2022/09/16 10:33:22 - 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: 1286756053 GPU 0: 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: 1.9.0+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 v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - 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 -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=1.9.0, 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: 0.10.0+cu111 OpenCV: 4.5.4 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 1 ------------------------------------------------------------ 2022/09/16 10:33:23 - mmengine - INFO - Config: mj_rec_data_root = 'data/rec/Syn90k/' mj_rec_train = dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None) mj_sub_rec_train = dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='subset_train_labels.json', test_mode=False, pipeline=None) st_data_root = 'data/rec/SynthText/' st_rec_train = dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='train_labels.json', test_mode=False, pipeline=None) st_an_rec_train = dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='alphanumeric_train_labels.json', test_mode=False, pipeline=None) st_sub_rec_train = dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='subset_train_labels.json', test_mode=False, pipeline=None) cute80_rec_data_root = 'data/rec/ct80/' cute80_rec_test = dict( type='OCRDataset', data_root='data/rec/ct80/', ann_file='test_labels.json', test_mode=True, pipeline=None) iiit5k_rec_data_root = 'data/rec/IIIT5K/' iiit5k_rec_train = dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='train_labels.json', test_mode=False, pipeline=None) iiit5k_rec_test = dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='test_labels.json', test_mode=True, pipeline=None) svt_rec_data_root = 'data/rec/svt/' svt_rec_test = dict( type='OCRDataset', data_root='data/rec/svt/', ann_file='test_labels.json', test_mode=True, pipeline=None) svtp_rec_data_root = 'data/rec/svtp/' svtp_rec_test = dict( type='OCRDataset', data_root='data/rec/svtp/', ann_file='test_labels.json', test_mode=True, pipeline=None) ic13_rec_data_root = 'data/rec/icdar_2013/' ic13_rec_train = dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='train_labels.json', test_mode=False, pipeline=None) ic13_rec_test = dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='test_labels.json', test_mode=True, pipeline=None) ic15_rec_data_root = 'data/rec/icdar_2015/' ic15_rec_train = dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='train_labels.json', test_mode=False, pipeline=None) ic15_rec_test = dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='test_labels.json', test_mode=True, pipeline=None) default_scope = 'mmocr' env_cfg = dict( cudnn_benchmark=True, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) randomness = dict(seed=None) default_hooks = dict( timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=100), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=1, out_dir='sproject:s3://1.0.0rc0_nrtr_retest'), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffer=dict(type='SyncBuffersHook'), visualization=dict( type='VisualizationHook', interval=1, enable=False, show=False, draw_gt=False, draw_pred=False)) log_level = 'INFO' log_processor = dict(type='LogProcessor', window_size=10, by_epoch=True) load_from = None resume = False val_evaluator = dict( type='MultiDatasetsEvaluator', metrics=[dict(type='WordMetric', mode=['ignore_case_symbol'])], dataset_prefixes=['CUTE80', 'IIIT5K', 'SVT', 'SVTP', 'IC13', 'IC15']) test_evaluator = dict( type='MultiDatasetsEvaluator', metrics=[dict(type='WordMetric', mode=['ignore_case_symbol'])], dataset_prefixes=['CUTE80', 'IIIT5K', 'SVT', 'SVTP', 'IC13', 'IC15']) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='TextRecogLocalVisualizer', name='visualizer', vis_backends=[dict(type='LocalVisBackend')]) optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='Adam', lr=0.0003)) train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=6, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [dict(type='MultiStepLR', milestones=[3, 4], end=6)] file_client_args = dict(backend='disk') dictionary = dict( type='Dictionary', dict_file= 'configs/textrecog/nrtr/../../../dicts/english_digits_symbols.txt', with_padding=True, with_unknown=True, same_start_end=True, with_start=True, with_end=True) model = dict( type='NRTR', backbone=dict(type='NRTRModalityTransform'), encoder=dict(type='NRTREncoder', n_layers=12), decoder=dict( type='NRTRDecoder', module_loss=dict( type='CEModuleLoss', ignore_first_char=True, flatten=True), postprocessor=dict(type='AttentionPostprocessor'), dictionary=dict( type='Dictionary', dict_file= 'configs/textrecog/nrtr/../../../dicts/english_digits_symbols.txt', with_padding=True, with_unknown=True, same_start_end=True, with_start=True, with_end=True), max_seq_len=30), data_preprocessor=dict( type='TextRecogDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375])) train_pipeline = [ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), ignore_empty=True, min_size=2), dict(type='LoadOCRAnnotations', with_text=True), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=4), dict(type='PadToWidth', width=160), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ] test_pipeline = [ dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=16), dict(type='PadToWidth', width=160), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ] train_list = [ dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None), dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='train_labels.json', test_mode=False, pipeline=None) ] test_list = [ dict( type='OCRDataset', data_root='data/rec/ct80/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svt/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svtp/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='test_labels.json', test_mode=True, pipeline=None) ] train_dataset = dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='data/rec/Syn90k/', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None), dict( type='OCRDataset', data_root='data/rec/SynthText/', data_prefix=dict(img_path='synthtext/SynthText_patch_horizontal'), ann_file='train_labels.json', test_mode=False, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), ignore_empty=True, min_size=2), dict(type='LoadOCRAnnotations', with_text=True), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=4), dict(type='PadToWidth', width=160), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ]) test_dataset = dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='data/rec/ct80/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/IIIT5K/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svt/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/svtp/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2013/', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='data/rec/icdar_2015/', ann_file='test_labels.json', test_mode=True, pipeline=None) ], pipeline=[ dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=16), dict(type='PadToWidth', width=160), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ]) train_dataloader = dict( batch_size=384, num_workers=24, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/Syn90k', data_prefix=dict(img_path='mnt/ramdisk/max/90kDICT32px'), ann_file='train_labels.json', test_mode=False, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/SynthText', data_prefix=dict( img_path='synthtext/SynthText_patch_horizontal'), ann_file='train_labels.json', test_mode=False, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel'), ignore_empty=True, min_size=2), dict(type='LoadOCRAnnotations', with_text=True), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=4), dict(type='PadToWidth', width=160), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ])) test_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/ct80', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/IIIT5K', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svt', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svtp', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2013', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2015', ann_file='test_labels.json', test_mode=True, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel')), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=16), dict(type='PadToWidth', width=160), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ])) val_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/ct80', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/IIIT5K', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svt', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/recog/svtp', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2013', ann_file='test_labels.json', test_mode=True, pipeline=None), dict( type='OCRDataset', data_root= 'openmmlab:s3://openmmlab/datasets/ocr/recog/icdar_2015', ann_file='test_labels.json', test_mode=True, pipeline=None) ], pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel')), dict( type='RescaleToHeight', height=32, min_width=32, max_width=160, width_divisor=16), dict(type='PadToWidth', width=160), dict(type='LoadOCRAnnotations', with_text=True), dict( type='PackTextRecogInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'valid_ratio')) ])) launcher = 'slurm' work_dir = './work_dirs/nrtr_modality-transform_6e_st_mj' Name of parameter - Initialization information backbone.conv_1.weight - torch.Size([32, 3, 3, 3]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 backbone.conv_1.bias - torch.Size([32]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 backbone.bn_1.weight - torch.Size([32]): UniformInit: a=0, b=1, bias=0 backbone.bn_1.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of NRTR backbone.conv_2.weight - torch.Size([64, 32, 3, 3]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 backbone.conv_2.bias - torch.Size([64]): KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0 backbone.bn_2.weight - torch.Size([64]): UniformInit: a=0, b=1, bias=0 backbone.bn_2.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of NRTR backbone.linear.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR backbone.linear.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.0.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.1.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.2.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.3.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.4.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.5.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.6.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.7.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.8.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.9.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.10.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_stack.11.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_norm.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR encoder.layer_norm.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.trg_word_emb.weight - torch.Size([93, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.norm3.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.norm3.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.self_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.self_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.self_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.self_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.enc_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.enc_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.enc_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.enc_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.0.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.norm3.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.norm3.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.self_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.self_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.self_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.self_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.enc_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.enc_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.enc_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.enc_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.1.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.norm3.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.norm3.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.self_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.self_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.self_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.self_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.enc_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.enc_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.enc_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.enc_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.2.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.norm3.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.norm3.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.self_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.self_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.self_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.self_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.enc_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.enc_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.enc_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.enc_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.3.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.norm3.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.norm3.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.self_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.self_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.self_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.self_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.enc_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.enc_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.enc_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.enc_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.4.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.norm1.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.norm1.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.norm2.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.norm2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.norm3.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.norm3.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.self_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.self_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.self_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.self_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.enc_attn.linear_q.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.enc_attn.linear_k.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.enc_attn.linear_v.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.enc_attn.fc.weight - torch.Size([512, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.mlp.w_1.weight - torch.Size([256, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.mlp.w_1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.mlp.w_2.weight - torch.Size([512, 256]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_stack.5.mlp.w_2.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_norm.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.layer_norm.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of NRTR decoder.classifier.weight - torch.Size([93, 512]): The value is the same before and after calling `init_weights` of NRTR decoder.classifier.bias - torch.Size([93]): The value is the same before and after calling `init_weights` of NRTR 2022/09/16 10:38:11 - mmengine - INFO - Checkpoints will be saved to sproject:s3://1.0.0rc0_nrtr_retest/nrtr_modality-transform_6e_st_mj by PetrelBackend. 2022/09/16 11:08:40 - mmengine - INFO - Epoch(train) [1][100/42151] lr: 3.0000e-04 eta: 53 days, 12:20:18 time: 0.4169 data_time: 0.2198 memory: 7850 loss_ce: 0.6136 loss: 0.6136 2022/09/16 11:09:13 - mmengine - INFO - Epoch(train) [1][200/42151] lr: 3.0000e-04 eta: 27 days, 5:26:43 time: 0.3149 data_time: 0.1220 memory: 7850 loss_ce: 0.5790 loss: 0.5790 2022/09/16 11:09:46 - mmengine - INFO - Epoch(train) [1][300/42151] lr: 3.0000e-04 eta: 18 days, 11:19:50 time: 0.2825 data_time: 0.0802 memory: 7850 loss_ce: 0.5536 loss: 0.5536 2022/09/16 11:10:21 - mmengine - INFO - Epoch(train) [1][400/42151] lr: 3.0000e-04 eta: 14 days, 2:22:18 time: 0.3489 data_time: 0.1192 memory: 7850 loss_ce: 0.5380 loss: 0.5380 2022/09/16 11:10:54 - mmengine - INFO - Epoch(train) [1][500/42151] lr: 3.0000e-04 eta: 11 days, 11:16:57 time: 0.3150 data_time: 0.1027 memory: 7850 loss_ce: 0.5334 loss: 0.5334 2022/09/16 11:11:28 - mmengine - INFO - Epoch(train) [1][600/42151] lr: 3.0000e-04 eta: 9 days, 17:20:24 time: 0.3138 data_time: 0.1190 memory: 7850 loss_ce: 0.5213 loss: 0.5213 2022/09/16 11:12:02 - mmengine - INFO - Epoch(train) [1][700/42151] lr: 3.0000e-04 eta: 8 days, 11:17:30 time: 0.3145 data_time: 0.0991 memory: 7850 loss_ce: 0.5180 loss: 0.5180 2022/09/16 11:12:36 - mmengine - INFO - Epoch(train) [1][800/42151] lr: 3.0000e-04 eta: 7 days, 12:45:28 time: 0.3326 data_time: 0.1018 memory: 7850 loss_ce: 0.4987 loss: 0.4987 2022/09/16 11:13:09 - mmengine - INFO - Epoch(train) [1][900/42151] lr: 3.0000e-04 eta: 6 days, 19:12:31 time: 0.2950 data_time: 0.1011 memory: 7850 loss_ce: 0.4935 loss: 0.4935 2022/09/16 11:13:44 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:13:44 - mmengine - INFO - Epoch(train) [1][1000/42151] lr: 3.0000e-04 eta: 6 days, 5:15:42 time: 0.3441 data_time: 0.1010 memory: 7850 loss_ce: 0.4870 loss: 0.4870 2022/09/16 11:14:18 - mmengine - INFO - Epoch(train) [1][1100/42151] lr: 3.0000e-04 eta: 5 days, 17:47:47 time: 0.3244 data_time: 0.1126 memory: 7850 loss_ce: 0.4757 loss: 0.4757 2022/09/16 11:14:53 - mmengine - INFO - Epoch(train) [1][1200/42151] lr: 3.0000e-04 eta: 5 days, 8:17:42 time: 0.3235 data_time: 0.1100 memory: 7850 loss_ce: 0.4652 loss: 0.4652 2022/09/16 11:15:27 - mmengine - INFO - Epoch(train) [1][1300/42151] lr: 3.0000e-04 eta: 5 days, 0:12:42 time: 0.3071 data_time: 0.1094 memory: 7850 loss_ce: 0.4529 loss: 0.4529 2022/09/16 11:16:01 - mmengine - INFO - Epoch(train) [1][1400/42151] lr: 3.0000e-04 eta: 4 days, 17:16:28 time: 0.3403 data_time: 0.1234 memory: 7850 loss_ce: 0.4421 loss: 0.4421 2022/09/16 11:16:35 - mmengine - INFO - Epoch(train) [1][1500/42151] lr: 3.0000e-04 eta: 4 days, 11:16:18 time: 0.3509 data_time: 0.1476 memory: 7850 loss_ce: 0.4199 loss: 0.4199 2022/09/16 11:17:09 - mmengine - INFO - Epoch(train) [1][1600/42151] lr: 3.0000e-04 eta: 4 days, 6:00:51 time: 0.3134 data_time: 0.1181 memory: 7850 loss_ce: 0.4023 loss: 0.4023 2022/09/16 11:17:44 - mmengine - INFO - Epoch(train) [1][1700/42151] lr: 3.0000e-04 eta: 4 days, 1:24:14 time: 0.3344 data_time: 0.1373 memory: 7850 loss_ce: 0.3756 loss: 0.3756 2022/09/16 11:18:19 - mmengine - INFO - Epoch(train) [1][1800/42151] lr: 3.0000e-04 eta: 3 days, 21:18:17 time: 0.3196 data_time: 0.1276 memory: 7850 loss_ce: 0.3547 loss: 0.3547 2022/09/16 11:18:53 - mmengine - INFO - Epoch(train) [1][1900/42151] lr: 3.0000e-04 eta: 3 days, 17:36:29 time: 0.2913 data_time: 0.0927 memory: 7850 loss_ce: 0.3322 loss: 0.3322 2022/09/16 11:19:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:19:27 - mmengine - INFO - Epoch(train) [1][2000/42151] lr: 3.0000e-04 eta: 3 days, 14:16:53 time: 0.3168 data_time: 0.0894 memory: 7850 loss_ce: 0.3042 loss: 0.3042 2022/09/16 11:20:02 - mmengine - INFO - Epoch(train) [1][2100/42151] lr: 3.0000e-04 eta: 3 days, 11:18:41 time: 0.3435 data_time: 0.1218 memory: 7850 loss_ce: 0.2822 loss: 0.2822 2022/09/16 11:20:36 - mmengine - INFO - Epoch(train) [1][2200/42151] lr: 3.0000e-04 eta: 3 days, 8:34:31 time: 0.3002 data_time: 0.1093 memory: 7850 loss_ce: 0.2739 loss: 0.2739 2022/09/16 11:21:12 - mmengine - INFO - Epoch(train) [1][2300/42151] lr: 3.0000e-04 eta: 3 days, 6:06:26 time: 0.3526 data_time: 0.1019 memory: 7850 loss_ce: 0.2396 loss: 0.2396 2022/09/16 11:21:45 - mmengine - INFO - Epoch(train) [1][2400/42151] lr: 3.0000e-04 eta: 3 days, 3:48:00 time: 0.3096 data_time: 0.0983 memory: 7850 loss_ce: 0.2299 loss: 0.2299 2022/09/16 11:22:19 - mmengine - INFO - Epoch(train) [1][2500/42151] lr: 3.0000e-04 eta: 3 days, 1:41:16 time: 0.3600 data_time: 0.1604 memory: 7850 loss_ce: 0.2219 loss: 0.2219 2022/09/16 11:22:53 - mmengine - INFO - Epoch(train) [1][2600/42151] lr: 3.0000e-04 eta: 2 days, 23:43:11 time: 0.3050 data_time: 0.1112 memory: 7850 loss_ce: 0.2015 loss: 0.2015 2022/09/16 11:23:28 - mmengine - INFO - Epoch(train) [1][2700/42151] lr: 3.0000e-04 eta: 2 days, 21:56:02 time: 0.3146 data_time: 0.0962 memory: 7850 loss_ce: 0.1902 loss: 0.1902 2022/09/16 11:24:02 - mmengine - INFO - Epoch(train) [1][2800/42151] lr: 3.0000e-04 eta: 2 days, 20:16:22 time: 0.3382 data_time: 0.1403 memory: 7850 loss_ce: 0.1865 loss: 0.1865 2022/09/16 11:24:37 - mmengine - INFO - Epoch(train) [1][2900/42151] lr: 3.0000e-04 eta: 2 days, 18:43:36 time: 0.3413 data_time: 0.1217 memory: 7850 loss_ce: 0.1734 loss: 0.1734 2022/09/16 11:25:11 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:25:11 - mmengine - INFO - Epoch(train) [1][3000/42151] lr: 3.0000e-04 eta: 2 days, 17:15:06 time: 0.3252 data_time: 0.1124 memory: 7850 loss_ce: 0.1661 loss: 0.1661 2022/09/16 11:25:46 - mmengine - INFO - Epoch(train) [1][3100/42151] lr: 3.0000e-04 eta: 2 days, 15:54:24 time: 0.3463 data_time: 0.1534 memory: 7850 loss_ce: 0.1554 loss: 0.1554 2022/09/16 11:26:19 - mmengine - INFO - Epoch(train) [1][3200/42151] lr: 3.0000e-04 eta: 2 days, 14:36:25 time: 0.3077 data_time: 0.1139 memory: 7850 loss_ce: 0.1515 loss: 0.1515 2022/09/16 11:26:55 - mmengine - INFO - Epoch(train) [1][3300/42151] lr: 3.0000e-04 eta: 2 days, 13:26:47 time: 0.3821 data_time: 0.1869 memory: 7850 loss_ce: 0.1438 loss: 0.1438 2022/09/16 11:27:30 - mmengine - INFO - Epoch(train) [1][3400/42151] lr: 3.0000e-04 eta: 2 days, 12:19:03 time: 0.3378 data_time: 0.1289 memory: 7850 loss_ce: 0.1394 loss: 0.1394 2022/09/16 11:28:05 - mmengine - INFO - Epoch(train) [1][3500/42151] lr: 3.0000e-04 eta: 2 days, 11:15:45 time: 0.3193 data_time: 0.1220 memory: 7850 loss_ce: 0.1388 loss: 0.1388 2022/09/16 11:28:40 - mmengine - INFO - Epoch(train) [1][3600/42151] lr: 3.0000e-04 eta: 2 days, 10:15:51 time: 0.3214 data_time: 0.1035 memory: 7850 loss_ce: 0.1267 loss: 0.1267 2022/09/16 11:29:14 - mmengine - INFO - Epoch(train) [1][3700/42151] lr: 3.0000e-04 eta: 2 days, 9:18:20 time: 0.3729 data_time: 0.1675 memory: 7850 loss_ce: 0.1212 loss: 0.1212 2022/09/16 11:29:48 - mmengine - INFO - Epoch(train) [1][3800/42151] lr: 3.0000e-04 eta: 2 days, 8:23:43 time: 0.3584 data_time: 0.1552 memory: 7850 loss_ce: 0.1188 loss: 0.1188 2022/09/16 11:30:23 - mmengine - INFO - Epoch(train) [1][3900/42151] lr: 3.0000e-04 eta: 2 days, 7:32:30 time: 0.3400 data_time: 0.1100 memory: 7850 loss_ce: 0.1173 loss: 0.1173 2022/09/16 11:30:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:30:57 - mmengine - INFO - Epoch(train) [1][4000/42151] lr: 3.0000e-04 eta: 2 days, 6:43:24 time: 0.3296 data_time: 0.1222 memory: 7850 loss_ce: 0.1118 loss: 0.1118 2022/09/16 11:31:32 - mmengine - INFO - Epoch(train) [1][4100/42151] lr: 3.0000e-04 eta: 2 days, 5:57:11 time: 0.3431 data_time: 0.1340 memory: 7850 loss_ce: 0.1076 loss: 0.1076 2022/09/16 11:32:06 - mmengine - INFO - Epoch(train) [1][4200/42151] lr: 3.0000e-04 eta: 2 days, 5:12:47 time: 0.3548 data_time: 0.1238 memory: 7850 loss_ce: 0.1122 loss: 0.1122 2022/09/16 11:32:40 - mmengine - INFO - Epoch(train) [1][4300/42151] lr: 3.0000e-04 eta: 2 days, 4:29:52 time: 0.3536 data_time: 0.1596 memory: 7850 loss_ce: 0.1077 loss: 0.1077 2022/09/16 11:33:13 - mmengine - INFO - Epoch(train) [1][4400/42151] lr: 3.0000e-04 eta: 2 days, 3:48:27 time: 0.3197 data_time: 0.1281 memory: 7850 loss_ce: 0.1031 loss: 0.1031 2022/09/16 11:33:47 - mmengine - INFO - Epoch(train) [1][4500/42151] lr: 3.0000e-04 eta: 2 days, 3:08:55 time: 0.3032 data_time: 0.0945 memory: 7850 loss_ce: 0.1027 loss: 0.1027 2022/09/16 11:34:19 - mmengine - INFO - Epoch(train) [1][4600/42151] lr: 3.0000e-04 eta: 2 days, 2:30:26 time: 0.3013 data_time: 0.1072 memory: 7850 loss_ce: 0.1083 loss: 0.1083 2022/09/16 11:34:54 - mmengine - INFO - Epoch(train) [1][4700/42151] lr: 3.0000e-04 eta: 2 days, 1:55:21 time: 0.3666 data_time: 0.1505 memory: 7850 loss_ce: 0.0995 loss: 0.0995 2022/09/16 11:35:28 - mmengine - INFO - Epoch(train) [1][4800/42151] lr: 3.0000e-04 eta: 2 days, 1:21:06 time: 0.3273 data_time: 0.1154 memory: 7850 loss_ce: 0.0896 loss: 0.0896 2022/09/16 11:36:02 - mmengine - INFO - Epoch(train) [1][4900/42151] lr: 3.0000e-04 eta: 2 days, 0:48:04 time: 0.3324 data_time: 0.1232 memory: 7850 loss_ce: 0.0953 loss: 0.0953 2022/09/16 11:36:36 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:36:36 - mmengine - INFO - Epoch(train) [1][5000/42151] lr: 3.0000e-04 eta: 2 days, 0:16:18 time: 0.3361 data_time: 0.1392 memory: 7850 loss_ce: 0.0926 loss: 0.0926 2022/09/16 11:37:11 - mmengine - INFO - Epoch(train) [1][5100/42151] lr: 3.0000e-04 eta: 1 day, 23:46:46 time: 0.3353 data_time: 0.1159 memory: 7850 loss_ce: 0.0968 loss: 0.0968 2022/09/16 11:37:45 - mmengine - INFO - Epoch(train) [1][5200/42151] lr: 3.0000e-04 eta: 1 day, 23:17:32 time: 0.3020 data_time: 0.1092 memory: 7850 loss_ce: 0.0891 loss: 0.0891 2022/09/16 11:38:20 - mmengine - INFO - Epoch(train) [1][5300/42151] lr: 3.0000e-04 eta: 1 day, 22:49:58 time: 0.3152 data_time: 0.1219 memory: 7850 loss_ce: 0.0897 loss: 0.0897 2022/09/16 11:38:55 - mmengine - INFO - Epoch(train) [1][5400/42151] lr: 3.0000e-04 eta: 1 day, 22:23:24 time: 0.3855 data_time: 0.1148 memory: 7850 loss_ce: 0.0915 loss: 0.0915 2022/09/16 11:39:28 - mmengine - INFO - Epoch(train) [1][5500/42151] lr: 3.0000e-04 eta: 1 day, 21:56:46 time: 0.3441 data_time: 0.1455 memory: 7850 loss_ce: 0.0895 loss: 0.0895 2022/09/16 11:40:01 - mmengine - INFO - Epoch(train) [1][5600/42151] lr: 3.0000e-04 eta: 1 day, 21:30:57 time: 0.3137 data_time: 0.1165 memory: 7850 loss_ce: 0.0803 loss: 0.0803 2022/09/16 11:40:37 - mmengine - INFO - Epoch(train) [1][5700/42151] lr: 3.0000e-04 eta: 1 day, 21:07:43 time: 0.5352 data_time: 0.2828 memory: 7850 loss_ce: 0.0877 loss: 0.0877 2022/09/16 11:41:11 - mmengine - INFO - Epoch(train) [1][5800/42151] lr: 3.0000e-04 eta: 1 day, 20:44:27 time: 0.3808 data_time: 0.1657 memory: 7850 loss_ce: 0.0872 loss: 0.0872 2022/09/16 11:41:46 - mmengine - INFO - Epoch(train) [1][5900/42151] lr: 3.0000e-04 eta: 1 day, 20:21:49 time: 0.4216 data_time: 0.2259 memory: 7850 loss_ce: 0.0828 loss: 0.0828 2022/09/16 11:42:19 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:42:19 - mmengine - INFO - Epoch(train) [1][6000/42151] lr: 3.0000e-04 eta: 1 day, 19:59:00 time: 0.3095 data_time: 0.1138 memory: 7850 loss_ce: 0.0829 loss: 0.0829 2022/09/16 11:42:54 - mmengine - INFO - Epoch(train) [1][6100/42151] lr: 3.0000e-04 eta: 1 day, 19:38:09 time: 0.3414 data_time: 0.1458 memory: 7850 loss_ce: 0.0811 loss: 0.0811 2022/09/16 11:43:28 - mmengine - INFO - Epoch(train) [1][6200/42151] lr: 3.0000e-04 eta: 1 day, 19:17:48 time: 0.3926 data_time: 0.1732 memory: 7850 loss_ce: 0.0803 loss: 0.0803 2022/09/16 11:44:01 - mmengine - INFO - Epoch(train) [1][6300/42151] lr: 3.0000e-04 eta: 1 day, 18:57:14 time: 0.3136 data_time: 0.1183 memory: 7850 loss_ce: 0.0801 loss: 0.0801 2022/09/16 11:44:36 - mmengine - INFO - Epoch(train) [1][6400/42151] lr: 3.0000e-04 eta: 1 day, 18:38:12 time: 0.3292 data_time: 0.1114 memory: 7850 loss_ce: 0.0753 loss: 0.0753 2022/09/16 11:45:19 - mmengine - INFO - Epoch(train) [1][6500/42151] lr: 3.0000e-04 eta: 1 day, 18:24:45 time: 0.6977 data_time: 0.1238 memory: 7850 loss_ce: 0.0756 loss: 0.0756 2022/09/16 11:45:53 - mmengine - INFO - Epoch(train) [1][6600/42151] lr: 3.0000e-04 eta: 1 day, 18:06:47 time: 0.3668 data_time: 0.1099 memory: 7850 loss_ce: 0.0799 loss: 0.0799 2022/09/16 11:46:27 - mmengine - INFO - Epoch(train) [1][6700/42151] lr: 3.0000e-04 eta: 1 day, 17:48:31 time: 0.3146 data_time: 0.1183 memory: 7850 loss_ce: 0.0794 loss: 0.0794 2022/09/16 11:47:02 - mmengine - INFO - Epoch(train) [1][6800/42151] lr: 3.0000e-04 eta: 1 day, 17:32:07 time: 0.4101 data_time: 0.1560 memory: 7850 loss_ce: 0.0749 loss: 0.0749 2022/09/16 11:47:37 - mmengine - INFO - Epoch(train) [1][6900/42151] lr: 3.0000e-04 eta: 1 day, 17:15:40 time: 0.3137 data_time: 0.0940 memory: 7850 loss_ce: 0.0702 loss: 0.0702 2022/09/16 11:48:13 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:48:13 - mmengine - INFO - Epoch(train) [1][7000/42151] lr: 3.0000e-04 eta: 1 day, 17:00:12 time: 0.3412 data_time: 0.1394 memory: 7850 loss_ce: 0.0720 loss: 0.0720 2022/09/16 11:48:47 - mmengine - INFO - Epoch(train) [1][7100/42151] lr: 3.0000e-04 eta: 1 day, 16:44:13 time: 0.3187 data_time: 0.1022 memory: 7850 loss_ce: 0.0735 loss: 0.0735 2022/09/16 11:49:21 - mmengine - INFO - Epoch(train) [1][7200/42151] lr: 3.0000e-04 eta: 1 day, 16:28:41 time: 0.2956 data_time: 0.1006 memory: 7850 loss_ce: 0.0757 loss: 0.0757 2022/09/16 11:49:56 - mmengine - INFO - Epoch(train) [1][7300/42151] lr: 3.0000e-04 eta: 1 day, 16:13:55 time: 0.3219 data_time: 0.1176 memory: 7850 loss_ce: 0.0757 loss: 0.0757 2022/09/16 11:50:31 - mmengine - INFO - Epoch(train) [1][7400/42151] lr: 3.0000e-04 eta: 1 day, 15:59:46 time: 0.4238 data_time: 0.1753 memory: 7850 loss_ce: 0.0697 loss: 0.0697 2022/09/16 11:51:06 - mmengine - INFO - Epoch(train) [1][7500/42151] lr: 3.0000e-04 eta: 1 day, 15:45:51 time: 0.3303 data_time: 0.1100 memory: 7850 loss_ce: 0.0755 loss: 0.0755 2022/09/16 11:51:41 - mmengine - INFO - Epoch(train) [1][7600/42151] lr: 3.0000e-04 eta: 1 day, 15:32:08 time: 0.3203 data_time: 0.1246 memory: 7850 loss_ce: 0.0682 loss: 0.0682 2022/09/16 11:52:16 - mmengine - INFO - Epoch(train) [1][7700/42151] lr: 3.0000e-04 eta: 1 day, 15:19:00 time: 0.3357 data_time: 0.1031 memory: 7850 loss_ce: 0.0676 loss: 0.0676 2022/09/16 11:52:50 - mmengine - INFO - Epoch(train) [1][7800/42151] lr: 3.0000e-04 eta: 1 day, 15:05:48 time: 0.3192 data_time: 0.1240 memory: 7850 loss_ce: 0.0678 loss: 0.0678 2022/09/16 11:53:25 - mmengine - INFO - Epoch(train) [1][7900/42151] lr: 3.0000e-04 eta: 1 day, 14:53:22 time: 0.3395 data_time: 0.1236 memory: 7850 loss_ce: 0.0722 loss: 0.0722 2022/09/16 11:54:07 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 11:54:07 - mmengine - INFO - Epoch(train) [1][8000/42151] lr: 3.0000e-04 eta: 1 day, 14:44:22 time: 0.3823 data_time: 0.0988 memory: 7850 loss_ce: 0.0732 loss: 0.0732 2022/09/16 11:54:43 - mmengine - INFO - Epoch(train) [1][8100/42151] lr: 3.0000e-04 eta: 1 day, 14:33:08 time: 0.3399 data_time: 0.1149 memory: 7850 loss_ce: 0.0668 loss: 0.0668 2022/09/16 11:55:20 - mmengine - INFO - Epoch(train) [1][8200/42151] lr: 3.0000e-04 eta: 1 day, 14:22:24 time: 0.3702 data_time: 0.1429 memory: 7850 loss_ce: 0.0711 loss: 0.0711 2022/09/16 11:55:56 - mmengine - INFO - Epoch(train) [1][8300/42151] lr: 3.0000e-04 eta: 1 day, 14:11:13 time: 0.3325 data_time: 0.1263 memory: 7850 loss_ce: 0.0677 loss: 0.0677 2022/09/16 11:56:31 - mmengine - INFO - Epoch(train) [1][8400/42151] lr: 3.0000e-04 eta: 1 day, 14:00:05 time: 0.3815 data_time: 0.1876 memory: 7850 loss_ce: 0.0638 loss: 0.0638 2022/09/16 11:57:07 - mmengine - INFO - Epoch(train) [1][8500/42151] lr: 3.0000e-04 eta: 1 day, 13:49:38 time: 0.3867 data_time: 0.1909 memory: 7850 loss_ce: 0.0648 loss: 0.0648 2022/09/16 11:57:44 - mmengine - INFO - Epoch(train) [1][8600/42151] lr: 3.0000e-04 eta: 1 day, 13:39:43 time: 0.3788 data_time: 0.1545 memory: 7850 loss_ce: 0.0725 loss: 0.0725 2022/09/16 11:58:20 - mmengine - INFO - Epoch(train) [1][8700/42151] lr: 3.0000e-04 eta: 1 day, 13:29:49 time: 0.3198 data_time: 0.1019 memory: 7850 loss_ce: 0.0632 loss: 0.0632 2022/09/16 11:59:01 - mmengine - INFO - Epoch(train) [1][8800/42151] lr: 3.0000e-04 eta: 1 day, 13:22:01 time: 0.3230 data_time: 0.1255 memory: 7850 loss_ce: 0.0677 loss: 0.0677 2022/09/16 11:59:37 - mmengine - INFO - Epoch(train) [1][8900/42151] lr: 3.0000e-04 eta: 1 day, 13:12:42 time: 0.3804 data_time: 0.1583 memory: 7850 loss_ce: 0.0659 loss: 0.0659 2022/09/16 12:00:17 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:00:17 - mmengine - INFO - Epoch(train) [1][9000/42151] lr: 3.0000e-04 eta: 1 day, 13:04:52 time: 0.3494 data_time: 0.1255 memory: 7850 loss_ce: 0.0622 loss: 0.0622 2022/09/16 12:00:52 - mmengine - INFO - Epoch(train) [1][9100/42151] lr: 3.0000e-04 eta: 1 day, 12:55:00 time: 0.3187 data_time: 0.1167 memory: 7850 loss_ce: 0.0626 loss: 0.0626 2022/09/16 12:01:26 - mmengine - INFO - Epoch(train) [1][9200/42151] lr: 3.0000e-04 eta: 1 day, 12:45:25 time: 0.3180 data_time: 0.1224 memory: 7850 loss_ce: 0.0616 loss: 0.0616 2022/09/16 12:02:02 - mmengine - INFO - Epoch(train) [1][9300/42151] lr: 3.0000e-04 eta: 1 day, 12:36:31 time: 0.3510 data_time: 0.1559 memory: 7850 loss_ce: 0.0630 loss: 0.0630 2022/09/16 12:02:39 - mmengine - INFO - Epoch(train) [1][9400/42151] lr: 3.0000e-04 eta: 1 day, 12:27:53 time: 0.4242 data_time: 0.1833 memory: 7850 loss_ce: 0.0617 loss: 0.0617 2022/09/16 12:03:17 - mmengine - INFO - Epoch(train) [1][9500/42151] lr: 3.0000e-04 eta: 1 day, 12:20:26 time: 0.4584 data_time: 0.1864 memory: 7850 loss_ce: 0.0649 loss: 0.0649 2022/09/16 12:03:52 - mmengine - INFO - Epoch(train) [1][9600/42151] lr: 3.0000e-04 eta: 1 day, 12:11:31 time: 0.3329 data_time: 0.0900 memory: 7850 loss_ce: 0.0618 loss: 0.0618 2022/09/16 12:04:27 - mmengine - INFO - Epoch(train) [1][9700/42151] lr: 3.0000e-04 eta: 1 day, 12:03:03 time: 0.4436 data_time: 0.1433 memory: 7850 loss_ce: 0.0626 loss: 0.0626 2022/09/16 12:05:02 - mmengine - INFO - Epoch(train) [1][9800/42151] lr: 3.0000e-04 eta: 1 day, 11:54:29 time: 0.3711 data_time: 0.1581 memory: 7850 loss_ce: 0.0623 loss: 0.0623 2022/09/16 12:05:38 - mmengine - INFO - Epoch(train) [1][9900/42151] lr: 3.0000e-04 eta: 1 day, 11:46:21 time: 0.3811 data_time: 0.1395 memory: 7850 loss_ce: 0.0600 loss: 0.0600 2022/09/16 12:06:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:06:12 - mmengine - INFO - Epoch(train) [1][10000/42151] lr: 3.0000e-04 eta: 1 day, 11:37:52 time: 0.3060 data_time: 0.1119 memory: 7850 loss_ce: 0.0604 loss: 0.0604 2022/09/16 12:06:48 - mmengine - INFO - Epoch(train) [1][10100/42151] lr: 3.0000e-04 eta: 1 day, 11:30:14 time: 0.5315 data_time: 0.0857 memory: 7850 loss_ce: 0.0630 loss: 0.0630 2022/09/16 12:07:28 - mmengine - INFO - Epoch(train) [1][10200/42151] lr: 3.0000e-04 eta: 1 day, 11:24:14 time: 0.3481 data_time: 0.1529 memory: 7850 loss_ce: 0.0612 loss: 0.0612 2022/09/16 12:08:01 - mmengine - INFO - Epoch(train) [1][10300/42151] lr: 3.0000e-04 eta: 1 day, 11:15:50 time: 0.2931 data_time: 0.0703 memory: 7850 loss_ce: 0.0623 loss: 0.0623 2022/09/16 12:08:36 - mmengine - INFO - Epoch(train) [1][10400/42151] lr: 3.0000e-04 eta: 1 day, 11:08:09 time: 0.4266 data_time: 0.1825 memory: 7850 loss_ce: 0.0546 loss: 0.0546 2022/09/16 12:09:10 - mmengine - INFO - Epoch(train) [1][10500/42151] lr: 3.0000e-04 eta: 1 day, 11:00:22 time: 0.3823 data_time: 0.1872 memory: 7850 loss_ce: 0.0606 loss: 0.0606 2022/09/16 12:09:44 - mmengine - INFO - Epoch(train) [1][10600/42151] lr: 3.0000e-04 eta: 1 day, 10:52:35 time: 0.3288 data_time: 0.0992 memory: 7850 loss_ce: 0.0540 loss: 0.0540 2022/09/16 12:10:18 - mmengine - INFO - Epoch(train) [1][10700/42151] lr: 3.0000e-04 eta: 1 day, 10:45:13 time: 0.3191 data_time: 0.0892 memory: 7850 loss_ce: 0.0583 loss: 0.0583 2022/09/16 12:10:52 - mmengine - INFO - Epoch(train) [1][10800/42151] lr: 3.0000e-04 eta: 1 day, 10:37:43 time: 0.3119 data_time: 0.1197 memory: 7850 loss_ce: 0.0569 loss: 0.0569 2022/09/16 12:11:27 - mmengine - INFO - Epoch(train) [1][10900/42151] lr: 3.0000e-04 eta: 1 day, 10:30:32 time: 0.3642 data_time: 0.1470 memory: 7850 loss_ce: 0.0591 loss: 0.0591 2022/09/16 12:12:01 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:12:01 - mmengine - INFO - Epoch(train) [1][11000/42151] lr: 3.0000e-04 eta: 1 day, 10:23:23 time: 0.3426 data_time: 0.1499 memory: 7850 loss_ce: 0.0591 loss: 0.0591 2022/09/16 12:12:35 - mmengine - INFO - Epoch(train) [1][11100/42151] lr: 3.0000e-04 eta: 1 day, 10:16:22 time: 0.3490 data_time: 0.1544 memory: 7850 loss_ce: 0.0560 loss: 0.0560 2022/09/16 12:13:09 - mmengine - INFO - Epoch(train) [1][11200/42151] lr: 3.0000e-04 eta: 1 day, 10:09:30 time: 0.3248 data_time: 0.1301 memory: 7850 loss_ce: 0.0606 loss: 0.0606 2022/09/16 12:13:44 - mmengine - INFO - Epoch(train) [1][11300/42151] lr: 3.0000e-04 eta: 1 day, 10:03:03 time: 0.3298 data_time: 0.1166 memory: 7850 loss_ce: 0.0542 loss: 0.0542 2022/09/16 12:14:19 - mmengine - INFO - Epoch(train) [1][11400/42151] lr: 3.0000e-04 eta: 1 day, 9:56:21 time: 0.3316 data_time: 0.1164 memory: 7850 loss_ce: 0.0556 loss: 0.0556 2022/09/16 12:14:52 - mmengine - INFO - Epoch(train) [1][11500/42151] lr: 3.0000e-04 eta: 1 day, 9:49:27 time: 0.3294 data_time: 0.1370 memory: 7850 loss_ce: 0.0566 loss: 0.0566 2022/09/16 12:15:26 - mmengine - INFO - Epoch(train) [1][11600/42151] lr: 3.0000e-04 eta: 1 day, 9:42:51 time: 0.3823 data_time: 0.1876 memory: 7850 loss_ce: 0.0561 loss: 0.0561 2022/09/16 12:15:59 - mmengine - INFO - Epoch(train) [1][11700/42151] lr: 3.0000e-04 eta: 1 day, 9:36:10 time: 0.3216 data_time: 0.1272 memory: 7850 loss_ce: 0.0543 loss: 0.0543 2022/09/16 12:16:34 - mmengine - INFO - Epoch(train) [1][11800/42151] lr: 3.0000e-04 eta: 1 day, 9:30:12 time: 0.3273 data_time: 0.1299 memory: 7850 loss_ce: 0.0593 loss: 0.0593 2022/09/16 12:17:08 - mmengine - INFO - Epoch(train) [1][11900/42151] lr: 3.0000e-04 eta: 1 day, 9:24:00 time: 0.3346 data_time: 0.1402 memory: 7850 loss_ce: 0.0577 loss: 0.0577 2022/09/16 12:17:42 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:17:42 - mmengine - INFO - Epoch(train) [1][12000/42151] lr: 3.0000e-04 eta: 1 day, 9:17:56 time: 0.3151 data_time: 0.1222 memory: 7850 loss_ce: 0.0559 loss: 0.0559 2022/09/16 12:18:17 - mmengine - INFO - Epoch(train) [1][12100/42151] lr: 3.0000e-04 eta: 1 day, 9:11:56 time: 0.3362 data_time: 0.1428 memory: 7850 loss_ce: 0.0541 loss: 0.0541 2022/09/16 12:18:52 - mmengine - INFO - Epoch(train) [1][12200/42151] lr: 3.0000e-04 eta: 1 day, 9:06:20 time: 0.3696 data_time: 0.1781 memory: 7850 loss_ce: 0.0580 loss: 0.0580 2022/09/16 12:19:27 - mmengine - INFO - Epoch(train) [1][12300/42151] lr: 3.0000e-04 eta: 1 day, 9:00:44 time: 0.3752 data_time: 0.1284 memory: 7850 loss_ce: 0.0550 loss: 0.0550 2022/09/16 12:20:00 - mmengine - INFO - Epoch(train) [1][12400/42151] lr: 3.0000e-04 eta: 1 day, 8:54:50 time: 0.3383 data_time: 0.1102 memory: 7850 loss_ce: 0.0535 loss: 0.0535 2022/09/16 12:20:35 - mmengine - INFO - Epoch(train) [1][12500/42151] lr: 3.0000e-04 eta: 1 day, 8:49:20 time: 0.3109 data_time: 0.1192 memory: 7850 loss_ce: 0.0510 loss: 0.0510 2022/09/16 12:21:10 - mmengine - INFO - Epoch(train) [1][12600/42151] lr: 3.0000e-04 eta: 1 day, 8:44:00 time: 0.4141 data_time: 0.1724 memory: 7850 loss_ce: 0.0544 loss: 0.0544 2022/09/16 12:21:44 - mmengine - INFO - Epoch(train) [1][12700/42151] lr: 3.0000e-04 eta: 1 day, 8:38:18 time: 0.3310 data_time: 0.1400 memory: 7850 loss_ce: 0.0545 loss: 0.0545 2022/09/16 12:22:19 - mmengine - INFO - Epoch(train) [1][12800/42151] lr: 3.0000e-04 eta: 1 day, 8:33:09 time: 0.4111 data_time: 0.2132 memory: 7850 loss_ce: 0.0554 loss: 0.0554 2022/09/16 12:22:53 - mmengine - INFO - Epoch(train) [1][12900/42151] lr: 3.0000e-04 eta: 1 day, 8:27:50 time: 0.3347 data_time: 0.1416 memory: 7850 loss_ce: 0.0529 loss: 0.0529 2022/09/16 12:23:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:23:28 - mmengine - INFO - Epoch(train) [1][13000/42151] lr: 3.0000e-04 eta: 1 day, 8:22:38 time: 0.3329 data_time: 0.1317 memory: 7850 loss_ce: 0.0520 loss: 0.0520 2022/09/16 12:24:02 - mmengine - INFO - Epoch(train) [1][13100/42151] lr: 3.0000e-04 eta: 1 day, 8:17:32 time: 0.3226 data_time: 0.1058 memory: 7850 loss_ce: 0.0535 loss: 0.0535 2022/09/16 12:24:36 - mmengine - INFO - Epoch(train) [1][13200/42151] lr: 3.0000e-04 eta: 1 day, 8:12:27 time: 0.3620 data_time: 0.1454 memory: 7850 loss_ce: 0.0510 loss: 0.0510 2022/09/16 12:25:10 - mmengine - INFO - Epoch(train) [1][13300/42151] lr: 3.0000e-04 eta: 1 day, 8:07:11 time: 0.3984 data_time: 0.2011 memory: 7850 loss_ce: 0.0532 loss: 0.0532 2022/09/16 12:25:43 - mmengine - INFO - Epoch(train) [1][13400/42151] lr: 3.0000e-04 eta: 1 day, 8:02:02 time: 0.3689 data_time: 0.1545 memory: 7850 loss_ce: 0.0558 loss: 0.0558 2022/09/16 12:26:18 - mmengine - INFO - Epoch(train) [1][13500/42151] lr: 3.0000e-04 eta: 1 day, 7:57:07 time: 0.3429 data_time: 0.1453 memory: 7850 loss_ce: 0.0474 loss: 0.0474 2022/09/16 12:26:52 - mmengine - INFO - Epoch(train) [1][13600/42151] lr: 3.0000e-04 eta: 1 day, 7:52:11 time: 0.3135 data_time: 0.0964 memory: 7850 loss_ce: 0.0504 loss: 0.0504 2022/09/16 12:27:24 - mmengine - INFO - Epoch(train) [1][13700/42151] lr: 3.0000e-04 eta: 1 day, 7:46:55 time: 0.3243 data_time: 0.1321 memory: 7850 loss_ce: 0.0522 loss: 0.0522 2022/09/16 12:27:58 - mmengine - INFO - Epoch(train) [1][13800/42151] lr: 3.0000e-04 eta: 1 day, 7:42:04 time: 0.3797 data_time: 0.1804 memory: 7850 loss_ce: 0.0503 loss: 0.0503 2022/09/16 12:28:33 - mmengine - INFO - Epoch(train) [1][13900/42151] lr: 3.0000e-04 eta: 1 day, 7:37:32 time: 0.3481 data_time: 0.1314 memory: 7850 loss_ce: 0.0520 loss: 0.0520 2022/09/16 12:29:07 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:29:07 - mmengine - INFO - Epoch(train) [1][14000/42151] lr: 3.0000e-04 eta: 1 day, 7:32:58 time: 0.3873 data_time: 0.1703 memory: 7850 loss_ce: 0.0512 loss: 0.0512 2022/09/16 12:29:41 - mmengine - INFO - Epoch(train) [1][14100/42151] lr: 3.0000e-04 eta: 1 day, 7:28:26 time: 0.3441 data_time: 0.1491 memory: 7850 loss_ce: 0.0491 loss: 0.0491 2022/09/16 12:30:16 - mmengine - INFO - Epoch(train) [1][14200/42151] lr: 3.0000e-04 eta: 1 day, 7:23:59 time: 0.3015 data_time: 0.1053 memory: 7850 loss_ce: 0.0520 loss: 0.0520 2022/09/16 12:30:50 - mmengine - INFO - Epoch(train) [1][14300/42151] lr: 3.0000e-04 eta: 1 day, 7:19:34 time: 0.3379 data_time: 0.1322 memory: 7850 loss_ce: 0.0514 loss: 0.0514 2022/09/16 12:31:26 - mmengine - INFO - Epoch(train) [1][14400/42151] lr: 3.0000e-04 eta: 1 day, 7:15:35 time: 0.3542 data_time: 0.1599 memory: 7850 loss_ce: 0.0494 loss: 0.0494 2022/09/16 12:31:59 - mmengine - INFO - Epoch(train) [1][14500/42151] lr: 3.0000e-04 eta: 1 day, 7:11:03 time: 0.3520 data_time: 0.1448 memory: 7850 loss_ce: 0.0529 loss: 0.0529 2022/09/16 12:32:34 - mmengine - INFO - Epoch(train) [1][14600/42151] lr: 3.0000e-04 eta: 1 day, 7:06:52 time: 0.3982 data_time: 0.1992 memory: 7850 loss_ce: 0.0484 loss: 0.0484 2022/09/16 12:33:09 - mmengine - INFO - Epoch(train) [1][14700/42151] lr: 3.0000e-04 eta: 1 day, 7:02:54 time: 0.3216 data_time: 0.1233 memory: 7850 loss_ce: 0.0484 loss: 0.0484 2022/09/16 12:33:43 - mmengine - INFO - Epoch(train) [1][14800/42151] lr: 3.0000e-04 eta: 1 day, 6:58:33 time: 0.3021 data_time: 0.1073 memory: 7850 loss_ce: 0.0537 loss: 0.0537 2022/09/16 12:34:18 - mmengine - INFO - Epoch(train) [1][14900/42151] lr: 3.0000e-04 eta: 1 day, 6:54:34 time: 0.3333 data_time: 0.1222 memory: 7850 loss_ce: 0.0471 loss: 0.0471 2022/09/16 12:34:52 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:34:52 - mmengine - INFO - Epoch(train) [1][15000/42151] lr: 3.0000e-04 eta: 1 day, 6:50:33 time: 0.3465 data_time: 0.1514 memory: 7850 loss_ce: 0.0495 loss: 0.0495 2022/09/16 12:35:27 - mmengine - INFO - Epoch(train) [1][15100/42151] lr: 3.0000e-04 eta: 1 day, 6:46:36 time: 0.3892 data_time: 0.1771 memory: 7850 loss_ce: 0.0497 loss: 0.0497 2022/09/16 12:36:02 - mmengine - INFO - Epoch(train) [1][15200/42151] lr: 3.0000e-04 eta: 1 day, 6:42:49 time: 0.3753 data_time: 0.1736 memory: 7850 loss_ce: 0.0514 loss: 0.0514 2022/09/16 12:36:37 - mmengine - INFO - Epoch(train) [1][15300/42151] lr: 3.0000e-04 eta: 1 day, 6:39:04 time: 0.3384 data_time: 0.1429 memory: 7850 loss_ce: 0.0504 loss: 0.0504 2022/09/16 12:37:11 - mmengine - INFO - Epoch(train) [1][15400/42151] lr: 3.0000e-04 eta: 1 day, 6:35:15 time: 0.2924 data_time: 0.0957 memory: 7850 loss_ce: 0.0469 loss: 0.0469 2022/09/16 12:37:46 - mmengine - INFO - Epoch(train) [1][15500/42151] lr: 3.0000e-04 eta: 1 day, 6:31:27 time: 0.3382 data_time: 0.1389 memory: 7850 loss_ce: 0.0454 loss: 0.0454 2022/09/16 12:38:21 - mmengine - INFO - Epoch(train) [1][15600/42151] lr: 3.0000e-04 eta: 1 day, 6:27:48 time: 0.3568 data_time: 0.1618 memory: 7850 loss_ce: 0.0486 loss: 0.0486 2022/09/16 12:38:55 - mmengine - INFO - Epoch(train) [1][15700/42151] lr: 3.0000e-04 eta: 1 day, 6:24:06 time: 0.3259 data_time: 0.1316 memory: 7850 loss_ce: 0.0467 loss: 0.0467 2022/09/16 12:39:31 - mmengine - INFO - Epoch(train) [1][15800/42151] lr: 3.0000e-04 eta: 1 day, 6:20:38 time: 0.4093 data_time: 0.1898 memory: 7850 loss_ce: 0.0489 loss: 0.0489 2022/09/16 12:40:05 - mmengine - INFO - Epoch(train) [1][15900/42151] lr: 3.0000e-04 eta: 1 day, 6:16:52 time: 0.3009 data_time: 0.1088 memory: 7850 loss_ce: 0.0509 loss: 0.0509 2022/09/16 12:40:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:40:40 - mmengine - INFO - Epoch(train) [1][16000/42151] lr: 3.0000e-04 eta: 1 day, 6:13:19 time: 0.2937 data_time: 0.0960 memory: 7850 loss_ce: 0.0534 loss: 0.0534 2022/09/16 12:41:15 - mmengine - INFO - Epoch(train) [1][16100/42151] lr: 3.0000e-04 eta: 1 day, 6:10:00 time: 0.3690 data_time: 0.1770 memory: 7850 loss_ce: 0.0489 loss: 0.0489 2022/09/16 12:41:49 - mmengine - INFO - Epoch(train) [1][16200/42151] lr: 3.0000e-04 eta: 1 day, 6:06:20 time: 0.3952 data_time: 0.1971 memory: 7850 loss_ce: 0.0472 loss: 0.0472 2022/09/16 12:42:22 - mmengine - INFO - Epoch(train) [1][16300/42151] lr: 3.0000e-04 eta: 1 day, 6:02:31 time: 0.3320 data_time: 0.1375 memory: 7850 loss_ce: 0.0481 loss: 0.0481 2022/09/16 12:42:57 - mmengine - INFO - Epoch(train) [1][16400/42151] lr: 3.0000e-04 eta: 1 day, 5:59:07 time: 0.4356 data_time: 0.2390 memory: 7850 loss_ce: 0.0508 loss: 0.0508 2022/09/16 12:43:31 - mmengine - INFO - Epoch(train) [1][16500/42151] lr: 3.0000e-04 eta: 1 day, 5:55:35 time: 0.3169 data_time: 0.1173 memory: 7850 loss_ce: 0.0472 loss: 0.0472 2022/09/16 12:44:05 - mmengine - INFO - Epoch(train) [1][16600/42151] lr: 3.0000e-04 eta: 1 day, 5:52:10 time: 0.3490 data_time: 0.1526 memory: 7850 loss_ce: 0.0462 loss: 0.0462 2022/09/16 12:44:39 - mmengine - INFO - Epoch(train) [1][16700/42151] lr: 3.0000e-04 eta: 1 day, 5:48:43 time: 0.3208 data_time: 0.1201 memory: 7850 loss_ce: 0.0465 loss: 0.0465 2022/09/16 12:45:14 - mmengine - INFO - Epoch(train) [1][16800/42151] lr: 3.0000e-04 eta: 1 day, 5:45:29 time: 0.3737 data_time: 0.1575 memory: 7850 loss_ce: 0.0451 loss: 0.0451 2022/09/16 12:45:48 - mmengine - INFO - Epoch(train) [1][16900/42151] lr: 3.0000e-04 eta: 1 day, 5:42:01 time: 0.3257 data_time: 0.1330 memory: 7850 loss_ce: 0.0422 loss: 0.0422 2022/09/16 12:46:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:46:22 - mmengine - INFO - Epoch(train) [1][17000/42151] lr: 3.0000e-04 eta: 1 day, 5:38:43 time: 0.3622 data_time: 0.1368 memory: 7850 loss_ce: 0.0476 loss: 0.0476 2022/09/16 12:46:56 - mmengine - INFO - Epoch(train) [1][17100/42151] lr: 3.0000e-04 eta: 1 day, 5:35:19 time: 0.3140 data_time: 0.1173 memory: 7850 loss_ce: 0.0478 loss: 0.0478 2022/09/16 12:47:31 - mmengine - INFO - Epoch(train) [1][17200/42151] lr: 3.0000e-04 eta: 1 day, 5:32:14 time: 0.3461 data_time: 0.1236 memory: 7850 loss_ce: 0.0446 loss: 0.0446 2022/09/16 12:48:08 - mmengine - INFO - Epoch(train) [1][17300/42151] lr: 3.0000e-04 eta: 1 day, 5:29:36 time: 0.4187 data_time: 0.1728 memory: 7850 loss_ce: 0.0436 loss: 0.0436 2022/09/16 12:48:44 - mmengine - INFO - Epoch(train) [1][17400/42151] lr: 3.0000e-04 eta: 1 day, 5:26:58 time: 0.4103 data_time: 0.2008 memory: 7850 loss_ce: 0.0457 loss: 0.0457 2022/09/16 12:49:21 - mmengine - INFO - Epoch(train) [1][17500/42151] lr: 3.0000e-04 eta: 1 day, 5:24:16 time: 0.3435 data_time: 0.1335 memory: 7850 loss_ce: 0.0486 loss: 0.0486 2022/09/16 12:49:57 - mmengine - INFO - Epoch(train) [1][17600/42151] lr: 3.0000e-04 eta: 1 day, 5:21:37 time: 0.3541 data_time: 0.1452 memory: 7850 loss_ce: 0.0457 loss: 0.0457 2022/09/16 12:50:33 - mmengine - INFO - Epoch(train) [1][17700/42151] lr: 3.0000e-04 eta: 1 day, 5:18:53 time: 0.3503 data_time: 0.1417 memory: 7850 loss_ce: 0.0434 loss: 0.0434 2022/09/16 12:51:08 - mmengine - INFO - Epoch(train) [1][17800/42151] lr: 3.0000e-04 eta: 1 day, 5:15:58 time: 0.3303 data_time: 0.1275 memory: 7850 loss_ce: 0.0437 loss: 0.0437 2022/09/16 12:51:44 - mmengine - INFO - Epoch(train) [1][17900/42151] lr: 3.0000e-04 eta: 1 day, 5:13:07 time: 0.3352 data_time: 0.1305 memory: 7850 loss_ce: 0.0474 loss: 0.0474 2022/09/16 12:52:19 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:52:20 - mmengine - INFO - Epoch(train) [1][18000/42151] lr: 3.0000e-04 eta: 1 day, 5:10:25 time: 0.3779 data_time: 0.1403 memory: 7850 loss_ce: 0.0472 loss: 0.0472 2022/09/16 12:52:54 - mmengine - INFO - Epoch(train) [1][18100/42151] lr: 3.0000e-04 eta: 1 day, 5:07:31 time: 0.3546 data_time: 0.1454 memory: 7850 loss_ce: 0.0462 loss: 0.0462 2022/09/16 12:53:29 - mmengine - INFO - Epoch(train) [1][18200/42151] lr: 3.0000e-04 eta: 1 day, 5:04:35 time: 0.3476 data_time: 0.1262 memory: 7850 loss_ce: 0.0468 loss: 0.0468 2022/09/16 12:54:04 - mmengine - INFO - Epoch(train) [1][18300/42151] lr: 3.0000e-04 eta: 1 day, 5:01:47 time: 0.3753 data_time: 0.1681 memory: 7850 loss_ce: 0.0457 loss: 0.0457 2022/09/16 12:54:40 - mmengine - INFO - Epoch(train) [1][18400/42151] lr: 3.0000e-04 eta: 1 day, 4:59:18 time: 0.3456 data_time: 0.1426 memory: 7850 loss_ce: 0.0471 loss: 0.0471 2022/09/16 12:55:15 - mmengine - INFO - Epoch(train) [1][18500/42151] lr: 3.0000e-04 eta: 1 day, 4:56:40 time: 0.3606 data_time: 0.1318 memory: 7850 loss_ce: 0.0461 loss: 0.0461 2022/09/16 12:55:51 - mmengine - INFO - Epoch(train) [1][18600/42151] lr: 3.0000e-04 eta: 1 day, 4:54:08 time: 0.4106 data_time: 0.1749 memory: 7850 loss_ce: 0.0426 loss: 0.0426 2022/09/16 12:56:25 - mmengine - INFO - Epoch(train) [1][18700/42151] lr: 3.0000e-04 eta: 1 day, 4:51:14 time: 0.3134 data_time: 0.1152 memory: 7850 loss_ce: 0.0474 loss: 0.0474 2022/09/16 12:57:01 - mmengine - INFO - Epoch(train) [1][18800/42151] lr: 3.0000e-04 eta: 1 day, 4:48:38 time: 0.3644 data_time: 0.1390 memory: 7850 loss_ce: 0.0449 loss: 0.0449 2022/09/16 12:57:35 - mmengine - INFO - Epoch(train) [1][18900/42151] lr: 3.0000e-04 eta: 1 day, 4:45:49 time: 0.3168 data_time: 0.1185 memory: 7850 loss_ce: 0.0447 loss: 0.0447 2022/09/16 12:58:10 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 12:58:10 - mmengine - INFO - Epoch(train) [1][19000/42151] lr: 3.0000e-04 eta: 1 day, 4:43:11 time: 0.3317 data_time: 0.1091 memory: 7850 loss_ce: 0.0461 loss: 0.0461 2022/09/16 12:58:44 - mmengine - INFO - Epoch(train) [1][19100/42151] lr: 3.0000e-04 eta: 1 day, 4:40:23 time: 0.3254 data_time: 0.1247 memory: 7850 loss_ce: 0.0431 loss: 0.0431 2022/09/16 12:59:19 - mmengine - INFO - Epoch(train) [1][19200/42151] lr: 3.0000e-04 eta: 1 day, 4:37:46 time: 0.3684 data_time: 0.1570 memory: 7850 loss_ce: 0.0427 loss: 0.0427 2022/09/16 12:59:54 - mmengine - INFO - Epoch(train) [1][19300/42151] lr: 3.0000e-04 eta: 1 day, 4:35:13 time: 0.3680 data_time: 0.1634 memory: 7850 loss_ce: 0.0430 loss: 0.0430 2022/09/16 13:00:30 - mmengine - INFO - Epoch(train) [1][19400/42151] lr: 3.0000e-04 eta: 1 day, 4:32:55 time: 0.3795 data_time: 0.1368 memory: 7850 loss_ce: 0.0413 loss: 0.0413 2022/09/16 13:01:05 - mmengine - INFO - Epoch(train) [1][19500/42151] lr: 3.0000e-04 eta: 1 day, 4:30:20 time: 0.3465 data_time: 0.1409 memory: 7850 loss_ce: 0.0403 loss: 0.0403 2022/09/16 13:01:40 - mmengine - INFO - Epoch(train) [1][19600/42151] lr: 3.0000e-04 eta: 1 day, 4:27:44 time: 0.3405 data_time: 0.1162 memory: 7850 loss_ce: 0.0429 loss: 0.0429 2022/09/16 13:02:14 - mmengine - INFO - Epoch(train) [1][19700/42151] lr: 3.0000e-04 eta: 1 day, 4:25:04 time: 0.2037 data_time: 0.0044 memory: 7850 loss_ce: 0.0467 loss: 0.0467 2022/09/16 13:02:49 - mmengine - INFO - Epoch(train) [1][19800/42151] lr: 3.0000e-04 eta: 1 day, 4:22:39 time: 0.2664 data_time: 0.0589 memory: 7850 loss_ce: 0.0426 loss: 0.0426 2022/09/16 13:03:22 - mmengine - INFO - Epoch(train) [1][19900/42151] lr: 3.0000e-04 eta: 1 day, 4:19:45 time: 0.3599 data_time: 0.1504 memory: 7850 loss_ce: 0.0451 loss: 0.0451 2022/09/16 13:03:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:03:58 - mmengine - INFO - Epoch(train) [1][20000/42151] lr: 3.0000e-04 eta: 1 day, 4:17:25 time: 0.4628 data_time: 0.2237 memory: 7850 loss_ce: 0.0455 loss: 0.0455 2022/09/16 13:04:31 - mmengine - INFO - Epoch(train) [1][20100/42151] lr: 3.0000e-04 eta: 1 day, 4:14:40 time: 0.4910 data_time: 0.2621 memory: 7850 loss_ce: 0.0403 loss: 0.0403 2022/09/16 13:05:04 - mmengine - INFO - Epoch(train) [1][20200/42151] lr: 3.0000e-04 eta: 1 day, 4:11:56 time: 0.2478 data_time: 0.0057 memory: 7850 loss_ce: 0.0462 loss: 0.0462 2022/09/16 13:05:46 - mmengine - INFO - Epoch(train) [1][20300/42151] lr: 3.0000e-04 eta: 1 day, 4:10:52 time: 0.2060 data_time: 0.0045 memory: 7850 loss_ce: 0.0464 loss: 0.0464 2022/09/16 13:06:24 - mmengine - INFO - Epoch(train) [1][20400/42151] lr: 3.0000e-04 eta: 1 day, 4:09:05 time: 0.2361 data_time: 0.0323 memory: 7850 loss_ce: 0.0428 loss: 0.0428 2022/09/16 13:06:57 - mmengine - INFO - Epoch(train) [1][20500/42151] lr: 3.0000e-04 eta: 1 day, 4:06:28 time: 0.2038 data_time: 0.0044 memory: 7850 loss_ce: 0.0419 loss: 0.0419 2022/09/16 13:07:33 - mmengine - INFO - Epoch(train) [1][20600/42151] lr: 3.0000e-04 eta: 1 day, 4:04:15 time: 0.2187 data_time: 0.0053 memory: 7850 loss_ce: 0.0420 loss: 0.0420 2022/09/16 13:08:09 - mmengine - INFO - Epoch(train) [1][20700/42151] lr: 3.0000e-04 eta: 1 day, 4:02:07 time: 0.4625 data_time: 0.2402 memory: 7850 loss_ce: 0.0431 loss: 0.0431 2022/09/16 13:08:42 - mmengine - INFO - Epoch(train) [1][20800/42151] lr: 3.0000e-04 eta: 1 day, 3:59:31 time: 0.2041 data_time: 0.0042 memory: 7850 loss_ce: 0.0442 loss: 0.0442 2022/09/16 13:09:15 - mmengine - INFO - Epoch(train) [1][20900/42151] lr: 3.0000e-04 eta: 1 day, 3:56:47 time: 0.2430 data_time: 0.0428 memory: 7850 loss_ce: 0.0414 loss: 0.0414 2022/09/16 13:09:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:09:51 - mmengine - INFO - Epoch(train) [1][21000/42151] lr: 3.0000e-04 eta: 1 day, 3:54:35 time: 0.2350 data_time: 0.0270 memory: 7850 loss_ce: 0.0440 loss: 0.0440 2022/09/16 13:10:24 - mmengine - INFO - Epoch(train) [1][21100/42151] lr: 3.0000e-04 eta: 1 day, 3:52:12 time: 0.2305 data_time: 0.0045 memory: 7850 loss_ce: 0.0415 loss: 0.0415 2022/09/16 13:10:56 - mmengine - INFO - Epoch(train) [1][21200/42151] lr: 3.0000e-04 eta: 1 day, 3:49:23 time: 0.2328 data_time: 0.0061 memory: 7850 loss_ce: 0.0414 loss: 0.0414 2022/09/16 13:11:35 - mmengine - INFO - Epoch(train) [1][21300/42151] lr: 3.0000e-04 eta: 1 day, 3:47:47 time: 0.2417 data_time: 0.0052 memory: 7850 loss_ce: 0.0436 loss: 0.0436 2022/09/16 13:12:07 - mmengine - INFO - Epoch(train) [1][21400/42151] lr: 3.0000e-04 eta: 1 day, 3:45:10 time: 0.2978 data_time: 0.0984 memory: 7850 loss_ce: 0.0433 loss: 0.0433 2022/09/16 13:12:44 - mmengine - INFO - Epoch(train) [1][21500/42151] lr: 3.0000e-04 eta: 1 day, 3:43:12 time: 0.5204 data_time: 0.3092 memory: 7850 loss_ce: 0.0436 loss: 0.0436 2022/09/16 13:13:17 - mmengine - INFO - Epoch(train) [1][21600/42151] lr: 3.0000e-04 eta: 1 day, 3:40:44 time: 0.2438 data_time: 0.0051 memory: 7850 loss_ce: 0.0388 loss: 0.0388 2022/09/16 13:13:56 - mmengine - INFO - Epoch(train) [1][21700/42151] lr: 3.0000e-04 eta: 1 day, 3:39:20 time: 0.2343 data_time: 0.0061 memory: 7850 loss_ce: 0.0398 loss: 0.0398 2022/09/16 13:14:32 - mmengine - INFO - Epoch(train) [1][21800/42151] lr: 3.0000e-04 eta: 1 day, 3:37:15 time: 0.4813 data_time: 0.2560 memory: 7850 loss_ce: 0.0452 loss: 0.0452 2022/09/16 13:15:04 - mmengine - INFO - Epoch(train) [1][21900/42151] lr: 3.0000e-04 eta: 1 day, 3:34:43 time: 0.2091 data_time: 0.0061 memory: 7850 loss_ce: 0.0425 loss: 0.0425 2022/09/16 13:15:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:15:39 - mmengine - INFO - Epoch(train) [1][22000/42151] lr: 3.0000e-04 eta: 1 day, 3:32:31 time: 0.3182 data_time: 0.1151 memory: 7850 loss_ce: 0.0415 loss: 0.0415 2022/09/16 13:16:18 - mmengine - INFO - Epoch(train) [1][22100/42151] lr: 3.0000e-04 eta: 1 day, 3:31:06 time: 0.2351 data_time: 0.0131 memory: 7850 loss_ce: 0.0388 loss: 0.0388 2022/09/16 13:16:51 - mmengine - INFO - Epoch(train) [1][22200/42151] lr: 3.0000e-04 eta: 1 day, 3:28:44 time: 0.2055 data_time: 0.0044 memory: 7850 loss_ce: 0.0407 loss: 0.0407 2022/09/16 13:17:40 - mmengine - INFO - Epoch(train) [1][22300/42151] lr: 3.0000e-04 eta: 1 day, 3:29:05 time: 0.2188 data_time: 0.0053 memory: 7850 loss_ce: 0.0424 loss: 0.0424 2022/09/16 13:18:27 - mmengine - INFO - Epoch(train) [1][22400/42151] lr: 3.0000e-04 eta: 1 day, 3:29:03 time: 1.5909 data_time: 1.3753 memory: 7850 loss_ce: 0.0387 loss: 0.0387 2022/09/16 13:19:02 - mmengine - INFO - Epoch(train) [1][22500/42151] lr: 3.0000e-04 eta: 1 day, 3:27:00 time: 0.2873 data_time: 0.0460 memory: 7850 loss_ce: 0.0395 loss: 0.0395 2022/09/16 13:19:34 - mmengine - INFO - Epoch(train) [1][22600/42151] lr: 3.0000e-04 eta: 1 day, 3:24:27 time: 0.2543 data_time: 0.0238 memory: 7850 loss_ce: 0.0440 loss: 0.0440 2022/09/16 13:20:06 - mmengine - INFO - Epoch(train) [1][22700/42151] lr: 3.0000e-04 eta: 1 day, 3:21:53 time: 0.2027 data_time: 0.0043 memory: 7850 loss_ce: 0.0440 loss: 0.0440 2022/09/16 13:20:41 - mmengine - INFO - Epoch(train) [1][22800/42151] lr: 3.0000e-04 eta: 1 day, 3:19:54 time: 0.2098 data_time: 0.0054 memory: 7850 loss_ce: 0.0418 loss: 0.0418 2022/09/16 13:21:19 - mmengine - INFO - Epoch(train) [1][22900/42151] lr: 3.0000e-04 eta: 1 day, 3:18:17 time: 0.2281 data_time: 0.0058 memory: 7850 loss_ce: 0.0396 loss: 0.0396 2022/09/16 13:21:55 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:21:55 - mmengine - INFO - Epoch(train) [1][23000/42151] lr: 3.0000e-04 eta: 1 day, 3:16:27 time: 0.5122 data_time: 0.2929 memory: 7850 loss_ce: 0.0411 loss: 0.0411 2022/09/16 13:22:27 - mmengine - INFO - Epoch(train) [1][23100/42151] lr: 3.0000e-04 eta: 1 day, 3:13:59 time: 0.2327 data_time: 0.0063 memory: 7850 loss_ce: 0.0404 loss: 0.0404 2022/09/16 13:23:03 - mmengine - INFO - Epoch(train) [1][23200/42151] lr: 3.0000e-04 eta: 1 day, 3:12:07 time: 0.4094 data_time: 0.1784 memory: 7850 loss_ce: 0.0399 loss: 0.0399 2022/09/16 13:23:37 - mmengine - INFO - Epoch(train) [1][23300/42151] lr: 3.0000e-04 eta: 1 day, 3:09:59 time: 0.6327 data_time: 0.3478 memory: 7850 loss_ce: 0.0406 loss: 0.0406 2022/09/16 13:24:09 - mmengine - INFO - Epoch(train) [1][23400/42151] lr: 3.0000e-04 eta: 1 day, 3:07:38 time: 0.4546 data_time: 0.2414 memory: 7850 loss_ce: 0.0410 loss: 0.0410 2022/09/16 13:24:44 - mmengine - INFO - Epoch(train) [1][23500/42151] lr: 3.0000e-04 eta: 1 day, 3:05:44 time: 0.4310 data_time: 0.1863 memory: 7850 loss_ce: 0.0393 loss: 0.0393 2022/09/16 13:25:18 - mmengine - INFO - Epoch(train) [1][23600/42151] lr: 3.0000e-04 eta: 1 day, 3:03:37 time: 0.4286 data_time: 0.2277 memory: 7850 loss_ce: 0.0424 loss: 0.0424 2022/09/16 13:25:56 - mmengine - INFO - Epoch(train) [1][23700/42151] lr: 3.0000e-04 eta: 1 day, 3:02:11 time: 0.2471 data_time: 0.0411 memory: 7850 loss_ce: 0.0408 loss: 0.0408 2022/09/16 13:26:32 - mmengine - INFO - Epoch(train) [1][23800/42151] lr: 3.0000e-04 eta: 1 day, 3:00:26 time: 0.3738 data_time: 0.1060 memory: 7850 loss_ce: 0.0402 loss: 0.0402 2022/09/16 13:27:07 - mmengine - INFO - Epoch(train) [1][23900/42151] lr: 3.0000e-04 eta: 1 day, 2:58:26 time: 0.4012 data_time: 0.1697 memory: 7850 loss_ce: 0.0394 loss: 0.0394 2022/09/16 13:27:37 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:27:37 - mmengine - INFO - Epoch(train) [1][24000/42151] lr: 3.0000e-04 eta: 1 day, 2:55:52 time: 0.2425 data_time: 0.0386 memory: 7850 loss_ce: 0.0380 loss: 0.0380 2022/09/16 13:28:12 - mmengine - INFO - Epoch(train) [1][24100/42151] lr: 3.0000e-04 eta: 1 day, 2:53:56 time: 0.3156 data_time: 0.1130 memory: 7850 loss_ce: 0.0421 loss: 0.0421 2022/09/16 13:28:46 - mmengine - INFO - Epoch(train) [1][24200/42151] lr: 3.0000e-04 eta: 1 day, 2:51:56 time: 0.3126 data_time: 0.0912 memory: 7850 loss_ce: 0.0395 loss: 0.0395 2022/09/16 13:29:21 - mmengine - INFO - Epoch(train) [1][24300/42151] lr: 3.0000e-04 eta: 1 day, 2:50:09 time: 0.4094 data_time: 0.1605 memory: 7850 loss_ce: 0.0399 loss: 0.0399 2022/09/16 13:29:56 - mmengine - INFO - Epoch(train) [1][24400/42151] lr: 3.0000e-04 eta: 1 day, 2:48:13 time: 0.3090 data_time: 0.1055 memory: 7850 loss_ce: 0.0378 loss: 0.0378 2022/09/16 13:30:32 - mmengine - INFO - Epoch(train) [1][24500/42151] lr: 3.0000e-04 eta: 1 day, 2:46:32 time: 0.3442 data_time: 0.1236 memory: 7850 loss_ce: 0.0401 loss: 0.0401 2022/09/16 13:31:06 - mmengine - INFO - Epoch(train) [1][24600/42151] lr: 3.0000e-04 eta: 1 day, 2:44:35 time: 0.2883 data_time: 0.0733 memory: 7850 loss_ce: 0.0413 loss: 0.0413 2022/09/16 13:31:41 - mmengine - INFO - Epoch(train) [1][24700/42151] lr: 3.0000e-04 eta: 1 day, 2:42:45 time: 0.3343 data_time: 0.1351 memory: 7850 loss_ce: 0.0410 loss: 0.0410 2022/09/16 13:32:16 - mmengine - INFO - Epoch(train) [1][24800/42151] lr: 3.0000e-04 eta: 1 day, 2:41:01 time: 0.3365 data_time: 0.0899 memory: 7850 loss_ce: 0.0388 loss: 0.0388 2022/09/16 13:32:52 - mmengine - INFO - Epoch(train) [1][24900/42151] lr: 3.0000e-04 eta: 1 day, 2:39:18 time: 0.3822 data_time: 0.1578 memory: 7850 loss_ce: 0.0396 loss: 0.0396 2022/09/16 13:33:26 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:33:26 - mmengine - INFO - Epoch(train) [1][25000/42151] lr: 3.0000e-04 eta: 1 day, 2:37:23 time: 0.3012 data_time: 0.1025 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 13:34:01 - mmengine - INFO - Epoch(train) [1][25100/42151] lr: 3.0000e-04 eta: 1 day, 2:35:38 time: 0.3080 data_time: 0.1118 memory: 7850 loss_ce: 0.0392 loss: 0.0392 2022/09/16 13:34:37 - mmengine - INFO - Epoch(train) [1][25200/42151] lr: 3.0000e-04 eta: 1 day, 2:34:01 time: 0.3432 data_time: 0.0889 memory: 7850 loss_ce: 0.0400 loss: 0.0400 2022/09/16 13:35:12 - mmengine - INFO - Epoch(train) [1][25300/42151] lr: 3.0000e-04 eta: 1 day, 2:32:19 time: 0.3828 data_time: 0.1309 memory: 7850 loss_ce: 0.0406 loss: 0.0406 2022/09/16 13:35:47 - mmengine - INFO - Epoch(train) [1][25400/42151] lr: 3.0000e-04 eta: 1 day, 2:30:38 time: 0.3369 data_time: 0.0942 memory: 7850 loss_ce: 0.0397 loss: 0.0397 2022/09/16 13:36:22 - mmengine - INFO - Epoch(train) [1][25500/42151] lr: 3.0000e-04 eta: 1 day, 2:28:53 time: 0.3840 data_time: 0.1760 memory: 7850 loss_ce: 0.0384 loss: 0.0384 2022/09/16 13:36:57 - mmengine - INFO - Epoch(train) [1][25600/42151] lr: 3.0000e-04 eta: 1 day, 2:27:02 time: 0.3291 data_time: 0.0907 memory: 7850 loss_ce: 0.0385 loss: 0.0385 2022/09/16 13:37:32 - mmengine - INFO - Epoch(train) [1][25700/42151] lr: 3.0000e-04 eta: 1 day, 2:25:19 time: 0.3475 data_time: 0.1303 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 13:38:07 - mmengine - INFO - Epoch(train) [1][25800/42151] lr: 3.0000e-04 eta: 1 day, 2:23:41 time: 0.4079 data_time: 0.0980 memory: 7850 loss_ce: 0.0414 loss: 0.0414 2022/09/16 13:38:43 - mmengine - INFO - Epoch(train) [1][25900/42151] lr: 3.0000e-04 eta: 1 day, 2:22:03 time: 0.3418 data_time: 0.1329 memory: 7850 loss_ce: 0.0412 loss: 0.0412 2022/09/16 13:39:18 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:39:18 - mmengine - INFO - Epoch(train) [1][26000/42151] lr: 3.0000e-04 eta: 1 day, 2:20:24 time: 0.3369 data_time: 0.1170 memory: 7850 loss_ce: 0.0401 loss: 0.0401 2022/09/16 13:39:54 - mmengine - INFO - Epoch(train) [1][26100/42151] lr: 3.0000e-04 eta: 1 day, 2:18:52 time: 0.3835 data_time: 0.1739 memory: 7850 loss_ce: 0.0393 loss: 0.0393 2022/09/16 13:40:28 - mmengine - INFO - Epoch(train) [1][26200/42151] lr: 3.0000e-04 eta: 1 day, 2:17:09 time: 0.3610 data_time: 0.1556 memory: 7850 loss_ce: 0.0405 loss: 0.0405 2022/09/16 13:41:05 - mmengine - INFO - Epoch(train) [1][26300/42151] lr: 3.0000e-04 eta: 1 day, 2:15:40 time: 0.3945 data_time: 0.1615 memory: 7850 loss_ce: 0.0414 loss: 0.0414 2022/09/16 13:41:40 - mmengine - INFO - Epoch(train) [1][26400/42151] lr: 3.0000e-04 eta: 1 day, 2:14:01 time: 0.3097 data_time: 0.1045 memory: 7850 loss_ce: 0.0391 loss: 0.0391 2022/09/16 13:42:17 - mmengine - INFO - Epoch(train) [1][26500/42151] lr: 3.0000e-04 eta: 1 day, 2:12:42 time: 0.4280 data_time: 0.1886 memory: 7850 loss_ce: 0.0372 loss: 0.0372 2022/09/16 13:42:52 - mmengine - INFO - Epoch(train) [1][26600/42151] lr: 3.0000e-04 eta: 1 day, 2:11:05 time: 0.3309 data_time: 0.1244 memory: 7850 loss_ce: 0.0398 loss: 0.0398 2022/09/16 13:43:28 - mmengine - INFO - Epoch(train) [1][26700/42151] lr: 3.0000e-04 eta: 1 day, 2:09:36 time: 0.3684 data_time: 0.1420 memory: 7850 loss_ce: 0.0395 loss: 0.0395 2022/09/16 13:44:02 - mmengine - INFO - Epoch(train) [1][26800/42151] lr: 3.0000e-04 eta: 1 day, 2:07:50 time: 0.3177 data_time: 0.1146 memory: 7850 loss_ce: 0.0393 loss: 0.0393 2022/09/16 13:44:38 - mmengine - INFO - Epoch(train) [1][26900/42151] lr: 3.0000e-04 eta: 1 day, 2:06:18 time: 0.3239 data_time: 0.1205 memory: 7850 loss_ce: 0.0374 loss: 0.0374 2022/09/16 13:45:13 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:45:13 - mmengine - INFO - Epoch(train) [1][27000/42151] lr: 3.0000e-04 eta: 1 day, 2:04:41 time: 0.3105 data_time: 0.0861 memory: 7850 loss_ce: 0.0406 loss: 0.0406 