2023/09/05 22:44:44 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.9.17 (main, Jul 5 2023, 20:41:20) [GCC 11.2.0] CUDA available: True numpy_random_seed: 1863707841 GPU 0,1,2,3,4,5,6,7: NVIDIA GeForce RTX 3090 CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 PyTorch: 1.12.1+cu113 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.2 - Built with CuDNN 8.3.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.13.1+cu113 OpenCV: 4.8.0 MMEngine: 0.8.4 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 1863707841 diff_rank_seed: False deterministic: False Distributed launcher: pytorch Distributed training: True GPU number: 8 ------------------------------------------------------------ 2023/09/05 22:44:44 - mmengine - INFO - Config: anno_file_test = 'data/msrvtt/annotations/msrvtt_qa_test.json' anno_file_train = 'data/msrvtt/annotations/msrvtt_qa_train.json' anno_file_val = 'data/msrvtt/annotations/msrvtt_qa_val.json' answer_list_file = 'data/msrvtt/annotations/msrvtt_qa_answer_list.json' auto_scale_lr = dict(base_batch_size=32, enable=True) dataset_type = 'MSRVTTVQA' default_hooks = dict( checkpoint=dict(interval=1, save_best='auto', type='CheckpointHook'), logger=dict(ignore_last=False, interval=20, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), runtime_info=dict(type='RuntimeInfoHook'), sampler_seed=dict(type='DistSamplerSeedHook'), sync_buffers=dict(type='SyncBuffersHook'), timer=dict(type='IterTimerHook')) default_scope = 'mmaction' env_cfg = dict( cudnn_benchmark=False, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) file_client_args = dict(io_backend='disk') find_unused_parameters = True launcher = 'pytorch' load_from = None log_level = 'INFO' log_processor = dict(by_epoch=True, type='LogProcessor', window_size=20) model = dict( answer_list_path='data/msrvtt/annotations/msrvtt_qa_answer_list.json', data_preprocessor=dict( format_shape='NCTHW', mean=[ 128, ], std=[ 128, ], type='ActionDataPreprocessor'), gradient_checkpointing=True, init_cfg=dict(checkpoint='checkpoints/5M-pretrain.pth', type='Pretrained'), max_answer_len=5, max_question_len=25, num_ans_candidates=128, proj_dim=256, temperature=0.07, text_decoder=dict( add_pooling_layer=True, encoder_width=768, fusion_layer=0, num_hidden_layers=3, pretrained_model_name_or_path='bert-base-uncased', type='BertDecoder'), text_encoder=dict( add_pooling_layer=False, encoder_width=768, fusion_layer=9, pretrained_model_name_or_path='bert-base-uncased', type='XBertModel'), tokenizer=dict( pretrained_model_name_or_path='bert-base-uncased', type='VindLUTokenizer'), type='VindLUVQA', vision_encoder=dict( add_ln=True, config='microsoft/beit-base-patch16-224-pt22k-ft22k', encoder_width=768, tem_config=dict( num_frames=12, temporal_model_block='timesformer', temporal_model_config=dict(input_dim=768), temporal_model_position='last', use_temporal_position_embedding=True), type='BeitModel3D')) model_wrapper_cfg = dict(static_graph=True, type='MMDistributedDataParallel') optim_wrapper = dict( clip_grad=dict(max_norm=50, norm_type=2), optimizer=dict(lr=1e-05, type='AdamW', weight_decay=0.02), paramwise_cfg=dict( bias_decay_mult=0.0, bypass_duplicate=True, norm_decay_mult=0.0), type='AmpOptimWrapper') param_scheduler = [ dict( begin=0, by_epoch=True, convert_to_iter_based=True, end=1, start_factor=0.01, type='LinearLR'), dict( T_max=10, begin=1, by_epoch=True, convert_to_iter_based=True, end=10, eta_min_ratio=0.01, type='CosineAnnealingLR'), ] pretrained_ckpt_path = 'checkpoints/5M-pretrain.pth' randomness = dict(deterministic=False, diff_rank_seed=False, seed=None) resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=16, dataset=dict( ann_file='data/msrvtt/annotations/msrvtt_qa_test.json', data_prefix=dict(video='data/msrvtt/videos_2fps_224'), pipeline=[ dict(io_backend='disk', type='DecordInit'), dict( clip_len=1, frame_interval=1, num_clips=12, out_of_bound_opt='repeat_last', test_mode=True, type='SampleFrames'), dict(type='DecordDecode'), dict( interpolation='bicubic', keep_ratio=False, scale=( 224, 224, ), type='Resize'), dict(input_format='NCHW', type='FormatShape'), dict( algorithm_keys=( 'question', 'gt_answer', 'question_id', ), type='PackActionInputs'), ], type='MSRVTTVQA'), num_workers=4, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict(type='VQAAcc') test_pipeline = [ dict(io_backend='disk', type='DecordInit'), dict( clip_len=1, frame_interval=1, num_clips=12, out_of_bound_opt='repeat_last', test_mode=True, type='SampleFrames'), dict(type='DecordDecode'), dict( interpolation='bicubic', keep_ratio=False, scale=( 224, 224, ), type='Resize'), dict(input_format='NCHW', type='FormatShape'), dict( algorithm_keys=( 'question', 'gt_answer', 'question_id', ), type='PackActionInputs'), ] train_cfg = dict( max_epochs=10, type='EpochBasedTrainLoop', val_begin=1, val_interval=1) train_dataloader = dict( batch_size=8, dataset=dict( ann_file='data/msrvtt/annotations/msrvtt_qa_train.json', data_prefix=dict(video='data/msrvtt/videos_2fps_224'), pipeline=[ dict(io_backend='disk', type='DecordInit'), dict( clip_len=1, frame_interval=1, num_clips=12, out_of_bound_opt='repeat_last', type='SampleFrames'), dict(type='DecordDecode'), dict(area_range=( 0.5, 1.0, ), type='RandomResizedCrop'), dict( interpolation='bicubic', keep_ratio=False, scale=( 224, 224, ), type='Resize'), dict(flip_ratio=0.5, type='Flip'), dict(input_format='NCHW', type='FormatShape'), dict( algorithm_keys=( 'question', 'question_id', 'gt_answer', 'gt_answer_weight', ), type='PackActionInputs'), ], type='MSRVTTVQA'), num_workers=8, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(io_backend='disk', type='DecordInit'), dict( clip_len=1, frame_interval=1, num_clips=12, out_of_bound_opt='repeat_last', type='SampleFrames'), dict(type='DecordDecode'), dict(area_range=( 0.5, 1.0, ), type='RandomResizedCrop'), dict( interpolation='bicubic', keep_ratio=False, scale=( 224, 224, ), type='Resize'), dict(flip_ratio=0.5, type='Flip'), dict(input_format='NCHW', type='FormatShape'), dict( algorithm_keys=( 'question', 'question_id', 'gt_answer', 'gt_answer_weight', ), type='PackActionInputs'), ] val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=16, dataset=dict( ann_file='data/msrvtt/annotations/msrvtt_qa_val.json', data_prefix=dict(video='data/msrvtt/videos_2fps_224'), pipeline=[ dict(io_backend='disk', type='DecordInit'), dict( clip_len=1, frame_interval=1, num_clips=12, out_of_bound_opt='repeat_last', test_mode=True, type='SampleFrames'), dict(type='DecordDecode'), dict( interpolation='bicubic', keep_ratio=False, scale=( 224, 224, ), type='Resize'), dict(input_format='NCHW', type='FormatShape'), dict( algorithm_keys=( 'question', 'gt_answer', 'question_id', ), type='PackActionInputs'), ], type='MSRVTTVQA'), num_workers=4, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict(type='VQAAcc') val_pipeline = [ dict(io_backend='disk', type='DecordInit'), dict( clip_len=1, frame_interval=1, num_clips=12, out_of_bound_opt='repeat_last', test_mode=True, type='SampleFrames'), dict(type='DecordDecode'), dict( interpolation='bicubic', keep_ratio=False, scale=( 224, 224, ), type='Resize'), dict(input_format='NCHW', type='FormatShape'), dict( algorithm_keys=( 'question', 'gt_answer', 'question_id', ), type='PackActionInputs'), ] video_root = 'data/msrvtt/videos_2fps_224' vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( type='ActionVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) work_dir = 'work_dirs/vindlu_9_4/msrvtt_vqa_8x8_train_bicubic' 2023/09/05 22:44:56 - mmengine - INFO - build bert with cross_module: ca 2023/09/05 22:44:57 - mmengine - INFO - build bert with cross_module: ca 2023/09/05 22:44:58 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (VERY_LOW ) CheckpointHook -------------------- before_train_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (NORMAL ) DistSamplerSeedHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_layernorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_layernorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.embeddings.patch_embeddings.projection.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.0.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.1.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.2.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.3.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.4.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.5.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.6.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.7.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.8.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.9.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.10.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.attention.attention.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.attention.attention.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.layernorm_before.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.layernorm_before.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.layernorm_after.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.layernorm_after.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.temp_model.temporal_attn.out_proj.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.temp_model.norm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.temp_model.norm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.encoder.layer.11.temp_model.linear.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.pooler.layernorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- vision_encoder.pooler.layernorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.embeddings.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.embeddings.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.0.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.1.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.2.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.3.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.4.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.5.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.6.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.7.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.8.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.crossattention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.crossattention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.crossattention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.crossattention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.crossattention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.crossattention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.9.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.crossattention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.crossattention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.crossattention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.crossattention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.crossattention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.crossattention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.10.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.crossattention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.crossattention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.crossattention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.crossattention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.crossattention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.crossattention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_encoder.encoder.layer.11.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.embeddings.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.embeddings.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.crossattention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.crossattention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.crossattention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.crossattention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.crossattention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.crossattention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.0.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.crossattention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.crossattention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.crossattention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.crossattention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.crossattention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.crossattention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.1.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.attention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.attention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.attention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.attention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.attention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.attention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.crossattention.self.query.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.crossattention.self.key.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.crossattention.self.value.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.crossattention.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.crossattention.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.crossattention.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.intermediate.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.output.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.output.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.bert.encoder.layer.2.output.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.cls.predictions.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.cls.predictions.transform.dense.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.cls.predictions.transform.LayerNorm.weight:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - INFO - paramwise_options -- text_decoder.cls.predictions.transform.LayerNorm.bias:weight_decay=0.0 2023/09/05 22:45:01 - mmengine - WARNING - text_decoder.cls.predictions.decoder is duplicate. It is skipped since bypass_duplicate=True 2023/09/05 22:45:01 - mmengine - INFO - LR is set based on batch size of 32 and the current batch size is 64. Scaling the original LR by 2.0. 2023/09/05 22:45:02 - mmengine - INFO - interpolate temporal positional embeddings: vision_encoder.embeddings.temporal_position_embeddings 2023/09/05 22:45:02 - mmengine - INFO - Load temporal_embeddings, lengths: 4-->12 2023/09/05 22:45:02 - mmengine - INFO - _IncompatibleKeys(missing_keys=[], unexpected_keys=['temp', 'temporal_embeddings', 'vision_proj.weight', 'vision_proj.bias', 'text_proj.weight', 'text_proj.bias', 'itm_head.weight', 'itm_head.bias']) 2023/09/05 22:45:02 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/09/05 22:45:02 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/09/05 22:45:02 - mmengine - INFO - Checkpoints will be saved to /mnt/workspace/lilin/Repos/mmaction2/work_dirs/vindlu_9_4/msrvtt_vqa_8x8_train_bicubic. 2023/09/05 22:45:30 - mmengine - INFO - Epoch(train) [1][ 20/2478] base_lr: 1.7594e-07 lr: 3.5188e-07 eta: 9:27:12 time: 1.3745 data_time: 0.0652 memory: 7583 grad_norm: nan loss: 28.1232 2023/09/05 22:45:52 - mmengine - INFO - Epoch(train) [1][ 40/2478] base_lr: 2.5587e-07 lr: 5.1175e-07 eta: 8:31:07 time: 1.1047 data_time: 0.0077 memory: 7583 grad_norm: 88.9494 loss: 26.7730 2023/09/05 22:46:14 - mmengine - INFO - Epoch(train) [1][ 60/2478] base_lr: 3.3581e-07 lr: 6.7162e-07 eta: 8:12:49 time: 1.1093 data_time: 0.0075 memory: 7583 grad_norm: 80.3153 loss: 25.8731 2023/09/05 22:46:36 - mmengine - INFO - Epoch(train) [1][ 80/2478] base_lr: 4.1574e-07 lr: 8.3149e-07 eta: 8:03:42 time: 1.1116 data_time: 0.0077 memory: 7583 grad_norm: 76.6999 loss: 24.4313 2023/09/05 22:46:58 - mmengine - INFO - Epoch(train) [1][ 100/2478] base_lr: 4.9568e-07 lr: 9.9136e-07 eta: 7:57:56 time: 1.1095 data_time: 0.0075 memory: 7583 grad_norm: 72.9473 loss: 22.1057 2023/09/05 22:47:20 - mmengine - INFO - Epoch(train) [1][ 120/2478] base_lr: 5.7562e-07 lr: 1.1512e-06 eta: 7:53:50 time: 1.1077 data_time: 0.0076 memory: 7583 grad_norm: 72.4285 loss: 18.7527 2023/09/05 22:47:43 - mmengine - INFO - Epoch(train) [1][ 140/2478] base_lr: 6.5555e-07 lr: 1.3111e-06 eta: 7:51:00 time: 1.1113 data_time: 0.0074 memory: 7583 grad_norm: 73.3304 loss: 16.2751 2023/09/05 22:48:05 - mmengine - INFO - Epoch(train) [1][ 160/2478] base_lr: 7.3549e-07 lr: 1.4710e-06 eta: 7:48:35 time: 1.1071 data_time: 0.0073 memory: 7583 grad_norm: inf loss: 11.9892 2023/09/05 22:48:27 - mmengine - INFO - Epoch(train) [1][ 180/2478] base_lr: 8.1542e-07 lr: 1.6308e-06 eta: 7:46:43 time: 1.1094 data_time: 0.0072 memory: 7583 grad_norm: 38.3644 loss: 10.2266 2023/09/05 22:48:49 - mmengine - INFO - Epoch(train) [1][ 200/2478] base_lr: 8.9536e-07 lr: 1.7907e-06 eta: 7:45:18 time: 1.1132 data_time: 0.0072 memory: 7583 grad_norm: 25.9483 loss: 9.1454 2023/09/05 22:49:12 - mmengine - INFO - Epoch(train) [1][ 220/2478] base_lr: 9.7529e-07 lr: 1.9506e-06 eta: 7:44:08 time: 1.1144 data_time: 0.0071 memory: 7583 grad_norm: 21.9505 loss: 8.8666 2023/09/05 22:49:34 - mmengine - INFO - Epoch(train) [1][ 240/2478] base_lr: 1.0552e-06 lr: 2.1105e-06 eta: 7:42:53 time: 1.1085 data_time: 0.0071 memory: 7583 grad_norm: 20.9304 loss: 8.4396 2023/09/05 22:49:56 - mmengine - INFO - Epoch(train) [1][ 260/2478] base_lr: 1.1352e-06 lr: 2.2703e-06 eta: 7:41:52 time: 1.1115 data_time: 0.0074 memory: 7583 grad_norm: 20.2325 loss: 8.4406 2023/09/05 22:50:18 - mmengine - INFO - Epoch(train) [1][ 280/2478] base_lr: 1.2151e-06 lr: 2.4302e-06 eta: 7:41:02 time: 1.1144 data_time: 0.0074 memory: 7583 grad_norm: 19.0917 loss: 8.0561 2023/09/05 22:50:41 - mmengine - INFO - Epoch(train) [1][ 300/2478] base_lr: 1.2950e-06 lr: 2.5901e-06 eta: 7:40:16 time: 1.1148 data_time: 0.0076 memory: 7583 grad_norm: 18.5971 loss: 7.4042 2023/09/05 22:51:03 - mmengine - INFO - Epoch(train) [1][ 320/2478] base_lr: 1.3750e-06 lr: 2.7499e-06 eta: 7:39:24 time: 1.1088 data_time: 0.0078 memory: 7583 grad_norm: 18.0070 loss: 6.8079 2023/09/05 22:51:25 - mmengine - INFO - Epoch(train) [1][ 340/2478] base_lr: 1.4549e-06 lr: 2.9098e-06 eta: 7:38:35 time: 1.1090 data_time: 0.0073 memory: 7583 grad_norm: 17.8403 loss: 7.2887 2023/09/05 22:51:47 - mmengine - INFO - Epoch(train) [1][ 360/2478] base_lr: 1.5348e-06 lr: 3.0697e-06 eta: 7:37:53 time: 1.1108 data_time: 0.0082 memory: 7583 grad_norm: 17.4114 loss: 7.5742 2023/09/05 22:52:09 - mmengine - INFO - Epoch(train) [1][ 380/2478] base_lr: 1.6148e-06 lr: 3.2296e-06 eta: 7:37:14 time: 1.1122 data_time: 0.0080 memory: 7583 grad_norm: 17.3044 loss: 7.8784 2023/09/05 22:52:32 - mmengine - INFO - Epoch(train) [1][ 400/2478] base_lr: 1.6947e-06 lr: 3.3894e-06 eta: 7:36:38 time: 1.1139 data_time: 0.0079 memory: 7583 grad_norm: 17.0531 loss: 6.8356 2023/09/05 22:52:54 - mmengine - INFO - Epoch(train) [1][ 420/2478] base_lr: 1.7746e-06 lr: 3.5493e-06 eta: 7:36:05 time: 1.1142 data_time: 0.0075 memory: 7583 grad_norm: 16.7277 loss: 7.1351 2023/09/05 22:53:16 - mmengine - INFO - Epoch(train) [1][ 440/2478] base_lr: 1.8546e-06 lr: 3.7092e-06 eta: 7:35:32 time: 1.1136 data_time: 0.0075 memory: 7583 grad_norm: 16.9329 loss: 6.3173 2023/09/05 22:53:38 - mmengine - INFO - Epoch(train) [1][ 460/2478] base_lr: 1.9345e-06 lr: 3.8690e-06 eta: 7:34:57 time: 1.1118 data_time: 0.0076 memory: 7583 grad_norm: 16.9812 loss: 6.6690 2023/09/05 22:54:01 - mmengine - INFO - Epoch(train) [1][ 480/2478] base_lr: 2.0145e-06 lr: 4.0289e-06 eta: 7:34:21 time: 1.1086 data_time: 0.0077 memory: 7583 grad_norm: 16.0738 loss: 6.1256 2023/09/05 22:54:23 - mmengine - INFO - Epoch(train) [1][ 500/2478] base_lr: 2.0944e-06 lr: 4.1888e-06 eta: 7:33:49 time: 1.1124 data_time: 0.0077 memory: 7583 grad_norm: 16.1276 loss: 6.8689 2023/09/05 22:54:45 - mmengine - INFO - Epoch(train) [1][ 520/2478] base_lr: 2.1743e-06 lr: 4.3486e-06 eta: 7:33:18 time: 1.1120 data_time: 0.0076 memory: 7583 grad_norm: 16.4027 loss: 6.2644 2023/09/05 22:55:07 - mmengine - INFO - Epoch(train) [1][ 540/2478] base_lr: 2.2543e-06 lr: 4.5085e-06 eta: 7:32:47 time: 1.1116 data_time: 0.0076 memory: 7583 grad_norm: 15.8516 loss: 6.1713 2023/09/05 22:55:30 - mmengine - INFO - Epoch(train) [1][ 560/2478] base_lr: 2.3342e-06 lr: 4.6684e-06 eta: 7:32:17 time: 1.1118 data_time: 0.0077 memory: 7583 grad_norm: 16.6775 loss: 6.5358 2023/09/05 22:55:52 - mmengine - INFO - Epoch(train) [1][ 580/2478] base_lr: 2.4141e-06 lr: 4.8283e-06 eta: 7:31:47 time: 1.1122 data_time: 0.0080 memory: 7583 grad_norm: 16.3106 loss: 5.8067 2023/09/05 22:56:14 - mmengine - INFO - Epoch(train) [1][ 600/2478] base_lr: 2.4941e-06 lr: 4.9881e-06 eta: 7:31:18 time: 1.1113 data_time: 0.0077 memory: 7583 grad_norm: 16.4944 loss: 5.2426 2023/09/05 22:56:36 - mmengine - INFO - Epoch(train) [1][ 620/2478] base_lr: 2.5740e-06 lr: 5.1480e-06 eta: 7:30:48 time: 1.1107 data_time: 0.0077 memory: 7583 grad_norm: 16.6984 loss: 5.7470 2023/09/05 22:56:59 - mmengine - INFO - Epoch(train) [1][ 640/2478] base_lr: 2.6539e-06 lr: 5.3079e-06 eta: 7:30:21 time: 1.1133 data_time: 0.0076 memory: 7583 grad_norm: 16.0365 loss: 6.0148 2023/09/05 22:57:21 - mmengine - INFO - Epoch(train) [1][ 660/2478] base_lr: 2.7339e-06 lr: 5.4677e-06 eta: 7:29:55 time: 1.1141 data_time: 0.0077 memory: 7583 grad_norm: 15.5397 loss: 5.5199 2023/09/05 22:57:43 - mmengine - INFO - Epoch(train) [1][ 680/2478] base_lr: 2.8138e-06 lr: 5.6276e-06 eta: 7:29:26 time: 1.1104 data_time: 0.0077 memory: 7583 grad_norm: 16.1056 loss: 5.9577 2023/09/05 22:58:05 - mmengine - INFO - Epoch(train) [1][ 700/2478] base_lr: 2.8937e-06 lr: 5.7875e-06 eta: 7:28:58 time: 1.1103 data_time: 0.0077 memory: 7583 grad_norm: 15.8095 loss: 5.4590 2023/09/05 22:58:27 - mmengine - INFO - Epoch(train) [1][ 720/2478] base_lr: 2.9737e-06 lr: 5.9474e-06 eta: 7:28:30 time: 1.1102 data_time: 0.0077 memory: 7583 grad_norm: 16.1251 loss: 5.7137 2023/09/05 22:58:50 - mmengine - INFO - Epoch(train) [1][ 740/2478] base_lr: 3.0536e-06 lr: 6.1072e-06 eta: 7:28:03 time: 1.1111 data_time: 0.0079 memory: 7583 grad_norm: 15.7652 loss: 5.5301 2023/09/05 22:59:12 - mmengine - INFO - Epoch(train) [1][ 760/2478] base_lr: 3.1335e-06 lr: 6.2671e-06 eta: 7:27:35 time: 1.1100 data_time: 0.0077 memory: 7583 grad_norm: 15.8822 loss: 5.8082 2023/09/05 22:59:34 - mmengine - INFO - Epoch(train) [1][ 780/2478] base_lr: 3.2135e-06 lr: 6.4270e-06 eta: 7:27:10 time: 1.1138 data_time: 0.0077 memory: 7583 grad_norm: 15.9272 loss: 5.5906 2023/09/05 22:59:56 - mmengine - INFO - Epoch(train) [1][ 800/2478] base_lr: 3.2934e-06 lr: 6.5868e-06 eta: 7:26:44 time: 1.1121 data_time: 0.0076 memory: 7583 grad_norm: 15.5324 loss: 5.1598 2023/09/05 23:00:19 - mmengine - INFO - Epoch(train) [1][ 820/2478] base_lr: 3.3734e-06 lr: 6.7467e-06 eta: 7:26:19 time: 1.1127 data_time: 0.0077 memory: 7583 grad_norm: 16.6423 loss: 5.1136 2023/09/05 23:00:41 - mmengine - INFO - Epoch(train) [1][ 840/2478] base_lr: 3.4533e-06 lr: 6.9066e-06 eta: 7:25:55 time: 1.1155 data_time: 0.0077 memory: 7583 grad_norm: 15.9396 loss: 5.0924 2023/09/05 23:01:03 - mmengine - INFO - Epoch(train) [1][ 860/2478] base_lr: 3.5332e-06 lr: 7.0665e-06 eta: 7:25:31 time: 1.1145 data_time: 0.0075 memory: 7583 grad_norm: 15.6486 loss: 5.1848 2023/09/05 23:01:25 - mmengine - INFO - Epoch(train) [1][ 880/2478] base_lr: 3.6132e-06 lr: 7.2263e-06 eta: 7:25:05 time: 1.1100 data_time: 0.0077 memory: 7583 grad_norm: 15.6196 loss: 4.8541 2023/09/05 23:01:48 - mmengine - INFO - Epoch(train) [1][ 900/2478] base_lr: 3.6931e-06 lr: 7.3862e-06 eta: 7:24:37 time: 1.1078 data_time: 0.0074 memory: 7583 grad_norm: 15.9342 loss: 4.4758 2023/09/05 23:02:10 - mmengine - INFO - Epoch(train) [1][ 920/2478] base_lr: 3.7730e-06 lr: 7.5461e-06 eta: 7:24:11 time: 1.1101 data_time: 0.0075 memory: 7583 grad_norm: 15.3722 loss: 4.8765 2023/09/05 23:02:32 - mmengine - INFO - Epoch(train) [1][ 940/2478] base_lr: 3.8530e-06 lr: 7.7059e-06 eta: 7:23:45 time: 1.1095 data_time: 0.0077 memory: 7583 grad_norm: 16.1429 loss: 5.9391 2023/09/05 23:02:54 - mmengine - INFO - Epoch(train) [1][ 960/2478] base_lr: 3.9329e-06 lr: 7.8658e-06 eta: 7:23:21 time: 1.1124 data_time: 0.0076 memory: 7583 grad_norm: 15.9525 loss: 4.4483 2023/09/05 23:03:16 - mmengine - INFO - Epoch(train) [1][ 980/2478] base_lr: 4.0128e-06 lr: 8.0257e-06 eta: 7:22:55 time: 1.1095 data_time: 0.0075 memory: 7583 grad_norm: 15.5410 loss: 5.3208 2023/09/05 23:03:39 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/05 23:03:39 - mmengine - INFO - Epoch(train) [1][1000/2478] base_lr: 4.0928e-06 lr: 8.1855e-06 eta: 7:22:29 time: 1.1098 data_time: 0.0074 memory: 7583 grad_norm: 15.5588 loss: 5.2904 2023/09/05 23:04:01 - mmengine - INFO - Epoch(train) [1][1020/2478] base_lr: 4.1727e-06 lr: 8.3454e-06 eta: 7:22:05 time: 1.1124 data_time: 0.0077 memory: 7583 grad_norm: 15.5843 loss: 4.9501 2023/09/05 23:04:23 - mmengine - INFO - Epoch(train) [1][1040/2478] base_lr: 4.2526e-06 lr: 8.5053e-06 eta: 7:21:41 time: 1.1119 data_time: 0.0075 memory: 7583 grad_norm: 15.8234 loss: 4.0666 2023/09/05 23:04:45 - mmengine - INFO - Epoch(train) [1][1060/2478] base_lr: 4.3326e-06 lr: 8.6652e-06 eta: 7:21:15 time: 1.1092 data_time: 0.0075 memory: 7583 grad_norm: 15.0982 loss: 5.3649 2023/09/05 23:05:08 - mmengine - INFO - Epoch(train) [1][1080/2478] base_lr: 4.4125e-06 lr: 8.8250e-06 eta: 7:20:51 time: 1.1119 data_time: 0.0077 memory: 7583 grad_norm: 16.0719 loss: 5.3476 2023/09/05 23:05:30 - mmengine - INFO - Epoch(train) [1][1100/2478] base_lr: 4.4925e-06 lr: 8.9849e-06 eta: 7:20:28 time: 1.1133 data_time: 0.0077 memory: 7583 grad_norm: 15.3353 loss: 4.3963 2023/09/05 23:05:52 - mmengine - INFO - Epoch(train) [1][1120/2478] base_lr: 4.5724e-06 lr: 9.1448e-06 eta: 7:20:04 time: 1.1143 data_time: 0.0074 memory: 7583 grad_norm: 15.2687 loss: 4.1716 2023/09/05 23:06:14 - mmengine - INFO - Epoch(train) [1][1140/2478] base_lr: 4.6523e-06 lr: 9.3046e-06 eta: 7:19:40 time: 1.1117 data_time: 0.0076 memory: 7583 grad_norm: 15.3739 loss: 5.1472 2023/09/05 23:06:37 - mmengine - INFO - Epoch(train) [1][1160/2478] base_lr: 4.7323e-06 lr: 9.4645e-06 eta: 7:19:16 time: 1.1113 data_time: 0.0076 memory: 7583 grad_norm: 15.7219 loss: 3.8695 2023/09/05 23:06:59 - mmengine - INFO - Epoch(train) [1][1180/2478] base_lr: 4.8122e-06 lr: 9.6244e-06 eta: 7:18:51 time: 1.1097 data_time: 0.0074 memory: 7583 grad_norm: 15.9676 loss: 4.4111 2023/09/05 23:07:21 - mmengine - INFO - Epoch(train) [1][1200/2478] base_lr: 4.8921e-06 lr: 9.7843e-06 eta: 7:18:28 time: 1.1126 data_time: 0.0076 memory: 7583 grad_norm: 16.0626 loss: 4.3850 2023/09/05 23:07:43 - mmengine - INFO - Epoch(train) [1][1220/2478] base_lr: 4.9721e-06 lr: 9.9441e-06 eta: 7:18:04 time: 1.1119 data_time: 0.0076 memory: 7583 grad_norm: 15.3457 loss: 4.5106 2023/09/05 23:08:05 - mmengine - INFO - Epoch(train) [1][1240/2478] base_lr: 5.0520e-06 lr: 1.0104e-05 eta: 7:17:41 time: 1.1127 data_time: 0.0074 memory: 7583 grad_norm: 14.8186 loss: 4.4630 2023/09/05 23:08:28 - mmengine - INFO - Epoch(train) [1][1260/2478] base_lr: 5.1319e-06 lr: 1.0264e-05 eta: 7:17:17 time: 1.1121 data_time: 0.0075 memory: 7583 grad_norm: 15.0330 loss: 4.2267 2023/09/05 23:08:50 - mmengine - INFO - Epoch(train) [1][1280/2478] base_lr: 5.2119e-06 lr: 1.0424e-05 eta: 7:16:52 time: 1.1084 data_time: 0.0073 memory: 7583 grad_norm: 14.7622 loss: 4.5798 2023/09/05 23:09:12 - mmengine - INFO - Epoch(train) [1][1300/2478] base_lr: 5.2918e-06 lr: 1.0584e-05 eta: 7:16:28 time: 1.1108 data_time: 0.0075 memory: 7583 grad_norm: 15.1801 loss: 4.0627 2023/09/05 23:09:34 - mmengine - INFO - Epoch(train) [1][1320/2478] base_lr: 5.3717e-06 lr: 1.0743e-05 eta: 7:16:04 time: 1.1108 data_time: 0.0073 memory: 7583 grad_norm: 14.8198 loss: 3.8448 2023/09/05 23:09:57 - mmengine - INFO - Epoch(train) [1][1340/2478] base_lr: 5.4517e-06 lr: 1.0903e-05 eta: 7:15:40 time: 1.1114 data_time: 0.0073 memory: 7583 grad_norm: 14.8887 loss: 4.5226 2023/09/05 23:10:19 - mmengine - INFO - Epoch(train) [1][1360/2478] base_lr: 5.5316e-06 lr: 1.1063e-05 eta: 7:15:17 time: 1.1111 data_time: 0.0074 memory: 7583 grad_norm: 15.4067 loss: 4.7735 2023/09/05 23:10:41 - mmengine - INFO - Epoch(train) [1][1380/2478] base_lr: 5.6115e-06 lr: 1.1223e-05 eta: 7:14:53 time: 1.1109 data_time: 0.0076 memory: 7583 grad_norm: 15.3550 loss: 4.1922 2023/09/05 23:11:03 - mmengine - INFO - Epoch(train) [1][1400/2478] base_lr: 5.6915e-06 lr: 1.1383e-05 eta: 7:14:29 time: 1.1090 data_time: 0.0076 memory: 7583 grad_norm: 15.5448 loss: 4.1576 2023/09/05 23:11:25 - mmengine - INFO - Epoch(train) [1][1420/2478] base_lr: 5.7714e-06 lr: 1.1543e-05 eta: 7:14:06 time: 1.1130 data_time: 0.0080 memory: 7583 grad_norm: 15.0674 loss: 3.8309 2023/09/05 23:11:48 - mmengine - INFO - Epoch(train) [1][1440/2478] base_lr: 5.8514e-06 lr: 1.1703e-05 eta: 7:13:42 time: 1.1096 data_time: 0.0076 memory: 7583 grad_norm: 15.5002 loss: 4.4392 2023/09/05 23:12:10 - mmengine - INFO - Epoch(train) [1][1460/2478] base_lr: 5.9313e-06 lr: 1.1863e-05 eta: 7:13:18 time: 1.1096 data_time: 0.0076 memory: 7583 grad_norm: 15.3564 loss: 4.0078 2023/09/05 23:12:32 - mmengine - INFO - Epoch(train) [1][1480/2478] base_lr: 6.0112e-06 lr: 1.2022e-05 eta: 7:12:55 time: 1.1126 data_time: 0.0074 memory: 7583 grad_norm: 14.7810 loss: 4.7119 2023/09/05 23:12:54 - mmengine - INFO - Epoch(train) [1][1500/2478] base_lr: 6.0912e-06 lr: 1.2182e-05 eta: 7:12:31 time: 1.1110 data_time: 0.0074 memory: 7583 grad_norm: 14.9036 loss: 4.0948 2023/09/05 23:13:16 - mmengine - INFO - Epoch(train) [1][1520/2478] base_lr: 6.1711e-06 lr: 1.2342e-05 eta: 7:12:07 time: 1.1101 data_time: 0.0077 memory: 7583 grad_norm: 15.2767 loss: 5.0265 2023/09/05 23:13:39 - mmengine - INFO - Epoch(train) [1][1540/2478] base_lr: 6.2510e-06 lr: 1.2502e-05 eta: 7:11:44 time: 1.1108 data_time: 0.0075 memory: 7583 grad_norm: 15.3351 loss: 4.4099 2023/09/05 23:14:01 - mmengine - INFO - Epoch(train) [1][1560/2478] base_lr: 6.3310e-06 lr: 1.2662e-05 eta: 7:11:21 time: 1.1113 data_time: 0.0074 memory: 7583 grad_norm: 14.5310 loss: 4.1712 2023/09/05 23:14:23 - mmengine - INFO - Epoch(train) [1][1580/2478] base_lr: 6.4109e-06 lr: 1.2822e-05 eta: 7:10:57 time: 1.1115 data_time: 0.0074 memory: 7583 grad_norm: 14.5109 loss: 3.9941 2023/09/05 23:14:45 - mmengine - INFO - Epoch(train) [1][1600/2478] base_lr: 6.4908e-06 lr: 1.2982e-05 eta: 7:10:35 time: 1.1127 data_time: 0.0075 memory: 7583 grad_norm: 15.1915 loss: 4.1303 2023/09/05 23:15:08 - mmengine - INFO - Epoch(train) [1][1620/2478] base_lr: 6.5708e-06 lr: 1.3142e-05 eta: 7:10:11 time: 1.1111 data_time: 0.0075 memory: 7583 grad_norm: 14.9544 loss: 3.5352 2023/09/05 23:15:30 - mmengine - INFO - Epoch(train) [1][1640/2478] base_lr: 6.6507e-06 lr: 1.3301e-05 eta: 7:09:48 time: 1.1122 data_time: 0.0073 memory: 7583 grad_norm: 14.4127 loss: 4.3342 2023/09/05 23:15:52 - mmengine - INFO - Epoch(train) [1][1660/2478] base_lr: 6.7306e-06 lr: 1.3461e-05 eta: 7:09:24 time: 1.1086 data_time: 0.0076 memory: 7583 grad_norm: 15.2213 loss: 3.9167 2023/09/05 23:16:14 - mmengine - INFO - Epoch(train) [1][1680/2478] base_lr: 6.8106e-06 lr: 1.3621e-05 eta: 7:09:01 time: 1.1104 data_time: 0.0075 memory: 7583 grad_norm: 14.0396 loss: 4.1352 2023/09/05 23:16:36 - mmengine - INFO - Epoch(train) [1][1700/2478] base_lr: 6.8905e-06 lr: 1.3781e-05 eta: 7:08:38 time: 1.1104 data_time: 0.0077 memory: 7583 grad_norm: 14.4270 loss: 3.3567 2023/09/05 23:16:59 - mmengine - INFO - Epoch(train) [1][1720/2478] base_lr: 6.9704e-06 lr: 1.3941e-05 eta: 7:08:14 time: 1.1101 data_time: 0.0078 memory: 7583 grad_norm: 13.9353 loss: 3.4878 2023/09/05 23:17:21 - mmengine - INFO - Epoch(train) [1][1740/2478] base_lr: 7.0504e-06 lr: 1.4101e-05 eta: 7:07:52 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 14.4004 loss: 4.3944 2023/09/05 23:17:43 - mmengine - INFO - Epoch(train) [1][1760/2478] base_lr: 7.1303e-06 lr: 1.4261e-05 eta: 7:07:28 time: 1.1110 data_time: 0.0078 memory: 7583 grad_norm: 14.7028 loss: 3.3830 2023/09/05 23:18:05 - mmengine - INFO - Epoch(train) [1][1780/2478] base_lr: 7.2103e-06 lr: 1.4421e-05 eta: 7:07:05 time: 1.1092 data_time: 0.0077 memory: 7583 grad_norm: 14.3658 loss: 4.0888 2023/09/05 23:18:28 - mmengine - INFO - Epoch(train) [1][1800/2478] base_lr: 7.2902e-06 lr: 1.4580e-05 eta: 7:06:42 time: 1.1127 data_time: 0.0081 memory: 7583 grad_norm: 14.1856 loss: 3.8429 2023/09/05 23:18:50 - mmengine - INFO - Epoch(train) [1][1820/2478] base_lr: 7.3701e-06 lr: 1.4740e-05 eta: 7:06:19 time: 1.1123 data_time: 0.0077 memory: 7583 grad_norm: 14.6757 loss: 4.0314 2023/09/05 23:19:12 - mmengine - INFO - Epoch(train) [1][1840/2478] base_lr: 7.4501e-06 lr: 1.4900e-05 eta: 