2023/03/22 05:34:57 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.13 (default, Oct 21 2022, 23:50:54) [GCC 11.2.0] CUDA available: True numpy_random_seed: 968612448 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/share/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 5.4.0 PyTorch: 1.11.0+cu113 PyTorch compiling details: PyTorch built with: - GCC 7.3 - 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 v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - 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 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -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 -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -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 -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0+cu113 OpenCV: 4.6.0 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 Distributed launcher: slurm Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/03/22 05:34:59 - mmengine - INFO - Config: default_scope = 'mmdet3d' default_hooks = dict( timer=dict(type='IterTimerHook', _scope_='mmdet3d'), logger=dict(type='LoggerHook', interval=50, _scope_='mmdet3d'), param_scheduler=dict(type='ParamSchedulerHook', _scope_='mmdet3d'), checkpoint=dict(type='CheckpointHook', interval=5, _scope_='mmdet3d'), sampler_seed=dict(type='DistSamplerSeedHook', _scope_='mmdet3d'), visualization=dict(type='Det3DVisualizationHook', _scope_='mmdet3d')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict( type='LogProcessor', window_size=50, by_epoch=True, _scope_='mmdet3d') log_level = 'INFO' load_from = 'checkpoints/bevfusion_init_converted.pth' resume = False custom_imports = dict( imports=['projects.BEVFusion.bevfusion'], allow_failed_imports=False) voxel_size = [0.075, 0.075, 0.2] point_cloud_range = [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0] class_names = [ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ] metainfo = dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]) dataset_type = 'NuScenesDataset' data_root = 'data/nuscenes/' data_prefix = dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP') input_modality = dict(use_lidar=True, use_camera=False) backend_args = None model = dict( type='BEVFusion', data_preprocessor=dict( type='Det3DDataPreprocessor', pad_size_divisor=32, voxelize_cfg=dict( max_num_points=10, point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0], voxel_size=[0.075, 0.075, 0.2], max_voxels=[120000, 160000], voxelize_reduce=True)), pts_voxel_encoder=dict(type='HardSimpleVFE', num_features=5), pts_middle_encoder=dict( type='BEVFusionSparseEncoder', in_channels=5, sparse_shape=[1440, 1440, 41], order=('conv', 'norm', 'act'), norm_cfg=dict(type='SyncBN', eps=0.001, momentum=0.01), encoder_channels=((16, 16, 32), (32, 32, 64), (64, 64, 128), (128, 128)), encoder_paddings=((0, 0, 1), (0, 0, 1), (0, 0, (1, 1, 0)), (0, 0)), block_type='basicblock'), pts_backbone=dict( type='SECOND', in_channels=256, out_channels=[128, 256], layer_nums=[5, 5], layer_strides=[1, 2], norm_cfg=dict(type='SyncBN', eps=0.001, momentum=0.01), conv_cfg=dict(type='Conv2d', bias=False)), pts_neck=dict( type='SECONDFPN', in_channels=[128, 256], out_channels=[256, 256], upsample_strides=[1, 2], norm_cfg=dict(type='SyncBN', eps=0.001, momentum=0.01), upsample_cfg=dict(type='deconv', bias=False), use_conv_for_no_stride=True), bbox_head=dict( type='TransFusionHead', num_proposals=200, auxiliary=True, in_channels=512, hidden_channel=128, num_classes=10, nms_kernel_size=3, bn_momentum=0.1, num_decoder_layers=1, decoder_layer=dict( type='TransformerDecoderLayer', self_attn_cfg=dict(embed_dims=128, num_heads=8, dropout=0.1), cross_attn_cfg=dict(embed_dims=128, num_heads=8, dropout=0.1), ffn_cfg=dict( embed_dims=128, feedforward_channels=256, num_fcs=2, ffn_drop=0.1, act_cfg=dict(type='ReLU', inplace=True)), norm_cfg=dict(type='LN'), pos_encoding_cfg=dict(input_channel=2, num_pos_feats=128)), train_cfg=dict( dataset='nuScenes', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0], grid_size=[1440, 1440, 41], voxel_size=[0.075, 0.075, 0.2], out_size_factor=8, gaussian_overlap=0.1, min_radius=2, pos_weight=-1, code_weights=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2], assigner=dict( type='HungarianAssigner3D', iou_calculator=dict(type='BboxOverlaps3D', coordinate='lidar'), cls_cost=dict( type='mmdet.FocalLossCost', gamma=2.0, alpha=0.25, weight=0.15), reg_cost=dict(type='BBoxBEVL1Cost', weight=0.25), iou_cost=dict(type='IoU3DCost', weight=0.25))), test_cfg=dict( dataset='nuScenes', grid_size=[1440, 1440, 41], out_size_factor=8, voxel_size=[0.075, 0.075], pc_range=[-54.0, -54.0], nms_type=None), common_heads=dict( center=[2, 2], height=[1, 2], dim=[3, 2], rot=[2, 2], vel=[2, 2]), bbox_coder=dict( type='TransFusionBBoxCoder', pc_range=[-54.0, -54.0], post_center_range=[-61.2, -61.2, -10.0, 61.2, 61.2, 10.0], score_threshold=0.0, out_size_factor=8, voxel_size=[0.075, 0.075], code_size=10), loss_cls=dict( type='mmdet.FocalLoss', use_sigmoid=True, gamma=2.0, alpha=0.25, reduction='mean', loss_weight=1.0), loss_heatmap=dict( type='mmdet.GaussianFocalLoss', reduction='mean', loss_weight=1.0), loss_bbox=dict( type='mmdet.L1Loss', reduction='mean', loss_weight=0.25))) db_sampler = dict( data_root='data/nuscenes/', info_path='data/nuscenes/nuscenes_dbinfos_train.pkl', rate=1.0, prepare=dict( filter_by_difficulty=[-1], filter_by_min_points=dict( car=5, truck=5, bus=5, trailer=5, construction_vehicle=5, traffic_cone=5, barrier=5, motorcycle=5, bicycle=5, pedestrian=5)), classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ], sample_groups=dict( car=2, truck=3, construction_vehicle=7, bus=4, trailer=6, barrier=2, motorcycle=6, bicycle=6, pedestrian=2, traffic_cone=2), points_loader=dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=[0, 1, 2, 3, 4], backend_args=None)) train_pipeline = [ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True, with_attr_label=False), dict( type='ObjectSample', db_sampler=dict( data_root='data/nuscenes/', info_path='data/nuscenes/nuscenes_dbinfos_train.pkl', rate=1.0, prepare=dict( filter_by_difficulty=[-1], filter_by_min_points=dict( car=5, truck=5, bus=5, trailer=5, construction_vehicle=5, traffic_cone=5, barrier=5, motorcycle=5, bicycle=5, pedestrian=5)), classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ], sample_groups=dict( car=2, truck=3, construction_vehicle=7, bus=4, trailer=6, barrier=2, motorcycle=6, bicycle=6, pedestrian=2, traffic_cone=2), points_loader=dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=[0, 1, 2, 3, 4], backend_args=None))), dict( type='GlobalRotScaleTrans', scale_ratio_range=[0.9, 1.1], rot_range=[-0.78539816, 0.78539816], translation_std=0.5), dict(type='BEVFusionRandomFlip3D'), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectNameFilter', classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), dict(type='PointShuffle'), dict( type='Pack3DDetInputs', keys=[ 'points', 'img', 'gt_bboxes_3d', 'gt_labels_3d', 'gt_bboxes', 'gt_labels' ], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path', 'transformation_3d_flow', 'pcd_rotation', 'pcd_scale_factor', 'pcd_trans', 'img_aug_matrix', 'lidar_aug_matrix' ]) ] test_pipeline = [ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='Pack3DDetInputs', keys=['img', 'points', 'gt_bboxes_3d', 'gt_labels_3d'], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path' ]) ] train_dataloader = dict( batch_size=4, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='CBGSDataset', dataset=dict( type='NuScenesDataset', data_root='data/nuscenes/', ann_file='nuscenes_infos_train.pkl', pipeline=[ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='LoadAnnotations3D', with_bbox_3d=True, with_label_3d=True, with_attr_label=False), dict( type='ObjectSample', db_sampler=dict( data_root='data/nuscenes/', info_path='data/nuscenes/nuscenes_dbinfos_train.pkl', rate=1.0, prepare=dict( filter_by_difficulty=[-1], filter_by_min_points=dict( car=5, truck=5, bus=5, trailer=5, construction_vehicle=5, traffic_cone=5, barrier=5, motorcycle=5, bicycle=5, pedestrian=5)), classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ], sample_groups=dict( car=2, truck=3, construction_vehicle=7, bus=4, trailer=6, barrier=2, motorcycle=6, bicycle=6, pedestrian=2, traffic_cone=2), points_loader=dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=[0, 1, 2, 3, 4], backend_args=None))), dict( type='GlobalRotScaleTrans', scale_ratio_range=[0.9, 1.1], rot_range=[-0.78539816, 0.78539816], translation_std=0.5), dict(type='BEVFusionRandomFlip3D'), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='ObjectNameFilter', classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), dict(type='PointShuffle'), dict( type='Pack3DDetInputs', keys=[ 'points', 'img', 'gt_bboxes_3d', 'gt_labels_3d', 'gt_bboxes', 'gt_labels' ], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path', 'transformation_3d_flow', 'pcd_rotation', 'pcd_scale_factor', 'pcd_trans', 'img_aug_matrix', 'lidar_aug_matrix' ]) ], metainfo=dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), modality=dict(use_lidar=True, use_camera=False), test_mode=False, data_prefix=dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP'), use_valid_flag=True, box_type_3d='LiDAR'))) val_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='NuScenesDataset', data_root='data/nuscenes/', ann_file='nuscenes_infos_val.pkl', pipeline=[ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='Pack3DDetInputs', keys=['img', 'points', 'gt_bboxes_3d', 'gt_labels_3d'], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path' ]) ], metainfo=dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), modality=dict(use_lidar=True, use_camera=False), data_prefix=dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP'), test_mode=True, box_type_3d='LiDAR', backend_args=None)) test_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='NuScenesDataset', data_root='data/nuscenes/', ann_file='nuscenes_infos_val.pkl', pipeline=[ dict( type='LoadPointsFromFile', coord_type='LIDAR', load_dim=5, use_dim=5, backend_args=None), dict( type='LoadPointsFromMultiSweeps', sweeps_num=9, load_dim=5, use_dim=5, pad_empty_sweeps=True, remove_close=True, backend_args=None), dict( type='PointsRangeFilter', point_cloud_range=[-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]), dict( type='Pack3DDetInputs', keys=['img', 'points', 'gt_bboxes_3d', 'gt_labels_3d'], meta_keys=[ 'cam2img', 'ori_cam2img', 'lidar2cam', 'lidar2img', 'cam2lidar', 'ori_lidar2img', 'img_aug_matrix', 'box_type_3d', 'sample_idx', 'lidar_path', 'img_path' ]) ], metainfo=dict(classes=[ 'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier', 'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone' ]), modality=dict(use_lidar=True, use_camera=False), data_prefix=dict( pts='samples/LIDAR_TOP', CAM_FRONT='samples/CAM_FRONT', CAM_FRONT_LEFT='samples/CAM_FRONT_LEFT', CAM_FRONT_RIGHT='samples/CAM_FRONT_RIGHT', CAM_BACK='samples/CAM_BACK', CAM_BACK_RIGHT='samples/CAM_BACK_RIGHT', CAM_BACK_LEFT='samples/CAM_BACK_LEFT', sweeps='sweeps/LIDAR_TOP'), test_mode=True, box_type_3d='LiDAR', backend_args=None)) val_evaluator = dict( type='NuScenesMetric', data_root='data/nuscenes/', ann_file='data/nuscenes/nuscenes_infos_val.pkl', metric='bbox', backend_args=None) test_evaluator = dict( type='NuScenesMetric', data_root='data/nuscenes/', ann_file='data/nuscenes/nuscenes_infos_val.pkl', metric='bbox', backend_args=None) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='Det3DLocalVisualizer', vis_backends=[dict(type='LocalVisBackend')], name='visualizer') lr = 0.0001 param_scheduler = [ dict( type='CosineAnnealingLR', T_max=8, eta_min=0.001, begin=0, end=8, by_epoch=True, convert_to_iter_based=True), dict( type='CosineAnnealingLR', T_max=12, eta_min=1e-08, begin=8, end=20, by_epoch=True, convert_to_iter_based=True), dict( type='CosineAnnealingMomentum', T_max=8, eta_min=0.8947368421052632, begin=0, end=8, by_epoch=True, convert_to_iter_based=True), dict( type='CosineAnnealingMomentum', T_max=12, eta_min=1, begin=8, end=20, by_epoch=True, convert_to_iter_based=True) ] train_cfg = dict(by_epoch=True, max_epochs=20, val_interval=5) val_cfg = dict() test_cfg = dict() optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='AdamW', lr=0.0001, weight_decay=0.01), clip_grad=dict(max_norm=35, norm_type=2)) auto_scale_lr = dict(enable=False, base_batch_size=32) custom_hooks = [dict(type='DisableObjectSampleHook', disable_after_epoch=15)] launcher = 'slurm' work_dir = 'logs/bevfusion_only_lidar_valid_flag' 2023/03/22 05:35:02 - 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 (NORMAL ) DisableObjectSampleHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) Det3DVisualizationHook (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 ) Det3DVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/03/22 05:35:06 - mmengine - INFO - load 62964 traffic_cone database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 65262 truck database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 339949 car database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 161928 pedestrian database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 133804 barrier database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 11050 construction_vehicle database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 8846 motorcycle database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 8185 bicycle database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 12286 bus database infos in DataBaseSampler 2023/03/22 05:35:06 - mmengine - INFO - load 19202 trailer database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - After filter database: 2023/03/22 05:35:08 - mmengine - INFO - load 56455 traffic_cone database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 60691 truck database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 296423 car database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 149198 pedestrian database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 127358 barrier database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 10622 construction_vehicle database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 8094 motorcycle database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 7565 bicycle database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 11662 bus database infos in DataBaseSampler 2023/03/22 05:35:08 - mmengine - INFO - load 18165 trailer database infos in DataBaseSampler 2023/03/22 05:36:44 - mmengine - INFO - ------------------------------ 2023/03/22 05:36:44 - mmengine - INFO - The length of the dataset: 28130 2023/03/22 05:36:44 - mmengine - INFO - The number of instances per category in the dataset: +----------------------+--------+ | category | number | +----------------------+--------+ | car | 413318 | | truck | 72815 | | construction_vehicle | 11993 | | bus | 13163 | | trailer | 20701 | | barrier | 125095 | | motorcycle | 10109 | | bicycle | 9478 | | pedestrian | 185847 | | traffic_cone | 82362 | +----------------------+--------+ 2023/03/22 05:37:15 - mmengine - INFO - ------------------------------ 2023/03/22 05:37:15 - mmengine - INFO - The length of the dataset: 6019 2023/03/22 05:37:15 - mmengine - INFO - The number of instances per category in the dataset: +----------------------+--------+ | category | number | +----------------------+--------+ | car | 80004 | | truck | 15704 | | construction_vehicle | 2678 | | bus | 3158 | | trailer | 4159 | | barrier | 26992 | | motorcycle | 2508 | | bicycle | 2381 | | pedestrian | 34347 | | traffic_cone | 15597 | +----------------------+--------+ 2023/03/22 05:37:20 - mmengine - INFO - Load checkpoint from checkpoints/bevfusion_init_converted.pth 2023/03/22 05:37:20 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/03/22 05:37:20 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/03/22 05:37:20 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/zhangjingwei/mmdetection3d_1/logs/bevfusion_only_lidar_valid_flag. 2023/03/22 05:38:52 - mmengine - INFO - Epoch(train) [1][ 50/3862] lr: 1.0001e-04 eta: 1 day, 15:09:46 time: 1.8265 data_time: 0.1466 memory: 8898 grad_norm: 1460.0667 loss: 247.8320 loss_heatmap: 232.7598 layer_-1_loss_cls: 4.3022 layer_-1_loss_bbox: 10.7700 matched_ious: 0.0115 2023/03/22 05:39:44 - mmengine - INFO - Epoch(train) [1][ 100/3862] lr: 1.0002e-04 eta: 1 day, 6:51:16 time: 1.0534 data_time: 0.0079 memory: 9367 grad_norm: 10.5844 loss: 13.0007 loss_heatmap: 3.2051 layer_-1_loss_cls: 2.8151 layer_-1_loss_bbox: 6.9805 matched_ious: 0.0532 2023/03/22 05:40:37 - mmengine - INFO - Epoch(train) [1][ 150/3862] lr: 1.0005e-04 eta: 1 day, 4:05:57 time: 1.0567 data_time: 0.0078 memory: 9328 grad_norm: 6.5619 loss: 8.7872 loss_heatmap: 2.6401 layer_-1_loss_cls: 1.7953 layer_-1_loss_bbox: 4.3518 matched_ious: 0.0939 2023/03/22 05:41:30 - mmengine - INFO - Epoch(train) [1][ 200/3862] lr: 1.0009e-04 eta: 1 day, 2:41:50 time: 1.0536 data_time: 0.0079 memory: 9087 grad_norm: 5.7808 loss: 7.4082 loss_heatmap: 2.3716 layer_-1_loss_cls: 1.3374 layer_-1_loss_bbox: 3.6991 matched_ious: 0.1115 2023/03/22 05:42:24 - mmengine - INFO - Epoch(train) [1][ 250/3862] lr: 1.0014e-04 eta: 1 day, 1:56:33 time: 1.0752 data_time: 0.0080 memory: 9039 grad_norm: 5.0743 loss: 6.3387 loss_heatmap: 2.1457 layer_-1_loss_cls: 1.0696 layer_-1_loss_bbox: 3.1234 matched_ious: 0.1051 2023/03/22 05:43:17 - mmengine - INFO - Epoch(train) [1][ 300/3862] lr: 1.0021e-04 eta: 1 day, 1:24:12 time: 1.0664 data_time: 0.0079 memory: 9114 grad_norm: 5.2604 loss: 5.7290 loss_heatmap: 2.0123 layer_-1_loss_cls: 0.8935 layer_-1_loss_bbox: 2.8231 matched_ious: 0.1637 2023/03/22 05:44:10 - mmengine - INFO - Epoch(train) [1][ 350/3862] lr: 1.0028e-04 eta: 1 day, 0:59:25 time: 1.0587 data_time: 0.0079 memory: 9086 grad_norm: 4.9743 loss: 5.4312 loss_heatmap: 1.9376 layer_-1_loss_cls: 0.7597 layer_-1_loss_bbox: 2.7339 matched_ious: 0.1268 2023/03/22 05:45:03 - mmengine - INFO - Epoch(train) [1][ 400/3862] lr: 1.0037e-04 eta: 1 day, 0:41:19 time: 1.0631 data_time: 0.0081 memory: 9094 grad_norm: 4.8242 loss: 4.8999 loss_heatmap: 1.8061 layer_-1_loss_cls: 0.6635 layer_-1_loss_bbox: 2.4304 matched_ious: 0.1982 2023/03/22 05:45:56 - mmengine - INFO - Epoch(train) [1][ 450/3862] lr: 1.0047e-04 eta: 1 day, 0:27:19 time: 1.0650 data_time: 0.0080 memory: 9011 grad_norm: 5.0948 loss: 4.4924 loss_heatmap: 1.6888 layer_-1_loss_cls: 0.5832 layer_-1_loss_bbox: 2.2204 matched_ious: 0.1607 2023/03/22 05:46:50 - mmengine - INFO - Epoch(train) [1][ 500/3862] lr: 1.0058e-04 eta: 1 day, 0:17:10 time: 1.0746 data_time: 0.0081 memory: 9022 grad_norm: 4.5275 loss: 4.4164 loss_heatmap: 1.6863 layer_-1_loss_cls: 0.5507 layer_-1_loss_bbox: 2.1794 matched_ious: 0.2238 2023/03/22 05:47:44 - mmengine - INFO - Epoch(train) [1][ 550/3862] lr: 1.0070e-04 eta: 1 day, 0:08:55 time: 1.0764 data_time: 0.0082 memory: 9269 grad_norm: 4.6357 loss: 4.2997 loss_heatmap: 1.6319 layer_-1_loss_cls: 0.4976 layer_-1_loss_bbox: 2.1701 matched_ious: 0.1910 2023/03/22 05:48:36 - mmengine - INFO - Epoch(train) [1][ 600/3862] lr: 1.0083e-04 eta: 23:58:26 time: 1.0440 data_time: 0.0088 memory: 9112 grad_norm: 4.4932 loss: 4.0483 loss_heatmap: 1.5797 layer_-1_loss_cls: 0.4711 layer_-1_loss_bbox: 1.9974 matched_ious: 0.2191 2023/03/22 05:49:29 - mmengine - INFO - Epoch(train) [1][ 650/3862] lr: 1.0098e-04 eta: 23:51:01 time: 1.0602 data_time: 0.0086 memory: 9049 grad_norm: 4.4373 loss: 3.8478 loss_heatmap: 1.5552 layer_-1_loss_cls: 0.4552 layer_-1_loss_bbox: 1.8374 matched_ious: 0.2406 2023/03/22 05:50:22 - mmengine - INFO - Epoch(train) [1][ 700/3862] lr: 1.0114e-04 eta: 23:44:05 time: 1.0552 data_time: 0.0084 memory: 9463 grad_norm: 4.6125 loss: 3.8737 loss_heatmap: 1.4913 layer_-1_loss_cls: 0.4105 layer_-1_loss_bbox: 1.9719 matched_ious: 0.2238 2023/03/22 05:51:15 - mmengine - INFO - Epoch(train) [1][ 750/3862] lr: 1.0130e-04 eta: 23:38:32 time: 1.0619 data_time: 0.0083 memory: 9044 grad_norm: 4.4663 loss: 3.7144 loss_heatmap: 1.4703 layer_-1_loss_cls: 0.4003 layer_-1_loss_bbox: 1.8438 matched_ious: 0.2428 2023/03/22 05:52:08 - mmengine - INFO - Epoch(train) [1][ 800/3862] lr: 1.0148e-04 eta: 23:33:35 time: 1.0623 data_time: 0.0083 memory: 8979 grad_norm: 4.5562 loss: 3.7757 loss_heatmap: 1.4963 layer_-1_loss_cls: 0.3928 layer_-1_loss_bbox: 1.8866 matched_ious: 0.2726 2023/03/22 05:53:01 - mmengine - INFO - Epoch(train) [1][ 850/3862] lr: 1.0168e-04 eta: 23:29:27 time: 1.0668 data_time: 0.0085 memory: 9001 grad_norm: 4.4711 loss: 3.5787 loss_heatmap: 1.4347 layer_-1_loss_cls: 0.3754 layer_-1_loss_bbox: 1.7687 matched_ious: 0.2708 2023/03/22 05:53:54 - mmengine - INFO - Epoch(train) [1][ 900/3862] lr: 1.0188e-04 eta: 23:24:45 time: 1.0534 data_time: 0.0084 memory: 8985 grad_norm: 4.1544 loss: 3.5409 loss_heatmap: 1.3919 layer_-1_loss_cls: 0.3594 layer_-1_loss_bbox: 1.7895 matched_ious: 0.2485 2023/03/22 05:54:47 - mmengine - INFO - Epoch(train) [1][ 950/3862] lr: 1.0209e-04 eta: 23:20:41 time: 1.0573 data_time: 0.0082 memory: 8977 grad_norm: 4.2975 loss: 3.4580 loss_heatmap: 1.3817 layer_-1_loss_cls: 0.3477 layer_-1_loss_bbox: 1.7286 matched_ious: 0.2108 2023/03/22 05:55:40 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 05:55:40 - mmengine - INFO - Epoch(train) [1][1000/3862] lr: 1.0232e-04 eta: 23:17:40 time: 1.0685 data_time: 0.0084 memory: 9285 grad_norm: 4.2848 loss: 3.5371 loss_heatmap: 1.3952 layer_-1_loss_cls: 0.3398 layer_-1_loss_bbox: 1.8021 matched_ious: 0.2514 2023/03/22 05:56:33 - mmengine - INFO - Epoch(train) [1][1050/3862] lr: 1.0256e-04 eta: 23:14:03 time: 1.0554 data_time: 0.0090 memory: 9210 grad_norm: 4.1147 loss: 3.4437 loss_heatmap: 1.3610 layer_-1_loss_cls: 0.3284 layer_-1_loss_bbox: 1.7543 matched_ious: 0.3055 2023/03/22 05:57:26 - mmengine - INFO - Epoch(train) [1][1100/3862] lr: 1.0281e-04 eta: 23:10:53 time: 1.0586 data_time: 0.0097 memory: 9033 grad_norm: 4.2110 loss: 3.3426 loss_heatmap: 1.3340 layer_-1_loss_cls: 0.3241 layer_-1_loss_bbox: 1.6844 matched_ious: 0.2819 2023/03/22 05:58:19 - mmengine - INFO - Epoch(train) [1][1150/3862] lr: 1.0307e-04 eta: 23:08:10 time: 1.0635 data_time: 0.0098 memory: 9031 grad_norm: 3.9431 loss: 3.3444 loss_heatmap: 1.3284 layer_-1_loss_cls: 0.3192 layer_-1_loss_bbox: 1.6968 matched_ious: 0.2282 2023/03/22 05:59:13 - mmengine - INFO - Epoch(train) [1][1200/3862] lr: 1.0334e-04 eta: 23:06:40 time: 1.0835 data_time: 0.0097 memory: 9299 grad_norm: 3.9873 loss: 3.3450 loss_heatmap: 1.3111 layer_-1_loss_cls: 0.3131 layer_-1_loss_bbox: 1.7208 matched_ious: 0.2572 2023/03/22 06:00:07 - mmengine - INFO - Epoch(train) [1][1250/3862] lr: 1.0362e-04 eta: 23:04:08 time: 1.0622 data_time: 0.0099 memory: 9006 grad_norm: 4.0309 loss: 3.3857 loss_heatmap: 1.3314 layer_-1_loss_cls: 0.3063 layer_-1_loss_bbox: 1.7480 matched_ious: 0.2423 2023/03/22 06:00:59 - mmengine - INFO - Epoch(train) [1][1300/3862] lr: 1.0392e-04 eta: 23:01:16 time: 1.0527 data_time: 0.0098 memory: 9218 grad_norm: 4.0752 loss: 3.1873 loss_heatmap: 1.2494 layer_-1_loss_cls: 0.2926 layer_-1_loss_bbox: 1.6454 matched_ious: 0.2556 2023/03/22 06:01:53 - mmengine - INFO - Epoch(train) [1][1350/3862] lr: 1.0423e-04 eta: 22:59:35 time: 1.0747 data_time: 0.0098 memory: 9086 grad_norm: 4.0847 loss: 3.2202 loss_heatmap: 1.2655 layer_-1_loss_cls: 0.2911 layer_-1_loss_bbox: 1.6637 matched_ious: 0.2417 2023/03/22 06:02:46 - mmengine - INFO - Epoch(train) [1][1400/3862] lr: 1.0455e-04 eta: 22:57:07 time: 1.0561 data_time: 0.0100 memory: 8913 grad_norm: 3.9667 loss: 3.2090 loss_heatmap: 1.2564 layer_-1_loss_cls: 0.2829 layer_-1_loss_bbox: 1.6698 matched_ious: 0.2532 2023/03/22 06:03:39 - mmengine - INFO - Epoch(train) [1][1450/3862] lr: 1.0488e-04 eta: 22:55:22 time: 1.0704 data_time: 0.0100 memory: 9308 grad_norm: 4.0715 loss: 3.1925 loss_heatmap: 1.2585 layer_-1_loss_cls: 0.2856 layer_-1_loss_bbox: 1.6483 matched_ious: 0.2805 2023/03/22 06:04:34 - mmengine - INFO - Epoch(train) [1][1500/3862] lr: 1.0522e-04 eta: 22:54:19 time: 1.0854 data_time: 0.0097 memory: 9302 grad_norm: 4.1395 loss: 3.1676 loss_heatmap: 1.2599 layer_-1_loss_cls: 0.2843 layer_-1_loss_bbox: 1.6235 matched_ious: 0.2499 2023/03/22 06:05:27 - mmengine - INFO - Epoch(train) [1][1550/3862] lr: 1.0557e-04 eta: 22:52:25 time: 1.0640 data_time: 0.0101 memory: 9053 grad_norm: 3.9250 loss: 3.1191 loss_heatmap: 1.2018 layer_-1_loss_cls: 0.2688 layer_-1_loss_bbox: 1.6485 matched_ious: 0.2516 2023/03/22 06:06:20 - mmengine - INFO - Epoch(train) [1][1600/3862] lr: 1.0593e-04 eta: 22:50:38 time: 1.0658 data_time: 0.0103 memory: 8957 grad_norm: 3.8708 loss: 3.0436 loss_heatmap: 1.1857 layer_-1_loss_cls: 0.2639 layer_-1_loss_bbox: 1.5940 matched_ious: 0.2535 2023/03/22 06:07:13 - mmengine - INFO - Epoch(train) [1][1650/3862] lr: 1.0631e-04 eta: 22:48:54 time: 1.0654 data_time: 0.0099 memory: 9208 grad_norm: 3.8529 loss: 3.1531 loss_heatmap: 1.2277 layer_-1_loss_cls: 0.2640 layer_-1_loss_bbox: 1.6614 matched_ious: 0.2533 2023/03/22 06:08:06 - mmengine - INFO - Epoch(train) [1][1700/3862] lr: 1.0670e-04 eta: 22:46:47 time: 1.0542 data_time: 0.0099 memory: 9296 grad_norm: 3.8567 loss: 3.0845 loss_heatmap: 1.2062 layer_-1_loss_cls: 0.2606 layer_-1_loss_bbox: 1.6177 matched_ious: 0.3171 2023/03/22 06:08:59 - mmengine - INFO - Epoch(train) [1][1750/3862] lr: 1.0710e-04 eta: 22:44:37 time: 1.0501 data_time: 0.0097 memory: 9261 grad_norm: 3.8850 loss: 3.0228 loss_heatmap: 1.1958 layer_-1_loss_cls: 0.2556 layer_-1_loss_bbox: 1.5714 matched_ious: 0.3014 2023/03/22 06:09:52 - mmengine - INFO - Epoch(train) [1][1800/3862] lr: 1.0751e-04 eta: 22:42:52 time: 1.0607 data_time: 0.0098 memory: 9338 grad_norm: 3.9144 loss: 3.0981 loss_heatmap: 1.2000 layer_-1_loss_cls: 0.2546 layer_-1_loss_bbox: 1.6435 matched_ious: 0.3139 2023/03/22 06:10:45 - mmengine - INFO - Epoch(train) [1][1850/3862] lr: 1.0793e-04 eta: 22:41:35 time: 1.0725 data_time: 0.0099 memory: 9069 grad_norm: 3.8142 loss: 3.0875 loss_heatmap: 1.1791 layer_-1_loss_cls: 0.2476 layer_-1_loss_bbox: 1.6608 matched_ious: 0.2981 2023/03/22 06:11:39 - mmengine - INFO - Epoch(train) [1][1900/3862] lr: 1.0836e-04 eta: 22:40:11 time: 1.0687 data_time: 0.0096 memory: 9065 grad_norm: 3.7519 loss: 2.9850 loss_heatmap: 1.1760 layer_-1_loss_cls: 0.2510 layer_-1_loss_bbox: 1.5579 matched_ious: 0.3160 2023/03/22 06:12:32 - mmengine - INFO - Epoch(train) [1][1950/3862] lr: 1.0881e-04 eta: 22:38:45 time: 1.0666 data_time: 0.0103 memory: 9071 grad_norm: 3.9908 loss: 2.9669 loss_heatmap: 1.1683 layer_-1_loss_cls: 0.2427 layer_-1_loss_bbox: 1.5559 matched_ious: 0.3133 2023/03/22 06:13:26 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 06:13:26 - mmengine - INFO - Epoch(train) [1][2000/3862] lr: 1.0926e-04 eta: 22:37:43 time: 1.0789 data_time: 0.0098 memory: 9372 grad_norm: 3.9382 loss: 2.9499 loss_heatmap: 1.1717 layer_-1_loss_cls: 0.2458 layer_-1_loss_bbox: 1.5324 matched_ious: 0.3564 2023/03/22 06:14:19 - mmengine - INFO - Epoch(train) [1][2050/3862] lr: 1.0973e-04 eta: 22:36:00 time: 1.0558 data_time: 0.0101 memory: 9062 grad_norm: 3.7696 loss: 2.8850 loss_heatmap: 1.1372 layer_-1_loss_cls: 0.2397 layer_-1_loss_bbox: 1.5081 matched_ious: 0.3503 2023/03/22 06:15:12 - mmengine - INFO - Epoch(train) [1][2100/3862] lr: 1.1021e-04 eta: 22:34:37 time: 1.0662 data_time: 0.0100 memory: 8939 grad_norm: 3.8633 loss: 2.9481 loss_heatmap: 1.1553 layer_-1_loss_cls: 0.2383 layer_-1_loss_bbox: 1.5544 matched_ious: 0.2960 2023/03/22 06:16:06 - mmengine - INFO - Epoch(train) [1][2150/3862] lr: 1.1070e-04 eta: 22:33:26 time: 1.0717 data_time: 0.0100 memory: 9043 grad_norm: 3.7220 loss: 2.9403 loss_heatmap: 1.1588 layer_-1_loss_cls: 0.2351 layer_-1_loss_bbox: 1.5465 matched_ious: 0.2812 2023/03/22 06:16:59 - mmengine - INFO - Epoch(train) [1][2200/3862] lr: 1.1120e-04 eta: 22:31:52 time: 1.0582 data_time: 0.0099 memory: 9147 grad_norm: 3.7231 loss: 2.9563 loss_heatmap: 1.1562 layer_-1_loss_cls: 0.2352 layer_-1_loss_bbox: 1.5649 matched_ious: 0.3108 2023/03/22 06:17:51 - mmengine - INFO - Epoch(train) [1][2250/3862] lr: 1.1172e-04 eta: 22:30:19 time: 1.0579 data_time: 0.0101 memory: 8992 grad_norm: 3.7261 loss: 2.9230 loss_heatmap: 1.1432 layer_-1_loss_cls: 0.2315 layer_-1_loss_bbox: 1.5483 matched_ious: 0.3083 2023/03/22 06:18:45 - mmengine - INFO - Epoch(train) [1][2300/3862] lr: 1.1224e-04 eta: 22:29:07 time: 1.0689 data_time: 0.0099 memory: 9184 grad_norm: 3.6216 loss: 2.9133 loss_heatmap: 1.1151 layer_-1_loss_cls: 0.2243 layer_-1_loss_bbox: 1.5739 matched_ious: 0.3147 2023/03/22 06:19:38 - mmengine - INFO - Epoch(train) [1][2350/3862] lr: 1.1278e-04 eta: 22:27:51 time: 1.0666 data_time: 0.0101 memory: 9035 grad_norm: 3.6713 loss: 2.9019 loss_heatmap: 1.1187 layer_-1_loss_cls: 0.2291 layer_-1_loss_bbox: 1.5541 matched_ious: 0.2640 2023/03/22 06:20:31 - mmengine - INFO - Epoch(train) [1][2400/3862] lr: 1.1332e-04 eta: 22:26:27 time: 1.0603 data_time: 0.0098 memory: 9152 grad_norm: 3.6661 loss: 2.8968 loss_heatmap: 1.1256 layer_-1_loss_cls: 0.2279 layer_-1_loss_bbox: 1.5432 matched_ious: 0.3745 2023/03/22 06:21:24 - mmengine - INFO - Epoch(train) [1][2450/3862] lr: 1.1388e-04 eta: 22:24:53 time: 1.0533 data_time: 0.0099 memory: 9205 grad_norm: 3.6610 loss: 2.8017 loss_heatmap: 1.0950 layer_-1_loss_cls: 0.2198 layer_-1_loss_bbox: 1.4868 matched_ious: 0.3306 2023/03/22 06:22:17 - mmengine - INFO - Epoch(train) [1][2500/3862] lr: 1.1445e-04 eta: 22:23:24 time: 1.0558 data_time: 0.0095 memory: 9465 grad_norm: 3.7439 loss: 2.8968 loss_heatmap: 1.1283 layer_-1_loss_cls: 0.2238 layer_-1_loss_bbox: 1.5447 matched_ious: 0.3518 2023/03/22 06:23:10 - mmengine - INFO - Epoch(train) [1][2550/3862] lr: 1.1503e-04 eta: 22:22:02 time: 1.0593 data_time: 0.0100 memory: 9012 grad_norm: 3.6114 loss: 2.8184 loss_heatmap: 1.0956 layer_-1_loss_cls: 0.2167 layer_-1_loss_bbox: 1.5061 matched_ious: 0.3833 2023/03/22 06:24:03 - mmengine - INFO - Epoch(train) [1][2600/3862] lr: 1.1562e-04 eta: 22:21:03 time: 1.0745 data_time: 0.0099 memory: 9001 grad_norm: 3.6193 loss: 2.8822 loss_heatmap: 1.1220 layer_-1_loss_cls: 0.2200 layer_-1_loss_bbox: 1.5403 matched_ious: 0.3354 2023/03/22 06:24:57 - mmengine - INFO - Epoch(train) [1][2650/3862] lr: 1.1623e-04 eta: 22:20:00 time: 1.0719 data_time: 0.0101 memory: 9025 grad_norm: 3.5980 loss: 2.8372 loss_heatmap: 1.1148 layer_-1_loss_cls: 0.2203 layer_-1_loss_bbox: 1.5021 matched_ious: 0.3738 2023/03/22 06:25:50 - mmengine - INFO - Epoch(train) [1][2700/3862] lr: 1.1684e-04 eta: 22:18:51 time: 1.0664 data_time: 0.0100 memory: 9064 grad_norm: 3.5492 loss: 2.8434 loss_heatmap: 1.0941 layer_-1_loss_cls: 0.2166 layer_-1_loss_bbox: 1.5327 matched_ious: 0.3530 2023/03/22 06:26:43 - mmengine - INFO - Epoch(train) [1][2750/3862] lr: 1.1747e-04 eta: 22:17:35 time: 1.0617 data_time: 0.0103 memory: 9142 grad_norm: 3.6426 loss: 2.8246 loss_heatmap: 1.0772 layer_-1_loss_cls: 0.2093 layer_-1_loss_bbox: 1.5380 matched_ious: 0.3739 2023/03/22 06:27:37 - mmengine - INFO - Epoch(train) [1][2800/3862] lr: 1.1810e-04 eta: 22:16:23 time: 1.0635 data_time: 0.0098 memory: 9140 grad_norm: 3.6075 loss: 2.8585 loss_heatmap: 1.1002 layer_-1_loss_cls: 0.2125 layer_-1_loss_bbox: 1.5458 matched_ious: 0.3594 2023/03/22 06:28:30 - mmengine - INFO - Epoch(train) [1][2850/3862] lr: 1.1875e-04 eta: 22:15:19 time: 1.0693 data_time: 0.0100 memory: 9019 grad_norm: 3.4394 loss: 2.7616 loss_heatmap: 1.0737 layer_-1_loss_cls: 0.2098 layer_-1_loss_bbox: 1.4781 matched_ious: 0.4068 2023/03/22 06:29:23 - mmengine - INFO - Epoch(train) [1][2900/3862] lr: 1.1941e-04 eta: 22:14:14 time: 1.0690 data_time: 0.0100 memory: 9139 grad_norm: 3.5249 loss: 2.7961 loss_heatmap: 1.0846 layer_-1_loss_cls: 0.2105 layer_-1_loss_bbox: 1.5010 matched_ious: 0.3819 2023/03/22 06:30:17 - mmengine - INFO - Epoch(train) [1][2950/3862] lr: 1.2008e-04 eta: 22:13:02 time: 1.0618 data_time: 0.0098 memory: 9182 grad_norm: 3.5410 loss: 2.8103 loss_heatmap: 1.0906 layer_-1_loss_cls: 0.2123 layer_-1_loss_bbox: 1.5074 matched_ious: 0.3114 2023/03/22 06:31:09 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 06:31:09 - mmengine - INFO - Epoch(train) [1][3000/3862] lr: 1.2076e-04 eta: 22:11:45 time: 1.0579 data_time: 0.0101 memory: 9298 grad_norm: 3.4232 loss: 2.8052 loss_heatmap: 1.0805 layer_-1_loss_cls: 0.2064 layer_-1_loss_bbox: 1.5184 matched_ious: 0.3140 2023/03/22 06:32:03 - mmengine - INFO - Epoch(train) [1][3050/3862] lr: 1.2145e-04 eta: 22:10:36 time: 1.0643 data_time: 0.0105 memory: 9166 grad_norm: 3.4849 loss: 2.7142 loss_heatmap: 1.0402 layer_-1_loss_cls: 0.2041 layer_-1_loss_bbox: 1.4699 matched_ious: 0.3125 2023/03/22 06:32:56 - mmengine - INFO - Epoch(train) [1][3100/3862] lr: 1.2216e-04 eta: 22:09:38 time: 1.0721 data_time: 0.0100 memory: 9127 grad_norm: 3.4838 loss: 2.7560 loss_heatmap: 1.0856 layer_-1_loss_cls: 0.2099 layer_-1_loss_bbox: 1.4605 matched_ious: 0.3733 2023/03/22 06:33:49 - mmengine - INFO - Epoch(train) [1][3150/3862] lr: 1.2287e-04 eta: 22:08:18 time: 1.0543 data_time: 0.0106 memory: 9388 grad_norm: 3.5224 loss: 2.7333 loss_heatmap: 1.0591 layer_-1_loss_cls: 0.2063 layer_-1_loss_bbox: 1.4679 matched_ious: 0.3830 2023/03/22 06:34:42 - mmengine - INFO - Epoch(train) [1][3200/3862] lr: 1.2360e-04 eta: 22:07:13 time: 1.0659 data_time: 0.0101 memory: 9127 grad_norm: 3.5714 loss: 2.7459 loss_heatmap: 1.0658 layer_-1_loss_cls: 0.2006 layer_-1_loss_bbox: 1.4795 matched_ious: 0.4029 2023/03/22 06:35:36 - mmengine - INFO - Epoch(train) [1][3250/3862] lr: 1.2433e-04 eta: 22:06:20 time: 1.0759 data_time: 0.0102 memory: 8916 grad_norm: 3.3940 loss: 2.7469 loss_heatmap: 1.0363 layer_-1_loss_cls: 0.1958 layer_-1_loss_bbox: 1.5148 matched_ious: 0.3527 2023/03/22 06:36:30 - mmengine - INFO - Epoch(train) [1][3300/3862] lr: 1.2508e-04 eta: 22:05:32 time: 1.0813 data_time: 0.0101 memory: 9155 grad_norm: 3.4254 loss: 2.6914 loss_heatmap: 1.0503 layer_-1_loss_cls: 0.1984 layer_-1_loss_bbox: 1.4427 matched_ious: 0.3351 2023/03/22 06:37:24 - mmengine - INFO - Epoch(train) [1][3350/3862] lr: 1.2584e-04 eta: 22:04:45 time: 1.0816 data_time: 0.0102 memory: 9067 grad_norm: 3.4122 loss: 2.7271 loss_heatmap: 1.0621 layer_-1_loss_cls: 0.1977 layer_-1_loss_bbox: 1.4672 matched_ious: 0.4040 2023/03/22 06:38:18 - mmengine - INFO - Epoch(train) [1][3400/3862] lr: 1.2661e-04 eta: 22:03:47 time: 1.0718 data_time: 0.0097 memory: 9078 grad_norm: 3.4488 loss: 2.6989 loss_heatmap: 1.0351 layer_-1_loss_cls: 0.1939 layer_-1_loss_bbox: 1.4699 matched_ious: 0.3685 2023/03/22 06:39:11 - mmengine - INFO - Epoch(train) [1][3450/3862] lr: 1.2739e-04 eta: 22:02:41 time: 1.0642 data_time: 0.0097 memory: 9453 grad_norm: 3.4379 loss: 2.7490 loss_heatmap: 1.0715 layer_-1_loss_cls: 0.1997 layer_-1_loss_bbox: 1.4778 matched_ious: 0.3973 2023/03/22 06:40:04 - mmengine - INFO - Epoch(train) [1][3500/3862] lr: 1.2818e-04 eta: 22:01:33 time: 1.0615 data_time: 0.0099 memory: 9224 grad_norm: 3.4567 loss: 2.6659 loss_heatmap: 1.0227 layer_-1_loss_cls: 0.1921 layer_-1_loss_bbox: 1.4510 matched_ious: 0.3587 2023/03/22 06:40:57 - mmengine - INFO - Epoch(train) [1][3550/3862] lr: 1.2898e-04 eta: 22:00:25 time: 1.0615 data_time: 0.0098 memory: 9183 grad_norm: 3.4488 loss: 2.6076 loss_heatmap: 1.0149 layer_-1_loss_cls: 0.1897 layer_-1_loss_bbox: 1.4030 matched_ious: 0.3837 2023/03/22 06:41:50 - mmengine - INFO - Epoch(train) [1][3600/3862] lr: 1.2980e-04 eta: 21:59:20 time: 1.0642 data_time: 0.0098 memory: 9079 grad_norm: 3.2777 loss: 2.7237 loss_heatmap: 1.0208 layer_-1_loss_cls: 0.1905 layer_-1_loss_bbox: 1.5124 matched_ious: 0.3753 2023/03/22 06:42:44 - mmengine - INFO - Epoch(train) [1][3650/3862] lr: 1.3062e-04 eta: 21:58:19 time: 1.0679 data_time: 0.0098 memory: 9516 grad_norm: 3.4289 loss: 2.7446 loss_heatmap: 1.0567 layer_-1_loss_cls: 0.1914 layer_-1_loss_bbox: 1.4965 matched_ious: 0.3634 2023/03/22 06:43:37 - mmengine - INFO - Epoch(train) [1][3700/3862] lr: 1.3146e-04 eta: 21:57:09 time: 1.0589 data_time: 0.0098 memory: 8936 grad_norm: 3.3861 loss: 2.6692 loss_heatmap: 1.0239 layer_-1_loss_cls: 0.1857 layer_-1_loss_bbox: 1.4596 matched_ious: 0.3547 2023/03/22 06:44:31 - mmengine - INFO - Epoch(train) [1][3750/3862] lr: 1.3230e-04 eta: 21:56:24 time: 1.0836 data_time: 0.0101 memory: 9243 grad_norm: 3.3324 loss: 2.7486 loss_heatmap: 1.0289 layer_-1_loss_cls: 0.1870 layer_-1_loss_bbox: 1.5327 matched_ious: 0.3200 2023/03/22 06:45:24 - mmengine - INFO - Epoch(train) [1][3800/3862] lr: 1.3316e-04 eta: 21:55:18 time: 1.0621 data_time: 0.0104 memory: 9321 grad_norm: 3.3514 loss: 2.6544 loss_heatmap: 1.0438 layer_-1_loss_cls: 0.1867 layer_-1_loss_bbox: 1.4239 matched_ious: 0.3727 2023/03/22 06:46:17 - mmengine - INFO - Epoch(train) [1][3850/3862] lr: 1.3403e-04 eta: 21:54:15 time: 1.0646 data_time: 0.0098 memory: 9262 grad_norm: 3.3729 loss: 2.6739 loss_heatmap: 1.0539 layer_-1_loss_cls: 0.1875 layer_-1_loss_bbox: 1.4325 matched_ious: 0.3999 2023/03/22 06:46:30 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 06:47:25 - mmengine - INFO - Epoch(train) [2][ 50/3862] lr: 1.3512e-04 eta: 21:53:33 time: 1.1078 data_time: 0.0504 memory: 9420 grad_norm: 3.3731 loss: 2.6612 loss_heatmap: 1.0402 layer_-1_loss_cls: 0.1869 layer_-1_loss_bbox: 1.4342 matched_ious: 0.3760 2023/03/22 06:48:19 - mmengine - INFO - Epoch(train) [2][ 100/3862] lr: 1.3601e-04 eta: 21:52:34 time: 1.0698 data_time: 0.0101 memory: 8986 grad_norm: 3.3187 loss: 2.6232 loss_heatmap: 1.0311 layer_-1_loss_cls: 0.1792 layer_-1_loss_bbox: 1.4128 matched_ious: 0.3985 2023/03/22 06:48:59 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 06:49:12 - mmengine - INFO - Epoch(train) [2][ 150/3862] lr: 1.3691e-04 eta: 21:51:37 time: 1.0706 data_time: 0.0097 memory: 9146 grad_norm: 3.5147 loss: 2.5924 loss_heatmap: 1.0010 layer_-1_loss_cls: 0.1779 layer_-1_loss_bbox: 1.4136 matched_ious: 0.4264 2023/03/22 06:50:06 - mmengine - INFO - Epoch(train) [2][ 200/3862] lr: 1.3782e-04 eta: 21:50:40 time: 1.0716 data_time: 0.0100 memory: 9308 grad_norm: 3.5524 loss: 2.6513 loss_heatmap: 1.0274 layer_-1_loss_cls: 0.1819 layer_-1_loss_bbox: 1.4420 matched_ious: 0.4024 2023/03/22 06:50:59 - mmengine - INFO - Epoch(train) [2][ 250/3862] lr: 1.3875e-04 eta: 21:49:34 time: 1.0611 data_time: 0.0102 memory: 9250 grad_norm: 3.3093 loss: 2.5673 loss_heatmap: 0.9809 layer_-1_loss_cls: 0.1721 layer_-1_loss_bbox: 1.4142 matched_ious: 0.3518 2023/03/22 06:51:52 - mmengine - INFO - Epoch(train) [2][ 300/3862] lr: 1.3968e-04 eta: 21:48:31 time: 1.0631 data_time: 0.0102 memory: 9160 grad_norm: 3.5409 loss: 2.5324 loss_heatmap: 1.0075 layer_-1_loss_cls: 0.1781 layer_-1_loss_bbox: 1.3468 matched_ious: 0.4079 2023/03/22 06:52:46 - mmengine - INFO - Epoch(train) [2][ 350/3862] lr: 1.4063e-04 eta: 21:47:40 time: 1.0776 data_time: 0.0099 memory: 9336 grad_norm: 3.5291 loss: 2.5876 loss_heatmap: 1.0085 layer_-1_loss_cls: 0.1756 layer_-1_loss_bbox: 1.4036 matched_ious: 0.3536 2023/03/22 06:53:39 - mmengine - INFO - Epoch(train) [2][ 400/3862] lr: 1.4158e-04 eta: 21:46:43 time: 1.0705 data_time: 0.0099 memory: 9023 grad_norm: 3.4562 loss: 2.5663 loss_heatmap: 0.9798 layer_-1_loss_cls: 0.1715 layer_-1_loss_bbox: 1.4149 matched_ious: 0.4067 2023/03/22 06:54:32 - mmengine - INFO - Epoch(train) [2][ 450/3862] lr: 1.4255e-04 eta: 21:45:34 time: 1.0567 data_time: 0.0096 memory: 9185 grad_norm: 3.5704 loss: 2.5951 loss_heatmap: 1.0083 layer_-1_loss_cls: 0.1751 layer_-1_loss_bbox: 1.4118 matched_ious: 0.3569 2023/03/22 06:55:26 - mmengine - INFO - Epoch(train) [2][ 500/3862] lr: 1.4352e-04 eta: 21:44:39 time: 1.0722 data_time: 0.0097 memory: 9236 grad_norm: 3.4538 loss: 2.5368 loss_heatmap: 0.9824 layer_-1_loss_cls: 0.1703 layer_-1_loss_bbox: 1.3840 matched_ious: 0.4016 2023/03/22 06:56:19 - mmengine - INFO - Epoch(train) [2][ 550/3862] lr: 1.4451e-04 eta: 21:43:34 time: 1.0613 data_time: 0.0099 memory: 9060 grad_norm: 3.4961 loss: 2.5721 loss_heatmap: 1.0117 layer_-1_loss_cls: 0.1760 layer_-1_loss_bbox: 1.3844 matched_ious: 0.3723 2023/03/22 06:57:12 - mmengine - INFO - Epoch(train) [2][ 600/3862] lr: 1.4551e-04 eta: 21:42:33 time: 1.0651 data_time: 0.0099 memory: 9256 grad_norm: 3.3311 loss: 2.5286 loss_heatmap: 0.9925 layer_-1_loss_cls: 0.1677 layer_-1_loss_bbox: 1.3684 matched_ious: 0.3674 2023/03/22 06:58:06 - mmengine - INFO - Epoch(train) [2][ 650/3862] lr: 1.4652e-04 eta: 21:41:37 time: 1.0705 data_time: 0.0094 memory: 9171 grad_norm: 3.4226 loss: 2.5260 loss_heatmap: 1.0044 layer_-1_loss_cls: 0.1729 layer_-1_loss_bbox: 1.3487 matched_ious: 0.4330 2023/03/22 06:58:59 - mmengine - INFO - Epoch(train) [2][ 700/3862] lr: 1.4753e-04 eta: 21:40:30 time: 1.0568 data_time: 0.0097 memory: 9177 grad_norm: 3.3344 loss: 2.4931 loss_heatmap: 0.9794 layer_-1_loss_cls: 0.1691 layer_-1_loss_bbox: 1.3446 matched_ious: 0.3774 2023/03/22 06:59:51 - mmengine - INFO - Epoch(train) [2][ 750/3862] lr: 1.4856e-04 eta: 21:39:25 time: 1.0595 data_time: 0.0097 memory: 8934 grad_norm: 3.3659 loss: 2.5041 loss_heatmap: 0.9678 layer_-1_loss_cls: 0.1674 layer_-1_loss_bbox: 1.3689 matched_ious: 0.3982 2023/03/22 07:00:44 - mmengine - INFO - Epoch(train) [2][ 800/3862] lr: 1.4960e-04 eta: 21:38:16 time: 1.0543 data_time: 0.0097 memory: 9127 grad_norm: 3.5631 loss: 2.5097 loss_heatmap: 0.9906 layer_-1_loss_cls: 0.1692 layer_-1_loss_bbox: 1.3499 matched_ious: 0.3778 2023/03/22 07:01:37 - mmengine - INFO - Epoch(train) [2][ 850/3862] lr: 1.5065e-04 eta: 21:37:16 time: 1.0640 data_time: 0.0097 memory: 8828 grad_norm: 3.3374 loss: 2.5142 loss_heatmap: 0.9636 layer_-1_loss_cls: 0.1648 layer_-1_loss_bbox: 1.3858 matched_ious: 0.4016 2023/03/22 07:02:31 - mmengine - INFO - Epoch(train) [2][ 900/3862] lr: 1.5171e-04 eta: 21:36:14 time: 1.0630 data_time: 0.0097 memory: 9343 grad_norm: 3.3443 loss: 2.5558 loss_heatmap: 0.9852 layer_-1_loss_cls: 0.1661 layer_-1_loss_bbox: 1.4046 matched_ious: 0.3994 2023/03/22 07:03:24 - mmengine - INFO - Epoch(train) [2][ 950/3862] lr: 1.5278e-04 eta: 21:35:20 time: 1.0724 data_time: 0.0098 memory: 9285 grad_norm: 3.3442 loss: 2.5220 loss_heatmap: 0.9741 layer_-1_loss_cls: 0.1641 layer_-1_loss_bbox: 1.3839 matched_ious: 0.3979 2023/03/22 07:04:17 - mmengine - INFO - Epoch(train) [2][1000/3862] lr: 1.5386e-04 eta: 21:34:21 time: 1.0652 data_time: 0.0099 memory: 9367 grad_norm: 3.5623 loss: 2.5597 loss_heatmap: 1.0017 layer_-1_loss_cls: 0.1695 layer_-1_loss_bbox: 1.3885 matched_ious: 0.3758 2023/03/22 07:05:11 - mmengine - INFO - Epoch(train) [2][1050/3862] lr: 1.5495e-04 eta: 21:33:28 time: 1.0740 data_time: 0.0096 memory: 9211 grad_norm: 3.3422 loss: 2.5419 loss_heatmap: 1.0014 layer_-1_loss_cls: 0.1668 layer_-1_loss_bbox: 1.3737 matched_ious: 0.4235 2023/03/22 07:06:04 - mmengine - INFO - Epoch(train) [2][1100/3862] lr: 1.5605e-04 eta: 21:32:28 time: 1.0646 data_time: 0.0098 memory: 9179 grad_norm: 3.3819 loss: 2.5158 loss_heatmap: 0.9703 layer_-1_loss_cls: 0.1640 layer_-1_loss_bbox: 1.3815 matched_ious: 0.3427 2023/03/22 07:06:45 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 07:06:57 - mmengine - INFO - Epoch(train) [2][1150/3862] lr: 1.5716e-04 eta: 21:31:26 time: 1.0609 data_time: 0.0099 memory: 9377 grad_norm: 3.4138 loss: 2.5183 loss_heatmap: 0.9858 layer_-1_loss_cls: 0.1660 layer_-1_loss_bbox: 1.3665 matched_ious: 0.4455 2023/03/22 07:07:51 - mmengine - INFO - Epoch(train) [2][1200/3862] lr: 1.5828e-04 eta: 21:30:26 time: 1.0640 data_time: 0.0103 memory: 8913 grad_norm: 3.3353 loss: 2.5131 loss_heatmap: 0.9723 layer_-1_loss_cls: 0.1613 layer_-1_loss_bbox: 1.3795 matched_ious: 0.3753 2023/03/22 07:08:44 - mmengine - INFO - Epoch(train) [2][1250/3862] lr: 1.5941e-04 eta: 21:29:22 time: 1.0578 data_time: 0.0099 memory: 9342 grad_norm: 3.5182 loss: 2.4349 loss_heatmap: 0.9496 layer_-1_loss_cls: 0.1612 layer_-1_loss_bbox: 1.3241 matched_ious: 0.3734 2023/03/22 07:09:36 - mmengine - INFO - Epoch(train) [2][1300/3862] lr: 1.6056e-04 eta: 21:28:17 time: 1.0565 data_time: 0.0099 memory: 8918 grad_norm: 3.2619 loss: 2.3803 loss_heatmap: 0.9386 layer_-1_loss_cls: 0.1591 layer_-1_loss_bbox: 1.2826 matched_ious: 0.4277 2023/03/22 07:10:30 - mmengine - INFO - Epoch(train) [2][1350/3862] lr: 1.6171e-04 eta: 21:27:18 time: 1.0649 data_time: 0.0101 memory: 9004 grad_norm: 3.4945 loss: 2.3882 loss_heatmap: 0.9395 layer_-1_loss_cls: 0.1574 layer_-1_loss_bbox: 1.2912 matched_ious: 0.3863 2023/03/22 07:11:22 - mmengine - INFO - Epoch(train) [2][1400/3862] lr: 1.6287e-04 eta: 21:26:13 time: 1.0563 data_time: 0.0098 memory: 9264 grad_norm: 3.3230 loss: 2.4397 loss_heatmap: 0.9474 layer_-1_loss_cls: 0.1576 layer_-1_loss_bbox: 1.3347 matched_ious: 0.4192 2023/03/22 07:12:16 - mmengine - INFO - Epoch(train) [2][1450/3862] lr: 1.6404e-04 eta: 21:25:16 time: 1.0665 data_time: 0.0098 memory: 8914 grad_norm: 3.5250 loss: 2.4379 loss_heatmap: 0.9683 layer_-1_loss_cls: 0.1601 layer_-1_loss_bbox: 1.3096 matched_ious: 0.4203 2023/03/22 07:13:09 - mmengine - INFO - Epoch(train) [2][1500/3862] lr: 1.6522e-04 eta: 21:24:16 time: 1.0636 data_time: 0.0101 memory: 9215 grad_norm: 3.3073 loss: 2.3885 loss_heatmap: 0.9411 layer_-1_loss_cls: 0.1579 layer_-1_loss_bbox: 1.2895 matched_ious: 0.4072 2023/03/22 07:14:03 - mmengine - INFO - Epoch(train) [2][1550/3862] lr: 1.6641e-04 eta: 21:23:33 time: 1.0878 data_time: 0.0099 memory: 9225 grad_norm: 3.3240 loss: 2.4447 loss_heatmap: 0.9711 layer_-1_loss_cls: 0.1602 layer_-1_loss_bbox: 1.3134 matched_ious: 0.4310 2023/03/22 07:14:56 - mmengine - INFO - Epoch(train) [2][1600/3862] lr: 1.6761e-04 eta: 21:22:30 time: 1.0581 data_time: 0.0099 memory: 9374 grad_norm: 3.1205 loss: 2.4321 loss_heatmap: 0.9278 layer_-1_loss_cls: 0.1543 layer_-1_loss_bbox: 1.3500 matched_ious: 0.4341 2023/03/22 07:15:50 - mmengine - INFO - Epoch(train) [2][1650/3862] lr: 1.6882e-04 eta: 21:21:36 time: 1.0706 data_time: 0.0097 memory: 9355 grad_norm: 3.3083 loss: 2.4061 loss_heatmap: 0.9350 layer_-1_loss_cls: 0.1541 layer_-1_loss_bbox: 1.3170 matched_ious: 0.4559 2023/03/22 07:16:43 - mmengine - INFO - Epoch(train) [2][1700/3862] lr: 1.7005e-04 eta: 21:20:42 time: 1.0711 data_time: 0.0098 memory: 9239 grad_norm: 3.2425 loss: 2.4866 loss_heatmap: 0.9680 layer_-1_loss_cls: 0.1580 layer_-1_loss_bbox: 1.3607 matched_ious: 0.3686 2023/03/22 07:17:36 - mmengine - INFO - Epoch(train) [2][1750/3862] lr: 1.7128e-04 eta: 21:19:39 time: 1.0574 data_time: 0.0096 memory: 9085 grad_norm: 3.1713 loss: 2.4055 loss_heatmap: 0.9548 layer_-1_loss_cls: 0.1568 layer_-1_loss_bbox: 1.2938 matched_ious: 0.4540 2023/03/22 07:18:29 - mmengine - INFO - Epoch(train) [2][1800/3862] lr: 1.7252e-04 eta: 21:18:38 time: 1.0608 data_time: 0.0095 memory: 9037 grad_norm: 3.2948 loss: 2.3613 loss_heatmap: 0.9256 layer_-1_loss_cls: 0.1542 layer_-1_loss_bbox: 1.2815 matched_ious: 0.3551 2023/03/22 07:19:22 - mmengine - INFO - Epoch(train) [2][1850/3862] lr: 1.7377e-04 eta: 21:17:39 time: 1.0632 data_time: 0.0099 memory: 9041 grad_norm: 3.3435 loss: 2.3919 loss_heatmap: 0.9421 layer_-1_loss_cls: 0.1557 layer_-1_loss_bbox: 1.2941 matched_ious: 0.3850 2023/03/22 07:20:15 - mmengine - INFO - Epoch(train) [2][1900/3862] lr: 1.7503e-04 eta: 21:16:38 time: 1.0591 data_time: 0.0096 memory: 9045 grad_norm: 3.3056 loss: 2.3641 loss_heatmap: 0.9117 layer_-1_loss_cls: 0.1508 layer_-1_loss_bbox: 1.3016 matched_ious: 0.3859 2023/03/22 07:21:08 - mmengine - INFO - Epoch(train) [2][1950/3862] lr: 1.7630e-04 eta: 21:15:38 time: 1.0620 data_time: 0.0095 memory: 9247 grad_norm: 3.1755 loss: 2.4431 loss_heatmap: 0.9418 layer_-1_loss_cls: 0.1542 layer_-1_loss_bbox: 1.3472 matched_ious: 0.3949 2023/03/22 07:22:01 - mmengine - INFO - Epoch(train) [2][2000/3862] lr: 1.7758e-04 eta: 21:14:38 time: 1.0601 data_time: 0.0098 memory: 9055 grad_norm: 3.3631 loss: 2.4419 loss_heatmap: 0.9376 layer_-1_loss_cls: 0.1554 layer_-1_loss_bbox: 1.3489 matched_ious: 0.4512 2023/03/22 07:22:55 - mmengine - INFO - Epoch(train) [2][2050/3862] lr: 1.7887e-04 eta: 21:13:39 time: 1.0628 data_time: 0.0100 memory: 9133 grad_norm: 3.1519 loss: 2.3190 loss_heatmap: 0.9262 layer_-1_loss_cls: 0.1524 layer_-1_loss_bbox: 1.2404 matched_ious: 0.3629 2023/03/22 07:23:48 - mmengine - INFO - Epoch(train) [2][2100/3862] lr: 1.8016e-04 eta: 21:12:45 time: 1.0717 data_time: 0.0104 memory: 9220 grad_norm: 3.2502 loss: 2.3763 loss_heatmap: 0.9300 layer_-1_loss_cls: 0.1506 layer_-1_loss_bbox: 1.2957 matched_ious: 0.3936 2023/03/22 07:24:29 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 07:24:42 - mmengine - INFO - Epoch(train) [2][2150/3862] lr: 1.8147e-04 eta: 21:11:53 time: 1.0729 data_time: 0.0098 memory: 9099 grad_norm: 3.1766 loss: 2.3587 loss_heatmap: 0.9340 layer_-1_loss_cls: 0.1519 layer_-1_loss_bbox: 1.2728 matched_ious: 0.3983 2023/03/22 07:25:35 - mmengine - INFO - Epoch(train) [2][2200/3862] lr: 1.8279e-04 eta: 21:10:57 time: 1.0676 data_time: 0.0098 memory: 9159 grad_norm: 3.3098 loss: 2.4207 loss_heatmap: 0.9446 layer_-1_loss_cls: 0.1533 layer_-1_loss_bbox: 1.3228 matched_ious: 0.3521 2023/03/22 07:26:28 - mmengine - INFO - Epoch(train) [2][2250/3862] lr: 1.8412e-04 eta: 21:09:59 time: 1.0629 data_time: 0.0099 memory: 8984 grad_norm: 3.1207 loss: 2.3315 loss_heatmap: 0.9217 layer_-1_loss_cls: 0.1516 layer_-1_loss_bbox: 1.2582 matched_ious: 0.4204 2023/03/22 07:27:22 - mmengine - INFO - Epoch(train) [2][2300/3862] lr: 1.8545e-04 eta: 21:09:07 time: 1.0748 data_time: 0.0099 memory: 9151 grad_norm: 3.1682 loss: 2.3355 loss_heatmap: 0.9118 layer_-1_loss_cls: 0.1489 layer_-1_loss_bbox: 1.2748 matched_ious: 0.3932 2023/03/22 07:28:15 - mmengine - INFO - Epoch(train) [2][2350/3862] lr: 1.8680e-04 eta: 21:08:09 time: 1.0631 data_time: 0.0102 memory: 9201 grad_norm: 3.1768 loss: 2.3275 loss_heatmap: 0.9139 layer_-1_loss_cls: 0.1516 layer_-1_loss_bbox: 1.2620 matched_ious: 0.4143 2023/03/22 07:29:08 - mmengine - INFO - Epoch(train) [2][2400/3862] lr: 1.8815e-04 eta: 21:07:10 time: 1.0630 data_time: 0.0100 memory: 8984 grad_norm: 3.1200 loss: 2.3238 loss_heatmap: 0.8927 layer_-1_loss_cls: 0.1485 layer_-1_loss_bbox: 1.2827 matched_ious: 0.3861 2023/03/22 07:30:02 - mmengine - INFO - Epoch(train) [2][2450/3862] lr: 1.8952e-04 eta: 21:06:16 time: 1.0704 data_time: 0.0098 memory: 9387 grad_norm: 3.1572 loss: 2.2849 loss_heatmap: 0.9030 layer_-1_loss_cls: 0.1475 layer_-1_loss_bbox: 1.2344 matched_ious: 0.4453 2023/03/22 07:30:55 - mmengine - INFO - Epoch(train) [2][2500/3862] lr: 1.9089e-04 eta: 21:05:16 time: 1.0582 data_time: 0.0100 memory: 9235 grad_norm: 3.1041 loss: 2.3058 loss_heatmap: 0.8999 layer_-1_loss_cls: 0.1469 layer_-1_loss_bbox: 1.2590 matched_ious: 0.3685 2023/03/22 07:31:48 - mmengine - INFO - Epoch(train) [2][2550/3862] lr: 1.9228e-04 eta: 21:04:15 time: 1.0591 data_time: 0.0102 memory: 9230 grad_norm: 3.1930 loss: 2.3386 loss_heatmap: 0.9238 layer_-1_loss_cls: 0.1493 layer_-1_loss_bbox: 1.2655 matched_ious: 0.3802 2023/03/22 07:32:41 - mmengine - INFO - Epoch(train) [2][2600/3862] lr: 1.9367e-04 eta: 21:03:22 time: 1.0712 data_time: 0.0099 memory: 9135 grad_norm: 3.1574 loss: 2.3389 loss_heatmap: 0.9274 layer_-1_loss_cls: 0.1500 layer_-1_loss_bbox: 1.2615 matched_ious: 0.3730 2023/03/22 07:33:35 - mmengine - INFO - Epoch(train) [2][2650/3862] lr: 1.9507e-04 eta: 21:02:25 time: 1.0650 data_time: 0.0099 memory: 9135 grad_norm: 3.1284 loss: 2.3222 loss_heatmap: 0.9241 layer_-1_loss_cls: 0.1492 layer_-1_loss_bbox: 1.2489 matched_ious: 0.4336 2023/03/22 07:34:29 - mmengine - INFO - Epoch(train) [2][2700/3862] lr: 1.9648e-04 eta: 21:01:36 time: 1.0794 data_time: 0.0103 memory: 9127 grad_norm: 3.0983 loss: 2.2378 loss_heatmap: 0.8852 layer_-1_loss_cls: 0.1460 layer_-1_loss_bbox: 1.2065 matched_ious: 0.4263 2023/03/22 07:35:22 - mmengine - INFO - Epoch(train) [2][2750/3862] lr: 1.9790e-04 eta: 21:00:41 time: 1.0676 data_time: 0.0100 memory: 9255 grad_norm: 3.0413 loss: 2.3535 loss_heatmap: 0.9299 layer_-1_loss_cls: 0.1499 layer_-1_loss_bbox: 1.2737 matched_ious: 0.4296 2023/03/22 07:36:16 - mmengine - INFO - Epoch(train) [2][2800/3862] lr: 1.9933e-04 eta: 20:59:49 time: 1.0734 data_time: 0.0103 memory: 9269 grad_norm: 3.1543 loss: 2.3219 loss_heatmap: 0.8931 layer_-1_loss_cls: 0.1450 layer_-1_loss_bbox: 1.2838 matched_ious: 0.4239 2023/03/22 07:37:09 - mmengine - INFO - Epoch(train) [2][2850/3862] lr: 2.0077e-04 eta: 20:58:52 time: 1.0650 data_time: 0.0103 memory: 9455 grad_norm: 3.0558 loss: 2.2944 loss_heatmap: 0.9084 layer_-1_loss_cls: 0.1491 layer_-1_loss_bbox: 1.2369 matched_ious: 0.4009 2023/03/22 07:38:02 - mmengine - INFO - Epoch(train) [2][2900/3862] lr: 2.0222e-04 eta: 20:57:58 time: 1.0708 data_time: 0.0104 memory: 9150 grad_norm: 3.1804 loss: 2.2668 loss_heatmap: 0.8972 layer_-1_loss_cls: 0.1484 layer_-1_loss_bbox: 1.2212 matched_ious: 0.4435 2023/03/22 07:38:55 - mmengine - INFO - Epoch(train) [2][2950/3862] lr: 2.0367e-04 eta: 20:56:57 time: 1.0566 data_time: 0.0100 memory: 8838 grad_norm: 3.0288 loss: 2.3180 loss_heatmap: 0.9072 layer_-1_loss_cls: 0.1468 layer_-1_loss_bbox: 1.2640 matched_ious: 0.4359 2023/03/22 07:39:48 - mmengine - INFO - Epoch(train) [2][3000/3862] lr: 2.0514e-04 eta: 20:55:57 time: 1.0575 data_time: 0.0102 memory: 8964 grad_norm: 3.0897 loss: 2.2022 loss_heatmap: 0.8890 layer_-1_loss_cls: 0.1460 layer_-1_loss_bbox: 1.1672 matched_ious: 0.4538 2023/03/22 07:40:42 - mmengine - INFO - Epoch(train) [2][3050/3862] lr: 2.0661e-04 eta: 20:55:04 time: 1.0716 data_time: 0.0098 memory: 9124 grad_norm: 3.1111 loss: 2.3010 loss_heatmap: 0.9087 layer_-1_loss_cls: 0.1484 layer_-1_loss_bbox: 1.2439 matched_ious: 0.4777 2023/03/22 07:41:35 - mmengine - INFO - Epoch(train) [2][3100/3862] lr: 2.0810e-04 eta: 20:54:07 time: 1.0635 data_time: 0.0098 memory: 9142 grad_norm: 3.2584 loss: 2.3212 loss_heatmap: 0.9096 layer_-1_loss_cls: 0.1472 layer_-1_loss_bbox: 1.2644 matched_ious: 0.4643 2023/03/22 07:42:15 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 07:42:28 - mmengine - INFO - Epoch(train) [2][3150/3862] lr: 2.0959e-04 eta: 20:53:12 time: 1.0693 data_time: 0.0098 memory: 9297 grad_norm: 3.1499 loss: 2.3103 loss_heatmap: 0.9274 layer_-1_loss_cls: 0.1488 layer_-1_loss_bbox: 1.2341 matched_ious: 0.4040 2023/03/22 07:43:22 - mmengine - INFO - Epoch(train) [2][3200/3862] lr: 2.1109e-04 eta: 20:52:17 time: 1.0676 data_time: 0.0100 memory: 9164 grad_norm: 3.0206 loss: 2.2396 loss_heatmap: 0.8908 layer_-1_loss_cls: 0.1466 layer_-1_loss_bbox: 1.2022 matched_ious: 0.4615 2023/03/22 07:44:15 - mmengine - INFO - Epoch(train) [2][3250/3862] lr: 2.1260e-04 eta: 20:51:19 time: 1.0604 data_time: 0.0100 memory: 9384 grad_norm: 2.9329 loss: 2.2791 loss_heatmap: 0.8761 layer_-1_loss_cls: 0.1381 layer_-1_loss_bbox: 1.2649 matched_ious: 0.4268 2023/03/22 07:45:08 - mmengine - INFO - Epoch(train) [2][3300/3862] lr: 2.1412e-04 eta: 20:50:21 time: 1.0621 data_time: 0.0103 memory: 9272 grad_norm: 3.0787 loss: 2.2549 loss_heatmap: 0.8924 layer_-1_loss_cls: 0.1439 layer_-1_loss_bbox: 1.2187 matched_ious: 0.4491 2023/03/22 07:46:01 - mmengine - INFO - Epoch(train) [2][3350/3862] lr: 2.1564e-04 eta: 20:49:22 time: 1.0589 data_time: 0.0101 memory: 9386 grad_norm: 2.9499 loss: 2.2546 loss_heatmap: 0.8865 layer_-1_loss_cls: 0.1462 layer_-1_loss_bbox: 1.2220 matched_ious: 0.4304 2023/03/22 07:46:55 - mmengine - INFO - Epoch(train) [2][3400/3862] lr: 2.1718e-04 eta: 20:48:36 time: 1.0859 data_time: 0.0101 memory: 8982 grad_norm: 2.9508 loss: 2.2627 loss_heatmap: 0.8784 layer_-1_loss_cls: 0.1415 layer_-1_loss_bbox: 1.2427 matched_ious: 0.4354 2023/03/22 07:47:48 - mmengine - INFO - Epoch(train) [2][3450/3862] lr: 2.1872e-04 eta: 20:47:39 time: 1.0628 data_time: 0.0102 memory: 9279 grad_norm: 3.1141 loss: 2.2231 loss_heatmap: 0.8954 layer_-1_loss_cls: 0.1470 layer_-1_loss_bbox: 1.1807 matched_ious: 0.4512 2023/03/22 07:48:42 - mmengine - INFO - Epoch(train) [2][3500/3862] lr: 2.2028e-04 eta: 20:46:45 time: 1.0693 data_time: 0.0104 memory: 9127 grad_norm: 3.0275 loss: 2.3269 loss_heatmap: 0.9030 layer_-1_loss_cls: 0.1445 layer_-1_loss_bbox: 1.2793 matched_ious: 0.4108 2023/03/22 07:49:35 - mmengine - INFO - Epoch(train) [2][3550/3862] lr: 2.2184e-04 eta: 20:45:49 time: 1.0667 data_time: 0.0099 memory: 8883 grad_norm: 3.0634 loss: 2.2595 loss_heatmap: 0.8785 layer_-1_loss_cls: 0.1392 layer_-1_loss_bbox: 1.2417 matched_ious: 0.4379 2023/03/22 07:50:28 - mmengine - INFO - Epoch(train) [2][3600/3862] lr: 2.2341e-04 eta: 20:44:55 time: 1.0692 data_time: 0.0101 memory: 9024 grad_norm: 2.9708 loss: 2.2070 loss_heatmap: 0.8603 layer_-1_loss_cls: 0.1397 layer_-1_loss_bbox: 1.2071 matched_ious: 0.3868 2023/03/22 07:51:22 - mmengine - INFO - Epoch(train) [2][3650/3862] lr: 2.2499e-04 eta: 20:43:58 time: 1.0619 data_time: 0.0099 memory: 9341 grad_norm: 2.8805 loss: 2.2111 loss_heatmap: 0.8727 layer_-1_loss_cls: 0.1398 layer_-1_loss_bbox: 1.1986 matched_ious: 0.4217 2023/03/22 07:52:15 - mmengine - INFO - Epoch(train) [2][3700/3862] lr: 2.2657e-04 eta: 20:43:04 time: 1.0699 data_time: 0.0099 memory: 9195 grad_norm: 3.0366 loss: 2.1980 loss_heatmap: 0.8735 layer_-1_loss_cls: 0.1422 layer_-1_loss_bbox: 1.1824 matched_ious: 0.4430 2023/03/22 07:53:08 - mmengine - INFO - Epoch(train) [2][3750/3862] lr: 2.2817e-04 eta: 20:42:07 time: 1.0631 data_time: 0.0099 memory: 9636 grad_norm: 3.0106 loss: 2.2252 loss_heatmap: 0.8954 layer_-1_loss_cls: 0.1443 layer_-1_loss_bbox: 1.1855 matched_ious: 0.3919 2023/03/22 07:54:02 - mmengine - INFO - Epoch(train) [2][3800/3862] lr: 2.2977e-04 eta: 20:41:15 time: 1.0738 data_time: 0.0102 memory: 9108 grad_norm: 3.0580 loss: 2.1885 loss_heatmap: 0.8700 layer_-1_loss_cls: 0.1387 layer_-1_loss_bbox: 1.1797 matched_ious: 0.4529 2023/03/22 07:54:55 - mmengine - INFO - Epoch(train) [2][3850/3862] lr: 2.3138e-04 eta: 20:40:22 time: 1.0712 data_time: 0.0105 memory: 8963 grad_norm: 2.8364 loss: 2.2207 loss_heatmap: 0.8707 layer_-1_loss_cls: 0.1402 layer_-1_loss_bbox: 1.2098 matched_ious: 0.4379 2023/03/22 07:55:08 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 07:56:04 - mmengine - INFO - Epoch(train) [3][ 50/3862] lr: 2.3339e-04 eta: 20:39:33 time: 1.1139 data_time: 0.0583 memory: 9219 grad_norm: 2.9294 loss: 2.2619 loss_heatmap: 0.8865 layer_-1_loss_cls: 0.1412 layer_-1_loss_bbox: 1.2341 matched_ious: 0.4393 2023/03/22 07:56:57 - mmengine - INFO - Epoch(train) [3][ 100/3862] lr: 2.3502e-04 eta: 20:38:38 time: 1.0683 data_time: 