2022/09/16 13:45:48 - mmengine - INFO - Epoch(train) [1][27100/42151] lr: 3.0000e-04 eta: 1 day, 2:03:04 time: 0.3594 data_time: 0.1334 memory: 7850 loss_ce: 0.0399 loss: 0.0399 2022/09/16 13:46:23 - mmengine - INFO - Epoch(train) [1][27200/42151] lr: 3.0000e-04 eta: 1 day, 2:01:33 time: 0.3244 data_time: 0.0983 memory: 7850 loss_ce: 0.0407 loss: 0.0407 2022/09/16 13:47:00 - mmengine - INFO - Epoch(train) [1][27300/42151] lr: 3.0000e-04 eta: 1 day, 2:00:08 time: 0.3962 data_time: 0.1904 memory: 7850 loss_ce: 0.0370 loss: 0.0370 2022/09/16 13:47:35 - mmengine - INFO - Epoch(train) [1][27400/42151] lr: 3.0000e-04 eta: 1 day, 1:58:37 time: 0.3463 data_time: 0.1035 memory: 7850 loss_ce: 0.0408 loss: 0.0408 2022/09/16 13:48:11 - mmengine - INFO - Epoch(train) [1][27500/42151] lr: 3.0000e-04 eta: 1 day, 1:57:10 time: 0.3101 data_time: 0.1123 memory: 7850 loss_ce: 0.0391 loss: 0.0391 2022/09/16 13:48:47 - mmengine - INFO - Epoch(train) [1][27600/42151] lr: 3.0000e-04 eta: 1 day, 1:55:44 time: 0.3608 data_time: 0.1048 memory: 7850 loss_ce: 0.0397 loss: 0.0397 2022/09/16 13:49:23 - mmengine - INFO - Epoch(train) [1][27700/42151] lr: 3.0000e-04 eta: 1 day, 1:54:16 time: 0.3414 data_time: 0.1365 memory: 7850 loss_ce: 0.0376 loss: 0.0376 2022/09/16 13:49:59 - mmengine - INFO - Epoch(train) [1][27800/42151] lr: 3.0000e-04 eta: 1 day, 1:52:52 time: 0.3888 data_time: 0.1340 memory: 7850 loss_ce: 0.0378 loss: 0.0378 2022/09/16 13:50:34 - mmengine - INFO - Epoch(train) [1][27900/42151] lr: 3.0000e-04 eta: 1 day, 1:51:21 time: 0.3575 data_time: 0.1548 memory: 7850 loss_ce: 0.0378 loss: 0.0378 2022/09/16 13:51:09 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:51:10 - mmengine - INFO - Epoch(train) [1][28000/42151] lr: 3.0000e-04 eta: 1 day, 1:49:49 time: 0.3227 data_time: 0.1155 memory: 7850 loss_ce: 0.0381 loss: 0.0381 2022/09/16 13:51:45 - mmengine - INFO - Epoch(train) [1][28100/42151] lr: 3.0000e-04 eta: 1 day, 1:48:25 time: 0.3307 data_time: 0.1281 memory: 7850 loss_ce: 0.0388 loss: 0.0388 2022/09/16 13:52:21 - mmengine - INFO - Epoch(train) [1][28200/42151] lr: 3.0000e-04 eta: 1 day, 1:47:02 time: 0.3191 data_time: 0.1165 memory: 7850 loss_ce: 0.0342 loss: 0.0342 2022/09/16 13:52:57 - mmengine - INFO - Epoch(train) [1][28300/42151] lr: 3.0000e-04 eta: 1 day, 1:45:36 time: 0.3759 data_time: 0.1682 memory: 7850 loss_ce: 0.0407 loss: 0.0407 2022/09/16 13:53:32 - mmengine - INFO - Epoch(train) [1][28400/42151] lr: 3.0000e-04 eta: 1 day, 1:44:00 time: 0.3174 data_time: 0.1167 memory: 7850 loss_ce: 0.0408 loss: 0.0408 2022/09/16 13:54:07 - mmengine - INFO - Epoch(train) [1][28500/42151] lr: 3.0000e-04 eta: 1 day, 1:42:36 time: 0.4054 data_time: 0.1493 memory: 7850 loss_ce: 0.0389 loss: 0.0389 2022/09/16 13:54:42 - mmengine - INFO - Epoch(train) [1][28600/42151] lr: 3.0000e-04 eta: 1 day, 1:41:05 time: 0.3243 data_time: 0.1193 memory: 7850 loss_ce: 0.0391 loss: 0.0391 2022/09/16 13:55:17 - mmengine - INFO - Epoch(train) [1][28700/42151] lr: 3.0000e-04 eta: 1 day, 1:39:36 time: 0.3319 data_time: 0.1215 memory: 7850 loss_ce: 0.0372 loss: 0.0372 2022/09/16 13:55:53 - mmengine - INFO - Epoch(train) [1][28800/42151] lr: 3.0000e-04 eta: 1 day, 1:38:07 time: 0.3334 data_time: 0.1051 memory: 7850 loss_ce: 0.0360 loss: 0.0360 2022/09/16 13:56:28 - mmengine - INFO - Epoch(train) [1][28900/42151] lr: 3.0000e-04 eta: 1 day, 1:36:43 time: 0.4162 data_time: 0.1197 memory: 7850 loss_ce: 0.0361 loss: 0.0361 2022/09/16 13:57:03 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 13:57:03 - mmengine - INFO - Epoch(train) [1][29000/42151] lr: 3.0000e-04 eta: 1 day, 1:35:16 time: 0.3239 data_time: 0.0981 memory: 7850 loss_ce: 0.0358 loss: 0.0358 2022/09/16 13:57:40 - mmengine - INFO - Epoch(train) [1][29100/42151] lr: 3.0000e-04 eta: 1 day, 1:33:59 time: 0.4098 data_time: 0.1958 memory: 7850 loss_ce: 0.0396 loss: 0.0396 2022/09/16 13:58:15 - mmengine - INFO - Epoch(train) [1][29200/42151] lr: 3.0000e-04 eta: 1 day, 1:32:32 time: 0.3405 data_time: 0.0868 memory: 7850 loss_ce: 0.0404 loss: 0.0404 2022/09/16 13:58:51 - mmengine - INFO - Epoch(train) [1][29300/42151] lr: 3.0000e-04 eta: 1 day, 1:31:08 time: 0.3475 data_time: 0.1454 memory: 7850 loss_ce: 0.0345 loss: 0.0345 2022/09/16 13:59:29 - mmengine - INFO - Epoch(train) [1][29400/42151] lr: 3.0000e-04 eta: 1 day, 1:30:06 time: 0.3356 data_time: 0.1312 memory: 7850 loss_ce: 0.0358 loss: 0.0358 2022/09/16 14:00:05 - mmengine - INFO - Epoch(train) [1][29500/42151] lr: 3.0000e-04 eta: 1 day, 1:28:49 time: 0.3944 data_time: 0.1910 memory: 7850 loss_ce: 0.0370 loss: 0.0370 2022/09/16 14:00:39 - mmengine - INFO - Epoch(train) [1][29600/42151] lr: 3.0000e-04 eta: 1 day, 1:27:15 time: 0.3197 data_time: 0.1191 memory: 7850 loss_ce: 0.0385 loss: 0.0385 2022/09/16 14:01:15 - mmengine - INFO - Epoch(train) [1][29700/42151] lr: 3.0000e-04 eta: 1 day, 1:25:57 time: 0.3643 data_time: 0.1436 memory: 7850 loss_ce: 0.0380 loss: 0.0380 2022/09/16 14:01:51 - mmengine - INFO - Epoch(train) [1][29800/42151] lr: 3.0000e-04 eta: 1 day, 1:24:32 time: 0.3147 data_time: 0.1164 memory: 7850 loss_ce: 0.0384 loss: 0.0384 2022/09/16 14:02:26 - mmengine - INFO - Epoch(train) [1][29900/42151] lr: 3.0000e-04 eta: 1 day, 1:23:09 time: 0.3106 data_time: 0.0726 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 14:03:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:03:02 - mmengine - INFO - Epoch(train) [1][30000/42151] lr: 3.0000e-04 eta: 1 day, 1:21:50 time: 0.3677 data_time: 0.1593 memory: 7850 loss_ce: 0.0363 loss: 0.0363 2022/09/16 14:03:38 - mmengine - INFO - Epoch(train) [1][30100/42151] lr: 3.0000e-04 eta: 1 day, 1:20:35 time: 0.4158 data_time: 0.2034 memory: 7850 loss_ce: 0.0373 loss: 0.0373 2022/09/16 14:04:13 - mmengine - INFO - Epoch(train) [1][30200/42151] lr: 3.0000e-04 eta: 1 day, 1:19:08 time: 0.3323 data_time: 0.1298 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 14:04:49 - mmengine - INFO - Epoch(train) [1][30300/42151] lr: 3.0000e-04 eta: 1 day, 1:17:50 time: 0.3540 data_time: 0.1190 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 14:05:25 - mmengine - INFO - Epoch(train) [1][30400/42151] lr: 3.0000e-04 eta: 1 day, 1:16:33 time: 0.3405 data_time: 0.1430 memory: 7850 loss_ce: 0.0363 loss: 0.0363 2022/09/16 14:06:01 - mmengine - INFO - Epoch(train) [1][30500/42151] lr: 3.0000e-04 eta: 1 day, 1:15:17 time: 0.3242 data_time: 0.1165 memory: 7850 loss_ce: 0.0365 loss: 0.0365 2022/09/16 14:06:37 - mmengine - INFO - Epoch(train) [1][30600/42151] lr: 3.0000e-04 eta: 1 day, 1:13:58 time: 0.4209 data_time: 0.1962 memory: 7850 loss_ce: 0.0343 loss: 0.0343 2022/09/16 14:07:12 - mmengine - INFO - Epoch(train) [1][30700/42151] lr: 3.0000e-04 eta: 1 day, 1:12:37 time: 0.3690 data_time: 0.1676 memory: 7850 loss_ce: 0.0370 loss: 0.0370 2022/09/16 14:07:48 - mmengine - INFO - Epoch(train) [1][30800/42151] lr: 3.0000e-04 eta: 1 day, 1:11:19 time: 0.3883 data_time: 0.1731 memory: 7850 loss_ce: 0.0356 loss: 0.0356 2022/09/16 14:08:22 - mmengine - INFO - Epoch(train) [1][30900/42151] lr: 3.0000e-04 eta: 1 day, 1:09:55 time: 0.3281 data_time: 0.1065 memory: 7850 loss_ce: 0.0349 loss: 0.0349 2022/09/16 14:08:59 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:08:59 - mmengine - INFO - Epoch(train) [1][31000/42151] lr: 3.0000e-04 eta: 1 day, 1:08:42 time: 0.3622 data_time: 0.1522 memory: 7850 loss_ce: 0.0354 loss: 0.0354 2022/09/16 14:09:34 - mmengine - INFO - Epoch(train) [1][31100/42151] lr: 3.0000e-04 eta: 1 day, 1:07:21 time: 0.3534 data_time: 0.1421 memory: 7850 loss_ce: 0.0356 loss: 0.0356 2022/09/16 14:10:10 - mmengine - INFO - Epoch(train) [1][31200/42151] lr: 3.0000e-04 eta: 1 day, 1:06:08 time: 0.4188 data_time: 0.1675 memory: 7850 loss_ce: 0.0392 loss: 0.0392 2022/09/16 14:10:45 - mmengine - INFO - Epoch(train) [1][31300/42151] lr: 3.0000e-04 eta: 1 day, 1:04:48 time: 0.4130 data_time: 0.2049 memory: 7850 loss_ce: 0.0367 loss: 0.0367 2022/09/16 14:11:19 - mmengine - INFO - Epoch(train) [1][31400/42151] lr: 3.0000e-04 eta: 1 day, 1:03:20 time: 0.3790 data_time: 0.1646 memory: 7850 loss_ce: 0.0349 loss: 0.0349 2022/09/16 14:11:54 - mmengine - INFO - Epoch(train) [1][31500/42151] lr: 3.0000e-04 eta: 1 day, 1:01:59 time: 0.3817 data_time: 0.1603 memory: 7850 loss_ce: 0.0351 loss: 0.0351 2022/09/16 14:12:29 - mmengine - INFO - Epoch(train) [1][31600/42151] lr: 3.0000e-04 eta: 1 day, 1:00:38 time: 0.3241 data_time: 0.1237 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 14:13:06 - mmengine - INFO - Epoch(train) [1][31700/42151] lr: 3.0000e-04 eta: 1 day, 0:59:25 time: 0.3184 data_time: 0.1163 memory: 7850 loss_ce: 0.0341 loss: 0.0341 2022/09/16 14:13:41 - mmengine - INFO - Epoch(train) [1][31800/42151] lr: 3.0000e-04 eta: 1 day, 0:58:10 time: 0.3581 data_time: 0.1303 memory: 7850 loss_ce: 0.0362 loss: 0.0362 2022/09/16 14:14:17 - mmengine - INFO - Epoch(train) [1][31900/42151] lr: 3.0000e-04 eta: 1 day, 0:56:55 time: 0.3931 data_time: 0.1737 memory: 7850 loss_ce: 0.0396 loss: 0.0396 2022/09/16 14:14:52 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:14:53 - mmengine - INFO - Epoch(train) [1][32000/42151] lr: 3.0000e-04 eta: 1 day, 0:55:38 time: 0.3241 data_time: 0.1041 memory: 7850 loss_ce: 0.0334 loss: 0.0334 2022/09/16 14:15:27 - mmengine - INFO - Epoch(train) [1][32100/42151] lr: 3.0000e-04 eta: 1 day, 0:54:19 time: 0.3330 data_time: 0.1366 memory: 7850 loss_ce: 0.0381 loss: 0.0381 2022/09/16 14:16:03 - mmengine - INFO - Epoch(train) [1][32200/42151] lr: 3.0000e-04 eta: 1 day, 0:53:02 time: 0.3185 data_time: 0.1186 memory: 7850 loss_ce: 0.0356 loss: 0.0356 2022/09/16 14:16:37 - mmengine - INFO - Epoch(train) [1][32300/42151] lr: 3.0000e-04 eta: 1 day, 0:51:41 time: 0.3113 data_time: 0.1079 memory: 7850 loss_ce: 0.0341 loss: 0.0341 2022/09/16 14:17:13 - mmengine - INFO - Epoch(train) [1][32400/42151] lr: 3.0000e-04 eta: 1 day, 0:50:27 time: 0.4098 data_time: 0.1789 memory: 7850 loss_ce: 0.0367 loss: 0.0367 2022/09/16 14:17:49 - mmengine - INFO - Epoch(train) [1][32500/42151] lr: 3.0000e-04 eta: 1 day, 0:49:13 time: 0.3704 data_time: 0.1361 memory: 7850 loss_ce: 0.0345 loss: 0.0345 2022/09/16 14:18:23 - mmengine - INFO - Epoch(train) [1][32600/42151] lr: 3.0000e-04 eta: 1 day, 0:47:53 time: 0.3287 data_time: 0.1064 memory: 7850 loss_ce: 0.0365 loss: 0.0365 2022/09/16 14:19:00 - mmengine - INFO - Epoch(train) [1][32700/42151] lr: 3.0000e-04 eta: 1 day, 0:46:43 time: 0.4134 data_time: 0.1677 memory: 7850 loss_ce: 0.0334 loss: 0.0334 2022/09/16 14:19:35 - mmengine - INFO - Epoch(train) [1][32800/42151] lr: 3.0000e-04 eta: 1 day, 0:45:27 time: 0.3647 data_time: 0.1408 memory: 7850 loss_ce: 0.0384 loss: 0.0384 2022/09/16 14:20:10 - mmengine - INFO - Epoch(train) [1][32900/42151] lr: 3.0000e-04 eta: 1 day, 0:44:08 time: 0.3102 data_time: 0.1074 memory: 7850 loss_ce: 0.0347 loss: 0.0347 2022/09/16 14:20:45 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:20:45 - mmengine - INFO - Epoch(train) [1][33000/42151] lr: 3.0000e-04 eta: 1 day, 0:42:51 time: 0.3532 data_time: 0.1346 memory: 7850 loss_ce: 0.0347 loss: 0.0347 2022/09/16 14:21:20 - mmengine - INFO - Epoch(train) [1][33100/42151] lr: 3.0000e-04 eta: 1 day, 0:41:38 time: 0.3852 data_time: 0.1820 memory: 7850 loss_ce: 0.0377 loss: 0.0377 2022/09/16 14:21:55 - mmengine - INFO - Epoch(train) [1][33200/42151] lr: 3.0000e-04 eta: 1 day, 0:40:19 time: 0.3606 data_time: 0.1536 memory: 7850 loss_ce: 0.0344 loss: 0.0344 2022/09/16 14:22:30 - mmengine - INFO - Epoch(train) [1][33300/42151] lr: 3.0000e-04 eta: 1 day, 0:39:03 time: 0.3771 data_time: 0.1718 memory: 7850 loss_ce: 0.0336 loss: 0.0336 2022/09/16 14:23:06 - mmengine - INFO - Epoch(train) [1][33400/42151] lr: 3.0000e-04 eta: 1 day, 0:37:52 time: 0.3365 data_time: 0.1377 memory: 7850 loss_ce: 0.0348 loss: 0.0348 2022/09/16 14:23:41 - mmengine - INFO - Epoch(train) [1][33500/42151] lr: 3.0000e-04 eta: 1 day, 0:36:37 time: 0.3081 data_time: 0.0848 memory: 7850 loss_ce: 0.0352 loss: 0.0352 2022/09/16 14:24:16 - mmengine - INFO - Epoch(train) [1][33600/42151] lr: 3.0000e-04 eta: 1 day, 0:35:22 time: 0.3635 data_time: 0.1643 memory: 7850 loss_ce: 0.0328 loss: 0.0328 2022/09/16 14:24:51 - mmengine - INFO - Epoch(train) [1][33700/42151] lr: 3.0000e-04 eta: 1 day, 0:34:08 time: 0.4076 data_time: 0.1513 memory: 7850 loss_ce: 0.0371 loss: 0.0371 2022/09/16 14:25:25 - mmengine - INFO - Epoch(train) [1][33800/42151] lr: 3.0000e-04 eta: 1 day, 0:32:48 time: 0.3437 data_time: 0.1277 memory: 7850 loss_ce: 0.0363 loss: 0.0363 2022/09/16 14:26:00 - mmengine - INFO - Epoch(train) [1][33900/42151] lr: 3.0000e-04 eta: 1 day, 0:31:32 time: 0.3868 data_time: 0.1626 memory: 7850 loss_ce: 0.0347 loss: 0.0347 2022/09/16 14:26:34 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:26:34 - mmengine - INFO - Epoch(train) [1][34000/42151] lr: 3.0000e-04 eta: 1 day, 0:30:13 time: 0.3410 data_time: 0.0992 memory: 7850 loss_ce: 0.0351 loss: 0.0351 2022/09/16 14:27:09 - mmengine - INFO - Epoch(train) [1][34100/42151] lr: 3.0000e-04 eta: 1 day, 0:28:54 time: 0.3357 data_time: 0.1133 memory: 7850 loss_ce: 0.0350 loss: 0.0350 2022/09/16 14:27:44 - mmengine - INFO - Epoch(train) [1][34200/42151] lr: 3.0000e-04 eta: 1 day, 0:27:39 time: 0.3602 data_time: 0.1375 memory: 7850 loss_ce: 0.0376 loss: 0.0376 2022/09/16 14:28:19 - mmengine - INFO - Epoch(train) [1][34300/42151] lr: 3.0000e-04 eta: 1 day, 0:26:28 time: 0.3917 data_time: 0.1707 memory: 7850 loss_ce: 0.0366 loss: 0.0366 2022/09/16 14:28:53 - mmengine - INFO - Epoch(train) [1][34400/42151] lr: 3.0000e-04 eta: 1 day, 0:25:06 time: 0.3548 data_time: 0.1515 memory: 7850 loss_ce: 0.0365 loss: 0.0365 2022/09/16 14:29:28 - mmengine - INFO - Epoch(train) [1][34500/42151] lr: 3.0000e-04 eta: 1 day, 0:23:53 time: 0.3726 data_time: 0.1613 memory: 7850 loss_ce: 0.0378 loss: 0.0378 2022/09/16 14:30:03 - mmengine - INFO - Epoch(train) [1][34600/42151] lr: 3.0000e-04 eta: 1 day, 0:22:38 time: 0.3631 data_time: 0.1502 memory: 7850 loss_ce: 0.0380 loss: 0.0380 2022/09/16 14:30:38 - mmengine - INFO - Epoch(train) [1][34700/42151] lr: 3.0000e-04 eta: 1 day, 0:21:27 time: 0.3613 data_time: 0.1314 memory: 7850 loss_ce: 0.0329 loss: 0.0329 2022/09/16 14:31:13 - mmengine - INFO - Epoch(train) [1][34800/42151] lr: 3.0000e-04 eta: 1 day, 0:20:14 time: 0.3394 data_time: 0.1130 memory: 7850 loss_ce: 0.0352 loss: 0.0352 2022/09/16 14:31:48 - mmengine - INFO - Epoch(train) [1][34900/42151] lr: 3.0000e-04 eta: 1 day, 0:19:03 time: 0.4015 data_time: 0.1786 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:32:23 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:32:23 - mmengine - INFO - Epoch(train) [1][35000/42151] lr: 3.0000e-04 eta: 1 day, 0:17:48 time: 0.3492 data_time: 0.1528 memory: 7850 loss_ce: 0.0328 loss: 0.0328 2022/09/16 14:32:58 - mmengine - INFO - Epoch(train) [1][35100/42151] lr: 3.0000e-04 eta: 1 day, 0:16:36 time: 0.3584 data_time: 0.1489 memory: 7850 loss_ce: 0.0359 loss: 0.0359 2022/09/16 14:33:32 - mmengine - INFO - Epoch(train) [1][35200/42151] lr: 3.0000e-04 eta: 1 day, 0:15:21 time: 0.2975 data_time: 0.0963 memory: 7850 loss_ce: 0.0345 loss: 0.0345 2022/09/16 14:34:08 - mmengine - INFO - Epoch(train) [1][35300/42151] lr: 3.0000e-04 eta: 1 day, 0:14:15 time: 0.3557 data_time: 0.1321 memory: 7850 loss_ce: 0.0347 loss: 0.0347 2022/09/16 14:34:43 - mmengine - INFO - Epoch(train) [1][35400/42151] lr: 3.0000e-04 eta: 1 day, 0:13:06 time: 0.3409 data_time: 0.1057 memory: 7850 loss_ce: 0.0350 loss: 0.0350 2022/09/16 14:35:20 - mmengine - INFO - Epoch(train) [1][35500/42151] lr: 3.0000e-04 eta: 1 day, 0:12:01 time: 0.4300 data_time: 0.1966 memory: 7850 loss_ce: 0.0364 loss: 0.0364 2022/09/16 14:35:53 - mmengine - INFO - Epoch(train) [1][35600/42151] lr: 3.0000e-04 eta: 1 day, 0:10:43 time: 0.3583 data_time: 0.1520 memory: 7850 loss_ce: 0.0313 loss: 0.0313 2022/09/16 14:36:29 - mmengine - INFO - Epoch(train) [1][35700/42151] lr: 3.0000e-04 eta: 1 day, 0:09:34 time: 0.3645 data_time: 0.1587 memory: 7850 loss_ce: 0.0342 loss: 0.0342 2022/09/16 14:37:03 - mmengine - INFO - Epoch(train) [1][35800/42151] lr: 3.0000e-04 eta: 1 day, 0:08:19 time: 0.3403 data_time: 0.1232 memory: 7850 loss_ce: 0.0361 loss: 0.0361 2022/09/16 14:37:37 - mmengine - INFO - Epoch(train) [1][35900/42151] lr: 3.0000e-04 eta: 1 day, 0:07:04 time: 0.3600 data_time: 0.1287 memory: 7850 loss_ce: 0.0369 loss: 0.0369 2022/09/16 14:38:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:38:13 - mmengine - INFO - Epoch(train) [1][36000/42151] lr: 3.0000e-04 eta: 1 day, 0:05:55 time: 0.3718 data_time: 0.1058 memory: 7850 loss_ce: 0.0347 loss: 0.0347 2022/09/16 14:38:48 - mmengine - INFO - Epoch(train) [1][36100/42151] lr: 3.0000e-04 eta: 1 day, 0:04:50 time: 0.4080 data_time: 0.1826 memory: 7850 loss_ce: 0.0341 loss: 0.0341 2022/09/16 14:39:23 - mmengine - INFO - Epoch(train) [1][36200/42151] lr: 3.0000e-04 eta: 1 day, 0:03:38 time: 0.3644 data_time: 0.1434 memory: 7850 loss_ce: 0.0342 loss: 0.0342 2022/09/16 14:39:58 - mmengine - INFO - Epoch(train) [1][36300/42151] lr: 3.0000e-04 eta: 1 day, 0:02:28 time: 0.3576 data_time: 0.1550 memory: 7850 loss_ce: 0.0364 loss: 0.0364 2022/09/16 14:40:33 - mmengine - INFO - Epoch(train) [1][36400/42151] lr: 3.0000e-04 eta: 1 day, 0:01:20 time: 0.3129 data_time: 0.1044 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:41:08 - mmengine - INFO - Epoch(train) [1][36500/42151] lr: 3.0000e-04 eta: 1 day, 0:00:13 time: 0.3511 data_time: 0.1156 memory: 7850 loss_ce: 0.0317 loss: 0.0317 2022/09/16 14:41:44 - mmengine - INFO - Epoch(train) [1][36600/42151] lr: 3.0000e-04 eta: 23:59:04 time: 0.3197 data_time: 0.0956 memory: 7850 loss_ce: 0.0354 loss: 0.0354 2022/09/16 14:42:19 - mmengine - INFO - Epoch(train) [1][36700/42151] lr: 3.0000e-04 eta: 23:57:59 time: 0.4032 data_time: 0.1713 memory: 7850 loss_ce: 0.0322 loss: 0.0322 2022/09/16 14:42:53 - mmengine - INFO - Epoch(train) [1][36800/42151] lr: 3.0000e-04 eta: 23:56:45 time: 0.3362 data_time: 0.1360 memory: 7850 loss_ce: 0.0351 loss: 0.0351 2022/09/16 14:43:27 - mmengine - INFO - Epoch(train) [1][36900/42151] lr: 3.0000e-04 eta: 23:55:30 time: 0.3586 data_time: 0.1631 memory: 7850 loss_ce: 0.0356 loss: 0.0356 2022/09/16 14:44:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:44:02 - mmengine - INFO - Epoch(train) [1][37000/42151] lr: 3.0000e-04 eta: 23:54:18 time: 0.3175 data_time: 0.1164 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:44:36 - mmengine - INFO - Epoch(train) [1][37100/42151] lr: 3.0000e-04 eta: 23:53:06 time: 0.3433 data_time: 0.1198 memory: 7850 loss_ce: 0.0335 loss: 0.0335 2022/09/16 14:45:11 - mmengine - INFO - Epoch(train) [1][37200/42151] lr: 3.0000e-04 eta: 23:52:00 time: 0.3330 data_time: 0.1101 memory: 7850 loss_ce: 0.0360 loss: 0.0360 2022/09/16 14:45:46 - mmengine - INFO - Epoch(train) [1][37300/42151] lr: 3.0000e-04 eta: 23:50:51 time: 0.3839 data_time: 0.1553 memory: 7850 loss_ce: 0.0314 loss: 0.0314 2022/09/16 14:46:21 - mmengine - INFO - Epoch(train) [1][37400/42151] lr: 3.0000e-04 eta: 23:49:40 time: 0.3708 data_time: 0.1358 memory: 7850 loss_ce: 0.0356 loss: 0.0356 2022/09/16 14:46:55 - mmengine - INFO - Epoch(train) [1][37500/42151] lr: 3.0000e-04 eta: 23:48:30 time: 0.3881 data_time: 0.1824 memory: 7850 loss_ce: 0.0361 loss: 0.0361 2022/09/16 14:47:30 - mmengine - INFO - Epoch(train) [1][37600/42151] lr: 3.0000e-04 eta: 23:47:21 time: 0.3035 data_time: 0.0995 memory: 7850 loss_ce: 0.0306 loss: 0.0306 2022/09/16 14:48:04 - mmengine - INFO - Epoch(train) [1][37700/42151] lr: 3.0000e-04 eta: 23:46:12 time: 0.3622 data_time: 0.1163 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:48:39 - mmengine - INFO - Epoch(train) [1][37800/42151] lr: 3.0000e-04 eta: 23:45:01 time: 0.3362 data_time: 0.1031 memory: 7850 loss_ce: 0.0342 loss: 0.0342 2022/09/16 14:49:14 - mmengine - INFO - Epoch(train) [1][37900/42151] lr: 3.0000e-04 eta: 23:43:55 time: 0.4171 data_time: 0.1776 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:49:48 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:49:48 - mmengine - INFO - Epoch(train) [1][38000/42151] lr: 3.0000e-04 eta: 23:42:44 time: 0.3498 data_time: 0.1453 memory: 7850 loss_ce: 0.0352 loss: 0.0352 2022/09/16 14:50:22 - mmengine - INFO - Epoch(train) [1][38100/42151] lr: 3.0000e-04 eta: 23:41:32 time: 0.3983 data_time: 0.1739 memory: 7850 loss_ce: 0.0342 loss: 0.0342 2022/09/16 14:50:57 - mmengine - INFO - Epoch(train) [1][38200/42151] lr: 3.0000e-04 eta: 23:40:23 time: 0.3022 data_time: 0.0954 memory: 7850 loss_ce: 0.0352 loss: 0.0352 2022/09/16 14:51:31 - mmengine - INFO - Epoch(train) [1][38300/42151] lr: 3.0000e-04 eta: 23:39:15 time: 0.3577 data_time: 0.1133 memory: 7850 loss_ce: 0.0353 loss: 0.0353 2022/09/16 14:52:06 - mmengine - INFO - Epoch(train) [1][38400/42151] lr: 3.0000e-04 eta: 23:38:08 time: 0.3765 data_time: 0.1142 memory: 7850 loss_ce: 0.0331 loss: 0.0331 2022/09/16 14:52:42 - mmengine - INFO - Epoch(train) [1][38500/42151] lr: 3.0000e-04 eta: 23:37:06 time: 0.4127 data_time: 0.1674 memory: 7850 loss_ce: 0.0356 loss: 0.0356 2022/09/16 14:53:16 - mmengine - INFO - Epoch(train) [1][38600/42151] lr: 3.0000e-04 eta: 23:35:57 time: 0.3502 data_time: 0.1455 memory: 7850 loss_ce: 0.0325 loss: 0.0325 2022/09/16 14:53:51 - mmengine - INFO - Epoch(train) [1][38700/42151] lr: 3.0000e-04 eta: 23:34:50 time: 0.3579 data_time: 0.1558 memory: 7850 loss_ce: 0.0337 loss: 0.0337 2022/09/16 14:54:25 - mmengine - INFO - Epoch(train) [1][38800/42151] lr: 3.0000e-04 eta: 23:33:42 time: 0.2879 data_time: 0.0919 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:55:00 - mmengine - INFO - Epoch(train) [1][38900/42151] lr: 3.0000e-04 eta: 23:32:36 time: 0.3350 data_time: 0.1105 memory: 7850 loss_ce: 0.0309 loss: 0.0309 2022/09/16 14:55:36 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 14:55:36 - mmengine - INFO - Epoch(train) [1][39000/42151] lr: 3.0000e-04 eta: 23:31:36 time: 0.3357 data_time: 0.1112 memory: 7850 loss_ce: 0.0342 loss: 0.0342 2022/09/16 14:56:12 - mmengine - INFO - Epoch(train) [1][39100/42151] lr: 3.0000e-04 eta: 23:30:34 time: 0.3890 data_time: 0.1620 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 14:56:46 - mmengine - INFO - Epoch(train) [1][39200/42151] lr: 3.0000e-04 eta: 23:29:28 time: 0.3462 data_time: 0.1487 memory: 7850 loss_ce: 0.0309 loss: 0.0309 2022/09/16 14:57:22 - mmengine - INFO - Epoch(train) [1][39300/42151] lr: 3.0000e-04 eta: 23:28:29 time: 0.4171 data_time: 0.1754 memory: 7850 loss_ce: 0.0335 loss: 0.0335 2022/09/16 14:57:57 - mmengine - INFO - Epoch(train) [1][39400/42151] lr: 3.0000e-04 eta: 23:27:21 time: 0.2964 data_time: 0.0953 memory: 7850 loss_ce: 0.0332 loss: 0.0332 2022/09/16 14:58:32 - mmengine - INFO - Epoch(train) [1][39500/42151] lr: 3.0000e-04 eta: 23:26:17 time: 0.3480 data_time: 0.1170 memory: 7850 loss_ce: 0.0328 loss: 0.0328 2022/09/16 14:59:07 - mmengine - INFO - Epoch(train) [1][39600/42151] lr: 3.0000e-04 eta: 23:25:13 time: 0.3354 data_time: 0.1080 memory: 7850 loss_ce: 0.0318 loss: 0.0318 2022/09/16 14:59:43 - mmengine - INFO - Epoch(train) [1][39700/42151] lr: 3.0000e-04 eta: 23:24:13 time: 0.4003 data_time: 0.1713 memory: 7850 loss_ce: 0.0325 loss: 0.0325 2022/09/16 15:00:18 - mmengine - INFO - Epoch(train) [1][39800/42151] lr: 3.0000e-04 eta: 23:23:10 time: 0.3628 data_time: 0.1545 memory: 7850 loss_ce: 0.0297 loss: 0.0297 2022/09/16 15:00:52 - mmengine - INFO - Epoch(train) [1][39900/42151] lr: 3.0000e-04 eta: 23:22:02 time: 0.3918 data_time: 0.1564 memory: 7850 loss_ce: 0.0338 loss: 0.0338 2022/09/16 15:01:25 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 15:01:25 - mmengine - INFO - Epoch(train) [1][40000/42151] lr: 3.0000e-04 eta: 23:20:51 time: 0.2964 data_time: 0.0989 memory: 7850 loss_ce: 0.0324 loss: 0.0324 2022/09/16 15:02:00 - mmengine - INFO - Epoch(train) [1][40100/42151] lr: 3.0000e-04 eta: 23:19:43 time: 0.3520 data_time: 0.1185 memory: 7850 loss_ce: 0.0336 loss: 0.0336 2022/09/16 15:02:35 - mmengine - INFO - Epoch(train) [1][40200/42151] lr: 3.0000e-04 eta: 23:18:42 time: 0.3881 data_time: 0.1312 memory: 7850 loss_ce: 0.0335 loss: 0.0335 2022/09/16 15:03:11 - mmengine - INFO - Epoch(train) [1][40300/42151] lr: 3.0000e-04 eta: 23:17:44 time: 0.4380 data_time: 0.1992 memory: 7850 loss_ce: 0.0313 loss: 0.0313 2022/09/16 15:03:46 - mmengine - INFO - Epoch(train) [1][40400/42151] lr: 3.0000e-04 eta: 23:16:42 time: 0.3524 data_time: 0.1426 memory: 7850 loss_ce: 0.0329 loss: 0.0329 2022/09/16 15:04:21 - mmengine - INFO - Epoch(train) [1][40500/42151] lr: 3.0000e-04 eta: 23:15:41 time: 0.3645 data_time: 0.1635 memory: 7850 loss_ce: 0.0359 loss: 0.0359 2022/09/16 15:04:56 - mmengine - INFO - Epoch(train) [1][40600/42151] lr: 3.0000e-04 eta: 23:14:36 time: 0.2908 data_time: 0.0931 memory: 7850 loss_ce: 0.0328 loss: 0.0328 2022/09/16 15:05:32 - mmengine - INFO - Epoch(train) [1][40700/42151] lr: 3.0000e-04 eta: 23:13:38 time: 0.3370 data_time: 0.1174 memory: 7850 loss_ce: 0.0341 loss: 0.0341 2022/09/16 15:06:08 - mmengine - INFO - Epoch(train) [1][40800/42151] lr: 3.0000e-04 eta: 23:12:40 time: 0.3370 data_time: 0.1042 memory: 7850 loss_ce: 0.0352 loss: 0.0352 2022/09/16 15:06:44 - mmengine - INFO - Epoch(train) [1][40900/42151] lr: 3.0000e-04 eta: 23:11:44 time: 0.4144 data_time: 0.1790 memory: 7850 loss_ce: 0.0340 loss: 0.0340 2022/09/16 15:07:18 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 15:07:18 - mmengine - INFO - Epoch(train) [1][41000/42151] lr: 3.0000e-04 eta: 23:10:39 time: 0.3607 data_time: 0.1645 memory: 7850 loss_ce: 0.0320 loss: 0.0320 2022/09/16 15:07:53 - mmengine - INFO - Epoch(train) [1][41100/42151] lr: 3.0000e-04 eta: 23:09:35 time: 0.3830 data_time: 0.1732 memory: 7850 loss_ce: 0.0331 loss: 0.0331 2022/09/16 15:08:28 - mmengine - INFO - Epoch(train) [1][41200/42151] lr: 3.0000e-04 eta: 23:08:31 time: 0.3440 data_time: 0.1276 memory: 7850 loss_ce: 0.0303 loss: 0.0303 2022/09/16 15:09:03 - mmengine - INFO - Epoch(train) [1][41300/42151] lr: 3.0000e-04 eta: 23:07:29 time: 0.3520 data_time: 0.1245 memory: 7850 loss_ce: 0.0367 loss: 0.0367 2022/09/16 15:09:38 - mmengine - INFO - Epoch(train) [1][41400/42151] lr: 3.0000e-04 eta: 23:06:28 time: 0.3205 data_time: 0.0982 memory: 7850 loss_ce: 0.0347 loss: 0.0347 2022/09/16 15:10:13 - mmengine - INFO - Epoch(train) [1][41500/42151] lr: 3.0000e-04 eta: 23:05:30 time: 0.3746 data_time: 0.1495 memory: 7850 loss_ce: 0.0343 loss: 0.0343 2022/09/16 15:10:48 - mmengine - INFO - Epoch(train) [1][41600/42151] lr: 3.0000e-04 eta: 23:04:27 time: 0.3881 data_time: 0.1740 memory: 7850 loss_ce: 0.0332 loss: 0.0332 2022/09/16 15:11:23 - mmengine - INFO - Epoch(train) [1][41700/42151] lr: 3.0000e-04 eta: 23:03:28 time: 0.4172 data_time: 0.1985 memory: 7850 loss_ce: 0.0316 loss: 0.0316 2022/09/16 15:11:58 - mmengine - INFO - Epoch(train) [1][41800/42151] lr: 3.0000e-04 eta: 23:02:26 time: 0.3190 data_time: 0.1190 memory: 7850 loss_ce: 0.0299 loss: 0.0299 2022/09/16 15:12:34 - mmengine - INFO - Epoch(train) [1][41900/42151] lr: 3.0000e-04 eta: 23:01:31 time: 0.3995 data_time: 0.1592 memory: 7850 loss_ce: 0.0313 loss: 0.0313 2022/09/16 15:13:09 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 15:13:09 - mmengine - INFO - Epoch(train) [1][42000/42151] lr: 3.0000e-04 eta: 23:00:29 time: 0.3443 data_time: 0.1125 memory: 7850 loss_ce: 0.0306 loss: 0.0306 2022/09/16 15:13:46 - mmengine - INFO - Epoch(train) [1][42100/42151] lr: 3.0000e-04 eta: 22:59:37 time: 0.4219 data_time: 0.1838 memory: 7850 loss_ce: 0.0315 loss: 0.0315 2022/09/16 15:14:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 15:14:02 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/09/16 15:17:05 - mmengine - INFO - Epoch(val) [1][100/7672] eta: 0:37:52 time: 0.3001 data_time: 0.0012 memory: 7850 2022/09/16 15:17:36 - mmengine - INFO - Epoch(val) [1][200/7672] eta: 0:37:42 time: 0.3028 data_time: 0.0017 memory: 580 2022/09/16 15:18:06 - mmengine - INFO - Epoch(val) [1][300/7672] eta: 0:25:47 time: 0.2099 data_time: 0.0018 memory: 580 2022/09/16 15:18:27 - mmengine - INFO - Epoch(val) [1][400/7672] eta: 0:23:33 time: 0.1944 data_time: 0.0007 memory: 580 2022/09/16 15:18:50 - mmengine - INFO - Epoch(val) [1][500/7672] eta: 0:29:06 time: 0.2435 data_time: 0.0009 memory: 580 2022/09/16 15:19:11 - mmengine - INFO - Epoch(val) [1][600/7672] eta: 0:23:45 time: 0.2016 data_time: 0.0007 memory: 580 2022/09/16 15:19:32 - mmengine - INFO - Epoch(val) [1][700/7672] eta: 0:23:24 time: 0.2014 data_time: 0.0007 memory: 580 2022/09/16 15:19:55 - mmengine - INFO - Epoch(val) [1][800/7672] eta: 0:24:45 time: 0.2162 data_time: 0.0010 memory: 580 2022/09/16 15:20:17 - mmengine - INFO - Epoch(val) [1][900/7672] eta: 0:28:39 time: 0.2538 data_time: 0.0009 memory: 580 2022/09/16 15:20:38 - mmengine - INFO - Epoch(val) [1][1000/7672] eta: 0:23:34 time: 0.2119 data_time: 0.0008 memory: 580 2022/09/16 15:20:59 - mmengine - INFO - Epoch(val) [1][1100/7672] eta: 0:22:05 time: 0.2017 data_time: 0.0026 memory: 580 2022/09/16 15:21:21 - mmengine - INFO - Epoch(val) [1][1200/7672] eta: 0:21:24 time: 0.1984 data_time: 0.0008 memory: 580 2022/09/16 15:21:42 - mmengine - INFO - Epoch(val) [1][1300/7672] eta: 0:25:20 time: 0.2387 data_time: 0.0009 memory: 580 2022/09/16 15:22:03 - mmengine - INFO - Epoch(val) [1][1400/7672] eta: 0:21:27 time: 0.2052 data_time: 0.0008 memory: 580 2022/09/16 15:22:25 - mmengine - INFO - Epoch(val) [1][1500/7672] eta: 0:26:37 time: 0.2589 data_time: 0.0020 memory: 580 2022/09/16 15:22:46 - mmengine - INFO - Epoch(val) [1][1600/7672] eta: 0:23:29 time: 0.2321 data_time: 0.0008 memory: 580 2022/09/16 15:23:07 - mmengine - INFO - Epoch(val) [1][1700/7672] eta: 0:19:51 time: 0.1995 data_time: 0.0008 memory: 580 2022/09/16 15:23:29 - mmengine - INFO - Epoch(val) [1][1800/7672] eta: 0:20:00 time: 0.2044 data_time: 0.0008 memory: 580 2022/09/16 15:23:51 - mmengine - INFO - Epoch(val) [1][1900/7672] eta: 0:19:01 time: 0.1978 data_time: 0.0007 memory: 580 2022/09/16 15:24:11 - mmengine - INFO - Epoch(val) [1][2000/7672] eta: 0:18:54 time: 0.2000 data_time: 0.0007 memory: 580 2022/09/16 15:24:33 - mmengine - INFO - Epoch(val) [1][2100/7672] eta: 0:18:54 time: 0.2037 data_time: 0.0007 memory: 580 2022/09/16 15:24:55 - mmengine - INFO - Epoch(val) [1][2200/7672] eta: 0:17:56 time: 0.1967 data_time: 0.0008 memory: 580 2022/09/16 15:25:15 - mmengine - INFO - Epoch(val) [1][2300/7672] eta: 0:19:05 time: 0.2133 data_time: 0.0008 memory: 580 2022/09/16 15:25:36 - mmengine - INFO - Epoch(val) [1][2400/7672] eta: 0:17:53 time: 0.2037 data_time: 0.0023 memory: 580 2022/09/16 15:25:57 - mmengine - INFO - Epoch(val) [1][2500/7672] eta: 0:16:53 time: 0.1960 data_time: 0.0007 memory: 580 2022/09/16 15:26:18 - mmengine - INFO - Epoch(val) [1][2600/7672] eta: 0:17:56 time: 0.2123 data_time: 0.0008 memory: 580 2022/09/16 15:26:40 - mmengine - INFO - Epoch(val) [1][2700/7672] eta: 0:16:25 time: 0.1983 data_time: 0.0013 memory: 580 2022/09/16 15:27:01 - mmengine - INFO - Epoch(val) [1][2800/7672] eta: 0:16:21 time: 0.2014 data_time: 0.0007 memory: 580 2022/09/16 15:27:22 - mmengine - INFO - Epoch(val) [1][2900/7672] eta: 0:15:52 time: 0.1997 data_time: 0.0007 memory: 580 2022/09/16 15:27:43 - mmengine - INFO - Epoch(val) [1][3000/7672] eta: 0:16:29 time: 0.2117 data_time: 0.0010 memory: 580 2022/09/16 15:28:05 - mmengine - INFO - Epoch(val) [1][3100/7672] eta: 0:19:06 time: 0.2508 data_time: 0.0009 memory: 580 2022/09/16 15:28:26 - mmengine - INFO - Epoch(val) [1][3200/7672] eta: 0:15:02 time: 0.2017 data_time: 0.0008 memory: 580 2022/09/16 15:28:48 - mmengine - INFO - Epoch(val) [1][3300/7672] eta: 0:15:34 time: 0.2138 data_time: 0.0009 memory: 580 2022/09/16 15:29:09 - mmengine - INFO - Epoch(val) [1][3400/7672] eta: 0:14:57 time: 0.2101 data_time: 0.0018 memory: 580 2022/09/16 15:29:30 - mmengine - INFO - Epoch(val) [1][3500/7672] eta: 0:13:55 time: 0.2001 data_time: 0.0008 memory: 580 2022/09/16 15:29:52 - mmengine - INFO - Epoch(val) [1][3600/7672] eta: 0:14:49 time: 0.2184 data_time: 0.0013 memory: 580 2022/09/16 15:30:13 - mmengine - INFO - Epoch(val) [1][3700/7672] eta: 0:13:12 time: 0.1995 data_time: 0.0008 memory: 580 2022/09/16 15:30:34 - mmengine - INFO - Epoch(val) [1][3800/7672] eta: 0:13:42 time: 0.2124 data_time: 0.0008 memory: 580 2022/09/16 15:30:55 - mmengine - INFO - Epoch(val) [1][3900/7672] eta: 0:13:50 time: 0.2202 data_time: 0.0021 memory: 580 2022/09/16 15:31:17 - mmengine - INFO - Epoch(val) [1][4000/7672] eta: 0:13:03 time: 0.2134 data_time: 0.0008 memory: 580 2022/09/16 15:31:38 - mmengine - INFO - Epoch(val) [1][4100/7672] eta: 0:12:12 time: 0.2050 data_time: 0.0021 memory: 580 2022/09/16 15:32:00 - mmengine - INFO - Epoch(val) [1][4200/7672] eta: 0:11:57 time: 0.2067 data_time: 0.0008 memory: 580 2022/09/16 15:32:22 - mmengine - INFO - Epoch(val) [1][4300/7672] eta: 0:12:40 time: 0.2255 data_time: 0.0007 memory: 580 2022/09/16 15:32:43 - mmengine - INFO - Epoch(val) [1][4400/7672] eta: 0:10:55 time: 0.2005 data_time: 0.0007 memory: 580 2022/09/16 15:33:04 - mmengine - INFO - Epoch(val) [1][4500/7672] eta: 0:11:10 time: 0.2115 data_time: 0.0008 memory: 580 2022/09/16 15:33:26 - mmengine - INFO - Epoch(val) [1][4600/7672] eta: 0:12:04 time: 0.2359 data_time: 0.0029 memory: 580 2022/09/16 15:33:48 - mmengine - INFO - Epoch(val) [1][4700/7672] eta: 0:10:54 time: 0.2203 data_time: 0.0015 memory: 580 2022/09/16 15:34:09 - mmengine - INFO - Epoch(val) [1][4800/7672] eta: 0:09:42 time: 0.2029 data_time: 0.0008 memory: 580 2022/09/16 15:34:30 - mmengine - INFO - Epoch(val) [1][4900/7672] eta: 0:09:40 time: 0.2094 data_time: 0.0007 memory: 580 2022/09/16 15:34:51 - mmengine - INFO - Epoch(val) [1][5000/7672] eta: 0:09:58 time: 0.2240 data_time: 0.0010 memory: 580 2022/09/16 15:35:12 - mmengine - INFO - Epoch(val) [1][5100/7672] eta: 0:08:35 time: 0.2005 data_time: 0.0008 memory: 580 2022/09/16 15:35:33 - mmengine - INFO - Epoch(val) [1][5200/7672] eta: 0:08:09 time: 0.1981 data_time: 0.0008 memory: 580 2022/09/16 15:35:54 - mmengine - INFO - Epoch(val) [1][5300/7672] eta: 0:07:48 time: 0.1975 data_time: 0.0007 memory: 580 2022/09/16 15:36:14 - mmengine - INFO - Epoch(val) [1][5400/7672] eta: 0:07:28 time: 0.1974 data_time: 0.0007 memory: 580 2022/09/16 15:36:35 - mmengine - INFO - Epoch(val) [1][5500/7672] eta: 0:07:04 time: 0.1953 data_time: 0.0008 memory: 580 2022/09/16 15:36:56 - mmengine - INFO - Epoch(val) [1][5600/7672] eta: 0:08:47 time: 0.2545 data_time: 0.0031 memory: 580 2022/09/16 15:37:17 - mmengine - INFO - Epoch(val) [1][5700/7672] eta: 0:06:34 time: 0.2000 data_time: 0.0021 memory: 580 2022/09/16 15:37:38 - mmengine - INFO - Epoch(val) [1][5800/7672] eta: 0:06:15 time: 0.2005 data_time: 0.0007 memory: 580 2022/09/16 15:38:00 - mmengine - INFO - Epoch(val) [1][5900/7672] eta: 0:06:04 time: 0.2055 data_time: 0.0007 memory: 580 2022/09/16 15:38:22 - mmengine - INFO - Epoch(val) [1][6000/7672] eta: 0:06:18 time: 0.2261 data_time: 0.0009 memory: 580 2022/09/16 15:38:43 - mmengine - INFO - Epoch(val) [1][6100/7672] eta: 0:05:31 time: 0.2111 data_time: 0.0011 memory: 580 2022/09/16 15:39:05 - mmengine - INFO - Epoch(val) [1][6200/7672] eta: 0:05:23 time: 0.2196 data_time: 0.0008 memory: 580 2022/09/16 15:39:27 - mmengine - INFO - Epoch(val) [1][6300/7672] eta: 0:05:09 time: 0.2257 data_time: 0.0030 memory: 580 2022/09/16 15:39:48 - mmengine - INFO - Epoch(val) [1][6400/7672] eta: 0:05:36 time: 0.2642 data_time: 0.0017 memory: 580 2022/09/16 15:40:09 - mmengine - INFO - Epoch(val) [1][6500/7672] eta: 0:03:51 time: 0.1975 data_time: 0.0007 memory: 580 2022/09/16 15:40:31 - mmengine - INFO - Epoch(val) [1][6600/7672] eta: 0:03:37 time: 0.2025 data_time: 0.0008 memory: 580 2022/09/16 15:40:52 - mmengine - INFO - Epoch(val) [1][6700/7672] eta: 0:03:11 time: 0.1975 data_time: 0.0007 memory: 580 2022/09/16 15:41:14 - mmengine - INFO - Epoch(val) [1][6800/7672] eta: 0:02:51 time: 0.1965 data_time: 0.0007 memory: 580 2022/09/16 15:41:35 - mmengine - INFO - Epoch(val) [1][6900/7672] eta: 0:02:49 time: 0.2200 data_time: 0.0009 memory: 580 2022/09/16 15:41:56 - mmengine - INFO - Epoch(val) [1][7000/7672] eta: 0:02:28 time: 0.2207 data_time: 0.0009 memory: 580 2022/09/16 15:42:17 - mmengine - INFO - Epoch(val) [1][7100/7672] eta: 0:02:01 time: 0.2127 data_time: 0.0008 memory: 580 2022/09/16 15:42:39 - mmengine - INFO - Epoch(val) [1][7200/7672] eta: 0:01:32 time: 0.1964 data_time: 0.0007 memory: 580 2022/09/16 15:43:00 - mmengine - INFO - Epoch(val) [1][7300/7672] eta: 0:01:16 time: 0.2062 data_time: 0.0008 memory: 580 2022/09/16 15:43:21 - mmengine - INFO - Epoch(val) [1][7400/7672] eta: 0:00:58 time: 0.2166 data_time: 0.0008 memory: 580 2022/09/16 15:43:43 - mmengine - INFO - Epoch(val) [1][7500/7672] eta: 0:00:34 time: 0.1982 data_time: 0.0008 memory: 580 2022/09/16 15:44:04 - mmengine - INFO - Epoch(val) [1][7600/7672] eta: 0:00:14 time: 0.1990 data_time: 0.0008 memory: 580 2022/09/16 15:44:20 - mmengine - INFO - Epoch(val) [1][7672/7672] CUTE80/recog/word_acc_ignore_case_symbol: 0.6701 IIIT5K/recog/word_acc_ignore_case_symbol: 0.8607 SVT/recog/word_acc_ignore_case_symbol: 0.8207 SVTP/recog/word_acc_ignore_case_symbol: 0.6496 IC13/recog/word_acc_ignore_case_symbol: 0.8887 IC15/recog/word_acc_ignore_case_symbol: 0.6505 2022/09/16 15:45:09 - mmengine - INFO - Epoch(train) [2][100/42151] lr: 3.0000e-04 eta: 22:59:00 time: 0.2116 data_time: 0.0135 memory: 7851 loss_ce: 0.0311 loss: 0.0311 2022/09/16 15:46:20 - mmengine - INFO - Epoch(train) [2][200/42151] lr: 3.0000e-04 eta: 23:01:01 time: 0.2067 data_time: 0.0047 memory: 7851 loss_ce: 0.0334 loss: 0.0334 2022/09/16 15:47:05 - mmengine - INFO - Epoch(train) [2][300/42151] lr: 3.0000e-04 eta: 23:00:47 time: 0.2322 data_time: 0.0195 memory: 7851 loss_ce: 0.0306 loss: 0.0306 2022/09/16 15:47:45 - mmengine - INFO - Epoch(train) [2][400/42151] lr: 3.0000e-04 eta: 23:00:11 time: 1.0657 data_time: 0.8121 memory: 7851 loss_ce: 0.0298 loss: 0.0298 2022/09/16 15:48:25 - mmengine - INFO - Epoch(train) [2][500/42151] lr: 3.0000e-04 eta: 22:59:34 time: 0.2093 data_time: 0.0060 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 15:49:02 - mmengine - INFO - Epoch(train) [2][600/42151] lr: 3.0000e-04 eta: 22:58:44 time: 0.6501 data_time: 0.4386 memory: 7851 loss_ce: 0.0333 loss: 0.0333 2022/09/16 15:49:41 - mmengine - INFO - Epoch(train) [2][700/42151] lr: 3.0000e-04 eta: 22:58:02 time: 0.3768 data_time: 0.1572 memory: 7851 loss_ce: 0.0303 loss: 0.0303 2022/09/16 15:50:15 - mmengine - INFO - Epoch(train) [2][800/42151] lr: 3.0000e-04 eta: 22:56:56 time: 0.5232 data_time: 0.3170 memory: 7851 loss_ce: 0.0321 loss: 0.0321 2022/09/16 15:50:33 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 15:50:49 - mmengine - INFO - Epoch(train) [2][900/42151] lr: 3.0000e-04 eta: 22:55:50 time: 0.2808 data_time: 0.0397 memory: 7851 loss_ce: 0.0312 loss: 0.0312 2022/09/16 15:51:34 - mmengine - INFO - Epoch(train) [2][1000/42151] lr: 3.0000e-04 eta: 22:55:37 time: 1.2729 data_time: 1.0690 memory: 7851 loss_ce: 0.0307 loss: 0.0307 2022/09/16 15:52:07 - mmengine - INFO - Epoch(train) [2][1100/42151] lr: 3.0000e-04 eta: 22:54:31 time: 0.2803 data_time: 0.0678 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 15:52:44 - mmengine - INFO - Epoch(train) [2][1200/42151] lr: 3.0000e-04 eta: 22:53:39 time: 0.5964 data_time: 0.3950 memory: 7851 loss_ce: 0.0314 loss: 0.0314 2022/09/16 15:53:19 - mmengine - INFO - Epoch(train) [2][1300/42151] lr: 3.0000e-04 eta: 22:52:40 time: 0.6761 data_time: 0.4734 memory: 7851 loss_ce: 0.0332 loss: 0.0332 2022/09/16 15:53:53 - mmengine - INFO - Epoch(train) [2][1400/42151] lr: 3.0000e-04 eta: 22:51:35 time: 0.6462 data_time: 0.4305 memory: 7851 loss_ce: 0.0319 loss: 0.0319 2022/09/16 15:54:27 - mmengine - INFO - Epoch(train) [2][1500/42151] lr: 3.0000e-04 eta: 22:50:31 time: 0.2536 data_time: 0.0063 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 15:54:59 - mmengine - INFO - Epoch(train) [2][1600/42151] lr: 3.0000e-04 eta: 22:49:14 time: 0.3228 data_time: 0.1225 memory: 7851 loss_ce: 0.0311 loss: 0.0311 2022/09/16 15:55:44 - mmengine - INFO - Epoch(train) [2][1700/42151] lr: 3.0000e-04 eta: 22:49:02 time: 0.4478 data_time: 0.2286 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 15:56:21 - mmengine - INFO - Epoch(train) [2][1800/42151] lr: 3.0000e-04 eta: 22:48:14 time: 0.5395 data_time: 0.2590 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 15:56:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 15:56:56 - mmengine - INFO - Epoch(train) [2][1900/42151] lr: 3.0000e-04 eta: 22:47:11 time: 0.2951 data_time: 0.0901 memory: 7851 loss_ce: 0.0289 loss: 0.0289 2022/09/16 15:57:32 - mmengine - INFO - Epoch(train) [2][2000/42151] lr: 3.0000e-04 eta: 22:46:17 time: 0.2293 data_time: 0.0069 memory: 7851 loss_ce: 0.0313 loss: 0.0313 2022/09/16 15:58:11 - mmengine - INFO - Epoch(train) [2][2100/42151] lr: 3.0000e-04 eta: 22:45:35 time: 0.2079 data_time: 0.0046 memory: 7851 loss_ce: 0.0307 loss: 0.0307 2022/09/16 15:58:56 - mmengine - INFO - Epoch(train) [2][2200/42151] lr: 3.0000e-04 eta: 22:45:23 time: 0.2348 data_time: 0.0063 memory: 7851 loss_ce: 0.0312 loss: 0.0312 2022/09/16 15:59:29 - mmengine - INFO - Epoch(train) [2][2300/42151] lr: 3.0000e-04 eta: 22:44:17 time: 0.2775 data_time: 0.0540 memory: 7851 loss_ce: 0.0321 loss: 0.0321 2022/09/16 16:00:02 - mmengine - INFO - Epoch(train) [2][2400/42151] lr: 3.0000e-04 eta: 22:43:06 time: 0.3347 data_time: 0.1067 memory: 7851 loss_ce: 0.0333 loss: 0.0333 2022/09/16 16:00:38 - mmengine - INFO - Epoch(train) [2][2500/42151] lr: 3.0000e-04 eta: 22:42:15 time: 0.3617 data_time: 0.1159 memory: 7851 loss_ce: 0.0315 loss: 0.0315 2022/09/16 16:01:10 - mmengine - INFO - Epoch(train) [2][2600/42151] lr: 3.0000e-04 eta: 22:40:58 time: 0.3368 data_time: 0.1264 memory: 7851 loss_ce: 0.0290 loss: 0.0290 2022/09/16 16:01:44 - mmengine - INFO - Epoch(train) [2][2700/42151] lr: 3.0000e-04 eta: 22:39:58 time: 0.3548 data_time: 0.1514 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 16:02:19 - mmengine - INFO - Epoch(train) [2][2800/42151] lr: 3.0000e-04 eta: 22:38:57 time: 0.3722 data_time: 0.0911 memory: 7851 loss_ce: 0.0324 loss: 0.0324 2022/09/16 16:02:36 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:02:53 - mmengine - INFO - Epoch(train) [2][2900/42151] lr: 3.0000e-04 eta: 22:37:54 time: 0.3231 data_time: 0.1207 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 16:03:28 - mmengine - INFO - Epoch(train) [2][3000/42151] lr: 3.0000e-04 eta: 22:36:55 time: 0.3267 data_time: 0.1025 memory: 7851 loss_ce: 0.0300 loss: 0.0300 2022/09/16 16:04:03 - mmengine - INFO - Epoch(train) [2][3100/42151] lr: 3.0000e-04 eta: 22:35:56 time: 0.4030 data_time: 0.1959 memory: 7851 loss_ce: 0.0325 loss: 0.0325 2022/09/16 16:04:37 - mmengine - INFO - Epoch(train) [2][3200/42151] lr: 3.0000e-04 eta: 22:34:54 time: 0.3178 data_time: 0.0966 memory: 7851 loss_ce: 0.0306 loss: 0.0306 2022/09/16 16:05:12 - mmengine - INFO - Epoch(train) [2][3300/42151] lr: 3.0000e-04 eta: 22:33:53 time: 0.3662 data_time: 0.1594 memory: 7851 loss_ce: 0.0298 loss: 0.0298 2022/09/16 16:05:46 - mmengine - INFO - Epoch(train) [2][3400/42151] lr: 3.0000e-04 eta: 22:32:50 time: 0.3198 data_time: 0.0885 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 16:06:20 - mmengine - INFO - Epoch(train) [2][3500/42151] lr: 3.0000e-04 eta: 22:31:48 time: 0.3380 data_time: 0.1233 memory: 7851 loss_ce: 0.0308 loss: 0.0308 2022/09/16 16:06:54 - mmengine - INFO - Epoch(train) [2][3600/42151] lr: 3.0000e-04 eta: 22:30:47 time: 0.3552 data_time: 0.1457 memory: 7851 loss_ce: 0.0316 loss: 0.0316 2022/09/16 16:07:30 - mmengine - INFO - Epoch(train) [2][3700/42151] lr: 3.0000e-04 eta: 22:29:52 time: 0.3961 data_time: 0.1738 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 16:08:04 - mmengine - INFO - Epoch(train) [2][3800/42151] lr: 3.0000e-04 eta: 22:28:51 time: 0.3688 data_time: 0.1450 memory: 7851 loss_ce: 0.0307 loss: 0.0307 2022/09/16 16:08:21 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:08:38 - mmengine - INFO - Epoch(train) [2][3900/42151] lr: 3.0000e-04 eta: 22:27:51 time: 0.3521 data_time: 0.1074 memory: 7851 loss_ce: 0.0303 loss: 0.0303 2022/09/16 16:09:13 - mmengine - INFO - Epoch(train) [2][4000/42151] lr: 3.0000e-04 eta: 22:26:53 time: 0.3120 data_time: 0.0826 memory: 7851 loss_ce: 0.0311 loss: 0.0311 2022/09/16 16:09:48 - mmengine - INFO - Epoch(train) [2][4100/42151] lr: 3.0000e-04 eta: 22:25:56 time: 0.3385 data_time: 0.1325 memory: 7851 loss_ce: 0.0308 loss: 0.0308 2022/09/16 16:10:24 - mmengine - INFO - Epoch(train) [2][4200/42151] lr: 3.0000e-04 eta: 22:25:02 time: 0.3635 data_time: 0.1142 memory: 7851 loss_ce: 0.0318 loss: 0.0318 2022/09/16 16:11:00 - mmengine - INFO - Epoch(train) [2][4300/42151] lr: 3.0000e-04 eta: 22:24:08 time: 0.3713 data_time: 0.1668 memory: 7851 loss_ce: 0.0300 loss: 0.0300 2022/09/16 16:11:34 - mmengine - INFO - Epoch(train) [2][4400/42151] lr: 3.0000e-04 eta: 22:23:06 time: 0.3252 data_time: 0.1237 memory: 7851 loss_ce: 0.0311 loss: 0.0311 2022/09/16 16:12:08 - mmengine - INFO - Epoch(train) [2][4500/42151] lr: 3.0000e-04 eta: 22:22:08 time: 0.3188 data_time: 0.1178 memory: 7851 loss_ce: 0.0298 loss: 0.0298 2022/09/16 16:12:44 - mmengine - INFO - Epoch(train) [2][4600/42151] lr: 3.0000e-04 eta: 22:21:12 time: 0.3229 data_time: 0.0908 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 16:13:18 - mmengine - INFO - Epoch(train) [2][4700/42151] lr: 3.0000e-04 eta: 22:20:14 time: 0.3459 data_time: 0.1090 memory: 7851 loss_ce: 0.0314 loss: 0.0314 2022/09/16 16:13:54 - mmengine - INFO - Epoch(train) [2][4800/42151] lr: 3.0000e-04 eta: 22:19:20 time: 0.4052 data_time: 0.1935 memory: 7851 loss_ce: 0.0326 loss: 0.0326 2022/09/16 16:14:11 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:14:30 - mmengine - INFO - Epoch(train) [2][4900/42151] lr: 3.0000e-04 eta: 22:18:28 time: 0.4245 data_time: 0.1619 memory: 7851 loss_ce: 0.0313 loss: 0.0313 2022/09/16 16:15:04 - mmengine - INFO - Epoch(train) [2][5000/42151] lr: 3.0000e-04 eta: 22:17:26 time: 0.3612 data_time: 0.1512 memory: 7851 loss_ce: 0.0314 loss: 0.0314 2022/09/16 16:15:38 - mmengine - INFO - Epoch(train) [2][5100/42151] lr: 3.0000e-04 eta: 22:16:27 time: 0.3755 data_time: 0.1587 memory: 7851 loss_ce: 0.0299 loss: 0.0299 2022/09/16 16:16:13 - mmengine - INFO - Epoch(train) [2][5200/42151] lr: 3.0000e-04 eta: 22:15:28 time: 0.3148 data_time: 0.1140 memory: 7851 loss_ce: 0.0316 loss: 0.0316 2022/09/16 16:16:48 - mmengine - INFO - Epoch(train) [2][5300/42151] lr: 3.0000e-04 eta: 22:14:34 time: 0.3366 data_time: 0.1031 memory: 7851 loss_ce: 0.0322 loss: 0.0322 2022/09/16 16:17:24 - mmengine - INFO - Epoch(train) [2][5400/42151] lr: 3.0000e-04 eta: 22:13:39 time: 0.3560 data_time: 0.1275 memory: 7851 loss_ce: 0.0319 loss: 0.0319 2022/09/16 16:17:59 - mmengine - INFO - Epoch(train) [2][5500/42151] lr: 3.0000e-04 eta: 22:12:45 time: 0.3389 data_time: 0.1377 memory: 7851 loss_ce: 0.0295 loss: 0.0295 2022/09/16 16:18:34 - mmengine - INFO - Epoch(train) [2][5600/42151] lr: 3.0000e-04 eta: 22:11:51 time: 0.3262 data_time: 0.1208 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 16:19:10 - mmengine - INFO - Epoch(train) [2][5700/42151] lr: 3.0000e-04 eta: 22:10:56 time: 0.3351 data_time: 0.1320 memory: 7851 loss_ce: 0.0300 loss: 0.0300 2022/09/16 16:19:44 - mmengine - INFO - Epoch(train) [2][5800/42151] lr: 3.0000e-04 eta: 22:09:58 time: 0.3092 data_time: 0.1016 memory: 7851 loss_ce: 0.0321 loss: 0.0321 2022/09/16 16:20:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:20:20 - mmengine - INFO - Epoch(train) [2][5900/42151] lr: 3.0000e-04 eta: 22:09:04 time: 0.3527 data_time: 0.1388 memory: 7851 loss_ce: 0.0313 loss: 0.0313 2022/09/16 16:20:54 - mmengine - INFO - Epoch(train) [2][6000/42151] lr: 3.0000e-04 eta: 22:08:04 time: 0.3317 data_time: 0.1264 memory: 7851 loss_ce: 0.0319 loss: 0.0319 2022/09/16 16:21:28 - mmengine - INFO - Epoch(train) [2][6100/42151] lr: 3.0000e-04 eta: 22:07:06 time: 0.3312 data_time: 0.1138 memory: 7851 loss_ce: 0.0299 loss: 0.0299 2022/09/16 16:22:03 - mmengine - INFO - Epoch(train) [2][6200/42151] lr: 3.0000e-04 eta: 22:06:09 time: 0.3221 data_time: 0.1154 memory: 7851 loss_ce: 0.0289 loss: 0.0289 2022/09/16 16:22:37 - mmengine - INFO - Epoch(train) [2][6300/42151] lr: 3.0000e-04 eta: 22:05:11 time: 0.3479 data_time: 0.1130 memory: 7851 loss_ce: 0.0310 loss: 0.0310 2022/09/16 16:23:12 - mmengine - INFO - Epoch(train) [2][6400/42151] lr: 3.0000e-04 eta: 22:04:14 time: 0.3172 data_time: 0.0904 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 16:23:47 - mmengine - INFO - Epoch(train) [2][6500/42151] lr: 3.0000e-04 eta: 22:03:19 time: 0.3490 data_time: 0.1443 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 16:24:22 - mmengine - INFO - Epoch(train) [2][6600/42151] lr: 3.0000e-04 eta: 22:02:25 time: 0.3753 data_time: 0.1008 memory: 7851 loss_ce: 0.0329 loss: 0.0329 2022/09/16 16:24:57 - mmengine - INFO - Epoch(train) [2][6700/42151] lr: 3.0000e-04 eta: 22:01:29 time: 0.3532 data_time: 0.1471 memory: 7851 loss_ce: 0.0322 loss: 0.0322 2022/09/16 16:25:32 - mmengine - INFO - Epoch(train) [2][6800/42151] lr: 3.0000e-04 eta: 22:00:35 time: 0.3298 data_time: 0.1209 memory: 7851 loss_ce: 0.0310 loss: 0.0310 2022/09/16 16:25:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:26:08 - mmengine - INFO - Epoch(train) [2][6900/42151] lr: 3.0000e-04 eta: 21:59:42 time: 0.3431 data_time: 0.1420 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 16:26:42 - mmengine - INFO - Epoch(train) [2][7000/42151] lr: 3.0000e-04 eta: 21:58:45 time: 0.3277 data_time: 0.1005 memory: 7851 loss_ce: 0.0333 loss: 0.0333 2022/09/16 16:27:18 - mmengine - INFO - Epoch(train) [2][7100/42151] lr: 3.0000e-04 eta: 21:57:54 time: 0.3316 data_time: 0.1045 memory: 7851 loss_ce: 0.0330 loss: 0.0330 2022/09/16 16:27:55 - mmengine - INFO - Epoch(train) [2][7200/42151] lr: 3.0000e-04 eta: 21:57:06 time: 0.3615 data_time: 0.1408 memory: 7851 loss_ce: 0.0309 loss: 0.0309 2022/09/16 16:28:31 - mmengine - INFO - Epoch(train) [2][7300/42151] lr: 3.0000e-04 eta: 21:56:16 time: 0.3924 data_time: 0.1609 memory: 7851 loss_ce: 0.0301 loss: 0.0301 2022/09/16 16:29:05 - mmengine - INFO - Epoch(train) [2][7400/42151] lr: 3.0000e-04 eta: 21:55:20 time: 0.3311 data_time: 0.1327 memory: 7851 loss_ce: 0.0299 loss: 0.0299 2022/09/16 16:29:40 - mmengine - INFO - Epoch(train) [2][7500/42151] lr: 3.0000e-04 eta: 21:54:24 time: 0.3346 data_time: 0.1321 memory: 7851 loss_ce: 0.0325 loss: 0.0325 2022/09/16 16:30:15 - mmengine - INFO - Epoch(train) [2][7600/42151] lr: 3.0000e-04 eta: 21:53:28 time: 0.3362 data_time: 0.1350 memory: 7851 loss_ce: 0.0341 loss: 0.0341 2022/09/16 16:30:49 - mmengine - INFO - Epoch(train) [2][7700/42151] lr: 3.0000e-04 eta: 21:52:30 time: 0.3121 data_time: 0.0957 memory: 7851 loss_ce: 0.0287 loss: 0.0287 2022/09/16 16:31:24 - mmengine - INFO - Epoch(train) [2][7800/42151] lr: 3.0000e-04 eta: 21:51:37 time: 0.3213 data_time: 0.1002 memory: 7851 loss_ce: 0.0283 loss: 0.0283 2022/09/16 16:31:41 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:31:59 - mmengine - INFO - Epoch(train) [2][7900/42151] lr: 3.0000e-04 eta: 21:50:44 time: 0.3466 data_time: 0.1458 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 16:32:34 - mmengine - INFO - Epoch(train) [2][8000/42151] lr: 3.0000e-04 eta: 21:49:49 time: 0.3727 data_time: 0.1717 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 16:33:09 - mmengine - INFO - Epoch(train) [2][8100/42151] lr: 3.0000e-04 eta: 21:48:56 time: 0.3473 data_time: 0.1408 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 16:33:44 - mmengine - INFO - Epoch(train) [2][8200/42151] lr: 3.0000e-04 eta: 21:48:01 time: 0.3160 data_time: 0.1156 memory: 7851 loss_ce: 0.0300 loss: 0.0300 2022/09/16 16:34:19 - mmengine - INFO - Epoch(train) [2][8300/42151] lr: 3.0000e-04 eta: 21:47:09 time: 0.3479 data_time: 0.1411 memory: 7851 loss_ce: 0.0325 loss: 0.0325 2022/09/16 16:34:55 - mmengine - INFO - Epoch(train) [2][8400/42151] lr: 3.0000e-04 eta: 21:46:16 time: 0.3649 data_time: 0.1491 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 16:35:31 - mmengine - INFO - Epoch(train) [2][8500/42151] lr: 3.0000e-04 eta: 21:45:26 time: 0.3805 data_time: 0.1368 memory: 7851 loss_ce: 0.0287 loss: 0.0287 2022/09/16 16:36:05 - mmengine - INFO - Epoch(train) [2][8600/42151] lr: 3.0000e-04 eta: 21:44:28 time: 0.3603 data_time: 0.1508 memory: 7851 loss_ce: 0.0329 loss: 0.0329 2022/09/16 16:36:40 - mmengine - INFO - Epoch(train) [2][8700/42151] lr: 3.0000e-04 eta: 21:43:35 time: 0.3606 data_time: 0.1151 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 16:37:15 - mmengine - INFO - Epoch(train) [2][8800/42151] lr: 3.0000e-04 eta: 21:42:44 time: 0.3506 data_time: 0.1297 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 16:37:34 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:37:51 - mmengine - INFO - Epoch(train) [2][8900/42151] lr: 3.0000e-04 eta: 21:41:54 time: 0.3388 data_time: 0.1361 memory: 7851 loss_ce: 0.0305 loss: 0.0305 2022/09/16 16:38:27 - mmengine - INFO - Epoch(train) [2][9000/42151] lr: 3.0000e-04 eta: 21:41:05 time: 0.3946 data_time: 0.1730 memory: 7851 loss_ce: 0.0292 loss: 0.0292 2022/09/16 16:39:03 - mmengine - INFO - Epoch(train) [2][9100/42151] lr: 3.0000e-04 eta: 21:40:15 time: 0.3548 data_time: 0.1482 memory: 7851 loss_ce: 0.0310 loss: 0.0310 2022/09/16 16:39:38 - mmengine - INFO - Epoch(train) [2][9200/42151] lr: 3.0000e-04 eta: 21:39:22 time: 0.3447 data_time: 0.1260 memory: 7851 loss_ce: 0.0312 loss: 0.0312 2022/09/16 16:40:15 - mmengine - INFO - Epoch(train) [2][9300/42151] lr: 3.0000e-04 eta: 21:38:35 time: 0.5046 data_time: 0.2730 memory: 7851 loss_ce: 0.0330 loss: 0.0330 2022/09/16 16:40:46 - mmengine - INFO - Epoch(train) [2][9400/42151] lr: 3.0000e-04 eta: 21:37:26 time: 0.3496 data_time: 0.1162 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 16:41:19 - mmengine - INFO - Epoch(train) [2][9500/42151] lr: 3.0000e-04 eta: 21:36:26 time: 0.2060 data_time: 0.0048 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 16:41:55 - mmengine - INFO - Epoch(train) [2][9600/42151] lr: 3.0000e-04 eta: 21:35:35 time: 0.3602 data_time: 0.1501 memory: 7851 loss_ce: 0.0292 loss: 0.0292 2022/09/16 16:42:29 - mmengine - INFO - Epoch(train) [2][9700/42151] lr: 3.0000e-04 eta: 21:34:41 time: 0.3181 data_time: 0.1153 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 16:43:04 - mmengine - INFO - Epoch(train) [2][9800/42151] lr: 3.0000e-04 eta: 21:33:49 time: 0.4117 data_time: 0.1272 memory: 7851 loss_ce: 0.0309 loss: 0.0309 2022/09/16 16:43:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:43:39 - mmengine - INFO - Epoch(train) [2][9900/42151] lr: 3.0000e-04 eta: 21:32:56 time: 0.3436 data_time: 0.1367 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 16:44:16 - mmengine - INFO - Epoch(train) [2][10000/42151] lr: 3.0000e-04 eta: 21:32:09 time: 0.2516 data_time: 0.0532 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 16:44:51 - mmengine - INFO - Epoch(train) [2][10100/42151] lr: 3.0000e-04 eta: 21:31:16 time: 0.3393 data_time: 0.1335 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 16:45:26 - mmengine - INFO - Epoch(train) [2][10200/42151] lr: 3.0000e-04 eta: 21:30:26 time: 0.3491 data_time: 0.1154 memory: 7851 loss_ce: 0.0319 loss: 0.0319 2022/09/16 16:46:01 - mmengine - INFO - Epoch(train) [2][10300/42151] lr: 3.0000e-04 eta: 21:29:33 time: 0.3355 data_time: 0.0590 memory: 7851 loss_ce: 0.0284 loss: 0.0284 2022/09/16 16:46:36 - mmengine - INFO - Epoch(train) [2][10400/42151] lr: 3.0000e-04 eta: 21:28:42 time: 0.4508 data_time: 0.2380 memory: 7851 loss_ce: 0.0301 loss: 0.0301 2022/09/16 16:47:11 - mmengine - INFO - Epoch(train) [2][10500/42151] lr: 3.0000e-04 eta: 21:27:46 time: 0.3578 data_time: 0.0753 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 16:47:46 - mmengine - INFO - Epoch(train) [2][10600/42151] lr: 3.0000e-04 eta: 21:26:54 time: 0.5224 data_time: 0.2844 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 16:48:19 - mmengine - INFO - Epoch(train) [2][10700/42151] lr: 3.0000e-04 eta: 21:25:55 time: 0.3748 data_time: 0.1344 memory: 7851 loss_ce: 0.0325 loss: 0.0325 2022/09/16 16:48:53 - mmengine - INFO - Epoch(train) [2][10800/42151] lr: 3.0000e-04 eta: 21:25:00 time: 0.4423 data_time: 0.2325 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 16:49:11 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:49:28 - mmengine - INFO - Epoch(train) [2][10900/42151] lr: 3.0000e-04 eta: 21:24:09 time: 0.3520 data_time: 0.1413 memory: 7851 loss_ce: 0.0289 loss: 0.0289 2022/09/16 16:50:03 - mmengine - INFO - Epoch(train) [2][11000/42151] lr: 3.0000e-04 eta: 21:23:15 time: 0.3357 data_time: 0.1211 memory: 7851 loss_ce: 0.0301 loss: 0.0301 2022/09/16 16:50:39 - mmengine - INFO - Epoch(train) [2][11100/42151] lr: 3.0000e-04 eta: 21:22:26 time: 0.3053 data_time: 0.1017 memory: 7851 loss_ce: 0.0325 loss: 0.0325 2022/09/16 16:51:14 - mmengine - INFO - Epoch(train) [2][11200/42151] lr: 3.0000e-04 eta: 21:21:35 time: 0.4381 data_time: 0.2262 memory: 7851 loss_ce: 0.0312 loss: 0.0312 2022/09/16 16:51:47 - mmengine - INFO - Epoch(train) [2][11300/42151] lr: 3.0000e-04 eta: 21:20:38 time: 0.2998 data_time: 0.0760 memory: 7851 loss_ce: 0.0285 loss: 0.0285 2022/09/16 16:52:23 - mmengine - INFO - Epoch(train) [2][11400/42151] lr: 3.0000e-04 eta: 21:19:50 time: 0.4097 data_time: 0.1748 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 16:52:58 - mmengine - INFO - Epoch(train) [2][11500/42151] lr: 3.0000e-04 eta: 21:18:57 time: 0.3047 data_time: 0.1038 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 16:53:33 - mmengine - INFO - Epoch(train) [2][11600/42151] lr: 3.0000e-04 eta: 21:18:05 time: 0.3699 data_time: 0.1326 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 16:54:07 - mmengine - INFO - Epoch(train) [2][11700/42151] lr: 3.0000e-04 eta: 21:17:11 time: 0.2866 data_time: 0.0377 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 16:54:45 - mmengine - INFO - Epoch(train) [2][11800/42151] lr: 3.0000e-04 eta: 21:16:31 time: 0.3578 data_time: 0.1468 memory: 7851 loss_ce: 0.0308 loss: 0.0308 2022/09/16 16:55:01 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 16:55:17 - mmengine - INFO - Epoch(train) [2][11900/42151] lr: 3.0000e-04 eta: 21:15:26 time: 0.3414 data_time: 0.1316 memory: 7851 loss_ce: 0.0319 loss: 0.0319 2022/09/16 16:55:51 - mmengine - INFO - Epoch(train) [2][12000/42151] lr: 3.0000e-04 eta: 21:14:31 time: 0.3630 data_time: 0.1470 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 16:56:25 - mmengine - INFO - Epoch(train) [2][12100/42151] lr: 3.0000e-04 eta: 21:13:37 time: 0.3388 data_time: 0.1127 memory: 7851 loss_ce: 0.0289 loss: 0.0289 2022/09/16 16:57:00 - mmengine - INFO - Epoch(train) [2][12200/42151] lr: 3.0000e-04 eta: 21:12:47 time: 0.3532 data_time: 0.1518 memory: 7851 loss_ce: 0.0314 loss: 0.0314 2022/09/16 16:57:36 - mmengine - INFO - Epoch(train) [2][12300/42151] lr: 3.0000e-04 eta: 21:11:57 time: 0.3589 data_time: 0.0976 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 16:58:11 - mmengine - INFO - Epoch(train) [2][12400/42151] lr: 3.0000e-04 eta: 21:11:08 time: 0.3824 data_time: 0.1677 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 16:58:45 - mmengine - INFO - Epoch(train) [2][12500/42151] lr: 3.0000e-04 eta: 21:10:13 time: 0.3208 data_time: 0.1221 memory: 7851 loss_ce: 0.0267 loss: 0.0267 2022/09/16 16:59:20 - mmengine - INFO - Epoch(train) [2][12600/42151] lr: 3.0000e-04 eta: 21:09:23 time: 0.3292 data_time: 0.1309 memory: 7851 loss_ce: 0.0284 loss: 0.0284 2022/09/16 16:59:55 - mmengine - INFO - Epoch(train) [2][12700/42151] lr: 3.0000e-04 eta: 21:08:31 time: 0.2949 data_time: 0.0952 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 17:00:31 - mmengine - INFO - Epoch(train) [2][12800/42151] lr: 3.0000e-04 eta: 21:07:42 time: 0.3563 data_time: 0.1514 memory: 7851 loss_ce: 0.0284 loss: 0.0284 2022/09/16 17:00:49 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:01:06 - mmengine - INFO - Epoch(train) [2][12900/42151] lr: 3.0000e-04 eta: 21:06:53 time: 0.3144 data_time: 0.1038 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 17:01:41 - mmengine - INFO - Epoch(train) [2][13000/42151] lr: 3.0000e-04 eta: 21:06:03 time: 0.3343 data_time: 0.0976 memory: 7851 loss_ce: 0.0290 loss: 0.0290 2022/09/16 17:02:16 - mmengine - INFO - Epoch(train) [2][13100/42151] lr: 3.0000e-04 eta: 21:05:12 time: 0.3273 data_time: 0.0986 memory: 7851 loss_ce: 0.0293 loss: 0.0293 2022/09/16 17:02:51 - mmengine - INFO - Epoch(train) [2][13200/42151] lr: 3.0000e-04 eta: 21:04:22 time: 0.3386 data_time: 0.1132 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:03:28 - mmengine - INFO - Epoch(train) [2][13300/42151] lr: 3.0000e-04 eta: 21:03:36 time: 0.2947 data_time: 0.0725 memory: 7851 loss_ce: 0.0293 loss: 0.0293 2022/09/16 17:04:03 - mmengine - INFO - Epoch(train) [2][13400/42151] lr: 3.0000e-04 eta: 21:02:48 time: 0.3459 data_time: 0.1090 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:04:38 - mmengine - INFO - Epoch(train) [2][13500/42151] lr: 3.0000e-04 eta: 21:01:57 time: 0.2946 data_time: 0.0741 memory: 7851 loss_ce: 0.0284 loss: 0.0284 2022/09/16 17:05:14 - mmengine - INFO - Epoch(train) [2][13600/42151] lr: 3.0000e-04 eta: 21:01:07 time: 0.3166 data_time: 0.1118 memory: 7851 loss_ce: 0.0292 loss: 0.0292 2022/09/16 17:05:48 - mmengine - INFO - Epoch(train) [2][13700/42151] lr: 3.0000e-04 eta: 21:00:14 time: 0.3362 data_time: 0.1337 memory: 7851 loss_ce: 0.0279 loss: 0.0279 2022/09/16 17:06:23 - mmengine - INFO - Epoch(train) [2][13800/42151] lr: 3.0000e-04 eta: 20:59:24 time: 0.3624 data_time: 0.1610 memory: 7851 loss_ce: 0.0320 loss: 0.0320 2022/09/16 17:06:40 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:06:58 - mmengine - INFO - Epoch(train) [2][13900/42151] lr: 3.0000e-04 eta: 20:58:35 time: 0.3058 data_time: 0.1043 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:07:34 - mmengine - INFO - Epoch(train) [2][14000/42151] lr: 3.0000e-04 eta: 20:57:48 time: 0.3375 data_time: 0.1363 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 17:08:10 - mmengine - INFO - Epoch(train) [2][14100/42151] lr: 3.0000e-04 eta: 20:57:02 time: 0.3046 data_time: 0.1024 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 17:08:46 - mmengine - INFO - Epoch(train) [2][14200/42151] lr: 3.0000e-04 eta: 20:56:15 time: 0.3697 data_time: 0.1108 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 17:09:22 - mmengine - INFO - Epoch(train) [2][14300/42151] lr: 3.0000e-04 eta: 20:55:29 time: 0.3610 data_time: 0.1205 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 17:09:58 - mmengine - INFO - Epoch(train) [2][14400/42151] lr: 3.0000e-04 eta: 20:54:40 time: 0.4020 data_time: 0.1432 memory: 7851 loss_ce: 0.0307 loss: 0.0307 2022/09/16 17:10:32 - mmengine - INFO - Epoch(train) [2][14500/42151] lr: 3.0000e-04 eta: 20:53:49 time: 0.3644 data_time: 0.1512 memory: 7851 loss_ce: 0.0274 loss: 0.0274 2022/09/16 17:11:08 - mmengine - INFO - Epoch(train) [2][14600/42151] lr: 3.0000e-04 eta: 20:53:00 time: 0.4179 data_time: 0.1600 memory: 7851 loss_ce: 0.0279 loss: 0.0279 2022/09/16 17:11:42 - mmengine - INFO - Epoch(train) [2][14700/42151] lr: 3.0000e-04 eta: 20:52:08 time: 0.3102 data_time: 0.0723 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 17:12:18 - mmengine - INFO - Epoch(train) [2][14800/42151] lr: 3.0000e-04 eta: 20:51:23 time: 0.3359 data_time: 0.0850 memory: 7851 loss_ce: 0.0325 loss: 0.0325 2022/09/16 17:12:36 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:12:54 - mmengine - INFO - Epoch(train) [2][14900/42151] lr: 3.0000e-04 eta: 20:50:34 time: 0.3115 data_time: 0.0894 memory: 7851 loss_ce: 0.0321 loss: 0.0321 2022/09/16 17:13:29 - mmengine - INFO - Epoch(train) [2][15000/42151] lr: 3.0000e-04 eta: 20:49:47 time: 0.3925 data_time: 0.1818 memory: 7851 loss_ce: 0.0274 loss: 0.0274 2022/09/16 17:14:05 - mmengine - INFO - Epoch(train) [2][15100/42151] lr: 3.0000e-04 eta: 20:48:58 time: 0.3254 data_time: 0.1064 memory: 7851 loss_ce: 0.0300 loss: 0.0300 2022/09/16 17:14:39 - mmengine - INFO - Epoch(train) [2][15200/42151] lr: 3.0000e-04 eta: 20:48:08 time: 0.3582 data_time: 0.1335 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 17:15:15 - mmengine - INFO - Epoch(train) [2][15300/42151] lr: 3.0000e-04 eta: 20:47:18 time: 0.3092 data_time: 0.0790 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 17:15:50 - mmengine - INFO - Epoch(train) [2][15400/42151] lr: 3.0000e-04 eta: 20:46:30 time: 0.3326 data_time: 0.0823 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 17:16:25 - mmengine - INFO - Epoch(train) [2][15500/42151] lr: 3.0000e-04 eta: 20:45:39 time: 0.3177 data_time: 0.0923 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 17:17:00 - mmengine - INFO - Epoch(train) [2][15600/42151] lr: 3.0000e-04 eta: 20:44:51 time: 0.3513 data_time: 0.1463 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 17:17:35 - mmengine - INFO - Epoch(train) [2][15700/42151] lr: 3.0000e-04 eta: 20:44:02 time: 0.3239 data_time: 0.1058 memory: 7851 loss_ce: 0.0274 loss: 0.0274 2022/09/16 17:18:10 - mmengine - INFO - Epoch(train) [2][15800/42151] lr: 3.0000e-04 eta: 20:43:14 time: 0.3774 data_time: 0.1419 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 17:18:29 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:18:46 - mmengine - INFO - Epoch(train) [2][15900/42151] lr: 3.0000e-04 eta: 20:42:28 time: 0.3258 data_time: 0.0876 memory: 7851 loss_ce: 0.0295 loss: 0.0295 2022/09/16 17:19:22 - mmengine - INFO - Epoch(train) [2][16000/42151] lr: 3.0000e-04 eta: 20:41:40 time: 0.3335 data_time: 0.0848 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:19:57 - mmengine - INFO - Epoch(train) [2][16100/42151] lr: 3.0000e-04 eta: 20:40:50 time: 0.3441 data_time: 0.1018 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 17:20:33 - mmengine - INFO - Epoch(train) [2][16200/42151] lr: 3.0000e-04 eta: 20:40:05 time: 0.3883 data_time: 0.1761 memory: 7851 loss_ce: 0.0295 loss: 0.0295 2022/09/16 17:21:08 - mmengine - INFO - Epoch(train) [2][16300/42151] lr: 3.0000e-04 eta: 20:39:16 time: 0.3376 data_time: 0.1305 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 17:21:43 - mmengine - INFO - Epoch(train) [2][16400/42151] lr: 3.0000e-04 eta: 20:38:26 time: 0.3382 data_time: 0.1343 memory: 7851 loss_ce: 0.0278 loss: 0.0278 2022/09/16 17:22:18 - mmengine - INFO - Epoch(train) [2][16500/42151] lr: 3.0000e-04 eta: 20:37:37 time: 0.3136 data_time: 0.0854 memory: 7851 loss_ce: 0.0285 loss: 0.0285 2022/09/16 17:22:53 - mmengine - INFO - Epoch(train) [2][16600/42151] lr: 3.0000e-04 eta: 20:36:51 time: 0.3352 data_time: 0.1103 memory: 7851 loss_ce: 0.0292 loss: 0.0292 2022/09/16 17:23:28 - mmengine - INFO - Epoch(train) [2][16700/42151] lr: 3.0000e-04 eta: 20:36:02 time: 0.3671 data_time: 0.1446 memory: 7851 loss_ce: 0.0297 loss: 0.0297 2022/09/16 17:24:04 - mmengine - INFO - Epoch(train) [2][16800/42151] lr: 3.0000e-04 eta: 20:35:16 time: 0.3528 data_time: 0.1491 memory: 7851 loss_ce: 0.0262 loss: 0.0262 2022/09/16 17:24:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:24:40 - mmengine - INFO - Epoch(train) [2][16900/42151] lr: 3.0000e-04 eta: 20:34:29 time: 0.3152 data_time: 0.1093 memory: 7851 loss_ce: 0.0293 loss: 0.0293 2022/09/16 17:25:16 - mmengine - INFO - Epoch(train) [2][17000/42151] lr: 3.0000e-04 eta: 20:33:44 time: 0.3484 data_time: 0.1422 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 17:25:53 - mmengine - INFO - Epoch(train) [2][17100/42151] lr: 3.0000e-04 eta: 20:33:02 time: 0.3505 data_time: 0.0924 memory: 7851 loss_ce: 0.0299 loss: 0.0299 2022/09/16 17:26:29 - mmengine - INFO - Epoch(train) [2][17200/42151] lr: 3.0000e-04 eta: 20:32:15 time: 0.3737 data_time: 0.1209 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 17:27:04 - mmengine - INFO - Epoch(train) [2][17300/42151] lr: 3.0000e-04 eta: 20:31:28 time: 0.3257 data_time: 0.1225 memory: 7851 loss_ce: 0.0287 loss: 0.0287 2022/09/16 17:27:39 - mmengine - INFO - Epoch(train) [2][17400/42151] lr: 3.0000e-04 eta: 20:30:40 time: 0.3535 data_time: 0.1537 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 17:28:14 - mmengine - INFO - Epoch(train) [2][17500/42151] lr: 3.0000e-04 eta: 20:29:51 time: 0.2995 data_time: 0.0978 memory: 7851 loss_ce: 0.0301 loss: 0.0301 2022/09/16 17:28:50 - mmengine - INFO - Epoch(train) [2][17600/42151] lr: 3.0000e-04 eta: 20:29:06 time: 0.3593 data_time: 0.1554 memory: 7851 loss_ce: 0.0302 loss: 0.0302 2022/09/16 17:29:27 - mmengine - INFO - Epoch(train) [2][17700/42151] lr: 3.0000e-04 eta: 20:28:22 time: 0.3417 data_time: 0.0982 memory: 7851 loss_ce: 0.0305 loss: 0.0305 2022/09/16 17:30:03 - mmengine - INFO - Epoch(train) [2][17800/42151] lr: 3.0000e-04 eta: 20:27:37 time: 0.3967 data_time: 0.1466 memory: 7851 loss_ce: 0.0290 loss: 0.0290 2022/09/16 17:30:19 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:30:38 - mmengine - INFO - Epoch(train) [2][17900/42151] lr: 3.0000e-04 eta: 20:26:48 time: 0.3544 data_time: 0.1496 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 17:31:13 - mmengine - INFO - Epoch(train) [2][18000/42151] lr: 3.0000e-04 eta: 20:26:01 time: 0.3313 data_time: 0.1312 memory: 7851 loss_ce: 0.0294 loss: 0.0294 2022/09/16 17:31:49 - mmengine - INFO - Epoch(train) [2][18100/42151] lr: 3.0000e-04 eta: 20:25:15 time: 0.3101 data_time: 0.1023 memory: 7851 loss_ce: 0.0302 loss: 0.0302 2022/09/16 17:32:25 - mmengine - INFO - Epoch(train) [2][18200/42151] lr: 3.0000e-04 eta: 20:24:30 time: 0.3390 data_time: 0.1392 memory: 7851 loss_ce: 0.0259 loss: 0.0259 2022/09/16 17:33:01 - mmengine - INFO - Epoch(train) [2][18300/42151] lr: 3.0000e-04 eta: 20:23:46 time: 0.3350 data_time: 0.0857 memory: 7851 loss_ce: 0.0290 loss: 0.0290 2022/09/16 17:33:38 - mmengine - INFO - Epoch(train) [2][18400/42151] lr: 3.0000e-04 eta: 20:23:03 time: 0.3625 data_time: 0.1255 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 17:34:14 - mmengine - INFO - Epoch(train) [2][18500/42151] lr: 3.0000e-04 eta: 20:22:19 time: 0.3343 data_time: 0.1267 memory: 7851 loss_ce: 0.0259 loss: 0.0259 2022/09/16 17:34:50 - mmengine - INFO - Epoch(train) [2][18600/42151] lr: 3.0000e-04 eta: 20:21:34 time: 0.3258 data_time: 0.1232 memory: 7851 loss_ce: 0.0298 loss: 0.0298 2022/09/16 17:35:25 - mmengine - INFO - Epoch(train) [2][18700/42151] lr: 3.0000e-04 eta: 20:20:47 time: 0.2954 data_time: 0.0933 memory: 7851 loss_ce: 0.0274 loss: 0.0274 2022/09/16 17:36:01 - mmengine - INFO - Epoch(train) [2][18800/42151] lr: 3.0000e-04 eta: 20:20:01 time: 0.3507 data_time: 0.1461 memory: 7851 loss_ce: 0.0290 loss: 0.0290 2022/09/16 17:36:19 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:36:37 - mmengine - INFO - Epoch(train) [2][18900/42151] lr: 3.0000e-04 eta: 20:19:14 time: 0.3053 data_time: 0.0750 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 17:37:12 - mmengine - INFO - Epoch(train) [2][19000/42151] lr: 3.0000e-04 eta: 20:18:29 time: 0.3439 data_time: 0.1133 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 17:37:48 - mmengine - INFO - Epoch(train) [2][19100/42151] lr: 3.0000e-04 eta: 20:17:41 time: 0.3519 data_time: 0.1263 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 17:38:23 - mmengine - INFO - Epoch(train) [2][19200/42151] lr: 3.0000e-04 eta: 20:16:55 time: 0.3458 data_time: 0.1279 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 17:38:59 - mmengine - INFO - Epoch(train) [2][19300/42151] lr: 3.0000e-04 eta: 20:16:09 time: 0.3439 data_time: 0.1051 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 17:39:33 - mmengine - INFO - Epoch(train) [2][19400/42151] lr: 3.0000e-04 eta: 20:15:20 time: 0.3457 data_time: 0.1420 memory: 7851 loss_ce: 0.0273 loss: 0.0273 2022/09/16 17:40:09 - mmengine - INFO - Epoch(train) [2][19500/42151] lr: 3.0000e-04 eta: 20:14:33 time: 0.3178 data_time: 0.0757 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 17:40:44 - mmengine - INFO - Epoch(train) [2][19600/42151] lr: 3.0000e-04 eta: 20:13:47 time: 0.3491 data_time: 0.1073 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 17:41:20 - mmengine - INFO - Epoch(train) [2][19700/42151] lr: 3.0000e-04 eta: 20:13:01 time: 0.3626 data_time: 0.1396 memory: 7851 loss_ce: 0.0307 loss: 0.0307 2022/09/16 17:41:55 - mmengine - INFO - Epoch(train) [2][19800/42151] lr: 3.0000e-04 eta: 20:12:13 time: 0.3196 data_time: 0.1183 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:42:13 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:42:30 - mmengine - INFO - Epoch(train) [2][19900/42151] lr: 3.0000e-04 eta: 20:11:27 time: 0.3003 data_time: 0.1003 memory: 7851 loss_ce: 0.0273 loss: 0.0273 2022/09/16 17:43:06 - mmengine - INFO - Epoch(train) [2][20000/42151] lr: 3.0000e-04 eta: 20:10:42 time: 0.3454 data_time: 0.1443 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 17:43:42 - mmengine - INFO - Epoch(train) [2][20100/42151] lr: 3.0000e-04 eta: 20:09:57 time: 0.2041 data_time: 0.0049 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:44:15 - mmengine - INFO - Epoch(train) [2][20200/42151] lr: 3.0000e-04 eta: 20:09:03 time: 0.2089 data_time: 0.0047 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 17:44:49 - mmengine - INFO - Epoch(train) [2][20300/42151] lr: 3.0000e-04 eta: 20:08:13 time: 0.2593 data_time: 0.0552 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 17:45:23 - mmengine - INFO - Epoch(train) [2][20400/42151] lr: 3.0000e-04 eta: 20:07:22 time: 0.2118 data_time: 0.0051 memory: 7851 loss_ce: 0.0293 loss: 0.0293 2022/09/16 17:46:08 - mmengine - INFO - Epoch(train) [2][20500/42151] lr: 3.0000e-04 eta: 20:07:06 time: 1.1462 data_time: 0.8819 memory: 7851 loss_ce: 0.0283 loss: 0.0283 2022/09/16 17:46:50 - mmengine - INFO - Epoch(train) [2][20600/42151] lr: 3.0000e-04 eta: 20:06:40 time: 1.5488 data_time: 1.3231 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 17:47:23 - mmengine - INFO - Epoch(train) [2][20700/42151] lr: 3.0000e-04 eta: 20:05:47 time: 0.4607 data_time: 0.2519 memory: 7851 loss_ce: 0.0287 loss: 0.0287 2022/09/16 17:47:55 - mmengine - INFO - Epoch(train) [2][20800/42151] lr: 3.0000e-04 eta: 20:04:51 time: 0.2111 data_time: 0.0053 memory: 7851 loss_ce: 0.0278 loss: 0.0278 2022/09/16 17:48:17 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:48:33 - mmengine - INFO - Epoch(train) [2][20900/42151] lr: 3.0000e-04 eta: 20:04:10 time: 0.2213 data_time: 0.0056 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 17:49:16 - mmengine - INFO - Epoch(train) [2][21000/42151] lr: 3.0000e-04 eta: 20:03:49 time: 0.8223 data_time: 0.6162 memory: 7851 loss_ce: 0.0289 loss: 0.0289 2022/09/16 17:49:53 - mmengine - INFO - Epoch(train) [2][21100/42151] lr: 3.0000e-04 eta: 20:03:06 time: 0.3163 data_time: 0.1018 memory: 7851 loss_ce: 0.0271 loss: 0.0271 2022/09/16 17:50:30 - mmengine - INFO - Epoch(train) [2][21200/42151] lr: 3.0000e-04 eta: 20:02:25 time: 0.5738 data_time: 0.3567 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 17:51:02 - mmengine - INFO - Epoch(train) [2][21300/42151] lr: 3.0000e-04 eta: 20:01:28 time: 0.2640 data_time: 0.0391 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 17:51:59 - mmengine - INFO - Epoch(train) [2][21400/42151] lr: 3.0000e-04 eta: 20:01:48 time: 0.2369 data_time: 0.0054 memory: 7851 loss_ce: 0.0298 loss: 0.0298 2022/09/16 17:53:16 - mmengine - INFO - Epoch(train) [2][21500/42151] lr: 3.0000e-04 eta: 20:03:06 time: 0.2193 data_time: 0.0066 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 17:53:48 - mmengine - INFO - Epoch(train) [2][21600/42151] lr: 3.0000e-04 eta: 20:02:10 time: 0.3792 data_time: 0.1691 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 17:54:21 - mmengine - INFO - Epoch(train) [2][21700/42151] lr: 3.0000e-04 eta: 20:01:14 time: 0.3284 data_time: 0.1198 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 17:54:55 - mmengine - INFO - Epoch(train) [2][21800/42151] lr: 3.0000e-04 eta: 20:00:26 time: 0.3588 data_time: 0.1557 memory: 7851 loss_ce: 0.0274 loss: 0.0274 2022/09/16 17:55:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 17:55:33 - mmengine - INFO - Epoch(train) [2][21900/42151] lr: 3.0000e-04 eta: 19:59:47 time: 0.6078 data_time: 0.4029 memory: 7851 loss_ce: 0.0267 loss: 0.0267 2022/09/16 17:56:11 - mmengine - INFO - Epoch(train) [2][22000/42151] lr: 3.0000e-04 eta: 19:59:07 time: 0.2955 data_time: 0.0541 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 17:56:49 - mmengine - INFO - Epoch(train) [2][22100/42151] lr: 3.0000e-04 eta: 19:58:29 time: 0.6532 data_time: 0.4203 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 17:57:22 - mmengine - INFO - Epoch(train) [2][22200/42151] lr: 3.0000e-04 eta: 19:57:35 time: 0.3433 data_time: 0.1050 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 17:58:03 - mmengine - INFO - Epoch(train) [2][22300/42151] lr: 3.0000e-04 eta: 19:57:07 time: 0.7171 data_time: 0.4974 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 17:58:35 - mmengine - INFO - Epoch(train) [2][22400/42151] lr: 3.0000e-04 eta: 19:56:11 time: 0.2592 data_time: 0.0051 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 17:59:17 - mmengine - INFO - Epoch(train) [2][22500/42151] lr: 3.0000e-04 eta: 19:55:43 time: 0.2112 data_time: 0.0051 memory: 7851 loss_ce: 0.0299 loss: 0.0299 2022/09/16 17:59:52 - mmengine - INFO - Epoch(train) [2][22600/42151] lr: 3.0000e-04 eta: 19:54:57 time: 0.2029 data_time: 0.0044 memory: 7851 loss_ce: 0.0283 loss: 0.0283 2022/09/16 18:00:32 - mmengine - INFO - Epoch(train) [2][22700/42151] lr: 3.0000e-04 eta: 19:54:23 time: 0.4222 data_time: 0.1986 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 18:01:16 - mmengine - INFO - Epoch(train) [2][22800/42151] lr: 3.0000e-04 eta: 19:54:03 time: 0.2089 data_time: 0.0050 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 18:01:31 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:01:50 - mmengine - INFO - Epoch(train) [2][22900/42151] lr: 3.0000e-04 eta: 19:53:11 time: 0.3126 data_time: 0.0774 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 18:02:26 - mmengine - INFO - Epoch(train) [2][23000/42151] lr: 3.0000e-04 eta: 19:52:26 time: 0.2072 data_time: 0.0047 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 18:02:59 - mmengine - INFO - Epoch(train) [2][23100/42151] lr: 3.0000e-04 eta: 19:51:35 time: 0.2279 data_time: 0.0064 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 18:03:50 - mmengine - INFO - Epoch(train) [2][23200/42151] lr: 3.0000e-04 eta: 19:51:33 time: 1.2424 data_time: 0.9837 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 18:04:22 - mmengine - INFO - Epoch(train) [2][23300/42151] lr: 3.0000e-04 eta: 19:50:39 time: 0.5094 data_time: 0.2242 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 18:04:55 - mmengine - INFO - Epoch(train) [2][23400/42151] lr: 3.0000e-04 eta: 19:49:44 time: 0.2065 data_time: 0.0047 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 18:05:35 - mmengine - INFO - Epoch(train) [2][23500/42151] lr: 3.0000e-04 eta: 19:49:13 time: 0.2048 data_time: 0.0046 memory: 7851 loss_ce: 0.0299 loss: 0.0299 2022/09/16 18:06:18 - mmengine - INFO - Epoch(train) [2][23600/42151] lr: 3.0000e-04 eta: 19:48:49 time: 0.2914 data_time: 0.0880 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 18:06:52 - mmengine - INFO - Epoch(train) [2][23700/42151] lr: 3.0000e-04 eta: 19:47:59 time: 0.2810 data_time: 0.0303 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 18:07:27 - mmengine - INFO - Epoch(train) [2][23800/42151] lr: 3.0000e-04 eta: 19:47:11 time: 0.3708 data_time: 0.1356 memory: 7851 loss_ce: 0.0287 loss: 0.0287 2022/09/16 18:07:44 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:08:01 - mmengine - INFO - Epoch(train) [2][23900/42151] lr: 3.0000e-04 eta: 19:46:21 time: 0.3128 data_time: 0.1022 memory: 7851 loss_ce: 0.0278 loss: 0.0278 2022/09/16 18:08:39 - mmengine - INFO - Epoch(train) [2][24000/42151] lr: 3.0000e-04 eta: 19:45:43 time: 0.2057 data_time: 0.0047 memory: 7851 loss_ce: 0.0267 loss: 0.0267 2022/09/16 18:09:14 - mmengine - INFO - Epoch(train) [2][24100/42151] lr: 3.0000e-04 eta: 19:44:55 time: 0.2532 data_time: 0.0546 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 18:09:56 - mmengine - INFO - Epoch(train) [2][24200/42151] lr: 3.0000e-04 eta: 19:44:28 time: 0.2162 data_time: 0.0091 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 18:10:28 - mmengine - INFO - Epoch(train) [2][24300/42151] lr: 3.0000e-04 eta: 19:43:35 time: 0.2050 data_time: 0.0048 memory: 7851 loss_ce: 0.0304 loss: 0.0304 2022/09/16 18:11:10 - mmengine - INFO - Epoch(train) [2][24400/42151] lr: 3.0000e-04 eta: 19:43:07 time: 0.5518 data_time: 0.3433 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 18:11:47 - mmengine - INFO - Epoch(train) [2][24500/42151] lr: 3.0000e-04 eta: 19:42:26 time: 0.4003 data_time: 0.1878 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 18:12:24 - mmengine - INFO - Epoch(train) [2][24600/42151] lr: 3.0000e-04 eta: 19:41:43 time: 0.2974 data_time: 0.0861 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 18:12:59 - mmengine - INFO - Epoch(train) [2][24700/42151] lr: 3.0000e-04 eta: 19:40:58 time: 0.3750 data_time: 0.1658 memory: 7851 loss_ce: 0.0283 loss: 0.0283 2022/09/16 18:13:33 - mmengine - INFO - Epoch(train) [2][24800/42151] lr: 3.0000e-04 eta: 19:40:08 time: 0.3728 data_time: 0.1571 memory: 7851 loss_ce: 0.0301 loss: 0.0301 2022/09/16 18:13:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:14:06 - mmengine - INFO - Epoch(train) [2][24900/42151] lr: 3.0000e-04 eta: 19:39:16 time: 0.2112 data_time: 0.0049 memory: 7851 loss_ce: 0.0280 loss: 0.0280 2022/09/16 18:14:42 - mmengine - INFO - Epoch(train) [2][25000/42151] lr: 3.0000e-04 eta: 19:38:31 time: 0.5072 data_time: 0.2964 memory: 7851 loss_ce: 0.0273 loss: 0.0273 2022/09/16 18:15:13 - mmengine - INFO - Epoch(train) [2][25100/42151] lr: 3.0000e-04 eta: 19:37:33 time: 0.3397 data_time: 0.1300 memory: 7851 loss_ce: 0.0281 loss: 0.0281 2022/09/16 18:15:51 - mmengine - INFO - Epoch(train) [2][25200/42151] lr: 3.0000e-04 eta: 19:36:55 time: 0.6828 data_time: 0.4371 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 18:16:23 - mmengine - INFO - Epoch(train) [2][25300/42151] lr: 3.0000e-04 eta: 19:36:02 time: 0.3811 data_time: 0.1303 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 18:16:58 - mmengine - INFO - Epoch(train) [2][25400/42151] lr: 3.0000e-04 eta: 19:35:14 time: 0.5153 data_time: 0.2725 memory: 7851 loss_ce: 0.0271 loss: 0.0271 2022/09/16 18:17:32 - mmengine - INFO - Epoch(train) [2][25500/42151] lr: 3.0000e-04 eta: 19:34:24 time: 0.3627 data_time: 0.1585 memory: 7851 loss_ce: 0.0292 loss: 0.0292 2022/09/16 18:18:07 - mmengine - INFO - Epoch(train) [2][25600/42151] lr: 3.0000e-04 eta: 19:33:38 time: 0.3154 data_time: 0.0795 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 18:18:44 - mmengine - INFO - Epoch(train) [2][25700/42151] lr: 3.0000e-04 eta: 19:32:59 time: 0.8772 data_time: 0.6640 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 18:19:15 - mmengine - INFO - Epoch(train) [2][25800/42151] lr: 3.0000e-04 eta: 19:32:01 time: 0.2390 data_time: 0.0273 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 18:19:30 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:19:51 - mmengine - INFO - Epoch(train) [2][25900/42151] lr: 3.0000e-04 eta: 19:31:17 time: 0.2481 data_time: 0.0400 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 18:20:33 - mmengine - INFO - Epoch(train) [2][26000/42151] lr: 3.0000e-04 eta: 19:30:49 time: 0.5858 data_time: 0.3794 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 18:21:05 - mmengine - INFO - Epoch(train) [2][26100/42151] lr: 3.0000e-04 eta: 19:29:55 time: 0.2060 data_time: 0.0049 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 18:21:43 - mmengine - INFO - Epoch(train) [2][26200/42151] lr: 3.0000e-04 eta: 19:29:19 time: 0.2546 data_time: 0.0056 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 18:22:18 - mmengine - INFO - Epoch(train) [2][26300/42151] lr: 3.0000e-04 eta: 19:28:30 time: 0.3214 data_time: 0.1116 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 18:22:53 - mmengine - INFO - Epoch(train) [2][26400/42151] lr: 3.0000e-04 eta: 19:27:45 time: 0.3814 data_time: 0.1588 memory: 7851 loss_ce: 0.0284 loss: 0.0284 2022/09/16 18:23:26 - mmengine - INFO - Epoch(train) [2][26500/42151] lr: 3.0000e-04 eta: 19:26:53 time: 0.2054 data_time: 0.0050 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 18:24:07 - mmengine - INFO - Epoch(train) [2][26600/42151] lr: 3.0000e-04 eta: 19:26:24 time: 0.4619 data_time: 0.2423 memory: 7851 loss_ce: 0.0279 loss: 0.0279 2022/09/16 18:24:57 - mmengine - INFO - Epoch(train) [2][26700/42151] lr: 3.0000e-04 eta: 19:26:17 time: 0.2069 data_time: 0.0048 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 18:25:38 - mmengine - INFO - Epoch(train) [2][26800/42151] lr: 3.0000e-04 eta: 19:25:49 time: 0.2064 data_time: 0.0047 memory: 7851 loss_ce: 0.0293 loss: 0.0293 2022/09/16 18:26:04 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:26:24 - mmengine - INFO - Epoch(train) [2][26900/42151] lr: 3.0000e-04 eta: 19:25:31 time: 0.2161 data_time: 0.0090 memory: 7851 loss_ce: 0.0281 loss: 0.0281 2022/09/16 18:27:05 - mmengine - INFO - Epoch(train) [2][27000/42151] lr: 3.0000e-04 eta: 19:25:00 time: 0.4527 data_time: 0.2459 memory: 7851 loss_ce: 0.0260 loss: 0.0260 2022/09/16 18:27:41 - mmengine - INFO - Epoch(train) [2][27100/42151] lr: 3.0000e-04 eta: 19:24:16 time: 0.2759 data_time: 0.0132 memory: 7851 loss_ce: 0.0305 loss: 0.0305 2022/09/16 18:28:17 - mmengine - INFO - Epoch(train) [2][27200/42151] lr: 3.0000e-04 eta: 19:23:33 time: 0.5078 data_time: 0.3002 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 18:28:54 - mmengine - INFO - Epoch(train) [2][27300/42151] lr: 3.0000e-04 eta: 19:22:53 time: 0.2095 data_time: 0.0047 memory: 7851 loss_ce: 0.0267 loss: 0.0267 2022/09/16 18:29:35 - mmengine - INFO - Epoch(train) [2][27400/42151] lr: 3.0000e-04 eta: 19:22:23 time: 0.2298 data_time: 0.0064 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 18:30:13 - mmengine - INFO - Epoch(train) [2][27500/42151] lr: 3.0000e-04 eta: 19:21:45 time: 0.4198 data_time: 0.2163 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 18:30:49 - mmengine - INFO - Epoch(train) [2][27600/42151] lr: 3.0000e-04 eta: 19:21:00 time: 0.2242 data_time: 0.0055 memory: 7851 loss_ce: 0.0260 loss: 0.0260 2022/09/16 18:31:22 - mmengine - INFO - Epoch(train) [2][27700/42151] lr: 3.0000e-04 eta: 19:20:10 time: 0.4129 data_time: 0.2076 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 18:32:06 - mmengine - INFO - Epoch(train) [2][27800/42151] lr: 3.0000e-04 eta: 19:19:47 time: 0.2467 data_time: 0.0053 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 18:32:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:32:38 - mmengine - INFO - Epoch(train) [2][27900/42151] lr: 3.0000e-04 eta: 19:18:54 time: 0.2669 data_time: 0.0675 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 18:33:15 - mmengine - INFO - Epoch(train) [2][28000/42151] lr: 3.0000e-04 eta: 19:18:12 time: 0.3329 data_time: 0.1234 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 18:33:49 - mmengine - INFO - Epoch(train) [2][28100/42151] lr: 3.0000e-04 eta: 19:17:23 time: 0.2694 data_time: 0.0060 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 18:34:42 - mmengine - INFO - Epoch(train) [2][28200/42151] lr: 3.0000e-04 eta: 19:17:23 time: 0.2929 data_time: 0.0871 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 18:35:27 - mmengine - INFO - Epoch(train) [2][28300/42151] lr: 3.0000e-04 eta: 19:17:04 time: 0.2341 data_time: 0.0305 memory: 7851 loss_ce: 0.0277 loss: 0.0277 2022/09/16 18:36:02 - mmengine - INFO - Epoch(train) [2][28400/42151] lr: 3.0000e-04 eta: 19:16:19 time: 0.3827 data_time: 0.1623 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 18:36:37 - mmengine - INFO - Epoch(train) [2][28500/42151] lr: 3.0000e-04 eta: 19:15:33 time: 0.3187 data_time: 0.1026 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 18:37:11 - mmengine - INFO - Epoch(train) [2][28600/42151] lr: 3.0000e-04 eta: 19:14:44 time: 0.2782 data_time: 0.0716 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 18:37:46 - mmengine - INFO - Epoch(train) [2][28700/42151] lr: 3.0000e-04 eta: 19:13:59 time: 0.3833 data_time: 0.1729 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 18:38:22 - mmengine - INFO - Epoch(train) [2][28800/42151] lr: 3.0000e-04 eta: 19:13:14 time: 0.4407 data_time: 0.2369 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 18:38:42 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:38:57 - mmengine - INFO - Epoch(train) [2][28900/42151] lr: 3.0000e-04 eta: 19:12:30 time: 0.4324 data_time: 0.2294 memory: 7851 loss_ce: 0.0258 loss: 0.0258 2022/09/16 18:39:46 - mmengine - INFO - Epoch(train) [2][29000/42151] lr: 3.0000e-04 eta: 19:12:18 time: 0.4060 data_time: 0.2002 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 18:40:18 - mmengine - INFO - Epoch(train) [2][29100/42151] lr: 3.0000e-04 eta: 19:11:25 time: 0.2147 data_time: 0.0072 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 18:40:52 - mmengine - INFO - Epoch(train) [2][29200/42151] lr: 3.0000e-04 eta: 19:10:37 time: 0.3377 data_time: 0.1371 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 18:41:27 - mmengine - INFO - Epoch(train) [2][29300/42151] lr: 3.0000e-04 eta: 19:09:51 time: 0.4287 data_time: 0.2014 memory: 7851 loss_ce: 0.0284 loss: 0.0284 2022/09/16 18:42:02 - mmengine - INFO - Epoch(train) [2][29400/42151] lr: 3.0000e-04 eta: 19:09:04 time: 0.3396 data_time: 0.1334 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 18:42:48 - mmengine - INFO - Epoch(train) [2][29500/42151] lr: 3.0000e-04 eta: 19:08:48 time: 0.4718 data_time: 0.2490 memory: 7851 loss_ce: 0.0283 loss: 0.0283 2022/09/16 18:43:21 - mmengine - INFO - Epoch(train) [2][29600/42151] lr: 3.0000e-04 eta: 19:07:56 time: 0.2815 data_time: 0.0809 memory: 7851 loss_ce: 0.0285 loss: 0.0285 2022/09/16 18:43:58 - mmengine - INFO - Epoch(train) [2][29700/42151] lr: 3.0000e-04 eta: 19:07:17 time: 0.7235 data_time: 0.5044 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 18:44:29 - mmengine - INFO - Epoch(train) [2][29800/42151] lr: 3.0000e-04 eta: 19:06:21 time: 0.2059 data_time: 0.0047 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 18:44:45 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:45:06 - mmengine - INFO - Epoch(train) [2][29900/42151] lr: 3.0000e-04 eta: 19:05:39 time: 0.6880 data_time: 0.4693 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 18:45:38 - mmengine - INFO - Epoch(train) [2][30000/42151] lr: 3.0000e-04 eta: 19:04:46 time: 0.2112 data_time: 0.0049 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 18:46:09 - mmengine - INFO - Epoch(train) [2][30100/42151] lr: 3.0000e-04 eta: 19:03:51 time: 0.2622 data_time: 0.0322 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 18:46:44 - mmengine - INFO - Epoch(train) [2][30200/42151] lr: 3.0000e-04 eta: 19:03:06 time: 0.3775 data_time: 0.1381 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 18:47:19 - mmengine - INFO - Epoch(train) [2][30300/42151] lr: 3.0000e-04 eta: 19:02:20 time: 0.2426 data_time: 0.0329 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 18:48:07 - mmengine - INFO - Epoch(train) [2][30400/42151] lr: 3.0000e-04 eta: 19:02:08 time: 0.2038 data_time: 0.0048 memory: 7851 loss_ce: 0.0257 loss: 0.0257 2022/09/16 18:48:45 - mmengine - INFO - Epoch(train) [2][30500/42151] lr: 3.0000e-04 eta: 19:01:30 time: 0.5490 data_time: 0.3309 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 18:49:39 - mmengine - INFO - Epoch(train) [2][30600/42151] lr: 3.0000e-04 eta: 19:01:29 time: 0.7283 data_time: 0.5187 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 18:50:22 - mmengine - INFO - Epoch(train) [2][30700/42151] lr: 3.0000e-04 eta: 19:01:04 time: 0.2238 data_time: 0.0062 memory: 7851 loss_ce: 0.0273 loss: 0.0273 2022/09/16 18:51:26 - mmengine - INFO - Epoch(train) [2][30800/42151] lr: 3.0000e-04 eta: 19:01:30 time: 0.2074 data_time: 0.0051 memory: 7851 loss_ce: 0.0249 loss: 0.0249 2022/09/16 18:51:41 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:52:13 - mmengine - INFO - Epoch(train) [2][30900/42151] lr: 3.0000e-04 eta: 19:01:14 time: 0.2130 data_time: 0.0052 memory: 7851 loss_ce: 0.0278 loss: 0.0278 2022/09/16 18:52:51 - mmengine - INFO - Epoch(train) [2][31000/42151] lr: 3.0000e-04 eta: 19:00:36 time: 0.3579 data_time: 0.1500 memory: 7851 loss_ce: 0.0273 loss: 0.0273 2022/09/16 18:53:22 - mmengine - INFO - Epoch(train) [2][31100/42151] lr: 3.0000e-04 eta: 18:59:42 time: 0.2045 data_time: 0.0046 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 18:53:59 - mmengine - INFO - Epoch(train) [2][31200/42151] lr: 3.0000e-04 eta: 18:59:01 time: 0.2046 data_time: 0.0046 memory: 7851 loss_ce: 0.0271 loss: 0.0271 2022/09/16 18:54:35 - mmengine - INFO - Epoch(train) [2][31300/42151] lr: 3.0000e-04 eta: 18:58:16 time: 0.2299 data_time: 0.0089 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 18:55:08 - mmengine - INFO - Epoch(train) [2][31400/42151] lr: 3.0000e-04 eta: 18:57:26 time: 0.2222 data_time: 0.0251 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 18:55:41 - mmengine - INFO - Epoch(train) [2][31500/42151] lr: 3.0000e-04 eta: 18:56:36 time: 0.2116 data_time: 0.0049 memory: 7851 loss_ce: 0.0262 loss: 0.0262 2022/09/16 18:56:16 - mmengine - INFO - Epoch(train) [2][31600/42151] lr: 3.0000e-04 eta: 18:55:51 time: 0.3588 data_time: 0.1504 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 18:56:53 - mmengine - INFO - Epoch(train) [2][31700/42151] lr: 3.0000e-04 eta: 18:55:10 time: 0.2306 data_time: 0.0242 memory: 7851 loss_ce: 0.0244 loss: 0.0244 2022/09/16 18:57:28 - mmengine - INFO - Epoch(train) [2][31800/42151] lr: 3.0000e-04 eta: 18:54:23 time: 0.2207 data_time: 0.0076 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 18:57:44 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 18:58:02 - mmengine - INFO - Epoch(train) [2][31900/42151] lr: 3.0000e-04 eta: 18:53:37 time: 0.5078 data_time: 0.2949 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 18:58:35 - mmengine - INFO - Epoch(train) [2][32000/42151] lr: 3.0000e-04 eta: 18:52:45 time: 0.2332 data_time: 0.0062 memory: 7851 loss_ce: 0.0281 loss: 0.0281 2022/09/16 18:59:07 - mmengine - INFO - Epoch(train) [2][32100/42151] lr: 3.0000e-04 eta: 18:51:54 time: 0.2227 data_time: 0.0053 memory: 7851 loss_ce: 0.0285 loss: 0.0285 2022/09/16 18:59:46 - mmengine - INFO - Epoch(train) [2][32200/42151] lr: 3.0000e-04 eta: 18:51:18 time: 0.3012 data_time: 0.0063 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 19:00:20 - mmengine - INFO - Epoch(train) [2][32300/42151] lr: 3.0000e-04 eta: 18:50:30 time: 0.3856 data_time: 0.1816 memory: 7851 loss_ce: 0.0292 loss: 0.0292 2022/09/16 19:01:04 - mmengine - INFO - Epoch(train) [2][32400/42151] lr: 3.0000e-04 eta: 18:50:07 time: 0.2431 data_time: 0.0357 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 19:01:38 - mmengine - INFO - Epoch(train) [2][32500/42151] lr: 3.0000e-04 eta: 18:49:19 time: 0.4811 data_time: 0.2388 memory: 7851 loss_ce: 0.0273 loss: 0.0273 2022/09/16 19:02:17 - mmengine - INFO - Epoch(train) [2][32600/42151] lr: 3.0000e-04 eta: 18:48:43 time: 0.5003 data_time: 0.2513 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 19:02:50 - mmengine - INFO - Epoch(train) [2][32700/42151] lr: 3.0000e-04 eta: 18:47:53 time: 0.3235 data_time: 0.1243 memory: 7851 loss_ce: 0.0267 loss: 0.0267 2022/09/16 19:03:32 - mmengine - INFO - Epoch(train) [2][32800/42151] lr: 3.0000e-04 eta: 18:47:25 time: 0.2022 data_time: 0.0044 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 19:03:46 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:04:04 - mmengine - INFO - Epoch(train) [2][32900/42151] lr: 3.0000e-04 eta: 18:46:33 time: 0.4871 data_time: 0.2417 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 19:04:37 - mmengine - INFO - Epoch(train) [2][33000/42151] lr: 3.0000e-04 eta: 18:45:42 time: 0.3188 data_time: 0.1227 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 19:05:09 - mmengine - INFO - Epoch(train) [2][33100/42151] lr: 3.0000e-04 eta: 18:44:51 time: 0.4010 data_time: 0.1817 memory: 7851 loss_ce: 0.0296 loss: 0.0296 2022/09/16 19:05:46 - mmengine - INFO - Epoch(train) [2][33200/42151] lr: 3.0000e-04 eta: 18:44:10 time: 0.3711 data_time: 0.1481 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 19:06:19 - mmengine - INFO - Epoch(train) [2][33300/42151] lr: 3.0000e-04 eta: 18:43:19 time: 0.2879 data_time: 0.0886 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 19:06:52 - mmengine - INFO - Epoch(train) [2][33400/42151] lr: 3.0000e-04 eta: 18:42:30 time: 0.2812 data_time: 0.0799 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 19:07:25 - mmengine - INFO - Epoch(train) [2][33500/42151] lr: 3.0000e-04 eta: 18:41:40 time: 0.3429 data_time: 0.1086 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 19:08:00 - mmengine - INFO - Epoch(train) [2][33600/42151] lr: 3.0000e-04 eta: 18:40:56 time: 0.4464 data_time: 0.2390 memory: 7851 loss_ce: 0.0275 loss: 0.0275 2022/09/16 19:08:33 - mmengine - INFO - Epoch(train) [2][33700/42151] lr: 3.0000e-04 eta: 18:40:06 time: 0.3856 data_time: 0.1784 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 19:09:07 - mmengine - INFO - Epoch(train) [2][33800/42151] lr: 3.0000e-04 eta: 18:39:19 time: 0.3967 data_time: 0.1720 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 19:09:24 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:09:41 - mmengine - INFO - Epoch(train) [2][33900/42151] lr: 3.0000e-04 eta: 18:38:31 time: 0.3301 data_time: 0.1300 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:10:15 - mmengine - INFO - Epoch(train) [2][34000/42151] lr: 3.0000e-04 eta: 18:37:44 time: 0.3340 data_time: 0.1303 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 19:10:50 - mmengine - INFO - Epoch(train) [2][34100/42151] lr: 3.0000e-04 eta: 18:36:59 time: 0.4102 data_time: 0.1679 memory: 7851 loss_ce: 0.0291 loss: 0.0291 2022/09/16 19:11:24 - mmengine - INFO - Epoch(train) [2][34200/42151] lr: 3.0000e-04 eta: 18:36:13 time: 0.3308 data_time: 0.1252 memory: 7851 loss_ce: 0.0288 loss: 0.0288 2022/09/16 19:12:01 - mmengine - INFO - Epoch(train) [2][34300/42151] lr: 3.0000e-04 eta: 18:35:31 time: 0.3496 data_time: 0.1436 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 19:12:36 - mmengine - INFO - Epoch(train) [2][34400/42151] lr: 3.0000e-04 eta: 18:34:47 time: 0.3579 data_time: 0.1176 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:13:11 - mmengine - INFO - Epoch(train) [2][34500/42151] lr: 3.0000e-04 eta: 18:34:04 time: 0.3524 data_time: 0.1462 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 19:13:46 - mmengine - INFO - Epoch(train) [2][34600/42151] lr: 3.0000e-04 eta: 18:33:19 time: 0.3800 data_time: 0.1692 memory: 7851 loss_ce: 0.0267 loss: 0.0267 2022/09/16 19:14:22 - mmengine - INFO - Epoch(train) [2][34700/42151] lr: 3.0000e-04 eta: 18:32:36 time: 0.3452 data_time: 0.1491 memory: 7851 loss_ce: 0.0262 loss: 0.0262 2022/09/16 19:14:57 - mmengine - INFO - Epoch(train) [2][34800/42151] lr: 3.0000e-04 eta: 18:31:51 time: 0.3309 data_time: 0.1306 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 19:15:13 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:15:31 - mmengine - INFO - Epoch(train) [2][34900/42151] lr: 3.0000e-04 eta: 18:31:05 time: 0.3494 data_time: 0.1536 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:16:06 - mmengine - INFO - Epoch(train) [2][35000/42151] lr: 3.0000e-04 eta: 18:30:20 time: 0.3656 data_time: 0.1459 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 19:16:41 - mmengine - INFO - Epoch(train) [2][35100/42151] lr: 3.0000e-04 eta: 18:29:34 time: 0.3326 data_time: 0.1281 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 19:17:16 - mmengine - INFO - Epoch(train) [2][35200/42151] lr: 3.0000e-04 eta: 18:28:52 time: 0.3744 data_time: 0.1586 memory: 7851 loss_ce: 0.0290 loss: 0.0290 2022/09/16 19:17:52 - mmengine - INFO - Epoch(train) [2][35300/42151] lr: 3.0000e-04 eta: 18:28:08 time: 0.3921 data_time: 0.1796 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 19:18:25 - mmengine - INFO - Epoch(train) [2][35400/42151] lr: 3.0000e-04 eta: 18:27:20 time: 0.3328 data_time: 0.1324 memory: 7851 loss_ce: 0.0281 loss: 0.0281 2022/09/16 19:19:01 - mmengine - INFO - Epoch(train) [2][35500/42151] lr: 3.0000e-04 eta: 18:26:38 time: 0.3783 data_time: 0.1639 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 19:19:37 - mmengine - INFO - Epoch(train) [2][35600/42151] lr: 3.0000e-04 eta: 18:25:55 time: 0.3957 data_time: 0.1869 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 19:20:13 - mmengine - INFO - Epoch(train) [2][35700/42151] lr: 3.0000e-04 eta: 18:25:12 time: 0.3224 data_time: 0.0994 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 19:20:49 - mmengine - INFO - Epoch(train) [2][35800/42151] lr: 3.0000e-04 eta: 18:24:30 time: 0.3973 data_time: 0.1860 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 19:21:07 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:21:25 - mmengine - INFO - Epoch(train) [2][35900/42151] lr: 3.0000e-04 eta: 18:23:48 time: 0.3497 data_time: 0.1509 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 19:22:01 - mmengine - INFO - Epoch(train) [2][36000/42151] lr: 3.0000e-04 eta: 18:23:05 time: 0.3832 data_time: 0.1660 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 19:22:36 - mmengine - INFO - Epoch(train) [2][36100/42151] lr: 3.0000e-04 eta: 18:22:22 time: 0.3772 data_time: 0.1590 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 19:23:11 - mmengine - INFO - Epoch(train) [2][36200/42151] lr: 3.0000e-04 eta: 18:21:38 time: 0.3643 data_time: 0.1419 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 19:23:46 - mmengine - INFO - Epoch(train) [2][36300/42151] lr: 3.0000e-04 eta: 18:20:54 time: 0.3238 data_time: 0.1258 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 19:24:22 - mmengine - INFO - Epoch(train) [2][36400/42151] lr: 3.0000e-04 eta: 18:20:11 time: 0.3660 data_time: 0.1663 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 19:24:57 - mmengine - INFO - Epoch(train) [2][36500/42151] lr: 3.0000e-04 eta: 18:19:28 time: 0.3479 data_time: 0.1430 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 19:25:33 - mmengine - INFO - Epoch(train) [2][36600/42151] lr: 3.0000e-04 eta: 18:18:44 time: 0.3719 data_time: 0.1679 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 19:26:08 - mmengine - INFO - Epoch(train) [2][36700/42151] lr: 3.0000e-04 eta: 18:18:02 time: 0.3763 data_time: 0.1553 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 19:26:45 - mmengine - INFO - Epoch(train) [2][36800/42151] lr: 3.0000e-04 eta: 18:17:20 time: 0.4291 data_time: 0.2069 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 19:27:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:27:20 - mmengine - INFO - Epoch(train) [2][36900/42151] lr: 3.0000e-04 eta: 18:16:38 time: 0.3694 data_time: 0.1623 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:27:56 - mmengine - INFO - Epoch(train) [2][37000/42151] lr: 3.0000e-04 eta: 18:15:54 time: 0.3541 data_time: 0.1332 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 19:28:34 - mmengine - INFO - Epoch(train) [2][37100/42151] lr: 3.0000e-04 eta: 18:15:16 time: 0.3742 data_time: 0.1748 memory: 7851 loss_ce: 0.0282 loss: 0.0282 2022/09/16 19:29:10 - mmengine - INFO - Epoch(train) [2][37200/42151] lr: 3.0000e-04 eta: 18:14:35 time: 0.2972 data_time: 0.0943 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 19:30:06 - mmengine - INFO - Epoch(train) [2][37300/42151] lr: 3.0000e-04 eta: 18:14:37 time: 1.5395 data_time: 1.3370 memory: 7851 loss_ce: 0.0268 loss: 0.0268 2022/09/16 19:30:38 - mmengine - INFO - Epoch(train) [2][37400/42151] lr: 3.0000e-04 eta: 18:13:46 time: 0.2052 data_time: 0.0047 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 19:31:13 - mmengine - INFO - Epoch(train) [2][37500/42151] lr: 3.0000e-04 eta: 18:13:03 time: 0.2106 data_time: 0.0122 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 19:31:48 - mmengine - INFO - Epoch(train) [2][37600/42151] lr: 3.0000e-04 eta: 18:12:19 time: 0.2868 data_time: 0.0675 memory: 7851 loss_ce: 0.0258 loss: 0.0258 2022/09/16 19:32:28 - mmengine - INFO - Epoch(train) [2][37700/42151] lr: 3.0000e-04 eta: 18:11:44 time: 0.4926 data_time: 0.2776 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 19:33:04 - mmengine - INFO - Epoch(train) [2][37800/42151] lr: 3.0000e-04 eta: 18:11:02 time: 0.6297 data_time: 0.4271 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 19:33:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:33:58 - mmengine - INFO - Epoch(train) [2][37900/42151] lr: 3.0000e-04 eta: 18:10:59 time: 0.2243 data_time: 0.0054 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 19:34:32 - mmengine - INFO - Epoch(train) [2][38000/42151] lr: 3.0000e-04 eta: 18:10:13 time: 0.2330 data_time: 0.0062 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 19:35:09 - mmengine - INFO - Epoch(train) [2][38100/42151] lr: 3.0000e-04 eta: 18:09:35 time: 0.2126 data_time: 0.0047 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 19:35:53 - mmengine - INFO - Epoch(train) [2][38200/42151] lr: 3.0000e-04 eta: 18:09:08 time: 0.2461 data_time: 0.0090 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 19:36:25 - mmengine - INFO - Epoch(train) [2][38300/42151] lr: 3.0000e-04 eta: 18:08:18 time: 0.2360 data_time: 0.0070 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 19:37:00 - mmengine - INFO - Epoch(train) [2][38400/42151] lr: 3.0000e-04 eta: 18:07:36 time: 0.3417 data_time: 0.0913 memory: 7851 loss_ce: 0.0274 loss: 0.0274 2022/09/16 19:37:39 - mmengine - INFO - Epoch(train) [2][38500/42151] lr: 3.0000e-04 eta: 18:06:58 time: 1.0019 data_time: 0.7775 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 19:38:12 - mmengine - INFO - Epoch(train) [2][38600/42151] lr: 3.0000e-04 eta: 18:06:11 time: 0.3386 data_time: 0.0695 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 19:38:46 - mmengine - INFO - Epoch(train) [2][38700/42151] lr: 3.0000e-04 eta: 18:05:24 time: 0.3888 data_time: 0.1896 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 19:39:35 - mmengine - INFO - Epoch(train) [2][38800/42151] lr: 3.0000e-04 eta: 18:05:09 time: 1.0282 data_time: 0.8203 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 19:39:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:40:06 - mmengine - INFO - Epoch(train) [2][38900/42151] lr: 3.0000e-04 eta: 18:04:17 time: 0.3638 data_time: 0.1450 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 19:40:40 - mmengine - INFO - Epoch(train) [2][39000/42151] lr: 3.0000e-04 eta: 18:03:31 time: 0.3857 data_time: 0.1555 memory: 7851 loss_ce: 0.0270 loss: 0.0270 2022/09/16 19:41:11 - mmengine - INFO - Epoch(train) [2][39100/42151] lr: 3.0000e-04 eta: 18:02:39 time: 0.2130 data_time: 0.0130 memory: 7851 loss_ce: 0.0271 loss: 0.0271 2022/09/16 19:41:48 - mmengine - INFO - Epoch(train) [2][39200/42151] lr: 3.0000e-04 eta: 18:02:00 time: 0.6097 data_time: 0.3599 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 19:42:23 - mmengine - INFO - Epoch(train) [2][39300/42151] lr: 3.0000e-04 eta: 18:01:16 time: 0.2375 data_time: 0.0048 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 19:42:54 - mmengine - INFO - Epoch(train) [2][39400/42151] lr: 3.0000e-04 eta: 18:00:23 time: 0.3093 data_time: 0.1086 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 19:43:28 - mmengine - INFO - Epoch(train) [2][39500/42151] lr: 3.0000e-04 eta: 17:59:37 time: 0.3866 data_time: 0.1863 memory: 7851 loss_ce: 0.0286 loss: 0.0286 2022/09/16 19:44:02 - mmengine - INFO - Epoch(train) [2][39600/42151] lr: 3.0000e-04 eta: 17:58:52 time: 0.3800 data_time: 0.1720 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 19:44:43 - mmengine - INFO - Epoch(train) [2][39700/42151] lr: 3.0000e-04 eta: 17:58:22 time: 1.1499 data_time: 0.9185 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:45:14 - mmengine - INFO - Epoch(train) [2][39800/42151] lr: 3.0000e-04 eta: 17:57:29 time: 0.2816 data_time: 0.0754 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 19:45:31 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:45:49 - mmengine - INFO - Epoch(train) [2][39900/42151] lr: 3.0000e-04 eta: 17:56:44 time: 0.2152 data_time: 0.0131 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 19:46:23 - mmengine - INFO - Epoch(train) [2][40000/42151] lr: 3.0000e-04 eta: 17:55:59 time: 0.2426 data_time: 0.0423 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 19:46:55 - mmengine - INFO - Epoch(train) [2][40100/42151] lr: 3.0000e-04 eta: 17:55:09 time: 0.3543 data_time: 0.1517 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 19:47:30 - mmengine - INFO - Epoch(train) [2][40200/42151] lr: 3.0000e-04 eta: 17:54:25 time: 0.2770 data_time: 0.0446 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 19:48:10 - mmengine - INFO - Epoch(train) [2][40300/42151] lr: 3.0000e-04 eta: 17:53:51 time: 0.2647 data_time: 0.0329 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 19:48:46 - mmengine - INFO - Epoch(train) [2][40400/42151] lr: 3.0000e-04 eta: 17:53:10 time: 0.2058 data_time: 0.0053 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:49:19 - mmengine - INFO - Epoch(train) [2][40500/42151] lr: 3.0000e-04 eta: 17:52:23 time: 0.4922 data_time: 0.2519 memory: 7851 loss_ce: 0.0244 loss: 0.0244 2022/09/16 19:49:54 - mmengine - INFO - Epoch(train) [2][40600/42151] lr: 3.0000e-04 eta: 17:51:39 time: 0.5714 data_time: 0.3277 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 19:50:26 - mmengine - INFO - Epoch(train) [2][40700/42151] lr: 3.0000e-04 eta: 17:50:50 time: 0.4355 data_time: 0.2030 memory: 7851 loss_ce: 0.0258 loss: 0.0258 2022/09/16 19:51:00 - mmengine - INFO - Epoch(train) [2][40800/42151] lr: 3.0000e-04 eta: 17:50:04 time: 0.2533 data_time: 0.0477 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 19:51:17 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:51:33 - mmengine - INFO - Epoch(train) [2][40900/42151] lr: 3.0000e-04 eta: 17:49:15 time: 0.2429 data_time: 0.0371 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 19:52:08 - mmengine - INFO - Epoch(train) [2][41000/42151] lr: 3.0000e-04 eta: 17:48:34 time: 0.3843 data_time: 0.1807 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 19:52:42 - mmengine - INFO - Epoch(train) [2][41100/42151] lr: 3.0000e-04 eta: 17:47:48 time: 0.3381 data_time: 0.1297 memory: 7851 loss_ce: 0.0269 loss: 0.0269 2022/09/16 19:53:16 - mmengine - INFO - Epoch(train) [2][41200/42151] lr: 3.0000e-04 eta: 17:47:02 time: 0.3230 data_time: 0.1246 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 19:53:50 - mmengine - INFO - Epoch(train) [2][41300/42151] lr: 3.0000e-04 eta: 17:46:16 time: 0.3485 data_time: 0.1264 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 19:54:25 - mmengine - INFO - Epoch(train) [2][41400/42151] lr: 3.0000e-04 eta: 17:45:32 time: 0.4853 data_time: 0.2811 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 19:54:58 - mmengine - INFO - Epoch(train) [2][41500/42151] lr: 3.0000e-04 eta: 17:44:45 time: 0.2504 data_time: 0.0478 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 19:55:34 - mmengine - INFO - Epoch(train) [2][41600/42151] lr: 3.0000e-04 eta: 17:44:04 time: 0.3840 data_time: 0.1775 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 19:56:07 - mmengine - INFO - Epoch(train) [2][41700/42151] lr: 3.0000e-04 eta: 17:43:18 time: 0.2458 data_time: 0.0422 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 19:56:41 - mmengine - INFO - Epoch(train) [2][41800/42151] lr: 3.0000e-04 eta: 17:42:31 time: 0.2298 data_time: 0.0057 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 19:57:00 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:57:16 - mmengine - INFO - Epoch(train) [2][41900/42151] lr: 3.0000e-04 eta: 17:41:48 time: 0.4227 data_time: 0.1831 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 19:57:50 - mmengine - INFO - Epoch(train) [2][42000/42151] lr: 3.0000e-04 eta: 17:41:02 time: 0.2097 data_time: 0.0048 memory: 7851 loss_ce: 0.0280 loss: 0.0280 2022/09/16 19:58:24 - mmengine - INFO - Epoch(train) [2][42100/42151] lr: 3.0000e-04 eta: 17:40:17 time: 0.2005 data_time: 0.0048 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 19:58:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 19:58:39 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/09/16 19:59:21 - mmengine - INFO - Epoch(val) [2][100/7672] eta: 0:46:49 time: 0.3711 data_time: 0.0027 memory: 7851 2022/09/16 19:59:59 - mmengine - INFO - Epoch(val) [2][200/7672] eta: 0:43:33 time: 0.3498 data_time: 0.0008 memory: 580 2022/09/16 20:00:35 - mmengine - INFO - Epoch(val) [2][300/7672] eta: 0:24:52 time: 0.2024 data_time: 0.0008 memory: 580 2022/09/16 20:00:57 - mmengine - INFO - Epoch(val) [2][400/7672] eta: 0:25:15 time: 0.2084 data_time: 0.0008 memory: 580 2022/09/16 20:01:18 - mmengine - INFO - Epoch(val) [2][500/7672] eta: 0:24:24 time: 0.2042 data_time: 0.0008 memory: 580 2022/09/16 20:01:39 - mmengine - INFO - Epoch(val) [2][600/7672] eta: 0:23:01 time: 0.1953 data_time: 0.0008 memory: 580 2022/09/16 20:02:01 - mmengine - INFO - Epoch(val) [2][700/7672] eta: 0:24:06 time: 0.2075 data_time: 0.0039 memory: 580 2022/09/16 20:02:22 - mmengine - INFO - Epoch(val) [2][800/7672] eta: 0:25:19 time: 0.2211 data_time: 0.0010 memory: 580 2022/09/16 20:02:44 - mmengine - INFO - Epoch(val) [2][900/7672] eta: 0:22:38 time: 0.2007 data_time: 0.0010 memory: 580 2022/09/16 20:03:06 - mmengine - INFO - Epoch(val) [2][1000/7672] eta: 0:23:25 time: 0.2106 data_time: 0.0008 memory: 580 2022/09/16 20:03:27 - mmengine - INFO - Epoch(val) [2][1100/7672] eta: 0:22:37 time: 0.2065 data_time: 0.0013 memory: 580 2022/09/16 20:03:49 - mmengine - INFO - Epoch(val) [2][1200/7672] eta: 0:23:20 time: 0.2164 data_time: 0.0008 memory: 580 2022/09/16 20:04:11 - mmengine - INFO - Epoch(val) [2][1300/7672] eta: 0:22:45 time: 0.2143 data_time: 0.0017 memory: 580 2022/09/16 20:04:33 - mmengine - INFO - Epoch(val) [2][1400/7672] eta: 0:25:41 time: 0.2458 data_time: 0.0019 memory: 580 2022/09/16 20:04:55 - mmengine - INFO - Epoch(val) [2][1500/7672] eta: 0:21:41 time: 0.2108 data_time: 0.0008 memory: 580 2022/09/16 20:05:17 - mmengine - INFO - Epoch(val) [2][1600/7672] eta: 0:21:55 time: 0.2166 data_time: 0.0008 memory: 580 2022/09/16 20:05:38 - mmengine - INFO - Epoch(val) [2][1700/7672] eta: 0:20:03 time: 0.2015 data_time: 0.0007 memory: 580 2022/09/16 20:05:59 - mmengine - INFO - Epoch(val) [2][1800/7672] eta: 0:20:44 time: 0.2120 data_time: 0.0008 memory: 580 2022/09/16 20:06:21 - mmengine - INFO - Epoch(val) [2][1900/7672] eta: 0:19:42 time: 0.2048 data_time: 0.0007 memory: 580 2022/09/16 20:06:43 - mmengine - INFO - Epoch(val) [2][2000/7672] eta: 0:19:05 time: 0.2020 data_time: 0.0012 memory: 580 2022/09/16 20:07:04 - mmengine - INFO - Epoch(val) [2][2100/7672] eta: 0:20:34 time: 0.2215 data_time: 0.0008 memory: 580 2022/09/16 20:07:26 - mmengine - INFO - Epoch(val) [2][2200/7672] eta: 0:19:07 time: 0.2097 data_time: 0.0008 memory: 580 2022/09/16 20:07:48 - mmengine - INFO - Epoch(val) [2][2300/7672] eta: 0:19:28 time: 0.2174 data_time: 0.0008 memory: 580 2022/09/16 20:08:10 - mmengine - INFO - Epoch(val) [2][2400/7672] eta: 0:18:49 time: 0.2143 data_time: 0.0008 memory: 580 2022/09/16 20:08:32 - mmengine - INFO - Epoch(val) [2][2500/7672] eta: 0:21:07 time: 0.2450 data_time: 0.0021 memory: 580 2022/09/16 20:08:54 - mmengine - INFO - Epoch(val) [2][2600/7672] eta: 0:18:24 time: 0.2178 data_time: 0.0008 memory: 580 2022/09/16 20:09:15 - mmengine - INFO - Epoch(val) [2][2700/7672] eta: 0:17:46 time: 0.2145 data_time: 0.0014 memory: 580 2022/09/16 20:09:37 - mmengine - INFO - Epoch(val) [2][2800/7672] eta: 0:17:10 time: 0.2116 data_time: 0.0008 memory: 580 2022/09/16 20:09:59 - mmengine - INFO - Epoch(val) [2][2900/7672] eta: 0:16:11 time: 0.2035 data_time: 0.0008 memory: 580 2022/09/16 20:10:21 - mmengine - INFO - Epoch(val) [2][3000/7672] eta: 0:15:26 time: 0.1983 data_time: 0.0013 memory: 580 2022/09/16 20:10:42 - mmengine - INFO - Epoch(val) [2][3100/7672] eta: 0:17:20 time: 0.2275 data_time: 0.0016 memory: 580 2022/09/16 20:11:04 - mmengine - INFO - Epoch(val) [2][3200/7672] eta: 0:14:47 time: 0.1984 data_time: 0.0009 memory: 580 2022/09/16 20:11:25 - mmengine - INFO - Epoch(val) [2][3300/7672] eta: 0:14:58 time: 0.2056 data_time: 0.0008 memory: 580 2022/09/16 20:11:47 - mmengine - INFO - Epoch(val) [2][3400/7672] eta: 0:15:58 time: 0.2243 data_time: 0.0009 memory: 580 2022/09/16 20:12:08 - mmengine - INFO - Epoch(val) [2][3500/7672] eta: 0:15:40 time: 0.2255 data_time: 0.0010 memory: 580 2022/09/16 20:12:30 - mmengine - INFO - Epoch(val) [2][3600/7672] eta: 0:13:47 time: 0.2033 data_time: 0.0010 memory: 580 2022/09/16 20:12:52 - mmengine - INFO - Epoch(val) [2][3700/7672] eta: 0:13:34 time: 0.2051 data_time: 0.0047 memory: 580 2022/09/16 20:13:13 - mmengine - INFO - Epoch(val) [2][3800/7672] eta: 0:13:57 time: 0.2164 data_time: 0.0012 memory: 580 2022/09/16 20:13:35 - mmengine - INFO - Epoch(val) [2][3900/7672] eta: 0:16:46 time: 0.2669 data_time: 0.0010 memory: 580 2022/09/16 20:13:56 - mmengine - INFO - Epoch(val) [2][4000/7672] eta: 0:13:45 time: 0.2248 data_time: 0.0008 memory: 580 2022/09/16 20:14:18 - mmengine - INFO - Epoch(val) [2][4100/7672] eta: 0:12:35 time: 0.2115 data_time: 0.0008 memory: 580 2022/09/16 20:14:40 - mmengine - INFO - Epoch(val) [2][4200/7672] eta: 0:12:02 time: 0.2082 data_time: 0.0008 memory: 580 2022/09/16 20:15:01 - mmengine - INFO - Epoch(val) [2][4300/7672] eta: 0:11:17 time: 0.2011 data_time: 0.0009 memory: 580 2022/09/16 20:15:23 - mmengine - INFO - Epoch(val) [2][4400/7672] eta: 0:11:06 time: 0.2037 data_time: 0.0016 memory: 580 2022/09/16 20:15:46 - mmengine - INFO - Epoch(val) [2][4500/7672] eta: 0:10:40 time: 0.2018 data_time: 0.0008 memory: 580 2022/09/16 20:16:07 - mmengine - INFO - Epoch(val) [2][4600/7672] eta: 0:10:30 time: 0.2054 data_time: 0.0008 memory: 580 2022/09/16 20:16:29 - mmengine - INFO - Epoch(val) [2][4700/7672] eta: 0:09:48 time: 0.1979 data_time: 0.0007 memory: 580 2022/09/16 20:16:51 - mmengine - INFO - Epoch(val) [2][4800/7672] eta: 0:09:38 time: 0.2014 data_time: 0.0008 memory: 580 2022/09/16 20:17:14 - mmengine - INFO - Epoch(val) [2][4900/7672] eta: 0:09:30 time: 0.2058 data_time: 0.0007 memory: 580 2022/09/16 20:17:35 - mmengine - INFO - Epoch(val) [2][5000/7672] eta: 0:09:06 time: 0.2045 data_time: 0.0010 memory: 580 2022/09/16 20:17:56 - mmengine - INFO - Epoch(val) [2][5100/7672] eta: 0:09:30 time: 0.2219 data_time: 0.0008 memory: 580 2022/09/16 20:18:19 - mmengine - INFO - Epoch(val) [2][5200/7672] eta: 0:08:29 time: 0.2062 data_time: 0.0007 memory: 580 2022/09/16 20:18:41 - mmengine - INFO - Epoch(val) [2][5300/7672] eta: 0:09:54 time: 0.2505 data_time: 0.0009 memory: 580 2022/09/16 20:19:02 - mmengine - INFO - Epoch(val) [2][5400/7672] eta: 0:09:28 time: 0.2500 data_time: 0.0008 memory: 580 2022/09/16 20:19:24 - mmengine - INFO - Epoch(val) [2][5500/7672] eta: 0:07:56 time: 0.2194 data_time: 0.0024 memory: 580 2022/09/16 20:19:46 - mmengine - INFO - Epoch(val) [2][5600/7672] eta: 0:06:47 time: 0.1965 data_time: 0.0010 memory: 580 2022/09/16 20:20:07 - mmengine - INFO - Epoch(val) [2][5700/7672] eta: 0:06:46 time: 0.2062 data_time: 0.0008 memory: 580 2022/09/16 20:20:28 - mmengine - INFO - Epoch(val) [2][5800/7672] eta: 0:06:08 time: 0.1967 data_time: 0.0010 memory: 580 2022/09/16 20:20:50 - mmengine - INFO - Epoch(val) [2][5900/7672] eta: 0:05:58 time: 0.2025 data_time: 0.0008 memory: 580 2022/09/16 20:21:12 - mmengine - INFO - Epoch(val) [2][6000/7672] eta: 0:07:07 time: 0.2558 data_time: 0.0010 memory: 580 2022/09/16 20:21:33 - mmengine - INFO - Epoch(val) [2][6100/7672] eta: 0:06:48 time: 0.2597 data_time: 0.0010 memory: 580 2022/09/16 20:21:55 - mmengine - INFO - Epoch(val) [2][6200/7672] eta: 0:05:30 time: 0.2246 data_time: 0.0012 memory: 580 2022/09/16 20:22:17 - mmengine - INFO - Epoch(val) [2][6300/7672] eta: 0:04:36 time: 0.2019 data_time: 0.0008 memory: 580 2022/09/16 20:22:39 - mmengine - INFO - Epoch(val) [2][6400/7672] eta: 0:05:24 time: 0.2554 data_time: 0.0009 memory: 580 2022/09/16 20:22:59 - mmengine - INFO - Epoch(val) [2][6500/7672] eta: 0:04:02 time: 0.2068 data_time: 0.0008 memory: 580 2022/09/16 20:23:20 - mmengine - INFO - Epoch(val) [2][6600/7672] eta: 0:03:39 time: 0.2044 data_time: 0.0013 memory: 580 2022/09/16 20:23:42 - mmengine - INFO - Epoch(val) [2][6700/7672] eta: 0:03:16 time: 0.2023 data_time: 0.0008 memory: 580 2022/09/16 20:24:03 - mmengine - INFO - Epoch(val) [2][6800/7672] eta: 0:03:30 time: 0.2416 data_time: 0.0034 memory: 580 2022/09/16 20:24:25 - mmengine - INFO - Epoch(val) [2][6900/7672] eta: 0:02:37 time: 0.2037 data_time: 0.0009 memory: 580 2022/09/16 20:24:47 - mmengine - INFO - Epoch(val) [2][7000/7672] eta: 0:02:13 time: 0.1984 data_time: 0.0007 memory: 580 2022/09/16 20:25:09 - mmengine - INFO - Epoch(val) [2][7100/7672] eta: 0:01:54 time: 0.2002 data_time: 0.0007 memory: 580 2022/09/16 20:25:30 - mmengine - INFO - Epoch(val) [2][7200/7672] eta: 0:01:34 time: 0.2001 data_time: 0.0007 memory: 580 2022/09/16 20:25:52 - mmengine - INFO - Epoch(val) [2][7300/7672] eta: 0:01:13 time: 0.1969 data_time: 0.0008 memory: 580 2022/09/16 20:26:14 - mmengine - INFO - Epoch(val) [2][7400/7672] eta: 0:00:57 time: 0.2098 data_time: 0.0017 memory: 580 2022/09/16 20:26:35 - mmengine - INFO - Epoch(val) [2][7500/7672] eta: 0:00:35 time: 0.2058 data_time: 0.0008 memory: 580 2022/09/16 20:26:56 - mmengine - INFO - Epoch(val) [2][7600/7672] eta: 0:00:14 time: 0.2021 data_time: 0.0009 memory: 580 2022/09/16 20:27:12 - mmengine - INFO - Epoch(val) [2][7672/7672] CUTE80/recog/word_acc_ignore_case_symbol: 0.7153 IIIT5K/recog/word_acc_ignore_case_symbol: 0.8857 SVT/recog/word_acc_ignore_case_symbol: 0.8501 SVTP/recog/word_acc_ignore_case_symbol: 0.7318 IC13/recog/word_acc_ignore_case_symbol: 0.9054 IC15/recog/word_acc_ignore_case_symbol: 0.6866 2022/09/16 20:27:54 - mmengine - INFO - Epoch(train) [3][100/42151] lr: 3.0000e-04 eta: 17:39:17 time: 0.3777 data_time: 0.1643 memory: 7851 loss_ce: 0.0272 loss: 0.0272 2022/09/16 20:28:28 - mmengine - INFO - Epoch(train) [3][200/42151] lr: 3.0000e-04 eta: 17:38:32 time: 0.3021 data_time: 0.0774 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 20:29:05 - mmengine - INFO - Epoch(train) [3][300/42151] lr: 3.0000e-04 eta: 17:37:52 time: 0.3927 data_time: 0.1260 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 20:29:39 - mmengine - INFO - Epoch(train) [3][400/42151] lr: 3.0000e-04 eta: 17:37:07 time: 0.3696 data_time: 0.1547 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 20:30:16 - mmengine - INFO - Epoch(train) [3][500/42151] lr: 3.0000e-04 eta: 17:36:28 time: 0.5526 data_time: 0.3432 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 20:30:48 - mmengine - INFO - Epoch(train) [3][600/42151] lr: 3.0000e-04 eta: 17:35:40 time: 0.3146 data_time: 0.0948 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 20:31:23 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 20:31:23 - mmengine - INFO - Epoch(train) [3][700/42151] lr: 3.0000e-04 eta: 17:34:57 time: 0.4201 data_time: 0.1904 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 20:31:58 - mmengine - INFO - Epoch(train) [3][800/42151] lr: 3.0000e-04 eta: 17:34:13 time: 0.3649 data_time: 0.1616 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 20:32:33 - mmengine - INFO - Epoch(train) [3][900/42151] lr: 3.0000e-04 eta: 17:33:30 time: 0.3042 data_time: 0.0974 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 20:33:08 - mmengine - INFO - Epoch(train) [3][1000/42151] lr: 3.0000e-04 eta: 17:32:47 time: 0.3579 data_time: 0.1557 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 20:33:48 - mmengine - INFO - Epoch(train) [3][1100/42151] lr: 3.0000e-04 eta: 17:32:14 time: 0.5615 data_time: 0.3467 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 20:34:25 - mmengine - INFO - Epoch(train) [3][1200/42151] lr: 3.0000e-04 eta: 17:31:36 time: 0.2405 data_time: 0.0055 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 20:35:15 - mmengine - INFO - Epoch(train) [3][1300/42151] lr: 3.0000e-04 eta: 17:31:21 time: 0.2769 data_time: 0.0704 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 20:35:48 - mmengine - INFO - Epoch(train) [3][1400/42151] lr: 3.0000e-04 eta: 17:30:34 time: 0.3206 data_time: 0.1196 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 20:36:34 - mmengine - INFO - Epoch(train) [3][1500/42151] lr: 3.0000e-04 eta: 17:30:12 time: 0.2180 data_time: 0.0051 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 20:37:08 - mmengine - INFO - Epoch(train) [3][1600/42151] lr: 3.0000e-04 eta: 17:29:28 time: 0.2075 data_time: 0.0048 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 20:37:40 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 20:37:41 - mmengine - INFO - Epoch(train) [3][1700/42151] lr: 3.0000e-04 eta: 17:28:41 time: 0.2125 data_time: 0.0134 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 20:38:18 - mmengine - INFO - Epoch(train) [3][1800/42151] lr: 3.0000e-04 eta: 17:28:02 time: 0.2243 data_time: 0.0060 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 20:38:51 - mmengine - INFO - Epoch(train) [3][1900/42151] lr: 3.0000e-04 eta: 17:27:15 time: 0.2088 data_time: 0.0048 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 20:39:27 - mmengine - INFO - Epoch(train) [3][2000/42151] lr: 3.0000e-04 eta: 17:26:33 time: 0.2123 data_time: 0.0051 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 20:40:01 - mmengine - INFO - Epoch(train) [3][2100/42151] lr: 3.0000e-04 eta: 17:25:48 time: 0.3558 data_time: 0.1265 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 20:40:33 - mmengine - INFO - Epoch(train) [3][2200/42151] lr: 3.0000e-04 eta: 17:25:00 time: 0.3693 data_time: 0.1539 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 20:41:07 - mmengine - INFO - Epoch(train) [3][2300/42151] lr: 3.0000e-04 eta: 17:24:16 time: 0.2386 data_time: 0.0339 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 20:41:44 - mmengine - INFO - Epoch(train) [3][2400/42151] lr: 3.0000e-04 eta: 17:23:37 time: 0.7520 data_time: 0.5223 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 20:42:24 - mmengine - INFO - Epoch(train) [3][2500/42151] lr: 3.0000e-04 eta: 17:23:03 time: 0.9306 data_time: 0.7188 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 20:42:54 - mmengine - INFO - Epoch(train) [3][2600/42151] lr: 3.0000e-04 eta: 17:22:10 time: 0.2325 data_time: 0.0062 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 20:43:43 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 20:43:44 - mmengine - INFO - Epoch(train) [3][2700/42151] lr: 3.0000e-04 eta: 17:21:57 time: 0.2751 data_time: 0.0208 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 20:44:20 - mmengine - INFO - Epoch(train) [3][2800/42151] lr: 3.0000e-04 eta: 17:21:15 time: 0.3682 data_time: 0.1457 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 20:44:53 - mmengine - INFO - Epoch(train) [3][2900/42151] lr: 3.0000e-04 eta: 17:20:28 time: 0.4064 data_time: 0.2019 memory: 7851 loss_ce: 0.0249 loss: 0.0249 2022/09/16 20:45:28 - mmengine - INFO - Epoch(train) [3][3000/42151] lr: 3.0000e-04 eta: 17:19:47 time: 0.6448 data_time: 0.4372 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 20:46:03 - mmengine - INFO - Epoch(train) [3][3100/42151] lr: 3.0000e-04 eta: 17:19:03 time: 0.3909 data_time: 0.1593 memory: 7851 loss_ce: 0.0264 loss: 0.0264 2022/09/16 20:46:39 - mmengine - INFO - Epoch(train) [3][3200/42151] lr: 3.0000e-04 eta: 17:18:23 time: 0.2574 data_time: 0.0064 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 20:47:14 - mmengine - INFO - Epoch(train) [3][3300/42151] lr: 3.0000e-04 eta: 17:17:39 time: 0.3264 data_time: 0.1189 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 20:47:52 - mmengine - INFO - Epoch(train) [3][3400/42151] lr: 3.0000e-04 eta: 17:17:03 time: 0.6200 data_time: 0.4104 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 20:48:26 - mmengine - INFO - Epoch(train) [3][3500/42151] lr: 3.0000e-04 eta: 17:16:19 time: 0.2721 data_time: 0.0709 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 20:49:02 - mmengine - INFO - Epoch(train) [3][3600/42151] lr: 3.0000e-04 eta: 17:15:36 time: 0.5398 data_time: 0.3278 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 20:49:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 20:49:38 - mmengine - INFO - Epoch(train) [3][3700/42151] lr: 3.0000e-04 eta: 17:14:57 time: 0.3283 data_time: 0.1251 memory: 7851 loss_ce: 0.0212 loss: 0.0212 2022/09/16 20:50:13 - mmengine - INFO - Epoch(train) [3][3800/42151] lr: 3.0000e-04 eta: 17:14:15 time: 0.3455 data_time: 0.1068 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 20:50:47 - mmengine - INFO - Epoch(train) [3][3900/42151] lr: 3.0000e-04 eta: 17:13:30 time: 0.2100 data_time: 0.0049 memory: 7851 loss_ce: 0.0261 loss: 0.0261 2022/09/16 20:51:22 - mmengine - INFO - Epoch(train) [3][4000/42151] lr: 3.0000e-04 eta: 17:12:47 time: 0.5173 data_time: 0.3141 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 20:51:56 - mmengine - INFO - Epoch(train) [3][4100/42151] lr: 3.0000e-04 eta: 17:12:02 time: 0.2376 data_time: 0.0126 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 20:52:43 - mmengine - INFO - Epoch(train) [3][4200/42151] lr: 3.0000e-04 eta: 17:11:43 time: 0.2589 data_time: 0.0049 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 20:53:14 - mmengine - INFO - Epoch(train) [3][4300/42151] lr: 3.0000e-04 eta: 17:10:52 time: 0.2753 data_time: 0.0724 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 20:53:56 - mmengine - INFO - Epoch(train) [3][4400/42151] lr: 3.0000e-04 eta: 17:10:22 time: 0.3272 data_time: 0.1247 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 20:54:28 - mmengine - INFO - Epoch(train) [3][4500/42151] lr: 3.0000e-04 eta: 17:09:35 time: 0.2138 data_time: 0.0133 memory: 7851 loss_ce: 0.0255 loss: 0.0255 2022/09/16 20:55:03 - mmengine - INFO - Epoch(train) [3][4600/42151] lr: 3.0000e-04 eta: 17:08:52 time: 0.2844 data_time: 0.0568 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 20:55:45 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 20:55:46 - mmengine - INFO - Epoch(train) [3][4700/42151] lr: 3.0000e-04 eta: 17:08:23 time: 0.4042 data_time: 0.1879 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 20:56:33 - mmengine - INFO - Epoch(train) [3][4800/42151] lr: 3.0000e-04 eta: 17:08:03 time: 1.0701 data_time: 0.8688 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 20:57:03 - mmengine - INFO - Epoch(train) [3][4900/42151] lr: 3.0000e-04 eta: 17:07:11 time: 0.4332 data_time: 0.2291 memory: 7851 loss_ce: 0.0226 loss: 0.0226 2022/09/16 20:57:46 - mmengine - INFO - Epoch(train) [3][5000/42151] lr: 3.0000e-04 eta: 17:06:44 time: 0.2234 data_time: 0.0083 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 20:58:21 - mmengine - INFO - Epoch(train) [3][5100/42151] lr: 3.0000e-04 eta: 17:06:00 time: 0.3308 data_time: 0.1314 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 20:58:53 - mmengine - INFO - Epoch(train) [3][5200/42151] lr: 3.0000e-04 eta: 17:05:13 time: 0.3308 data_time: 0.0927 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 20:59:27 - mmengine - INFO - Epoch(train) [3][5300/42151] lr: 3.0000e-04 eta: 17:04:28 time: 0.2153 data_time: 0.0054 memory: 7851 loss_ce: 0.0205 loss: 0.0205 2022/09/16 21:00:00 - mmengine - INFO - Epoch(train) [3][5400/42151] lr: 3.0000e-04 eta: 17:03:42 time: 0.2398 data_time: 0.0048 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 21:00:36 - mmengine - INFO - Epoch(train) [3][5500/42151] lr: 3.0000e-04 eta: 17:03:02 time: 0.4392 data_time: 