2023/03/11 06:34:00 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 295567301 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.10.0+cu111 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 v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX512 - CUDA Runtime 11.1 - 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 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, 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-variable -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=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.11.0+cu111 OpenCV: 4.5.5 MMEngine: 0.5.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None diff_rank_seed: False deterministic: False Distributed launcher: slurm Distributed training: True GPU number: 32 ------------------------------------------------------------ 2023/03/11 06:34:01 - mmengine - INFO - Config: default_scope = 'mmaction' default_hooks = dict( runtime_info=dict(type='RuntimeInfoHook'), timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=20, ignore_last=False), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=1, save_best='auto', max_keep_ckpts=2), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffers=dict(type='SyncBuffersHook')) env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) log_processor = dict(type='LogProcessor', window_size=20, by_epoch=True) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='ActionVisualizer', vis_backends=[dict(type='LocalVisBackend')]) log_level = 'INFO' load_from = None resume = False url = 'https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth' model = dict( type='FastRCNN', _scope_='mmdet', init_cfg=dict( type='Pretrained', checkpoint= 'https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth' ), backbone=dict( type='VisionTransformer', img_size=224, patch_size=16, embed_dims=1024, depth=24, num_heads=16, mlp_ratio=4, qkv_bias=True, num_frames=16, norm_cfg=dict(type='LN', eps=1e-06), drop_path_rate=0.2, use_mean_pooling=False, return_feat_map=True), roi_head=dict( type='AVARoIHead', bbox_roi_extractor=dict( type='SingleRoIExtractor3D', roi_layer_type='RoIAlign', output_size=8, with_temporal_pool=True), bbox_head=dict( type='BBoxHeadAVA', in_channels=1024, num_classes=81, multilabel=True, dropout_ratio=0.5)), data_preprocessor=dict( type='ActionDataPreprocessor', _scope_='mmaction', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], format_shape='NCTHW'), train_cfg=dict( rcnn=dict( assigner=dict( type='MaxIoUAssignerAVA', pos_iou_thr=0.9, neg_iou_thr=0.9, min_pos_iou=0.9), sampler=dict( type='RandomSampler', num=32, pos_fraction=1, neg_pos_ub=-1, add_gt_as_proposals=True), pos_weight=1.0)), test_cfg=dict(rcnn=None)) dataset_type = 'AVAKineticsDataset' data_root = 'data/ava_kinetics/rawframes' anno_root = 'data/ava_kinetics/annotations' ann_file_train = 'data/ava_kinetics/annotations/ava_train_v2.2.csv' ann_file_val = 'data/ava_kinetics/annotations/ava_val_v2.2.csv' exclude_file_train = 'data/ava_kinetics/annotations/ava_train_excluded_timestamps_v2.2.csv' exclude_file_val = 'data/ava_kinetics/annotations/ava_val_excluded_timestamps_v2.2.csv' label_file = 'data/ava_kinetics/annotations/ava_action_list_v2.2_for_activitynet_2019.pbtxt' proposal_file_train = 'data/ava_kinetics/annotations/ava_dense_proposals_train.FAIR.recall_93.9.pkl' proposal_file_val = 'data/ava_kinetics/annotations/ava_dense_proposals_val.FAIR.recall_93.9.pkl' file_client_args = dict( io_backend='petrel', path_mapping=dict({ 'data/ava_kinetics/rawframes/': 's3://openmmlab/datasets/action/ava/rawframes/' })) train_pipeline = [ dict(type='SampleAVAFrames', clip_len=16, frame_interval=4), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/ava_kinetics/rawframes/': 's3://openmmlab/datasets/action/ava/rawframes/' })), dict(type='RandomRescale', scale_range=(256, 320)), dict(type='RandomCrop', size=256), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW', collapse=True), dict(type='PackActionInputs') ] val_pipeline = [ dict( type='SampleAVAFrames', clip_len=16, frame_interval=4, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/ava_kinetics/rawframes/': 's3://openmmlab/datasets/action/ava/rawframes/' })), dict(type='Resize', scale=(-1, 256)), dict(type='FormatShape', input_format='NCTHW', collapse=True), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=4, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='AVAKineticsDataset', ann_file='data/ava_kinetics/annotations/ava_train_v2.2.csv', exclude_file= 'data/ava_kinetics/annotations/ava_train_excluded_timestamps_v2.2.csv', pipeline=[ dict(type='SampleAVAFrames', clip_len=16, frame_interval=4), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/ava_kinetics/rawframes/': 's3://openmmlab/datasets/action/ava/rawframes/' })), dict(type='RandomRescale', scale_range=(256, 320)), dict(type='RandomCrop', size=256), dict(type='Flip', flip_ratio=0.5), dict(type='FormatShape', input_format='NCTHW', collapse=True), dict(type='PackActionInputs') ], label_file= 'data/ava_kinetics/annotations/ava_action_list_v2.2_for_activitynet_2019.pbtxt', proposal_file= 'data/ava_kinetics/annotations/ava_dense_proposals_train.FAIR.recall_93.9.pkl', data_prefix=dict(img='data/ava_kinetics/rawframes'))) val_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='AVAKineticsDataset', ann_file='data/ava_kinetics/annotations/ava_val_v2.2.csv', exclude_file= 'data/ava_kinetics/annotations/ava_val_excluded_timestamps_v2.2.csv', pipeline=[ dict( type='SampleAVAFrames', clip_len=16, frame_interval=4, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/ava_kinetics/rawframes/': 's3://openmmlab/datasets/action/ava/rawframes/' })), dict(type='Resize', scale=(-1, 256)), dict(type='FormatShape', input_format='NCTHW', collapse=True), dict(type='PackActionInputs') ], label_file= 'data/ava_kinetics/annotations/ava_action_list_v2.2_for_activitynet_2019.pbtxt', proposal_file= 'data/ava_kinetics/annotations/ava_dense_proposals_val.FAIR.recall_93.9.pkl', data_prefix=dict(img='data/ava_kinetics/rawframes'), test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='AVAKineticsDataset', ann_file='data/ava_kinetics/annotations/ava_val_v2.2.csv', exclude_file= 'data/ava_kinetics/annotations/ava_val_excluded_timestamps_v2.2.csv', pipeline=[ dict( type='SampleAVAFrames', clip_len=16, frame_interval=4, test_mode=True), dict( type='RawFrameDecode', io_backend='petrel', path_mapping=dict({ 'data/ava_kinetics/rawframes/': 's3://openmmlab/datasets/action/ava/rawframes/' })), dict(type='Resize', scale=(-1, 256)), dict(type='FormatShape', input_format='NCTHW', collapse=True), dict(type='PackActionInputs') ], label_file= 'data/ava_kinetics/annotations/ava_action_list_v2.2_for_activitynet_2019.pbtxt', proposal_file= 'data/ava_kinetics/annotations/ava_dense_proposals_val.FAIR.recall_93.9.pkl', data_prefix=dict(img='data/ava_kinetics/rawframes'), test_mode=True)) val_evaluator = dict( type='AVAMetric', ann_file='data/ava_kinetics/annotations/ava_val_v2.2.csv', label_file= 'data/ava_kinetics/annotations/ava_action_list_v2.2_for_activitynet_2019.pbtxt', exclude_file= 'data/ava_kinetics/annotations/ava_val_excluded_timestamps_v2.2.csv') test_evaluator = dict( type='AVAMetric', ann_file='data/ava_kinetics/annotations/ava_val_v2.2.csv', label_file= 'data/ava_kinetics/annotations/ava_action_list_v2.2_for_activitynet_2019.pbtxt', exclude_file= 'data/ava_kinetics/annotations/ava_val_excluded_timestamps_v2.2.csv') train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=20, val_begin=1, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='LinearLR', start_factor=0.1, by_epoch=True, begin=0, end=5, convert_to_iter_based=True), dict( type='CosineAnnealingLR', T_max=15, eta_min=0, by_epoch=True, begin=5, end=20, convert_to_iter_based=True) ] optim_wrapper = dict( optimizer=dict(type='AdamW', lr=0.00025, weight_decay=0.05), constructor='LearningRateDecayOptimizerConstructor', paramwise_cfg=dict(decay_rate=0.8, decay_type='layer_wise', num_layers=24), clip_grad=dict(max_norm=40, norm_type=2)) auto_scale_lr = dict(enable=False, base_batch_size=128) launcher = 'slurm' work_dir = './work_dirs/vit-l_16x4' randomness = dict(seed=None, diff_rank_seed=False, deterministic=False) 2023/03/11 06:34:06 - mmengine - WARNING - The "model" registry in mmdet did not set import location. Fallback to call `mmdet.utils.register_all_modules` instead. 2023/03/11 06:34:10 - mmengine - WARNING - The "task util" registry in mmdet did not set import location. Fallback to call `mmdet.utils.register_all_modules` instead. 2023/03/11 06:34:11 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (VERY_LOW ) CheckpointHook -------------------- before_train_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (NORMAL ) DistSamplerSeedHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (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 (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/03/11 06:34:43 - mmengine - INFO - 284842 out of 284842 frames are valid. 2023/03/11 06:34:51 - mmengine - INFO - self.paramwise_cfg is {'decay_rate': 0.8, 'decay_type': 'layer_wise', 'num_layers': 24} 2023/03/11 06:34:51 - mmengine - INFO - Build LearningRateDecayOptimizerConstructor layer_wise 0.8 - 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.patch_embed.projection.weight as id 0 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.patch_embed.projection.bias as id 0 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.norm1.weight as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.norm1.bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.attn.q_bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.attn.v_bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.attn.qkv.weight as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.attn.proj.weight as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.attn.proj.bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.norm2.weight as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.norm2.bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.mlp.layers.0.0.weight as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.mlp.layers.0.0.bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.mlp.layers.1.weight as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.0.mlp.layers.1.bias as id 1 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.norm1.weight as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.norm1.bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.attn.q_bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.attn.v_bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.attn.qkv.weight as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.attn.proj.weight as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.attn.proj.bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.norm2.weight as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.norm2.bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.mlp.layers.0.0.weight as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.mlp.layers.0.0.bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.mlp.layers.1.weight as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.1.mlp.layers.1.bias as id 2 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.norm1.weight as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.norm1.bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.attn.q_bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.attn.v_bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.attn.qkv.weight as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.attn.proj.weight as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.attn.proj.bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.norm2.weight as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.norm2.bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.mlp.layers.0.0.weight as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.mlp.layers.0.0.bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.mlp.layers.1.weight as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.2.mlp.layers.1.bias as id 3 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.norm1.weight as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.norm1.bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.attn.q_bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.attn.v_bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.attn.qkv.weight as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.attn.proj.weight as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.attn.proj.bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.norm2.weight as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.norm2.bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.mlp.layers.0.0.weight as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.mlp.layers.0.0.bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.mlp.layers.1.weight as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.3.mlp.layers.1.bias as id 4 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.norm1.weight as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.norm1.bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.attn.q_bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.attn.v_bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.attn.qkv.weight as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.attn.proj.weight as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.attn.proj.bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.norm2.weight as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.norm2.bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.mlp.layers.0.0.weight as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.mlp.layers.0.0.bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.mlp.layers.1.weight as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.4.mlp.layers.1.bias as id 5 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.norm1.weight as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.norm1.bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.attn.q_bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.attn.v_bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.attn.qkv.weight as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.attn.proj.weight as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.attn.proj.bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.norm2.weight as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.norm2.bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.mlp.layers.0.0.weight as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.mlp.layers.0.0.bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.mlp.layers.1.weight as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.5.mlp.layers.1.bias as id 6 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.norm1.weight as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.norm1.bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.attn.q_bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.attn.v_bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.attn.qkv.weight as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.attn.proj.weight as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.attn.proj.bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.norm2.weight as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.norm2.bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.mlp.layers.0.0.weight as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.mlp.layers.0.0.bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.mlp.layers.1.weight as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.6.mlp.layers.1.bias as id 7 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.norm1.weight as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.norm1.bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.attn.q_bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.attn.v_bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.attn.qkv.weight as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.attn.proj.weight as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.attn.proj.bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.norm2.weight as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.norm2.bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.mlp.layers.0.0.weight as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.mlp.layers.0.0.bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.mlp.layers.1.weight as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.7.mlp.layers.1.bias as id 8 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.norm1.weight as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.norm1.bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.attn.q_bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.attn.v_bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.attn.qkv.weight as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.attn.proj.weight as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.attn.proj.bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.norm2.weight as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.norm2.bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.mlp.layers.0.0.weight as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.mlp.layers.0.0.bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.mlp.layers.1.weight as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.8.mlp.layers.1.bias as id 9 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.norm1.weight as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.norm1.bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.attn.q_bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.attn.v_bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.attn.qkv.weight as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.attn.proj.weight as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.attn.proj.bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.norm2.weight as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.norm2.bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.mlp.layers.0.0.weight as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.mlp.layers.0.0.bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.mlp.layers.1.weight as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.9.mlp.layers.1.bias as id 10 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.norm1.weight as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.norm1.bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.attn.q_bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.attn.v_bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.attn.qkv.weight as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.attn.proj.weight as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.attn.proj.bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.norm2.weight as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.norm2.bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.mlp.layers.0.0.weight as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.mlp.layers.0.0.bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.mlp.layers.1.weight as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.10.mlp.layers.1.bias as id 11 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.norm1.weight as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.norm1.bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.attn.q_bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.attn.v_bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.attn.qkv.weight as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.attn.proj.weight as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.attn.proj.bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.norm2.weight as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.norm2.bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.mlp.layers.0.0.weight as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.mlp.layers.0.0.bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.mlp.layers.1.weight as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.11.mlp.layers.1.bias as id 12 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.norm1.weight as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.norm1.bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.attn.q_bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.attn.v_bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.attn.qkv.weight as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.attn.proj.weight as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.attn.proj.bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.norm2.weight as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.norm2.bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.mlp.layers.0.0.weight as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.mlp.layers.0.0.bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.mlp.layers.1.weight as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.12.mlp.layers.1.bias as id 13 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.norm1.weight as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.norm1.bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.attn.q_bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.attn.v_bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.attn.qkv.weight as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.attn.proj.weight as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.attn.proj.bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.norm2.weight as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.norm2.bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.mlp.layers.0.0.weight as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.mlp.layers.0.0.bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.mlp.layers.1.weight as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.13.mlp.layers.1.bias as id 14 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.norm1.weight as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.norm1.bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.attn.q_bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.attn.v_bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.attn.qkv.weight as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.attn.proj.weight as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.attn.proj.bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.norm2.weight as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.norm2.bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.mlp.layers.0.0.weight as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.mlp.layers.0.0.bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.mlp.layers.1.weight as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.14.mlp.layers.1.bias as id 15 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.norm1.weight as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.norm1.bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.attn.q_bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.attn.v_bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.attn.qkv.weight as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.attn.proj.weight as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.attn.proj.bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.norm2.weight as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.norm2.bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.mlp.layers.0.0.weight as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.mlp.layers.0.0.bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.mlp.layers.1.weight as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.15.mlp.layers.1.bias as id 16 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.norm1.weight as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.norm1.bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.attn.q_bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.attn.v_bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.attn.qkv.weight as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.attn.proj.weight as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.attn.proj.bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.norm2.weight as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.norm2.bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.mlp.layers.0.0.weight as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.mlp.layers.0.0.bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.mlp.layers.1.weight as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.16.mlp.layers.1.bias as id 17 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.norm1.weight as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.norm1.bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.attn.q_bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.attn.v_bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.attn.qkv.weight as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.attn.proj.weight as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.attn.proj.bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.norm2.weight as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.norm2.bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.mlp.layers.0.0.weight as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.mlp.layers.0.0.bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.mlp.layers.1.weight as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.17.mlp.layers.1.bias as id 18 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.norm1.weight as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.norm1.bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.attn.q_bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.attn.v_bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.attn.qkv.weight as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.attn.proj.weight as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.attn.proj.bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.norm2.weight as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.norm2.bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.mlp.layers.0.0.weight as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.mlp.layers.0.0.bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.mlp.layers.1.weight as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.18.mlp.layers.1.bias as id 19 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.norm1.weight as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.norm1.bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.attn.q_bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.attn.v_bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.attn.qkv.weight as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.attn.proj.weight as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.attn.proj.bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.norm2.weight as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.norm2.bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.mlp.layers.0.0.weight as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.mlp.layers.0.0.bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.mlp.layers.1.weight as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.19.mlp.layers.1.bias as id 20 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.norm1.weight as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.norm1.bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.attn.q_bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.attn.v_bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.attn.qkv.weight as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.attn.proj.weight as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.attn.proj.bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.norm2.weight as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.norm2.bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.mlp.layers.0.0.weight as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.mlp.layers.0.0.bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.mlp.layers.1.weight as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.20.mlp.layers.1.bias as id 21 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.norm1.weight as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.norm1.bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.attn.q_bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.attn.v_bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.attn.qkv.weight as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.attn.proj.weight as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.attn.proj.bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.norm2.weight as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.norm2.bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.mlp.layers.0.0.weight as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.mlp.layers.0.0.bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.mlp.layers.1.weight as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.21.mlp.layers.1.bias as id 22 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.norm1.weight as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.norm1.bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.attn.q_bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.attn.v_bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.attn.qkv.weight as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.attn.proj.weight as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.attn.proj.bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.norm2.weight as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.norm2.bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.mlp.layers.0.0.weight as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.mlp.layers.0.0.bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.mlp.layers.1.weight as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.22.mlp.layers.1.bias as id 23 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.norm1.weight as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.norm1.bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.attn.q_bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.attn.v_bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.attn.qkv.weight as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.attn.proj.weight as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.attn.proj.bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.norm2.weight as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.norm2.bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.mlp.layers.0.0.weight as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.mlp.layers.0.0.bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.mlp.layers.1.weight as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.blocks.23.mlp.layers.1.bias as id 24 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.norm.weight as id 25 2023/03/11 06:34:51 - mmengine - INFO - set param backbone.norm.bias as id 25 2023/03/11 06:34:51 - mmengine - INFO - set param roi_head.bbox_head.fc_cls.weight as id 25 2023/03/11 06:34:51 - mmengine - INFO - set param roi_head.bbox_head.fc_cls.bias as id 25 2023/03/11 06:34:51 - mmengine - INFO - Param groups = { "layer_0_decay": { "param_names": [ "backbone.patch_embed.projection.weight" ], "lr_scale": 0.0037778931862957215, "lr": 9.444732965739304e-07, "weight_decay": 0.05 }, "layer_0_no_decay": { "param_names": [ "backbone.patch_embed.projection.bias" ], "lr_scale": 0.0037778931862957215, "lr": 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"backbone.blocks.21.mlp.layers.1.bias" ], "lr_scale": 0.5120000000000001, "lr": 0.00012800000000000002, "weight_decay": 0.0 }, "layer_22_decay": { "param_names": [ "backbone.blocks.21.attn.qkv.weight", "backbone.blocks.21.attn.proj.weight", "backbone.blocks.21.mlp.layers.0.0.weight", "backbone.blocks.21.mlp.layers.1.weight" ], "lr_scale": 0.5120000000000001, "lr": 0.00012800000000000002, "weight_decay": 0.05 }, "layer_23_no_decay": { "param_names": [ "backbone.blocks.22.norm1.weight", "backbone.blocks.22.norm1.bias", "backbone.blocks.22.attn.q_bias", "backbone.blocks.22.attn.v_bias", "backbone.blocks.22.attn.proj.bias", "backbone.blocks.22.norm2.weight", "backbone.blocks.22.norm2.bias", "backbone.blocks.22.mlp.layers.0.0.bias", "backbone.blocks.22.mlp.layers.1.bias" ], "lr_scale": 0.6400000000000001, "lr": 0.00016000000000000004, "weight_decay": 0.0 }, "layer_23_decay": { "param_names": [ "backbone.blocks.22.attn.qkv.weight", "backbone.blocks.22.attn.proj.weight", "backbone.blocks.22.mlp.layers.0.0.weight", "backbone.blocks.22.mlp.layers.1.weight" ], "lr_scale": 0.6400000000000001, "lr": 0.00016000000000000004, "weight_decay": 0.05 }, "layer_24_no_decay": { "param_names": [ "backbone.blocks.23.norm1.weight", "backbone.blocks.23.norm1.bias", "backbone.blocks.23.attn.q_bias", "backbone.blocks.23.attn.v_bias", "backbone.blocks.23.attn.proj.bias", "backbone.blocks.23.norm2.weight", "backbone.blocks.23.norm2.bias", "backbone.blocks.23.mlp.layers.0.0.bias", "backbone.blocks.23.mlp.layers.1.bias" ], "lr_scale": 0.8, "lr": 0.0002, "weight_decay": 0.0 }, "layer_24_decay": { "param_names": [ "backbone.blocks.23.attn.qkv.weight", "backbone.blocks.23.attn.proj.weight", "backbone.blocks.23.mlp.layers.0.0.weight", "backbone.blocks.23.mlp.layers.1.weight" ], "lr_scale": 0.8, "lr": 0.0002, "weight_decay": 0.05 }, "layer_25_no_decay": { "param_names": [ "backbone.norm.weight", "backbone.norm.bias", "roi_head.bbox_head.fc_cls.bias" ], "lr_scale": 1.0, "lr": 0.00025, "weight_decay": 0.0 }, "layer_25_decay": { "param_names": [ "roi_head.bbox_head.fc_cls.weight" ], "lr_scale": 1.0, "lr": 0.00025, "weight_decay": 0.05 } } 2023/03/11 06:34:57 - mmengine - INFO - 50252 out of 50252 frames are valid. 2023/03/11 06:35:00 - mmengine - INFO - load model from: https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth 2023/03/11 06:35:00 - mmengine - INFO - Loads checkpoint by http backend from path: https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth 2023/03/11 06:36:43 - mmengine - WARNING - The model and loaded state dict do not match exactly unexpected key in source state_dict: cls_head.fc_cls.weight, cls_head.fc_cls.bias, backbone.fc_norm.weight, backbone.fc_norm.bias missing keys in source state_dict: backbone.pos_embed, backbone.norm.weight, backbone.norm.bias, roi_head.bbox_head.fc_cls.weight, roi_head.bbox_head.fc_cls.bias Name of parameter - Initialization information backbone.patch_embed.projection.weight - torch.Size([1024, 3, 2, 16, 16]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.patch_embed.projection.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.norm1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.attn.q_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.attn.v_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.attn.qkv.weight - torch.Size([3072, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.attn.proj.weight - torch.Size([1024, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.0.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.norm1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.attn.q_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.attn.v_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.attn.qkv.weight - torch.Size([3072, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.attn.proj.weight - torch.Size([1024, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.1.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.norm1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.attn.q_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.attn.v_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.attn.qkv.weight - torch.Size([3072, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.attn.proj.weight - torch.Size([1024, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.2.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.norm1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.attn.q_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.attn.v_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.attn.qkv.weight - torch.Size([3072, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.attn.proj.weight - torch.Size([1024, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.3.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.4.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.4.norm1.bias - torch.Size([1024]): PretrainedInit: load from 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https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.4.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.4.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.4.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.4.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from 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https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.21.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.21.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.21.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.21.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.norm1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.attn.q_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.attn.v_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.attn.qkv.weight - torch.Size([3072, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.attn.proj.weight - torch.Size([1024, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.22.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.norm1.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.norm1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.attn.q_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.attn.v_bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.attn.qkv.weight - torch.Size([3072, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.attn.proj.weight - torch.Size([1024, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.attn.proj.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.norm2.weight - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.norm2.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.mlp.layers.0.0.weight - torch.Size([4096, 1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.mlp.layers.0.0.bias - torch.Size([4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.mlp.layers.1.weight - torch.Size([1024, 4096]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.blocks.23.mlp.layers.1.bias - torch.Size([1024]): PretrainedInit: load from https://download.openmmlab.com/mmaction/v1.0/recognition/videomae/vit-large-p16_videomae-k400-pre_16x4x1_kinetics-400_20221013-229dbb03.pth backbone.norm.weight - torch.Size([1024]): The value is the same before and after calling `init_weights` of FastRCNN backbone.norm.bias - torch.Size([1024]): The value is the same before and after calling `init_weights` of FastRCNN roi_head.bbox_head.fc_cls.weight - torch.Size([81, 1024]): Initialized by user-defined `init_weights` in BBoxHeadAVA roi_head.bbox_head.fc_cls.bias - torch.Size([81]): Initialized by user-defined `init_weights` in BBoxHeadAVA 2023/03/11 06:36:43 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/hukai/mmaction2/work_dirs/vit-l_16x4. 