss: 1.2093 2023/04/13 19:14:07 - mmengine - INFO - Epoch(train) [3][2100/5005] lr: 3.3333e-05 eta: 5:11:46 time: 0.5981 data_time: 0.0109 memory: 1637 loss: 1.4600 2023/04/13 19:15:07 - mmengine - INFO - Epoch(train) [3][2200/5005] lr: 3.3333e-05 eta: 5:11:30 time: 0.6179 data_time: 0.0115 memory: 1637 loss: 1.5385 2023/04/13 19:16:08 - mmengine - INFO - Epoch(train) [3][2300/5005] lr: 3.3333e-05 eta: 5:11:16 time: 0.6109 data_time: 0.0115 memory: 1637 loss: 1.4044 2023/04/13 19:17:08 - mmengine - INFO - Epoch(train) [3][2400/5005] lr: 3.3333e-05 eta: 5:11:00 time: 0.5848 data_time: 0.0115 memory: 1637 loss: 1.3907 2023/04/13 19:18:08 - mmengine - INFO - Epoch(train) [3][2500/5005] lr: 3.3333e-05 eta: 5:10:42 time: 0.6228 data_time: 0.0112 memory: 1637 loss: 1.4399 2023/04/13 19:19:11 - mmengine - INFO - Epoch(train) [3][2600/5005] lr: 3.3333e-05 eta: 5:10:31 time: 0.9002 data_time: 0.0085 memory: 1637 loss: 1.2886 2023/04/13 19:20:13 - mmengine - INFO - Epoch(train) [3][2700/5005] lr: 3.3333e-05 eta: 5:10:17 time: 0.5773 data_time: 0.0106 memory: 1637 loss: 1.4824 2023/04/13 19:21:14 - mmengine - INFO - Epoch(train) [3][2800/5005] lr: 3.3333e-05 eta: 5:10:01 time: 0.6063 data_time: 0.0121 memory: 1637 loss: 1.3133 2023/04/13 19:22:14 - mmengine - INFO - Epoch(train) [3][2900/5005] lr: 3.3333e-05 eta: 5:09:38 time: 0.6271 data_time: 0.0113 memory: 1637 loss: 1.3042 2023/04/13 19:23:07 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:23:13 - mmengine - INFO - Epoch(train) [3][3000/5005] lr: 3.3333e-05 eta: 5:09:14 time: 0.6029 data_time: 0.0116 memory: 1637 loss: 1.4885 2023/04/13 19:24:13 - mmengine - INFO - Epoch(train) [3][3100/5005] lr: 3.3333e-05 eta: 5:08:53 time: 0.6162 data_time: 0.0115 memory: 1637 loss: 1.3986 2023/04/13 19:25:14 - mmengine - INFO - Epoch(train) [3][3200/5005] lr: 3.3333e-05 eta: 5:08:32 time: 0.5944 data_time: 0.0113 memory: 1637 loss: 1.3616 2023/04/13 19:26:15 - mmengine - INFO - Epoch(train) [3][3300/5005] lr: 3.3333e-05 eta: 5:08:12 time: 0.6673 data_time: 0.0254 memory: 1637 loss: 1.3224 2023/04/13 19:27:15 - mmengine - INFO - Epoch(train) [3][3400/5005] lr: 3.3333e-05 eta: 5:07:47 time: 0.5582 data_time: 0.0113 memory: 1637 loss: 1.2717 2023/04/13 19:28:14 - mmengine - INFO - Epoch(train) [3][3500/5005] lr: 3.3333e-05 eta: 5:07:21 time: 0.5899 data_time: 0.0129 memory: 1637 loss: 1.4295 2023/04/13 19:29:15 - mmengine - INFO - Epoch(train) [3][3600/5005] lr: 3.3333e-05 eta: 5:06:57 time: 0.5395 data_time: 0.0137 memory: 1637 loss: 1.1998 2023/04/13 19:30:19 - mmengine - INFO - Epoch(train) [3][3700/5005] lr: 3.3333e-05 eta: 5:06:44 time: 0.6673 data_time: 0.0115 memory: 1637 loss: 1.1916 2023/04/13 19:31:19 - mmengine - INFO - Epoch(train) [3][3800/5005] lr: 3.3333e-05 eta: 5:06:17 time: 0.5938 data_time: 0.0103 memory: 1637 loss: 1.6045 2023/04/13 19:32:19 - mmengine - INFO - Epoch(train) [3][3900/5005] lr: 3.3333e-05 eta: 5:05:51 time: 0.6039 data_time: 0.0101 memory: 1637 loss: 1.2940 2023/04/13 19:33:13 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:33:19 - mmengine - INFO - Epoch(train) [3][4000/5005] lr: 3.3333e-05 eta: 5:05:23 time: 0.5769 data_time: 0.0109 memory: 1637 loss: 1.2721 2023/04/13 19:34:19 - mmengine - INFO - Epoch(train) [3][4100/5005] lr: 3.3333e-05 eta: 5:04:56 time: 0.5865 data_time: 0.0106 memory: 1637 loss: 1.2634 2023/04/13 19:35:19 - mmengine - INFO - Epoch(train) [3][4200/5005] lr: 3.3333e-05 eta: 5:04:27 time: 0.5611 data_time: 0.0118 memory: 1637 loss: 1.2065 2023/04/13 19:36:18 - mmengine - INFO - Epoch(train) [3][4300/5005] lr: 3.3333e-05 eta: 5:03:57 time: 0.5717 data_time: 0.0115 memory: 1637 loss: 1.3805 2023/04/13 19:37:18 - mmengine - INFO - Epoch(train) [3][4400/5005] lr: 3.3333e-05 eta: 5:03:27 time: 0.5834 data_time: 0.0128 memory: 1637 loss: 1.2775 2023/04/13 19:38:18 - mmengine - INFO - Epoch(train) [3][4500/5005] lr: 3.3333e-05 eta: 5:03:00 time: 0.6166 data_time: 0.0110 memory: 1637 loss: 1.4458 2023/04/13 19:39:18 - mmengine - INFO - Epoch(train) [3][4600/5005] lr: 3.3333e-05 eta: 5:02:30 time: 0.6108 data_time: 0.0115 memory: 1637 loss: 1.6431 2023/04/13 19:40:21 - mmengine - INFO - Epoch(train) [3][4700/5005] lr: 3.3333e-05 eta: 5:02:06 time: 0.6431 data_time: 0.0115 memory: 1637 loss: 1.4289 2023/04/13 19:41:23 - mmengine - INFO - Epoch(train) [3][4800/5005] lr: 3.3333e-05 eta: 5:01:40 time: 0.6072 data_time: 0.0105 memory: 1637 loss: 1.3556 2023/04/13 19:42:23 - mmengine - INFO - Epoch(train) [3][4900/5005] lr: 3.3333e-05 eta: 5:01:09 time: 0.5938 data_time: 0.0106 memory: 1637 loss: 1.4599 2023/04/13 19:43:19 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:43:24 - mmengine - INFO - Epoch(train) [3][5000/5005] lr: 3.3333e-05 eta: 5:00:40 time: 0.5495 data_time: 0.0132 memory: 1637 loss: 1.2725 2023/04/13 19:43:27 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:43:28 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/04/13 19:43:54 - mmengine - INFO - Epoch(val) [3][100/196] eta: 0:00:23 time: 0.2358 data_time: 0.0114 memory: 1637 2023/04/13 19:45:13 - mmengine - INFO - Epoch(val) [3][196/196] qat.accuracy/top1: 69.9320 qat.accuracy/top5: 89.4100data_time: 0.0073 time: 0.4601 2023/04/13 19:45:17 - mmengine - INFO - Epoch(val) [3][100/196] eta: 0:00:04 time: 0.0340 data_time: 0.0158 memory: 967 2023/04/13 19:46:15 - mmengine - INFO - Epoch(val) [3][196/196] original.accuracy/top1: 70.0100 original.accuracy/top5: 89.4580data_time: 0.0194 time: 0.0373 2023/04/13 19:47:17 - mmengine - INFO - Epoch(train) [4][ 100/5005] lr: 3.3333e-05 eta: 5:00:12 time: 0.6029 data_time: 0.0100 memory: 1637 loss: 1.4075 2023/04/13 19:48:16 - mmengine - INFO - Epoch(train) [4][ 200/5005] lr: 3.3333e-05 eta: 4:59:37 time: 0.5871 data_time: 0.0115 memory: 1637 loss: 1.3971 2023/04/13 19:49:15 - mmengine - INFO - Epoch(train) [4][ 300/5005] lr: 3.3333e-05 eta: 4:59:01 time: 0.5974 data_time: 0.0116 memory: 1637 loss: 1.3483 2023/04/13 19:50:16 - mmengine - INFO - Epoch(train) [4][ 400/5005] lr: 3.3333e-05 eta: 4:58:30 time: 0.8721 data_time: 0.0090 memory: 1637 loss: 1.4130 2023/04/13 19:51:14 - mmengine - INFO - Epoch(train) [4][ 500/5005] lr: 3.3333e-05 eta: 4:57:53 time: 0.5758 data_time: 0.0113 memory: 1637 loss: 1.4996 2023/04/13 19:52:14 - mmengine - INFO - Epoch(train) [4][ 600/5005] lr: 3.3333e-05 eta: 4:57:20 time: 0.6203 data_time: 0.0108 memory: 1637 loss: 1.2211 2023/04/13 19:53:13 - mmengine - INFO - Epoch(train) [4][ 700/5005] lr: 3.3333e-05 eta: 4:56:44 time: 0.5801 data_time: 0.0112 memory: 1637 loss: 1.4964 2023/04/13 19:54:12 - mmengine - INFO - Epoch(train) [4][ 800/5005] lr: 3.3333e-05 eta: 4:56:06 time: 0.6180 data_time: 0.0101 memory: 1637 loss: 1.1571 2023/04/13 19:55:10 - mmengine - INFO - Epoch(train) [4][ 900/5005] lr: 3.3333e-05 eta: 4:55:29 time: 0.5798 data_time: 0.0118 memory: 1637 loss: 1.5278 2023/04/13 19:56:00 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 19:56:09 - mmengine - INFO - Epoch(train) [4][1000/5005] lr: 3.3333e-05 eta: 4:54:52 time: 0.6140 data_time: 0.0111 memory: 1637 loss: 1.4365 2023/04/13 19:57:09 - mmengine - INFO - Epoch(train) [4][1100/5005] lr: 3.3333e-05 eta: 4:54:16 time: 0.5731 data_time: 0.0119 memory: 1637 loss: 1.5457 2023/04/13 19:58:08 - mmengine - INFO - Epoch(train) [4][1200/5005] lr: 3.3333e-05 eta: 4:53:38 time: 0.6025 data_time: 0.0111 memory: 1637 loss: 1.3866 2023/04/13 19:59:07 - mmengine - INFO - Epoch(train) [4][1300/5005] lr: 3.3333e-05 eta: 4:53:01 time: 0.6033 data_time: 0.0126 memory: 1637 loss: 1.3209 2023/04/13 20:00:07 - mmengine - INFO - Epoch(train) [4][1400/5005] lr: 3.3333e-05 eta: 4:52:26 time: 0.5993 data_time: 0.0123 memory: 1637 loss: 1.4063 2023/04/13 20:01:10 - mmengine - INFO - Epoch(train) [4][1500/5005] lr: 3.3333e-05 eta: 4:51:55 time: 0.6208 data_time: 0.0123 memory: 1637 loss: 1.3518 2023/04/13 20:02:11 - mmengine - INFO - Epoch(train) [4][1600/5005] lr: 3.3333e-05 eta: 4:51:20 time: 0.6194 data_time: 0.0109 memory: 1637 loss: 1.5684 2023/04/13 20:03:14 - mmengine - INFO - Epoch(train) [4][1700/5005] lr: 3.3333e-05 eta: 4:50:49 time: 0.5842 data_time: 0.0103 memory: 1637 loss: 1.3509 2023/04/13 20:04:16 - mmengine - INFO - Epoch(train) [4][1800/5005] lr: 3.3333e-05 eta: 4:50:16 time: 0.5989 data_time: 0.0103 