0.2316 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 21:01:08 - mmengine - INFO - Epoch(train) [3][5600/42151] lr: 3.0000e-04 eta: 17:02:14 time: 0.2137 data_time: 0.0053 memory: 7851 loss_ce: 0.0233 loss: 0.0233 2022/09/16 21:01:41 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:01:42 - mmengine - INFO - Epoch(train) [3][5700/42151] lr: 3.0000e-04 eta: 17:01:30 time: 0.2243 data_time: 0.0159 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 21:02:14 - mmengine - INFO - Epoch(train) [3][5800/42151] lr: 3.0000e-04 eta: 17:00:42 time: 0.2535 data_time: 0.0144 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 21:02:48 - mmengine - INFO - Epoch(train) [3][5900/42151] lr: 3.0000e-04 eta: 16:59:58 time: 0.3838 data_time: 0.1802 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 21:03:23 - mmengine - INFO - Epoch(train) [3][6000/42151] lr: 3.0000e-04 eta: 16:59:15 time: 0.4616 data_time: 0.2556 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 21:03:55 - mmengine - INFO - Epoch(train) [3][6100/42151] lr: 3.0000e-04 eta: 16:58:26 time: 0.2678 data_time: 0.0588 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 21:04:34 - mmengine - INFO - Epoch(train) [3][6200/42151] lr: 3.0000e-04 eta: 16:57:53 time: 0.9377 data_time: 0.7319 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 21:05:05 - mmengine - INFO - Epoch(train) [3][6300/42151] lr: 3.0000e-04 eta: 16:57:02 time: 0.3093 data_time: 0.0705 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 21:05:39 - mmengine - INFO - Epoch(train) [3][6400/42151] lr: 3.0000e-04 eta: 16:56:18 time: 0.3026 data_time: 0.0939 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/16 21:06:13 - mmengine - INFO - Epoch(train) [3][6500/42151] lr: 3.0000e-04 eta: 16:55:34 time: 0.4035 data_time: 0.1979 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 21:06:55 - mmengine - INFO - Epoch(train) [3][6600/42151] lr: 3.0000e-04 eta: 16:55:05 time: 0.4733 data_time: 0.2442 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 21:07:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:07:28 - mmengine - INFO - Epoch(train) [3][6700/42151] lr: 3.0000e-04 eta: 16:54:18 time: 0.2757 data_time: 0.0174 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 21:08:03 - mmengine - INFO - Epoch(train) [3][6800/42151] lr: 3.0000e-04 eta: 16:53:36 time: 0.2062 data_time: 0.0048 memory: 7851 loss_ce: 0.0223 loss: 0.0223 2022/09/16 21:08:57 - mmengine - INFO - Epoch(train) [3][6900/42151] lr: 3.0000e-04 eta: 16:53:28 time: 1.8140 data_time: 1.5565 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 21:09:27 - mmengine - INFO - Epoch(train) [3][7000/42151] lr: 3.0000e-04 eta: 16:52:38 time: 0.4444 data_time: 0.2388 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 21:10:11 - mmengine - INFO - Epoch(train) [3][7100/42151] lr: 3.0000e-04 eta: 16:52:11 time: 0.5180 data_time: 0.2968 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 21:10:43 - mmengine - INFO - Epoch(train) [3][7200/42151] lr: 3.0000e-04 eta: 16:51:23 time: 0.4550 data_time: 0.2200 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 21:11:17 - mmengine - INFO - Epoch(train) [3][7300/42151] lr: 3.0000e-04 eta: 16:50:39 time: 0.3333 data_time: 0.1267 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/16 21:11:52 - mmengine - INFO - Epoch(train) [3][7400/42151] lr: 3.0000e-04 eta: 16:49:57 time: 0.2233 data_time: 0.0058 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 21:12:33 - mmengine - INFO - Epoch(train) [3][7500/42151] lr: 3.0000e-04 eta: 16:49:25 time: 0.3581 data_time: 0.1557 memory: 7851 loss_ce: 0.0249 loss: 0.0249 2022/09/16 21:13:15 - mmengine - INFO - Epoch(train) [3][7600/42151] lr: 3.0000e-04 eta: 16:48:56 time: 0.2090 data_time: 0.0048 memory: 7851 loss_ce: 0.0233 loss: 0.0233 2022/09/16 21:13:46 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:13:46 - mmengine - INFO - Epoch(train) [3][7700/42151] lr: 3.0000e-04 eta: 16:48:07 time: 0.2820 data_time: 0.0783 memory: 7851 loss_ce: 0.0276 loss: 0.0276 2022/09/16 21:14:24 - mmengine - INFO - Epoch(train) [3][7800/42151] lr: 3.0000e-04 eta: 16:47:30 time: 0.6274 data_time: 0.4246 memory: 7851 loss_ce: 0.0257 loss: 0.0257 2022/09/16 21:15:01 - mmengine - INFO - Epoch(train) [3][7900/42151] lr: 3.0000e-04 eta: 16:46:51 time: 0.2068 data_time: 0.0048 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 21:15:33 - mmengine - INFO - Epoch(train) [3][8000/42151] lr: 3.0000e-04 eta: 16:46:03 time: 0.2072 data_time: 0.0051 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 21:16:08 - mmengine - INFO - Epoch(train) [3][8100/42151] lr: 3.0000e-04 eta: 16:45:20 time: 0.4303 data_time: 0.2046 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 21:16:43 - mmengine - INFO - Epoch(train) [3][8200/42151] lr: 3.0000e-04 eta: 16:44:38 time: 0.4794 data_time: 0.2520 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 21:17:15 - mmengine - INFO - Epoch(train) [3][8300/42151] lr: 3.0000e-04 eta: 16:43:51 time: 0.2871 data_time: 0.0866 memory: 7851 loss_ce: 0.0260 loss: 0.0260 2022/09/16 21:17:59 - mmengine - INFO - Epoch(train) [3][8400/42151] lr: 3.0000e-04 eta: 16:43:25 time: 0.2275 data_time: 0.0052 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 21:18:34 - mmengine - INFO - Epoch(train) [3][8500/42151] lr: 3.0000e-04 eta: 16:42:43 time: 0.2425 data_time: 0.0123 memory: 7851 loss_ce: 0.0233 loss: 0.0233 2022/09/16 21:19:14 - mmengine - INFO - Epoch(train) [3][8600/42151] lr: 3.0000e-04 eta: 16:42:09 time: 0.9349 data_time: 0.7042 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 21:20:26 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:20:27 - mmengine - INFO - Epoch(train) [3][8700/42151] lr: 3.0000e-04 eta: 16:42:33 time: 1.8330 data_time: 1.6314 memory: 7851 loss_ce: 0.0233 loss: 0.0233 2022/09/16 21:21:00 - mmengine - INFO - Epoch(train) [3][8800/42151] lr: 3.0000e-04 eta: 16:41:46 time: 0.2042 data_time: 0.0048 memory: 7851 loss_ce: 0.0271 loss: 0.0271 2022/09/16 21:21:35 - mmengine - INFO - Epoch(train) [3][8900/42151] lr: 3.0000e-04 eta: 16:41:06 time: 0.2096 data_time: 0.0051 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 21:22:20 - mmengine - INFO - Epoch(train) [3][9000/42151] lr: 3.0000e-04 eta: 16:40:41 time: 0.3347 data_time: 0.0671 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 21:22:53 - mmengine - INFO - Epoch(train) [3][9100/42151] lr: 3.0000e-04 eta: 16:39:55 time: 0.2354 data_time: 0.0065 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 21:23:37 - mmengine - INFO - Epoch(train) [3][9200/42151] lr: 3.0000e-04 eta: 16:39:27 time: 0.2033 data_time: 0.0046 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 21:24:12 - mmengine - INFO - Epoch(train) [3][9300/42151] lr: 3.0000e-04 eta: 16:38:46 time: 0.2159 data_time: 0.0068 memory: 7851 loss_ce: 0.0259 loss: 0.0259 2022/09/16 21:24:49 - mmengine - INFO - Epoch(train) [3][9400/42151] lr: 3.0000e-04 eta: 16:38:07 time: 0.2159 data_time: 0.0067 memory: 7851 loss_ce: 0.0250 loss: 0.0250 2022/09/16 21:25:24 - mmengine - INFO - Epoch(train) [3][9500/42151] lr: 3.0000e-04 eta: 16:37:24 time: 0.2475 data_time: 0.0307 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 21:26:13 - mmengine - INFO - Epoch(train) [3][9600/42151] lr: 3.0000e-04 eta: 16:37:06 time: 0.3959 data_time: 0.1885 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 21:26:58 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:27:00 - mmengine - INFO - Epoch(train) [3][9700/42151] lr: 3.0000e-04 eta: 16:36:44 time: 0.4737 data_time: 0.2655 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 21:27:36 - mmengine - INFO - Epoch(train) [3][9800/42151] lr: 3.0000e-04 eta: 16:36:04 time: 0.2348 data_time: 0.0046 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 21:28:25 - mmengine - INFO - Epoch(train) [3][9900/42151] lr: 3.0000e-04 eta: 16:35:46 time: 1.2212 data_time: 1.0181 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 21:28:55 - mmengine - INFO - Epoch(train) [3][10000/42151] lr: 3.0000e-04 eta: 16:34:56 time: 0.2314 data_time: 0.0285 memory: 7851 loss_ce: 0.0229 loss: 0.0229 2022/09/16 21:29:32 - mmengine - INFO - Epoch(train) [3][10100/42151] lr: 3.0000e-04 eta: 16:34:16 time: 0.3269 data_time: 0.1225 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 21:30:04 - mmengine - INFO - Epoch(train) [3][10200/42151] lr: 3.0000e-04 eta: 16:33:29 time: 0.3253 data_time: 0.1216 memory: 7851 loss_ce: 0.0244 loss: 0.0244 2022/09/16 21:30:40 - mmengine - INFO - Epoch(train) [3][10300/42151] lr: 3.0000e-04 eta: 16:32:48 time: 0.3878 data_time: 0.1736 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 21:31:17 - mmengine - INFO - Epoch(train) [3][10400/42151] lr: 3.0000e-04 eta: 16:32:11 time: 0.2255 data_time: 0.0217 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 21:31:51 - mmengine - INFO - Epoch(train) [3][10500/42151] lr: 3.0000e-04 eta: 16:31:26 time: 0.4410 data_time: 0.2343 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 21:32:36 - mmengine - INFO - Epoch(train) [3][10600/42151] lr: 3.0000e-04 eta: 16:31:01 time: 0.2562 data_time: 0.0135 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 21:33:07 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:33:08 - mmengine - INFO - Epoch(train) [3][10700/42151] lr: 3.0000e-04 eta: 16:30:14 time: 0.3478 data_time: 0.1438 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/16 21:33:42 - mmengine - INFO - Epoch(train) [3][10800/42151] lr: 3.0000e-04 eta: 16:29:31 time: 0.4928 data_time: 0.2329 memory: 7851 loss_ce: 0.0263 loss: 0.0263 2022/09/16 21:34:15 - mmengine - INFO - Epoch(train) [3][10900/42151] lr: 3.0000e-04 eta: 16:28:44 time: 0.2147 data_time: 0.0055 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 21:34:56 - mmengine - INFO - Epoch(train) [3][11000/42151] lr: 3.0000e-04 eta: 16:28:12 time: 0.2213 data_time: 0.0056 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 21:35:28 - mmengine - INFO - Epoch(train) [3][11100/42151] lr: 3.0000e-04 eta: 16:27:25 time: 0.2679 data_time: 0.0672 memory: 7851 loss_ce: 0.0249 loss: 0.0249 2022/09/16 21:36:03 - mmengine - INFO - Epoch(train) [3][11200/42151] lr: 3.0000e-04 eta: 16:26:43 time: 0.2084 data_time: 0.0055 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/16 21:36:36 - mmengine - INFO - Epoch(train) [3][11300/42151] lr: 3.0000e-04 eta: 16:25:58 time: 0.2044 data_time: 0.0048 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 21:37:09 - mmengine - INFO - Epoch(train) [3][11400/42151] lr: 3.0000e-04 eta: 16:25:14 time: 0.2258 data_time: 0.0220 memory: 7851 loss_ce: 0.0216 loss: 0.0216 2022/09/16 21:37:46 - mmengine - INFO - Epoch(train) [3][11500/42151] lr: 3.0000e-04 eta: 16:24:34 time: 0.2957 data_time: 0.0964 memory: 7851 loss_ce: 0.0223 loss: 0.0223 2022/09/16 21:38:19 - mmengine - INFO - Epoch(train) [3][11600/42151] lr: 3.0000e-04 eta: 16:23:50 time: 0.2060 data_time: 0.0047 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 21:38:52 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:38:52 - mmengine - INFO - Epoch(train) [3][11700/42151] lr: 3.0000e-04 eta: 16:23:05 time: 0.2559 data_time: 0.0535 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 21:39:30 - mmengine - INFO - Epoch(train) [3][11800/42151] lr: 3.0000e-04 eta: 16:22:28 time: 0.3271 data_time: 0.1182 memory: 7851 loss_ce: 0.0229 loss: 0.0229 2022/09/16 21:40:03 - mmengine - INFO - Epoch(train) [3][11900/42151] lr: 3.0000e-04 eta: 16:21:41 time: 0.2196 data_time: 0.0146 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 21:40:40 - mmengine - INFO - Epoch(train) [3][12000/42151] lr: 3.0000e-04 eta: 16:21:03 time: 0.4072 data_time: 0.2028 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 21:41:10 - mmengine - INFO - Epoch(train) [3][12100/42151] lr: 3.0000e-04 eta: 16:20:14 time: 0.3413 data_time: 0.1030 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 21:41:59 - mmengine - INFO - Epoch(train) [3][12200/42151] lr: 3.0000e-04 eta: 16:19:55 time: 0.2155 data_time: 0.0050 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 21:42:35 - mmengine - INFO - Epoch(train) [3][12300/42151] lr: 3.0000e-04 eta: 16:19:15 time: 0.4898 data_time: 0.2848 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 21:43:23 - mmengine - INFO - Epoch(train) [3][12400/42151] lr: 3.0000e-04 eta: 16:18:54 time: 0.2085 data_time: 0.0063 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 21:43:59 - mmengine - INFO - Epoch(train) [3][12500/42151] lr: 3.0000e-04 eta: 16:18:13 time: 0.4069 data_time: 0.2035 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 21:44:34 - mmengine - INFO - Epoch(train) [3][12600/42151] lr: 3.0000e-04 eta: 16:17:31 time: 0.2635 data_time: 0.0571 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 21:45:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:45:13 - mmengine - INFO - Epoch(train) [3][12700/42151] lr: 3.0000e-04 eta: 16:16:56 time: 0.2402 data_time: 0.0306 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 21:45:45 - mmengine - INFO - Epoch(train) [3][12800/42151] lr: 3.0000e-04 eta: 16:16:10 time: 0.2068 data_time: 0.0049 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 21:46:22 - mmengine - INFO - Epoch(train) [3][12900/42151] lr: 3.0000e-04 eta: 16:15:31 time: 0.5213 data_time: 0.3169 memory: 7851 loss_ce: 0.0226 loss: 0.0226 2022/09/16 21:46:53 - mmengine - INFO - Epoch(train) [3][13000/42151] lr: 3.0000e-04 eta: 16:14:43 time: 0.2066 data_time: 0.0047 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 21:47:36 - mmengine - INFO - Epoch(train) [3][13100/42151] lr: 3.0000e-04 eta: 16:14:14 time: 0.3152 data_time: 0.1064 memory: 7851 loss_ce: 0.0265 loss: 0.0265 2022/09/16 21:48:12 - mmengine - INFO - Epoch(train) [3][13200/42151] lr: 3.0000e-04 eta: 16:13:33 time: 0.4531 data_time: 0.2452 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 21:48:47 - mmengine - INFO - Epoch(train) [3][13300/42151] lr: 3.0000e-04 eta: 16:12:51 time: 0.5841 data_time: 0.3661 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 21:49:18 - mmengine - INFO - Epoch(train) [3][13400/42151] lr: 3.0000e-04 eta: 16:12:03 time: 0.2135 data_time: 0.0054 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 21:49:53 - mmengine - INFO - Epoch(train) [3][13500/42151] lr: 3.0000e-04 eta: 16:11:21 time: 0.3062 data_time: 0.0251 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 21:50:26 - mmengine - INFO - Epoch(train) [3][13600/42151] lr: 3.0000e-04 eta: 16:10:37 time: 0.2145 data_time: 0.0052 memory: 7851 loss_ce: 0.0252 loss: 0.0252 2022/09/16 21:51:00 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:51:01 - mmengine - INFO - Epoch(train) [3][13700/42151] lr: 3.0000e-04 eta: 16:09:55 time: 0.4553 data_time: 0.2296 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/16 21:51:38 - mmengine - INFO - Epoch(train) [3][13800/42151] lr: 3.0000e-04 eta: 16:09:17 time: 0.8567 data_time: 0.6570 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 21:52:09 - mmengine - INFO - Epoch(train) [3][13900/42151] lr: 3.0000e-04 eta: 16:08:28 time: 0.3047 data_time: 0.0913 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 21:52:50 - mmengine - INFO - Epoch(train) [3][14000/42151] lr: 3.0000e-04 eta: 16:07:57 time: 0.4921 data_time: 0.2666 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 21:53:24 - mmengine - INFO - Epoch(train) [3][14100/42151] lr: 3.0000e-04 eta: 16:07:14 time: 0.4146 data_time: 0.1869 memory: 7851 loss_ce: 0.0233 loss: 0.0233 2022/09/16 21:53:55 - mmengine - INFO - Epoch(train) [3][14200/42151] lr: 3.0000e-04 eta: 16:06:26 time: 0.2161 data_time: 0.0050 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 21:54:30 - mmengine - INFO - Epoch(train) [3][14300/42151] lr: 3.0000e-04 eta: 16:05:43 time: 0.2548 data_time: 0.0503 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 21:55:05 - mmengine - INFO - Epoch(train) [3][14400/42151] lr: 3.0000e-04 eta: 16:05:02 time: 0.5004 data_time: 0.2772 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 21:55:38 - mmengine - INFO - Epoch(train) [3][14500/42151] lr: 3.0000e-04 eta: 16:04:17 time: 0.2104 data_time: 0.0048 memory: 7851 loss_ce: 0.0245 loss: 0.0245 2022/09/16 21:56:14 - mmengine - INFO - Epoch(train) [3][14600/42151] lr: 3.0000e-04 eta: 16:03:37 time: 0.5260 data_time: 0.3180 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 21:56:46 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 21:56:47 - mmengine - INFO - Epoch(train) [3][14700/42151] lr: 3.0000e-04 eta: 16:02:52 time: 0.3525 data_time: 0.1403 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 21:57:22 - mmengine - INFO - Epoch(train) [3][14800/42151] lr: 3.0000e-04 eta: 16:02:11 time: 0.3653 data_time: 0.1291 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 21:57:53 - mmengine - INFO - Epoch(train) [3][14900/42151] lr: 3.0000e-04 eta: 16:01:24 time: 0.2927 data_time: 0.0466 memory: 7851 loss_ce: 0.0204 loss: 0.0204 2022/09/16 21:58:27 - mmengine - INFO - Epoch(train) [3][15000/42151] lr: 3.0000e-04 eta: 16:00:40 time: 0.3129 data_time: 0.1040 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/16 21:59:03 - mmengine - INFO - Epoch(train) [3][15100/42151] lr: 3.0000e-04 eta: 16:00:00 time: 0.2975 data_time: 0.0898 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 21:59:41 - mmengine - INFO - Epoch(train) [3][15200/42151] lr: 3.0000e-04 eta: 15:59:23 time: 0.4633 data_time: 0.2570 memory: 7851 loss_ce: 0.0206 loss: 0.0206 2022/09/16 22:00:13 - mmengine - INFO - Epoch(train) [3][15300/42151] lr: 3.0000e-04 eta: 15:58:38 time: 0.2150 data_time: 0.0051 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 22:00:48 - mmengine - INFO - Epoch(train) [3][15400/42151] lr: 3.0000e-04 eta: 15:57:57 time: 0.4635 data_time: 0.2558 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 22:01:23 - mmengine - INFO - Epoch(train) [3][15500/42151] lr: 3.0000e-04 eta: 15:57:15 time: 0.2262 data_time: 0.0067 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/16 22:01:55 - mmengine - INFO - Epoch(train) [3][15600/42151] lr: 3.0000e-04 eta: 15:56:28 time: 0.2252 data_time: 0.0148 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 22:02:28 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:02:29 - mmengine - INFO - Epoch(train) [3][15700/42151] lr: 3.0000e-04 eta: 15:55:46 time: 0.2996 data_time: 0.1006 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 22:03:03 - mmengine - INFO - Epoch(train) [3][15800/42151] lr: 3.0000e-04 eta: 15:55:04 time: 0.2159 data_time: 0.0051 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 22:03:38 - mmengine - INFO - Epoch(train) [3][15900/42151] lr: 3.0000e-04 eta: 15:54:22 time: 0.4356 data_time: 0.2318 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 22:04:12 - mmengine - INFO - Epoch(train) [3][16000/42151] lr: 3.0000e-04 eta: 15:53:38 time: 0.2429 data_time: 0.0055 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 22:04:47 - mmengine - INFO - Epoch(train) [3][16100/42151] lr: 3.0000e-04 eta: 15:52:57 time: 0.3604 data_time: 0.1307 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 22:05:19 - mmengine - INFO - Epoch(train) [3][16200/42151] lr: 3.0000e-04 eta: 15:52:12 time: 0.2481 data_time: 0.0054 memory: 7851 loss_ce: 0.0229 loss: 0.0229 2022/09/16 22:05:52 - mmengine - INFO - Epoch(train) [3][16300/42151] lr: 3.0000e-04 eta: 15:51:27 time: 0.2901 data_time: 0.0832 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 22:06:38 - mmengine - INFO - Epoch(train) [3][16400/42151] lr: 3.0000e-04 eta: 15:51:02 time: 0.2050 data_time: 0.0048 memory: 7851 loss_ce: 0.0249 loss: 0.0249 2022/09/16 22:07:10 - mmengine - INFO - Epoch(train) [3][16500/42151] lr: 3.0000e-04 eta: 15:50:17 time: 0.2100 data_time: 0.0064 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 22:07:45 - mmengine - INFO - Epoch(train) [3][16600/42151] lr: 3.0000e-04 eta: 15:49:36 time: 0.4375 data_time: 0.2314 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 22:08:19 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:08:20 - mmengine - INFO - Epoch(train) [3][16700/42151] lr: 3.0000e-04 eta: 15:48:54 time: 0.2894 data_time: 0.0375 memory: 7851 loss_ce: 0.0251 loss: 0.0251 2022/09/16 22:08:53 - mmengine - INFO - Epoch(train) [3][16800/42151] lr: 3.0000e-04 eta: 15:48:10 time: 0.3068 data_time: 0.0473 memory: 7851 loss_ce: 0.0216 loss: 0.0216 2022/09/16 22:09:27 - mmengine - INFO - Epoch(train) [3][16900/42151] lr: 3.0000e-04 eta: 15:47:27 time: 0.2094 data_time: 0.0051 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 22:10:00 - mmengine - INFO - Epoch(train) [3][17000/42151] lr: 3.0000e-04 eta: 15:46:43 time: 0.2032 data_time: 0.0046 memory: 7851 loss_ce: 0.0260 loss: 0.0260 2022/09/16 22:10:37 - mmengine - INFO - Epoch(train) [3][17100/42151] lr: 3.0000e-04 eta: 15:46:04 time: 0.2199 data_time: 0.0051 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 22:11:14 - mmengine - INFO - Epoch(train) [3][17200/42151] lr: 3.0000e-04 eta: 15:45:26 time: 0.2164 data_time: 0.0056 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 22:11:58 - mmengine - INFO - Epoch(train) [3][17300/42151] lr: 3.0000e-04 eta: 15:44:59 time: 0.5042 data_time: 0.2948 memory: 7851 loss_ce: 0.0247 loss: 0.0247 2022/09/16 22:12:33 - mmengine - INFO - Epoch(train) [3][17400/42151] lr: 3.0000e-04 eta: 15:44:17 time: 0.2092 data_time: 0.0049 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 22:13:09 - mmengine - INFO - Epoch(train) [3][17500/42151] lr: 3.0000e-04 eta: 15:43:38 time: 0.2099 data_time: 0.0077 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/16 22:13:47 - mmengine - INFO - Epoch(train) [3][17600/42151] lr: 3.0000e-04 eta: 15:43:01 time: 0.5005 data_time: 0.2918 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 22:14:18 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:14:20 - mmengine - INFO - Epoch(train) [3][17700/42151] lr: 3.0000e-04 eta: 15:42:17 time: 0.4244 data_time: 0.2124 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 22:14:53 - mmengine - INFO - Epoch(train) [3][17800/42151] lr: 3.0000e-04 eta: 15:41:32 time: 0.2161 data_time: 0.0054 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 22:15:26 - mmengine - INFO - Epoch(train) [3][17900/42151] lr: 3.0000e-04 eta: 15:40:48 time: 0.3289 data_time: 0.1170 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 22:16:01 - mmengine - INFO - Epoch(train) [3][18000/42151] lr: 3.0000e-04 eta: 15:40:08 time: 0.4573 data_time: 0.2380 memory: 7851 loss_ce: 0.0254 loss: 0.0254 2022/09/16 22:16:34 - mmengine - INFO - Epoch(train) [3][18100/42151] lr: 3.0000e-04 eta: 15:39:23 time: 0.2314 data_time: 0.0119 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 22:17:12 - mmengine - INFO - Epoch(train) [3][18200/42151] lr: 3.0000e-04 eta: 15:38:47 time: 0.2449 data_time: 0.0059 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/16 22:17:44 - mmengine - INFO - Epoch(train) [3][18300/42151] lr: 3.0000e-04 eta: 15:38:02 time: 0.2235 data_time: 0.0055 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 22:18:18 - mmengine - INFO - Epoch(train) [3][18400/42151] lr: 3.0000e-04 eta: 15:37:19 time: 0.3087 data_time: 0.0849 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 22:18:58 - mmengine - INFO - Epoch(train) [3][18500/42151] lr: 3.0000e-04 eta: 15:36:45 time: 0.2077 data_time: 0.0048 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/16 22:19:32 - mmengine - INFO - Epoch(train) [3][18600/42151] lr: 3.0000e-04 eta: 15:36:02 time: 0.2387 data_time: 0.0240 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 22:20:06 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:20:07 - mmengine - INFO - Epoch(train) [3][18700/42151] lr: 3.0000e-04 eta: 15:35:21 time: 0.2183 data_time: 0.0205 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/16 22:20:44 - mmengine - INFO - Epoch(train) [3][18800/42151] lr: 3.0000e-04 eta: 15:34:43 time: 0.2054 data_time: 0.0049 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 22:21:24 - mmengine - INFO - Epoch(train) [3][18900/42151] lr: 3.0000e-04 eta: 15:34:10 time: 0.2108 data_time: 0.0064 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 22:22:03 - mmengine - INFO - Epoch(train) [3][19000/42151] lr: 3.0000e-04 eta: 15:33:34 time: 0.2856 data_time: 0.0758 memory: 7851 loss_ce: 0.0223 loss: 0.0223 2022/09/16 22:22:43 - mmengine - INFO - Epoch(train) [3][19100/42151] lr: 3.0000e-04 eta: 15:33:01 time: 1.0538 data_time: 0.8475 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 22:23:19 - mmengine - INFO - Epoch(train) [3][19200/42151] lr: 3.0000e-04 eta: 15:32:21 time: 0.2112 data_time: 0.0066 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/16 22:23:56 - mmengine - INFO - Epoch(train) [3][19300/42151] lr: 3.0000e-04 eta: 15:31:43 time: 0.3304 data_time: 0.1332 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 22:24:28 - mmengine - INFO - Epoch(train) [3][19400/42151] lr: 3.0000e-04 eta: 15:30:58 time: 0.3511 data_time: 0.1534 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 22:25:01 - mmengine - INFO - Epoch(train) [3][19500/42151] lr: 3.0000e-04 eta: 15:30:13 time: 0.3089 data_time: 0.0725 memory: 7851 loss_ce: 0.0266 loss: 0.0266 2022/09/16 22:25:37 - mmengine - INFO - Epoch(train) [3][19600/42151] lr: 3.0000e-04 eta: 15:29:34 time: 0.2187 data_time: 0.0139 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 22:26:14 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:26:15 - mmengine - INFO - Epoch(train) [3][19700/42151] lr: 3.0000e-04 eta: 15:28:57 time: 0.3450 data_time: 0.1419 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 22:26:48 - mmengine - INFO - Epoch(train) [3][19800/42151] lr: 3.0000e-04 eta: 15:28:13 time: 0.4428 data_time: 0.2393 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 22:27:20 - mmengine - INFO - Epoch(train) [3][19900/42151] lr: 3.0000e-04 eta: 15:27:29 time: 0.4165 data_time: 0.2070 memory: 7851 loss_ce: 0.0244 loss: 0.0244 2022/09/16 22:27:55 - mmengine - INFO - Epoch(train) [3][20000/42151] lr: 3.0000e-04 eta: 15:26:47 time: 0.4972 data_time: 0.2695 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 22:28:27 - mmengine - INFO - Epoch(train) [3][20100/42151] lr: 3.0000e-04 eta: 15:26:02 time: 0.2414 data_time: 0.0401 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/16 22:29:00 - mmengine - INFO - Epoch(train) [3][20200/42151] lr: 3.0000e-04 eta: 15:25:18 time: 0.3286 data_time: 0.1231 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 22:29:33 - mmengine - INFO - Epoch(train) [3][20300/42151] lr: 3.0000e-04 eta: 15:24:35 time: 0.3212 data_time: 0.1210 memory: 7851 loss_ce: 0.0241 loss: 0.0241 2022/09/16 22:30:09 - mmengine - INFO - Epoch(train) [3][20400/42151] lr: 3.0000e-04 eta: 15:23:55 time: 0.3271 data_time: 0.0867 memory: 7851 loss_ce: 0.0253 loss: 0.0253 2022/09/16 22:30:45 - mmengine - INFO - Epoch(train) [3][20500/42151] lr: 3.0000e-04 eta: 15:23:15 time: 0.3535 data_time: 0.1521 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 22:31:19 - mmengine - INFO - Epoch(train) [3][20600/42151] lr: 3.0000e-04 eta: 15:22:33 time: 0.3156 data_time: 0.0716 memory: 7851 loss_ce: 0.0248 loss: 0.0248 2022/09/16 22:31:54 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:31:54 - mmengine - INFO - Epoch(train) [3][20700/42151] lr: 3.0000e-04 eta: 15:21:53 time: 0.4230 data_time: 0.2090 memory: 7851 loss_ce: 0.0229 loss: 0.0229 2022/09/16 22:32:27 - mmengine - INFO - Epoch(train) [3][20800/42151] lr: 3.0000e-04 eta: 15:21:10 time: 0.3745 data_time: 0.1544 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 22:33:02 - mmengine - INFO - Epoch(train) [3][20900/42151] lr: 3.0000e-04 eta: 15:20:29 time: 0.3538 data_time: 0.1538 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 22:33:38 - mmengine - INFO - Epoch(train) [3][21000/42151] lr: 3.0000e-04 eta: 15:19:49 time: 0.4064 data_time: 0.1525 memory: 7851 loss_ce: 0.0193 loss: 0.0193 2022/09/16 22:34:13 - mmengine - INFO - Epoch(train) [3][21100/42151] lr: 3.0000e-04 eta: 15:19:09 time: 0.3281 data_time: 0.0964 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 22:34:48 - mmengine - INFO - Epoch(train) [3][21200/42151] lr: 3.0000e-04 eta: 15:18:27 time: 0.2226 data_time: 0.0152 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 22:35:21 - mmengine - INFO - Epoch(train) [3][21300/42151] lr: 3.0000e-04 eta: 15:17:44 time: 0.3268 data_time: 0.1253 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/16 22:35:58 - mmengine - INFO - Epoch(train) [3][21400/42151] lr: 3.0000e-04 eta: 15:17:06 time: 0.3991 data_time: 0.1748 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/16 22:36:33 - mmengine - INFO - Epoch(train) [3][21500/42151] lr: 3.0000e-04 eta: 15:16:25 time: 0.3805 data_time: 0.1672 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 22:37:07 - mmengine - INFO - Epoch(train) [3][21600/42151] lr: 3.0000e-04 eta: 15:15:43 time: 0.3515 data_time: 0.1548 memory: 7851 loss_ce: 0.0216 loss: 0.0216 2022/09/16 22:37:42 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:37:43 - mmengine - INFO - Epoch(train) [3][21700/42151] lr: 3.0000e-04 eta: 15:15:04 time: 0.4130 data_time: 0.1559 memory: 7851 loss_ce: 0.0206 loss: 0.0206 2022/09/16 22:38:17 - mmengine - INFO - Epoch(train) [3][21800/42151] lr: 3.0000e-04 eta: 15:14:22 time: 0.4105 data_time: 0.1691 memory: 7851 loss_ce: 0.0260 loss: 0.0260 2022/09/16 22:38:52 - mmengine - INFO - Epoch(train) [3][21900/42151] lr: 3.0000e-04 eta: 15:13:40 time: 0.2722 data_time: 0.0759 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 22:39:26 - mmengine - INFO - Epoch(train) [3][22000/42151] lr: 3.0000e-04 eta: 15:12:59 time: 0.2270 data_time: 0.0052 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 22:40:01 - mmengine - INFO - Epoch(train) [3][22100/42151] lr: 3.0000e-04 eta: 15:12:18 time: 0.3345 data_time: 0.1347 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 22:40:34 - mmengine - INFO - Epoch(train) [3][22200/42151] lr: 3.0000e-04 eta: 15:11:34 time: 0.2298 data_time: 0.0310 memory: 7851 loss_ce: 0.0233 loss: 0.0233 2022/09/16 22:41:09 - mmengine - INFO - Epoch(train) [3][22300/42151] lr: 3.0000e-04 eta: 15:10:54 time: 0.3602 data_time: 0.1549 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 22:41:44 - mmengine - INFO - Epoch(train) [3][22400/42151] lr: 3.0000e-04 eta: 15:10:14 time: 0.2402 data_time: 0.0404 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 22:42:20 - mmengine - INFO - Epoch(train) [3][22500/42151] lr: 3.0000e-04 eta: 15:09:34 time: 0.4162 data_time: 0.2050 memory: 7851 loss_ce: 0.0201 loss: 0.0201 2022/09/16 22:42:54 - mmengine - INFO - Epoch(train) [3][22600/42151] lr: 3.0000e-04 eta: 15:08:52 time: 0.3880 data_time: 0.1860 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 22:43:26 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:43:27 - mmengine - INFO - Epoch(train) [3][22700/42151] lr: 3.0000e-04 eta: 15:08:08 time: 0.3335 data_time: 0.0763 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 22:44:00 - mmengine - INFO - Epoch(train) [3][22800/42151] lr: 3.0000e-04 eta: 15:07:26 time: 0.3169 data_time: 0.1199 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 22:44:34 - mmengine - INFO - Epoch(train) [3][22900/42151] lr: 3.0000e-04 eta: 15:06:44 time: 0.3539 data_time: 0.1089 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 22:45:10 - mmengine - INFO - Epoch(train) [3][23000/42151] lr: 3.0000e-04 eta: 15:06:04 time: 0.3842 data_time: 0.1503 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/16 22:45:44 - mmengine - INFO - Epoch(train) [3][23100/42151] lr: 3.0000e-04 eta: 15:05:22 time: 0.3143 data_time: 0.1153 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 22:46:19 - mmengine - INFO - Epoch(train) [3][23200/42151] lr: 3.0000e-04 eta: 15:04:42 time: 0.3826 data_time: 0.1533 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 22:46:54 - mmengine - INFO - Epoch(train) [3][23300/42151] lr: 3.0000e-04 eta: 15:04:01 time: 0.3199 data_time: 0.1188 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 22:47:29 - mmengine - INFO - Epoch(train) [3][23400/42151] lr: 3.0000e-04 eta: 15:03:21 time: 0.3780 data_time: 0.1702 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 22:48:05 - mmengine - INFO - Epoch(train) [3][23500/42151] lr: 3.0000e-04 eta: 15:02:41 time: 0.3638 data_time: 0.1583 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/16 22:48:40 - mmengine - INFO - Epoch(train) [3][23600/42151] lr: 3.0000e-04 eta: 15:02:01 time: 0.4060 data_time: 0.1975 memory: 7851 loss_ce: 0.0217 loss: 0.0217 2022/09/16 22:49:15 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:49:15 - mmengine - INFO - Epoch(train) [3][23700/42151] lr: 3.0000e-04 eta: 15:01:21 time: 0.4038 data_time: 0.1835 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 22:49:51 - mmengine - INFO - Epoch(train) [3][23800/42151] lr: 3.0000e-04 eta: 15:00:41 time: 0.3660 data_time: 0.1656 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 22:50:27 - mmengine - INFO - Epoch(train) [3][23900/42151] lr: 3.0000e-04 eta: 15:00:02 time: 0.3121 data_time: 0.1107 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 22:51:03 - mmengine - INFO - Epoch(train) [3][24000/42151] lr: 3.0000e-04 eta: 14:59:23 time: 0.4280 data_time: 0.2086 memory: 7851 loss_ce: 0.0198 loss: 0.0198 2022/09/16 22:51:37 - mmengine - INFO - Epoch(train) [3][24100/42151] lr: 3.0000e-04 eta: 14:58:41 time: 0.3594 data_time: 0.1504 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 22:52:11 - mmengine - INFO - Epoch(train) [3][24200/42151] lr: 3.0000e-04 eta: 14:58:00 time: 0.3605 data_time: 0.1565 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/16 22:52:46 - mmengine - INFO - Epoch(train) [3][24300/42151] lr: 3.0000e-04 eta: 14:57:19 time: 0.3619 data_time: 0.1323 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 22:53:21 - mmengine - INFO - Epoch(train) [3][24400/42151] lr: 3.0000e-04 eta: 14:56:39 time: 0.3983 data_time: 0.1663 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 22:53:57 - mmengine - INFO - Epoch(train) [3][24500/42151] lr: 3.0000e-04 eta: 14:56:00 time: 0.3762 data_time: 0.1547 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 22:54:31 - mmengine - INFO - Epoch(train) [3][24600/42151] lr: 3.0000e-04 eta: 14:55:18 time: 0.3293 data_time: 0.1247 memory: 7851 loss_ce: 0.0204 loss: 0.0204 2022/09/16 22:55:05 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 22:55:06 - mmengine - INFO - Epoch(train) [3][24700/42151] lr: 3.0000e-04 eta: 14:54:38 time: 0.3957 data_time: 0.1851 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 22:55:42 - mmengine - INFO - Epoch(train) [3][24800/42151] lr: 3.0000e-04 eta: 14:53:58 time: 0.3528 data_time: 0.1421 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 22:56:17 - mmengine - INFO - Epoch(train) [3][24900/42151] lr: 3.0000e-04 eta: 14:53:18 time: 0.3250 data_time: 0.1191 memory: 7851 loss_ce: 0.0242 loss: 0.0242 2022/09/16 22:56:52 - mmengine - INFO - Epoch(train) [3][25000/42151] lr: 3.0000e-04 eta: 14:52:38 time: 0.3602 data_time: 0.1565 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 22:57:27 - mmengine - INFO - Epoch(train) [3][25100/42151] lr: 3.0000e-04 eta: 14:51:58 time: 0.3508 data_time: 0.1417 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/16 22:58:02 - mmengine - INFO - Epoch(train) [3][25200/42151] lr: 3.0000e-04 eta: 14:51:17 time: 0.3619 data_time: 0.1140 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/16 22:58:37 - mmengine - INFO - Epoch(train) [3][25300/42151] lr: 3.0000e-04 eta: 14:50:37 time: 0.4202 data_time: 0.1944 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 22:59:11 - mmengine - INFO - Epoch(train) [3][25400/42151] lr: 3.0000e-04 eta: 14:49:56 time: 0.3502 data_time: 0.1327 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 22:59:47 - mmengine - INFO - Epoch(train) [3][25500/42151] lr: 3.0000e-04 eta: 14:49:16 time: 0.3723 data_time: 0.1638 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/16 23:00:22 - mmengine - INFO - Epoch(train) [3][25600/42151] lr: 3.0000e-04 eta: 14:48:36 time: 0.3870 data_time: 0.1746 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/16 23:00:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:00:58 - mmengine - INFO - Epoch(train) [3][25700/42151] lr: 3.0000e-04 eta: 14:47:57 time: 0.4120 data_time: 0.2035 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 23:01:33 - mmengine - INFO - Epoch(train) [3][25800/42151] lr: 3.0000e-04 eta: 14:47:17 time: 0.3251 data_time: 0.1145 memory: 7851 loss_ce: 0.0212 loss: 0.0212 2022/09/16 23:02:10 - mmengine - INFO - Epoch(train) [3][25900/42151] lr: 3.0000e-04 eta: 14:46:38 time: 0.4208 data_time: 0.1782 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 23:02:44 - mmengine - INFO - Epoch(train) [3][26000/42151] lr: 3.0000e-04 eta: 14:45:58 time: 0.3313 data_time: 0.1240 memory: 7851 loss_ce: 0.0206 loss: 0.0206 2022/09/16 23:03:19 - mmengine - INFO - Epoch(train) [3][26100/42151] lr: 3.0000e-04 eta: 14:45:17 time: 0.3719 data_time: 0.1635 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 23:03:54 - mmengine - INFO - Epoch(train) [3][26200/42151] lr: 3.0000e-04 eta: 14:44:37 time: 0.3597 data_time: 0.1169 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/16 23:04:29 - mmengine - INFO - Epoch(train) [3][26300/42151] lr: 3.0000e-04 eta: 14:43:57 time: 0.3447 data_time: 0.1439 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 23:05:04 - mmengine - INFO - Epoch(train) [3][26400/42151] lr: 3.0000e-04 eta: 14:43:16 time: 0.3062 data_time: 0.1038 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 23:05:39 - mmengine - INFO - Epoch(train) [3][26500/42151] lr: 3.0000e-04 eta: 14:42:36 time: 0.3518 data_time: 0.1419 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 23:06:14 - mmengine - INFO - Epoch(train) [3][26600/42151] lr: 3.0000e-04 eta: 14:41:56 time: 0.3229 data_time: 0.1231 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/16 23:06:49 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:06:50 - mmengine - INFO - Epoch(train) [3][26700/42151] lr: 3.0000e-04 eta: 14:41:17 time: 0.3924 data_time: 0.1504 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 23:07:26 - mmengine - INFO - Epoch(train) [3][26800/42151] lr: 3.0000e-04 eta: 14:40:39 time: 0.5068 data_time: 0.2818 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/16 23:08:00 - mmengine - INFO - Epoch(train) [3][26900/42151] lr: 3.0000e-04 eta: 14:39:57 time: 0.3252 data_time: 0.0761 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/16 23:08:35 - mmengine - INFO - Epoch(train) [3][27000/42151] lr: 3.0000e-04 eta: 14:39:17 time: 0.3259 data_time: 0.1219 memory: 7851 loss_ce: 0.0246 loss: 0.0246 2022/09/16 23:09:11 - mmengine - INFO - Epoch(train) [3][27100/42151] lr: 3.0000e-04 eta: 14:38:38 time: 0.3689 data_time: 0.1614 memory: 7851 loss_ce: 0.0212 loss: 0.0212 2022/09/16 23:09:46 - mmengine - INFO - Epoch(train) [3][27200/42151] lr: 3.0000e-04 eta: 14:37:57 time: 0.3370 data_time: 0.1327 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/16 23:10:20 - mmengine - INFO - Epoch(train) [3][27300/42151] lr: 3.0000e-04 eta: 14:37:16 time: 0.3817 data_time: 0.1106 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 23:10:55 - mmengine - INFO - Epoch(train) [3][27400/42151] lr: 3.0000e-04 eta: 14:36:36 time: 0.4031 data_time: 0.1996 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 23:11:29 - mmengine - INFO - Epoch(train) [3][27500/42151] lr: 3.0000e-04 eta: 14:35:55 time: 0.3171 data_time: 0.1195 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 23:12:04 - mmengine - INFO - Epoch(train) [3][27600/42151] lr: 3.0000e-04 eta: 14:35:14 time: 0.3306 data_time: 0.1117 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 23:12:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:12:40 - mmengine - INFO - Epoch(train) [3][27700/42151] lr: 3.0000e-04 eta: 14:34:35 time: 0.3600 data_time: 0.1400 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/16 23:13:14 - mmengine - INFO - Epoch(train) [3][27800/42151] lr: 3.0000e-04 eta: 14:33:55 time: 0.3330 data_time: 0.1291 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 23:13:49 - mmengine - INFO - Epoch(train) [3][27900/42151] lr: 3.0000e-04 eta: 14:33:14 time: 0.3866 data_time: 0.1324 memory: 7851 loss_ce: 0.0199 loss: 0.0199 2022/09/16 23:14:25 - mmengine - INFO - Epoch(train) [3][28000/42151] lr: 3.0000e-04 eta: 14:32:35 time: 0.3974 data_time: 0.1573 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/16 23:14:59 - mmengine - INFO - Epoch(train) [3][28100/42151] lr: 3.0000e-04 eta: 14:31:54 time: 0.3310 data_time: 0.1119 memory: 7851 loss_ce: 0.0192 loss: 0.0192 2022/09/16 23:15:34 - mmengine - INFO - Epoch(train) [3][28200/42151] lr: 3.0000e-04 eta: 14:31:14 time: 0.3714 data_time: 0.1668 memory: 7851 loss_ce: 0.0256 loss: 0.0256 2022/09/16 23:16:08 - mmengine - INFO - Epoch(train) [3][28300/42151] lr: 3.0000e-04 eta: 14:30:33 time: 0.2909 data_time: 0.0881 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 23:16:42 - mmengine - INFO - Epoch(train) [3][28400/42151] lr: 3.0000e-04 eta: 14:29:52 time: 0.3534 data_time: 0.1546 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/16 23:17:17 - mmengine - INFO - Epoch(train) [3][28500/42151] lr: 3.0000e-04 eta: 14:29:11 time: 0.3303 data_time: 0.1278 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 23:17:52 - mmengine - INFO - Epoch(train) [3][28600/42151] lr: 3.0000e-04 eta: 14:28:31 time: 0.4283 data_time: 0.1874 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 23:18:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:18:27 - mmengine - INFO - Epoch(train) [3][28700/42151] lr: 3.0000e-04 eta: 14:27:51 time: 0.4123 data_time: 0.2066 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/16 23:19:03 - mmengine - INFO - Epoch(train) [3][28800/42151] lr: 3.0000e-04 eta: 14:27:12 time: 0.3678 data_time: 0.1015 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 23:19:38 - mmengine - INFO - Epoch(train) [3][28900/42151] lr: 3.0000e-04 eta: 14:26:32 time: 0.3117 data_time: 0.0814 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/16 23:20:13 - mmengine - INFO - Epoch(train) [3][29000/42151] lr: 3.0000e-04 eta: 14:25:52 time: 0.3157 data_time: 0.1168 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 23:20:48 - mmengine - INFO - Epoch(train) [3][29100/42151] lr: 3.0000e-04 eta: 14:25:12 time: 0.3312 data_time: 0.1073 memory: 7851 loss_ce: 0.0216 loss: 0.0216 2022/09/16 23:21:24 - mmengine - INFO - Epoch(train) [3][29200/42151] lr: 3.0000e-04 eta: 14:24:33 time: 0.3882 data_time: 0.1808 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 23:21:59 - mmengine - INFO - Epoch(train) [3][29300/42151] lr: 3.0000e-04 eta: 14:23:53 time: 0.3622 data_time: 0.1608 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/16 23:22:34 - mmengine - INFO - Epoch(train) [3][29400/42151] lr: 3.0000e-04 eta: 14:23:13 time: 0.3562 data_time: 0.1554 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 23:23:09 - mmengine - INFO - Epoch(train) [3][29500/42151] lr: 3.0000e-04 eta: 14:22:33 time: 0.2898 data_time: 0.0648 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 23:23:45 - mmengine - INFO - Epoch(train) [3][29600/42151] lr: 3.0000e-04 eta: 14:21:55 time: 0.4844 data_time: 0.2692 memory: 7851 loss_ce: 0.0243 loss: 0.0243 2022/09/16 23:24:18 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:24:19 - mmengine - INFO - Epoch(train) [3][29700/42151] lr: 3.0000e-04 eta: 14:21:13 time: 0.3309 data_time: 0.1319 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/16 23:24:54 - mmengine - INFO - Epoch(train) [3][29800/42151] lr: 3.0000e-04 eta: 14:20:33 time: 0.3630 data_time: 0.1586 memory: 7851 loss_ce: 0.0202 loss: 0.0202 2022/09/16 23:25:27 - mmengine - INFO - Epoch(train) [3][29900/42151] lr: 3.0000e-04 eta: 14:19:52 time: 0.2506 data_time: 0.0500 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/16 23:26:03 - mmengine - INFO - Epoch(train) [3][30000/42151] lr: 3.0000e-04 eta: 14:19:13 time: 0.3832 data_time: 0.1806 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/16 23:26:38 - mmengine - INFO - Epoch(train) [3][30100/42151] lr: 3.0000e-04 eta: 14:18:33 time: 0.3148 data_time: 0.1106 memory: 7851 loss_ce: 0.0217 loss: 0.0217 2022/09/16 23:27:14 - mmengine - INFO - Epoch(train) [3][30200/42151] lr: 3.0000e-04 eta: 14:17:54 time: 0.3023 data_time: 0.0760 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 23:27:49 - mmengine - INFO - Epoch(train) [3][30300/42151] lr: 3.0000e-04 eta: 14:17:14 time: 0.3354 data_time: 0.1285 memory: 7851 loss_ce: 0.0206 loss: 0.0206 2022/09/16 23:28:25 - mmengine - INFO - Epoch(train) [3][30400/42151] lr: 3.0000e-04 eta: 14:16:35 time: 0.3601 data_time: 0.1552 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 23:29:00 - mmengine - INFO - Epoch(train) [3][30500/42151] lr: 3.0000e-04 eta: 14:15:55 time: 0.3064 data_time: 0.0732 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 23:29:34 - mmengine - INFO - Epoch(train) [3][30600/42151] lr: 3.0000e-04 eta: 14:15:15 time: 0.3267 data_time: 0.1001 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/16 23:30:08 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:30:09 - mmengine - INFO - Epoch(train) [3][30700/42151] lr: 3.0000e-04 eta: 14:14:35 time: 0.3195 data_time: 0.1129 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 23:30:44 - mmengine - INFO - Epoch(train) [3][30800/42151] lr: 3.0000e-04 eta: 14:13:55 time: 0.2101 data_time: 0.0073 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 23:31:18 - mmengine - INFO - Epoch(train) [3][30900/42151] lr: 3.0000e-04 eta: 14:13:15 time: 0.3359 data_time: 0.1115 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/16 23:31:53 - mmengine - INFO - Epoch(train) [3][31000/42151] lr: 3.0000e-04 eta: 14:12:34 time: 0.4153 data_time: 0.2062 memory: 7851 loss_ce: 0.0229 loss: 0.0229 2022/09/16 23:32:27 - mmengine - INFO - Epoch(train) [3][31100/42151] lr: 3.0000e-04 eta: 14:11:53 time: 0.3645 data_time: 0.1643 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 23:33:02 - mmengine - INFO - Epoch(train) [3][31200/42151] lr: 3.0000e-04 eta: 14:11:13 time: 0.3514 data_time: 0.1392 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/16 23:33:36 - mmengine - INFO - Epoch(train) [3][31300/42151] lr: 3.0000e-04 eta: 14:10:32 time: 0.2959 data_time: 0.0702 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/16 23:34:11 - mmengine - INFO - Epoch(train) [3][31400/42151] lr: 3.0000e-04 eta: 14:09:52 time: 0.3631 data_time: 0.1402 memory: 7851 loss_ce: 0.0223 loss: 0.0223 2022/09/16 23:34:44 - mmengine - INFO - Epoch(train) [3][31500/42151] lr: 3.0000e-04 eta: 14:09:11 time: 0.2412 data_time: 0.0063 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 23:35:18 - mmengine - INFO - Epoch(train) [3][31600/42151] lr: 3.0000e-04 eta: 14:08:30 time: 0.4290 data_time: 0.2188 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/16 23:35:52 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:35:53 - mmengine - INFO - Epoch(train) [3][31700/42151] lr: 3.0000e-04 eta: 14:07:49 time: 0.3339 data_time: 0.1148 memory: 7851 loss_ce: 0.0197 loss: 0.0197 2022/09/16 23:36:27 - mmengine - INFO - Epoch(train) [3][31800/42151] lr: 3.0000e-04 eta: 14:07:09 time: 0.3517 data_time: 0.1528 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/16 23:37:01 - mmengine - INFO - Epoch(train) [3][31900/42151] lr: 3.0000e-04 eta: 14:06:28 time: 0.2053 data_time: 0.0049 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 23:37:36 - mmengine - INFO - Epoch(train) [3][32000/42151] lr: 3.0000e-04 eta: 14:05:49 time: 0.2753 data_time: 0.0563 memory: 7851 loss_ce: 0.0206 loss: 0.0206 2022/09/16 23:38:12 - mmengine - INFO - Epoch(train) [3][32100/42151] lr: 3.0000e-04 eta: 14:05:10 time: 0.5107 data_time: 0.3046 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 23:38:45 - mmengine - INFO - Epoch(train) [3][32200/42151] lr: 3.0000e-04 eta: 14:04:27 time: 0.3574 data_time: 0.1252 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/16 23:39:19 - mmengine - INFO - Epoch(train) [3][32300/42151] lr: 3.0000e-04 eta: 14:03:47 time: 0.3126 data_time: 0.1133 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 23:39:54 - mmengine - INFO - Epoch(train) [3][32400/42151] lr: 3.0000e-04 eta: 14:03:07 time: 0.3705 data_time: 0.1686 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/16 23:40:29 - mmengine - INFO - Epoch(train) [3][32500/42151] lr: 3.0000e-04 eta: 14:02:28 time: 0.3458 data_time: 0.1463 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 23:41:04 - mmengine - INFO - Epoch(train) [3][32600/42151] lr: 3.0000e-04 eta: 14:01:47 time: 0.2236 data_time: 0.0064 memory: 7851 loss_ce: 0.0237 loss: 0.0237 2022/09/16 23:41:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:41:40 - mmengine - INFO - Epoch(train) [3][32700/42151] lr: 3.0000e-04 eta: 14:01:09 time: 0.3194 data_time: 0.1169 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 23:42:16 - mmengine - INFO - Epoch(train) [3][32800/42151] lr: 3.0000e-04 eta: 14:00:30 time: 0.4976 data_time: 0.2692 memory: 7851 loss_ce: 0.0226 loss: 0.0226 2022/09/16 23:42:49 - mmengine - INFO - Epoch(train) [3][32900/42151] lr: 3.0000e-04 eta: 13:59:49 time: 0.3327 data_time: 0.1262 memory: 7851 loss_ce: 0.0217 loss: 0.0217 2022/09/16 23:43:24 - mmengine - INFO - Epoch(train) [3][33000/42151] lr: 3.0000e-04 eta: 13:59:09 time: 0.3749 data_time: 0.1704 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 23:43:58 - mmengine - INFO - Epoch(train) [3][33100/42151] lr: 3.0000e-04 eta: 13:58:28 time: 0.3195 data_time: 0.1114 memory: 7851 loss_ce: 0.0202 loss: 0.0202 2022/09/16 23:44:34 - mmengine - INFO - Epoch(train) [3][33200/42151] lr: 3.0000e-04 eta: 13:57:49 time: 0.4435 data_time: 0.2345 memory: 7851 loss_ce: 0.0230 loss: 0.0230 2022/09/16 23:45:07 - mmengine - INFO - Epoch(train) [3][33300/42151] lr: 3.0000e-04 eta: 13:57:08 time: 0.3014 data_time: 0.0930 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 23:45:43 - mmengine - INFO - Epoch(train) [3][33400/42151] lr: 3.0000e-04 eta: 13:56:29 time: 0.3997 data_time: 0.1546 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/16 23:46:18 - mmengine - INFO - Epoch(train) [3][33500/42151] lr: 3.0000e-04 eta: 13:55:50 time: 0.4464 data_time: 0.2409 memory: 7851 loss_ce: 0.0229 loss: 0.0229 2022/09/16 23:46:53 - mmengine - INFO - Epoch(train) [3][33600/42151] lr: 3.0000e-04 eta: 13:55:10 time: 0.4485 data_time: 0.2342 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 23:47:26 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:47:27 - mmengine - INFO - Epoch(train) [3][33700/42151] lr: 3.0000e-04 eta: 13:54:30 time: 0.3471 data_time: 0.1393 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 23:48:03 - mmengine - INFO - Epoch(train) [3][33800/42151] lr: 3.0000e-04 eta: 13:53:51 time: 0.3882 data_time: 0.1823 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 23:48:38 - mmengine - INFO - Epoch(train) [3][33900/42151] lr: 3.0000e-04 eta: 13:53:12 time: 0.3716 data_time: 0.1646 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/16 23:49:13 - mmengine - INFO - Epoch(train) [3][34000/42151] lr: 3.0000e-04 eta: 13:52:32 time: 0.3355 data_time: 0.1204 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 23:49:49 - mmengine - INFO - Epoch(train) [3][34100/42151] lr: 3.0000e-04 eta: 13:51:53 time: 0.3165 data_time: 0.1115 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/16 23:50:25 - mmengine - INFO - Epoch(train) [3][34200/42151] lr: 3.0000e-04 eta: 13:51:15 time: 0.4382 data_time: 0.2267 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/16 23:51:00 - mmengine - INFO - Epoch(train) [3][34300/42151] lr: 3.0000e-04 eta: 13:50:35 time: 0.2033 data_time: 0.0048 memory: 7851 loss_ce: 0.0239 loss: 0.0239 2022/09/16 23:51:35 - mmengine - INFO - Epoch(train) [3][34400/42151] lr: 3.0000e-04 eta: 13:49:56 time: 0.3272 data_time: 0.0651 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 23:52:10 - mmengine - INFO - Epoch(train) [3][34500/42151] lr: 3.0000e-04 eta: 13:49:16 time: 0.3942 data_time: 0.1781 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/16 23:52:45 - mmengine - INFO - Epoch(train) [3][34600/42151] lr: 3.0000e-04 eta: 13:48:37 time: 0.4206 data_time: 0.1870 memory: 7851 loss_ce: 0.0225 loss: 0.0225 2022/09/16 23:53:18 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:53:20 - mmengine - INFO - Epoch(train) [3][34700/42151] lr: 3.0000e-04 eta: 13:47:57 time: 0.3918 data_time: 0.1832 memory: 7851 loss_ce: 0.0226 loss: 0.0226 2022/09/16 23:53:54 - mmengine - INFO - Epoch(train) [3][34800/42151] lr: 3.0000e-04 eta: 13:47:17 time: 0.3234 data_time: 0.0439 memory: 7851 loss_ce: 0.0223 loss: 0.0223 2022/09/16 23:54:29 - mmengine - INFO - Epoch(train) [3][34900/42151] lr: 3.0000e-04 eta: 13:46:37 time: 0.3740 data_time: 0.1051 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/16 23:55:03 - mmengine - INFO - Epoch(train) [3][35000/42151] lr: 3.0000e-04 eta: 13:45:57 time: 0.4151 data_time: 0.1676 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 23:55:37 - mmengine - INFO - Epoch(train) [3][35100/42151] lr: 3.0000e-04 eta: 13:45:16 time: 0.2796 data_time: 0.0522 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/16 23:56:12 - mmengine - INFO - Epoch(train) [3][35200/42151] lr: 3.0000e-04 eta: 13:44:37 time: 0.3391 data_time: 0.1310 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/16 23:56:46 - mmengine - INFO - Epoch(train) [3][35300/42151] lr: 3.0000e-04 eta: 13:43:56 time: 0.3413 data_time: 0.1360 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/16 23:57:21 - mmengine - INFO - Epoch(train) [3][35400/42151] lr: 3.0000e-04 eta: 13:43:16 time: 0.3374 data_time: 0.1248 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/16 23:57:56 - mmengine - INFO - Epoch(train) [3][35500/42151] lr: 3.0000e-04 eta: 13:42:37 time: 0.3393 data_time: 0.1097 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/16 23:58:30 - mmengine - INFO - Epoch(train) [3][35600/42151] lr: 3.0000e-04 eta: 13:41:56 time: 0.3493 data_time: 0.1205 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/16 23:59:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/16 23:59:03 - mmengine - INFO - Epoch(train) [3][35700/42151] lr: 3.0000e-04 eta: 13:41:15 time: 0.3186 data_time: 0.1080 memory: 7851 loss_ce: 0.0223 loss: 0.0223 2022/09/16 23:59:37 - mmengine - INFO - Epoch(train) [3][35800/42151] lr: 3.0000e-04 eta: 13:40:35 time: 0.3280 data_time: 0.0997 memory: 7851 loss_ce: 0.0227 loss: 0.0227 2022/09/17 00:00:19 - mmengine - INFO - Epoch(train) [3][35900/42151] lr: 3.0000e-04 eta: 13:40:02 time: 0.4323 data_time: 0.2112 memory: 7851 loss_ce: 0.0209 loss: 0.0209 2022/09/17 00:00:52 - mmengine - INFO - Epoch(train) [3][36000/42151] lr: 3.0000e-04 eta: 13:39:21 time: 0.4001 data_time: 0.1782 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/17 00:01:26 - mmengine - INFO - Epoch(train) [3][36100/42151] lr: 3.0000e-04 eta: 13:38:41 time: 0.4311 data_time: 0.2121 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/17 00:02:00 - mmengine - INFO - Epoch(train) [3][36200/42151] lr: 3.0000e-04 eta: 13:38:01 time: 0.3982 data_time: 0.1825 memory: 7851 loss_ce: 0.0235 loss: 0.0235 2022/09/17 00:02:35 - mmengine - INFO - Epoch(train) [3][36300/42151] lr: 3.0000e-04 eta: 13:37:21 time: 0.2542 data_time: 0.0130 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/17 00:03:09 - mmengine - INFO - Epoch(train) [3][36400/42151] lr: 3.0000e-04 eta: 13:36:40 time: 0.3105 data_time: 0.1067 memory: 7851 loss_ce: 0.0232 loss: 0.0232 2022/09/17 00:03:44 - mmengine - INFO - Epoch(train) [3][36500/42151] lr: 3.0000e-04 eta: 13:36:01 time: 0.3205 data_time: 0.1138 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/17 00:04:18 - mmengine - INFO - Epoch(train) [3][36600/42151] lr: 3.0000e-04 eta: 13:35:21 time: 0.2130 data_time: 0.0049 memory: 7851 loss_ce: 0.0236 loss: 0.0236 2022/09/17 00:04:53 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:04:53 - mmengine - INFO - Epoch(train) [3][36700/42151] lr: 3.0000e-04 eta: 13:34:41 time: 0.3200 data_time: 0.0815 memory: 7851 loss_ce: 0.0258 loss: 0.0258 2022/09/17 00:05:28 - mmengine - INFO - Epoch(train) [3][36800/42151] lr: 3.0000e-04 eta: 13:34:02 time: 0.3283 data_time: 0.1222 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/17 00:06:01 - mmengine - INFO - Epoch(train) [3][36900/42151] lr: 3.0000e-04 eta: 13:33:21 time: 0.2605 data_time: 0.0539 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/17 00:06:36 - mmengine - INFO - Epoch(train) [3][37000/42151] lr: 3.0000e-04 eta: 13:32:41 time: 0.3479 data_time: 0.1220 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/17 00:07:10 - mmengine - INFO - Epoch(train) [3][37100/42151] lr: 3.0000e-04 eta: 13:32:01 time: 0.3219 data_time: 0.1206 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/17 00:07:44 - mmengine - INFO - Epoch(train) [3][37200/42151] lr: 3.0000e-04 eta: 13:31:20 time: 0.2049 data_time: 0.0047 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/17 00:08:18 - mmengine - INFO - Epoch(train) [3][37300/42151] lr: 3.0000e-04 eta: 13:30:39 time: 0.2081 data_time: 0.0047 memory: 7851 loss_ce: 0.0216 loss: 0.0216 2022/09/17 00:08:52 - mmengine - INFO - Epoch(train) [3][37400/42151] lr: 3.0000e-04 eta: 13:29:59 time: 0.2890 data_time: 0.0690 memory: 7851 loss_ce: 0.0212 loss: 0.0212 2022/09/17 00:09:27 - mmengine - INFO - Epoch(train) [3][37500/42151] lr: 3.0000e-04 eta: 13:29:20 time: 0.3536 data_time: 0.1338 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/17 00:10:01 - mmengine - INFO - Epoch(train) [3][37600/42151] lr: 3.0000e-04 eta: 13:28:39 time: 0.3045 data_time: 0.0821 memory: 7851 loss_ce: 0.0231 loss: 0.0231 2022/09/17 00:10:34 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:10:35 - mmengine - INFO - Epoch(train) [3][37700/42151] lr: 3.0000e-04 eta: 13:28:00 time: 0.3735 data_time: 0.1570 memory: 7851 loss_ce: 0.0221 loss: 0.0221 2022/09/17 00:11:10 - mmengine - INFO - Epoch(train) [3][37800/42151] lr: 3.0000e-04 eta: 13:27:20 time: 0.2036 data_time: 0.0046 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/17 00:11:45 - mmengine - INFO - Epoch(train) [3][37900/42151] lr: 3.0000e-04 eta: 13:26:41 time: 0.3658 data_time: 0.1274 memory: 7851 loss_ce: 0.0212 loss: 0.0212 2022/09/17 00:12:18 - mmengine - INFO - Epoch(train) [3][38000/42151] lr: 3.0000e-04 eta: 13:26:00 time: 0.2602 data_time: 0.0539 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/17 00:12:53 - mmengine - INFO - Epoch(train) [3][38100/42151] lr: 3.0000e-04 eta: 13:25:20 time: 0.2413 data_time: 0.0383 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/17 00:13:26 - mmengine - INFO - Epoch(train) [3][38200/42151] lr: 3.0000e-04 eta: 13:24:39 time: 0.3040 data_time: 0.1005 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/17 00:14:01 - mmengine - INFO - Epoch(train) [3][38300/42151] lr: 3.0000e-04 eta: 13:24:00 time: 0.3653 data_time: 0.1432 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/17 00:14:35 - mmengine - INFO - Epoch(train) [3][38400/42151] lr: 3.0000e-04 eta: 13:23:20 time: 0.2292 data_time: 0.0309 memory: 7851 loss_ce: 0.0234 loss: 0.0234 2022/09/17 00:15:09 - mmengine - INFO - Epoch(train) [3][38500/42151] lr: 3.0000e-04 eta: 13:22:39 time: 0.3474 data_time: 0.1288 memory: 7851 loss_ce: 0.0198 loss: 0.0198 2022/09/17 00:15:43 - mmengine - INFO - Epoch(train) [3][38600/42151] lr: 3.0000e-04 eta: 13:21:59 time: 0.4245 data_time: 0.1982 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 00:16:16 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:16:17 - mmengine - INFO - Epoch(train) [3][38700/42151] lr: 3.0000e-04 eta: 13:21:19 time: 0.3794 data_time: 0.1450 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/17 00:16:51 - mmengine - INFO - Epoch(train) [3][38800/42151] lr: 3.0000e-04 eta: 13:20:38 time: 0.2356 data_time: 0.0381 memory: 7851 loss_ce: 0.0217 loss: 0.0217 2022/09/17 00:17:25 - mmengine - INFO - Epoch(train) [3][38900/42151] lr: 3.0000e-04 eta: 13:19:59 time: 0.2920 data_time: 0.0363 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/17 00:18:02 - mmengine - INFO - Epoch(train) [3][39000/42151] lr: 3.0000e-04 eta: 13:19:21 time: 0.5245 data_time: 0.3221 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 00:18:35 - mmengine - INFO - Epoch(train) [3][39100/42151] lr: 3.0000e-04 eta: 13:18:39 time: 0.4082 data_time: 0.2076 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/17 00:19:08 - mmengine - INFO - Epoch(train) [3][39200/42151] lr: 3.0000e-04 eta: 13:17:59 time: 0.3379 data_time: 0.1374 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/17 00:19:43 - mmengine - INFO - Epoch(train) [3][39300/42151] lr: 3.0000e-04 eta: 13:17:19 time: 0.3136 data_time: 0.1111 memory: 7851 loss_ce: 0.0215 loss: 0.0215 2022/09/17 00:20:16 - mmengine - INFO - Epoch(train) [3][39400/42151] lr: 3.0000e-04 eta: 13:16:39 time: 0.3357 data_time: 0.1166 memory: 7851 loss_ce: 0.0213 loss: 0.0213 2022/09/17 00:20:52 - mmengine - INFO - Epoch(train) [3][39500/42151] lr: 3.0000e-04 eta: 13:16:00 time: 0.3437 data_time: 0.1342 memory: 7851 loss_ce: 0.0196 loss: 0.0196 2022/09/17 00:21:26 - mmengine - INFO - Epoch(train) [3][39600/42151] lr: 3.0000e-04 eta: 13:15:20 time: 0.3433 data_time: 0.1368 memory: 7851 loss_ce: 0.0240 loss: 0.0240 2022/09/17 00:21:59 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:22:00 - mmengine - INFO - Epoch(train) [3][39700/42151] lr: 3.0000e-04 eta: 13:14:40 time: 0.3568 data_time: 0.1308 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/17 00:22:34 - mmengine - INFO - Epoch(train) [3][39800/42151] lr: 3.0000e-04 eta: 13:14:00 time: 0.3116 data_time: 0.0960 memory: 7851 loss_ce: 0.0238 loss: 0.0238 2022/09/17 00:23:07 - mmengine - INFO - Epoch(train) [3][39900/42151] lr: 3.0000e-04 eta: 13:13:19 time: 0.3144 data_time: 0.1091 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/17 00:23:42 - mmengine - INFO - Epoch(train) [3][40000/42151] lr: 3.0000e-04 eta: 13:12:40 time: 0.3334 data_time: 0.1257 memory: 7851 loss_ce: 0.0216 loss: 0.0216 2022/09/17 00:24:17 - mmengine - INFO - Epoch(train) [3][40100/42151] lr: 3.0000e-04 eta: 13:12:01 time: 0.3798 data_time: 0.1701 memory: 7851 loss_ce: 0.0218 loss: 0.0218 2022/09/17 00:24:51 - mmengine - INFO - Epoch(train) [3][40200/42151] lr: 3.0000e-04 eta: 13:11:20 time: 0.2014 data_time: 0.0047 memory: 7851 loss_ce: 0.0228 loss: 0.0228 2022/09/17 00:25:25 - mmengine - INFO - Epoch(train) [3][40300/42151] lr: 3.0000e-04 eta: 13:10:40 time: 0.2626 data_time: 0.0612 memory: 7851 loss_ce: 0.0226 loss: 0.0226 2022/09/17 00:26:00 - mmengine - INFO - Epoch(train) [3][40400/42151] lr: 3.0000e-04 eta: 13:10:01 time: 0.3229 data_time: 0.0843 memory: 7851 loss_ce: 0.0222 loss: 0.0222 2022/09/17 00:26:34 - mmengine - INFO - Epoch(train) [3][40500/42151] lr: 3.0000e-04 eta: 13:09:21 time: 0.3207 data_time: 0.1228 memory: 7851 loss_ce: 0.0204 loss: 0.0204 2022/09/17 00:27:09 - mmengine - INFO - Epoch(train) [3][40600/42151] lr: 3.0000e-04 eta: 13:08:42 time: 0.5350 data_time: 0.2951 memory: 7851 loss_ce: 0.0201 loss: 0.0201 2022/09/17 00:27:40 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:27:40 - mmengine - INFO - Epoch(train) [3][40700/42151] lr: 3.0000e-04 eta: 13:07:59 time: 0.2125 data_time: 0.0138 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/17 00:28:19 - mmengine - INFO - Epoch(train) [3][40800/42151] lr: 3.0000e-04 eta: 13:07:24 time: 0.2578 data_time: 0.0514 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/17 00:28:53 - mmengine - INFO - Epoch(train) [3][40900/42151] lr: 3.0000e-04 eta: 13:06:44 time: 0.2384 data_time: 0.0066 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/17 00:29:25 - mmengine - INFO - Epoch(train) [3][41000/42151] lr: 3.0000e-04 eta: 13:06:02 time: 0.3569 data_time: 0.1251 memory: 7851 loss_ce: 0.0220 loss: 0.0220 2022/09/17 00:30:01 - mmengine - INFO - Epoch(train) [3][41100/42151] lr: 3.0000e-04 eta: 13:05:24 time: 0.4600 data_time: 0.2552 memory: 7851 loss_ce: 0.0202 loss: 0.0202 2022/09/17 00:30:34 - mmengine - INFO - Epoch(train) [3][41200/42151] lr: 3.0000e-04 eta: 13:04:43 time: 0.3935 data_time: 0.1928 memory: 7851 loss_ce: 0.0198 loss: 0.0198 2022/09/17 00:31:08 - mmengine - INFO - Epoch(train) [3][41300/42151] lr: 3.0000e-04 eta: 13:04:03 time: 0.4185 data_time: 0.2104 memory: 7851 loss_ce: 0.0211 loss: 0.0211 2022/09/17 00:31:40 - mmengine - INFO - Epoch(train) [3][41400/42151] lr: 3.0000e-04 eta: 13:03:21 time: 0.2177 data_time: 0.0128 memory: 7851 loss_ce: 0.0224 loss: 0.0224 2022/09/17 00:32:15 - mmengine - INFO - Epoch(train) [3][41500/42151] lr: 3.0000e-04 eta: 13:02:42 time: 0.3361 data_time: 0.1300 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/17 00:32:48 - mmengine - INFO - Epoch(train) [3][41600/42151] lr: 3.0000e-04 eta: 13:02:01 time: 0.3465 data_time: 0.1462 memory: 7851 loss_ce: 0.0208 loss: 0.0208 2022/09/17 00:33:20 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:33:21 - mmengine - INFO - Epoch(train) [3][41700/42151] lr: 3.0000e-04 eta: 13:01:20 time: 0.4083 data_time: 0.1470 memory: 7851 loss_ce: 0.0198 loss: 0.0198 2022/09/17 00:33:55 - mmengine - INFO - Epoch(train) [3][41800/42151] lr: 3.0000e-04 eta: 13:00:40 time: 0.3969 data_time: 0.1860 memory: 7851 loss_ce: 0.0219 loss: 0.0219 2022/09/17 00:34:28 - mmengine - INFO - Epoch(train) [3][41900/42151] lr: 3.0000e-04 eta: 12:59:59 time: 0.4252 data_time: 0.1597 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/17 00:35:12 - mmengine - INFO - Epoch(train) [3][42000/42151] lr: 3.0000e-04 eta: 12:59:30 time: 0.7369 data_time: 0.5098 memory: 7851 loss_ce: 0.0214 loss: 0.0214 2022/09/17 00:36:16 - mmengine - INFO - Epoch(train) [3][42100/42151] lr: 3.0000e-04 eta: 12:59:19 time: 0.2114 data_time: 0.0053 memory: 7851 loss_ce: 0.0210 loss: 0.0210 2022/09/17 00:36:32 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 00:36:32 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/09/17 