2023/03/11 06:37:24 - mmengine - INFO - Epoch(train) [1][ 20/2226] lr: 9.5899e-08 eta: 1 day, 1:16:14 time: 2.0444 data_time: 0.3460 memory: 70046 grad_norm: 1.7495 loss: 0.7372 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.1527 recall@top3: 0.1389 prec@top3: 0.1389 recall@top5: 0.1389 prec@top5: 0.0833 loss_action_cls: 0.7372 2023/03/11 06:37:41 - mmengine - INFO - Epoch(train) [1][ 40/2226] lr: 9.7426e-08 eta: 17:57:58 time: 0.8638 data_time: 0.0081 memory: 70046 grad_norm: 1.1478 loss: 0.4185 recall@thr=0.5: 0.2333 prec@thr=0.5: 0.1256 recall@top3: 0.1889 prec@top3: 0.1556 recall@top5: 0.3000 prec@top5: 0.1467 loss_action_cls: 0.4185 2023/03/11 06:38:03 - mmengine - INFO - Epoch(train) [1][ 60/2226] lr: 9.8954e-08 eta: 16:24:47 time: 1.0789 data_time: 0.0129 memory: 70046 grad_norm: 0.6216 loss: 0.2343 recall@thr=0.5: 0.2667 prec@thr=0.5: 0.5833 recall@top3: 0.4556 prec@top3: 0.4444 recall@top5: 0.7000 prec@top5: 0.4167 loss_action_cls: 0.2343 2023/03/11 06:38:22 - mmengine - INFO - Epoch(train) [1][ 80/2226] lr: 1.0048e-07 eta: 15:17:54 time: 0.9702 data_time: 0.0090 memory: 70046 grad_norm: 0.2847 loss: 0.1411 recall@thr=0.5: 0.1905 prec@thr=0.5: 0.1905 recall@top3: 0.4762 prec@top3: 0.2857 recall@top5: 0.7143 prec@top5: 0.2571 loss_action_cls: 0.1411 2023/03/11 06:38:43 - mmengine - INFO - Epoch(train) [1][ 100/2226] lr: 1.0201e-07 eta: 14:45:47 time: 1.0252 data_time: 0.0089 memory: 70046 grad_norm: 0.1718 loss: 0.1263 recall@thr=0.5: 0.1750 prec@thr=0.5: 0.3167 recall@top3: 0.6250 prec@top3: 0.5333 recall@top5: 0.8000 prec@top5: 0.4400 loss_action_cls: 0.1263 2023/03/11 06:39:01 - mmengine - INFO - Epoch(train) [1][ 120/2226] lr: 1.0354e-07 eta: 14:09:03 time: 0.9018 data_time: 0.0112 memory: 70046 grad_norm: 0.1430 loss: 0.0887 recall@thr=0.5: 0.1146 prec@thr=0.5: 0.3750 recall@top3: 0.5729 prec@top3: 0.4167 recall@top5: 0.6042 prec@top5: 0.2750 loss_action_cls: 0.0887 2023/03/11 06:39:23 - mmengine - INFO - Epoch(train) [1][ 140/2226] lr: 1.0506e-07 eta: 14:07:41 time: 1.1381 data_time: 0.0126 memory: 70046 grad_norm: 0.1325 loss: 0.1533 recall@thr=0.5: 0.2208 prec@thr=0.5: 0.3333 recall@top3: 0.4908 prec@top3: 0.5333 recall@top5: 0.6392 prec@top5: 0.4300 loss_action_cls: 0.1533 2023/03/11 06:39:42 - mmengine - INFO - Epoch(train) [1][ 160/2226] lr: 1.0659e-07 eta: 13:45:44 time: 0.9127 data_time: 0.0079 memory: 70046 grad_norm: 0.1229 loss: 0.0996 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.4524 recall@top3: 1.0000 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.2857 loss_action_cls: 0.0996 2023/03/11 06:40:05 - mmengine - INFO - Epoch(train) [1][ 180/2226] lr: 1.0812e-07 eta: 13:47:11 time: 1.1390 data_time: 0.0090 memory: 70046 grad_norm: 0.1203 loss: 0.1122 recall@thr=0.5: 0.1562 prec@thr=0.5: 0.1875 recall@top3: 0.5104 prec@top3: 0.4167 recall@top5: 0.7344 prec@top5: 0.3750 loss_action_cls: 0.1122 2023/03/11 06:40:23 - mmengine - INFO - Epoch(train) [1][ 200/2226] lr: 1.0965e-07 eta: 13:31:08 time: 0.9071 data_time: 0.0092 memory: 70046 grad_norm: 0.1202 loss: 0.0979 recall@thr=0.5: 0.0364 prec@thr=0.5: 0.1818 recall@top3: 0.7667 prec@top3: 0.5455 recall@top5: 0.8848 prec@top5: 0.4182 loss_action_cls: 0.0979 2023/03/11 06:40:47 - mmengine - INFO - Epoch(train) [1][ 220/2226] lr: 1.1117e-07 eta: 13:37:21 time: 1.1961 data_time: 0.0104 memory: 70046 grad_norm: 0.1171 loss: 0.1159 recall@thr=0.5: 0.2222 prec@thr=0.5: 0.4444 recall@top3: 0.6111 prec@top3: 0.5000 recall@top5: 0.8611 prec@top5: 0.4333 loss_action_cls: 0.1159 2023/03/11 06:41:03 - mmengine - INFO - Epoch(train) [1][ 240/2226] lr: 1.1270e-07 eta: 13:17:54 time: 0.7967 data_time: 0.0066 memory: 70046 grad_norm: 0.1201 loss: 0.1176 recall@thr=0.5: 0.0000 prec@thr=0.5: 0.0000 recall@top3: 0.5000 prec@top3: 0.3333 recall@top5: 0.6667 prec@top5: 0.2333 loss_action_cls: 0.1176 2023/03/11 06:41:25 - mmengine - INFO - Epoch(train) [1][ 260/2226] lr: 1.1423e-07 eta: 13:21:08 time: 1.1447 data_time: 0.0105 memory: 70046 grad_norm: 0.1158 loss: 0.1141 recall@thr=0.5: 0.0000 prec@thr=0.5: 0.0000 recall@top3: 0.5833 prec@top3: 0.3889 recall@top5: 0.6667 prec@top5: 0.2667 loss_action_cls: 0.1141 2023/03/11 06:41:45 - mmengine - INFO - Epoch(train) [1][ 280/2226] lr: 1.1576e-07 eta: 13:15:35 time: 0.9874 data_time: 0.0095 memory: 70046 grad_norm: 0.1708 loss: 0.0956 recall@thr=0.5: 0.4583 prec@thr=0.5: 0.5625 recall@top3: 0.8333 prec@top3: 0.6250 recall@top5: 0.9375 prec@top5: 0.4250 loss_action_cls: 0.0956 2023/03/11 06:42:05 - mmengine - INFO - Epoch(train) [1][ 300/2226] lr: 1.1728e-07 eta: 13:12:09 time: 1.0165 data_time: 0.0119 memory: 70046 grad_norm: 0.1121 loss: 0.0999 recall@thr=0.5: 0.0606 prec@thr=0.5: 0.1364 recall@top3: 0.3939 prec@top3: 0.3636 recall@top5: 0.8182 prec@top5: 0.3636 loss_action_cls: 0.0999 2023/03/11 06:42:26 - mmengine - INFO - Epoch(train) [1][ 320/2226] lr: 1.1881e-07 eta: 13:08:39 time: 1.0067 data_time: 0.0106 memory: 70046 grad_norm: 0.1218 loss: 0.1069 recall@thr=0.5: 0.4333 prec@thr=0.5: 0.8000 recall@top3: 0.7000 prec@top3: 0.5000 recall@top5: 0.7500 prec@top5: 0.3200 loss_action_cls: 0.1069 2023/03/11 06:42:48 - mmengine - INFO - Epoch(train) [1][ 340/2226] lr: 1.2034e-07 eta: 13:09:53 time: 1.1074 data_time: 0.0093 memory: 70046 grad_norm: 0.1140 loss: 0.0928 recall@thr=0.5: 0.1856 prec@thr=0.5: 0.3939 recall@top3: 0.6894 prec@top3: 0.6515 recall@top5: 0.8561 prec@top5: 0.4727 loss_action_cls: 0.0928 2023/03/11 06:43:07 - mmengine - INFO - Epoch(train) [1][ 360/2226] lr: 1.2187e-07 eta: 13:04:48 time: 0.9569 data_time: 0.0086 memory: 70046 grad_norm: 0.1167 loss: 0.0993 recall@thr=0.5: 0.5758 prec@thr=0.5: 0.8030 recall@top3: 0.6894 prec@top3: 0.6667 recall@top5: 0.9545 prec@top5: 0.5636 loss_action_cls: 0.0993 2023/03/11 06:43:28 - mmengine - INFO - Epoch(train) [1][ 380/2226] lr: 1.2340e-07 eta: 13:03:27 time: 1.0407 data_time: 0.0084 memory: 70046 grad_norm: 0.1241 loss: 0.0832 recall@thr=0.5: 0.4286 prec@thr=0.5: 0.5714 recall@top3: 0.9048 prec@top3: 0.6190 recall@top5: 0.9048 prec@top5: 0.3714 loss_action_cls: 0.0832 2023/03/11 06:43:47 - mmengine - INFO - Epoch(train) [1][ 400/2226] lr: 1.2492e-07 eta: 12:59:42 time: 0.9727 data_time: 0.0081 memory: 70046 grad_norm: 0.1162 loss: 0.1026 recall@thr=0.5: 0.2500 prec@thr=0.5: 0.3333 recall@top3: 0.6667 prec@top3: 0.3889 recall@top5: 0.6667 prec@top5: 0.2333 loss_action_cls: 0.1026 2023/03/11 06:44:06 - mmengine - INFO - Epoch(train) [1][ 420/2226] lr: 1.2645e-07 eta: 12:54:42 time: 0.9276 data_time: 0.0099 memory: 70046 grad_norm: 0.1203 loss: 0.0963 recall@thr=0.5: 0.4000 prec@thr=0.5: 0.4000 recall@top3: 0.8000 prec@top3: 0.5667 recall@top5: 0.8333 prec@top5: 0.3600 loss_action_cls: 0.0963 2023/03/11 06:44:30 - mmengine - INFO - Epoch(train) [1][ 440/2226] lr: 1.2798e-07 eta: 12:59:05 time: 1.1957 data_time: 0.0105 memory: 70046 grad_norm: 0.1120 loss: 0.1123 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.8074 recall@top3: 0.8148 prec@top3: 0.6667 recall@top5: 0.8889 prec@top5: 0.4444 loss_action_cls: 0.1123 2023/03/11 06:44:50 - mmengine - INFO - Epoch(train) [1][ 460/2226] lr: 1.2951e-07 eta: 12:57:49 time: 1.0322 data_time: 0.0093 memory: 70046 grad_norm: 0.1149 loss: 0.0760 recall@thr=0.5: 0.4286 prec@thr=0.5: 0.5714 recall@top3: 0.7857 prec@top3: 0.4286 recall@top5: 0.9286 prec@top5: 0.3143 loss_action_cls: 0.0760 2023/03/11 06:45:08 - mmengine - INFO - Epoch(train) [1][ 480/2226] lr: 1.3103e-07 eta: 12:52:01 time: 0.8807 data_time: 0.0097 memory: 70046 grad_norm: 0.1138 loss: 0.1057 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.4500 recall@top3: 0.7333 prec@top3: 0.5667 recall@top5: 0.8167 prec@top5: 0.3800 loss_action_cls: 0.1057 2023/03/11 06:45:30 - mmengine - INFO - Epoch(train) [1][ 500/2226] lr: 1.3256e-07 eta: 12:53:40 time: 1.1204 data_time: 0.0108 memory: 70046 grad_norm: 0.1098 loss: 0.1151 recall@thr=0.5: 0.4048 prec@thr=0.5: 0.5238 recall@top3: 0.7202 prec@top3: 0.5000 recall@top5: 0.7917 prec@top5: 0.3286 loss_action_cls: 0.1151 2023/03/11 06:45:52 - mmengine - INFO - Epoch(train) [1][ 520/2226] lr: 1.3409e-07 eta: 12:53:39 time: 1.0662 data_time: 0.0099 memory: 70046 grad_norm: 0.1127 loss: 0.1175 recall@thr=0.5: 0.3681 prec@thr=0.5: 0.7917 recall@top3: 0.6389 prec@top3: 0.6111 recall@top5: 0.7708 prec@top5: 0.4500 loss_action_cls: 0.1175 2023/03/11 06:46:13 - mmengine - INFO - Epoch(train) [1][ 540/2226] lr: 1.3562e-07 eta: 12:53:08 time: 1.0491 data_time: 0.0073 memory: 70046 grad_norm: 0.1149 loss: 0.1078 recall@thr=0.5: 0.4861 prec@thr=0.5: 0.5625 recall@top3: 0.5972 prec@top3: 0.5278 recall@top5: 0.6736 prec@top5: 0.3667 loss_action_cls: 0.1078 2023/03/11 06:46:31 - mmengine - INFO - Epoch(train) [1][ 560/2226] lr: 1.3714e-07 eta: 12:49:32 time: 0.9303 data_time: 0.0083 memory: 70046 grad_norm: 0.1343 loss: 0.1013 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.6528 recall@top3: 0.8194 prec@top3: 0.5278 recall@top5: 0.8194 prec@top5: 0.3167 loss_action_cls: 0.1013 2023/03/11 06:46:54 - mmengine - INFO - Epoch(train) [1][ 580/2226] lr: 1.3867e-07 eta: 12:51:21 time: 1.1360 data_time: 0.0107 memory: 70046 grad_norm: 0.1128 loss: 0.0963 recall@thr=0.5: 0.3590 prec@thr=0.5: 0.6154 recall@top3: 0.6026 prec@top3: 0.6410 recall@top5: 0.7179 prec@top5: 0.4615 loss_action_cls: 0.0963 2023/03/11 06:47:14 - mmengine - INFO - Epoch(train) [1][ 600/2226] lr: 1.4020e-07 eta: 12:49:12 time: 0.9798 data_time: 0.0096 memory: 70046 grad_norm: 0.1098 loss: 0.1025 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.5000 recall@top3: 0.4833 prec@top3: 0.4000 recall@top5: 0.8667 prec@top5: 0.4400 loss_action_cls: 0.1025 2023/03/11 06:47:35 - mmengine - INFO - Epoch(train) [1][ 620/2226] lr: 1.4173e-07 eta: 12:49:29 time: 1.0772 data_time: 0.0088 memory: 70046 grad_norm: 0.1124 loss: 0.0900 recall@thr=0.5: 0.5444 prec@thr=0.5: 0.6111 recall@top3: 0.7528 prec@top3: 0.4722 recall@top5: 0.8833 prec@top5: 0.3667 loss_action_cls: 0.0900 2023/03/11 06:47:54 - mmengine - INFO - Epoch(train) [1][ 640/2226] lr: 1.4325e-07 eta: 12:47:06 time: 0.9634 data_time: 0.0089 memory: 70046 grad_norm: 0.1175 loss: 0.0915 recall@thr=0.5: 0.4444 prec@thr=0.5: 0.3333 recall@top3: 0.5185 prec@top3: 0.2963 recall@top5: 0.7407 prec@top5: 0.2667 loss_action_cls: 0.0915 2023/03/11 06:48:17 - mmengine - INFO - Epoch(train) [1][ 660/2226] lr: 1.4478e-07 eta: 12:48:10 time: 1.1123 data_time: 0.0106 memory: 70046 grad_norm: 0.1209 loss: 0.0970 recall@thr=0.5: 0.2143 prec@thr=0.5: 0.2143 recall@top3: 0.7143 prec@top3: 0.4762 recall@top5: 0.9048 prec@top5: 0.4000 loss_action_cls: 0.0970 2023/03/11 06:48:37 - mmengine - INFO - Epoch(train) [1][ 680/2226] lr: 1.4631e-07 eta: 12:47:24 time: 1.0316 data_time: 0.0088 memory: 70046 grad_norm: 0.1158 loss: 0.0939 recall@thr=0.5: 0.4762 prec@thr=0.5: 0.3333 recall@top3: 0.6905 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0939 2023/03/11 06:48:56 - mmengine - INFO - Epoch(train) [1][ 700/2226] lr: 1.4784e-07 eta: 12:44:35 time: 0.9326 data_time: 0.0093 memory: 70046 grad_norm: 0.1135 loss: 0.1098 recall@thr=0.5: 0.3939 prec@thr=0.5: 0.4091 recall@top3: 0.6288 prec@top3: 0.3939 recall@top5: 0.7500 prec@top5: 0.3091 loss_action_cls: 0.1098 2023/03/11 06:49:15 - mmengine - INFO - Epoch(train) [1][ 720/2226] lr: 1.4936e-07 eta: 12:41:55 time: 0.9320 data_time: 0.0109 memory: 70046 grad_norm: 0.1231 loss: 0.1100 recall@thr=0.5: 0.1111 prec@thr=0.5: 0.1667 recall@top3: 0.5000 prec@top3: 0.2593 recall@top5: 0.5556 prec@top5: 0.1778 loss_action_cls: 0.1100 2023/03/11 06:49:38 - mmengine - INFO - Epoch(train) [1][ 740/2226] lr: 1.5089e-07 eta: 12:44:25 time: 1.1884 data_time: 0.0100 memory: 70046 grad_norm: 0.1155 loss: 0.0855 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.7222 recall@top3: 0.5972 prec@top3: 0.4722 recall@top5: 0.9444 prec@top5: 0.4500 loss_action_cls: 0.0855 2023/03/11 06:50:02 - mmengine - INFO - Epoch(train) [1][ 760/2226] lr: 1.5242e-07 eta: 12:46:31 time: 1.1749 data_time: 0.0110 memory: 70046 grad_norm: 0.1294 loss: 0.0884 recall@thr=0.5: 0.2500 prec@thr=0.5: 0.3333 recall@top3: 0.5000 prec@top3: 0.2778 recall@top5: 0.7222 prec@top5: 0.3000 loss_action_cls: 0.0884 2023/03/11 06:50:22 - mmengine - INFO - Epoch(train) [1][ 780/2226] lr: 1.5395e-07 eta: 12:45:32 time: 1.0179 data_time: 0.0084 memory: 70046 grad_norm: 0.1202 loss: 0.1070 recall@thr=0.5: 0.5233 prec@thr=0.5: 0.7667 recall@top3: 0.6933 prec@top3: 0.7667 recall@top5: 0.7883 prec@top5: 0.5200 loss_action_cls: 0.1070 2023/03/11 06:50:41 - mmengine - INFO - Epoch(train) [1][ 800/2226] lr: 1.5547e-07 eta: 12:43:05 time: 0.9341 data_time: 0.0098 memory: 70046 grad_norm: 0.1289 loss: 0.1020 recall@thr=0.5: 0.5600 prec@thr=0.5: 0.6917 recall@top3: 0.6267 prec@top3: 0.5667 recall@top5: 0.7800 prec@top5: 0.4400 loss_action_cls: 0.1020 2023/03/11 06:51:02 - mmengine - INFO - Epoch(train) [1][ 820/2226] lr: 1.5700e-07 eta: 12:43:14 time: 1.0760 data_time: 0.0125 memory: 70046 grad_norm: 0.1196 loss: 0.1088 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.8889 recall@top3: 0.7222 prec@top3: 0.7037 recall@top5: 0.8796 prec@top5: 0.5333 loss_action_cls: 0.1088 2023/03/11 06:51:24 - mmengine - INFO - Epoch(train) [1][ 840/2226] lr: 1.5853e-07 eta: 12:43:05 time: 1.0587 data_time: 0.0103 memory: 70046 grad_norm: 0.1162 loss: 0.0807 recall@thr=0.5: 0.4222 prec@thr=0.5: 0.7778 recall@top3: 0.6222 prec@top3: 0.5926 recall@top5: 0.9778 prec@top5: 0.5333 loss_action_cls: 0.0807 2023/03/11 06:51:44 - mmengine - INFO - Epoch(train) [1][ 860/2226] lr: 1.6006e-07 eta: 12:42:19 time: 1.0236 data_time: 0.0095 memory: 70046 grad_norm: 0.1207 loss: 0.0949 recall@thr=0.5: 0.3083 prec@thr=0.5: 0.5500 recall@top3: 0.7917 prec@top3: 0.5667 recall@top5: 0.7917 prec@top5: 0.3400 loss_action_cls: 0.0949 2023/03/11 06:52:06 - mmengine - INFO - Epoch(train) [1][ 880/2226] lr: 1.6158e-07 eta: 12:42:59 time: 1.1090 data_time: 0.0089 memory: 70046 grad_norm: 0.1250 loss: 0.0952 recall@thr=0.5: 0.4792 prec@thr=0.5: 0.4792 recall@top3: 0.8542 prec@top3: 0.6250 recall@top5: 0.9167 prec@top5: 0.4000 loss_action_cls: 0.0952 2023/03/11 06:52:29 - mmengine - INFO - Epoch(train) [1][ 900/2226] lr: 1.6311e-07 eta: 12:43:55 time: 1.1289 data_time: 0.0091 memory: 70046 grad_norm: 0.1169 loss: 0.0912 recall@thr=0.5: 0.3636 prec@thr=0.5: 0.4545 recall@top3: 0.6667 prec@top3: 0.4242 recall@top5: 0.9545 prec@top5: 0.4000 loss_action_cls: 0.0912 2023/03/11 06:52:50 - mmengine - INFO - Epoch(train) [1][ 920/2226] lr: 1.6464e-07 eta: 12:43:27 time: 1.0433 data_time: 0.0089 memory: 70046 grad_norm: 0.1217 loss: 0.1012 recall@thr=0.5: 0.4000 prec@thr=0.5: 0.6167 recall@top3: 0.7167 prec@top3: 0.5000 recall@top5: 0.9333 prec@top5: 0.4000 loss_action_cls: 0.1012 2023/03/11 06:53:07 - mmengine - INFO - Epoch(train) [1][ 940/2226] lr: 1.6617e-07 eta: 12:40:04 time: 0.8542 data_time: 0.0103 memory: 70046 grad_norm: 0.1256 loss: 0.1111 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.8262 recall@top3: 0.7500 prec@top3: 0.6429 recall@top5: 0.8988 prec@top5: 0.5000 loss_action_cls: 0.1111 2023/03/11 06:53:26 - mmengine - INFO - Epoch(train) [1][ 960/2226] lr: 1.6770e-07 eta: 12:38:41 time: 0.9783 data_time: 0.0117 memory: 70046 grad_norm: 0.1291 loss: 0.1014 recall@thr=0.5: 0.5111 prec@thr=0.5: 0.5556 recall@top3: 0.6889 prec@top3: 0.5556 recall@top5: 0.8444 prec@top5: 0.4444 loss_action_cls: 0.1014 2023/03/11 06:53:47 - mmengine - INFO - Epoch(train) [1][ 980/2226] lr: 1.6922e-07 eta: 12:38:21 time: 1.0466 data_time: 0.0121 memory: 70046 grad_norm: 0.1258 loss: 0.0952 recall@thr=0.5: 0.6833 prec@thr=0.5: 0.7333 recall@top3: 0.7667 prec@top3: 0.6333 recall@top5: 0.9000 prec@top5: 0.4600 loss_action_cls: 0.0952 2023/03/11 06:54:10 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 06:54:10 - mmengine - INFO - Epoch(train) [1][1000/2226] lr: 1.7075e-07 eta: 12:39:09 time: 1.1241 data_time: 0.0112 memory: 70046 grad_norm: 0.1178 loss: 0.1057 recall@thr=0.5: 0.3889 prec@thr=0.5: 0.4861 recall@top3: 0.4861 prec@top3: 0.4722 recall@top5: 0.9028 prec@top5: 0.4500 loss_action_cls: 0.1057 2023/03/11 06:54:28 - mmengine - INFO - Epoch(train) [1][1020/2226] lr: 1.7228e-07 eta: 12:36:55 time: 0.9136 data_time: 0.0092 memory: 70046 grad_norm: 0.1205 loss: 0.0839 recall@thr=0.5: 0.5455 prec@thr=0.5: 0.6061 recall@top3: 0.7424 prec@top3: 0.5758 recall@top5: 0.8333 prec@top5: 0.3818 loss_action_cls: 0.0839 2023/03/11 06:54:48 - mmengine - INFO - Epoch(train) [1][1040/2226] lr: 1.7381e-07 eta: 12:35:45 time: 0.9853 data_time: 0.0106 memory: 70046 grad_norm: 0.1203 loss: 0.1039 recall@thr=0.5: 0.3333 prec@thr=0.5: 0.2778 recall@top3: 0.7407 prec@top3: 0.5185 recall@top5: 0.8519 prec@top5: 0.3778 loss_action_cls: 0.1039 2023/03/11 06:55:08 - mmengine - INFO - Epoch(train) [1][1060/2226] lr: 1.7533e-07 eta: 12:34:49 time: 0.9997 data_time: 0.0102 memory: 70046 grad_norm: 0.1288 loss: 0.1025 recall@thr=0.5: 0.4722 prec@thr=0.5: 0.6250 recall@top3: 0.6319 prec@top3: 0.5556 recall@top5: 0.8333 prec@top5: 0.4667 loss_action_cls: 0.1025 2023/03/11 06:55:31 - mmengine - INFO - Epoch(train) [1][1080/2226] lr: 1.7686e-07 eta: 12:35:58 time: 1.1539 data_time: 0.0101 memory: 70046 grad_norm: 0.1193 loss: 0.0806 recall@thr=0.5: 0.5500 prec@thr=0.5: 0.7333 recall@top3: 0.6167 prec@top3: 0.5667 recall@top5: 0.8500 prec@top5: 0.4600 loss_action_cls: 0.0806 2023/03/11 06:55:50 - mmengine - INFO - Epoch(train) [1][1100/2226] lr: 1.7839e-07 eta: 12:34:29 time: 0.9579 data_time: 0.0091 memory: 70046 grad_norm: 0.1187 loss: 0.0891 recall@thr=0.5: 0.5167 prec@thr=0.5: 0.7333 recall@top3: 0.6167 prec@top3: 0.4000 recall@top5: 0.6833 prec@top5: 0.2800 loss_action_cls: 0.0891 2023/03/11 06:56:09 - mmengine - INFO - Epoch(train) [1][1120/2226] lr: 1.7992e-07 eta: 12:33:14 time: 0.9729 data_time: 0.0102 memory: 70046 grad_norm: 0.1266 loss: 0.0748 recall@thr=0.5: 0.6296 prec@thr=0.5: 0.7778 recall@top3: 0.9630 prec@top3: 0.5185 recall@top5: 1.0000 prec@top5: 0.3333 loss_action_cls: 0.0748 2023/03/11 06:56:31 - mmengine - INFO - Epoch(train) [1][1140/2226] lr: 1.8144e-07 eta: 12:33:20 time: 1.0762 data_time: 0.0127 memory: 70046 grad_norm: 0.1267 loss: 0.1004 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.4000 recall@top3: 0.9333 prec@top3: 0.4667 recall@top5: 1.0000 prec@top5: 0.3200 loss_action_cls: 0.1004 2023/03/11 06:56:52 - mmengine - INFO - Epoch(train) [1][1160/2226] lr: 1.8297e-07 eta: 12:33:27 time: 1.0803 data_time: 0.0103 memory: 70046 grad_norm: 0.1264 loss: 0.0814 recall@thr=0.5: 0.4861 prec@thr=0.5: 0.5278 recall@top3: 0.7778 prec@top3: 0.5556 recall@top5: 0.9167 prec@top5: 0.4000 loss_action_cls: 0.0814 2023/03/11 06:57:11 - mmengine - INFO - Epoch(train) [1][1180/2226] lr: 1.8450e-07 eta: 12:31:44 time: 0.9308 data_time: 0.0098 memory: 70046 grad_norm: 0.1256 loss: 0.0919 recall@thr=0.5: 0.3515 prec@thr=0.5: 0.5455 recall@top3: 0.6015 prec@top3: 0.5152 recall@top5: 0.6909 prec@top5: 0.3818 loss_action_cls: 0.0919 2023/03/11 06:57:32 - mmengine - INFO - Epoch(train) [1][1200/2226] lr: 1.8603e-07 eta: 12:31:22 time: 1.0392 data_time: 0.0107 memory: 70046 grad_norm: 0.1187 loss: 0.0813 recall@thr=0.5: 0.7000 prec@thr=0.5: 0.8000 recall@top3: 1.0000 prec@top3: 0.6000 recall@top5: 1.0000 prec@top5: 0.3600 loss_action_cls: 0.0813 2023/03/11 06:57:54 - mmengine - INFO - Epoch(train) [1][1220/2226] lr: 1.8755e-07 eta: 12:31:35 time: 1.0883 data_time: 0.0097 memory: 70046 grad_norm: 0.1241 loss: 0.0965 recall@thr=0.5: 0.7381 prec@thr=0.5: 0.8571 recall@top3: 0.7857 prec@top3: 0.7619 recall@top5: 0.9643 prec@top5: 0.5143 loss_action_cls: 0.0965 2023/03/11 06:58:15 - mmengine - INFO - Epoch(train) [1][1240/2226] lr: 1.8908e-07 eta: 12:31:33 time: 1.0685 data_time: 0.0097 memory: 70046 grad_norm: 0.1219 loss: 0.0690 recall@thr=0.5: 0.7143 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.5714 recall@top5: 1.0000 prec@top5: 0.3429 loss_action_cls: 0.0690 2023/03/11 06:58:36 - mmengine - INFO - Epoch(train) [1][1260/2226] lr: 1.9061e-07 eta: 12:31:00 time: 1.0242 data_time: 0.0072 memory: 70046 grad_norm: 0.1277 loss: 0.0819 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.8485 recall@top3: 0.8182 prec@top3: 0.7879 recall@top5: 0.8788 prec@top5: 0.5091 loss_action_cls: 0.0819 2023/03/11 06:58:53 - mmengine - INFO - Epoch(train) [1][1280/2226] lr: 1.9214e-07 eta: 12:28:59 time: 0.8924 data_time: 0.0082 memory: 70046 grad_norm: 0.1244 loss: 0.0874 recall@thr=0.5: 0.6500 prec@thr=0.5: 0.6500 recall@top3: 0.9250 prec@top3: 0.5667 recall@top5: 0.9250 prec@top5: 0.3400 loss_action_cls: 0.0874 2023/03/11 06:59:16 - mmengine - INFO - Epoch(train) [1][1300/2226] lr: 1.9366e-07 eta: 12:29:39 time: 1.1316 data_time: 0.0107 memory: 70046 grad_norm: 0.1240 loss: 0.1060 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.5556 recall@top3: 0.7778 prec@top3: 0.4815 recall@top5: 0.7778 prec@top5: 0.2889 loss_action_cls: 0.1060 2023/03/11 06:59:36 - mmengine - INFO - Epoch(train) [1][1320/2226] lr: 1.9519e-07 eta: 12:28:59 time: 1.0104 data_time: 0.0098 memory: 70046 grad_norm: 0.1249 loss: 0.0720 recall@thr=0.5: 0.7513 prec@thr=0.5: 0.7821 recall@top3: 0.7718 prec@top3: 0.7436 recall@top5: 0.8731 prec@top5: 0.5231 loss_action_cls: 0.0720 2023/03/11 06:59:57 - mmengine - INFO - Epoch(train) [1][1340/2226] lr: 1.9672e-07 eta: 12:28:29 time: 1.0264 data_time: 0.0094 memory: 70046 grad_norm: 0.1248 loss: 0.0849 recall@thr=0.5: 0.4848 prec@thr=0.5: 0.5758 recall@top3: 0.6515 prec@top3: 0.4848 recall@top5: 0.8258 prec@top5: 0.3636 loss_action_cls: 0.0849 2023/03/11 07:00:17 - mmengine - INFO - Epoch(train) [1][1360/2226] lr: 1.9825e-07 eta: 12:28:04 time: 1.0339 data_time: 0.0096 memory: 70046 grad_norm: 0.1297 loss: 0.0626 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.8889 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 0.9722 prec@top5: 0.5111 loss_action_cls: 0.0626 2023/03/11 07:00:38 - mmengine - INFO - Epoch(train) [1][1380/2226] lr: 1.9977e-07 eta: 12:27:45 time: 1.0421 data_time: 0.0096 memory: 70046 grad_norm: 0.1272 loss: 0.0922 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.5952 recall@top3: 0.7143 prec@top3: 0.5000 recall@top5: 0.8571 prec@top5: 0.3857 loss_action_cls: 0.0922 2023/03/11 07:00:58 - mmengine - INFO - Epoch(train) [1][1400/2226] lr: 2.0130e-07 eta: 12:26:57 time: 0.9968 data_time: 0.0108 memory: 70046 grad_norm: 0.1302 loss: 0.0882 recall@thr=0.5: 0.7059 prec@thr=0.5: 0.7353 recall@top3: 0.9118 prec@top3: 0.5686 recall@top5: 0.9706 prec@top5: 0.3647 loss_action_cls: 0.0882 2023/03/11 07:01:19 - mmengine - INFO - Epoch(train) [1][1420/2226] lr: 2.0283e-07 eta: 12:26:42 time: 1.0483 data_time: 0.0105 memory: 70046 grad_norm: 0.1283 loss: 0.0902 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.7467 recall@top3: 0.8250 prec@top3: 0.7667 recall@top5: 0.8500 prec@top5: 0.4800 loss_action_cls: 0.0902 2023/03/11 07:01:38 - mmengine - INFO - Epoch(train) [1][1440/2226] lr: 2.0436e-07 eta: 12:25:23 time: 0.9425 data_time: 0.0083 memory: 70046 grad_norm: 0.1319 loss: 0.0865 recall@thr=0.5: 0.5897 prec@thr=0.5: 0.6154 recall@top3: 0.6282 prec@top3: 0.5641 recall@top5: 0.9808 prec@top5: 0.4769 loss_action_cls: 0.0865 2023/03/11 07:01:56 - mmengine - INFO - Epoch(train) [1][1460/2226] lr: 2.0588e-07 eta: 12:23:38 time: 0.8956 data_time: 0.0107 memory: 70046 grad_norm: 0.1301 loss: 0.0734 recall@thr=0.5: 0.4444 prec@thr=0.5: 0.4444 recall@top3: 0.6944 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3500 loss_action_cls: 0.0734 2023/03/11 07:02:18 - mmengine - INFO - Epoch(train) [1][1480/2226] lr: 2.0741e-07 eta: 12:23:56 time: 1.1024 data_time: 0.0113 memory: 70046 grad_norm: 0.1231 loss: 0.0734 recall@thr=0.5: 0.3000 prec@thr=0.5: 0.2500 recall@top3: 0.6000 prec@top3: 0.5000 recall@top5: 0.9000 prec@top5: 0.3800 loss_action_cls: 0.0734 2023/03/11 07:02:39 - mmengine - INFO - Epoch(train) [1][1500/2226] lr: 2.0894e-07 eta: 12:23:56 time: 1.0720 data_time: 0.0095 memory: 70046 grad_norm: 0.1303 loss: 0.1038 recall@thr=0.5: 0.5303 prec@thr=0.5: 0.6515 recall@top3: 0.7121 prec@top3: 0.5758 recall@top5: 0.8636 prec@top5: 0.4364 loss_action_cls: 0.1038 2023/03/11 07:02:59 - mmengine - INFO - Epoch(train) [1][1520/2226] lr: 2.1047e-07 eta: 12:22:54 time: 0.9657 data_time: 0.0099 memory: 70046 grad_norm: 0.1287 loss: 0.0928 recall@thr=0.5: 0.6806 prec@thr=0.5: 0.6528 recall@top3: 0.7500 prec@top3: 0.5833 recall@top5: 0.9583 prec@top5: 0.4500 loss_action_cls: 0.0928 2023/03/11 07:03:21 - mmengine - INFO - Epoch(train) [1][1540/2226] lr: 2.1200e-07 eta: 12:23:19 time: 1.1177 data_time: 0.0108 memory: 70046 grad_norm: 0.1266 loss: 0.1087 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.5556 recall@top3: 0.8333 prec@top3: 0.3333 recall@top5: 0.8889 prec@top5: 0.2222 loss_action_cls: 0.1087 2023/03/11 07:03:40 - mmengine - INFO - Epoch(train) [1][1560/2226] lr: 2.1352e-07 eta: 12:21:56 time: 0.9252 data_time: 0.0082 memory: 70046 grad_norm: 0.1284 loss: 0.0777 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.6250 recall@top3: 0.7500 prec@top3: 0.3750 recall@top5: 0.8750 prec@top5: 0.2750 loss_action_cls: 0.0777 2023/03/11 07:04:00 - mmengine - INFO - Epoch(train) [1][1580/2226] lr: 2.1505e-07 eta: 12:21:25 time: 1.0175 data_time: 0.0093 memory: 70046 grad_norm: 0.1340 loss: 0.0671 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.7667 recall@top3: 1.0000 prec@top3: 0.7333 recall@top5: 1.0000 prec@top5: 0.4400 loss_action_cls: 0.0671 2023/03/11 07:04:22 - mmengine - INFO - Epoch(train) [1][1600/2226] lr: 2.1658e-07 eta: 12:21:31 time: 1.0867 data_time: 0.0096 memory: 70046 grad_norm: 0.1246 loss: 0.1047 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.5278 recall@top3: 0.7222 prec@top3: 0.5000 recall@top5: 0.9444 prec@top5: 0.4000 loss_action_cls: 0.1047 2023/03/11 07:04:41 - mmengine - INFO - Epoch(train) [1][1620/2226] lr: 2.1811e-07 eta: 12:20:34 time: 0.9664 data_time: 0.0093 memory: 70046 grad_norm: 0.1294 loss: 0.0707 recall@thr=0.5: 0.3667 prec@thr=0.5: 0.4000 recall@top3: 0.7333 prec@top3: 0.4333 recall@top5: 0.9000 prec@top5: 0.3400 loss_action_cls: 0.0707 2023/03/11 07:05:01 - mmengine - INFO - Epoch(train) [1][1640/2226] lr: 2.1963e-07 eta: 12:20:06 time: 1.0221 data_time: 0.0087 memory: 70046 grad_norm: 0.1299 loss: 0.0853 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.6000 recall@top3: 0.6000 prec@top3: 0.2667 recall@top5: 0.6000 prec@top5: 0.1600 loss_action_cls: 0.0853 2023/03/11 07:05:20 - mmengine - INFO - Epoch(train) [1][1660/2226] lr: 2.2116e-07 eta: 12:18:49 time: 0.9266 data_time: 0.0111 memory: 70046 grad_norm: 0.1300 loss: 0.0790 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.8125 recall@top3: 0.6042 prec@top3: 0.5417 recall@top5: 0.8750 prec@top5: 0.4750 loss_action_cls: 0.0790 2023/03/11 07:05:44 - mmengine - INFO - Epoch(train) [1][1680/2226] lr: 2.2269e-07 eta: 12:19:45 time: 1.1854 data_time: 0.0120 memory: 70046 grad_norm: 0.1323 loss: 0.0708 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7778 recall@top3: 0.8333 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3000 loss_action_cls: 0.0708 2023/03/11 07:06:04 - mmengine - INFO - Epoch(train) [1][1700/2226] lr: 2.2422e-07 eta: 12:19:12 time: 1.0116 data_time: 0.0115 memory: 70046 grad_norm: 0.1270 loss: 0.0862 recall@thr=0.5: 0.6061 prec@thr=0.5: 0.7121 recall@top3: 0.7348 prec@top3: 0.6364 recall@top5: 0.8864 prec@top5: 0.4909 loss_action_cls: 0.0862 2023/03/11 07:06:23 - mmengine - INFO - Epoch(train) [1][1720/2226] lr: 2.2574e-07 eta: 12:18:13 time: 0.9585 data_time: 0.0086 memory: 70046 grad_norm: 0.1289 loss: 0.0734 recall@thr=0.5: 0.8611 prec@thr=0.5: 1.0000 recall@top3: 0.9444 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4333 loss_action_cls: 0.0734 2023/03/11 07:06:45 - mmengine - INFO - Epoch(train) [1][1740/2226] lr: 2.2727e-07 eta: 12:18:27 time: 1.1050 data_time: 0.0101 memory: 70046 grad_norm: 0.1425 loss: 0.0820 recall@thr=0.5: 0.4848 prec@thr=0.5: 0.5455 recall@top3: 0.6364 prec@top3: 0.6061 recall@top5: 0.7273 prec@top5: 0.4182 loss_action_cls: 0.0820 2023/03/11 07:07:03 - mmengine - INFO - Epoch(train) [1][1760/2226] lr: 2.2880e-07 eta: 12:17:07 time: 0.9143 data_time: 0.0078 memory: 70046 grad_norm: 0.1297 loss: 0.0736 recall@thr=0.5: 0.5389 prec@thr=0.5: 0.6778 recall@top3: 0.7722 prec@top3: 0.6444 recall@top5: 0.9333 prec@top5: 0.4933 loss_action_cls: 0.0736 2023/03/11 07:07:23 - mmengine - INFO - Epoch(train) [1][1780/2226] lr: 2.3033e-07 eta: 12:16:26 time: 0.9929 data_time: 0.0098 memory: 70046 grad_norm: 0.1251 loss: 0.0762 recall@thr=0.5: 0.7357 prec@thr=0.5: 0.7500 recall@top3: 0.7524 prec@top3: 0.8095 recall@top5: 0.9643 prec@top5: 0.6429 loss_action_cls: 0.0762 2023/03/11 07:07:44 - mmengine - INFO - Epoch(train) [1][1800/2226] lr: 2.3185e-07 eta: 12:15:55 time: 1.0107 data_time: 0.0105 memory: 70046 grad_norm: 0.1277 loss: 0.0856 recall@thr=0.5: 0.3750 prec@thr=0.5: 0.5000 recall@top3: 0.7083 prec@top3: 0.6250 recall@top5: 0.9167 prec@top5: 0.5000 loss_action_cls: 0.0856 2023/03/11 07:08:05 - mmengine - INFO - Epoch(train) [1][1820/2226] lr: 2.3338e-07 eta: 12:15:46 time: 1.0587 data_time: 0.0088 memory: 70046 grad_norm: 0.1349 loss: 0.0905 recall@thr=0.5: 0.2778 prec@thr=0.5: 0.4583 recall@top3: 0.5000 prec@top3: 0.3889 recall@top5: 0.8472 prec@top5: 0.3833 loss_action_cls: 0.0905 2023/03/11 07:08:25 - mmengine - INFO - Epoch(train) [1][1840/2226] lr: 2.3491e-07 eta: 12:15:05 time: 0.9909 data_time: 0.0087 memory: 70046 grad_norm: 0.1224 loss: 0.0798 recall@thr=0.5: 0.4444 prec@thr=0.5: 0.6250 recall@top3: 0.8056 prec@top3: 0.6944 recall@top5: 0.8889 prec@top5: 0.4667 loss_action_cls: 0.0798 2023/03/11 07:08:43 - mmengine - INFO - Epoch(train) [1][1860/2226] lr: 2.3644e-07 eta: 12:13:49 time: 0.9121 data_time: 0.0093 memory: 70046 grad_norm: 0.1270 loss: 0.0784 recall@thr=0.5: 0.4813 prec@thr=0.5: 0.5729 recall@top3: 0.5958 prec@top3: 0.5833 recall@top5: 0.8958 prec@top5: 0.5125 loss_action_cls: 0.0784 2023/03/11 07:09:03 - mmengine - INFO - Epoch(train) [1][1880/2226] lr: 2.3796e-07 eta: 12:13:25 time: 1.0260 data_time: 0.0134 memory: 70046 grad_norm: 0.1264 loss: 0.0809 recall@thr=0.5: 0.5333 prec@thr=0.5: 0.6000 recall@top3: 0.7000 prec@top3: 0.6000 recall@top5: 0.9000 prec@top5: 0.4600 loss_action_cls: 0.0809 2023/03/11 07:09:29 - mmengine - INFO - Epoch(train) [1][1900/2226] lr: 2.3949e-07 eta: 12:15:09 time: 1.3082 data_time: 0.0114 memory: 70046 grad_norm: 0.1262 loss: 0.0733 recall@thr=0.5: 0.4722 prec@thr=0.5: 0.5972 recall@top3: 0.6944 prec@top3: 0.5833 recall@top5: 0.9167 prec@top5: 0.4500 loss_action_cls: 0.0733 2023/03/11 07:09:46 - mmengine - INFO - Epoch(train) [1][1920/2226] lr: 2.4102e-07 eta: 12:13:19 time: 0.8348 data_time: 0.0086 memory: 70046 grad_norm: 0.1273 loss: 0.0930 recall@thr=0.5: 0.6042 prec@thr=0.5: 0.6667 recall@top3: 0.6458 prec@top3: 0.4583 recall@top5: 0.7917 prec@top5: 0.3500 loss_action_cls: 0.0930 2023/03/11 07:10:08 - mmengine - INFO - Epoch(train) [1][1940/2226] lr: 2.4255e-07 eta: 12:13:31 time: 1.1066 data_time: 0.0139 memory: 70046 grad_norm: 0.1269 loss: 0.0887 recall@thr=0.5: 0.6917 prec@thr=0.5: 0.7333 recall@top3: 0.8139 prec@top3: 0.7222 recall@top5: 0.8861 prec@top5: 0.4833 loss_action_cls: 0.0887 2023/03/11 07:10:30 - mmengine - INFO - Epoch(train) [1][1960/2226] lr: 2.4407e-07 eta: 12:13:24 time: 1.0646 data_time: 0.0088 memory: 70046 grad_norm: 0.1258 loss: 0.0669 recall@thr=0.5: 0.7037 prec@thr=0.5: 0.8148 recall@top3: 0.7593 prec@top3: 0.5926 recall@top5: 0.8889 prec@top5: 0.4222 loss_action_cls: 0.0669 2023/03/11 07:10:50 - mmengine - INFO - Epoch(train) [1][1980/2226] lr: 2.4560e-07 eta: 12:12:52 time: 1.0080 data_time: 0.0089 memory: 70046 grad_norm: 0.1316 loss: 0.0960 recall@thr=0.5: 0.5625 prec@thr=0.5: 0.5833 recall@top3: 0.8542 prec@top3: 0.5833 recall@top5: 0.8542 prec@top5: 0.3500 loss_action_cls: 0.0960 2023/03/11 07:11:10 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 07:11:10 - mmengine - INFO - Epoch(train) [1][2000/2226] lr: 2.4713e-07 eta: 12:12:31 time: 1.0341 data_time: 0.0094 memory: 70046 grad_norm: 0.1342 loss: 0.0876 recall@thr=0.5: 0.3810 prec@thr=0.5: 0.5714 recall@top3: 0.7143 prec@top3: 0.5238 recall@top5: 0.9048 prec@top5: 0.4286 loss_action_cls: 0.0876 2023/03/11 07:11:30 - mmengine - INFO - Epoch(train) [1][2020/2226] lr: 2.4866e-07 eta: 12:11:43 time: 0.9684 data_time: 0.0103 memory: 70046 grad_norm: 0.1360 loss: 0.0765 recall@thr=0.5: 0.1212 prec@thr=0.5: 0.2273 recall@top3: 0.4167 prec@top3: 0.3333 recall@top5: 0.5606 prec@top5: 0.2727 loss_action_cls: 0.0765 2023/03/11 07:11:51 - mmengine - INFO - Epoch(train) [1][2040/2226] lr: 2.5018e-07 eta: 12:11:24 time: 1.0363 data_time: 0.0083 memory: 70046 grad_norm: 0.1242 loss: 0.0973 recall@thr=0.5: 0.7639 prec@thr=0.5: 0.7083 recall@top3: 0.8472 prec@top3: 0.7500 recall@top5: 0.9444 prec@top5: 0.5167 loss_action_cls: 0.0973 2023/03/11 07:12:10 - mmengine - INFO - Epoch(train) [1][2060/2226] lr: 2.5171e-07 eta: 12:10:37 time: 0.9686 data_time: 0.0083 memory: 70046 grad_norm: 0.1206 loss: 0.0833 recall@thr=0.5: 0.3889 prec@thr=0.5: 0.4167 recall@top3: 0.6389 prec@top3: 0.5556 recall@top5: 0.6667 prec@top5: 0.3556 loss_action_cls: 0.0833 2023/03/11 07:12:33 - mmengine - INFO - Epoch(train) [1][2080/2226] lr: 2.5324e-07 eta: 12:11:14 time: 1.1740 data_time: 0.0087 memory: 70046 grad_norm: 0.1286 loss: 0.0748 recall@thr=0.5: 0.6458 prec@thr=0.5: 0.7917 recall@top3: 0.7153 prec@top3: 0.6667 recall@top5: 0.8889 prec@top5: 0.5167 loss_action_cls: 0.0748 2023/03/11 07:12:50 - mmengine - INFO - Epoch(train) [1][2100/2226] lr: 2.5477e-07 eta: 12:09:27 time: 0.8212 data_time: 0.0087 memory: 70046 grad_norm: 0.1289 loss: 0.0601 recall@thr=0.5: 0.3571 prec@thr=0.5: 0.4286 recall@top3: 0.5714 prec@top3: 0.3333 recall@top5: 0.8571 prec@top5: 0.2571 loss_action_cls: 0.0601 2023/03/11 07:13:13 - mmengine - INFO - Epoch(train) [1][2120/2226] lr: 2.5630e-07 eta: 12:09:52 time: 1.1454 data_time: 0.0106 memory: 70046 grad_norm: 0.1288 loss: 0.1145 recall@thr=0.5: 0.2857 prec@thr=0.5: 0.2738 recall@top3: 0.7262 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3429 loss_action_cls: 0.1145 2023/03/11 07:13:32 - mmengine - INFO - Epoch(train) [1][2140/2226] lr: 2.5782e-07 eta: 12:09:03 time: 0.9615 data_time: 0.0101 memory: 70046 grad_norm: 0.1270 loss: 0.0839 recall@thr=0.5: 0.7986 prec@thr=0.5: 0.7569 recall@top3: 0.7986 prec@top3: 0.7500 recall@top5: 0.9583 prec@top5: 0.5500 loss_action_cls: 0.0839 2023/03/11 07:13:53 - mmengine - INFO - Epoch(train) [1][2160/2226] lr: 2.5935e-07 eta: 12:08:54 time: 1.0614 data_time: 0.0091 memory: 70046 grad_norm: 0.1295 loss: 0.0798 recall@thr=0.5: 0.7262 prec@thr=0.5: 1.0000 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 0.8690 prec@top5: 0.4286 loss_action_cls: 0.0798 2023/03/11 07:14:16 - mmengine - INFO - Epoch(train) [1][2180/2226] lr: 2.6088e-07 eta: 12:09:20 time: 1.1521 data_time: 0.0103 memory: 70046 grad_norm: 0.1256 loss: 0.1084 recall@thr=0.5: 0.3889 prec@thr=0.5: 0.4444 recall@top3: 0.6111 prec@top3: 0.3333 recall@top5: 1.0000 prec@top5: 0.3111 loss_action_cls: 0.1084 2023/03/11 07:14:33 - mmengine - INFO - Epoch(train) [1][2200/2226] lr: 2.6241e-07 eta: 12:07:52 time: 0.8586 data_time: 0.0072 memory: 70046 grad_norm: 0.1269 loss: 0.0886 recall@thr=0.5: 0.7708 prec@thr=0.5: 0.8542 recall@top3: 0.8854 prec@top3: 0.8750 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0886 2023/03/11 07:14:53 - mmengine - INFO - Epoch(train) [1][2220/2226] lr: 2.6393e-07 eta: 12:07:13 time: 0.9842 data_time: 0.0117 memory: 70046 grad_norm: 0.1237 loss: 0.0689 recall@thr=0.5: 0.6204 prec@thr=0.5: 0.8333 recall@top3: 0.7685 prec@top3: 0.5185 recall@top5: 0.7963 prec@top5: 0.3333 loss_action_cls: 0.0689 2023/03/11 07:14:57 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 07:14:57 - mmengine - INFO - Epoch(train) [1][2226/2226] lr: 2.6439e-07 eta: 12:06:21 time: 0.8082 data_time: 0.0080 memory: 70046 grad_norm: 0.1282 loss: 0.0605 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.7500 recall@top3: 0.7500 prec@top3: 0.2500 recall@top5: 0.8333 prec@top5: 0.2000 loss_action_cls: 0.0605 2023/03/11 07:14:57 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/03/11 07:15:16 - mmengine - INFO - Epoch(val) [1][ 20/1571] eta: 0:08:40 time: 0.3358 data_time: 0.2403 memory: 6688 2023/03/11 07:15:19 - mmengine - INFO - Epoch(val) [1][ 40/1571] eta: 0:06:27 time: 0.1701 data_time: 0.0483 memory: 7490 2023/03/11 07:15:23 - mmengine - INFO - Epoch(val) [1][ 60/1571] eta: 0:05:49 time: 0.1885 data_time: 0.0686 memory: 7490 2023/03/11 07:15:26 - mmengine - INFO - Epoch(val) [1][ 80/1571] eta: 0:05:20 time: 0.1658 data_time: 0.0495 memory: 7490 2023/03/11 07:15:30 - mmengine - INFO - Epoch(val) [1][ 100/1571] eta: 0:05:08 time: 0.1883 data_time: 0.0506 memory: 7490 2023/03/11 07:15:33 - mmengine - INFO - Epoch(val) [1][ 120/1571] eta: 0:04:54 time: 0.1708 data_time: 0.0722 memory: 6775 2023/03/11 07:15:37 - mmengine - INFO - Epoch(val) [1][ 140/1571] eta: 0:04:42 time: 0.1636 data_time: 0.0532 memory: 6775 2023/03/11 07:15:39 - mmengine - INFO - Epoch(val) [1][ 160/1571] eta: 0:04:25 time: 0.1250 data_time: 0.0299 memory: 6775 2023/03/11 07:15:43 - mmengine - INFO - Epoch(val) [1][ 180/1571] eta: 0:04:25 time: 0.2103 data_time: 0.1095 memory: 7490 2023/03/11 07:15:47 - mmengine - INFO - Epoch(val) [1][ 200/1571] eta: 0:04:21 time: 0.1884 data_time: 0.0544 memory: 7490 2023/03/11 07:15:51 - mmengine - INFO - Epoch(val) [1][ 220/1571] eta: 0:04:16 time: 0.1851 data_time: 0.0799 memory: 7490 2023/03/11 07:15:54 - mmengine - INFO - Epoch(val) [1][ 240/1571] eta: 0:04:10 time: 0.1682 data_time: 0.0721 memory: 6775 2023/03/11 07:15:58 - mmengine - INFO - Epoch(val) [1][ 260/1571] eta: 0:04:05 time: 0.1730 data_time: 0.0809 memory: 6775 2023/03/11 07:16:00 - mmengine - INFO - Epoch(val) [1][ 280/1571] eta: 0:03:56 time: 0.1320 data_time: 0.0384 memory: 6775 2023/03/11 07:16:03 - mmengine - INFO - Epoch(val) [1][ 300/1571] eta: 0:03:49 time: 0.1484 data_time: 0.0449 memory: 6775 2023/03/11 07:16:07 - mmengine - INFO - Epoch(val) [1][ 320/1571] eta: 0:03:45 time: 0.1645 data_time: 0.0407 memory: 7490 2023/03/11 07:16:11 - mmengine - INFO - Epoch(val) [1][ 340/1571] eta: 0:03:42 time: 0.2013 data_time: 0.0609 memory: 7490 2023/03/11 07:16:14 - mmengine - INFO - Epoch(val) [1][ 360/1571] eta: 0:03:39 time: 0.1843 data_time: 0.0463 memory: 7490 2023/03/11 07:16:18 - mmengine - INFO - Epoch(val) [1][ 380/1571] eta: 0:03:35 time: 0.1729 data_time: 0.0359 memory: 7490 2023/03/11 07:16:22 - mmengine - INFO - Epoch(val) [1][ 400/1571] eta: 0:03:32 time: 0.1973 data_time: 0.0028 memory: 8853 2023/03/11 07:16:25 - mmengine - INFO - Epoch(val) [1][ 420/1571] eta: 0:03:28 time: 0.1782 data_time: 0.0265 memory: 8853 2023/03/11 07:16:28 - mmengine - INFO - Epoch(val) [1][ 440/1571] eta: 0:03:23 time: 0.1422 data_time: 0.0065 memory: 7490 2023/03/11 07:16:31 - mmengine - INFO - Epoch(val) [1][ 460/1571] eta: 0:03:18 time: 0.1541 data_time: 0.0179 memory: 7490 2023/03/11 07:16:35 - mmengine - INFO - Epoch(val) [1][ 480/1571] eta: 0:03:15 time: 0.1944 data_time: 0.0487 memory: 7490 2023/03/11 07:16:39 - mmengine - INFO - Epoch(val) [1][ 500/1571] eta: 0:03:13 time: 0.2101 data_time: 0.1019 memory: 7490 2023/03/11 07:16:42 - mmengine - INFO - Epoch(val) [1][ 520/1571] eta: 0:03:08 time: 0.1554 data_time: 0.0594 memory: 6775 2023/03/11 07:16:47 - mmengine - INFO - Epoch(val) [1][ 540/1571] eta: 0:03:06 time: 0.2069 data_time: 0.1126 memory: 6775 2023/03/11 07:16:50 - mmengine - INFO - Epoch(val) [1][ 560/1571] eta: 0:03:01 time: 0.1513 data_time: 0.0491 memory: 6775 2023/03/11 07:16:53 - mmengine - INFO - Epoch(val) [1][ 580/1571] eta: 0:02:58 time: 0.1851 data_time: 0.0815 memory: 6775 2023/03/11 07:16:56 - mmengine - INFO - Epoch(val) [1][ 600/1571] eta: 0:02:53 time: 0.1407 data_time: 0.0474 memory: 6775 2023/03/11 07:17:00 - mmengine - INFO - Epoch(val) [1][ 620/1571] eta: 0:02:49 time: 0.1758 data_time: 0.0607 memory: 7490 2023/03/11 07:17:03 - mmengine - INFO - Epoch(val) [1][ 640/1571] eta: 0:02:46 time: 0.1867 data_time: 0.0460 memory: 7490 2023/03/11 07:17:08 - mmengine - INFO - Epoch(val) [1][ 660/1571] eta: 0:02:43 time: 0.2163 data_time: 0.0783 memory: 7490 2023/03/11 07:17:12 - mmengine - INFO - Epoch(val) [1][ 680/1571] eta: 0:02:40 time: 0.2028 data_time: 0.0034 memory: 8699 2023/03/11 07:17:15 - mmengine - INFO - Epoch(val) [1][ 700/1571] eta: 0:02:36 time: 0.1354 data_time: 0.0127 memory: 8699 2023/03/11 07:17:18 - mmengine - INFO - Epoch(val) [1][ 720/1571] eta: 0:02:32 time: 0.1780 data_time: 0.0611 memory: 7490 2023/03/11 07:17:22 - mmengine - INFO - Epoch(val) [1][ 740/1571] eta: 0:02:28 time: 0.1770 data_time: 0.0617 memory: 7490 2023/03/11 07:17:25 - mmengine - INFO - Epoch(val) [1][ 760/1571] eta: 0:02:24 time: 0.1655 data_time: 0.0398 memory: 7490 2023/03/11 07:17:28 - mmengine - INFO - Epoch(val) [1][ 780/1571] eta: 0:02:20 time: 0.1621 data_time: 0.0398 memory: 7490 2023/03/11 07:17:31 - 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eta: 0:00:51 time: 0.1630 data_time: 0.0670 memory: 6775 2023/03/11 07:18:59 - mmengine - INFO - Epoch(val) [1][1300/1571] eta: 0:00:47 time: 0.1789 data_time: 0.0827 memory: 6775 2023/03/11 07:19:02 - mmengine - INFO - Epoch(val) [1][1320/1571] eta: 0:00:44 time: 0.1479 data_time: 0.0461 memory: 6775 2023/03/11 07:19:06 - mmengine - INFO - Epoch(val) [1][1340/1571] eta: 0:00:40 time: 0.1941 data_time: 0.0975 memory: 6775 2023/03/11 07:19:10 - mmengine - INFO - Epoch(val) [1][1360/1571] eta: 0:00:37 time: 0.2106 data_time: 0.1112 memory: 6775 2023/03/11 07:19:14 - mmengine - INFO - Epoch(val) [1][1380/1571] eta: 0:00:33 time: 0.1923 data_time: 0.0925 memory: 7057 2023/03/11 07:19:17 - mmengine - INFO - Epoch(val) [1][1400/1571] eta: 0:00:30 time: 0.1636 data_time: 0.0535 memory: 7057 2023/03/11 07:19:21 - mmengine - INFO - Epoch(val) [1][1420/1571] eta: 0:00:26 time: 0.1953 data_time: 0.1000 memory: 7057 2023/03/11 07:19:24 - mmengine - INFO - Epoch(val) [1][1440/1571] eta: 0:00:23 time: 0.1601 data_time: 0.0459 memory: 7160 2023/03/11 07:19:28 - mmengine - INFO - Epoch(val) [1][1460/1571] eta: 0:00:19 time: 0.1974 data_time: 0.0760 memory: 7160 2023/03/11 07:19:31 - mmengine - INFO - Epoch(val) [1][1480/1571] eta: 0:00:16 time: 0.1481 data_time: 0.0405 memory: 7057 2023/03/11 07:19:35 - mmengine - INFO - Epoch(val) [1][1500/1571] eta: 0:00:12 time: 0.1796 data_time: 0.0712 memory: 7490 2023/03/11 07:19:38 - mmengine - INFO - Epoch(val) [1][1520/1571] eta: 0:00:09 time: 0.1755 data_time: 0.0260 memory: 7490 2023/03/11 07:19:41 - mmengine - INFO - Epoch(val) [1][1540/1571] eta: 0:00:05 time: 0.1387 data_time: 0.0058 memory: 7490 2023/03/11 07:19:44 - mmengine - INFO - Epoch(val) [1][1560/1571] eta: 0:00:01 time: 0.1329 data_time: 0.0016 memory: 7490 2023/03/11 07:24:58 - mmengine - INFO - Epoch(val) [1][1571/1571] mAP/mAP@0.5IOU: 0.2617 2023/03/11 07:25:03 - mmengine - INFO - The best checkpoint with 0.2617 mAP/mAP@0.5IOU at 1 epoch is saved to best_mAP/mAP@0.5IOU_epoch_1.pth. 2023/03/11 07:25:26 - mmengine - INFO - Epoch(train) [2][ 20/2226] lr: 2.6592e-07 eta: 12:06:47 time: 1.1535 data_time: 0.4747 memory: 70046 grad_norm: 0.1286 loss: 0.0954 recall@thr=0.5: 0.7569 prec@thr=0.5: 0.8403 recall@top3: 0.7431 prec@top3: 0.8056 recall@top5: 1.0000 prec@top5: 0.6833 loss_action_cls: 0.0954 2023/03/11 07:25:47 - mmengine - INFO - Epoch(train) [2][ 40/2226] lr: 2.6745e-07 eta: 12:06:21 time: 1.0187 data_time: 0.0993 memory: 70046 grad_norm: 0.1286 loss: 0.1274 recall@thr=0.5: 0.5845 prec@thr=0.5: 0.8046 recall@top3: 0.7856 prec@top3: 0.6437 recall@top5: 0.8506 prec@top5: 0.4345 loss_action_cls: 0.1274 2023/03/11 07:26:11 - mmengine - INFO - Epoch(train) [2][ 60/2226] lr: 2.6897e-07 eta: 12:07:12 time: 1.2254 data_time: 0.0117 memory: 70046 grad_norm: 0.1357 loss: 0.0684 recall@thr=0.5: 0.8148 prec@thr=0.5: 0.8889 recall@top3: 0.9444 prec@top3: 0.8519 recall@top5: 1.0000 prec@top5: 0.5556 loss_action_cls: 0.0684 2023/03/11 07:26:29 - mmengine - INFO - Epoch(train) [2][ 80/2226] lr: 2.7050e-07 eta: 12:05:55 time: 0.8799 data_time: 0.0107 memory: 70046 grad_norm: 0.1300 loss: 0.0939 recall@thr=0.5: 0.6548 prec@thr=0.5: 0.7500 recall@top3: 0.8333 prec@top3: 0.6905 recall@top5: 0.9286 prec@top5: 0.4571 loss_action_cls: 0.0939 2023/03/11 07:26:52 - mmengine - INFO - Epoch(train) [2][ 100/2226] lr: 2.7203e-07 eta: 12:06:10 time: 1.1275 data_time: 0.0129 memory: 70046 grad_norm: 0.1300 loss: 0.0944 recall@thr=0.5: 0.5714 prec@thr=0.5: 0.5714 recall@top3: 0.7619 prec@top3: 0.7143 recall@top5: 0.8571 prec@top5: 0.4857 loss_action_cls: 0.0944 2023/03/11 07:27:10 - mmengine - INFO - Epoch(train) [2][ 120/2226] lr: 2.7356e-07 eta: 12:05:08 time: 0.9183 data_time: 0.0096 memory: 70046 grad_norm: 0.1274 loss: 0.0735 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.8095 recall@top3: 0.7857 prec@top3: 0.5238 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0735 2023/03/11 07:27:30 - mmengine - INFO - Epoch(train) [2][ 140/2226] lr: 2.7508e-07 eta: 12:04:43 time: 1.0202 data_time: 0.0114 memory: 70046 