7:05:57 time: 1.1123 data_time: 0.0079 memory: 7583 grad_norm: 13.9216 loss: 4.1205 2023/09/05 23:19:34 - mmengine - INFO - Epoch(train) [1][1860/2478] base_lr: 7.5300e-06 lr: 1.5060e-05 eta: 7:05:34 time: 1.1120 data_time: 0.0077 memory: 7583 grad_norm: 14.2425 loss: 3.5392 2023/09/05 23:19:56 - mmengine - INFO - Epoch(train) [1][1880/2478] base_lr: 7.6099e-06 lr: 1.5220e-05 eta: 7:05:11 time: 1.1099 data_time: 0.0079 memory: 7583 grad_norm: 14.0764 loss: 3.5194 2023/09/05 23:20:19 - mmengine - INFO - Epoch(train) [1][1900/2478] base_lr: 7.6899e-06 lr: 1.5380e-05 eta: 7:04:48 time: 1.1108 data_time: 0.0077 memory: 7583 grad_norm: 13.8144 loss: 4.1007 2023/09/05 23:20:41 - mmengine - INFO - Epoch(train) [1][1920/2478] base_lr: 7.7698e-06 lr: 1.5540e-05 eta: 7:04:24 time: 1.1096 data_time: 0.0079 memory: 7583 grad_norm: 14.4932 loss: 3.8523 2023/09/05 23:21:03 - mmengine - INFO - Epoch(train) [1][1940/2478] base_lr: 7.8497e-06 lr: 1.5699e-05 eta: 7:04:01 time: 1.1111 data_time: 0.0082 memory: 7583 grad_norm: 14.6256 loss: 4.0400 2023/09/05 23:21:25 - mmengine - INFO - Epoch(train) [1][1960/2478] base_lr: 7.9297e-06 lr: 1.5859e-05 eta: 7:03:39 time: 1.1131 data_time: 0.0079 memory: 7583 grad_norm: 13.7590 loss: 3.8276 2023/09/05 23:21:48 - mmengine - INFO - Epoch(train) [1][1980/2478] base_lr: 8.0096e-06 lr: 1.6019e-05 eta: 7:03:16 time: 1.1110 data_time: 0.0080 memory: 7583 grad_norm: 14.4401 loss: 3.3480 2023/09/05 23:22:10 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/05 23:22:10 - mmengine - INFO - Epoch(train) [1][2000/2478] base_lr: 8.0895e-06 lr: 1.6179e-05 eta: 7:02:54 time: 1.1144 data_time: 0.0078 memory: 7583 grad_norm: 13.8919 loss: 3.3051 2023/09/05 23:22:32 - mmengine - INFO - Epoch(train) [1][2020/2478] base_lr: 8.1695e-06 lr: 1.6339e-05 eta: 7:02:31 time: 1.1097 data_time: 0.0080 memory: 7583 grad_norm: 14.1041 loss: 3.5518 2023/09/05 23:22:54 - mmengine - INFO - Epoch(train) [1][2040/2478] base_lr: 8.2494e-06 lr: 1.6499e-05 eta: 7:02:09 time: 1.1165 data_time: 0.0079 memory: 7583 grad_norm: 14.7112 loss: 4.2313 2023/09/05 23:23:17 - mmengine - INFO - Epoch(train) [1][2060/2478] base_lr: 8.3294e-06 lr: 1.6659e-05 eta: 7:01:46 time: 1.1130 data_time: 0.0077 memory: 7583 grad_norm: 14.2886 loss: 4.2280 2023/09/05 23:23:39 - mmengine - INFO - Epoch(train) [1][2080/2478] base_lr: 8.4093e-06 lr: 1.6819e-05 eta: 7:01:24 time: 1.1114 data_time: 0.0080 memory: 7583 grad_norm: 13.8020 loss: 3.8972 2023/09/05 23:24:01 - mmengine - INFO - Epoch(train) [1][2100/2478] base_lr: 8.4892e-06 lr: 1.6978e-05 eta: 7:01:00 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 14.2726 loss: 3.7872 2023/09/05 23:24:23 - mmengine - INFO - Epoch(train) [1][2120/2478] base_lr: 8.5692e-06 lr: 1.7138e-05 eta: 7:00:37 time: 1.1096 data_time: 0.0079 memory: 7583 grad_norm: 14.0120 loss: 3.9111 2023/09/05 23:24:45 - mmengine - INFO - Epoch(train) [1][2140/2478] base_lr: 8.6491e-06 lr: 1.7298e-05 eta: 7:00:14 time: 1.1092 data_time: 0.0079 memory: 7583 grad_norm: 13.6515 loss: 3.4752 2023/09/05 23:25:08 - mmengine - INFO - Epoch(train) [1][2160/2478] base_lr: 8.7290e-06 lr: 1.7458e-05 eta: 6:59:51 time: 1.1118 data_time: 0.0080 memory: 7583 grad_norm: 13.4626 loss: 3.8688 2023/09/05 23:25:30 - mmengine - INFO - Epoch(train) [1][2180/2478] base_lr: 8.8090e-06 lr: 1.7618e-05 eta: 6:59:29 time: 1.1129 data_time: 0.0080 memory: 7583 grad_norm: 13.8308 loss: 3.7366 2023/09/05 23:25:52 - mmengine - INFO - Epoch(train) [1][2200/2478] base_lr: 8.8889e-06 lr: 1.7778e-05 eta: 6:59:06 time: 1.1099 data_time: 0.0081 memory: 7583 grad_norm: 14.1799 loss: 4.1666 2023/09/05 23:26:14 - mmengine - INFO - Epoch(train) [1][2220/2478] base_lr: 8.9688e-06 lr: 1.7938e-05 eta: 6:58:43 time: 1.1112 data_time: 0.0080 memory: 7583 grad_norm: 13.5403 loss: 3.7801 2023/09/05 23:26:37 - mmengine - INFO - Epoch(train) [1][2240/2478] base_lr: 9.0488e-06 lr: 1.8098e-05 eta: 6:58:20 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 14.6743 loss: 3.6983 2023/09/05 23:26:59 - mmengine - INFO - Epoch(train) [1][2260/2478] base_lr: 9.1287e-06 lr: 1.8257e-05 eta: 6:57:57 time: 1.1119 data_time: 0.0079 memory: 7583 grad_norm: 13.8324 loss: 4.1542 2023/09/05 23:27:21 - mmengine - INFO - Epoch(train) [1][2280/2478] base_lr: 9.2086e-06 lr: 1.8417e-05 eta: 6:57:35 time: 1.1110 data_time: 0.0078 memory: 7583 grad_norm: 13.6885 loss: 3.9179 2023/09/05 23:27:43 - mmengine - INFO - Epoch(train) [1][2300/2478] base_lr: 9.2886e-06 lr: 1.8577e-05 eta: 6:57:12 time: 1.1108 data_time: 0.0076 memory: 7583 grad_norm: 13.3666 loss: 3.7569 2023/09/05 23:28:05 - mmengine - INFO - Epoch(train) [1][2320/2478] base_lr: 9.3685e-06 lr: 1.8737e-05 eta: 6:56:49 time: 1.1094 data_time: 0.0076 memory: 7583 grad_norm: 13.9774 loss: 3.8181 2023/09/05 23:28:28 - mmengine - INFO - Epoch(train) [1][2340/2478] base_lr: 9.4484e-06 lr: 1.8897e-05 eta: 6:56:26 time: 1.1124 data_time: 0.0076 memory: 7583 grad_norm: 13.7712 loss: 3.7302 2023/09/05 23:28:50 - mmengine - INFO - Epoch(train) [1][2360/2478] base_lr: 9.5284e-06 lr: 1.9057e-05 eta: 6:56:03 time: 1.1097 data_time: 0.0075 memory: 7583 grad_norm: 13.5563 loss: 3.6967 2023/09/05 23:29:12 - mmengine - INFO - Epoch(train) [1][2380/2478] base_lr: 9.6083e-06 lr: 1.9217e-05 eta: 6:55:41 time: 1.1112 data_time: 0.0074 memory: 7583 grad_norm: 13.2479 loss: 3.3141 2023/09/05 23:29:34 - mmengine - INFO - Epoch(train) [1][2400/2478] base_lr: 9.6883e-06 lr: 1.9377e-05 eta: 6:55:18 time: 1.1089 data_time: 0.0079 memory: 7583 grad_norm: 13.3683 loss: 3.1596 2023/09/05 23:29:56 - mmengine - INFO - Epoch(train) [1][2420/2478] base_lr: 9.7682e-06 lr: 1.9536e-05 eta: 6:54:54 time: 1.1080 data_time: 0.0076 memory: 7583 grad_norm: 13.2268 loss: 3.7029 2023/09/05 23:30:19 - mmengine - INFO - Epoch(train) [1][2440/2478] base_lr: 9.8481e-06 lr: 1.9696e-05 eta: 6:54:32 time: 1.1124 data_time: 0.0076 memory: 7583 grad_norm: 13.4257 loss: 4.0249 2023/09/05 23:30:41 - mmengine - INFO - Epoch(train) [1][2460/2478] base_lr: 9.9281e-06 lr: 1.9856e-05 eta: 6:54:09 time: 1.1110 data_time: 0.0075 memory: 7583 grad_norm: 13.2569 loss: 3.8270 2023/09/05 23:31:01 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/05 23:31:01 - mmengine - INFO - Epoch(train) [1][2478/2478] base_lr: 1.0000e-05 lr: 2.0000e-05 eta: 6:53:48 time: 1.1076 data_time: 0.0075 memory: 7583 grad_norm: 13.5720 loss: 4.0649 2023/09/05 23:31:01 - mmengine - INFO - Saving checkpoint at 1 epochs 2023/09/05 23:31:32 - mmengine - INFO - Epoch(val) [1][20/96] eta: 0:01:23 time: 1.0970 data_time: 0.0527 memory: 8884 2023/09/05 23:31:53 - mmengine - INFO - Epoch(val) [1][40/96] eta: 0:00:59 time: 1.0456 data_time: 0.0062 memory: 8884 2023/09/05 23:32:14 - mmengine - INFO - Epoch(val) [1][60/96] eta: 0:00:38 time: 1.0452 data_time: 0.0063 memory: 8884 2023/09/05 23:32:35 - mmengine - INFO - Epoch(val) [1][80/96] eta: 0:00:16 time: 1.0520 data_time: 0.0063 memory: 8884 2023/09/05 23:32:53 - mmengine - INFO - Epoch(val) [1][96/96] VQA/acc: 37.6120 data_time: 0.0160 time: 1.0570 2023/09/05 23:32:57 - mmengine - INFO - The best checkpoint with 37.6120 VQA/acc at 1 epoch is saved to best_VQA_acc_epoch_1.pth. 2023/09/05 23:33:28 - mmengine - INFO - Epoch(train) [2][ 20/2478] base_lr: 1.0000e-05 lr: 2.0000e-05 eta: 6:53:28 time: 1.1252 data_time: 0.0228 memory: 8884 grad_norm: 13.4294 loss: 3.4401 2023/09/05 23:33:50 - mmengine - INFO - Epoch(train) [2][ 40/2478] base_lr: 9.9999e-06 lr: 2.0000e-05 eta: 6:53:05 time: 1.1120 data_time: 0.0079 memory: 7583 grad_norm: 13.2684 loss: 3.4124 2023/09/05 23:34:12 - mmengine - INFO - Epoch(train) [2][ 60/2478] base_lr: 9.9999e-06 lr: 2.0000e-05 eta: 6:52:42 time: 1.1082 data_time: 0.0079 memory: 7583 grad_norm: 13.8656 loss: 3.4267 2023/09/05 23:34:35 - mmengine - INFO - Epoch(train) [2][ 80/2478] base_lr: 9.9998e-06 lr: 2.0000e-05 eta: 6:52:20 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 13.4825 loss: 3.5268 2023/09/05 23:34:57 - mmengine - INFO - Epoch(train) [2][ 100/2478] base_lr: 9.9996e-06 lr: 1.9999e-05 eta: 6:51:56 time: 1.1082 data_time: 0.0080 memory: 7583 grad_norm: 13.6422 loss: 3.5561 2023/09/05 23:35:19 - mmengine - INFO - Epoch(train) [2][ 120/2478] base_lr: 9.9994e-06 lr: 1.9999e-05 eta: 6:51:33 time: 1.1074 data_time: 0.0080 memory: 7583 grad_norm: 13.8512 loss: 3.6067 2023/09/05 23:35:41 - mmengine - INFO - Epoch(train) [2][ 140/2478] base_lr: 9.9992e-06 lr: 1.9998e-05 eta: 6:51:10 time: 1.1110 data_time: 0.0081 memory: 7583 grad_norm: 13.8751 loss: 3.5236 2023/09/05 23:36:03 - mmengine - INFO - Epoch(train) [2][ 160/2478] base_lr: 9.9990e-06 lr: 1.9998e-05 eta: 6:50:48 time: 1.1103 data_time: 0.0081 memory: 7583 grad_norm: 13.8497 loss: 3.4180 2023/09/05 23:36:26 - mmengine - INFO - Epoch(train) [2][ 180/2478] base_lr: 9.9987e-06 lr: 1.9997e-05 eta: 6:50:25 time: 1.1118 data_time: 0.0082 memory: 7583 grad_norm: 13.4534 loss: 3.4826 2023/09/05 23:36:48 - mmengine - INFO - Epoch(train) [2][ 200/2478] base_lr: 9.9984e-06 lr: 1.9997e-05 eta: 6:50:02 time: 1.1101 data_time: 0.0080 memory: 7583 grad_norm: 13.3375 loss: 3.7631 2023/09/05 23:37:10 - mmengine - INFO - Epoch(train) [2][ 220/2478] base_lr: 9.9981e-06 lr: 1.9996e-05 eta: 6:49:40 time: 1.1108 data_time: 0.0078 memory: 7583 grad_norm: 13.1539 loss: 3.2883 2023/09/05 23:37:32 - mmengine - INFO - Epoch(train) [2][ 240/2478] base_lr: 9.9977e-06 lr: 1.9995e-05 eta: 6:49:17 time: 1.1121 data_time: 0.0078 memory: 7583 grad_norm: 13.8260 loss: 3.2563 2023/09/05 23:37:54 - mmengine - INFO - Epoch(train) [2][ 260/2478] base_lr: 9.9973e-06 lr: 1.9995e-05 eta: 6:48:54 time: 1.1080 data_time: 0.0081 memory: 7583 grad_norm: 13.5161 loss: 3.2143 2023/09/05 23:38:17 - mmengine - INFO - Epoch(train) [2][ 280/2478] base_lr: 9.9969e-06 lr: 1.9994e-05 eta: 6:48:31 time: 1.1095 data_time: 0.0081 memory: 7583 grad_norm: 13.6559 loss: 3.1518 2023/09/05 23:38:39 - mmengine - INFO - Epoch(train) [2][ 300/2478] base_lr: 9.9964e-06 lr: 1.9993e-05 eta: 6:48:09 time: 1.1111 data_time: 0.0082 memory: 7583 grad_norm: 13.1021 loss: 3.0524 2023/09/05 23:39:01 - mmengine - INFO - Epoch(train) [2][ 320/2478] base_lr: 9.9960e-06 lr: 1.9992e-05 eta: 6:47:46 time: 1.1101 data_time: 0.0081 memory: 7583 grad_norm: 13.3988 loss: 3.3995 2023/09/05 23:39:23 - mmengine - INFO - Epoch(train) [2][ 340/2478] base_lr: 9.9954e-06 lr: 1.9991e-05 eta: 6:47:24 time: 1.1123 data_time: 0.0079 memory: 7583 grad_norm: 13.3882 loss: 3.5560 2023/09/05 23:39:46 - mmengine - INFO - Epoch(train) [2][ 360/2478] base_lr: 9.9949e-06 lr: 1.9990e-05 eta: 6:47:01 time: 1.1104 data_time: 0.0077 memory: 7583 grad_norm: 13.0512 loss: 3.2439 2023/09/05 23:40:08 - mmengine - INFO - Epoch(train) [2][ 380/2478] base_lr: 9.9943e-06 lr: 1.9989e-05 eta: 6:46:38 time: 1.1089 data_time: 0.0078 memory: 7583 grad_norm: 13.3754 loss: 2.9482 2023/09/05 23:40:30 - mmengine - INFO - Epoch(train) [2][ 400/2478] base_lr: 9.9937e-06 lr: 1.9987e-05 eta: 6:46:16 time: 1.1107 data_time: 0.0078 memory: 7583 grad_norm: 13.3356 loss: 3.0135 2023/09/05 23:40:52 - mmengine - INFO - Epoch(train) [2][ 420/2478] base_lr: 9.9930e-06 lr: 1.9986e-05 eta: 6:45:53 time: 1.1086 data_time: 0.0076 memory: 7583 grad_norm: 13.2354 loss: 3.5388 2023/09/05 23:41:14 - mmengine - INFO - Epoch(train) [2][ 440/2478] base_lr: 9.9923e-06 lr: 1.9985e-05 eta: 6:45:30 time: 1.1094 data_time: 0.0077 memory: 7583 grad_norm: 13.3234 loss: 3.1756 2023/09/05 23:41:37 - mmengine - INFO - Epoch(train) [2][ 460/2478] base_lr: 9.9916e-06 lr: 1.9983e-05 eta: 6:45:07 time: 1.1119 data_time: 0.0079 memory: 7583 grad_norm: 12.7376 loss: 3.4909 2023/09/05 23:41:59 - mmengine - INFO - Epoch(train) [2][ 480/2478] base_lr: 9.9909e-06 lr: 1.9982e-05 eta: 6:44:44 time: 1.1065 data_time: 0.0076 memory: 7583 grad_norm: 13.3061 loss: 3.5576 2023/09/05 23:42:21 - mmengine - INFO - Epoch(train) [2][ 500/2478] base_lr: 9.9901e-06 lr: 1.9980e-05 eta: 6:44:22 time: 1.1107 data_time: 0.0080 memory: 7583 grad_norm: 12.9628 loss: 3.2700 2023/09/05 23:42:43 - mmengine - INFO - Epoch(train) [2][ 520/2478] base_lr: 9.9893e-06 lr: 1.9979e-05 eta: 6:43:59 time: 1.1105 data_time: 0.0079 memory: 7583 grad_norm: 13.3261 loss: 3.1728 2023/09/05 23:42:45 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/05 23:43:05 - mmengine - INFO - Epoch(train) [2][ 540/2478] base_lr: 9.9884e-06 lr: 1.9977e-05 eta: 6:43:37 time: 1.1125 data_time: 0.0078 memory: 7583 grad_norm: 13.1179 loss: 3.0124 2023/09/05 23:43:28 - mmengine - INFO - Epoch(train) [2][ 560/2478] base_lr: 9.9876e-06 lr: 1.9975e-05 eta: 6:43:14 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 13.2551 loss: 3.2980 2023/09/05 23:43:50 - mmengine - INFO - Epoch(train) [2][ 580/2478] base_lr: 9.9867e-06 lr: 1.9973e-05 eta: 6:42:52 time: 1.1112 data_time: 0.0080 memory: 7583 grad_norm: 13.3556 loss: 3.2345 2023/09/05 23:44:12 - mmengine - INFO - Epoch(train) [2][ 600/2478] base_lr: 9.9857e-06 lr: 1.9971e-05 eta: 6:42:29 time: 1.1119 data_time: 0.0080 memory: 7583 grad_norm: 13.1316 loss: 3.4494 2023/09/05 23:44:34 - mmengine - INFO - Epoch(train) [2][ 620/2478] base_lr: 9.9848e-06 lr: 1.9970e-05 eta: 6:42:07 time: 1.1119 data_time: 0.0080 memory: 7583 grad_norm: 12.7971 loss: 3.3741 2023/09/05 23:44:57 - mmengine - INFO - Epoch(train) [2][ 640/2478] base_lr: 9.9838e-06 lr: 1.9968e-05 eta: 6:41:45 time: 1.1135 data_time: 0.0083 memory: 7583 grad_norm: 12.9978 loss: 3.2826 2023/09/05 23:45:19 - mmengine - INFO - Epoch(train) [2][ 660/2478] base_lr: 9.9827e-06 lr: 1.9965e-05 eta: 6:41:22 time: 1.1105 data_time: 0.0081 memory: 7583 grad_norm: 12.8953 loss: 3.0933 2023/09/05 23:45:41 - mmengine - INFO - Epoch(train) [2][ 680/2478] base_lr: 9.9817e-06 lr: 1.9963e-05 eta: 6:41:00 time: 1.1120 data_time: 0.0080 memory: 7583 grad_norm: 13.1374 loss: 3.2308 2023/09/05 23:46:03 - mmengine - INFO - Epoch(train) [2][ 700/2478] base_lr: 9.9806e-06 lr: 1.9961e-05 eta: 6:40:37 time: 1.1088 data_time: 0.0083 memory: 7583 grad_norm: 13.4078 loss: 3.4875 2023/09/05 23:46:25 - mmengine - INFO - Epoch(train) [2][ 720/2478] base_lr: 9.9794e-06 lr: 1.9959e-05 eta: 6:40:15 time: 1.1104 data_time: 0.0083 memory: 7583 grad_norm: 13.4396 loss: 3.4312 2023/09/05 23:46:48 - mmengine - INFO - Epoch(train) [2][ 740/2478] base_lr: 9.9783e-06 lr: 1.9957e-05 eta: 6:39:52 time: 1.1122 data_time: 0.0079 memory: 7583 grad_norm: 12.7703 loss: 3.1382 2023/09/05 23:47:10 - mmengine - INFO - Epoch(train) [2][ 760/2478] base_lr: 9.9771e-06 lr: 1.9954e-05 eta: 6:39:29 time: 1.1088 data_time: 0.0081 memory: 7583 grad_norm: 13.0843 loss: 2.4485 2023/09/05 23:47:32 - mmengine - INFO - Epoch(train) [2][ 780/2478] base_lr: 9.9759e-06 lr: 1.9952e-05 eta: 6:39:07 time: 1.1117 data_time: 0.0083 memory: 7583 grad_norm: 13.0210 loss: 3.2361 2023/09/05 23:47:54 - mmengine - INFO - Epoch(train) [2][ 800/2478] base_lr: 9.9746e-06 lr: 1.9949e-05 eta: 6:38:45 time: 1.1117 data_time: 0.0077 memory: 7583 grad_norm: 13.6874 loss: 3.7278 2023/09/05 23:48:16 - mmengine - INFO - Epoch(train) [2][ 820/2478] base_lr: 9.9733e-06 lr: 1.9947e-05 eta: 6:38:22 time: 1.1093 data_time: 0.0078 memory: 7583 grad_norm: 12.7286 loss: 3.3998 2023/09/05 23:48:39 - mmengine - INFO - Epoch(train) [2][ 840/2478] base_lr: 9.9720e-06 lr: 1.9944e-05 eta: 6:37:59 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 12.9462 loss: 3.3256 2023/09/05 23:49:01 - mmengine - INFO - Epoch(train) [2][ 860/2478] base_lr: 9.9707e-06 lr: 1.9941e-05 eta: 6:37:37 time: 1.1140 data_time: 0.0080 memory: 7583 grad_norm: 13.0596 loss: 3.0285 2023/09/05 23:49:23 - mmengine - INFO - Epoch(train) [2][ 880/2478] base_lr: 9.9693e-06 lr: 1.9939e-05 eta: 6:37:15 time: 1.1099 data_time: 0.0078 memory: 7583 grad_norm: 13.2535 loss: 3.3294 2023/09/05 23:49:45 - mmengine - INFO - Epoch(train) [2][ 900/2478] base_lr: 9.9679e-06 lr: 1.9936e-05 eta: 6:36:53 time: 1.1146 data_time: 0.0077 memory: 7583 grad_norm: 12.5631 loss: 3.0775 2023/09/05 23:50:08 - mmengine - INFO - Epoch(train) [2][ 920/2478] base_lr: 9.9664e-06 lr: 1.9933e-05 eta: 6:36:30 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 13.2561 loss: 3.1070 2023/09/05 23:50:30 - mmengine - INFO - Epoch(train) [2][ 940/2478] base_lr: 9.9650e-06 lr: 1.9930e-05 eta: 6:36:08 time: 1.1108 data_time: 0.0080 memory: 7583 grad_norm: 12.8554 loss: 2.6417 2023/09/05 23:50:52 - mmengine - INFO - Epoch(train) [2][ 960/2478] base_lr: 9.9635e-06 lr: 1.9927e-05 eta: 6:35:45 time: 1.1082 data_time: 0.0079 memory: 7583 grad_norm: 13.6033 loss: 3.9435 2023/09/05 23:51:14 - mmengine - INFO - Epoch(train) [2][ 980/2478] base_lr: 9.9619e-06 lr: 1.9924e-05 eta: 6:35:23 time: 1.1130 data_time: 0.0083 memory: 7583 grad_norm: 12.3383 loss: 2.9095 2023/09/05 23:51:36 - mmengine - INFO - Epoch(train) [2][1000/2478] base_lr: 9.9604e-06 lr: 1.9921e-05 eta: 6:35:00 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 12.8120 loss: 3.2259 2023/09/05 23:51:59 - mmengine - INFO - Epoch(train) [2][1020/2478] base_lr: 9.9588e-06 lr: 1.9918e-05 eta: 6:34:38 time: 1.1100 data_time: 0.0079 memory: 7583 grad_norm: 13.4194 loss: 2.9521 2023/09/05 23:52:21 - mmengine - INFO - Epoch(train) [2][1040/2478] base_lr: 9.9571e-06 lr: 1.9914e-05 eta: 6:34:15 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 12.2816 loss: 2.8867 2023/09/05 23:52:43 - mmengine - INFO - Epoch(train) [2][1060/2478] base_lr: 9.9555e-06 lr: 1.9911e-05 eta: 6:33:53 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 13.0514 loss: 3.2326 2023/09/05 23:53:05 - mmengine - INFO - Epoch(train) [2][1080/2478] base_lr: 9.9538e-06 lr: 1.9908e-05 eta: 6:33:30 time: 1.1106 data_time: 0.0078 memory: 7583 grad_norm: 12.9554 loss: 3.8581 2023/09/05 23:53:28 - mmengine - INFO - Epoch(train) [2][1100/2478] base_lr: 9.9520e-06 lr: 1.9904e-05 eta: 6:33:08 time: 1.1144 data_time: 0.0081 memory: 7583 grad_norm: 12.7236 loss: 3.0515 2023/09/05 23:53:50 - mmengine - INFO - Epoch(train) [2][1120/2478] base_lr: 9.9503e-06 lr: 1.9901e-05 eta: 6:32:46 time: 1.1139 data_time: 0.0081 memory: 7583 grad_norm: 12.7097 loss: 2.9796 2023/09/05 23:54:12 - mmengine - INFO - Epoch(train) [2][1140/2478] base_lr: 9.9485e-06 lr: 1.9897e-05 eta: 6:32:24 time: 1.1091 data_time: 0.0083 memory: 7583 grad_norm: 13.0833 loss: 3.8993 2023/09/05 23:54:34 - mmengine - INFO - Epoch(train) [2][1160/2478] base_lr: 9.9467e-06 lr: 1.9893e-05 eta: 6:32:01 time: 1.1091 data_time: 0.0082 memory: 7583 grad_norm: 12.7047 loss: 3.1899 2023/09/05 23:54:56 - mmengine - INFO - Epoch(train) [2][1180/2478] base_lr: 9.9448e-06 lr: 1.9890e-05 eta: 6:31:39 time: 1.1117 data_time: 0.0082 memory: 7583 grad_norm: 13.0975 loss: 2.9389 2023/09/05 23:55:19 - mmengine - INFO - Epoch(train) [2][1200/2478] base_lr: 9.9429e-06 lr: 1.9886e-05 eta: 6:31:16 time: 1.1115 data_time: 0.0082 memory: 7583 grad_norm: 12.6631 loss: 3.1799 2023/09/05 23:55:41 - mmengine - INFO - Epoch(train) [2][1220/2478] base_lr: 9.9410e-06 lr: 1.9882e-05 eta: 6:30:54 time: 1.1100 data_time: 0.0078 memory: 7583 grad_norm: 13.0817 loss: 2.9634 2023/09/05 23:56:03 - mmengine - INFO - Epoch(train) [2][1240/2478] base_lr: 9.9391e-06 lr: 1.9878e-05 eta: 6:30:31 time: 1.1112 data_time: 0.0079 memory: 7583 grad_norm: 12.6412 loss: 3.4794 2023/09/05 23:56:25 - mmengine - INFO - Epoch(train) [2][1260/2478] base_lr: 9.9371e-06 lr: 1.9874e-05 eta: 6:30:09 time: 1.1109 data_time: 0.0081 memory: 7583 grad_norm: 12.3333 loss: 2.7002 2023/09/05 23:56:48 - mmengine - INFO - Epoch(train) [2][1280/2478] base_lr: 9.9351e-06 lr: 1.9870e-05 eta: 6:29:47 time: 1.1145 data_time: 0.0079 memory: 7583 grad_norm: 12.8634 loss: 3.4076 2023/09/05 23:57:10 - mmengine - INFO - Epoch(train) [2][1300/2478] base_lr: 9.9330e-06 lr: 1.9866e-05 eta: 6:29:25 time: 1.1131 data_time: 0.0082 memory: 7583 grad_norm: 13.0780 loss: 3.2527 2023/09/05 23:57:32 - mmengine - INFO - Epoch(train) [2][1320/2478] base_lr: 9.9310e-06 lr: 1.9862e-05 eta: 6:29:02 time: 1.1115 data_time: 0.0079 memory: 7583 grad_norm: 12.7228 loss: 3.2593 2023/09/05 23:57:54 - mmengine - INFO - Epoch(train) [2][1340/2478] base_lr: 9.9288e-06 lr: 1.9858e-05 eta: 6:28:40 time: 1.1122 data_time: 0.0081 memory: 7583 grad_norm: 12.8926 loss: 3.3517 2023/09/05 23:58:17 - mmengine - INFO - Epoch(train) [2][1360/2478] base_lr: 9.9267e-06 lr: 1.9853e-05 eta: 6:28:18 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 12.9415 loss: 3.4227 2023/09/05 23:58:39 - mmengine - INFO - Epoch(train) [2][1380/2478] base_lr: 9.9245e-06 lr: 1.9849e-05 eta: 6:27:55 time: 1.1126 data_time: 0.0081 memory: 7583 grad_norm: 12.7074 loss: 3.8028 2023/09/05 23:59:01 - mmengine - INFO - Epoch(train) [2][1400/2478] base_lr: 9.9223e-06 lr: 1.9845e-05 eta: 6:27:33 time: 1.1101 data_time: 0.0080 memory: 7583 grad_norm: 12.6175 loss: 2.9704 2023/09/05 23:59:23 - mmengine - INFO - Epoch(train) [2][1420/2478] base_lr: 9.9201e-06 lr: 1.9840e-05 eta: 6:27:10 time: 1.1114 data_time: 0.0081 memory: 7583 grad_norm: 13.2060 loss: 3.0895 2023/09/05 23:59:46 - mmengine - INFO - Epoch(train) [2][1440/2478] base_lr: 9.9179e-06 lr: 1.9836e-05 eta: 6:26:48 time: 1.1134 data_time: 0.0081 memory: 7583 grad_norm: 12.3256 loss: 2.7461 2023/09/06 00:00:08 - mmengine - INFO - Epoch(train) [2][1460/2478] base_lr: 9.9156e-06 lr: 1.9831e-05 eta: 6:26:26 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 12.9393 loss: 3.3017 2023/09/06 00:00:30 - mmengine - INFO - Epoch(train) [2][1480/2478] base_lr: 9.9132e-06 lr: 1.9826e-05 eta: 6:26:03 time: 1.1108 data_time: 0.0080 memory: 7583 grad_norm: 12.3205 loss: 3.0709 2023/09/06 00:00:52 - mmengine - INFO - Epoch(train) [2][1500/2478] base_lr: 9.9109e-06 lr: 1.9822e-05 eta: 6:25:41 time: 1.1094 data_time: 0.0079 memory: 7583 grad_norm: 12.5128 loss: 2.6402 2023/09/06 00:01:14 - mmengine - INFO - Epoch(train) [2][1520/2478] base_lr: 9.9085e-06 lr: 1.9817e-05 eta: 6:25:18 time: 1.1079 data_time: 0.0079 memory: 7583 grad_norm: 12.7935 loss: 3.4165 2023/09/06 00:01:17 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 00:01:37 - mmengine - INFO - Epoch(train) [2][1540/2478] base_lr: 9.9061e-06 lr: 1.9812e-05 eta: 6:24:56 time: 1.1128 data_time: 0.0082 memory: 7583 grad_norm: 12.3489 loss: 3.1641 2023/09/06 00:01:59 - mmengine - INFO - Epoch(train) [2][1560/2478] base_lr: 9.9036e-06 lr: 1.9807e-05 eta: 6:24:33 time: 1.1094 data_time: 0.0078 memory: 7583 grad_norm: 12.8494 loss: 2.8869 2023/09/06 00:02:21 - mmengine - INFO - Epoch(train) [2][1580/2478] base_lr: 9.9011e-06 lr: 1.9802e-05 eta: 6:24:11 time: 1.1127 data_time: 0.0081 memory: 7583 grad_norm: 12.5642 loss: 3.0875 2023/09/06 00:02:43 - mmengine - INFO - Epoch(train) [2][1600/2478] base_lr: 9.8986e-06 lr: 1.9797e-05 eta: 6:23:49 time: 1.1122 data_time: 0.0085 memory: 7583 grad_norm: 12.2395 loss: 3.1470 2023/09/06 00:03:06 - mmengine - INFO - Epoch(train) [2][1620/2478] base_lr: 9.8961e-06 lr: 1.9792e-05 eta: 6:23:26 time: 1.1113 data_time: 0.0085 memory: 7583 grad_norm: 12.4718 loss: 3.7542 2023/09/06 00:03:28 - mmengine - INFO - Epoch(train) [2][1640/2478] base_lr: 9.8935e-06 lr: 1.9787e-05 eta: 6:23:04 time: 1.1092 data_time: 0.0083 memory: 7583 grad_norm: 12.5407 loss: 2.6046 2023/09/06 00:03:50 - mmengine - INFO - Epoch(train) [2][1660/2478] base_lr: 9.8909e-06 lr: 1.9782e-05 eta: 6:22:41 time: 1.1112 data_time: 0.0080 memory: 7583 grad_norm: 12.6901 loss: 2.8755 2023/09/06 00:04:12 - mmengine - INFO - Epoch(train) [2][1680/2478] base_lr: 9.8883e-06 lr: 1.9777e-05 eta: 6:22:19 time: 1.1103 data_time: 0.0081 memory: 7583 grad_norm: 12.6256 loss: 3.0495 2023/09/06 00:04:34 - mmengine - INFO - Epoch(train) [2][1700/2478] base_lr: 9.8856e-06 lr: 1.9771e-05 eta: 6:21:57 time: 1.1110 data_time: 0.0082 memory: 7583 grad_norm: 12.3654 loss: 2.7750 2023/09/06 00:04:57 - mmengine - INFO - Epoch(train) [2][1720/2478] base_lr: 9.8829e-06 lr: 1.9766e-05 eta: 6:21:34 time: 1.1105 data_time: 0.0083 memory: 7583 grad_norm: 12.1450 loss: 3.3495 2023/09/06 00:05:19 - mmengine - INFO - Epoch(train) [2][1740/2478] base_lr: 9.8802e-06 lr: 1.9760e-05 eta: 6:21:12 time: 1.1110 data_time: 0.0082 memory: 7583 grad_norm: inf loss: 3.6590 2023/09/06 00:05:41 - mmengine - INFO - Epoch(train) [2][1760/2478] base_lr: 9.8774e-06 lr: 1.9755e-05 eta: 6:20:49 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 12.7903 loss: 2.7343 2023/09/06 00:06:03 - mmengine - INFO - Epoch(train) [2][1780/2478] base_lr: 9.8746e-06 lr: 1.9749e-05 eta: 6:20:27 time: 1.1112 data_time: 0.0081 memory: 7583 grad_norm: 12.8574 loss: 3.2101 2023/09/06 00:06:25 - mmengine - INFO - Epoch(train) [2][1800/2478] base_lr: 9.8718e-06 lr: 1.9744e-05 eta: 6:20:05 time: 1.1124 data_time: 0.0080 memory: 7583 grad_norm: 12.3049 loss: 3.1860 2023/09/06 00:06:48 - mmengine - INFO - Epoch(train) [2][1820/2478] base_lr: 9.8690e-06 lr: 1.9738e-05 eta: 6:19:43 time: 1.1123 data_time: 0.0078 memory: 7583 grad_norm: 12.4378 loss: 3.2096 2023/09/06 00:07:10 - mmengine - INFO - Epoch(train) [2][1840/2478] base_lr: 9.8661e-06 lr: 1.9732e-05 eta: 6:19:20 time: 1.1120 data_time: 0.0078 memory: 7583 grad_norm: 12.1639 loss: 3.6703 2023/09/06 00:07:32 - mmengine - INFO - Epoch(train) [2][1860/2478] base_lr: 9.8632e-06 lr: 1.9726e-05 eta: 6:18:58 time: 1.1085 data_time: 0.0077 memory: 7583 grad_norm: 12.6136 loss: 2.9042 2023/09/06 00:07:54 - mmengine - INFO - Epoch(train) [2][1880/2478] base_lr: 9.8602e-06 lr: 1.9720e-05 eta: 6:18:35 time: 1.1096 data_time: 0.0080 memory: 7583 grad_norm: 12.3649 loss: 2.8989 2023/09/06 00:08:16 - mmengine - INFO - Epoch(train) [2][1900/2478] base_lr: 9.8572e-06 lr: 1.9714e-05 eta: 6:18:13 time: 1.1087 data_time: 0.0078 memory: 7583 grad_norm: 12.1610 loss: 2.8304 2023/09/06 00:08:39 - mmengine - INFO - Epoch(train) [2][1920/2478] base_lr: 9.8542e-06 lr: 1.9708e-05 eta: 6:17:50 time: 1.1113 data_time: 0.0081 memory: 7583 grad_norm: 12.3290 loss: 3.3983 2023/09/06 00:09:01 - mmengine - INFO - Epoch(train) [2][1940/2478] base_lr: 9.8512e-06 lr: 1.9702e-05 eta: 6:17:28 time: 1.1099 data_time: 0.0083 memory: 7583 grad_norm: 12.3551 loss: 3.1753 2023/09/06 00:09:23 - mmengine - INFO - Epoch(train) [2][1960/2478] base_lr: 9.8481e-06 lr: 1.9696e-05 eta: 6:17:05 time: 1.1072 data_time: 0.0081 memory: 7583 grad_norm: 12.1215 loss: 3.0734 2023/09/06 00:09:45 - mmengine - INFO - Epoch(train) [2][1980/2478] base_lr: 9.8450e-06 lr: 1.9690e-05 eta: 6:16:43 time: 1.1090 data_time: 0.0079 memory: 7583 grad_norm: 11.8083 loss: 3.0023 2023/09/06 00:10:07 - mmengine - INFO - Epoch(train) [2][2000/2478] base_lr: 9.8419e-06 lr: 1.9684e-05 eta: 6:16:20 time: 1.1090 data_time: 0.0082 memory: 7583 grad_norm: 12.3623 loss: 3.1799 2023/09/06 00:10:30 - mmengine - INFO - Epoch(train) [2][2020/2478] base_lr: 9.8387e-06 lr: 1.9677e-05 eta: 6:15:57 time: 1.1087 data_time: 0.0080 memory: 7583 grad_norm: 12.2724 loss: 2.9625 2023/09/06 00:10:52 - mmengine - INFO - Epoch(train) [2][2040/2478] base_lr: 9.8355e-06 lr: 1.9671e-05 eta: 6:15:35 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 12.0804 loss: 2.9166 2023/09/06 00:11:14 - mmengine - INFO - Epoch(train) [2][2060/2478] base_lr: 9.8323e-06 lr: 1.9665e-05 eta: 6:15:13 time: 1.1116 data_time: 0.0081 memory: 7583 grad_norm: 12.7318 loss: 3.0079 2023/09/06 00:11:36 - mmengine - INFO - Epoch(train) [2][2080/2478] base_lr: 9.8291e-06 lr: 1.9658e-05 eta: 6:14:50 time: 1.1101 data_time: 0.0081 memory: 7583 grad_norm: 12.3477 loss: 3.0757 2023/09/06 00:11:58 - mmengine - INFO - Epoch(train) [2][2100/2478] base_lr: 9.8258e-06 lr: 1.9652e-05 eta: 6:14:28 time: 1.1077 data_time: 0.0080 memory: 7583 grad_norm: 12.6205 loss: 2.7103 2023/09/06 00:12:21 - mmengine - INFO - Epoch(train) [2][2120/2478] base_lr: 9.8224e-06 lr: 1.9645e-05 eta: 6:14:05 time: 1.1111 data_time: 0.0080 memory: 7583 grad_norm: 12.2388 loss: 2.7736 2023/09/06 00:12:43 - mmengine - INFO - Epoch(train) [2][2140/2478] base_lr: 9.8191e-06 lr: 1.9638e-05 eta: 6:13:43 time: 1.1114 data_time: 0.0082 memory: 7583 grad_norm: 12.3610 loss: 3.0680 2023/09/06 00:13:05 - mmengine - INFO - Epoch(train) [2][2160/2478] base_lr: 9.8157e-06 lr: 1.9631e-05 eta: 6:13:21 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 12.3242 loss: 3.1497 2023/09/06 00:13:27 - mmengine - INFO - Epoch(train) [2][2180/2478] base_lr: 9.8123e-06 lr: 1.9625e-05 eta: 6:12:58 time: 1.1103 data_time: 0.0081 memory: 7583 grad_norm: 12.0973 loss: 2.6558 2023/09/06 00:13:49 - mmengine - INFO - Epoch(train) [2][2200/2478] base_lr: 9.8089e-06 lr: 1.9618e-05 eta: 6:12:36 time: 1.1110 data_time: 0.0085 memory: 7583 grad_norm: 12.2411 loss: 3.2653 2023/09/06 00:14:12 - mmengine - INFO - Epoch(train) [2][2220/2478] base_lr: 9.8054e-06 lr: 1.9611e-05 eta: 6:12:14 time: 1.1113 data_time: 0.0085 memory: 7583 grad_norm: 12.0727 loss: 3.1109 2023/09/06 00:14:34 - mmengine - INFO - Epoch(train) [2][2240/2478] base_lr: 9.8019e-06 lr: 1.9604e-05 eta: 6:11:51 time: 1.1100 data_time: 0.0086 memory: 7583 grad_norm: 12.2671 loss: 3.1257 2023/09/06 00:14:56 - mmengine - INFO - Epoch(train) [2][2260/2478] base_lr: 9.7984e-06 lr: 1.9597e-05 eta: 6:11:29 time: 1.1123 data_time: 0.0084 memory: 7583 grad_norm: 11.8836 loss: 2.9253 2023/09/06 00:15:18 - mmengine - INFO - Epoch(train) [2][2280/2478] base_lr: 9.7948e-06 lr: 1.9590e-05 eta: 6:11:07 time: 1.1105 data_time: 0.0084 memory: 7583 grad_norm: 12.2920 loss: 3.2697 2023/09/06 00:15:41 - mmengine - INFO - Epoch(train) [2][2300/2478] base_lr: 9.7912e-06 lr: 1.9582e-05 eta: 6:10:44 time: 1.1107 data_time: 0.0080 memory: 7583 grad_norm: 12.1300 loss: 2.9598 2023/09/06 00:16:03 - mmengine - INFO - Epoch(train) [2][2320/2478] base_lr: 9.7876e-06 lr: 1.9575e-05 eta: 6:10:22 time: 1.1114 data_time: 0.0078 memory: 7583 grad_norm: 12.4371 loss: 2.6221 2023/09/06 00:16:25 - mmengine - INFO - Epoch(train) [2][2340/2478] base_lr: 9.7840e-06 lr: 1.9568e-05 eta: 6:09:59 time: 1.1098 data_time: 0.0079 memory: 7583 grad_norm: 12.2191 loss: 2.7283 2023/09/06 00:16:47 - mmengine - INFO - Epoch(train) [2][2360/2478] base_lr: 9.7803e-06 lr: 1.9561e-05 eta: 6:09:37 time: 1.1121 data_time: 0.0082 memory: 7583 grad_norm: 12.8778 loss: 3.0347 2023/09/06 00:17:09 - mmengine - INFO - Epoch(train) [2][2380/2478] base_lr: 9.7766e-06 lr: 1.9553e-05 eta: 6:09:15 time: 1.1117 data_time: 0.0079 memory: 7583 grad_norm: 12.2930 loss: 3.1554 2023/09/06 00:17:32 - mmengine - INFO - Epoch(train) [2][2400/2478] base_lr: 9.7728e-06 lr: 1.9546e-05 eta: 6:08:53 time: 1.1125 data_time: 0.0077 memory: 7583 grad_norm: 11.9687 loss: 3.1872 2023/09/06 00:17:54 - mmengine - INFO - Epoch(train) [2][2420/2478] base_lr: 9.7690e-06 lr: 1.9538e-05 eta: 6:08:30 time: 1.1107 data_time: 0.0080 memory: 7583 grad_norm: 12.0901 loss: 2.6470 2023/09/06 00:18:16 - mmengine - INFO - Epoch(train) [2][2440/2478] base_lr: 9.7652e-06 lr: 1.9530e-05 eta: 6:08:08 time: 1.1081 data_time: 0.0080 memory: 7583 grad_norm: 12.3085 loss: 3.3455 2023/09/06 00:18:38 - mmengine - INFO - Epoch(train) [2][2460/2478] base_lr: 9.7614e-06 lr: 1.9523e-05 eta: 6:07:45 time: 1.1089 data_time: 0.0080 memory: 7583 grad_norm: 12.4103 loss: 2.7952 2023/09/06 00:18:58 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 00:18:58 - mmengine - INFO - Epoch(train) [2][2478/2478] base_lr: 9.7579e-06 lr: 1.9516e-05 eta: 6:07:25 time: 1.1076 data_time: 0.0081 memory: 7583 grad_norm: 12.3709 loss: 3.1826 2023/09/06 00:18:58 - mmengine - INFO - Saving checkpoint at 2 epochs 2023/09/06 00:19:28 - mmengine - INFO - Epoch(val) [2][20/96] eta: 0:01:21 time: 1.0771 data_time: 0.0385 memory: 8884 2023/09/06 00:19:49 - mmengine - INFO - Epoch(val) [2][40/96] eta: 0:00:59 time: 1.0509 data_time: 0.0065 memory: 8884 2023/09/06 00:20:10 - mmengine - INFO - Epoch(val) [2][60/96] eta: 0:00:38 time: 1.0455 data_time: 0.0069 memory: 8884 2023/09/06 00:20:31 - mmengine - INFO - Epoch(val) [2][80/96] eta: 0:00:16 time: 1.0511 data_time: 0.0067 memory: 8884 2023/09/06 00:20:49 - mmengine - INFO - Epoch(val) [2][96/96] VQA/acc: 41.8065 data_time: 0.0132 time: 1.0532 2023/09/06 00:20:49 - mmengine - INFO - The previous best checkpoint /mnt/workspace/lilin/Repos/mmaction2/work_dirs/vindlu_9_4/msrvtt_vqa_8x8_train_bicubic/best_VQA_acc_epoch_1.pth is removed 2023/09/06 00:20:52 - mmengine - INFO - The best checkpoint with 41.8065 VQA/acc at 2 epoch is saved to best_VQA_acc_epoch_2.pth. 2023/09/06 00:21:23 - mmengine - INFO - Epoch(train) [3][ 20/2478] base_lr: 9.7540e-06 lr: 1.9508e-05 eta: 6:07:03 time: 1.1210 data_time: 0.0191 memory: 8884 grad_norm: 11.7636 loss: 2.7913 2023/09/06 00:21:46 - mmengine - INFO - Epoch(train) [3][ 40/2478] base_lr: 9.7501e-06 lr: 1.9500e-05 eta: 6:06:41 time: 1.1097 data_time: 0.0079 memory: 7583 grad_norm: 12.0965 loss: 2.6879 2023/09/06 00:21:50 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 00:22:08 - mmengine - INFO - Epoch(train) [3][ 60/2478] base_lr: 9.7462e-06 lr: 1.9492e-05 eta: 6:06:19 time: 1.1124 data_time: 0.0080 memory: 7583 grad_norm: 12.2629 loss: 2.9318 2023/09/06 00:22:30 - mmengine - INFO - Epoch(train) [3][ 80/2478] base_lr: 9.7422e-06 lr: 1.9484e-05 eta: 6:05:56 time: 1.1113 data_time: 0.0079 memory: 7583 