00:37:19 - mmengine - INFO - Epoch(val) [3][100/7672] eta: 0:50:06 time: 0.3970 data_time: 0.0021 memory: 7851 2022/09/17 00:38:01 - mmengine - INFO - Epoch(val) [3][200/7672] eta: 0:55:27 time: 0.4454 data_time: 0.0023 memory: 580 2022/09/17 00:38:40 - mmengine - INFO - Epoch(val) [3][300/7672] eta: 0:31:21 time: 0.2552 data_time: 0.0012 memory: 580 2022/09/17 00:39:02 - mmengine - INFO - Epoch(val) [3][400/7672] eta: 0:27:28 time: 0.2266 data_time: 0.0008 memory: 580 2022/09/17 00:39:24 - mmengine - INFO - Epoch(val) [3][500/7672] eta: 0:24:54 time: 0.2084 data_time: 0.0008 memory: 580 2022/09/17 00:39:46 - mmengine - INFO - Epoch(val) [3][600/7672] eta: 0:26:16 time: 0.2230 data_time: 0.0008 memory: 580 2022/09/17 00:40:07 - mmengine - INFO - Epoch(val) [3][700/7672] eta: 0:22:58 time: 0.1977 data_time: 0.0007 memory: 580 2022/09/17 00:40:29 - mmengine - INFO - Epoch(val) [3][800/7672] eta: 0:23:18 time: 0.2035 data_time: 0.0008 memory: 580 2022/09/17 00:40:49 - mmengine - INFO - Epoch(val) [3][900/7672] eta: 0:22:20 time: 0.1980 data_time: 0.0008 memory: 580 2022/09/17 00:41:12 - mmengine - INFO - Epoch(val) [3][1000/7672] eta: 0:22:45 time: 0.2047 data_time: 0.0008 memory: 580 2022/09/17 00:41:33 - mmengine - INFO - Epoch(val) [3][1100/7672] eta: 0:23:22 time: 0.2133 data_time: 0.0008 memory: 580 2022/09/17 00:41:55 - mmengine - INFO - Epoch(val) [3][1200/7672] eta: 0:21:43 time: 0.2014 data_time: 0.0010 memory: 580 2022/09/17 00:42:17 - mmengine - INFO - Epoch(val) [3][1300/7672] eta: 0:22:07 time: 0.2084 data_time: 0.0008 memory: 580 2022/09/17 00:42:38 - mmengine - INFO - Epoch(val) [3][1400/7672] eta: 0:20:59 time: 0.2009 data_time: 0.0007 memory: 580 2022/09/17 00:43:00 - mmengine - INFO - Epoch(val) [3][1500/7672] eta: 0:20:50 time: 0.2027 data_time: 0.0008 memory: 580 2022/09/17 00:43:22 - mmengine - INFO - Epoch(val) [3][1600/7672] eta: 0:24:48 time: 0.2451 data_time: 0.0009 memory: 580 2022/09/17 00:43:43 - mmengine - INFO - Epoch(val) [3][1700/7672] eta: 0:20:23 time: 0.2048 data_time: 0.0008 memory: 580 2022/09/17 00:44:05 - mmengine - INFO - Epoch(val) [3][1800/7672] eta: 0:21:13 time: 0.2170 data_time: 0.0008 memory: 580 2022/09/17 00:44:27 - mmengine - INFO - Epoch(val) [3][1900/7672] eta: 0:20:19 time: 0.2113 data_time: 0.0008 memory: 580 2022/09/17 00:44:48 - mmengine - INFO - Epoch(val) [3][2000/7672] eta: 0:19:51 time: 0.2100 data_time: 0.0024 memory: 580 2022/09/17 00:45:10 - mmengine - INFO - Epoch(val) [3][2100/7672] eta: 0:18:52 time: 0.2032 data_time: 0.0008 memory: 580 2022/09/17 00:45:32 - mmengine - INFO - Epoch(val) [3][2200/7672] eta: 0:19:17 time: 0.2115 data_time: 0.0008 memory: 580 2022/09/17 00:45:54 - mmengine - INFO - Epoch(val) [3][2300/7672] eta: 0:18:01 time: 0.2014 data_time: 0.0008 memory: 580 2022/09/17 00:46:15 - mmengine - INFO - Epoch(val) [3][2400/7672] eta: 0:17:38 time: 0.2008 data_time: 0.0008 memory: 580 2022/09/17 00:46:37 - mmengine - INFO - Epoch(val) [3][2500/7672] eta: 0:18:47 time: 0.2179 data_time: 0.0008 memory: 580 2022/09/17 00:46:58 - mmengine - INFO - Epoch(val) [3][2600/7672] eta: 0:16:42 time: 0.1977 data_time: 0.0007 memory: 580 2022/09/17 00:47:19 - mmengine - INFO - Epoch(val) [3][2700/7672] eta: 0:17:57 time: 0.2168 data_time: 0.0016 memory: 580 2022/09/17 00:47:41 - mmengine - INFO - Epoch(val) [3][2800/7672] eta: 0:19:34 time: 0.2412 data_time: 0.0025 memory: 580 2022/09/17 00:48:02 - mmengine - INFO - Epoch(val) [3][2900/7672] eta: 0:17:06 time: 0.2151 data_time: 0.0013 memory: 580 2022/09/17 00:48:23 - mmengine - INFO - Epoch(val) [3][3000/7672] eta: 0:16:13 time: 0.2083 data_time: 0.0007 memory: 580 2022/09/17 00:48:44 - mmengine - INFO - Epoch(val) [3][3100/7672] eta: 0:15:00 time: 0.1970 data_time: 0.0008 memory: 580 2022/09/17 00:49:05 - mmengine - INFO - Epoch(val) [3][3200/7672] eta: 0:15:02 time: 0.2017 data_time: 0.0008 memory: 580 2022/09/17 00:49:27 - mmengine - INFO - Epoch(val) [3][3300/7672] eta: 0:15:14 time: 0.2091 data_time: 0.0008 memory: 580 2022/09/17 00:49:48 - mmengine - INFO - Epoch(val) [3][3400/7672] eta: 0:14:16 time: 0.2006 data_time: 0.0010 memory: 580 2022/09/17 00:50:09 - mmengine - INFO - Epoch(val) [3][3500/7672] eta: 0:15:09 time: 0.2179 data_time: 0.0008 memory: 580 2022/09/17 00:50:31 - mmengine - INFO - Epoch(val) [3][3600/7672] eta: 0:14:37 time: 0.2154 data_time: 0.0011 memory: 580 2022/09/17 00:50:53 - mmengine - INFO - Epoch(val) [3][3700/7672] eta: 0:13:32 time: 0.2046 data_time: 0.0008 memory: 580 2022/09/17 00:51:14 - mmengine - INFO - Epoch(val) [3][3800/7672] eta: 0:13:50 time: 0.2145 data_time: 0.0008 memory: 580 2022/09/17 00:51:36 - mmengine - INFO - Epoch(val) [3][3900/7672] eta: 0:13:20 time: 0.2123 data_time: 0.0007 memory: 580 2022/09/17 00:51:57 - mmengine - INFO - Epoch(val) [3][4000/7672] eta: 0:12:16 time: 0.2007 data_time: 0.0007 memory: 580 2022/09/17 00:52:18 - mmengine - INFO - Epoch(val) [3][4100/7672] eta: 0:12:46 time: 0.2145 data_time: 0.0008 memory: 580 2022/09/17 00:52:40 - mmengine - INFO - Epoch(val) [3][4200/7672] eta: 0:11:48 time: 0.2040 data_time: 0.0010 memory: 580 2022/09/17 00:53:02 - mmengine - INFO - Epoch(val) [3][4300/7672] eta: 0:11:55 time: 0.2122 data_time: 0.0008 memory: 580 2022/09/17 00:53:23 - mmengine - INFO - Epoch(val) [3][4400/7672] eta: 0:11:12 time: 0.2057 data_time: 0.0008 memory: 580 2022/09/17 00:53:44 - mmengine - INFO - Epoch(val) [3][4500/7672] eta: 0:10:47 time: 0.2041 data_time: 0.0007 memory: 580 2022/09/17 00:54:06 - mmengine - INFO - Epoch(val) [3][4600/7672] eta: 0:10:33 time: 0.2063 data_time: 0.0008 memory: 580 2022/09/17 00:54:27 - mmengine - INFO - Epoch(val) [3][4700/7672] eta: 0:10:52 time: 0.2195 data_time: 0.0008 memory: 580 2022/09/17 00:54:48 - mmengine - INFO - Epoch(val) [3][4800/7672] eta: 0:09:52 time: 0.2062 data_time: 0.0008 memory: 580 2022/09/17 00:55:10 - mmengine - INFO - Epoch(val) [3][4900/7672] eta: 0:10:21 time: 0.2242 data_time: 0.0008 memory: 580 2022/09/17 00:55:32 - mmengine - INFO - Epoch(val) [3][5000/7672] eta: 0:09:34 time: 0.2150 data_time: 0.0008 memory: 580 2022/09/17 00:55:53 - mmengine - INFO - Epoch(val) [3][5100/7672] eta: 0:08:48 time: 0.2053 data_time: 0.0008 memory: 580 2022/09/17 00:56:15 - mmengine - INFO - Epoch(val) [3][5200/7672] eta: 0:08:50 time: 0.2146 data_time: 0.0008 memory: 580 2022/09/17 00:56:37 - mmengine - INFO - Epoch(val) [3][5300/7672] eta: 0:08:46 time: 0.2218 data_time: 0.0008 memory: 580 2022/09/17 00:56:59 - mmengine - INFO - Epoch(val) [3][5400/7672] eta: 0:08:58 time: 0.2368 data_time: 0.0010 memory: 580 2022/09/17 00:57:19 - mmengine - INFO - Epoch(val) [3][5500/7672] eta: 0:07:44 time: 0.2139 data_time: 0.0020 memory: 580 2022/09/17 00:57:40 - mmengine - INFO - Epoch(val) [3][5600/7672] eta: 0:07:06 time: 0.2061 data_time: 0.0011 memory: 580 2022/09/17 00:58:00 - mmengine - INFO - Epoch(val) [3][5700/7672] eta: 0:06:42 time: 0.2040 data_time: 0.0012 memory: 580 2022/09/17 00:58:21 - mmengine - INFO - Epoch(val) [3][5800/7672] eta: 0:06:30 time: 0.2087 data_time: 0.0015 memory: 580 2022/09/17 00:58:42 - mmengine - INFO - Epoch(val) [3][5900/7672] eta: 0:05:56 time: 0.2014 data_time: 0.0010 memory: 580 2022/09/17 00:59:02 - mmengine - INFO - Epoch(val) [3][6000/7672] eta: 0:05:37 time: 0.2018 data_time: 0.0008 memory: 580 2022/09/17 00:59:23 - mmengine - INFO - Epoch(val) [3][6100/7672] eta: 0:05:10 time: 0.1977 data_time: 0.0007 memory: 580 2022/09/17 00:59:44 - mmengine - INFO - Epoch(val) [3][6200/7672] eta: 0:05:06 time: 0.2084 data_time: 0.0007 memory: 580 2022/09/17 01:00:04 - mmengine - INFO - Epoch(val) [3][6300/7672] eta: 0:04:45 time: 0.2080 data_time: 0.0009 memory: 580 2022/09/17 01:00:25 - mmengine - INFO - Epoch(val) [3][6400/7672] eta: 0:04:15 time: 0.2005 data_time: 0.0008 memory: 580 2022/09/17 01:00:46 - mmengine - INFO - Epoch(val) [3][6500/7672] eta: 0:03:50 time: 0.1970 data_time: 0.0007 memory: 580 2022/09/17 01:01:06 - mmengine - INFO - Epoch(val) [3][6600/7672] eta: 0:03:31 time: 0.1975 data_time: 0.0007 memory: 580 2022/09/17 01:01:27 - mmengine - INFO - Epoch(val) [3][6700/7672] eta: 0:03:37 time: 0.2243 data_time: 0.0007 memory: 580 2022/09/17 01:01:47 - mmengine - INFO - Epoch(val) [3][6800/7672] eta: 0:02:56 time: 0.2028 data_time: 0.0007 memory: 580 2022/09/17 01:02:08 - mmengine - INFO - Epoch(val) [3][6900/7672] eta: 0:02:35 time: 0.2009 data_time: 0.0008 memory: 580 2022/09/17 01:02:28 - mmengine - INFO - Epoch(val) [3][7000/7672] eta: 0:02:12 time: 0.1970 data_time: 0.0007 memory: 580 2022/09/17 01:02:49 - mmengine - INFO - Epoch(val) [3][7100/7672] eta: 0:01:57 time: 0.2062 data_time: 0.0008 memory: 580 2022/09/17 01:03:10 - mmengine - INFO - Epoch(val) [3][7200/7672] eta: 0:01:35 time: 0.2017 data_time: 0.0015 memory: 580 2022/09/17 01:03:30 - mmengine - INFO - Epoch(val) [3][7300/7672] eta: 0:01:17 time: 0.2083 data_time: 0.0026 memory: 580 2022/09/17 01:03:50 - mmengine - INFO - Epoch(val) [3][7400/7672] eta: 0:00:56 time: 0.2089 data_time: 0.0023 memory: 580 2022/09/17 01:04:10 - mmengine - INFO - Epoch(val) [3][7500/7672] eta: 0:00:37 time: 0.2168 data_time: 0.0024 memory: 580 2022/09/17 01:04:31 - mmengine - INFO - Epoch(val) [3][7600/7672] eta: 0:00:14 time: 0.2037 data_time: 0.0008 memory: 580 2022/09/17 01:04:45 - mmengine - INFO - Epoch(val) [3][7672/7672] CUTE80/recog/word_acc_ignore_case_symbol: 0.7465 IIIT5K/recog/word_acc_ignore_case_symbol: 0.8910 SVT/recog/word_acc_ignore_case_symbol: 0.8609 SVTP/recog/word_acc_ignore_case_symbol: 0.7256 IC13/recog/word_acc_ignore_case_symbol: 0.9212 IC15/recog/word_acc_ignore_case_symbol: 0.6895 2022/09/17 01:05:28 - mmengine - INFO - Epoch(train) [4][100/42151] lr: 3.0000e-05 eta: 12:58:24 time: 0.2061 data_time: 0.0053 memory: 7851 loss_ce: 0.0199 loss: 0.0199 2022/09/17 01:06:05 - mmengine - INFO - Epoch(train) [4][200/42151] lr: 3.0000e-05 eta: 12:57:48 time: 0.2374 data_time: 0.0052 memory: 7851 loss_ce: 0.0192 loss: 0.0192 2022/09/17 01:07:13 - mmengine - INFO - Epoch(train) [4][300/42151] lr: 3.0000e-05 eta: 12:57:42 time: 0.3217 data_time: 0.1180 memory: 7851 loss_ce: 0.0183 loss: 0.0183 2022/09/17 01:08:25 - mmengine - INFO - Epoch(train) [4][400/42151] lr: 3.0000e-05 eta: 12:57:40 time: 0.2326 data_time: 0.0288 memory: 7851 loss_ce: 0.0203 loss: 0.0203 2022/09/17 01:09:24 - mmengine - INFO - Epoch(train) [4][500/42151] lr: 3.0000e-05 eta: 12:57:24 time: 1.1219 data_time: 0.9221 memory: 7851 loss_ce: 0.0196 loss: 0.0196 2022/09/17 01:09:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:09:55 - mmengine - INFO - Epoch(train) [4][600/42151] lr: 3.0000e-05 eta: 12:56:42 time: 0.3721 data_time: 0.1474 memory: 7851 loss_ce: 0.0196 loss: 0.0196 2022/09/17 01:10:28 - mmengine - INFO - Epoch(train) [4][700/42151] lr: 3.0000e-05 eta: 12:56:00 time: 0.3308 data_time: 0.1170 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 01:11:07 - mmengine - INFO - Epoch(train) [4][800/42151] lr: 3.0000e-05 eta: 12:55:25 time: 0.7926 data_time: 0.5935 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 01:11:39 - mmengine - INFO - Epoch(train) [4][900/42151] lr: 3.0000e-05 eta: 12:54:43 time: 0.4565 data_time: 0.2217 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 01:12:34 - mmengine - INFO - Epoch(train) [4][1000/42151] lr: 3.0000e-05 eta: 12:54:24 time: 1.1116 data_time: 0.9010 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 01:13:04 - mmengine - INFO - Epoch(train) [4][1100/42151] lr: 3.0000e-05 eta: 12:53:40 time: 0.2062 data_time: 0.0050 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 01:13:39 - mmengine - INFO - Epoch(train) [4][1200/42151] lr: 3.0000e-05 eta: 12:53:01 time: 0.4507 data_time: 0.2420 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 01:14:11 - mmengine - INFO - Epoch(train) [4][1300/42151] lr: 3.0000e-05 eta: 12:52:19 time: 0.2164 data_time: 0.0050 memory: 7851 loss_ce: 0.0201 loss: 0.0201 2022/09/17 01:14:46 - mmengine - INFO - Epoch(train) [4][1400/42151] lr: 3.0000e-05 eta: 12:51:40 time: 0.4936 data_time: 0.2894 memory: 7851 loss_ce: 0.0180 loss: 0.0180 2022/09/17 01:15:19 - mmengine - INFO - Epoch(train) [4][1500/42151] lr: 3.0000e-05 eta: 12:50:59 time: 0.2111 data_time: 0.0053 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 01:15:35 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:15:52 - mmengine - INFO - Epoch(train) [4][1600/42151] lr: 3.0000e-05 eta: 12:50:18 time: 0.3169 data_time: 0.1072 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 01:16:27 - mmengine - INFO - Epoch(train) [4][1700/42151] lr: 3.0000e-05 eta: 12:49:38 time: 0.3844 data_time: 0.1819 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 01:17:00 - mmengine - INFO - Epoch(train) [4][1800/42151] lr: 3.0000e-05 eta: 12:48:57 time: 0.3537 data_time: 0.1352 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 01:17:34 - mmengine - INFO - Epoch(train) [4][1900/42151] lr: 3.0000e-05 eta: 12:48:18 time: 0.3784 data_time: 0.1740 memory: 7851 loss_ce: 0.0194 loss: 0.0194 2022/09/17 01:18:06 - mmengine - INFO - Epoch(train) [4][2000/42151] lr: 3.0000e-05 eta: 12:47:35 time: 0.2703 data_time: 0.0397 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 01:18:40 - mmengine - INFO - Epoch(train) [4][2100/42151] lr: 3.0000e-05 eta: 12:46:56 time: 0.2345 data_time: 0.0056 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 01:19:12 - mmengine - INFO - Epoch(train) [4][2200/42151] lr: 3.0000e-05 eta: 12:46:14 time: 0.2204 data_time: 0.0069 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:19:46 - mmengine - INFO - Epoch(train) [4][2300/42151] lr: 3.0000e-05 eta: 12:45:34 time: 0.2911 data_time: 0.0583 memory: 7851 loss_ce: 0.0186 loss: 0.0186 2022/09/17 01:20:20 - mmengine - INFO - Epoch(train) [4][2400/42151] lr: 3.0000e-05 eta: 12:44:54 time: 0.3565 data_time: 0.1278 memory: 7851 loss_ce: 0.0195 loss: 0.0195 2022/09/17 01:20:54 - mmengine - INFO - Epoch(train) [4][2500/42151] lr: 3.0000e-05 eta: 12:44:14 time: 0.3979 data_time: 0.1962 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 01:21:10 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:21:28 - mmengine - INFO - Epoch(train) [4][2600/42151] lr: 3.0000e-05 eta: 12:43:34 time: 0.3488 data_time: 0.1187 memory: 7851 loss_ce: 0.0186 loss: 0.0186 2022/09/17 01:22:03 - mmengine - INFO - Epoch(train) [4][2700/42151] lr: 3.0000e-05 eta: 12:42:56 time: 0.4987 data_time: 0.2857 memory: 7851 loss_ce: 0.0189 loss: 0.0189 2022/09/17 01:22:35 - mmengine - INFO - Epoch(train) [4][2800/42151] lr: 3.0000e-05 eta: 12:42:13 time: 0.4380 data_time: 0.2292 memory: 7851 loss_ce: 0.0177 loss: 0.0177 2022/09/17 01:23:07 - mmengine - INFO - Epoch(train) [4][2900/42151] lr: 3.0000e-05 eta: 12:41:32 time: 0.3253 data_time: 0.0958 memory: 7851 loss_ce: 0.0192 loss: 0.0192 2022/09/17 01:23:42 - mmengine - INFO - Epoch(train) [4][3000/42151] lr: 3.0000e-05 eta: 12:40:52 time: 0.4178 data_time: 0.2101 memory: 7851 loss_ce: 0.0207 loss: 0.0207 2022/09/17 01:24:14 - mmengine - INFO - Epoch(train) [4][3100/42151] lr: 3.0000e-05 eta: 12:40:11 time: 0.3758 data_time: 0.1765 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 01:24:47 - mmengine - INFO - Epoch(train) [4][3200/42151] lr: 3.0000e-05 eta: 12:39:30 time: 0.2701 data_time: 0.0486 memory: 7851 loss_ce: 0.0202 loss: 0.0202 2022/09/17 01:25:22 - mmengine - INFO - Epoch(train) [4][3300/42151] lr: 3.0000e-05 eta: 12:38:51 time: 0.2977 data_time: 0.0645 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 01:25:57 - mmengine - INFO - Epoch(train) [4][3400/42151] lr: 3.0000e-05 eta: 12:38:12 time: 0.4010 data_time: 0.1943 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 01:26:32 - mmengine - INFO - Epoch(train) [4][3500/42151] lr: 3.0000e-05 eta: 12:37:33 time: 0.3463 data_time: 0.1408 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 01:26:48 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:27:07 - mmengine - INFO - Epoch(train) [4][3600/42151] lr: 3.0000e-05 eta: 12:36:54 time: 0.3619 data_time: 0.1293 memory: 7851 loss_ce: 0.0187 loss: 0.0187 2022/09/17 01:27:41 - mmengine - INFO - Epoch(train) [4][3700/42151] lr: 3.0000e-05 eta: 12:36:15 time: 0.3554 data_time: 0.1515 memory: 7851 loss_ce: 0.0182 loss: 0.0182 2022/09/17 01:28:14 - mmengine - INFO - Epoch(train) [4][3800/42151] lr: 3.0000e-05 eta: 12:35:34 time: 0.3487 data_time: 0.1239 memory: 7851 loss_ce: 0.0205 loss: 0.0205 2022/09/17 01:28:48 - mmengine - INFO - Epoch(train) [4][3900/42151] lr: 3.0000e-05 eta: 12:34:54 time: 0.2990 data_time: 0.0664 memory: 7851 loss_ce: 0.0187 loss: 0.0187 2022/09/17 01:29:23 - mmengine - INFO - Epoch(train) [4][4000/42151] lr: 3.0000e-05 eta: 12:34:16 time: 0.3544 data_time: 0.1497 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 01:29:58 - mmengine - INFO - Epoch(train) [4][4100/42151] lr: 3.0000e-05 eta: 12:33:37 time: 0.3474 data_time: 0.1454 memory: 7851 loss_ce: 0.0194 loss: 0.0194 2022/09/17 01:30:33 - mmengine - INFO - Epoch(train) [4][4200/42151] lr: 3.0000e-05 eta: 12:32:58 time: 0.3632 data_time: 0.1315 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 01:31:07 - mmengine - INFO - Epoch(train) [4][4300/42151] lr: 3.0000e-05 eta: 12:32:18 time: 0.3405 data_time: 0.1354 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 01:31:41 - mmengine - INFO - Epoch(train) [4][4400/42151] lr: 3.0000e-05 eta: 12:31:38 time: 0.3171 data_time: 0.1156 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 01:32:15 - mmengine - INFO - Epoch(train) [4][4500/42151] lr: 3.0000e-05 eta: 12:30:59 time: 0.3028 data_time: 0.0762 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 01:32:33 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:32:51 - mmengine - INFO - Epoch(train) [4][4600/42151] lr: 3.0000e-05 eta: 12:30:21 time: 0.3759 data_time: 0.1494 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 01:33:26 - mmengine - INFO - Epoch(train) [4][4700/42151] lr: 3.0000e-05 eta: 12:29:42 time: 0.3708 data_time: 0.1670 memory: 7851 loss_ce: 0.0183 loss: 0.0183 2022/09/17 01:34:00 - mmengine - INFO - Epoch(train) [4][4800/42151] lr: 3.0000e-05 eta: 12:29:03 time: 0.3201 data_time: 0.0972 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 01:34:34 - mmengine - INFO - Epoch(train) [4][4900/42151] lr: 3.0000e-05 eta: 12:28:22 time: 0.3452 data_time: 0.1430 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:35:08 - mmengine - INFO - Epoch(train) [4][5000/42151] lr: 3.0000e-05 eta: 12:27:42 time: 0.3380 data_time: 0.1158 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 01:35:42 - mmengine - INFO - Epoch(train) [4][5100/42151] lr: 3.0000e-05 eta: 12:27:03 time: 0.3179 data_time: 0.0923 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 01:36:17 - mmengine - INFO - Epoch(train) [4][5200/42151] lr: 3.0000e-05 eta: 12:26:24 time: 0.3477 data_time: 0.1242 memory: 7851 loss_ce: 0.0205 loss: 0.0205 2022/09/17 01:36:51 - mmengine - INFO - Epoch(train) [4][5300/42151] lr: 3.0000e-05 eta: 12:25:45 time: 0.3598 data_time: 0.1598 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 01:37:26 - mmengine - INFO - Epoch(train) [4][5400/42151] lr: 3.0000e-05 eta: 12:25:06 time: 0.3366 data_time: 0.1003 memory: 7851 loss_ce: 0.0186 loss: 0.0186 2022/09/17 01:38:00 - mmengine - INFO - Epoch(train) [4][5500/42151] lr: 3.0000e-05 eta: 12:24:26 time: 0.3446 data_time: 0.1407 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 01:38:16 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:38:34 - mmengine - INFO - Epoch(train) [4][5600/42151] lr: 3.0000e-05 eta: 12:23:47 time: 0.3150 data_time: 0.1071 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 01:39:08 - mmengine - INFO - Epoch(train) [4][5700/42151] lr: 3.0000e-05 eta: 12:23:08 time: 0.3076 data_time: 0.0841 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 01:39:43 - mmengine - INFO - Epoch(train) [4][5800/42151] lr: 3.0000e-05 eta: 12:22:28 time: 0.3568 data_time: 0.1453 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:40:17 - mmengine - INFO - Epoch(train) [4][5900/42151] lr: 3.0000e-05 eta: 12:21:49 time: 0.3619 data_time: 0.1592 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 01:40:52 - mmengine - INFO - Epoch(train) [4][6000/42151] lr: 3.0000e-05 eta: 12:21:10 time: 0.3338 data_time: 0.1328 memory: 7851 loss_ce: 0.0188 loss: 0.0188 2022/09/17 01:41:26 - mmengine - INFO - Epoch(train) [4][6100/42151] lr: 3.0000e-05 eta: 12:20:30 time: 0.3829 data_time: 0.1339 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 01:42:00 - mmengine - INFO - Epoch(train) [4][6200/42151] lr: 3.0000e-05 eta: 12:19:51 time: 0.3094 data_time: 0.1104 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 01:42:35 - mmengine - INFO - Epoch(train) [4][6300/42151] lr: 3.0000e-05 eta: 12:19:12 time: 0.3201 data_time: 0.0870 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 01:43:09 - mmengine - INFO - Epoch(train) [4][6400/42151] lr: 3.0000e-05 eta: 12:18:33 time: 0.3493 data_time: 0.1431 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 01:43:44 - mmengine - INFO - Epoch(train) [4][6500/42151] lr: 3.0000e-05 eta: 12:17:54 time: 0.3959 data_time: 0.1664 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 01:44:00 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:44:18 - mmengine - INFO - Epoch(train) [4][6600/42151] lr: 3.0000e-05 eta: 12:17:15 time: 0.3309 data_time: 0.1222 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 01:44:52 - mmengine - INFO - Epoch(train) [4][6700/42151] lr: 3.0000e-05 eta: 12:16:35 time: 0.3653 data_time: 0.1383 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 01:45:27 - mmengine - INFO - Epoch(train) [4][6800/42151] lr: 3.0000e-05 eta: 12:15:56 time: 0.3135 data_time: 0.0914 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 01:46:02 - mmengine - INFO - Epoch(train) [4][6900/42151] lr: 3.0000e-05 eta: 12:15:17 time: 0.3131 data_time: 0.1066 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:46:36 - mmengine - INFO - Epoch(train) [4][7000/42151] lr: 3.0000e-05 eta: 12:14:38 time: 0.3589 data_time: 0.1351 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 01:47:10 - mmengine - INFO - Epoch(train) [4][7100/42151] lr: 3.0000e-05 eta: 12:13:58 time: 0.3872 data_time: 0.1623 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 01:47:43 - mmengine - INFO - Epoch(train) [4][7200/42151] lr: 3.0000e-05 eta: 12:13:18 time: 0.3480 data_time: 0.1475 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 01:48:17 - mmengine - INFO - Epoch(train) [4][7300/42151] lr: 3.0000e-05 eta: 12:12:38 time: 0.3409 data_time: 0.1382 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:48:51 - mmengine - INFO - Epoch(train) [4][7400/42151] lr: 3.0000e-05 eta: 12:11:59 time: 0.3217 data_time: 0.1012 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 01:49:26 - mmengine - INFO - Epoch(train) [4][7500/42151] lr: 3.0000e-05 eta: 12:11:20 time: 0.3084 data_time: 0.0858 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 01:49:41 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:50:00 - mmengine - INFO - Epoch(train) [4][7600/42151] lr: 3.0000e-05 eta: 12:10:41 time: 0.3736 data_time: 0.1451 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:50:34 - mmengine - INFO - Epoch(train) [4][7700/42151] lr: 3.0000e-05 eta: 12:10:02 time: 0.3739 data_time: 0.1581 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 01:51:08 - mmengine - INFO - Epoch(train) [4][7800/42151] lr: 3.0000e-05 eta: 12:09:22 time: 0.3263 data_time: 0.1203 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 01:51:42 - mmengine - INFO - Epoch(train) [4][7900/42151] lr: 3.0000e-05 eta: 12:08:42 time: 0.3457 data_time: 0.1400 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 01:52:15 - mmengine - INFO - Epoch(train) [4][8000/42151] lr: 3.0000e-05 eta: 12:08:02 time: 0.3248 data_time: 0.1227 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 01:52:50 - mmengine - INFO - Epoch(train) [4][8100/42151] lr: 3.0000e-05 eta: 12:07:23 time: 0.3048 data_time: 0.0818 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 01:53:24 - mmengine - INFO - Epoch(train) [4][8200/42151] lr: 3.0000e-05 eta: 12:06:44 time: 0.3337 data_time: 0.1072 memory: 7851 loss_ce: 0.0182 loss: 0.0182 2022/09/17 01:53:58 - mmengine - INFO - Epoch(train) [4][8300/42151] lr: 3.0000e-05 eta: 12:06:04 time: 0.3827 data_time: 0.1570 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 01:54:32 - mmengine - INFO - Epoch(train) [4][8400/42151] lr: 3.0000e-05 eta: 12:05:25 time: 0.3697 data_time: 0.1594 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 01:55:06 - mmengine - INFO - Epoch(train) [4][8500/42151] lr: 3.0000e-05 eta: 12:04:46 time: 0.3583 data_time: 0.1598 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 01:55:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 01:55:40 - mmengine - INFO - Epoch(train) [4][8600/42151] lr: 3.0000e-05 eta: 12:04:06 time: 0.3211 data_time: 0.1194 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 01:56:14 - mmengine - INFO - Epoch(train) [4][8700/42151] lr: 3.0000e-05 eta: 12:03:27 time: 0.3112 data_time: 0.0846 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 01:56:49 - mmengine - INFO - Epoch(train) [4][8800/42151] lr: 3.0000e-05 eta: 12:02:49 time: 0.3420 data_time: 0.1153 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 01:57:24 - mmengine - INFO - Epoch(train) [4][8900/42151] lr: 3.0000e-05 eta: 12:02:10 time: 0.4084 data_time: 0.1772 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 01:57:59 - mmengine - INFO - Epoch(train) [4][9000/42151] lr: 3.0000e-05 eta: 12:01:31 time: 0.3540 data_time: 0.1566 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 01:58:33 - mmengine - INFO - Epoch(train) [4][9100/42151] lr: 3.0000e-05 eta: 12:00:52 time: 0.3626 data_time: 0.1634 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 01:59:07 - mmengine - INFO - Epoch(train) [4][9200/42151] lr: 3.0000e-05 eta: 12:00:13 time: 0.3273 data_time: 0.1249 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 01:59:42 - mmengine - INFO - Epoch(train) [4][9300/42151] lr: 3.0000e-05 eta: 11:59:34 time: 0.3013 data_time: 0.0763 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 02:00:19 - mmengine - INFO - Epoch(train) [4][9400/42151] lr: 3.0000e-05 eta: 11:58:57 time: 0.3571 data_time: 0.1281 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 02:00:54 - mmengine - INFO - Epoch(train) [4][9500/42151] lr: 3.0000e-05 eta: 11:58:19 time: 0.3857 data_time: 0.1582 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 02:01:11 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:01:29 - mmengine - INFO - Epoch(train) [4][9600/42151] lr: 3.0000e-05 eta: 11:57:41 time: 0.3589 data_time: 0.1590 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 02:02:04 - mmengine - INFO - Epoch(train) [4][9700/42151] lr: 3.0000e-05 eta: 11:57:02 time: 0.3531 data_time: 0.1471 memory: 7851 loss_ce: 0.0182 loss: 0.0182 2022/09/17 02:02:38 - mmengine - INFO - Epoch(train) [4][9800/42151] lr: 3.0000e-05 eta: 11:56:23 time: 0.3523 data_time: 0.1421 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 02:03:13 - mmengine - INFO - Epoch(train) [4][9900/42151] lr: 3.0000e-05 eta: 11:55:44 time: 0.3215 data_time: 0.0845 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 02:03:48 - mmengine - INFO - Epoch(train) [4][10000/42151] lr: 3.0000e-05 eta: 11:55:06 time: 0.3787 data_time: 0.1461 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 02:04:23 - mmengine - INFO - Epoch(train) [4][10100/42151] lr: 3.0000e-05 eta: 11:54:27 time: 0.3525 data_time: 0.1513 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 02:04:57 - mmengine - INFO - Epoch(train) [4][10200/42151] lr: 3.0000e-05 eta: 11:53:48 time: 0.3327 data_time: 0.1272 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 02:05:32 - mmengine - INFO - Epoch(train) [4][10300/42151] lr: 3.0000e-05 eta: 11:53:09 time: 0.3417 data_time: 0.1159 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 02:06:07 - mmengine - INFO - Epoch(train) [4][10400/42151] lr: 3.0000e-05 eta: 11:52:31 time: 0.3574 data_time: 0.0928 memory: 7851 loss_ce: 0.0186 loss: 0.0186 2022/09/17 02:06:41 - mmengine - INFO - Epoch(train) [4][10500/42151] lr: 3.0000e-05 eta: 11:51:52 time: 0.3092 data_time: 0.1059 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 02:06:58 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:07:16 - mmengine - INFO - Epoch(train) [4][10600/42151] lr: 3.0000e-05 eta: 11:51:13 time: 0.3595 data_time: 0.1595 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 02:07:51 - mmengine - INFO - Epoch(train) [4][10700/42151] lr: 3.0000e-05 eta: 11:50:35 time: 0.3471 data_time: 0.1226 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 02:08:27 - mmengine - INFO - Epoch(train) [4][10800/42151] lr: 3.0000e-05 eta: 11:49:57 time: 0.3838 data_time: 0.1350 memory: 7851 loss_ce: 0.0184 loss: 0.0184 2022/09/17 02:09:01 - mmengine - INFO - Epoch(train) [4][10900/42151] lr: 3.0000e-05 eta: 11:49:18 time: 0.3255 data_time: 0.1003 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 02:09:36 - mmengine - INFO - Epoch(train) [4][11000/42151] lr: 3.0000e-05 eta: 11:48:40 time: 0.3487 data_time: 0.1402 memory: 7851 loss_ce: 0.0184 loss: 0.0184 2022/09/17 02:10:11 - mmengine - INFO - Epoch(train) [4][11100/42151] lr: 3.0000e-05 eta: 11:48:01 time: 0.3062 data_time: 0.0804 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 02:10:46 - mmengine - INFO - Epoch(train) [4][11200/42151] lr: 3.0000e-05 eta: 11:47:23 time: 0.3905 data_time: 0.1532 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 02:11:21 - mmengine - INFO - Epoch(train) [4][11300/42151] lr: 3.0000e-05 eta: 11:46:45 time: 0.3874 data_time: 0.1603 memory: 7851 loss_ce: 0.0190 loss: 0.0190 2022/09/17 02:11:56 - mmengine - INFO - Epoch(train) [4][11400/42151] lr: 3.0000e-05 eta: 11:46:06 time: 0.3848 data_time: 0.1820 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 02:12:30 - mmengine - INFO - Epoch(train) [4][11500/42151] lr: 3.0000e-05 eta: 11:45:27 time: 0.3522 data_time: 0.1481 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 02:12:47 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:13:05 - mmengine - INFO - Epoch(train) [4][11600/42151] lr: 3.0000e-05 eta: 11:44:48 time: 0.3524 data_time: 0.1460 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 02:13:40 - mmengine - INFO - Epoch(train) [4][11700/42151] lr: 3.0000e-05 eta: 11:44:10 time: 0.3723 data_time: 0.1434 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 02:14:16 - mmengine - INFO - Epoch(train) [4][11800/42151] lr: 3.0000e-05 eta: 11:43:33 time: 0.4019 data_time: 0.1844 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 02:14:51 - mmengine - INFO - Epoch(train) [4][11900/42151] lr: 3.0000e-05 eta: 11:42:54 time: 0.3665 data_time: 0.1608 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 02:15:26 - mmengine - INFO - Epoch(train) [4][12000/42151] lr: 3.0000e-05 eta: 11:42:16 time: 0.3545 data_time: 0.1494 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 02:16:00 - mmengine - INFO - Epoch(train) [4][12100/42151] lr: 3.0000e-05 eta: 11:41:36 time: 0.3434 data_time: 0.1391 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 02:16:35 - mmengine - INFO - Epoch(train) [4][12200/42151] lr: 3.0000e-05 eta: 11:40:58 time: 0.3363 data_time: 0.1318 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 02:17:10 - mmengine - INFO - Epoch(train) [4][12300/42151] lr: 3.0000e-05 eta: 11:40:20 time: 0.3177 data_time: 0.1124 memory: 7851 loss_ce: 0.0193 loss: 0.0193 2022/09/17 02:17:44 - mmengine - INFO - Epoch(train) [4][12400/42151] lr: 3.0000e-05 eta: 11:39:41 time: 0.3408 data_time: 0.1378 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 02:18:18 - mmengine - INFO - Epoch(train) [4][12500/42151] lr: 3.0000e-05 eta: 11:39:02 time: 0.3750 data_time: 0.1422 memory: 7851 loss_ce: 0.0197 loss: 0.0197 2022/09/17 02:18:35 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:18:54 - mmengine - INFO - Epoch(train) [4][12600/42151] lr: 3.0000e-05 eta: 11:38:24 time: 0.3614 data_time: 0.1561 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 02:19:28 - mmengine - INFO - Epoch(train) [4][12700/42151] lr: 3.0000e-05 eta: 11:37:45 time: 0.3437 data_time: 0.1340 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 02:20:03 - mmengine - INFO - Epoch(train) [4][12800/42151] lr: 3.0000e-05 eta: 11:37:06 time: 0.3269 data_time: 0.1233 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 02:20:37 - mmengine - INFO - Epoch(train) [4][12900/42151] lr: 3.0000e-05 eta: 11:36:27 time: 0.3089 data_time: 0.1044 memory: 7851 loss_ce: 0.0180 loss: 0.0180 2022/09/17 02:21:12 - mmengine - INFO - Epoch(train) [4][13000/42151] lr: 3.0000e-05 eta: 11:35:49 time: 0.3588 data_time: 0.1506 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 02:21:46 - mmengine - INFO - Epoch(train) [4][13100/42151] lr: 3.0000e-05 eta: 11:35:11 time: 0.3458 data_time: 0.1413 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 02:22:20 - mmengine - INFO - Epoch(train) [4][13200/42151] lr: 3.0000e-05 eta: 11:34:31 time: 0.3757 data_time: 0.1731 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 02:22:54 - mmengine - INFO - Epoch(train) [4][13300/42151] lr: 3.0000e-05 eta: 11:33:52 time: 0.3196 data_time: 0.1158 memory: 7851 loss_ce: 0.0180 loss: 0.0180 2022/09/17 02:23:28 - mmengine - INFO - Epoch(train) [4][13400/42151] lr: 3.0000e-05 eta: 11:33:13 time: 0.3352 data_time: 0.1303 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 02:24:03 - mmengine - INFO - Epoch(train) [4][13500/42151] lr: 3.0000e-05 eta: 11:32:34 time: 0.3324 data_time: 0.1245 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 02:24:20 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:24:38 - mmengine - INFO - Epoch(train) [4][13600/42151] lr: 3.0000e-05 eta: 11:31:56 time: 0.3629 data_time: 0.1334 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 02:25:12 - mmengine - INFO - Epoch(train) [4][13700/42151] lr: 3.0000e-05 eta: 11:31:17 time: 0.3724 data_time: 0.1458 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 02:25:45 - mmengine - INFO - Epoch(train) [4][13800/42151] lr: 3.0000e-05 eta: 11:30:38 time: 0.3649 data_time: 0.1398 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 02:26:19 - mmengine - INFO - Epoch(train) [4][13900/42151] lr: 3.0000e-05 eta: 11:29:59 time: 0.3425 data_time: 0.1298 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 02:26:54 - mmengine - INFO - Epoch(train) [4][14000/42151] lr: 3.0000e-05 eta: 11:29:20 time: 0.3334 data_time: 0.1275 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 02:27:29 - mmengine - INFO - Epoch(train) [4][14100/42151] lr: 3.0000e-05 eta: 11:28:42 time: 0.3663 data_time: 0.1276 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 02:28:03 - mmengine - INFO - Epoch(train) [4][14200/42151] lr: 3.0000e-05 eta: 11:28:03 time: 0.3673 data_time: 0.1665 memory: 7851 loss_ce: 0.0182 loss: 0.0182 2022/09/17 02:28:38 - mmengine - INFO - Epoch(train) [4][14300/42151] lr: 3.0000e-05 eta: 11:27:25 time: 0.4132 data_time: 0.1779 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 02:29:12 - mmengine - INFO - Epoch(train) [4][14400/42151] lr: 3.0000e-05 eta: 11:26:46 time: 0.3625 data_time: 0.1614 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 02:29:46 - mmengine - INFO - Epoch(train) [4][14500/42151] lr: 3.0000e-05 eta: 11:26:07 time: 0.3400 data_time: 0.1110 memory: 7851 loss_ce: 0.0187 loss: 0.0187 2022/09/17 02:30:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:30:20 - mmengine - INFO - Epoch(train) [4][14600/42151] lr: 3.0000e-05 eta: 11:25:28 time: 0.3341 data_time: 0.1279 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 02:30:55 - mmengine - INFO - Epoch(train) [4][14700/42151] lr: 3.0000e-05 eta: 11:24:49 time: 0.3293 data_time: 0.1289 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 02:31:30 - mmengine - INFO - Epoch(train) [4][14800/42151] lr: 3.0000e-05 eta: 11:24:11 time: 0.3696 data_time: 0.1424 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 02:32:04 - mmengine - INFO - Epoch(train) [4][14900/42151] lr: 3.0000e-05 eta: 11:23:33 time: 0.3621 data_time: 0.1403 memory: 7851 loss_ce: 0.0192 loss: 0.0192 2022/09/17 02:32:39 - mmengine - INFO - Epoch(train) [4][15000/42151] lr: 3.0000e-05 eta: 11:22:54 time: 0.3547 data_time: 0.1180 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 02:33:14 - mmengine - INFO - Epoch(train) [4][15100/42151] lr: 3.0000e-05 eta: 11:22:16 time: 0.3426 data_time: 0.1385 memory: 7851 loss_ce: 0.0186 loss: 0.0186 2022/09/17 02:33:48 - mmengine - INFO - Epoch(train) [4][15200/42151] lr: 3.0000e-05 eta: 11:21:37 time: 0.3318 data_time: 0.0845 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 02:34:23 - mmengine - INFO - Epoch(train) [4][15300/42151] lr: 3.0000e-05 eta: 11:20:59 time: 0.3200 data_time: 0.1157 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 02:34:57 - mmengine - INFO - Epoch(train) [4][15400/42151] lr: 3.0000e-05 eta: 11:20:20 time: 0.3594 data_time: 0.1218 memory: 7851 loss_ce: 0.0183 loss: 0.0183 2022/09/17 02:35:32 - mmengine - INFO - Epoch(train) [4][15500/42151] lr: 3.0000e-05 eta: 11:19:42 time: 0.3676 data_time: 0.1623 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 02:35:49 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:36:06 - mmengine - INFO - Epoch(train) [4][15600/42151] lr: 3.0000e-05 eta: 11:19:03 time: 0.3324 data_time: 0.1304 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 02:36:40 - mmengine - INFO - Epoch(train) [4][15700/42151] lr: 3.0000e-05 eta: 11:18:24 time: 0.3391 data_time: 0.1346 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 02:37:14 - mmengine - INFO - Epoch(train) [4][15800/42151] lr: 3.0000e-05 eta: 11:17:45 time: 0.3286 data_time: 0.0817 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 02:37:48 - mmengine - INFO - Epoch(train) [4][15900/42151] lr: 3.0000e-05 eta: 11:17:06 time: 0.3094 data_time: 0.1033 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 02:38:22 - mmengine - INFO - Epoch(train) [4][16000/42151] lr: 3.0000e-05 eta: 11:16:27 time: 0.3338 data_time: 0.1333 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 02:38:57 - mmengine - INFO - Epoch(train) [4][16100/42151] lr: 3.0000e-05 eta: 11:15:49 time: 0.3565 data_time: 0.1353 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 02:39:31 - mmengine - INFO - Epoch(train) [4][16200/42151] lr: 3.0000e-05 eta: 11:15:10 time: 0.3883 data_time: 0.1449 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 02:40:04 - mmengine - INFO - Epoch(train) [4][16300/42151] lr: 3.0000e-05 eta: 11:14:30 time: 0.3244 data_time: 0.0885 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 02:40:39 - mmengine - INFO - Epoch(train) [4][16400/42151] lr: 3.0000e-05 eta: 11:13:52 time: 0.3545 data_time: 0.1507 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 02:41:13 - mmengine - INFO - Epoch(train) [4][16500/42151] lr: 3.0000e-05 eta: 11:13:13 time: 0.3138 data_time: 0.0836 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 02:41:30 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:41:48 - mmengine - INFO - Epoch(train) [4][16600/42151] lr: 3.0000e-05 eta: 11:12:35 time: 0.3601 data_time: 0.1304 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 02:42:22 - mmengine - INFO - Epoch(train) [4][16700/42151] lr: 3.0000e-05 eta: 11:11:57 time: 0.3883 data_time: 0.1547 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 02:42:57 - mmengine - INFO - Epoch(train) [4][16800/42151] lr: 3.0000e-05 eta: 11:11:18 time: 0.3821 data_time: 0.1793 memory: 7851 loss_ce: 0.0180 loss: 0.0180 2022/09/17 02:43:31 - mmengine - INFO - Epoch(train) [4][16900/42151] lr: 3.0000e-05 eta: 11:10:40 time: 0.3604 data_time: 0.1493 memory: 7851 loss_ce: 0.0187 loss: 0.0187 2022/09/17 02:44:06 - mmengine - INFO - Epoch(train) [4][17000/42151] lr: 3.0000e-05 eta: 11:10:01 time: 0.3558 data_time: 0.1536 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 02:44:40 - mmengine - INFO - Epoch(train) [4][17100/42151] lr: 3.0000e-05 eta: 11:09:23 time: 0.3423 data_time: 0.1080 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 02:45:15 - mmengine - INFO - Epoch(train) [4][17200/42151] lr: 3.0000e-05 eta: 11:08:44 time: 0.3873 data_time: 0.1841 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 02:45:49 - mmengine - INFO - Epoch(train) [4][17300/42151] lr: 3.0000e-05 eta: 11:08:06 time: 0.3770 data_time: 0.1708 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 02:46:24 - mmengine - INFO - Epoch(train) [4][17400/42151] lr: 3.0000e-05 eta: 11:07:27 time: 0.3475 data_time: 0.1204 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 02:46:57 - mmengine - INFO - Epoch(train) [4][17500/42151] lr: 3.0000e-05 eta: 11:06:48 time: 0.3192 data_time: 0.1135 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 02:47:14 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:47:32 - mmengine - INFO - Epoch(train) [4][17600/42151] lr: 3.0000e-05 eta: 11:06:09 time: 0.3138 data_time: 0.1132 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 02:48:06 - mmengine - INFO - Epoch(train) [4][17700/42151] lr: 3.0000e-05 eta: 11:05:31 time: 0.3354 data_time: 0.1218 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 02:48:41 - mmengine - INFO - Epoch(train) [4][17800/42151] lr: 3.0000e-05 eta: 11:04:53 time: 0.3358 data_time: 0.1281 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 02:49:15 - mmengine - INFO - Epoch(train) [4][17900/42151] lr: 3.0000e-05 eta: 11:04:14 time: 0.3636 data_time: 0.1586 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 02:49:49 - mmengine - INFO - Epoch(train) [4][18000/42151] lr: 3.0000e-05 eta: 11:03:35 time: 0.3432 data_time: 0.1218 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 02:50:21 - mmengine - INFO - Epoch(train) [4][18100/42151] lr: 3.0000e-05 eta: 11:02:55 time: 0.3142 data_time: 0.1113 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 02:50:56 - mmengine - INFO - Epoch(train) [4][18200/42151] lr: 3.0000e-05 eta: 11:02:17 time: 0.3176 data_time: 0.1083 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 02:51:31 - mmengine - INFO - Epoch(train) [4][18300/42151] lr: 3.0000e-05 eta: 11:01:39 time: 0.3049 data_time: 0.1019 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 02:52:05 - mmengine - INFO - Epoch(train) [4][18400/42151] lr: 3.0000e-05 eta: 11:01:01 time: 0.3281 data_time: 0.1274 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 02:52:41 - mmengine - INFO - Epoch(train) [4][18500/42151] lr: 3.0000e-05 eta: 11:00:23 time: 0.3734 data_time: 0.1687 memory: 7851 loss_ce: 0.0181 loss: 0.0181 2022/09/17 02:52:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:53:15 - mmengine - INFO - Epoch(train) [4][18600/42151] lr: 3.0000e-05 eta: 10:59:44 time: 0.3809 data_time: 0.1549 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 02:53:48 - mmengine - INFO - Epoch(train) [4][18700/42151] lr: 3.0000e-05 eta: 10:59:05 time: 0.3319 data_time: 0.1291 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 02:54:23 - mmengine - INFO - Epoch(train) [4][18800/42151] lr: 3.0000e-05 eta: 10:58:27 time: 0.3175 data_time: 0.1096 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 02:54:57 - mmengine - INFO - Epoch(train) [4][18900/42151] lr: 3.0000e-05 eta: 10:57:48 time: 0.3212 data_time: 0.1180 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 02:55:32 - mmengine - INFO - Epoch(train) [4][19000/42151] lr: 3.0000e-05 eta: 10:57:10 time: 0.3447 data_time: 0.1289 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 02:56:06 - mmengine - INFO - Epoch(train) [4][19100/42151] lr: 3.0000e-05 eta: 10:56:32 time: 0.3728 data_time: 0.1692 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 02:56:40 - mmengine - INFO - Epoch(train) [4][19200/42151] lr: 3.0000e-05 eta: 10:55:53 time: 0.3414 data_time: 0.1177 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 02:57:14 - mmengine - INFO - Epoch(train) [4][19300/42151] lr: 3.0000e-05 eta: 10:55:14 time: 0.3263 data_time: 0.1149 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 02:57:48 - mmengine - INFO - Epoch(train) [4][19400/42151] lr: 3.0000e-05 eta: 10:54:35 time: 0.3071 data_time: 0.1038 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 02:58:22 - mmengine - INFO - Epoch(train) [4][19500/42151] lr: 3.0000e-05 eta: 10:53:57 time: 0.3320 data_time: 0.1236 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 02:58:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 02:58:56 - mmengine - INFO - Epoch(train) [4][19600/42151] lr: 3.0000e-05 eta: 10:53:18 time: 0.3302 data_time: 0.1228 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 02:59:31 - mmengine - INFO - Epoch(train) [4][19700/42151] lr: 3.0000e-05 eta: 10:52:40 time: 0.3379 data_time: 0.1128 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:00:06 - mmengine - INFO - Epoch(train) [4][19800/42151] lr: 3.0000e-05 eta: 10:52:02 time: 0.3601 data_time: 0.1614 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:00:40 - mmengine - INFO - Epoch(train) [4][19900/42151] lr: 3.0000e-05 eta: 10:51:23 time: 0.3448 data_time: 0.1413 memory: 7851 loss_ce: 0.0190 loss: 0.0190 2022/09/17 03:01:14 - mmengine - INFO - Epoch(train) [4][20000/42151] lr: 3.0000e-05 eta: 10:50:45 time: 0.3455 data_time: 0.1167 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 03:01:49 - mmengine - INFO - Epoch(train) [4][20100/42151] lr: 3.0000e-05 eta: 10:50:07 time: 0.3221 data_time: 0.1191 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:02:23 - mmengine - INFO - Epoch(train) [4][20200/42151] lr: 3.0000e-05 eta: 10:49:28 time: 0.3411 data_time: 0.1361 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 03:02:58 - mmengine - INFO - Epoch(train) [4][20300/42151] lr: 3.0000e-05 eta: 10:48:50 time: 0.3345 data_time: 0.1307 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 03:03:33 - mmengine - INFO - Epoch(train) [4][20400/42151] lr: 3.0000e-05 eta: 10:48:12 time: 0.3474 data_time: 0.1172 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 03:04:08 - mmengine - INFO - Epoch(train) [4][20500/42151] lr: 3.0000e-05 eta: 10:47:34 time: 0.3156 data_time: 0.1150 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 03:04:24 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:04:43 - mmengine - INFO - Epoch(train) [4][20600/42151] lr: 3.0000e-05 eta: 10:46:56 time: 0.3630 data_time: 0.1266 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 03:05:17 - mmengine - INFO - Epoch(train) [4][20700/42151] lr: 3.0000e-05 eta: 10:46:18 time: 0.3245 data_time: 0.1176 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 03:05:51 - mmengine - INFO - Epoch(train) [4][20800/42151] lr: 3.0000e-05 eta: 10:45:39 time: 0.3247 data_time: 0.1249 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:06:26 - mmengine - INFO - Epoch(train) [4][20900/42151] lr: 3.0000e-05 eta: 10:45:01 time: 0.3635 data_time: 0.1395 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 03:07:00 - mmengine - INFO - Epoch(train) [4][21000/42151] lr: 3.0000e-05 eta: 10:44:23 time: 0.3337 data_time: 0.1073 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 03:07:34 - mmengine - INFO - Epoch(train) [4][21100/42151] lr: 3.0000e-05 eta: 10:43:44 time: 0.3400 data_time: 0.1395 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 03:08:08 - mmengine - INFO - Epoch(train) [4][21200/42151] lr: 3.0000e-05 eta: 10:43:05 time: 0.3202 data_time: 0.1201 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 03:08:42 - mmengine - INFO - Epoch(train) [4][21300/42151] lr: 3.0000e-05 eta: 10:42:27 time: 0.3333 data_time: 0.1260 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 03:09:17 - mmengine - INFO - Epoch(train) [4][21400/42151] lr: 3.0000e-05 eta: 10:41:49 time: 0.3463 data_time: 0.1400 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:09:51 - mmengine - INFO - Epoch(train) [4][21500/42151] lr: 3.0000e-05 eta: 10:41:11 time: 0.3698 data_time: 0.1710 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 03:10:08 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:10:26 - mmengine - INFO - Epoch(train) [4][21600/42151] lr: 3.0000e-05 eta: 10:40:33 time: 0.3504 data_time: 0.1456 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:10:59 - mmengine - INFO - Epoch(train) [4][21700/42151] lr: 3.0000e-05 eta: 10:39:54 time: 0.3260 data_time: 0.0943 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 03:11:34 - mmengine - INFO - Epoch(train) [4][21800/42151] lr: 3.0000e-05 eta: 10:39:15 time: 0.3372 data_time: 0.1196 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 03:12:08 - mmengine - INFO - Epoch(train) [4][21900/42151] lr: 3.0000e-05 eta: 10:38:37 time: 0.3119 data_time: 0.0913 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 03:12:41 - mmengine - INFO - Epoch(train) [4][22000/42151] lr: 3.0000e-05 eta: 10:37:58 time: 0.3329 data_time: 0.1094 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 03:13:16 - mmengine - INFO - Epoch(train) [4][22100/42151] lr: 3.0000e-05 eta: 10:37:20 time: 0.3682 data_time: 0.1676 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 03:13:50 - mmengine - INFO - Epoch(train) [4][22200/42151] lr: 3.0000e-05 eta: 10:36:41 time: 0.3594 data_time: 0.1322 memory: 7851 loss_ce: 0.0180 loss: 0.0180 2022/09/17 03:14:24 - mmengine - INFO - Epoch(train) [4][22300/42151] lr: 3.0000e-05 eta: 10:36:02 time: 0.3358 data_time: 0.0899 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 03:14:58 - mmengine - INFO - Epoch(train) [4][22400/42151] lr: 3.0000e-05 eta: 10:35:24 time: 0.3234 data_time: 0.1239 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 03:15:31 - mmengine - INFO - Epoch(train) [4][22500/42151] lr: 3.0000e-05 eta: 10:34:45 time: 0.3065 data_time: 0.1090 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:15:47 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:16:05 - mmengine - INFO - Epoch(train) [4][22600/42151] lr: 3.0000e-05 eta: 10:34:07 time: 0.3697 data_time: 0.1565 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:16:39 - mmengine - INFO - Epoch(train) [4][22700/42151] lr: 3.0000e-05 eta: 10:33:28 time: 0.3631 data_time: 0.1397 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 03:17:13 - mmengine - INFO - Epoch(train) [4][22800/42151] lr: 3.0000e-05 eta: 10:32:49 time: 0.3572 data_time: 0.1489 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 03:17:46 - mmengine - INFO - Epoch(train) [4][22900/42151] lr: 3.0000e-05 eta: 10:32:10 time: 0.3188 data_time: 0.1176 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 03:18:20 - mmengine - INFO - Epoch(train) [4][23000/42151] lr: 3.0000e-05 eta: 10:31:32 time: 0.3222 data_time: 0.1153 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 03:18:54 - mmengine - INFO - Epoch(train) [4][23100/42151] lr: 3.0000e-05 eta: 10:30:53 time: 0.3387 data_time: 0.1365 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 03:19:29 - mmengine - INFO - Epoch(train) [4][23200/42151] lr: 3.0000e-05 eta: 10:30:15 time: 0.3748 data_time: 0.1180 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 03:20:02 - mmengine - INFO - Epoch(train) [4][23300/42151] lr: 3.0000e-05 eta: 10:29:36 time: 0.3508 data_time: 0.1262 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 03:20:36 - mmengine - INFO - Epoch(train) [4][23400/42151] lr: 3.0000e-05 eta: 10:28:58 time: 0.3417 data_time: 0.1339 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 03:21:11 - mmengine - INFO - Epoch(train) [4][23500/42151] lr: 3.0000e-05 eta: 10:28:20 time: 0.3178 data_time: 0.1172 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 03:21:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:21:46 - mmengine - INFO - Epoch(train) [4][23600/42151] lr: 3.0000e-05 eta: 10:27:42 time: 0.3591 data_time: 0.1245 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 03:22:20 - mmengine - INFO - Epoch(train) [4][23700/42151] lr: 3.0000e-05 eta: 10:27:04 time: 0.3686 data_time: 0.1620 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 03:22:54 - mmengine - INFO - Epoch(train) [4][23800/42151] lr: 3.0000e-05 eta: 10:26:26 time: 0.3481 data_time: 0.1476 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 03:23:29 - mmengine - INFO - Epoch(train) [4][23900/42151] lr: 3.0000e-05 eta: 10:25:48 time: 0.3439 data_time: 0.1403 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 03:24:05 - mmengine - INFO - Epoch(train) [4][24000/42151] lr: 3.0000e-05 eta: 10:25:10 time: 0.3521 data_time: 0.1220 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 03:24:39 - mmengine - INFO - Epoch(train) [4][24100/42151] lr: 3.0000e-05 eta: 10:24:32 time: 0.3231 data_time: 0.1213 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 03:25:13 - mmengine - INFO - Epoch(train) [4][24200/42151] lr: 3.0000e-05 eta: 10:23:54 time: 0.3494 data_time: 0.1186 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 03:25:48 - mmengine - INFO - Epoch(train) [4][24300/42151] lr: 3.0000e-05 eta: 10:23:16 time: 0.3327 data_time: 0.1272 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 03:26:22 - mmengine - INFO - Epoch(train) [4][24400/42151] lr: 3.0000e-05 eta: 10:22:38 time: 0.3492 data_time: 0.1459 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 03:26:57 - mmengine - INFO - Epoch(train) [4][24500/42151] lr: 3.0000e-05 eta: 10:22:00 time: 0.3515 data_time: 0.1283 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 03:27:14 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:27:31 - mmengine - INFO - Epoch(train) [4][24600/42151] lr: 3.0000e-05 eta: 10:21:22 time: 0.3535 data_time: 0.1279 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:28:06 - mmengine - INFO - Epoch(train) [4][24700/42151] lr: 3.0000e-05 eta: 10:20:44 time: 0.3256 data_time: 0.1235 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 03:28:40 - mmengine - INFO - Epoch(train) [4][24800/42151] lr: 3.0000e-05 eta: 10:20:05 time: 0.3170 data_time: 0.1133 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 03:29:15 - mmengine - INFO - Epoch(train) [4][24900/42151] lr: 3.0000e-05 eta: 10:19:28 time: 0.3496 data_time: 0.1449 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 03:29:49 - mmengine - INFO - Epoch(train) [4][25000/42151] lr: 3.0000e-05 eta: 10:18:50 time: 0.3387 data_time: 0.1347 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 03:30:24 - mmengine - INFO - Epoch(train) [4][25100/42151] lr: 3.0000e-05 eta: 10:18:12 time: 0.3607 data_time: 0.1581 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:30:59 - mmengine - INFO - Epoch(train) [4][25200/42151] lr: 3.0000e-05 eta: 10:17:34 time: 0.3493 data_time: 0.1434 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:31:33 - mmengine - INFO - Epoch(train) [4][25300/42151] lr: 3.0000e-05 eta: 10:16:56 time: 0.3341 data_time: 0.0995 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 03:32:07 - mmengine - INFO - Epoch(train) [4][25400/42151] lr: 3.0000e-05 eta: 10:16:18 time: 0.3277 data_time: 0.1248 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:32:43 - mmengine - INFO - Epoch(train) [4][25500/42151] lr: 3.0000e-05 eta: 10:15:40 time: 0.3518 data_time: 0.1277 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 03:32:59 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:33:17 - mmengine - INFO - Epoch(train) [4][25600/42151] lr: 3.0000e-05 eta: 10:15:02 time: 0.3723 data_time: 0.1425 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:33:52 - mmengine - INFO - Epoch(train) [4][25700/42151] lr: 3.0000e-05 eta: 10:14:24 time: 0.3818 data_time: 0.1787 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 03:34:26 - mmengine - INFO - Epoch(train) [4][25800/42151] lr: 3.0000e-05 eta: 10:13:46 time: 0.3899 data_time: 0.1612 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 03:35:00 - mmengine - INFO - Epoch(train) [4][25900/42151] lr: 3.0000e-05 eta: 10:13:07 time: 0.3145 data_time: 0.0878 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 03:35:34 - mmengine - INFO - Epoch(train) [4][26000/42151] lr: 3.0000e-05 eta: 10:12:29 time: 0.3252 data_time: 0.1160 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 03:36:08 - mmengine - INFO - Epoch(train) [4][26100/42151] lr: 3.0000e-05 eta: 10:11:51 time: 0.3060 data_time: 0.1059 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 03:36:43 - mmengine - INFO - Epoch(train) [4][26200/42151] lr: 3.0000e-05 eta: 10:11:13 time: 0.3662 data_time: 0.1595 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 03:37:17 - mmengine - INFO - Epoch(train) [4][26300/42151] lr: 3.0000e-05 eta: 10:10:35 time: 0.4036 data_time: 0.1689 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:37:51 - mmengine - INFO - Epoch(train) [4][26400/42151] lr: 3.0000e-05 eta: 10:09:57 time: 0.3436 data_time: 0.1364 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 03:38:26 - mmengine - INFO - Epoch(train) [4][26500/42151] lr: 3.0000e-05 eta: 10:09:19 time: 0.3289 data_time: 0.1144 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 03:38:42 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:39:00 - mmengine - INFO - Epoch(train) [4][26600/42151] lr: 3.0000e-05 eta: 10:08:41 time: 0.3179 data_time: 0.0914 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 03:39:34 - mmengine - INFO - Epoch(train) [4][26700/42151] lr: 3.0000e-05 eta: 10:08:03 time: 0.3184 data_time: 0.1117 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:40:09 - mmengine - INFO - Epoch(train) [4][26800/42151] lr: 3.0000e-05 eta: 10:07:25 time: 0.3532 data_time: 0.1512 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 03:40:43 - mmengine - INFO - Epoch(train) [4][26900/42151] lr: 3.0000e-05 eta: 10:06:46 time: 0.3320 data_time: 0.1295 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 03:41:17 - mmengine - INFO - Epoch(train) [4][27000/42151] lr: 3.0000e-05 eta: 10:06:09 time: 0.3646 data_time: 0.1566 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 03:41:51 - mmengine - INFO - Epoch(train) [4][27100/42151] lr: 3.0000e-05 eta: 10:05:30 time: 0.3226 data_time: 0.1201 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 03:42:25 - mmengine - INFO - Epoch(train) [4][27200/42151] lr: 3.0000e-05 eta: 10:04:52 time: 0.3600 data_time: 0.1576 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 03:43:00 - mmengine - INFO - Epoch(train) [4][27300/42151] lr: 3.0000e-05 eta: 10:04:15 time: 0.3398 data_time: 0.1337 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 03:43:35 - mmengine - INFO - Epoch(train) [4][27400/42151] lr: 3.0000e-05 eta: 10:03:36 time: 0.3599 data_time: 0.1594 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 03:44:08 - mmengine - INFO - Epoch(train) [4][27500/42151] lr: 3.0000e-05 eta: 10:02:58 time: 0.3418 data_time: 0.1399 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 03:44:24 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:44:42 - mmengine - INFO - Epoch(train) [4][27600/42151] lr: 3.0000e-05 eta: 10:02:20 time: 0.3756 data_time: 0.1751 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 03:45:16 - mmengine - INFO - Epoch(train) [4][27700/42151] lr: 3.0000e-05 eta: 10:01:42 time: 0.3238 data_time: 0.1220 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 03:45:51 - mmengine - INFO - Epoch(train) [4][27800/42151] lr: 3.0000e-05 eta: 10:01:04 time: 0.3535 data_time: 0.1482 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 03:46:26 - mmengine - INFO - Epoch(train) [4][27900/42151] lr: 3.0000e-05 eta: 10:00:26 time: 0.3398 data_time: 0.1281 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 03:47:00 - mmengine - INFO - Epoch(train) [4][28000/42151] lr: 3.0000e-05 eta: 9:59:48 time: 0.3736 data_time: 0.1693 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 03:47:34 - mmengine - INFO - Epoch(train) [4][28100/42151] lr: 3.0000e-05 eta: 9:59:10 time: 0.3513 data_time: 0.1493 memory: 7851 loss_ce: 0.0190 loss: 0.0190 2022/09/17 03:48:09 - mmengine - INFO - Epoch(train) [4][28200/42151] lr: 3.0000e-05 eta: 9:58:32 time: 0.3672 data_time: 0.1637 memory: 7851 loss_ce: 0.0183 loss: 0.0183 2022/09/17 03:48:43 - mmengine - INFO - Epoch(train) [4][28300/42151] lr: 3.0000e-05 eta: 9:57:54 time: 0.3243 data_time: 0.1203 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 03:49:17 - mmengine - INFO - Epoch(train) [4][28400/42151] lr: 3.0000e-05 eta: 9:57:16 time: 0.3547 data_time: 0.1472 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 03:49:51 - mmengine - INFO - Epoch(train) [4][28500/42151] lr: 3.0000e-05 eta: 9:56:38 time: 0.3187 data_time: 0.1164 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 03:50:08 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:50:26 - mmengine - INFO - Epoch(train) [4][28600/42151] lr: 3.0000e-05 eta: 9:56:00 time: 0.3585 data_time: 0.1529 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 03:51:00 - mmengine - INFO - Epoch(train) [4][28700/42151] lr: 3.0000e-05 eta: 9:55:22 time: 0.3435 data_time: 0.1396 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 03:51:34 - mmengine - INFO - Epoch(train) [4][28800/42151] lr: 3.0000e-05 eta: 9:54:44 time: 0.3616 data_time: 0.1547 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 03:52:08 - mmengine - INFO - Epoch(train) [4][28900/42151] lr: 3.0000e-05 eta: 9:54:06 time: 0.3227 data_time: 0.1169 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 03:52:42 - mmengine - INFO - Epoch(train) [4][29000/42151] lr: 3.0000e-05 eta: 9:53:27 time: 0.3391 data_time: 0.1388 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 03:53:16 - mmengine - INFO - Epoch(train) [4][29100/42151] lr: 3.0000e-05 eta: 9:52:49 time: 0.3218 data_time: 0.1143 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 03:53:51 - mmengine - INFO - Epoch(train) [4][29200/42151] lr: 3.0000e-05 eta: 9:52:12 time: 0.3417 data_time: 0.1436 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 03:54:25 - mmengine - INFO - Epoch(train) [4][29300/42151] lr: 3.0000e-05 eta: 9:51:34 time: 0.3354 data_time: 0.1349 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 03:55:00 - mmengine - INFO - Epoch(train) [4][29400/42151] lr: 3.0000e-05 eta: 9:50:56 time: 0.3880 data_time: 0.1877 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 03:55:34 - mmengine - INFO - Epoch(train) [4][29500/42151] lr: 3.0000e-05 eta: 9:50:17 time: 0.3440 data_time: 0.1429 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 03:55:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 03:56:08 - mmengine - INFO - Epoch(train) [4][29600/42151] lr: 3.0000e-05 eta: 9:49:40 time: 0.3916 data_time: 0.1795 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 03:56:43 - mmengine - INFO - Epoch(train) [4][29700/42151] lr: 3.0000e-05 eta: 9:49:02 time: 0.3136 data_time: 0.1115 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 03:57:17 - mmengine - INFO - Epoch(train) [4][29800/42151] lr: 3.0000e-05 eta: 9:48:24 time: 0.3639 data_time: 0.1638 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 03:57:52 - mmengine - INFO - Epoch(train) [4][29900/42151] lr: 3.0000e-05 eta: 9:47:46 time: 0.3351 data_time: 0.1365 memory: 7851 loss_ce: 0.0183 loss: 0.0183 2022/09/17 03:58:27 - mmengine - INFO - Epoch(train) [4][30000/42151] lr: 3.0000e-05 eta: 9:47:09 time: 0.3725 data_time: 0.1563 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 03:59:02 - mmengine - INFO - Epoch(train) [4][30100/42151] lr: 3.0000e-05 eta: 9:46:31 time: 0.3153 data_time: 0.1175 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 03:59:36 - mmengine - INFO - Epoch(train) [4][30200/42151] lr: 3.0000e-05 eta: 9:45:54 time: 0.3818 data_time: 0.1808 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:00:10 - mmengine - INFO - Epoch(train) [4][30300/42151] lr: 3.0000e-05 eta: 9:45:15 time: 0.3487 data_time: 0.1440 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 04:00:45 - mmengine - INFO - Epoch(train) [4][30400/42151] lr: 3.0000e-05 eta: 9:44:38 time: 0.3676 data_time: 0.1683 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:01:20 - mmengine - INFO - Epoch(train) [4][30500/42151] lr: 3.0000e-05 eta: 9:44:00 time: 0.3789 data_time: 0.1585 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 04:01:36 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:01:54 - mmengine - INFO - Epoch(train) [4][30600/42151] lr: 3.0000e-05 eta: 9:43:22 time: 0.3569 data_time: 0.1586 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:02:28 - mmengine - INFO - Epoch(train) [4][30700/42151] lr: 3.0000e-05 eta: 9:42:44 time: 0.3310 data_time: 0.1292 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 04:03:02 - mmengine - INFO - Epoch(train) [4][30800/42151] lr: 3.0000e-05 eta: 9:42:06 time: 0.3633 data_time: 0.1650 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 04:03:36 - mmengine - INFO - Epoch(train) [4][30900/42151] lr: 3.0000e-05 eta: 9:41:28 time: 0.3382 data_time: 0.1330 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 04:04:10 - mmengine - INFO - Epoch(train) [4][31000/42151] lr: 3.0000e-05 eta: 9:40:50 time: 0.3713 data_time: 0.1636 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 04:04:44 - mmengine - INFO - Epoch(train) [4][31100/42151] lr: 3.0000e-05 eta: 9:40:12 time: 0.3323 data_time: 0.1354 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 04:05:19 - mmengine - INFO - Epoch(train) [4][31200/42151] lr: 3.0000e-05 eta: 9:39:34 time: 0.3753 data_time: 0.1528 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 04:05:52 - mmengine - INFO - Epoch(train) [4][31300/42151] lr: 3.0000e-05 eta: 9:38:56 time: 0.3208 data_time: 0.1218 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 04:06:27 - mmengine - INFO - Epoch(train) [4][31400/42151] lr: 3.0000e-05 eta: 9:38:18 time: 0.3739 data_time: 0.1713 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:07:00 - mmengine - INFO - Epoch(train) [4][31500/42151] lr: 3.0000e-05 eta: 9:37:40 time: 0.3199 data_time: 0.1146 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 04:07:17 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:07:35 - mmengine - INFO - Epoch(train) [4][31600/42151] lr: 