grad_norm: 0.1277 loss: 0.1032 recall@thr=0.5: 0.4545 prec@thr=0.5: 0.7955 recall@top3: 0.7045 prec@top3: 0.6970 recall@top5: 0.8182 prec@top5: 0.4909 loss_action_cls: 0.1032 2023/03/11 07:27:49 - mmengine - INFO - Epoch(train) [2][ 160/2226] lr: 2.7661e-07 eta: 12:03:50 time: 0.9401 data_time: 0.0110 memory: 70046 grad_norm: 0.1243 loss: 0.0748 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.7917 recall@top3: 0.9167 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0748 2023/03/11 07:28:12 - mmengine - INFO - Epoch(train) [2][ 180/2226] lr: 2.7814e-07 eta: 12:04:05 time: 1.1322 data_time: 0.0117 memory: 70046 grad_norm: 0.1252 loss: 0.0901 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.6250 recall@top3: 0.7500 prec@top3: 0.3333 recall@top5: 0.7500 prec@top5: 0.2000 loss_action_cls: 0.0901 2023/03/11 07:28:31 - mmengine - INFO - Epoch(train) [2][ 200/2226] lr: 2.7967e-07 eta: 12:03:20 time: 0.9602 data_time: 0.0134 memory: 70046 grad_norm: 0.1314 loss: 0.0819 recall@thr=0.5: 0.4464 prec@thr=0.5: 0.5714 recall@top3: 0.7202 prec@top3: 0.5000 recall@top5: 1.0000 prec@top5: 0.4571 loss_action_cls: 0.0819 2023/03/11 07:28:51 - mmengine - INFO - Epoch(train) [2][ 220/2226] lr: 2.8119e-07 eta: 12:02:52 time: 1.0118 data_time: 0.0120 memory: 70046 grad_norm: 0.1282 loss: 0.0839 recall@thr=0.5: 0.5714 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.7143 recall@top5: 0.9048 prec@top5: 0.4571 loss_action_cls: 0.0839 2023/03/11 07:29:12 - mmengine - INFO - Epoch(train) [2][ 240/2226] lr: 2.8272e-07 eta: 12:02:38 time: 1.0498 data_time: 0.0114 memory: 70046 grad_norm: 0.1345 loss: 0.0821 recall@thr=0.5: 0.4167 prec@thr=0.5: 0.5500 recall@top3: 0.7167 prec@top3: 0.4667 recall@top5: 0.8500 prec@top5: 0.3400 loss_action_cls: 0.0821 2023/03/11 07:29:33 - mmengine - INFO - Epoch(train) [2][ 260/2226] lr: 2.8425e-07 eta: 12:02:21 time: 1.0422 data_time: 0.0109 memory: 70046 grad_norm: 0.1288 loss: 0.0646 recall@thr=0.5: 0.2455 prec@thr=0.5: 0.3182 recall@top3: 0.4030 prec@top3: 0.4242 recall@top5: 0.6333 prec@top5: 0.4182 loss_action_cls: 0.0646 2023/03/11 07:29:54 - mmengine - INFO - Epoch(train) [2][ 280/2226] lr: 2.8578e-07 eta: 12:02:02 time: 1.0353 data_time: 0.0121 memory: 70046 grad_norm: 0.1314 loss: 0.0836 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6597 recall@top3: 0.7222 prec@top3: 0.5556 recall@top5: 0.9167 prec@top5: 0.3833 loss_action_cls: 0.0836 2023/03/11 07:30:16 - mmengine - INFO - Epoch(train) [2][ 300/2226] lr: 2.8731e-07 eta: 12:02:08 time: 1.1093 data_time: 0.0118 memory: 70046 grad_norm: 0.1316 loss: 0.0849 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.7083 recall@top3: 0.7500 prec@top3: 0.3333 recall@top5: 0.9375 prec@top5: 0.2750 loss_action_cls: 0.0849 2023/03/11 07:30:36 - mmengine - INFO - Epoch(train) [2][ 320/2226] lr: 2.8883e-07 eta: 12:01:35 time: 0.9942 data_time: 0.0103 memory: 70046 grad_norm: 0.1290 loss: 0.0916 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.7500 recall@top3: 0.9375 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0916 2023/03/11 07:30:56 - mmengine - INFO - Epoch(train) [2][ 340/2226] lr: 2.9036e-07 eta: 12:01:05 time: 1.0026 data_time: 0.0106 memory: 70046 grad_norm: 0.1363 loss: 0.0891 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.6667 recall@top3: 0.8095 prec@top3: 0.5238 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0891 2023/03/11 07:31:16 - mmengine - INFO - Epoch(train) [2][ 360/2226] lr: 2.9189e-07 eta: 12:00:29 time: 0.9844 data_time: 0.0141 memory: 70046 grad_norm: 0.1356 loss: 0.0879 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.4815 recall@top3: 0.8241 prec@top3: 0.5556 recall@top5: 0.9259 prec@top5: 0.4000 loss_action_cls: 0.0879 2023/03/11 07:31:39 - mmengine - INFO - Epoch(train) [2][ 380/2226] lr: 2.9342e-07 eta: 12:00:57 time: 1.1840 data_time: 0.0104 memory: 70046 grad_norm: 0.1312 loss: 0.0623 recall@thr=0.5: 0.5250 prec@thr=0.5: 0.8125 recall@top3: 0.5917 prec@top3: 0.4167 recall@top5: 0.8042 prec@top5: 0.3750 loss_action_cls: 0.0623 2023/03/11 07:32:01 - mmengine - INFO - Epoch(train) [2][ 400/2226] lr: 2.9494e-07 eta: 12:00:50 time: 1.0733 data_time: 0.0087 memory: 70046 grad_norm: 0.1364 loss: 0.0881 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.8125 recall@top3: 0.8333 prec@top3: 0.3750 recall@top5: 0.8750 prec@top5: 0.2500 loss_action_cls: 0.0881 2023/03/11 07:32:24 - mmengine - INFO - Epoch(train) [2][ 420/2226] lr: 2.9647e-07 eta: 12:01:05 time: 1.1447 data_time: 0.0101 memory: 70046 grad_norm: 0.1381 loss: 0.0870 recall@thr=0.5: 0.6042 prec@thr=0.5: 0.6875 recall@top3: 0.7083 prec@top3: 0.6667 recall@top5: 0.9062 prec@top5: 0.5250 loss_action_cls: 0.0870 2023/03/11 07:32:42 - mmengine - INFO - Epoch(train) [2][ 440/2226] lr: 2.9800e-07 eta: 12:00:15 time: 0.9420 data_time: 0.0092 memory: 70046 grad_norm: 0.1303 loss: 0.1002 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7778 recall@top3: 0.9583 prec@top3: 0.6944 recall@top5: 0.9792 prec@top5: 0.4333 loss_action_cls: 0.1002 2023/03/11 07:33:08 - mmengine - INFO - Epoch(train) [2][ 460/2226] lr: 2.9953e-07 eta: 12:01:05 time: 1.2590 data_time: 0.0108 memory: 70046 grad_norm: 0.1226 loss: 0.1016 recall@thr=0.5: 0.6176 prec@thr=0.5: 0.6765 recall@top3: 0.7941 prec@top3: 0.6863 recall@top5: 0.8431 prec@top5: 0.4353 loss_action_cls: 0.1016 2023/03/11 07:33:25 - mmengine - INFO - Epoch(train) [2][ 480/2226] lr: 3.0105e-07 eta: 11:59:51 time: 0.8616 data_time: 0.0091 memory: 70046 grad_norm: 0.1324 loss: 0.0932 recall@thr=0.5: 0.6528 prec@thr=0.5: 0.5833 recall@top3: 0.7708 prec@top3: 0.6389 recall@top5: 0.9583 prec@top5: 0.5000 loss_action_cls: 0.0932 2023/03/11 07:33:48 - mmengine - INFO - Epoch(train) [2][ 500/2226] lr: 3.0258e-07 eta: 12:00:15 time: 1.1787 data_time: 0.0103 memory: 70046 grad_norm: 0.1256 loss: 0.0702 recall@thr=0.5: 0.6786 prec@thr=0.5: 0.9524 recall@top3: 0.7738 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.5429 loss_action_cls: 0.0702 2023/03/11 07:34:08 - mmengine - INFO - Epoch(train) [2][ 520/2226] lr: 3.0411e-07 eta: 11:59:34 time: 0.9673 data_time: 0.0109 memory: 70046 grad_norm: 0.1238 loss: 0.0760 recall@thr=0.5: 0.5238 prec@thr=0.5: 0.7143 recall@top3: 0.8810 prec@top3: 0.5714 recall@top5: 0.8810 prec@top5: 0.3429 loss_action_cls: 0.0760 2023/03/11 07:34:31 - mmengine - INFO - Epoch(train) [2][ 540/2226] lr: 3.0564e-07 eta: 11:59:49 time: 1.1501 data_time: 0.0124 memory: 70046 grad_norm: 0.1311 loss: 0.0721 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.6111 recall@top3: 0.9167 prec@top3: 0.6296 recall@top5: 0.9722 prec@top5: 0.4000 loss_action_cls: 0.0721 2023/03/11 07:34:54 - mmengine - INFO - Epoch(train) [2][ 560/2226] lr: 3.0716e-07 eta: 12:00:00 time: 1.1409 data_time: 0.0122 memory: 70046 grad_norm: 0.1363 loss: 0.0722 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8333 recall@top3: 1.0000 prec@top3: 0.7222 recall@top5: 1.0000 prec@top5: 0.4333 loss_action_cls: 0.0722 2023/03/11 07:35:15 - mmengine - INFO - Epoch(train) [2][ 580/2226] lr: 3.0869e-07 eta: 11:59:56 time: 1.0914 data_time: 0.0108 memory: 70046 grad_norm: 0.1321 loss: 0.0723 recall@thr=0.5: 0.6357 prec@thr=0.5: 0.7488 recall@top3: 0.5881 prec@top3: 0.6190 recall@top5: 0.7619 prec@top5: 0.4857 loss_action_cls: 0.0723 2023/03/11 07:35:36 - mmengine - INFO - Epoch(train) [2][ 600/2226] lr: 3.1022e-07 eta: 11:59:30 time: 1.0157 data_time: 0.0091 memory: 70046 grad_norm: 0.1233 loss: 0.0807 recall@thr=0.5: 0.7292 prec@thr=0.5: 0.8750 recall@top3: 0.8750 prec@top3: 0.7917 recall@top5: 1.0000 prec@top5: 0.5250 loss_action_cls: 0.0807 2023/03/11 07:35:57 - mmengine - INFO - Epoch(train) [2][ 620/2226] lr: 3.1175e-07 eta: 11:59:23 time: 1.0838 data_time: 0.0121 memory: 70046 grad_norm: 0.1294 loss: 0.0763 recall@thr=0.5: 0.4444 prec@thr=0.5: 0.8333 recall@top3: 0.6574 prec@top3: 0.5926 recall@top5: 0.7593 prec@top5: 0.4222 loss_action_cls: 0.0763 2023/03/11 07:36:19 - mmengine - INFO - Epoch(train) [2][ 640/2226] lr: 3.1327e-07 eta: 11:59:15 time: 1.0781 data_time: 0.0095 memory: 70046 grad_norm: 0.1334 loss: 0.0750 recall@thr=0.5: 0.8111 prec@thr=0.5: 0.7667 recall@top3: 0.8444 prec@top3: 0.6444 recall@top5: 0.9556 prec@top5: 0.4400 loss_action_cls: 0.0750 2023/03/11 07:36:44 - mmengine - INFO - Epoch(train) [2][ 660/2226] lr: 3.1480e-07 eta: 11:59:55 time: 1.2492 data_time: 0.0090 memory: 70046 grad_norm: 0.1343 loss: 0.0764 recall@thr=0.5: 0.5167 prec@thr=0.5: 0.6000 recall@top3: 0.7667 prec@top3: 0.4000 recall@top5: 1.0000 prec@top5: 0.3400 loss_action_cls: 0.0764 2023/03/11 07:37:05 - mmengine - INFO - Epoch(train) [2][ 680/2226] lr: 3.1633e-07 eta: 11:59:43 time: 1.0661 data_time: 0.0101 memory: 70046 grad_norm: 0.1260 loss: 0.0792 recall@thr=0.5: 0.7193 prec@thr=0.5: 0.7368 recall@top3: 0.7544 prec@top3: 0.5965 recall@top5: 0.7895 prec@top5: 0.3789 loss_action_cls: 0.0792 2023/03/11 07:37:25 - mmengine - INFO - Epoch(train) [2][ 700/2226] lr: 3.1786e-07 eta: 11:59:05 time: 0.9775 data_time: 0.0083 memory: 70046 grad_norm: 0.1274 loss: 0.0950 recall@thr=0.5: 0.4271 prec@thr=0.5: 0.6250 recall@top3: 0.6771 prec@top3: 0.6250 recall@top5: 0.9167 prec@top5: 0.5250 loss_action_cls: 0.0950 2023/03/11 07:37:47 - mmengine - INFO - Epoch(train) [2][ 720/2226] lr: 3.1938e-07 eta: 11:58:59 time: 1.0887 data_time: 0.0118 memory: 70046 grad_norm: 0.1320 loss: 0.1022 recall@thr=0.5: 0.6958 prec@thr=0.5: 0.7500 recall@top3: 0.8458 prec@top3: 0.4583 recall@top5: 0.8708 prec@top5: 0.3000 loss_action_cls: 0.1022 2023/03/11 07:38:09 - mmengine - INFO - Epoch(train) [2][ 740/2226] lr: 3.2091e-07 eta: 11:58:56 time: 1.1017 data_time: 0.0112 memory: 70046 grad_norm: 0.1295 loss: 0.0770 recall@thr=0.5: 0.3000 prec@thr=0.5: 0.3500 recall@top3: 0.6500 prec@top3: 0.5000 recall@top5: 0.8667 prec@top5: 0.3800 loss_action_cls: 0.0770 2023/03/11 07:38:32 - mmengine - INFO - Epoch(train) [2][ 760/2226] lr: 3.2244e-07 eta: 11:59:09 time: 1.1602 data_time: 0.0096 memory: 70046 grad_norm: 0.1304 loss: 0.0662 recall@thr=0.5: 0.7628 prec@thr=0.5: 0.8269 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 0.9487 prec@top5: 0.4923 loss_action_cls: 0.0662 2023/03/11 07:38:47 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 07:38:54 - mmengine - INFO - Epoch(train) [2][ 780/2226] lr: 3.2397e-07 eta: 11:59:02 time: 1.0889 data_time: 0.0098 memory: 70046 grad_norm: 0.1281 loss: 0.0711 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7500 recall@top3: 0.7738 prec@top3: 0.3333 recall@top5: 0.7976 prec@top5: 0.2143 loss_action_cls: 0.0711 2023/03/11 07:39:15 - mmengine - INFO - Epoch(train) [2][ 800/2226] lr: 3.2549e-07 eta: 11:58:44 time: 1.0487 data_time: 0.0103 memory: 70046 grad_norm: 0.1220 loss: 0.0561 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.8333 recall@top3: 0.9286 prec@top3: 0.6190 recall@top5: 0.9286 prec@top5: 0.3714 loss_action_cls: 0.0561 2023/03/11 07:39:35 - mmengine - INFO - Epoch(train) [2][ 820/2226] lr: 3.2702e-07 eta: 11:58:22 time: 1.0367 data_time: 0.0090 memory: 70046 grad_norm: 0.1334 loss: 0.0663 recall@thr=0.5: 0.7130 prec@thr=0.5: 0.7531 recall@top3: 0.8241 prec@top3: 0.7160 recall@top5: 0.8858 prec@top5: 0.4741 loss_action_cls: 0.0663 2023/03/11 07:39:59 - mmengine - INFO - Epoch(train) [2][ 840/2226] lr: 3.2855e-07 eta: 11:58:38 time: 1.1750 data_time: 0.0105 memory: 70046 grad_norm: 0.1241 loss: 0.0798 recall@thr=0.5: 0.7051 prec@thr=0.5: 0.8526 recall@top3: 0.6795 prec@top3: 0.6154 recall@top5: 0.9103 prec@top5: 0.4923 loss_action_cls: 0.0798 2023/03/11 07:40:21 - mmengine - INFO - Epoch(train) [2][ 860/2226] lr: 3.3008e-07 eta: 11:58:30 time: 1.0882 data_time: 0.0093 memory: 70046 grad_norm: 0.1289 loss: 0.0675 recall@thr=0.5: 0.4306 prec@thr=0.5: 0.8333 recall@top3: 0.7500 prec@top3: 0.5556 recall@top5: 0.9167 prec@top5: 0.4333 loss_action_cls: 0.0675 2023/03/11 07:40:39 - mmengine - INFO - Epoch(train) [2][ 880/2226] lr: 3.3161e-07 eta: 11:57:34 time: 0.9055 data_time: 0.0083 memory: 70046 grad_norm: 0.1301 loss: 0.1056 recall@thr=0.5: 0.4667 prec@thr=0.5: 0.4833 recall@top3: 0.7167 prec@top3: 0.5333 recall@top5: 0.9250 prec@top5: 0.4400 loss_action_cls: 0.1056 2023/03/11 07:41:01 - mmengine - INFO - Epoch(train) [2][ 900/2226] lr: 3.3313e-07 eta: 11:57:39 time: 1.1382 data_time: 0.0106 memory: 70046 grad_norm: 0.1349 loss: 0.0607 recall@thr=0.5: 0.9394 prec@thr=0.5: 0.9545 recall@top3: 0.9242 prec@top3: 0.8485 recall@top5: 1.0000 prec@top5: 0.5636 loss_action_cls: 0.0607 2023/03/11 07:41:24 - mmengine - INFO - Epoch(train) [2][ 920/2226] lr: 3.3466e-07 eta: 11:57:36 time: 1.1072 data_time: 0.0105 memory: 70046 grad_norm: 0.1307 loss: 0.0736 recall@thr=0.5: 0.7174 prec@thr=0.5: 0.7246 recall@top3: 0.7971 prec@top3: 0.5507 recall@top5: 0.8986 prec@top5: 0.3913 loss_action_cls: 0.0736 2023/03/11 07:41:48 - mmengine - INFO - Epoch(train) [2][ 940/2226] lr: 3.3619e-07 eta: 11:57:56 time: 1.1991 data_time: 0.0127 memory: 70046 grad_norm: 0.1317 loss: 0.0940 recall@thr=0.5: 0.4375 prec@thr=0.5: 0.4792 recall@top3: 0.6458 prec@top3: 0.4583 recall@top5: 0.9167 prec@top5: 0.4000 loss_action_cls: 0.0940 2023/03/11 07:42:08 - mmengine - INFO - Epoch(train) [2][ 960/2226] lr: 3.3772e-07 eta: 11:57:25 time: 1.0007 data_time: 0.0118 memory: 70046 grad_norm: 0.1305 loss: 0.0924 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.7500 recall@top3: 0.8125 prec@top3: 0.5000 recall@top5: 0.8750 prec@top5: 0.3250 loss_action_cls: 0.0924 2023/03/11 07:42:32 - mmengine - INFO - Epoch(train) [2][ 980/2226] lr: 3.3924e-07 eta: 11:57:46 time: 1.2037 data_time: 0.0100 memory: 70046 grad_norm: 0.1202 loss: 0.0832 recall@thr=0.5: 0.4062 prec@thr=0.5: 0.5208 recall@top3: 0.7604 prec@top3: 0.5208 recall@top5: 0.7969 prec@top5: 0.3375 loss_action_cls: 0.0832 2023/03/11 07:42:53 - mmengine - INFO - Epoch(train) [2][1000/2226] lr: 3.4077e-07 eta: 11:57:29 time: 1.0558 data_time: 0.0098 memory: 70046 grad_norm: 0.1222 loss: 0.0906 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8750 recall@top3: 0.9375 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0906 2023/03/11 07:43:16 - mmengine - INFO - Epoch(train) [2][1020/2226] lr: 3.4230e-07 eta: 11:57:40 time: 1.1697 data_time: 0.0087 memory: 70046 grad_norm: 0.1253 loss: 0.0945 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.7292 recall@top3: 0.8750 prec@top3: 0.5417 recall@top5: 0.9375 prec@top5: 0.3500 loss_action_cls: 0.0945 2023/03/11 07:43:35 - mmengine - INFO - Epoch(train) [2][1040/2226] lr: 3.4383e-07 eta: 11:56:49 time: 0.9241 data_time: 0.0082 memory: 70046 grad_norm: 0.1273 loss: 0.0835 recall@thr=0.5: 0.5952 prec@thr=0.5: 0.9048 recall@top3: 0.6667 prec@top3: 0.7143 recall@top5: 0.9048 prec@top5: 0.5714 loss_action_cls: 0.0835 2023/03/11 07:43:56 - mmengine - INFO - Epoch(train) [2][1060/2226] lr: 3.4535e-07 eta: 11:56:38 time: 1.0824 data_time: 0.0104 memory: 70046 grad_norm: 0.1292 loss: 0.0851 recall@thr=0.5: 0.7130 prec@thr=0.5: 0.8611 recall@top3: 0.8889 prec@top3: 0.7778 recall@top5: 0.9167 prec@top5: 0.4889 loss_action_cls: 0.0851 2023/03/11 07:44:16 - mmengine - INFO - Epoch(train) [2][1080/2226] lr: 3.4688e-07 eta: 11:56:09 time: 1.0081 data_time: 0.0102 memory: 70046 grad_norm: 0.1270 loss: 0.0631 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7361 recall@top3: 0.7500 prec@top3: 0.6111 recall@top5: 0.9167 prec@top5: 0.4833 loss_action_cls: 0.0631 2023/03/11 07:44:40 - mmengine - INFO - Epoch(train) [2][1100/2226] lr: 3.4841e-07 eta: 11:56:25 time: 1.1933 data_time: 0.0119 memory: 70046 grad_norm: 0.1303 loss: 0.0682 recall@thr=0.5: 0.7667 prec@thr=0.5: 0.8333 recall@top3: 0.8667 prec@top3: 0.8000 recall@top5: 1.0000 prec@top5: 0.5600 loss_action_cls: 0.0682 2023/03/11 07:45:00 - mmengine - INFO - Epoch(train) [2][1120/2226] lr: 3.4994e-07 eta: 11:55:50 time: 0.9864 data_time: 0.0100 memory: 70046 grad_norm: 0.1294 loss: 0.0817 recall@thr=0.5: 0.4375 prec@thr=0.5: 0.7500 recall@top3: 0.6042 prec@top3: 0.4583 recall@top5: 0.8958 prec@top5: 0.4250 loss_action_cls: 0.0817 2023/03/11 07:45:24 - mmengine - INFO - Epoch(train) [2][1140/2226] lr: 3.5146e-07 eta: 11:56:08 time: 1.2008 data_time: 0.0098 memory: 70046 grad_norm: 0.1204 loss: 0.0747 recall@thr=0.5: 0.9286 prec@thr=0.5: 0.8333 recall@top3: 0.9286 prec@top3: 0.8095 recall@top5: 1.0000 prec@top5: 0.5143 loss_action_cls: 0.0747 2023/03/11 07:45:40 - mmengine - INFO - Epoch(train) [2][1160/2226] lr: 3.5299e-07 eta: 11:54:46 time: 0.7917 data_time: 0.0084 memory: 70046 grad_norm: 0.1233 loss: 0.0704 recall@thr=0.5: 0.9091 prec@thr=0.5: 0.9697 recall@top3: 1.0000 prec@top3: 0.7879 recall@top5: 1.0000 prec@top5: 0.4727 loss_action_cls: 0.0704 2023/03/11 07:46:06 - mmengine - INFO - Epoch(train) [2][1180/2226] lr: 3.5452e-07 eta: 11:55:29 time: 1.3068 data_time: 0.0101 memory: 70046 grad_norm: 0.1318 loss: 0.0867 recall@thr=0.5: 0.3258 prec@thr=0.5: 0.5606 recall@top3: 0.6591 prec@top3: 0.6364 recall@top5: 0.8939 prec@top5: 0.5273 loss_action_cls: 0.0867 2023/03/11 07:46:25 - mmengine - INFO - Epoch(train) [2][1200/2226] lr: 3.5605e-07 eta: 11:54:50 time: 0.9684 data_time: 0.0096 memory: 70046 grad_norm: 0.1291 loss: 0.0684 recall@thr=0.5: 0.9583 prec@thr=0.5: 0.8889 recall@top3: 0.9167 prec@top3: 0.8611 recall@top5: 1.0000 prec@top5: 0.5833 loss_action_cls: 0.0684 2023/03/11 07:46:43 - mmengine - INFO - Epoch(train) [2][1220/2226] lr: 3.5757e-07 eta: 11:53:44 time: 0.8560 data_time: 0.0097 memory: 70046 grad_norm: 0.1229 loss: 0.0649 recall@thr=0.5: 0.3182 prec@thr=0.5: 0.4091 recall@top3: 0.5909 prec@top3: 0.3333 recall@top5: 0.9091 prec@top5: 0.2909 loss_action_cls: 0.0649 2023/03/11 07:46:57 - mmengine - INFO - Epoch(train) [2][1240/2226] lr: 3.5910e-07 eta: 11:52:06 time: 0.7184 data_time: 0.0094 memory: 70046 grad_norm: 0.1303 loss: 0.0719 recall@thr=0.5: 0.7333 prec@thr=0.5: 0.6917 recall@top3: 0.8000 prec@top3: 0.8000 recall@top5: 0.9500 prec@top5: 0.5800 loss_action_cls: 0.0719 2023/03/11 07:47:15 - mmengine - INFO - Epoch(train) [2][1260/2226] lr: 3.6063e-07 eta: 11:51:19 time: 0.9264 data_time: 0.0093 memory: 70046 grad_norm: 0.1236 loss: 0.0569 recall@thr=0.5: 0.4815 prec@thr=0.5: 0.5556 recall@top3: 0.6111 prec@top3: 0.4444 recall@top5: 0.7778 prec@top5: 0.3333 loss_action_cls: 0.0569 2023/03/11 07:47:30 - mmengine - INFO - Epoch(train) [2][1280/2226] lr: 3.6216e-07 eta: 11:49:48 time: 0.7404 data_time: 0.0079 memory: 70046 grad_norm: 0.1240 loss: 0.0763 recall@thr=0.5: 0.7515 prec@thr=0.5: 0.8333 recall@top3: 0.8061 prec@top3: 0.6364 recall@top5: 0.9212 prec@top5: 0.4727 loss_action_cls: 0.0763 2023/03/11 07:47:48 - mmengine - INFO - Epoch(train) [2][1300/2226] lr: 3.6368e-07 eta: 11:48:53 time: 0.8912 data_time: 0.0119 memory: 70046 grad_norm: 0.1186 loss: 0.0814 recall@thr=0.5: 0.5370 prec@thr=0.5: 0.7407 recall@top3: 0.8056 prec@top3: 0.6667 recall@top5: 0.9444 prec@top5: 0.4667 loss_action_cls: 0.0814 2023/03/11 07:48:05 - mmengine - INFO - Epoch(train) [2][1320/2226] lr: 3.6521e-07 eta: 11:47:45 time: 0.8333 data_time: 0.0083 memory: 70046 grad_norm: 0.1274 loss: 0.0665 recall@thr=0.5: 0.8889 prec@thr=0.5: 0.7778 recall@top3: 0.8889 prec@top3: 0.7037 recall@top5: 1.0000 prec@top5: 0.4444 loss_action_cls: 0.0665 2023/03/11 07:48:20 - mmengine - INFO - Epoch(train) [2][1340/2226] lr: 3.6674e-07 eta: 11:46:25 time: 0.7778 data_time: 0.0093 memory: 70046 grad_norm: 0.1222 loss: 0.0882 recall@thr=0.5: 0.4314 prec@thr=0.5: 0.4706 recall@top3: 0.5882 prec@top3: 0.4706 recall@top5: 0.7843 prec@top5: 0.3765 loss_action_cls: 0.0882 2023/03/11 07:48:36 - mmengine - INFO - Epoch(train) [2][1360/2226] lr: 3.6827e-07 eta: 11:45:02 time: 0.7645 data_time: 0.0095 memory: 70046 grad_norm: 0.1237 loss: 0.1083 recall@thr=0.5: 0.5333 prec@thr=0.5: 0.6000 recall@top3: 0.7333 prec@top3: 0.6333 recall@top5: 0.9333 prec@top5: 0.4800 loss_action_cls: 0.1083 2023/03/11 07:48:56 - mmengine - INFO - Epoch(train) [2][1380/2226] lr: 3.6979e-07 eta: 11:44:41 time: 1.0323 data_time: 0.0097 memory: 70046 grad_norm: 0.1242 loss: 0.0947 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.7778 recall@top3: 0.8889 prec@top3: 0.7037 recall@top5: 0.8889 prec@top5: 0.4222 loss_action_cls: 0.0947 2023/03/11 07:49:17 - mmengine - INFO - Epoch(train) [2][1400/2226] lr: 3.7132e-07 eta: 11:44:26 time: 1.0599 data_time: 0.0125 memory: 70046 grad_norm: 0.1225 loss: 0.0846 recall@thr=0.5: 0.4103 prec@thr=0.5: 0.3718 recall@top3: 0.7179 prec@top3: 0.4872 recall@top5: 0.8718 prec@top5: 0.3692 loss_action_cls: 0.0846 2023/03/11 07:49:39 - mmengine - INFO - Epoch(train) [2][1420/2226] lr: 3.7285e-07 eta: 11:44:16 time: 1.0770 data_time: 0.0098 memory: 70046 grad_norm: 0.1274 loss: 0.0765 recall@thr=0.5: 0.1750 prec@thr=0.5: 0.2500 recall@top3: 0.5542 prec@top3: 0.6250 recall@top5: 0.7458 prec@top5: 0.5000 loss_action_cls: 0.0765 2023/03/11 07:49:59 - mmengine - INFO - Epoch(train) [2][1440/2226] lr: 3.7438e-07 eta: 11:43:49 time: 1.0074 data_time: 0.0083 memory: 70046 grad_norm: 0.1220 loss: 0.1140 recall@thr=0.5: 0.6458 prec@thr=0.5: 0.6875 recall@top3: 0.8125 prec@top3: 0.6667 recall@top5: 0.8125 prec@top5: 0.4000 loss_action_cls: 0.1140 2023/03/11 07:50:18 - mmengine - INFO - Epoch(train) [2][1460/2226] lr: 3.7591e-07 eta: 11:43:07 time: 0.9370 data_time: 0.0091 memory: 70046 grad_norm: 0.1213 loss: 0.1137 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8056 recall@top3: 0.9167 prec@top3: 0.5000 recall@top5: 0.9167 prec@top5: 0.3000 loss_action_cls: 0.1137 2023/03/11 07:50:40 - mmengine - INFO - Epoch(train) [2][1480/2226] lr: 3.7743e-07 eta: 11:42:59 time: 1.0895 data_time: 0.0100 memory: 70046 grad_norm: 0.1204 loss: 0.1005 recall@thr=0.5: 0.0500 prec@thr=0.5: 0.1000 recall@top3: 0.6500 prec@top3: 0.4000 recall@top5: 0.9000 prec@top5: 0.3200 loss_action_cls: 0.1005 2023/03/11 07:51:01 - mmengine - INFO - Epoch(train) [2][1500/2226] lr: 3.7896e-07 eta: 11:42:49 time: 1.0842 data_time: 0.0102 memory: 70046 grad_norm: 0.1256 loss: 0.0760 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.9000 recall@top3: 0.8083 prec@top3: 0.8333 recall@top5: 0.9667 prec@top5: 0.6400 loss_action_cls: 0.0760 2023/03/11 07:51:21 - mmengine - INFO - Epoch(train) [2][1520/2226] lr: 3.8049e-07 eta: 11:42:23 time: 1.0068 data_time: 0.0096 memory: 70046 grad_norm: 0.1217 loss: 0.0670 recall@thr=0.5: 1.0000 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.8333 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0670 2023/03/11 07:51:39 - mmengine - INFO - Epoch(train) [2][1540/2226] lr: 3.8202e-07 eta: 11:41:30 time: 0.8874 data_time: 0.0087 memory: 70046 grad_norm: 0.1250 loss: 0.0757 recall@thr=0.5: 0.4833 prec@thr=0.5: 0.7000 recall@top3: 0.9500 prec@top3: 0.6667 recall@top5: 0.9500 prec@top5: 0.4000 loss_action_cls: 0.0757 2023/03/11 07:52:01 - mmengine - INFO - Epoch(train) [2][1560/2226] lr: 3.8354e-07 eta: 11:41:24 time: 1.1006 data_time: 0.0104 memory: 70046 grad_norm: 0.1201 loss: 0.0575 recall@thr=0.5: 0.5278 prec@thr=0.5: 0.5833 recall@top3: 0.8333 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3000 loss_action_cls: 0.0575 2023/03/11 07:52:22 - mmengine - INFO - Epoch(train) [2][1580/2226] lr: 3.8507e-07 eta: 11:41:00 time: 1.0154 data_time: 0.0146 memory: 70046 grad_norm: 0.1251 loss: 0.0861 recall@thr=0.5: 0.5500 prec@thr=0.5: 0.7000 recall@top3: 0.9167 prec@top3: 0.8000 recall@top5: 0.9500 prec@top5: 0.5000 loss_action_cls: 0.0861 2023/03/11 07:52:45 - mmengine - INFO - Epoch(train) [2][1600/2226] lr: 3.8660e-07 eta: 11:41:09 time: 1.1748 data_time: 0.0105 memory: 70046 grad_norm: 0.1291 loss: 0.1105 recall@thr=0.5: 0.5357 prec@thr=0.5: 0.6667 recall@top3: 0.7500 prec@top3: 0.5238 recall@top5: 0.8571 prec@top5: 0.3714 loss_action_cls: 0.1105 2023/03/11 07:53:05 - mmengine - INFO - Epoch(train) [2][1620/2226] lr: 3.8813e-07 eta: 11:40:43 time: 1.0069 data_time: 0.0112 memory: 70046 grad_norm: 0.1226 loss: 0.0717 recall@thr=0.5: 0.9286 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0717 2023/03/11 07:53:25 - mmengine - INFO - Epoch(train) [2][1640/2226] lr: 3.8965e-07 eta: 11:40:08 time: 0.9686 data_time: 0.0099 memory: 70046 grad_norm: 0.1268 loss: 0.0854 recall@thr=0.5: 0.4872 prec@thr=0.5: 0.5641 recall@top3: 0.5769 prec@top3: 0.3590 recall@top5: 0.7179 prec@top5: 0.2923 loss_action_cls: 0.0854 2023/03/11 07:53:45 - mmengine - INFO - Epoch(train) [2][1660/2226] lr: 3.9118e-07 eta: 11:39:43 time: 1.0112 data_time: 0.0120 memory: 70046 grad_norm: 0.1310 loss: 0.0761 recall@thr=0.5: 0.6944 prec@thr=0.5: 0.9074 recall@top3: 0.8426 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.5778 loss_action_cls: 0.0761 2023/03/11 07:54:05 - mmengine - INFO - Epoch(train) [2][1680/2226] lr: 3.9271e-07 eta: 11:39:21 time: 1.0271 data_time: 0.0091 memory: 70046 grad_norm: 0.1258 loss: 0.0665 recall@thr=0.5: 0.3667 prec@thr=0.5: 0.5667 recall@top3: 0.7000 prec@top3: 0.6333 recall@top5: 0.8667 prec@top5: 0.4800 loss_action_cls: 0.0665 2023/03/11 07:54:25 - mmengine - INFO - Epoch(train) [2][1700/2226] lr: 3.9424e-07 eta: 11:38:55 time: 1.0065 data_time: 0.0106 memory: 70046 grad_norm: 0.1256 loss: 0.0874 recall@thr=0.5: 0.8333 prec@thr=0.5: 1.0000 recall@top3: 0.8704 prec@top3: 0.6296 recall@top5: 1.0000 prec@top5: 0.4444 loss_action_cls: 0.0874 2023/03/11 07:54:45 - mmengine - INFO - Epoch(train) [2][1720/2226] lr: 3.9576e-07 eta: 11:38:25 time: 0.9892 data_time: 0.0104 memory: 70046 grad_norm: 0.1245 loss: 0.0772 recall@thr=0.5: 0.7879 prec@thr=0.5: 0.9091 recall@top3: 0.9394 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4364 loss_action_cls: 0.0772 2023/03/11 07:55:08 - mmengine - INFO - Epoch(train) [2][1740/2226] lr: 3.9729e-07 eta: 11:38:26 time: 1.1353 data_time: 0.0111 memory: 70046 grad_norm: 0.1229 loss: 0.0727 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6250 recall@top3: 0.6250 prec@top3: 0.3889 recall@top5: 0.7917 prec@top5: 0.2833 loss_action_cls: 0.0727 2023/03/11 07:55:29 - mmengine - INFO - Epoch(train) [2][1760/2226] lr: 3.9882e-07 eta: 11:38:06 time: 1.0394 data_time: 0.0082 memory: 70046 grad_norm: 0.1324 loss: 0.0512 recall@thr=0.5: 0.6979 prec@thr=0.5: 0.7187 recall@top3: 0.6458 prec@top3: 0.4167 recall@top5: 0.7917 prec@top5: 0.3500 loss_action_cls: 0.0512 2023/03/11 07:55:43 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 07:55:49 - mmengine - INFO - Epoch(train) [2][1780/2226] lr: 4.0035e-07 eta: 11:37:37 time: 0.9916 data_time: 0.0105 memory: 70046 grad_norm: 0.1289 loss: 0.0773 recall@thr=0.5: 0.5500 prec@thr=0.5: 0.4600 recall@top3: 0.7000 prec@top3: 0.6000 recall@top5: 0.9500 prec@top5: 0.5000 loss_action_cls: 0.0773 2023/03/11 07:56:11 - mmengine - INFO - Epoch(train) [2][1800/2226] lr: 4.0187e-07 eta: 11:37:33 time: 1.1145 data_time: 0.0092 memory: 70046 grad_norm: 0.1266 loss: 0.0925 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.5417 recall@top3: 0.8125 prec@top3: 0.6667 recall@top5: 0.8125 prec@top5: 0.4000 loss_action_cls: 0.0925 2023/03/11 07:56:31 - mmengine - INFO - Epoch(train) [2][1820/2226] lr: 4.0340e-07 eta: 11:37:09 time: 1.0169 data_time: 0.0096 memory: 70046 grad_norm: 0.1249 loss: 0.0926 recall@thr=0.5: 0.4167 prec@thr=0.5: 0.5556 recall@top3: 0.6667 prec@top3: 0.5556 recall@top5: 0.8889 prec@top5: 0.4333 loss_action_cls: 0.0926 2023/03/11 07:56:52 - mmengine - INFO - Epoch(train) [2][1840/2226] lr: 4.0493e-07 eta: 11:36:47 time: 1.0268 data_time: 0.0111 memory: 70046 grad_norm: 0.1296 loss: 0.0728 recall@thr=0.5: 0.6759 prec@thr=0.5: 0.7778 recall@top3: 0.8611 prec@top3: 0.6667 recall@top5: 0.8611 prec@top5: 0.4000 loss_action_cls: 0.0728 2023/03/11 07:57:12 - mmengine - INFO - Epoch(train) [2][1860/2226] lr: 4.0646e-07 eta: 11:36:20 time: 1.0003 data_time: 0.0090 memory: 70046 grad_norm: 0.1303 loss: 0.0886 recall@thr=0.5: 0.7762 prec@thr=0.5: 0.6250 recall@top3: 0.8310 prec@top3: 0.5238 recall@top5: 0.8976 prec@top5: 0.3714 loss_action_cls: 0.0886 2023/03/11 07:57:32 - mmengine - INFO - Epoch(train) [2][1880/2226] lr: 4.0798e-07 eta: 11:35:52 time: 0.9980 data_time: 0.0127 memory: 70046 grad_norm: 0.1246 loss: 0.0796 recall@thr=0.5: 0.6296 prec@thr=0.5: 0.5926 recall@top3: 0.7037 prec@top3: 0.4815 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0796 2023/03/11 07:57:55 - mmengine - INFO - Epoch(train) [2][1900/2226] lr: 4.0951e-07 eta: 11:35:53 time: 1.1462 data_time: 0.0097 memory: 70046 grad_norm: 0.1232 loss: 0.0725 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.7778 recall@top3: 0.8889 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.3556 loss_action_cls: 0.0725 2023/03/11 07:58:13 - mmengine - INFO - Epoch(train) [2][1920/2226] lr: 4.1104e-07 eta: 11:35:10 time: 0.9147 data_time: 0.0116 memory: 70046 grad_norm: 0.1219 loss: 0.0764 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.7143 recall@top3: 0.7381 prec@top3: 0.6190 recall@top5: 1.0000 prec@top5: 0.5143 loss_action_cls: 0.0764 2023/03/11 07:58:35 - mmengine - INFO - Epoch(train) [2][1940/2226] lr: 4.1257e-07 eta: 11:35:00 time: 1.0885 data_time: 0.0106 memory: 70046 grad_norm: 0.1212 loss: 0.0813 recall@thr=0.5: 0.6852 prec@thr=0.5: 0.8519 recall@top3: 0.7593 prec@top3: 0.6296 recall@top5: 0.8889 prec@top5: 0.4667 loss_action_cls: 0.0813 2023/03/11 07:58:54 - mmengine - INFO - Epoch(train) [2][1960/2226] lr: 4.1409e-07 eta: 11:34:25 time: 0.9622 data_time: 0.0100 memory: 70046 grad_norm: 0.1244 loss: 0.0886 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8333 recall@top3: 0.8333 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3000 loss_action_cls: 0.0886 2023/03/11 07:59:14 - mmengine - INFO - Epoch(train) [2][1980/2226] lr: 4.1562e-07 eta: 11:33:56 time: 0.9888 data_time: 0.0108 memory: 70046 grad_norm: 0.1191 loss: 0.0983 recall@thr=0.5: 0.8056 prec@thr=0.5: 0.8889 recall@top3: 0.8426 prec@top3: 0.8519 recall@top5: 0.9444 prec@top5: 0.5778 loss_action_cls: 0.0983 2023/03/11 07:59:35 - mmengine - INFO - Epoch(train) [2][2000/2226] lr: 4.1715e-07 eta: 11:33:40 time: 1.0580 data_time: 0.0109 memory: 70046 grad_norm: 0.1221 loss: 0.0657 recall@thr=0.5: 0.7963 prec@thr=0.5: 0.9444 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 0.9444 prec@top5: 0.4667 loss_action_cls: 0.0657 2023/03/11 07:59:56 - mmengine - INFO - Epoch(train) [2][2020/2226] lr: 4.1868e-07 eta: 11:33:20 time: 1.0342 data_time: 0.0106 memory: 70046 grad_norm: 0.1227 loss: 0.0583 recall@thr=0.5: 0.8222 prec@thr=0.5: 0.5741 recall@top3: 0.8222 prec@top3: 0.4074 recall@top5: 0.9111 prec@top5: 0.3333 loss_action_cls: 0.0583 2023/03/11 08:00:17 - mmengine - INFO - Epoch(train) [2][2040/2226] lr: 4.2021e-07 eta: 11:33:11 time: 1.0961 data_time: 0.0104 memory: 70046 grad_norm: 0.1221 loss: 0.0880 recall@thr=0.5: 0.5897 prec@thr=0.5: 0.7179 recall@top3: 0.6795 prec@top3: 0.5897 recall@top5: 0.8269 prec@top5: 0.4308 loss_action_cls: 0.0880 2023/03/11 08:00:38 - mmengine - INFO - Epoch(train) [2][2060/2226] lr: 4.2173e-07 eta: 11:32:52 time: 1.0426 data_time: 0.0103 memory: 70046 grad_norm: 0.1254 loss: 0.0501 recall@thr=0.5: 0.4074 prec@thr=0.5: 0.4074 recall@top3: 0.7407 prec@top3: 0.3704 recall@top5: 0.8148 prec@top5: 0.2667 loss_action_cls: 0.0501 2023/03/11 08:00:59 - mmengine - INFO - Epoch(train) [2][2080/2226] lr: 4.2326e-07 eta: 11:32:34 time: 1.0471 data_time: 0.0085 memory: 70046 grad_norm: 0.1223 loss: 0.0694 recall@thr=0.5: 0.7315 prec@thr=0.5: 0.9259 recall@top3: 0.8426 prec@top3: 0.8519 recall@top5: 1.0000 prec@top5: 0.6222 loss_action_cls: 0.0694 2023/03/11 08:01:19 - mmengine - INFO - Epoch(train) [2][2100/2226] lr: 4.2479e-07 eta: 11:32:01 time: 0.9655 data_time: 0.0088 memory: 70046 grad_norm: 0.1260 loss: 0.0808 recall@thr=0.5: 0.6042 prec@thr=0.5: 0.6875 recall@top3: 0.7917 prec@top3: 0.5000 recall@top5: 0.9375 prec@top5: 0.3750 loss_action_cls: 0.0808 2023/03/11 08:01:37 - mmengine - INFO - Epoch(train) [2][2120/2226] lr: 4.2632e-07 eta: 11:31:22 time: 0.9319 data_time: 0.0107 memory: 70046 grad_norm: 0.1218 loss: 0.0731 recall@thr=0.5: 0.5926 prec@thr=0.5: 0.7407 recall@top3: 0.8148 prec@top3: 0.7407 recall@top5: 0.9352 prec@top5: 0.5333 loss_action_cls: 0.0731 2023/03/11 08:01:59 - mmengine - INFO - Epoch(train) [2][2140/2226] lr: 4.2784e-07 eta: 11:31:16 time: 1.1136 data_time: 0.0110 memory: 70046 grad_norm: 0.1312 loss: 0.0901 recall@thr=0.5: 0.4167 prec@thr=0.5: 0.7222 recall@top3: 0.7500 prec@top3: 0.6667 recall@top5: 0.9167 prec@top5: 0.4833 loss_action_cls: 0.0901 2023/03/11 08:02:18 - mmengine - INFO - Epoch(train) [2][2160/2226] lr: 4.2937e-07 eta: 11:30:33 time: 0.9116 data_time: 0.0095 memory: 70046 grad_norm: 0.1217 loss: 0.0676 recall@thr=0.5: 0.8846 prec@thr=0.5: 0.9231 recall@top3: 0.9231 prec@top3: 0.7949 recall@top5: 1.0000 prec@top5: 0.4923 loss_action_cls: 0.0676 2023/03/11 08:02:39 - mmengine - INFO - Epoch(train) [2][2180/2226] lr: 4.3090e-07 eta: 11:30:21 time: 1.0790 data_time: 0.0105 memory: 70046 grad_norm: 0.1214 loss: 0.0626 recall@thr=0.5: 0.3485 prec@thr=0.5: 0.4545 recall@top3: 0.4545 prec@top3: 0.3030 recall@top5: 0.4545 prec@top5: 0.1818 loss_action_cls: 0.0626 2023/03/11 08:03:02 - mmengine - INFO - Epoch(train) [2][2200/2226] lr: 4.3243e-07 eta: 11:30:19 time: 1.1377 data_time: 0.0131 memory: 70046 grad_norm: 0.1169 loss: 0.0668 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.7917 recall@top3: 1.0000 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.3500 loss_action_cls: 0.0668 2023/03/11 08:03:19 - mmengine - INFO - Epoch(train) [2][2220/2226] lr: 4.3395e-07 eta: 11:29:22 time: 0.8277 data_time: 0.0128 memory: 70046 grad_norm: 0.1222 loss: 0.0539 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.5417 recall@top3: 0.7500 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3333 loss_action_cls: 0.0539 2023/03/11 08:03:22 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 08:03:22 - mmengine - INFO - Epoch(train) [2][2226/2226] lr: 4.3441e-07 eta: 11:28:54 time: 0.7605 data_time: 0.0080 memory: 70046 grad_norm: 0.1286 loss: 0.0571 recall@thr=0.5: 0.1667 prec@thr=0.5: 0.5000 recall@top3: 0.1667 prec@top3: 0.1667 recall@top5: 0.8333 prec@top5: 0.3000 loss_action_cls: 0.0571 2023/03/11 08:03:22 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/03/11 08:03:38 - mmengine - INFO - Epoch(val) [2][ 20/1571] eta: 0:05:29 time: 0.2126 data_time: 0.1222 memory: 6688 2023/03/11 08:03:41 - mmengine - INFO - Epoch(val) [2][ 40/1571] eta: 0:04:48 time: 0.1648 data_time: 0.0416 memory: 7490 2023/03/11 08:03:45 - mmengine - INFO - Epoch(val) [2][ 60/1571] eta: 0:04:35 time: 0.1706 data_time: 0.0507 memory: 7490 2023/03/11 08:03:48 - mmengine - INFO - Epoch(val) [2][ 80/1571] eta: 0:04:33 time: 0.1848 data_time: 0.0717 memory: 7490 2023/03/11 08:03:52 - mmengine - INFO - Epoch(val) [2][ 100/1571] eta: 0:04:25 time: 0.1707 data_time: 0.0434 memory: 7490 2023/03/11 08:03:55 - mmengine - INFO - Epoch(val) [2][ 120/1571] eta: 0:04:13 time: 0.1427 data_time: 0.0418 memory: 6775 2023/03/11 08:03:58 - mmengine - INFO - Epoch(val) [2][ 140/1571] eta: 0:04:06 time: 0.1596 data_time: 0.0623 memory: 6775 2023/03/11 08:04:01 - mmengine - INFO - Epoch(val) [2][ 160/1571] eta: 0:04:02 time: 0.1666 data_time: 0.0656 memory: 6775 2023/03/11 08:04:05 - mmengine - INFO - Epoch(val) [2][ 180/1571] eta: 0:04:05 time: 0.2154 data_time: 0.1102 memory: 7490 2023/03/11 08:04:10 - mmengine - INFO - Epoch(val) [2][ 200/1571] eta: 0:04:06 time: 0.2135 data_time: 0.0762 memory: 7490 2023/03/11 08:04:13 - mmengine - INFO - Epoch(val) [2][ 220/1571] eta: 0:04:02 time: 0.1699 data_time: 0.0707 memory: 7490 2023/03/11 08:04:16 - mmengine - INFO - Epoch(val) [2][ 240/1571] eta: 0:03:56 time: 0.1631 data_time: 0.0699 memory: 6775 2023/03/11 08:04:20 - mmengine - INFO - Epoch(val) [2][ 260/1571] eta: 0:03:51 time: 0.1617 data_time: 0.0723 memory: 6775 2023/03/11 08:04:22 - mmengine - INFO - Epoch(val) [2][ 280/1571] eta: 0:03:44 time: 0.1399 data_time: 0.0427 memory: 6775 2023/03/11 08:04:26 - mmengine - INFO - Epoch(val) [2][ 300/1571] eta: 0:03:40 time: 0.1674 data_time: 0.0668 memory: 6775 2023/03/11 08:04:30 - mmengine - INFO - Epoch(val) [2][ 320/1571] eta: 0:03:39 time: 0.1990 data_time: 0.0698 memory: 7490 2023/03/11 08:04:34 - mmengine - INFO - Epoch(val) [2][ 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data_time: 0.0754 memory: 7490 2023/03/11 08:06:02 - mmengine - INFO - Epoch(val) [2][ 840/1571] eta: 0:02:08 time: 0.1690 data_time: 0.0334 memory: 7490 2023/03/11 08:06:05 - mmengine - INFO - Epoch(val) [2][ 860/1571] eta: 0:02:05 time: 0.1793 data_time: 0.0770 memory: 7490 2023/03/11 08:06:09 - mmengine - INFO - Epoch(val) [2][ 880/1571] eta: 0:02:01 time: 0.1568 data_time: 0.0628 memory: 6775 2023/03/11 08:06:12 - mmengine - INFO - Epoch(val) [2][ 900/1571] eta: 0:01:58 time: 0.1779 data_time: 0.0769 memory: 7266 2023/03/11 08:06:16 - mmengine - INFO - Epoch(val) [2][ 920/1571] eta: 0:01:55 time: 0.2141 data_time: 0.0918 memory: 7490 2023/03/11 08:06:21 - mmengine - INFO - Epoch(val) [2][ 940/1571] eta: 0:01:52 time: 0.2255 data_time: 0.0860 memory: 7490 2023/03/11 08:06:25 - mmengine - INFO - Epoch(val) [2][ 960/1571] eta: 0:01:48 time: 0.1819 data_time: 0.0423 memory: 7490 2023/03/11 08:06:29 - mmengine - INFO - Epoch(val) [2][ 980/1571] eta: 0:01:45 time: 0.1997 data_time: 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7610 2023/03/11 08:07:00 - mmengine - INFO - Epoch(val) [2][1160/1571] eta: 0:01:13 time: 0.1777 data_time: 0.0618 memory: 7610 2023/03/11 08:07:04 - mmengine - INFO - Epoch(val) [2][1180/1571] eta: 0:01:09 time: 0.1840 data_time: 0.0403 memory: 7610 2023/03/11 08:07:07 - mmengine - INFO - Epoch(val) [2][1200/1571] eta: 0:01:06 time: 0.1584 data_time: 0.0525 memory: 7057 2023/03/11 08:07:11 - mmengine - INFO - Epoch(val) [2][1220/1571] eta: 0:01:02 time: 0.1931 data_time: 0.0562 memory: 7490 2023/03/11 08:07:15 - mmengine - INFO - Epoch(val) [2][1240/1571] eta: 0:00:59 time: 0.1828 data_time: 0.0439 memory: 7490 2023/03/11 08:07:19 - mmengine - INFO - Epoch(val) [2][1260/1571] eta: 0:00:55 time: 0.2013 data_time: 0.0762 memory: 7490 2023/03/11 08:07:22 - mmengine - INFO - Epoch(val) [2][1280/1571] eta: 0:00:51 time: 0.1756 data_time: 0.0830 memory: 6775 2023/03/11 08:07:26 - mmengine - INFO - Epoch(val) [2][1300/1571] eta: 0:00:48 time: 0.1890 data_time: 0.0925 memory: 6775 2023/03/11 08:07:30 - mmengine - INFO - Epoch(val) [2][1320/1571] eta: 0:00:44 time: 0.1759 data_time: 0.0752 memory: 6775 2023/03/11 08:07:33 - mmengine - INFO - Epoch(val) [2][1340/1571] eta: 0:00:41 time: 0.1829 data_time: 0.0837 memory: 6775 2023/03/11 08:07:37 - mmengine - INFO - Epoch(val) [2][1360/1571] eta: 0:00:37 time: 0.1674 data_time: 0.0589 memory: 6775 2023/03/11 08:07:41 - mmengine - INFO - Epoch(val) [2][1380/1571] eta: 0:00:34 time: 0.2060 data_time: 0.1097 memory: 7057 2023/03/11 08:07:44 - mmengine - INFO - Epoch(val) [2][1400/1571] eta: 0:00:30 time: 0.1749 data_time: 0.0613 memory: 7057 2023/03/11 08:07:48 - mmengine - INFO - Epoch(val) [2][1420/1571] eta: 0:00:27 time: 0.1980 data_time: 0.1043 memory: 7057 2023/03/11 08:07:51 - mmengine - INFO - Epoch(val) [2][1440/1571] eta: 0:00:23 time: 0.1622 data_time: 0.0561 memory: 7160 2023/03/11 08:07:55 - mmengine - INFO - Epoch(val) [2][1460/1571] eta: 0:00:19 time: 0.1901 data_time: 0.0754 memory: 7160 2023/03/11 08:07:59 - mmengine - INFO - Epoch(val) [2][1480/1571] eta: 0:00:16 time: 0.1708 data_time: 0.0631 memory: 7057 2023/03/11 08:08:02 - mmengine - INFO - Epoch(val) [2][1500/1571] eta: 0:00:12 time: 0.1533 data_time: 0.0546 memory: 7490 2023/03/11 08:08:04 - mmengine - INFO - Epoch(val) [2][1520/1571] eta: 0:00:09 time: 0.1319 data_time: 0.0018 memory: 7490 2023/03/11 08:08:07 - mmengine - INFO - Epoch(val) [2][1540/1571] eta: 0:00:05 time: 0.1328 data_time: 0.0020 memory: 7490 2023/03/11 08:08:10 - mmengine - INFO - Epoch(val) [2][1560/1571] eta: 0:00:01 time: 0.1326 data_time: 0.0020 memory: 7490 2023/03/11 08:13:09 - mmengine - INFO - Epoch(val) [2][1571/1571] mAP/mAP@0.5IOU: 0.3247 2023/03/11 08:13:09 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/hukai/mmaction2/work_dirs/vit-l_16x4/best_mAP/mAP@0.5IOU_epoch_1.pth is removed 2023/03/11 08:13:14 - mmengine - INFO - The best checkpoint with 0.3247 mAP/mAP@0.5IOU at 2 epoch is saved to best_mAP/mAP@0.5IOU_epoch_2.pth. 2023/03/11 08:13:39 - mmengine - INFO - Epoch(train) [3][ 20/2226] lr: 4.3594e-07 eta: 11:29:14 time: 1.2613 data_time: 0.6130 memory: 70046 grad_norm: 0.1300 loss: 0.0828 recall@thr=0.5: 0.7619 prec@thr=0.5: 0.6905 recall@top3: 0.9048 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.3429 loss_action_cls: 0.0828 2023/03/11 08:13:57 - mmengine - INFO - Epoch(train) [3][ 40/2226] lr: 4.3747e-07 eta: 11:28:32 time: 0.9122 data_time: 0.2085 memory: 70046 grad_norm: 0.1207 loss: 0.0785 recall@thr=0.5: 0.8000 prec@thr=0.5: 0.8000 recall@top3: 1.0000 prec@top3: 0.5333 recall@top5: 1.0000 prec@top5: 0.3200 loss_action_cls: 0.0785 2023/03/11 08:14:21 - mmengine - INFO - Epoch(train) [3][ 60/2226] lr: 4.3899e-07 eta: 11:28:40 time: 1.1932 data_time: 0.0553 memory: 70046 grad_norm: 0.1249 loss: 0.0767 recall@thr=0.5: 0.7296 prec@thr=0.5: 0.7037 recall@top3: 0.7889 prec@top3: 0.5926 recall@top5: 0.9630 prec@top5: 0.4667 loss_action_cls: 0.0767 2023/03/11 08:14:42 - mmengine - INFO - Epoch(train) [3][ 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1.1264 data_time: 0.0099 memory: 70046 grad_norm: 0.1290 loss: 0.0516 recall@thr=0.5: 0.8148 prec@thr=0.5: 0.7778 recall@top3: 0.9630 prec@top3: 0.7407 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0516 2023/03/11 08:16:04 - mmengine - INFO - Epoch(train) [3][ 160/2226] lr: 4.4663e-07 eta: 11:26:50 time: 0.8733 data_time: 0.0101 memory: 70046 grad_norm: 0.1259 loss: 0.0674 recall@thr=0.5: 0.4792 prec@thr=0.5: 0.5000 recall@top3: 0.6458 prec@top3: 0.4167 recall@top5: 0.8750 prec@top5: 0.3750 loss_action_cls: 0.0674 2023/03/11 08:16:27 - mmengine - INFO - Epoch(train) [3][ 180/2226] lr: 4.4816e-07 eta: 11:26:51 time: 1.1560 data_time: 0.0127 memory: 70046 grad_norm: 0.1231 loss: 0.0620 recall@thr=0.5: 0.8519 prec@thr=0.5: 0.8148 recall@top3: 0.8889 prec@top3: 0.7407 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0620 2023/03/11 08:16:45 - mmengine - INFO - Epoch(train) [3][ 200/2226] lr: 4.4969e-07 eta: 11:26:08 time: 0.9023 data_time: 0.0090 memory: 70046 grad_norm: 0.1241 loss: 0.0859 recall@thr=0.5: 0.8095 prec@thr=0.5: 1.0000 recall@top3: 0.8571 prec@top3: 