grad_norm: 13.1938 loss: 3.2318 2023/09/06 00:22:52 - mmengine - INFO - Epoch(train) [3][ 100/2478] base_lr: 9.7382e-06 lr: 1.9476e-05 eta: 6:05:34 time: 1.1105 data_time: 0.0079 memory: 7583 grad_norm: 12.2046 loss: 2.1426 2023/09/06 00:23:14 - mmengine - INFO - Epoch(train) [3][ 120/2478] base_lr: 9.7341e-06 lr: 1.9468e-05 eta: 6:05:12 time: 1.1113 data_time: 0.0081 memory: 7583 grad_norm: 12.8916 loss: 2.5232 2023/09/06 00:23:37 - mmengine - INFO - Epoch(train) [3][ 140/2478] base_lr: 9.7300e-06 lr: 1.9460e-05 eta: 6:04:49 time: 1.1109 data_time: 0.0081 memory: 7583 grad_norm: 13.2241 loss: 2.6010 2023/09/06 00:23:59 - mmengine - INFO - Epoch(train) [3][ 160/2478] base_lr: 9.7259e-06 lr: 1.9452e-05 eta: 6:04:27 time: 1.1088 data_time: 0.0081 memory: 7583 grad_norm: 13.1032 loss: 2.7720 2023/09/06 00:24:21 - mmengine - INFO - Epoch(train) [3][ 180/2478] base_lr: 9.7218e-06 lr: 1.9444e-05 eta: 6:04:05 time: 1.1099 data_time: 0.0080 memory: 7583 grad_norm: 12.9773 loss: 2.7525 2023/09/06 00:24:43 - mmengine - INFO - Epoch(train) [3][ 200/2478] base_lr: 9.7176e-06 lr: 1.9435e-05 eta: 6:03:42 time: 1.1105 data_time: 0.0081 memory: 7583 grad_norm: 12.7184 loss: 2.7005 2023/09/06 00:25:05 - mmengine - INFO - Epoch(train) [3][ 220/2478] base_lr: 9.7135e-06 lr: 1.9427e-05 eta: 6:03:20 time: 1.1089 data_time: 0.0080 memory: 7583 grad_norm: 12.8091 loss: 2.3512 2023/09/06 00:25:28 - mmengine - INFO - Epoch(train) [3][ 240/2478] base_lr: 9.7092e-06 lr: 1.9418e-05 eta: 6:02:58 time: 1.1133 data_time: 0.0079 memory: 7583 grad_norm: 13.0865 loss: 2.4037 2023/09/06 00:25:50 - mmengine - INFO - Epoch(train) [3][ 260/2478] base_lr: 9.7050e-06 lr: 1.9410e-05 eta: 6:02:35 time: 1.1116 data_time: 0.0084 memory: 7583 grad_norm: 13.0120 loss: 3.0826 2023/09/06 00:26:12 - mmengine - INFO - Epoch(train) [3][ 280/2478] base_lr: 9.7007e-06 lr: 1.9401e-05 eta: 6:02:13 time: 1.1116 data_time: 0.0079 memory: 7583 grad_norm: 12.8678 loss: 1.9883 2023/09/06 00:26:34 - mmengine - INFO - Epoch(train) [3][ 300/2478] base_lr: 9.6964e-06 lr: 1.9393e-05 eta: 6:01:50 time: 1.1082 data_time: 0.0081 memory: 7583 grad_norm: 12.7341 loss: 2.5319 2023/09/06 00:26:56 - mmengine - INFO - Epoch(train) [3][ 320/2478] base_lr: 9.6920e-06 lr: 1.9384e-05 eta: 6:01:28 time: 1.1100 data_time: 0.0083 memory: 7583 grad_norm: 13.0290 loss: 2.6975 2023/09/06 00:27:19 - mmengine - INFO - Epoch(train) [3][ 340/2478] base_lr: 9.6877e-06 lr: 1.9375e-05 eta: 6:01:06 time: 1.1128 data_time: 0.0079 memory: 7583 grad_norm: 12.5038 loss: 2.3699 2023/09/06 00:27:41 - mmengine - INFO - Epoch(train) [3][ 360/2478] base_lr: 9.6833e-06 lr: 1.9367e-05 eta: 6:00:44 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 13.0521 loss: 2.4806 2023/09/06 00:28:03 - mmengine - INFO - Epoch(train) [3][ 380/2478] base_lr: 9.6788e-06 lr: 1.9358e-05 eta: 6:00:21 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 13.3008 loss: 2.6448 2023/09/06 00:28:25 - mmengine - INFO - Epoch(train) [3][ 400/2478] base_lr: 9.6744e-06 lr: 1.9349e-05 eta: 5:59:59 time: 1.1089 data_time: 0.0077 memory: 7583 grad_norm: 13.4552 loss: 3.2323 2023/09/06 00:28:48 - mmengine - INFO - Epoch(train) [3][ 420/2478] base_lr: 9.6699e-06 lr: 1.9340e-05 eta: 5:59:36 time: 1.1092 data_time: 0.0079 memory: 7583 grad_norm: 12.6982 loss: 2.5874 2023/09/06 00:29:10 - mmengine - INFO - Epoch(train) [3][ 440/2478] base_lr: 9.6654e-06 lr: 1.9331e-05 eta: 5:59:14 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 13.0436 loss: 2.9977 2023/09/06 00:29:32 - mmengine - INFO - Epoch(train) [3][ 460/2478] base_lr: 9.6608e-06 lr: 1.9322e-05 eta: 5:58:52 time: 1.1122 data_time: 0.0079 memory: 7583 grad_norm: 13.1832 loss: 2.7523 2023/09/06 00:29:54 - mmengine - INFO - Epoch(train) [3][ 480/2478] base_lr: 9.6562e-06 lr: 1.9312e-05 eta: 5:58:30 time: 1.1130 data_time: 0.0076 memory: 7583 grad_norm: 12.9704 loss: 2.5487 2023/09/06 00:30:16 - mmengine - INFO - Epoch(train) [3][ 500/2478] base_lr: 9.6516e-06 lr: 1.9303e-05 eta: 5:58:07 time: 1.1122 data_time: 0.0082 memory: 7583 grad_norm: 12.8999 loss: 2.5475 2023/09/06 00:30:39 - mmengine - INFO - Epoch(train) [3][ 520/2478] base_lr: 9.6470e-06 lr: 1.9294e-05 eta: 5:57:45 time: 1.1111 data_time: 0.0080 memory: 7583 grad_norm: 12.5998 loss: 2.9563 2023/09/06 00:31:01 - mmengine - INFO - Epoch(train) [3][ 540/2478] base_lr: 9.6423e-06 lr: 1.9285e-05 eta: 5:57:23 time: 1.1105 data_time: 0.0082 memory: 7583 grad_norm: 12.8954 loss: 2.5607 2023/09/06 00:31:23 - mmengine - INFO - Epoch(train) [3][ 560/2478] base_lr: 9.6376e-06 lr: 1.9275e-05 eta: 5:57:00 time: 1.1088 data_time: 0.0080 memory: 7583 grad_norm: 12.9602 loss: 2.4117 2023/09/06 00:31:45 - mmengine - INFO - Epoch(train) [3][ 580/2478] base_lr: 9.6329e-06 lr: 1.9266e-05 eta: 5:56:38 time: 1.1154 data_time: 0.0077 memory: 7583 grad_norm: 13.2821 loss: 3.2298 2023/09/06 00:32:08 - mmengine - INFO - Epoch(train) [3][ 600/2478] base_lr: 9.6281e-06 lr: 1.9256e-05 eta: 5:56:16 time: 1.1098 data_time: 0.0077 memory: 7583 grad_norm: 13.0314 loss: 3.0793 2023/09/06 00:32:30 - mmengine - INFO - Epoch(train) [3][ 620/2478] base_lr: 9.6233e-06 lr: 1.9247e-05 eta: 5:55:53 time: 1.1099 data_time: 0.0082 memory: 7583 grad_norm: 12.9358 loss: 2.2743 2023/09/06 00:32:52 - mmengine - INFO - Epoch(train) [3][ 640/2478] base_lr: 9.6185e-06 lr: 1.9237e-05 eta: 5:55:31 time: 1.1108 data_time: 0.0082 memory: 7583 grad_norm: 13.1555 loss: 2.6018 2023/09/06 00:33:14 - mmengine - INFO - Epoch(train) [3][ 660/2478] base_lr: 9.6137e-06 lr: 1.9227e-05 eta: 5:55:09 time: 1.1123 data_time: 0.0083 memory: 7583 grad_norm: 13.0451 loss: 2.7049 2023/09/06 00:33:36 - mmengine - INFO - Epoch(train) [3][ 680/2478] base_lr: 9.6088e-06 lr: 1.9218e-05 eta: 5:54:47 time: 1.1100 data_time: 0.0080 memory: 7583 grad_norm: 13.2136 loss: 2.4421 2023/09/06 00:33:59 - mmengine - INFO - Epoch(train) [3][ 700/2478] base_lr: 9.6039e-06 lr: 1.9208e-05 eta: 5:54:24 time: 1.1049 data_time: 0.0081 memory: 7583 grad_norm: inf loss: 2.5670 2023/09/06 00:34:21 - mmengine - INFO - Epoch(train) [3][ 720/2478] base_lr: 9.5989e-06 lr: 1.9198e-05 eta: 5:54:02 time: 1.1117 data_time: 0.0084 memory: 7583 grad_norm: 12.7103 loss: 2.6221 2023/09/06 00:34:43 - mmengine - INFO - Epoch(train) [3][ 740/2478] base_lr: 9.5940e-06 lr: 1.9188e-05 eta: 5:53:39 time: 1.1134 data_time: 0.0081 memory: 7583 grad_norm: 13.0085 loss: 2.4982 2023/09/06 00:35:05 - mmengine - INFO - Epoch(train) [3][ 760/2478] base_lr: 9.5890e-06 lr: 1.9178e-05 eta: 5:53:17 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 13.1630 loss: 2.2314 2023/09/06 00:35:27 - mmengine - INFO - Epoch(train) [3][ 780/2478] base_lr: 9.5840e-06 lr: 1.9168e-05 eta: 5:52:54 time: 1.1073 data_time: 0.0080 memory: 7583 grad_norm: 12.9498 loss: 2.6543 2023/09/06 00:35:50 - mmengine - INFO - Epoch(train) [3][ 800/2478] base_lr: 9.5789e-06 lr: 1.9158e-05 eta: 5:52:32 time: 1.1122 data_time: 0.0082 memory: 7583 grad_norm: 13.1057 loss: 2.8407 2023/09/06 00:36:12 - mmengine - INFO - Epoch(train) [3][ 820/2478] base_lr: 9.5738e-06 lr: 1.9148e-05 eta: 5:52:10 time: 1.1143 data_time: 0.0084 memory: 7583 grad_norm: 12.8432 loss: 3.0859 2023/09/06 00:36:34 - mmengine - INFO - Epoch(train) [3][ 840/2478] base_lr: 9.5687e-06 lr: 1.9137e-05 eta: 5:51:48 time: 1.1128 data_time: 0.0083 memory: 7583 grad_norm: 13.1658 loss: 3.0054 2023/09/06 00:36:56 - mmengine - INFO - Epoch(train) [3][ 860/2478] base_lr: 9.5636e-06 lr: 1.9127e-05 eta: 5:51:26 time: 1.1123 data_time: 0.0083 memory: 7583 grad_norm: 13.4017 loss: 2.9529 2023/09/06 00:37:19 - mmengine - INFO - Epoch(train) [3][ 880/2478] base_lr: 9.5584e-06 lr: 1.9117e-05 eta: 5:51:03 time: 1.1080 data_time: 0.0081 memory: 7583 grad_norm: 13.1867 loss: 2.4865 2023/09/06 00:37:41 - mmengine - INFO - Epoch(train) [3][ 900/2478] base_lr: 9.5532e-06 lr: 1.9106e-05 eta: 5:50:41 time: 1.1096 data_time: 0.0080 memory: 7583 grad_norm: 12.8824 loss: 2.1147 2023/09/06 00:38:03 - mmengine - INFO - Epoch(train) [3][ 920/2478] base_lr: 9.5480e-06 lr: 1.9096e-05 eta: 5:50:18 time: 1.1096 data_time: 0.0083 memory: 7583 grad_norm: 12.7994 loss: 2.9197 2023/09/06 00:38:25 - mmengine - INFO - Epoch(train) [3][ 940/2478] base_lr: 9.5427e-06 lr: 1.9085e-05 eta: 5:49:56 time: 1.1102 data_time: 0.0083 memory: 7583 grad_norm: 13.5167 loss: 3.1264 2023/09/06 00:38:47 - mmengine - INFO - Epoch(train) [3][ 960/2478] base_lr: 9.5375e-06 lr: 1.9075e-05 eta: 5:49:34 time: 1.1122 data_time: 0.0082 memory: 7583 grad_norm: 13.0237 loss: 2.8214 2023/09/06 00:39:10 - mmengine - INFO - Epoch(train) [3][ 980/2478] base_lr: 9.5321e-06 lr: 1.9064e-05 eta: 5:49:11 time: 1.1080 data_time: 0.0084 memory: 7583 grad_norm: 12.5622 loss: 2.7625 2023/09/06 00:39:32 - mmengine - INFO - Epoch(train) [3][1000/2478] base_lr: 9.5268e-06 lr: 1.9054e-05 eta: 5:48:49 time: 1.1089 data_time: 0.0081 memory: 7583 grad_norm: 12.9932 loss: 2.9430 2023/09/06 00:39:54 - mmengine - INFO - Epoch(train) [3][1020/2478] base_lr: 9.5214e-06 lr: 1.9043e-05 eta: 5:48:27 time: 1.1177 data_time: 0.0083 memory: 7583 grad_norm: 13.4686 loss: 2.4617 2023/09/06 00:40:16 - mmengine - INFO - Epoch(train) [3][1040/2478] base_lr: 9.5160e-06 lr: 1.9032e-05 eta: 5:48:05 time: 1.1126 data_time: 0.0084 memory: 7583 grad_norm: 12.9116 loss: 2.4590 2023/09/06 00:40:21 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 00:40:39 - mmengine - INFO - Epoch(train) [3][1060/2478] base_lr: 9.5106e-06 lr: 1.9021e-05 eta: 5:47:43 time: 1.1129 data_time: 0.0081 memory: 7583 grad_norm: 12.9726 loss: 2.7514 2023/09/06 00:41:01 - mmengine - INFO - Epoch(train) [3][1080/2478] base_lr: 9.5052e-06 lr: 1.9010e-05 eta: 5:47:20 time: 1.1108 data_time: 0.0081 memory: 7583 grad_norm: 12.9158 loss: 2.7283 2023/09/06 00:41:23 - mmengine - INFO - Epoch(train) [3][1100/2478] base_lr: 9.4997e-06 lr: 1.8999e-05 eta: 5:46:58 time: 1.1119 data_time: 0.0081 memory: 7583 grad_norm: 13.1488 loss: 2.5340 2023/09/06 00:41:45 - mmengine - INFO - Epoch(train) [3][1120/2478] base_lr: 9.4942e-06 lr: 1.8988e-05 eta: 5:46:36 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 13.3109 loss: 2.7071 2023/09/06 00:42:07 - mmengine - INFO - Epoch(train) [3][1140/2478] base_lr: 9.4886e-06 lr: 1.8977e-05 eta: 5:46:14 time: 1.1115 data_time: 0.0081 memory: 7583 grad_norm: 13.1930 loss: 2.5347 2023/09/06 00:42:30 - mmengine - INFO - Epoch(train) [3][1160/2478] base_lr: 9.4830e-06 lr: 1.8966e-05 eta: 5:45:51 time: 1.1106 data_time: 0.0082 memory: 7583 grad_norm: 13.3919 loss: 2.6171 2023/09/06 00:42:52 - mmengine - INFO - Epoch(train) [3][1180/2478] base_lr: 9.4774e-06 lr: 1.8955e-05 eta: 5:45:29 time: 1.1121 data_time: 0.0080 memory: 7583 grad_norm: 12.5793 loss: 2.5550 2023/09/06 00:43:14 - mmengine - INFO - Epoch(train) [3][1200/2478] base_lr: 9.4718e-06 lr: 1.8944e-05 eta: 5:45:07 time: 1.1092 data_time: 0.0080 memory: 7583 grad_norm: 12.8161 loss: 2.4306 2023/09/06 00:43:36 - mmengine - INFO - Epoch(train) [3][1220/2478] base_lr: 9.4662e-06 lr: 1.8932e-05 eta: 5:44:44 time: 1.1102 data_time: 0.0081 memory: 7583 grad_norm: 12.9871 loss: 2.7328 2023/09/06 00:43:59 - mmengine - INFO - Epoch(train) [3][1240/2478] base_lr: 9.4605e-06 lr: 1.8921e-05 eta: 5:44:22 time: 1.1094 data_time: 0.0079 memory: 7583 grad_norm: 13.2345 loss: 2.4292 2023/09/06 00:44:21 - mmengine - INFO - Epoch(train) [3][1260/2478] base_lr: 9.4548e-06 lr: 1.8910e-05 eta: 5:44:00 time: 1.1108 data_time: 0.0085 memory: 7583 grad_norm: 12.7001 loss: 2.4287 2023/09/06 00:44:43 - mmengine - INFO - Epoch(train) [3][1280/2478] base_lr: 9.4490e-06 lr: 1.8898e-05 eta: 5:43:38 time: 1.1150 data_time: 0.0084 memory: 7583 grad_norm: 13.1619 loss: 2.5727 2023/09/06 00:45:05 - mmengine - INFO - Epoch(train) [3][1300/2478] base_lr: 9.4433e-06 lr: 1.8887e-05 eta: 5:43:15 time: 1.1136 data_time: 0.0083 memory: 7583 grad_norm: 12.8073 loss: 2.7214 2023/09/06 00:45:28 - mmengine - INFO - Epoch(train) [3][1320/2478] base_lr: 9.4375e-06 lr: 1.8875e-05 eta: 5:42:53 time: 1.1114 data_time: 0.0085 memory: 7583 grad_norm: 12.4998 loss: 2.9609 2023/09/06 00:45:50 - mmengine - INFO - Epoch(train) [3][1340/2478] base_lr: 9.4316e-06 lr: 1.8863e-05 eta: 5:42:31 time: 1.1133 data_time: 0.0083 memory: 7583 grad_norm: 12.6870 loss: 2.6448 2023/09/06 00:46:12 - mmengine - INFO - Epoch(train) [3][1360/2478] base_lr: 9.4258e-06 lr: 1.8852e-05 eta: 5:42:09 time: 1.1116 data_time: 0.0082 memory: 7583 grad_norm: 12.7583 loss: 2.6107 2023/09/06 00:46:34 - mmengine - INFO - Epoch(train) [3][1380/2478] base_lr: 9.4199e-06 lr: 1.8840e-05 eta: 5:41:46 time: 1.1083 data_time: 0.0081 memory: 7583 grad_norm: 12.8757 loss: 2.2140 2023/09/06 00:46:56 - mmengine - INFO - Epoch(train) [3][1400/2478] base_lr: 9.4140e-06 lr: 1.8828e-05 eta: 5:41:24 time: 1.1103 data_time: 0.0083 memory: 7583 grad_norm: 12.6662 loss: 2.7388 2023/09/06 00:47:19 - mmengine - INFO - Epoch(train) [3][1420/2478] base_lr: 9.4081e-06 lr: 1.8816e-05 eta: 5:41:02 time: 1.1102 data_time: 0.0080 memory: 7583 grad_norm: 12.7310 loss: 2.7467 2023/09/06 00:47:41 - mmengine - INFO - Epoch(train) [3][1440/2478] base_lr: 9.4021e-06 lr: 1.8804e-05 eta: 5:40:39 time: 1.1107 data_time: 0.0080 memory: 7583 grad_norm: 13.0868 loss: 2.6576 2023/09/06 00:48:03 - mmengine - INFO - Epoch(train) [3][1460/2478] base_lr: 9.3961e-06 lr: 1.8792e-05 eta: 5:40:17 time: 1.1087 data_time: 0.0085 memory: 7583 grad_norm: 12.9756 loss: 2.7460 2023/09/06 00:48:25 - mmengine - INFO - Epoch(train) [3][1480/2478] base_lr: 9.3901e-06 lr: 1.8780e-05 eta: 5:39:55 time: 1.1117 data_time: 0.0082 memory: 7583 grad_norm: 13.2258 loss: 2.7525 2023/09/06 00:48:47 - mmengine - INFO - Epoch(train) [3][1500/2478] base_lr: 9.3840e-06 lr: 1.8768e-05 eta: 5:39:32 time: 1.1108 data_time: 0.0081 memory: 7583 grad_norm: 12.8127 loss: 2.7462 2023/09/06 00:49:10 - mmengine - INFO - Epoch(train) [3][1520/2478] base_lr: 9.3779e-06 lr: 1.8756e-05 eta: 5:39:10 time: 1.1088 data_time: 0.0081 memory: 7583 grad_norm: 12.4872 loss: 2.7279 2023/09/06 00:49:32 - mmengine - INFO - Epoch(train) [3][1540/2478] base_lr: 9.3718e-06 lr: 1.8744e-05 eta: 5:38:48 time: 1.1113 data_time: 0.0081 memory: 7583 grad_norm: 12.7575 loss: 2.5616 2023/09/06 00:49:54 - mmengine - INFO - Epoch(train) [3][1560/2478] base_lr: 9.3657e-06 lr: 1.8731e-05 eta: 5:38:25 time: 1.1091 data_time: 0.0079 memory: 7583 grad_norm: 13.4407 loss: 3.3276 2023/09/06 00:50:16 - mmengine - INFO - Epoch(train) [3][1580/2478] base_lr: 9.3595e-06 lr: 1.8719e-05 eta: 5:38:03 time: 1.1139 data_time: 0.0081 memory: 7583 grad_norm: 13.1644 loss: 2.5951 2023/09/06 00:50:38 - mmengine - INFO - Epoch(train) [3][1600/2478] base_lr: 9.3534e-06 lr: 1.8707e-05 eta: 5:37:41 time: 1.1081 data_time: 0.0079 memory: 7583 grad_norm: 12.8618 loss: 2.2914 2023/09/06 00:51:01 - mmengine - INFO - Epoch(train) [3][1620/2478] base_lr: 9.3471e-06 lr: 1.8694e-05 eta: 5:37:19 time: 1.1107 data_time: 0.0077 memory: 7583 grad_norm: 12.5496 loss: 2.1687 2023/09/06 00:51:23 - mmengine - INFO - Epoch(train) [3][1640/2478] base_lr: 9.3409e-06 lr: 1.8682e-05 eta: 5:36:56 time: 1.1136 data_time: 0.0077 memory: 7583 grad_norm: 12.9451 loss: 2.3241 2023/09/06 00:51:45 - mmengine - INFO - Epoch(train) [3][1660/2478] base_lr: 9.3346e-06 lr: 1.8669e-05 eta: 5:36:34 time: 1.1120 data_time: 0.0079 memory: 7583 grad_norm: 12.7829 loss: 2.3590 2023/09/06 00:52:07 - mmengine - INFO - Epoch(train) [3][1680/2478] base_lr: 9.3283e-06 lr: 1.8657e-05 eta: 5:36:12 time: 1.1120 data_time: 0.0080 memory: 7583 grad_norm: 12.8766 loss: 2.4906 2023/09/06 00:52:30 - mmengine - INFO - Epoch(train) [3][1700/2478] base_lr: 9.3220e-06 lr: 1.8644e-05 eta: 5:35:50 time: 1.1128 data_time: 0.0080 memory: 7583 grad_norm: 13.0728 loss: 2.7200 2023/09/06 00:52:52 - mmengine - INFO - Epoch(train) [3][1720/2478] base_lr: 9.3156e-06 lr: 1.8631e-05 eta: 5:35:27 time: 1.1094 data_time: 0.0082 memory: 7583 grad_norm: 12.4336 loss: 2.1098 2023/09/06 00:53:14 - mmengine - INFO - Epoch(train) [3][1740/2478] base_lr: 9.3093e-06 lr: 1.8619e-05 eta: 5:35:05 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 12.4259 loss: 2.3576 2023/09/06 00:53:36 - mmengine - INFO - Epoch(train) [3][1760/2478] base_lr: 9.3029e-06 lr: 1.8606e-05 eta: 5:34:43 time: 1.1109 data_time: 0.0079 memory: 7583 grad_norm: 12.4761 loss: 2.6876 2023/09/06 00:53:58 - mmengine - INFO - Epoch(train) [3][1780/2478] base_lr: 9.2964e-06 lr: 1.8593e-05 eta: 5:34:20 time: 1.1083 data_time: 0.0082 memory: 7583 grad_norm: 13.0820 loss: 2.0594 2023/09/06 00:54:21 - mmengine - INFO - Epoch(train) [3][1800/2478] base_lr: 9.2900e-06 lr: 1.8580e-05 eta: 5:33:58 time: 1.1115 data_time: 0.0082 memory: 7583 grad_norm: 12.6502 loss: 2.9117 2023/09/06 00:54:43 - mmengine - INFO - Epoch(train) [3][1820/2478] base_lr: 9.2835e-06 lr: 1.8567e-05 eta: 5:33:36 time: 1.1081 data_time: 0.0083 memory: 7583 grad_norm: 12.3882 loss: 2.7581 2023/09/06 00:55:05 - mmengine - INFO - Epoch(train) [3][1840/2478] base_lr: 9.2769e-06 lr: 1.8554e-05 eta: 5:33:13 time: 1.1097 data_time: 0.0081 memory: 7583 grad_norm: 12.3642 loss: 2.3959 2023/09/06 00:55:27 - mmengine - INFO - Epoch(train) [3][1860/2478] base_lr: 9.2704e-06 lr: 1.8541e-05 eta: 5:32:51 time: 1.1133 data_time: 0.0082 memory: 7583 grad_norm: 12.7969 loss: 2.1845 2023/09/06 00:55:50 - mmengine - INFO - Epoch(train) [3][1880/2478] base_lr: 9.2638e-06 lr: 1.8528e-05 eta: 5:32:29 time: 1.1118 data_time: 0.0082 memory: 7583 grad_norm: 12.8640 loss: 2.3459 2023/09/06 00:56:12 - mmengine - INFO - Epoch(train) [3][1900/2478] base_lr: 9.2572e-06 lr: 1.8514e-05 eta: 5:32:07 time: 1.1131 data_time: 0.0082 memory: 7583 grad_norm: 12.5566 loss: 2.9646 2023/09/06 00:56:34 - mmengine - INFO - Epoch(train) [3][1920/2478] base_lr: 9.2506e-06 lr: 1.8501e-05 eta: 5:31:44 time: 1.1102 data_time: 0.0081 memory: 7583 grad_norm: 12.8826 loss: 2.3749 2023/09/06 00:56:56 - mmengine - INFO - Epoch(train) [3][1940/2478] base_lr: 9.2440e-06 lr: 1.8488e-05 eta: 5:31:22 time: 1.1076 data_time: 0.0082 memory: 7583 grad_norm: 12.9156 loss: 2.6740 2023/09/06 00:57:18 - mmengine - INFO - Epoch(train) [3][1960/2478] base_lr: 9.2373e-06 lr: 1.8475e-05 eta: 5:31:00 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 13.1942 loss: 2.7288 2023/09/06 00:57:41 - mmengine - INFO - Epoch(train) [3][1980/2478] base_lr: 9.2306e-06 lr: 1.8461e-05 eta: 5:30:37 time: 1.1097 data_time: 0.0078 memory: 7583 grad_norm: 12.9388 loss: 2.3533 2023/09/06 00:58:03 - mmengine - INFO - Epoch(train) [3][2000/2478] base_lr: 9.2238e-06 lr: 1.8448e-05 eta: 5:30:15 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 13.4657 loss: 3.1435 2023/09/06 00:58:25 - mmengine - INFO - Epoch(train) [3][2020/2478] base_lr: 9.2171e-06 lr: 1.8434e-05 eta: 5:29:53 time: 1.1092 data_time: 0.0080 memory: 7583 grad_norm: 12.7562 loss: 2.4815 2023/09/06 00:58:47 - mmengine - INFO - Epoch(train) [3][2040/2478] base_lr: 9.2103e-06 lr: 1.8421e-05 eta: 5:29:30 time: 1.1060 data_time: 0.0078 memory: 7583 grad_norm: 12.8333 loss: 2.5307 2023/09/06 00:58:52 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 00:59:09 - mmengine - INFO - Epoch(train) [3][2060/2478] base_lr: 9.2035e-06 lr: 1.8407e-05 eta: 5:29:08 time: 1.1080 data_time: 0.0078 memory: 7583 grad_norm: 12.6641 loss: 2.7076 2023/09/06 00:59:32 - mmengine - INFO - Epoch(train) [3][2080/2478] base_lr: 9.1966e-06 lr: 1.8393e-05 eta: 5:28:46 time: 1.1128 data_time: 0.0079 memory: 7583 grad_norm: 12.9663 loss: 2.6749 2023/09/06 00:59:54 - mmengine - INFO - Epoch(train) [3][2100/2478] base_lr: 9.1898e-06 lr: 1.8380e-05 eta: 5:28:23 time: 1.1113 data_time: 0.0080 memory: 7583 grad_norm: 13.0449 loss: 2.7533 2023/09/06 01:00:16 - mmengine - INFO - Epoch(train) [3][2120/2478] base_lr: 9.1829e-06 lr: 1.8366e-05 eta: 5:28:01 time: 1.1102 data_time: 0.0078 memory: 7583 grad_norm: 12.5265 loss: 2.1295 2023/09/06 01:00:38 - mmengine - INFO - Epoch(train) [3][2140/2478] base_lr: 9.1759e-06 lr: 1.8352e-05 eta: 5:27:39 time: 1.1115 data_time: 0.0077 memory: 7583 grad_norm: 12.4427 loss: 2.4833 2023/09/06 01:01:00 - mmengine - INFO - Epoch(train) [3][2160/2478] base_lr: 9.1690e-06 lr: 1.8338e-05 eta: 5:27:17 time: 1.1102 data_time: 0.0079 memory: 7583 grad_norm: 12.3526 loss: 2.5886 2023/09/06 01:01:23 - mmengine - INFO - Epoch(train) [3][2180/2478] base_lr: 9.1620e-06 lr: 1.8324e-05 eta: 5:26:54 time: 1.1114 data_time: 0.0081 memory: 7583 grad_norm: 12.8405 loss: 2.6301 2023/09/06 01:01:45 - mmengine - INFO - Epoch(train) [3][2200/2478] base_lr: 9.1550e-06 lr: 1.8310e-05 eta: 5:26:32 time: 1.1117 data_time: 0.0079 memory: 7583 grad_norm: 12.7487 loss: 2.1748 2023/09/06 01:02:07 - mmengine - INFO - Epoch(train) [3][2220/2478] base_lr: 9.1480e-06 lr: 1.8296e-05 eta: 5:26:10 time: 1.1157 data_time: 0.0081 memory: 7583 grad_norm: 12.8166 loss: 2.4719 2023/09/06 01:02:29 - mmengine - INFO - Epoch(train) [3][2240/2478] base_lr: 9.1409e-06 lr: 1.8282e-05 eta: 5:25:48 time: 1.1134 data_time: 0.0080 memory: 7583 grad_norm: 12.7749 loss: 2.6405 2023/09/06 01:02:52 - mmengine - INFO - Epoch(train) [3][2260/2478] base_lr: 9.1339e-06 lr: 1.8268e-05 eta: 5:25:26 time: 1.1145 data_time: 0.0082 memory: 7583 grad_norm: 12.8174 loss: 2.8531 2023/09/06 01:03:14 - mmengine - INFO - Epoch(train) [3][2280/2478] base_lr: 9.1268e-06 lr: 1.8254e-05 eta: 5:25:03 time: 1.1094 data_time: 0.0081 memory: 7583 grad_norm: 13.3884 loss: 2.5110 2023/09/06 01:03:36 - mmengine - INFO - Epoch(train) [3][2300/2478] base_lr: 9.1196e-06 lr: 1.8239e-05 eta: 5:24:41 time: 1.1108 data_time: 0.0083 memory: 7583 grad_norm: 12.6422 loss: 2.6292 2023/09/06 01:03:58 - mmengine - INFO - Epoch(train) [3][2320/2478] base_lr: 9.1125e-06 lr: 1.8225e-05 eta: 5:24:19 time: 1.1097 data_time: 0.0080 memory: 7583 grad_norm: 13.2664 loss: 2.7128 2023/09/06 01:04:21 - mmengine - INFO - Epoch(train) [3][2340/2478] base_lr: 9.1053e-06 lr: 1.8211e-05 eta: 5:23:57 time: 1.1100 data_time: 0.0079 memory: 7583 grad_norm: 12.6491 loss: 2.3062 2023/09/06 01:04:43 - mmengine - INFO - Epoch(train) [3][2360/2478] base_lr: 9.0981e-06 lr: 1.8196e-05 eta: 5:23:34 time: 1.1094 data_time: 0.0079 memory: 7583 grad_norm: 12.7494 loss: 2.5824 2023/09/06 01:05:05 - mmengine - INFO - Epoch(train) [3][2380/2478] base_lr: 9.0908e-06 lr: 1.8182e-05 eta: 5:23:12 time: 1.1113 data_time: 0.0077 memory: 7583 grad_norm: 13.4093 loss: 2.6953 2023/09/06 01:05:27 - mmengine - INFO - Epoch(train) [3][2400/2478] base_lr: 9.0836e-06 lr: 1.8167e-05 eta: 5:22:50 time: 1.1093 data_time: 0.0078 memory: 7583 grad_norm: 12.4133 loss: 2.3824 2023/09/06 01:05:49 - mmengine - INFO - Epoch(train) [3][2420/2478] base_lr: 9.0763e-06 lr: 1.8153e-05 eta: 5:22:27 time: 1.1098 data_time: 0.0079 memory: 7583 grad_norm: 13.0264 loss: 2.5779 2023/09/06 01:06:12 - mmengine - INFO - Epoch(train) [3][2440/2478] base_lr: 9.0690e-06 lr: 1.8138e-05 eta: 5:22:05 time: 1.1131 data_time: 0.0077 memory: 7583 grad_norm: 12.6210 loss: 2.7553 2023/09/06 01:06:34 - mmengine - INFO - Epoch(train) [3][2460/2478] base_lr: 9.0616e-06 lr: 1.8123e-05 eta: 5:21:43 time: 1.1102 data_time: 0.0078 memory: 7583 grad_norm: 13.2254 loss: 2.7720 2023/09/06 01:06:54 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 01:06:54 - mmengine - INFO - Epoch(train) [3][2478/2478] base_lr: 9.0550e-06 lr: 1.8110e-05 eta: 5:21:23 time: 1.1077 data_time: 0.0079 memory: 7583 grad_norm: 12.9503 loss: 2.5780 2023/09/06 01:06:54 - mmengine - INFO - Saving checkpoint at 3 epochs 2023/09/06 01:07:24 - mmengine - INFO - Epoch(val) [3][20/96] eta: 0:01:22 time: 1.0796 data_time: 0.0386 memory: 8884 2023/09/06 01:07:45 - mmengine - INFO - Epoch(val) [3][40/96] eta: 0:00:59 time: 1.0536 data_time: 0.0064 memory: 8884 2023/09/06 01:08:06 - mmengine - INFO - Epoch(val) [3][60/96] eta: 0:00:38 time: 1.0459 data_time: 0.0066 memory: 8884 2023/09/06 01:08:27 - mmengine - INFO - Epoch(val) [3][80/96] eta: 0:00:16 time: 1.0515 data_time: 0.0070 memory: 8884 2023/09/06 01:08:45 - mmengine - INFO - Epoch(val) [3][96/96] VQA/acc: 42.2381 data_time: 0.0133 time: 1.0539 2023/09/06 01:08:45 - mmengine - INFO - The previous best checkpoint /mnt/workspace/lilin/Repos/mmaction2/work_dirs/vindlu_9_4/msrvtt_vqa_8x8_train_bicubic/best_VQA_acc_epoch_2.pth is removed 2023/09/06 01:08:48 - mmengine - INFO - The best checkpoint with 42.2381 VQA/acc at 3 epoch is saved to best_VQA_acc_epoch_3.pth. 2023/09/06 01:09:19 - mmengine - INFO - Epoch(train) [4][ 20/2478] base_lr: 9.0476e-06 lr: 1.8095e-05 eta: 5:21:01 time: 1.1215 data_time: 0.0194 memory: 8884 grad_norm: 12.1250 loss: 2.4466 2023/09/06 01:09:41 - mmengine - INFO - Epoch(train) [4][ 40/2478] base_lr: 9.0402e-06 lr: 1.8080e-05 eta: 5:20:39 time: 1.1107 data_time: 0.0077 memory: 7583 grad_norm: 13.2845 loss: 2.7227 2023/09/06 01:10:04 - mmengine - INFO - Epoch(train) [4][ 60/2478] base_lr: 9.0328e-06 lr: 1.8066e-05 eta: 5:20:16 time: 1.1120 data_time: 0.0079 memory: 7583 grad_norm: 12.7938 loss: 2.3258 2023/09/06 01:10:26 - mmengine - INFO - Epoch(train) [4][ 80/2478] base_lr: 9.0253e-06 lr: 1.8051e-05 eta: 5:19:54 time: 1.1125 data_time: 0.0076 memory: 7583 grad_norm: 13.1665 loss: 2.5265 2023/09/06 01:10:48 - mmengine - INFO - Epoch(train) [4][ 100/2478] base_lr: 9.0178e-06 lr: 1.8036e-05 eta: 5:19:32 time: 1.1086 data_time: 0.0078 memory: 7583 grad_norm: 12.5988 loss: 2.1948 2023/09/06 01:11:10 - mmengine - INFO - Epoch(train) [4][ 120/2478] base_lr: 9.0103e-06 lr: 1.8021e-05 eta: 5:19:09 time: 1.1101 data_time: 0.0082 memory: 7583 grad_norm: 14.1813 loss: 2.3046 2023/09/06 01:11:32 - mmengine - INFO - Epoch(train) [4][ 140/2478] base_lr: 9.0027e-06 lr: 1.8005e-05 eta: 5:18:47 time: 1.1092 data_time: 0.0082 memory: 7583 grad_norm: 13.7098 loss: 2.2397 2023/09/06 01:11:55 - mmengine - INFO - Epoch(train) [4][ 160/2478] base_lr: 8.9952e-06 lr: 1.7990e-05 eta: 5:18:25 time: 1.1116 data_time: 0.0080 memory: 7583 grad_norm: 13.5425 loss: 2.0229 2023/09/06 01:12:17 - mmengine - INFO - Epoch(train) [4][ 180/2478] base_lr: 8.9876e-06 lr: 1.7975e-05 eta: 5:18:02 time: 1.1092 data_time: 0.0081 memory: 7583 grad_norm: 13.5940 loss: 2.0518 2023/09/06 01:12:39 - mmengine - INFO - Epoch(train) [4][ 200/2478] base_lr: 8.9800e-06 lr: 1.7960e-05 eta: 5:17:40 time: 1.1096 data_time: 0.0078 memory: 7583 grad_norm: 13.3844 loss: 2.1572 2023/09/06 01:13:01 - mmengine - INFO - Epoch(train) [4][ 220/2478] base_lr: 8.9723e-06 lr: 1.7945e-05 eta: 5:17:18 time: 1.1097 data_time: 0.0079 memory: 7583 grad_norm: 13.5131 loss: 2.1114 2023/09/06 01:13:23 - mmengine - INFO - Epoch(train) [4][ 240/2478] base_lr: 8.9646e-06 lr: 1.7929e-05 eta: 5:16:56 time: 1.1103 data_time: 0.0079 memory: 7583 grad_norm: 13.5446 loss: 2.0161 2023/09/06 01:13:46 - mmengine - INFO - Epoch(train) [4][ 260/2478] base_lr: 8.9570e-06 lr: 1.7914e-05 eta: 5:16:33 time: 1.1096 data_time: 0.0080 memory: 7583 grad_norm: 14.0583 loss: 2.2931 2023/09/06 01:14:08 - mmengine - INFO - Epoch(train) [4][ 280/2478] base_lr: 8.9492e-06 lr: 1.7898e-05 eta: 5:16:11 time: 1.1129 data_time: 0.0077 memory: 7583 grad_norm: 13.9943 loss: 2.3036 2023/09/06 01:14:30 - mmengine - INFO - Epoch(train) [4][ 300/2478] base_lr: 8.9415e-06 lr: 1.7883e-05 eta: 5:15:49 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 14.0437 loss: 2.3725 2023/09/06 01:14:52 - mmengine - INFO - Epoch(train) [4][ 320/2478] base_lr: 8.9337e-06 lr: 1.7867e-05 eta: 5:15:27 time: 1.1126 data_time: 0.0082 memory: 7583 grad_norm: 13.9987 loss: 2.0977 2023/09/06 01:15:15 - mmengine - INFO - Epoch(train) [4][ 340/2478] base_lr: 8.9259e-06 lr: 1.7852e-05 eta: 5:15:04 time: 1.1129 data_time: 0.0079 memory: 7583 grad_norm: 14.0590 loss: 2.3492 2023/09/06 01:15:37 - mmengine - INFO - Epoch(train) [4][ 360/2478] base_lr: 8.9181e-06 lr: 1.7836e-05 eta: 5:14:42 time: 1.1123 data_time: 0.0080 memory: 7583 grad_norm: 13.8571 loss: 2.1405 2023/09/06 01:15:59 - mmengine - INFO - Epoch(train) [4][ 380/2478] base_lr: 8.9103e-06 lr: 1.7821e-05 eta: 5:14:20 time: 1.1118 data_time: 0.0080 memory: 7583 grad_norm: 13.1313 loss: 1.8694 2023/09/06 01:16:21 - mmengine - INFO - Epoch(train) [4][ 400/2478] base_lr: 8.9024e-06 lr: 1.7805e-05 eta: 5:13:58 time: 1.1098 data_time: 0.0079 memory: 7583 grad_norm: 13.5353 loss: 2.0131 2023/09/06 01:16:44 - mmengine - INFO - Epoch(train) [4][ 420/2478] base_lr: 8.8945e-06 lr: 1.7789e-05 eta: 5:13:35 time: 1.1132 data_time: 0.0081 memory: 7583 grad_norm: 13.8290 loss: 2.0160 2023/09/06 01:17:06 - mmengine - INFO - Epoch(train) [4][ 440/2478] base_lr: 8.8866e-06 lr: 1.7773e-05 eta: 5:13:13 time: 1.1067 data_time: 0.0081 memory: 7583 grad_norm: 13.8031 loss: 2.2599 2023/09/06 01:17:28 - mmengine - INFO - Epoch(train) [4][ 460/2478] base_lr: 8.8786e-06 lr: 1.7757e-05 eta: 5:12:51 time: 1.1085 data_time: 0.0082 memory: 7583 grad_norm: 13.2865 loss: 2.1040 2023/09/06 01:17:50 - mmengine - INFO - Epoch(train) [4][ 480/2478] base_lr: 8.8707e-06 lr: 1.7741e-05 eta: 5:12:28 time: 1.1118 data_time: 0.0080 memory: 7583 grad_norm: 13.6608 loss: 2.6473 2023/09/06 01:18:12 - mmengine - INFO - Epoch(train) [4][ 500/2478] base_lr: 8.8627e-06 lr: 1.7725e-05 eta: 5:12:06 time: 1.1105 data_time: 0.0083 memory: 7583 grad_norm: 13.2362 loss: 2.2464 2023/09/06 01:18:35 - mmengine - INFO - Epoch(train) [4][ 520/2478] base_lr: 8.8547e-06 lr: 1.7709e-05 eta: 5:11:44 time: 1.1100 data_time: 0.0081 memory: 7583 grad_norm: 13.5823 loss: 2.1329 2023/09/06 01:18:57 - mmengine - INFO - Epoch(train) [4][ 540/2478] base_lr: 8.8466e-06 lr: 1.7693e-05 eta: 5:11:21 time: 1.1085 data_time: 0.0081 memory: 7583 grad_norm: 13.6224 loss: 2.3001 2023/09/06 01:19:19 - mmengine - INFO - Epoch(train) [4][ 560/2478] base_lr: 8.8386e-06 lr: 1.7677e-05 eta: 5:10:59 time: 1.1101 data_time: 0.0081 memory: 7583 grad_norm: 14.1920 loss: 1.7375 2023/09/06 01:19:26 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 01:19:41 - mmengine - INFO - Epoch(train) [4][ 580/2478] base_lr: 8.8305e-06 lr: 1.7661e-05 eta: 5:10:37 time: 1.1107 data_time: 0.0085 memory: 7583 grad_norm: 14.1230 loss: 2.1722 2023/09/06 01:20:03 - mmengine - INFO - Epoch(train) [4][ 600/2478] base_lr: 8.8224e-06 lr: 1.7645e-05 eta: 5:10:15 time: 1.1137 data_time: 0.0084 memory: 7583 grad_norm: 14.0730 loss: 2.0898 2023/09/06 01:20:26 - mmengine - INFO - Epoch(train) [4][ 620/2478] base_lr: 8.8142e-06 lr: 1.7628e-05 eta: 5:09:52 time: 1.1101 data_time: 0.0086 memory: 7583 grad_norm: 13.7479 loss: 2.3631 2023/09/06 01:20:48 - mmengine - INFO - Epoch(train) [4][ 640/2478] base_lr: 8.8061e-06 lr: 1.7612e-05 eta: 5:09:30 time: 1.1111 data_time: 0.0085 memory: 7583 grad_norm: 13.5361 loss: 2.3523 2023/09/06 01:21:10 - mmengine - INFO - Epoch(train) [4][ 660/2478] base_lr: 8.7979e-06 lr: 1.7596e-05 eta: 5:09:08 time: 1.1109 data_time: 0.0085 memory: 7583 grad_norm: 13.6461 loss: 2.3306 2023/09/06 01:21:32 - mmengine - INFO - Epoch(train) [4][ 680/2478] base_lr: 8.7897e-06 lr: 1.7579e-05 eta: 5:08:46 time: 1.1130 data_time: 0.0084 memory: 7583 grad_norm: 13.6878 loss: 1.8331 2023/09/06 01:21:54 - mmengine - INFO - Epoch(train) [4][ 700/2478] base_lr: 8.7814e-06 lr: 1.7563e-05 eta: 5:08:24 time: 1.1109 data_time: 0.0084 memory: 7583 grad_norm: 14.0404 loss: 2.0435 2023/09/06 01:22:17 - mmengine - INFO - Epoch(train) [4][ 720/2478] base_lr: 8.7732e-06 lr: 1.7546e-05 eta: 5:08:01 time: 1.1109 data_time: 0.0083 memory: 7583 grad_norm: 13.8799 loss: 1.9281 2023/09/06 01:22:39 - mmengine - INFO - Epoch(train) [4][ 740/2478] base_lr: 8.7649e-06 lr: 1.7530e-05 eta: 5:07:39 time: 1.1105 data_time: 0.0085 memory: 7583 grad_norm: 13.8988 loss: 1.9703 2023/09/06 01:23:01 - mmengine - INFO - Epoch(train) [4][ 760/2478] base_lr: 8.7566e-06 lr: 1.7513e-05 eta: 5:07:17 time: 1.1170 data_time: 0.0084 memory: 7583 grad_norm: 13.0085 loss: 2.2824 2023/09/06 01:23:23 - mmengine - INFO - Epoch(train) [4][ 780/2478] base_lr: 8.7482e-06 lr: 1.7496e-05 eta: 5:06:55 time: 1.1110 data_time: 0.0084 memory: 7583 grad_norm: 13.9562 loss: 2.1419 2023/09/06 01:23:46 - mmengine - INFO - Epoch(train) [4][ 800/2478] base_lr: 8.7399e-06 lr: 1.7480e-05 eta: 5:06:32 time: 1.1096 data_time: 0.0085 memory: 7583 grad_norm: 13.9595 loss: 1.9981 2023/09/06 01:24:08 - mmengine - INFO - Epoch(train) [4][ 820/2478] base_lr: 8.7315e-06 lr: 1.7463e-05 eta: 5:06:10 time: 1.1091 data_time: 0.0085 memory: 7583 grad_norm: 14.1553 loss: 2.0048 2023/09/06 01:24:30 - mmengine - INFO - Epoch(train) [4][ 840/2478] base_lr: 8.7231e-06 lr: 1.7446e-05 eta: 5:05:48 time: 1.1131 data_time: 0.0084 memory: 7583 grad_norm: 13.4905 loss: 2.4933 2023/09/06 01:24:52 - mmengine - INFO - Epoch(train) [4][ 860/2478] base_lr: 8.7147e-06 lr: 1.7429e-05 eta: 5:05:26 time: 1.1119 data_time: 0.0084 memory: 7583 grad_norm: 13.6301 loss: 2.1870 2023/09/06 01:25:15 - mmengine - INFO - Epoch(train) [4][ 880/2478] base_lr: 8.7062e-06 lr: 1.7412e-05 eta: 5:05:03 time: 1.1119 data_time: 0.0084 memory: 7583 grad_norm: 13.8509 loss: 2.1294 2023/09/06 01:25:37 - mmengine - INFO - Epoch(train) [4][ 900/2478] base_lr: 8.6978e-06 lr: 1.7396e-05 eta: 5:04:41 time: 1.1083 data_time: 0.0084 memory: 7583 