3.0000e-05 eta: 9:37:02 time: 0.3502 data_time: 0.1506 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 04:08:09 - mmengine - INFO - Epoch(train) [4][31700/42151] lr: 3.0000e-05 eta: 9:36:25 time: 0.3714 data_time: 0.1679 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 04:08:43 - mmengine - INFO - Epoch(train) [4][31800/42151] lr: 3.0000e-05 eta: 9:35:46 time: 0.3690 data_time: 0.1683 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 04:09:18 - mmengine - INFO - Epoch(train) [4][31900/42151] lr: 3.0000e-05 eta: 9:35:09 time: 0.3293 data_time: 0.1210 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:09:52 - mmengine - INFO - Epoch(train) [4][32000/42151] lr: 3.0000e-05 eta: 9:34:31 time: 0.3458 data_time: 0.1461 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 04:10:26 - mmengine - INFO - Epoch(train) [4][32100/42151] lr: 3.0000e-05 eta: 9:33:53 time: 0.3638 data_time: 0.1324 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 04:11:00 - mmengine - INFO - Epoch(train) [4][32200/42151] lr: 3.0000e-05 eta: 9:33:15 time: 0.3670 data_time: 0.1512 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 04:11:32 - mmengine - INFO - Epoch(train) [4][32300/42151] lr: 3.0000e-05 eta: 9:32:36 time: 0.3473 data_time: 0.1220 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 04:12:05 - mmengine - INFO - Epoch(train) [4][32400/42151] lr: 3.0000e-05 eta: 9:31:57 time: 0.3328 data_time: 0.1326 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 04:12:39 - mmengine - INFO - Epoch(train) [4][32500/42151] lr: 3.0000e-05 eta: 9:31:19 time: 0.3231 data_time: 0.0867 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 04:12:55 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:13:13 - mmengine - INFO - Epoch(train) [4][32600/42151] lr: 3.0000e-05 eta: 9:30:41 time: 0.3481 data_time: 0.1509 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 04:13:47 - mmengine - INFO - Epoch(train) [4][32700/42151] lr: 3.0000e-05 eta: 9:30:03 time: 0.3843 data_time: 0.1628 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 04:14:21 - mmengine - INFO - Epoch(train) [4][32800/42151] lr: 3.0000e-05 eta: 9:29:25 time: 0.3322 data_time: 0.1025 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:14:55 - mmengine - INFO - Epoch(train) [4][32900/42151] lr: 3.0000e-05 eta: 9:28:47 time: 0.3946 data_time: 0.1956 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 04:15:29 - mmengine - INFO - Epoch(train) [4][33000/42151] lr: 3.0000e-05 eta: 9:28:09 time: 0.3157 data_time: 0.0874 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 04:16:03 - mmengine - INFO - Epoch(train) [4][33100/42151] lr: 3.0000e-05 eta: 9:27:31 time: 0.3247 data_time: 0.1261 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 04:16:37 - mmengine - INFO - Epoch(train) [4][33200/42151] lr: 3.0000e-05 eta: 9:26:53 time: 0.3282 data_time: 0.1262 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 04:17:12 - mmengine - INFO - Epoch(train) [4][33300/42151] lr: 3.0000e-05 eta: 9:26:16 time: 0.3885 data_time: 0.1920 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:17:46 - mmengine - INFO - Epoch(train) [4][33400/42151] lr: 3.0000e-05 eta: 9:25:38 time: 0.3316 data_time: 0.1275 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 04:18:21 - mmengine - INFO - Epoch(train) [4][33500/42151] lr: 3.0000e-05 eta: 9:25:01 time: 0.3563 data_time: 0.1562 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:18:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:18:55 - mmengine - INFO - Epoch(train) [4][33600/42151] lr: 3.0000e-05 eta: 9:24:23 time: 0.3149 data_time: 0.1121 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 04:19:29 - mmengine - INFO - Epoch(train) [4][33700/42151] lr: 3.0000e-05 eta: 9:23:45 time: 0.3236 data_time: 0.1002 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 04:20:03 - mmengine - INFO - Epoch(train) [4][33800/42151] lr: 3.0000e-05 eta: 9:23:07 time: 0.3313 data_time: 0.1282 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:20:37 - mmengine - INFO - Epoch(train) [4][33900/42151] lr: 3.0000e-05 eta: 9:22:29 time: 0.3495 data_time: 0.1277 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 04:21:11 - mmengine - INFO - Epoch(train) [4][34000/42151] lr: 3.0000e-05 eta: 9:21:51 time: 0.3376 data_time: 0.1079 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:21:45 - mmengine - INFO - Epoch(train) [4][34100/42151] lr: 3.0000e-05 eta: 9:21:13 time: 0.3378 data_time: 0.1152 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 04:22:20 - mmengine - INFO - Epoch(train) [4][34200/42151] lr: 3.0000e-05 eta: 9:20:36 time: 0.3562 data_time: 0.1179 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 04:22:55 - mmengine - INFO - Epoch(train) [4][34300/42151] lr: 3.0000e-05 eta: 9:19:59 time: 0.3401 data_time: 0.1126 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 04:23:30 - mmengine - INFO - Epoch(train) [4][34400/42151] lr: 3.0000e-05 eta: 9:19:21 time: 0.3614 data_time: 0.1276 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:24:05 - mmengine - INFO - Epoch(train) [4][34500/42151] lr: 3.0000e-05 eta: 9:18:44 time: 0.3723 data_time: 0.1365 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 04:24:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:24:40 - mmengine - INFO - Epoch(train) [4][34600/42151] lr: 3.0000e-05 eta: 9:18:07 time: 0.3763 data_time: 0.1463 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:25:15 - mmengine - INFO - Epoch(train) [4][34700/42151] lr: 3.0000e-05 eta: 9:17:29 time: 0.3511 data_time: 0.1187 memory: 7851 loss_ce: 0.0185 loss: 0.0185 2022/09/17 04:25:50 - mmengine - INFO - Epoch(train) [4][34800/42151] lr: 3.0000e-05 eta: 9:16:52 time: 0.3531 data_time: 0.1164 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 04:26:25 - mmengine - INFO - Epoch(train) [4][34900/42151] lr: 3.0000e-05 eta: 9:16:15 time: 0.3213 data_time: 0.0985 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 04:26:59 - mmengine - INFO - Epoch(train) [4][35000/42151] lr: 3.0000e-05 eta: 9:15:37 time: 0.3520 data_time: 0.1194 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:27:33 - mmengine - INFO - Epoch(train) [4][35100/42151] lr: 3.0000e-05 eta: 9:14:59 time: 0.3364 data_time: 0.1153 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 04:28:08 - mmengine - INFO - Epoch(train) [4][35200/42151] lr: 3.0000e-05 eta: 9:14:21 time: 0.3677 data_time: 0.1169 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:28:42 - mmengine - INFO - Epoch(train) [4][35300/42151] lr: 3.0000e-05 eta: 9:13:44 time: 0.3605 data_time: 0.1107 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 04:29:17 - mmengine - INFO - Epoch(train) [4][35400/42151] lr: 3.0000e-05 eta: 9:13:06 time: 0.3371 data_time: 0.1148 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 04:29:51 - mmengine - INFO - Epoch(train) [4][35500/42151] lr: 3.0000e-05 eta: 9:12:28 time: 0.3153 data_time: 0.0927 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:30:07 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:30:25 - mmengine - INFO - Epoch(train) [4][35600/42151] lr: 3.0000e-05 eta: 9:11:51 time: 0.3380 data_time: 0.1052 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 04:30:59 - mmengine - INFO - Epoch(train) [4][35700/42151] lr: 3.0000e-05 eta: 9:11:13 time: 0.3420 data_time: 0.1173 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:31:33 - mmengine - INFO - Epoch(train) [4][35800/42151] lr: 3.0000e-05 eta: 9:10:35 time: 0.3457 data_time: 0.1117 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 04:32:07 - mmengine - INFO - Epoch(train) [4][35900/42151] lr: 3.0000e-05 eta: 9:09:57 time: 0.3404 data_time: 0.1143 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 04:32:41 - mmengine - INFO - Epoch(train) [4][36000/42151] lr: 3.0000e-05 eta: 9:09:20 time: 0.3589 data_time: 0.1162 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 04:33:16 - mmengine - INFO - Epoch(train) [4][36100/42151] lr: 3.0000e-05 eta: 9:08:42 time: 0.3270 data_time: 0.0998 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 04:33:50 - mmengine - INFO - Epoch(train) [4][36200/42151] lr: 3.0000e-05 eta: 9:08:04 time: 0.3400 data_time: 0.1004 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 04:34:24 - mmengine - INFO - Epoch(train) [4][36300/42151] lr: 3.0000e-05 eta: 9:07:27 time: 0.3394 data_time: 0.1135 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:34:58 - mmengine - INFO - Epoch(train) [4][36400/42151] lr: 3.0000e-05 eta: 9:06:48 time: 0.3386 data_time: 0.1065 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 04:35:32 - mmengine - INFO - Epoch(train) [4][36500/42151] lr: 3.0000e-05 eta: 9:06:11 time: 0.3645 data_time: 0.1178 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 04:35:48 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:36:06 - mmengine - INFO - Epoch(train) [4][36600/42151] lr: 3.0000e-05 eta: 9:05:33 time: 0.3207 data_time: 0.0989 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 04:36:40 - mmengine - INFO - Epoch(train) [4][36700/42151] lr: 3.0000e-05 eta: 9:04:55 time: 0.3270 data_time: 0.1028 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 04:37:14 - mmengine - INFO - Epoch(train) [4][36800/42151] lr: 3.0000e-05 eta: 9:04:17 time: 0.3511 data_time: 0.1252 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 04:37:48 - mmengine - INFO - Epoch(train) [4][36900/42151] lr: 3.0000e-05 eta: 9:03:40 time: 0.3451 data_time: 0.1098 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 04:38:23 - mmengine - INFO - Epoch(train) [4][37000/42151] lr: 3.0000e-05 eta: 9:03:02 time: 0.3552 data_time: 0.1176 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 04:38:56 - mmengine - INFO - Epoch(train) [4][37100/42151] lr: 3.0000e-05 eta: 9:02:24 time: 0.3565 data_time: 0.1285 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 04:39:30 - mmengine - INFO - Epoch(train) [4][37200/42151] lr: 3.0000e-05 eta: 9:01:46 time: 0.3283 data_time: 0.1015 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 04:40:05 - mmengine - INFO - Epoch(train) [4][37300/42151] lr: 3.0000e-05 eta: 9:01:09 time: 0.3223 data_time: 0.0999 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 04:40:38 - mmengine - INFO - Epoch(train) [4][37400/42151] lr: 3.0000e-05 eta: 9:00:31 time: 0.3414 data_time: 0.1175 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 04:41:13 - mmengine - INFO - Epoch(train) [4][37500/42151] lr: 3.0000e-05 eta: 8:59:54 time: 0.3652 data_time: 0.1104 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 04:41:29 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:41:47 - mmengine - INFO - Epoch(train) [4][37600/42151] lr: 3.0000e-05 eta: 8:59:16 time: 0.3562 data_time: 0.1368 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:42:21 - mmengine - INFO - Epoch(train) [4][37700/42151] lr: 3.0000e-05 eta: 8:58:38 time: 0.3424 data_time: 0.1092 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 04:42:56 - mmengine - INFO - Epoch(train) [4][37800/42151] lr: 3.0000e-05 eta: 8:58:01 time: 0.3294 data_time: 0.1080 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 04:43:30 - mmengine - INFO - Epoch(train) [4][37900/42151] lr: 3.0000e-05 eta: 8:57:23 time: 0.3152 data_time: 0.0914 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:44:05 - mmengine - INFO - Epoch(train) [4][38000/42151] lr: 3.0000e-05 eta: 8:56:46 time: 0.3346 data_time: 0.1035 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 04:44:40 - mmengine - INFO - Epoch(train) [4][38100/42151] lr: 3.0000e-05 eta: 8:56:09 time: 0.3525 data_time: 0.1175 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 04:45:14 - mmengine - INFO - Epoch(train) [4][38200/42151] lr: 3.0000e-05 eta: 8:55:31 time: 0.3621 data_time: 0.1193 memory: 7851 loss_ce: 0.0177 loss: 0.0177 2022/09/17 04:45:48 - mmengine - INFO - Epoch(train) [4][38300/42151] lr: 3.0000e-05 eta: 8:54:53 time: 0.3440 data_time: 0.1161 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 04:46:23 - mmengine - INFO - Epoch(train) [4][38400/42151] lr: 3.0000e-05 eta: 8:54:16 time: 0.3515 data_time: 0.1079 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 04:46:58 - mmengine - INFO - Epoch(train) [4][38500/42151] lr: 3.0000e-05 eta: 8:53:39 time: 0.3228 data_time: 0.0986 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:47:14 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:47:33 - mmengine - INFO - Epoch(train) [4][38600/42151] lr: 3.0000e-05 eta: 8:53:01 time: 0.3264 data_time: 0.0969 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 04:48:08 - mmengine - INFO - Epoch(train) [4][38700/42151] lr: 3.0000e-05 eta: 8:52:24 time: 0.3418 data_time: 0.1176 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 04:48:42 - mmengine - INFO - Epoch(train) [4][38800/42151] lr: 3.0000e-05 eta: 8:51:47 time: 0.3704 data_time: 0.1183 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 04:49:17 - mmengine - INFO - Epoch(train) [4][38900/42151] lr: 3.0000e-05 eta: 8:51:10 time: 0.3733 data_time: 0.1425 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 04:49:52 - mmengine - INFO - Epoch(train) [4][39000/42151] lr: 3.0000e-05 eta: 8:50:32 time: 0.3377 data_time: 0.1015 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 04:50:27 - mmengine - INFO - Epoch(train) [4][39100/42151] lr: 3.0000e-05 eta: 8:49:55 time: 0.3284 data_time: 0.1049 memory: 7851 loss_ce: 0.0177 loss: 0.0177 2022/09/17 04:51:01 - mmengine - INFO - Epoch(train) [4][39200/42151] lr: 3.0000e-05 eta: 8:49:18 time: 0.3274 data_time: 0.1011 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:51:35 - mmengine - INFO - Epoch(train) [4][39300/42151] lr: 3.0000e-05 eta: 8:48:40 time: 0.3362 data_time: 0.1154 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 04:52:10 - mmengine - INFO - Epoch(train) [4][39400/42151] lr: 3.0000e-05 eta: 8:48:03 time: 0.3377 data_time: 0.1105 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:52:45 - mmengine - INFO - Epoch(train) [4][39500/42151] lr: 3.0000e-05 eta: 8:47:26 time: 0.3419 data_time: 0.1194 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 04:53:02 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:53:20 - mmengine - INFO - Epoch(train) [4][39600/42151] lr: 3.0000e-05 eta: 8:46:48 time: 0.3329 data_time: 0.1038 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 04:53:55 - mmengine - INFO - Epoch(train) [4][39700/42151] lr: 3.0000e-05 eta: 8:46:11 time: 0.3483 data_time: 0.1191 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:54:29 - mmengine - INFO - Epoch(train) [4][39800/42151] lr: 3.0000e-05 eta: 8:45:34 time: 0.3296 data_time: 0.1014 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 04:55:04 - mmengine - INFO - Epoch(train) [4][39900/42151] lr: 3.0000e-05 eta: 8:44:57 time: 0.3789 data_time: 0.1382 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 04:55:39 - mmengine - INFO - Epoch(train) [4][40000/42151] lr: 3.0000e-05 eta: 8:44:19 time: 0.3392 data_time: 0.1104 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:56:14 - mmengine - INFO - Epoch(train) [4][40100/42151] lr: 3.0000e-05 eta: 8:43:42 time: 0.3526 data_time: 0.1237 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 04:56:48 - mmengine - INFO - Epoch(train) [4][40200/42151] lr: 3.0000e-05 eta: 8:43:05 time: 0.3325 data_time: 0.1079 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 04:57:23 - mmengine - INFO - Epoch(train) [4][40300/42151] lr: 3.0000e-05 eta: 8:42:27 time: 0.3312 data_time: 0.1073 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 04:57:58 - mmengine - INFO - Epoch(train) [4][40400/42151] lr: 3.0000e-05 eta: 8:41:50 time: 0.3312 data_time: 0.1064 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 04:58:33 - mmengine - INFO - Epoch(train) [4][40500/42151] lr: 3.0000e-05 eta: 8:41:13 time: 0.3703 data_time: 0.1200 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 04:58:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 04:59:08 - mmengine - INFO - Epoch(train) [4][40600/42151] lr: 3.0000e-05 eta: 8:40:36 time: 0.3420 data_time: 0.1061 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 04:59:43 - mmengine - INFO - Epoch(train) [4][40700/42151] lr: 3.0000e-05 eta: 8:39:59 time: 0.3420 data_time: 0.1200 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 05:00:17 - mmengine - INFO - Epoch(train) [4][40800/42151] lr: 3.0000e-05 eta: 8:39:21 time: 0.3401 data_time: 0.1070 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 05:00:51 - mmengine - INFO - Epoch(train) [4][40900/42151] lr: 3.0000e-05 eta: 8:38:44 time: 0.3279 data_time: 0.0991 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 05:01:26 - mmengine - INFO - Epoch(train) [4][41000/42151] lr: 3.0000e-05 eta: 8:38:06 time: 0.3786 data_time: 0.1240 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 05:02:00 - mmengine - INFO - Epoch(train) [4][41100/42151] lr: 3.0000e-05 eta: 8:37:29 time: 0.3463 data_time: 0.1187 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 05:02:34 - mmengine - INFO - Epoch(train) [4][41200/42151] lr: 3.0000e-05 eta: 8:36:51 time: 0.3548 data_time: 0.1226 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 05:03:08 - mmengine - INFO - Epoch(train) [4][41300/42151] lr: 3.0000e-05 eta: 8:36:14 time: 0.3480 data_time: 0.1174 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:03:42 - mmengine - INFO - Epoch(train) [4][41400/42151] lr: 3.0000e-05 eta: 8:35:36 time: 0.3160 data_time: 0.0968 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 05:04:17 - mmengine - INFO - Epoch(train) [4][41500/42151] lr: 3.0000e-05 eta: 8:34:59 time: 0.3353 data_time: 0.1066 memory: 7851 loss_ce: 0.0186 loss: 0.0186 2022/09/17 05:04:33 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 05:04:51 - mmengine - INFO - Epoch(train) [4][41600/42151] lr: 3.0000e-05 eta: 8:34:22 time: 0.3323 data_time: 0.1073 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 05:05:26 - mmengine - INFO - Epoch(train) [4][41700/42151] lr: 3.0000e-05 eta: 8:33:44 time: 0.3710 data_time: 0.1241 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 05:05:59 - mmengine - INFO - Epoch(train) [4][41800/42151] lr: 3.0000e-05 eta: 8:33:06 time: 0.3282 data_time: 0.1050 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 05:06:32 - mmengine - INFO - Epoch(train) [4][41900/42151] lr: 3.0000e-05 eta: 8:32:28 time: 0.3595 data_time: 0.1331 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 05:07:06 - mmengine - INFO - Epoch(train) [4][42000/42151] lr: 3.0000e-05 eta: 8:31:51 time: 0.3254 data_time: 0.1000 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 05:07:40 - mmengine - INFO - Epoch(train) [4][42100/42151] lr: 3.0000e-05 eta: 8:31:13 time: 0.3355 data_time: 0.1015 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 05:07:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 05:07:57 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/09/17 05:08:41 - mmengine - INFO - Epoch(val) [4][100/7672] eta: 0:46:33 time: 0.3689 data_time: 0.0008 memory: 7851 2022/09/17 05:09:17 - mmengine - INFO - Epoch(val) [4][200/7672] eta: 0:41:14 time: 0.3312 data_time: 0.0010 memory: 580 2022/09/17 05:09:53 - mmengine - INFO - Epoch(val) [4][300/7672] eta: 0:24:45 time: 0.2014 data_time: 0.0008 memory: 580 2022/09/17 05:10:14 - mmengine - INFO - Epoch(val) [4][400/7672] eta: 0:24:45 time: 0.2043 data_time: 0.0008 memory: 580 2022/09/17 05:10:35 - mmengine - INFO - Epoch(val) [4][500/7672] eta: 0:24:42 time: 0.2067 data_time: 0.0008 memory: 580 2022/09/17 05:10:56 - mmengine - INFO - Epoch(val) [4][600/7672] eta: 0:24:13 time: 0.2056 data_time: 0.0008 memory: 580 2022/09/17 05:11:16 - mmengine - INFO - Epoch(val) [4][700/7672] eta: 0:23:17 time: 0.2004 data_time: 0.0010 memory: 580 2022/09/17 05:11:36 - mmengine - INFO - Epoch(val) [4][800/7672] eta: 0:22:40 time: 0.1980 data_time: 0.0007 memory: 580 2022/09/17 05:11:57 - mmengine - INFO - Epoch(val) [4][900/7672] eta: 0:22:45 time: 0.2016 data_time: 0.0008 memory: 580 2022/09/17 05:12:17 - mmengine - INFO - Epoch(val) [4][1000/7672] eta: 0:22:17 time: 0.2004 data_time: 0.0007 memory: 580 2022/09/17 05:12:38 - mmengine - INFO - Epoch(val) [4][1100/7672] eta: 0:22:08 time: 0.2022 data_time: 0.0007 memory: 580 2022/09/17 05:12:58 - mmengine - INFO - Epoch(val) [4][1200/7672] eta: 0:22:12 time: 0.2059 data_time: 0.0008 memory: 580 2022/09/17 05:13:19 - mmengine - INFO - Epoch(val) [4][1300/7672] eta: 0:21:25 time: 0.2017 data_time: 0.0009 memory: 580 2022/09/17 05:13:39 - mmengine - INFO - Epoch(val) [4][1400/7672] eta: 0:21:40 time: 0.2074 data_time: 0.0008 memory: 580 2022/09/17 05:14:01 - mmengine - INFO - Epoch(val) [4][1500/7672] eta: 0:23:03 time: 0.2242 data_time: 0.0008 memory: 580 2022/09/17 05:14:21 - mmengine - INFO - Epoch(val) [4][1600/7672] eta: 0:20:07 time: 0.1989 data_time: 0.0007 memory: 580 2022/09/17 05:14:42 - mmengine - INFO - Epoch(val) [4][1700/7672] eta: 0:20:14 time: 0.2034 data_time: 0.0008 memory: 580 2022/09/17 05:15:02 - mmengine - INFO - Epoch(val) [4][1800/7672] eta: 0:20:23 time: 0.2083 data_time: 0.0008 memory: 580 2022/09/17 05:15:23 - mmengine - INFO - Epoch(val) [4][1900/7672] eta: 0:20:05 time: 0.2089 data_time: 0.0008 memory: 580 2022/09/17 05:15:44 - mmengine - INFO - Epoch(val) [4][2000/7672] eta: 0:19:28 time: 0.2059 data_time: 0.0011 memory: 580 2022/09/17 05:16:05 - mmengine - INFO - Epoch(val) [4][2100/7672] eta: 0:18:41 time: 0.2013 data_time: 0.0010 memory: 580 2022/09/17 05:16:26 - mmengine - INFO - Epoch(val) [4][2200/7672] eta: 0:18:31 time: 0.2032 data_time: 0.0023 memory: 580 2022/09/17 05:16:46 - mmengine - INFO - Epoch(val) [4][2300/7672] eta: 0:18:07 time: 0.2025 data_time: 0.0010 memory: 580 2022/09/17 05:17:06 - mmengine - INFO - Epoch(val) [4][2400/7672] eta: 0:17:45 time: 0.2021 data_time: 0.0007 memory: 580 2022/09/17 05:17:27 - mmengine - INFO - Epoch(val) [4][2500/7672] eta: 0:17:16 time: 0.2005 data_time: 0.0007 memory: 580 2022/09/17 05:17:47 - mmengine - INFO - Epoch(val) [4][2600/7672] eta: 0:16:52 time: 0.1995 data_time: 0.0009 memory: 580 2022/09/17 05:18:08 - mmengine - INFO - Epoch(val) [4][2700/7672] eta: 0:17:02 time: 0.2057 data_time: 0.0008 memory: 580 2022/09/17 05:18:29 - mmengine - INFO - Epoch(val) [4][2800/7672] eta: 0:16:11 time: 0.1995 data_time: 0.0008 memory: 580 2022/09/17 05:18:49 - mmengine - INFO - Epoch(val) [4][2900/7672] eta: 0:15:41 time: 0.1974 data_time: 0.0008 memory: 580 2022/09/17 05:19:10 - mmengine - INFO - Epoch(val) [4][3000/7672] eta: 0:15:35 time: 0.2003 data_time: 0.0007 memory: 580 2022/09/17 05:19:30 - mmengine - INFO - Epoch(val) [4][3100/7672] eta: 0:15:10 time: 0.1992 data_time: 0.0008 memory: 580 2022/09/17 05:19:51 - mmengine - INFO - Epoch(val) [4][3200/7672] eta: 0:15:05 time: 0.2024 data_time: 0.0008 memory: 580 2022/09/17 05:20:12 - mmengine - INFO - Epoch(val) [4][3300/7672] eta: 0:14:48 time: 0.2032 data_time: 0.0007 memory: 580 2022/09/17 05:20:33 - mmengine - INFO - Epoch(val) [4][3400/7672] eta: 0:14:22 time: 0.2019 data_time: 0.0007 memory: 580 2022/09/17 05:20:54 - mmengine - INFO - Epoch(val) [4][3500/7672] eta: 0:14:28 time: 0.2083 data_time: 0.0008 memory: 580 2022/09/17 05:21:15 - mmengine - INFO - Epoch(val) [4][3600/7672] eta: 0:14:06 time: 0.2080 data_time: 0.0013 memory: 580 2022/09/17 05:21:35 - mmengine - INFO - Epoch(val) [4][3700/7672] eta: 0:13:21 time: 0.2018 data_time: 0.0011 memory: 580 2022/09/17 05:21:56 - mmengine - INFO - Epoch(val) [4][3800/7672] eta: 0:13:09 time: 0.2040 data_time: 0.0008 memory: 580 2022/09/17 05:22:16 - mmengine - INFO - Epoch(val) [4][3900/7672] eta: 0:12:41 time: 0.2018 data_time: 0.0008 memory: 580 2022/09/17 05:22:37 - mmengine - INFO - Epoch(val) [4][4000/7672] eta: 0:12:11 time: 0.1993 data_time: 0.0008 memory: 580 2022/09/17 05:22:57 - mmengine - INFO - Epoch(val) [4][4100/7672] eta: 0:13:34 time: 0.2279 data_time: 0.0008 memory: 580 2022/09/17 05:23:18 - mmengine - INFO - Epoch(val) [4][4200/7672] eta: 0:11:41 time: 0.2020 data_time: 0.0007 memory: 580 2022/09/17 05:23:38 - mmengine - INFO - Epoch(val) [4][4300/7672] eta: 0:11:11 time: 0.1990 data_time: 0.0009 memory: 580 2022/09/17 05:23:59 - mmengine - INFO - Epoch(val) [4][4400/7672] eta: 0:10:51 time: 0.1992 data_time: 0.0010 memory: 580 2022/09/17 05:24:19 - mmengine - INFO - Epoch(val) [4][4500/7672] eta: 0:10:39 time: 0.2017 data_time: 0.0008 memory: 580 2022/09/17 05:24:40 - mmengine - INFO - Epoch(val) [4][4600/7672] eta: 0:10:14 time: 0.1999 data_time: 0.0007 memory: 580 2022/09/17 05:25:01 - mmengine - INFO - Epoch(val) [4][4700/7672] eta: 0:10:19 time: 0.2086 data_time: 0.0008 memory: 580 2022/09/17 05:25:21 - mmengine - INFO - Epoch(val) [4][4800/7672] eta: 0:09:28 time: 0.1980 data_time: 0.0008 memory: 580 2022/09/17 05:25:41 - mmengine - INFO - Epoch(val) [4][4900/7672] eta: 0:09:17 time: 0.2010 data_time: 0.0007 memory: 580 2022/09/17 05:26:02 - mmengine - INFO - Epoch(val) [4][5000/7672] eta: 0:09:07 time: 0.2050 data_time: 0.0008 memory: 580 2022/09/17 05:26:23 - mmengine - INFO - Epoch(val) [4][5100/7672] eta: 0:08:37 time: 0.2011 data_time: 0.0007 memory: 580 2022/09/17 05:26:43 - mmengine - INFO - Epoch(val) [4][5200/7672] eta: 0:08:10 time: 0.1983 data_time: 0.0007 memory: 580 2022/09/17 05:27:04 - mmengine - INFO - Epoch(val) [4][5300/7672] eta: 0:08:03 time: 0.2037 data_time: 0.0007 memory: 580 2022/09/17 05:27:24 - mmengine - INFO - Epoch(val) [4][5400/7672] eta: 0:07:29 time: 0.1980 data_time: 0.0008 memory: 580 2022/09/17 05:27:44 - mmengine - INFO - Epoch(val) [4][5500/7672] eta: 0:07:12 time: 0.1991 data_time: 0.0007 memory: 580 2022/09/17 05:28:05 - mmengine - INFO - Epoch(val) [4][5600/7672] eta: 0:07:04 time: 0.2049 data_time: 0.0008 memory: 580 2022/09/17 05:28:26 - mmengine - INFO - Epoch(val) [4][5700/7672] eta: 0:06:56 time: 0.2112 data_time: 0.0020 memory: 580 2022/09/17 05:28:46 - mmengine - INFO - Epoch(val) [4][5800/7672] eta: 0:06:21 time: 0.2036 data_time: 0.0011 memory: 580 2022/09/17 05:29:07 - mmengine - INFO - Epoch(val) [4][5900/7672] eta: 0:05:59 time: 0.2027 data_time: 0.0008 memory: 580 2022/09/17 05:29:27 - mmengine - INFO - Epoch(val) [4][6000/7672] eta: 0:05:36 time: 0.2015 data_time: 0.0020 memory: 580 2022/09/17 05:29:48 - mmengine - INFO - Epoch(val) [4][6100/7672] eta: 0:05:16 time: 0.2014 data_time: 0.0009 memory: 580 2022/09/17 05:30:08 - mmengine - INFO - Epoch(val) [4][6200/7672] eta: 0:04:51 time: 0.1983 data_time: 0.0007 memory: 580 2022/09/17 05:30:29 - mmengine - INFO - Epoch(val) [4][6300/7672] eta: 0:04:39 time: 0.2038 data_time: 0.0007 memory: 580 2022/09/17 05:30:50 - mmengine - INFO - Epoch(val) [4][6400/7672] eta: 0:04:11 time: 0.1981 data_time: 0.0007 memory: 580 2022/09/17 05:31:10 - mmengine - INFO - Epoch(val) [4][6500/7672] eta: 0:03:56 time: 0.2015 data_time: 0.0007 memory: 580 2022/09/17 05:31:31 - mmengine - INFO - Epoch(val) [4][6600/7672] eta: 0:03:41 time: 0.2067 data_time: 0.0008 memory: 580 2022/09/17 05:31:52 - mmengine - INFO - Epoch(val) [4][6700/7672] eta: 0:03:15 time: 0.2007 data_time: 0.0007 memory: 580 2022/09/17 05:32:13 - mmengine - INFO - Epoch(val) [4][6800/7672] eta: 0:02:58 time: 0.2045 data_time: 0.0008 memory: 580 2022/09/17 05:32:33 - mmengine - INFO - Epoch(val) [4][6900/7672] eta: 0:02:34 time: 0.1999 data_time: 0.0008 memory: 580 2022/09/17 05:32:54 - mmengine - INFO - Epoch(val) [4][7000/7672] eta: 0:02:12 time: 0.1972 data_time: 0.0007 memory: 580 2022/09/17 05:33:14 - mmengine - INFO - Epoch(val) [4][7100/7672] eta: 0:01:52 time: 0.1969 data_time: 0.0007 memory: 580 2022/09/17 05:33:34 - mmengine - INFO - Epoch(val) [4][7200/7672] eta: 0:01:33 time: 0.1983 data_time: 0.0007 memory: 580 2022/09/17 05:33:54 - mmengine - INFO - Epoch(val) [4][7300/7672] eta: 0:01:14 time: 0.1994 data_time: 0.0008 memory: 580 2022/09/17 05:34:15 - mmengine - INFO - Epoch(val) [4][7400/7672] eta: 0:00:54 time: 0.1993 data_time: 0.0008 memory: 580 2022/09/17 05:34:35 - mmengine - INFO - Epoch(val) [4][7500/7672] eta: 0:00:35 time: 0.2059 data_time: 0.0007 memory: 580 2022/09/17 05:34:56 - mmengine - INFO - Epoch(val) [4][7600/7672] eta: 0:00:14 time: 0.2044 data_time: 0.0012 memory: 580 2022/09/17 05:35:11 - mmengine - INFO - Epoch(val) [4][7672/7672] CUTE80/recog/word_acc_ignore_case_symbol: 0.7569 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9163 SVT/recog/word_acc_ignore_case_symbol: 0.8810 SVTP/recog/word_acc_ignore_case_symbol: 0.7690 IC13/recog/word_acc_ignore_case_symbol: 0.9379 IC15/recog/word_acc_ignore_case_symbol: 0.7241 2022/09/17 05:35:52 - mmengine - INFO - Epoch(train) [5][100/42151] lr: 3.0000e-06 eta: 8:30:19 time: 0.3351 data_time: 0.1166 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 05:36:26 - mmengine - INFO - Epoch(train) [5][200/42151] lr: 3.0000e-06 eta: 8:29:41 time: 0.3395 data_time: 0.1338 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 05:37:00 - mmengine - INFO - Epoch(train) [5][300/42151] lr: 3.0000e-06 eta: 8:29:04 time: 0.3038 data_time: 0.1042 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 05:37:33 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 05:37:35 - mmengine - INFO - Epoch(train) [5][400/42151] lr: 3.0000e-06 eta: 8:28:26 time: 0.3098 data_time: 0.1073 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 05:38:09 - mmengine - INFO - Epoch(train) [5][500/42151] lr: 3.0000e-06 eta: 8:27:49 time: 0.3903 data_time: 0.1476 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 05:38:43 - mmengine - INFO - Epoch(train) [5][600/42151] lr: 3.0000e-06 eta: 8:27:11 time: 0.3081 data_time: 0.0817 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 05:39:17 - mmengine - INFO - Epoch(train) [5][700/42151] lr: 3.0000e-06 eta: 8:26:34 time: 0.3110 data_time: 0.0803 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 05:39:52 - mmengine - INFO - Epoch(train) [5][800/42151] lr: 3.0000e-06 eta: 8:25:57 time: 0.3340 data_time: 0.1307 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:40:27 - mmengine - INFO - Epoch(train) [5][900/42151] lr: 3.0000e-06 eta: 8:25:20 time: 0.3250 data_time: 0.1097 memory: 7851 loss_ce: 0.0177 loss: 0.0177 2022/09/17 05:41:02 - mmengine - INFO - Epoch(train) [5][1000/42151] lr: 3.0000e-06 eta: 8:24:43 time: 0.3219 data_time: 0.0945 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:41:36 - mmengine - INFO - Epoch(train) [5][1100/42151] lr: 3.0000e-06 eta: 8:24:05 time: 0.3609 data_time: 0.1369 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 05:42:10 - mmengine - INFO - Epoch(train) [5][1200/42151] lr: 3.0000e-06 eta: 8:23:28 time: 0.3544 data_time: 0.1467 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 05:42:44 - mmengine - INFO - Epoch(train) [5][1300/42151] lr: 3.0000e-06 eta: 8:22:50 time: 0.3108 data_time: 0.0833 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 05:43:17 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 05:43:19 - mmengine - INFO - Epoch(train) [5][1400/42151] lr: 3.0000e-06 eta: 8:22:13 time: 0.3382 data_time: 0.1355 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 05:43:52 - mmengine - INFO - Epoch(train) [5][1500/42151] lr: 3.0000e-06 eta: 8:21:35 time: 0.2962 data_time: 0.0949 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 05:44:26 - mmengine - INFO - Epoch(train) [5][1600/42151] lr: 3.0000e-06 eta: 8:20:58 time: 0.3075 data_time: 0.0887 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 05:44:59 - mmengine - INFO - Epoch(train) [5][1700/42151] lr: 3.0000e-06 eta: 8:20:20 time: 0.3595 data_time: 0.1370 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:45:33 - mmengine - INFO - Epoch(train) [5][1800/42151] lr: 3.0000e-06 eta: 8:19:42 time: 0.3288 data_time: 0.1268 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 05:46:07 - mmengine - INFO - Epoch(train) [5][1900/42151] lr: 3.0000e-06 eta: 8:19:05 time: 0.3168 data_time: 0.0821 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 05:46:40 - mmengine - INFO - Epoch(train) [5][2000/42151] lr: 3.0000e-06 eta: 8:18:27 time: 0.3306 data_time: 0.1326 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 05:47:14 - mmengine - INFO - Epoch(train) [5][2100/42151] lr: 3.0000e-06 eta: 8:17:49 time: 0.3055 data_time: 0.1033 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 05:47:47 - mmengine - INFO - Epoch(train) [5][2200/42151] lr: 3.0000e-06 eta: 8:17:11 time: 0.2926 data_time: 0.0660 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 05:48:21 - mmengine - INFO - Epoch(train) [5][2300/42151] lr: 3.0000e-06 eta: 8:16:34 time: 0.3365 data_time: 0.1326 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 05:48:55 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 05:48:56 - mmengine - INFO - Epoch(train) [5][2400/42151] lr: 3.0000e-06 eta: 8:15:57 time: 0.3423 data_time: 0.1374 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 05:49:29 - mmengine - INFO - Epoch(train) [5][2500/42151] lr: 3.0000e-06 eta: 8:15:19 time: 0.3101 data_time: 0.0824 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 05:50:03 - mmengine - INFO - Epoch(train) [5][2600/42151] lr: 3.0000e-06 eta: 8:14:41 time: 0.3453 data_time: 0.1443 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 05:50:37 - mmengine - INFO - Epoch(train) [5][2700/42151] lr: 3.0000e-06 eta: 8:14:04 time: 0.2960 data_time: 0.0969 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 05:51:11 - mmengine - INFO - Epoch(train) [5][2800/42151] lr: 3.0000e-06 eta: 8:13:27 time: 0.2964 data_time: 0.0673 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 05:51:46 - mmengine - INFO - Epoch(train) [5][2900/42151] lr: 3.0000e-06 eta: 8:12:49 time: 0.3481 data_time: 0.1457 memory: 7851 loss_ce: 0.0121 loss: 0.0121 2022/09/17 05:52:20 - mmengine - INFO - Epoch(train) [5][3000/42151] lr: 3.0000e-06 eta: 8:12:12 time: 0.3672 data_time: 0.1441 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 05:52:55 - mmengine - INFO - Epoch(train) [5][3100/42151] lr: 3.0000e-06 eta: 8:11:35 time: 0.3405 data_time: 0.1076 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:53:29 - mmengine - INFO - Epoch(train) [5][3200/42151] lr: 3.0000e-06 eta: 8:10:58 time: 0.3617 data_time: 0.1313 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:54:04 - mmengine - INFO - Epoch(train) [5][3300/42151] lr: 3.0000e-06 eta: 8:10:20 time: 0.2950 data_time: 0.0947 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 05:54:37 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 05:54:39 - mmengine - INFO - Epoch(train) [5][3400/42151] lr: 3.0000e-06 eta: 8:09:43 time: 0.2890 data_time: 0.0857 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 05:55:14 - mmengine - INFO - Epoch(train) [5][3500/42151] lr: 3.0000e-06 eta: 8:09:07 time: 0.3693 data_time: 0.1288 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 05:55:49 - mmengine - INFO - Epoch(train) [5][3600/42151] lr: 3.0000e-06 eta: 8:08:29 time: 0.3663 data_time: 0.1229 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 05:56:23 - mmengine - INFO - Epoch(train) [5][3700/42151] lr: 3.0000e-06 eta: 8:07:52 time: 0.3114 data_time: 0.1102 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 05:56:58 - mmengine - INFO - Epoch(train) [5][3800/42151] lr: 3.0000e-06 eta: 8:07:15 time: 0.3272 data_time: 0.1252 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 05:57:32 - mmengine - INFO - Epoch(train) [5][3900/42151] lr: 3.0000e-06 eta: 8:06:38 time: 0.3091 data_time: 0.1076 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 05:58:06 - mmengine - INFO - Epoch(train) [5][4000/42151] lr: 3.0000e-06 eta: 8:06:01 time: 0.3293 data_time: 0.1219 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 05:58:41 - mmengine - INFO - Epoch(train) [5][4100/42151] lr: 3.0000e-06 eta: 8:05:24 time: 0.3442 data_time: 0.1200 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 05:59:15 - mmengine - INFO - Epoch(train) [5][4200/42151] lr: 3.0000e-06 eta: 8:04:46 time: 0.3356 data_time: 0.1116 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 05:59:50 - mmengine - INFO - Epoch(train) [5][4300/42151] lr: 3.0000e-06 eta: 8:04:09 time: 0.3353 data_time: 0.1137 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 06:00:28 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:00:29 - mmengine - INFO - Epoch(train) [5][4400/42151] lr: 3.0000e-06 eta: 8:03:34 time: 0.3368 data_time: 0.1266 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 06:01:03 - mmengine - INFO - Epoch(train) [5][4500/42151] lr: 3.0000e-06 eta: 8:02:57 time: 0.2969 data_time: 0.0930 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 06:01:38 - mmengine - INFO - Epoch(train) [5][4600/42151] lr: 3.0000e-06 eta: 8:02:20 time: 0.3326 data_time: 0.1252 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 06:02:13 - mmengine - INFO - Epoch(train) [5][4700/42151] lr: 3.0000e-06 eta: 8:01:43 time: 0.3398 data_time: 0.1173 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 06:02:47 - mmengine - INFO - Epoch(train) [5][4800/42151] lr: 3.0000e-06 eta: 8:01:06 time: 0.3409 data_time: 0.1135 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 06:03:22 - mmengine - INFO - Epoch(train) [5][4900/42151] lr: 3.0000e-06 eta: 8:00:28 time: 0.3138 data_time: 0.1143 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 06:03:56 - mmengine - INFO - Epoch(train) [5][5000/42151] lr: 3.0000e-06 eta: 7:59:51 time: 0.3064 data_time: 0.1035 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 06:04:30 - mmengine - INFO - Epoch(train) [5][5100/42151] lr: 3.0000e-06 eta: 7:59:14 time: 0.2961 data_time: 0.0972 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 06:05:04 - mmengine - INFO - Epoch(train) [5][5200/42151] lr: 3.0000e-06 eta: 7:58:36 time: 0.3023 data_time: 0.1041 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 06:05:39 - mmengine - INFO - Epoch(train) [5][5300/42151] lr: 3.0000e-06 eta: 7:57:59 time: 0.3650 data_time: 0.1111 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 06:06:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:06:13 - mmengine - INFO - Epoch(train) [5][5400/42151] lr: 3.0000e-06 eta: 7:57:22 time: 0.3548 data_time: 0.1266 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 06:06:48 - mmengine - INFO - Epoch(train) [5][5500/42151] lr: 3.0000e-06 eta: 7:56:45 time: 0.3128 data_time: 0.1112 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 06:07:22 - mmengine - INFO - Epoch(train) [5][5600/42151] lr: 3.0000e-06 eta: 7:56:08 time: 0.3220 data_time: 0.1177 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 06:07:55 - mmengine - INFO - Epoch(train) [5][5700/42151] lr: 3.0000e-06 eta: 7:55:30 time: 0.2942 data_time: 0.0933 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 06:08:29 - mmengine - INFO - Epoch(train) [5][5800/42151] lr: 3.0000e-06 eta: 7:54:53 time: 0.3143 data_time: 0.1081 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 06:09:04 - mmengine - INFO - Epoch(train) [5][5900/42151] lr: 3.0000e-06 eta: 7:54:16 time: 0.3528 data_time: 0.1269 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 06:09:39 - mmengine - INFO - Epoch(train) [5][6000/42151] lr: 3.0000e-06 eta: 7:53:39 time: 0.3286 data_time: 0.1043 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 06:10:14 - mmengine - INFO - Epoch(train) [5][6100/42151] lr: 3.0000e-06 eta: 7:53:02 time: 0.3033 data_time: 0.1031 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 06:10:48 - mmengine - INFO - Epoch(train) [5][6200/42151] lr: 3.0000e-06 eta: 7:52:25 time: 0.3284 data_time: 0.1296 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 06:11:24 - mmengine - INFO - Epoch(train) [5][6300/42151] lr: 3.0000e-06 eta: 7:51:48 time: 0.3397 data_time: 0.1407 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 06:11:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:11:59 - mmengine - INFO - Epoch(train) [5][6400/42151] lr: 3.0000e-06 eta: 7:51:11 time: 0.3412 data_time: 0.1374 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 06:12:33 - mmengine - INFO - Epoch(train) [5][6500/42151] lr: 3.0000e-06 eta: 7:50:34 time: 0.3504 data_time: 0.1218 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 06:13:08 - mmengine - INFO - Epoch(train) [5][6600/42151] lr: 3.0000e-06 eta: 7:49:57 time: 0.3134 data_time: 0.0916 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 06:13:42 - mmengine - INFO - Epoch(train) [5][6700/42151] lr: 3.0000e-06 eta: 7:49:20 time: 0.3114 data_time: 0.1046 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 06:14:16 - mmengine - INFO - Epoch(train) [5][6800/42151] lr: 3.0000e-06 eta: 7:48:42 time: 0.3417 data_time: 0.1426 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 06:14:51 - mmengine - INFO - Epoch(train) [5][6900/42151] lr: 3.0000e-06 eta: 7:48:05 time: 0.3097 data_time: 0.0992 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 06:15:25 - mmengine - INFO - Epoch(train) [5][7000/42151] lr: 3.0000e-06 eta: 7:47:28 time: 0.3179 data_time: 0.1152 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 06:16:01 - mmengine - INFO - Epoch(train) [5][7100/42151] lr: 3.0000e-06 eta: 7:46:52 time: 0.3777 data_time: 0.1272 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 06:16:35 - mmengine - INFO - Epoch(train) [5][7200/42151] lr: 3.0000e-06 eta: 7:46:14 time: 0.3169 data_time: 0.0911 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 06:17:10 - mmengine - INFO - Epoch(train) [5][7300/42151] lr: 3.0000e-06 eta: 7:45:37 time: 0.3426 data_time: 0.1415 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 06:17:44 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:17:45 - mmengine - INFO - Epoch(train) [5][7400/42151] lr: 3.0000e-06 eta: 7:45:01 time: 0.3611 data_time: 0.1605 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 06:18:19 - mmengine - INFO - Epoch(train) [5][7500/42151] lr: 3.0000e-06 eta: 7:44:23 time: 0.3064 data_time: 0.0978 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 06:18:54 - mmengine - INFO - Epoch(train) [5][7600/42151] lr: 3.0000e-06 eta: 7:43:47 time: 0.3221 data_time: 0.1204 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 06:19:29 - mmengine - INFO - Epoch(train) [5][7700/42151] lr: 3.0000e-06 eta: 7:43:10 time: 0.3491 data_time: 0.1253 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 06:20:03 - mmengine - INFO - Epoch(train) [5][7800/42151] lr: 3.0000e-06 eta: 7:42:32 time: 0.3065 data_time: 0.0826 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 06:20:37 - mmengine - INFO - Epoch(train) [5][7900/42151] lr: 3.0000e-06 eta: 7:41:55 time: 0.3071 data_time: 0.1045 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 06:21:12 - mmengine - INFO - Epoch(train) [5][8000/42151] lr: 3.0000e-06 eta: 7:41:18 time: 0.3280 data_time: 0.1132 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 06:21:46 - mmengine - INFO - Epoch(train) [5][8100/42151] lr: 3.0000e-06 eta: 7:40:41 time: 0.3003 data_time: 0.0979 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 06:22:21 - mmengine - INFO - Epoch(train) [5][8200/42151] lr: 3.0000e-06 eta: 7:40:04 time: 0.3407 data_time: 0.1312 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 06:22:56 - mmengine - INFO - Epoch(train) [5][8300/42151] lr: 3.0000e-06 eta: 7:39:27 time: 0.3575 data_time: 0.1262 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 06:23:29 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:23:31 - mmengine - INFO - Epoch(train) [5][8400/42151] lr: 3.0000e-06 eta: 7:38:50 time: 0.3637 data_time: 0.1020 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 06:24:05 - mmengine - INFO - Epoch(train) [5][8500/42151] lr: 3.0000e-06 eta: 7:38:13 time: 0.3163 data_time: 0.1113 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 06:24:40 - mmengine - INFO - Epoch(train) [5][8600/42151] lr: 3.0000e-06 eta: 7:37:36 time: 0.3483 data_time: 0.1302 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 06:25:14 - mmengine - INFO - Epoch(train) [5][8700/42151] lr: 3.0000e-06 eta: 7:36:59 time: 0.3371 data_time: 0.1376 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 06:25:48 - mmengine - INFO - Epoch(train) [5][8800/42151] lr: 3.0000e-06 eta: 7:36:22 time: 0.3241 data_time: 0.1231 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 06:26:22 - mmengine - INFO - Epoch(train) [5][8900/42151] lr: 3.0000e-06 eta: 7:35:45 time: 0.3477 data_time: 0.1233 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 06:26:56 - mmengine - INFO - Epoch(train) [5][9000/42151] lr: 3.0000e-06 eta: 7:35:07 time: 0.3033 data_time: 0.0826 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 06:27:30 - mmengine - INFO - Epoch(train) [5][9100/42151] lr: 3.0000e-06 eta: 7:34:30 time: 0.3079 data_time: 0.1054 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 06:28:04 - mmengine - INFO - Epoch(train) [5][9200/42151] lr: 3.0000e-06 eta: 7:33:53 time: 0.3021 data_time: 0.1039 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 06:28:38 - mmengine - INFO - Epoch(train) [5][9300/42151] lr: 3.0000e-06 eta: 7:33:15 time: 0.2954 data_time: 0.0953 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 06:29:11 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:29:12 - mmengine - INFO - Epoch(train) [5][9400/42151] lr: 3.0000e-06 eta: 7:32:38 time: 0.3375 data_time: 0.1339 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 06:29:47 - mmengine - INFO - Epoch(train) [5][9500/42151] lr: 3.0000e-06 eta: 7:32:01 time: 0.3498 data_time: 0.1257 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 06:30:21 - mmengine - INFO - Epoch(train) [5][9600/42151] lr: 3.0000e-06 eta: 7:31:24 time: 0.3218 data_time: 0.0930 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 06:30:55 - mmengine - INFO - Epoch(train) [5][9700/42151] lr: 3.0000e-06 eta: 7:30:47 time: 0.3095 data_time: 0.1050 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 06:31:29 - mmengine - INFO - Epoch(train) [5][9800/42151] lr: 3.0000e-06 eta: 7:30:10 time: 0.3289 data_time: 0.1266 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 06:32:04 - mmengine - INFO - Epoch(train) [5][9900/42151] lr: 3.0000e-06 eta: 7:29:33 time: 0.2981 data_time: 0.0933 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 06:32:38 - mmengine - INFO - Epoch(train) [5][10000/42151] lr: 3.0000e-06 eta: 7:28:56 time: 0.3113 data_time: 0.1067 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 06:33:13 - mmengine - INFO - Epoch(train) [5][10100/42151] lr: 3.0000e-06 eta: 7:28:19 time: 0.3910 data_time: 0.1329 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 06:33:47 - mmengine - INFO - Epoch(train) [5][10200/42151] lr: 3.0000e-06 eta: 7:27:42 time: 0.3294 data_time: 0.0933 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 06:34:21 - mmengine - INFO - Epoch(train) [5][10300/42151] lr: 3.0000e-06 eta: 7:27:05 time: 0.3172 data_time: 0.1167 memory: 7851 loss_ce: 0.0133 loss: 0.0133 2022/09/17 06:34:55 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:34:56 - mmengine - INFO - Epoch(train) [5][10400/42151] lr: 3.0000e-06 eta: 7:26:28 time: 0.3642 data_time: 0.1637 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 06:35:32 - mmengine - INFO - Epoch(train) [5][10500/42151] lr: 3.0000e-06 eta: 7:25:51 time: 0.3340 data_time: 0.1275 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 06:36:06 - mmengine - INFO - Epoch(train) [5][10600/42151] lr: 3.0000e-06 eta: 7:25:14 time: 0.3356 data_time: 0.1342 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 06:36:42 - mmengine - INFO - Epoch(train) [5][10700/42151] lr: 3.0000e-06 eta: 7:24:38 time: 0.3484 data_time: 0.1222 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 06:37:17 - mmengine - INFO - Epoch(train) [5][10800/42151] lr: 3.0000e-06 eta: 7:24:01 time: 0.3392 data_time: 0.1123 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 06:37:52 - mmengine - INFO - Epoch(train) [5][10900/42151] lr: 3.0000e-06 eta: 7:23:24 time: 0.3405 data_time: 0.1142 memory: 7851 loss_ce: 0.0131 loss: 0.0131 2022/09/17 06:38:27 - mmengine - INFO - Epoch(train) [5][11000/42151] lr: 3.0000e-06 eta: 7:22:48 time: 0.3224 data_time: 0.1231 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 06:39:02 - mmengine - INFO - Epoch(train) [5][11100/42151] lr: 3.0000e-06 eta: 7:22:11 time: 0.3120 data_time: 0.1063 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 06:39:37 - mmengine - INFO - Epoch(train) [5][11200/42151] lr: 3.0000e-06 eta: 7:21:34 time: 0.3361 data_time: 0.1385 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 06:40:12 - mmengine - INFO - Epoch(train) [5][11300/42151] lr: 3.0000e-06 eta: 7:20:57 time: 0.3460 data_time: 0.1200 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 06:40:45 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:40:47 - mmengine - INFO - Epoch(train) [5][11400/42151] lr: 3.0000e-06 eta: 7:20:20 time: 0.3313 data_time: 0.1051 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 06:41:22 - mmengine - INFO - Epoch(train) [5][11500/42151] lr: 3.0000e-06 eta: 7:19:44 time: 0.3358 data_time: 0.1399 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 06:41:56 - mmengine - INFO - Epoch(train) [5][11600/42151] lr: 3.0000e-06 eta: 7:19:06 time: 0.3058 data_time: 0.1127 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 06:42:30 - mmengine - INFO - Epoch(train) [5][11700/42151] lr: 3.0000e-06 eta: 7:18:29 time: 0.2968 data_time: 0.1010 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 06:43:06 - mmengine - INFO - Epoch(train) [5][11800/42151] lr: 3.0000e-06 eta: 7:17:53 time: 0.3741 data_time: 0.1765 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 06:43:41 - mmengine - INFO - Epoch(train) [5][11900/42151] lr: 3.0000e-06 eta: 7:17:16 time: 0.3290 data_time: 0.1113 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 06:44:16 - mmengine - INFO - Epoch(train) [5][12000/42151] lr: 3.0000e-06 eta: 7:16:39 time: 0.3015 data_time: 0.0825 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 06:44:51 - mmengine - INFO - Epoch(train) [5][12100/42151] lr: 3.0000e-06 eta: 7:16:03 time: 0.3421 data_time: 0.1454 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 06:45:25 - mmengine - INFO - Epoch(train) [5][12200/42151] lr: 3.0000e-06 eta: 7:15:25 time: 0.3316 data_time: 0.1320 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 06:46:00 - mmengine - INFO - Epoch(train) [5][12300/42151] lr: 3.0000e-06 eta: 7:14:49 time: 0.3021 data_time: 0.1071 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 06:46:34 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:46:35 - mmengine - INFO - Epoch(train) [5][12400/42151] lr: 3.0000e-06 eta: 7:14:12 time: 0.4002 data_time: 0.1731 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 06:47:10 - mmengine - INFO - Epoch(train) [5][12500/42151] lr: 3.0000e-06 eta: 7:13:35 time: 0.3384 data_time: 0.1234 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 06:47:47 - mmengine - INFO - Epoch(train) [5][12600/42151] lr: 3.0000e-06 eta: 7:12:59 time: 0.3331 data_time: 0.1030 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 06:48:23 - mmengine - INFO - Epoch(train) [5][12700/42151] lr: 3.0000e-06 eta: 7:12:23 time: 0.3478 data_time: 0.1460 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 06:48:58 - mmengine - INFO - Epoch(train) [5][12800/42151] lr: 3.0000e-06 eta: 7:11:46 time: 0.3255 data_time: 0.1261 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 06:49:33 - mmengine - INFO - Epoch(train) [5][12900/42151] lr: 3.0000e-06 eta: 7:11:10 time: 0.3087 data_time: 0.1097 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 06:50:09 - mmengine - INFO - Epoch(train) [5][13000/42151] lr: 3.0000e-06 eta: 7:10:33 time: 0.3508 data_time: 0.1555 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 06:50:44 - mmengine - INFO - Epoch(train) [5][13100/42151] lr: 3.0000e-06 eta: 7:09:56 time: 0.3561 data_time: 0.1204 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 06:51:18 - mmengine - INFO - Epoch(train) [5][13200/42151] lr: 3.0000e-06 eta: 7:09:20 time: 0.3268 data_time: 0.0968 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 06:51:53 - mmengine - INFO - Epoch(train) [5][13300/42151] lr: 3.0000e-06 eta: 7:08:43 time: 0.3214 data_time: 0.1251 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 06:52:27 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:52:29 - mmengine - INFO - Epoch(train) [5][13400/42151] lr: 3.0000e-06 eta: 7:08:06 time: 0.3460 data_time: 0.1443 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 06:53:04 - mmengine - INFO - Epoch(train) [5][13500/42151] lr: 3.0000e-06 eta: 7:07:30 time: 0.3156 data_time: 0.1172 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 06:53:38 - mmengine - INFO - Epoch(train) [5][13600/42151] lr: 3.0000e-06 eta: 7:06:52 time: 0.3295 data_time: 0.1335 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 06:54:14 - mmengine - INFO - Epoch(train) [5][13700/42151] lr: 3.0000e-06 eta: 7:06:16 time: 0.3663 data_time: 0.1167 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 06:54:48 - mmengine - INFO - Epoch(train) [5][13800/42151] lr: 3.0000e-06 eta: 7:05:39 time: 0.3115 data_time: 0.0923 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 06:55:22 - mmengine - INFO - Epoch(train) [5][13900/42151] lr: 3.0000e-06 eta: 7:05:02 time: 0.3504 data_time: 0.1563 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 06:55:57 - mmengine - INFO - Epoch(train) [5][14000/42151] lr: 3.0000e-06 eta: 7:04:25 time: 0.3388 data_time: 0.1424 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 06:56:33 - mmengine - INFO - Epoch(train) [5][14100/42151] lr: 3.0000e-06 eta: 7:03:49 time: 0.3095 data_time: 0.1050 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 06:57:09 - mmengine - INFO - Epoch(train) [5][14200/42151] lr: 3.0000e-06 eta: 7:03:13 time: 0.3625 data_time: 0.1589 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 06:57:45 - mmengine - INFO - Epoch(train) [5][14300/42151] lr: 3.0000e-06 eta: 7:02:36 time: 0.3567 data_time: 0.1099 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 06:58:19 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 06:58:21 - mmengine - INFO - Epoch(train) [5][14400/42151] lr: 3.0000e-06 eta: 7:02:00 time: 0.3578 data_time: 0.1253 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 06:58:56 - mmengine - INFO - Epoch(train) [5][14500/42151] lr: 3.0000e-06 eta: 7:01:23 time: 0.3213 data_time: 0.1203 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 06:59:31 - mmengine - INFO - Epoch(train) [5][14600/42151] lr: 3.0000e-06 eta: 7:00:46 time: 0.3138 data_time: 0.1105 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 07:00:06 - mmengine - INFO - Epoch(train) [5][14700/42151] lr: 3.0000e-06 eta: 7:00:10 time: 0.2984 data_time: 0.0982 memory: 7851 loss_ce: 0.0176 loss: 0.0176 2022/09/17 07:00:41 - mmengine - INFO - Epoch(train) [5][14800/42151] lr: 3.0000e-06 eta: 6:59:33 time: 0.3572 data_time: 0.1525 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 07:01:15 - mmengine - INFO - Epoch(train) [5][14900/42151] lr: 3.0000e-06 eta: 6:58:56 time: 0.3400 data_time: 0.1082 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 07:01:50 - mmengine - INFO - Epoch(train) [5][15000/42151] lr: 3.0000e-06 eta: 6:58:19 time: 0.3113 data_time: 0.0889 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 07:02:26 - mmengine - INFO - Epoch(train) [5][15100/42151] lr: 3.0000e-06 eta: 6:57:43 time: 0.3289 data_time: 0.1178 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 07:03:00 - mmengine - INFO - Epoch(train) [5][15200/42151] lr: 3.0000e-06 eta: 6:57:06 time: 0.3064 data_time: 0.1041 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 07:03:35 - mmengine - INFO - Epoch(train) [5][15300/42151] lr: 3.0000e-06 eta: 6:56:29 time: 0.2981 data_time: 0.0941 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 07:04:08 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:04:10 - mmengine - INFO - Epoch(train) [5][15400/42151] lr: 3.0000e-06 eta: 6:55:52 time: 0.3471 data_time: 0.1418 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 07:04:44 - mmengine - INFO - Epoch(train) [5][15500/42151] lr: 3.0000e-06 eta: 6:55:15 time: 0.3425 data_time: 0.1143 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:05:19 - mmengine - INFO - Epoch(train) [5][15600/42151] lr: 3.0000e-06 eta: 6:54:39 time: 0.3260 data_time: 0.1003 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 07:05:53 - mmengine - INFO - Epoch(train) [5][15700/42151] lr: 3.0000e-06 eta: 6:54:02 time: 0.3270 data_time: 0.1246 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 07:06:27 - mmengine - INFO - Epoch(train) [5][15800/42151] lr: 3.0000e-06 eta: 6:53:25 time: 0.3219 data_time: 0.1173 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 07:07:02 - mmengine - INFO - Epoch(train) [5][15900/42151] lr: 3.0000e-06 eta: 6:52:48 time: 0.2974 data_time: 0.0941 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 07:07:36 - mmengine - INFO - Epoch(train) [5][16000/42151] lr: 3.0000e-06 eta: 6:52:11 time: 0.3183 data_time: 0.1141 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 07:08:11 - mmengine - INFO - Epoch(train) [5][16100/42151] lr: 3.0000e-06 eta: 6:51:34 time: 0.3638 data_time: 0.1084 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 07:08:45 - mmengine - INFO - Epoch(train) [5][16200/42151] lr: 3.0000e-06 eta: 6:50:57 time: 0.3510 data_time: 0.0989 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 07:09:19 - mmengine - INFO - Epoch(train) [5][16300/42151] lr: 3.0000e-06 eta: 6:50:20 time: 0.3181 data_time: 0.1149 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 07:09:53 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:09:55 - mmengine - INFO - Epoch(train) [5][16400/42151] lr: 3.0000e-06 eta: 6:49:44 time: 0.3374 data_time: 0.1297 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 07:10:29 - mmengine - INFO - Epoch(train) [5][16500/42151] lr: 3.0000e-06 eta: 6:49:07 time: 0.3122 data_time: 0.1127 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 07:11:03 - mmengine - INFO - Epoch(train) [5][16600/42151] lr: 3.0000e-06 eta: 6:48:30 time: 0.3351 data_time: 0.1316 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 07:11:39 - mmengine - INFO - Epoch(train) [5][16700/42151] lr: 3.0000e-06 eta: 6:47:53 time: 0.3402 data_time: 0.1079 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:12:13 - mmengine - INFO - Epoch(train) [5][16800/42151] lr: 3.0000e-06 eta: 6:47:16 time: 0.3243 data_time: 0.1055 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:12:47 - mmengine - INFO - Epoch(train) [5][16900/42151] lr: 3.0000e-06 eta: 6:46:40 time: 0.3642 data_time: 0.1293 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 07:13:21 - mmengine - INFO - Epoch(train) [5][17000/42151] lr: 3.0000e-06 eta: 6:46:02 time: 0.3064 data_time: 0.1079 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 07:13:55 - mmengine - INFO - Epoch(train) [5][17100/42151] lr: 3.0000e-06 eta: 6:45:25 time: 0.3004 data_time: 0.0993 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 07:14:29 - mmengine - INFO - Epoch(train) [5][17200/42151] lr: 3.0000e-06 eta: 6:44:48 time: 0.3060 data_time: 0.1068 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 07:15:03 - mmengine - INFO - Epoch(train) [5][17300/42151] lr: 3.0000e-06 eta: 6:44:11 time: 0.3461 data_time: 0.1215 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 07:15:36 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:15:38 - mmengine - INFO - Epoch(train) [5][17400/42151] lr: 3.0000e-06 eta: 6:43:35 time: 0.3614 data_time: 0.1125 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 07:16:12 - mmengine - INFO - Epoch(train) [5][17500/42151] lr: 3.0000e-06 eta: 6:42:58 time: 0.3190 data_time: 0.1161 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 07:16:46 - mmengine - INFO - Epoch(train) [5][17600/42151] lr: 3.0000e-06 eta: 6:42:21 time: 0.3175 data_time: 0.1124 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 07:17:20 - mmengine - INFO - Epoch(train) [5][17700/42151] lr: 3.0000e-06 eta: 6:41:44 time: 0.3101 data_time: 0.1120 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 07:17:54 - mmengine - INFO - Epoch(train) [5][17800/42151] lr: 3.0000e-06 eta: 6:41:07 time: 0.3153 data_time: 0.1130 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 07:18:29 - mmengine - INFO - Epoch(train) [5][17900/42151] lr: 3.0000e-06 eta: 6:40:30 time: 0.3392 data_time: 0.1090 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:19:03 - mmengine - INFO - Epoch(train) [5][18000/42151] lr: 3.0000e-06 eta: 6:39:53 time: 0.3221 data_time: 0.0960 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:19:38 - mmengine - INFO - Epoch(train) [5][18100/42151] lr: 3.0000e-06 eta: 6:39:16 time: 0.3813 data_time: 0.1523 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 07:20:12 - mmengine - INFO - Epoch(train) [5][18200/42151] lr: 3.0000e-06 eta: 6:38:39 time: 0.3116 data_time: 0.1103 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 07:20:47 - mmengine - INFO - Epoch(train) [5][18300/42151] lr: 3.0000e-06 eta: 6:38:03 time: 0.3189 data_time: 0.1148 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 07:21:20 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:21:21 - mmengine - INFO - Epoch(train) [5][18400/42151] lr: 3.0000e-06 eta: 6:37:26 time: 0.3180 data_time: 0.1177 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 07:21:56 - mmengine - INFO - Epoch(train) [5][18500/42151] lr: 3.0000e-06 eta: 6:36:49 time: 0.3627 data_time: 0.1153 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 07:22:30 - mmengine - INFO - Epoch(train) [5][18600/42151] lr: 3.0000e-06 eta: 6:36:12 time: 0.3155 data_time: 0.0914 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 07:23:04 - mmengine - INFO - Epoch(train) [5][18700/42151] lr: 3.0000e-06 eta: 6:35:35 time: 0.3240 data_time: 0.1250 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:23:39 - mmengine - INFO - Epoch(train) [5][18800/42151] lr: 3.0000e-06 eta: 6:34:58 time: 0.3185 data_time: 0.1130 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 07:24:13 - mmengine - INFO - Epoch(train) [5][18900/42151] lr: 3.0000e-06 eta: 6:34:22 time: 0.3117 data_time: 0.1107 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 07:24:48 - mmengine - INFO - Epoch(train) [5][19000/42151] lr: 3.0000e-06 eta: 6:33:45 time: 0.3087 data_time: 0.1069 memory: 7851 loss_ce: 0.0128 loss: 0.0128 2022/09/17 07:25:22 - mmengine - INFO - Epoch(train) [5][19100/42151] lr: 3.0000e-06 eta: 6:33:08 time: 0.3474 data_time: 0.1247 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 07:25:56 - mmengine - INFO - Epoch(train) [5][19200/42151] lr: 3.0000e-06 eta: 6:32:31 time: 0.3146 data_time: 0.0891 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 07:26:31 - mmengine - INFO - Epoch(train) [5][19300/42151] lr: 3.0000e-06 eta: 6:31:55 time: 0.3369 data_time: 0.1299 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 07:27:04 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:27:05 - mmengine - INFO - Epoch(train) [5][19400/42151] lr: 3.0000e-06 eta: 6:31:18 time: 0.3514 data_time: 0.1490 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 07:27:40 - mmengine - INFO - Epoch(train) [5][19500/42151] lr: 3.0000e-06 eta: 6:30:41 time: 0.3175 data_time: 0.1097 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 07:28:15 - mmengine - INFO - Epoch(train) [5][19600/42151] lr: 3.0000e-06 eta: 6:30:04 time: 0.3051 data_time: 0.1001 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 07:28:49 - mmengine - INFO - Epoch(train) [5][19700/42151] lr: 3.0000e-06 eta: 6:29:28 time: 0.3530 data_time: 0.1246 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 07:29:24 - mmengine - INFO - Epoch(train) [5][19800/42151] lr: 3.0000e-06 eta: 6:28:51 time: 0.3195 data_time: 0.0952 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 07:29:58 - mmengine - INFO - Epoch(train) [5][19900/42151] lr: 3.0000e-06 eta: 6:28:14 time: 0.3371 data_time: 0.1233 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 07:30:32 - mmengine - INFO - Epoch(train) [5][20000/42151] lr: 3.0000e-06 eta: 6:27:37 time: 0.3271 data_time: 0.1201 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 07:31:07 - mmengine - INFO - Epoch(train) [5][20100/42151] lr: 3.0000e-06 eta: 6:27:00 time: 0.3327 data_time: 0.1299 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 07:31:42 - mmengine - INFO - Epoch(train) [5][20200/42151] lr: 3.0000e-06 eta: 6:26:24 time: 0.3085 data_time: 0.1056 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 07:32:16 - mmengine - INFO - Epoch(train) [5][20300/42151] lr: 3.0000e-06 eta: 6:25:47 time: 0.3428 data_time: 0.1158 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 07:32:50 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:32:51 - mmengine - INFO - Epoch(train) [5][20400/42151] lr: 3.0000e-06 eta: 6:25:10 time: 0.3280 data_time: 0.1001 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 07:33:26 - mmengine - INFO - Epoch(train) [5][20500/42151] lr: 3.0000e-06 eta: 6:24:34 time: 0.3546 data_time: 0.1454 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:34:01 - mmengine - INFO - Epoch(train) [5][20600/42151] lr: 3.0000e-06 eta: 6:23:57 time: 0.3198 data_time: 0.1186 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:34:35 - mmengine - INFO - Epoch(train) [5][20700/42151] lr: 3.0000e-06 eta: 6:23:20 time: 0.3135 data_time: 0.1124 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 07:35:09 - mmengine - INFO - Epoch(train) [5][20800/42151] lr: 3.0000e-06 eta: 6:22:44 time: 0.3139 data_time: 0.1130 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 07:35:44 - mmengine - INFO - Epoch(train) [5][20900/42151] lr: 3.0000e-06 eta: 6:22:07 time: 0.3397 data_time: 0.1172 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 07:36:18 - mmengine - INFO - Epoch(train) [5][21000/42151] lr: 3.0000e-06 eta: 6:21:30 time: 0.3098 data_time: 0.0832 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 07:36:53 - mmengine - INFO - Epoch(train) [5][21100/42151] lr: 3.0000e-06 eta: 6:20:53 time: 0.3333 data_time: 0.1301 