memory: 1637 loss: 1.4565 2023/04/13 20:05:17 - mmengine - INFO - Epoch(train) [4][1900/5005] lr: 3.3333e-05 eta: 4:49:41 time: 0.6185 data_time: 0.0102 memory: 1637 loss: 1.2570 2023/04/13 20:06:09 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:06:18 - mmengine - INFO - Epoch(train) [4][2000/5005] lr: 3.3333e-05 eta: 4:49:05 time: 0.6040 data_time: 0.0123 memory: 1637 loss: 1.3549 2023/04/13 20:07:18 - mmengine - INFO - Epoch(train) [4][2100/5005] lr: 3.3333e-05 eta: 4:48:27 time: 0.5803 data_time: 0.0104 memory: 1637 loss: 1.2294 2023/04/13 20:08:00 - mmengine - INFO - Epoch(train) [4][2200/5005] lr: 3.3333e-05 eta: 4:47:14 time: 0.4099 data_time: 0.0111 memory: 1637 loss: 1.3178 2023/04/13 20:09:11 - mmengine - INFO - Epoch(train) [4][2300/5005] lr: 3.3333e-05 eta: 4:46:57 time: 1.4445 data_time: 0.0108 memory: 1637 loss: 1.6544 2023/04/13 20:10:23 - mmengine - INFO - Epoch(train) [4][2400/5005] lr: 3.3333e-05 eta: 4:46:40 time: 0.7187 data_time: 0.0111 memory: 1637 loss: 1.2387 2023/04/13 20:11:27 - mmengine - INFO - Epoch(train) [4][2500/5005] lr: 3.3333e-05 eta: 4:46:08 time: 0.6453 data_time: 0.0113 memory: 1637 loss: 1.4950 2023/04/13 20:12:26 - mmengine - INFO - Epoch(train) [4][2600/5005] lr: 3.3333e-05 eta: 4:45:27 time: 0.5791 data_time: 0.0117 memory: 1637 loss: 1.3494 2023/04/13 20:13:29 - mmengine - INFO - Epoch(train) [4][2700/5005] lr: 3.3333e-05 eta: 4:44:52 time: 0.6071 data_time: 0.0115 memory: 1637 loss: 1.3631 2023/04/13 20:14:29 - mmengine - INFO - Epoch(train) [4][2800/5005] lr: 3.3333e-05 eta: 4:44:13 time: 0.6081 data_time: 0.0118 memory: 1637 loss: 1.1747 2023/04/13 20:15:31 - mmengine - INFO - Epoch(train) [4][2900/5005] lr: 3.3333e-05 eta: 4:43:36 time: 0.6290 data_time: 0.0107 memory: 1637 loss: 1.5007 2023/04/13 20:16:24 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:16:33 - mmengine - INFO - Epoch(train) [4][3000/5005] lr: 3.3333e-05 eta: 4:43:00 time: 0.6362 data_time: 0.0122 memory: 1637 loss: 1.2412 2023/04/13 20:17:36 - mmengine - INFO - Epoch(train) [4][3100/5005] lr: 3.3333e-05 eta: 4:42:23 time: 0.6511 data_time: 0.0119 memory: 1637 loss: 1.2770 2023/04/13 20:18:40 - mmengine - INFO - Epoch(train) [4][3200/5005] lr: 3.3333e-05 eta: 4:41:50 time: 0.6843 data_time: 0.0100 memory: 1637 loss: 1.4369 2023/04/13 20:19:42 - mmengine - INFO - Epoch(train) [4][3300/5005] lr: 3.3333e-05 eta: 4:41:12 time: 0.6267 data_time: 0.0129 memory: 1637 loss: 1.2792 2023/04/13 20:20:45 - mmengine - INFO - Epoch(train) [4][3400/5005] lr: 3.3333e-05 eta: 4:40:36 time: 0.6418 data_time: 0.0120 memory: 1637 loss: 1.3955 2023/04/13 20:21:49 - mmengine - INFO - Epoch(train) [4][3500/5005] lr: 3.3333e-05 eta: 4:40:01 time: 0.6503 data_time: 0.0126 memory: 1637 loss: 1.4983 2023/04/13 20:22:52 - mmengine - INFO - Epoch(train) [4][3600/5005] lr: 3.3333e-05 eta: 4:39:24 time: 0.6465 data_time: 0.0116 memory: 1637 loss: 1.2363 2023/04/13 20:23:55 - mmengine - INFO - Epoch(train) [4][3700/5005] lr: 3.3333e-05 eta: 4:38:47 time: 0.6273 data_time: 0.0117 memory: 1637 loss: 1.4264 2023/04/13 20:24:56 - mmengine - INFO - Epoch(train) [4][3800/5005] lr: 3.3333e-05 eta: 4:38:06 time: 0.6081 data_time: 0.0116 memory: 1637 loss: 1.2991 2023/04/13 20:25:57 - mmengine - INFO - Epoch(train) [4][3900/5005] lr: 3.3333e-05 eta: 4:37:25 time: 0.6052 data_time: 0.0114 memory: 1637 loss: 1.4983 2023/04/13 20:26:38 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:26:41 - mmengine - INFO - Epoch(train) [4][4000/5005] lr: 3.3333e-05 eta: 4:36:17 time: 0.2036 data_time: 0.0106 memory: 1637 loss: 1.3632 2023/04/13 20:27:01 - mmengine - INFO - Epoch(train) [4][4100/5005] lr: 3.3333e-05 eta: 4:34:29 time: 0.1906 data_time: 0.0099 memory: 1637 loss: 1.3519 2023/04/13 20:27:21 - mmengine - INFO - Epoch(train) [4][4200/5005] lr: 3.3333e-05 eta: 4:32:42 time: 0.2116 data_time: 0.0101 memory: 1637 loss: 1.2839 2023/04/13 20:27:41 - mmengine - INFO - Epoch(train) [4][4300/5005] lr: 3.3333e-05 eta: 4:30:56 time: 0.2160 data_time: 0.0103 memory: 1637 loss: 1.2386 2023/04/13 20:28:02 - mmengine - INFO - Epoch(train) [4][4400/5005] lr: 3.3333e-05 eta: 4:29:12 time: 0.2204 data_time: 0.0110 memory: 1637 loss: 1.3567 2023/04/13 20:28:28 - mmengine - INFO - Epoch(train) [4][4500/5005] lr: 3.3333e-05 eta: 4:27:39 time: 0.2179 data_time: 0.0104 memory: 1637 loss: 1.4523 2023/04/13 20:29:26 - mmengine - INFO - Epoch(train) [4][4600/5005] lr: 3.3333e-05 eta: 4:26:55 time: 0.5542 data_time: 0.0103 memory: 1637 loss: 1.3129 2023/04/13 20:30:25 - mmengine - INFO - Epoch(train) [4][4700/5005] lr: 3.3333e-05 eta: 4:26:12 time: 0.5576 data_time: 0.0102 memory: 1637 loss: 1.2865 2023/04/13 20:31:26 - mmengine - INFO - Epoch(train) [4][4800/5005] lr: 3.3333e-05 eta: 4:25:31 time: 0.6224 data_time: 0.0092 memory: 1637 loss: 1.3629 2023/04/13 20:32:25 - mmengine - INFO - Epoch(train) [4][4900/5005] lr: 3.3333e-05 eta: 4:24:48 time: 0.5796 data_time: 0.0097 memory: 1637 loss: 1.3355 2023/04/13 20:33:15 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:33:23 - mmengine - INFO - Epoch(train) [4][5000/5005] lr: 3.3333e-05 eta: 4:24:04 time: 0.5945 data_time: 0.0109 memory: 1637 loss: 1.3223 2023/04/13 20:33:26 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:33:27 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/04/13 20:33:52 - mmengine - INFO - Epoch(val) [4][100/196] eta: 0:00:22 time: 0.2200 data_time: 0.0107 memory: 1637 2023/04/13 20:35:11 - mmengine - INFO - Epoch(val) [4][196/196] qat.accuracy/top1: 69.9360 qat.accuracy/top5: 89.3700data_time: 0.0066 time: 0.4648 2023/04/13 20:35:16 - mmengine - INFO - Epoch(val) [4][100/196] eta: 0:00:04 time: 0.0315 data_time: 0.0130 memory: 967 2023/04/13 20:36:14 - mmengine - INFO - Epoch(val) [4][196/196] original.accuracy/top1: 69.9900 original.accuracy/top5: 89.4780data_time: 0.0235 time: 0.0400 2023/04/13 20:37:15 - mmengine - INFO - Epoch(train) [5][ 100/5005] lr: 3.3333e-05 eta: 4:23:22 time: 0.5945 data_time: 0.0106 memory: 1637 loss: 1.4122 2023/04/13 20:38:14 - mmengine - INFO - Epoch(train) [5][ 200/5005] lr: 3.3333e-05 eta: 4:22:38 time: 0.5843 data_time: 0.0099 memory: 1637 loss: 1.4382 2023/04/13 20:39:14 - mmengine - INFO - Epoch(train) [5][ 300/5005] lr: 3.3333e-05 eta: 4:21:56 time: 0.5939 data_time: 0.0114 memory: 1637 loss: 1.5056 2023/04/13 20:40:14 - mmengine - INFO - Epoch(train) [5][ 400/5005] lr: 3.3333e-05 eta: 4:21:13 time: 0.7094 data_time: 0.0248 memory: 1637 loss: 1.3916 2023/04/13 20:41:14 - mmengine - INFO - Epoch(train) [5][ 500/5005] lr: 3.3333e-05 eta: 4:20:30 time: 0.5949 data_time: 0.0096 memory: 1637 loss: 1.4555 2023/04/13 20:42:15 - mmengine - INFO - Epoch(train) [5][ 600/5005] lr: 3.3333e-05 eta: 4:19:49 time: 0.6385 data_time: 0.0103 memory: 1637 loss: 1.5417 2023/04/13 20:43:18 - mmengine - INFO - Epoch(train) [5][ 700/5005] lr: 3.3333e-05 eta: 4:19:10 time: 0.6283 data_time: 0.0095 memory: 1637 loss: 1.5468 2023/04/13 20:44:20 - mmengine - INFO - Epoch(train) [5][ 800/5005] lr: 3.3333e-05 eta: 4:18:29 time: 0.6622 data_time: 0.0109 memory: 1637 loss: 1.3802 2023/04/13 20:45:21 - mmengine - INFO - Epoch(train) [5][ 900/5005] lr: 3.3333e-05 eta: 4:17:47 time: 0.6066 data_time: 0.0106 memory: 1637 loss: 1.2230 2023/04/13 20:46:10 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:46:21 - mmengine - INFO - Epoch(train) [5][1000/5005] lr: 3.3333e-05 eta: 4:17:05 time: 0.5770 data_time: 0.0120 memory: 1637 loss: 1.2557 2023/04/13 20:47:21 - mmengine - INFO - Epoch(train) [5][1100/5005] lr: 3.3333e-05 eta: 4:16:20 time: 0.5924 data_time: 0.0112 memory: 1637 loss: 1.3808 2023/04/13 20:48:21 - mmengine - INFO - Epoch(train) [5][1200/5005] lr: 3.3333e-05 eta: 4:15:36 time: 0.5662 data_time: 0.0095 memory: 1637 loss: 1.2620 2023/04/13 20:49:20 - mmengine - INFO - Epoch(train) [5][1300/5005] lr: 3.3333e-05 eta: 4:14:51 time: 0.5886 data_time: 0.0106 memory: 1637 loss: 1.2653 2023/04/13 20:50:19 - mmengine - INFO - Epoch(train) [5][1400/5005] lr: 3.3333e-05 eta: 4:14:06 time: 0.6209 data_time: 0.0108 memory: 1637 loss: 1.2856 2023/04/13 20:51:22 - mmengine - INFO - Epoch(train) [5][1500/5005] lr: 3.3333e-05 eta: 4:13:25 time: 0.6145 data_time: 0.0107 memory: 1637 loss: 1.3252 2023/04/13 20:52:24 - mmengine - INFO - Epoch(train) [5][1600/5005] lr: 3.3333e-05 eta: 4:12:44 time: 0.6118 data_time: 0.0105 memory: 1637 loss: 1.3346 2023/04/13 20:53:26 - mmengine - INFO - Epoch(train) [5][1700/5005] lr: 3.3333e-05 eta: 4:12:01 time: 0.6854 data_time: 0.0101 memory: 1637 loss: 1.4252 2023/04/13 20:54:26 - mmengine - INFO - Epoch(train) [5][1800/5005] lr: 3.3333e-05 eta: 4:11:17 time: 0.5633 data_time: 0.0105 memory: 1637 loss: 1.2082 2023/04/13 20:55:27 - mmengine - INFO - Epoch(train) [5][1900/5005] lr: 3.3333e-05 eta: 4:10:33 time: 0.5855 data_time: 0.0095 memory: 1637 loss: 1.4134 2023/04/13 20:56:16 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 20:56:28 - mmengine - INFO - Epoch(train) [5][2000/5005] lr: 3.3333e-05 eta: 4:09:49 time: 0.5898 data_time: 0.0125 memory: 1637 loss: 1.2959 2023/04/13 20:57:29 - mmengine - INFO - Epoch(train) [5][2100/5005] lr: 3.3333e-05 eta: 4:09:05 time: 0.5756 data_time: 0.0103 memory: 1637 loss: 1.5778 2023/04/13 20:58:29 - mmengine - INFO - Epoch(train) [5][2200/5005] lr: 3.3333e-05 eta: 4:08:19 time: 0.6138 data_time: 0.0105 memory: 1637 loss: 1.4631 2023/04/13 20:59:30 - mmengine - INFO - Epoch(train) [5][2300/5005] lr: 3.3333e-05 eta: 4:07:35 time: 0.6148 data_time: 0.0104 memory: 1637 loss: 1.3447 2023/04/13 21:00:30 - mmengine - INFO - Epoch(train) [5][2400/5005] lr: 3.3333e-05 eta: 4:06:50 time: 0.5875 data_time: 0.0239 memory: 1637 loss: 1.4366 2023/04/13 21:01:29 - mmengine - INFO - Epoch(train) [5][2500/5005] lr: 3.3333e-05 eta: 4:06:03 time: 0.6005 data_time: 0.0111 memory: 1637 loss: 1.3963 2023/04/13 21:02:33 - mmengine - INFO - Epoch(train) [5][2600/5005] lr: 3.3333e-05 eta: 4:05:22 time: 0.6079 data_time: 0.0104 memory: 1637 loss: 1.3289 2023/04/13 21:03:35 - mmengine - INFO - Epoch(train) [5][2700/5005] lr: 3.3333e-05 eta: 4:04:37 time: 0.6083 data_time: 0.0100 memory: 1637 loss: 1.3898 2023/04/13 21:04:36 - mmengine - INFO - Epoch(train) [5][2800/5005] lr: 3.3333e-05 eta: 4:03:52 time: 0.6225 data_time: 0.0102 memory: 1637 loss: 1.1373 2023/04/13 21:05:36 - mmengine - INFO - Epoch(train) [5][2900/5005] lr: 3.3333e-05 eta: 4:03:07 time: 0.5944 data_time: 0.0127 memory: 1637 loss: 1.4176 2023/04/13 21:06:26 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:06:39 - mmengine - INFO - Epoch(train) [5][3000/5005] lr: 3.3333e-05 eta: 4:02:23 time: 0.6550 data_time: 0.0115 memory: 1637 loss: 1.4879 2023/04/13 21:07:40 - mmengine - INFO - Epoch(train) [5][3100/5005] lr: 3.3333e-05 eta: 4:01:38 time: 0.6121 data_time: 0.0112 memory: 1637 loss: 1.3183 2023/04/13 21:08:40 - mmengine - INFO - Epoch(train) [5][3200/5005] lr: 3.3333e-05 eta: 4:00:52 time: 0.6627 data_time: 0.0115 memory: 1637 loss: 1.3198 2023/04/13 21:09:41 - mmengine - INFO - Epoch(train) [5][3300/5005] lr: 3.3333e-05 eta: 4:00:05 time: 0.5931 data_time: 0.0100 memory: 1637 loss: 1.4291 2023/04/13 21:10:41 - mmengine - INFO - Epoch(train) [5][3400/5005] lr: 3.3333e-05 eta: 3:59:19 time: 0.6374 data_time: 0.0105 memory: 1637 loss: 1.2207 2023/04/13 21:11:43 - mmengine - INFO - Epoch(train) [5][3500/5005] lr: 3.3333e-05 eta: 3:58:34 time: 0.6045 data_time: 0.0117 memory: 1637 loss: 1.4347 2023/04/13 21:12:47 - mmengine - INFO - Epoch(train) [5][3600/5005] lr: 3.3333e-05 eta: 3:57:51 time: 0.6070 data_time: 0.0112 memory: 1637 loss: 1.3759 2023/04/13 21:13:49 - mmengine - INFO - Epoch(train) [5][3700/5005] lr: 3.3333e-05 eta: 3:57:06 time: 0.6239 data_time: 0.0116 memory: 1637 loss: 1.3485 2023/04/13 21:14:51 - mmengine - INFO - Epoch(train) [5][3800/5005] lr: 3.3333e-05 eta: 3:56:21 time: 0.5715 data_time: 0.0119 memory: 1637 loss: 1.4032 2023/04/13 21:15:52 - mmengine - INFO - Epoch(train) [5][3900/5005] lr: 3.3333e-05 eta: 3:55:34 time: 0.5930 data_time: 0.0108 memory: 1637 loss: 1.5490 2023/04/13 21:16:43 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:16:55 - mmengine - INFO - Epoch(train) [5][4000/5005] lr: 3.3333e-05 eta: 3:54:50 time: 0.6299 data_time: 0.0128 memory: 1637 loss: 1.2972 2023/04/13 21:17:57 - mmengine - INFO - Epoch(train) [5][4100/5005] lr: 3.3333e-05 eta: 3:54:05 time: 0.6290 data_time: 0.0104 memory: 1637 loss: 1.1040 2023/04/13 21:18:59 - mmengine - INFO - Epoch(train) [5][4200/5005] lr: 3.3333e-05 eta: 3:53:18 time: 0.6222 data_time: 0.0109 memory: 1637 loss: 1.3607 2023/04/13 21:20:00 - mmengine - INFO - Epoch(train) [5][4300/5005] lr: 3.3333e-05 eta: 3:52:32 time: 0.6223 data_time: 0.0101 memory: 1637 loss: 1.5079 2023/04/13 21:21:03 - mmengine - INFO - Epoch(train) [5][4400/5005] lr: 3.3333e-05 eta: 3:51:46 time: 0.5882 data_time: 0.0114 memory: 1637 loss: 1.1387 2023/04/13 21:22:05 - mmengine - INFO - Epoch(train) [5][4500/5005] lr: 3.3333e-05 eta: 3:50:59 time: 0.6161 data_time: 0.0121 memory: 1637 loss: 1.3814 2023/04/13 21:23:08 - mmengine - INFO - Epoch(train) [5][4600/5005] lr: 3.3333e-05 eta: 3:50:15 time: 0.5997 data_time: 0.0099 memory: 1637 loss: 1.5047 2023/04/13 21:24:09 - mmengine - INFO - Epoch(train) [5][4700/5005] lr: 3.3333e-05 eta: 3:49:27 time: 0.6293 data_time: 0.0103 memory: 1637 loss: 1.4881 2023/04/13 21:25:11 - mmengine - INFO - Epoch(train) [5][4800/5005] lr: 3.3333e-05 eta: 3:48:40 time: 0.5987 data_time: 0.0106 memory: 1637 loss: 1.4091 2023/04/13 21:26:11 - mmengine - INFO - Epoch(train) [5][4900/5005] lr: 3.3333e-05 eta: 3:47:52 time: 0.6065 data_time: 0.0097 memory: 1637 loss: 1.1896 2023/04/13 21:27:00 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:27:13 - mmengine - INFO - Epoch(train) [5][5000/5005] lr: 3.3333e-05 eta: 3:47:05 time: 0.6220 data_time: 0.0109 memory: 1637 loss: 1.4177 2023/04/13 21:27:15 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:27:16 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/04/13 21:27:42 - mmengine - INFO - Epoch(val) [5][100/196] eta: 0:00:22 time: 0.2267 data_time: 0.0103 memory: 1637 2023/04/13 21:29:02 - mmengine - INFO - Epoch(val) [5][196/196] qat.accuracy/top1: 69.9180 qat.accuracy/top5: 89.3140data_time: 0.0064 time: 0.4363 2023/04/13 21:29:07 - mmengine - INFO - Epoch(val) [5][100/196] eta: 0:00:04 time: 0.0315 data_time: 0.0139 memory: 967 2023/04/13 21:30:05 - mmengine - INFO - Epoch(val) [5][196/196] original.accuracy/top1: 69.9540 original.accuracy/top5: 89.4460data_time: 0.0112 time: 0.0286 2023/04/13 21:31:07 - mmengine - INFO - Epoch(train) [6][ 100/5005] lr: 3.3333e-05 eta: 3:46:15 time: 0.6031 data_time: 0.0100 memory: 1637 loss: 1.3986 2023/04/13 21:32:09 - mmengine - INFO - Epoch(train) [6][ 200/5005] lr: 3.3333e-05 eta: 3:45:27 time: 0.6139 data_time: 0.0101 memory: 1637 loss: 1.4243 2023/04/13 21:33:10 - mmengine - INFO - Epoch(train) [6][ 300/5005] lr: 3.3333e-05 eta: 3:44:39 time: 0.7850 data_time: 0.0103 memory: 1637 loss: 1.3111 2023/04/13 21:34:12 - mmengine - INFO - Epoch(train) [6][ 400/5005] lr: 3.3333e-05 eta: 3:43:52 time: 0.5828 data_time: 0.0106 memory: 1637 loss: 1.3346 2023/04/13 21:35:13 - mmengine - INFO - Epoch(train) [6][ 500/5005] lr: 3.3333e-05 eta: 3:43:03 time: 0.5939 data_time: 0.0109 memory: 1637 loss: 1.2611 2023/04/13 21:36:14 - mmengine - INFO - Epoch(train) [6][ 600/5005] lr: 3.3333e-05 eta: 3:42:15 time: 0.6116 data_time: 0.0096 memory: 1637 loss: 1.4322 2023/04/13 21:37:14 - mmengine - INFO - Epoch(train) [6][ 700/5005] lr: 3.3333e-05 eta: 3:41:25 time: 0.6020 data_time: 0.0113 memory: 1637 loss: 1.4998 2023/04/13 21:38:15 - mmengine - INFO - Epoch(train) [6][ 800/5005] lr: 3.3333e-05 eta: 3:40:37 time: 0.5782 data_time: 0.0105 memory: 1637 loss: 1.1902 2023/04/13 21:39:17 - mmengine - INFO - Epoch(train) [6][ 900/5005] lr: 3.3333e-05 eta: 3:39:49 time: 0.5954 data_time: 0.0100 memory: 1637 loss: 1.2770 2023/04/13 21:40:03 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:40:18 - mmengine - INFO - Epoch(train) [6][1000/5005] lr: 3.3333e-05 eta: 3:39:00 time: 0.6620 data_time: 0.0106 memory: 1637 loss: 1.5674 2023/04/13 21:41:19 - mmengine - INFO - Epoch(train) [6][1100/5005] lr: 3.3333e-05 eta: 3:38:11 time: 0.5958 data_time: 0.0115 memory: 1637 loss: 1.2299 2023/04/13 21:42:20 - mmengine - INFO - Epoch(train) [6][1200/5005] lr: 3.3333e-05 eta: 3:37:22 time: 0.6543 data_time: 0.0105 memory: 1637 loss: 1.4168 2023/04/13 21:43:13 - mmengine - INFO - Epoch(train) [6][1300/5005] lr: 3.3333e-05 eta: 3:36:26 time: 0.2209 data_time: 0.0129 