grad_norm: 13.6245 loss: 2.1763 2023/09/06 01:25:59 - mmengine - INFO - Epoch(train) [4][ 920/2478] base_lr: 8.6893e-06 lr: 1.7379e-05 eta: 5:04:19 time: 1.1096 data_time: 0.0085 memory: 7583 grad_norm: 13.8101 loss: 2.3777 2023/09/06 01:26:21 - mmengine - INFO - Epoch(train) [4][ 940/2478] base_lr: 8.6807e-06 lr: 1.7361e-05 eta: 5:03:57 time: 1.1141 data_time: 0.0085 memory: 7583 grad_norm: 13.9159 loss: 2.0531 2023/09/06 01:26:43 - mmengine - INFO - Epoch(train) [4][ 960/2478] base_lr: 8.6722e-06 lr: 1.7344e-05 eta: 5:03:34 time: 1.1126 data_time: 0.0085 memory: 7583 grad_norm: 13.8744 loss: 2.7520 2023/09/06 01:27:06 - mmengine - INFO - Epoch(train) [4][ 980/2478] base_lr: 8.6636e-06 lr: 1.7327e-05 eta: 5:03:12 time: 1.1115 data_time: 0.0085 memory: 7583 grad_norm: 14.0341 loss: 2.4114 2023/09/06 01:27:28 - mmengine - INFO - Epoch(train) [4][1000/2478] base_lr: 8.6550e-06 lr: 1.7310e-05 eta: 5:02:50 time: 1.1104 data_time: 0.0083 memory: 7583 grad_norm: 13.6393 loss: 1.8659 2023/09/06 01:27:50 - mmengine - INFO - Epoch(train) [4][1020/2478] base_lr: 8.6464e-06 lr: 1.7293e-05 eta: 5:02:28 time: 1.1120 data_time: 0.0082 memory: 7583 grad_norm: 13.3307 loss: 2.2444 2023/09/06 01:28:12 - mmengine - INFO - Epoch(train) [4][1040/2478] base_lr: 8.6378e-06 lr: 1.7276e-05 eta: 5:02:05 time: 1.1097 data_time: 0.0082 memory: 7583 grad_norm: 13.4876 loss: 2.3160 2023/09/06 01:28:35 - mmengine - INFO - Epoch(train) [4][1060/2478] base_lr: 8.6291e-06 lr: 1.7258e-05 eta: 5:01:43 time: 1.1110 data_time: 0.0084 memory: 7583 grad_norm: 13.8530 loss: 1.9612 2023/09/06 01:28:57 - mmengine - INFO - Epoch(train) [4][1080/2478] base_lr: 8.6205e-06 lr: 1.7241e-05 eta: 5:01:21 time: 1.1113 data_time: 0.0083 memory: 7583 grad_norm: 13.4260 loss: 2.3591 2023/09/06 01:29:19 - mmengine - INFO - Epoch(train) [4][1100/2478] base_lr: 8.6117e-06 lr: 1.7223e-05 eta: 5:00:59 time: 1.1100 data_time: 0.0084 memory: 7583 grad_norm: 13.6214 loss: 2.4027 2023/09/06 01:29:41 - mmengine - INFO - Epoch(train) [4][1120/2478] base_lr: 8.6030e-06 lr: 1.7206e-05 eta: 5:00:36 time: 1.1086 data_time: 0.0086 memory: 7583 grad_norm: 13.8124 loss: 2.0785 2023/09/06 01:30:03 - mmengine - INFO - Epoch(train) [4][1140/2478] base_lr: 8.5943e-06 lr: 1.7189e-05 eta: 5:00:14 time: 1.1077 data_time: 0.0085 memory: 7583 grad_norm: 13.9507 loss: 2.2673 2023/09/06 01:30:26 - mmengine - INFO - Epoch(train) [4][1160/2478] base_lr: 8.5855e-06 lr: 1.7171e-05 eta: 4:59:52 time: 1.1105 data_time: 0.0082 memory: 7583 grad_norm: 13.9520 loss: 2.5748 2023/09/06 01:30:48 - mmengine - INFO - Epoch(train) [4][1180/2478] base_lr: 8.5767e-06 lr: 1.7153e-05 eta: 4:59:29 time: 1.1130 data_time: 0.0082 memory: 7583 grad_norm: 13.5518 loss: 2.2234 2023/09/06 01:31:10 - mmengine - INFO - Epoch(train) [4][1200/2478] base_lr: 8.5679e-06 lr: 1.7136e-05 eta: 4:59:07 time: 1.1085 data_time: 0.0082 memory: 7583 grad_norm: 13.2855 loss: 1.9436 2023/09/06 01:31:32 - mmengine - INFO - Epoch(train) [4][1220/2478] base_lr: 8.5590e-06 lr: 1.7118e-05 eta: 4:58:45 time: 1.1124 data_time: 0.0081 memory: 7583 grad_norm: 13.5699 loss: 2.2529 2023/09/06 01:31:54 - mmengine - INFO - Epoch(train) [4][1240/2478] base_lr: 8.5502e-06 lr: 1.7100e-05 eta: 4:58:23 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 13.5040 loss: 1.8324 2023/09/06 01:32:17 - mmengine - INFO - Epoch(train) [4][1260/2478] base_lr: 8.5413e-06 lr: 1.7083e-05 eta: 4:58:00 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 13.9009 loss: 2.2813 2023/09/06 01:32:39 - mmengine - INFO - Epoch(train) [4][1280/2478] base_lr: 8.5324e-06 lr: 1.7065e-05 eta: 4:57:38 time: 1.1166 data_time: 0.0079 memory: 7583 grad_norm: 13.9199 loss: 2.2443 2023/09/06 01:33:01 - mmengine - INFO - Epoch(train) [4][1300/2478] base_lr: 8.5235e-06 lr: 1.7047e-05 eta: 4:57:16 time: 1.1114 data_time: 0.0080 memory: 7583 grad_norm: 13.9530 loss: 2.0424 2023/09/06 01:33:23 - mmengine - INFO - Epoch(train) [4][1320/2478] base_lr: 8.5145e-06 lr: 1.7029e-05 eta: 4:56:54 time: 1.1092 data_time: 0.0083 memory: 7583 grad_norm: 14.2967 loss: 2.3924 2023/09/06 01:33:46 - mmengine - INFO - Epoch(train) [4][1340/2478] base_lr: 8.5055e-06 lr: 1.7011e-05 eta: 4:56:31 time: 1.1096 data_time: 0.0084 memory: 7583 grad_norm: 14.0463 loss: 2.0494 2023/09/06 01:34:08 - mmengine - INFO - Epoch(train) [4][1360/2478] base_lr: 8.4965e-06 lr: 1.6993e-05 eta: 4:56:09 time: 1.1141 data_time: 0.0081 memory: 7583 grad_norm: 13.9032 loss: 2.1103 2023/09/06 01:34:30 - mmengine - INFO - Epoch(train) [4][1380/2478] base_lr: 8.4875e-06 lr: 1.6975e-05 eta: 4:55:47 time: 1.1109 data_time: 0.0079 memory: 7583 grad_norm: 14.1750 loss: 2.1767 2023/09/06 01:34:52 - mmengine - INFO - Epoch(train) [4][1400/2478] base_lr: 8.4785e-06 lr: 1.6957e-05 eta: 4:55:25 time: 1.1119 data_time: 0.0081 memory: 7583 grad_norm: 13.2645 loss: 2.1536 2023/09/06 01:35:15 - mmengine - INFO - Epoch(train) [4][1420/2478] base_lr: 8.4694e-06 lr: 1.6939e-05 eta: 4:55:03 time: 1.1126 data_time: 0.0082 memory: 7583 grad_norm: inf loss: 2.4933 2023/09/06 01:35:37 - mmengine - INFO - Epoch(train) [4][1440/2478] base_lr: 8.4603e-06 lr: 1.6921e-05 eta: 4:54:40 time: 1.1112 data_time: 0.0081 memory: 7583 grad_norm: 13.8371 loss: 2.3339 2023/09/06 01:35:59 - mmengine - INFO - Epoch(train) [4][1460/2478] base_lr: 8.4512e-06 lr: 1.6902e-05 eta: 4:54:18 time: 1.1120 data_time: 0.0082 memory: 7583 grad_norm: 13.8579 loss: 2.1071 2023/09/06 01:36:21 - mmengine - INFO - Epoch(train) [4][1480/2478] base_lr: 8.4421e-06 lr: 1.6884e-05 eta: 4:53:56 time: 1.1106 data_time: 0.0080 memory: 7583 grad_norm: 13.9399 loss: 2.0204 2023/09/06 01:36:43 - mmengine - INFO - Epoch(train) [4][1500/2478] base_lr: 8.4329e-06 lr: 1.6866e-05 eta: 4:53:34 time: 1.1086 data_time: 0.0079 memory: 7583 grad_norm: 14.5355 loss: 2.5278 2023/09/06 01:37:06 - mmengine - INFO - Epoch(train) [4][1520/2478] base_lr: 8.4237e-06 lr: 1.6847e-05 eta: 4:53:11 time: 1.1112 data_time: 0.0079 memory: 7583 grad_norm: 13.7989 loss: 2.3098 2023/09/06 01:37:28 - mmengine - INFO - Epoch(train) [4][1540/2478] base_lr: 8.4146e-06 lr: 1.6829e-05 eta: 4:52:49 time: 1.1111 data_time: 0.0077 memory: 7583 grad_norm: 13.7310 loss: 2.2649 2023/09/06 01:37:50 - mmengine - INFO - Epoch(train) [4][1560/2478] base_lr: 8.4053e-06 lr: 1.6811e-05 eta: 4:52:27 time: 1.1120 data_time: 0.0080 memory: 7583 grad_norm: 14.0588 loss: 2.2128 2023/09/06 01:37:57 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 01:38:12 - mmengine - INFO - Epoch(train) [4][1580/2478] base_lr: 8.3961e-06 lr: 1.6792e-05 eta: 4:52:05 time: 1.1123 data_time: 0.0083 memory: 7583 grad_norm: 13.7117 loss: 2.6156 2023/09/06 01:38:35 - mmengine - INFO - Epoch(train) [4][1600/2478] base_lr: 8.3868e-06 lr: 1.6774e-05 eta: 4:51:42 time: 1.1112 data_time: 0.0080 memory: 7583 grad_norm: 13.8035 loss: 2.1830 2023/09/06 01:38:57 - mmengine - INFO - Epoch(train) [4][1620/2478] base_lr: 8.3776e-06 lr: 1.6755e-05 eta: 4:51:20 time: 1.1131 data_time: 0.0083 memory: 7583 grad_norm: 14.2121 loss: 2.0958 2023/09/06 01:39:19 - mmengine - INFO - Epoch(train) [4][1640/2478] base_lr: 8.3683e-06 lr: 1.6737e-05 eta: 4:50:58 time: 1.1126 data_time: 0.0086 memory: 7583 grad_norm: 14.0324 loss: 2.2619 2023/09/06 01:39:41 - mmengine - INFO - Epoch(train) [4][1660/2478] base_lr: 8.3589e-06 lr: 1.6718e-05 eta: 4:50:36 time: 1.1115 data_time: 0.0081 memory: 7583 grad_norm: 13.8760 loss: 2.2762 2023/09/06 01:40:04 - mmengine - INFO - Epoch(train) [4][1680/2478] base_lr: 8.3496e-06 lr: 1.6699e-05 eta: 4:50:14 time: 1.1115 data_time: 0.0082 memory: 7583 grad_norm: 13.5410 loss: 1.8793 2023/09/06 01:40:26 - mmengine - INFO - Epoch(train) [4][1700/2478] base_lr: 8.3402e-06 lr: 1.6680e-05 eta: 4:49:51 time: 1.1118 data_time: 0.0082 memory: 7583 grad_norm: 13.4166 loss: 2.0878 2023/09/06 01:40:48 - mmengine - INFO - Epoch(train) [4][1720/2478] base_lr: 8.3308e-06 lr: 1.6662e-05 eta: 4:49:29 time: 1.1099 data_time: 0.0081 memory: 7583 grad_norm: 13.6663 loss: 2.2681 2023/09/06 01:41:10 - mmengine - INFO - Epoch(train) [4][1740/2478] base_lr: 8.3214e-06 lr: 1.6643e-05 eta: 4:49:07 time: 1.1124 data_time: 0.0082 memory: 7583 grad_norm: 13.9286 loss: 2.2435 2023/09/06 01:41:33 - mmengine - INFO - Epoch(train) [4][1760/2478] base_lr: 8.3120e-06 lr: 1.6624e-05 eta: 4:48:45 time: 1.1121 data_time: 0.0085 memory: 7583 grad_norm: 13.3271 loss: 2.4383 2023/09/06 01:41:55 - mmengine - INFO - Epoch(train) [4][1780/2478] base_lr: 8.3025e-06 lr: 1.6605e-05 eta: 4:48:22 time: 1.1107 data_time: 0.0082 memory: 7583 grad_norm: 14.3120 loss: 2.1722 2023/09/06 01:42:17 - mmengine - INFO - Epoch(train) [4][1800/2478] base_lr: 8.2931e-06 lr: 1.6586e-05 eta: 4:48:00 time: 1.1105 data_time: 0.0081 memory: 7583 grad_norm: 13.6455 loss: 2.1043 2023/09/06 01:42:39 - mmengine - INFO - Epoch(train) [4][1820/2478] base_lr: 8.2836e-06 lr: 1.6567e-05 eta: 4:47:38 time: 1.1100 data_time: 0.0085 memory: 7583 grad_norm: 13.6024 loss: 2.3852 2023/09/06 01:43:01 - mmengine - INFO - Epoch(train) [4][1840/2478] base_lr: 8.2741e-06 lr: 1.6548e-05 eta: 4:47:16 time: 1.1130 data_time: 0.0080 memory: 7583 grad_norm: 13.5182 loss: 2.0695 2023/09/06 01:43:24 - mmengine - INFO - Epoch(train) [4][1860/2478] base_lr: 8.2645e-06 lr: 1.6529e-05 eta: 4:46:53 time: 1.1092 data_time: 0.0082 memory: 7583 grad_norm: 14.0849 loss: 2.1386 2023/09/06 01:43:46 - mmengine - INFO - Epoch(train) [4][1880/2478] base_lr: 8.2550e-06 lr: 1.6510e-05 eta: 4:46:31 time: 1.1137 data_time: 0.0082 memory: 7583 grad_norm: 13.5126 loss: 2.4193 2023/09/06 01:44:08 - mmengine - INFO - Epoch(train) [4][1900/2478] base_lr: 8.2454e-06 lr: 1.6491e-05 eta: 4:46:09 time: 1.1068 data_time: 0.0083 memory: 7583 grad_norm: 13.2581 loss: 1.7339 2023/09/06 01:44:30 - mmengine - INFO - Epoch(train) [4][1920/2478] base_lr: 8.2358e-06 lr: 1.6472e-05 eta: 4:45:47 time: 1.1130 data_time: 0.0080 memory: 7583 grad_norm: 13.9360 loss: 2.5476 2023/09/06 01:44:52 - mmengine - INFO - Epoch(train) [4][1940/2478] base_lr: 8.2262e-06 lr: 1.6452e-05 eta: 4:45:24 time: 1.1110 data_time: 0.0082 memory: 7583 grad_norm: 13.4851 loss: 1.9886 2023/09/06 01:45:15 - mmengine - INFO - Epoch(train) [4][1960/2478] base_lr: 8.2165e-06 lr: 1.6433e-05 eta: 4:45:02 time: 1.1138 data_time: 0.0081 memory: 7583 grad_norm: 13.5757 loss: 2.1332 2023/09/06 01:45:37 - mmengine - INFO - Epoch(train) [4][1980/2478] base_lr: 8.2069e-06 lr: 1.6414e-05 eta: 4:44:40 time: 1.1148 data_time: 0.0079 memory: 7583 grad_norm: 13.7053 loss: 1.9723 2023/09/06 01:45:59 - mmengine - INFO - Epoch(train) [4][2000/2478] base_lr: 8.1972e-06 lr: 1.6394e-05 eta: 4:44:18 time: 1.1105 data_time: 0.0081 memory: 7583 grad_norm: 13.9580 loss: 2.3224 2023/09/06 01:46:21 - mmengine - INFO - Epoch(train) [4][2020/2478] base_lr: 8.1875e-06 lr: 1.6375e-05 eta: 4:43:56 time: 1.1109 data_time: 0.0083 memory: 7583 grad_norm: 14.2033 loss: 2.2667 2023/09/06 01:46:44 - mmengine - INFO - Epoch(train) [4][2040/2478] base_lr: 8.1778e-06 lr: 1.6356e-05 eta: 4:43:33 time: 1.1116 data_time: 0.0083 memory: 7583 grad_norm: 14.0968 loss: 2.2016 2023/09/06 01:47:06 - mmengine - INFO - Epoch(train) [4][2060/2478] base_lr: 8.1681e-06 lr: 1.6336e-05 eta: 4:43:11 time: 1.1102 data_time: 0.0085 memory: 7583 grad_norm: 13.4760 loss: 2.4429 2023/09/06 01:47:28 - mmengine - INFO - Epoch(train) [4][2080/2478] base_lr: 8.1583e-06 lr: 1.6317e-05 eta: 4:42:49 time: 1.1088 data_time: 0.0080 memory: 7583 grad_norm: 13.7943 loss: 2.4045 2023/09/06 01:47:50 - mmengine - INFO - Epoch(train) [4][2100/2478] base_lr: 8.1485e-06 lr: 1.6297e-05 eta: 4:42:26 time: 1.1101 data_time: 0.0084 memory: 7583 grad_norm: 13.7936 loss: 2.2650 2023/09/06 01:48:13 - mmengine - INFO - Epoch(train) [4][2120/2478] base_lr: 8.1387e-06 lr: 1.6277e-05 eta: 4:42:04 time: 1.1116 data_time: 0.0083 memory: 7583 grad_norm: 14.8977 loss: 2.2180 2023/09/06 01:48:35 - mmengine - INFO - Epoch(train) [4][2140/2478] base_lr: 8.1289e-06 lr: 1.6258e-05 eta: 4:41:42 time: 1.1084 data_time: 0.0082 memory: 7583 grad_norm: 13.6673 loss: 2.1809 2023/09/06 01:48:57 - mmengine - INFO - Epoch(train) [4][2160/2478] base_lr: 8.1191e-06 lr: 1.6238e-05 eta: 4:41:20 time: 1.1084 data_time: 0.0082 memory: 7583 grad_norm: 13.5866 loss: 2.0174 2023/09/06 01:49:19 - mmengine - INFO - Epoch(train) [4][2180/2478] base_lr: 8.1092e-06 lr: 1.6218e-05 eta: 4:40:57 time: 1.1100 data_time: 0.0084 memory: 7583 grad_norm: 13.9054 loss: 2.1682 2023/09/06 01:49:41 - mmengine - INFO - Epoch(train) [4][2200/2478] base_lr: 8.0993e-06 lr: 1.6199e-05 eta: 4:40:35 time: 1.1107 data_time: 0.0083 memory: 7583 grad_norm: 13.7766 loss: 1.8673 2023/09/06 01:50:03 - mmengine - INFO - Epoch(train) [4][2220/2478] base_lr: 8.0894e-06 lr: 1.6179e-05 eta: 4:40:13 time: 1.1093 data_time: 0.0085 memory: 7583 grad_norm: 13.8169 loss: 2.3831 2023/09/06 01:50:26 - mmengine - INFO - Epoch(train) [4][2240/2478] base_lr: 8.0795e-06 lr: 1.6159e-05 eta: 4:39:50 time: 1.1106 data_time: 0.0086 memory: 7583 grad_norm: 14.0882 loss: 2.3063 2023/09/06 01:50:48 - mmengine - INFO - Epoch(train) [4][2260/2478] base_lr: 8.0696e-06 lr: 1.6139e-05 eta: 4:39:28 time: 1.1109 data_time: 0.0086 memory: 7583 grad_norm: 13.5635 loss: 1.8308 2023/09/06 01:51:10 - mmengine - INFO - Epoch(train) [4][2280/2478] base_lr: 8.0596e-06 lr: 1.6119e-05 eta: 4:39:06 time: 1.1126 data_time: 0.0087 memory: 7583 grad_norm: 13.8628 loss: 2.1997 2023/09/06 01:51:32 - mmengine - INFO - Epoch(train) [4][2300/2478] base_lr: 8.0497e-06 lr: 1.6099e-05 eta: 4:38:44 time: 1.1119 data_time: 0.0085 memory: 7583 grad_norm: 14.1246 loss: 2.5069 2023/09/06 01:51:55 - mmengine - INFO - Epoch(train) [4][2320/2478] base_lr: 8.0397e-06 lr: 1.6079e-05 eta: 4:38:22 time: 1.1124 data_time: 0.0082 memory: 7583 grad_norm: 13.8129 loss: 2.3078 2023/09/06 01:52:17 - mmengine - INFO - Epoch(train) [4][2340/2478] base_lr: 8.0297e-06 lr: 1.6059e-05 eta: 4:37:59 time: 1.1103 data_time: 0.0082 memory: 7583 grad_norm: 13.5967 loss: 2.0281 2023/09/06 01:52:39 - mmengine - INFO - Epoch(train) [4][2360/2478] base_lr: 8.0196e-06 lr: 1.6039e-05 eta: 4:37:37 time: 1.1123 data_time: 0.0084 memory: 7583 grad_norm: 13.5093 loss: 2.1346 2023/09/06 01:53:01 - mmengine - INFO - Epoch(train) [4][2380/2478] base_lr: 8.0096e-06 lr: 1.6019e-05 eta: 4:37:15 time: 1.1102 data_time: 0.0082 memory: 7583 grad_norm: 13.6181 loss: 2.0064 2023/09/06 01:53:24 - mmengine - INFO - Epoch(train) [4][2400/2478] base_lr: 7.9995e-06 lr: 1.5999e-05 eta: 4:36:53 time: 1.1107 data_time: 0.0082 memory: 7583 grad_norm: 13.4507 loss: 1.9270 2023/09/06 01:53:46 - mmengine - INFO - Epoch(train) [4][2420/2478] base_lr: 7.9894e-06 lr: 1.5979e-05 eta: 4:36:30 time: 1.1095 data_time: 0.0083 memory: 7583 grad_norm: 14.2441 loss: 2.1011 2023/09/06 01:54:08 - mmengine - INFO - Epoch(train) [4][2440/2478] base_lr: 7.9793e-06 lr: 1.5959e-05 eta: 4:36:08 time: 1.1096 data_time: 0.0085 memory: 7583 grad_norm: 13.7407 loss: 2.0177 2023/09/06 01:54:30 - mmengine - INFO - Epoch(train) [4][2460/2478] base_lr: 7.9692e-06 lr: 1.5938e-05 eta: 4:35:46 time: 1.1103 data_time: 0.0078 memory: 7583 grad_norm: 14.2113 loss: 2.2962 2023/09/06 01:54:50 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 01:54:50 - mmengine - INFO - Epoch(train) [4][2478/2478] base_lr: 7.9600e-06 lr: 1.5920e-05 eta: 4:35:26 time: 1.1076 data_time: 0.0079 memory: 7583 grad_norm: 13.7981 loss: 2.2905 2023/09/06 01:54:50 - mmengine - INFO - Saving checkpoint at 4 epochs 2023/09/06 01:55:21 - mmengine - INFO - Epoch(val) [4][20/96] eta: 0:01:22 time: 1.0862 data_time: 0.0393 memory: 8884 2023/09/06 01:55:42 - mmengine - INFO - Epoch(val) [4][40/96] eta: 0:00:59 time: 1.0482 data_time: 0.0066 memory: 8884 2023/09/06 01:56:03 - mmengine - INFO - Epoch(val) [4][60/96] eta: 0:00:38 time: 1.0520 data_time: 0.0066 memory: 8884 2023/09/06 01:56:24 - mmengine - INFO - Epoch(val) [4][80/96] eta: 0:00:16 time: 1.0465 data_time: 0.0066 memory: 8884 2023/09/06 01:56:41 - mmengine - INFO - Epoch(val) [4][96/96] VQA/acc: 43.3458 data_time: 0.0134 time: 1.0542 2023/09/06 01:56:41 - mmengine - INFO - The previous best checkpoint /mnt/workspace/lilin/Repos/mmaction2/work_dirs/vindlu_9_4/msrvtt_vqa_8x8_train_bicubic/best_VQA_acc_epoch_3.pth is removed 2023/09/06 01:56:45 - mmengine - INFO - The best checkpoint with 43.3458 VQA/acc at 4 epoch is saved to best_VQA_acc_epoch_4.pth. 2023/09/06 01:57:16 - mmengine - INFO - Epoch(train) [5][ 20/2478] base_lr: 7.9499e-06 lr: 1.5900e-05 eta: 4:35:04 time: 1.1244 data_time: 0.0220 memory: 8884 grad_norm: 12.7032 loss: 1.7697 2023/09/06 01:57:38 - mmengine - INFO - Epoch(train) [5][ 40/2478] base_lr: 7.9397e-06 lr: 1.5879e-05 eta: 4:34:41 time: 1.1098 data_time: 0.0077 memory: 7583 grad_norm: 13.4536 loss: 1.5712 2023/09/06 01:58:00 - mmengine - INFO - Epoch(train) [5][ 60/2478] base_lr: 7.9295e-06 lr: 1.5859e-05 eta: 4:34:19 time: 1.1088 data_time: 0.0078 memory: 7583 grad_norm: 14.0806 loss: 1.7919 2023/09/06 01:58:23 - mmengine - INFO - Epoch(train) [5][ 80/2478] base_lr: 7.9193e-06 lr: 1.5839e-05 eta: 4:33:57 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 13.9781 loss: 1.9485 2023/09/06 01:58:31 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 01:58:45 - mmengine - INFO - Epoch(train) [5][ 100/2478] base_lr: 7.9090e-06 lr: 1.5818e-05 eta: 4:33:35 time: 1.1113 data_time: 0.0082 memory: 7583 grad_norm: 13.9463 loss: 1.5447 2023/09/06 01:59:07 - mmengine - INFO - Epoch(train) [5][ 120/2478] base_lr: 7.8988e-06 lr: 1.5798e-05 eta: 4:33:12 time: 1.1091 data_time: 0.0080 memory: 7583 grad_norm: 14.1457 loss: 1.8048 2023/09/06 01:59:29 - mmengine - INFO - Epoch(train) [5][ 140/2478] base_lr: 7.8885e-06 lr: 1.5777e-05 eta: 4:32:50 time: 1.1124 data_time: 0.0081 memory: 7583 grad_norm: 13.5678 loss: 1.6847 2023/09/06 01:59:51 - mmengine - INFO - Epoch(train) [5][ 160/2478] base_lr: 7.8782e-06 lr: 1.5756e-05 eta: 4:32:28 time: 1.1099 data_time: 0.0083 memory: 7583 grad_norm: 14.5041 loss: 1.5831 2023/09/06 02:00:14 - mmengine - INFO - Epoch(train) [5][ 180/2478] base_lr: 7.8679e-06 lr: 1.5736e-05 eta: 4:32:06 time: 1.1121 data_time: 0.0082 memory: 7583 grad_norm: 14.2785 loss: 1.6651 2023/09/06 02:00:36 - mmengine - INFO - Epoch(train) [5][ 200/2478] base_lr: 7.8576e-06 lr: 1.5715e-05 eta: 4:31:43 time: 1.1093 data_time: 0.0079 memory: 7583 grad_norm: 14.4653 loss: 1.6190 2023/09/06 02:00:58 - mmengine - INFO - Epoch(train) [5][ 220/2478] base_lr: 7.8472e-06 lr: 1.5694e-05 eta: 4:31:21 time: 1.1102 data_time: 0.0078 memory: 7583 grad_norm: 14.9500 loss: 1.6371 2023/09/06 02:01:20 - mmengine - INFO - Epoch(train) [5][ 240/2478] base_lr: 7.8369e-06 lr: 1.5674e-05 eta: 4:30:59 time: 1.1079 data_time: 0.0079 memory: 7583 grad_norm: 14.8584 loss: 2.1433 2023/09/06 02:01:42 - mmengine - INFO - Epoch(train) [5][ 260/2478] base_lr: 7.8265e-06 lr: 1.5653e-05 eta: 4:30:37 time: 1.1134 data_time: 0.0080 memory: 7583 grad_norm: 14.0289 loss: 1.8441 2023/09/06 02:02:05 - mmengine - INFO - Epoch(train) [5][ 280/2478] base_lr: 7.8161e-06 lr: 1.5632e-05 eta: 4:30:14 time: 1.1122 data_time: 0.0079 memory: 7583 grad_norm: 14.6764 loss: 1.7692 2023/09/06 02:02:27 - mmengine - INFO - Epoch(train) [5][ 300/2478] base_lr: 7.8057e-06 lr: 1.5611e-05 eta: 4:29:52 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 15.1195 loss: 2.0522 2023/09/06 02:02:49 - mmengine - INFO - Epoch(train) [5][ 320/2478] base_lr: 7.7952e-06 lr: 1.5590e-05 eta: 4:29:30 time: 1.1110 data_time: 0.0082 memory: 7583 grad_norm: 14.2068 loss: 1.8543 2023/09/06 02:03:11 - mmengine - INFO - Epoch(train) [5][ 340/2478] base_lr: 7.7848e-06 lr: 1.5570e-05 eta: 4:29:08 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 14.2726 loss: 1.9408 2023/09/06 02:03:34 - mmengine - INFO - Epoch(train) [5][ 360/2478] base_lr: 7.7743e-06 lr: 1.5549e-05 eta: 4:28:45 time: 1.1117 data_time: 0.0080 memory: 7583 grad_norm: 14.4697 loss: 2.0385 2023/09/06 02:03:56 - mmengine - INFO - Epoch(train) [5][ 380/2478] base_lr: 7.7638e-06 lr: 1.5528e-05 eta: 4:28:23 time: 1.1098 data_time: 0.0081 memory: 7583 grad_norm: 14.4929 loss: 1.9098 2023/09/06 02:04:18 - mmengine - INFO - Epoch(train) [5][ 400/2478] base_lr: 7.7533e-06 lr: 1.5507e-05 eta: 4:28:01 time: 1.1113 data_time: 0.0083 memory: 7583 grad_norm: 14.5945 loss: 1.7687 2023/09/06 02:04:40 - mmengine - INFO - Epoch(train) [5][ 420/2478] base_lr: 7.7428e-06 lr: 1.5486e-05 eta: 4:27:39 time: 1.1116 data_time: 0.0085 memory: 7583 grad_norm: 14.4887 loss: 1.9949 2023/09/06 02:05:02 - mmengine - INFO - Epoch(train) [5][ 440/2478] base_lr: 7.7323e-06 lr: 1.5465e-05 eta: 4:27:16 time: 1.1092 data_time: 0.0085 memory: 7583 grad_norm: 15.2734 loss: 1.7776 2023/09/06 02:05:25 - mmengine - INFO - Epoch(train) [5][ 460/2478] base_lr: 7.7217e-06 lr: 1.5443e-05 eta: 4:26:54 time: 1.1122 data_time: 0.0082 memory: 7583 grad_norm: 14.5249 loss: 2.0192 2023/09/06 02:05:47 - mmengine - INFO - Epoch(train) [5][ 480/2478] base_lr: 7.7111e-06 lr: 1.5422e-05 eta: 4:26:32 time: 1.1102 data_time: 0.0081 memory: 7583 grad_norm: 14.6729 loss: 1.8018 2023/09/06 02:06:09 - mmengine - INFO - Epoch(train) [5][ 500/2478] base_lr: 7.7005e-06 lr: 1.5401e-05 eta: 4:26:10 time: 1.1109 data_time: 0.0084 memory: 7583 grad_norm: 14.5361 loss: 1.7169 2023/09/06 02:06:31 - mmengine - INFO - Epoch(train) [5][ 520/2478] base_lr: 7.6899e-06 lr: 1.5380e-05 eta: 4:25:47 time: 1.1094 data_time: 0.0081 memory: 7583 grad_norm: 14.1554 loss: 1.4639 2023/09/06 02:06:53 - mmengine - INFO - Epoch(train) [5][ 540/2478] base_lr: 7.6793e-06 lr: 1.5359e-05 eta: 4:25:25 time: 1.1085 data_time: 0.0080 memory: 7583 grad_norm: 14.7729 loss: 1.6983 2023/09/06 02:07:16 - mmengine - INFO - Epoch(train) [5][ 560/2478] base_lr: 7.6687e-06 lr: 1.5337e-05 eta: 4:25:03 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 14.8435 loss: 1.7454 2023/09/06 02:07:38 - mmengine - INFO - Epoch(train) [5][ 580/2478] base_lr: 7.6580e-06 lr: 1.5316e-05 eta: 4:24:40 time: 1.1098 data_time: 0.0076 memory: 7583 grad_norm: 14.5303 loss: 1.9532 2023/09/06 02:08:00 - mmengine - INFO - Epoch(train) [5][ 600/2478] base_lr: 7.6473e-06 lr: 1.5295e-05 eta: 4:24:18 time: 1.1103 data_time: 0.0079 memory: 7583 grad_norm: 14.7018 loss: 2.0038 2023/09/06 02:08:22 - mmengine - INFO - Epoch(train) [5][ 620/2478] base_lr: 7.6366e-06 lr: 1.5273e-05 eta: 4:23:56 time: 1.1119 data_time: 0.0079 memory: 7583 grad_norm: 14.7555 loss: 2.0948 2023/09/06 02:08:44 - mmengine - INFO - Epoch(train) [5][ 640/2478] base_lr: 7.6259e-06 lr: 1.5252e-05 eta: 4:23:34 time: 1.1098 data_time: 0.0078 memory: 7583 grad_norm: 14.2621 loss: 1.9035 2023/09/06 02:09:07 - mmengine - INFO - Epoch(train) [5][ 660/2478] base_lr: 7.6152e-06 lr: 1.5230e-05 eta: 4:23:11 time: 1.1102 data_time: 0.0078 memory: 7583 grad_norm: 14.3989 loss: 1.8235 2023/09/06 02:09:29 - mmengine - INFO - Epoch(train) [5][ 680/2478] base_lr: 7.6045e-06 lr: 1.5209e-05 eta: 4:22:49 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 15.0989 loss: 2.0576 2023/09/06 02:09:51 - mmengine - INFO - Epoch(train) [5][ 700/2478] base_lr: 7.5937e-06 lr: 1.5187e-05 eta: 4:22:27 time: 1.1090 data_time: 0.0079 memory: 7583 grad_norm: 14.9638 loss: 2.1859 2023/09/06 02:10:13 - mmengine - INFO - Epoch(train) [5][ 720/2478] base_lr: 7.5829e-06 lr: 1.5166e-05 eta: 4:22:05 time: 1.1114 data_time: 0.0079 memory: 7583 grad_norm: 14.5842 loss: 1.5066 2023/09/06 02:10:36 - mmengine - INFO - Epoch(train) [5][ 740/2478] base_lr: 7.5721e-06 lr: 1.5144e-05 eta: 4:21:42 time: 1.1135 data_time: 0.0080 memory: 7583 grad_norm: 14.8767 loss: 2.1398 2023/09/06 02:10:58 - mmengine - INFO - Epoch(train) [5][ 760/2478] base_lr: 7.5613e-06 lr: 1.5123e-05 eta: 4:21:20 time: 1.1078 data_time: 0.0078 memory: 7583 grad_norm: 14.6993 loss: 2.0932 2023/09/06 02:11:20 - mmengine - INFO - Epoch(train) [5][ 780/2478] base_lr: 7.5505e-06 lr: 1.5101e-05 eta: 4:20:58 time: 1.1101 data_time: 0.0077 memory: 7583 grad_norm: 15.0844 loss: 2.0505 2023/09/06 02:11:42 - mmengine - INFO - Epoch(train) [5][ 800/2478] base_lr: 7.5397e-06 lr: 1.5079e-05 eta: 4:20:36 time: 1.1123 data_time: 0.0081 memory: 7583 grad_norm: 14.8499 loss: 1.8347 2023/09/06 02:12:04 - mmengine - INFO - Epoch(train) [5][ 820/2478] base_lr: 7.5288e-06 lr: 1.5058e-05 eta: 4:20:13 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 15.3153 loss: 2.1290 2023/09/06 02:12:27 - mmengine - INFO - Epoch(train) [5][ 840/2478] base_lr: 7.5179e-06 lr: 1.5036e-05 eta: 4:19:51 time: 1.1100 data_time: 0.0077 memory: 7583 grad_norm: 14.6444 loss: 1.9208 2023/09/06 02:12:49 - mmengine - INFO - Epoch(train) [5][ 860/2478] base_lr: 7.5070e-06 lr: 1.5014e-05 eta: 4:19:29 time: 1.1141 data_time: 0.0084 memory: 7583 grad_norm: 14.7083 loss: 1.6399 2023/09/06 02:13:11 - mmengine - INFO - Epoch(train) [5][ 880/2478] base_lr: 7.4961e-06 lr: 1.4992e-05 eta: 4:19:07 time: 1.1081 data_time: 0.0082 memory: 7583 grad_norm: 15.2046 loss: 1.6907 2023/09/06 02:13:33 - mmengine - INFO - Epoch(train) [5][ 900/2478] base_lr: 7.4852e-06 lr: 1.4970e-05 eta: 4:18:44 time: 1.1109 data_time: 0.0082 memory: 7583 grad_norm: 14.2727 loss: 1.8080 2023/09/06 02:13:55 - mmengine - INFO - Epoch(train) [5][ 920/2478] base_lr: 7.4743e-06 lr: 1.4949e-05 eta: 4:18:22 time: 1.1086 data_time: 0.0084 memory: 7583 grad_norm: 15.1833 loss: 2.2313 2023/09/06 02:14:18 - mmengine - INFO - Epoch(train) [5][ 940/2478] base_lr: 7.4633e-06 lr: 1.4927e-05 eta: 4:18:00 time: 1.1093 data_time: 0.0081 memory: 7583 grad_norm: 15.0953 loss: 1.9924 2023/09/06 02:14:40 - mmengine - INFO - Epoch(train) [5][ 960/2478] base_lr: 7.4524e-06 lr: 1.4905e-05 eta: 4:17:38 time: 1.1092 data_time: 0.0081 memory: 7583 grad_norm: 14.8423 loss: 1.8323 2023/09/06 02:15:02 - mmengine - INFO - Epoch(train) [5][ 980/2478] base_lr: 7.4414e-06 lr: 1.4883e-05 eta: 4:17:15 time: 1.1097 data_time: 0.0080 memory: 7583 grad_norm: 15.0817 loss: 1.7098 2023/09/06 02:15:24 - mmengine - INFO - Epoch(train) [5][1000/2478] base_lr: 7.4304e-06 lr: 1.4861e-05 eta: 4:16:53 time: 1.1094 data_time: 0.0081 memory: 7583 grad_norm: 15.1604 loss: 1.9284 2023/09/06 02:15:46 - mmengine - INFO - Epoch(train) [5][1020/2478] base_lr: 7.4194e-06 lr: 1.4839e-05 eta: 4:16:31 time: 1.1087 data_time: 0.0080 memory: 7583 grad_norm: 15.5839 loss: 1.6142 2023/09/06 02:16:09 - mmengine - INFO - Epoch(train) [5][1040/2478] base_lr: 7.4084e-06 lr: 1.4817e-05 eta: 4:16:08 time: 1.1110 data_time: 0.0078 memory: 7583 grad_norm: 14.8796 loss: 2.0152 2023/09/06 02:16:31 - mmengine - INFO - Epoch(train) [5][1060/2478] base_lr: 7.3973e-06 lr: 1.4795e-05 eta: 4:15:46 time: 1.1117 data_time: 0.0078 memory: 7583 grad_norm: 14.7492 loss: 1.8657 2023/09/06 02:16:53 - mmengine - INFO - Epoch(train) [5][1080/2478] base_lr: 7.3862e-06 lr: 1.4772e-05 eta: 4:15:24 time: 1.1107 data_time: 0.0078 memory: 7583 grad_norm: 14.7516 loss: 1.9908 2023/09/06 02:17:02 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 02:17:15 - mmengine - INFO - Epoch(train) [5][1100/2478] base_lr: 7.3752e-06 lr: 1.4750e-05 eta: 4:15:02 time: 1.1126 data_time: 0.0082 memory: 7583 grad_norm: 15.0183 loss: 1.9411 2023/09/06 02:17:37 - mmengine - INFO - Epoch(train) [5][1120/2478] base_lr: 7.3641e-06 lr: 1.4728e-05 eta: 4:14:39 time: 1.1089 data_time: 0.0083 memory: 7583 grad_norm: 15.1334 loss: 1.7491 2023/09/06 02:18:00 - mmengine - INFO - Epoch(train) [5][1140/2478] base_lr: 7.3530e-06 lr: 1.4706e-05 eta: 4:14:17 time: 1.1111 data_time: 0.0079 memory: 7583 grad_norm: 14.6598 loss: 2.1754 2023/09/06 02:18:22 - mmengine - INFO - Epoch(train) [5][1160/2478] base_lr: 7.3419e-06 lr: 1.4684e-05 eta: 4:13:55 time: 1.1126 data_time: 0.0080 memory: 7583 grad_norm: 14.9392 loss: 1.8757 2023/09/06 02:18:44 - mmengine - INFO - Epoch(train) [5][1180/2478] base_lr: 7.3307e-06 lr: 1.4661e-05 eta: 4:13:33 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 15.0216 loss: 1.9867 2023/09/06 02:19:06 - mmengine - INFO - Epoch(train) [5][1200/2478] base_lr: 7.3196e-06 lr: 1.4639e-05 eta: 4:13:11 time: 1.1129 data_time: 0.0079 memory: 7583 grad_norm: 14.6342 loss: 1.8150 2023/09/06 02:19:29 - mmengine - INFO - Epoch(train) [5][1220/2478] base_lr: 7.3084e-06 lr: 1.4617e-05 eta: 4:12:48 time: 1.1144 data_time: 0.0083 memory: 7583 grad_norm: 14.9804 loss: 1.9395 2023/09/06 02:19:51 - mmengine - INFO - Epoch(train) [5][1240/2478] base_lr: 7.2973e-06 lr: 1.4595e-05 eta: 4:12:26 time: 1.1111 data_time: 0.0078 memory: 7583 grad_norm: 15.2557 loss: 2.0650 2023/09/06 02:20:13 - mmengine - INFO - Epoch(train) [5][1260/2478] base_lr: 7.2861e-06 lr: 1.4572e-05 eta: 4:12:04 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 14.8200 loss: 1.9420 2023/09/06 02:20:35 - mmengine - INFO - Epoch(train) [5][1280/2478] base_lr: 7.2749e-06 lr: 1.4550e-05 eta: 4:11:42 time: 1.1090 data_time: 0.0079 memory: 7583 grad_norm: 14.6725 loss: 1.6825 2023/09/06 02:20:57 - mmengine - INFO - Epoch(train) [5][1300/2478] base_lr: 7.2636e-06 lr: 1.4527e-05 eta: 4:11:19 time: 1.1089 data_time: 0.0079 memory: 7583 grad_norm: 14.7332 loss: 1.6597 2023/09/06 02:21:20 - mmengine - INFO - Epoch(train) [5][1320/2478] base_lr: 7.2524e-06 lr: 1.4505e-05 eta: 4:10:57 time: 1.1067 data_time: 0.0080 memory: 7583 grad_norm: 14.4474 loss: 1.8445 2023/09/06 02:21:42 - mmengine - INFO - Epoch(train) [5][1340/2478] base_lr: 7.2412e-06 lr: 1.4482e-05 eta: 4:10:35 time: 1.1087 data_time: 0.0080 memory: 7583 grad_norm: 15.4702 loss: 2.1037 2023/09/06 02:22:04 - mmengine - INFO - Epoch(train) [5][1360/2478] base_lr: 7.2299e-06 lr: 1.4460e-05 eta: 4:10:13 time: 1.1110 data_time: 0.0080 memory: 7583 grad_norm: 14.4402 loss: 2.0378 2023/09/06 02:22:26 - mmengine - INFO - Epoch(train) [5][1380/2478] base_lr: 7.2186e-06 lr: 1.4437e-05 eta: 4:09:50 time: 1.1102 data_time: 0.0079 memory: 7583 grad_norm: 14.9836 loss: 1.5786 2023/09/06 02:22:48 - mmengine - INFO - Epoch(train) [5][1400/2478] base_lr: 7.2073e-06 lr: 1.4415e-05 eta: 4:09:28 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 14.7140 loss: 1.5464 2023/09/06 02:23:11 - mmengine - INFO - Epoch(train) [5][1420/2478] base_lr: 7.1960e-06 lr: 1.4392e-05 eta: 4:09:06 time: 1.1087 data_time: 0.0080 memory: 7583 grad_norm: 14.2776 loss: 1.9195 2023/09/06 02:23:33 - mmengine - INFO - Epoch(train) [5][1440/2478] base_lr: 7.1847e-06 lr: 1.4369e-05 eta: 4:08:43 time: 1.1110 data_time: 0.0080 memory: 7583 grad_norm: 14.7174 loss: 1.7398 2023/09/06 02:23:55 - mmengine - INFO - Epoch(train) [5][1460/2478] base_lr: 7.1734e-06 lr: 1.4347e-05 eta: 4:08:21 time: 1.1087 data_time: 0.0081 memory: 7583 grad_norm: 14.7205 loss: 2.1565 2023/09/06 02:24:17 - mmengine - INFO - Epoch(train) [5][1480/2478] base_lr: 7.1620e-06 lr: 1.4324e-05 eta: 4:07:59 time: 1.1093 data_time: 0.0079 memory: 7583 grad_norm: 15.1108 loss: 1.6886 2023/09/06 02:24:39 - mmengine - INFO - Epoch(train) [5][1500/2478] base_lr: 7.1507e-06 lr: 1.4301e-05 eta: 4:07:37 time: 1.1087 data_time: 0.0080 memory: 7583 grad_norm: 14.9080 loss: 1.8539 2023/09/06 02:25:02 - mmengine - INFO - Epoch(train) [5][1520/2478] base_lr: 7.1393e-06 lr: 1.4279e-05 eta: 4:07:14 time: 1.1098 data_time: 0.0086 memory: 7583 grad_norm: 14.6816 loss: 1.7077 2023/09/06 02:25:24 - mmengine - INFO - Epoch(train) [5][1540/2478] base_lr: 7.1279e-06 lr: 1.4256e-05 eta: 4:06:52 time: 1.1103 data_time: 0.0083 memory: 7583 grad_norm: 14.6611 loss: 1.7973 2023/09/06 02:25:46 - mmengine - INFO - Epoch(train) [5][1560/2478] base_lr: 7.1165e-06 lr: 1.4233e-05 eta: 4:06:30 time: 1.1084 data_time: 0.0082 memory: 7583 grad_norm: 15.1995 loss: 2.0372 2023/09/06 02:26:08 - mmengine - INFO - Epoch(train) [5][1580/2478] base_lr: 7.1051e-06 lr: 1.4210e-05 eta: 4:06:08 time: 1.1111 data_time: 0.0083 memory: 7583 grad_norm: 14.9979 loss: 1.8388 2023/09/06 02:26:30 - mmengine - INFO - Epoch(train) [5][1600/2478] base_lr: 7.0937e-06 lr: 1.4187e-05 eta: 4:05:45 time: 1.1087 data_time: 0.0084 memory: 7583 grad_norm: 14.9586 loss: 1.7619 2023/09/06 02:26:53 - mmengine - INFO - Epoch(train) [5][1620/2478] base_lr: 7.0822e-06 lr: 1.4164e-05 eta: 4:05:23 time: 1.1109 data_time: 0.0083 memory: 7583 grad_norm: 14.8024 loss: 1.7373 2023/09/06 02:27:15 - mmengine - INFO - Epoch(train) [5][1640/2478] base_lr: 7.0708e-06 lr: 1.4142e-05 eta: 4:05:01 time: 1.1089 data_time: 0.0083 memory: 7583 grad_norm: 14.4546 loss: 1.8694 2023/09/06 02:27:37 - mmengine - INFO - Epoch(train) [5][1660/2478] base_lr: 7.0593e-06 lr: 1.4119e-05 eta: 4:04:39 time: 1.1109 data_time: 0.0081 memory: 7583 grad_norm: 14.7050 loss: 1.7891 2023/09/06 02:27:59 - mmengine - INFO - Epoch(train) [5][1680/2478] base_lr: 7.0479e-06 lr: 1.4096e-05 eta: 4:04:16 time: 1.1121 data_time: 0.0080 memory: 7583 grad_norm: 15.1392 loss: 1.7685 2023/09/06 02:28:21 - mmengine - INFO - Epoch(train) [5][1700/2478] base_lr: 7.0364e-06 lr: 1.4073e-05 eta: 4:03:54 time: 1.1122 data_time: 0.0082 memory: 7583 grad_norm: 14.8035 loss: 1.5001 2023/09/06 02:28:44 - mmengine - INFO - Epoch(train) [5][1720/2478] base_lr: 7.0249e-06 lr: 1.4050e-05 eta: 4:03:32 time: 1.1101 data_time: 0.0080 memory: 7583 grad_norm: 