0.7143 recall@top5: 0.8571 prec@top5: 0.4286 loss_action_cls: 0.0859 2023/03/11 08:17:06 - mmengine - INFO - Epoch(train) [3][ 220/2226] lr: 4.5122e-07 eta: 11:25:53 time: 1.0637 data_time: 0.0103 memory: 70046 grad_norm: 0.1244 loss: 0.0550 recall@thr=0.5: 0.4792 prec@thr=0.5: 0.5000 recall@top3: 0.7708 prec@top3: 0.6250 recall@top5: 1.0000 prec@top5: 0.5250 loss_action_cls: 0.0550 2023/03/11 08:17:28 - mmengine - INFO - Epoch(train) [3][ 240/2226] lr: 4.5274e-07 eta: 11:25:39 time: 1.0742 data_time: 0.0124 memory: 70046 grad_norm: 0.1259 loss: 0.0716 recall@thr=0.5: 0.3000 prec@thr=0.5: 0.5000 recall@top3: 0.6500 prec@top3: 0.5667 recall@top5: 0.8167 prec@top5: 0.4200 loss_action_cls: 0.0716 2023/03/11 08:17:50 - mmengine - INFO - Epoch(train) [3][ 260/2226] lr: 4.5427e-07 eta: 11:25:35 time: 1.1320 data_time: 0.0096 memory: 70046 grad_norm: 0.1244 loss: 0.0750 recall@thr=0.5: 0.3125 prec@thr=0.5: 0.5000 recall@top3: 0.5000 prec@top3: 0.2917 recall@top5: 0.6875 prec@top5: 0.2500 loss_action_cls: 0.0750 2023/03/11 08:18:10 - mmengine - INFO - Epoch(train) [3][ 280/2226] lr: 4.5580e-07 eta: 11:25:02 time: 0.9596 data_time: 0.0090 memory: 70046 grad_norm: 0.1230 loss: 0.0639 recall@thr=0.5: 0.6296 prec@thr=0.5: 0.7407 recall@top3: 0.6667 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.5333 loss_action_cls: 0.0639 2023/03/11 08:18:30 - mmengine - INFO - Epoch(train) [3][ 300/2226] lr: 4.5733e-07 eta: 11:24:35 time: 0.9970 data_time: 0.0121 memory: 70046 grad_norm: 0.1233 loss: 0.0565 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.7917 recall@top3: 0.7917 prec@top3: 0.6667 recall@top5: 0.8333 prec@top5: 0.4250 loss_action_cls: 0.0565 2023/03/11 08:18:52 - mmengine - INFO - Epoch(train) [3][ 320/2226] lr: 4.5885e-07 eta: 11:24:28 time: 1.1125 data_time: 0.0117 memory: 70046 grad_norm: 0.1167 loss: 0.0748 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8417 recall@top3: 0.7375 prec@top3: 0.6000 recall@top5: 0.9250 prec@top5: 0.4400 loss_action_cls: 0.0748 2023/03/11 08:19:11 - mmengine - INFO - Epoch(train) [3][ 340/2226] lr: 4.6038e-07 eta: 11:23:55 time: 0.9618 data_time: 0.0095 memory: 70046 grad_norm: 0.1263 loss: 0.0649 recall@thr=0.5: 0.5778 prec@thr=0.5: 0.6889 recall@top3: 0.7556 prec@top3: 0.6444 recall@top5: 0.8778 prec@top5: 0.4533 loss_action_cls: 0.0649 2023/03/11 08:19:33 - mmengine - INFO - Epoch(train) [3][ 360/2226] lr: 4.6191e-07 eta: 11:23:48 time: 1.1163 data_time: 0.0126 memory: 70046 grad_norm: 0.1165 loss: 0.0806 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8889 recall@top3: 0.8889 prec@top3: 0.4815 recall@top5: 1.0000 prec@top5: 0.3333 loss_action_cls: 0.0806 2023/03/11 08:19:53 - mmengine - INFO - Epoch(train) [3][ 380/2226] lr: 4.6344e-07 eta: 11:23:22 time: 0.9977 data_time: 0.0101 memory: 70046 grad_norm: 0.1189 loss: 0.0603 recall@thr=0.5: 0.8182 prec@thr=0.5: 0.7424 recall@top3: 0.7576 prec@top3: 0.5152 recall@top5: 1.0000 prec@top5: 0.4545 loss_action_cls: 0.0603 2023/03/11 08:20:16 - mmengine - INFO - Epoch(train) [3][ 400/2226] lr: 4.6496e-07 eta: 11:23:13 time: 1.1074 data_time: 0.0098 memory: 70046 grad_norm: 0.1243 loss: 0.1015 recall@thr=0.5: 0.6296 prec@thr=0.5: 0.7315 recall@top3: 0.7639 prec@top3: 0.7963 recall@top5: 0.9074 prec@top5: 0.5889 loss_action_cls: 0.1015 2023/03/11 08:20:35 - mmengine - INFO - Epoch(train) [3][ 420/2226] lr: 4.6649e-07 eta: 11:22:46 time: 0.9900 data_time: 0.0077 memory: 70046 grad_norm: 0.1191 loss: 0.0619 recall@thr=0.5: 0.9545 prec@thr=0.5: 0.8333 recall@top3: 1.0000 prec@top3: 0.5455 recall@top5: 1.0000 prec@top5: 0.3273 loss_action_cls: 0.0619 2023/03/11 08:20:56 - mmengine - INFO - Epoch(train) [3][ 440/2226] lr: 4.6802e-07 eta: 11:22:21 time: 1.0108 data_time: 0.0092 memory: 70046 grad_norm: 0.1222 loss: 0.0906 recall@thr=0.5: 0.5926 prec@thr=0.5: 0.7963 recall@top3: 0.7407 prec@top3: 0.5926 recall@top5: 0.8889 prec@top5: 0.4222 loss_action_cls: 0.0906 2023/03/11 08:21:15 - mmengine - INFO - Epoch(train) [3][ 460/2226] lr: 4.6955e-07 eta: 11:21:54 time: 0.9903 data_time: 0.0098 memory: 70046 grad_norm: 0.1202 loss: 0.0820 recall@thr=0.5: 0.5583 prec@thr=0.5: 0.9750 recall@top3: 0.7750 prec@top3: 0.7333 recall@top5: 0.8750 prec@top5: 0.4800 loss_action_cls: 0.0820 2023/03/11 08:21:34 - mmengine - INFO - Epoch(train) [3][ 480/2226] lr: 4.7107e-07 eta: 11:21:15 time: 0.9172 data_time: 0.0104 memory: 70046 grad_norm: 0.1243 loss: 0.0838 recall@thr=0.5: 0.5714 prec@thr=0.5: 0.7143 recall@top3: 0.7143 prec@top3: 0.4762 recall@top5: 0.9286 prec@top5: 0.3714 loss_action_cls: 0.0838 2023/03/11 08:21:56 - mmengine - INFO - Epoch(train) [3][ 500/2226] lr: 4.7260e-07 eta: 11:21:05 time: 1.0997 data_time: 0.0132 memory: 70046 grad_norm: 0.1229 loss: 0.0930 recall@thr=0.5: 0.9375 prec@thr=0.5: 0.7500 recall@top3: 0.9375 prec@top3: 0.3750 recall@top5: 0.9375 prec@top5: 0.2250 loss_action_cls: 0.0930 2023/03/11 08:22:16 - mmengine - INFO - Epoch(train) [3][ 520/2226] lr: 4.7413e-07 eta: 11:20:41 time: 1.0154 data_time: 0.0098 memory: 70046 grad_norm: 0.1160 loss: 0.0558 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.7500 recall@top3: 0.7708 prec@top3: 0.5417 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0558 2023/03/11 08:22:37 - mmengine - INFO - Epoch(train) [3][ 540/2226] lr: 4.7566e-07 eta: 11:20:21 time: 1.0367 data_time: 0.0143 memory: 70046 grad_norm: 0.1254 loss: 0.0667 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.8333 recall@top3: 0.8542 prec@top3: 0.5833 recall@top5: 0.9375 prec@top5: 0.4000 loss_action_cls: 0.0667 2023/03/11 08:22:45 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 08:22:59 - mmengine - INFO - Epoch(train) [3][ 560/2226] lr: 4.7718e-07 eta: 11:20:17 time: 1.1347 data_time: 0.0088 memory: 70046 grad_norm: 0.1168 loss: 0.0425 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.7333 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 0.9333 prec@top5: 0.4400 loss_action_cls: 0.0425 2023/03/11 08:23:20 - mmengine - INFO - Epoch(train) [3][ 580/2226] lr: 4.7871e-07 eta: 11:19:56 time: 1.0313 data_time: 0.0072 memory: 70046 grad_norm: 0.1149 loss: 0.0691 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.6667 recall@top3: 0.8095 prec@top3: 0.7143 recall@top5: 0.8571 prec@top5: 0.4571 loss_action_cls: 0.0691 2023/03/11 08:23:38 - mmengine - INFO - Epoch(train) [3][ 600/2226] lr: 4.8024e-07 eta: 11:19:16 time: 0.9112 data_time: 0.0097 memory: 70046 grad_norm: 0.1251 loss: 0.0656 recall@thr=0.5: 0.6806 prec@thr=0.5: 0.8750 recall@top3: 0.8194 prec@top3: 0.7222 recall@top5: 0.9583 prec@top5: 0.5333 loss_action_cls: 0.0656 2023/03/11 08:24:01 - mmengine - INFO - Epoch(train) [3][ 620/2226] lr: 4.8177e-07 eta: 11:19:14 time: 1.1541 data_time: 0.0097 memory: 70046 grad_norm: 0.1168 loss: 0.0629 recall@thr=0.5: 0.7333 prec@thr=0.5: 0.7500 recall@top3: 0.8000 prec@top3: 0.7667 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0629 2023/03/11 08:24:20 - mmengine - INFO - Epoch(train) [3][ 640/2226] lr: 4.8329e-07 eta: 11:18:39 time: 0.9422 data_time: 0.0086 memory: 70046 grad_norm: 0.1248 loss: 0.0714 recall@thr=0.5: 0.6417 prec@thr=0.5: 0.7083 recall@top3: 0.6708 prec@top3: 0.6833 recall@top5: 0.8917 prec@top5: 0.5600 loss_action_cls: 0.0714 2023/03/11 08:24:42 - mmengine - INFO - Epoch(train) [3][ 660/2226] lr: 4.8482e-07 eta: 11:18:25 time: 1.0701 data_time: 0.0099 memory: 70046 grad_norm: 0.1238 loss: 0.0573 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.8571 recall@top3: 0.9286 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.3143 loss_action_cls: 0.0573 2023/03/11 08:25:02 - mmengine - INFO - Epoch(train) [3][ 680/2226] lr: 4.8635e-07 eta: 11:18:05 time: 1.0379 data_time: 0.0101 memory: 70046 grad_norm: 0.1219 loss: 0.0714 recall@thr=0.5: 0.7719 prec@thr=0.5: 0.7982 recall@top3: 0.8947 prec@top3: 0.6842 recall@top5: 0.9298 prec@top5: 0.4316 loss_action_cls: 0.0714 2023/03/11 08:25:23 - mmengine - INFO - Epoch(train) [3][ 700/2226] lr: 4.8788e-07 eta: 11:17:41 time: 1.0151 data_time: 0.0085 memory: 70046 grad_norm: 0.1161 loss: 0.0566 recall@thr=0.5: 0.9048 prec@thr=0.5: 1.0000 recall@top3: 0.9048 prec@top3: 0.5238 recall@top5: 1.0000 prec@top5: 0.3714 loss_action_cls: 0.0566 2023/03/11 08:25:42 - mmengine - INFO - Epoch(train) [3][ 720/2226] lr: 4.8941e-07 eta: 11:17:10 time: 0.9631 data_time: 0.0098 memory: 70046 grad_norm: 0.1210 loss: 0.0606 recall@thr=0.5: 0.5312 prec@thr=0.5: 0.6667 recall@top3: 0.6458 prec@top3: 0.5833 recall@top5: 0.9062 prec@top5: 0.4750 loss_action_cls: 0.0606 2023/03/11 08:26:02 - mmengine - INFO - Epoch(train) [3][ 740/2226] lr: 4.9093e-07 eta: 11:16:42 time: 0.9851 data_time: 0.0137 memory: 70046 grad_norm: 0.1209 loss: 0.0418 recall@thr=0.5: 0.6833 prec@thr=0.5: 0.9000 recall@top3: 0.8333 prec@top3: 0.5333 recall@top5: 0.9000 prec@top5: 0.3600 loss_action_cls: 0.0418 2023/03/11 08:26:25 - mmengine - INFO - Epoch(train) [3][ 760/2226] lr: 4.9246e-07 eta: 11:16:39 time: 1.1449 data_time: 0.0112 memory: 70046 grad_norm: 0.1209 loss: 0.0669 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.8571 recall@top3: 0.8452 prec@top3: 0.8095 recall@top5: 0.9286 prec@top5: 0.5429 loss_action_cls: 0.0669 2023/03/11 08:26:45 - mmengine - INFO - Epoch(train) [3][ 780/2226] lr: 4.9399e-07 eta: 11:16:14 time: 1.0044 data_time: 0.0113 memory: 70046 grad_norm: 0.1164 loss: 0.0640 recall@thr=0.5: 0.6905 prec@thr=0.5: 0.7857 recall@top3: 0.8929 prec@top3: 0.8571 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0640 2023/03/11 08:27:05 - mmengine - INFO - Epoch(train) [3][ 800/2226] lr: 4.9552e-07 eta: 11:15:50 time: 1.0150 data_time: 0.0115 memory: 70046 grad_norm: 0.1201 loss: 0.0696 recall@thr=0.5: 0.5185 prec@thr=0.5: 0.4815 recall@top3: 0.6759 prec@top3: 0.5185 recall@top5: 0.7778 prec@top5: 0.3778 loss_action_cls: 0.0696 2023/03/11 08:27:26 - mmengine - INFO - Epoch(train) [3][ 820/2226] lr: 4.9704e-07 eta: 11:15:35 time: 1.0661 data_time: 0.0107 memory: 70046 grad_norm: 0.1151 loss: 0.0598 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7500 recall@top3: 0.8056 prec@top3: 0.6944 recall@top5: 0.9306 prec@top5: 0.5000 loss_action_cls: 0.0598 2023/03/11 08:27:46 - mmengine - INFO - Epoch(train) [3][ 840/2226] lr: 4.9857e-07 eta: 11:15:06 time: 0.9818 data_time: 0.0081 memory: 70046 grad_norm: 0.1198 loss: 0.0701 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.8500 recall@top3: 0.9333 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4400 loss_action_cls: 0.0701 2023/03/11 08:28:08 - mmengine - INFO - Epoch(train) [3][ 860/2226] lr: 5.0010e-07 eta: 11:14:58 time: 1.1140 data_time: 0.0093 memory: 70046 grad_norm: 0.1213 loss: 0.0635 recall@thr=0.5: 0.6218 prec@thr=0.5: 0.6923 recall@top3: 0.8269 prec@top3: 0.6923 recall@top5: 0.9231 prec@top5: 0.4769 loss_action_cls: 0.0635 2023/03/11 08:28:24 - mmengine - INFO - Epoch(train) [3][ 880/2226] lr: 5.0163e-07 eta: 11:14:02 time: 0.7924 data_time: 0.0109 memory: 70046 grad_norm: 0.1113 loss: 0.0815 recall@thr=0.5: 0.6852 prec@thr=0.5: 0.6481 recall@top3: 0.7963 prec@top3: 0.6296 recall@top5: 0.8704 prec@top5: 0.4222 loss_action_cls: 0.0815 2023/03/11 08:28:46 - mmengine - INFO - Epoch(train) [3][ 900/2226] lr: 5.0315e-07 eta: 11:13:48 time: 1.0801 data_time: 0.0119 memory: 70046 grad_norm: 0.1174 loss: 0.0597 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.7083 recall@top3: 0.9722 prec@top3: 0.6389 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0597 2023/03/11 08:29:06 - mmengine - INFO - Epoch(train) [3][ 920/2226] lr: 5.0468e-07 eta: 11:13:27 time: 1.0321 data_time: 0.0119 memory: 70046 grad_norm: 0.1165 loss: 0.0607 recall@thr=0.5: 0.8519 prec@thr=0.5: 0.8889 recall@top3: 0.9259 prec@top3: 0.7037 recall@top5: 0.9259 prec@top5: 0.4222 loss_action_cls: 0.0607 2023/03/11 08:29:28 - mmengine - INFO - Epoch(train) [3][ 940/2226] lr: 5.0621e-07 eta: 11:13:15 time: 1.0875 data_time: 0.0100 memory: 70046 grad_norm: 0.1162 loss: 0.0630 recall@thr=0.5: 0.8500 prec@thr=0.5: 0.8000 recall@top3: 0.9000 prec@top3: 0.6000 recall@top5: 0.9500 prec@top5: 0.4000 loss_action_cls: 0.0630 2023/03/11 08:29:46 - mmengine - INFO - Epoch(train) [3][ 960/2226] lr: 5.0774e-07 eta: 11:12:33 time: 0.8862 data_time: 0.0123 memory: 70046 grad_norm: 0.1184 loss: 0.0723 recall@thr=0.5: 0.5741 prec@thr=0.5: 0.7222 recall@top3: 0.7593 prec@top3: 0.7407 recall@top5: 0.9259 prec@top5: 0.5556 loss_action_cls: 0.0723 2023/03/11 08:30:07 - mmengine - INFO - Epoch(train) [3][ 980/2226] lr: 5.0926e-07 eta: 11:12:16 time: 1.0551 data_time: 0.0121 memory: 70046 grad_norm: 0.1187 loss: 0.0560 recall@thr=0.5: 0.2564 prec@thr=0.5: 0.2821 recall@top3: 0.7949 prec@top3: 0.4615 recall@top5: 0.9487 prec@top5: 0.3538 loss_action_cls: 0.0560 2023/03/11 08:30:27 - mmengine - INFO - Epoch(train) [3][1000/2226] lr: 5.1079e-07 eta: 11:11:53 time: 1.0172 data_time: 0.0130 memory: 70046 grad_norm: 0.1180 loss: 0.0694 recall@thr=0.5: 0.7917 prec@thr=0.5: 1.0000 recall@top3: 0.8750 prec@top3: 0.9167 recall@top5: 0.9688 prec@top5: 0.6250 loss_action_cls: 0.0694 2023/03/11 08:30:49 - mmengine - INFO - Epoch(train) [3][1020/2226] lr: 5.1232e-07 eta: 11:11:45 time: 1.1168 data_time: 0.0129 memory: 70046 grad_norm: 0.1160 loss: 0.0679 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.9048 recall@top3: 0.8095 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.5714 loss_action_cls: 0.0679 2023/03/11 08:31:08 - mmengine - INFO - Epoch(train) [3][1040/2226] lr: 5.1385e-07 eta: 11:11:09 time: 0.9275 data_time: 0.0109 memory: 70046 grad_norm: 0.1180 loss: 0.0544 recall@thr=0.5: 0.8462 prec@thr=0.5: 0.7949 recall@top3: 0.8462 prec@top3: 0.4615 recall@top5: 1.0000 prec@top5: 0.3538 loss_action_cls: 0.0544 2023/03/11 08:31:28 - mmengine - INFO - Epoch(train) [3][1060/2226] lr: 5.1537e-07 eta: 11:10:46 time: 1.0181 data_time: 0.0117 memory: 70046 grad_norm: 0.1203 loss: 0.0646 recall@thr=0.5: 0.2778 prec@thr=0.5: 0.3611 recall@top3: 0.5000 prec@top3: 0.4444 recall@top5: 0.8889 prec@top5: 0.4000 loss_action_cls: 0.0646 2023/03/11 08:31:50 - mmengine - INFO - Epoch(train) [3][1080/2226] lr: 5.1690e-07 eta: 11:10:33 time: 1.0814 data_time: 0.0126 memory: 70046 grad_norm: 0.1200 loss: 0.0668 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.7778 recall@top3: 0.8519 prec@top3: 0.5926 recall@top5: 0.8889 prec@top5: 0.3778 loss_action_cls: 0.0668 2023/03/11 08:32:10 - mmengine - INFO - Epoch(train) [3][1100/2226] lr: 5.1843e-07 eta: 11:10:10 time: 1.0196 data_time: 0.0121 memory: 70046 grad_norm: 0.1165 loss: 0.0560 recall@thr=0.5: 0.5909 prec@thr=0.5: 0.8182 recall@top3: 0.6818 prec@top3: 0.5152 recall@top5: 0.8030 prec@top5: 0.3455 loss_action_cls: 0.0560 2023/03/11 08:32:31 - mmengine - INFO - Epoch(train) [3][1120/2226] lr: 5.1996e-07 eta: 11:09:46 time: 1.0072 data_time: 0.0112 memory: 70046 grad_norm: 0.1205 loss: 0.0800 recall@thr=0.5: 0.5470 prec@thr=0.5: 0.7273 recall@top3: 0.6833 prec@top3: 0.6061 recall@top5: 0.7318 prec@top5: 0.4000 loss_action_cls: 0.0800 2023/03/11 08:32:50 - mmengine - INFO - Epoch(train) [3][1140/2226] lr: 5.2148e-07 eta: 11:09:15 time: 0.9579 data_time: 0.0098 memory: 70046 grad_norm: 0.1219 loss: 0.0637 recall@thr=0.5: 0.4444 prec@thr=0.5: 0.7500 recall@top3: 0.6917 prec@top3: 0.8056 recall@top5: 0.9236 prec@top5: 0.6833 loss_action_cls: 0.0637 2023/03/11 08:33:10 - mmengine - INFO - Epoch(train) [3][1160/2226] lr: 5.2301e-07 eta: 11:08:50 time: 0.9978 data_time: 0.0110 memory: 70046 grad_norm: 0.1139 loss: 0.0684 recall@thr=0.5: 0.8000 prec@thr=0.5: 0.7167 recall@top3: 0.7333 prec@top3: 0.5667 recall@top5: 0.9667 prec@top5: 0.5000 loss_action_cls: 0.0684 2023/03/11 08:33:31 - mmengine - INFO - Epoch(train) [3][1180/2226] lr: 5.2454e-07 eta: 11:08:35 time: 1.0750 data_time: 0.0098 memory: 70046 grad_norm: 0.1180 loss: 0.0664 recall@thr=0.5: 0.5556 prec@thr=0.5: 1.0000 recall@top3: 0.6389 prec@top3: 0.5000 recall@top5: 0.6944 prec@top5: 0.3333 loss_action_cls: 0.0664 2023/03/11 08:33:50 - mmengine - INFO - Epoch(train) [3][1200/2226] lr: 5.2607e-07 eta: 11:08:05 time: 0.9609 data_time: 0.0108 memory: 70046 grad_norm: 0.1257 loss: 0.0645 recall@thr=0.5: 0.6282 prec@thr=0.5: 0.7564 recall@top3: 0.7321 prec@top3: 0.8205 recall@top5: 0.9077 prec@top5: 0.6154 loss_action_cls: 0.0645 2023/03/11 08:34:12 - mmengine - INFO - Epoch(train) [3][1220/2226] lr: 5.2759e-07 eta: 11:07:48 time: 1.0592 data_time: 0.0097 memory: 70046 grad_norm: 0.1213 loss: 0.0704 recall@thr=0.5: 0.6607 prec@thr=0.5: 0.6786 recall@top3: 0.7857 prec@top3: 0.7381 recall@top5: 0.9643 prec@top5: 0.5714 loss_action_cls: 0.0704 2023/03/11 08:34:32 - mmengine - INFO - Epoch(train) [3][1240/2226] lr: 5.2912e-07 eta: 11:07:28 time: 1.0369 data_time: 0.0110 memory: 70046 grad_norm: 0.1148 loss: 0.0642 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.7500 recall@top3: 0.7500 prec@top3: 0.4167 recall@top5: 0.9375 prec@top5: 0.3250 loss_action_cls: 0.0642 2023/03/11 08:34:52 - mmengine - INFO - Epoch(train) [3][1260/2226] lr: 5.3065e-07 eta: 11:06:58 time: 0.9600 data_time: 0.0102 memory: 70046 grad_norm: 0.1181 loss: 0.0592 recall@thr=0.5: 0.5303 prec@thr=0.5: 0.8182 recall@top3: 0.7576 prec@top3: 0.6061 recall@top5: 0.7576 prec@top5: 0.3636 loss_action_cls: 0.0592 2023/03/11 08:35:15 - mmengine - INFO - Epoch(train) [3][1280/2226] lr: 5.3218e-07 eta: 11:06:56 time: 1.1652 data_time: 0.0100 memory: 70046 grad_norm: 0.1134 loss: 0.0667 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.8571 recall@top3: 0.7143 prec@top3: 0.5238 recall@top5: 0.8571 prec@top5: 0.3714 loss_action_cls: 0.0667 2023/03/11 08:35:33 - mmengine - INFO - Epoch(train) [3][1300/2226] lr: 5.3371e-07 eta: 11:06:21 time: 0.9254 data_time: 0.0078 memory: 70046 grad_norm: 0.1206 loss: 0.0525 recall@thr=0.5: 0.8889 prec@thr=0.5: 0.8889 recall@top3: 0.9259 prec@top3: 0.6296 recall@top5: 1.0000 prec@top5: 0.4222 loss_action_cls: 0.0525 2023/03/11 08:35:55 - mmengine - INFO - Epoch(train) [3][1320/2226] lr: 5.3523e-07 eta: 11:06:08 time: 1.0909 data_time: 0.0095 memory: 70046 grad_norm: 0.1134 loss: 0.0546 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.9062 recall@top3: 0.7292 prec@top3: 0.8333 recall@top5: 0.8542 prec@top5: 0.6000 loss_action_cls: 0.0546 2023/03/11 08:36:16 - mmengine - INFO - Epoch(train) [3][1340/2226] lr: 5.3676e-07 eta: 11:05:48 time: 1.0389 data_time: 0.0084 memory: 70046 grad_norm: 0.1160 loss: 0.0668 recall@thr=0.5: 0.4679 prec@thr=0.5: 0.6923 recall@top3: 0.7885 prec@top3: 0.5897 recall@top5: 0.9551 prec@top5: 0.4462 loss_action_cls: 0.0668 2023/03/11 08:36:34 - mmengine - INFO - Epoch(train) [3][1360/2226] lr: 5.3829e-07 eta: 11:05:12 time: 0.9136 data_time: 0.0085 memory: 70046 grad_norm: 0.1197 loss: 0.0536 recall@thr=0.5: 0.5952 prec@thr=0.5: 0.7143 recall@top3: 0.7262 prec@top3: 0.6667 recall@top5: 0.8452 prec@top5: 0.4714 loss_action_cls: 0.0536 2023/03/11 08:36:53 - mmengine - INFO - Epoch(train) [3][1380/2226] lr: 5.3982e-07 eta: 11:04:38 time: 0.9274 data_time: 0.0091 memory: 70046 grad_norm: 0.1137 loss: 0.0528 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.7667 recall@top3: 0.9500 prec@top3: 0.6333 recall@top5: 1.0000 prec@top5: 0.4200 loss_action_cls: 0.0528 2023/03/11 08:37:15 - mmengine - INFO - Epoch(train) [3][1400/2226] lr: 5.4134e-07 eta: 11:04:28 time: 1.1099 data_time: 0.0113 memory: 70046 grad_norm: 0.1185 loss: 0.0683 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.5556 recall@top3: 0.7037 prec@top3: 0.2593 recall@top5: 0.8148 prec@top5: 0.2000 loss_action_cls: 0.0683 2023/03/11 08:37:31 - mmengine - INFO - Epoch(train) [3][1420/2226] lr: 5.4287e-07 eta: 11:03:40 time: 0.8230 data_time: 0.0113 memory: 70046 grad_norm: 0.1148 loss: 0.0591 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.7500 recall@top3: 0.7292 prec@top3: 0.5417 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0591 2023/03/11 08:37:53 - mmengine - INFO - Epoch(train) [3][1440/2226] lr: 5.4440e-07 eta: 11:03:27 time: 1.0923 data_time: 0.0093 memory: 70046 grad_norm: 0.1178 loss: 0.0689 recall@thr=0.5: 0.5227 prec@thr=0.5: 0.5909 recall@top3: 0.7955 prec@top3: 0.5758 recall@top5: 0.8182 prec@top5: 0.3636 loss_action_cls: 0.0689 2023/03/11 08:38:16 - mmengine - INFO - Epoch(train) [3][1460/2226] lr: 5.4593e-07 eta: 11:03:18 time: 1.1198 data_time: 0.0127 memory: 70046 grad_norm: 0.1166 loss: 0.0782 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8600 recall@top3: 0.8667 prec@top3: 0.9667 recall@top5: 0.9500 prec@top5: 0.6400 loss_action_cls: 0.0782 2023/03/11 08:38:35 - mmengine - INFO - Epoch(train) [3][1480/2226] lr: 5.4745e-07 eta: 11:02:52 time: 0.9903 data_time: 0.0124 memory: 70046 grad_norm: 0.1141 loss: 0.0682 recall@thr=0.5: 0.3333 prec@thr=0.5: 0.5000 recall@top3: 0.7667 prec@top3: 0.5333 recall@top5: 0.9000 prec@top5: 0.4000 loss_action_cls: 0.0682 2023/03/11 08:38:55 - mmengine - INFO - Epoch(train) [3][1500/2226] lr: 5.4898e-07 eta: 11:02:26 time: 0.9883 data_time: 0.0112 memory: 70046 grad_norm: 0.1204 loss: 0.0897 recall@thr=0.5: 0.6818 prec@thr=0.5: 0.8030 recall@top3: 0.8636 prec@top3: 0.7273 recall@top5: 0.8636 prec@top5: 0.4364 loss_action_cls: 0.0897 2023/03/11 08:39:18 - mmengine - INFO - Epoch(train) [3][1520/2226] lr: 5.5051e-07 eta: 11:02:22 time: 1.1622 data_time: 0.0093 memory: 70046 grad_norm: 0.1142 loss: 0.0459 recall@thr=0.5: 0.8561 prec@thr=0.5: 0.9394 recall@top3: 0.9470 prec@top3: 0.7879 recall@top5: 1.0000 prec@top5: 0.5091 loss_action_cls: 0.0459 2023/03/11 08:39:40 - mmengine - INFO - Epoch(train) [3][1540/2226] lr: 5.5204e-07 eta: 11:02:05 time: 1.0541 data_time: 0.0093 memory: 70046 grad_norm: 0.1105 loss: 0.0537 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.5714 recall@top3: 0.9643 prec@top3: 0.5714 recall@top5: 1.0000 prec@top5: 0.3714 loss_action_cls: 0.0537 2023/03/11 08:39:46 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 08:40:00 - mmengine - INFO - Epoch(train) [3][1560/2226] lr: 5.5356e-07 eta: 11:01:46 time: 1.0455 data_time: 0.0091 memory: 70046 grad_norm: 0.1212 loss: 0.0623 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.7778 recall@top3: 0.8889 prec@top3: 0.5185 recall@top5: 0.9444 prec@top5: 0.3556 loss_action_cls: 0.0623 2023/03/11 08:40:18 - mmengine - INFO - Epoch(train) [3][1580/2226] lr: 5.5509e-07 eta: 11:01:08 time: 0.8923 data_time: 0.0077 memory: 70046 grad_norm: 0.1169 loss: 0.0692 recall@thr=0.5: 0.6667 prec@thr=0.5: 1.0000 recall@top3: 0.8148 prec@top3: 0.6296 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0692 2023/03/11 08:40:42 - mmengine - INFO - Epoch(train) [3][1600/2226] lr: 5.5662e-07 eta: 11:01:05 time: 1.1683 data_time: 0.0101 memory: 70046 grad_norm: 0.1132 loss: 0.0655 recall@thr=0.5: 0.7000 prec@thr=0.5: 0.7000 recall@top3: 0.7000 prec@top3: 0.5667 recall@top5: 0.9500 prec@top5: 0.4200 loss_action_cls: 0.0655 2023/03/11 08:41:03 - mmengine - INFO - Epoch(train) [3][1620/2226] lr: 5.5815e-07 eta: 11:00:46 time: 1.0487 data_time: 0.0088 memory: 70046 grad_norm: 0.1114 loss: 0.0667 recall@thr=0.5: 0.6333 prec@thr=0.5: 0.5833 recall@top3: 0.7000 prec@top3: 0.5333 recall@top5: 0.7333 prec@top5: 0.3400 loss_action_cls: 0.0667 2023/03/11 08:41:21 - mmengine - INFO - Epoch(train) [3][1640/2226] lr: 5.5967e-07 eta: 11:00:12 time: 0.9269 data_time: 0.0091 memory: 70046 grad_norm: 0.1129 loss: 0.0740 recall@thr=0.5: 0.7407 prec@thr=0.5: 0.9444 recall@top3: 0.8889 prec@top3: 0.7778 recall@top5: 0.9444 prec@top5: 0.5111 loss_action_cls: 0.0740 2023/03/11 08:41:42 - mmengine - INFO - Epoch(train) [3][1660/2226] lr: 5.6120e-07 eta: 10:59:51 time: 1.0238 data_time: 0.0122 memory: 70046 grad_norm: 0.1148 loss: 0.0487 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.5167 recall@top3: 0.7500 prec@top3: 0.4667 recall@top5: 1.0000 prec@top5: 0.3400 loss_action_cls: 0.0487 2023/03/11 08:42:02 - mmengine - INFO - Epoch(train) [3][1680/2226] lr: 5.6273e-07 eta: 10:59:31 time: 1.0352 data_time: 0.0097 memory: 70046 grad_norm: 0.1200 loss: 0.0591 recall@thr=0.5: 1.0000 prec@thr=0.5: 0.8333 recall@top3: 1.0000 prec@top3: 0.5667 recall@top5: 1.0000 prec@top5: 0.3400 loss_action_cls: 0.0591 2023/03/11 08:42:23 - mmengine - INFO - Epoch(train) [3][1700/2226] lr: 5.6426e-07 eta: 10:59:13 time: 1.0547 data_time: 0.0099 memory: 70046 grad_norm: 0.1150 loss: 0.0588 recall@thr=0.5: 0.7545 prec@thr=0.5: 0.8500 recall@top3: 0.8273 prec@top3: 0.7576 recall@top5: 0.9545 prec@top5: 0.5636 loss_action_cls: 0.0588 2023/03/11 08:42:43 - mmengine - INFO - Epoch(train) [3][1720/2226] lr: 5.6578e-07 eta: 10:58:46 time: 0.9806 data_time: 0.0111 memory: 70046 grad_norm: 0.1195 loss: 0.0999 recall@thr=0.5: 0.8667 prec@thr=0.5: 0.7583 recall@top3: 0.8083 prec@top3: 0.6000 recall@top5: 1.0000 prec@top5: 0.4400 loss_action_cls: 0.0999 2023/03/11 08:43:07 - mmengine - INFO - Epoch(train) [3][1740/2226] lr: 5.6731e-07 eta: 10:58:45 time: 1.1832 data_time: 0.0083 memory: 70046 grad_norm: 0.1140 loss: 0.0543 recall@thr=0.5: 0.8229 prec@thr=0.5: 0.8437 recall@top3: 0.8750 prec@top3: 0.7500 recall@top5: 1.0000 prec@top5: 0.5500 loss_action_cls: 0.0543 2023/03/11 08:43:25 - mmengine - INFO - Epoch(train) [3][1760/2226] lr: 5.6884e-07 eta: 10:58:09 time: 0.9127 data_time: 0.0098 memory: 70046 grad_norm: 0.1173 loss: 0.0544 recall@thr=0.5: 0.7833 prec@thr=0.5: 0.8500 recall@top3: 0.8167 prec@top3: 0.5000 recall@top5: 0.9667 prec@top5: 0.3800 loss_action_cls: 0.0544 2023/03/11 08:43:47 - mmengine - INFO - Epoch(train) [3][1780/2226] lr: 5.7037e-07 eta: 10:57:58 time: 1.1091 data_time: 0.0090 memory: 70046 grad_norm: 0.1097 loss: 0.0756 recall@thr=0.5: 0.4762 prec@thr=0.5: 0.6429 recall@top3: 0.5476 prec@top3: 0.5714 recall@top5: 0.9286 prec@top5: 0.5429 loss_action_cls: 0.0756 2023/03/11 08:44:05 - mmengine - INFO - Epoch(train) [3][1800/2226] lr: 5.7189e-07 eta: 10:57:19 time: 0.8776 data_time: 0.0108 memory: 70046 grad_norm: 0.1178 loss: 0.0751 recall@thr=0.5: 0.8030 prec@thr=0.5: 0.9470 recall@top3: 0.8939 prec@top3: 0.6364 recall@top5: 0.9545 prec@top5: 0.4182 loss_action_cls: 0.0751 2023/03/11 08:44:25 - mmengine - INFO - Epoch(train) [3][1820/2226] lr: 5.7342e-07 eta: 10:56:57 time: 1.0223 data_time: 0.0095 memory: 70046 grad_norm: 0.1156 loss: 0.0701 recall@thr=0.5: 0.6607 prec@thr=0.5: 0.8333 recall@top3: 0.8393 prec@top3: 0.7381 recall@top5: 0.9107 prec@top5: 0.5000 loss_action_cls: 0.0701 2023/03/11 08:44:46 - mmengine - INFO - Epoch(train) [3][1840/2226] lr: 5.7495e-07 eta: 10:56:37 time: 1.0335 data_time: 0.0091 memory: 70046 grad_norm: 0.1160 loss: 0.0964 recall@thr=0.5: 0.4375 prec@thr=0.5: 0.5000 recall@top3: 0.7917 prec@top3: 0.4583 recall@top5: 0.8958 prec@top5: 0.3250 loss_action_cls: 0.0964 2023/03/11 08:45:09 - mmengine - INFO - Epoch(train) [3][1860/2226] lr: 5.7648e-07 eta: 10:56:32 time: 1.1557 data_time: 0.0089 memory: 70046 grad_norm: 0.1120 loss: 0.0619 recall@thr=0.5: 0.8030 prec@thr=0.5: 0.6515 recall@top3: 0.9545 prec@top3: 0.5152 recall@top5: 0.9545 prec@top5: 0.3091 loss_action_cls: 0.0619 2023/03/11 08:45:28 - mmengine - INFO - Epoch(train) [3][1880/2226] lr: 5.7801e-07 eta: 10:55:59 time: 0.9337 data_time: 0.0100 memory: 70046 grad_norm: 0.1139 loss: 0.0632 recall@thr=0.5: 1.0000 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.2857 loss_action_cls: 0.0632 2023/03/11 08:45:50 - mmengine - INFO - Epoch(train) [3][1900/2226] lr: 5.7953e-07 eta: 10:55:46 time: 1.0954 data_time: 0.0122 memory: 70046 grad_norm: 0.1172 loss: 0.0564 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6250 recall@top3: 0.8750 prec@top3: 0.5417 recall@top5: 1.0000 prec@top5: 0.3750 loss_action_cls: 0.0564 2023/03/11 08:46:08 - mmengine - INFO - Epoch(train) [3][1920/2226] lr: 5.8106e-07 eta: 10:55:14 time: 0.9343 data_time: 0.0103 memory: 70046 grad_norm: 0.1161 loss: 0.0617 recall@thr=0.5: 0.7037 prec@thr=0.5: 0.7407 recall@top3: 0.7037 prec@top3: 0.5556 recall@top5: 0.9630 prec@top5: 0.4889 loss_action_cls: 0.0617 2023/03/11 08:46:30 - mmengine - INFO - Epoch(train) [3][1940/2226] lr: 5.8259e-07 eta: 10:55:02 time: 1.1045 data_time: 0.0129 memory: 70046 grad_norm: 0.1142 loss: 0.0622 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7407 recall@top3: 0.7778 prec@top3: 0.7593 recall@top5: 0.9213 prec@top5: 0.5556 loss_action_cls: 0.0622 2023/03/11 08:46:50 - mmengine - INFO - Epoch(train) [3][1960/2226] lr: 5.8412e-07 eta: 10:54:33 time: 0.9594 data_time: 0.0110 memory: 70046 grad_norm: 0.1162 loss: 0.0487 recall@thr=0.5: 0.9286 prec@thr=0.5: 0.8393 recall@top3: 0.9524 prec@top3: 0.6190 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0487 2023/03/11 08:47:14 - mmengine - INFO - Epoch(train) [3][1980/2226] lr: 5.8564e-07 eta: 10:54:38 time: 1.2448 data_time: 0.0114 memory: 70046 grad_norm: 0.1125 loss: 0.0646 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.8571 recall@top3: 0.6952 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.6857 loss_action_cls: 0.0646 2023/03/11 08:47:33 - mmengine - INFO - Epoch(train) [3][2000/2226] lr: 5.8717e-07 eta: 10:54:03 time: 0.9061 data_time: 0.0086 memory: 70046 grad_norm: 0.1246 loss: 0.0737 recall@thr=0.5: 0.8667 prec@thr=0.5: 0.8167 recall@top3: 0.9167 prec@top3: 0.8000 recall@top5: 0.9667 prec@top5: 0.5200 loss_action_cls: 0.0737 2023/03/11 08:47:53 - mmengine - INFO - Epoch(train) [3][2020/2226] lr: 5.8870e-07 eta: 10:53:39 time: 1.0078 data_time: 0.0112 memory: 70046 grad_norm: 0.1127 loss: 0.0513 recall@thr=0.5: 0.8167 prec@thr=0.5: 0.8833 recall@top3: 0.7000 prec@top3: 0.6333 recall@top5: 0.9500 prec@top5: 0.5600 loss_action_cls: 0.0513 2023/03/11 08:48:14 - mmengine - INFO - Epoch(train) [3][2040/2226] lr: 5.9023e-07 eta: 10:53:22 time: 1.0583 data_time: 0.0122 memory: 70046 grad_norm: 0.1221 loss: 0.0633 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.6667 recall@top3: 0.7500 prec@top3: 0.5556 recall@top5: 0.7500 prec@top5: 0.3333 loss_action_cls: 0.0633 2023/03/11 08:48:34 - mmengine - INFO - Epoch(train) [3][2060/2226] lr: 5.9175e-07 eta: 10:53:00 time: 1.0235 data_time: 0.0139 memory: 70046 grad_norm: 0.1136 loss: 0.0500 recall@thr=0.5: 0.7381 prec@thr=0.5: 0.8810 recall@top3: 0.8810 prec@top3: 0.5238 recall@top5: 0.9286 prec@top5: 0.3429 loss_action_cls: 0.0500 2023/03/11 08:48:57 - mmengine - INFO - Epoch(train) [3][2080/2226] lr: 5.9328e-07 eta: 10:52:52 time: 1.1342 data_time: 0.0112 memory: 70046 grad_norm: 0.1161 loss: 0.0582 recall@thr=0.5: 0.6944 prec@thr=0.5: 0.8056 recall@top3: 0.9028 prec@top3: 0.8333 recall@top5: 1.0000 prec@top5: 0.5667 loss_action_cls: 0.0582 2023/03/11 08:49:15 - mmengine - INFO - Epoch(train) [3][2100/2226] lr: 5.9481e-07 eta: 10:52:15 time: 0.8869 data_time: 0.0093 memory: 70046 grad_norm: 0.1144 loss: 0.0707 recall@thr=0.5: 0.6591 prec@thr=0.5: 0.6818 recall@top3: 0.7879 prec@top3: 0.5758 recall@top5: 0.9394 prec@top5: 0.4545 loss_action_cls: 0.0707 2023/03/11 08:49:34 - mmengine - INFO - Epoch(train) [3][2120/2226] lr: 5.9634e-07 eta: 10:51:45 time: 0.9548 data_time: 0.0115 memory: 70046 grad_norm: 0.1118 loss: 0.0778 recall@thr=0.5: 0.9167 prec@thr=0.5: 1.0000 recall@top3: 0.9167 prec@top3: 0.5833 recall@top5: 0.9167 prec@top5: 0.3500 loss_action_cls: 0.0778 2023/03/11 08:49:55 - mmengine - INFO - Epoch(train) [3][2140/2226] lr: 5.9786e-07 eta: 10:51:29 time: 1.0654 data_time: 0.0133 memory: 70046 grad_norm: 0.1157 loss: 0.0656 recall@thr=0.5: 0.7477 prec@thr=0.5: 0.7841 recall@top3: 0.7636 prec@top3: 0.6970 recall@top5: 0.9667 prec@top5: 0.5455 loss_action_cls: 0.0656 2023/03/11 08:50:17 - mmengine - INFO - Epoch(train) [3][2160/2226] lr: 5.9939e-07 eta: 10:51:12 time: 1.0687 data_time: 0.0101 memory: 70046 grad_norm: 0.1171 loss: 0.0747 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.8571 recall@top3: 1.0000 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.2857 loss_action_cls: 0.0747 2023/03/11 08:50:36 - mmengine - INFO - Epoch(train) [3][2180/2226] lr: 6.0092e-07 eta: 10:50:47 time: 0.9900 data_time: 0.0095 memory: 70046 grad_norm: 0.1145 loss: 0.0603 recall@thr=0.5: 0.4167 prec@thr=0.5: 0.6667 recall@top3: 0.7222 prec@top3: 0.6296 recall@top5: 1.0000 prec@top5: 0.5778 loss_action_cls: 0.0603 2023/03/11 08:50:58 - mmengine - INFO - Epoch(train) [3][2200/2226] lr: 6.0245e-07 eta: 10:50:34 time: 1.0953 data_time: 0.0100 memory: 70046 grad_norm: 0.1171 loss: 0.0521 recall@thr=0.5: 0.9048 prec@thr=0.5: 0.9000 recall@top3: 0.9643 prec@top3: 0.8095 recall@top5: 1.0000 prec@top5: 0.5143 loss_action_cls: 0.0521 2023/03/11 08:51:16 - mmengine - INFO - Epoch(train) [3][2220/2226] lr: 6.0397e-07 eta: 10:49:58 time: 0.8978 data_time: 0.0111 memory: 70046 grad_norm: 0.1118 loss: 0.0658 recall@thr=0.5: 0.9583 prec@thr=0.5: 0.9583 recall@top3: 0.9583 prec@top3: 0.7083 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0658 2023/03/11 08:51:20 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 08:51:20 - mmengine - INFO - Epoch(train) [3][2226/2226] lr: 6.0443e-07 eta: 10:49:38 time: 0.7072 data_time: 0.0088 memory: 70046 grad_norm: 0.1158 loss: 0.0627 recall@thr=0.5: 1.0000 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.4444 recall@top5: 1.0000 prec@top5: 0.2667 loss_action_cls: 0.0627 2023/03/11 08:51:20 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/03/11 08:51:36 - mmengine - INFO - Epoch(val) [3][ 20/1571] eta: 0:05:24 time: 0.2092 data_time: 0.1185 memory: 6688 2023/03/11 08:51:40 - mmengine - INFO - Epoch(val) [3][ 40/1571] eta: 0:04:50 time: 0.1703 data_time: 0.0451 memory: 7490 2023/03/11 08:51:43 - mmengine - INFO - Epoch(val) [3][ 60/1571] eta: 0:04:37 time: 0.1711 data_time: 0.0461 memory: 7490 2023/03/11 08:51:47 - mmengine - INFO - Epoch(val) [3][ 80/1571] eta: 0:04:28 time: 0.1697 data_time: 0.0602 memory: 7490 2023/03/11 08:51:51 - mmengine - INFO - Epoch(val) [3][ 100/1571] eta: 0:04:30 time: 0.1995 data_time: 0.0729 memory: 7490 2023/03/11 08:51:54 - mmengine - INFO - Epoch(val) [3][ 120/1571] eta: 0:04:17 time: 0.1470 data_time: 0.0418 memory: 6775 2023/03/11 08:51:57 - mmengine - INFO - Epoch(val) [3][ 140/1571] eta: 0:04:09 time: 0.1552 data_time: 0.0524 memory: 6775 2023/03/11 08:52:00 - mmengine - INFO - Epoch(val) [3][ 160/1571] eta: 0:04:05 time: 0.1717 data_time: 0.0754 memory: 6775 2023/03/11 08:52:04 - mmengine - INFO - Epoch(val) [3][ 180/1571] eta: 0:04:06 time: 0.2033 data_time: 0.1063 memory: 7490 2023/03/11 08:52:08 - mmengine - INFO - Epoch(val) [3][ 200/1571] eta: 0:04:05 time: 0.1950 data_time: 0.0550 memory: 7490 2023/03/11 08:52:13 - mmengine - INFO - Epoch(val) [3][ 220/1571] eta: 0:04:10 time: 0.2437 data_time: 0.1431 memory: 7490 2023/03/11 08:52:16 - mmengine - INFO - Epoch(val) [3][ 240/1571] eta: 0:04:01 time: 0.1388 data_time: 0.0498 memory: 6775 2023/03/11 08:52:19 - mmengine - INFO - Epoch(val) [3][ 260/1571] eta: 0:03:55 time: 0.1599 data_time: 0.0662 memory: 6775 2023/03/11 08:52:22 - mmengine - INFO - Epoch(val) [3][ 280/1571] eta: 0:03:47 time: 0.1320 data_time: 0.0336 memory: 6775 2023/03/11 08:52:25 - mmengine - INFO - Epoch(val) [3][ 300/1571] eta: 0:03:42 time: 0.1615 data_time: 0.0648 memory: 6775 2023/03/11 08:52:29 - mmengine - INFO - Epoch(val) [3][ 320/1571] eta: 0:03:40 time: 0.1873 data_time: 0.0643 memory: 7490 2023/03/11 08:52:33 - mmengine - INFO - Epoch(val) [3][ 340/1571] eta: 0:03:38 time: 0.2046 data_time: 0.0636 memory: 7490 2023/03/11 08:52:36 - mmengine - INFO - Epoch(val) [3][ 360/1571] eta: 0:03:33 time: 0.1598 data_time: 0.0242 memory: 7490 2023/03/11 08:52:39 - mmengine - INFO - Epoch(val) [3][ 380/1571] eta: 0:03:30 time: 0.1765 data_time: 0.0359 memory: 7490 2023/03/11 08:52:43 - mmengine - INFO - Epoch(val) [3][ 400/1571] eta: 0:03:28 time: 0.2015 data_time: 0.0025 memory: 8853 2023/03/11 08:52:46 - mmengine - INFO - Epoch(val) [3][ 420/1571] eta: 0:03:23 time: 0.1534 data_time: 0.0026 memory: 8853 2023/03/11 08:52:49 - mmengine - INFO - Epoch(val) [3][ 440/1571] eta: 0:03:17 time: 0.1363 data_time: 0.0026 memory: 7490 2023/03/11 08:52:53 - mmengine - INFO - Epoch(val) [3][ 460/1571] eta: 0:03:14 time: 0.1855 data_time: 0.0467 memory: 7490 2023/03/11 08:52:57 - mmengine - INFO - Epoch(val) [3][ 480/1571] eta: 0:03:11 time: 0.1887 data_time: 0.0496 memory: 7490 2023/03/11 08:53:00 - mmengine - INFO - Epoch(val) [3][ 500/1571] eta: 0:03:08 time: 0.1822 data_time: 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08:54:00 - mmengine - INFO - Epoch(val) [3][ 840/1571] eta: 0:02:08 time: 0.1666 data_time: 0.0257 memory: 7490 2023/03/11 08:54:04 - mmengine - INFO - Epoch(val) [3][ 860/1571] eta: 0:02:05 time: 0.1709 data_time: 0.0632 memory: 7490 2023/03/11 08:54:07 - mmengine - INFO - Epoch(val) [3][ 880/1571] eta: 0:02:01 time: 0.1653 data_time: 0.0682 memory: 6775 2023/03/11 08:54:11 - mmengine - INFO - Epoch(val) [3][ 900/1571] eta: 0:01:57 time: 0.1736 data_time: 0.0717 memory: 7266 2023/03/11 08:54:14 - mmengine - INFO - Epoch(val) [3][ 920/1571] eta: 0:01:54 time: 0.1602 data_time: 0.0359 memory: 7490 2023/03/11 08:54:17 - mmengine - INFO - Epoch(val) [3][ 940/1571] eta: 0:01:50 time: 0.1768 data_time: 0.0402 memory: 7490 2023/03/11 08:54:21 - mmengine - INFO - Epoch(val) [3][ 960/1571] eta: 0:01:47 time: 0.1862 data_time: 0.0408 memory: 7490 2023/03/11 08:54:25 - mmengine - INFO - Epoch(val) [3][ 980/1571] eta: 0:01:43 time: 0.1827 data_time: 0.0483 memory: 7490 2023/03/11 08:54:28 - 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eta: 0:00:15 time: 0.1574 data_time: 0.0409 memory: 7057 2023/03/11 08:55:53 - mmengine - INFO - Epoch(val) [3][1500/1571] eta: 0:00:12 time: 0.1717 data_time: 0.0720 memory: 7490 2023/03/11 08:55:55 - mmengine - INFO - Epoch(val) [3][1520/1571] eta: 0:00:08 time: 0.1325 data_time: 0.0018 memory: 7490 2023/03/11 08:55:58 - mmengine - INFO - Epoch(val) [3][1540/1571] eta: 0:00:05 time: 0.1326 data_time: 0.0020 memory: 7490 2023/03/11 08:56:01 - mmengine - INFO - Epoch(val) [3][1560/1571] eta: 0:00:01 time: 0.1323 data_time: 0.0019 memory: 7490 2023/03/11 09:00:47 - mmengine - INFO - Epoch(val) [3][1571/1571] mAP/mAP@0.5IOU: 0.3552 2023/03/11 09:00:47 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/hukai/mmaction2/work_dirs/vit-l_16x4/best_mAP/mAP@0.5IOU_epoch_2.pth is removed 2023/03/11 09:00:52 - mmengine - INFO - The best checkpoint with 0.3552 mAP/mAP@0.5IOU at 3 epoch is saved to best_mAP/mAP@0.5IOU_epoch_3.pth. 2023/03/11 09:01:17 - mmengine - INFO - Epoch(train) [4][ 20/2226] lr: 6.0596e-07 eta: 10:49:38 time: 1.2128 data_time: 0.4025 memory: 70046 grad_norm: 0.1073 loss: 0.0804 recall@thr=0.5: 0.7692 prec@thr=0.5: 0.6487 recall@top3: 0.8205 prec@top3: 0.6667 recall@top5: 0.8462 prec@top5: 0.4154 loss_action_cls: 0.0804 2023/03/11 09:01:38 - mmengine - INFO - Epoch(train) [4][ 40/2226] lr: 6.0749e-07 eta: 10:49:24 time: 1.0854 data_time: 0.0551 memory: 70046 grad_norm: 0.1204 loss: 0.0713 recall@thr=0.5: 0.5455 prec@thr=0.5: 0.6818 recall@top3: 0.7500 prec@top3: 0.5758 recall@top5: 0.9394 prec@top5: 0.4545 loss_action_cls: 0.0713 2023/03/11 09:02:03 - mmengine - INFO - Epoch(train) [4][ 60/2226] lr: 6.0902e-07 eta: 10:49:28 time: 1.2517 data_time: 0.0106 memory: 70046 grad_norm: 0.1142 loss: 0.0498 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.7778 recall@top3: 0.9167 prec@top3: 0.8333 recall@top5: 1.0000 prec@top5: 0.5667 loss_action_cls: 0.0498 2023/03/11 09:02:20 - mmengine - INFO - Epoch(train) [4][ 80/2226] lr: 6.1054e-07 eta: 10:48:44 time: 0.8233 data_time: 0.0085 memory: 70046 grad_norm: 0.1143 loss: 0.0551 recall@thr=0.5: 0.7667 prec@thr=0.5: 0.8667 recall@top3: 0.9000 prec@top3: 0.8000 recall@top5: 1.0000 prec@top5: 0.5200 loss_action_cls: 0.0551 2023/03/11 09:02:43 - mmengine - INFO - Epoch(train) [4][ 100/2226] lr: 6.1207e-07 eta: 10:48:38 time: 1.1613 data_time: 0.0126 memory: 70046 grad_norm: 0.1162 loss: 0.0515 recall@thr=0.5: 0.9167 prec@thr=0.5: 0.8889 recall@top3: 1.0000 prec@top3: 0.7222 recall@top5: 1.0000 prec@top5: 0.4333 loss_action_cls: 0.0515 2023/03/11 09:03:01 - mmengine - INFO - Epoch(train) [4][ 120/2226] lr: 6.1360e-07 eta: 10:48:06 time: 0.9248 data_time: 0.0113 memory: 70046 grad_norm: 0.1185 loss: 0.0388 recall@thr=0.5: 0.7958 prec@thr=0.5: 0.8250 recall@top3: 0.7667 prec@top3: 0.7167 recall@top5: 0.9458 prec@top5: 0.5400 loss_action_cls: 0.0388 2023/03/11 09:03:24 - mmengine - INFO - Epoch(train) [4][ 140/2226] lr: 6.1513e-07 eta: 10:47:53 time: 1.1039 data_time: 0.0123 memory: 70046 grad_norm: 0.1112 loss: 0.0777 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.5714 recall@top5: 0.9524 prec@top5: 0.4000 loss_action_cls: 0.0777 2023/03/11 09:03:41 - mmengine - INFO - Epoch(train) [4][ 160/2226] lr: 6.1665e-07 eta: 10:47:15 time: 0.8722 data_time: 0.0137 memory: 70046 grad_norm: 0.1148 loss: 0.0653 recall@thr=0.5: 0.4524 prec@thr=0.5: 0.5714 recall@top3: 0.5952 prec@top3: 0.4286 recall@top5: 0.7857 prec@top5: 0.3714 loss_action_cls: 0.0653 2023/03/11 09:04:01 - mmengine - INFO - Epoch(train) [4][ 180/2226] lr: 6.1818e-07 eta: 10:46:49 time: 0.9806 data_time: 0.0141 memory: 70046 grad_norm: 0.1117 loss: 0.0614 recall@thr=0.5: 0.7917 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.7917 recall@top5: 1.0000 prec@top5: 0.4750 loss_action_cls: 0.0614 2023/03/11 09:04:21 - mmengine - INFO - Epoch(train) [4][ 200/2226] lr: 6.1971e-07 eta: 10:46:30 time: 1.0441 data_time: 0.0124 memory: 70046 grad_norm: 0.1123 loss: 0.0740 recall@thr=0.5: 0.6111 prec@thr=0.5: 0.5417 recall@top3: 0.9167 prec@top3: 0.7222 recall@top5: 0.9167 prec@top5: 0.4333 loss_action_cls: 0.0740 2023/03/11 09:04:42 - mmengine - INFO - Epoch(train) [4][ 220/2226] lr: 6.2124e-07 eta: 10:46:07 time: 1.0097 data_time: 0.0123 memory: 70046 grad_norm: 0.1119 loss: 0.0710 recall@thr=0.5: 0.6061 prec@thr=0.5: 0.6970 recall@top3: 0.7879 prec@top3: 0.6061 recall@top5: 0.9697 prec@top5: 0.4545 loss_action_cls: 0.0710 2023/03/11 09:05:03 - mmengine - INFO - Epoch(train) [4][ 240/2226] lr: 6.2276e-07 eta: 10:45:51 time: 1.0724 data_time: 0.0133 memory: 70046 grad_norm: 0.1149 loss: 0.0573 recall@thr=0.5: 0.5952 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.5429 loss_action_cls: 0.0573 2023/03/11 09:05:25 - mmengine - INFO - Epoch(train) [4][ 260/2226] lr: 6.2429e-07 eta: 10:45:39 time: 1.1134 data_time: 0.0116 memory: 70046 grad_norm: 0.1140 loss: 0.0558 recall@thr=0.5: 0.4583 prec@thr=0.5: 0.3958 recall@top3: 0.5208 prec@top3: 0.4583 recall@top5: 0.8750 prec@top5: 0.4250 loss_action_cls: 0.0558 2023/03/11 09:05:45 - mmengine - INFO - Epoch(train) [4][ 