memory: 1637 loss: 1.2752 2023/04/13 21:43:53 - mmengine - INFO - Epoch(train) [6][1400/5005] lr: 3.3333e-05 eta: 3:35:18 time: 0.4167 data_time: 0.0121 memory: 1637 loss: 1.6111 2023/04/13 21:45:37 - mmengine - INFO - Epoch(train) [6][1500/5005] lr: 3.3333e-05 eta: 3:35:07 time: 0.2960 data_time: 0.0113 memory: 1637 loss: 1.3642 2023/04/13 21:46:58 - mmengine - INFO - Epoch(train) [6][1600/5005] lr: 3.3333e-05 eta: 3:34:35 time: 0.6311 data_time: 0.0115 memory: 1637 loss: 1.4335 2023/04/13 21:47:58 - mmengine - INFO - Epoch(train) [6][1700/5005] lr: 3.3333e-05 eta: 3:33:45 time: 0.5819 data_time: 0.0111 memory: 1637 loss: 1.1674 2023/04/13 21:48:59 - mmengine - INFO - Epoch(train) [6][1800/5005] lr: 3.3333e-05 eta: 3:32:55 time: 0.5871 data_time: 0.0114 memory: 1637 loss: 1.3446 2023/04/13 21:50:00 - mmengine - INFO - Epoch(train) [6][1900/5005] lr: 3.3333e-05 eta: 3:32:05 time: 0.6144 data_time: 0.0108 memory: 1637 loss: 1.4177 2023/04/13 21:50:46 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:51:00 - mmengine - INFO - Epoch(train) [6][2000/5005] lr: 3.3333e-05 eta: 3:31:14 time: 0.4675 data_time: 0.0092 memory: 1637 loss: 1.1483 2023/04/13 21:51:20 - mmengine - INFO - Epoch(train) [6][2100/5005] lr: 3.3333e-05 eta: 3:29:50 time: 0.2008 data_time: 0.0100 memory: 1637 loss: 1.3084 2023/04/13 21:51:41 - mmengine - INFO - Epoch(train) [6][2200/5005] lr: 3.3333e-05 eta: 3:28:26 time: 0.1913 data_time: 0.0121 memory: 1637 loss: 1.4380 2023/04/13 21:52:02 - mmengine - INFO - Epoch(train) [6][2300/5005] lr: 3.3333e-05 eta: 3:27:03 time: 0.2084 data_time: 0.0099 memory: 1637 loss: 1.3691 2023/04/13 21:52:22 - mmengine - INFO - Epoch(train) [6][2400/5005] lr: 3.3333e-05 eta: 3:25:40 time: 0.1812 data_time: 0.0104 memory: 1637 loss: 1.2626 2023/04/13 21:52:44 - mmengine - INFO - Epoch(train) [6][2500/5005] lr: 3.3333e-05 eta: 3:24:18 time: 0.2653 data_time: 0.0111 memory: 1637 loss: 1.4975 2023/04/13 21:53:16 - mmengine - INFO - Epoch(train) [6][2600/5005] lr: 3.3333e-05 eta: 3:23:06 time: 0.4474 data_time: 0.0117 memory: 1637 loss: 1.2181 2023/04/13 21:54:15 - mmengine - INFO - Epoch(train) [6][2700/5005] lr: 3.3333e-05 eta: 3:22:15 time: 0.5976 data_time: 0.0118 memory: 1637 loss: 1.3964 2023/04/13 21:55:18 - mmengine - INFO - Epoch(train) [6][2800/5005] lr: 3.3333e-05 eta: 3:21:28 time: 0.6453 data_time: 0.0109 memory: 1637 loss: 1.3970 2023/04/13 21:56:19 - mmengine - INFO - Epoch(train) [6][2900/5005] lr: 3.3333e-05 eta: 3:20:38 time: 0.6054 data_time: 0.0103 memory: 1637 loss: 1.2686 2023/04/13 21:57:04 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 21:57:19 - mmengine - INFO - Epoch(train) [6][3000/5005] lr: 3.3333e-05 eta: 3:19:49 time: 0.6105 data_time: 0.0117 memory: 1637 loss: 1.5524 2023/04/13 21:58:20 - mmengine - INFO - Epoch(train) [6][3100/5005] lr: 3.3333e-05 eta: 3:19:00 time: 0.6467 data_time: 0.0109 memory: 1637 loss: 1.4655 2023/04/13 21:59:22 - mmengine - INFO - Epoch(train) [6][3200/5005] lr: 3.3333e-05 eta: 3:18:11 time: 0.5730 data_time: 0.0094 memory: 1637 loss: 1.4150 2023/04/13 22:00:26 - mmengine - INFO - Epoch(train) [6][3300/5005] lr: 3.3333e-05 eta: 3:17:24 time: 0.6574 data_time: 0.0108 memory: 1637 loss: 1.4049 2023/04/13 22:01:27 - mmengine - INFO - Epoch(train) [6][3400/5005] lr: 3.3333e-05 eta: 3:16:34 time: 0.6806 data_time: 0.0111 memory: 1637 loss: 1.2503 2023/04/13 22:02:31 - mmengine - INFO - Epoch(train) [6][3500/5005] lr: 3.3333e-05 eta: 3:15:46 time: 0.5686 data_time: 0.0113 memory: 1637 loss: 1.4225 2023/04/13 22:03:33 - mmengine - INFO - Epoch(train) [6][3600/5005] lr: 3.3333e-05 eta: 3:14:58 time: 0.5519 data_time: 0.0235 memory: 1637 loss: 1.4191 2023/04/13 22:04:34 - mmengine - INFO - Epoch(train) [6][3700/5005] lr: 3.3333e-05 eta: 3:14:08 time: 0.5117 data_time: 0.0118 memory: 1637 loss: 1.4315 2023/04/13 22:05:37 - mmengine - INFO - Epoch(train) [6][3800/5005] lr: 3.3333e-05 eta: 3:13:19 time: 0.6298 data_time: 0.0107 memory: 1637 loss: 1.4097 2023/04/13 22:06:39 - mmengine - INFO - Epoch(train) [6][3900/5005] lr: 3.3333e-05 eta: 3:12:30 time: 0.6863 data_time: 0.0095 memory: 1637 loss: 1.3235 2023/04/13 22:07:26 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:07:42 - mmengine - INFO - Epoch(train) [6][4000/5005] lr: 3.3333e-05 eta: 3:11:41 time: 0.6458 data_time: 0.0104 memory: 1637 loss: 1.4319 2023/04/13 22:08:45 - mmengine - INFO - Epoch(train) [6][4100/5005] lr: 3.3333e-05 eta: 3:10:52 time: 0.6319 data_time: 0.0235 memory: 1637 loss: 1.4973 2023/04/13 22:09:46 - mmengine - INFO - Epoch(train) [6][4200/5005] lr: 3.3333e-05 eta: 3:10:03 time: 0.5943 data_time: 0.0103 memory: 1637 loss: 1.3512 2023/04/13 22:10:48 - mmengine - INFO - Epoch(train) [6][4300/5005] lr: 3.3333e-05 eta: 3:09:12 time: 0.6252 data_time: 0.0113 memory: 1637 loss: 1.4319 2023/04/13 22:11:47 - mmengine - INFO - Epoch(train) [6][4400/5005] lr: 3.3333e-05 eta: 3:08:21 time: 0.6145 data_time: 0.0114 memory: 1637 loss: 1.4560 2023/04/13 22:12:50 - mmengine - INFO - Epoch(train) [6][4500/5005] lr: 3.3333e-05 eta: 3:07:32 time: 0.5851 data_time: 0.0100 memory: 1637 loss: 1.3608 2023/04/13 22:13:53 - mmengine - INFO - Epoch(train) [6][4600/5005] lr: 3.3333e-05 eta: 3:06:42 time: 0.6205 data_time: 0.0106 memory: 1637 loss: 1.5401 2023/04/13 22:14:56 - mmengine - INFO - Epoch(train) [6][4700/5005] lr: 3.3333e-05 eta: 3:05:53 time: 0.6366 data_time: 0.0111 memory: 1637 loss: 1.2879 2023/04/13 22:15:55 - mmengine - INFO - Epoch(train) [6][4800/5005] lr: 3.3333e-05 eta: 3:05:01 time: 0.7654 data_time: 0.0097 memory: 1637 loss: 1.5299 2023/04/13 22:16:56 - mmengine - INFO - Epoch(train) [6][4900/5005] lr: 3.3333e-05 eta: 3:04:10 time: 0.5765 data_time: 0.0096 memory: 1637 loss: 1.5234 2023/04/13 22:17:40 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:17:56 - mmengine - INFO - Epoch(train) [6][5000/5005] lr: 3.3333e-05 eta: 3:03:19 time: 0.5392 data_time: 0.0140 memory: 1637 loss: 1.1547 2023/04/13 22:17:58 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:17:59 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/04/13 22:18:25 - mmengine - INFO - Epoch(val) [6][100/196] eta: 0:00:23 time: 0.2461 data_time: 0.0101 memory: 1637 2023/04/13 22:19:48 - mmengine - INFO - Epoch(val) [6][196/196] qat.accuracy/top1: 69.9600 qat.accuracy/top5: 89.3860data_time: 0.0075 time: 0.4529 2023/04/13 22:19:53 - mmengine - INFO - Epoch(val) [6][100/196] eta: 0:00:04 time: 0.0313 data_time: 0.0128 memory: 967 2023/04/13 22:20:52 - mmengine - INFO - Epoch(val) [6][196/196] original.accuracy/top1: 69.9880 original.accuracy/top5: 89.4420data_time: 0.0245 time: 0.0418 2023/04/13 22:21:52 - mmengine - INFO - Epoch(train) [7][ 100/5005] lr: 3.3333e-05 eta: 3:02:23 time: 0.6372 data_time: 0.0102 memory: 1637 loss: 1.3532 2023/04/13 22:22:52 - mmengine - INFO - Epoch(train) [7][ 200/5005] lr: 3.3333e-05 eta: 3:01:32 time: 0.6256 data_time: 0.0099 memory: 1637 loss: 1.3521 2023/04/13 22:23:51 - mmengine - INFO - Epoch(train) [7][ 300/5005] lr: 3.3333e-05 eta: 3:00:40 time: 0.6125 data_time: 0.0108 memory: 1637 loss: 1.3557 2023/04/13 22:24:50 - mmengine - INFO - Epoch(train) [7][ 400/5005] lr: 3.3333e-05 eta: 2:59:47 time: 0.5539 data_time: 0.0104 memory: 1637 loss: 1.4039 2023/04/13 22:25:52 - mmengine - INFO - Epoch(train) [7][ 500/5005] lr: 3.3333e-05 eta: 2:58:57 time: 0.6661 data_time: 0.0099 memory: 1637 loss: 1.4615 2023/04/13 22:26:50 - mmengine - INFO - Epoch(train) [7][ 600/5005] lr: 3.3333e-05 eta: 2:58:04 time: 0.4339 data_time: 0.0109 memory: 1637 loss: 1.2423 2023/04/13 22:27:52 - mmengine - INFO - Epoch(train) [7][ 700/5005] lr: 3.3333e-05 eta: 2:57:13 time: 0.6126 data_time: 0.0096 memory: 1637 loss: 1.2706 2023/04/13 22:28:52 - mmengine - INFO - Epoch(train) [7][ 800/5005] lr: 3.3333e-05 eta: 2:56:21 time: 0.5400 data_time: 0.0118 memory: 1637 loss: 1.2613 2023/04/13 22:29:53 - mmengine - INFO - Epoch(train) [7][ 900/5005] lr: 3.3333e-05 eta: 2:55:29 time: 0.6076 data_time: 0.0112 memory: 1637 loss: 1.3795 2023/04/13 22:30:37 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:30:54 - mmengine - INFO - Epoch(train) [7][1000/5005] lr: 3.3333e-05 eta: 2:54:39 time: 0.5440 data_time: 0.0122 memory: 1637 loss: 1.3234 2023/04/13 22:31:57 - mmengine - INFO - Epoch(train) [7][1100/5005] lr: 3.3333e-05 eta: 2:53:48 time: 0.6298 data_time: 0.0114 memory: 1637 loss: 1.1725 2023/04/13 22:33:01 - mmengine - INFO - Epoch(train) [7][1200/5005] lr: 3.3333e-05 eta: 2:52:58 time: 0.6159 data_time: 0.0119 memory: 1637 loss: 1.4951 2023/04/13 22:33:58 - mmengine - INFO - Epoch(train) [7][1300/5005] lr: 3.3333e-05 eta: 2:52:04 time: 0.5201 data_time: 0.0113 memory: 1637 loss: 1.2125 2023/04/13 22:34:56 - mmengine - INFO - Epoch(train) [7][1400/5005] lr: 3.3333e-05 eta: 2:51:11 time: 0.5367 data_time: 0.0116 memory: 1637 loss: 1.5041 2023/04/13 22:35:55 - mmengine - INFO - Epoch(train) [7][1500/5005] lr: 3.3333e-05 eta: 2:50:18 time: 0.5633 data_time: 0.0109 memory: 1637 loss: 1.4286 2023/04/13 22:36:53 - mmengine - INFO - Epoch(train) [7][1600/5005] lr: 3.3333e-05 eta: 2:49:24 time: 0.5431 data_time: 0.0125 memory: 1637 loss: 1.4692 2023/04/13 22:37:50 - mmengine - INFO - Epoch(train) [7][1700/5005] lr: 3.3333e-05 eta: 2:48:30 time: 0.4445 data_time: 0.0122 memory: 1637 loss: 1.4931 2023/04/13 22:38:44 - mmengine - INFO - Epoch(train) [7][1800/5005] lr: 3.3333e-05 eta: 2:47:34 time: 0.4014 data_time: 0.0127 memory: 1637 loss: 1.4737 2023/04/13 22:39:26 - mmengine - INFO - Epoch(train) [7][1900/5005] lr: 3.3333e-05 eta: 2:46:31 time: 0.4491 data_time: 0.0121 memory: 1637 loss: 1.3988 2023/04/13 22:40:49 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:41:06 - mmengine - INFO - Epoch(train) [7][2000/5005] lr: 3.3333e-05 eta: 2:46:01 time: 0.4326 data_time: 0.0166 memory: 1637 loss: 1.2835 2023/04/13 22:41:46 - mmengine - INFO - Epoch(train) [7][2100/5005] lr: 3.3333e-05 eta: 2:44:58 time: 0.1907 data_time: 0.0097 memory: 1637 loss: 1.5309 2023/04/13 22:42:06 - mmengine - INFO - Epoch(train) [7][2200/5005] lr: 3.3333e-05 eta: 2:43:43 time: 0.2192 data_time: 0.0105 memory: 1637 loss: 1.3080 2023/04/13 22:42:26 - mmengine - INFO - Epoch(train) [7][2300/5005] lr: 3.3333e-05 eta: 2:42:29 time: 0.2036 data_time: 0.0089 memory: 1637 loss: 1.3374 2023/04/13 22:42:47 - mmengine - INFO - Epoch(train) [7][2400/5005] lr: 3.3333e-05 eta: 2:41:15 time: 0.2683 data_time: 0.0108 memory: 1637 loss: 1.1917 2023/04/13 22:43:22 - mmengine - INFO - Epoch(train) [7][2500/5005] lr: 3.3333e-05 eta: 2:40:09 time: 0.5142 data_time: 0.0113 memory: 1637 loss: 1.4852 2023/04/13 22:44:19 - mmengine - INFO - Epoch(train) [7][2600/5005] lr: 3.3333e-05 eta: 2:39:16 time: 0.5374 data_time: 0.0118 memory: 1637 loss: 1.3644 2023/04/13 22:45:17 - mmengine - INFO - Epoch(train) [7][2700/5005] lr: 3.3333e-05 eta: 2:38:23 time: 0.5648 data_time: 0.0229 memory: 1637 loss: 1.4576 2023/04/13 22:46:18 - mmengine - INFO - Epoch(train) [7][2800/5005] lr: 3.3333e-05 eta: 2:37:31 time: 0.6284 data_time: 0.0097 memory: 1637 loss: 1.3940 2023/04/13 22:47:20 - mmengine - INFO - Epoch(train) [7][2900/5005] lr: 3.3333e-05 eta: 2:36:40 time: 0.6256 data_time: 0.0105 memory: 1637 loss: 1.4349 2023/04/13 22:48:03 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:48:20 - mmengine - INFO - Epoch(train) [7][3000/5005] lr: 3.3333e-05 eta: 2:35:48 time: 0.5827 data_time: 0.0117 memory: 1637 loss: 1.4885 2023/04/13 22:49:21 - mmengine - INFO - Epoch(train) [7][3100/5005] lr: 3.3333e-05 eta: 2:34:56 time: 0.6009 data_time: 0.0105 memory: 1637 loss: 1.5123 2023/04/13 22:50:22 - mmengine - INFO - Epoch(train) [7][3200/5005] lr: 3.3333e-05 eta: 2:34:04 time: 0.6065 data_time: 0.0109 memory: 1637 loss: 1.3199 2023/04/13 22:51:23 - mmengine - INFO - Epoch(train) [7][3300/5005] lr: 3.3333e-05 eta: 2:33:12 time: 0.5960 data_time: 0.0113 memory: 1637 loss: 1.3539 2023/04/13 22:52:25 - mmengine - INFO - Epoch(train) [7][3400/5005] lr: 3.3333e-05 eta: 2:32:20 time: 0.6238 data_time: 0.0112 memory: 1637 loss: 1.4154 2023/04/13 22:53:25 - mmengine - INFO - Epoch(train) [7][3500/5005] lr: 3.3333e-05 eta: 2:31:28 time: 0.6243 data_time: 0.0114 memory: 1637 loss: 1.4027 2023/04/13 22:54:28 - mmengine - INFO - Epoch(train) [7][3600/5005] lr: 3.3333e-05 eta: 2:30:37 time: 0.6392 data_time: 0.0115 memory: 1637 loss: 1.3555 2023/04/13 22:55:29 - mmengine - INFO - Epoch(train) [7][3700/5005] lr: 3.3333e-05 eta: 2:29:44 time: 0.6498 data_time: 0.0106 memory: 1637 loss: 1.4403 2023/04/13 22:56:28 - mmengine - INFO - Epoch(train) [7][3800/5005] lr: 3.3333e-05 eta: 2:28:51 time: 0.6304 data_time: 0.0109 memory: 1637 loss: 1.3992 2023/04/13 22:57:29 - mmengine - INFO - Epoch(train) [7][3900/5005] lr: 3.3333e-05 eta: 2:27:59 time: 0.5738 data_time: 0.0115 memory: 1637 loss: 1.3383 2023/04/13 22:58:12 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 22:58:31 - mmengine - INFO - Epoch(train) [7][4000/5005] lr: 3.3333e-05 eta: 2:27:07 time: 0.6444 data_time: 0.0122 memory: 1637 loss: 1.2842 2023/04/13 22:59:31 - mmengine - INFO - Epoch(train) [7][4100/5005] lr: 3.3333e-05 eta: 2:26:15 time: 0.4594 data_time: 0.0135 memory: 1637 loss: 1.4263 2023/04/13 23:00:33 - mmengine - INFO - Epoch(train) [7][4200/5005] lr: 3.3333e-05 eta: 2:25:22 time: 0.5706 data_time: 0.0111 memory: 1637 loss: 1.5206 2023/04/13 23:01:34 - mmengine - INFO - Epoch(train) [7][4300/5005] lr: 3.3333e-05 eta: 2:24:30 time: 0.5893 data_time: 0.0099 memory: 1637 loss: 1.2054 2023/04/13 23:02:34 - mmengine - INFO - Epoch(train) [7][4400/5005] lr: 3.3333e-05 eta: 2:23:37 time: 0.6528 data_time: 0.0265 memory: 1637 loss: 1.3646 2023/04/13 23:03:33 - mmengine - INFO - Epoch(train) [7][4500/5005] lr: 3.3333e-05 eta: 2:22:44 time: 0.6079 data_time: 0.0119 memory: 1637 loss: 1.4211 2023/04/13 23:04:34 - mmengine - INFO - Epoch(train) [7][4600/5005] lr: 3.3333e-05 eta: 2:21:51 time: 0.5852 data_time: 0.0111 memory: 1637 loss: 1.4434 2023/04/13 23:05:33 - mmengine - INFO - Epoch(train) [7][4700/5005] lr: 3.3333e-05 eta: 2:20:58 time: 0.6294 data_time: 0.0108 memory: 1637 loss: 1.5009 2023/04/13 23:06:35 - mmengine - INFO - Epoch(train) [7][4800/5005] lr: 3.3333e-05 eta: 2:20:05 time: 0.6159 data_time: 0.0127 memory: 1637 loss: 1.3724 2023/04/13 23:07:35 - mmengine - INFO - Epoch(train) [7][4900/5005] lr: 3.3333e-05 eta: 2:19:12 time: 0.6368 data_time: 0.0123 memory: 1637 loss: 1.4656 2023/04/13 23:08:18 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 23:08:38 - mmengine - INFO - Epoch(train) [7][5000/5005] lr: 3.3333e-05 eta: 2:18:20 time: 0.6619 data_time: 0.0104 memory: 1637 loss: 1.3824 2023/04/13 23:08:41 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 23:08:42 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/04/13 23:09:08 - mmengine - INFO - Epoch(val) [7][100/196] eta: 0:00:23 time: 0.2105 data_time: 0.0119 memory: 1637 2023/04/13 23:10:35 - mmengine - INFO - Epoch(val) [7][196/196] qat.accuracy/top1: 69.9420 qat.accuracy/top5: 89.3640data_time: 0.0090 time: 0.4967 2023/04/13 23:10:40 - mmengine - INFO - Epoch(val) [7][100/196] eta: 0:00:05 time: 0.0393 data_time: 0.0204 memory: 967 2023/04/13 23:11:40 - mmengine - INFO - Epoch(val) [7][196/196] original.accuracy/top1: 69.9660 original.accuracy/top5: 89.4500data_time: 0.0345 time: 0.0496 2023/04/13 23:12:41 - mmengine - INFO - Epoch(train) [8][ 100/5005] lr: 3.3333e-05 eta: 2:17:25 time: 0.6311 data_time: 0.0112 memory: 1637 loss: 1.1574 2023/04/13 23:13:39 - mmengine - INFO - Epoch(train) [8][ 200/5005] lr: 3.3333e-05 eta: 2:16:30 time: 0.5833 data_time: 0.0128 memory: 1637 loss: 1.4256 2023/04/13 23:14:38 - mmengine - INFO - Epoch(train) [8][ 300/5005] lr: 3.3333e-05 eta: 2:15:36 time: 0.5821 data_time: 0.0113 memory: 1637 loss: 1.3251 2023/04/13 23:15:39 - mmengine - INFO - Epoch(train) [8][ 400/5005] lr: 3.3333e-05 eta: 2:14:44 time: 0.5945 data_time: 0.0128 memory: 1637 loss: 1.4289 2023/04/13 23:16:41 - mmengine - INFO - Epoch(train) [8][ 500/5005] lr: 3.3333e-05 eta: 2:13:51 time: 0.5383 data_time: 0.0132 memory: 1637 loss: 1.4706 2023/04/13 23:17:40 - mmengine - INFO - Epoch(train) [8][ 600/5005] lr: 3.3333e-05 eta: 2:12:57 time: 0.5668 data_time: 0.0122 memory: 1637 loss: 1.5884 2023/04/13 23:18:41 - mmengine - INFO - Epoch(train) [8][ 700/5005] lr: 3.3333e-05 eta: 2:12:04 time: 0.6191 data_time: 0.0121 memory: 1637 loss: 1.3498 2023/04/13 23:19:43 - mmengine - INFO - Epoch(train) [8][ 800/5005] lr: 3.3333e-05 eta: 2:11:11 time: 0.6499 data_time: 0.0118 memory: 1637 loss: 1.6261 2023/04/13 23:20:44 - mmengine - INFO - Epoch(train) [8][ 900/5005] lr: 3.3333e-05 eta: 2:10:18 time: 0.6222 data_time: 0.0115 memory: 1637 loss: 1.3868 2023/04/13 23:21:23 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 23:21:45 - mmengine - INFO - Epoch(train) [8][1000/5005] lr: 3.3333e-05 eta: 2:09:25 time: 0.5735 data_time: 0.0118 memory: 1637 loss: 1.5805 2023/04/13 23:22:42 - mmengine - INFO - Epoch(train) [8][1100/5005] lr: 3.3333e-05 eta: 2:08:30 time: 0.6588 data_time: 0.0106 memory: 1637 loss: 1.4662 2023/04/13 23:23:43 - mmengine - INFO - Epoch(train) [8][1200/5005] lr: 3.3333e-05 eta: 2:07:37 time: 0.6241 data_time: 0.0109 memory: 1637 loss: 1.4670 2023/04/13 23:24:44 - mmengine - INFO - Epoch(train) [8][1300/5005] lr: 3.3333e-05 eta: 2:06:44 time: 0.5858 data_time: 0.0114 memory: 1637 loss: 1.4882 2023/04/13 23:25:47 - mmengine - INFO - Epoch(train) [8][1400/5005] lr: 3.3333e-05 eta: 2:05:51 time: 0.6303 data_time: 0.0103 memory: 1637 loss: 1.4495 2023/04/13 23:26:48 - mmengine - INFO - Epoch(train) [8][1500/5005] lr: 3.3333e-05 eta: 2:04:57 time: 0.5181 data_time: 0.0116 memory: 1637 loss: 1.3430 2023/04/13 23:27:50 - mmengine - INFO - Epoch(train) [8][1600/5005] lr: 3.3333e-05 eta: 2:04:04 time: 0.6545 data_time: 0.0243 memory: 1637 loss: 1.4465 2023/04/13 23:28:35 - mmengine - INFO - Epoch(train) [8][1700/5005] lr: 3.3333e-05 eta: 2:03:05 time: 0.1495 data_time: 0.0099 memory: 1637 loss: 1.4217 2023/04/13 23:28:50 - mmengine - INFO - Epoch(train) [8][1800/5005] lr: 3.3333e-05 eta: 2:01:55 time: 0.1474 data_time: 0.0125 memory: 1637 loss: 1.2393 2023/04/13 23:29:07 - mmengine - INFO - Epoch(train) [8][1900/5005] lr: 3.3333e-05 eta: 2:00:46 time: 0.6564 data_time: 0.0100 memory: 1637 loss: 1.3083 2023/04/13 23:30:10 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 23:30:29 - mmengine - INFO - Epoch(train) [8][2000/5005] lr: 3.3333e-05 eta: 2:00:00 time: 0.2333 data_time: 0.0096 memory: 1637 loss: 1.5094 2023/04/13 23:31:51 - mmengine - INFO - Epoch(train) [8][2100/5005] lr: 3.3333e-05 eta: 1:59:14 time: 0.5670 data_time: 0.0088 memory: 1637 loss: 1.1942 2023/04/13 23:32:48 - mmengine - INFO - Epoch(train) [8][2200/5005] lr: 3.3333e-05 eta: 1:58:19 time: 0.5656 data_time: 0.0091 memory: 1637 loss: 1.1584 2023/04/13 23:33:45 - mmengine - INFO - Epoch(train) [8][2300/5005] lr: 3.3333e-05 eta: 1:57:24 time: 0.5687 data_time: 0.0083 memory: 1637 loss: 1.3459 2023/04/13 23:34:42 - mmengine - INFO - Epoch(train) [8][2400/5005] lr: 3.3333e-05 eta: 1:56:30 time: 0.5813 data_time: 0.0090 memory: 1637 loss: 1.3327 2023/04/13 23:35:40 - mmengine - INFO - Epoch(train) [8][2500/5005] lr: 3.3333e-05 eta: 1:55:35 time: 0.6265 data_time: 0.0098 memory: 1637 loss: 1.3479 2023/04/13 23:36:38 - mmengine - INFO - Epoch(train) [8][2600/5005] lr: 3.3333e-05 eta: 1:54:41 time: 0.5538 data_time: 0.0095 memory: 1637 loss: 1.3333 2023/04/13 23:37:36 - mmengine - INFO - Epoch(train) [8][2700/5005] lr: 3.3333e-05 eta: 1:53:46 time: 0.5790 data_time: 0.0099 memory: 1637 loss: 1.5072 2023/04/13 23:38:36 - mmengine - INFO - Epoch(train) [8][2800/5005] lr: 3.3333e-05 eta: 1:52:52 time: 0.5852 data_time: 0.0105 memory: 1637 loss: 1.6160 2023/04/13 23:39:37 - mmengine - INFO - Epoch(train) [8][2900/5005] lr: 3.3333e-05 eta: 1:51:58 time: 0.5925 data_time: 0.0126 memory: 1637 loss: 1.3305 2023/04/13 23:40:18 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 23:40:40 - mmengine - INFO - Epoch(train) [8][3000/5005] lr: 3.3333e-05 eta: 1:51:05 time: 0.6037 data_time: 0.0112 memory: 1637 loss: 1.4324 2023/04/13 23:41:42 - mmengine - INFO - Epoch(train) [8][3100/5005] lr: 3.3333e-05 eta: 1:50:12 time: 0.6250 data_time: 0.0119 memory: 1637 loss: 1.3316 2023/04/13 23:42:43 - mmengine - INFO - Epoch(train) [8][3200/5005] lr: 3.3333e-05 eta: 1:49:18 time: 0.6097 data_time: 0.0112 memory: 1637 loss: 1.3428 2023/04/13 23:43:45 - mmengine - INFO - Epoch(train) [8][3300/5005] lr: 3.3333e-05 eta: 1:48:25 time: 0.6106 data_time: 0.0105 memory: 1637 loss: 1.2819 2023/04/13 23:44:46 - mmengine - INFO - Epoch(train) [8][3400/5005] lr: 3.3333e-05 eta: 1:47:31 time: 0.5987 data_time: 0.0105 memory: 1637 loss: 1.2765 2023/04/13 23:45:48 - mmengine - INFO - Epoch(train) [8][3500/5005] lr: 3.3333e-05 eta: 1:46:37 time: 0.6065 data_time: 0.0112 memory: 1637 loss: 1.2005 2023/04/13 23:46:50 - mmengine - INFO - Epoch(train) [8][3600/5005] lr: 3.3333e-05 eta: 1:45:43 time: 0.6076 data_time: 0.0109 memory: 1637 loss: 1.4091 2023/04/13 23:47:52 - mmengine - INFO - Epoch(train) [8][3700/5005] lr: 3.3333e-05 eta: 1:44:50 time: 0.6265 data_time: 0.0107 memory: 1637 loss: 1.3270 2023/04/13 23:48:55 - mmengine - INFO - Epoch(train) [8][3800/5005] lr: 3.3333e-05 eta: 1:43:56 time: 0.6395 data_time: 0.0115 memory: 1637 loss: 1.3047 2023/04/13 23:49:58 - mmengine - INFO - Epoch(train) [8][3900/5005] lr: 3.3333e-05 eta: 1:43:03 time: 0.6508 data_time: 0.0110 memory: 1637 loss: 1.2287 2023/04/13 23:50:39 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/13 23:51:02 - mmengine - INFO - Epoch(train) [8][4000/5005] lr: 3.3333e-05 eta: 1:42:09 time: 0.6322 data_time: 0.0107 memory: 1637 loss: 1.4176 2023/04/13 23:52:04 - mmengine - INFO - Epoch(train) [8][4100/5005] lr: 3.3333e-05 eta: 1:41:16 time: 0.6227 data_time: 0.0120 memory: 1637 loss: 1.5301 2023/04/13 23:53:07 - mmengine - INFO - Epoch(train) [8][4200/5005] lr: 3.3333e-05 eta: 1:40:22 time: 0.6273 data_time: 0.0109 memory: 1637 loss: 1.4814 2023/04/13 23:54:07 - mmengine - INFO - Epoch(train) [8][4300/5005] lr: 3.3333e-05 eta: 1:39:27 time: 0.5964 data_time: 0.0103 memory: 1637 loss: 1.5408 2023/04/13 23:55:07 - mmengine - INFO - Epoch(train) [8][4400/5005] lr: 3.3333e-05 eta: 1:38:33 time: 0.5645 data_time: 0.0104 memory: 1637 loss: 1.2461 2023/04/13 23:56:05 - mmengine - INFO - Epoch(train) [8][4500/5005] lr: 3.3333e-05 eta: 1:37:38 time: 0.5690 data_time: 0.0085 memory: 1637 loss: 1.3099 2023/04/13 23:57:02 - mmengine - INFO - Epoch(train) [8][4600/5005] lr: 3.3333e-05 eta: 1:36:42 time: 0.5836 data_time: 0.0094 memory: 1637 loss: 1.3344 2023/04/13 23:58:00 - mmengine - INFO - Epoch(train) [8][4700/5005] lr: 3.3333e-05 eta: 1:35:47 time: 0.5647 data_time: 0.0086 memory: 1637 loss: 1.4401 2023/04/13 23:58:59 - mmengine - INFO - Epoch(train) [8][4800/5005] lr: 3.3333e-05 eta: 1:34:52 time: 0.5816 data_time: 0.0083 memory: 1637 loss: 1.2559 2023/04/13 23:59:55 - mmengine - INFO - Epoch(train) [8][4900/5005] lr: 3.3333e-05 eta: 1:33:56 time: 0.5652 data_time: 0.0087 memory: 1637 loss: 1.1858 2023/04/14 00:00:31 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:00:52 - mmengine - INFO - Epoch(train) [8][5000/5005] lr: 3.3333e-05 eta: 1:33:01 time: 0.6089 data_time: 0.0105 memory: 1637 loss: 1.3896 2023/04/14 00:00:55 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:00:56 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/04/14 00:01:22 - mmengine - INFO - Epoch(val) [8][100/196] eta: 0:00:23 time: 0.2492 data_time: 0.0080 memory: 1637 2023/04/14 00:02:41 - mmengine - INFO - Epoch(val) [8][196/196] qat.accuracy/top1: 69.9800 qat.accuracy/top5: 89.3160data_time: 0.0070 time: 0.4595 2023/04/14 00:02:45 - mmengine - INFO - Epoch(val) [8][100/196] eta: 0:00:04 time: 0.0323 data_time: 0.0146 memory: 967 2023/04/14 00:03:42 - mmengine - INFO - Epoch(val) [8][196/196] original.accuracy/top1: 69.9640 original.accuracy/top5: 89.4700data_time: 0.0221 time: 0.0421 2023/04/14 00:04:43 - mmengine - INFO - Epoch(train) [9][ 100/5005] lr: 3.3333e-05 eta: 1:32:04 time: 0.5848 data_time: 0.0080 memory: 1637 loss: 1.3511 2023/04/14 00:05:40 - mmengine - INFO - Epoch(train) [9][ 200/5005] lr: 3.3333e-05 eta: 1:31:08 time: 0.5618 data_time: 0.0081 memory: 1637 loss: 1.3791 2023/04/14 00:06:38 - mmengine - INFO - Epoch(train) [9][ 300/5005] lr: 3.3333e-05 eta: 1:30:13 time: 0.5719 data_time: 0.0093 memory: 1637 loss: 1.2734 2023/04/14 00:07:37 - mmengine - INFO - Epoch(train) [9][ 400/5005] lr: 3.3333e-05 eta: 1:29:18 time: 0.5892 data_time: 0.0099 memory: 1637 loss: 1.2762 2023/04/14 00:08:35 - mmengine - INFO - Epoch(train) [9][ 500/5005] lr: 3.3333e-05 eta: 1:28:23 time: 0.5846 data_time: 0.0092 memory: 1637 loss: 1.5983 2023/04/14 00:09:33 - mmengine - INFO - Epoch(train) [9][ 600/5005] lr: 3.3333e-05 eta: 