15.0719 loss: 1.8972 2023/09/06 02:29:06 - mmengine - INFO - Epoch(train) [5][1740/2478] base_lr: 7.0133e-06 lr: 1.4027e-05 eta: 4:03:10 time: 1.1116 data_time: 0.0082 memory: 7583 grad_norm: 14.8210 loss: 1.8431 2023/09/06 02:29:28 - mmengine - INFO - Epoch(train) [5][1760/2478] base_lr: 7.0018e-06 lr: 1.4004e-05 eta: 4:02:47 time: 1.1091 data_time: 0.0080 memory: 7583 grad_norm: 14.5579 loss: 1.8071 2023/09/06 02:29:50 - mmengine - INFO - Epoch(train) [5][1780/2478] base_lr: 6.9903e-06 lr: 1.3981e-05 eta: 4:02:25 time: 1.1115 data_time: 0.0079 memory: 7583 grad_norm: 15.1246 loss: 1.6126 2023/09/06 02:30:12 - mmengine - INFO - Epoch(train) [5][1800/2478] base_lr: 6.9787e-06 lr: 1.3957e-05 eta: 4:02:03 time: 1.1099 data_time: 0.0082 memory: 7583 grad_norm: 15.0664 loss: 1.7126 2023/09/06 02:30:35 - mmengine - INFO - Epoch(train) [5][1820/2478] base_lr: 6.9672e-06 lr: 1.3934e-05 eta: 4:01:41 time: 1.1100 data_time: 0.0083 memory: 7583 grad_norm: 14.7754 loss: 1.9596 2023/09/06 02:30:57 - mmengine - INFO - Epoch(train) [5][1840/2478] base_lr: 6.9556e-06 lr: 1.3911e-05 eta: 4:01:18 time: 1.1132 data_time: 0.0082 memory: 7583 grad_norm: 15.0294 loss: 1.5020 2023/09/06 02:31:19 - mmengine - INFO - Epoch(train) [5][1860/2478] base_lr: 6.9440e-06 lr: 1.3888e-05 eta: 4:00:56 time: 1.1104 data_time: 0.0082 memory: 7583 grad_norm: 14.9777 loss: 1.6689 2023/09/06 02:31:41 - mmengine - INFO - Epoch(train) [5][1880/2478] base_lr: 6.9324e-06 lr: 1.3865e-05 eta: 4:00:34 time: 1.1111 data_time: 0.0081 memory: 7583 grad_norm: 15.3352 loss: 2.0162 2023/09/06 02:32:04 - mmengine - INFO - Epoch(train) [5][1900/2478] base_lr: 6.9208e-06 lr: 1.3842e-05 eta: 4:00:12 time: 1.1154 data_time: 0.0078 memory: 7583 grad_norm: 14.8817 loss: 1.8334 2023/09/06 02:32:26 - mmengine - INFO - Epoch(train) [5][1920/2478] base_lr: 6.9092e-06 lr: 1.3818e-05 eta: 3:59:50 time: 1.1106 data_time: 0.0079 memory: 7583 grad_norm: 14.8556 loss: 2.0259 2023/09/06 02:32:48 - mmengine - INFO - Epoch(train) [5][1940/2478] base_lr: 6.8975e-06 lr: 1.3795e-05 eta: 3:59:27 time: 1.1165 data_time: 0.0078 memory: 7583 grad_norm: 14.8008 loss: 1.6214 2023/09/06 02:33:10 - mmengine - INFO - Epoch(train) [5][1960/2478] base_lr: 6.8859e-06 lr: 1.3772e-05 eta: 3:59:05 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 15.0741 loss: 2.0447 2023/09/06 02:33:33 - mmengine - INFO - Epoch(train) [5][1980/2478] base_lr: 6.8742e-06 lr: 1.3748e-05 eta: 3:58:43 time: 1.1124 data_time: 0.0078 memory: 7583 grad_norm: 14.6267 loss: 1.7251 2023/09/06 02:33:55 - mmengine - INFO - Epoch(train) [5][2000/2478] base_lr: 6.8625e-06 lr: 1.3725e-05 eta: 3:58:21 time: 1.1068 data_time: 0.0080 memory: 7583 grad_norm: 15.3131 loss: 2.0792 2023/09/06 02:34:17 - mmengine - INFO - Epoch(train) [5][2020/2478] base_lr: 6.8508e-06 lr: 1.3702e-05 eta: 3:57:58 time: 1.1082 data_time: 0.0079 memory: 7583 grad_norm: 14.9219 loss: 1.6340 2023/09/06 02:34:39 - mmengine - INFO - Epoch(train) [5][2040/2478] base_lr: 6.8391e-06 lr: 1.3678e-05 eta: 3:57:36 time: 1.1099 data_time: 0.0080 memory: 7583 grad_norm: 14.9373 loss: 1.8436 2023/09/06 02:35:01 - mmengine - INFO - Epoch(train) [5][2060/2478] base_lr: 6.8274e-06 lr: 1.3655e-05 eta: 3:57:14 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 14.8196 loss: 1.7462 2023/09/06 02:35:24 - mmengine - INFO - Epoch(train) [5][2080/2478] base_lr: 6.8157e-06 lr: 1.3631e-05 eta: 3:56:52 time: 1.1150 data_time: 0.0081 memory: 7583 grad_norm: 14.4119 loss: 1.6746 2023/09/06 02:35:33 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 02:35:46 - mmengine - INFO - Epoch(train) [5][2100/2478] base_lr: 6.8040e-06 lr: 1.3608e-05 eta: 3:56:29 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 15.1412 loss: 1.4855 2023/09/06 02:36:08 - mmengine - INFO - Epoch(train) [5][2120/2478] base_lr: 6.7922e-06 lr: 1.3584e-05 eta: 3:56:07 time: 1.1130 data_time: 0.0083 memory: 7583 grad_norm: 15.0174 loss: 1.8213 2023/09/06 02:36:30 - mmengine - INFO - Epoch(train) [5][2140/2478] base_lr: 6.7805e-06 lr: 1.3561e-05 eta: 3:55:45 time: 1.1132 data_time: 0.0079 memory: 7583 grad_norm: 14.6126 loss: 1.9712 2023/09/06 02:36:53 - mmengine - INFO - Epoch(train) [5][2160/2478] base_lr: 6.7687e-06 lr: 1.3537e-05 eta: 3:55:23 time: 1.1094 data_time: 0.0081 memory: 7583 grad_norm: 15.0385 loss: 2.0053 2023/09/06 02:37:15 - mmengine - INFO - Epoch(train) [5][2180/2478] base_lr: 6.7569e-06 lr: 1.3514e-05 eta: 3:55:01 time: 1.1093 data_time: 0.0084 memory: 7583 grad_norm: 14.1770 loss: 1.7407 2023/09/06 02:37:37 - mmengine - INFO - Epoch(train) [5][2200/2478] base_lr: 6.7452e-06 lr: 1.3490e-05 eta: 3:54:38 time: 1.1122 data_time: 0.0081 memory: 7583 grad_norm: 14.7058 loss: 1.7127 2023/09/06 02:37:59 - mmengine - INFO - Epoch(train) [5][2220/2478] base_lr: 6.7334e-06 lr: 1.3467e-05 eta: 3:54:16 time: 1.1106 data_time: 0.0079 memory: 7583 grad_norm: 14.9748 loss: 1.6561 2023/09/06 02:38:22 - mmengine - INFO - Epoch(train) [5][2240/2478] base_lr: 6.7216e-06 lr: 1.3443e-05 eta: 3:53:54 time: 1.1115 data_time: 0.0081 memory: 7583 grad_norm: 15.2148 loss: 1.9905 2023/09/06 02:38:44 - mmengine - INFO - Epoch(train) [5][2260/2478] base_lr: 6.7097e-06 lr: 1.3419e-05 eta: 3:53:32 time: 1.1075 data_time: 0.0081 memory: 7583 grad_norm: 14.6499 loss: 1.7737 2023/09/06 02:39:06 - mmengine - INFO - Epoch(train) [5][2280/2478] base_lr: 6.6979e-06 lr: 1.3396e-05 eta: 3:53:09 time: 1.1086 data_time: 0.0078 memory: 7583 grad_norm: 14.4570 loss: 1.9325 2023/09/06 02:39:28 - mmengine - INFO - Epoch(train) [5][2300/2478] base_lr: 6.6861e-06 lr: 1.3372e-05 eta: 3:52:47 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 14.5689 loss: 1.8326 2023/09/06 02:39:50 - mmengine - INFO - Epoch(train) [5][2320/2478] base_lr: 6.6742e-06 lr: 1.3348e-05 eta: 3:52:25 time: 1.1114 data_time: 0.0078 memory: 7583 grad_norm: 15.1112 loss: 1.9153 2023/09/06 02:40:12 - mmengine - INFO - Epoch(train) [5][2340/2478] base_lr: 6.6624e-06 lr: 1.3325e-05 eta: 3:52:03 time: 1.1102 data_time: 0.0079 memory: 7583 grad_norm: 14.7593 loss: 1.8404 2023/09/06 02:40:35 - mmengine - INFO - Epoch(train) [5][2360/2478] base_lr: 6.6505e-06 lr: 1.3301e-05 eta: 3:51:40 time: 1.1118 data_time: 0.0079 memory: 7583 grad_norm: 14.9599 loss: 1.8292 2023/09/06 02:40:57 - mmengine - INFO - Epoch(train) [5][2380/2478] base_lr: 6.6386e-06 lr: 1.3277e-05 eta: 3:51:18 time: 1.1116 data_time: 0.0079 memory: 7583 grad_norm: 15.6375 loss: 1.8967 2023/09/06 02:41:19 - mmengine - INFO - Epoch(train) [5][2400/2478] base_lr: 6.6267e-06 lr: 1.3253e-05 eta: 3:50:56 time: 1.1096 data_time: 0.0077 memory: 7583 grad_norm: 14.9746 loss: 1.7843 2023/09/06 02:41:41 - mmengine - INFO - Epoch(train) [5][2420/2478] base_lr: 6.6148e-06 lr: 1.3230e-05 eta: 3:50:34 time: 1.1108 data_time: 0.0080 memory: 7583 grad_norm: 14.9785 loss: 1.9452 2023/09/06 02:42:04 - mmengine - INFO - Epoch(train) [5][2440/2478] base_lr: 6.6029e-06 lr: 1.3206e-05 eta: 3:50:11 time: 1.1093 data_time: 0.0079 memory: 7583 grad_norm: 15.4671 loss: 1.7566 2023/09/06 02:42:26 - mmengine - INFO - Epoch(train) [5][2460/2478] base_lr: 6.5910e-06 lr: 1.3182e-05 eta: 3:49:49 time: 1.1103 data_time: 0.0084 memory: 7583 grad_norm: 14.6097 loss: 1.8187 2023/09/06 02:42:46 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 02:42:46 - mmengine - INFO - Epoch(train) [5][2478/2478] base_lr: 6.5802e-06 lr: 1.3160e-05 eta: 3:49:29 time: 1.1059 data_time: 0.0085 memory: 7583 grad_norm: 15.2247 loss: 1.8560 2023/09/06 02:42:46 - mmengine - INFO - Saving checkpoint at 5 epochs 2023/09/06 02:43:16 - mmengine - INFO - Epoch(val) [5][20/96] eta: 0:01:22 time: 1.0838 data_time: 0.0396 memory: 8884 2023/09/06 02:43:37 - mmengine - INFO - Epoch(val) [5][40/96] eta: 0:00:59 time: 1.0452 data_time: 0.0065 memory: 8884 2023/09/06 02:43:58 - mmengine - INFO - Epoch(val) [5][60/96] eta: 0:00:38 time: 1.0410 data_time: 0.0064 memory: 8884 2023/09/06 02:44:19 - mmengine - INFO - Epoch(val) [5][80/96] eta: 0:00:16 time: 1.0506 data_time: 0.0067 memory: 8884 2023/09/06 02:44:36 - mmengine - INFO - Epoch(val) [5][96/96] VQA/acc: 43.1911 data_time: 0.0134 time: 1.0514 2023/09/06 02:44:59 - mmengine - INFO - Epoch(train) [6][ 20/2478] base_lr: 6.5683e-06 lr: 1.3137e-05 eta: 3:49:07 time: 1.1257 data_time: 0.0234 memory: 8884 grad_norm: 13.8836 loss: 1.6068 2023/09/06 02:45:21 - mmengine - INFO - Epoch(train) [6][ 40/2478] base_lr: 6.5563e-06 lr: 1.3113e-05 eta: 3:48:45 time: 1.1121 data_time: 0.0075 memory: 7583 grad_norm: 13.9389 loss: 1.2958 2023/09/06 02:45:43 - mmengine - INFO - Epoch(train) [6][ 60/2478] base_lr: 6.5444e-06 lr: 1.3089e-05 eta: 3:48:23 time: 1.1122 data_time: 0.0075 memory: 7583 grad_norm: 13.7801 loss: 1.5509 2023/09/06 02:46:05 - mmengine - INFO - Epoch(train) [6][ 80/2478] base_lr: 6.5324e-06 lr: 1.3065e-05 eta: 3:48:00 time: 1.1120 data_time: 0.0082 memory: 7583 grad_norm: 14.3593 loss: 1.6201 2023/09/06 02:46:28 - mmengine - INFO - Epoch(train) [6][ 100/2478] base_lr: 6.5204e-06 lr: 1.3041e-05 eta: 3:47:38 time: 1.1084 data_time: 0.0077 memory: 7583 grad_norm: 14.7312 loss: 1.6399 2023/09/06 02:46:50 - mmengine - INFO - Epoch(train) [6][ 120/2478] base_lr: 6.5084e-06 lr: 1.3017e-05 eta: 3:47:16 time: 1.1121 data_time: 0.0077 memory: 7583 grad_norm: 14.6102 loss: 1.6050 2023/09/06 02:47:12 - mmengine - INFO - Epoch(train) [6][ 140/2478] base_lr: 6.4964e-06 lr: 1.2993e-05 eta: 3:46:54 time: 1.1109 data_time: 0.0077 memory: 7583 grad_norm: 14.5854 loss: 1.4331 2023/09/06 02:47:34 - mmengine - INFO - Epoch(train) [6][ 160/2478] base_lr: 6.4844e-06 lr: 1.2969e-05 eta: 3:46:31 time: 1.1138 data_time: 0.0077 memory: 7583 grad_norm: 14.7199 loss: 1.4867 2023/09/06 02:47:57 - mmengine - INFO - Epoch(train) [6][ 180/2478] base_lr: 6.4724e-06 lr: 1.2945e-05 eta: 3:46:09 time: 1.1094 data_time: 0.0076 memory: 7583 grad_norm: 14.3116 loss: 1.6822 2023/09/06 02:48:19 - mmengine - INFO - Epoch(train) [6][ 200/2478] base_lr: 6.4604e-06 lr: 1.2921e-05 eta: 3:45:47 time: 1.1085 data_time: 0.0078 memory: 7583 grad_norm: 14.5454 loss: 1.5070 2023/09/06 02:48:41 - mmengine - INFO - Epoch(train) [6][ 220/2478] base_lr: 6.4484e-06 lr: 1.2897e-05 eta: 3:45:25 time: 1.1100 data_time: 0.0078 memory: 7583 grad_norm: 14.5903 loss: 1.6089 2023/09/06 02:49:03 - mmengine - INFO - Epoch(train) [6][ 240/2478] base_lr: 6.4363e-06 lr: 1.2873e-05 eta: 3:45:02 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 14.9466 loss: 1.6065 2023/09/06 02:49:25 - mmengine - INFO - Epoch(train) [6][ 260/2478] base_lr: 6.4243e-06 lr: 1.2849e-05 eta: 3:44:40 time: 1.1141 data_time: 0.0078 memory: 7583 grad_norm: 15.1476 loss: 1.3847 2023/09/06 02:49:48 - mmengine - INFO - Epoch(train) [6][ 280/2478] base_lr: 6.4122e-06 lr: 1.2824e-05 eta: 3:44:18 time: 1.1120 data_time: 0.0078 memory: 7583 grad_norm: 14.8440 loss: 1.1338 2023/09/06 02:50:10 - mmengine - INFO - Epoch(train) [6][ 300/2478] base_lr: 6.4001e-06 lr: 1.2800e-05 eta: 3:43:56 time: 1.1124 data_time: 0.0078 memory: 7583 grad_norm: 15.0265 loss: 1.5980 2023/09/06 02:50:32 - mmengine - INFO - Epoch(train) [6][ 320/2478] base_lr: 6.3880e-06 lr: 1.2776e-05 eta: 3:43:34 time: 1.1115 data_time: 0.0077 memory: 7583 grad_norm: 15.1915 loss: 1.6172 2023/09/06 02:50:54 - mmengine - INFO - Epoch(train) [6][ 340/2478] base_lr: 6.3760e-06 lr: 1.2752e-05 eta: 3:43:11 time: 1.1110 data_time: 0.0077 memory: 7583 grad_norm: 15.2477 loss: 1.4117 2023/09/06 02:51:17 - mmengine - INFO - Epoch(train) [6][ 360/2478] base_lr: 6.3639e-06 lr: 1.2728e-05 eta: 3:42:49 time: 1.1116 data_time: 0.0076 memory: 7583 grad_norm: 15.6258 loss: 1.5101 2023/09/06 02:51:39 - mmengine - INFO - Epoch(train) [6][ 380/2478] base_lr: 6.3518e-06 lr: 1.2704e-05 eta: 3:42:27 time: 1.1149 data_time: 0.0078 memory: 7583 grad_norm: 15.5372 loss: 1.6130 2023/09/06 02:52:01 - mmengine - INFO - Epoch(train) [6][ 400/2478] base_lr: 6.3396e-06 lr: 1.2679e-05 eta: 3:42:05 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 15.1702 loss: 1.6333 2023/09/06 02:52:23 - mmengine - INFO - Epoch(train) [6][ 420/2478] base_lr: 6.3275e-06 lr: 1.2655e-05 eta: 3:41:43 time: 1.1149 data_time: 0.0080 memory: 7583 grad_norm: 14.7275 loss: 1.3218 2023/09/06 02:52:46 - mmengine - INFO - Epoch(train) [6][ 440/2478] base_lr: 6.3154e-06 lr: 1.2631e-05 eta: 3:41:20 time: 1.1110 data_time: 0.0083 memory: 7583 grad_norm: 15.1119 loss: 1.6190 2023/09/06 02:53:08 - mmengine - INFO - Epoch(train) [6][ 460/2478] base_lr: 6.3032e-06 lr: 1.2606e-05 eta: 3:40:58 time: 1.1106 data_time: 0.0081 memory: 7583 grad_norm: 14.4031 loss: 1.1567 2023/09/06 02:53:30 - mmengine - INFO - Epoch(train) [6][ 480/2478] base_lr: 6.2911e-06 lr: 1.2582e-05 eta: 3:40:36 time: 1.1188 data_time: 0.0079 memory: 7583 grad_norm: 15.0234 loss: 1.2648 2023/09/06 02:53:52 - mmengine - INFO - Epoch(train) [6][ 500/2478] base_lr: 6.2789e-06 lr: 1.2558e-05 eta: 3:40:14 time: 1.1134 data_time: 0.0077 memory: 7583 grad_norm: 14.9899 loss: 1.3840 2023/09/06 02:54:15 - mmengine - INFO - Epoch(train) [6][ 520/2478] base_lr: 6.2668e-06 lr: 1.2534e-05 eta: 3:39:52 time: 1.1097 data_time: 0.0079 memory: 7583 grad_norm: 14.4685 loss: 1.4181 2023/09/06 02:54:37 - mmengine - INFO - Epoch(train) [6][ 540/2478] base_lr: 6.2546e-06 lr: 1.2509e-05 eta: 3:39:29 time: 1.1078 data_time: 0.0079 memory: 7583 grad_norm: inf loss: 1.3201 2023/09/06 02:54:59 - mmengine - INFO - Epoch(train) [6][ 560/2478] base_lr: 6.2424e-06 lr: 1.2485e-05 eta: 3:39:07 time: 1.1101 data_time: 0.0079 memory: 7583 grad_norm: 14.6020 loss: 1.2135 2023/09/06 02:55:21 - mmengine - INFO - Epoch(train) [6][ 580/2478] base_lr: 6.2303e-06 lr: 1.2461e-05 eta: 3:38:45 time: 1.1139 data_time: 0.0080 memory: 7583 grad_norm: 14.8508 loss: 1.6232 2023/09/06 02:55:44 - mmengine - INFO - Epoch(train) [6][ 600/2478] base_lr: 6.2181e-06 lr: 1.2436e-05 eta: 3:38:23 time: 1.1159 data_time: 0.0078 memory: 7583 grad_norm: 15.1811 loss: 1.4866 2023/09/06 02:55:55 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 02:56:06 - mmengine - INFO - Epoch(train) [6][ 620/2478] base_lr: 6.2059e-06 lr: 1.2412e-05 eta: 3:38:01 time: 1.1131 data_time: 0.0079 memory: 7583 grad_norm: 15.4971 loss: 1.6647 2023/09/06 02:56:28 - mmengine - INFO - Epoch(train) [6][ 640/2478] base_lr: 6.1937e-06 lr: 1.2387e-05 eta: 3:37:38 time: 1.1094 data_time: 0.0077 memory: 7583 grad_norm: 15.1000 loss: 1.7619 2023/09/06 02:56:50 - mmengine - INFO - Epoch(train) [6][ 660/2478] base_lr: 6.1814e-06 lr: 1.2363e-05 eta: 3:37:16 time: 1.1118 data_time: 0.0079 memory: 7583 grad_norm: 15.0613 loss: 1.6924 2023/09/06 02:57:12 - mmengine - INFO - Epoch(train) [6][ 680/2478] base_lr: 6.1692e-06 lr: 1.2338e-05 eta: 3:36:54 time: 1.1078 data_time: 0.0078 memory: 7583 grad_norm: 15.1430 loss: 1.3974 2023/09/06 02:57:35 - mmengine - INFO - Epoch(train) [6][ 700/2478] base_lr: 6.1570e-06 lr: 1.2314e-05 eta: 3:36:31 time: 1.1083 data_time: 0.0078 memory: 7583 grad_norm: 15.8915 loss: 1.4086 2023/09/06 02:57:57 - mmengine - INFO - Epoch(train) [6][ 720/2478] base_lr: 6.1447e-06 lr: 1.2289e-05 eta: 3:36:09 time: 1.1124 data_time: 0.0078 memory: 7583 grad_norm: 15.2231 loss: 1.7694 2023/09/06 02:58:19 - mmengine - INFO - Epoch(train) [6][ 740/2478] base_lr: 6.1325e-06 lr: 1.2265e-05 eta: 3:35:47 time: 1.1110 data_time: 0.0078 memory: 7583 grad_norm: 15.0105 loss: 1.4201 2023/09/06 02:58:41 - mmengine - INFO - Epoch(train) [6][ 760/2478] base_lr: 6.1203e-06 lr: 1.2241e-05 eta: 3:35:25 time: 1.1103 data_time: 0.0081 memory: 7583 grad_norm: 15.6825 loss: 1.3483 2023/09/06 02:59:04 - mmengine - INFO - Epoch(train) [6][ 780/2478] base_lr: 6.1080e-06 lr: 1.2216e-05 eta: 3:35:03 time: 1.1100 data_time: 0.0084 memory: 7583 grad_norm: 15.3506 loss: 1.5416 2023/09/06 02:59:26 - mmengine - INFO - Epoch(train) [6][ 800/2478] base_lr: 6.0957e-06 lr: 1.2191e-05 eta: 3:34:40 time: 1.1126 data_time: 0.0082 memory: 7583 grad_norm: 14.8451 loss: 1.6166 2023/09/06 02:59:48 - mmengine - INFO - Epoch(train) [6][ 820/2478] base_lr: 6.0835e-06 lr: 1.2167e-05 eta: 3:34:18 time: 1.1132 data_time: 0.0084 memory: 7583 grad_norm: 15.0571 loss: 1.5193 2023/09/06 03:00:10 - mmengine - INFO - Epoch(train) [6][ 840/2478] base_lr: 6.0712e-06 lr: 1.2142e-05 eta: 3:33:56 time: 1.1095 data_time: 0.0083 memory: 7583 grad_norm: 15.2791 loss: 1.7209 2023/09/06 03:00:32 - mmengine - INFO - Epoch(train) [6][ 860/2478] base_lr: 6.0589e-06 lr: 1.2118e-05 eta: 3:33:34 time: 1.1109 data_time: 0.0086 memory: 7583 grad_norm: 15.8627 loss: 1.5592 2023/09/06 03:00:55 - mmengine - INFO - Epoch(train) [6][ 880/2478] base_lr: 6.0466e-06 lr: 1.2093e-05 eta: 3:33:11 time: 1.1103 data_time: 0.0086 memory: 7583 grad_norm: 15.2238 loss: 1.4205 2023/09/06 03:01:17 - mmengine - INFO - Epoch(train) [6][ 900/2478] base_lr: 6.0343e-06 lr: 1.2069e-05 eta: 3:32:49 time: 1.1109 data_time: 0.0079 memory: 7583 grad_norm: 15.1595 loss: 1.5123 2023/09/06 03:01:39 - mmengine - INFO - Epoch(train) [6][ 920/2478] base_lr: 6.0220e-06 lr: 1.2044e-05 eta: 3:32:27 time: 1.1074 data_time: 0.0080 memory: 7583 grad_norm: 15.4035 loss: 1.2826 2023/09/06 03:02:01 - mmengine - INFO - Epoch(train) [6][ 940/2478] base_lr: 6.0097e-06 lr: 1.2019e-05 eta: 3:32:05 time: 1.1081 data_time: 0.0080 memory: 7583 grad_norm: 14.9982 loss: 1.4702 2023/09/06 03:02:23 - mmengine - INFO - Epoch(train) [6][ 960/2478] base_lr: 5.9974e-06 lr: 1.1995e-05 eta: 3:31:42 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 15.1354 loss: 1.4859 2023/09/06 03:02:46 - mmengine - INFO - Epoch(train) [6][ 980/2478] base_lr: 5.9851e-06 lr: 1.1970e-05 eta: 3:31:20 time: 1.1105 data_time: 0.0081 memory: 7583 grad_norm: 15.2623 loss: 1.4945 2023/09/06 03:03:08 - mmengine - INFO - Epoch(train) [6][1000/2478] base_lr: 5.9727e-06 lr: 1.1945e-05 eta: 3:30:58 time: 1.1129 data_time: 0.0080 memory: 7583 grad_norm: 15.2382 loss: 1.4693 2023/09/06 03:03:30 - mmengine - INFO - Epoch(train) [6][1020/2478] base_lr: 5.9604e-06 lr: 1.1921e-05 eta: 3:30:36 time: 1.1109 data_time: 0.0079 memory: 7583 grad_norm: 14.9869 loss: 1.4339 2023/09/06 03:03:52 - mmengine - INFO - Epoch(train) [6][1040/2478] base_lr: 5.9481e-06 lr: 1.1896e-05 eta: 3:30:13 time: 1.1062 data_time: 0.0079 memory: 7583 grad_norm: 15.1331 loss: 1.4288 2023/09/06 03:04:14 - mmengine - INFO - Epoch(train) [6][1060/2478] base_lr: 5.9357e-06 lr: 1.1871e-05 eta: 3:29:51 time: 1.1087 data_time: 0.0085 memory: 7583 grad_norm: 15.2738 loss: 1.4408 2023/09/06 03:04:37 - mmengine - INFO - Epoch(train) [6][1080/2478] base_lr: 5.9234e-06 lr: 1.1847e-05 eta: 3:29:29 time: 1.1116 data_time: 0.0077 memory: 7583 grad_norm: 15.2548 loss: 1.2805 2023/09/06 03:04:59 - mmengine - INFO - Epoch(train) [6][1100/2478] base_lr: 5.9110e-06 lr: 1.1822e-05 eta: 3:29:07 time: 1.1090 data_time: 0.0078 memory: 7583 grad_norm: 15.5834 loss: 1.4724 2023/09/06 03:05:21 - mmengine - INFO - Epoch(train) [6][1120/2478] base_lr: 5.8986e-06 lr: 1.1797e-05 eta: 3:28:44 time: 1.1097 data_time: 0.0078 memory: 7583 grad_norm: 16.4136 loss: 1.4951 2023/09/06 03:05:43 - mmengine - INFO - Epoch(train) [6][1140/2478] base_lr: 5.8863e-06 lr: 1.1773e-05 eta: 3:28:22 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 14.9358 loss: 1.5737 2023/09/06 03:06:05 - mmengine - INFO - Epoch(train) [6][1160/2478] base_lr: 5.8739e-06 lr: 1.1748e-05 eta: 3:28:00 time: 1.1134 data_time: 0.0078 memory: 7583 grad_norm: 15.5474 loss: 1.3744 2023/09/06 03:06:28 - mmengine - INFO - Epoch(train) [6][1180/2478] base_lr: 5.8615e-06 lr: 1.1723e-05 eta: 3:27:38 time: 1.1095 data_time: 0.0078 memory: 7583 grad_norm: 15.5075 loss: 1.8064 2023/09/06 03:06:50 - mmengine - INFO - Epoch(train) [6][1200/2478] base_lr: 5.8491e-06 lr: 1.1698e-05 eta: 3:27:15 time: 1.1092 data_time: 0.0081 memory: 7583 grad_norm: 16.1494 loss: 1.3661 2023/09/06 03:07:12 - mmengine - INFO - Epoch(train) [6][1220/2478] base_lr: 5.8367e-06 lr: 1.1673e-05 eta: 3:26:53 time: 1.1078 data_time: 0.0084 memory: 7583 grad_norm: 15.2036 loss: 1.5537 2023/09/06 03:07:34 - mmengine - INFO - Epoch(train) [6][1240/2478] base_lr: 5.8244e-06 lr: 1.1649e-05 eta: 3:26:31 time: 1.1090 data_time: 0.0082 memory: 7583 grad_norm: 15.5789 loss: 1.3638 2023/09/06 03:07:56 - mmengine - INFO - Epoch(train) [6][1260/2478] base_lr: 5.8120e-06 lr: 1.1624e-05 eta: 3:26:09 time: 1.1064 data_time: 0.0081 memory: 7583 grad_norm: 15.1498 loss: 1.2689 2023/09/06 03:08:18 - mmengine - INFO - Epoch(train) [6][1280/2478] base_lr: 5.7995e-06 lr: 1.1599e-05 eta: 3:25:46 time: 1.1091 data_time: 0.0082 memory: 7583 grad_norm: 15.6252 loss: 1.7100 2023/09/06 03:08:41 - mmengine - INFO - Epoch(train) [6][1300/2478] base_lr: 5.7871e-06 lr: 1.1574e-05 eta: 3:25:24 time: 1.1099 data_time: 0.0083 memory: 7583 grad_norm: 15.0332 loss: 1.4819 2023/09/06 03:09:03 - mmengine - INFO - Epoch(train) [6][1320/2478] base_lr: 5.7747e-06 lr: 1.1549e-05 eta: 3:25:02 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 15.6565 loss: 1.7485 2023/09/06 03:09:25 - mmengine - INFO - Epoch(train) [6][1340/2478] base_lr: 5.7623e-06 lr: 1.1525e-05 eta: 3:24:40 time: 1.1114 data_time: 0.0077 memory: 7583 grad_norm: 15.2424 loss: 1.4858 2023/09/06 03:09:47 - mmengine - INFO - Epoch(train) [6][1360/2478] base_lr: 5.7499e-06 lr: 1.1500e-05 eta: 3:24:17 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 14.9390 loss: 1.6787 2023/09/06 03:10:10 - mmengine - INFO - Epoch(train) [6][1380/2478] base_lr: 5.7375e-06 lr: 1.1475e-05 eta: 3:23:55 time: 1.1081 data_time: 0.0082 memory: 7583 grad_norm: 15.6433 loss: 1.6343 2023/09/06 03:10:32 - mmengine - INFO - Epoch(train) [6][1400/2478] base_lr: 5.7250e-06 lr: 1.1450e-05 eta: 3:23:33 time: 1.1090 data_time: 0.0081 memory: 7583 grad_norm: 15.1873 loss: 1.4247 2023/09/06 03:10:54 - mmengine - INFO - Epoch(train) [6][1420/2478] base_lr: 5.7126e-06 lr: 1.1425e-05 eta: 3:23:11 time: 1.1110 data_time: 0.0081 memory: 7583 grad_norm: 15.4274 loss: 1.6124 2023/09/06 03:11:16 - mmengine - INFO - Epoch(train) [6][1440/2478] base_lr: 5.7001e-06 lr: 1.1400e-05 eta: 3:22:48 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 15.7403 loss: 1.7339 2023/09/06 03:11:38 - mmengine - INFO - Epoch(train) [6][1460/2478] base_lr: 5.6877e-06 lr: 1.1375e-05 eta: 3:22:26 time: 1.1122 data_time: 0.0078 memory: 7583 grad_norm: 16.0246 loss: 1.5740 2023/09/06 03:12:01 - mmengine - INFO - Epoch(train) [6][1480/2478] base_lr: 5.6753e-06 lr: 1.1351e-05 eta: 3:22:04 time: 1.1118 data_time: 0.0081 memory: 7583 grad_norm: 16.0299 loss: 1.7475 2023/09/06 03:12:23 - mmengine - INFO - Epoch(train) [6][1500/2478] base_lr: 5.6628e-06 lr: 1.1326e-05 eta: 3:21:42 time: 1.1108 data_time: 0.0084 memory: 7583 grad_norm: 15.3581 loss: 1.4980 2023/09/06 03:12:45 - mmengine - INFO - Epoch(train) [6][1520/2478] base_lr: 5.6503e-06 lr: 1.1301e-05 eta: 3:21:19 time: 1.1082 data_time: 0.0085 memory: 7583 grad_norm: 15.5851 loss: 1.7910 2023/09/06 03:13:07 - mmengine - INFO - Epoch(train) [6][1540/2478] base_lr: 5.6379e-06 lr: 1.1276e-05 eta: 3:20:57 time: 1.1093 data_time: 0.0084 memory: 7583 grad_norm: 15.2832 loss: 1.5432 2023/09/06 03:13:29 - mmengine - INFO - Epoch(train) [6][1560/2478] base_lr: 5.6254e-06 lr: 1.1251e-05 eta: 3:20:35 time: 1.1119 data_time: 0.0081 memory: 7583 grad_norm: 15.0098 loss: 1.4339 2023/09/06 03:13:52 - mmengine - INFO - Epoch(train) [6][1580/2478] base_lr: 5.6130e-06 lr: 1.1226e-05 eta: 3:20:13 time: 1.1126 data_time: 0.0082 memory: 7583 grad_norm: 15.5291 loss: 1.3348 2023/09/06 03:14:14 - mmengine - INFO - Epoch(train) [6][1600/2478] base_lr: 5.6005e-06 lr: 1.1201e-05 eta: 3:19:50 time: 1.1107 data_time: 0.0083 memory: 7583 grad_norm: 15.5650 loss: 1.3789 2023/09/06 03:14:25 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 03:14:36 - mmengine - INFO - Epoch(train) [6][1620/2478] base_lr: 5.5880e-06 lr: 1.1176e-05 eta: 3:19:28 time: 1.1084 data_time: 0.0081 memory: 7583 grad_norm: 15.5039 loss: 1.3684 2023/09/06 03:14:58 - mmengine - INFO - Epoch(train) [6][1640/2478] base_lr: 5.5755e-06 lr: 1.1151e-05 eta: 3:19:06 time: 1.1140 data_time: 0.0081 memory: 7583 grad_norm: 15.8255 loss: 1.5693 2023/09/06 03:15:20 - mmengine - INFO - Epoch(train) [6][1660/2478] base_lr: 5.5630e-06 lr: 1.1126e-05 eta: 3:18:44 time: 1.1079 data_time: 0.0079 memory: 7583 grad_norm: 15.4183 loss: 1.3257 2023/09/06 03:15:43 - mmengine - INFO - Epoch(train) [6][1680/2478] base_lr: 5.5506e-06 lr: 1.1101e-05 eta: 3:18:21 time: 1.1083 data_time: 0.0079 memory: 7583 grad_norm: 15.2303 loss: 1.6915 2023/09/06 03:16:05 - mmengine - INFO - Epoch(train) [6][1700/2478] base_lr: 5.5381e-06 lr: 1.1076e-05 eta: 3:17:59 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 15.3784 loss: 1.6752 2023/09/06 03:16:27 - mmengine - INFO - Epoch(train) [6][1720/2478] base_lr: 5.5256e-06 lr: 1.1051e-05 eta: 3:17:37 time: 1.1107 data_time: 0.0078 memory: 7583 grad_norm: 15.5455 loss: 1.2963 2023/09/06 03:16:49 - mmengine - INFO - Epoch(train) [6][1740/2478] base_lr: 5.5131e-06 lr: 1.1026e-05 eta: 3:17:15 time: 1.1108 data_time: 0.0078 memory: 7583 grad_norm: 15.3311 loss: 1.6587 2023/09/06 03:17:12 - mmengine - INFO - Epoch(train) [6][1760/2478] base_lr: 5.5006e-06 lr: 1.1001e-05 eta: 3:16:52 time: 1.1116 data_time: 0.0079 memory: 7583 grad_norm: 15.2859 loss: 1.4216 2023/09/06 03:17:34 - mmengine - INFO - Epoch(train) [6][1780/2478] base_lr: 5.4881e-06 lr: 1.0976e-05 eta: 3:16:30 time: 1.1152 data_time: 0.0080 memory: 7583 grad_norm: 15.6466 loss: 1.6364 2023/09/06 03:17:56 - mmengine - INFO - Epoch(train) [6][1800/2478] base_lr: 5.4756e-06 lr: 1.0951e-05 eta: 3:16:08 time: 1.1102 data_time: 0.0077 memory: 7583 grad_norm: 15.2420 loss: 1.5212 2023/09/06 03:18:18 - mmengine - INFO - Epoch(train) [6][1820/2478] base_lr: 5.4631e-06 lr: 1.0926e-05 eta: 3:15:46 time: 1.1125 data_time: 0.0080 memory: 7583 grad_norm: 15.1732 loss: 1.5997 2023/09/06 03:18:40 - mmengine - INFO - Epoch(train) [6][1840/2478] base_lr: 5.4506e-06 lr: 1.0901e-05 eta: 3:15:24 time: 1.1107 data_time: 0.0080 memory: 7583 grad_norm: 15.8672 loss: 1.6010 2023/09/06 03:19:03 - mmengine - INFO - Epoch(train) [6][1860/2478] base_lr: 5.4381e-06 lr: 1.0876e-05 eta: 3:15:01 time: 1.1105 data_time: 0.0079 memory: 7583 grad_norm: 15.0619 loss: 1.3824 2023/09/06 03:19:25 - mmengine - INFO - Epoch(train) [6][1880/2478] base_lr: 5.4255e-06 lr: 1.0851e-05 eta: 3:14:39 time: 1.1102 data_time: 0.0077 memory: 7583 grad_norm: 15.3503 loss: 1.5242 2023/09/06 03:19:47 - mmengine - INFO - Epoch(train) [6][1900/2478] base_lr: 5.4130e-06 lr: 1.0826e-05 eta: 3:14:17 time: 1.1084 data_time: 0.0079 memory: 7583 grad_norm: 15.1367 loss: 1.4643 2023/09/06 03:20:09 - mmengine - INFO - Epoch(train) [6][1920/2478] base_lr: 5.4005e-06 lr: 1.0801e-05 eta: 3:13:55 time: 1.1122 data_time: 0.0081 memory: 7583 grad_norm: 15.8242 loss: 1.3602 2023/09/06 03:20:32 - mmengine - INFO - Epoch(train) [6][1940/2478] base_lr: 5.3880e-06 lr: 1.0776e-05 eta: 3:13:32 time: 1.1120 data_time: 0.0082 memory: 7583 grad_norm: 15.7663 loss: 1.4787 2023/09/06 03:20:54 - mmengine - INFO - Epoch(train) [6][1960/2478] base_lr: 5.3755e-06 lr: 1.0751e-05 eta: 3:13:10 time: 1.1116 data_time: 0.0081 memory: 7583 grad_norm: 15.8662 loss: 1.7517 2023/09/06 03:21:16 - mmengine - INFO - Epoch(train) [6][1980/2478] base_lr: 5.3629e-06 lr: 1.0726e-05 eta: 3:12:48 time: 1.1132 data_time: 0.0079 memory: 7583 grad_norm: 15.4836 loss: 1.4724 2023/09/06 03:21:38 - mmengine - INFO - Epoch(train) [6][2000/2478] base_lr: 5.3504e-06 lr: 1.0701e-05 eta: 3:12:26 time: 1.1094 data_time: 0.0078 memory: 7583 grad_norm: 15.8950 loss: 1.6147 2023/09/06 03:22:00 - mmengine - INFO - Epoch(train) [6][2020/2478] base_lr: 5.3379e-06 lr: 1.0676e-05 eta: 3:12:04 time: 1.1085 data_time: 0.0078 memory: 7583 grad_norm: 15.4289 loss: 1.7706 2023/09/06 03:22:23 - mmengine - INFO - Epoch(train) [6][2040/2478] base_lr: 5.3254e-06 lr: 1.0651e-05 eta: 3:11:41 time: 1.1119 data_time: 0.0081 memory: 7583 grad_norm: 15.6031 loss: 1.8349 2023/09/06 03:22:45 - mmengine - INFO - Epoch(train) [6][2060/2478] base_lr: 5.3128e-06 lr: 1.0626e-05 eta: 3:11:19 time: 1.1129 data_time: 0.0083 memory: 7583 grad_norm: 15.5404 loss: 1.7029 2023/09/06 03:23:07 - mmengine - INFO - Epoch(train) [6][2080/2478] base_lr: 5.3003e-06 lr: 1.0601e-05 eta: 3:10:57 time: 1.1091 data_time: 0.0081 memory: 7583 grad_norm: 15.5046 loss: 1.3942 2023/09/06 03:23:29 - mmengine - INFO - Epoch(train) [6][2100/2478] base_lr: 5.2878e-06 lr: 1.0576e-05 eta: 3:10:35 time: 1.1111 data_time: 0.0081 memory: 7583 grad_norm: 15.4012 loss: 1.7464 2023/09/06 03:23:52 - mmengine - INFO - Epoch(train) [6][2120/2478] base_lr: 5.2752e-06 lr: 1.0550e-05 eta: 3:10:12 time: 1.1112 data_time: 0.0082 memory: 7583 grad_norm: 15.3845 loss: 1.4983 2023/09/06 03:24:14 - mmengine - INFO - Epoch(train) [6][2140/2478] base_lr: 5.2627e-06 lr: 1.0525e-05 eta: 3:09:50 time: 1.1116 data_time: 0.0081 memory: 7583 grad_norm: 15.3233 loss: 1.3927 2023/09/06 03:24:36 - mmengine - INFO - Epoch(train) [6][2160/2478] base_lr: 5.2501e-06 lr: 1.0500e-05 eta: 3:09:28 time: 1.1089 data_time: 0.0082 memory: 7583 grad_norm: 15.2700 loss: 1.3872 2023/09/06 03:24:58 - mmengine - INFO - Epoch(train) [6][2180/2478] base_lr: 5.2376e-06 lr: 1.0475e-05 eta: 3:09:06 time: 1.1090 data_time: 0.0082 memory: 7583 grad_norm: 15.6247 loss: 1.4882 2023/09/06 03:25:20 - mmengine - INFO - Epoch(train) [6][2200/2478] base_lr: 5.2251e-06 lr: 1.0450e-05 eta: 3:08:43 time: 1.1101 data_time: 0.0080 memory: 7583 grad_norm: 15.8891 loss: 1.8144 2023/09/06 03:25:43 - mmengine - INFO - Epoch(train) [6][2220/2478] base_lr: 5.2125e-06 lr: 1.0425e-05 eta: 3:08:21 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 15.1474 loss: 1.3760 2023/09/06 03:26:05 - mmengine - INFO - Epoch(train) [6][2240/2478] base_lr: 5.2000e-06 lr: 1.0400e-05 eta: 3:07:59 time: 1.1119 data_time: 0.0082 memory: 7583 grad_norm: 15.6712 loss: 1.7956 2023/09/06 03:26:27 - mmengine - INFO - Epoch(train) [6][2260/2478] base_lr: 5.1874e-06 lr: 1.0375e-05 eta: 3:07:37 time: 1.1102 data_time: 0.0085 memory: 7583 grad_norm: 15.1438 loss: 1.4594 2023/09/06 03:26:49 - mmengine - INFO - Epoch(train) [6][2280/2478] base_lr: 5.1749e-06 lr: 1.0350e-05 eta: 3:07:15 time: 1.1121 data_time: 0.0082 memory: 7583 grad_norm: 15.4735 loss: 1.2802 2023/09/06 03:27:11 - mmengine - INFO - Epoch(train) [6][2300/2478] base_lr: 5.1623e-06 lr: 1.0325e-05 eta: 3:06:52 time: 1.1076 data_time: 0.0082 memory: 7583 grad_norm: 15.8249 loss: 1.5121 2023/09/06 03:27:34 - mmengine - INFO - Epoch(train) [6][2320/2478] base_lr: 5.1498e-06 lr: 1.0300e-05 eta: 3:06:30 time: 1.1097 data_time: 0.0082 memory: 7583 grad_norm: inf loss: 1.3491 2023/09/06 03:27:56 - mmengine - INFO - Epoch(train) [6][2340/2478] base_lr: 5.1372e-06 lr: 1.0274e-05 eta: 3:06:08 time: 1.1110 data_time: 0.0080 memory: 7583 grad_norm: 15.1972 loss: 1.1511 2023/09/06 03:28:18 - mmengine - INFO - Epoch(train) [6][2360/2478] base_lr: 5.1247e-06 lr: 1.0249e-05 eta: 3:05:46 time: 1.1095 data_time: 0.0081 memory: 7583 grad_norm: 15.6378 loss: 1.6034 2023/09/06 03:28:40 - mmengine - INFO - Epoch(train) [6][2380/2478] base_lr: 5.1121e-06 lr: 1.0224e-05 eta: 3:05:23 time: 1.1111 data_time: 0.0080 memory: 7583 grad_norm: 15.8544 loss: 1.6444 2023/09/06 03:29:02 - mmengine - INFO - Epoch(train) [6][2400/2478] base_lr: 5.0996e-06 lr: 1.0199e-05 eta: 3:05:01 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 15.8690 loss: 1.5071 2023/09/06 03:29:25 - mmengine - INFO - Epoch(train) [6][2420/2478] base_lr: 5.0870e-06 lr: 1.0174e-05 eta: 3:04:39 time: 1.1065 data_time: 0.0080 memory: 7583 grad_norm: 15.6379 loss: 1.3938 2023/09/06 03:29:47 - mmengine - INFO - Epoch(train) [6][2440/2478] base_lr: 5.0745e-06 lr: 1.0149e-05 eta: 3:04:16 time: 1.1066 data_time: 0.0083 memory: 7583 grad_norm: 15.3078 loss: 1.5451 2023/09/06 03:30:09 - mmengine - INFO - Epoch(train) [6][2460/2478] base_lr: 5.0619e-06 lr: 1.0124e-05 eta: 3:03:54 time: 1.1099 data_time: 0.0082 memory: 7583 grad_norm: 15.5287 loss: 1.5228 2023/09/06 03:30:29 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 03:30:29 - mmengine - INFO - Epoch(train) [6][2478/2478] base_lr: 5.0506e-06 lr: 1.0101e-05 eta: 3:03:34 time: 1.1065 data_time: 0.0083 memory: 7583 grad_norm: 15.5617 loss: 2.0296 2023/09/06 03:30:29 - mmengine - INFO - Saving checkpoint at 6 epochs 2023/09/06 03:30:59 - mmengine - INFO - Epoch(val) [6][20/96] eta: 0:01:22 time: 1.0814 data_time: 0.0378 memory: 8884 2023/09/06 03:31:20 - mmengine - INFO - Epoch(val) [6][40/96] eta: 0:00:59 time: 1.0461 data_time: 0.0063 memory: 8884 2023/09/06 03:31:41 - mmengine - INFO - Epoch(val) [6][60/96] eta: 0:00:38 time: 1.0442 data_time: 0.0063 memory: 8884 2023/09/06 03:32:02 - mmengine - INFO - Epoch(val) [6][80/96] eta: 0:00:16 time: 1.0492 data_time: 0.0065 memory: 8884 2023/09/06 03:32:19 - mmengine - INFO - Epoch(val) [6][96/96] VQA/acc: 42.3277 data_time: 0.0129 time: 1.0525 2023/09/06 03:32:42 - mmengine - INFO - Epoch(train) [7][ 20/2478] base_lr: 5.0381e-06 lr: 1.0076e-05 eta: 3:03:12 time: 1.1289 data_time: 0.0242 memory: 8884 grad_norm: 