2024/07/14 02:24:11 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0] CUDA available: True numpy_random_seed: 473517714 GPU 0: NVIDIA GeForce RTX 4090 CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.8, V11.8.89 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 PyTorch: 2.1.0+cu118 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201703 - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v3.1.1 (Git Hash 64f6bcbcbab628e96f33a62c3e975f8535a7bde4) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.8 - NVCC architecture flags: -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;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_90,code=sm_90 - CuDNN 8.7 - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-invalid-partial-specialization -Wno-unused-private-field -Wno-aligned-allocation-unavailable -Wno-missing-braces -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_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.1.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.16.0+cu118 OpenCV: 4.10.0 MMEngine: 0.8.3 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 473517714 Distributed launcher: pytorch Distributed training: True GPU number: 1 ------------------------------------------------------------ 2024/07/14 02:24:11 - mmengine - INFO - Config: auto_scale_lr = dict(base_batch_size=24) caption_cfgs = dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True) caption_test_pipeline = [ dict(type='LoadImageFromFile'), dict( meta_dict=dict( git_cfg=dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True), head_cfg=dict( alpha=0.7, beam_num=2, ignore_index=-100, max_length=20, num_classes=30524, num_vocal=30524, temperature=1.0), task_name='caption'), type='AddMetaInfo'), dict( backend='pillow', interpolation='bicubic', scale=( 224, 224, ), type='Resize'), dict( meta_keys=[ 'image_id', 'img_shape', 'task_name', 'head_cfg', 'git_cfg', ], type='PackInputs'), ] caption_train_pipeline = [ dict(type='LoadImageFromFile'), dict( meta_dict=dict( git_cfg=dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True), head_cfg=dict( beam_num=2, ignore_index=-100, max_length=20, num_classes=30524, num_vocal=30524), task_name='caption'), type='AddMetaInfo'), dict( backend='pillow', interpolation='bicubic', scale=224, type='RandomResizedCrop'), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(keys='gt_caption', type='CleanCaption'), dict( algorithm_keys=[ 'gt_caption', ], meta_keys=[ 'image_id', 'img_shape', 'task_name', 'head_cfg', 'git_cfg', ], type='PackInputs'), ] custom_hooks = [ dict( ema_type='ExpMomentumEMA', momentum=0.0002, priority=49, type='EMAHook', update_buffers=True), ] default_hooks = dict( checkpoint=dict( by_epoch=False, interval=1000, max_keep_ckpts=1, type='CheckpointHook'), logger=dict(interval=50, log_metric_by_epoch=False, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict(type='DetVisualizationHook')) default_scope = 'mmdet' env_cfg = dict( cudnn_benchmark=True, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) launcher = 'pytorch' load_from = None log_level = 'INFO' log_processor = dict(by_epoch=False, type='LogProcessor', window_size=4000) max_iters = 120000 model = dict( backbone=dict( arch='base', drop_path_rate=0.1, img_size=1120, init_cfg=dict( checkpoint= 'https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth', prefix='backbone.', type='Pretrained'), new_more_layers=[ 'win', 'win', 'win', 'win', 'win', 'win', ], out_channels=0, out_type='featmap', patch_size=16, text_cfg=dict( hidden_size=768, pretrain_path='./blip_embed.pt', type='bert-base'), type='ViTGiTPromptBeta', use_abs_pos=True, use_checkpoints=True, use_rel_pos=True, window_size=14), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], pad_seg=True, pad_size_divisor=224, seg_pad_value=255, std=[ 58.395, 57.12, 57.375, ], type='GeneralDataPreprocessor'), head_list=dict(caption_head=dict(type='GiTCaptionHeadPromptBeta')), mean_layes=[ 12, 13, 14, 15, 16, 17, ], mean_output=True, support_tasks=[ 'detection', 'semantic_segmentation', 'instance_segmentation', 'caption', 'grounding', ], tokenizer=dict(name_or_path='bert-base-uncased', type='BlipTokenizer'), type='GiTPromptBeta', use_checkpoints=True) optim_wrapper = dict( clip_grad=dict(max_norm=0.1, norm_type=2), optimizer=dict(lr=0.0002, type='AdamW', weight_decay=0.05), paramwise_cfg=dict( custom_keys=dict({ 'backbone': dict(lr_mult=0.1), 'backbone.embed': dict(lr_mult=1.0), 'backbone.layers.10': dict(lr_mult=0.7429), 'backbone.layers.11': dict(lr_mult=0.8714), 'backbone.layers.12': dict(lr_mult=1.0), 'backbone.layers.13': dict(lr_mult=1.0), 'backbone.layers.14': dict(lr_mult=1.0), 'backbone.layers.15': dict(lr_mult=1.0), 'backbone.layers.16': dict(lr_mult=1.0), 'backbone.layers.17': dict(lr_mult=1.0), 'backbone.layers.6': dict(lr_mult=0.2286), 'backbone.layers.7': dict(lr_mult=0.3571), 'backbone.layers.8': dict(lr_mult=0.4858), 'backbone.layers.9': dict(lr_mult=0.6143), 'reference_points': dict(lr_mult=0.1), 'sampling_offsets': dict(lr_mult=0.1) })), type='OptimWrapper') param_scheduler = [ dict( T_max=120000, begin=0, by_epoch=False, end=120000, eta_min=2e-06, type='CosineAnnealingLR'), ] pretrained = 'https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth' resume = False test_cfg = dict(type='TestLoop') test_dataloader = dict( batch_size=16, dataset=dict( ann_file='annotations/coco_karpathy_test.json', data_root='data/coco_2014', pipeline=[ dict(type='LoadImageFromFile'), dict( meta_dict=dict( git_cfg=dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True), head_cfg=dict( alpha=0.7, beam_num=2, ignore_index=-100, max_length=20, num_classes=30524, num_vocal=30524, temperature=1.0), task_name='caption'), type='AddMetaInfo'), dict( backend='pillow', interpolation='bicubic', scale=( 224, 224, ), type='Resize'), dict( meta_keys=[ 'image_id', 'img_shape', 'task_name', 'head_cfg', 'git_cfg', ], type='PackInputs'), ], type='COCOCaption'), num_workers=2, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) test_evaluator = dict( ann_file='data/coco_2014/annotations/coco_karpathy_test_gt.json', type='COCOCaption') test_pipeline = [ dict(type='LoadImageFromFile'), dict( meta_dict=dict( git_cfg=dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True), head_cfg=dict( alpha=0.7, beam_num=2, ignore_index=-100, max_length=20, num_classes=30524, num_vocal=30524, temperature=1.0), task_name='caption'), type='AddMetaInfo'), dict( backend='pillow', interpolation='bicubic', scale=( 224, 224, ), type='Resize'), dict( meta_keys=[ 'image_id', 'img_shape', 'task_name', 'head_cfg', 'git_cfg', ], type='PackInputs'), ] train_cfg = dict( max_iters=120000, type='IterBasedTrainLoop', val_interval=5000) train_dataloader = dict( batch_sampler=None, batch_size=24, dataset=dict( datasets=[ dict( ann_file='annotations/coco_karpathy_train.json', data_root='data/coco_2014', pipeline=[ dict(type='LoadImageFromFile'), dict( meta_dict=dict( git_cfg=dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True), head_cfg=dict( beam_num=2, ignore_index=-100, max_length=20, num_classes=30524, num_vocal=30524), task_name='caption'), type='AddMetaInfo'), dict( backend='pillow', interpolation='bicubic', scale=224, type='RandomResizedCrop'), dict(direction='horizontal', prob=0.5, type='RandomFlip'), dict(keys='gt_caption', type='CleanCaption'), dict( algorithm_keys=[ 'gt_caption', ], meta_keys=[ 'image_id', 'img_shape', 'task_name', 'head_cfg', 'git_cfg', ], type='PackInputs'), ], type='COCOCaption'), ], ignore_keys=[ 'reduce_zero_label', 'label_map', 'classes', 'palette', ], type='ConcatDataset'), num_workers=4, persistent_workers=True, sampler=dict( batch_size=24, if_group=[ False, ], shuffle=True, source_ratio=[ 1.0, ], type='GroupMultiSourceNonMixedSampler')) tta_model = dict(type='SegTTAModel') val_cfg = dict(type='ValLoop') val_dataloader = dict( batch_size=16, dataset=dict( ann_file='annotations/coco_karpathy_test.json', data_root='data/coco_2014', pipeline=[ dict(type='LoadImageFromFile'), dict( meta_dict=dict( git_cfg=dict( global_only_image=False, grid_interpolate=False, grid_resolution_perwin=[ 1, 1, ], ignore_index=-100, max_length=20, mode='caption', num_vocal=30524, samples_grids_eachwin=1, use_checkpoints=True), head_cfg=dict( alpha=0.7, beam_num=2, ignore_index=-100, max_length=20, num_classes=30524, num_vocal=30524, temperature=1.0), task_name='caption'), type='AddMetaInfo'), dict( backend='pillow', interpolation='bicubic', scale=( 224, 224, ), type='Resize'), dict( meta_keys=[ 'image_id', 'img_shape', 'task_name', 'head_cfg', 'git_cfg', ], type='PackInputs'), ], type='COCOCaption'), num_workers=2, persistent_workers=True, sampler=dict(shuffle=False, type='DefaultSampler')) val_evaluator = dict( ann_file='data/coco_2014/annotations/coco_karpathy_test_gt.json', type='COCOCaption') vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( name='visualizer', type='DetLocalVisualizer', vis_backends=[ dict(type='LocalVisBackend'), ]) work_dir = './work_dirs/single_caption_base_prompt_beta_raw' 2024/07/14 02:25:14 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (49 ) EMAHook (BELOW_NORMAL) LoggerHook -------------------- after_load_checkpoint: (49 ) EMAHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (49 ) EMAHook (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 (49 ) EMAHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (49 ) EMAHook (NORMAL ) IterTimerHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (49 ) EMAHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- before_save_checkpoint: (49 ) EMAHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (49 ) EMAHook (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) DetVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (49 ) EMAHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.pos_embed:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.pos_embed:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.pos_embed:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.patch_embed.projection.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.patch_embed.projection.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.patch_embed.projection.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.patch_embed.projection.bias:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.patch_embed.projection.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.patch_embed.projection.bias:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.word_embeddings.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.word_embeddings.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.word_embeddings.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.position_embeddings.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.position_embeddings.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.position_embeddings.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.LayerNorm.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.LayerNorm.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.LayerNorm.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.LayerNorm.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.LayerNorm.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.embed.LayerNorm.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln1.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln1.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln1.bias:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln1.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln1.bias:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.rel_pos_h:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.rel_pos_h:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.rel_pos_h:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.rel_pos_w:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.rel_pos_w:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.rel_pos_w:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.qkv.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.qkv.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.qkv.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.qkv.bias:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.qkv.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.qkv.bias:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.proj.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.proj.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.proj.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.proj.bias:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.proj.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.attn.proj.bias:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln2.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln2.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln2.bias:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.0.ln2.bias:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- 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02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.qkv.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.qkv.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.qkv.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.qkv.bias:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.qkv.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.qkv.bias:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.proj.weight:lr=2e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.proj.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.5.attn.proj.weight:lr_mult=0.1 2024/07/14 02:25:21 - mmengine - INFO - 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backbone.layers.6.ln2.weight:lr=4.572e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ln2.weight:lr_mult=0.2286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ln2.bias:lr=4.572e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ln2.bias:lr_mult=0.2286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ffn.layers.0.0.weight:lr=4.572e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ffn.layers.0.0.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.6.ffn.layers.0.0.weight:lr_mult=0.2286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- 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02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.attn.proj.bias:lr=9.716000000000001e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.attn.proj.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.attn.proj.bias:lr_mult=0.4858 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ln2.weight:lr=9.716000000000001e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ln2.weight:lr_mult=0.4858 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ln2.bias:lr=9.716000000000001e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ln2.bias:lr_mult=0.4858 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.0.0.weight:lr=9.716000000000001e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.0.0.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.0.0.weight:lr_mult=0.4858 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.0.0.bias:lr=9.716000000000001e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.0.0.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.0.0.bias:lr_mult=0.4858 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.1.weight:lr=9.716000000000001e-05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.8.ffn.layers.1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- 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backbone.layers.9.ln1.bias:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.rel_pos_h:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.rel_pos_h:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.rel_pos_h:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.rel_pos_w:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.rel_pos_w:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.rel_pos_w:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.qkv.weight:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.qkv.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.qkv.weight:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.qkv.bias:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.qkv.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.qkv.bias:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.proj.weight:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.proj.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.proj.weight:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.proj.bias:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.proj.