1:27:28 time: 0.5888 data_time: 0.0103 memory: 1637 loss: 1.4884 2023/04/14 00:10:36 - mmengine - INFO - Epoch(train) [9][ 700/5005] lr: 3.3333e-05 eta: 1:26:33 time: 0.6448 data_time: 0.0104 memory: 1637 loss: 1.4144 2023/04/14 00:11:39 - mmengine - INFO - Epoch(train) [9][ 800/5005] lr: 3.3333e-05 eta: 1:25:39 time: 0.6614 data_time: 0.0108 memory: 1637 loss: 1.2315 2023/04/14 00:12:43 - mmengine - INFO - Epoch(train) [9][ 900/5005] lr: 3.3333e-05 eta: 1:24:45 time: 0.6267 data_time: 0.0131 memory: 1637 loss: 1.3030 2023/04/14 00:13:21 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:13:47 - mmengine - INFO - Epoch(train) [9][1000/5005] lr: 3.3333e-05 eta: 1:23:51 time: 0.6130 data_time: 0.0107 memory: 1637 loss: 1.1711 2023/04/14 00:14:49 - mmengine - INFO - Epoch(train) [9][1100/5005] lr: 3.3333e-05 eta: 1:22:57 time: 0.6222 data_time: 0.0121 memory: 1637 loss: 1.4729 2023/04/14 00:15:42 - mmengine - INFO - Epoch(train) [9][1200/5005] lr: 3.3333e-05 eta: 1:22:00 time: 0.4579 data_time: 0.0110 memory: 1637 loss: 1.4729 2023/04/14 00:16:32 - mmengine - INFO - Epoch(train) [9][1300/5005] lr: 3.3333e-05 eta: 1:21:03 time: 0.8094 data_time: 0.0093 memory: 1637 loss: 1.4575 2023/04/14 00:18:16 - mmengine - INFO - Epoch(train) [9][1400/5005] lr: 3.3333e-05 eta: 1:20:18 time: 0.7600 data_time: 0.0085 memory: 1637 loss: 1.4130 2023/04/14 00:19:14 - mmengine - INFO - Epoch(train) [9][1500/5005] lr: 3.3333e-05 eta: 1:19:22 time: 0.5582 data_time: 0.0081 memory: 1637 loss: 1.3821 2023/04/14 00:20:15 - mmengine - INFO - Epoch(train) [9][1600/5005] lr: 3.3333e-05 eta: 1:18:27 time: 0.6621 data_time: 0.0088 memory: 1637 loss: 1.5761 2023/04/14 00:21:12 - mmengine - INFO - Epoch(train) [9][1700/5005] lr: 3.3333e-05 eta: 1:17:31 time: 0.5597 data_time: 0.0080 memory: 1637 loss: 1.4736 2023/04/14 00:22:12 - mmengine - INFO - Epoch(train) [9][1800/5005] lr: 3.3333e-05 eta: 1:16:36 time: 0.6031 data_time: 0.0084 memory: 1637 loss: 1.6246 2023/04/14 00:23:12 - mmengine - INFO - Epoch(train) [9][1900/5005] lr: 3.3333e-05 eta: 1:15:41 time: 0.5929 data_time: 0.0085 memory: 1637 loss: 1.3934 2023/04/14 00:23:48 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:24:11 - mmengine - INFO - Epoch(train) [9][2000/5005] lr: 3.3333e-05 eta: 1:14:45 time: 0.5725 data_time: 0.0081 memory: 1637 loss: 1.3094 2023/04/14 00:25:10 - mmengine - INFO - Epoch(train) [9][2100/5005] lr: 3.3333e-05 eta: 1:13:50 time: 0.5370 data_time: 0.0080 memory: 1637 loss: 1.4496 2023/04/14 00:26:07 - mmengine - INFO - Epoch(train) [9][2200/5005] lr: 3.3333e-05 eta: 1:12:54 time: 0.5420 data_time: 0.0093 memory: 1637 loss: 1.2878 2023/04/14 00:27:08 - mmengine - INFO - Epoch(train) [9][2300/5005] lr: 3.3333e-05 eta: 1:11:59 time: 0.5575 data_time: 0.0085 memory: 1637 loss: 1.4633 2023/04/14 00:28:06 - mmengine - INFO - Epoch(train) [9][2400/5005] lr: 3.3333e-05 eta: 1:11:03 time: 0.5542 data_time: 0.0084 memory: 1637 loss: 1.5106 2023/04/14 00:29:05 - mmengine - INFO - Epoch(train) [9][2500/5005] lr: 3.3333e-05 eta: 1:10:08 time: 0.5591 data_time: 0.0082 memory: 1637 loss: 1.6232 2023/04/14 00:30:04 - mmengine - INFO - Epoch(train) [9][2600/5005] lr: 3.3333e-05 eta: 1:09:12 time: 0.6344 data_time: 0.0083 memory: 1637 loss: 1.2223 2023/04/14 00:31:02 - mmengine - INFO - Epoch(train) [9][2700/5005] lr: 3.3333e-05 eta: 1:08:17 time: 0.5689 data_time: 0.0080 memory: 1637 loss: 1.1420 2023/04/14 00:32:00 - mmengine - INFO - Epoch(train) [9][2800/5005] lr: 3.3333e-05 eta: 1:07:21 time: 0.5875 data_time: 0.0086 memory: 1637 loss: 1.2953 2023/04/14 00:32:59 - mmengine - INFO - Epoch(train) [9][2900/5005] lr: 3.3333e-05 eta: 1:06:25 time: 0.5889 data_time: 0.0079 memory: 1637 loss: 1.6093 2023/04/14 00:33:34 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:33:57 - mmengine - INFO - Epoch(train) [9][3000/5005] lr: 3.3333e-05 eta: 1:05:30 time: 0.6164 data_time: 0.0086 memory: 1637 loss: 1.3372 2023/04/14 00:34:57 - mmengine - INFO - Epoch(train) [9][3100/5005] lr: 3.3333e-05 eta: 1:04:34 time: 0.5995 data_time: 0.0092 memory: 1637 loss: 1.4751 2023/04/14 00:35:56 - mmengine - INFO - Epoch(train) [9][3200/5005] lr: 3.3333e-05 eta: 1:03:38 time: 0.6140 data_time: 0.0081 memory: 1637 loss: 1.4354 2023/04/14 00:36:54 - mmengine - INFO - Epoch(train) [9][3300/5005] lr: 3.3333e-05 eta: 1:02:43 time: 0.5534 data_time: 0.0080 memory: 1637 loss: 1.3357 2023/04/14 00:37:53 - mmengine - INFO - Epoch(train) [9][3400/5005] lr: 3.3333e-05 eta: 1:01:47 time: 0.5867 data_time: 0.0083 memory: 1637 loss: 1.4096 2023/04/14 00:38:51 - mmengine - INFO - Epoch(train) [9][3500/5005] lr: 3.3333e-05 eta: 1:00:51 time: 0.5793 data_time: 0.0078 memory: 1637 loss: 1.3442 2023/04/14 00:39:51 - mmengine - INFO - Epoch(train) [9][3600/5005] lr: 3.3333e-05 eta: 0:59:56 time: 0.6041 data_time: 0.0086 memory: 1637 loss: 1.2524 2023/04/14 00:40:50 - mmengine - INFO - Epoch(train) [9][3700/5005] lr: 3.3333e-05 eta: 0:59:00 time: 0.5739 data_time: 0.0080 memory: 1637 loss: 1.3674 2023/04/14 00:41:49 - mmengine - INFO - Epoch(train) [9][3800/5005] lr: 3.3333e-05 eta: 0:58:04 time: 0.5783 data_time: 0.0081 memory: 1637 loss: 1.3825 2023/04/14 00:42:47 - mmengine - INFO - Epoch(train) [9][3900/5005] lr: 3.3333e-05 eta: 0:57:09 time: 0.6284 data_time: 0.0084 memory: 1637 loss: 1.2912 2023/04/14 00:43:23 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:43:46 - mmengine - INFO - Epoch(train) [9][4000/5005] lr: 3.3333e-05 eta: 0:56:13 time: 0.5986 data_time: 0.0197 memory: 1637 loss: 1.5646 2023/04/14 00:44:46 - mmengine - INFO - Epoch(train) [9][4100/5005] lr: 3.3333e-05 eta: 0:55:17 time: 0.5905 data_time: 0.0094 memory: 1637 loss: 1.4303 2023/04/14 00:45:44 - mmengine - INFO - Epoch(train) [9][4200/5005] lr: 3.3333e-05 eta: 0:54:21 time: 0.5819 data_time: 0.0091 memory: 1637 loss: 1.2599 2023/04/14 00:46:45 - mmengine - INFO - Epoch(train) [9][4300/5005] lr: 3.3333e-05 eta: 0:53:26 time: 0.6177 data_time: 0.0100 memory: 1637 loss: 1.3843 2023/04/14 00:47:48 - mmengine - INFO - Epoch(train) [9][4400/5005] lr: 3.3333e-05 eta: 0:52:30 time: 0.6444 data_time: 0.0100 memory: 1637 loss: 1.1295 2023/04/14 00:48:52 - mmengine - INFO - Epoch(train) [9][4500/5005] lr: 3.3333e-05 eta: 0:51:35 time: 0.5784 data_time: 0.0105 memory: 1637 loss: 1.3535 2023/04/14 00:49:56 - mmengine - INFO - Epoch(train) [9][4600/5005] lr: 3.3333e-05 eta: 0:50:40 time: 0.6202 data_time: 0.0101 memory: 1637 loss: 1.2281 2023/04/14 00:50:59 - mmengine - INFO - Epoch(train) [9][4700/5005] lr: 3.3333e-05 eta: 0:49:45 time: 0.6966 data_time: 0.0113 memory: 1637 loss: 1.2874 2023/04/14 00:52:04 - mmengine - INFO - Epoch(train) [9][4800/5005] lr: 3.3333e-05 eta: 0:48:49 time: 0.6147 data_time: 0.0105 memory: 1637 loss: 1.3726 2023/04/14 00:53:09 - mmengine - INFO - Epoch(train) [9][4900/5005] lr: 3.3333e-05 eta: 0:47:54 time: 0.6209 data_time: 0.0098 memory: 1637 loss: 1.3008 2023/04/14 00:53:46 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:54:11 - mmengine - INFO - Epoch(train) [9][5000/5005] lr: 3.3333e-05 eta: 0:46:59 time: 0.6084 data_time: 0.0110 memory: 1637 loss: 1.3958 2023/04/14 00:54:14 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 00:54:15 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/04/14 00:54:44 - mmengine - INFO - Epoch(val) [9][100/196] eta: 0:00:26 time: 0.2415 data_time: 0.0094 memory: 1637 2023/04/14 00:56:06 - mmengine - INFO - Epoch(val) [9][196/196] qat.accuracy/top1: 69.9460 qat.accuracy/top5: 89.3860data_time: 0.0081 time: 0.4534 2023/04/14 00:56:10 - mmengine - INFO - Epoch(val) [9][100/196] eta: 0:00:03 time: 0.0334 data_time: 0.0149 memory: 967 2023/04/14 00:57:07 - mmengine - INFO - Epoch(val) [9][196/196] original.accuracy/top1: 69.9760 original.accuracy/top5: 89.4280data_time: 0.0180 time: 0.0346 2023/04/14 00:58:08 - mmengine - INFO - Epoch(train) [10][ 100/5005] lr: 1.0000e-04 eta: 0:46:00 time: 0.5957 data_time: 0.0083 memory: 1637 loss: 1.5164 2023/04/14 00:59:06 - mmengine - INFO - Epoch(train) [10][ 200/5005] lr: 1.0000e-04 eta: 0:45:04 time: 0.5719 data_time: 0.0084 memory: 1637 loss: 1.3650 2023/04/14 01:00:03 - mmengine - INFO - Epoch(train) [10][ 300/5005] lr: 1.0000e-04 eta: 0:44:08 time: 0.5601 data_time: 0.0083 memory: 1637 loss: 1.4592 2023/04/14 