280/2226] lr: 6.2582e-07 eta: 10:45:11 time: 0.9578 data_time: 0.0128 memory: 70046 grad_norm: 0.1151 loss: 0.0545 recall@thr=0.5: 0.6481 prec@thr=0.5: 0.7407 recall@top3: 0.8889 prec@top3: 0.7037 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0545 2023/03/11 09:06:04 - mmengine - INFO - Epoch(train) [4][ 300/2226] lr: 6.2735e-07 eta: 10:44:44 time: 0.9734 data_time: 0.0122 memory: 70046 grad_norm: 0.1154 loss: 0.0732 recall@thr=0.5: 0.2798 prec@thr=0.5: 0.3333 recall@top3: 0.6250 prec@top3: 0.5000 recall@top5: 0.7083 prec@top5: 0.3429 loss_action_cls: 0.0732 2023/03/11 09:06:23 - mmengine - INFO - Epoch(train) [4][ 320/2226] lr: 6.2887e-07 eta: 10:44:17 time: 0.9685 data_time: 0.0126 memory: 70046 grad_norm: 0.1183 loss: 0.0742 recall@thr=0.5: 0.4259 prec@thr=0.5: 0.5741 recall@top3: 0.8333 prec@top3: 0.7407 recall@top5: 0.9074 prec@top5: 0.4889 loss_action_cls: 0.0742 2023/03/11 09:06:26 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 09:06:44 - mmengine - INFO - Epoch(train) [4][ 340/2226] lr: 6.3040e-07 eta: 10:43:57 time: 1.0410 data_time: 0.0164 memory: 70046 grad_norm: 0.1178 loss: 0.0621 recall@thr=0.5: 0.5128 prec@thr=0.5: 0.7308 recall@top3: 0.8333 prec@top3: 0.6154 recall@top5: 1.0000 prec@top5: 0.4923 loss_action_cls: 0.0621 2023/03/11 09:07:06 - mmengine - INFO - Epoch(train) [4][ 360/2226] lr: 6.3193e-07 eta: 10:43:40 time: 1.0659 data_time: 0.0134 memory: 70046 grad_norm: 0.1170 loss: 0.0589 recall@thr=0.5: 0.8681 prec@thr=0.5: 0.8333 recall@top3: 0.8681 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0589 2023/03/11 09:07:23 - mmengine - INFO - Epoch(train) [4][ 380/2226] lr: 6.3346e-07 eta: 10:43:05 time: 0.8902 data_time: 0.0107 memory: 70046 grad_norm: 0.1106 loss: 0.0673 recall@thr=0.5: 0.6900 prec@thr=0.5: 0.8000 recall@top3: 0.8067 prec@top3: 0.7333 recall@top5: 0.9467 prec@top5: 0.5400 loss_action_cls: 0.0673 2023/03/11 09:07:48 - mmengine - INFO - Epoch(train) [4][ 400/2226] lr: 6.3498e-07 eta: 10:43:07 time: 1.2426 data_time: 0.0140 memory: 70046 grad_norm: 0.1123 loss: 0.0594 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8333 recall@top3: 0.8667 prec@top3: 0.7667 recall@top5: 1.0000 prec@top5: 0.5400 loss_action_cls: 0.0594 2023/03/11 09:08:06 - mmengine - INFO - Epoch(train) [4][ 420/2226] lr: 6.3651e-07 eta: 10:42:31 time: 0.8893 data_time: 0.0129 memory: 70046 grad_norm: 0.1126 loss: 0.0581 recall@thr=0.5: 0.7685 prec@thr=0.5: 0.7963 recall@top3: 0.9537 prec@top3: 0.7963 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0581 2023/03/11 09:08:27 - mmengine - INFO - Epoch(train) [4][ 440/2226] lr: 6.3804e-07 eta: 10:42:15 time: 1.0751 data_time: 0.0108 memory: 70046 grad_norm: 0.1148 loss: 0.0648 recall@thr=0.5: 0.4667 prec@thr=0.5: 0.6000 recall@top3: 0.6833 prec@top3: 0.5667 recall@top5: 0.9000 prec@top5: 0.4600 loss_action_cls: 0.0648 2023/03/11 09:08:45 - mmengine - INFO - Epoch(train) [4][ 460/2226] lr: 6.3957e-07 eta: 10:41:41 time: 0.8949 data_time: 0.0113 memory: 70046 grad_norm: 0.1101 loss: 0.0579 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8750 recall@top3: 0.8750 prec@top3: 0.4167 recall@top5: 1.0000 prec@top5: 0.3000 loss_action_cls: 0.0579 2023/03/11 09:09:04 - mmengine - INFO - Epoch(train) [4][ 480/2226] lr: 6.4109e-07 eta: 10:41:08 time: 0.9153 data_time: 0.0120 memory: 70046 grad_norm: 0.1164 loss: 0.0612 recall@thr=0.5: 0.8250 prec@thr=0.5: 1.0000 recall@top3: 0.9000 prec@top3: 0.9333 recall@top5: 1.0000 prec@top5: 0.6400 loss_action_cls: 0.0612 2023/03/11 09:09:26 - mmengine - INFO - Epoch(train) [4][ 500/2226] lr: 6.4262e-07 eta: 10:40:55 time: 1.0974 data_time: 0.0142 memory: 70046 grad_norm: 0.1163 loss: 0.0580 recall@thr=0.5: 0.4167 prec@thr=0.5: 0.3889 recall@top3: 0.7083 prec@top3: 0.4167 recall@top5: 0.9583 prec@top5: 0.3500 loss_action_cls: 0.0580 2023/03/11 09:09:45 - mmengine - INFO - Epoch(train) [4][ 520/2226] lr: 6.4415e-07 eta: 10:40:29 time: 0.9784 data_time: 0.0145 memory: 70046 grad_norm: 0.1122 loss: 0.0630 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.6250 recall@top3: 0.8611 prec@top3: 0.6111 recall@top5: 0.9167 prec@top5: 0.4000 loss_action_cls: 0.0630 2023/03/11 09:10:08 - mmengine - INFO - Epoch(train) [4][ 540/2226] lr: 6.4568e-07 eta: 10:40:20 time: 1.1482 data_time: 0.0127 memory: 70046 grad_norm: 0.1150 loss: 0.0525 recall@thr=0.5: 0.6111 prec@thr=0.5: 0.6667 recall@top3: 0.6481 prec@top3: 0.5926 recall@top5: 0.8148 prec@top5: 0.4222 loss_action_cls: 0.0525 2023/03/11 09:10:29 - mmengine - INFO - Epoch(train) [4][ 560/2226] lr: 6.4720e-07 eta: 10:39:58 time: 1.0182 data_time: 0.0108 memory: 70046 grad_norm: 0.1122 loss: 0.0791 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.5192 recall@top3: 0.7628 prec@top3: 0.7692 recall@top5: 0.8974 prec@top5: 0.5538 loss_action_cls: 0.0791 2023/03/11 09:10:49 - mmengine - INFO - Epoch(train) [4][ 580/2226] lr: 6.4873e-07 eta: 10:39:40 time: 1.0472 data_time: 0.0128 memory: 70046 grad_norm: 0.1095 loss: 0.0746 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.5185 recall@top3: 0.8056 prec@top3: 0.5926 recall@top5: 0.8611 prec@top5: 0.3778 loss_action_cls: 0.0746 2023/03/11 09:11:07 - mmengine - INFO - Epoch(train) [4][ 600/2226] lr: 6.5026e-07 eta: 10:39:05 time: 0.8937 data_time: 0.0101 memory: 70046 grad_norm: 0.1127 loss: 0.0595 recall@thr=0.5: 0.9286 prec@thr=0.5: 0.9286 recall@top3: 0.9286 prec@top3: 0.5714 recall@top5: 1.0000 prec@top5: 0.3714 loss_action_cls: 0.0595 2023/03/11 09:11:28 - mmengine - INFO - Epoch(train) [4][ 620/2226] lr: 6.5179e-07 eta: 10:38:46 time: 1.0418 data_time: 0.0096 memory: 70046 grad_norm: 0.1132 loss: 0.0625 recall@thr=0.5: 0.6472 prec@thr=0.5: 0.5986 recall@top3: 0.6028 prec@top3: 0.5556 recall@top5: 0.6750 prec@top5: 0.3833 loss_action_cls: 0.0625 2023/03/11 09:11:50 - mmengine - INFO - Epoch(train) [4][ 640/2226] lr: 6.5332e-07 eta: 10:38:31 time: 1.0924 data_time: 0.0102 memory: 70046 grad_norm: 0.1141 loss: 0.0504 recall@thr=0.5: 0.5938 prec@thr=0.5: 0.5937 recall@top3: 0.8438 prec@top3: 0.6250 recall@top5: 0.9167 prec@top5: 0.4250 loss_action_cls: 0.0504 2023/03/11 09:12:10 - mmengine - INFO - Epoch(train) [4][ 660/2226] lr: 6.5484e-07 eta: 10:38:10 time: 1.0187 data_time: 0.0104 memory: 70046 grad_norm: 0.1170 loss: 0.0500 recall@thr=0.5: 0.8095 prec@thr=0.5: 0.9524 recall@top3: 1.0000 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.4571 loss_action_cls: 0.0500 2023/03/11 09:12:30 - mmengine - INFO - Epoch(train) [4][ 680/2226] lr: 6.5637e-07 eta: 10:37:42 time: 0.9611 data_time: 0.0094 memory: 70046 grad_norm: 0.1111 loss: 0.0557 recall@thr=0.5: 0.8796 prec@thr=0.5: 0.9630 recall@top3: 0.9074 prec@top3: 0.7407 recall@top5: 1.0000 prec@top5: 0.5111 loss_action_cls: 0.0557 2023/03/11 09:12:53 - mmengine - INFO - Epoch(train) [4][ 700/2226] lr: 6.5790e-07 eta: 10:37:34 time: 1.1481 data_time: 0.0126 memory: 70046 grad_norm: 0.1136 loss: 0.0574 recall@thr=0.5: 0.7407 prec@thr=0.5: 0.8519 recall@top3: 0.8148 prec@top3: 0.5926 recall@top5: 0.8889 prec@top5: 0.4000 loss_action_cls: 0.0574 2023/03/11 09:13:12 - mmengine - INFO - Epoch(train) [4][ 720/2226] lr: 6.5943e-07 eta: 10:37:07 time: 0.9722 data_time: 0.0103 memory: 70046 grad_norm: 0.1092 loss: 0.0590 recall@thr=0.5: 0.7576 prec@thr=0.5: 0.7879 recall@top3: 0.8939 prec@top3: 0.6061 recall@top5: 1.0000 prec@top5: 0.4182 loss_action_cls: 0.0590 2023/03/11 09:13:34 - mmengine - INFO - Epoch(train) [4][ 740/2226] lr: 6.6095e-07 eta: 10:36:54 time: 1.1054 data_time: 0.0110 memory: 70046 grad_norm: 0.1146 loss: 0.0652 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.9667 recall@top3: 0.9333 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4400 loss_action_cls: 0.0652 2023/03/11 09:13:52 - mmengine - INFO - Epoch(train) [4][ 760/2226] lr: 6.6248e-07 eta: 10:36:18 time: 0.8720 data_time: 0.0101 memory: 70046 grad_norm: 0.1094 loss: 0.0496 recall@thr=0.5: 0.7273 prec@thr=0.5: 0.4788 recall@top3: 0.8333 prec@top3: 0.5758 recall@top5: 0.9394 prec@top5: 0.4182 loss_action_cls: 0.0496 2023/03/11 09:14:15 - mmengine - INFO - Epoch(train) [4][ 780/2226] lr: 6.6401e-07 eta: 10:36:10 time: 1.1600 data_time: 0.0108 memory: 70046 grad_norm: 0.1066 loss: 0.0694 recall@thr=0.5: 0.4545 prec@thr=0.5: 0.4545 recall@top3: 0.7955 prec@top3: 0.6364 recall@top5: 0.9394 prec@top5: 0.4364 loss_action_cls: 0.0694 2023/03/11 09:14:31 - mmengine - INFO - Epoch(train) [4][ 800/2226] lr: 6.6554e-07 eta: 10:35:28 time: 0.8091 data_time: 0.0076 memory: 70046 grad_norm: 0.1090 loss: 0.0680 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6875 recall@top3: 0.8750 prec@top3: 0.4167 recall@top5: 1.0000 prec@top5: 0.3000 loss_action_cls: 0.0680 2023/03/11 09:14:51 - mmengine - INFO - Epoch(train) [4][ 820/2226] lr: 6.6706e-07 eta: 10:35:06 time: 1.0188 data_time: 0.0143 memory: 70046 grad_norm: 0.1128 loss: 0.0560 recall@thr=0.5: 0.5333 prec@thr=0.5: 0.7167 recall@top3: 0.7250 prec@top3: 0.6333 recall@top5: 0.8917 prec@top5: 0.5000 loss_action_cls: 0.0560 2023/03/11 09:15:12 - mmengine - INFO - Epoch(train) [4][ 840/2226] lr: 6.6859e-07 eta: 10:34:44 time: 1.0182 data_time: 0.0135 memory: 70046 grad_norm: 0.1134 loss: 0.0542 recall@thr=0.5: 0.5167 prec@thr=0.5: 0.5500 recall@top3: 0.7833 prec@top3: 0.5000 recall@top5: 0.8833 prec@top5: 0.3600 loss_action_cls: 0.0542 2023/03/11 09:15:34 - mmengine - INFO - Epoch(train) [4][ 860/2226] lr: 6.7012e-07 eta: 10:34:32 time: 1.1180 data_time: 0.0139 memory: 70046 grad_norm: 0.1117 loss: 0.0461 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.5000 recall@top3: 0.7917 prec@top3: 0.5000 recall@top5: 0.8542 prec@top5: 0.3250 loss_action_cls: 0.0461 2023/03/11 09:15:53 - mmengine - INFO - Epoch(train) [4][ 880/2226] lr: 6.7165e-07 eta: 10:34:06 time: 0.9654 data_time: 0.0126 memory: 70046 grad_norm: 0.1123 loss: 0.0601 recall@thr=0.5: 0.6894 prec@thr=0.5: 0.7045 recall@top3: 0.8409 prec@top3: 0.6667 recall@top5: 0.8864 prec@top5: 0.4182 loss_action_cls: 0.0601 2023/03/11 09:16:15 - mmengine - INFO - Epoch(train) [4][ 900/2226] lr: 6.7317e-07 eta: 10:33:51 time: 1.0907 data_time: 0.0134 memory: 70046 grad_norm: 0.1092 loss: 0.0677 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.7778 recall@top3: 0.8519 prec@top3: 0.5926 recall@top5: 0.9259 prec@top5: 0.4000 loss_action_cls: 0.0677 2023/03/11 09:16:33 - mmengine - INFO - Epoch(train) [4][ 920/2226] lr: 6.7470e-07 eta: 10:33:17 time: 0.8951 data_time: 0.0132 memory: 70046 grad_norm: 0.1098 loss: 0.0520 recall@thr=0.5: 0.5278 prec@thr=0.5: 0.8889 recall@top3: 0.7500 prec@top3: 0.7222 recall@top5: 0.8611 prec@top5: 0.5000 loss_action_cls: 0.0520 2023/03/11 09:16:56 - mmengine - INFO - Epoch(train) [4][ 940/2226] lr: 6.7623e-07 eta: 10:33:06 time: 1.1279 data_time: 0.0132 memory: 70046 grad_norm: 0.1142 loss: 0.0614 recall@thr=0.5: 0.3807 prec@thr=0.5: 0.5789 recall@top3: 0.5079 prec@top3: 0.4737 recall@top5: 0.6939 prec@top5: 0.4000 loss_action_cls: 0.0614 2023/03/11 09:17:14 - mmengine - INFO - Epoch(train) [4][ 960/2226] lr: 6.7776e-07 eta: 10:32:37 time: 0.9405 data_time: 0.0126 memory: 70046 grad_norm: 0.1148 loss: 0.0633 recall@thr=0.5: 0.8444 prec@thr=0.5: 0.9259 recall@top3: 0.8278 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.6222 loss_action_cls: 0.0633 2023/03/11 09:17:34 - mmengine - INFO - Epoch(train) [4][ 980/2226] lr: 6.7928e-07 eta: 10:32:12 time: 0.9764 data_time: 0.0112 memory: 70046 grad_norm: 0.1117 loss: 0.0674 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.5417 recall@top3: 0.7500 prec@top3: 0.5000 recall@top5: 0.8611 prec@top5: 0.3667 loss_action_cls: 0.0674 2023/03/11 09:17:55 - mmengine - INFO - Epoch(train) [4][1000/2226] lr: 6.8081e-07 eta: 10:31:51 time: 1.0282 data_time: 0.0120 memory: 70046 grad_norm: 0.1180 loss: 0.0456 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.7857 recall@top3: 0.8571 prec@top3: 0.6667 recall@top5: 0.9286 prec@top5: 0.4286 loss_action_cls: 0.0456 2023/03/11 09:18:17 - mmengine - INFO - Epoch(train) [4][1020/2226] lr: 6.8234e-07 eta: 10:31:37 time: 1.1005 data_time: 0.0105 memory: 70046 grad_norm: 0.1140 loss: 0.0457 recall@thr=0.5: 0.4250 prec@thr=0.5: 0.7083 recall@top3: 0.7500 prec@top3: 0.7000 recall@top5: 0.9667 prec@top5: 0.5600 loss_action_cls: 0.0457 2023/03/11 09:18:32 - mmengine - INFO - Epoch(train) [4][1040/2226] lr: 6.8387e-07 eta: 10:30:52 time: 0.7713 data_time: 0.0079 memory: 70046 grad_norm: 0.1115 loss: 0.0560 recall@thr=0.5: 0.3833 prec@thr=0.5: 0.3833 recall@top3: 0.6333 prec@top3: 0.4000 recall@top5: 0.9000 prec@top5: 0.3200 loss_action_cls: 0.0560 2023/03/11 09:18:54 - mmengine - INFO - Epoch(train) [4][1060/2226] lr: 6.8539e-07 eta: 10:30:39 time: 1.1084 data_time: 0.0119 memory: 70046 grad_norm: 0.1103 loss: 0.0697 recall@thr=0.5: 0.6500 prec@thr=0.5: 0.7667 recall@top3: 0.8667 prec@top3: 0.9000 recall@top5: 0.9667 prec@top5: 0.6200 loss_action_cls: 0.0697 2023/03/11 09:19:13 - mmengine - INFO - Epoch(train) [4][1080/2226] lr: 6.8692e-07 eta: 10:30:11 time: 0.9472 data_time: 0.0144 memory: 70046 grad_norm: 0.1120 loss: 0.0625 recall@thr=0.5: 0.8704 prec@thr=0.5: 0.9444 recall@top3: 0.9259 prec@top3: 0.7407 recall@top5: 1.0000 prec@top5: 0.4889 loss_action_cls: 0.0625 2023/03/11 09:19:34 - mmengine - INFO - Epoch(train) [4][1100/2226] lr: 6.8845e-07 eta: 10:29:51 time: 1.0328 data_time: 0.0128 memory: 70046 grad_norm: 0.1097 loss: 0.0650 recall@thr=0.5: 0.6852 prec@thr=0.5: 0.7222 recall@top3: 0.7778 prec@top3: 0.4815 recall@top5: 1.0000 prec@top5: 0.3556 loss_action_cls: 0.0650 2023/03/11 09:19:55 - mmengine - INFO - Epoch(train) [4][1120/2226] lr: 6.8998e-07 eta: 10:29:31 time: 1.0365 data_time: 0.0111 memory: 70046 grad_norm: 0.1125 loss: 0.0562 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.7083 recall@top3: 0.8958 prec@top3: 0.7500 recall@top5: 1.0000 prec@top5: 0.5250 loss_action_cls: 0.0562 2023/03/11 09:20:14 - mmengine - INFO - Epoch(train) [4][1140/2226] lr: 6.9150e-07 eta: 10:29:03 time: 0.9523 data_time: 0.0150 memory: 70046 grad_norm: 0.1125 loss: 0.0694 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.6875 recall@top3: 0.9375 prec@top3: 0.3750 recall@top5: 1.0000 prec@top5: 0.2500 loss_action_cls: 0.0694 2023/03/11 09:20:36 - mmengine - INFO - Epoch(train) [4][1160/2226] lr: 6.9303e-07 eta: 10:28:50 time: 1.1047 data_time: 0.0097 memory: 70046 grad_norm: 0.1116 loss: 0.0672 recall@thr=0.5: 0.1667 prec@thr=0.5: 0.3000 recall@top3: 0.6667 prec@top3: 0.5667 recall@top5: 0.8167 prec@top5: 0.4000 loss_action_cls: 0.0672 2023/03/11 09:20:54 - mmengine - INFO - Epoch(train) [4][1180/2226] lr: 6.9456e-07 eta: 10:28:21 time: 0.9406 data_time: 0.0102 memory: 70046 grad_norm: 0.1103 loss: 0.0512 recall@thr=0.5: 0.7333 prec@thr=0.5: 0.8667 recall@top3: 0.7667 prec@top3: 0.7000 recall@top5: 0.9333 prec@top5: 0.5200 loss_action_cls: 0.0512 2023/03/11 09:21:17 - mmengine - INFO - Epoch(train) [4][1200/2226] lr: 6.9609e-07 eta: 10:28:09 time: 1.1255 data_time: 0.0092 memory: 70046 grad_norm: 0.1064 loss: 0.0597 recall@thr=0.5: 0.7000 prec@thr=0.5: 0.8000 recall@top3: 0.8000 prec@top3: 0.4667 recall@top5: 1.0000 prec@top5: 0.3600 loss_action_cls: 0.0597 2023/03/11 09:21:36 - mmengine - INFO - Epoch(train) [4][1220/2226] lr: 6.9762e-07 eta: 10:27:42 time: 0.9566 data_time: 0.0095 memory: 70046 grad_norm: 0.1088 loss: 0.0605 recall@thr=0.5: 0.4733 prec@thr=0.5: 0.5333 recall@top3: 0.5600 prec@top3: 0.4667 recall@top5: 0.7800 prec@top5: 0.4400 loss_action_cls: 0.0605 2023/03/11 09:21:59 - mmengine - INFO - Epoch(train) [4][1240/2226] lr: 6.9914e-07 eta: 10:27:30 time: 1.1217 data_time: 0.0131 memory: 70046 grad_norm: 0.1092 loss: 0.0658 recall@thr=0.5: 0.5952 prec@thr=0.5: 0.8571 recall@top3: 0.7857 prec@top3: 0.5714 recall@top5: 0.8571 prec@top5: 0.3714 loss_action_cls: 0.0658 2023/03/11 09:22:18 - mmengine - INFO - Epoch(train) [4][1260/2226] lr: 7.0067e-07 eta: 10:27:03 time: 0.9588 data_time: 0.0135 memory: 70046 grad_norm: 0.1148 loss: 0.0544 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.5556 recall@top3: 0.7222 prec@top3: 0.4815 recall@top5: 0.8519 prec@top5: 0.3556 loss_action_cls: 0.0544 2023/03/11 09:22:40 - mmengine - INFO - Epoch(train) [4][1280/2226] lr: 7.0220e-07 eta: 10:26:50 time: 1.1111 data_time: 0.0102 memory: 70046 grad_norm: 0.1102 loss: 0.0484 recall@thr=0.5: 0.7407 prec@thr=0.5: 0.6852 recall@top3: 0.8148 prec@top3: 0.6667 recall@top5: 0.9630 prec@top5: 0.4889 loss_action_cls: 0.0484 2023/03/11 09:23:01 - mmengine - INFO - Epoch(train) [4][1300/2226] lr: 7.0373e-07 eta: 10:26:31 time: 1.0460 data_time: 0.0102 memory: 70046 grad_norm: 0.1148 loss: 0.0653 recall@thr=0.5: 0.7593 prec@thr=0.5: 0.9259 recall@top3: 0.7407 prec@top3: 0.8148 recall@top5: 1.0000 prec@top5: 0.6667 loss_action_cls: 0.0653 2023/03/11 09:23:19 - mmengine - INFO - Epoch(train) [4][1320/2226] lr: 7.0525e-07 eta: 10:25:59 time: 0.9053 data_time: 0.0130 memory: 70046 grad_norm: 0.1112 loss: 0.0621 recall@thr=0.5: 0.6742 prec@thr=0.5: 0.8182 recall@top3: 0.8485 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4909 loss_action_cls: 0.0621 2023/03/11 09:23:24 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 09:23:39 - mmengine - INFO - Epoch(train) [4][1340/2226] lr: 7.0678e-07 eta: 10:25:38 time: 1.0194 data_time: 0.0121 memory: 70046 grad_norm: 0.1115 loss: 0.0475 recall@thr=0.5: 0.7262 prec@thr=0.5: 0.7815 recall@top3: 0.8601 prec@top3: 0.7500 recall@top5: 0.8869 prec@top5: 0.4714 loss_action_cls: 0.0475 2023/03/11 09:23:58 - mmengine - INFO - Epoch(train) [4][1360/2226] lr: 7.0831e-07 eta: 10:25:08 time: 0.9255 data_time: 0.0125 memory: 70046 grad_norm: 0.1138 loss: 0.0479 recall@thr=0.5: 0.4722 prec@thr=0.5: 0.7222 recall@top3: 0.5278 prec@top3: 0.6296 recall@top5: 0.7500 prec@top5: 0.5556 loss_action_cls: 0.0479 2023/03/11 09:24:22 - mmengine - INFO - Epoch(train) [4][1380/2226] lr: 7.0984e-07 eta: 10:25:02 time: 1.1854 data_time: 0.0138 memory: 70046 grad_norm: 0.1097 loss: 0.0525 recall@thr=0.5: 0.7111 prec@thr=0.5: 0.7778 recall@top3: 0.8556 prec@top3: 0.6444 recall@top5: 0.9000 prec@top5: 0.4133 loss_action_cls: 0.0525 2023/03/11 09:24:40 - mmengine - INFO - Epoch(train) [4][1400/2226] lr: 7.1136e-07 eta: 10:24:32 time: 0.9240 data_time: 0.0084 memory: 70046 grad_norm: 0.1111 loss: 0.0543 recall@thr=0.5: 0.7708 prec@thr=0.5: 0.9375 recall@top3: 0.9062 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4750 loss_action_cls: 0.0543 2023/03/11 09:25:00 - mmengine - INFO - Epoch(train) [4][1420/2226] lr: 7.1289e-07 eta: 10:24:07 time: 0.9876 data_time: 0.0108 memory: 70046 grad_norm: 0.1058 loss: 0.0561 recall@thr=0.5: 0.5714 prec@thr=0.5: 0.5714 recall@top3: 0.8571 prec@top3: 0.5714 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0561 2023/03/11 09:25:23 - mmengine - INFO - Epoch(train) [4][1440/2226] lr: 7.1442e-07 eta: 10:23:58 time: 1.1484 data_time: 0.0117 memory: 70046 grad_norm: 0.1110 loss: 0.0513 recall@thr=0.5: 0.4286 prec@thr=0.5: 0.5714 recall@top3: 0.7619 prec@top3: 0.6190 recall@top5: 0.7619 prec@top5: 0.3714 loss_action_cls: 0.0513 2023/03/11 09:25:43 - mmengine - INFO - Epoch(train) [4][1460/2226] lr: 7.1595e-07 eta: 10:23:37 time: 1.0310 data_time: 0.0094 memory: 70046 grad_norm: 0.1090 loss: 0.0477 recall@thr=0.5: 0.6833 prec@thr=0.5: 0.7500 recall@top3: 0.8000 prec@top3: 0.5333 recall@top5: 0.9000 prec@top5: 0.3800 loss_action_cls: 0.0477 2023/03/11 09:25:58 - mmengine - INFO - Epoch(train) [4][1480/2226] lr: 7.1747e-07 eta: 10:22:48 time: 0.7075 data_time: 0.0094 memory: 70046 grad_norm: 0.1119 loss: 0.0564 recall@thr=0.5: 0.6481 prec@thr=0.5: 0.7222 recall@top3: 0.7222 prec@top3: 0.7037 recall@top5: 0.8704 prec@top5: 0.5111 loss_action_cls: 0.0564 2023/03/11 09:26:23 - mmengine - INFO - Epoch(train) [4][1500/2226] lr: 7.1900e-07 eta: 10:22:48 time: 1.2597 data_time: 0.0131 memory: 70046 grad_norm: 0.1159 loss: 0.0698 recall@thr=0.5: 0.5530 prec@thr=0.5: 0.5091 recall@top3: 0.6667 prec@top3: 0.5758 recall@top5: 0.8788 prec@top5: 0.4909 loss_action_cls: 0.0698 2023/03/11 09:26:41 - mmengine - INFO - Epoch(train) [4][1520/2226] lr: 7.2053e-07 eta: 10:22:18 time: 0.9240 data_time: 0.0091 memory: 70046 grad_norm: 0.1149 loss: 0.0688 recall@thr=0.5: 0.8854 prec@thr=0.5: 1.0000 recall@top3: 0.9375 prec@top3: 0.9167 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0688 2023/03/11 09:27:02 - mmengine - INFO - Epoch(train) [4][1540/2226] lr: 7.2206e-07 eta: 10:21:58 time: 1.0272 data_time: 0.0098 memory: 70046 grad_norm: 0.1091 loss: 0.0629 recall@thr=0.5: 0.5769 prec@thr=0.5: 0.7308 recall@top3: 0.6923 prec@top3: 0.5128 recall@top5: 0.8077 prec@top5: 0.3846 loss_action_cls: 0.0629 2023/03/11 09:27:21 - mmengine - INFO - Epoch(train) [4][1560/2226] lr: 7.2358e-07 eta: 10:21:33 time: 0.9795 data_time: 0.0104 memory: 70046 grad_norm: 0.1065 loss: 0.0592 recall@thr=0.5: 0.7812 prec@thr=0.5: 0.6875 recall@top3: 0.7812 prec@top3: 0.4375 recall@top5: 0.8750 prec@top5: 0.3000 loss_action_cls: 0.0592 2023/03/11 09:27:39 - mmengine - INFO - Epoch(train) [4][1580/2226] lr: 7.2511e-07 eta: 10:21:01 time: 0.8986 data_time: 0.0107 memory: 70046 grad_norm: 0.1110 loss: 0.0435 recall@thr=0.5: 0.6905 prec@thr=0.5: 0.8571 recall@top3: 1.0000 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0435 2023/03/11 09:28:00 - mmengine - INFO - Epoch(train) [4][1600/2226] lr: 7.2664e-07 eta: 10:20:39 time: 1.0122 data_time: 0.0127 memory: 70046 grad_norm: 0.1090 loss: 0.0603 recall@thr=0.5: 0.2778 prec@thr=0.5: 0.3750 recall@top3: 0.4306 prec@top3: 0.3611 recall@top5: 0.5972 prec@top5: 0.3167 loss_action_cls: 0.0603 2023/03/11 09:28:23 - mmengine - INFO - Epoch(train) [4][1620/2226] lr: 7.2817e-07 eta: 10:20:30 time: 1.1575 data_time: 0.0107 memory: 70046 grad_norm: 0.1124 loss: 0.0630 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.8333 recall@top3: 0.7778 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.5333 loss_action_cls: 0.0630 2023/03/11 09:28:42 - mmengine - INFO - Epoch(train) [4][1640/2226] lr: 7.2969e-07 eta: 10:20:05 time: 0.9807 data_time: 0.0092 memory: 70046 grad_norm: 0.1067 loss: 0.0529 recall@thr=0.5: 0.9259 prec@thr=0.5: 0.9278 recall@top3: 1.0000 prec@top3: 0.8148 recall@top5: 1.0000 prec@top5: 0.4889 loss_action_cls: 0.0529 2023/03/11 09:29:04 - mmengine - INFO - Epoch(train) [4][1660/2226] lr: 7.3122e-07 eta: 10:19:49 time: 1.0837 data_time: 0.0090 memory: 70046 grad_norm: 0.1064 loss: 0.0460 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.9167 recall@top3: 0.8611 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.5667 loss_action_cls: 0.0460 2023/03/11 09:29:25 - mmengine - INFO - Epoch(train) [4][1680/2226] lr: 7.3275e-07 eta: 10:19:30 time: 1.0423 data_time: 0.0093 memory: 70046 grad_norm: 0.1098 loss: 0.0465 recall@thr=0.5: 1.0000 prec@thr=0.5: 0.9583 recall@top3: 1.0000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0465 2023/03/11 09:29:46 - mmengine - INFO - Epoch(train) [4][1700/2226] lr: 7.3428e-07 eta: 10:19:12 time: 1.0564 data_time: 0.0091 memory: 70046 grad_norm: 0.1096 loss: 0.0557 recall@thr=0.5: 0.5278 prec@thr=0.5: 0.6944 recall@top3: 0.6667 prec@top3: 0.5556 recall@top5: 0.9514 prec@top5: 0.4500 loss_action_cls: 0.0557 2023/03/11 09:30:06 - mmengine - INFO - Epoch(train) [4][1720/2226] lr: 7.3580e-07 eta: 10:18:51 time: 1.0168 data_time: 0.0089 memory: 70046 grad_norm: 0.1097 loss: 0.0666 recall@thr=0.5: 0.6905 prec@thr=0.5: 1.0000 recall@top3: 0.8810 prec@top3: 0.7619 recall@top5: 0.9643 prec@top5: 0.5143 loss_action_cls: 0.0666 2023/03/11 09:30:27 - mmengine - INFO - Epoch(train) [4][1740/2226] lr: 7.3733e-07 eta: 10:18:29 time: 1.0205 data_time: 0.0091 memory: 70046 grad_norm: 0.1054 loss: 0.0596 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.7619 recall@top5: 0.8571 prec@top5: 0.4571 loss_action_cls: 0.0596 2023/03/11 09:30:46 - mmengine - INFO - Epoch(train) [4][1760/2226] lr: 7.3886e-07 eta: 10:18:02 time: 0.9516 data_time: 0.0095 memory: 70046 grad_norm: 0.1089 loss: 0.0569 recall@thr=0.5: 0.8264 prec@thr=0.5: 0.7500 recall@top3: 0.8264 prec@top3: 0.6389 recall@top5: 0.9792 prec@top5: 0.4500 loss_action_cls: 0.0569 2023/03/11 09:31:07 - mmengine - INFO - Epoch(train) [4][1780/2226] lr: 7.4039e-07 eta: 10:17:44 time: 1.0581 data_time: 0.0118 memory: 70046 grad_norm: 0.1071 loss: 0.0547 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.3583 recall@top3: 0.5667 prec@top3: 0.4000 recall@top5: 0.9167 prec@top5: 0.4200 loss_action_cls: 0.0547 2023/03/11 09:31:28 - mmengine - INFO - Epoch(train) [4][1800/2226] lr: 7.4192e-07 eta: 10:17:27 time: 1.0695 data_time: 0.0096 memory: 70046 grad_norm: 0.1085 loss: 0.0613 recall@thr=0.5: 0.7731 prec@thr=0.5: 0.6611 recall@top3: 0.7176 prec@top3: 0.6296 recall@top5: 0.8981 prec@top5: 0.4778 loss_action_cls: 0.0613 2023/03/11 09:31:45 - mmengine - INFO - Epoch(train) [4][1820/2226] lr: 7.4344e-07 eta: 10:16:51 time: 0.8397 data_time: 0.0088 memory: 70046 grad_norm: 0.1106 loss: 0.0469 recall@thr=0.5: 0.5185 prec@thr=0.5: 0.6111 recall@top3: 1.0000 prec@top3: 0.5185 recall@top5: 1.0000 prec@top5: 0.3111 loss_action_cls: 0.0469 2023/03/11 09:32:03 - mmengine - INFO - Epoch(train) [4][1840/2226] lr: 7.4497e-07 eta: 10:16:20 time: 0.9073 data_time: 0.0115 memory: 70046 grad_norm: 0.1081 loss: 0.0566 recall@thr=0.5: 0.6544 prec@thr=0.5: 0.8667 recall@top3: 0.8411 prec@top3: 0.8667 recall@top5: 1.0000 prec@top5: 0.6400 loss_action_cls: 0.0566 2023/03/11 09:32:25 - mmengine - INFO - Epoch(train) [4][1860/2226] lr: 7.4650e-07 eta: 10:16:05 time: 1.0965 data_time: 0.0109 memory: 70046 grad_norm: 0.1084 loss: 0.0524 recall@thr=0.5: 0.6154 prec@thr=0.5: 0.6154 recall@top3: 0.8077 prec@top3: 0.6410 recall@top5: 0.8846 prec@top5: 0.4154 loss_action_cls: 0.0524 2023/03/11 09:32:48 - mmengine - INFO - Epoch(train) [4][1880/2226] lr: 7.4803e-07 eta: 10:15:53 time: 1.1282 data_time: 0.0107 memory: 70046 grad_norm: 0.1116 loss: 0.0519 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.6667 recall@top5: 0.8571 prec@top5: 0.4000 loss_action_cls: 0.0519 2023/03/11 09:33:05 - mmengine - INFO - Epoch(train) [4][1900/2226] lr: 7.4955e-07 eta: 10:15:19 time: 0.8600 data_time: 0.0092 memory: 70046 grad_norm: 0.1102 loss: 0.0362 recall@thr=0.5: 0.8125 prec@thr=0.5: 0.8750 recall@top3: 0.9167 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0362 2023/03/11 09:33:27 - mmengine - INFO - Epoch(train) [4][1920/2226] lr: 7.5108e-07 eta: 10:15:03 time: 1.0826 data_time: 0.0103 memory: 70046 grad_norm: 0.1148 loss: 0.0550 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8148 recall@top3: 0.8889 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.3778 loss_action_cls: 0.0550 2023/03/11 09:33:45 - mmengine - INFO - Epoch(train) [4][1940/2226] lr: 7.5261e-07 eta: 10:14:33 time: 0.9108 data_time: 0.0104 memory: 70046 grad_norm: 0.1071 loss: 0.0653 recall@thr=0.5: 0.6905 prec@thr=0.5: 0.7024 recall@top3: 0.8095 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.5143 loss_action_cls: 0.0653 2023/03/11 09:34:07 - mmengine - INFO - Epoch(train) [4][1960/2226] lr: 7.5414e-07 eta: 10:14:20 time: 1.1210 data_time: 0.0104 memory: 70046 grad_norm: 0.1063 loss: 0.0522 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.8667 recall@top3: 1.0000 prec@top3: 0.6000 recall@top5: 1.0000 prec@top5: 0.3600 loss_action_cls: 0.0522 2023/03/11 09:34:26 - mmengine - INFO - Epoch(train) [4][1980/2226] lr: 7.5566e-07 eta: 10:13:50 time: 0.9152 data_time: 0.0082 memory: 70046 grad_norm: 0.1103 loss: 0.0632 recall@thr=0.5: 0.8974 prec@thr=0.5: 0.8974 recall@top3: 0.8974 prec@top3: 0.7436 recall@top5: 1.0000 prec@top5: 0.4769 loss_action_cls: 0.0632 2023/03/11 09:34:49 - mmengine - INFO - Epoch(train) [4][2000/2226] lr: 7.5719e-07 eta: 10:13:41 time: 1.1697 data_time: 0.0091 memory: 70046 grad_norm: 0.1107 loss: 0.0529 recall@thr=0.5: 0.6818 prec@thr=0.5: 0.6970 recall@top3: 0.7879 prec@top3: 0.7273 recall@top5: 0.9091 prec@top5: 0.5273 loss_action_cls: 0.0529 2023/03/11 09:35:08 - mmengine - INFO - Epoch(train) [4][2020/2226] lr: 7.5872e-07 eta: 10:13:15 time: 0.9606 data_time: 0.0098 memory: 70046 grad_norm: 0.1065 loss: 0.0561 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 0.7143 prec@top3: 0.3810 recall@top5: 0.8571 prec@top5: 0.2857 loss_action_cls: 0.0561 2023/03/11 09:35:29 - mmengine - INFO - Epoch(train) [4][2040/2226] lr: 7.6025e-07 eta: 10:12:56 time: 1.0450 data_time: 0.0103 memory: 70046 grad_norm: 0.1117 loss: 0.0440 recall@thr=0.5: 0.8500 prec@thr=0.5: 1.0000 recall@top3: 0.8500 prec@top3: 0.6000 recall@top5: 1.0000 prec@top5: 0.4400 loss_action_cls: 0.0440 2023/03/11 09:35:47 - mmengine - INFO - Epoch(train) [4][2060/2226] lr: 7.6177e-07 eta: 10:12:23 time: 0.8797 data_time: 0.0101 memory: 70046 grad_norm: 0.1096 loss: 0.0496 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.7037 recall@top3: 0.6667 prec@top3: 0.5556 recall@top5: 0.8148 prec@top5: 0.4222 loss_action_cls: 0.0496 2023/03/11 09:36:09 - mmengine - INFO - Epoch(train) [4][2080/2226] lr: 7.6330e-07 eta: 10:12:11 time: 1.1268 data_time: 0.0110 memory: 70046 grad_norm: 0.1050 loss: 0.0659 recall@thr=0.5: 0.4333 prec@thr=0.5: 0.8000 recall@top3: 0.6500 prec@top3: 0.5667 recall@top5: 0.9667 prec@top5: 0.5000 loss_action_cls: 0.0659 2023/03/11 09:36:31 - mmengine - INFO - Epoch(train) [4][2100/2226] lr: 7.6483e-07 eta: 10:11:56 time: 1.0942 data_time: 0.0100 memory: 70046 grad_norm: 0.1080 loss: 0.0386 recall@thr=0.5: 0.7627 prec@thr=0.5: 0.9314 recall@top3: 0.7912 prec@top3: 0.8039 recall@top5: 0.9314 prec@top5: 0.5882 loss_action_cls: 0.0386 2023/03/11 09:36:48 - mmengine - INFO - Epoch(train) [4][2120/2226] lr: 7.6636e-07 eta: 10:11:23 time: 0.8692 data_time: 0.0104 memory: 70046 grad_norm: 0.1110 loss: 0.0666 recall@thr=0.5: 0.7407 prec@thr=0.5: 0.8148 recall@top3: 0.8148 prec@top3: 0.7037 recall@top5: 1.0000 prec@top5: 0.5111 loss_action_cls: 0.0666 2023/03/11 09:37:12 - mmengine - INFO - Epoch(train) [4][2140/2226] lr: 7.6788e-07 eta: 10:11:15 time: 1.1896 data_time: 0.0102 memory: 70046 grad_norm: 0.1058 loss: 0.0574 recall@thr=0.5: 0.8667 prec@thr=0.5: 0.9524 recall@top3: 0.8952 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.5429 loss_action_cls: 0.0574 2023/03/11 09:37:31 - mmengine - INFO - Epoch(train) [4][2160/2226] lr: 7.6941e-07 eta: 10:10:49 time: 0.9579 data_time: 0.0083 memory: 70046 grad_norm: 0.1069 loss: 0.0520 recall@thr=0.5: 0.3833 prec@thr=0.5: 0.4083 recall@top3: 0.8833 prec@top3: 0.5333 recall@top5: 0.9333 prec@top5: 0.3400 loss_action_cls: 0.0520 2023/03/11 09:37:53 - mmengine - INFO - Epoch(train) [4][2180/2226] lr: 7.7094e-07 eta: 10:10:32 time: 1.0680 data_time: 0.0096 memory: 70046 grad_norm: 0.1083 loss: 0.0617 recall@thr=0.5: 0.2593 prec@thr=0.5: 0.3333 recall@top3: 0.3333 prec@top3: 0.2963 recall@top5: 0.5185 prec@top5: 0.2444 loss_action_cls: 0.0617 2023/03/11 09:38:12 - mmengine - INFO - Epoch(train) [4][2200/2226] lr: 7.7247e-07 eta: 10:10:06 time: 0.9657 data_time: 0.0103 memory: 70046 grad_norm: 0.1061 loss: 0.0482 recall@thr=0.5: 0.5500 prec@thr=0.5: 0.8750 recall@top3: 0.8000 prec@top3: 0.5833 recall@top5: 0.9750 prec@top5: 0.4500 loss_action_cls: 0.0482 2023/03/11 09:38:30 - mmengine - INFO - Epoch(train) [4][2220/2226] lr: 7.7399e-07 eta: 10:09:37 time: 0.9162 data_time: 0.0110 memory: 70046 grad_norm: 0.1049 loss: 0.0418 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.6667 recall@top3: 1.0000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0418 2023/03/11 09:38:34 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 09:38:34 - mmengine - INFO - Epoch(train) [4][2226/2226] lr: 7.7445e-07 eta: 10:09:21 time: 0.7518 data_time: 0.0074 memory: 70046 grad_norm: 0.1078 loss: 0.0381 recall@thr=0.5: 0.8667 prec@thr=0.5: 1.0000 recall@top3: 0.8667 prec@top3: 0.6000 recall@top5: 0.8667 prec@top5: 0.3600 loss_action_cls: 0.0381 2023/03/11 09:38:34 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/03/11 09:38:50 - mmengine - INFO - Epoch(val) [4][ 20/1571] eta: 0:05:49 time: 0.2255 data_time: 0.1257 memory: 6688 2023/03/11 09:38:54 - mmengine - INFO - Epoch(val) [4][ 40/1571] eta: 0:05:11 time: 0.1815 data_time: 0.0630 memory: 7490 2023/03/11 09:38:57 - mmengine - INFO - Epoch(val) [4][ 60/1571] eta: 0:04:53 time: 0.1753 data_time: 0.0514 memory: 7490 2023/03/11 09:39:01 - mmengine - INFO - Epoch(val) [4][ 80/1571] eta: 0:04:43 time: 0.1779 data_time: 0.0683 memory: 7490 2023/03/11 09:39:05 - mmengine - INFO - Epoch(val) [4][ 100/1571] eta: 0:04:42 time: 0.2012 data_time: 0.0659 memory: 7490 2023/03/11 09:39:08 - mmengine - INFO - Epoch(val) [4][ 120/1571] eta: 0:04:26 time: 0.1421 data_time: 0.0397 memory: 6775 2023/03/11 09:39:11 - mmengine - INFO - Epoch(val) [4][ 140/1571] eta: 0:04:19 time: 0.1638 data_time: 0.0667 memory: 6775 2023/03/11 09:39:15 - mmengine - INFO - Epoch(val) [4][ 160/1571] eta: 0:04:14 time: 0.1757 data_time: 0.0796 memory: 6775 2023/03/11 09:39:19 - mmengine - INFO - Epoch(val) [4][ 180/1571] eta: 0:04:15 time: 0.2080 data_time: 0.1107 memory: 7490 2023/03/11 09:39:23 - mmengine - INFO - Epoch(val) [4][ 200/1571] eta: 0:04:15 time: 0.2115 data_time: 0.0639 memory: 7490 2023/03/11 09:39:27 - mmengine - INFO - Epoch(val) [4][ 220/1571] eta: 0:04:13 time: 0.2027 data_time: 0.1008 memory: 7490 2023/03/11 09:39:30 - mmengine - INFO - Epoch(val) [4][ 240/1571] eta: 0:04:05 time: 0.1492 data_time: 0.0568 memory: 6775 2023/03/11 09:39:33 - mmengine - INFO - Epoch(val) [4][ 260/1571] eta: 0:04:00 time: 0.1698 data_time: 0.0735 memory: 6775 2023/03/11 09:39:36 - mmengine - INFO - Epoch(val) [4][ 280/1571] eta: 0:03:52 time: 0.1347 data_time: 0.0376 memory: 6775 2023/03/11 09:39:40 - mmengine - INFO - Epoch(val) [4][ 300/1571] eta: 0:03:49 time: 0.1875 data_time: 0.0830 memory: 6775 2023/03/11 09:39:44 - mmengine - INFO - Epoch(val) [4][ 320/1571] eta: 0:03:46 time: 0.1947 data_time: 0.0705 memory: 7490 2023/03/11 09:39:48 - mmengine - INFO - Epoch(val) [4][ 340/1571] eta: 0:03:46 time: 0.2231 data_time: 0.0871 memory: 7490 2023/03/11 09:39:52 - mmengine - INFO - Epoch(val) [4][ 360/1571] eta: 0:03:43 time: 0.1965 data_time: 0.0623 memory: 7490 2023/03/11 09:39:56 - mmengine - INFO - Epoch(val) [4][ 380/1571] eta: 0:03:38 time: 0.1727 data_time: 0.0386 memory: 7490 2023/03/11 09:40:00 - mmengine - INFO - Epoch(val) [4][ 400/1571] eta: 0:03:37 time: 0.2186 data_time: 0.0164 memory: 8853 2023/03/11 09:40:03 - mmengine - INFO - Epoch(val) [4][ 420/1571] eta: 0:03:31 time: 0.1524 data_time: 0.0037 memory: 8853 2023/03/11 09:40:06 - mmengine - INFO - Epoch(val) [4][ 440/1571] eta: 0:03:25 time: 0.1377 data_time: 0.0022 memory: 7490 2023/03/11 09:40:09 - mmengine - INFO - Epoch(val) [4][ 460/1571] eta: 0:03:21 time: 0.1632 data_time: 0.0268 memory: 7490 2023/03/11 09:40:13 - mmengine - INFO - Epoch(val) [4][ 480/1571] eta: 0:03:17 time: 0.1852 data_time: 0.0521 memory: 7490 2023/03/11 09:40:17 - mmengine - INFO - Epoch(val) [4][ 500/1571] eta: 0:03:14 time: 0.1927 data_time: 0.0814 memory: 7490 2023/03/11 09:40:20 - mmengine - INFO - Epoch(val) [4][ 520/1571] eta: 0:03:10 time: 0.1624 data_time: 0.0632 memory: 6775 2023/03/11 09:40:24 - mmengine - INFO - Epoch(val) [4][ 540/1571] eta: 0:03:06 time: 0.1811 data_time: 0.0820 memory: 6775 2023/03/11 09:40:27 - mmengine - INFO - Epoch(val) [4][ 560/1571] eta: 0:03:01 time: 0.1534 data_time: 0.0517 memory: 6775 2023/03/11 09:40:30 - mmengine - INFO - Epoch(val) [4][ 580/1571] eta: 0:02:57 time: 0.1570 data_time: 0.0631 memory: 6775 2023/03/11 09:40:33 - mmengine - INFO - Epoch(val) [4][ 600/1571] eta: 0:02:52 time: 0.1436 data_time: 0.0495 memory: 6775 2023/03/11 09:40:37 - mmengine - INFO - Epoch(val) [4][ 620/1571] eta: 0:02:50 time: 0.2050 data_time: 0.0897 memory: 7490 2023/03/11 09:40:40 - mmengine - INFO - Epoch(val) [4][ 640/1571] eta: 0:02:46 time: 0.1738 data_time: 0.0383 memory: 7490 2023/03/11 09:40:45 - mmengine - INFO - Epoch(val) [4][ 660/1571] eta: 0:02:44 time: 0.2265 data_time: 0.0841 memory: 7490 2023/03/11 09:40:49 - mmengine - INFO 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eta: 0:01:41 time: 0.1584 data_time: 0.0225 memory: 7490 2023/03/11 09:41:48 - mmengine - INFO - Epoch(val) [4][1020/1571] eta: 0:01:38 time: 0.1965 data_time: 0.0374 memory: 8699 2023/03/11 09:41:52 - mmengine - INFO - Epoch(val) [4][1040/1571] eta: 0:01:34 time: 0.1589 data_time: 0.0021 memory: 8699 2023/03/11 09:41:55 - mmengine - INFO - Epoch(val) [4][1060/1571] eta: 0:01:31 time: 0.1698 data_time: 0.0738 memory: 6775 2023/03/11 09:41:58 - mmengine - INFO - Epoch(val) [4][1080/1571] eta: 0:01:27 time: 0.1703 data_time: 0.0732 memory: 6775 2023/03/11 09:42:02 - mmengine - INFO - Epoch(val) [4][1100/1571] eta: 0:01:24 time: 0.1851 data_time: 0.0573 memory: 7490 2023/03/11 09:42:06 - mmengine - INFO - Epoch(val) [4][1120/1571] eta: 0:01:20 time: 0.1769 data_time: 0.0332 memory: 7610 2023/03/11 09:42:09 - mmengine - INFO - Epoch(val) [4][1140/1571] eta: 0:01:16 time: 0.1612 data_time: 0.0355 memory: 7610 2023/03/11 09:42:12 - mmengine - INFO - Epoch(val) [4][1160/1571] eta: 0:01:13 time: 0.1741 data_time: 0.0614 memory: 7610 2023/03/11 09:42:16 - mmengine - INFO - Epoch(val) [4][1180/1571] eta: 0:01:09 time: 0.1799 data_time: 0.0342 memory: 7610 2023/03/11 09:42:19 - mmengine - INFO - Epoch(val) [4][1200/1571] eta: 0:01:05 time: 0.1597 data_time: 0.0553 memory: 7057 2023/03/11 09:42:23 - mmengine - INFO - Epoch(val) [4][1220/1571] eta: 0:01:02 time: 0.1964 data_time: 0.0579 memory: 7490 2023/03/11 09:42:27 - mmengine - INFO - Epoch(val) [4][1240/1571] eta: 0:00:58 time: 0.1770 data_time: 0.0374 memory: 7490 2023/03/11 09:42:30 - mmengine - INFO - Epoch(val) [4][1260/1571] eta: 0:00:55 time: 0.1758 data_time: 0.0580 memory: 7490 2023/03/11 09:42:33 - mmengine - INFO - Epoch(val) [4][1280/1571] eta: 0:00:51 time: 0.1579 data_time: 0.0647 memory: 6775 2023/03/11 09:42:37 - mmengine - INFO - Epoch(val) [4][1300/1571] eta: 0:00:48 time: 0.1777 data_time: 0.0729 memory: 6775 2023/03/11 09:42:40 - mmengine - INFO - Epoch(val) [4][1320/1571] eta: 0:00:44 time: 0.1599 data_time: 0.0666 memory: 6775 2023/03/11 09:42:44 - mmengine - INFO - Epoch(val) [4][1340/1571] eta: 0:00:40 time: 0.1767 data_time: 0.0806 memory: 6775 2023/03/11 09:42:47 - mmengine - INFO - Epoch(val) [4][1360/1571] eta: 0:00:37 time: 0.1634 data_time: 0.0650 memory: 6775 2023/03/11 09:42:50 - mmengine - INFO - Epoch(val) [4][1380/1571] eta: 0:00:33 time: 0.1789 data_time: 0.0801 memory: 7057 2023/03/11 09:42:54 - mmengine - INFO - Epoch(val) [4][1400/1571] eta: 0:00:30 time: 0.1678 data_time: 0.0608 memory: 7057 2023/03/11 09:42:57 - mmengine - INFO - Epoch(val) [4][1420/1571] eta: 0:00:26 time: 0.1805 data_time: 0.0719 memory: 7057 2023/03/11 09:43:00 - mmengine - INFO - Epoch(val) [4][1440/1571] eta: 0:00:23 time: 0.1531 data_time: 0.0493 memory: 7160 2023/03/11 09:43:04 - mmengine - INFO - Epoch(val) [4][1460/1571] eta: 0:00:19 time: 0.1736 data_time: 0.0552 memory: 7160 2023/03/11 09:43:07 - mmengine - INFO - Epoch(val) [4][1480/1571] eta: 0:00:16 time: 0.1439 data_time: 0.0406 memory: 7057 2023/03/11 09:43:10 - mmengine - INFO - Epoch(val) [4][1500/1571] eta: 0:00:12 time: 0.1645 data_time: 0.0602 memory: 7490 2023/03/11 09:43:13 - mmengine - INFO - Epoch(val) [4][1520/1571] eta: 0:00:08 time: 0.1324 data_time: 0.0017 memory: 7490 2023/03/11 09:43:15 - mmengine - INFO - Epoch(val) [4][1540/1571] eta: 0:00:05 time: 0.1326 data_time: 0.0020 memory: 7490 2023/03/11 09:43:18 - mmengine - INFO - Epoch(val) [4][1560/1571] eta: 0:00:01 time: 0.1325 data_time: 0.0019 memory: 7490 2023/03/11 09:47:39 - mmengine - INFO - Epoch(val) [4][1571/1571] mAP/mAP@0.5IOU: 0.3670 2023/03/11 09:47:39 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/hukai/mmaction2/work_dirs/vit-l_16x4/best_mAP/mAP@0.5IOU_epoch_3.pth is removed 2023/03/11 09:47:44 - mmengine - INFO - The best checkpoint with 0.3670 mAP/mAP@0.5IOU at 4 epoch is saved to best_mAP/mAP@0.5IOU_epoch_4.pth. 2023/03/11 09:48:08 - mmengine - INFO - Epoch(train) [5][ 20/2226] lr: 7.7598e-07 eta: 10:09:14 time: 1.1890 data_time: 0.5202 memory: 70046 grad_norm: 0.1079 loss: 0.0530 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.8889 recall@top3: 0.8704 prec@top3: 0.8889 recall@top5: 0.9259 prec@top5: 0.5778 loss_action_cls: 0.0530 2023/03/11 09:48:31 - mmengine - INFO - Epoch(train) [5][ 40/2226] lr: 7.7751e-07 eta: 10:09:03 time: 1.1533 data_time: 0.0118 memory: 70046 grad_norm: 0.1063 loss: 0.0555 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.6800 recall@top3: 0.6500 prec@top3: 0.6667 recall@top5: 0.9000 prec@top5: 0.5200 loss_action_cls: 0.0555 2023/03/11 09:48:57 - mmengine - INFO - Epoch(train) [5][ 60/2226] lr: 7.7904e-07 eta: 10:09:02 time: 1.2713 data_time: 0.0138 memory: 70046 grad_norm: 0.1104 loss: 0.0625 recall@thr=0.5: 0.6950 prec@thr=0.5: 0.7000 recall@top3: 0.8517 prec@top3: 0.5667 recall@top5: 0.9500 prec@top5: 0.4200 loss_action_cls: 0.0625 2023/03/11 09:49:18 - mmengine - INFO - Epoch(train) [5][ 80/2226] lr: 7.8056e-07 eta: 10:08:44 time: 1.0642 data_time: 0.0116 memory: 70046 grad_norm: 0.1098 loss: 0.0495 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.8571 recall@top3: 0.7024 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.4571 loss_action_cls: 0.0495 2023/03/11 09:49:34 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 09:49:40 - mmengine - INFO - Epoch(train) [5][ 100/2226] lr: 7.8209e-07 eta: 10:08:28 time: 1.0855 data_time: 0.0121 memory: 70046 grad_norm: 0.1081 loss: 0.0577 recall@thr=0.5: 0.9444 prec@thr=0.5: 0.8889 recall@top3: 1.0000 prec@top3: 0.4444 recall@top5: 1.0000 prec@top5: 0.2667 loss_action_cls: 0.0577 2023/03/11 09:50:02 - mmengine - INFO - Epoch(train) [5][ 120/2226] lr: 7.8362e-07 eta: 10:08:15 time: 1.1117 data_time: 0.0123 memory: 70046 grad_norm: 0.1086 loss: 0.0646 recall@thr=0.5: 0.3857 prec@thr=0.5: 0.6071 recall@top3: 0.5048 prec@top3: 0.4524 recall@top5: 0.7119 prec@top5: 0.4000 loss_action_cls: 0.0646 2023/03/11 09:50:25 - mmengine - INFO - Epoch(train) [5][ 140/2226] lr: 7.8515e-07 eta: 10:08:06 time: 1.1795 data_time: 0.0133 memory: 70046 grad_norm: 0.1098 loss: 0.0623 recall@thr=0.5: 0.6296 prec@thr=0.5: 0.6667 recall@top3: 0.9074 prec@top3: 0.5556 recall@top5: 0.9074 prec@top5: 0.3333 loss_action_cls: 0.0623 2023/03/11 09:50:42 - mmengine - INFO - Epoch(train) [5][ 160/2226] lr: 7.8667e-07 eta: 10:07:29 time: 0.8184 data_time: 0.0089 memory: 