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.attn.proj.bias:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ln2.weight:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ln2.weight:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ln2.bias:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ln2.bias:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.0.0.weight:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.0.0.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.0.0.weight:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.0.0.bias:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.0.0.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.0.0.bias:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.1.weight:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.1.weight:lr_mult=0.6143 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.1.bias:lr=0.00012286 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.9.ffn.layers.1.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine 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mmengine - INFO - paramwise_options -- backbone.layers.10.attn.rel_pos_h:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.rel_pos_w:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.rel_pos_w:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.rel_pos_w:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.qkv.weight:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.qkv.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.qkv.weight:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.qkv.bias:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.qkv.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.qkv.bias:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.proj.weight:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.proj.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.proj.weight:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.proj.bias:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.proj.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.attn.proj.bias:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ln2.weight:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ln2.weight:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ln2.bias:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ln2.bias:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ffn.layers.0.0.weight:lr=0.00014858000000000002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ffn.layers.0.0.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.10.ffn.layers.0.0.weight:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- 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backbone.layers.10.ffn.layers.1.bias:lr_mult=0.7429 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.ln1.weight:lr=0.00017428 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.ln1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.ln1.weight:lr_mult=0.8714 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.ln1.bias:lr=0.00017428 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.ln1.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.ln1.bias:lr_mult=0.8714 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.attn.rel_pos_h:lr=0.00017428 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.11.attn.rel_pos_h:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- 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backbone.layers.16.ln2.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ln2.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ln2.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ln2.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.0.0.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.0.0.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.0.0.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.0.0.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.0.0.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.0.0.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.1.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.1.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.1.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.1.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.16.ffn.layers.1.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln1.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln1.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln1.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln1.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln1.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.qkv.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.qkv.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.qkv.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.qkv.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.qkv.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.qkv.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.proj.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.proj.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.proj.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.proj.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.proj.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.attn.proj.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln2.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln2.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln2.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln2.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln2.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ln2.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.0.0.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.0.0.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.0.0.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.0.0.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.0.0.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.0.0.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.1.weight:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.1.weight:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.1.weight:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.1.bias:lr=0.0002 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.1.bias:weight_decay=0.05 2024/07/14 02:25:21 - mmengine - INFO - paramwise_options -- backbone.layers.17.ffn.layers.1.bias:lr_mult=1.0 2024/07/14 02:25:21 - mmengine - WARNING - The prefix is not set in metric class COCOCaption. 2024/07/14 02:25:22 - mmengine - INFO - load backbone. in model from: https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth 2024/07/14 02:25:22 - mmengine - INFO - Resize the pos_embed shape from torch.Size([1, 64, 64, 768]) to torch.Size([1, 70, 70, 768]). 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.2.attn.rel_pos_h from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.2.attn.rel_pos_w from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.5.attn.rel_pos_h from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.5.attn.rel_pos_w from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.8.attn.rel_pos_h from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.8.attn.rel_pos_w from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.11.attn.rel_pos_h from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - INFO - Resize the layers.11.attn.rel_pos_w from torch.Size([127, 64]) to torch.Size([139, 64]) 2024/07/14 02:25:22 - mmengine - WARNING - The model and loaded state dict do not match exactly unexpected key in source state_dict: channel_reduction.0.weight, channel_reduction.1.weight, channel_reduction.1.bias, channel_reduction.2.weight, channel_reduction.3.weight, channel_reduction.3.bias missing keys in source state_dict: embed.position_ids, embed.word_embeddings.weight, embed.position_embeddings.weight, embed.LayerNorm.weight, embed.LayerNorm.bias, layers.12.ln1.weight, layers.12.ln1.bias, layers.12.attn.rel_pos_h, layers.12.attn.rel_pos_w, layers.12.attn.qkv.weight, layers.12.attn.qkv.bias, layers.12.attn.proj.weight, layers.12.attn.proj.bias, layers.12.ln2.weight, layers.12.ln2.bias, layers.12.ffn.layers.0.0.weight, layers.12.ffn.layers.0.0.bias, layers.12.ffn.layers.1.weight, layers.12.ffn.layers.1.bias, layers.13.ln1.weight, layers.13.ln1.bias, layers.13.attn.rel_pos_h, layers.13.attn.rel_pos_w, layers.13.attn.qkv.weight, layers.13.attn.qkv.bias, layers.13.attn.proj.weight, layers.13.attn.proj.bias, layers.13.ln2.weight, layers.13.ln2.bias, layers.13.ffn.layers.0.0.weight, layers.13.ffn.layers.0.0.bias, layers.13.ffn.layers.1.weight, layers.13.ffn.layers.1.bias, layers.14.ln1.weight, layers.14.ln1.bias, layers.14.attn.rel_pos_h, layers.14.attn.rel_pos_w, layers.14.attn.qkv.weight, layers.14.attn.qkv.bias, layers.14.attn.proj.weight, layers.14.attn.proj.bias, layers.14.ln2.weight, layers.14.ln2.bias, layers.14.ffn.layers.0.0.weight, layers.14.ffn.layers.0.0.bias, layers.14.ffn.layers.1.weight, layers.14.ffn.layers.1.bias, layers.15.ln1.weight, layers.15.ln1.bias, layers.15.attn.rel_pos_h, layers.15.attn.rel_pos_w, layers.15.attn.qkv.weight, layers.15.attn.qkv.bias, layers.15.attn.proj.weight, layers.15.attn.proj.bias, layers.15.ln2.weight, layers.15.ln2.bias, layers.15.ffn.layers.0.0.weight, layers.15.ffn.layers.0.0.bias, layers.15.ffn.layers.1.weight, layers.15.ffn.layers.1.bias, layers.16.ln1.weight, layers.16.ln1.bias, layers.16.attn.rel_pos_h, layers.16.attn.rel_pos_w, layers.16.attn.qkv.weight, layers.16.attn.qkv.bias, layers.16.attn.proj.weight, layers.16.attn.proj.bias, layers.16.ln2.weight, layers.16.ln2.bias, layers.16.ffn.layers.0.0.weight, layers.16.ffn.layers.0.0.bias, layers.16.ffn.layers.1.weight, layers.16.ffn.layers.1.bias, layers.17.ln1.weight, layers.17.ln1.bias, layers.17.attn.rel_pos_h, layers.17.attn.rel_pos_w, layers.17.attn.qkv.weight, layers.17.attn.qkv.bias, layers.17.attn.proj.weight, layers.17.attn.proj.bias, layers.17.ln2.weight, layers.17.ln2.bias, layers.17.ffn.layers.0.0.weight, layers.17.ffn.layers.0.0.bias, layers.17.ffn.layers.1.weight, layers.17.ffn.layers.1.bias Name of parameter - Initialization information backbone.pos_embed - torch.Size([1, 70, 70, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.patch_embed.projection.weight - torch.Size([768, 3, 16, 16]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.patch_embed.projection.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.embed.word_embeddings.weight - torch.Size([30524, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.embed.position_embeddings.weight - torch.Size([512, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.embed.LayerNorm.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.embed.LayerNorm.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.0.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.0.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.1.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.attn.rel_pos_h - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.attn.rel_pos_w - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.2.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.3.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.4.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.attn.rel_pos_h - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.attn.rel_pos_w - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.5.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.6.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.7.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.attn.rel_pos_h - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.attn.rel_pos_w - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.8.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.9.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.attn.rel_pos_h - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.attn.rel_pos_w - torch.Size([27, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.10.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ln1.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ln1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.attn.rel_pos_h - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.attn.rel_pos_w - torch.Size([139, 64]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.attn.qkv.weight - torch.Size([2304, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.attn.qkv.bias - torch.Size([2304]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.attn.proj.weight - torch.Size([768, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.attn.proj.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ln2.weight - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ln2.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ffn.layers.0.0.weight - torch.Size([3072, 768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ffn.layers.0.0.bias - torch.Size([3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ffn.layers.1.weight - torch.Size([768, 3072]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.11.ffn.layers.1.bias - torch.Size([768]): PretrainedInit: load from https://download.openmmlab.com/mmclassification/v1/vit_sam/vit-base-p16_sam-pre_3rdparty_sa1b-1024px_20230411-2320f9cc.pth backbone.layers.12.ln1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ln1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.attn.rel_pos_h - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.attn.rel_pos_w - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ln2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ln2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ffn.layers.0.0.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ffn.layers.0.0.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ffn.layers.1.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.12.ffn.layers.1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ln1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ln1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.attn.rel_pos_h - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.attn.rel_pos_w - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ln2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ln2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ffn.layers.0.0.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ffn.layers.0.0.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ffn.layers.1.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.13.ffn.layers.1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ln1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ln1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.attn.rel_pos_h - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.attn.rel_pos_w - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ln2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ln2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ffn.layers.0.0.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ffn.layers.0.0.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ffn.layers.1.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.14.ffn.layers.1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ln1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ln1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.attn.rel_pos_h - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.attn.rel_pos_w - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ln2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ln2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ffn.layers.0.0.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ffn.layers.0.0.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ffn.layers.1.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.15.ffn.layers.1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ln1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ln1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.attn.rel_pos_h - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.attn.rel_pos_w - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ln2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ln2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ffn.layers.0.0.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ffn.layers.0.0.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ffn.layers.1.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.16.ffn.layers.1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ln1.