diff --git "a/downstream/det/maskrcnn.log" "b/downstream/det/maskrcnn.log" new file mode 100644--- /dev/null +++ "b/downstream/det/maskrcnn.log" @@ -0,0 +1,4191 @@ +2024/10/27 21:57:32 - mmengine - INFO - +------------------------------------------------------------ +System environment: + sys.platform: linux + Python: 3.9.5 (default, Jun 4 2021, 12:28:51) [GCC 7.5.0] + CUDA available: True + MUSA available: False + numpy_random_seed: 4189642 + GPU 0,1,2,3: A100-SXM4-40GB + CUDA_HOME: /usr/local/cuda + NVCC: Cuda compilation tools, release 11.8, V11.8.89 + GCC: gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5) + PyTorch: 2.1.2+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=2.1.2, 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: 0.16.2+cu118 + OpenCV: 4.9.0 + MMEngine: 0.10.5 + +Runtime environment: + cudnn_benchmark: False + mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} + dist_cfg: {'backend': 'nccl'} + seed: 4189642 + Distributed launcher: pytorch + Distributed training: True + GPU number: 4 +------------------------------------------------------------ + +2024/10/27 21:57:33 - mmengine - INFO - Config: +auto_scale_lr = dict(base_batch_size=16, enable=False) +backend_args = None +bs_ratio = 2 +data_root = 'data/coco/' +dataset_type = 'CocoDataset' +default_hooks = dict( + checkpoint=dict(interval=1, type='CheckpointHook'), + logger=dict(interval=50, 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=False, + 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=True, type='LogProcessor', window_size=50) +max_epochs = 12 +model = dict( + backbone=dict( + depth=[ + 2, + 3, + 2, + ], + distillation=False, + down_ops=[ + [ + 'subsample', + 2, + ], + [ + 'subsample', + 2, + ], + [ + '', + ], + ], + drop_path=0.03, + embed_dim=[ + 200, + 376, + 448, + ], + forward_type='v052d', + frozen_stages=-1, + global_ratio=[ + 0.8, + 0.7, + 0.6, + ], + img_size=224, + in_chans=3, + kernels=[ + 7, + 5, + 3, + ], + local_ratio=[ + 0.2, + 0.2, + 0.3, + ], + norm_eval=True, + num_classes=80, + num_heads=[ + 4, + 4, + 4, + ], + out_indices=( + 1, + 2, + 3, + ), + patch_size=16, + pretrained= + '../../weights/MobileMamba_B1/mobilemamba_b1.pth', + ssm_ratio=2, + stages=[ + 's', + 's', + 's', + ], + sync_bn=False, + type='MobileMambaF', + window_size=[ + 7, + 7, + 7, + ]), + data_preprocessor=dict( + bgr_to_rgb=True, + mean=[ + 123.675, + 116.28, + 103.53, + ], + pad_mask=True, + pad_size_divisor=32, + std=[ + 58.395, + 57.12, + 57.375, + ], + type='DetDataPreprocessor'), + neck=dict( + in_channels=[ + 200, + 376, + 448, + ], + num_extra_trans_convs=2, + num_outs=5, + out_channels=256, + start_level=0, + type='EfficientViTFPN'), + roi_head=dict( + bbox_head=dict( + bbox_coder=dict( + target_means=[ + 0.0, + 0.0, + 0.0, + 0.0, + ], + target_stds=[ + 0.1, + 0.1, + 0.2, + 0.2, + ], + type='DeltaXYWHBBoxCoder'), + fc_out_channels=1024, + in_channels=256, + loss_bbox=dict(loss_weight=1.0, type='L1Loss'), + loss_cls=dict( + loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=False), + num_classes=80, + reg_class_agnostic=False, + roi_feat_size=7, + type='Shared2FCBBoxHead'), + bbox_roi_extractor=dict( + featmap_strides=[ + 4, + 8, + 16, + 32, + ], + out_channels=256, + roi_layer=dict(output_size=7, sampling_ratio=0, type='RoIAlign'), + type='SingleRoIExtractor'), + mask_head=dict( + conv_out_channels=256, + in_channels=256, + loss_mask=dict( + loss_weight=1.0, type='CrossEntropyLoss', use_mask=True), + num_classes=80, + num_convs=4, + type='FCNMaskHead'), + mask_roi_extractor=dict( + featmap_strides=[ + 4, + 8, + 16, + 32, + ], + out_channels=256, + roi_layer=dict(output_size=14, sampling_ratio=0, type='RoIAlign'), + type='SingleRoIExtractor'), + type='StandardRoIHead'), + rpn_head=dict( + anchor_generator=dict( + ratios=[ + 0.5, + 1.0, + 2.0, + ], + scales=[ + 8, + ], + strides=[ + 4, + 8, + 16, + 32, + 64, + ], + type='AnchorGenerator'), + bbox_coder=dict( + target_means=[ + 0.0, + 0.0, + 0.0, + 0.0, + ], + target_stds=[ + 1.0, + 1.0, + 1.0, + 1.0, + ], + type='DeltaXYWHBBoxCoder'), + feat_channels=256, + in_channels=256, + loss_bbox=dict(loss_weight=1.0, type='L1Loss'), + loss_cls=dict( + loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=True), + type='RPNHead'), + test_cfg=dict( + rcnn=dict( + mask_thr_binary=0.5, + max_per_img=100, + nms=dict(iou_threshold=0.5, type='nms'), + score_thr=0.05), + rpn=dict( + max_per_img=1000, + min_bbox_size=0, + nms=dict(iou_threshold=0.7, type='nms'), + nms_pre=1000)), + train_cfg=dict( + rcnn=dict( + assigner=dict( + ignore_iof_thr=-1, + match_low_quality=True, + min_pos_iou=0.5, + neg_iou_thr=0.5, + pos_iou_thr=0.5, + type='MaxIoUAssigner'), + debug=False, + mask_size=28, + pos_weight=-1, + sampler=dict( + add_gt_as_proposals=True, + neg_pos_ub=-1, + num=512, + pos_fraction=0.25, + type='RandomSampler')), + rpn=dict( + allowed_border=-1, + assigner=dict( + ignore_iof_thr=-1, + match_low_quality=True, + min_pos_iou=0.3, + neg_iou_thr=0.3, + pos_iou_thr=0.7, + type='MaxIoUAssigner'), + debug=False, + pos_weight=-1, + sampler=dict( + add_gt_as_proposals=False, + neg_pos_ub=-1, + num=256, + pos_fraction=0.5, + type='RandomSampler')), + rpn_proposal=dict( + max_per_img=1000, + min_bbox_size=0, + nms=dict(iou_threshold=0.7, type='nms'), + nms_pre=2000)), + type='MaskRCNN') +optim_wrapper = dict( + clip_grad=dict(max_norm=0.1, norm_type=2), + optimizer=dict( + betas=( + 0.9, + 0.999, + ), lr=0.0002, type='AdamW', weight_decay=0.05), + paramwise_cfg=dict( + custom_keys=dict( + absolute_pos_embed=dict(decay_mult=0.0), + norm=dict(decay_mult=0.0), + relative_position_bias_table=dict(decay_mult=0.0))), + type='OptimWrapper') +param_scheduler = [ + dict( + begin=0, by_epoch=False, end=500, start_factor=1e-05, type='LinearLR'), + dict( + T_max=6, + begin=6, + by_epoch=True, + end=12, + eta_min=0, + type='CosineAnnealingLR'), +] +ratio = 1 +resume = False +test_cfg = dict(type='TestLoop') +test_dataloader = dict( + batch_size=1, + dataset=dict( + ann_file='annotations/instances_val2017.json', + backend_args=None, + data_prefix=dict(img='val2017/'), + data_root='data/coco/', + pipeline=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(keep_ratio=True, scale=( + 1333, + 800, + ), type='Resize'), + dict(type='LoadAnnotations', with_bbox=True, with_mask=True), + dict( + meta_keys=( + 'img_id', + 'img_path', + 'ori_shape', + 'img_shape', + 'scale_factor', + ), + type='PackDetInputs'), + ], + test_mode=True, + type='CocoDataset'), + drop_last=False, + num_workers=2, + persistent_workers=True, + sampler=dict(shuffle=False, type='DefaultSampler')) +test_evaluator = dict( + ann_file='data/coco/annotations/instances_val2017.json', + backend_args=None, + format_only=False, + metric=[ + 'bbox', + 'segm', + ], + type='CocoMetric') +test_pipeline = [ + dict(backend_args=None, type='LoadImageFromFile'), + dict(keep_ratio=True, scale=( + 1333, + 800, + ), type='Resize'), + dict(type='LoadAnnotations', with_bbox=True, with_mask=True), + dict( + meta_keys=( + 'img_id', + 'img_path', + 'ori_shape', + 'img_shape', + 'scale_factor', + ), + type='PackDetInputs'), +] +train_cfg = dict(max_epochs=12, type='EpochBasedTrainLoop', val_interval=1) +train_dataloader = dict( + batch_sampler=dict(type='AspectRatioBatchSampler'), + batch_size=4, + dataset=dict( + ann_file='annotations/instances_train2017.json', + backend_args=None, + data_prefix=dict(img='train2017/'), + data_root='data/coco/', + filter_cfg=dict(filter_empty_gt=True, min_size=32), + pipeline=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(type='LoadAnnotations', with_bbox=True, with_mask=True), + dict(keep_ratio=True, scale=( + 1333, + 800, + ), type='Resize'), + dict(prob=0.5, type='RandomFlip'), + dict(type='PackDetInputs'), + ], + type='CocoDataset'), + num_workers=4, + persistent_workers=True, + sampler=dict(shuffle=True, type='DefaultSampler')) +train_pipeline = [ + dict(backend_args=None, type='LoadImageFromFile'), + dict(type='LoadAnnotations', with_bbox=True, with_mask=True), + dict(keep_ratio=True, scale=( + 1333, + 800, + ), type='Resize'), + dict(prob=0.5, type='RandomFlip'), + dict(type='PackDetInputs'), +] +val_cfg = dict(type='ValLoop') +val_dataloader = dict( + batch_size=1, + dataset=dict( + ann_file='annotations/instances_val2017.json', + backend_args=None, + data_prefix=dict(img='val2017/'), + data_root='data/coco/', + pipeline=[ + dict(backend_args=None, type='LoadImageFromFile'), + dict(keep_ratio=True, scale=( + 1333, + 800, + ), type='Resize'), + dict(type='LoadAnnotations', with_bbox=True, with_mask=True), + dict( + meta_keys=( + 'img_id', + 'img_path', + 'ori_shape', + 'img_shape', + 'scale_factor', + ), + type='PackDetInputs'), + ], + test_mode=True, + type='CocoDataset'), + drop_last=False, + num_workers=2, + persistent_workers=True, + sampler=dict(shuffle=False, type='DefaultSampler')) +val_evaluator = dict( + ann_file='data/coco/annotations/instances_val2017.json', + backend_args=None, + format_only=False, + metric=[ + 'bbox', + 'segm', + ], + type='CocoMetric') +vis_backends = [ + dict(type='LocalVisBackend'), +] +visualizer = dict( + name='visualizer', + type='DetLocalVisualizer', + vis_backends=[ + dict(type='LocalVisBackend'), + ]) +work_dir = './work_dirs/mask-rcnn_mobilemamba_b1_fpn_1x_coco' + +2024/10/27 21:59:40 - mmengine - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) RuntimeInfoHook +(BELOW_NORMAL) LoggerHook + -------------------- +before_train: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_train_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(NORMAL ) DistSamplerSeedHook + -------------------- +before_train_iter: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook + -------------------- +after_train_iter: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(BELOW_NORMAL) LoggerHook +(LOW ) ParamSchedulerHook +(VERY_LOW ) CheckpointHook + -------------------- +after_train_epoch: +(NORMAL ) IterTimerHook +(LOW ) ParamSchedulerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_val: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +before_val_epoch: +(NORMAL ) IterTimerHook + -------------------- +before_val_iter: +(NORMAL ) IterTimerHook + -------------------- +after_val_iter: +(NORMAL ) IterTimerHook +(NORMAL ) DetVisualizationHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_val_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(BELOW_NORMAL) LoggerHook +(LOW ) ParamSchedulerHook +(VERY_LOW ) CheckpointHook + -------------------- +after_val: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +after_train: +(VERY_HIGH ) RuntimeInfoHook +(VERY_LOW ) CheckpointHook + -------------------- +before_test: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +before_test_epoch: +(NORMAL ) IterTimerHook + -------------------- +before_test_iter: +(NORMAL ) IterTimerHook + -------------------- +after_test_iter: +(NORMAL ) IterTimerHook +(NORMAL ) DetVisualizationHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_test_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_test: +(VERY_HIGH ) RuntimeInfoHook + -------------------- +after_run: +(BELOW_NORMAL) LoggerHook + -------------------- +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks1.0.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks1.0.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks1.1.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks1.1.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks2.3.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks2.3.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks2.4.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks2.4.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks2.5.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks2.5.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks3.3.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks3.3.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks3.4.mixer.m.attn.global_op.wt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - WARNING - backbone.blocks3.4.mixer.m.attn.global_op.iwt_filter is skipped since its requires_grad=False +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.weight:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.weight:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.weight:decay_mult=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.bias:lr=0.0002 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.bias:weight_decay=0.0 +2024/10/27 22:00:04 - mmengine - INFO - paramwise_options -- backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.bias:decay_mult=0.0 +Name of parameter - Initialization information + +backbone.patch_embed.0.c.weight - torch.Size([25, 3, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.0.bn.weight - torch.Size([25]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.0.bn.bias - torch.Size([25]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.2.c.weight - torch.Size([50, 25, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.2.bn.weight - torch.Size([50]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.2.bn.bias - torch.Size([50]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.4.c.weight - torch.Size([100, 50, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.4.bn.weight - torch.Size([100]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.4.bn.bias - torch.Size([100]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.6.c.weight - torch.Size([200, 100, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.6.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.patch_embed.6.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.dw0.m.c.weight - torch.Size([200, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.dw0.m.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.dw0.m.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn0.m.pw1.c.weight - torch.Size([400, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn0.m.pw1.bn.weight - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn0.m.pw1.bn.bias - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn0.m.pw2.c.weight - torch.Size([200, 400, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn0.m.pw2.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn0.m.pw2.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([40, 1, 7, 7]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.local_op.bn1.weight - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.local_op.bn1.bias - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([40, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.local_op.bn2.weight - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.local_op.bn2.bias - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.wt_filter - torch.Size([640, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.iwt_filter - torch.Size([640, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 12, 320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.Ds - torch.Size([640]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([640, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 320, 10]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([640, 160, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([640]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([640]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([320, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([160, 320, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([160]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([160]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 160, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([640, 1, 7, 7]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 640, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.proj.1.c.weight - torch.Size([200, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.proj.1.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.mixer.m.attn.proj.1.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.dw1.m.c.weight - torch.Size([200, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.dw1.m.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.dw1.m.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn1.m.pw1.c.weight - torch.Size([400, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn1.m.pw1.bn.weight - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn1.m.pw1.bn.bias - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn1.m.pw2.c.weight - torch.Size([200, 400, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn1.m.pw2.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.0.ffn1.m.pw2.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.dw0.m.c.weight - torch.Size([200, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.dw0.m.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.dw0.m.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn0.m.pw1.c.weight - torch.Size([400, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn0.m.pw1.bn.weight - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn0.m.pw1.bn.bias - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn0.m.pw2.c.weight - torch.Size([200, 400, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn0.m.pw2.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn0.m.pw2.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([40, 1, 7, 7]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.local_op.bn1.weight - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.local_op.bn1.bias - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([40, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.local_op.bn2.weight - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.local_op.bn2.bias - torch.Size([40]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.wt_filter - torch.Size([640, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.iwt_filter - torch.Size([640, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 12, 320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.Ds - torch.Size([640]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([640, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 320, 10]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([640, 160, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([640]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([640]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([320, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([320]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([160, 320, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([160]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([160]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 160, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([640, 1, 7, 7]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 640, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.proj.1.c.weight - torch.Size([200, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.proj.1.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.mixer.m.attn.proj.1.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.dw1.m.c.weight - torch.Size([200, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.dw1.m.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.dw1.m.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn1.m.pw1.c.weight - torch.Size([400, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn1.m.pw1.bn.weight - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn1.m.pw1.bn.bias - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn1.m.pw2.c.weight - torch.Size([200, 400, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn1.m.pw2.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks1.1.ffn1.m.pw2.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.0.m.c.weight - torch.Size([200, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.0.m.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.0.m.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.1.m.pw1.c.weight - torch.Size([400, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.1.m.pw1.bn.weight - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.1.m.pw1.bn.bias - torch.Size([400]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.1.m.pw2.c.weight - torch.Size([200, 400, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.1.m.pw2.bn.weight - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.0.1.m.pw2.bn.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv1.c.weight - torch.Size([800, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv1.bn.weight - torch.Size([800]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv1.bn.bias - torch.Size([800]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv2.c.weight - torch.Size([800, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv2.bn.weight - torch.Size([800]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv2.bn.bias - torch.Size([800]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.se.fc1.weight - torch.Size([200, 800, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.se.fc1.bias - torch.Size([200]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.se.fc2.weight - torch.Size([800, 200, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.se.fc2.bias - torch.Size([800]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv3.c.weight - torch.Size([376, 800, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv3.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.1.conv3.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.0.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.0.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.0.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.1.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.1.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.1.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.1.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.1.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.2.1.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.dw0.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.dw0.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.dw0.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn0.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn0.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn0.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn0.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn0.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn0.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([75, 1, 5, 5]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.local_op.bn1.weight - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.local_op.bn1.bias - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([75, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.local_op.bn2.weight - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.local_op.bn2.bias - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.wt_filter - torch.Size([1024, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.iwt_filter - torch.Size([1024, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 18, 512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.Ds - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([1024, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 512, 16]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([1024, 256, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([512, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([256, 512, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 256, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([1024, 1, 5, 5]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 1024, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.proj.1.c.weight - torch.Size([376, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.proj.1.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.mixer.m.attn.proj.1.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.dw1.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.dw1.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.dw1.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn1.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn1.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn1.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn1.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn1.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.3.ffn1.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.dw0.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.dw0.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.dw0.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn0.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn0.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn0.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn0.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn0.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn0.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([75, 1, 5, 5]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.local_op.bn1.weight - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.local_op.bn1.bias - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([75, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.local_op.bn2.weight - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.local_op.bn2.bias - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.wt_filter - torch.Size([1024, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.iwt_filter - torch.Size([1024, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 18, 512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.Ds - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([1024, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 512, 16]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([1024, 256, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([512, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([256, 512, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 256, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([1024, 1, 5, 5]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 1024, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.proj.1.c.weight - torch.Size([376, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.proj.1.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.mixer.m.attn.proj.1.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.dw1.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.dw1.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.dw1.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn1.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn1.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn1.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn1.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn1.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.4.ffn1.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.dw0.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.dw0.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.dw0.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn0.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn0.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn0.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn0.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn0.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn0.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([75, 1, 5, 5]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.local_op.bn1.weight - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.local_op.bn1.bias - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([75, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.local_op.bn2.weight - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.local_op.bn2.bias - torch.Size([75]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.wt_filter - torch.Size([1024, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.iwt_filter - torch.Size([1024, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 18, 512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.Ds - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([1024, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 512, 16]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([1024, 256, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([512, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([256, 512, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 256, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([1024, 1, 5, 5]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 1024, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.proj.1.c.weight - torch.Size([376, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.proj.1.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.mixer.m.attn.proj.1.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.dw1.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.dw1.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.dw1.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn1.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn1.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn1.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn1.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn1.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks2.5.ffn1.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.0.m.c.weight - torch.Size([376, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.0.m.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.0.m.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.1.m.pw1.c.weight - torch.Size([752, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.1.m.pw1.bn.weight - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.1.m.pw1.bn.bias - torch.Size([752]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.1.m.pw2.c.weight - torch.Size([376, 752, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.1.m.pw2.bn.weight - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.0.1.m.pw2.bn.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv1.c.weight - torch.Size([1504, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv1.bn.weight - torch.Size([1504]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv1.bn.bias - torch.Size([1504]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv2.c.weight - torch.Size([1504, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv2.bn.weight - torch.Size([1504]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv2.bn.bias - torch.Size([1504]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.se.fc1.weight - torch.Size([376, 1504, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.se.fc1.bias - torch.Size([376]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.se.fc2.weight - torch.Size([1504, 376, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.se.fc2.bias - torch.Size([1504]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv3.c.weight - torch.Size([448, 1504, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv3.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.1.conv3.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.0.m.c.weight - torch.Size([448, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.0.m.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.0.m.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.1.m.pw1.c.weight - torch.Size([896, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.1.m.pw1.bn.weight - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.1.m.pw1.bn.bias - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.1.m.pw2.c.weight - torch.Size([448, 896, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.1.m.pw2.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.2.1.m.pw2.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.dw0.m.c.weight - torch.Size([448, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.dw0.m.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.dw0.m.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn0.m.pw1.c.weight - torch.Size([896, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn0.m.pw1.bn.weight - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn0.m.pw1.bn.bias - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn0.m.pw2.c.weight - torch.Size([448, 896, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn0.m.pw2.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn0.m.pw2.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([134, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.local_op.bn1.weight - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.local_op.bn1.bias - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([134, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.local_op.bn2.weight - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.local_op.bn2.bias - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.wt_filter - torch.Size([1088, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.iwt_filter - torch.Size([1088, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 19, 544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.Ds - torch.Size([1088]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([1088, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 544, 17]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([1088, 272, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([1088]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([1088]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([544, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([272, 544, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([272]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([272]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 272, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([1088, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 1088, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.proj.1.c.weight - torch.Size([448, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.proj.1.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.mixer.m.attn.proj.1.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.dw1.m.c.weight - torch.Size([448, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.dw1.m.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.dw1.m.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn1.m.pw1.c.weight - torch.Size([896, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn1.m.pw1.bn.weight - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn1.m.pw1.bn.bias - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn1.m.pw2.c.weight - torch.Size([448, 896, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn1.m.pw2.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.3.ffn1.m.pw2.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.dw0.m.c.weight - torch.Size([448, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.dw0.m.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.dw0.m.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn0.m.pw1.c.weight - torch.Size([896, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn0.m.pw1.bn.weight - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn0.m.pw1.bn.bias - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn0.m.pw2.c.weight - torch.Size([448, 896, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn0.m.pw2.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn0.m.pw2.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.local_op.dwconv3x3.weight - torch.Size([134, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.local_op.bn1.weight - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.local_op.bn1.bias - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.local_op.dwconv1x1.weight - torch.Size([134, 1, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.local_op.bn2.weight - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.local_op.bn2.bias - torch.Size([134]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.wt_filter - torch.Size([1088, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.iwt_filter - torch.Size([1088, 1, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.x_proj_weight - torch.Size([2, 19, 544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.Ds - torch.Size([1088]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.A_logs - torch.Size([1088, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.dt_projs_weight - torch.Size([2, 544, 17]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.dt_projs_bias - torch.Size([2, 544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.weight - torch.Size([544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_norm.bias - torch.Size([544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.in_proj.c.weight - torch.Size([1088, 272, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.in_proj.bn.weight - torch.Size([1088]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.in_proj.bn.bias - torch.Size([1088]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.conv2d.weight - torch.Size([544, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.conv2d.bias - torch.Size([544]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_proj.c.weight - torch.Size([272, 544, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_proj.bn.weight - torch.Size([272]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.global_atten.out_proj.bn.bias - torch.Size([272]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.base_scale.weight - torch.Size([1, 272, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.wavelet_convs.0.weight - torch.Size([1088, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.global_op.wavelet_scale.0.weight - torch.Size([1, 1088, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.proj.1.c.weight - torch.Size([448, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.proj.1.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.mixer.m.attn.proj.1.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.dw1.m.c.weight - torch.Size([448, 1, 3, 3]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.dw1.m.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.dw1.m.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn1.m.pw1.c.weight - torch.Size([896, 448, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn1.m.pw1.bn.weight - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn1.m.pw1.bn.bias - torch.Size([896]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn1.m.pw2.c.weight - torch.Size([448, 896, 1, 1]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn1.m.pw2.bn.weight - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +backbone.blocks3.4.ffn1.m.pw2.bn.bias - torch.Size([448]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.lateral_convs.0.conv.weight - torch.Size([256, 200, 1, 1]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.lateral_convs.0.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.lateral_convs.1.conv.weight - torch.Size([256, 376, 1, 1]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.lateral_convs.1.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.lateral_convs.2.conv.weight - torch.Size([256, 448, 1, 1]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.lateral_convs.2.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.fpn_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.fpn_convs.0.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.fpn_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.fpn_convs.1.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.fpn_convs.2.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.fpn_convs.2.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.extra_trans_convs.0.conv.weight - torch.Size([256, 256, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.extra_trans_convs.0.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.extra_trans_convs.1.conv.weight - torch.Size([256, 256, 2, 2]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.extra_trans_convs.1.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.extra_fpn_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.extra_fpn_convs.0.