13.5061 loss: 1.1790 2023/09/06 03:33:04 - mmengine - INFO - Epoch(train) [7][ 40/2478] base_lr: 5.0255e-06 lr: 1.0051e-05 eta: 3:02:50 time: 1.1112 data_time: 0.0081 memory: 7583 grad_norm: 14.7437 loss: 1.3544 2023/09/06 03:33:26 - mmengine - INFO - Epoch(train) [7][ 60/2478] base_lr: 5.0130e-06 lr: 1.0026e-05 eta: 3:02:28 time: 1.1090 data_time: 0.0081 memory: 7583 grad_norm: 14.5526 loss: 1.1192 2023/09/06 03:33:49 - mmengine - INFO - Epoch(train) [7][ 80/2478] base_lr: 5.0004e-06 lr: 1.0001e-05 eta: 3:02:05 time: 1.1118 data_time: 0.0078 memory: 7583 grad_norm: 14.9624 loss: 1.3861 2023/09/06 03:34:11 - mmengine - INFO - Epoch(train) [7][ 100/2478] base_lr: 4.9879e-06 lr: 9.9757e-06 eta: 3:01:43 time: 1.1130 data_time: 0.0080 memory: 7583 grad_norm: 14.5893 loss: 1.0181 2023/09/06 03:34:33 - mmengine - INFO - Epoch(train) [7][ 120/2478] base_lr: 4.9753e-06 lr: 9.9506e-06 eta: 3:01:21 time: 1.1088 data_time: 0.0080 memory: 7583 grad_norm: 15.0185 loss: 0.9643 2023/09/06 03:34:46 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 03:34:55 - mmengine - INFO - Epoch(train) [7][ 140/2478] base_lr: 4.9628e-06 lr: 9.9255e-06 eta: 3:00:59 time: 1.1120 data_time: 0.0080 memory: 7583 grad_norm: 14.2170 loss: 1.2631 2023/09/06 03:35:17 - mmengine - INFO - Epoch(train) [7][ 160/2478] base_lr: 4.9502e-06 lr: 9.9005e-06 eta: 3:00:37 time: 1.1093 data_time: 0.0080 memory: 7583 grad_norm: 14.4610 loss: 1.1351 2023/09/06 03:35:40 - mmengine - INFO - Epoch(train) [7][ 180/2478] base_lr: 4.9377e-06 lr: 9.8754e-06 eta: 3:00:14 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 14.8688 loss: 1.0766 2023/09/06 03:36:02 - mmengine - INFO - Epoch(train) [7][ 200/2478] base_lr: 4.9251e-06 lr: 9.8503e-06 eta: 2:59:52 time: 1.1091 data_time: 0.0084 memory: 7583 grad_norm: 14.1959 loss: 1.3684 2023/09/06 03:36:24 - mmengine - INFO - Epoch(train) [7][ 220/2478] base_lr: 4.9126e-06 lr: 9.8252e-06 eta: 2:59:30 time: 1.1119 data_time: 0.0082 memory: 7583 grad_norm: 14.7754 loss: 0.9101 2023/09/06 03:36:46 - mmengine - INFO - Epoch(train) [7][ 240/2478] base_lr: 4.9000e-06 lr: 9.8001e-06 eta: 2:59:08 time: 1.1084 data_time: 0.0082 memory: 7583 grad_norm: 14.2155 loss: 1.1982 2023/09/06 03:37:08 - mmengine - INFO - Epoch(train) [7][ 260/2478] base_lr: 4.8875e-06 lr: 9.7750e-06 eta: 2:58:45 time: 1.1093 data_time: 0.0082 memory: 7583 grad_norm: 14.3369 loss: 1.2382 2023/09/06 03:37:31 - mmengine - INFO - Epoch(train) [7][ 280/2478] base_lr: 4.8749e-06 lr: 9.7499e-06 eta: 2:58:23 time: 1.1088 data_time: 0.0082 memory: 7583 grad_norm: 15.0910 loss: 1.3494 2023/09/06 03:37:53 - mmengine - INFO - Epoch(train) [7][ 300/2478] base_lr: 4.8624e-06 lr: 9.7248e-06 eta: 2:58:01 time: 1.1086 data_time: 0.0081 memory: 7583 grad_norm: 15.5252 loss: 1.4004 2023/09/06 03:38:15 - mmengine - INFO - Epoch(train) [7][ 320/2478] base_lr: 4.8499e-06 lr: 9.6997e-06 eta: 2:57:39 time: 1.1120 data_time: 0.0081 memory: 7583 grad_norm: 15.0467 loss: 1.4869 2023/09/06 03:38:37 - mmengine - INFO - Epoch(train) [7][ 340/2478] base_lr: 4.8373e-06 lr: 9.6746e-06 eta: 2:57:16 time: 1.1104 data_time: 0.0082 memory: 7583 grad_norm: 14.4519 loss: 1.4969 2023/09/06 03:38:59 - mmengine - INFO - Epoch(train) [7][ 360/2478] base_lr: 4.8248e-06 lr: 9.6496e-06 eta: 2:56:54 time: 1.1123 data_time: 0.0082 memory: 7583 grad_norm: 14.8494 loss: 1.1105 2023/09/06 03:39:22 - mmengine - INFO - Epoch(train) [7][ 380/2478] base_lr: 4.8122e-06 lr: 9.6245e-06 eta: 2:56:32 time: 1.1139 data_time: 0.0080 memory: 7583 grad_norm: 15.1969 loss: 1.2373 2023/09/06 03:39:44 - mmengine - INFO - Epoch(train) [7][ 400/2478] base_lr: 4.7997e-06 lr: 9.5994e-06 eta: 2:56:10 time: 1.1122 data_time: 0.0079 memory: 7583 grad_norm: 14.7596 loss: 1.1422 2023/09/06 03:40:06 - mmengine - INFO - Epoch(train) [7][ 420/2478] base_lr: 4.7872e-06 lr: 9.5744e-06 eta: 2:55:47 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 14.6720 loss: 1.0352 2023/09/06 03:40:28 - mmengine - INFO - Epoch(train) [7][ 440/2478] base_lr: 4.7746e-06 lr: 9.5493e-06 eta: 2:55:25 time: 1.1124 data_time: 0.0084 memory: 7583 grad_norm: 15.0714 loss: 1.3444 2023/09/06 03:40:51 - mmengine - INFO - Epoch(train) [7][ 460/2478] base_lr: 4.7621e-06 lr: 9.5242e-06 eta: 2:55:03 time: 1.1131 data_time: 0.0082 memory: 7583 grad_norm: 15.0045 loss: 1.5319 2023/09/06 03:41:13 - mmengine - INFO - Epoch(train) [7][ 480/2478] base_lr: 4.7496e-06 lr: 9.4992e-06 eta: 2:54:41 time: 1.1123 data_time: 0.0082 memory: 7583 grad_norm: 14.9840 loss: 1.3649 2023/09/06 03:41:35 - mmengine - INFO - Epoch(train) [7][ 500/2478] base_lr: 4.7371e-06 lr: 9.4741e-06 eta: 2:54:19 time: 1.1140 data_time: 0.0083 memory: 7583 grad_norm: 15.0712 loss: 1.2157 2023/09/06 03:41:57 - mmengine - INFO - Epoch(train) [7][ 520/2478] base_lr: 4.7245e-06 lr: 9.4491e-06 eta: 2:53:56 time: 1.1097 data_time: 0.0082 memory: 7583 grad_norm: 15.6841 loss: 1.4873 2023/09/06 03:42:20 - mmengine - INFO - Epoch(train) [7][ 540/2478] base_lr: 4.7120e-06 lr: 9.4240e-06 eta: 2:53:34 time: 1.1122 data_time: 0.0084 memory: 7583 grad_norm: 14.7678 loss: 1.1897 2023/09/06 03:42:42 - mmengine - INFO - Epoch(train) [7][ 560/2478] base_lr: 4.6995e-06 lr: 9.3990e-06 eta: 2:53:12 time: 1.1084 data_time: 0.0082 memory: 7583 grad_norm: 14.6430 loss: 1.2713 2023/09/06 03:43:04 - mmengine - INFO - Epoch(train) [7][ 580/2478] base_lr: 4.6870e-06 lr: 9.3739e-06 eta: 2:52:50 time: 1.1103 data_time: 0.0080 memory: 7583 grad_norm: 14.8239 loss: 1.0899 2023/09/06 03:43:26 - mmengine - INFO - Epoch(train) [7][ 600/2478] base_lr: 4.6745e-06 lr: 9.3489e-06 eta: 2:52:28 time: 1.1144 data_time: 0.0079 memory: 7583 grad_norm: 15.3188 loss: 1.1376 2023/09/06 03:43:49 - mmengine - INFO - Epoch(train) [7][ 620/2478] base_lr: 4.6619e-06 lr: 9.3239e-06 eta: 2:52:05 time: 1.1114 data_time: 0.0081 memory: 7583 grad_norm: 15.0762 loss: 1.0002 2023/09/06 03:44:11 - mmengine - INFO - Epoch(train) [7][ 640/2478] base_lr: 4.6494e-06 lr: 9.2989e-06 eta: 2:51:43 time: 1.1093 data_time: 0.0079 memory: 7583 grad_norm: 15.5235 loss: 1.3279 2023/09/06 03:44:33 - mmengine - INFO - Epoch(train) [7][ 660/2478] base_lr: 4.6369e-06 lr: 9.2738e-06 eta: 2:51:21 time: 1.1106 data_time: 0.0080 memory: 7583 grad_norm: 15.4299 loss: 1.2285 2023/09/06 03:44:55 - mmengine - INFO - Epoch(train) [7][ 680/2478] base_lr: 4.6244e-06 lr: 9.2488e-06 eta: 2:50:59 time: 1.1104 data_time: 0.0082 memory: 7583 grad_norm: 14.7802 loss: 1.2026 2023/09/06 03:45:17 - mmengine - INFO - Epoch(train) [7][ 700/2478] base_lr: 4.6119e-06 lr: 9.2238e-06 eta: 2:50:36 time: 1.1092 data_time: 0.0080 memory: 7583 grad_norm: 15.3564 loss: 1.2673 2023/09/06 03:45:40 - mmengine - INFO - Epoch(train) [7][ 720/2478] base_lr: 4.5994e-06 lr: 9.1988e-06 eta: 2:50:14 time: 1.1133 data_time: 0.0080 memory: 7583 grad_norm: 15.6464 loss: 1.2478 2023/09/06 03:46:02 - mmengine - INFO - Epoch(train) [7][ 740/2478] base_lr: 4.5869e-06 lr: 9.1738e-06 eta: 2:49:52 time: 1.1112 data_time: 0.0083 memory: 7583 grad_norm: 15.1887 loss: 1.2226 2023/09/06 03:46:24 - mmengine - INFO - Epoch(train) [7][ 760/2478] base_lr: 4.5744e-06 lr: 9.1488e-06 eta: 2:49:30 time: 1.1074 data_time: 0.0082 memory: 7583 grad_norm: 14.8903 loss: 1.3125 2023/09/06 03:46:46 - mmengine - INFO - Epoch(train) [7][ 780/2478] base_lr: 4.5619e-06 lr: 9.1239e-06 eta: 2:49:07 time: 1.1074 data_time: 0.0082 memory: 7583 grad_norm: 14.9088 loss: 1.2909 2023/09/06 03:47:08 - mmengine - INFO - Epoch(train) [7][ 800/2478] base_lr: 4.5494e-06 lr: 9.0989e-06 eta: 2:48:45 time: 1.1113 data_time: 0.0083 memory: 7583 grad_norm: 15.2658 loss: 1.1436 2023/09/06 03:47:31 - mmengine - INFO - Epoch(train) [7][ 820/2478] base_lr: 4.5370e-06 lr: 9.0739e-06 eta: 2:48:23 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 15.8482 loss: 1.4816 2023/09/06 03:47:53 - mmengine - INFO - Epoch(train) [7][ 840/2478] base_lr: 4.5245e-06 lr: 9.0489e-06 eta: 2:48:01 time: 1.1099 data_time: 0.0083 memory: 7583 grad_norm: 15.0027 loss: 1.4248 2023/09/06 03:48:15 - mmengine - INFO - Epoch(train) [7][ 860/2478] base_lr: 4.5120e-06 lr: 9.0240e-06 eta: 2:47:38 time: 1.1101 data_time: 0.0082 memory: 7583 grad_norm: 15.4454 loss: 1.2911 2023/09/06 03:48:37 - mmengine - INFO - Epoch(train) [7][ 880/2478] base_lr: 4.4995e-06 lr: 8.9990e-06 eta: 2:47:16 time: 1.1106 data_time: 0.0082 memory: 7583 grad_norm: 15.0750 loss: 1.4516 2023/09/06 03:48:59 - mmengine - INFO - Epoch(train) [7][ 900/2478] base_lr: 4.4870e-06 lr: 8.9741e-06 eta: 2:46:54 time: 1.1124 data_time: 0.0081 memory: 7583 grad_norm: 14.9773 loss: 1.1566 2023/09/06 03:49:22 - mmengine - INFO - Epoch(train) [7][ 920/2478] base_lr: 4.4746e-06 lr: 8.9492e-06 eta: 2:46:32 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 15.1080 loss: 1.4618 2023/09/06 03:49:44 - mmengine - INFO - Epoch(train) [7][ 940/2478] base_lr: 4.4621e-06 lr: 8.9242e-06 eta: 2:46:10 time: 1.1115 data_time: 0.0082 memory: 7583 grad_norm: 14.7781 loss: 1.1062 2023/09/06 03:50:06 - mmengine - INFO - Epoch(train) [7][ 960/2478] base_lr: 4.4497e-06 lr: 8.8993e-06 eta: 2:45:47 time: 1.1071 data_time: 0.0078 memory: 7583 grad_norm: 15.3152 loss: 1.0874 2023/09/06 03:50:28 - mmengine - INFO - Epoch(train) [7][ 980/2478] base_lr: 4.4372e-06 lr: 8.8744e-06 eta: 2:45:25 time: 1.1087 data_time: 0.0081 memory: 7583 grad_norm: 14.3932 loss: 1.3576 2023/09/06 03:50:50 - mmengine - INFO - Epoch(train) [7][1000/2478] base_lr: 4.4247e-06 lr: 8.8495e-06 eta: 2:45:03 time: 1.1092 data_time: 0.0083 memory: 7583 grad_norm: 15.5180 loss: 1.2883 2023/09/06 03:51:13 - mmengine - INFO - Epoch(train) [7][1020/2478] base_lr: 4.4123e-06 lr: 8.8246e-06 eta: 2:44:41 time: 1.1081 data_time: 0.0078 memory: 7583 grad_norm: 15.0169 loss: 1.4122 2023/09/06 03:51:35 - mmengine - INFO - Epoch(train) [7][1040/2478] base_lr: 4.3999e-06 lr: 8.7997e-06 eta: 2:44:18 time: 1.1097 data_time: 0.0080 memory: 7583 grad_norm: 14.8631 loss: 1.3157 2023/09/06 03:51:57 - mmengine - INFO - Epoch(train) [7][1060/2478] base_lr: 4.3874e-06 lr: 8.7748e-06 eta: 2:43:56 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 15.1456 loss: 1.2731 2023/09/06 03:52:19 - mmengine - INFO - Epoch(train) [7][1080/2478] base_lr: 4.3750e-06 lr: 8.7499e-06 eta: 2:43:34 time: 1.1080 data_time: 0.0082 memory: 7583 grad_norm: 15.2299 loss: 1.3563 2023/09/06 03:52:41 - mmengine - INFO - Epoch(train) [7][1100/2478] base_lr: 4.3625e-06 lr: 8.7251e-06 eta: 2:43:12 time: 1.1110 data_time: 0.0084 memory: 7583 grad_norm: 15.1743 loss: 1.2716 2023/09/06 03:53:04 - mmengine - INFO - Epoch(train) [7][1120/2478] base_lr: 4.3501e-06 lr: 8.7002e-06 eta: 2:42:49 time: 1.1105 data_time: 0.0083 memory: 7583 grad_norm: 15.0824 loss: 1.1637 2023/09/06 03:53:17 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 03:53:26 - mmengine - INFO - Epoch(train) [7][1140/2478] base_lr: 4.3377e-06 lr: 8.6754e-06 eta: 2:42:27 time: 1.1116 data_time: 0.0082 memory: 7583 grad_norm: 15.1501 loss: 1.2012 2023/09/06 03:53:48 - mmengine - INFO - Epoch(train) [7][1160/2478] base_lr: 4.3253e-06 lr: 8.6505e-06 eta: 2:42:05 time: 1.1128 data_time: 0.0079 memory: 7583 grad_norm: 15.1465 loss: 1.3106 2023/09/06 03:54:10 - mmengine - INFO - Epoch(train) [7][1180/2478] base_lr: 4.3129e-06 lr: 8.6257e-06 eta: 2:41:43 time: 1.1103 data_time: 0.0080 memory: 7583 grad_norm: 15.6818 loss: 1.4983 2023/09/06 03:54:32 - mmengine - INFO - Epoch(train) [7][1200/2478] base_lr: 4.3005e-06 lr: 8.6009e-06 eta: 2:41:20 time: 1.1090 data_time: 0.0080 memory: 7583 grad_norm: 15.1418 loss: 1.2688 2023/09/06 03:54:55 - mmengine - INFO - Epoch(train) [7][1220/2478] base_lr: 4.2880e-06 lr: 8.5761e-06 eta: 2:40:58 time: 1.1096 data_time: 0.0083 memory: 7583 grad_norm: 15.4064 loss: 1.2484 2023/09/06 03:55:17 - mmengine - INFO - Epoch(train) [7][1240/2478] base_lr: 4.2756e-06 lr: 8.5513e-06 eta: 2:40:36 time: 1.1092 data_time: 0.0079 memory: 7583 grad_norm: 15.7273 loss: 1.1374 2023/09/06 03:55:39 - mmengine - INFO - Epoch(train) [7][1260/2478] base_lr: 4.2633e-06 lr: 8.5265e-06 eta: 2:40:14 time: 1.1094 data_time: 0.0079 memory: 7583 grad_norm: 15.6350 loss: 1.3482 2023/09/06 03:56:01 - mmengine - INFO - Epoch(train) [7][1280/2478] base_lr: 4.2509e-06 lr: 8.5017e-06 eta: 2:39:51 time: 1.1110 data_time: 0.0081 memory: 7583 grad_norm: 15.5557 loss: 1.1611 2023/09/06 03:56:23 - mmengine - INFO - Epoch(train) [7][1300/2478] base_lr: 4.2385e-06 lr: 8.4770e-06 eta: 2:39:29 time: 1.1144 data_time: 0.0080 memory: 7583 grad_norm: 15.2503 loss: 1.2639 2023/09/06 03:56:46 - mmengine - INFO - Epoch(train) [7][1320/2478] base_lr: 4.2261e-06 lr: 8.4522e-06 eta: 2:39:07 time: 1.1105 data_time: 0.0080 memory: 7583 grad_norm: 15.8350 loss: 1.5169 2023/09/06 03:57:08 - mmengine - INFO - Epoch(train) [7][1340/2478] base_lr: 4.2137e-06 lr: 8.4275e-06 eta: 2:38:45 time: 1.1145 data_time: 0.0081 memory: 7583 grad_norm: 14.9839 loss: 1.5318 2023/09/06 03:57:30 - mmengine - INFO - Epoch(train) [7][1360/2478] base_lr: 4.2014e-06 lr: 8.4027e-06 eta: 2:38:23 time: 1.1106 data_time: 0.0083 memory: 7583 grad_norm: 15.5985 loss: 1.3776 2023/09/06 03:57:52 - mmengine - INFO - Epoch(train) [7][1380/2478] base_lr: 4.1890e-06 lr: 8.3780e-06 eta: 2:38:00 time: 1.1115 data_time: 0.0081 memory: 7583 grad_norm: 15.2737 loss: 1.1055 2023/09/06 03:58:15 - mmengine - INFO - Epoch(train) [7][1400/2478] base_lr: 4.1766e-06 lr: 8.3533e-06 eta: 2:37:38 time: 1.1105 data_time: 0.0082 memory: 7583 grad_norm: 15.9983 loss: 1.3447 2023/09/06 03:58:37 - mmengine - INFO - Epoch(train) [7][1420/2478] base_lr: 4.1643e-06 lr: 8.3286e-06 eta: 2:37:16 time: 1.1116 data_time: 0.0083 memory: 7583 grad_norm: 15.2891 loss: 1.2724 2023/09/06 03:58:59 - mmengine - INFO - Epoch(train) [7][1440/2478] base_lr: 4.1519e-06 lr: 8.3039e-06 eta: 2:36:54 time: 1.1145 data_time: 0.0082 memory: 7583 grad_norm: 15.3585 loss: 1.2065 2023/09/06 03:59:21 - mmengine - INFO - Epoch(train) [7][1460/2478] base_lr: 4.1396e-06 lr: 8.2792e-06 eta: 2:36:32 time: 1.1121 data_time: 0.0080 memory: 7583 grad_norm: 15.5690 loss: 1.2505 2023/09/06 03:59:44 - mmengine - INFO - Epoch(train) [7][1480/2478] base_lr: 4.1273e-06 lr: 8.2545e-06 eta: 2:36:09 time: 1.1128 data_time: 0.0080 memory: 7583 grad_norm: 15.9719 loss: 1.2391 2023/09/06 04:00:06 - mmengine - INFO - Epoch(train) [7][1500/2478] base_lr: 4.1149e-06 lr: 8.2299e-06 eta: 2:35:47 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 15.6938 loss: 1.1154 2023/09/06 04:00:28 - mmengine - INFO - Epoch(train) [7][1520/2478] base_lr: 4.1026e-06 lr: 8.2052e-06 eta: 2:35:25 time: 1.1121 data_time: 0.0078 memory: 7583 grad_norm: 15.3884 loss: 1.3069 2023/09/06 04:00:50 - mmengine - INFO - Epoch(train) [7][1540/2478] base_lr: 4.0903e-06 lr: 8.1806e-06 eta: 2:35:03 time: 1.1130 data_time: 0.0079 memory: 7583 grad_norm: 15.2057 loss: 1.2111 2023/09/06 04:01:13 - mmengine - INFO - Epoch(train) [7][1560/2478] base_lr: 4.0780e-06 lr: 8.1560e-06 eta: 2:34:40 time: 1.1105 data_time: 0.0079 memory: 7583 grad_norm: 14.9341 loss: 1.4141 2023/09/06 04:01:35 - mmengine - INFO - Epoch(train) [7][1580/2478] base_lr: 4.0657e-06 lr: 8.1314e-06 eta: 2:34:18 time: 1.1157 data_time: 0.0079 memory: 7583 grad_norm: 15.6366 loss: 1.3414 2023/09/06 04:01:57 - mmengine - INFO - Epoch(train) [7][1600/2478] base_lr: 4.0534e-06 lr: 8.1068e-06 eta: 2:33:56 time: 1.1134 data_time: 0.0079 memory: 7583 grad_norm: 15.3255 loss: 1.1145 2023/09/06 04:02:19 - mmengine - INFO - Epoch(train) [7][1620/2478] base_lr: 4.0411e-06 lr: 8.0822e-06 eta: 2:33:34 time: 1.1132 data_time: 0.0076 memory: 7583 grad_norm: 15.4861 loss: 1.3442 2023/09/06 04:02:42 - mmengine - INFO - Epoch(train) [7][1640/2478] base_lr: 4.0288e-06 lr: 8.0576e-06 eta: 2:33:12 time: 1.1121 data_time: 0.0079 memory: 7583 grad_norm: 15.0688 loss: 1.1241 2023/09/06 04:03:04 - mmengine - INFO - Epoch(train) [7][1660/2478] base_lr: 4.0165e-06 lr: 8.0331e-06 eta: 2:32:49 time: 1.1116 data_time: 0.0078 memory: 7583 grad_norm: 14.8557 loss: 1.1623 2023/09/06 04:03:26 - mmengine - INFO - Epoch(train) [7][1680/2478] base_lr: 4.0043e-06 lr: 8.0085e-06 eta: 2:32:27 time: 1.1123 data_time: 0.0077 memory: 7583 grad_norm: 15.6992 loss: 1.2029 2023/09/06 04:03:48 - mmengine - INFO - Epoch(train) [7][1700/2478] base_lr: 3.9920e-06 lr: 7.9840e-06 eta: 2:32:05 time: 1.1088 data_time: 0.0081 memory: 7583 grad_norm: 15.7213 loss: 1.1203 2023/09/06 04:04:11 - mmengine - INFO - Epoch(train) [7][1720/2478] base_lr: 3.9797e-06 lr: 7.9595e-06 eta: 2:31:43 time: 1.1111 data_time: 0.0081 memory: 7583 grad_norm: 15.4670 loss: 1.2275 2023/09/06 04:04:33 - mmengine - INFO - Epoch(train) [7][1740/2478] base_lr: 3.9675e-06 lr: 7.9350e-06 eta: 2:31:20 time: 1.1083 data_time: 0.0079 memory: 7583 grad_norm: 15.4679 loss: 1.2821 2023/09/06 04:04:55 - mmengine - INFO - Epoch(train) [7][1760/2478] base_lr: 3.9553e-06 lr: 7.9105e-06 eta: 2:30:58 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 15.7125 loss: 1.6474 2023/09/06 04:05:17 - mmengine - INFO - Epoch(train) [7][1780/2478] base_lr: 3.9430e-06 lr: 7.8860e-06 eta: 2:30:36 time: 1.1136 data_time: 0.0079 memory: 7583 grad_norm: 15.1995 loss: 1.2876 2023/09/06 04:05:39 - mmengine - INFO - Epoch(train) [7][1800/2478] base_lr: 3.9308e-06 lr: 7.8616e-06 eta: 2:30:14 time: 1.1109 data_time: 0.0078 memory: 7583 grad_norm: 15.1794 loss: 1.3648 2023/09/06 04:06:02 - mmengine - INFO - Epoch(train) [7][1820/2478] base_lr: 3.9186e-06 lr: 7.8371e-06 eta: 2:29:52 time: 1.1095 data_time: 0.0081 memory: 7583 grad_norm: 15.2695 loss: 1.0880 2023/09/06 04:06:24 - mmengine - INFO - Epoch(train) [7][1840/2478] base_lr: 3.9063e-06 lr: 7.8127e-06 eta: 2:29:29 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 15.6208 loss: 1.3934 2023/09/06 04:06:46 - mmengine - INFO - Epoch(train) [7][1860/2478] base_lr: 3.8941e-06 lr: 7.7883e-06 eta: 2:29:07 time: 1.1096 data_time: 0.0078 memory: 7583 grad_norm: 15.8294 loss: 1.4026 2023/09/06 04:07:08 - mmengine - INFO - Epoch(train) [7][1880/2478] base_lr: 3.8819e-06 lr: 7.7639e-06 eta: 2:28:45 time: 1.1099 data_time: 0.0083 memory: 7583 grad_norm: 15.7207 loss: 1.3677 2023/09/06 04:07:30 - mmengine - INFO - Epoch(train) [7][1900/2478] base_lr: 3.8697e-06 lr: 7.7395e-06 eta: 2:28:23 time: 1.1074 data_time: 0.0083 memory: 7583 grad_norm: 15.5484 loss: 1.1849 2023/09/06 04:07:53 - mmengine - INFO - Epoch(train) [7][1920/2478] base_lr: 3.8576e-06 lr: 7.7151e-06 eta: 2:28:00 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 15.7477 loss: 1.1444 2023/09/06 04:08:15 - mmengine - INFO - Epoch(train) [7][1940/2478] base_lr: 3.8454e-06 lr: 7.6908e-06 eta: 2:27:38 time: 1.1114 data_time: 0.0081 memory: 7583 grad_norm: 16.0309 loss: 1.3250 2023/09/06 04:08:37 - mmengine - INFO - Epoch(train) [7][1960/2478] base_lr: 3.8332e-06 lr: 7.6664e-06 eta: 2:27:16 time: 1.1104 data_time: 0.0085 memory: 7583 grad_norm: 15.4532 loss: 1.2327 2023/09/06 04:08:59 - mmengine - INFO - Epoch(train) [7][1980/2478] base_lr: 3.8211e-06 lr: 7.6421e-06 eta: 2:26:54 time: 1.1107 data_time: 0.0084 memory: 7583 grad_norm: 15.2211 loss: 1.3310 2023/09/06 04:09:21 - mmengine - INFO - Epoch(train) [7][2000/2478] base_lr: 3.8089e-06 lr: 7.6178e-06 eta: 2:26:31 time: 1.1099 data_time: 0.0085 memory: 7583 grad_norm: 15.4627 loss: 1.2849 2023/09/06 04:09:43 - mmengine - INFO - Epoch(train) [7][2020/2478] base_lr: 3.7968e-06 lr: 7.5935e-06 eta: 2:26:09 time: 1.1063 data_time: 0.0083 memory: 7583 grad_norm: 14.8033 loss: 1.0389 2023/09/06 04:10:06 - mmengine - INFO - Epoch(train) [7][2040/2478] base_lr: 3.7846e-06 lr: 7.5692e-06 eta: 2:25:47 time: 1.1102 data_time: 0.0082 memory: 7583 grad_norm: 16.0735 loss: 1.4647 2023/09/06 04:10:28 - mmengine - INFO - Epoch(train) [7][2060/2478] base_lr: 3.7725e-06 lr: 7.5450e-06 eta: 2:25:25 time: 1.1130 data_time: 0.0087 memory: 7583 grad_norm: 15.5454 loss: 1.2760 2023/09/06 04:10:50 - mmengine - INFO - Epoch(train) [7][2080/2478] base_lr: 3.7604e-06 lr: 7.5207e-06 eta: 2:25:03 time: 1.1138 data_time: 0.0082 memory: 7583 grad_norm: 15.4361 loss: 1.4227 2023/09/06 04:11:12 - mmengine - INFO - Epoch(train) [7][2100/2478] base_lr: 3.7482e-06 lr: 7.4965e-06 eta: 2:24:40 time: 1.1082 data_time: 0.0083 memory: 7583 grad_norm: 15.4100 loss: 1.3788 2023/09/06 04:11:35 - mmengine - INFO - Epoch(train) [7][2120/2478] base_lr: 3.7361e-06 lr: 7.4723e-06 eta: 2:24:18 time: 1.1094 data_time: 0.0082 memory: 7583 grad_norm: 15.5587 loss: 1.1334 2023/09/06 04:11:48 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 04:11:57 - mmengine - INFO - Epoch(train) [7][2140/2478] base_lr: 3.7240e-06 lr: 7.4481e-06 eta: 2:23:56 time: 1.1087 data_time: 0.0083 memory: 7583 grad_norm: 15.2637 loss: 1.3119 2023/09/06 04:12:19 - mmengine - INFO - Epoch(train) [7][2160/2478] base_lr: 3.7120e-06 lr: 7.4239e-06 eta: 2:23:34 time: 1.1094 data_time: 0.0083 memory: 7583 grad_norm: 15.7573 loss: 1.2545 2023/09/06 04:12:41 - mmengine - INFO - Epoch(train) [7][2180/2478] base_lr: 3.6999e-06 lr: 7.3998e-06 eta: 2:23:11 time: 1.1133 data_time: 0.0086 memory: 7583 grad_norm: 15.2150 loss: 1.2741 2023/09/06 04:13:03 - mmengine - INFO - Epoch(train) [7][2200/2478] base_lr: 3.6878e-06 lr: 7.3756e-06 eta: 2:22:49 time: 1.1105 data_time: 0.0083 memory: 7583 grad_norm: 15.5068 loss: 1.2762 2023/09/06 04:13:26 - mmengine - INFO - Epoch(train) [7][2220/2478] base_lr: 3.6757e-06 lr: 7.3515e-06 eta: 2:22:27 time: 1.1113 data_time: 0.0079 memory: 7583 grad_norm: 14.9417 loss: 1.2774 2023/09/06 04:13:48 - mmengine - INFO - Epoch(train) [7][2240/2478] base_lr: 3.6637e-06 lr: 7.3274e-06 eta: 2:22:05 time: 1.1099 data_time: 0.0082 memory: 7583 grad_norm: 15.5945 loss: 1.2754 2023/09/06 04:14:10 - mmengine - INFO - Epoch(train) [7][2260/2478] base_lr: 3.6516e-06 lr: 7.3033e-06 eta: 2:21:42 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 15.6133 loss: 1.2467 2023/09/06 04:14:32 - mmengine - INFO - Epoch(train) [7][2280/2478] base_lr: 3.6396e-06 lr: 7.2792e-06 eta: 2:21:20 time: 1.1113 data_time: 0.0078 memory: 7583 grad_norm: 15.5142 loss: 1.1040 2023/09/06 04:14:54 - mmengine - INFO - Epoch(train) [7][2300/2478] base_lr: 3.6276e-06 lr: 7.2552e-06 eta: 2:20:58 time: 1.1091 data_time: 0.0080 memory: 7583 grad_norm: 15.5301 loss: 1.2297 2023/09/06 04:15:17 - mmengine - INFO - Epoch(train) [7][2320/2478] base_lr: 3.6156e-06 lr: 7.2311e-06 eta: 2:20:36 time: 1.1116 data_time: 0.0080 memory: 7583 grad_norm: 14.8300 loss: 1.4736 2023/09/06 04:15:39 - mmengine - INFO - Epoch(train) [7][2340/2478] base_lr: 3.6036e-06 lr: 7.2071e-06 eta: 2:20:13 time: 1.1070 data_time: 0.0081 memory: 7583 grad_norm: 15.9354 loss: 1.3168 2023/09/06 04:16:01 - mmengine - INFO - Epoch(train) [7][2360/2478] base_lr: 3.5916e-06 lr: 7.1831e-06 eta: 2:19:51 time: 1.1121 data_time: 0.0082 memory: 7583 grad_norm: 14.8102 loss: 1.2851 2023/09/06 04:16:23 - mmengine - INFO - Epoch(train) [7][2380/2478] base_lr: 3.5796e-06 lr: 7.1591e-06 eta: 2:19:29 time: 1.1113 data_time: 0.0082 memory: 7583 grad_norm: 15.5542 loss: 1.0706 2023/09/06 04:16:46 - mmengine - INFO - Epoch(train) [7][2400/2478] base_lr: 3.5676e-06 lr: 7.1352e-06 eta: 2:19:07 time: 1.1103 data_time: 0.0083 memory: 7583 grad_norm: 15.8323 loss: 1.3680 2023/09/06 04:17:08 - mmengine - INFO - Epoch(train) [7][2420/2478] base_lr: 3.5556e-06 lr: 7.1112e-06 eta: 2:18:45 time: 1.1085 data_time: 0.0082 memory: 7583 grad_norm: 15.8312 loss: 1.3618 2023/09/06 04:17:30 - mmengine - INFO - Epoch(train) [7][2440/2478] base_lr: 3.5437e-06 lr: 7.0873e-06 eta: 2:18:22 time: 1.1114 data_time: 0.0080 memory: 7583 grad_norm: 15.6199 loss: 1.2795 2023/09/06 04:17:52 - mmengine - INFO - Epoch(train) [7][2460/2478] base_lr: 3.5317e-06 lr: 7.0634e-06 eta: 2:18:00 time: 1.1093 data_time: 0.0081 memory: 7583 grad_norm: 15.4561 loss: 1.0776 2023/09/06 04:18:12 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 04:18:12 - mmengine - INFO - Epoch(train) [7][2478/2478] base_lr: 3.5210e-06 lr: 7.0419e-06 eta: 2:17:40 time: 1.1058 data_time: 0.0080 memory: 7583 grad_norm: 15.7983 loss: 1.4815 2023/09/06 04:18:12 - mmengine - INFO - Saving checkpoint at 7 epochs 2023/09/06 04:18:43 - mmengine - INFO - Epoch(val) [7][20/96] eta: 0:01:22 time: 1.0825 data_time: 0.0386 memory: 8884 2023/09/06 04:19:04 - mmengine - INFO - Epoch(val) [7][40/96] eta: 0:00:59 time: 1.0466 data_time: 0.0064 memory: 8884 2023/09/06 04:19:25 - mmengine - INFO - Epoch(val) [7][60/96] eta: 0:00:38 time: 1.0506 data_time: 0.0064 memory: 8884 2023/09/06 04:19:46 - mmengine - INFO - Epoch(val) [7][80/96] eta: 0:00:16 time: 1.0447 data_time: 0.0066 memory: 8884 2023/09/06 04:20:03 - mmengine - INFO - Epoch(val) [7][96/96] VQA/acc: 42.3277 data_time: 0.0131 time: 1.0543 2023/09/06 04:20:26 - mmengine - INFO - Epoch(train) [8][ 20/2478] base_lr: 3.5090e-06 lr: 7.0181e-06 eta: 2:17:18 time: 1.1317 data_time: 0.0217 memory: 8884 grad_norm: 13.4153 loss: 1.0330 2023/09/06 04:20:48 - mmengine - INFO - Epoch(train) [8][ 40/2478] base_lr: 3.4971e-06 lr: 6.9942e-06 eta: 2:16:56 time: 1.1089 data_time: 0.0079 memory: 7583 grad_norm: 13.9757 loss: 0.9164 2023/09/06 04:21:10 - mmengine - INFO - Epoch(train) [8][ 60/2478] base_lr: 3.4852e-06 lr: 6.9704e-06 eta: 2:16:34 time: 1.1125 data_time: 0.0084 memory: 7583 grad_norm: 13.9159 loss: 0.9907 2023/09/06 04:21:32 - mmengine - INFO - Epoch(train) [8][ 80/2478] base_lr: 3.4733e-06 lr: 6.9466e-06 eta: 2:16:11 time: 1.1102 data_time: 0.0078 memory: 7583 grad_norm: 14.3029 loss: 0.9480 2023/09/06 04:21:54 - mmengine - INFO - Epoch(train) [8][ 100/2478] base_lr: 3.4614e-06 lr: 6.9228e-06 eta: 2:15:49 time: 1.1111 data_time: 0.0077 memory: 7583 grad_norm: 14.1304 loss: 0.9739 2023/09/06 04:22:17 - mmengine - INFO - Epoch(train) [8][ 120/2478] base_lr: 3.4495e-06 lr: 6.8990e-06 eta: 2:15:27 time: 1.1094 data_time: 0.0077 memory: 7583 grad_norm: 14.8171 loss: 1.2018 2023/09/06 04:22:39 - mmengine - INFO - Epoch(train) [8][ 140/2478] base_lr: 3.4376e-06 lr: 6.8753e-06 eta: 2:15:05 time: 1.1133 data_time: 0.0078 memory: 7583 grad_norm: 14.4158 loss: 1.1343 2023/09/06 04:23:01 - mmengine - INFO - Epoch(train) [8][ 160/2478] base_lr: 3.4258e-06 lr: 6.8516e-06 eta: 2:14:42 time: 1.1063 data_time: 0.0080 memory: 7583 grad_norm: 14.8456 loss: 1.2109 2023/09/06 04:23:23 - mmengine - INFO - Epoch(train) [8][ 180/2478] base_lr: 3.4139e-06 lr: 6.8279e-06 eta: 2:14:20 time: 1.1076 data_time: 0.0079 memory: 7583 grad_norm: inf loss: 0.9793 2023/09/06 04:23:45 - mmengine - INFO - Epoch(train) [8][ 200/2478] base_lr: 3.4021e-06 lr: 6.8042e-06 eta: 2:13:58 time: 1.1119 data_time: 0.0081 memory: 7583 grad_norm: 14.4501 loss: 0.8018 2023/09/06 04:24:08 - mmengine - INFO - Epoch(train) [8][ 220/2478] base_lr: 3.3903e-06 lr: 6.7805e-06 eta: 2:13:36 time: 1.1091 data_time: 0.0082 memory: 7583 grad_norm: 13.9470 loss: 1.0784 2023/09/06 04:24:30 - mmengine - INFO - Epoch(train) [8][ 240/2478] base_lr: 3.3784e-06 lr: 6.7569e-06 eta: 2:13:13 time: 1.1138 data_time: 0.0080 memory: 7583 grad_norm: 14.7286 loss: 1.1409 2023/09/06 04:24:52 - mmengine - INFO - Epoch(train) [8][ 260/2478] base_lr: 3.3666e-06 lr: 6.7333e-06 eta: 2:12:51 time: 1.1128 data_time: 0.0079 memory: 7583 grad_norm: 14.4899 loss: 1.1594 2023/09/06 04:25:14 - mmengine - INFO - Epoch(train) [8][ 280/2478] base_lr: 3.3548e-06 lr: 6.7097e-06 eta: 2:12:29 time: 1.1098 data_time: 0.0083 memory: 7583 grad_norm: 15.1371 loss: 1.0819 2023/09/06 04:25:36 - mmengine - INFO - Epoch(train) [8][ 300/2478] base_lr: 3.3431e-06 lr: 6.6861e-06 eta: 2:12:07 time: 1.1112 data_time: 0.0084 memory: 7583 grad_norm: 14.7026 loss: 0.9402 2023/09/06 04:25:59 - mmengine - INFO - Epoch(train) [8][ 320/2478] base_lr: 3.3313e-06 lr: 6.6626e-06 eta: 2:11:45 time: 1.1120 data_time: 0.0084 memory: 7583 grad_norm: 14.5270 loss: 0.8879 2023/09/06 04:26:21 - mmengine - INFO - Epoch(train) [8][ 340/2478] base_lr: 3.3195e-06 lr: 6.6390e-06 eta: 2:11:22 time: 1.1112 data_time: 0.0083 memory: 7583 grad_norm: 15.0982 loss: 0.9594 2023/09/06 04:26:43 - mmengine - INFO - Epoch(train) [8][ 360/2478] base_lr: 3.3078e-06 lr: 6.6155e-06 eta: 2:11:00 time: 1.1129 data_time: 0.0084 memory: 7583 grad_norm: 14.8579 loss: 0.9620 2023/09/06 04:27:05 - mmengine - INFO - Epoch(train) [8][ 380/2478] base_lr: 3.2960e-06 lr: 6.5920e-06 eta: 2:10:38 time: 1.1089 data_time: 0.0078 memory: 7583 grad_norm: 14.5938 loss: 1.1428 2023/09/06 04:27:28 - mmengine - INFO - Epoch(train) [8][ 400/2478] base_lr: 3.2843e-06 lr: 6.5686e-06 eta: 2:10:16 time: 1.1123 data_time: 0.0082 memory: 7583 grad_norm: 15.0604 loss: 1.0357 2023/09/06 04:27:50 - mmengine - INFO - Epoch(train) [8][ 420/2478] base_lr: 3.2726e-06 lr: 6.5451e-06 eta: 2:09:53 time: 1.1094 data_time: 0.0078 memory: 7583 grad_norm: 14.8023 loss: 0.9397 2023/09/06 04:28:12 - mmengine - INFO - Epoch(train) [8][ 440/2478] base_lr: 3.2609e-06 lr: 6.5217e-06 eta: 2:09:31 time: 1.1091 data_time: 0.0082 memory: 7583 grad_norm: 14.5851 loss: 0.9571 2023/09/06 04:28:34 - mmengine - INFO - Epoch(train) [8][ 460/2478] base_lr: 3.2492e-06 lr: 6.4983e-06 eta: 2:09:09 time: 1.1113 data_time: 0.0078 memory: 7583 grad_norm: 15.3424 loss: 1.0388 2023/09/06 04:28:56 - mmengine - INFO - Epoch(train) [8][ 480/2478] base_lr: 3.2375e-06 lr: 6.4749e-06 eta: 2:08:47 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 14.9447 loss: 1.0564 2023/09/06 04:29:19 - mmengine - INFO - Epoch(train) [8][ 500/2478] base_lr: 3.2258e-06 lr: 6.4516e-06 eta: 2:08:24 time: 1.1084 data_time: 0.0079 memory: 7583 grad_norm: 14.7096 loss: 1.1024 2023/09/06 04:29:41 - mmengine - INFO - Epoch(train) [8][ 520/2478] base_lr: 3.2141e-06 lr: 6.4283e-06 eta: 2:08:02 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 14.8882 loss: 0.9847 2023/09/06 04:30:03 - mmengine - INFO - Epoch(train) [8][ 540/2478] base_lr: 3.2025e-06 lr: 6.4050e-06 eta: 2:07:40 time: 1.1083 data_time: 0.0082 memory: 7583 grad_norm: 15.0873 loss: 1.0745 2023/09/06 04:30:25 - mmengine - INFO - Epoch(train) [8][ 560/2478] base_lr: 3.1908e-06 lr: 6.3817e-06 eta: 2:07:18 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 14.8035 loss: 1.0575 2023/09/06 04:30:47 - mmengine - INFO - Epoch(train) [8][ 580/2478] base_lr: 3.1792e-06 lr: 6.3584e-06 eta: 2:06:56 time: 1.1115 data_time: 0.0078 memory: 7583 grad_norm: 15.0701 loss: 1.1818 2023/09/06 04:31:10 - mmengine - INFO - Epoch(train) [8][ 600/2478] base_lr: 3.1676e-06 lr: 6.3352e-06 eta: 2:06:33 time: 1.1104 data_time: 0.0081 memory: 7583 grad_norm: 14.8806 loss: 0.8606 2023/09/06 04:31:32 - mmengine - INFO - Epoch(train) [8][ 620/2478] base_lr: 3.1560e-06 lr: 6.3120e-06 eta: 2:06:11 time: 1.1110 data_time: 0.0081 memory: 7583 grad_norm: 15.2927 loss: 0.9294 2023/09/06 04:31:54 - mmengine - INFO - Epoch(train) [8][ 640/2478] base_lr: 3.1444e-06 lr: 6.2888e-06 eta: 2:05:49 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 14.7654 loss: 0.9813 2023/09/06 04:32:10 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 04:32:16 - mmengine - INFO - Epoch(train) [8][ 660/2478] base_lr: 3.1328e-06 lr: 6.2657e-06 eta: 2:05:27 time: 1.1096 data_time: 0.0085 memory: 7583 grad_norm: 14.6661 loss: 0.9670 2023/09/06 04:32:38 - mmengine - INFO - Epoch(train) [8][ 680/2478] base_lr: 3.1213e-06 lr: 6.2425e-06 eta: 2:05:04 time: 1.1091 data_time: 0.0081 memory: 7583 grad_norm: 15.0690 loss: 1.1656 2023/09/06 04:33:01 - mmengine - INFO - Epoch(train) [8][ 700/2478] base_lr: 3.1097e-06 lr: 6.2194e-06 eta: 2:04:42 time: 1.1110 data_time: 0.0080 memory: 7583 grad_norm: 14.8413 loss: 1.1623 2023/09/06 04:33:23 - mmengine - INFO - Epoch(train) [8][ 720/2478] base_lr: 3.0982e-06 lr: 6.1964e-06 eta: 2:04:20 time: 1.1133 data_time: 0.0093 memory: 7583 grad_norm: 14.9789 loss: 1.1199 2023/09/06 04:33:45 - mmengine - INFO - Epoch(train) [8][ 740/2478] base_lr: 3.0867e-06 lr: 6.1733e-06 eta: 2:03:58 time: 1.1135 data_time: 0.0080 memory: 7583 grad_norm: 14.1072 loss: 1.0320 2023/09/06 04:34:07 - mmengine - INFO - Epoch(train) [8][ 760/2478] base_lr: 3.0751e-06 lr: 6.1503e-06 eta: 2:03:36 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 15.4102 loss: 1.2095 2023/09/06 04:34:30 - mmengine - INFO - Epoch(train) [8][ 780/2478] base_lr: 3.0636e-06 lr: 6.1273e-06 eta: 2:03:13 time: 1.1108 data_time: 0.0085 memory: 7583 grad_norm: 15.2365 loss: 1.1191 2023/09/06 04:34:52 - mmengine - INFO - Epoch(train) [8][ 800/2478] base_lr: 3.0521e-06 lr: 6.1043e-06 eta: 2:02:51 time: 1.1117 data_time: 0.0082 memory: 7583 grad_norm: 14.7518 loss: 1.1009 2023/09/06 04:35:14 - mmengine - INFO - Epoch(train) [8][ 820/2478] base_lr: 3.0407e-06 lr: 6.0813e-06 eta: 2:02:29 time: 1.1100 data_time: 0.0081 memory: 7583 grad_norm: 15.3782 loss: 1.0764 2023/09/06 04:35:36 - mmengine - INFO - Epoch(train) [8][ 840/2478] base_lr: 3.0292e-06 lr: 6.0584e-06 eta: 2:02:07 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 14.5247 loss: 1.0657 2023/09/06 04:35:58 - mmengine - INFO - Epoch(train) [8][ 860/2478] base_lr: 3.0178e-06 lr: 6.0355e-06 eta: 2:01:44 time: 1.1098 data_time: 0.0083 memory: 7583 grad_norm: 15.0539 loss: 0.9801 2023/09/06 04:36:21 - mmengine - INFO - Epoch(train) [8][ 