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ln1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.attn.rel_pos_h - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.attn.rel_pos_w - torch.Size([27, 64]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.attn.qkv.weight - torch.Size([2304, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.attn.qkv.bias - torch.Size([2304]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.attn.proj.weight - torch.Size([768, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.attn.proj.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ln2.weight - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ln2.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ffn.layers.0.0.weight - torch.Size([3072, 768]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ffn.layers.0.0.bias - torch.Size([3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ffn.layers.1.weight - torch.Size([768, 3072]): The value is the same before and after calling `init_weights` of GiTPromptBeta backbone.layers.17.ffn.layers.1.bias - torch.Size([768]): The value is the same before and after calling `init_weights` of GiTPromptBeta 2024/07/14 02:25:22 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2024/07/14 02:25:22 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2024/07/14 02:25:22 - mmengine - INFO - Checkpoints will be saved to /home/tanghao/mpi/GiT/work_dirs/single_caption_base_prompt_beta_raw. 2024/07/14 02:25:45 - mmengine - INFO - Iter(train) [ 50/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:24:43 time: 0.4626 data_time: 0.0112 memory: 4385 grad_norm: 13.4113 loss: 5.5884 caption_loss_cls: 5.5884 2024/07/14 02:26:08 - mmengine - INFO - Iter(train) [ 100/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:23:09 time: 0.4620 data_time: 0.0114 memory: 4383 grad_norm: 9.8905 loss: 4.9125 caption_loss_cls: 4.9125 2024/07/14 02:26:31 - mmengine - INFO - Iter(train) [ 150/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:23:55 time: 0.4625 data_time: 0.0113 memory: 4383 grad_norm: 8.5695 loss: 4.5811 caption_loss_cls: 4.5811 2024/07/14 02:26:54 - mmengine - INFO - Iter(train) [ 200/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:23:45 time: 0.4626 data_time: 0.0114 memory: 4383 grad_norm: 7.9215 loss: 4.3797 caption_loss_cls: 4.3797 2024/07/14 02:27:18 - mmengine - INFO - Iter(train) [ 250/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:24:24 time: 0.4632 data_time: 0.0115 memory: 4383 grad_norm: 7.4862 loss: 4.2491 caption_loss_cls: 4.2491 2024/07/14 02:27:41 - mmengine - INFO - Iter(train) [ 300/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:24:45 time: 0.4635 data_time: 0.0116 memory: 4383 grad_norm: 7.1560 loss: 4.1386 caption_loss_cls: 4.1386 2024/07/14 02:28:04 - mmengine - INFO - Iter(train) [ 350/120000] base_lr: 2.0000e-04 lr: 2.0000e-05 eta: 15:25:33 time: 0.4641 data_time: 0.0117 memory: 4383 grad_norm: 6.9409 loss: 4.0673 caption_loss_cls: 4.0673 2024/07/14 02:28:27 - mmengine - INFO - Iter(train) [ 400/120000] base_lr: 1.9999e-04 lr: 2.0000e-05 eta: 15:23:20 time: 0.4632 data_time: 0.0117 memory: 4383 grad_norm: 6.7532 loss: 3.9929 caption_loss_cls: 3.9929 2024/07/14 02:28:51 - 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mmengine - INFO - Iter(train) [ 1900/120000] base_lr: 1.9988e-04 lr: 1.9989e-05 eta: 15:13:04 time: 0.4639 data_time: 0.0135 memory: 4383 grad_norm: 5.2445 loss: 3.3413 caption_loss_cls: 3.3413 2024/07/14 02:40:26 - mmengine - INFO - Iter(train) [ 1950/120000] base_lr: 1.9987e-04 lr: 1.9988e-05 eta: 15:12:31 time: 0.4638 data_time: 0.0134 memory: 4383 grad_norm: 5.2241 loss: 3.3304 caption_loss_cls: 3.3304 2024/07/14 02:40:49 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240714_022410 2024/07/14 02:40:49 - mmengine - INFO - Iter(train) [ 2000/120000] base_lr: 1.9986e-04 lr: 1.9988e-05 eta: 15:11:39 time: 0.4636 data_time: 0.0134 memory: 4383 grad_norm: 5.2044 loss: 3.3190 caption_loss_cls: 3.3190 2024/07/14 02:40:49 - mmengine - INFO - Saving checkpoint at 2000 iterations 2024/07/14 02:41:17 - mmengine - INFO - Iter(train) [ 2050/120000] base_lr: 1.9986e-04 lr: 1.9987e-05 eta: 15:15:59 time: 0.4660 data_time: 0.0157 memory: 4383 grad_norm: 5.1875 loss: 3.3087 caption_loss_cls: 3.3087 2024/07/14 02:41:41 - 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mmengine - INFO - Iter(train) [ 2600/120000] base_lr: 1.9977e-04 lr: 1.9979e-05 eta: 15:11:54 time: 0.4661 data_time: 0.0148 memory: 4383 grad_norm: 5.0119 loss: 3.2197 caption_loss_cls: 3.2197 2024/07/14 02:45:57 - mmengine - INFO - Iter(train) [ 2650/120000] base_lr: 1.9976e-04 lr: 1.9978e-05 eta: 15:11:23 time: 0.4660 data_time: 0.0147 memory: 4383 grad_norm: 4.9985 loss: 3.2127 caption_loss_cls: 3.2127 2024/07/14 02:46:20 - mmengine - INFO - Iter(train) [ 2700/120000] base_lr: 1.9975e-04 lr: 1.9978e-05 eta: 15:11:02 time: 0.4660 data_time: 0.0147 memory: 4383 grad_norm: 4.9852 loss: 3.2058 caption_loss_cls: 3.2058 2024/07/14 02:46:43 - mmengine - INFO - Iter(train) [ 2750/120000] base_lr: 1.9974e-04 lr: 1.9977e-05 eta: 15:10:35 time: 0.4660 data_time: 0.0146 memory: 4383 grad_norm: 4.9724 loss: 3.1998 caption_loss_cls: 3.1998 2024/07/14 02:47:07 - mmengine - INFO - Iter(train) [ 2800/120000] base_lr: 1.9973e-04 lr: 1.9976e-05 eta: 15:10:24 time: 0.4661 data_time: 0.0145 memory: 4383 grad_norm: 4.9593 loss: 3.1935 caption_loss_cls: 3.1935 2024/07/14 02:47:31 - 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mmengine - INFO - Saving checkpoint at 5000 iterations 2024/07/14 03:04:29 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2879 data_time: 0.0096 memory: 3761 2024/07/14 03:04:43 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2837 data_time: 0.0073 memory: 3761 2024/07/14 03:04:57 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2825 data_time: 0.0067 memory: 3763 2024/07/14 03:05:10 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2802 data_time: 0.0063 memory: 3760 2024/07/14 03:05:24 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2791 data_time: 0.0061 memory: 3761 2024/07/14 03:05:38 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2782 data_time: 0.0059 memory: 3763 2024/07/14 03:06:15 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.6646 Bleu_2: 0.4840 Bleu_3: 0.3475 Bleu_4: 0.2508 METEOR: 0.2227 ROUGE_L: 0.4881 CIDEr: 0.7574 SPICE: 0.1528 data_time: 0.0059 time: 0.2779 2024/07/14 03:06:38 - mmengine - INFO - Iter(train) [ 5050/120000] base_lr: 1.9914e-04 lr: 1.9921e-05 eta: 15:04:28 time: 0.4736 data_time: 0.0230 memory: 4390 grad_norm: 4.2533 loss: 2.8319 caption_loss_cls: 2.8319 2024/07/14 03:07:01 - mmengine - INFO - Iter(train) [ 5100/120000] base_lr: 1.9912e-04 lr: 1.9920e-05 eta: 15:03:51 time: 0.4736 data_time: 0.0230 memory: 4388 grad_norm: 4.2421 loss: 2.8263 caption_loss_cls: 2.8263 2024/07/14 03:07:24 - mmengine - INFO - Iter(train) [ 5150/120000] base_lr: 1.9910e-04 lr: 1.9918e-05 eta: 15:03:16 time: 0.4736 data_time: 0.0230 memory: 4388 grad_norm: 4.2305 loss: 2.8200 caption_loss_cls: 2.8200 2024/07/14 03:07:47 - mmengine - INFO - Iter(train) [ 5200/120000] base_lr: 1.9908e-04 lr: 1.9917e-05 eta: 15:02:46 time: 0.4735 data_time: 0.0230 memory: 4388 grad_norm: 4.2191 loss: 2.8145 caption_loss_cls: 2.8145 2024/07/14 03:08:10 - mmengine - INFO - Iter(train) [ 5250/120000] base_lr: 1.9907e-04 lr: 1.9915e-05 eta: 15:02:14 time: 0.4735 data_time: 0.0230 memory: 4388 grad_norm: 4.2084 loss: 2.8077 caption_loss_cls: 2.8077 2024/07/14 03:08:33 - 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mmengine - INFO - Saving checkpoint at 8000 iterations 2024/07/14 03:29:56 - mmengine - INFO - Iter(train) [ 8050/120000] base_lr: 1.9781e-04 lr: 1.9801e-05 eta: 14:36:37 time: 0.4725 data_time: 0.0234 memory: 4388 grad_norm: 3.8480 loss: 2.6082 caption_loss_cls: 2.6082 2024/07/14 03:30:19 - mmengine - INFO - Iter(train) [ 8100/120000] base_lr: 1.9778e-04 lr: 1.9798e-05 eta: 14:36:10 time: 0.4725 data_time: 0.0234 memory: 4388 grad_norm: 3.8443 loss: 2.6069 caption_loss_cls: 2.6069 2024/07/14 03:30:42 - mmengine - INFO - Iter(train) [ 8150/120000] base_lr: 1.9776e-04 lr: 1.9796e-05 eta: 14:35:39 time: 0.4724 data_time: 0.0235 memory: 4388 grad_norm: 3.8409 loss: 2.6059 caption_loss_cls: 2.6059 2024/07/14 03:31:05 - mmengine - INFO - Iter(train) [ 8200/120000] base_lr: 1.9773e-04 lr: 1.9793e-05 eta: 14:35:12 time: 0.4725 data_time: 0.0235 memory: 4388 grad_norm: 3.8374 loss: 2.6037 caption_loss_cls: 2.6037 2024/07/14 03:31:28 - mmengine - INFO - Iter(train) [ 8250/120000] base_lr: 1.9770e-04 lr: 1.9791e-05 eta: 14:34:41 time: 0.4725 data_time: 0.0235 memory: 4388 grad_norm: 3.8341 loss: 2.6009 caption_loss_cls: 2.6009 2024/07/14 03:31:51 - 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mmengine - INFO - Saving checkpoint at 9000 iterations 2024/07/14 03:37:41 - mmengine - INFO - Iter(train) [ 9050/120000] base_lr: 1.9723e-04 lr: 1.9749e-05 eta: 14:27:41 time: 0.4656 data_time: 0.0165 memory: 4388 grad_norm: 3.7781 loss: 2.5738 caption_loss_cls: 2.5738 2024/07/14 03:38:04 - mmengine - INFO - Iter(train) [ 9100/120000] base_lr: 1.9720e-04 lr: 1.9746e-05 eta: 14:27:15 time: 0.4657 data_time: 0.0165 memory: 4388 grad_norm: 3.7759 loss: 2.5717 caption_loss_cls: 2.5717 2024/07/14 03:38:27 - mmengine - INFO - Iter(train) [ 9150/120000] base_lr: 1.9717e-04 lr: 1.9743e-05 eta: 14:26:49 time: 0.4657 data_time: 0.0165 memory: 4388 grad_norm: 3.7736 loss: 2.5699 caption_loss_cls: 2.5699 2024/07/14 03:38:50 - mmengine - INFO - Iter(train) [ 9200/120000] base_lr: 1.9714e-04 lr: 1.9740e-05 eta: 14:26:21 time: 0.4657 data_time: 0.0165 memory: 4388 grad_norm: 3.7705 loss: 2.5689 caption_loss_cls: 2.5689 2024/07/14 03:39:13 - mmengine - INFO - Iter(train) [ 9250/120000] base_lr: 1.9711e-04 lr: 1.9737e-05 eta: 14:25:52 time: 0.4656 data_time: 0.0165 memory: 4388 grad_norm: 3.7676 loss: 2.5678 caption_loss_cls: 2.5678 2024/07/14 03:39:36 - 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mmengine - INFO - Saving checkpoint at 10000 iterations 2024/07/14 03:45:17 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:13 time: 0.2779 data_time: 0.0061 memory: 3762 2024/07/14 03:45:31 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:59 time: 0.2783 data_time: 0.0060 memory: 3760 2024/07/14 03:45:45 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:45 time: 0.2785 data_time: 0.0059 memory: 3762 2024/07/14 03:45:59 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2781 data_time: 0.0058 memory: 3762 2024/07/14 03:46:13 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2783 data_time: 0.0058 memory: 3763 2024/07/14 03:46:27 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2782 data_time: 0.0058 memory: 3761 2024/07/14 03:47:01 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7002 Bleu_2: 0.5272 Bleu_3: 0.3886 Bleu_4: 0.2857 METEOR: 0.2406 ROUGE_L: 0.5159 CIDEr: 0.8887 SPICE: 0.1717 data_time: 0.0057 time: 0.2783 2024/07/14 03:47:24 - mmengine - 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mmengine - INFO - Saving checkpoint at 11000 iterations 2024/07/14 03:55:07 - mmengine - INFO - Iter(train) [ 11050/120000] base_lr: 1.9589e-04 lr: 1.9626e-05 eta: 14:14:50 time: 0.4714 data_time: 0.0229 memory: 4387 grad_norm: 3.6777 loss: 2.5157 caption_loss_cls: 2.5157 2024/07/14 03:55:30 - mmengine - INFO - Iter(train) [ 11100/120000] base_lr: 1.9585e-04 lr: 1.9623e-05 eta: 14:14:20 time: 0.4713 data_time: 0.0229 memory: 4387 grad_norm: 3.6763 loss: 2.5141 caption_loss_cls: 2.5141 2024/07/14 03:55:53 - mmengine - INFO - Iter(train) [ 11150/120000] base_lr: 1.9581e-04 lr: 1.9619e-05 eta: 14:13:51 time: 0.4712 data_time: 0.0229 memory: 4387 grad_norm: 3.6741 loss: 2.5132 caption_loss_cls: 2.5132 2024/07/14 03:56:17 - mmengine - INFO - Iter(train) [ 11200/120000] base_lr: 1.9578e-04 lr: 1.9616e-05 eta: 14:13:25 time: 0.4713 data_time: 0.0229 memory: 4387 grad_norm: 3.6724 loss: 2.5117 caption_loss_cls: 2.5117 2024/07/14 03:56:40 - mmengine - INFO - Iter(train) [ 11250/120000] base_lr: 1.9574e-04 lr: 1.9613e-05 eta: 14:12:57 time: 0.4712 data_time: 0.0229 memory: 4387 grad_norm: 3.6708 loss: 2.5101 caption_loss_cls: 2.5101 2024/07/14 03:57:02 - 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mmengine - INFO - Saving checkpoint at 15000 iterations 2024/07/14 04:25:44 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:12 time: 0.2781 data_time: 0.0058 memory: 3761 2024/07/14 04:25:58 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:58 time: 0.2776 data_time: 0.0058 memory: 3758 2024/07/14 04:26:12 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:44 time: 0.2772 data_time: 0.0057 memory: 3764 2024/07/14 04:26:25 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2772 data_time: 0.0057 memory: 3766 2024/07/14 04:26:39 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2772 data_time: 0.0056 memory: 3759 2024/07/14 04:26:53 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2774 data_time: 0.0056 memory: 3760 2024/07/14 04:27:32 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7177 Bleu_2: 0.5488 Bleu_3: 0.4111 Bleu_4: 0.3074 METEOR: 0.2532 ROUGE_L: 0.5323 CIDEr: 0.9687 SPICE: 0.1810 data_time: 0.0052 time: 0.2757 2024/07/14 04:27:54 - mmengine - INFO - Iter(train) [ 15050/120000] base_lr: 1.9242e-04 lr: 1.9310e-05 eta: 13:42:36 time: 0.4689 data_time: 0.0239 memory: 4388 grad_norm: 3.5364 loss: 2.4289 caption_loss_cls: 2.4289 2024/07/14 04:28:17 - mmengine - INFO - Iter(train) [ 15100/120000] base_lr: 1.9237e-04 lr: 1.9306e-05 eta: 13:42:06 time: 0.4689 data_time: 0.0239 memory: 4388 grad_norm: 3.5346 loss: 2.4284 caption_loss_cls: 2.4284 2024/07/14 04:28:39 - mmengine - INFO - Iter(train) [ 15150/120000] base_lr: 1.9232e-04 lr: 1.9301e-05 eta: 13:41:34 time: 0.4687 data_time: 0.0239 memory: 4388 grad_norm: 3.5334 loss: 2.4276 caption_loss_cls: 2.4276 2024/07/14 04:29:02 - mmengine - INFO - Iter(train) [ 15200/120000] base_lr: 1.9227e-04 lr: 1.9297e-05 eta: 13:41:07 time: 0.4686 data_time: 0.0238 memory: 4388 grad_norm: 3.5322 loss: 2.4268 caption_loss_cls: 2.4268 2024/07/14 04:29:25 - mmengine - INFO - Iter(train) [ 15250/120000] base_lr: 1.9222e-04 lr: 1.9292e-05 eta: 13:40:38 time: 0.4685 data_time: 0.0238 memory: 4388 grad_norm: 3.5311 loss: 2.4264 caption_loss_cls: 2.4264 2024/07/14 04:29:47 - 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mmengine - INFO - Saving checkpoint at 19000 iterations 2024/07/14 04:58:28 - mmengine - INFO - Iter(train) [ 19050/120000] base_lr: 1.8794e-04 lr: 1.8904e-05 eta: 13:07:04 time: 0.4584 data_time: 0.0155 memory: 4388 grad_norm: 3.4762 loss: 2.3823 caption_loss_cls: 2.3823 2024/07/14 04:58:51 - mmengine - INFO - Iter(train) [ 19100/120000] base_lr: 1.8788e-04 lr: 1.8898e-05 eta: 13:06:37 time: 0.4585 data_time: 0.0155 memory: 4388 grad_norm: 3.4757 loss: 2.3815 caption_loss_cls: 2.3815 2024/07/14 04:59:13 - mmengine - INFO - Iter(train) [ 19150/120000] base_lr: 1.8782e-04 lr: 1.8893e-05 eta: 13:06:09 time: 0.4585 data_time: 0.0155 memory: 4388 grad_norm: 3.4768 loss: 2.3812 caption_loss_cls: 2.3812 2024/07/14 04:59:36 - mmengine - INFO - Iter(train) [ 19200/120000] base_lr: 1.8776e-04 lr: 1.8887e-05 eta: 13:05:41 time: 0.4584 data_time: 0.0155 memory: 4388 grad_norm: 3.4773 loss: 2.3815 caption_loss_cls: 2.3815 2024/07/14 04:59:59 - mmengine - INFO - Iter(train) [ 19250/120000] base_lr: 1.8769e-04 lr: 1.8881e-05 eta: 13:05:14 time: 0.4584 data_time: 0.0155 memory: 4388 grad_norm: 3.4770 loss: 2.3806 caption_loss_cls: 2.3806 2024/07/14 05:00:21 - 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mmengine - INFO - Saving checkpoint at 20000 iterations 2024/07/14 05:05:57 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:13 time: 0.2775 data_time: 0.0056 memory: 3764 2024/07/14 05:06:11 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:59 time: 0.2776 data_time: 0.0056 memory: 3766 2024/07/14 05:06:25 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:45 time: 0.2775 data_time: 0.0056 memory: 3760 2024/07/14 05:06:39 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2778 data_time: 0.0056 memory: 3759 2024/07/14 05:06:53 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2780 data_time: 0.0056 memory: 3760 2024/07/14 05:07:07 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2779 data_time: 0.0056 memory: 3758 2024/07/14 05:07:40 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7212 Bleu_2: 0.5550 Bleu_3: 0.4197 Bleu_4: 0.3176 METEOR: 0.2583 ROUGE_L: 0.5379 CIDEr: 0.9969 SPICE: 0.1856 data_time: 0.0055 time: 0.2790 2024/07/14 05:08:03 - mmengine - 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mmengine - INFO - Saving checkpoint at 21000 iterations 2024/07/14 05:15:42 - mmengine - INFO - Iter(train) [ 21050/120000] base_lr: 1.8534e-04 lr: 1.8668e-05 eta: 12:51:58 time: 0.4642 data_time: 0.0218 memory: 4388 grad_norm: 3.5061 loss: 2.3623 caption_loss_cls: 2.3623 2024/07/14 05:16:05 - mmengine - INFO - Iter(train) [ 21100/120000] base_lr: 1.8528e-04 lr: 1.8662e-05 eta: 12:51:32 time: 0.4643 data_time: 0.0218 memory: 4388 grad_norm: 3.5065 loss: 2.3619 caption_loss_cls: 2.3619 2024/07/14 05:16:27 - mmengine - INFO - Iter(train) [ 21150/120000] base_lr: 1.8521e-04 lr: 1.8655e-05 eta: 12:51:04 time: 0.4642 data_time: 0.0218 memory: 4388 grad_norm: 3.5066 loss: 2.3616 caption_loss_cls: 2.3616 2024/07/14 05:16:50 - mmengine - INFO - Iter(train) [ 21200/120000] base_lr: 1.8514e-04 lr: 1.8649e-05 eta: 12:50:37 time: 0.4642 data_time: 0.0218 memory: 4388 grad_norm: 3.5072 loss: 2.3615 caption_loss_cls: 2.3615 2024/07/14 05:17:12 - mmengine - INFO - Iter(train) [ 21250/120000] base_lr: 1.8507e-04 lr: 1.8643e-05 eta: 12:50:09 time: 0.4642 data_time: 0.0218 memory: 4388 grad_norm: 3.5080 loss: 2.3604 caption_loss_cls: 2.3604 2024/07/14 05:17:35 - 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mmengine - INFO - Saving checkpoint at 22000 iterations 2024/07/14 05:23:20 - mmengine - INFO - Iter(train) [ 22050/120000] base_lr: 1.8396e-04 lr: 1.8542e-05 eta: 12:43:23 time: 0.4642 data_time: 0.0218 memory: 4388 grad_norm: 3.5109 loss: 2.3485 caption_loss_cls: 2.3485 2024/07/14 05:23:42 - mmengine - INFO - Iter(train) [ 22100/120000] base_lr: 1.8389e-04 lr: 1.8535e-05 eta: 12:42:57 time: 0.4642 data_time: 0.0218 memory: 4388 grad_norm: 3.5105 loss: 2.3484 caption_loss_cls: 2.3484 2024/07/14 05:24:05 - mmengine - INFO - Iter(train) [ 22150/120000] base_lr: 1.8382e-04 lr: 1.8529e-05 eta: 12:42:29 time: 0.4641 data_time: 0.0218 memory: 4388 grad_norm: 3.5118 loss: 2.3475 caption_loss_cls: 2.3475 2024/07/14 05:24:28 - mmengine - INFO - Iter(train) [ 22200/120000] base_lr: 1.8375e-04 lr: 1.8522e-05 eta: 12:42:03 time: 0.4641 data_time: 0.0218 memory: 4388 grad_norm: 3.5126 loss: 2.3472 caption_loss_cls: 2.3472 2024/07/14 05:24:50 - mmengine - INFO - Iter(train) [ 22250/120000] base_lr: 1.8368e-04 lr: 1.8516e-05 eta: 12:41:36 time: 0.4640 data_time: 0.0218 memory: 4388 grad_norm: 3.5144 loss: 2.3477 caption_loss_cls: 2.3477 2024/07/14 05:25:13 - 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mmengine - INFO - Saving checkpoint at 25000 iterations 2024/07/14 05:46:02 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:13 time: 0.2779 data_time: 0.0056 memory: 3759 2024/07/14 05:46:16 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:59 time: 0.2780 data_time: 0.0056 memory: 3760 2024/07/14 05:46:30 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:45 time: 0.2782 data_time: 0.0056 memory: 3760 2024/07/14 05:46:44 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2784 data_time: 0.0056 memory: 3759 2024/07/14 05:46:58 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2784 data_time: 0.0056 memory: 3762 2024/07/14 05:47:12 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2786 data_time: 0.0056 memory: 3760 2024/07/14 05:47:45 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7249 Bleu_2: 0.5586 Bleu_3: 0.4243 Bleu_4: 0.3218 METEOR: 0.2613 ROUGE_L: 0.5415 CIDEr: 1.0213 SPICE: 0.1890 data_time: 0.0057 time: 0.2819 2024/07/14 05:48:08 - mmengine - INFO - Iter(train) [ 25050/120000] base_lr: 1.7946e-04 lr: 1.8133e-05 eta: 12:19:31 time: 0.4632 data_time: 0.0214 memory: 4388 grad_norm: 3.5459 loss: 2.2766 caption_loss_cls: 2.2766 2024/07/14 05:48:30 - mmengine - INFO - Iter(train) [ 25100/120000] base_lr: 1.7939e-04 lr: 1.8126e-05 eta: 12:19:05 time: 0.4632 data_time: 0.0214 memory: 4388 grad_norm: 3.5469 loss: 2.2748 caption_loss_cls: 2.2748 2024/07/14 05:48:53 - mmengine - INFO - Iter(train) [ 25150/120000] base_lr: 1.7931e-04 lr: 1.8119e-05 eta: 12:18:41 time: 0.4633 data_time: 0.0214 memory: 4388 grad_norm: 3.5479 loss: 2.2737 caption_loss_cls: 2.2737 2024/07/14 05:49:16 - mmengine - INFO - Iter(train) [ 25200/120000] base_lr: 1.7923e-04 lr: 1.8112e-05 eta: 12:18:16 time: 0.4634 data_time: 0.0214 memory: 4388 grad_norm: 3.5493 loss: 2.2713 caption_loss_cls: 2.2713 2024/07/14 05:49:39 - mmengine - INFO - Iter(train) [ 25250/120000] base_lr: 1.7915e-04 lr: 1.8104e-05 eta: 12:17:50 time: 0.4635 data_time: 0.0214 memory: 4388 grad_norm: 3.5505 loss: 2.2701 caption_loss_cls: 2.2701 2024/07/14 05:50:02 - 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mmengine - INFO - Saving checkpoint at 35000 iterations 2024/07/14 07:06:08 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:16 time: 0.2795 data_time: 0.0056 memory: 3761 2024/07/14 07:06:22 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2796 data_time: 0.0056 memory: 3760 2024/07/14 07:06:36 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2795 data_time: 0.0056 memory: 3762 2024/07/14 07:06:50 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2796 data_time: 0.0056 memory: 3762 2024/07/14 07:07:04 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2798 data_time: 0.0056 memory: 3762 2024/07/14 07:07:18 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2799 data_time: 0.0056 memory: 3760 2024/07/14 07:07:52 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7274 Bleu_2: 0.5636 Bleu_3: 0.4297 Bleu_4: 0.3274 METEOR: 0.2657 ROUGE_L: 0.5465 CIDEr: 1.0440 SPICE: 0.1946 data_time: 0.0056 time: 0.2837 2024/07/14 07:08:14 - mmengine - 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mmengine - INFO - Saving checkpoint at 40000 iterations 2024/07/14 07:46:25 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2801 data_time: 0.0056 memory: 3761 2024/07/14 07:46:39 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2801 data_time: 0.0056 memory: 3760 2024/07/14 07:46:53 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2801 data_time: 0.0056 memory: 3762 2024/07/14 07:47:07 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2801 data_time: 0.0056 memory: 3760 2024/07/14 07:47:21 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2802 data_time: 0.0056 memory: 3759 2024/07/14 07:47:35 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2802 data_time: 0.0056 memory: 3762 2024/07/14 07:48:10 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7309 Bleu_2: 0.5670 Bleu_3: 0.4332 Bleu_4: 0.3307 METEOR: 0.2676 ROUGE_L: 0.5477 CIDEr: 1.0620 SPICE: 0.1959 data_time: 0.0056 time: 0.2820 2024/07/14 07:48:32 - mmengine - 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mmengine - INFO - Saving checkpoint at 41000 iterations 2024/07/14 07:56:05 - mmengine - INFO - Iter(train) [ 41050/120000] base_lr: 1.4813e-04 lr: 1.5284e-05 eta: 10:12:21 time: 0.4652 data_time: 0.0223 memory: 4388 grad_norm: 3.7258 loss: 2.1655 caption_loss_cls: 2.1655 2024/07/14 07:56:28 - mmengine - INFO - Iter(train) [ 41100/120000] base_lr: 1.4801e-04 lr: 1.5274e-05 eta: 10:11:56 time: 0.4650 data_time: 0.0223 memory: 4388 grad_norm: 3.7285 loss: 2.1656 caption_loss_cls: 2.1656 2024/07/14 07:56:51 - mmengine - INFO - Iter(train) [ 41150/120000] base_lr: 1.4790e-04 lr: 1.5264e-05 eta: 10:11:33 time: 0.4651 data_time: 0.0223 memory: 4388 grad_norm: 3.7313 loss: 2.1644 caption_loss_cls: 2.1644 2024/07/14 07:57:14 - mmengine - INFO - Iter(train) [ 41200/120000] base_lr: 1.4778e-04 lr: 1.5253e-05 eta: 10:11:10 time: 0.4654 data_time: 0.0223 memory: 4388 grad_norm: 3.7323 loss: 2.1648 caption_loss_cls: 2.1648 2024/07/14 07:57:37 - mmengine - INFO - Iter(train) [ 41250/120000] base_lr: 1.4767e-04 lr: 1.5243e-05 eta: 10:10:45 time: 0.4652 data_time: 0.0223 memory: 4388 grad_norm: 3.7328 loss: 2.1645 caption_loss_cls: 2.1645 2024/07/14 07:57:59 - 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mmengine - INFO - Saving checkpoint at 45000 iterations 2024/07/14 08:25:52 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2803 data_time: 0.0056 memory: 3760 2024/07/14 08:26:06 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2803 data_time: 0.0056 memory: 3762 2024/07/14 08:26:21 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2804 data_time: 0.0056 memory: 3767 2024/07/14 08:26:35 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2804 data_time: 0.0056 memory: 3760 2024/07/14 08:26:49 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2804 data_time: 0.0056 memory: 3760 2024/07/14 08:27:03 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2804 data_time: 0.0056 memory: 3759 2024/07/14 08:27:36 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7366 Bleu_2: 0.5736 Bleu_3: 0.4384 Bleu_4: 0.3335 METEOR: 0.2695 ROUGE_L: 0.5522 CIDEr: 1.0734 SPICE: 0.1963 data_time: 0.0055 time: 0.2823 2024/07/14 08:27:58 - mmengine - 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mmengine - INFO - Saving checkpoint at 48000 iterations 2024/07/14 08:50:48 - mmengine - INFO - Iter(train) [ 48050/120000] base_lr: 1.3147e-04 lr: 1.3770e-05 eta: 9:16:20 time: 0.4608 data_time: 0.0217 memory: 4388 grad_norm: 3.7857 loss: 2.1022 caption_loss_cls: 2.1022 2024/07/14 08:51:11 - mmengine - INFO - Iter(train) [ 48100/120000] base_lr: 1.3135e-04 lr: 1.3759e-05 eta: 9:15:57 time: 0.4609 data_time: 0.0217 memory: 4388 grad_norm: 3.7821 loss: 2.1005 caption_loss_cls: 2.1005 2024/07/14 08:51:33 - mmengine - INFO - Iter(train) [ 48150/120000] base_lr: 1.3123e-04 lr: 1.3748e-05 eta: 9:15:32 time: 0.4611 data_time: 0.0217 memory: 4388 grad_norm: 3.7804 loss: 2.0984 caption_loss_cls: 2.0984 2024/07/14 08:51:56 - mmengine - INFO - Iter(train) [ 48200/120000] base_lr: 1.3110e-04 lr: 1.3737e-05 eta: 9:15:08 time: 0.4612 data_time: 0.0217 memory: 4388 grad_norm: 3.7816 loss: 2.0962 caption_loss_cls: 2.0962 2024/07/14 08:52:18 - mmengine - INFO - Iter(train) [ 48250/120000] base_lr: 1.3098e-04 lr: 1.3725e-05 eta: 9:14:44 time: 0.4613 data_time: 0.0217 memory: 4388 grad_norm: 3.7807 loss: 2.0947 caption_loss_cls: 2.0947 2024/07/14 08:52:41 - 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mmengine - INFO - Saving checkpoint at 50000 iterations 2024/07/14 09:05:53 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:14 time: 0.2805 data_time: 0.0056 memory: 3761 2024/07/14 09:06:07 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:01 time: 0.2806 data_time: 0.0056 memory: 3762 2024/07/14 09:06:22 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2807 data_time: 0.0056 memory: 3762 2024/07/14 09:06:36 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2807 data_time: 0.0056 memory: 3759 2024/07/14 09:06:50 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2808 data_time: 0.0056 memory: 3762 2024/07/14 09:07:04 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2807 data_time: 0.0056 memory: 3759 2024/07/14 09:07:37 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7373 Bleu_2: 0.5759 Bleu_3: 0.4419 Bleu_4: 0.3385 METEOR: 0.2712 ROUGE_L: 0.5533 CIDEr: 1.0842 SPICE: 0.1988 data_time: 0.0055 time: 0.2835 2024/07/14 09:08:00 - mmengine - 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mmengine - INFO - Saving checkpoint at 51000 iterations 2024/07/14 09:15:35 - mmengine - INFO - Iter(train) [ 51050/120000] base_lr: 1.2399e-04 lr: 1.3090e-05 eta: 8:53:11 time: 0.4628 data_time: 0.0220 memory: 4388 grad_norm: 3.7039 loss: 1.9883 caption_loss_cls: 1.9883 2024/07/14 09:15:57 - mmengine - INFO - Iter(train) [ 51100/120000] base_lr: 1.2386e-04 lr: 1.3078e-05 eta: 8:52:47 time: 0.4628 data_time: 0.0220 memory: 4388 grad_norm: 3.7016 loss: 1.9866 caption_loss_cls: 1.9866 2024/07/14 09:16:20 - mmengine - INFO - Iter(train) [ 51150/120000] base_lr: 1.2374e-04 lr: 1.3067e-05 eta: 8:52:23 time: 0.4629 data_time: 0.0220 memory: 4388 grad_norm: 3.7013 loss: 1.9856 caption_loss_cls: 1.9856 2024/07/14 09:16:43 - mmengine - INFO - Iter(train) [ 51200/120000] base_lr: 1.2361e-04 lr: 1.3055e-05 eta: 8:51:59 time: 0.4628 data_time: 0.0220 memory: 4388 grad_norm: 3.7009 loss: 1.9840 caption_loss_cls: 1.9840 2024/07/14 09:17:05 - mmengine - INFO - Iter(train) [ 51250/120000] base_lr: 1.2348e-04 lr: 1.3044e-05 eta: 8:51:35 time: 0.4629 data_time: 0.0220 memory: 4388 grad_norm: 3.7011 loss: 1.9836 caption_loss_cls: 1.9836 2024/07/14 09:17:28 - 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mmengine - INFO - Saving checkpoint at 52000 iterations 2024/07/14 09:23:12 - mmengine - INFO - Iter(train) [ 52050/120000] base_lr: 1.2146e-04 lr: 1.2860e-05 eta: 8:45:18 time: 0.4626 data_time: 0.0218 memory: 4388 grad_norm: 3.7101 loss: 1.9865 caption_loss_cls: 1.9865 2024/07/14 09:23:34 - mmengine - INFO - Iter(train) [ 52100/120000] base_lr: 1.2133e-04 lr: 1.2848e-05 eta: 8:44:53 time: 0.4625 data_time: 0.0218 memory: 4388 grad_norm: 3.7124 loss: 1.9863 caption_loss_cls: 1.9863 2024/07/14 09:23:57 - mmengine - INFO - Iter(train) [ 52150/120000] base_lr: 1.2121e-04 lr: 1.2837e-05 eta: 8:44:30 time: 0.4625 data_time: 0.0218 memory: 4388 grad_norm: 3.7137 loss: 1.9868 caption_loss_cls: 1.9868 2024/07/14 09:24:19 - mmengine - INFO - Iter(train) [ 52200/120000] base_lr: 1.2108e-04 lr: 1.2825e-05 eta: 8:44:05 time: 0.4625 data_time: 0.0218 memory: 4388 grad_norm: 3.7128 loss: 1.9873 caption_loss_cls: 1.9873 2024/07/14 09:24:42 - mmengine - INFO - Iter(train) [ 52250/120000] base_lr: 1.2095e-04 lr: 1.2814e-05 eta: 8:43:41 time: 0.4625 data_time: 0.0218 memory: 4388 grad_norm: 3.7140 loss: 1.9872 caption_loss_cls: 1.9872 2024/07/14 09:25:05 - 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mmengine - INFO - Saving checkpoint at 55000 iterations 2024/07/14 09:45:57 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2809 data_time: 0.0056 memory: 3764 2024/07/14 09:46:11 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2809 data_time: 0.0056 memory: 3762 2024/07/14 09:46:25 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2809 data_time: 0.0056 memory: 3763 2024/07/14 09:46:39 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2810 data_time: 0.0056 memory: 3761 2024/07/14 09:46:54 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2811 data_time: 0.0056 memory: 3762 2024/07/14 09:47:08 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2812 data_time: 0.0056 memory: 3760 2024/07/14 09:47:42 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7376 Bleu_2: 0.5764 Bleu_3: 0.4410 Bleu_4: 0.3364 METEOR: 0.2716 ROUGE_L: 0.5544 CIDEr: 1.0850 SPICE: 0.1986 data_time: 0.0055 time: 0.2857 2024/07/14 09:48:05 - mmengine - 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mmengine - INFO - Saving checkpoint at 60000 iterations 2024/07/14 10:26:08 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2813 data_time: 0.0056 memory: 3762 2024/07/14 10:26:22 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2813 data_time: 0.0056 memory: 3759 2024/07/14 10:26:36 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2814 data_time: 0.0056 memory: 3764 2024/07/14 10:26:51 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2814 data_time: 0.0056 memory: 3760 2024/07/14 10:27:05 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2814 data_time: 0.0056 memory: 3760 2024/07/14 10:27:19 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2815 data_time: 0.0056 memory: 3762 2024/07/14 10:27:54 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7415 Bleu_2: 0.5800 Bleu_3: 0.4452 Bleu_4: 0.3402 METEOR: 0.2744 ROUGE_L: 0.5564 CIDEr: 1.1003 SPICE: 0.2021 data_time: 0.0056 time: 0.2844 2024/07/14 10:28:17 - mmengine - 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mmengine - INFO - Saving checkpoint at 61000 iterations 2024/07/14 10:35:59 - mmengine - INFO - Iter(train) [ 61050/120000] base_lr: 9.8282e-05 lr: 1.0753e-05 eta: 7:35:47 time: 0.4653 data_time: 0.0227 memory: 4388 grad_norm: 3.7375 loss: 1.9824 caption_loss_cls: 1.9824 2024/07/14 10:36:22 - mmengine - INFO - Iter(train) [ 61100/120000] base_lr: 9.8152e-05 lr: 1.0741e-05 eta: 7:35:23 time: 0.4653 data_time: 0.0227 memory: 4388 grad_norm: 3.7376 loss: 1.9821 caption_loss_cls: 1.9821 2024/07/14 10:36:45 - mmengine - INFO - Iter(train) [ 61150/120000] base_lr: 9.8022e-05 lr: 1.0729e-05 eta: 7:35:00 time: 0.4654 data_time: 0.0227 memory: 4388 grad_norm: 3.7377 loss: 1.9820 caption_loss_cls: 1.9820 2024/07/14 10:37:08 - mmengine - INFO - Iter(train) [ 61200/120000] base_lr: 9.7893e-05 lr: 1.0718e-05 eta: 7:34:36 time: 0.4656 data_time: 0.0227 memory: 4388 grad_norm: 3.7367 loss: 1.9823 caption_loss_cls: 1.9823 2024/07/14 10:37:30 - mmengine - INFO - Iter(train) [ 61250/120000] base_lr: 9.7763e-05 lr: 1.0706e-05 eta: 7:34:12 time: 0.4657 data_time: 0.0227 memory: 4388 grad_norm: 3.7386 loss: 1.9828 caption_loss_cls: 1.9828 2024/07/14 10:37:53 - 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mmengine - INFO - Saving checkpoint at 65000 iterations 2024/07/14 11:06:28 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:16 time: 0.2816 data_time: 0.0056 memory: 3761 2024/07/14 11:06:42 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:01 time: 0.2817 data_time: 0.0056 memory: 3762 2024/07/14 11:06:56 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:47 time: 0.2817 data_time: 0.0056 memory: 3764 2024/07/14 11:07:11 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2819 data_time: 0.0056 memory: 3760 2024/07/14 11:07:26 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2819 data_time: 0.0055 memory: 3762 2024/07/14 11:07:40 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2820 data_time: 0.0055 memory: 3762 2024/07/14 11:08:14 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7380 Bleu_2: 0.5771 Bleu_3: 0.4429 Bleu_4: 0.3383 METEOR: 0.2736 ROUGE_L: 0.5545 CIDEr: 1.0979 SPICE: 0.2006 data_time: 0.0053 time: 0.2894 2024/07/14 11:08:37 - mmengine - INFO - Iter(train) [ 65050/120000] base_lr: 8.7952e-05 lr: 9.8138e-06 eta: 7:04:57 time: 0.4655 data_time: 0.0221 memory: 4388 grad_norm: 3.8374 loss: 1.9755 caption_loss_cls: 1.9755 2024/07/14 11:09:00 - mmengine - INFO - Iter(train) [ 65100/120000] base_lr: 8.7824e-05 lr: 9.8021e-06 eta: 7:04:33 time: 0.4657 data_time: 0.0221 memory: 4388 grad_norm: 3.8351 loss: 1.9755 caption_loss_cls: 1.9755 2024/07/14 11:09:23 - mmengine - INFO - Iter(train) [ 65150/120000] base_lr: 8.7695e-05 lr: 9.7905e-06 eta: 7:04:10 time: 0.4657 data_time: 0.0221 memory: 4388 grad_norm: 3.8343 loss: 1.9753 caption_loss_cls: 1.9753 2024/07/14 11:09:47 - mmengine - INFO - Iter(train) [ 65200/120000] base_lr: 8.7567e-05 lr: 9.7788e-06 eta: 7:03:47 time: 0.4658 data_time: 0.0221 memory: 4388 grad_norm: 3.8347 loss: 1.9755 caption_loss_cls: 1.9755 2024/07/14 11:10:10 - mmengine - INFO - Iter(train) [ 65250/120000] base_lr: 8.7438e-05 lr: 9.7671e-06 eta: 7:03:24 time: 0.4660 data_time: 0.0221 memory: 4388 grad_norm: 3.8320 loss: 1.9745 caption_loss_cls: 1.9745 2024/07/14 11:10:33 - 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mmengine - INFO - Saving checkpoint at 70000 iterations 2024/07/14 11:46:55 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:16 time: 0.2822 data_time: 0.0055 memory: 3760 2024/07/14 11:47:10 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:01 time: 0.2823 data_time: 0.0055 memory: 3760 2024/07/14 11:47:24 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2824 data_time: 0.0055 memory: 3763 2024/07/14 11:47:38 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2826 data_time: 0.0055 memory: 3762 2024/07/14 11:47:53 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2828 data_time: 0.0055 memory: 3762 2024/07/14 11:48:07 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2829 data_time: 0.0055 memory: 3766 2024/07/14 11:48:41 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7395 Bleu_2: 0.5785 Bleu_3: 0.4445 Bleu_4: 0.3407 METEOR: 0.2742 ROUGE_L: 0.5563 CIDEr: 1.1056 SPICE: 0.2022 data_time: 0.0056 time: 0.2876 2024/07/14 11:49:04 - mmengine - 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mmengine - INFO - Saving checkpoint at 71000 iterations 2024/07/14 11:56:40 - mmengine - INFO - Iter(train) [ 71050/120000] base_lr: 7.2761e-05 lr: 8.4328e-06 eta: 6:18:35 time: 0.4652 data_time: 0.0221 memory: 4388 grad_norm: 3.6881 loss: 1.9445 caption_loss_cls: 1.9445 2024/07/14 11:57:02 - mmengine - INFO - Iter(train) [ 71100/120000] base_lr: 7.2637e-05 lr: 8.4215e-06 eta: 6:18:12 time: 0.4652 data_time: 0.0221 memory: 4388 grad_norm: 3.6885 loss: 1.9427 caption_loss_cls: 1.9427 2024/07/14 11:57:26 - mmengine - INFO - Iter(train) [ 71150/120000] base_lr: 7.2512e-05 lr: 8.4102e-06 eta: 6:17:48 time: 0.4652 data_time: 0.0221 memory: 4388 grad_norm: 3.6872 loss: 1.9398 caption_loss_cls: 1.9398 2024/07/14 11:57:48 - mmengine - INFO - Iter(train) [ 71200/120000] base_lr: 7.2388e-05 lr: 8.3989e-06 eta: 6:17:25 time: 0.4652 data_time: 0.0221 memory: 4388 grad_norm: 3.6878 loss: 1.9386 caption_loss_cls: 1.9386 2024/07/14 11:58:11 - mmengine - INFO - Iter(train) [ 71250/120000] base_lr: 7.2264e-05 lr: 8.3877e-06 eta: 6:17:01 time: 0.4652 data_time: 0.0221 memory: 4388 grad_norm: 3.6873 loss: 1.9368 caption_loss_cls: 1.9368 2024/07/14 11:58:34 - 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mmengine - INFO - Saving checkpoint at 75000 iterations 2024/07/14 12:27:13 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2830 data_time: 0.0055 memory: 3759 2024/07/14 12:27:27 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2831 data_time: 0.0055 memory: 3762 2024/07/14 12:27:41 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2831 data_time: 0.0055 memory: 3765 2024/07/14 12:27:56 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2832 data_time: 0.0055 memory: 3762 2024/07/14 12:28:10 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2834 data_time: 0.0055 memory: 3764 2024/07/14 12:28:24 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2834 data_time: 0.0055 memory: 3761 2024/07/14 12:28:59 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7419 Bleu_2: 0.5807 Bleu_3: 0.4457 Bleu_4: 0.3408 METEOR: 0.2751 ROUGE_L: 0.5572 CIDEr: 1.1146 SPICE: 0.2025 data_time: 0.0053 time: 0.2845 2024/07/14 12:29:22 - mmengine - 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mmengine - INFO - Saving checkpoint at 78000 iterations 2024/07/14 12:52:21 - mmengine - INFO - Iter(train) [ 78050/120000] base_lr: 5.5942e-05 lr: 6.9038e-06 eta: 5:24:26 time: 0.4669 data_time: 0.0224 memory: 4388 grad_norm: 3.7817 loss: 1.7981 caption_loss_cls: 1.7981 2024/07/14 12:52:44 - mmengine - INFO - Iter(train) [ 78100/120000] base_lr: 5.5826e-05 lr: 6.8933e-06 eta: 5:24:02 time: 0.4668 data_time: 0.0224 memory: 4388 grad_norm: 3.7819 loss: 1.7976 caption_loss_cls: 1.7976 2024/07/14 12:53:07 - mmengine - INFO - Iter(train) [ 78150/120000] base_lr: 5.5711e-05 lr: 6.8828e-06 eta: 5:23:39 time: 0.4666 data_time: 0.0224 memory: 4388 grad_norm: 3.7831 loss: 1.7972 caption_loss_cls: 1.7972 2024/07/14 12:53:29 - mmengine - INFO - Iter(train) [ 78200/120000] base_lr: 5.5596e-05 lr: 6.8724e-06 eta: 5:23:16 time: 0.4666 data_time: 0.0224 memory: 4388 grad_norm: 3.7828 loss: 1.7967 caption_loss_cls: 1.7967 2024/07/14 12:53:52 - mmengine - INFO - Iter(train) [ 78250/120000] base_lr: 5.5481e-05 lr: 6.8619e-06 eta: 5:22:52 time: 0.4664 data_time: 0.0224 memory: 4388 grad_norm: 3.7830 loss: 1.7971 caption_loss_cls: 1.7971 2024/07/14 12:54:15 - 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mmengine - INFO - Saving checkpoint at 79000 iterations 2024/07/14 13:00:02 - mmengine - INFO - Iter(train) [ 79050/120000] base_lr: 5.3650e-05 lr: 6.6954e-06 eta: 5:16:40 time: 0.4597 data_time: 0.0157 memory: 4388 grad_norm: 3.7833 loss: 1.7955 caption_loss_cls: 1.7955 2024/07/14 13:00:24 - mmengine - INFO - Iter(train) [ 79100/120000] base_lr: 5.3536e-05 lr: 6.6851e-06 eta: 5:16:16 time: 0.4597 data_time: 0.0157 memory: 4388 grad_norm: 3.7828 loss: 1.7950 caption_loss_cls: 1.7950 2024/07/14 13:00:47 - mmengine - INFO - Iter(train) [ 79150/120000] base_lr: 5.3422e-05 lr: 6.6748e-06 eta: 5:15:53 time: 0.4597 data_time: 0.0157 memory: 4388 grad_norm: 3.7838 loss: 1.7955 caption_loss_cls: 1.7955 2024/07/14 13:01:10 - mmengine - INFO - Iter(train) [ 79200/120000] base_lr: 5.3309e-05 lr: 6.6644e-06 eta: 5:15:30 time: 0.4598 data_time: 0.0157 memory: 4388 grad_norm: 3.7832 loss: 1.7956 caption_loss_cls: 1.7956 2024/07/14 13:01:33 - mmengine - INFO - Iter(train) [ 79250/120000] base_lr: 5.3195e-05 lr: 6.6541e-06 eta: 5:15:06 time: 0.4597 data_time: 0.0157 memory: 4388 grad_norm: 3.7828 loss: 1.7958 caption_loss_cls: 1.7958 2024/07/14 13:01:55 - 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mmengine - INFO - Saving checkpoint at 80000 iterations 2024/07/14 13:07:33 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:16 time: 0.2837 data_time: 0.0055 memory: 3762 2024/07/14 13:07:47 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:02 time: 0.2839 data_time: 0.0055 memory: 3762 2024/07/14 13:08:02 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:47 time: 0.2840 data_time: 0.0055 memory: 3766 2024/07/14 13:08:16 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2842 data_time: 0.0055 memory: 3762 2024/07/14 13:08:30 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2843 data_time: 0.0055 memory: 3762 2024/07/14 13:08:45 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2844 data_time: 0.0055 memory: 3765 2024/07/14 13:09:19 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7436 Bleu_2: 0.5827 Bleu_3: 0.4488 Bleu_4: 0.3443 METEOR: 0.2762 ROUGE_L: 0.5587 CIDEr: 1.1162 SPICE: 0.2033 data_time: 0.0057 time: 0.2885 2024/07/14 13:09:41 - mmengine - 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mmengine - INFO - Saving checkpoint at 81000 iterations 2024/07/14 13:17:21 - mmengine - INFO - Iter(train) [ 81050/120000] base_lr: 4.9164e-05 lr: 6.2877e-06 eta: 5:01:20 time: 0.4661 data_time: 0.0222 memory: 4388 grad_norm: 3.7893 loss: 1.7950 caption_loss_cls: 1.7950 2024/07/14 13:17:44 - mmengine - INFO - Iter(train) [ 81100/120000] base_lr: 4.9054e-05 lr: 6.2776e-06 eta: 5:00:56 time: 0.4659 data_time: 0.0222 memory: 4388 grad_norm: 3.7893 loss: 1.7957 caption_loss_cls: 1.7957 2024/07/14 13:18:07 - mmengine - INFO - Iter(train) [ 81150/120000] base_lr: 4.8944e-05 lr: 6.2676e-06 eta: 5:00:33 time: 0.4660 data_time: 0.0222 memory: 4388 grad_norm: 3.7888 loss: 1.7960 caption_loss_cls: 1.7960 2024/07/14 13:18:29 - mmengine - INFO - Iter(train) [ 81200/120000] base_lr: 4.8834e-05 lr: 6.2576e-06 eta: 5:00:10 time: 0.4659 data_time: 0.0222 memory: 4388 grad_norm: 3.7886 loss: 1.7957 caption_loss_cls: 1.7957 2024/07/14 13:18:52 - mmengine - INFO - Iter(train) [ 81250/120000] base_lr: 4.8723e-05 lr: 6.2476e-06 eta: 4:59:46 time: 0.4659 data_time: 0.0222 memory: 4388 grad_norm: 3.7883 loss: 1.7958 caption_loss_cls: 1.7958 2024/07/14 13:19:15 - 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mmengine - INFO - Saving checkpoint at 85000 iterations 2024/07/14 13:47:51 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:17 time: 0.2846 data_time: 0.0056 memory: 3762 2024/07/14 13:48:05 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:01 time: 0.2847 data_time: 0.0056 memory: 3762 2024/07/14 13:48:19 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:47 time: 0.2847 data_time: 0.0055 memory: 3766 2024/07/14 13:48:33 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2847 data_time: 0.0055 memory: 3760 2024/07/14 13:48:48 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2849 data_time: 0.0055 memory: 3762 2024/07/14 13:49:02 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2850 data_time: 0.0055 memory: 3764 2024/07/14 13:49:34 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7430 Bleu_2: 0.5813 Bleu_3: 0.4470 Bleu_4: 0.3427 METEOR: 0.2769 ROUGE_L: 0.5593 CIDEr: 1.1166 SPICE: 0.2045 data_time: 0.0053 time: 0.2874 2024/07/14 13:49:57 - mmengine - 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mmengine - INFO - Saving checkpoint at 88000 iterations 2024/07/14 14:13:00 - mmengine - INFO - Iter(train) [ 88050/120000] base_lr: 3.4662e-05 lr: 4.9692e-06 eta: 4:07:09 time: 0.4668 data_time: 0.0218 memory: 4388 grad_norm: 3.8156 loss: 1.7844 caption_loss_cls: 1.7844 2024/07/14 14:13:23 - mmengine - INFO - Iter(train) [ 88100/120000] base_lr: 3.4566e-05 lr: 4.9605e-06 eta: 4:06:45 time: 0.4668 data_time: 0.0218 memory: 4388 grad_norm: 3.8156 loss: 1.7841 caption_loss_cls: 1.7841 2024/07/14 14:13:46 - mmengine - INFO - Iter(train) [ 88150/120000] base_lr: 3.4470e-05 lr: 4.9518e-06 eta: 4:06:22 time: 0.4669 data_time: 0.0218 memory: 4388 grad_norm: 3.8162 loss: 1.7839 caption_loss_cls: 1.7839 2024/07/14 14:14:09 - mmengine - INFO - Iter(train) [ 88200/120000] base_lr: 3.4374e-05 lr: 4.9431e-06 eta: 4:05:59 time: 0.4669 data_time: 0.0217 memory: 4388 grad_norm: 3.8162 loss: 1.7835 caption_loss_cls: 1.7835 2024/07/14 14:14:32 - mmengine - INFO - Iter(train) [ 88250/120000] base_lr: 3.4278e-05 lr: 4.9344e-06 eta: 4:05:35 time: 0.4670 data_time: 0.0217 memory: 4388 grad_norm: 3.8173 loss: 1.7838 caption_loss_cls: 1.7838 2024/07/14 14:14:55 - 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mmengine - INFO - Saving checkpoint at 90000 iterations 2024/07/14 14:28:14 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:17 time: 0.2852 data_time: 0.0055 memory: 3759 2024/07/14 14:28:29 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:01 time: 0.2852 data_time: 0.0055 memory: 3764 2024/07/14 14:28:43 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:47 time: 0.2853 data_time: 0.0055 memory: 3764 2024/07/14 14:28:57 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2853 data_time: 0.0055 memory: 3762 2024/07/14 14:29:11 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2853 data_time: 0.0055 memory: 3764 2024/07/14 14:29:26 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2853 data_time: 0.0055 memory: 3766 2024/07/14 14:30:02 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7400 Bleu_2: 0.5794 Bleu_3: 0.4460 Bleu_4: 0.3425 METEOR: 0.2763 ROUGE_L: 0.5583 CIDEr: 1.1125 SPICE: 0.2039 data_time: 0.0053 time: 0.2863 2024/07/14 14:30:25 - mmengine - 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mmengine - INFO - Saving checkpoint at 91000 iterations 2024/07/14 14:38:06 - mmengine - INFO - Iter(train) [ 91050/120000] base_lr: 2.9101e-05 lr: 4.4637e-06 eta: 3:44:02 time: 0.4682 data_time: 0.0230 memory: 4388 grad_norm: 3.8360 loss: 1.7806 caption_loss_cls: 1.7806 2024/07/14 14:38:28 - mmengine - INFO - Iter(train) [ 91100/120000] base_lr: 2.9012e-05 lr: 4.4556e-06 eta: 3:43:39 time: 0.4681 data_time: 0.0230 memory: 4388 grad_norm: 3.8362 loss: 1.7804 caption_loss_cls: 1.7804 2024/07/14 14:38:52 - mmengine - INFO - Iter(train) [ 91150/120000] base_lr: 2.8923e-05 lr: 4.4475e-06 eta: 3:43:15 time: 0.4682 data_time: 0.0230 memory: 4388 grad_norm: 3.8355 loss: 1.7802 caption_loss_cls: 1.7802 2024/07/14 14:39:14 - mmengine - INFO - Iter(train) [ 91200/120000] base_lr: 2.8834e-05 lr: 4.4394e-06 eta: 3:42:52 time: 0.4682 data_time: 0.0230 memory: 4388 grad_norm: 3.8358 loss: 1.7804 caption_loss_cls: 1.7804 2024/07/14 14:39:37 - mmengine - INFO - Iter(train) [ 91250/120000] base_lr: 2.8745e-05 lr: 4.4314e-06 eta: 3:42:29 time: 0.4682 data_time: 0.0230 memory: 4388 grad_norm: 3.8366 loss: 1.7809 caption_loss_cls: 1.7809 2024/07/14 14:40:00 - 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mmengine - INFO - Saving checkpoint at 95000 iterations 2024/07/14 15:07:39 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:09 time: 0.2851 data_time: 0.0055 memory: 3762 2024/07/14 15:07:53 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:56 time: 0.2849 data_time: 0.0055 memory: 3764 2024/07/14 15:08:06 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:43 time: 0.2847 data_time: 0.0055 memory: 3764 2024/07/14 15:08:19 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:30 time: 0.2845 data_time: 0.0055 memory: 3760 2024/07/14 15:08:33 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:16 time: 0.2843 data_time: 0.0054 memory: 3762 2024/07/14 15:08:46 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2840 data_time: 0.0054 memory: 3762 2024/07/14 15:09:17 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7417 Bleu_2: 0.5802 Bleu_3: 0.4461 Bleu_4: 0.3424 METEOR: 0.2763 ROUGE_L: 0.5586 CIDEr: 1.1102 SPICE: 0.2049 data_time: 0.0050 time: 0.2656 2024/07/14 15:09:39 - mmengine - 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mmengine - INFO - Saving checkpoint at 98000 iterations 2024/07/14 15:31:31 - mmengine - INFO - Iter(train) [ 98050/120000] base_lr: 1.7903e-05 lr: 3.4457e-06 eta: 2:49:22 time: 0.4436 data_time: 0.0208 memory: 4388 grad_norm: 3.8706 loss: 1.6576 caption_loss_cls: 1.6576 2024/07/14 15:31:53 - mmengine - INFO - Iter(train) [ 98100/120000] base_lr: 1.7832e-05 lr: 3.4393e-06 eta: 2:48:58 time: 0.4436 data_time: 0.0208 memory: 4388 grad_norm: 3.8709 loss: 1.6557 caption_loss_cls: 1.6557 2024/07/14 15:32:15 - mmengine - INFO - Iter(train) [ 98150/120000] base_lr: 1.7762e-05 lr: 3.4329e-06 eta: 2:48:35 time: 0.4434 data_time: 0.0208 memory: 4388 grad_norm: 3.8701 loss: 1.6534 caption_loss_cls: 1.6534 2024/07/14 15:32:36 - mmengine - INFO - Iter(train) [ 98200/120000] base_lr: 1.7692e-05 lr: 3.4265e-06 eta: 2:48:11 time: 0.4433 data_time: 0.0208 memory: 4388 grad_norm: 3.8709 loss: 1.6523 caption_loss_cls: 1.6523 2024/07/14 15:32:57 - mmengine - INFO - Iter(train) [ 98250/120000] base_lr: 1.7622e-05 lr: 3.4202e-06 eta: 2:47:48 time: 0.4432 data_time: 0.0208 memory: 4388 grad_norm: 3.8719 loss: 1.6509 caption_loss_cls: 1.6509 2024/07/14 15:33:19 - 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mmengine - INFO - Saving checkpoint at 100000 iterations 2024/07/14 15:45:59 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:11 time: 0.2838 data_time: 0.0054 memory: 3768 2024/07/14 15:46:12 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:57 time: 0.2837 data_time: 0.0054 memory: 3766 2024/07/14 15:46:26 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:43 time: 0.2835 data_time: 0.0054 memory: 3766 2024/07/14 15:46:39 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:30 time: 0.2832 data_time: 0.0054 memory: 3762 2024/07/14 15:46:52 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:16 time: 0.2829 data_time: 0.0054 memory: 3764 2024/07/14 15:47:05 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2827 data_time: 0.0054 memory: 3762 2024/07/14 15:47:38 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7422 Bleu_2: 0.5809 Bleu_3: 0.4463 Bleu_4: 0.3417 METEOR: 0.2767 ROUGE_L: 0.5587 CIDEr: 1.1118 SPICE: 0.2052 data_time: 0.0049 time: 0.2665 2024/07/14 15:47:59 - mmengine - 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mmengine - INFO - Saving checkpoint at 101000 iterations 2024/07/14 15:55:26 - mmengine - INFO - Iter(train) [101050/120000] base_lr: 1.3937e-05 lr: 3.0851e-06 eta: 2:26:05 time: 0.4462 data_time: 0.0212 memory: 4388 grad_norm: 3.9072 loss: 1.6463 caption_loss_cls: 1.6463 2024/07/14 15:55:49 - mmengine - INFO - Iter(train) [101100/120000] base_lr: 1.3875e-05 lr: 3.0795e-06 eta: 2:25:42 time: 0.4465 data_time: 0.0212 memory: 4388 grad_norm: 3.9070 loss: 1.6465 caption_loss_cls: 1.6465 2024/07/14 15:56:12 - mmengine - INFO - Iter(train) [101150/120000] base_lr: 1.3813e-05 lr: 3.0740e-06 eta: 2:25:18 time: 0.4466 data_time: 0.0212 memory: 4388 grad_norm: 3.9074 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 15:56:34 - mmengine - INFO - Iter(train) [101200/120000] base_lr: 1.3752e-05 lr: 3.0684e-06 eta: 2:24:55 time: 0.4468 data_time: 0.0212 memory: 4388 grad_norm: 3.9076 loss: 1.6462 caption_loss_cls: 1.6462 2024/07/14 15:56:57 - mmengine - INFO - Iter(train) [101250/120000] base_lr: 1.3691e-05 lr: 3.0628e-06 eta: 2:24:32 time: 0.4470 data_time: 0.0212 memory: 4388 grad_norm: 3.9083 loss: 1.6463 caption_loss_cls: 1.6463 2024/07/14 15:57:20 - mmengine - INFO - Iter(train) [101300/120000] base_lr: 1.3630e-05 lr: 3.0573e-06 eta: 2:24:09 time: 0.4473 data_time: 0.0213 memory: 4388 grad_norm: 3.9088 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 15:57:43 - mmengine - INFO - Iter(train) [101350/120000] base_lr: 1.3569e-05 lr: 3.0517e-06 eta: 2:23:46 time: 0.4475 data_time: 0.0213 memory: 4388 grad_norm: 3.9092 loss: 1.6470 caption_loss_cls: 1.6470 2024/07/14 15:58:06 - mmengine - INFO - Iter(train) [101400/120000] base_lr: 1.3508e-05 lr: 3.0462e-06 eta: 2:23:22 time: 0.4478 data_time: 0.0213 memory: 4388 grad_norm: 3.9097 loss: 1.6475 caption_loss_cls: 1.6475 2024/07/14 15:58:29 - mmengine - INFO - Iter(train) [101450/120000] base_lr: 1.3448e-05 lr: 3.0407e-06 eta: 2:22:59 time: 0.4480 data_time: 0.0213 memory: 4388 grad_norm: 3.9102 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 15:58:51 - mmengine - INFO - Iter(train) [101500/120000] base_lr: 1.3387e-05 lr: 3.0352e-06 eta: 2:22:36 time: 0.4483 data_time: 0.0213 memory: 4388 grad_norm: 3.9101 loss: 1.6460 caption_loss_cls: 1.6460 2024/07/14 15:59:14 - mmengine - INFO - Iter(train) [101550/120000] base_lr: 1.3327e-05 lr: 3.0297e-06 eta: 2:22:13 time: 0.4486 data_time: 0.0213 memory: 4388 grad_norm: 3.9103 loss: 1.6458 caption_loss_cls: 1.6458 2024/07/14 15:59:37 - mmengine - INFO - Iter(train) [101600/120000] base_lr: 1.3267e-05 lr: 3.0243e-06 eta: 2:21:50 time: 0.4488 data_time: 0.0213 memory: 4388 grad_norm: 3.9105 loss: 1.6458 caption_loss_cls: 1.6458 2024/07/14 16:00:00 - mmengine - INFO - Iter(train) [101650/120000] base_lr: 1.3207e-05 lr: 3.0188e-06 eta: 2:21:27 time: 0.4493 data_time: 0.0213 memory: 4388 grad_norm: 3.9109 loss: 1.6457 caption_loss_cls: 1.6457 2024/07/14 16:00:23 - mmengine - INFO - Iter(train) [101700/120000] base_lr: 1.3147e-05 lr: 3.0134e-06 eta: 2:21:03 time: 0.4495 data_time: 0.0214 memory: 4388 grad_norm: 3.9133 loss: 1.6463 caption_loss_cls: 1.6463 2024/07/14 16:00:46 - mmengine - INFO - Iter(train) [101750/120000] base_lr: 1.3088e-05 lr: 3.0080e-06 eta: 2:20:40 time: 0.4498 data_time: 0.0214 memory: 4388 grad_norm: 3.9147 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 16:01:08 - mmengine - INFO - Iter(train) [101800/120000] base_lr: 1.3028e-05 lr: 3.0026e-06 eta: 2:20:17 time: 0.4501 data_time: 0.0214 memory: 4388 grad_norm: 3.9145 loss: 1.6461 caption_loss_cls: 1.6461 2024/07/14 16:01:31 - mmengine - INFO - Iter(train) [101850/120000] base_lr: 1.2969e-05 lr: 2.9972e-06 eta: 2:19:54 time: 0.4503 data_time: 0.0214 memory: 4388 grad_norm: 3.9153 loss: 1.6462 caption_loss_cls: 1.6462 2024/07/14 16:01:54 - mmengine - INFO - Iter(train) [101900/120000] base_lr: 1.2910e-05 lr: 2.9918e-06 eta: 2:19:31 time: 0.4506 data_time: 0.0214 memory: 4388 grad_norm: 3.9162 loss: 1.6462 caption_loss_cls: 1.6462 2024/07/14 16:02:16 - mmengine - INFO - Iter(train) [101950/120000] base_lr: 1.2850e-05 lr: 2.9864e-06 eta: 2:19:07 time: 0.4508 data_time: 0.0214 memory: 4388 grad_norm: 3.9173 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 16:02:39 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240714_022410 2024/07/14 16:02:39 - mmengine - INFO - Iter(train) [102000/120000] base_lr: 1.2792e-05 lr: 2.9810e-06 eta: 2:18:44 time: 0.4510 data_time: 0.0214 memory: 4388 grad_norm: 3.9177 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 16:02:39 - mmengine - INFO - Saving checkpoint at 102000 iterations 2024/07/14 16:03:06 - mmengine - INFO - Iter(train) [102050/120000] base_lr: 1.2733e-05 lr: 2.9757e-06 eta: 2:18:22 time: 0.4513 data_time: 0.0215 memory: 4388 grad_norm: 3.9171 loss: 1.6462 caption_loss_cls: 1.6462 2024/07/14 16:03:29 - mmengine - INFO - Iter(train) [102100/120000] base_lr: 1.2674e-05 lr: 2.9704e-06 eta: 2:17:59 time: 0.4516 data_time: 0.0215 memory: 4388 grad_norm: 3.9180 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 16:03:52 - mmengine - INFO - Iter(train) [102150/120000] base_lr: 1.2616e-05 lr: 2.9651e-06 eta: 2:17:35 time: 0.4518 data_time: 0.0215 memory: 4388 grad_norm: 3.9205 loss: 1.6477 caption_loss_cls: 1.6477 2024/07/14 16:04:15 - mmengine - INFO - Iter(train) [102200/120000] base_lr: 1.2557e-05 lr: 2.9598e-06 eta: 2:17:12 time: 0.4522 data_time: 0.0215 memory: 4388 grad_norm: 3.9212 loss: 1.6471 caption_loss_cls: 1.6471 2024/07/14 16:04:38 - mmengine - INFO - Iter(train) [102250/120000] base_lr: 1.2499e-05 lr: 2.9545e-06 eta: 2:16:49 time: 0.4527 data_time: 0.0215 memory: 4388 grad_norm: 3.9217 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 16:05:01 - mmengine - INFO - Iter(train) [102300/120000] base_lr: 1.2441e-05 lr: 2.9492e-06 eta: 2:16:26 time: 0.4531 data_time: 0.0216 memory: 4388 grad_norm: 3.9214 loss: 1.6465 caption_loss_cls: 1.6465 2024/07/14 16:05:24 - mmengine - INFO - Iter(train) [102350/120000] base_lr: 1.2383e-05 lr: 2.9439e-06 eta: 2:16:03 time: 0.4535 data_time: 0.0216 memory: 4388 grad_norm: 3.9223 loss: 1.6470 caption_loss_cls: 1.6470 2024/07/14 16:05:47 - mmengine - INFO - Iter(train) [102400/120000] base_lr: 1.2326e-05 lr: 2.9387e-06 eta: 2:15:40 time: 0.4539 data_time: 0.0216 memory: 4388 grad_norm: 3.9225 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 16:06:10 - mmengine - INFO - Iter(train) [102450/120000] base_lr: 1.2268e-05 lr: 2.9335e-06 eta: 2:15:16 time: 0.4543 data_time: 0.0216 memory: 4388 grad_norm: 3.9230 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 16:06:32 - mmengine - INFO - Iter(train) [102500/120000] base_lr: 1.2211e-05 lr: 2.9282e-06 eta: 2:14:53 time: 0.4546 data_time: 0.0217 memory: 4388 grad_norm: 3.9243 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 16:06:55 - mmengine - INFO - Iter(train) [102550/120000] base_lr: 1.2154e-05 lr: 2.9230e-06 eta: 2:14:30 time: 0.4551 data_time: 0.0217 memory: 4388 grad_norm: 3.9241 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 16:07:18 - mmengine - INFO - Iter(train) [102600/120000] base_lr: 1.2096e-05 lr: 2.9179e-06 eta: 2:14:07 time: 0.4554 data_time: 0.0217 memory: 4388 grad_norm: 3.9243 loss: 1.6470 caption_loss_cls: 1.6470 2024/07/14 16:07:41 - mmengine - INFO - Iter(train) [102650/120000] base_lr: 1.2039e-05 lr: 2.9127e-06 eta: 2:13:44 time: 0.4558 data_time: 0.0217 memory: 4388 grad_norm: 3.9244 loss: 1.6472 caption_loss_cls: 1.6472 2024/07/14 16:08:04 - mmengine - INFO - Iter(train) [102700/120000] base_lr: 1.1983e-05 lr: 2.9075e-06 eta: 2:13:21 time: 0.4560 data_time: 0.0217 memory: 4388 grad_norm: 3.9256 loss: 1.6476 caption_loss_cls: 1.6476 2024/07/14 16:08:26 - mmengine - INFO - Iter(train) [102750/120000] base_lr: 1.1926e-05 lr: 2.9024e-06 eta: 2:12:57 time: 0.4562 data_time: 0.0217 memory: 4388 grad_norm: 3.9259 loss: 1.6474 caption_loss_cls: 1.6474 2024/07/14 16:08:49 - mmengine - INFO - Iter(train) [102800/120000] base_lr: 1.1870e-05 lr: 2.8972e-06 eta: 2:12:34 time: 0.4565 data_time: 0.0218 memory: 4388 grad_norm: 3.9262 loss: 1.6472 caption_loss_cls: 1.6472 2024/07/14 16:09:12 - mmengine - INFO - Iter(train) [102850/120000] base_lr: 1.1813e-05 lr: 2.8921e-06 eta: 2:12:11 time: 0.4568 data_time: 0.0218 memory: 4388 grad_norm: 3.9270 loss: 1.6478 caption_loss_cls: 1.6478 2024/07/14 16:09:35 - mmengine - INFO - Iter(train) [102900/120000] base_lr: 1.1757e-05 lr: 2.8870e-06 eta: 2:11:48 time: 0.4570 data_time: 0.0218 memory: 4388 grad_norm: 3.9262 loss: 1.6472 caption_loss_cls: 1.6472 2024/07/14 16:09:58 - mmengine - INFO - Iter(train) [102950/120000] base_lr: 1.1701e-05 lr: 2.8819e-06 eta: 2:11:25 time: 0.4573 data_time: 0.0218 memory: 4388 grad_norm: 3.9261 loss: 1.6474 caption_loss_cls: 1.6474 2024/07/14 16:10:21 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240714_022410 2024/07/14 16:10:21 - mmengine - INFO - Iter(train) [103000/120000] base_lr: 1.1645e-05 lr: 2.8768e-06 eta: 2:11:01 time: 0.4576 data_time: 0.0218 memory: 4388 grad_norm: 3.9257 loss: 1.6472 caption_loss_cls: 1.6472 2024/07/14 16:10:21 - mmengine - INFO - Saving checkpoint at 103000 iterations 2024/07/14 16:10:48 - mmengine - INFO - Iter(train) [103050/120000] base_lr: 1.1589e-05 lr: 2.8718e-06 eta: 2:10:39 time: 0.4578 data_time: 0.0219 memory: 4388 grad_norm: 3.9262 loss: 1.6472 caption_loss_cls: 1.6472 2024/07/14 16:11:11 - mmengine - INFO - Iter(train) [103100/120000] base_lr: 1.1534e-05 lr: 2.8667e-06 eta: 2:10:16 time: 0.4581 data_time: 0.0219 memory: 4388 grad_norm: 3.9267 loss: 1.6476 caption_loss_cls: 1.6476 2024/07/14 16:11:34 - mmengine - INFO - Iter(train) [103150/120000] base_lr: 1.1478e-05 lr: 2.8617e-06 eta: 2:09:53 time: 0.4584 data_time: 0.0219 memory: 4388 grad_norm: 3.9280 loss: 1.6479 caption_loss_cls: 1.6479 2024/07/14 16:11:57 - mmengine - INFO - Iter(train) [103200/120000] base_lr: 1.1423e-05 lr: 2.8567e-06 eta: 2:09:30 time: 0.4587 data_time: 0.0219 memory: 4388 grad_norm: 3.9288 loss: 1.6484 caption_loss_cls: 1.6484 2024/07/14 16:12:20 - mmengine - INFO - Iter(train) [103250/120000] base_lr: 1.1368e-05 lr: 2.8516e-06 eta: 2:09:06 time: 0.4590 data_time: 0.0219 memory: 4388 grad_norm: 3.9301 loss: 1.6489 caption_loss_cls: 1.6489 2024/07/14 16:12:42 - 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mmengine - INFO - Saving checkpoint at 105000 iterations 2024/07/14 16:26:02 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2827 data_time: 0.0054 memory: 3759 2024/07/14 16:26:16 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2828 data_time: 0.0054 memory: 3764 2024/07/14 16:26:30 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2828 data_time: 0.0054 memory: 3764 2024/07/14 16:26:44 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2828 data_time: 0.0054 memory: 3762 2024/07/14 16:26:59 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:18 time: 0.2830 data_time: 0.0054 memory: 3760 2024/07/14 16:27:13 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2831 data_time: 0.0054 memory: 3766 2024/07/14 16:27:48 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7426 Bleu_2: 0.5803 Bleu_3: 0.4452 Bleu_4: 0.3406 METEOR: 0.2762 ROUGE_L: 0.5584 CIDEr: 1.1114 SPICE: 0.2052 data_time: 0.0054 time: 0.2877 2024/07/14 16:28:11 - mmengine - INFO - Iter(train) [105050/120000] base_lr: 9.4874e-06 lr: 2.6807e-06 eta: 1:55:17 time: 0.4673 data_time: 0.0227 memory: 4388 grad_norm: 3.9470 loss: 1.6471 caption_loss_cls: 1.6471 2024/07/14 16:28:34 - mmengine - INFO - Iter(train) [105100/120000] base_lr: 9.4380e-06 lr: 2.6762e-06 eta: 1:54:54 time: 0.4674 data_time: 0.0227 memory: 4388 grad_norm: 3.9471 loss: 1.6469 caption_loss_cls: 1.6469 2024/07/14 16:28:57 - mmengine - INFO - Iter(train) [105150/120000] base_lr: 9.3888e-06 lr: 2.6717e-06 eta: 1:54:31 time: 0.4675 data_time: 0.0227 memory: 4388 grad_norm: 3.9470 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 16:29:20 - mmengine - INFO - Iter(train) [105200/120000] base_lr: 9.3398e-06 lr: 2.6673e-06 eta: 1:54:08 time: 0.4676 data_time: 0.0227 memory: 4388 grad_norm: 3.9483 loss: 1.6474 caption_loss_cls: 1.6474 2024/07/14 16:29:43 - mmengine - INFO - Iter(train) [105250/120000] base_lr: 9.2909e-06 lr: 2.6628e-06 eta: 1:53:45 time: 0.4676 data_time: 0.0227 memory: 4388 grad_norm: 3.9485 loss: 1.6474 caption_loss_cls: 1.6474 2024/07/14 16:30:06 - 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mmengine - INFO - Saving checkpoint at 106000 iterations 2024/07/14 16:35:49 - mmengine - INFO - Iter(train) [106050/120000] base_lr: 8.5301e-06 lr: 2.5936e-06 eta: 1:47:34 time: 0.4669 data_time: 0.0227 memory: 4388 grad_norm: 3.9535 loss: 1.6484 caption_loss_cls: 1.6484 2024/07/14 16:36:12 - mmengine - INFO - Iter(train) [106100/120000] base_lr: 8.4839e-06 lr: 2.5894e-06 eta: 1:47:11 time: 0.4668 data_time: 0.0227 memory: 4388 grad_norm: 3.9537 loss: 1.6481 caption_loss_cls: 1.6481 2024/07/14 16:36:35 - mmengine - INFO - Iter(train) [106150/120000] base_lr: 8.4378e-06 lr: 2.5853e-06 eta: 1:46:48 time: 0.4669 data_time: 0.0227 memory: 4388 grad_norm: 3.9528 loss: 1.6480 caption_loss_cls: 1.6480 2024/07/14 16:36:57 - mmengine - INFO - Iter(train) [106200/120000] base_lr: 8.3920e-06 lr: 2.5811e-06 eta: 1:46:24 time: 0.4667 data_time: 0.0227 memory: 4388 grad_norm: 3.9528 loss: 1.6480 caption_loss_cls: 1.6480 2024/07/14 16:37:19 - mmengine - INFO - Iter(train) [106250/120000] base_lr: 8.3462e-06 lr: 2.5769e-06 eta: 1:46:01 time: 0.4665 data_time: 0.0226 memory: 4388 grad_norm: 3.9525 loss: 1.6475 caption_loss_cls: 1.6475 2024/07/14 16:37:42 - 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mmengine - INFO - Saving checkpoint at 108000 iterations 2024/07/14 16:51:02 - mmengine - INFO - Iter(train) [108050/120000] base_lr: 6.8062e-06 lr: 2.4369e-06 eta: 1:32:07 time: 0.4646 data_time: 0.0224 memory: 4388 grad_norm: 3.9588 loss: 1.6457 caption_loss_cls: 1.6457 2024/07/14 16:51:25 - mmengine - INFO - Iter(train) [108100/120000] base_lr: 6.7664e-06 lr: 2.4333e-06 eta: 1:31:44 time: 0.4646 data_time: 0.0224 memory: 4388 grad_norm: 3.9586 loss: 1.6452 caption_loss_cls: 1.6452 2024/07/14 16:51:48 - mmengine - INFO - Iter(train) [108150/120000] base_lr: 6.7268e-06 lr: 2.4297e-06 eta: 1:31:21 time: 0.4646 data_time: 0.0224 memory: 4388 grad_norm: 3.9589 loss: 1.6454 caption_loss_cls: 1.6454 2024/07/14 16:52:11 - mmengine - INFO - Iter(train) [108200/120000] base_lr: 6.6873e-06 lr: 2.4261e-06 eta: 1:30:58 time: 0.4646 data_time: 0.0224 memory: 4388 grad_norm: 3.9593 loss: 1.6455 caption_loss_cls: 1.6455 2024/07/14 16:52:33 - mmengine - INFO - Iter(train) [108250/120000] base_lr: 6.6480e-06 lr: 2.4225e-06 eta: 1:30:35 time: 0.4646 data_time: 0.0224 memory: 4388 grad_norm: 3.9595 loss: 1.6453 caption_loss_cls: 1.6453 2024/07/14 16:52:56 - 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mmengine - INFO - Iter(train) [108550/120000] base_lr: 6.4154e-06 lr: 2.4014e-06 eta: 1:28:15 time: 0.4642 data_time: 0.0224 memory: 4388 grad_norm: 3.9623 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 16:55:12 - mmengine - INFO - Iter(train) [108600/120000] base_lr: 6.3773e-06 lr: 2.3979e-06 eta: 1:27:52 time: 0.4640 data_time: 0.0223 memory: 4388 grad_norm: 3.9628 loss: 1.6464 caption_loss_cls: 1.6464 2024/07/14 16:55:35 - mmengine - INFO - Iter(train) [108650/120000] base_lr: 6.3392e-06 lr: 2.3945e-06 eta: 