0.0106 memory: 9185 grad_norm: 2.9214 loss: 2.2245 loss_heatmap: 0.8848 layer_-1_loss_cls: 0.1448 layer_-1_loss_bbox: 1.1949 matched_ious: 0.4239 2023/03/22 07:57:50 - mmengine - INFO - Epoch(train) [3][ 150/3862] lr: 2.3666e-04 eta: 20:37:38 time: 1.0542 data_time: 0.0101 memory: 9425 grad_norm: 2.9127 loss: 2.1832 loss_heatmap: 0.8618 layer_-1_loss_cls: 0.1380 layer_-1_loss_bbox: 1.1834 matched_ious: 0.4324 2023/03/22 07:58:44 - mmengine - INFO - Epoch(train) [3][ 200/3862] lr: 2.3831e-04 eta: 20:36:46 time: 1.0751 data_time: 0.0108 memory: 9109 grad_norm: 3.0018 loss: 2.2498 loss_heatmap: 0.8661 layer_-1_loss_cls: 0.1405 layer_-1_loss_bbox: 1.2432 matched_ious: 0.4069 2023/03/22 07:59:37 - mmengine - INFO - Epoch(train) [3][ 250/3862] lr: 2.3996e-04 eta: 20:35:50 time: 1.0639 data_time: 0.0105 memory: 9460 grad_norm: 3.0139 loss: 2.2919 loss_heatmap: 0.9114 layer_-1_loss_cls: 0.1456 layer_-1_loss_bbox: 1.2349 matched_ious: 0.4484 2023/03/22 08:00:04 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 08:00:30 - mmengine - INFO - Epoch(train) [3][ 300/3862] lr: 2.4162e-04 eta: 20:34:52 time: 1.0605 data_time: 0.0102 memory: 9483 grad_norm: 2.8424 loss: 2.1813 loss_heatmap: 0.8813 layer_-1_loss_cls: 0.1428 layer_-1_loss_bbox: 1.1573 matched_ious: 0.4181 2023/03/22 08:01:23 - mmengine - INFO - Epoch(train) [3][ 350/3862] lr: 2.4329e-04 eta: 20:33:57 time: 1.0670 data_time: 0.0103 memory: 9145 grad_norm: 2.9006 loss: 2.2382 loss_heatmap: 0.8887 layer_-1_loss_cls: 0.1402 layer_-1_loss_bbox: 1.2093 matched_ious: 0.4527 2023/03/22 08:02:16 - mmengine - INFO - Epoch(train) [3][ 400/3862] lr: 2.4497e-04 eta: 20:33:01 time: 1.0640 data_time: 0.0098 memory: 9234 grad_norm: 2.7718 loss: 2.2771 loss_heatmap: 0.8938 layer_-1_loss_cls: 0.1428 layer_-1_loss_bbox: 1.2404 matched_ious: 0.4382 2023/03/22 08:03:09 - mmengine - INFO - Epoch(train) [3][ 450/3862] lr: 2.4666e-04 eta: 20:32:01 time: 1.0564 data_time: 0.0100 memory: 9151 grad_norm: 2.8837 loss: 2.1882 loss_heatmap: 0.8648 layer_-1_loss_cls: 0.1394 layer_-1_loss_bbox: 1.1840 matched_ious: 0.4663 2023/03/22 08:04:03 - mmengine - INFO - Epoch(train) [3][ 500/3862] lr: 2.4835e-04 eta: 20:31:06 time: 1.0673 data_time: 0.0099 memory: 8982 grad_norm: 2.9659 loss: 2.2565 loss_heatmap: 0.8814 layer_-1_loss_cls: 0.1426 layer_-1_loss_bbox: 1.2325 matched_ious: 0.4168 2023/03/22 08:04:56 - mmengine - INFO - Epoch(train) [3][ 550/3862] lr: 2.5005e-04 eta: 20:30:09 time: 1.0601 data_time: 0.0100 memory: 9339 grad_norm: 2.8386 loss: 2.1513 loss_heatmap: 0.8729 layer_-1_loss_cls: 0.1402 layer_-1_loss_bbox: 1.1382 matched_ious: 0.4511 2023/03/22 08:05:49 - mmengine - INFO - Epoch(train) [3][ 600/3862] lr: 2.5176e-04 eta: 20:29:14 time: 1.0683 data_time: 0.0097 memory: 9208 grad_norm: 2.8135 loss: 2.1875 loss_heatmap: 0.8582 layer_-1_loss_cls: 0.1368 layer_-1_loss_bbox: 1.1925 matched_ious: 0.3881 2023/03/22 08:06:42 - mmengine - INFO - Epoch(train) [3][ 650/3862] lr: 2.5348e-04 eta: 20:28:17 time: 1.0618 data_time: 0.0099 memory: 9113 grad_norm: 2.8775 loss: 2.2151 loss_heatmap: 0.8775 layer_-1_loss_cls: 0.1388 layer_-1_loss_bbox: 1.1989 matched_ious: 0.4375 2023/03/22 08:07:35 - mmengine - INFO - Epoch(train) [3][ 700/3862] lr: 2.5520e-04 eta: 20:27:21 time: 1.0641 data_time: 0.0099 memory: 9143 grad_norm: 2.7701 loss: 2.2232 loss_heatmap: 0.8921 layer_-1_loss_cls: 0.1418 layer_-1_loss_bbox: 1.1892 matched_ious: 0.4071 2023/03/22 08:08:29 - mmengine - INFO - Epoch(train) [3][ 750/3862] lr: 2.5694e-04 eta: 20:26:26 time: 1.0659 data_time: 0.0095 memory: 9183 grad_norm: 2.8482 loss: 2.2238 loss_heatmap: 0.8890 layer_-1_loss_cls: 0.1441 layer_-1_loss_bbox: 1.1906 matched_ious: 0.4251 2023/03/22 08:09:23 - mmengine - INFO - Epoch(train) [3][ 800/3862] lr: 2.5867e-04 eta: 20:25:35 time: 1.0761 data_time: 0.0096 memory: 9282 grad_norm: 2.8849 loss: 2.2362 loss_heatmap: 0.8752 layer_-1_loss_cls: 0.1387 layer_-1_loss_bbox: 1.2224 matched_ious: 0.4304 2023/03/22 08:10:16 - mmengine - INFO - Epoch(train) [3][ 850/3862] lr: 2.6042e-04 eta: 20:24:43 time: 1.0734 data_time: 0.0101 memory: 8930 grad_norm: 2.8820 loss: 2.1997 loss_heatmap: 0.8796 layer_-1_loss_cls: 0.1388 layer_-1_loss_bbox: 1.1814 matched_ious: 0.3806 2023/03/22 08:11:09 - mmengine - INFO - Epoch(train) [3][ 900/3862] lr: 2.6218e-04 eta: 20:23:45 time: 1.0584 data_time: 0.0100 memory: 9205 grad_norm: 2.9109 loss: 2.2022 loss_heatmap: 0.8545 layer_-1_loss_cls: 0.1391 layer_-1_loss_bbox: 1.2087 matched_ious: 0.4458 2023/03/22 08:12:02 - mmengine - INFO - Epoch(train) [3][ 950/3862] lr: 2.6394e-04 eta: 20:22:50 time: 1.0663 data_time: 0.0097 memory: 9380 grad_norm: 2.8899 loss: 2.1218 loss_heatmap: 0.8504 layer_-1_loss_cls: 0.1365 layer_-1_loss_bbox: 1.1348 matched_ious: 0.4457 2023/03/22 08:12:55 - mmengine - INFO - Epoch(train) [3][1000/3862] lr: 2.6571e-04 eta: 20:21:52 time: 1.0589 data_time: 0.0097 memory: 9590 grad_norm: 2.7602 loss: 2.1209 loss_heatmap: 0.8410 layer_-1_loss_cls: 0.1379 layer_-1_loss_bbox: 1.1420 matched_ious: 0.4542 2023/03/22 08:13:48 - mmengine - INFO - Epoch(train) [3][1050/3862] lr: 2.6749e-04 eta: 20:20:55 time: 1.0613 data_time: 0.0096 memory: 9156 grad_norm: 2.8968 loss: 2.2110 loss_heatmap: 0.8973 layer_-1_loss_cls: 0.1446 layer_-1_loss_bbox: 1.1690 matched_ious: 0.4758 2023/03/22 08:14:42 - mmengine - INFO - Epoch(train) [3][1100/3862] lr: 2.6927e-04 eta: 20:20:04 time: 1.0774 data_time: 0.0097 memory: 9255 grad_norm: 2.7812 loss: 2.2117 loss_heatmap: 0.8733 layer_-1_loss_cls: 0.1397 layer_-1_loss_bbox: 1.1987 matched_ious: 0.4299 2023/03/22 08:15:35 - mmengine - INFO - Epoch(train) [3][1150/3862] lr: 2.7106e-04 eta: 20:19:07 time: 1.0591 data_time: 0.0100 memory: 9142 grad_norm: 2.7780 loss: 2.1589 loss_heatmap: 0.8666 layer_-1_loss_cls: 0.1401 layer_-1_loss_bbox: 1.1522 matched_ious: 0.4394 2023/03/22 08:16:29 - mmengine - INFO - Epoch(train) [3][1200/3862] lr: 2.7286e-04 eta: 20:18:13 time: 1.0705 data_time: 0.0099 memory: 8976 grad_norm: 2.7732 loss: 2.1120 loss_heatmap: 0.8562 layer_-1_loss_cls: 0.1375 layer_-1_loss_bbox: 1.1183 matched_ious: 0.4867 2023/03/22 08:17:22 - mmengine - INFO - Epoch(train) [3][1250/3862] lr: 2.7467e-04 eta: 20:17:19 time: 1.0676 data_time: 0.0102 memory: 9190 grad_norm: 2.7474 loss: 2.1324 loss_heatmap: 0.8516 layer_-1_loss_cls: 0.1366 layer_-1_loss_bbox: 1.1441 matched_ious: 0.4380 2023/03/22 08:17:50 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 08:18:15 - mmengine - INFO - Epoch(train) [3][1300/3862] lr: 2.7648e-04 eta: 20:16:24 time: 1.0667 data_time: 0.0099 memory: 9260 grad_norm: 2.7364 loss: 2.2109 loss_heatmap: 0.8695 layer_-1_loss_cls: 0.1368 layer_-1_loss_bbox: 1.2046 matched_ious: 0.4132 2023/03/22 08:19:08 - mmengine - INFO - Epoch(train) [3][1350/3862] lr: 2.7830e-04 eta: 20:15:27 time: 1.0598 data_time: 0.0101 memory: 9179 grad_norm: 2.7660 loss: 2.2408 loss_heatmap: 0.8540 layer_-1_loss_cls: 0.1362 layer_-1_loss_bbox: 1.2506 matched_ious: 0.4611 2023/03/22 08:20:02 - mmengine - INFO - Epoch(train) [3][1400/3862] lr: 2.8013e-04 eta: 20:14:35 time: 1.0733 data_time: 0.0100 memory: 9390 grad_norm: 2.6802 loss: 2.1994 loss_heatmap: 0.8941 layer_-1_loss_cls: 0.1422 layer_-1_loss_bbox: 1.1631 matched_ious: 0.4463 2023/03/22 08:20:56 - mmengine - INFO - Epoch(train) [3][1450/3862] lr: 2.8196e-04 eta: 20:13:41 time: 1.0680 data_time: 0.0100 memory: 9205 grad_norm: 2.7622 loss: 2.1933 loss_heatmap: 0.8593 layer_-1_loss_cls: 0.1366 layer_-1_loss_bbox: 1.1973 matched_ious: 0.4435 2023/03/22 08:21:49 - mmengine - INFO - Epoch(train) [3][1500/3862] lr: 2.8380e-04 eta: 20:12:47 time: 1.0685 data_time: 0.0101 memory: 9234 grad_norm: 2.8731 loss: 2.1734 loss_heatmap: 0.8643 layer_-1_loss_cls: 0.1387 layer_-1_loss_bbox: 1.1704 matched_ious: 0.4384 2023/03/22 08:22:42 - mmengine - INFO - Epoch(train) [3][1550/3862] lr: 2.8565e-04 eta: 20:11:52 time: 1.0676 data_time: 0.0100 memory: 9279 grad_norm: 2.6777 loss: 2.1732 loss_heatmap: 0.8552 layer_-1_loss_cls: 0.1367 layer_-1_loss_bbox: 1.1813 matched_ious: 0.4481 2023/03/22 08:23:35 - mmengine - INFO - Epoch(train) [3][1600/3862] lr: 2.8751e-04 eta: 20:10:56 time: 1.0609 data_time: 0.0099 memory: 9168 grad_norm: 2.6909 loss: 2.1261 loss_heatmap: 0.8533 layer_-1_loss_cls: 0.1337 layer_-1_loss_bbox: 1.1391 matched_ious: 0.4408 2023/03/22 08:24:28 - mmengine - INFO - Epoch(train) [3][1650/3862] lr: 2.8937e-04 eta: 20:09:59 time: 1.0604 data_time: 0.0098 memory: 9104 grad_norm: 2.8272 loss: 2.1068 loss_heatmap: 0.8636 layer_-1_loss_cls: 0.1382 layer_-1_loss_bbox: 1.1051 matched_ious: 0.4467 2023/03/22 08:25:22 - mmengine - INFO - Epoch(train) [3][1700/3862] lr: 2.9124e-04 eta: 20:09:04 time: 1.0667 data_time: 0.0098 memory: 9167 grad_norm: 2.8999 loss: 2.1297 loss_heatmap: 0.8734 layer_-1_loss_cls: 0.1401 layer_-1_loss_bbox: 1.1162 matched_ious: 0.4499 2023/03/22 08:26:15 - mmengine - INFO - Epoch(train) [3][1750/3862] lr: 2.9311e-04 eta: 20:08:12 time: 1.0723 data_time: 0.0100 memory: 9083 grad_norm: 2.7312 loss: 2.1807 loss_heatmap: 0.8463 layer_-1_loss_cls: 0.1358 layer_-1_loss_bbox: 1.1986 matched_ious: 0.5075 2023/03/22 08:27:08 - mmengine - INFO - Epoch(train) [3][1800/3862] lr: 2.9499e-04 eta: 20:07:14 time: 1.0591 data_time: 0.0098 memory: 9456 grad_norm: 2.7490 loss: 2.1432 loss_heatmap: 0.8642 layer_-1_loss_cls: 0.1387 layer_-1_loss_bbox: 1.1403 matched_ious: 0.4809 2023/03/22 08:28:02 - mmengine - INFO - Epoch(train) [3][1850/3862] lr: 2.9688e-04 eta: 20:06:20 time: 1.0680 data_time: 0.0102 memory: 9228 grad_norm: 2.6586 loss: 2.1851 loss_heatmap: 0.8580 layer_-1_loss_cls: 0.1341 layer_-1_loss_bbox: 1.1930 matched_ious: 0.4543 2023/03/22 08:28:55 - mmengine - INFO - Epoch(train) [3][1900/3862] lr: 2.9878e-04 eta: 20:05:25 time: 1.0635 data_time: 0.0099 memory: 9261 grad_norm: 2.7086 loss: 2.1064 loss_heatmap: 0.8313 layer_-1_loss_cls: 0.1327 layer_-1_loss_bbox: 1.1424 matched_ious: 0.3992 2023/03/22 08:29:48 - mmengine - INFO - Epoch(train) [3][1950/3862] lr: 3.0068e-04 eta: 20:04:27 time: 1.0574 data_time: 0.0098 memory: 8951 grad_norm: 2.6813 loss: 2.1362 loss_heatmap: 0.8329 layer_-1_loss_cls: 0.1323 layer_-1_loss_bbox: 1.1711 matched_ious: 0.4562 2023/03/22 08:30:41 - mmengine - INFO - Epoch(train) [3][2000/3862] lr: 3.0259e-04 eta: 20:03:31 time: 1.0639 data_time: 0.0100 memory: 9321 grad_norm: 2.7399 loss: 2.1070 loss_heatmap: 0.8501 layer_-1_loss_cls: 0.1360 layer_-1_loss_bbox: 1.1210 matched_ious: 0.4416 2023/03/22 08:31:34 - mmengine - INFO - Epoch(train) [3][2050/3862] lr: 3.0450e-04 eta: 20:02:37 time: 1.0676 data_time: 0.0100 memory: 9675 grad_norm: 2.8132 loss: 2.1360 loss_heatmap: 0.8530 layer_-1_loss_cls: 0.1363 layer_-1_loss_bbox: 1.1467 matched_ious: 0.5066 2023/03/22 08:32:28 - mmengine - INFO - Epoch(train) [3][2100/3862] lr: 3.0642e-04 eta: 20:01:43 time: 1.0663 data_time: 0.0096 memory: 9171 grad_norm: 2.7172 loss: 2.1691 loss_heatmap: 0.8615 layer_-1_loss_cls: 0.1373 layer_-1_loss_bbox: 1.1702 matched_ious: 0.4286 2023/03/22 08:33:21 - mmengine - INFO - Epoch(train) [3][2150/3862] lr: 3.0835e-04 eta: 20:00:50 time: 1.0728 data_time: 0.0101 memory: 9177 grad_norm: 2.7563 loss: 2.1260 loss_heatmap: 0.8569 layer_-1_loss_cls: 0.1351 layer_-1_loss_bbox: 1.1340 matched_ious: 0.4523 2023/03/22 08:34:14 - mmengine - INFO - Epoch(train) [3][2200/3862] lr: 3.1028e-04 eta: 19:59:53 time: 1.0577 data_time: 0.0098 memory: 9248 grad_norm: 2.7183 loss: 2.1488 loss_heatmap: 0.8515 layer_-1_loss_cls: 0.1333 layer_-1_loss_bbox: 1.1640 matched_ious: 0.4523 2023/03/22 08:35:08 - mmengine - INFO - Epoch(train) [3][2250/3862] lr: 3.1222e-04 eta: 19:59:04 time: 1.0838 data_time: 0.0104 memory: 8974 grad_norm: 2.6602 loss: 2.0959 loss_heatmap: 0.8366 layer_-1_loss_cls: 0.1342 layer_-1_loss_bbox: 1.1251 matched_ious: 0.4283 2023/03/22 08:35:36 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 08:36:01 - mmengine - INFO - Epoch(train) [3][2300/3862] lr: 3.1417e-04 eta: 19:58:06 time: 1.0562 data_time: 0.0100 memory: 9365 grad_norm: 2.8805 loss: 2.1726 loss_heatmap: 0.8656 layer_-1_loss_cls: 0.1371 layer_-1_loss_bbox: 1.1699 matched_ious: 0.4627 2023/03/22 08:36:55 - mmengine - INFO - Epoch(train) [3][2350/3862] lr: 3.1612e-04 eta: 19:57:12 time: 1.0660 data_time: 0.0100 memory: 9483 grad_norm: 2.6736 loss: 2.1602 loss_heatmap: 0.8593 layer_-1_loss_cls: 0.1370 layer_-1_loss_bbox: 1.1639 matched_ious: 0.4377 2023/03/22 08:37:47 - mmengine - INFO - Epoch(train) [3][2400/3862] lr: 3.1808e-04 eta: 19:56:14 time: 1.0583 data_time: 0.0107 memory: 9167 grad_norm: 2.6797 loss: 2.0518 loss_heatmap: 0.8293 layer_-1_loss_cls: 0.1327 layer_-1_loss_bbox: 1.0898 matched_ious: 0.4219 2023/03/22 08:38:41 - mmengine - INFO - Epoch(train) [3][2450/3862] lr: 3.2004e-04 eta: 19:55:19 time: 1.0632 data_time: 0.0103 memory: 8968 grad_norm: 2.9248 loss: 2.1014 loss_heatmap: 0.8360 layer_-1_loss_cls: 0.1331 layer_-1_loss_bbox: 1.1323 matched_ious: 0.4469 2023/03/22 08:39:34 - mmengine - INFO - Epoch(train) [3][2500/3862] lr: 3.2201e-04 eta: 19:54:24 time: 1.0653 data_time: 0.0101 memory: 9089 grad_norm: 2.8168 loss: 2.1620 loss_heatmap: 0.8286 layer_-1_loss_cls: 0.1318 layer_-1_loss_bbox: 1.2016 matched_ious: 0.4676 2023/03/22 08:40:27 - mmengine - INFO - Epoch(train) [3][2550/3862] lr: 3.2398e-04 eta: 19:53:27 time: 1.0600 data_time: 0.0103 memory: 9143 grad_norm: 2.7105 loss: 2.0671 loss_heatmap: 0.8227 layer_-1_loss_cls: 0.1335 layer_-1_loss_bbox: 1.1109 matched_ious: 0.4417 2023/03/22 08:41:20 - mmengine - INFO - Epoch(train) [3][2600/3862] lr: 3.2596e-04 eta: 19:52:32 time: 1.0645 data_time: 0.0105 memory: 9148 grad_norm: 2.6684 loss: 2.1329 loss_heatmap: 0.8331 layer_-1_loss_cls: 0.1338 layer_-1_loss_bbox: 1.1660 matched_ious: 0.4383 2023/03/22 08:42:13 - mmengine - INFO - Epoch(train) [3][2650/3862] lr: 3.2795e-04 eta: 19:51:37 time: 1.0639 data_time: 0.0103 memory: 9064 grad_norm: 2.7666 loss: 2.1357 loss_heatmap: 0.8391 layer_-1_loss_cls: 0.1312 layer_-1_loss_bbox: 1.1654 matched_ious: 0.4500 2023/03/22 08:43:07 - mmengine - INFO - Epoch(train) [3][2700/3862] lr: 3.2994e-04 eta: 19:50:43 time: 1.0675 data_time: 0.0101 memory: 9250 grad_norm: 2.7228 loss: 2.1559 loss_heatmap: 0.8623 layer_-1_loss_cls: 0.1354 layer_-1_loss_bbox: 1.1581 matched_ious: 0.4637 2023/03/22 08:44:00 - mmengine - INFO - Epoch(train) [3][2750/3862] lr: 3.3194e-04 eta: 19:49:49 time: 1.0679 data_time: 0.0109 memory: 9047 grad_norm: 2.6667 loss: 2.1029 loss_heatmap: 0.8376 layer_-1_loss_cls: 0.1318 layer_-1_loss_bbox: 1.1336 matched_ious: 0.4282 2023/03/22 08:44:53 - mmengine - INFO - Epoch(train) [3][2800/3862] lr: 3.3395e-04 eta: 19:48:54 time: 1.0626 data_time: 0.0107 memory: 9168 grad_norm: 2.7691 loss: 2.0541 loss_heatmap: 0.8429 layer_-1_loss_cls: 0.1343 layer_-1_loss_bbox: 1.0769 matched_ious: 0.4771 2023/03/22 08:45:46 - mmengine - INFO - Epoch(train) [3][2850/3862] lr: 3.3596e-04 eta: 19:47:58 time: 1.0620 data_time: 0.0104 memory: 9132 grad_norm: 2.6539 loss: 2.1112 loss_heatmap: 0.8472 layer_-1_loss_cls: 0.1330 layer_-1_loss_bbox: 1.1310 matched_ious: 0.4458 2023/03/22 08:46:40 - mmengine - INFO - Epoch(train) [3][2900/3862] lr: 3.3797e-04 eta: 19:47:03 time: 1.0659 data_time: 0.0112 memory: 9234 grad_norm: 2.6456 loss: 2.0946 loss_heatmap: 0.8287 layer_-1_loss_cls: 0.1318 layer_-1_loss_bbox: 1.1341 matched_ious: 0.4391 2023/03/22 08:47:33 - mmengine - INFO - Epoch(train) [3][2950/3862] lr: 3.3999e-04 eta: 19:46:09 time: 1.0645 data_time: 0.0110 memory: 9395 grad_norm: 2.4857 loss: 2.1583 loss_heatmap: 0.8548 layer_-1_loss_cls: 0.1364 layer_-1_loss_bbox: 1.1671 matched_ious: 0.4492 2023/03/22 08:48:26 - mmengine - INFO - Epoch(train) [3][3000/3862] lr: 3.4202e-04 eta: 19:45:14 time: 1.0668 data_time: 0.0107 memory: 9260 grad_norm: 2.6995 loss: 2.0806 loss_heatmap: 0.8242 layer_-1_loss_cls: 0.1320 layer_-1_loss_bbox: 1.1244 matched_ious: 0.4370 2023/03/22 08:49:19 - mmengine - INFO - Epoch(train) [3][3050/3862] lr: 3.4405e-04 eta: 19:44:18 time: 1.0583 data_time: 0.0102 memory: 9033 grad_norm: 2.8390 loss: 2.0678 loss_heatmap: 0.8171 layer_-1_loss_cls: 0.1291 layer_-1_loss_bbox: 1.1217 matched_ious: 0.4355 2023/03/22 08:50:12 - mmengine - INFO - Epoch(train) [3][3100/3862] lr: 3.4609e-04 eta: 19:43:24 time: 1.0677 data_time: 0.0117 memory: 9279 grad_norm: 2.7524 loss: 2.0698 loss_heatmap: 0.8379 layer_-1_loss_cls: 0.1348 layer_-1_loss_bbox: 1.0970 matched_ious: 0.4647 2023/03/22 08:51:05 - mmengine - INFO - Epoch(train) [3][3150/3862] lr: 3.4813e-04 eta: 19:42:28 time: 1.0607 data_time: 0.0115 memory: 9259 grad_norm: 2.6630 loss: 2.0947 loss_heatmap: 0.8176 layer_-1_loss_cls: 0.1285 layer_-1_loss_bbox: 1.1486 matched_ious: 0.4254 2023/03/22 08:51:58 - mmengine - INFO - Epoch(train) [3][3200/3862] lr: 3.5018e-04 eta: 19:41:31 time: 1.0599 data_time: 0.0120 memory: 9252 grad_norm: 2.6351 loss: 2.1912 loss_heatmap: 0.8553 layer_-1_loss_cls: 0.1339 layer_-1_loss_bbox: 1.2021 matched_ious: 0.3859 2023/03/22 08:52:51 - mmengine - INFO - Epoch(train) [3][3250/3862] lr: 3.5223e-04 eta: 19:40:33 time: 1.0534 data_time: 0.0112 memory: 9227 grad_norm: 2.7814 loss: 2.0944 loss_heatmap: 0.8293 layer_-1_loss_cls: 0.1302 layer_-1_loss_bbox: 1.1349 matched_ious: 0.4700 2023/03/22 08:53:19 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 08:53:44 - mmengine - INFO - Epoch(train) [3][3300/3862] lr: 3.5429e-04 eta: 19:39:38 time: 1.0637 data_time: 0.0107 memory: 9068 grad_norm: 2.6186 loss: 2.0832 loss_heatmap: 0.8407 layer_-1_loss_cls: 0.1329 layer_-1_loss_bbox: 1.1095 matched_ious: 0.4335 2023/03/22 08:54:38 - mmengine - INFO - Epoch(train) [3][3350/3862] lr: 3.5635e-04 eta: 19:38:47 time: 1.0764 data_time: 0.0111 memory: 9223 grad_norm: 2.6100 loss: 2.0583 loss_heatmap: 0.8168 layer_-1_loss_cls: 0.1311 layer_-1_loss_bbox: 1.1104 matched_ious: 0.4023 2023/03/22 08:55:32 - mmengine - INFO - Epoch(train) [3][3400/3862] lr: 3.5842e-04 eta: 19:37:57 time: 1.0788 data_time: 0.0116 memory: 9377 grad_norm: 2.7374 loss: 2.1320 loss_heatmap: 0.8413 layer_-1_loss_cls: 0.1317 layer_-1_loss_bbox: 1.1590 matched_ious: 0.5337 2023/03/22 08:56:25 - mmengine - INFO - Epoch(train) [3][3450/3862] lr: 3.6049e-04 eta: 19:37:01 time: 1.0630 data_time: 0.0118 memory: 8990 grad_norm: 2.4539 loss: 2.0926 loss_heatmap: 0.8376 layer_-1_loss_cls: 0.1317 layer_-1_loss_bbox: 1.1233 matched_ious: 0.4204 2023/03/22 08:57:18 - mmengine - INFO - Epoch(train) [3][3500/3862] lr: 3.6257e-04 eta: 19:36:05 time: 1.0575 data_time: 0.0118 memory: 9309 grad_norm: 2.5412 loss: 2.1379 loss_heatmap: 0.8405 layer_-1_loss_cls: 0.1305 layer_-1_loss_bbox: 1.1669 matched_ious: 0.4370 2023/03/22 08:58:11 - mmengine - INFO - Epoch(train) [3][3550/3862] lr: 3.6465e-04 eta: 19:35:10 time: 1.0636 data_time: 0.0117 memory: 9230 grad_norm: 2.5529 loss: 2.1393 loss_heatmap: 0.8605 layer_-1_loss_cls: 0.1334 layer_-1_loss_bbox: 1.1454 matched_ious: 0.4316 2023/03/22 08:59:05 - mmengine - INFO - Epoch(train) [3][3600/3862] lr: 3.6674e-04 eta: 19:34:16 time: 1.0670 data_time: 0.0117 memory: 9037 grad_norm: 2.5473 loss: 2.0974 loss_heatmap: 0.8211 layer_-1_loss_cls: 0.1295 layer_-1_loss_bbox: 1.1467 matched_ious: 0.4750 2023/03/22 08:59:58 - mmengine - INFO - Epoch(train) [3][3650/3862] lr: 3.6883e-04 eta: 19:33:23 time: 1.0727 data_time: 0.0117 memory: 9099 grad_norm: 2.4178 loss: 2.0151 loss_heatmap: 0.7820 layer_-1_loss_cls: 0.1230 layer_-1_loss_bbox: 1.1101 matched_ious: 0.4679 2023/03/22 09:00:52 - mmengine - INFO - Epoch(train) [3][3700/3862] lr: 3.7093e-04 eta: 19:32:30 time: 1.0683 data_time: 0.0116 memory: 9297 grad_norm: 2.5258 loss: 2.1111 loss_heatmap: 0.8420 layer_-1_loss_cls: 0.1316 layer_-1_loss_bbox: 1.1376 matched_ious: 0.4392 2023/03/22 09:01:45 - mmengine - INFO - Epoch(train) [3][3750/3862] lr: 3.7303e-04 eta: 19:31:37 time: 1.0707 data_time: 0.0120 memory: 9485 grad_norm: 2.5944 loss: 2.0600 loss_heatmap: 0.8339 layer_-1_loss_cls: 0.1327 layer_-1_loss_bbox: 1.0933 matched_ious: 0.4500 2023/03/22 09:02:39 - mmengine - INFO - Epoch(train) [3][3800/3862] lr: 3.7513e-04 eta: 19:30:42 time: 1.0650 data_time: 0.0117 memory: 9269 grad_norm: 2.4034 loss: 2.0874 loss_heatmap: 0.8482 layer_-1_loss_cls: 0.1339 layer_-1_loss_bbox: 1.1053 matched_ious: 0.4550 2023/03/22 09:03:32 - mmengine - INFO - Epoch(train) [3][3850/3862] lr: 3.7724e-04 eta: 19:29:47 time: 1.0641 data_time: 0.0119 memory: 9425 grad_norm: 2.6809 loss: 1.9953 loss_heatmap: 0.7919 layer_-1_loss_cls: 0.1274 layer_-1_loss_bbox: 1.0760 matched_ious: 0.4898 2023/03/22 09:03:44 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 09:04:40 - mmengine - INFO - Epoch(train) [4][ 50/3862] lr: 3.7987e-04 eta: 19:28:54 time: 1.1186 data_time: 0.0650 memory: 9102 grad_norm: 2.5922 loss: 2.0959 loss_heatmap: 0.8201 layer_-1_loss_cls: 0.1295 layer_-1_loss_bbox: 1.1464 matched_ious: 0.4890 2023/03/22 09:05:34 - mmengine - INFO - Epoch(train) [4][ 100/3862] lr: 3.8199e-04 eta: 19:28:00 time: 1.0653 data_time: 0.0114 memory: 8951 grad_norm: 2.4952 loss: 2.0897 loss_heatmap: 0.8174 layer_-1_loss_cls: 0.1295 layer_-1_loss_bbox: 1.1429 matched_ious: 0.5042 2023/03/22 09:06:27 - mmengine - INFO - Epoch(train) [4][ 150/3862] lr: 3.8411e-04 eta: 19:27:04 time: 1.0604 data_time: 0.0121 memory: 9343 grad_norm: 2.5840 loss: 2.0722 loss_heatmap: 0.8291 layer_-1_loss_cls: 0.1312 layer_-1_loss_bbox: 1.1119 matched_ious: 0.4593 2023/03/22 09:07:20 - mmengine - INFO - Epoch(train) [4][ 200/3862] lr: 3.8624e-04 eta: 19:26:08 time: 1.0608 data_time: 0.0117 memory: 9382 grad_norm: 2.5104 loss: 2.0565 loss_heatmap: 0.8201 layer_-1_loss_cls: 0.1313 layer_-1_loss_bbox: 1.1052 matched_ious: 0.4781 2023/03/22 09:08:13 - mmengine - INFO - Epoch(train) [4][ 250/3862] lr: 3.8837e-04 eta: 19:25:14 time: 1.0655 data_time: 0.0118 memory: 9159 grad_norm: 2.5059 loss: 2.1148 loss_heatmap: 0.8129 layer_-1_loss_cls: 0.1298 layer_-1_loss_bbox: 1.1722 matched_ious: 0.4209 2023/03/22 09:09:06 - mmengine - INFO - Epoch(train) [4][ 300/3862] lr: 3.9051e-04 eta: 19:24:19 time: 1.0649 data_time: 0.0111 memory: 9388 grad_norm: 2.5729 loss: 2.0457 loss_heatmap: 0.8330 layer_-1_loss_cls: 0.1326 layer_-1_loss_bbox: 1.0801 matched_ious: 0.4692 2023/03/22 09:10:00 - mmengine - INFO - Epoch(train) [4][ 350/3862] lr: 3.9265e-04 eta: 19:23:26 time: 1.0696 data_time: 0.0119 memory: 9257 grad_norm: 2.3894 loss: 2.0184 loss_heatmap: 0.7814 layer_-1_loss_cls: 0.1271 layer_-1_loss_bbox: 1.1099 matched_ious: 0.4870 2023/03/22 09:10:53 - mmengine - INFO - Epoch(train) [4][ 400/3862] lr: 3.9480e-04 eta: 19:22:30 time: 1.0607 data_time: 0.0113 memory: 9369 grad_norm: 2.4547 loss: 1.9927 loss_heatmap: 0.7985 layer_-1_loss_cls: 0.1274 layer_-1_loss_bbox: 1.0667 matched_ious: 0.4778 2023/03/22 09:11:08 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 09:11:46 - mmengine - INFO - Epoch(train) [4][ 450/3862] lr: 3.9695e-04 eta: 19:21:36 time: 1.0665 data_time: 0.0115 memory: 9062 grad_norm: 2.6939 loss: 2.0640 loss_heatmap: 0.8252 layer_-1_loss_cls: 0.1319 layer_-1_loss_bbox: 1.1070 matched_ious: 0.4456 2023/03/22 09:12:40 - mmengine - INFO - Epoch(train) [4][ 500/3862] lr: 3.9910e-04 eta: 19:20:43 time: 1.0695 data_time: 0.0120 memory: 9197 grad_norm: 2.4863 loss: 1.9606 loss_heatmap: 0.7927 layer_-1_loss_cls: 0.1266 layer_-1_loss_bbox: 1.0412 matched_ious: 0.4086 2023/03/22 09:13:33 - mmengine - INFO - Epoch(train) [4][ 550/3862] lr: 4.0126e-04 eta: 19:19:48 time: 1.0632 data_time: 0.0119 memory: 9306 grad_norm: 2.3989 loss: 2.1130 loss_heatmap: 0.8449 layer_-1_loss_cls: 0.1336 layer_-1_loss_bbox: 1.1344 matched_ious: 0.4285 2023/03/22 09:14:26 - mmengine - INFO - Epoch(train) [4][ 600/3862] lr: 4.0342e-04 eta: 19:18:53 time: 1.0620 data_time: 0.0122 memory: 9057 grad_norm: 2.5266 loss: 2.0533 loss_heatmap: 0.8176 layer_-1_loss_cls: 0.1276 layer_-1_loss_bbox: 1.1081 matched_ious: 0.4367 2023/03/22 09:15:20 - mmengine - INFO - Epoch(train) [4][ 650/3862] lr: 4.0558e-04 eta: 19:18:03 time: 1.0816 data_time: 0.0116 memory: 9160 grad_norm: 2.4176 loss: 2.0322 loss_heatmap: 0.8023 layer_-1_loss_cls: 0.1265 layer_-1_loss_bbox: 1.1034 matched_ious: 0.4737 2023/03/22 09:16:13 - mmengine - INFO - Epoch(train) [4][ 700/3862] lr: 4.0775e-04 eta: 19:17:09 time: 1.0670 data_time: 0.0114 memory: 9124 grad_norm: 2.4010 loss: 2.0289 loss_heatmap: 0.8092 layer_-1_loss_cls: 0.1276 layer_-1_loss_bbox: 1.0921 matched_ious: 0.4513 2023/03/22 09:17:06 - mmengine - INFO - Epoch(train) [4][ 750/3862] lr: 4.0992e-04 eta: 19:16:12 time: 1.0574 data_time: 0.0117 memory: 9337 grad_norm: 2.4048 loss: 2.0953 loss_heatmap: 0.8402 layer_-1_loss_cls: 0.1297 layer_-1_loss_bbox: 1.1254 matched_ious: 0.4419 2023/03/22 09:18:00 - mmengine - INFO - Epoch(train) [4][ 800/3862] lr: 4.1210e-04 eta: 19:15:19 time: 1.0698 data_time: 0.0114 memory: 9318 grad_norm: 2.5917 loss: 1.9972 loss_heatmap: 0.7955 layer_-1_loss_cls: 0.1245 layer_-1_loss_bbox: 1.0772 matched_ious: 0.4979 2023/03/22 09:18:53 - mmengine - INFO - Epoch(train) [4][ 850/3862] lr: 4.1428e-04 eta: 19:14:26 time: 1.0696 data_time: 0.0113 memory: 9164 grad_norm: 2.4323 loss: 2.0813 loss_heatmap: 0.8368 layer_-1_loss_cls: 0.1310 layer_-1_loss_bbox: 1.1135 matched_ious: 0.4267 2023/03/22 09:19:46 - mmengine - INFO - Epoch(train) [4][ 900/3862] lr: 4.1646e-04 eta: 19:13:31 time: 1.0627 data_time: 0.0115 memory: 9321 grad_norm: 2.6179 loss: 1.9995 loss_heatmap: 0.8124 layer_-1_loss_cls: 0.1263 layer_-1_loss_bbox: 1.0608 matched_ious: 0.4474 2023/03/22 09:20:39 - mmengine - INFO - Epoch(train) [4][ 950/3862] lr: 4.1865e-04 eta: 19:12:36 time: 1.0634 data_time: 0.0113 memory: 9110 grad_norm: 2.3886 loss: 2.0524 loss_heatmap: 0.8226 layer_-1_loss_cls: 0.1312 layer_-1_loss_bbox: 1.0985 matched_ious: 0.4490 2023/03/22 09:21:32 - mmengine - INFO - Epoch(train) [4][1000/3862] lr: 4.2084e-04 eta: 19:11:40 time: 1.0572 data_time: 0.0114 memory: 9021 grad_norm: 2.4325 loss: 2.0660 loss_heatmap: 0.8184 layer_-1_loss_cls: 0.1262 layer_-1_loss_bbox: 1.1214 matched_ious: 0.4790 2023/03/22 09:22:26 - mmengine - INFO - Epoch(train) [4][1050/3862] lr: 4.2303e-04 eta: 19:10:46 time: 1.0686 data_time: 0.0112 memory: 8995 grad_norm: 2.5293 loss: 2.0139 loss_heatmap: 0.8107 layer_-1_loss_cls: 0.1293 layer_-1_loss_bbox: 1.0739 matched_ious: 0.4567 2023/03/22 09:23:19 - mmengine - INFO - Epoch(train) [4][1100/3862] lr: 4.2523e-04 eta: 19:09:52 time: 1.0653 data_time: 0.0119 memory: 9427 grad_norm: 2.4258 loss: 2.0239 loss_heatmap: 0.8048 layer_-1_loss_cls: 0.1301 layer_-1_loss_bbox: 1.0890 matched_ious: 0.4681 2023/03/22 09:24:13 - mmengine - INFO - Epoch(train) [4][1150/3862] lr: 4.2743e-04 eta: 19:09:01 time: 1.0802 data_time: 0.0122 memory: 9252 grad_norm: 2.5023 loss: 1.9575 loss_heatmap: 0.7826 layer_-1_loss_cls: 0.1219 layer_-1_loss_bbox: 1.0530 matched_ious: 0.4404 2023/03/22 09:25:06 - mmengine - INFO - Epoch(train) [4][1200/3862] lr: 4.2963e-04 eta: 19:08:06 time: 1.0636 data_time: 0.0119 memory: 9499 grad_norm: 2.4175 loss: 2.0154 loss_heatmap: 0.8136 layer_-1_loss_cls: 0.1303 layer_-1_loss_bbox: 1.0716 matched_ious: 0.4856 2023/03/22 09:25:59 - mmengine - INFO - Epoch(train) [4][1250/3862] lr: 4.3184e-04 eta: 19:07:09 time: 1.0526 data_time: 0.0117 memory: 9232 grad_norm: 2.3522 loss: 1.9876 loss_heatmap: 0.8064 layer_-1_loss_cls: 0.1272 layer_-1_loss_bbox: 1.0540 matched_ious: 0.4347 2023/03/22 09:26:52 - mmengine - INFO - Epoch(train) [4][1300/3862] lr: 4.3405e-04 eta: 19:06:15 time: 1.0663 data_time: 0.0121 memory: 8920 grad_norm: 2.2433 loss: 2.0406 loss_heatmap: 0.8131 layer_-1_loss_cls: 0.1267 layer_-1_loss_bbox: 1.1008 matched_ious: 0.4282 2023/03/22 09:27:46 - mmengine - INFO - Epoch(train) [4][1350/3862] lr: 4.3626e-04 eta: 19:05:22 time: 1.0707 data_time: 0.0119 memory: 8931 grad_norm: 2.3979 loss: 2.0403 loss_heatmap: 0.8165 layer_-1_loss_cls: 0.1305 layer_-1_loss_bbox: 1.0932 matched_ious: 0.4707 2023/03/22 09:28:39 - mmengine - INFO - Epoch(train) [4][1400/3862] lr: 4.3847e-04 eta: 19:04:27 time: 1.0604 data_time: 0.0120 memory: 9198 grad_norm: 2.4769 loss: 2.0568 loss_heatmap: 0.8187 layer_-1_loss_cls: 0.1285 layer_-1_loss_bbox: 1.1096 matched_ious: 0.4935 2023/03/22 09:28:53 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 09:29:31 - mmengine - INFO - Epoch(train) [4][1450/3862] lr: 4.4069e-04 eta: 19:03:28 time: 1.0486 data_time: 0.0116 memory: 9207 grad_norm: 2.2815 loss: 2.0410 loss_heatmap: 0.8214 layer_-1_loss_cls: 0.1297 layer_-1_loss_bbox: 1.0898 matched_ious: 0.4960 2023/03/22 09:30:25 - mmengine - INFO - Epoch(train) [4][1500/3862] lr: 4.4291e-04 eta: 19:02:35 time: 1.0697 data_time: 0.0119 memory: 8892 grad_norm: 2.4020 loss: 2.0302 loss_heatmap: 0.8200 layer_-1_loss_cls: 0.1286 layer_-1_loss_bbox: 1.0816 matched_ious: 0.4750 2023/03/22 09:31:18 - mmengine - INFO - Epoch(train) [4][1550/3862] lr: 4.4514e-04 eta: 19:01:41 time: 1.0663 data_time: 0.0122 memory: 8926 grad_norm: 2.3881 loss: 2.0038 loss_heatmap: 0.8010 layer_-1_loss_cls: 0.1267 layer_-1_loss_bbox: 1.0761 matched_ious: 0.4535 2023/03/22 09:32:11 - mmengine - INFO - Epoch(train) [4][1600/3862] lr: 4.4736e-04 eta: 19:00:47 time: 1.0650 data_time: 0.0122 memory: 9264 grad_norm: 2.3608 loss: 2.0864 loss_heatmap: 0.8435 layer_-1_loss_cls: 0.1295 layer_-1_loss_bbox: 1.1134 matched_ious: 0.4513 2023/03/22 09:33:04 - mmengine - INFO - Epoch(train) [4][1650/3862] lr: 4.4959e-04 eta: 18:59:50 time: 1.0547 data_time: 0.0120 memory: 9038 grad_norm: 2.4743 loss: 2.0222 loss_heatmap: 0.8128 layer_-1_loss_cls: 0.1281 layer_-1_loss_bbox: 1.0813 matched_ious: 0.4200 2023/03/22 09:33:57 - mmengine - INFO - Epoch(train) [4][1700/3862] lr: 4.5182e-04 eta: 18:58:54 time: 1.0593 data_time: 0.0116 memory: 8959 grad_norm: 2.5858 loss: 1.9723 loss_heatmap: 0.8014 layer_-1_loss_cls: 0.1257 layer_-1_loss_bbox: 1.0451 matched_ious: 0.4721 2023/03/22 09:34:50 - mmengine - INFO - Epoch(train) [4][1750/3862] lr: 4.5406e-04 eta: 18:58:00 time: 1.0648 data_time: 0.0125 memory: 9142 grad_norm: 2.2926 loss: 1.9846 loss_heatmap: 0.7962 layer_-1_loss_cls: 0.1239 layer_-1_loss_bbox: 1.0645 matched_ious: 0.4613 2023/03/22 09:35:44 - mmengine - INFO - Epoch(train) [4][1800/3862] lr: 4.5629e-04 eta: 18:57:11 time: 1.0859 data_time: 0.0121 memory: 9068 grad_norm: 2.4369 loss: 1.9228 loss_heatmap: 0.7779 layer_-1_loss_cls: 0.1233 layer_-1_loss_bbox: 1.0216 matched_ious: 0.4331 2023/03/22 09:36:38 - mmengine - INFO - Epoch(train) [4][1850/3862] lr: 4.5853e-04 eta: 18:56:17 time: 1.0681 data_time: 0.0119 memory: 9127 grad_norm: 2.2913 loss: 2.0706 loss_heatmap: 0.8298 layer_-1_loss_cls: 0.1303 layer_-1_loss_bbox: 1.1105 matched_ious: 0.4937 2023/03/22 09:37:31 - mmengine - INFO - Epoch(train) [4][1900/3862] lr: 4.6077e-04 eta: 18:55:21 time: 1.0589 data_time: 0.0120 memory: 9052 grad_norm: 2.2616 loss: 1.9983 loss_heatmap: 0.8086 layer_-1_loss_cls: 0.1283 layer_-1_loss_bbox: 1.0614 matched_ious: 0.4569 2023/03/22 09:38:24 - mmengine - INFO - Epoch(train) [4][1950/3862] lr: 4.6302e-04 eta: 18:54:28 time: 1.0691 data_time: 0.0122 memory: 9061 grad_norm: 2.3789 loss: 2.0732 loss_heatmap: 0.8106 layer_-1_loss_cls: 0.1263 layer_-1_loss_bbox: 1.1363 matched_ious: 0.4471 2023/03/22 09:39:18 - mmengine - INFO - Epoch(train) [4][2000/3862] lr: 4.6526e-04 eta: 18:53:34 time: 1.0674 data_time: 0.0122 memory: 9216 grad_norm: 2.3985 loss: 1.9830 loss_heatmap: 0.8043 layer_-1_loss_cls: 0.1249 layer_-1_loss_bbox: 1.0538 matched_ious: 0.4623 2023/03/22 09:40:11 - mmengine - INFO - Epoch(train) [4][2050/3862] lr: 4.6751e-04 eta: 18:52:39 time: 1.0615 data_time: 0.0123 memory: 9146 grad_norm: 2.3162 loss: 2.0230 loss_heatmap: 0.7976 layer_-1_loss_cls: 0.1268 layer_-1_loss_bbox: 1.0986 matched_ious: 0.4588 2023/03/22 09:41:05 - mmengine - INFO - Epoch(train) [4][2100/3862] lr: 4.6976e-04 eta: 18:51:48 time: 1.0773 data_time: 0.0124 memory: 9211 grad_norm: 2.2044 loss: 1.9954 loss_heatmap: 0.7963 layer_-1_loss_cls: 0.1244 layer_-1_loss_bbox: 1.0747 matched_ious: 0.4633 2023/03/22 09:41:58 - mmengine - INFO - Epoch(train) [4][2150/3862] lr: 4.7201e-04 eta: 18:50:54 time: 1.0659 data_time: 0.0123 memory: 9291 grad_norm: 2.2835 loss: 1.9978 loss_heatmap: 0.7952 layer_-1_loss_cls: 0.1244 layer_-1_loss_bbox: 1.0781 matched_ious: 0.4687 2023/03/22 09:42:51 - mmengine - INFO - Epoch(train) [4][2200/3862] lr: 4.7427e-04 eta: 18:50:01 time: 1.0698 data_time: 0.0127 memory: 9053 grad_norm: 2.1709 loss: 1.9745 loss_heatmap: 0.7969 layer_-1_loss_cls: 0.1242 layer_-1_loss_bbox: 1.0533 matched_ious: 0.4491 2023/03/22 09:43:45 - mmengine - INFO - Epoch(train) [4][2250/3862] lr: 4.7652e-04 eta: 18:49:10 time: 1.0804 data_time: 0.0127 memory: 9386 grad_norm: 2.3287 loss: 2.0107 loss_heatmap: 0.8050 layer_-1_loss_cls: 0.1278 layer_-1_loss_bbox: 1.0779 matched_ious: 0.4022 2023/03/22 09:44:39 - mmengine - INFO - Epoch(train) [4][2300/3862] lr: 4.7878e-04 eta: 18:48:16 time: 1.0670 data_time: 0.0119 memory: 9201 grad_norm: 2.1665 loss: 1.9536 loss_heatmap: 0.7830 layer_-1_loss_cls: 0.1217 layer_-1_loss_bbox: 1.0489 matched_ious: 0.4427 2023/03/22 09:45:32 - mmengine - INFO - Epoch(train) [4][2350/3862] lr: 4.8104e-04 eta: 18:47:23 time: 1.0668 data_time: 0.0124 memory: 9224 grad_norm: 2.0514 loss: 1.9746 loss_heatmap: 0.7947 layer_-1_loss_cls: 0.1247 layer_-1_loss_bbox: 1.0551 matched_ious: 0.4289 2023/03/22 09:46:25 - mmengine - INFO - Epoch(train) [4][2400/3862] lr: 4.8330e-04 eta: 18:46:29 time: 1.0669 data_time: 0.0122 memory: 8988 grad_norm: 2.2740 loss: 1.9891 loss_heatmap: 0.8079 layer_-1_loss_cls: 0.1270 layer_-1_loss_bbox: 1.0543 matched_ious: 0.4454 2023/03/22 09:46:40 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 09:47:19 - mmengine - INFO - Epoch(train) [4][2450/3862] lr: 4.8557e-04 eta: 18:45:36 time: 1.0718 data_time: 0.0120 memory: 9155 grad_norm: 2.0983 loss: 1.9563 loss_heatmap: 0.8036 layer_-1_loss_cls: 0.1237 layer_-1_loss_bbox: 1.0289 matched_ious: 0.4866 2023/03/22 09:48:12 - mmengine - INFO - Epoch(train) [4][2500/3862] lr: 4.8783e-04 eta: 18:44:43 time: 1.0687 data_time: 0.0126 memory: 8974 grad_norm: 2.1611 loss: 1.9975 loss_heatmap: 0.8024 layer_-1_loss_cls: 0.1278 layer_-1_loss_bbox: 1.0672 matched_ious: 0.4780 2023/03/22 09:49:06 - mmengine - INFO - Epoch(train) [4][2550/3862] lr: 4.9010e-04 eta: 18:43:49 time: 1.0693 data_time: 0.0123 memory: 9187 grad_norm: 2.1956 loss: 2.0185 loss_heatmap: 0.8271 layer_-1_loss_cls: 0.1279 layer_-1_loss_bbox: 1.0634 matched_ious: 0.4898 2023/03/22 09:49:59 - mmengine - INFO - Epoch(train) [4][2600/3862] lr: 4.9237e-04 eta: 18:42:54 time: 1.0597 data_time: 0.0124 memory: 9224 grad_norm: 2.1854 loss: 2.0097 loss_heatmap: 0.8216 layer_-1_loss_cls: 0.1308 layer_-1_loss_bbox: 1.0573 matched_ious: 0.5018 2023/03/22 09:50:52 - mmengine - INFO - Epoch(train) [4][2650/3862] lr: 4.9464e-04 eta: 18:41:58 time: 1.0584 data_time: 0.0118 memory: 9391 grad_norm: 2.3013 loss: 1.9842 loss_heatmap: 0.7971 layer_-1_loss_cls: 0.1250 layer_-1_loss_bbox: 1.0621 matched_ious: 0.4804 2023/03/22 09:51:45 - mmengine - INFO - Epoch(train) [4][2700/3862] lr: 4.9691e-04 eta: 18:41:02 time: 1.0559 data_time: 0.0122 memory: 9269 grad_norm: 2.1552 loss: 1.9989 loss_heatmap: 0.8103 layer_-1_loss_cls: 0.1269 layer_-1_loss_bbox: 1.0617 matched_ious: 0.4631 2023/03/22 09:52:38 - mmengine - INFO - Epoch(train) [4][2750/3862] lr: 4.9918e-04 eta: 18:40:10 time: 1.0721 data_time: 0.0124 memory: 9226 grad_norm: 2.3341 loss: 1.9961 loss_heatmap: 0.7990 layer_-1_loss_cls: 0.1281 layer_-1_loss_bbox: 1.0690 matched_ious: 0.4238 2023/03/22 09:53:31 - mmengine - INFO - Epoch(train) [4][2800/3862] lr: 5.0145e-04 eta: 18:39:15 time: 1.0629 data_time: 0.0120 memory: 9110 grad_norm: 2.4169 loss: 2.0055 loss_heatmap: 0.8009 layer_-1_loss_cls: 0.1240 layer_-1_loss_bbox: 1.0806 matched_ious: 0.4620 2023/03/22 09:54:24 - mmengine - INFO - Epoch(train) [4][2850/3862] lr: 5.0373e-04 eta: 18:38:20 time: 1.0620 data_time: 0.0119 memory: 9439 grad_norm: 2.2682 loss: 1.9903 loss_heatmap: 0.8155 layer_-1_loss_cls: 0.1267 layer_-1_loss_bbox: 1.0481 matched_ious: 0.4571 2023/03/22 09:55:18 - mmengine - INFO - Epoch(train) [4][2900/3862] lr: 5.0601e-04 eta: 18:37:26 time: 1.0657 data_time: 0.0119 memory: 9389 grad_norm: 2.3266 loss: 1.9371 loss_heatmap: 0.7823 layer_-1_loss_cls: 0.1238 layer_-1_loss_bbox: 1.0310 matched_ious: 0.4759 2023/03/22 09:56:11 - mmengine - INFO - Epoch(train) [4][2950/3862] lr: 5.0828e-04 eta: 18:36:33 time: 1.0700 data_time: 0.0121 memory: 9361 grad_norm: 2.2406 loss: 2.0347 loss_heatmap: 0.8040 layer_-1_loss_cls: 0.1260 layer_-1_loss_bbox: 1.1047 matched_ious: 0.4229 2023/03/22 09:57:04 - mmengine - INFO - Epoch(train) [4][3000/3862] lr: 5.1056e-04 eta: 18:35:37 time: 1.0570 data_time: 0.0124 memory: 9089 grad_norm: 2.0703 loss: 2.0041 loss_heatmap: 0.8233 layer_-1_loss_cls: 0.1303 layer_-1_loss_bbox: 1.0505 matched_ious: 0.4817 2023/03/22 09:57:57 - mmengine - INFO - Epoch(train) [4][3050/3862] lr: 5.1284e-04 eta: 18:34:44 time: 1.0685 data_time: 0.0121 memory: 9343 grad_norm: 2.0421 loss: 1.9940 loss_heatmap: 0.7931 layer_-1_loss_cls: 0.1244 layer_-1_loss_bbox: 1.0765 matched_ious: 0.4290 2023/03/22 09:58:51 - mmengine - INFO - Epoch(train) [4][3100/3862] lr: 5.1512e-04 eta: 18:33:52 time: 1.0743 data_time: 0.0123 memory: 9202 grad_norm: 2.1622 loss: 1.9684 loss_heatmap: 0.7970 layer_-1_loss_cls: 0.1262 layer_-1_loss_bbox: 1.0453 matched_ious: 0.4851 2023/03/22 09:59:45 - mmengine - INFO - Epoch(train) [4][3150/3862] lr: 5.1740e-04 eta: 18:32:59 time: 1.0728 data_time: 0.0118 memory: 9114 grad_norm: 2.2825 loss: 1.9866 loss_heatmap: 0.7837 layer_-1_loss_cls: 0.1222 layer_-1_loss_bbox: 1.0807 matched_ious: 0.5003 2023/03/22 10:00:39 - mmengine - INFO - Epoch(train) [4][3200/3862] lr: 5.1969e-04 eta: 18:32:07 time: 1.0747 data_time: 0.0114 memory: 9061 grad_norm: 2.1579 loss: 1.9734 loss_heatmap: 0.7711 layer_-1_loss_cls: 0.1212 layer_-1_loss_bbox: 1.0811 matched_ious: 0.4629 2023/03/22 10:01:32 - mmengine - INFO - Epoch(train) [4][3250/3862] lr: 5.2197e-04 eta: 18:31:12 time: 1.0621 data_time: 0.0114 memory: 9455 grad_norm: 2.2084 loss: 2.0214 loss_heatmap: 0.8200 layer_-1_loss_cls: 0.1266 layer_-1_loss_bbox: 1.0749 matched_ious: 0.4797 2023/03/22 10:02:25 - mmengine - INFO - Epoch(train) [4][3300/3862] lr: 5.2425e-04 eta: 18:30:19 time: 1.0706 data_time: 0.0113 memory: 9351 grad_norm: 1.9505 loss: 1.9716 loss_heatmap: 0.7933 layer_-1_loss_cls: 0.1238 layer_-1_loss_bbox: 1.0546 matched_ious: 0.4667 2023/03/22 10:03:18 - mmengine - INFO - Epoch(train) [4][3350/3862] lr: 5.2654e-04 eta: 18:29:25 time: 1.0632 data_time: 0.0114 memory: 9185 grad_norm: 1.9977 loss: 1.9137 loss_heatmap: 0.7827 layer_-1_loss_cls: 0.1225 layer_-1_loss_bbox: 1.0085 matched_ious: 0.4269 2023/03/22 10:04:12 - mmengine - INFO - Epoch(train) [4][3400/3862] lr: 5.2882e-04 eta: 18:28:30 time: 1.0643 data_time: 0.0113 memory: 8990 grad_norm: 2.1402 loss: 2.0163 loss_heatmap: 0.8107 layer_-1_loss_cls: 0.1268 layer_-1_loss_bbox: 1.0787 matched_ious: 0.4582 2023/03/22 10:04:27 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 10:05:05 - mmengine - INFO - Epoch(train) [4][3450/3862] lr: 5.3111e-04 eta: 18:27:36 time: 1.0637 data_time: 0.0115 memory: 8973 grad_norm: 2.1845 loss: 1.9597 loss_heatmap: 0.7770 layer_-1_loss_cls: 0.1232 layer_-1_loss_bbox: 1.0595 matched_ious: 0.4321 2023/03/22 10:05:58 - mmengine - INFO - Epoch(train) [4][3500/3862] lr: 5.3339e-04 eta: 18:26:42 time: 1.0659 data_time: 0.0117 memory: 9259 grad_norm: 1.9927 loss: 2.0359 loss_heatmap: 0.8281 layer_-1_loss_cls: 0.1301 layer_-1_loss_bbox: 1.0778 matched_ious: 0.4588 2023/03/22 10:06:52 - mmengine - INFO - Epoch(train) [4][3550/3862] lr: 5.3568e-04 eta: 18:25:49 time: 1.0698 data_time: 0.0116 memory: 9025 grad_norm: 2.2414 loss: 2.0249 loss_heatmap: 0.8067 layer_-1_loss_cls: 0.1259 layer_-1_loss_bbox: 1.0924 matched_ious: 0.5000 2023/03/22 10:07:45 - mmengine - INFO - Epoch(train) [4][3600/3862] lr: 5.3797e-04 eta: 18:24:56 time: 1.0693 data_time: 0.0118 memory: 9407 grad_norm: 1.8905 loss: 1.9984 loss_heatmap: 0.8019 layer_-1_loss_cls: 0.1242 layer_-1_loss_bbox: 1.0723 matched_ious: 0.4525 2023/03/22 10:08:38 - mmengine - INFO - Epoch(train) [4][3650/3862] lr: 5.4025e-04 eta: 18:24:02 time: 1.0663 data_time: 0.0119 memory: 8840 grad_norm: 2.1483 loss: 1.9450 loss_heatmap: 0.7876 layer_-1_loss_cls: 0.1243 layer_-1_loss_bbox: 1.0331 matched_ious: 0.4829 2023/03/22 10:09:32 - mmengine - INFO - Epoch(train) [4][3700/3862] lr: 5.4254e-04 eta: 18:23:08 time: 1.0655 data_time: 0.0123 memory: 9166 grad_norm: 2.2037 loss: 1.9665 loss_heatmap: 0.7790 layer_-1_loss_cls: 0.1225 layer_-1_loss_bbox: 1.0649 matched_ious: 0.5203 2023/03/22 10:10:25 - mmengine - INFO - Epoch(train) [4][3750/3862] lr: 5.4483e-04 eta: 18:22:14 time: 1.0639 data_time: 0.0123 memory: 9142 grad_norm: 2.0667 loss: 1.9505 loss_heatmap: 0.7708 layer_-1_loss_cls: 0.1208 layer_-1_loss_bbox: 1.0589 matched_ious: 0.4442 2023/03/22 10:11:18 - mmengine - INFO - Epoch(train) [4][3800/3862] lr: 5.4712e-04 eta: 18:21:20 time: 1.0647 data_time: 0.0127 memory: 9076 grad_norm: 1.9797 loss: 1.8898 loss_heatmap: 0.7892 layer_-1_loss_cls: 0.1224 layer_-1_loss_bbox: 0.9783 matched_ious: 0.4736 2023/03/22 10:12:11 - mmengine - INFO - Epoch(train) [4][3850/3862] lr: 5.4941e-04 eta: 18:20:26 time: 1.0662 data_time: 0.0122 memory: 9040 grad_norm: 1.9401 loss: 1.9383 loss_heatmap: 0.7993 layer_-1_loss_cls: 0.1244 layer_-1_loss_bbox: 1.0146 matched_ious: 0.4861 2023/03/22 10:12:24 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 10:13:20 - mmengine - INFO - Epoch(train) [5][ 50/3862] lr: 5.5224e-04 eta: 18:19:29 time: 1.1158 data_time: 0.0533 memory: 8995 grad_norm: 2.0292 loss: 1.9128 loss_heatmap: 0.7796 layer_-1_loss_cls: 0.1242 layer_-1_loss_bbox: 1.0091 matched_ious: 0.5335 2023/03/22 10:14:13 - mmengine - INFO - Epoch(train) [5][ 100/3862] lr: 5.5453e-04 eta: 18:18:35 time: 1.0652 data_time: 0.0123 memory: 9557 grad_norm: 1.9013 loss: 1.9865 loss_heatmap: 0.7965 layer_-1_loss_cls: 0.1233 layer_-1_loss_bbox: 1.0668 matched_ious: 0.4934 2023/03/22 10:15:06 - mmengine - INFO - Epoch(train) [5][ 150/3862] lr: 5.5682e-04 eta: 18:17:40 time: 1.0631 data_time: 0.0123 memory: 9239 grad_norm: 2.0654 loss: 1.9129 loss_heatmap: 0.7787 layer_-1_loss_cls: 0.1242 layer_-1_loss_bbox: 1.0100 matched_ious: 0.5035 2023/03/22 10:16:01 - mmengine - INFO - Epoch(train) [5][ 200/3862] lr: 5.5911e-04 eta: 18:16:50 time: 1.0851 data_time: 0.0122 memory: 9369 grad_norm: 2.1097 loss: 1.9736 loss_heatmap: 0.7827 layer_-1_loss_cls: 0.1211 layer_-1_loss_bbox: 1.0698 matched_ious: 0.5027 2023/03/22 10:16:54 - mmengine - INFO - Epoch(train) [5][ 250/3862] lr: 5.6139e-04 eta: 18:15:55 time: 1.0628 data_time: 0.0122 memory: 9156 grad_norm: 2.0097 loss: 1.9190 loss_heatmap: 0.7828 layer_-1_loss_cls: 0.1242 layer_-1_loss_bbox: 1.0121 matched_ious: 0.5000 2023/03/22 10:17:47 - mmengine - INFO - Epoch(train) [5][ 300/3862] lr: 5.6368e-04 eta: 18:15:02 time: 1.0704 data_time: 0.0124 memory: 9139 grad_norm: 2.0556 loss: 1.9954 loss_heatmap: 0.7998 layer_-1_loss_cls: 0.1230 layer_-1_loss_bbox: 1.0727 matched_ious: 0.4449 2023/03/22 10:18:41 - mmengine - INFO - Epoch(train) [5][ 350/3862] lr: 5.6597e-04 eta: 18:14:09 time: 1.0685 data_time: 0.0123 memory: 9327 grad_norm: 1.9054 loss: 2.0114 loss_heatmap: 0.8211 layer_-1_loss_cls: 0.1293 layer_-1_loss_bbox: 1.0609 matched_ious: 0.4723 2023/03/22 10:19:34 - mmengine - INFO - Epoch(train) [5][ 400/3862] lr: 5.6825e-04 eta: 18:13:16 time: 1.0687 data_time: 0.0121 memory: 9121 grad_norm: 1.9960 loss: 1.9282 loss_heatmap: 0.7737 layer_-1_loss_cls: 0.1222 layer_-1_loss_bbox: 1.0322 matched_ious: 0.5050 2023/03/22 10:20:28 - mmengine - INFO - Epoch(train) [5][ 450/3862] lr: 5.7054e-04 eta: 18:12:23 time: 1.0704 data_time: 0.0119 memory: 9136 grad_norm: 1.8931 loss: 1.9116 loss_heatmap: 0.7804 layer_-1_loss_cls: 0.1209 layer_-1_loss_bbox: 1.0103 matched_ious: 0.4870 2023/03/22 10:21:21 - mmengine - INFO - Epoch(train) [5][ 500/3862] lr: 5.7282e-04 eta: 18:11:29 time: 1.0695 data_time: 0.0122 memory: 9180 grad_norm: 1.8132 loss: 1.9694 loss_heatmap: 0.7923 layer_-1_loss_cls: 0.1218 layer_-1_loss_bbox: 1.0553 matched_ious: 0.4401 2023/03/22 10:22:15 - mmengine - INFO - Epoch(train) [5][ 550/3862] lr: 5.7511e-04 eta: 18:10:37 time: 1.0716 data_time: 0.0122 memory: 9168 grad_norm: 1.9235 loss: 1.9353 loss_heatmap: 0.7801 layer_-1_loss_cls: 0.1218 layer_-1_loss_bbox: 1.0334 matched_ious: 0.4290 2023/03/22 10:22:17 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 10:23:08 - mmengine - INFO - Epoch(train) [5][ 600/3862] lr: 5.7739e-04 eta: 18:09:42 time: 1.0605 data_time: 0.0119 memory: 9350 grad_norm: 1.9500 loss: 1.9394 loss_heatmap: 0.7945 layer_-1_loss_cls: 0.1215 layer_-1_loss_bbox: 1.0234 matched_ious: 0.4973 2023/03/22 10:24:01 - mmengine - INFO - Epoch(train) [5][ 650/3862] lr: 5.7967e-04 eta: 18:08:47 time: 1.0637 data_time: 0.0123 memory: 9338 grad_norm: 1.9388 loss: 1.9339 loss_heatmap: 0.7710 layer_-1_loss_cls: 0.1212 layer_-1_loss_bbox: 1.0417 matched_ious: 0.4597 2023/03/22 10:24:54 - mmengine - INFO - Epoch(train) [5][ 700/3862] lr: 5.8196e-04 eta: 18:07:54 time: 1.0682 data_time: 0.0121 memory: 9177 grad_norm: 1.9586 loss: 1.9092 loss_heatmap: 0.7792 layer_-1_loss_cls: 0.1213 layer_-1_loss_bbox: 1.0087 matched_ious: 0.4294 2023/03/22 10:25:48 - mmengine - INFO - Epoch(train) [5][ 750/3862] lr: 5.8424e-04 eta: 18:07:00 time: 1.0641 data_time: 0.0122 memory: 9121 grad_norm: 1.9120 loss: 1.9791 loss_heatmap: 0.7887 layer_-1_loss_cls: 0.1247 layer_-1_loss_bbox: 1.0657 matched_ious: 0.4453 2023/03/22 10:26:40 - mmengine - INFO - Epoch(train) [5][ 800/3862] lr: 5.8652e-04 eta: 18:06:04 time: 1.0583 data_time: 0.0121 memory: 9161 grad_norm: 1.9657 loss: 1.9787 loss_heatmap: 0.7932 layer_-1_loss_cls: 0.1215 layer_-1_loss_bbox: 1.0640 matched_ious: 0.4905 2023/03/22 10:27:33 - mmengine - INFO - Epoch(train) [5][ 850/3862] lr: 5.8880e-04 eta: 18:05:09 time: 1.0570 data_time: 0.0121 memory: 9302 grad_norm: 1.8560 loss: 1.9405 loss_heatmap: 0.7811 layer_-1_loss_cls: 0.1242 layer_-1_loss_bbox: 1.0352 matched_ious: 0.4994 2023/03/22 10:28:26 - mmengine - INFO - Epoch(train) [5][ 900/3862] lr: 5.9108e-04 eta: 18:04:14 time: 1.0617 data_time: 0.0120 memory: 8817 grad_norm: 1.9984 loss: 1.9493 loss_heatmap: 0.7884 layer_-1_loss_cls: 0.1221 layer_-1_loss_bbox: 1.0387 matched_ious: 0.4811 2023/03/22 10:29:20 - mmengine - INFO - Epoch(train) [5][ 950/3862] lr: 5.9336e-04 eta: 18:03:22 time: 1.0753 data_time: 0.0117 memory: 9111 grad_norm: 1.8955 loss: 2.0140 loss_heatmap: 0.8075 layer_-1_loss_cls: 0.1259 layer_-1_loss_bbox: 1.0806 matched_ious: 0.4882 2023/03/22 10:30:14 - mmengine - INFO - Epoch(train) [5][1000/3862] lr: 5.9563e-04 eta: 18:02:30 time: 1.0747 data_time: 0.0247 memory: 8995 grad_norm: 1.8444 loss: 1.8886 loss_heatmap: 0.7610 layer_-1_loss_cls: 0.1204 layer_-1_loss_bbox: 1.0072 matched_ious: 0.4687 2023/03/22 10:31:07 - mmengine - INFO - Epoch(train) [5][1050/3862] lr: 5.9791e-04 eta: 18:01:35 time: 1.0598 data_time: 0.0117 memory: 9344 grad_norm: 1.8375 loss: 1.9150 loss_heatmap: 0.7672 layer_-1_loss_cls: 0.1166 layer_-1_loss_bbox: 1.0312 matched_ious: 0.4877 2023/03/22 10:32:01 - mmengine - INFO - Epoch(train) [5][1100/3862] lr: 6.0018e-04 eta: 18:00:42 time: 1.0736 data_time: 0.0118 memory: 9338 grad_norm: 1.8695 loss: 1.9355 loss_heatmap: 0.7825 layer_-1_loss_cls: 0.1194 layer_-1_loss_bbox: 1.0336 matched_ious: 0.4954 2023/03/22 10:32:54 - mmengine - INFO - Epoch(train) [5][1150/3862] lr: 6.0246e-04 eta: 17:59:47 time: 1.0588 data_time: 0.0117 memory: 9219 grad_norm: 2.0037 loss: 1.9358 loss_heatmap: 0.7687 layer_-1_loss_cls: 0.1206 layer_-1_loss_bbox: 1.0465 matched_ious: 0.5069 2023/03/22 10:33:47 - mmengine - INFO - Epoch(train) [5][1200/3862] lr: 6.0473e-04 eta: 17:58:52 time: 1.0614 data_time: 0.0114 memory: 8999 grad_norm: 1.8856 loss: 1.9487 loss_heatmap: 0.7724 layer_-1_loss_cls: 0.1202 layer_-1_loss_bbox: 1.0561 matched_ious: 0.4869 2023/03/22 10:34:40 - mmengine - INFO - Epoch(train) [5][1250/3862] lr: 6.0700e-04 eta: 17:57:59 time: 1.0711 data_time: 0.0111 memory: 9412 grad_norm: 1.8131 loss: 1.9449 loss_heatmap: 0.7883 layer_-1_loss_cls: 0.1208 layer_-1_loss_bbox: 1.0358 matched_ious: 0.4840 2023/03/22 10:35:34 - mmengine - INFO - Epoch(train) [5][1300/3862] lr: 6.0927e-04 eta: 17:57:06 time: 1.0701 data_time: 0.0114 memory: 9156 grad_norm: 1.8768 loss: 1.9903 loss_heatmap: 0.7993 layer_-1_loss_cls: 0.1218 layer_-1_loss_bbox: 1.0692 matched_ious: 0.5105 2023/03/22 10:36:28 - mmengine - INFO - Epoch(train) [5][1350/3862] lr: 6.1153e-04 eta: 17:56:14 time: 1.0773 data_time: 0.0115 memory: 8939 grad_norm: 1.7914 loss: 1.9038 loss_heatmap: 0.7830 layer_-1_loss_cls: 0.1214 layer_-1_loss_bbox: 0.9994 matched_ious: 0.4335 2023/03/22 10:37:21 - mmengine - INFO - Epoch(train) [5][1400/3862] lr: 6.1380e-04 eta: 17:55:21 time: 1.0700 data_time: 0.0159 memory: 8950 grad_norm: 1.8033 loss: 1.9794 loss_heatmap: 0.7847 layer_-1_loss_cls: 0.1227 layer_-1_loss_bbox: 1.0720 matched_ious: 0.4988 2023/03/22 10:38:14 - mmengine - INFO - Epoch(train) [5][1450/3862] lr: 6.1606e-04 eta: 17:54:28 time: 1.0666 data_time: 0.0118 memory: 9064 grad_norm: 1.8479 loss: 1.9087 loss_heatmap: 0.7820 layer_-1_loss_cls: 0.1224 layer_-1_loss_bbox: 1.0043 matched_ious: 0.5278 2023/03/22 10:39:08 - mmengine - INFO - Epoch(train) [5][1500/3862] lr: 6.1832e-04 eta: 17:53:33 time: 1.0638 data_time: 0.0118 memory: 9183 grad_norm: 1.8294 loss: 1.9170 loss_heatmap: 0.7663 layer_-1_loss_cls: 0.1168 layer_-1_loss_bbox: 1.0339 matched_ious: 0.4208 2023/03/22 10:40:01 - mmengine - INFO - Epoch(train) [5][1550/3862] lr: 6.2059e-04 eta: 17:52:40 time: 1.0665 data_time: 0.0120 memory: 9218 grad_norm: 1.7850 loss: 1.9564 loss_heatmap: 0.7867 layer_-1_loss_cls: 0.1218 layer_-1_loss_bbox: 1.0479 matched_ious: 0.4540 2023/03/22 10:40:03 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 10:40:54 - mmengine - INFO - Epoch(train) [5][1600/3862] lr: 6.2284e-04 eta: 17:51:46 time: 1.0644 data_time: 0.0118 memory: 9299 grad_norm: 2.0260 loss: 1.9287 loss_heatmap: 0.7793 layer_-1_loss_cls: 0.1194 layer_-1_loss_bbox: 1.0300 matched_ious: 0.4364 2023/03/22 10:41:47 - mmengine - INFO - Epoch(train) [5][1650/3862] lr: 6.2510e-04 eta: 17:50:50 time: 1.0581 data_time: 0.0114 memory: 9426 grad_norm: 1.7778 loss: 1.9029 loss_heatmap: 0.7678 layer_-1_loss_cls: 0.1181 layer_-1_loss_bbox: 1.0170 matched_ious: 0.4770 2023/03/22 10:42:41 - mmengine - INFO - Epoch(train) [5][1700/3862] lr: 6.2736e-04 eta: 17:49:59 time: 1.0782 data_time: 0.0125 memory: 8971 grad_norm: 1.7845 loss: 1.9236 loss_heatmap: 0.7764 layer_-1_loss_cls: 0.1220 layer_-1_loss_bbox: 1.0253 matched_ious: 0.4737 2023/03/22 10:43:35 - mmengine - INFO - Epoch(train) [5][1750/3862] lr: 6.2961e-04 eta: 17:49:06 time: 1.0718 data_time: 0.0117 memory: 9037 grad_norm: 1.7355 loss: 1.9605 loss_heatmap: 0.7796 layer_-1_loss_cls: 0.1186 layer_-1_loss_bbox: 1.0624 matched_ious: 0.4551 2023/03/22 10:44:28 - mmengine - INFO - Epoch(train) [5][1800/3862] lr: 6.3186e-04 eta: 17:48:12 time: 1.0637 data_time: 0.0122 memory: 9407 grad_norm: 1.8079 loss: 2.0143 loss_heatmap: 0.8037 layer_-1_loss_cls: 0.1232 layer_-1_loss_bbox: 1.0873 matched_ious: 0.4749 2023/03/22 10:45:21 - mmengine - INFO - Epoch(train) [5][1850/3862] lr: 6.3411e-04 eta: 17:47:17 time: 1.0640 data_time: 0.0119 memory: 9173 grad_norm: 1.8256 loss: 1.8806 loss_heatmap: 0.7657 layer_-1_loss_cls: 0.1190 layer_-1_loss_bbox: 0.9959 matched_ious: 0.4792 2023/03/22 10:46:14 - mmengine - INFO - Epoch(train) [5][1900/3862] lr: 6.3635e-04 eta: 17:46:24 time: 1.0709 data_time: 0.0122 memory: 9116 grad_norm: 1.8925 loss: 1.8650 loss_heatmap: 0.7669 layer_-1_loss_cls: 0.1216 layer_-1_loss_bbox: 0.9765 matched_ious: 0.4825 2023/03/22 10:47:08 - mmengine - INFO - Epoch(train) [5][1950/3862] lr: 6.3860e-04 eta: 17:45:30 time: 1.0641 data_time: 0.0121 memory: 9038 grad_norm: 1.8868 loss: 1.8854 loss_heatmap: 0.7612 layer_-1_loss_cls: 0.1202 layer_-1_loss_bbox: 1.0040 matched_ious: 0.4516 2023/03/22 10:48:01 - mmengine - INFO - Epoch(train) [5][2000/3862] lr: 6.4084e-04 eta: 17:44:37 time: 1.0683 data_time: 0.0120 memory: 9091 grad_norm: 1.8399 loss: 1.8660 loss_heatmap: 0.7501 layer_-1_loss_cls: 0.1187 layer_-1_loss_bbox: 0.9971 matched_ious: 0.4549 2023/03/22 10:48:55 - mmengine - INFO - Epoch(train) [5][2050/3862] lr: 6.4308e-04 eta: 17:43:44 time: 1.0702 data_time: 0.0127 memory: 8877 grad_norm: 1.7531 loss: 1.8964 loss_heatmap: 0.7727 layer_-1_loss_cls: 0.1198 layer_-1_loss_bbox: 1.0038 matched_ious: 0.4788 2023/03/22 10:49:48 - mmengine - INFO - Epoch(train) [5][2100/3862] lr: 6.4532e-04 eta: 17:42:49 time: 1.0629 data_time: 0.0122 memory: 9018 grad_norm: 1.8523 loss: 1.8683 loss_heatmap: 0.7588 layer_-1_loss_cls: 0.1208 layer_-1_loss_bbox: 0.9888 matched_ious: 0.4702 2023/03/22 10:50:41 - mmengine - INFO - Epoch(train) [5][2150/3862] lr: 6.4755e-04 eta: 17:41:56 time: 1.0705 data_time: 0.0118 memory: 9180 grad_norm: 1.8825 loss: 1.8995 loss_heatmap: 0.7783 layer_-1_loss_cls: 0.1225 layer_-1_loss_bbox: 0.9986 matched_ious: 0.5000 2023/03/22 10:51:35 - mmengine - INFO - Epoch(train) [5][2200/3862] lr: 6.4978e-04 eta: 17:41:05 time: 1.0803 data_time: 0.0120 memory: 9155 grad_norm: 1.7669 loss: 1.8568 loss_heatmap: 0.7516 layer_-1_loss_cls: 0.1167 layer_-1_loss_bbox: 0.9885 matched_ious: 0.4737 2023/03/22 10:52:29 - mmengine - INFO - Epoch(train) [5][2250/3862] lr: 6.5201e-04 eta: 17:40:11 time: 1.0653 data_time: 0.0121 memory: 9237 grad_norm: 1.7970 loss: 1.9539 loss_heatmap: 0.7975 layer_-1_loss_cls: 0.1249 layer_-1_loss_bbox: 1.0315 matched_ious: 0.4641 2023/03/22 10:53:21 - mmengine - INFO - Epoch(train) [5][2300/3862] lr: 6.5424e-04 eta: 17:39:15 time: 1.0535 data_time: 0.0122 memory: 9155 grad_norm: 1.6627 loss: 1.8734 loss_heatmap: 0.7710 layer_-1_loss_cls: 0.1202 layer_-1_loss_bbox: 0.9823 matched_ious: 0.4999 2023/03/22 10:54:15 - mmengine - INFO - Epoch(train) [5][2350/3862] lr: 6.5646e-04 eta: 17:38:21 time: 1.0662 data_time: 0.0122 memory: 9013 grad_norm: 1.6474 loss: 1.8678 loss_heatmap: 0.7514 layer_-1_loss_cls: 0.1154 layer_-1_loss_bbox: 1.0010 matched_ious: 0.4775 2023/03/22 10:55:08 - mmengine - INFO - Epoch(train) [5][2400/3862] lr: 6.5869e-04 eta: 17:37:27 time: 1.0635 data_time: 0.0121 memory: 9152 grad_norm: 1.7480 loss: 1.9688 loss_heatmap: 0.7821 layer_-1_loss_cls: 0.1189 layer_-1_loss_bbox: 1.0679 matched_ious: 0.4632 2023/03/22 10:56:01 - mmengine - INFO - Epoch(train) [5][2450/3862] lr: 6.6090e-04 eta: 17:36:34 time: 1.0701 data_time: 0.0119 memory: 9092 grad_norm: 1.7748 loss: 1.9245 loss_heatmap: 0.7641 layer_-1_loss_cls: 0.1212 layer_-1_loss_bbox: 1.0392 matched_ious: 0.4732 2023/03/22 10:56:55 - mmengine - INFO - Epoch(train) [5][2500/3862] lr: 6.6312e-04 eta: 17:35:43 time: 1.0827 data_time: 0.0123 memory: 9189 grad_norm: 1.7243 loss: 1.9429 loss_heatmap: 0.7863 layer_-1_loss_cls: 0.1203 layer_-1_loss_bbox: 1.0363 matched_ious: 0.4780 2023/03/22 10:57:49 - mmengine - INFO - Epoch(train) [5][2550/3862] lr: 6.6533e-04 eta: 17:34:50 time: 1.0689 data_time: 0.0120 memory: 9219 grad_norm: 1.6822 loss: 1.8616 loss_heatmap: 0.7628 layer_-1_loss_cls: 0.1182 layer_-1_loss_bbox: 0.9805 matched_ious: 0.5195 2023/03/22 10:57:51 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 10:58:42 - mmengine - INFO - Epoch(train) [5][2600/3862] lr: 6.6754e-04 eta: 17:33:57 time: 1.0732 data_time: 0.0119 memory: 9082 grad_norm: 1.8362 loss: 2.0145 loss_heatmap: 0.8001 layer_-1_loss_cls: 0.1243 layer_-1_loss_bbox: 1.0901 matched_ious: 0.4849 2023/03/22 10:59:35 - mmengine - INFO - Epoch(train) [5][2650/3862] lr: 6.6975e-04 eta: 17:33:02 time: 1.0570 data_time: 0.0118 memory: 9135 grad_norm: 1.6187 loss: 1.8734 loss_heatmap: 0.7641 layer_-1_loss_cls: 0.1198 layer_-1_loss_bbox: 0.9895 matched_ious: 0.4387 2023/03/22 11:00:29 - mmengine - INFO - Epoch(train) [5][2700/3862] lr: 6.7195e-04 eta: 17:32:08 time: 1.0646 data_time: 0.0117 memory: 9000 grad_norm: 1.6627 loss: 1.9085 loss_heatmap: 0.7688 layer_-1_loss_cls: 0.1211 layer_-1_loss_bbox: 1.0187 matched_ious: 0.4929 2023/03/22 11:01:22 - mmengine - INFO - Epoch(train) [5][2750/3862] lr: 6.7416e-04 eta: 17:31:13 time: 1.0618 data_time: 0.0122 memory: 9386 grad_norm: 1.5537 loss: 1.8258 loss_heatmap: 0.7406 layer_-1_loss_cls: 0.1180 layer_-1_loss_bbox: 0.9672 matched_ious: 0.4747 2023/03/22 11:02:15 - mmengine - INFO - Epoch(train) [5][2800/3862] lr: 6.7635e-04 eta: 17:30:20 time: 1.0672 data_time: 0.0119 memory: 9142 grad_norm: 1.5053 loss: 1.8699 loss_heatmap: 0.7521 layer_-1_loss_cls: 0.1157 layer_-1_loss_bbox: 1.0021 matched_ious: 0.4893 2023/03/22 11:03:09 - mmengine - INFO - Epoch(train) [5][2850/3862] lr: 6.7855e-04 eta: 17:29:27 time: 1.0719 data_time: 0.0121 memory: 8895 grad_norm: 1.5756 loss: 1.8958 loss_heatmap: 0.7570 layer_-1_loss_cls: 0.1166 layer_-1_loss_bbox: 1.0222 matched_ious: 0.5088 2023/03/22 11:04:02 - mmengine - INFO - Epoch(train) [5][2900/3862] lr: 6.8074e-04 eta: 17:28:32 time: 1.0618 data_time: 0.0117 memory: 9451 grad_norm: 1.6845 loss: 1.9066 loss_heatmap: 0.7677 layer_-1_loss_cls: 0.1188 layer_-1_loss_bbox: 1.0200 matched_ious: 0.4549 2023/03/22 11:04:55 - mmengine - INFO - Epoch(train) [5][2950/3862] lr: 6.8293e-04 eta: 17:27:39 time: 1.0707 data_time: 0.0121 memory: 9078 grad_norm: 1.7043 loss: 1.8734 loss_heatmap: 0.7566 layer_-1_loss_cls: 0.1179 layer_-1_loss_bbox: 0.9989 matched_ious: 0.5174 2023/03/22 11:05:49 - mmengine - INFO - Epoch(train) [5][3000/3862] lr: 6.8511e-04 eta: 17:26:46 time: 1.0673 data_time: 0.0120 memory: 9227 grad_norm: 1.6233 loss: 1.9228 loss_heatmap: 0.7743 layer_-1_loss_cls: 0.1187 layer_-1_loss_bbox: 1.0298 matched_ious: 0.4817 2023/03/22 11:06:42 - mmengine - INFO - Epoch(train) [5][3050/3862] lr: 6.8729e-04 eta: 17:25:52 time: 1.0627 data_time: 0.0120 memory: 9198 grad_norm: 1.6092 loss: 1.8956 loss_heatmap: 0.7602 layer_-1_loss_cls: 0.1188 layer_-1_loss_bbox: 1.0166 matched_ious: 0.4750 2023/03/22 11:07:35 - mmengine - INFO - Epoch(train) [5][3100/3862] lr: 6.8947e-04 eta: 17:24:57 time: 1.0629 data_time: 0.0117 memory: 9351 grad_norm: 1.4853 loss: 1.9346 loss_heatmap: 0.7595 layer_-1_loss_cls: 0.1188 layer_-1_loss_bbox: 1.0563 matched_ious: 0.4571 2023/03/22 11:08:28 - mmengine - INFO - Epoch(train) [5][3150/3862] lr: 6.9164e-04 eta: 17:24:03 time: 1.0619 data_time: 0.0121 memory: 