880/2478] base_lr: 3.0063e-06 lr: 6.0126e-06 eta: 2:01:22 time: 1.1109 data_time: 0.0082 memory: 7583 grad_norm: 15.3380 loss: 1.2232 2023/09/06 04:36:43 - mmengine - INFO - Epoch(train) [8][ 900/2478] base_lr: 2.9949e-06 lr: 5.9898e-06 eta: 2:01:00 time: 1.1122 data_time: 0.0081 memory: 7583 grad_norm: 14.6679 loss: 1.0898 2023/09/06 04:37:05 - mmengine - INFO - Epoch(train) [8][ 920/2478] base_lr: 2.9835e-06 lr: 5.9670e-06 eta: 2:00:38 time: 1.1116 data_time: 0.0082 memory: 7583 grad_norm: 15.2312 loss: 0.8876 2023/09/06 04:37:27 - mmengine - INFO - Epoch(train) [8][ 940/2478] base_lr: 2.9721e-06 lr: 5.9442e-06 eta: 2:00:15 time: 1.1104 data_time: 0.0080 memory: 7583 grad_norm: 14.5140 loss: 0.9937 2023/09/06 04:37:50 - mmengine - INFO - Epoch(train) [8][ 960/2478] base_lr: 2.9607e-06 lr: 5.9214e-06 eta: 1:59:53 time: 1.1116 data_time: 0.0081 memory: 7583 grad_norm: 14.8247 loss: 1.0497 2023/09/06 04:38:12 - mmengine - INFO - Epoch(train) [8][ 980/2478] base_lr: 2.9493e-06 lr: 5.8986e-06 eta: 1:59:31 time: 1.1117 data_time: 0.0083 memory: 7583 grad_norm: 15.1415 loss: 1.0853 2023/09/06 04:38:34 - mmengine - INFO - Epoch(train) [8][1000/2478] base_lr: 2.9380e-06 lr: 5.8759e-06 eta: 1:59:09 time: 1.1118 data_time: 0.0084 memory: 7583 grad_norm: 14.9340 loss: 1.1008 2023/09/06 04:38:56 - mmengine - INFO - Epoch(train) [8][1020/2478] base_lr: 2.9266e-06 lr: 5.8532e-06 eta: 1:58:47 time: 1.1087 data_time: 0.0082 memory: 7583 grad_norm: 14.8396 loss: 0.9557 2023/09/06 04:39:18 - mmengine - INFO - Epoch(train) [8][1040/2478] base_lr: 2.9153e-06 lr: 5.8306e-06 eta: 1:58:24 time: 1.1099 data_time: 0.0086 memory: 7583 grad_norm: 15.3948 loss: 1.1023 2023/09/06 04:39:41 - mmengine - INFO - Epoch(train) [8][1060/2478] base_lr: 2.9040e-06 lr: 5.8079e-06 eta: 1:58:02 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 15.1317 loss: 0.9527 2023/09/06 04:40:03 - mmengine - INFO - Epoch(train) [8][1080/2478] base_lr: 2.8927e-06 lr: 5.7853e-06 eta: 1:57:40 time: 1.1059 data_time: 0.0081 memory: 7583 grad_norm: 14.8262 loss: 0.9856 2023/09/06 04:40:25 - mmengine - INFO - Epoch(train) [8][1100/2478] base_lr: 2.8814e-06 lr: 5.7628e-06 eta: 1:57:18 time: 1.1138 data_time: 0.0081 memory: 7583 grad_norm: 15.0578 loss: 1.1162 2023/09/06 04:40:47 - mmengine - INFO - Epoch(train) [8][1120/2478] base_lr: 2.8701e-06 lr: 5.7402e-06 eta: 1:56:55 time: 1.1123 data_time: 0.0080 memory: 7583 grad_norm: 15.3974 loss: 1.1195 2023/09/06 04:41:09 - mmengine - INFO - Epoch(train) [8][1140/2478] base_lr: 2.8588e-06 lr: 5.7177e-06 eta: 1:56:33 time: 1.1106 data_time: 0.0080 memory: 7583 grad_norm: 15.1653 loss: 1.0081 2023/09/06 04:41:32 - mmengine - INFO - Epoch(train) [8][1160/2478] base_lr: 2.8476e-06 lr: 5.6952e-06 eta: 1:56:11 time: 1.1132 data_time: 0.0081 memory: 7583 grad_norm: 14.4982 loss: 1.0918 2023/09/06 04:41:54 - mmengine - INFO - Epoch(train) [8][1180/2478] base_lr: 2.8364e-06 lr: 5.6727e-06 eta: 1:55:49 time: 1.1094 data_time: 0.0082 memory: 7583 grad_norm: 15.1490 loss: 0.8169 2023/09/06 04:42:16 - mmengine - INFO - Epoch(train) [8][1200/2478] base_lr: 2.8251e-06 lr: 5.6503e-06 eta: 1:55:27 time: 1.1123 data_time: 0.0082 memory: 7583 grad_norm: 15.0773 loss: 1.1262 2023/09/06 04:42:38 - mmengine - INFO - Epoch(train) [8][1220/2478] base_lr: 2.8139e-06 lr: 5.6279e-06 eta: 1:55:04 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 15.3313 loss: 1.1574 2023/09/06 04:43:01 - mmengine - INFO - Epoch(train) [8][1240/2478] base_lr: 2.8027e-06 lr: 5.6055e-06 eta: 1:54:42 time: 1.1125 data_time: 0.0077 memory: 7583 grad_norm: 15.7209 loss: 1.0958 2023/09/06 04:43:23 - mmengine - INFO - Epoch(train) [8][1260/2478] base_lr: 2.7916e-06 lr: 5.5831e-06 eta: 1:54:20 time: 1.1100 data_time: 0.0078 memory: 7583 grad_norm: 15.5649 loss: 1.2702 2023/09/06 04:43:45 - mmengine - INFO - Epoch(train) [8][1280/2478] base_lr: 2.7804e-06 lr: 5.5608e-06 eta: 1:53:58 time: 1.1131 data_time: 0.0079 memory: 7583 grad_norm: 15.2889 loss: 1.0273 2023/09/06 04:44:07 - mmengine - INFO - Epoch(train) [8][1300/2478] base_lr: 2.7693e-06 lr: 5.5385e-06 eta: 1:53:35 time: 1.1084 data_time: 0.0081 memory: 7583 grad_norm: 14.9737 loss: 0.9756 2023/09/06 04:44:29 - mmengine - INFO - Epoch(train) [8][1320/2478] base_lr: 2.7581e-06 lr: 5.5163e-06 eta: 1:53:13 time: 1.1115 data_time: 0.0081 memory: 7583 grad_norm: 14.5952 loss: 0.8328 2023/09/06 04:44:52 - mmengine - INFO - Epoch(train) [8][1340/2478] base_lr: 2.7470e-06 lr: 5.4940e-06 eta: 1:52:51 time: 1.1109 data_time: 0.0079 memory: 7583 grad_norm: 15.6490 loss: 1.0979 2023/09/06 04:45:14 - mmengine - INFO - Epoch(train) [8][1360/2478] base_lr: 2.7359e-06 lr: 5.4718e-06 eta: 1:52:29 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 14.6227 loss: 1.1921 2023/09/06 04:45:36 - mmengine - INFO - Epoch(train) [8][1380/2478] base_lr: 2.7248e-06 lr: 5.4496e-06 eta: 1:52:07 time: 1.1115 data_time: 0.0083 memory: 7583 grad_norm: 14.8794 loss: 1.1125 2023/09/06 04:45:58 - mmengine - INFO - Epoch(train) [8][1400/2478] base_lr: 2.7138e-06 lr: 5.4275e-06 eta: 1:51:44 time: 1.1120 data_time: 0.0086 memory: 7583 grad_norm: 15.8876 loss: 1.1037 2023/09/06 04:46:21 - mmengine - INFO - Epoch(train) [8][1420/2478] base_lr: 2.7027e-06 lr: 5.4054e-06 eta: 1:51:22 time: 1.1116 data_time: 0.0081 memory: 7583 grad_norm: 15.1940 loss: 1.1371 2023/09/06 04:46:43 - mmengine - INFO - Epoch(train) [8][1440/2478] base_lr: 2.6916e-06 lr: 5.3833e-06 eta: 1:51:00 time: 1.1128 data_time: 0.0080 memory: 7583 grad_norm: 14.8384 loss: 1.0134 2023/09/06 04:47:05 - mmengine - INFO - Epoch(train) [8][1460/2478] base_lr: 2.6806e-06 lr: 5.3612e-06 eta: 1:50:38 time: 1.1117 data_time: 0.0080 memory: 7583 grad_norm: 14.8378 loss: 1.1853 2023/09/06 04:47:27 - mmengine - INFO - Epoch(train) [8][1480/2478] base_lr: 2.6696e-06 lr: 5.3392e-06 eta: 1:50:15 time: 1.1178 data_time: 0.0080 memory: 7583 grad_norm: 14.8108 loss: 1.1532 2023/09/06 04:47:50 - mmengine - INFO - Epoch(train) [8][1500/2478] base_lr: 2.6586e-06 lr: 5.3172e-06 eta: 1:49:53 time: 1.1121 data_time: 0.0080 memory: 7583 grad_norm: 15.1170 loss: 1.0935 2023/09/06 04:48:12 - mmengine - INFO - Epoch(train) [8][1520/2478] base_lr: 2.6476e-06 lr: 5.2953e-06 eta: 1:49:31 time: 1.1131 data_time: 0.0081 memory: 7583 grad_norm: 14.9451 loss: 1.0506 2023/09/06 04:48:34 - mmengine - INFO - Epoch(train) [8][1540/2478] base_lr: 2.6367e-06 lr: 5.2733e-06 eta: 1:49:09 time: 1.1106 data_time: 0.0081 memory: 7583 grad_norm: 15.1460 loss: 0.9641 2023/09/06 04:48:56 - mmengine - INFO - Epoch(train) [8][1560/2478] base_lr: 2.6257e-06 lr: 5.2514e-06 eta: 1:48:47 time: 1.1097 data_time: 0.0079 memory: 7583 grad_norm: 14.3496 loss: 1.1691 2023/09/06 04:49:19 - mmengine - INFO - Epoch(train) [8][1580/2478] base_lr: 2.6148e-06 lr: 5.2296e-06 eta: 1:48:24 time: 1.1116 data_time: 0.0080 memory: 7583 grad_norm: 15.1762 loss: 1.1863 2023/09/06 04:49:41 - mmengine - INFO - Epoch(train) [8][1600/2478] base_lr: 2.6039e-06 lr: 5.2077e-06 eta: 1:48:02 time: 1.1102 data_time: 0.0082 memory: 7583 grad_norm: 15.6505 loss: 1.0500 2023/09/06 04:50:03 - mmengine - INFO - Epoch(train) [8][1620/2478] base_lr: 2.5930e-06 lr: 5.1859e-06 eta: 1:47:40 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 15.6329 loss: 1.2082 2023/09/06 04:50:25 - mmengine - INFO - Epoch(train) [8][1640/2478] base_lr: 2.5821e-06 lr: 5.1641e-06 eta: 1:47:18 time: 1.1095 data_time: 0.0083 memory: 7583 grad_norm: 15.2950 loss: 1.3057 2023/09/06 04:50:41 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 04:50:47 - mmengine - INFO - Epoch(train) [8][1660/2478] base_lr: 2.5712e-06 lr: 5.1424e-06 eta: 1:46:55 time: 1.1104 data_time: 0.0080 memory: 7583 grad_norm: 14.9267 loss: 1.1080 2023/09/06 04:51:10 - mmengine - INFO - Epoch(train) [8][1680/2478] base_lr: 2.5603e-06 lr: 5.1207e-06 eta: 1:46:33 time: 1.1108 data_time: 0.0081 memory: 7583 grad_norm: 14.7457 loss: 0.9589 2023/09/06 04:51:32 - mmengine - INFO - Epoch(train) [8][1700/2478] base_lr: 2.5495e-06 lr: 5.0990e-06 eta: 1:46:11 time: 1.1130 data_time: 0.0084 memory: 7583 grad_norm: 15.2476 loss: 1.1714 2023/09/06 04:51:54 - mmengine - INFO - Epoch(train) [8][1720/2478] base_lr: 2.5387e-06 lr: 5.0774e-06 eta: 1:45:49 time: 1.1090 data_time: 0.0087 memory: 7583 grad_norm: 15.1019 loss: 1.1971 2023/09/06 04:52:16 - mmengine - INFO - Epoch(train) [8][1740/2478] base_lr: 2.5279e-06 lr: 5.0557e-06 eta: 1:45:27 time: 1.1112 data_time: 0.0085 memory: 7583 grad_norm: 15.1679 loss: 1.2071 2023/09/06 04:52:38 - mmengine - INFO - Epoch(train) [8][1760/2478] base_lr: 2.5171e-06 lr: 5.0342e-06 eta: 1:45:04 time: 1.1113 data_time: 0.0084 memory: 7583 grad_norm: 14.8404 loss: 1.0822 2023/09/06 04:53:01 - mmengine - INFO - Epoch(train) [8][1780/2478] base_lr: 2.5063e-06 lr: 5.0126e-06 eta: 1:44:42 time: 1.1080 data_time: 0.0082 memory: 7583 grad_norm: 15.1122 loss: 1.0794 2023/09/06 04:53:23 - mmengine - INFO - Epoch(train) [8][1800/2478] base_lr: 2.4955e-06 lr: 4.9911e-06 eta: 1:44:20 time: 1.1114 data_time: 0.0083 memory: 7583 grad_norm: 14.6761 loss: 0.8509 2023/09/06 04:53:45 - mmengine - INFO - Epoch(train) [8][1820/2478] base_lr: 2.4848e-06 lr: 4.9696e-06 eta: 1:43:58 time: 1.1104 data_time: 0.0084 memory: 7583 grad_norm: 14.9959 loss: 1.0256 2023/09/06 04:54:07 - mmengine - INFO - Epoch(train) [8][1840/2478] base_lr: 2.4741e-06 lr: 4.9481e-06 eta: 1:43:35 time: 1.1130 data_time: 0.0083 memory: 7583 grad_norm: 14.5416 loss: 1.0100 2023/09/06 04:54:30 - mmengine - INFO - Epoch(train) [8][1860/2478] base_lr: 2.4634e-06 lr: 4.9267e-06 eta: 1:43:13 time: 1.1094 data_time: 0.0084 memory: 7583 grad_norm: 15.3504 loss: 1.1404 2023/09/06 04:54:52 - mmengine - INFO - Epoch(train) [8][1880/2478] base_lr: 2.4527e-06 lr: 4.9053e-06 eta: 1:42:51 time: 1.1119 data_time: 0.0083 memory: 7583 grad_norm: 14.8900 loss: 1.1709 2023/09/06 04:55:14 - mmengine - INFO - Epoch(train) [8][1900/2478] base_lr: 2.4420e-06 lr: 4.8840e-06 eta: 1:42:29 time: 1.1100 data_time: 0.0084 memory: 7583 grad_norm: 15.2280 loss: 0.9934 2023/09/06 04:55:36 - mmengine - INFO - Epoch(train) [8][1920/2478] base_lr: 2.4313e-06 lr: 4.8627e-06 eta: 1:42:06 time: 1.1104 data_time: 0.0082 memory: 7583 grad_norm: 15.2542 loss: 1.2017 2023/09/06 04:55:58 - mmengine - INFO - Epoch(train) [8][1940/2478] base_lr: 2.4207e-06 lr: 4.8414e-06 eta: 1:41:44 time: 1.1143 data_time: 0.0087 memory: 7583 grad_norm: 14.9673 loss: 0.9997 2023/09/06 04:56:21 - mmengine - INFO - Epoch(train) [8][1960/2478] base_lr: 2.4101e-06 lr: 4.8201e-06 eta: 1:41:22 time: 1.1105 data_time: 0.0086 memory: 7583 grad_norm: 15.4209 loss: 1.3134 2023/09/06 04:56:43 - mmengine - INFO - Epoch(train) [8][1980/2478] base_lr: 2.3995e-06 lr: 4.7989e-06 eta: 1:41:00 time: 1.1091 data_time: 0.0085 memory: 7583 grad_norm: 15.0650 loss: 1.2988 2023/09/06 04:57:05 - mmengine - INFO - Epoch(train) [8][2000/2478] base_lr: 2.3889e-06 lr: 4.7777e-06 eta: 1:40:38 time: 1.1084 data_time: 0.0085 memory: 7583 grad_norm: 15.5204 loss: 1.2077 2023/09/06 04:57:27 - mmengine - INFO - Epoch(train) [8][2020/2478] base_lr: 2.3783e-06 lr: 4.7566e-06 eta: 1:40:15 time: 1.1083 data_time: 0.0083 memory: 7583 grad_norm: 15.3261 loss: 1.1089 2023/09/06 04:57:49 - mmengine - INFO - Epoch(train) [8][2040/2478] base_lr: 2.3677e-06 lr: 4.7355e-06 eta: 1:39:53 time: 1.1087 data_time: 0.0085 memory: 7583 grad_norm: 15.4838 loss: 1.1366 2023/09/06 04:58:12 - mmengine - INFO - Epoch(train) [8][2060/2478] base_lr: 2.3572e-06 lr: 4.7144e-06 eta: 1:39:31 time: 1.1137 data_time: 0.0097 memory: 7583 grad_norm: 16.2419 loss: 1.3807 2023/09/06 04:58:34 - mmengine - INFO - Epoch(train) [8][2080/2478] base_lr: 2.3467e-06 lr: 4.6933e-06 eta: 1:39:09 time: 1.1101 data_time: 0.0081 memory: 7583 grad_norm: 15.8356 loss: 1.0074 2023/09/06 04:58:56 - mmengine - INFO - Epoch(train) [8][2100/2478] base_lr: 2.3362e-06 lr: 4.6723e-06 eta: 1:38:46 time: 1.1134 data_time: 0.0083 memory: 7583 grad_norm: 15.1484 loss: 1.0391 2023/09/06 04:59:18 - mmengine - INFO - Epoch(train) [8][2120/2478] base_lr: 2.3257e-06 lr: 4.6514e-06 eta: 1:38:24 time: 1.1108 data_time: 0.0082 memory: 7583 grad_norm: 15.2206 loss: 1.2716 2023/09/06 04:59:41 - mmengine - INFO - Epoch(train) [8][2140/2478] base_lr: 2.3152e-06 lr: 4.6304e-06 eta: 1:38:02 time: 1.1123 data_time: 0.0082 memory: 7583 grad_norm: 14.8996 loss: 0.8487 2023/09/06 05:00:03 - mmengine - INFO - Epoch(train) [8][2160/2478] base_lr: 2.3048e-06 lr: 4.6095e-06 eta: 1:37:40 time: 1.1123 data_time: 0.0080 memory: 7583 grad_norm: 15.1346 loss: 0.9194 2023/09/06 05:00:25 - mmengine - INFO - Epoch(train) [8][2180/2478] base_lr: 2.2943e-06 lr: 4.5886e-06 eta: 1:37:18 time: 1.1130 data_time: 0.0080 memory: 7583 grad_norm: 14.5234 loss: 1.1032 2023/09/06 05:00:47 - mmengine - INFO - Epoch(train) [8][2200/2478] base_lr: 2.2839e-06 lr: 4.5678e-06 eta: 1:36:55 time: 1.1102 data_time: 0.0080 memory: 7583 grad_norm: 14.8463 loss: 1.0381 2023/09/06 05:01:09 - mmengine - INFO - Epoch(train) [8][2220/2478] base_lr: 2.2735e-06 lr: 4.5470e-06 eta: 1:36:33 time: 1.1093 data_time: 0.0080 memory: 7583 grad_norm: 14.6412 loss: 1.1349 2023/09/06 05:01:32 - mmengine - INFO - Epoch(train) [8][2240/2478] base_lr: 2.2631e-06 lr: 4.5262e-06 eta: 1:36:11 time: 1.1100 data_time: 0.0082 memory: 7583 grad_norm: 15.2880 loss: 0.8660 2023/09/06 05:01:54 - mmengine - INFO - Epoch(train) [8][2260/2478] base_lr: 2.2528e-06 lr: 4.5055e-06 eta: 1:35:49 time: 1.1108 data_time: 0.0080 memory: 7583 grad_norm: 15.2675 loss: 1.0054 2023/09/06 05:02:16 - mmengine - INFO - Epoch(train) [8][2280/2478] base_lr: 2.2424e-06 lr: 4.4848e-06 eta: 1:35:26 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 15.3542 loss: 1.2087 2023/09/06 05:02:38 - mmengine - INFO - Epoch(train) [8][2300/2478] base_lr: 2.2321e-06 lr: 4.4642e-06 eta: 1:35:04 time: 1.1109 data_time: 0.0081 memory: 7583 grad_norm: 15.5970 loss: 0.9726 2023/09/06 05:03:01 - mmengine - INFO - Epoch(train) [8][2320/2478] base_lr: 2.2218e-06 lr: 4.4435e-06 eta: 1:34:42 time: 1.1121 data_time: 0.0082 memory: 7583 grad_norm: 15.6718 loss: 1.0840 2023/09/06 05:03:23 - mmengine - INFO - Epoch(train) [8][2340/2478] base_lr: 2.2115e-06 lr: 4.4230e-06 eta: 1:34:20 time: 1.1095 data_time: 0.0083 memory: 7583 grad_norm: 15.1555 loss: 1.2013 2023/09/06 05:03:45 - mmengine - INFO - Epoch(train) [8][2360/2478] base_lr: 2.2012e-06 lr: 4.4024e-06 eta: 1:33:58 time: 1.1111 data_time: 0.0083 memory: 7583 grad_norm: 15.2102 loss: 1.1325 2023/09/06 05:04:07 - mmengine - INFO - Epoch(train) [8][2380/2478] base_lr: 2.1910e-06 lr: 4.3819e-06 eta: 1:33:35 time: 1.1115 data_time: 0.0083 memory: 7583 grad_norm: 14.9841 loss: 1.1183 2023/09/06 05:04:29 - mmengine - INFO - Epoch(train) [8][2400/2478] base_lr: 2.1807e-06 lr: 4.3614e-06 eta: 1:33:13 time: 1.1102 data_time: 0.0084 memory: 7583 grad_norm: 15.1219 loss: 0.9400 2023/09/06 05:04:52 - mmengine - INFO - Epoch(train) [8][2420/2478] base_lr: 2.1705e-06 lr: 4.3410e-06 eta: 1:32:51 time: 1.1120 data_time: 0.0086 memory: 7583 grad_norm: 15.4941 loss: 1.0550 2023/09/06 05:05:14 - mmengine - INFO - Epoch(train) [8][2440/2478] base_lr: 2.1603e-06 lr: 4.3206e-06 eta: 1:32:29 time: 1.1126 data_time: 0.0081 memory: 7583 grad_norm: 15.3939 loss: 1.1497 2023/09/06 05:05:36 - mmengine - INFO - Epoch(train) [8][2460/2478] base_lr: 2.1501e-06 lr: 4.3002e-06 eta: 1:32:06 time: 1.1116 data_time: 0.0080 memory: 7583 grad_norm: 14.9909 loss: 0.9275 2023/09/06 05:05:56 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 05:05:56 - mmengine - INFO - Epoch(train) [8][2478/2478] base_lr: 2.1410e-06 lr: 4.2819e-06 eta: 1:31:46 time: 1.1071 data_time: 0.0085 memory: 7583 grad_norm: 15.5799 loss: 0.9762 2023/09/06 05:05:56 - mmengine - INFO - Saving checkpoint at 8 epochs 2023/09/06 05:06:27 - mmengine - INFO - Epoch(val) [8][20/96] eta: 0:01:22 time: 1.0820 data_time: 0.0383 memory: 8884 2023/09/06 05:06:48 - mmengine - INFO - Epoch(val) [8][40/96] eta: 0:00:59 time: 1.0486 data_time: 0.0065 memory: 8884 2023/09/06 05:07:09 - mmengine - INFO - Epoch(val) [8][60/96] eta: 0:00:38 time: 1.0523 data_time: 0.0064 memory: 8884 2023/09/06 05:07:30 - mmengine - INFO - Epoch(val) [8][80/96] eta: 0:00:16 time: 1.0453 data_time: 0.0066 memory: 8884 2023/09/06 05:07:47 - mmengine - INFO - Epoch(val) [8][96/96] VQA/acc: 42.3766 data_time: 0.0131 time: 1.0545 2023/09/06 05:08:09 - mmengine - INFO - Epoch(train) [9][ 20/2478] base_lr: 2.1308e-06 lr: 4.2617e-06 eta: 1:31:24 time: 1.1276 data_time: 0.0216 memory: 8884 grad_norm: 13.8388 loss: 0.8565 2023/09/06 05:08:32 - mmengine - INFO - Epoch(train) [9][ 40/2478] base_lr: 2.1207e-06 lr: 4.2414e-06 eta: 1:31:02 time: 1.1098 data_time: 0.0080 memory: 7583 grad_norm: 13.7452 loss: 0.8846 2023/09/06 05:08:54 - mmengine - INFO - Epoch(train) [9][ 60/2478] base_lr: 2.1106e-06 lr: 4.2212e-06 eta: 1:30:40 time: 1.1103 data_time: 0.0080 memory: 7583 grad_norm: 14.0869 loss: 0.8771 2023/09/06 05:09:16 - mmengine - INFO - Epoch(train) [9][ 80/2478] base_lr: 2.1005e-06 lr: 4.2010e-06 eta: 1:30:18 time: 1.1109 data_time: 0.0082 memory: 7583 grad_norm: 14.1848 loss: 1.0074 2023/09/06 05:09:38 - mmengine - INFO - Epoch(train) [9][ 100/2478] base_lr: 2.0904e-06 lr: 4.1809e-06 eta: 1:29:55 time: 1.1113 data_time: 0.0077 memory: 7583 grad_norm: 14.1778 loss: 1.0442 2023/09/06 05:10:01 - mmengine - INFO - Epoch(train) [9][ 120/2478] base_lr: 2.0804e-06 lr: 4.1608e-06 eta: 1:29:33 time: 1.1106 data_time: 0.0080 memory: 7583 grad_norm: 14.3000 loss: 0.8973 2023/09/06 05:10:23 - mmengine - INFO - Epoch(train) [9][ 140/2478] base_lr: 2.0703e-06 lr: 4.1407e-06 eta: 1:29:11 time: 1.1094 data_time: 0.0078 memory: 7583 grad_norm: 14.5370 loss: 0.9119 2023/09/06 05:10:45 - mmengine - INFO - Epoch(train) [9][ 160/2478] base_lr: 2.0603e-06 lr: 4.1207e-06 eta: 1:28:49 time: 1.1100 data_time: 0.0077 memory: 7583 grad_norm: 14.9859 loss: 1.0106 2023/09/06 05:11:03 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 05:11:07 - mmengine - INFO - Epoch(train) [9][ 180/2478] base_lr: 2.0503e-06 lr: 4.1007e-06 eta: 1:28:26 time: 1.1124 data_time: 0.0078 memory: 7583 grad_norm: 13.5888 loss: 0.7108 2023/09/06 05:11:29 - mmengine - INFO - Epoch(train) [9][ 200/2478] base_lr: 2.0404e-06 lr: 4.0807e-06 eta: 1:28:04 time: 1.1093 data_time: 0.0080 memory: 7583 grad_norm: 14.4109 loss: 0.8323 2023/09/06 05:11:52 - mmengine - INFO - Epoch(train) [9][ 220/2478] base_lr: 2.0304e-06 lr: 4.0608e-06 eta: 1:27:42 time: 1.1091 data_time: 0.0080 memory: 7583 grad_norm: 14.1866 loss: 0.9552 2023/09/06 05:12:14 - mmengine - INFO - Epoch(train) [9][ 240/2478] base_lr: 2.0205e-06 lr: 4.0410e-06 eta: 1:27:20 time: 1.1126 data_time: 0.0088 memory: 7583 grad_norm: 15.0978 loss: 0.9319 2023/09/06 05:12:36 - mmengine - INFO - Epoch(train) [9][ 260/2478] base_lr: 2.0106e-06 lr: 4.0211e-06 eta: 1:26:58 time: 1.1124 data_time: 0.0080 memory: 7583 grad_norm: 14.4840 loss: 0.9004 2023/09/06 05:12:58 - mmengine - INFO - Epoch(train) [9][ 280/2478] base_lr: 2.0007e-06 lr: 4.0013e-06 eta: 1:26:35 time: 1.1099 data_time: 0.0081 memory: 7583 grad_norm: 14.3461 loss: 1.1690 2023/09/06 05:13:21 - mmengine - INFO - Epoch(train) [9][ 300/2478] base_lr: 1.9908e-06 lr: 3.9816e-06 eta: 1:26:13 time: 1.1133 data_time: 0.0085 memory: 7583 grad_norm: 14.2091 loss: 0.8905 2023/09/06 05:13:43 - mmengine - INFO - Epoch(train) [9][ 320/2478] base_lr: 1.9809e-06 lr: 3.9619e-06 eta: 1:25:51 time: 1.1107 data_time: 0.0081 memory: 7583 grad_norm: 13.5211 loss: 0.8150 2023/09/06 05:14:05 - mmengine - INFO - Epoch(train) [9][ 340/2478] base_lr: 1.9711e-06 lr: 3.9422e-06 eta: 1:25:29 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 14.7289 loss: 0.8382 2023/09/06 05:14:27 - mmengine - INFO - Epoch(train) [9][ 360/2478] base_lr: 1.9613e-06 lr: 3.9225e-06 eta: 1:25:06 time: 1.1103 data_time: 0.0078 memory: 7583 grad_norm: 14.3118 loss: 1.1871 2023/09/06 05:14:49 - mmengine - INFO - Epoch(train) [9][ 380/2478] base_lr: 1.9515e-06 lr: 3.9029e-06 eta: 1:24:44 time: 1.1094 data_time: 0.0078 memory: 7583 grad_norm: 14.6985 loss: 0.9652 2023/09/06 05:15:12 - mmengine - INFO - Epoch(train) [9][ 400/2478] base_lr: 1.9417e-06 lr: 3.8834e-06 eta: 1:24:22 time: 1.1157 data_time: 0.0078 memory: 7583 grad_norm: 14.6316 loss: 0.9308 2023/09/06 05:15:34 - mmengine - INFO - Epoch(train) [9][ 420/2478] base_lr: 1.9319e-06 lr: 3.8639e-06 eta: 1:24:00 time: 1.1119 data_time: 0.0077 memory: 7583 grad_norm: 13.7251 loss: 0.9102 2023/09/06 05:15:56 - mmengine - INFO - Epoch(train) [9][ 440/2478] base_lr: 1.9222e-06 lr: 3.8444e-06 eta: 1:23:38 time: 1.1147 data_time: 0.0079 memory: 7583 grad_norm: 14.5426 loss: 1.0129 2023/09/06 05:16:18 - mmengine - INFO - Epoch(train) [9][ 460/2478] base_lr: 1.9125e-06 lr: 3.8250e-06 eta: 1:23:15 time: 1.1108 data_time: 0.0082 memory: 7583 grad_norm: 15.2774 loss: 1.1206 2023/09/06 05:16:41 - mmengine - INFO - Epoch(train) [9][ 480/2478] base_lr: 1.9028e-06 lr: 3.8056e-06 eta: 1:22:53 time: 1.1127 data_time: 0.0081 memory: 7583 grad_norm: 14.4546 loss: 0.7690 2023/09/06 05:17:03 - mmengine - INFO - Epoch(train) [9][ 500/2478] base_lr: 1.8931e-06 lr: 3.7862e-06 eta: 1:22:31 time: 1.1117 data_time: 0.0083 memory: 7583 grad_norm: 15.2559 loss: 1.0734 2023/09/06 05:17:25 - mmengine - INFO - Epoch(train) [9][ 520/2478] base_lr: 1.8835e-06 lr: 3.7669e-06 eta: 1:22:09 time: 1.1114 data_time: 0.0080 memory: 7583 grad_norm: 14.4396 loss: 0.9759 2023/09/06 05:17:47 - mmengine - INFO - Epoch(train) [9][ 540/2478] base_lr: 1.8738e-06 lr: 3.7476e-06 eta: 1:21:46 time: 1.1085 data_time: 0.0079 memory: 7583 grad_norm: 14.4848 loss: 0.9592 2023/09/06 05:18:10 - mmengine - INFO - Epoch(train) [9][ 560/2478] base_lr: 1.8642e-06 lr: 3.7284e-06 eta: 1:21:24 time: 1.1121 data_time: 0.0081 memory: 7583 grad_norm: 14.1401 loss: 0.8548 2023/09/06 05:18:32 - mmengine - INFO - Epoch(train) [9][ 580/2478] base_lr: 1.8546e-06 lr: 3.7092e-06 eta: 1:21:02 time: 1.1136 data_time: 0.0080 memory: 7583 grad_norm: 14.4173 loss: 0.9201 2023/09/06 05:18:54 - mmengine - INFO - Epoch(train) [9][ 600/2478] base_lr: 1.8450e-06 lr: 3.6901e-06 eta: 1:20:40 time: 1.1109 data_time: 0.0080 memory: 7583 grad_norm: 14.5315 loss: 0.8805 2023/09/06 05:19:16 - mmengine - INFO - Epoch(train) [9][ 620/2478] base_lr: 1.8355e-06 lr: 3.6709e-06 eta: 1:20:18 time: 1.1095 data_time: 0.0078 memory: 7583 grad_norm: 14.8686 loss: 0.8312 2023/09/06 05:19:38 - mmengine - INFO - Epoch(train) [9][ 640/2478] base_lr: 1.8259e-06 lr: 3.6519e-06 eta: 1:19:55 time: 1.1108 data_time: 0.0079 memory: 7583 grad_norm: 14.8493 loss: 0.9654 2023/09/06 05:20:01 - mmengine - INFO - Epoch(train) [9][ 660/2478] base_lr: 1.8164e-06 lr: 3.6328e-06 eta: 1:19:33 time: 1.1118 data_time: 0.0079 memory: 7583 grad_norm: 14.8785 loss: 1.1050 2023/09/06 05:20:23 - mmengine - INFO - Epoch(train) [9][ 680/2478] base_lr: 1.8069e-06 lr: 3.6139e-06 eta: 1:19:11 time: 1.1103 data_time: 0.0077 memory: 7583 grad_norm: 14.1163 loss: 0.9458 2023/09/06 05:20:45 - mmengine - INFO - Epoch(train) [9][ 700/2478] base_lr: 1.7975e-06 lr: 3.5949e-06 eta: 1:18:49 time: 1.1105 data_time: 0.0082 memory: 7583 grad_norm: 14.8252 loss: 0.7873 2023/09/06 05:21:07 - mmengine - INFO - Epoch(train) [9][ 720/2478] base_lr: 1.7880e-06 lr: 3.5760e-06 eta: 1:18:26 time: 1.1107 data_time: 0.0082 memory: 7583 grad_norm: 14.6955 loss: 0.7595 2023/09/06 05:21:30 - mmengine - INFO - Epoch(train) [9][ 740/2478] base_lr: 1.7786e-06 lr: 3.5572e-06 eta: 1:18:04 time: 1.1178 data_time: 0.0079 memory: 7583 grad_norm: 14.3048 loss: 0.8313 2023/09/06 05:21:52 - mmengine - INFO - Epoch(train) [9][ 760/2478] base_lr: 1.7692e-06 lr: 3.5383e-06 eta: 1:17:42 time: 1.1098 data_time: 0.0078 memory: 7583 grad_norm: 15.0361 loss: 0.9740 2023/09/06 05:22:14 - mmengine - INFO - Epoch(train) [9][ 780/2478] base_lr: 1.7598e-06 lr: 3.5196e-06 eta: 1:17:20 time: 1.1087 data_time: 0.0078 memory: 7583 grad_norm: 14.5090 loss: 0.8354 2023/09/06 05:22:36 - mmengine - INFO - Epoch(train) [9][ 800/2478] base_lr: 1.7504e-06 lr: 3.5008e-06 eta: 1:16:58 time: 1.1109 data_time: 0.0078 memory: 7583 grad_norm: 14.7717 loss: 0.9699 2023/09/06 05:22:58 - mmengine - INFO - Epoch(train) [9][ 820/2478] base_lr: 1.7411e-06 lr: 3.4821e-06 eta: 1:16:35 time: 1.1113 data_time: 0.0080 memory: 7583 grad_norm: 14.5888 loss: 1.0271 2023/09/06 05:23:21 - mmengine - INFO - Epoch(train) [9][ 840/2478] base_lr: 1.7317e-06 lr: 3.4635e-06 eta: 1:16:13 time: 1.1104 data_time: 0.0080 memory: 7583 grad_norm: 15.3320 loss: 0.8959 2023/09/06 05:23:43 - mmengine - INFO - Epoch(train) [9][ 860/2478] base_lr: 1.7224e-06 lr: 3.4449e-06 eta: 1:15:51 time: 1.1113 data_time: 0.0079 memory: 7583 grad_norm: 14.0849 loss: 0.8194 2023/09/06 05:24:05 - mmengine - INFO - Epoch(train) [9][ 880/2478] base_lr: 1.7132e-06 lr: 3.4263e-06 eta: 1:15:29 time: 1.1067 data_time: 0.0082 memory: 7583 grad_norm: 14.4484 loss: 0.8894 2023/09/06 05:24:27 - mmengine - INFO - Epoch(train) [9][ 900/2478] base_lr: 1.7039e-06 lr: 3.4078e-06 eta: 1:15:06 time: 1.1123 data_time: 0.0091 memory: 7583 grad_norm: 14.2431 loss: 0.9545 2023/09/06 05:24:50 - mmengine - INFO - Epoch(train) [9][ 920/2478] base_lr: 1.6947e-06 lr: 3.3893e-06 eta: 1:14:44 time: 1.1108 data_time: 0.0091 memory: 7583 grad_norm: 14.3394 loss: 0.7753 2023/09/06 05:25:12 - mmengine - INFO - Epoch(train) [9][ 940/2478] base_lr: 1.6854e-06 lr: 3.3709e-06 eta: 1:14:22 time: 1.1090 data_time: 0.0083 memory: 7583 grad_norm: 14.7473 loss: 0.8038 2023/09/06 05:25:34 - mmengine - INFO - Epoch(train) [9][ 960/2478] base_lr: 1.6763e-06 lr: 3.3525e-06 eta: 1:14:00 time: 1.1084 data_time: 0.0082 memory: 7583 grad_norm: 14.8228 loss: 1.1346 2023/09/06 05:25:56 - mmengine - INFO - Epoch(train) [9][ 980/2478] base_lr: 1.6671e-06 lr: 3.3342e-06 eta: 1:13:38 time: 1.1094 data_time: 0.0083 memory: 7583 grad_norm: 15.0670 loss: 0.9801 2023/09/06 05:26:18 - mmengine - INFO - Epoch(train) [9][1000/2478] base_lr: 1.6579e-06 lr: 3.3159e-06 eta: 1:13:15 time: 1.1062 data_time: 0.0081 memory: 7583 grad_norm: inf loss: 1.0622 2023/09/06 05:26:40 - mmengine - INFO - Epoch(train) [9][1020/2478] base_lr: 1.6488e-06 lr: 3.2976e-06 eta: 1:12:53 time: 1.1109 data_time: 0.0087 memory: 7583 grad_norm: 14.0124 loss: 0.9819 2023/09/06 05:27:03 - mmengine - INFO - Epoch(train) [9][1040/2478] base_lr: 1.6397e-06 lr: 3.2794e-06 eta: 1:12:31 time: 1.1096 data_time: 0.0080 memory: 7583 grad_norm: 14.2879 loss: 0.8665 2023/09/06 05:27:25 - mmengine - INFO - Epoch(train) [9][1060/2478] base_lr: 1.6306e-06 lr: 3.2612e-06 eta: 1:12:09 time: 1.1091 data_time: 0.0081 memory: 7583 grad_norm: 14.9248 loss: 1.0162 2023/09/06 05:27:47 - mmengine - INFO - Epoch(train) [9][1080/2478] base_lr: 1.6215e-06 lr: 3.2431e-06 eta: 1:11:46 time: 1.1091 data_time: 0.0080 memory: 7583 grad_norm: 15.3913 loss: 1.0131 2023/09/06 05:28:09 - mmengine - INFO - Epoch(train) [9][1100/2478] base_lr: 1.6125e-06 lr: 3.2250e-06 eta: 1:11:24 time: 1.1100 data_time: 0.0086 memory: 7583 grad_norm: 14.6960 loss: 0.8596 2023/09/06 05:28:31 - mmengine - INFO - Epoch(train) [9][1120/2478] base_lr: 1.6035e-06 lr: 3.2069e-06 eta: 1:11:02 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 14.4437 loss: 0.8880 2023/09/06 05:28:54 - mmengine - INFO - Epoch(train) [9][1140/2478] base_lr: 1.5945e-06 lr: 3.1890e-06 eta: 1:10:40 time: 1.1085 data_time: 0.0085 memory: 7583 grad_norm: 15.0388 loss: 0.9628 2023/09/06 05:29:16 - mmengine - INFO - Epoch(train) [9][1160/2478] base_lr: 1.5855e-06 lr: 3.1710e-06 eta: 1:10:17 time: 1.1124 data_time: 0.0084 memory: 7583 grad_norm: 14.7581 loss: 0.8295 2023/09/06 05:29:34 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 05:29:38 - mmengine - INFO - Epoch(train) [9][1180/2478] base_lr: 1.5765e-06 lr: 3.1531e-06 eta: 1:09:55 time: 1.1129 data_time: 0.0081 memory: 7583 grad_norm: 14.3561 loss: 1.1558 2023/09/06 05:30:00 - mmengine - INFO - Epoch(train) [9][1200/2478] base_lr: 1.5676e-06 lr: 3.1352e-06 eta: 1:09:33 time: 1.1104 data_time: 0.0079 memory: 7583 grad_norm: 14.7789 loss: 1.0324 2023/09/06 05:30:22 - mmengine - INFO - Epoch(train) [9][1220/2478] base_lr: 1.5587e-06 lr: 3.1174e-06 eta: 1:09:11 time: 1.1101 data_time: 0.0080 memory: 7583 grad_norm: 14.5636 loss: 0.7737 2023/09/06 05:30:45 - mmengine - INFO - Epoch(train) [9][1240/2478] base_lr: 1.5498e-06 lr: 3.0996e-06 eta: 1:08:49 time: 1.1110 data_time: 0.0082 memory: 7583 grad_norm: 14.7850 loss: 0.7980 2023/09/06 05:31:07 - mmengine - INFO - Epoch(train) [9][1260/2478] base_lr: 1.5410e-06 lr: 3.0819e-06 eta: 1:08:26 time: 1.1131 data_time: 0.0080 memory: 7583 grad_norm: 14.5573 loss: 0.9457 2023/09/06 05:31:29 - mmengine - INFO - Epoch(train) [9][1280/2478] base_lr: 1.5321e-06 lr: 3.0642e-06 eta: 1:08:04 time: 1.1093 data_time: 0.0082 memory: 7583 grad_norm: 14.3321 loss: 1.1024 2023/09/06 05:31:51 - mmengine - INFO - Epoch(train) [9][1300/2478] base_lr: 1.5233e-06 lr: 3.0466e-06 eta: 1:07:42 time: 1.1122 data_time: 0.0080 memory: 7583 grad_norm: 14.6692 loss: 1.0405 2023/09/06 05:32:14 - mmengine - INFO - Epoch(train) [9][1320/2478] base_lr: 1.5145e-06 lr: 3.0290e-06 eta: 1:07:20 time: 1.1102 data_time: 0.0079 memory: 7583 grad_norm: 15.2611 loss: 0.9219 2023/09/06 05:32:36 - mmengine - INFO - Epoch(train) [9][1340/2478] base_lr: 1.5057e-06 lr: 3.0115e-06 eta: 1:06:57 time: 1.1137 data_time: 0.0082 memory: 7583 grad_norm: 14.7270 loss: 0.7578 2023/09/06 05:32:58 - mmengine - INFO - Epoch(train) [9][1360/2478] base_lr: 1.4970e-06 lr: 2.9940e-06 eta: 1:06:35 time: 1.1116 data_time: 0.0079 memory: 7583 grad_norm: 15.2961 loss: 1.0242 2023/09/06 05:33:20 - mmengine - INFO - Epoch(train) [9][1380/2478] base_lr: 1.4883e-06 lr: 2.9765e-06 eta: 1:06:13 time: 1.1142 data_time: 0.0084 memory: 7583 grad_norm: 15.5796 loss: 1.1824 2023/09/06 05:33:43 - mmengine - INFO - Epoch(train) [9][1400/2478] base_lr: 1.4795e-06 lr: 2.9591e-06 eta: 1:05:51 time: 1.1094 data_time: 0.0084 memory: 7583 grad_norm: 15.0552 loss: 0.9823 2023/09/06 05:34:05 - mmengine - INFO - Epoch(train) [9][1420/2478] base_lr: 1.4709e-06 lr: 2.9417e-06 eta: 1:05:29 time: 1.1112 data_time: 0.0088 memory: 7583 grad_norm: 14.9362 loss: 0.9163 2023/09/06 05:34:27 - mmengine - INFO - Epoch(train) [9][1440/2478] base_lr: 1.4622e-06 lr: 2.9244e-06 eta: 1:05:06 time: 1.1122 data_time: 0.0083 memory: 7583 grad_norm: 14.7148 loss: 0.8611 2023/09/06 05:34:49 - mmengine - INFO - Epoch(train) [9][1460/2478] base_lr: 1.4536e-06 lr: 2.9071e-06 eta: 1:04:44 time: 1.1100 data_time: 0.0081 memory: 7583 grad_norm: 14.7148 loss: 0.7725 2023/09/06 05:35:11 - mmengine - INFO - Epoch(train) [9][1480/2478] base_lr: 1.4450e-06 lr: 2.8899e-06 eta: 1:04:22 time: 1.1091 data_time: 0.0081 memory: 7583 grad_norm: 14.5440 loss: 0.9024 2023/09/06 05:35:34 - mmengine - INFO - Epoch(train) [9][1500/2478] base_lr: 1.4364e-06 lr: 2.8727e-06 eta: 1:04:00 time: 1.1121 data_time: 0.0081 memory: 7583 grad_norm: 14.5642 loss: 1.0382 2023/09/06 05:35:56 - mmengine - INFO - Epoch(train) [9][1520/2478] base_lr: 1.4278e-06 lr: 2.8556e-06 eta: 1:03:37 time: 1.1114 data_time: 0.0083 memory: 7583 grad_norm: 15.5739 loss: 0.9323 2023/09/06 05:36:18 - mmengine - INFO - Epoch(train) [9][1540/2478] base_lr: 1.4193e-06 lr: 2.8385e-06 eta: 1:03:15 time: 1.1112 data_time: 0.0082 memory: 7583 grad_norm: 14.6464 loss: 0.9865 2023/09/06 05:36:40 - mmengine - INFO - Epoch(train) [9][1560/2478] base_lr: 1.4107e-06 lr: 2.8215e-06 eta: 1:02:53 time: 1.1087 data_time: 0.0083 memory: 7583 grad_norm: 14.8720 loss: 0.9257 2023/09/06 05:37:03 - mmengine - INFO - Epoch(train) [9][1580/2478] base_lr: 1.4022e-06 lr: 2.8045e-06 eta: 1:02:31 time: 1.1110 data_time: 0.0099 memory: 7583 grad_norm: 14.7821 loss: 0.8286 2023/09/06 05:37:25 - mmengine - INFO - Epoch(train) [9][1600/2478] base_lr: 1.3938e-06 lr: 2.7875e-06 eta: 1:02:09 time: 1.1124 data_time: 0.0086 memory: 7583 grad_norm: 14.9420 loss: 1.1384 2023/09/06 05:37:47 - mmengine - INFO - Epoch(train) [9][1620/2478] base_lr: 1.3853e-06 lr: 2.7706e-06 eta: 1:01:46 time: 1.1103 data_time: 0.0083 memory: 7583 grad_norm: 14.7655 loss: 0.8743 2023/09/06 05:38:09 - mmengine - INFO - Epoch(train) [9][1640/2478] base_lr: 1.3769e-06 lr: 2.7538e-06 eta: 1:01:24 time: 1.1083 data_time: 0.0085 memory: 7583 grad_norm: 14.6834 loss: 1.0080 2023/09/06 05:38:31 - mmengine - INFO - Epoch(train) [9][1660/2478] base_lr: 1.3685e-06 lr: 2.7370e-06 eta: 1:01:02 time: 1.1157 data_time: 0.0086 memory: 7583 grad_norm: 15.6531 loss: 1.0061 2023/09/06 05:38:54 - mmengine - INFO - Epoch(train) [9][1680/2478] base_lr: 1.3601e-06 lr: 2.7202e-06 eta: 1:00:40 time: 1.1070 data_time: 0.0083 memory: 7583 grad_norm: 15.1856 loss: 0.6789 2023/09/06 05:39:16 - mmengine - INFO - Epoch(train) [9][1700/2478] base_lr: 1.3518e-06 lr: 2.7035e-06 eta: 1:00:17 time: 1.1128 data_time: 0.0083 memory: 7583 grad_norm: 15.1177 loss: 0.9321 2023/09/06 05:39:38 - mmengine - INFO - Epoch(train) [9][1720/2478] base_lr: 1.3434e-06 lr: 2.6869e-06 eta: 0:59:55 time: 1.1106 data_time: 0.0082 memory: 7583 grad_norm: 15.1322 loss: 