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +neck.extra_fpn_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in EfficientViTFPN + +neck.extra_fpn_convs.1.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +rpn_head.rpn_conv.weight - torch.Size([256, 256, 3, 3]): +NormalInit: mean=0, std=0.01, bias=0 + +rpn_head.rpn_conv.bias - torch.Size([256]): +NormalInit: mean=0, std=0.01, bias=0 + +rpn_head.rpn_cls.weight - torch.Size([3, 256, 1, 1]): +NormalInit: mean=0, std=0.01, bias=0 + +rpn_head.rpn_cls.bias - torch.Size([3]): +NormalInit: mean=0, std=0.01, bias=0 + +rpn_head.rpn_reg.weight - torch.Size([12, 256, 1, 1]): +NormalInit: mean=0, std=0.01, bias=0 + +rpn_head.rpn_reg.bias - torch.Size([12]): +NormalInit: mean=0, std=0.01, bias=0 + +roi_head.bbox_head.fc_cls.weight - torch.Size([81, 1024]): +NormalInit: mean=0, std=0.01, bias=0 + +roi_head.bbox_head.fc_cls.bias - torch.Size([81]): +NormalInit: mean=0, std=0.01, bias=0 + +roi_head.bbox_head.fc_reg.weight - torch.Size([320, 1024]): +NormalInit: mean=0, std=0.001, bias=0 + +roi_head.bbox_head.fc_reg.bias - torch.Size([320]): +NormalInit: mean=0, std=0.001, bias=0 + +roi_head.bbox_head.shared_fcs.0.weight - torch.Size([1024, 12544]): +XavierInit: gain=1, distribution=uniform, bias=0 + +roi_head.bbox_head.shared_fcs.0.bias - torch.Size([1024]): +XavierInit: gain=1, distribution=uniform, bias=0 + +roi_head.bbox_head.shared_fcs.1.weight - torch.Size([1024, 1024]): +XavierInit: gain=1, distribution=uniform, bias=0 + +roi_head.bbox_head.shared_fcs.1.bias - torch.Size([1024]): +XavierInit: gain=1, distribution=uniform, bias=0 + +roi_head.mask_head.convs.0.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in ConvModule + +roi_head.mask_head.convs.0.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +roi_head.mask_head.convs.1.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in ConvModule + +roi_head.mask_head.convs.1.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +roi_head.mask_head.convs.2.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in ConvModule + +roi_head.mask_head.convs.2.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +roi_head.mask_head.convs.3.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in ConvModule + +roi_head.mask_head.convs.3.conv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of MaskRCNN + +roi_head.mask_head.upsample.weight - torch.Size([256, 256, 2, 2]): +Initialized by user-defined `init_weights` in FCNMaskHead + +roi_head.mask_head.upsample.bias - torch.Size([256]): +Initialized by user-defined `init_weights` in FCNMaskHead + +roi_head.mask_head.conv_logits.weight - torch.Size([80, 256, 1, 1]): +Initialized by user-defined `init_weights` in FCNMaskHead + +roi_head.mask_head.conv_logits.bias - torch.Size([80]): +Initialized by user-defined `init_weights` in FCNMaskHead +2024/10/27 22:00:10 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io +2024/10/27 22:00:10 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. +2024/10/27 22:00:10 - mmengine - INFO - Checkpoints will be saved to work_dirs/mask-rcnn_mobilemamba_b1_fpn_1x_coco. +2024/10/27 22:00:51 - mmengine - INFO - Epoch(train) [1][ 50/7330] base_lr: 1.9641e-05 lr: 1.9641e-05 eta: 19:47:39 time: 0.8106 data_time: 0.0496 memory: 5635 grad_norm: 65.8919 loss: 5.6975 loss_rpn_cls: 0.5109 loss_rpn_bbox: 0.2622 loss_cls: 2.0138 acc: 93.9453 loss_bbox: 0.0844 loss_mask: 2.8262 +2024/10/27 22:01:17 - mmengine - INFO - Epoch(train) [1][ 100/7330] base_lr: 3.9681e-05 lr: 3.9681e-05 eta: 16:25:55 time: 0.5360 data_time: 0.0410 memory: 5691 grad_norm: 9.2527 loss: 1.5906 loss_rpn_cls: 0.2202 loss_rpn_bbox: 0.1181 loss_cls: 0.3412 acc: 95.8984 loss_bbox: 0.1638 loss_mask: 0.7473 +2024/10/27 22:01:39 - mmengine - INFO - Epoch(train) [1][ 150/7330] base_lr: 5.9721e-05 lr: 5.9721e-05 eta: 14:28:36 time: 0.4340 data_time: 0.0454 memory: 5935 grad_norm: 10.0274 loss: 1.5811 loss_rpn_cls: 0.1586 loss_rpn_bbox: 0.1062 loss_cls: 0.4202 acc: 93.1641 loss_bbox: 0.2138 loss_mask: 0.6823 +2024/10/27 22:02:01 - mmengine - INFO - Epoch(train) [1][ 200/7330] base_lr: 7.9761e-05 lr: 7.9761e-05 eta: 13:32:29 time: 0.4414 data_time: 0.0477 memory: 5796 grad_norm: 9.0812 loss: 1.6767 loss_rpn_cls: 0.1310 loss_rpn_bbox: 0.1154 loss_cls: 0.4972 acc: 87.2559 loss_bbox: 0.2815 loss_mask: 0.6515 +2024/10/27 22:02:26 - mmengine - INFO - Epoch(train) [1][ 250/7330] base_lr: 9.9801e-05 lr: 9.9801e-05 eta: 13:13:14 time: 0.4912 data_time: 0.1402 memory: 6064 grad_norm: 11.0264 loss: 1.6723 loss_rpn_cls: 0.1164 loss_rpn_bbox: 0.1121 loss_cls: 0.5090 acc: 88.9160 loss_bbox: 0.3290 loss_mask: 0.6058 +2024/10/27 22:02:47 - mmengine - INFO - Epoch(train) [1][ 300/7330] base_lr: 1.1984e-04 lr: 1.1984e-04 eta: 12:42:23 time: 0.4178 data_time: 0.0435 memory: 6133 grad_norm: 9.5105 loss: 1.6191 loss_rpn_cls: 0.0980 loss_rpn_bbox: 0.1008 loss_cls: 0.5207 acc: 91.1133 loss_bbox: 0.3385 loss_mask: 0.5612 +2024/10/27 22:03:07 - mmengine - INFO - Epoch(train) [1][ 350/7330] base_lr: 1.3988e-04 lr: 1.3988e-04 eta: 12:18:12 time: 0.4080 data_time: 0.0494 memory: 6122 grad_norm: 8.8102 loss: 1.5635 loss_rpn_cls: 0.0910 loss_rpn_bbox: 0.0994 loss_cls: 0.5135 acc: 91.0156 loss_bbox: 0.3674 loss_mask: 0.4922 +2024/10/27 22:03:27 - mmengine - INFO - Epoch(train) [1][ 400/7330] base_lr: 1.5992e-04 lr: 1.5992e-04 eta: 11:58:39 time: 0.4006 data_time: 0.0437 memory: 5985 grad_norm: 8.4489 loss: 1.4544 loss_rpn_cls: 0.0772 loss_rpn_bbox: 0.0890 loss_cls: 0.4580 acc: 92.0898 loss_bbox: 0.3462 loss_mask: 0.4840 +2024/10/27 22:03:48 - mmengine - INFO - Epoch(train) [1][ 450/7330] base_lr: 1.7996e-04 lr: 1.7996e-04 eta: 11:46:39 time: 0.4210 data_time: 0.0490 memory: 6195 grad_norm: 7.8470 loss: 1.4189 loss_rpn_cls: 0.0797 loss_rpn_bbox: 0.0933 loss_cls: 0.4593 acc: 91.6992 loss_bbox: 0.3435 loss_mask: 0.4431 +2024/10/27 22:04:08 - mmengine - INFO - Epoch(train) [1][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:35:21 time: 0.4098 data_time: 0.0616 memory: 6040 grad_norm: 8.2358 loss: 1.4518 loss_rpn_cls: 0.0914 loss_rpn_bbox: 0.0850 loss_cls: 0.4800 acc: 88.6230 loss_bbox: 0.3698 loss_mask: 0.4256 +2024/10/27 22:04:29 - mmengine - INFO - Epoch(train) [1][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:27:23 time: 0.4199 data_time: 0.0544 memory: 6156 grad_norm: 8.0733 loss: 1.3866 loss_rpn_cls: 0.0720 loss_rpn_bbox: 0.0805 loss_cls: 0.4506 acc: 93.6035 loss_bbox: 0.3633 loss_mask: 0.4202 +2024/10/27 22:04:51 - mmengine - INFO - Epoch(train) [1][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:20 time: 0.4252 data_time: 0.0492 memory: 6195 grad_norm: 7.6367 loss: 1.4492 loss_rpn_cls: 0.0764 loss_rpn_bbox: 0.0805 loss_cls: 0.4964 acc: 86.9141 loss_bbox: 0.3867 loss_mask: 0.4091 +2024/10/27 22:05:11 - mmengine - INFO - Epoch(train) [1][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:14:07 time: 0.4068 data_time: 0.0428 memory: 6215 grad_norm: 6.9088 loss: 1.3028 loss_rpn_cls: 0.0740 loss_rpn_bbox: 0.0781 loss_cls: 0.4249 acc: 87.3535 loss_bbox: 0.3314 loss_mask: 0.3945 +2024/10/27 22:05:31 - mmengine - INFO - Epoch(train) [1][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:07:49 time: 0.4063 data_time: 0.0446 memory: 6311 grad_norm: 7.0441 loss: 1.3099 loss_rpn_cls: 0.0862 loss_rpn_bbox: 0.0759 loss_cls: 0.4127 acc: 92.2852 loss_bbox: 0.3424 loss_mask: 0.3927 +2024/10/27 22:05:52 - mmengine - INFO - Epoch(train) [1][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:02:07 time: 0.4044 data_time: 0.0410 memory: 6231 grad_norm: 6.6800 loss: 1.2784 loss_rpn_cls: 0.0607 loss_rpn_bbox: 0.0708 loss_cls: 0.4167 acc: 90.2832 loss_bbox: 0.3387 loss_mask: 0.3915 +2024/10/27 22:06:13 - mmengine - INFO - Epoch(train) [1][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:59:25 time: 0.4300 data_time: 0.0490 memory: 6158 grad_norm: 6.7585 loss: 1.2406 loss_rpn_cls: 0.0755 loss_rpn_bbox: 0.0744 loss_cls: 0.4034 acc: 87.6465 loss_bbox: 0.3228 loss_mask: 0.3645 +2024/10/27 22:06:35 - mmengine - INFO - Epoch(train) [1][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:56:50 time: 0.4281 data_time: 0.0650 memory: 6153 grad_norm: 6.7995 loss: 1.3481 loss_rpn_cls: 0.0730 loss_rpn_bbox: 0.0743 loss_cls: 0.4553 acc: 92.0898 loss_bbox: 0.3637 loss_mask: 0.3817 +2024/10/27 22:06:56 - mmengine - INFO - Epoch(train) [1][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:55:14 time: 0.4373 data_time: 0.0531 memory: 6138 grad_norm: 6.9577 loss: 1.2066 loss_rpn_cls: 0.0593 loss_rpn_bbox: 0.0743 loss_cls: 0.3866 acc: 92.6758 loss_bbox: 0.3089 loss_mask: 0.3774 +2024/10/27 22:07:18 - mmengine - INFO - Epoch(train) [1][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:52:41 time: 0.4231 data_time: 0.0614 memory: 6192 grad_norm: 6.5419 loss: 1.3070 loss_rpn_cls: 0.0701 loss_rpn_bbox: 0.0733 loss_cls: 0.4164 acc: 89.1113 loss_bbox: 0.3720 loss_mask: 0.3752 +2024/10/27 22:07:38 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:07:38 - mmengine - INFO - Epoch(train) [1][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:49:10 time: 0.4067 data_time: 0.0504 memory: 6032 grad_norm: 6.3852 loss: 1.1631 loss_rpn_cls: 0.0595 loss_rpn_bbox: 0.0631 loss_cls: 0.3645 acc: 97.3633 loss_bbox: 0.3117 loss_mask: 0.3644 +2024/10/27 22:07:59 - mmengine - INFO - Epoch(train) [1][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:46:33 time: 0.4155 data_time: 0.0548 memory: 6247 grad_norm: 6.4710 loss: 1.2202 loss_rpn_cls: 0.0638 loss_rpn_bbox: 0.0673 loss_cls: 0.3938 acc: 86.9141 loss_bbox: 0.3370 loss_mask: 0.3583 +2024/10/27 22:08:20 - mmengine - INFO - Epoch(train) [1][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:44:43 time: 0.4239 data_time: 0.0644 memory: 6211 grad_norm: 6.3209 loss: 1.1886 loss_rpn_cls: 0.0596 loss_rpn_bbox: 0.0691 loss_cls: 0.3766 acc: 91.9434 loss_bbox: 0.3203 loss_mask: 0.3630 +2024/10/27 22:08:41 - mmengine - INFO - Epoch(train) [1][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:42:28 time: 0.4155 data_time: 0.0502 memory: 6035 grad_norm: 6.6768 loss: 1.1811 loss_rpn_cls: 0.0603 loss_rpn_bbox: 0.0601 loss_cls: 0.3771 acc: 84.6680 loss_bbox: 0.3154 loss_mask: 0.3683 +2024/10/27 22:09:01 - mmengine - INFO - Epoch(train) [1][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:40:24 time: 0.4159 data_time: 0.0588 memory: 6343 grad_norm: 6.0582 loss: 1.1659 loss_rpn_cls: 0.0579 loss_rpn_bbox: 0.0665 loss_cls: 0.3748 acc: 89.2090 loss_bbox: 0.3287 loss_mask: 0.3380 +2024/10/27 22:09:22 - mmengine - INFO - Epoch(train) [1][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:38:40 time: 0.4194 data_time: 0.0599 memory: 6160 grad_norm: 6.3687 loss: 1.1926 loss_rpn_cls: 0.0564 loss_rpn_bbox: 0.0647 loss_cls: 0.3769 acc: 91.7969 loss_bbox: 0.3381 loss_mask: 0.3566 +2024/10/27 22:09:43 - mmengine - INFO - Epoch(train) [1][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:36:32 time: 0.4100 data_time: 0.0513 memory: 6330 grad_norm: 6.4062 loss: 1.2195 loss_rpn_cls: 0.0532 loss_rpn_bbox: 0.0620 loss_cls: 0.4010 acc: 90.5762 loss_bbox: 0.3448 loss_mask: 0.3584 +2024/10/27 22:10:04 - mmengine - INFO - Epoch(train) [1][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:35:12 time: 0.4227 data_time: 0.0633 memory: 6170 grad_norm: 6.3052 loss: 1.1516 loss_rpn_cls: 0.0558 loss_rpn_bbox: 0.0681 loss_cls: 0.3548 acc: 89.7461 loss_bbox: 0.3332 loss_mask: 0.3396 +2024/10/27 22:10:26 - mmengine - INFO - Epoch(train) [1][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:34:58 time: 0.4427 data_time: 0.0793 memory: 6177 grad_norm: 6.4272 loss: 1.1741 loss_rpn_cls: 0.0536 loss_rpn_bbox: 0.0642 loss_cls: 0.3820 acc: 89.4043 loss_bbox: 0.3289 loss_mask: 0.3453 +2024/10/27 22:10:47 - mmengine - INFO - Epoch(train) [1][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:40 time: 0.4213 data_time: 0.0554 memory: 6176 grad_norm: 5.9560 loss: 1.2173 loss_rpn_cls: 0.0704 loss_rpn_bbox: 0.0736 loss_cls: 0.3822 acc: 87.6465 loss_bbox: 0.3413 loss_mask: 0.3498 +2024/10/27 22:11:09 - mmengine - INFO - Epoch(train) [1][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:26 time: 0.4423 data_time: 0.0630 memory: 6404 grad_norm: 6.2887 loss: 1.1913 loss_rpn_cls: 0.0664 loss_rpn_bbox: 0.0681 loss_cls: 0.3741 acc: 91.2109 loss_bbox: 0.3330 loss_mask: 0.3496 +2024/10/27 22:11:30 - mmengine - INFO - Epoch(train) [1][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:31:57 time: 0.4156 data_time: 0.0561 memory: 6130 grad_norm: 6.4174 loss: 1.1936 loss_rpn_cls: 0.0543 loss_rpn_bbox: 0.0620 loss_cls: 0.3841 acc: 93.4570 loss_bbox: 0.3420 loss_mask: 0.3512 +2024/10/27 22:11:52 - mmengine - INFO - Epoch(train) [1][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:31:07 time: 0.4281 data_time: 0.0640 memory: 6174 grad_norm: 6.1174 loss: 1.1113 loss_rpn_cls: 0.0632 loss_rpn_bbox: 0.0692 loss_cls: 0.3372 acc: 90.8691 loss_bbox: 0.3043 loss_mask: 0.3374 +2024/10/27 22:12:12 - mmengine - INFO - Epoch(train) [1][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:51 time: 0.4181 data_time: 0.0542 memory: 6189 grad_norm: 6.3913 loss: 1.1706 loss_rpn_cls: 0.0655 loss_rpn_bbox: 0.0714 loss_cls: 0.3631 acc: 90.9668 loss_bbox: 0.3283 loss_mask: 0.3421 +2024/10/27 22:12:35 - mmengine - INFO - Epoch(train) [1][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:58 time: 0.4493 data_time: 0.0584 memory: 6295 grad_norm: 6.4270 loss: 1.1978 loss_rpn_cls: 0.0562 loss_rpn_bbox: 0.0669 loss_cls: 0.3828 acc: 91.6992 loss_bbox: 0.3481 loss_mask: 0.3438 +2024/10/27 22:12:56 - mmengine - INFO - Epoch(train) [1][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:17 time: 0.4304 data_time: 0.0663 memory: 6280 grad_norm: 6.1072 loss: 1.1490 loss_rpn_cls: 0.0570 loss_rpn_bbox: 0.0654 loss_cls: 0.3507 acc: 90.7715 loss_bbox: 0.3295 loss_mask: 0.3465 +2024/10/27 22:13:17 - mmengine - INFO - Epoch(train) [1][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:52 time: 0.4117 data_time: 0.0437 memory: 6102 grad_norm: 6.4940 loss: 1.0311 loss_rpn_cls: 0.0501 loss_rpn_bbox: 0.0547 loss_cls: 0.3180 acc: 90.9668 loss_bbox: 0.2752 loss_mask: 0.3332 +2024/10/27 22:13:39 - mmengine - INFO - Epoch(train) [1][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:13 time: 0.4296 data_time: 0.0591 memory: 6086 grad_norm: 6.2141 loss: 1.1375 loss_rpn_cls: 0.0555 loss_rpn_bbox: 0.0656 loss_cls: 0.3519 acc: 92.0898 loss_bbox: 0.3198 loss_mask: 0.3447 +2024/10/27 22:13:59 - mmengine - INFO - Epoch(train) [1][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:26:04 time: 0.4165 data_time: 0.0540 memory: 5948 grad_norm: 5.9660 loss: 1.0777 loss_rpn_cls: 0.0634 loss_rpn_bbox: 0.0638 loss_cls: 0.3287 acc: 97.8516 loss_bbox: 0.2950 loss_mask: 0.3268 +2024/10/27 22:14:20 - mmengine - INFO - Epoch(train) [1][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:24:54 time: 0.4146 data_time: 0.0518 memory: 6118 grad_norm: 6.0998 loss: 1.1172 loss_rpn_cls: 0.0512 loss_rpn_bbox: 0.0602 loss_cls: 0.3526 acc: 90.6250 loss_bbox: 0.3180 loss_mask: 0.3353 +2024/10/27 22:14:41 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:14:41 - mmengine - INFO - Epoch(train) [1][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:23:42 time: 0.4126 data_time: 0.0471 memory: 6164 grad_norm: 6.0085 loss: 1.0279 loss_rpn_cls: 0.0481 loss_rpn_bbox: 0.0546 loss_cls: 0.3100 acc: 94.4336 loss_bbox: 0.2707 loss_mask: 0.3446 +2024/10/27 22:15:01 - mmengine - INFO - Epoch(train) [1][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:22:36 time: 0.4140 data_time: 0.0541 memory: 6172 grad_norm: 6.0849 loss: 1.1096 loss_rpn_cls: 0.0512 loss_rpn_bbox: 0.0574 loss_cls: 0.3447 acc: 87.9883 loss_bbox: 0.3299 loss_mask: 0.3264 +2024/10/27 22:15:22 - mmengine - INFO - Epoch(train) [1][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:21:43 time: 0.4197 data_time: 0.0549 memory: 6193 grad_norm: 6.1836 loss: 1.1637 loss_rpn_cls: 0.0524 loss_rpn_bbox: 0.0668 loss_cls: 0.3741 acc: 94.1406 loss_bbox: 0.3264 loss_mask: 0.3440 +2024/10/27 22:15:43 - mmengine - INFO - Epoch(train) [1][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:20:54 time: 0.4207 data_time: 0.0493 memory: 6273 grad_norm: 5.6519 loss: 1.0683 loss_rpn_cls: 0.0493 loss_rpn_bbox: 0.0593 loss_cls: 0.3225 acc: 92.9688 loss_bbox: 0.3134 loss_mask: 0.3237 +2024/10/27 22:16:05 - mmengine - INFO - Epoch(train) [1][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:20:12 time: 0.4237 data_time: 0.0575 memory: 6284 grad_norm: 6.1799 loss: 1.1422 loss_rpn_cls: 0.0556 loss_rpn_bbox: 0.0669 loss_cls: 0.3440 acc: 94.9707 loss_bbox: 0.3426 loss_mask: 0.3332 +2024/10/27 22:16:27 - mmengine - INFO - Epoch(train) [1][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:20:25 time: 0.4522 data_time: 0.0824 memory: 6081 grad_norm: 5.7497 loss: 1.1026 loss_rpn_cls: 0.0517 loss_rpn_bbox: 0.0680 loss_cls: 0.3357 acc: 88.4277 loss_bbox: 0.3144 loss_mask: 0.3329 +2024/10/27 22:16:49 - mmengine - INFO - Epoch(train) [1][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:20:01 time: 0.4330 data_time: 0.0597 memory: 6122 grad_norm: 5.6387 loss: 1.1182 loss_rpn_cls: 0.0560 loss_rpn_bbox: 0.0666 loss_cls: 0.3374 acc: 91.0645 loss_bbox: 0.3266 loss_mask: 0.3316 +2024/10/27 22:17:11 - mmengine - INFO - Epoch(train) [1][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:19:44 time: 0.4367 data_time: 0.0693 memory: 6363 grad_norm: 6.0600 loss: 1.1955 loss_rpn_cls: 0.0618 loss_rpn_bbox: 0.0713 loss_cls: 0.3794 acc: 86.8652 loss_bbox: 0.3470 loss_mask: 0.3360 +2024/10/27 22:17:33 - mmengine - INFO - Epoch(train) [1][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:19:55 time: 0.4528 data_time: 0.0542 memory: 5933 grad_norm: 5.9426 loss: 1.0786 loss_rpn_cls: 0.0549 loss_rpn_bbox: 0.0636 loss_cls: 0.3273 acc: 86.6211 loss_bbox: 0.3024 loss_mask: 0.3304 +2024/10/27 22:17:54 - mmengine - INFO - Epoch(train) [1][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:19:08 time: 0.4206 data_time: 0.0547 memory: 6179 grad_norm: 5.9957 loss: 1.0870 loss_rpn_cls: 0.0573 loss_rpn_bbox: 0.0626 loss_cls: 0.3416 acc: 90.7715 loss_bbox: 0.3145 loss_mask: 0.3110 +2024/10/27 22:18:16 - mmengine - INFO - Epoch(train) [1][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:18:42 time: 0.4318 data_time: 0.0597 memory: 6077 grad_norm: 5.7973 loss: 1.0729 loss_rpn_cls: 0.0465 loss_rpn_bbox: 0.0642 loss_cls: 0.3310 acc: 88.4766 loss_bbox: 0.3093 loss_mask: 0.3217 +2024/10/27 22:18:37 - mmengine - INFO - Epoch(train) [1][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:17:58 time: 0.4212 data_time: 0.0523 memory: 6201 grad_norm: 6.0618 loss: 1.1007 loss_rpn_cls: 0.0573 loss_rpn_bbox: 0.0602 loss_cls: 0.3440 acc: 96.1426 loss_bbox: 0.3151 loss_mask: 0.3241 +2024/10/27 22:18:58 - mmengine - INFO - Epoch(train) [1][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:17:26 time: 0.4279 data_time: 0.0530 memory: 6281 grad_norm: 5.9205 loss: 1.0627 loss_rpn_cls: 0.0606 loss_rpn_bbox: 0.0637 loss_cls: 0.3144 acc: 95.6055 loss_bbox: 0.3092 loss_mask: 0.3148 +2024/10/27 22:19:20 - mmengine - INFO - Epoch(train) [1][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:16:55 time: 0.4278 data_time: 0.0508 memory: 6252 grad_norm: 5.5569 loss: 1.0993 loss_rpn_cls: 0.0534 loss_rpn_bbox: 0.0620 loss_cls: 0.3530 acc: 94.1895 loss_bbox: 0.3165 loss_mask: 0.3143 +2024/10/27 22:19:40 - mmengine - INFO - Epoch(train) [1][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:15:57 time: 0.4112 data_time: 0.0419 memory: 6151 grad_norm: 5.8206 loss: 1.0772 loss_rpn_cls: 0.0558 loss_rpn_bbox: 0.0656 loss_cls: 0.3178 acc: 92.3828 loss_bbox: 0.3058 loss_mask: 0.3322 +2024/10/27 22:20:02 - mmengine - INFO - Epoch(train) [1][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:15:28 time: 0.4288 data_time: 0.0477 memory: 6238 grad_norm: 5.6583 loss: 1.0800 loss_rpn_cls: 0.0450 loss_rpn_bbox: 0.0582 loss_cls: 0.3356 acc: 94.1895 loss_bbox: 0.3098 loss_mask: 0.3314 +2024/10/27 22:20:26 - mmengine - INFO - Epoch(train) [1][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:16:37 time: 0.4929 data_time: 0.1128 memory: 6165 grad_norm: 5.6156 loss: 1.0259 loss_rpn_cls: 0.0441 loss_rpn_bbox: 0.0561 loss_cls: 0.3211 acc: 96.2402 loss_bbox: 0.2921 loss_mask: 0.3126 +2024/10/27 22:20:47 - mmengine - INFO - Epoch(train) [1][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:15:44 time: 0.4136 data_time: 0.0373 memory: 6174 grad_norm: 5.9872 loss: 1.0671 loss_rpn_cls: 0.0507 loss_rpn_bbox: 0.0607 loss_cls: 0.3224 acc: 96.3867 loss_bbox: 0.3105 loss_mask: 0.3229 +2024/10/27 22:21:08 - mmengine - INFO - Epoch(train) [1][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:14:47 time: 0.4098 data_time: 0.0388 memory: 5944 grad_norm: 5.9013 loss: 1.1225 loss_rpn_cls: 0.0505 loss_rpn_bbox: 0.0632 loss_cls: 0.3629 acc: 85.7422 loss_bbox: 0.3205 loss_mask: 0.3254 +2024/10/27 22:21:29 - mmengine - INFO - Epoch(train) [1][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:14:16 time: 0.4270 data_time: 0.0563 memory: 6207 grad_norm: 5.5604 loss: 1.1223 loss_rpn_cls: 0.0535 loss_rpn_bbox: 0.0689 loss_cls: 0.3390 acc: 87.4023 loss_bbox: 0.3316 loss_mask: 0.3292 +2024/10/27 22:21:50 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:21:50 - mmengine - INFO - Epoch(train) [1][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:13:44 time: 0.4266 data_time: 0.0348 memory: 6161 grad_norm: 6.0150 loss: 1.0411 loss_rpn_cls: 0.0404 loss_rpn_bbox: 0.0540 loss_cls: 0.3287 acc: 84.6680 loss_bbox: 0.2918 loss_mask: 0.3263 +2024/10/27 22:22:12 - mmengine - INFO - Epoch(train) [1][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:13:15 time: 0.4282 data_time: 0.0372 memory: 6099 grad_norm: 5.9515 loss: 0.9938 loss_rpn_cls: 0.0448 loss_rpn_bbox: 0.0576 loss_cls: 0.3036 acc: 91.0156 loss_bbox: 0.2868 loss_mask: 0.3011 +2024/10/27 22:22:33 - mmengine - INFO - Epoch(train) [1][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:39 time: 0.4232 data_time: 0.0382 memory: 6032 grad_norm: 5.8002 loss: 1.0738 loss_rpn_cls: 0.0668 loss_rpn_bbox: 0.0619 loss_cls: 0.3260 acc: 92.0410 loss_bbox: 0.3027 loss_mask: 0.3164 +2024/10/27 22:22:56 - mmengine - INFO - Epoch(train) [1][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:46 time: 0.4543 data_time: 0.0611 memory: 6083 grad_norm: 5.8126 loss: 1.0685 loss_rpn_cls: 0.0569 loss_rpn_bbox: 0.0576 loss_cls: 0.3277 acc: 88.9648 loss_bbox: 0.3112 loss_mask: 0.3151 +2024/10/27 22:23:18 - mmengine - INFO - Epoch(train) [1][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:42 time: 0.4470 data_time: 0.0667 memory: 6235 grad_norm: 5.8192 loss: 1.0777 loss_rpn_cls: 0.0580 loss_rpn_bbox: 0.0612 loss_cls: 0.3312 acc: 91.7969 loss_bbox: 0.3126 loss_mask: 0.3149 +2024/10/27 22:23:39 - mmengine - INFO - Epoch(train) [1][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:07 time: 0.4234 data_time: 0.0528 memory: 6085 grad_norm: 5.8293 loss: 1.0605 loss_rpn_cls: 0.0465 loss_rpn_bbox: 0.0585 loss_cls: 0.3188 acc: 92.1387 loss_bbox: 0.3086 loss_mask: 0.3282 +2024/10/27 22:24:01 - mmengine - INFO - Epoch(train) [1][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:49 time: 0.4361 data_time: 0.0501 memory: 6103 grad_norm: 5.5657 loss: 1.0021 loss_rpn_cls: 0.0461 loss_rpn_bbox: 0.0572 loss_cls: 0.2988 acc: 90.7715 loss_bbox: 0.2880 loss_mask: 0.3120 +2024/10/27 22:24:23 - mmengine - INFO - Epoch(train) [1][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:46 time: 0.4489 data_time: 0.0557 memory: 6286 grad_norm: 5.8859 loss: 1.0409 loss_rpn_cls: 0.0559 loss_rpn_bbox: 0.0626 loss_cls: 0.3044 acc: 91.4062 loss_bbox: 0.2961 loss_mask: 0.3219 +2024/10/27 22:24:46 - mmengine - INFO - Epoch(train) [1][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:50 time: 0.4539 data_time: 0.0550 memory: 6166 grad_norm: 5.6625 loss: 1.1172 loss_rpn_cls: 0.0516 loss_rpn_bbox: 0.0649 loss_cls: 0.3471 acc: 88.8672 loss_bbox: 0.3246 loss_mask: 0.3290 +2024/10/27 22:25:09 - mmengine - INFO - Epoch(train) [1][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:54 time: 0.4552 data_time: 0.0692 memory: 6169 grad_norm: 5.7417 loss: 1.1003 loss_rpn_cls: 0.0556 loss_rpn_bbox: 0.0684 loss_cls: 0.3429 acc: 87.8906 loss_bbox: 0.3238 loss_mask: 0.3096 +2024/10/27 22:25:31 - mmengine - INFO - Epoch(train) [1][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:42 time: 0.4430 data_time: 0.0650 memory: 6132 grad_norm: 5.5177 loss: 1.0390 loss_rpn_cls: 0.0450 loss_rpn_bbox: 0.0601 loss_cls: 0.3180 acc: 91.5039 loss_bbox: 0.2989 loss_mask: 0.3171 +2024/10/27 22:25:53 - mmengine - INFO - Epoch(train) [1][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:20 time: 0.4342 data_time: 0.0543 memory: 6293 grad_norm: 5.6603 loss: 1.0926 loss_rpn_cls: 0.0455 loss_rpn_bbox: 0.0661 loss_cls: 0.3346 acc: 83.8867 loss_bbox: 0.3268 loss_mask: 0.3197 +2024/10/27 22:26:15 - mmengine - INFO - Epoch(train) [1][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:14 time: 0.4479 data_time: 0.0599 memory: 6078 grad_norm: 5.7282 loss: 1.0500 loss_rpn_cls: 0.0592 loss_rpn_bbox: 0.0620 loss_cls: 0.3167 acc: 93.7500 loss_bbox: 0.2929 loss_mask: 0.3192 +2024/10/27 22:26:36 - mmengine - INFO - Epoch(train) [1][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:43 time: 0.4263 data_time: 0.0527 memory: 6058 grad_norm: 5.6487 loss: 1.0097 loss_rpn_cls: 0.0480 loss_rpn_bbox: 0.0579 loss_cls: 0.3054 acc: 94.3359 loss_bbox: 0.2856 loss_mask: 0.3129 +2024/10/27 22:26:58 - mmengine - INFO - Epoch(train) [1][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:23 time: 0.4363 data_time: 0.0570 memory: 6066 grad_norm: 5.6393 loss: 1.0525 loss_rpn_cls: 0.0612 loss_rpn_bbox: 0.0645 loss_cls: 0.3080 acc: 95.0195 loss_bbox: 0.2949 loss_mask: 0.3238 +2024/10/27 22:27:20 - mmengine - INFO - Epoch(train) [1][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:59 time: 0.4326 data_time: 0.0485 memory: 6112 grad_norm: 5.6400 loss: 1.0243 loss_rpn_cls: 0.0480 loss_rpn_bbox: 0.0560 loss_cls: 0.3042 acc: 89.5020 loss_bbox: 0.2975 loss_mask: 0.3185 +2024/10/27 22:27:42 - mmengine - INFO - Epoch(train) [1][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:47 time: 0.4432 data_time: 0.0433 memory: 6266 grad_norm: 5.7032 loss: 1.1004 loss_rpn_cls: 0.0569 loss_rpn_bbox: 0.0627 loss_cls: 0.3344 acc: 96.2891 loss_bbox: 0.3208 loss_mask: 0.3257 +2024/10/27 22:28:03 - mmengine - INFO - Epoch(train) [1][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:18 time: 0.4280 data_time: 0.0453 memory: 6270 grad_norm: 5.5774 loss: 1.1069 loss_rpn_cls: 0.0526 loss_rpn_bbox: 0.0559 loss_cls: 0.3425 acc: 89.5020 loss_bbox: 0.3276 loss_mask: 0.3283 +2024/10/27 22:28:27 - mmengine - INFO - Epoch(train) [1][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:31 time: 0.4673 data_time: 0.0646 memory: 6274 grad_norm: 5.5476 loss: 1.0411 loss_rpn_cls: 0.0602 loss_rpn_bbox: 0.0598 loss_cls: 0.3058 acc: 94.1406 loss_bbox: 0.3024 loss_mask: 0.3129 +2024/10/27 22:28:49 - mmengine - INFO - Epoch(train) [1][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:23 time: 0.4479 data_time: 0.0399 memory: 6079 grad_norm: 5.6429 loss: 1.0515 loss_rpn_cls: 0.0490 loss_rpn_bbox: 0.0620 loss_cls: 0.3067 acc: 92.4316 loss_bbox: 0.3146 loss_mask: 0.3192 +2024/10/27 22:29:12 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:29:12 - mmengine - INFO - Epoch(train) [1][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:14 time: 0.4473 data_time: 0.0469 memory: 6132 grad_norm: 5.4400 loss: 1.0503 loss_rpn_cls: 0.0540 loss_rpn_bbox: 0.0637 loss_cls: 0.3189 acc: 86.5723 loss_bbox: 0.3036 loss_mask: 0.3100 +2024/10/27 22:29:33 - mmengine - INFO - Epoch(train) [1][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:55 time: 0.4385 data_time: 0.0392 memory: 6081 grad_norm: 5.7210 loss: 1.0210 loss_rpn_cls: 0.0441 loss_rpn_bbox: 0.0579 loss_cls: 0.3150 acc: 90.0391 loss_bbox: 0.2942 loss_mask: 0.3097 +2024/10/27 22:29:56 - mmengine - INFO - Epoch(train) [1][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:49 time: 0.4501 data_time: 0.0366 memory: 6409 grad_norm: 5.7868 loss: 0.9968 loss_rpn_cls: 0.0483 loss_rpn_bbox: 0.0544 loss_cls: 0.2963 acc: 92.5293 loss_bbox: 0.2839 loss_mask: 0.3138 +2024/10/27 22:30:18 - mmengine - INFO - Epoch(train) [1][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:31 time: 0.4398 data_time: 0.0425 memory: 6280 grad_norm: 5.9201 loss: 1.0706 loss_rpn_cls: 0.0510 loss_rpn_bbox: 0.0562 loss_cls: 0.3345 acc: 90.2832 loss_bbox: 0.3138 loss_mask: 0.3151 +2024/10/27 22:30:40 - mmengine - INFO - Epoch(train) [1][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:16 time: 0.4419 data_time: 0.0441 memory: 6291 grad_norm: 5.5579 loss: 1.0633 loss_rpn_cls: 0.0577 loss_rpn_bbox: 0.0593 loss_cls: 0.3204 acc: 96.1426 loss_bbox: 0.3085 loss_mask: 0.3174 +2024/10/27 22:31:02 - mmengine - INFO - Epoch(train) [1][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:03 time: 0.4454 data_time: 0.0445 memory: 6213 grad_norm: 5.5708 loss: 1.0693 loss_rpn_cls: 0.0478 loss_rpn_bbox: 0.0591 loss_cls: 0.3346 acc: 85.8398 loss_bbox: 0.3130 loss_mask: 0.3149 +2024/10/27 22:31:28 - mmengine - INFO - Epoch(train) [1][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:53 time: 0.5093 data_time: 0.0998 memory: 6093 grad_norm: 5.7893 loss: 1.0670 loss_rpn_cls: 0.0563 loss_rpn_bbox: 0.0630 loss_cls: 0.3206 acc: 97.4609 loss_bbox: 0.3161 loss_mask: 0.3110 +2024/10/27 22:31:51 - mmengine - INFO - Epoch(train) [1][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:48 time: 0.4547 data_time: 0.0404 memory: 6151 grad_norm: 5.7146 loss: 0.9853 loss_rpn_cls: 0.0487 loss_rpn_bbox: 0.0539 loss_cls: 0.2889 acc: 93.0664 loss_bbox: 0.2898 loss_mask: 0.3040 +2024/10/27 22:32:13 - mmengine - INFO - Epoch(train) [1][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:31 time: 0.4416 data_time: 0.0349 memory: 6253 grad_norm: 5.8768 loss: 1.0278 loss_rpn_cls: 0.0452 loss_rpn_bbox: 0.0576 loss_cls: 0.3145 acc: 90.0391 loss_bbox: 0.3036 loss_mask: 0.3069 +2024/10/27 22:32:35 - mmengine - INFO - Epoch(train) [1][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:22 time: 0.4503 data_time: 0.0427 memory: 6371 grad_norm: 5.6991 loss: 1.0774 loss_rpn_cls: 0.0516 loss_rpn_bbox: 0.0623 loss_cls: 0.3338 acc: 89.9902 loss_bbox: 0.3140 loss_mask: 0.3158 +2024/10/27 22:32:58 - mmengine - INFO - Epoch(train) [1][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:18 time: 0.4565 data_time: 0.0541 memory: 6244 grad_norm: 5.5120 loss: 1.0268 loss_rpn_cls: 0.0457 loss_rpn_bbox: 0.0572 loss_cls: 0.3145 acc: 95.3125 loss_bbox: 0.2951 loss_mask: 0.3143 +2024/10/27 22:33:21 - mmengine - INFO - Epoch(train) [1][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:23 time: 0.4665 data_time: 0.0677 memory: 6152 grad_norm: 5.4564 loss: 1.0540 loss_rpn_cls: 0.0486 loss_rpn_bbox: 0.0606 loss_cls: 0.3310 acc: 90.7715 loss_bbox: 0.3064 loss_mask: 0.3074 +2024/10/27 22:33:43 - mmengine - INFO - Epoch(train) [1][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:06 time: 0.4432 data_time: 0.0574 memory: 6268 grad_norm: 5.6535 loss: 1.0658 loss_rpn_cls: 0.0618 loss_rpn_bbox: 0.0630 loss_cls: 0.3181 acc: 88.0371 loss_bbox: 0.3121 loss_mask: 0.3107 +2024/10/27 22:34:06 - mmengine - INFO - Epoch(train) [1][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:52 time: 0.4462 data_time: 0.0512 memory: 6108 grad_norm: 5.8477 loss: 1.0302 loss_rpn_cls: 0.0472 loss_rpn_bbox: 0.0529 loss_cls: 0.3113 acc: 92.3340 loss_bbox: 0.3008 loss_mask: 0.3181 +2024/10/27 22:34:28 - mmengine - INFO - Epoch(train) [1][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:43 time: 0.4529 data_time: 0.0582 memory: 6264 grad_norm: 5.6482 loss: 1.0441 loss_rpn_cls: 0.0520 loss_rpn_bbox: 0.0649 loss_cls: 0.3133 acc: 90.9668 loss_bbox: 0.2998 loss_mask: 0.3143 +2024/10/27 22:34:51 - mmengine - INFO - Epoch(train) [1][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:31 time: 0.4493 data_time: 0.0540 memory: 6420 grad_norm: 5.8573 loss: 1.0612 loss_rpn_cls: 0.0504 loss_rpn_bbox: 0.0598 loss_cls: 0.3193 acc: 91.2598 loss_bbox: 0.3235 loss_mask: 0.3083 +2024/10/27 22:35:13 - mmengine - INFO - Epoch(train) [1][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:05 time: 0.4333 data_time: 0.0566 memory: 6011 grad_norm: 5.5793 loss: 1.0655 loss_rpn_cls: 0.0551 loss_rpn_bbox: 0.0574 loss_cls: 0.3138 acc: 81.7383 loss_bbox: 0.3209 loss_mask: 0.3183 +2024/10/27 22:35:34 - mmengine - INFO - Epoch(train) [1][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:43 time: 0.4376 data_time: 0.0524 memory: 5958 grad_norm: 5.5560 loss: 1.0722 loss_rpn_cls: 0.0450 loss_rpn_bbox: 0.0635 loss_cls: 0.3238 acc: 90.1367 loss_bbox: 0.3206 loss_mask: 0.3193 +2024/10/27 22:35:56 - mmengine - INFO - Epoch(train) [1][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:17 time: 0.4329 data_time: 0.0541 memory: 6234 grad_norm: 5.7663 loss: 1.0598 loss_rpn_cls: 0.0503 loss_rpn_bbox: 0.0606 loss_cls: 0.3246 acc: 95.3125 loss_bbox: 0.3046 loss_mask: 0.3197 +2024/10/27 22:36:18 - mmengine - INFO - Epoch(train) [1][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:52 time: 0.4347 data_time: 0.0513 memory: 6103 grad_norm: 5.4949 loss: 1.0583 loss_rpn_cls: 0.0467 loss_rpn_bbox: 0.0594 loss_cls: 0.3135 acc: 88.8184 loss_bbox: 0.3225 loss_mask: 0.3161 +2024/10/27 22:36:39 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:36:39 - mmengine - INFO - Epoch(train) [1][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:24 time: 0.4301 data_time: 0.0486 memory: 6315 grad_norm: 5.8454 loss: 1.0037 loss_rpn_cls: 0.0436 loss_rpn_bbox: 0.0611 loss_cls: 0.3031 acc: 93.6523 loss_bbox: 0.2949 loss_mask: 0.3010 +2024/10/27 22:37:02 - mmengine - INFO - Epoch(train) [1][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:17 time: 0.4565 data_time: 0.0633 memory: 6145 grad_norm: 5.4781 loss: 1.0200 loss_rpn_cls: 0.0445 loss_rpn_bbox: 0.0578 loss_cls: 0.3052 acc: 89.5996 loss_bbox: 0.3027 loss_mask: 0.3098 +2024/10/27 22:37:27 - mmengine - INFO - Epoch(train) [1][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:45 time: 0.4989 data_time: 0.1031 memory: 6251 grad_norm: 5.4336 loss: 1.0063 loss_rpn_cls: 0.0429 loss_rpn_bbox: 0.0575 loss_cls: 0.3101 acc: 93.6523 loss_bbox: 0.2942 loss_mask: 0.3016 +2024/10/27 22:37:48 - mmengine - INFO - Epoch(train) [1][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:10 time: 0.4228 data_time: 0.0424 memory: 6065 grad_norm: 5.5333 loss: 1.0170 loss_rpn_cls: 0.0404 loss_rpn_bbox: 0.0564 loss_cls: 0.3009 acc: 92.6270 loss_bbox: 0.3015 loss_mask: 0.3178 +2024/10/27 22:38:09 - mmengine - INFO - Epoch(train) [1][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:35 time: 0.4228 data_time: 0.0443 memory: 6191 grad_norm: 5.5519 loss: 1.0348 loss_rpn_cls: 0.0499 loss_rpn_bbox: 0.0568 loss_cls: 0.3171 acc: 89.5996 loss_bbox: 0.3014 loss_mask: 0.3096 +2024/10/27 22:38:31 - mmengine - INFO - Epoch(train) [1][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:11 time: 0.4350 data_time: 0.0479 memory: 6176 grad_norm: 5.7844 loss: 1.0729 loss_rpn_cls: 0.0470 loss_rpn_bbox: 0.0592 loss_cls: 0.3277 acc: 90.1855 loss_bbox: 0.3148 loss_mask: 0.3242 +2024/10/27 22:38:53 - mmengine - INFO - Epoch(train) [1][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:50 time: 0.4401 data_time: 0.0544 memory: 6252 grad_norm: 5.6194 loss: 1.0759 loss_rpn_cls: 0.0532 loss_rpn_bbox: 0.0654 loss_cls: 0.3273 acc: 94.7754 loss_bbox: 0.3183 loss_mask: 0.3116 +2024/10/27 22:39:15 - mmengine - INFO - Epoch(train) [1][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:27 time: 0.4366 data_time: 0.0512 memory: 6240 grad_norm: 5.1834 loss: 1.0478 loss_rpn_cls: 0.0556 loss_rpn_bbox: 0.0566 loss_cls: 0.3217 acc: 91.1621 loss_bbox: 0.3040 loss_mask: 0.3099 +2024/10/27 22:39:37 - mmengine - INFO - Epoch(train) [1][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:04 time: 0.4370 data_time: 0.0505 memory: 6310 grad_norm: 5.6005 loss: 1.0794 loss_rpn_cls: 0.0557 loss_rpn_bbox: 0.0672 loss_cls: 0.3236 acc: 96.0938 loss_bbox: 0.3257 loss_mask: 0.3072 +2024/10/27 22:39:58 - mmengine - INFO - Epoch(train) [1][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:37 time: 0.4316 data_time: 0.0468 memory: 6128 grad_norm: 5.4822 loss: 1.0523 loss_rpn_cls: 0.0452 loss_rpn_bbox: 0.0567 loss_cls: 0.3189 acc: 91.3574 loss_bbox: 0.3099 loss_mask: 0.3217 +2024/10/27 22:40:19 - mmengine - INFO - Epoch(train) [1][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:01 time: 0.4196 data_time: 0.0415 memory: 6282 grad_norm: 5.5722 loss: 0.9678 loss_rpn_cls: 0.0381 loss_rpn_bbox: 0.0576 loss_cls: 0.2939 acc: 90.0391 loss_bbox: 0.2710 loss_mask: 0.3072 +2024/10/27 22:40:41 - mmengine - INFO - Epoch(train) [1][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:29 time: 0.4234 data_time: 0.0455 memory: 6138 grad_norm: 5.5217 loss: 1.0143 loss_rpn_cls: 0.0463 loss_rpn_bbox: 0.0514 loss_cls: 0.3059 acc: 87.5000 loss_bbox: 0.3004 loss_mask: 0.3104 +2024/10/27 22:41:02 - mmengine - INFO - Epoch(train) [1][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:00 time: 0.4293 data_time: 0.0540 memory: 6205 grad_norm: 5.4365 loss: 1.0643 loss_rpn_cls: 0.0495 loss_rpn_bbox: 0.0627 loss_cls: 0.3183 acc: 93.5547 loss_bbox: 0.3061 loss_mask: 0.3278 +2024/10/27 22:41:27 - mmengine - INFO - Epoch(train) [1][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:24 time: 0.5007 data_time: 0.1177 memory: 6180 grad_norm: 5.3824 loss: 0.9154 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0470 loss_cls: 0.2634 acc: 92.5293 loss_bbox: 0.2683 loss_mask: 0.2981 +2024/10/27 22:41:49 - mmengine - INFO - Epoch(train) [1][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:01 time: 0.4367 data_time: 0.0438 memory: 6221 grad_norm: 5.4969 loss: 1.0137 loss_rpn_cls: 0.0495 loss_rpn_bbox: 0.0559 loss_cls: 0.3061 acc: 94.8242 loss_bbox: 0.2969 loss_mask: 0.3053 +2024/10/27 22:42:11 - mmengine - INFO - Epoch(train) [1][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:46 time: 0.4483 data_time: 0.0579 memory: 6180 grad_norm: 5.6683 loss: 1.0865 loss_rpn_cls: 0.0558 loss_rpn_bbox: 0.0672 loss_cls: 0.3281 acc: 89.8438 loss_bbox: 0.3188 loss_mask: 0.3166 +2024/10/27 22:42:33 - mmengine - INFO - Epoch(train) [1][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:22 time: 0.4357 data_time: 0.0527 memory: 6156 grad_norm: 5.6710 loss: 1.0183 loss_rpn_cls: 0.0424 loss_rpn_bbox: 0.0551 loss_cls: 0.3197 acc: 89.1602 loss_bbox: 0.3028 loss_mask: 0.2982 +2024/10/27 22:42:55 - mmengine - INFO - Epoch(train) [1][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:04 time: 0.4439 data_time: 0.0542 memory: 6267 grad_norm: 5.6023 loss: 1.0048 loss_rpn_cls: 0.0466 loss_rpn_bbox: 0.0544 loss_cls: 0.3075 acc: 94.0430 loss_bbox: 0.3019 loss_mask: 0.2944 +2024/10/27 22:43:17 - mmengine - INFO - Epoch(train) [1][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:35 time: 0.4277 data_time: 0.0497 memory: 6174 grad_norm: 5.3208 loss: 1.0172 loss_rpn_cls: 0.0532 loss_rpn_bbox: 0.0584 loss_cls: 0.3072 acc: 98.4863 loss_bbox: 0.2900 loss_mask: 0.3083 +2024/10/27 22:43:39 - mmengine - INFO - Epoch(train) [1][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:13 time: 0.4391 data_time: 0.0546 memory: 6298 grad_norm: 5.3432 loss: 1.0283 loss_rpn_cls: 0.0494 loss_rpn_bbox: 0.0619 loss_cls: 0.3036 acc: 90.9180 loss_bbox: 0.2954 loss_mask: 0.3180 +2024/10/27 22:44:02 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:44:02 - mmengine - INFO - Epoch(train) [1][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:07 time: 0.4611 data_time: 0.0584 memory: 6416 grad_norm: 5.5061 loss: 1.0265 loss_rpn_cls: 0.0501 loss_rpn_bbox: 0.0614 loss_cls: 0.3030 acc: 81.6406 loss_bbox: 0.2947 loss_mask: 0.3174 +2024/10/27 22:44:27 - mmengine - INFO - Epoch(train) [1][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:29 time: 0.5038 data_time: 0.1271 memory: 6376 grad_norm: 5.5263 loss: 1.0137 loss_rpn_cls: 0.0500 loss_rpn_bbox: 0.0533 loss_cls: 0.3125 acc: 85.9863 loss_bbox: 0.2960 loss_mask: 0.3019 +2024/10/27 22:44:48 - mmengine - INFO - Epoch(train) [1][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:57 time: 0.4236 data_time: 0.0514 memory: 6194 grad_norm: 5.3783 loss: 1.0526 loss_rpn_cls: 0.0486 loss_rpn_bbox: 0.0590 loss_cls: 0.3414 acc: 90.8691 loss_bbox: 