70046 grad_norm: 0.1057 loss: 0.0502 recall@thr=0.5: 0.7667 prec@thr=0.5: 0.8000 recall@top3: 0.8500 prec@top3: 0.7667 recall@top5: 1.0000 prec@top5: 0.5600 loss_action_cls: 0.0502 2023/03/11 09:51:05 - mmengine - INFO - Epoch(train) [5][ 180/2226] lr: 7.8820e-07 eta: 10:07:18 time: 1.1567 data_time: 0.0143 memory: 70046 grad_norm: 0.1098 loss: 0.0566 recall@thr=0.5: 0.4375 prec@thr=0.5: 0.7500 recall@top3: 0.7500 prec@top3: 0.5000 recall@top5: 0.8750 prec@top5: 0.3750 loss_action_cls: 0.0566 2023/03/11 09:51:26 - mmengine - INFO - Epoch(train) [5][ 200/2226] lr: 7.8973e-07 eta: 10:07:00 time: 1.0527 data_time: 0.0117 memory: 70046 grad_norm: 0.1057 loss: 0.0495 recall@thr=0.5: 0.5122 prec@thr=0.5: 0.6500 recall@top3: 0.7011 prec@top3: 0.6444 recall@top5: 0.9033 prec@top5: 0.4800 loss_action_cls: 0.0495 2023/03/11 09:51:47 - mmengine - INFO - Epoch(train) [5][ 220/2226] lr: 7.9126e-07 eta: 10:06:40 time: 1.0399 data_time: 0.0099 memory: 70046 grad_norm: 0.1116 loss: 0.0550 recall@thr=0.5: 0.8167 prec@thr=0.5: 0.8417 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4800 loss_action_cls: 0.0550 2023/03/11 09:52:08 - mmengine - INFO - Epoch(train) [5][ 240/2226] lr: 7.9278e-07 eta: 10:06:20 time: 1.0358 data_time: 0.0122 memory: 70046 grad_norm: 0.1111 loss: 0.0481 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.4861 recall@top3: 0.6667 prec@top3: 0.5833 recall@top5: 0.7917 prec@top5: 0.4167 loss_action_cls: 0.0481 2023/03/11 09:52:32 - mmengine - INFO - Epoch(train) [5][ 260/2226] lr: 7.9431e-07 eta: 10:06:14 time: 1.2167 data_time: 0.0131 memory: 70046 grad_norm: 0.1034 loss: 0.0710 recall@thr=0.5: 0.7889 prec@thr=0.5: 0.8815 recall@top3: 0.7278 prec@top3: 0.7778 recall@top5: 0.9333 prec@top5: 0.6444 loss_action_cls: 0.0710 2023/03/11 09:52:53 - mmengine - INFO - Epoch(train) [5][ 280/2226] lr: 7.9584e-07 eta: 10:05:56 time: 1.0679 data_time: 0.0124 memory: 70046 grad_norm: 0.1085 loss: 0.0599 recall@thr=0.5: 0.8083 prec@thr=0.5: 0.9000 recall@top3: 0.7667 prec@top3: 0.7333 recall@top5: 0.9167 prec@top5: 0.5400 loss_action_cls: 0.0599 2023/03/11 09:53:14 - mmengine - INFO - Epoch(train) [5][ 300/2226] lr: 7.9737e-07 eta: 10:05:37 time: 1.0465 data_time: 0.0111 memory: 70046 grad_norm: 0.1075 loss: 0.0420 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7000 recall@top3: 0.8833 prec@top3: 0.6000 recall@top5: 0.8833 prec@top5: 0.3600 loss_action_cls: 0.0420 2023/03/11 09:53:36 - mmengine - INFO - Epoch(train) [5][ 320/2226] lr: 7.9889e-07 eta: 10:05:21 time: 1.0895 data_time: 0.0124 memory: 70046 grad_norm: 0.1076 loss: 0.0483 recall@thr=0.5: 0.6111 prec@thr=0.5: 0.6667 recall@top3: 0.6528 prec@top3: 0.7222 recall@top5: 0.7778 prec@top5: 0.5333 loss_action_cls: 0.0483 2023/03/11 09:53:57 - mmengine - INFO - Epoch(train) [5][ 340/2226] lr: 8.0042e-07 eta: 10:05:03 time: 1.0619 data_time: 0.0136 memory: 70046 grad_norm: 0.1033 loss: 0.0368 recall@thr=0.5: 0.9286 prec@thr=0.5: 0.7143 recall@top3: 0.9286 prec@top3: 0.6190 recall@top5: 0.9286 prec@top5: 0.3714 loss_action_cls: 0.0368 2023/03/11 09:54:19 - mmengine - INFO - Epoch(train) [5][ 360/2226] lr: 8.0195e-07 eta: 10:04:48 time: 1.0980 data_time: 0.0108 memory: 70046 grad_norm: 0.1074 loss: 0.0599 recall@thr=0.5: 0.4974 prec@thr=0.5: 0.6154 recall@top3: 0.5731 prec@top3: 0.7179 recall@top5: 0.8628 prec@top5: 0.6769 loss_action_cls: 0.0599 2023/03/11 09:54:41 - mmengine - INFO - Epoch(train) [5][ 380/2226] lr: 8.0348e-07 eta: 10:04:31 time: 1.0793 data_time: 0.0133 memory: 70046 grad_norm: 0.1094 loss: 0.0594 recall@thr=0.5: 0.8472 prec@thr=0.5: 0.8542 recall@top3: 0.8819 prec@top3: 0.8611 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0594 2023/03/11 09:55:03 - mmengine - INFO - Epoch(train) [5][ 400/2226] lr: 8.0500e-07 eta: 10:04:17 time: 1.1101 data_time: 0.0131 memory: 70046 grad_norm: 0.1077 loss: 0.0495 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.8636 recall@top3: 0.8485 prec@top3: 0.6667 recall@top5: 0.9091 prec@top5: 0.4364 loss_action_cls: 0.0495 2023/03/11 09:55:24 - mmengine - INFO - Epoch(train) [5][ 420/2226] lr: 8.0653e-07 eta: 10:03:59 time: 1.0671 data_time: 0.0126 memory: 70046 grad_norm: 0.1070 loss: 0.0469 recall@thr=0.5: 0.5909 prec@thr=0.5: 0.5758 recall@top3: 0.6818 prec@top3: 0.4848 recall@top5: 0.8864 prec@top5: 0.3818 loss_action_cls: 0.0469 2023/03/11 09:55:45 - mmengine - INFO - Epoch(train) [5][ 440/2226] lr: 8.0806e-07 eta: 10:03:39 time: 1.0440 data_time: 0.0119 memory: 70046 grad_norm: 0.1065 loss: 0.0481 recall@thr=0.5: 0.8077 prec@thr=0.5: 0.8462 recall@top3: 1.0000 prec@top3: 0.7692 recall@top5: 1.0000 prec@top5: 0.4615 loss_action_cls: 0.0481 2023/03/11 09:56:07 - mmengine - INFO - Epoch(train) [5][ 460/2226] lr: 8.0959e-07 eta: 10:03:23 time: 1.0897 data_time: 0.0089 memory: 70046 grad_norm: 0.1072 loss: 0.0583 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.6667 recall@top3: 0.8333 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0583 2023/03/11 09:56:25 - mmengine - INFO - Epoch(train) [5][ 480/2226] lr: 8.1111e-07 eta: 10:02:52 time: 0.8838 data_time: 0.0104 memory: 70046 grad_norm: 0.1101 loss: 0.0472 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.8125 recall@top3: 0.8542 prec@top3: 0.5833 recall@top5: 0.9167 prec@top5: 0.3750 loss_action_cls: 0.0472 2023/03/11 09:56:51 - mmengine - INFO - Epoch(train) [5][ 500/2226] lr: 8.1264e-07 eta: 10:02:54 time: 1.3338 data_time: 0.0125 memory: 70046 grad_norm: 0.1150 loss: 0.0433 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.8333 recall@top3: 0.9524 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.4571 loss_action_cls: 0.0433 2023/03/11 09:57:12 - mmengine - INFO - Epoch(train) [5][ 520/2226] lr: 8.1417e-07 eta: 10:02:33 time: 1.0239 data_time: 0.0111 memory: 70046 grad_norm: 0.1096 loss: 0.0388 recall@thr=0.5: 0.9048 prec@thr=0.5: 0.9405 recall@top3: 0.9643 prec@top3: 0.7381 recall@top5: 1.0000 prec@top5: 0.4714 loss_action_cls: 0.0388 2023/03/11 09:57:32 - mmengine - INFO - Epoch(train) [5][ 540/2226] lr: 8.1570e-07 eta: 10:02:12 time: 1.0245 data_time: 0.0410 memory: 70046 grad_norm: 0.1032 loss: 0.0494 recall@thr=0.5: 0.1333 prec@thr=0.5: 0.2000 recall@top3: 0.8500 prec@top3: 0.4667 recall@top5: 0.9000 prec@top5: 0.3200 loss_action_cls: 0.0494 2023/03/11 09:57:58 - mmengine - INFO - Epoch(train) [5][ 560/2226] lr: 8.1723e-07 eta: 10:02:12 time: 1.3113 data_time: 0.0125 memory: 70046 grad_norm: 0.1081 loss: 0.0575 recall@thr=0.5: 0.7652 prec@thr=0.5: 0.7652 recall@top3: 0.8303 prec@top3: 0.7879 recall@top5: 0.9530 prec@top5: 0.5364 loss_action_cls: 0.0575 2023/03/11 09:58:14 - mmengine - INFO - Epoch(train) [5][ 580/2226] lr: 8.1875e-07 eta: 10:01:34 time: 0.7984 data_time: 0.0077 memory: 70046 grad_norm: 0.1050 loss: 0.0558 recall@thr=0.5: 0.5278 prec@thr=0.5: 0.7500 recall@top3: 0.7778 prec@top3: 0.7222 recall@top5: 0.8333 prec@top5: 0.4667 loss_action_cls: 0.0558 2023/03/11 09:58:37 - mmengine - INFO - Epoch(train) [5][ 600/2226] lr: 8.2028e-07 eta: 10:01:21 time: 1.1312 data_time: 0.0138 memory: 70046 grad_norm: 0.1136 loss: 0.0454 recall@thr=0.5: 0.9259 prec@thr=0.5: 0.8148 recall@top3: 1.0000 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0454 2023/03/11 09:58:59 - mmengine - INFO - Epoch(train) [5][ 620/2226] lr: 8.2181e-07 eta: 10:01:04 time: 1.0799 data_time: 0.0122 memory: 70046 grad_norm: 0.1117 loss: 0.0589 recall@thr=0.5: 0.8039 prec@thr=0.5: 0.8529 recall@top3: 0.9020 prec@top3: 0.6078 recall@top5: 0.9020 prec@top5: 0.3647 loss_action_cls: 0.0589 2023/03/11 09:59:16 - mmengine - INFO - Epoch(train) [5][ 640/2226] lr: 8.2334e-07 eta: 10:00:31 time: 0.8593 data_time: 0.0116 memory: 70046 grad_norm: 0.1060 loss: 0.0482 recall@thr=0.5: 0.8500 prec@thr=0.5: 0.8500 recall@top3: 0.8700 prec@top3: 0.8000 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0482 2023/03/11 09:59:29 - mmengine - INFO - Epoch(train) [5][ 660/2226] lr: 8.2486e-07 eta: 9:59:44 time: 0.6668 data_time: 0.0104 memory: 70046 grad_norm: 0.1121 loss: 0.0528 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.9167 recall@top3: 0.8333 prec@top3: 0.7500 recall@top5: 0.8333 prec@top5: 0.4500 loss_action_cls: 0.0528 2023/03/11 09:59:45 - mmengine - INFO - Epoch(train) [5][ 680/2226] lr: 8.2639e-07 eta: 9:59:05 time: 0.7872 data_time: 0.0106 memory: 70046 grad_norm: 0.1068 loss: 0.0405 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.9000 recall@top3: 0.8333 prec@top3: 0.7333 recall@top5: 0.9667 prec@top5: 0.5200 loss_action_cls: 0.0405 2023/03/11 10:00:03 - mmengine - INFO - Epoch(train) [5][ 700/2226] lr: 8.2792e-07 eta: 9:58:36 time: 0.9102 data_time: 0.0121 memory: 70046 grad_norm: 0.1049 loss: 0.0494 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.8333 recall@top3: 0.7083 prec@top3: 0.5556 recall@top5: 0.9444 prec@top5: 0.4667 loss_action_cls: 0.0494 2023/03/11 10:00:19 - mmengine - INFO - Epoch(train) [5][ 720/2226] lr: 8.2945e-07 eta: 9:57:58 time: 0.7829 data_time: 0.0119 memory: 70046 grad_norm: 0.1019 loss: 0.0533 recall@thr=0.5: 0.6333 prec@thr=0.5: 0.8333 recall@top3: 0.7333 prec@top3: 0.6333 recall@top5: 1.0000 prec@top5: 0.5200 loss_action_cls: 0.0533 2023/03/11 10:00:37 - mmengine - INFO - Epoch(train) [5][ 740/2226] lr: 8.3097e-07 eta: 9:57:30 time: 0.9338 data_time: 0.0109 memory: 70046 grad_norm: 0.1054 loss: 0.0418 recall@thr=0.5: 0.9167 prec@thr=0.5: 0.8333 recall@top3: 1.0000 prec@top3: 0.5000 recall@top5: 1.0000 prec@top5: 0.3000 loss_action_cls: 0.0418 2023/03/11 10:00:53 - mmengine - INFO - Epoch(train) [5][ 760/2226] lr: 8.3250e-07 eta: 9:56:51 time: 0.7703 data_time: 0.0105 memory: 70046 grad_norm: 0.1037 loss: 0.0589 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.7407 recall@top3: 0.7407 prec@top3: 0.6296 recall@top5: 0.8056 prec@top5: 0.4222 loss_action_cls: 0.0589 2023/03/11 10:01:11 - mmengine - INFO - Epoch(train) [5][ 780/2226] lr: 8.3403e-07 eta: 9:56:24 time: 0.9273 data_time: 0.0102 memory: 70046 grad_norm: 0.1041 loss: 0.0440 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.7000 recall@top3: 0.9000 prec@top3: 0.6000 recall@top5: 0.9000 prec@top5: 0.3600 loss_action_cls: 0.0440 2023/03/11 10:01:30 - mmengine - INFO - Epoch(train) [5][ 800/2226] lr: 8.3556e-07 eta: 9:55:55 time: 0.9122 data_time: 0.0094 memory: 70046 grad_norm: 0.1077 loss: 0.0387 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.9259 recall@top3: 0.8056 prec@top3: 0.8889 recall@top5: 0.8889 prec@top5: 0.6000 loss_action_cls: 0.0387 2023/03/11 10:01:51 - mmengine - INFO - Epoch(train) [5][ 820/2226] lr: 8.3708e-07 eta: 9:55:37 time: 1.0605 data_time: 0.0113 memory: 70046 grad_norm: 0.1107 loss: 0.0589 recall@thr=0.5: 0.6905 prec@thr=0.5: 0.7619 recall@top3: 0.8571 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.5143 loss_action_cls: 0.0589 2023/03/11 10:02:10 - mmengine - INFO - Epoch(train) [5][ 840/2226] lr: 8.3861e-07 eta: 9:55:09 time: 0.9345 data_time: 0.0141 memory: 70046 grad_norm: 0.1074 loss: 0.0389 recall@thr=0.5: 0.5778 prec@thr=0.5: 0.6667 recall@top3: 0.5778 prec@top3: 0.4444 recall@top5: 1.0000 prec@top5: 0.4222 loss_action_cls: 0.0389 2023/03/11 10:02:31 - mmengine - INFO - Epoch(train) [5][ 860/2226] lr: 8.4014e-07 eta: 9:54:51 time: 1.0498 data_time: 0.0121 memory: 70046 grad_norm: 0.1074 loss: 0.0510 recall@thr=0.5: 0.5952 prec@thr=0.5: 0.7143 recall@top3: 0.6905 prec@top3: 0.5714 recall@top5: 0.9286 prec@top5: 0.4857 loss_action_cls: 0.0510 2023/03/11 10:02:50 - mmengine - INFO - Epoch(train) [5][ 880/2226] lr: 8.4167e-07 eta: 9:54:25 time: 0.9502 data_time: 0.0102 memory: 70046 grad_norm: 0.1040 loss: 0.0515 recall@thr=0.5: 0.6833 prec@thr=0.5: 0.8667 recall@top3: 0.8333 prec@top3: 0.5667 recall@top5: 0.9333 prec@top5: 0.3800 loss_action_cls: 0.0515 2023/03/11 10:03:11 - mmengine - INFO - Epoch(train) [5][ 900/2226] lr: 8.4319e-07 eta: 9:54:08 time: 1.0814 data_time: 0.0133 memory: 70046 grad_norm: 0.1073 loss: 0.0443 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.6000 recall@top3: 0.9000 prec@top3: 0.5000 recall@top5: 0.9000 prec@top5: 0.3000 loss_action_cls: 0.0443 2023/03/11 10:03:32 - mmengine - INFO - Epoch(train) [5][ 920/2226] lr: 8.4472e-07 eta: 9:53:47 time: 1.0194 data_time: 0.0114 memory: 70046 grad_norm: 0.1093 loss: 0.0569 recall@thr=0.5: 0.5741 prec@thr=0.5: 0.4815 recall@top3: 0.7222 prec@top3: 0.4815 recall@top5: 0.9630 prec@top5: 0.4222 loss_action_cls: 0.0569 2023/03/11 10:03:51 - mmengine - INFO - Epoch(train) [5][ 940/2226] lr: 8.4625e-07 eta: 9:53:24 time: 0.9929 data_time: 0.0102 memory: 70046 grad_norm: 0.1050 loss: 0.0548 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.7917 recall@top3: 0.8611 prec@top3: 0.7500 recall@top5: 0.9722 prec@top5: 0.5167 loss_action_cls: 0.0548 2023/03/11 10:04:13 - mmengine - INFO - Epoch(train) [5][ 960/2226] lr: 8.4778e-07 eta: 9:53:07 time: 1.0854 data_time: 0.0092 memory: 70046 grad_norm: 0.1068 loss: 0.0554 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.8750 recall@top3: 0.8750 prec@top3: 0.7917 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0554 2023/03/11 10:04:31 - mmengine - INFO - Epoch(train) [5][ 980/2226] lr: 8.4930e-07 eta: 9:52:38 time: 0.8936 data_time: 0.0091 memory: 70046 grad_norm: 0.1042 loss: 0.0484 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.6389 recall@top3: 0.6389 prec@top3: 0.4722 recall@top5: 0.7917 prec@top5: 0.3333 loss_action_cls: 0.0484 2023/03/11 10:04:52 - mmengine - INFO - Epoch(train) [5][1000/2226] lr: 8.5083e-07 eta: 9:52:17 time: 1.0321 data_time: 0.0147 memory: 70046 grad_norm: 0.1113 loss: 0.0484 recall@thr=0.5: 0.7372 prec@thr=0.5: 0.5962 recall@top3: 0.6410 prec@top3: 0.5897 recall@top5: 0.7885 prec@top5: 0.4615 loss_action_cls: 0.0484 2023/03/11 10:05:10 - mmengine - INFO - Epoch(train) [5][1020/2226] lr: 8.5236e-07 eta: 9:51:50 time: 0.9249 data_time: 0.0128 memory: 70046 grad_norm: 0.1046 loss: 0.0553 recall@thr=0.5: 0.6364 prec@thr=0.5: 0.6667 recall@top3: 0.7273 prec@top3: 0.4545 recall@top5: 0.8788 prec@top5: 0.3636 loss_action_cls: 0.0553 2023/03/11 10:05:31 - mmengine - INFO - Epoch(train) [5][1040/2226] lr: 8.5389e-07 eta: 9:51:32 time: 1.0649 data_time: 0.0153 memory: 70046 grad_norm: 0.1044 loss: 0.0457 recall@thr=0.5: 0.8667 prec@thr=0.5: 0.9750 recall@top3: 0.9000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4600 loss_action_cls: 0.0457 2023/03/11 10:05:53 - mmengine - INFO - Epoch(train) [5][1060/2226] lr: 8.5541e-07 eta: 9:51:15 time: 1.0768 data_time: 0.0115 memory: 70046 grad_norm: 0.1025 loss: 0.0409 recall@thr=0.5: 0.9231 prec@thr=0.5: 0.8269 recall@top3: 0.9615 prec@top3: 0.6410 recall@top5: 1.0000 prec@top5: 0.4154 loss_action_cls: 0.0409 2023/03/11 10:06:10 - mmengine - INFO - Epoch(train) [5][1080/2226] lr: 8.5694e-07 eta: 9:50:41 time: 0.8387 data_time: 0.0112 memory: 70046 grad_norm: 0.1058 loss: 0.0436 recall@thr=0.5: 0.7333 prec@thr=0.5: 0.8000 recall@top3: 0.7333 prec@top3: 0.7333 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0436 2023/03/11 10:06:27 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 10:06:33 - mmengine - INFO - Epoch(train) [5][1100/2226] lr: 8.5847e-07 eta: 9:50:28 time: 1.1366 data_time: 0.0128 memory: 70046 grad_norm: 0.1074 loss: 0.0486 recall@thr=0.5: 0.6905 prec@thr=0.5: 0.7381 recall@top3: 0.7500 prec@top3: 0.4286 recall@top5: 0.8214 prec@top5: 0.2857 loss_action_cls: 0.0486 2023/03/11 10:06:51 - mmengine - INFO - Epoch(train) [5][1120/2226] lr: 8.6000e-07 eta: 9:50:00 time: 0.9128 data_time: 0.0149 memory: 70046 grad_norm: 0.1046 loss: 0.0488 recall@thr=0.5: 0.5938 prec@thr=0.5: 0.8750 recall@top3: 0.8438 prec@top3: 0.8750 recall@top5: 0.9688 prec@top5: 0.6250 loss_action_cls: 0.0488 2023/03/11 10:07:11 - mmengine - INFO - Epoch(train) [5][1140/2226] lr: 8.6153e-07 eta: 9:49:38 time: 1.0024 data_time: 0.0112 memory: 70046 grad_norm: 0.1122 loss: 0.0512 recall@thr=0.5: 1.0000 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.7667 recall@top5: 1.0000 prec@top5: 0.4600 loss_action_cls: 0.0512 2023/03/11 10:07:31 - mmengine - INFO - Epoch(train) [5][1160/2226] lr: 8.6305e-07 eta: 9:49:15 time: 0.9978 data_time: 0.0112 memory: 70046 grad_norm: 0.1074 loss: 0.0436 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.8333 recall@top3: 0.8889 prec@top3: 0.5556 recall@top5: 0.8889 prec@top5: 0.3333 loss_action_cls: 0.0436 2023/03/11 10:07:52 - mmengine - INFO - Epoch(train) [5][1180/2226] lr: 8.6458e-07 eta: 9:48:56 time: 1.0408 data_time: 0.0120 memory: 70046 grad_norm: 0.1137 loss: 0.0418 recall@thr=0.5: 0.6806 prec@thr=0.5: 0.9583 recall@top3: 0.9167 prec@top3: 0.6111 recall@top5: 0.9375 prec@top5: 0.3833 loss_action_cls: 0.0418 2023/03/11 10:08:13 - mmengine - INFO - Epoch(train) [5][1200/2226] lr: 8.6611e-07 eta: 9:48:40 time: 1.0888 data_time: 0.0109 memory: 70046 grad_norm: 0.1088 loss: 0.0426 recall@thr=0.5: 0.6026 prec@thr=0.5: 0.5385 recall@top3: 0.5641 prec@top3: 0.4872 recall@top5: 0.9038 prec@top5: 0.4308 loss_action_cls: 0.0426 2023/03/11 10:08:33 - mmengine - INFO - Epoch(train) [5][1220/2226] lr: 8.6764e-07 eta: 9:48:15 time: 0.9664 data_time: 0.0099 memory: 70046 grad_norm: 0.1133 loss: 0.0594 recall@thr=0.5: 0.8571 prec@thr=0.5: 1.0000 recall@top3: 0.9286 prec@top3: 0.6190 recall@top5: 0.9286 prec@top5: 0.3714 loss_action_cls: 0.0594 2023/03/11 10:08:53 - mmengine - INFO - Epoch(train) [5][1240/2226] lr: 8.6916e-07 eta: 9:47:52 time: 0.9949 data_time: 0.0109 memory: 70046 grad_norm: 0.1101 loss: 0.0497 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8048 recall@top3: 0.7560 prec@top3: 0.7143 recall@top5: 0.9107 prec@top5: 0.5286 loss_action_cls: 0.0497 2023/03/11 10:09:14 - mmengine - INFO - Epoch(train) [5][1260/2226] lr: 8.7069e-07 eta: 9:47:33 time: 1.0486 data_time: 0.0122 memory: 70046 grad_norm: 0.1148 loss: 0.0576 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.9630 recall@top3: 0.8889 prec@top3: 0.5926 recall@top5: 0.9722 prec@top5: 0.4222 loss_action_cls: 0.0576 2023/03/11 10:09:35 - mmengine - INFO - Epoch(train) [5][1280/2226] lr: 8.7222e-07 eta: 9:47:15 time: 1.0603 data_time: 0.0100 memory: 70046 grad_norm: 0.1036 loss: 0.0441 recall@thr=0.5: 0.8462 prec@thr=0.5: 0.8141 recall@top3: 0.8782 prec@top3: 0.6923 recall@top5: 1.0000 prec@top5: 0.4923 loss_action_cls: 0.0441 2023/03/11 10:09:52 - mmengine - INFO - Epoch(train) [5][1300/2226] lr: 8.7375e-07 eta: 9:46:44 time: 0.8689 data_time: 0.0088 memory: 70046 grad_norm: 0.1100 loss: 0.0464 recall@thr=0.5: 0.8600 prec@thr=0.5: 0.8917 recall@top3: 0.8900 prec@top3: 0.6000 recall@top5: 0.9350 prec@top5: 0.4000 loss_action_cls: 0.0464 2023/03/11 10:10:14 - mmengine - INFO - Epoch(train) [5][1320/2226] lr: 8.7527e-07 eta: 9:46:27 time: 1.0765 data_time: 0.0110 memory: 70046 grad_norm: 0.1035 loss: 0.0405 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.9286 recall@top3: 0.8571 prec@top3: 0.5714 recall@top5: 0.9286 prec@top5: 0.3714 loss_action_cls: 0.0405 2023/03/11 10:10:32 - mmengine - INFO - Epoch(train) [5][1340/2226] lr: 8.7680e-07 eta: 9:45:59 time: 0.9188 data_time: 0.0128 memory: 70046 grad_norm: 0.1047 loss: 0.0520 recall@thr=0.5: 0.5844 prec@thr=0.5: 0.7333 recall@top3: 0.7256 prec@top3: 0.7556 recall@top5: 0.8878 prec@top5: 0.5867 loss_action_cls: 0.0520 2023/03/11 10:10:56 - mmengine - INFO - Epoch(train) [5][1360/2226] lr: 8.7833e-07 eta: 9:45:49 time: 1.1761 data_time: 0.0109 memory: 70046 grad_norm: 0.1053 loss: 0.0504 recall@thr=0.5: 0.2889 prec@thr=0.5: 0.2917 recall@top3: 0.4556 prec@top3: 0.3333 recall@top5: 0.4889 prec@top5: 0.2333 loss_action_cls: 0.0504 2023/03/11 10:11:15 - mmengine - INFO - Epoch(train) [5][1380/2226] lr: 8.7986e-07 eta: 9:45:26 time: 0.9887 data_time: 0.0074 memory: 70046 grad_norm: 0.1092 loss: 0.0506 recall@thr=0.5: 0.6500 prec@thr=0.5: 0.8000 recall@top3: 0.8000 prec@top3: 0.7333 recall@top5: 0.8500 prec@top5: 0.4800 loss_action_cls: 0.0506 2023/03/11 10:11:38 - mmengine - INFO - Epoch(train) [5][1400/2226] lr: 8.8138e-07 eta: 9:45:11 time: 1.1156 data_time: 0.0102 memory: 70046 grad_norm: 0.1040 loss: 0.0426 recall@thr=0.5: 0.5758 prec@thr=0.5: 0.8182 recall@top3: 0.8333 prec@top3: 0.6364 recall@top5: 0.9091 prec@top5: 0.4182 loss_action_cls: 0.0426 2023/03/11 10:11:54 - mmengine - INFO - Epoch(train) [5][1420/2226] lr: 8.8291e-07 eta: 9:44:37 time: 0.8187 data_time: 0.0090 memory: 70046 grad_norm: 0.1022 loss: 0.0476 recall@thr=0.5: 0.7639 prec@thr=0.5: 0.8194 recall@top3: 0.7917 prec@top3: 0.7778 recall@top5: 0.9514 prec@top5: 0.5833 loss_action_cls: 0.0476 2023/03/11 10:12:14 - mmengine - INFO - Epoch(train) [5][1440/2226] lr: 8.8444e-07 eta: 9:44:16 time: 1.0159 data_time: 0.0103 memory: 70046 grad_norm: 0.1068 loss: 0.0441 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.6905 recall@top3: 0.7143 prec@top3: 0.3810 recall@top5: 1.0000 prec@top5: 0.3429 loss_action_cls: 0.0441 2023/03/11 10:12:36 - mmengine - INFO - Epoch(train) [5][1460/2226] lr: 8.8597e-07 eta: 9:43:58 time: 1.0600 data_time: 0.0123 memory: 70046 grad_norm: 0.1041 loss: 0.0433 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.9444 recall@top3: 1.0000 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.3333 loss_action_cls: 0.0433 2023/03/11 10:12:57 - mmengine - INFO - Epoch(train) [5][1480/2226] lr: 8.8749e-07 eta: 9:43:38 time: 1.0458 data_time: 0.0096 memory: 70046 grad_norm: 0.1061 loss: 0.0463 recall@thr=0.5: 0.4306 prec@thr=0.5: 0.5278 recall@top3: 0.7639 prec@top3: 0.5278 recall@top5: 0.9583 prec@top5: 0.4167 loss_action_cls: 0.0463 2023/03/11 10:13:13 - mmengine - INFO - Epoch(train) [5][1500/2226] lr: 8.8902e-07 eta: 9:43:05 time: 0.8373 data_time: 0.0105 memory: 70046 grad_norm: 0.1013 loss: 0.0610 recall@thr=0.5: 0.6500 prec@thr=0.5: 0.4833 recall@top3: 0.8667 prec@top3: 0.4667 recall@top5: 0.9000 prec@top5: 0.3000 loss_action_cls: 0.0610 2023/03/11 10:13:33 - mmengine - INFO - Epoch(train) [5][1520/2226] lr: 8.9055e-07 eta: 9:42:43 time: 0.9940 data_time: 0.0123 memory: 70046 grad_norm: 0.1030 loss: 0.0565 recall@thr=0.5: 0.6538 prec@thr=0.5: 0.6923 recall@top3: 0.6923 prec@top3: 0.5128 recall@top5: 1.0000 prec@top5: 0.4308 loss_action_cls: 0.0565 2023/03/11 10:13:56 - mmengine - INFO - Epoch(train) [5][1540/2226] lr: 8.9208e-07 eta: 9:42:30 time: 1.1452 data_time: 0.0130 memory: 70046 grad_norm: 0.1058 loss: 0.0576 recall@thr=0.5: 0.5903 prec@thr=0.5: 0.7083 recall@top3: 0.7569 prec@top3: 0.6944 recall@top5: 0.8889 prec@top5: 0.5167 loss_action_cls: 0.0576 2023/03/11 10:14:17 - mmengine - INFO - Epoch(train) [5][1560/2226] lr: 8.9360e-07 eta: 9:42:10 time: 1.0234 data_time: 0.0120 memory: 70046 grad_norm: 0.1021 loss: 0.0542 recall@thr=0.5: 0.5208 prec@thr=0.5: 0.7083 recall@top3: 0.8125 prec@top3: 0.7083 recall@top5: 0.8750 prec@top5: 0.4750 loss_action_cls: 0.0542 2023/03/11 10:14:36 - mmengine - INFO - Epoch(train) [5][1580/2226] lr: 8.9513e-07 eta: 9:41:47 time: 0.9899 data_time: 0.0126 memory: 70046 grad_norm: 0.1061 loss: 0.0503 recall@thr=0.5: 0.4286 prec@thr=0.5: 0.4405 recall@top3: 0.8929 prec@top3: 0.5238 recall@top5: 0.9107 prec@top5: 0.3286 loss_action_cls: 0.0503 2023/03/11 10:14:57 - mmengine - INFO - Epoch(train) [5][1600/2226] lr: 8.9666e-07 eta: 9:41:27 time: 1.0347 data_time: 0.0127 memory: 70046 grad_norm: 0.0960 loss: 0.0486 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7083 recall@top3: 0.6667 prec@top3: 0.6111 recall@top5: 0.7778 prec@top5: 0.4333 loss_action_cls: 0.0486 2023/03/11 10:15:16 - mmengine - INFO - Epoch(train) [5][1620/2226] lr: 8.9819e-07 eta: 9:41:01 time: 0.9501 data_time: 0.0114 memory: 70046 grad_norm: 0.1040 loss: 0.0570 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7222 recall@top3: 0.8333 prec@top3: 0.6111 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0570 2023/03/11 10:15:38 - mmengine - INFO - Epoch(train) [5][1640/2226] lr: 8.9971e-07 eta: 9:40:45 time: 1.0883 data_time: 0.0119 memory: 70046 grad_norm: 0.1030 loss: 0.0536 recall@thr=0.5: 0.4352 prec@thr=0.5: 0.4444 recall@top3: 0.6667 prec@top3: 0.4630 recall@top5: 0.7315 prec@top5: 0.3111 loss_action_cls: 0.0536 2023/03/11 10:15:58 - mmengine - INFO - Epoch(train) [5][1660/2226] lr: 9.0124e-07 eta: 9:40:24 time: 1.0169 data_time: 0.0097 memory: 70046 grad_norm: 0.1053 loss: 0.0493 recall@thr=0.5: 0.5758 prec@thr=0.5: 0.7348 recall@top3: 0.7803 prec@top3: 0.7273 recall@top5: 0.9167 prec@top5: 0.5091 loss_action_cls: 0.0493 2023/03/11 10:16:22 - mmengine - INFO - Epoch(train) [5][1680/2226] lr: 9.0277e-07 eta: 9:40:15 time: 1.2012 data_time: 0.0100 memory: 70046 grad_norm: 0.1062 loss: 0.0441 recall@thr=0.5: 0.5833 prec@thr=0.5: 0.7083 recall@top3: 0.8333 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0441 2023/03/11 10:16:36 - mmengine - INFO - Epoch(train) [5][1700/2226] lr: 9.0430e-07 eta: 9:39:31 time: 0.6690 data_time: 0.0102 memory: 70046 grad_norm: 0.1014 loss: 0.0558 recall@thr=0.5: 0.5952 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.6190 recall@top5: 0.8571 prec@top5: 0.3714 loss_action_cls: 0.0558 2023/03/11 10:16:56 - mmengine - INFO - Epoch(train) [5][1720/2226] lr: 9.0583e-07 eta: 9:39:10 time: 1.0083 data_time: 0.0117 memory: 70046 grad_norm: 0.1023 loss: 0.0578 recall@thr=0.5: 0.8333 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.3333 loss_action_cls: 0.0578 2023/03/11 10:17:22 - mmengine - INFO - Epoch(train) [5][1740/2226] lr: 9.0735e-07 eta: 9:39:07 time: 1.3044 data_time: 0.0187 memory: 70046 grad_norm: 0.1063 loss: 0.0393 recall@thr=0.5: 0.4028 prec@thr=0.5: 0.6111 recall@top3: 0.7500 prec@top3: 0.5278 recall@top5: 0.9583 prec@top5: 0.3833 loss_action_cls: 0.0393 2023/03/11 10:17:42 - mmengine - INFO - Epoch(train) [5][1760/2226] lr: 9.0888e-07 eta: 9:38:45 time: 1.0039 data_time: 0.0110 memory: 70046 grad_norm: 0.1068 loss: 0.0467 recall@thr=0.5: 0.6759 prec@thr=0.5: 0.7778 recall@top3: 0.8981 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.5333 loss_action_cls: 0.0467 2023/03/11 10:18:00 - mmengine - INFO - Epoch(train) [5][1780/2226] lr: 9.1041e-07 eta: 9:38:17 time: 0.9061 data_time: 0.0112 memory: 70046 grad_norm: 0.1077 loss: 0.0509 recall@thr=0.5: 0.3409 prec@thr=0.5: 0.4318 recall@top3: 0.6364 prec@top3: 0.5606 recall@top5: 0.8182 prec@top5: 0.4273 loss_action_cls: 0.0509 2023/03/11 10:18:18 - mmengine - INFO - Epoch(train) [5][1800/2226] lr: 9.1194e-07 eta: 9:37:49 time: 0.9109 data_time: 0.0132 memory: 70046 grad_norm: 0.1112 loss: 0.0516 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.9444 recall@top3: 0.6667 prec@top3: 0.7222 recall@top5: 0.8056 prec@top5: 0.5333 loss_action_cls: 0.0516 2023/03/11 10:18:39 - mmengine - INFO - Epoch(train) [5][1820/2226] lr: 9.1346e-07 eta: 9:37:29 time: 1.0306 data_time: 0.0805 memory: 70046 grad_norm: 0.1036 loss: 0.0496 recall@thr=0.5: 0.6481 prec@thr=0.5: 0.7407 recall@top3: 0.7315 prec@top3: 0.5926 recall@top5: 0.9074 prec@top5: 0.4778 loss_action_cls: 0.0496 2023/03/11 10:18:59 - mmengine - INFO - Epoch(train) [5][1840/2226] lr: 9.1499e-07 eta: 9:37:08 time: 1.0159 data_time: 0.1790 memory: 70046 grad_norm: 0.1100 loss: 0.0446 recall@thr=0.5: 0.7611 prec@thr=0.5: 0.7593 recall@top3: 0.9278 prec@top3: 0.8148 recall@top5: 1.0000 prec@top5: 0.5556 loss_action_cls: 0.0446 2023/03/11 10:19:21 - mmengine - INFO - Epoch(train) [5][1860/2226] lr: 9.1652e-07 eta: 9:36:53 time: 1.1056 data_time: 0.0125 memory: 70046 grad_norm: 0.1023 loss: 0.0512 recall@thr=0.5: 0.4500 prec@thr=0.5: 0.6500 recall@top3: 0.6167 prec@top3: 0.6333 recall@top5: 0.6667 prec@top5: 0.4200 loss_action_cls: 0.0512 2023/03/11 10:19:38 - mmengine - INFO - Epoch(train) [5][1880/2226] lr: 9.1805e-07 eta: 9:36:20 time: 0.8405 data_time: 0.0133 memory: 70046 grad_norm: 0.1047 loss: 0.0505 recall@thr=0.5: 0.7549 prec@thr=0.5: 0.8235 recall@top3: 0.8529 prec@top3: 0.5686 recall@top5: 0.8922 prec@top5: 0.3647 loss_action_cls: 0.0505 2023/03/11 10:19:59 - mmengine - INFO - Epoch(train) [5][1900/2226] lr: 9.1957e-07 eta: 9:36:00 time: 1.0285 data_time: 0.0128 memory: 70046 grad_norm: 0.0976 loss: 0.0420 recall@thr=0.5: 0.7389 prec@thr=0.5: 0.7556 recall@top3: 0.7833 prec@top3: 0.6667 recall@top5: 0.9333 prec@top5: 0.4933 loss_action_cls: 0.0420 2023/03/11 10:20:19 - mmengine - INFO - Epoch(train) [5][1920/2226] lr: 9.2110e-07 eta: 9:35:40 time: 1.0342 data_time: 0.0124 memory: 70046 grad_norm: 0.1085 loss: 0.0440 recall@thr=0.5: 0.6364 prec@thr=0.5: 0.8182 recall@top3: 0.9697 prec@top3: 0.8182 recall@top5: 1.0000 prec@top5: 0.5091 loss_action_cls: 0.0440 2023/03/11 10:20:41 - mmengine - INFO - Epoch(train) [5][1940/2226] lr: 9.2263e-07 eta: 9:35:24 time: 1.0935 data_time: 0.0122 memory: 70046 grad_norm: 0.0971 loss: 0.0421 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.7500 recall@top3: 0.8750 prec@top3: 0.8333 recall@top5: 0.8750 prec@top5: 0.5000 loss_action_cls: 0.0421 2023/03/11 10:20:57 - mmengine - INFO - Epoch(train) [5][1960/2226] lr: 9.2416e-07 eta: 9:34:48 time: 0.7736 data_time: 0.0150 memory: 70046 grad_norm: 0.1105 loss: 0.0550 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.9375 recall@top3: 0.7500 prec@top3: 0.5833 recall@top5: 0.9167 prec@top5: 0.4500 loss_action_cls: 0.0550 2023/03/11 10:21:21 - mmengine - INFO - Epoch(train) [5][1980/2226] lr: 9.2568e-07 eta: 9:34:38 time: 1.2044 data_time: 0.0132 memory: 70046 grad_norm: 0.1082 loss: 0.0429 recall@thr=0.5: 0.6111 prec@thr=0.5: 0.5000 recall@top3: 0.7222 prec@top3: 0.3889 recall@top5: 0.9583 prec@top5: 0.3000 loss_action_cls: 0.0429 2023/03/11 10:21:41 - mmengine - INFO - Epoch(train) [5][2000/2226] lr: 9.2721e-07 eta: 9:34:16 time: 0.9995 data_time: 0.0138 memory: 70046 grad_norm: 0.1033 loss: 0.0481 recall@thr=0.5: 0.8625 prec@thr=0.5: 0.7875 recall@top3: 0.9250 prec@top3: 0.6833 recall@top5: 0.9583 prec@top5: 0.4300 loss_action_cls: 0.0481 2023/03/11 10:21:59 - mmengine - INFO - Epoch(train) [5][2020/2226] lr: 9.2874e-07 eta: 9:33:49 time: 0.9098 data_time: 0.0122 memory: 70046 grad_norm: 0.1033 loss: 0.0415 recall@thr=0.5: 0.7879 prec@thr=0.5: 0.6515 recall@top3: 0.8182 prec@top3: 0.6364 recall@top5: 0.9394 prec@top5: 0.4545 loss_action_cls: 0.0415 2023/03/11 10:22:19 - mmengine - INFO - Epoch(train) [5][2040/2226] lr: 9.3027e-07 eta: 9:33:26 time: 0.9864 data_time: 0.0110 memory: 70046 grad_norm: 0.1017 loss: 0.0507 recall@thr=0.5: 0.6417 prec@thr=0.5: 0.7500 recall@top3: 0.8333 prec@top3: 0.7667 recall@top5: 1.0000 prec@top5: 0.5800 loss_action_cls: 0.0507 2023/03/11 10:22:39 - mmengine - INFO - Epoch(train) [5][2060/2226] lr: 9.3179e-07 eta: 9:33:04 time: 1.0065 data_time: 0.0133 memory: 70046 grad_norm: 0.1077 loss: 0.0393 recall@thr=0.5: 0.4667 prec@thr=0.5: 0.8000 recall@top3: 0.8333 prec@top3: 0.7667 recall@top5: 0.9167 prec@top5: 0.5000 loss_action_cls: 0.0393 2023/03/11 10:23:00 - mmengine - INFO - Epoch(train) [5][2080/2226] lr: 9.3332e-07 eta: 9:32:47 time: 1.0690 data_time: 0.0144 memory: 70046 grad_norm: 0.1014 loss: 0.0414 recall@thr=0.5: 0.8167 prec@thr=0.5: 0.8167 recall@top3: 1.0000 prec@top3: 0.8000 recall@top5: 1.0000 prec@top5: 0.4800 loss_action_cls: 0.0414 2023/03/11 10:23:14 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 10:23:17 - mmengine - INFO - Epoch(train) [5][2100/2226] lr: 9.3485e-07 eta: 9:32:16 time: 0.8619 data_time: 0.0105 memory: 70046 grad_norm: 0.0997 loss: 0.0503 recall@thr=0.5: 0.7857 prec@thr=0.5: 0.7857 recall@top3: 0.7381 prec@top3: 0.5714 recall@top5: 0.8571 prec@top5: 0.4286 loss_action_cls: 0.0503 2023/03/11 10:23:38 - mmengine - INFO - Epoch(train) [5][2120/2226] lr: 9.3638e-07 eta: 9:31:57 time: 1.0522 data_time: 0.0136 memory: 70046 grad_norm: 0.1023 loss: 0.0437 recall@thr=0.5: 0.6333 prec@thr=0.5: 0.6333 recall@top3: 0.8167 prec@top3: 0.7000 recall@top5: 0.9667 prec@top5: 0.4800 loss_action_cls: 0.0437 2023/03/11 10:23:58 - mmengine - INFO - Epoch(train) [5][2140/2226] lr: 9.3790e-07 eta: 9:31:33 time: 0.9653 data_time: 0.0135 memory: 70046 grad_norm: 0.1056 loss: 0.0485 recall@thr=0.5: 0.9048 prec@thr=0.5: 0.9286 recall@top3: 1.0000 prec@top3: 0.5238 recall@top5: 1.0000 prec@top5: 0.3143 loss_action_cls: 0.0485 2023/03/11 10:24:20 - mmengine - INFO - Epoch(train) [5][2160/2226] lr: 9.3943e-07 eta: 9:31:18 time: 1.1150 data_time: 0.0139 memory: 70046 grad_norm: 0.1082 loss: 0.0444 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 0.8571 prec@top3: 0.4286 recall@top5: 1.0000 prec@top5: 0.3143 loss_action_cls: 0.0444 2023/03/11 10:24:38 - mmengine - INFO - Epoch(train) [5][2180/2226] lr: 9.4096e-07 eta: 9:30:51 time: 0.9106 data_time: 0.0119 memory: 70046 grad_norm: 0.1004 loss: 0.0458 recall@thr=0.5: 0.5625 prec@thr=0.5: 0.6667 recall@top3: 0.8750 prec@top3: 0.7500 recall@top5: 1.0000 prec@top5: 0.5250 loss_action_cls: 0.0458 2023/03/11 10:24:58 - mmengine - INFO - Epoch(train) [5][2200/2226] lr: 9.4249e-07 eta: 9:30:29 time: 0.9943 data_time: 0.0128 memory: 70046 grad_norm: 0.1123 loss: 0.0392 recall@thr=0.5: 0.4444 prec@thr=0.5: 0.4444 recall@top3: 0.7222 prec@top3: 0.4444 recall@top5: 0.9444 prec@top5: 0.3333 loss_action_cls: 0.0392 2023/03/11 10:25:18 - mmengine - INFO - Epoch(train) [5][2220/2226] lr: 9.4402e-07 eta: 9:30:06 time: 0.9865 data_time: 0.0137 memory: 70046 grad_norm: 0.1022 loss: 0.0547 recall@thr=0.5: 0.5417 prec@thr=0.5: 0.5208 recall@top3: 0.7292 prec@top3: 0.5833 recall@top5: 0.9375 prec@top5: 0.4750 loss_action_cls: 0.0547 2023/03/11 10:25:22 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 10:25:22 - mmengine - INFO - Epoch(train) [5][2226/2226] lr: 9.4447e-07 eta: 9:29:53 time: 0.7875 data_time: 0.0088 memory: 70046 grad_norm: 0.1061 loss: 0.0500 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.7500 recall@top3: 0.8750 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0500 2023/03/11 10:25:22 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/03/11 10:25:37 - mmengine - INFO - Epoch(val) [5][ 20/1571] eta: 0:05:25 time: 0.2101 data_time: 0.1145 memory: 6688 2023/03/11 10:25:40 - mmengine - INFO - Epoch(val) 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0:04:05 time: 0.1964 data_time: 0.0617 memory: 7490 2023/03/11 10:26:12 - mmengine - INFO - Epoch(val) [5][ 220/1571] eta: 0:04:03 time: 0.1911 data_time: 0.0826 memory: 7490 2023/03/11 10:26:15 - mmengine - INFO - Epoch(val) [5][ 240/1571] eta: 0:03:56 time: 0.1475 data_time: 0.0577 memory: 6775 2023/03/11 10:26:19 - mmengine - INFO - Epoch(val) [5][ 260/1571] eta: 0:03:51 time: 0.1637 data_time: 0.0677 memory: 6775 2023/03/11 10:26:21 - mmengine - INFO - Epoch(val) [5][ 280/1571] eta: 0:03:42 time: 0.1241 data_time: 0.0274 memory: 6775 2023/03/11 10:26:25 - mmengine - INFO - Epoch(val) [5][ 300/1571] eta: 0:03:39 time: 0.1741 data_time: 0.0754 memory: 6775 2023/03/11 10:26:28 - mmengine - INFO - Epoch(val) [5][ 320/1571] eta: 0:03:37 time: 0.1937 data_time: 0.0688 memory: 7490 2023/03/11 10:26:33 - mmengine - INFO - Epoch(val) [5][ 340/1571] eta: 0:03:37 time: 0.2193 data_time: 0.0784 memory: 7490 2023/03/11 10:26:36 - mmengine - INFO - Epoch(val) [5][ 360/1571] eta: 0:03:34 time: 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data_time: 0.0577 memory: 6775 2023/03/11 10:27:08 - mmengine - INFO - Epoch(val) [5][ 540/1571] eta: 0:03:01 time: 0.1814 data_time: 0.0788 memory: 6775 2023/03/11 10:27:11 - mmengine - INFO - Epoch(val) [5][ 560/1571] eta: 0:02:57 time: 0.1526 data_time: 0.0532 memory: 6775 2023/03/11 10:27:14 - mmengine - INFO - Epoch(val) [5][ 580/1571] eta: 0:02:53 time: 0.1570 data_time: 0.0604 memory: 6775 2023/03/11 10:27:17 - mmengine - INFO - Epoch(val) [5][ 600/1571] eta: 0:02:48 time: 0.1286 data_time: 0.0352 memory: 6775 2023/03/11 10:27:20 - mmengine - INFO - Epoch(val) [5][ 620/1571] eta: 0:02:44 time: 0.1828 data_time: 0.0666 memory: 7490 2023/03/11 10:27:24 - mmengine - INFO - Epoch(val) [5][ 640/1571] eta: 0:02:42 time: 0.2005 data_time: 0.0638 memory: 7490 2023/03/11 10:27:29 - mmengine - INFO - Epoch(val) [5][ 660/1571] eta: 0:02:39 time: 0.2146 data_time: 0.0792 memory: 7490 2023/03/11 10:27:33 - mmengine - INFO - Epoch(val) [5][ 680/1571] eta: 0:02:36 time: 0.1985 data_time: 0.0048 memory: 8699 2023/03/11 10:27:36 - mmengine - INFO - Epoch(val) [5][ 700/1571] eta: 0:02:33 time: 0.1654 data_time: 0.0451 memory: 8699 2023/03/11 10:27:39 - mmengine - INFO - Epoch(val) [5][ 720/1571] eta: 0:02:29 time: 0.1720 data_time: 0.0523 memory: 7490 2023/03/11 10:27:43 - mmengine - INFO - Epoch(val) [5][ 740/1571] eta: 0:02:26 time: 0.1896 data_time: 0.0731 memory: 7490 2023/03/11 10:27:46 - mmengine - INFO - Epoch(val) [5][ 760/1571] eta: 0:02:22 time: 0.1536 data_time: 0.0326 memory: 7490 2023/03/11 10:27:50 - mmengine - INFO - Epoch(val) [5][ 780/1571] eta: 0:02:18 time: 0.1774 data_time: 0.0563 memory: 7490 2023/03/11 10:27:53 - mmengine - INFO - Epoch(val) [5][ 800/1571] eta: 0:02:15 time: 0.1692 data_time: 0.0610 memory: 7490 2023/03/11 10:27:57 - mmengine - INFO - Epoch(val) [5][ 820/1571] eta: 0:02:11 time: 0.1823 data_time: 0.0493 memory: 7490 2023/03/11 10:28:00 - mmengine - INFO - Epoch(val) [5][ 840/1571] eta: 0:02:08 time: 0.1710 data_time: 0.0327 memory: 7490 2023/03/11 10:28:04 - mmengine - INFO - Epoch(val) [5][ 860/1571] eta: 0:02:05 time: 0.1893 data_time: 0.0802 memory: 7490 2023/03/11 10:28:07 - mmengine - INFO - Epoch(val) [5][ 880/1571] eta: 0:02:00 time: 0.1404 data_time: 0.0466 memory: 6775 2023/03/11 10:28:10 - mmengine - INFO - Epoch(val) [5][ 900/1571] eta: 0:01:57 time: 0.1794 data_time: 0.0769 memory: 7266 2023/03/11 10:28:14 - mmengine - INFO - Epoch(val) [5][ 920/1571] eta: 0:01:53 time: 0.1670 data_time: 0.0422 memory: 7490 2023/03/11 10:28:17 - mmengine - INFO - Epoch(val) [5][ 940/1571] eta: 0:01:50 time: 0.1899 data_time: 0.0507 memory: 7490 2023/03/11 10:28:21 - mmengine - INFO - Epoch(val) [5][ 960/1571] eta: 0:01:47 time: 0.1754 data_time: 0.0415 memory: 7490 2023/03/11 10:28:26 - mmengine - INFO - Epoch(val) [5][ 980/1571] eta: 0:01:44 time: 0.2265 data_time: 0.0819 memory: 7490 2023/03/11 10:28:29 - mmengine - INFO - Epoch(val) [5][1000/1571] eta: 0:01:40 time: 0.1749 data_time: 0.0317 memory: 7490 2023/03/11 10:28:33 - mmengine - INFO - Epoch(val) [5][1020/1571] eta: 0:01:37 time: 0.1924 data_time: 0.0320 memory: 8699 2023/03/11 10:28:36 - mmengine - INFO - Epoch(val) [5][1040/1571] eta: 0:01:33 time: 0.1579 data_time: 0.0021 memory: 8699 2023/03/11 10:28:40 - mmengine - INFO - Epoch(val) [5][1060/1571] eta: 0:01:30 time: 0.1905 data_time: 0.0916 memory: 6775 2023/03/11 10:28:43 - mmengine - INFO - Epoch(val) [5][1080/1571] eta: 0:01:26 time: 0.1614 data_time: 0.0605 memory: 6775 2023/03/11 10:28:47 - mmengine - INFO - Epoch(val) [5][1100/1571] eta: 0:01:23 time: 0.1867 data_time: 0.0618 memory: 7490 2023/03/11 10:28:51 - mmengine - INFO - Epoch(val) [5][1120/1571] eta: 0:01:19 time: 0.1893 data_time: 0.0381 memory: 7610 2023/03/11 10:28:54 - mmengine - INFO - Epoch(val) [5][1140/1571] eta: 0:01:16 time: 0.1715 data_time: 0.0480 memory: 7610 2023/03/11 10:28:57 - mmengine - INFO - Epoch(val) [5][1160/1571] eta: 0:01:12 time: 0.1629 data_time: 0.0510 memory: 7610 2023/03/11 10:29:01 - mmengine - INFO - Epoch(val) [5][1180/1571] eta: 0:01:08 time: 0.1738 data_time: 0.0358 memory: 7610 2023/03/11 10:29:04 - mmengine - INFO - Epoch(val) [5][1200/1571] eta: 0:01:05 time: 0.1607 data_time: 0.0507 memory: 7057 2023/03/11 10:29:08 - mmengine - INFO - Epoch(val) [5][1220/1571] eta: 0:01:01 time: 0.1777 data_time: 0.0441 memory: 7490 2023/03/11 10:29:11 - mmengine - INFO - Epoch(val) [5][1240/1571] eta: 0:00:58 time: 0.1759 data_time: 0.0400 memory: 7490 2023/03/11 10:29:14 - mmengine - INFO - Epoch(val) [5][1260/1571] eta: 0:00:54 time: 0.1673 data_time: 0.0492 memory: 7490 2023/03/11 10:29:18 - mmengine - INFO - Epoch(val) [5][1280/1571] eta: 0:00:51 time: 0.1594 data_time: 0.0595 memory: 6775 2023/03/11 10:29:21 - mmengine - INFO - Epoch(val) [5][1300/1571] eta: 0:00:47 time: 0.1753 data_time: 0.0817 memory: 6775 2023/03/11 10:29:25 - mmengine - INFO - Epoch(val) [5][1320/1571] eta: 0:00:44 time: 0.1726 data_time: 0.0767 memory: 6775 2023/03/11 10:29:28 - mmengine - INFO - Epoch(val) [5][1340/1571] eta: 0:00:40 time: 0.1691 data_time: 0.0705 memory: 6775 2023/03/11 10:29:31 - mmengine - INFO - Epoch(val) [5][1360/1571] eta: 0:00:37 time: 0.1707 data_time: 0.0768 memory: 6775 2023/03/11 10:29:35 - mmengine - INFO - Epoch(val) [5][1380/1571] eta: 0:00:33 time: 0.1810 data_time: 0.0755 memory: 7057 2023/03/11 10:29:39 - mmengine - INFO - Epoch(val) [5][1400/1571] eta: 0:00:30 time: 0.1774 data_time: 0.0698 memory: 7057 2023/03/11 10:29:42 - mmengine - INFO - Epoch(val) [5][1420/1571] eta: 0:00:26 time: 0.1829 data_time: 0.0799 memory: 7057 2023/03/11 10:29:45 - mmengine - INFO - Epoch(val) [5][1440/1571] eta: 0:00:22 time: 0.1498 data_time: 0.0417 memory: 7160 2023/03/11 10:29:49 - mmengine - INFO - Epoch(val) [5][1460/1571] eta: 0:00:19 time: 0.1746 data_time: 0.0625 memory: 7160 2023/03/11 10:29:52 - mmengine - INFO - Epoch(val) [5][1480/1571] eta: 0:00:15 time: 0.1648 data_time: 0.0602 memory: 7057 2023/03/11 10:29:55 - mmengine - INFO - Epoch(val) [5][1500/1571] eta: 0:00:12 time: 0.1639 data_time: 0.0627 memory: 7490 2023/03/11 10:29:58 - mmengine - INFO - Epoch(val) [5][1520/1571] eta: 0:00:08 time: 0.1326 data_time: 0.0019 memory: 7490 2023/03/11 10:30:01 - mmengine - INFO - Epoch(val) [5][1540/1571] eta: 0:00:05 time: 0.1326 data_time: 0.0020 memory: 7490 2023/03/11 10:30:03 - mmengine - INFO - Epoch(val) [5][1560/1571] eta: 0:00:01 time: 0.1325 data_time: 0.0019 memory: 7490 2023/03/11 10:34:18 - mmengine - INFO - Epoch(val) [5][1571/1571] mAP/mAP@0.5IOU: 0.3734 2023/03/11 10:34:18 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/hukai/mmaction2/work_dirs/vit-l_16x4/best_mAP/mAP@0.5IOU_epoch_4.pth is removed 2023/03/11 10:34:23 - mmengine - INFO - The best checkpoint with 0.3734 mAP/mAP@0.5IOU at 5 epoch is saved to best_mAP/mAP@0.5IOU_epoch_5.pth. 2023/03/11 10:34:47 - mmengine - INFO - Epoch(train) [6][ 20/2226] lr: 9.4447e-07 eta: 9:29:42 time: 1.1916 data_time: 0.5123 memory: 70046 grad_norm: 0.1041 loss: 0.0431 recall@thr=0.5: 0.8500 prec@thr=0.5: 0.9125 recall@top3: 0.8875 prec@top3: 0.7500 recall@top5: 1.0000 prec@top5: 0.5200 loss_action_cls: 0.0431 2023/03/11 10:35:07 - mmengine - INFO - Epoch(train) [6][ 40/2226] lr: 9.4447e-07 eta: 9:29:21 time: 1.0182 data_time: 0.0804 memory: 70046 grad_norm: 0.1050 loss: 0.0467 recall@thr=0.5: 0.7812 prec@thr=0.5: 0.8125 recall@top3: 0.8438 prec@top3: 0.6250 