9298 grad_norm: 1.6827 loss: 1.8780 loss_heatmap: 0.7541 layer_-1_loss_cls: 0.1183 layer_-1_loss_bbox: 1.0056 matched_ious: 0.4865 2023/03/22 11:09:21 - mmengine - INFO - Epoch(train) [5][3200/3862] lr: 6.9381e-04 eta: 17:23:10 time: 1.0686 data_time: 0.0121 memory: 9203 grad_norm: 1.5281 loss: 1.8750 loss_heatmap: 0.7568 layer_-1_loss_cls: 0.1177 layer_-1_loss_bbox: 1.0005 matched_ious: 0.5265 2023/03/22 11:10:15 - mmengine - INFO - Epoch(train) [5][3250/3862] lr: 6.9598e-04 eta: 17:22:17 time: 1.0711 data_time: 0.0120 memory: 9150 grad_norm: 1.5483 loss: 1.8291 loss_heatmap: 0.7417 layer_-1_loss_cls: 0.1177 layer_-1_loss_bbox: 0.9697 matched_ious: 0.5175 2023/03/22 11:11:08 - mmengine - INFO - Epoch(train) [5][3300/3862] lr: 6.9814e-04 eta: 17:21:23 time: 1.0683 data_time: 0.0116 memory: 9255 grad_norm: 1.5555 loss: 1.9199 loss_heatmap: 0.7679 layer_-1_loss_cls: 0.1173 layer_-1_loss_bbox: 1.0347 matched_ious: 0.5154 2023/03/22 11:12:02 - mmengine - INFO - Epoch(train) [5][3350/3862] lr: 7.0030e-04 eta: 17:20:31 time: 1.0783 data_time: 0.0118 memory: 9177 grad_norm: 1.5597 loss: 1.9221 loss_heatmap: 0.7822 layer_-1_loss_cls: 0.1221 layer_-1_loss_bbox: 1.0178 matched_ious: 0.4399 2023/03/22 11:12:56 - mmengine - INFO - Epoch(train) [5][3400/3862] lr: 7.0245e-04 eta: 17:19:39 time: 1.0770 data_time: 0.0119 memory: 9027 grad_norm: 1.4970 loss: 1.8407 loss_heatmap: 0.7501 layer_-1_loss_cls: 0.1186 layer_-1_loss_bbox: 0.9721 matched_ious: 0.4463 2023/03/22 11:13:50 - mmengine - INFO - Epoch(train) [5][3450/3862] lr: 7.0460e-04 eta: 17:18:46 time: 1.0675 data_time: 0.0120 memory: 8957 grad_norm: 1.4977 loss: 1.8624 loss_heatmap: 0.7649 layer_-1_loss_cls: 0.1175 layer_-1_loss_bbox: 0.9800 matched_ious: 0.5081 2023/03/22 11:14:43 - mmengine - INFO - Epoch(train) [5][3500/3862] lr: 7.0675e-04 eta: 17:17:53 time: 1.0715 data_time: 0.0120 memory: 9039 grad_norm: 1.6093 loss: 1.9703 loss_heatmap: 0.8025 layer_-1_loss_cls: 0.1250 layer_-1_loss_bbox: 1.0428 matched_ious: 0.4818 2023/03/22 11:15:37 - mmengine - INFO - Epoch(train) [5][3550/3862] lr: 7.0889e-04 eta: 17:17:00 time: 1.0716 data_time: 0.0118 memory: 9041 grad_norm: 1.5867 loss: 1.8384 loss_heatmap: 0.7561 layer_-1_loss_cls: 0.1210 layer_-1_loss_bbox: 0.9613 matched_ious: 0.4779 2023/03/22 11:15:39 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 11:16:30 - mmengine - INFO - Epoch(train) [5][3600/3862] lr: 7.1103e-04 eta: 17:16:05 time: 1.0604 data_time: 0.0118 memory: 9071 grad_norm: 1.4498 loss: 1.8875 loss_heatmap: 0.7655 layer_-1_loss_cls: 0.1187 layer_-1_loss_bbox: 1.0034 matched_ious: 0.4949 2023/03/22 11:17:24 - mmengine - INFO - Epoch(train) [5][3650/3862] lr: 7.1316e-04 eta: 17:15:14 time: 1.0804 data_time: 0.0123 memory: 9038 grad_norm: 1.6061 loss: 1.8912 loss_heatmap: 0.7653 layer_-1_loss_cls: 0.1215 layer_-1_loss_bbox: 1.0044 matched_ious: 0.4824 2023/03/22 11:18:17 - mmengine - INFO - Epoch(train) [5][3700/3862] lr: 7.1529e-04 eta: 17:14:20 time: 1.0679 data_time: 0.0122 memory: 9484 grad_norm: 1.5586 loss: 1.8586 loss_heatmap: 0.7503 layer_-1_loss_cls: 0.1163 layer_-1_loss_bbox: 0.9920 matched_ious: 0.4968 2023/03/22 11:19:11 - mmengine - INFO - Epoch(train) [5][3750/3862] lr: 7.1742e-04 eta: 17:13:27 time: 1.0726 data_time: 0.0123 memory: 9237 grad_norm: 1.4873 loss: 1.8032 loss_heatmap: 0.7339 layer_-1_loss_cls: 0.1159 layer_-1_loss_bbox: 0.9534 matched_ious: 0.4754 2023/03/22 11:20:04 - mmengine - INFO - Epoch(train) [5][3800/3862] lr: 7.1954e-04 eta: 17:12:34 time: 1.0673 data_time: 0.0118 memory: 9218 grad_norm: 1.6870 loss: 1.8931 loss_heatmap: 0.7655 layer_-1_loss_cls: 0.1218 layer_-1_loss_bbox: 1.0058 matched_ious: 0.5092 2023/03/22 11:20:57 - mmengine - INFO - Epoch(train) [5][3850/3862] lr: 7.2166e-04 eta: 17:11:40 time: 1.0638 data_time: 0.0124 memory: 9575 grad_norm: 1.5095 loss: 1.8413 loss_heatmap: 0.7552 layer_-1_loss_cls: 0.1206 layer_-1_loss_bbox: 0.9655 matched_ious: 0.5011 2023/03/22 11:21:10 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 11:21:10 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/03/22 11:21:21 - mmengine - INFO - Epoch(val) [5][ 50/753] eta: 0:01:59 time: 0.1694 data_time: 0.0165 memory: 8728 2023/03/22 11:21:29 - mmengine - INFO - Epoch(val) [5][100/753] eta: 0:01:42 time: 0.1456 data_time: 0.0035 memory: 730 2023/03/22 11:21:36 - mmengine - INFO - Epoch(val) [5][150/753] eta: 0:01:32 time: 0.1463 data_time: 0.0039 memory: 730 2023/03/22 11:21:44 - mmengine - INFO - Epoch(val) [5][200/753] eta: 0:01:25 time: 0.1542 data_time: 0.0039 memory: 730 2023/03/22 11:21:51 - mmengine - INFO - Epoch(val) [5][250/753] eta: 0:01:16 time: 0.1459 data_time: 0.0029 memory: 730 2023/03/22 11:21:58 - mmengine - INFO - Epoch(val) [5][300/753] eta: 0:01:08 time: 0.1449 data_time: 0.0034 memory: 730 2023/03/22 11:22:05 - mmengine - INFO - Epoch(val) [5][350/753] eta: 0:01:00 time: 0.1449 data_time: 0.0031 memory: 730 2023/03/22 11:22:12 - mmengine - INFO - Epoch(val) [5][400/753] eta: 0:00:52 time: 0.1313 data_time: 0.0035 memory: 730 2023/03/22 11:22:19 - mmengine - INFO - Epoch(val) [5][450/753] eta: 0:00:44 time: 0.1432 data_time: 0.0031 memory: 730 2023/03/22 11:22:27 - mmengine - INFO - Epoch(val) [5][500/753] eta: 0:00:37 time: 0.1496 data_time: 0.0031 memory: 730 2023/03/22 11:22:34 - mmengine - INFO - Epoch(val) [5][550/753] eta: 0:00:29 time: 0.1373 data_time: 0.0036 memory: 730 2023/03/22 11:22:41 - mmengine - INFO - Epoch(val) [5][600/753] eta: 0:00:22 time: 0.1544 data_time: 0.0035 memory: 730 2023/03/22 11:22:49 - mmengine - INFO - Epoch(val) [5][650/753] eta: 0:00:15 time: 0.1503 data_time: 0.0028 memory: 730 2023/03/22 11:22:57 - mmengine - INFO - Epoch(val) [5][700/753] eta: 0:00:07 time: 0.1553 data_time: 0.0029 memory: 730 2023/03/22 11:23:04 - mmengine - INFO - Epoch(val) [5][750/753] eta: 0:00:00 time: 0.1545 data_time: 0.0027 memory: 730 2023/03/22 11:34:07 - mmengine - INFO - Epoch(val) [5][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.7324 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8342 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.8650 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.8820 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1936 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1697 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.1500 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.3849 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1989 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.3118 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2687 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3601 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.4046 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1943 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.2968 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.4941 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.5894 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.6274 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3711 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1993 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.1432 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.3104 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2032 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0207 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.1120 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.2195 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.3114 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6933 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4374 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.9918 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1408 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3570 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.3403 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.5987 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.7573 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.7933 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.4083 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1927 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.1649 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.6906 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2503 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.0697 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.2810 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.3682 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.4689 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5444 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2247 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.5255 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.3720 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1752 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.5317 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.6475 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.6893 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7049 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.2186 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2957 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0839 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.3982 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.4526 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.4634 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.4668 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.2116 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2569 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.3300 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.7550 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2535 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.2306 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.2420 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.2428 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.2447 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1642 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2671 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.4283 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.3056 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0271 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.7717 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.7929 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8092 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8260 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1641 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2882 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.4237 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2779 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0894 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.6155 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.6297 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.6528 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.6937 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1487 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3553 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6056 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.5192data_time: 0.0027 time: 0.1535 2023/03/22 11:35:03 - mmengine - INFO - Epoch(train) [6][ 50/3862] lr: 7.2428e-04 eta: 17:10:39 time: 1.1105 data_time: 0.0501 memory: 8954 grad_norm: 1.6057 loss: 1.9206 loss_heatmap: 0.7747 layer_-1_loss_cls: 0.1195 layer_-1_loss_bbox: 1.0264 matched_ious: 0.4978 2023/03/22 11:35:56 - mmengine - INFO - Epoch(train) [6][ 100/3862] lr: 7.2638e-04 eta: 17:09:46 time: 1.0692 data_time: 0.0111 memory: 9116 grad_norm: 1.5471 loss: 1.8493 loss_heatmap: 0.7658 layer_-1_loss_cls: 0.1188 layer_-1_loss_bbox: 0.9647 matched_ious: 0.4220 2023/03/22 11:36:49 - mmengine - INFO - Epoch(train) [6][ 150/3862] lr: 7.2849e-04 eta: 17:08:51 time: 1.0571 data_time: 0.0114 memory: 9209 grad_norm: 1.5295 loss: 1.9333 loss_heatmap: 0.7647 layer_-1_loss_cls: 0.1193 layer_-1_loss_bbox: 1.0493 matched_ious: 0.4775 2023/03/22 11:37:43 - mmengine - INFO - Epoch(train) [6][ 200/3862] lr: 7.3058e-04 eta: 17:07:57 time: 1.0647 data_time: 0.0114 memory: 9195 grad_norm: 1.5807 loss: 1.8940 loss_heatmap: 0.7661 layer_-1_loss_cls: 0.1193 layer_-1_loss_bbox: 1.0085 matched_ious: 0.5088 2023/03/22 11:38:36 - mmengine - INFO - Epoch(train) [6][ 250/3862] lr: 7.3268e-04 eta: 17:07:02 time: 1.0629 data_time: 0.0115 memory: 9262 grad_norm: 1.5657 loss: 1.8137 loss_heatmap: 0.7272 layer_-1_loss_cls: 0.1159 layer_-1_loss_bbox: 0.9706 matched_ious: 0.5308 2023/03/22 11:39:29 - mmengine - INFO - Epoch(train) [6][ 300/3862] lr: 7.3477e-04 eta: 17:06:10 time: 1.0749 data_time: 0.0118 memory: 9106 grad_norm: 1.4889 loss: 1.8059 loss_heatmap: 0.7391 layer_-1_loss_cls: 0.1171 layer_-1_loss_bbox: 0.9498 matched_ious: 0.4861 2023/03/22 11:40:22 - mmengine - INFO - Epoch(train) [6][ 350/3862] lr: 7.3685e-04 eta: 17:05:15 time: 1.0599 data_time: 0.0118 memory: 9140 grad_norm: 1.4209 loss: 1.8038 loss_heatmap: 0.7325 layer_-1_loss_cls: 0.1131 layer_-1_loss_bbox: 0.9582 matched_ious: 0.4747 2023/03/22 11:41:15 - mmengine - INFO - Epoch(train) [6][ 400/3862] lr: 7.3893e-04 eta: 17:04:20 time: 1.0533 data_time: 0.0118 memory: 9278 grad_norm: 1.5405 loss: 1.8438 loss_heatmap: 0.7558 layer_-1_loss_cls: 0.1160 layer_-1_loss_bbox: 0.9720 matched_ious: 0.4841 2023/03/22 11:42:09 - mmengine - INFO - Epoch(train) [6][ 450/3862] lr: 7.4100e-04 eta: 17:03:27 time: 1.0708 data_time: 0.0117 memory: 9295 grad_norm: 1.5583 loss: 1.9351 loss_heatmap: 0.7795 layer_-1_loss_cls: 0.1180 layer_-1_loss_bbox: 1.0377 matched_ious: 0.5154 2023/03/22 11:43:02 - mmengine - INFO - Epoch(train) [6][ 500/3862] lr: 7.4307e-04 eta: 17:02:32 time: 1.0626 data_time: 0.0115 memory: 9180 grad_norm: 1.4510 loss: 1.8323 loss_heatmap: 0.7297 layer_-1_loss_cls: 0.1149 layer_-1_loss_bbox: 0.9876 matched_ious: 0.4768 2023/03/22 11:43:55 - mmengine - INFO - Epoch(train) [6][ 550/3862] lr: 7.4514e-04 eta: 17:01:38 time: 1.0644 data_time: 0.0120 memory: 9083 grad_norm: 1.5384 loss: 1.8617 loss_heatmap: 0.7712 layer_-1_loss_cls: 0.1200 layer_-1_loss_bbox: 0.9706 matched_ious: 0.5137 2023/03/22 11:44:48 - mmengine - INFO - Epoch(train) [6][ 600/3862] lr: 7.4719e-04 eta: 17:00:45 time: 1.0673 data_time: 0.0114 memory: 8981 grad_norm: 1.5837 loss: 1.8277 loss_heatmap: 0.7490 layer_-1_loss_cls: 0.1169 layer_-1_loss_bbox: 0.9618 matched_ious: 0.4673 2023/03/22 11:45:41 - mmengine - INFO - Epoch(train) [6][ 650/3862] lr: 7.4925e-04 eta: 16:59:50 time: 1.0574 data_time: 0.0116 memory: 9176 grad_norm: 1.6550 loss: 1.8748 loss_heatmap: 0.7509 layer_-1_loss_cls: 0.1157 layer_-1_loss_bbox: 1.0082 matched_ious: 0.4643 2023/03/22 11:46:24 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 11:46:36 - mmengine - INFO - Epoch(train) [6][ 700/3862] lr: 7.5130e-04 eta: 16:58:59 time: 1.0878 data_time: 0.0117 memory: 9273 grad_norm: 1.5334 loss: 1.8545 loss_heatmap: 0.7556 layer_-1_loss_cls: 0.1176 layer_-1_loss_bbox: 0.9812 matched_ious: 0.4766 2023/03/22 11:47:29 - mmengine - INFO - Epoch(train) [6][ 750/3862] lr: 7.5334e-04 eta: 16:58:05 time: 1.0628 data_time: 0.0117 memory: 9219 grad_norm: 1.4366 loss: 1.8648 loss_heatmap: 0.7722 layer_-1_loss_cls: 0.1194 layer_-1_loss_bbox: 0.9732 matched_ious: 0.5005 2023/03/22 11:48:22 - mmengine - INFO - Epoch(train) [6][ 800/3862] lr: 7.5538e-04 eta: 16:57:12 time: 1.0733 data_time: 0.0116 memory: 9302 grad_norm: 1.4040 loss: 1.8585 loss_heatmap: 0.7670 layer_-1_loss_cls: 0.1198 layer_-1_loss_bbox: 0.9717 matched_ious: 0.4927 2023/03/22 11:49:16 - mmengine - INFO - Epoch(train) [6][ 850/3862] lr: 7.5741e-04 eta: 16:56:19 time: 1.0656 data_time: 0.0119 memory: 8894 grad_norm: 1.3968 loss: 1.8531 loss_heatmap: 0.7600 layer_-1_loss_cls: 0.1173 layer_-1_loss_bbox: 0.9758 matched_ious: 0.5003 2023/03/22 11:50:09 - mmengine - INFO - Epoch(train) [6][ 900/3862] lr: 7.5944e-04 eta: 16:55:25 time: 1.0665 data_time: 0.0121 memory: 9202 grad_norm: 1.4353 loss: 1.7727 loss_heatmap: 0.7234 layer_-1_loss_cls: 0.1126 layer_-1_loss_bbox: 0.9367 matched_ious: 0.5387 2023/03/22 11:51:02 - mmengine - INFO - Epoch(train) [6][ 950/3862] lr: 7.6146e-04 eta: 16:54:31 time: 1.0666 data_time: 0.0121 memory: 9084 grad_norm: 1.4537 loss: 1.8508 loss_heatmap: 0.7666 layer_-1_loss_cls: 0.1191 layer_-1_loss_bbox: 0.9652 matched_ious: 0.4957 2023/03/22 11:51:56 - mmengine - INFO - Epoch(train) [6][1000/3862] lr: 7.6348e-04 eta: 16:53:38 time: 1.0670 data_time: 0.0121 memory: 9148 grad_norm: 1.3802 loss: 1.8190 loss_heatmap: 0.7293 layer_-1_loss_cls: 0.1175 layer_-1_loss_bbox: 0.9722 matched_ious: 0.4947 2023/03/22 11:52:49 - mmengine - INFO - Epoch(train) [6][1050/3862] lr: 7.6549e-04 eta: 16:52:43 time: 1.0620 data_time: 0.0117 memory: 9485 grad_norm: 1.4494 loss: 1.8761 loss_heatmap: 0.7563 layer_-1_loss_cls: 0.1211 layer_-1_loss_bbox: 0.9988 matched_ious: 0.5177 2023/03/22 11:53:42 - mmengine - INFO - Epoch(train) [6][1100/3862] lr: 7.6750e-04 eta: 16:51:49 time: 1.0578 data_time: 0.0117 memory: 9052 grad_norm: 1.4457 loss: 1.8335 loss_heatmap: 0.7691 layer_-1_loss_cls: 0.1215 layer_-1_loss_bbox: 0.9429 matched_ious: 0.5096 2023/03/22 11:54:35 - mmengine - INFO - Epoch(train) [6][1150/3862] lr: 7.6950e-04 eta: 16:50:56 time: 1.0727 data_time: 0.0120 memory: 9213 grad_norm: 1.4051 loss: 1.7926 loss_heatmap: 0.7280 layer_-1_loss_cls: 0.1154 layer_-1_loss_bbox: 0.9492 matched_ious: 0.5144 2023/03/22 11:55:29 - mmengine - INFO - Epoch(train) [6][1200/3862] lr: 7.7149e-04 eta: 16:50:02 time: 1.0658 data_time: 0.0121 memory: 9223 grad_norm: 1.3275 loss: 1.8694 loss_heatmap: 0.7467 layer_-1_loss_cls: 0.1168 layer_-1_loss_bbox: 1.0059 matched_ious: 0.4900 2023/03/22 11:56:22 - mmengine - INFO - Epoch(train) [6][1250/3862] lr: 7.7348e-04 eta: 16:49:08 time: 1.0616 data_time: 0.0121 memory: 9299 grad_norm: 1.4578 loss: 1.8761 loss_heatmap: 0.7533 layer_-1_loss_cls: 0.1144 layer_-1_loss_bbox: 1.0084 matched_ious: 0.4458 2023/03/22 11:57:15 - mmengine - INFO - Epoch(train) [6][1300/3862] lr: 7.7546e-04 eta: 16:48:14 time: 1.0692 data_time: 0.0120 memory: 8890 grad_norm: 1.4658 loss: 1.7787 loss_heatmap: 0.7318 layer_-1_loss_cls: 0.1158 layer_-1_loss_bbox: 0.9311 matched_ious: 0.5118 2023/03/22 11:58:09 - mmengine - INFO - Epoch(train) [6][1350/3862] lr: 7.7744e-04 eta: 16:47:21 time: 1.0716 data_time: 0.0120 memory: 9506 grad_norm: 1.4145 loss: 1.8326 loss_heatmap: 0.7453 layer_-1_loss_cls: 0.1158 layer_-1_loss_bbox: 0.9715 matched_ious: 0.4794 2023/03/22 11:59:02 - mmengine - INFO - Epoch(train) [6][1400/3862] lr: 7.7941e-04 eta: 16:46:28 time: 1.0684 data_time: 0.0120 memory: 9204 grad_norm: 1.4043 loss: 1.8369 loss_heatmap: 0.7601 layer_-1_loss_cls: 0.1185 layer_-1_loss_bbox: 0.9583 matched_ious: 0.4462 2023/03/22 11:59:55 - mmengine - INFO - Epoch(train) [6][1450/3862] lr: 7.8138e-04 eta: 16:45:33 time: 1.0595 data_time: 0.0127 memory: 8951 grad_norm: 1.4160 loss: 1.8895 loss_heatmap: 0.7826 layer_-1_loss_cls: 0.1227 layer_-1_loss_bbox: 0.9842 matched_ious: 0.5133 2023/03/22 12:00:49 - mmengine - INFO - Epoch(train) [6][1500/3862] lr: 7.8333e-04 eta: 16:44:41 time: 1.0766 data_time: 0.0124 memory: 9625 grad_norm: 1.3899 loss: 1.8142 loss_heatmap: 0.7309 layer_-1_loss_cls: 0.1119 layer_-1_loss_bbox: 0.9714 matched_ious: 0.5031 2023/03/22 12:01:43 - mmengine - INFO - Epoch(train) [6][1550/3862] lr: 7.8529e-04 eta: 16:43:49 time: 1.0750 data_time: 0.0123 memory: 9177 grad_norm: 1.4051 loss: 1.8180 loss_heatmap: 0.7306 layer_-1_loss_cls: 0.1152 layer_-1_loss_bbox: 0.9722 matched_ious: 0.4746 2023/03/22 12:02:36 - mmengine - INFO - Epoch(train) [6][1600/3862] lr: 7.8724e-04 eta: 16:42:54 time: 1.0628 data_time: 0.0119 memory: 9082 grad_norm: 1.5118 loss: 1.8406 loss_heatmap: 0.7418 layer_-1_loss_cls: 0.1148 layer_-1_loss_bbox: 0.9841 matched_ious: 0.5056 2023/03/22 12:03:30 - mmengine - INFO - Epoch(train) [6][1650/3862] lr: 7.8918e-04 eta: 16:42:02 time: 1.0769 data_time: 0.0124 memory: 9054 grad_norm: 1.4374 loss: 1.8924 loss_heatmap: 0.7546 layer_-1_loss_cls: 0.1163 layer_-1_loss_bbox: 1.0215 matched_ious: 0.5158 2023/03/22 12:04:12 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 12:04:23 - mmengine - INFO - Epoch(train) [6][1700/3862] lr: 7.9111e-04 eta: 16:41:08 time: 1.0640 data_time: 0.0120 memory: 9030 grad_norm: 1.3750 loss: 1.8315 loss_heatmap: 0.7439 layer_-1_loss_cls: 0.1155 layer_-1_loss_bbox: 0.9721 matched_ious: 0.5180 2023/03/22 12:05:16 - mmengine - INFO - Epoch(train) [6][1750/3862] lr: 7.9304e-04 eta: 16:40:15 time: 1.0705 data_time: 0.0128 memory: 9459 grad_norm: 1.3411 loss: 1.8543 loss_heatmap: 0.7454 layer_-1_loss_cls: 0.1145 layer_-1_loss_bbox: 0.9944 matched_ious: 0.5150 2023/03/22 12:06:10 - mmengine - INFO - Epoch(train) [6][1800/3862] lr: 7.9496e-04 eta: 16:39:22 time: 1.0707 data_time: 0.0122 memory: 9162 grad_norm: 1.3268 loss: 1.8482 loss_heatmap: 0.7248 layer_-1_loss_cls: 0.1126 layer_-1_loss_bbox: 1.0108 matched_ious: 0.4796 2023/03/22 12:07:04 - mmengine - INFO - Epoch(train) [6][1850/3862] lr: 7.9688e-04 eta: 16:38:30 time: 1.0796 data_time: 0.0120 memory: 9255 grad_norm: 1.3356 loss: 1.7690 loss_heatmap: 0.7464 layer_-1_loss_cls: 0.1165 layer_-1_loss_bbox: 0.9061 matched_ious: 0.4801 2023/03/22 12:07:58 - mmengine - INFO - Epoch(train) [6][1900/3862] lr: 7.9879e-04 eta: 16:37:38 time: 1.0761 data_time: 0.0119 memory: 9677 grad_norm: 1.3529 loss: 1.8123 loss_heatmap: 0.7388 layer_-1_loss_cls: 0.1166 layer_-1_loss_bbox: 0.9568 matched_ious: 0.5364 2023/03/22 12:08:51 - mmengine - INFO - Epoch(train) [6][1950/3862] lr: 8.0069e-04 eta: 16:36:44 time: 1.0649 data_time: 0.0125 memory: 9167 grad_norm: 1.4086 loss: 1.7712 loss_heatmap: 0.7303 layer_-1_loss_cls: 0.1149 layer_-1_loss_bbox: 0.9260 matched_ious: 0.5226 2023/03/22 12:09:44 - mmengine - INFO - Epoch(train) [6][2000/3862] lr: 8.0259e-04 eta: 16:35:49 time: 1.0594 data_time: 0.0123 memory: 9243 grad_norm: 1.3678 loss: 1.8701 loss_heatmap: 0.7653 layer_-1_loss_cls: 0.1175 layer_-1_loss_bbox: 0.9874 matched_ious: 0.4849 2023/03/22 12:10:37 - mmengine - INFO - Epoch(train) [6][2050/3862] lr: 8.0448e-04 eta: 16:34:55 time: 1.0620 data_time: 0.0120 memory: 9023 grad_norm: 1.3734 loss: 1.8518 loss_heatmap: 0.7584 layer_-1_loss_cls: 0.1180 layer_-1_loss_bbox: 0.9754 matched_ious: 0.4770 2023/03/22 12:11:30 - mmengine - INFO - Epoch(train) [6][2100/3862] lr: 8.0636e-04 eta: 16:34:01 time: 1.0660 data_time: 0.0124 memory: 9224 grad_norm: 1.3585 loss: 1.8366 loss_heatmap: 0.7342 layer_-1_loss_cls: 0.1147 layer_-1_loss_bbox: 0.9876 matched_ious: 0.4682 2023/03/22 12:12:24 - mmengine - INFO - Epoch(train) [6][2150/3862] lr: 8.0824e-04 eta: 16:33:07 time: 1.0642 data_time: 0.0127 memory: 8895 grad_norm: 1.4182 loss: 1.7539 loss_heatmap: 0.7302 layer_-1_loss_cls: 0.1132 layer_-1_loss_bbox: 0.9105 matched_ious: 0.4766 2023/03/22 12:13:17 - mmengine - INFO - Epoch(train) [6][2200/3862] lr: 8.1011e-04 eta: 16:32:13 time: 1.0630 data_time: 0.0125 memory: 9357 grad_norm: 1.3087 loss: 1.8128 loss_heatmap: 0.7308 layer_-1_loss_cls: 0.1135 layer_-1_loss_bbox: 0.9685 matched_ious: 0.4885 2023/03/22 12:14:10 - mmengine - INFO - Epoch(train) [6][2250/3862] lr: 8.1197e-04 eta: 16:31:20 time: 1.0727 data_time: 0.0120 memory: 9202 grad_norm: 1.4003 loss: 1.8149 loss_heatmap: 0.7476 layer_-1_loss_cls: 0.1150 layer_-1_loss_bbox: 0.9523 matched_ious: 0.5160 2023/03/22 12:15:04 - mmengine - INFO - Epoch(train) [6][2300/3862] lr: 8.1383e-04 eta: 16:30:27 time: 1.0686 data_time: 0.0122 memory: 9094 grad_norm: 1.3088 loss: 1.7958 loss_heatmap: 0.7184 layer_-1_loss_cls: 0.1146 layer_-1_loss_bbox: 0.9628 matched_ious: 0.4785 2023/03/22 12:15:58 - mmengine - INFO - Epoch(train) [6][2350/3862] lr: 8.1568e-04 eta: 16:29:35 time: 1.0807 data_time: 0.0120 memory: 9215 grad_norm: 1.2539 loss: 1.8463 loss_heatmap: 0.7553 layer_-1_loss_cls: 0.1164 layer_-1_loss_bbox: 0.9746 matched_ious: 0.5130 2023/03/22 12:16:51 - mmengine - INFO - Epoch(train) [6][2400/3862] lr: 8.1752e-04 eta: 16:28:41 time: 1.0596 data_time: 0.0122 memory: 9101 grad_norm: 1.2867 loss: 1.8330 loss_heatmap: 0.7526 layer_-1_loss_cls: 0.1166 layer_-1_loss_bbox: 0.9638 matched_ious: 0.5030 2023/03/22 12:17:44 - mmengine - INFO - Epoch(train) [6][2450/3862] lr: 8.1936e-04 eta: 16:27:47 time: 1.0629 data_time: 0.0123 memory: 9162 grad_norm: 1.4359 loss: 1.8542 loss_heatmap: 0.7572 layer_-1_loss_cls: 0.1172 layer_-1_loss_bbox: 0.9798 matched_ious: 0.4857 2023/03/22 12:18:38 - mmengine - INFO - Epoch(train) [6][2500/3862] lr: 8.2119e-04 eta: 16:26:54 time: 1.0717 data_time: 0.0122 memory: 9261 grad_norm: 1.2912 loss: 1.8420 loss_heatmap: 0.7508 layer_-1_loss_cls: 0.1167 layer_-1_loss_bbox: 0.9745 matched_ious: 0.5464 2023/03/22 12:19:31 - mmengine - INFO - Epoch(train) [6][2550/3862] lr: 8.2301e-04 eta: 16:26:00 time: 1.0682 data_time: 0.0124 memory: 9077 grad_norm: 1.2892 loss: 1.8694 loss_heatmap: 0.7582 layer_-1_loss_cls: 0.1183 layer_-1_loss_bbox: 0.9929 matched_ious: 0.5296 2023/03/22 12:20:24 - mmengine - INFO - Epoch(train) [6][2600/3862] lr: 8.2483e-04 eta: 16:25:06 time: 1.0640 data_time: 0.0122 memory: 9053 grad_norm: 1.2690 loss: 1.8476 loss_heatmap: 0.7441 layer_-1_loss_cls: 0.1143 layer_-1_loss_bbox: 0.9893 matched_ious: 0.4588 2023/03/22 12:21:18 - mmengine - INFO - Epoch(train) [6][2650/3862] lr: 8.2663e-04 eta: 16:24:13 time: 1.0671 data_time: 0.0120 memory: 9115 grad_norm: 1.2848 loss: 1.7196 loss_heatmap: 0.7107 layer_-1_loss_cls: 0.1100 layer_-1_loss_bbox: 0.8989 matched_ious: 0.4941 2023/03/22 12:22:00 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 12:22:11 - mmengine - INFO - Epoch(train) [6][2700/3862] lr: 8.2843e-04 eta: 16:23:19 time: 1.0692 data_time: 0.0121 memory: 9496 grad_norm: 1.2729 loss: 1.8359 loss_heatmap: 0.7349 layer_-1_loss_cls: 0.1131 layer_-1_loss_bbox: 0.9880 matched_ious: 0.4891 2023/03/22 12:23:05 - mmengine - INFO - Epoch(train) [6][2750/3862] lr: 8.3023e-04 eta: 16:22:26 time: 1.0703 data_time: 0.0125 memory: 9089 grad_norm: 1.3305 loss: 1.8266 loss_heatmap: 0.7435 layer_-1_loss_cls: 0.1149 layer_-1_loss_bbox: 0.9682 matched_ious: 0.4608 2023/03/22 12:23:58 - mmengine - INFO - Epoch(train) [6][2800/3862] lr: 8.3201e-04 eta: 16:21:32 time: 1.0633 data_time: 0.0124 memory: 9181 grad_norm: 1.3451 loss: 1.8097 loss_heatmap: 0.7402 layer_-1_loss_cls: 0.1116 layer_-1_loss_bbox: 0.9579 matched_ious: 0.4523 2023/03/22 12:24:51 - mmengine - INFO - Epoch(train) [6][2850/3862] lr: 8.3379e-04 eta: 16:20:38 time: 1.0615 data_time: 0.0121 memory: 9344 grad_norm: 1.3178 loss: 1.8572 loss_heatmap: 0.7504 layer_-1_loss_cls: 0.1140 layer_-1_loss_bbox: 0.9928 matched_ious: 0.5110 2023/03/22 12:25:44 - mmengine - INFO - Epoch(train) [6][2900/3862] lr: 8.3557e-04 eta: 16:19:44 time: 1.0618 data_time: 0.0126 memory: 9053 grad_norm: 1.4711 loss: 1.8299 loss_heatmap: 0.7413 layer_-1_loss_cls: 0.1155 layer_-1_loss_bbox: 0.9731 matched_ious: 0.5149 2023/03/22 12:26:37 - mmengine - INFO - Epoch(train) [6][2950/3862] lr: 8.3733e-04 eta: 16:18:50 time: 1.0688 data_time: 0.0124 memory: 9368 grad_norm: 1.2859 loss: 1.8001 loss_heatmap: 0.7404 layer_-1_loss_cls: 0.1137 layer_-1_loss_bbox: 0.9459 matched_ious: 0.5239 2023/03/22 12:27:31 - mmengine - INFO - Epoch(train) [6][3000/3862] lr: 8.3909e-04 eta: 16:17:59 time: 1.0815 data_time: 0.0122 memory: 9033 grad_norm: 1.3220 loss: 1.8133 loss_heatmap: 0.7232 layer_-1_loss_cls: 0.1100 layer_-1_loss_bbox: 0.9800 matched_ious: 0.4559 2023/03/22 12:28:25 - mmengine - INFO - Epoch(train) [6][3050/3862] lr: 8.4084e-04 eta: 16:17:05 time: 1.0688 data_time: 0.0120 memory: 9026 grad_norm: 1.2925 loss: 1.8297 loss_heatmap: 0.7478 layer_-1_loss_cls: 0.1142 layer_-1_loss_bbox: 0.9677 matched_ious: 0.4857 2023/03/22 12:29:18 - mmengine - INFO - Epoch(train) [6][3100/3862] lr: 8.4258e-04 eta: 16:16:11 time: 1.0646 data_time: 0.0122 memory: 9260 grad_norm: 1.2433 loss: 1.8483 loss_heatmap: 0.7448 layer_-1_loss_cls: 0.1167 layer_-1_loss_bbox: 0.9869 matched_ious: 0.5152 2023/03/22 12:30:11 - mmengine - INFO - Epoch(train) [6][3150/3862] lr: 8.4431e-04 eta: 16:15:18 time: 1.0644 data_time: 0.0127 memory: 9022 grad_norm: 1.2683 loss: 1.7756 loss_heatmap: 0.7220 layer_-1_loss_cls: 0.1128 layer_-1_loss_bbox: 0.9409 matched_ious: 0.5398 2023/03/22 12:31:05 - mmengine - INFO - Epoch(train) [6][3200/3862] lr: 8.4604e-04 eta: 16:14:24 time: 1.0697 data_time: 0.0122 memory: 9096 grad_norm: 1.2162 loss: 1.8570 loss_heatmap: 0.7473 layer_-1_loss_cls: 0.1182 layer_-1_loss_bbox: 0.9914 matched_ious: 0.4960 2023/03/22 12:31:59 - mmengine - INFO - Epoch(train) [6][3250/3862] lr: 8.4776e-04 eta: 16:13:32 time: 1.0746 data_time: 0.0121 memory: 9145 grad_norm: 1.2358 loss: 1.8714 loss_heatmap: 0.7466 layer_-1_loss_cls: 0.1147 layer_-1_loss_bbox: 1.0100 matched_ious: 0.4650 2023/03/22 12:32:52 - mmengine - INFO - Epoch(train) [6][3300/3862] lr: 8.4947e-04 eta: 16:12:38 time: 1.0674 data_time: 0.0121 memory: 9214 grad_norm: 1.2728 loss: 1.8234 loss_heatmap: 0.7475 layer_-1_loss_cls: 0.1154 layer_-1_loss_bbox: 0.9605 matched_ious: 0.5009 2023/03/22 12:33:46 - mmengine - INFO - Epoch(train) [6][3350/3862] lr: 8.5117e-04 eta: 16:11:46 time: 1.0761 data_time: 0.0124 memory: 9281 grad_norm: 1.3812 loss: 1.7978 loss_heatmap: 0.7365 layer_-1_loss_cls: 0.1146 layer_-1_loss_bbox: 0.9467 matched_ious: 0.5027 2023/03/22 12:34:39 - mmengine - INFO - Epoch(train) [6][3400/3862] lr: 8.5287e-04 eta: 16:10:52 time: 1.0642 data_time: 0.0121 memory: 9193 grad_norm: 1.3312 loss: 1.8095 loss_heatmap: 0.7224 layer_-1_loss_cls: 0.1109 layer_-1_loss_bbox: 0.9761 matched_ious: 0.4562 2023/03/22 12:35:32 - mmengine - INFO - Epoch(train) [6][3450/3862] lr: 8.5456e-04 eta: 16:09:58 time: 1.0659 data_time: 0.0118 memory: 9269 grad_norm: 1.2784 loss: 1.7980 loss_heatmap: 0.7387 layer_-1_loss_cls: 0.1136 layer_-1_loss_bbox: 0.9457 matched_ious: 0.5397 2023/03/22 12:36:26 - mmengine - INFO - Epoch(train) [6][3500/3862] lr: 8.5624e-04 eta: 16:09:04 time: 1.0664 data_time: 0.0120 memory: 9349 grad_norm: 1.2296 loss: 1.8764 loss_heatmap: 0.7545 layer_-1_loss_cls: 0.1149 layer_-1_loss_bbox: 1.0069 matched_ious: 0.5102 2023/03/22 12:37:19 - mmengine - INFO - Epoch(train) [6][3550/3862] lr: 8.5791e-04 eta: 16:08:11 time: 1.0698 data_time: 0.0122 memory: 9063 grad_norm: 1.2677 loss: 1.8191 loss_heatmap: 0.7415 layer_-1_loss_cls: 0.1148 layer_-1_loss_bbox: 0.9627 matched_ious: 0.5080 2023/03/22 12:38:12 - mmengine - INFO - Epoch(train) [6][3600/3862] lr: 8.5958e-04 eta: 16:07:17 time: 1.0614 data_time: 0.0123 memory: 9260 grad_norm: 1.2248 loss: 1.8128 loss_heatmap: 0.7364 layer_-1_loss_cls: 0.1108 layer_-1_loss_bbox: 0.9656 matched_ious: 0.5139 2023/03/22 12:39:05 - mmengine - INFO - Epoch(train) [6][3650/3862] lr: 8.6123e-04 eta: 16:06:23 time: 1.0652 data_time: 0.0124 memory: 9147 grad_norm: 1.3014 loss: 1.7973 loss_heatmap: 0.7586 layer_-1_loss_cls: 0.1159 layer_-1_loss_bbox: 0.9228 matched_ious: 0.4734 2023/03/22 12:39:48 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 12:39:59 - mmengine - INFO - Epoch(train) [6][3700/3862] lr: 8.6288e-04 eta: 16:05:30 time: 1.0741 data_time: 0.0118 memory: 9331 grad_norm: 1.1664 loss: 1.7576 loss_heatmap: 0.7243 layer_-1_loss_cls: 0.1100 layer_-1_loss_bbox: 0.9233 matched_ious: 0.5166 2023/03/22 12:40:52 - mmengine - INFO - Epoch(train) [6][3750/3862] lr: 8.6452e-04 eta: 16:04:36 time: 1.0595 data_time: 0.0120 memory: 9221 grad_norm: 1.2751 loss: 1.7115 loss_heatmap: 0.7038 layer_-1_loss_cls: 0.1104 layer_-1_loss_bbox: 0.8973 matched_ious: 0.4965 2023/03/22 12:41:45 - mmengine - INFO - Epoch(train) [6][3800/3862] lr: 8.6615e-04 eta: 16:03:42 time: 1.0594 data_time: 0.0121 memory: 9187 grad_norm: 1.2798 loss: 1.7952 loss_heatmap: 0.7244 layer_-1_loss_cls: 0.1107 layer_-1_loss_bbox: 0.9601 matched_ious: 0.4903 2023/03/22 12:42:38 - mmengine - INFO - Epoch(train) [6][3850/3862] lr: 8.6778e-04 eta: 16:02:47 time: 1.0607 data_time: 0.0121 memory: 9359 grad_norm: 1.1947 loss: 1.8362 loss_heatmap: 0.7563 layer_-1_loss_cls: 0.1154 layer_-1_loss_bbox: 0.9645 matched_ious: 0.5151 2023/03/22 12:42:51 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 12:43:47 - mmengine - INFO - Epoch(train) [7][ 50/3862] lr: 8.6978e-04 eta: 16:01:47 time: 1.1243 data_time: 0.0514 memory: 9194 grad_norm: 1.2627 loss: 1.7618 loss_heatmap: 0.7174 layer_-1_loss_cls: 0.1094 layer_-1_loss_bbox: 0.9350 matched_ious: 0.4736 2023/03/22 12:44:41 - mmengine - INFO - Epoch(train) [7][ 100/3862] lr: 8.7139e-04 eta: 16:00:55 time: 1.0747 data_time: 0.0121 memory: 9339 grad_norm: 1.1765 loss: 1.7292 loss_heatmap: 0.7115 layer_-1_loss_cls: 0.1109 layer_-1_loss_bbox: 0.9068 matched_ious: 0.4857 2023/03/22 12:45:34 - mmengine - INFO - Epoch(train) [7][ 150/3862] lr: 8.7298e-04 eta: 16:00:00 time: 1.0608 data_time: 0.0116 memory: 9214 grad_norm: 1.2010 loss: 1.7962 loss_heatmap: 0.7216 layer_-1_loss_cls: 0.1136 layer_-1_loss_bbox: 0.9610 matched_ious: 0.4809 2023/03/22 12:46:27 - mmengine - INFO - Epoch(train) [7][ 200/3862] lr: 8.7457e-04 eta: 15:59:06 time: 1.0593 data_time: 0.0117 memory: 9053 grad_norm: 1.2622 loss: 1.8280 loss_heatmap: 0.7421 layer_-1_loss_cls: 0.1146 layer_-1_loss_bbox: 0.9713 matched_ious: 0.4454 2023/03/22 12:47:20 - mmengine - INFO - Epoch(train) [7][ 250/3862] lr: 8.7615e-04 eta: 15:58:12 time: 1.0642 data_time: 0.0120 memory: 9089 grad_norm: 1.1455 loss: 1.7627 loss_heatmap: 0.7185 layer_-1_loss_cls: 0.1122 layer_-1_loss_bbox: 0.9319 matched_ious: 0.5455 2023/03/22 12:48:14 - mmengine - INFO - Epoch(train) [7][ 300/3862] lr: 8.7772e-04 eta: 15:57:20 time: 1.0773 data_time: 0.0116 memory: 9065 grad_norm: 1.1828 loss: 1.7297 loss_heatmap: 0.7145 layer_-1_loss_cls: 0.1140 layer_-1_loss_bbox: 0.9011 matched_ious: 0.5021 2023/03/22 12:49:07 - mmengine - INFO - Epoch(train) [7][ 350/3862] lr: 8.7929e-04 eta: 15:56:26 time: 1.0625 data_time: 0.0116 memory: 9133 grad_norm: 1.1943 loss: 1.7717 loss_heatmap: 0.7295 layer_-1_loss_cls: 0.1117 layer_-1_loss_bbox: 0.9306 matched_ious: 0.4748 2023/03/22 12:50:00 - mmengine - INFO - Epoch(train) [7][ 400/3862] lr: 8.8084e-04 eta: 15:55:31 time: 1.0613 data_time: 0.0119 memory: 9323 grad_norm: 1.1814 loss: 1.7433 loss_heatmap: 0.7138 layer_-1_loss_cls: 0.1113 layer_-1_loss_bbox: 0.9183 matched_ious: 0.5131 2023/03/22 12:50:54 - mmengine - INFO - Epoch(train) [7][ 450/3862] lr: 8.8239e-04 eta: 15:54:39 time: 1.0774 data_time: 0.0123 memory: 9170 grad_norm: 1.1556 loss: 1.8159 loss_heatmap: 0.7461 layer_-1_loss_cls: 0.1139 layer_-1_loss_bbox: 0.9559 matched_ious: 0.5282 2023/03/22 12:51:47 - mmengine - INFO - Epoch(train) [7][ 500/3862] lr: 8.8393e-04 eta: 15:53:46 time: 1.0672 data_time: 0.0124 memory: 9095 grad_norm: 1.1828 loss: 1.8266 loss_heatmap: 0.7397 layer_-1_loss_cls: 0.1149 layer_-1_loss_bbox: 0.9721 matched_ious: 0.4685 2023/03/22 12:52:41 - mmengine - INFO - Epoch(train) [7][ 550/3862] lr: 8.8546e-04 eta: 15:52:52 time: 1.0688 data_time: 0.0123 memory: 9165 grad_norm: 1.2173 loss: 1.7809 loss_heatmap: 0.7347 layer_-1_loss_cls: 0.1147 layer_-1_loss_bbox: 0.9315 matched_ious: 0.4618 2023/03/22 12:53:34 - mmengine - INFO - Epoch(train) [7][ 600/3862] lr: 8.8698e-04 eta: 15:51:58 time: 1.0658 data_time: 0.0119 memory: 9121 grad_norm: 1.1039 loss: 1.7866 loss_heatmap: 0.7463 layer_-1_loss_cls: 0.1139 layer_-1_loss_bbox: 0.9264 matched_ious: 0.5145 2023/03/22 12:54:28 - mmengine - INFO - Epoch(train) [7][ 650/3862] lr: 8.8849e-04 eta: 15:51:05 time: 1.0708 data_time: 0.0119 memory: 9191 grad_norm: 1.1975 loss: 1.8040 loss_heatmap: 0.7353 layer_-1_loss_cls: 0.1139 layer_-1_loss_bbox: 0.9548 matched_ious: 0.4662 2023/03/22 12:55:21 - mmengine - INFO - Epoch(train) [7][ 700/3862] lr: 8.8999e-04 eta: 15:50:11 time: 1.0632 data_time: 0.0121 memory: 9207 grad_norm: 1.0945 loss: 1.7713 loss_heatmap: 0.7427 layer_-1_loss_cls: 0.1134 layer_-1_loss_bbox: 0.9151 matched_ious: 0.4980 2023/03/22 12:56:14 - mmengine - INFO - Epoch(train) [7][ 750/3862] lr: 8.9149e-04 eta: 15:49:19 time: 1.0737 data_time: 0.0122 memory: 9033 grad_norm: 1.1354 loss: 1.8116 loss_heatmap: 0.7262 layer_-1_loss_cls: 0.1120 layer_-1_loss_bbox: 0.9734 matched_ious: 0.4575 2023/03/22 12:57:07 - mmengine - INFO - Epoch(train) [7][ 800/3862] lr: 8.9297e-04 eta: 15:48:24 time: 1.0602 data_time: 0.0120 memory: 8980 grad_norm: 1.1273 loss: 1.8214 loss_heatmap: 0.7293 layer_-1_loss_cls: 0.1132 layer_-1_loss_bbox: 0.9790 matched_ious: 0.4918 2023/03/22 12:57:37 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 12:58:01 - mmengine - INFO - Epoch(train) [7][ 850/3862] lr: 8.9445e-04 eta: 15:47:31 time: 1.0678 data_time: 0.0124 memory: 9335 grad_norm: 1.2791 loss: 1.8566 loss_heatmap: 0.7305 layer_-1_loss_cls: 0.1127 layer_-1_loss_bbox: 1.0134 matched_ious: 0.4938 2023/03/22 12:58:54 - mmengine - INFO - Epoch(train) [7][ 900/3862] lr: 8.9592e-04 eta: 15:46:37 time: 1.0639 data_time: 0.0118 memory: 9069 grad_norm: 1.1113 loss: 1.7395 loss_heatmap: 0.7200 layer_-1_loss_cls: 0.1122 layer_-1_loss_bbox: 0.9074 matched_ious: 0.5104 2023/03/22 12:59:47 - mmengine - INFO - Epoch(train) [7][ 950/3862] lr: 8.9738e-04 eta: 15:45:43 time: 1.0683 data_time: 0.0119 memory: 9294 grad_norm: 1.3788 loss: 1.8733 loss_heatmap: 0.7582 layer_-1_loss_cls: 0.1154 layer_-1_loss_bbox: 0.9996 matched_ious: 0.4729 2023/03/22 13:00:41 - mmengine - INFO - Epoch(train) [7][1000/3862] lr: 8.9883e-04 eta: 15:44:50 time: 1.0698 data_time: 0.0118 memory: 9322 grad_norm: 1.1569 loss: 1.7919 loss_heatmap: 0.7340 layer_-1_loss_cls: 0.1129 layer_-1_loss_bbox: 0.9450 matched_ious: 0.4759 2023/03/22 13:01:34 - mmengine - INFO - Epoch(train) [7][1050/3862] lr: 9.0027e-04 eta: 15:43:56 time: 1.0645 data_time: 0.0121 memory: 9258 grad_norm: 1.0680 loss: 1.7977 loss_heatmap: 0.7258 layer_-1_loss_cls: 0.1128 layer_-1_loss_bbox: 0.9591 matched_ious: 0.5087 2023/03/22 13:02:28 - mmengine - INFO - Epoch(train) [7][1100/3862] lr: 9.0170e-04 eta: 15:43:03 time: 1.0718 data_time: 0.0119 memory: 9112 grad_norm: 1.1034 loss: 1.7368 loss_heatmap: 0.7147 layer_-1_loss_cls: 0.1095 layer_-1_loss_bbox: 0.9125 matched_ious: 0.5114 2023/03/22 13:03:22 - mmengine - INFO - Epoch(train) [7][1150/3862] lr: 9.0312e-04 eta: 15:42:11 time: 1.0755 data_time: 0.0123 memory: 9012 grad_norm: 1.1748 loss: 1.7977 loss_heatmap: 0.7225 layer_-1_loss_cls: 0.1110 layer_-1_loss_bbox: 0.9642 matched_ious: 0.5212 2023/03/22 13:04:15 - mmengine - INFO - Epoch(train) [7][1200/3862] lr: 9.0453e-04 eta: 15:41:18 time: 1.0730 data_time: 0.0126 memory: 9021 grad_norm: 1.0600 loss: 1.7887 loss_heatmap: 0.7418 layer_-1_loss_cls: 0.1142 layer_-1_loss_bbox: 0.9327 matched_ious: 0.4749 2023/03/22 13:05:09 - mmengine - INFO - Epoch(train) [7][1250/3862] lr: 9.0594e-04 eta: 15:40:25 time: 1.0748 data_time: 0.0122 memory: 9271 grad_norm: 1.0896 loss: 1.7940 loss_heatmap: 0.7547 layer_-1_loss_cls: 0.1139 layer_-1_loss_bbox: 0.9255 matched_ious: 0.5307 2023/03/22 13:06:03 - mmengine - INFO - Epoch(train) [7][1300/3862] lr: 9.0733e-04 eta: 15:39:32 time: 1.0731 data_time: 0.0117 memory: 9211 grad_norm: 1.1848 loss: 1.8063 loss_heatmap: 0.7299 layer_-1_loss_cls: 0.1129 layer_-1_loss_bbox: 0.9635 matched_ious: 0.4824 2023/03/22 13:06:56 - mmengine - INFO - Epoch(train) [7][1350/3862] lr: 9.0872e-04 eta: 15:38:38 time: 1.0619 data_time: 0.0121 memory: 9239 grad_norm: 1.1057 loss: 1.7884 loss_heatmap: 0.7218 layer_-1_loss_cls: 0.1119 layer_-1_loss_bbox: 0.9547 matched_ious: 0.5038 2023/03/22 13:07:50 - mmengine - INFO - Epoch(train) [7][1400/3862] lr: 9.1010e-04 eta: 15:37:46 time: 1.0845 data_time: 0.0122 memory: 9267 grad_norm: 1.1063 loss: 1.7860 loss_heatmap: 0.7524 layer_-1_loss_cls: 0.1171 layer_-1_loss_bbox: 0.9165 matched_ious: 0.5195 2023/03/22 13:08:44 - mmengine - INFO - Epoch(train) [7][1450/3862] lr: 9.1146e-04 eta: 15:36:54 time: 1.0756 data_time: 0.0120 memory: 9225 grad_norm: 1.1323 loss: 1.7943 loss_heatmap: 0.7274 layer_-1_loss_cls: 0.1114 layer_-1_loss_bbox: 0.9555 matched_ious: 0.4909 2023/03/22 13:09:37 - mmengine - INFO - Epoch(train) [7][1500/3862] lr: 9.1282e-04 eta: 15:36:00 time: 1.0664 data_time: 0.0119 memory: 8983 grad_norm: 1.1225 loss: 1.7696 loss_heatmap: 0.7230 layer_-1_loss_cls: 0.1099 layer_-1_loss_bbox: 0.9367 matched_ious: 0.5118 2023/03/22 13:10:31 - mmengine - INFO - Epoch(train) [7][1550/3862] lr: 9.1417e-04 eta: 15:35:07 time: 1.0701 data_time: 0.0120 memory: 9043 grad_norm: 1.1055 loss: 1.7574 loss_heatmap: 0.7195 layer_-1_loss_cls: 0.1106 layer_-1_loss_bbox: 0.9274 matched_ious: 0.5035 2023/03/22 13:11:24 - mmengine - INFO - Epoch(train) [7][1600/3862] lr: 9.1551e-04 eta: 15:34:13 time: 1.0671 data_time: 0.0121 memory: 9334 grad_norm: 1.1455 loss: 1.8089 loss_heatmap: 0.7402 layer_-1_loss_cls: 0.1112 layer_-1_loss_bbox: 0.9575 matched_ious: 0.5052 2023/03/22 13:12:17 - mmengine - INFO - Epoch(train) [7][1650/3862] lr: 9.1684e-04 eta: 15:33:19 time: 1.0577 data_time: 0.0124 memory: 9268 grad_norm: 1.2071 loss: 1.7417 loss_heatmap: 0.7332 layer_-1_loss_cls: 0.1121 layer_-1_loss_bbox: 0.8965 matched_ious: 0.4808 2023/03/22 13:13:10 - mmengine - INFO - Epoch(train) [7][1700/3862] lr: 9.1816e-04 eta: 15:32:25 time: 1.0648 data_time: 0.0125 memory: 9010 grad_norm: 1.0565 loss: 1.7739 loss_heatmap: 0.6977 layer_-1_loss_cls: 0.1076 layer_-1_loss_bbox: 0.9686 matched_ious: 0.4913 2023/03/22 13:14:04 - mmengine - INFO - Epoch(train) [7][1750/3862] lr: 9.1947e-04 eta: 15:31:32 time: 1.0751 data_time: 0.0126 memory: 9378 grad_norm: 1.0775 loss: 1.7478 loss_heatmap: 0.7253 layer_-1_loss_cls: 0.1117 layer_-1_loss_bbox: 0.9108 matched_ious: 0.5171 2023/03/22 13:14:57 - mmengine - INFO - Epoch(train) [7][1800/3862] lr: 9.2077e-04 eta: 15:30:39 time: 1.0653 data_time: 0.0121 memory: 9099 grad_norm: 1.0319 loss: 1.7494 loss_heatmap: 0.7124 layer_-1_loss_cls: 0.1119 layer_-1_loss_bbox: 0.9250 matched_ious: 0.4940 2023/03/22 13:15:27 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 13:15:50 - mmengine - INFO - Epoch(train) [7][1850/3862] lr: 9.2206e-04 eta: 15:29:45 time: 1.0692 data_time: 0.0129 memory: 9237 grad_norm: 1.1107 loss: 1.7401 loss_heatmap: 0.7214 layer_-1_loss_cls: 0.1129 layer_-1_loss_bbox: 0.9057 matched_ious: 0.5019 2023/03/22 13:16:44 - mmengine - INFO - Epoch(train) [7][1900/3862] lr: 9.2335e-04 eta: 15:28:52 time: 1.0671 data_time: 0.0123 memory: 9404 grad_norm: 1.0161 loss: 1.8302 loss_heatmap: 0.7477 layer_-1_loss_cls: 0.1136 layer_-1_loss_bbox: 0.9689 matched_ious: 0.4884 2023/03/22 13:17:37 - mmengine - INFO - Epoch(train) [7][1950/3862] lr: 9.2462e-04 eta: 15:27:59 time: 1.0698 data_time: 0.0125 memory: 9060 grad_norm: 1.1291 loss: 1.7142 loss_heatmap: 0.7120 layer_-1_loss_cls: 0.1089 layer_-1_loss_bbox: 0.8932 matched_ious: 0.5323 2023/03/22 13:18:31 - mmengine - INFO - Epoch(train) [7][2000/3862] lr: 9.2588e-04 eta: 15:27:06 time: 1.0752 data_time: 0.0121 memory: 8858 grad_norm: 1.0825 loss: 1.7312 loss_heatmap: 0.7051 layer_-1_loss_cls: 0.1114 layer_-1_loss_bbox: 0.9147 matched_ious: 0.5153 2023/03/22 13:19:25 - mmengine - INFO - Epoch(train) [7][2050/3862] lr: 9.2713e-04 eta: 15:26:13 time: 1.0766 data_time: 0.0122 memory: 9178 grad_norm: 1.0936 loss: 1.7988 loss_heatmap: 0.7433 layer_-1_loss_cls: 0.1164 layer_-1_loss_bbox: 0.9391 matched_ious: 0.5197 2023/03/22 13:20:19 - mmengine - INFO - Epoch(train) [7][2100/3862] lr: 9.2838e-04 eta: 15:25:20 time: 1.0736 data_time: 0.0125 memory: 9087 grad_norm: 1.1071 loss: 1.7377 loss_heatmap: 0.7194 layer_-1_loss_cls: 0.1115 layer_-1_loss_bbox: 0.9069 matched_ious: 0.4820 2023/03/22 13:21:12 - mmengine - INFO - Epoch(train) [7][2150/3862] lr: 9.2961e-04 eta: 15:24:27 time: 1.0649 data_time: 0.0122 memory: 9279 grad_norm: 1.0595 loss: 1.7635 loss_heatmap: 0.7246 layer_-1_loss_cls: 0.1099 layer_-1_loss_bbox: 0.9290 matched_ious: 0.5079 2023/03/22 13:22:05 - mmengine - INFO - Epoch(train) [7][2200/3862] lr: 9.3083e-04 eta: 15:23:33 time: 1.0663 data_time: 0.0125 memory: 9205 grad_norm: 1.0665 loss: 1.7701 loss_heatmap: 0.7208 layer_-1_loss_cls: 0.1102 layer_-1_loss_bbox: 0.9390 matched_ious: 0.5347 2023/03/22 13:22:58 - mmengine - INFO - Epoch(train) [7][2250/3862] lr: 9.3205e-04 eta: 15:22:39 time: 1.0662 data_time: 0.0127 memory: 9350 grad_norm: 1.1070 loss: 1.7368 loss_heatmap: 0.7149 layer_-1_loss_cls: 0.1081 layer_-1_loss_bbox: 0.9138 matched_ious: 0.5335 2023/03/22 13:23:52 - mmengine - INFO - Epoch(train) [7][2300/3862] lr: 9.3325e-04 eta: 15:21:46 time: 1.0714 data_time: 0.0123 memory: 9003 grad_norm: 1.0530 loss: 1.7749 loss_heatmap: 0.7252 layer_-1_loss_cls: 0.1107 layer_-1_loss_bbox: 0.9390 matched_ious: 0.4669 2023/03/22 13:24:46 - mmengine - INFO - Epoch(train) [7][2350/3862] lr: 9.3445e-04 eta: 15:20:53 time: 1.0727 data_time: 0.0125 memory: 9315 grad_norm: 1.2298 loss: 1.8064 loss_heatmap: 0.7413 layer_-1_loss_cls: 0.1129 layer_-1_loss_bbox: 0.9522 matched_ious: 0.4914 2023/03/22 13:25:39 - mmengine - INFO - Epoch(train) [7][2400/3862] lr: 9.3563e-04 eta: 15:20:00 time: 1.0666 data_time: 0.0118 memory: 9212 grad_norm: 1.0110 loss: 1.7622 loss_heatmap: 0.7206 layer_-1_loss_cls: 0.1106 layer_-1_loss_bbox: 0.9310 matched_ious: 0.4997 2023/03/22 13:26:32 - mmengine - INFO - Epoch(train) [7][2450/3862] lr: 9.3680e-04 eta: 15:19:06 time: 1.0668 data_time: 0.0125 memory: 9048 grad_norm: 1.0247 loss: 1.7707 loss_heatmap: 0.7266 layer_-1_loss_cls: 0.1116 layer_-1_loss_bbox: 0.9324 matched_ious: 0.5490 2023/03/22 13:27:25 - mmengine - INFO - Epoch(train) [7][2500/3862] lr: 9.3797e-04 eta: 15:18:12 time: 1.0606 data_time: 0.0122 memory: 9105 grad_norm: 1.1682 loss: 1.7652 loss_heatmap: 0.7149 layer_-1_loss_cls: 0.1098 layer_-1_loss_bbox: 0.9405 matched_ious: 0.5084 2023/03/22 13:28:19 - mmengine - INFO - Epoch(train) [7][2550/3862] lr: 9.3912e-04 eta: 15:17:19 time: 1.0753 data_time: 0.0122 memory: 9355 grad_norm: 1.0439 loss: 1.7727 loss_heatmap: 0.7321 layer_-1_loss_cls: 0.1097 layer_-1_loss_bbox: 0.9308 matched_ious: 0.4876 2023/03/22 13:29:13 - mmengine - INFO - Epoch(train) [7][2600/3862] lr: 9.4027e-04 eta: 15:16:26 time: 1.0669 data_time: 0.0122 memory: 9094 grad_norm: 1.1260 loss: 1.7486 loss_heatmap: 0.7091 layer_-1_loss_cls: 0.1110 layer_-1_loss_bbox: 0.9285 matched_ious: 0.5119 2023/03/22 13:30:05 - mmengine - INFO - Epoch(train) [7][2650/3862] lr: 9.4140e-04 eta: 15:15:31 time: 1.0590 data_time: 0.0122 memory: 9151 grad_norm: 1.0512 loss: 1.7491 loss_heatmap: 0.7266 layer_-1_loss_cls: 0.1118 layer_-1_loss_bbox: 0.9107 matched_ious: 0.4831 2023/03/22 13:30:59 - mmengine - INFO - Epoch(train) [7][2700/3862] lr: 9.4252e-04 eta: 15:14:38 time: 1.0663 data_time: 0.0119 memory: 9422 grad_norm: 1.0334 loss: 1.7027 loss_heatmap: 0.7110 layer_-1_loss_cls: 0.1094 layer_-1_loss_bbox: 0.8823 matched_ious: 0.5486 2023/03/22 13:31:52 - mmengine - INFO - Epoch(train) [7][2750/3862] lr: 9.4364e-04 eta: 15:13:45 time: 1.0730 data_time: 0.0123 memory: 9163 grad_norm: 1.0483 loss: 1.7788 loss_heatmap: 0.7154 layer_-1_loss_cls: 0.1108 layer_-1_loss_bbox: 0.9525 matched_ious: 0.5063 2023/03/22 13:32:46 - mmengine - INFO - Epoch(train) [7][2800/3862] lr: 9.4474e-04 eta: 15:12:51 time: 1.0666 data_time: 0.0125 memory: 9047 grad_norm: 1.1005 loss: 1.7617 loss_heatmap: 0.7168 layer_-1_loss_cls: 0.1085 layer_-1_loss_bbox: 0.9363 matched_ious: 0.5433 2023/03/22 13:33:16 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 13:33:39 - mmengine - INFO - Epoch(train) [7][2850/3862] lr: 9.4584e-04 eta: 15:11:58 time: 1.0713 data_time: 0.0125 memory: 9225 grad_norm: 1.0754 loss: 1.7311 loss_heatmap: 0.7105 layer_-1_loss_cls: 0.1103 layer_-1_loss_bbox: 0.9102 matched_ious: 0.4818 2023/03/22 13:34:33 - mmengine - INFO - Epoch(train) [7][2900/3862] lr: 9.4692e-04 eta: 15:11:05 time: 1.0701 data_time: 0.0125 memory: 9059 grad_norm: 0.9972 loss: 1.6420 loss_heatmap: 0.6719 layer_-1_loss_cls: 0.1036 layer_-1_loss_bbox: 0.8665 matched_ious: 0.4771 2023/03/22 13:35:26 - mmengine - INFO - Epoch(train) [7][2950/3862] lr: 9.4799e-04 eta: 15:10:12 time: 1.0709 data_time: 0.0127 memory: 9343 grad_norm: 1.1756 loss: 1.7683 loss_heatmap: 0.7272 layer_-1_loss_cls: 0.1113 layer_-1_loss_bbox: 0.9298 matched_ious: 0.5268 2023/03/22 13:36:20 - mmengine - INFO - Epoch(train) [7][3000/3862] lr: 9.4905e-04 eta: 15:09:18 time: 1.0717 data_time: 0.0121 memory: 9131 grad_norm: 1.0523 loss: 1.7569 loss_heatmap: 0.7185 layer_-1_loss_cls: 0.1116 layer_-1_loss_bbox: 0.9268 matched_ious: 0.5225 2023/03/22 13:37:13 - mmengine - INFO - Epoch(train) [7][3050/3862] lr: 9.5011e-04 eta: 15:08:25 time: 1.0637 data_time: 0.0123 memory: 8985 grad_norm: 1.0361 loss: 1.7843 loss_heatmap: 0.7172 layer_-1_loss_cls: 0.1117 layer_-1_loss_bbox: 0.9553 matched_ious: 0.4830 2023/03/22 13:38:07 - mmengine - INFO - Epoch(train) [7][3100/3862] lr: 9.5115e-04 eta: 15:07:31 time: 1.0669 data_time: 0.0121 memory: 9162 grad_norm: 1.0653 loss: 1.7405 loss_heatmap: 0.7105 layer_-1_loss_cls: 0.1071 layer_-1_loss_bbox: 0.9229 matched_ious: 0.4611 2023/03/22 13:39:00 - mmengine - INFO - Epoch(train) [7][3150/3862] lr: 9.5218e-04 eta: 15:06:38 time: 1.0705 data_time: 0.0123 memory: 9175 grad_norm: 1.0853 loss: 1.7396 loss_heatmap: 0.7217 layer_-1_loss_cls: 0.1114 layer_-1_loss_bbox: 0.9066 matched_ious: 0.4769 2023/03/22 13:39:54 - mmengine - INFO - Epoch(train) [7][3200/3862] lr: 9.5320e-04 eta: 15:05:45 time: 1.0792 data_time: 0.0127 memory: 9279 grad_norm: 1.0003 loss: 1.7874 loss_heatmap: 0.7280 layer_-1_loss_cls: 0.1134 layer_-1_loss_bbox: 0.9460 matched_ious: 0.4898 2023/03/22 13:40:47 - mmengine - INFO - Epoch(train) [7][3250/3862] lr: 9.5421e-04 eta: 15:04:52 time: 1.0660 data_time: 0.0122 memory: 9414 grad_norm: 1.0273 loss: 1.7072 loss_heatmap: 0.6980 layer_-1_loss_cls: 0.1067 layer_-1_loss_bbox: 0.9026 matched_ious: 0.4670 2023/03/22 13:41:41 - mmengine - INFO - Epoch(train) [7][3300/3862] lr: 9.5521e-04 eta: 15:03:58 time: 1.0689 data_time: 0.0121 memory: 9189 grad_norm: 1.0642 loss: 1.6958 loss_heatmap: 0.7066 layer_-1_loss_cls: 0.1092 layer_-1_loss_bbox: 0.8800 matched_ious: 0.4899 2023/03/22 13:42:34 - mmengine - INFO - Epoch(train) [7][3350/3862] lr: 9.5620e-04 eta: 15:03:05 time: 1.0695 data_time: 0.0120 memory: 9283 grad_norm: 1.1143 loss: 1.7168 loss_heatmap: 0.7181 layer_-1_loss_cls: 0.1119 layer_-1_loss_bbox: 0.8868 matched_ious: 0.5206 2023/03/22 13:43:27 - mmengine - INFO - Epoch(train) [7][3400/3862] lr: 9.5718e-04 eta: 15:02:11 time: 1.0629 data_time: 0.0126 memory: 9125 grad_norm: 1.0853 loss: 1.7037 loss_heatmap: 0.7043 layer_-1_loss_cls: 0.1104 layer_-1_loss_bbox: 0.8890 matched_ious: 0.4818 2023/03/22 13:44:21 - mmengine - INFO - Epoch(train) [7][3450/3862] lr: 9.5815e-04 eta: 15:01:19 time: 1.0808 data_time: 0.0126 memory: 9143 grad_norm: 1.0983 loss: 1.7690 loss_heatmap: 0.7215 layer_-1_loss_cls: 0.1153 layer_-1_loss_bbox: 0.9322 matched_ious: 0.5115 2023/03/22 13:45:15 - mmengine - INFO - Epoch(train) [7][3500/3862] lr: 9.5911e-04 eta: 15:00:25 time: 1.0653 data_time: 0.0122 memory: 9130 grad_norm: 1.0282 loss: 1.7275 loss_heatmap: 0.7003 layer_-1_loss_cls: 0.1093 layer_-1_loss_bbox: 0.9179 matched_ious: 0.5224 2023/03/22 13:46:08 - mmengine - INFO - Epoch(train) [7][3550/3862] lr: 9.6006e-04 eta: 14:59:31 time: 1.0638 data_time: 0.0121 memory: 9225 grad_norm: 0.9298 loss: 1.7149 loss_heatmap: 0.6986 layer_-1_loss_cls: 0.1066 layer_-1_loss_bbox: 0.9098 matched_ious: 0.5080 2023/03/22 13:47:01 - mmengine - INFO - Epoch(train) [7][3600/3862] lr: 9.6099e-04 eta: 14:58:38 time: 1.0712 data_time: 0.0120 memory: 9077 grad_norm: 0.9715 loss: 1.8049 loss_heatmap: 0.7138 layer_-1_loss_cls: 0.1105 layer_-1_loss_bbox: 0.9806 matched_ious: 0.4950 2023/03/22 13:47:55 - mmengine - INFO - Epoch(train) [7][3650/3862] lr: 9.6192e-04 eta: 14:57:45 time: 1.0722 data_time: 0.0122 memory: 9190 grad_norm: 1.0016 loss: 1.7662 loss_heatmap: 0.6918 layer_-1_loss_cls: 0.1082 layer_-1_loss_bbox: 0.9663 matched_ious: 0.4813 2023/03/22 13:48:49 - mmengine - INFO - Epoch(train) [7][3700/3862] lr: 9.6283e-04 eta: 14:56:53 time: 1.0804 data_time: 0.0120 memory: 9096 grad_norm: 1.0647 loss: 1.7755 loss_heatmap: 0.7109 layer_-1_loss_cls: 0.1097 layer_-1_loss_bbox: 0.9549 matched_ious: 0.4758 2023/03/22 13:49:43 - mmengine - INFO - Epoch(train) [7][3750/3862] lr: 9.6374e-04 eta: 14:56:00 time: 1.0717 data_time: 0.0121 memory: 9031 grad_norm: 0.9682 loss: 1.7181 loss_heatmap: 0.7001 layer_-1_loss_cls: 0.1097 layer_-1_loss_bbox: 0.9083 matched_ious: 0.4922 2023/03/22 13:50:36 - mmengine - INFO - Epoch(train) [7][3800/3862] lr: 9.6463e-04 eta: 14:55:06 time: 1.0615 data_time: 0.0124 memory: 9183 grad_norm: 0.9700 loss: 1.6924 loss_heatmap: 0.6985 layer_-1_loss_cls: 0.1084 layer_-1_loss_bbox: 0.8855 matched_ious: 0.5137 2023/03/22 13:51:06 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 13:51:29 - mmengine - INFO - Epoch(train) [7][3850/3862] lr: 9.6552e-04 eta: 14:54:12 time: 1.0618 data_time: 0.0126 memory: 9260 grad_norm: 1.0022 loss: 1.6613 loss_heatmap: 0.6828 layer_-1_loss_cls: 0.1051 layer_-1_loss_bbox: 0.8734 matched_ious: 0.4961 2023/03/22 13:51:41 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 13:52:37 - mmengine - INFO - Epoch(train) [8][ 50/3862] lr: 9.6660e-04 eta: 14:53:09 time: 1.1124 data_time: 0.0638 memory: 9087 grad_norm: 0.9243 loss: 1.7130 loss_heatmap: 0.6967 layer_-1_loss_cls: 0.1082 layer_-1_loss_bbox: 0.9082 matched_ious: 0.4911 2023/03/22 13:53:30 - mmengine - INFO - Epoch(train) [8][ 100/3862] lr: 9.6746e-04 eta: 14:52:15 time: 1.0651 data_time: 0.0125 memory: 9248 grad_norm: 1.0641 loss: 1.7105 loss_heatmap: 0.6950 layer_-1_loss_cls: 0.1064 layer_-1_loss_bbox: 0.9091 matched_ious: 0.5535 2023/03/22 13:54:23 - mmengine - INFO - Epoch(train) [8][ 150/3862] lr: 9.6831e-04 eta: 14:51:21 time: 1.0574 data_time: 0.0127 memory: 9090 grad_norm: 1.1295 loss: 1.7486 loss_heatmap: 0.7150 layer_-1_loss_cls: 0.1089 layer_-1_loss_bbox: 0.9247 matched_ious: 0.4910 2023/03/22 13:55:16 - mmengine - INFO - Epoch(train) [8][ 200/3862] lr: 9.6915e-04 eta: 14:50:27 time: 1.0636 data_time: 0.0124 memory: 9151 grad_norm: 0.9930 loss: 1.7328 loss_heatmap: 0.7008 layer_-1_loss_cls: 0.1067 layer_-1_loss_bbox: 0.9252 matched_ious: 0.5106 2023/03/22 13:56:09 - mmengine - INFO - Epoch(train) [8][ 250/3862] lr: 9.6997e-04 eta: 14:49:33 time: 1.0598 data_time: 0.0124 memory: 9011 grad_norm: 1.0020 loss: 1.7399 loss_heatmap: 0.7153 layer_-1_loss_cls: 0.1090 layer_-1_loss_bbox: 0.9155 matched_ious: 0.5524 2023/03/22 13:57:03 - mmengine - INFO - Epoch(train) [8][ 300/3862] lr: 9.7079e-04 eta: 14:48:39 time: 1.0663 data_time: 0.0127 memory: 9270 grad_norm: 0.9960 loss: 1.7350 loss_heatmap: 0.7213 layer_-1_loss_cls: 0.1096 layer_-1_loss_bbox: 0.9042 matched_ious: 0.4972 2023/03/22 13:57:57 - mmengine - INFO - Epoch(train) [8][ 350/3862] lr: 9.7159e-04 eta: 14:47:47 time: 1.0761 data_time: 0.0120 memory: 9123 grad_norm: 1.0708 loss: 1.7722 loss_heatmap: 0.7045 layer_-1_loss_cls: 0.1072 layer_-1_loss_bbox: 0.9605 matched_ious: 0.4916 2023/03/22 13:58:50 - mmengine - INFO - Epoch(train) [8][ 400/3862] lr: 9.7239e-04 eta: 14:46:53 time: 1.0670 data_time: 0.0119 memory: 9142 grad_norm: 1.0116 loss: 1.7505 loss_heatmap: 0.7169 layer_-1_loss_cls: 0.1095 layer_-1_loss_bbox: 0.9241 matched_ious: 0.5318 2023/03/22 13:59:43 - mmengine - INFO - Epoch(train) [8][ 450/3862] lr: 9.7317e-04 eta: 14:45:59 time: 1.0643 data_time: 0.0120 memory: 9340 grad_norm: 0.9345 loss: 1.7747 loss_heatmap: 0.7111 layer_-1_loss_cls: 0.1087 layer_-1_loss_bbox: 0.9550 matched_ious: 0.5059 2023/03/22 14:00:36 - mmengine - INFO - Epoch(train) [8][ 500/3862] lr: 9.7394e-04 eta: 14:45:05 time: 1.0615 data_time: 0.0122 memory: 9043 grad_norm: 0.9870 loss: 1.6735 loss_heatmap: 0.6940 layer_-1_loss_cls: 0.1072 layer_-1_loss_bbox: 0.8722 matched_ious: 0.4897 2023/03/22 14:01:29 - mmengine - INFO - Epoch(train) [8][ 550/3862] lr: 9.7471e-04 eta: 14:44:11 time: 1.0620 data_time: 0.0123 memory: 9300 grad_norm: 0.9386 loss: 1.7432 loss_heatmap: 0.7086 layer_-1_loss_cls: 0.1095 layer_-1_loss_bbox: 0.9251 matched_ious: 0.5153 2023/03/22 14:02:23 - mmengine - INFO - Epoch(train) [8][ 600/3862] lr: 9.7546e-04 eta: 14:43:18 time: 1.0673 data_time: 0.0124 memory: 9257 grad_norm: 0.9176 loss: 1.7262 loss_heatmap: 0.7134 layer_-1_loss_cls: 0.1094 layer_-1_loss_bbox: 0.9033 matched_ious: 0.5309 2023/03/22 14:03:16 - mmengine - INFO - Epoch(train) [8][ 650/3862] lr: 9.7620e-04 eta: 14:42:24 time: 1.0677 data_time: 0.0124 memory: 9103 grad_norm: 0.9966 loss: 1.6860 loss_heatmap: 0.7068 layer_-1_loss_cls: 0.1093 layer_-1_loss_bbox: 0.8699 matched_ious: 0.5184 2023/03/22 14:04:09 - mmengine - INFO - Epoch(train) [8][ 700/3862] lr: 9.7693e-04 eta: 14:41:30 time: 1.0649 data_time: 0.0124 memory: 9069 grad_norm: 0.9164 loss: 1.6716 loss_heatmap: 0.6995 layer_-1_loss_cls: 0.1087 layer_-1_loss_bbox: 0.8634 matched_ious: 0.5377 2023/03/22 14:05:03 - mmengine - INFO - Epoch(train) [8][ 750/3862] lr: 9.7764e-04 eta: 14:40:38 time: 1.0788 data_time: 0.0130 memory: 9285 grad_norm: 0.9890 loss: 1.6972 loss_heatmap: 0.6969 layer_-1_loss_cls: 0.1060 layer_-1_loss_bbox: 0.8943 matched_ious: 0.4900 2023/03/22 14:05:56 - mmengine - INFO - Epoch(train) [8][ 800/3862] lr: 9.7835e-04 eta: 14:39:44 time: 1.0620 data_time: 0.0125 memory: 8963 grad_norm: 0.9181 loss: 1.7011 loss_heatmap: 0.6960 layer_-1_loss_cls: 0.1039 layer_-1_loss_bbox: 0.9012 matched_ious: 0.4675 2023/03/22 14:06:50 - mmengine - INFO - Epoch(train) [8][ 850/3862] lr: 9.7905e-04 eta: 14:38:51 time: 1.0743 data_time: 0.0123 memory: 9031 grad_norm: 0.9928 loss: 1.7114 loss_heatmap: 0.6913 layer_-1_loss_cls: 0.1057 layer_-1_loss_bbox: 0.9144 matched_ious: 0.4885 2023/03/22 14:07:44 - mmengine - INFO - Epoch(train) [8][ 900/3862] lr: 9.7973e-04 eta: 14:37:58 time: 1.0708 data_time: 0.0128 memory: 9122 grad_norm: 1.0725 loss: 1.7546 loss_heatmap: 0.7098 layer_-1_loss_cls: 0.1104 layer_-1_loss_bbox: 0.9344 matched_ious: 0.4852 2023/03/22 14:08:38 - mmengine - INFO - Epoch(train) [8][ 950/3862] lr: 9.8040e-04 eta: 14:37:05 time: 1.0784 data_time: 0.0126 memory: 9491 grad_norm: 0.9848 loss: 1.7184 loss_heatmap: 0.6906 layer_-1_loss_cls: 0.1080 layer_-1_loss_bbox: 0.9198 matched_ious: 0.5053 2023/03/22 14:08:55 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 