0.2955 loss_mask: 0.3082 +2024/10/27 22:45:09 - mmengine - INFO - Epoch(train) [1][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:28 time: 0.4280 data_time: 0.0498 memory: 6209 grad_norm: 5.4041 loss: 0.9682 loss_rpn_cls: 0.0430 loss_rpn_bbox: 0.0527 loss_cls: 0.2862 acc: 92.0898 loss_bbox: 0.2801 loss_mask: 0.3062 +2024/10/27 22:45:32 - mmengine - INFO - Epoch(train) [1][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:09 time: 0.4434 data_time: 0.0640 memory: 6168 grad_norm: 5.4089 loss: 0.9881 loss_rpn_cls: 0.0423 loss_rpn_bbox: 0.0536 loss_cls: 0.2988 acc: 91.6992 loss_bbox: 0.2896 loss_mask: 0.3038 +2024/10/27 22:45:54 - mmengine - INFO - Epoch(train) [1][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:46 time: 0.4383 data_time: 0.0579 memory: 6229 grad_norm: 5.4370 loss: 1.0368 loss_rpn_cls: 0.0471 loss_rpn_bbox: 0.0614 loss_cls: 0.3105 acc: 90.8203 loss_bbox: 0.3092 loss_mask: 0.3087 +2024/10/27 22:46:15 - mmengine - INFO - Epoch(train) [1][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:20 time: 0.4330 data_time: 0.0506 memory: 6171 grad_norm: 5.6489 loss: 1.0402 loss_rpn_cls: 0.0527 loss_rpn_bbox: 0.0606 loss_cls: 0.3110 acc: 86.7676 loss_bbox: 0.2960 loss_mask: 0.3199 +2024/10/27 22:46:37 - mmengine - INFO - Epoch(train) [1][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:01 time: 0.4437 data_time: 0.0569 memory: 6319 grad_norm: 5.7604 loss: 1.0867 loss_rpn_cls: 0.0521 loss_rpn_bbox: 0.0647 loss_cls: 0.3349 acc: 90.8203 loss_bbox: 0.3202 loss_mask: 0.3148 +2024/10/27 22:46:59 - mmengine - INFO - Epoch(train) [1][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:33 time: 0.4280 data_time: 0.0517 memory: 5968 grad_norm: 5.4835 loss: 0.9818 loss_rpn_cls: 0.0467 loss_rpn_bbox: 0.0533 loss_cls: 0.2975 acc: 93.5547 loss_bbox: 0.2855 loss_mask: 0.2987 +2024/10/27 22:47:21 - mmengine - INFO - Epoch(train) [1][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:15 time: 0.4454 data_time: 0.0557 memory: 6256 grad_norm: 5.3664 loss: 1.0087 loss_rpn_cls: 0.0486 loss_rpn_bbox: 0.0588 loss_cls: 0.3086 acc: 86.0352 loss_bbox: 0.2949 loss_mask: 0.2977 +2024/10/27 22:47:44 - mmengine - INFO - Epoch(train) [1][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:03 time: 0.4551 data_time: 0.0716 memory: 6421 grad_norm: 5.1712 loss: 0.9586 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0542 loss_cls: 0.2837 acc: 94.0918 loss_bbox: 0.2821 loss_mask: 0.2977 +2024/10/27 22:48:06 - mmengine - INFO - Epoch(train) [1][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:41 time: 0.4398 data_time: 0.0525 memory: 6323 grad_norm: 5.1018 loss: 0.9988 loss_rpn_cls: 0.0459 loss_rpn_bbox: 0.0587 loss_cls: 0.2885 acc: 93.6035 loss_bbox: 0.2941 loss_mask: 0.3115 +2024/10/27 22:48:28 - mmengine - INFO - Epoch(train) [1][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:21 time: 0.4407 data_time: 0.0529 memory: 6392 grad_norm: 5.5930 loss: 1.0678 loss_rpn_cls: 0.0534 loss_rpn_bbox: 0.0650 loss_cls: 0.3333 acc: 96.4355 loss_bbox: 0.3141 loss_mask: 0.3020 +2024/10/27 22:48:49 - mmengine - INFO - Epoch(train) [1][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:49 time: 0.4241 data_time: 0.0517 memory: 6104 grad_norm: 5.3429 loss: 1.0347 loss_rpn_cls: 0.0481 loss_rpn_bbox: 0.0605 loss_cls: 0.3133 acc: 89.3555 loss_bbox: 0.3073 loss_mask: 0.3054 +2024/10/27 22:49:12 - mmengine - INFO - Epoch(train) [1][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:36 time: 0.4533 data_time: 0.0448 memory: 6101 grad_norm: 5.5404 loss: 0.9794 loss_rpn_cls: 0.0446 loss_rpn_bbox: 0.0529 loss_cls: 0.2929 acc: 94.4824 loss_bbox: 0.2849 loss_mask: 0.3041 +2024/10/27 22:49:34 - mmengine - INFO - Epoch(train) [1][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:17 time: 0.4437 data_time: 0.0398 memory: 6205 grad_norm: 5.7337 loss: 0.9901 loss_rpn_cls: 0.0435 loss_rpn_bbox: 0.0553 loss_cls: 0.2903 acc: 95.1660 loss_bbox: 0.2875 loss_mask: 0.3134 +2024/10/27 22:49:57 - mmengine - INFO - Epoch(train) [1][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:12 time: 0.4668 data_time: 0.0509 memory: 6154 grad_norm: 5.4376 loss: 0.9557 loss_rpn_cls: 0.0411 loss_rpn_bbox: 0.0537 loss_cls: 0.2871 acc: 91.9434 loss_bbox: 0.2740 loss_mask: 0.2999 +2024/10/27 22:50:19 - mmengine - INFO - Epoch(train) [1][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:53 time: 0.4442 data_time: 0.0519 memory: 6048 grad_norm: 5.1588 loss: 0.9994 loss_rpn_cls: 0.0494 loss_rpn_bbox: 0.0587 loss_cls: 0.2931 acc: 88.2324 loss_bbox: 0.2838 loss_mask: 0.3143 +2024/10/27 22:50:42 - mmengine - INFO - Epoch(train) [1][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:40 time: 0.4544 data_time: 0.0573 memory: 6288 grad_norm: 5.6520 loss: 1.0475 loss_rpn_cls: 0.0589 loss_rpn_bbox: 0.0587 loss_cls: 0.3199 acc: 93.5059 loss_bbox: 0.3063 loss_mask: 0.3037 +2024/10/27 22:51:04 - mmengine - INFO - Epoch(train) [1][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:20 time: 0.4434 data_time: 0.0496 memory: 6294 grad_norm: 5.6640 loss: 1.0179 loss_rpn_cls: 0.0445 loss_rpn_bbox: 0.0535 loss_cls: 0.3328 acc: 85.3027 loss_bbox: 0.2967 loss_mask: 0.2904 +2024/10/27 22:51:28 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:51:28 - mmengine - INFO - Epoch(train) [1][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:14 time: 0.4665 data_time: 0.0761 memory: 6197 grad_norm: 5.4244 loss: 1.0182 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0573 loss_cls: 0.3106 acc: 88.4766 loss_bbox: 0.3023 loss_mask: 0.3070 +2024/10/27 22:51:49 - mmengine - INFO - Epoch(train) [1][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:52:49 time: 0.4354 data_time: 0.0472 memory: 6238 grad_norm: 5.4072 loss: 0.9598 loss_rpn_cls: 0.0501 loss_rpn_bbox: 0.0547 loss_cls: 0.2821 acc: 91.8457 loss_bbox: 0.2771 loss_mask: 0.2959 +2024/10/27 22:52:11 - mmengine - INFO - Epoch(train) [1][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:52:27 time: 0.4396 data_time: 0.0442 memory: 6252 grad_norm: 5.6177 loss: 0.9335 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0511 loss_cls: 0.2707 acc: 92.7734 loss_bbox: 0.2736 loss_mask: 0.2994 +2024/10/27 22:52:33 - mmengine - INFO - Epoch(train) [1][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:52:03 time: 0.4357 data_time: 0.0548 memory: 6221 grad_norm: 5.6840 loss: 1.0620 loss_rpn_cls: 0.0540 loss_rpn_bbox: 0.0628 loss_cls: 0.3133 acc: 86.5723 loss_bbox: 0.3218 loss_mask: 0.3100 +2024/10/27 22:52:56 - mmengine - INFO - Epoch(train) [1][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:46 time: 0.4485 data_time: 0.0563 memory: 6309 grad_norm: 5.7412 loss: 1.0496 loss_rpn_cls: 0.0490 loss_rpn_bbox: 0.0575 loss_cls: 0.3203 acc: 92.5781 loss_bbox: 0.3149 loss_mask: 0.3080 +2024/10/27 22:53:18 - mmengine - INFO - Epoch(train) [1][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:24 time: 0.4393 data_time: 0.0485 memory: 6345 grad_norm: 5.5520 loss: 1.0261 loss_rpn_cls: 0.0426 loss_rpn_bbox: 0.0562 loss_cls: 0.3165 acc: 88.0371 loss_bbox: 0.3057 loss_mask: 0.3051 +2024/10/27 22:53:40 - mmengine - INFO - Epoch(train) [1][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:08 time: 0.4510 data_time: 0.0583 memory: 6125 grad_norm: 5.5373 loss: 1.0360 loss_rpn_cls: 0.0452 loss_rpn_bbox: 0.0602 loss_cls: 0.3079 acc: 93.1152 loss_bbox: 0.3142 loss_mask: 0.3085 +2024/10/27 22:53:54 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 22:53:54 - mmengine - INFO - Saving checkpoint at 1 epochs +2024/10/27 22:54:04 - mmengine - INFO - Epoch(val) [1][ 50/1250] eta: 0:02:08 time: 0.1070 data_time: 0.0106 memory: 7526 +2024/10/27 22:54:10 - mmengine - INFO - Epoch(val) [1][ 100/1250] eta: 0:02:09 time: 0.1184 data_time: 0.0039 memory: 1114 +2024/10/27 22:54:16 - mmengine - INFO - Epoch(val) [1][ 150/1250] eta: 0:02:09 time: 0.1290 data_time: 0.0037 memory: 1114 +2024/10/27 22:54:21 - mmengine - INFO - Epoch(val) [1][ 200/1250] eta: 0:02:00 time: 0.1055 data_time: 0.0051 memory: 1114 +2024/10/27 22:54:27 - mmengine - INFO - Epoch(val) [1][ 250/1250] eta: 0:01:55 time: 0.1184 data_time: 0.0040 memory: 1221 +2024/10/27 22:54:35 - mmengine - INFO - Epoch(val) [1][ 300/1250] eta: 0:01:55 time: 0.1519 data_time: 0.0049 memory: 1114 +2024/10/27 22:54:41 - mmengine - INFO - Epoch(val) [1][ 350/1250] eta: 0:01:49 time: 0.1200 data_time: 0.0033 memory: 1117 +2024/10/27 22:54:47 - mmengine - INFO - Epoch(val) [1][ 400/1250] eta: 0:01:43 time: 0.1211 data_time: 0.0035 memory: 1086 +2024/10/27 22:54:52 - mmengine - INFO - Epoch(val) [1][ 450/1250] eta: 0:01:35 time: 0.1022 data_time: 0.0033 memory: 1160 +2024/10/27 22:54:57 - mmengine - INFO - Epoch(val) [1][ 500/1250] eta: 0:01:28 time: 0.1030 data_time: 0.0039 memory: 1134 +2024/10/27 22:55:03 - mmengine - INFO - Epoch(val) [1][ 550/1250] eta: 0:01:21 time: 0.1080 data_time: 0.0036 memory: 1176 +2024/10/27 22:55:08 - mmengine - INFO - Epoch(val) [1][ 600/1250] eta: 0:01:15 time: 0.1131 data_time: 0.0047 memory: 1114 +2024/10/27 22:55:14 - mmengine - INFO - Epoch(val) [1][ 650/1250] eta: 0:01:09 time: 0.1077 data_time: 0.0034 memory: 1219 +2024/10/27 22:55:19 - mmengine - INFO - Epoch(val) [1][ 700/1250] eta: 0:01:03 time: 0.1098 data_time: 0.0044 memory: 1114 +2024/10/27 22:55:25 - mmengine - INFO - Epoch(val) [1][ 750/1250] eta: 0:00:57 time: 0.1098 data_time: 0.0049 memory: 1116 +2024/10/27 22:55:30 - mmengine - INFO - Epoch(val) [1][ 800/1250] eta: 0:00:51 time: 0.1149 data_time: 0.0040 memory: 1160 +2024/10/27 22:55:36 - mmengine - INFO - Epoch(val) [1][ 850/1250] eta: 0:00:45 time: 0.1054 data_time: 0.0033 memory: 1192 +2024/10/27 22:55:41 - mmengine - INFO - Epoch(val) [1][ 900/1250] eta: 0:00:39 time: 0.1085 data_time: 0.0032 memory: 1114 +2024/10/27 22:55:47 - mmengine - INFO - Epoch(val) [1][ 950/1250] eta: 0:00:34 time: 0.1105 data_time: 0.0051 memory: 1219 +2024/10/27 22:55:53 - mmengine - INFO - Epoch(val) [1][1000/1250] eta: 0:00:28 time: 0.1229 data_time: 0.0038 memory: 1081 +2024/10/27 22:55:59 - mmengine - INFO - Epoch(val) [1][1050/1250] eta: 0:00:22 time: 0.1247 data_time: 0.0052 memory: 1114 +2024/10/27 22:56:04 - mmengine - INFO - Epoch(val) [1][1100/1250] eta: 0:00:17 time: 0.1081 data_time: 0.0034 memory: 1114 +2024/10/27 22:56:10 - mmengine - INFO - Epoch(val) [1][1150/1250] eta: 0:00:11 time: 0.1111 data_time: 0.0043 memory: 1114 +2024/10/27 22:56:16 - mmengine - INFO - Epoch(val) [1][1200/1250] eta: 0:00:05 time: 0.1123 data_time: 0.0030 memory: 1176 +2024/10/27 22:56:21 - mmengine - INFO - Epoch(val) [1][1250/1250] eta: 0:00:00 time: 0.1077 data_time: 0.0036 memory: 1114 +2024/10/27 22:56:33 - mmengine - INFO - Evaluating bbox... +2024/10/27 22:57:05 - mmengine - INFO - bbox_mAP_copypaste: 0.227 0.423 0.226 0.103 0.256 0.310 +2024/10/27 22:57:05 - mmengine - INFO - Evaluating segm... +2024/10/27 22:57:42 - mmengine - INFO - segm_mAP_copypaste: 0.238 0.404 0.248 0.077 0.252 0.374 +2024/10/27 22:57:42 - mmengine - INFO - Epoch(val) [1][1250/1250] coco/bbox_mAP: 0.2270 coco/bbox_mAP_50: 0.4230 coco/bbox_mAP_75: 0.2260 coco/bbox_mAP_s: 0.1030 coco/bbox_mAP_m: 0.2560 coco/bbox_mAP_l: 0.3100 coco/segm_mAP: 0.2380 coco/segm_mAP_50: 0.4040 coco/segm_mAP_75: 0.2480 coco/segm_mAP_s: 0.0770 coco/segm_mAP_m: 0.2520 coco/segm_mAP_l: 0.3740 data_time: 0.0042 time: 0.1140 +2024/10/27 22:58:31 - mmengine - INFO - Epoch(train) [2][ 50/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:30 time: 0.9728 data_time: 0.0498 memory: 5979 grad_norm: 5.2698 loss: 0.9664 loss_rpn_cls: 0.0449 loss_rpn_bbox: 0.0559 loss_cls: 0.2941 acc: 83.2520 loss_bbox: 0.2793 loss_mask: 0.2921 +2024/10/27 22:59:14 - mmengine - INFO - Epoch(train) [2][ 100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:50 time: 0.8535 data_time: 0.0579 memory: 6295 grad_norm: 5.4544 loss: 1.0370 loss_rpn_cls: 0.0484 loss_rpn_bbox: 0.0656 loss_cls: 0.3002 acc: 88.8672 loss_bbox: 0.3196 loss_mask: 0.3032 +2024/10/27 22:59:58 - mmengine - INFO - Epoch(train) [2][ 150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:19 time: 0.8762 data_time: 0.0424 memory: 6180 grad_norm: 5.2987 loss: 0.9448 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0471 loss_cls: 0.2906 acc: 86.8652 loss_bbox: 0.2826 loss_mask: 0.2901 +2024/10/27 23:00:47 - mmengine - INFO - Epoch(train) [2][ 200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:44 time: 0.9869 data_time: 0.0483 memory: 6419 grad_norm: 5.5738 loss: 0.9645 loss_rpn_cls: 0.0421 loss_rpn_bbox: 0.0535 loss_cls: 0.2825 acc: 95.6055 loss_bbox: 0.2874 loss_mask: 0.2989 +2024/10/27 23:01:30 - mmengine - INFO - Epoch(train) [2][ 250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:52 time: 0.8494 data_time: 0.0435 memory: 6229 grad_norm: 5.3732 loss: 0.9340 loss_rpn_cls: 0.0383 loss_rpn_bbox: 0.0553 loss_cls: 0.2779 acc: 95.6055 loss_bbox: 0.2743 loss_mask: 0.2882 +2024/10/27 23:02:12 - mmengine - INFO - Epoch(train) [2][ 300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:58 time: 0.8534 data_time: 0.0398 memory: 6085 grad_norm: 5.3306 loss: 0.9190 loss_rpn_cls: 0.0435 loss_rpn_bbox: 0.0511 loss_cls: 0.2699 acc: 94.8730 loss_bbox: 0.2692 loss_mask: 0.2854 +2024/10/27 23:02:58 - mmengine - INFO - Epoch(train) [2][ 350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:16:32 time: 0.9109 data_time: 0.0455 memory: 6131 grad_norm: 5.4644 loss: 0.9886 loss_rpn_cls: 0.0463 loss_rpn_bbox: 0.0561 loss_cls: 0.2941 acc: 92.4805 loss_bbox: 0.3077 loss_mask: 0.2844 +2024/10/27 23:03:42 - mmengine - INFO - Epoch(train) [2][ 400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:19:52 time: 0.8904 data_time: 0.0389 memory: 6233 grad_norm: 5.2504 loss: 0.9487 loss_rpn_cls: 0.0389 loss_rpn_bbox: 0.0529 loss_cls: 0.2782 acc: 93.9453 loss_bbox: 0.2723 loss_mask: 0.3064 +2024/10/27 23:04:31 - mmengine - INFO - Epoch(train) [2][ 450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:23:57 time: 0.9826 data_time: 0.0510 memory: 6204 grad_norm: 5.3470 loss: 1.0625 loss_rpn_cls: 0.0497 loss_rpn_bbox: 0.0692 loss_cls: 0.3175 acc: 95.1660 loss_bbox: 0.3211 loss_mask: 0.3051 +2024/10/27 23:05:17 - mmengine - INFO - Epoch(train) [2][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:21 time: 0.9115 data_time: 0.0484 memory: 6122 grad_norm: 5.3278 loss: 0.9417 loss_rpn_cls: 0.0419 loss_rpn_bbox: 0.0563 loss_cls: 0.2771 acc: 91.3086 loss_bbox: 0.2806 loss_mask: 0.2859 +2024/10/27 23:06:02 - mmengine - INFO - Epoch(train) [2][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:30:31 time: 0.8910 data_time: 0.0453 memory: 6188 grad_norm: 5.3462 loss: 0.9789 loss_rpn_cls: 0.0490 loss_rpn_bbox: 0.0547 loss_cls: 0.2908 acc: 93.4570 loss_bbox: 0.2834 loss_mask: 0.3011 +2024/10/27 23:06:53 - mmengine - INFO - Epoch(train) [2][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:34:46 time: 1.0238 data_time: 0.1183 memory: 6160 grad_norm: 5.3520 loss: 0.9141 loss_rpn_cls: 0.0348 loss_rpn_bbox: 0.0458 loss_cls: 0.2690 acc: 95.8984 loss_bbox: 0.2663 loss_mask: 0.2981 +2024/10/27 23:07:36 - mmengine - INFO - Epoch(train) [2][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:37:39 time: 0.8696 data_time: 0.0465 memory: 6123 grad_norm: 5.3861 loss: 0.9954 loss_rpn_cls: 0.0456 loss_rpn_bbox: 0.0530 loss_cls: 0.3054 acc: 95.8496 loss_bbox: 0.2948 loss_mask: 0.2968 +2024/10/27 23:07:55 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 23:08:23 - mmengine - INFO - Epoch(train) [2][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:41:00 time: 0.9304 data_time: 0.0441 memory: 6131 grad_norm: 5.3810 loss: 0.9766 loss_rpn_cls: 0.0424 loss_rpn_bbox: 0.0552 loss_cls: 0.2930 acc: 85.9863 loss_bbox: 0.2821 loss_mask: 0.3039 +2024/10/27 23:09:08 - mmengine - INFO - Epoch(train) [2][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:44:05 time: 0.9035 data_time: 0.0514 memory: 6250 grad_norm: 5.2591 loss: 0.9756 loss_rpn_cls: 0.0479 loss_rpn_bbox: 0.0587 loss_cls: 0.2803 acc: 87.4512 loss_bbox: 0.2910 loss_mask: 0.2976 +2024/10/27 23:09:55 - mmengine - INFO - Epoch(train) [2][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:47:23 time: 0.9357 data_time: 0.0506 memory: 6264 grad_norm: 5.2950 loss: 1.0024 loss_rpn_cls: 0.0446 loss_rpn_bbox: 0.0571 loss_cls: 0.3017 acc: 89.4531 loss_bbox: 0.2939 loss_mask: 0.3051 +2024/10/27 23:10:40 - mmengine - INFO - Epoch(train) [2][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:50:24 time: 0.9078 data_time: 0.0504 memory: 6223 grad_norm: 5.2754 loss: 0.9894 loss_rpn_cls: 0.0430 loss_rpn_bbox: 0.0552 loss_cls: 0.3017 acc: 93.1641 loss_bbox: 0.2894 loss_mask: 0.3001 +2024/10/27 23:11:26 - mmengine - INFO - Epoch(train) [2][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:53:28 time: 0.9189 data_time: 0.0420 memory: 6135 grad_norm: 5.3223 loss: 0.8974 loss_rpn_cls: 0.0372 loss_rpn_bbox: 0.0503 loss_cls: 0.2610 acc: 88.8184 loss_bbox: 0.2583 loss_mask: 0.2905 +2024/10/27 23:12:15 - mmengine - INFO - Epoch(train) [2][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:56:53 time: 0.9703 data_time: 0.0429 memory: 6177 grad_norm: 5.4129 loss: 0.9331 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0500 loss_cls: 0.2790 acc: 94.2383 loss_bbox: 0.2786 loss_mask: 0.2868 +2024/10/27 23:13:02 - mmengine - INFO - Epoch(train) [2][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:00:10 time: 0.9569 data_time: 0.0475 memory: 6221 grad_norm: 5.3490 loss: 0.9723 loss_rpn_cls: 0.0437 loss_rpn_bbox: 0.0548 loss_cls: 0.3011 acc: 94.1406 loss_bbox: 0.2809 loss_mask: 0.2919 +2024/10/27 23:13:53 - mmengine - INFO - Epoch(train) [2][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:03:46 time: 1.0049 data_time: 0.1129 memory: 6319 grad_norm: 5.0683 loss: 0.9755 loss_rpn_cls: 0.0458 loss_rpn_bbox: 0.0580 loss_cls: 0.2866 acc: 93.0664 loss_bbox: 0.2972 loss_mask: 0.2879 +2024/10/27 23:14:41 - mmengine - INFO - Epoch(train) [2][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:06:57 time: 0.9586 data_time: 0.0506 memory: 6122 grad_norm: 5.2756 loss: 0.9688 loss_rpn_cls: 0.0400 loss_rpn_bbox: 0.0576 loss_cls: 0.2915 acc: 88.9160 loss_bbox: 0.2849 loss_mask: 0.2947 +2024/10/27 23:15:25 - mmengine - INFO - Epoch(train) [2][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:09:31 time: 0.8870 data_time: 0.0518 memory: 6215 grad_norm: 5.4958 loss: 0.9762 loss_rpn_cls: 0.0414 loss_rpn_bbox: 0.0575 loss_cls: 0.2948 acc: 88.0371 loss_bbox: 0.2891 loss_mask: 0.2934 +2024/10/27 23:16:11 - mmengine - INFO - Epoch(train) [2][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:12:18 time: 0.9186 data_time: 0.0495 memory: 6182 grad_norm: 5.4483 loss: 0.9619 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0532 loss_cls: 0.2901 acc: 86.2793 loss_bbox: 0.2858 loss_mask: 0.2919 +2024/10/27 23:16:58 - mmengine - INFO - Epoch(train) [2][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:15:17 time: 0.9490 data_time: 0.0539 memory: 6138 grad_norm: 5.6196 loss: 1.0169 loss_rpn_cls: 0.0439 loss_rpn_bbox: 0.0572 loss_cls: 0.3054 acc: 86.7676 loss_bbox: 0.3080 loss_mask: 0.3024 +2024/10/27 23:17:45 - mmengine - INFO - Epoch(train) [2][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:18:10 time: 0.9425 data_time: 0.0489 memory: 6273 grad_norm: 5.3589 loss: 0.9906 loss_rpn_cls: 0.0400 loss_rpn_bbox: 0.0558 loss_cls: 0.2984 acc: 93.8965 loss_bbox: 0.3060 loss_mask: 0.2904 +2024/10/27 23:18:35 - mmengine - INFO - Epoch(train) [2][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:21 time: 0.9879 data_time: 0.0492 memory: 6191 grad_norm: 5.3687 loss: 0.9814 loss_rpn_cls: 0.0412 loss_rpn_bbox: 0.0593 loss_cls: 0.2826 acc: 93.0176 loss_bbox: 0.2912 loss_mask: 0.3071 +2024/10/27 23:19:22 - mmengine - INFO - Epoch(train) [2][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:24:07 time: 0.9379 data_time: 0.0530 memory: 6097 grad_norm: 5.1761 loss: 0.9877 loss_rpn_cls: 0.0415 loss_rpn_bbox: 0.0543 loss_cls: 0.2940 acc: 87.6465 loss_bbox: 0.3000 loss_mask: 0.2979 +2024/10/27 23:20:06 - mmengine - INFO - Epoch(train) [2][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:26:28 time: 0.8869 data_time: 0.0442 memory: 6086 grad_norm: 5.1966 loss: 0.9407 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0469 loss_cls: 0.2779 acc: 94.1406 loss_bbox: 0.2836 loss_mask: 0.2944 +2024/10/27 23:20:52 - mmengine - INFO - Epoch(train) [2][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:29:04 time: 0.9281 data_time: 0.0611 memory: 6231 grad_norm: 5.3386 loss: 0.9865 loss_rpn_cls: 0.0461 loss_rpn_bbox: 0.0597 loss_cls: 0.3021 acc: 93.6523 loss_bbox: 0.2944 loss_mask: 0.2841 +2024/10/27 23:21:38 - mmengine - INFO - Epoch(train) [2][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:31:29 time: 0.9068 data_time: 0.0486 memory: 6204 grad_norm: 5.3301 loss: 1.0035 loss_rpn_cls: 0.0421 loss_rpn_bbox: 0.0579 loss_cls: 0.3108 acc: 93.9941 loss_bbox: 0.2933 loss_mask: 0.2994 +2024/10/27 23:22:02 - mmengine - INFO - Epoch(train) [2][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:30:43 time: 0.4798 data_time: 0.0403 memory: 6087 grad_norm: 5.2668 loss: 0.8713 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0432 loss_cls: 0.2561 acc: 89.2090 loss_bbox: 0.2497 loss_mask: 0.2854 +2024/10/27 23:22:29 - mmengine - INFO - Epoch(train) [2][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:30:26 time: 0.5456 data_time: 0.1233 memory: 6171 grad_norm: 5.3227 loss: 0.9760 loss_rpn_cls: 0.0497 loss_rpn_bbox: 0.0559 loss_cls: 0.2846 acc: 94.1406 loss_bbox: 0.2867 loss_mask: 0.2992 +2024/10/27 23:22:39 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 23:22:53 - mmengine - INFO - Epoch(train) [2][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:29:38 time: 0.4733 data_time: 0.0474 memory: 6390 grad_norm: 5.0490 loss: 0.9883 loss_rpn_cls: 0.0465 loss_rpn_bbox: 0.0591 loss_cls: 0.2988 acc: 88.4766 loss_bbox: 0.2862 loss_mask: 0.2978 +2024/10/27 23:23:17 - mmengine - INFO - Epoch(train) [2][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:28:51 time: 0.4772 data_time: 0.0514 memory: 6170 grad_norm: 5.3419 loss: 0.9559 loss_rpn_cls: 0.0400 loss_rpn_bbox: 0.0560 loss_cls: 0.2935 acc: 86.0840 loss_bbox: 0.2767 loss_mask: 0.2897 +2024/10/27 23:23:41 - mmengine - INFO - Epoch(train) [2][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:28:10 time: 0.4894 data_time: 0.0580 memory: 6197 grad_norm: 5.4134 loss: 0.9451 loss_rpn_cls: 0.0449 loss_rpn_bbox: 0.0574 loss_cls: 0.2764 acc: 87.5488 loss_bbox: 0.2823 loss_mask: 0.2842 +2024/10/27 23:24:05 - mmengine - INFO - Epoch(train) [2][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:27:27 time: 0.4848 data_time: 0.0477 memory: 6126 grad_norm: 5.5218 loss: 0.9367 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0516 loss_cls: 0.2746 acc: 94.7266 loss_bbox: 0.2756 loss_mask: 0.2962 +2024/10/27 23:24:29 - mmengine - INFO - Epoch(train) [2][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:26:44 time: 0.4831 data_time: 0.0533 memory: 6105 grad_norm: 5.2120 loss: 0.9542 loss_rpn_cls: 0.0420 loss_rpn_bbox: 0.0555 loss_cls: 0.2920 acc: 92.5293 loss_bbox: 0.2733 loss_mask: 0.2915 +2024/10/27 23:24:54 - mmengine - INFO - Epoch(train) [2][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:26:03 time: 0.4896 data_time: 0.0536 memory: 6248 grad_norm: 5.3546 loss: 0.9099 loss_rpn_cls: 0.0429 loss_rpn_bbox: 0.0515 loss_cls: 0.2621 acc: 88.8184 loss_bbox: 0.2688 loss_mask: 0.2845 +2024/10/27 23:25:18 - mmengine - INFO - Epoch(train) [2][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:25:21 time: 0.4852 data_time: 0.0498 memory: 6135 grad_norm: 5.1771 loss: 0.9299 loss_rpn_cls: 0.0423 loss_rpn_bbox: 0.0536 loss_cls: 0.2733 acc: 90.4785 loss_bbox: 0.2731 loss_mask: 0.2877 +2024/10/27 23:25:43 - mmengine - INFO - Epoch(train) [2][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:24:39 time: 0.4858 data_time: 0.0582 memory: 6154 grad_norm: 5.3202 loss: 0.9648 loss_rpn_cls: 0.0450 loss_rpn_bbox: 0.0540 loss_cls: 0.2757 acc: 92.7246 loss_bbox: 0.2916 loss_mask: 0.2984 +2024/10/27 23:26:07 - mmengine - INFO - Epoch(train) [2][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:24:02 time: 0.4954 data_time: 0.0671 memory: 6257 grad_norm: 5.2224 loss: 1.0478 loss_rpn_cls: 0.0532 loss_rpn_bbox: 0.0666 loss_cls: 0.3110 acc: 87.4023 loss_bbox: 0.3198 loss_mask: 0.2972 +2024/10/27 23:26:31 - mmengine - INFO - Epoch(train) [2][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:23:20 time: 0.4841 data_time: 0.0482 memory: 6207 grad_norm: 5.1909 loss: 0.9039 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0498 loss_cls: 0.2602 acc: 93.8477 loss_bbox: 0.2708 loss_mask: 0.2847 +2024/10/27 23:26:56 - mmengine - INFO - Epoch(train) [2][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:22:41 time: 0.4922 data_time: 0.0492 memory: 6279 grad_norm: 5.5570 loss: 0.9312 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0482 loss_cls: 0.2825 acc: 93.1641 loss_bbox: 0.2788 loss_mask: 0.2851 +2024/10/27 23:27:20 - mmengine - INFO - Epoch(train) [2][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:59 time: 0.4842 data_time: 0.0454 memory: 6393 grad_norm: 5.1877 loss: 0.9455 loss_rpn_cls: 0.0399 loss_rpn_bbox: 0.0533 loss_cls: 0.2807 acc: 95.2637 loss_bbox: 0.2710 loss_mask: 0.3007 +2024/10/27 23:27:46 - mmengine - INFO - Epoch(train) [2][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:26 time: 0.5039 data_time: 0.0616 memory: 6170 grad_norm: 5.3451 loss: 0.9071 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0493 loss_cls: 0.2670 acc: 90.8691 loss_bbox: 0.2725 loss_mask: 0.2816 +2024/10/27 23:28:09 - mmengine - INFO - Epoch(train) [2][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:20:41 time: 0.4754 data_time: 0.0489 memory: 6330 grad_norm: 5.4375 loss: 0.9482 loss_rpn_cls: 0.0408 loss_rpn_bbox: 0.0513 loss_cls: 0.2675 acc: 89.6484 loss_bbox: 0.2910 loss_mask: 0.2977 +2024/10/27 23:28:33 - mmengine - INFO - Epoch(train) [2][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:19:57 time: 0.4771 data_time: 0.0376 memory: 6420 grad_norm: 4.9832 loss: 0.9075 loss_rpn_cls: 0.0309 loss_rpn_bbox: 0.0426 loss_cls: 0.2728 acc: 96.3867 loss_bbox: 0.2665 loss_mask: 0.2947 +2024/10/27 23:28:57 - mmengine - INFO - Epoch(train) [2][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:19:13 time: 0.4779 data_time: 0.0481 memory: 6296 grad_norm: 5.3206 loss: 0.9366 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0518 loss_cls: 0.2691 acc: 94.7266 loss_bbox: 0.2806 loss_mask: 0.2945 +2024/10/27 23:29:21 - mmengine - INFO - Epoch(train) [2][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:18:29 time: 0.4747 data_time: 0.0453 memory: 6419 grad_norm: 5.1607 loss: 0.9594 loss_rpn_cls: 0.0466 loss_rpn_bbox: 0.0565 loss_cls: 0.2832 acc: 87.9883 loss_bbox: 0.2770 loss_mask: 0.2961 +2024/10/27 23:29:45 - mmengine - INFO - Epoch(train) [2][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:17:45 time: 0.4765 data_time: 0.0422 memory: 6089 grad_norm: 5.2768 loss: 0.9285 loss_rpn_cls: 0.0407 loss_rpn_bbox: 0.0560 loss_cls: 0.2731 acc: 89.3066 loss_bbox: 0.2632 loss_mask: 0.2956 +2024/10/27 23:30:09 - mmengine - INFO - Epoch(train) [2][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:17:06 time: 0.4876 data_time: 0.0487 memory: 6073 grad_norm: 5.4106 loss: 0.9265 loss_rpn_cls: 0.0413 loss_rpn_bbox: 0.0499 loss_cls: 0.2680 acc: 93.1641 loss_bbox: 0.2738 loss_mask: 0.2936 +2024/10/27 23:30:33 - mmengine - INFO - Epoch(train) [2][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:16:24 time: 0.4787 data_time: 0.0445 memory: 6200 grad_norm: 5.1652 loss: 0.8842 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0475 loss_cls: 0.2568 acc: 94.5312 loss_bbox: 0.2527 loss_mask: 0.2950 +2024/10/27 23:30:43 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 23:30:57 - mmengine - INFO - Epoch(train) [2][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:15:40 time: 0.4742 data_time: 0.0470 memory: 6035 grad_norm: 5.0849 loss: 0.9115 loss_rpn_cls: 0.0372 loss_rpn_bbox: 0.0485 loss_cls: 0.2748 acc: 84.3262 loss_bbox: 0.2592 loss_mask: 0.2917 +2024/10/27 23:31:21 - mmengine - INFO - Epoch(train) [2][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:14:59 time: 0.4834 data_time: 0.0539 memory: 6135 grad_norm: 5.0719 loss: 0.9877 loss_rpn_cls: 0.0437 loss_rpn_bbox: 0.0596 loss_cls: 0.3009 acc: 83.3984 loss_bbox: 0.2942 loss_mask: 0.2893 +2024/10/27 23:31:45 - mmengine - INFO - Epoch(train) [2][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:14:19 time: 0.4831 data_time: 0.0430 memory: 6106 grad_norm: 5.0334 loss: 0.9250 loss_rpn_cls: 0.0442 loss_rpn_bbox: 0.0543 loss_cls: 0.2621 acc: 91.1133 loss_bbox: 0.2756 loss_mask: 0.2888 +2024/10/27 23:32:10 - mmengine - INFO - Epoch(train) [2][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:13:46 time: 0.4994 data_time: 0.0453 memory: 6234 grad_norm: 5.4802 loss: 0.9801 loss_rpn_cls: 0.0407 loss_rpn_bbox: 0.0531 loss_cls: 0.2899 acc: 93.9453 loss_bbox: 0.3069 loss_mask: 0.2894 +2024/10/27 23:32:34 - mmengine - INFO - Epoch(train) [2][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:13:02 time: 0.4744 data_time: 0.0458 memory: 6189 grad_norm: 5.1995 loss: 0.9598 loss_rpn_cls: 0.0456 loss_rpn_bbox: 0.0587 loss_cls: 0.2833 acc: 93.2617 loss_bbox: 0.2845 loss_mask: 0.2878 +2024/10/27 23:32:58 - mmengine - INFO - Epoch(train) [2][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:12:22 time: 0.4804 data_time: 0.0550 memory: 6088 grad_norm: 5.2274 loss: 0.9550 loss_rpn_cls: 0.0413 loss_rpn_bbox: 0.0544 loss_cls: 0.2822 acc: 86.3770 loss_bbox: 0.2839 loss_mask: 0.2931 +2024/10/27 23:33:21 - mmengine - INFO - Epoch(train) [2][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:11:39 time: 0.4761 data_time: 0.0486 memory: 6068 grad_norm: 5.0802 loss: 1.0126 loss_rpn_cls: 0.0466 loss_rpn_bbox: 0.0653 loss_cls: 0.2987 acc: 95.0195 loss_bbox: 0.2960 loss_mask: 0.3060 +2024/10/27 23:33:45 - mmengine - INFO - Epoch(train) [2][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:10:58 time: 0.4788 data_time: 0.0450 memory: 6157 grad_norm: 5.3260 loss: 0.9364 loss_rpn_cls: 0.0382 loss_rpn_bbox: 0.0508 loss_cls: 0.2750 acc: 94.4824 loss_bbox: 0.2756 loss_mask: 0.2968 +2024/10/27 23:34:09 - mmengine - INFO - Epoch(train) [2][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:10:17 time: 0.4770 data_time: 0.0496 memory: 6211 grad_norm: 5.2515 loss: 1.0192 loss_rpn_cls: 0.0465 loss_rpn_bbox: 0.0624 loss_cls: 0.3074 acc: 96.6309 loss_bbox: 0.2998 loss_mask: 0.3031 +2024/10/27 23:34:33 - mmengine - INFO - Epoch(train) [2][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:09:31 time: 0.4660 data_time: 0.0400 memory: 6249 grad_norm: 5.2129 loss: 0.9189 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0471 loss_cls: 0.2714 acc: 86.1328 loss_bbox: 0.2690 loss_mask: 0.2929 +2024/10/27 23:34:56 - mmengine - INFO - Epoch(train) [2][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:08:47 time: 0.4682 data_time: 0.0375 memory: 6096 grad_norm: 5.1428 loss: 0.9000 loss_rpn_cls: 0.0430 loss_rpn_bbox: 0.0529 loss_cls: 0.2637 acc: 94.4336 loss_bbox: 0.2621 loss_mask: 0.2782 +2024/10/27 23:35:20 - mmengine - INFO - Epoch(train) [2][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:08:07 time: 0.4808 data_time: 0.0485 memory: 6290 grad_norm: 5.1109 loss: 0.9637 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0535 loss_cls: 0.2931 acc: 84.1309 loss_bbox: 0.2835 loss_mask: 0.2957 +2024/10/27 23:35:45 - mmengine - INFO - Epoch(train) [2][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:07:36 time: 0.5032 data_time: 0.0726 memory: 6300 grad_norm: 5.1702 loss: 0.9320 loss_rpn_cls: 0.0434 loss_rpn_bbox: 0.0529 loss_cls: 0.2842 acc: 95.5078 loss_bbox: 0.2605 loss_mask: 0.2911 +2024/10/27 23:36:09 - mmengine - INFO - Epoch(train) [2][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:06:54 time: 0.4725 data_time: 0.0455 memory: 6251 grad_norm: 4.9935 loss: 0.9661 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0512 loss_cls: 0.2867 acc: 89.2578 loss_bbox: 0.2855 loss_mask: 0.3054 +2024/10/27 23:36:33 - mmengine - INFO - Epoch(train) [2][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:06:16 time: 0.4839 data_time: 0.0500 memory: 6420 grad_norm: 5.3520 loss: 0.9177 loss_rpn_cls: 0.0419 loss_rpn_bbox: 0.0528 loss_cls: 0.2669 acc: 90.9180 loss_bbox: 0.2743 loss_mask: 0.2818 +2024/10/27 23:36:58 - mmengine - INFO - Epoch(train) [2][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:05:41 time: 0.4929 data_time: 0.0583 memory: 6237 grad_norm: 5.0464 loss: 1.0179 loss_rpn_cls: 0.0568 loss_rpn_bbox: 0.0595 loss_cls: 0.2995 acc: 89.0137 loss_bbox: 0.3016 loss_mask: 0.3004 +2024/10/27 23:37:22 - mmengine - INFO - Epoch(train) [2][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:05:01 time: 0.4791 data_time: 0.0424 memory: 6144 grad_norm: 5.2795 loss: 0.9517 loss_rpn_cls: 0.0482 loss_rpn_bbox: 0.0516 loss_cls: 0.2754 acc: 88.5742 loss_bbox: 0.2744 loss_mask: 0.3021 +2024/10/27 23:37:46 - mmengine - INFO - Epoch(train) [2][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:04:22 time: 0.4781 data_time: 0.0420 memory: 6128 grad_norm: 5.3600 loss: 0.9120 loss_rpn_cls: 0.0466 loss_rpn_bbox: 0.0531 loss_cls: 0.2633 acc: 95.1660 loss_bbox: 0.2684 loss_mask: 0.2806 +2024/10/27 23:38:10 - mmengine - INFO - Epoch(train) [2][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:03:42 time: 0.4795 data_time: 0.0503 memory: 6101 grad_norm: 5.0572 loss: 0.9680 loss_rpn_cls: 0.0417 loss_rpn_bbox: 0.0576 loss_cls: 0.2954 acc: 92.9199 loss_bbox: 0.2795 loss_mask: 0.2938 +2024/10/27 23:38:34 - mmengine - INFO - Epoch(train) [2][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:03:06 time: 0.4875 data_time: 0.0543 memory: 6290 grad_norm: 5.2644 loss: 0.9280 loss_rpn_cls: 0.0386 loss_rpn_bbox: 0.0541 loss_cls: 0.2786 acc: 91.6992 loss_bbox: 0.2756 loss_mask: 0.2811 +2024/10/27 23:38:44 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 23:38:58 - mmengine - INFO - Epoch(train) [2][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:02:32 time: 0.4919 data_time: 0.0586 memory: 6242 grad_norm: 5.1374 loss: 0.9040 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0474 loss_cls: 0.2739 acc: 90.0391 loss_bbox: 0.2644 loss_mask: 0.2804 +2024/10/27 23:39:23 - mmengine - INFO - Epoch(train) [2][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:01:56 time: 0.4890 data_time: 0.0670 memory: 6253 grad_norm: 5.0976 loss: 0.9951 loss_rpn_cls: 0.0451 loss_rpn_bbox: 0.0578 loss_cls: 0.3067 acc: 89.4531 loss_bbox: 0.2946 loss_mask: 0.2907 +2024/10/27 23:39:46 - mmengine - INFO - Epoch(train) [2][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:01:14 time: 0.4686 data_time: 0.0482 memory: 6189 grad_norm: 5.3739 loss: 0.8878 loss_rpn_cls: 0.0383 loss_rpn_bbox: 0.0511 loss_cls: 0.2652 acc: 92.6270 loss_bbox: 0.2452 loss_mask: 0.2880 +2024/10/27 23:40:11 - mmengine - INFO - Epoch(train) [2][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:00:38 time: 0.4874 data_time: 0.0606 memory: 6266 grad_norm: 5.3722 loss: 0.9305 loss_rpn_cls: 0.0433 loss_rpn_bbox: 0.0538 loss_cls: 0.2885 acc: 85.4492 loss_bbox: 0.2741 loss_mask: 0.2708 +2024/10/27 23:40:34 - mmengine - INFO - Epoch(train) [2][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:59:57 time: 0.4718 data_time: 0.0524 memory: 6192 grad_norm: 5.3979 loss: 0.8940 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0509 loss_cls: 0.2609 acc: 89.6973 loss_bbox: 0.2748 loss_mask: 0.2711 +2024/10/27 23:40:59 - mmengine - INFO - Epoch(train) [2][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:59:22 time: 0.4874 data_time: 0.0569 memory: 6260 grad_norm: 5.1035 loss: 0.9563 loss_rpn_cls: 0.0453 loss_rpn_bbox: 0.0575 loss_cls: 0.2786 acc: 95.9473 loss_bbox: 0.2862 loss_mask: 0.2887 +2024/10/27 23:41:23 - mmengine - INFO - Epoch(train) [2][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:58:43 time: 0.4797 data_time: 0.0615 memory: 6302 grad_norm: 5.4321 loss: 0.9841 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0561 loss_cls: 0.2916 acc: 90.9668 loss_bbox: 0.2994 loss_mask: 0.3017 +2024/10/27 23:41:46 - mmengine - INFO - Epoch(train) [2][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:58:04 time: 0.4752 data_time: 0.0512 memory: 6402 grad_norm: 5.2933 loss: 0.9485 loss_rpn_cls: 0.0397 loss_rpn_bbox: 0.0521 loss_cls: 0.2842 acc: 95.2148 loss_bbox: 0.2881 loss_mask: 0.2844 +2024/10/27 23:42:11 - mmengine - INFO - Epoch(train) [2][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:57:31 time: 0.4929 data_time: 0.0516 memory: 6343 grad_norm: 5.3314 loss: 0.9074 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0528 loss_cls: 0.2606 acc: 95.4590 loss_bbox: 0.2656 loss_mask: 0.2931 +2024/10/27 23:42:35 - mmengine - INFO - Epoch(train) [2][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:56:52 time: 0.4759 data_time: 0.0458 memory: 6366 grad_norm: 5.2797 loss: 0.9663 loss_rpn_cls: 0.0418 loss_rpn_bbox: 0.0551 loss_cls: 0.2856 acc: 96.3379 loss_bbox: 0.2957 loss_mask: 0.2881 +2024/10/27 23:42:58 - mmengine - INFO - Epoch(train) [2][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:56:11 time: 0.4689 data_time: 0.0425 memory: 6115 grad_norm: 5.0507 loss: 0.8729 loss_rpn_cls: 0.0426 loss_rpn_bbox: 0.0481 loss_cls: 0.2556 acc: 93.3594 loss_bbox: 0.2514 loss_mask: 0.2752 +2024/10/27 23:43:22 - mmengine - INFO - Epoch(train) [2][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:55:33 time: 0.4809 data_time: 0.0455 memory: 6248 grad_norm: 5.3619 loss: 0.9603 loss_rpn_cls: 0.0401 loss_rpn_bbox: 0.0521 loss_cls: 0.3023 acc: 89.2578 loss_bbox: 0.2790 loss_mask: 0.2868 +2024/10/27 23:43:47 - mmengine - INFO - Epoch(train) [2][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:54:58 time: 0.4859 data_time: 0.0441 memory: 6420 grad_norm: 5.2682 loss: 0.8841 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0475 loss_cls: 0.2623 acc: 92.5293 loss_bbox: 0.2607 loss_mask: 0.2759 +2024/10/27 23:44:12 - mmengine - INFO - Epoch(train) [2][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:54:27 time: 0.4995 data_time: 0.0586 memory: 6329 grad_norm: 5.2524 loss: 0.9555 loss_rpn_cls: 0.0474 loss_rpn_bbox: 0.0548 loss_cls: 0.2811 acc: 83.9844 loss_bbox: 0.2741 loss_mask: 0.2981 +2024/10/27 23:44:36 - mmengine - INFO - Epoch(train) [2][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:53:53 time: 0.4871 data_time: 0.0452 memory: 6090 grad_norm: 5.0184 loss: 0.9641 loss_rpn_cls: 0.0424 loss_rpn_bbox: 0.0594 loss_cls: 0.2816 acc: 93.8965 loss_bbox: 0.2777 loss_mask: 0.3030 +2024/10/27 23:45:00 - mmengine - INFO - Epoch(train) [2][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:53:13 time: 0.4711 data_time: 0.0465 memory: 6239 grad_norm: 5.3257 loss: 0.9216 loss_rpn_cls: 0.0427 loss_rpn_bbox: 0.0554 loss_cls: 0.2669 acc: 95.1660 loss_bbox: 0.2625 loss_mask: 0.2940 +2024/10/27 23:45:23 - mmengine - INFO - Epoch(train) [2][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:52:35 time: 0.4768 data_time: 0.0463 memory: 6044 grad_norm: 4.9731 loss: 0.9583 loss_rpn_cls: 0.0415 loss_rpn_bbox: 0.0550 loss_cls: 0.2781 acc: 95.5078 loss_bbox: 0.2903 loss_mask: 0.2934 +2024/10/27 23:45:47 - mmengine - INFO - Epoch(train) [2][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:51:56 time: 0.4732 data_time: 0.0458 memory: 6295 grad_norm: 4.9404 loss: 0.9366 loss_rpn_cls: 0.0370 loss_rpn_bbox: 0.0500 loss_cls: 0.2829 acc: 83.2031 loss_bbox: 0.2768 loss_mask: 0.2899 +2024/10/27 23:46:11 - mmengine - INFO - Epoch(train) [2][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:51:19 time: 0.4798 data_time: 0.0467 memory: 6039 grad_norm: 5.1128 loss: 0.9550 loss_rpn_cls: 0.0389 loss_rpn_bbox: 0.0524 loss_cls: 0.2864 acc: 94.8242 loss_bbox: 0.2800 loss_mask: 0.2971 +2024/10/27 23:46:35 - mmengine - INFO - Epoch(train) [2][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:50:45 time: 0.4849 data_time: 0.0426 memory: 6185 grad_norm: 5.0090 loss: 0.9157 loss_rpn_cls: 0.0342 loss_rpn_bbox: 0.0497 loss_cls: 0.2704 acc: 85.1562 loss_bbox: 0.2716 loss_mask: 0.2897 +2024/10/27 23:46:45 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 23:46:59 - mmengine - INFO - Epoch(train) [2][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:50:05 