recall@top5: 0.9583 prec@top5: 0.4500 loss_action_cls: 0.0467 2023/03/11 10:35:29 - mmengine - INFO - Epoch(train) [6][ 60/2226] lr: 9.4447e-07 eta: 9:29:04 time: 1.0858 data_time: 0.0147 memory: 70046 grad_norm: 0.1093 loss: 0.0436 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.9444 recall@top3: 0.8611 prec@top3: 0.5556 recall@top5: 0.8889 prec@top5: 0.3556 loss_action_cls: 0.0436 2023/03/11 10:35:47 - mmengine - INFO - Epoch(train) [6][ 80/2226] lr: 9.4446e-07 eta: 9:28:36 time: 0.8948 data_time: 0.0106 memory: 70046 grad_norm: 0.1039 loss: 0.0420 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.8125 recall@top3: 0.7604 prec@top3: 0.5417 recall@top5: 0.8750 prec@top5: 0.4000 loss_action_cls: 0.0420 2023/03/11 10:36:11 - mmengine - INFO - Epoch(train) [6][ 100/2226] lr: 9.4445e-07 eta: 9:28:25 time: 1.1874 data_time: 0.0117 memory: 70046 grad_norm: 0.1052 loss: 0.0385 recall@thr=0.5: 0.9524 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.4571 loss_action_cls: 0.0385 2023/03/11 10:36:29 - mmengine - INFO - Epoch(train) [6][ 120/2226] lr: 9.4444e-07 eta: 9:27:57 time: 0.8948 data_time: 0.0094 memory: 70046 grad_norm: 0.1020 loss: 0.0472 recall@thr=0.5: 0.7692 prec@thr=0.5: 0.9308 recall@top3: 0.9487 prec@top3: 0.8462 recall@top5: 1.0000 prec@top5: 0.5385 loss_action_cls: 0.0472 2023/03/11 10:36:49 - mmengine - INFO - Epoch(train) [6][ 140/2226] lr: 9.4443e-07 eta: 9:27:36 time: 1.0070 data_time: 0.0114 memory: 70046 grad_norm: 0.1089 loss: 0.0396 recall@thr=0.5: 0.7700 prec@thr=0.5: 0.9417 recall@top3: 0.7450 prec@top3: 0.8000 recall@top5: 0.8950 prec@top5: 0.6200 loss_action_cls: 0.0396 2023/03/11 10:37:09 - mmengine - INFO - Epoch(train) [6][ 160/2226] lr: 9.4442e-07 eta: 9:27:13 time: 0.9914 data_time: 0.0111 memory: 70046 grad_norm: 0.1107 loss: 0.0454 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.5833 recall@top3: 0.8750 prec@top3: 0.3333 recall@top5: 1.0000 prec@top5: 0.2500 loss_action_cls: 0.0454 2023/03/11 10:37:29 - mmengine - INFO - Epoch(train) [6][ 180/2226] lr: 9.4441e-07 eta: 9:26:54 time: 1.0366 data_time: 0.0109 memory: 70046 grad_norm: 0.1043 loss: 0.0488 recall@thr=0.5: 0.6852 prec@thr=0.5: 0.9352 recall@top3: 0.9074 prec@top3: 0.8148 recall@top5: 0.9722 prec@top5: 0.5333 loss_action_cls: 0.0488 2023/03/11 10:37:52 - mmengine - INFO - Epoch(train) [6][ 200/2226] lr: 9.4439e-07 eta: 9:26:38 time: 1.1044 data_time: 0.0119 memory: 70046 grad_norm: 0.1039 loss: 0.0431 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.8333 recall@top3: 0.7500 prec@top3: 0.6667 recall@top5: 0.9333 prec@top5: 0.5200 loss_action_cls: 0.0431 2023/03/11 10:38:13 - mmengine - INFO - Epoch(train) [6][ 220/2226] lr: 9.4437e-07 eta: 9:26:19 time: 1.0582 data_time: 0.0096 memory: 70046 grad_norm: 0.1050 loss: 0.0434 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7222 recall@top3: 0.8889 prec@top3: 0.5185 recall@top5: 0.8889 prec@top5: 0.3111 loss_action_cls: 0.0434 2023/03/11 10:38:33 - mmengine - INFO - Epoch(train) [6][ 240/2226] lr: 9.4435e-07 eta: 9:25:58 time: 1.0099 data_time: 0.0105 memory: 70046 grad_norm: 0.1054 loss: 0.0469 recall@thr=0.5: 0.7292 prec@thr=0.5: 0.9583 recall@top3: 0.8333 prec@top3: 0.6250 recall@top5: 0.9583 prec@top5: 0.4500 loss_action_cls: 0.0469 2023/03/11 10:38:53 - mmengine - INFO - Epoch(train) [6][ 260/2226] lr: 9.4433e-07 eta: 9:25:36 time: 1.0035 data_time: 0.0123 memory: 70046 grad_norm: 0.1030 loss: 0.0512 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.9630 recall@top3: 0.9259 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4444 loss_action_cls: 0.0512 2023/03/11 10:39:14 - mmengine - INFO - Epoch(train) [6][ 280/2226] lr: 9.4431e-07 eta: 9:25:17 time: 1.0468 data_time: 0.0142 memory: 70046 grad_norm: 0.1116 loss: 0.0432 recall@thr=0.5: 0.7500 prec@thr=0.5: 1.0000 recall@top3: 0.8258 prec@top3: 0.7576 recall@top5: 1.0000 prec@top5: 0.5636 loss_action_cls: 0.0432 2023/03/11 10:39:33 - mmengine - INFO - Epoch(train) [6][ 300/2226] lr: 9.4429e-07 eta: 9:24:52 time: 0.9394 data_time: 0.0095 memory: 70046 grad_norm: 0.1061 loss: 0.0429 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.8750 recall@top3: 0.8646 prec@top3: 0.8750 recall@top5: 1.0000 prec@top5: 0.6250 loss_action_cls: 0.0429 2023/03/11 10:39:52 - mmengine - INFO - Epoch(train) [6][ 320/2226] lr: 9.4426e-07 eta: 9:24:28 time: 0.9765 data_time: 0.0114 memory: 70046 grad_norm: 0.1045 loss: 0.0470 recall@thr=0.5: 0.8125 prec@thr=0.5: 0.8125 recall@top3: 0.7778 prec@top3: 0.7222 recall@top5: 0.8958 prec@top5: 0.5167 loss_action_cls: 0.0470 2023/03/11 10:40:14 - mmengine - INFO - Epoch(train) [6][ 340/2226] lr: 9.4423e-07 eta: 9:24:11 time: 1.0816 data_time: 0.0135 memory: 70046 grad_norm: 0.1036 loss: 0.0468 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.7500 recall@top3: 1.0000 prec@top3: 0.7083 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0468 2023/03/11 10:40:33 - mmengine - INFO - Epoch(train) [6][ 360/2226] lr: 9.4420e-07 eta: 9:23:48 time: 0.9756 data_time: 0.0123 memory: 70046 grad_norm: 0.1075 loss: 0.0481 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.7000 recall@top3: 0.8000 prec@top3: 0.6667 recall@top5: 0.8667 prec@top5: 0.4400 loss_action_cls: 0.0481 2023/03/11 10:40:55 - mmengine - INFO - Epoch(train) [6][ 380/2226] lr: 9.4417e-07 eta: 9:23:30 time: 1.0651 data_time: 0.0118 memory: 70046 grad_norm: 0.1043 loss: 0.0423 recall@thr=0.5: 0.6736 prec@thr=0.5: 0.7500 recall@top3: 0.8472 prec@top3: 0.8333 recall@top5: 0.9444 prec@top5: 0.5667 loss_action_cls: 0.0423 2023/03/11 10:41:12 - mmengine - INFO - Epoch(train) [6][ 400/2226] lr: 9.4414e-07 eta: 9:23:01 time: 0.8805 data_time: 0.0098 memory: 70046 grad_norm: 0.1041 loss: 0.0500 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.8690 recall@top3: 1.0000 prec@top3: 0.8095 recall@top5: 1.0000 prec@top5: 0.4857 loss_action_cls: 0.0500 2023/03/11 10:41:35 - mmengine - INFO - Epoch(train) [6][ 420/2226] lr: 9.4411e-07 eta: 9:22:46 time: 1.1208 data_time: 0.0120 memory: 70046 grad_norm: 0.1086 loss: 0.0447 recall@thr=0.5: 1.0000 prec@thr=0.5: 0.9444 recall@top3: 1.0000 prec@top3: 0.6296 recall@top5: 1.0000 prec@top5: 0.3778 loss_action_cls: 0.0447 2023/03/11 10:41:53 - mmengine - INFO - Epoch(train) [6][ 440/2226] lr: 9.4407e-07 eta: 9:22:19 time: 0.9069 data_time: 0.0119 memory: 70046 grad_norm: 0.1009 loss: 0.0435 recall@thr=0.5: 0.8889 prec@thr=0.5: 1.0000 recall@top3: 0.9444 prec@top3: 0.8519 recall@top5: 1.0000 prec@top5: 0.5556 loss_action_cls: 0.0435 2023/03/11 10:42:13 - mmengine - INFO - Epoch(train) [6][ 460/2226] lr: 9.4403e-07 eta: 9:21:58 time: 1.0195 data_time: 0.0136 memory: 70046 grad_norm: 0.1084 loss: 0.0505 recall@thr=0.5: 0.5985 prec@thr=0.5: 0.6970 recall@top3: 0.7348 prec@top3: 0.6364 recall@top5: 0.8106 prec@top5: 0.4364 loss_action_cls: 0.0505 2023/03/11 10:42:36 - mmengine - INFO - Epoch(train) [6][ 480/2226] lr: 9.4399e-07 eta: 9:21:46 time: 1.1624 data_time: 0.0114 memory: 70046 grad_norm: 0.1018 loss: 0.0531 recall@thr=0.5: 0.9394 prec@thr=0.5: 0.8788 recall@top3: 1.0000 prec@top3: 0.7273 recall@top5: 1.0000 prec@top5: 0.4364 loss_action_cls: 0.0531 2023/03/11 10:42:55 - mmengine - INFO - Epoch(train) [6][ 500/2226] lr: 9.4395e-07 eta: 9:21:19 time: 0.9198 data_time: 0.0119 memory: 70046 grad_norm: 0.1044 loss: 0.0440 recall@thr=0.5: 1.0000 prec@thr=0.5: 0.7682 recall@top3: 0.9697 prec@top3: 0.7273 recall@top5: 1.0000 prec@top5: 0.4545 loss_action_cls: 0.0440 2023/03/11 10:43:14 - mmengine - INFO - Epoch(train) [6][ 520/2226] lr: 9.4391e-07 eta: 9:20:55 time: 0.9616 data_time: 0.0107 memory: 70046 grad_norm: 0.1053 loss: 0.0395 recall@thr=0.5: 0.5885 prec@thr=0.5: 0.7917 recall@top3: 0.7552 prec@top3: 0.6667 recall@top5: 0.9375 prec@top5: 0.5125 loss_action_cls: 0.0395 2023/03/11 10:43:38 - mmengine - INFO - Epoch(train) [6][ 540/2226] lr: 9.4387e-07 eta: 9:20:44 time: 1.1933 data_time: 0.0146 memory: 70046 grad_norm: 0.1016 loss: 0.0402 recall@thr=0.5: 0.8333 prec@thr=0.5: 1.0000 recall@top3: 0.9583 prec@top3: 0.7917 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0402 2023/03/11 10:43:56 - mmengine - INFO - Epoch(train) [6][ 560/2226] lr: 9.4382e-07 eta: 9:20:18 time: 0.9170 data_time: 0.0101 memory: 70046 grad_norm: 0.1073 loss: 0.0437 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.7639 recall@top3: 0.6667 prec@top3: 0.5833 recall@top5: 0.8472 prec@top5: 0.4667 loss_action_cls: 0.0437 2023/03/11 10:44:16 - mmengine - INFO - Epoch(train) [6][ 580/2226] lr: 9.4377e-07 eta: 9:19:54 time: 0.9665 data_time: 0.0102 memory: 70046 grad_norm: 0.1020 loss: 0.0468 recall@thr=0.5: 0.6889 prec@thr=0.5: 0.5778 recall@top3: 0.8889 prec@top3: 0.5778 recall@top5: 0.9556 prec@top5: 0.3733 loss_action_cls: 0.0468 2023/03/11 10:44:36 - mmengine - INFO - Epoch(train) [6][ 600/2226] lr: 9.4372e-07 eta: 9:19:33 time: 1.0213 data_time: 0.0117 memory: 70046 grad_norm: 0.0995 loss: 0.0466 recall@thr=0.5: 0.6389 prec@thr=0.5: 0.7222 recall@top3: 0.9722 prec@top3: 0.5185 recall@top5: 0.9722 prec@top5: 0.3111 loss_action_cls: 0.0466 2023/03/11 10:44:57 - mmengine - INFO - Epoch(train) [6][ 620/2226] lr: 9.4367e-07 eta: 9:19:13 time: 1.0250 data_time: 0.0114 memory: 70046 grad_norm: 0.1040 loss: 0.0435 recall@thr=0.5: 1.0000 prec@thr=0.5: 0.9722 recall@top3: 0.8889 prec@top3: 0.8148 recall@top5: 1.0000 prec@top5: 0.5778 loss_action_cls: 0.0435 2023/03/11 10:45:15 - mmengine - INFO - Epoch(train) [6][ 640/2226] lr: 9.4362e-07 eta: 9:18:47 time: 0.9295 data_time: 0.0104 memory: 70046 grad_norm: 0.1036 loss: 0.0400 recall@thr=0.5: 0.8611 prec@thr=0.5: 0.9259 recall@top3: 0.9167 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.5333 loss_action_cls: 0.0400 2023/03/11 10:45:36 - mmengine - INFO - Epoch(train) [6][ 660/2226] lr: 9.4357e-07 eta: 9:18:28 time: 1.0399 data_time: 0.0115 memory: 70046 grad_norm: 0.1102 loss: 0.0455 recall@thr=0.5: 0.4902 prec@thr=0.5: 0.7059 recall@top3: 0.6912 prec@top3: 0.6078 recall@top5: 0.7500 prec@top5: 0.3765 loss_action_cls: 0.0455 2023/03/11 10:46:00 - mmengine - INFO - Epoch(train) [6][ 680/2226] lr: 9.4351e-07 eta: 9:18:17 time: 1.1983 data_time: 0.0148 memory: 70046 grad_norm: 0.1022 loss: 0.0388 recall@thr=0.5: 0.9722 prec@thr=0.5: 0.7083 recall@top3: 0.9722 prec@top3: 0.6111 recall@top5: 1.0000 prec@top5: 0.3833 loss_action_cls: 0.0388 2023/03/11 10:46:15 - mmengine - INFO - Epoch(train) [6][ 700/2226] lr: 9.4345e-07 eta: 9:17:43 time: 0.7753 data_time: 0.0090 memory: 70046 grad_norm: 0.1077 loss: 0.0375 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.7083 recall@top3: 0.7083 prec@top3: 0.5417 recall@top5: 0.7500 prec@top5: 0.3500 loss_action_cls: 0.0375 2023/03/11 10:46:37 - mmengine - INFO - Epoch(train) [6][ 720/2226] lr: 9.4339e-07 eta: 9:17:26 time: 1.0893 data_time: 0.0112 memory: 70046 grad_norm: 0.1026 loss: 0.0455 recall@thr=0.5: 0.9318 prec@thr=0.5: 0.7576 recall@top3: 0.9318 prec@top3: 0.6667 recall@top5: 0.9545 prec@top5: 0.4182 loss_action_cls: 0.0455 2023/03/11 10:46:59 - mmengine - INFO - Epoch(train) [6][ 740/2226] lr: 9.4333e-07 eta: 9:17:09 time: 1.0877 data_time: 0.0100 memory: 70046 grad_norm: 0.1043 loss: 0.0472 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.5741 recall@top3: 0.6111 prec@top3: 0.4444 recall@top5: 0.8148 prec@top5: 0.4000 loss_action_cls: 0.0472 2023/03/11 10:47:15 - mmengine - INFO - Epoch(train) [6][ 760/2226] lr: 9.4327e-07 eta: 9:16:36 time: 0.8050 data_time: 0.0118 memory: 70046 grad_norm: 0.1038 loss: 0.0480 recall@thr=0.5: 0.6250 prec@thr=0.5: 1.0000 recall@top3: 0.8194 prec@top3: 0.9167 recall@top5: 0.9167 prec@top5: 0.6167 loss_action_cls: 0.0480 2023/03/11 10:47:38 - mmengine - INFO - Epoch(train) [6][ 780/2226] lr: 9.4321e-07 eta: 9:16:23 time: 1.1614 data_time: 0.0132 memory: 70046 grad_norm: 0.1060 loss: 0.0513 recall@thr=0.5: 0.5972 prec@thr=0.5: 0.6250 recall@top3: 0.8750 prec@top3: 0.6389 recall@top5: 0.8958 prec@top5: 0.4000 loss_action_cls: 0.0513 2023/03/11 10:47:59 - mmengine - INFO - Epoch(train) [6][ 800/2226] lr: 9.4314e-07 eta: 9:16:04 time: 1.0392 data_time: 0.0387 memory: 70046 grad_norm: 0.1052 loss: 0.0491 recall@thr=0.5: 0.5208 prec@thr=0.5: 0.5375 recall@top3: 0.5729 prec@top3: 0.6667 recall@top5: 0.8958 prec@top5: 0.5500 loss_action_cls: 0.0491 2023/03/11 10:48:22 - mmengine - INFO - Epoch(train) [6][ 820/2226] lr: 9.4307e-07 eta: 9:15:49 time: 1.1294 data_time: 0.0121 memory: 70046 grad_norm: 0.1033 loss: 0.0336 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7778 recall@top3: 0.8333 prec@top3: 0.7222 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0336 2023/03/11 10:48:41 - mmengine - INFO - Epoch(train) [6][ 840/2226] lr: 9.4300e-07 eta: 9:15:26 time: 0.9698 data_time: 0.0121 memory: 70046 grad_norm: 0.1069 loss: 0.0373 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.8750 recall@top3: 0.7917 prec@top3: 0.5833 recall@top5: 0.9583 prec@top5: 0.4250 loss_action_cls: 0.0373 2023/03/11 10:49:03 - mmengine - INFO - Epoch(train) [6][ 860/2226] lr: 9.4293e-07 eta: 9:15:10 time: 1.1124 data_time: 0.0119 memory: 70046 grad_norm: 0.1075 loss: 0.0444 recall@thr=0.5: 0.8083 prec@thr=0.5: 0.8437 recall@top3: 0.8823 prec@top3: 0.6458 recall@top5: 1.0000 prec@top5: 0.4750 loss_action_cls: 0.0444 2023/03/11 10:49:11 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 10:49:19 - mmengine - INFO - Epoch(train) [6][ 880/2226] lr: 9.4286e-07 eta: 9:14:36 time: 0.7736 data_time: 0.0083 memory: 70046 grad_norm: 0.1080 loss: 0.0422 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6250 recall@top3: 0.8750 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0422 2023/03/11 10:49:40 - mmengine - INFO - Epoch(train) [6][ 900/2226] lr: 9.4278e-07 eta: 9:14:18 time: 1.0781 data_time: 0.0128 memory: 70046 grad_norm: 0.1051 loss: 0.0521 recall@thr=0.5: 0.6818 prec@thr=0.5: 0.7879 recall@top3: 0.8106 prec@top3: 0.6364 recall@top5: 0.9318 prec@top5: 0.4545 loss_action_cls: 0.0521 2023/03/11 10:50:00 - mmengine - INFO - Epoch(train) [6][ 920/2226] lr: 9.4271e-07 eta: 9:13:56 time: 0.9876 data_time: 0.0154 memory: 70046 grad_norm: 0.1031 loss: 0.0473 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6667 recall@top3: 0.8125 prec@top3: 0.5417 recall@top5: 0.9375 prec@top5: 0.3750 loss_action_cls: 0.0473 2023/03/11 10:50:23 - mmengine - INFO - Epoch(train) [6][ 940/2226] lr: 9.4263e-07 eta: 9:13:43 time: 1.1650 data_time: 0.0125 memory: 70046 grad_norm: 0.1052 loss: 0.0311 recall@thr=0.5: 0.6923 prec@thr=0.5: 0.8718 recall@top3: 0.7308 prec@top3: 0.6410 recall@top5: 0.8846 prec@top5: 0.4769 loss_action_cls: 0.0311 2023/03/11 10:50:41 - mmengine - INFO - Epoch(train) [6][ 960/2226] lr: 9.4255e-07 eta: 9:13:15 time: 0.8711 data_time: 0.0094 memory: 70046 grad_norm: 0.1047 loss: 0.0456 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.7833 recall@top3: 0.9333 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4400 loss_action_cls: 0.0456 2023/03/11 10:51:03 - mmengine - INFO - Epoch(train) [6][ 980/2226] lr: 9.4247e-07 eta: 9:12:59 time: 1.1186 data_time: 0.0123 memory: 70046 grad_norm: 0.1022 loss: 0.0377 recall@thr=0.5: 0.9333 prec@thr=0.5: 0.9000 recall@top3: 0.9417 prec@top3: 0.7333 recall@top5: 1.0000 prec@top5: 0.4800 loss_action_cls: 0.0377 2023/03/11 10:51:23 - mmengine - INFO - Epoch(train) [6][1000/2226] lr: 9.4239e-07 eta: 9:12:36 time: 0.9692 data_time: 0.0118 memory: 70046 grad_norm: 0.1055 loss: 0.0461 recall@thr=0.5: 0.2381 prec@thr=0.5: 0.3333 recall@top3: 0.5952 prec@top3: 0.6190 recall@top5: 0.8333 prec@top5: 0.5429 loss_action_cls: 0.0461 2023/03/11 10:51:44 - mmengine - INFO - Epoch(train) [6][1020/2226] lr: 9.4230e-07 eta: 9:12:17 time: 1.0560 data_time: 0.0122 memory: 70046 grad_norm: 0.1085 loss: 0.0435 recall@thr=0.5: 0.3571 prec@thr=0.5: 0.4286 recall@top3: 0.6071 prec@top3: 0.3571 recall@top5: 0.8214 prec@top5: 0.2857 loss_action_cls: 0.0435 2023/03/11 10:52:03 - mmengine - INFO - Epoch(train) [6][1040/2226] lr: 9.4222e-07 eta: 9:11:53 time: 0.9660 data_time: 0.0096 memory: 70046 grad_norm: 0.1007 loss: 0.0428 recall@thr=0.5: 0.7750 prec@thr=0.5: 0.9167 recall@top3: 0.8000 prec@top3: 0.7667 recall@top5: 0.8750 prec@top5: 0.5000 loss_action_cls: 0.0428 2023/03/11 10:52:22 - mmengine - INFO - Epoch(train) [6][1060/2226] lr: 9.4213e-07 eta: 9:11:28 time: 0.9382 data_time: 0.0095 memory: 70046 grad_norm: 0.0988 loss: 0.0404 recall@thr=0.5: 0.8981 prec@thr=0.5: 0.8667 recall@top3: 0.8889 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.5556 loss_action_cls: 0.0404 2023/03/11 10:52:43 - mmengine - INFO - Epoch(train) [6][1080/2226] lr: 9.4204e-07 eta: 9:11:10 time: 1.0708 data_time: 0.0143 memory: 70046 grad_norm: 0.0974 loss: 0.0370 recall@thr=0.5: 0.7037 prec@thr=0.5: 0.8889 recall@top3: 0.8519 prec@top3: 0.7778 recall@top5: 0.9259 prec@top5: 0.5111 loss_action_cls: 0.0370 2023/03/11 10:53:05 - mmengine - INFO - Epoch(train) [6][1100/2226] lr: 9.4195e-07 eta: 9:10:52 time: 1.0669 data_time: 0.0109 memory: 70046 grad_norm: 0.1039 loss: 0.0374 recall@thr=0.5: 0.7667 prec@thr=0.5: 0.8333 recall@top3: 0.8000 prec@top3: 0.7000 recall@top5: 0.8833 prec@top5: 0.4800 loss_action_cls: 0.0374 2023/03/11 10:53:26 - mmengine - INFO - Epoch(train) [6][1120/2226] lr: 9.4186e-07 eta: 9:10:34 time: 1.0646 data_time: 0.0098 memory: 70046 grad_norm: 0.1018 loss: 0.0466 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.8333 recall@top3: 0.8333 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3000 loss_action_cls: 0.0466 2023/03/11 10:53:44 - mmengine - INFO - Epoch(train) [6][1140/2226] lr: 9.4176e-07 eta: 9:10:08 time: 0.9265 data_time: 0.0113 memory: 70046 grad_norm: 0.1014 loss: 0.0415 recall@thr=0.5: 0.5714 prec@thr=0.5: 0.9048 recall@top3: 0.6667 prec@top3: 0.5714 recall@top5: 1.0000 prec@top5: 0.5143 loss_action_cls: 0.0415 2023/03/11 10:54:07 - mmengine - INFO - Epoch(train) [6][1160/2226] lr: 9.4167e-07 eta: 9:09:53 time: 1.1137 data_time: 0.0121 memory: 70046 grad_norm: 0.1020 loss: 0.0409 recall@thr=0.5: 0.6569 prec@thr=0.5: 0.7598 recall@top3: 0.8824 prec@top3: 0.7451 recall@top5: 0.9412 prec@top5: 0.4706 loss_action_cls: 0.0409 2023/03/11 10:54:27 - mmengine - INFO - Epoch(train) [6][1180/2226] lr: 9.4157e-07 eta: 9:09:31 time: 0.9926 data_time: 0.0108 memory: 70046 grad_norm: 0.1032 loss: 0.0470 recall@thr=0.5: 0.8854 prec@thr=0.5: 0.9375 recall@top3: 0.8854 prec@top3: 0.7083 recall@top5: 0.9271 prec@top5: 0.4500 loss_action_cls: 0.0470 2023/03/11 10:54:48 - mmengine - INFO - Epoch(train) [6][1200/2226] lr: 9.4147e-07 eta: 9:09:12 time: 1.0695 data_time: 0.0099 memory: 70046 grad_norm: 0.1003 loss: 0.0352 recall@thr=0.5: 0.8000 prec@thr=0.5: 0.8333 recall@top3: 0.9500 prec@top3: 0.6000 recall@top5: 0.9500 prec@top5: 0.3600 loss_action_cls: 0.0352 2023/03/11 10:55:06 - mmengine - INFO - Epoch(train) [6][1220/2226] lr: 9.4137e-07 eta: 9:08:46 time: 0.9059 data_time: 0.0090 memory: 70046 grad_norm: 0.1015 loss: 0.0288 recall@thr=0.5: 0.8125 prec@thr=0.5: 0.8958 recall@top3: 0.8958 prec@top3: 0.7917 recall@top5: 0.8958 prec@top5: 0.4750 loss_action_cls: 0.0288 2023/03/11 10:55:25 - mmengine - INFO - Epoch(train) [6][1240/2226] lr: 9.4127e-07 eta: 9:08:22 time: 0.9577 data_time: 0.0091 memory: 70046 grad_norm: 0.1026 loss: 0.0495 recall@thr=0.5: 0.9111 prec@thr=0.5: 0.8417 recall@top3: 0.9000 prec@top3: 0.7500 recall@top5: 0.9667 prec@top5: 0.5167 loss_action_cls: 0.0495 2023/03/11 10:55:44 - mmengine - INFO - Epoch(train) [6][1260/2226] lr: 9.4116e-07 eta: 9:07:57 time: 0.9359 data_time: 0.0131 memory: 70046 grad_norm: 0.1030 loss: 0.0454 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.6389 recall@top3: 0.7500 prec@top3: 0.5278 recall@top5: 0.7500 prec@top5: 0.3167 loss_action_cls: 0.0454 2023/03/11 10:56:06 - mmengine - INFO - Epoch(train) [6][1280/2226] lr: 9.4106e-07 eta: 9:07:40 time: 1.0988 data_time: 0.0130 memory: 70046 grad_norm: 0.1030 loss: 0.0405 recall@thr=0.5: 0.6500 prec@thr=0.5: 0.8667 recall@top3: 0.8500 prec@top3: 0.4667 recall@top5: 0.9000 prec@top5: 0.3000 loss_action_cls: 0.0405 2023/03/11 10:56:28 - mmengine - INFO - Epoch(train) [6][1300/2226] lr: 9.4095e-07 eta: 9:07:23 time: 1.0901 data_time: 0.0112 memory: 70046 grad_norm: 0.1015 loss: 0.0480 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.5000 recall@top3: 0.6250 prec@top3: 0.4167 recall@top5: 0.6250 prec@top5: 0.2500 loss_action_cls: 0.0480 2023/03/11 10:56:49 - mmengine - INFO - Epoch(train) [6][1320/2226] lr: 9.4084e-07 eta: 9:07:05 time: 1.0719 data_time: 0.0093 memory: 70046 grad_norm: 0.1011 loss: 0.0496 recall@thr=0.5: 0.3704 prec@thr=0.5: 0.4444 recall@top3: 0.7963 prec@top3: 0.5185 recall@top5: 0.9722 prec@top5: 0.4000 loss_action_cls: 0.0496 2023/03/11 10:57:08 - mmengine - INFO - Epoch(train) [6][1340/2226] lr: 9.4073e-07 eta: 9:06:41 time: 0.9438 data_time: 0.0093 memory: 70046 grad_norm: 0.1030 loss: 0.0361 recall@thr=0.5: 0.8667 prec@thr=0.5: 0.9000 recall@top3: 0.9333 prec@top3: 0.6333 recall@top5: 1.0000 prec@top5: 0.4200 loss_action_cls: 0.0361 2023/03/11 10:57:28 - mmengine - INFO - Epoch(train) [6][1360/2226] lr: 9.4062e-07 eta: 9:06:18 time: 0.9803 data_time: 0.0122 memory: 70046 grad_norm: 0.1014 loss: 0.0423 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.5893 recall@top3: 0.6667 prec@top3: 0.5000 recall@top5: 0.7857 prec@top5: 0.3429 loss_action_cls: 0.0423 2023/03/11 10:57:51 - mmengine - INFO - Epoch(train) [6][1380/2226] lr: 9.4050e-07 eta: 9:06:05 time: 1.1745 data_time: 0.0101 memory: 70046 grad_norm: 0.0996 loss: 0.0454 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.8571 recall@top3: 1.0000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0454 2023/03/11 10:58:07 - mmengine - INFO - Epoch(train) [6][1400/2226] lr: 9.4039e-07 eta: 9:05:33 time: 0.7930 data_time: 0.0101 memory: 70046 grad_norm: 0.1015 loss: 0.0473 recall@thr=0.5: 0.7037 prec@thr=0.5: 0.9444 recall@top3: 0.8889 prec@top3: 0.5926 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0473 2023/03/11 10:58:30 - mmengine - INFO - Epoch(train) [6][1420/2226] lr: 9.4027e-07 eta: 9:05:19 time: 1.1448 data_time: 0.0128 memory: 70046 grad_norm: 0.1009 loss: 0.0514 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.6667 recall@top3: 0.9444 prec@top3: 0.3333 recall@top5: 1.0000 prec@top5: 0.2222 loss_action_cls: 0.0514 2023/03/11 10:58:48 - mmengine - INFO - Epoch(train) [6][1440/2226] lr: 9.4015e-07 eta: 9:04:52 time: 0.8930 data_time: 0.0087 memory: 70046 grad_norm: 0.1023 loss: 0.0470 recall@thr=0.5: 0.7436 prec@thr=0.5: 0.8205 recall@top3: 0.8718 prec@top3: 0.7179 recall@top5: 1.0000 prec@top5: 0.5077 loss_action_cls: 0.0470 2023/03/11 10:59:09 - mmengine - INFO - Epoch(train) [6][1460/2226] lr: 9.4003e-07 eta: 9:04:34 time: 1.0798 data_time: 0.0102 memory: 70046 grad_norm: 0.1075 loss: 0.0422 recall@thr=0.5: 0.4722 prec@thr=0.5: 0.6667 recall@top3: 0.7083 prec@top3: 0.5000 recall@top5: 0.8472 prec@top5: 0.3667 loss_action_cls: 0.0422 2023/03/11 10:59:29 - mmengine - INFO - Epoch(train) [6][1480/2226] lr: 9.3991e-07 eta: 9:04:11 time: 0.9642 data_time: 0.0123 memory: 70046 grad_norm: 0.1002 loss: 0.0416 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.8125 recall@top3: 0.8438 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0416 2023/03/11 10:59:51 - mmengine - INFO - Epoch(train) [6][1500/2226] lr: 9.3978e-07 eta: 9:03:56 time: 1.1330 data_time: 0.0110 memory: 70046 grad_norm: 0.1032 loss: 0.0374 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7857 recall@top3: 0.8571 prec@top3: 0.8095 recall@top5: 0.9286 prec@top5: 0.5429 loss_action_cls: 0.0374 2023/03/11 11:00:11 - mmengine - INFO - Epoch(train) [6][1520/2226] lr: 9.3966e-07 eta: 9:03:34 time: 0.9977 data_time: 0.0091 memory: 70046 grad_norm: 0.1039 loss: 0.0350 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.8571 recall@top3: 0.8571 prec@top3: 0.6190 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0350 2023/03/11 11:00:31 - mmengine - INFO - Epoch(train) [6][1540/2226] lr: 9.3953e-07 eta: 9:03:12 time: 0.9898 data_time: 0.0091 memory: 70046 grad_norm: 0.0996 loss: 0.0379 recall@thr=0.5: 0.8571 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0379 2023/03/11 11:00:53 - mmengine - INFO - Epoch(train) [6][1560/2226] lr: 9.3940e-07 eta: 9:02:56 time: 1.1060 data_time: 0.0096 memory: 70046 grad_norm: 0.1005 loss: 0.0471 recall@thr=0.5: 0.8125 prec@thr=0.5: 0.7812 recall@top3: 0.8125 prec@top3: 0.7083 recall@top5: 0.9375 prec@top5: 0.4750 loss_action_cls: 0.0471 2023/03/11 11:01:15 - mmengine - INFO - Epoch(train) [6][1580/2226] lr: 9.3927e-07 eta: 9:02:38 time: 1.0804 data_time: 0.0089 memory: 70046 grad_norm: 0.1000 loss: 0.0378 recall@thr=0.5: 0.6190 prec@thr=0.5: 0.7143 recall@top3: 0.7619 prec@top3: 0.5238 recall@top5: 0.9286 prec@top5: 0.4000 loss_action_cls: 0.0378 2023/03/11 11:01:35 - mmengine - INFO - Epoch(train) [6][1600/2226] lr: 9.3914e-07 eta: 9:02:18 time: 1.0333 data_time: 0.0081 memory: 70046 grad_norm: 0.1037 loss: 0.0377 recall@thr=0.5: 0.7179 prec@thr=0.5: 0.8077 recall@top3: 0.9808 prec@top3: 0.7436 recall@top5: 0.9808 prec@top5: 0.4462 loss_action_cls: 0.0377 2023/03/11 11:01:49 - mmengine - INFO - Epoch(train) [6][1620/2226] lr: 9.3901e-07 eta: 9:01:41 time: 0.7010 data_time: 0.0091 memory: 70046 grad_norm: 0.1040 loss: 0.0359 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8333 recall@top3: 0.8333 prec@top3: 0.4444 recall@top5: 1.0000 prec@top5: 0.3000 loss_action_cls: 0.0359 2023/03/11 11:02:12 - mmengine - INFO - Epoch(train) [6][1640/2226] lr: 9.3887e-07 eta: 9:01:26 time: 1.1183 data_time: 0.0110 memory: 70046 grad_norm: 0.1028 loss: 0.0447 recall@thr=0.5: 0.8036 prec@thr=0.5: 0.8393 recall@top3: 0.8214 prec@top3: 0.6190 recall@top5: 0.8929 prec@top5: 0.4143 loss_action_cls: 0.0447 2023/03/11 11:02:35 - mmengine - INFO - Epoch(train) [6][1660/2226] lr: 9.3873e-07 eta: 9:01:11 time: 1.1421 data_time: 0.0121 memory: 70046 grad_norm: 0.1011 loss: 0.0381 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.7143 recall@top3: 0.9524 prec@top3: 0.5714 recall@top5: 0.9524 prec@top5: 0.3429 loss_action_cls: 0.0381 2023/03/11 11:02:52 - mmengine - INFO - Epoch(train) [6][1680/2226] lr: 9.3859e-07 eta: 9:00:43 time: 0.8757 data_time: 0.0130 memory: 70046 grad_norm: 0.1035 loss: 0.0465 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 1.0000 prec@top3: 0.4286 recall@top5: 1.0000 prec@top5: 0.2571 loss_action_cls: 0.0465 2023/03/11 11:03:14 - mmengine - INFO - Epoch(train) [6][1700/2226] lr: 9.3845e-07 eta: 9:00:26 time: 1.0897 data_time: 0.0129 memory: 70046 grad_norm: 0.1005 loss: 0.0475 recall@thr=0.5: 0.8148 prec@thr=0.5: 0.8889 recall@top3: 0.8889 prec@top3: 0.6296 recall@top5: 0.9444 prec@top5: 0.4000 loss_action_cls: 0.0475 2023/03/11 11:03:33 - mmengine - INFO - Epoch(train) [6][1720/2226] lr: 9.3831e-07 eta: 9:00:03 time: 0.9663 data_time: 0.0138 memory: 70046 grad_norm: 0.1015 loss: 0.0457 recall@thr=0.5: 0.6833 prec@thr=0.5: 0.7333 recall@top3: 0.7333 prec@top3: 0.5333 recall@top5: 0.8583 prec@top5: 0.3800 loss_action_cls: 0.0457 2023/03/11 11:03:55 - mmengine - INFO - Epoch(train) [6][1740/2226] lr: 9.3817e-07 eta: 8:59:45 time: 1.0759 data_time: 0.0125 memory: 70046 grad_norm: 0.1030 loss: 0.0463 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 0.7857 prec@top3: 0.4762 recall@top5: 0.7857 prec@top5: 0.2857 loss_action_cls: 0.0463 2023/03/11 11:04:17 - mmengine - INFO - Epoch(train) [6][1760/2226] lr: 9.3802e-07 eta: 8:59:29 time: 1.1035 data_time: 0.0121 memory: 70046 grad_norm: 0.1012 loss: 0.0323 recall@thr=0.5: 0.8485 prec@thr=0.5: 0.7727 recall@top3: 0.8333 prec@top3: 0.6970 recall@top5: 0.9091 prec@top5: 0.4727 loss_action_cls: 0.0323 2023/03/11 11:04:38 - mmengine - INFO - Epoch(train) [6][1780/2226] lr: 9.3787e-07 eta: 8:59:09 time: 1.0522 data_time: 0.0128 memory: 70046 grad_norm: 0.1061 loss: 0.0410 recall@thr=0.5: 0.7222 prec@thr=0.5: 0.7500 recall@top3: 0.7778 prec@top3: 0.7407 recall@top5: 0.8333 prec@top5: 0.4889 loss_action_cls: 0.0410 2023/03/11 11:04:58 - mmengine - INFO - Epoch(train) [6][1800/2226] lr: 9.3772e-07 eta: 8:58:47 time: 0.9877 data_time: 0.0101 memory: 70046 grad_norm: 0.1045 loss: 0.0425 recall@thr=0.5: 0.9167 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.8333 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0425 2023/03/11 11:05:18 - mmengine - INFO - Epoch(train) [6][1820/2226] lr: 9.3757e-07 eta: 8:58:27 time: 1.0282 data_time: 0.0091 memory: 70046 grad_norm: 0.1088 loss: 0.0389 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.8125 recall@top3: 0.9167 prec@top3: 0.7500 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0389 2023/03/11 11:05:37 - mmengine - INFO - Epoch(train) [6][1840/2226] lr: 9.3742e-07 eta: 8:58:03 time: 0.9495 data_time: 0.0099 memory: 70046 grad_norm: 0.0974 loss: 0.0375 recall@thr=0.5: 0.8548 prec@thr=0.5: 0.8393 recall@top3: 0.8940 prec@top3: 0.8333 recall@top5: 0.9679 prec@top5: 0.5571 loss_action_cls: 0.0375 2023/03/11 11:06:01 - mmengine - INFO - Epoch(train) [6][1860/2226] lr: 9.3727e-07 eta: 8:57:50 time: 1.1777 data_time: 0.0094 memory: 70046 grad_norm: 0.1002 loss: 0.0498 recall@thr=0.5: 0.7500 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.7000 recall@top5: 1.0000 prec@top5: 0.4200 loss_action_cls: 0.0498 2023/03/11 11:06:09 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 11:06:20 - mmengine - INFO - Epoch(train) [6][1880/2226] lr: 9.3711e-07 eta: 8:57:25 time: 0.9392 data_time: 0.0107 memory: 70046 grad_norm: 0.1034 loss: 0.0364 recall@thr=0.5: 0.9167 prec@thr=0.5: 0.7917 recall@top3: 0.9167 prec@top3: 0.6250 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0364 2023/03/11 11:06:41 - mmengine - INFO - Epoch(train) [6][1900/2226] lr: 9.3696e-07 eta: 8:57:07 time: 1.0711 data_time: 0.0088 memory: 70046 grad_norm: 0.1018 loss: 0.0442 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8889 recall@top3: 0.9167 prec@top3: 0.7037 recall@top5: 0.9444 prec@top5: 0.4444 loss_action_cls: 0.0442 2023/03/11 11:07:00 - mmengine - INFO - Epoch(train) [6][1920/2226] lr: 9.3680e-07 eta: 8:56:44 time: 0.9658 data_time: 0.0093 memory: 70046 grad_norm: 0.1014 loss: 0.0398 recall@thr=0.5: 0.8121 prec@thr=0.5: 0.8424 recall@top3: 0.8515 prec@top3: 0.7273 recall@top5: 0.9182 prec@top5: 0.4909 loss_action_cls: 0.0398 2023/03/11 11:07:21 - mmengine - INFO - Epoch(train) [6][1940/2226] lr: 9.3664e-07 eta: 8:56:25 time: 1.0441 data_time: 0.0093 memory: 70046 grad_norm: 0.0986 loss: 0.0441 recall@thr=0.5: 0.9167 prec@thr=0.5: 0.8167 recall@top3: 0.9167 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4600 loss_action_cls: 0.0441 2023/03/11 11:07:41 - mmengine - INFO - Epoch(train) [6][1960/2226] lr: 9.3647e-07 eta: 8:56:03 time: 1.0005 data_time: 0.0099 memory: 70046 grad_norm: 0.0969 loss: 0.0430 recall@thr=0.5: 0.6556 prec@thr=0.5: 0.7778 recall@top3: 0.8056 prec@top3: 0.5778 recall@top5: 0.8444 prec@top5: 0.3733 loss_action_cls: 0.0430 2023/03/11 11:08:03 - mmengine - INFO - Epoch(train) [6][1980/2226] lr: 9.3631e-07 eta: 8:55:46 time: 1.0883 data_time: 0.0111 memory: 70046 grad_norm: 0.1035 loss: 0.0445 recall@thr=0.5: 0.8889 prec@thr=0.5: 0.8472 recall@top3: 0.8333 prec@top3: 0.7778 recall@top5: 1.0000 prec@top5: 0.5667 loss_action_cls: 0.0445 2023/03/11 11:08:22 - mmengine - INFO - Epoch(train) [6][2000/2226] lr: 9.3615e-07 eta: 8:55:22 time: 0.9473 data_time: 0.0110 memory: 70046 grad_norm: 0.1028 loss: 0.0450 recall@thr=0.5: 0.8571 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.6190 recall@top5: 1.0000 prec@top5: 0.3714 loss_action_cls: 0.0450 2023/03/11 11:08:45 - mmengine - INFO - Epoch(train) [6][2020/2226] lr: 9.3598e-07 eta: 8:55:07 time: 1.1393 data_time: 0.0100 memory: 70046 grad_norm: 0.0989 loss: 0.0413 recall@thr=0.5: 0.7576 prec@thr=0.5: 0.8485 recall@top3: 0.8485 prec@top3: 0.5758 recall@top5: 0.9394 prec@top5: 0.4000 loss_action_cls: 0.0413 2023/03/11 11:09:05 - mmengine - INFO - Epoch(train) [6][2040/2226] lr: 9.3581e-07 eta: 8:54:45 time: 1.0011 data_time: 0.0103 memory: 70046 grad_norm: 0.0992 loss: 0.0459 recall@thr=0.5: 0.7708 prec@thr=0.5: 0.9583 recall@top3: 0.9583 prec@top3: 0.7500 recall@top5: 1.0000 prec@top5: 0.4750 loss_action_cls: 0.0459 2023/03/11 11:09:30 - mmengine - INFO - Epoch(train) [6][2060/2226] lr: 9.3564e-07 eta: 8:54:36 time: 1.2553 data_time: 0.0089 memory: 70046 grad_norm: 0.0976 loss: 0.0382 recall@thr=0.5: 0.8148 prec@thr=0.5: 0.9259 recall@top3: 0.8889 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0382 2023/03/11 11:09:43 - mmengine - INFO - Epoch(train) [6][2080/2226] lr: 9.3547e-07 eta: 8:53:58 time: 0.6668 data_time: 0.0091 memory: 70046 grad_norm: 0.0968 loss: 0.0421 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8333 recall@top3: 0.7500 prec@top3: 0.4583 recall@top5: 0.8750 prec@top5: 0.3250 loss_action_cls: 0.0421 2023/03/11 11:10:05 - mmengine - INFO - Epoch(train) [6][2100/2226] lr: 9.3529e-07 eta: 8:53:41 time: 1.0982 data_time: 0.0136 memory: 70046 grad_norm: 0.0986 loss: 0.0375 recall@thr=0.5: 0.5000 prec@thr=0.5: 0.6667 recall@top3: 0.8333 prec@top3: 0.5185 recall@top5: 0.8889 prec@top5: 0.3556 loss_action_cls: 0.0375 2023/03/11 11:10:29 - mmengine - INFO - Epoch(train) [6][2120/2226] lr: 9.3512e-07 eta: 8:53:28 time: 1.1691 data_time: 0.0103 memory: 70046 grad_norm: 0.0989 loss: 0.0489 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.7500 recall@top3: 0.8571 prec@top3: 0.5238 recall@top5: 0.8571 prec@top5: 0.3143 loss_action_cls: 0.0489 2023/03/11 11:10:47 - mmengine - INFO - Epoch(train) [6][2140/2226] lr: 9.3494e-07 eta: 8:53:03 time: 0.9273 data_time: 0.0237 memory: 70046 grad_norm: 0.0970 loss: 0.0409 recall@thr=0.5: 0.6354 prec@thr=0.5: 0.7500 recall@top3: 0.7708 prec@top3: 0.6250 recall@top5: 0.8750 prec@top5: 0.4500 loss_action_cls: 0.0409 2023/03/11 11:11:10 - mmengine - INFO - Epoch(train) [6][2160/2226] lr: 9.3476e-07 eta: 8:52:47 time: 1.1336 data_time: 0.0157 memory: 70046 grad_norm: 0.0965 loss: 0.0415 recall@thr=0.5: 0.6431 prec@thr=0.5: 0.8235 recall@top3: 0.7961 prec@top3: 0.7059 recall@top5: 0.9471 prec@top5: 0.5176 loss_action_cls: 0.0415 2023/03/11 11:11:30 - mmengine - INFO - Epoch(train) [6][2180/2226] lr: 9.3458e-07 eta: 8:52:26 time: 0.9990 data_time: 0.0105 memory: 70046 grad_norm: 0.1001 loss: 0.0340 recall@thr=0.5: 0.7333 prec@thr=0.5: 0.8000 recall@top3: 0.8000 prec@top3: 0.6000 recall@top5: 0.8667 prec@top5: 0.4000 loss_action_cls: 0.0340 2023/03/11 11:11:49 - mmengine - INFO - Epoch(train) [6][2200/2226] lr: 9.3440e-07 eta: 8:52:04 time: 0.9863 data_time: 0.0091 memory: 70046 grad_norm: 0.0995 loss: 0.0440 recall@thr=0.5: 0.5938 prec@thr=0.5: 0.6562 recall@top3: 0.8750 prec@top3: 0.6875 recall@top5: 0.9375 prec@top5: 0.4500 loss_action_cls: 0.0440 2023/03/11 11:12:06 - mmengine - INFO - Epoch(train) [6][2220/2226] lr: 9.3422e-07 eta: 8:51:35 time: 0.8496 data_time: 0.0107 memory: 70046 grad_norm: 0.0970 loss: 0.0413 recall@thr=0.5: 0.6000 prec@thr=0.5: 0.8000 recall@top3: 0.7667 prec@top3: 0.7333 recall@top5: 1.0000 prec@top5: 0.5800 loss_action_cls: 0.0413 2023/03/11 11:12:10 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 11:12:10 - mmengine - INFO - Epoch(train) [6][2226/2226] lr: 9.3416e-07 eta: 8:51:23 time: 0.8379 data_time: 0.0086 memory: 70046 grad_norm: 0.1000 loss: 0.0448 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.8333 recall@top3: 0.7500 prec@top3: 0.8333 recall@top5: 0.7917 prec@top5: 0.5333 loss_action_cls: 0.0448 2023/03/11 11:12:10 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/03/11 11:12:27 - mmengine - INFO - Epoch(val) [6][ 20/1571] eta: 0:05:40 time: 0.2198 data_time: 0.1289 memory: 6688 2023/03/11 11:12:30 - mmengine - INFO - Epoch(val) [6][ 40/1571] eta: 0:05:04 time: 0.1774 data_time: 0.0587 memory: 7490 2023/03/11 11:12:34 - mmengine - INFO - Epoch(val) [6][ 60/1571] eta: 0:04:46 time: 0.1715 data_time: 0.0549 memory: 7490 2023/03/11 11:12:37 - mmengine - INFO - Epoch(val) [6][ 80/1571] eta: 0:04:41 time: 0.1860 data_time: 0.0744 memory: 7490 2023/03/11 11:12:41 - mmengine - INFO - Epoch(val) [6][ 100/1571] eta: 0:04:34 time: 0.1793 data_time: 0.0471 memory: 7490 2023/03/11 11:12:44 - mmengine - INFO - Epoch(val) [6][ 120/1571] eta: 0:04:19 time: 0.1403 data_time: 0.0363 memory: 6775 2023/03/11 11:12:47 - mmengine - INFO - Epoch(val) [6][ 140/1571] eta: 0:04:12 time: 0.1628 data_time: 0.0633 memory: 6775 2023/03/11 11:12:50 - mmengine - INFO - Epoch(val) [6][ 160/1571] eta: 0:04:06 time: 0.1616 data_time: 0.0662 memory: 6775 2023/03/11 11:12:54 - mmengine - INFO - Epoch(val) [6][ 180/1571] eta: 0:04:05 time: 0.1922 data_time: 0.0927 memory: 7490 2023/03/11 11:12:58 - mmengine - INFO - Epoch(val) [6][ 200/1571] eta: 0:04:07 time: 0.2119 data_time: 0.0688 memory: 7490 2023/03/11 11:13:02 - mmengine - INFO - Epoch(val) [6][ 220/1571] eta: 0:04:04 time: 0.1892 data_time: 0.0913 memory: 7490 2023/03/11 11:13:05 - mmengine - INFO - Epoch(val) [6][ 240/1571] eta: 0:03:56 time: 0.1362 data_time: 0.0373 memory: 6775 2023/03/11 11:13:08 - mmengine - INFO - Epoch(val) [6][ 260/1571] eta: 0:03:49 time: 0.1482 data_time: 0.0574 memory: 6775 2023/03/11 11:13:10 - mmengine - INFO - Epoch(val) [6][ 280/1571] eta: 0:03:42 time: 0.1324 data_time: 0.0357 memory: 6775 2023/03/11 11:13:14 - mmengine - INFO - Epoch(val) [6][ 300/1571] eta: 0:03:38 time: 0.1724 data_time: 0.0800 memory: 6775 2023/03/11 11:13:18 - mmengine - INFO - Epoch(val) [6][ 320/1571] eta: 0:03:37 time: 0.1945 data_time: 0.0647 memory: 7490 2023/03/11 11:13:22 - mmengine - INFO - Epoch(val) [6][ 340/1571] eta: 0:03:35 time: 0.1936 data_time: 0.0590 memory: 7490 2023/03/11 11:13:25 - mmengine - INFO - Epoch(val) [6][ 360/1571] eta: 0:03:31 time: 0.1794 data_time: 0.0453 memory: 7490 2023/03/11 11:13:29 - mmengine - INFO - Epoch(val) [6][ 380/1571] eta: 0:03:29 time: 0.1869 data_time: 0.0517 memory: 7490 2023/03/11 11:13:33 - mmengine - INFO - Epoch(val) [6][ 400/1571] eta: 0:03:26 time: 0.1942 data_time: 0.0024 memory: 8853 2023/03/11 11:13:36 - mmengine - INFO - Epoch(val) [6][ 420/1571] eta: 0:03:21 time: 0.1551 data_time: 0.0076 memory: 8853 2023/03/11 11:13:39 - mmengine - INFO - Epoch(val) [6][ 440/1571] eta: 0:03:16 time: 0.1407 data_time: 0.0054 memory: 7490 2023/03/11 11:13:43 - mmengine - INFO - Epoch(val) [6][ 460/1571] eta: 0:03:13 time: 0.1885 data_time: 0.0499 memory: 7490 2023/03/11 11:13:47 - mmengine - INFO - Epoch(val) [6][ 480/1571] eta: 0:03:11 time: 0.1972 data_time: 0.0605 memory: 7490 2023/03/11 11:13:50 - mmengine - INFO - Epoch(val) [6][ 500/1571] eta: 0:03:07 time: 0.1747 data_time: 0.0752 memory: 7490 2023/03/11 11:13:53 - mmengine - INFO - Epoch(val) [6][ 520/1571] eta: 0:03:03 time: 0.1613 data_time: 0.0590 memory: 6775 2023/03/11 11:13:57 - mmengine - INFO - Epoch(val) [6][ 540/1571] eta: 0:03:01 time: 0.2014 data_time: 0.1040 memory: 6775 2023/03/11 11:14:00 - mmengine - INFO 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eta: 0:02:00 time: 0.1607 data_time: 0.0571 memory: 6775 2023/03/11 11:14:59 - mmengine - INFO - Epoch(val) [6][ 900/1571] eta: 0:01:57 time: 0.1648 data_time: 0.0585 memory: 7266 2023/03/11 11:15:02 - mmengine - INFO - Epoch(val) [6][ 920/1571] eta: 0:01:53 time: 0.1551 data_time: 0.0256 memory: 7490 2023/03/11 11:15:06 - mmengine - INFO - Epoch(val) [6][ 940/1571] eta: 0:01:50 time: 0.1895 data_time: 0.0483 memory: 7490 2023/03/11 11:15:10 - mmengine - INFO - Epoch(val) [6][ 960/1571] eta: 0:01:46 time: 0.1680 data_time: 0.0302 memory: 7490 2023/03/11 11:15:13 - mmengine - INFO - Epoch(val) [6][ 980/1571] eta: 0:01:43 time: 0.1866 data_time: 0.0504 memory: 7490 2023/03/11 11:15:17 - mmengine - INFO - Epoch(val) [6][1000/1571] eta: 0:01:39 time: 0.1708 data_time: 0.0339 memory: 7490 2023/03/11 11:15:21 - mmengine - INFO - Epoch(val) [6][1020/1571] eta: 0:01:36 time: 0.1943 data_time: 0.0261 memory: 8699 2023/03/11 11:15:24 - mmengine - INFO - Epoch(val) [6][1040/1571] eta: 0:01:32 time: 0.1632 data_time: 0.0020 memory: 8699 2023/03/11 11:15:27 - mmengine - INFO - Epoch(val) [6][1060/1571] eta: 0:01:28 time: 0.1446 data_time: 0.0446 memory: 6775 2023/03/11 11:15:30 - mmengine - INFO - Epoch(val) [6][1080/1571] eta: 0:01:25 time: 0.1581 data_time: 0.0595 memory: 6775 2023/03/11 11:15:34 - mmengine - INFO - Epoch(val) [6][1100/1571] eta: 0:01:21 time: 0.1856 data_time: 0.0561 memory: 7490 2023/03/11 11:15:37 - mmengine - INFO - Epoch(val) [6][1120/1571] eta: 0:01:18 time: 0.1723 data_time: 0.0342 memory: 7610 2023/03/11 11:15:41 - mmengine - INFO - Epoch(val) [6][1140/1571] eta: 0:01:14 time: 0.1762 data_time: 0.0536 memory: 7610 2023/03/11 11:15:44 - mmengine - INFO - Epoch(val) [6][1160/1571] eta: 0:01:11 time: 0.1712 data_time: 0.0635 memory: 7610 2023/03/11 11:15:48 - mmengine - INFO - Epoch(val) [6][1180/1571] eta: 0:01:08 time: 0.1875 data_time: 0.0336 memory: 7610 2023/03/11 11:15:51 - mmengine - INFO - Epoch(val) [6][1200/1571] eta: 0:01:04 time: 0.1623 data_time: 0.0474 memory: 7057 2023/03/11 11:15:55 - mmengine - INFO - Epoch(val) [6][1220/1571] eta: 0:01:01 time: 0.1921 data_time: 0.0560 memory: 7490 2023/03/11 11:15:58 - mmengine - INFO - Epoch(val) [6][1240/1571] eta: 0:00:57 time: 0.1645 data_time: 0.0227 memory: 7490 2023/03/11 11:16:01 - mmengine - INFO - Epoch(val) [6][1260/1571] eta: 0:00:54 time: 0.1617 data_time: 0.0336 memory: 7490 2023/03/11 11:16:05 - mmengine - INFO - Epoch(val) [6][1280/1571] eta: 0:00:50 time: 0.1679 data_time: 0.0667 memory: 6775 2023/03/11 11:16:08 - mmengine - INFO - Epoch(val) [6][1300/1571] eta: 0:00:47 time: 0.1775 data_time: 0.0836 memory: 6775 2023/03/11 11:16:12 - mmengine - INFO - Epoch(val) [6][1320/1571] eta: 0:00:43 time: 0.1580 data_time: 0.0585 memory: 6775 2023/03/11 11:16:16 - mmengine - INFO - Epoch(val) [6][1340/1571] eta: 0:00:40 time: 0.1999 data_time: 0.0921 memory: 6775 2023/03/11 11:16:19 - mmengine - INFO - Epoch(val) [6][1360/1571] eta: 0:00:36 time: 0.1619 data_time: 0.0658 memory: 6775 2023/03/11 11:16:23 - mmengine - INFO - Epoch(val) [6][1380/1571] eta: 0:00:33 time: 0.1879 data_time: 0.0888 memory: 7057 2023/03/11 11:16:26 - mmengine - INFO - Epoch(val) [6][1400/1571] eta: 0:00:29 time: 0.1590 data_time: 0.0486 memory: 7057 2023/03/11 11:16:29 - mmengine - INFO - Epoch(val) [6][1420/1571] eta: 0:00:26 time: 0.1800 data_time: 0.0846 memory: 7057 2023/03/11 11:16:33 - mmengine - INFO - Epoch(val) [6][1440/1571] eta: 0:00:22 time: 0.1608 