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 07:37:28 - mmengine - INFO - Epoch(train) [5][21200/42151] lr: 3.0000e-06 eta: 6:20:17 time: 0.3166 data_time: 0.1144 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 07:38:03 - mmengine - INFO - Epoch(train) [5][21300/42151] lr: 3.0000e-06 eta: 6:19:40 time: 0.3191 data_time: 0.1154 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 07:38:37 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:38:38 - mmengine - INFO - Epoch(train) [5][21400/42151] lr: 3.0000e-06 eta: 6:19:04 time: 0.3240 data_time: 0.1204 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 07:39:13 - mmengine - INFO - Epoch(train) [5][21500/42151] lr: 3.0000e-06 eta: 6:18:27 time: 0.3397 data_time: 0.1183 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:39:48 - mmengine - INFO - Epoch(train) [5][21600/42151] lr: 3.0000e-06 eta: 6:17:50 time: 0.3507 data_time: 0.1223 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 07:40:23 - mmengine - INFO - Epoch(train) [5][21700/42151] lr: 3.0000e-06 eta: 6:17:14 time: 0.3207 data_time: 0.1181 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 07:40:58 - mmengine - INFO - Epoch(train) [5][21800/42151] lr: 3.0000e-06 eta: 6:16:38 time: 0.3355 data_time: 0.1179 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 07:41:33 - mmengine - INFO - Epoch(train) [5][21900/42151] lr: 3.0000e-06 eta: 6:16:01 time: 0.3257 data_time: 0.1199 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 07:42:07 - mmengine - INFO - Epoch(train) [5][22000/42151] lr: 3.0000e-06 eta: 6:15:24 time: 0.3016 data_time: 0.1010 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:42:42 - mmengine - INFO - Epoch(train) [5][22100/42151] lr: 3.0000e-06 eta: 6:14:47 time: 0.3391 data_time: 0.1162 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 07:43:16 - mmengine - INFO - Epoch(train) [5][22200/42151] lr: 3.0000e-06 eta: 6:14:11 time: 0.3322 data_time: 0.1112 memory: 7851 loss_ce: 0.0124 loss: 0.0124 2022/09/17 07:43:51 - mmengine - INFO - Epoch(train) [5][22300/42151] lr: 3.0000e-06 eta: 6:13:34 time: 0.3109 data_time: 0.1115 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 07:44:24 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:44:25 - mmengine - INFO - Epoch(train) [5][22400/42151] lr: 3.0000e-06 eta: 6:12:57 time: 0.3394 data_time: 0.1342 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 07:45:00 - mmengine - INFO - Epoch(train) [5][22500/42151] lr: 3.0000e-06 eta: 6:12:21 time: 0.3380 data_time: 0.1146 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:45:34 - mmengine - INFO - Epoch(train) [5][22600/42151] lr: 3.0000e-06 eta: 6:11:44 time: 0.3155 data_time: 0.1147 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 07:46:09 - mmengine - INFO - Epoch(train) [5][22700/42151] lr: 3.0000e-06 eta: 6:11:07 time: 0.3440 data_time: 0.1095 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 07:46:43 - mmengine - INFO - Epoch(train) [5][22800/42151] lr: 3.0000e-06 eta: 6:10:30 time: 0.3203 data_time: 0.0915 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 07:47:17 - mmengine - INFO - Epoch(train) [5][22900/42151] lr: 3.0000e-06 eta: 6:09:54 time: 0.3147 data_time: 0.1100 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 07:47:52 - mmengine - INFO - Epoch(train) [5][23000/42151] lr: 3.0000e-06 eta: 6:09:17 time: 0.3352 data_time: 0.1311 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 07:48:27 - mmengine - INFO - Epoch(train) [5][23100/42151] lr: 3.0000e-06 eta: 6:08:40 time: 0.3096 data_time: 0.1070 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 07:49:01 - mmengine - INFO - Epoch(train) [5][23200/42151] lr: 3.0000e-06 eta: 6:08:04 time: 0.3383 data_time: 0.1119 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 07:49:35 - mmengine - INFO - Epoch(train) [5][23300/42151] lr: 3.0000e-06 eta: 6:07:27 time: 0.3457 data_time: 0.1211 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 07:50:08 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:50:09 - mmengine - INFO - Epoch(train) [5][23400/42151] lr: 3.0000e-06 eta: 6:06:50 time: 0.3689 data_time: 0.1320 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 07:50:43 - mmengine - INFO - Epoch(train) [5][23500/42151] lr: 3.0000e-06 eta: 6:06:13 time: 0.3159 data_time: 0.1123 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 07:51:18 - mmengine - INFO - Epoch(train) [5][23600/42151] lr: 3.0000e-06 eta: 6:05:36 time: 0.3197 data_time: 0.1131 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 07:51:52 - mmengine - INFO - Epoch(train) [5][23700/42151] lr: 3.0000e-06 eta: 6:05:00 time: 0.3246 data_time: 0.1249 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:52:27 - mmengine - INFO - Epoch(train) [5][23800/42151] lr: 3.0000e-06 eta: 6:04:23 time: 0.3313 data_time: 0.1313 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 07:53:01 - mmengine - INFO - Epoch(train) [5][23900/42151] lr: 3.0000e-06 eta: 6:03:46 time: 0.3625 data_time: 0.1198 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 07:53:36 - mmengine - INFO - Epoch(train) [5][24000/42151] lr: 3.0000e-06 eta: 6:03:10 time: 0.3183 data_time: 0.0946 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 07:54:10 - mmengine - INFO - Epoch(train) [5][24100/42151] lr: 3.0000e-06 eta: 6:02:33 time: 0.3331 data_time: 0.1225 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 07:54:45 - mmengine - INFO - Epoch(train) [5][24200/42151] lr: 3.0000e-06 eta: 6:01:57 time: 0.3231 data_time: 0.1211 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 07:55:20 - mmengine - INFO - Epoch(train) [5][24300/42151] lr: 3.0000e-06 eta: 6:01:20 time: 0.3036 data_time: 0.0975 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 07:55:53 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 07:55:55 - mmengine - INFO - Epoch(train) [5][24400/42151] lr: 3.0000e-06 eta: 6:00:44 time: 0.3430 data_time: 0.1393 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 07:56:30 - mmengine - INFO - Epoch(train) [5][24500/42151] lr: 3.0000e-06 eta: 6:00:07 time: 0.3562 data_time: 0.1072 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 07:57:03 - mmengine - INFO - Epoch(train) [5][24600/42151] lr: 3.0000e-06 eta: 5:59:30 time: 0.3193 data_time: 0.0912 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 07:57:38 - mmengine - INFO - Epoch(train) [5][24700/42151] lr: 3.0000e-06 eta: 5:58:53 time: 0.3095 data_time: 0.1079 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 07:58:12 - mmengine - INFO - Epoch(train) [5][24800/42151] lr: 3.0000e-06 eta: 5:58:17 time: 0.3316 data_time: 0.1266 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 07:58:47 - mmengine - INFO - Epoch(train) [5][24900/42151] lr: 3.0000e-06 eta: 5:57:40 time: 0.3319 data_time: 0.1223 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 07:59:21 - mmengine - INFO - Epoch(train) [5][25000/42151] lr: 3.0000e-06 eta: 5:57:03 time: 0.3556 data_time: 0.1503 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 07:59:56 - mmengine - INFO - Epoch(train) [5][25100/42151] lr: 3.0000e-06 eta: 5:56:27 time: 0.3349 data_time: 0.1098 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 08:00:30 - mmengine - INFO - Epoch(train) [5][25200/42151] lr: 3.0000e-06 eta: 5:55:50 time: 0.3554 data_time: 0.1102 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 08:01:05 - mmengine - INFO - Epoch(train) [5][25300/42151] lr: 3.0000e-06 eta: 5:55:14 time: 0.3233 data_time: 0.1184 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 08:01:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:01:39 - mmengine - INFO - Epoch(train) [5][25400/42151] lr: 3.0000e-06 eta: 5:54:37 time: 0.3351 data_time: 0.1313 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 08:02:14 - mmengine - INFO - Epoch(train) [5][25500/42151] lr: 3.0000e-06 eta: 5:54:00 time: 0.3009 data_time: 0.0996 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 08:02:49 - mmengine - INFO - Epoch(train) [5][25600/42151] lr: 3.0000e-06 eta: 5:53:24 time: 0.3231 data_time: 0.1173 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 08:03:24 - mmengine - INFO - Epoch(train) [5][25700/42151] lr: 3.0000e-06 eta: 5:52:47 time: 0.3289 data_time: 0.1079 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 08:03:58 - mmengine - INFO - Epoch(train) [5][25800/42151] lr: 3.0000e-06 eta: 5:52:11 time: 0.3452 data_time: 0.1190 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:04:33 - mmengine - INFO - Epoch(train) [5][25900/42151] lr: 3.0000e-06 eta: 5:51:34 time: 0.3440 data_time: 0.1292 memory: 7851 loss_ce: 0.0177 loss: 0.0177 2022/09/17 08:05:07 - mmengine - INFO - Epoch(train) [5][26000/42151] lr: 3.0000e-06 eta: 5:50:57 time: 0.3101 data_time: 0.1089 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 08:05:42 - mmengine - INFO - Epoch(train) [5][26100/42151] lr: 3.0000e-06 eta: 5:50:21 time: 0.3096 data_time: 0.0996 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 08:06:16 - mmengine - INFO - Epoch(train) [5][26200/42151] lr: 3.0000e-06 eta: 5:49:44 time: 0.3006 data_time: 0.1007 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 08:06:51 - mmengine - INFO - Epoch(train) [5][26300/42151] lr: 3.0000e-06 eta: 5:49:08 time: 0.3547 data_time: 0.1086 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:07:25 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:07:26 - mmengine - INFO - Epoch(train) [5][26400/42151] lr: 3.0000e-06 eta: 5:48:31 time: 0.3718 data_time: 0.1275 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 08:08:01 - mmengine - INFO - Epoch(train) [5][26500/42151] lr: 3.0000e-06 eta: 5:47:55 time: 0.3257 data_time: 0.1181 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 08:08:35 - mmengine - INFO - Epoch(train) [5][26600/42151] lr: 3.0000e-06 eta: 5:47:18 time: 0.3164 data_time: 0.1125 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 08:09:10 - mmengine - INFO - Epoch(train) [5][26700/42151] lr: 3.0000e-06 eta: 5:46:42 time: 0.3171 data_time: 0.1130 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 08:09:44 - mmengine - INFO - Epoch(train) [5][26800/42151] lr: 3.0000e-06 eta: 5:46:05 time: 0.2914 data_time: 0.0916 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 08:10:19 - mmengine - INFO - Epoch(train) [5][26900/42151] lr: 3.0000e-06 eta: 5:45:28 time: 0.3574 data_time: 0.1329 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 08:10:53 - mmengine - INFO - Epoch(train) [5][27000/42151] lr: 3.0000e-06 eta: 5:44:51 time: 0.3183 data_time: 0.0929 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:11:27 - mmengine - INFO - Epoch(train) [5][27100/42151] lr: 3.0000e-06 eta: 5:44:15 time: 0.3200 data_time: 0.1134 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:12:01 - mmengine - INFO - Epoch(train) [5][27200/42151] lr: 3.0000e-06 eta: 5:43:38 time: 0.3163 data_time: 0.1123 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 08:12:36 - mmengine - INFO - Epoch(train) [5][27300/42151] lr: 3.0000e-06 eta: 5:43:01 time: 0.3113 data_time: 0.1102 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 08:13:09 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:13:10 - mmengine - INFO - Epoch(train) [5][27400/42151] lr: 3.0000e-06 eta: 5:42:25 time: 0.3093 data_time: 0.1081 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 08:13:45 - mmengine - INFO - Epoch(train) [5][27500/42151] lr: 3.0000e-06 eta: 5:41:48 time: 0.3688 data_time: 0.1231 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 08:14:19 - mmengine - INFO - Epoch(train) [5][27600/42151] lr: 3.0000e-06 eta: 5:41:12 time: 0.3493 data_time: 0.1002 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 08:14:54 - mmengine - INFO - Epoch(train) [5][27700/42151] lr: 3.0000e-06 eta: 5:40:35 time: 0.3325 data_time: 0.1238 memory: 7851 loss_ce: 0.0133 loss: 0.0133 2022/09/17 08:15:29 - mmengine - INFO - Epoch(train) [5][27800/42151] lr: 3.0000e-06 eta: 5:39:59 time: 0.3018 data_time: 0.1016 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 08:16:04 - mmengine - INFO - Epoch(train) [5][27900/42151] lr: 3.0000e-06 eta: 5:39:22 time: 0.3136 data_time: 0.1072 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 08:16:38 - mmengine - INFO - Epoch(train) [5][28000/42151] lr: 3.0000e-06 eta: 5:38:46 time: 0.2980 data_time: 0.0978 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 08:17:12 - mmengine - INFO - Epoch(train) [5][28100/42151] lr: 3.0000e-06 eta: 5:38:09 time: 0.3714 data_time: 0.1438 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 08:17:47 - mmengine - INFO - Epoch(train) [5][28200/42151] lr: 3.0000e-06 eta: 5:37:32 time: 0.3200 data_time: 0.0928 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 08:18:22 - mmengine - INFO - Epoch(train) [5][28300/42151] lr: 3.0000e-06 eta: 5:36:56 time: 0.3389 data_time: 0.1151 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 08:18:55 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:18:57 - mmengine - INFO - Epoch(train) [5][28400/42151] lr: 3.0000e-06 eta: 5:36:19 time: 0.3458 data_time: 0.1451 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 08:19:32 - mmengine - INFO - Epoch(train) [5][28500/42151] lr: 3.0000e-06 eta: 5:35:43 time: 0.3233 data_time: 0.1067 memory: 7851 loss_ce: 0.0180 loss: 0.0180 2022/09/17 08:20:06 - mmengine - INFO - Epoch(train) [5][28600/42151] lr: 3.0000e-06 eta: 5:35:07 time: 0.2959 data_time: 0.0935 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 08:20:41 - mmengine - INFO - Epoch(train) [5][28700/42151] lr: 3.0000e-06 eta: 5:34:30 time: 0.3501 data_time: 0.1268 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:21:15 - mmengine - INFO - Epoch(train) [5][28800/42151] lr: 3.0000e-06 eta: 5:33:53 time: 0.3249 data_time: 0.0996 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 08:21:49 - mmengine - INFO - Epoch(train) [5][28900/42151] lr: 3.0000e-06 eta: 5:33:17 time: 0.3181 data_time: 0.1167 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 08:22:23 - mmengine - INFO - Epoch(train) [5][29000/42151] lr: 3.0000e-06 eta: 5:32:40 time: 0.3215 data_time: 0.1124 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:22:58 - mmengine - INFO - Epoch(train) [5][29100/42151] lr: 3.0000e-06 eta: 5:32:03 time: 0.3067 data_time: 0.1083 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:23:31 - mmengine - INFO - Epoch(train) [5][29200/42151] lr: 3.0000e-06 eta: 5:31:27 time: 0.3035 data_time: 0.0947 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 08:24:07 - mmengine - INFO - Epoch(train) [5][29300/42151] lr: 3.0000e-06 eta: 5:30:50 time: 0.3627 data_time: 0.1311 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 08:24:40 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:24:41 - mmengine - INFO - Epoch(train) [5][29400/42151] lr: 3.0000e-06 eta: 5:30:14 time: 0.3306 data_time: 0.1047 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 08:25:16 - mmengine - INFO - Epoch(train) [5][29500/42151] lr: 3.0000e-06 eta: 5:29:37 time: 0.3201 data_time: 0.1191 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 08:25:50 - mmengine - INFO - Epoch(train) [5][29600/42151] lr: 3.0000e-06 eta: 5:29:01 time: 0.3074 data_time: 0.1054 memory: 7851 loss_ce: 0.0178 loss: 0.0178 2022/09/17 08:26:24 - mmengine - INFO - Epoch(train) [5][29700/42151] lr: 3.0000e-06 eta: 5:28:24 time: 0.3316 data_time: 0.1272 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 08:26:59 - mmengine - INFO - Epoch(train) [5][29800/42151] lr: 3.0000e-06 eta: 5:27:48 time: 0.3254 data_time: 0.1209 memory: 7851 loss_ce: 0.0128 loss: 0.0128 2022/09/17 08:27:34 - mmengine - INFO - Epoch(train) [5][29900/42151] lr: 3.0000e-06 eta: 5:27:11 time: 0.3572 data_time: 0.1287 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 08:28:08 - mmengine - INFO - Epoch(train) [5][30000/42151] lr: 3.0000e-06 eta: 5:26:35 time: 0.3223 data_time: 0.0909 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 08:28:43 - mmengine - INFO - Epoch(train) [5][30100/42151] lr: 3.0000e-06 eta: 5:25:58 time: 0.3080 data_time: 0.1054 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 08:29:17 - mmengine - INFO - Epoch(train) [5][30200/42151] lr: 3.0000e-06 eta: 5:25:22 time: 0.3174 data_time: 0.1080 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 08:29:53 - mmengine - INFO - Epoch(train) [5][30300/42151] lr: 3.0000e-06 eta: 5:24:45 time: 0.3032 data_time: 0.0970 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 08:30:26 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:30:28 - mmengine - INFO - Epoch(train) [5][30400/42151] lr: 3.0000e-06 eta: 5:24:09 time: 0.3349 data_time: 0.1279 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 08:31:02 - mmengine - INFO - Epoch(train) [5][30500/42151] lr: 3.0000e-06 eta: 5:23:32 time: 0.3403 data_time: 0.1179 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:31:36 - mmengine - INFO - Epoch(train) [5][30600/42151] lr: 3.0000e-06 eta: 5:22:56 time: 0.3120 data_time: 0.0895 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:32:11 - mmengine - INFO - Epoch(train) [5][30700/42151] lr: 3.0000e-06 eta: 5:22:19 time: 0.3329 data_time: 0.1295 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 08:32:46 - mmengine - INFO - Epoch(train) [5][30800/42151] lr: 3.0000e-06 eta: 5:21:43 time: 0.3233 data_time: 0.1234 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 08:33:21 - mmengine - INFO - Epoch(train) [5][30900/42151] lr: 3.0000e-06 eta: 5:21:06 time: 0.2985 data_time: 0.1006 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:33:56 - mmengine - INFO - Epoch(train) [5][31000/42151] lr: 3.0000e-06 eta: 5:20:30 time: 0.3278 data_time: 0.1148 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:34:30 - mmengine - INFO - Epoch(train) [5][31100/42151] lr: 3.0000e-06 eta: 5:19:53 time: 0.3527 data_time: 0.1182 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 08:35:04 - mmengine - INFO - Epoch(train) [5][31200/42151] lr: 3.0000e-06 eta: 5:19:17 time: 0.3240 data_time: 0.0959 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 08:35:39 - mmengine - INFO - Epoch(train) [5][31300/42151] lr: 3.0000e-06 eta: 5:18:40 time: 0.3071 data_time: 0.1063 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 08:36:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:36:14 - mmengine - INFO - Epoch(train) [5][31400/42151] lr: 3.0000e-06 eta: 5:18:04 time: 0.3783 data_time: 0.1405 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 08:36:49 - mmengine - INFO - Epoch(train) [5][31500/42151] lr: 3.0000e-06 eta: 5:17:28 time: 0.3120 data_time: 0.1055 memory: 7851 loss_ce: 0.0179 loss: 0.0179 2022/09/17 08:37:23 - mmengine - INFO - Epoch(train) [5][31600/42151] lr: 3.0000e-06 eta: 5:16:51 time: 0.3213 data_time: 0.1107 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 08:37:58 - mmengine - INFO - Epoch(train) [5][31700/42151] lr: 3.0000e-06 eta: 5:16:15 time: 0.3385 data_time: 0.1145 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 08:38:32 - mmengine - INFO - Epoch(train) [5][31800/42151] lr: 3.0000e-06 eta: 5:15:38 time: 0.3289 data_time: 0.0982 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 08:39:07 - mmengine - INFO - Epoch(train) [5][31900/42151] lr: 3.0000e-06 eta: 5:15:02 time: 0.3202 data_time: 0.1135 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 08:39:41 - mmengine - INFO - Epoch(train) [5][32000/42151] lr: 3.0000e-06 eta: 5:14:25 time: 0.3075 data_time: 0.1041 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 08:40:15 - mmengine - INFO - Epoch(train) [5][32100/42151] lr: 3.0000e-06 eta: 5:13:48 time: 0.3183 data_time: 0.0941 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:40:50 - mmengine - INFO - Epoch(train) [5][32200/42151] lr: 3.0000e-06 eta: 5:13:12 time: 0.3239 data_time: 0.1160 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 08:41:24 - mmengine - INFO - Epoch(train) [5][32300/42151] lr: 3.0000e-06 eta: 5:12:35 time: 0.3320 data_time: 0.1072 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 08:41:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:41:59 - mmengine - INFO - Epoch(train) [5][32400/42151] lr: 3.0000e-06 eta: 5:11:59 time: 0.3357 data_time: 0.1107 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 08:42:34 - mmengine - INFO - Epoch(train) [5][32500/42151] lr: 3.0000e-06 eta: 5:11:23 time: 0.3229 data_time: 0.1162 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 08:43:08 - mmengine - INFO - Epoch(train) [5][32600/42151] lr: 3.0000e-06 eta: 5:10:46 time: 0.3111 data_time: 0.1097 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 08:43:42 - mmengine - INFO - Epoch(train) [5][32700/42151] lr: 3.0000e-06 eta: 5:10:09 time: 0.3064 data_time: 0.1050 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 08:44:16 - mmengine - INFO - Epoch(train) [5][32800/42151] lr: 3.0000e-06 eta: 5:09:33 time: 0.3134 data_time: 0.1047 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 08:44:51 - mmengine - INFO - Epoch(train) [5][32900/42151] lr: 3.0000e-06 eta: 5:08:56 time: 0.3345 data_time: 0.1097 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 08:45:25 - mmengine - INFO - Epoch(train) [5][33000/42151] lr: 3.0000e-06 eta: 5:08:20 time: 0.3384 data_time: 0.0828 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 08:45:58 - mmengine - INFO - Epoch(train) [5][33100/42151] lr: 3.0000e-06 eta: 5:07:43 time: 0.3222 data_time: 0.1176 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 08:46:32 - mmengine - INFO - Epoch(train) [5][33200/42151] lr: 3.0000e-06 eta: 5:07:06 time: 0.3131 data_time: 0.1098 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 08:47:06 - mmengine - INFO - Epoch(train) [5][33300/42151] lr: 3.0000e-06 eta: 5:06:30 time: 0.3262 data_time: 0.1253 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:47:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:47:40 - mmengine - INFO - Epoch(train) [5][33400/42151] lr: 3.0000e-06 eta: 5:05:53 time: 0.3613 data_time: 0.1325 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 08:48:15 - mmengine - INFO - Epoch(train) [5][33500/42151] lr: 3.0000e-06 eta: 5:05:17 time: 0.3426 data_time: 0.1187 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 08:48:49 - mmengine - INFO - Epoch(train) [5][33600/42151] lr: 3.0000e-06 eta: 5:04:40 time: 0.3267 data_time: 0.0927 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 08:49:24 - mmengine - INFO - Epoch(train) [5][33700/42151] lr: 3.0000e-06 eta: 5:04:04 time: 0.3317 data_time: 0.1298 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 08:49:58 - mmengine - INFO - Epoch(train) [5][33800/42151] lr: 3.0000e-06 eta: 5:03:28 time: 0.3169 data_time: 0.1053 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 08:50:33 - mmengine - INFO - Epoch(train) [5][33900/42151] lr: 3.0000e-06 eta: 5:02:51 time: 0.2935 data_time: 0.0930 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 08:51:07 - mmengine - INFO - Epoch(train) [5][34000/42151] lr: 3.0000e-06 eta: 5:02:14 time: 0.3301 data_time: 0.1237 memory: 7851 loss_ce: 0.0191 loss: 0.0191 2022/09/17 08:51:42 - mmengine - INFO - Epoch(train) [5][34100/42151] lr: 3.0000e-06 eta: 5:01:38 time: 0.3509 data_time: 0.1263 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 08:52:15 - mmengine - INFO - Epoch(train) [5][34200/42151] lr: 3.0000e-06 eta: 5:01:01 time: 0.3362 data_time: 0.0940 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 08:52:50 - mmengine - INFO - Epoch(train) [5][34300/42151] lr: 3.0000e-06 eta: 5:00:25 time: 0.3093 data_time: 0.1086 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 08:53:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:53:24 - mmengine - INFO - Epoch(train) [5][34400/42151] lr: 3.0000e-06 eta: 4:59:48 time: 0.3233 data_time: 0.1204 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 08:53:58 - mmengine - INFO - Epoch(train) [5][34500/42151] lr: 3.0000e-06 eta: 4:59:12 time: 0.2991 data_time: 0.0966 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 08:54:32 - mmengine - INFO - Epoch(train) [5][34600/42151] lr: 3.0000e-06 eta: 4:58:35 time: 0.2955 data_time: 0.0954 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 08:55:07 - mmengine - INFO - Epoch(train) [5][34700/42151] lr: 3.0000e-06 eta: 4:57:59 time: 0.3470 data_time: 0.1174 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 08:55:41 - mmengine - INFO - Epoch(train) [5][34800/42151] lr: 3.0000e-06 eta: 4:57:22 time: 0.3377 data_time: 0.1103 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 08:56:15 - mmengine - INFO - Epoch(train) [5][34900/42151] lr: 3.0000e-06 eta: 4:56:46 time: 0.3195 data_time: 0.1100 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 08:56:49 - mmengine - INFO - Epoch(train) [5][35000/42151] lr: 3.0000e-06 eta: 4:56:09 time: 0.3126 data_time: 0.1072 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 08:57:23 - mmengine - INFO - Epoch(train) [5][35100/42151] lr: 3.0000e-06 eta: 4:55:33 time: 0.3047 data_time: 0.1001 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 08:57:57 - mmengine - INFO - Epoch(train) [5][35200/42151] lr: 3.0000e-06 eta: 4:54:56 time: 0.3142 data_time: 0.0946 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 08:58:31 - mmengine - INFO - Epoch(train) [5][35300/42151] lr: 3.0000e-06 eta: 4:54:20 time: 0.3348 data_time: 0.1158 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 08:59:04 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 08:59:05 - mmengine - INFO - Epoch(train) [5][35400/42151] lr: 3.0000e-06 eta: 4:53:43 time: 0.3326 data_time: 0.1024 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 08:59:39 - mmengine - INFO - Epoch(train) [5][35500/42151] lr: 3.0000e-06 eta: 4:53:07 time: 0.3169 data_time: 0.1129 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 09:00:13 - mmengine - INFO - Epoch(train) [5][35600/42151] lr: 3.0000e-06 eta: 4:52:30 time: 0.3213 data_time: 0.1167 memory: 7851 loss_ce: 0.0173 loss: 0.0173 2022/09/17 09:00:47 - mmengine - INFO - Epoch(train) [5][35700/42151] lr: 3.0000e-06 eta: 4:51:53 time: 0.3173 data_time: 0.1026 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 09:01:20 - mmengine - INFO - Epoch(train) [5][35800/42151] lr: 3.0000e-06 eta: 4:51:17 time: 0.3028 data_time: 0.0962 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 09:01:55 - mmengine - INFO - Epoch(train) [5][35900/42151] lr: 3.0000e-06 eta: 4:50:41 time: 0.3523 data_time: 0.1185 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 09:02:29 - mmengine - INFO - Epoch(train) [5][36000/42151] lr: 3.0000e-06 eta: 4:50:04 time: 0.3149 data_time: 0.0886 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 09:03:04 - mmengine - INFO - Epoch(train) [5][36100/42151] lr: 3.0000e-06 eta: 4:49:28 time: 0.3255 data_time: 0.1221 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 09:03:38 - mmengine - INFO - Epoch(train) [5][36200/42151] lr: 3.0000e-06 eta: 4:48:51 time: 0.3304 data_time: 0.1260 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 09:04:12 - mmengine - INFO - Epoch(train) [5][36300/42151] lr: 3.0000e-06 eta: 4:48:15 time: 0.3194 data_time: 0.1196 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 09:04:45 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:04:46 - mmengine - INFO - Epoch(train) [5][36400/42151] lr: 3.0000e-06 eta: 4:47:38 time: 0.3286 data_time: 0.1185 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 09:05:20 - mmengine - INFO - Epoch(train) [5][36500/42151] lr: 3.0000e-06 eta: 4:47:02 time: 0.3299 data_time: 0.1082 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 09:05:54 - mmengine - INFO - Epoch(train) [5][36600/42151] lr: 3.0000e-06 eta: 4:46:25 time: 0.3247 data_time: 0.1007 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 09:06:28 - mmengine - INFO - Epoch(train) [5][36700/42151] lr: 3.0000e-06 eta: 4:45:49 time: 0.3158 data_time: 0.1146 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 09:07:02 - mmengine - INFO - Epoch(train) [5][36800/42151] lr: 3.0000e-06 eta: 4:45:12 time: 0.3027 data_time: 0.1004 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 09:07:36 - mmengine - INFO - Epoch(train) [5][36900/42151] lr: 3.0000e-06 eta: 4:44:36 time: 0.3204 data_time: 0.1146 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 09:08:10 - mmengine - INFO - Epoch(train) [5][37000/42151] lr: 3.0000e-06 eta: 4:43:59 time: 0.3055 data_time: 0.0993 memory: 7851 loss_ce: 0.0127 loss: 0.0127 2022/09/17 09:08:45 - mmengine - INFO - Epoch(train) [5][37100/42151] lr: 3.0000e-06 eta: 4:43:23 time: 0.3451 data_time: 0.1210 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 09:09:18 - mmengine - INFO - Epoch(train) [5][37200/42151] lr: 3.0000e-06 eta: 4:42:46 time: 0.3363 data_time: 0.0989 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 09:09:52 - mmengine - INFO - Epoch(train) [5][37300/42151] lr: 3.0000e-06 eta: 4:42:10 time: 0.3202 data_time: 0.1191 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 09:10:25 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:10:26 - mmengine - INFO - Epoch(train) [5][37400/42151] lr: 3.0000e-06 eta: 4:41:33 time: 0.3117 data_time: 0.1069 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 09:11:00 - mmengine - INFO - Epoch(train) [5][37500/42151] lr: 3.0000e-06 eta: 4:40:57 time: 0.3245 data_time: 0.1165 memory: 7851 loss_ce: 0.0171 loss: 0.0171 2022/09/17 09:11:34 - mmengine - INFO - Epoch(train) [5][37600/42151] lr: 3.0000e-06 eta: 4:40:20 time: 0.3192 data_time: 0.1147 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 09:12:09 - mmengine - INFO - Epoch(train) [5][37700/42151] lr: 3.0000e-06 eta: 4:39:44 time: 0.3774 data_time: 0.1491 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 09:12:43 - mmengine - INFO - Epoch(train) [5][37800/42151] lr: 3.0000e-06 eta: 4:39:07 time: 0.3278 data_time: 0.0824 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 09:13:18 - mmengine - INFO - Epoch(train) [5][37900/42151] lr: 3.0000e-06 eta: 4:38:31 time: 0.3299 data_time: 0.1196 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 09:13:52 - mmengine - INFO - Epoch(train) [5][38000/42151] lr: 3.0000e-06 eta: 4:37:55 time: 0.3169 data_time: 0.1179 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 09:14:26 - mmengine - INFO - Epoch(train) [5][38100/42151] lr: 3.0000e-06 eta: 4:37:18 time: 0.3088 data_time: 0.1083 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 09:15:01 - mmengine - INFO - Epoch(train) [5][38200/42151] lr: 3.0000e-06 eta: 4:36:42 time: 0.3225 data_time: 0.1202 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 09:15:36 - mmengine - INFO - Epoch(train) [5][38300/42151] lr: 3.0000e-06 eta: 4:36:06 time: 0.3263 data_time: 0.1054 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 09:16:09 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:16:10 - mmengine - INFO - Epoch(train) [5][38400/42151] lr: 3.0000e-06 eta: 4:35:29 time: 0.3230 data_time: 0.0947 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 09:16:44 - mmengine - INFO - Epoch(train) [5][38500/42151] lr: 3.0000e-06 eta: 4:34:53 time: 0.3354 data_time: 0.1264 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 09:17:18 - mmengine - INFO - Epoch(train) [5][38600/42151] lr: 3.0000e-06 eta: 4:34:16 time: 0.3092 data_time: 0.1050 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 09:17:53 - mmengine - INFO - Epoch(train) [5][38700/42151] lr: 3.0000e-06 eta: 4:33:40 time: 0.3172 data_time: 0.1166 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 09:18:27 - mmengine - INFO - Epoch(train) [5][38800/42151] lr: 3.0000e-06 eta: 4:33:04 time: 0.3351 data_time: 0.1364 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 09:19:02 - mmengine - INFO - Epoch(train) [5][38900/42151] lr: 3.0000e-06 eta: 4:32:27 time: 0.3508 data_time: 0.1221 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 09:19:36 - mmengine - INFO - Epoch(train) [5][39000/42151] lr: 3.0000e-06 eta: 4:31:51 time: 0.3061 data_time: 0.0817 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 09:20:10 - mmengine - INFO - Epoch(train) [5][39100/42151] lr: 3.0000e-06 eta: 4:31:14 time: 0.3213 data_time: 0.1171 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 09:20:44 - mmengine - INFO - Epoch(train) [5][39200/42151] lr: 3.0000e-06 eta: 4:30:38 time: 0.3093 data_time: 0.1077 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 09:21:19 - mmengine - INFO - Epoch(train) [5][39300/42151] lr: 3.0000e-06 eta: 4:30:02 time: 0.3097 data_time: 0.1077 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 09:21:52 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:21:54 - mmengine - INFO - Epoch(train) [5][39400/42151] lr: 3.0000e-06 eta: 4:29:25 time: 0.3379 data_time: 0.1349 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 09:22:29 - mmengine - INFO - Epoch(train) [5][39500/42151] lr: 3.0000e-06 eta: 4:28:49 time: 0.3549 data_time: 0.1206 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 09:23:03 - mmengine - INFO - Epoch(train) [5][39600/42151] lr: 3.0000e-06 eta: 4:28:13 time: 0.3141 data_time: 0.0916 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 09:23:38 - mmengine - INFO - Epoch(train) [5][39700/42151] lr: 3.0000e-06 eta: 4:27:36 time: 0.3203 data_time: 0.1102 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 09:24:12 - mmengine - INFO - Epoch(train) [5][39800/42151] lr: 3.0000e-06 eta: 4:27:00 time: 0.3088 data_time: 0.1078 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 09:24:47 - mmengine - INFO - Epoch(train) [5][39900/42151] lr: 3.0000e-06 eta: 4:26:24 time: 0.3251 data_time: 0.1128 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 09:25:21 - mmengine - INFO - Epoch(train) [5][40000/42151] lr: 3.0000e-06 eta: 4:25:47 time: 0.3230 data_time: 0.1185 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 09:25:56 - mmengine - INFO - Epoch(train) [5][40100/42151] lr: 3.0000e-06 eta: 4:25:11 time: 0.3439 data_time: 0.1171 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 09:26:30 - mmengine - INFO - Epoch(train) [5][40200/42151] lr: 3.0000e-06 eta: 4:24:35 time: 0.3213 data_time: 0.0871 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 09:27:05 - mmengine - INFO - Epoch(train) [5][40300/42151] lr: 3.0000e-06 eta: 4:23:59 time: 0.3308 data_time: 0.1223 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 09:27:38 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:27:40 - mmengine - INFO - Epoch(train) [5][40400/42151] lr: 3.0000e-06 eta: 4:23:22 time: 0.3408 data_time: 0.1266 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 09:28:14 - mmengine - INFO - Epoch(train) [5][40500/42151] lr: 3.0000e-06 eta: 4:22:46 time: 0.3105 data_time: 0.1095 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 09:28:49 - mmengine - INFO - Epoch(train) [5][40600/42151] lr: 3.0000e-06 eta: 4:22:10 time: 0.3320 data_time: 0.1250 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 09:29:23 - mmengine - INFO - Epoch(train) [5][40700/42151] lr: 3.0000e-06 eta: 4:21:33 time: 0.3483 data_time: 0.1200 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 09:29:57 - mmengine - INFO - Epoch(train) [5][40800/42151] lr: 3.0000e-06 eta: 4:20:57 time: 0.3080 data_time: 0.0813 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 09:30:31 - mmengine - INFO - Epoch(train) [5][40900/42151] lr: 3.0000e-06 eta: 4:20:20 time: 0.3072 data_time: 0.1046 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 09:31:05 - mmengine - INFO - Epoch(train) [5][41000/42151] lr: 3.0000e-06 eta: 4:19:44 time: 0.3078 data_time: 0.1100 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 09:31:40 - mmengine - INFO - Epoch(train) [5][41100/42151] lr: 3.0000e-06 eta: 4:19:08 time: 0.3435 data_time: 0.1412 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 09:32:14 - mmengine - INFO - Epoch(train) [5][41200/42151] lr: 3.0000e-06 eta: 4:18:31 time: 0.3031 data_time: 0.0929 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 09:32:49 - mmengine - INFO - Epoch(train) [5][41300/42151] lr: 3.0000e-06 eta: 4:17:55 time: 0.3642 data_time: 0.1224 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 09:33:21 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:33:23 - mmengine - INFO - Epoch(train) [5][41400/42151] lr: 3.0000e-06 eta: 4:17:19 time: 0.3297 data_time: 0.1010 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 09:33:57 - mmengine - INFO - Epoch(train) [5][41500/42151] lr: 3.0000e-06 eta: 4:16:42 time: 0.3069 data_time: 0.1035 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 09:34:31 - mmengine - INFO - Epoch(train) [5][41600/42151] lr: 3.0000e-06 eta: 4:16:06 time: 0.3163 data_time: 0.1138 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 09:35:06 - mmengine - INFO - Epoch(train) [5][41700/42151] lr: 3.0000e-06 eta: 4:15:30 time: 0.3191 data_time: 0.1166 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 09:35:41 - mmengine - INFO - Epoch(train) [5][41800/42151] lr: 3.0000e-06 eta: 4:14:54 time: 0.3401 data_time: 0.1386 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 09:36:15 - mmengine - INFO - Epoch(train) [5][41900/42151] lr: 3.0000e-06 eta: 4:14:17 time: 0.3616 data_time: 0.1358 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 09:36:50 - mmengine - INFO - Epoch(train) [5][42000/42151] lr: 3.0000e-06 eta: 4:13:41 time: 0.3311 data_time: 0.0911 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 09:37:24 - mmengine - INFO - Epoch(train) [5][42100/42151] lr: 3.0000e-06 eta: 4:13:05 time: 0.3012 data_time: 0.1004 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 09:37:39 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 09:37:39 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/09/17 09:38:16 - mmengine - INFO - Epoch(val) [5][100/7672] eta: 0:35:37 time: 0.2822 data_time: 0.0007 memory: 7851 2022/09/17 09:38:48 - mmengine - INFO - Epoch(val) [5][200/7672] eta: 0:41:46 time: 0.3355 data_time: 0.0017 memory: 580 2022/09/17 09:39:24 - mmengine - INFO - Epoch(val) [5][300/7672] eta: 0:24:19 time: 0.1980 data_time: 0.0009 memory: 580 2022/09/17 09:39:45 - mmengine - INFO - Epoch(val) [5][400/7672] eta: 0:24:25 time: 0.2016 data_time: 0.0007 memory: 580 2022/09/17 09:40:05 - mmengine - INFO - Epoch(val) [5][500/7672] eta: 0:24:35 time: 0.2058 data_time: 0.0008 memory: 580 2022/09/17 09:40:26 - mmengine - INFO - Epoch(val) [5][600/7672] eta: 0:24:10 time: 0.2051 data_time: 0.0007 memory: 580 2022/09/17 09:40:47 - mmengine - INFO - Epoch(val) [5][700/7672] eta: 0:24:09 time: 0.2079 data_time: 0.0007 memory: 580 2022/09/17 09:41:08 - mmengine - INFO - Epoch(val) [5][800/7672] eta: 0:24:15 time: 0.2118 data_time: 0.0007 memory: 580 2022/09/17 09:41:29 - mmengine - INFO - Epoch(val) [5][900/7672] eta: 0:23:53 time: 0.2116 data_time: 0.0008 memory: 580 2022/09/17 09:41:50 - mmengine - INFO - Epoch(val) [5][1000/7672] eta: 0:22:43 time: 0.2044 data_time: 0.0011 memory: 580 2022/09/17 09:42:10 - mmengine - INFO - Epoch(val) [5][1100/7672] eta: 0:23:09 time: 0.2114 data_time: 0.0019 memory: 580 2022/09/17 09:42:31 - mmengine - INFO - Epoch(val) [5][1200/7672] eta: 0:24:07 time: 0.2237 data_time: 0.0008 memory: 580 2022/09/17 09:42:51 - mmengine - INFO - Epoch(val) [5][1300/7672] eta: 0:21:00 time: 0.1978 data_time: 0.0008 memory: 580 2022/09/17 09:43:12 - mmengine - INFO - Epoch(val) [5][1400/7672] eta: 0:21:05 time: 0.2018 data_time: 0.0013 memory: 580 2022/09/17 09:43:33 - mmengine - INFO - Epoch(val) [5][1500/7672] eta: 0:21:21 time: 0.2076 data_time: 0.0009 memory: 580 2022/09/17 09:43:54 - mmengine - INFO - Epoch(val) [5][1600/7672] eta: 0:20:21 time: 0.2012 data_time: 0.0010 memory: 580 2022/09/17 09:44:15 - mmengine - INFO - Epoch(val) [5][1700/7672] eta: 0:20:06 time: 0.2019 data_time: 0.0009 memory: 580 2022/09/17 09:44:36 - mmengine - INFO - Epoch(val) [5][1800/7672] eta: 0:19:22 time: 0.1981 data_time: 0.0007 memory: 580 2022/09/17 09:44:57 - mmengine - INFO - Epoch(val) [5][1900/7672] eta: 0:20:03 time: 0.2085 data_time: 0.0008 memory: 580 2022/09/17 09:45:18 - mmengine - INFO - Epoch(val) [5][2000/7672] eta: 0:18:52 time: 0.1996 data_time: 0.0007 memory: 580 2022/09/17 09:45:39 - mmengine - INFO - Epoch(val) [5][2100/7672] eta: 0:18:35 time: 0.2002 data_time: 0.0007 memory: 580 2022/09/17 09:46:00 - mmengine - INFO - Epoch(val) [5][2200/7672] eta: 0:19:12 time: 0.2106 data_time: 0.0008 memory: 580 2022/09/17 09:46:21 - mmengine - INFO - Epoch(val) [5][2300/7672] eta: 0:19:31 time: 0.2181 data_time: 0.0017 memory: 580 2022/09/17 09:46:41 - mmengine - INFO - Epoch(val) [5][2400/7672] eta: 0:18:09 time: 0.2067 data_time: 0.0009 memory: 580 2022/09/17 09:47:01 - mmengine - INFO - Epoch(val) [5][2500/7672] eta: 0:18:42 time: 0.2171 data_time: 0.0017 memory: 580 2022/09/17 09:47:23 - mmengine - INFO - Epoch(val) [5][2600/7672] eta: 0:17:07 time: 0.2027 data_time: 0.0008 memory: 580 2022/09/17 09:47:44 - mmengine - INFO - Epoch(val) [5][2700/7672] eta: 0:16:37 time: 0.2006 data_time: 0.0008 memory: 580 2022/09/17 09:48:05 - mmengine - INFO - Epoch(val) [5][2800/7672] eta: 0:16:09 time: 0.1989 data_time: 0.0007 memory: 580 2022/09/17 09:48:26 - mmengine - INFO - Epoch(val) [5][2900/7672] eta: 0:16:12 time: 0.2038 data_time: 0.0010 memory: 580 2022/09/17 09:48:47 - mmengine - INFO - Epoch(val) [5][3000/7672] eta: 0:16:47 time: 0.2156 data_time: 0.0008 memory: 580 2022/09/17 09:49:07 - mmengine - INFO - Epoch(val) [5][3100/7672] eta: 0:15:18 time: 0.2009 data_time: 0.0007 memory: 580 2022/09/17 09:49:28 - mmengine - INFO - Epoch(val) [5][3200/7672] eta: 0:15:09 time: 0.2033 data_time: 0.0014 memory: 580 2022/09/17 09:49:49 - mmengine - INFO - Epoch(val) [5][3300/7672] eta: 0:14:44 time: 0.2023 data_time: 0.0007 memory: 580 2022/09/17 09:50:10 - mmengine - INFO - Epoch(val) [5][3400/7672] eta: 0:14:43 time: 0.2067 data_time: 0.0007 memory: 580 2022/09/17 09:50:30 - mmengine - INFO - Epoch(val) [5][3500/7672] eta: 0:14:13 time: 0.2045 data_time: 0.0019 memory: 580 2022/09/17 09:50:52 - mmengine - INFO - Epoch(val) [5][3600/7672] eta: 0:14:29 time: 0.2136 data_time: 0.0025 memory: 580 2022/09/17 09:51:12 - mmengine - INFO - Epoch(val) [5][3700/7672] eta: 0:13:55 time: 0.2104 data_time: 0.0019 memory: 580 2022/09/17 09:51:33 - mmengine - INFO - Epoch(val) [5][3800/7672] eta: 0:13:01 time: 0.2018 data_time: 0.0008 memory: 580 2022/09/17 09:51:53 - mmengine - INFO - Epoch(val) [5][3900/7672] eta: 0:12:37 time: 0.2009 data_time: 0.0014 memory: 580 2022/09/17 09:52:14 - mmengine - INFO - Epoch(val) [5][4000/7672] eta: 0:12:22 time: 0.2023 data_time: 0.0008 memory: 580 2022/09/17 09:52:35 - mmengine - INFO - Epoch(val) [5][4100/7672] eta: 0:11:54 time: 0.2000 data_time: 0.0014 memory: 580 2022/09/17 09:52:55 - mmengine - INFO - Epoch(val) [5][4200/7672] eta: 0:11:37 time: 0.2008 data_time: 0.0007 memory: 580 2022/09/17 09:53:15 - mmengine - INFO - Epoch(val) [5][4300/7672] eta: 0:11:13 time: 0.1997 data_time: 0.0009 memory: 580 2022/09/17 09:53:36 - mmengine - INFO - Epoch(val) [5][4400/7672] eta: 0:11:16 time: 0.2068 data_time: 0.0008 memory: 580 2022/09/17 09:53:57 - mmengine - INFO - Epoch(val) [5][4500/7672] eta: 0:10:44 time: 0.2032 data_time: 0.0007 memory: 580 2022/09/17 09:54:17 - mmengine - INFO - Epoch(val) [5][4600/7672] eta: 0:10:29 time: 0.2050 data_time: 0.0008 memory: 580 2022/09/17 09:54:38 - mmengine - INFO - Epoch(val) [5][4700/7672] eta: 0:10:28 time: 0.2113 data_time: 0.0008 memory: 580 2022/09/17 09:54:59 - mmengine - INFO - Epoch(val) [5][4800/7672] eta: 0:10:23 time: 0.2171 data_time: 0.0008 memory: 580 2022/09/17 09:55:20 - mmengine - INFO - Epoch(val) [5][4900/7672] eta: 0:09:25 time: 0.2041 data_time: 0.0008 memory: 580 2022/09/17 09:55:41 - mmengine - INFO - Epoch(val) [5][5000/7672] eta: 0:09:38 time: 0.2165 data_time: 0.0015 memory: 580 2022/09/17 09:56:02 - mmengine - INFO - Epoch(val) [5][5100/7672] eta: 0:08:58 time: 0.2095 data_time: 0.0008 memory: 580 2022/09/17 09:56:23 - mmengine - INFO - Epoch(val) [5][5200/7672] eta: 0:08:22 time: 0.2033 data_time: 0.0008 memory: 580 2022/09/17 09:56:44 - mmengine - INFO - Epoch(val) [5][5300/7672] eta: 0:08:06 time: 0.2053 data_time: 0.0008 memory: 580 2022/09/17 09:57:05 - mmengine - INFO - Epoch(val) [5][5400/7672] eta: 0:07:40 time: 0.2025 data_time: 0.0007 memory: 580 2022/09/17 09:57:25 - mmengine - INFO - Epoch(val) [5][5500/7672] eta: 0:07:22 time: 0.2036 data_time: 0.0009 memory: 580 2022/09/17 09:57:46 - mmengine - INFO - Epoch(val) [5][5600/7672] eta: 0:06:50 time: 0.1980 data_time: 0.0007 memory: 580 2022/09/17 09:58:06 - mmengine - INFO - Epoch(val) [5][5700/7672] eta: 0:06:37 time: 0.2015 data_time: 0.0007 memory: 580 2022/09/17 09:58:27 - mmengine - INFO - Epoch(val) [5][5800/7672] eta: 0:06:17 time: 0.2014 data_time: 0.0007 memory: 580 2022/09/17 09:58:48 - mmengine - INFO - Epoch(val) [5][5900/7672] eta: 0:06:07 time: 0.2073 data_time: 0.0008 memory: 580 2022/09/17 09:59:09 - mmengine - INFO - Epoch(val) [5][6000/7672] eta: 0:05:38 time: 0.2027 data_time: 0.0008 memory: 580 2022/09/17 09:59:29 - mmengine - INFO - Epoch(val) [5][6100/7672] eta: 0:05:13 time: 0.1997 data_time: 0.0008 memory: 580 2022/09/17 09:59:50 - mmengine - INFO - Epoch(val) [5][6200/7672] eta: 0:04:53 time: 0.1994 data_time: 0.0007 memory: 580 2022/09/17 10:00:11 - mmengine - INFO - Epoch(val) [5][6300/7672] eta: 0:04:57 time: 0.2171 data_time: 0.0007 memory: 580 2022/09/17 10:00:32 - mmengine - INFO - Epoch(val) [5][6400/7672] eta: 0:05:00 time: 0.2358 data_time: 0.0010 memory: 580 2022/09/17 10:00:52 - mmengine - INFO - Epoch(val) [5][6500/7672] eta: 0:04:06 time: 0.2102 data_time: 0.0007 memory: 580 2022/09/17 10:01:13 - mmengine - INFO - Epoch(val) [5][6600/7672] eta: 0:03:34 time: 0.2002 data_time: 0.0007 memory: 580 2022/09/17 10:01:34 - mmengine - INFO - Epoch(val) [5][6700/7672] eta: 0:03:18 time: 0.2045 data_time: 0.0010 memory: 580 2022/09/17 10:01:55 - mmengine - INFO - Epoch(val) [5][6800/7672] eta: 0:02:53 time: 0.1995 data_time: 0.0007 memory: 580 2022/09/17 10:02:15 - mmengine - INFO - Epoch(val) [5][6900/7672] eta: 0:02:33 time: 0.1985 data_time: 0.0007 memory: 580 2022/09/17 10:02:36 - mmengine - INFO - Epoch(val) [5][7000/7672] eta: 0:02:14 time: 0.2005 data_time: 0.0008 memory: 580 2022/09/17 10:02:56 - mmengine - INFO - Epoch(val) [5][7100/7672] eta: 0:01:53 time: 0.1988 data_time: 0.0008 memory: 580 2022/09/17 10:03:16 - mmengine - INFO - Epoch(val) [5][7200/7672] eta: 0:01:32 time: 0.1961 data_time: 0.0009 memory: 580 2022/09/17 10:03:37 - mmengine - INFO - Epoch(val) [5][7300/7672] eta: 0:01:13 time: 0.1970 data_time: 0.0008 memory: 580 2022/09/17 10:03:58 - mmengine - INFO - Epoch(val) [5][7400/7672] eta: 0:00:54 time: 0.2000 data_time: 0.0008 memory: 580 2022/09/17 10:04:18 - mmengine - INFO - Epoch(val) [5][7500/7672] eta: 0:00:38 time: 0.2232 data_time: 0.0008 memory: 580 2022/09/17 10:04:39 - mmengine - INFO - Epoch(val) [5][7600/7672] eta: 0:00:14 time: 0.1970 data_time: 0.0014 memory: 580 2022/09/17 10:04:54 - mmengine - INFO - Epoch(val) [5][7672/7672] CUTE80/recog/word_acc_ignore_case_symbol: 0.7500 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9163 SVT/recog/word_acc_ignore_case_symbol: 0.8825 SVTP/recog/word_acc_ignore_case_symbol: 0.7690 IC13/recog/word_acc_ignore_case_symbol: 0.9350 IC15/recog/word_acc_ignore_case_symbol: 0.7208 2022/09/17 10:05:33 - mmengine - INFO - Epoch(train) [6][100/42151] lr: 3.0000e-06 eta: 4:12:10 time: 0.3714 data_time: 0.1623 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 10:06:06 - mmengine - INFO - Epoch(train) [6][200/42151] lr: 3.0000e-06 eta: 4:11:34 time: 0.3515 data_time: 0.1204 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 10:06:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:06:40 - mmengine - INFO - Epoch(train) [6][300/42151] lr: 3.0000e-06 eta: 4:10:57 time: 0.2994 data_time: 0.1011 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 10:07:14 - mmengine - INFO - Epoch(train) [6][400/42151] lr: 3.0000e-06 eta: 4:10:21 time: 0.2943 data_time: 0.0956 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 10:07:48 - mmengine - INFO - Epoch(train) [6][500/42151] lr: 3.0000e-06 eta: 4:09:44 time: 0.3759 data_time: 0.1326 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:08:21 - mmengine - INFO - Epoch(train) [6][600/42151] lr: 3.0000e-06 eta: 4:09:08 time: 0.3053 data_time: 0.1032 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 10:08:56 - mmengine - INFO - Epoch(train) [6][700/42151] lr: 3.0000e-06 eta: 4:08:32 time: 0.3892 data_time: 0.1809 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 10:09:30 - mmengine - INFO - Epoch(train) [6][800/42151] lr: 3.0000e-06 eta: 4:07:55 time: 0.3370 data_time: 0.1328 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 10:10:05 - mmengine - INFO - Epoch(train) [6][900/42151] lr: 3.0000e-06 eta: 4:07:19 time: 0.3127 data_time: 0.1049 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:10:39 - mmengine - INFO - Epoch(train) [6][1000/42151] lr: 3.0000e-06 eta: 4:06:43 time: 0.3497 data_time: 0.1241 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 10:11:14 - mmengine - INFO - Epoch(train) [6][1100/42151] lr: 3.0000e-06 eta: 4:06:07 time: 0.3476 data_time: 0.1103 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 10:11:48 - mmengine - INFO - Epoch(train) [6][1200/42151] lr: 3.0000e-06 eta: 4:05:30 time: 0.3245 data_time: 0.1214 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 10:12:05 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:12:24 - mmengine - INFO - Epoch(train) [6][1300/42151] lr: 3.0000e-06 eta: 4:04:54 time: 0.3803 data_time: 0.1335 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 10:12:59 - mmengine - INFO - Epoch(train) [6][1400/42151] lr: 3.0000e-06 eta: 4:04:18 time: 0.3506 data_time: 0.1233 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 10:13:33 - mmengine - INFO - Epoch(train) [6][1500/42151] lr: 3.0000e-06 eta: 4:03:42 time: 0.3106 data_time: 0.1076 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 10:14:07 - mmengine - INFO - Epoch(train) [6][1600/42151] lr: 3.0000e-06 eta: 4:03:06 time: 0.3249 data_time: 0.0999 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 10:14:43 - mmengine - INFO - Epoch(train) [6][1700/42151] lr: 3.0000e-06 eta: 4:02:29 time: 0.3570 data_time: 0.1577 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 10:15:16 - mmengine - INFO - Epoch(train) [6][1800/42151] lr: 3.0000e-06 eta: 4:01:53 time: 0.3099 data_time: 0.0855 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 10:15:50 - mmengine - INFO - Epoch(train) [6][1900/42151] lr: 3.0000e-06 eta: 4:01:17 time: 0.3569 data_time: 0.1184 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 10:16:24 - mmengine - INFO - Epoch(train) [6][2000/42151] lr: 3.0000e-06 eta: 4:00:40 time: 0.3692 data_time: 0.1362 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 10:16:59 - mmengine - INFO - Epoch(train) [6][2100/42151] lr: 3.0000e-06 eta: 4:00:04 time: 0.3107 data_time: 0.1105 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 10:17:33 - mmengine - INFO - Epoch(train) [6][2200/42151] lr: 3.0000e-06 eta: 3:59:28 time: 0.3306 data_time: 0.1243 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 10:17:49 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:18:07 - mmengine - INFO - Epoch(train) [6][2300/42151] lr: 3.0000e-06 eta: 3:58:51 time: 0.3294 data_time: 0.1075 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 10:18:41 - mmengine - INFO - Epoch(train) [6][2400/42151] lr: 3.0000e-06 eta: 3:58:15 time: 0.3159 data_time: 0.1143 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 10:19:17 - mmengine - INFO - Epoch(train) [6][2500/42151] lr: 3.0000e-06 eta: 3:57:39 time: 0.3607 data_time: 0.1544 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 10:19:52 - mmengine - INFO - Epoch(train) [6][2600/42151] lr: 3.0000e-06 eta: 3:57:03 time: 0.3180 data_time: 0.1174 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 10:20:28 - mmengine - INFO - Epoch(train) [6][2700/42151] lr: 3.0000e-06 eta: 3:56:27 time: 0.3395 data_time: 0.1288 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:21:03 - mmengine - INFO - Epoch(train) [6][2800/42151] lr: 3.0000e-06 eta: 3:55:51 time: 0.3734 data_time: 0.1517 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 10:21:38 - mmengine - INFO - Epoch(train) [6][2900/42151] lr: 3.0000e-06 eta: 3:55:15 time: 0.3600 data_time: 0.1590 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 10:22:12 - mmengine - INFO - Epoch(train) [6][3000/42151] lr: 3.0000e-06 eta: 3:54:38 time: 0.3364 data_time: 0.1323 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 10:22:46 - mmengine - INFO - Epoch(train) [6][3100/42151] lr: 3.0000e-06 eta: 3:54:02 time: 0.3351 data_time: 0.1085 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 10:23:20 - mmengine - INFO - Epoch(train) [6][3200/42151] lr: 3.0000e-06 eta: 3:53:26 time: 0.3403 data_time: 0.1388 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 10:23:37 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:23:56 - mmengine - INFO - Epoch(train) [6][3300/42151] lr: 3.0000e-06 eta: 3:52:50 time: 0.3384 data_time: 0.1122 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 10:24:30 - mmengine - INFO - Epoch(train) [6][3400/42151] lr: 3.0000e-06 eta: 3:52:13 time: 0.3511 data_time: 0.1421 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 10:25:04 - mmengine - INFO - Epoch(train) [6][3500/42151] lr: 3.0000e-06 eta: 3:51:37 time: 0.3601 data_time: 0.1518 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 10:25:39 - mmengine - INFO - Epoch(train) [6][3600/42151] lr: 3.0000e-06 eta: 3:51:01 time: 0.3263 data_time: 0.1227 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:26:14 - mmengine - INFO - Epoch(train) [6][3700/42151] lr: 3.0000e-06 eta: 3:50:25 time: 0.3732 data_time: 0.1191 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 10:26:48 - mmengine - INFO - Epoch(train) [6][3800/42151] lr: 3.0000e-06 eta: 3:49:48 time: 0.3458 data_time: 0.1356 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 10:27:23 - mmengine - INFO - Epoch(train) [6][3900/42151] lr: 3.0000e-06 eta: 3:49:12 time: 0.3259 data_time: 0.1223 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 10:27:57 - mmengine - INFO - Epoch(train) [6][4000/42151] lr: 3.0000e-06 eta: 3:48:36 time: 0.3490 data_time: 0.1434 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 10:28:32 - mmengine - INFO - Epoch(train) [6][4100/42151] lr: 3.0000e-06 eta: 3:48:00 time: 0.3620 data_time: 0.1573 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:29:06 - mmengine - INFO - Epoch(train) [6][4200/42151] lr: 3.0000e-06 eta: 3:47:23 time: 0.3079 data_time: 0.1028 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 10:29:21 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:29:40 - mmengine - INFO - Epoch(train) [6][4300/42151] lr: 3.0000e-06 eta: 3:46:47 time: 0.3459 data_time: 0.1225 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 10:30:13 - mmengine - INFO - Epoch(train) [6][4400/42151] lr: 3.0000e-06 eta: 3:46:11 time: 0.3210 data_time: 0.1170 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 10:30:48 - mmengine - INFO - Epoch(train) [6][4500/42151] lr: 3.0000e-06 eta: 3:45:35 time: 0.3279 data_time: 0.1251 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 10:31:22 - mmengine - INFO - Epoch(train) [6][4600/42151] lr: 3.0000e-06 eta: 3:44:58 time: 0.3127 data_time: 0.1127 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 10:31:56 - mmengine - INFO - Epoch(train) [6][4700/42151] lr: 3.0000e-06 eta: 3:44:22 time: 0.3749 data_time: 0.1590 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 10:32:29 - mmengine - INFO - Epoch(train) [6][4800/42151] lr: 3.0000e-06 eta: 3:43:46 time: 0.3025 data_time: 0.1015 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 10:33:02 - mmengine - INFO - Epoch(train) [6][4900/42151] lr: 3.0000e-06 eta: 3:43:09 time: 0.3415 data_time: 0.1161 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 10:33:36 - mmengine - INFO - Epoch(train) [6][5000/42151] lr: 3.0000e-06 eta: 3:42:33 time: 0.3422 data_time: 0.1435 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 10:34:11 - mmengine - INFO - Epoch(train) [6][5100/42151] lr: 3.0000e-06 eta: 3:41:57 time: 0.3257 data_time: 0.1234 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 10:34:45 - mmengine - INFO - Epoch(train) [6][5200/42151] lr: 3.0000e-06 eta: 3:41:20 time: 0.3543 data_time: 0.1264 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 10:35:01 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:35:19 - mmengine - INFO - Epoch(train) [6][5300/42151] lr: 3.0000e-06 eta: 3:40:44 time: 0.3608 data_time: 0.1580 memory: 7851 loss_ce: 0.0121 loss: 0.0121 2022/09/17 10:35:53 - mmengine - INFO - Epoch(train) [6][5400/42151] lr: 3.0000e-06 eta: 3:40:08 time: 0.3064 data_time: 0.0991 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 10:36:27 - mmengine - INFO - Epoch(train) [6][5500/42151] lr: 3.0000e-06 eta: 3:39:32 time: 0.3413 data_time: 0.1135 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 10:37:01 - mmengine - INFO - Epoch(train) [6][5600/42151] lr: 3.0000e-06 eta: 3:38:55 time: 0.3405 data_time: 0.1359 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 10:37:36 - mmengine - INFO - Epoch(train) [6][5700/42151] lr: 3.0000e-06 eta: 3:38:19 time: 0.3433 data_time: 0.1177 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 10:38:09 - mmengine - INFO - Epoch(train) [6][5800/42151] lr: 3.0000e-06 eta: 3:37:43 time: 0.3305 data_time: 0.1182 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 10:38:45 - mmengine - INFO - Epoch(train) [6][5900/42151] lr: 3.0000e-06 eta: 3:37:07 time: 0.3952 data_time: 0.1798 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 10:39:18 - mmengine - INFO - Epoch(train) [6][6000/42151] lr: 3.0000e-06 eta: 3:36:30 time: 0.3072 data_time: 0.1062 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 10:39:53 - mmengine - INFO - Epoch(train) [6][6100/42151] lr: 3.0000e-06 eta: 3:35:54 time: 0.3658 data_time: 0.1319 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 10:40:28 - mmengine - INFO - Epoch(train) [6][6200/42151] lr: 3.0000e-06 eta: 3:35:18 time: 0.3762 data_time: 0.1430 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 10:40:44 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:41:03 - mmengine - INFO - Epoch(train) [6][6300/42151] lr: 3.0000e-06 eta: 3:34:42 time: 0.3273 data_time: 0.1245 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 10:41:38 - mmengine - INFO - Epoch(train) [6][6400/42151] lr: 3.0000e-06 eta: 3:34:06 time: 0.3626 data_time: 0.1326 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 10:42:13 - mmengine - INFO - Epoch(train) [6][6500/42151] lr: 3.0000e-06 eta: 3:33:30 time: 0.3898 data_time: 0.1882 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 10:42:47 - mmengine - INFO - Epoch(train) [6][6600/42151] lr: 3.0000e-06 eta: 3:32:54 time: 0.3192 data_time: 0.1134 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 10:43:21 - mmengine - INFO - Epoch(train) [6][6700/42151] lr: 3.0000e-06 eta: 3:32:17 time: 0.3695 data_time: 0.1225 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 10:43:54 - mmengine - INFO - Epoch(train) [6][6800/42151] lr: 3.0000e-06 eta: 3:31:41 time: 0.3202 data_time: 0.0991 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 10:44:28 - mmengine - INFO - Epoch(train) [6][6900/42151] lr: 3.0000e-06 eta: 3:31:05 time: 0.3594 data_time: 0.1012 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 10:45:02 - mmengine - INFO - Epoch(train) [6][7000/42151] lr: 3.0000e-06 eta: 3:30:28 time: 0.3347 data_time: 0.1035 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 10:45:37 - mmengine - INFO - Epoch(train) [6][7100/42151] lr: 3.0000e-06 eta: 3:29:52 time: 0.3576 data_time: 0.1278 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 10:46:11 - mmengine - INFO - Epoch(train) [6][7200/42151] lr: 3.0000e-06 eta: 3:29:16 time: 0.3448 data_time: 0.1381 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 10:46:28 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:46:47 - mmengine - INFO - Epoch(train) [6][7300/42151] lr: 3.0000e-06 eta: 3:28:40 time: 0.3667 data_time: 0.1623 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 10:47:21 - mmengine - INFO - Epoch(train) [6][7400/42151] lr: 3.0000e-06 eta: 3:28:04 time: 0.3271 data_time: 0.1249 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 10:47:56 - mmengine - INFO - Epoch(train) [6][7500/42151] lr: 3.0000e-06 eta: 3:27:28 time: 0.3136 data_time: 0.1098 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 10:48:31 - mmengine - INFO - Epoch(train) [6][7600/42151] lr: 3.0000e-06 eta: 3:26:52 time: 0.3430 data_time: 0.1366 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:49:06 - mmengine - INFO - Epoch(train) [6][7700/42151] lr: 3.0000e-06 eta: 3:26:16 time: 0.3740 data_time: 0.1737 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 10:49:40 - mmengine - INFO - Epoch(train) [6][7800/42151] lr: 3.0000e-06 eta: 3:25:39 time: 0.3096 data_time: 0.1073 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 10:50:14 - mmengine - INFO - Epoch(train) [6][7900/42151] lr: 3.0000e-06 eta: 3:25:03 time: 0.3475 data_time: 0.1495 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 10:50:48 - mmengine - INFO - Epoch(train) [6][8000/42151] lr: 3.0000e-06 eta: 3:24:27 time: 0.3364 data_time: 0.1198 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 10:51:24 - mmengine - INFO - Epoch(train) [6][8100/42151] lr: 3.0000e-06 eta: 3:23:51 time: 0.3149 data_time: 0.0790 memory: 7851 loss_ce: 0.0131 loss: 0.0131 2022/09/17 10:51:58 - mmengine - INFO - Epoch(train) [6][8200/42151] lr: 3.0000e-06 eta: 3:23:15 time: 0.3539 data_time: 0.1012 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 10:52:14 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:52:33 - mmengine - INFO - Epoch(train) [6][8300/42151] lr: 3.0000e-06 eta: 3:22:39 time: 0.3508 data_time: 0.1437 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 10:53:07 - mmengine - INFO - Epoch(train) [6][8400/42151] lr: 3.0000e-06 eta: 3:22:03 time: 0.3466 data_time: 0.1033 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 10:53:42 - mmengine - INFO - Epoch(train) [6][8500/42151] lr: 3.0000e-06 eta: 3:21:26 time: 0.3645 data_time: 0.1622 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 10:54:15 - mmengine - INFO - Epoch(train) [6][8600/42151] lr: 3.0000e-06 eta: 3:20:50 time: 0.3136 data_time: 0.1134 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 10:54:51 - mmengine - INFO - Epoch(train) [6][8700/42151] lr: 3.0000e-06 eta: 3:20:14 time: 0.3275 data_time: 0.1217 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 10:55:25 - mmengine - INFO - Epoch(train) [6][8800/42151] lr: 3.0000e-06 eta: 3:19:38 time: 0.3297 data_time: 0.1281 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 10:55:59 - mmengine - INFO - Epoch(train) [6][8900/42151] lr: 3.0000e-06 eta: 3:19:02 time: 0.3726 data_time: 0.1484 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 10:56:33 - mmengine - INFO - Epoch(train) [6][9000/42151] lr: 3.0000e-06 eta: 3:18:26 time: 0.3178 data_time: 0.0911 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 10:57:08 - mmengine - INFO - Epoch(train) [6][9100/42151] lr: 3.0000e-06 eta: 3:17:49 time: 0.3737 data_time: 0.1110 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 10:57:42 - mmengine - INFO - Epoch(train) [6][9200/42151] lr: 3.0000e-06 eta: 3:17:13 time: 0.3167 data_time: 0.0896 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 10:57:58 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 10:58:16 - mmengine - INFO - Epoch(train) [6][9300/42151] lr: 3.0000e-06 eta: 3:16:37 time: 0.3398 data_time: 0.0912 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 10:58:50 - mmengine - INFO - Epoch(train) [6][9400/42151] lr: 3.0000e-06 eta: 3:16:01 time: 0.3178 data_time: 0.0971 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 10:59:24 - mmengine - INFO - Epoch(train) [6][9500/42151] lr: 3.0000e-06 eta: 3:15:25 time: 0.3410 data_time: 0.1149 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 10:59:58 - mmengine - INFO - Epoch(train) [6][9600/42151] lr: 3.0000e-06 eta: 3:14:48 time: 0.3151 data_time: 0.1143 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 11:00:32 - mmengine - INFO - Epoch(train) [6][9700/42151] lr: 3.0000e-06 eta: 3:14:12 time: 0.3427 data_time: 0.1359 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 11:01:06 - mmengine - INFO - Epoch(train) [6][9800/42151] lr: 3.0000e-06 eta: 3:13:36 time: 0.3251 data_time: 0.1243 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 11:01:40 - mmengine - INFO - Epoch(train) [6][9900/42151] lr: 3.0000e-06 eta: 3:13:00 time: 0.3117 data_time: 0.1102 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 11:02:15 - mmengine - INFO - Epoch(train) [6][10000/42151] lr: 3.0000e-06 eta: 3:12:24 time: 0.3524 data_time: 0.1473 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 11:02:50 - mmengine - INFO - Epoch(train) [6][10100/42151] lr: 3.0000e-06 eta: 3:11:48 time: 0.3688 data_time: 0.1615 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 11:03:24 - mmengine - INFO - Epoch(train) [6][10200/42151] lr: 3.0000e-06 eta: 3:11:12 time: 0.3062 data_time: 0.1042 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 11:03:40 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:03:59 - mmengine - INFO - Epoch(train) [6][10300/42151] lr: 3.0000e-06 eta: 3:10:36 time: 0.3550 data_time: 0.1376 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 11:04:34 - mmengine - INFO - Epoch(train) [6][10400/42151] lr: 3.0000e-06 eta: 3:09:59 time: 0.3154 data_time: 0.1153 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 11:05:08 - mmengine - INFO - Epoch(train) [6][10500/42151] lr: 3.0000e-06 eta: 3:09:23 time: 0.3476 data_time: 0.1012 memory: 7851 loss_ce: 0.0131 loss: 0.0131 2022/09/17 11:05:42 - mmengine - INFO - Epoch(train) [6][10600/42151] lr: 3.0000e-06 eta: 3:08:47 time: 0.3602 data_time: 