time: 0.4705 data_time: 0.0526 memory: 6215 grad_norm: 4.9969 loss: 0.9785 loss_rpn_cls: 0.0521 loss_rpn_bbox: 0.0586 loss_cls: 0.2875 acc: 89.0625 loss_bbox: 0.2898 loss_mask: 0.2904 +2024/10/27 23:47:23 - mmengine - INFO - Epoch(train) [2][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:49:30 time: 0.4822 data_time: 0.0455 memory: 6103 grad_norm: 5.2238 loss: 0.9601 loss_rpn_cls: 0.0458 loss_rpn_bbox: 0.0541 loss_cls: 0.2840 acc: 87.9883 loss_bbox: 0.2835 loss_mask: 0.2928 +2024/10/27 23:47:46 - mmengine - INFO - Epoch(train) [2][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:48:49 time: 0.4645 data_time: 0.0414 memory: 6095 grad_norm: 5.2292 loss: 0.9103 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0469 loss_cls: 0.2753 acc: 92.9199 loss_bbox: 0.2675 loss_mask: 0.2829 +2024/10/27 23:48:11 - mmengine - INFO - Epoch(train) [2][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:48:15 time: 0.4890 data_time: 0.0552 memory: 6260 grad_norm: 5.0775 loss: 0.9863 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0553 loss_cls: 0.2902 acc: 88.5254 loss_bbox: 0.2969 loss_mask: 0.3049 +2024/10/27 23:48:35 - mmengine - INFO - Epoch(train) [2][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:47:42 time: 0.4890 data_time: 0.0582 memory: 6136 grad_norm: 5.1406 loss: 0.9121 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0509 loss_cls: 0.2706 acc: 85.6445 loss_bbox: 0.2689 loss_mask: 0.2806 +2024/10/27 23:48:59 - mmengine - INFO - Epoch(train) [2][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:47:07 time: 0.4816 data_time: 0.0480 memory: 6121 grad_norm: 5.4516 loss: 0.9414 loss_rpn_cls: 0.0426 loss_rpn_bbox: 0.0534 loss_cls: 0.2788 acc: 95.3613 loss_bbox: 0.2753 loss_mask: 0.2912 +2024/10/27 23:49:24 - mmengine - INFO - Epoch(train) [2][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:46:33 time: 0.4872 data_time: 0.0487 memory: 6215 grad_norm: 5.6198 loss: 0.9693 loss_rpn_cls: 0.0439 loss_rpn_bbox: 0.0567 loss_cls: 0.2935 acc: 90.8203 loss_bbox: 0.2905 loss_mask: 0.2847 +2024/10/27 23:49:47 - mmengine - INFO - Epoch(train) [2][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:45:54 time: 0.4703 data_time: 0.0458 memory: 6265 grad_norm: 5.0417 loss: 0.8853 loss_rpn_cls: 0.0407 loss_rpn_bbox: 0.0486 loss_cls: 0.2549 acc: 92.6270 loss_bbox: 0.2481 loss_mask: 0.2930 +2024/10/27 23:50:11 - mmengine - INFO - Epoch(train) [2][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:45:16 time: 0.4719 data_time: 0.0449 memory: 6215 grad_norm: 5.2309 loss: 0.9377 loss_rpn_cls: 0.0411 loss_rpn_bbox: 0.0521 loss_cls: 0.2789 acc: 90.6738 loss_bbox: 0.2715 loss_mask: 0.2941 +2024/10/27 23:50:34 - mmengine - INFO - Epoch(train) [2][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:44:39 time: 0.4748 data_time: 0.0516 memory: 5983 grad_norm: 5.2211 loss: 0.8991 loss_rpn_cls: 0.0372 loss_rpn_bbox: 0.0486 loss_cls: 0.2586 acc: 95.3613 loss_bbox: 0.2652 loss_mask: 0.2895 +2024/10/27 23:50:58 - mmengine - INFO - Epoch(train) [2][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:44:04 time: 0.4786 data_time: 0.0529 memory: 6404 grad_norm: 5.7793 loss: 0.9714 loss_rpn_cls: 0.0436 loss_rpn_bbox: 0.0539 loss_cls: 0.2928 acc: 89.7461 loss_bbox: 0.2941 loss_mask: 0.2870 +2024/10/27 23:51:22 - mmengine - INFO - Epoch(train) [2][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:43:27 time: 0.4772 data_time: 0.0445 memory: 6144 grad_norm: 5.1862 loss: 0.9131 loss_rpn_cls: 0.0368 loss_rpn_bbox: 0.0512 loss_cls: 0.2686 acc: 95.8984 loss_bbox: 0.2639 loss_mask: 0.2926 +2024/10/27 23:51:46 - mmengine - INFO - Epoch(train) [2][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:42:54 time: 0.4847 data_time: 0.0481 memory: 6164 grad_norm: 5.2778 loss: 0.9372 loss_rpn_cls: 0.0394 loss_rpn_bbox: 0.0514 loss_cls: 0.2784 acc: 90.2832 loss_bbox: 0.2773 loss_mask: 0.2907 +2024/10/27 23:52:10 - mmengine - INFO - Epoch(train) [2][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:42:19 time: 0.4814 data_time: 0.0555 memory: 6189 grad_norm: 5.0292 loss: 0.9232 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0521 loss_cls: 0.2612 acc: 92.2852 loss_bbox: 0.2775 loss_mask: 0.2915 +2024/10/27 23:52:34 - mmengine - INFO - Epoch(train) [2][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:41:43 time: 0.4767 data_time: 0.0542 memory: 6223 grad_norm: 5.2886 loss: 0.9545 loss_rpn_cls: 0.0425 loss_rpn_bbox: 0.0529 loss_cls: 0.2943 acc: 91.6992 loss_bbox: 0.2831 loss_mask: 0.2819 +2024/10/27 23:52:58 - mmengine - INFO - Epoch(train) [2][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:41:07 time: 0.4757 data_time: 0.0481 memory: 6124 grad_norm: 5.2031 loss: 0.8805 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0489 loss_cls: 0.2510 acc: 96.5332 loss_bbox: 0.2570 loss_mask: 0.2872 +2024/10/27 23:53:22 - mmengine - INFO - Epoch(train) [2][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:40:32 time: 0.4818 data_time: 0.0498 memory: 6284 grad_norm: 5.2400 loss: 0.9666 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0582 loss_cls: 0.2875 acc: 91.3086 loss_bbox: 0.2886 loss_mask: 0.2953 +2024/10/27 23:53:46 - mmengine - INFO - Epoch(train) [2][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:39:58 time: 0.4831 data_time: 0.0489 memory: 6174 grad_norm: 5.0816 loss: 0.9531 loss_rpn_cls: 0.0462 loss_rpn_bbox: 0.0587 loss_cls: 0.2728 acc: 89.8438 loss_bbox: 0.2889 loss_mask: 0.2864 +2024/10/27 23:54:10 - mmengine - INFO - Epoch(train) [2][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:39:24 time: 0.4793 data_time: 0.0543 memory: 6333 grad_norm: 5.3204 loss: 0.9770 loss_rpn_cls: 0.0475 loss_rpn_bbox: 0.0591 loss_cls: 0.2983 acc: 85.5469 loss_bbox: 0.2865 loss_mask: 0.2855 +2024/10/27 23:54:35 - mmengine - INFO - Epoch(train) [2][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:38:53 time: 0.4927 data_time: 0.0550 memory: 6036 grad_norm: 5.0378 loss: 0.9480 loss_rpn_cls: 0.0540 loss_rpn_bbox: 0.0581 loss_cls: 0.2803 acc: 91.6992 loss_bbox: 0.2617 loss_mask: 0.2939 +2024/10/27 23:54:45 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/27 23:54:59 - mmengine - INFO - Epoch(train) [2][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:38:18 time: 0.4805 data_time: 0.0481 memory: 6064 grad_norm: 5.0336 loss: 0.9010 loss_rpn_cls: 0.0445 loss_rpn_bbox: 0.0518 loss_cls: 0.2497 acc: 95.7520 loss_bbox: 0.2617 loss_mask: 0.2934 +2024/10/27 23:55:23 - mmengine - INFO - Epoch(train) [2][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:37:42 time: 0.4750 data_time: 0.0487 memory: 6297 grad_norm: 5.0635 loss: 0.9415 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0532 loss_cls: 0.2785 acc: 87.0605 loss_bbox: 0.2842 loss_mask: 0.2887 +2024/10/27 23:55:47 - mmengine - INFO - Epoch(train) [2][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:37:09 time: 0.4837 data_time: 0.0529 memory: 6256 grad_norm: 5.1008 loss: 1.0004 loss_rpn_cls: 0.0504 loss_rpn_bbox: 0.0605 loss_cls: 0.2968 acc: 93.4082 loss_bbox: 0.2913 loss_mask: 0.3014 +2024/10/27 23:56:11 - mmengine - INFO - Epoch(train) [2][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:36:38 time: 0.4915 data_time: 0.0542 memory: 6392 grad_norm: 4.8796 loss: 1.0060 loss_rpn_cls: 0.0494 loss_rpn_bbox: 0.0637 loss_cls: 0.2997 acc: 82.5684 loss_bbox: 0.3001 loss_mask: 0.2932 +2024/10/27 23:56:35 - mmengine - INFO - Epoch(train) [2][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:36:02 time: 0.4746 data_time: 0.0491 memory: 6298 grad_norm: 5.2291 loss: 0.9597 loss_rpn_cls: 0.0433 loss_rpn_bbox: 0.0621 loss_cls: 0.2734 acc: 91.8457 loss_bbox: 0.2802 loss_mask: 0.3007 +2024/10/27 23:56:59 - mmengine - INFO - Epoch(train) [2][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:35:28 time: 0.4810 data_time: 0.0520 memory: 6270 grad_norm: 4.8560 loss: 0.9683 loss_rpn_cls: 0.0435 loss_rpn_bbox: 0.0578 loss_cls: 0.2887 acc: 93.1152 loss_bbox: 0.2829 loss_mask: 0.2954 +2024/10/27 23:57:23 - mmengine - INFO - Epoch(train) [2][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:34:55 time: 0.4827 data_time: 0.0459 memory: 6184 grad_norm: 4.9548 loss: 0.8994 loss_rpn_cls: 0.0349 loss_rpn_bbox: 0.0482 loss_cls: 0.2617 acc: 91.6504 loss_bbox: 0.2745 loss_mask: 0.2802 +2024/10/27 23:57:48 - mmengine - INFO - Epoch(train) [2][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:34:22 time: 0.4843 data_time: 0.0492 memory: 6225 grad_norm: 5.1777 loss: 0.9015 loss_rpn_cls: 0.0371 loss_rpn_bbox: 0.0501 loss_cls: 0.2671 acc: 93.1152 loss_bbox: 0.2703 loss_mask: 0.2770 +2024/10/27 23:58:12 - mmengine - INFO - Epoch(train) [2][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:49 time: 0.4810 data_time: 0.0451 memory: 6374 grad_norm: 5.1998 loss: 0.9348 loss_rpn_cls: 0.0396 loss_rpn_bbox: 0.0496 loss_cls: 0.2660 acc: 91.1621 loss_bbox: 0.2847 loss_mask: 0.2950 +2024/10/27 23:58:36 - mmengine - INFO - Epoch(train) [2][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:17 time: 0.4893 data_time: 0.0547 memory: 6219 grad_norm: 5.3419 loss: 0.9493 loss_rpn_cls: 0.0397 loss_rpn_bbox: 0.0539 loss_cls: 0.2748 acc: 92.3340 loss_bbox: 0.2843 loss_mask: 0.2966 +2024/10/27 23:59:00 - mmengine - INFO - Epoch(train) [2][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:32:45 time: 0.4869 data_time: 0.0551 memory: 6087 grad_norm: 5.0848 loss: 0.8775 loss_rpn_cls: 0.0370 loss_rpn_bbox: 0.0499 loss_cls: 0.2482 acc: 88.6719 loss_bbox: 0.2559 loss_mask: 0.2865 +2024/10/27 23:59:25 - mmengine - INFO - Epoch(train) [2][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:32:14 time: 0.4870 data_time: 0.0461 memory: 6217 grad_norm: 5.0769 loss: 0.9284 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0515 loss_cls: 0.2750 acc: 84.9609 loss_bbox: 0.2793 loss_mask: 0.2818 +2024/10/27 23:59:48 - mmengine - INFO - Epoch(train) [2][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:31:38 time: 0.4719 data_time: 0.0459 memory: 6193 grad_norm: 4.8368 loss: 0.8919 loss_rpn_cls: 0.0383 loss_rpn_bbox: 0.0523 loss_cls: 0.2581 acc: 95.3125 loss_bbox: 0.2673 loss_mask: 0.2759 +2024/10/28 00:00:12 - mmengine - INFO - Epoch(train) [2][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:31:04 time: 0.4806 data_time: 0.0492 memory: 6191 grad_norm: 5.1999 loss: 0.9464 loss_rpn_cls: 0.0474 loss_rpn_bbox: 0.0560 loss_cls: 0.2707 acc: 88.8672 loss_bbox: 0.2767 loss_mask: 0.2955 +2024/10/28 00:00:37 - mmengine - INFO - Epoch(train) [2][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:30:31 time: 0.4827 data_time: 0.0472 memory: 6325 grad_norm: 5.0798 loss: 0.9408 loss_rpn_cls: 0.0420 loss_rpn_bbox: 0.0536 loss_cls: 0.2865 acc: 93.9941 loss_bbox: 0.2818 loss_mask: 0.2769 +2024/10/28 00:01:01 - mmengine - INFO - Epoch(train) [2][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:59 time: 0.4848 data_time: 0.0444 memory: 6197 grad_norm: 5.4347 loss: 0.9013 loss_rpn_cls: 0.0440 loss_rpn_bbox: 0.0490 loss_cls: 0.2610 acc: 93.0176 loss_bbox: 0.2669 loss_mask: 0.2803 +2024/10/28 00:01:25 - mmengine - INFO - Epoch(train) [2][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:26 time: 0.4812 data_time: 0.0473 memory: 6058 grad_norm: 4.9646 loss: 0.9203 loss_rpn_cls: 0.0449 loss_rpn_bbox: 0.0539 loss_cls: 0.2756 acc: 89.5996 loss_bbox: 0.2550 loss_mask: 0.2909 +2024/10/28 00:01:49 - mmengine - INFO - Epoch(train) [2][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:28:56 time: 0.4915 data_time: 0.0540 memory: 6087 grad_norm: 5.3334 loss: 0.9262 loss_rpn_cls: 0.0400 loss_rpn_bbox: 0.0502 loss_cls: 0.2775 acc: 95.3125 loss_bbox: 0.2701 loss_mask: 0.2884 +2024/10/28 00:02:14 - mmengine - INFO - Epoch(train) [2][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:28:25 time: 0.4906 data_time: 0.0499 memory: 6076 grad_norm: 5.2423 loss: 0.9628 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0531 loss_cls: 0.2897 acc: 89.2090 loss_bbox: 0.2848 loss_mask: 0.2982 +2024/10/28 00:02:39 - mmengine - INFO - Epoch(train) [2][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:57 time: 0.4975 data_time: 0.0555 memory: 6268 grad_norm: 4.9692 loss: 0.9398 loss_rpn_cls: 0.0429 loss_rpn_bbox: 0.0557 loss_cls: 0.2777 acc: 88.7207 loss_bbox: 0.2774 loss_mask: 0.2862 +2024/10/28 00:02:49 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 00:03:03 - mmengine - INFO - Epoch(train) [2][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:26 time: 0.4882 data_time: 0.0545 memory: 6126 grad_norm: 5.0145 loss: 1.0370 loss_rpn_cls: 0.0530 loss_rpn_bbox: 0.0659 loss_cls: 0.3011 acc: 86.2305 loss_bbox: 0.3061 loss_mask: 0.3110 +2024/10/28 00:03:30 - mmengine - INFO - Epoch(train) [2][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:05 time: 0.5260 data_time: 0.0892 memory: 6215 grad_norm: 5.0107 loss: 0.8622 loss_rpn_cls: 0.0375 loss_rpn_bbox: 0.0476 loss_cls: 0.2461 acc: 89.2578 loss_bbox: 0.2560 loss_mask: 0.2749 +2024/10/28 00:03:55 - mmengine - INFO - Epoch(train) [2][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:26:38 time: 0.5029 data_time: 0.0565 memory: 6201 grad_norm: 5.4338 loss: 0.9619 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0524 loss_cls: 0.2902 acc: 90.9668 loss_bbox: 0.2888 loss_mask: 0.2896 +2024/10/28 00:04:19 - mmengine - INFO - Epoch(train) [2][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:26:07 time: 0.4903 data_time: 0.0518 memory: 6203 grad_norm: 5.2238 loss: 0.9564 loss_rpn_cls: 0.0441 loss_rpn_bbox: 0.0514 loss_cls: 0.2861 acc: 97.5586 loss_bbox: 0.2879 loss_mask: 0.2869 +2024/10/28 00:04:43 - mmengine - INFO - Epoch(train) [2][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:25:35 time: 0.4813 data_time: 0.0485 memory: 6172 grad_norm: 4.8433 loss: 0.9187 loss_rpn_cls: 0.0368 loss_rpn_bbox: 0.0538 loss_cls: 0.2793 acc: 91.2109 loss_bbox: 0.2717 loss_mask: 0.2771 +2024/10/28 00:05:08 - mmengine - INFO - Epoch(train) [2][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:25:03 time: 0.4868 data_time: 0.0509 memory: 6282 grad_norm: 5.0353 loss: 0.9390 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0542 loss_cls: 0.2765 acc: 85.2539 loss_bbox: 0.2849 loss_mask: 0.2867 +2024/10/28 00:05:32 - mmengine - INFO - Epoch(train) [2][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:24:31 time: 0.4838 data_time: 0.0513 memory: 6346 grad_norm: 5.2764 loss: 0.9596 loss_rpn_cls: 0.0418 loss_rpn_bbox: 0.0539 loss_cls: 0.2856 acc: 90.5273 loss_bbox: 0.2900 loss_mask: 0.2882 +2024/10/28 00:05:56 - mmengine - INFO - Epoch(train) [2][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:23:59 time: 0.4830 data_time: 0.0487 memory: 6130 grad_norm: 4.8961 loss: 0.9067 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0522 loss_cls: 0.2695 acc: 93.2129 loss_bbox: 0.2626 loss_mask: 0.2844 +2024/10/28 00:06:20 - mmengine - INFO - Epoch(train) [2][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:23:29 time: 0.4892 data_time: 0.0408 memory: 6054 grad_norm: 5.0495 loss: 0.8673 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0452 loss_cls: 0.2518 acc: 94.0918 loss_bbox: 0.2578 loss_mask: 0.2820 +2024/10/28 00:06:44 - mmengine - INFO - Epoch(train) [2][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:22:56 time: 0.4783 data_time: 0.0474 memory: 6212 grad_norm: 5.0834 loss: 0.9697 loss_rpn_cls: 0.0401 loss_rpn_bbox: 0.0515 loss_cls: 0.2907 acc: 92.1387 loss_bbox: 0.2867 loss_mask: 0.3007 +2024/10/28 00:07:09 - mmengine - INFO - Epoch(train) [2][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:22:26 time: 0.4899 data_time: 0.0489 memory: 6196 grad_norm: 5.0563 loss: 0.9713 loss_rpn_cls: 0.0416 loss_rpn_bbox: 0.0567 loss_cls: 0.2895 acc: 91.8457 loss_bbox: 0.2883 loss_mask: 0.2952 +2024/10/28 00:07:33 - mmengine - INFO - Epoch(train) [2][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:21:53 time: 0.4793 data_time: 0.0464 memory: 6369 grad_norm: 4.9477 loss: 0.8992 loss_rpn_cls: 0.0419 loss_rpn_bbox: 0.0512 loss_cls: 0.2699 acc: 89.6484 loss_bbox: 0.2623 loss_mask: 0.2739 +2024/10/28 00:07:57 - mmengine - INFO - Epoch(train) [2][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:21:23 time: 0.4912 data_time: 0.0439 memory: 6264 grad_norm: 5.0406 loss: 0.9064 loss_rpn_cls: 0.0413 loss_rpn_bbox: 0.0510 loss_cls: 0.2757 acc: 87.0605 loss_bbox: 0.2588 loss_mask: 0.2795 +2024/10/28 00:08:12 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 00:08:12 - mmengine - INFO - Saving checkpoint at 2 epochs +2024/10/28 00:08:23 - mmengine - INFO - Epoch(val) [2][ 50/1250] eta: 0:02:23 time: 0.1194 data_time: 0.0068 memory: 6419 +2024/10/28 00:08:29 - mmengine - INFO - Epoch(val) [2][ 100/1250] eta: 0:02:15 time: 0.1160 data_time: 0.0046 memory: 1114 +2024/10/28 00:08:34 - mmengine - INFO - Epoch(val) [2][ 150/1250] eta: 0:02:07 time: 0.1129 data_time: 0.0039 memory: 1114 +2024/10/28 00:08:40 - mmengine - INFO - Epoch(val) [2][ 200/1250] eta: 0:02:02 time: 0.1195 data_time: 0.0047 memory: 1114 +2024/10/28 00:08:46 - mmengine - INFO - Epoch(val) [2][ 250/1250] eta: 0:01:56 time: 0.1128 data_time: 0.0039 memory: 1221 +2024/10/28 00:08:52 - mmengine - INFO - Epoch(val) [2][ 300/1250] eta: 0:01:50 time: 0.1161 data_time: 0.0046 memory: 1114 +2024/10/28 00:08:57 - mmengine - INFO - Epoch(val) [2][ 350/1250] eta: 0:01:44 time: 0.1135 data_time: 0.0035 memory: 1117 +2024/10/28 00:09:03 - mmengine - INFO - Epoch(val) [2][ 400/1250] eta: 0:01:38 time: 0.1130 data_time: 0.0038 memory: 1114 +2024/10/28 00:09:09 - mmengine - INFO - Epoch(val) [2][ 450/1250] eta: 0:01:32 time: 0.1124 data_time: 0.0037 memory: 1114 +2024/10/28 00:09:14 - mmengine - INFO - Epoch(val) [2][ 500/1250] eta: 0:01:26 time: 0.1130 data_time: 0.0041 memory: 1134 +2024/10/28 00:09:20 - mmengine - INFO - Epoch(val) [2][ 550/1250] eta: 0:01:20 time: 0.1102 data_time: 0.0034 memory: 1176 +2024/10/28 00:09:26 - mmengine - INFO - Epoch(val) [2][ 600/1250] eta: 0:01:14 time: 0.1162 data_time: 0.0046 memory: 1114 +2024/10/28 00:09:31 - mmengine - INFO - Epoch(val) [2][ 650/1250] eta: 0:01:08 time: 0.1120 data_time: 0.0039 memory: 1219 +2024/10/28 00:09:37 - mmengine - INFO - Epoch(val) [2][ 700/1250] eta: 0:01:02 time: 0.1152 data_time: 0.0042 memory: 1093 +2024/10/28 00:09:43 - mmengine - INFO - Epoch(val) [2][ 750/1250] eta: 0:00:57 time: 0.1202 data_time: 0.0050 memory: 1116 +2024/10/28 00:09:49 - mmengine - INFO - Epoch(val) [2][ 800/1250] eta: 0:00:51 time: 0.1144 data_time: 0.0051 memory: 1122 +2024/10/28 00:09:55 - mmengine - INFO - Epoch(val) [2][ 850/1250] eta: 0:00:45 time: 0.1171 data_time: 0.0056 memory: 1192 +2024/10/28 00:10:00 - mmengine - INFO - Epoch(val) [2][ 900/1250] eta: 0:00:40 time: 0.1177 data_time: 0.0067 memory: 1114 +2024/10/28 00:10:07 - mmengine - INFO - Epoch(val) [2][ 950/1250] eta: 0:00:34 time: 0.1208 data_time: 0.0076 memory: 1219 +2024/10/28 00:10:12 - mmengine - INFO - Epoch(val) [2][1000/1250] eta: 0:00:28 time: 0.1119 data_time: 0.0052 memory: 1081 +2024/10/28 00:10:18 - mmengine - INFO - Epoch(val) [2][1050/1250] eta: 0:00:23 time: 0.1218 data_time: 0.0066 memory: 1114 +2024/10/28 00:10:24 - mmengine - INFO - Epoch(val) [2][1100/1250] eta: 0:00:17 time: 0.1159 data_time: 0.0048 memory: 1116 +2024/10/28 00:10:30 - mmengine - INFO - Epoch(val) [2][1150/1250] eta: 0:00:11 time: 0.1199 data_time: 0.0061 memory: 1114 +2024/10/28 00:10:36 - mmengine - INFO - Epoch(val) [2][1200/1250] eta: 0:00:05 time: 0.1152 data_time: 0.0047 memory: 1176 +2024/10/28 00:10:41 - mmengine - INFO - Epoch(val) [2][1250/1250] eta: 0:00:00 time: 0.1122 data_time: 0.0048 memory: 1114 +2024/10/28 00:10:55 - mmengine - INFO - Evaluating bbox... +2024/10/28 00:11:33 - mmengine - INFO - bbox_mAP_copypaste: 0.266 0.460 0.281 0.129 0.293 0.367 +2024/10/28 00:11:33 - mmengine - INFO - Evaluating segm... +2024/10/28 00:12:14 - mmengine - INFO - segm_mAP_copypaste: 0.261 0.436 0.273 0.092 0.284 0.409 +2024/10/28 00:12:15 - mmengine - INFO - Epoch(val) [2][1250/1250] coco/bbox_mAP: 0.2660 coco/bbox_mAP_50: 0.4600 coco/bbox_mAP_75: 0.2810 coco/bbox_mAP_s: 0.1290 coco/bbox_mAP_m: 0.2930 coco/bbox_mAP_l: 0.3670 coco/segm_mAP: 0.2610 coco/segm_mAP_50: 0.4360 coco/segm_mAP_75: 0.2730 coco/segm_mAP_s: 0.0920 coco/segm_mAP_m: 0.2840 coco/segm_mAP_l: 0.4090 data_time: 0.0049 time: 0.1156 +2024/10/28 00:13:05 - mmengine - INFO - Epoch(train) [3][ 50/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:22:42 time: 0.9935 data_time: 0.0494 memory: 6341 grad_norm: 5.0204 loss: 0.9610 loss_rpn_cls: 0.0472 loss_rpn_bbox: 0.0585 loss_cls: 0.2801 acc: 95.3613 loss_bbox: 0.2940 loss_mask: 0.2812 +2024/10/28 00:13:57 - mmengine - INFO - Epoch(train) [3][ 100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:24:30 time: 1.0515 data_time: 0.0770 memory: 6148 grad_norm: 4.9307 loss: 0.9342 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0524 loss_cls: 0.2776 acc: 88.4277 loss_bbox: 0.2908 loss_mask: 0.2770 +2024/10/28 00:14:43 - mmengine - INFO - Epoch(train) [3][ 150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:25:44 time: 0.9131 data_time: 0.0476 memory: 6154 grad_norm: 5.3678 loss: 0.9576 loss_rpn_cls: 0.0411 loss_rpn_bbox: 0.0533 loss_cls: 0.2786 acc: 91.7969 loss_bbox: 0.2882 loss_mask: 0.2964 +2024/10/28 00:15:32 - mmengine - INFO - Epoch(train) [3][ 200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:13 time: 0.9816 data_time: 0.0377 memory: 6156 grad_norm: 4.9387 loss: 0.8450 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0456 loss_cls: 0.2275 acc: 94.4336 loss_bbox: 0.2550 loss_mask: 0.2852 +2024/10/28 00:16:19 - mmengine - INFO - Epoch(train) [3][ 250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:28:33 time: 0.9444 data_time: 0.0436 memory: 6179 grad_norm: 5.1372 loss: 0.8963 loss_rpn_cls: 0.0436 loss_rpn_bbox: 0.0503 loss_cls: 0.2673 acc: 93.7500 loss_bbox: 0.2624 loss_mask: 0.2727 +2024/10/28 00:17:08 - mmengine - INFO - Epoch(train) [3][ 300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:57 time: 0.9684 data_time: 0.0424 memory: 6303 grad_norm: 4.8283 loss: 0.8942 loss_rpn_cls: 0.0417 loss_rpn_bbox: 0.0525 loss_cls: 0.2674 acc: 92.2852 loss_bbox: 0.2575 loss_mask: 0.2751 +2024/10/28 00:17:48 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 00:17:58 - mmengine - INFO - Epoch(train) [3][ 350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:31:28 time: 0.9974 data_time: 0.0414 memory: 6313 grad_norm: 4.8405 loss: 0.8541 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0486 loss_cls: 0.2466 acc: 87.1582 loss_bbox: 0.2516 loss_mask: 0.2706 +2024/10/28 00:18:52 - mmengine - INFO - Epoch(train) [3][ 400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:18 time: 1.0815 data_time: 0.0551 memory: 6236 grad_norm: 4.9116 loss: 0.9941 loss_rpn_cls: 0.0388 loss_rpn_bbox: 0.0586 loss_cls: 0.2964 acc: 95.1172 loss_bbox: 0.3117 loss_mask: 0.2886 +2024/10/28 00:19:42 - mmengine - INFO - Epoch(train) [3][ 450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:34:50 time: 1.0120 data_time: 0.0502 memory: 6209 grad_norm: 5.3702 loss: 0.9151 loss_rpn_cls: 0.0379 loss_rpn_bbox: 0.0537 loss_cls: 0.2587 acc: 91.4551 loss_bbox: 0.2737 loss_mask: 0.2911 +2024/10/28 00:20:29 - mmengine - INFO - Epoch(train) [3][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:36:03 time: 0.9337 data_time: 0.0497 memory: 6093 grad_norm: 5.0066 loss: 0.9674 loss_rpn_cls: 0.0383 loss_rpn_bbox: 0.0575 loss_cls: 0.2910 acc: 87.4512 loss_bbox: 0.2888 loss_mask: 0.2918 +2024/10/28 00:21:20 - mmengine - INFO - Epoch(train) [3][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:37:35 time: 1.0195 data_time: 0.0545 memory: 6133 grad_norm: 5.1534 loss: 0.9109 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0510 loss_cls: 0.2686 acc: 91.1621 loss_bbox: 0.2737 loss_mask: 0.2786 +2024/10/28 00:22:07 - mmengine - INFO - Epoch(train) [3][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:38:50 time: 0.9518 data_time: 0.0510 memory: 6160 grad_norm: 5.0596 loss: 0.8672 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0495 loss_cls: 0.2510 acc: 91.6504 loss_bbox: 0.2559 loss_mask: 0.2719 +2024/10/28 00:22:59 - mmengine - INFO - Epoch(train) [3][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:40:24 time: 1.0336 data_time: 0.0446 memory: 6086 grad_norm: 4.9123 loss: 0.8770 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0496 loss_cls: 0.2514 acc: 91.7480 loss_bbox: 0.2645 loss_mask: 0.2735 +2024/10/28 00:23:47 - mmengine - INFO - Epoch(train) [3][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:41:39 time: 0.9567 data_time: 0.0475 memory: 6303 grad_norm: 5.1090 loss: 0.9116 loss_rpn_cls: 0.0459 loss_rpn_bbox: 0.0504 loss_cls: 0.2654 acc: 86.8652 loss_bbox: 0.2715 loss_mask: 0.2784 +2024/10/28 00:24:35 - mmengine - INFO - Epoch(train) [3][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:42:56 time: 0.9691 data_time: 0.0485 memory: 6256 grad_norm: 4.7711 loss: 0.8777 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0502 loss_cls: 0.2557 acc: 86.5723 loss_bbox: 0.2601 loss_mask: 0.2801 +2024/10/28 00:25:26 - mmengine - INFO - Epoch(train) [3][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:44:22 time: 1.0150 data_time: 0.0484 memory: 6103 grad_norm: 5.2303 loss: 0.9355 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0548 loss_cls: 0.2779 acc: 91.0645 loss_bbox: 0.2804 loss_mask: 0.2870 +2024/10/28 00:26:15 - mmengine - INFO - Epoch(train) [3][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:45:39 time: 0.9741 data_time: 0.0478 memory: 6194 grad_norm: 4.9537 loss: 0.9270 loss_rpn_cls: 0.0414 loss_rpn_bbox: 0.0507 loss_cls: 0.2738 acc: 84.3750 loss_bbox: 0.2741 loss_mask: 0.2869 +2024/10/28 00:27:07 - mmengine - INFO - Epoch(train) [3][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:47:10 time: 1.0402 data_time: 0.0496 memory: 6200 grad_norm: 4.9635 loss: 0.9650 loss_rpn_cls: 0.0444 loss_rpn_bbox: 0.0560 loss_cls: 0.2873 acc: 87.2559 loss_bbox: 0.2903 loss_mask: 0.2869 +2024/10/28 00:28:00 - mmengine - INFO - Epoch(train) [3][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:48:44 time: 1.0593 data_time: 0.0533 memory: 6077 grad_norm: 4.9373 loss: 0.9283 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0531 loss_cls: 0.2601 acc: 91.6992 loss_bbox: 0.2859 loss_mask: 0.2915 +2024/10/28 00:28:48 - mmengine - INFO - Epoch(train) [3][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:49:57 time: 0.9723 data_time: 0.0480 memory: 6197 grad_norm: 4.8852 loss: 0.9133 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0549 loss_cls: 0.2596 acc: 91.9922 loss_bbox: 0.2715 loss_mask: 0.2870 +2024/10/28 00:29:37 - mmengine - INFO - Epoch(train) [3][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:51:11 time: 0.9790 data_time: 0.0534 memory: 6160 grad_norm: 4.8784 loss: 0.9144 loss_rpn_cls: 0.0406 loss_rpn_bbox: 0.0558 loss_cls: 0.2661 acc: 91.1621 loss_bbox: 0.2666 loss_mask: 0.2854 +2024/10/28 00:30:31 - mmengine - INFO - Epoch(train) [3][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:52:44 time: 1.0630 data_time: 0.0551 memory: 6230 grad_norm: 5.0311 loss: 0.9460 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0553 loss_cls: 0.2779 acc: 91.3574 loss_bbox: 0.2825 loss_mask: 0.2899 +2024/10/28 00:31:18 - mmengine - INFO - Epoch(train) [3][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:53:47 time: 0.9382 data_time: 0.0467 memory: 6205 grad_norm: 4.7497 loss: 0.9012 loss_rpn_cls: 0.0337 loss_rpn_bbox: 0.0494 loss_cls: 0.2725 acc: 92.1387 loss_bbox: 0.2636 loss_mask: 0.2820 +2024/10/28 00:32:07 - mmengine - INFO - Epoch(train) [3][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:55:03 time: 0.9965 data_time: 0.0482 memory: 6102 grad_norm: 4.7646 loss: 0.9321 loss_rpn_cls: 0.0370 loss_rpn_bbox: 0.0539 loss_cls: 0.2772 acc: 91.9434 loss_bbox: 0.2819 loss_mask: 0.2820 +2024/10/28 00:32:57 - mmengine - INFO - Epoch(train) [3][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:56:18 time: 0.9975 data_time: 0.0528 memory: 6220 grad_norm: 5.2011 loss: 0.8655 loss_rpn_cls: 0.0374 loss_rpn_bbox: 0.0510 loss_cls: 0.2408 acc: 86.7676 loss_bbox: 0.2523 loss_mask: 0.2841 +2024/10/28 00:33:46 - mmengine - INFO - Epoch(train) [3][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:57:29 time: 0.9807 data_time: 0.0544 memory: 6315 grad_norm: 4.8910 loss: 0.9122 loss_rpn_cls: 0.0384 loss_rpn_bbox: 0.0554 loss_cls: 0.2606 acc: 83.2520 loss_bbox: 0.2715 loss_mask: 0.2863 +2024/10/28 00:34:29 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 00:34:38 - mmengine - INFO - Epoch(train) [3][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:58:52 time: 1.0403 data_time: 0.0469 memory: 6235 grad_norm: 5.2044 loss: 0.8749 loss_rpn_cls: 0.0397 loss_rpn_bbox: 0.0568 loss_cls: 0.2609 acc: 90.1367 loss_bbox: 0.2544 loss_mask: 0.2631 +2024/10/28 00:35:28 - mmengine - INFO - Epoch(train) [3][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:00:03 time: 0.9884 data_time: 0.0484 memory: 6272 grad_norm: 4.9009 loss: 0.9173 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0520 loss_cls: 0.2627 acc: 89.7461 loss_bbox: 0.2704 loss_mask: 0.2949 +2024/10/28 00:36:17 - mmengine - INFO - Epoch(train) [3][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:01:14 time: 0.9948 data_time: 0.0459 memory: 6138 grad_norm: 5.0525 loss: 0.8454 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0435 loss_cls: 0.2429 acc: 88.2324 loss_bbox: 0.2559 loss_mask: 0.2738 +2024/10/28 00:37:07 - mmengine - INFO - Epoch(train) [3][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:02:22 time: 0.9819 data_time: 0.0509 memory: 6091 grad_norm: 5.2456 loss: 0.9123 loss_rpn_cls: 0.0396 loss_rpn_bbox: 0.0506 loss_cls: 0.2694 acc: 90.3809 loss_bbox: 0.2656 loss_mask: 0.2872 +2024/10/28 00:37:57 - mmengine - INFO - Epoch(train) [3][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:03:36 time: 1.0134 data_time: 0.0530 memory: 6175 grad_norm: 5.2887 loss: 0.8834 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0526 loss_cls: 0.2548 acc: 93.3594 loss_bbox: 0.2632 loss_mask: 0.2785 +2024/10/28 00:38:49 - mmengine - INFO - Epoch(train) [3][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:04:55 time: 1.0380 data_time: 0.0511 memory: 6203 grad_norm: 4.9065 loss: 0.9182 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0576 loss_cls: 0.2650 acc: 91.5527 loss_bbox: 0.2830 loss_mask: 0.2763 +2024/10/28 00:39:38 - mmengine - INFO - Epoch(train) [3][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:06:00 time: 0.9811 data_time: 0.0462 memory: 6287 grad_norm: 4.9910 loss: 0.9066 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0504 loss_cls: 0.2650 acc: 90.1855 loss_bbox: 0.2776 loss_mask: 0.2802 +2024/10/28 00:40:25 - mmengine - INFO - Epoch(train) [3][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:06:55 time: 0.9339 data_time: 0.0528 memory: 6213 grad_norm: 4.8771 loss: 0.9440 loss_rpn_cls: 0.0421 loss_rpn_bbox: 0.0534 loss_cls: 0.2828 acc: 94.0430 loss_bbox: 0.2799 loss_mask: 0.2858 +2024/10/28 00:41:13 - mmengine - INFO - Epoch(train) [3][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:07:54 time: 0.9582 data_time: 0.0517 memory: 6217 grad_norm: 5.0086 loss: 0.8992 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0505 loss_cls: 0.2729 acc: 94.3359 loss_bbox: 0.2699 loss_mask: 0.2696 +2024/10/28 00:42:01 - mmengine - INFO - Epoch(train) [3][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:08:53 time: 0.9595 data_time: 0.0470 memory: 6157 grad_norm: 5.0287 loss: 0.8936 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0476 loss_cls: 0.2574 acc: 88.7207 loss_bbox: 0.2678 loss_mask: 0.2824 +2024/10/28 00:42:56 - mmengine - INFO - Epoch(train) [3][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:10:21 time: 1.1001 data_time: 0.0591 memory: 6233 grad_norm: 5.0771 loss: 0.9322 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0572 loss_cls: 0.2715 acc: 95.5566 loss_bbox: 0.2771 loss_mask: 0.2886 +2024/10/28 00:43:46 - mmengine - INFO - Epoch(train) [3][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:11:28 time: 1.0023 data_time: 0.0580 memory: 6392 grad_norm: 4.9641 loss: 1.0092 loss_rpn_cls: 0.0456 loss_rpn_bbox: 0.0601 loss_cls: 0.3037 acc: 92.0410 loss_bbox: 0.3093 loss_mask: 0.2906 +2024/10/28 00:44:36 - mmengine - INFO - Epoch(train) [3][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:12:32 time: 0.9954 data_time: 0.0548 memory: 6185 grad_norm: 5.2642 loss: 0.9241 loss_rpn_cls: 0.0400 loss_rpn_bbox: 0.0480 loss_cls: 0.2686 acc: 94.6777 loss_bbox: 0.2784 loss_mask: 0.2891 +2024/10/28 00:45:28 - mmengine - INFO - Epoch(train) [3][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:13:46 time: 1.0445 data_time: 0.0540 memory: 6421 grad_norm: 4.9545 loss: 0.9414 loss_rpn_cls: 0.0451 loss_rpn_bbox: 0.0574 loss_cls: 0.2845 acc: 86.7188 loss_bbox: 0.2755 loss_mask: 0.2789 +2024/10/28 00:46:18 - mmengine - INFO - Epoch(train) [3][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:14:50 time: 0.9977 data_time: 0.0556 memory: 6232 grad_norm: 5.1273 loss: 0.9058 loss_rpn_cls: 0.0392 loss_rpn_bbox: 0.0580 loss_cls: 0.2635 acc: 92.7246 loss_bbox: 0.2728 loss_mask: 0.2723 +2024/10/28 00:47:07 - mmengine - INFO - Epoch(train) [3][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:15:52 time: 0.9934 data_time: 0.0464 memory: 5969 grad_norm: 4.8023 loss: 0.8690 loss_rpn_cls: 0.0404 loss_rpn_bbox: 0.0492 loss_cls: 0.2506 acc: 93.7988 loss_bbox: 0.2474 loss_mask: 0.2813 +2024/10/28 00:47:59 - mmengine - INFO - Epoch(train) [3][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:17:00 time: 1.0249 data_time: 0.0505 memory: 6087 grad_norm: 4.9761 loss: 0.9238 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0528 loss_cls: 0.2747 acc: 90.6250 loss_bbox: 0.2725 loss_mask: 0.2848 +2024/10/28 00:48:52 - mmengine - INFO - Epoch(train) [3][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:18:14 time: 1.0570 data_time: 0.0503 memory: 6223 grad_norm: 4.8395 loss: 0.9112 loss_rpn_cls: 0.0400 loss_rpn_bbox: 0.0552 loss_cls: 0.2630 acc: 90.7227 loss_bbox: 0.2733 loss_mask: 0.2799 +2024/10/28 00:49:40 - mmengine - INFO - Epoch(train) [3][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:19:10 time: 0.9790 data_time: 0.0628 memory: 6388 grad_norm: 5.0637 loss: 0.9719 loss_rpn_cls: 0.0403 loss_rpn_bbox: 0.0579 loss_cls: 0.2947 acc: 91.7969 loss_bbox: 0.3048 loss_mask: 0.2741 +2024/10/28 00:50:32 - mmengine - INFO - Epoch(train) [3][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:20:17 time: 1.0302 data_time: 0.0500 memory: 6419 grad_norm: 4.8274 loss: 0.9067 loss_rpn_cls: 0.0393 loss_rpn_bbox: 0.0524 loss_cls: 0.2717 acc: 92.7734 loss_bbox: 0.2614 loss_mask: 0.2820 +2024/10/28 00:51:09 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 00:51:19 - mmengine - INFO - Epoch(train) [3][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:04 time: 0.9360 data_time: 0.0514 memory: 6290 grad_norm: 4.8113 loss: 0.9524 loss_rpn_cls: 0.0434 loss_rpn_bbox: 0.0553 loss_cls: 0.2791 acc: 91.5039 loss_bbox: 0.2854 loss_mask: 0.2891 +2024/10/28 00:52:07 - mmengine - INFO - Epoch(train) [3][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:55 time: 0.9607 data_time: 0.0479 memory: 6105 grad_norm: 4.9481 loss: 0.9229 loss_rpn_cls: 0.0473 loss_rpn_bbox: 0.0535 loss_cls: 0.2673 acc: 87.3535 loss_bbox: 0.2627 loss_mask: 0.2922 +2024/10/28 00:52:56 - mmengine - INFO - Epoch(train) [3][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:22:52 time: 0.9916 data_time: 0.0478 memory: 6256 grad_norm: 4.9211 loss: 0.8728 loss_rpn_cls: 0.0397 loss_rpn_bbox: 0.0521 loss_cls: 0.2560 acc: 94.5801 loss_bbox: 0.2544 loss_mask: 0.2705 +2024/10/28 00:53:42 - mmengine - INFO - Epoch(train) [3][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:23:33 time: 0.9165 data_time: 0.0518 memory: 6312 grad_norm: 4.8505 loss: 0.9455 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0552 loss_cls: 0.2846 acc: 86.2793 loss_bbox: 0.2834 loss_mask: 0.2857 +2024/10/28 00:54:34 - mmengine - INFO - Epoch(train) [3][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:24:37 time: 1.0323 data_time: 0.0436 memory: 6311 grad_norm: 4.8750 loss: 0.8785 loss_rpn_cls: 0.0384 loss_rpn_bbox: 0.0479 loss_cls: 0.2517 acc: 90.8203 loss_bbox: 0.2630 loss_mask: 0.2775 +2024/10/28 00:55:25 - mmengine - INFO - Epoch(train) [3][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:25:39 time: 1.0234 data_time: 0.0545 memory: 6255 grad_norm: 4.7875 loss: 0.9995 loss_rpn_cls: 0.0464 loss_rpn_bbox: 0.0637 loss_cls: 0.2946 acc: 87.7441 loss_bbox: 0.3069 loss_mask: 0.2879 +2024/10/28 00:56:16 - mmengine - INFO - Epoch(train) [3][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:26:38 time: 1.0139 data_time: 0.0462 memory: 6347 grad_norm: 4.9645 loss: 0.9256 loss_rpn_cls: 0.0412 loss_rpn_bbox: 0.0529 loss_cls: 0.2743 acc: 94.2871 loss_bbox: 0.2728 loss_mask: 0.2844 +2024/10/28 00:57:08 - mmengine - INFO - Epoch(train) [3][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:27:41 time: 1.0365 data_time: 0.0525 memory: 6309 grad_norm: 5.0628 loss: 0.9400 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0542 loss_cls: 0.2699 acc: 88.0859 loss_bbox: 0.2962 loss_mask: 0.2811 +2024/10/28 00:57:56 - mmengine - INFO - Epoch(train) [3][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:28:30 time: 0.9725 data_time: 0.0489 memory: 6135 grad_norm: 4.8733 loss: 0.9101 loss_rpn_cls: 0.0350 loss_rpn_bbox: 0.0577 loss_cls: 0.2619 acc: 94.0430 loss_bbox: 0.2743 loss_mask: 0.2812 +2024/10/28 00:58:45 - mmengine - INFO - Epoch(train) [3][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:29:18 time: 0.9675 data_time: 0.0458 memory: 6300 grad_norm: 5.0510 loss: 0.9010 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0560 loss_cls: 0.2606 acc: 91.6016 loss_bbox: 0.2640 loss_mask: 0.2828 +2024/10/28 00:59:31 - mmengine - INFO - Epoch(train) [3][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:29:58 time: 0.9298 data_time: 0.0603 memory: 6219 grad_norm: 4.7927 loss: 0.9414 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0571 loss_cls: 0.2724 acc: 95.8984 loss_bbox: 0.2832 loss_mask: 0.2877 +2024/10/28 01:00:22 - mmengine - INFO - Epoch(train) [3][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:30:55 time: 1.0223 data_time: 0.0504 memory: 6043 grad_norm: 4.7109 loss: 0.8604 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0460 loss_cls: 0.2444 acc: 96.3867 loss_bbox: 0.2556 loss_mask: 0.2764 +2024/10/28 01:01:09 - mmengine - INFO - Epoch(train) [3][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:31:34 time: 0.9306 data_time: 0.0535 memory: 6241 grad_norm: 4.8892 loss: 0.9091 loss_rpn_cls: 0.0381 loss_rpn_bbox: 0.0512 loss_cls: 0.2676 acc: 86.9141 loss_bbox: 0.2746 loss_mask: 0.2776 +2024/10/28 01:01:55 - mmengine - INFO - Epoch(train) [3][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:32:11 time: 0.9253 data_time: 0.0457 memory: 6107 grad_norm: 4.9800 loss: 0.8454 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0451 loss_cls: 0.2435 acc: 93.2617 loss_bbox: 0.2503 loss_mask: 0.2722 +2024/10/28 01:02:45 - mmengine - INFO - Epoch(train) [3][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:33:04 time: 1.0041 data_time: 0.0570 memory: 6090 grad_norm: 4.8663 loss: 0.9134 loss_rpn_cls: 0.0393 loss_rpn_bbox: 0.0527 loss_cls: 0.2684 acc: 93.2129 loss_bbox: 0.2722 loss_mask: 0.2807 +2024/10/28 01:03:34 - mmengine - INFO - Epoch(train) [3][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:33:51 time: 0.9779 data_time: 0.0484 memory: 6347 grad_norm: 4.8667 loss: 0.9161 loss_rpn_cls: 0.0413 loss_rpn_bbox: 0.0507 loss_cls: 0.2628 acc: 93.8965 loss_bbox: 0.2740 loss_mask: 0.2873 +2024/10/28 01:04:19 - mmengine - INFO - Epoch(train) [3][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:34:20 time: 0.8916 data_time: 0.0471 memory: 6003 grad_norm: 4.8362 loss: 0.8834 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0496 loss_cls: 0.2558 acc: 92.1875 loss_bbox: 0.2579 loss_mask: 0.2834 +2024/10/28 01:05:08 - mmengine - INFO - Epoch(train) [3][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:35:07 time: 0.9849 data_time: 0.0546 memory: 6335 grad_norm: 4.9334 loss: 0.9369 loss_rpn_cls: 0.0403 loss_rpn_bbox: 0.0538 loss_cls: 0.2709 acc: 95.8008 loss_bbox: 