14:09:32 - mmengine - INFO - Epoch(train) [8][1000/3862] lr: 9.8107e-04 eta: 14:36:13 time: 1.0842 data_time: 0.0124 memory: 9346 grad_norm: 0.9555 loss: 1.6875 loss_heatmap: 0.6898 layer_-1_loss_cls: 0.1075 layer_-1_loss_bbox: 0.8902 matched_ious: 0.5213 2023/03/22 14:10:25 - mmengine - INFO - Epoch(train) [8][1050/3862] lr: 9.8172e-04 eta: 14:35:19 time: 1.0622 data_time: 0.0122 memory: 9369 grad_norm: 1.0414 loss: 1.6630 loss_heatmap: 0.6848 layer_-1_loss_cls: 0.1057 layer_-1_loss_bbox: 0.8724 matched_ious: 0.4758 2023/03/22 14:11:19 - mmengine - INFO - Epoch(train) [8][1100/3862] lr: 9.8236e-04 eta: 14:34:27 time: 1.0763 data_time: 0.0125 memory: 8983 grad_norm: 0.9463 loss: 1.6423 loss_heatmap: 0.6706 layer_-1_loss_cls: 0.1037 layer_-1_loss_bbox: 0.8681 matched_ious: 0.5111 2023/03/22 14:12:12 - mmengine - INFO - Epoch(train) [8][1150/3862] lr: 9.8299e-04 eta: 14:33:33 time: 1.0654 data_time: 0.0123 memory: 8896 grad_norm: 0.9136 loss: 1.6860 loss_heatmap: 0.6947 layer_-1_loss_cls: 0.1088 layer_-1_loss_bbox: 0.8826 matched_ious: 0.4878 2023/03/22 14:13:05 - mmengine - INFO - Epoch(train) [8][1200/3862] lr: 9.8360e-04 eta: 14:32:39 time: 1.0623 data_time: 0.0121 memory: 9173 grad_norm: 1.0191 loss: 1.7557 loss_heatmap: 0.7104 layer_-1_loss_cls: 0.1085 layer_-1_loss_bbox: 0.9367 matched_ious: 0.5120 2023/03/22 14:13:59 - mmengine - INFO - Epoch(train) [8][1250/3862] lr: 9.8421e-04 eta: 14:31:46 time: 1.0701 data_time: 0.0122 memory: 9216 grad_norm: 0.8753 loss: 1.6946 loss_heatmap: 0.6930 layer_-1_loss_cls: 0.1063 layer_-1_loss_bbox: 0.8953 matched_ious: 0.4654 2023/03/22 14:14:52 - mmengine - INFO - Epoch(train) [8][1300/3862] lr: 9.8480e-04 eta: 14:30:52 time: 1.0666 data_time: 0.0125 memory: 9322 grad_norm: 0.9622 loss: 1.7289 loss_heatmap: 0.7131 layer_-1_loss_cls: 0.1070 layer_-1_loss_bbox: 0.9087 matched_ious: 0.5230 2023/03/22 14:15:45 - mmengine - INFO - Epoch(train) [8][1350/3862] lr: 9.8539e-04 eta: 14:29:58 time: 1.0633 data_time: 0.0125 memory: 9419 grad_norm: 1.0187 loss: 1.6721 loss_heatmap: 0.7014 layer_-1_loss_cls: 0.1077 layer_-1_loss_bbox: 0.8629 matched_ious: 0.5066 2023/03/22 14:16:39 - mmengine - INFO - Epoch(train) [8][1400/3862] lr: 9.8596e-04 eta: 14:29:06 time: 1.0804 data_time: 0.0126 memory: 9100 grad_norm: 0.9432 loss: 1.6648 loss_heatmap: 0.6932 layer_-1_loss_cls: 0.1074 layer_-1_loss_bbox: 0.8642 matched_ious: 0.5294 2023/03/22 14:17:32 - mmengine - INFO - Epoch(train) [8][1450/3862] lr: 9.8652e-04 eta: 14:28:12 time: 1.0636 data_time: 0.0121 memory: 9364 grad_norm: 0.9403 loss: 1.6695 loss_heatmap: 0.6920 layer_-1_loss_cls: 0.1078 layer_-1_loss_bbox: 0.8697 matched_ious: 0.5543 2023/03/22 14:18:25 - mmengine - INFO - Epoch(train) [8][1500/3862] lr: 9.8707e-04 eta: 14:27:18 time: 1.0610 data_time: 0.0127 memory: 9320 grad_norm: 0.9378 loss: 1.7096 loss_heatmap: 0.6982 layer_-1_loss_cls: 0.1079 layer_-1_loss_bbox: 0.9035 matched_ious: 0.5330 2023/03/22 14:19:18 - mmengine - INFO - Epoch(train) [8][1550/3862] lr: 9.8761e-04 eta: 14:26:24 time: 1.0634 data_time: 0.0124 memory: 9259 grad_norm: 0.9632 loss: 1.6509 loss_heatmap: 0.6897 layer_-1_loss_cls: 0.1076 layer_-1_loss_bbox: 0.8536 matched_ious: 0.4930 2023/03/22 14:20:12 - mmengine - INFO - Epoch(train) [8][1600/3862] lr: 9.8814e-04 eta: 14:25:31 time: 1.0774 data_time: 0.0125 memory: 9176 grad_norm: 0.9628 loss: 1.7022 loss_heatmap: 0.6914 layer_-1_loss_cls: 0.1066 layer_-1_loss_bbox: 0.9041 matched_ious: 0.4758 2023/03/22 14:21:06 - mmengine - INFO - Epoch(train) [8][1650/3862] lr: 9.8865e-04 eta: 14:24:38 time: 1.0734 data_time: 0.0126 memory: 9207 grad_norm: 1.0455 loss: 1.7716 loss_heatmap: 0.7202 layer_-1_loss_cls: 0.1097 layer_-1_loss_bbox: 0.9417 matched_ious: 0.4916 2023/03/22 14:22:00 - mmengine - INFO - Epoch(train) [8][1700/3862] lr: 9.8916e-04 eta: 14:23:45 time: 1.0727 data_time: 0.0128 memory: 9279 grad_norm: 1.0715 loss: 1.7039 loss_heatmap: 0.6899 layer_-1_loss_cls: 0.1070 layer_-1_loss_bbox: 0.9070 matched_ious: 0.4807 2023/03/22 14:22:53 - mmengine - INFO - Epoch(train) [8][1750/3862] lr: 9.8965e-04 eta: 14:22:52 time: 1.0723 data_time: 0.0123 memory: 9228 grad_norm: 0.9036 loss: 1.7390 loss_heatmap: 0.6927 layer_-1_loss_cls: 0.1080 layer_-1_loss_bbox: 0.9383 matched_ious: 0.5123 2023/03/22 14:23:46 - mmengine - INFO - Epoch(train) [8][1800/3862] lr: 9.9014e-04 eta: 14:21:58 time: 1.0574 data_time: 0.0123 memory: 9142 grad_norm: 0.8759 loss: 1.6805 loss_heatmap: 0.6991 layer_-1_loss_cls: 0.1069 layer_-1_loss_bbox: 0.8744 matched_ious: 0.4674 2023/03/22 14:24:39 - mmengine - INFO - Epoch(train) [8][1850/3862] lr: 9.9061e-04 eta: 14:21:04 time: 1.0648 data_time: 0.0121 memory: 9035 grad_norm: 1.0210 loss: 1.7341 loss_heatmap: 0.7044 layer_-1_loss_cls: 0.1087 layer_-1_loss_bbox: 0.9209 matched_ious: 0.5174 2023/03/22 14:25:33 - mmengine - INFO - Epoch(train) [8][1900/3862] lr: 9.9107e-04 eta: 14:20:10 time: 1.0649 data_time: 0.0125 memory: 9094 grad_norm: 0.9511 loss: 1.6636 loss_heatmap: 0.6812 layer_-1_loss_cls: 0.1051 layer_-1_loss_bbox: 0.8773 matched_ious: 0.5420 2023/03/22 14:26:26 - mmengine - INFO - Epoch(train) [8][1950/3862] lr: 9.9151e-04 eta: 14:19:17 time: 1.0738 data_time: 0.0129 memory: 9224 grad_norm: 1.0350 loss: 1.7449 loss_heatmap: 0.7009 layer_-1_loss_cls: 0.1077 layer_-1_loss_bbox: 0.9363 matched_ious: 0.4990 2023/03/22 14:26:43 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 14:27:20 - mmengine - INFO - Epoch(train) [8][2000/3862] lr: 9.9195e-04 eta: 14:18:24 time: 1.0632 data_time: 0.0130 memory: 9423 grad_norm: 0.9338 loss: 1.7049 loss_heatmap: 0.6950 layer_-1_loss_cls: 0.1076 layer_-1_loss_bbox: 0.9022 matched_ious: 0.4397 2023/03/22 14:28:12 - mmengine - INFO - Epoch(train) [8][2050/3862] lr: 9.9237e-04 eta: 14:17:29 time: 1.0591 data_time: 0.0128 memory: 9291 grad_norm: 0.8856 loss: 1.6678 loss_heatmap: 0.6872 layer_-1_loss_cls: 0.1042 layer_-1_loss_bbox: 0.8764 matched_ious: 0.5391 2023/03/22 14:29:07 - mmengine - INFO - Epoch(train) [8][2100/3862] lr: 9.9279e-04 eta: 14:16:37 time: 1.0840 data_time: 0.0129 memory: 9098 grad_norm: 0.9779 loss: 1.7398 loss_heatmap: 0.7029 layer_-1_loss_cls: 0.1095 layer_-1_loss_bbox: 0.9274 matched_ious: 0.4736 2023/03/22 14:30:00 - mmengine - INFO - Epoch(train) [8][2150/3862] lr: 9.9319e-04 eta: 14:15:44 time: 1.0676 data_time: 0.0126 memory: 9089 grad_norm: 1.0445 loss: 1.6980 loss_heatmap: 0.6968 layer_-1_loss_cls: 0.1062 layer_-1_loss_bbox: 0.8950 matched_ious: 0.4802 2023/03/22 14:30:54 - mmengine - INFO - Epoch(train) [8][2200/3862] lr: 9.9358e-04 eta: 14:14:51 time: 1.0730 data_time: 0.0126 memory: 9241 grad_norm: 0.9901 loss: 1.6695 loss_heatmap: 0.6850 layer_-1_loss_cls: 0.1060 layer_-1_loss_bbox: 0.8784 matched_ious: 0.4894 2023/03/22 14:31:47 - mmengine - INFO - Epoch(train) [8][2250/3862] lr: 9.9396e-04 eta: 14:13:57 time: 1.0609 data_time: 0.0127 memory: 9278 grad_norm: 0.9435 loss: 1.6663 loss_heatmap: 0.6886 layer_-1_loss_cls: 0.1057 layer_-1_loss_bbox: 0.8720 matched_ious: 0.4733 2023/03/22 14:32:40 - mmengine - INFO - Epoch(train) [8][2300/3862] lr: 9.9433e-04 eta: 14:13:03 time: 1.0705 data_time: 0.0125 memory: 9351 grad_norm: 0.9071 loss: 1.7155 loss_heatmap: 0.6962 layer_-1_loss_cls: 0.1062 layer_-1_loss_bbox: 0.9130 matched_ious: 0.4622 2023/03/22 14:33:34 - mmengine - INFO - Epoch(train) [8][2350/3862] lr: 9.9469e-04 eta: 14:12:10 time: 1.0684 data_time: 0.0122 memory: 9181 grad_norm: 0.9604 loss: 1.7289 loss_heatmap: 0.7092 layer_-1_loss_cls: 0.1102 layer_-1_loss_bbox: 0.9095 matched_ious: 0.5401 2023/03/22 14:34:27 - mmengine - INFO - Epoch(train) [8][2400/3862] lr: 9.9503e-04 eta: 14:11:17 time: 1.0755 data_time: 0.0128 memory: 9077 grad_norm: 0.9487 loss: 1.6928 loss_heatmap: 0.6986 layer_-1_loss_cls: 0.1082 layer_-1_loss_bbox: 0.8860 matched_ious: 0.5036 2023/03/22 14:35:21 - mmengine - INFO - Epoch(train) [8][2450/3862] lr: 9.9536e-04 eta: 14:10:24 time: 1.0664 data_time: 0.0124 memory: 9216 grad_norm: 0.9432 loss: 1.6615 loss_heatmap: 0.6915 layer_-1_loss_cls: 0.1072 layer_-1_loss_bbox: 0.8628 matched_ious: 0.5070 2023/03/22 14:36:14 - mmengine - INFO - Epoch(train) [8][2500/3862] lr: 9.9569e-04 eta: 14:09:30 time: 1.0620 data_time: 0.0125 memory: 9045 grad_norm: 1.0112 loss: 1.7098 loss_heatmap: 0.7061 layer_-1_loss_cls: 0.1081 layer_-1_loss_bbox: 0.8956 matched_ious: 0.5051 2023/03/22 14:37:07 - mmengine - INFO - Epoch(train) [8][2550/3862] lr: 9.9600e-04 eta: 14:08:36 time: 1.0676 data_time: 0.0128 memory: 9006 grad_norm: 0.8919 loss: 1.6258 loss_heatmap: 0.6838 layer_-1_loss_cls: 0.1060 layer_-1_loss_bbox: 0.8360 matched_ious: 0.5481 2023/03/22 14:38:01 - mmengine - INFO - Epoch(train) [8][2600/3862] lr: 9.9629e-04 eta: 14:07:42 time: 1.0643 data_time: 0.0129 memory: 8940 grad_norm: 0.9399 loss: 1.6796 loss_heatmap: 0.6889 layer_-1_loss_cls: 0.1048 layer_-1_loss_bbox: 0.8859 matched_ious: 0.5281 2023/03/22 14:38:54 - mmengine - INFO - Epoch(train) [8][2650/3862] lr: 9.9658e-04 eta: 14:06:49 time: 1.0686 data_time: 0.0124 memory: 9426 grad_norm: 0.9227 loss: 1.6677 loss_heatmap: 0.6992 layer_-1_loss_cls: 0.1079 layer_-1_loss_bbox: 0.8605 matched_ious: 0.5095 2023/03/22 14:39:47 - mmengine - INFO - Epoch(train) [8][2700/3862] lr: 9.9686e-04 eta: 14:05:55 time: 1.0591 data_time: 0.0124 memory: 9149 grad_norm: 0.8923 loss: 1.6630 loss_heatmap: 0.6801 layer_-1_loss_cls: 0.1047 layer_-1_loss_bbox: 0.8781 matched_ious: 0.5058 2023/03/22 14:40:40 - mmengine - INFO - Epoch(train) [8][2750/3862] lr: 9.9712e-04 eta: 14:05:01 time: 1.0629 data_time: 0.0124 memory: 9193 grad_norm: 0.8769 loss: 1.6387 loss_heatmap: 0.6780 layer_-1_loss_cls: 0.1034 layer_-1_loss_bbox: 0.8573 matched_ious: 0.5178 2023/03/22 14:41:34 - mmengine - INFO - Epoch(train) [8][2800/3862] lr: 9.9737e-04 eta: 14:04:08 time: 1.0726 data_time: 0.0127 memory: 9283 grad_norm: 0.9060 loss: 1.7421 loss_heatmap: 0.6825 layer_-1_loss_cls: 0.1030 layer_-1_loss_bbox: 0.9566 matched_ious: 0.5050 2023/03/22 14:42:27 - mmengine - INFO - Epoch(train) [8][2850/3862] lr: 9.9761e-04 eta: 14:03:15 time: 1.0725 data_time: 0.0134 memory: 9151 grad_norm: 0.8832 loss: 1.7025 loss_heatmap: 0.7138 layer_-1_loss_cls: 0.1067 layer_-1_loss_bbox: 0.8820 matched_ious: 0.4639 2023/03/22 14:43:21 - mmengine - INFO - Epoch(train) [8][2900/3862] lr: 9.9784e-04 eta: 14:02:21 time: 1.0658 data_time: 0.0127 memory: 9149 grad_norm: 0.9953 loss: 1.7744 loss_heatmap: 0.7080 layer_-1_loss_cls: 0.1067 layer_-1_loss_bbox: 0.9597 matched_ious: 0.4715 2023/03/22 14:44:14 - mmengine - INFO - Epoch(train) [8][2950/3862] lr: 9.9806e-04 eta: 14:01:28 time: 1.0696 data_time: 0.0120 memory: 9227 grad_norm: 0.9503 loss: 1.7022 loss_heatmap: 0.7028 layer_-1_loss_cls: 0.1079 layer_-1_loss_bbox: 0.8915 matched_ious: 0.5054 2023/03/22 14:44:31 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 14:45:08 - mmengine - INFO - Epoch(train) [8][3000/3862] lr: 9.9827e-04 eta: 14:00:34 time: 1.0685 data_time: 0.0119 memory: 9180 grad_norm: 0.8083 loss: 1.6511 loss_heatmap: 0.6859 layer_-1_loss_cls: 0.1057 layer_-1_loss_bbox: 0.8595 matched_ious: 0.5042 2023/03/22 14:46:01 - mmengine - INFO - Epoch(train) [8][3050/3862] lr: 9.9846e-04 eta: 13:59:41 time: 1.0669 data_time: 0.0122 memory: 9155 grad_norm: 0.8884 loss: 1.6753 loss_heatmap: 0.6878 layer_-1_loss_cls: 0.1056 layer_-1_loss_bbox: 0.8820 matched_ious: 0.5115 2023/03/22 14:46:55 - mmengine - INFO - Epoch(train) [8][3100/3862] lr: 9.9865e-04 eta: 13:58:49 time: 1.0817 data_time: 0.0121 memory: 9229 grad_norm: 0.8925 loss: 1.7015 loss_heatmap: 0.6823 layer_-1_loss_cls: 0.1044 layer_-1_loss_bbox: 0.9148 matched_ious: 0.5020 2023/03/22 14:47:48 - mmengine - INFO - Epoch(train) [8][3150/3862] lr: 9.9882e-04 eta: 13:57:55 time: 1.0677 data_time: 0.0121 memory: 9320 grad_norm: 0.9692 loss: 1.7400 loss_heatmap: 0.6848 layer_-1_loss_cls: 0.1040 layer_-1_loss_bbox: 0.9512 matched_ious: 0.5181 2023/03/22 14:48:42 - mmengine - INFO - Epoch(train) [8][3200/3862] lr: 9.9898e-04 eta: 13:57:02 time: 1.0700 data_time: 0.0119 memory: 9082 grad_norm: 0.9448 loss: 1.6375 loss_heatmap: 0.6751 layer_-1_loss_cls: 0.1028 layer_-1_loss_bbox: 0.8596 matched_ious: 0.5148 2023/03/22 14:49:36 - mmengine - INFO - Epoch(train) [8][3250/3862] lr: 9.9913e-04 eta: 13:56:09 time: 1.0771 data_time: 0.0119 memory: 9542 grad_norm: 0.8639 loss: 1.7479 loss_heatmap: 0.6962 layer_-1_loss_cls: 0.1077 layer_-1_loss_bbox: 0.9439 matched_ious: 0.4716 2023/03/22 14:50:30 - mmengine - INFO - Epoch(train) [8][3300/3862] lr: 9.9926e-04 eta: 13:55:16 time: 1.0793 data_time: 0.0118 memory: 9383 grad_norm: 0.8293 loss: 1.7189 loss_heatmap: 0.7003 layer_-1_loss_cls: 0.1104 layer_-1_loss_bbox: 0.9082 matched_ious: 0.5322 2023/03/22 14:51:23 - mmengine - INFO - Epoch(train) [8][3350/3862] lr: 9.9939e-04 eta: 13:54:23 time: 1.0627 data_time: 0.0114 memory: 9045 grad_norm: 0.9080 loss: 1.7303 loss_heatmap: 0.7069 layer_-1_loss_cls: 0.1064 layer_-1_loss_bbox: 0.9171 matched_ious: 0.5021 2023/03/22 14:52:16 - mmengine - INFO - Epoch(train) [8][3400/3862] lr: 9.9950e-04 eta: 13:53:28 time: 1.0582 data_time: 0.0113 memory: 9237 grad_norm: 0.9270 loss: 1.6737 loss_heatmap: 0.6867 layer_-1_loss_cls: 0.1040 layer_-1_loss_bbox: 0.8830 matched_ious: 0.5532 2023/03/22 14:53:09 - mmengine - INFO - Epoch(train) [8][3450/3862] lr: 9.9960e-04 eta: 13:52:35 time: 1.0655 data_time: 0.0121 memory: 8977 grad_norm: 0.9280 loss: 1.6855 loss_heatmap: 0.6950 layer_-1_loss_cls: 0.1035 layer_-1_loss_bbox: 0.8870 matched_ious: 0.4872 2023/03/22 14:54:02 - mmengine - INFO - Epoch(train) [8][3500/3862] lr: 9.9969e-04 eta: 13:51:41 time: 1.0655 data_time: 0.0117 memory: 9206 grad_norm: 0.8740 loss: 1.7253 loss_heatmap: 0.7004 layer_-1_loss_cls: 0.1068 layer_-1_loss_bbox: 0.9180 matched_ious: 0.4679 2023/03/22 14:54:56 - mmengine - INFO - Epoch(train) [8][3550/3862] lr: 9.9977e-04 eta: 13:50:48 time: 1.0712 data_time: 0.0119 memory: 9189 grad_norm: 0.8805 loss: 1.7189 loss_heatmap: 0.6939 layer_-1_loss_cls: 0.1062 layer_-1_loss_bbox: 0.9188 matched_ious: 0.4780 2023/03/22 14:55:50 - mmengine - INFO - Epoch(train) [8][3600/3862] lr: 9.9984e-04 eta: 13:49:55 time: 1.0781 data_time: 0.0118 memory: 8976 grad_norm: 0.8581 loss: 1.5947 loss_heatmap: 0.6606 layer_-1_loss_cls: 0.1000 layer_-1_loss_bbox: 0.8341 matched_ious: 0.5059 2023/03/22 14:56:43 - mmengine - INFO - Epoch(train) [8][3650/3862] lr: 9.9989e-04 eta: 13:49:02 time: 1.0654 data_time: 0.0115 memory: 9258 grad_norm: 0.9371 loss: 1.6246 loss_heatmap: 0.6744 layer_-1_loss_cls: 0.1047 layer_-1_loss_bbox: 0.8455 matched_ious: 0.5151 2023/03/22 14:57:37 - mmengine - INFO - Epoch(train) [8][3700/3862] lr: 9.9994e-04 eta: 13:48:08 time: 1.0704 data_time: 0.0119 memory: 9400 grad_norm: 0.8334 loss: 1.7170 loss_heatmap: 0.6987 layer_-1_loss_cls: 0.1058 layer_-1_loss_bbox: 0.9125 matched_ious: 0.4864 2023/03/22 14:58:30 - mmengine - INFO - Epoch(train) [8][3750/3862] lr: 9.9997e-04 eta: 13:47:14 time: 1.0635 data_time: 0.0118 memory: 9176 grad_norm: 0.8733 loss: 1.7034 loss_heatmap: 0.7177 layer_-1_loss_cls: 0.1095 layer_-1_loss_bbox: 0.8763 matched_ious: 0.5137 2023/03/22 14:59:23 - mmengine - INFO - Epoch(train) [8][3800/3862] lr: 9.9999e-04 eta: 13:46:20 time: 1.0579 data_time: 0.0120 memory: 9289 grad_norm: 0.8977 loss: 1.6958 loss_heatmap: 0.6952 layer_-1_loss_cls: 0.1056 layer_-1_loss_bbox: 0.8950 matched_ious: 0.5010 2023/03/22 15:00:16 - mmengine - INFO - Epoch(train) [8][3850/3862] lr: 1.0000e-03 eta: 13:45:27 time: 1.0678 data_time: 0.0118 memory: 8850 grad_norm: 0.8642 loss: 1.6748 loss_heatmap: 0.6836 layer_-1_loss_cls: 0.1025 layer_-1_loss_bbox: 0.8887 matched_ious: 0.5739 2023/03/22 15:00:29 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 15:01:28 - mmengine - INFO - Epoch(train) [9][ 50/3862] lr: 1.0000e-03 eta: 13:44:30 time: 1.1869 data_time: 0.1017 memory: 9007 grad_norm: 0.7996 loss: 1.6676 loss_heatmap: 0.6803 layer_-1_loss_cls: 0.1019 layer_-1_loss_bbox: 0.8855 matched_ious: 0.5338 2023/03/22 15:02:22 - mmengine - INFO - Epoch(train) [9][ 100/3862] lr: 9.9999e-04 eta: 13:43:37 time: 1.0766 data_time: 0.0120 memory: 9284 grad_norm: 0.8418 loss: 1.6802 loss_heatmap: 0.6843 layer_-1_loss_cls: 0.1041 layer_-1_loss_bbox: 0.8919 matched_ious: 0.4890 2023/03/22 15:02:26 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 15:03:16 - mmengine - INFO - Epoch(train) [9][ 150/3862] lr: 9.9997e-04 eta: 13:42:44 time: 1.0808 data_time: 0.0120 memory: 9239 grad_norm: 0.8712 loss: 1.6588 loss_heatmap: 0.6832 layer_-1_loss_cls: 0.1020 layer_-1_loss_bbox: 0.8737 matched_ious: 0.5029 2023/03/22 15:04:10 - mmengine - INFO - Epoch(train) [9][ 200/3862] lr: 9.9995e-04 eta: 13:41:51 time: 1.0687 data_time: 0.0113 memory: 9355 grad_norm: 0.9147 loss: 1.6309 loss_heatmap: 0.6797 layer_-1_loss_cls: 0.1065 layer_-1_loss_bbox: 0.8448 matched_ious: 0.4584 2023/03/22 15:05:04 - mmengine - INFO - Epoch(train) [9][ 250/3862] lr: 9.9993e-04 eta: 13:40:58 time: 1.0794 data_time: 0.0117 memory: 8962 grad_norm: 0.9637 loss: 1.7549 loss_heatmap: 0.7110 layer_-1_loss_cls: 0.1085 layer_-1_loss_bbox: 0.9354 matched_ious: 0.5096 2023/03/22 15:05:57 - mmengine - INFO - Epoch(train) [9][ 300/3862] lr: 9.9990e-04 eta: 13:40:04 time: 1.0638 data_time: 0.0119 memory: 9281 grad_norm: 0.8674 loss: 1.6920 loss_heatmap: 0.7002 layer_-1_loss_cls: 0.1057 layer_-1_loss_bbox: 0.8860 matched_ious: 0.5239 2023/03/22 15:06:50 - mmengine - INFO - Epoch(train) [9][ 350/3862] lr: 9.9986e-04 eta: 13:39:10 time: 1.0612 data_time: 0.0118 memory: 9400 grad_norm: 0.8867 loss: 1.6418 loss_heatmap: 0.6653 layer_-1_loss_cls: 0.1031 layer_-1_loss_bbox: 0.8734 matched_ious: 0.5059 2023/03/22 15:07:43 - mmengine - INFO - Epoch(train) [9][ 400/3862] lr: 9.9982e-04 eta: 13:38:17 time: 1.0656 data_time: 0.0117 memory: 9181 grad_norm: 0.8161 loss: 1.7010 loss_heatmap: 0.6987 layer_-1_loss_cls: 0.1074 layer_-1_loss_bbox: 0.8949 matched_ious: 0.5018 2023/03/22 15:08:37 - mmengine - INFO - Epoch(train) [9][ 450/3862] lr: 9.9977e-04 eta: 13:37:24 time: 1.0735 data_time: 0.0114 memory: 9259 grad_norm: 0.8850 loss: 1.7095 loss_heatmap: 0.6975 layer_-1_loss_cls: 0.1059 layer_-1_loss_bbox: 0.9060 matched_ious: 0.5205 2023/03/22 15:09:30 - mmengine - INFO - Epoch(train) [9][ 500/3862] lr: 9.9971e-04 eta: 13:36:30 time: 1.0660 data_time: 0.0118 memory: 9129 grad_norm: 0.8621 loss: 1.7701 loss_heatmap: 0.7137 layer_-1_loss_cls: 0.1088 layer_-1_loss_bbox: 0.9476 matched_ious: 0.5168 2023/03/22 15:10:25 - mmengine - INFO - Epoch(train) [9][ 550/3862] lr: 9.9965e-04 eta: 13:35:39 time: 1.1018 data_time: 0.0116 memory: 9014 grad_norm: 0.8442 loss: 1.6295 loss_heatmap: 0.6739 layer_-1_loss_cls: 0.1037 layer_-1_loss_bbox: 0.8519 matched_ious: 0.5428 2023/03/22 15:11:19 - mmengine - INFO - Epoch(train) [9][ 600/3862] lr: 9.9959e-04 eta: 13:34:46 time: 1.0697 data_time: 0.0117 memory: 9435 grad_norm: 0.8734 loss: 1.6732 loss_heatmap: 0.6868 layer_-1_loss_cls: 0.1050 layer_-1_loss_bbox: 0.8814 matched_ious: 0.5170 2023/03/22 15:12:13 - mmengine - INFO - Epoch(train) [9][ 650/3862] lr: 9.9952e-04 eta: 13:33:53 time: 1.0785 data_time: 0.0116 memory: 9214 grad_norm: 0.8333 loss: 1.7015 loss_heatmap: 0.6833 layer_-1_loss_cls: 0.1039 layer_-1_loss_bbox: 0.9143 matched_ious: 0.4845 2023/03/22 15:13:06 - mmengine - INFO - Epoch(train) [9][ 700/3862] lr: 9.9944e-04 eta: 13:32:59 time: 1.0682 data_time: 0.0120 memory: 9138 grad_norm: 0.9734 loss: 1.6438 loss_heatmap: 0.6715 layer_-1_loss_cls: 0.1046 layer_-1_loss_bbox: 0.8677 matched_ious: 0.4883 2023/03/22 15:14:00 - mmengine - INFO - Epoch(train) [9][ 750/3862] lr: 9.9936e-04 eta: 13:32:06 time: 1.0729 data_time: 0.0120 memory: 9134 grad_norm: 0.7714 loss: 1.6659 loss_heatmap: 0.6649 layer_-1_loss_cls: 0.1014 layer_-1_loss_bbox: 0.8996 matched_ious: 0.4240 2023/03/22 15:14:53 - mmengine - INFO - Epoch(train) [9][ 800/3862] lr: 9.9927e-04 eta: 13:31:13 time: 1.0669 data_time: 0.0117 memory: 9040 grad_norm: 0.8948 loss: 1.5518 loss_heatmap: 0.6417 layer_-1_loss_cls: 0.0966 layer_-1_loss_bbox: 0.8135 matched_ious: 0.5246 2023/03/22 15:15:46 - mmengine - INFO - Epoch(train) [9][ 850/3862] lr: 9.9917e-04 eta: 13:30:19 time: 1.0671 data_time: 0.0117 memory: 8995 grad_norm: 0.8029 loss: 1.6418 loss_heatmap: 0.6773 layer_-1_loss_cls: 0.1024 layer_-1_loss_bbox: 0.8621 matched_ious: 0.5312 2023/03/22 15:16:39 - mmengine - INFO - Epoch(train) [9][ 900/3862] lr: 9.9907e-04 eta: 13:29:25 time: 1.0615 data_time: 0.0119 memory: 9191 grad_norm: 0.8138 loss: 1.6844 loss_heatmap: 0.6953 layer_-1_loss_cls: 0.1072 layer_-1_loss_bbox: 0.8819 matched_ious: 0.4961 2023/03/22 15:17:33 - mmengine - INFO - Epoch(train) [9][ 950/3862] lr: 9.9897e-04 eta: 13:28:32 time: 1.0735 data_time: 0.0114 memory: 9349 grad_norm: 0.8373 loss: 1.6499 loss_heatmap: 0.6806 layer_-1_loss_cls: 0.1047 layer_-1_loss_bbox: 0.8646 matched_ious: 0.5027 2023/03/22 15:18:27 - mmengine - INFO - Epoch(train) [9][1000/3862] lr: 9.9885e-04 eta: 13:27:39 time: 1.0673 data_time: 0.0120 memory: 9038 grad_norm: 0.9274 loss: 1.6095 loss_heatmap: 0.6607 layer_-1_loss_cls: 0.1038 layer_-1_loss_bbox: 0.8450 matched_ious: 0.4553 2023/03/22 15:19:20 - mmengine - INFO - Epoch(train) [9][1050/3862] lr: 9.9874e-04 eta: 13:26:45 time: 1.0698 data_time: 0.0118 memory: 9025 grad_norm: 0.8032 loss: 1.6282 loss_heatmap: 0.6799 layer_-1_loss_cls: 0.1044 layer_-1_loss_bbox: 0.8440 matched_ious: 0.4929 2023/03/22 15:20:14 - mmengine - INFO - Epoch(train) [9][1100/3862] lr: 9.9861e-04 eta: 13:25:52 time: 1.0712 data_time: 0.0117 memory: 9212 grad_norm: 0.8523 loss: 1.7096 loss_heatmap: 0.6880 layer_-1_loss_cls: 0.1066 layer_-1_loss_bbox: 0.9150 matched_ious: 0.4746 2023/03/22 15:20:18 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 15:21:07 - mmengine - INFO - Epoch(train) [9][1150/3862] lr: 9.9848e-04 eta: 13:24:59 time: 1.0701 data_time: 0.0120 memory: 9330 grad_norm: 0.7994 loss: 1.6609 loss_heatmap: 0.6765 layer_-1_loss_cls: 0.1013 layer_-1_loss_bbox: 0.8831 matched_ious: 0.5310 2023/03/22 15:22:00 - mmengine - INFO - Epoch(train) [9][1200/3862] lr: 9.9835e-04 eta: 13:24:05 time: 1.0658 data_time: 0.0120 memory: 9369 grad_norm: 0.8600 loss: 1.5642 loss_heatmap: 0.6501 layer_-1_loss_cls: 0.0990 layer_-1_loss_bbox: 0.8151 matched_ious: 0.4584 2023/03/22 15:22:54 - mmengine - INFO - Epoch(train) [9][1250/3862] lr: 9.9821e-04 eta: 13:23:12 time: 1.0752 data_time: 0.0118 memory: 9282 grad_norm: 0.8723 loss: 1.5965 loss_heatmap: 0.6724 layer_-1_loss_cls: 0.1056 layer_-1_loss_bbox: 0.8184 matched_ious: 0.5315 2023/03/22 15:23:47 - mmengine - INFO - Epoch(train) [9][1300/3862] lr: 9.9806e-04 eta: 13:22:18 time: 1.0669 data_time: 0.0117 memory: 9175 grad_norm: 0.8882 loss: 1.6184 loss_heatmap: 0.6663 layer_-1_loss_cls: 0.1010 layer_-1_loss_bbox: 0.8511 matched_ious: 0.5033 2023/03/22 15:24:41 - mmengine - INFO - Epoch(train) [9][1350/3862] lr: 9.9791e-04 eta: 13:21:25 time: 1.0719 data_time: 0.0118 memory: 9216 grad_norm: 0.7978 loss: 1.6071 loss_heatmap: 0.6752 layer_-1_loss_cls: 0.1047 layer_-1_loss_bbox: 0.8273 matched_ious: 0.5249 2023/03/22 15:25:34 - mmengine - INFO - Epoch(train) [9][1400/3862] lr: 9.9775e-04 eta: 13:20:31 time: 1.0596 data_time: 0.0116 memory: 9257 grad_norm: 0.9114 loss: 1.5850 loss_heatmap: 0.6686 layer_-1_loss_cls: 0.1024 layer_-1_loss_bbox: 0.8140 matched_ious: 0.5245 2023/03/22 15:26:28 - mmengine - INFO - Epoch(train) [9][1450/3862] lr: 9.9759e-04 eta: 13:19:38 time: 1.0712 data_time: 0.0118 memory: 9009 grad_norm: 0.8295 loss: 1.6701 loss_heatmap: 0.6743 layer_-1_loss_cls: 0.1036 layer_-1_loss_bbox: 0.8922 matched_ious: 0.5573 2023/03/22 15:27:21 - mmengine - INFO - Epoch(train) [9][1500/3862] lr: 9.9742e-04 eta: 13:18:44 time: 1.0684 data_time: 0.0117 memory: 9373 grad_norm: 0.7948 loss: 1.6786 loss_heatmap: 0.6943 layer_-1_loss_cls: 0.1048 layer_-1_loss_bbox: 0.8795 matched_ious: 0.5396 2023/03/22 15:28:15 - mmengine - INFO - Epoch(train) [9][1550/3862] lr: 9.9725e-04 eta: 13:17:52 time: 1.0771 data_time: 0.0117 memory: 9002 grad_norm: 0.8315 loss: 1.5960 loss_heatmap: 0.6632 layer_-1_loss_cls: 0.0999 layer_-1_loss_bbox: 0.8329 matched_ious: 0.4977 2023/03/22 15:29:08 - mmengine - INFO - Epoch(train) [9][1600/3862] lr: 9.9707e-04 eta: 13:16:58 time: 1.0682 data_time: 0.0117 memory: 9159 grad_norm: 0.8350 loss: 1.6898 loss_heatmap: 0.6939 layer_-1_loss_cls: 0.1045 layer_-1_loss_bbox: 0.8915 matched_ious: 0.5060 2023/03/22 15:30:02 - mmengine - INFO - Epoch(train) [9][1650/3862] lr: 9.9688e-04 eta: 13:16:06 time: 1.0824 data_time: 0.0117 memory: 9095 grad_norm: 0.8410 loss: 1.6052 loss_heatmap: 0.6646 layer_-1_loss_cls: 0.1011 layer_-1_loss_bbox: 0.8396 matched_ious: 0.4874 2023/03/22 15:30:56 - mmengine - INFO - Epoch(train) [9][1700/3862] lr: 9.9669e-04 eta: 13:15:13 time: 1.0785 data_time: 0.0117 memory: 9495 grad_norm: 0.7846 loss: 1.6978 loss_heatmap: 0.7006 layer_-1_loss_cls: 0.1069 layer_-1_loss_bbox: 0.8903 matched_ious: 0.5484 2023/03/22 15:31:50 - mmengine - INFO - Epoch(train) [9][1750/3862] lr: 9.9649e-04 eta: 13:14:20 time: 1.0796 data_time: 0.0118 memory: 8973 grad_norm: 0.8982 loss: 1.6316 loss_heatmap: 0.6605 layer_-1_loss_cls: 0.0982 layer_-1_loss_bbox: 0.8730 matched_ious: 0.5223 2023/03/22 15:32:44 - mmengine - INFO - Epoch(train) [9][1800/3862] lr: 9.9629e-04 eta: 13:13:27 time: 1.0695 data_time: 0.0117 memory: 9124 grad_norm: 0.9960 loss: 1.6134 loss_heatmap: 0.6584 layer_-1_loss_cls: 0.1046 layer_-1_loss_bbox: 0.8504 matched_ious: 0.5134 2023/03/22 15:33:37 - mmengine - INFO - Epoch(train) [9][1850/3862] lr: 9.9608e-04 eta: 13:12:33 time: 1.0636 data_time: 0.0119 memory: 9189 grad_norm: 0.8168 loss: 1.6325 loss_heatmap: 0.6901 layer_-1_loss_cls: 0.1044 layer_-1_loss_bbox: 0.8380 matched_ious: 0.5746 2023/03/22 15:34:30 - mmengine - INFO - Epoch(train) [9][1900/3862] lr: 9.9586e-04 eta: 13:11:39 time: 1.0676 data_time: 0.0118 memory: 9098 grad_norm: 0.8778 loss: 1.6437 loss_heatmap: 0.6658 layer_-1_loss_cls: 0.1011 layer_-1_loss_bbox: 0.8768 matched_ious: 0.5026 2023/03/22 15:35:24 - mmengine - INFO - Epoch(train) [9][1950/3862] lr: 9.9564e-04 eta: 13:10:46 time: 1.0732 data_time: 0.0118 memory: 9205 grad_norm: 0.9748 loss: 1.6497 loss_heatmap: 0.6732 layer_-1_loss_cls: 0.1014 layer_-1_loss_bbox: 0.8752 matched_ious: 0.4909 2023/03/22 15:36:17 - mmengine - INFO - Epoch(train) [9][2000/3862] lr: 9.9542e-04 eta: 13:09:53 time: 1.0637 data_time: 0.0115 memory: 9025 grad_norm: 0.8329 loss: 1.6755 loss_heatmap: 0.6869 layer_-1_loss_cls: 0.1038 layer_-1_loss_bbox: 0.8848 matched_ious: 0.4982 2023/03/22 15:37:11 - mmengine - INFO - Epoch(train) [9][2050/3862] lr: 9.9518e-04 eta: 13:09:00 time: 1.0743 data_time: 0.0118 memory: 9213 grad_norm: 0.8196 loss: 1.6138 loss_heatmap: 0.6645 layer_-1_loss_cls: 0.1006 layer_-1_loss_bbox: 0.8487 matched_ious: 0.5371 2023/03/22 15:38:15 - mmengine - INFO - Epoch(train) [9][2100/3862] lr: 9.9495e-04 eta: 13:08:20 time: 1.2819 data_time: 0.0118 memory: 8848 grad_norm: 0.8548 loss: 1.6738 loss_heatmap: 0.6812 layer_-1_loss_cls: 0.1038 layer_-1_loss_bbox: 0.8888 matched_ious: 0.5130 2023/03/22 15:38:19 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 15:39:08 - mmengine - INFO - Epoch(train) [9][2150/3862] lr: 9.9470e-04 eta: 13:07:27 time: 1.0648 data_time: 0.0116 memory: 9177 grad_norm: 0.7822 loss: 1.6297 loss_heatmap: 0.6709 layer_-1_loss_cls: 0.1038 layer_-1_loss_bbox: 0.8550 matched_ious: 0.4735 2023/03/22 15:40:02 - mmengine - INFO - Epoch(train) [9][2200/3862] lr: 9.9446e-04 eta: 13:06:33 time: 1.0712 data_time: 0.0116 memory: 9152 grad_norm: 0.8473 loss: 1.6293 loss_heatmap: 0.6648 layer_-1_loss_cls: 0.1004 layer_-1_loss_bbox: 0.8641 matched_ious: 0.5060 2023/03/22 15:40:55 - mmengine - INFO - Epoch(train) [9][2250/3862] lr: 9.9420e-04 eta: 13:05:40 time: 1.0718 data_time: 0.0118 memory: 9173 grad_norm: 0.7883 loss: 1.6326 loss_heatmap: 0.6755 layer_-1_loss_cls: 0.1029 layer_-1_loss_bbox: 0.8542 matched_ious: 0.5315 2023/03/22 15:41:49 - mmengine - INFO - Epoch(train) [9][2300/3862] lr: 9.9394e-04 eta: 13:04:47 time: 1.0732 data_time: 0.0114 memory: 9324 grad_norm: 0.8320 loss: 1.6899 loss_heatmap: 0.6948 layer_-1_loss_cls: 0.1049 layer_-1_loss_bbox: 0.8902 matched_ious: 0.5121 2023/03/22 15:42:43 - mmengine - INFO - Epoch(train) [9][2350/3862] lr: 9.9367e-04 eta: 13:03:53 time: 1.0680 data_time: 0.0114 memory: 9201 grad_norm: 0.8723 loss: 1.5927 loss_heatmap: 0.6588 layer_-1_loss_cls: 0.1017 layer_-1_loss_bbox: 0.8322 matched_ious: 0.5522 2023/03/22 15:43:36 - mmengine - INFO - Epoch(train) [9][2400/3862] lr: 9.9340e-04 eta: 13:03:00 time: 1.0734 data_time: 0.0116 memory: 9248 grad_norm: 0.7728 loss: 1.6333 loss_heatmap: 0.6757 layer_-1_loss_cls: 0.1040 layer_-1_loss_bbox: 0.8537 matched_ious: 0.4881 2023/03/22 15:44:30 - mmengine - INFO - Epoch(train) [9][2450/3862] lr: 9.9313e-04 eta: 13:02:07 time: 1.0698 data_time: 0.0117 memory: 9299 grad_norm: 0.7954 loss: 1.6394 loss_heatmap: 0.6718 layer_-1_loss_cls: 0.1026 layer_-1_loss_bbox: 0.8650 matched_ious: 0.5582 2023/03/22 15:45:23 - mmengine - INFO - Epoch(train) [9][2500/3862] lr: 9.9284e-04 eta: 13:01:13 time: 1.0615 data_time: 0.0116 memory: 9336 grad_norm: 0.8084 loss: 1.6401 loss_heatmap: 0.6657 layer_-1_loss_cls: 0.1011 layer_-1_loss_bbox: 0.8732 matched_ious: 0.5214 2023/03/22 15:46:16 - mmengine - INFO - Epoch(train) [9][2550/3862] lr: 9.9255e-04 eta: 13:00:20 time: 1.0718 data_time: 0.0119 memory: 9402 grad_norm: 0.8292 loss: 1.6236 loss_heatmap: 0.6699 layer_-1_loss_cls: 0.1037 layer_-1_loss_bbox: 0.8499 matched_ious: 0.5041 2023/03/22 15:47:10 - mmengine - INFO - Epoch(train) [9][2600/3862] lr: 9.9226e-04 eta: 12:59:26 time: 1.0753 data_time: 0.0117 memory: 9084 grad_norm: 0.7955 loss: 1.6621 loss_heatmap: 0.6909 layer_-1_loss_cls: 0.1044 layer_-1_loss_bbox: 0.8667 matched_ious: 0.5381 2023/03/22 15:48:03 - mmengine - INFO - Epoch(train) [9][2650/3862] lr: 9.9196e-04 eta: 12:58:33 time: 1.0632 data_time: 0.0117 memory: 9102 grad_norm: 0.8897 loss: 1.6163 loss_heatmap: 0.6605 layer_-1_loss_cls: 0.1002 layer_-1_loss_bbox: 0.8556 matched_ious: 0.5244 2023/03/22 15:48:57 - mmengine - INFO - Epoch(train) [9][2700/3862] lr: 9.9165e-04 eta: 12:57:39 time: 1.0663 data_time: 0.0119 memory: 9337 grad_norm: 0.7703 loss: 1.6170 loss_heatmap: 0.6677 layer_-1_loss_cls: 0.1034 layer_-1_loss_bbox: 0.8459 matched_ious: 0.5058 2023/03/22 15:49:50 - mmengine - INFO - Epoch(train) [9][2750/3862] lr: 9.9134e-04 eta: 12:56:45 time: 1.0659 data_time: 0.0121 memory: 9106 grad_norm: 0.8213 loss: 1.6128 loss_heatmap: 0.6583 layer_-1_loss_cls: 0.1008 layer_-1_loss_bbox: 0.8537 matched_ious: 0.5300 2023/03/22 15:50:44 - mmengine - INFO - Epoch(train) [9][2800/3862] lr: 9.9103e-04 eta: 12:55:53 time: 1.0868 data_time: 0.0117 memory: 9400 grad_norm: 0.8336 loss: 1.5528 loss_heatmap: 0.6617 layer_-1_loss_cls: 0.1040 layer_-1_loss_bbox: 0.7872 matched_ious: 0.5279 2023/03/22 15:51:38 - mmengine - INFO - Epoch(train) [9][2850/3862] lr: 9.9070e-04 eta: 12:55:00 time: 1.0805 data_time: 0.0117 memory: 8926 grad_norm: 0.8787 loss: 1.6695 loss_heatmap: 0.6942 layer_-1_loss_cls: 0.1044 layer_-1_loss_bbox: 0.8709 matched_ious: 0.5216 2023/03/22 15:52:31 - mmengine - INFO - Epoch(train) [9][2900/3862] lr: 9.9038e-04 eta: 12:54:06 time: 1.0605 data_time: 0.0118 memory: 9281 grad_norm: 0.8231 loss: 1.5709 loss_heatmap: 0.6533 layer_-1_loss_cls: 0.0991 layer_-1_loss_bbox: 0.8185 matched_ious: 0.4980 2023/03/22 15:53:25 - mmengine - INFO - Epoch(train) [9][2950/3862] lr: 9.9004e-04 eta: 12:53:13 time: 1.0740 data_time: 0.0117 memory: 9153 grad_norm: 0.7908 loss: 1.6577 loss_heatmap: 0.6734 layer_-1_loss_cls: 0.1013 layer_-1_loss_bbox: 0.8830 matched_ious: 0.4783 2023/03/22 15:54:18 - mmengine - INFO - Epoch(train) [9][3000/3862] lr: 9.8970e-04 eta: 12:52:19 time: 1.0633 data_time: 0.0115 memory: 9151 grad_norm: 0.8051 loss: 1.6621 loss_heatmap: 0.6697 layer_-1_loss_cls: 0.1013 layer_-1_loss_bbox: 0.8911 matched_ious: 0.5072 2023/03/22 15:55:11 - mmengine - INFO - Epoch(train) [9][3050/3862] lr: 9.8936e-04 eta: 12:51:25 time: 1.0591 data_time: 0.0118 memory: 9512 grad_norm: 0.8065 loss: 1.5648 loss_heatmap: 0.6572 layer_-1_loss_cls: 0.1011 layer_-1_loss_bbox: 0.8065 matched_ious: 0.5754 2023/03/22 15:56:04 - mmengine - INFO - Epoch(train) [9][3100/3862] lr: 9.8901e-04 eta: 12:50:31 time: 1.0566 data_time: 0.0116 memory: 9320 grad_norm: 0.7968 loss: 1.6108 loss_heatmap: 0.6402 layer_-1_loss_cls: 0.0970 layer_-1_loss_bbox: 0.8736 matched_ious: 0.5249 2023/03/22 15:56:08 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 15:56:58 - mmengine - INFO - Epoch(train) [9][3150/3862] lr: 9.8865e-04 eta: 12:49:38 time: 1.0745 data_time: 0.0116 memory: 9309 grad_norm: 0.8590 loss: 1.6332 loss_heatmap: 0.6660 layer_-1_loss_cls: 0.1005 layer_-1_loss_bbox: 0.8667 matched_ious: 0.5224 2023/03/22 15:57:51 - mmengine - INFO - Epoch(train) [9][3200/3862] lr: 9.8829e-04 eta: 12:48:44 time: 1.0657 data_time: 0.0116 memory: 9091 grad_norm: 0.8050 loss: 1.6287 loss_heatmap: 0.6746 layer_-1_loss_cls: 0.1038 layer_-1_loss_bbox: 0.8503 matched_ious: 0.5108 2023/03/22 15:58:44 - mmengine - INFO - Epoch(train) [9][3250/3862] lr: 9.8792e-04 eta: 12:47:50 time: 1.0510 data_time: 0.0118 memory: 8966 grad_norm: 0.8196 loss: 1.5853 loss_heatmap: 0.6511 layer_-1_loss_cls: 0.0993 layer_-1_loss_bbox: 0.8349 matched_ious: 0.5715 2023/03/22 15:59:37 - mmengine - INFO - Epoch(train) [9][3300/3862] lr: 9.8755e-04 eta: 12:46:56 time: 1.0681 data_time: 0.0117 memory: 9076 grad_norm: 0.7935 loss: 1.6437 loss_heatmap: 0.6704 layer_-1_loss_cls: 0.1025 layer_-1_loss_bbox: 0.8708 matched_ious: 0.5534 2023/03/22 16:00:30 - mmengine - INFO - Epoch(train) [9][3350/3862] lr: 9.8717e-04 eta: 12:46:03 time: 1.0689 data_time: 0.0114 memory: 9328 grad_norm: 0.8512 loss: 1.6737 loss_heatmap: 0.6768 layer_-1_loss_cls: 0.1033 layer_-1_loss_bbox: 0.8935 matched_ious: 0.4840 2023/03/22 16:01:23 - mmengine - INFO - Epoch(train) [9][3400/3862] lr: 9.8679e-04 eta: 12:45:08 time: 1.0580 data_time: 0.0117 memory: 9238 grad_norm: 0.8525 loss: 1.6550 loss_heatmap: 0.6868 layer_-1_loss_cls: 0.1058 layer_-1_loss_bbox: 0.8624 matched_ious: 0.5391 2023/03/22 16:02:17 - mmengine - INFO - Epoch(train) [9][3450/3862] lr: 9.8640e-04 eta: 12:44:15 time: 1.0743 data_time: 0.0119 memory: 9144 grad_norm: 0.8502 loss: 1.5988 loss_heatmap: 0.6477 layer_-1_loss_cls: 0.0967 layer_-1_loss_bbox: 0.8544 matched_ious: 0.4524 2023/03/22 16:03:10 - mmengine - INFO - Epoch(train) [9][3500/3862] lr: 9.8600e-04 eta: 12:43:22 time: 1.0665 data_time: 0.0117 memory: 9180 grad_norm: 0.7934 loss: 1.6399 loss_heatmap: 0.6733 layer_-1_loss_cls: 0.1010 layer_-1_loss_bbox: 0.8656 matched_ious: 0.5323 2023/03/22 16:04:04 - mmengine - INFO - Epoch(train) [9][3550/3862] lr: 9.8560e-04 eta: 12:42:28 time: 1.0702 data_time: 0.0115 memory: 9399 grad_norm: 0.7807 loss: 1.6428 loss_heatmap: 0.6824 layer_-1_loss_cls: 0.1027 layer_-1_loss_bbox: 0.8578 matched_ious: 0.5501 2023/03/22 16:04:57 - mmengine - INFO - Epoch(train) [9][3600/3862] lr: 9.8519e-04 eta: 12:41:35 time: 1.0664 data_time: 0.0119 memory: 9016 grad_norm: 0.7899 loss: 1.6484 loss_heatmap: 0.6624 layer_-1_loss_cls: 0.1017 layer_-1_loss_bbox: 0.8843 matched_ious: 0.5442 2023/03/22 16:05:50 - mmengine - INFO - Epoch(train) [9][3650/3862] lr: 9.8478e-04 eta: 12:40:41 time: 1.0596 data_time: 0.0112 memory: 9419 grad_norm: 0.8137 loss: 1.5409 loss_heatmap: 0.6531 layer_-1_loss_cls: 0.1016 layer_-1_loss_bbox: 0.7863 matched_ious: 0.5436 2023/03/22 16:06:44 - mmengine - INFO - Epoch(train) [9][3700/3862] lr: 9.8436e-04 eta: 12:39:47 time: 1.0675 data_time: 0.0116 memory: 9011 grad_norm: 0.9031 loss: 1.6067 loss_heatmap: 0.6610 layer_-1_loss_cls: 0.1021 layer_-1_loss_bbox: 0.8437 matched_ious: 0.5319 2023/03/22 16:07:37 - mmengine - INFO - Epoch(train) [9][3750/3862] lr: 9.8394e-04 eta: 12:38:54 time: 1.0688 data_time: 0.0116 memory: 9210 grad_norm: 0.9057 loss: 1.6670 loss_heatmap: 0.6860 layer_-1_loss_cls: 0.1044 layer_-1_loss_bbox: 0.8766 matched_ious: 0.5038 2023/03/22 16:08:31 - mmengine - INFO - Epoch(train) [9][3800/3862] lr: 9.8351e-04 eta: 12:38:00 time: 1.0696 data_time: 0.0118 memory: 9245 grad_norm: 1.1388 loss: 1.6138 loss_heatmap: 0.6754 layer_-1_loss_cls: 0.1027 layer_-1_loss_bbox: 0.8357 matched_ious: 0.5751 2023/03/22 16:09:24 - mmengine - INFO - Epoch(train) [9][3850/3862] lr: 9.8308e-04 eta: 12:37:07 time: 1.0686 data_time: 0.0117 memory: 9373 grad_norm: 0.7365 loss: 1.6077 loss_heatmap: 0.6558 layer_-1_loss_cls: 0.1000 layer_-1_loss_bbox: 0.8519 matched_ious: 0.5134 2023/03/22 16:09:37 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 16:10:32 - mmengine - INFO - Epoch(train) [10][ 50/3862] lr: 9.8253e-04 eta: 12:36:03 time: 1.1140 data_time: 0.0559 memory: 9294 grad_norm: 0.7837 loss: 1.5950 loss_heatmap: 0.6660 layer_-1_loss_cls: 0.0992 layer_-1_loss_bbox: 0.8299 matched_ious: 0.5294 2023/03/22 16:11:27 - mmengine - INFO - Epoch(train) [10][ 100/3862] lr: 9.8208e-04 eta: 12:35:11 time: 1.0859 data_time: 0.0115 memory: 9253 grad_norm: 0.7945 loss: 1.6095 loss_heatmap: 0.6582 layer_-1_loss_cls: 0.1015 layer_-1_loss_bbox: 0.8498 matched_ious: 0.5216 2023/03/22 16:12:21 - mmengine - INFO - Epoch(train) [10][ 150/3862] lr: 9.8163e-04 eta: 12:34:18 time: 1.0776 data_time: 0.0115 memory: 9046 grad_norm: 0.7857 loss: 1.6182 loss_heatmap: 0.6610 layer_-1_loss_cls: 0.1017 layer_-1_loss_bbox: 0.8554 matched_ious: 0.4907 2023/03/22 16:13:14 - mmengine - INFO - Epoch(train) [10][ 200/3862] lr: 9.8117e-04 eta: 12:33:24 time: 1.0601 data_time: 0.0118 memory: 9166 grad_norm: 0.7845 loss: 1.6077 loss_heatmap: 0.6558 layer_-1_loss_cls: 0.1014 layer_-1_loss_bbox: 0.8505 matched_ious: 0.5416 2023/03/22 16:13:58 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 16:14:07 - mmengine - INFO - Epoch(train) [10][ 250/3862] lr: 9.8071e-04 eta: 12:32:30 time: 1.0579 data_time: 0.0116 memory: 8934 grad_norm: 0.7443 loss: 1.5974 loss_heatmap: 0.6509 layer_-1_loss_cls: 0.1000 layer_-1_loss_bbox: 0.8466 matched_ious: 0.5287 2023/03/22 16:15:00 - mmengine - INFO - Epoch(train) [10][ 300/3862] lr: 9.8024e-04 eta: 12:31:36 time: 1.0678 data_time: 0.0118 memory: 9323 grad_norm: 0.7489 loss: 1.6066 loss_heatmap: 0.6519 layer_-1_loss_cls: 0.1017 layer_-1_loss_bbox: 0.8530 matched_ious: 0.5356 2023/03/22 16:15:54 - mmengine - INFO - Epoch(train) [10][ 350/3862] lr: 9.7977e-04 eta: 12:30:43 time: 1.0752 data_time: 0.0115 memory: 9234 grad_norm: 0.7815 loss: 1.6102 loss_heatmap: 0.6594 layer_-1_loss_cls: 0.0995 layer_-1_loss_bbox: 0.8513 matched_ious: 0.4901 2023/03/22 16:16:47 - mmengine - INFO - Epoch(train) [10][ 400/3862] lr: 9.7929e-04 eta: 12:29:49 time: 1.0653 data_time: 0.0115 memory: 9065 grad_norm: 0.7051 loss: 1.5925 loss_heatmap: 0.6519 layer_-1_loss_cls: 0.0990 layer_-1_loss_bbox: 0.8415 matched_ious: 0.5430 2023/03/22 16:17:40 - mmengine - INFO - Epoch(train) [10][ 450/3862] lr: 9.7880e-04 eta: 12:28:56 time: 1.0634 data_time: 0.0118 memory: 9199 grad_norm: 0.8201 loss: 1.5775 loss_heatmap: 0.6692 layer_-1_loss_cls: 0.1027 layer_-1_loss_bbox: 0.8056 matched_ious: 0.5144 2023/03/22 16:18:34 - mmengine - INFO - Epoch(train) [10][ 500/3862] lr: 9.7831e-04 eta: 12:28:02 time: 1.0685 data_time: 0.0116 memory: 9123 grad_norm: 0.7975 loss: 1.6292 loss_heatmap: 0.6524 layer_-1_loss_cls: 0.0991 layer_-1_loss_bbox: 0.8777 matched_ious: 0.5314 2023/03/22 16:19:27 - mmengine - INFO - Epoch(train) [10][ 550/3862] lr: 9.7781e-04 eta: 12:27:08 time: 1.0653 data_time: 0.0114 memory: 9015 grad_norm: 0.8484 loss: 1.6011 loss_heatmap: 0.6755 layer_-1_loss_cls: 0.1048 layer_-1_loss_bbox: 0.8207 matched_ious: 0.5131 2023/03/22 16:20:21 - mmengine - INFO - Epoch(train) [10][ 600/3862] lr: 9.7731e-04 eta: 12:26:16 time: 1.0777 data_time: 0.0118 memory: 9428 grad_norm: 0.7010 loss: 1.6529 loss_heatmap: 0.6673 layer_-1_loss_cls: 0.1004 layer_-1_loss_bbox: 0.8852 matched_ious: 0.4746 2023/03/22 16:21:14 - mmengine - INFO - Epoch(train) [10][ 650/3862] lr: 9.7680e-04 eta: 12:25:22 time: 1.0648 data_time: 0.0121 memory: 9180 grad_norm: 0.8244 loss: 1.6001 loss_heatmap: 0.6685 layer_-1_loss_cls: 0.1002 layer_-1_loss_bbox: 0.8314 matched_ious: 0.4986 2023/03/22 16:22:07 - mmengine - INFO - Epoch(train) [10][ 700/3862] lr: 9.7629e-04 eta: 12:24:28 time: 1.0643 data_time: 0.0122 memory: 9152 grad_norm: 0.7934 loss: 1.6040 loss_heatmap: 0.6505 layer_-1_loss_cls: 0.0993 layer_-1_loss_bbox: 0.8542 matched_ious: 0.5400 2023/03/22 16:23:01 - mmengine - INFO - Epoch(train) [10][ 750/3862] lr: 9.7577e-04 eta: 12:23:35 time: 1.0746 data_time: 0.0120 memory: 9208 grad_norm: 0.8272 loss: 1.5948 loss_heatmap: 0.6614 layer_-1_loss_cls: 0.1015 layer_-1_loss_bbox: 0.8320 matched_ious: 0.5264 2023/03/22 16:23:54 - mmengine - INFO - Epoch(train) [10][ 800/3862] lr: 9.7525e-04 eta: 12:22:41 time: 1.0629 data_time: 0.0118 memory: 9376 grad_norm: 0.7891 loss: 1.6220 loss_heatmap: 0.6613 layer_-1_loss_cls: 0.1009 layer_-1_loss_bbox: 0.8598 matched_ious: 0.5122 2023/03/22 16:24:47 - mmengine - INFO - Epoch(train) [10][ 850/3862] lr: 9.7472e-04 eta: 12:21:47 time: 1.0639 data_time: 0.0119 memory: 9397 grad_norm: 0.7050 loss: 1.6091 loss_heatmap: 0.6572 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.8531 matched_ious: 0.5551 2023/03/22 16:25:41 - mmengine - INFO - Epoch(train) [10][ 900/3862] lr: 9.7419e-04 eta: 12:20:54 time: 1.0729 data_time: 0.0117 memory: 9043 grad_norm: 0.8215 loss: 1.5677 loss_heatmap: 0.6570 layer_-1_loss_cls: 0.1024 layer_-1_loss_bbox: 0.8083 matched_ious: 0.5432 2023/03/22 16:26:35 - mmengine - INFO - Epoch(train) [10][ 950/3862] lr: 9.7364e-04 eta: 12:20:01 time: 1.0748 data_time: 0.0115 memory: 9105 grad_norm: 0.8709 loss: 1.6452 loss_heatmap: 0.6613 layer_-1_loss_cls: 0.1029 layer_-1_loss_bbox: 0.8809 matched_ious: 0.4954 2023/03/22 16:27:28 - mmengine - INFO - Epoch(train) [10][1000/3862] lr: 9.7310e-04 eta: 12:19:07 time: 1.0598 data_time: 0.0114 memory: 9007 grad_norm: 0.8352 loss: 1.5743 loss_heatmap: 0.6590 layer_-1_loss_cls: 0.0995 layer_-1_loss_bbox: 0.8158 matched_ious: 0.5571 2023/03/22 16:28:21 - mmengine - INFO - Epoch(train) [10][1050/3862] lr: 9.7255e-04 eta: 12:18:14 time: 1.0750 data_time: 0.0117 memory: 9079 grad_norm: 0.7676 loss: 1.6305 loss_heatmap: 0.6764 layer_-1_loss_cls: 0.1037 layer_-1_loss_bbox: 0.8505 matched_ious: 0.5701 2023/03/22 16:29:15 - mmengine - INFO - Epoch(train) [10][1100/3862] lr: 9.7199e-04 eta: 12:17:21 time: 1.0722 data_time: 0.0119 memory: 9067 grad_norm: 0.9583 loss: 1.6307 loss_heatmap: 0.6710 layer_-1_loss_cls: 0.1040 layer_-1_loss_bbox: 0.8557 matched_ious: 0.5093 2023/03/22 16:30:08 - mmengine - INFO - Epoch(train) [10][1150/3862] lr: 9.7143e-04 eta: 12:16:27 time: 1.0602 data_time: 0.0115 memory: 9161 grad_norm: 0.8726 loss: 1.6226 loss_heatmap: 0.6737 layer_-1_loss_cls: 0.1032 layer_-1_loss_bbox: 0.8456 matched_ious: 0.5239 2023/03/22 16:31:02 - mmengine - INFO - Epoch(train) [10][1200/3862] lr: 9.7086e-04 eta: 12:15:33 time: 1.0730 data_time: 0.0116 memory: 9038 grad_norm: 0.8630 loss: 1.6264 loss_heatmap: 0.6627 layer_-1_loss_cls: 0.1003 layer_-1_loss_bbox: 0.8633 matched_ious: 0.5171 2023/03/22 16:31:47 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 16:31:56 - mmengine - INFO - Epoch(train) [10][1250/3862] lr: 9.7029e-04 eta: 12:14:41 time: 1.0930 data_time: 0.0120 memory: 8874 grad_norm: 0.7113 loss: 1.6477 loss_heatmap: 0.6632 layer_-1_loss_cls: 0.1030 layer_-1_loss_bbox: 0.8815 matched_ious: 0.4823 2023/03/22 16:32:50 - mmengine - INFO - Epoch(train) [10][1300/3862] lr: 9.6971e-04 eta: 12:13:48 time: 1.0639 data_time: 0.0119 memory: 9242 grad_norm: 0.7422 loss: 1.5944 loss_heatmap: 0.6592 layer_-1_loss_cls: 0.1008 layer_-1_loss_bbox: 0.8344 matched_ious: 0.5342 2023/03/22 16:33:43 - mmengine - INFO - Epoch(train) [10][1350/3862] lr: 9.6913e-04 eta: 12:12:54 time: 1.0733 data_time: 0.0118 memory: 9160 grad_norm: 0.7213 loss: 1.5893 loss_heatmap: 0.6415 layer_-1_loss_cls: 0.0972 layer_-1_loss_bbox: 0.8507 matched_ious: 0.5471 2023/03/22 16:34:36 - mmengine - INFO - Epoch(train) [10][1400/3862] lr: 9.6854e-04 eta: 12:12:00 time: 1.0597 data_time: 0.0116 memory: 9103 grad_norm: 0.8023 loss: 1.6139 loss_heatmap: 0.6660 layer_-1_loss_cls: 0.0996 layer_-1_loss_bbox: 0.8484 matched_ious: 0.4919 2023/03/22 16:35:29 - mmengine - INFO - Epoch(train) [10][1450/3862] lr: 9.6794e-04 eta: 12:11:07 time: 1.0615 data_time: 0.0119 memory: 9126 grad_norm: 0.6985 loss: 1.5687 loss_heatmap: 0.6440 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.8258 matched_ious: 0.5191 2023/03/22 16:36:23 - mmengine - INFO - Epoch(train) [10][1500/3862] lr: 9.6734e-04 eta: 12:10:13 time: 1.0694 data_time: 0.0115 memory: 9118 grad_norm: 0.7536 loss: 1.5950 loss_heatmap: 0.6704 layer_-1_loss_cls: 0.1022 layer_-1_loss_bbox: 0.8224 matched_ious: 0.5009 2023/03/22 16:37:16 - mmengine - INFO - Epoch(train) [10][1550/3862] lr: 9.6674e-04 eta: 12:09:20 time: 1.0678 data_time: 0.0118 memory: 9015 grad_norm: 0.7037 loss: 1.5125 loss_heatmap: 0.6258 layer_-1_loss_cls: 0.0974 layer_-1_loss_bbox: 0.7892 matched_ious: 0.5598 2023/03/22 16:38:10 - mmengine - INFO - Epoch(train) [10][1600/3862] lr: 9.6613e-04 eta: 12:08:26 time: 1.0683 data_time: 0.0117 memory: 8993 grad_norm: 0.7364 loss: 1.6061 loss_heatmap: 0.6704 layer_-1_loss_cls: 0.1033 layer_-1_loss_bbox: 0.8324 matched_ious: 0.5003 2023/03/22 16:39:03 - mmengine - INFO - Epoch(train) [10][1650/3862] lr: 9.6551e-04 eta: 12:07:33 time: 1.0700 data_time: 0.0120 memory: 9225 grad_norm: 0.7350 loss: 1.5234 loss_heatmap: 0.6413 layer_-1_loss_cls: 0.0996 layer_-1_loss_bbox: 0.7825 matched_ious: 0.5733 2023/03/22 16:39:56 - mmengine - INFO - Epoch(train) [10][1700/3862] lr: 9.6489e-04 eta: 12:06:39 time: 1.0646 data_time: 0.0119 memory: 9084 grad_norm: 0.7331 loss: 1.6181 loss_heatmap: 0.6744 layer_-1_loss_cls: 0.1012 layer_-1_loss_bbox: 0.8424 matched_ious: 0.5430 2023/03/22 16:40:50 - mmengine - INFO - Epoch(train) [10][1750/3862] lr: 9.6427e-04 eta: 12:05:46 time: 1.0743 data_time: 0.0119 memory: 9096 grad_norm: 0.7577 loss: 1.5486 loss_heatmap: 0.6292 layer_-1_loss_cls: 0.0957 layer_-1_loss_bbox: 0.8237 matched_ious: 0.4762 2023/03/22 16:41:44 - mmengine - INFO - Epoch(train) [10][1800/3862] lr: 9.6363e-04 eta: 12:04:53 time: 1.0736 data_time: 0.0120 memory: 9274 grad_norm: 0.7634 loss: 1.5562 loss_heatmap: 0.6423 layer_-1_loss_cls: 0.0970 layer_-1_loss_bbox: 0.8170 matched_ious: 0.5334 2023/03/22 16:42:37 - mmengine - INFO - Epoch(train) [10][1850/3862] lr: 9.6300e-04 eta: 12:03:59 time: 1.0657 data_time: 0.0118 memory: 8976 grad_norm: 0.7940 loss: 1.6293 loss_heatmap: 0.6657 layer_-1_loss_cls: 0.0987 layer_-1_loss_bbox: 0.8649 matched_ious: 0.4634 2023/03/22 16:43:30 - mmengine - INFO - Epoch(train) [10][1900/3862] lr: 9.6235e-04 eta: 12:03:05 time: 1.0615 data_time: 0.0117 memory: 9091 grad_norm: 0.7244 loss: 1.5786 loss_heatmap: 0.6587 layer_-1_loss_cls: 0.1013 layer_-1_loss_bbox: 0.8187 matched_ious: 0.5584 2023/03/22 16:44:24 - mmengine - INFO - Epoch(train) [10][1950/3862] lr: 9.6171e-04 eta: 12:02:12 time: 1.0699 data_time: 0.0117 memory: 9057 grad_norm: 0.7512 loss: 1.5559 loss_heatmap: 0.6470 layer_-1_loss_cls: 0.0998 layer_-1_loss_bbox: 0.8091 matched_ious: 0.5203 2023/03/22 16:45:17 - mmengine - INFO - Epoch(train) [10][2000/3862] lr: 9.6105e-04 eta: 12:01:18 time: 1.0660 data_time: 0.0118 memory: 9214 grad_norm: 0.7853 loss: 1.5986 loss_heatmap: 0.6587 layer_-1_loss_cls: 0.1002 layer_-1_loss_bbox: 0.8396 matched_ious: 0.5263 2023/03/22 16:46:10 - mmengine - INFO - Epoch(train) [10][2050/3862] lr: 9.6039e-04 eta: 12:00:25 time: 1.0718 data_time: 0.0119 memory: 9144 grad_norm: 0.8045 loss: 1.6526 loss_heatmap: 0.6624 layer_-1_loss_cls: 0.0994 layer_-1_loss_bbox: 0.8908 matched_ious: 0.4990 2023/03/22 16:47:04 - mmengine - INFO - Epoch(train) [10][2100/3862] lr: 9.5973e-04 eta: 11:59:31 time: 1.0643 data_time: 0.0118 memory: 9199 grad_norm: 0.8173 loss: 1.5544 loss_heatmap: 0.6456 layer_-1_loss_cls: 0.0980 layer_-1_loss_bbox: 0.8108 matched_ious: 0.5069 2023/03/22 16:47:57 - mmengine - INFO - Epoch(train) [10][2150/3862] lr: 9.5906e-04 eta: 11:58:38 time: 1.0694 data_time: 0.0119 memory: 9136 grad_norm: 0.7852 loss: 1.5968 loss_heatmap: 0.6526 layer_-1_loss_cls: 0.0994 layer_-1_loss_bbox: 0.8449 matched_ious: 0.4913 2023/03/22 16:48:51 - mmengine - INFO - Epoch(train) [10][2200/3862] lr: 9.5839e-04 eta: 11:57:44 time: 1.0685 data_time: 0.0119 memory: 9388 grad_norm: 0.7363 loss: 1.5831 loss_heatmap: 0.6380 layer_-1_loss_cls: 0.0968 layer_-1_loss_bbox: 0.8482 matched_ious: 0.5285 2023/03/22 16:49:35 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 16:49:44 - mmengine - INFO - Epoch(train) [10][2250/3862] lr: 9.5771e-04 eta: 11:56:50 time: 1.0598 data_time: 0.0117 memory: 9167 grad_norm: 0.8441 loss: 1.5587 loss_heatmap: 0.6463 layer_-1_loss_cls: 0.0990 layer_-1_loss_bbox: 0.8134 matched_ious: 0.5252 2023/03/22 16:50:37 - mmengine - INFO - Epoch(train) [10][2300/3862] lr: 9.5702e-04 eta: 11:55:56 time: 1.0640 data_time: 0.0120 memory: 9033 grad_norm: 0.7467 loss: 1.5955 loss_heatmap: 0.6628 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8339 matched_ious: 0.5424 2023/03/22 16:51:30 - mmengine - INFO - Epoch(train) [10][2350/3862] lr: 9.5633e-04 eta: 11:55:03 time: 1.0716 data_time: 0.0116 memory: 9183 grad_norm: 0.6859 loss: 1.6072 loss_heatmap: 0.6617 layer_-1_loss_cls: 0.0987 layer_-1_loss_bbox: 0.8468 matched_ious: 0.5387 2023/03/22 16:52:24 - mmengine - INFO - Epoch(train) [10][2400/3862] lr: 9.5564e-04 eta: 11:54:10 time: 1.0803 data_time: 0.0121 memory: 9174 grad_norm: 0.7353 loss: 1.5212 loss_heatmap: 0.6398 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.7825 matched_ious: 0.5364 2023/03/22 16:53:18 - mmengine - INFO - Epoch(train) [10][2450/3862] lr: 9.5494e-04 eta: 11:53:17 time: 1.0681 data_time: 0.0115 memory: 9301 grad_norm: 0.7129 loss: 1.5659 loss_heatmap: 0.6555 layer_-1_loss_cls: 0.1021 layer_-1_loss_bbox: 0.8083 matched_ious: 0.5028 2023/03/22 16:54:13 - mmengine - INFO - Epoch(train) [10][2500/3862] lr: 9.5423e-04 eta: 11:52:25 time: 1.0959 data_time: 0.0392 memory: 9186 grad_norm: 0.7553 loss: 1.5713 loss_heatmap: 0.6620 layer_-1_loss_cls: 0.0997 layer_-1_loss_bbox: 0.8096 matched_ious: 0.5214 2023/03/22 16:55:06 - mmengine - INFO - Epoch(train) [10][2550/3862] lr: 9.5352e-04 eta: 11:51:31 time: 1.0627 data_time: 0.0116 memory: 9008 grad_norm: 0.7878 loss: 1.5892 loss_heatmap: 0.6606 layer_-1_loss_cls: 0.1009 layer_-1_loss_bbox: 0.8277 matched_ious: 0.5368 2023/03/22 16:55:59 - mmengine - INFO - Epoch(train) [10][2600/3862] lr: 9.5281e-04 eta: 11:50:37 time: 1.0672 data_time: 0.0117 memory: 9014 grad_norm: 0.6904 loss: 1.5856 loss_heatmap: 0.6579 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.8301 matched_ious: 0.5256 2023/03/22 16:56:52 - mmengine - INFO - Epoch(train) [10][2650/3862] lr: 9.5208e-04 eta: 11:49:44 time: 1.0671 data_time: 0.0120 memory: 9000 grad_norm: 0.7685 loss: 1.5396 loss_heatmap: 0.6246 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.8195 matched_ious: 0.4950 2023/03/22 16:57:46 - mmengine - INFO - Epoch(train) [10][2700/3862] lr: 9.5136e-04 eta: 11:48:50 time: 1.0651 data_time: 0.0119 memory: 9276 grad_norm: 0.7124 loss: 1.5933 loss_heatmap: 0.6499 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8446 matched_ious: 0.5111 2023/03/22 16:58:39 - mmengine - INFO - Epoch(train) [10][2750/3862] lr: 9.5063e-04 eta: 11:47:56 time: 1.0621 data_time: 0.0119 memory: 9360 grad_norm: 0.8200 loss: 1.6156 loss_heatmap: 0.6617 layer_-1_loss_cls: 0.0993 layer_-1_loss_bbox: 0.8546 matched_ious: 0.4844 2023/03/22 16:59:32 - mmengine - INFO - Epoch(train) [10][2800/3862] lr: 9.4989e-04 eta: 11:47:03 time: 1.0629 data_time: 0.0119 memory: 9204 grad_norm: 0.7734 loss: 1.5476 loss_heatmap: 0.6414 layer_-1_loss_cls: 0.0954 layer_-1_loss_bbox: 0.8108 matched_ious: 0.5252 2023/03/22 17:00:25 - mmengine - INFO - Epoch(train) [10][2850/3862] lr: 9.4915e-04 eta: 11:46:09 time: 1.0678 data_time: 0.0118 memory: 9155 grad_norm: 0.7291 loss: 1.5636 loss_heatmap: 0.6521 layer_-1_loss_cls: 0.1027 layer_-1_loss_bbox: 0.8088 matched_ious: 0.5290 2023/03/22 17:01:19 - mmengine - INFO - Epoch(train) [10][2900/3862] lr: 9.4840e-04 eta: 11:45:16 time: 1.0700 data_time: 0.0120 memory: 9294 grad_norm: 0.7078 loss: 1.5581 loss_heatmap: 0.6389 layer_-1_loss_cls: 0.0997 layer_-1_loss_bbox: 0.8196 matched_ious: 0.5026 2023/03/22 17:02:12 - mmengine - INFO - Epoch(train) [10][2950/3862] lr: 9.4765e-04 eta: 11:44:22 time: 1.0712 data_time: 0.0121 memory: 9466 grad_norm: 0.7544 loss: 1.6344 loss_heatmap: 0.6653 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8702 matched_ious: 0.5024 2023/03/22 17:03:06 - mmengine - INFO - Epoch(train) [10][3000/3862] lr: 9.4689e-04 eta: 11:43:29 time: 1.0719 data_time: 0.0117 memory: 9252 grad_norm: 0.7050 loss: 1.5785 loss_heatmap: 0.6539 layer_-1_loss_cls: 0.0979 layer_-1_loss_bbox: 0.8268 matched_ious: 0.5194 2023/03/22 17:03:59 - mmengine - INFO - Epoch(train) [10][3050/3862] lr: 9.4613e-04 eta: 11:42:35 time: 1.0662 data_time: 0.0117 memory: 9046 grad_norm: 0.7368 loss: 1.5772 loss_heatmap: 0.6729 layer_-1_loss_cls: 0.1032 layer_-1_loss_bbox: 0.8010 matched_ious: 0.5612 2023/03/22 17:04:53 - mmengine - INFO - Epoch(train) [10][3100/3862] lr: 9.4536e-04 eta: 11:41:42 time: 1.0695 data_time: 0.0119 memory: 9528 grad_norm: 0.7603 loss: 1.5627 loss_heatmap: 0.6490 layer_-1_loss_cls: 0.0997 layer_-1_loss_bbox: 0.8140 matched_ious: 0.4927 2023/03/22 17:05:46 - mmengine - INFO - Epoch(train) [10][3150/3862] lr: 9.4459e-04 eta: 11:40:49 time: 1.0708 data_time: 0.0119 memory: 9471 grad_norm: 0.7664 loss: 1.6096 loss_heatmap: 0.6535 layer_-1_loss_cls: 0.0994 layer_-1_loss_bbox: 0.8568 matched_ious: 0.5298 2023/03/22 17:06:40 - mmengine - INFO - Epoch(train) [10][3200/3862] lr: 9.4381e-04 eta: 11:39:55 time: 1.0660 data_time: 0.0117 memory: 9420 grad_norm: 0.8381 loss: 1.5639 loss_heatmap: 0.6435 layer_-1_loss_cls: 0.0980 layer_-1_loss_bbox: 0.8224 matched_ious: 0.5525 2023/03/22 17:07:24 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 17:07:33 - mmengine - INFO - Epoch(train) [10][3250/3862] lr: 9.4303e-04 eta: 11:39:01 time: 1.0614 data_time: 0.0124 memory: 9263 grad_norm: 0.7316 loss: 1.5384 loss_heatmap: 0.6404 layer_-1_loss_cls: 0.0971 layer_-1_loss_bbox: 0.8010 matched_ious: 0.5592 2023/03/22 17:08:26 - mmengine - INFO - Epoch(train) [10][3300/3862] lr: 9.4224e-04 eta: 11:38:07 time: 1.0587 data_time: 0.0116 memory: 9024 grad_norm: 0.7687 loss: 1.6189 loss_heatmap: 0.6593 layer_-1_loss_cls: 0.1020 layer_-1_loss_bbox: 0.8577 matched_ious: 0.5173 2023/03/22 17:09:19 - mmengine - INFO - Epoch(train) [10][3350/3862] lr: 9.4144e-04 eta: 11:37:13 time: 1.0614 data_time: 0.0116 memory: 9061 grad_norm: 0.9012 loss: 1.5405 loss_heatmap: 0.6402 layer_-1_loss_cls: 0.0995 layer_-1_loss_bbox: 0.8008 matched_ious: 0.5221 2023/03/22 17:10:12 - mmengine - INFO - Epoch(train) [10][3400/3862] lr: 9.4065e-04 eta: 11:36:19 time: 1.0572 data_time: 0.0120 memory: 9292 grad_norm: 0.7020 loss: 1.6144 loss_heatmap: 0.6524 layer_-1_loss_cls: 0.0982 layer_-1_loss_bbox: 0.8638 matched_ious: 0.5165 2023/03/22 17:11:05 - mmengine - INFO - Epoch(train) [10][3450/3862] lr: 9.3984e-04 eta: 11:35:26 time: 1.0708 data_time: 0.0119 memory: 9221 grad_norm: 0.7597 loss: 1.6045 loss_heatmap: 0.6427 layer_-1_loss_cls: 0.0996 layer_-1_loss_bbox: 0.8622 matched_ious: 0.5493 2023/03/22 17:11:59 - mmengine - INFO - Epoch(train) [10][3500/3862] lr: 9.3903e-04 eta: 11:34:33 time: 1.0721 data_time: 0.0120 memory: 9348 grad_norm: 0.7155 loss: 1.5684 loss_heatmap: 0.6388 layer_-1_loss_cls: 0.0964 layer_-1_loss_bbox: 0.8332 matched_ious: 0.5314 2023/03/22 17:12:53 - mmengine - INFO - Epoch(train) [10][3550/3862] lr: 9.3822e-04 eta: 11:33:40 time: 1.0825 data_time: 0.0117 memory: 9087 grad_norm: 0.7650 loss: 1.5576 loss_heatmap: 0.6468 layer_-1_loss_cls: 0.0980 layer_-1_loss_bbox: 0.8128 matched_ious: 0.4848 2023/03/22 17:13:46 - mmengine - INFO - Epoch(train) [10][3600/3862] lr: 9.3740e-04 eta: 11:32:46 time: 1.0617 data_time: 0.0118 memory: 9164 grad_norm: 0.7733 loss: 1.5404 loss_heatmap: 0.6415 layer_-1_loss_cls: 0.0999 layer_-1_loss_bbox: 0.7991 matched_ious: 0.5246 2023/03/22 17:14:40 - mmengine - INFO - Epoch(train) [10][3650/3862] lr: 9.3658e-04 eta: 11:31:53 time: 1.0707 data_time: 0.0116 memory: 9356 grad_norm: 0.6698 loss: 1.5476 loss_heatmap: 0.6399 layer_-1_loss_cls: 0.1010 layer_-1_loss_bbox: 0.8067 matched_ious: 0.5640 2023/03/22 17:15:33 - mmengine - INFO - Epoch(train) [10][3700/3862] lr: 9.3575e-04 eta: 11:30:59 time: 1.0735 data_time: 0.0114 memory: 9327 grad_norm: 0.7367 loss: 1.5060 loss_heatmap: 0.6343 layer_-1_loss_cls: 0.0965 layer_-1_loss_bbox: 0.7752 matched_ious: 0.5945 2023/03/22 17:16:26 - mmengine - INFO - Epoch(train) [10][3750/3862] lr: 9.3492e-04 eta: 11:30:06 time: 1.0628 data_time: 0.0119 memory: 9181 grad_norm: 0.7407 loss: 1.5720 loss_heatmap: 0.6348 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.8395 matched_ious: 0.5416 2023/03/22 17:17:19 - mmengine - INFO - Epoch(train) [10][3800/3862] lr: 9.3408e-04 eta: 11:29:12 time: 1.0597 data_time: 0.0116 memory: 9418 grad_norm: 0.7449 loss: 1.5696 loss_heatmap: 0.6456 layer_-1_loss_cls: 0.0995 layer_-1_loss_bbox: 0.8245 matched_ious: 0.5456 2023/03/22 17:18:13 - mmengine - INFO - Epoch(train) [10][3850/3862] lr: 9.3323e-04 eta: 11:28:18 time: 1.0679 data_time: 0.0117 memory: 9373 grad_norm: 0.8442 loss: 1.5456 loss_heatmap: 0.6370 layer_-1_loss_cls: 0.0948 layer_-1_loss_bbox: 0.8139 matched_ious: 0.5381 2023/03/22 17:18:25 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 17:18:25 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/03/22 17:18:36 - mmengine - INFO - Epoch(val) [10][ 50/753] eta: 0:01:50 time: 0.1567 data_time: 0.0048 memory: 8893 2023/03/22 17:18:43 - mmengine - INFO - Epoch(val) [10][100/753] eta: 0:01:38 time: 0.1451 data_time: 0.0037 memory: 730 2023/03/22 17:18:50 - mmengine - INFO - Epoch(val) [10][150/753] eta: 0:01:30 time: 0.1474 data_time: 0.0046 memory: 730 2023/03/22 17:18:58 - mmengine - INFO - Epoch(val) [10][200/753] eta: 0:01:23 time: 0.1534 data_time: 0.0040 memory: 730 2023/03/22 17:19:05 - mmengine - INFO - Epoch(val) [10][250/753] eta: 0:01:15 time: 0.1458 data_time: 0.0038 memory: 730 2023/03/22 17:19:13 - mmengine - INFO - Epoch(val) [10][300/753] eta: 0:01:07 time: 0.1447 data_time: 0.0047 memory: 730 2023/03/22 17:19:20 - mmengine - INFO - Epoch(val) [10][350/753] eta: 0:00:59 time: 0.1466 data_time: 0.0036 memory: 730 2023/03/22 17:19:27 - mmengine - INFO - Epoch(val) [10][400/753] eta: 0:00:51 time: 0.1342 data_time: 0.0039 memory: 730 2023/03/22 17:19:34 - mmengine - INFO - Epoch(val) [10][450/753] eta: 0:00:44 time: 0.1459 data_time: 0.0035 memory: 730 2023/03/22 17:19:41 - mmengine - INFO - Epoch(val) [10][500/753] eta: 0:00:37 time: 0.1503 data_time: 0.0038 memory: 730 2023/03/22 17:19:48 - mmengine - INFO - Epoch(val) [10][550/753] eta: 0:00:29 time: 0.1381 data_time: 0.0041 memory: 730 2023/03/22 17:19:56 - mmengine - INFO - Epoch(val) [10][600/753] eta: 0:00:22 time: 0.1530 data_time: 0.0041 memory: 730 2023/03/22 17:20:04 - mmengine - INFO - Epoch(val) [10][650/753] eta: 0:00:15 time: 0.1527 data_time: 0.0034 memory: 730 2023/03/22 17:20:11 - mmengine - INFO - Epoch(val) [10][700/753] eta: 0:00:07 time: 0.1567 data_time: 0.0040 memory: 730 2023/03/22 17:20:19 - mmengine - INFO - Epoch(val) [10][750/753] eta: 0:00:00 time: 0.1579 data_time: 0.0034 memory: 730 2023/03/22 17:31:52 - mmengine - INFO - Epoch(val) [10][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.7638 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8564 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.8864 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.8984 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1823 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1601 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.1346 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.3555 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1971 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2965 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2644 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3466 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.3778 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1983 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.3486 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.5479 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6192 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.6580 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3448 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1949 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.1299 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.3286 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2347 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0181 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.1011 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.1979 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.2899 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6952 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4345 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 1.0017 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1395 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3513 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4156 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.6829 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.7964 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8298 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3574 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1953 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.1159 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.9229 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2321 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.0991 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.2766 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.4490 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.5282 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5420 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2342 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.5621 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.2384 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1934 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.5563 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.6600 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7079 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7237 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.2143 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2911 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0705 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.4970 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.5520 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.5603 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.5701 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1937 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2454 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2669 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.5096 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2636 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.3400 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.3475 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.3479 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.3505 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1515 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2601 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.4337 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2724 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0191 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8148 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8297 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8433 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8598 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1476 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2875 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.4039 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2556 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0950 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.6458 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.6583 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.6759 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.7101 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1362 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3413 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6331 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.5629data_time: 0.0034 time: 0.1562 2023/03/22 17:32:48 - mmengine - INFO - Epoch(train) [11][ 50/3862] lr: 9.3218e-04 eta: 11:27:14 time: 1.1206 data_time: 0.0531 memory: 9140 grad_norm: 0.7956 loss: 1.5537 loss_heatmap: 0.6298 layer_-1_loss_cls: 0.0971 layer_-1_loss_bbox: 0.8268 matched_ious: 0.5752 2023/03/22 17:33:41 - mmengine - INFO - Epoch(train) [11][ 100/3862] lr: 9.3133e-04 eta: 11:26:21 time: 1.0682 data_time: 0.0111 memory: 9196 grad_norm: 0.7545 loss: 1.5544 loss_heatmap: 0.6432 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8124 matched_ious: 0.4983 2023/03/22 17:34:34 - mmengine - INFO - Epoch(train) [11][ 150/3862] lr: 9.3047e-04 eta: 11:25:27 time: 1.0625 data_time: 0.0109 memory: 9161 grad_norm: 0.7888 loss: 1.6107 loss_heatmap: 0.6461 layer_-1_loss_cls: 0.0971 layer_-1_loss_bbox: 0.8676 matched_ious: 0.5483 2023/03/22 17:35:28 - mmengine - INFO - Epoch(train) [11][ 200/3862] lr: 9.2960e-04 eta: 11:24:33 time: 1.0620 data_time: 0.0112 memory: 9215 grad_norm: 0.7519 loss: 1.5624 loss_heatmap: 0.6503 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8133 matched_ious: 0.5124 2023/03/22 17:36:22 - mmengine - INFO - Epoch(train) [11][ 250/3862] lr: 9.2873e-04 eta: 11:23:40 time: 1.0789 data_time: 0.0113 memory: 9208 grad_norm: 0.7818 loss: 1.6323 loss_heatmap: 0.6650 layer_-1_loss_cls: 0.0990 layer_-1_loss_bbox: 0.8683 matched_ious: 0.4880 2023/03/22 17:37:15 - mmengine - INFO - Epoch(train) [11][ 300/3862] lr: 9.2786e-04 eta: 11:22:47 time: 1.0651 data_time: 0.0117 memory: 9190 grad_norm: 0.7819 loss: 1.5431 loss_heatmap: 0.6395 layer_-1_loss_cls: 0.0982 layer_-1_loss_bbox: 0.8054 matched_ious: 0.5538 2023/03/22 17:38:08 - mmengine - INFO - Epoch(train) [11][ 350/3862] lr: 9.2698e-04 eta: 11:21:53 time: 1.0688 data_time: 0.0116 memory: 9310 grad_norm: 0.8310 loss: 1.5229 loss_heatmap: 0.6293 layer_-1_loss_cls: 0.0959 layer_-1_loss_bbox: 0.7977 matched_ious: 0.5390 2023/03/22 17:38:40 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 17:39:01 - mmengine - INFO - Epoch(train) [11][ 400/3862] lr: 9.2609e-04 eta: 11:20:59 time: 1.0620 data_time: 0.0117 memory: 9020 grad_norm: 0.7569 loss: 1.5612 loss_heatmap: 0.6406 layer_-1_loss_cls: 0.0965 layer_-1_loss_bbox: 0.8241 matched_ious: 0.5207 2023/03/22 17:39:54 - mmengine - INFO - Epoch(train) [11][ 450/3862] lr: 9.2520e-04 eta: 11:20:06 time: 1.0621 data_time: 0.0114 memory: 9138 grad_norm: 0.7743 loss: 1.5309 loss_heatmap: 0.6361 layer_-1_loss_cls: 0.0991 layer_-1_loss_bbox: 0.7957 matched_ious: 0.5525 2023/03/22 17:40:48 - mmengine - INFO - Epoch(train) [11][ 500/3862] lr: 9.2431e-04 eta: 11:19:12 time: 1.0763 data_time: 0.0119 memory: 8984 grad_norm: 0.7641 loss: 1.5992 loss_heatmap: 0.6521 layer_-1_loss_cls: 0.1003 layer_-1_loss_bbox: 0.8467 matched_ious: 0.5153 2023/03/22 17:41:42 - mmengine - INFO - Epoch(train) [11][ 550/3862] lr: 9.2341e-04 eta: 11:18:19 time: 1.0689 data_time: 0.0118 memory: 9172 grad_norm: 0.7227 loss: 1.5604 loss_heatmap: 0.6331 layer_-1_loss_cls: 0.0957 layer_-1_loss_bbox: 0.8316 matched_ious: 0.4697 2023/03/22 17:42:35 - mmengine - INFO - Epoch(train) [11][ 600/3862] lr: 9.2251e-04 eta: 11:17:26 time: 1.0748 data_time: 0.0120 memory: 9038 grad_norm: 0.7045 loss: 1.5244 loss_heatmap: 0.6459 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.7796 matched_ious: 0.4887 2023/03/22 17:43:29 - mmengine - INFO - Epoch(train) [11][ 650/3862] lr: 9.2160e-04 eta: 11:16:33 time: 1.0740 data_time: 0.0122 memory: 9183 grad_norm: 0.8309 loss: 1.5690 loss_heatmap: 0.6342 layer_-1_loss_cls: 0.0965 layer_-1_loss_bbox: 0.8383 matched_ious: 0.5099 2023/03/22 17:44:23 - mmengine - INFO - Epoch(train) [11][ 700/3862] lr: 9.2069e-04 eta: 11:15:39 time: 1.0671 data_time: 0.0119 memory: 9350 grad_norm: 0.7612 loss: 1.5495 loss_heatmap: 0.6546 layer_-1_loss_cls: 0.1004 layer_-1_loss_bbox: 0.7945 matched_ious: 0.5469 2023/03/22 17:45:16 - mmengine - INFO - Epoch(train) [11][ 750/3862] lr: 9.1977e-04 eta: 11:14:46 time: 1.0704 data_time: 0.0121 memory: 9512 grad_norm: 0.6845 loss: 1.5602 loss_heatmap: 0.6412 layer_-1_loss_cls: 0.0982 layer_-1_loss_bbox: 0.8208 matched_ious: 0.5223 2023/03/22 17:46:09 - mmengine - INFO - Epoch(train) [11][ 800/3862] lr: 9.1884e-04 eta: 11:13:52 time: 1.0622 data_time: 0.0118 memory: 9129 grad_norm: 0.7433 loss: 1.5466 loss_heatmap: 0.6339 layer_-1_loss_cls: 0.0962 layer_-1_loss_bbox: 0.8165 matched_ious: 0.5301 2023/03/22 17:47:03 - mmengine - INFO - Epoch(train) [11][ 850/3862] lr: 9.1792e-04 eta: 11:12:58 time: 1.0669 data_time: 0.0124 memory: 9167 grad_norm: 0.7474 loss: 1.5907 loss_heatmap: 0.6678 layer_-1_loss_cls: 0.1018 layer_-1_loss_bbox: 0.8211 matched_ious: 0.5621 2023/03/22 17:47:56 - mmengine - INFO - Epoch(train) [11][ 900/3862] lr: 9.1698e-04 eta: 11:12:05 time: 1.0712 data_time: 0.0118 memory: 9011 grad_norm: 0.6765 loss: 1.5428 loss_heatmap: 0.6379 layer_-1_loss_cls: 0.0967 layer_-1_loss_bbox: 0.8082 matched_ious: 0.5046 2023/03/22 17:48:50 - mmengine - INFO - Epoch(train) [11][ 950/3862] lr: 9.1605e-04 eta: 11:11:12 time: 1.0769 data_time: 0.0117 memory: 8993 grad_norm: 0.7920 loss: 1.5607 loss_heatmap: 0.6346 layer_-1_loss_cls: 0.0974 layer_-1_loss_bbox: 0.8288 matched_ious: 0.5636 2023/03/22 17:49:44 - mmengine - INFO - Epoch(train) [11][1000/3862] lr: 9.1510e-04 eta: 11:10:19 time: 1.0739 data_time: 0.0117 memory: 9063 grad_norm: 0.7178 loss: 1.5165 loss_heatmap: 0.6296 layer_-1_loss_cls: 0.0974 layer_-1_loss_bbox: 0.7896 matched_ious: 0.5036 2023/03/22 17:50:37 - mmengine - INFO - Epoch(train) [11][1050/3862] lr: 9.1416e-04 eta: 11:09:25 time: 1.0659 data_time: 0.0118 memory: 9085 grad_norm: 0.7846 loss: 1.5530 loss_heatmap: 0.6467 layer_-1_loss_cls: 0.0973 layer_-1_loss_bbox: 0.8090 matched_ious: 0.5135 2023/03/22 17:51:30 - mmengine - INFO - Epoch(train) [11][1100/3862] lr: 9.1320e-04 eta: 11:08:31 time: 1.0634 data_time: 0.0118 memory: 9229 grad_norm: 0.6724 loss: 1.5559 loss_heatmap: 0.6398 layer_-1_loss_cls: 0.0961 layer_-1_loss_bbox: 0.8201 matched_ious: 0.5406 2023/03/22 17:52:23 - mmengine - INFO - Epoch(train) [11][1150/3862] lr: 9.1225e-04 eta: 11:07:38 time: 1.0638 data_time: 0.0119 memory: 9103 grad_norm: 0.7624 loss: 1.5106 loss_heatmap: 0.6360 layer_-1_loss_cls: 0.0961 layer_-1_loss_bbox: 0.7785 matched_ious: 0.5353 2023/03/22 17:53:17 - mmengine - INFO - Epoch(train) [11][1200/3862] lr: 9.1129e-04 eta: 11:06:44 time: 1.0673 data_time: 0.0119 memory: 9305 grad_norm: 0.6904 loss: 1.5086 loss_heatmap: 0.6432 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.7678 matched_ious: 0.5827 2023/03/22 17:54:10 - mmengine - INFO - Epoch(train) [11][1250/3862] lr: 9.1032e-04 eta: 11:05:50 time: 1.0651 data_time: 0.0117 memory: 9060 grad_norm: 0.6887 loss: 1.5485 loss_heatmap: 0.6348 layer_-1_loss_cls: 0.0972 layer_-1_loss_bbox: 0.8165 matched_ious: 0.5116 2023/03/22 17:55:03 - mmengine - INFO - Epoch(train) [11][1300/3862] lr: 9.0935e-04 eta: 11:04:57 time: 1.0642 data_time: 0.0115 memory: 9108 grad_norm: 0.7463 loss: 1.5317 loss_heatmap: 0.6392 layer_-1_loss_cls: 0.0953 layer_-1_loss_bbox: 0.7972 matched_ious: 0.5458 2023/03/22 17:55:57 - mmengine - INFO - Epoch(train) [11][1350/3862] lr: 9.0837e-04 eta: 11:04:03 time: 1.0675 data_time: 0.0116 memory: 9395 grad_norm: 0.7910 loss: 1.5934 loss_heatmap: 0.6616 layer_-1_loss_cls: 0.1002 layer_-1_loss_bbox: 0.8316 matched_ious: 0.5081 2023/03/22 17:56:29 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 17:56:50 - mmengine - INFO - Epoch(train) [11][1400/3862] lr: 9.0739e-04 eta: 11:03:10 time: 1.0695 data_time: 0.0120 memory: 9159 grad_norm: 0.6969 loss: 1.4892 loss_heatmap: 0.6142 layer_-1_loss_cls: 0.0937 layer_-1_loss_bbox: 0.7813 matched_ious: 0.5209 2023/03/22 17:57:43 - mmengine - INFO - Epoch(train) [11][1450/3862] lr: 9.0641e-04 eta: 11:02:16 time: 1.0677 data_time: 0.0116 memory: 9243 grad_norm: 0.8783 loss: 1.6779 loss_heatmap: 0.6890 layer_-1_loss_cls: 0.1067 layer_-1_loss_bbox: 0.8823 matched_ious: 0.5010 2023/03/22 17:58:37 - mmengine - INFO - Epoch(train) [11][1500/3862] lr: 9.0542e-04 eta: 11:01:23 time: 1.0778 data_time: 0.0125 memory: 9318 grad_norm: 0.7388 loss: 1.5830 loss_heatmap: 0.6575 layer_-1_loss_cls: 0.1006 layer_-1_loss_bbox: 0.8248 matched_ious: 0.4932 2023/03/22 17:59:30 - mmengine - INFO - Epoch(train) [11][1550/3862] lr: 9.0443e-04 eta: 11:00:29 time: 1.0594 data_time: 0.0121 memory: 9050 grad_norm: 0.7210 loss: 1.5854 loss_heatmap: 0.6509 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.8356 matched_ious: 0.5260 2023/03/22 18:00:24 - mmengine - INFO - Epoch(train) [11][1600/3862] lr: 9.0343e-04 eta: 10:59:36 time: 1.0688 data_time: 0.0121 memory: 9152 grad_norm: 0.7242 loss: 1.5368 loss_heatmap: 0.6343 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.8049 matched_ious: 0.5473 2023/03/22 18:01:17 - mmengine - INFO - Epoch(train) [11][1650/3862] lr: 9.0242e-04 eta: 10:58:42 time: 1.0683 data_time: 0.0127 memory: 9051 grad_norm: 0.6915 loss: 1.6629 loss_heatmap: 0.6763 layer_-1_loss_cls: 0.1021 layer_-1_loss_bbox: 0.8845 matched_ious: 0.4993 2023/03/22 18:02:11 - mmengine - INFO - Epoch(train) [11][1700/3862] lr: 9.0142e-04 eta: 10:57:49 time: 1.0711 data_time: 0.0119 memory: 9225 grad_norm: 0.6847 loss: 1.6025 loss_heatmap: 0.6613 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.8423 matched_ious: 0.5407 2023/03/22 18:03:05 - mmengine - INFO - Epoch(train) [11][1750/3862] lr: 9.0040e-04 eta: 10:56:56 time: 1.0823 data_time: 0.0128 memory: 8996 grad_norm: 0.7344 loss: 1.5282 loss_heatmap: 0.6141 layer_-1_loss_cls: 0.0928 layer_-1_loss_bbox: 0.8214 matched_ious: 0.5289 2023/03/22 18:03:58 - mmengine - INFO - Epoch(train) [11][1800/3862] lr: 8.9939e-04 eta: 10:56:03 time: 1.0673 data_time: 0.0122 memory: 9581 grad_norm: 0.7951 loss: 1.5559 loss_heatmap: 0.6428 layer_-1_loss_cls: 0.0972 layer_-1_loss_bbox: 0.8159 matched_ious: 0.4953 2023/03/22 18:04:52 - mmengine - INFO - Epoch(train) [11][1850/3862] lr: 8.9836e-04 eta: 10:55:09 time: 1.0695 data_time: 0.0121 memory: 9113 grad_norm: 0.7629 loss: 1.5228 loss_heatmap: 0.6417 layer_-1_loss_cls: 0.0975 layer_-1_loss_bbox: 0.7837 matched_ious: 0.5287 2023/03/22 18:05:45 - mmengine - INFO - Epoch(train) [11][1900/3862] lr: 8.9734e-04 eta: 10:54:16 time: 1.0669 data_time: 0.0122 memory: 9093 grad_norm: 0.7125 loss: 1.5304 loss_heatmap: 0.6259 layer_-1_loss_cls: 0.0929 layer_-1_loss_bbox: 0.8116 matched_ious: 0.5727 2023/03/22 18:06:38 - mmengine - INFO - Epoch(train) [11][1950/3862] lr: 8.9631e-04 eta: 10:53:22 time: 1.0650 data_time: 0.0122 memory: 9275 grad_norm: 0.8122 loss: 1.5790 loss_heatmap: 0.6412 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.8402 matched_ious: 0.5083 2023/03/22 18:07:32 - mmengine - INFO - Epoch(train) [11][2000/3862] lr: 8.9527e-04 eta: 10:52:29 time: 1.0719 data_time: 0.0120 memory: 9292 grad_norm: 0.7440 loss: 1.5635 loss_heatmap: 0.6610 layer_-1_loss_cls: 0.1010 layer_-1_loss_bbox: 0.8016 matched_ious: 0.5215 2023/03/22 18:08:25 - mmengine - INFO - Epoch(train) [11][2050/3862] lr: 8.9423e-04 eta: 10:51:35 time: 1.0623 data_time: 0.0121 memory: 9168 grad_norm: 0.6799 loss: 1.5678 loss_heatmap: 0.6406 layer_-1_loss_cls: 0.0987 layer_-1_loss_bbox: 0.8284 matched_ious: 0.5654 2023/03/22 18:09:19 - mmengine - INFO - Epoch(train) [11][2100/3862] lr: 8.9319e-04 eta: 10:50:42 time: 1.0729 data_time: 0.0118 memory: 9340 grad_norm: 0.7931 loss: 1.5214 loss_heatmap: 0.6265 layer_-1_loss_cls: 0.0971 layer_-1_loss_bbox: 0.7978 matched_ious: 0.5260 2023/03/22 18:10:12 - mmengine - INFO - Epoch(train) [11][2150/3862] lr: 8.9214e-04 eta: 10:49:48 time: 1.0636 data_time: 0.0119 memory: 9191 grad_norm: 0.6947 loss: 1.5123 loss_heatmap: 0.6261 layer_-1_loss_cls: 0.0954 layer_-1_loss_bbox: 0.7908 matched_ious: 0.5341 2023/03/22 18:11:06 - mmengine - INFO - Epoch(train) [11][2200/3862] lr: 8.9108e-04 eta: 10:48:55 time: 1.0745 data_time: 0.0125 memory: 9401 grad_norm: 0.6931 loss: 1.5869 loss_heatmap: 0.6564 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8316 matched_ious: 0.4936 2023/03/22 18:11:59 - mmengine - INFO - Epoch(train) [11][2250/3862] lr: 8.9002e-04 eta: 10:48:02 time: 1.0741 data_time: 0.0127 memory: 9077 grad_norm: 0.7115 loss: 1.5631 loss_heatmap: 0.6396 layer_-1_loss_cls: 0.0978 layer_-1_loss_bbox: 0.8256 matched_ious: 0.5238 2023/03/22 18:12:53 - mmengine - INFO - Epoch(train) [11][2300/3862] lr: 8.8896e-04 eta: 10:47:08 time: 1.0665 data_time: 0.0122 memory: 9120 grad_norm: 0.7091 loss: 1.5461 loss_heatmap: 0.6316 layer_-1_loss_cls: 0.0981 layer_-1_loss_bbox: 0.8164 matched_ious: 0.5388 2023/03/22 18:13:46 - mmengine - INFO - Epoch(train) [11][2350/3862] lr: 8.8789e-04 eta: 10:46:14 time: 1.0654 data_time: 0.0119 memory: 9083 grad_norm: 0.8051 loss: 1.5780 loss_heatmap: 0.6472 layer_-1_loss_cls: 0.0988 layer_-1_loss_bbox: 0.8320 matched_ious: 0.5137 2023/03/22 18:14:18 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 18:14:39 - mmengine - INFO - Epoch(train) [11][2400/3862] lr: 8.8682e-04 eta: 10:45:20 time: 1.0600 data_time: 0.0122 memory: 9468 grad_norm: 0.6989 loss: 1.5323 loss_heatmap: 0.6353 layer_-1_loss_cls: 0.0968 layer_-1_loss_bbox: 0.8002 matched_ious: 0.5212 2023/03/22 18:15:32 - mmengine - INFO - Epoch(train) [11][2450/3862] lr: 8.8575e-04 eta: 10:44:27 time: 1.0656 data_time: 0.0123 memory: 9114 grad_norm: 0.7331 loss: 1.5032 loss_heatmap: 0.6165 layer_-1_loss_cls: 0.0949 layer_-1_loss_bbox: 0.7917 matched_ious: 0.5413 2023/03/22 18:16:25 - mmengine - INFO - Epoch(train) [11][2500/3862] lr: 8.8467e-04 eta: 10:43:33 time: 1.0651 data_time: 0.0124 memory: 9179 grad_norm: 0.7084 loss: 1.5609 loss_heatmap: 0.6355 layer_-1_loss_cls: 0.0959 layer_-1_loss_bbox: 0.8295 matched_ious: 0.5181 2023/03/22 18:17:19 - mmengine - INFO - Epoch(train) [11][2550/3862] lr: 8.8358e-04 eta: 10:42:40 time: 1.0665 data_time: 0.0124 memory: 9046 grad_norm: 0.7094 loss: 1.5100 loss_heatmap: 0.6208 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.7937 matched_ious: 0.5072 2023/03/22 18:18:12 - mmengine - INFO - Epoch(train) [11][2600/3862] lr: 8.8249e-04 eta: 10:41:46 time: 1.0681 data_time: 0.0126 memory: 9497 grad_norm: 0.6998 loss: 1.5056 loss_heatmap: 0.6257 layer_-1_loss_cls: 0.0945 layer_-1_loss_bbox: 0.7854 matched_ious: 0.5416 2023/03/22 18:19:06 - mmengine - INFO - Epoch(train) [11][2650/3862] lr: 8.8140e-04 eta: 10:40:53 time: 1.0691 data_time: 0.0124 memory: 8921 grad_norm: 0.7131 loss: 1.5378 loss_heatmap: 0.6247 layer_-1_loss_cls: 0.0967 layer_-1_loss_bbox: 0.8164 matched_ious: 0.5314 2023/03/22 18:19:59 - mmengine - INFO - Epoch(train) [11][2700/3862] lr: 8.8030e-04 eta: 10:39:59 time: 1.0661 data_time: 0.0123 memory: 9285 grad_norm: 0.7462 loss: 1.4615 loss_heatmap: 0.6218 layer_-1_loss_cls: 0.0966 layer_-1_loss_bbox: 0.7432 matched_ious: 0.5578 2023/03/22 18:20:52 - mmengine - INFO - Epoch(train) [11][2750/3862] lr: 8.7920e-04 eta: 10:39:05 time: 1.0636 data_time: 0.0126 memory: 9292 grad_norm: 0.6992 loss: 1.5118 loss_heatmap: 0.6268 layer_-1_loss_cls: 0.0969 layer_-1_loss_bbox: 0.7882 matched_ious: 0.5384 2023/03/22 18:21:45 - mmengine - INFO - Epoch(train) [11][2800/3862] lr: 8.7809e-04 eta: 10:38:12 time: 1.0663 data_time: 0.0126 memory: 9091 grad_norm: 0.7816 loss: 1.5639 loss_heatmap: 0.6412 layer_-1_loss_cls: 0.0975 layer_-1_loss_bbox: 0.8253 matched_ious: 0.4837 2023/03/22 18:22:39 - mmengine - INFO - Epoch(train) [11][2850/3862] lr: 8.7698e-04 eta: 10:37:19 time: 1.0767 data_time: 0.0125 memory: 9162 grad_norm: 0.7744 loss: 1.5135 loss_heatmap: 0.6187 layer_-1_loss_cls: 0.0942 layer_-1_loss_bbox: 0.8006 matched_ious: 0.5319 2023/03/22 18:23:34 - mmengine - INFO - Epoch(train) [11][2900/3862] lr: 8.7587e-04 eta: 10:36:26 time: 1.0892 data_time: 0.0128 memory: 9165 grad_norm: 0.8203 loss: 1.5902 loss_heatmap: 0.6649 layer_-1_loss_cls: 0.0993 layer_-1_loss_bbox: 0.8259 matched_ious: 0.5716 2023/03/22 18:24:27 - mmengine - INFO - Epoch(train) [11][2950/3862] lr: 8.7475e-04 eta: 10:35:33 time: 1.0644 data_time: 0.0128 memory: 9360 grad_norm: 0.8154 loss: 1.4900 loss_heatmap: 0.6206 layer_-1_loss_cls: 0.0965 layer_-1_loss_bbox: 0.7730 matched_ious: 0.5456 2023/03/22 18:25:21 - mmengine - INFO - Epoch(train) [11][3000/3862] lr: 8.7362e-04 eta: 10:34:39 time: 1.0760 data_time: 0.0127 memory: 9174 grad_norm: 0.7183 loss: 1.4638 loss_heatmap: 0.6124 layer_-1_loss_cls: 0.0919 layer_-1_loss_bbox: 0.7595 matched_ious: 0.5447 2023/03/22 18:26:14 - mmengine - INFO - Epoch(train) [11][3050/3862] lr: 8.7249e-04 eta: 10:33:46 time: 1.0643 data_time: 0.0126 memory: 9190 grad_norm: 0.7440 loss: 1.4804 loss_heatmap: 0.6129 layer_-1_loss_cls: 0.0921 layer_-1_loss_bbox: 0.7754 matched_ious: 0.5316 2023/03/22 18:27:07 - mmengine - INFO - Epoch(train) [11][3100/3862] lr: 8.7136e-04 eta: 10:32:52 time: 1.0656 data_time: 0.0123 memory: 9268 grad_norm: 0.7122 loss: 1.4829 loss_heatmap: 0.6152 layer_-1_loss_cls: 0.0934 layer_-1_loss_bbox: 0.7743 matched_ious: 0.5473 2023/03/22 18:28:00 - mmengine - INFO - Epoch(train) [11][3150/3862] lr: 8.7022e-04 eta: 10:31:58 time: 1.0586 data_time: 0.0125 memory: 9116 grad_norm: 0.7793 loss: 1.4998 loss_heatmap: 0.6155 layer_-1_loss_cls: 0.0926 layer_-1_loss_bbox: 0.7917 matched_ious: 0.5509 2023/03/22 18:28:54 - mmengine - INFO - Epoch(train) [11][3200/3862] lr: 8.6908e-04 eta: 10:31:05 time: 1.0666 data_time: 0.0125 memory: 9035 grad_norm: 0.7168 loss: 1.5302 loss_heatmap: 0.6376 layer_-1_loss_cls: 0.0952 layer_-1_loss_bbox: 0.7975 matched_ious: 0.5618 2023/03/22 18:29:48 - mmengine - INFO - Epoch(train) [11][3250/3862] lr: 8.6794e-04 eta: 10:30:12 time: 1.0806 data_time: 0.0121 memory: 9071 grad_norm: 0.6928 loss: 1.4851 loss_heatmap: 0.6070 layer_-1_loss_cls: 0.0932 layer_-1_loss_bbox: 0.7849 matched_ious: 0.5438 2023/03/22 18:30:41 - mmengine - INFO - Epoch(train) [11][3300/3862] lr: 8.6679e-04 eta: 10:29:18 time: 1.0710 data_time: 0.0124 memory: 9589 grad_norm: 0.7142 loss: 1.5831 loss_heatmap: 0.6572 layer_-1_loss_cls: 0.0981 layer_-1_loss_bbox: 0.8277 matched_ious: 0.5084 2023/03/22 18:31:35 - mmengine - INFO - Epoch(train) [11][3350/3862] lr: 8.6563e-04 eta: 10:28:25 time: 1.0693 data_time: 0.0125 memory: 9011 grad_norm: 0.7022 loss: 1.4915 loss_heatmap: 0.6188 layer_-1_loss_cls: 0.0935 layer_-1_loss_bbox: 0.7792 matched_ious: 0.5502 2023/03/22 18:32:07 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 18:32:28 - mmengine - INFO - Epoch(train) [11][3400/3862] lr: 8.6448e-04 eta: 10:27:32 time: 1.0723 data_time: 0.0121 memory: 9374 grad_norm: 0.7487 loss: 1.5066 loss_heatmap: 0.6350 layer_-1_loss_cls: 0.0942 layer_-1_loss_bbox: 0.7774 matched_ious: 0.5147 2023/03/22 18:33:22 - mmengine - INFO - Epoch(train) [11][3450/3862] lr: 8.6331e-04 eta: 10:26:38 time: 1.0677 data_time: 0.0125 memory: 9118 grad_norm: 0.8077 loss: 1.4525 loss_heatmap: 0.6129 layer_-1_loss_cls: 0.0953 layer_-1_loss_bbox: 0.7443 matched_ious: 0.5127 2023/03/22 18:34:15 - mmengine - INFO - Epoch(train) [11][3500/3862] lr: 8.6215e-04 eta: 10:25:45 time: 1.0670 data_time: 0.0127 memory: 9184 grad_norm: 0.6969 loss: 1.5622 loss_heatmap: 0.6366 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.8302 matched_ious: 0.4808 2023/03/22 18:35:08 - mmengine - INFO - Epoch(train) [11][3550/3862] lr: 8.6098e-04 eta: 10:24:51 time: 1.0572 data_time: 0.0126 memory: 9418 grad_norm: 0.7398 loss: 1.4529 loss_heatmap: 0.6112 layer_-1_loss_cls: 0.0933 layer_-1_loss_bbox: 0.7484 matched_ious: 0.4630 2023/03/22 18:36:01 - mmengine - INFO - Epoch(train) [11][3600/3862] lr: 8.5980e-04 eta: 10:23:57 time: 1.0666 data_time: 0.0126 memory: 9174 grad_norm: 0.7583 loss: 1.4715 loss_heatmap: 0.6243 layer_-1_loss_cls: 0.0945 layer_-1_loss_bbox: 0.7527 matched_ious: 0.4961 2023/03/22 18:36:54 - mmengine - INFO - Epoch(train) [11][3650/3862] lr: 8.5862e-04 eta: 10:23:03 time: 1.0633 data_time: 0.0124 memory: 9116 grad_norm: 0.7106 loss: 1.5476 loss_heatmap: 0.6473 layer_-1_loss_cls: 0.0993 layer_-1_loss_bbox: 0.8009 matched_ious: 0.5481 2023/03/22 18:37:47 - mmengine - INFO - Epoch(train) [11][3700/3862] lr: 8.5744e-04 eta: 10:22:10 time: 1.0639 data_time: 0.0129 memory: 9532 grad_norm: 0.7090 loss: 1.4935 loss_heatmap: 0.6190 layer_-1_loss_cls: 0.0954 layer_-1_loss_bbox: 0.7790 matched_ious: 0.4857 2023/03/22 18:38:40 - mmengine - INFO - Epoch(train) [11][3750/3862] lr: 8.5625e-04 eta: 10:21:16 time: 1.0601 data_time: 0.0127 memory: 9376 grad_norm: 0.7416 loss: 1.4760 loss_heatmap: 0.6176 layer_-1_loss_cls: 0.0931 layer_-1_loss_bbox: 0.7652 matched_ious: 0.4980 2023/03/22 18:39:34 - mmengine - INFO - Epoch(train) [11][3800/3862] lr: 8.5506e-04 eta: 10:20:23 time: 1.0735 data_time: 0.0124 memory: 9381 grad_norm: 0.6564 loss: 1.5596 loss_heatmap: 0.6440 layer_-1_loss_cls: 0.0964 layer_-1_loss_bbox: 0.8192 matched_ious: 0.5278 2023/03/22 18:40:28 - mmengine - INFO - Epoch(train) [11][3850/3862] lr: 8.5387e-04 eta: 10:19:29 time: 1.0712 data_time: 0.0125 memory: 9289 grad_norm: 0.6865 loss: 1.5845 loss_heatmap: 0.6511 layer_-1_loss_cls: 0.0983 layer_-1_loss_bbox: 0.8350 matched_ious: 0.5465 2023/03/22 18:40:41 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 18:41:37 - mmengine - INFO - Epoch(train) [12][ 50/3862] lr: 8.5238e-04 eta: 10:18:25 time: 1.1227 data_time: 0.0584 memory: 9186 grad_norm: 0.7333 loss: 1.6115 loss_heatmap: 0.6529 layer_-1_loss_cls: 0.0975 layer_-1_loss_bbox: 0.8611 matched_ious: 0.5287 2023/03/22 18:42:30 - mmengine - INFO - Epoch(train) [12][ 100/3862] lr: 8.5117e-04 eta: 10:17:32 time: 1.0739 data_time: 0.0123 memory: 9480 grad_norm: 0.7149 loss: 1.4756 loss_heatmap: 0.6058 layer_-1_loss_cls: 0.0937 layer_-1_loss_bbox: 0.7761 matched_ious: 0.4949 2023/03/22 18:43:24 - mmengine - INFO - Epoch(train) [12][ 150/3862] lr: 8.4997e-04 eta: 10:16:39 time: 1.0746 data_time: 0.0123 memory: 9651 grad_norm: 0.7044 loss: 1.4516 loss_heatmap: 0.6044 layer_-1_loss_cls: 0.0931 layer_-1_loss_bbox: 0.7541 matched_ious: 0.5717 2023/03/22 18:44:18 - mmengine - INFO - Epoch(train) [12][ 200/3862] lr: 8.4875e-04 eta: 10:15:46 time: 1.0778 data_time: 0.0124 memory: 9171 grad_norm: 0.6780 loss: 1.5020 loss_heatmap: 0.6317 layer_-1_loss_cls: 0.0970 layer_-1_loss_bbox: 0.7732 matched_ious: 0.5671 2023/03/22 18:45:11 - mmengine - INFO - Epoch(train) [12][ 250/3862] lr: 8.4754e-04 eta: 10:14:52 time: 1.0649 data_time: 0.0124 memory: 9454 grad_norm: 0.7166 loss: 1.5412 loss_heatmap: 0.6387 layer_-1_loss_cls: 0.0961 layer_-1_loss_bbox: 0.8064 matched_ious: 0.5553 2023/03/22 18:46:05 - mmengine - INFO - Epoch(train) [12][ 300/3862] lr: 8.4632e-04 eta: 10:13:58 time: 1.0671 data_time: 0.0122 memory: 9302 grad_norm: 0.7580 loss: 1.5217 loss_heatmap: 0.6451 layer_-1_loss_cls: 0.0984 layer_-1_loss_bbox: 0.7782 matched_ious: 0.5405 2023/03/22 18:46:58 - mmengine - INFO - Epoch(train) [12][ 350/3862] lr: 8.4509e-04 eta: 10:13:05 time: 1.0698 data_time: 0.0123 memory: 9130 grad_norm: 0.7124 loss: 1.5407 loss_heatmap: 0.6276 layer_-1_loss_cls: 0.0939 layer_-1_loss_bbox: 0.8192 matched_ious: 0.4902 2023/03/22 18:47:51 - mmengine - INFO - Epoch(train) [12][ 400/3862] lr: 8.4386e-04 eta: 10:12:11 time: 1.0624 data_time: 0.0125 memory: 9274 grad_norm: 0.6795 loss: 1.4885 loss_heatmap: 0.6303 layer_-1_loss_cls: 0.0947 layer_-1_loss_bbox: 0.7635 matched_ious: 0.5652 2023/03/22 18:48:45 - mmengine - INFO - Epoch(train) [12][ 450/3862] lr: 8.4263e-04 eta: 10:11:18 time: 1.0660 data_time: 0.0124 memory: 9115 grad_norm: 0.7121 loss: 1.5219 loss_heatmap: 0.6335 layer_-1_loss_cls: 0.0937 layer_-1_loss_bbox: 0.7947 matched_ious: 0.5318 2023/03/22 18:49:38 - mmengine - INFO - Epoch(train) [12][ 500/3862] lr: 8.4140e-04 eta: 10:10:24 time: 1.0638 data_time: 0.0126 memory: 9191 grad_norm: 0.7683 loss: 1.5478 loss_heatmap: 0.6350 layer_-1_loss_cls: 0.0967 layer_-1_loss_bbox: 0.8161 matched_ious: 0.5362 2023/03/22 18:49:57 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 18:50:31 - mmengine - INFO - Epoch(train) [12][ 550/3862] lr: 8.4016e-04 eta: 10:09:31 time: 1.0678 data_time: 0.0122 memory: 9220 grad_norm: 0.7431 loss: 1.5767 loss_heatmap: 0.6429 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.8362 matched_ious: 0.5469 2023/03/22 18:51:25 - mmengine - INFO - Epoch(train) [12][ 600/3862] lr: 8.3891e-04 eta: 10:08:37 time: 1.0710 data_time: 0.0129 memory: 9098 grad_norm: 0.7154 loss: 1.5414 loss_heatmap: 0.6458 layer_-1_loss_cls: 0.0978 layer_-1_loss_bbox: 0.7978 matched_ious: 0.5770 2023/03/22 18:52:18 - mmengine - INFO - Epoch(train) [12][ 650/3862] lr: 8.3766e-04 eta: 10:07:44 time: 1.0692 data_time: 0.0125 memory: 9249 grad_norm: 0.7408 loss: 1.5025 loss_heatmap: 0.6204 layer_-1_loss_cls: 0.0962 layer_-1_loss_bbox: 0.7859 matched_ious: 0.5598 2023/03/22 18:53:12 - mmengine - INFO - Epoch(train) [12][ 700/3862] lr: 8.3641e-04 eta: 10:06:50 time: 1.0674 data_time: 0.0123 memory: 9164 grad_norm: 0.8496 loss: 1.4906 loss_heatmap: 0.6242 layer_-1_loss_cls: 0.0960 layer_-1_loss_bbox: 0.7704 matched_ious: 0.5255 2023/03/22 18:54:04 - mmengine - INFO - Epoch(train) [12][ 750/3862] lr: 8.3516e-04 eta: 10:05:56 time: 1.0553 data_time: 0.0121 memory: 9174 grad_norm: 0.8368 loss: 1.4824 loss_heatmap: 0.6207 layer_-1_loss_cls: 0.0963 layer_-1_loss_bbox: 0.7654 matched_ious: 0.5562 2023/03/22 18:54:58 - mmengine - INFO - Epoch(train) [12][ 800/3862] lr: 8.3390e-04 eta: 10:05:03 time: 1.0679 data_time: 0.0125 memory: 9267 grad_norm: 0.6876 loss: 1.5136 loss_heatmap: 0.6207 layer_-1_loss_cls: 0.0952 layer_-1_loss_bbox: 0.7978 matched_ious: 0.5481 2023/03/22 18:55:51 - mmengine - INFO - Epoch(train) [12][ 850/3862] lr: 8.3263e-04 eta: 10:04:09 time: 1.0715 data_time: 0.0122 memory: 9164 grad_norm: 0.6959 loss: 1.5820 loss_heatmap: 0.6425 layer_-1_loss_cls: 0.0989 layer_-1_loss_bbox: 0.8405 matched_ious: 0.5306 2023/03/22 18:56:45 - mmengine - INFO - Epoch(train) [12][ 900/3862] lr: 8.3137e-04 eta: 10:03:16 time: 1.0665 data_time: 0.0123 memory: 9162 grad_norm: 0.6885 loss: 1.5207 loss_heatmap: 0.6411 layer_-1_loss_cls: 0.0975 layer_-1_loss_bbox: 0.7821 matched_ious: 0.5169 2023/03/22 18:57:38 - mmengine - INFO - Epoch(train) [12][ 950/3862] lr: 8.3009e-04 eta: 10:02:22 time: 1.0675 data_time: 0.0121 memory: 9183 grad_norm: 0.7203 loss: 1.5255 loss_heatmap: 0.6325 layer_-1_loss_cls: 0.0959 layer_-1_loss_bbox: 0.7971 matched_ious: 0.5631 2023/03/22 18:58:32 - mmengine - INFO - Epoch(train) [12][1000/3862] lr: 8.2882e-04 eta: 10:01:29 time: 1.0724 data_time: 0.0123 memory: 9025 grad_norm: 0.7794 loss: 1.4962 loss_heatmap: 0.6298 layer_-1_loss_cls: 0.0950 layer_-1_loss_bbox: 0.7714 matched_ious: 0.5767 2023/03/22 18:59:25 - mmengine - INFO - Epoch(train) [12][1050/3862] lr: 8.2754e-04 eta: 10:00:36 time: 1.0726 data_time: 0.0121 memory: 8938 grad_norm: 0.6704 loss: 1.5429 loss_heatmap: 0.6417 layer_-1_loss_cls: 0.0975 layer_-1_loss_bbox: 0.8037 matched_ious: 0.5336 2023/03/22 19:00:19 - mmengine - INFO - Epoch(train) [12][1100/3862] lr: 8.2626e-04 eta: 9:59:42 time: 1.0730 data_time: 0.0125 memory: 9237 grad_norm: 0.7105 loss: 1.4292 loss_heatmap: 0.5915 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.7458 matched_ious: 0.5285 2023/03/22 19:01:12 - mmengine - INFO - Epoch(train) [12][1150/3862] lr: 8.2497e-04 eta: 9:58:49 time: 1.0667 data_time: 0.0123 memory: 9078 grad_norm: 0.8564 loss: 1.4975 loss_heatmap: 0.6283 layer_-1_loss_cls: 0.0957 layer_-1_loss_bbox: 0.7736 matched_ious: 0.4785 2023/03/22 19:02:06 - mmengine - INFO - Epoch(train) [12][1200/3862] lr: 8.2368e-04 eta: 9:57:56 time: 1.0746 data_time: 0.0128 memory: 9170 grad_norm: 0.7565 loss: 1.4870 loss_heatmap: 0.6196 layer_-1_loss_cls: 0.0939 layer_-1_loss_bbox: 0.7735 matched_ious: 0.5549 2023/03/22 19:03:00 - mmengine - INFO - Epoch(train) [12][1250/3862] lr: 8.2239e-04 eta: 9:57:02 time: 1.0718 data_time: 0.0122 memory: 9095 grad_norm: 0.7063 loss: 1.4458 loss_heatmap: 0.6118 layer_-1_loss_cls: 0.0933 layer_-1_loss_bbox: 0.7408 matched_ious: 0.5590 2023/03/22 19:03:54 - mmengine - INFO - Epoch(train) [12][1300/3862] lr: 8.2109e-04 eta: 9:56:09 time: 1.0796 data_time: 0.0123 memory: 9138 grad_norm: 0.7084 loss: 1.4675 loss_heatmap: 0.6077 layer_-1_loss_cls: 0.0951 layer_-1_loss_bbox: 0.7647 matched_ious: 0.5210 2023/03/22 19:04:48 - mmengine - INFO - Epoch(train) [12][1350/3862] lr: 8.1979e-04 eta: 9:55:16 time: 1.0817 data_time: 0.0123 memory: 9262 grad_norm: 0.7080 loss: 1.4654 loss_heatmap: 0.5994 layer_-1_loss_cls: 0.0900 layer_-1_loss_bbox: 0.7761 matched_ious: 0.5449 2023/03/22 19:05:41 - mmengine - INFO - Epoch(train) [12][1400/3862] lr: 8.1849e-04 eta: 9:54:23 time: 1.0718 data_time: 0.0125 memory: 9042 grad_norm: 0.7588 loss: 1.4490 loss_heatmap: 0.5928 layer_-1_loss_cls: 0.0913 layer_-1_loss_bbox: 0.7649 matched_ious: 0.5680 2023/03/22 19:06:35 - mmengine - INFO - Epoch(train) [12][1450/3862] lr: 8.1718e-04 eta: 9:53:30 time: 1.0734 data_time: 0.0123 memory: 9106 grad_norm: 0.6929 loss: 1.5401 loss_heatmap: 0.6389 layer_-1_loss_cls: 0.0995 layer_-1_loss_bbox: 0.8018 matched_ious: 0.4944 2023/03/22 19:07:28 - mmengine - INFO - Epoch(train) [12][1500/3862] lr: 8.1587e-04 eta: 9:52:36 time: 1.0624 data_time: 0.0123 memory: 9521 grad_norm: 0.6806 loss: 1.4848 loss_heatmap: 0.6238 layer_-1_loss_cls: 0.0970 layer_-1_loss_bbox: 0.7641 matched_ious: 0.5272 2023/03/22 19:07:47 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 19:08:22 - mmengine - INFO - Epoch(train) [12][1550/3862] lr: 8.1455e-04 eta: 9:51:42 time: 1.0723 data_time: 0.0121 memory: 9187 grad_norm: 0.7209 loss: 1.4824 loss_heatmap: 0.6153 layer_-1_loss_cls: 0.0930 layer_-1_loss_bbox: 0.7741 matched_ious: 0.5419 2023/03/22 19:09:15 - mmengine - INFO - Epoch(train) [12][1600/3862] lr: 8.1323e-04 eta: 9:50:49 time: 1.0728 data_time: 0.0126 memory: 9336 grad_norm: 0.9866 loss: 1.4983 loss_heatmap: 0.6234 layer_-1_loss_cls: 0.0981 layer_-1_loss_bbox: 0.7769 matched_ious: 0.5480 2023/03/22 19:10:09 - mmengine - INFO - Epoch(train) [12][1650/3862] lr: 8.1191e-04 eta: 9:49:56 time: 1.0746 data_time: 0.0121 memory: 9124 grad_norm: 0.7387 loss: 1.5243 loss_heatmap: 0.6270 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.8017 matched_ious: 0.5375 2023/03/22 19:11:03 - mmengine - INFO - Epoch(train) [12][1700/3862] lr: 8.1058e-04 eta: 9:49:03 time: 1.0721 data_time: 0.0121 memory: 9267 grad_norm: 0.7847 loss: 1.5076 loss_heatmap: 0.6314 layer_-1_loss_cls: 0.0945 layer_-1_loss_bbox: 0.7816 matched_ious: 0.5204 2023/03/22 19:11:56 - mmengine - INFO - Epoch(train) [12][1750/3862] lr: 8.0925e-04 eta: 9:48:09 time: 1.0584 data_time: 0.0125 memory: 8998 grad_norm: 0.7060 loss: 1.4714 loss_heatmap: 0.6227 layer_-1_loss_cls: 0.0940 layer_-1_loss_bbox: 0.7547 matched_ious: 0.5256 2023/03/22 19:12:49 - mmengine - INFO - Epoch(train) [12][1800/3862] lr: 8.0792e-04 eta: 9:47:15 time: 1.0656 data_time: 0.0127 memory: 9150 grad_norm: 0.6823 loss: 1.5149 loss_heatmap: 0.6366 layer_-1_loss_cls: 0.0965 layer_-1_loss_bbox: 0.7818 matched_ious: 0.5782 2023/03/22 19:13:43 - mmengine - INFO - Epoch(train) [12][1850/3862] lr: 8.0658e-04 eta: 9:46:22 time: 1.0743 data_time: 0.0130 memory: 9158 grad_norm: 0.8115 loss: 1.5290 loss_heatmap: 0.6227 layer_-1_loss_cls: 0.0946 layer_-1_loss_bbox: 0.8117 matched_ious: 0.4614 2023/03/22 19:14:36 - mmengine - INFO - Epoch(train) [12][1900/3862] lr: 8.0524e-04 eta: 9:45:29 time: 1.0763 data_time: 0.0125 memory: 9103 grad_norm: 0.7542 loss: 1.5133 loss_heatmap: 0.6272 layer_-1_loss_cls: 0.0951 layer_-1_loss_bbox: 0.7910 matched_ious: 0.5319 2023/03/22 19:15:30 - mmengine - INFO - Epoch(train) [12][1950/3862] lr: 8.0390e-04 eta: 9:44:35 time: 1.0713 data_time: 0.0129 memory: 9464 grad_norm: 0.8174 loss: 1.4439 loss_heatmap: 0.6079 layer_-1_loss_cls: 0.0924 layer_-1_loss_bbox: 0.7435 matched_ious: 0.5363 2023/03/22 19:16:24 - mmengine - INFO - Epoch(train) [12][2000/3862] lr: 8.0255e-04 eta: 9:43:42 time: 1.0784 data_time: 0.0126 memory: 9113 grad_norm: 0.6952 loss: 1.5078 loss_heatmap: 0.6359 layer_-1_loss_cls: 0.0951 layer_-1_loss_bbox: 0.7769 matched_ious: 0.5190 2023/03/22 19:17:17 - mmengine - INFO - Epoch(train) [12][2050/3862] lr: 8.0120e-04 eta: 9:42:49 time: 1.0647 data_time: 0.0124 memory: 9038 grad_norm: 0.7535 loss: 1.5489 loss_heatmap: 0.6337 layer_-1_loss_cls: 0.0964 layer_-1_loss_bbox: 0.8188 matched_ious: 0.5542 2023/03/22 19:18:11 - mmengine - INFO - Epoch(train) [12][2100/3862] lr: 7.9985e-04 eta: 9:41:55 time: 1.0665 data_time: 0.0124 memory: 9259 grad_norm: 1.0514 loss: 1.5460 loss_heatmap: 0.6433 layer_-1_loss_cls: 0.1001 layer_-1_loss_bbox: 0.8025 matched_ious: 0.5662 2023/03/22 19:19:04 - mmengine - INFO - Epoch(train) [12][2150/3862] lr: 7.9849e-04 eta: 9:41:02 time: 1.0725 data_time: 0.0126 memory: 9200 grad_norm: 0.6207 loss: 1.5093 loss_heatmap: 0.6181 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.7958 matched_ious: 0.5113 2023/03/22 19:19:58 - mmengine - INFO - Epoch(train) [12][2200/3862] lr: 7.9713e-04 eta: 9:40:08 time: 1.0687 data_time: 0.0129 memory: 9142 grad_norm: 0.6767 loss: 1.3928 loss_heatmap: 0.5941 layer_-1_loss_cls: 0.0935 layer_-1_loss_bbox: 0.7052 matched_ious: 0.5399 2023/03/22 19:20:51 - mmengine - INFO - Epoch(train) [12][2250/3862] lr: 7.9576e-04 eta: 9:39:15 time: 1.0771 data_time: 0.0126 memory: 9155 grad_norm: 0.7947 loss: 1.5496 loss_heatmap: 0.6342 layer_-1_loss_cls: 0.0964 layer_-1_loss_bbox: 0.8189 matched_ious: 0.5196 2023/03/22 19:21:45 - mmengine - INFO - Epoch(train) [12][2300/3862] lr: 7.9439e-04 eta: 9:38:22 time: 1.0704 data_time: 0.0124 memory: 9368 grad_norm: 0.7769 loss: 1.5188 loss_heatmap: 0.6310 layer_-1_loss_cls: 0.0957 layer_-1_loss_bbox: 0.7922 matched_ious: 0.4952 2023/03/22 19:22:39 - mmengine - INFO - Epoch(train) [12][2350/3862] lr: 7.9302e-04 eta: 9:37:28 time: 1.0717 data_time: 0.0124 memory: 9192 grad_norm: 0.7286 loss: 1.4788 loss_heatmap: 0.6031 layer_-1_loss_cls: 0.0906 layer_-1_loss_bbox: 0.7850 matched_ious: 0.4853 2023/03/22 19:23:32 - mmengine - INFO - Epoch(train) [12][2400/3862] lr: 7.9165e-04 eta: 9:36:35 time: 1.0746 data_time: 0.0127 memory: 9160 grad_norm: 0.7388 loss: 1.4993 loss_heatmap: 0.6189 layer_-1_loss_cls: 0.0954 layer_-1_loss_bbox: 0.7849 matched_ious: 0.5085 2023/03/22 19:24:26 - mmengine - INFO - Epoch(train) [12][2450/3862] lr: 7.9027e-04 eta: 9:35:42 time: 1.0761 data_time: 0.0126 memory: 9165 grad_norm: 0.6958 loss: 1.4910 loss_heatmap: 0.6082 layer_-1_loss_cls: 0.0957 layer_-1_loss_bbox: 0.7872 matched_ious: 0.5059 2023/03/22 19:25:20 - mmengine - INFO - Epoch(train) [12][2500/3862] lr: 7.8889e-04 eta: 9:34:49 time: 1.0756 data_time: 0.0122 memory: 9259 grad_norm: 0.8005 loss: 1.5137 loss_heatmap: 0.6130 layer_-1_loss_cls: 0.0917 layer_-1_loss_bbox: 0.8090 matched_ious: 0.5110 2023/03/22 19:25:39 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 19:26:13 - mmengine - INFO - Epoch(train) [12][2550/3862] lr: 7.8750e-04 eta: 9:33:55 time: 1.0678 data_time: 0.0127 memory: 9070 grad_norm: 0.7367 loss: 1.5325 loss_heatmap: 0.6164 layer_-1_loss_cls: 0.0925 layer_-1_loss_bbox: 0.8235 matched_ious: 0.5367 2023/03/22 19:27:06 - mmengine - INFO - Epoch(train) [12][2600/3862] lr: 7.8611e-04 eta: 9:33:01 time: 1.0609 data_time: 0.0120 memory: 9568 grad_norm: 0.7239 loss: 1.4785 loss_heatmap: 0.6184 layer_-1_loss_cls: 0.0952 layer_-1_loss_bbox: 0.7649 matched_ious: 0.5009 2023/03/22 19:28:00 - mmengine - INFO - Epoch(train) [12][2650/3862] lr: 7.8472e-04 eta: 9:32:08 time: 1.0642 data_time: 0.0122 memory: 9059 grad_norm: 0.9415 loss: 1.4907 loss_heatmap: 0.6275 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.7677 matched_ious: 0.5294 2023/03/22 19:28:53 - mmengine - INFO - Epoch(train) [12][2700/3862] lr: 7.8333e-04 eta: 9:31:14 time: 1.0649 data_time: 0.0121 memory: 9592 grad_norm: 0.7822 loss: 1.4938 loss_heatmap: 0.6130 layer_-1_loss_cls: 0.0932 layer_-1_loss_bbox: 0.7876 matched_ious: 0.5048 2023/03/22 19:29:46 - mmengine - INFO - Epoch(train) [12][2750/3862] lr: 7.8193e-04 eta: 9:30:20 time: 1.0645 data_time: 0.0123 memory: 9188 grad_norm: 0.8577 loss: 1.4963 loss_heatmap: 0.6199 layer_-1_loss_cls: 0.0947 layer_-1_loss_bbox: 0.7817 matched_ious: 0.5191 2023/03/22 19:30:39 - mmengine - INFO - Epoch(train) [12][2800/3862] lr: 7.8053e-04 eta: 9:29:27 time: 1.0668 data_time: 0.0122 memory: 9491 grad_norm: 0.8452 loss: 1.5242 loss_heatmap: 0.6418 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.7870 matched_ious: 0.5182 2023/03/22 19:31:32 - mmengine - INFO - Epoch(train) [12][2850/3862] lr: 7.7912e-04 eta: 9:28:33 time: 1.0610 data_time: 0.0117 memory: 8909 grad_norm: 0.7465 loss: 1.4379 loss_heatmap: 0.6191 layer_-1_loss_cls: 0.0922 layer_-1_loss_bbox: 0.7266 matched_ious: 0.5279 2023/03/22 19:32:26 - mmengine - INFO - Epoch(train) [12][2900/3862] lr: 7.7772e-04 eta: 9:27:40 time: 1.0702 data_time: 0.0123 memory: 9065 grad_norm: 0.7069 loss: 1.5043 loss_heatmap: 0.6234 layer_-1_loss_cls: 0.0929 layer_-1_loss_bbox: 0.7880 matched_ious: 0.5355 2023/03/22 19:33:20 - mmengine - INFO - Epoch(train) [12][2950/3862] lr: 7.7631e-04 eta: 9:26:46 time: 1.0746 data_time: 0.0122 memory: 9311 grad_norm: 0.7427 loss: 1.4304 loss_heatmap: 0.6024 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.7360 matched_ious: 0.5349 2023/03/22 19:34:13 - mmengine - INFO - Epoch(train) [12][3000/3862] lr: 7.7489e-04 eta: 9:25:53 time: 1.0656 data_time: 0.0122 memory: 9134 grad_norm: 0.7147 loss: 1.4755 loss_heatmap: 0.6096 layer_-1_loss_cls: 0.0914 layer_-1_loss_bbox: 0.7745 matched_ious: 0.5187 2023/03/22 19:35:06 - mmengine - INFO - Epoch(train) [12][3050/3862] lr: 7.7347e-04 eta: 9:24:59 time: 1.0679 data_time: 0.0119 memory: 9288 grad_norm: 0.7222 loss: 1.4978 loss_heatmap: 0.6197 layer_-1_loss_cls: 0.0963 layer_-1_loss_bbox: 0.7819 matched_ious: 0.5200 2023/03/22 19:35:59 - mmengine - INFO - Epoch(train) [12][3100/3862] lr: 7.7205e-04 eta: 9:24:06 time: 1.0628 data_time: 0.0119 memory: 9174 grad_norm: 0.6735 loss: 1.5740 loss_heatmap: 0.6221 layer_-1_loss_cls: 0.0953 layer_-1_loss_bbox: 0.8567 matched_ious: 0.5567 2023/03/22 19:36:53 - mmengine - INFO - Epoch(train) [12][3150/3862] lr: 7.7063e-04 eta: 9:23:12 time: 1.0665 data_time: 0.0118 memory: 9200 grad_norm: 0.7250 loss: 1.5228 loss_heatmap: 0.6458 layer_-1_loss_cls: 0.0956 layer_-1_loss_bbox: 0.7813 matched_ious: 0.5461 2023/03/22 19:37:46 - mmengine - INFO - Epoch(train) [12][3200/3862] lr: 7.6920e-04 eta: 9:22:19 time: 1.0725 data_time: 0.0243 memory: 9182 grad_norm: 0.6775 loss: 1.4820 loss_heatmap: 0.6136 layer_-1_loss_cls: 0.0949 layer_-1_loss_bbox: 0.7735 matched_ious: 0.5224 2023/03/22 19:38:40 - mmengine - INFO - Epoch(train) [12][3250/3862] lr: 7.6777e-04 eta: 9:21:25 time: 1.0657 data_time: 0.0124 memory: 9470 grad_norm: 0.6850 loss: 1.4688 loss_heatmap: 0.6126 layer_-1_loss_cls: 0.0939 layer_-1_loss_bbox: 0.7622 matched_ious: 0.5378 2023/03/22 19:39:33 - mmengine - INFO - Epoch(train) [12][3300/3862] lr: 7.6634e-04 eta: 9:20:32 time: 1.0639 data_time: 0.0118 memory: 9164 grad_norm: 0.6946 loss: 1.5554 loss_heatmap: 0.6301 layer_-1_loss_cls: 0.0940 layer_-1_loss_bbox: 0.8313 matched_ious: 0.5417 2023/03/22 19:40:26 - mmengine - INFO - Epoch(train) [12][3350/3862] lr: 7.6491e-04 eta: 9:19:38 time: 1.0660 data_time: 0.0121 memory: 9116 grad_norm: 0.7082 loss: 1.4476 loss_heatmap: 0.6063 layer_-1_loss_cls: 0.0933 layer_-1_loss_bbox: 0.7481 matched_ious: 0.5536 2023/03/22 19:41:20 - mmengine - INFO - Epoch(train) [12][3400/3862] lr: 7.6347e-04 eta: 9:18:45 time: 1.0690 data_time: 0.0123 memory: 9143 grad_norm: 0.6600 loss: 1.4721 loss_heatmap: 0.6048 layer_-1_loss_cls: 0.0914 layer_-1_loss_bbox: 0.7758 matched_ious: 0.5398 2023/03/22 19:42:13 - mmengine - INFO - Epoch(train) [12][3450/3862] lr: 7.6203e-04 eta: 9:17:51 time: 1.0707 data_time: 0.0121 memory: 9173 grad_norm: 0.6722 loss: 1.4940 loss_heatmap: 0.6079 layer_-1_loss_cls: 0.0929 layer_-1_loss_bbox: 0.7932 matched_ious: 0.5265 2023/03/22 19:43:07 - mmengine - INFO - Epoch(train) [12][3500/3862] lr: 7.6058e-04 eta: 9:16:58 time: 1.0665 data_time: 0.0121 memory: 9123 grad_norm: 0.7130 loss: 1.5284 loss_heatmap: 0.6272 layer_-1_loss_cls: 0.0948 layer_-1_loss_bbox: 0.8064 matched_ious: 0.5234 2023/03/22 19:43:26 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 19:44:00 - mmengine - INFO - Epoch(train) [12][3550/3862] lr: 7.5913e-04 eta: 9:16:04 time: 1.0617 data_time: 0.0123 memory: 9153 grad_norm: 0.7690 loss: 1.5086 loss_heatmap: 0.6106 layer_-1_loss_cls: 0.0928 layer_-1_loss_bbox: 0.8051 matched_ious: 0.5360 2023/03/22 19:44:54 - mmengine - INFO - Epoch(train) [12][3600/3862] lr: 7.5768e-04 eta: 9:15:11 time: 1.0904 data_time: 0.0124 memory: 9077 grad_norm: 0.6854 loss: 1.4781 loss_heatmap: 0.6143 layer_-1_loss_cls: 0.0908 layer_-1_loss_bbox: 0.7730 matched_ious: 0.5785 2023/03/22 19:45:48 - mmengine - INFO - Epoch(train) [12][3650/3862] lr: 7.5623e-04 eta: 9:14:18 time: 1.0686 data_time: 0.0123 memory: 9235 grad_norm: 0.7878 loss: 1.4509 loss_heatmap: 0.6010 layer_-1_loss_cls: 0.0919 layer_-1_loss_bbox: 0.7580 matched_ious: 0.5248 2023/03/22 19:46:41 - mmengine - INFO - Epoch(train) [12][3700/3862] lr: 7.5477e-04 eta: 9:13:24 time: 1.0667 data_time: 0.0124 memory: 9160 grad_norm: 0.7365 loss: 1.4368 loss_heatmap: 0.5974 layer_-1_loss_cls: 0.0921 layer_-1_loss_bbox: 0.7474 matched_ious: 0.5450 2023/03/22 19:47:34 - mmengine - INFO - Epoch(train) [12][3750/3862] lr: 7.5331e-04 eta: 9:12:30 time: 1.0609 data_time: 0.0121 memory: 9049 grad_norm: 0.7204 loss: 1.4660 loss_heatmap: 0.6137 layer_-1_loss_cls: 0.0915 layer_-1_loss_bbox: 0.7608 matched_ious: 0.5424 2023/03/22 19:48:28 - mmengine - INFO - Epoch(train) [12][3800/3862] lr: 7.5185e-04 eta: 9:11:37 time: 1.0719 data_time: 0.0122 memory: 9239 grad_norm: 0.7507 loss: 1.4101 loss_heatmap: 0.5884 layer_-1_loss_cls: 0.0900 layer_-1_loss_bbox: 0.7317 matched_ious: 0.4973 2023/03/22 19:49:21 - mmengine - INFO - Epoch(train) [12][3850/3862] lr: 7.5038e-04 eta: 9:10:44 time: 1.0683 data_time: 0.0122 memory: 9257 grad_norm: 0.7019 loss: 1.4608 loss_heatmap: 0.6105 layer_-1_loss_cls: 0.0932 layer_-1_loss_bbox: 0.7572 matched_ious: 0.5685 2023/03/22 19:49:34 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 19:50:30 - mmengine - INFO - Epoch(train) [13][ 50/3862] lr: 7.4856e-04 eta: 9:09:39 time: 1.1162 data_time: 0.0533 memory: 9071 grad_norm: 0.7000 loss: 1.5270 loss_heatmap: 0.6273 layer_-1_loss_cls: 0.0971 layer_-1_loss_bbox: 0.8027 matched_ious: 0.5271 2023/03/22 19:51:23 - mmengine - INFO - Epoch(train) [13][ 100/3862] lr: 7.4709e-04 eta: 9:08:45 time: 1.0650 data_time: 0.0120 memory: 9023 grad_norm: 0.7302 loss: 1.4227 loss_heatmap: 0.5961 layer_-1_loss_cls: 0.0908 layer_-1_loss_bbox: 0.7358 matched_ious: 0.5355 2023/03/22 19:52:16 - mmengine - INFO - Epoch(train) [13][ 150/3862] lr: 7.4562e-04 eta: 9:07:52 time: 1.0661 data_time: 0.0123 memory: 9145 grad_norm: 0.7314 loss: 1.5072 loss_heatmap: 0.6247 layer_-1_loss_cls: 0.0954 layer_-1_loss_bbox: 0.7872 matched_ious: 0.5537 2023/03/22 19:53:09 - mmengine - INFO - Epoch(train) [13][ 200/3862] lr: 7.4414e-04 eta: 9:06:58 time: 1.0649 data_time: 0.0122 memory: 9436 grad_norm: 0.7260 loss: 1.5405 loss_heatmap: 0.6123 layer_-1_loss_cls: 0.0931 layer_-1_loss_bbox: 0.8351 matched_ious: 0.5336 2023/03/22 19:54:03 - mmengine - INFO - Epoch(train) [13][ 250/3862] lr: 7.4266e-04 eta: 9:06:05 time: 1.0655 data_time: 0.0121 memory: 9035 grad_norm: 0.6385 loss: 1.4689 loss_heatmap: 0.6165 layer_-1_loss_cls: 0.0930 layer_-1_loss_bbox: 0.7593 matched_ious: 0.5074 2023/03/22 19:54:57 - mmengine - INFO - Epoch(train) [13][ 300/3862] lr: 7.4118e-04 eta: 9:05:11 time: 1.0769 data_time: 0.0122 memory: 9271 grad_norm: 0.7378 loss: 1.5036 loss_heatmap: 0.6117 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.7998 matched_ious: 0.5640 2023/03/22 19:55:50 - mmengine - INFO - Epoch(train) [13][ 350/3862] lr: 7.3969e-04 eta: 9:04:18 time: 1.0714 data_time: 0.0122 memory: 9169 grad_norm: 0.7282 loss: 1.3898 loss_heatmap: 0.5761 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.7279 matched_ious: 0.5060 2023/03/22 19:56:43 - mmengine - INFO - Epoch(train) [13][ 400/3862] lr: 7.3820e-04 eta: 9:03:24 time: 1.0665 data_time: 0.0124 memory: 9267 grad_norm: 0.6989 loss: 1.4585 loss_heatmap: 0.6193 layer_-1_loss_cls: 0.0948 layer_-1_loss_bbox: 0.7444 matched_ious: 0.5732 2023/03/22 19:57:37 - mmengine - INFO - Epoch(train) [13][ 450/3862] lr: 7.3671e-04 eta: 9:02:31 time: 1.0658 data_time: 0.0125 memory: 9219 grad_norm: 1.0031 loss: 1.4508 loss_heatmap: 0.6000 layer_-1_loss_cls: 0.0927 layer_-1_loss_bbox: 0.7581 matched_ious: 0.5224 2023/03/22 19:58:30 - mmengine - INFO - Epoch(train) [13][ 500/3862] lr: 7.3522e-04 eta: 9:01:37 time: 1.0641 data_time: 0.0122 memory: 9238 grad_norm: 0.6925 loss: 1.5066 loss_heatmap: 0.6163 layer_-1_loss_cls: 0.0909 layer_-1_loss_bbox: 0.7995 matched_ious: 0.5718 2023/03/22 19:59:24 - mmengine - INFO - Epoch(train) [13][ 550/3862] lr: 7.3372e-04 eta: 9:00:44 time: 1.0781 data_time: 0.0122 memory: 9227 grad_norm: 0.7319 loss: 1.5251 loss_heatmap: 0.6324 layer_-1_loss_cls: 0.0950 layer_-1_loss_bbox: 0.7978 matched_ious: 0.4905 2023/03/22 20:00:17 - mmengine - INFO - Epoch(train) [13][ 600/3862] lr: 7.3222e-04 eta: 8:59:51 time: 1.0709 data_time: 0.0122 memory: 9193 grad_norm: 0.7708 loss: 1.4519 loss_heatmap: 0.6063 layer_-1_loss_cls: 0.0919 layer_-1_loss_bbox: 0.7537 matched_ious: 0.5715 2023/03/22 20:01:11 - mmengine - INFO - Epoch(train) [13][ 650/3862] lr: 7.3072e-04 eta: 8:58:57 time: 1.0676 data_time: 0.0121 memory: 9314 grad_norm: 0.6800 loss: 1.4544 loss_heatmap: 0.6114 layer_-1_loss_cls: 0.0935 layer_-1_loss_bbox: 0.7494 matched_ious: 0.5336 2023/03/22 20:01:17 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 20:02:04 - mmengine - INFO - Epoch(train) [13][ 700/3862] lr: 7.2921e-04 eta: 8:58:04 time: 1.0683 data_time: 0.0123 memory: 9237 grad_norm: 0.7417 loss: 1.4647 loss_heatmap: 0.6062 layer_-1_loss_cls: 0.0916 layer_-1_loss_bbox: 0.7669 matched_ious: 0.5477 2023/03/22 20:02:58 - mmengine - INFO - Epoch(train) [13][ 750/3862] lr: 7.2770e-04 eta: 8:57:10 time: 1.0678 data_time: 0.0120 memory: 9175 grad_norm: 0.7790 loss: 1.4454 loss_heatmap: 0.5879 layer_-1_loss_cls: 0.0877 layer_-1_loss_bbox: 0.7698 matched_ious: 0.5224 2023/03/22 20:03:51 - mmengine - INFO - Epoch(train) [13][ 800/3862] lr: 7.2619e-04 eta: 8:56:17 time: 1.0655 data_time: 0.0119 memory: 9205 grad_norm: 0.7413 loss: 1.4249 loss_heatmap: 0.6042 layer_-1_loss_cls: 0.0924 layer_-1_loss_bbox: 0.7283 matched_ious: 0.4932 2023/03/22 20:04:45 - mmengine - INFO - Epoch(train) [13][ 850/3862] lr: 7.2468e-04 eta: 8:55:23 time: 1.0785 data_time: 0.0119 memory: 9069 grad_norm: 0.7959 loss: 1.4970 loss_heatmap: 0.6119 layer_-1_loss_cls: 0.0939 layer_-1_loss_bbox: 0.7912 matched_ious: 0.5563 2023/03/22 20:05:39 - mmengine - INFO - Epoch(train) [13][ 900/3862] lr: 7.2317e-04 eta: 8:54:30 time: 1.0766 data_time: 0.0120 memory: 9517 grad_norm: 0.6478 loss: 1.4795 loss_heatmap: 0.6031 layer_-1_loss_cls: 0.0930 layer_-1_loss_bbox: 0.7834 matched_ious: 0.5122 2023/03/22 20:06:33 - mmengine - INFO - Epoch(train) [13][ 950/3862] lr: 7.2165e-04 eta: 8:53:37 time: 1.0773 data_time: 0.0122 memory: 9088 grad_norm: 0.6490 loss: 1.4224 loss_heatmap: 0.5899 layer_-1_loss_cls: 0.0906 layer_-1_loss_bbox: 0.7419 matched_ious: 0.5152 2023/03/22 20:07:26 - mmengine - INFO - Epoch(train) [13][1000/3862] lr: 7.2013e-04 eta: 8:52:44 time: 1.0687 data_time: 0.0122 memory: 9425 grad_norm: 0.6716 loss: 1.4461 loss_heatmap: 0.5930 layer_-1_loss_cls: 0.0894 layer_-1_loss_bbox: 0.7638 matched_ious: 0.5673 2023/03/22 20:08:19 - mmengine - INFO - Epoch(train) [13][1050/3862] lr: 7.1861e-04 eta: 8:51:50 time: 1.0630 data_time: 0.0121 memory: 9311 grad_norm: 0.6742 loss: 1.4313 loss_heatmap: 0.6064 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.7347 matched_ious: 0.5519 2023/03/22 20:09:12 - mmengine - INFO - Epoch(train) [13][1100/3862] lr: 7.1708e-04 eta: 8:50:56 time: 1.0629 data_time: 0.0125 memory: 9388 grad_norm: 0.7141 loss: 1.4232 loss_heatmap: 0.6001 layer_-1_loss_cls: 0.0925 layer_-1_loss_bbox: 0.7306 matched_ious: 0.5520 2023/03/22 20:10:06 - mmengine - INFO - Epoch(train) [13][1150/3862] lr: 7.1555e-04 eta: 8:50:03 time: 1.0665 data_time: 0.0126 memory: 9294 grad_norm: 0.7173 loss: 1.4444 loss_heatmap: 0.5993 layer_-1_loss_cls: 0.0913 layer_-1_loss_bbox: 0.7538 matched_ious: 0.5425 2023/03/22 20:10:59 - mmengine - INFO - Epoch(train) [13][1200/3862] lr: 7.1402e-04 eta: 8:49:09 time: 1.0700 data_time: 0.0123 memory: 9542 grad_norm: 0.6914 loss: 1.4429 loss_heatmap: 0.6029 layer_-1_loss_cls: 0.0921 layer_-1_loss_bbox: 0.7480 matched_ious: 0.5410 2023/03/22 20:11:53 - mmengine - INFO - Epoch(train) [13][1250/3862] lr: 7.1249e-04 eta: 8:48:16 time: 1.0705 data_time: 0.0123 memory: 9005 grad_norm: 0.6485 loss: 1.4423 loss_heatmap: 0.6139 layer_-1_loss_cls: 0.0925 layer_-1_loss_bbox: 0.7359 matched_ious: 0.5308 2023/03/22 20:12:46 - mmengine - INFO - Epoch(train) [13][1300/3862] lr: 7.1095e-04 eta: 8:47:22 time: 1.0710 data_time: 0.0121 memory: 9150 grad_norm: 0.7296 loss: 1.4910 loss_heatmap: 0.6185 layer_-1_loss_cls: 0.0933 layer_-1_loss_bbox: 0.7791 matched_ious: 0.5122 2023/03/22 20:13:39 - mmengine - INFO - Epoch(train) [13][1350/3862] lr: 7.0942e-04 eta: 8:46:29 time: 1.0580 data_time: 0.0120 memory: 8972 grad_norm: 0.7244 loss: 1.4281 loss_heatmap: 0.5896 layer_-1_loss_cls: 0.0915 layer_-1_loss_bbox: 0.7471 matched_ious: 0.5448 2023/03/22 20:14:32 - mmengine - INFO - Epoch(train) [13][1400/3862] lr: 7.0788e-04 eta: 8:45:35 time: 1.0645 data_time: 0.0122 memory: 9120 grad_norm: 0.7402 loss: 1.4953 loss_heatmap: 0.6168 layer_-1_loss_cls: 0.0934 layer_-1_loss_bbox: 0.7851 matched_ious: 0.5714 2023/03/22 20:15:26 - mmengine - INFO - Epoch(train) [13][1450/3862] lr: 7.0633e-04 eta: 8:44:41 time: 1.0631 data_time: 0.0123 memory: 9001 grad_norm: 0.8622 loss: 1.4563 loss_heatmap: 0.6046 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.7597 matched_ious: 0.5610 2023/03/22 20:16:19 - mmengine - INFO - Epoch(train) [13][1500/3862] lr: 7.0479e-04 eta: 8:43:48 time: 1.0641 data_time: 0.0123 memory: 9417 grad_norm: 0.8165 loss: 1.5208 loss_heatmap: 0.6215 layer_-1_loss_cls: 0.0951 layer_-1_loss_bbox: 0.8043 matched_ious: 0.5047 2023/03/22 20:17:12 - mmengine - INFO - Epoch(train) [13][1550/3862] lr: 7.0324e-04 eta: 8:42:54 time: 1.0697 data_time: 0.0126 memory: 8996 grad_norm: 0.6701 loss: 1.4744 loss_heatmap: 0.6014 layer_-1_loss_cls: 0.0918 layer_-1_loss_bbox: 0.7812 matched_ious: 0.5532 2023/03/22 20:18:06 - mmengine - INFO - Epoch(train) [13][1600/3862] lr: 7.0169e-04 eta: 8:42:01 time: 1.0662 data_time: 0.0119 memory: 9406 grad_norm: 0.6566 loss: 1.4620 loss_heatmap: 0.6075 layer_-1_loss_cls: 0.0924 layer_-1_loss_bbox: 0.7622 matched_ious: 0.5566 2023/03/22 20:18:59 - mmengine - INFO - Epoch(train) [13][1650/3862] lr: 7.0014e-04 eta: 8:41:07 time: 1.0628 data_time: 0.0120 memory: 8986 grad_norm: 0.7524 loss: 1.4149 loss_heatmap: 0.5768 layer_-1_loss_cls: 0.0892 layer_-1_loss_bbox: 0.7489 matched_ious: 0.5573 2023/03/22 20:19:05 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 20:19:52 - mmengine - INFO - Epoch(train) [13][1700/3862] lr: 6.9859e-04 eta: 8:40:13 time: 1.0613 data_time: 0.0121 memory: 9033 grad_norm: 0.7400 loss: 1.4585 loss_heatmap: 0.6017 layer_-1_loss_cls: 0.0933 layer_-1_loss_bbox: 0.7635 matched_ious: 0.4930 2023/03/22 20:20:45 - mmengine - INFO - Epoch(train) [13][1750/3862] lr: 6.9703e-04 eta: 8:39:20 time: 1.0665 data_time: 0.0118 memory: 9191 grad_norm: 0.6292 loss: 1.4415 loss_heatmap: 0.5950 layer_-1_loss_cls: 0.0893 layer_-1_loss_bbox: 0.7572 matched_ious: 0.5084 2023/03/22 20:21:39 - mmengine - INFO - Epoch(train) [13][1800/3862] lr: 6.9547e-04 eta: 8:38:27 time: 1.0729 data_time: 0.0119 memory: 9154 