0.1046 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 11:06:17 - mmengine - INFO - Epoch(train) [6][10700/42151] lr: 3.0000e-06 eta: 3:08:11 time: 0.3504 data_time: 0.1475 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 11:06:51 - mmengine - INFO - Epoch(train) [6][10800/42151] lr: 3.0000e-06 eta: 3:07:35 time: 0.3036 data_time: 0.1034 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 11:07:25 - mmengine - INFO - Epoch(train) [6][10900/42151] lr: 3.0000e-06 eta: 3:06:59 time: 0.3534 data_time: 0.1495 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 11:07:59 - mmengine - INFO - Epoch(train) [6][11000/42151] lr: 3.0000e-06 eta: 3:06:22 time: 0.3212 data_time: 0.1102 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 11:08:33 - mmengine - INFO - Epoch(train) [6][11100/42151] lr: 3.0000e-06 eta: 3:05:46 time: 0.3080 data_time: 0.1039 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 11:09:06 - mmengine - INFO - Epoch(train) [6][11200/42151] lr: 3.0000e-06 eta: 3:05:10 time: 0.3097 data_time: 0.1093 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 11:09:22 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:09:41 - mmengine - INFO - Epoch(train) [6][11300/42151] lr: 3.0000e-06 eta: 3:04:34 time: 0.3740 data_time: 0.1729 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 11:10:14 - mmengine - INFO - Epoch(train) [6][11400/42151] lr: 3.0000e-06 eta: 3:03:58 time: 0.3067 data_time: 0.1034 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 11:10:49 - mmengine - INFO - Epoch(train) [6][11500/42151] lr: 3.0000e-06 eta: 3:03:22 time: 0.3467 data_time: 0.1298 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 11:11:23 - mmengine - INFO - Epoch(train) [6][11600/42151] lr: 3.0000e-06 eta: 3:02:46 time: 0.3353 data_time: 0.1268 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 11:11:57 - mmengine - INFO - Epoch(train) [6][11700/42151] lr: 3.0000e-06 eta: 3:02:09 time: 0.3140 data_time: 0.1106 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 11:12:32 - mmengine - INFO - Epoch(train) [6][11800/42151] lr: 3.0000e-06 eta: 3:01:33 time: 0.3110 data_time: 0.1114 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 11:13:07 - mmengine - INFO - Epoch(train) [6][11900/42151] lr: 3.0000e-06 eta: 3:00:57 time: 0.3508 data_time: 0.1492 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 11:13:41 - mmengine - INFO - Epoch(train) [6][12000/42151] lr: 3.0000e-06 eta: 3:00:21 time: 0.3143 data_time: 0.1117 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 11:14:15 - mmengine - INFO - Epoch(train) [6][12100/42151] lr: 3.0000e-06 eta: 2:59:45 time: 0.3246 data_time: 0.1199 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 11:14:49 - mmengine - INFO - Epoch(train) [6][12200/42151] lr: 3.0000e-06 eta: 2:59:09 time: 0.3153 data_time: 0.1115 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 11:15:05 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:15:24 - mmengine - INFO - Epoch(train) [6][12300/42151] lr: 3.0000e-06 eta: 2:58:33 time: 0.3380 data_time: 0.1330 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 11:15:58 - mmengine - INFO - Epoch(train) [6][12400/42151] lr: 3.0000e-06 eta: 2:57:57 time: 0.3341 data_time: 0.1114 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 11:16:32 - mmengine - INFO - Epoch(train) [6][12500/42151] lr: 3.0000e-06 eta: 2:57:21 time: 0.3531 data_time: 0.1492 memory: 7851 loss_ce: 0.0124 loss: 0.0124 2022/09/17 11:17:06 - mmengine - INFO - Epoch(train) [6][12600/42151] lr: 3.0000e-06 eta: 2:56:44 time: 0.3055 data_time: 0.1050 memory: 7851 loss_ce: 0.0131 loss: 0.0131 2022/09/17 11:17:40 - mmengine - INFO - Epoch(train) [6][12700/42151] lr: 3.0000e-06 eta: 2:56:08 time: 0.3277 data_time: 0.1277 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 11:18:14 - mmengine - INFO - Epoch(train) [6][12800/42151] lr: 3.0000e-06 eta: 2:55:32 time: 0.3244 data_time: 0.1229 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 11:18:49 - mmengine - INFO - Epoch(train) [6][12900/42151] lr: 3.0000e-06 eta: 2:54:56 time: 0.3287 data_time: 0.1157 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 11:19:23 - mmengine - INFO - Epoch(train) [6][13000/42151] lr: 3.0000e-06 eta: 2:54:20 time: 0.3107 data_time: 0.1113 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 11:19:58 - mmengine - INFO - Epoch(train) [6][13100/42151] lr: 3.0000e-06 eta: 2:53:44 time: 0.3718 data_time: 0.1711 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 11:20:32 - mmengine - INFO - Epoch(train) [6][13200/42151] lr: 3.0000e-06 eta: 2:53:08 time: 0.3207 data_time: 0.1171 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 11:20:48 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:21:07 - mmengine - INFO - Epoch(train) [6][13300/42151] lr: 3.0000e-06 eta: 2:52:32 time: 0.3351 data_time: 0.1336 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 11:21:41 - mmengine - INFO - Epoch(train) [6][13400/42151] lr: 3.0000e-06 eta: 2:51:56 time: 0.3532 data_time: 0.1276 memory: 7851 loss_ce: 0.0131 loss: 0.0131 2022/09/17 11:22:16 - mmengine - INFO - Epoch(train) [6][13500/42151] lr: 3.0000e-06 eta: 2:51:20 time: 0.3163 data_time: 0.1128 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 11:22:50 - mmengine - INFO - Epoch(train) [6][13600/42151] lr: 3.0000e-06 eta: 2:50:43 time: 0.3369 data_time: 0.1351 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 11:23:25 - mmengine - INFO - Epoch(train) [6][13700/42151] lr: 3.0000e-06 eta: 2:50:07 time: 0.3707 data_time: 0.1645 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 11:23:58 - mmengine - INFO - Epoch(train) [6][13800/42151] lr: 3.0000e-06 eta: 2:49:31 time: 0.3101 data_time: 0.1088 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 11:24:33 - mmengine - INFO - Epoch(train) [6][13900/42151] lr: 3.0000e-06 eta: 2:48:55 time: 0.3377 data_time: 0.1344 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 11:25:08 - mmengine - INFO - Epoch(train) [6][14000/42151] lr: 3.0000e-06 eta: 2:48:19 time: 0.3464 data_time: 0.1435 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 11:25:44 - mmengine - INFO - Epoch(train) [6][14100/42151] lr: 3.0000e-06 eta: 2:47:43 time: 0.3190 data_time: 0.1154 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 11:26:19 - mmengine - INFO - Epoch(train) [6][14200/42151] lr: 3.0000e-06 eta: 2:47:07 time: 0.3337 data_time: 0.1220 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 11:26:35 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:26:54 - mmengine - INFO - Epoch(train) [6][14300/42151] lr: 3.0000e-06 eta: 2:46:31 time: 0.3623 data_time: 0.1564 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 11:27:28 - mmengine - INFO - Epoch(train) [6][14400/42151] lr: 3.0000e-06 eta: 2:45:55 time: 0.3377 data_time: 0.1360 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 11:28:03 - mmengine - INFO - Epoch(train) [6][14500/42151] lr: 3.0000e-06 eta: 2:45:19 time: 0.3581 data_time: 0.1561 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 11:28:38 - mmengine - INFO - Epoch(train) [6][14600/42151] lr: 3.0000e-06 eta: 2:44:43 time: 0.3284 data_time: 0.1202 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 11:29:13 - mmengine - INFO - Epoch(train) [6][14700/42151] lr: 3.0000e-06 eta: 2:44:07 time: 0.3359 data_time: 0.1273 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 11:29:47 - mmengine - INFO - Epoch(train) [6][14800/42151] lr: 3.0000e-06 eta: 2:43:31 time: 0.3270 data_time: 0.1214 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 11:30:22 - mmengine - INFO - Epoch(train) [6][14900/42151] lr: 3.0000e-06 eta: 2:42:55 time: 0.3588 data_time: 0.1498 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 11:30:56 - mmengine - INFO - Epoch(train) [6][15000/42151] lr: 3.0000e-06 eta: 2:42:19 time: 0.3220 data_time: 0.1155 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 11:31:31 - mmengine - INFO - Epoch(train) [6][15100/42151] lr: 3.0000e-06 eta: 2:41:43 time: 0.3334 data_time: 0.1292 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 11:32:05 - mmengine - INFO - Epoch(train) [6][15200/42151] lr: 3.0000e-06 eta: 2:41:07 time: 0.3394 data_time: 0.1344 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 11:32:21 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:32:40 - mmengine - INFO - Epoch(train) [6][15300/42151] lr: 3.0000e-06 eta: 2:40:31 time: 0.3227 data_time: 0.1189 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 11:33:14 - mmengine - INFO - Epoch(train) [6][15400/42151] lr: 3.0000e-06 eta: 2:39:55 time: 0.3281 data_time: 0.1234 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 11:33:48 - mmengine - INFO - Epoch(train) [6][15500/42151] lr: 3.0000e-06 eta: 2:39:19 time: 0.3439 data_time: 0.1418 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 11:34:22 - mmengine - INFO - Epoch(train) [6][15600/42151] lr: 3.0000e-06 eta: 2:38:43 time: 0.3349 data_time: 0.1334 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 11:34:57 - mmengine - INFO - Epoch(train) [6][15700/42151] lr: 3.0000e-06 eta: 2:38:07 time: 0.3260 data_time: 0.1226 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 11:35:31 - mmengine - INFO - Epoch(train) [6][15800/42151] lr: 3.0000e-06 eta: 2:37:31 time: 0.3335 data_time: 0.1169 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 11:36:06 - mmengine - INFO - Epoch(train) [6][15900/42151] lr: 3.0000e-06 eta: 2:36:55 time: 0.3033 data_time: 0.1060 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 11:36:41 - mmengine - INFO - Epoch(train) [6][16000/42151] lr: 3.0000e-06 eta: 2:36:19 time: 0.3208 data_time: 0.1132 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 11:37:15 - mmengine - INFO - Epoch(train) [6][16100/42151] lr: 3.0000e-06 eta: 2:35:43 time: 0.3328 data_time: 0.1296 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 11:37:49 - mmengine - INFO - Epoch(train) [6][16200/42151] lr: 3.0000e-06 eta: 2:35:07 time: 0.3317 data_time: 0.1306 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 11:38:05 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:38:24 - mmengine - INFO - Epoch(train) [6][16300/42151] lr: 3.0000e-06 eta: 2:34:31 time: 0.3795 data_time: 0.1693 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 11:38:57 - mmengine - INFO - Epoch(train) [6][16400/42151] lr: 3.0000e-06 eta: 2:33:54 time: 0.3263 data_time: 0.1242 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 11:39:32 - mmengine - INFO - Epoch(train) [6][16500/42151] lr: 3.0000e-06 eta: 2:33:18 time: 0.3215 data_time: 0.1155 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 11:40:05 - mmengine - INFO - Epoch(train) [6][16600/42151] lr: 3.0000e-06 eta: 2:32:42 time: 0.3178 data_time: 0.1163 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 11:40:40 - mmengine - INFO - Epoch(train) [6][16700/42151] lr: 3.0000e-06 eta: 2:32:06 time: 0.3552 data_time: 0.1501 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 11:41:14 - mmengine - INFO - Epoch(train) [6][16800/42151] lr: 3.0000e-06 eta: 2:31:30 time: 0.3369 data_time: 0.1323 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 11:41:49 - mmengine - INFO - Epoch(train) [6][16900/42151] lr: 3.0000e-06 eta: 2:30:54 time: 0.3341 data_time: 0.1277 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 11:42:24 - mmengine - INFO - Epoch(train) [6][17000/42151] lr: 3.0000e-06 eta: 2:30:18 time: 0.3489 data_time: 0.1455 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 11:42:59 - mmengine - INFO - Epoch(train) [6][17100/42151] lr: 3.0000e-06 eta: 2:29:42 time: 0.3200 data_time: 0.1141 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 11:43:33 - mmengine - INFO - Epoch(train) [6][17200/42151] lr: 3.0000e-06 eta: 2:29:06 time: 0.3329 data_time: 0.1223 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 11:43:49 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:44:08 - mmengine - INFO - Epoch(train) [6][17300/42151] lr: 3.0000e-06 eta: 2:28:30 time: 0.3486 data_time: 0.1470 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 11:44:42 - mmengine - INFO - Epoch(train) [6][17400/42151] lr: 3.0000e-06 eta: 2:27:54 time: 0.3144 data_time: 0.1139 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 11:45:16 - mmengine - INFO - Epoch(train) [6][17500/42151] lr: 3.0000e-06 eta: 2:27:18 time: 0.3258 data_time: 0.1206 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 11:45:51 - mmengine - INFO - Epoch(train) [6][17600/42151] lr: 3.0000e-06 eta: 2:26:42 time: 0.3299 data_time: 0.1279 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 11:46:26 - mmengine - INFO - Epoch(train) [6][17700/42151] lr: 3.0000e-06 eta: 2:26:06 time: 0.3131 data_time: 0.1137 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 11:47:00 - mmengine - INFO - Epoch(train) [6][17800/42151] lr: 3.0000e-06 eta: 2:25:30 time: 0.3241 data_time: 0.1173 memory: 7851 loss_ce: 0.0124 loss: 0.0124 2022/09/17 11:47:34 - mmengine - INFO - Epoch(train) [6][17900/42151] lr: 3.0000e-06 eta: 2:24:54 time: 0.3649 data_time: 0.1609 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 11:48:08 - mmengine - INFO - Epoch(train) [6][18000/42151] lr: 3.0000e-06 eta: 2:24:18 time: 0.3213 data_time: 0.1211 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 11:48:42 - mmengine - INFO - Epoch(train) [6][18100/42151] lr: 3.0000e-06 eta: 2:23:42 time: 0.3329 data_time: 0.1294 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 11:49:17 - mmengine - INFO - Epoch(train) [6][18200/42151] lr: 3.0000e-06 eta: 2:23:06 time: 0.3415 data_time: 0.1343 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 11:49:33 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:49:53 - mmengine - INFO - Epoch(train) [6][18300/42151] lr: 3.0000e-06 eta: 2:22:30 time: 0.3166 data_time: 0.1135 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 11:50:27 - mmengine - INFO - Epoch(train) [6][18400/42151] lr: 3.0000e-06 eta: 2:21:54 time: 0.3238 data_time: 0.1218 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 11:51:02 - mmengine - INFO - Epoch(train) [6][18500/42151] lr: 3.0000e-06 eta: 2:21:18 time: 0.3653 data_time: 0.1626 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 11:51:36 - mmengine - INFO - Epoch(train) [6][18600/42151] lr: 3.0000e-06 eta: 2:20:42 time: 0.3225 data_time: 0.1225 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 11:52:10 - mmengine - INFO - Epoch(train) [6][18700/42151] lr: 3.0000e-06 eta: 2:20:06 time: 0.3543 data_time: 0.1445 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 11:52:45 - mmengine - INFO - Epoch(train) [6][18800/42151] lr: 3.0000e-06 eta: 2:19:30 time: 0.3367 data_time: 0.1269 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 11:53:19 - mmengine - INFO - Epoch(train) [6][18900/42151] lr: 3.0000e-06 eta: 2:18:54 time: 0.3202 data_time: 0.1178 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 11:53:53 - mmengine - INFO - Epoch(train) [6][19000/42151] lr: 3.0000e-06 eta: 2:18:18 time: 0.3273 data_time: 0.1185 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 11:54:27 - mmengine - INFO - Epoch(train) [6][19100/42151] lr: 3.0000e-06 eta: 2:17:42 time: 0.3726 data_time: 0.1645 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 11:55:01 - mmengine - INFO - Epoch(train) [6][19200/42151] lr: 3.0000e-06 eta: 2:17:06 time: 0.3222 data_time: 0.1188 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 11:55:18 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 11:55:38 - mmengine - INFO - Epoch(train) [6][19300/42151] lr: 3.0000e-06 eta: 2:16:30 time: 0.3559 data_time: 0.1537 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 11:56:12 - mmengine - INFO - Epoch(train) [6][19400/42151] lr: 3.0000e-06 eta: 2:15:54 time: 0.3249 data_time: 0.1210 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 11:56:47 - mmengine - INFO - Epoch(train) [6][19500/42151] lr: 3.0000e-06 eta: 2:15:18 time: 0.3242 data_time: 0.1215 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 11:57:21 - mmengine - INFO - Epoch(train) [6][19600/42151] lr: 3.0000e-06 eta: 2:14:42 time: 0.3138 data_time: 0.1123 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 11:57:56 - mmengine - INFO - Epoch(train) [6][19700/42151] lr: 3.0000e-06 eta: 2:14:06 time: 0.3534 data_time: 0.1480 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 11:58:30 - mmengine - INFO - Epoch(train) [6][19800/42151] lr: 3.0000e-06 eta: 2:13:30 time: 0.3328 data_time: 0.1220 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 11:59:04 - mmengine - INFO - Epoch(train) [6][19900/42151] lr: 3.0000e-06 eta: 2:12:54 time: 0.3693 data_time: 0.1380 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 11:59:39 - mmengine - INFO - Epoch(train) [6][20000/42151] lr: 3.0000e-06 eta: 2:12:18 time: 0.3140 data_time: 0.1108 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 12:00:19 - mmengine - INFO - Epoch(train) [6][20100/42151] lr: 3.0000e-06 eta: 2:11:43 time: 0.3310 data_time: 0.1155 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 12:00:53 - mmengine - INFO - Epoch(train) [6][20200/42151] lr: 3.0000e-06 eta: 2:11:07 time: 0.3148 data_time: 0.1151 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 12:01:09 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:01:28 - mmengine - INFO - Epoch(train) [6][20300/42151] lr: 3.0000e-06 eta: 2:10:31 time: 0.3524 data_time: 0.1488 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:02:03 - mmengine - INFO - Epoch(train) [6][20400/42151] lr: 3.0000e-06 eta: 2:09:55 time: 0.3256 data_time: 0.1171 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 12:02:37 - mmengine - INFO - Epoch(train) [6][20500/42151] lr: 3.0000e-06 eta: 2:09:19 time: 0.3378 data_time: 0.1352 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 12:03:12 - mmengine - INFO - Epoch(train) [6][20600/42151] lr: 3.0000e-06 eta: 2:08:43 time: 0.3549 data_time: 0.1501 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 12:03:47 - mmengine - INFO - Epoch(train) [6][20700/42151] lr: 3.0000e-06 eta: 2:08:07 time: 0.3201 data_time: 0.1189 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 12:04:22 - mmengine - INFO - Epoch(train) [6][20800/42151] lr: 3.0000e-06 eta: 2:07:31 time: 0.3135 data_time: 0.1104 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 12:04:56 - mmengine - INFO - Epoch(train) [6][20900/42151] lr: 3.0000e-06 eta: 2:06:55 time: 0.3503 data_time: 0.1503 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 12:05:30 - mmengine - INFO - Epoch(train) [6][21000/42151] lr: 3.0000e-06 eta: 2:06:19 time: 0.3216 data_time: 0.1179 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 12:06:06 - mmengine - INFO - Epoch(train) [6][21100/42151] lr: 3.0000e-06 eta: 2:05:43 time: 0.3980 data_time: 0.1828 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 12:06:40 - mmengine - INFO - Epoch(train) [6][21200/42151] lr: 3.0000e-06 eta: 2:05:07 time: 0.3417 data_time: 0.1379 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 12:06:57 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:07:16 - mmengine - INFO - Epoch(train) [6][21300/42151] lr: 3.0000e-06 eta: 2:04:32 time: 0.3296 data_time: 0.1242 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 12:07:50 - mmengine - INFO - Epoch(train) [6][21400/42151] lr: 3.0000e-06 eta: 2:03:56 time: 0.3240 data_time: 0.1210 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 12:08:25 - mmengine - INFO - Epoch(train) [6][21500/42151] lr: 3.0000e-06 eta: 2:03:20 time: 0.3621 data_time: 0.1540 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 12:08:59 - mmengine - INFO - Epoch(train) [6][21600/42151] lr: 3.0000e-06 eta: 2:02:44 time: 0.3292 data_time: 0.1180 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 12:09:34 - mmengine - INFO - Epoch(train) [6][21700/42151] lr: 3.0000e-06 eta: 2:02:08 time: 0.3590 data_time: 0.1318 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 12:10:09 - mmengine - INFO - Epoch(train) [6][21800/42151] lr: 3.0000e-06 eta: 2:01:32 time: 0.3647 data_time: 0.1322 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 12:10:44 - mmengine - INFO - Epoch(train) [6][21900/42151] lr: 3.0000e-06 eta: 2:00:56 time: 0.3253 data_time: 0.1212 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 12:11:18 - mmengine - INFO - Epoch(train) [6][22000/42151] lr: 3.0000e-06 eta: 2:00:20 time: 0.3304 data_time: 0.1215 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 12:11:53 - mmengine - INFO - Epoch(train) [6][22100/42151] lr: 3.0000e-06 eta: 1:59:44 time: 0.3837 data_time: 0.1795 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 12:12:27 - mmengine - INFO - Epoch(train) [6][22200/42151] lr: 3.0000e-06 eta: 1:59:08 time: 0.3329 data_time: 0.0954 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 12:12:43 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:13:02 - mmengine - INFO - Epoch(train) [6][22300/42151] lr: 3.0000e-06 eta: 1:58:32 time: 0.3231 data_time: 0.0983 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 12:13:36 - mmengine - INFO - Epoch(train) [6][22400/42151] lr: 3.0000e-06 eta: 1:57:56 time: 0.3745 data_time: 0.1354 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 12:14:11 - mmengine - INFO - Epoch(train) [6][22500/42151] lr: 3.0000e-06 eta: 1:57:20 time: 0.3246 data_time: 0.1251 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 12:14:45 - mmengine - INFO - Epoch(train) [6][22600/42151] lr: 3.0000e-06 eta: 1:56:44 time: 0.3200 data_time: 0.1167 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 12:15:20 - mmengine - INFO - Epoch(train) [6][22700/42151] lr: 3.0000e-06 eta: 1:56:08 time: 0.3707 data_time: 0.1659 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 12:15:54 - mmengine - INFO - Epoch(train) [6][22800/42151] lr: 3.0000e-06 eta: 1:55:32 time: 0.3292 data_time: 0.0987 memory: 7851 loss_ce: 0.0133 loss: 0.0133 2022/09/17 12:16:28 - mmengine - INFO - Epoch(train) [6][22900/42151] lr: 3.0000e-06 eta: 1:54:56 time: 0.3380 data_time: 0.1040 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 12:17:02 - mmengine - INFO - Epoch(train) [6][23000/42151] lr: 3.0000e-06 eta: 1:54:20 time: 0.3482 data_time: 0.1239 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 12:17:36 - mmengine - INFO - Epoch(train) [6][23100/42151] lr: 3.0000e-06 eta: 1:53:44 time: 0.3365 data_time: 0.1360 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 12:18:10 - mmengine - INFO - Epoch(train) [6][23200/42151] lr: 3.0000e-06 eta: 1:53:08 time: 0.3347 data_time: 0.1343 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 12:18:25 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:18:44 - mmengine - INFO - Epoch(train) [6][23300/42151] lr: 3.0000e-06 eta: 1:52:32 time: 0.3974 data_time: 0.1878 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 12:19:18 - mmengine - INFO - Epoch(train) [6][23400/42151] lr: 3.0000e-06 eta: 1:51:56 time: 0.3285 data_time: 0.0800 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 12:19:52 - mmengine - INFO - Epoch(train) [6][23500/42151] lr: 3.0000e-06 eta: 1:51:21 time: 0.3182 data_time: 0.0967 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 12:20:27 - mmengine - INFO - Epoch(train) [6][23600/42151] lr: 3.0000e-06 eta: 1:50:45 time: 0.3487 data_time: 0.1124 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 12:21:00 - mmengine - INFO - Epoch(train) [6][23700/42151] lr: 3.0000e-06 eta: 1:50:09 time: 0.3307 data_time: 0.1271 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 12:21:33 - mmengine - INFO - Epoch(train) [6][23800/42151] lr: 3.0000e-06 eta: 1:49:33 time: 0.3245 data_time: 0.1249 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 12:22:07 - mmengine - INFO - Epoch(train) [6][23900/42151] lr: 3.0000e-06 eta: 1:48:57 time: 0.3897 data_time: 0.1852 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 12:22:40 - mmengine - INFO - Epoch(train) [6][24000/42151] lr: 3.0000e-06 eta: 1:48:21 time: 0.3079 data_time: 0.0808 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 12:23:14 - mmengine - INFO - Epoch(train) [6][24100/42151] lr: 3.0000e-06 eta: 1:47:45 time: 0.3253 data_time: 0.0988 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 12:23:49 - mmengine - INFO - Epoch(train) [6][24200/42151] lr: 3.0000e-06 eta: 1:47:09 time: 0.3346 data_time: 0.1087 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 12:24:05 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:24:23 - mmengine - INFO - Epoch(train) [6][24300/42151] lr: 3.0000e-06 eta: 1:46:33 time: 0.3255 data_time: 0.1253 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 12:24:57 - mmengine - INFO - Epoch(train) [6][24400/42151] lr: 3.0000e-06 eta: 1:45:57 time: 0.3266 data_time: 0.1210 memory: 7851 loss_ce: 0.0175 loss: 0.0175 2022/09/17 12:25:32 - mmengine - INFO - Epoch(train) [6][24500/42151] lr: 3.0000e-06 eta: 1:45:21 time: 0.3672 data_time: 0.1671 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 12:26:06 - mmengine - INFO - Epoch(train) [6][24600/42151] lr: 3.0000e-06 eta: 1:44:45 time: 0.3178 data_time: 0.0801 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 12:26:40 - mmengine - INFO - Epoch(train) [6][24700/42151] lr: 3.0000e-06 eta: 1:44:09 time: 0.3366 data_time: 0.1066 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 12:27:14 - mmengine - INFO - Epoch(train) [6][24800/42151] lr: 3.0000e-06 eta: 1:43:33 time: 0.3342 data_time: 0.1106 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 12:27:49 - mmengine - INFO - Epoch(train) [6][24900/42151] lr: 3.0000e-06 eta: 1:42:57 time: 0.3295 data_time: 0.1287 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 12:28:23 - mmengine - INFO - Epoch(train) [6][25000/42151] lr: 3.0000e-06 eta: 1:42:21 time: 0.3206 data_time: 0.1208 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 12:28:58 - mmengine - INFO - Epoch(train) [6][25100/42151] lr: 3.0000e-06 eta: 1:41:45 time: 0.3877 data_time: 0.1834 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 12:29:32 - mmengine - INFO - Epoch(train) [6][25200/42151] lr: 3.0000e-06 eta: 1:41:09 time: 0.3160 data_time: 0.0855 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 12:29:48 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:30:07 - mmengine - INFO - Epoch(train) [6][25300/42151] lr: 3.0000e-06 eta: 1:40:34 time: 0.3344 data_time: 0.1068 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 12:30:42 - mmengine - INFO - Epoch(train) [6][25400/42151] lr: 3.0000e-06 eta: 1:39:58 time: 0.3638 data_time: 0.1129 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 12:31:16 - mmengine - INFO - Epoch(train) [6][25500/42151] lr: 3.0000e-06 eta: 1:39:22 time: 0.3278 data_time: 0.1222 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 12:31:50 - mmengine - INFO - Epoch(train) [6][25600/42151] lr: 3.0000e-06 eta: 1:38:46 time: 0.3148 data_time: 0.1116 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 12:32:24 - mmengine - INFO - Epoch(train) [6][25700/42151] lr: 3.0000e-06 eta: 1:38:10 time: 0.3537 data_time: 0.1543 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 12:32:57 - mmengine - INFO - Epoch(train) [6][25800/42151] lr: 3.0000e-06 eta: 1:37:34 time: 0.2994 data_time: 0.0801 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 12:33:31 - mmengine - INFO - Epoch(train) [6][25900/42151] lr: 3.0000e-06 eta: 1:36:58 time: 0.3380 data_time: 0.1101 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 12:34:05 - mmengine - INFO - Epoch(train) [6][26000/42151] lr: 3.0000e-06 eta: 1:36:22 time: 0.3313 data_time: 0.1095 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 12:34:39 - mmengine - INFO - Epoch(train) [6][26100/42151] lr: 3.0000e-06 eta: 1:35:46 time: 0.3311 data_time: 0.1308 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:35:13 - mmengine - INFO - Epoch(train) [6][26200/42151] lr: 3.0000e-06 eta: 1:35:10 time: 0.3147 data_time: 0.1092 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 12:35:29 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:35:47 - mmengine - INFO - Epoch(train) [6][26300/42151] lr: 3.0000e-06 eta: 1:34:34 time: 0.3834 data_time: 0.1728 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 12:36:22 - mmengine - INFO - Epoch(train) [6][26400/42151] lr: 3.0000e-06 eta: 1:33:58 time: 0.3210 data_time: 0.0893 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 12:36:57 - mmengine - INFO - Epoch(train) [6][26500/42151] lr: 3.0000e-06 eta: 1:33:22 time: 0.3229 data_time: 0.0990 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 12:37:31 - mmengine - INFO - Epoch(train) [6][26600/42151] lr: 3.0000e-06 eta: 1:32:47 time: 0.3583 data_time: 0.1232 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 12:38:05 - mmengine - INFO - Epoch(train) [6][26700/42151] lr: 3.0000e-06 eta: 1:32:11 time: 0.3095 data_time: 0.1085 memory: 7851 loss_ce: 0.0162 loss: 0.0162 2022/09/17 12:38:39 - mmengine - INFO - Epoch(train) [6][26800/42151] lr: 3.0000e-06 eta: 1:31:35 time: 0.3184 data_time: 0.1160 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 12:39:14 - mmengine - INFO - Epoch(train) [6][26900/42151] lr: 3.0000e-06 eta: 1:30:59 time: 0.3730 data_time: 0.1718 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 12:39:48 - mmengine - INFO - Epoch(train) [6][27000/42151] lr: 3.0000e-06 eta: 1:30:23 time: 0.3576 data_time: 0.1186 memory: 7851 loss_ce: 0.0130 loss: 0.0130 2022/09/17 12:40:22 - mmengine - INFO - Epoch(train) [6][27100/42151] lr: 3.0000e-06 eta: 1:29:47 time: 0.3185 data_time: 0.0992 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 12:40:56 - mmengine - INFO - Epoch(train) [6][27200/42151] lr: 3.0000e-06 eta: 1:29:11 time: 0.3370 data_time: 0.1179 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 12:41:12 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:41:30 - mmengine - INFO - Epoch(train) [6][27300/42151] lr: 3.0000e-06 eta: 1:28:35 time: 0.3137 data_time: 0.1111 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:42:04 - mmengine - INFO - Epoch(train) [6][27400/42151] lr: 3.0000e-06 eta: 1:27:59 time: 0.3096 data_time: 0.1103 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:42:38 - mmengine - INFO - Epoch(train) [6][27500/42151] lr: 3.0000e-06 eta: 1:27:23 time: 0.3594 data_time: 0.1574 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 12:43:12 - mmengine - INFO - Epoch(train) [6][27600/42151] lr: 3.0000e-06 eta: 1:26:47 time: 0.3203 data_time: 0.0837 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 12:43:46 - mmengine - INFO - Epoch(train) [6][27700/42151] lr: 3.0000e-06 eta: 1:26:12 time: 0.3173 data_time: 0.0949 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 12:44:20 - mmengine - INFO - Epoch(train) [6][27800/42151] lr: 3.0000e-06 eta: 1:25:36 time: 0.3465 data_time: 0.1205 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 12:44:54 - mmengine - INFO - Epoch(train) [6][27900/42151] lr: 3.0000e-06 eta: 1:25:00 time: 0.3287 data_time: 0.1238 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 12:45:28 - mmengine - INFO - Epoch(train) [6][28000/42151] lr: 3.0000e-06 eta: 1:24:24 time: 0.3284 data_time: 0.1209 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 12:46:03 - mmengine - INFO - Epoch(train) [6][28100/42151] lr: 3.0000e-06 eta: 1:23:48 time: 0.3607 data_time: 0.1583 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 12:46:38 - mmengine - INFO - Epoch(train) [6][28200/42151] lr: 3.0000e-06 eta: 1:23:12 time: 0.3594 data_time: 0.1216 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 12:46:54 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:47:12 - mmengine - INFO - Epoch(train) [6][28300/42151] lr: 3.0000e-06 eta: 1:22:36 time: 0.3249 data_time: 0.0997 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:47:46 - mmengine - INFO - Epoch(train) [6][28400/42151] lr: 3.0000e-06 eta: 1:22:00 time: 0.3640 data_time: 0.1291 memory: 7851 loss_ce: 0.0136 loss: 0.0136 2022/09/17 12:48:19 - mmengine - INFO - Epoch(train) [6][28500/42151] lr: 3.0000e-06 eta: 1:21:25 time: 0.3340 data_time: 0.1204 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 12:48:53 - mmengine - INFO - Epoch(train) [6][28600/42151] lr: 3.0000e-06 eta: 1:20:49 time: 0.3154 data_time: 0.1130 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 12:49:28 - mmengine - INFO - Epoch(train) [6][28700/42151] lr: 3.0000e-06 eta: 1:20:13 time: 0.3799 data_time: 0.1685 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 12:50:02 - mmengine - INFO - Epoch(train) [6][28800/42151] lr: 3.0000e-06 eta: 1:19:37 time: 0.3210 data_time: 0.0917 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 12:50:37 - mmengine - INFO - Epoch(train) [6][28900/42151] lr: 3.0000e-06 eta: 1:19:01 time: 0.3241 data_time: 0.0980 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 12:51:11 - mmengine - INFO - Epoch(train) [6][29000/42151] lr: 3.0000e-06 eta: 1:18:25 time: 0.3742 data_time: 0.1458 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:51:46 - mmengine - INFO - Epoch(train) [6][29100/42151] lr: 3.0000e-06 eta: 1:17:49 time: 0.3223 data_time: 0.1205 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 12:52:20 - mmengine - INFO - Epoch(train) [6][29200/42151] lr: 3.0000e-06 eta: 1:17:13 time: 0.3301 data_time: 0.1139 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 12:52:37 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:52:56 - mmengine - INFO - Epoch(train) [6][29300/42151] lr: 3.0000e-06 eta: 1:16:38 time: 0.3775 data_time: 0.1731 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 12:53:30 - mmengine - INFO - Epoch(train) [6][29400/42151] lr: 3.0000e-06 eta: 1:16:02 time: 0.3222 data_time: 0.0919 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 12:54:05 - mmengine - INFO - Epoch(train) [6][29500/42151] lr: 3.0000e-06 eta: 1:15:26 time: 0.3323 data_time: 0.1065 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 12:54:41 - mmengine - INFO - Epoch(train) [6][29600/42151] lr: 3.0000e-06 eta: 1:14:50 time: 0.3743 data_time: 0.1292 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 12:55:15 - mmengine - INFO - Epoch(train) [6][29700/42151] lr: 3.0000e-06 eta: 1:14:14 time: 0.3232 data_time: 0.1221 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 12:55:51 - mmengine - INFO - Epoch(train) [6][29800/42151] lr: 3.0000e-06 eta: 1:13:39 time: 0.3825 data_time: 0.1380 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 12:56:25 - mmengine - INFO - Epoch(train) [6][29900/42151] lr: 3.0000e-06 eta: 1:13:03 time: 0.3561 data_time: 0.1539 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 12:57:00 - mmengine - INFO - Epoch(train) [6][30000/42151] lr: 3.0000e-06 eta: 1:12:27 time: 0.3045 data_time: 0.0828 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 12:57:35 - mmengine - INFO - Epoch(train) [6][30100/42151] lr: 3.0000e-06 eta: 1:11:51 time: 0.3419 data_time: 0.1121 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 12:58:10 - mmengine - INFO - Epoch(train) [6][30200/42151] lr: 3.0000e-06 eta: 1:11:15 time: 0.3474 data_time: 0.1239 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 12:58:26 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 12:58:44 - mmengine - INFO - Epoch(train) [6][30300/42151] lr: 3.0000e-06 eta: 1:10:39 time: 0.3211 data_time: 0.1213 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 12:59:19 - mmengine - INFO - Epoch(train) [6][30400/42151] lr: 3.0000e-06 eta: 1:10:04 time: 0.3199 data_time: 0.1154 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 12:59:53 - mmengine - INFO - Epoch(train) [6][30500/42151] lr: 3.0000e-06 eta: 1:09:28 time: 0.3790 data_time: 0.1737 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 13:00:28 - mmengine - INFO - Epoch(train) [6][30600/42151] lr: 3.0000e-06 eta: 1:08:52 time: 0.3215 data_time: 0.0931 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 13:01:03 - mmengine - INFO - Epoch(train) [6][30700/42151] lr: 3.0000e-06 eta: 1:08:16 time: 0.3391 data_time: 0.1124 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 13:01:37 - mmengine - INFO - Epoch(train) [6][30800/42151] lr: 3.0000e-06 eta: 1:07:40 time: 0.3366 data_time: 0.1118 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 13:02:12 - mmengine - INFO - Epoch(train) [6][30900/42151] lr: 3.0000e-06 eta: 1:07:04 time: 0.3333 data_time: 0.1283 memory: 7851 loss_ce: 0.0169 loss: 0.0169 2022/09/17 13:02:47 - mmengine - INFO - Epoch(train) [6][31000/42151] lr: 3.0000e-06 eta: 1:06:29 time: 0.3346 data_time: 0.1270 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 13:03:21 - mmengine - INFO - Epoch(train) [6][31100/42151] lr: 3.0000e-06 eta: 1:05:53 time: 0.3700 data_time: 0.1598 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 13:03:55 - mmengine - INFO - Epoch(train) [6][31200/42151] lr: 3.0000e-06 eta: 1:05:17 time: 0.3219 data_time: 0.1009 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 13:04:11 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:04:30 - mmengine - INFO - Epoch(train) [6][31300/42151] lr: 3.0000e-06 eta: 1:04:41 time: 0.3635 data_time: 0.1357 memory: 7851 loss_ce: 0.0168 loss: 0.0168 2022/09/17 13:05:05 - mmengine - INFO - Epoch(train) [6][31400/42151] lr: 3.0000e-06 eta: 1:04:05 time: 0.3368 data_time: 0.1131 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 13:05:39 - mmengine - INFO - Epoch(train) [6][31500/42151] lr: 3.0000e-06 eta: 1:03:29 time: 0.3389 data_time: 0.1282 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 13:06:13 - mmengine - INFO - Epoch(train) [6][31600/42151] lr: 3.0000e-06 eta: 1:02:54 time: 0.3105 data_time: 0.1093 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 13:06:49 - mmengine - INFO - Epoch(train) [6][31700/42151] lr: 3.0000e-06 eta: 1:02:18 time: 0.3853 data_time: 0.1657 memory: 7851 loss_ce: 0.0161 loss: 0.0161 2022/09/17 13:07:23 - mmengine - INFO - Epoch(train) [6][31800/42151] lr: 3.0000e-06 eta: 1:01:42 time: 0.3265 data_time: 0.1015 memory: 7851 loss_ce: 0.0130 loss: 0.0130 2022/09/17 13:07:58 - mmengine - INFO - Epoch(train) [6][31900/42151] lr: 3.0000e-06 eta: 1:01:06 time: 0.3818 data_time: 0.1596 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 13:08:33 - mmengine - INFO - Epoch(train) [6][32000/42151] lr: 3.0000e-06 eta: 1:00:30 time: 0.3417 data_time: 0.1169 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 13:09:08 - mmengine - INFO - Epoch(train) [6][32100/42151] lr: 3.0000e-06 eta: 0:59:54 time: 0.3306 data_time: 0.1284 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 13:09:43 - mmengine - INFO - Epoch(train) [6][32200/42151] lr: 3.0000e-06 eta: 0:59:19 time: 0.3315 data_time: 0.1245 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 13:09:58 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:10:18 - mmengine - INFO - Epoch(train) [6][32300/42151] lr: 3.0000e-06 eta: 0:58:43 time: 0.3794 data_time: 0.1779 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 13:10:52 - mmengine - INFO - Epoch(train) [6][32400/42151] lr: 3.0000e-06 eta: 0:58:07 time: 0.3195 data_time: 0.0958 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 13:11:27 - mmengine - INFO - Epoch(train) [6][32500/42151] lr: 3.0000e-06 eta: 0:57:31 time: 0.3753 data_time: 0.1531 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 13:12:02 - mmengine - INFO - Epoch(train) [6][32600/42151] lr: 3.0000e-06 eta: 0:56:55 time: 0.3313 data_time: 0.1108 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 13:12:36 - mmengine - INFO - Epoch(train) [6][32700/42151] lr: 3.0000e-06 eta: 0:56:20 time: 0.3485 data_time: 0.1412 memory: 7851 loss_ce: 0.0174 loss: 0.0174 2022/09/17 13:13:10 - mmengine - INFO - Epoch(train) [6][32800/42151] lr: 3.0000e-06 eta: 0:55:44 time: 0.3292 data_time: 0.1246 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 13:13:45 - mmengine - INFO - Epoch(train) [6][32900/42151] lr: 3.0000e-06 eta: 0:55:08 time: 0.3617 data_time: 0.1550 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 13:14:18 - mmengine - INFO - Epoch(train) [6][33000/42151] lr: 3.0000e-06 eta: 0:54:32 time: 0.3222 data_time: 0.0933 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 13:14:54 - mmengine - INFO - Epoch(train) [6][33100/42151] lr: 3.0000e-06 eta: 0:53:56 time: 0.3483 data_time: 0.1065 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 13:15:27 - mmengine - INFO - Epoch(train) [6][33200/42151] lr: 3.0000e-06 eta: 0:53:21 time: 0.3452 data_time: 0.1174 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 13:15:43 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:16:02 - mmengine - INFO - Epoch(train) [6][33300/42151] lr: 3.0000e-06 eta: 0:52:45 time: 0.3719 data_time: 0.1592 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 13:16:35 - mmengine - INFO - Epoch(train) [6][33400/42151] lr: 3.0000e-06 eta: 0:52:09 time: 0.3109 data_time: 0.1112 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 13:17:11 - mmengine - INFO - Epoch(train) [6][33500/42151] lr: 3.0000e-06 eta: 0:51:33 time: 0.3596 data_time: 0.1511 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 13:17:46 - mmengine - INFO - Epoch(train) [6][33600/42151] lr: 3.0000e-06 eta: 0:50:57 time: 0.3310 data_time: 0.0844 memory: 7851 loss_ce: 0.0166 loss: 0.0166 2022/09/17 13:18:20 - mmengine - INFO - Epoch(train) [6][33700/42151] lr: 3.0000e-06 eta: 0:50:21 time: 0.3505 data_time: 0.1173 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 13:18:54 - mmengine - INFO - Epoch(train) [6][33800/42151] lr: 3.0000e-06 eta: 0:49:46 time: 0.3310 data_time: 0.1085 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 13:19:28 - mmengine - INFO - Epoch(train) [6][33900/42151] lr: 3.0000e-06 eta: 0:49:10 time: 0.3678 data_time: 0.1679 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 13:20:02 - mmengine - INFO - Epoch(train) [6][34000/42151] lr: 3.0000e-06 eta: 0:48:34 time: 0.3277 data_time: 0.1244 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 13:20:36 - mmengine - INFO - Epoch(train) [6][34100/42151] lr: 3.0000e-06 eta: 0:47:58 time: 0.3698 data_time: 0.1678 memory: 7851 loss_ce: 0.0150 loss: 0.0150 2022/09/17 13:21:09 - mmengine - INFO - Epoch(train) [6][34200/42151] lr: 3.0000e-06 eta: 0:47:22 time: 0.3124 data_time: 0.0899 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 13:21:25 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:21:43 - mmengine - INFO - Epoch(train) [6][34300/42151] lr: 3.0000e-06 eta: 0:46:47 time: 0.3313 data_time: 0.1065 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 13:22:18 - mmengine - INFO - Epoch(train) [6][34400/42151] lr: 3.0000e-06 eta: 0:46:11 time: 0.3582 data_time: 0.1164 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 13:22:53 - mmengine - INFO - Epoch(train) [6][34500/42151] lr: 3.0000e-06 eta: 0:45:35 time: 0.3587 data_time: 0.1509 memory: 7851 loss_ce: 0.0170 loss: 0.0170 2022/09/17 13:23:28 - mmengine - INFO - Epoch(train) [6][34600/42151] lr: 3.0000e-06 eta: 0:44:59 time: 0.3368 data_time: 0.1326 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 13:24:04 - mmengine - INFO - Epoch(train) [6][34700/42151] lr: 3.0000e-06 eta: 0:44:23 time: 0.4227 data_time: 0.1803 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 13:24:38 - mmengine - INFO - Epoch(train) [6][34800/42151] lr: 3.0000e-06 eta: 0:43:48 time: 0.3184 data_time: 0.0820 memory: 7851 loss_ce: 0.0137 loss: 0.0137 2022/09/17 13:25:14 - mmengine - INFO - Epoch(train) [6][34900/42151] lr: 3.0000e-06 eta: 0:43:12 time: 0.3547 data_time: 0.1194 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 13:25:48 - mmengine - INFO - Epoch(train) [6][35000/42151] lr: 3.0000e-06 eta: 0:42:36 time: 0.3536 data_time: 0.1180 memory: 7851 loss_ce: 0.0123 loss: 0.0123 2022/09/17 13:26:23 - mmengine - INFO - Epoch(train) [6][35100/42151] lr: 3.0000e-06 eta: 0:42:00 time: 0.3760 data_time: 0.1678 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 13:26:57 - mmengine - INFO - Epoch(train) [6][35200/42151] lr: 3.0000e-06 eta: 0:41:25 time: 0.3363 data_time: 0.1270 memory: 7851 loss_ce: 0.0142 loss: 0.0142 2022/09/17 13:27:13 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:27:32 - mmengine - INFO - Epoch(train) [6][35300/42151] lr: 3.0000e-06 eta: 0:40:49 time: 0.3962 data_time: 0.1775 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 13:28:07 - mmengine - INFO - Epoch(train) [6][35400/42151] lr: 3.0000e-06 eta: 0:40:13 time: 0.3217 data_time: 0.0866 memory: 7851 loss_ce: 0.0139 loss: 0.0139 2022/09/17 13:28:42 - mmengine - INFO - Epoch(train) [6][35500/42151] lr: 3.0000e-06 eta: 0:39:37 time: 0.3567 data_time: 0.1093 memory: 7851 loss_ce: 0.0124 loss: 0.0124 2022/09/17 13:29:16 - mmengine - INFO - Epoch(train) [6][35600/42151] lr: 3.0000e-06 eta: 0:39:01 time: 0.3544 data_time: 0.1250 memory: 7851 loss_ce: 0.0135 loss: 0.0135 2022/09/17 13:29:51 - mmengine - INFO - Epoch(train) [6][35700/42151] lr: 3.0000e-06 eta: 0:38:26 time: 0.3669 data_time: 0.1548 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 13:30:26 - mmengine - INFO - Epoch(train) [6][35800/42151] lr: 3.0000e-06 eta: 0:37:50 time: 0.3320 data_time: 0.1209 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 13:31:02 - mmengine - INFO - Epoch(train) [6][35900/42151] lr: 3.0000e-06 eta: 0:37:14 time: 0.3931 data_time: 0.1786 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 13:31:36 - mmengine - INFO - Epoch(train) [6][36000/42151] lr: 3.0000e-06 eta: 0:36:38 time: 0.3113 data_time: 0.0825 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 13:32:11 - mmengine - INFO - Epoch(train) [6][36100/42151] lr: 3.0000e-06 eta: 0:36:03 time: 0.3568 data_time: 0.1215 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 13:32:46 - mmengine - INFO - Epoch(train) [6][36200/42151] lr: 3.0000e-06 eta: 0:35:27 time: 0.3561 data_time: 0.1246 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 13:33:03 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:33:22 - mmengine - INFO - Epoch(train) [6][36300/42151] lr: 3.0000e-06 eta: 0:34:51 time: 0.3720 data_time: 0.1631 memory: 7851 loss_ce: 0.0134 loss: 0.0134 2022/09/17 13:33:56 - mmengine - INFO - Epoch(train) [6][36400/42151] lr: 3.0000e-06 eta: 0:34:15 time: 0.3219 data_time: 0.1181 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 13:34:31 - mmengine - INFO - Epoch(train) [6][36500/42151] lr: 3.0000e-06 eta: 0:33:40 time: 0.3727 data_time: 0.1692 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 13:35:06 - mmengine - INFO - Epoch(train) [6][36600/42151] lr: 3.0000e-06 eta: 0:33:04 time: 0.3292 data_time: 0.0870 memory: 7851 loss_ce: 0.0159 loss: 0.0159 2022/09/17 13:35:40 - mmengine - INFO - Epoch(train) [6][36700/42151] lr: 3.0000e-06 eta: 0:32:28 time: 0.3345 data_time: 0.1017 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 13:36:15 - mmengine - INFO - Epoch(train) [6][36800/42151] lr: 3.0000e-06 eta: 0:31:52 time: 0.4065 data_time: 0.1426 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 13:36:50 - mmengine - INFO - Epoch(train) [6][36900/42151] lr: 3.0000e-06 eta: 0:31:16 time: 0.3510 data_time: 0.1381 memory: 7851 loss_ce: 0.0147 loss: 0.0147 2022/09/17 13:37:25 - mmengine - INFO - Epoch(train) [6][37000/42151] lr: 3.0000e-06 eta: 0:30:41 time: 0.3513 data_time: 0.1310 memory: 7851 loss_ce: 0.0182 loss: 0.0182 2022/09/17 13:38:00 - mmengine - INFO - Epoch(train) [6][37100/42151] lr: 3.0000e-06 eta: 0:30:05 time: 0.3794 data_time: 0.1741 memory: 7851 loss_ce: 0.0163 loss: 0.0163 2022/09/17 13:38:35 - mmengine - INFO - Epoch(train) [6][37200/42151] lr: 3.0000e-06 eta: 0:29:29 time: 0.3114 data_time: 0.0849 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 13:38:51 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:39:11 - mmengine - INFO - Epoch(train) [6][37300/42151] lr: 3.0000e-06 eta: 0:28:53 time: 0.3348 data_time: 0.1040 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 13:39:46 - mmengine - INFO - Epoch(train) [6][37400/42151] lr: 3.0000e-06 eta: 0:28:18 time: 0.3914 data_time: 0.1526 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 13:40:21 - mmengine - INFO - Epoch(train) [6][37500/42151] lr: 3.0000e-06 eta: 0:27:42 time: 0.3236 data_time: 0.1192 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 13:40:56 - mmengine - INFO - Epoch(train) [6][37600/42151] lr: 3.0000e-06 eta: 0:27:06 time: 0.3411 data_time: 0.1331 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 13:41:31 - mmengine - INFO - Epoch(train) [6][37700/42151] lr: 3.0000e-06 eta: 0:26:30 time: 0.3761 data_time: 0.1679 memory: 7851 loss_ce: 0.0132 loss: 0.0132 2022/09/17 13:42:05 - mmengine - INFO - Epoch(train) [6][37800/42151] lr: 3.0000e-06 eta: 0:25:55 time: 0.3115 data_time: 0.0867 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 13:42:41 - mmengine - INFO - Epoch(train) [6][37900/42151] lr: 3.0000e-06 eta: 0:25:19 time: 0.3293 data_time: 0.0993 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 13:43:16 - mmengine - INFO - Epoch(train) [6][38000/42151] lr: 3.0000e-06 eta: 0:24:43 time: 0.3915 data_time: 0.1508 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 13:43:51 - mmengine - INFO - Epoch(train) [6][38100/42151] lr: 3.0000e-06 eta: 0:24:07 time: 0.3334 data_time: 0.1260 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 13:44:26 - mmengine - INFO - Epoch(train) [6][38200/42151] lr: 3.0000e-06 eta: 0:23:32 time: 0.3535 data_time: 0.1419 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 13:44:42 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:45:01 - mmengine - INFO - Epoch(train) [6][38300/42151] lr: 3.0000e-06 eta: 0:22:56 time: 0.3876 data_time: 0.1786 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 13:45:36 - mmengine - INFO - Epoch(train) [6][38400/42151] lr: 3.0000e-06 eta: 0:22:20 time: 0.3306 data_time: 0.0990 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 13:46:11 - mmengine - INFO - Epoch(train) [6][38500/42151] lr: 3.0000e-06 eta: 0:21:44 time: 0.3347 data_time: 0.1047 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 13:46:45 - mmengine - INFO - Epoch(train) [6][38600/42151] lr: 3.0000e-06 eta: 0:21:09 time: 0.3760 data_time: 0.1461 memory: 7851 loss_ce: 0.0155 loss: 0.0155 2022/09/17 13:47:20 - mmengine - INFO - Epoch(train) [6][38700/42151] lr: 3.0000e-06 eta: 0:20:33 time: 0.3434 data_time: 0.1317 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 13:47:55 - mmengine - INFO - Epoch(train) [6][38800/42151] lr: 3.0000e-06 eta: 0:19:57 time: 0.3432 data_time: 0.1303 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 13:48:29 - mmengine - INFO - Epoch(train) [6][38900/42151] lr: 3.0000e-06 eta: 0:19:21 time: 0.3751 data_time: 0.1725 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 13:49:03 - mmengine - INFO - Epoch(train) [6][39000/42151] lr: 3.0000e-06 eta: 0:18:46 time: 0.3352 data_time: 0.1004 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 13:49:39 - mmengine - INFO - Epoch(train) [6][39100/42151] lr: 3.0000e-06 eta: 0:18:10 time: 0.3528 data_time: 0.1172 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 13:50:14 - mmengine - INFO - Epoch(train) [6][39200/42151] lr: 3.0000e-06 eta: 0:17:34 time: 0.3878 data_time: 0.1588 memory: 7851 loss_ce: 0.0138 loss: 0.0138 2022/09/17 13:50:30 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:50:49 - mmengine - INFO - Epoch(train) [6][39300/42151] lr: 3.0000e-06 eta: 0:16:58 time: 0.3422 data_time: 0.1217 memory: 7851 loss_ce: 0.0172 loss: 0.0172 2022/09/17 13:51:23 - mmengine - INFO - Epoch(train) [6][39400/42151] lr: 3.0000e-06 eta: 0:16:23 time: 0.3519 data_time: 0.1379 memory: 7851 loss_ce: 0.0160 loss: 0.0160 2022/09/17 13:51:58 - mmengine - INFO - Epoch(train) [6][39500/42151] lr: 3.0000e-06 eta: 0:15:47 time: 0.3768 data_time: 0.1737 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 13:52:33 - mmengine - INFO - Epoch(train) [6][39600/42151] lr: 3.0000e-06 eta: 0:15:11 time: 0.3335 data_time: 0.0999 memory: 7851 loss_ce: 0.0167 loss: 0.0167 2022/09/17 13:53:07 - mmengine - INFO - Epoch(train) [6][39700/42151] lr: 3.0000e-06 eta: 0:14:35 time: 0.3341 data_time: 0.1101 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 13:53:42 - mmengine - INFO - Epoch(train) [6][39800/42151] lr: 3.0000e-06 eta: 0:14:00 time: 0.3986 data_time: 0.1606 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 13:54:17 - mmengine - INFO - Epoch(train) [6][39900/42151] lr: 3.0000e-06 eta: 0:13:24 time: 0.3426 data_time: 0.1379 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 13:54:52 - mmengine - INFO - Epoch(train) [6][40000/42151] lr: 3.0000e-06 eta: 0:12:48 time: 0.3285 data_time: 0.1238 memory: 7851 loss_ce: 0.0154 loss: 0.0154 2022/09/17 13:55:26 - mmengine - INFO - Epoch(train) [6][40100/42151] lr: 3.0000e-06 eta: 0:12:12 time: 0.3771 data_time: 0.1675 memory: 7851 loss_ce: 0.0141 loss: 0.0141 2022/09/17 13:56:00 - mmengine - INFO - Epoch(train) [6][40200/42151] lr: 3.0000e-06 eta: 0:11:37 time: 0.3219 data_time: 0.0951 memory: 7851 loss_ce: 0.0140 loss: 0.0140 2022/09/17 13:56:16 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 13:56:36 - mmengine - INFO - Epoch(train) [6][40300/42151] lr: 3.0000e-06 eta: 0:11:01 time: 0.3574 data_time: 0.1061 memory: 7851 loss_ce: 0.0158 loss: 0.0158 2022/09/17 13:57:11 - mmengine - INFO - Epoch(train) [6][40400/42151] lr: 3.0000e-06 eta: 0:10:25 time: 0.4000 data_time: 0.1523 memory: 7851 loss_ce: 0.0145 loss: 0.0145 2022/09/17 13:57:45 - mmengine - INFO - Epoch(train) [6][40500/42151] lr: 3.0000e-06 eta: 0:09:49 time: 0.3216 data_time: 0.1184 memory: 7851 loss_ce: 0.0156 loss: 0.0156 2022/09/17 13:58:20 - mmengine - INFO - Epoch(train) [6][40600/42151] lr: 3.0000e-06 eta: 0:09:14 time: 0.3360 data_time: 0.1263 memory: 7851 loss_ce: 0.0153 loss: 0.0153 2022/09/17 13:58:56 - mmengine - INFO - Epoch(train) [6][40700/42151] lr: 3.0000e-06 eta: 0:08:38 time: 0.4266 data_time: 0.1884 memory: 7851 loss_ce: 0.0143 loss: 0.0143 2022/09/17 13:59:31 - mmengine - INFO - Epoch(train) [6][40800/42151] lr: 3.0000e-06 eta: 0:08:02 time: 0.3215 data_time: 0.0833 memory: 7851 loss_ce: 0.0149 loss: 0.0149 2022/09/17 14:00:07 - mmengine - INFO - Epoch(train) [6][40900/42151] lr: 3.0000e-06 eta: 0:07:26 time: 0.3930 data_time: 0.1028 memory: 7851 loss_ce: 0.0151 loss: 0.0151 2022/09/17 14:00:41 - mmengine - INFO - Epoch(train) [6][41000/42151] lr: 3.0000e-06 eta: 0:06:51 time: 0.3773 data_time: 0.1492 memory: 7851 loss_ce: 0.0157 loss: 0.0157 2022/09/17 14:01:16 - mmengine - INFO - Epoch(train) [6][41100/42151] lr: 3.0000e-06 eta: 0:06:15 time: 0.3468 data_time: 0.1218 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 14:01:50 - mmengine - INFO - Epoch(train) [6][41200/42151] lr: 3.0000e-06 eta: 0:05:39 time: 0.3388 data_time: 0.1279 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 14:02:05 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 14:02:24 - mmengine - INFO - Epoch(train) [6][41300/42151] lr: 3.0000e-06 eta: 0:05:04 time: 0.3635 data_time: 0.1553 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 14:02:59 - mmengine - INFO - Epoch(train) [6][41400/42151] lr: 3.0000e-06 eta: 0:04:28 time: 0.3245 data_time: 0.0884 memory: 7851 loss_ce: 0.0146 loss: 0.0146 2022/09/17 14:03:33 - mmengine - INFO - Epoch(train) [6][41500/42151] lr: 3.0000e-06 eta: 0:03:52 time: 0.3581 data_time: 0.1251 memory: 7851 loss_ce: 0.0133 loss: 0.0133 2022/09/17 14:04:07 - mmengine - INFO - Epoch(train) [6][41600/42151] lr: 3.0000e-06 eta: 0:03:16 time: 0.3519 data_time: 0.1243 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 14:04:42 - mmengine - INFO - Epoch(train) [6][41700/42151] lr: 3.0000e-06 eta: 0:02:41 time: 0.3308 data_time: 0.1223 memory: 7851 loss_ce: 0.0152 loss: 0.0152 2022/09/17 14:05:15 - mmengine - INFO - Epoch(train) [6][41800/42151] lr: 3.0000e-06 eta: 0:02:05 time: 0.3541 data_time: 0.1430 memory: 7851 loss_ce: 0.0165 loss: 0.0165 2022/09/17 14:05:50 - mmengine - INFO - Epoch(train) [6][41900/42151] lr: 3.0000e-06 eta: 0:01:29 time: 0.3654 data_time: 0.1590 memory: 7851 loss_ce: 0.0144 loss: 0.0144 2022/09/17 14:06:24 - mmengine - INFO - Epoch(train) [6][42000/42151] lr: 3.0000e-06 eta: 0:00:53 time: 0.3152 data_time: 0.0831 memory: 7851 loss_ce: 0.0148 loss: 0.0148 2022/09/17 14:06:59 - mmengine - INFO - Epoch(train) [6][42100/42151] lr: 3.0000e-06 eta: 0:00:18 time: 0.3611 data_time: 0.1252 memory: 7851 loss_ce: 0.0164 loss: 0.0164 2022/09/17 14:07:15 - mmengine - INFO - Exp name: nrtr_modality-transform_6e_st_mj_20220916_103322 2022/09/17 14:07:15 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/09/17 14:07:55 - mmengine - INFO - Epoch(val) [6][100/7672] eta: 0:45:12 time: 0.3583 data_time: 0.0008 memory: 7851 2022/09/17 14:08:26 - mmengine - INFO - Epoch(val) [6][200/7672] eta: 0:38:51 time: 0.3120 data_time: 0.0008 memory: 580 2022/09/17 14:08:57 - mmengine - INFO - Epoch(val) [6][300/7672] eta: 0:26:30 time: 0.2157 data_time: 0.0008 memory: 580 2022/09/17 14:09:18 - mmengine - INFO - Epoch(val) [6][400/7672] eta: 0:25:02 time: 0.2067 data_time: 0.0008 memory: 580 2022/09/17 14:09:40 - mmengine - INFO - Epoch(val) [6][500/7672] eta: 0:24:46 time: 0.2073 data_time: 0.0008 memory: 580 2022/09/17 14:10:01 - mmengine - INFO - Epoch(val) [6][600/7672] eta: 0:26:01 time: 0.2208 data_time: 0.0008 memory: 580 2022/09/17 14:10:22 - mmengine - INFO - Epoch(val) [6][700/7672] eta: 0:24:17 time: 0.2090 data_time: 0.0008 memory: 580 2022/09/17 14:10:44 - mmengine - INFO - Epoch(val) [6][800/7672] eta: 0:23:58 time: 0.2093 data_time: 0.0008 memory: 580 2022/09/17 14:11:05 - mmengine - INFO - Epoch(val) [6][900/7672] eta: 0:25:02 time: 0.2219 data_time: 0.0009 memory: 580 2022/09/17 14:11:27 - mmengine - INFO - Epoch(val) [6][1000/7672] eta: 0:25:17 time: 0.2274 data_time: 0.0015 memory: 580 2022/09/17 14:11:48 - mmengine - INFO - Epoch(val) [6][1100/7672] eta: 0:23:20 time: 0.2132 data_time: 0.0008 memory: 580 2022/09/17 14:12:09 - mmengine - INFO - Epoch(val) [6][1200/7672] eta: 0:22:27 time: 0.2082 data_time: 0.0010 memory: 580 2022/09/17 14:12:29 - mmengine - INFO - Epoch(val) [6][1300/7672] eta: 0:22:26 time: 0.2113 data_time: 0.0008 memory: 580 2022/09/17 14:12:51 - mmengine - INFO - Epoch(val) [6][1400/7672] eta: 0:22:07 time: 0.2117 data_time: 0.0008 memory: 580 2022/09/17 14:13:13 - mmengine - INFO - Epoch(val) [6][1500/7672] eta: 0:21:14 time: 0.2065 data_time: 0.0008 memory: 580 2022/09/17 14:13:34 - mmengine - INFO - Epoch(val) [6][1600/7672] eta: 0:20:34 time: 0.2033 data_time: 0.0008 memory: 580 2022/09/17 14:13:55 - mmengine - INFO - Epoch(val) [6][1700/7672] eta: 0:21:07 time: 0.2122 data_time: 0.0014 memory: 580 2022/09/17 14:14:17 - mmengine - INFO - Epoch(val) [6][1800/7672] eta: 0:20:23 time: 0.2084 data_time: 0.0010 memory: 580 2022/09/17 14:14:38 - mmengine - INFO - Epoch(val) [6][1900/7672] eta: 0:19:52 time: 0.2066 data_time: 0.0011 memory: 580 2022/09/17 14:14:59 - mmengine - INFO - Epoch(val) [6][2000/7672] eta: 0:19:36 time: 0.2075 data_time: 0.0010 memory: 580 2022/09/17 14:15:21 - mmengine - INFO - Epoch(val) [6][2100/7672] eta: 0:19:59 time: 0.2152 data_time: 0.0008 memory: 580 2022/09/17 14:15:42 - mmengine - INFO - Epoch(val) [6][2200/7672] eta: 0:21:24 time: 0.2348 data_time: 0.0008 memory: 580 2022/09/17 14:16:03 - mmengine - INFO - Epoch(val) [6][2300/7672] eta: 0:18:48 time: 0.2101 data_time: 0.0007 memory: 580 2022/09/17 14:16:24 - mmengine - INFO - Epoch(val) [6][2400/7672] eta: 0:17:59 time: 0.2048 data_time: 0.0008 memory: 580 2022/09/17 14:16:45 - mmengine - INFO - Epoch(val) [6][2500/7672] eta: 0:17:42 time: 0.2055 data_time: 0.0007 memory: 580 2022/09/17 14:17:07 - mmengine - INFO - Epoch(val) [6][2600/7672] eta: 0:19:09 time: 0.2266 data_time: 0.0011 memory: 580 2022/09/17 14:17:28 - mmengine - INFO - Epoch(val) [6][2700/7672] eta: 0:17:07 time: 0.2066 data_time: 0.0017 memory: 580 2022/09/17 14:17:49 - mmengine - INFO - Epoch(val) [6][2800/7672] eta: 0:16:57 time: 0.2088 data_time: 0.0008 memory: 580 2022/09/17 14:18:10 - mmengine - INFO - Epoch(val) [6][2900/7672] eta: 0:16:34 time: 0.2083 data_time: 0.0008 memory: 580 2022/09/17 14:18:31 - mmengine - INFO - Epoch(val) [6][3000/7672] eta: 0:16:13 time: 0.2084 data_time: 0.0008 memory: 580 2022/09/17 14:18:52 - mmengine - INFO - Epoch(val) [6][3100/7672] eta: 0:15:56 time: 0.2093 data_time: 0.0008 memory: 580 2022/09/17 14:19:14 - mmengine - INFO - Epoch(val) [6][3200/7672] eta: 0:16:03 time: 0.2154 data_time: 0.0007 memory: 580 2022/09/17 14:19:35 - mmengine - INFO - Epoch(val) [6][3300/7672] eta: 0:15:56 time: 0.2189 data_time: 0.0008 memory: 580 2022/09/17 14:19:56 - mmengine - INFO - Epoch(val) [6][3400/7672] eta: 0:16:06 time: 0.2263 data_time: 0.0020 memory: 580 2022/09/17 14:20:18 - mmengine - INFO - Epoch(val) [6][3500/7672] eta: 0:14:49 time: 0.2132 data_time: 0.0032 memory: 580 2022/09/17 14:20:39 - mmengine - INFO - Epoch(val) [6][3600/7672] eta: 0:14:05 time: 0.2077 data_time: 0.0014 memory: 580 2022/09/17 14:21:00 - mmengine - INFO - Epoch(val) [6][3700/7672] eta: 0:15:09 time: 0.2290 data_time: 0.0009 memory: 580 2022/09/17 14:21:22 - mmengine - INFO - Epoch(val) [6][3800/7672] eta: 0:13:44 time: 0.2129 data_time: 0.0008 memory: 580 2022/09/17 14:21:44 - mmengine - INFO - Epoch(val) [6][3900/7672] eta: 0:13:27 time: 0.2140 data_time: 0.0008 memory: 580 2022/09/17 14:22:05 - mmengine - INFO - Epoch(val) [6][4000/7672] eta: 0:12:39 time: 0.2068 data_time: 0.0008 memory: 580 2022/09/17 14:22:26 - mmengine - INFO - Epoch(val) [6][4100/7672] eta: 0:12:26 time: 0.2089 data_time: 0.0008 memory: 580 2022/09/17 14:22:47 - mmengine - INFO - Epoch(val) [6][4200/7672] eta: 0:12:24 time: 0.2144 data_time: 0.0009 memory: 580 2022/09/17 14:23:09 - mmengine - INFO - Epoch(val) [6][4300/7672] eta: 0:12:16 time: 0.2184 data_time: 0.0026 memory: 580 2022/09/17 14:23:30 - mmengine - INFO - Epoch(val) [6][4400/7672] eta: 0:11:20 time: 0.2079 data_time: 0.0009 memory: 580 2022/09/17 14:23:51 - mmengine - INFO - Epoch(val) [6][4500/7672] eta: 0:11:12 time: 0.2121 data_time: 0.0008 memory: 580 2022/09/17 14:24:12 - mmengine - INFO - Epoch(val) [6][4600/7672] eta: 0:10:19 time: 0.2017 data_time: 0.0011 memory: 580 2022/09/17 14:24:33 - mmengine - INFO - Epoch(val) [6][4700/7672] eta: 0:10:58 time: 0.2215 data_time: 0.0009 memory: 580 2022/09/17 14:24:55 - mmengine - INFO - Epoch(val) [6][4800/7672] eta: 0:10:26 time: 0.2180 data_time: 0.0008 memory: 580 2022/09/17 14:25:16 - mmengine - INFO - Epoch(val) [6][4900/7672] eta: 0:09:43 time: 0.2104 data_time: 0.0008 memory: 580 2022/09/17 14:25:37 - mmengine - INFO - Epoch(val) [6][5000/7672] eta: 0:09:11 time: 0.2065 data_time: 0.0010 memory: 580 2022/09/17 14:25:59 - mmengine - INFO - Epoch(val) [6][5100/7672] eta: 0:08:55 time: 0.2081 data_time: 0.0008 memory: 580 2022/09/17 14:26:21 - mmengine - INFO - Epoch(val) [6][5200/7672] eta: 0:09:08 time: 0.2220 data_time: 0.0008 memory: 580 2022/09/17 14:26:42 - mmengine - INFO - Epoch(val) [6][5300/7672] eta: 0:08:59 time: 0.2274 data_time: 0.0008 memory: 580 2022/09/17 14:27:04 - mmengine - INFO - Epoch(val) [6][5400/7672] eta: 0:08:11 time: 0.2165 data_time: 0.0008 memory: 580 2022/09/17 14:27:25 - mmengine - INFO - Epoch(val) [6][5500/7672] eta: 0:07:27 time: 0.2062 data_time: 0.0008 memory: 580 2022/09/17 14:27:46 - mmengine - INFO - Epoch(val) [6][5600/7672] eta: 0:07:11 time: 0.2082 data_time: 0.0008 memory: 580 2022/09/17 14:28:07 - mmengine - INFO - Epoch(val) [6][5700/7672] eta: 0:06:56 time: 0.2114 data_time: 0.0011 memory: 580 2022/09/17 14:28:29 - mmengine - INFO - Epoch(val) [6][5800/7672] eta: 0:06:24 time: 0.2055 data_time: 0.0010 memory: 580 2022/09/17 14:28:51 - mmengine - INFO - Epoch(val) [6][5900/7672] eta: 0:06:05 time: 0.2061 data_time: 0.0010 memory: 580 2022/09/17 14:29:12 - mmengine - INFO - Epoch(val) [6][6000/7672] eta: 0:05:41 time: 0.2043 data_time: 0.0011 memory: 580 2022/09/17 14:29:33 - mmengine - INFO - Epoch(val) [6][6100/7672] eta: 0:05:33 time: 0.2120 data_time: 0.0008 memory: 580 2022/09/17 14:29:54 - mmengine - INFO - Epoch(val) [6][6200/7672] eta: 0:05:07 time: 0.2089 data_time: 0.0008 memory: 580 2022/09/17 14:30:15 - mmengine - INFO - Epoch(val) [6][6300/7672] eta: 0:04:52 time: 0.2130 data_time: 0.0011 memory: 580 2022/09/17 14:30:36 - mmengine - INFO - Epoch(val) [6][6400/7672] eta: 0:04:22 time: 0.2063 data_time: 0.0008 memory: 580 2022/09/17 14:30:57 - mmengine - INFO - Epoch(val) [6][6500/7672] eta: 0:04:01 time: 0.2064 data_time: 0.0008 memory: 580 2022/09/17 14:31:19 - mmengine - INFO - Epoch(val) [6][6600/7672] eta: 0:03:50 time: 0.2149 data_time: 0.0022 memory: 580 2022/09/17 14:31:40 - mmengine - INFO - Epoch(val) [6][6700/7672] eta: 0:03:20 time: 0.2060 data_time: 0.0008 memory: 580 2022/09/17 14:32:01 - mmengine - INFO - Epoch(val) [6][6800/7672] eta: 0:03:09 time: 0.2168 data_time: 0.0008 memory: 580 2022/09/17 14:32:22 - mmengine - INFO - Epoch(val) [6][6900/7672] eta: 0:02:36 time: 0.2031 data_time: 0.0009 memory: 580 2022/09/17 14:32:44 - mmengine - INFO - Epoch(val) [6][7000/7672] eta: 0:02:16 time: 0.2028 data_time: 0.0008 memory: 580 2022/09/17 14:33:05 - mmengine - INFO - Epoch(val) [6][7100/7672] eta: 0:01:59 time: 0.2086 data_time: 0.0008 memory: 580 2022/09/17 14:33:27 - mmengine - INFO - Epoch(val) [6][7200/7672] eta: 0:01:38 time: 0.2088 data_time: 0.0008 memory: 580 2022/09/17 14:33:48 - mmengine - INFO - Epoch(val) [6][7300/7672] eta: 0:01:18 time: 0.2117 data_time: 0.0011 memory: 580 2022/09/17 14:34:10 - mmengine - INFO - Epoch(val) [6][7400/7672] eta: 0:00:56 time: 0.2067 data_time: 0.0008 memory: 580 2022/09/17 14:34:31 - mmengine - INFO - Epoch(val) [6][7500/7672] eta: 0:00:35 time: 0.2074 data_time: 0.0008 memory: 580 2022/09/17 14:34:52 - mmengine - INFO - Epoch(val) [6][7600/7672] eta: 0:00:14 time: 0.2065 data_time: 0.0008 memory: 580 2022/09/17 14:35:07 - mmengine - INFO - Epoch(val) [6][7672/7672] CUTE80/recog/word_acc_ignore_case_symbol: 0.7500 IIIT5K/recog/word_acc_ignore_case_symbol: 0.9150 SVT/recog/word_acc_ignore_case_symbol: 0.8825 SVTP/recog/word_acc_ignore_case_symbol: 0.7783 IC13/recog/word_acc_ignore_case_symbol: 0.9369 IC15/recog/word_acc_ignore_case_symbol: 0.7232