0.2890 loss_mask: 0.2830 +2024/10/28 01:05:57 - mmengine - INFO - Epoch(train) [3][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:35:51 time: 0.9736 data_time: 0.0552 memory: 6290 grad_norm: 4.9957 loss: 0.9316 loss_rpn_cls: 0.0417 loss_rpn_bbox: 0.0538 loss_cls: 0.2728 acc: 96.5332 loss_bbox: 0.2843 loss_mask: 0.2790 +2024/10/28 01:06:50 - mmengine - INFO - Epoch(train) [3][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:36:53 time: 1.0667 data_time: 0.0528 memory: 6419 grad_norm: 4.5335 loss: 0.8924 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0508 loss_cls: 0.2586 acc: 90.0391 loss_bbox: 0.2699 loss_mask: 0.2790 +2024/10/28 01:07:28 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 01:07:39 - mmengine - INFO - Epoch(train) [3][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:37:37 time: 0.9773 data_time: 0.0608 memory: 6123 grad_norm: 4.8433 loss: 0.9053 loss_rpn_cls: 0.0421 loss_rpn_bbox: 0.0516 loss_cls: 0.2638 acc: 90.5762 loss_bbox: 0.2633 loss_mask: 0.2845 +2024/10/28 01:08:29 - mmengine - INFO - Epoch(train) [3][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:38:27 time: 1.0107 data_time: 0.0537 memory: 6419 grad_norm: 4.9877 loss: 0.9140 loss_rpn_cls: 0.0440 loss_rpn_bbox: 0.0535 loss_cls: 0.2712 acc: 93.8477 loss_bbox: 0.2716 loss_mask: 0.2737 +2024/10/28 01:09:19 - mmengine - INFO - Epoch(train) [3][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:39:13 time: 0.9961 data_time: 0.0518 memory: 6101 grad_norm: 4.8049 loss: 0.9202 loss_rpn_cls: 0.0443 loss_rpn_bbox: 0.0545 loss_cls: 0.2708 acc: 94.0918 loss_bbox: 0.2693 loss_mask: 0.2813 +2024/10/28 01:10:09 - mmengine - INFO - Epoch(train) [3][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:39:58 time: 0.9908 data_time: 0.0515 memory: 6146 grad_norm: 4.9674 loss: 0.9273 loss_rpn_cls: 0.0418 loss_rpn_bbox: 0.0506 loss_cls: 0.2789 acc: 84.6191 loss_bbox: 0.2775 loss_mask: 0.2785 +2024/10/28 01:10:57 - mmengine - INFO - Epoch(train) [3][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:40:40 time: 0.9756 data_time: 0.0511 memory: 6248 grad_norm: 4.7045 loss: 0.8894 loss_rpn_cls: 0.0388 loss_rpn_bbox: 0.0554 loss_cls: 0.2553 acc: 94.0430 loss_bbox: 0.2623 loss_mask: 0.2775 +2024/10/28 01:11:49 - mmengine - INFO - Epoch(train) [3][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:41:32 time: 1.0332 data_time: 0.0597 memory: 6246 grad_norm: 4.7151 loss: 0.8904 loss_rpn_cls: 0.0422 loss_rpn_bbox: 0.0515 loss_cls: 0.2652 acc: 88.0859 loss_bbox: 0.2597 loss_mask: 0.2718 +2024/10/28 01:12:41 - mmengine - INFO - Epoch(train) [3][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:42:24 time: 1.0352 data_time: 0.0637 memory: 6349 grad_norm: 4.9407 loss: 0.9607 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0549 loss_cls: 0.2939 acc: 92.0410 loss_bbox: 0.2840 loss_mask: 0.2870 +2024/10/28 01:13:30 - mmengine - INFO - Epoch(train) [3][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:43:05 time: 0.9843 data_time: 0.0544 memory: 6315 grad_norm: 4.6571 loss: 0.8967 loss_rpn_cls: 0.0420 loss_rpn_bbox: 0.0492 loss_cls: 0.2596 acc: 94.3359 loss_bbox: 0.2673 loss_mask: 0.2787 +2024/10/28 01:14:19 - mmengine - INFO - Epoch(train) [3][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:43:46 time: 0.9843 data_time: 0.0550 memory: 6315 grad_norm: 4.7643 loss: 0.8916 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0526 loss_cls: 0.2523 acc: 95.8984 loss_bbox: 0.2707 loss_mask: 0.2793 +2024/10/28 01:15:08 - mmengine - INFO - Epoch(train) [3][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:44:24 time: 0.9664 data_time: 0.0519 memory: 6195 grad_norm: 4.9091 loss: 0.8831 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0476 loss_cls: 0.2540 acc: 94.8730 loss_bbox: 0.2637 loss_mask: 0.2857 +2024/10/28 01:15:58 - mmengine - INFO - Epoch(train) [3][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:45:09 time: 1.0124 data_time: 0.0471 memory: 6148 grad_norm: 5.1160 loss: 0.8916 loss_rpn_cls: 0.0365 loss_rpn_bbox: 0.0515 loss_cls: 0.2606 acc: 90.6738 loss_bbox: 0.2618 loss_mask: 0.2812 +2024/10/28 01:16:47 - mmengine - INFO - Epoch(train) [3][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:45:46 time: 0.9683 data_time: 0.0486 memory: 6197 grad_norm: 5.0552 loss: 0.8750 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0459 loss_cls: 0.2591 acc: 92.7734 loss_bbox: 0.2601 loss_mask: 0.2719 +2024/10/28 01:17:33 - mmengine - INFO - Epoch(train) [3][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:46:15 time: 0.9305 data_time: 0.0454 memory: 6237 grad_norm: 4.9489 loss: 0.8916 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0496 loss_cls: 0.2648 acc: 94.2383 loss_bbox: 0.2598 loss_mask: 0.2810 +2024/10/28 01:18:24 - mmengine - INFO - Epoch(train) [3][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:46:58 time: 1.0060 data_time: 0.0482 memory: 5990 grad_norm: 4.9183 loss: 0.9007 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0489 loss_cls: 0.2674 acc: 91.2598 loss_bbox: 0.2547 loss_mask: 0.2907 +2024/10/28 01:19:18 - mmengine - INFO - Epoch(train) [3][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:47:55 time: 1.0849 data_time: 0.0558 memory: 6188 grad_norm: 4.9509 loss: 0.9568 loss_rpn_cls: 0.0445 loss_rpn_bbox: 0.0600 loss_cls: 0.2788 acc: 92.1875 loss_bbox: 0.2920 loss_mask: 0.2815 +2024/10/28 01:20:07 - mmengine - INFO - Epoch(train) [3][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:48:33 time: 0.9888 data_time: 0.0493 memory: 6138 grad_norm: 4.7938 loss: 0.9191 loss_rpn_cls: 0.0346 loss_rpn_bbox: 0.0522 loss_cls: 0.2682 acc: 93.9941 loss_bbox: 0.2767 loss_mask: 0.2874 +2024/10/28 01:20:55 - mmengine - INFO - Epoch(train) [3][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:49:05 time: 0.9537 data_time: 0.0503 memory: 6207 grad_norm: 4.6893 loss: 0.8900 loss_rpn_cls: 0.0425 loss_rpn_bbox: 0.0561 loss_cls: 0.2482 acc: 89.3066 loss_bbox: 0.2549 loss_mask: 0.2882 +2024/10/28 01:21:44 - mmengine - INFO - Epoch(train) [3][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:49:41 time: 0.9787 data_time: 0.0498 memory: 6364 grad_norm: 4.8476 loss: 0.9314 loss_rpn_cls: 0.0440 loss_rpn_bbox: 0.0545 loss_cls: 0.2729 acc: 91.3574 loss_bbox: 0.2755 loss_mask: 0.2844 +2024/10/28 01:22:31 - mmengine - INFO - Epoch(train) [3][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:50:10 time: 0.9464 data_time: 0.0503 memory: 6057 grad_norm: 4.7777 loss: 0.8674 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0500 loss_cls: 0.2427 acc: 91.4551 loss_bbox: 0.2585 loss_mask: 0.2803 +2024/10/28 01:23:21 - mmengine - INFO - Epoch(train) [3][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:50:50 time: 1.0035 data_time: 0.0512 memory: 6344 grad_norm: 4.6987 loss: 0.8749 loss_rpn_cls: 0.0346 loss_rpn_bbox: 0.0490 loss_cls: 0.2483 acc: 93.5547 loss_bbox: 0.2664 loss_mask: 0.2765 +2024/10/28 01:24:00 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 01:24:09 - mmengine - INFO - Epoch(train) [3][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:51:18 time: 0.9448 data_time: 0.0405 memory: 6205 grad_norm: 4.8196 loss: 0.8152 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0503 loss_cls: 0.2324 acc: 91.9922 loss_bbox: 0.2380 loss_mask: 0.2621 +2024/10/28 01:25:03 - mmengine - INFO - Epoch(train) [3][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:52:12 time: 1.0911 data_time: 0.0423 memory: 6219 grad_norm: 4.8877 loss: 0.8631 loss_rpn_cls: 0.0409 loss_rpn_bbox: 0.0472 loss_cls: 0.2525 acc: 90.3320 loss_bbox: 0.2499 loss_mask: 0.2726 +2024/10/28 01:25:56 - mmengine - INFO - Epoch(train) [3][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:53:01 time: 1.0600 data_time: 0.1142 memory: 6316 grad_norm: 5.0569 loss: 0.9406 loss_rpn_cls: 0.0374 loss_rpn_bbox: 0.0528 loss_cls: 0.2693 acc: 88.3789 loss_bbox: 0.2922 loss_mask: 0.2890 +2024/10/28 01:26:48 - mmengine - INFO - Epoch(train) [3][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:53:45 time: 1.0446 data_time: 0.0487 memory: 6419 grad_norm: 5.0349 loss: 0.9036 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0551 loss_cls: 0.2651 acc: 94.6777 loss_bbox: 0.2720 loss_mask: 0.2745 +2024/10/28 01:27:36 - mmengine - INFO - Epoch(train) [3][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:54:15 time: 0.9602 data_time: 0.0474 memory: 6091 grad_norm: 5.0651 loss: 0.8016 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0446 loss_cls: 0.2256 acc: 89.1602 loss_bbox: 0.2319 loss_mask: 0.2650 +2024/10/28 01:28:26 - mmengine - INFO - Epoch(train) [3][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:54:51 time: 1.0018 data_time: 0.0492 memory: 6150 grad_norm: 4.8753 loss: 0.8929 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0525 loss_cls: 0.2541 acc: 92.3828 loss_bbox: 0.2704 loss_mask: 0.2749 +2024/10/28 01:29:17 - mmengine - INFO - Epoch(train) [3][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:55:30 time: 1.0173 data_time: 0.0542 memory: 6183 grad_norm: 4.6619 loss: 0.9117 loss_rpn_cls: 0.0361 loss_rpn_bbox: 0.0565 loss_cls: 0.2647 acc: 93.2617 loss_bbox: 0.2812 loss_mask: 0.2732 +2024/10/28 01:30:06 - mmengine - INFO - Epoch(train) [3][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:55:59 time: 0.9650 data_time: 0.0489 memory: 6343 grad_norm: 4.7170 loss: 0.9346 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0516 loss_cls: 0.2744 acc: 90.3809 loss_bbox: 0.2782 loss_mask: 0.2916 +2024/10/28 01:30:56 - mmengine - INFO - Epoch(train) [3][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:56:37 time: 1.0180 data_time: 0.0525 memory: 6257 grad_norm: 4.9443 loss: 0.9247 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0536 loss_cls: 0.2713 acc: 89.9902 loss_bbox: 0.2788 loss_mask: 0.2847 +2024/10/28 01:31:45 - mmengine - INFO - Epoch(train) [3][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:57:06 time: 0.9743 data_time: 0.0587 memory: 6057 grad_norm: 4.7074 loss: 0.8729 loss_rpn_cls: 0.0342 loss_rpn_bbox: 0.0473 loss_cls: 0.2561 acc: 92.8223 loss_bbox: 0.2616 loss_mask: 0.2737 +2024/10/28 01:32:39 - mmengine - INFO - Epoch(train) [3][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:57:52 time: 1.0684 data_time: 0.0566 memory: 6336 grad_norm: 4.6894 loss: 0.9561 loss_rpn_cls: 0.0407 loss_rpn_bbox: 0.0552 loss_cls: 0.2718 acc: 86.4746 loss_bbox: 0.2943 loss_mask: 0.2941 +2024/10/28 01:33:28 - mmengine - INFO - Epoch(train) [3][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:58:24 time: 0.9912 data_time: 0.0526 memory: 6162 grad_norm: 4.8964 loss: 0.9063 loss_rpn_cls: 0.0416 loss_rpn_bbox: 0.0519 loss_cls: 0.2622 acc: 90.4297 loss_bbox: 0.2717 loss_mask: 0.2789 +2024/10/28 01:34:20 - mmengine - INFO - Epoch(train) [3][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:59:03 time: 1.0350 data_time: 0.0545 memory: 6232 grad_norm: 5.0046 loss: 0.9136 loss_rpn_cls: 0.0449 loss_rpn_bbox: 0.0550 loss_cls: 0.2646 acc: 93.4570 loss_bbox: 0.2698 loss_mask: 0.2793 +2024/10/28 01:35:09 - mmengine - INFO - Epoch(train) [3][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:59:31 time: 0.9740 data_time: 0.0466 memory: 6272 grad_norm: 4.9816 loss: 0.8934 loss_rpn_cls: 0.0411 loss_rpn_bbox: 0.0522 loss_cls: 0.2565 acc: 90.9668 loss_bbox: 0.2658 loss_mask: 0.2779 +2024/10/28 01:35:58 - mmengine - INFO - Epoch(train) [3][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:00:02 time: 0.9920 data_time: 0.0443 memory: 6215 grad_norm: 4.6394 loss: 0.8664 loss_rpn_cls: 0.0371 loss_rpn_bbox: 0.0469 loss_cls: 0.2506 acc: 90.7227 loss_bbox: 0.2522 loss_mask: 0.2797 +2024/10/28 01:36:49 - mmengine - INFO - Epoch(train) [3][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:00:35 time: 1.0114 data_time: 0.0458 memory: 6139 grad_norm: 4.9406 loss: 0.8580 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0480 loss_cls: 0.2555 acc: 91.7480 loss_bbox: 0.2458 loss_mask: 0.2735 +2024/10/28 01:37:36 - mmengine - INFO - Epoch(train) [3][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:00:58 time: 0.9498 data_time: 0.0506 memory: 6085 grad_norm: 4.6680 loss: 0.8978 loss_rpn_cls: 0.0379 loss_rpn_bbox: 0.0458 loss_cls: 0.2768 acc: 91.6504 loss_bbox: 0.2605 loss_mask: 0.2769 +2024/10/28 01:38:26 - mmengine - INFO - Epoch(train) [3][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:01:28 time: 0.9931 data_time: 0.0594 memory: 6152 grad_norm: 4.6682 loss: 0.9114 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0565 loss_cls: 0.2659 acc: 95.4590 loss_bbox: 0.2739 loss_mask: 0.2761 +2024/10/28 01:39:13 - mmengine - INFO - Epoch(train) [3][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:01:48 time: 0.9406 data_time: 0.0506 memory: 6148 grad_norm: 5.0808 loss: 0.8941 loss_rpn_cls: 0.0357 loss_rpn_bbox: 0.0505 loss_cls: 0.2641 acc: 92.4805 loss_bbox: 0.2672 loss_mask: 0.2766 +2024/10/28 01:40:00 - mmengine - INFO - Epoch(train) [3][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:02:06 time: 0.9303 data_time: 0.0489 memory: 6291 grad_norm: 4.7761 loss: 0.8795 loss_rpn_cls: 0.0386 loss_rpn_bbox: 0.0494 loss_cls: 0.2554 acc: 96.0938 loss_bbox: 0.2633 loss_mask: 0.2728 +2024/10/28 01:40:39 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 01:40:48 - mmengine - INFO - Epoch(train) [3][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:02:32 time: 0.9771 data_time: 0.0532 memory: 6219 grad_norm: 4.7925 loss: 0.8950 loss_rpn_cls: 0.0329 loss_rpn_bbox: 0.0481 loss_cls: 0.2571 acc: 94.9219 loss_bbox: 0.2745 loss_mask: 0.2824 +2024/10/28 01:41:34 - mmengine - INFO - Epoch(train) [3][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:02:47 time: 0.9155 data_time: 0.0466 memory: 6373 grad_norm: 4.4766 loss: 0.8302 loss_rpn_cls: 0.0362 loss_rpn_bbox: 0.0427 loss_cls: 0.2368 acc: 91.5527 loss_bbox: 0.2551 loss_mask: 0.2596 +2024/10/28 01:42:21 - mmengine - INFO - Epoch(train) [3][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:03:04 time: 0.9288 data_time: 0.0484 memory: 6091 grad_norm: 4.6946 loss: 0.9125 loss_rpn_cls: 0.0428 loss_rpn_bbox: 0.0518 loss_cls: 0.2750 acc: 89.4531 loss_bbox: 0.2642 loss_mask: 0.2787 +2024/10/28 01:43:11 - mmengine - INFO - Epoch(train) [3][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:03:34 time: 1.0060 data_time: 0.0462 memory: 6151 grad_norm: 4.9857 loss: 0.8757 loss_rpn_cls: 0.0338 loss_rpn_bbox: 0.0485 loss_cls: 0.2577 acc: 91.4062 loss_bbox: 0.2614 loss_mask: 0.2743 +2024/10/28 01:44:01 - mmengine - INFO - Epoch(train) [3][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:04:02 time: 1.0013 data_time: 0.0473 memory: 6240 grad_norm: 4.8961 loss: 0.8809 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0531 loss_cls: 0.2534 acc: 93.9941 loss_bbox: 0.2587 loss_mask: 0.2817 +2024/10/28 01:44:52 - mmengine - INFO - Epoch(train) [3][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:04:32 time: 1.0131 data_time: 0.0412 memory: 6105 grad_norm: 4.8378 loss: 0.8406 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0405 loss_cls: 0.2461 acc: 92.7734 loss_bbox: 0.2458 loss_mask: 0.2763 +2024/10/28 01:45:41 - mmengine - INFO - Epoch(train) [3][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:04:59 time: 0.9950 data_time: 0.0468 memory: 6140 grad_norm: 4.8318 loss: 0.8942 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0512 loss_cls: 0.2531 acc: 94.0430 loss_bbox: 0.2582 loss_mask: 0.2907 +2024/10/28 01:46:31 - mmengine - INFO - Epoch(train) [3][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:05:24 time: 0.9851 data_time: 0.0468 memory: 6301 grad_norm: 4.9088 loss: 0.8826 loss_rpn_cls: 0.0388 loss_rpn_bbox: 0.0483 loss_cls: 0.2573 acc: 85.7422 loss_bbox: 0.2671 loss_mask: 0.2711 +2024/10/28 01:47:20 - mmengine - INFO - Epoch(train) [3][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:05:48 time: 0.9850 data_time: 0.0486 memory: 6121 grad_norm: 4.6259 loss: 0.9232 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0511 loss_cls: 0.2713 acc: 90.4297 loss_bbox: 0.2785 loss_mask: 0.2846 +2024/10/28 01:48:09 - mmengine - INFO - Epoch(train) [3][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:06:12 time: 0.9873 data_time: 0.0456 memory: 6305 grad_norm: 5.0474 loss: 0.9004 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0501 loss_cls: 0.2689 acc: 93.7012 loss_bbox: 0.2593 loss_mask: 0.2865 +2024/10/28 01:49:01 - mmengine - INFO - Epoch(train) [3][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:06:43 time: 1.0299 data_time: 0.0536 memory: 6419 grad_norm: 4.7003 loss: 0.8785 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0483 loss_cls: 0.2522 acc: 91.6992 loss_bbox: 0.2633 loss_mask: 0.2756 +2024/10/28 01:49:49 - mmengine - INFO - Epoch(train) [3][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:07:03 time: 0.9637 data_time: 0.0471 memory: 6199 grad_norm: 4.7834 loss: 0.8625 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0510 loss_cls: 0.2334 acc: 89.3066 loss_bbox: 0.2541 loss_mask: 0.2875 +2024/10/28 01:50:41 - mmengine - INFO - Epoch(train) [3][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:07:34 time: 1.0381 data_time: 0.0520 memory: 6345 grad_norm: 4.9414 loss: 0.8716 loss_rpn_cls: 0.0399 loss_rpn_bbox: 0.0504 loss_cls: 0.2501 acc: 97.1191 loss_bbox: 0.2503 loss_mask: 0.2809 +2024/10/28 01:51:29 - mmengine - INFO - Epoch(train) [3][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:07:53 time: 0.9608 data_time: 0.0528 memory: 6333 grad_norm: 4.6385 loss: 0.8829 loss_rpn_cls: 0.0365 loss_rpn_bbox: 0.0522 loss_cls: 0.2445 acc: 95.4102 loss_bbox: 0.2641 loss_mask: 0.2856 +2024/10/28 01:52:15 - mmengine - INFO - Epoch(train) [3][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:08:06 time: 0.9315 data_time: 0.0602 memory: 6268 grad_norm: 4.7215 loss: 0.8800 loss_rpn_cls: 0.0398 loss_rpn_bbox: 0.0505 loss_cls: 0.2597 acc: 92.7246 loss_bbox: 0.2634 loss_mask: 0.2665 +2024/10/28 01:53:06 - mmengine - INFO - Epoch(train) [3][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:08:32 time: 1.0116 data_time: 0.0500 memory: 6349 grad_norm: 4.9920 loss: 0.9364 loss_rpn_cls: 0.0382 loss_rpn_bbox: 0.0513 loss_cls: 0.2755 acc: 91.0645 loss_bbox: 0.2790 loss_mask: 0.2925 +2024/10/28 01:53:56 - mmengine - INFO - Epoch(train) [3][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:08:57 time: 1.0072 data_time: 0.0517 memory: 6233 grad_norm: 4.7109 loss: 0.8459 loss_rpn_cls: 0.0359 loss_rpn_bbox: 0.0494 loss_cls: 0.2379 acc: 93.8477 loss_bbox: 0.2525 loss_mask: 0.2702 +2024/10/28 01:54:48 - mmengine - INFO - Epoch(train) [3][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:09:24 time: 1.0221 data_time: 0.0481 memory: 6214 grad_norm: 4.5805 loss: 0.9238 loss_rpn_cls: 0.0358 loss_rpn_bbox: 0.0485 loss_cls: 0.2779 acc: 97.0215 loss_bbox: 0.2729 loss_mask: 0.2887 +2024/10/28 01:55:35 - mmengine - INFO - Epoch(train) [3][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:09:41 time: 0.9561 data_time: 0.0418 memory: 6047 grad_norm: 4.6732 loss: 0.8438 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0435 loss_cls: 0.2443 acc: 98.1445 loss_bbox: 0.2511 loss_mask: 0.2736 +2024/10/28 01:56:24 - mmengine - INFO - Epoch(train) [3][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:09:58 time: 0.9667 data_time: 0.0458 memory: 6241 grad_norm: 4.8363 loss: 0.8752 loss_rpn_cls: 0.0351 loss_rpn_bbox: 0.0495 loss_cls: 0.2539 acc: 94.8242 loss_bbox: 0.2558 loss_mask: 0.2809 +2024/10/28 01:57:04 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 01:57:13 - mmengine - INFO - Epoch(train) [3][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:10:17 time: 0.9781 data_time: 0.0456 memory: 6080 grad_norm: 5.1443 loss: 0.8790 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0507 loss_cls: 0.2625 acc: 90.3809 loss_bbox: 0.2540 loss_mask: 0.2750 +2024/10/28 01:58:00 - mmengine - INFO - Epoch(train) [3][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:10:30 time: 0.9420 data_time: 0.0452 memory: 6136 grad_norm: 4.5197 loss: 0.8761 loss_rpn_cls: 0.0365 loss_rpn_bbox: 0.0474 loss_cls: 0.2606 acc: 90.9668 loss_bbox: 0.2536 loss_mask: 0.2779 +2024/10/28 01:58:47 - mmengine - INFO - Epoch(train) [3][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:10:43 time: 0.9422 data_time: 0.0566 memory: 6268 grad_norm: 4.8974 loss: 0.9669 loss_rpn_cls: 0.0401 loss_rpn_bbox: 0.0546 loss_cls: 0.2912 acc: 95.5566 loss_bbox: 0.2925 loss_mask: 0.2885 +2024/10/28 01:59:34 - mmengine - INFO - Epoch(train) [3][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:10:55 time: 0.9404 data_time: 0.0475 memory: 6411 grad_norm: 4.5272 loss: 0.9289 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0532 loss_cls: 0.2792 acc: 94.3359 loss_bbox: 0.2742 loss_mask: 0.2833 +2024/10/28 02:00:24 - mmengine - INFO - Epoch(train) [3][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:11:17 time: 1.0094 data_time: 0.0434 memory: 6186 grad_norm: 4.6260 loss: 0.8621 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0466 loss_cls: 0.2476 acc: 93.3105 loss_bbox: 0.2574 loss_mask: 0.2791 +2024/10/28 02:01:12 - mmengine - INFO - Epoch(train) [3][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:11:30 time: 0.9445 data_time: 0.0482 memory: 6390 grad_norm: 4.7583 loss: 0.8962 loss_rpn_cls: 0.0361 loss_rpn_bbox: 0.0466 loss_cls: 0.2722 acc: 90.3320 loss_bbox: 0.2577 loss_mask: 0.2836 +2024/10/28 02:02:00 - mmengine - INFO - Epoch(train) [3][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:11:45 time: 0.9667 data_time: 0.0457 memory: 6314 grad_norm: 4.9742 loss: 0.8093 loss_rpn_cls: 0.0358 loss_rpn_bbox: 0.0452 loss_cls: 0.2267 acc: 91.8945 loss_bbox: 0.2455 loss_mask: 0.2561 +2024/10/28 02:02:48 - mmengine - INFO - Epoch(train) [3][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:12:00 time: 0.9688 data_time: 0.0498 memory: 6420 grad_norm: 4.8387 loss: 0.8716 loss_rpn_cls: 0.0343 loss_rpn_bbox: 0.0456 loss_cls: 0.2519 acc: 96.3379 loss_bbox: 0.2620 loss_mask: 0.2778 +2024/10/28 02:03:37 - mmengine - INFO - Epoch(train) [3][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:12:16 time: 0.9725 data_time: 0.0525 memory: 6286 grad_norm: 4.6911 loss: 0.9225 loss_rpn_cls: 0.0474 loss_rpn_bbox: 0.0537 loss_cls: 0.2711 acc: 85.8887 loss_bbox: 0.2804 loss_mask: 0.2699 +2024/10/28 02:04:23 - mmengine - INFO - Epoch(train) [3][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:12:24 time: 0.9272 data_time: 0.0555 memory: 6191 grad_norm: 4.6799 loss: 0.9297 loss_rpn_cls: 0.0495 loss_rpn_bbox: 0.0539 loss_cls: 0.2749 acc: 91.4062 loss_bbox: 0.2771 loss_mask: 0.2743 +2024/10/28 02:05:10 - mmengine - INFO - Epoch(train) [3][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:12:35 time: 0.9439 data_time: 0.0463 memory: 6112 grad_norm: 4.9770 loss: 0.7859 loss_rpn_cls: 0.0312 loss_rpn_bbox: 0.0387 loss_cls: 0.2189 acc: 87.7930 loss_bbox: 0.2366 loss_mask: 0.2605 +2024/10/28 02:05:59 - mmengine - INFO - Epoch(train) [3][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:12:49 time: 0.9683 data_time: 0.0498 memory: 6219 grad_norm: 4.7911 loss: 0.8864 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0501 loss_cls: 0.2567 acc: 96.2891 loss_bbox: 0.2648 loss_mask: 0.2757 +2024/10/28 02:06:52 - mmengine - INFO - Epoch(train) [3][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:13:18 time: 1.0670 data_time: 0.0555 memory: 6132 grad_norm: 4.8793 loss: 0.9294 loss_rpn_cls: 0.0481 loss_rpn_bbox: 0.0578 loss_cls: 0.2694 acc: 92.5781 loss_bbox: 0.2774 loss_mask: 0.2767 +2024/10/28 02:07:41 - mmengine - INFO - Epoch(train) [3][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:13:33 time: 0.9767 data_time: 0.0548 memory: 6215 grad_norm: 4.7694 loss: 0.8644 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0510 loss_cls: 0.2491 acc: 88.4277 loss_bbox: 0.2551 loss_mask: 0.2729 +2024/10/28 02:08:29 - mmengine - INFO - Epoch(train) [3][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:13:45 time: 0.9577 data_time: 0.0532 memory: 6000 grad_norm: 5.1421 loss: 0.8804 loss_rpn_cls: 0.0453 loss_rpn_bbox: 0.0545 loss_cls: 0.2622 acc: 95.8496 loss_bbox: 0.2481 loss_mask: 0.2704 +2024/10/28 02:09:22 - mmengine - INFO - Epoch(train) [3][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:14:10 time: 1.0508 data_time: 0.0496 memory: 6289 grad_norm: 4.7265 loss: 0.8267 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0441 loss_cls: 0.2318 acc: 89.7949 loss_bbox: 0.2419 loss_mask: 0.2750 +2024/10/28 02:10:09 - mmengine - INFO - Epoch(train) [3][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:14:19 time: 0.9414 data_time: 0.0466 memory: 6091 grad_norm: 4.8326 loss: 0.8696 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0491 loss_cls: 0.2443 acc: 91.4062 loss_bbox: 0.2645 loss_mask: 0.2741 +2024/10/28 02:11:00 - mmengine - INFO - Epoch(train) [3][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:14:41 time: 1.0325 data_time: 0.0541 memory: 6319 grad_norm: 4.7412 loss: 0.9057 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0552 loss_cls: 0.2565 acc: 90.8203 loss_bbox: 0.2767 loss_mask: 0.2797 +2024/10/28 02:11:48 - mmengine - INFO - Epoch(train) [3][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:14:52 time: 0.9588 data_time: 0.0591 memory: 6203 grad_norm: 4.7633 loss: 0.9145 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0540 loss_cls: 0.2712 acc: 90.2344 loss_bbox: 0.2724 loss_mask: 0.2784 +2024/10/28 02:12:39 - mmengine - INFO - Epoch(train) [3][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:15:11 time: 1.0173 data_time: 0.0532 memory: 6147 grad_norm: 4.6938 loss: 0.9356 loss_rpn_cls: 0.0464 loss_rpn_bbox: 0.0510 loss_cls: 0.2856 acc: 86.6699 loss_bbox: 0.2771 loss_mask: 0.2756 +2024/10/28 02:13:09 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 02:13:09 - mmengine - INFO - Saving checkpoint at 3 epochs +2024/10/28 02:13:23 - mmengine - INFO - Epoch(val) [3][ 50/1250] eta: 0:03:30 time: 0.1751 data_time: 0.0067 memory: 6226 +2024/10/28 02:13:31 - mmengine - INFO - Epoch(val) [3][ 100/1250] eta: 0:03:20 time: 0.1732 data_time: 0.0055 memory: 1114 +2024/10/28 02:13:40 - mmengine - INFO - Epoch(val) [3][ 150/1250] eta: 0:03:10 time: 0.1721 data_time: 0.0058 memory: 1114 +2024/10/28 02:13:49 - mmengine - INFO - Epoch(val) [3][ 200/1250] eta: 0:03:02 time: 0.1768 data_time: 0.0074 memory: 1114 +2024/10/28 02:13:58 - mmengine - INFO - Epoch(val) [3][ 250/1250] eta: 0:02:54 time: 0.1754 data_time: 0.0063 memory: 1221 +2024/10/28 02:14:06 - mmengine - INFO - Epoch(val) [3][ 300/1250] eta: 0:02:45 time: 0.1707 data_time: 0.0075 memory: 1114 +2024/10/28 02:14:15 - mmengine - INFO - Epoch(val) [3][ 350/1250] eta: 0:02:37 time: 0.1819 data_time: 0.0061 memory: 1117 +2024/10/28 02:14:23 - mmengine - INFO - Epoch(val) [3][ 400/1250] eta: 0:02:27 time: 0.1613 data_time: 0.0053 memory: 1164 +2024/10/28 02:14:32 - mmengine - INFO - Epoch(val) [3][ 450/1250] eta: 0:02:18 time: 0.1694 data_time: 0.0046 memory: 1114 +2024/10/28 02:14:40 - mmengine - INFO - Epoch(val) [3][ 500/1250] eta: 0:02:09 time: 0.1719 data_time: 0.0053 memory: 1134 +2024/10/28 02:14:49 - mmengine - INFO - Epoch(val) [3][ 550/1250] eta: 0:02:00 time: 0.1637 data_time: 0.0046 memory: 1176 +2024/10/28 02:14:57 - mmengine - INFO - Epoch(val) [3][ 600/1250] eta: 0:01:52 time: 0.1764 data_time: 0.0064 memory: 1114 +2024/10/28 02:15:06 - mmengine - INFO - Epoch(val) [3][ 650/1250] eta: 0:01:43 time: 0.1643 data_time: 0.0051 memory: 1219 +2024/10/28 02:15:15 - mmengine - INFO - Epoch(val) [3][ 700/1250] eta: 0:01:35 time: 0.1861 data_time: 0.0057 memory: 1125 +2024/10/28 02:15:24 - mmengine - INFO - Epoch(val) [3][ 750/1250] eta: 0:01:26 time: 0.1834 data_time: 0.0064 memory: 1116 +2024/10/28 02:15:32 - mmengine - INFO - Epoch(val) [3][ 800/1250] eta: 0:01:17 time: 0.1645 data_time: 0.0052 memory: 1160 +2024/10/28 02:15:41 - mmengine - INFO - Epoch(val) [3][ 850/1250] eta: 0:01:09 time: 0.1703 data_time: 0.0055 memory: 1192 +2024/10/28 02:15:49 - mmengine - INFO - Epoch(val) [3][ 900/1250] eta: 0:01:00 time: 0.1686 data_time: 0.0052 memory: 1114 +2024/10/28 02:15:58 - mmengine - INFO - Epoch(val) [3][ 950/1250] eta: 0:00:51 time: 0.1747 data_time: 0.0071 memory: 1219 +2024/10/28 02:16:06 - mmengine - INFO - Epoch(val) [3][1000/1250] eta: 0:00:43 time: 0.1643 data_time: 0.0056 memory: 1115 +2024/10/28 02:16:15 - mmengine - INFO - Epoch(val) [3][1050/1250] eta: 0:00:34 time: 0.1783 data_time: 0.0061 memory: 1114 +2024/10/28 02:16:24 - mmengine - INFO - Epoch(val) [3][1100/1250] eta: 0:00:25 time: 0.1766 data_time: 0.0047 memory: 1114 +2024/10/28 02:16:33 - mmengine - INFO - Epoch(val) [3][1150/1250] eta: 0:00:17 time: 0.1759 data_time: 0.0061 memory: 1114 +2024/10/28 02:16:41 - mmengine - INFO - Epoch(val) [3][1200/1250] eta: 0:00:08 time: 0.1727 data_time: 0.0052 memory: 1176 +2024/10/28 02:16:50 - mmengine - INFO - Epoch(val) [3][1250/1250] eta: 0:00:00 time: 0.1646 data_time: 0.0052 memory: 1143 +2024/10/28 02:17:05 - mmengine - INFO - Evaluating bbox... +2024/10/28 02:17:42 - mmengine - INFO - bbox_mAP_copypaste: 0.293 0.493 0.312 0.143 0.322 0.399 +2024/10/28 02:17:42 - mmengine - INFO - Evaluating segm... +2024/10/28 02:18:24 - mmengine - INFO - segm_mAP_copypaste: 0.279 0.466 0.290 0.101 0.299 0.431 +2024/10/28 02:18:25 - mmengine - INFO - Epoch(val) [3][1250/1250] coco/bbox_mAP: 0.2930 coco/bbox_mAP_50: 0.4930 coco/bbox_mAP_75: 0.3120 coco/bbox_mAP_s: 0.1430 coco/bbox_mAP_m: 0.3220 coco/bbox_mAP_l: 0.3990 coco/segm_mAP: 0.2790 coco/segm_mAP_50: 0.4660 coco/segm_mAP_75: 0.2900 coco/segm_mAP_s: 0.1010 coco/segm_mAP_m: 0.2990 coco/segm_mAP_l: 0.4310 data_time: 0.0058 time: 0.1724 +2024/10/28 02:18:36 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 02:19:14 - mmengine - INFO - Epoch(train) [4][ 50/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:15:34 time: 0.9772 data_time: 0.0475 memory: 6195 grad_norm: 4.7353 loss: 0.8261 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0462 loss_cls: 0.2355 acc: 91.1133 loss_bbox: 0.2389 loss_mask: 0.2702 +2024/10/28 02:20:02 - mmengine - INFO - Epoch(train) [4][ 100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:15:44 time: 0.9604 data_time: 0.0492 memory: 6366 grad_norm: 4.7439 loss: 0.8630 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0489 loss_cls: 0.2433 acc: 94.0430 loss_bbox: 0.2717 loss_mask: 0.2671 +2024/10/28 02:20:53 - mmengine - INFO - Epoch(train) [4][ 150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:16:03 time: 1.0225 data_time: 0.1235 memory: 6345 grad_norm: 4.8100 loss: 0.9137 loss_rpn_cls: 0.0358 loss_rpn_bbox: 0.0535 loss_cls: 0.2557 acc: 93.3105 loss_bbox: 0.2804 loss_mask: 0.2885 +2024/10/28 02:21:36 - mmengine - INFO - Epoch(train) [4][ 200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:15:57 time: 0.8535 data_time: 0.0461 memory: 6245 grad_norm: 4.9102 loss: 0.8966 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0503 loss_cls: 0.2713 acc: 93.0176 loss_bbox: 0.2750 loss_mask: 0.2685 +2024/10/28 02:22:08 - mmengine - INFO - Epoch(train) [4][ 250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:15:18 time: 0.6396 data_time: 0.0425 memory: 6180 grad_norm: 4.7449 loss: 0.8322 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0489 loss_cls: 0.2441 acc: 91.0645 loss_bbox: 0.2430 loss_mask: 0.2657 +2024/10/28 02:22:32 - mmengine - INFO - Epoch(train) [4][ 300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:14:15 time: 0.4674 data_time: 0.0427 memory: 6302 grad_norm: 4.7789 loss: 0.8085 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0451 loss_cls: 0.2320 acc: 92.8223 loss_bbox: 0.2395 loss_mask: 0.2614 +2024/10/28 02:22:55 - mmengine - INFO - Epoch(train) [4][ 350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:13:12 time: 0.4741 data_time: 0.0484 memory: 6319 grad_norm: 4.5656 loss: 0.8868 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0526 loss_cls: 0.2595 acc: 89.4531 loss_bbox: 0.2606 loss_mask: 0.2789 +2024/10/28 02:23:19 - mmengine - INFO - Epoch(train) [4][ 400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:12:12 time: 0.4857 data_time: 0.0446 memory: 6182 grad_norm: 4.7093 loss: 0.8833 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0499 loss_cls: 0.2600 acc: 92.4316 loss_bbox: 0.2640 loss_mask: 0.2763 +2024/10/28 02:23:44 - mmengine - INFO - Epoch(train) [4][ 450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:11:11 time: 0.4822 data_time: 0.0476 memory: 6185 grad_norm: 4.5830 loss: 0.8576 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0471 loss_cls: 0.2464 acc: 88.7695 loss_bbox: 0.2601 loss_mask: 0.2715 +2024/10/28 02:24:08 - mmengine - INFO - Epoch(train) [4][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:10:12 time: 0.4934 data_time: 0.0527 memory: 6238 grad_norm: 5.0143 loss: 0.8746 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0489 loss_cls: 0.2529 acc: 93.4082 loss_bbox: 0.2653 loss_mask: 0.2708 +2024/10/28 02:24:33 - mmengine - INFO - Epoch(train) [4][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:09:12 time: 0.4856 data_time: 0.0504 memory: 6080 grad_norm: 4.8025 loss: 0.8517 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0456 loss_cls: 0.2489 acc: 98.0957 loss_bbox: 0.2511 loss_mask: 0.2752 +2024/10/28 02:24:57 - mmengine - INFO - Epoch(train) [4][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:08:12 time: 0.4881 data_time: 0.0516 memory: 6211 grad_norm: 4.6711 loss: 0.9170 loss_rpn_cls: 0.0436 loss_rpn_bbox: 0.0547 loss_cls: 0.2660 acc: 88.6230 loss_bbox: 0.2757 loss_mask: 0.2770 +2024/10/28 02:25:22 - mmengine - INFO - Epoch(train) [4][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:07:14 time: 0.4955 data_time: 0.0533 memory: 6301 grad_norm: 4.7096 loss: 0.8902 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0482 loss_cls: 0.2616 acc: 94.8242 loss_bbox: 0.2681 loss_mask: 0.2756 +2024/10/28 02:25:46 - mmengine - INFO - Epoch(train) [4][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:06:13 time: 0.4754 data_time: 0.0454 memory: 6314 grad_norm: 4.6539 loss: 0.8557 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0454 loss_cls: 0.2491 acc: 93.5547 loss_bbox: 0.2644 loss_mask: 0.2685 +2024/10/28 02:26:11 - mmengine - INFO - Epoch(train) [4][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:05:16 time: 0.5036 data_time: 0.0680 memory: 6236 grad_norm: 4.5293 loss: 0.9242 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0526 loss_cls: 0.2700 acc: 92.4316 loss_bbox: 0.2698 loss_mask: 0.2908 +2024/10/28 02:26:35 - mmengine - INFO - Epoch(train) [4][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:04:16 time: 0.4835 data_time: 0.0466 memory: 6111 grad_norm: 4.7011 loss: 0.8519 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0469 loss_cls: 0.2495 acc: 93.9453 loss_bbox: 0.2539 loss_mask: 0.2685 +2024/10/28 02:26:59 - mmengine - INFO - Epoch(train) [4][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:03:16 time: 0.4822 data_time: 0.0486 memory: 6183 grad_norm: 4.8941 loss: 0.8796 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0512 loss_cls: 0.2568 acc: 87.8418 loss_bbox: 0.2596 loss_mask: 0.2760 +2024/10/28 02:27:23 - mmengine - INFO - Epoch(train) [4][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:02:17 time: 0.4808 data_time: 0.0529 memory: 6193 grad_norm: 4.8218 loss: 0.8921 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0525 loss_cls: 0.2542 acc: 95.3125 loss_bbox: 0.2702 loss_mask: 0.2792 +2024/10/28 02:27:47 - mmengine - INFO - Epoch(train) [4][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:01:16 time: 0.4741 data_time: 0.0482 memory: 6115 grad_norm: 4.7282 loss: 0.7993 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0423 loss_cls: 0.2230 acc: 91.6504 loss_bbox: 0.2402 loss_mask: 0.2656 +2024/10/28 02:28:11 - mmengine - INFO - Epoch(train) [4][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 12:00:17 time: 0.4818 data_time: 0.0492 memory: 6333 grad_norm: 4.6037 loss: 0.8726 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0532 loss_cls: 0.2459 acc: 94.4336 loss_bbox: 0.2630 loss_mask: 0.2749 +2024/10/28 02:28:16 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 02:28:36 - mmengine - INFO - Epoch(train) [4][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:59:20 time: 0.4974 data_time: 0.0525 memory: 6253 grad_norm: 4.7927 loss: 0.9163 loss_rpn_cls: 0.0381 loss_rpn_bbox: 0.0552 loss_cls: 0.2774 acc: 93.7988 loss_bbox: 0.2686 loss_mask: 0.2771 +2024/10/28 02:29:00 - mmengine - INFO - Epoch(train) [4][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:58:22 time: 0.4904 data_time: 0.0486 memory: 6250 grad_norm: 4.7654 loss: 0.8510 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0471 loss_cls: 0.2441 acc: 87.0605 loss_bbox: 0.2519 loss_mask: 0.2725 +2024/10/28 02:29:25 - mmengine - INFO - Epoch(train) [4][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:57:24 time: 0.4855 data_time: 0.0507 memory: 6246 grad_norm: 4.7441 loss: 0.8632 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0448 loss_cls: 0.2483 acc: 97.9492 loss_bbox: 0.2649 loss_mask: 0.2688 +2024/10/28 02:29:48 - mmengine - INFO - Epoch(train) [4][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:56:24 time: 0.4744 data_time: 0.0443 memory: 6237 grad_norm: 4.5797 loss: 0.8548 loss_rpn_cls: 0.0342 loss_rpn_bbox: 0.0485 loss_cls: 0.2507 acc: 96.7285 loss_bbox: 0.2542 loss_mask: 0.2671 +2024/10/28 02:30:12 - mmengine - INFO - Epoch(train) [4][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:55:25 time: 0.4755 data_time: 0.0447 memory: 6222 grad_norm: 4.7281 loss: 0.8511 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0455 loss_cls: 0.2482 acc: 96.4844 loss_bbox: 0.2553 loss_mask: 0.2641 +2024/10/28 02:30:36 - mmengine - INFO - Epoch(train) [4][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:54:26 time: 0.4797 data_time: 0.0396 memory: 6188 grad_norm: 4.8466 loss: 0.8361 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0468 loss_cls: 0.2414 acc: 93.3594 loss_bbox: 0.2442 loss_mask: 0.2732 +2024/10/28 02:31:01 - mmengine - INFO - Epoch(train) [4][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:53:29 time: 0.4908 data_time: 0.0430 memory: 6147 grad_norm: 4.4751 loss: 0.8018 loss_rpn_cls: 0.0279 loss_rpn_bbox: 0.0417 loss_cls: 0.2265 acc: 93.0664 loss_bbox: 0.2421 loss_mask: 0.2636 +2024/10/28 02:31:25 - mmengine - INFO - Epoch(train) [4][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:52:32 time: 0.4853 data_time: 0.0405 memory: 6325 grad_norm: 4.8456 loss: 0.8711 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0461 loss_cls: 0.2463 acc: 95.0195 loss_bbox: 0.2694 loss_mask: 0.2766 +2024/10/28 02:31:49 - mmengine - INFO - Epoch(train) [4][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:51:34 time: 0.4812 data_time: 0.0468 memory: 6125 grad_norm: 4.8085 loss: 0.8562 loss_rpn_cls: 0.0295 loss_rpn_bbox: 0.0519 loss_cls: 0.2516 acc: 90.2344 loss_bbox: 0.2585 loss_mask: 0.2647 +2024/10/28 02:32:13 - mmengine - INFO - Epoch(train) [4][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:50:36 time: 0.4854 data_time: 0.0456 memory: 6325 grad_norm: 4.5341 loss: 0.8693 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0509 loss_cls: 0.2523 acc: 93.9453 loss_bbox: 0.2630 loss_mask: 0.2690 +2024/10/28 02:32:37 - mmengine - INFO - Epoch(train) [4][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:49:38 time: 0.4747 data_time: 0.0481 memory: 6259 grad_norm: 4.6614 loss: 0.9161 loss_rpn_cls: 0.0381 loss_rpn_bbox: 0.0515 loss_cls: 0.2641 acc: 90.1855 loss_bbox: 0.2781 loss_mask: 0.2844 +2024/10/28 02:33:00 - mmengine - INFO - Epoch(train) [4][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:48:39 time: 0.4701 data_time: 0.0396 memory: 6215 grad_norm: 4.5146 loss: 0.8389 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0441 loss_cls: 0.2480 acc: 95.3125 loss_bbox: 0.2419 loss_mask: 0.2747 +2024/10/28 02:33:24 - mmengine - INFO - Epoch(train) [4][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:47:40 time: 0.4743 data_time: 0.0429 memory: 6089 grad_norm: 4.5821 loss: 0.8696 loss_rpn_cls: 0.0354 loss_rpn_bbox: 0.0539 loss_cls: 0.2440 acc: 91.9434 loss_bbox: 0.2636 loss_mask: 0.2728 +2024/10/28 02:33:48 - mmengine - INFO - Epoch(train) [4][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:46:42 time: 0.4757 data_time: 0.0437 memory: 6310 grad_norm: 4.6263 loss: 0.9146 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0578 loss_cls: 0.2556 acc: 90.5273 loss_bbox: 0.2794 loss_mask: 0.2850 +2024/10/28 02:34:12 - mmengine - INFO - Epoch(train) [4][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:45:44 time: 0.4732 data_time: 0.0498 memory: 6107 grad_norm: 4.8238 loss: 0.9121 loss_rpn_cls: 0.0375 loss_rpn_bbox: 0.0544 loss_cls: 0.2698 acc: 93.5059 loss_bbox: 0.2735 loss_mask: 0.2770 +2024/10/28 02:34:35 - mmengine - INFO - Epoch(train) [4][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:44:46 time: 0.4734 data_time: 0.0429 memory: 6411 grad_norm: 4.6109 loss: 0.8438 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0486 loss_cls: 0.2387 acc: 92.3828 loss_bbox: 0.2492 loss_mask: 0.2765 +2024/10/28 02:34:59 - mmengine - INFO - Epoch(train) [4][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:43:50 time: 0.4840 data_time: 0.0423 memory: 6163 grad_norm: 4.7430 loss: 0.8591 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0465 loss_cls: 0.2535 acc: 89.1113 loss_bbox: 0.2561 loss_mask: 0.2709 +2024/10/28 02:35:23 - mmengine - INFO - Epoch(train) [4][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:42:53 time: 0.4789 data_time: 0.0409 memory: 6155 grad_norm: 5.0582 loss: 0.8710 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0478 loss_cls: 0.2488 acc: 94.8730 loss_bbox: 0.2626 loss_mask: 0.2755 +2024/10/28 02:35:48 - mmengine - INFO - Epoch(train) [4][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:41:56 time: 0.4841 data_time: 0.0426 memory: 6098 grad_norm: 4.7612 loss: 0.8497 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0488 loss_cls: 0.2492 acc: 92.2852 loss_bbox: 0.2449 loss_mask: 0.2717 +2024/10/28 02:36:12 - mmengine - INFO - Epoch(train) [4][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:41:01 time: 0.4890 data_time: 0.0463 memory: 6197 grad_norm: 4.7310 loss: 0.8867 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0498 loss_cls: 0.2471 acc: 89.8926 loss_bbox: 0.2600 loss_mask: 0.2919 +2024/10/28 02:36:17 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 02:36:37 - mmengine - INFO - Epoch(train) [4][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:40:07 time: 0.4955 data_time: 0.0541 memory: 6196 grad_norm: 4.6163 loss: 0.8890 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0550 loss_cls: 0.2551 acc: 89.1113 loss_bbox: 0.2671 loss_mask: 0.2756 +2024/10/28 02:37:01 - mmengine - INFO - Epoch(train) [4][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:39:11 time: 0.4825 data_time: 0.0474 memory: 6119 grad_norm: 4.4781 loss: 0.8609 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0519 loss_cls: 0.2420 acc: 90.9668 loss_bbox: 0.2528 loss_mask: 0.2798 +2024/10/28 02:37:26 - mmengine - INFO - Epoch(train) [4][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:38:16 time: 0.4943 data_time: 0.0593 memory: 6363 grad_norm: 4.6473 loss: 0.8901 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0494 loss_cls: 0.2661 acc: 94.6289 loss_bbox: 0.2613 loss_mask: 0.2773 +2024/10/28 02:37:50 - mmengine - INFO - Epoch(train) [4][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:37:21 time: 0.4885 data_time: 0.0536 memory: 6126 grad_norm: 4.6940 loss: 0.8711 loss_rpn_cls: 0.0359 loss_rpn_bbox: 0.0509 loss_cls: 0.2406 acc: 88.4277 loss_bbox: 0.2659 loss_mask: 0.2779 +2024/10/28 02:38:15 - mmengine - INFO - Epoch(train) [4][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:36:28 time: 0.4998 data_time: 0.0565 memory: 6333 grad_norm: 4.6592 loss: 0.8046 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0462 loss_cls: 0.2138 acc: 90.4297 loss_bbox: 0.2418 loss_mask: 0.2704 +2024/10/28 02:38:40 - mmengine - INFO - Epoch(train) [4][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:35:35 time: 0.4997 data_time: 0.0613 memory: 6172 grad_norm: 4.6405 loss: 0.8156 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0443 loss_cls: 0.2306 acc: 90.4297 loss_bbox: 0.2461 loss_mask: 0.2636 +2024/10/28 02:39:04 - mmengine - INFO - Epoch(train) [4][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:34:40 time: 0.4847 data_time: 0.0542 memory: 6208 grad_norm: 4.6616 loss: 0.8757 loss_rpn_cls: 0.0398 loss_rpn_bbox: 0.0526 loss_cls: 0.2431 acc: 86.6699 loss_bbox: 0.2658 loss_mask: 0.2745 +2024/10/28 02:39:31 - mmengine - INFO - Epoch(train) [4][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:33:50 time: 0.5249 data_time: 0.0952 memory: 6244 grad_norm: 4.4636 loss: 0.8056 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0443 loss_cls: 0.2320 acc: 97.8027 loss_bbox: 0.2388 loss_mask: 0.2622 +2024/10/28 02:39:55 - mmengine - INFO - Epoch(train) [4][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:32:56 time: 0.4961 data_time: 0.0587 memory: 6311 grad_norm: 4.5641 loss: 0.8611 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0476 loss_cls: 0.2473 acc: 94.2383 loss_bbox: 0.2592 loss_mask: 0.2752 +2024/10/28 02:40:20 - mmengine - INFO - Epoch(train) [4][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:32:02 time: 0.4877 data_time: 0.0620 memory: 6201 grad_norm: 4.6891 loss: 0.8418 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0522 loss_cls: 0.2396 acc: 90.6738 loss_bbox: 0.2542 loss_mask: 0.2641 +2024/10/28 02:40:44 - mmengine - INFO - Epoch(train) [4][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:31:08 time: 0.4896 data_time: 0.0640 memory: 6229 grad_norm: 4.7078 loss: 0.9561 loss_rpn_cls: 0.0437 loss_rpn_bbox: 0.0596 loss_cls: 0.2792 acc: 92.1875 loss_bbox: 0.2906 loss_mask: 0.2830 +2024/10/28 02:41:08 - mmengine - INFO - Epoch(train) [4][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:30:12 time: 0.4741 data_time: 0.0519 memory: 6152 grad_norm: 4.5482 loss: 0.8893 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0493 loss_cls: 0.2555 acc: 94.5312 loss_bbox: 0.2776 loss_mask: 0.2734 +2024/10/28 02:41:32 - mmengine - INFO - Epoch(train) [4][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:29:17 time: 0.4742 data_time: 0.0453 memory: 6055 grad_norm: 4.8084 loss: 0.7789 loss_rpn_cls: 0.0256 loss_rpn_bbox: 0.0414 loss_cls: 0.2158 acc: 95.9473 loss_bbox: 0.2355 loss_mask: 0.2606 +2024/10/28 02:41:56 - mmengine - INFO - Epoch(train) [4][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:28:23 time: 0.4938 data_time: 0.0539 memory: 6288 grad_norm: 4.6400 loss: 0.8669 loss_rpn_cls: 0.0388 loss_rpn_bbox: 0.0496 loss_cls: 0.2495 acc: 90.8691 loss_bbox: 0.2565 loss_mask: 0.2726 +2024/10/28 02:42:20 - mmengine - INFO - Epoch(train) [4][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:27:29 time: 0.4821 data_time: 0.0492 memory: 6028 grad_norm: 4.5762 loss: 0.8665 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0450 loss_cls: 0.2532 acc: 96.9727 loss_bbox: 0.2573 loss_mask: 0.2777 +2024/10/28 02:42:44 - mmengine - INFO - Epoch(train) [4][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:26:34 time: 0.4742 data_time: 0.0468 memory: 6259 grad_norm: 4.5328 loss: 0.8669 loss_rpn_cls: 0.0348 loss_rpn_bbox: 0.0507 loss_cls: 0.2527 acc: 93.0176 loss_bbox: 0.2566 loss_mask: 0.2723 +2024/10/28 02:43:08 - mmengine - INFO - Epoch(train) [4][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:25:39 time: 0.4798 data_time: 0.0507 memory: 6115 grad_norm: 4.9664 loss: 0.8886 loss_rpn_cls: 0.0419 loss_rpn_bbox: 0.0550 loss_cls: 0.2525 acc: 95.6543 loss_bbox: 0.2664 loss_mask: 0.2728 +2024/10/28 02:43:32 - mmengine - INFO - Epoch(train) [4][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:24:44 time: 0.4755 data_time: 0.0437 memory: 6032 grad_norm: 4.6590 loss: 0.8405 loss_rpn_cls: 0.0413 loss_rpn_bbox: 0.0460 loss_cls: 0.2352 acc: 86.8164 loss_bbox: 0.2419 loss_mask: 0.2761 +2024/10/28 02:43:56 - mmengine - INFO - Epoch(train) [4][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:23:51 time: 0.4845 data_time: 0.0504 memory: 6188 grad_norm: 4.7193 loss: 0.9380 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0530 loss_cls: 0.2776 acc: 90.9180 loss_bbox: 0.2828 loss_mask: 0.2855 +2024/10/28 02:44:20 - mmengine - INFO - Epoch(train) [4][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:22:57 time: 0.4820 data_time: 0.0569 memory: 6328 grad_norm: 4.6622 loss: 0.9571 loss_rpn_cls: 0.0386 loss_rpn_bbox: 0.0582 loss_cls: 0.2770 acc: 89.8438 loss_bbox: 0.2986 loss_mask: 0.2847 +2024/10/28 02:44:25 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 02:44:44 - mmengine - INFO - Epoch(train) [4][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:22:02 time: 0.4723 data_time: 0.0469 memory: 6020 grad_norm: 4.5727 loss: 0.8287 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0436 loss_cls: 0.2423 acc: 89.7461 loss_bbox: 0.2462 loss_mask: 0.2677 +2024/10/28 02:45:08 - mmengine - INFO - Epoch(train) [4][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:21:08 time: 0.4830 data_time: 0.0427 memory: 6127 grad_norm: 4.6437 loss: 0.8307 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0426 loss_cls: 0.2488 acc: 92.2363 loss_bbox: 0.2422 loss_mask: 0.2679 +2024/10/28 02:45:32 - mmengine - INFO - Epoch(train) [4][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:20:15 time: 0.4833 data_time: 0.0509 memory: 6215 grad_norm: 4.6864 loss: 0.8655 loss_rpn_cls: 0.0383 loss_rpn_bbox: 0.0506 loss_cls: 0.2467 acc: 86.8164 loss_bbox: 0.2599 loss_mask: 0.2699 +2024/10/28 02:45:56 - mmengine - INFO - Epoch(train) [4][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:19:21 time: 0.4753 data_time: 0.0484 memory: 6217 grad_norm: 4.4686 loss: 0.8215 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0502 loss_cls: 0.2259 acc: 83.9355 loss_bbox: 0.2423 loss_mask: 0.2697 +2024/10/28 02:46:20 - mmengine - INFO - Epoch(train) [4][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:18:27 time: 0.4752 data_time: 0.0494 memory: 6162 grad_norm: 4.4346 loss: 0.8271 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0470 loss_cls: 0.2412 acc: 89.3066 loss_bbox: 0.2450 loss_mask: 0.2607 +2024/10/28 02:46:44 - mmengine - INFO - Epoch(train) [4][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:17:35 time: 0.4916 data_time: 0.0563 memory: 6285 grad_norm: 4.8088 loss: 0.9361 loss_rpn_cls: 0.0377 loss_rpn_bbox: 0.0560 loss_cls: 0.2701 acc: 94.1406 loss_bbox: 0.2884 loss_mask: 0.2838 +2024/10/28 02:47:08 - mmengine - INFO - Epoch(train) [4][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:16:41 time: 0.4731 data_time: 0.0495 memory: 6188 grad_norm: 4.8022 loss: 0.8857 loss_rpn_cls: 0.0411 loss_rpn_bbox: 0.0523 loss_cls: 0.2623 acc: 83.7402 loss_bbox: 0.2579 loss_mask: 0.2721 +2024/10/28 02:47:33 - mmengine - INFO - Epoch(train) [4][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:15:49 time: 0.4936 data_time: 0.0518 memory: 6129 grad_norm: 4.7348 loss: 0.8922 loss_rpn_cls: 0.0351 loss_rpn_bbox: 0.0495 loss_cls: 0.2526 acc: 90.4785 loss_bbox: 0.2741 loss_mask: 0.2809 +2024/10/28 02:47:57 - mmengine - INFO - Epoch(train) [4][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:14:56 time: 0.4814 data_time: 0.0451 memory: 6223 grad_norm: 4.6135 loss: 0.8396 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0449 loss_cls: 0.2398 acc: 93.7500 loss_bbox: 0.2523 loss_mask: 0.2684 +2024/10/28 02:48:21 - mmengine - INFO - Epoch(train) [4][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:14:05 time: 0.4912 data_time: 0.0492 memory: 6356 grad_norm: 4.4424 loss: 0.8341 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0421 loss_cls: 0.2465 acc: 95.0195 loss_bbox: 0.2523 loss_mask: 0.2628 +2024/10/28 02:48:46 - mmengine - INFO - Epoch(train) [4][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:13:12 time: 0.4848 data_time: 0.0485 memory: 6300 grad_norm: 4.8428 loss: 0.8269 loss_rpn_cls: 0.0291 loss_rpn_bbox: 0.0442 loss_cls: 0.2392 acc: 91.3574 loss_bbox: 0.2477 loss_mask: 0.2668 +2024/10/28 02:49:09 - mmengine - INFO - Epoch(train) [4][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:12:19 time: 0.4718 data_time: 0.0501 memory: 6353 grad_norm: 4.7858 loss: 0.8906 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0477 loss_cls: 0.2611 acc: 85.2539 loss_bbox: 0.2700 loss_mask: 0.2733 +2024/10/28 02:49:33 - mmengine - INFO - Epoch(train) [4][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:11:26 time: 0.4821 data_time: 0.0457 memory: 6160 grad_norm: 4.7368 loss: 0.8639 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0442 loss_cls: 0.2524 acc: 94.5801 loss_bbox: 0.2594 loss_mask: 0.2773 +2024/10/28 02:49:58 - mmengine - INFO - Epoch(train) [4][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:10:36 time: 0.4958 data_time: 0.0553 memory: 6280 grad_norm: 4.6360 loss: 0.8814 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0563 loss_cls: 0.2548 acc: 90.4785 loss_bbox: 0.2617 loss_mask: 0.2708 +2024/10/28 02:50:23 - mmengine - INFO - Epoch(train) [4][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:09:45 time: 0.4922 data_time: 0.0485 memory: 6195 grad_norm: 4.5455 loss: 0.8781 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0473 loss_cls: 0.2618 acc: 93.9453 loss_bbox: 0.2641 loss_mask: 0.2694 +2024/10/28 02:50:47 - mmengine - INFO - Epoch(train) [4][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:08:53 time: 0.4848 data_time: 0.0443 memory: 6139 grad_norm: 4.7784 loss: 0.8318 loss_rpn_cls: 0.0351 loss_rpn_bbox: 0.0433 loss_cls: 0.2427 acc: 90.7715 loss_bbox: 0.2493 loss_mask: 0.2614 +2024/10/28 02:51:12 - mmengine - INFO - Epoch(train) [4][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:08:03 time: 0.4982 data_time: 0.0542 memory: 6248 grad_norm: 4.6094 loss: 0.8770 loss_rpn_cls: 0.0381 loss_rpn_bbox: 0.0524 loss_cls: 0.2509 acc: 91.9434 loss_bbox: 0.2687 loss_mask: 0.2669 +2024/10/28 02:51:36 - mmengine - INFO - Epoch(train) [4][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:07:13 time: 0.4926 data_time: 0.0455 memory: 6135 grad_norm: 4.6995 loss: 0.8591 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0525 loss_cls: 0.2448 acc: 93.5547 loss_bbox: 0.2561 loss_mask: 0.2691 +2024/10/28 02:52:01 - mmengine - INFO - Epoch(train) [4][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:06:22 time: 0.4945 data_time: 0.0564 memory: 6217 grad_norm: 4.6361 loss: 0.8475 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0480 loss_cls: 0.2472 acc: 93.8477 loss_bbox: 0.2530 loss_mask: 0.2673 +2024/10/28 02:52:26 - mmengine - INFO - Epoch(train) [4][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:05:33 time: 0.5043 data_time: 0.0509 memory: 6260 grad_norm: 4.5776 loss: 0.8837 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0524 loss_cls: 0.2569 acc: 88.4766 loss_bbox: 0.2661 loss_mask: 0.2731 +2024/10/28 02:52:31 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 02:52:51 - mmengine - INFO - Epoch(train) [4][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:04:44 time: 0.4989 data_time: 0.0460 memory: 6211 grad_norm: 5.3804 loss: 0.8577 loss_rpn_cls: 0.0403 loss_rpn_bbox: 0.0444 loss_cls: 0.2484 acc: 95.8008 loss_bbox: 0.2505 loss_mask: 0.2741 +2024/10/28 02:53:16 - mmengine - INFO - Epoch(train) [4][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:03:53 time: 0.4859 data_time: 0.0465 memory: 6190 grad_norm: 4.5125 loss: 0.8423 loss_rpn_cls: 0.0351 loss_rpn_bbox: 0.0441 loss_cls: 0.2584 acc: 92.3828 loss_bbox: 0.2474 loss_mask: 0.2573 +2024/10/28 02:53:40 - mmengine - INFO - Epoch(train) [4][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:03:03 time: 0.4956 data_time: 0.0478 memory: 6216 grad_norm: 4.5298 loss: 0.8517 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0469 loss_cls: 0.2409 acc: 95.8496 loss_bbox: 0.2652 loss_mask: 0.2682 +2024/10/28 02:54:05 - mmengine - INFO - Epoch(train) [4][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:02:13 time: 0.4946 data_time: 0.0515 memory: 6059 grad_norm: 4.5651 loss: 0.8922 loss_rpn_cls: 0.0336 loss_rpn_bbox: 0.0495 loss_cls: 0.2609 acc: 94.3848 loss_bbox: 0.2670 loss_mask: 0.2813 +2024/10/28 02:54:30 - mmengine - INFO - Epoch(train) [4][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:01:24 time: 0.5007 data_time: 0.0588 memory: 6410 grad_norm: 4.5628 loss: 0.8717 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0498 loss_cls: 0.2479 acc: 95.6055 loss_bbox: 0.2605 loss_mask: 0.2812 +2024/10/28 02:54:55 - mmengine - INFO - Epoch(train) [4][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 11:00:35 time: 0.4914 data_time: 0.0578 memory: 6275 grad_norm: 4.3684 loss: 0.9669 loss_rpn_cls: 0.0411 loss_rpn_bbox: 0.0596 loss_cls: 0.2853 acc: 92.0898 loss_bbox: 0.2937 loss_mask: 0.2872 +2024/10/28 02:55:19 - mmengine - INFO - Epoch(train) [4][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:59:44 time: 0.4897 data_time: 0.0468 memory: 6291 grad_norm: 4.5913 loss: 0.8758 loss_rpn_cls: 0.0358 loss_rpn_bbox: 0.0496 loss_cls: 0.2486 acc: 94.3359 loss_bbox: 0.2655 loss_mask: 0.2762 +2024/10/28 02:55:44 - mmengine - INFO - Epoch(train) [4][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:58:55 time: 0.4907 data_time: 0.0395 memory: 6253 grad_norm: 4.3551 loss: 0.8300 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0440 loss_cls: 0.2437 acc: 92.2363 loss_bbox: 0.2507 loss_mask: 0.2631 +2024/10/28 02:56:08 - mmengine - INFO - Epoch(train) [4][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:58:05 time: 0.4935 data_time: 0.0359 memory: 6217 grad_norm: 4.7505 loss: 0.7975 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0429 loss_cls: 0.2356 acc: 97.2168 loss_bbox: 0.2300 loss_mask: 0.2571 +2024/10/28 02:56:32 - mmengine - INFO - Epoch(train) [4][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:57:14 time: 0.4798 data_time: 0.0387 memory: 6148 grad_norm: 4.4538 loss: 0.8367 loss_rpn_cls: 0.0349 loss_rpn_bbox: 0.0492 loss_cls: 0.2381 acc: 91.9922 loss_bbox: 0.2432 loss_mask: 0.2712 +2024/10/28 02:56:57 - mmengine - INFO - Epoch(train) [4][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:56:25 time: 0.4927 data_time: 0.0466 memory: 6098 grad_norm: 4.3924 loss: 0.8051 loss_rpn_cls: 0.0284 loss_rpn_bbox: 0.0471 loss_cls: 0.2338 acc: 90.6250 loss_bbox: 0.2366 loss_mask: 0.2592 +2024/10/28 02:57:22 - mmengine - INFO - Epoch(train) [4][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:55:35 time: 0.4892 data_time: 0.0425 memory: 6266 grad_norm: 4.5962 loss: 0.8745 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0470 loss_cls: 0.2522 acc: 96.0938 loss_bbox: 0.2618 loss_mask: 0.2808 +2024/10/28 02:57:45 - mmengine - INFO - Epoch(train) [4][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:54:44 time: 0.4741 data_time: 0.0473 memory: 6223 grad_norm: 4.7583 loss: 0.8592 loss_rpn_cls: 0.0403 loss_rpn_bbox: 0.0525 loss_cls: 0.2435 acc: 92.9199 loss_bbox: 0.2513 loss_mask: 0.2716 +2024/10/28 02:58:10 - mmengine - INFO - Epoch(train) [4][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:53:55 time: 0.4911 data_time: 0.0410 memory: 6201 grad_norm: 4.5241 loss: 0.8783 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0478 loss_cls: 0.2523 acc: 94.8730 loss_bbox: 0.2581 loss_mask: 0.2796 +2024/10/28 02:58:34 - mmengine - INFO - Epoch(train) [4][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:53:06 time: 0.4886 data_time: 0.0366 memory: 6173 grad_norm: 4.5878 loss: 0.8052 loss_rpn_cls: 0.0291 loss_rpn_bbox: 0.0440 loss_cls: 0.2395 acc: 93.7500 loss_bbox: 0.2390 loss_mask: 0.2536 +2024/10/28 02:59:00 - mmengine - INFO - Epoch(train) [4][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:52:18 time: 0.5073 data_time: 0.0448 memory: 6176 grad_norm: 4.5196 loss: 0.8234 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0400 loss_cls: 0.2423 acc: 91.6504 loss_bbox: 0.2468 loss_mask: 0.2648 +2024/10/28 02:59:24 - mmengine - INFO - Epoch(train) [4][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:51:29 time: 0.4843 data_time: 0.0439 memory: 6419 grad_norm: 4.4769 loss: 0.8515 loss_rpn_cls: 0.0349 loss_rpn_bbox: 0.0500 loss_cls: 0.2508 acc: 96.4844 loss_bbox: 0.2538 loss_mask: 0.2621 +2024/10/28 02:59:48 - mmengine - INFO - Epoch(train) [4][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:50:40 time: 0.4932 data_time: 0.0586 memory: 6328 grad_norm: 4.6206 loss: 0.8986 loss_rpn_cls: 0.0408 loss_rpn_bbox: 0.0498 loss_cls: 0.2602 acc: 89.6484 loss_bbox: 0.2760 loss_mask: 0.2719 +2024/10/28 03:00:13 - mmengine - INFO - Epoch(train) [4][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:49:52 time: 0.4945 data_time: 0.0524 memory: 6137 grad_norm: 4.3242 loss: 0.8616 loss_rpn_cls: 0.0349 loss_rpn_bbox: 0.0458 loss_cls: 0.2501 acc: 92.5293 loss_bbox: 0.2644 loss_mask: 0.2664 +2024/10/28 03:00:38 - mmengine - INFO - Epoch(train) [4][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:49:03 time: 0.4907 data_time: 0.0539 memory: 6382 grad_norm: 4.4724 loss: 0.8513 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0484 loss_cls: 0.2427 acc: 95.7031 loss_bbox: 0.2583 loss_mask: 0.2695 +2024/10/28 03:00:42 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 03:01:02 - mmengine - INFO - Epoch(train) [4][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:48:14 time: 0.4877 data_time: 0.0549 memory: 6370 grad_norm: 4.5324 loss: 0.8725 loss_rpn_cls: 0.0384 loss_rpn_bbox: 0.0535 loss_cls: 0.2451 acc: 94.2871 loss_bbox: 0.2657 loss_mask: 0.2697 +2024/10/28 03:01:29 - mmengine - INFO - Epoch(train) [4][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:47:31 time: 0.5399 data_time: 0.1081 memory: 6194 grad_norm: 4.5864 loss: 0.8592 loss_rpn_cls: 0.0429 loss_rpn_bbox: 0.0526 loss_cls: 0.2443 acc: 91.0156 loss_bbox: 0.2456 loss_mask: 0.2739 +2024/10/28 03:01:54 - mmengine - INFO - Epoch(train) [4][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:46:43 time: 0.4927 data_time: 0.0494 memory: 6234 grad_norm: 4.6512 loss: 0.8164 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0439 loss_cls: 0.2266 acc: 84.5703 loss_bbox: 0.2461 loss_mask: 0.2669 +2024/10/28 03:02:19 - mmengine - INFO - Epoch(train) [4][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:45:55 time: 0.4953 data_time: 0.0517 memory: 6305 grad_norm: 4.7784 loss: 0.8941 loss_rpn_cls: 0.0402 loss_rpn_bbox: 0.0520 loss_cls: 0.2561 acc: 89.0137 loss_bbox: 0.2658 loss_mask: 0.2800 +2024/10/28 03:02:43 - mmengine - INFO - Epoch(train) [4][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:45:06 time: 0.4813 data_time: 0.0479 memory: 6109 grad_norm: 4.5255 loss: 0.8262 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0470 loss_cls: 0.2306 acc: 99.2676 loss_bbox: 0.2328 loss_mask: 0.2755 +2024/10/28 03:03:07 - mmengine - INFO - Epoch(train) [4][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:44:18 time: 0.4920 data_time: 0.0505 memory: 6108 grad_norm: 4.5176 loss: 0.8567 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0501 loss_cls: 0.2489 acc: 93.0176 loss_bbox: 0.2571 loss_mask: 0.2680 +2024/10/28 03:03:31 - mmengine - INFO - Epoch(train) [4][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:43:29 time: 0.4853 data_time: 0.0588 memory: 6302 grad_norm: 4.4858 loss: 0.9396 loss_rpn_cls: 0.0370 loss_rpn_bbox: 0.0572 loss_cls: 0.2831 acc: 96.2891 loss_bbox: 0.2787 loss_mask: 0.2837 +2024/10/28 03:03:56 - mmengine - INFO - Epoch(train) [4][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:42:40 time: 0.4843 data_time: 0.0502 memory: 6294 grad_norm: 4.5418 loss: 0.8530 loss_rpn_cls: 0.0346 loss_rpn_bbox: 0.0478 loss_cls: 0.2417 acc: 88.6230 loss_bbox: 0.2601 loss_mask: 0.2688 +2024/10/28 03:04:20 - mmengine - INFO - Epoch(train) [4][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:41:51 time: 0.4800 data_time: 0.0455 memory: 6056 grad_norm: 4.6337 loss: 0.8347 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0470 loss_cls: 0.2418 acc: 91.7969 loss_bbox: 0.2452 loss_mask: 0.2705 +2024/10/28 03:04:45 - mmengine - INFO - Epoch(train) [4][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:41:05 time: 0.5022 data_time: 0.0530 memory: 6231 grad_norm: 4.3571 loss: 0.8703 loss_rpn_cls: 0.0349 loss_rpn_bbox: 0.0500 loss_cls: 0.2424 acc: 90.3809 loss_bbox: 0.2570 loss_mask: 0.2860 +2024/10/28 03:05:09 - mmengine - INFO - Epoch(train) [4][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:40:17 time: 0.4899 data_time: 0.0497 memory: 6199 grad_norm: 4.5721 loss: 0.9079 loss_rpn_cls: 0.0381 loss_rpn_bbox: 0.0522 loss_cls: 0.2641 acc: 91.2598 loss_bbox: 0.2748 loss_mask: 0.2787 +2024/10/28 03:05:34 - mmengine - INFO - Epoch(train) [4][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:39:30 time: 0.4947 data_time: 0.0450 memory: 6164 grad_norm: 4.5293 loss: 0.8490 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0452 loss_cls: 0.2421 acc: 92.8711 loss_bbox: 0.2599 loss_mask: 0.2689 +2024/10/28 03:05:58 - mmengine - INFO - Epoch(train) [4][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:38:42 time: 0.4877 data_time: 0.0497 memory: 6204 grad_norm: 4.4966 loss: 0.8597 loss_rpn_cls: 0.0401 loss_rpn_bbox: 0.0505 loss_cls: 0.2487 acc: 95.9473 loss_bbox: 0.2472 loss_mask: 0.2732 +2024/10/28 03:06:23 - mmengine - INFO - Epoch(train) [4][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:37:54 time: 0.4906 data_time: 0.0496 memory: 6400 grad_norm: 4.5016 loss: 0.8641 loss_rpn_cls: 0.0338 loss_rpn_bbox: 0.0509 loss_cls: 0.2503 acc: 93.1152 loss_bbox: 0.2571 loss_mask: 0.2721 +2024/10/28 03:06:48 - mmengine - INFO - Epoch(train) [4][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:37:07 time: 0.4970 data_time: 0.0554 memory: 6420 grad_norm: 4.4184 loss: 0.9317 loss_rpn_cls: 0.0431 loss_rpn_bbox: 0.0555 loss_cls: 0.2740 acc: 94.0430 loss_bbox: 0.2792 loss_mask: 0.2798 +2024/10/28 03:07:12 - mmengine - INFO - Epoch(train) [4][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:36:20 time: 0.4932 data_time: 0.0497 memory: 6139 grad_norm: 4.4037 loss: 0.8478 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0536 loss_cls: 0.2411 acc: 91.7480 loss_bbox: 0.2538 loss_mask: 0.2657 +2024/10/28 03:07:36 - mmengine - INFO - Epoch(train) [4][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:35:32 time: 0.4789 data_time: 0.0456 memory: 6333 grad_norm: 4.6920 loss: 0.8486 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0468 loss_cls: 0.2510 acc: 92.3828 loss_bbox: 0.2519 loss_mask: 0.2657 +2024/10/28 03:08:01 - mmengine - INFO - Epoch(train) [4][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:34:44 time: 0.4840 data_time: 0.0563 memory: 6209 grad_norm: 4.7064 loss: 0.8696 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0524 loss_cls: 0.2435 acc: 91.6992 loss_bbox: 0.2655 loss_mask: 0.2678 +2024/10/28 03:08:24 - mmengine - INFO - Epoch(train) [4][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:55 time: 0.4772 data_time: 0.0494 memory: 6309 grad_norm: 4.5609 loss: 0.8517 loss_rpn_cls: 0.0350 loss_rpn_bbox: 0.0476 loss_cls: 0.2421 acc: 94.0430 loss_bbox: 0.2569 loss_mask: 0.2701 +2024/10/28 03:08:49 - mmengine - INFO - Epoch(train) [4][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:33:09 time: 0.4962 data_time: 0.0574 memory: 6164 grad_norm: 4.4740 loss: 0.9450 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0565 loss_cls: 0.2861 acc: 89.5020 loss_bbox: 0.2902 loss_mask: 0.2761 +2024/10/28 03:08:54 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 03:09:14 - mmengine - INFO - Epoch(train) [4][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:32:23 time: 0.5034 data_time: 0.0544 memory: 6116 grad_norm: 4.8374 loss: 0.8955 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0505 loss_cls: 0.2621 acc: 91.8945 loss_bbox: 0.2678 loss_mask: 0.2771 +2024/10/28 03:09:39 - mmengine - INFO - Epoch(train) [4][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:31:36 time: 0.4899 data_time: 0.0569 memory: 6404 grad_norm: 4.3627 loss: 0.8557 loss_rpn_cls: 0.0385 loss_rpn_bbox: 0.0468 loss_cls: 0.2461 acc: 96.3379 loss_bbox: 0.2486 loss_mask: 0.2757 +2024/10/28 03:10:03 - mmengine - INFO - Epoch(train) [4][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:30:49 time: 0.4842 data_time: 0.0450 memory: 6193 grad_norm: 4.3666 loss: 0.8230 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0476 loss_cls: 0.2328 acc: 91.0156 loss_bbox: 0.2416 loss_mask: 0.2686 +2024/10/28 03:10:30 - mmengine - INFO - Epoch(train) [4][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:30:07 time: 0.5348 data_time: 0.0948 memory: 6219 grad_norm: 4.6145 loss: 0.8500 loss_rpn_cls: 0.0376 loss_rpn_bbox: 0.0476 loss_cls: 0.2470 acc: 87.2070 loss_bbox: 0.2426 loss_mask: 0.2752 +2024/10/28 03:10:54 - mmengine - INFO - Epoch(train) [4][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:29:19 time: 0.4746 data_time: 0.0461 memory: 6189 grad_norm: 4.5450 loss: 0.9041 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0481 loss_cls: 0.2714 acc: 90.3320 loss_bbox: 0.2801 loss_mask: 0.2694 +2024/10/28 03:11:18 - mmengine - INFO - Epoch(train) [4][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:28:31 time: 0.4783 data_time: 0.0460 memory: 6331 grad_norm: 4.3313 loss: 0.8227 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0420 loss_cls: 0.2429 acc: 88.8184 loss_bbox: 0.2510 loss_mask: 0.2625 +2024/10/28 03:11:41 - mmengine - INFO - Epoch(train) [4][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:27:42 time: 0.4717 data_time: 0.0484 memory: 6217 grad_norm: 4.3250 loss: 0.8753 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0497 loss_cls: 0.2545 acc: 94.0430 loss_bbox: 0.2553 loss_mask: 0.2770 +2024/10/28 03:12:06 - mmengine - INFO - Epoch(train) [4][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:26:56 time: 0.4946 data_time: 0.0501 memory: 6233 grad_norm: 4.4531 loss: 0.8890 loss_rpn_cls: 0.0433 loss_rpn_bbox: 0.0517 loss_cls: 0.2502 acc: 96.9238 loss_bbox: 0.2660 loss_mask: 0.2778 +2024/10/28 03:12:31 - mmengine - INFO - Epoch(train) [4][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:26:11 time: 0.5004 data_time: 0.0617 memory: 6238 grad_norm: 4.6024 loss: 0.8667 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0521 loss_cls: 0.2467 acc: 96.2402 loss_bbox: 0.2694 loss_mask: 0.2630 +2024/10/28 03:12:56 - mmengine - INFO - Epoch(train) [4][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:25:25 time: 0.4975 data_time: 0.0502 memory: 6225 grad_norm: 4.6307 loss: 0.8908 loss_rpn_cls: 0.0346 loss_rpn_bbox: 0.0528 loss_cls: 0.2602 acc: 89.9902 loss_bbox: 0.2650 loss_mask: 0.2782 +2024/10/28 03:13:20 - mmengine - INFO - Epoch(train) [4][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:24:38 time: 0.4792 data_time: 0.0487 memory: 6217 grad_norm: 4.7891 loss: 0.8835 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0470 loss_cls: 0.2578 acc: 93.1641 loss_bbox: 0.2724 loss_mask: 0.2729 +2024/10/28 03:13:44 - mmengine - INFO - Epoch(train) [4][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:23:51 time: 0.4834 data_time: 0.0501 memory: 6259 grad_norm: 4.4618 loss: 0.9021 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0533 loss_cls: 0.2519 acc: 92.8223 loss_bbox: 0.2776 loss_mask: 0.2806 +2024/10/28 03:14:08 - mmengine - INFO - Epoch(train) [4][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:23:05 time: 0.4889 data_time: 0.0459 memory: 6279 grad_norm: 4.4201 loss: 0.7959 loss_rpn_cls: 0.0356 loss_rpn_bbox: 0.0450 loss_cls: 0.2235 acc: 90.1367 loss_bbox: 0.2360 loss_mask: 0.2557 +2024/10/28 03:14:32 - mmengine - INFO - Epoch(train) [4][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:22:18 time: 0.4821 data_time: 0.0499 memory: 6372 grad_norm: 4.3967 loss: 0.8616 loss_rpn_cls: 0.0401 loss_rpn_bbox: 0.0471 loss_cls: 0.2436 acc: 91.1133 loss_bbox: 0.2579 loss_mask: 0.2729 +2024/10/28 03:14:56 - mmengine - INFO - Epoch(train) [4][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:21:31 time: 0.4784 data_time: 0.0435 memory: 6119 grad_norm: 4.6021 loss: 0.8395 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0447 loss_cls: 0.2402 acc: 91.7969 loss_bbox: 0.2488 loss_mask: 0.2751 +2024/10/28 03:15:21 - mmengine - INFO - Epoch(train) [4][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:20:45 time: 0.4894 data_time: 0.0562 memory: 6221 grad_norm: 4.4510 loss: 0.8979 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0461 loss_cls: 0.2637 acc: 89.7949 loss_bbox: 0.2727 loss_mask: 0.2835 +2024/10/28 03:15:46 - mmengine - INFO - Epoch(train) [4][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:20:00 time: 0.4932 data_time: 0.0497 memory: 6197 grad_norm: 4.4396 loss: 0.8386 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0495 loss_cls: 0.2490 acc: 92.0898 loss_bbox: 0.2469 loss_mask: 0.2611 +2024/10/28 03:16:11 - mmengine - INFO - Epoch(train) [4][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:19:15 time: 0.5016 data_time: 0.0688 memory: 6286 grad_norm: 4.4844 loss: 0.8718 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0492 loss_cls: 0.2547 acc: 89.6973 loss_bbox: 0.2645 loss_mask: 0.2680 +2024/10/28 03:16:35 - mmengine - INFO - Epoch(train) [4][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:18:30 time: 0.4880 data_time: 0.0535 memory: 6335 grad_norm: 4.5601 loss: 0.8654 loss_rpn_cls: 0.0309 loss_rpn_bbox: 0.0527 loss_cls: 0.2497 acc: 93.5059 loss_bbox: 0.2599 loss_mask: 0.2721 +2024/10/28 03:16:59 - mmengine - INFO - Epoch(train) [4][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:17:43 time: 0.4781 data_time: 0.0497 memory: 6067 grad_norm: 4.6395 loss: 0.8490 loss_rpn_cls: 0.0345 loss_rpn_bbox: 0.0511 loss_cls: 0.2434 acc: 85.5957 loss_bbox: 0.2505 loss_mask: 0.2695 +2024/10/28 03:17:04 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 03:17:23 - mmengine - INFO - Epoch(train) [4][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:16:57 time: 0.4830 data_time: 0.0521 memory: 6099 grad_norm: 4.3780 loss: 0.8668 loss_rpn_cls: 0.0395 loss_rpn_bbox: 0.0538 loss_cls: 0.2487 acc: 89.3066 loss_bbox: 0.2546 loss_mask: 0.2701 +2024/10/28 03:17:47 - mmengine - INFO - Epoch(train) [4][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:16:11 time: 0.4862 data_time: 0.0527 memory: 6181 grad_norm: 4.5623 loss: 0.8900 loss_rpn_cls: 0.0412 loss_rpn_bbox: 0.0504 loss_cls: 0.2610 acc: 90.3320 loss_bbox: 0.2565 loss_mask: 0.2809 +2024/10/28 03:18:12 - mmengine - INFO - Epoch(train) [4][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:15:26 time: 0.4971 data_time: 0.0584 memory: 6351 grad_norm: 4.5518 loss: 0.8252 loss_rpn_cls: 0.0352 loss_rpn_bbox: 0.0458 loss_cls: 0.2333 acc: 90.4785 loss_bbox: 0.2428 loss_mask: 0.2680 +2024/10/28 03:18:37 - mmengine - INFO - Epoch(train) [4][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:14:42 time: 0.5016 data_time: 0.0593 memory: 6306 grad_norm: 4.6801 loss: 0.8701 loss_rpn_cls: 0.0345 loss_rpn_bbox: 0.0448 loss_cls: 0.2475 acc: 93.7988 loss_bbox: 0.2667 loss_mask: 0.2767 +2024/10/28 03:19:02 - mmengine - INFO - Epoch(train) [4][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:13:57 time: 0.4928 data_time: 0.0524 memory: 6231 grad_norm: 4.5365 loss: 0.8409 loss_rpn_cls: 0.0322 loss_rpn_bbox: 0.0509 loss_cls: 0.2389 acc: 97.8516 loss_bbox: 0.2551 loss_mask: 0.2639 +2024/10/28 03:19:30 - mmengine - INFO - Epoch(train) [4][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:13:18 time: 0.5518 data_time: 0.1149 memory: 6303 grad_norm: 4.4687 loss: 0.8334 loss_rpn_cls: 0.0338 loss_rpn_bbox: 0.0487 loss_cls: 0.2361 acc: 92.8711 loss_bbox: 0.2373 loss_mask: 0.2775 +2024/10/28 03:19:44 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 03:19:44 - mmengine - INFO - Saving checkpoint at 4 epochs +2024/10/28 03:19:55 - mmengine - INFO - Epoch(val) [4][ 50/1250] eta: 0:02:17 time: 0.1143 data_time: 0.0053 memory: 6923 +2024/10/28 03:20:01 - mmengine - INFO - Epoch(val) [4][ 100/1250] eta: 0:02:10 time: 0.1133 data_time: 0.0038 memory: 1114 +2024/10/28 03:20:07 - mmengine - INFO - Epoch(val) [4][ 150/1250] eta: 0:02:05 time: 0.1141 data_time: 0.0039 memory: 1114 +2024/10/28 03:20:13 - mmengine - INFO - Epoch(val) [4][ 200/1250] eta: 0:02:01 time: 0.1201 data_time: 0.0052 memory: 1149 +2024/10/28 03:20:19 - mmengine - INFO - Epoch(val) [4][ 250/1250] eta: 0:01:55 time: 0.1138 data_time: 0.0038 memory: 1221 +2024/10/28 03:20:24 - mmengine - INFO - Epoch(val) [4][ 300/1250] eta: 0:01:49 time: 0.1147 data_time: 0.0044 memory: 1114 +2024/10/28 03:20:30 - mmengine - INFO - Epoch(val) [4][ 350/1250] eta: 0:01:43 time: 0.1130 data_time: 0.0035 memory: 1117 +2024/10/28 03:20:35 - mmengine - INFO - Epoch(val) [4][ 400/1250] eta: 0:01:37 time: 0.1111 data_time: 0.0035 memory: 1114 +2024/10/28 03:20:41 - mmengine - INFO - Epoch(val) [4][ 450/1250] eta: 0:01:31 time: 0.1106 data_time: 0.0032 memory: 1114 +2024/10/28 03:20:47 - mmengine - INFO - Epoch(val) [4][ 500/1250] eta: 0:01:25 time: 0.1131 data_time: 0.0041 memory: 1134 +2024/10/28 03:20:52 - mmengine - INFO - Epoch(val) [4][ 550/1250] eta: 0:01:19 time: 0.1120 data_time: 0.0036 memory: 1176 +2024/10/28 03:20:58 - mmengine - INFO - Epoch(val) [4][ 600/1250] eta: 0:01:14 time: 0.1172 data_time: 0.0046 memory: 1114 +2024/10/28 03:21:04 - mmengine - INFO - Epoch(val) [4][ 650/1250] eta: 0:01:08 time: 0.1115 data_time: 0.0033 memory: 1219 +2024/10/28 03:21:10 - mmengine - INFO - Epoch(val) [4][ 700/1250] eta: 0:01:02 time: 0.1182 data_time: 0.0050 memory: 1219 +2024/10/28 03:21:16 - mmengine - INFO - Epoch(val) [4][ 750/1250] eta: 0:00:57 time: 0.1210 data_time: 0.0063 memory: 1114 +2024/10/28 03:21:21 - mmengine - INFO - Epoch(val) [4][ 800/1250] eta: 0:00:51 time: 0.1152 data_time: 0.0052 memory: 1136 +2024/10/28 03:21:27 - mmengine - INFO - Epoch(val) [4][ 850/1250] eta: 0:00:45 time: 0.1159 data_time: 0.0057 memory: 1176 +2024/10/28 03:21:33 - mmengine - INFO - Epoch(val) [4][ 900/1250] eta: 0:00:40 time: 0.1149 data_time: 0.0051 memory: 1114 +2024/10/28 03:21:39 - mmengine - INFO - Epoch(val) [4][ 950/1250] eta: 0:00:34 time: 0.1201 data_time: 0.0069 memory: 1219 +2024/10/28 03:21:45 - mmengine - INFO - Epoch(val) [4][1000/1250] eta: 0:00:28 time: 0.1129 data_time: 0.0053 memory: 1081 +2024/10/28 03:21:51 - mmengine - INFO - Epoch(val) [4][1050/1250] eta: 0:00:23 time: 0.1225 data_time: 0.0068 memory: 1114 +2024/10/28 03:21:57 - mmengine - INFO - Epoch(val) [4][1100/1250] eta: 0:00:17 time: 0.1231 data_time: 0.0049 memory: 1114 +2024/10/28 03:22:03 - mmengine - INFO - Epoch(val) [4][1150/1250] eta: 0:00:11 time: 0.1192 data_time: 0.0073 memory: 1114 +2024/10/28 03:22:09 - mmengine - INFO - Epoch(val) [4][1200/1250] eta: 0:00:05 time: 0.1184 data_time: 0.0051 memory: 1176 +2024/10/28 03:22:15 - mmengine - INFO - Epoch(val) [4][1250/1250] eta: 0:00:00 time: 0.1268 data_time: 0.0053 memory: 1114 +2024/10/28 03:22:28 - mmengine - INFO - Evaluating bbox... +2024/10/28 03:23:04 - mmengine - INFO - bbox_mAP_copypaste: 0.311 0.517 0.337 0.156 0.346 0.422 +2024/10/28 03:23:04 - mmengine - INFO - Evaluating segm... +2024/10/28 03:23:44 - mmengine - INFO - segm_mAP_copypaste: 0.299 0.492 0.315 0.112 0.322 0.457 +2024/10/28 03:23:45 - mmengine - INFO - Epoch(val) [4][1250/1250] coco/bbox_mAP: 0.3110 coco/bbox_mAP_50: 0.5170 coco/bbox_mAP_75: 0.3370 coco/bbox_mAP_s: 0.1560 coco/bbox_mAP_m: 0.3460 coco/bbox_mAP_l: 0.4220 coco/segm_mAP: 0.2990 coco/segm_mAP_50: 0.4920 coco/segm_mAP_75: 0.3150 coco/segm_mAP_s: 0.1120 coco/segm_mAP_m: 0.3220 coco/segm_mAP_l: 0.4570 data_time: 0.0049 time: 0.1163 +2024/10/28 03:24:34 - mmengine - INFO - Epoch(train) [5][ 50/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:56 time: 0.9832 data_time: 0.0490 memory: 6348 grad_norm: 4.3070 loss: 0.8842 loss_rpn_cls: 0.0371 loss_rpn_bbox: 0.0508 loss_cls: 0.2517 acc: 87.9395 loss_bbox: 0.2746 loss_mask: 0.2700 +2024/10/28 03:25:17 - mmengine - INFO - Epoch(train) [5][ 100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:47 time: 0.8567 data_time: 0.0429 memory: 6136 grad_norm: 4.5246 loss: 0.8340 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0510 loss_cls: 0.2326 acc: 94.5801 loss_bbox: 0.2558 loss_mask: 0.2574 +2024/10/28 03:26:05 - mmengine - INFO - Epoch(train) [5][ 150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:48 time: 0.9571 data_time: 0.0509 memory: 6256 grad_norm: 4.3266 