grad_norm: 0.6863 loss: 1.3998 loss_heatmap: 0.6005 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.7090 matched_ious: 0.5514 2023/03/22 20:22:32 - mmengine - INFO - Epoch(train) [13][1850/3862] lr: 6.9391e-04 eta: 8:37:33 time: 1.0749 data_time: 0.0122 memory: 9179 grad_norm: 0.7014 loss: 1.4498 loss_heatmap: 0.5958 layer_-1_loss_cls: 0.0895 layer_-1_loss_bbox: 0.7645 matched_ious: 0.5144 2023/03/22 20:23:26 - mmengine - INFO - Epoch(train) [13][1900/3862] lr: 6.9235e-04 eta: 8:36:40 time: 1.0669 data_time: 0.0122 memory: 9370 grad_norm: 0.7080 loss: 1.4400 loss_heatmap: 0.5993 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.7488 matched_ious: 0.5500 2023/03/22 20:24:19 - mmengine - INFO - Epoch(train) [13][1950/3862] lr: 6.9078e-04 eta: 8:35:46 time: 1.0645 data_time: 0.0123 memory: 9540 grad_norm: 0.6296 loss: 1.3995 loss_heatmap: 0.5773 layer_-1_loss_cls: 0.0891 layer_-1_loss_bbox: 0.7331 matched_ious: 0.5861 2023/03/22 20:25:13 - mmengine - INFO - Epoch(train) [13][2000/3862] lr: 6.8921e-04 eta: 8:34:53 time: 1.0773 data_time: 0.0125 memory: 9024 grad_norm: 0.7067 loss: 1.4182 loss_heatmap: 0.5862 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.7434 matched_ious: 0.5012 2023/03/22 20:26:07 - mmengine - INFO - Epoch(train) [13][2050/3862] lr: 6.8764e-04 eta: 8:34:00 time: 1.0734 data_time: 0.0122 memory: 9324 grad_norm: 0.6381 loss: 1.4063 loss_heatmap: 0.5893 layer_-1_loss_cls: 0.0901 layer_-1_loss_bbox: 0.7269 matched_ious: 0.5120 2023/03/22 20:27:00 - mmengine - INFO - Epoch(train) [13][2100/3862] lr: 6.8607e-04 eta: 8:33:06 time: 1.0674 data_time: 0.0119 memory: 9176 grad_norm: 0.9057 loss: 1.4696 loss_heatmap: 0.6155 layer_-1_loss_cls: 0.0914 layer_-1_loss_bbox: 0.7628 matched_ious: 0.5800 2023/03/22 20:27:53 - mmengine - INFO - Epoch(train) [13][2150/3862] lr: 6.8450e-04 eta: 8:32:12 time: 1.0618 data_time: 0.0121 memory: 8883 grad_norm: 0.7266 loss: 1.4283 loss_heatmap: 0.5838 layer_-1_loss_cls: 0.0901 layer_-1_loss_bbox: 0.7545 matched_ious: 0.5000 2023/03/22 20:28:46 - mmengine - INFO - Epoch(train) [13][2200/3862] lr: 6.8292e-04 eta: 8:31:19 time: 1.0627 data_time: 0.0118 memory: 9345 grad_norm: 0.6825 loss: 1.4328 loss_heatmap: 0.5976 layer_-1_loss_cls: 0.0918 layer_-1_loss_bbox: 0.7434 matched_ious: 0.5507 2023/03/22 20:29:39 - mmengine - INFO - Epoch(train) [13][2250/3862] lr: 6.8134e-04 eta: 8:30:25 time: 1.0630 data_time: 0.0123 memory: 8999 grad_norm: 0.6639 loss: 1.4260 loss_heatmap: 0.5890 layer_-1_loss_cls: 0.0900 layer_-1_loss_bbox: 0.7471 matched_ious: 0.5012 2023/03/22 20:30:33 - mmengine - INFO - Epoch(train) [13][2300/3862] lr: 6.7976e-04 eta: 8:29:32 time: 1.0754 data_time: 0.0122 memory: 9285 grad_norm: 0.7752 loss: 1.4579 loss_heatmap: 0.6113 layer_-1_loss_cls: 0.0917 layer_-1_loss_bbox: 0.7549 matched_ious: 0.5449 2023/03/22 20:31:26 - mmengine - INFO - Epoch(train) [13][2350/3862] lr: 6.7818e-04 eta: 8:28:38 time: 1.0666 data_time: 0.0122 memory: 9117 grad_norm: 0.6945 loss: 1.4757 loss_heatmap: 0.5986 layer_-1_loss_cls: 0.0898 layer_-1_loss_bbox: 0.7873 matched_ious: 0.5530 2023/03/22 20:32:20 - mmengine - INFO - Epoch(train) [13][2400/3862] lr: 6.7660e-04 eta: 8:27:45 time: 1.0652 data_time: 0.0121 memory: 9196 grad_norm: 0.7275 loss: 1.4659 loss_heatmap: 0.6003 layer_-1_loss_cls: 0.0899 layer_-1_loss_bbox: 0.7757 matched_ious: 0.5673 2023/03/22 20:33:14 - mmengine - INFO - Epoch(train) [13][2450/3862] lr: 6.7501e-04 eta: 8:26:52 time: 1.0758 data_time: 0.0122 memory: 9212 grad_norm: 0.8550 loss: 1.4924 loss_heatmap: 0.6188 layer_-1_loss_cls: 0.0940 layer_-1_loss_bbox: 0.7796 matched_ious: 0.5255 2023/03/22 20:34:07 - mmengine - INFO - Epoch(train) [13][2500/3862] lr: 6.7342e-04 eta: 8:25:58 time: 1.0694 data_time: 0.0122 memory: 9271 grad_norm: 0.6841 loss: 1.4222 loss_heatmap: 0.5973 layer_-1_loss_cls: 0.0912 layer_-1_loss_bbox: 0.7338 matched_ious: 0.5116 2023/03/22 20:35:01 - mmengine - INFO - Epoch(train) [13][2550/3862] lr: 6.7183e-04 eta: 8:25:05 time: 1.0809 data_time: 0.0120 memory: 9273 grad_norm: 0.6622 loss: 1.4029 loss_heatmap: 0.5793 layer_-1_loss_cls: 0.0877 layer_-1_loss_bbox: 0.7359 matched_ious: 0.5734 2023/03/22 20:35:55 - mmengine - INFO - Epoch(train) [13][2600/3862] lr: 6.7024e-04 eta: 8:24:12 time: 1.0746 data_time: 0.0120 memory: 9156 grad_norm: 0.7071 loss: 1.4225 loss_heatmap: 0.5809 layer_-1_loss_cls: 0.0899 layer_-1_loss_bbox: 0.7517 matched_ious: 0.5337 2023/03/22 20:36:48 - mmengine - INFO - Epoch(train) [13][2650/3862] lr: 6.6864e-04 eta: 8:23:18 time: 1.0670 data_time: 0.0119 memory: 9357 grad_norm: 0.6498 loss: 1.4143 loss_heatmap: 0.5915 layer_-1_loss_cls: 0.0911 layer_-1_loss_bbox: 0.7317 matched_ious: 0.5324 2023/03/22 20:36:55 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 20:37:42 - mmengine - INFO - Epoch(train) [13][2700/3862] lr: 6.6705e-04 eta: 8:22:25 time: 1.0729 data_time: 0.0123 memory: 9309 grad_norm: 0.7662 loss: 1.3721 loss_heatmap: 0.5823 layer_-1_loss_cls: 0.0914 layer_-1_loss_bbox: 0.6984 matched_ious: 0.5757 2023/03/22 20:38:35 - mmengine - INFO - Epoch(train) [13][2750/3862] lr: 6.6545e-04 eta: 8:21:31 time: 1.0606 data_time: 0.0119 memory: 9455 grad_norm: 0.6928 loss: 1.4354 loss_heatmap: 0.6040 layer_-1_loss_cls: 0.0929 layer_-1_loss_bbox: 0.7385 matched_ious: 0.5645 2023/03/22 20:39:28 - mmengine - INFO - Epoch(train) [13][2800/3862] lr: 6.6385e-04 eta: 8:20:38 time: 1.0645 data_time: 0.0127 memory: 9278 grad_norm: 0.7555 loss: 1.4431 loss_heatmap: 0.5945 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.7583 matched_ious: 0.5450 2023/03/22 20:40:21 - mmengine - INFO - Epoch(train) [13][2850/3862] lr: 6.6225e-04 eta: 8:19:44 time: 1.0666 data_time: 0.0119 memory: 9441 grad_norm: 0.7154 loss: 1.4040 loss_heatmap: 0.5904 layer_-1_loss_cls: 0.0902 layer_-1_loss_bbox: 0.7234 matched_ious: 0.5662 2023/03/22 20:41:15 - mmengine - INFO - Epoch(train) [13][2900/3862] lr: 6.6064e-04 eta: 8:18:50 time: 1.0665 data_time: 0.0123 memory: 9246 grad_norm: 0.6865 loss: 1.4261 loss_heatmap: 0.6029 layer_-1_loss_cls: 0.0901 layer_-1_loss_bbox: 0.7331 matched_ious: 0.5378 2023/03/22 20:42:08 - mmengine - INFO - Epoch(train) [13][2950/3862] lr: 6.5904e-04 eta: 8:17:57 time: 1.0671 data_time: 0.0122 memory: 9140 grad_norm: 0.6384 loss: 1.4643 loss_heatmap: 0.5981 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.7776 matched_ious: 0.5907 2023/03/22 20:43:01 - mmengine - INFO - Epoch(train) [13][3000/3862] lr: 6.5743e-04 eta: 8:17:03 time: 1.0680 data_time: 0.0124 memory: 9060 grad_norm: 0.6677 loss: 1.4262 loss_heatmap: 0.5857 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.7509 matched_ious: 0.5679 2023/03/22 20:43:54 - mmengine - INFO - Epoch(train) [13][3050/3862] lr: 6.5582e-04 eta: 8:16:10 time: 1.0569 data_time: 0.0125 memory: 9152 grad_norm: 0.7103 loss: 1.4545 loss_heatmap: 0.6170 layer_-1_loss_cls: 0.0946 layer_-1_loss_bbox: 0.7428 matched_ious: 0.5515 2023/03/22 20:44:48 - mmengine - INFO - Epoch(train) [13][3100/3862] lr: 6.5421e-04 eta: 8:15:16 time: 1.0778 data_time: 0.0124 memory: 8985 grad_norm: 0.6802 loss: 1.4013 loss_heatmap: 0.5855 layer_-1_loss_cls: 0.0872 layer_-1_loss_bbox: 0.7287 matched_ious: 0.5489 2023/03/22 20:45:42 - mmengine - INFO - Epoch(train) [13][3150/3862] lr: 6.5260e-04 eta: 8:14:23 time: 1.0799 data_time: 0.0123 memory: 9159 grad_norm: 0.7491 loss: 1.4273 loss_heatmap: 0.5972 layer_-1_loss_cls: 0.0926 layer_-1_loss_bbox: 0.7375 matched_ious: 0.5395 2023/03/22 20:46:36 - mmengine - INFO - Epoch(train) [13][3200/3862] lr: 6.5098e-04 eta: 8:13:30 time: 1.0660 data_time: 0.0120 memory: 9054 grad_norm: 0.7279 loss: 1.4276 loss_heatmap: 0.5833 layer_-1_loss_cls: 0.0870 layer_-1_loss_bbox: 0.7572 matched_ious: 0.5257 2023/03/22 20:47:29 - mmengine - INFO - Epoch(train) [13][3250/3862] lr: 6.4936e-04 eta: 8:12:36 time: 1.0649 data_time: 0.0117 memory: 9160 grad_norm: 0.6823 loss: 1.4359 loss_heatmap: 0.6041 layer_-1_loss_cls: 0.0906 layer_-1_loss_bbox: 0.7412 matched_ious: 0.5461 2023/03/22 20:48:22 - mmengine - INFO - Epoch(train) [13][3300/3862] lr: 6.4775e-04 eta: 8:11:43 time: 1.0680 data_time: 0.0123 memory: 9354 grad_norm: 0.6525 loss: 1.4214 loss_heatmap: 0.5989 layer_-1_loss_cls: 0.0913 layer_-1_loss_bbox: 0.7311 matched_ious: 0.5157 2023/03/22 20:49:15 - mmengine - INFO - Epoch(train) [13][3350/3862] lr: 6.4613e-04 eta: 8:10:49 time: 1.0603 data_time: 0.0123 memory: 9133 grad_norm: 0.6881 loss: 1.4226 loss_heatmap: 0.5869 layer_-1_loss_cls: 0.0880 layer_-1_loss_bbox: 0.7477 matched_ious: 0.5199 2023/03/22 20:50:09 - mmengine - INFO - Epoch(train) [13][3400/3862] lr: 6.4451e-04 eta: 8:09:56 time: 1.0795 data_time: 0.0122 memory: 8956 grad_norm: 0.6932 loss: 1.4514 loss_heatmap: 0.6039 layer_-1_loss_cls: 0.0915 layer_-1_loss_bbox: 0.7560 matched_ious: 0.5320 2023/03/22 20:51:02 - mmengine - INFO - Epoch(train) [13][3450/3862] lr: 6.4288e-04 eta: 8:09:02 time: 1.0656 data_time: 0.0120 memory: 9229 grad_norm: 0.7007 loss: 1.3896 loss_heatmap: 0.5711 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.7320 matched_ious: 0.5260 2023/03/22 20:51:56 - mmengine - INFO - Epoch(train) [13][3500/3862] lr: 6.4126e-04 eta: 8:08:09 time: 1.0734 data_time: 0.0116 memory: 9187 grad_norm: 0.8116 loss: 1.4743 loss_heatmap: 0.6045 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.7802 matched_ious: 0.4806 2023/03/22 20:52:49 - mmengine - INFO - Epoch(train) [13][3550/3862] lr: 6.3963e-04 eta: 8:07:15 time: 1.0583 data_time: 0.0123 memory: 9097 grad_norm: 0.7270 loss: 1.4830 loss_heatmap: 0.6114 layer_-1_loss_cls: 0.0912 layer_-1_loss_bbox: 0.7804 matched_ious: 0.5526 2023/03/22 20:53:42 - mmengine - INFO - Epoch(train) [13][3600/3862] lr: 6.3800e-04 eta: 8:06:22 time: 1.0675 data_time: 0.0122 memory: 9185 grad_norm: 0.7691 loss: 1.4365 loss_heatmap: 0.6055 layer_-1_loss_cls: 0.0914 layer_-1_loss_bbox: 0.7396 matched_ious: 0.5512 2023/03/22 20:54:36 - mmengine - INFO - Epoch(train) [13][3650/3862] lr: 6.3637e-04 eta: 8:05:28 time: 1.0670 data_time: 0.0118 memory: 9281 grad_norm: 0.7634 loss: 1.4201 loss_heatmap: 0.5906 layer_-1_loss_cls: 0.0882 layer_-1_loss_bbox: 0.7413 matched_ious: 0.5560 2023/03/22 20:54:42 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 20:55:29 - mmengine - INFO - Epoch(train) [13][3700/3862] lr: 6.3474e-04 eta: 8:04:35 time: 1.0720 data_time: 0.0120 memory: 9268 grad_norm: 0.7342 loss: 1.4381 loss_heatmap: 0.5959 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.7532 matched_ious: 0.5365 2023/03/22 20:57:01 - mmengine - INFO - Epoch(train) [13][3750/3862] lr: 6.3311e-04 eta: 8:04:02 time: 1.8401 data_time: 0.3526 memory: 9271 grad_norm: 0.7653 loss: 1.4271 loss_heatmap: 0.5975 layer_-1_loss_cls: 0.0907 layer_-1_loss_bbox: 0.7389 matched_ious: 0.5275 2023/03/22 20:57:55 - mmengine - INFO - Epoch(train) [13][3800/3862] lr: 6.3147e-04 eta: 8:03:09 time: 1.0705 data_time: 0.0117 memory: 9059 grad_norm: 0.7451 loss: 1.4754 loss_heatmap: 0.6211 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.7587 matched_ious: 0.5031 2023/03/22 20:58:49 - mmengine - INFO - Epoch(train) [13][3850/3862] lr: 6.2984e-04 eta: 8:02:15 time: 1.0724 data_time: 0.0123 memory: 8984 grad_norm: 0.6714 loss: 1.4089 loss_heatmap: 0.5953 layer_-1_loss_cls: 0.0882 layer_-1_loss_bbox: 0.7254 matched_ious: 0.5636 2023/03/22 20:59:01 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 20:59:57 - mmengine - INFO - Epoch(train) [14][ 50/3862] lr: 6.2781e-04 eta: 8:01:10 time: 1.1144 data_time: 0.0570 memory: 9283 grad_norm: 0.7365 loss: 1.4722 loss_heatmap: 0.5930 layer_-1_loss_cls: 0.0880 layer_-1_loss_bbox: 0.7912 matched_ious: 0.5795 2023/03/22 21:00:51 - mmengine - INFO - Epoch(train) [14][ 100/3862] lr: 6.2617e-04 eta: 8:00:17 time: 1.0712 data_time: 0.0118 memory: 9562 grad_norm: 0.7297 loss: 1.3940 loss_heatmap: 0.5858 layer_-1_loss_cls: 0.0878 layer_-1_loss_bbox: 0.7204 matched_ious: 0.5509 2023/03/22 21:01:43 - mmengine - INFO - Epoch(train) [14][ 150/3862] lr: 6.2453e-04 eta: 7:59:23 time: 1.0559 data_time: 0.0123 memory: 9114 grad_norm: 0.7110 loss: 1.3680 loss_heatmap: 0.5896 layer_-1_loss_cls: 0.0909 layer_-1_loss_bbox: 0.6875 matched_ious: 0.5787 2023/03/22 21:02:37 - mmengine - INFO - Epoch(train) [14][ 200/3862] lr: 6.2289e-04 eta: 7:58:30 time: 1.0775 data_time: 0.0124 memory: 9210 grad_norm: 0.7521 loss: 1.4941 loss_heatmap: 0.6077 layer_-1_loss_cls: 0.0913 layer_-1_loss_bbox: 0.7950 matched_ious: 0.5980 2023/03/22 21:03:30 - mmengine - INFO - Epoch(train) [14][ 250/3862] lr: 6.2124e-04 eta: 7:57:36 time: 1.0627 data_time: 0.0121 memory: 9065 grad_norm: 0.7142 loss: 1.3846 loss_heatmap: 0.5732 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.7227 matched_ious: 0.5474 2023/03/22 21:04:24 - mmengine - INFO - Epoch(train) [14][ 300/3862] lr: 6.1960e-04 eta: 7:56:42 time: 1.0750 data_time: 0.0127 memory: 9190 grad_norm: 0.6821 loss: 1.3924 loss_heatmap: 0.5837 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.7200 matched_ious: 0.5699 2023/03/22 21:05:17 - mmengine - INFO - Epoch(train) [14][ 350/3862] lr: 6.1795e-04 eta: 7:55:49 time: 1.0601 data_time: 0.0121 memory: 9117 grad_norm: 0.7394 loss: 1.4034 loss_heatmap: 0.5912 layer_-1_loss_cls: 0.0889 layer_-1_loss_bbox: 0.7233 matched_ious: 0.5425 2023/03/22 21:06:11 - mmengine - INFO - Epoch(train) [14][ 400/3862] lr: 6.1630e-04 eta: 7:54:55 time: 1.0754 data_time: 0.0120 memory: 9022 grad_norm: 0.7601 loss: 1.4842 loss_heatmap: 0.6085 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.7869 matched_ious: 0.5726 2023/03/22 21:07:05 - mmengine - INFO - Epoch(train) [14][ 450/3862] lr: 6.1466e-04 eta: 7:54:02 time: 1.0875 data_time: 0.0122 memory: 9137 grad_norm: 0.8007 loss: 1.4265 loss_heatmap: 0.6002 layer_-1_loss_cls: 0.0909 layer_-1_loss_bbox: 0.7355 matched_ious: 0.5331 2023/03/22 21:07:59 - mmengine - INFO - Epoch(train) [14][ 500/3862] lr: 6.1301e-04 eta: 7:53:09 time: 1.0652 data_time: 0.0120 memory: 9048 grad_norm: 0.6961 loss: 1.4191 loss_heatmap: 0.5916 layer_-1_loss_cls: 0.0901 layer_-1_loss_bbox: 0.7373 matched_ious: 0.5371 2023/03/22 21:08:52 - mmengine - INFO - Epoch(train) [14][ 550/3862] lr: 6.1135e-04 eta: 7:52:15 time: 1.0662 data_time: 0.0122 memory: 9123 grad_norm: 0.7474 loss: 1.3934 loss_heatmap: 0.5812 layer_-1_loss_cls: 0.0882 layer_-1_loss_bbox: 0.7241 matched_ious: 0.5946 2023/03/22 21:09:45 - mmengine - INFO - Epoch(train) [14][ 600/3862] lr: 6.0970e-04 eta: 7:51:22 time: 1.0678 data_time: 0.0123 memory: 9169 grad_norm: 0.7938 loss: 1.4638 loss_heatmap: 0.6091 layer_-1_loss_cls: 0.0922 layer_-1_loss_bbox: 0.7624 matched_ious: 0.4990 2023/03/22 21:10:39 - mmengine - INFO - Epoch(train) [14][ 650/3862] lr: 6.0805e-04 eta: 7:50:28 time: 1.0654 data_time: 0.0124 memory: 9415 grad_norm: 0.6840 loss: 1.4304 loss_heatmap: 0.6018 layer_-1_loss_cls: 0.0904 layer_-1_loss_bbox: 0.7382 matched_ious: 0.5326 2023/03/22 21:11:32 - mmengine - INFO - Epoch(train) [14][ 700/3862] lr: 6.0639e-04 eta: 7:49:34 time: 1.0605 data_time: 0.0123 memory: 9025 grad_norm: 0.6725 loss: 1.4179 loss_heatmap: 0.5748 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.7544 matched_ious: 0.5724 2023/03/22 21:12:25 - mmengine - INFO - Epoch(train) [14][ 750/3862] lr: 6.0474e-04 eta: 7:48:41 time: 1.0708 data_time: 0.0127 memory: 9122 grad_norm: 0.8571 loss: 1.4002 loss_heatmap: 0.5833 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.7298 matched_ious: 0.5622 2023/03/22 21:13:12 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 21:13:18 - mmengine - INFO - Epoch(train) [14][ 800/3862] lr: 6.0308e-04 eta: 7:47:47 time: 1.0644 data_time: 0.0125 memory: 9380 grad_norm: 0.6735 loss: 1.4259 loss_heatmap: 0.5950 layer_-1_loss_cls: 0.0898 layer_-1_loss_bbox: 0.7412 matched_ious: 0.5519 2023/03/22 21:14:12 - mmengine - INFO - Epoch(train) [14][ 850/3862] lr: 6.0142e-04 eta: 7:46:54 time: 1.0705 data_time: 0.0125 memory: 9325 grad_norm: 0.8492 loss: 1.3886 loss_heatmap: 0.5778 layer_-1_loss_cls: 0.0881 layer_-1_loss_bbox: 0.7227 matched_ious: 0.5294 2023/03/22 21:15:05 - mmengine - INFO - Epoch(train) [14][ 900/3862] lr: 5.9976e-04 eta: 7:46:00 time: 1.0575 data_time: 0.0128 memory: 9115 grad_norm: 0.6740 loss: 1.4201 loss_heatmap: 0.5936 layer_-1_loss_cls: 0.0885 layer_-1_loss_bbox: 0.7380 matched_ious: 0.5668 2023/03/22 21:15:58 - mmengine - INFO - Epoch(train) [14][ 950/3862] lr: 5.9810e-04 eta: 7:45:06 time: 1.0667 data_time: 0.0123 memory: 9266 grad_norm: 0.7099 loss: 1.4049 loss_heatmap: 0.5796 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.7365 matched_ious: 0.5126 2023/03/22 21:16:51 - mmengine - INFO - Epoch(train) [14][1000/3862] lr: 5.9644e-04 eta: 7:44:13 time: 1.0611 data_time: 0.0122 memory: 9240 grad_norm: 0.7558 loss: 1.4050 loss_heatmap: 0.5711 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.7450 matched_ious: 0.5516 2023/03/22 21:17:45 - mmengine - INFO - Epoch(train) [14][1050/3862] lr: 5.9477e-04 eta: 7:43:19 time: 1.0744 data_time: 0.0123 memory: 9149 grad_norm: 0.6593 loss: 1.4390 loss_heatmap: 0.5967 layer_-1_loss_cls: 0.0911 layer_-1_loss_bbox: 0.7512 matched_ious: 0.5410 2023/03/22 21:18:38 - mmengine - INFO - Epoch(train) [14][1100/3862] lr: 5.9311e-04 eta: 7:42:26 time: 1.0669 data_time: 0.0123 memory: 9038 grad_norm: 0.7012 loss: 1.3760 loss_heatmap: 0.5784 layer_-1_loss_cls: 0.0905 layer_-1_loss_bbox: 0.7071 matched_ious: 0.5455 2023/03/22 21:19:32 - mmengine - INFO - Epoch(train) [14][1150/3862] lr: 5.9144e-04 eta: 7:41:32 time: 1.0742 data_time: 0.0122 memory: 9123 grad_norm: 0.7725 loss: 1.4201 loss_heatmap: 0.5919 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.7397 matched_ious: 0.5278 2023/03/22 21:20:25 - mmengine - INFO - Epoch(train) [14][1200/3862] lr: 5.8978e-04 eta: 7:40:39 time: 1.0658 data_time: 0.0126 memory: 9069 grad_norm: 0.6559 loss: 1.4474 loss_heatmap: 0.5935 layer_-1_loss_cls: 0.0910 layer_-1_loss_bbox: 0.7629 matched_ious: 0.5508 2023/03/22 21:21:19 - mmengine - INFO - Epoch(train) [14][1250/3862] lr: 5.8811e-04 eta: 7:39:45 time: 1.0790 data_time: 0.0127 memory: 8954 grad_norm: 0.6435 loss: 1.4436 loss_heatmap: 0.5973 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.7544 matched_ious: 0.5927 2023/03/22 21:22:13 - mmengine - INFO - Epoch(train) [14][1300/3862] lr: 5.8644e-04 eta: 7:38:52 time: 1.0726 data_time: 0.0127 memory: 9210 grad_norm: 0.6502 loss: 1.4239 loss_heatmap: 0.5894 layer_-1_loss_cls: 0.0892 layer_-1_loss_bbox: 0.7454 matched_ious: 0.5384 2023/03/22 21:23:06 - mmengine - INFO - Epoch(train) [14][1350/3862] lr: 5.8477e-04 eta: 7:37:58 time: 1.0627 data_time: 0.0126 memory: 9005 grad_norm: 0.6491 loss: 1.3821 loss_heatmap: 0.5744 layer_-1_loss_cls: 0.0873 layer_-1_loss_bbox: 0.7204 matched_ious: 0.5604 2023/03/22 21:23:59 - mmengine - INFO - Epoch(train) [14][1400/3862] lr: 5.8310e-04 eta: 7:37:05 time: 1.0635 data_time: 0.0123 memory: 9129 grad_norm: 0.7452 loss: 1.4306 loss_heatmap: 0.5861 layer_-1_loss_cls: 0.0883 layer_-1_loss_bbox: 0.7563 matched_ious: 0.4937 2023/03/22 21:24:53 - mmengine - INFO - Epoch(train) [14][1450/3862] lr: 5.8143e-04 eta: 7:36:11 time: 1.0719 data_time: 0.0128 memory: 9291 grad_norm: 0.7793 loss: 1.3716 loss_heatmap: 0.5673 layer_-1_loss_cls: 0.0856 layer_-1_loss_bbox: 0.7186 matched_ious: 0.5688 2023/03/22 21:25:46 - mmengine - INFO - Epoch(train) [14][1500/3862] lr: 5.7975e-04 eta: 7:35:17 time: 1.0603 data_time: 0.0125 memory: 9314 grad_norm: 0.7269 loss: 1.3804 loss_heatmap: 0.5786 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.7147 matched_ious: 0.5141 2023/03/22 21:26:40 - mmengine - INFO - Epoch(train) [14][1550/3862] lr: 5.7808e-04 eta: 7:34:24 time: 1.0827 data_time: 0.0124 memory: 9382 grad_norm: 0.7347 loss: 1.3948 loss_heatmap: 0.5777 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.7284 matched_ious: 0.5630 2023/03/22 21:27:34 - mmengine - INFO - Epoch(train) [14][1600/3862] lr: 5.7641e-04 eta: 7:33:31 time: 1.0753 data_time: 0.0124 memory: 9051 grad_norm: 0.6559 loss: 1.4224 loss_heatmap: 0.5921 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.7407 matched_ious: 0.5798 2023/03/22 21:28:27 - mmengine - INFO - Epoch(train) [14][1650/3862] lr: 5.7473e-04 eta: 7:32:37 time: 1.0689 data_time: 0.0130 memory: 9140 grad_norm: 0.6652 loss: 1.4133 loss_heatmap: 0.6001 layer_-1_loss_cls: 0.0900 layer_-1_loss_bbox: 0.7231 matched_ious: 0.5656 2023/03/22 21:29:21 - mmengine - INFO - Epoch(train) [14][1700/3862] lr: 5.7306e-04 eta: 7:31:44 time: 1.0715 data_time: 0.0130 memory: 9226 grad_norm: 0.6809 loss: 1.3869 loss_heatmap: 0.5783 layer_-1_loss_cls: 0.0879 layer_-1_loss_bbox: 0.7207 matched_ious: 0.5398 2023/03/22 21:30:14 - mmengine - INFO - Epoch(train) [14][1750/3862] lr: 5.7138e-04 eta: 7:30:50 time: 1.0597 data_time: 0.0126 memory: 9065 grad_norm: 0.6922 loss: 1.4496 loss_heatmap: 0.5937 layer_-1_loss_cls: 0.0899 layer_-1_loss_bbox: 0.7661 matched_ious: 0.5729 2023/03/22 21:31:01 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 21:31:08 - mmengine - INFO - Epoch(train) [14][1800/3862] lr: 5.6970e-04 eta: 7:29:57 time: 1.0756 data_time: 0.0121 memory: 9208 grad_norm: 0.6769 loss: 1.4084 loss_heatmap: 0.5892 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.7303 matched_ious: 0.5562 2023/03/22 21:32:00 - mmengine - INFO - Epoch(train) [14][1850/3862] lr: 5.6802e-04 eta: 7:29:03 time: 1.0580 data_time: 0.0122 memory: 8972 grad_norm: 0.6278 loss: 1.4308 loss_heatmap: 0.5961 layer_-1_loss_cls: 0.0892 layer_-1_loss_bbox: 0.7455 matched_ious: 0.5518 2023/03/22 21:32:54 - mmengine - INFO - Epoch(train) [14][1900/3862] lr: 5.6634e-04 eta: 7:28:10 time: 1.0684 data_time: 0.0123 memory: 9324 grad_norm: 0.6360 loss: 1.4012 loss_heatmap: 0.5774 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.7364 matched_ious: 0.5452 2023/03/22 21:33:47 - mmengine - INFO - Epoch(train) [14][1950/3862] lr: 5.6466e-04 eta: 7:27:16 time: 1.0682 data_time: 0.0124 memory: 9401 grad_norm: 0.6401 loss: 1.3514 loss_heatmap: 0.5681 layer_-1_loss_cls: 0.0860 layer_-1_loss_bbox: 0.6973 matched_ious: 0.5061 2023/03/22 21:34:41 - mmengine - INFO - Epoch(train) [14][2000/3862] lr: 5.6298e-04 eta: 7:26:23 time: 1.0712 data_time: 0.0123 memory: 9406 grad_norm: 0.6684 loss: 1.4098 loss_heatmap: 0.5896 layer_-1_loss_cls: 0.0910 layer_-1_loss_bbox: 0.7292 matched_ious: 0.5363 2023/03/22 21:35:34 - mmengine - INFO - Epoch(train) [14][2050/3862] lr: 5.6130e-04 eta: 7:25:29 time: 1.0627 data_time: 0.0127 memory: 9207 grad_norm: 0.6825 loss: 1.4804 loss_heatmap: 0.6000 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.7901 matched_ious: 0.4989 2023/03/22 21:36:27 - mmengine - INFO - Epoch(train) [14][2100/3862] lr: 5.5962e-04 eta: 7:24:35 time: 1.0645 data_time: 0.0125 memory: 9204 grad_norm: 0.7549 loss: 1.3979 loss_heatmap: 0.5929 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.7166 matched_ious: 0.5678 2023/03/22 21:37:20 - mmengine - INFO - Epoch(train) [14][2150/3862] lr: 5.5793e-04 eta: 7:23:41 time: 1.0550 data_time: 0.0122 memory: 9054 grad_norm: 0.6984 loss: 1.2891 loss_heatmap: 0.5505 layer_-1_loss_cls: 0.0846 layer_-1_loss_bbox: 0.6540 matched_ious: 0.5604 2023/03/22 21:38:13 - mmengine - INFO - Epoch(train) [14][2200/3862] lr: 5.5625e-04 eta: 7:22:48 time: 1.0615 data_time: 0.0130 memory: 9046 grad_norm: 0.6490 loss: 1.4717 loss_heatmap: 0.6013 layer_-1_loss_cls: 0.0912 layer_-1_loss_bbox: 0.7792 matched_ious: 0.5615 2023/03/22 21:39:06 - mmengine - INFO - Epoch(train) [14][2250/3862] lr: 5.5457e-04 eta: 7:21:54 time: 1.0673 data_time: 0.0122 memory: 9193 grad_norm: 0.7022 loss: 1.3930 loss_heatmap: 0.5768 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.7266 matched_ious: 0.5336 2023/03/22 21:40:00 - mmengine - INFO - Epoch(train) [14][2300/3862] lr: 5.5288e-04 eta: 7:21:00 time: 1.0626 data_time: 0.0126 memory: 9262 grad_norm: 0.6598 loss: 1.4121 loss_heatmap: 0.5925 layer_-1_loss_cls: 0.0873 layer_-1_loss_bbox: 0.7323 matched_ious: 0.5247 2023/03/22 21:40:54 - mmengine - INFO - Epoch(train) [14][2350/3862] lr: 5.5120e-04 eta: 7:20:07 time: 1.0857 data_time: 0.0128 memory: 9054 grad_norm: 0.6628 loss: 1.3723 loss_heatmap: 0.5725 layer_-1_loss_cls: 0.0869 layer_-1_loss_bbox: 0.7128 matched_ious: 0.5708 2023/03/22 21:41:47 - mmengine - INFO - Epoch(train) [14][2400/3862] lr: 5.4951e-04 eta: 7:19:14 time: 1.0700 data_time: 0.0124 memory: 9190 grad_norm: 0.6544 loss: 1.3809 loss_heatmap: 0.5846 layer_-1_loss_cls: 0.0883 layer_-1_loss_bbox: 0.7080 matched_ious: 0.5216 2023/03/22 21:42:41 - mmengine - INFO - Epoch(train) [14][2450/3862] lr: 5.4782e-04 eta: 7:18:20 time: 1.0715 data_time: 0.0126 memory: 9596 grad_norm: 0.6728 loss: 1.4180 loss_heatmap: 0.5931 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.7363 matched_ious: 0.5273 2023/03/22 21:43:34 - mmengine - INFO - Epoch(train) [14][2500/3862] lr: 5.4614e-04 eta: 7:17:27 time: 1.0591 data_time: 0.0124 memory: 9174 grad_norm: 0.7418 loss: 1.3913 loss_heatmap: 0.5774 layer_-1_loss_cls: 0.0889 layer_-1_loss_bbox: 0.7250 matched_ious: 0.5662 2023/03/22 21:44:27 - mmengine - INFO - Epoch(train) [14][2550/3862] lr: 5.4445e-04 eta: 7:16:33 time: 1.0650 data_time: 0.0123 memory: 9076 grad_norm: 0.6570 loss: 1.3933 loss_heatmap: 0.5935 layer_-1_loss_cls: 0.0883 layer_-1_loss_bbox: 0.7115 matched_ious: 0.6126 2023/03/22 21:45:21 - mmengine - INFO - Epoch(train) [14][2600/3862] lr: 5.4276e-04 eta: 7:15:40 time: 1.0700 data_time: 0.0125 memory: 9003 grad_norm: 0.6842 loss: 1.4288 loss_heatmap: 0.5847 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.7570 matched_ious: 0.5513 2023/03/22 21:46:14 - mmengine - INFO - Epoch(train) [14][2650/3862] lr: 5.4107e-04 eta: 7:14:46 time: 1.0635 data_time: 0.0125 memory: 9032 grad_norm: 0.6842 loss: 1.3815 loss_heatmap: 0.5765 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.7186 matched_ious: 0.5604 2023/03/22 21:47:08 - mmengine - INFO - Epoch(train) [14][2700/3862] lr: 5.3938e-04 eta: 7:13:53 time: 1.0922 data_time: 0.0126 memory: 9316 grad_norm: 0.6979 loss: 1.3918 loss_heatmap: 0.5879 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.7154 matched_ious: 0.5760 2023/03/22 21:48:02 - mmengine - INFO - Epoch(train) [14][2750/3862] lr: 5.3769e-04 eta: 7:13:00 time: 1.0776 data_time: 0.0122 memory: 9418 grad_norm: 0.6891 loss: 1.3926 loss_heatmap: 0.5710 layer_-1_loss_cls: 0.0863 layer_-1_loss_bbox: 0.7353 matched_ious: 0.5395 2023/03/22 21:48:49 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 21:48:56 - mmengine - INFO - Epoch(train) [14][2800/3862] lr: 5.3600e-04 eta: 7:12:06 time: 1.0705 data_time: 0.0124 memory: 9140 grad_norm: 0.6531 loss: 1.4106 loss_heatmap: 0.5923 layer_-1_loss_cls: 0.0893 layer_-1_loss_bbox: 0.7291 matched_ious: 0.5351 2023/03/22 21:49:49 - mmengine - INFO - Epoch(train) [14][2850/3862] lr: 5.3431e-04 eta: 7:11:13 time: 1.0679 data_time: 0.0128 memory: 9292 grad_norm: 0.7575 loss: 1.3691 loss_heatmap: 0.5762 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.7055 matched_ious: 0.5679 2023/03/22 21:50:43 - mmengine - INFO - Epoch(train) [14][2900/3862] lr: 5.3262e-04 eta: 7:10:19 time: 1.0744 data_time: 0.0124 memory: 9407 grad_norm: 0.7041 loss: 1.3832 loss_heatmap: 0.5633 layer_-1_loss_cls: 0.0849 layer_-1_loss_bbox: 0.7350 matched_ious: 0.5362 2023/03/22 21:51:37 - mmengine - INFO - Epoch(train) [14][2950/3862] lr: 5.3093e-04 eta: 7:09:26 time: 1.0786 data_time: 0.0126 memory: 9355 grad_norm: 0.7028 loss: 1.3959 loss_heatmap: 0.5845 layer_-1_loss_cls: 0.0878 layer_-1_loss_bbox: 0.7236 matched_ious: 0.5456 2023/03/22 21:52:30 - mmengine - INFO - Epoch(train) [14][3000/3862] lr: 5.2924e-04 eta: 7:08:32 time: 1.0677 data_time: 0.0124 memory: 9096 grad_norm: 0.6690 loss: 1.3222 loss_heatmap: 0.5614 layer_-1_loss_cls: 0.0869 layer_-1_loss_bbox: 0.6739 matched_ious: 0.5585 2023/03/22 21:53:24 - mmengine - INFO - Epoch(train) [14][3050/3862] lr: 5.2755e-04 eta: 7:07:39 time: 1.0735 data_time: 0.0125 memory: 9534 grad_norm: 0.7737 loss: 1.4600 loss_heatmap: 0.5952 layer_-1_loss_cls: 0.0892 layer_-1_loss_bbox: 0.7757 matched_ious: 0.5372 2023/03/22 21:54:17 - mmengine - INFO - Epoch(train) [14][3100/3862] lr: 5.2585e-04 eta: 7:06:46 time: 1.0696 data_time: 0.0121 memory: 9315 grad_norm: 0.7251 loss: 1.4257 loss_heatmap: 0.5956 layer_-1_loss_cls: 0.0910 layer_-1_loss_bbox: 0.7390 matched_ious: 0.5365 2023/03/22 21:55:11 - mmengine - INFO - Epoch(train) [14][3150/3862] lr: 5.2416e-04 eta: 7:05:52 time: 1.0649 data_time: 0.0120 memory: 9360 grad_norm: 0.7746 loss: 1.3717 loss_heatmap: 0.5826 layer_-1_loss_cls: 0.0891 layer_-1_loss_bbox: 0.7000 matched_ious: 0.5401 2023/03/22 21:56:04 - mmengine - INFO - Epoch(train) [14][3200/3862] lr: 5.2247e-04 eta: 7:04:58 time: 1.0634 data_time: 0.0124 memory: 9014 grad_norm: 0.6690 loss: 1.3881 loss_heatmap: 0.5795 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.7210 matched_ious: 0.5270 2023/03/22 21:56:57 - mmengine - INFO - Epoch(train) [14][3250/3862] lr: 5.2078e-04 eta: 7:04:05 time: 1.0640 data_time: 0.0122 memory: 8918 grad_norm: 0.6428 loss: 1.3829 loss_heatmap: 0.5734 layer_-1_loss_cls: 0.0864 layer_-1_loss_bbox: 0.7231 matched_ious: 0.5357 2023/03/22 21:57:51 - mmengine - INFO - Epoch(train) [14][3300/3862] lr: 5.1908e-04 eta: 7:03:11 time: 1.0730 data_time: 0.0126 memory: 9093 grad_norm: 0.6909 loss: 1.3561 loss_heatmap: 0.5704 layer_-1_loss_cls: 0.0861 layer_-1_loss_bbox: 0.6996 matched_ious: 0.5405 2023/03/22 21:58:45 - mmengine - INFO - Epoch(train) [14][3350/3862] lr: 5.1739e-04 eta: 7:02:18 time: 1.0769 data_time: 0.0123 memory: 9235 grad_norm: 0.6783 loss: 1.3592 loss_heatmap: 0.5677 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.7050 matched_ious: 0.5369 2023/03/22 21:59:38 - mmengine - INFO - Epoch(train) [14][3400/3862] lr: 5.1570e-04 eta: 7:01:24 time: 1.0690 data_time: 0.0120 memory: 9010 grad_norm: 0.6626 loss: 1.4101 loss_heatmap: 0.5894 layer_-1_loss_cls: 0.0883 layer_-1_loss_bbox: 0.7324 matched_ious: 0.5381 2023/03/22 22:00:31 - mmengine - INFO - Epoch(train) [14][3450/3862] lr: 5.1400e-04 eta: 7:00:31 time: 1.0624 data_time: 0.0125 memory: 9030 grad_norm: 0.6650 loss: 1.4237 loss_heatmap: 0.6043 layer_-1_loss_cls: 0.0909 layer_-1_loss_bbox: 0.7285 matched_ious: 0.5130 2023/03/22 22:01:25 - mmengine - INFO - Epoch(train) [14][3500/3862] lr: 5.1231e-04 eta: 6:59:37 time: 1.0701 data_time: 0.0121 memory: 9156 grad_norm: 0.7052 loss: 1.3526 loss_heatmap: 0.5694 layer_-1_loss_cls: 0.0862 layer_-1_loss_bbox: 0.6969 matched_ious: 0.5745 2023/03/22 22:02:18 - mmengine - INFO - Epoch(train) [14][3550/3862] lr: 5.1061e-04 eta: 6:58:44 time: 1.0755 data_time: 0.0125 memory: 8992 grad_norm: 0.6848 loss: 1.3687 loss_heatmap: 0.5790 layer_-1_loss_cls: 0.0891 layer_-1_loss_bbox: 0.7006 matched_ious: 0.5600 2023/03/22 22:03:12 - mmengine - INFO - Epoch(train) [14][3600/3862] lr: 5.0892e-04 eta: 6:57:50 time: 1.0689 data_time: 0.0125 memory: 9165 grad_norm: 0.6596 loss: 1.3873 loss_heatmap: 0.5836 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.7161 matched_ious: 0.5361 2023/03/22 22:04:05 - mmengine - INFO - Epoch(train) [14][3650/3862] lr: 5.0722e-04 eta: 6:56:57 time: 1.0694 data_time: 0.0125 memory: 9091 grad_norm: 0.6270 loss: 1.3434 loss_heatmap: 0.5567 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.7016 matched_ious: 0.5062 2023/03/22 22:04:59 - mmengine - INFO - Epoch(train) [14][3700/3862] lr: 5.0553e-04 eta: 6:56:03 time: 1.0707 data_time: 0.0126 memory: 9147 grad_norm: 0.7870 loss: 1.3708 loss_heatmap: 0.5719 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.7115 matched_ious: 0.5323 2023/03/22 22:05:53 - mmengine - INFO - Epoch(train) [14][3750/3862] lr: 5.0383e-04 eta: 6:55:10 time: 1.0748 data_time: 0.0121 memory: 9337 grad_norm: 0.8477 loss: 1.3794 loss_heatmap: 0.5664 layer_-1_loss_cls: 0.0868 layer_-1_loss_bbox: 0.7263 matched_ious: 0.5571 2023/03/22 22:06:40 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 22:06:46 - mmengine - INFO - Epoch(train) [14][3800/3862] lr: 5.0214e-04 eta: 6:54:17 time: 1.0756 data_time: 0.0127 memory: 9102 grad_norm: 0.6596 loss: 1.3858 loss_heatmap: 0.5902 layer_-1_loss_cls: 0.0906 layer_-1_loss_bbox: 0.7051 matched_ious: 0.5808 2023/03/22 22:07:41 - mmengine - INFO - Epoch(train) [14][3850/3862] lr: 5.0045e-04 eta: 6:53:24 time: 1.0879 data_time: 0.0129 memory: 9360 grad_norm: 0.7335 loss: 1.3784 loss_heatmap: 0.5882 layer_-1_loss_cls: 0.0872 layer_-1_loss_bbox: 0.7030 matched_ious: 0.5661 2023/03/22 22:07:54 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 22:08:50 - mmengine - INFO - Epoch(train) [15][ 50/3862] lr: 4.9834e-04 eta: 6:52:18 time: 1.1113 data_time: 0.0482 memory: 9500 grad_norm: 0.7552 loss: 1.3940 loss_heatmap: 0.5918 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.7119 matched_ious: 0.5304 2023/03/22 22:09:43 - mmengine - INFO - Epoch(train) [15][ 100/3862] lr: 4.9665e-04 eta: 6:51:25 time: 1.0713 data_time: 0.0126 memory: 9171 grad_norm: 0.7482 loss: 1.3661 loss_heatmap: 0.5709 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.7081 matched_ious: 0.5564 2023/03/22 22:10:37 - mmengine - INFO - Epoch(train) [15][ 150/3862] lr: 4.9495e-04 eta: 6:50:31 time: 1.0770 data_time: 0.0128 memory: 9204 grad_norm: 0.8200 loss: 1.3773 loss_heatmap: 0.5826 layer_-1_loss_cls: 0.0863 layer_-1_loss_bbox: 0.7083 matched_ious: 0.5620 2023/03/22 22:11:30 - mmengine - INFO - Epoch(train) [15][ 200/3862] lr: 4.9326e-04 eta: 6:49:38 time: 1.0649 data_time: 0.0124 memory: 9084 grad_norm: 0.8640 loss: 1.4223 loss_heatmap: 0.5880 layer_-1_loss_cls: 0.0881 layer_-1_loss_bbox: 0.7462 matched_ious: 0.5421 2023/03/22 22:12:24 - mmengine - INFO - Epoch(train) [15][ 250/3862] lr: 4.9157e-04 eta: 6:48:44 time: 1.0655 data_time: 0.0120 memory: 9049 grad_norm: 0.6839 loss: 1.4119 loss_heatmap: 0.5833 layer_-1_loss_cls: 0.0868 layer_-1_loss_bbox: 0.7418 matched_ious: 0.5447 2023/03/22 22:13:17 - mmengine - INFO - Epoch(train) [15][ 300/3862] lr: 4.8987e-04 eta: 6:47:51 time: 1.0630 data_time: 0.0121 memory: 9192 grad_norm: 0.8104 loss: 1.3931 loss_heatmap: 0.5909 layer_-1_loss_cls: 0.0885 layer_-1_loss_bbox: 0.7136 matched_ious: 0.5739 2023/03/22 22:14:10 - mmengine - INFO - Epoch(train) [15][ 350/3862] lr: 4.8818e-04 eta: 6:46:57 time: 1.0640 data_time: 0.0121 memory: 8924 grad_norm: 0.7830 loss: 1.4043 loss_heatmap: 0.5866 layer_-1_loss_cls: 0.0882 layer_-1_loss_bbox: 0.7295 matched_ious: 0.5370 2023/03/22 22:15:03 - mmengine - INFO - Epoch(train) [15][ 400/3862] lr: 4.8648e-04 eta: 6:46:03 time: 1.0683 data_time: 0.0118 memory: 8849 grad_norm: 0.7019 loss: 1.4007 loss_heatmap: 0.5798 layer_-1_loss_cls: 0.0879 layer_-1_loss_bbox: 0.7330 matched_ious: 0.5400 2023/03/22 22:15:57 - mmengine - INFO - Epoch(train) [15][ 450/3862] lr: 4.8479e-04 eta: 6:45:10 time: 1.0735 data_time: 0.0123 memory: 9111 grad_norm: 0.8142 loss: 1.3693 loss_heatmap: 0.5859 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.6943 matched_ious: 0.5429 2023/03/22 22:16:51 - mmengine - INFO - Epoch(train) [15][ 500/3862] lr: 4.8310e-04 eta: 6:44:17 time: 1.0720 data_time: 0.0118 memory: 9055 grad_norm: 0.6955 loss: 1.4389 loss_heatmap: 0.6020 layer_-1_loss_cls: 0.0895 layer_-1_loss_bbox: 0.7474 matched_ious: 0.5661 2023/03/22 22:17:45 - mmengine - INFO - Epoch(train) [15][ 550/3862] lr: 4.8140e-04 eta: 6:43:23 time: 1.0768 data_time: 0.0122 memory: 9193 grad_norm: 0.6467 loss: 1.4266 loss_heatmap: 0.5887 layer_-1_loss_cls: 0.0864 layer_-1_loss_bbox: 0.7515 matched_ious: 0.5143 2023/03/22 22:18:38 - mmengine - INFO - Epoch(train) [15][ 600/3862] lr: 4.7971e-04 eta: 6:42:30 time: 1.0740 data_time: 0.0119 memory: 9126 grad_norm: 0.6601 loss: 1.3490 loss_heatmap: 0.5699 layer_-1_loss_cls: 0.0853 layer_-1_loss_bbox: 0.6938 matched_ious: 0.5493 2023/03/22 22:19:32 - mmengine - INFO - Epoch(train) [15][ 650/3862] lr: 4.7801e-04 eta: 6:41:36 time: 1.0654 data_time: 0.0124 memory: 9364 grad_norm: 0.6950 loss: 1.3682 loss_heatmap: 0.5698 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.7118 matched_ious: 0.5440 2023/03/22 22:20:25 - mmengine - INFO - Epoch(train) [15][ 700/3862] lr: 4.7632e-04 eta: 6:40:43 time: 1.0627 data_time: 0.0123 memory: 9410 grad_norm: 0.8486 loss: 1.3556 loss_heatmap: 0.5640 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.7095 matched_ious: 0.5374 2023/03/22 22:21:18 - mmengine - INFO - Epoch(train) [15][ 750/3862] lr: 4.7463e-04 eta: 6:39:49 time: 1.0745 data_time: 0.0118 memory: 9508 grad_norm: 0.7689 loss: 1.4425 loss_heatmap: 0.5920 layer_-1_loss_cls: 0.0893 layer_-1_loss_bbox: 0.7611 matched_ious: 0.5699 2023/03/22 22:22:12 - mmengine - INFO - Epoch(train) [15][ 800/3862] lr: 4.7294e-04 eta: 6:38:56 time: 1.0675 data_time: 0.0118 memory: 8988 grad_norm: 0.6717 loss: 1.3798 loss_heatmap: 0.5784 layer_-1_loss_cls: 0.0869 layer_-1_loss_bbox: 0.7146 matched_ious: 0.5716 2023/03/22 22:23:05 - mmengine - INFO - Epoch(train) [15][ 850/3862] lr: 4.7124e-04 eta: 6:38:02 time: 1.0663 data_time: 0.0115 memory: 9071 grad_norm: 0.7872 loss: 1.3678 loss_heatmap: 0.5721 layer_-1_loss_cls: 0.0853 layer_-1_loss_bbox: 0.7104 matched_ious: 0.5375 2023/03/22 22:23:59 - mmengine - INFO - Epoch(train) [15][ 900/3862] lr: 4.6955e-04 eta: 6:37:09 time: 1.0696 data_time: 0.0118 memory: 9120 grad_norm: 0.6698 loss: 1.3537 loss_heatmap: 0.5646 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.7041 matched_ious: 0.6024 2023/03/22 22:24:33 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 22:24:52 - mmengine - INFO - Epoch(train) [15][ 950/3862] lr: 4.6786e-04 eta: 6:36:15 time: 1.0732 data_time: 0.0112 memory: 9450 grad_norm: 0.6451 loss: 1.3571 loss_heatmap: 0.5742 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.6955 matched_ious: 0.5939 2023/03/22 22:25:46 - mmengine - INFO - Epoch(train) [15][1000/3862] lr: 4.6617e-04 eta: 6:35:22 time: 1.0698 data_time: 0.0116 memory: 9137 grad_norm: 0.7273 loss: 1.3840 loss_heatmap: 0.5861 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.7089 matched_ious: 0.5294 2023/03/22 22:26:39 - mmengine - INFO - Epoch(train) [15][1050/3862] lr: 4.6448e-04 eta: 6:34:28 time: 1.0744 data_time: 0.0116 memory: 8991 grad_norm: 0.6995 loss: 1.4049 loss_heatmap: 0.5809 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.7356 matched_ious: 0.5645 2023/03/22 22:27:33 - mmengine - INFO - Epoch(train) [15][1100/3862] lr: 4.6279e-04 eta: 6:33:35 time: 1.0764 data_time: 0.0122 memory: 9328 grad_norm: 0.7743 loss: 1.3888 loss_heatmap: 0.5761 layer_-1_loss_cls: 0.0872 layer_-1_loss_bbox: 0.7254 matched_ious: 0.5133 2023/03/22 22:28:28 - mmengine - INFO - Epoch(train) [15][1150/3862] lr: 4.6110e-04 eta: 6:32:42 time: 1.0935 data_time: 0.0123 memory: 9098 grad_norm: 0.9525 loss: 1.3788 loss_heatmap: 0.5790 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.7133 matched_ious: 0.5509 2023/03/22 22:29:21 - mmengine - INFO - Epoch(train) [15][1200/3862] lr: 4.5941e-04 eta: 6:31:48 time: 1.0607 data_time: 0.0118 memory: 9143 grad_norm: 0.7005 loss: 1.4075 loss_heatmap: 0.5962 layer_-1_loss_cls: 0.0895 layer_-1_loss_bbox: 0.7219 matched_ious: 0.5285 2023/03/22 22:30:14 - mmengine - INFO - Epoch(train) [15][1250/3862] lr: 4.5772e-04 eta: 6:30:55 time: 1.0678 data_time: 0.0119 memory: 9435 grad_norm: 0.8375 loss: 1.3609 loss_heatmap: 0.5677 layer_-1_loss_cls: 0.0872 layer_-1_loss_bbox: 0.7060 matched_ious: 0.5575 2023/03/22 22:31:08 - mmengine - INFO - Epoch(train) [15][1300/3862] lr: 4.5603e-04 eta: 6:30:01 time: 1.0668 data_time: 0.0121 memory: 9337 grad_norm: 0.7239 loss: 1.3642 loss_heatmap: 0.5769 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.6997 matched_ious: 0.5466 2023/03/22 22:32:01 - mmengine - INFO - Epoch(train) [15][1350/3862] lr: 4.5435e-04 eta: 6:29:08 time: 1.0711 data_time: 0.0119 memory: 9090 grad_norm: 0.8269 loss: 1.4276 loss_heatmap: 0.5907 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.7492 matched_ious: 0.5332 2023/03/22 22:32:55 - mmengine - INFO - Epoch(train) [15][1400/3862] lr: 4.5266e-04 eta: 6:28:14 time: 1.0661 data_time: 0.0119 memory: 9324 grad_norm: 0.7408 loss: 1.3944 loss_heatmap: 0.5749 layer_-1_loss_cls: 0.0902 layer_-1_loss_bbox: 0.7294 matched_ious: 0.5591 2023/03/22 22:33:48 - mmengine - INFO - Epoch(train) [15][1450/3862] lr: 4.5097e-04 eta: 6:27:21 time: 1.0768 data_time: 0.0126 memory: 9190 grad_norm: 0.6912 loss: 1.3932 loss_heatmap: 0.5833 layer_-1_loss_cls: 0.0875 layer_-1_loss_bbox: 0.7223 matched_ious: 0.5408 2023/03/22 22:34:42 - mmengine - INFO - Epoch(train) [15][1500/3862] lr: 4.4929e-04 eta: 6:26:27 time: 1.0662 data_time: 0.0122 memory: 9157 grad_norm: 0.7796 loss: 1.3694 loss_heatmap: 0.5656 layer_-1_loss_cls: 0.0845 layer_-1_loss_bbox: 0.7192 matched_ious: 0.5381 2023/03/22 22:35:35 - mmengine - INFO - Epoch(train) [15][1550/3862] lr: 4.4760e-04 eta: 6:25:33 time: 1.0647 data_time: 0.0118 memory: 9153 grad_norm: 0.7200 loss: 1.3513 loss_heatmap: 0.5592 layer_-1_loss_cls: 0.0830 layer_-1_loss_bbox: 0.7091 matched_ious: 0.5184 2023/03/22 22:36:28 - mmengine - INFO - Epoch(train) [15][1600/3862] lr: 4.4591e-04 eta: 6:24:40 time: 1.0666 data_time: 0.0119 memory: 9207 grad_norm: 0.7526 loss: 1.4360 loss_heatmap: 0.5834 layer_-1_loss_cls: 0.0873 layer_-1_loss_bbox: 0.7652 matched_ious: 0.5199 2023/03/22 22:37:22 - mmengine - INFO - Epoch(train) [15][1650/3862] lr: 4.4423e-04 eta: 6:23:46 time: 1.0688 data_time: 0.0120 memory: 9109 grad_norm: 0.6607 loss: 1.3632 loss_heatmap: 0.5771 layer_-1_loss_cls: 0.0872 layer_-1_loss_bbox: 0.6989 matched_ious: 0.5546 2023/03/22 22:38:15 - mmengine - INFO - Epoch(train) [15][1700/3862] lr: 4.4255e-04 eta: 6:22:53 time: 1.0658 data_time: 0.0120 memory: 9053 grad_norm: 0.7337 loss: 1.3865 loss_heatmap: 0.5713 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.7302 matched_ious: 0.5801 2023/03/22 22:39:09 - mmengine - INFO - Epoch(train) [15][1750/3862] lr: 4.4086e-04 eta: 6:21:59 time: 1.0778 data_time: 0.0123 memory: 9293 grad_norm: 1.0675 loss: 1.3632 loss_heatmap: 0.5743 layer_-1_loss_cls: 0.0851 layer_-1_loss_bbox: 0.7038 matched_ious: 0.5555 2023/03/22 22:40:03 - mmengine - INFO - Epoch(train) [15][1800/3862] lr: 4.3918e-04 eta: 6:21:06 time: 1.0710 data_time: 0.0122 memory: 9027 grad_norm: 0.6974 loss: 1.3413 loss_heatmap: 0.5670 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.6867 matched_ious: 0.5317 2023/03/22 22:40:56 - mmengine - INFO - Epoch(train) [15][1850/3862] lr: 4.3750e-04 eta: 6:20:13 time: 1.0700 data_time: 0.0121 memory: 9288 grad_norm: 0.7053 loss: 1.3546 loss_heatmap: 0.5722 layer_-1_loss_cls: 0.0868 layer_-1_loss_bbox: 0.6956 matched_ious: 0.5270 2023/03/22 22:41:49 - mmengine - INFO - Epoch(train) [15][1900/3862] lr: 4.3582e-04 eta: 6:19:19 time: 1.0629 data_time: 0.0119 memory: 9350 grad_norm: 0.7375 loss: 1.3210 loss_heatmap: 0.5684 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.6667 matched_ious: 0.5533 2023/03/22 22:42:23 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 22:42:43 - mmengine - INFO - Epoch(train) [15][1950/3862] lr: 4.3414e-04 eta: 6:18:25 time: 1.0687 data_time: 0.0116 memory: 9279 grad_norm: 0.8770 loss: 1.3553 loss_heatmap: 0.5718 layer_-1_loss_cls: 0.0845 layer_-1_loss_bbox: 0.6991 matched_ious: 0.5595 2023/03/22 22:43:36 - mmengine - INFO - Epoch(train) [15][2000/3862] lr: 4.3246e-04 eta: 6:17:32 time: 1.0733 data_time: 0.0115 memory: 9162 grad_norm: 0.7769 loss: 1.3851 loss_heatmap: 0.5630 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.7385 matched_ious: 0.5738 2023/03/22 22:44:29 - mmengine - INFO - Epoch(train) [15][2050/3862] lr: 4.3078e-04 eta: 6:16:38 time: 1.0602 data_time: 0.0115 memory: 9155 grad_norm: 0.7807 loss: 1.3572 loss_heatmap: 0.5677 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.7030 matched_ious: 0.5478 2023/03/22 22:45:23 - mmengine - INFO - Epoch(train) [15][2100/3862] lr: 4.2910e-04 eta: 6:15:45 time: 1.0661 data_time: 0.0118 memory: 9077 grad_norm: 0.8626 loss: 1.4081 loss_heatmap: 0.5928 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.7250 matched_ious: 0.5327 2023/03/22 22:46:16 - mmengine - INFO - Epoch(train) [15][2150/3862] lr: 4.2742e-04 eta: 6:14:51 time: 1.0758 data_time: 0.0118 memory: 9320 grad_norm: 0.7113 loss: 1.3735 loss_heatmap: 0.5623 layer_-1_loss_cls: 0.0861 layer_-1_loss_bbox: 0.7250 matched_ious: 0.5509 2023/03/22 22:47:10 - mmengine - INFO - Epoch(train) [15][2200/3862] lr: 4.2575e-04 eta: 6:13:58 time: 1.0687 data_time: 0.0121 memory: 9452 grad_norm: 0.7607 loss: 1.4380 loss_heatmap: 0.5859 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.7655 matched_ious: 0.5573 2023/03/22 22:48:04 - mmengine - INFO - Epoch(train) [15][2250/3862] lr: 4.2407e-04 eta: 6:13:04 time: 1.0759 data_time: 0.0119 memory: 9247 grad_norm: 0.6722 loss: 1.3938 loss_heatmap: 0.5755 layer_-1_loss_cls: 0.0864 layer_-1_loss_bbox: 0.7320 matched_ious: 0.5500 2023/03/22 22:48:58 - mmengine - INFO - Epoch(train) [15][2300/3862] lr: 4.2240e-04 eta: 6:12:11 time: 1.0959 data_time: 0.0120 memory: 9095 grad_norm: 0.6875 loss: 1.3246 loss_heatmap: 0.5554 layer_-1_loss_cls: 0.0831 layer_-1_loss_bbox: 0.6861 matched_ious: 0.5877 2023/03/22 22:49:52 - mmengine - INFO - Epoch(train) [15][2350/3862] lr: 4.2072e-04 eta: 6:11:18 time: 1.0663 data_time: 0.0120 memory: 9013 grad_norm: 0.9199 loss: 1.3209 loss_heatmap: 0.5455 layer_-1_loss_cls: 0.0830 layer_-1_loss_bbox: 0.6924 matched_ious: 0.5502 2023/03/22 22:50:46 - mmengine - INFO - Epoch(train) [15][2400/3862] lr: 4.1905e-04 eta: 6:10:24 time: 1.0750 data_time: 0.0120 memory: 9024 grad_norm: 0.7088 loss: 1.2807 loss_heatmap: 0.5487 layer_-1_loss_cls: 0.0831 layer_-1_loss_bbox: 0.6488 matched_ious: 0.5135 2023/03/22 22:51:39 - mmengine - INFO - Epoch(train) [15][2450/3862] lr: 4.1738e-04 eta: 6:09:31 time: 1.0649 data_time: 0.0119 memory: 9283 grad_norm: 0.7164 loss: 1.3710 loss_heatmap: 0.5683 layer_-1_loss_cls: 0.0848 layer_-1_loss_bbox: 0.7179 matched_ious: 0.5371 2023/03/22 22:52:32 - mmengine - INFO - Epoch(train) [15][2500/3862] lr: 4.1571e-04 eta: 6:08:37 time: 1.0640 data_time: 0.0119 memory: 9044 grad_norm: 0.6965 loss: 1.3843 loss_heatmap: 0.5885 layer_-1_loss_cls: 0.0897 layer_-1_loss_bbox: 0.7060 matched_ious: 0.5261 2023/03/22 22:53:25 - mmengine - INFO - Epoch(train) [15][2550/3862] lr: 4.1404e-04 eta: 6:07:44 time: 1.0687 data_time: 0.0119 memory: 9016 grad_norm: 0.6538 loss: 1.3705 loss_heatmap: 0.5680 layer_-1_loss_cls: 0.0830 layer_-1_loss_bbox: 0.7195 matched_ious: 0.5474 2023/03/22 22:54:19 - mmengine - INFO - Epoch(train) [15][2600/3862] lr: 4.1237e-04 eta: 6:06:50 time: 1.0734 data_time: 0.0118 memory: 9316 grad_norm: 0.6987 loss: 1.3416 loss_heatmap: 0.5585 layer_-1_loss_cls: 0.0849 layer_-1_loss_bbox: 0.6981 matched_ious: 0.5400 2023/03/22 22:55:13 - mmengine - INFO - Epoch(train) [15][2650/3862] lr: 4.1070e-04 eta: 6:05:57 time: 1.0737 data_time: 0.0117 memory: 9200 grad_norm: 0.7983 loss: 1.3347 loss_heatmap: 0.5557 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.6955 matched_ious: 0.5541 2023/03/22 22:56:07 - mmengine - INFO - Epoch(train) [15][2700/3862] lr: 4.0903e-04 eta: 6:05:03 time: 1.0747 data_time: 0.0118 memory: 9177 grad_norm: 0.9531 loss: 1.3389 loss_heatmap: 0.5603 layer_-1_loss_cls: 0.0853 layer_-1_loss_bbox: 0.6932 matched_ious: 0.5323 2023/03/22 22:57:00 - mmengine - INFO - Epoch(train) [15][2750/3862] lr: 4.0737e-04 eta: 6:04:10 time: 1.0646 data_time: 0.0118 memory: 9382 grad_norm: 0.8360 loss: 1.3323 loss_heatmap: 0.5524 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.6965 matched_ious: 0.5093 2023/03/22 22:57:53 - mmengine - INFO - Epoch(train) [15][2800/3862] lr: 4.0570e-04 eta: 6:03:16 time: 1.0673 data_time: 0.0120 memory: 9213 grad_norm: 0.7196 loss: 1.3228 loss_heatmap: 0.5660 layer_-1_loss_cls: 0.0870 layer_-1_loss_bbox: 0.6698 matched_ious: 0.5055 2023/03/22 22:58:47 - mmengine - INFO - Epoch(train) [15][2850/3862] lr: 4.0404e-04 eta: 6:02:23 time: 1.0758 data_time: 0.0119 memory: 9560 grad_norm: 0.9880 loss: 1.3539 loss_heatmap: 0.5593 layer_-1_loss_cls: 0.0839 layer_-1_loss_bbox: 0.7106 matched_ious: 0.5777 2023/03/22 22:59:40 - mmengine - INFO - Epoch(train) [15][2900/3862] lr: 4.0238e-04 eta: 6:01:29 time: 1.0685 data_time: 0.0116 memory: 9048 grad_norm: 0.8721 loss: 1.4382 loss_heatmap: 0.5951 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.7545 matched_ious: 0.5536 2023/03/22 23:00:15 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 23:00:34 - mmengine - INFO - Epoch(train) [15][2950/3862] lr: 4.0072e-04 eta: 6:00:36 time: 1.0700 data_time: 0.0116 memory: 9171 grad_norm: 0.7358 loss: 1.3466 loss_heatmap: 0.5753 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.6829 matched_ious: 0.5644 2023/03/22 23:01:27 - mmengine - INFO - Epoch(train) [15][3000/3862] lr: 3.9906e-04 eta: 5:59:42 time: 1.0638 data_time: 0.0118 memory: 9326 grad_norm: 0.7336 loss: 1.3485 loss_heatmap: 0.5580 layer_-1_loss_cls: 0.0837 layer_-1_loss_bbox: 0.7069 matched_ious: 0.5295 2023/03/22 23:02:21 - mmengine - INFO - Epoch(train) [15][3050/3862] lr: 3.9740e-04 eta: 5:58:49 time: 1.0707 data_time: 0.0117 memory: 9138 grad_norm: 0.6486 loss: 1.3373 loss_heatmap: 0.5681 layer_-1_loss_cls: 0.0843 layer_-1_loss_bbox: 0.6849 matched_ious: 0.5665 2023/03/22 23:03:14 - mmengine - INFO - Epoch(train) [15][3100/3862] lr: 3.9574e-04 eta: 5:57:55 time: 1.0642 data_time: 0.0117 memory: 9037 grad_norm: 0.6513 loss: 1.3660 loss_heatmap: 0.5722 layer_-1_loss_cls: 0.0861 layer_-1_loss_bbox: 0.7077 matched_ious: 0.5270 2023/03/22 23:04:07 - mmengine - INFO - Epoch(train) [15][3150/3862] lr: 3.9408e-04 eta: 5:57:02 time: 1.0670 data_time: 0.0120 memory: 9077 grad_norm: 0.7454 loss: 1.3754 loss_heatmap: 0.5756 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.7162 matched_ious: 0.5741 2023/03/22 23:05:01 - mmengine - INFO - Epoch(train) [15][3200/3862] lr: 3.9243e-04 eta: 5:56:08 time: 1.0687 data_time: 0.0117 memory: 9214 grad_norm: 0.6622 loss: 1.3409 loss_heatmap: 0.5750 layer_-1_loss_cls: 0.0880 layer_-1_loss_bbox: 0.6779 matched_ious: 0.5417 2023/03/22 23:05:54 - mmengine - INFO - Epoch(train) [15][3250/3862] lr: 3.9077e-04 eta: 5:55:15 time: 1.0681 data_time: 0.0120 memory: 9524 grad_norm: 0.6708 loss: 1.3470 loss_heatmap: 0.5624 layer_-1_loss_cls: 0.0822 layer_-1_loss_bbox: 0.7024 matched_ious: 0.5455 2023/03/22 23:06:47 - mmengine - INFO - Epoch(train) [15][3300/3862] lr: 3.8912e-04 eta: 5:54:21 time: 1.0639 data_time: 0.0118 memory: 9094 grad_norm: 0.6750 loss: 1.3961 loss_heatmap: 0.5702 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.7408 matched_ious: 0.5423 2023/03/22 23:07:40 - mmengine - INFO - Epoch(train) [15][3350/3862] lr: 3.8747e-04 eta: 5:53:27 time: 1.0625 data_time: 0.0117 memory: 8936 grad_norm: 0.7974 loss: 1.3548 loss_heatmap: 0.5694 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.6979 matched_ious: 0.5600 2023/03/22 23:08:35 - mmengine - INFO - Epoch(train) [15][3400/3862] lr: 3.8582e-04 eta: 5:52:34 time: 1.0846 data_time: 0.0118 memory: 9089 grad_norm: 0.7285 loss: 1.3618 loss_heatmap: 0.5843 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.6899 matched_ious: 0.5387 2023/03/22 23:09:29 - mmengine - INFO - Epoch(train) [15][3450/3862] lr: 3.8417e-04 eta: 5:51:41 time: 1.0779 data_time: 0.0122 memory: 9175 grad_norm: 0.6943 loss: 1.3848 loss_heatmap: 0.5810 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.7163 matched_ious: 0.5481 2023/03/22 23:10:22 - mmengine - INFO - Epoch(train) [15][3500/3862] lr: 3.8252e-04 eta: 5:50:47 time: 1.0706 data_time: 0.0118 memory: 9022 grad_norm: 0.6880 loss: 1.3958 loss_heatmap: 0.5813 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.7279 matched_ious: 0.4990 2023/03/22 23:11:15 - mmengine - INFO - Epoch(train) [15][3550/3862] lr: 3.8087e-04 eta: 5:49:54 time: 1.0680 data_time: 0.0117 memory: 9095 grad_norm: 0.6805 loss: 1.3255 loss_heatmap: 0.5558 layer_-1_loss_cls: 0.0851 layer_-1_loss_bbox: 0.6847 matched_ious: 0.5440 2023/03/22 23:12:09 - mmengine - INFO - Epoch(train) [15][3600/3862] lr: 3.7923e-04 eta: 5:49:00 time: 1.0668 data_time: 0.0121 memory: 9124 grad_norm: 0.6830 loss: 1.3403 loss_heatmap: 0.5549 layer_-1_loss_cls: 0.0838 layer_-1_loss_bbox: 0.7016 matched_ious: 0.5446 2023/03/22 23:13:02 - mmengine - INFO - Epoch(train) [15][3650/3862] lr: 3.7758e-04 eta: 5:48:07 time: 1.0721 data_time: 0.0115 memory: 9182 grad_norm: 0.8084 loss: 1.3279 loss_heatmap: 0.5516 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.6911 matched_ious: 0.5129 2023/03/22 23:13:56 - mmengine - INFO - Epoch(train) [15][3700/3862] lr: 3.7594e-04 eta: 5:47:13 time: 1.0661 data_time: 0.0119 memory: 9179 grad_norm: 0.7011 loss: 1.3565 loss_heatmap: 0.5858 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.6816 matched_ious: 0.5817 2023/03/22 23:14:49 - mmengine - INFO - Epoch(train) [15][3750/3862] lr: 3.7430e-04 eta: 5:46:20 time: 1.0725 data_time: 0.0119 memory: 9314 grad_norm: 0.6899 loss: 1.3300 loss_heatmap: 0.5564 layer_-1_loss_cls: 0.0843 layer_-1_loss_bbox: 0.6892 matched_ious: 0.5791 2023/03/22 23:15:43 - mmengine - INFO - Epoch(train) [15][3800/3862] lr: 3.7266e-04 eta: 5:45:26 time: 1.0729 data_time: 0.0120 memory: 9047 grad_norm: 0.8596 loss: 1.2635 loss_heatmap: 0.5367 layer_-1_loss_cls: 0.0817 layer_-1_loss_bbox: 0.6451 matched_ious: 0.5325 2023/03/22 23:16:36 - mmengine - INFO - Epoch(train) [15][3850/3862] lr: 3.7102e-04 eta: 5:44:33 time: 1.0614 data_time: 0.0120 memory: 9088 grad_norm: 0.7056 loss: 1.3401 loss_heatmap: 0.5725 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.6819 matched_ious: 0.5576 2023/03/22 23:16:49 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230322_053447 2023/03/22 23:16:49 - mmengine - INFO - Saving checkpoint at 15 epochs 2023/03/22 23:16:59 - mmengine - INFO - Epoch(val) [15][ 50/753] eta: 0:01:50 time: 0.1569 data_time: 0.0047 memory: 9007 2023/03/22 23:17:06 - mmengine - INFO - Epoch(val) [15][100/753] eta: 0:01:38 time: 0.1458 data_time: 0.0035 memory: 730 2023/03/22 23:17:14 - mmengine - INFO - Epoch(val) [15][150/753] eta: 0:01:31 time: 0.1502 data_time: 0.0056 memory: 730 2023/03/22 23:17:22 - mmengine - INFO - Epoch(val) [15][200/753] eta: 0:01:23 time: 0.1521 data_time: 0.0034 memory: 730 2023/03/22 23:17:29 - mmengine - INFO - Epoch(val) [15][250/753] eta: 0:01:15 time: 0.1502 data_time: 0.0042 memory: 730 2023/03/22 23:17:36 - mmengine - INFO - Epoch(val) [15][300/753] eta: 0:01:08 time: 0.1456 data_time: 0.0042 memory: 730 2023/03/22 23:17:44 - mmengine - INFO - Epoch(val) [15][350/753] eta: 0:01:00 time: 0.1456 data_time: 0.0038 memory: 730 2023/03/22 23:17:50 - mmengine - INFO - Epoch(val) [15][400/753] eta: 0:00:52 time: 0.1353 data_time: 0.0035 memory: 730 2023/03/22 23:17:58 - mmengine - INFO - Epoch(val) [15][450/753] eta: 0:00:44 time: 0.1458 data_time: 0.0037 memory: 730 2023/03/22 23:18:06 - mmengine - INFO - Epoch(val) [15][500/753] eta: 0:00:37 time: 0.1671 data_time: 0.0037 memory: 730 2023/03/22 23:18:13 - mmengine - INFO - Epoch(val) [15][550/753] eta: 0:00:30 time: 0.1436 data_time: 0.0053 memory: 730 2023/03/22 23:18:21 - mmengine - INFO - Epoch(val) [15][600/753] eta: 0:00:22 time: 0.1542 data_time: 0.0040 memory: 730 2023/03/22 23:18:29 - mmengine - INFO - Epoch(val) [15][650/753] eta: 0:00:15 time: 0.1578 data_time: 0.0042 memory: 730 2023/03/22 23:18:37 - mmengine - INFO - Epoch(val) [15][700/753] eta: 0:00:07 time: 0.1567 data_time: 0.0031 memory: 730 2023/03/22 23:18:45 - mmengine - INFO - Epoch(val) [15][750/753] eta: 0:00:00 time: 0.1593 data_time: 0.0039 memory: 730 2023/03/22 23:30:15 - mmengine - INFO - Epoch(val) [15][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.7734 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8680 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.8939 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9097 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1793 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1551 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.1003 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2999 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1840 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2911 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2552 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.3091 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2849 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1883 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.3645 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.5483 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6412 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.6758 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3564 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1874 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0995 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2443 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2352 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0186 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.1244 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.2215 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.3269 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6749 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4120 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.9224 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1297 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3248 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4514 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7180 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8258 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8509 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3472 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1870 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0516 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4824 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2454 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1139 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.3626 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.5169 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.5717 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5386 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2055 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.4996 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1953 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1626 