1:27:29 time: 0.4640 data_time: 0.0223 memory: 4388 grad_norm: 3.9635 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 16:55:57 - mmengine - INFO - Iter(train) [108700/120000] base_lr: 6.3014e-06 lr: 2.3910e-06 eta: 1:27:06 time: 0.4639 data_time: 0.0223 memory: 4388 grad_norm: 3.9644 loss: 1.6469 caption_loss_cls: 1.6469 2024/07/14 16:56:19 - mmengine - INFO - Iter(train) [108750/120000] base_lr: 6.2637e-06 lr: 2.3876e-06 eta: 1:26:43 time: 0.4638 data_time: 0.0223 memory: 4388 grad_norm: 3.9641 loss: 1.6469 caption_loss_cls: 1.6469 2024/07/14 16:56:42 - 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mmengine - INFO - Saving checkpoint at 109000 iterations 2024/07/14 16:58:39 - mmengine - INFO - Iter(train) [109050/120000] base_lr: 6.0409e-06 lr: 2.3674e-06 eta: 1:24:24 time: 0.4569 data_time: 0.0157 memory: 4388 grad_norm: 3.9681 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 16:59:02 - mmengine - INFO - Iter(train) [109100/120000] base_lr: 6.0043e-06 lr: 2.3640e-06 eta: 1:24:01 time: 0.4567 data_time: 0.0158 memory: 4388 grad_norm: 3.9696 loss: 1.6473 caption_loss_cls: 1.6473 2024/07/14 16:59:25 - mmengine - INFO - Iter(train) [109150/120000] base_lr: 5.9679e-06 lr: 2.3607e-06 eta: 1:23:38 time: 0.4567 data_time: 0.0157 memory: 4388 grad_norm: 3.9710 loss: 1.6478 caption_loss_cls: 1.6478 2024/07/14 16:59:48 - mmengine - INFO - Iter(train) [109200/120000] base_lr: 5.9316e-06 lr: 2.3574e-06 eta: 1:23:15 time: 0.4566 data_time: 0.0157 memory: 4388 grad_norm: 3.9700 loss: 1.6474 caption_loss_cls: 1.6474 2024/07/14 17:00:10 - mmengine - INFO - Iter(train) [109250/120000] base_lr: 5.8956e-06 lr: 2.3541e-06 eta: 1:22:51 time: 0.4566 data_time: 0.0157 memory: 4388 grad_norm: 3.9711 loss: 1.6479 caption_loss_cls: 1.6479 2024/07/14 17:00:33 - mmengine - INFO - Iter(train) [109300/120000] base_lr: 5.8597e-06 lr: 2.3509e-06 eta: 1:22:28 time: 0.4566 data_time: 0.0157 memory: 4388 grad_norm: 3.9712 loss: 1.6477 caption_loss_cls: 1.6477 2024/07/14 17:00:56 - mmengine - INFO - Iter(train) [109350/120000] base_lr: 5.8239e-06 lr: 2.3476e-06 eta: 1:22:05 time: 0.4567 data_time: 0.0158 memory: 4388 grad_norm: 3.9712 loss: 1.6473 caption_loss_cls: 1.6473 2024/07/14 17:01:19 - mmengine - INFO - Iter(train) [109400/120000] base_lr: 5.7883e-06 lr: 2.3444e-06 eta: 1:21:42 time: 0.4568 data_time: 0.0158 memory: 4388 grad_norm: 3.9705 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 17:01:41 - mmengine - INFO - Iter(train) [109450/120000] base_lr: 5.7529e-06 lr: 2.3412e-06 eta: 1:21:19 time: 0.4568 data_time: 0.0157 memory: 4388 grad_norm: 3.9716 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 17:02:04 - mmengine - INFO - Iter(train) [109500/120000] base_lr: 5.7176e-06 lr: 2.3380e-06 eta: 1:20:56 time: 0.4567 data_time: 0.0157 memory: 4388 grad_norm: 3.9722 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 17:02:26 - mmengine - INFO - Iter(train) [109550/120000] base_lr: 5.6825e-06 lr: 2.3348e-06 eta: 1:20:32 time: 0.4567 data_time: 0.0157 memory: 4388 grad_norm: 3.9725 loss: 1.6468 caption_loss_cls: 1.6468 2024/07/14 17:02:49 - mmengine - INFO - Iter(train) [109600/120000] base_lr: 5.6476e-06 lr: 2.3316e-06 eta: 1:20:09 time: 0.4565 data_time: 0.0157 memory: 4388 grad_norm: 3.9724 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 17:03:12 - mmengine - INFO - Iter(train) [109650/120000] base_lr: 5.6128e-06 lr: 2.3284e-06 eta: 1:19:46 time: 0.4566 data_time: 0.0157 memory: 4388 grad_norm: 3.9729 loss: 1.6467 caption_loss_cls: 1.6467 2024/07/14 17:03:34 - mmengine - INFO - Iter(train) [109700/120000] base_lr: 5.5782e-06 lr: 2.3253e-06 eta: 1:19:23 time: 0.4566 data_time: 0.0157 memory: 4388 grad_norm: 3.9727 loss: 1.6463 caption_loss_cls: 1.6463 2024/07/14 17:03:57 - mmengine - INFO - Iter(train) [109750/120000] base_lr: 5.5438e-06 lr: 2.3222e-06 eta: 1:19:00 time: 0.4567 data_time: 0.0157 memory: 4388 grad_norm: 3.9729 loss: 1.6464 caption_loss_cls: 1.6464 2024/07/14 17:04:20 - mmengine - INFO - Iter(train) [109800/120000] base_lr: 5.5095e-06 lr: 2.3190e-06 eta: 1:18:37 time: 0.4567 data_time: 0.0157 memory: 4388 grad_norm: 3.9734 loss: 1.6463 caption_loss_cls: 1.6463 2024/07/14 17:04:43 - mmengine - INFO - Iter(train) [109850/120000] base_lr: 5.4754e-06 lr: 2.3159e-06 eta: 1:18:13 time: 0.4568 data_time: 0.0157 memory: 4388 grad_norm: 3.9731 loss: 1.6466 caption_loss_cls: 1.6466 2024/07/14 17:05:06 - mmengine - INFO - Iter(train) [109900/120000] base_lr: 5.4414e-06 lr: 2.3129e-06 eta: 1:17:50 time: 0.4568 data_time: 0.0157 memory: 4388 grad_norm: 3.9730 loss: 1.6469 caption_loss_cls: 1.6469 2024/07/14 17:05:28 - mmengine - INFO - Iter(train) [109950/120000] base_lr: 5.4076e-06 lr: 2.3098e-06 eta: 1:17:27 time: 0.4569 data_time: 0.0157 memory: 4388 grad_norm: 3.9729 loss: 1.6470 caption_loss_cls: 1.6470 2024/07/14 17:05:52 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240714_022410 2024/07/14 17:05:52 - mmengine - INFO - Iter(train) [110000/120000] base_lr: 5.3740e-06 lr: 2.3067e-06 eta: 1:17:04 time: 0.4570 data_time: 0.0157 memory: 4388 grad_norm: 3.9728 loss: 1.6465 caption_loss_cls: 1.6465 2024/07/14 17:05:52 - mmengine - INFO - Saving checkpoint at 110000 iterations 2024/07/14 17:06:11 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:15 time: 0.2831 data_time: 0.0054 memory: 3762 2024/07/14 17:06:25 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:00 time: 0.2831 data_time: 0.0054 memory: 3767 2024/07/14 17:06:39 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2832 data_time: 0.0054 memory: 3766 2024/07/14 17:06:53 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2832 data_time: 0.0054 memory: 3762 2024/07/14 17:07:07 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2832 data_time: 0.0054 memory: 3762 2024/07/14 17:07:21 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2832 data_time: 0.0054 memory: 3762 2024/07/14 17:07:53 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7433 Bleu_2: 0.5827 Bleu_3: 0.4491 Bleu_4: 0.3451 METEOR: 0.2781 ROUGE_L: 0.5614 CIDEr: 1.1218 SPICE: 0.2064 data_time: 0.0055 time: 0.2835 024/07/15 03:35:25 - mmengine - INFO - Iter(train) [110050/120000] base_lr: 5.3406e-06 lr: 2.3037e-06 eta: 1:16:18 time: 0.4561 data_time: 0.0146 memory: 4383 grad_norm: 3.9730 loss: 1.6459 caption_loss_cls: 1.6459 2024/07/15 03:35:48 - mmengine - INFO - Iter(train) [110100/120000] base_lr: 5.3073e-06 lr: 2.3007e-06 eta: 1:15:13 time: 0.4561 data_time: 0.0146 memory: 4379 grad_norm: 3.9729 loss: 1.6454 caption_loss_cls: 1.6454 2024/07/15 03:36:11 - mmengine - INFO - Iter(train) [110150/120000] base_lr: 5.2741e-06 lr: 2.2976e-06 eta: 1:15:10 time: 0.4562 data_time: 0.0146 memory: 4379 grad_norm: 3.9724 loss: 1.6447 caption_loss_cls: 1.6447 2024/07/15 03:36:33 - mmengine - INFO - Iter(train) [110200/120000] base_lr: 5.2412e-06 lr: 2.2947e-06 eta: 1:14:26 time: 0.4562 data_time: 0.0146 memory: 4379 grad_norm: 3.9732 loss: 1.6446 caption_loss_cls: 1.6446 2024/07/15 03:36:56 - mmengine - INFO - Iter(train) [110250/120000] base_lr: 5.2083e-06 lr: 2.2917e-06 eta: 1:14:20 time: 0.4564 data_time: 0.0146 memory: 4379 grad_norm: 3.9726 loss: 1.6444 caption_loss_cls: 1.6444 2024/07/15 03:37:19 - 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mmengine - INFO - Saving checkpoint at 111000 iterations 2024/07/15 03:43:08 - mmengine - INFO - Iter(train) [111050/120000] base_lr: 4.7058e-06 lr: 2.2460e-06 eta: 1:08:57 time: 0.4581 data_time: 0.0145 memory: 4379 grad_norm: 3.9737 loss: 1.6384 caption_loss_cls: 1.6384 2024/07/15 03:43:31 - mmengine - INFO - Iter(train) [111100/120000] base_lr: 4.6758e-06 lr: 2.2433e-06 eta: 1:08:32 time: 0.4583 data_time: 0.0145 memory: 4379 grad_norm: 3.9732 loss: 1.6375 caption_loss_cls: 1.6375 2024/07/15 03:43:54 - mmengine - INFO - Iter(train) [111150/120000] base_lr: 4.6460e-06 lr: 2.2405e-06 eta: 1:08:08 time: 0.4584 data_time: 0.0145 memory: 4379 grad_norm: 3.9728 loss: 1.6371 caption_loss_cls: 1.6371 2024/07/15 03:44:17 - mmengine - INFO - Iter(train) [111200/120000] base_lr: 4.6163e-06 lr: 2.2378e-06 eta: 1:07:44 time: 0.4585 data_time: 0.0145 memory: 4379 grad_norm: 3.9733 loss: 1.6370 caption_loss_cls: 1.6370 2024/07/15 03:44:40 - mmengine - INFO - Iter(train) [111250/120000] base_lr: 4.5868e-06 lr: 2.2352e-06 eta: 1:07:23 time: 0.4586 data_time: 0.0145 memory: 4379 grad_norm: 3.9721 loss: 1.6356 caption_loss_cls: 1.6356 2024/07/15 03:45:03 - 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mmengine - INFO - Iter(train) [111550/120000] base_lr: 4.4132e-06 lr: 2.2194e-06 eta: 1:04:58 time: 0.4588 data_time: 0.0145 memory: 4379 grad_norm: 3.9730 loss: 1.6314 caption_loss_cls: 1.6314 2024/07/15 03:47:20 - mmengine - INFO - Iter(train) [111600/120000] base_lr: 4.3848e-06 lr: 2.2168e-06 eta: 1:04:34 time: 0.4589 data_time: 0.0144 memory: 4379 grad_norm: 3.9733 loss: 1.6309 caption_loss_cls: 1.6309 2024/07/15 03:47:43 - mmengine - INFO - Iter(train) [111650/120000] base_lr: 4.3566e-06 lr: 2.2142e-06 eta: 1:04:10 time: 0.4589 data_time: 0.0144 memory: 4379 grad_norm: 3.9732 loss: 1.6297 caption_loss_cls: 1.6297 2024/07/15 03:48:06 - mmengine - INFO - Iter(train) [111700/120000] base_lr: 4.3286e-06 lr: 2.2117e-06 eta: 1:03:47 time: 0.4590 data_time: 0.0144 memory: 4379 grad_norm: 3.9736 loss: 1.6293 caption_loss_cls: 1.6293 2024/07/15 03:48:30 - mmengine - INFO - Iter(train) [111750/120000] base_lr: 4.3007e-06 lr: 2.2092e-06 eta: 1:03:25 time: 0.4592 data_time: 0.0144 memory: 4379 grad_norm: 3.9732 loss: 1.6286 caption_loss_cls: 1.6286 2024/07/15 03:48:53 - 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mmengine - INFO - Saving checkpoint at 112000 iterations 2024/07/15 03:50:52 - mmengine - INFO - Iter(train) [112050/120000] base_lr: 4.1371e-06 lr: 2.1943e-06 eta: 1:01:21 time: 0.4595 data_time: 0.0145 memory: 4379 grad_norm: 3.9747 loss: 1.6255 caption_loss_cls: 1.6255 2024/07/15 03:51:15 - mmengine - INFO - Iter(train) [112100/120000] base_lr: 4.1104e-06 lr: 2.1919e-06 eta: 1:00:57 time: 0.4596 data_time: 0.0145 memory: 4379 grad_norm: 3.9743 loss: 1.6251 caption_loss_cls: 1.6251 2024/07/15 03:51:38 - mmengine - INFO - Iter(train) [112150/120000] base_lr: 4.0838e-06 lr: 2.1894e-06 eta: 1:00:32 time: 0.4595 data_time: 0.0145 memory: 4379 grad_norm: 3.9748 loss: 1.6245 caption_loss_cls: 1.6245 2024/07/15 03:52:00 - mmengine - INFO - Iter(train) [112200/120000] base_lr: 4.0575e-06 lr: 2.1870e-06 eta: 1:00:07 time: 0.4595 data_time: 0.0144 memory: 4379 grad_norm: 3.9745 loss: 1.6237 caption_loss_cls: 1.6237 2024/07/15 03:52:23 - mmengine - INFO - Iter(train) [112250/120000] base_lr: 4.0313e-06 lr: 2.1847e-06 eta: 0:59:42 time: 0.4594 data_time: 0.0144 memory: 4379 grad_norm: 3.9735 loss: 1.6229 caption_loss_cls: 1.6229 2024/07/15 03:52:45 - 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mmengine - INFO - Iter(train) [112800/120000] base_lr: 3.7540e-06 lr: 2.1595e-06 eta: 0:55:18 time: 0.4601 data_time: 0.0143 memory: 4379 grad_norm: 3.9669 loss: 1.6148 caption_loss_cls: 1.6148 2024/07/15 03:56:56 - mmengine - INFO - Iter(train) [112850/120000] base_lr: 3.7298e-06 lr: 2.1573e-06 eta: 0:54:55 time: 0.4603 data_time: 0.0143 memory: 4379 grad_norm: 3.9673 loss: 1.6144 caption_loss_cls: 1.6144 2024/07/15 03:57:19 - mmengine - INFO - Iter(train) [112900/120000] base_lr: 3.7058e-06 lr: 2.1551e-06 eta: 0:54:31 time: 0.4602 data_time: 0.0143 memory: 4379 grad_norm: 3.9668 loss: 1.6132 caption_loss_cls: 1.6132 2024/07/15 03:57:42 - mmengine - INFO - Iter(train) [112950/120000] base_lr: 3.6819e-06 lr: 2.1529e-06 eta: 0:54:08 time: 0.4603 data_time: 0.0143 memory: 4379 grad_norm: 3.9677 loss: 1.6134 caption_loss_cls: 1.6134 2024/07/15 03:58:05 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240715_033349 2024/07/15 03:58:05 - mmengine - INFO - Iter(train) [113000/120000] base_lr: 3.6582e-06 lr: 2.1507e-06 eta: 0:53:44 time: 0.4602 data_time: 0.0142 memory: 4379 grad_norm: 3.9679 loss: 1.6131 caption_loss_cls: 1.6131 2024/07/15 03:58:05 - mmengine - INFO - Saving checkpoint at 113000 iterations 2024/07/15 03:58:32 - mmengine - INFO - Iter(train) [113050/120000] base_lr: 3.6347e-06 lr: 2.1486e-06 eta: 0:53:30 time: 0.4602 data_time: 0.0143 memory: 4379 grad_norm: 3.9669 loss: 1.6125 caption_loss_cls: 1.6125 2024/07/15 03:58:55 - mmengine - INFO - Iter(train) [113100/120000] base_lr: 3.6113e-06 lr: 2.1465e-06 eta: 0:53:06 time: 0.4603 data_time: 0.0142 memory: 4379 grad_norm: 3.9655 loss: 1.6113 caption_loss_cls: 1.6113 2024/07/15 03:59:17 - mmengine - INFO - Iter(train) [113150/120000] base_lr: 3.5881e-06 lr: 2.1444e-06 eta: 0:52:42 time: 0.4601 data_time: 0.0142 memory: 4379 grad_norm: 3.9647 loss: 1.6105 caption_loss_cls: 1.6105 2024/07/15 03:59:40 - mmengine - INFO - Iter(train) [113200/120000] base_lr: 3.5651e-06 lr: 2.1423e-06 eta: 0:52:19 time: 0.4603 data_time: 0.0142 memory: 4379 grad_norm: 3.9653 loss: 1.6101 caption_loss_cls: 1.6101 2024/07/15 04:00:03 - mmengine - INFO - Iter(train) [113250/120000] base_lr: 3.5422e-06 lr: 2.1402e-06 eta: 0:51:55 time: 0.4604 data_time: 0.0142 memory: 4379 grad_norm: 3.9649 loss: 1.6090 caption_loss_cls: 1.6090 2024/07/15 04:00:26 - 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mmengine - INFO - Iter(train) [114550/120000] base_lr: 3.0064e-06 lr: 2.0915e-06 eta: 0:41:52 time: 0.4613 data_time: 0.0150 memory: 4379 grad_norm: 3.9959 loss: 1.6010 caption_loss_cls: 1.6010 2024/07/15 04:10:24 - mmengine - INFO - Iter(train) [114600/120000] base_lr: 2.9880e-06 lr: 2.0898e-06 eta: 0:41:29 time: 0.4614 data_time: 0.0151 memory: 4379 grad_norm: 3.9968 loss: 1.6009 caption_loss_cls: 1.6009 2024/07/15 04:10:46 - mmengine - INFO - Iter(train) [114650/120000] base_lr: 2.9698e-06 lr: 2.0882e-06 eta: 0:41:05 time: 0.4613 data_time: 0.0151 memory: 4379 grad_norm: 3.9971 loss: 1.6004 caption_loss_cls: 1.6004 2024/07/15 04:11:09 - mmengine - INFO - Iter(train) [114700/120000] base_lr: 2.9518e-06 lr: 2.0865e-06 eta: 0:40:42 time: 0.4613 data_time: 0.0150 memory: 4379 grad_norm: 3.9986 loss: 1.6006 caption_loss_cls: 1.6006 2024/07/15 04:11:32 - mmengine - INFO - Iter(train) [114750/120000] base_lr: 2.9340e-06 lr: 2.0849e-06 eta: 0:40:19 time: 0.4613 data_time: 0.0151 memory: 4379 grad_norm: 3.9988 loss: 1.6006 caption_loss_cls: 1.6006 2024/07/15 04:11:55 - mmengine - INFO - Iter(train) [114800/120000] base_lr: 2.9163e-06 lr: 2.0833e-06 eta: 0:39:55 time: 0.4612 data_time: 0.0150 memory: 4379 grad_norm: 3.9995 loss: 1.6006 caption_loss_cls: 1.6006 2024/07/15 04:12:17 - mmengine - INFO - Iter(train) [114850/120000] base_lr: 2.8988e-06 lr: 2.0817e-06 eta: 0:39:32 time: 0.4612 data_time: 0.0151 memory: 4379 grad_norm: 4.0000 loss: 1.6006 caption_loss_cls: 1.6006 2024/07/15 04:12:40 - mmengine - INFO - Iter(train) [114900/120000] base_lr: 2.8815e-06 lr: 2.0801e-06 eta: 0:39:09 time: 0.4613 data_time: 0.0151 memory: 4379 grad_norm: 4.0006 loss: 1.6004 caption_loss_cls: 1.6004 2024/07/15 04:13:04 - mmengine - INFO - Iter(train) [114950/120000] base_lr: 2.8643e-06 lr: 2.0786e-06 eta: 0:38:46 time: 0.4614 data_time: 0.0151 memory: 4379 grad_norm: 4.0005 loss: 1.6005 caption_loss_cls: 1.6005 2024/07/15 04:13:27 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240715_033349 2024/07/15 04:13:27 - mmengine - INFO - Iter(train) [115000/120000] base_lr: 2.8473e-06 lr: 2.0770e-06 eta: 0:38:23 time: 0.4615 data_time: 0.0151 memory: 4379 grad_norm: 4.0008 loss: 1.6004 caption_loss_cls: 1.6004 2024/07/15 04:13:27 - mmengine - INFO - Saving checkpoint at 115000 iterations 2024/07/15 04:13:46 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:17 time: 0.2832 data_time: 0.0054 memory: 3760 2024/07/15 04:14:00 - mmengine - INFO - Iter(val) [100/313] eta: 0:01:01 time: 0.2832 data_time: 0.0054 memory: 3769 2024/07/15 04:14:15 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:46 time: 0.2832 data_time: 0.0054 memory: 3766 2024/07/15 04:14:29 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:32 time: 0.2832 data_time: 0.0054 memory: 3764 2024/07/15 04:14:43 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2832 data_time: 0.0054 memory: 3763 2024/07/15 04:14:57 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2832 data_time: 0.0054 memory: 3764 2024/07/15 04:15:29 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7420 Bleu_2: 0.5799 Bleu_3: 0.4453 Bleu_4: 0.3409 METEOR: 0.2762 ROUGE_L: 0.5582 CIDEr: 1.1113 SPICE: 0.2057 data_time: 0.0055 time: 0.2831 2024/07/15 04:15:53 - mmengine - INFO - Iter(train) [115050/120000] base_lr: 2.8305e-06 lr: 2.0755e-06 eta: 0:38:29 time: 0.4677 data_time: 0.0212 memory: 4388 grad_norm: 4.0004 loss: 1.6003 caption_loss_cls: 1.6003 