1.0033 2023/09/06 05:40:00 - mmengine - INFO - Epoch(train) [9][1740/2478] base_lr: 1.3351e-06 lr: 2.6702e-06 eta: 0:59:33 time: 1.1079 data_time: 0.0079 memory: 7583 grad_norm: 14.8191 loss: 1.0381 2023/09/06 05:40:22 - mmengine - INFO - Epoch(train) [9][1760/2478] base_lr: 1.3268e-06 lr: 2.6537e-06 eta: 0:59:11 time: 1.1109 data_time: 0.0081 memory: 7583 grad_norm: 14.3069 loss: 1.0309 2023/09/06 05:40:45 - mmengine - INFO - Epoch(train) [9][1780/2478] base_lr: 1.3186e-06 lr: 2.6372e-06 eta: 0:58:49 time: 1.1100 data_time: 0.0080 memory: 7583 grad_norm: 15.1252 loss: 0.8989 2023/09/06 05:41:07 - mmengine - INFO - Epoch(train) [9][1800/2478] base_lr: 1.3103e-06 lr: 2.6207e-06 eta: 0:58:26 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 14.7606 loss: 1.0748 2023/09/06 05:41:29 - mmengine - INFO - Epoch(train) [9][1820/2478] base_lr: 1.3021e-06 lr: 2.6043e-06 eta: 0:58:04 time: 1.1137 data_time: 0.0082 memory: 7583 grad_norm: 15.0189 loss: 0.9364 2023/09/06 05:41:51 - mmengine - INFO - Epoch(train) [9][1840/2478] base_lr: 1.2939e-06 lr: 2.5879e-06 eta: 0:57:42 time: 1.1117 data_time: 0.0081 memory: 7583 grad_norm: 14.6977 loss: 0.9534 2023/09/06 05:42:14 - mmengine - INFO - Epoch(train) [9][1860/2478] base_lr: 1.2858e-06 lr: 2.5716e-06 eta: 0:57:20 time: 1.1131 data_time: 0.0078 memory: 7583 grad_norm: 14.6014 loss: 0.7390 2023/09/06 05:42:36 - mmengine - INFO - Epoch(train) [9][1880/2478] base_lr: 1.2776e-06 lr: 2.5553e-06 eta: 0:56:57 time: 1.1129 data_time: 0.0080 memory: 7583 grad_norm: 14.5624 loss: 0.7626 2023/09/06 05:42:58 - mmengine - INFO - Epoch(train) [9][1900/2478] base_lr: 1.2695e-06 lr: 2.5391e-06 eta: 0:56:35 time: 1.1151 data_time: 0.0083 memory: 7583 grad_norm: 15.1025 loss: 0.9131 2023/09/06 05:43:20 - mmengine - INFO - Epoch(train) [9][1920/2478] base_lr: 1.2614e-06 lr: 2.5229e-06 eta: 0:56:13 time: 1.1106 data_time: 0.0080 memory: 7583 grad_norm: 14.7639 loss: 1.0537 2023/09/06 05:43:43 - mmengine - INFO - Epoch(train) [9][1940/2478] base_lr: 1.2534e-06 lr: 2.5068e-06 eta: 0:55:51 time: 1.1086 data_time: 0.0081 memory: 7583 grad_norm: 14.8694 loss: 1.0444 2023/09/06 05:44:05 - mmengine - INFO - Epoch(train) [9][1960/2478] base_lr: 1.2453e-06 lr: 2.4907e-06 eta: 0:55:29 time: 1.1144 data_time: 0.0079 memory: 7583 grad_norm: 15.1536 loss: 1.0121 2023/09/06 05:44:27 - mmengine - INFO - Epoch(train) [9][1980/2478] base_lr: 1.2373e-06 lr: 2.4746e-06 eta: 0:55:06 time: 1.1115 data_time: 0.0080 memory: 7583 grad_norm: 14.1308 loss: 0.8346 2023/09/06 05:44:49 - mmengine - INFO - Epoch(train) [9][2000/2478] base_lr: 1.2293e-06 lr: 2.4587e-06 eta: 0:54:44 time: 1.1122 data_time: 0.0081 memory: 7583 grad_norm: 14.6242 loss: 0.9565 2023/09/06 05:45:12 - mmengine - INFO - Epoch(train) [9][2020/2478] base_lr: 1.2214e-06 lr: 2.4427e-06 eta: 0:54:22 time: 1.1096 data_time: 0.0080 memory: 7583 grad_norm: 14.9065 loss: 1.0738 2023/09/06 05:45:34 - mmengine - INFO - Epoch(train) [9][2040/2478] base_lr: 1.2134e-06 lr: 2.4268e-06 eta: 0:54:00 time: 1.1111 data_time: 0.0082 memory: 7583 grad_norm: 14.5381 loss: 0.8238 2023/09/06 05:45:56 - mmengine - INFO - Epoch(train) [9][2060/2478] base_lr: 1.2055e-06 lr: 2.4110e-06 eta: 0:53:37 time: 1.1105 data_time: 0.0081 memory: 7583 grad_norm: 14.5864 loss: 1.0460 2023/09/06 05:46:18 - mmengine - INFO - Epoch(train) [9][2080/2478] base_lr: 1.1976e-06 lr: 2.3952e-06 eta: 0:53:15 time: 1.1108 data_time: 0.0085 memory: 7583 grad_norm: 15.3344 loss: 0.9796 2023/09/06 05:46:40 - mmengine - INFO - Epoch(train) [9][2100/2478] base_lr: 1.1897e-06 lr: 2.3795e-06 eta: 0:52:53 time: 1.1102 data_time: 0.0083 memory: 7583 grad_norm: 14.7500 loss: 0.8188 2023/09/06 05:47:03 - mmengine - INFO - Epoch(train) [9][2120/2478] base_lr: 1.1819e-06 lr: 2.3638e-06 eta: 0:52:31 time: 1.1126 data_time: 0.0082 memory: 7583 grad_norm: 15.1610 loss: 1.1201 2023/09/06 05:47:25 - mmengine - INFO - Epoch(train) [9][2140/2478] base_lr: 1.1741e-06 lr: 2.3481e-06 eta: 0:52:09 time: 1.1127 data_time: 0.0078 memory: 7583 grad_norm: 15.3622 loss: 1.1352 2023/09/06 05:47:47 - mmengine - INFO - Epoch(train) [9][2160/2478] base_lr: 1.1663e-06 lr: 2.3326e-06 eta: 0:51:46 time: 1.1085 data_time: 0.0079 memory: 7583 grad_norm: 15.1489 loss: 1.0246 2023/09/06 05:48:05 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 05:48:09 - mmengine - INFO - Epoch(train) [9][2180/2478] base_lr: 1.1585e-06 lr: 2.3170e-06 eta: 0:51:24 time: 1.1081 data_time: 0.0080 memory: 7583 grad_norm: 15.0634 loss: 0.8720 2023/09/06 05:48:31 - mmengine - INFO - Epoch(train) [9][2200/2478] base_lr: 1.1508e-06 lr: 2.3015e-06 eta: 0:51:02 time: 1.1101 data_time: 0.0079 memory: 7583 grad_norm: 14.7911 loss: 1.0381 2023/09/06 05:48:54 - mmengine - INFO - Epoch(train) [9][2220/2478] base_lr: 1.1430e-06 lr: 2.2861e-06 eta: 0:50:40 time: 1.1098 data_time: 0.0083 memory: 7583 grad_norm: 14.9611 loss: 0.9197 2023/09/06 05:49:16 - mmengine - INFO - Epoch(train) [9][2240/2478] base_lr: 1.1354e-06 lr: 2.2707e-06 eta: 0:50:17 time: 1.1102 data_time: 0.0102 memory: 7583 grad_norm: 15.4558 loss: 1.0212 2023/09/06 05:49:38 - mmengine - INFO - Epoch(train) [9][2260/2478] base_lr: 1.1277e-06 lr: 2.2554e-06 eta: 0:49:55 time: 1.1116 data_time: 0.0083 memory: 7583 grad_norm: 14.2068 loss: 0.8033 2023/09/06 05:50:00 - mmengine - INFO - Epoch(train) [9][2280/2478] base_lr: 1.1200e-06 lr: 2.2401e-06 eta: 0:49:33 time: 1.1097 data_time: 0.0084 memory: 7583 grad_norm: 14.0976 loss: 0.7881 2023/09/06 05:50:23 - mmengine - INFO - Epoch(train) [9][2300/2478] base_lr: 1.1124e-06 lr: 2.2248e-06 eta: 0:49:11 time: 1.1132 data_time: 0.0083 memory: 7583 grad_norm: 14.9854 loss: 0.8725 2023/09/06 05:50:45 - mmengine - INFO - Epoch(train) [9][2320/2478] base_lr: 1.1048e-06 lr: 2.2097e-06 eta: 0:48:49 time: 1.1102 data_time: 0.0082 memory: 7583 grad_norm: 14.7624 loss: 0.9454 2023/09/06 05:51:07 - mmengine - INFO - Epoch(train) [9][2340/2478] base_lr: 1.0973e-06 lr: 2.1945e-06 eta: 0:48:26 time: 1.1098 data_time: 0.0083 memory: 7583 grad_norm: 15.2662 loss: 0.8420 2023/09/06 05:51:29 - mmengine - INFO - Epoch(train) [9][2360/2478] base_lr: 1.0897e-06 lr: 2.1794e-06 eta: 0:48:04 time: 1.1082 data_time: 0.0080 memory: 7583 grad_norm: 15.0722 loss: 1.0141 2023/09/06 05:51:51 - mmengine - INFO - Epoch(train) [9][2380/2478] base_lr: 1.0822e-06 lr: 2.1644e-06 eta: 0:47:42 time: 1.1095 data_time: 0.0082 memory: 7583 grad_norm: 15.1539 loss: 0.8558 2023/09/06 05:52:14 - mmengine - INFO - Epoch(train) [9][2400/2478] base_lr: 1.0747e-06 lr: 2.1494e-06 eta: 0:47:20 time: 1.1120 data_time: 0.0080 memory: 7583 grad_norm: 15.4495 loss: 0.8717 2023/09/06 05:52:36 - mmengine - INFO - Epoch(train) [9][2420/2478] base_lr: 1.0672e-06 lr: 2.1345e-06 eta: 0:46:57 time: 1.1092 data_time: 0.0085 memory: 7583 grad_norm: 15.1430 loss: 1.1878 2023/09/06 05:52:58 - mmengine - INFO - Epoch(train) [9][2440/2478] base_lr: 1.0598e-06 lr: 2.1196e-06 eta: 0:46:35 time: 1.1125 data_time: 0.0081 memory: 7583 grad_norm: 15.4924 loss: 0.8808 2023/09/06 05:53:20 - mmengine - INFO - Epoch(train) [9][2460/2478] base_lr: 1.0524e-06 lr: 2.1048e-06 eta: 0:46:13 time: 1.1102 data_time: 0.0080 memory: 7583 grad_norm: 14.6164 loss: 0.8699 2023/09/06 05:53:40 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 05:53:40 - mmengine - INFO - Epoch(train) [9][2478/2478] base_lr: 1.0457e-06 lr: 2.0915e-06 eta: 0:45:53 time: 1.1075 data_time: 0.0083 memory: 7583 grad_norm: 14.9768 loss: 0.8272 2023/09/06 05:53:40 - mmengine - INFO - Saving checkpoint at 9 epochs 2023/09/06 05:54:11 - mmengine - INFO - Epoch(val) [9][20/96] eta: 0:01:22 time: 1.0809 data_time: 0.0386 memory: 8884 2023/09/06 05:54:32 - mmengine - INFO - Epoch(val) [9][40/96] eta: 0:00:59 time: 1.0514 data_time: 0.0064 memory: 8884 2023/09/06 05:54:52 - mmengine - INFO - Epoch(val) [9][60/96] eta: 0:00:38 time: 1.0436 data_time: 0.0064 memory: 8884 2023/09/06 05:55:13 - mmengine - INFO - Epoch(val) [9][80/96] eta: 0:00:16 time: 1.0440 data_time: 0.0065 memory: 8884 2023/09/06 05:55:31 - mmengine - INFO - Epoch(val) [9][96/96] VQA/acc: 42.2626 data_time: 0.0131 time: 1.0523 2023/09/06 05:55:53 - mmengine - INFO - Epoch(train) [10][ 20/2478] base_lr: 1.0384e-06 lr: 2.0767e-06 eta: 0:45:31 time: 1.1275 data_time: 0.0211 memory: 8884 grad_norm: 13.7328 loss: 0.9560 2023/09/06 05:56:16 - mmengine - INFO - Epoch(train) [10][ 40/2478] base_lr: 1.0310e-06 lr: 2.0621e-06 eta: 0:45:09 time: 1.1123 data_time: 0.0079 memory: 7583 grad_norm: 13.9701 loss: 0.7552 2023/09/06 05:56:38 - mmengine - INFO - Epoch(train) [10][ 60/2478] base_lr: 1.0237e-06 lr: 2.0474e-06 eta: 0:44:46 time: 1.1111 data_time: 0.0077 memory: 7583 grad_norm: 13.7866 loss: 0.8317 2023/09/06 05:57:00 - mmengine - INFO - Epoch(train) [10][ 80/2478] base_lr: 1.0164e-06 lr: 2.0329e-06 eta: 0:44:24 time: 1.1118 data_time: 0.0077 memory: 7583 grad_norm: 14.1776 loss: 0.8577 2023/09/06 05:57:22 - mmengine - INFO - Epoch(train) [10][ 100/2478] base_lr: 1.0092e-06 lr: 2.0183e-06 eta: 0:44:02 time: 1.1099 data_time: 0.0079 memory: 7583 grad_norm: 13.9489 loss: 0.7993 2023/09/06 05:57:44 - mmengine - INFO - Epoch(train) [10][ 120/2478] base_lr: 1.0019e-06 lr: 2.0039e-06 eta: 0:43:40 time: 1.1138 data_time: 0.0081 memory: 7583 grad_norm: 13.9896 loss: 0.9117 2023/09/06 05:58:07 - mmengine - INFO - Epoch(train) [10][ 140/2478] base_lr: 9.9472e-07 lr: 1.9894e-06 eta: 0:43:17 time: 1.1118 data_time: 0.0082 memory: 7583 grad_norm: 13.9928 loss: 0.7702 2023/09/06 05:58:29 - mmengine - INFO - Epoch(train) [10][ 160/2478] base_lr: 9.8753e-07 lr: 1.9751e-06 eta: 0:42:55 time: 1.1086 data_time: 0.0079 memory: 7583 grad_norm: 14.2914 loss: 0.9291 2023/09/06 05:58:51 - mmengine - INFO - Epoch(train) [10][ 180/2478] base_lr: 9.8038e-07 lr: 1.9608e-06 eta: 0:42:33 time: 1.1128 data_time: 0.0081 memory: 7583 grad_norm: 14.2575 loss: 0.6965 2023/09/06 05:59:13 - mmengine - INFO - Epoch(train) [10][ 200/2478] base_lr: 9.7324e-07 lr: 1.9465e-06 eta: 0:42:11 time: 1.1099 data_time: 0.0083 memory: 7583 grad_norm: 14.6203 loss: 1.0322 2023/09/06 05:59:35 - mmengine - INFO - Epoch(train) [10][ 220/2478] base_lr: 9.6614e-07 lr: 1.9323e-06 eta: 0:41:48 time: 1.1095 data_time: 0.0077 memory: 7583 grad_norm: 14.2906 loss: 0.9323 2023/09/06 05:59:58 - mmengine - INFO - Epoch(train) [10][ 240/2478] base_lr: 9.5906e-07 lr: 1.9181e-06 eta: 0:41:26 time: 1.1077 data_time: 0.0081 memory: 7583 grad_norm: 13.7374 loss: 0.5819 2023/09/06 06:00:20 - mmengine - INFO - Epoch(train) [10][ 260/2478] base_lr: 9.5200e-07 lr: 1.9040e-06 eta: 0:41:04 time: 1.1099 data_time: 0.0081 memory: 7583 grad_norm: 14.1486 loss: 0.9258 2023/09/06 06:00:42 - mmengine - INFO - Epoch(train) [10][ 280/2478] base_lr: 9.4498e-07 lr: 1.8900e-06 eta: 0:40:42 time: 1.1111 data_time: 0.0078 memory: 7583 grad_norm: 14.0580 loss: 0.7848 2023/09/06 06:01:04 - mmengine - INFO - Epoch(train) [10][ 300/2478] base_lr: 9.3798e-07 lr: 1.8760e-06 eta: 0:40:20 time: 1.1113 data_time: 0.0082 memory: 7583 grad_norm: 13.9968 loss: 0.7784 2023/09/06 06:01:26 - mmengine - INFO - Epoch(train) [10][ 320/2478] base_lr: 9.3100e-07 lr: 1.8620e-06 eta: 0:39:57 time: 1.1097 data_time: 0.0081 memory: 7583 grad_norm: 13.9497 loss: 0.8077 2023/09/06 06:01:49 - mmengine - INFO - Epoch(train) [10][ 340/2478] base_lr: 9.2406e-07 lr: 1.8481e-06 eta: 0:39:35 time: 1.1104 data_time: 0.0081 memory: 7583 grad_norm: 14.1868 loss: 0.8543 2023/09/06 06:02:11 - mmengine - INFO - Epoch(train) [10][ 360/2478] base_lr: 9.1713e-07 lr: 1.8343e-06 eta: 0:39:13 time: 1.1097 data_time: 0.0081 memory: 7583 grad_norm: 14.4383 loss: 0.9372 2023/09/06 06:02:33 - mmengine - INFO - Epoch(train) [10][ 380/2478] base_lr: 9.1024e-07 lr: 1.8205e-06 eta: 0:38:51 time: 1.1113 data_time: 0.0084 memory: 7583 grad_norm: 14.8339 loss: 0.9352 2023/09/06 06:02:55 - mmengine - INFO - Epoch(train) [10][ 400/2478] base_lr: 9.0337e-07 lr: 1.8067e-06 eta: 0:38:28 time: 1.1107 data_time: 0.0084 memory: 7583 grad_norm: 14.3654 loss: 1.0460 2023/09/06 06:03:18 - mmengine - INFO - Epoch(train) [10][ 420/2478] base_lr: 8.9653e-07 lr: 1.7931e-06 eta: 0:38:06 time: 1.1079 data_time: 0.0084 memory: 7583 grad_norm: 13.7394 loss: 0.8530 2023/09/06 06:03:40 - mmengine - INFO - Epoch(train) [10][ 440/2478] base_lr: 8.8972e-07 lr: 1.7794e-06 eta: 0:37:44 time: 1.1100 data_time: 0.0085 memory: 7583 grad_norm: 15.0261 loss: 1.0954 2023/09/06 06:04:02 - mmengine - INFO - Epoch(train) [10][ 460/2478] base_lr: 8.8293e-07 lr: 1.7659e-06 eta: 0:37:22 time: 1.1102 data_time: 0.0084 memory: 7583 grad_norm: 14.4106 loss: 0.9570 2023/09/06 06:04:24 - mmengine - INFO - Epoch(train) [10][ 480/2478] base_lr: 8.7617e-07 lr: 1.7523e-06 eta: 0:37:00 time: 1.1094 data_time: 0.0082 memory: 7583 grad_norm: 14.0058 loss: 0.7457 2023/09/06 06:04:46 - mmengine - INFO - Epoch(train) [10][ 500/2478] base_lr: 8.6943e-07 lr: 1.7389e-06 eta: 0:36:37 time: 1.1104 data_time: 0.0085 memory: 7583 grad_norm: 14.6007 loss: 0.9376 2023/09/06 06:05:09 - mmengine - INFO - Epoch(train) [10][ 520/2478] base_lr: 8.6273e-07 lr: 1.7255e-06 eta: 0:36:15 time: 1.1099 data_time: 0.0082 memory: 7583 grad_norm: 14.4033 loss: 0.8225 2023/09/06 06:05:31 - mmengine - INFO - Epoch(train) [10][ 540/2478] base_lr: 8.5605e-07 lr: 1.7121e-06 eta: 0:35:53 time: 1.1128 data_time: 0.0081 memory: 7583 grad_norm: 14.3566 loss: 0.8372 2023/09/06 06:05:53 - mmengine - INFO - Epoch(train) [10][ 560/2478] base_lr: 8.4939e-07 lr: 1.6988e-06 eta: 0:35:31 time: 1.1082 data_time: 0.0082 memory: 7583 grad_norm: inf loss: 0.8413 2023/09/06 06:06:15 - mmengine - INFO - Epoch(train) [10][ 580/2478] base_lr: 8.4277e-07 lr: 1.6855e-06 eta: 0:35:08 time: 1.1083 data_time: 0.0079 memory: 7583 grad_norm: 14.6514 loss: 1.0031 2023/09/06 06:06:37 - mmengine - INFO - Epoch(train) [10][ 600/2478] base_lr: 8.3617e-07 lr: 1.6723e-06 eta: 0:34:46 time: 1.1103 data_time: 0.0082 memory: 7583 grad_norm: 14.3869 loss: 0.9298 2023/09/06 06:06:59 - mmengine - INFO - Epoch(train) [10][ 620/2478] base_lr: 8.2960e-07 lr: 1.6592e-06 eta: 0:34:24 time: 1.1095 data_time: 0.0080 memory: 7583 grad_norm: 14.6624 loss: 1.0337 2023/09/06 06:07:22 - mmengine - INFO - Epoch(train) [10][ 640/2478] base_lr: 8.2305e-07 lr: 1.6461e-06 eta: 0:34:02 time: 1.1091 data_time: 0.0078 memory: 7583 grad_norm: 14.0286 loss: 0.6524 2023/09/06 06:07:44 - mmengine - INFO - Epoch(train) [10][ 660/2478] base_lr: 8.1653e-07 lr: 1.6331e-06 eta: 0:33:40 time: 1.1125 data_time: 0.0080 memory: 7583 grad_norm: 14.4422 loss: 0.9078 2023/09/06 06:08:06 - mmengine - INFO - Epoch(train) [10][ 680/2478] base_lr: 8.1004e-07 lr: 1.6201e-06 eta: 0:33:17 time: 1.1090 data_time: 0.0079 memory: 7583 grad_norm: 13.9157 loss: 0.9439 2023/09/06 06:08:26 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 06:08:28 - mmengine - INFO - Epoch(train) [10][ 700/2478] base_lr: 8.0358e-07 lr: 1.6072e-06 eta: 0:32:55 time: 1.1080 data_time: 0.0084 memory: 7583 grad_norm: 14.2941 loss: 0.8888 2023/09/06 06:08:50 - mmengine - INFO - Epoch(train) [10][ 720/2478] base_lr: 7.9714e-07 lr: 1.5943e-06 eta: 0:32:33 time: 1.1112 data_time: 0.0084 memory: 7583 grad_norm: 14.0510 loss: 0.7265 2023/09/06 06:09:13 - mmengine - INFO - Epoch(train) [10][ 740/2478] base_lr: 7.9073e-07 lr: 1.5815e-06 eta: 0:32:11 time: 1.1108 data_time: 0.0081 memory: 7583 grad_norm: 14.1921 loss: 1.0641 2023/09/06 06:09:35 - mmengine - INFO - Epoch(train) [10][ 760/2478] base_lr: 7.8435e-07 lr: 1.5687e-06 eta: 0:31:48 time: 1.1119 data_time: 0.0081 memory: 7583 grad_norm: 14.1119 loss: 0.8425 2023/09/06 06:09:57 - mmengine - INFO - Epoch(train) [10][ 780/2478] base_lr: 7.7800e-07 lr: 1.5560e-06 eta: 0:31:26 time: 1.1092 data_time: 0.0080 memory: 7583 grad_norm: 13.8854 loss: 0.6495 2023/09/06 06:10:19 - mmengine - INFO - Epoch(train) [10][ 800/2478] base_lr: 7.7167e-07 lr: 1.5433e-06 eta: 0:31:04 time: 1.1111 data_time: 0.0083 memory: 7583 grad_norm: 14.5222 loss: 0.8431 2023/09/06 06:10:42 - mmengine - INFO - Epoch(train) [10][ 820/2478] base_lr: 7.6537e-07 lr: 1.5307e-06 eta: 0:30:42 time: 1.1092 data_time: 0.0082 memory: 7583 grad_norm: 14.3840 loss: 0.9246 2023/09/06 06:11:04 - mmengine - INFO - Epoch(train) [10][ 840/2478] base_lr: 7.5910e-07 lr: 1.5182e-06 eta: 0:30:20 time: 1.1092 data_time: 0.0083 memory: 7583 grad_norm: 14.7130 loss: 0.7875 2023/09/06 06:11:26 - mmengine - INFO - Epoch(train) [10][ 860/2478] base_lr: 7.5286e-07 lr: 1.5057e-06 eta: 0:29:57 time: 1.1070 data_time: 0.0082 memory: 7583 grad_norm: 14.3746 loss: 1.0601 2023/09/06 06:11:48 - mmengine - INFO - Epoch(train) [10][ 880/2478] base_lr: 7.4664e-07 lr: 1.4933e-06 eta: 0:29:35 time: 1.1117 data_time: 0.0080 memory: 7583 grad_norm: 14.0682 loss: 0.8810 2023/09/06 06:12:10 - mmengine - INFO - Epoch(train) [10][ 900/2478] base_lr: 7.4045e-07 lr: 1.4809e-06 eta: 0:29:13 time: 1.1077 data_time: 0.0080 memory: 7583 grad_norm: 14.4043 loss: 0.7589 2023/09/06 06:12:32 - mmengine - INFO - Epoch(train) [10][ 920/2478] base_lr: 7.3429e-07 lr: 1.4686e-06 eta: 0:28:51 time: 1.1084 data_time: 0.0080 memory: 7583 grad_norm: 14.5992 loss: 0.9977 2023/09/06 06:12:55 - mmengine - INFO - Epoch(train) [10][ 940/2478] base_lr: 7.2816e-07 lr: 1.4563e-06 eta: 0:28:28 time: 1.1104 data_time: 0.0080 memory: 7583 grad_norm: 14.4564 loss: 0.9115 2023/09/06 06:13:17 - mmengine - INFO - Epoch(train) [10][ 960/2478] base_lr: 7.2205e-07 lr: 1.4441e-06 eta: 0:28:06 time: 1.1073 data_time: 0.0079 memory: 7583 grad_norm: 14.6471 loss: 0.8589 2023/09/06 06:13:39 - mmengine - INFO - Epoch(train) [10][ 980/2478] base_lr: 7.1598e-07 lr: 1.4320e-06 eta: 0:27:44 time: 1.1093 data_time: 0.0081 memory: 7583 grad_norm: 14.6282 loss: 0.7605 2023/09/06 06:14:01 - mmengine - INFO - Epoch(train) [10][1000/2478] base_lr: 7.0993e-07 lr: 1.4199e-06 eta: 0:27:22 time: 1.1099 data_time: 0.0079 memory: 7583 grad_norm: 15.0593 loss: 0.8814 2023/09/06 06:14:23 - mmengine - INFO - Epoch(train) [10][1020/2478] base_lr: 7.0390e-07 lr: 1.4078e-06 eta: 0:27:00 time: 1.1127 data_time: 0.0081 memory: 7583 grad_norm: 14.2363 loss: 0.6997 2023/09/06 06:14:46 - mmengine - INFO - Epoch(train) [10][1040/2478] base_lr: 6.9791e-07 lr: 1.3958e-06 eta: 0:26:37 time: 1.1102 data_time: 0.0083 memory: 7583 grad_norm: 14.9352 loss: 0.9574 2023/09/06 06:15:08 - mmengine - INFO - Epoch(train) [10][1060/2478] base_lr: 6.9194e-07 lr: 1.3839e-06 eta: 0:26:15 time: 1.1078 data_time: 0.0083 memory: 7583 grad_norm: 14.8564 loss: 0.7462 2023/09/06 06:15:30 - mmengine - INFO - Epoch(train) [10][1080/2478] base_lr: 6.8601e-07 lr: 1.3720e-06 eta: 0:25:53 time: 1.1124 data_time: 0.0094 memory: 7583 grad_norm: 14.1468 loss: 0.9188 2023/09/06 06:15:52 - mmengine - INFO - Epoch(train) [10][1100/2478] base_lr: 6.8010e-07 lr: 1.3602e-06 eta: 0:25:31 time: 1.1112 data_time: 0.0081 memory: 7583 grad_norm: 14.2072 loss: 0.8078 2023/09/06 06:16:14 - mmengine - INFO - Epoch(train) [10][1120/2478] base_lr: 6.7422e-07 lr: 1.3484e-06 eta: 0:25:08 time: 1.1094 data_time: 0.0080 memory: 7583 grad_norm: 14.5763 loss: 1.0155 2023/09/06 06:16:37 - mmengine - INFO - Epoch(train) [10][1140/2478] base_lr: 6.6836e-07 lr: 1.3367e-06 eta: 0:24:46 time: 1.1082 data_time: 0.0082 memory: 7583 grad_norm: 13.8283 loss: 1.0359 2023/09/06 06:16:59 - mmengine - INFO - Epoch(train) [10][1160/2478] base_lr: 6.6254e-07 lr: 1.3251e-06 eta: 0:24:24 time: 1.1091 data_time: 0.0081 memory: 7583 grad_norm: 14.3769 loss: 0.8830 2023/09/06 06:17:21 - mmengine - INFO - Epoch(train) [10][1180/2478] base_lr: 6.5674e-07 lr: 1.3135e-06 eta: 0:24:02 time: 1.1117 data_time: 0.0079 memory: 7583 grad_norm: 14.2429 loss: 0.8984 2023/09/06 06:17:43 - mmengine - INFO - Epoch(train) [10][1200/2478] base_lr: 6.5097e-07 lr: 1.3019e-06 eta: 0:23:39 time: 1.1115 data_time: 0.0080 memory: 7583 grad_norm: 14.1513 loss: 0.7510 2023/09/06 06:18:06 - mmengine - INFO - Epoch(train) [10][1220/2478] base_lr: 6.4523e-07 lr: 1.2905e-06 eta: 0:23:17 time: 1.1126 data_time: 0.0086 memory: 7583 grad_norm: 14.2258 loss: 0.8544 2023/09/06 06:18:28 - mmengine - INFO - Epoch(train) [10][1240/2478] base_lr: 6.3952e-07 lr: 1.2790e-06 eta: 0:22:55 time: 1.1126 data_time: 0.0084 memory: 7583 grad_norm: 14.6977 loss: 0.9194 2023/09/06 06:18:50 - mmengine - INFO - Epoch(train) [10][1260/2478] base_lr: 6.3383e-07 lr: 1.2677e-06 eta: 0:22:33 time: 1.1135 data_time: 0.0083 memory: 7583 grad_norm: 14.2269 loss: 0.8702 2023/09/06 06:19:12 - mmengine - INFO - Epoch(train) [10][1280/2478] base_lr: 6.2818e-07 lr: 1.2564e-06 eta: 0:22:11 time: 1.1135 data_time: 0.0085 memory: 7583 grad_norm: 14.5694 loss: 0.8628 2023/09/06 06:19:35 - mmengine - INFO - Epoch(train) [10][1300/2478] base_lr: 6.2255e-07 lr: 1.2451e-06 eta: 0:21:48 time: 1.1102 data_time: 0.0083 memory: 7583 grad_norm: 14.4667 loss: 0.8694 2023/09/06 06:19:57 - mmengine - INFO - Epoch(train) [10][1320/2478] base_lr: 6.1695e-07 lr: 1.2339e-06 eta: 0:21:26 time: 1.1102 data_time: 0.0081 memory: 7583 grad_norm: 14.3265 loss: 0.9118 2023/09/06 06:20:19 - mmengine - INFO - Epoch(train) [10][1340/2478] base_lr: 6.1138e-07 lr: 1.2228e-06 eta: 0:21:04 time: 1.1104 data_time: 0.0083 memory: 7583 grad_norm: 13.9332 loss: 0.7792 2023/09/06 06:20:41 - mmengine - INFO - Epoch(train) [10][1360/2478] base_lr: 6.0584e-07 lr: 1.2117e-06 eta: 0:20:42 time: 1.1094 data_time: 0.0079 memory: 7583 grad_norm: 14.5369 loss: 0.9869 2023/09/06 06:21:03 - mmengine - INFO - Epoch(train) [10][1380/2478] base_lr: 6.0033e-07 lr: 1.2007e-06 eta: 0:20:19 time: 1.1121 data_time: 0.0081 memory: 7583 grad_norm: 14.5248 loss: 0.7578 2023/09/06 06:21:26 - mmengine - INFO - Epoch(train) [10][1400/2478] base_lr: 5.9484e-07 lr: 1.1897e-06 eta: 0:19:57 time: 1.1118 data_time: 0.0082 memory: 7583 grad_norm: 14.3598 loss: 0.7396 2023/09/06 06:21:48 - mmengine - INFO - Epoch(train) [10][1420/2478] base_lr: 5.8939e-07 lr: 1.1788e-06 eta: 0:19:35 time: 1.1087 data_time: 0.0081 memory: 7583 grad_norm: 14.9163 loss: 1.1132 2023/09/06 06:22:10 - mmengine - INFO - Epoch(train) [10][1440/2478] base_lr: 5.8396e-07 lr: 1.1679e-06 eta: 0:19:13 time: 1.1092 data_time: 0.0082 memory: 7583 grad_norm: 14.5347 loss: 0.7504 2023/09/06 06:22:32 - mmengine - INFO - Epoch(train) [10][1460/2478] base_lr: 5.7856e-07 lr: 1.1571e-06 eta: 0:18:51 time: 1.1119 data_time: 0.0084 memory: 7583 grad_norm: 14.3874 loss: 0.6471 2023/09/06 06:22:54 - mmengine - INFO - Epoch(train) [10][1480/2478] base_lr: 5.7319e-07 lr: 1.1464e-06 eta: 0:18:28 time: 1.1141 data_time: 0.0086 memory: 7583 grad_norm: 14.6606 loss: 0.7414 2023/09/06 06:23:17 - mmengine - INFO - Epoch(train) [10][1500/2478] base_lr: 5.6785e-07 lr: 1.1357e-06 eta: 0:18:06 time: 1.1103 data_time: 0.0082 memory: 7583 grad_norm: 14.5560 loss: 0.8108 2023/09/06 06:23:39 - mmengine - INFO - Epoch(train) [10][1520/2478] base_lr: 5.6254e-07 lr: 1.1251e-06 eta: 0:17:44 time: 1.1114 data_time: 0.0084 memory: 7583 grad_norm: 14.4679 loss: 0.9350 2023/09/06 06:24:01 - mmengine - INFO - Epoch(train) [10][1540/2478] base_lr: 5.5726e-07 lr: 1.1145e-06 eta: 0:17:22 time: 1.1090 data_time: 0.0081 memory: 7583 grad_norm: 14.4507 loss: 0.9716 2023/09/06 06:24:23 - mmengine - INFO - Epoch(train) [10][1560/2478] base_lr: 5.5200e-07 lr: 1.1040e-06 eta: 0:16:59 time: 1.1102 data_time: 0.0080 memory: 7583 grad_norm: 14.5413 loss: 0.8756 2023/09/06 06:24:46 - mmengine - INFO - Epoch(train) [10][1580/2478] base_lr: 5.4678e-07 lr: 1.0936e-06 eta: 0:16:37 time: 1.1117 data_time: 0.0083 memory: 7583 grad_norm: 14.2638 loss: 0.7777 2023/09/06 06:25:08 - mmengine - INFO - Epoch(train) [10][1600/2478] base_lr: 5.4158e-07 lr: 1.0832e-06 eta: 0:16:15 time: 1.1098 data_time: 0.0082 memory: 7583 grad_norm: 14.4063 loss: 0.8521 2023/09/06 06:25:30 - mmengine - INFO - Epoch(train) [10][1620/2478] base_lr: 5.3641e-07 lr: 1.0728e-06 eta: 0:15:53 time: 1.1105 data_time: 0.0083 memory: 7583 grad_norm: 14.8962 loss: 0.9394 2023/09/06 06:25:52 - mmengine - INFO - Epoch(train) [10][1640/2478] base_lr: 5.3127e-07 lr: 1.0625e-06 eta: 0:15:31 time: 1.1119 data_time: 0.0083 memory: 7583 grad_norm: 14.2336 loss: 0.9438 2023/09/06 06:26:14 - mmengine - INFO - Epoch(train) [10][1660/2478] base_lr: 5.2617e-07 lr: 1.0523e-06 eta: 0:15:08 time: 1.1107 data_time: 0.0082 memory: 7583 grad_norm: 14.3665 loss: 0.8022 2023/09/06 06:26:37 - mmengine - INFO - Epoch(train) [10][1680/2478] base_lr: 5.2108e-07 lr: 1.0422e-06 eta: 0:14:46 time: 1.1096 data_time: 0.0082 memory: 7583 grad_norm: 14.2828 loss: 0.8796 2023/09/06 06:26:57 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 06:26:59 - mmengine - INFO - Epoch(train) [10][1700/2478] base_lr: 5.1603e-07 lr: 1.0321e-06 eta: 0:14:24 time: 1.1103 data_time: 0.0084 memory: 7583 grad_norm: 14.7040 loss: 0.7729 2023/09/06 06:27:21 - mmengine - INFO - Epoch(train) [10][1720/2478] base_lr: 5.1101e-07 lr: 1.0220e-06 eta: 0:14:02 time: 1.1112 data_time: 0.0083 memory: 7583 grad_norm: 14.7544 loss: 1.0189 2023/09/06 06:27:43 - mmengine - INFO - Epoch(train) [10][1740/2478] base_lr: 5.0602e-07 lr: 1.0120e-06 eta: 0:13:39 time: 1.1134 data_time: 0.0098 memory: 7583 grad_norm: 14.4935 loss: 0.9076 2023/09/06 06:28:06 - mmengine - INFO - Epoch(train) [10][1760/2478] base_lr: 5.0106e-07 lr: 1.0021e-06 eta: 0:13:17 time: 1.1116 data_time: 0.0084 memory: 7583 grad_norm: 14.2376 loss: 0.8067 2023/09/06 06:28:28 - mmengine - INFO - Epoch(train) [10][1780/2478] base_lr: 4.9612e-07 lr: 9.9224e-07 eta: 0:12:55 time: 1.1081 data_time: 0.0082 memory: 7583 grad_norm: 14.5015 loss: 1.0089 2023/09/06 06:28:50 - mmengine - INFO - Epoch(train) [10][1800/2478] base_lr: 4.9122e-07 lr: 9.8243e-07 eta: 0:12:33 time: 1.1105 data_time: 0.0083 memory: 7583 grad_norm: 14.5329 loss: 1.0821 2023/09/06 06:29:12 - mmengine - INFO - Epoch(train) [10][1820/2478] base_lr: 4.8634e-07 lr: 9.7268e-07 eta: 0:12:11 time: 1.1088 data_time: 0.0087 memory: 7583 grad_norm: 14.6188 loss: 0.9179 2023/09/06 06:29:34 - mmengine - INFO - Epoch(train) [10][1840/2478] base_lr: 4.8149e-07 lr: 9.6299e-07 eta: 0:11:48 time: 1.1092 data_time: 0.0080 memory: 7583 grad_norm: 14.4954 loss: 0.9141 2023/09/06 06:29:56 - mmengine - INFO - Epoch(train) [10][1860/2478] base_lr: 4.7668e-07 lr: 9.5335e-07 eta: 0:11:26 time: 1.1095 data_time: 0.0084 memory: 7583 grad_norm: 14.6676 loss: 0.8146 2023/09/06 06:30:19 - mmengine - INFO - Epoch(train) [10][1880/2478] base_lr: 4.7189e-07 lr: 9.4378e-07 eta: 0:11:04 time: 1.1091 data_time: 0.0082 memory: 7583 grad_norm: 14.5698 loss: 1.0701 2023/09/06 06:30:41 - mmengine - INFO - Epoch(train) [10][1900/2478] base_lr: 4.6713e-07 lr: 9.3426e-07 eta: 0:10:42 time: 1.1107 data_time: 0.0082 memory: 7583 grad_norm: 14.8190 loss: 0.9918 2023/09/06 06:31:03 - mmengine - INFO - Epoch(train) [10][1920/2478] base_lr: 4.6240e-07 lr: 9.2480e-07 eta: 0:10:19 time: 1.1096 data_time: 0.0082 memory: 7583 grad_norm: 14.2140 loss: 0.8432 2023/09/06 06:31:25 - mmengine - INFO - Epoch(train) [10][1940/2478] base_lr: 4.5770e-07 lr: 9.1540e-07 eta: 0:09:57 time: 1.1094 data_time: 0.0083 memory: 7583 grad_norm: 14.5964 loss: 0.7498 2023/09/06 06:31:47 - mmengine - INFO - Epoch(train) [10][1960/2478] base_lr: 4.5303e-07 lr: 9.0606e-07 eta: 0:09:35 time: 1.1092 data_time: 0.0084 memory: 7583 grad_norm: 14.3863 loss: 0.8417 2023/09/06 06:32:10 - mmengine - INFO - Epoch(train) [10][1980/2478] base_lr: 4.4839e-07 lr: 8.9678e-07 eta: 0:09:13 time: 1.1108 data_time: 0.0084 memory: 7583 grad_norm: 14.2121 loss: 1.0739 2023/09/06 06:32:32 - mmengine - INFO - Epoch(train) [10][2000/2478] base_lr: 4.4378e-07 lr: 8.8756e-07 eta: 0:08:51 time: 1.1130 data_time: 0.0085 memory: 7583 grad_norm: 14.1097 loss: 0.8518 2023/09/06 06:32:54 - mmengine - INFO - Epoch(train) [10][2020/2478] base_lr: 4.3920e-07 lr: 8.7840e-07 eta: 0:08:28 time: 1.1081 data_time: 0.0084 memory: 7583 grad_norm: 15.0778 loss: 0.8784 2023/09/06 06:33:16 - mmengine - INFO - Epoch(train) [10][2040/2478] base_lr: 4.3465e-07 lr: 8.6930e-07 eta: 0:08:06 time: 1.1107 data_time: 0.0083 memory: 7583 grad_norm: 14.2600 loss: 0.9528 2023/09/06 06:33:38 - mmengine - INFO - Epoch(train) [10][2060/2478] base_lr: 4.3013e-07 lr: 8.6026e-07 eta: 0:07:44 time: 1.1088 data_time: 0.0085 memory: 7583 grad_norm: 14.1442 loss: 0.7627 2023/09/06 06:34:01 - mmengine - INFO - Epoch(train) [10][2080/2478] base_lr: 4.2564e-07 lr: 8.5127e-07 eta: 0:07:22 time: 1.1103 data_time: 0.0082 memory: 7583 grad_norm: 14.7649 loss: 0.9018 2023/09/06 06:34:23 - mmengine - INFO - Epoch(train) [10][2100/2478] base_lr: 4.2117e-07 lr: 8.4235e-07 eta: 0:06:59 time: 1.1103 data_time: 0.0084 memory: 7583 grad_norm: 14.8188 loss: 0.6928 2023/09/06 06:34:45 - mmengine - INFO - Epoch(train) [10][2120/2478] base_lr: 4.1674e-07 lr: 8.3348e-07 eta: 0:06:37 time: 1.1127 data_time: 0.0082 memory: 7583 grad_norm: 14.3375 loss: 0.8276 2023/09/06 06:35:07 - mmengine - INFO - Epoch(train) [10][2140/2478] base_lr: 4.1234e-07 lr: 8.2468e-07 eta: 0:06:15 time: 1.1096 data_time: 0.0081 memory: 7583 grad_norm: 14.5637 loss: 0.8607 2023/09/06 06:35:30 - mmengine - INFO - Epoch(train) [10][2160/2478] base_lr: 4.0797e-07 lr: 8.1593e-07 eta: 0:05:53 time: 1.1091 data_time: 0.0078 memory: 7583 grad_norm: 14.5196 loss: 0.9619 2023/09/06 06:35:52 - mmengine - INFO - Epoch(train) [10][2180/2478] base_lr: 4.0362e-07 lr: 8.0724e-07 eta: 0:05:31 time: 1.1110 data_time: 0.0079 memory: 7583 grad_norm: 14.2246 loss: 1.1608 2023/09/06 06:36:14 - mmengine - INFO - Epoch(train) [10][2200/2478] base_lr: 3.9931e-07 lr: 7.9862e-07 eta: 0:05:08 time: 1.1093 data_time: 0.0081 memory: 7583 grad_norm: 14.9572 loss: 0.9391 2023/09/06 06:36:36 - mmengine - INFO - Epoch(train) [10][2220/2478] base_lr: 3.9503e-07 lr: 7.9005e-07 eta: 0:04:46 time: 1.1089 data_time: 0.0081 memory: 7583 grad_norm: 14.5645 loss: 0.8044 2023/09/06 06:36:58 - mmengine - INFO - Epoch(train) [10][2240/2478] base_lr: 3.9077e-07 lr: 7.8154e-07 eta: 0:04:24 time: 1.1108 data_time: 0.0085 memory: 7583 grad_norm: 14.9476 loss: 0.7766 2023/09/06 06:37:20 - mmengine - INFO - Epoch(train) [10][2260/2478] base_lr: 3.8655e-07 lr: 7.7310e-07 eta: 0:04:02 time: 1.1077 data_time: 0.0083 memory: 7583 grad_norm: 14.4156 loss: 0.6592 2023/09/06 06:37:43 - mmengine - INFO - Epoch(train) [10][2280/2478] base_lr: 3.8236e-07 lr: 7.6471e-07 eta: 0:03:39 time: 1.1079 data_time: 0.0081 memory: 7583 grad_norm: 14.2285 loss: 0.7894 2023/09/06 06:38:05 - mmengine - INFO - Epoch(train) [10][2300/2478] base_lr: 3.7819e-07 lr: 7.5638e-07 eta: 0:03:17 time: 1.1136 data_time: 0.0084 memory: 7583 grad_norm: 14.2784 loss: 0.7243 2023/09/06 06:38:27 - mmengine - INFO - Epoch(train) [10][2320/2478] base_lr: 3.7406e-07 lr: 7.4812e-07 eta: 0:02:55 time: 1.1110 data_time: 0.0081 memory: 7583 grad_norm: 14.2299 loss: 0.8703 2023/09/06 06:38:49 - mmengine - INFO - Epoch(train) [10][2340/2478] base_lr: 3.6996e-07 lr: 7.3991e-07 eta: 0:02:33 time: 1.1116 data_time: 0.0082 memory: 7583 grad_norm: 15.0178 loss: 1.0108 2023/09/06 06:39:12 - mmengine - INFO - Epoch(train) [10][2360/2478] base_lr: 3.6588e-07 lr: 7.3176e-07 eta: 0:02:11 time: 1.1085 data_time: 0.0084 memory: 7583 grad_norm: 14.3063 loss: 0.9206 2023/09/06 06:39:34 - mmengine - INFO - Epoch(train) [10][2380/2478] base_lr: 3.6184e-07 lr: 7.2368e-07 eta: 0:01:48 time: 1.1086 data_time: 0.0086 memory: 7583 grad_norm: 13.5540 loss: 0.9177 2023/09/06 06:39:56 - mmengine - INFO - Epoch(train) [10][2400/2478] base_lr: 3.5783e-07 lr: 7.1565e-07 eta: 0:01:26 time: 1.1136 data_time: 0.0096 memory: 7583 grad_norm: 14.9941 loss: 1.0602 2023/09/06 06:40:18 - mmengine - INFO - Epoch(train) [10][2420/2478] base_lr: 3.5384e-07 lr: 7.0769e-07 eta: 0:01:04 time: 1.1081 data_time: 0.0084 memory: 7583 grad_norm: 14.7223 loss: 0.9355 2023/09/06 06:40:40 - mmengine - INFO - Epoch(train) [10][2440/2478] base_lr: 3.4989e-07 lr: 6.9978e-07 eta: 0:00:42 time: 1.1121 data_time: 0.0083 memory: 7583 grad_norm: 14.8855 loss: 0.9032 2023/09/06 06:41:03 - mmengine - INFO - Epoch(train) [10][2460/2478] base_lr: 3.4597e-07 lr: 6.9194e-07 eta: 0:00:19 time: 1.1129 data_time: 0.0082 memory: 7583 grad_norm: 14.9970 loss: 0.8761 2023/09/06 06:41:23 - mmengine - INFO - Exp name: vindlu_beit-base_8x32_vqa_msrvtt-qa_20230905_224438 2023/09/06 06:41:23 - mmengine - INFO - Epoch(train) [10][2478/2478] base_lr: 3.4246e-07 lr: 6.8493e-07 eta: 0:00:00 time: 1.1116 data_time: 0.0082 memory: 7583 grad_norm: 14.5247 loss: 0.9406 2023/09/06 06:41:23 - mmengine - INFO - Saving checkpoint at 10 epochs 2023/09/06 06:41:53 - mmengine - INFO - Epoch(val) [10][20/96] eta: 0:01:21 time: 1.0780 data_time: 0.0398 memory: 8884 2023/09/06 06:42:14 - mmengine - INFO - Epoch(val) [10][40/96] eta: 0:00:59 time: 1.0494 data_time: 0.0064 memory: 8884 2023/09/06 06:42:35 - mmengine - INFO - Epoch(val) [10][60/96] eta: 0:00:38 time: 1.0420 data_time: 0.0067 memory: 8884 2023/09/06 06:42:56 - mmengine - INFO - Epoch(val) [10][80/96] eta: 0:00:16 time: 1.0448 data_time: 0.0068 memory: 8884 2023/09/06 06:43:13 - mmengine - INFO - Epoch(val) [10][96/96] VQA/acc: 42.4173 data_time: 0.0135 time: 1.0513