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.5909 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.6880 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7289 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7428 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.1933 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2922 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0619 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.4996 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.5638 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.5743 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.5832 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1931 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2419 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2812 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4736 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2457 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.3698 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.3766 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.3770 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.3797 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1520 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2614 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3898 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2221 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0197 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8365 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8509 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8631 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8751 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1415 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2890 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3758 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2315 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0892 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.6791 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.6934 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.7136 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.7481 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1343 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3208 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6610 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.5878data_time: 0.0039 time: 0.1577 2023/03/22 23:30:15 - mmengine - INFO - Disable ObjectSample 2023/03/23 10:05:00 - mmengine - INFO - Load checkpoint from logs/bevfusion_only_lidar_valid_flag/epoch_15.pth 2023/03/23 10:05:00 - mmengine - INFO - resumed epoch: 15, iter: 57930 2023/03/23 10:05:00 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/03/23 10:05:00 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/03/23 10:05:00 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/zhangjingwei/mmdetection3d_1/logs/bevfusion_only_lidar_valid_flag. 2023/03/23 10:05:00 - mmengine - INFO - Disable ObjectSample 2023/03/23 10:06:15 - mmengine - INFO - Epoch(train) [16][ 50/3862] lr: 3.6899e-04 eta: 8:05:01 time: 1.5110 data_time: 0.0356 memory: 9152 grad_norm: 1.0014 loss: 1.3210 loss_heatmap: 0.5951 layer_-1_loss_cls: 0.1015 layer_-1_loss_bbox: 0.6244 matched_ious: 0.5011 2023/03/23 10:06:34 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 10:07:02 - mmengine - INFO - Epoch(train) [16][ 100/3862] lr: 3.6736e-04 eta: 6:30:34 time: 0.9289 data_time: 0.0085 memory: 9156 grad_norm: 0.9496 loss: 1.3149 loss_heatmap: 0.5833 layer_-1_loss_cls: 0.0948 layer_-1_loss_bbox: 0.6368 matched_ious: 0.5807 2023/03/23 10:07:48 - mmengine - INFO - Epoch(train) [16][ 150/3862] lr: 3.6573e-04 eta: 5:58:43 time: 0.9302 data_time: 0.0084 memory: 9037 grad_norm: 1.1416 loss: 1.3599 loss_heatmap: 0.5987 layer_-1_loss_cls: 0.0963 layer_-1_loss_bbox: 0.6649 matched_ious: 0.5124 2023/03/23 10:08:35 - mmengine - INFO - Epoch(train) [16][ 200/3862] lr: 3.6409e-04 eta: 5:42:48 time: 0.9354 data_time: 0.0085 memory: 9066 grad_norm: 0.8580 loss: 1.2986 loss_heatmap: 0.5941 layer_-1_loss_cls: 0.1002 layer_-1_loss_bbox: 0.6043 matched_ious: 0.5592 2023/03/23 10:09:21 - mmengine - INFO - Epoch(train) [16][ 250/3862] lr: 3.6246e-04 eta: 5:32:19 time: 0.9254 data_time: 0.0084 memory: 9031 grad_norm: 0.9267 loss: 1.3238 loss_heatmap: 0.5981 layer_-1_loss_cls: 0.0955 layer_-1_loss_bbox: 0.6302 matched_ious: 0.5873 2023/03/23 10:10:08 - mmengine - INFO - Epoch(train) [16][ 300/3862] lr: 3.6084e-04 eta: 5:24:52 time: 0.9214 data_time: 0.0086 memory: 8861 grad_norm: 0.9137 loss: 1.2386 loss_heatmap: 0.5519 layer_-1_loss_cls: 0.0902 layer_-1_loss_bbox: 0.5964 matched_ious: 0.5638 2023/03/23 10:10:54 - mmengine - INFO - Epoch(train) [16][ 350/3862] lr: 3.5921e-04 eta: 5:19:28 time: 0.9248 data_time: 0.0085 memory: 9193 grad_norm: 0.8506 loss: 1.2648 loss_heatmap: 0.5635 layer_-1_loss_cls: 0.0915 layer_-1_loss_bbox: 0.6097 matched_ious: 0.5799 2023/03/23 10:11:40 - mmengine - INFO - Epoch(train) [16][ 400/3862] lr: 3.5758e-04 eta: 5:15:02 time: 0.9198 data_time: 0.0084 memory: 8899 grad_norm: 0.8822 loss: 1.3042 loss_heatmap: 0.5760 layer_-1_loss_cls: 0.0935 layer_-1_loss_bbox: 0.6347 matched_ious: 0.5159 2023/03/23 10:12:26 - mmengine - INFO - Epoch(train) [16][ 450/3862] lr: 3.5596e-04 eta: 5:11:48 time: 0.9311 data_time: 0.0085 memory: 9219 grad_norm: 0.9340 loss: 1.2969 loss_heatmap: 0.5867 layer_-1_loss_cls: 0.0933 layer_-1_loss_bbox: 0.6170 matched_ious: 0.6008 2023/03/23 10:13:13 - mmengine - INFO - Epoch(train) [16][ 500/3862] lr: 3.5434e-04 eta: 5:08:58 time: 0.9276 data_time: 0.0084 memory: 9151 grad_norm: 0.8633 loss: 1.3118 loss_heatmap: 0.5866 layer_-1_loss_cls: 0.0981 layer_-1_loss_bbox: 0.6270 matched_ious: 0.5156 2023/03/23 10:13:59 - mmengine - INFO - Epoch(train) [16][ 550/3862] lr: 3.5272e-04 eta: 5:06:29 time: 0.9273 data_time: 0.0087 memory: 8961 grad_norm: 0.9225 loss: 1.2208 loss_heatmap: 0.5591 layer_-1_loss_cls: 0.0913 layer_-1_loss_bbox: 0.5704 matched_ious: 0.5202 2023/03/23 10:14:45 - mmengine - INFO - Epoch(train) [16][ 600/3862] lr: 3.5110e-04 eta: 5:04:19 time: 0.9283 data_time: 0.0086 memory: 9160 grad_norm: 0.8786 loss: 1.2799 loss_heatmap: 0.5746 layer_-1_loss_cls: 0.0923 layer_-1_loss_bbox: 0.6130 matched_ious: 0.6416 2023/03/23 10:15:32 - mmengine - INFO - Epoch(train) [16][ 650/3862] lr: 3.4948e-04 eta: 5:02:15 time: 0.9235 data_time: 0.0084 memory: 9499 grad_norm: 0.9449 loss: 1.2346 loss_heatmap: 0.5598 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.5829 matched_ious: 0.6158 2023/03/23 10:16:18 - mmengine - INFO - Epoch(train) [16][ 700/3862] lr: 3.4787e-04 eta: 5:00:25 time: 0.9259 data_time: 0.0085 memory: 8893 grad_norm: 0.9200 loss: 1.2645 loss_heatmap: 0.5776 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.5973 matched_ious: 0.5756 2023/03/23 10:17:04 - mmengine - INFO - Epoch(train) [16][ 750/3862] lr: 3.4625e-04 eta: 4:58:39 time: 0.9220 data_time: 0.0083 memory: 8896 grad_norm: 1.0547 loss: 1.3001 loss_heatmap: 0.6015 layer_-1_loss_cls: 0.0930 layer_-1_loss_bbox: 0.6055 matched_ious: 0.5958 2023/03/23 10:17:50 - mmengine - INFO - Epoch(train) [16][ 800/3862] lr: 3.4464e-04 eta: 4:56:56 time: 0.9183 data_time: 0.0086 memory: 9086 grad_norm: 0.8833 loss: 1.2069 loss_heatmap: 0.5509 layer_-1_loss_cls: 0.0908 layer_-1_loss_bbox: 0.5652 matched_ious: 0.5137 2023/03/23 10:18:37 - mmengine - INFO - Epoch(train) [16][ 850/3862] lr: 3.4303e-04 eta: 4:55:54 time: 0.9492 data_time: 0.0084 memory: 9097 grad_norm: 0.8850 loss: 1.2913 loss_heatmap: 0.5789 layer_-1_loss_cls: 0.0942 layer_-1_loss_bbox: 0.6181 matched_ious: 0.5029 2023/03/23 10:19:24 - mmengine - INFO - Epoch(train) [16][ 900/3862] lr: 3.4142e-04 eta: 4:54:36 time: 0.9326 data_time: 0.0089 memory: 8961 grad_norm: 0.9285 loss: 1.2061 loss_heatmap: 0.5497 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.5688 matched_ious: 0.5837 2023/03/23 10:20:10 - mmengine - INFO - Epoch(train) [16][ 950/3862] lr: 3.3982e-04 eta: 4:53:13 time: 0.9238 data_time: 0.0088 memory: 9341 grad_norm: 0.8870 loss: 1.2653 loss_heatmap: 0.5735 layer_-1_loss_cls: 0.0926 layer_-1_loss_bbox: 0.5991 matched_ious: 0.5155 2023/03/23 10:20:57 - mmengine - INFO - Epoch(train) [16][1000/3862] lr: 3.3821e-04 eta: 4:52:02 time: 0.9331 data_time: 0.0087 memory: 9217 grad_norm: 0.8890 loss: 1.2134 loss_heatmap: 0.5322 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5958 matched_ious: 0.5792 2023/03/23 10:21:43 - mmengine - INFO - Epoch(train) [16][1050/3862] lr: 3.3661e-04 eta: 4:50:49 time: 0.9288 data_time: 0.0089 memory: 9072 grad_norm: 0.8688 loss: 1.2886 loss_heatmap: 0.5861 layer_-1_loss_cls: 0.0976 layer_-1_loss_bbox: 0.6050 matched_ious: 0.5424 2023/03/23 10:22:02 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 10:22:30 - mmengine - INFO - Epoch(train) [16][1100/3862] lr: 3.3501e-04 eta: 4:49:38 time: 0.9267 data_time: 0.0088 memory: 9145 grad_norm: 0.8518 loss: 1.2364 loss_heatmap: 0.5556 layer_-1_loss_cls: 0.0870 layer_-1_loss_bbox: 0.5938 matched_ious: 0.6090 2023/03/23 10:23:16 - mmengine - INFO - Epoch(train) [16][1150/3862] lr: 3.3341e-04 eta: 4:48:24 time: 0.9213 data_time: 0.0089 memory: 9249 grad_norm: 0.9030 loss: 1.2127 loss_heatmap: 0.5605 layer_-1_loss_cls: 0.0922 layer_-1_loss_bbox: 0.5600 matched_ious: 0.5725 2023/03/23 10:24:02 - mmengine - INFO - Epoch(train) [16][1200/3862] lr: 3.3181e-04 eta: 4:47:19 time: 0.9300 data_time: 0.0089 memory: 9257 grad_norm: 0.8104 loss: 1.3185 loss_heatmap: 0.5842 layer_-1_loss_cls: 0.0922 layer_-1_loss_bbox: 0.6421 matched_ious: 0.5368 2023/03/23 10:24:49 - mmengine - INFO - Epoch(train) [16][1250/3862] lr: 3.3022e-04 eta: 4:46:15 time: 0.9290 data_time: 0.0088 memory: 9065 grad_norm: 0.8503 loss: 1.1699 loss_heatmap: 0.5317 layer_-1_loss_cls: 0.0860 layer_-1_loss_bbox: 0.5522 matched_ious: 0.5372 2023/03/23 10:25:35 - mmengine - INFO - Epoch(train) [16][1300/3862] lr: 3.2863e-04 eta: 4:45:08 time: 0.9231 data_time: 0.0087 memory: 9130 grad_norm: 0.8147 loss: 1.2701 loss_heatmap: 0.5925 layer_-1_loss_cls: 0.0940 layer_-1_loss_bbox: 0.5836 matched_ious: 0.5354 2023/03/23 10:26:21 - mmengine - INFO - Epoch(train) [16][1350/3862] lr: 3.2703e-04 eta: 4:44:07 time: 0.9300 data_time: 0.0090 memory: 9413 grad_norm: 0.8278 loss: 1.1541 loss_heatmap: 0.5361 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.5297 matched_ious: 0.5835 2023/03/23 10:27:08 - mmengine - INFO - Epoch(train) [16][1400/3862] lr: 3.2545e-04 eta: 4:43:04 time: 0.9245 data_time: 0.0087 memory: 8999 grad_norm: 0.9610 loss: 1.2548 loss_heatmap: 0.5681 layer_-1_loss_cls: 0.0875 layer_-1_loss_bbox: 0.5992 matched_ious: 0.5773 2023/03/23 10:27:54 - mmengine - INFO - Epoch(train) [16][1450/3862] lr: 3.2386e-04 eta: 4:42:01 time: 0.9238 data_time: 0.0092 memory: 8973 grad_norm: 0.8297 loss: 1.2528 loss_heatmap: 0.5652 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.5987 matched_ious: 0.5812 2023/03/23 10:28:40 - mmengine - INFO - Epoch(train) [16][1500/3862] lr: 3.2227e-04 eta: 4:41:01 time: 0.9263 data_time: 0.0090 memory: 9091 grad_norm: 0.8615 loss: 1.2673 loss_heatmap: 0.5973 layer_-1_loss_cls: 0.0957 layer_-1_loss_bbox: 0.5743 matched_ious: 0.6278 2023/03/23 10:29:26 - mmengine - INFO - Epoch(train) [16][1550/3862] lr: 3.2069e-04 eta: 4:40:02 time: 0.9262 data_time: 0.0088 memory: 9051 grad_norm: 0.8831 loss: 1.2086 loss_heatmap: 0.5645 layer_-1_loss_cls: 0.0908 layer_-1_loss_bbox: 0.5534 matched_ious: 0.5547 2023/03/23 10:30:13 - mmengine - INFO - Epoch(train) [16][1600/3862] lr: 3.1911e-04 eta: 4:39:06 time: 0.9295 data_time: 0.0086 memory: 8911 grad_norm: 0.8670 loss: 1.2294 loss_heatmap: 0.5792 layer_-1_loss_cls: 0.0909 layer_-1_loss_bbox: 0.5593 matched_ious: 0.6057 2023/03/23 10:30:59 - mmengine - INFO - Epoch(train) [16][1650/3862] lr: 3.1753e-04 eta: 4:38:08 time: 0.9249 data_time: 0.0089 memory: 9158 grad_norm: 0.8492 loss: 1.2820 loss_heatmap: 0.5761 layer_-1_loss_cls: 0.0930 layer_-1_loss_bbox: 0.6129 matched_ious: 0.5495 2023/03/23 10:31:46 - mmengine - INFO - Epoch(train) [16][1700/3862] lr: 3.1595e-04 eta: 4:37:11 time: 0.9264 data_time: 0.0089 memory: 9028 grad_norm: 0.8056 loss: 1.2600 loss_heatmap: 0.5575 layer_-1_loss_cls: 0.0862 layer_-1_loss_bbox: 0.6163 matched_ious: 0.5829 2023/03/23 10:32:31 - mmengine - INFO - Epoch(train) [16][1750/3862] lr: 3.1438e-04 eta: 4:36:11 time: 0.9186 data_time: 0.0089 memory: 8810 grad_norm: 0.8356 loss: 1.2158 loss_heatmap: 0.5699 layer_-1_loss_cls: 0.0905 layer_-1_loss_bbox: 0.5554 matched_ious: 0.5481 2023/03/23 10:33:18 - mmengine - INFO - Epoch(train) [16][1800/3862] lr: 3.1281e-04 eta: 4:35:13 time: 0.9235 data_time: 0.0086 memory: 9092 grad_norm: 0.9038 loss: 1.2736 loss_heatmap: 0.5823 layer_-1_loss_cls: 0.0907 layer_-1_loss_bbox: 0.6006 matched_ious: 0.5423 2023/03/23 10:34:04 - mmengine - INFO - Epoch(train) [16][1850/3862] lr: 3.1124e-04 eta: 4:34:19 time: 0.9285 data_time: 0.0088 memory: 9264 grad_norm: 1.2295 loss: 1.2678 loss_heatmap: 0.5762 layer_-1_loss_cls: 0.0918 layer_-1_loss_bbox: 0.5999 matched_ious: 0.5644 2023/03/23 10:34:50 - mmengine - INFO - Epoch(train) [16][1900/3862] lr: 3.0967e-04 eta: 4:33:26 time: 0.9280 data_time: 0.0088 memory: 9092 grad_norm: 0.8628 loss: 1.1898 loss_heatmap: 0.5430 layer_-1_loss_cls: 0.0887 layer_-1_loss_bbox: 0.5581 matched_ious: 0.7021 2023/03/23 10:35:37 - mmengine - INFO - Epoch(train) [16][1950/3862] lr: 3.0810e-04 eta: 4:32:33 time: 0.9311 data_time: 0.0090 memory: 8895 grad_norm: 0.8890 loss: 1.2161 loss_heatmap: 0.5664 layer_-1_loss_cls: 0.0896 layer_-1_loss_bbox: 0.5601 matched_ious: 0.6120 2023/03/23 10:36:24 - mmengine - INFO - Epoch(train) [16][2000/3862] lr: 3.0654e-04 eta: 4:31:43 time: 0.9353 data_time: 0.0087 memory: 9065 grad_norm: 0.9182 loss: 1.1882 loss_heatmap: 0.5405 layer_-1_loss_cls: 0.0855 layer_-1_loss_bbox: 0.5623 matched_ious: 0.5864 2023/03/23 10:37:10 - mmengine - INFO - Epoch(train) [16][2050/3862] lr: 3.0498e-04 eta: 4:30:51 time: 0.9292 data_time: 0.0086 memory: 9083 grad_norm: 1.0136 loss: 1.2485 loss_heatmap: 0.5536 layer_-1_loss_cls: 0.0863 layer_-1_loss_bbox: 0.6086 matched_ious: 0.5164 2023/03/23 10:37:29 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 10:37:56 - mmengine - INFO - Epoch(train) [16][2100/3862] lr: 3.0342e-04 eta: 4:29:55 time: 0.9199 data_time: 0.0085 memory: 8975 grad_norm: 0.8630 loss: 1.1796 loss_heatmap: 0.5448 layer_-1_loss_cls: 0.0867 layer_-1_loss_bbox: 0.5481 matched_ious: 0.5603 2023/03/23 10:38:43 - mmengine - INFO - Epoch(train) [16][2150/3862] lr: 3.0186e-04 eta: 4:29:07 time: 0.9391 data_time: 0.0089 memory: 9005 grad_norm: 0.9008 loss: 1.2168 loss_heatmap: 0.5540 layer_-1_loss_cls: 0.0891 layer_-1_loss_bbox: 0.5737 matched_ious: 0.5291 2023/03/23 10:39:29 - mmengine - INFO - Epoch(train) [16][2200/3862] lr: 3.0031e-04 eta: 4:28:13 time: 0.9239 data_time: 0.0086 memory: 8977 grad_norm: 0.7798 loss: 1.1977 loss_heatmap: 0.5591 layer_-1_loss_cls: 0.0905 layer_-1_loss_bbox: 0.5481 matched_ious: 0.5766 2023/03/23 10:40:16 - mmengine - INFO - Epoch(train) [16][2250/3862] lr: 2.9875e-04 eta: 4:27:21 time: 0.9261 data_time: 0.0085 memory: 9105 grad_norm: 0.8084 loss: 1.1424 loss_heatmap: 0.5183 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.5405 matched_ious: 0.5799 2023/03/23 10:41:02 - mmengine - INFO - Epoch(train) [16][2300/3862] lr: 2.9720e-04 eta: 4:26:27 time: 0.9204 data_time: 0.0084 memory: 9085 grad_norm: 0.8482 loss: 1.1567 loss_heatmap: 0.5285 layer_-1_loss_cls: 0.0844 layer_-1_loss_bbox: 0.5438 matched_ious: 0.5415 2023/03/23 10:41:48 - mmengine - INFO - Epoch(train) [16][2350/3862] lr: 2.9565e-04 eta: 4:25:31 time: 0.9172 data_time: 0.0086 memory: 9014 grad_norm: 0.8974 loss: 1.1662 loss_heatmap: 0.5331 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.5481 matched_ious: 0.6064 2023/03/23 10:42:34 - mmengine - INFO - Epoch(train) [16][2400/3862] lr: 2.9411e-04 eta: 4:24:40 time: 0.9265 data_time: 0.0087 memory: 8889 grad_norm: 0.8478 loss: 1.1911 loss_heatmap: 0.5483 layer_-1_loss_cls: 0.0889 layer_-1_loss_bbox: 0.5539 matched_ious: 0.6336 2023/03/23 10:43:20 - mmengine - INFO - Epoch(train) [16][2450/3862] lr: 2.9257e-04 eta: 4:23:48 time: 0.9238 data_time: 0.0085 memory: 9003 grad_norm: 0.8184 loss: 1.2385 loss_heatmap: 0.5550 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.5947 matched_ious: 0.5834 2023/03/23 10:44:07 - mmengine - INFO - Epoch(train) [16][2500/3862] lr: 2.9103e-04 eta: 4:22:59 time: 0.9330 data_time: 0.0090 memory: 8897 grad_norm: 0.8437 loss: 1.2503 loss_heatmap: 0.5592 layer_-1_loss_cls: 0.0903 layer_-1_loss_bbox: 0.6009 matched_ious: 0.5639 2023/03/23 10:44:53 - mmengine - INFO - Epoch(train) [16][2550/3862] lr: 2.8949e-04 eta: 4:22:06 time: 0.9222 data_time: 0.0085 memory: 9054 grad_norm: 0.8881 loss: 1.2047 loss_heatmap: 0.5377 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5816 matched_ious: 0.6006 2023/03/23 10:45:39 - mmengine - INFO - Epoch(train) [16][2600/3862] lr: 2.8795e-04 eta: 4:21:15 time: 0.9231 data_time: 0.0087 memory: 9030 grad_norm: 1.0591 loss: 1.2693 loss_heatmap: 0.5811 layer_-1_loss_cls: 0.0922 layer_-1_loss_bbox: 0.5960 matched_ious: 0.5844 2023/03/23 10:46:26 - mmengine - INFO - Epoch(train) [16][2650/3862] lr: 2.8642e-04 eta: 4:20:25 time: 0.9294 data_time: 0.0086 memory: 9036 grad_norm: 0.9168 loss: 1.1395 loss_heatmap: 0.5160 layer_-1_loss_cls: 0.0840 layer_-1_loss_bbox: 0.5396 matched_ious: 0.6319 2023/03/23 10:47:12 - mmengine - INFO - Epoch(train) [16][2700/3862] lr: 2.8489e-04 eta: 4:19:33 time: 0.9216 data_time: 0.0085 memory: 9070 grad_norm: 0.8633 loss: 1.2163 loss_heatmap: 0.5532 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.5773 matched_ious: 0.6070 2023/03/23 10:47:58 - mmengine - INFO - Epoch(train) [16][2750/3862] lr: 2.8336e-04 eta: 4:18:42 time: 0.9248 data_time: 0.0084 memory: 9195 grad_norm: 0.9099 loss: 1.2413 loss_heatmap: 0.5574 layer_-1_loss_cls: 0.0891 layer_-1_loss_bbox: 0.5948 matched_ious: 0.5778 2023/03/23 10:48:44 - mmengine - INFO - Epoch(train) [16][2800/3862] lr: 2.8183e-04 eta: 4:17:51 time: 0.9210 data_time: 0.0086 memory: 9104 grad_norm: 0.8674 loss: 1.2244 loss_heatmap: 0.5494 layer_-1_loss_cls: 0.0851 layer_-1_loss_bbox: 0.5899 matched_ious: 0.5693 2023/03/23 10:49:30 - mmengine - INFO - Epoch(train) [16][2850/3862] lr: 2.8031e-04 eta: 4:16:59 time: 0.9219 data_time: 0.0088 memory: 8886 grad_norm: 0.8623 loss: 1.2398 loss_heatmap: 0.5628 layer_-1_loss_cls: 0.0901 layer_-1_loss_bbox: 0.5869 matched_ious: 0.5548 2023/03/23 10:50:16 - mmengine - INFO - Epoch(train) [16][2900/3862] lr: 2.7879e-04 eta: 4:16:09 time: 0.9258 data_time: 0.0087 memory: 9581 grad_norm: 0.7997 loss: 1.2182 loss_heatmap: 0.5533 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.5782 matched_ious: 0.5233 2023/03/23 10:51:03 - mmengine - INFO - Epoch(train) [16][2950/3862] lr: 2.7727e-04 eta: 4:15:20 time: 0.9268 data_time: 0.0089 memory: 8968 grad_norm: 0.9482 loss: 1.1806 loss_heatmap: 0.5239 layer_-1_loss_cls: 0.0879 layer_-1_loss_bbox: 0.5688 matched_ious: 0.5458 2023/03/23 10:51:49 - mmengine - INFO - Epoch(train) [16][3000/3862] lr: 2.7575e-04 eta: 4:14:32 time: 0.9342 data_time: 0.0087 memory: 9219 grad_norm: 0.8606 loss: 1.2332 loss_heatmap: 0.5396 layer_-1_loss_cls: 0.0862 layer_-1_loss_bbox: 0.6074 matched_ious: 0.5654 2023/03/23 10:52:36 - mmengine - INFO - Epoch(train) [16][3050/3862] lr: 2.7424e-04 eta: 4:13:45 time: 0.9345 data_time: 0.0086 memory: 8890 grad_norm: 0.8300 loss: 1.2289 loss_heatmap: 0.5476 layer_-1_loss_cls: 0.0860 layer_-1_loss_bbox: 0.5953 matched_ious: 0.5318 2023/03/23 10:52:55 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 10:53:23 - mmengine - INFO - Epoch(train) [16][3100/3862] lr: 2.7273e-04 eta: 4:13:01 time: 0.9473 data_time: 0.0087 memory: 9011 grad_norm: 0.8244 loss: 1.1911 loss_heatmap: 0.5438 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.5614 matched_ious: 0.5705 2023/03/23 10:54:10 - mmengine - INFO - Epoch(train) [16][3150/3862] lr: 2.7122e-04 eta: 4:12:13 time: 0.9304 data_time: 0.0089 memory: 8863 grad_norm: 1.0243 loss: 1.2097 loss_heatmap: 0.5577 layer_-1_loss_cls: 0.0862 layer_-1_loss_bbox: 0.5658 matched_ious: 0.4471 2023/03/23 10:54:56 - mmengine - INFO - Epoch(train) [16][3200/3862] lr: 2.6971e-04 eta: 4:11:23 time: 0.9262 data_time: 0.0093 memory: 9054 grad_norm: 0.9766 loss: 1.1999 loss_heatmap: 0.5483 layer_-1_loss_cls: 0.0881 layer_-1_loss_bbox: 0.5635 matched_ious: 0.5746 2023/03/23 10:55:43 - mmengine - INFO - Epoch(train) [16][3250/3862] lr: 2.6821e-04 eta: 4:10:35 time: 0.9315 data_time: 0.0092 memory: 9099 grad_norm: 1.0018 loss: 1.1932 loss_heatmap: 0.5327 layer_-1_loss_cls: 0.0813 layer_-1_loss_bbox: 0.5793 matched_ious: 0.5426 2023/03/23 10:56:30 - mmengine - INFO - Epoch(train) [16][3300/3862] lr: 2.6671e-04 eta: 4:09:48 time: 0.9333 data_time: 0.0091 memory: 8964 grad_norm: 0.9182 loss: 1.2512 loss_heatmap: 0.5635 layer_-1_loss_cls: 0.0913 layer_-1_loss_bbox: 0.5964 matched_ious: 0.6344 2023/03/23 10:57:16 - mmengine - INFO - Epoch(train) [16][3350/3862] lr: 2.6521e-04 eta: 4:08:58 time: 0.9218 data_time: 0.0093 memory: 8759 grad_norm: 0.8767 loss: 1.2012 loss_heatmap: 0.5266 layer_-1_loss_cls: 0.0841 layer_-1_loss_bbox: 0.5905 matched_ious: 0.5480 2023/03/23 10:58:02 - mmengine - INFO - Epoch(train) [16][3400/3862] lr: 2.6372e-04 eta: 4:08:08 time: 0.9233 data_time: 0.0093 memory: 9131 grad_norm: 0.8508 loss: 1.1688 loss_heatmap: 0.5326 layer_-1_loss_cls: 0.0863 layer_-1_loss_bbox: 0.5500 matched_ious: 0.5890 2023/03/23 10:58:48 - mmengine - INFO - Epoch(train) [16][3450/3862] lr: 2.6223e-04 eta: 4:07:20 time: 0.9327 data_time: 0.0092 memory: 8854 grad_norm: 0.8748 loss: 1.2415 loss_heatmap: 0.5311 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.6247 matched_ious: 0.5785 2023/03/23 10:59:35 - mmengine - INFO - Epoch(train) [16][3500/3862] lr: 2.6074e-04 eta: 4:06:32 time: 0.9271 data_time: 0.0095 memory: 9311 grad_norm: 0.8437 loss: 1.1516 loss_heatmap: 0.5119 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5586 matched_ious: 0.5735 2023/03/23 11:00:21 - mmengine - INFO - Epoch(train) [16][3550/3862] lr: 2.5925e-04 eta: 4:05:43 time: 0.9258 data_time: 0.0094 memory: 8977 grad_norm: 0.8016 loss: 1.1875 loss_heatmap: 0.5492 layer_-1_loss_cls: 0.0876 layer_-1_loss_bbox: 0.5507 matched_ious: 0.6240 2023/03/23 11:01:08 - mmengine - INFO - Epoch(train) [16][3600/3862] lr: 2.5777e-04 eta: 4:04:54 time: 0.9291 data_time: 0.0095 memory: 9004 grad_norm: 0.9071 loss: 1.1867 loss_heatmap: 0.5378 layer_-1_loss_cls: 0.0866 layer_-1_loss_bbox: 0.5623 matched_ious: 0.4961 2023/03/23 11:01:54 - mmengine - INFO - Epoch(train) [16][3650/3862] lr: 2.5629e-04 eta: 4:04:06 time: 0.9261 data_time: 0.0094 memory: 9211 grad_norm: 0.8520 loss: 1.1876 loss_heatmap: 0.5407 layer_-1_loss_cls: 0.0856 layer_-1_loss_bbox: 0.5613 matched_ious: 0.6329 2023/03/23 11:02:40 - mmengine - INFO - Epoch(train) [16][3700/3862] lr: 2.5481e-04 eta: 4:03:18 time: 0.9294 data_time: 0.0093 memory: 9048 grad_norm: 0.8543 loss: 1.2143 loss_heatmap: 0.5549 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.5706 matched_ious: 0.5514 2023/03/23 11:03:27 - mmengine - INFO - Epoch(train) [16][3750/3862] lr: 2.5333e-04 eta: 4:02:29 time: 0.9253 data_time: 0.0093 memory: 9016 grad_norm: 0.8897 loss: 1.2671 loss_heatmap: 0.5757 layer_-1_loss_cls: 0.0920 layer_-1_loss_bbox: 0.5995 matched_ious: 0.5977 2023/03/23 11:04:13 - mmengine - INFO - Epoch(train) [16][3800/3862] lr: 2.5186e-04 eta: 4:01:42 time: 0.9329 data_time: 0.0092 memory: 9220 grad_norm: 0.8395 loss: 1.2297 loss_heatmap: 0.5595 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.5817 matched_ious: 0.6114 2023/03/23 11:05:00 - mmengine - INFO - Epoch(train) [16][3850/3862] lr: 2.5039e-04 eta: 4:00:55 time: 0.9340 data_time: 0.0094 memory: 9028 grad_norm: 0.8664 loss: 1.2380 loss_heatmap: 0.5526 layer_-1_loss_cls: 0.0899 layer_-1_loss_bbox: 0.5955 matched_ious: 0.5734 2023/03/23 11:05:11 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 11:05:59 - mmengine - INFO - Epoch(train) [17][ 50/3862] lr: 2.4857e-04 eta: 4:00:00 time: 0.9532 data_time: 0.0288 memory: 8992 grad_norm: 0.8295 loss: 1.1903 loss_heatmap: 0.5514 layer_-1_loss_cls: 0.0886 layer_-1_loss_bbox: 0.5503 matched_ious: 0.5495 2023/03/23 11:06:45 - mmengine - INFO - Epoch(train) [17][ 100/3862] lr: 2.4711e-04 eta: 3:59:12 time: 0.9303 data_time: 0.0095 memory: 9171 grad_norm: 0.8538 loss: 1.2314 loss_heatmap: 0.5601 layer_-1_loss_cls: 0.0898 layer_-1_loss_bbox: 0.5814 matched_ious: 0.5805 2023/03/23 11:07:31 - mmengine - INFO - Epoch(train) [17][ 150/3862] lr: 2.4565e-04 eta: 3:58:23 time: 0.9225 data_time: 0.0093 memory: 9235 grad_norm: 0.8286 loss: 1.2054 loss_heatmap: 0.5491 layer_-1_loss_cls: 0.0888 layer_-1_loss_bbox: 0.5675 matched_ious: 0.6440 2023/03/23 11:08:18 - mmengine - INFO - Epoch(train) [17][ 200/3862] lr: 2.4419e-04 eta: 3:57:35 time: 0.9272 data_time: 0.0093 memory: 8909 grad_norm: 0.8299 loss: 1.1939 loss_heatmap: 0.5391 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.5689 matched_ious: 0.5380 2023/03/23 11:08:25 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 11:09:04 - mmengine - INFO - Epoch(train) [17][ 250/3862] lr: 2.4273e-04 eta: 3:56:47 time: 0.9272 data_time: 0.0090 memory: 9147 grad_norm: 1.0774 loss: 1.3206 loss_heatmap: 0.5849 layer_-1_loss_cls: 0.0898 layer_-1_loss_bbox: 0.6460 matched_ious: 0.6007 2023/03/23 11:09:51 - mmengine - INFO - Epoch(train) [17][ 300/3862] lr: 2.4128e-04 eta: 3:55:59 time: 0.9271 data_time: 0.0091 memory: 9221 grad_norm: 0.8574 loss: 1.1693 loss_heatmap: 0.5319 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5517 matched_ious: 0.6223 2023/03/23 11:10:37 - mmengine - INFO - Epoch(train) [17][ 350/3862] lr: 2.3983e-04 eta: 3:55:11 time: 0.9289 data_time: 0.0091 memory: 9069 grad_norm: 0.9063 loss: 1.2541 loss_heatmap: 0.5527 layer_-1_loss_cls: 0.0891 layer_-1_loss_bbox: 0.6122 matched_ious: 0.5798 2023/03/23 11:11:25 - mmengine - INFO - Epoch(train) [17][ 400/3862] lr: 2.3839e-04 eta: 3:54:28 time: 0.9541 data_time: 0.0092 memory: 9102 grad_norm: 0.8541 loss: 1.2033 loss_heatmap: 0.5407 layer_-1_loss_cls: 0.0847 layer_-1_loss_bbox: 0.5779 matched_ious: 0.6221 2023/03/23 11:12:11 - mmengine - INFO - Epoch(train) [17][ 450/3862] lr: 2.3695e-04 eta: 3:53:40 time: 0.9280 data_time: 0.0091 memory: 9241 grad_norm: 0.7867 loss: 1.1661 loss_heatmap: 0.5270 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5538 matched_ious: 0.5612 2023/03/23 11:12:58 - mmengine - INFO - Epoch(train) [17][ 500/3862] lr: 2.3551e-04 eta: 3:52:52 time: 0.9304 data_time: 0.0092 memory: 9466 grad_norm: 0.8743 loss: 1.2645 loss_heatmap: 0.5652 layer_-1_loss_cls: 0.0860 layer_-1_loss_bbox: 0.6133 matched_ious: 0.5451 2023/03/23 11:13:44 - mmengine - INFO - Epoch(train) [17][ 550/3862] lr: 2.3407e-04 eta: 3:52:04 time: 0.9286 data_time: 0.0091 memory: 9006 grad_norm: 0.9476 loss: 1.1769 loss_heatmap: 0.5194 layer_-1_loss_cls: 0.0819 layer_-1_loss_bbox: 0.5756 matched_ious: 0.5655 2023/03/23 11:14:31 - mmengine - INFO - Epoch(train) [17][ 600/3862] lr: 2.3264e-04 eta: 3:51:17 time: 0.9329 data_time: 0.0090 memory: 9106 grad_norm: 0.8709 loss: 1.1760 loss_heatmap: 0.5416 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.5510 matched_ious: 0.6262 2023/03/23 11:15:17 - mmengine - INFO - Epoch(train) [17][ 650/3862] lr: 2.3121e-04 eta: 3:50:29 time: 0.9240 data_time: 0.0092 memory: 9210 grad_norm: 1.0038 loss: 1.1706 loss_heatmap: 0.5578 layer_-1_loss_cls: 0.0893 layer_-1_loss_bbox: 0.5235 matched_ious: 0.6197 2023/03/23 11:16:04 - mmengine - INFO - Epoch(train) [17][ 700/3862] lr: 2.2978e-04 eta: 3:49:43 time: 0.9403 data_time: 0.0093 memory: 8997 grad_norm: 0.9012 loss: 1.2111 loss_heatmap: 0.5613 layer_-1_loss_cls: 0.0894 layer_-1_loss_bbox: 0.5605 matched_ious: 0.5818 2023/03/23 11:16:50 - mmengine - INFO - Epoch(train) [17][ 750/3862] lr: 2.2835e-04 eta: 3:48:55 time: 0.9262 data_time: 0.0095 memory: 9005 grad_norm: 0.9210 loss: 1.2247 loss_heatmap: 0.5521 layer_-1_loss_cls: 0.0890 layer_-1_loss_bbox: 0.5836 matched_ious: 0.5669 2023/03/23 11:17:37 - mmengine - INFO - Epoch(train) [17][ 800/3862] lr: 2.2693e-04 eta: 3:48:07 time: 0.9293 data_time: 0.0093 memory: 8925 grad_norm: 0.8479 loss: 1.1979 loss_heatmap: 0.5447 layer_-1_loss_cls: 0.0864 layer_-1_loss_bbox: 0.5668 matched_ious: 0.6280 2023/03/23 11:18:23 - mmengine - INFO - Epoch(train) [17][ 850/3862] lr: 2.2551e-04 eta: 3:47:20 time: 0.9283 data_time: 0.0096 memory: 9240 grad_norm: 0.8391 loss: 1.2767 loss_heatmap: 0.5773 layer_-1_loss_cls: 0.0869 layer_-1_loss_bbox: 0.6125 matched_ious: 0.5714 2023/03/23 11:19:10 - mmengine - INFO - Epoch(train) [17][ 900/3862] lr: 2.2410e-04 eta: 3:46:33 time: 0.9334 data_time: 0.0092 memory: 8934 grad_norm: 0.8419 loss: 1.1431 loss_heatmap: 0.5272 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5307 matched_ious: 0.5545 2023/03/23 11:19:56 - mmengine - INFO - Epoch(train) [17][ 950/3862] lr: 2.2269e-04 eta: 3:45:45 time: 0.9265 data_time: 0.0092 memory: 9130 grad_norm: 0.9566 loss: 1.2085 loss_heatmap: 0.5481 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.5746 matched_ious: 0.5790 2023/03/23 11:20:42 - mmengine - INFO - Epoch(train) [17][1000/3862] lr: 2.2128e-04 eta: 3:44:57 time: 0.9250 data_time: 0.0093 memory: 8985 grad_norm: 0.9299 loss: 1.1615 loss_heatmap: 0.5193 layer_-1_loss_cls: 0.0816 layer_-1_loss_bbox: 0.5606 matched_ious: 0.5608 2023/03/23 11:21:29 - mmengine - INFO - Epoch(train) [17][1050/3862] lr: 2.1987e-04 eta: 3:44:10 time: 0.9298 data_time: 0.0092 memory: 8860 grad_norm: 0.8373 loss: 1.1842 loss_heatmap: 0.5305 layer_-1_loss_cls: 0.0813 layer_-1_loss_bbox: 0.5724 matched_ious: 0.5079 2023/03/23 11:22:15 - mmengine - INFO - Epoch(train) [17][1100/3862] lr: 2.1847e-04 eta: 3:43:22 time: 0.9277 data_time: 0.0094 memory: 8750 grad_norm: 0.8675 loss: 1.1956 loss_heatmap: 0.5351 layer_-1_loss_cls: 0.0822 layer_-1_loss_bbox: 0.5783 matched_ious: 0.4510 2023/03/23 11:23:02 - mmengine - INFO - Epoch(train) [17][1150/3862] lr: 2.1707e-04 eta: 3:42:35 time: 0.9335 data_time: 0.0091 memory: 9128 grad_norm: 0.8191 loss: 1.1553 loss_heatmap: 0.5299 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5432 matched_ious: 0.6164 2023/03/23 11:23:49 - mmengine - INFO - Epoch(train) [17][1200/3862] lr: 2.1568e-04 eta: 3:41:48 time: 0.9325 data_time: 0.0091 memory: 9198 grad_norm: 0.8249 loss: 1.1905 loss_heatmap: 0.5232 layer_-1_loss_cls: 0.0808 layer_-1_loss_bbox: 0.5865 matched_ious: 0.6112 2023/03/23 11:23:56 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 11:24:35 - mmengine - INFO - Epoch(train) [17][1250/3862] lr: 2.1428e-04 eta: 3:41:01 time: 0.9287 data_time: 0.0093 memory: 8946 grad_norm: 0.8414 loss: 1.2227 loss_heatmap: 0.5446 layer_-1_loss_cls: 0.0858 layer_-1_loss_bbox: 0.5922 matched_ious: 0.5616 2023/03/23 11:25:21 - mmengine - INFO - Epoch(train) [17][1300/3862] lr: 2.1290e-04 eta: 3:40:13 time: 0.9258 data_time: 0.0091 memory: 8925 grad_norm: 0.8605 loss: 1.1695 loss_heatmap: 0.5242 layer_-1_loss_cls: 0.0828 layer_-1_loss_bbox: 0.5625 matched_ious: 0.6175 2023/03/23 11:26:08 - mmengine - INFO - Epoch(train) [17][1350/3862] lr: 2.1151e-04 eta: 3:39:25 time: 0.9249 data_time: 0.0093 memory: 9207 grad_norm: 0.8230 loss: 1.1403 loss_heatmap: 0.5409 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5137 matched_ious: 0.5794 2023/03/23 11:26:54 - mmengine - INFO - Epoch(train) [17][1400/3862] lr: 2.1013e-04 eta: 3:38:38 time: 0.9309 data_time: 0.0091 memory: 8981 grad_norm: 0.8606 loss: 1.1440 loss_heatmap: 0.5087 layer_-1_loss_cls: 0.0853 layer_-1_loss_bbox: 0.5500 matched_ious: 0.5159 2023/03/23 11:27:41 - mmengine - INFO - Epoch(train) [17][1450/3862] lr: 2.0875e-04 eta: 3:37:51 time: 0.9297 data_time: 0.0091 memory: 9090 grad_norm: 0.8515 loss: 1.1441 loss_heatmap: 0.5112 layer_-1_loss_cls: 0.0829 layer_-1_loss_bbox: 0.5500 matched_ious: 0.5512 2023/03/23 11:28:27 - mmengine - INFO - Epoch(train) [17][1500/3862] lr: 2.0737e-04 eta: 3:37:04 time: 0.9305 data_time: 0.0090 memory: 9448 grad_norm: 0.8365 loss: 1.1556 loss_heatmap: 0.5327 layer_-1_loss_cls: 0.0838 layer_-1_loss_bbox: 0.5391 matched_ious: 0.6055 2023/03/23 11:29:14 - mmengine - INFO - Epoch(train) [17][1550/3862] lr: 2.0600e-04 eta: 3:36:18 time: 0.9415 data_time: 0.0090 memory: 8984 grad_norm: 0.8628 loss: 1.2114 loss_heatmap: 0.5567 layer_-1_loss_cls: 0.0848 layer_-1_loss_bbox: 0.5699 matched_ious: 0.6482 2023/03/23 11:30:01 - mmengine - INFO - Epoch(train) [17][1600/3862] lr: 2.0463e-04 eta: 3:35:30 time: 0.9284 data_time: 0.0092 memory: 9032 grad_norm: 0.9537 loss: 1.1677 loss_heatmap: 0.5414 layer_-1_loss_cls: 0.0878 layer_-1_loss_bbox: 0.5385 matched_ious: 0.5181 2023/03/23 11:30:47 - mmengine - INFO - Epoch(train) [17][1650/3862] lr: 2.0327e-04 eta: 3:34:43 time: 0.9279 data_time: 0.0094 memory: 9045 grad_norm: 0.9145 loss: 1.1770 loss_heatmap: 0.5516 layer_-1_loss_cls: 0.0840 layer_-1_loss_bbox: 0.5414 matched_ious: 0.5751 2023/03/23 11:31:33 - mmengine - INFO - Epoch(train) [17][1700/3862] lr: 2.0190e-04 eta: 3:33:56 time: 0.9273 data_time: 0.0091 memory: 9125 grad_norm: 0.8616 loss: 1.2132 loss_heatmap: 0.5486 layer_-1_loss_cls: 0.0862 layer_-1_loss_bbox: 0.5785 matched_ious: 0.6193 2023/03/23 11:32:20 - mmengine - INFO - Epoch(train) [17][1750/3862] lr: 2.0054e-04 eta: 3:33:08 time: 0.9264 data_time: 0.0092 memory: 9112 grad_norm: 0.8369 loss: 1.1976 loss_heatmap: 0.5320 layer_-1_loss_cls: 0.0831 layer_-1_loss_bbox: 0.5825 matched_ious: 0.6137 2023/03/23 11:33:06 - mmengine - INFO - Epoch(train) [17][1800/3862] lr: 1.9919e-04 eta: 3:32:21 time: 0.9298 data_time: 0.0093 memory: 9058 grad_norm: 0.8451 loss: 1.1815 loss_heatmap: 0.5217 layer_-1_loss_cls: 0.0825 layer_-1_loss_bbox: 0.5772 matched_ious: 0.5152 2023/03/23 11:33:53 - mmengine - INFO - Epoch(train) [17][1850/3862] lr: 1.9784e-04 eta: 3:31:33 time: 0.9264 data_time: 0.0091 memory: 8801 grad_norm: 0.8142 loss: 1.1599 loss_heatmap: 0.5311 layer_-1_loss_cls: 0.0859 layer_-1_loss_bbox: 0.5430 matched_ious: 0.5624 2023/03/23 11:34:39 - mmengine - INFO - Epoch(train) [17][1900/3862] lr: 1.9649e-04 eta: 3:30:46 time: 0.9278 data_time: 0.0092 memory: 9118 grad_norm: 0.8113 loss: 1.1538 loss_heatmap: 0.5121 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.5639 matched_ious: 0.6738 2023/03/23 11:35:25 - mmengine - INFO - Epoch(train) [17][1950/3862] lr: 1.9514e-04 eta: 3:29:58 time: 0.9251 data_time: 0.0091 memory: 8923 grad_norm: 0.8119 loss: 1.1798 loss_heatmap: 0.5464 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.5460 matched_ious: 0.5210 2023/03/23 11:36:12 - mmengine - INFO - Epoch(train) [17][2000/3862] lr: 1.9380e-04 eta: 3:29:11 time: 0.9269 data_time: 0.0091 memory: 8992 grad_norm: 0.8345 loss: 1.1499 loss_heatmap: 0.5248 layer_-1_loss_cls: 0.0840 layer_-1_loss_bbox: 0.5410 matched_ious: 0.5816 2023/03/23 11:36:58 - mmengine - INFO - Epoch(train) [17][2050/3862] lr: 1.9246e-04 eta: 3:28:23 time: 0.9259 data_time: 0.0089 memory: 8883 grad_norm: 0.7599 loss: 1.1452 loss_heatmap: 0.5243 layer_-1_loss_cls: 0.0835 layer_-1_loss_bbox: 0.5374 matched_ious: 0.5633 2023/03/23 11:37:44 - mmengine - INFO - Epoch(train) [17][2100/3862] lr: 1.9113e-04 eta: 3:27:36 time: 0.9272 data_time: 0.0093 memory: 9055 grad_norm: 0.8592 loss: 1.1635 loss_heatmap: 0.5371 layer_-1_loss_cls: 0.0828 layer_-1_loss_bbox: 0.5437 matched_ious: 0.6073 2023/03/23 11:38:30 - mmengine - INFO - Epoch(train) [17][2150/3862] lr: 1.8980e-04 eta: 3:26:48 time: 0.9224 data_time: 0.0091 memory: 8999 grad_norm: 0.8433 loss: 1.1419 loss_heatmap: 0.5386 layer_-1_loss_cls: 0.0863 layer_-1_loss_bbox: 0.5170 matched_ious: 0.5759 2023/03/23 11:39:17 - mmengine - INFO - Epoch(train) [17][2200/3862] lr: 1.8847e-04 eta: 3:26:01 time: 0.9309 data_time: 0.0091 memory: 8866 grad_norm: 0.8736 loss: 1.1673 loss_heatmap: 0.5067 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5799 matched_ious: 0.5527 2023/03/23 11:39:24 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 11:40:03 - mmengine - INFO - Epoch(train) [17][2250/3862] lr: 1.8715e-04 eta: 3:25:14 time: 0.9288 data_time: 0.0090 memory: 9290 grad_norm: 0.8308 loss: 1.1080 loss_heatmap: 0.5093 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.5153 matched_ious: 0.6086 2023/03/23 11:40:49 - mmengine - INFO - Epoch(train) [17][2300/3862] lr: 1.8583e-04 eta: 3:24:26 time: 0.9216 data_time: 0.0090 memory: 9073 grad_norm: 0.8151 loss: 1.1154 loss_heatmap: 0.4862 layer_-1_loss_cls: 0.0772 layer_-1_loss_bbox: 0.5520 matched_ious: 0.6021 2023/03/23 11:41:36 - mmengine - INFO - Epoch(train) [17][2350/3862] lr: 1.8451e-04 eta: 3:23:39 time: 0.9257 data_time: 0.0092 memory: 8979 grad_norm: 0.8352 loss: 1.1970 loss_heatmap: 0.5489 layer_-1_loss_cls: 0.0871 layer_-1_loss_bbox: 0.5610 matched_ious: 0.6218 2023/03/23 11:42:23 - mmengine - INFO - Epoch(train) [17][2400/3862] lr: 1.8320e-04 eta: 3:22:53 time: 0.9356 data_time: 0.0090 memory: 8886 grad_norm: 0.9056 loss: 1.1390 loss_heatmap: 0.5210 layer_-1_loss_cls: 0.0832 layer_-1_loss_bbox: 0.5348 matched_ious: 0.5681 2023/03/23 11:43:09 - mmengine - INFO - Epoch(train) [17][2450/3862] lr: 1.8189e-04 eta: 3:22:04 time: 0.9195 data_time: 0.0093 memory: 9407 grad_norm: 0.8348 loss: 1.1507 loss_heatmap: 0.5288 layer_-1_loss_cls: 0.0824 layer_-1_loss_bbox: 0.5395 matched_ious: 0.5895 2023/03/23 11:43:55 - mmengine - INFO - Epoch(train) [17][2500/3862] lr: 1.8058e-04 eta: 3:21:17 time: 0.9253 data_time: 0.0091 memory: 9511 grad_norm: 0.8281 loss: 1.1700 loss_heatmap: 0.5287 layer_-1_loss_cls: 0.0827 layer_-1_loss_bbox: 0.5585 matched_ious: 0.5686 2023/03/23 11:44:41 - mmengine - INFO - Epoch(train) [17][2550/3862] lr: 1.7928e-04 eta: 3:20:30 time: 0.9272 data_time: 0.0091 memory: 9124 grad_norm: 0.8709 loss: 1.2170 loss_heatmap: 0.5519 layer_-1_loss_cls: 0.0874 layer_-1_loss_bbox: 0.5777 matched_ious: 0.5873 2023/03/23 11:45:28 - mmengine - INFO - Epoch(train) [17][2600/3862] lr: 1.7798e-04 eta: 3:19:43 time: 0.9314 data_time: 0.0089 memory: 9106 grad_norm: 0.8668 loss: 1.1681 loss_heatmap: 0.5291 layer_-1_loss_cls: 0.0839 layer_-1_loss_bbox: 0.5550 matched_ious: 0.5897 2023/03/23 11:46:14 - mmengine - INFO - Epoch(train) [17][2650/3862] lr: 1.7669e-04 eta: 3:18:56 time: 0.9292 data_time: 0.0091 memory: 8788 grad_norm: 0.8620 loss: 1.1609 loss_heatmap: 0.5325 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5459 matched_ious: 0.5993 2023/03/23 11:47:02 - mmengine - INFO - Epoch(train) [17][2700/3862] lr: 1.7540e-04 eta: 3:18:11 time: 0.9459 data_time: 0.0093 memory: 9307 grad_norm: 0.8580 loss: 1.1124 loss_heatmap: 0.5208 layer_-1_loss_cls: 0.0841 layer_-1_loss_bbox: 0.5076 matched_ious: 0.5779 2023/03/23 11:47:48 - mmengine - INFO - Epoch(train) [17][2750/3862] lr: 1.7411e-04 eta: 3:17:23 time: 0.9262 data_time: 0.0091 memory: 9395 grad_norm: 0.8099 loss: 1.0950 loss_heatmap: 0.4972 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5178 matched_ious: 0.5688 2023/03/23 11:48:34 - mmengine - INFO - Epoch(train) [17][2800/3862] lr: 1.7283e-04 eta: 3:16:36 time: 0.9280 data_time: 0.0092 memory: 8785 grad_norm: 0.8741 loss: 1.1190 loss_heatmap: 0.5104 layer_-1_loss_cls: 0.0829 layer_-1_loss_bbox: 0.5258 matched_ious: 0.5196 2023/03/23 11:49:20 - mmengine - INFO - Epoch(train) [17][2850/3862] lr: 1.7155e-04 eta: 3:15:49 time: 0.9243 data_time: 0.0091 memory: 9248 grad_norm: 0.7641 loss: 1.1141 loss_heatmap: 0.5169 layer_-1_loss_cls: 0.0812 layer_-1_loss_bbox: 0.5160 matched_ious: 0.5775 2023/03/23 11:50:07 - mmengine - INFO - Epoch(train) [17][2900/3862] lr: 1.7027e-04 eta: 3:15:02 time: 0.9316 data_time: 0.0092 memory: 8685 grad_norm: 0.9281 loss: 1.1189 loss_heatmap: 0.5297 layer_-1_loss_cls: 0.0854 layer_-1_loss_bbox: 0.5038 matched_ious: 0.5828 2023/03/23 11:50:53 - mmengine - INFO - Epoch(train) [17][2950/3862] lr: 1.6900e-04 eta: 3:14:15 time: 0.9229 data_time: 0.0093 memory: 9202 grad_norm: 0.8066 loss: 1.1187 loss_heatmap: 0.5049 layer_-1_loss_cls: 0.0785 layer_-1_loss_bbox: 0.5353 matched_ious: 0.5485 2023/03/23 11:51:39 - mmengine - INFO - Epoch(train) [17][3000/3862] lr: 1.6773e-04 eta: 3:13:27 time: 0.9237 data_time: 0.0091 memory: 9071 grad_norm: 0.8379 loss: 1.2038 loss_heatmap: 0.5450 layer_-1_loss_cls: 0.0858 layer_-1_loss_bbox: 0.5730 matched_ious: 0.5450 2023/03/23 11:52:25 - mmengine - INFO - Epoch(train) [17][3050/3862] lr: 1.6647e-04 eta: 3:12:40 time: 0.9219 data_time: 0.0097 memory: 9091 grad_norm: 0.8305 loss: 1.1234 loss_heatmap: 0.5143 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5281 matched_ious: 0.6045 2023/03/23 11:53:12 - mmengine - INFO - Epoch(train) [17][3100/3862] lr: 1.6521e-04 eta: 3:11:53 time: 0.9315 data_time: 0.0096 memory: 9318 grad_norm: 0.7927 loss: 1.1599 loss_heatmap: 0.5307 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5440 matched_ious: 0.6106 2023/03/23 11:53:59 - mmengine - INFO - Epoch(train) [17][3150/3862] lr: 1.6395e-04 eta: 3:11:06 time: 0.9291 data_time: 0.0095 memory: 9103 grad_norm: 0.8396 loss: 1.0679 loss_heatmap: 0.4844 layer_-1_loss_cls: 0.0786 layer_-1_loss_bbox: 0.5049 matched_ious: 0.5698 2023/03/23 11:54:45 - mmengine - INFO - Epoch(train) [17][3200/3862] lr: 1.6270e-04 eta: 3:10:19 time: 0.9299 data_time: 0.0094 memory: 8829 grad_norm: 0.7904 loss: 1.1349 loss_heatmap: 0.5166 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5383 matched_ious: 0.5601 2023/03/23 11:54:52 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 11:55:31 - mmengine - INFO - Epoch(train) [17][3250/3862] lr: 1.6145e-04 eta: 3:09:32 time: 0.9256 data_time: 0.0092 memory: 9202 grad_norm: 0.8394 loss: 1.1175 loss_heatmap: 0.5174 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.5167 matched_ious: 0.5583 2023/03/23 11:56:17 - mmengine - INFO - Epoch(train) [17][3300/3862] lr: 1.6020e-04 eta: 3:08:45 time: 0.9239 data_time: 0.0094 memory: 9123 grad_norm: 0.8610 loss: 1.1785 loss_heatmap: 0.5301 layer_-1_loss_cls: 0.0831 layer_-1_loss_bbox: 0.5653 matched_ious: 0.5969 2023/03/23 11:57:04 - mmengine - INFO - Epoch(train) [17][3350/3862] lr: 1.5896e-04 eta: 3:07:58 time: 0.9336 data_time: 0.0092 memory: 9076 grad_norm: 1.1743 loss: 1.1625 loss_heatmap: 0.5315 layer_-1_loss_cls: 0.0844 layer_-1_loss_bbox: 0.5466 matched_ious: 0.5768 2023/03/23 11:57:51 - mmengine - INFO - Epoch(train) [17][3400/3862] lr: 1.5772e-04 eta: 3:07:11 time: 0.9265 data_time: 0.0091 memory: 8984 grad_norm: 0.9722 loss: 1.1050 loss_heatmap: 0.5044 layer_-1_loss_cls: 0.0812 layer_-1_loss_bbox: 0.5195 matched_ious: 0.5797 2023/03/23 11:58:37 - mmengine - INFO - Epoch(train) [17][3450/3862] lr: 1.5649e-04 eta: 3:06:25 time: 0.9342 data_time: 0.0094 memory: 8989 grad_norm: 0.8329 loss: 1.1425 loss_heatmap: 0.5188 layer_-1_loss_cls: 0.0849 layer_-1_loss_bbox: 0.5388 matched_ious: 0.5826 2023/03/23 11:59:24 - mmengine - INFO - Epoch(train) [17][3500/3862] lr: 1.5526e-04 eta: 3:05:38 time: 0.9321 data_time: 0.0095 memory: 9035 grad_norm: 0.8854 loss: 1.2057 loss_heatmap: 0.5374 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5863 matched_ious: 0.5300 2023/03/23 12:00:10 - mmengine - INFO - Epoch(train) [17][3550/3862] lr: 1.5404e-04 eta: 3:04:51 time: 0.9302 data_time: 0.0092 memory: 9017 grad_norm: 0.9111 loss: 1.1535 loss_heatmap: 0.5209 layer_-1_loss_cls: 0.0842 layer_-1_loss_bbox: 0.5484 matched_ious: 0.5830 2023/03/23 12:00:57 - mmengine - INFO - Epoch(train) [17][3600/3862] lr: 1.5281e-04 eta: 3:04:04 time: 0.9289 data_time: 0.0093 memory: 9062 grad_norm: 0.8307 loss: 1.1415 loss_heatmap: 0.5193 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5402 matched_ious: 0.5638 2023/03/23 12:01:43 - mmengine - INFO - Epoch(train) [17][3650/3862] lr: 1.5160e-04 eta: 3:03:17 time: 0.9248 data_time: 0.0093 memory: 8905 grad_norm: 0.9260 loss: 1.1695 loss_heatmap: 0.5334 layer_-1_loss_cls: 0.0850 layer_-1_loss_bbox: 0.5511 matched_ious: 0.6422 2023/03/23 12:02:30 - mmengine - INFO - Epoch(train) [17][3700/3862] lr: 1.5038e-04 eta: 3:02:31 time: 0.9342 data_time: 0.0091 memory: 8878 grad_norm: 0.8767 loss: 1.2006 loss_heatmap: 0.5286 layer_-1_loss_cls: 0.0827 layer_-1_loss_bbox: 0.5894 matched_ious: 0.5560 2023/03/23 12:03:16 - mmengine - INFO - Epoch(train) [17][3750/3862] lr: 1.4917e-04 eta: 3:01:44 time: 0.9308 data_time: 0.0093 memory: 9370 grad_norm: 0.8660 loss: 1.1468 loss_heatmap: 0.5371 layer_-1_loss_cls: 0.0861 layer_-1_loss_bbox: 0.5236 matched_ious: 0.6441 2023/03/23 12:04:03 - mmengine - INFO - Epoch(train) [17][3800/3862] lr: 1.4797e-04 eta: 3:00:58 time: 0.9420 data_time: 0.0092 memory: 9455 grad_norm: 0.9064 loss: 1.1229 loss_heatmap: 0.5103 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5323 matched_ious: 0.6226 2023/03/23 12:04:50 - mmengine - INFO - Epoch(train) [17][3850/3862] lr: 1.4677e-04 eta: 3:00:12 time: 0.9321 data_time: 0.0097 memory: 9043 grad_norm: 0.8402 loss: 1.1640 loss_heatmap: 0.5357 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.5448 matched_ious: 0.5796 2023/03/23 12:05:01 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 12:05:48 - mmengine - INFO - Epoch(train) [18][ 50/3862] lr: 1.4528e-04 eta: 2:59:15 time: 0.9457 data_time: 0.0252 memory: 9054 grad_norm: 0.8593 loss: 1.1600 loss_heatmap: 0.5363 layer_-1_loss_cls: 0.0833 layer_-1_loss_bbox: 0.5403 matched_ious: 0.6029 2023/03/23 12:06:35 - mmengine - INFO - Epoch(train) [18][ 100/3862] lr: 1.4409e-04 eta: 2:58:28 time: 0.9370 data_time: 0.0091 memory: 8950 grad_norm: 0.8352 loss: 1.0525 loss_heatmap: 0.4847 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.4872 matched_ious: 0.5553 2023/03/23 12:07:22 - mmengine - INFO - Epoch(train) [18][ 150/3862] lr: 1.4290e-04 eta: 2:57:42 time: 0.9302 data_time: 0.0091 memory: 9366 grad_norm: 0.8116 loss: 1.1530 loss_heatmap: 0.5164 layer_-1_loss_cls: 0.0820 layer_-1_loss_bbox: 0.5545 matched_ious: 0.6150 2023/03/23 12:08:09 - mmengine - INFO - Epoch(train) [18][ 200/3862] lr: 1.4172e-04 eta: 2:56:55 time: 0.9351 data_time: 0.0094 memory: 9141 grad_norm: 0.8934 loss: 1.1794 loss_heatmap: 0.5362 layer_-1_loss_cls: 0.0884 layer_-1_loss_bbox: 0.5549 matched_ious: 0.6147 2023/03/23 12:08:55 - mmengine - INFO - Epoch(train) [18][ 250/3862] lr: 1.4054e-04 eta: 2:56:09 time: 0.9320 data_time: 0.0096 memory: 9030 grad_norm: 0.8238 loss: 1.0970 loss_heatmap: 0.5166 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.4969 matched_ious: 0.6472 2023/03/23 12:09:41 - mmengine - INFO - Epoch(train) [18][ 300/3862] lr: 1.3936e-04 eta: 2:55:21 time: 0.9231 data_time: 0.0095 memory: 9300 grad_norm: 0.8686 loss: 1.1111 loss_heatmap: 0.4985 layer_-1_loss_cls: 0.0796 layer_-1_loss_bbox: 0.5330 matched_ious: 0.5455 2023/03/23 12:10:24 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 12:10:28 - mmengine - INFO - Epoch(train) [18][ 350/3862] lr: 1.3819e-04 eta: 2:54:35 time: 0.9337 data_time: 0.0094 memory: 9058 grad_norm: 0.8045 loss: 1.1042 loss_heatmap: 0.5025 layer_-1_loss_cls: 0.0773 layer_-1_loss_bbox: 0.5244 matched_ious: 0.6156 2023/03/23 12:11:14 - mmengine - INFO - Epoch(train) [18][ 400/3862] lr: 1.3702e-04 eta: 2:53:48 time: 0.9261 data_time: 0.0095 memory: 9326 grad_norm: 0.8143 loss: 1.1101 loss_heatmap: 0.5172 layer_-1_loss_cls: 0.0833 layer_-1_loss_bbox: 0.5096 matched_ious: 0.5415 2023/03/23 12:12:01 - mmengine - INFO - Epoch(train) [18][ 450/3862] lr: 1.3586e-04 eta: 2:53:01 time: 0.9335 data_time: 0.0092 memory: 9262 grad_norm: 0.8432 loss: 1.1565 loss_heatmap: 0.5172 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5585 matched_ious: 0.6606 2023/03/23 12:12:48 - mmengine - INFO - Epoch(train) [18][ 500/3862] lr: 1.3470e-04 eta: 2:52:15 time: 0.9398 data_time: 0.0092 memory: 9108 grad_norm: 0.8406 loss: 1.1762 loss_heatmap: 0.5289 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5652 matched_ious: 0.5520 2023/03/23 12:13:35 - mmengine - INFO - Epoch(train) [18][ 550/3862] lr: 1.3355e-04 eta: 2:51:28 time: 0.9308 data_time: 0.0092 memory: 8996 grad_norm: 0.8307 loss: 1.1554 loss_heatmap: 0.5217 layer_-1_loss_cls: 0.0875 layer_-1_loss_bbox: 0.5461 matched_ious: 0.5500 2023/03/23 12:14:21 - mmengine - INFO - Epoch(train) [18][ 600/3862] lr: 1.3239e-04 eta: 2:50:42 time: 0.9335 data_time: 0.0092 memory: 9162 grad_norm: 0.8628 loss: 1.1634 loss_heatmap: 0.5287 layer_-1_loss_cls: 0.0843 layer_-1_loss_bbox: 0.5504 matched_ious: 0.5793 2023/03/23 12:15:08 - mmengine - INFO - Epoch(train) [18][ 650/3862] lr: 1.3125e-04 eta: 2:49:55 time: 0.9324 data_time: 0.0090 memory: 9118 grad_norm: 0.7670 loss: 1.1825 loss_heatmap: 0.5437 layer_-1_loss_cls: 0.0819 layer_-1_loss_bbox: 0.5569 matched_ious: 0.5144 2023/03/23 12:15:54 - mmengine - INFO - Epoch(train) [18][ 700/3862] lr: 1.3011e-04 eta: 2:49:08 time: 0.9247 data_time: 0.0090 memory: 9031 grad_norm: 0.8594 loss: 1.1500 loss_heatmap: 0.5138 layer_-1_loss_cls: 0.0798 layer_-1_loss_bbox: 0.5564 matched_ious: 0.5193 2023/03/23 12:16:41 - mmengine - INFO - Epoch(train) [18][ 750/3862] lr: 1.2897e-04 eta: 2:48:22 time: 0.9339 data_time: 0.0091 memory: 9111 grad_norm: 0.8034 loss: 1.1776 loss_heatmap: 0.5109 layer_-1_loss_cls: 0.0796 layer_-1_loss_bbox: 0.5870 matched_ious: 0.5277 2023/03/23 12:17:27 - mmengine - INFO - Epoch(train) [18][ 800/3862] lr: 1.2783e-04 eta: 2:47:35 time: 0.9297 data_time: 0.0090 memory: 9042 grad_norm: 0.8142 loss: 1.0941 loss_heatmap: 0.5109 layer_-1_loss_cls: 0.0802 layer_-1_loss_bbox: 0.5030 matched_ious: 0.5404 2023/03/23 12:18:14 - mmengine - INFO - Epoch(train) [18][ 850/3862] lr: 1.2670e-04 eta: 2:46:48 time: 0.9279 data_time: 0.0091 memory: 9170 grad_norm: 0.8232 loss: 1.1727 loss_heatmap: 0.5350 layer_-1_loss_cls: 0.0858 layer_-1_loss_bbox: 0.5519 matched_ious: 0.5968 2023/03/23 12:19:00 - mmengine - INFO - Epoch(train) [18][ 900/3862] lr: 1.2558e-04 eta: 2:46:01 time: 0.9317 data_time: 0.0091 memory: 9228 grad_norm: 0.7938 loss: 1.1020 loss_heatmap: 0.5084 layer_-1_loss_cls: 0.0816 layer_-1_loss_bbox: 0.5120 matched_ious: 0.5431 2023/03/23 12:19:47 - mmengine - INFO - Epoch(train) [18][ 950/3862] lr: 1.2446e-04 eta: 2:45:15 time: 0.9301 data_time: 0.0091 memory: 8796 grad_norm: 0.8501 loss: 1.1721 loss_heatmap: 0.5316 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5579 matched_ious: 0.5357 2023/03/23 12:20:33 - mmengine - INFO - Epoch(train) [18][1000/3862] lr: 1.2334e-04 eta: 2:44:28 time: 0.9268 data_time: 0.0091 memory: 9369 grad_norm: 0.8835 loss: 1.1399 loss_heatmap: 0.5030 layer_-1_loss_cls: 0.0793 layer_-1_loss_bbox: 0.5577 matched_ious: 0.6473 2023/03/23 12:21:19 - mmengine - INFO - Epoch(train) [18][1050/3862] lr: 1.2223e-04 eta: 2:43:41 time: 0.9254 data_time: 0.0091 memory: 9190 grad_norm: 0.7603 loss: 1.1122 loss_heatmap: 0.5111 layer_-1_loss_cls: 0.0823 layer_-1_loss_bbox: 0.5188 matched_ious: 0.5997 2023/03/23 12:22:06 - mmengine - INFO - Epoch(train) [18][1100/3862] lr: 1.2112e-04 eta: 2:42:54 time: 0.9372 data_time: 0.0091 memory: 9292 grad_norm: 0.8461 loss: 1.1403 loss_heatmap: 0.5141 layer_-1_loss_cls: 0.0833 layer_-1_loss_bbox: 0.5428 matched_ious: 0.5827 2023/03/23 12:22:53 - mmengine - INFO - Epoch(train) [18][1150/3862] lr: 1.2002e-04 eta: 2:42:08 time: 0.9303 data_time: 0.0092 memory: 9021 grad_norm: 0.8588 loss: 1.1310 loss_heatmap: 0.5246 layer_-1_loss_cls: 0.0820 layer_-1_loss_bbox: 0.5245 matched_ious: 0.6199 2023/03/23 12:23:39 - mmengine - INFO - Epoch(train) [18][1200/3862] lr: 1.1892e-04 eta: 2:41:21 time: 0.9318 data_time: 0.0092 memory: 8938 grad_norm: 0.8603 loss: 1.1453 loss_heatmap: 0.5090 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.5559 matched_ious: 0.5929 2023/03/23 12:24:26 - mmengine - INFO - Epoch(train) [18][1250/3862] lr: 1.1782e-04 eta: 2:40:35 time: 0.9361 data_time: 0.0091 memory: 9117 grad_norm: 0.8932 loss: 1.1601 loss_heatmap: 0.5322 layer_-1_loss_cls: 0.0869 layer_-1_loss_bbox: 0.5410 matched_ious: 0.5133 2023/03/23 12:25:13 - mmengine - INFO - Epoch(train) [18][1300/3862] lr: 1.1673e-04 eta: 2:39:48 time: 0.9338 data_time: 0.0092 memory: 9413 grad_norm: 0.9895 loss: 1.1300 loss_heatmap: 0.5075 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5404 matched_ious: 0.5948 2023/03/23 12:25:56 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 12:26:00 - mmengine - INFO - Epoch(train) [18][1350/3862] lr: 1.1565e-04 eta: 2:39:02 time: 0.9332 data_time: 0.0097 memory: 9284 grad_norm: 0.8534 loss: 1.0784 loss_heatmap: 0.4947 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5026 matched_ious: 0.5597 2023/03/23 12:26:46 - mmengine - INFO - Epoch(train) [18][1400/3862] lr: 1.1456e-04 eta: 2:38:15 time: 0.9305 data_time: 0.0092 memory: 9026 grad_norm: 0.8589 loss: 1.1126 loss_heatmap: 0.5091 layer_-1_loss_cls: 0.0789 layer_-1_loss_bbox: 0.5246 matched_ious: 0.5550 2023/03/23 12:27:32 - mmengine - INFO - Epoch(train) [18][1450/3862] lr: 1.1349e-04 eta: 2:37:28 time: 0.9263 data_time: 0.0093 memory: 9021 grad_norm: 0.8960 loss: 1.1240 loss_heatmap: 0.5206 layer_-1_loss_cls: 0.0833 layer_-1_loss_bbox: 0.5201 matched_ious: 0.5433 2023/03/23 12:28:19 - mmengine - INFO - Epoch(train) [18][1500/3862] lr: 1.1241e-04 eta: 2:36:41 time: 0.9290 data_time: 0.0093 memory: 9026 grad_norm: 0.8503 loss: 1.0906 loss_heatmap: 0.5072 layer_-1_loss_cls: 0.0781 layer_-1_loss_bbox: 0.5053 matched_ious: 0.5627 2023/03/23 12:29:05 - mmengine - INFO - Epoch(train) [18][1550/3862] lr: 1.1135e-04 eta: 2:35:54 time: 0.9219 data_time: 0.0093 memory: 9300 grad_norm: 0.7910 loss: 1.1466 loss_heatmap: 0.5179 layer_-1_loss_cls: 0.0846 layer_-1_loss_bbox: 0.5441 matched_ious: 0.5476 2023/03/23 12:29:51 - mmengine - INFO - Epoch(train) [18][1600/3862] lr: 1.1028e-04 eta: 2:35:07 time: 0.9217 data_time: 0.0093 memory: 8919 grad_norm: 0.7768 loss: 1.1526 loss_heatmap: 0.5318 layer_-1_loss_cls: 0.0852 layer_-1_loss_bbox: 0.5356 matched_ious: 0.5874 2023/03/23 12:30:38 - mmengine - INFO - Epoch(train) [18][1650/3862] lr: 1.0922e-04 eta: 2:34:20 time: 0.9316 data_time: 0.0092 memory: 9130 grad_norm: 0.8369 loss: 1.1317 loss_heatmap: 0.5032 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5474 matched_ious: 0.5859 2023/03/23 12:31:24 - mmengine - INFO - Epoch(train) [18][1700/3862] lr: 1.0817e-04 eta: 2:33:33 time: 0.9296 data_time: 0.0091 memory: 9251 grad_norm: 0.8141 loss: 1.1603 loss_heatmap: 0.5361 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5432 matched_ious: 0.5077 2023/03/23 12:32:10 - mmengine - INFO - Epoch(train) [18][1750/3862] lr: 1.0712e-04 eta: 2:32:46 time: 0.9252 data_time: 0.0092 memory: 8967 grad_norm: 0.8504 loss: 1.1213 loss_heatmap: 0.4920 layer_-1_loss_cls: 0.0775 layer_-1_loss_bbox: 0.5518 matched_ious: 0.5537 2023/03/23 12:32:57 - mmengine - INFO - Epoch(train) [18][1800/3862] lr: 1.0607e-04 eta: 2:32:00 time: 0.9339 data_time: 0.0092 memory: 9034 grad_norm: 0.8641 loss: 1.0631 loss_heatmap: 0.5026 layer_-1_loss_cls: 0.0779 layer_-1_loss_bbox: 0.4826 matched_ious: 0.5772 2023/03/23 12:33:43 - mmengine - INFO - Epoch(train) [18][1850/3862] lr: 1.0503e-04 eta: 2:31:13 time: 0.9213 data_time: 0.0093 memory: 9333 grad_norm: 0.8483 loss: 1.1721 loss_heatmap: 0.5112 layer_-1_loss_cls: 0.0797 layer_-1_loss_bbox: 0.5812 matched_ious: 0.5462 2023/03/23 12:34:29 - mmengine - INFO - Epoch(train) [18][1900/3862] lr: 1.0399e-04 eta: 2:30:26 time: 0.9237 data_time: 0.0090 memory: 9527 grad_norm: 0.9336 loss: 1.0840 loss_heatmap: 0.4973 layer_-1_loss_cls: 0.0784 layer_-1_loss_bbox: 0.5082 matched_ious: 0.6372 2023/03/23 12:35:16 - mmengine - INFO - Epoch(train) [18][1950/3862] lr: 1.0296e-04 eta: 2:29:39 time: 0.9270 data_time: 0.0092 memory: 8818 grad_norm: 0.8467 loss: 1.1293 loss_heatmap: 0.5049 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5439 matched_ious: 0.5935 2023/03/23 12:36:02 - mmengine - INFO - Epoch(train) [18][2000/3862] lr: 1.0193e-04 eta: 2:28:52 time: 0.9226 data_time: 0.0091 memory: 9091 grad_norm: 0.8466 loss: 1.0958 loss_heatmap: 0.5047 layer_-1_loss_cls: 0.0833 layer_-1_loss_bbox: 0.5078 matched_ious: 0.5817 2023/03/23 12:36:48 - mmengine - INFO - Epoch(train) [18][2050/3862] lr: 1.0091e-04 eta: 2:28:05 time: 0.9265 data_time: 0.0095 memory: 9030 grad_norm: 0.8524 loss: 1.2006 loss_heatmap: 0.5278 layer_-1_loss_cls: 0.0814 layer_-1_loss_bbox: 0.5914 matched_ious: 0.5988 2023/03/23 12:37:35 - mmengine - INFO - Epoch(train) [18][2100/3862] lr: 9.9892e-05 eta: 2:27:18 time: 0.9311 data_time: 0.0092 memory: 9269 grad_norm: 0.8139 loss: 1.1145 loss_heatmap: 0.5071 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5256 matched_ious: 0.5977 2023/03/23 12:38:21 - mmengine - INFO - Epoch(train) [18][2150/3862] lr: 9.8878e-05 eta: 2:26:32 time: 0.9324 data_time: 0.0092 memory: 9056 grad_norm: 0.8447 loss: 1.1196 loss_heatmap: 0.5207 layer_-1_loss_cls: 0.0837 layer_-1_loss_bbox: 0.5152 matched_ious: 0.6474 2023/03/23 12:39:07 - mmengine - INFO - Epoch(train) [18][2200/3862] lr: 9.7868e-05 eta: 2:25:45 time: 0.9202 data_time: 0.0092 memory: 8938 grad_norm: 0.8006 loss: 1.0522 loss_heatmap: 0.4833 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.4899 matched_ious: 0.6482 2023/03/23 12:39:55 - mmengine - INFO - Epoch(train) [18][2250/3862] lr: 9.6864e-05 eta: 2:24:59 time: 0.9444 data_time: 0.0093 memory: 8904 grad_norm: 0.8984 loss: 1.0990 loss_heatmap: 0.4987 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.5226 matched_ious: 0.6261 2023/03/23 12:40:40 - mmengine - INFO - Epoch(train) [18][2300/3862] lr: 9.5863e-05 eta: 2:24:12 time: 0.9178 data_time: 0.0091 memory: 8971 grad_norm: 0.8092 loss: 1.1324 loss_heatmap: 0.5214 layer_-1_loss_cls: 0.0809 layer_-1_loss_bbox: 0.5301 matched_ious: 0.4971 2023/03/23 12:41:23 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 12:41:27 - mmengine - INFO - Epoch(train) [18][2350/3862] lr: 9.4868e-05 eta: 2:23:25 time: 0.9275 data_time: 0.0097 memory: 8779 grad_norm: 0.7908 loss: 1.1518 loss_heatmap: 0.5292 layer_-1_loss_cls: 0.0831 layer_-1_loss_bbox: 0.5395 matched_ious: 0.5356 2023/03/23 12:42:13 - mmengine - INFO - Epoch(train) [18][2400/3862] lr: 9.3877e-05 eta: 2:22:38 time: 0.9243 data_time: 0.0092 memory: 9115 grad_norm: 0.8033 loss: 1.1466 loss_heatmap: 0.5170 layer_-1_loss_cls: 0.0819 layer_-1_loss_bbox: 0.5478 matched_ious: 0.6404 2023/03/23 12:43:00 - mmengine - INFO - Epoch(train) [18][2450/3862] lr: 9.2891e-05 eta: 2:21:51 time: 0.9292 data_time: 