2024/07/15 04:16:16 - mmengine - INFO - Iter(train) [115100/120000] base_lr: 2.8138e-06 lr: 2.0740e-06 eta: 0:38:05 time: 0.4677 data_time: 0.0212 memory: 4383 grad_norm: 4.0003 loss: 1.6004 caption_loss_cls: 1.6004 2024/07/15 04:16:39 - mmengine - INFO - Iter(train) [115150/120000] base_lr: 2.7973e-06 lr: 2.0725e-06 eta: 0:37:42 time: 0.4678 data_time: 0.0212 memory: 4383 grad_norm: 4.0005 loss: 1.5999 caption_loss_cls: 1.5999 2024/07/15 04:17:02 - mmengine - INFO - Iter(train) [115200/120000] base_lr: 2.7810e-06 lr: 2.0710e-06 eta: 0:37:19 time: 0.4678 data_time: 0.0212 memory: 4383 grad_norm: 4.0004 loss: 1.5995 caption_loss_cls: 1.5995 2024/07/15 04:17:26 - mmengine - INFO - Iter(train) [115250/120000] base_lr: 2.7648e-06 lr: 2.0695e-06 eta: 0:36:55 time: 0.4679 data_time: 0.0212 memory: 4383 grad_norm: 4.0011 loss: 1.6000 caption_loss_cls: 1.6000 2024/07/15 04:17:49 - mmengine - INFO - Iter(train) [115300/120000] base_lr: 2.7488e-06 lr: 2.0681e-06 eta: 0:36:32 time: 0.4680 data_time: 0.0212 memory: 4383 grad_norm: 4.0019 loss: 1.6005 caption_loss_cls: 1.6005 2024/07/15 04:18:12 - mmengine - INFO - Iter(train) [115350/120000] base_lr: 2.7330e-06 lr: 2.0666e-06 eta: 0:36:09 time: 0.4681 data_time: 0.0213 memory: 4383 grad_norm: 4.0027 loss: 1.6005 caption_loss_cls: 1.6005 2024/07/15 04:18:36 - mmengine - INFO - Iter(train) [115400/120000] base_lr: 2.7173e-06 lr: 2.0652e-06 eta: 0:35:45 time: 0.4682 data_time: 0.0213 memory: 4383 grad_norm: 4.0040 loss: 1.6011 caption_loss_cls: 1.6011 2024/07/15 04:18:59 - mmengine - INFO - Iter(train) [115450/120000] base_lr: 2.7018e-06 lr: 2.0638e-06 eta: 0:35:22 time: 0.4682 data_time: 0.0213 memory: 4383 grad_norm: 4.0038 loss: 1.6009 caption_loss_cls: 1.6009 2024/07/15 04:19:22 - mmengine - INFO - Iter(train) [115500/120000] base_lr: 2.6865e-06 lr: 2.0624e-06 eta: 0:34:58 time: 0.4683 data_time: 0.0213 memory: 4383 grad_norm: 4.0036 loss: 1.6014 caption_loss_cls: 1.6014 2024/07/15 04:19:45 - mmengine - INFO - Iter(train) [115550/120000] base_lr: 2.6714e-06 lr: 2.0610e-06 eta: 0:34:35 time: 0.4683 data_time: 0.0213 memory: 4383 grad_norm: 4.0036 loss: 1.6020 caption_loss_cls: 1.6020 2024/07/15 04:20:08 - mmengine - INFO - Iter(train) [115600/120000] base_lr: 2.6564e-06 lr: 2.0597e-06 eta: 0:34:11 time: 0.4683 data_time: 0.0213 memory: 4383 grad_norm: 4.0043 loss: 1.6021 caption_loss_cls: 1.6021 2024/07/15 04:20:31 - mmengine - INFO - Iter(train) [115650/120000] base_lr: 2.6416e-06 lr: 2.0583e-06 eta: 0:33:48 time: 0.4683 data_time: 0.0213 memory: 4383 grad_norm: 4.0053 loss: 1.6028 caption_loss_cls: 1.6028 2024/07/15 04:20:54 - mmengine - INFO - Iter(train) [115700/120000] base_lr: 2.6269e-06 lr: 2.0570e-06 eta: 0:33:24 time: 0.4683 data_time: 0.0214 memory: 4383 grad_norm: 4.0052 loss: 1.6027 caption_loss_cls: 1.6027 2024/07/15 04:21:17 - mmengine - INFO - Iter(train) [115750/120000] base_lr: 2.6125e-06 lr: 2.0557e-06 eta: 0:33:01 time: 0.4683 data_time: 0.0214 memory: 4383 grad_norm: 4.0064 loss: 1.6032 caption_loss_cls: 1.6032 2024/07/15 04:21:40 - mmengine - INFO - Iter(train) [115800/120000] base_lr: 2.5981e-06 lr: 2.0544e-06 eta: 0:32:37 time: 0.4683 data_time: 0.0214 memory: 4383 grad_norm: 4.0075 loss: 1.6035 caption_loss_cls: 1.6035 2024/07/15 04:22:04 - mmengine - INFO - Iter(train) [115850/120000] base_lr: 2.5840e-06 lr: 2.0531e-06 eta: 0:32:14 time: 0.4683 data_time: 0.0214 memory: 4383 grad_norm: 4.0069 loss: 1.6037 caption_loss_cls: 1.6037 2024/07/15 04:22:27 - mmengine - INFO - Iter(train) [115900/120000] base_lr: 2.5700e-06 lr: 2.0518e-06 eta: 0:31:51 time: 0.4684 data_time: 0.0214 memory: 4383 grad_norm: 4.0070 loss: 1.6037 caption_loss_cls: 1.6037 2024/07/15 04:22:50 - mmengine - INFO - Iter(train) [115950/120000] base_lr: 2.5562e-06 lr: 2.0506e-06 eta: 0:31:27 time: 0.4685 data_time: 0.0214 memory: 4383 grad_norm: 4.0081 loss: 1.6039 caption_loss_cls: 1.6039 2024/07/15 04:23:13 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240715_033349 2024/07/15 04:23:13 - mmengine - INFO - Iter(train) [116000/120000] base_lr: 2.5426e-06 lr: 2.0493e-06 eta: 0:31:04 time: 0.4687 data_time: 0.0214 memory: 4383 grad_norm: 4.0086 loss: 1.6040 caption_loss_cls: 1.6040 2024/07/15 04:23:13 - mmengine - INFO - Saving checkpoint at 116000 iterations 2024/07/15 04:23:41 - mmengine - INFO - Iter(train) [116050/120000] base_lr: 2.5291e-06 lr: 2.0481e-06 eta: 0:30:43 time: 0.4687 data_time: 0.0214 memory: 4383 grad_norm: 4.0085 loss: 1.6038 caption_loss_cls: 1.6038 2024/07/15 04:24:04 - mmengine - INFO - Iter(train) [116100/120000] base_lr: 2.5158e-06 lr: 2.0469e-06 eta: 0:30:20 time: 0.4686 data_time: 0.0214 memory: 4383 grad_norm: 4.0086 loss: 1.6037 caption_loss_cls: 1.6037 2024/07/15 04:24:27 - mmengine - INFO - Iter(train) [116150/120000] base_lr: 2.5027e-06 lr: 2.0457e-06 eta: 0:29:56 time: 0.4687 data_time: 0.0214 memory: 4383 grad_norm: 4.0088 loss: 1.6041 caption_loss_cls: 1.6041 2024/07/15 04:24:50 - mmengine - INFO - Iter(train) [116200/120000] base_lr: 2.4898e-06 lr: 2.0445e-06 eta: 0:29:33 time: 0.4689 data_time: 0.0214 memory: 4383 grad_norm: 4.0104 loss: 1.6044 caption_loss_cls: 1.6044 2024/07/15 04:25:13 - mmengine - INFO - Iter(train) [116250/120000] base_lr: 2.4770e-06 lr: 2.0434e-06 eta: 0:29:09 time: 0.4690 data_time: 0.0214 memory: 4383 grad_norm: 4.0114 loss: 1.6046 caption_loss_cls: 1.6046 2024/07/15 04:25:36 - 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mmengine - INFO - Saving checkpoint at 117000 iterations 2024/07/15 04:31:26 - mmengine - INFO - Iter(train) [117050/120000] base_lr: 2.2953e-06 lr: 2.0268e-06 eta: 0:22:56 time: 0.4700 data_time: 0.0216 memory: 4383 grad_norm: 4.0159 loss: 1.6056 caption_loss_cls: 1.6056 2024/07/15 04:31:49 - mmengine - INFO - Iter(train) [117100/120000] base_lr: 2.2854e-06 lr: 2.0259e-06 eta: 0:22:32 time: 0.4701 data_time: 0.0216 memory: 4383 grad_norm: 4.0166 loss: 1.6061 caption_loss_cls: 1.6061 2024/07/15 04:32:12 - mmengine - INFO - Iter(train) [117150/120000] base_lr: 2.2756e-06 lr: 2.0251e-06 eta: 0:22:09 time: 0.4702 data_time: 0.0216 memory: 4383 grad_norm: 4.0174 loss: 1.6057 caption_loss_cls: 1.6057 2024/07/15 04:32:35 - mmengine - INFO - Iter(train) [117200/120000] base_lr: 2.2661e-06 lr: 2.0242e-06 eta: 0:21:45 time: 0.4702 data_time: 0.0216 memory: 4383 grad_norm: 4.0179 loss: 1.6058 caption_loss_cls: 1.6058 2024/07/15 04:32:59 - mmengine - INFO - Iter(train) [117250/120000] base_lr: 2.2566e-06 lr: 2.0233e-06 eta: 0:21:22 time: 0.4703 data_time: 0.0216 memory: 4383 grad_norm: 4.0185 loss: 1.6060 caption_loss_cls: 1.6060 2024/07/15 04:33:22 - 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mmengine - INFO - Saving checkpoint at 118000 iterations 2024/07/15 04:39:11 - mmengine - INFO - Iter(train) [118050/120000] base_lr: 2.1291e-06 lr: 2.0117e-06 eta: 0:15:09 time: 0.4707 data_time: 0.0217 memory: 4383 grad_norm: 4.0254 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:39:34 - mmengine - INFO - Iter(train) [118100/120000] base_lr: 2.1226e-06 lr: 2.0111e-06 eta: 0:14:45 time: 0.4708 data_time: 0.0218 memory: 4383 grad_norm: 4.0251 loss: 1.6073 caption_loss_cls: 1.6073 2024/07/15 04:39:57 - mmengine - INFO - Iter(train) [118150/120000] base_lr: 2.1162e-06 lr: 2.0106e-06 eta: 0:14:22 time: 0.4710 data_time: 0.0218 memory: 4383 grad_norm: 4.0237 loss: 1.6065 caption_loss_cls: 1.6065 2024/07/15 04:40:20 - mmengine - INFO - Iter(train) [118200/120000] base_lr: 2.1100e-06 lr: 2.0100e-06 eta: 0:13:59 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 3.9967 loss: 1.6062 caption_loss_cls: 1.6062 2024/07/15 04:40:43 - mmengine - INFO - Iter(train) [118250/120000] base_lr: 2.1040e-06 lr: 2.0095e-06 eta: 0:13:35 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 3.9980 loss: 1.6069 caption_loss_cls: 1.6069 2024/07/15 04:41:06 - mmengine - INFO - Iter(train) [118300/120000] base_lr: 2.0981e-06 lr: 2.0089e-06 eta: 0:13:12 time: 0.4710 data_time: 0.0218 memory: 4383 grad_norm: 3.9973 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:41:29 - mmengine - INFO - Iter(train) [118350/120000] base_lr: 2.0925e-06 lr: 2.0084e-06 eta: 0:12:48 time: 0.4710 data_time: 0.0218 memory: 4383 grad_norm: 3.9981 loss: 1.6074 caption_loss_cls: 1.6074 2024/07/15 04:41:52 - mmengine - INFO - Iter(train) [118400/120000] base_lr: 2.0869e-06 lr: 2.0079e-06 eta: 0:12:25 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 3.9986 loss: 1.6075 caption_loss_cls: 1.6075 2024/07/15 04:42:14 - mmengine - INFO - Iter(train) [118450/120000] base_lr: 2.0816e-06 lr: 2.0074e-06 eta: 0:12:02 time: 0.4712 data_time: 0.0218 memory: 4383 grad_norm: 3.9993 loss: 1.6077 caption_loss_cls: 1.6077 2024/07/15 04:42:37 - mmengine - INFO - Iter(train) [118500/120000] base_lr: 2.0764e-06 lr: 2.0069e-06 eta: 0:11:38 time: 0.4713 data_time: 0.0218 memory: 4383 grad_norm: 3.9992 loss: 1.6075 caption_loss_cls: 1.6075 2024/07/15 04:43:00 - mmengine - INFO - Iter(train) [118550/120000] base_lr: 2.0714e-06 lr: 2.0065e-06 eta: 0:11:15 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 4.0001 loss: 1.6074 caption_loss_cls: 1.6074 2024/07/15 04:43:22 - mmengine - INFO - Iter(train) [118600/120000] base_lr: 2.0666e-06 lr: 2.0061e-06 eta: 0:10:51 time: 0.4710 data_time: 0.0218 memory: 4383 grad_norm: 3.9991 loss: 1.6070 caption_loss_cls: 1.6070 2024/07/15 04:43:45 - mmengine - INFO - Iter(train) [118650/120000] base_lr: 2.0619e-06 lr: 2.0056e-06 eta: 0:10:28 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 3.9993 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:44:08 - mmengine - INFO - Iter(train) [118700/120000] base_lr: 2.0574e-06 lr: 2.0052e-06 eta: 0:10:05 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 3.9989 loss: 1.6070 caption_loss_cls: 1.6070 2024/07/15 04:44:31 - mmengine - INFO - Iter(train) [118750/120000] base_lr: 2.0531e-06 lr: 2.0048e-06 eta: 0:09:41 time: 0.4711 data_time: 0.0218 memory: 4383 grad_norm: 4.0000 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:44:54 - mmengine - INFO - Iter(train) [118800/120000] base_lr: 2.0489e-06 lr: 2.0044e-06 eta: 0:09:18 time: 0.4712 data_time: 0.0218 memory: 4383 grad_norm: 3.9994 loss: 1.6067 caption_loss_cls: 1.6067 2024/07/15 04:45:17 - mmengine - INFO - Iter(train) [118850/120000] base_lr: 2.0449e-06 lr: 2.0041e-06 eta: 0:08:55 time: 0.4713 data_time: 0.0218 memory: 4383 grad_norm: 3.9997 loss: 1.6072 caption_loss_cls: 1.6072 2024/07/15 04:45:39 - mmengine - INFO - Iter(train) [118900/120000] base_lr: 2.0411e-06 lr: 2.0037e-06 eta: 0:08:31 time: 0.4712 data_time: 0.0218 memory: 4383 grad_norm: 4.0005 loss: 1.6074 caption_loss_cls: 1.6074 2024/07/15 04:46:02 - mmengine - INFO - Iter(train) [118950/120000] base_lr: 2.0375e-06 lr: 2.0034e-06 eta: 0:08:08 time: 0.4710 data_time: 0.0218 memory: 4383 grad_norm: 4.0007 loss: 1.6072 caption_loss_cls: 1.6072 2024/07/15 04:46:25 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240715_033349 2024/07/15 04:46:25 - mmengine - INFO - Iter(train) [119000/120000] base_lr: 2.0340e-06 lr: 2.0031e-06 eta: 0:07:45 time: 0.4709 data_time: 0.0218 memory: 4383 grad_norm: 4.0005 loss: 1.6073 caption_loss_cls: 1.6073 2024/07/15 04:46:25 - mmengine - INFO - Saving checkpoint at 119000 iterations 2024/07/15 04:46:53 - mmengine - INFO - Iter(train) [119050/120000] base_lr: 2.0307e-06 lr: 2.0028e-06 eta: 0:07:22 time: 0.4648 data_time: 0.0156 memory: 4383 grad_norm: 4.0006 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:47:16 - mmengine - INFO - Iter(train) [119100/120000] base_lr: 2.0275e-06 lr: 2.0025e-06 eta: 0:06:59 time: 0.4648 data_time: 0.0156 memory: 4383 grad_norm: 4.0013 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:47:39 - mmengine - INFO - Iter(train) [119150/120000] base_lr: 2.0246e-06 lr: 2.0022e-06 eta: 0:06:35 time: 0.4646 data_time: 0.0156 memory: 4383 grad_norm: 4.0021 loss: 1.6080 caption_loss_cls: 1.6080 2024/07/15 04:48:02 - mmengine - INFO - Iter(train) [119200/120000] base_lr: 2.0218e-06 lr: 2.0020e-06 eta: 0:06:12 time: 0.4646 data_time: 0.0156 memory: 4383 grad_norm: 4.0021 loss: 1.6077 caption_loss_cls: 1.6077 2024/07/15 04:48:25 - mmengine - INFO - Iter(train) [119250/120000] base_lr: 2.0191e-06 lr: 2.0017e-06 eta: 0:05:49 time: 0.4646 data_time: 0.0156 memory: 4383 grad_norm: 4.0018 loss: 1.6076 caption_loss_cls: 1.6076 2024/07/15 04:48:49 - mmengine - INFO - Iter(train) [119300/120000] base_lr: 2.0167e-06 lr: 2.0015e-06 eta: 0:05:25 time: 0.4645 data_time: 0.0156 memory: 4383 grad_norm: 4.0014 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:49:11 - mmengine - INFO - Iter(train) [119350/120000] base_lr: 2.0144e-06 lr: 2.0013e-06 eta: 0:05:02 time: 0.4644 data_time: 0.0155 memory: 4383 grad_norm: 4.0016 loss: 1.6073 caption_loss_cls: 1.6073 2024/07/15 04:49:34 - mmengine - INFO - Iter(train) [119400/120000] base_lr: 2.0123e-06 lr: 2.0011e-06 eta: 0:04:39 time: 0.4643 data_time: 0.0155 memory: 4383 grad_norm: 4.0009 loss: 1.6069 caption_loss_cls: 1.6069 2024/07/15 04:49:57 - mmengine - INFO - Iter(train) [119450/120000] base_lr: 2.0103e-06 lr: 2.0009e-06 eta: 0:04:16 time: 0.4643 data_time: 0.0155 memory: 4383 grad_norm: 4.0006 loss: 1.6068 caption_loss_cls: 1.6068 2024/07/15 04:50:20 - mmengine - INFO - Iter(train) [119500/120000] base_lr: 2.0085e-06 lr: 2.0008e-06 eta: 0:03:52 time: 0.4644 data_time: 0.0155 memory: 4383 grad_norm: 4.0021 loss: 1.6067 caption_loss_cls: 1.6067 2024/07/15 04:50:44 - mmengine - INFO - Iter(train) [119550/120000] base_lr: 2.0069e-06 lr: 2.0006e-06 eta: 0:03:29 time: 0.4644 data_time: 0.0155 memory: 4383 grad_norm: 4.0018 loss: 1.6062 caption_loss_cls: 1.6062 2024/07/15 04:51:07 - mmengine - INFO - Iter(train) [119600/120000] base_lr: 2.0055e-06 lr: 2.0005e-06 eta: 0:03:06 time: 0.4645 data_time: 0.0155 memory: 4383 grad_norm: 4.0020 loss: 1.6062 caption_loss_cls: 1.6062 2024/07/15 04:51:30 - mmengine - INFO - Iter(train) [119650/120000] base_lr: 2.0042e-06 lr: 2.0004e-06 eta: 0:02:42 time: 0.4645 data_time: 0.0155 memory: 4383 grad_norm: 4.0021 loss: 1.6065 caption_loss_cls: 1.6065 2024/07/15 04:51:53 - mmengine - INFO - Iter(train) [119700/120000] base_lr: 2.0031e-06 lr: 2.0003e-06 eta: 0:02:19 time: 0.4645 data_time: 0.0155 memory: 4383 grad_norm: 4.0029 loss: 1.6068 caption_loss_cls: 1.6068 2024/07/15 04:52:16 - mmengine - INFO - Iter(train) [119750/120000] base_lr: 2.0021e-06 lr: 2.0002e-06 eta: 0:01:56 time: 0.4645 data_time: 0.0155 memory: 4383 grad_norm: 4.0026 loss: 1.6069 caption_loss_cls: 1.6069 2024/07/15 04:52:39 - mmengine - INFO - Iter(train) [119800/120000] base_lr: 2.0014e-06 lr: 2.0001e-06 eta: 0:01:33 time: 0.4644 data_time: 0.0154 memory: 4383 grad_norm: 4.0020 loss: 1.6071 caption_loss_cls: 1.6071 2024/07/15 04:53:02 - mmengine - INFO - Iter(train) [119850/120000] base_lr: 2.0008e-06 lr: 2.0001e-06 eta: 0:01:09 time: 0.4644 data_time: 0.0154 memory: 4383 grad_norm: 4.0026 loss: 1.6073 caption_loss_cls: 1.6073 2024/07/15 04:53:25 - mmengine - INFO - Iter(train) [119900/120000] base_lr: 2.0003e-06 lr: 2.0000e-06 eta: 0:00:46 time: 0.4644 data_time: 0.0155 memory: 4383 grad_norm: 4.0029 loss: 1.6076 caption_loss_cls: 1.6076 2024/07/15 04:53:49 - mmengine - INFO - Iter(train) [119950/120000] base_lr: 2.0001e-06 lr: 2.0000e-06 eta: 0:00:23 time: 0.4644 data_time: 0.0155 memory: 4383 grad_norm: 4.0026 loss: 1.6075 caption_loss_cls: 1.6075 2024/07/15 04:54:11 - mmengine - INFO - Exp name: single_caption_base_prompt_beta_raw_20240715_033349 2024/07/15 04:54:11 - mmengine - INFO - Iter(train) [120000/120000] base_lr: 2.0000e-06 lr: 2.0000e-06 eta: 0:00:00 time: 0.4643 data_time: 0.0154 memory: 4383 grad_norm: 4.0020 loss: 1.6070 caption_loss_cls: 1.6070 2024/07/15 04:54:11 - mmengine - INFO - Saving checkpoint at 120000 iterations 2024/07/15 04:54:30 - mmengine - INFO - Iter(val) [ 50/313] eta: 0:01:13 time: 0.2831 data_time: 0.0054 memory: 3758 2024/07/15 04:54:44 - mmengine - INFO - Iter(val) [100/313] eta: 0:00:59 time: 0.2830 data_time: 0.0054 memory: 3766 2024/07/15 04:54:58 - mmengine - INFO - Iter(val) [150/313] eta: 0:00:45 time: 0.2830 data_time: 0.0054 memory: 3766 2024/07/15 04:55:12 - mmengine - INFO - Iter(val) [200/313] eta: 0:00:31 time: 0.2829 data_time: 0.0054 memory: 3762 2024/07/15 04:55:26 - mmengine - INFO - Iter(val) [250/313] eta: 0:00:17 time: 0.2829 data_time: 0.0054 memory: 3763 2024/07/15 04:55:40 - mmengine - INFO - Iter(val) [300/313] eta: 0:00:03 time: 0.2828 data_time: 0.0054 memory: 3763 2024/07/15 04:56:12 - mmengine - INFO - Iter(val) [313/313] Bleu_1: 0.7429 Bleu_2: 0.5804 Bleu_3: 0.4450 Bleu_4: 0.3399 METEOR: 0.2769 ROUGE_L: 0.5593 CIDEr: 1.1135 SPICE: 0.2055 data_time: 0.0055 time: 0.2797