data_time: 0.0505 memory: 7160 2023/03/11 11:16:36 - mmengine - INFO - Epoch(val) [6][1460/1571] eta: 0:00:19 time: 0.1867 data_time: 0.0675 memory: 7160 2023/03/11 11:16:39 - mmengine - INFO - Epoch(val) [6][1480/1571] eta: 0:00:15 time: 0.1554 data_time: 0.0462 memory: 7057 2023/03/11 11:16:43 - mmengine - INFO - Epoch(val) [6][1500/1571] eta: 0:00:12 time: 0.1723 data_time: 0.0679 memory: 7490 2023/03/11 11:16:45 - mmengine - INFO - Epoch(val) [6][1520/1571] eta: 0:00:08 time: 0.1324 data_time: 0.0019 memory: 7490 2023/03/11 11:16:48 - mmengine - INFO - Epoch(val) [6][1540/1571] eta: 0:00:05 time: 0.1327 data_time: 0.0020 memory: 7490 2023/03/11 11:16:51 - mmengine - INFO - Epoch(val) [6][1560/1571] eta: 0:00:01 time: 0.1322 data_time: 0.0019 memory: 7490 2023/03/11 11:20:41 - mmengine - INFO - Epoch(val) [6][1571/1571] mAP/mAP@0.5IOU: 0.3872 2023/03/11 11:20:41 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/hukai/mmaction2/work_dirs/vit-l_16x4/best_mAP/mAP@0.5IOU_epoch_5.pth is removed 2023/03/11 11:20:46 - mmengine - INFO - The best checkpoint with 0.3872 mAP/mAP@0.5IOU at 6 epoch is saved to best_mAP/mAP@0.5IOU_epoch_6.pth. 2023/03/11 11:21:10 - mmengine - INFO - Epoch(train) [7][ 20/2226] lr: 9.3398e-07 eta: 8:51:12 time: 1.2221 data_time: 0.5720 memory: 70046 grad_norm: 0.0965 loss: 0.0373 recall@thr=0.5: 0.6458 prec@thr=0.5: 0.7500 recall@top3: 0.9167 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0373 2023/03/11 11:21:29 - mmengine - INFO - Epoch(train) [7][ 40/2226] lr: 9.3379e-07 eta: 8:50:47 time: 0.9166 data_time: 0.2718 memory: 70046 grad_norm: 0.1048 loss: 0.0377 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8056 recall@top3: 0.8333 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.4667 loss_action_cls: 0.0377 2023/03/11 11:21:52 - mmengine - INFO - Epoch(train) [7][ 60/2226] lr: 9.3360e-07 eta: 8:50:32 time: 1.1455 data_time: 0.4206 memory: 70046 grad_norm: 0.1004 loss: 0.0413 recall@thr=0.5: 0.2857 prec@thr=0.5: 0.1905 recall@top3: 0.9286 prec@top3: 0.3810 recall@top5: 0.9286 prec@top5: 0.2286 loss_action_cls: 0.0413 2023/03/11 11:22:10 - mmengine - INFO - Epoch(train) [7][ 80/2226] lr: 9.3341e-07 eta: 8:50:06 time: 0.9127 data_time: 0.0131 memory: 70046 grad_norm: 0.1046 loss: 0.0413 recall@thr=0.5: 0.6131 prec@thr=0.5: 0.7500 recall@top3: 0.7048 prec@top3: 0.6905 recall@top5: 0.9821 prec@top5: 0.5714 loss_action_cls: 0.0413 2023/03/11 11:22:32 - mmengine - INFO - Epoch(train) [7][ 100/2226] lr: 9.3322e-07 eta: 8:49:50 time: 1.1115 data_time: 0.2095 memory: 70046 grad_norm: 0.1021 loss: 0.0389 recall@thr=0.5: 0.8000 prec@thr=0.5: 1.0000 recall@top3: 0.9333 prec@top3: 0.7333 recall@top5: 1.0000 prec@top5: 0.4800 loss_action_cls: 0.0389 2023/03/11 11:22:52 - mmengine - INFO - Epoch(train) [7][ 120/2226] lr: 9.3303e-07 eta: 8:49:28 time: 0.9811 data_time: 0.2798 memory: 70046 grad_norm: 0.1026 loss: 0.0422 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.5000 recall@top3: 1.0000 prec@top3: 0.5238 recall@top5: 1.0000 prec@top5: 0.3143 loss_action_cls: 0.0422 2023/03/11 11:23:14 - mmengine - INFO - Epoch(train) [7][ 140/2226] lr: 9.3283e-07 eta: 8:49:10 time: 1.0955 data_time: 0.4382 memory: 70046 grad_norm: 0.1006 loss: 0.0429 recall@thr=0.5: 0.5521 prec@thr=0.5: 0.6250 recall@top3: 0.5521 prec@top3: 0.4167 recall@top5: 0.7188 prec@top5: 0.3000 loss_action_cls: 0.0429 2023/03/11 11:23:33 - mmengine - INFO - Epoch(train) [7][ 160/2226] lr: 9.3263e-07 eta: 8:48:48 time: 0.9732 data_time: 0.3233 memory: 70046 grad_norm: 0.1027 loss: 0.0472 recall@thr=0.5: 0.9333 prec@thr=0.5: 0.8000 recall@top3: 1.0000 prec@top3: 0.4667 recall@top5: 1.0000 prec@top5: 0.2800 loss_action_cls: 0.0472 2023/03/11 11:23:53 - mmengine - INFO - Epoch(train) [7][ 180/2226] lr: 9.3243e-07 eta: 8:48:25 time: 0.9747 data_time: 0.3244 memory: 70046 grad_norm: 0.1023 loss: 0.0377 recall@thr=0.5: 0.5513 prec@thr=0.5: 0.7692 recall@top3: 0.8141 prec@top3: 0.7436 recall@top5: 0.9487 prec@top5: 0.5385 loss_action_cls: 0.0377 2023/03/11 11:24:11 - mmengine - INFO - Epoch(train) [7][ 200/2226] lr: 9.3223e-07 eta: 8:47:59 time: 0.9009 data_time: 0.1562 memory: 70046 grad_norm: 0.1070 loss: 0.0419 recall@thr=0.5: 0.4545 prec@thr=0.5: 0.4545 recall@top3: 0.6818 prec@top3: 0.7576 recall@top5: 0.8712 prec@top5: 0.5818 loss_action_cls: 0.0419 2023/03/11 11:24:32 - mmengine - INFO - Epoch(train) [7][ 220/2226] lr: 9.3203e-07 eta: 8:47:41 time: 1.0815 data_time: 0.3679 memory: 70046 grad_norm: 0.0979 loss: 0.0470 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.9375 recall@top3: 0.9062 prec@top3: 0.8333 recall@top5: 1.0000 prec@top5: 0.5750 loss_action_cls: 0.0470 2023/03/11 11:24:52 - mmengine - INFO - Epoch(train) [7][ 240/2226] lr: 9.3183e-07 eta: 8:47:19 time: 0.9789 data_time: 0.1468 memory: 70046 grad_norm: 0.0998 loss: 0.0407 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.7083 recall@top3: 0.9167 prec@top3: 0.5417 recall@top5: 0.9167 prec@top5: 0.3250 loss_action_cls: 0.0407 2023/03/11 11:25:13 - mmengine - INFO - Epoch(train) [7][ 260/2226] lr: 9.3162e-07 eta: 8:46:59 time: 1.0486 data_time: 0.1444 memory: 70046 grad_norm: 0.1003 loss: 0.0325 recall@thr=0.5: 0.7833 prec@thr=0.5: 0.9500 recall@top3: 1.0000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0325 2023/03/11 11:25:33 - mmengine - INFO - Epoch(train) [7][ 280/2226] lr: 9.3142e-07 eta: 8:46:39 time: 1.0259 data_time: 0.0113 memory: 70046 grad_norm: 0.1046 loss: 0.0363 recall@thr=0.5: 0.7917 prec@thr=0.5: 0.7917 recall@top3: 0.8958 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.3833 loss_action_cls: 0.0363 2023/03/11 11:25:53 - mmengine - INFO - Epoch(train) [7][ 300/2226] lr: 9.3121e-07 eta: 8:46:18 time: 1.0079 data_time: 0.0106 memory: 70046 grad_norm: 0.1015 loss: 0.0407 recall@thr=0.5: 0.8636 prec@thr=0.5: 0.8030 recall@top3: 0.8636 prec@top3: 0.6667 recall@top5: 0.9318 prec@top5: 0.4545 loss_action_cls: 0.0407 2023/03/11 11:26:14 - mmengine - INFO - Epoch(train) [7][ 320/2226] lr: 9.3100e-07 eta: 8:45:57 time: 1.0166 data_time: 0.0122 memory: 70046 grad_norm: 0.1005 loss: 0.0366 recall@thr=0.5: 0.6154 prec@thr=0.5: 0.6731 recall@top3: 0.8333 prec@top3: 0.5385 recall@top5: 0.9487 prec@top5: 0.3846 loss_action_cls: 0.0366 2023/03/11 11:26:34 - mmengine - INFO - Epoch(train) [7][ 340/2226] lr: 9.3079e-07 eta: 8:45:36 time: 1.0159 data_time: 0.0120 memory: 70046 grad_norm: 0.1055 loss: 0.0366 recall@thr=0.5: 0.7121 prec@thr=0.5: 0.8121 recall@top3: 0.8030 prec@top3: 0.6970 recall@top5: 0.9545 prec@top5: 0.5091 loss_action_cls: 0.0366 2023/03/11 11:26:51 - mmengine - INFO - Epoch(train) [7][ 360/2226] lr: 9.3057e-07 eta: 8:45:08 time: 0.8497 data_time: 0.0097 memory: 70046 grad_norm: 0.1030 loss: 0.0419 recall@thr=0.5: 0.7708 prec@thr=0.5: 0.7708 recall@top3: 0.8333 prec@top3: 0.7083 recall@top5: 1.0000 prec@top5: 0.5250 loss_action_cls: 0.0419 2023/03/11 11:27:14 - mmengine - INFO - Epoch(train) [7][ 380/2226] lr: 9.3036e-07 eta: 8:44:52 time: 1.1289 data_time: 0.0106 memory: 70046 grad_norm: 0.1033 loss: 0.0460 recall@thr=0.5: 0.3889 prec@thr=0.5: 0.5000 recall@top3: 0.8611 prec@top3: 0.4444 recall@top5: 0.9167 prec@top5: 0.3000 loss_action_cls: 0.0460 2023/03/11 11:27:33 - mmengine - INFO - Epoch(train) [7][ 400/2226] lr: 9.3014e-07 eta: 8:44:30 time: 0.9732 data_time: 0.0113 memory: 70046 grad_norm: 0.1059 loss: 0.0396 recall@thr=0.5: 0.3333 prec@thr=0.5: 0.4896 recall@top3: 0.8438 prec@top3: 0.6250 recall@top5: 0.9792 prec@top5: 0.4500 loss_action_cls: 0.0396 2023/03/11 11:27:57 - mmengine - INFO - Epoch(train) [7][ 420/2226] lr: 9.2993e-07 eta: 8:44:17 time: 1.1988 data_time: 0.0118 memory: 70046 grad_norm: 0.1021 loss: 0.0329 recall@thr=0.5: 0.7000 prec@thr=0.5: 0.9111 recall@top3: 0.8556 prec@top3: 0.7556 recall@top5: 0.9444 prec@top5: 0.5067 loss_action_cls: 0.0329 2023/03/11 11:28:16 - mmengine - INFO - Epoch(train) [7][ 440/2226] lr: 9.2971e-07 eta: 8:43:52 time: 0.9250 data_time: 0.0086 memory: 70046 grad_norm: 0.1044 loss: 0.0364 recall@thr=0.5: 0.8095 prec@thr=0.5: 0.9524 recall@top3: 0.9524 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.4571 loss_action_cls: 0.0364 2023/03/11 11:28:38 - mmengine - INFO - Epoch(train) [7][ 460/2226] lr: 9.2948e-07 eta: 8:43:35 time: 1.1009 data_time: 0.0086 memory: 70046 grad_norm: 0.1021 loss: 0.0376 recall@thr=0.5: 0.5926 prec@thr=0.5: 0.8519 recall@top3: 0.8333 prec@top3: 0.6296 recall@top5: 0.8333 prec@top5: 0.3778 loss_action_cls: 0.0376 2023/03/11 11:28:56 - mmengine - INFO - Epoch(train) [7][ 480/2226] lr: 9.2926e-07 eta: 8:43:10 time: 0.9216 data_time: 0.0070 memory: 70046 grad_norm: 0.1034 loss: 0.0387 recall@thr=0.5: 0.6439 prec@thr=0.5: 0.8158 recall@top3: 0.8193 prec@top3: 0.5965 recall@top5: 0.8561 prec@top5: 0.3789 loss_action_cls: 0.0387 2023/03/11 11:29:15 - mmengine - INFO - Epoch(train) [7][ 500/2226] lr: 9.2904e-07 eta: 8:42:46 time: 0.9370 data_time: 0.0110 memory: 70046 grad_norm: 0.1038 loss: 0.0412 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.7500 recall@top3: 0.7685 prec@top3: 0.6667 recall@top5: 0.8611 prec@top5: 0.4667 loss_action_cls: 0.0412 2023/03/11 11:29:38 - mmengine - INFO - Epoch(train) [7][ 520/2226] lr: 9.2881e-07 eta: 8:42:31 time: 1.1479 data_time: 0.0107 memory: 70046 grad_norm: 0.1066 loss: 0.0392 recall@thr=0.5: 0.8574 prec@thr=0.5: 0.8981 recall@top3: 0.8944 prec@top3: 0.8333 recall@top5: 0.9611 prec@top5: 0.5556 loss_action_cls: 0.0392 2023/03/11 11:29:55 - mmengine - INFO - Epoch(train) [7][ 540/2226] lr: 9.2858e-07 eta: 8:42:04 time: 0.8862 data_time: 0.0116 memory: 70046 grad_norm: 0.1002 loss: 0.0386 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.7222 recall@top3: 0.7778 prec@top3: 0.5000 recall@top5: 0.8333 prec@top5: 0.3333 loss_action_cls: 0.0386 2023/03/11 11:30:16 - mmengine - INFO - Epoch(train) [7][ 560/2226] lr: 9.2835e-07 eta: 8:41:44 time: 1.0159 data_time: 0.0113 memory: 70046 grad_norm: 0.1022 loss: 0.0328 recall@thr=0.5: 0.9000 prec@thr=0.5: 0.8833 recall@top3: 0.9250 prec@top3: 0.8000 recall@top5: 0.9750 prec@top5: 0.5200 loss_action_cls: 0.0328 2023/03/11 11:30:37 - mmengine - INFO - Epoch(train) [7][ 580/2226] lr: 9.2812e-07 eta: 8:41:25 time: 1.0544 data_time: 0.0123 memory: 70046 grad_norm: 0.1034 loss: 0.0391 recall@thr=0.5: 0.8182 prec@thr=0.5: 0.7576 recall@top3: 1.0000 prec@top3: 0.5758 recall@top5: 1.0000 prec@top5: 0.3455 loss_action_cls: 0.0391 2023/03/11 11:30:55 - mmengine - INFO - Epoch(train) [7][ 600/2226] lr: 9.2789e-07 eta: 8:40:59 time: 0.9087 data_time: 0.0133 memory: 70046 grad_norm: 0.1037 loss: 0.0317 recall@thr=0.5: 0.9630 prec@thr=0.5: 0.8519 recall@top3: 0.9630 prec@top3: 0.8148 recall@top5: 1.0000 prec@top5: 0.5111 loss_action_cls: 0.0317 2023/03/11 11:31:18 - mmengine - INFO - Epoch(train) [7][ 620/2226] lr: 9.2766e-07 eta: 8:40:45 time: 1.1590 data_time: 0.0120 memory: 70046 grad_norm: 0.1039 loss: 0.0388 recall@thr=0.5: 0.4931 prec@thr=0.5: 0.7500 recall@top3: 0.6444 prec@top3: 0.6944 recall@top5: 0.8486 prec@top5: 0.5500 loss_action_cls: 0.0388 2023/03/11 11:31:36 - mmengine - INFO - Epoch(train) [7][ 640/2226] lr: 9.2742e-07 eta: 8:40:18 time: 0.8781 data_time: 0.0102 memory: 70046 grad_norm: 0.1063 loss: 0.0421 recall@thr=0.5: 0.6212 prec@thr=0.5: 0.7273 recall@top3: 0.7879 prec@top3: 0.6970 recall@top5: 0.9242 prec@top5: 0.5091 loss_action_cls: 0.0421 2023/03/11 11:31:41 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 11:31:58 - mmengine - INFO - Epoch(train) [7][ 660/2226] lr: 9.2718e-07 eta: 8:40:01 time: 1.1165 data_time: 0.0113 memory: 70046 grad_norm: 0.1024 loss: 0.0414 recall@thr=0.5: 0.8462 prec@thr=0.5: 0.8974 recall@top3: 0.8974 prec@top3: 0.6923 recall@top5: 0.9487 prec@top5: 0.4462 loss_action_cls: 0.0414 2023/03/11 11:32:18 - mmengine - INFO - Epoch(train) [7][ 680/2226] lr: 9.2694e-07 eta: 8:39:39 time: 0.9874 data_time: 0.0087 memory: 70046 grad_norm: 0.1042 loss: 0.0483 recall@thr=0.5: 0.7051 prec@thr=0.5: 0.8590 recall@top3: 0.8397 prec@top3: 0.8718 recall@top5: 1.0000 prec@top5: 0.6308 loss_action_cls: 0.0483 2023/03/11 11:32:35 - mmengine - INFO - Epoch(train) [7][ 700/2226] lr: 9.2670e-07 eta: 8:39:12 time: 0.8634 data_time: 0.0090 memory: 70046 grad_norm: 0.1025 loss: 0.0397 recall@thr=0.5: 0.8889 prec@thr=0.5: 0.6667 recall@top3: 0.8889 prec@top3: 0.5000 recall@top5: 1.0000 prec@top5: 0.3667 loss_action_cls: 0.0397 2023/03/11 11:32:56 - mmengine - INFO - Epoch(train) [7][ 720/2226] lr: 9.2646e-07 eta: 8:38:53 time: 1.0582 data_time: 0.0091 memory: 70046 grad_norm: 0.1059 loss: 0.0407 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.9167 recall@top3: 0.8125 prec@top3: 0.9167 recall@top5: 0.9375 prec@top5: 0.6500 loss_action_cls: 0.0407 2023/03/11 11:33:16 - mmengine - INFO - Epoch(train) [7][ 740/2226] lr: 9.2622e-07 eta: 8:38:32 time: 0.9999 data_time: 0.0092 memory: 70046 grad_norm: 0.0974 loss: 0.0355 recall@thr=0.5: 0.7692 prec@thr=0.5: 0.8205 recall@top3: 0.8333 prec@top3: 0.8205 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0355 2023/03/11 11:33:36 - mmengine - INFO - Epoch(train) [7][ 760/2226] lr: 9.2597e-07 eta: 8:38:10 time: 1.0019 data_time: 0.0109 memory: 70046 grad_norm: 0.1012 loss: 0.0331 recall@thr=0.5: 0.5556 prec@thr=0.5: 0.5926 recall@top3: 0.6296 prec@top3: 0.4815 recall@top5: 0.8519 prec@top5: 0.4000 loss_action_cls: 0.0331 2023/03/11 11:33:56 - mmengine - INFO - Epoch(train) [7][ 780/2226] lr: 9.2572e-07 eta: 8:37:48 time: 0.9855 data_time: 0.0143 memory: 70046 grad_norm: 0.1046 loss: 0.0473 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.8021 recall@top3: 0.8021 prec@top3: 0.5833 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0473 2023/03/11 11:34:16 - mmengine - INFO - Epoch(train) [7][ 800/2226] lr: 9.2548e-07 eta: 8:37:27 time: 0.9909 data_time: 0.0106 memory: 70046 grad_norm: 0.1045 loss: 0.0367 recall@thr=0.5: 0.7121 prec@thr=0.5: 0.8788 recall@top3: 0.9182 prec@top3: 0.9091 recall@top5: 0.9818 prec@top5: 0.6000 loss_action_cls: 0.0367 2023/03/11 11:34:35 - mmengine - INFO - Epoch(train) [7][ 820/2226] lr: 9.2522e-07 eta: 8:37:03 time: 0.9430 data_time: 0.0088 memory: 70046 grad_norm: 0.1001 loss: 0.0341 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.6875 recall@top3: 0.8750 prec@top3: 0.3333 recall@top5: 1.0000 prec@top5: 0.2500 loss_action_cls: 0.0341 2023/03/11 11:34:54 - mmengine - INFO - Epoch(train) [7][ 840/2226] lr: 9.2497e-07 eta: 8:36:41 time: 0.9822 data_time: 0.0100 memory: 70046 grad_norm: 0.1059 loss: 0.0415 recall@thr=0.5: 0.6818 prec@thr=0.5: 0.8409 recall@top3: 0.8106 prec@top3: 0.7576 recall@top5: 0.9015 prec@top5: 0.5273 loss_action_cls: 0.0415 2023/03/11 11:35:15 - mmengine - INFO - Epoch(train) [7][ 860/2226] lr: 9.2472e-07 eta: 8:36:21 time: 1.0545 data_time: 0.0115 memory: 70046 grad_norm: 0.0998 loss: 0.0394 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.6875 recall@top3: 1.0000 prec@top3: 0.7083 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0394 2023/03/11 11:35:37 - mmengine - INFO - Epoch(train) [7][ 880/2226] lr: 9.2446e-07 eta: 8:36:03 time: 1.0803 data_time: 0.0114 memory: 70046 grad_norm: 0.0999 loss: 0.0407 recall@thr=0.5: 0.8750 prec@thr=0.5: 0.9375 recall@top3: 0.9375 prec@top3: 0.6250 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0407 2023/03/11 11:35:56 - mmengine - INFO - Epoch(train) [7][ 900/2226] lr: 9.2421e-07 eta: 8:35:40 time: 0.9619 data_time: 0.0095 memory: 70046 grad_norm: 0.1022 loss: 0.0372 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7500 recall@top3: 0.9167 prec@top3: 0.5556 recall@top5: 1.0000 prec@top5: 0.3667 loss_action_cls: 0.0372 2023/03/11 11:36:18 - mmengine - INFO - Epoch(train) [7][ 920/2226] lr: 9.2395e-07 eta: 8:35:22 time: 1.0678 data_time: 0.0092 memory: 70046 grad_norm: 0.1049 loss: 0.0416 recall@thr=0.5: 0.9250 prec@thr=0.5: 0.9167 recall@top3: 0.9250 prec@top3: 0.6667 recall@top5: 0.9750 prec@top5: 0.4400 loss_action_cls: 0.0416 2023/03/11 11:36:39 - mmengine - INFO - Epoch(train) [7][ 940/2226] lr: 9.2369e-07 eta: 8:35:03 time: 1.0520 data_time: 0.0099 memory: 70046 grad_norm: 0.1114 loss: 0.0367 recall@thr=0.5: 0.6400 prec@thr=0.5: 0.6333 recall@top3: 0.8067 prec@top3: 0.7667 recall@top5: 0.8933 prec@top5: 0.5200 loss_action_cls: 0.0367 2023/03/11 11:36:58 - mmengine - INFO - Epoch(train) [7][ 960/2226] lr: 9.2343e-07 eta: 8:34:39 time: 0.9524 data_time: 0.0105 memory: 70046 grad_norm: 0.0983 loss: 0.0432 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.9167 recall@top3: 0.9167 prec@top3: 0.7917 recall@top5: 1.0000 prec@top5: 0.5250 loss_action_cls: 0.0432 2023/03/11 11:37:17 - mmengine - INFO - Epoch(train) [7][ 980/2226] lr: 9.2316e-07 eta: 8:34:15 time: 0.9408 data_time: 0.0129 memory: 70046 grad_norm: 0.1053 loss: 0.0419 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.5104 recall@top3: 0.8125 prec@top3: 0.5833 recall@top5: 0.8750 prec@top5: 0.3750 loss_action_cls: 0.0419 2023/03/11 11:37:36 - mmengine - INFO - Epoch(train) [7][1000/2226] lr: 9.2290e-07 eta: 8:33:53 time: 0.9850 data_time: 0.0121 memory: 70046 grad_norm: 0.1064 loss: 0.0343 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 0.7143 prec@top3: 0.5238 recall@top5: 1.0000 prec@top5: 0.3714 loss_action_cls: 0.0343 2023/03/11 11:37:58 - mmengine - INFO - Epoch(train) [7][1020/2226] lr: 9.2263e-07 eta: 8:33:35 time: 1.0756 data_time: 0.0111 memory: 70046 grad_norm: 0.1094 loss: 0.0361 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 1.0000 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0361 2023/03/11 11:38:18 - mmengine - INFO - Epoch(train) [7][1040/2226] lr: 9.2237e-07 eta: 8:33:14 time: 0.9950 data_time: 0.0086 memory: 70046 grad_norm: 0.1000 loss: 0.0390 recall@thr=0.5: 0.7976 prec@thr=0.5: 0.8929 recall@top3: 0.9048 prec@top3: 0.7857 recall@top5: 0.9643 prec@top5: 0.5143 loss_action_cls: 0.0390 2023/03/11 11:38:38 - mmengine - INFO - Epoch(train) [7][1060/2226] lr: 9.2210e-07 eta: 8:32:53 time: 1.0177 data_time: 0.0104 memory: 70046 grad_norm: 0.1032 loss: 0.0299 recall@thr=0.5: 0.7857 prec@thr=0.5: 0.8929 recall@top3: 0.9286 prec@top3: 0.6667 recall@top5: 0.9286 prec@top5: 0.4000 loss_action_cls: 0.0299 2023/03/11 11:38:56 - mmengine - INFO - Epoch(train) [7][1080/2226] lr: 9.2182e-07 eta: 8:32:28 time: 0.9018 data_time: 0.0101 memory: 70046 grad_norm: 0.1022 loss: 0.0410 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8654 recall@top3: 0.8333 prec@top3: 0.6923 recall@top5: 1.0000 prec@top5: 0.5077 loss_action_cls: 0.0410 2023/03/11 11:39:19 - mmengine - INFO - Epoch(train) [7][1100/2226] lr: 9.2155e-07 eta: 8:32:11 time: 1.1262 data_time: 0.0114 memory: 70046 grad_norm: 0.0998 loss: 0.0335 recall@thr=0.5: 0.8000 prec@thr=0.5: 0.9000 recall@top3: 0.9000 prec@top3: 0.8000 recall@top5: 1.0000 prec@top5: 0.5600 loss_action_cls: 0.0335 2023/03/11 11:39:34 - mmengine - INFO - Epoch(train) [7][1120/2226] lr: 9.2128e-07 eta: 8:31:40 time: 0.7621 data_time: 0.0106 memory: 70046 grad_norm: 0.1028 loss: 0.0363 recall@thr=0.5: 0.8500 prec@thr=0.5: 0.9333 recall@top3: 0.9500 prec@top3: 0.5333 recall@top5: 1.0000 prec@top5: 0.3400 loss_action_cls: 0.0363 2023/03/11 11:39:55 - mmengine - INFO - Epoch(train) [7][1140/2226] lr: 9.2100e-07 eta: 8:31:22 time: 1.0727 data_time: 0.0156 memory: 70046 grad_norm: 0.1002 loss: 0.0335 recall@thr=0.5: 0.6944 prec@thr=0.5: 0.7500 recall@top3: 0.7778 prec@top3: 0.4444 recall@top5: 1.0000 prec@top5: 0.3667 loss_action_cls: 0.0335 2023/03/11 11:40:15 - mmengine - INFO - Epoch(train) [7][1160/2226] lr: 9.2072e-07 eta: 8:31:01 time: 1.0033 data_time: 0.0125 memory: 70046 grad_norm: 0.1005 loss: 0.0424 recall@thr=0.5: 0.2879 prec@thr=0.5: 0.4545 recall@top3: 0.6515 prec@top3: 0.4545 recall@top5: 1.0000 prec@top5: 0.4182 loss_action_cls: 0.0424 2023/03/11 11:40:33 - mmengine - INFO - Epoch(train) [7][1180/2226] lr: 9.2045e-07 eta: 8:30:34 time: 0.8793 data_time: 0.0106 memory: 70046 grad_norm: 0.0992 loss: 0.0447 recall@thr=0.5: 0.4615 prec@thr=0.5: 0.5385 recall@top3: 0.6795 prec@top3: 0.5897 recall@top5: 0.7949 prec@top5: 0.4154 loss_action_cls: 0.0447 2023/03/11 11:40:56 - mmengine - INFO - Epoch(train) [7][1200/2226] lr: 9.2016e-07 eta: 8:30:20 time: 1.1686 data_time: 0.0112 memory: 70046 grad_norm: 0.1050 loss: 0.0361 recall@thr=0.5: 0.9444 prec@thr=0.5: 0.8889 recall@top3: 1.0000 prec@top3: 0.7222 recall@top5: 1.0000 prec@top5: 0.4333 loss_action_cls: 0.0361 2023/03/11 11:41:16 - mmengine - INFO - Epoch(train) [7][1220/2226] lr: 9.1988e-07 eta: 8:29:58 time: 0.9957 data_time: 0.0096 memory: 70046 grad_norm: 0.1056 loss: 0.0370 recall@thr=0.5: 0.8167 prec@thr=0.5: 0.8500 recall@top3: 0.7833 prec@top3: 0.8000 recall@top5: 0.9667 prec@top5: 0.6000 loss_action_cls: 0.0370 2023/03/11 11:41:36 - mmengine - INFO - Epoch(train) [7][1240/2226] lr: 9.1960e-07 eta: 8:29:37 time: 0.9996 data_time: 0.0089 memory: 70046 grad_norm: 0.0992 loss: 0.0299 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.8333 recall@top3: 0.9048 prec@top3: 0.7857 recall@top5: 1.0000 prec@top5: 0.5286 loss_action_cls: 0.0299 2023/03/11 11:41:54 - mmengine - INFO - Epoch(train) [7][1260/2226] lr: 9.1931e-07 eta: 8:29:12 time: 0.9037 data_time: 0.0101 memory: 70046 grad_norm: 0.1025 loss: 0.0369 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.8750 recall@top3: 0.9583 prec@top3: 0.6250 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0369 2023/03/11 11:42:14 - mmengine - INFO - Epoch(train) [7][1280/2226] lr: 9.1903e-07 eta: 8:28:50 time: 0.9817 data_time: 0.0117 memory: 70046 grad_norm: 0.0997 loss: 0.0377 recall@thr=0.5: 0.7692 prec@thr=0.5: 0.7436 recall@top3: 0.8718 prec@top3: 0.6923 recall@top5: 0.9359 prec@top5: 0.4462 loss_action_cls: 0.0377 2023/03/11 11:42:35 - mmengine - INFO - Epoch(train) [7][1300/2226] lr: 9.1874e-07 eta: 8:28:30 time: 1.0403 data_time: 0.0127 memory: 70046 grad_norm: 0.1018 loss: 0.0382 recall@thr=0.5: 0.7857 prec@thr=0.5: 0.7500 recall@top3: 0.8571 prec@top3: 0.7619 recall@top5: 1.0000 prec@top5: 0.5714 loss_action_cls: 0.0382 2023/03/11 11:42:56 - mmengine - INFO - Epoch(train) [7][1320/2226] lr: 9.1845e-07 eta: 8:28:10 time: 1.0373 data_time: 0.0135 memory: 70046 grad_norm: 0.1039 loss: 0.0356 recall@thr=0.5: 0.9375 prec@thr=0.5: 0.9583 recall@top3: 0.9688 prec@top3: 0.7083 recall@top5: 1.0000 prec@top5: 0.4500 loss_action_cls: 0.0356 2023/03/11 11:43:19 - mmengine - INFO - Epoch(train) [7][1340/2226] lr: 9.1816e-07 eta: 8:27:57 time: 1.1903 data_time: 0.0124 memory: 70046 grad_norm: 0.1032 loss: 0.0330 recall@thr=0.5: 0.8000 prec@thr=0.5: 0.9000 recall@top3: 1.0000 prec@top3: 0.5667 recall@top5: 1.0000 prec@top5: 0.3400 loss_action_cls: 0.0330 2023/03/11 11:43:36 - mmengine - INFO - Epoch(train) [7][1360/2226] lr: 9.1786e-07 eta: 8:27:29 time: 0.8371 data_time: 0.0087 memory: 70046 grad_norm: 0.0987 loss: 0.0394 recall@thr=0.5: 0.8182 prec@thr=0.5: 0.8182 recall@top3: 0.8636 prec@top3: 0.5758 recall@top5: 0.9545 prec@top5: 0.3818 loss_action_cls: 0.0394 2023/03/11 11:43:58 - mmengine - INFO - Epoch(train) [7][1380/2226] lr: 9.1757e-07 eta: 8:27:12 time: 1.0997 data_time: 0.0127 memory: 70046 grad_norm: 0.0989 loss: 0.0403 recall@thr=0.5: 0.9524 prec@thr=0.5: 0.9524 recall@top3: 0.9524 prec@top3: 0.6190 recall@top5: 0.9524 prec@top5: 0.3714 loss_action_cls: 0.0403 2023/03/11 11:44:18 - mmengine - INFO - Epoch(train) [7][1400/2226] lr: 9.1727e-07 eta: 8:26:50 time: 0.9953 data_time: 0.0089 memory: 70046 grad_norm: 0.1039 loss: 0.0425 recall@thr=0.5: 0.3214 prec@thr=0.5: 0.4286 recall@top3: 0.3571 prec@top3: 0.3810 recall@top5: 0.7143 prec@top5: 0.3429 loss_action_cls: 0.0425 2023/03/11 11:44:37 - mmengine - INFO - Epoch(train) [7][1420/2226] lr: 9.1697e-07 eta: 8:26:27 time: 0.9572 data_time: 0.0084 memory: 70046 grad_norm: 0.0962 loss: 0.0439 recall@thr=0.5: 0.8571 prec@thr=0.5: 0.8571 recall@top3: 1.0000 prec@top3: 0.7143 recall@top5: 1.0000 prec@top5: 0.4286 loss_action_cls: 0.0439 2023/03/11 11:44:57 - mmengine - INFO - Epoch(train) [7][1440/2226] lr: 9.1667e-07 eta: 8:26:05 time: 0.9848 data_time: 0.0104 memory: 70046 grad_norm: 0.1006 loss: 0.0444 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.6250 recall@top3: 0.8438 prec@top3: 0.4583 recall@top5: 0.8854 prec@top5: 0.3000 loss_action_cls: 0.0444 2023/03/11 11:45:17 - mmengine - INFO - Epoch(train) [7][1460/2226] lr: 9.1637e-07 eta: 8:25:43 time: 0.9920 data_time: 0.0094 memory: 70046 grad_norm: 0.1010 loss: 0.0399 recall@thr=0.5: 0.7396 prec@thr=0.5: 0.8021 recall@top3: 0.8333 prec@top3: 0.5417 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0399 2023/03/11 11:45:37 - mmengine - INFO - Epoch(train) [7][1480/2226] lr: 9.1607e-07 eta: 8:25:22 time: 0.9962 data_time: 0.0100 memory: 70046 grad_norm: 0.0990 loss: 0.0429 recall@thr=0.5: 0.7593 prec@thr=0.5: 0.7454 recall@top3: 0.9167 prec@top3: 0.8148 recall@top5: 1.0000 prec@top5: 0.5444 loss_action_cls: 0.0429 2023/03/11 11:45:56 - mmengine - INFO - Epoch(train) [7][1500/2226] lr: 9.1577e-07 eta: 8:25:00 time: 0.9840 data_time: 0.0098 memory: 70046 grad_norm: 0.1012 loss: 0.0345 recall@thr=0.5: 0.7083 prec@thr=0.5: 0.7917 recall@top3: 0.7153 prec@top3: 0.7222 recall@top5: 0.9583 prec@top5: 0.5833 loss_action_cls: 0.0345 2023/03/11 11:46:20 - mmengine - INFO - Epoch(train) [7][1520/2226] lr: 9.1546e-07 eta: 8:24:46 time: 1.1690 data_time: 0.0116 memory: 70046 grad_norm: 0.1008 loss: 0.0333 recall@thr=0.5: 0.7727 prec@thr=0.5: 0.8636 recall@top3: 1.0000 prec@top3: 0.5152 recall@top5: 1.0000 prec@top5: 0.3091 loss_action_cls: 0.0333 2023/03/11 11:46:37 - mmengine - INFO - Epoch(train) [7][1540/2226] lr: 9.1515e-07 eta: 8:24:18 time: 0.8534 data_time: 0.0070 memory: 70046 grad_norm: 0.1002 loss: 0.0340 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7424 recall@top3: 0.9015 prec@top3: 0.5455 recall@top5: 0.9697 prec@top5: 0.3818 loss_action_cls: 0.0340 2023/03/11 11:46:57 - mmengine - INFO - Epoch(train) [7][1560/2226] lr: 9.1484e-07 eta: 8:23:58 time: 1.0272 data_time: 0.0107 memory: 70046 grad_norm: 0.1024 loss: 0.0370 recall@thr=0.5: 0.7051 prec@thr=0.5: 0.6859 recall@top3: 0.8462 prec@top3: 0.6667 recall@top5: 0.8462 prec@top5: 0.4000 loss_action_cls: 0.0370 2023/03/11 11:47:18 - mmengine - INFO - Epoch(train) [7][1580/2226] lr: 9.1453e-07 eta: 8:23:38 time: 1.0167 data_time: 0.0121 memory: 70046 grad_norm: 0.1039 loss: 0.0369 recall@thr=0.5: 0.5705 prec@thr=0.5: 0.7051 recall@top3: 0.7628 prec@top3: 0.4615 recall@top5: 0.8846 prec@top5: 0.3385 loss_action_cls: 0.0369 2023/03/11 11:47:39 - mmengine - INFO - Epoch(train) [7][1600/2226] lr: 9.1422e-07 eta: 8:23:19 time: 1.0720 data_time: 0.0101 memory: 70046 grad_norm: 0.1004 loss: 0.0397 recall@thr=0.5: 0.6429 prec@thr=0.5: 0.7143 recall@top3: 0.7143 prec@top3: 0.5714 recall@top5: 0.8571 prec@top5: 0.3714 loss_action_cls: 0.0397 2023/03/11 11:48:00 - mmengine - INFO - Epoch(train) [7][1620/2226] lr: 9.1391e-07 eta: 8:23:00 time: 1.0527 data_time: 0.0092 memory: 70046 grad_norm: 0.0974 loss: 0.0383 recall@thr=0.5: 0.5238 prec@thr=0.5: 0.8214 recall@top3: 0.6690 prec@top3: 0.5952 recall@top5: 0.8881 prec@top5: 0.4714 loss_action_cls: 0.0383 2023/03/11 11:48:18 - mmengine - INFO - Epoch(train) [7][1640/2226] lr: 9.1359e-07 eta: 8:22:34 time: 0.8931 data_time: 0.0082 memory: 70046 grad_norm: 0.1036 loss: 0.0411 recall@thr=0.5: 0.8273 prec@thr=0.5: 0.9394 recall@top3: 0.7182 prec@top3: 0.6667 recall@top5: 0.9091 prec@top5: 0.5636 loss_action_cls: 0.0411 2023/03/11 11:48:21 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 11:48:38 - mmengine - INFO - Epoch(train) [7][1660/2226] lr: 9.1327e-07 eta: 8:22:13 time: 1.0050 data_time: 0.0095 memory: 70046 grad_norm: 0.0997 loss: 0.0350 recall@thr=0.5: 0.7963 prec@thr=0.5: 0.9444 recall@top3: 0.9630 prec@top3: 0.9259 recall@top5: 0.9630 prec@top5: 0.5556 loss_action_cls: 0.0350 2023/03/11 11:49:00 - mmengine - INFO - Epoch(train) [7][1680/2226] lr: 9.1296e-07 eta: 8:21:55 time: 1.0846 data_time: 0.0109 memory: 70046 grad_norm: 0.0994 loss: 0.0420 recall@thr=0.5: 0.8333 prec@thr=0.5: 0.7500 recall@top3: 0.8542 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.5000 loss_action_cls: 0.0420 2023/03/11 11:49:18 - mmengine - INFO - Epoch(train) [7][1700/2226] lr: 9.1264e-07 eta: 8:21:31 time: 0.9249 data_time: 0.0096 memory: 70046 grad_norm: 0.1005 loss: 0.0414 recall@thr=0.5: 0.6875 prec@thr=0.5: 0.5417 recall@top3: 0.9167 prec@top3: 0.6250 recall@top5: 0.9583 prec@top5: 0.4000 loss_action_cls: 0.0414 2023/03/11 11:49:37 - mmengine - INFO - Epoch(train) [7][1720/2226] lr: 9.1231e-07 eta: 8:21:08 time: 0.9589 data_time: 0.0094 memory: 70046 grad_norm: 0.0961 loss: 0.0391 recall@thr=0.5: 0.8125 prec@thr=0.5: 0.8125 recall@top3: 0.8750 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4250 loss_action_cls: 0.0391 2023/03/11 11:49:57 - mmengine - INFO - Epoch(train) [7][1740/2226] lr: 9.1199e-07 eta: 8:20:47 time: 0.9960 data_time: 0.0094 memory: 70046 grad_norm: 0.1017 loss: 0.0408 recall@thr=0.5: 0.7500 prec@thr=0.5: 0.9167 recall@top3: 0.8056 prec@top3: 0.6944 recall@top5: 0.9583 prec@top5: 0.5000 loss_action_cls: 0.0408 2023/03/11 11:50:17 - mmengine - INFO - Epoch(train) [7][1760/2226] lr: 9.1167e-07 eta: 8:20:24 time: 0.9574 data_time: 0.0103 memory: 70046 grad_norm: 0.0997 loss: 0.0371 recall@thr=0.5: 0.6929 prec@thr=0.5: 0.7381 recall@top3: 0.8964 prec@top3: 0.7143 recall@top5: 0.9571 prec@top5: 0.4857 loss_action_cls: 0.0371 2023/03/11 11:50:34 - mmengine - INFO - Epoch(train) [7][1780/2226] lr: 9.1134e-07 eta: 8:19:58 time: 0.8709 data_time: 0.0103 memory: 70046 grad_norm: 0.0989 loss: 0.0289 recall@thr=0.5: 0.6288 prec@thr=0.5: 0.6818 recall@top3: 0.7652 prec@top3: 0.5152 recall@top5: 0.7955 prec@top5: 0.3273 loss_action_cls: 0.0289 2023/03/11 11:50:57 - mmengine - INFO - Epoch(train) [7][1800/2226] lr: 9.1101e-07 eta: 8:19:43 time: 1.1672 data_time: 0.0133 memory: 70046 grad_norm: 0.1006 loss: 0.0366 recall@thr=0.5: 0.5893 prec@thr=0.5: 0.5357 recall@top3: 0.6845 prec@top3: 0.5238 recall@top5: 0.8690 prec@top5: 0.4143 loss_action_cls: 0.0366 2023/03/11 11:51:15 - mmengine - INFO - Epoch(train) [7][1820/2226] lr: 9.1068e-07 eta: 8:19:17 time: 0.8847 data_time: 0.0086 memory: 70046 grad_norm: 0.1067 loss: 0.0369 recall@thr=0.5: 0.9167 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4000 loss_action_cls: 0.0369 2023/03/11 11:51:36 - mmengine - INFO - Epoch(train) [7][1840/2226] lr: 9.1035e-07 eta: 8:18:58 time: 1.0565 data_time: 0.0089 memory: 70046 grad_norm: 0.0997 loss: 0.0407 recall@thr=0.5: 0.3810 prec@thr=0.5: 0.5714 recall@top3: 0.9286 prec@top3: 0.4762 recall@top5: 1.0000 prec@top5: 0.3143 loss_action_cls: 0.0407 2023/03/11 11:51:53 - mmengine - INFO - Epoch(train) [7][1860/2226] lr: 9.1002e-07 eta: 8:18:32 time: 0.8652 data_time: 0.0101 memory: 70046 grad_norm: 0.1009 loss: 0.0308 recall@thr=0.5: 0.9545 prec@thr=0.5: 1.0000 recall@top3: 0.9545 prec@top3: 0.7879 recall@top5: 1.0000 prec@top5: 0.5091 loss_action_cls: 0.0308 2023/03/11 11:52:15 - mmengine - INFO - Epoch(train) [7][1880/2226] lr: 9.0969e-07 eta: 8:18:13 time: 1.0582 data_time: 0.0096 memory: 70046 grad_norm: 0.1038 loss: 0.0336 recall@thr=0.5: 0.8889 prec@thr=0.5: 0.9259 recall@top3: 0.9444 prec@top3: 0.6296 recall@top5: 1.0000 prec@top5: 0.4222 loss_action_cls: 0.0336 2023/03/11 11:52:33 - mmengine - INFO - Epoch(train) [7][1900/2226] lr: 9.0935e-07 eta: 8:17:49 time: 0.9371 data_time: 0.0095 memory: 70046 grad_norm: 0.0986 loss: 0.0503 recall@thr=0.5: 0.7778 prec@thr=0.5: 0.7778 recall@top3: 0.7778 prec@top3: 0.6111 recall@top5: 0.9444 prec@top5: 0.4667 loss_action_cls: 0.0503 2023/03/11 11:52:55 - mmengine - INFO - Epoch(train) [7][1920/2226] lr: 9.0901e-07 eta: 8:17:32 time: 1.0984 data_time: 0.0104 memory: 70046 grad_norm: 0.0999 loss: 0.0409 recall@thr=0.5: 0.7812 prec@thr=0.5: 0.7917 recall@top3: 0.7500 prec@top3: 0.6667 recall@top5: 0.8854 prec@top5: 0.4750 loss_action_cls: 0.0409 2023/03/11 11:53:14 - mmengine - INFO - Epoch(train) [7][1940/2226] lr: 9.0868e-07 eta: 8:17:09 time: 0.9456 data_time: 0.0112 memory: 70046 grad_norm: 0.0942 loss: 0.0346 recall@thr=0.5: 0.6667 prec@thr=0.5: 0.6111 recall@top3: 0.8889 prec@top3: 0.5926 recall@top5: 0.9630 prec@top5: 0.4000 loss_action_cls: 0.0346 2023/03/11 11:53:36 - mmengine - INFO - Epoch(train) [7][1960/2226] lr: 9.0833e-07 eta: 8:16:51 time: 1.0937 data_time: 0.0130 memory: 70046 grad_norm: 0.1008 loss: 0.0339 recall@thr=0.5: 0.6250 prec@thr=0.5: 0.5833 recall@top3: 0.7500 prec@top3: 0.3750 recall@top5: 0.8750 prec@top5: 0.2500 loss_action_cls: 0.0339 2023/03/11 11:53:55 - mmengine - INFO - Epoch(train) [7][1980/2226] lr: 9.0799e-07 eta: 8:16:29 time: 0.9700 data_time: 0.0111 memory: 70046 grad_norm: 0.1013 loss: 0.0340 recall@thr=0.5: 0.7143 prec@thr=0.5: 0.7143 recall@top3: 0.9286 prec@top3: 0.6190 recall@top5: 0.9286 prec@top5: 0.3714 loss_action_cls: 0.0340 2023/03/11 11:54:19 - mmengine - INFO - Epoch(train) [7][2000/2226] lr: 9.0765e-07 eta: 8:16:13 time: 1.1598 data_time: 0.0118 memory: 70046 grad_norm: 0.1003 loss: 0.0335 recall@thr=0.5: 1.0000 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.6111 recall@top5: 1.0000 prec@top5: 0.3667 loss_action_cls: 0.0335 2023/03/11 11:54:38 - mmengine - INFO - Epoch(train) [7][2020/2226] lr: 9.0731e-07 eta: 8:15:51 time: 0.9759 data_time: 0.0088 memory: 70046 grad_norm: 0.1003 loss: 0.0386 recall@thr=0.5: 0.5370 prec@thr=0.5: 0.6852 recall@top3: 0.6852 prec@top3: 0.5926 recall@top5: 0.8333 prec@top5: 0.4444 loss_action_cls: 0.0386 2023/03/11 11:54:58 - mmengine - INFO - Epoch(train) [7][2040/2226] lr: 9.0696e-07 eta: 8:15:30 time: 0.9850 data_time: 0.0088 memory: 70046 grad_norm: 0.0999 loss: 0.0359 recall@thr=0.5: 0.6611 prec@thr=0.5: 0.7611 recall@top3: 0.7000 prec@top3: 0.4222 recall@top5: 0.7778 prec@top5: 0.3067 loss_action_cls: 0.0359 2023/03/11 11:55:18 - mmengine - INFO - Epoch(train) [7][2060/2226] lr: 9.0661e-07 eta: 8:15:08 time: 1.0032 data_time: 0.0097 memory: 70046 grad_norm: 0.1037 loss: 0.0395 recall@thr=0.5: 0.6538 prec@thr=0.5: 0.7308 recall@top3: 0.9487 prec@top3: 0.6667 recall@top5: 1.0000 prec@top5: 0.4308 loss_action_cls: 0.0395 2023/03/11 11:55:35 - mmengine - INFO - Epoch(train) [7][2080/2226] lr: 9.0626e-07 eta: 8:14:41 time: 0.8455 data_time: 0.0109 memory: 70046 grad_norm: 0.0963 loss: 0.0354 recall@thr=0.5: 0.8000 prec@thr=0.5: 0.6667 recall@top3: 0.9333 prec@top3: 0.6000 recall@top5: 0.9667 prec@top5: 0.3800 loss_action_cls: 0.0354 2023/03/11 11:55:55 - mmengine - INFO - Epoch(train) [7][2100/2226] lr: 9.0591e-07 eta: 8:14:21 time: 1.0090 data_time: 0.0118 memory: 70046 grad_norm: 0.1051 loss: 0.0319 recall@thr=0.5: 1.0000 prec@thr=0.5: 0.9500 recall@top3: 1.0000 prec@top3: 0.6333 recall@top5: 1.0000 prec@top5: 0.3800 loss_action_cls: 0.0319 2023/03/11 11:56:15 - mmengine - INFO - Epoch(train) [7][2120/2226] lr: 9.0556e-07 eta: 8:14:00 time: 1.0192 data_time: 0.0118 memory: 70046 grad_norm: 0.0969 loss: 0.0313 recall@thr=0.5: 1.0000 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 0.3333 recall@top5: 1.0000 prec@top5: 0.2000 loss_action_cls: 0.0313 2023/03/11 11:56:35 - mmengine - INFO - Epoch(train) [7][2140/2226] lr: 9.0520e-07 eta: 8:13:38 time: 0.9681 data_time: 0.0115 memory: 70046 grad_norm: 0.0993 loss: 0.0333 recall@thr=0.5: 0.3519 prec@thr=0.5: 0.5556 recall@top3: 0.7500 prec@top3: 0.6667 recall@top5: 0.9444 prec@top5: 0.4889 loss_action_cls: 0.0333 2023/03/11 11:56:56 - mmengine - INFO - Epoch(train) [7][2160/2226] lr: 9.0485e-07 eta: 8:13:18 time: 1.0387 data_time: 0.0091 memory: 70046 grad_norm: 0.0962 loss: 0.0341 recall@thr=0.5: 0.9394 prec@thr=0.5: 0.9545 recall@top3: 0.9394 prec@top3: 0.7879 recall@top5: 1.0000 prec@top5: 0.5091 loss_action_cls: 0.0341 2023/03/11 11:57:14 - mmengine - INFO - Epoch(train) [7][2180/2226] lr: 9.0449e-07 eta: 8:12:53 time: 0.9055 data_time: 0.0102 memory: 70046 grad_norm: 0.0998 loss: 0.0346 recall@thr=0.5: 0.6818 prec@thr=0.5: 0.6364 recall@top3: 0.8333 prec@top3: 0.7576 recall@top5: 0.9091 prec@top5: 0.4909 loss_action_cls: 0.0346 2023/03/11 11:57:36 - mmengine - INFO - Epoch(train) [7][2200/2226] lr: 9.0413e-07 eta: 8:12:37 time: 1.1230 data_time: 0.0118 memory: 70046 grad_norm: 0.1011 loss: 0.0348 recall@thr=0.5: 0.5185 prec@thr=0.5: 0.6333 recall@top3: 0.6574 prec@top3: 0.6667 recall@top5: 0.7778 prec@top5: 0.4889 loss_action_cls: 0.0348 2023/03/11 11:57:52 - mmengine - INFO - Epoch(train) [7][2220/2226] lr: 9.0377e-07 eta: 8:12:07 time: 0.7719 data_time: 0.0119 memory: 70046 grad_norm: 0.0965 loss: 0.0322 recall@thr=0.5: 0.5500 prec@thr=0.5: 0.5167 recall@top3: 0.8333 prec@top3: 0.4333 recall@top5: 0.8667 prec@top5: 0.2800 loss_action_cls: 0.0322 2023/03/11 11:57:55 - mmengine - INFO - Exp name: vit-l_16x4_20230311_063351 2023/03/11 11:57:55 - mmengine - INFO - Epoch(train) [7][2226/2226] lr: 9.0366e-07 eta: 8:11:57 time: 0.7602 data_time: 0.0077 memory: 70046 grad_norm: 0.0999 loss: 0.0308 recall@thr=0.5: 0.7778 prec@thr=0.5: 1.0000 recall@top3: 1.0000 prec@top3: 1.0000 recall@top5: 1.0000 prec@top5: 0.6000 loss_action_cls: 0.0308 2023/03/11 11:57:55 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/03/11 11:58:10 - mmengine - INFO - Epoch(val) [7][ 20/1571] eta: 0:05:23 time: 0.2085 data_time: 0.1187 memory: 6688 2023/03/11 11:58:14 - mmengine - INFO - Epoch(val) [7][ 40/1571] eta: 0:04:51 time: 0.1726 data_time: 0.0481 memory: 7490 2023/03/11 11:58:17 - mmengine - INFO - Epoch(val) [7][ 60/1571] eta: 0:04:28 time: 0.1530 data_time: 0.0350 memory: 7490 2023/03/11 11:58:20 - mmengine - INFO - Epoch(val) [7][ 80/1571] eta: 0:04:20 time: 0.1642 data_time: 0.0491 memory: 7490 2023/03/11 11:58:24 - mmengine - INFO - Epoch(val) [7][ 100/1571] eta: 0:04:24 time: 0.1996 data_time: 0.0688 memory: 7490 2023/03/11 11:58:27 - mmengine - INFO - Epoch(val) [7][ 120/1571] eta: 0:04:08 time: 0.1316 data_time: 0.0345 memory: 6775 2023/03/11 11:58:30 - mmengine - INFO - Epoch(val) [7][ 140/1571] eta: 0:04:01 time: 0.1498 data_time: 0.0504 memory: 6775 2023/03/11 11:58:33 - mmengine - INFO - Epoch(val) [7][ 160/1571] eta: 0:03:55 time: 0.1533 data_time: 0.0597 memory: 6775 2023/03/11 11:58:37 - mmengine - INFO - Epoch(val) [7][ 180/1571] eta: 0:03:56 time: 0.1965 data_time: 0.0942 memory: 7490 2023/03/11 11:58:41 - mmengine - INFO - Epoch(val) [7][ 200/1571] eta: 0:03:58 time: 0.2079 data_time: 0.0735 memory: 7490 2023/03/11 11:58:45 - mmengine - INFO - Epoch(val) [7][ 220/1571] eta: 0:03:56 time: 0.1847 data_time: 0.0768 memory: 7490 2023/03/11 11:58:48 - mmengine - INFO - Epoch(val) [7][ 240/1571] eta: 0:03:48 time: 0.1411 data_time: 0.0487 memory: 6775 2023/03/11 11:58:51 - mmengine - INFO - Epoch(val) [7][ 260/1571] eta: 0:03:43 time: 0.1530 data_time: 0.0656 memory: 6775 2023/03/11 11:58:53 - mmengine - INFO - Epoch(val) [7][ 280/1571] eta: 0:03:36 time: 0.1356 data_time: 0.0392 memory: 6775 2023/03/11 11:58:56 - mmengine - INFO - Epoch(val) [7][ 300/1571] eta: 0:03:32 time: 0.1546 data_time: 0.0616 memory: 6775 2023/03/11 11:59:00 - mmengine - INFO - Epoch(val) [7][ 320/1571] eta: 0:03:29 time: 0.1785 data_time: 0.0497 memory: 7490 2023/03/11 11:59:04 - mmengine - INFO - Epoch(val) [7][ 340/1571] eta: 0:03:30 time: 0.2250 data_time: 0.0911 memory: 7490 2023/03/11 11:59:08 - mmengine - INFO - Epoch(val) [7][ 360/1571] eta: 0:03:27 time: 0.1761 data_time: 0.0368 memory: 7490 2023/03/11 11:59:11 - mmengine - INFO - Epoch(val) [7][ 380/1571] eta: 0:03:24 time: 0.1735 data_time: 0.0378 memory: 7490 2023/03/11 11:59:16 - mmengine - INFO - Epoch(val) [7][ 400/1571] eta: 0:03:23 time: 0.2081 data_time: 0.0061 memory: 8853 2023/03/11 11:59:19 - mmengine - INFO - Epoch(val) [7][ 420/1571] eta: 0:03:18 time: 0.1544 data_time: 0.0024 memory: 8853 2023/03/11 11:59:22 - mmengine - INFO - Epoch(val) [7][ 440/1571] eta: 0:03:13 time: 0.1432 data_time: 0.0022 memory: 7490 2023/03/11 11:59:25 - mmengine - INFO - Epoch(val) [7][ 460/1571] eta: 0:03:09 time: 0.1605 data_time: 0.0265 memory: 7490 2023/03/11 11:59:29 - mmengine - INFO - Epoch(val) [7][ 480/1571] eta: 0:03:07 time: 0.2059 data_time: 0.0735 memory: 7490 2023/03/11 11:59:32 - mmengine - INFO - Epoch(val) [7][ 500/1571] eta: 0:03:04 time: 0.1700 data_time: 0.0636 memory: 7490 2023/03/11 11:59:36 - mmengine - INFO - Epoch(val) [7][ 520/1571] eta: 0:03:00 time: 0.1680 data_time: 0.0697 memory: 6775 2023/03/11 11:59:39 - mmengine - INFO - Epoch(val) [7][ 540/1571] eta: 0:02:56 time: 0.1659 data_time: 0.0726 memory: 6775 2023/03/11 11:59:42 - mmengine - INFO - Epoch(val) [7][ 560/1571] eta: 0:02:53 time: 0.1734 data_time: 0.0713 memory: 6775 2023/03/11 11:59:45 - mmengine - INFO - Epoch(val) [7][ 580/1571] eta: 0:02:49 time: 0.1482 data_time: 0.0493 memory: 6775 2023/03/11 11:59:48 - mmengine - INFO - Epoch(val) [7][ 600/1571] eta: 0:02:44 time: 0.1276 data_time: 0.0281 memory: 6775 2023/03/11 11:59:51 - mmengine - INFO - Epoch(val) [7][ 620/1571] eta: 0:02:41 time: 0.1691 data_time: 0.0520 memory: 7490 2023/03/11 11:59:55 - mmengine - INFO - Epoch(val) [7][ 640/1571] eta: 0:02:38 time: 0.1929 data_time: 0.0546 memory: 7490 2023/03/11 11:59:59 - mmengine - INFO - Epoch(val) [7][ 660/1571] eta: 0:02:35 time: 0.1891 data_time: 0.0530 memory: 7490 2023/03/11 12:00:03 - mmengine - INFO - Epoch(val) [7][ 680/1571] eta: 0:02:33 time: 0.2059 data_time: 0.0152 memory: 8699 2023/03/11 12:00:07 - mmengine - INFO - Epoch(val) [7][ 700/1571] eta: 0:02:30 time: 0.1865 data_time: 0.0647 memory: 8699 2023/03/11 12:00:11 - mmengine - INFO - Epoch(val) [7][ 720/1571] eta: 0:02:27 time: 0.1926 data_time: 0.0769 memory: 7490 2023/03/11 12:00:14 - mmengine - INFO - Epoch(val) [7][ 740/1571] eta: 0:02:23 time: 0.1863 data_time: 0.0697 memory: 7490 2023/03/11 12:00:18 - mmengine - INFO - Epoch(val) [7][ 760/1571] eta: 0:02:20 time: 0.1602 data_time: 0.0366 memory: 7490 2023/03/11 12:00:21 - mmengine - INFO - Epoch(val) [7][ 780/1571] eta: 0:02:16 time: 0.1785 data_time: 0.0521 memory: 7490 2023/03/11 12:00:24 - mmengine - INFO - Epoch(val) [7][ 800/1571] eta: 0:02:12 time: 0.1532 data_time: 0.0509 memory: 7490 2023/03/11 12:00:28 - mmengine - INFO - Epoch(val) [7][ 820/1571] eta: 0:02:09 time: 0.1888 data_time: 0.0483 memory: 7490 2023/03/11 12:00:32 - mmengine - INFO - Epoch(val) [7][ 840/1571] eta: 0:02:06 time: 0.1739 data_time: 0.0309 memory: 7490 2023/03/11 12:00:35 - mmengine - INFO - Epoch(val) [7][ 860/1571] eta: 0:02:02 time: 0.1669 data_time: 0.0628 memory: 7490