0.0091 memory: 8981 grad_norm: 0.8666 loss: 1.1662 loss_heatmap: 0.5338 layer_-1_loss_cls: 0.0847 layer_-1_loss_bbox: 0.5477 matched_ious: 0.5879 2023/03/23 12:43:46 - mmengine - INFO - Epoch(train) [18][2500/3862] lr: 9.1909e-05 eta: 2:21:05 time: 0.9342 data_time: 0.0089 memory: 9053 grad_norm: 0.8212 loss: 1.2045 loss_heatmap: 0.5536 layer_-1_loss_cls: 0.0847 layer_-1_loss_bbox: 0.5663 matched_ious: 0.6289 2023/03/23 12:44:33 - mmengine - INFO - Epoch(train) [18][2550/3862] lr: 9.0933e-05 eta: 2:20:18 time: 0.9258 data_time: 0.0091 memory: 9027 grad_norm: 0.9229 loss: 1.1338 loss_heatmap: 0.5006 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.5553 matched_ious: 0.5680 2023/03/23 12:45:19 - mmengine - INFO - Epoch(train) [18][2600/3862] lr: 8.9961e-05 eta: 2:19:31 time: 0.9213 data_time: 0.0089 memory: 8978 grad_norm: 0.8095 loss: 1.1255 loss_heatmap: 0.5083 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5351 matched_ious: 0.6375 2023/03/23 12:46:05 - mmengine - INFO - Epoch(train) [18][2650/3862] lr: 8.8993e-05 eta: 2:18:44 time: 0.9345 data_time: 0.0091 memory: 9445 grad_norm: 0.8688 loss: 1.1092 loss_heatmap: 0.4906 layer_-1_loss_cls: 0.0782 layer_-1_loss_bbox: 0.5404 matched_ious: 0.5758 2023/03/23 12:46:52 - mmengine - INFO - Epoch(train) [18][2700/3862] lr: 8.8031e-05 eta: 2:17:57 time: 0.9246 data_time: 0.0093 memory: 9030 grad_norm: 0.8093 loss: 1.0794 loss_heatmap: 0.4878 layer_-1_loss_cls: 0.0770 layer_-1_loss_bbox: 0.5147 matched_ious: 0.5712 2023/03/23 12:47:38 - mmengine - INFO - Epoch(train) [18][2750/3862] lr: 8.7073e-05 eta: 2:17:10 time: 0.9208 data_time: 0.0091 memory: 9138 grad_norm: 0.7999 loss: 1.1865 loss_heatmap: 0.5437 layer_-1_loss_cls: 0.0837 layer_-1_loss_bbox: 0.5591 matched_ious: 0.5622 2023/03/23 12:48:24 - mmengine - INFO - Epoch(train) [18][2800/3862] lr: 8.6119e-05 eta: 2:16:24 time: 0.9252 data_time: 0.0090 memory: 9128 grad_norm: 0.8582 loss: 1.1586 loss_heatmap: 0.5288 layer_-1_loss_cls: 0.0827 layer_-1_loss_bbox: 0.5471 matched_ious: 0.5623 2023/03/23 12:49:10 - mmengine - INFO - Epoch(train) [18][2850/3862] lr: 8.5171e-05 eta: 2:15:37 time: 0.9287 data_time: 0.0090 memory: 8836 grad_norm: 0.8543 loss: 1.1193 loss_heatmap: 0.4930 layer_-1_loss_cls: 0.0781 layer_-1_loss_bbox: 0.5483 matched_ious: 0.6231 2023/03/23 12:49:57 - mmengine - INFO - Epoch(train) [18][2900/3862] lr: 8.4227e-05 eta: 2:14:50 time: 0.9252 data_time: 0.0093 memory: 8863 grad_norm: 0.8248 loss: 1.1286 loss_heatmap: 0.5268 layer_-1_loss_cls: 0.0814 layer_-1_loss_bbox: 0.5204 matched_ious: 0.5885 2023/03/23 12:50:43 - mmengine - INFO - Epoch(train) [18][2950/3862] lr: 8.3288e-05 eta: 2:14:03 time: 0.9306 data_time: 0.0092 memory: 9280 grad_norm: 0.7827 loss: 1.1250 loss_heatmap: 0.5264 layer_-1_loss_cls: 0.0844 layer_-1_loss_bbox: 0.5142 matched_ious: 0.5780 2023/03/23 12:51:30 - mmengine - INFO - Epoch(train) [18][3000/3862] lr: 8.2354e-05 eta: 2:13:17 time: 0.9290 data_time: 0.0091 memory: 8993 grad_norm: 0.9572 loss: 1.1368 loss_heatmap: 0.5076 layer_-1_loss_cls: 0.0815 layer_-1_loss_bbox: 0.5477 matched_ious: 0.5324 2023/03/23 12:52:16 - mmengine - INFO - Epoch(train) [18][3050/3862] lr: 8.1425e-05 eta: 2:12:30 time: 0.9296 data_time: 0.0090 memory: 8945 grad_norm: 0.8210 loss: 1.1062 loss_heatmap: 0.5065 layer_-1_loss_cls: 0.0816 layer_-1_loss_bbox: 0.5181 matched_ious: 0.6066 2023/03/23 12:53:03 - mmengine - INFO - Epoch(train) [18][3100/3862] lr: 8.0500e-05 eta: 2:11:44 time: 0.9314 data_time: 0.0095 memory: 8900 grad_norm: 0.8354 loss: 1.0885 loss_heatmap: 0.4783 layer_-1_loss_cls: 0.0745 layer_-1_loss_bbox: 0.5357 matched_ious: 0.5667 2023/03/23 12:53:49 - mmengine - INFO - Epoch(train) [18][3150/3862] lr: 7.9581e-05 eta: 2:10:57 time: 0.9321 data_time: 0.0094 memory: 8862 grad_norm: 0.9483 loss: 1.1673 loss_heatmap: 0.5338 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.5470 matched_ious: 0.4916 2023/03/23 12:54:36 - mmengine - INFO - Epoch(train) [18][3200/3862] lr: 7.8666e-05 eta: 2:10:10 time: 0.9307 data_time: 0.0090 memory: 9167 grad_norm: 0.9160 loss: 1.1072 loss_heatmap: 0.5039 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5216 matched_ious: 0.5727 2023/03/23 12:55:23 - mmengine - INFO - Epoch(train) [18][3250/3862] lr: 7.7756e-05 eta: 2:09:24 time: 0.9343 data_time: 0.0093 memory: 9047 grad_norm: 0.8960 loss: 1.1290 loss_heatmap: 0.5167 layer_-1_loss_cls: 0.0809 layer_-1_loss_bbox: 0.5314 matched_ious: 0.5542 2023/03/23 12:56:09 - mmengine - INFO - Epoch(train) [18][3300/3862] lr: 7.6851e-05 eta: 2:08:37 time: 0.9309 data_time: 0.0093 memory: 9323 grad_norm: 0.8279 loss: 1.1402 loss_heatmap: 0.5179 layer_-1_loss_cls: 0.0824 layer_-1_loss_bbox: 0.5400 matched_ious: 0.5476 2023/03/23 12:56:52 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 12:56:55 - mmengine - INFO - Epoch(train) [18][3350/3862] lr: 7.5950e-05 eta: 2:07:51 time: 0.9279 data_time: 0.0094 memory: 9290 grad_norm: 0.8212 loss: 1.1255 loss_heatmap: 0.5156 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5289 matched_ious: 0.5964 2023/03/23 12:57:43 - mmengine - INFO - Epoch(train) [18][3400/3862] lr: 7.5055e-05 eta: 2:07:05 time: 0.9441 data_time: 0.0093 memory: 9278 grad_norm: 0.8423 loss: 1.1625 loss_heatmap: 0.5214 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.5574 matched_ious: 0.5185 2023/03/23 12:58:29 - mmengine - INFO - Epoch(train) [18][3450/3862] lr: 7.4164e-05 eta: 2:06:18 time: 0.9312 data_time: 0.0097 memory: 9050 grad_norm: 0.9529 loss: 1.0884 loss_heatmap: 0.4959 layer_-1_loss_cls: 0.0768 layer_-1_loss_bbox: 0.5156 matched_ious: 0.5488 2023/03/23 12:59:16 - mmengine - INFO - Epoch(train) [18][3500/3862] lr: 7.3279e-05 eta: 2:05:31 time: 0.9264 data_time: 0.0093 memory: 9180 grad_norm: 0.8407 loss: 1.1133 loss_heatmap: 0.5188 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5127 matched_ious: 0.5687 2023/03/23 13:00:02 - mmengine - INFO - Epoch(train) [18][3550/3862] lr: 7.2398e-05 eta: 2:04:44 time: 0.9242 data_time: 0.0099 memory: 8982 grad_norm: 0.8768 loss: 1.1278 loss_heatmap: 0.5086 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.5405 matched_ious: 0.5978 2023/03/23 13:00:48 - mmengine - INFO - Epoch(train) [18][3600/3862] lr: 7.1522e-05 eta: 2:03:58 time: 0.9257 data_time: 0.0098 memory: 9200 grad_norm: 0.9009 loss: 1.0980 loss_heatmap: 0.4974 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5194 matched_ious: 0.5915 2023/03/23 13:01:34 - mmengine - INFO - Epoch(train) [18][3650/3862] lr: 7.0651e-05 eta: 2:03:11 time: 0.9246 data_time: 0.0101 memory: 9031 grad_norm: 0.7854 loss: 1.1375 loss_heatmap: 0.5171 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.5424 matched_ious: 0.5947 2023/03/23 13:02:21 - mmengine - INFO - Epoch(train) [18][3700/3862] lr: 6.9785e-05 eta: 2:02:24 time: 0.9311 data_time: 0.0094 memory: 9025 grad_norm: 0.8792 loss: 1.1064 loss_heatmap: 0.5050 layer_-1_loss_cls: 0.0796 layer_-1_loss_bbox: 0.5217 matched_ious: 0.5775 2023/03/23 13:03:08 - mmengine - INFO - Epoch(train) [18][3750/3862] lr: 6.8924e-05 eta: 2:01:38 time: 0.9329 data_time: 0.0097 memory: 9043 grad_norm: 0.8294 loss: 1.1774 loss_heatmap: 0.5270 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5693 matched_ious: 0.6182 2023/03/23 13:03:54 - mmengine - INFO - Epoch(train) [18][3800/3862] lr: 6.8068e-05 eta: 2:00:51 time: 0.9312 data_time: 0.0099 memory: 9213 grad_norm: 0.8195 loss: 1.1291 loss_heatmap: 0.5026 layer_-1_loss_cls: 0.0808 layer_-1_loss_bbox: 0.5456 matched_ious: 0.5429 2023/03/23 13:04:41 - mmengine - INFO - Epoch(train) [18][3850/3862] lr: 6.7217e-05 eta: 2:00:05 time: 0.9296 data_time: 0.0097 memory: 8910 grad_norm: 0.7967 loss: 1.0907 loss_heatmap: 0.5083 layer_-1_loss_cls: 0.0801 layer_-1_loss_bbox: 0.5023 matched_ious: 0.5932 2023/03/23 13:04:52 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 13:05:39 - mmengine - INFO - Epoch(train) [19][ 50/3862] lr: 6.6169e-05 eta: 1:59:07 time: 0.9496 data_time: 0.0260 memory: 8936 grad_norm: 0.7667 loss: 1.1455 loss_heatmap: 0.5271 layer_-1_loss_cls: 0.0803 layer_-1_loss_bbox: 0.5381 matched_ious: 0.5631 2023/03/23 13:06:26 - mmengine - INFO - Epoch(train) [19][ 100/3862] lr: 6.5329e-05 eta: 1:58:21 time: 0.9330 data_time: 0.0095 memory: 8978 grad_norm: 0.8637 loss: 1.1013 loss_heatmap: 0.5212 layer_-1_loss_cls: 0.0813 layer_-1_loss_bbox: 0.4987 matched_ious: 0.6162 2023/03/23 13:07:12 - mmengine - INFO - Epoch(train) [19][ 150/3862] lr: 6.4494e-05 eta: 1:57:34 time: 0.9289 data_time: 0.0093 memory: 9089 grad_norm: 0.8006 loss: 1.1392 loss_heatmap: 0.5266 layer_-1_loss_cls: 0.0832 layer_-1_loss_bbox: 0.5293 matched_ious: 0.5550 2023/03/23 13:07:59 - mmengine - INFO - Epoch(train) [19][ 200/3862] lr: 6.3664e-05 eta: 1:56:48 time: 0.9327 data_time: 0.0093 memory: 9256 grad_norm: 0.9424 loss: 1.1597 loss_heatmap: 0.5173 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5614 matched_ious: 0.5629 2023/03/23 13:08:45 - mmengine - INFO - Epoch(train) [19][ 250/3862] lr: 6.2839e-05 eta: 1:56:01 time: 0.9265 data_time: 0.0091 memory: 9105 grad_norm: 0.8934 loss: 1.0941 loss_heatmap: 0.5113 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5028 matched_ious: 0.6142 2023/03/23 13:09:32 - mmengine - INFO - Epoch(train) [19][ 300/3862] lr: 6.2019e-05 eta: 1:55:14 time: 0.9294 data_time: 0.0097 memory: 8888 grad_norm: 0.8874 loss: 1.0639 loss_heatmap: 0.4960 layer_-1_loss_cls: 0.0801 layer_-1_loss_bbox: 0.4878 matched_ious: 0.5722 2023/03/23 13:10:18 - mmengine - INFO - Epoch(train) [19][ 350/3862] lr: 6.1204e-05 eta: 1:54:27 time: 0.9206 data_time: 0.0093 memory: 8998 grad_norm: 0.8221 loss: 1.1349 loss_heatmap: 0.4934 layer_-1_loss_cls: 0.0765 layer_-1_loss_bbox: 0.5651 matched_ious: 0.5664 2023/03/23 13:11:04 - mmengine - INFO - Epoch(train) [19][ 400/3862] lr: 6.0394e-05 eta: 1:53:41 time: 0.9282 data_time: 0.0092 memory: 9305 grad_norm: 0.7786 loss: 1.0918 loss_heatmap: 0.5255 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.4798 matched_ious: 0.6633 2023/03/23 13:11:51 - mmengine - INFO - Epoch(train) [19][ 450/3862] lr: 5.9589e-05 eta: 1:52:54 time: 0.9260 data_time: 0.0092 memory: 8965 grad_norm: 0.8064 loss: 1.1215 loss_heatmap: 0.5276 layer_-1_loss_cls: 0.0843 layer_-1_loss_bbox: 0.5096 matched_ious: 0.5841 2023/03/23 13:12:22 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 13:12:37 - mmengine - INFO - Epoch(train) [19][ 500/3862] lr: 5.8789e-05 eta: 1:52:07 time: 0.9224 data_time: 0.0093 memory: 9147 grad_norm: 0.8568 loss: 1.2020 loss_heatmap: 0.5458 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5745 matched_ious: 0.5948 2023/03/23 13:13:23 - mmengine - INFO - Epoch(train) [19][ 550/3862] lr: 5.7995e-05 eta: 1:51:21 time: 0.9258 data_time: 0.0091 memory: 8900 grad_norm: 0.8428 loss: 1.0650 loss_heatmap: 0.4877 layer_-1_loss_cls: 0.0787 layer_-1_loss_bbox: 0.4987 matched_ious: 0.5548 2023/03/23 13:14:09 - mmengine - INFO - Epoch(train) [19][ 600/3862] lr: 5.7205e-05 eta: 1:50:34 time: 0.9261 data_time: 0.0091 memory: 9492 grad_norm: 0.8622 loss: 1.0813 loss_heatmap: 0.4989 layer_-1_loss_cls: 0.0772 layer_-1_loss_bbox: 0.5052 matched_ious: 0.5235 2023/03/23 13:14:57 - mmengine - INFO - Epoch(train) [19][ 650/3862] lr: 5.6421e-05 eta: 1:49:48 time: 0.9516 data_time: 0.0093 memory: 8947 grad_norm: 0.8043 loss: 1.0894 loss_heatmap: 0.4958 layer_-1_loss_cls: 0.0814 layer_-1_loss_bbox: 0.5122 matched_ious: 0.5436 2023/03/23 13:15:43 - mmengine - INFO - Epoch(train) [19][ 700/3862] lr: 5.5641e-05 eta: 1:49:01 time: 0.9243 data_time: 0.0092 memory: 9140 grad_norm: 0.8654 loss: 1.1064 loss_heatmap: 0.5098 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5148 matched_ious: 0.5663 2023/03/23 13:16:30 - mmengine - INFO - Epoch(train) [19][ 750/3862] lr: 5.4867e-05 eta: 1:48:14 time: 0.9279 data_time: 0.0093 memory: 9187 grad_norm: 0.7994 loss: 1.1503 loss_heatmap: 0.5048 layer_-1_loss_cls: 0.0785 layer_-1_loss_bbox: 0.5670 matched_ious: 0.4989 2023/03/23 13:17:16 - mmengine - INFO - Epoch(train) [19][ 800/3862] lr: 5.4098e-05 eta: 1:47:28 time: 0.9296 data_time: 0.0094 memory: 9219 grad_norm: 0.8235 loss: 1.1392 loss_heatmap: 0.5233 layer_-1_loss_cls: 0.0838 layer_-1_loss_bbox: 0.5320 matched_ious: 0.5970 2023/03/23 13:18:03 - mmengine - INFO - Epoch(train) [19][ 850/3862] lr: 5.3334e-05 eta: 1:46:41 time: 0.9335 data_time: 0.0091 memory: 9023 grad_norm: 0.8457 loss: 1.0520 loss_heatmap: 0.4829 layer_-1_loss_cls: 0.0770 layer_-1_loss_bbox: 0.4921 matched_ious: 0.5626 2023/03/23 13:18:49 - mmengine - INFO - Epoch(train) [19][ 900/3862] lr: 5.2575e-05 eta: 1:45:55 time: 0.9337 data_time: 0.0092 memory: 9263 grad_norm: 0.8642 loss: 1.0558 loss_heatmap: 0.4808 layer_-1_loss_cls: 0.0775 layer_-1_loss_bbox: 0.4975 matched_ious: 0.6103 2023/03/23 13:19:36 - mmengine - INFO - Epoch(train) [19][ 950/3862] lr: 5.1821e-05 eta: 1:45:08 time: 0.9322 data_time: 0.0098 memory: 8970 grad_norm: 0.7781 loss: 1.0959 loss_heatmap: 0.4853 layer_-1_loss_cls: 0.0767 layer_-1_loss_bbox: 0.5340 matched_ious: 0.6243 2023/03/23 13:20:23 - mmengine - INFO - Epoch(train) [19][1000/3862] lr: 5.1072e-05 eta: 1:44:22 time: 0.9299 data_time: 0.0093 memory: 9060 grad_norm: 0.8267 loss: 1.1173 loss_heatmap: 0.5124 layer_-1_loss_cls: 0.0794 layer_-1_loss_bbox: 0.5255 matched_ious: 0.5315 2023/03/23 13:21:09 - mmengine - INFO - Epoch(train) [19][1050/3862] lr: 5.0329e-05 eta: 1:43:35 time: 0.9237 data_time: 0.0092 memory: 8932 grad_norm: 0.8433 loss: 1.1027 loss_heatmap: 0.5021 layer_-1_loss_cls: 0.0769 layer_-1_loss_bbox: 0.5237 matched_ious: 0.5275 2023/03/23 13:21:55 - mmengine - INFO - Epoch(train) [19][1100/3862] lr: 4.9590e-05 eta: 1:42:48 time: 0.9245 data_time: 0.0091 memory: 9256 grad_norm: 0.8048 loss: 1.1257 loss_heatmap: 0.4984 layer_-1_loss_cls: 0.0787 layer_-1_loss_bbox: 0.5486 matched_ious: 0.5584 2023/03/23 13:22:41 - mmengine - INFO - Epoch(train) [19][1150/3862] lr: 4.8857e-05 eta: 1:42:01 time: 0.9290 data_time: 0.0092 memory: 9219 grad_norm: 0.8302 loss: 1.1199 loss_heatmap: 0.5301 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5090 matched_ious: 0.6144 2023/03/23 13:23:28 - mmengine - INFO - Epoch(train) [19][1200/3862] lr: 4.8129e-05 eta: 1:41:15 time: 0.9260 data_time: 0.0092 memory: 9179 grad_norm: 0.8340 loss: 1.1498 loss_heatmap: 0.5292 layer_-1_loss_cls: 0.0828 layer_-1_loss_bbox: 0.5378 matched_ious: 0.5834 2023/03/23 13:24:14 - mmengine - INFO - Epoch(train) [19][1250/3862] lr: 4.7406e-05 eta: 1:40:28 time: 0.9301 data_time: 0.0093 memory: 9126 grad_norm: 0.8162 loss: 1.0597 loss_heatmap: 0.4838 layer_-1_loss_cls: 0.0793 layer_-1_loss_bbox: 0.4966 matched_ious: 0.5488 2023/03/23 13:25:01 - mmengine - INFO - Epoch(train) [19][1300/3862] lr: 4.6689e-05 eta: 1:39:42 time: 0.9349 data_time: 0.0092 memory: 8979 grad_norm: 0.8270 loss: 1.0932 loss_heatmap: 0.5040 layer_-1_loss_cls: 0.0791 layer_-1_loss_bbox: 0.5100 matched_ious: 0.5933 2023/03/23 13:25:47 - mmengine - INFO - Epoch(train) [19][1350/3862] lr: 4.5976e-05 eta: 1:38:55 time: 0.9263 data_time: 0.0092 memory: 9498 grad_norm: 0.8413 loss: 1.1015 loss_heatmap: 0.4997 layer_-1_loss_cls: 0.0782 layer_-1_loss_bbox: 0.5236 matched_ious: 0.5306 2023/03/23 13:26:34 - mmengine - INFO - Epoch(train) [19][1400/3862] lr: 4.5269e-05 eta: 1:38:09 time: 0.9322 data_time: 0.0093 memory: 8918 grad_norm: 0.7892 loss: 1.1146 loss_heatmap: 0.5152 layer_-1_loss_cls: 0.0806 layer_-1_loss_bbox: 0.5189 matched_ious: 0.5628 2023/03/23 13:27:20 - mmengine - INFO - Epoch(train) [19][1450/3862] lr: 4.4567e-05 eta: 1:37:22 time: 0.9282 data_time: 0.0093 memory: 8953 grad_norm: 0.8436 loss: 1.0526 loss_heatmap: 0.4887 layer_-1_loss_cls: 0.0770 layer_-1_loss_bbox: 0.4869 matched_ious: 0.5835 2023/03/23 13:27:52 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 13:28:07 - mmengine - INFO - Epoch(train) [19][1500/3862] lr: 4.3870e-05 eta: 1:36:35 time: 0.9251 data_time: 0.0091 memory: 9494 grad_norm: 0.7825 loss: 1.1526 loss_heatmap: 0.5175 layer_-1_loss_cls: 0.0803 layer_-1_loss_bbox: 0.5547 matched_ious: 0.5793 2023/03/23 13:28:53 - mmengine - INFO - Epoch(train) [19][1550/3862] lr: 4.3179e-05 eta: 1:35:49 time: 0.9288 data_time: 0.0091 memory: 8979 grad_norm: 0.8309 loss: 1.1094 loss_heatmap: 0.5174 layer_-1_loss_cls: 0.0810 layer_-1_loss_bbox: 0.5111 matched_ious: 0.5953 2023/03/23 13:29:40 - mmengine - INFO - Epoch(train) [19][1600/3862] lr: 4.2493e-05 eta: 1:35:02 time: 0.9309 data_time: 0.0092 memory: 9177 grad_norm: 0.8090 loss: 1.1114 loss_heatmap: 0.5080 layer_-1_loss_cls: 0.0777 layer_-1_loss_bbox: 0.5258 matched_ious: 0.6664 2023/03/23 13:30:26 - mmengine - INFO - Epoch(train) [19][1650/3862] lr: 4.1812e-05 eta: 1:34:15 time: 0.9334 data_time: 0.0090 memory: 9005 grad_norm: 0.7773 loss: 1.1032 loss_heatmap: 0.5103 layer_-1_loss_cls: 0.0783 layer_-1_loss_bbox: 0.5146 matched_ious: 0.6097 2023/03/23 13:31:13 - mmengine - INFO - Epoch(train) [19][1700/3862] lr: 4.1136e-05 eta: 1:33:29 time: 0.9354 data_time: 0.0092 memory: 9098 grad_norm: 0.8918 loss: 1.1528 loss_heatmap: 0.5237 layer_-1_loss_cls: 0.0821 layer_-1_loss_bbox: 0.5470 matched_ious: 0.5612 2023/03/23 13:31:59 - mmengine - INFO - Epoch(train) [19][1750/3862] lr: 4.0466e-05 eta: 1:32:42 time: 0.9236 data_time: 0.0092 memory: 9232 grad_norm: 0.8479 loss: 1.1382 loss_heatmap: 0.5256 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.5322 matched_ious: 0.5452 2023/03/23 13:32:46 - mmengine - INFO - Epoch(train) [19][1800/3862] lr: 3.9800e-05 eta: 1:31:56 time: 0.9403 data_time: 0.0093 memory: 9091 grad_norm: 0.8419 loss: 1.0980 loss_heatmap: 0.4970 layer_-1_loss_cls: 0.0783 layer_-1_loss_bbox: 0.5227 matched_ious: 0.6041 2023/03/23 13:33:33 - mmengine - INFO - Epoch(train) [19][1850/3862] lr: 3.9141e-05 eta: 1:31:09 time: 0.9258 data_time: 0.0093 memory: 9195 grad_norm: 0.8250 loss: 1.1520 loss_heatmap: 0.5284 layer_-1_loss_cls: 0.0837 layer_-1_loss_bbox: 0.5400 matched_ious: 0.6033 2023/03/23 13:34:19 - mmengine - INFO - Epoch(train) [19][1900/3862] lr: 3.8486e-05 eta: 1:30:23 time: 0.9286 data_time: 0.0095 memory: 9208 grad_norm: 0.7863 loss: 1.1102 loss_heatmap: 0.5031 layer_-1_loss_cls: 0.0787 layer_-1_loss_bbox: 0.5284 matched_ious: 0.6183 2023/03/23 13:35:05 - mmengine - INFO - Epoch(train) [19][1950/3862] lr: 3.7837e-05 eta: 1:29:36 time: 0.9274 data_time: 0.0092 memory: 8759 grad_norm: 1.1784 loss: 1.1230 loss_heatmap: 0.5114 layer_-1_loss_cls: 0.0802 layer_-1_loss_bbox: 0.5314 matched_ious: 0.6455 2023/03/23 13:35:52 - mmengine - INFO - Epoch(train) [19][2000/3862] lr: 3.7193e-05 eta: 1:28:49 time: 0.9301 data_time: 0.0095 memory: 8998 grad_norm: 0.8489 loss: 0.9968 loss_heatmap: 0.4688 layer_-1_loss_cls: 0.0762 layer_-1_loss_bbox: 0.4517 matched_ious: 0.5728 2023/03/23 13:36:38 - mmengine - INFO - Epoch(train) [19][2050/3862] lr: 3.6554e-05 eta: 1:28:03 time: 0.9264 data_time: 0.0096 memory: 8840 grad_norm: 0.7938 loss: 1.0521 loss_heatmap: 0.4941 layer_-1_loss_cls: 0.0758 layer_-1_loss_bbox: 0.4822 matched_ious: 0.5795 2023/03/23 13:37:25 - mmengine - INFO - Epoch(train) [19][2100/3862] lr: 3.5921e-05 eta: 1:27:16 time: 0.9302 data_time: 0.0093 memory: 8919 grad_norm: 0.7939 loss: 1.1404 loss_heatmap: 0.5229 layer_-1_loss_cls: 0.0832 layer_-1_loss_bbox: 0.5344 matched_ious: 0.6219 2023/03/23 13:38:11 - mmengine - INFO - Epoch(train) [19][2150/3862] lr: 3.5293e-05 eta: 1:26:30 time: 0.9289 data_time: 0.0095 memory: 9418 grad_norm: 0.7538 loss: 1.0599 loss_heatmap: 0.4795 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.5013 matched_ious: 0.5991 2023/03/23 13:38:58 - mmengine - INFO - Epoch(train) [19][2200/3862] lr: 3.4670e-05 eta: 1:25:43 time: 0.9306 data_time: 0.0093 memory: 9187 grad_norm: 0.8220 loss: 1.1005 loss_heatmap: 0.5142 layer_-1_loss_cls: 0.0809 layer_-1_loss_bbox: 0.5053 matched_ious: 0.5683 2023/03/23 13:39:44 - mmengine - INFO - Epoch(train) [19][2250/3862] lr: 3.4053e-05 eta: 1:24:56 time: 0.9264 data_time: 0.0093 memory: 8970 grad_norm: 0.8014 loss: 1.0758 loss_heatmap: 0.5062 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.4908 matched_ious: 0.6317 2023/03/23 13:40:31 - mmengine - INFO - Epoch(train) [19][2300/3862] lr: 3.3441e-05 eta: 1:24:10 time: 0.9293 data_time: 0.0097 memory: 9089 grad_norm: 0.9282 loss: 1.0921 loss_heatmap: 0.4904 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.5228 matched_ious: 0.5630 2023/03/23 13:41:17 - mmengine - INFO - Epoch(train) [19][2350/3862] lr: 3.2834e-05 eta: 1:23:23 time: 0.9298 data_time: 0.0096 memory: 8991 grad_norm: 0.8003 loss: 1.0749 loss_heatmap: 0.5005 layer_-1_loss_cls: 0.0797 layer_-1_loss_bbox: 0.4948 matched_ious: 0.5465 2023/03/23 13:42:03 - mmengine - INFO - Epoch(train) [19][2400/3862] lr: 3.2233e-05 eta: 1:22:36 time: 0.9211 data_time: 0.0093 memory: 9049 grad_norm: 0.7985 loss: 1.1299 loss_heatmap: 0.5028 layer_-1_loss_cls: 0.0797 layer_-1_loss_bbox: 0.5474 matched_ious: 0.5630 2023/03/23 13:42:49 - mmengine - INFO - Epoch(train) [19][2450/3862] lr: 3.1637e-05 eta: 1:21:50 time: 0.9259 data_time: 0.0092 memory: 9006 grad_norm: 0.8485 loss: 1.1597 loss_heatmap: 0.5197 layer_-1_loss_cls: 0.0824 layer_-1_loss_bbox: 0.5576 matched_ious: 0.5748 2023/03/23 13:43:21 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 13:43:36 - mmengine - INFO - Epoch(train) [19][2500/3862] lr: 3.1047e-05 eta: 1:21:03 time: 0.9245 data_time: 0.0093 memory: 8797 grad_norm: 0.8193 loss: 1.1345 loss_heatmap: 0.5050 layer_-1_loss_cls: 0.0801 layer_-1_loss_bbox: 0.5493 matched_ious: 0.5692 2023/03/23 13:44:22 - mmengine - INFO - Epoch(train) [19][2550/3862] lr: 3.0462e-05 eta: 1:20:17 time: 0.9281 data_time: 0.0094 memory: 9284 grad_norm: 0.7981 loss: 1.1523 loss_heatmap: 0.5210 layer_-1_loss_cls: 0.0795 layer_-1_loss_bbox: 0.5518 matched_ious: 0.5363 2023/03/23 13:45:08 - mmengine - INFO - Epoch(train) [19][2600/3862] lr: 2.9882e-05 eta: 1:19:30 time: 0.9281 data_time: 0.0093 memory: 9191 grad_norm: 0.8562 loss: 1.1374 loss_heatmap: 0.5470 layer_-1_loss_cls: 0.0861 layer_-1_loss_bbox: 0.5043 matched_ious: 0.6560 2023/03/23 13:45:55 - mmengine - INFO - Epoch(train) [19][2650/3862] lr: 2.9308e-05 eta: 1:18:43 time: 0.9215 data_time: 0.0096 memory: 9128 grad_norm: 0.8444 loss: 1.1463 loss_heatmap: 0.5192 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5453 matched_ious: 0.6213 2023/03/23 13:46:41 - mmengine - INFO - Epoch(train) [19][2700/3862] lr: 2.8739e-05 eta: 1:17:57 time: 0.9264 data_time: 0.0095 memory: 8963 grad_norm: 0.8729 loss: 1.0710 loss_heatmap: 0.4914 layer_-1_loss_cls: 0.0767 layer_-1_loss_bbox: 0.5030 matched_ious: 0.6080 2023/03/23 13:47:27 - mmengine - INFO - Epoch(train) [19][2750/3862] lr: 2.8175e-05 eta: 1:17:10 time: 0.9317 data_time: 0.0096 memory: 9039 grad_norm: 0.8593 loss: 1.1830 loss_heatmap: 0.5300 layer_-1_loss_cls: 0.0865 layer_-1_loss_bbox: 0.5664 matched_ious: 0.5417 2023/03/23 13:48:14 - mmengine - INFO - Epoch(train) [19][2800/3862] lr: 2.7617e-05 eta: 1:16:23 time: 0.9279 data_time: 0.0093 memory: 9125 grad_norm: 0.8058 loss: 1.0048 loss_heatmap: 0.4757 layer_-1_loss_cls: 0.0746 layer_-1_loss_bbox: 0.4545 matched_ious: 0.6603 2023/03/23 13:49:00 - mmengine - INFO - Epoch(train) [19][2850/3862] lr: 2.7065e-05 eta: 1:15:37 time: 0.9284 data_time: 0.0095 memory: 9010 grad_norm: 0.8710 loss: 1.0344 loss_heatmap: 0.4678 layer_-1_loss_cls: 0.0738 layer_-1_loss_bbox: 0.4928 matched_ious: 0.5823 2023/03/23 13:49:46 - mmengine - INFO - Epoch(train) [19][2900/3862] lr: 2.6517e-05 eta: 1:14:50 time: 0.9244 data_time: 0.0093 memory: 9075 grad_norm: 0.7983 loss: 1.1007 loss_heatmap: 0.4939 layer_-1_loss_cls: 0.0782 layer_-1_loss_bbox: 0.5286 matched_ious: 0.5388 2023/03/23 13:50:33 - mmengine - INFO - Epoch(train) [19][2950/3862] lr: 2.5976e-05 eta: 1:14:04 time: 0.9398 data_time: 0.0093 memory: 9354 grad_norm: 0.8231 loss: 1.1132 loss_heatmap: 0.5059 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5272 matched_ious: 0.5419 2023/03/23 13:51:20 - mmengine - INFO - Epoch(train) [19][3000/3862] lr: 2.5439e-05 eta: 1:13:17 time: 0.9339 data_time: 0.0094 memory: 9000 grad_norm: 0.8091 loss: 1.0149 loss_heatmap: 0.4755 layer_-1_loss_cls: 0.0760 layer_-1_loss_bbox: 0.4634 matched_ious: 0.5775 2023/03/23 13:52:07 - mmengine - INFO - Epoch(train) [19][3050/3862] lr: 2.4909e-05 eta: 1:12:31 time: 0.9307 data_time: 0.0094 memory: 8906 grad_norm: 0.8425 loss: 1.0986 loss_heatmap: 0.5111 layer_-1_loss_cls: 0.0789 layer_-1_loss_bbox: 0.5086 matched_ious: 0.5176 2023/03/23 13:52:53 - mmengine - INFO - Epoch(train) [19][3100/3862] lr: 2.4383e-05 eta: 1:11:44 time: 0.9325 data_time: 0.0098 memory: 9227 grad_norm: 0.8420 loss: 1.1669 loss_heatmap: 0.5473 layer_-1_loss_cls: 0.0857 layer_-1_loss_bbox: 0.5340 matched_ious: 0.5344 2023/03/23 13:53:40 - mmengine - INFO - Epoch(train) [19][3150/3862] lr: 2.3863e-05 eta: 1:10:58 time: 0.9344 data_time: 0.0092 memory: 9022 grad_norm: 0.8287 loss: 1.1320 loss_heatmap: 0.5088 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.5427 matched_ious: 0.5513 2023/03/23 13:54:26 - mmengine - INFO - Epoch(train) [19][3200/3862] lr: 2.3349e-05 eta: 1:10:11 time: 0.9235 data_time: 0.0093 memory: 9250 grad_norm: 0.8148 loss: 1.0915 loss_heatmap: 0.5224 layer_-1_loss_cls: 0.0793 layer_-1_loss_bbox: 0.4898 matched_ious: 0.5414 2023/03/23 13:55:13 - mmengine - INFO - Epoch(train) [19][3250/3862] lr: 2.2840e-05 eta: 1:09:24 time: 0.9253 data_time: 0.0092 memory: 8935 grad_norm: 0.8447 loss: 1.0938 loss_heatmap: 0.5059 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.5091 matched_ious: 0.5673 2023/03/23 13:55:59 - mmengine - INFO - Epoch(train) [19][3300/3862] lr: 2.2336e-05 eta: 1:08:38 time: 0.9293 data_time: 0.0094 memory: 9368 grad_norm: 0.8444 loss: 1.1333 loss_heatmap: 0.5127 layer_-1_loss_cls: 0.0783 layer_-1_loss_bbox: 0.5423 matched_ious: 0.6040 2023/03/23 13:56:46 - mmengine - INFO - Epoch(train) [19][3350/3862] lr: 2.1838e-05 eta: 1:07:51 time: 0.9302 data_time: 0.0095 memory: 9119 grad_norm: 0.9088 loss: 1.0545 loss_heatmap: 0.4847 layer_-1_loss_cls: 0.0787 layer_-1_loss_bbox: 0.4911 matched_ious: 0.4944 2023/03/23 13:57:32 - mmengine - INFO - Epoch(train) [19][3400/3862] lr: 2.1346e-05 eta: 1:07:05 time: 0.9263 data_time: 0.0096 memory: 8939 grad_norm: 0.8579 loss: 1.1020 loss_heatmap: 0.5054 layer_-1_loss_cls: 0.0776 layer_-1_loss_bbox: 0.5190 matched_ious: 0.5290 2023/03/23 13:58:18 - mmengine - INFO - Epoch(train) [19][3450/3862] lr: 2.0859e-05 eta: 1:06:18 time: 0.9290 data_time: 0.0093 memory: 9412 grad_norm: 0.7891 loss: 1.0059 loss_heatmap: 0.4667 layer_-1_loss_cls: 0.0743 layer_-1_loss_bbox: 0.4648 matched_ious: 0.5451 2023/03/23 13:58:50 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 13:59:05 - mmengine - INFO - Epoch(train) [19][3500/3862] lr: 2.0377e-05 eta: 1:05:32 time: 0.9372 data_time: 0.0092 memory: 9267 grad_norm: 0.7792 loss: 1.1723 loss_heatmap: 0.5329 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5576 matched_ious: 0.5903 2023/03/23 13:59:51 - mmengine - INFO - Epoch(train) [19][3550/3862] lr: 1.9901e-05 eta: 1:04:45 time: 0.9225 data_time: 0.0093 memory: 9086 grad_norm: 0.7740 loss: 1.0475 loss_heatmap: 0.4895 layer_-1_loss_cls: 0.0743 layer_-1_loss_bbox: 0.4837 matched_ious: 0.6490 2023/03/23 14:00:38 - mmengine - INFO - Epoch(train) [19][3600/3862] lr: 1.9431e-05 eta: 1:03:58 time: 0.9262 data_time: 0.0092 memory: 8831 grad_norm: 0.8529 loss: 1.0849 loss_heatmap: 0.4865 layer_-1_loss_cls: 0.0763 layer_-1_loss_bbox: 0.5222 matched_ious: 0.5530 2023/03/23 14:01:24 - mmengine - INFO - Epoch(train) [19][3650/3862] lr: 1.8966e-05 eta: 1:03:12 time: 0.9325 data_time: 0.0094 memory: 9365 grad_norm: 0.9054 loss: 1.1319 loss_heatmap: 0.5273 layer_-1_loss_cls: 0.0836 layer_-1_loss_bbox: 0.5210 matched_ious: 0.5914 2023/03/23 14:02:10 - mmengine - INFO - Epoch(train) [19][3700/3862] lr: 1.8506e-05 eta: 1:02:25 time: 0.9221 data_time: 0.0092 memory: 8833 grad_norm: 0.8160 loss: 1.1493 loss_heatmap: 0.5096 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.5591 matched_ious: 0.5807 2023/03/23 14:02:57 - mmengine - INFO - Epoch(train) [19][3750/3862] lr: 1.8052e-05 eta: 1:01:39 time: 0.9273 data_time: 0.0092 memory: 9088 grad_norm: 0.8429 loss: 1.1188 loss_heatmap: 0.5151 layer_-1_loss_cls: 0.0796 layer_-1_loss_bbox: 0.5241 matched_ious: 0.5786 2023/03/23 14:03:43 - mmengine - INFO - Epoch(train) [19][3800/3862] lr: 1.7604e-05 eta: 1:00:52 time: 0.9188 data_time: 0.0095 memory: 8821 grad_norm: 0.8390 loss: 1.1030 loss_heatmap: 0.5113 layer_-1_loss_cls: 0.0806 layer_-1_loss_bbox: 0.5111 matched_ious: 0.5815 2023/03/23 14:04:29 - mmengine - INFO - Epoch(train) [19][3850/3862] lr: 1.7161e-05 eta: 1:00:05 time: 0.9289 data_time: 0.0093 memory: 8911 grad_norm: 0.8302 loss: 1.1523 loss_heatmap: 0.5091 layer_-1_loss_cls: 0.0804 layer_-1_loss_bbox: 0.5629 matched_ious: 0.5883 2023/03/23 14:04:40 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 14:05:28 - mmengine - INFO - Epoch(train) [20][ 50/3862] lr: 1.6620e-05 eta: 0:59:08 time: 0.9457 data_time: 0.0257 memory: 9285 grad_norm: 0.8005 loss: 1.0843 loss_heatmap: 0.4910 layer_-1_loss_cls: 0.0747 layer_-1_loss_bbox: 0.5186 matched_ious: 0.5512 2023/03/23 14:06:14 - mmengine - INFO - Epoch(train) [20][ 100/3862] lr: 1.6189e-05 eta: 0:58:21 time: 0.9311 data_time: 0.0090 memory: 8936 grad_norm: 0.8132 loss: 1.1714 loss_heatmap: 0.5402 layer_-1_loss_cls: 0.0824 layer_-1_loss_bbox: 0.5489 matched_ious: 0.6258 2023/03/23 14:07:01 - mmengine - INFO - Epoch(train) [20][ 150/3862] lr: 1.5764e-05 eta: 0:57:35 time: 0.9304 data_time: 0.0093 memory: 9057 grad_norm: 0.8129 loss: 1.1466 loss_heatmap: 0.5413 layer_-1_loss_cls: 0.0838 layer_-1_loss_bbox: 0.5214 matched_ious: 0.6136 2023/03/23 14:07:47 - mmengine - INFO - Epoch(train) [20][ 200/3862] lr: 1.5345e-05 eta: 0:56:48 time: 0.9293 data_time: 0.0091 memory: 8920 grad_norm: 0.8564 loss: 1.1419 loss_heatmap: 0.5237 layer_-1_loss_cls: 0.0812 layer_-1_loss_bbox: 0.5369 matched_ious: 0.5810 2023/03/23 14:08:34 - mmengine - INFO - Epoch(train) [20][ 250/3862] lr: 1.4931e-05 eta: 0:56:02 time: 0.9351 data_time: 0.0092 memory: 8868 grad_norm: 1.0079 loss: 1.1004 loss_heatmap: 0.5216 layer_-1_loss_cls: 0.0797 layer_-1_loss_bbox: 0.4992 matched_ious: 0.5470 2023/03/23 14:09:21 - mmengine - INFO - Epoch(train) [20][ 300/3862] lr: 1.4523e-05 eta: 0:55:15 time: 0.9334 data_time: 0.0091 memory: 9182 grad_norm: 0.8301 loss: 1.1058 loss_heatmap: 0.4963 layer_-1_loss_cls: 0.0777 layer_-1_loss_bbox: 0.5317 matched_ious: 0.6679 2023/03/23 14:10:07 - mmengine - INFO - Epoch(train) [20][ 350/3862] lr: 1.4121e-05 eta: 0:54:29 time: 0.9331 data_time: 0.0094 memory: 9025 grad_norm: 0.8675 loss: 1.0639 loss_heatmap: 0.4878 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.4981 matched_ious: 0.6253 2023/03/23 14:10:54 - mmengine - INFO - Epoch(train) [20][ 400/3862] lr: 1.3724e-05 eta: 0:53:42 time: 0.9339 data_time: 0.0093 memory: 9230 grad_norm: 0.8667 loss: 1.1083 loss_heatmap: 0.5032 layer_-1_loss_cls: 0.0793 layer_-1_loss_bbox: 0.5258 matched_ious: 0.6100 2023/03/23 14:11:40 - mmengine - INFO - Epoch(train) [20][ 450/3862] lr: 1.3332e-05 eta: 0:52:56 time: 0.9295 data_time: 0.0093 memory: 8911 grad_norm: 0.8089 loss: 1.1801 loss_heatmap: 0.5144 layer_-1_loss_cls: 0.0791 layer_-1_loss_bbox: 0.5866 matched_ious: 0.5707 2023/03/23 14:12:26 - mmengine - INFO - Epoch(train) [20][ 500/3862] lr: 1.2947e-05 eta: 0:52:09 time: 0.9175 data_time: 0.0091 memory: 8944 grad_norm: 0.8677 loss: 1.1224 loss_heatmap: 0.4987 layer_-1_loss_cls: 0.0754 layer_-1_loss_bbox: 0.5483 matched_ious: 0.5233 2023/03/23 14:13:13 - mmengine - INFO - Epoch(train) [20][ 550/3862] lr: 1.2566e-05 eta: 0:51:22 time: 0.9373 data_time: 0.0094 memory: 9200 grad_norm: 0.8732 loss: 1.1568 loss_heatmap: 0.5222 layer_-1_loss_cls: 0.0828 layer_-1_loss_bbox: 0.5518 matched_ious: 0.6242 2023/03/23 14:14:00 - mmengine - INFO - Epoch(train) [20][ 600/3862] lr: 1.2192e-05 eta: 0:50:36 time: 0.9291 data_time: 0.0091 memory: 9181 grad_norm: 0.8094 loss: 1.1075 loss_heatmap: 0.5087 layer_-1_loss_cls: 0.0790 layer_-1_loss_bbox: 0.5198 matched_ious: 0.6481 2023/03/23 14:14:20 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 14:14:46 - mmengine - INFO - Epoch(train) [20][ 650/3862] lr: 1.1823e-05 eta: 0:49:49 time: 0.9308 data_time: 0.0095 memory: 9280 grad_norm: 0.8304 loss: 1.0965 loss_heatmap: 0.4947 layer_-1_loss_cls: 0.0759 layer_-1_loss_bbox: 0.5260 matched_ious: 0.5950 2023/03/23 14:15:32 - mmengine - INFO - Epoch(train) [20][ 700/3862] lr: 1.1459e-05 eta: 0:49:03 time: 0.9201 data_time: 0.0091 memory: 8914 grad_norm: 0.8433 loss: 1.0363 loss_heatmap: 0.4627 layer_-1_loss_cls: 0.0741 layer_-1_loss_bbox: 0.4994 matched_ious: 0.5736 2023/03/23 14:16:18 - mmengine - INFO - Epoch(train) [20][ 750/3862] lr: 1.1102e-05 eta: 0:48:16 time: 0.9242 data_time: 0.0091 memory: 9028 grad_norm: 0.8706 loss: 1.1007 loss_heatmap: 0.5058 layer_-1_loss_cls: 0.0780 layer_-1_loss_bbox: 0.5169 matched_ious: 0.5434 2023/03/23 14:17:05 - mmengine - INFO - Epoch(train) [20][ 800/3862] lr: 1.0749e-05 eta: 0:47:30 time: 0.9304 data_time: 0.0091 memory: 9063 grad_norm: 0.8127 loss: 1.0146 loss_heatmap: 0.4763 layer_-1_loss_cls: 0.0748 layer_-1_loss_bbox: 0.4636 matched_ious: 0.5967 2023/03/23 14:17:51 - mmengine - INFO - Epoch(train) [20][ 850/3862] lr: 1.0403e-05 eta: 0:46:43 time: 0.9254 data_time: 0.0094 memory: 8918 grad_norm: 0.8481 loss: 1.0982 loss_heatmap: 0.5005 layer_-1_loss_cls: 0.0760 layer_-1_loss_bbox: 0.5217 matched_ious: 0.6089 2023/03/23 14:18:38 - mmengine - INFO - Epoch(train) [20][ 900/3862] lr: 1.0062e-05 eta: 0:45:56 time: 0.9359 data_time: 0.0097 memory: 8951 grad_norm: 0.8707 loss: 1.1176 loss_heatmap: 0.5056 layer_-1_loss_cls: 0.0766 layer_-1_loss_bbox: 0.5354 matched_ious: 0.5535 2023/03/23 14:19:24 - mmengine - INFO - Epoch(train) [20][ 950/3862] lr: 9.7267e-06 eta: 0:45:10 time: 0.9215 data_time: 0.0091 memory: 9100 grad_norm: 0.8292 loss: 1.0953 loss_heatmap: 0.5076 layer_-1_loss_cls: 0.0770 layer_-1_loss_bbox: 0.5107 matched_ious: 0.5854 2023/03/23 14:20:11 - mmengine - INFO - Epoch(train) [20][1000/3862] lr: 9.3970e-06 eta: 0:44:23 time: 0.9339 data_time: 0.0092 memory: 8911 grad_norm: 0.8026 loss: 1.0621 loss_heatmap: 0.5059 layer_-1_loss_cls: 0.0786 layer_-1_loss_bbox: 0.4776 matched_ious: 0.5922 2023/03/23 14:20:57 - mmengine - INFO - Epoch(train) [20][1050/3862] lr: 9.0730e-06 eta: 0:43:37 time: 0.9211 data_time: 0.0091 memory: 8793 grad_norm: 0.8282 loss: 1.1055 loss_heatmap: 0.5107 layer_-1_loss_cls: 0.0784 layer_-1_loss_bbox: 0.5163 matched_ious: 0.5508 2023/03/23 14:21:43 - mmengine - INFO - Epoch(train) [20][1100/3862] lr: 8.7546e-06 eta: 0:42:50 time: 0.9246 data_time: 0.0092 memory: 9162 grad_norm: 0.7964 loss: 1.1012 loss_heatmap: 0.4925 layer_-1_loss_cls: 0.0772 layer_-1_loss_bbox: 0.5315 matched_ious: 0.5655 2023/03/23 14:22:29 - mmengine - INFO - Epoch(train) [20][1150/3862] lr: 8.4419e-06 eta: 0:42:04 time: 0.9253 data_time: 0.0091 memory: 9338 grad_norm: 0.8403 loss: 1.0505 loss_heatmap: 0.4936 layer_-1_loss_cls: 0.0792 layer_-1_loss_bbox: 0.4777 matched_ious: 0.5623 2023/03/23 14:23:16 - mmengine - INFO - Epoch(train) [20][1200/3862] lr: 8.1348e-06 eta: 0:41:17 time: 0.9287 data_time: 0.0091 memory: 9180 grad_norm: 0.7980 loss: 1.1284 loss_heatmap: 0.5242 layer_-1_loss_cls: 0.0817 layer_-1_loss_bbox: 0.5224 matched_ious: 0.5785 2023/03/23 14:24:02 - mmengine - INFO - Epoch(train) [20][1250/3862] lr: 7.8333e-06 eta: 0:40:30 time: 0.9252 data_time: 0.0094 memory: 8922 grad_norm: 0.8609 loss: 1.1022 loss_heatmap: 0.4949 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5267 matched_ious: 0.6528 2023/03/23 14:24:48 - mmengine - INFO - Epoch(train) [20][1300/3862] lr: 7.5375e-06 eta: 0:39:44 time: 0.9258 data_time: 0.0092 memory: 9099 grad_norm: 0.8468 loss: 1.1444 loss_heatmap: 0.5194 layer_-1_loss_cls: 0.0813 layer_-1_loss_bbox: 0.5437 matched_ious: 0.6184 2023/03/23 14:25:36 - mmengine - INFO - Epoch(train) [20][1350/3862] lr: 7.2474e-06 eta: 0:38:58 time: 0.9534 data_time: 0.0093 memory: 8944 grad_norm: 0.7967 loss: 1.0884 loss_heatmap: 0.4909 layer_-1_loss_cls: 0.0789 layer_-1_loss_bbox: 0.5186 matched_ious: 0.5332 2023/03/23 14:26:23 - mmengine - INFO - Epoch(train) [20][1400/3862] lr: 6.9629e-06 eta: 0:38:11 time: 0.9350 data_time: 0.0092 memory: 9013 grad_norm: 0.8436 loss: 1.0499 loss_heatmap: 0.4726 layer_-1_loss_cls: 0.0738 layer_-1_loss_bbox: 0.5035 matched_ious: 0.5361 2023/03/23 14:27:09 - mmengine - INFO - Epoch(train) [20][1450/3862] lr: 6.6841e-06 eta: 0:37:24 time: 0.9321 data_time: 0.0092 memory: 8857 grad_norm: 0.8359 loss: 1.1818 loss_heatmap: 0.5365 layer_-1_loss_cls: 0.0826 layer_-1_loss_bbox: 0.5626 matched_ious: 0.5676 2023/03/23 14:27:56 - mmengine - INFO - Epoch(train) [20][1500/3862] lr: 6.4110e-06 eta: 0:36:38 time: 0.9282 data_time: 0.0096 memory: 8991 grad_norm: 0.8128 loss: 1.1046 loss_heatmap: 0.5086 layer_-1_loss_cls: 0.0786 layer_-1_loss_bbox: 0.5174 matched_ious: 0.5447 2023/03/23 14:28:43 - mmengine - INFO - Epoch(train) [20][1550/3862] lr: 6.1435e-06 eta: 0:35:51 time: 0.9337 data_time: 0.0092 memory: 9245 grad_norm: 0.8149 loss: 1.0506 loss_heatmap: 0.4904 layer_-1_loss_cls: 0.0802 layer_-1_loss_bbox: 0.4801 matched_ious: 0.4836 2023/03/23 14:29:29 - mmengine - INFO - Epoch(train) [20][1600/3862] lr: 5.8817e-06 eta: 0:35:05 time: 0.9321 data_time: 0.0091 memory: 9233 grad_norm: 0.7893 loss: 1.1626 loss_heatmap: 0.5123 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.5714 matched_ious: 0.5455 2023/03/23 14:29:50 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 14:30:15 - mmengine - INFO - Epoch(train) [20][1650/3862] lr: 5.6256e-06 eta: 0:34:18 time: 0.9253 data_time: 0.0091 memory: 9046 grad_norm: 0.7875 loss: 1.1432 loss_heatmap: 0.5185 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5436 matched_ious: 0.5500 2023/03/23 14:31:02 - mmengine - INFO - Epoch(train) [20][1700/3862] lr: 5.3752e-06 eta: 0:33:32 time: 0.9329 data_time: 0.0094 memory: 8877 grad_norm: 0.8658 loss: 1.1292 loss_heatmap: 0.5194 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5291 matched_ious: 0.6191 2023/03/23 14:31:49 - mmengine - INFO - Epoch(train) [20][1750/3862] lr: 5.1304e-06 eta: 0:32:45 time: 0.9307 data_time: 0.0094 memory: 9079 grad_norm: 0.8072 loss: 1.0988 loss_heatmap: 0.4940 layer_-1_loss_cls: 0.0769 layer_-1_loss_bbox: 0.5279 matched_ious: 0.5537 2023/03/23 14:32:35 - mmengine - INFO - Epoch(train) [20][1800/3862] lr: 4.8913e-06 eta: 0:31:59 time: 0.9262 data_time: 0.0093 memory: 9015 grad_norm: 0.8142 loss: 1.0213 loss_heatmap: 0.4722 layer_-1_loss_cls: 0.0751 layer_-1_loss_bbox: 0.4740 matched_ious: 0.5163 2023/03/23 14:33:21 - mmengine - INFO - Epoch(train) [20][1850/3862] lr: 4.6580e-06 eta: 0:31:12 time: 0.9302 data_time: 0.0093 memory: 9025 grad_norm: 0.7621 loss: 1.0908 loss_heatmap: 0.4874 layer_-1_loss_cls: 0.0770 layer_-1_loss_bbox: 0.5265 matched_ious: 0.5622 2023/03/23 14:34:08 - mmengine - INFO - Epoch(train) [20][1900/3862] lr: 4.4303e-06 eta: 0:30:26 time: 0.9289 data_time: 0.0091 memory: 8771 grad_norm: 0.8264 loss: 1.0773 loss_heatmap: 0.4873 layer_-1_loss_cls: 0.0768 layer_-1_loss_bbox: 0.5131 matched_ious: 0.5639 2023/03/23 14:34:54 - mmengine - INFO - Epoch(train) [20][1950/3862] lr: 4.2083e-06 eta: 0:29:39 time: 0.9306 data_time: 0.0095 memory: 8863 grad_norm: 0.8257 loss: 1.0233 loss_heatmap: 0.4667 layer_-1_loss_cls: 0.0751 layer_-1_loss_bbox: 0.4816 matched_ious: 0.5444 2023/03/23 14:35:41 - mmengine - INFO - Epoch(train) [20][2000/3862] lr: 3.9920e-06 eta: 0:28:53 time: 0.9309 data_time: 0.0092 memory: 9201 grad_norm: 0.8870 loss: 1.0517 loss_heatmap: 0.4749 layer_-1_loss_cls: 0.0765 layer_-1_loss_bbox: 0.5003 matched_ious: 0.5779 2023/03/23 14:36:28 - mmengine - INFO - Epoch(train) [20][2050/3862] lr: 3.7814e-06 eta: 0:28:06 time: 0.9320 data_time: 0.0093 memory: 8839 grad_norm: 0.8161 loss: 1.1579 loss_heatmap: 0.5142 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.5659 matched_ious: 0.5499 2023/03/23 14:37:14 - mmengine - INFO - Epoch(train) [20][2100/3862] lr: 3.5764e-06 eta: 0:27:19 time: 0.9361 data_time: 0.0096 memory: 9239 grad_norm: 0.8656 loss: 1.1270 loss_heatmap: 0.5070 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.5413 matched_ious: 0.5787 2023/03/23 14:38:01 - mmengine - INFO - Epoch(train) [20][2150/3862] lr: 3.3772e-06 eta: 0:26:33 time: 0.9318 data_time: 0.0094 memory: 9260 grad_norm: 0.7851 loss: 1.1023 loss_heatmap: 0.5100 layer_-1_loss_cls: 0.0806 layer_-1_loss_bbox: 0.5117 matched_ious: 0.6132 2023/03/23 14:38:47 - mmengine - INFO - Epoch(train) [20][2200/3862] lr: 3.1838e-06 eta: 0:25:46 time: 0.9274 data_time: 0.0100 memory: 9007 grad_norm: 0.8357 loss: 1.0642 loss_heatmap: 0.4859 layer_-1_loss_cls: 0.0778 layer_-1_loss_bbox: 0.5004 matched_ious: 0.5503 2023/03/23 14:39:34 - mmengine - INFO - Epoch(train) [20][2250/3862] lr: 2.9960e-06 eta: 0:25:00 time: 0.9259 data_time: 0.0123 memory: 9267 grad_norm: 0.8536 loss: 1.1087 loss_heatmap: 0.5161 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5108 matched_ious: 0.5623 2023/03/23 14:40:20 - mmengine - INFO - Epoch(train) [20][2300/3862] lr: 2.8139e-06 eta: 0:24:13 time: 0.9300 data_time: 0.0110 memory: 8836 grad_norm: 0.7833 loss: 1.1202 loss_heatmap: 0.5000 layer_-1_loss_cls: 0.0761 layer_-1_loss_bbox: 0.5441 matched_ious: 0.6489 2023/03/23 14:41:06 - mmengine - INFO - Epoch(train) [20][2350/3862] lr: 2.6375e-06 eta: 0:23:27 time: 0.9246 data_time: 0.0101 memory: 8878 grad_norm: 0.8349 loss: 1.0930 loss_heatmap: 0.5053 layer_-1_loss_cls: 0.0808 layer_-1_loss_bbox: 0.5068 matched_ious: 0.5745 2023/03/23 14:41:53 - mmengine - INFO - Epoch(train) [20][2400/3862] lr: 2.4669e-06 eta: 0:22:40 time: 0.9255 data_time: 0.0109 memory: 8810 grad_norm: 0.7719 loss: 1.1523 loss_heatmap: 0.5256 layer_-1_loss_cls: 0.0818 layer_-1_loss_bbox: 0.5449 matched_ious: 0.5631 2023/03/23 14:42:39 - mmengine - INFO - Epoch(train) [20][2450/3862] lr: 2.3019e-06 eta: 0:21:54 time: 0.9254 data_time: 0.0115 memory: 8942 grad_norm: 0.7962 loss: 1.0898 loss_heatmap: 0.4956 layer_-1_loss_cls: 0.0766 layer_-1_loss_bbox: 0.5175 matched_ious: 0.5978 2023/03/23 14:43:27 - mmengine - INFO - Epoch(train) [20][2500/3862] lr: 2.1427e-06 eta: 0:21:07 time: 0.9528 data_time: 0.0107 memory: 9126 grad_norm: 0.8426 loss: 1.0348 loss_heatmap: 0.4764 layer_-1_loss_cls: 0.0777 layer_-1_loss_bbox: 0.4807 matched_ious: 0.6023 2023/03/23 14:44:13 - mmengine - INFO - Epoch(train) [20][2550/3862] lr: 1.9892e-06 eta: 0:20:21 time: 0.9275 data_time: 0.0111 memory: 9264 grad_norm: 0.8115 loss: 1.1342 loss_heatmap: 0.5145 layer_-1_loss_cls: 0.0807 layer_-1_loss_bbox: 0.5390 matched_ious: 0.5838 2023/03/23 14:44:59 - mmengine - INFO - Epoch(train) [20][2600/3862] lr: 1.8414e-06 eta: 0:19:34 time: 0.9288 data_time: 0.0113 memory: 8877 grad_norm: 0.8227 loss: 1.1290 loss_heatmap: 0.5085 layer_-1_loss_cls: 0.0764 layer_-1_loss_bbox: 0.5440 matched_ious: 0.6523 2023/03/23 14:45:20 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 14:45:46 - mmengine - INFO - Epoch(train) [20][2650/3862] lr: 1.6994e-06 eta: 0:18:48 time: 0.9290 data_time: 0.0119 memory: 8749 grad_norm: 0.8091 loss: 1.0718 loss_heatmap: 0.4927 layer_-1_loss_cls: 0.0773 layer_-1_loss_bbox: 0.5018 matched_ious: 0.5958 2023/03/23 14:46:32 - mmengine - INFO - Epoch(train) [20][2700/3862] lr: 1.5630e-06 eta: 0:18:01 time: 0.9292 data_time: 0.0120 memory: 8998 grad_norm: 0.7783 loss: 1.0950 loss_heatmap: 0.4819 layer_-1_loss_cls: 0.0795 layer_-1_loss_bbox: 0.5336 matched_ious: 0.5906 2023/03/23 14:47:19 - mmengine - INFO - Epoch(train) [20][2750/3862] lr: 1.4324e-06 eta: 0:17:14 time: 0.9253 data_time: 0.0114 memory: 8941 grad_norm: 0.7578 loss: 1.0858 loss_heatmap: 0.4957 layer_-1_loss_cls: 0.0786 layer_-1_loss_bbox: 0.5116 matched_ious: 0.5261 2023/03/23 14:48:05 - mmengine - INFO - Epoch(train) [20][2800/3862] lr: 1.3076e-06 eta: 0:16:28 time: 0.9318 data_time: 0.0118 memory: 9106 grad_norm: 0.7679 loss: 1.1209 loss_heatmap: 0.5122 layer_-1_loss_cls: 0.0784 layer_-1_loss_bbox: 0.5304 matched_ious: 0.6093 2023/03/23 14:48:52 - mmengine - INFO - Epoch(train) [20][2850/3862] lr: 1.1884e-06 eta: 0:15:41 time: 0.9309 data_time: 0.0116 memory: 8754 grad_norm: 0.7814 loss: 1.0458 loss_heatmap: 0.4893 layer_-1_loss_cls: 0.0787 layer_-1_loss_bbox: 0.4779 matched_ious: 0.5336 2023/03/23 14:49:38 - mmengine - INFO - Epoch(train) [20][2900/3862] lr: 1.0750e-06 eta: 0:14:55 time: 0.9267 data_time: 0.0113 memory: 9212 grad_norm: 0.8378 loss: 1.0954 loss_heatmap: 0.5055 layer_-1_loss_cls: 0.0800 layer_-1_loss_bbox: 0.5098 matched_ious: 0.4924 2023/03/23 14:50:25 - mmengine - INFO - Epoch(train) [20][2950/3862] lr: 9.6731e-07 eta: 0:14:08 time: 0.9344 data_time: 0.0117 memory: 8876 grad_norm: 0.7969 loss: 1.1119 loss_heatmap: 0.5223 layer_-1_loss_cls: 0.0816 layer_-1_loss_bbox: 0.5080 matched_ious: 0.6379 2023/03/23 14:51:11 - mmengine - INFO - Epoch(train) [20][3000/3862] lr: 8.6535e-07 eta: 0:13:22 time: 0.9280 data_time: 0.0115 memory: 8878 grad_norm: 0.8579 loss: 1.0522 loss_heatmap: 0.4897 layer_-1_loss_cls: 0.0764 layer_-1_loss_bbox: 0.4861 matched_ious: 0.6231 2023/03/23 14:51:58 - mmengine - INFO - Epoch(train) [20][3050/3862] lr: 7.6914e-07 eta: 0:12:35 time: 0.9298 data_time: 0.0116 memory: 9392 grad_norm: 0.8182 loss: 1.1355 loss_heatmap: 0.5179 layer_-1_loss_cls: 0.0831 layer_-1_loss_bbox: 0.5344 matched_ious: 0.5992 2023/03/23 14:52:45 - mmengine - INFO - Epoch(train) [20][3100/3862] lr: 6.7865e-07 eta: 0:11:49 time: 0.9372 data_time: 0.0115 memory: 9232 grad_norm: 0.7777 loss: 1.1182 loss_heatmap: 0.5089 layer_-1_loss_cls: 0.0757 layer_-1_loss_bbox: 0.5336 matched_ious: 0.5850 2023/03/23 14:53:31 - mmengine - INFO - Epoch(train) [20][3150/3862] lr: 5.9391e-07 eta: 0:11:02 time: 0.9304 data_time: 0.0118 memory: 9103 grad_norm: 0.8354 loss: 1.1091 loss_heatmap: 0.5094 layer_-1_loss_cls: 0.0809 layer_-1_loss_bbox: 0.5188 matched_ious: 0.6099 2023/03/23 14:54:18 - mmengine - INFO - Epoch(train) [20][3200/3862] lr: 5.1490e-07 eta: 0:10:16 time: 0.9285 data_time: 0.0115 memory: 8803 grad_norm: 0.8697 loss: 1.0843 loss_heatmap: 0.5024 layer_-1_loss_cls: 0.0785 layer_-1_loss_bbox: 0.5034 matched_ious: 0.5593 2023/03/23 14:55:04 - mmengine - INFO - Epoch(train) [20][3250/3862] lr: 4.4163e-07 eta: 0:09:29 time: 0.9252 data_time: 0.0116 memory: 9062 grad_norm: 0.8304 loss: 1.0766 loss_heatmap: 0.4964 layer_-1_loss_cls: 0.0795 layer_-1_loss_bbox: 0.5007 matched_ious: 0.5942 2023/03/23 14:55:51 - mmengine - INFO - Epoch(train) [20][3300/3862] lr: 3.7409e-07 eta: 0:08:43 time: 0.9337 data_time: 0.0116 memory: 9211 grad_norm: 0.8296 loss: 1.1073 loss_heatmap: 0.5138 layer_-1_loss_cls: 0.0834 layer_-1_loss_bbox: 0.5100 matched_ious: 0.5778 2023/03/23 14:56:37 - mmengine - INFO - Epoch(train) [20][3350/3862] lr: 3.1230e-07 eta: 0:07:56 time: 0.9257 data_time: 0.0115 memory: 8977 grad_norm: 0.7773 loss: 1.0968 loss_heatmap: 0.5029 layer_-1_loss_cls: 0.0805 layer_-1_loss_bbox: 0.5134 matched_ious: 0.5993 2023/03/23 14:57:23 - mmengine - INFO - Epoch(train) [20][3400/3862] lr: 2.5625e-07 eta: 0:07:09 time: 0.9217 data_time: 0.0112 memory: 8899 grad_norm: 0.8810 loss: 1.0441 loss_heatmap: 0.4833 layer_-1_loss_cls: 0.0768 layer_-1_loss_bbox: 0.4840 matched_ious: 0.5898 2023/03/23 14:58:09 - mmengine - INFO - Epoch(train) [20][3450/3862] lr: 2.0594e-07 eta: 0:06:23 time: 0.9288 data_time: 0.0118 memory: 8857 grad_norm: 0.8388 loss: 1.1286 loss_heatmap: 0.5102 layer_-1_loss_cls: 0.0811 layer_-1_loss_bbox: 0.5373 matched_ious: 0.6245 2023/03/23 14:58:56 - mmengine - INFO - Epoch(train) [20][3500/3862] lr: 1.6137e-07 eta: 0:05:36 time: 0.9306 data_time: 0.0116 memory: 9206 grad_norm: 0.8664 loss: 1.0719 loss_heatmap: 0.4735 layer_-1_loss_cls: 0.0744 layer_-1_loss_bbox: 0.5240 matched_ious: 0.5534 2023/03/23 14:59:42 - mmengine - INFO - Epoch(train) [20][3550/3862] lr: 1.2254e-07 eta: 0:04:50 time: 0.9265 data_time: 0.0112 memory: 9229 grad_norm: 0.8268 loss: 1.0894 loss_heatmap: 0.4842 layer_-1_loss_cls: 0.0771 layer_-1_loss_bbox: 0.5282 matched_ious: 0.5430 2023/03/23 15:00:29 - mmengine - INFO - Epoch(train) [20][3600/3862] lr: 8.9460e-08 eta: 0:04:03 time: 0.9340 data_time: 0.0114 memory: 9075 grad_norm: 0.8645 loss: 1.1047 loss_heatmap: 0.5006 layer_-1_loss_cls: 0.0776 layer_-1_loss_bbox: 0.5265 matched_ious: 0.4860 2023/03/23 15:00:50 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 15:01:17 - mmengine - INFO - Epoch(train) [20][3650/3862] lr: 6.2119e-08 eta: 0:03:17 time: 0.9500 data_time: 0.0112 memory: 9005 grad_norm: 0.8178 loss: 1.0471 loss_heatmap: 0.4814 layer_-1_loss_cls: 0.0774 layer_-1_loss_bbox: 0.4882 matched_ious: 0.5447 2023/03/23 15:02:03 - mmengine - INFO - Epoch(train) [20][3700/3862] lr: 4.0522e-08 eta: 0:02:30 time: 0.9264 data_time: 0.0115 memory: 9246 grad_norm: 0.7522 loss: 1.0372 loss_heatmap: 0.4800 layer_-1_loss_cls: 0.0761 layer_-1_loss_bbox: 0.4811 matched_ious: 0.4944 2023/03/23 15:02:49 - mmengine - INFO - Epoch(train) [20][3750/3862] lr: 2.4669e-08 eta: 0:01:44 time: 0.9319 data_time: 0.0117 memory: 9037 grad_norm: 0.7734 loss: 1.1378 loss_heatmap: 0.5145 layer_-1_loss_cls: 0.0793 layer_-1_loss_bbox: 0.5440 matched_ious: 0.6062 2023/03/23 15:03:36 - mmengine - INFO - Epoch(train) [20][3800/3862] lr: 1.4560e-08 eta: 0:00:57 time: 0.9291 data_time: 0.0114 memory: 9266 grad_norm: 0.7950 loss: 1.0617 loss_heatmap: 0.4912 layer_-1_loss_cls: 0.0788 layer_-1_loss_bbox: 0.4917 matched_ious: 0.5790 2023/03/23 15:04:22 - mmengine - INFO - Epoch(train) [20][3850/3862] lr: 1.0194e-08 eta: 0:00:11 time: 0.9289 data_time: 0.0117 memory: 8939 grad_norm: 0.8774 loss: 1.1434 loss_heatmap: 0.5300 layer_-1_loss_cls: 0.0819 layer_-1_loss_bbox: 0.5315 matched_ious: 0.5620 2023/03/23 15:04:33 - mmengine - INFO - Exp name: bevfusion_lidar_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d_20230323_100227 2023/03/23 15:04:33 - mmengine - INFO - Saving checkpoint at 20 epochs 2023/03/23 15:04:46 - mmengine - INFO - Epoch(val) [20][ 50/753] eta: 0:02:01 time: 0.1730 data_time: 0.0144 memory: 8898 2023/03/23 15:04:53 - mmengine - INFO - Epoch(val) [20][100/753] eta: 0:01:44 time: 0.1464 data_time: 0.0029 memory: 732 2023/03/23 15:05:01 - mmengine - INFO - Epoch(val) [20][150/753] eta: 0:01:34 time: 0.1502 data_time: 0.0034 memory: 732 2023/03/23 15:05:08 - mmengine - INFO - Epoch(val) [20][200/753] eta: 0:01:26 time: 0.1526 data_time: 0.0030 memory: 732 2023/03/23 15:05:16 - mmengine - INFO - Epoch(val) [20][250/753] eta: 0:01:17 time: 0.1491 data_time: 0.0035 memory: 732 2023/03/23 15:05:23 - mmengine - INFO - Epoch(val) [20][300/753] eta: 0:01:09 time: 0.1503 data_time: 0.0040 memory: 732 2023/03/23 15:05:31 - mmengine - INFO - Epoch(val) [20][350/753] eta: 0:01:01 time: 0.1463 data_time: 0.0029 memory: 732 2023/03/23 15:05:37 - mmengine - INFO - Epoch(val) [20][400/753] eta: 0:00:52 time: 0.1321 data_time: 0.0030 memory: 732 2023/03/23 15:05:44 - mmengine - INFO - Epoch(val) [20][450/753] eta: 0:00:45 time: 0.1444 data_time: 0.0031 memory: 732 2023/03/23 15:05:52 - mmengine - INFO - Epoch(val) [20][500/753] eta: 0:00:37 time: 0.1487 data_time: 0.0031 memory: 732 2023/03/23 15:05:59 - mmengine - INFO - Epoch(val) [20][550/753] eta: 0:00:30 time: 0.1366 data_time: 0.0033 memory: 732 2023/03/23 15:06:06 - mmengine - INFO - Epoch(val) [20][600/753] eta: 0:00:22 time: 0.1554 data_time: 0.0041 memory: 732 2023/03/23 15:06:14 - mmengine - INFO - Epoch(val) [20][650/753] eta: 0:00:15 time: 0.1532 data_time: 0.0033 memory: 732 2023/03/23 15:06:22 - mmengine - INFO - Epoch(val) [20][700/753] eta: 0:00:07 time: 0.1648 data_time: 0.0057 memory: 732 2023/03/23 15:06:31 - mmengine - INFO - Epoch(val) [20][750/753] eta: 0:00:00 time: 0.1700 data_time: 0.0026 memory: 732 2023/03/23 15:17:40 - mmengine - INFO - Epoch(val) [20][753/753] NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_0.5: 0.7891 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_1.0: 0.8771 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_2.0: 0.9060 NuScenes metric/pred_instances_3d_NuScenes/car_AP_dist_4.0: 0.9176 NuScenes metric/pred_instances_3d_NuScenes/car_trans_err: 0.1758 NuScenes metric/pred_instances_3d_NuScenes/car_scale_err: 0.1513 NuScenes metric/pred_instances_3d_NuScenes/car_orient_err: 0.0859 NuScenes metric/pred_instances_3d_NuScenes/car_vel_err: 0.2681 NuScenes metric/pred_instances_3d_NuScenes/car_attr_err: 0.1892 NuScenes metric/pred_instances_3d_NuScenes/mATE: 0.2856 NuScenes metric/pred_instances_3d_NuScenes/mASE: 0.2519 NuScenes metric/pred_instances_3d_NuScenes/mAOE: 0.2906 NuScenes metric/pred_instances_3d_NuScenes/mAVE: 0.2740 NuScenes metric/pred_instances_3d_NuScenes/mAAE: 0.1850 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_0.5: 0.4021 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_1.0: 0.5971 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_2.0: 0.6776 NuScenes metric/pred_instances_3d_NuScenes/truck_AP_dist_4.0: 0.7143 NuScenes metric/pred_instances_3d_NuScenes/truck_trans_err: 0.3358 NuScenes metric/pred_instances_3d_NuScenes/truck_scale_err: 0.1837 NuScenes metric/pred_instances_3d_NuScenes/truck_orient_err: 0.0886 NuScenes metric/pred_instances_3d_NuScenes/truck_vel_err: 0.2372 NuScenes metric/pred_instances_3d_NuScenes/truck_attr_err: 0.2254 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_0.5: 0.0404 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_1.0: 0.1929 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_2.0: 0.3381 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_AP_dist_4.0: 0.4699 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_trans_err: 0.6691 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_scale_err: 0.4033 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_orient_err: 0.8369 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_vel_err: 0.1240 NuScenes metric/pred_instances_3d_NuScenes/construction_vehicle_attr_err: 0.3214 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_0.5: 0.4748 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_1.0: 0.7284 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_2.0: 0.8537 NuScenes metric/pred_instances_3d_NuScenes/bus_AP_dist_4.0: 0.8757 NuScenes metric/pred_instances_3d_NuScenes/bus_trans_err: 0.3381 NuScenes metric/pred_instances_3d_NuScenes/bus_scale_err: 0.1877 NuScenes metric/pred_instances_3d_NuScenes/bus_orient_err: 0.0553 NuScenes metric/pred_instances_3d_NuScenes/bus_vel_err: 0.4482 NuScenes metric/pred_instances_3d_NuScenes/bus_attr_err: 0.2367 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_0.5: 0.1371 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_1.0: 0.4088 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_2.0: 0.5848 NuScenes metric/pred_instances_3d_NuScenes/trailer_AP_dist_4.0: 0.6626 NuScenes metric/pred_instances_3d_NuScenes/trailer_trans_err: 0.5325 NuScenes metric/pred_instances_3d_NuScenes/trailer_scale_err: 0.2164 NuScenes metric/pred_instances_3d_NuScenes/trailer_orient_err: 0.5515 NuScenes metric/pred_instances_3d_NuScenes/trailer_vel_err: 0.1923 NuScenes metric/pred_instances_3d_NuScenes/trailer_attr_err: 0.1599 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_0.5: 0.6082 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_1.0: 0.7009 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_2.0: 0.7437 NuScenes metric/pred_instances_3d_NuScenes/barrier_AP_dist_4.0: 0.7561 NuScenes metric/pred_instances_3d_NuScenes/barrier_trans_err: 0.1960 NuScenes metric/pred_instances_3d_NuScenes/barrier_scale_err: 0.2832 NuScenes metric/pred_instances_3d_NuScenes/barrier_orient_err: 0.0574 NuScenes metric/pred_instances_3d_NuScenes/barrier_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/barrier_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_0.5: 0.6176 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_1.0: 0.7197 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_2.0: 0.7345 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_AP_dist_4.0: 0.7457 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_trans_err: 0.1883 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_scale_err: 0.2366 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_orient_err: 0.2220 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_vel_err: 0.4984 NuScenes metric/pred_instances_3d_NuScenes/motorcycle_attr_err: 0.2450 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_0.5: 0.5256 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_1.0: 0.5468 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_2.0: 0.5501 NuScenes metric/pred_instances_3d_NuScenes/bicycle_AP_dist_4.0: 0.5554 NuScenes metric/pred_instances_3d_NuScenes/bicycle_trans_err: 0.1531 NuScenes metric/pred_instances_3d_NuScenes/bicycle_scale_err: 0.2518 NuScenes metric/pred_instances_3d_NuScenes/bicycle_orient_err: 0.3419 NuScenes metric/pred_instances_3d_NuScenes/bicycle_vel_err: 0.2139 NuScenes metric/pred_instances_3d_NuScenes/bicycle_attr_err: 0.0097 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_0.5: 0.8520 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_1.0: 0.8648 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_2.0: 0.8751 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_AP_dist_4.0: 0.8866 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_trans_err: 0.1378 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_scale_err: 0.2846 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_orient_err: 0.3758 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_vel_err: 0.2098 NuScenes metric/pred_instances_3d_NuScenes/pedestrian_attr_err: 0.0930 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_0.5: 0.7272 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_1.0: 0.7388 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_2.0: 0.7567 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_AP_dist_4.0: 0.7873 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_trans_err: 0.1291 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_scale_err: 0.3201 NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_orient_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_vel_err: nan NuScenes metric/pred_instances_3d_NuScenes/traffic_cone_attr_err: nan NuScenes metric/pred_instances_3d_NuScenes/NDS: 0.6956 NuScenes metric/pred_instances_3d_NuScenes/mAP: 0.6485data_time: 0.0026 time: 0.1692