loss: 0.8975 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0535 loss_cls: 0.2457 acc: 87.9883 loss_bbox: 0.2811 loss_mask: 0.2806 +2024/10/28 03:26:55 - mmengine - INFO - Epoch(train) [5][ 200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:53 time: 0.9888 data_time: 0.0626 memory: 6221 grad_norm: 4.4363 loss: 0.8225 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0453 loss_cls: 0.2367 acc: 94.3359 loss_bbox: 0.2468 loss_mask: 0.2631 +2024/10/28 03:27:40 - mmengine - INFO - Epoch(train) [5][ 250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:49 time: 0.9115 data_time: 0.0498 memory: 6200 grad_norm: 4.4378 loss: 0.8314 loss_rpn_cls: 0.0288 loss_rpn_bbox: 0.0448 loss_cls: 0.2364 acc: 97.7539 loss_bbox: 0.2613 loss_mask: 0.2601 +2024/10/28 03:28:25 - mmengine - INFO - Epoch(train) [5][ 300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:44 time: 0.9025 data_time: 0.0429 memory: 6146 grad_norm: 4.5639 loss: 0.8502 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0466 loss_cls: 0.2470 acc: 93.5547 loss_bbox: 0.2600 loss_mask: 0.2674 +2024/10/28 03:29:10 - mmengine - INFO - Epoch(train) [5][ 350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:39 time: 0.9006 data_time: 0.0447 memory: 6226 grad_norm: 4.4803 loss: 0.7845 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0434 loss_cls: 0.2226 acc: 94.1406 loss_bbox: 0.2326 loss_mask: 0.2591 +2024/10/28 03:29:58 - mmengine - INFO - Epoch(train) [5][ 400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:40 time: 0.9561 data_time: 0.0504 memory: 6275 grad_norm: 4.7119 loss: 0.8641 loss_rpn_cls: 0.0347 loss_rpn_bbox: 0.0523 loss_cls: 0.2453 acc: 92.7246 loss_bbox: 0.2657 loss_mask: 0.2660 +2024/10/28 03:30:45 - mmengine - INFO - Epoch(train) [5][ 450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:38 time: 0.9384 data_time: 0.0446 memory: 6328 grad_norm: 4.5303 loss: 0.8169 loss_rpn_cls: 0.0298 loss_rpn_bbox: 0.0442 loss_cls: 0.2287 acc: 88.4766 loss_bbox: 0.2477 loss_mask: 0.2664 +2024/10/28 03:31:31 - mmengine - INFO - Epoch(train) [5][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:35 time: 0.9252 data_time: 0.0488 memory: 6146 grad_norm: 4.3651 loss: 0.8297 loss_rpn_cls: 0.0331 loss_rpn_bbox: 0.0449 loss_cls: 0.2331 acc: 86.6699 loss_bbox: 0.2544 loss_mask: 0.2642 +2024/10/28 03:32:17 - mmengine - INFO - Epoch(train) [5][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:32 time: 0.9230 data_time: 0.0458 memory: 6223 grad_norm: 4.5602 loss: 0.8660 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0498 loss_cls: 0.2472 acc: 90.8691 loss_bbox: 0.2642 loss_mask: 0.2734 +2024/10/28 03:33:02 - mmengine - INFO - Epoch(train) [5][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:25 time: 0.8822 data_time: 0.0447 memory: 6288 grad_norm: 4.3618 loss: 0.8198 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0478 loss_cls: 0.2307 acc: 95.2148 loss_bbox: 0.2493 loss_mask: 0.2617 +2024/10/28 03:33:50 - mmengine - INFO - Epoch(train) [5][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:25 time: 0.9692 data_time: 0.1313 memory: 6294 grad_norm: 4.3125 loss: 0.8360 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0450 loss_cls: 0.2317 acc: 92.9199 loss_bbox: 0.2600 loss_mask: 0.2672 +2024/10/28 03:34:16 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 03:34:36 - mmengine - INFO - Epoch(train) [5][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:21 time: 0.9127 data_time: 0.0450 memory: 6265 grad_norm: 4.4395 loss: 0.8097 loss_rpn_cls: 0.0276 loss_rpn_bbox: 0.0422 loss_cls: 0.2327 acc: 89.2578 loss_bbox: 0.2510 loss_mask: 0.2563 +2024/10/28 03:35:21 - mmengine - INFO - Epoch(train) [5][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:15 time: 0.9042 data_time: 0.0447 memory: 6182 grad_norm: 4.4904 loss: 0.8238 loss_rpn_cls: 0.0276 loss_rpn_bbox: 0.0418 loss_cls: 0.2332 acc: 92.5293 loss_bbox: 0.2534 loss_mask: 0.2679 +2024/10/28 03:36:08 - mmengine - INFO - Epoch(train) [5][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:14 time: 0.9523 data_time: 0.0480 memory: 6205 grad_norm: 4.5771 loss: 0.8577 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0512 loss_cls: 0.2441 acc: 93.6035 loss_bbox: 0.2613 loss_mask: 0.2631 +2024/10/28 03:36:57 - mmengine - INFO - Epoch(train) [5][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:14 time: 0.9739 data_time: 0.0512 memory: 6103 grad_norm: 4.6291 loss: 0.8461 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0457 loss_cls: 0.2498 acc: 91.3086 loss_bbox: 0.2586 loss_mask: 0.2595 +2024/10/28 03:37:42 - mmengine - INFO - Epoch(train) [5][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:12:07 time: 0.8898 data_time: 0.0459 memory: 6087 grad_norm: 4.5714 loss: 0.8299 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0448 loss_cls: 0.2399 acc: 88.7695 loss_bbox: 0.2449 loss_mask: 0.2689 +2024/10/28 03:38:24 - mmengine - INFO - Epoch(train) [5][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:55 time: 0.8445 data_time: 0.0484 memory: 6112 grad_norm: 4.4786 loss: 0.8354 loss_rpn_cls: 0.0337 loss_rpn_bbox: 0.0474 loss_cls: 0.2407 acc: 93.5547 loss_bbox: 0.2477 loss_mask: 0.2658 +2024/10/28 03:39:09 - mmengine - INFO - Epoch(train) [5][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:48 time: 0.8992 data_time: 0.0436 memory: 6360 grad_norm: 4.6314 loss: 0.8723 loss_rpn_cls: 0.0330 loss_rpn_bbox: 0.0484 loss_cls: 0.2496 acc: 97.9980 loss_bbox: 0.2693 loss_mask: 0.2721 +2024/10/28 03:39:53 - mmengine - INFO - Epoch(train) [5][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:40 time: 0.8902 data_time: 0.0499 memory: 6242 grad_norm: 4.1238 loss: 0.8730 loss_rpn_cls: 0.0368 loss_rpn_bbox: 0.0507 loss_cls: 0.2451 acc: 89.3555 loss_bbox: 0.2660 loss_mask: 0.2744 +2024/10/28 03:40:38 - mmengine - INFO - Epoch(train) [5][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:33 time: 0.8977 data_time: 0.0437 memory: 6309 grad_norm: 4.3991 loss: 0.8665 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0473 loss_cls: 0.2465 acc: 88.8672 loss_bbox: 0.2683 loss_mask: 0.2709 +2024/10/28 03:41:24 - mmengine - INFO - Epoch(train) [5][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:28 time: 0.9193 data_time: 0.0421 memory: 6180 grad_norm: 4.5578 loss: 0.8165 loss_rpn_cls: 0.0343 loss_rpn_bbox: 0.0437 loss_cls: 0.2310 acc: 90.9668 loss_bbox: 0.2461 loss_mask: 0.2614 +2024/10/28 03:42:10 - mmengine - INFO - Epoch(train) [5][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:23 time: 0.9241 data_time: 0.0388 memory: 6132 grad_norm: 4.3515 loss: 0.8157 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0451 loss_cls: 0.2319 acc: 95.6055 loss_bbox: 0.2473 loss_mask: 0.2598 +2024/10/28 03:43:00 - mmengine - INFO - Epoch(train) [5][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:23 time: 0.9863 data_time: 0.0545 memory: 6376 grad_norm: 4.4495 loss: 0.8526 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0551 loss_cls: 0.2278 acc: 95.6543 loss_bbox: 0.2654 loss_mask: 0.2710 +2024/10/28 03:43:47 - mmengine - INFO - Epoch(train) [5][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:21 time: 0.9530 data_time: 0.0472 memory: 6241 grad_norm: 4.4128 loss: 0.7996 loss_rpn_cls: 0.0347 loss_rpn_bbox: 0.0523 loss_cls: 0.2210 acc: 88.7695 loss_bbox: 0.2389 loss_mask: 0.2527 +2024/10/28 03:44:35 - mmengine - INFO - Epoch(train) [5][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:18 time: 0.9542 data_time: 0.0612 memory: 6276 grad_norm: 4.5954 loss: 0.9443 loss_rpn_cls: 0.0389 loss_rpn_bbox: 0.0594 loss_cls: 0.2685 acc: 85.6934 loss_bbox: 0.2925 loss_mask: 0.2850 +2024/10/28 03:45:22 - mmengine - INFO - Epoch(train) [5][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:14 time: 0.9334 data_time: 0.0403 memory: 6187 grad_norm: 4.5246 loss: 0.8199 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0422 loss_cls: 0.2384 acc: 90.8691 loss_bbox: 0.2449 loss_mask: 0.2650 +2024/10/28 03:46:09 - mmengine - INFO - Epoch(train) [5][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:10 time: 0.9452 data_time: 0.0529 memory: 6133 grad_norm: 4.3800 loss: 0.9197 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0571 loss_cls: 0.2624 acc: 93.5547 loss_bbox: 0.2851 loss_mask: 0.2784 +2024/10/28 03:46:53 - mmengine - INFO - Epoch(train) [5][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:11:00 time: 0.8794 data_time: 0.0403 memory: 6054 grad_norm: 4.6696 loss: 0.8090 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0468 loss_cls: 0.2232 acc: 95.6055 loss_bbox: 0.2395 loss_mask: 0.2668 +2024/10/28 03:47:37 - mmengine - INFO - Epoch(train) [5][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:50 time: 0.8851 data_time: 0.0496 memory: 6134 grad_norm: 4.2123 loss: 0.9068 loss_rpn_cls: 0.0413 loss_rpn_bbox: 0.0545 loss_cls: 0.2527 acc: 89.8926 loss_bbox: 0.2714 loss_mask: 0.2868 +2024/10/28 03:48:23 - mmengine - INFO - Epoch(train) [5][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:43 time: 0.9163 data_time: 0.0427 memory: 6380 grad_norm: 4.3695 loss: 0.8411 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0480 loss_cls: 0.2394 acc: 88.2812 loss_bbox: 0.2572 loss_mask: 0.2638 +2024/10/28 03:49:07 - mmengine - INFO - Epoch(train) [5][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:34 time: 0.8846 data_time: 0.0439 memory: 6252 grad_norm: 4.3056 loss: 0.7917 loss_rpn_cls: 0.0296 loss_rpn_bbox: 0.0394 loss_cls: 0.2235 acc: 93.6523 loss_bbox: 0.2393 loss_mask: 0.2599 +2024/10/28 03:49:35 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 03:49:53 - mmengine - INFO - Epoch(train) [5][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:26 time: 0.9151 data_time: 0.0408 memory: 6295 grad_norm: 4.4551 loss: 0.8279 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0492 loss_cls: 0.2308 acc: 93.8477 loss_bbox: 0.2493 loss_mask: 0.2659 +2024/10/28 03:50:39 - mmengine - INFO - Epoch(train) [5][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:19 time: 0.9152 data_time: 0.0418 memory: 6203 grad_norm: 4.2820 loss: 0.8329 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0462 loss_cls: 0.2403 acc: 95.3125 loss_bbox: 0.2538 loss_mask: 0.2600 +2024/10/28 03:51:24 - mmengine - INFO - Epoch(train) [5][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:11 time: 0.9110 data_time: 0.0443 memory: 6162 grad_norm: 4.3135 loss: 0.8284 loss_rpn_cls: 0.0274 loss_rpn_bbox: 0.0435 loss_cls: 0.2443 acc: 91.6992 loss_bbox: 0.2515 loss_mask: 0.2617 +2024/10/28 03:52:11 - mmengine - INFO - Epoch(train) [5][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:10:05 time: 0.9294 data_time: 0.0438 memory: 6107 grad_norm: 4.4334 loss: 0.8082 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0456 loss_cls: 0.2285 acc: 93.3105 loss_bbox: 0.2460 loss_mask: 0.2578 +2024/10/28 03:52:57 - mmengine - INFO - Epoch(train) [5][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:58 time: 0.9227 data_time: 0.0397 memory: 6213 grad_norm: 4.4252 loss: 0.8157 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0475 loss_cls: 0.2210 acc: 93.3105 loss_bbox: 0.2364 loss_mask: 0.2787 +2024/10/28 03:53:40 - mmengine - INFO - Epoch(train) [5][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:46 time: 0.8665 data_time: 0.0381 memory: 6078 grad_norm: 4.6326 loss: 0.7688 loss_rpn_cls: 0.0280 loss_rpn_bbox: 0.0406 loss_cls: 0.2196 acc: 94.2383 loss_bbox: 0.2325 loss_mask: 0.2482 +2024/10/28 03:54:30 - mmengine - INFO - Epoch(train) [5][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:46 time: 1.0030 data_time: 0.0465 memory: 6231 grad_norm: 4.2700 loss: 0.8917 loss_rpn_cls: 0.0345 loss_rpn_bbox: 0.0533 loss_cls: 0.2602 acc: 93.3105 loss_bbox: 0.2747 loss_mask: 0.2690 +2024/10/28 03:55:17 - mmengine - INFO - Epoch(train) [5][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:40 time: 0.9402 data_time: 0.0435 memory: 6420 grad_norm: 4.4441 loss: 0.8572 loss_rpn_cls: 0.0371 loss_rpn_bbox: 0.0489 loss_cls: 0.2530 acc: 91.5527 loss_bbox: 0.2610 loss_mask: 0.2572 +2024/10/28 03:56:04 - mmengine - INFO - Epoch(train) [5][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:33 time: 0.9277 data_time: 0.0527 memory: 6120 grad_norm: 4.4621 loss: 0.8402 loss_rpn_cls: 0.0349 loss_rpn_bbox: 0.0447 loss_cls: 0.2395 acc: 92.5293 loss_bbox: 0.2587 loss_mask: 0.2624 +2024/10/28 03:56:53 - mmengine - INFO - Epoch(train) [5][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:32 time: 0.9888 data_time: 0.0795 memory: 6211 grad_norm: 4.4175 loss: 0.8064 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0450 loss_cls: 0.2301 acc: 89.2578 loss_bbox: 0.2434 loss_mask: 0.2586 +2024/10/28 03:57:39 - mmengine - INFO - Epoch(train) [5][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:23 time: 0.9146 data_time: 0.0540 memory: 6153 grad_norm: 4.3128 loss: 0.8337 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0478 loss_cls: 0.2360 acc: 94.9219 loss_bbox: 0.2492 loss_mask: 0.2667 +2024/10/28 03:58:26 - mmengine - INFO - Epoch(train) [5][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:17 time: 0.9367 data_time: 0.0534 memory: 6113 grad_norm: 4.4251 loss: 0.8435 loss_rpn_cls: 0.0288 loss_rpn_bbox: 0.0474 loss_cls: 0.2473 acc: 89.2578 loss_bbox: 0.2538 loss_mask: 0.2662 +2024/10/28 03:59:11 - mmengine - INFO - Epoch(train) [5][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:09:06 time: 0.8955 data_time: 0.0389 memory: 6271 grad_norm: 4.4208 loss: 0.7980 loss_rpn_cls: 0.0278 loss_rpn_bbox: 0.0428 loss_cls: 0.2216 acc: 93.5547 loss_bbox: 0.2385 loss_mask: 0.2673 +2024/10/28 03:59:56 - mmengine - INFO - Epoch(train) [5][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:57 time: 0.9113 data_time: 0.0448 memory: 6325 grad_norm: 4.2800 loss: 0.8429 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0494 loss_cls: 0.2495 acc: 94.1895 loss_bbox: 0.2467 loss_mask: 0.2620 +2024/10/28 04:00:45 - mmengine - INFO - Epoch(train) [5][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:54 time: 0.9841 data_time: 0.0440 memory: 6187 grad_norm: 4.4285 loss: 0.8382 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0480 loss_cls: 0.2391 acc: 93.5059 loss_bbox: 0.2547 loss_mask: 0.2647 +2024/10/28 04:01:30 - mmengine - INFO - Epoch(train) [5][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:44 time: 0.8990 data_time: 0.0437 memory: 6337 grad_norm: 4.5458 loss: 0.7875 loss_rpn_cls: 0.0257 loss_rpn_bbox: 0.0407 loss_cls: 0.2256 acc: 97.3633 loss_bbox: 0.2318 loss_mask: 0.2636 +2024/10/28 04:02:18 - mmengine - INFO - Epoch(train) [5][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:38 time: 0.9545 data_time: 0.0446 memory: 6178 grad_norm: 4.5677 loss: 0.8388 loss_rpn_cls: 0.0374 loss_rpn_bbox: 0.0502 loss_cls: 0.2295 acc: 93.4082 loss_bbox: 0.2497 loss_mask: 0.2719 +2024/10/28 04:03:05 - mmengine - INFO - Epoch(train) [5][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:31 time: 0.9370 data_time: 0.0573 memory: 6220 grad_norm: 4.4047 loss: 0.8790 loss_rpn_cls: 0.0370 loss_rpn_bbox: 0.0558 loss_cls: 0.2502 acc: 94.0430 loss_bbox: 0.2687 loss_mask: 0.2673 +2024/10/28 04:03:53 - mmengine - INFO - Epoch(train) [5][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:26 time: 0.9635 data_time: 0.0721 memory: 6364 grad_norm: 4.3883 loss: 0.8681 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0523 loss_cls: 0.2458 acc: 97.5098 loss_bbox: 0.2681 loss_mask: 0.2645 +2024/10/28 04:04:40 - mmengine - INFO - Epoch(train) [5][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:18 time: 0.9321 data_time: 0.0455 memory: 6045 grad_norm: 4.4990 loss: 0.7984 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0411 loss_cls: 0.2310 acc: 95.5078 loss_bbox: 0.2359 loss_mask: 0.2602 +2024/10/28 04:05:08 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 04:05:26 - mmengine - INFO - Epoch(train) [5][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:09 time: 0.9194 data_time: 0.0474 memory: 6250 grad_norm: 4.2992 loss: 0.8318 loss_rpn_cls: 0.0311 loss_rpn_bbox: 0.0454 loss_cls: 0.2372 acc: 92.9199 loss_bbox: 0.2551 loss_mask: 0.2629 +2024/10/28 04:06:15 - mmengine - INFO - Epoch(train) [5][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:06 time: 0.9922 data_time: 0.0500 memory: 6325 grad_norm: 4.6976 loss: 0.9087 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0581 loss_cls: 0.2608 acc: 90.6250 loss_bbox: 0.2798 loss_mask: 0.2721 +2024/10/28 04:07:05 - mmengine - INFO - Epoch(train) [5][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:08:03 time: 0.9917 data_time: 0.0489 memory: 6410 grad_norm: 4.1773 loss: 0.8909 loss_rpn_cls: 0.0356 loss_rpn_bbox: 0.0522 loss_cls: 0.2526 acc: 94.4336 loss_bbox: 0.2695 loss_mask: 0.2810 +2024/10/28 04:07:51 - mmengine - INFO - Epoch(train) [5][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:53 time: 0.9202 data_time: 0.0520 memory: 6250 grad_norm: 4.4101 loss: 0.8907 loss_rpn_cls: 0.0387 loss_rpn_bbox: 0.0556 loss_cls: 0.2530 acc: 89.1602 loss_bbox: 0.2652 loss_mask: 0.2782 +2024/10/28 04:08:33 - mmengine - INFO - Epoch(train) [5][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:37 time: 0.8434 data_time: 0.0380 memory: 6085 grad_norm: 4.2160 loss: 0.7750 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0378 loss_cls: 0.2107 acc: 95.7031 loss_bbox: 0.2362 loss_mask: 0.2675 +2024/10/28 04:09:15 - mmengine - INFO - Epoch(train) [5][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:20 time: 0.8356 data_time: 0.0421 memory: 6314 grad_norm: 4.4504 loss: 0.8504 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0523 loss_cls: 0.2405 acc: 88.2324 loss_bbox: 0.2564 loss_mask: 0.2652 +2024/10/28 04:10:01 - mmengine - INFO - Epoch(train) [5][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:10 time: 0.9263 data_time: 0.0442 memory: 6199 grad_norm: 4.4022 loss: 0.8618 loss_rpn_cls: 0.0397 loss_rpn_bbox: 0.0536 loss_cls: 0.2444 acc: 95.2148 loss_bbox: 0.2527 loss_mask: 0.2714 +2024/10/28 04:10:52 - mmengine - INFO - Epoch(train) [5][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:07:09 time: 1.0230 data_time: 0.1192 memory: 6110 grad_norm: 4.3992 loss: 0.8731 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0544 loss_cls: 0.2467 acc: 91.4551 loss_bbox: 0.2616 loss_mask: 0.2731 +2024/10/28 04:11:37 - mmengine - INFO - Epoch(train) [5][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:56 time: 0.8877 data_time: 0.0365 memory: 6097 grad_norm: 4.4087 loss: 0.7981 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0455 loss_cls: 0.2227 acc: 92.0410 loss_bbox: 0.2398 loss_mask: 0.2584 +2024/10/28 04:12:22 - mmengine - INFO - Epoch(train) [5][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:44 time: 0.8970 data_time: 0.0438 memory: 6403 grad_norm: 4.1370 loss: 0.8041 loss_rpn_cls: 0.0297 loss_rpn_bbox: 0.0453 loss_cls: 0.2251 acc: 91.6992 loss_bbox: 0.2427 loss_mask: 0.2614 +2024/10/28 04:13:08 - mmengine - INFO - Epoch(train) [5][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:34 time: 0.9243 data_time: 0.0426 memory: 6239 grad_norm: 4.3579 loss: 0.8620 loss_rpn_cls: 0.0347 loss_rpn_bbox: 0.0518 loss_cls: 0.2511 acc: 95.6543 loss_bbox: 0.2554 loss_mask: 0.2690 +2024/10/28 04:13:53 - mmengine - INFO - Epoch(train) [5][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:22 time: 0.9035 data_time: 0.0450 memory: 6101 grad_norm: 4.7340 loss: 0.8548 loss_rpn_cls: 0.0380 loss_rpn_bbox: 0.0504 loss_cls: 0.2427 acc: 95.8984 loss_bbox: 0.2564 loss_mask: 0.2674 +2024/10/28 04:14:38 - mmengine - INFO - Epoch(train) [5][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:10 time: 0.9008 data_time: 0.0405 memory: 6112 grad_norm: 4.0963 loss: 0.8344 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0465 loss_cls: 0.2328 acc: 91.7480 loss_bbox: 0.2514 loss_mask: 0.2743 +2024/10/28 04:15:24 - mmengine - INFO - Epoch(train) [5][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:06:00 time: 0.9189 data_time: 0.0466 memory: 6235 grad_norm: 4.4091 loss: 0.8520 loss_rpn_cls: 0.0399 loss_rpn_bbox: 0.0475 loss_cls: 0.2410 acc: 93.9941 loss_bbox: 0.2446 loss_mask: 0.2789 +2024/10/28 04:16:09 - mmengine - INFO - Epoch(train) [5][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:47 time: 0.8945 data_time: 0.0423 memory: 6298 grad_norm: 4.2360 loss: 0.8458 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0475 loss_cls: 0.2393 acc: 94.9219 loss_bbox: 0.2533 loss_mask: 0.2702 +2024/10/28 04:16:55 - mmengine - INFO - Epoch(train) [5][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:37 time: 0.9301 data_time: 0.0401 memory: 6281 grad_norm: 4.3963 loss: 0.8702 loss_rpn_cls: 0.0362 loss_rpn_bbox: 0.0509 loss_cls: 0.2490 acc: 89.5508 loss_bbox: 0.2606 loss_mask: 0.2734 +2024/10/28 04:17:42 - mmengine - INFO - Epoch(train) [5][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:26 time: 0.9271 data_time: 0.0483 memory: 6266 grad_norm: 4.4514 loss: 0.8956 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0550 loss_cls: 0.2504 acc: 93.8965 loss_bbox: 0.2718 loss_mask: 0.2811 +2024/10/28 04:18:29 - mmengine - INFO - Epoch(train) [5][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:17 time: 0.9415 data_time: 0.0415 memory: 6339 grad_norm: 4.4091 loss: 0.8626 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0496 loss_cls: 0.2424 acc: 94.8730 loss_bbox: 0.2661 loss_mask: 0.2719 +2024/10/28 04:19:13 - mmengine - INFO - Epoch(train) [5][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:05:03 time: 0.8865 data_time: 0.0423 memory: 6413 grad_norm: 4.3156 loss: 0.8946 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0528 loss_cls: 0.2610 acc: 92.4805 loss_bbox: 0.2658 loss_mask: 0.2759 +2024/10/28 04:19:59 - mmengine - INFO - Epoch(train) [5][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:53 time: 0.9282 data_time: 0.0408 memory: 6236 grad_norm: 4.3771 loss: 0.8265 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0412 loss_cls: 0.2431 acc: 94.8242 loss_bbox: 0.2512 loss_mask: 0.2602 +2024/10/28 04:20:27 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 04:20:44 - mmengine - INFO - Epoch(train) [5][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:39 time: 0.8978 data_time: 0.0437 memory: 6262 grad_norm: 4.2392 loss: 0.8631 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0504 loss_cls: 0.2412 acc: 93.7988 loss_bbox: 0.2674 loss_mask: 0.2681 +2024/10/28 04:21:29 - mmengine - INFO - Epoch(train) [5][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:25 time: 0.8847 data_time: 0.0422 memory: 6291 grad_norm: 4.2286 loss: 0.8452 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0459 loss_cls: 0.2341 acc: 95.6055 loss_bbox: 0.2617 loss_mask: 0.2700 +2024/10/28 04:22:12 - mmengine - INFO - Epoch(train) [5][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:10 time: 0.8777 data_time: 0.0410 memory: 6339 grad_norm: 4.5978 loss: 0.8124 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0463 loss_cls: 0.2294 acc: 95.9473 loss_bbox: 0.2438 loss_mask: 0.2623 +2024/10/28 04:23:00 - mmengine - INFO - Epoch(train) [5][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:04:01 time: 0.9582 data_time: 0.0462 memory: 6122 grad_norm: 4.2044 loss: 0.8989 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0579 loss_cls: 0.2600 acc: 91.1621 loss_bbox: 0.2668 loss_mask: 0.2764 +2024/10/28 04:23:43 - mmengine - INFO - Epoch(train) [5][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:45 time: 0.8615 data_time: 0.0517 memory: 6079 grad_norm: 4.4497 loss: 0.8033 loss_rpn_cls: 0.0297 loss_rpn_bbox: 0.0432 loss_cls: 0.2212 acc: 91.5039 loss_bbox: 0.2331 loss_mask: 0.2760 +2024/10/28 04:24:31 - mmengine - INFO - Epoch(train) [5][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:35 time: 0.9432 data_time: 0.0430 memory: 6152 grad_norm: 4.5573 loss: 0.8664 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0449 loss_cls: 0.2564 acc: 87.4512 loss_bbox: 0.2575 loss_mask: 0.2744 +2024/10/28 04:25:16 - mmengine - INFO - Epoch(train) [5][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:22 time: 0.9071 data_time: 0.0495 memory: 6317 grad_norm: 4.2854 loss: 0.8769 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0488 loss_cls: 0.2495 acc: 86.3770 loss_bbox: 0.2692 loss_mask: 0.2762 +2024/10/28 04:26:03 - mmengine - INFO - Epoch(train) [5][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:11 time: 0.9382 data_time: 0.0515 memory: 6221 grad_norm: 4.0854 loss: 0.8649 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0475 loss_cls: 0.2447 acc: 86.4258 loss_bbox: 0.2669 loss_mask: 0.2726 +2024/10/28 04:26:52 - mmengine - INFO - Epoch(train) [5][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:03:04 time: 0.9864 data_time: 0.1002 memory: 6276 grad_norm: 4.5467 loss: 0.8391 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0458 loss_cls: 0.2458 acc: 90.7227 loss_bbox: 0.2552 loss_mask: 0.2596 +2024/10/28 04:27:38 - mmengine - INFO - Epoch(train) [5][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:52 time: 0.9233 data_time: 0.0432 memory: 6152 grad_norm: 4.5660 loss: 0.8435 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0511 loss_cls: 0.2360 acc: 93.1641 loss_bbox: 0.2465 loss_mask: 0.2766 +2024/10/28 04:28:23 - mmengine - INFO - Epoch(train) [5][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:39 time: 0.9007 data_time: 0.0415 memory: 6278 grad_norm: 4.3505 loss: 0.8723 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0470 loss_cls: 0.2529 acc: 93.7500 loss_bbox: 0.2647 loss_mask: 0.2773 +2024/10/28 04:29:08 - mmengine - INFO - Epoch(train) [5][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:23 time: 0.8864 data_time: 0.0406 memory: 6235 grad_norm: 4.4926 loss: 0.7857 loss_rpn_cls: 0.0311 loss_rpn_bbox: 0.0454 loss_cls: 0.2203 acc: 92.8711 loss_bbox: 0.2330 loss_mask: 0.2560 +2024/10/28 04:29:52 - mmengine - INFO - Epoch(train) [5][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:02:07 time: 0.8774 data_time: 0.0454 memory: 6261 grad_norm: 4.3489 loss: 0.8988 loss_rpn_cls: 0.0361 loss_rpn_bbox: 0.0476 loss_cls: 0.2619 acc: 97.6562 loss_bbox: 0.2789 loss_mask: 0.2742 +2024/10/28 04:30:38 - mmengine - INFO - Epoch(train) [5][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:55 time: 0.9214 data_time: 0.0395 memory: 6225 grad_norm: 3.9638 loss: 0.7969 loss_rpn_cls: 0.0298 loss_rpn_bbox: 0.0441 loss_cls: 0.2290 acc: 93.9941 loss_bbox: 0.2278 loss_mask: 0.2661 +2024/10/28 04:31:24 - mmengine - INFO - Epoch(train) [5][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:42 time: 0.9247 data_time: 0.0470 memory: 6278 grad_norm: 4.2435 loss: 0.8721 loss_rpn_cls: 0.0421 loss_rpn_bbox: 0.0555 loss_cls: 0.2454 acc: 95.8496 loss_bbox: 0.2530 loss_mask: 0.2761 +2024/10/28 04:32:10 - mmengine - INFO - Epoch(train) [5][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:30 time: 0.9241 data_time: 0.0529 memory: 6130 grad_norm: 4.1972 loss: 0.8568 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0474 loss_cls: 0.2419 acc: 93.2617 loss_bbox: 0.2643 loss_mask: 0.2640 +2024/10/28 04:32:57 - mmengine - INFO - Epoch(train) [5][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:18 time: 0.9364 data_time: 0.0451 memory: 6176 grad_norm: 4.2684 loss: 0.8320 loss_rpn_cls: 0.0342 loss_rpn_bbox: 0.0443 loss_cls: 0.2344 acc: 93.4570 loss_bbox: 0.2459 loss_mask: 0.2731 +2024/10/28 04:33:41 - mmengine - INFO - Epoch(train) [5][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:01:02 time: 0.8770 data_time: 0.0412 memory: 6146 grad_norm: 4.2955 loss: 0.7943 loss_rpn_cls: 0.0281 loss_rpn_bbox: 0.0393 loss_cls: 0.2334 acc: 86.1328 loss_bbox: 0.2426 loss_mask: 0.2509 +2024/10/28 04:34:27 - mmengine - INFO - Epoch(train) [5][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:49 time: 0.9268 data_time: 0.0491 memory: 6194 grad_norm: 4.1804 loss: 0.8090 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0500 loss_cls: 0.2218 acc: 97.0215 loss_bbox: 0.2410 loss_mask: 0.2646 +2024/10/28 04:35:12 - mmengine - INFO - Epoch(train) [5][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:33 time: 0.8884 data_time: 0.0463 memory: 6146 grad_norm: 4.3574 loss: 0.7600 loss_rpn_cls: 0.0266 loss_rpn_bbox: 0.0411 loss_cls: 0.2112 acc: 93.0664 loss_bbox: 0.2293 loss_mask: 0.2517 +2024/10/28 04:35:38 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 04:35:57 - mmengine - INFO - Epoch(train) [5][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:19 time: 0.9109 data_time: 0.0526 memory: 6262 grad_norm: 4.2266 loss: 0.8749 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0513 loss_cls: 0.2530 acc: 87.7930 loss_bbox: 0.2687 loss_mask: 0.2694 +2024/10/28 04:36:45 - mmengine - INFO - Epoch(train) [5][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 10:00:09 time: 0.9580 data_time: 0.0482 memory: 6249 grad_norm: 4.4417 loss: 0.8305 loss_rpn_cls: 0.0323 loss_rpn_bbox: 0.0518 loss_cls: 0.2424 acc: 91.4062 loss_bbox: 0.2401 loss_mask: 0.2639 +2024/10/28 04:37:32 - mmengine - INFO - Epoch(train) [5][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:56 time: 0.9299 data_time: 0.0478 memory: 6189 grad_norm: 4.3440 loss: 0.8305 loss_rpn_cls: 0.0319 loss_rpn_bbox: 0.0489 loss_cls: 0.2387 acc: 91.4551 loss_bbox: 0.2480 loss_mask: 0.2629 +2024/10/28 04:38:18 - mmengine - INFO - Epoch(train) [5][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:43 time: 0.9276 data_time: 0.0476 memory: 6081 grad_norm: 4.4610 loss: 0.8579 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0504 loss_cls: 0.2430 acc: 90.5273 loss_bbox: 0.2490 loss_mask: 0.2792 +2024/10/28 04:39:04 - mmengine - INFO - Epoch(train) [5][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:29 time: 0.9146 data_time: 0.0481 memory: 6419 grad_norm: 4.3306 loss: 0.8748 loss_rpn_cls: 0.0354 loss_rpn_bbox: 0.0530 loss_cls: 0.2515 acc: 91.5527 loss_bbox: 0.2681 loss_mask: 0.2668 +2024/10/28 04:39:54 - mmengine - INFO - Epoch(train) [5][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:22 time: 1.0070 data_time: 0.0904 memory: 6190 grad_norm: 4.4393 loss: 0.8330 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0473 loss_cls: 0.2385 acc: 91.0156 loss_bbox: 0.2520 loss_mask: 0.2610 +2024/10/28 04:40:39 - mmengine - INFO - Epoch(train) [5][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:59:06 time: 0.8990 data_time: 0.0425 memory: 6170 grad_norm: 4.4292 loss: 0.8138 loss_rpn_cls: 0.0270 loss_rpn_bbox: 0.0444 loss_cls: 0.2390 acc: 87.5977 loss_bbox: 0.2430 loss_mask: 0.2604 +2024/10/28 04:41:24 - mmengine - INFO - Epoch(train) [5][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:51 time: 0.8998 data_time: 0.0493 memory: 6253 grad_norm: 4.4255 loss: 0.8744 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0501 loss_cls: 0.2514 acc: 91.0156 loss_bbox: 0.2624 loss_mask: 0.2728 +2024/10/28 04:42:10 - mmengine - INFO - Epoch(train) [5][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:37 time: 0.9236 data_time: 0.0492 memory: 6188 grad_norm: 4.2823 loss: 0.8766 loss_rpn_cls: 0.0370 loss_rpn_bbox: 0.0497 loss_cls: 0.2632 acc: 92.2852 loss_bbox: 0.2618 loss_mask: 0.2650 +2024/10/28 04:42:59 - mmengine - INFO - Epoch(train) [5][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:27 time: 0.9743 data_time: 0.0477 memory: 6139 grad_norm: 4.1741 loss: 0.8828 loss_rpn_cls: 0.0386 loss_rpn_bbox: 0.0531 loss_cls: 0.2488 acc: 89.0137 loss_bbox: 0.2700 loss_mask: 0.2723 +2024/10/28 04:43:46 - mmengine - INFO - Epoch(train) [5][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:58:14 time: 0.9420 data_time: 0.0513 memory: 6112 grad_norm: 4.4374 loss: 0.8159 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0483 loss_cls: 0.2332 acc: 96.2891 loss_bbox: 0.2388 loss_mask: 0.2601 +2024/10/28 04:44:31 - mmengine - INFO - Epoch(train) [5][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:59 time: 0.9102 data_time: 0.0513 memory: 6257 grad_norm: 4.3470 loss: 0.8664 loss_rpn_cls: 0.0412 loss_rpn_bbox: 0.0506 loss_cls: 0.2387 acc: 91.4062 loss_bbox: 0.2631 loss_mask: 0.2728 +2024/10/28 04:45:16 - mmengine - INFO - Epoch(train) [5][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:43 time: 0.9003 data_time: 0.0515 memory: 6289 grad_norm: 4.5138 loss: 0.8496 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0464 loss_cls: 0.2533 acc: 90.8203 loss_bbox: 0.2494 loss_mask: 0.2637 +2024/10/28 04:46:03 - mmengine - INFO - Epoch(train) [5][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:29 time: 0.9259 data_time: 0.0502 memory: 6130 grad_norm: 4.2219 loss: 0.8895 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0500 loss_cls: 0.2583 acc: 95.4102 loss_bbox: 0.2721 loss_mask: 0.2759 +2024/10/28 04:46:53 - mmengine - INFO - Epoch(train) [5][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:21 time: 1.0147 data_time: 0.1138 memory: 6206 grad_norm: 4.5320 loss: 0.8753 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0487 loss_cls: 0.2615 acc: 90.1367 loss_bbox: 0.2667 loss_mask: 0.2658 +2024/10/28 04:47:38 - mmengine - INFO - Epoch(train) [5][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:57:05 time: 0.8975 data_time: 0.0453 memory: 6201 grad_norm: 4.4238 loss: 0.7756 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0431 loss_cls: 0.2213 acc: 92.5781 loss_bbox: 0.2263 loss_mask: 0.2581 +2024/10/28 04:48:24 - mmengine - INFO - Epoch(train) [5][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:50 time: 0.9210 data_time: 0.0488 memory: 6075 grad_norm: 4.2010 loss: 0.8039 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0440 loss_cls: 0.2288 acc: 96.2402 loss_bbox: 0.2388 loss_mask: 0.2621 +2024/10/28 04:49:11 - mmengine - INFO - Epoch(train) [5][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:35 time: 0.9221 data_time: 0.0563 memory: 6242 grad_norm: 4.2699 loss: 0.8737 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0506 loss_cls: 0.2524 acc: 89.4531 loss_bbox: 0.2562 loss_mask: 0.2779 +2024/10/28 04:49:58 - mmengine - INFO - Epoch(train) [5][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:22 time: 0.9416 data_time: 0.0479 memory: 6227 grad_norm: 4.4236 loss: 0.8194 loss_rpn_cls: 0.0330 loss_rpn_bbox: 0.0458 loss_cls: 0.2391 acc: 87.5977 loss_bbox: 0.2450 loss_mask: 0.2566 +2024/10/28 04:50:44 - mmengine - INFO - Epoch(train) [5][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:56:08 time: 0.9329 data_time: 0.0501 memory: 6419 grad_norm: 4.3104 loss: 0.8562 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0524 loss_cls: 0.2353 acc: 91.7480 loss_bbox: 0.2657 loss_mask: 0.2689 +2024/10/28 04:51:13 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 04:51:32 - mmengine - INFO - Epoch(train) [5][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:55 time: 0.9493 data_time: 0.0531 memory: 6332 grad_norm: 4.2700 loss: 0.8961 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0542 loss_cls: 0.2637 acc: 84.4727 loss_bbox: 0.2740 loss_mask: 0.2724 +2024/10/28 04:52:18 - mmengine - INFO - Epoch(train) [5][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:40 time: 0.9320 data_time: 0.0524 memory: 6222 grad_norm: 4.4509 loss: 0.8511 loss_rpn_cls: 0.0359 loss_rpn_bbox: 0.0504 loss_cls: 0.2417 acc: 98.2910 loss_bbox: 0.2588 loss_mask: 0.2644 +2024/10/28 04:53:05 - mmengine - INFO - Epoch(train) [5][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:25 time: 0.9251 data_time: 0.0537 memory: 6310 grad_norm: 4.4104 loss: 0.8690 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0510 loss_cls: 0.2503 acc: 93.7500 loss_bbox: 0.2632 loss_mask: 0.2676 +2024/10/28 04:53:52 - mmengine - INFO - Epoch(train) [5][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:55:11 time: 0.9413 data_time: 0.0696 memory: 6277 grad_norm: 4.2940 loss: 0.8373 loss_rpn_cls: 0.0329 loss_rpn_bbox: 0.0477 loss_cls: 0.2331 acc: 89.9414 loss_bbox: 0.2535 loss_mask: 0.2701 +2024/10/28 04:54:39 - mmengine - INFO - Epoch(train) [5][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:58 time: 0.9515 data_time: 0.0494 memory: 6185 grad_norm: 4.1747 loss: 0.8165 loss_rpn_cls: 0.0371 loss_rpn_bbox: 0.0451 loss_cls: 0.2425 acc: 93.2617 loss_bbox: 0.2354 loss_mask: 0.2564 +2024/10/28 04:55:24 - mmengine - INFO - Epoch(train) [5][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:41 time: 0.9045 data_time: 0.0580 memory: 6230 grad_norm: 4.3049 loss: 0.8883 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0467 loss_cls: 0.2518 acc: 89.5508 loss_bbox: 0.2761 loss_mask: 0.2822 +2024/10/28 04:56:10 - mmengine - INFO - Epoch(train) [5][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:26 time: 0.9200 data_time: 0.0521 memory: 6181 grad_norm: 4.2910 loss: 0.8613 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0482 loss_cls: 0.2453 acc: 92.8223 loss_bbox: 0.2579 loss_mask: 0.2733 +2024/10/28 04:56:58 - mmengine - INFO - Epoch(train) [5][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:54:12 time: 0.9498 data_time: 0.0478 memory: 6113 grad_norm: 4.3211 loss: 0.8047 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0419 loss_cls: 0.2220 acc: 97.6074 loss_bbox: 0.2366 loss_mask: 0.2713 +2024/10/28 04:57:43 - mmengine - INFO - Epoch(train) [5][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:55 time: 0.9077 data_time: 0.0497 memory: 6140 grad_norm: 4.3483 loss: 0.8605 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0431 loss_cls: 0.2511 acc: 93.8477 loss_bbox: 0.2641 loss_mask: 0.2696 +2024/10/28 04:58:29 - mmengine - INFO - Epoch(train) [5][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:39 time: 0.9159 data_time: 0.0474 memory: 6273 grad_norm: 4.1141 loss: 0.7962 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0416 loss_cls: 0.2307 acc: 91.5039 loss_bbox: 0.2378 loss_mask: 0.2528 +2024/10/28 04:59:15 - mmengine - INFO - Epoch(train) [5][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:22 time: 0.9104 data_time: 0.0456 memory: 6286 grad_norm: 4.2532 loss: 0.8069 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0486 loss_cls: 0.2256 acc: 95.8008 loss_bbox: 0.2371 loss_mask: 0.2652 +2024/10/28 05:00:03 - mmengine - INFO - Epoch(train) [5][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:10 time: 0.9760 data_time: 0.0583 memory: 6289 grad_norm: 4.3704 loss: 0.9587 loss_rpn_cls: 0.0396 loss_rpn_bbox: 0.0557 loss_cls: 0.2762 acc: 89.5020 loss_bbox: 0.2952 loss_mask: 0.2920 +2024/10/28 05:00:56 - mmengine - INFO - Epoch(train) [5][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:53:03 time: 1.0544 data_time: 0.1280 memory: 6253 grad_norm: 4.4587 loss: 0.8975 loss_rpn_cls: 0.0357 loss_rpn_bbox: 0.0506 loss_cls: 0.2661 acc: 90.3809 loss_bbox: 0.2694 loss_mask: 0.2757 +2024/10/28 05:01:43 - mmengine - INFO - Epoch(train) [5][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:52:48 time: 0.9360 data_time: 0.0535 memory: 6197 grad_norm: 4.2661 loss: 0.8169 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0445 loss_cls: 0.2325 acc: 88.0371 loss_bbox: 0.2448 loss_mask: 0.2641 +2024/10/28 05:02:28 - mmengine - INFO - Epoch(train) [5][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:52:30 time: 0.8979 data_time: 0.0509 memory: 6039 grad_norm: 4.5941 loss: 0.8051 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0469 loss_cls: 0.2307 acc: 88.1348 loss_bbox: 0.2383 loss_mask: 0.2573 +2024/10/28 05:03:14 - mmengine - INFO - Epoch(train) [5][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:52:13 time: 0.9138 data_time: 0.0525 memory: 6262 grad_norm: 4.3506 loss: 0.8168 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0497 loss_cls: 0.2292 acc: 96.2402 loss_bbox: 0.2411 loss_mask: 0.2642 +2024/10/28 05:04:01 - mmengine - INFO - Epoch(train) [5][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:58 time: 0.9468 data_time: 0.0533 memory: 6179 grad_norm: 4.1681 loss: 0.8285 loss_rpn_cls: 0.0343 loss_rpn_bbox: 0.0462 loss_cls: 0.2373 acc: 89.4531 loss_bbox: 0.2498 loss_mask: 0.2610 +2024/10/28 05:04:48 - mmengine - INFO - Epoch(train) [5][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:44 time: 0.9480 data_time: 0.0577 memory: 6230 grad_norm: 4.2647 loss: 0.9187 loss_rpn_cls: 0.0354 loss_rpn_bbox: 0.0515 loss_cls: 0.2736 acc: 90.5273 loss_bbox: 0.2837 loss_mask: 0.2745 +2024/10/28 05:05:35 - mmengine - INFO - Epoch(train) [5][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:28 