01:01:01 - mmengine - INFO - Epoch(train) [10][ 400/5005] lr: 1.0000e-04 eta: 0:43:11 time: 0.5548 data_time: 0.0085 memory: 1637 loss: 1.2503 2023/04/14 01:01:58 - mmengine - INFO - Epoch(train) [10][ 500/5005] lr: 1.0000e-04 eta: 0:42:15 time: 0.5933 data_time: 0.0080 memory: 1637 loss: 1.2636 2023/04/14 01:02:42 - mmengine - INFO - Epoch(train) [10][ 600/5005] lr: 1.0000e-04 eta: 0:41:18 time: 0.4385 data_time: 0.0084 memory: 1637 loss: 1.3553 2023/04/14 01:03:59 - mmengine - INFO - Epoch(train) [10][ 700/5005] lr: 1.0000e-04 eta: 0:40:23 time: 0.7513 data_time: 0.0104 memory: 1637 loss: 1.4163 2023/04/14 01:05:17 - mmengine - INFO - Epoch(train) [10][ 800/5005] lr: 1.0000e-04 eta: 0:39:29 time: 0.6210 data_time: 0.0088 memory: 1637 loss: 1.4721 2023/04/14 01:06:15 - mmengine - INFO - Epoch(train) [10][ 900/5005] lr: 1.0000e-04 eta: 0:38:33 time: 0.5674 data_time: 0.0083 memory: 1637 loss: 1.3814 2023/04/14 01:06:48 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 01:07:15 - mmengine - INFO - Epoch(train) [10][1000/5005] lr: 1.0000e-04 eta: 0:37:37 time: 0.5796 data_time: 0.0084 memory: 1637 loss: 1.3447 2023/04/14 01:08:13 - mmengine - INFO - Epoch(train) [10][1100/5005] lr: 1.0000e-04 eta: 0:36:41 time: 0.5837 data_time: 0.0082 memory: 1637 loss: 1.3673 2023/04/14 01:09:11 - mmengine - INFO - Epoch(train) [10][1200/5005] lr: 1.0000e-04 eta: 0:35:44 time: 0.5726 data_time: 0.0085 memory: 1637 loss: 1.2983 2023/04/14 01:10:09 - mmengine - INFO - Epoch(train) [10][1300/5005] lr: 1.0000e-04 eta: 0:34:48 time: 0.5603 data_time: 0.0089 memory: 1637 loss: 1.4947 2023/04/14 01:11:08 - mmengine - INFO - Epoch(train) [10][1400/5005] lr: 1.0000e-04 eta: 0:33:52 time: 0.5634 data_time: 0.0085 memory: 1637 loss: 1.3855 2023/04/14 01:12:06 - mmengine - INFO - Epoch(train) [10][1500/5005] lr: 1.0000e-04 eta: 0:32:56 time: 0.6185 data_time: 0.0081 memory: 1637 loss: 1.3503 2023/04/14 01:13:05 - mmengine - INFO - Epoch(train) [10][1600/5005] lr: 1.0000e-04 eta: 0:32:00 time: 0.5770 data_time: 0.0085 memory: 1637 loss: 1.4026 2023/04/14 01:14:03 - mmengine - INFO - Epoch(train) [10][1700/5005] lr: 1.0000e-04 eta: 0:31:03 time: 0.5660 data_time: 0.0082 memory: 1637 loss: 1.4392 2023/04/14 01:15:03 - mmengine - INFO - Epoch(train) [10][1800/5005] lr: 1.0000e-04 eta: 0:30:07 time: 0.5686 data_time: 0.0080 memory: 1637 loss: 1.6007 2023/04/14 01:16:02 - mmengine - INFO - Epoch(train) [10][1900/5005] lr: 1.0000e-04 eta: 0:29:11 time: 0.5688 data_time: 0.0087 memory: 1637 loss: 1.5106 2023/04/14 01:16:34 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 01:17:01 - mmengine - INFO - Epoch(train) [10][2000/5005] lr: 1.0000e-04 eta: 0:28:15 time: 0.6133 data_time: 0.0086 memory: 1637 loss: 1.2836 2023/04/14 01:17:58 - mmengine - INFO - Epoch(train) [10][2100/5005] lr: 1.0000e-04 eta: 0:27:18 time: 0.5535 data_time: 0.0088 memory: 1637 loss: 1.2854 2023/04/14 01:18:57 - mmengine - INFO - Epoch(train) [10][2200/5005] lr: 1.0000e-04 eta: 0:26:22 time: 0.5819 data_time: 0.0082 memory: 1637 loss: 1.3735 2023/04/14 01:19:58 - mmengine - INFO - Epoch(train) [10][2300/5005] lr: 1.0000e-04 eta: 0:25:26 time: 0.6437 data_time: 0.0085 memory: 1637 loss: 1.3459 2023/04/14 01:20:56 - mmengine - INFO - Epoch(train) [10][2400/5005] lr: 1.0000e-04 eta: 0:24:30 time: 0.5867 data_time: 0.0090 memory: 1637 loss: 1.3834 2023/04/14 01:21:56 - mmengine - INFO - Epoch(train) [10][2500/5005] lr: 1.0000e-04 eta: 0:23:33 time: 0.6000 data_time: 0.0098 memory: 1637 loss: 1.3768 2023/04/14 01:22:54 - mmengine - INFO - Epoch(train) [10][2600/5005] lr: 1.0000e-04 eta: 0:22:37 time: 0.6190 data_time: 0.0094 memory: 1637 loss: 1.4303 2023/04/14 01:23:53 - mmengine - INFO - Epoch(train) [10][2700/5005] lr: 1.0000e-04 eta: 0:21:41 time: 0.5756 data_time: 0.0091 memory: 1637 loss: 1.3368 2023/04/14 01:24:52 - mmengine - INFO - Epoch(train) [10][2800/5005] lr: 1.0000e-04 eta: 0:20:44 time: 0.6110 data_time: 0.0095 memory: 1637 loss: 1.3183 2023/04/14 01:25:51 - mmengine - INFO - Epoch(train) [10][2900/5005] lr: 1.0000e-04 eta: 0:19:48 time: 0.5726 data_time: 0.0095 memory: 1637 loss: 1.2104 2023/04/14 01:26:23 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 01:26:49 - mmengine - INFO - Epoch(train) [10][3000/5005] lr: 1.0000e-04 eta: 0:18:52 time: 0.6194 data_time: 0.0090 memory: 1637 loss: 1.2243 2023/04/14 01:27:48 - mmengine - INFO - Epoch(train) [10][3100/5005] lr: 1.0000e-04 eta: 0:17:55 time: 0.6554 data_time: 0.0086 memory: 1637 loss: 1.2606 2023/04/14 01:28:47 - mmengine - INFO - Epoch(train) [10][3200/5005] lr: 1.0000e-04 eta: 0:16:59 time: 0.5913 data_time: 0.0103 memory: 1637 loss: 1.4236 2023/04/14 01:29:46 - mmengine - INFO - Epoch(train) [10][3300/5005] lr: 1.0000e-04 eta: 0:16:02 time: 0.5773 data_time: 0.0092 memory: 1637 loss: 1.4315 2023/04/14 01:30:46 - mmengine - INFO - Epoch(train) [10][3400/5005] lr: 1.0000e-04 eta: 0:15:06 time: 0.6270 data_time: 0.0085 memory: 1637 loss: 1.2831 2023/04/14 01:31:44 - mmengine - INFO - Epoch(train) [10][3500/5005] lr: 1.0000e-04 eta: 0:14:10 time: 0.5734 data_time: 0.0084 memory: 1637 loss: 1.2629 2023/04/14 01:32:43 - mmengine - INFO - Epoch(train) [10][3600/5005] lr: 1.0000e-04 eta: 0:13:13 time: 0.5935 data_time: 0.0093 memory: 1637 loss: 1.2946 2023/04/14 01:33:43 - mmengine - INFO - Epoch(train) [10][3700/5005] lr: 1.0000e-04 eta: 0:12:17 time: 0.5666 data_time: 0.0087 memory: 1637 loss: 1.2880 2023/04/14 01:34:42 - mmengine - INFO - Epoch(train) [10][3800/5005] lr: 1.0000e-04 eta: 0:11:20 time: 0.5724 data_time: 0.0087 memory: 1637 loss: 1.5519 2023/04/14 01:35:42 - mmengine - INFO - Epoch(train) [10][3900/5005] lr: 1.0000e-04 eta: 0:10:24 time: 0.5856 data_time: 0.0092 memory: 1637 loss: 1.2643 2023/04/14 01:36:13 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 01:36:40 - mmengine - INFO - Epoch(train) [10][4000/5005] lr: 1.0000e-04 eta: 0:09:27 time: 0.6004 data_time: 0.0096 memory: 1637 loss: 1.2345 2023/04/14 01:37:38 - mmengine - INFO - Epoch(train) [10][4100/5005] lr: 1.0000e-04 eta: 0:08:31 time: 0.5637 data_time: 0.0092 memory: 1637 loss: 1.4546 2023/04/14 01:38:37 - mmengine - INFO - Epoch(train) [10][4200/5005] lr: 1.0000e-04 eta: 0:07:35 time: 0.5517 data_time: 0.0095 memory: 1637 loss: 1.2690 2023/04/14 01:39:36 - mmengine - INFO - Epoch(train) [10][4300/5005] lr: 1.0000e-04 eta: 0:06:38 time: 0.5941 data_time: 0.0090 memory: 1637 loss: 1.2833 2023/04/14 01:40:35 - mmengine - INFO - Epoch(train) [10][4400/5005] lr: 1.0000e-04 eta: 0:05:42 time: 0.5895 data_time: 0.0089 memory: 1637 loss: 1.2279 2023/04/14 01:41:34 - mmengine - INFO - Epoch(train) [10][4500/5005] lr: 1.0000e-04 eta: 0:04:45 time: 0.5856 data_time: 0.0090 memory: 1637 loss: 1.3920 2023/04/14 01:42:34 - mmengine - INFO - Epoch(train) [10][4600/5005] lr: 1.0000e-04 eta: 0:03:49 time: 0.6391 data_time: 0.0089 memory: 1637 loss: 1.5156 2023/04/14 01:43:33 - mmengine - INFO - Epoch(train) [10][4700/5005] lr: 1.0000e-04 eta: 0:02:52 time: 0.5840 data_time: 0.0093 memory: 1637 loss: 1.2429 2023/04/14 01:44:30 - mmengine - INFO - Epoch(train) [10][4800/5005] lr: 1.0000e-04 eta: 0:01:55 time: 0.5519 data_time: 0.0084 memory: 1637 loss: 1.2965 2023/04/14 01:45:27 - mmengine - INFO - Epoch(train) [10][4900/5005] lr: 1.0000e-04 eta: 0:00:59 time: 0.5933 data_time: 0.0084 memory: 1637 loss: 1.2946 2023/04/14 01:45:59 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 01:46:25 - mmengine - INFO - Epoch(train) [10][5000/5005] lr: 1.0000e-04 eta: 0:00:02 time: 0.6029 data_time: 0.0095 memory: 1637 loss: 1.5318 2023/04/14 01:46:27 - mmengine - INFO - Exp name: qat_openvino_r18_20230413_172732 2023/04/14 01:46:28 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/04/14 01:46:55 - mmengine - INFO - Epoch(val) [10][100/196] eta: 0:00:24 time: 0.2053 data_time: 0.0079 memory: 1637 2023/04/14 01:48:06 - mmengine - INFO - Epoch(val) [10][196/196] qat.accuracy/top1: 69.8480 qat.accuracy/top5: 89.3580data_time: 0.0077 time: 0.2193 2023/04/14 01:48:11 - mmengine - INFO - Epoch(val) [10][100/196] eta: 0:00:04 time: 0.0329 data_time: 0.0143 memory: 967 2023/04/14 01:49:06 - mmengine - INFO - Epoch(val) [10][196/196] original.accuracy/top1: 69.9860 original.accuracy/top5: 89.4600data_time: 0.0131 time: 0.0331