time: 0.9321 data_time: 0.0483 memory: 6197 grad_norm: 4.1316 loss: 0.8642 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0460 loss_cls: 0.2616 acc: 90.1855 loss_bbox: 0.2644 loss_mask: 0.2607 +2024/10/28 05:06:22 - mmengine - INFO - Epoch(train) [5][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:51:12 time: 0.9410 data_time: 0.0446 memory: 6102 grad_norm: 4.0731 loss: 0.7626 loss_rpn_cls: 0.0298 loss_rpn_bbox: 0.0388 loss_cls: 0.2259 acc: 93.2129 loss_bbox: 0.2219 loss_mask: 0.2463 +2024/10/28 05:06:50 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:07:08 - mmengine - INFO - Epoch(train) [5][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:50:56 time: 0.9276 data_time: 0.0497 memory: 6386 grad_norm: 4.1337 loss: 0.8599 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0477 loss_cls: 0.2365 acc: 94.1895 loss_bbox: 0.2591 loss_mask: 0.2840 +2024/10/28 05:07:54 - mmengine - INFO - Epoch(train) [5][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:50:38 time: 0.9056 data_time: 0.0434 memory: 6060 grad_norm: 4.0587 loss: 0.8095 loss_rpn_cls: 0.0329 loss_rpn_bbox: 0.0473 loss_cls: 0.2299 acc: 95.3125 loss_bbox: 0.2364 loss_mask: 0.2630 +2024/10/28 05:08:39 - mmengine - INFO - Epoch(train) [5][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:50:20 time: 0.9106 data_time: 0.0539 memory: 6328 grad_norm: 4.1318 loss: 0.9331 loss_rpn_cls: 0.0419 loss_rpn_bbox: 0.0584 loss_cls: 0.2684 acc: 89.7949 loss_bbox: 0.2816 loss_mask: 0.2827 +2024/10/28 05:09:26 - mmengine - INFO - Epoch(train) [5][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:50:04 time: 0.9330 data_time: 0.0518 memory: 6276 grad_norm: 4.2339 loss: 0.8851 loss_rpn_cls: 0.0412 loss_rpn_bbox: 0.0534 loss_cls: 0.2572 acc: 86.1816 loss_bbox: 0.2674 loss_mask: 0.2658 +2024/10/28 05:10:12 - mmengine - INFO - Epoch(train) [5][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:49:47 time: 0.9209 data_time: 0.0480 memory: 6286 grad_norm: 4.4922 loss: 0.9011 loss_rpn_cls: 0.0337 loss_rpn_bbox: 0.0528 loss_cls: 0.2618 acc: 84.9609 loss_bbox: 0.2735 loss_mask: 0.2793 +2024/10/28 05:10:58 - mmengine - INFO - Epoch(train) [5][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:49:30 time: 0.9263 data_time: 0.0438 memory: 6385 grad_norm: 4.2299 loss: 0.8424 loss_rpn_cls: 0.0345 loss_rpn_bbox: 0.0509 loss_cls: 0.2479 acc: 91.0156 loss_bbox: 0.2517 loss_mask: 0.2575 +2024/10/28 05:11:45 - mmengine - INFO - Epoch(train) [5][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:49:13 time: 0.9266 data_time: 0.0457 memory: 6207 grad_norm: 4.3284 loss: 0.8519 loss_rpn_cls: 0.0347 loss_rpn_bbox: 0.0466 loss_cls: 0.2471 acc: 89.1602 loss_bbox: 0.2603 loss_mask: 0.2632 +2024/10/28 05:12:31 - mmengine - INFO - Epoch(train) [5][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:48:56 time: 0.9341 data_time: 0.0413 memory: 6188 grad_norm: 4.5296 loss: 0.8101 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0411 loss_cls: 0.2301 acc: 96.1914 loss_bbox: 0.2370 loss_mask: 0.2707 +2024/10/28 05:13:15 - mmengine - INFO - Epoch(train) [5][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:48:35 time: 0.8698 data_time: 0.0455 memory: 6283 grad_norm: 4.4732 loss: 0.8625 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0478 loss_cls: 0.2551 acc: 89.4531 loss_bbox: 0.2553 loss_mask: 0.2699 +2024/10/28 05:13:59 - mmengine - INFO - Epoch(train) [5][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:48:15 time: 0.8881 data_time: 0.0512 memory: 6322 grad_norm: 4.2148 loss: 0.7877 loss_rpn_cls: 0.0340 loss_rpn_bbox: 0.0424 loss_cls: 0.2245 acc: 88.1836 loss_bbox: 0.2251 loss_mask: 0.2617 +2024/10/28 05:14:43 - mmengine - INFO - Epoch(train) [5][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:47:54 time: 0.8786 data_time: 0.0407 memory: 6266 grad_norm: 4.5329 loss: 0.8040 loss_rpn_cls: 0.0297 loss_rpn_bbox: 0.0396 loss_cls: 0.2342 acc: 90.9668 loss_bbox: 0.2330 loss_mask: 0.2675 +2024/10/28 05:15:28 - mmengine - INFO - Epoch(train) [5][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:47:34 time: 0.8913 data_time: 0.0423 memory: 6165 grad_norm: 4.2351 loss: 0.8257 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0437 loss_cls: 0.2337 acc: 93.8477 loss_bbox: 0.2446 loss_mask: 0.2737 +2024/10/28 05:16:13 - mmengine - INFO - Epoch(train) [5][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:47:15 time: 0.9000 data_time: 0.0463 memory: 6283 grad_norm: 4.3214 loss: 0.8733 loss_rpn_cls: 0.0350 loss_rpn_bbox: 0.0479 loss_cls: 0.2656 acc: 89.3555 loss_bbox: 0.2561 loss_mask: 0.2687 +2024/10/28 05:16:42 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:16:42 - mmengine - INFO - Saving checkpoint at 5 epochs +2024/10/28 05:16:55 - mmengine - INFO - Epoch(val) [5][ 50/1250] eta: 0:03:21 time: 0.1682 data_time: 0.0054 memory: 7325 +2024/10/28 05:17:03 - mmengine - INFO - Epoch(val) [5][ 100/1250] eta: 0:03:10 time: 0.1634 data_time: 0.0035 memory: 1114 +2024/10/28 05:17:12 - mmengine - INFO - Epoch(val) [5][ 150/1250] eta: 0:03:03 time: 0.1701 data_time: 0.0036 memory: 1114 +2024/10/28 05:17:21 - mmengine - INFO - Epoch(val) [5][ 200/1250] eta: 0:02:59 time: 0.1836 data_time: 0.0045 memory: 1114 +2024/10/28 05:17:29 - mmengine - INFO - Epoch(val) [5][ 250/1250] eta: 0:02:50 time: 0.1691 data_time: 0.0038 memory: 1221 +2024/10/28 05:17:38 - mmengine - INFO - Epoch(val) [5][ 300/1250] eta: 0:02:42 time: 0.1749 data_time: 0.0048 memory: 1114 +2024/10/28 05:17:47 - mmengine - INFO - Epoch(val) [5][ 350/1250] eta: 0:02:34 time: 0.1707 data_time: 0.0034 memory: 1117 +2024/10/28 05:17:55 - mmengine - INFO - Epoch(val) [5][ 400/1250] eta: 0:02:25 time: 0.1691 data_time: 0.0035 memory: 1114 +2024/10/28 05:18:04 - mmengine - INFO - Epoch(val) [5][ 450/1250] eta: 0:02:16 time: 0.1686 data_time: 0.0034 memory: 1155 +2024/10/28 05:18:12 - mmengine - INFO - Epoch(val) [5][ 500/1250] eta: 0:02:07 time: 0.1658 data_time: 0.0041 memory: 1134 +2024/10/28 05:18:21 - mmengine - INFO - Epoch(val) [5][ 550/1250] eta: 0:01:59 time: 0.1819 data_time: 0.0037 memory: 1176 +2024/10/28 05:18:29 - mmengine - INFO - Epoch(val) [5][ 600/1250] eta: 0:01:50 time: 0.1628 data_time: 0.0048 memory: 1114 +2024/10/28 05:18:37 - mmengine - INFO - Epoch(val) [5][ 650/1250] eta: 0:01:42 time: 0.1672 data_time: 0.0035 memory: 1219 +2024/10/28 05:18:46 - mmengine - INFO - Epoch(val) [5][ 700/1250] eta: 0:01:33 time: 0.1735 data_time: 0.0042 memory: 1219 +2024/10/28 05:18:55 - mmengine - INFO - Epoch(val) [5][ 750/1250] eta: 0:01:25 time: 0.1744 data_time: 0.0049 memory: 1116 +2024/10/28 05:19:04 - mmengine - INFO - Epoch(val) [5][ 800/1250] eta: 0:01:16 time: 0.1733 data_time: 0.0038 memory: 1160 +2024/10/28 05:19:13 - mmengine - INFO - Epoch(val) [5][ 850/1250] eta: 0:01:08 time: 0.1806 data_time: 0.0043 memory: 1192 +2024/10/28 05:19:21 - mmengine - INFO - Epoch(val) [5][ 900/1250] eta: 0:01:00 time: 0.1764 data_time: 0.0033 memory: 1114 +2024/10/28 05:19:30 - mmengine - INFO - Epoch(val) [5][ 950/1250] eta: 0:00:51 time: 0.1755 data_time: 0.0053 memory: 1219 +2024/10/28 05:19:39 - mmengine - INFO - Epoch(val) [5][1000/1250] eta: 0:00:43 time: 0.1741 data_time: 0.0043 memory: 1142 +2024/10/28 05:19:48 - mmengine - INFO - Epoch(val) [5][1050/1250] eta: 0:00:34 time: 0.1773 data_time: 0.0047 memory: 1114 +2024/10/28 05:19:56 - mmengine - INFO - Epoch(val) [5][1100/1250] eta: 0:00:25 time: 0.1690 data_time: 0.0034 memory: 1116 +2024/10/28 05:20:05 - mmengine - INFO - Epoch(val) [5][1150/1250] eta: 0:00:17 time: 0.1759 data_time: 0.0041 memory: 1114 +2024/10/28 05:20:14 - mmengine - INFO - Epoch(val) [5][1200/1250] eta: 0:00:08 time: 0.1795 data_time: 0.0032 memory: 1176 +2024/10/28 05:20:23 - mmengine - INFO - Epoch(val) [5][1250/1250] eta: 0:00:00 time: 0.1769 data_time: 0.0038 memory: 1114 +2024/10/28 05:20:35 - mmengine - INFO - Evaluating bbox... +2024/10/28 05:21:06 - mmengine - INFO - bbox_mAP_copypaste: 0.314 0.521 0.335 0.150 0.346 0.439 +2024/10/28 05:21:06 - mmengine - INFO - Evaluating segm... +2024/10/28 05:21:43 - mmengine - INFO - segm_mAP_copypaste: 0.301 0.494 0.319 0.108 0.324 0.471 +2024/10/28 05:21:44 - mmengine - INFO - Epoch(val) [5][1250/1250] coco/bbox_mAP: 0.3140 coco/bbox_mAP_50: 0.5210 coco/bbox_mAP_75: 0.3350 coco/bbox_mAP_s: 0.1500 coco/bbox_mAP_m: 0.3460 coco/bbox_mAP_l: 0.4390 coco/segm_mAP: 0.3010 coco/segm_mAP_50: 0.4940 coco/segm_mAP_75: 0.3190 coco/segm_mAP_s: 0.1080 coco/segm_mAP_m: 0.3240 coco/segm_mAP_l: 0.4710 data_time: 0.0041 time: 0.1729 +2024/10/28 05:22:15 - mmengine - INFO - Epoch(train) [6][ 50/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:46:29 time: 0.6307 data_time: 0.0477 memory: 6262 grad_norm: 4.0546 loss: 0.8478 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0536 loss_cls: 0.2366 acc: 89.3555 loss_bbox: 0.2629 loss_mask: 0.2647 +2024/10/28 05:22:40 - mmengine - INFO - Epoch(train) [6][ 100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:45:41 time: 0.4839 data_time: 0.0419 memory: 6244 grad_norm: 4.0126 loss: 0.8539 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0523 loss_cls: 0.2401 acc: 96.2891 loss_bbox: 0.2601 loss_mask: 0.2670 +2024/10/28 05:23:04 - mmengine - INFO - Epoch(train) [6][ 150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:44:53 time: 0.4903 data_time: 0.0442 memory: 6151 grad_norm: 4.0592 loss: 0.8105 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0474 loss_cls: 0.2354 acc: 94.2383 loss_bbox: 0.2454 loss_mask: 0.2512 +2024/10/28 05:23:30 - mmengine - INFO - Epoch(train) [6][ 200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:44:07 time: 0.5248 data_time: 0.0775 memory: 6282 grad_norm: 4.1907 loss: 0.8086 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0483 loss_cls: 0.2250 acc: 91.8457 loss_bbox: 0.2472 loss_mask: 0.2592 +2024/10/28 05:23:55 - mmengine - INFO - Epoch(train) [6][ 250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:43:19 time: 0.4827 data_time: 0.0411 memory: 6173 grad_norm: 4.1873 loss: 0.8081 loss_rpn_cls: 0.0276 loss_rpn_bbox: 0.0432 loss_cls: 0.2251 acc: 93.9453 loss_bbox: 0.2532 loss_mask: 0.2590 +2024/10/28 05:24:19 - mmengine - INFO - Epoch(train) [6][ 300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:42:31 time: 0.4914 data_time: 0.0430 memory: 6366 grad_norm: 4.1046 loss: 0.8147 loss_rpn_cls: 0.0319 loss_rpn_bbox: 0.0483 loss_cls: 0.2222 acc: 93.5059 loss_bbox: 0.2457 loss_mask: 0.2666 +2024/10/28 05:24:43 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:24:43 - mmengine - INFO - Epoch(train) [6][ 350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:41:43 time: 0.4877 data_time: 0.0372 memory: 6293 grad_norm: 4.3518 loss: 0.7870 loss_rpn_cls: 0.0231 loss_rpn_bbox: 0.0420 loss_cls: 0.2214 acc: 94.6289 loss_bbox: 0.2357 loss_mask: 0.2649 +2024/10/28 05:25:08 - mmengine - INFO - Epoch(train) [6][ 400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:40:55 time: 0.4816 data_time: 0.0430 memory: 6404 grad_norm: 4.3011 loss: 0.8146 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0451 loss_cls: 0.2282 acc: 96.3867 loss_bbox: 0.2432 loss_mask: 0.2673 +2024/10/28 05:25:32 - mmengine - INFO - Epoch(train) [6][ 450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:40:08 time: 0.4967 data_time: 0.0524 memory: 6328 grad_norm: 4.2998 loss: 0.8300 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0484 loss_cls: 0.2356 acc: 89.1602 loss_bbox: 0.2465 loss_mask: 0.2689 +2024/10/28 05:25:57 - mmengine - INFO - Epoch(train) [6][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:39:20 time: 0.4885 data_time: 0.0505 memory: 6280 grad_norm: 4.3083 loss: 0.8780 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0507 loss_cls: 0.2532 acc: 96.6309 loss_bbox: 0.2707 loss_mask: 0.2718 +2024/10/28 05:26:22 - mmengine - INFO - Epoch(train) [6][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:38:34 time: 0.5060 data_time: 0.0499 memory: 6152 grad_norm: 4.2446 loss: 0.8143 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0449 loss_cls: 0.2350 acc: 92.9688 loss_bbox: 0.2460 loss_mask: 0.2567 +2024/10/28 05:26:47 - mmengine - INFO - Epoch(train) [6][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:37:48 time: 0.5061 data_time: 0.0522 memory: 6232 grad_norm: 4.1559 loss: 0.8344 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0491 loss_cls: 0.2433 acc: 90.3809 loss_bbox: 0.2487 loss_mask: 0.2609 +2024/10/28 05:27:13 - mmengine - INFO - Epoch(train) [6][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:37:02 time: 0.5117 data_time: 0.0528 memory: 6223 grad_norm: 4.1559 loss: 0.8699 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0480 loss_cls: 0.2471 acc: 93.3105 loss_bbox: 0.2640 loss_mask: 0.2803 +2024/10/28 05:27:38 - mmengine - INFO - Epoch(train) [6][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:36:15 time: 0.4912 data_time: 0.0541 memory: 6345 grad_norm: 4.2511 loss: 0.8649 loss_rpn_cls: 0.0361 loss_rpn_bbox: 0.0501 loss_cls: 0.2463 acc: 97.9980 loss_bbox: 0.2543 loss_mask: 0.2782 +2024/10/28 05:28:03 - mmengine - INFO - Epoch(train) [6][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:35:28 time: 0.5049 data_time: 0.0495 memory: 6342 grad_norm: 4.2719 loss: 0.8111 loss_rpn_cls: 0.0350 loss_rpn_bbox: 0.0481 loss_cls: 0.2285 acc: 92.1387 loss_bbox: 0.2416 loss_mask: 0.2579 +2024/10/28 05:28:31 - mmengine - INFO - Epoch(train) [6][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:34:46 time: 0.5593 data_time: 0.1145 memory: 6278 grad_norm: 4.1374 loss: 0.8152 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0493 loss_cls: 0.2278 acc: 96.1426 loss_bbox: 0.2504 loss_mask: 0.2542 +2024/10/28 05:28:56 - mmengine - INFO - Epoch(train) [6][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:33:59 time: 0.4943 data_time: 0.0526 memory: 6298 grad_norm: 4.1282 loss: 0.8630 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0478 loss_cls: 0.2448 acc: 83.6426 loss_bbox: 0.2660 loss_mask: 0.2731 +2024/10/28 05:29:20 - mmengine - INFO - Epoch(train) [6][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:33:13 time: 0.4981 data_time: 0.0519 memory: 6378 grad_norm: 4.1189 loss: 0.8083 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0452 loss_cls: 0.2309 acc: 91.0645 loss_bbox: 0.2514 loss_mask: 0.2517 +2024/10/28 05:29:45 - mmengine - INFO - Epoch(train) [6][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:32:26 time: 0.4944 data_time: 0.0479 memory: 6064 grad_norm: 4.2093 loss: 0.8210 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0415 loss_cls: 0.2366 acc: 89.9414 loss_bbox: 0.2546 loss_mask: 0.2612 +2024/10/28 05:30:10 - mmengine - INFO - Epoch(train) [6][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:31:39 time: 0.4903 data_time: 0.0520 memory: 6259 grad_norm: 4.1585 loss: 0.7916 loss_rpn_cls: 0.0260 loss_rpn_bbox: 0.0446 loss_cls: 0.2229 acc: 93.1641 loss_bbox: 0.2401 loss_mask: 0.2579 +2024/10/28 05:30:34 - mmengine - INFO - Epoch(train) [6][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:30:52 time: 0.4845 data_time: 0.0470 memory: 6419 grad_norm: 4.3025 loss: 0.8038 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0465 loss_cls: 0.2314 acc: 91.0645 loss_bbox: 0.2409 loss_mask: 0.2567 +2024/10/28 05:30:59 - mmengine - INFO - Epoch(train) [6][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:30:06 time: 0.5002 data_time: 0.0529 memory: 6187 grad_norm: 4.1817 loss: 0.8774 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0478 loss_cls: 0.2562 acc: 95.8496 loss_bbox: 0.2703 loss_mask: 0.2731 +2024/10/28 05:31:24 - mmengine - INFO - Epoch(train) [6][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:29:20 time: 0.5044 data_time: 0.0505 memory: 6215 grad_norm: 4.1744 loss: 0.8726 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0483 loss_cls: 0.2573 acc: 88.4766 loss_bbox: 0.2700 loss_mask: 0.2662 +2024/10/28 05:31:49 - mmengine - INFO - Epoch(train) [6][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:28:34 time: 0.5041 data_time: 0.0556 memory: 6152 grad_norm: 4.0104 loss: 0.8851 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0502 loss_cls: 0.2535 acc: 95.6543 loss_bbox: 0.2771 loss_mask: 0.2709 +2024/10/28 05:32:14 - mmengine - INFO - Epoch(train) [6][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:27:48 time: 0.4975 data_time: 0.0557 memory: 6248 grad_norm: 4.3580 loss: 0.8694 loss_rpn_cls: 0.0338 loss_rpn_bbox: 0.0467 loss_cls: 0.2617 acc: 88.4766 loss_bbox: 0.2611 loss_mask: 0.2661 +2024/10/28 05:32:39 - mmengine - INFO - Epoch(train) [6][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:27:01 time: 0.4874 data_time: 0.0455 memory: 6319 grad_norm: 4.0926 loss: 0.7986 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0478 loss_cls: 0.2226 acc: 97.4121 loss_bbox: 0.2404 loss_mask: 0.2575 +2024/10/28 05:33:04 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:33:04 - mmengine - INFO - Epoch(train) [6][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:26:16 time: 0.5029 data_time: 0.0555 memory: 6239 grad_norm: 4.3744 loss: 0.8313 loss_rpn_cls: 0.0281 loss_rpn_bbox: 0.0478 loss_cls: 0.2364 acc: 95.6055 loss_bbox: 0.2565 loss_mask: 0.2625 +2024/10/28 05:33:31 - mmengine - INFO - Epoch(train) [6][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:25:32 time: 0.5352 data_time: 0.0780 memory: 6112 grad_norm: 4.3503 loss: 0.7737 loss_rpn_cls: 0.0252 loss_rpn_bbox: 0.0442 loss_cls: 0.2122 acc: 94.5801 loss_bbox: 0.2312 loss_mask: 0.2608 +2024/10/28 05:33:56 - mmengine - INFO - Epoch(train) [6][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:24:46 time: 0.5026 data_time: 0.0493 memory: 6241 grad_norm: 4.0098 loss: 0.8166 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0437 loss_cls: 0.2309 acc: 95.9961 loss_bbox: 0.2484 loss_mask: 0.2654 +2024/10/28 05:34:21 - mmengine - INFO - Epoch(train) [6][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:24:02 time: 0.5124 data_time: 0.0596 memory: 6211 grad_norm: 4.0910 loss: 0.9319 loss_rpn_cls: 0.0415 loss_rpn_bbox: 0.0605 loss_cls: 0.2561 acc: 86.5723 loss_bbox: 0.2892 loss_mask: 0.2846 +2024/10/28 05:34:46 - mmengine - INFO - Epoch(train) [6][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:23:15 time: 0.4893 data_time: 0.0534 memory: 6063 grad_norm: 4.3342 loss: 0.8855 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0476 loss_cls: 0.2571 acc: 83.6914 loss_bbox: 0.2750 loss_mask: 0.2724 +2024/10/28 05:35:10 - mmengine - INFO - Epoch(train) [6][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:22:29 time: 0.4927 data_time: 0.0483 memory: 6234 grad_norm: 4.1729 loss: 0.8347 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0524 loss_cls: 0.2356 acc: 96.9727 loss_bbox: 0.2581 loss_mask: 0.2599 +2024/10/28 05:35:35 - mmengine - INFO - Epoch(train) [6][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:21:43 time: 0.4940 data_time: 0.0454 memory: 6007 grad_norm: 4.1448 loss: 0.8438 loss_rpn_cls: 0.0323 loss_rpn_bbox: 0.0497 loss_cls: 0.2423 acc: 96.4355 loss_bbox: 0.2555 loss_mask: 0.2640 +2024/10/28 05:36:00 - mmengine - INFO - Epoch(train) [6][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:20:57 time: 0.4934 data_time: 0.0515 memory: 6237 grad_norm: 4.1979 loss: 0.8242 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0428 loss_cls: 0.2319 acc: 87.0605 loss_bbox: 0.2580 loss_mask: 0.2624 +2024/10/28 05:36:25 - mmengine - INFO - Epoch(train) [6][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:20:12 time: 0.5026 data_time: 0.0495 memory: 6330 grad_norm: 4.0695 loss: 0.7721 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0450 loss_cls: 0.2139 acc: 91.4062 loss_bbox: 0.2385 loss_mask: 0.2475 +2024/10/28 05:36:49 - mmengine - INFO - Epoch(train) [6][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:19:26 time: 0.4879 data_time: 0.0509 memory: 6419 grad_norm: 4.1723 loss: 0.8097 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0485 loss_cls: 0.2245 acc: 91.6016 loss_bbox: 0.2424 loss_mask: 0.2612 +2024/10/28 05:37:14 - mmengine - INFO - Epoch(train) [6][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:18:40 time: 0.4979 data_time: 0.0600 memory: 6233 grad_norm: 4.2505 loss: 0.8484 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0509 loss_cls: 0.2384 acc: 89.4043 loss_bbox: 0.2516 loss_mask: 0.2736 +2024/10/28 05:37:40 - mmengine - INFO - Epoch(train) [6][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:17:56 time: 0.5198 data_time: 0.0728 memory: 6266 grad_norm: 4.3236 loss: 0.8686 loss_rpn_cls: 0.0367 loss_rpn_bbox: 0.0486 loss_cls: 0.2434 acc: 91.4062 loss_bbox: 0.2751 loss_mask: 0.2649 +2024/10/28 05:38:06 - mmengine - INFO - Epoch(train) [6][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:17:12 time: 0.5124 data_time: 0.0535 memory: 6087 grad_norm: 4.1920 loss: 0.8008 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0447 loss_cls: 0.2207 acc: 93.7988 loss_bbox: 0.2468 loss_mask: 0.2616 +2024/10/28 05:38:31 - mmengine - INFO - Epoch(train) [6][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:16:26 time: 0.4948 data_time: 0.0580 memory: 6138 grad_norm: 3.9796 loss: 0.7995 loss_rpn_cls: 0.0288 loss_rpn_bbox: 0.0455 loss_cls: 0.2324 acc: 90.9180 loss_bbox: 0.2368 loss_mask: 0.2561 +2024/10/28 05:38:56 - mmengine - INFO - Epoch(train) [6][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:15:41 time: 0.4994 data_time: 0.0497 memory: 6151 grad_norm: 4.3589 loss: 0.8313 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0476 loss_cls: 0.2355 acc: 94.3359 loss_bbox: 0.2517 loss_mask: 0.2675 +2024/10/28 05:39:21 - mmengine - INFO - Epoch(train) [6][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:14:57 time: 0.5068 data_time: 0.0598 memory: 6325 grad_norm: 4.0448 loss: 0.8249 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0440 loss_cls: 0.2477 acc: 90.3320 loss_bbox: 0.2460 loss_mask: 0.2571 +2024/10/28 05:39:47 - mmengine - INFO - Epoch(train) [6][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:14:12 time: 0.5147 data_time: 0.0625 memory: 6147 grad_norm: 4.3726 loss: 0.8481 loss_rpn_cls: 0.0297 loss_rpn_bbox: 0.0492 loss_cls: 0.2454 acc: 93.0664 loss_bbox: 0.2603 loss_mask: 0.2635 +2024/10/28 05:40:12 - mmengine - INFO - Epoch(train) [6][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:13:28 time: 0.5010 data_time: 0.0542 memory: 6042 grad_norm: 4.3065 loss: 0.7751 loss_rpn_cls: 0.0299 loss_rpn_bbox: 0.0421 loss_cls: 0.2094 acc: 91.8945 loss_bbox: 0.2346 loss_mask: 0.2590 +2024/10/28 05:40:36 - mmengine - INFO - Epoch(train) [6][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:12:42 time: 0.4960 data_time: 0.0554 memory: 6345 grad_norm: 4.3055 loss: 0.8476 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0463 loss_cls: 0.2428 acc: 94.2871 loss_bbox: 0.2564 loss_mask: 0.2721 +2024/10/28 05:41:02 - mmengine - INFO - Epoch(train) [6][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:11:58 time: 0.5109 data_time: 0.0590 memory: 6225 grad_norm: 4.2360 loss: 0.8474 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0488 loss_cls: 0.2542 acc: 94.5801 loss_bbox: 0.2568 loss_mask: 0.2551 +2024/10/28 05:41:31 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:41:31 - mmengine - INFO - Epoch(train) [6][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:11:18 time: 0.5719 data_time: 0.1300 memory: 6206 grad_norm: 4.4853 loss: 0.8120 loss_rpn_cls: 0.0278 loss_rpn_bbox: 0.0462 loss_cls: 0.2231 acc: 90.4297 loss_bbox: 0.2421 loss_mask: 0.2728 +2024/10/28 05:41:55 - mmengine - INFO - Epoch(train) [6][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:10:33 time: 0.4928 data_time: 0.0522 memory: 6268 grad_norm: 4.1414 loss: 0.8152 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0414 loss_cls: 0.2389 acc: 92.7734 loss_bbox: 0.2445 loss_mask: 0.2622 +2024/10/28 05:42:20 - mmengine - INFO - Epoch(train) [6][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:09:48 time: 0.4933 data_time: 0.0553 memory: 6146 grad_norm: 4.1907 loss: 0.8183 loss_rpn_cls: 0.0260 loss_rpn_bbox: 0.0435 loss_cls: 0.2303 acc: 94.4824 loss_bbox: 0.2526 loss_mask: 0.2659 +2024/10/28 05:42:45 - mmengine - INFO - Epoch(train) [6][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:09:03 time: 0.4993 data_time: 0.0605 memory: 6245 grad_norm: 4.2523 loss: 0.8434 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0482 loss_cls: 0.2424 acc: 95.8496 loss_bbox: 0.2639 loss_mask: 0.2579 +2024/10/28 05:43:11 - mmengine - INFO - Epoch(train) [6][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:08:19 time: 0.5193 data_time: 0.0576 memory: 6159 grad_norm: 4.2709 loss: 0.8339 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0478 loss_cls: 0.2483 acc: 94.2871 loss_bbox: 0.2507 loss_mask: 0.2568 +2024/10/28 05:43:36 - mmengine - INFO - Epoch(train) [6][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:07:35 time: 0.5041 data_time: 0.0596 memory: 6150 grad_norm: 4.1311 loss: 0.8631 loss_rpn_cls: 0.0281 loss_rpn_bbox: 0.0518 loss_cls: 0.2417 acc: 94.5312 loss_bbox: 0.2683 loss_mask: 0.2732 +2024/10/28 05:44:02 - mmengine - INFO - Epoch(train) [6][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:06:51 time: 0.5080 data_time: 0.0506 memory: 6136 grad_norm: 4.2514 loss: 0.7486 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0388 loss_cls: 0.2060 acc: 90.6250 loss_bbox: 0.2209 loss_mask: 0.2578 +2024/10/28 05:44:27 - mmengine - INFO - Epoch(train) [6][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:06:07 time: 0.5017 data_time: 0.0543 memory: 6217 grad_norm: 3.9438 loss: 0.8233 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0465 loss_cls: 0.2243 acc: 93.2617 loss_bbox: 0.2556 loss_mask: 0.2650 +2024/10/28 05:44:52 - mmengine - INFO - Epoch(train) [6][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:05:22 time: 0.4997 data_time: 0.0557 memory: 6220 grad_norm: 4.3312 loss: 0.8426 loss_rpn_cls: 0.0371 loss_rpn_bbox: 0.0476 loss_cls: 0.2373 acc: 93.7500 loss_bbox: 0.2515 loss_mask: 0.2691 +2024/10/28 05:45:16 - mmengine - INFO - Epoch(train) [6][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:04:37 time: 0.4888 data_time: 0.0544 memory: 6106 grad_norm: 4.0111 loss: 0.7912 loss_rpn_cls: 0.0246 loss_rpn_bbox: 0.0426 loss_cls: 0.2172 acc: 92.7734 loss_bbox: 0.2452 loss_mask: 0.2616 +2024/10/28 05:45:41 - mmengine - INFO - Epoch(train) [6][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:03:53 time: 0.4998 data_time: 0.0556 memory: 6171 grad_norm: 4.0411 loss: 0.8186 loss_rpn_cls: 0.0284 loss_rpn_bbox: 0.0455 loss_cls: 0.2269 acc: 93.4082 loss_bbox: 0.2459 loss_mask: 0.2719 +2024/10/28 05:46:06 - mmengine - INFO - Epoch(train) [6][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:03:08 time: 0.4956 data_time: 0.0506 memory: 6297 grad_norm: 4.1350 loss: 0.8294 loss_rpn_cls: 0.0362 loss_rpn_bbox: 0.0465 loss_cls: 0.2369 acc: 93.7988 loss_bbox: 0.2469 loss_mask: 0.2630 +2024/10/28 05:46:32 - mmengine - INFO - Epoch(train) [6][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:02:25 time: 0.5223 data_time: 0.0663 memory: 6252 grad_norm: 4.1282 loss: 0.8375 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0472 loss_cls: 0.2395 acc: 94.4824 loss_bbox: 0.2581 loss_mask: 0.2610 +2024/10/28 05:46:57 - mmengine - INFO - Epoch(train) [6][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:01:41 time: 0.4988 data_time: 0.0554 memory: 6179 grad_norm: 3.9610 loss: 0.7962 loss_rpn_cls: 0.0293 loss_rpn_bbox: 0.0416 loss_cls: 0.2289 acc: 95.8496 loss_bbox: 0.2382 loss_mask: 0.2583 +2024/10/28 05:47:22 - mmengine - INFO - Epoch(train) [6][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:00:57 time: 0.5003 data_time: 0.0539 memory: 6239 grad_norm: 4.1832 loss: 0.7939 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0447 loss_cls: 0.2205 acc: 89.8926 loss_bbox: 0.2383 loss_mask: 0.2577 +2024/10/28 05:47:46 - mmengine - INFO - Epoch(train) [6][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 9:00:12 time: 0.4906 data_time: 0.0506 memory: 6333 grad_norm: 4.0681 loss: 0.8045 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0429 loss_cls: 0.2341 acc: 81.7383 loss_bbox: 0.2396 loss_mask: 0.2575 +2024/10/28 05:48:11 - mmengine - INFO - Epoch(train) [6][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:59:28 time: 0.4934 data_time: 0.0573 memory: 6276 grad_norm: 4.2122 loss: 0.8182 loss_rpn_cls: 0.0296 loss_rpn_bbox: 0.0468 loss_cls: 0.2279 acc: 93.9941 loss_bbox: 0.2587 loss_mask: 0.2552 +2024/10/28 05:48:36 - mmengine - INFO - Epoch(train) [6][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:58:44 time: 0.5049 data_time: 0.0584 memory: 6341 grad_norm: 4.3176 loss: 0.8569 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0494 loss_cls: 0.2433 acc: 90.9180 loss_bbox: 0.2630 loss_mask: 0.2705 +2024/10/28 05:49:02 - mmengine - INFO - Epoch(train) [6][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:58:01 time: 0.5050 data_time: 0.0602 memory: 6212 grad_norm: 4.1492 loss: 0.8471 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0482 loss_cls: 0.2428 acc: 94.6777 loss_bbox: 0.2700 loss_mask: 0.2560 +2024/10/28 05:49:31 - mmengine - INFO - Epoch(train) [6][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:57:22 time: 0.5976 data_time: 0.1477 memory: 6279 grad_norm: 4.1987 loss: 0.8208 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0431 loss_cls: 0.2342 acc: 98.1934 loss_bbox: 0.2503 loss_mask: 0.2627 +2024/10/28 05:49:57 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:49:57 - mmengine - INFO - Epoch(train) [6][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:56:39 time: 0.5041 data_time: 0.0566 memory: 6207 grad_norm: 3.9960 loss: 0.8107 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0467 loss_cls: 0.2275 acc: 95.6055 loss_bbox: 0.2472 loss_mask: 0.2579 +2024/10/28 05:50:22 - mmengine - INFO - Epoch(train) [6][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:55:55 time: 0.5071 data_time: 0.0636 memory: 6302 grad_norm: 4.1184 loss: 0.8803 loss_rpn_cls: 0.0379 loss_rpn_bbox: 0.0494 loss_cls: 0.2519 acc: 90.7227 loss_bbox: 0.2678 loss_mask: 0.2733 +2024/10/28 05:50:47 - mmengine - INFO - Epoch(train) [6][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:55:12 time: 0.5031 data_time: 0.0597 memory: 6231 grad_norm: 4.0937 loss: 0.7779 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0477 loss_cls: 0.2085 acc: 96.6797 loss_bbox: 0.2391 loss_mask: 0.2525 +2024/10/28 05:51:13 - mmengine - INFO - Epoch(train) [6][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:54:29 time: 0.5058 data_time: 0.0562 memory: 6231 grad_norm: 4.2544 loss: 0.7851 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0469 loss_cls: 0.2149 acc: 86.5723 loss_bbox: 0.2381 loss_mask: 0.2549 +2024/10/28 05:51:37 - mmengine - INFO - Epoch(train) [6][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:53:45 time: 0.4950 data_time: 0.0538 memory: 6221 grad_norm: 4.1937 loss: 0.7930 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0435 loss_cls: 0.2201 acc: 89.3066 loss_bbox: 0.2306 loss_mask: 0.2685 +2024/10/28 05:52:02 - mmengine - INFO - Epoch(train) [6][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:53:01 time: 0.4944 data_time: 0.0561 memory: 6243 grad_norm: 4.2390 loss: 0.8603 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0517 loss_cls: 0.2505 acc: 94.3848 loss_bbox: 0.2544 loss_mask: 0.2710 +2024/10/28 05:52:30 - mmengine - INFO - Epoch(train) [6][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:52:21 time: 0.5684 data_time: 0.1329 memory: 6309 grad_norm: 4.1094 loss: 0.8113 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0457 loss_cls: 0.2213 acc: 92.3828 loss_bbox: 0.2451 loss_mask: 0.2690 +2024/10/28 05:52:55 - mmengine - INFO - Epoch(train) [6][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:51:37 time: 0.4998 data_time: 0.0543 memory: 6133 grad_norm: 4.0480 loss: 0.8035 loss_rpn_cls: 0.0274 loss_rpn_bbox: 0.0464 loss_cls: 0.2265 acc: 94.1895 loss_bbox: 0.2431 loss_mask: 0.2601 +2024/10/28 05:53:20 - mmengine - INFO - Epoch(train) [6][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:50:54 time: 0.5002 data_time: 0.0521 memory: 6221 grad_norm: 4.0288 loss: 0.7609 loss_rpn_cls: 0.0264 loss_rpn_bbox: 0.0406 loss_cls: 0.2162 acc: 97.8516 loss_bbox: 0.2219 loss_mask: 0.2558 +2024/10/28 05:53:46 - mmengine - INFO - Epoch(train) [6][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:50:11 time: 0.5066 data_time: 0.0610 memory: 6231 grad_norm: 4.2850 loss: 0.8589 loss_rpn_cls: 0.0373 loss_rpn_bbox: 0.0519 loss_cls: 0.2535 acc: 92.0898 loss_bbox: 0.2575 loss_mask: 0.2587 +2024/10/28 05:54:10 - mmengine - INFO - Epoch(train) [6][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:49:27 time: 0.4919 data_time: 0.0536 memory: 6213 grad_norm: 4.3544 loss: 0.8398 loss_rpn_cls: 0.0295 loss_rpn_bbox: 0.0485 loss_cls: 0.2386 acc: 95.3613 loss_bbox: 0.2525 loss_mask: 0.2707 +2024/10/28 05:54:36 - mmengine - INFO - Epoch(train) [6][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:48:44 time: 0.5057 data_time: 0.0546 memory: 6183 grad_norm: 4.2253 loss: 0.8320 loss_rpn_cls: 0.0299 loss_rpn_bbox: 0.0446 loss_cls: 0.2412 acc: 91.0645 loss_bbox: 0.2461 loss_mask: 0.2702 +2024/10/28 05:55:00 - mmengine - INFO - Epoch(train) [6][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:48:00 time: 0.4910 data_time: 0.0536 memory: 6187 grad_norm: 4.0234 loss: 0.8219 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0405 loss_cls: 0.2454 acc: 95.4102 loss_bbox: 0.2421 loss_mask: 0.2628 +2024/10/28 05:55:27 - mmengine - INFO - Epoch(train) [6][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:47:19 time: 0.5313 data_time: 0.0655 memory: 6247 grad_norm: 4.2256 loss: 0.8484 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0487 loss_cls: 0.2338 acc: 98.3398 loss_bbox: 0.2688 loss_mask: 0.2666 +2024/10/28 05:55:52 - mmengine - INFO - Epoch(train) [6][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:46:35 time: 0.4999 data_time: 0.0552 memory: 6213 grad_norm: 4.1279 loss: 0.8126 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0450 loss_cls: 0.2235 acc: 90.7715 loss_bbox: 0.2435 loss_mask: 0.2745 +2024/10/28 05:56:18 - mmengine - INFO - Epoch(train) [6][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:45:53 time: 0.5152 data_time: 0.0571 memory: 6420 grad_norm: 4.3885 loss: 0.8537 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0527 loss_cls: 0.2420 acc: 92.6758 loss_bbox: 0.2643 loss_mask: 0.2591 +2024/10/28 05:56:42 - mmengine - INFO - Epoch(train) [6][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:45:10 time: 0.4981 data_time: 0.0501 memory: 6208 grad_norm: 4.2266 loss: 0.7793 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0426 loss_cls: 0.2222 acc: 96.5820 loss_bbox: 0.2390 loss_mask: 0.2438 +2024/10/28 05:57:08 - mmengine - INFO - Epoch(train) [6][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:44:27 time: 0.5067 data_time: 0.0593 memory: 6223 grad_norm: 3.9859 loss: 0.8489 loss_rpn_cls: 0.0372 loss_rpn_bbox: 0.0479 loss_cls: 0.2374 acc: 94.4336 loss_bbox: 0.2572 loss_mask: 0.2692 +2024/10/28 05:57:33 - mmengine - INFO - Epoch(train) [6][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:43:45 time: 0.5077 data_time: 0.0654 memory: 6146 grad_norm: 4.0925 loss: 0.8236 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0511 loss_cls: 0.2228 acc: 95.7520 loss_bbox: 0.2515 loss_mask: 0.2667 +2024/10/28 05:57:58 - mmengine - INFO - Epoch(train) [6][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:43:01 time: 0.4919 data_time: 0.0491 memory: 6128 grad_norm: 4.0088 loss: 0.7904 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0452 loss_cls: 0.2151 acc: 90.5273 loss_bbox: 0.2340 loss_mask: 0.2642 +2024/10/28 05:58:23 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 05:58:23 - mmengine - INFO - Epoch(train) [6][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:42:18 time: 0.5016 data_time: 0.0533 memory: 6121 grad_norm: 4.1155 loss: 0.8380 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0491 loss_cls: 0.2434 acc: 87.9883 loss_bbox: 0.2503 loss_mask: 0.2642 +2024/10/28 05:58:48 - mmengine - INFO - Epoch(train) [6][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:41:35 time: 0.4995 data_time: 0.0571 memory: 6153 grad_norm: 4.3496 loss: 0.8020 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0431 loss_cls: 0.2235 acc: 96.9727 loss_bbox: 0.2333 loss_mask: 0.2703 +2024/10/28 05:59:13 - mmengine - INFO - Epoch(train) [6][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:40:53 time: 0.5084 data_time: 0.0557 memory: 6249 grad_norm: 4.5532 loss: 0.8285 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0493 loss_cls: 0.2376 acc: 93.5547 loss_bbox: 0.2416 loss_mask: 0.2699 +2024/10/28 05:59:38 - mmengine - INFO - Epoch(train) [6][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:40:10 time: 0.5043 data_time: 0.0617 memory: 6058 grad_norm: 4.2837 loss: 0.8405 loss_rpn_cls: 0.0372 loss_rpn_bbox: 0.0537 loss_cls: 0.2265 acc: 90.1855 loss_bbox: 0.2570 loss_mask: 0.2661 +2024/10/28 06:00:03 - mmengine - INFO - Epoch(train) [6][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:39:27 time: 0.4965 data_time: 0.0541 memory: 6351 grad_norm: 3.9934 loss: 0.8037 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0471 loss_cls: 0.2223 acc: 92.1387 loss_bbox: 0.2408 loss_mask: 0.2615 +2024/10/28 06:00:31 - mmengine - INFO - Epoch(train) [6][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:38:47 time: 0.5530 data_time: 0.1070 memory: 6254 grad_norm: 4.0904 loss: 0.8378 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0450 loss_cls: 0.2504 acc: 88.9160 loss_bbox: 0.2538 loss_mask: 0.2572 +2024/10/28 06:00:57 - mmengine - INFO - Epoch(train) [6][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:38:05 time: 0.5112 data_time: 0.0679 memory: 6168 grad_norm: 4.1383 loss: 0.8728 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0521 loss_cls: 0.2500 acc: 93.2617 loss_bbox: 0.2711 loss_mask: 0.2678 +2024/10/28 06:01:22 - mmengine - INFO - Epoch(train) [6][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:37:23 time: 0.5036 data_time: 0.0514 memory: 6293 grad_norm: 4.0266 loss: 0.8293 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0450 loss_cls: 0.2412 acc: 89.2578 loss_bbox: 0.2492 loss_mask: 0.2619 +2024/10/28 06:01:47 - mmengine - INFO - Epoch(train) [6][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:36:40 time: 0.5021 data_time: 0.0547 memory: 6188 grad_norm: 4.1455 loss: 0.8405 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0464 loss_cls: 0.2401 acc: 94.9707 loss_bbox: 0.2523 loss_mask: 0.2716 +2024/10/28 06:02:13 - mmengine - INFO - Epoch(train) [6][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:35:59 time: 0.5247 data_time: 0.0642 memory: 6232 grad_norm: 4.2326 loss: 0.7871 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0460 loss_cls: 0.2233 acc: 90.6250 loss_bbox: 0.2395 loss_mask: 0.2443 +2024/10/28 06:02:38 - mmengine - INFO - Epoch(train) [6][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:35:17 time: 0.5046 data_time: 0.0528 memory: 6231 grad_norm: 4.3374 loss: 0.8658 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0478 loss_cls: 0.2566 acc: 90.7715 loss_bbox: 0.2585 loss_mask: 0.2695 +2024/10/28 06:03:04 - mmengine - INFO - Epoch(train) [6][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:34:35 time: 0.5086 data_time: 0.0510 memory: 6168 grad_norm: 4.0720 loss: 0.8694 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0500 loss_cls: 0.2533 acc: 89.0625 loss_bbox: 0.2678 loss_mask: 0.2662 +2024/10/28 06:03:31 - mmengine - INFO - Epoch(train) [6][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:33:55 time: 0.5505 data_time: 0.0945 memory: 6245 grad_norm: 4.1787 loss: 0.8687 loss_rpn_cls: 0.0378 loss_rpn_bbox: 0.0492 loss_cls: 0.2495 acc: 89.7949 loss_bbox: 0.2707 loss_mask: 0.2615 +2024/10/28 06:03:57 - mmengine - INFO - Epoch(train) [6][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:33:13 time: 0.5101 data_time: 0.0557 memory: 6420 grad_norm: 4.1401 loss: 0.8775 loss_rpn_cls: 0.0351 loss_rpn_bbox: 0.0500 loss_cls: 0.2542 acc: 93.7500 loss_bbox: 0.2651 loss_mask: 0.2731 +2024/10/28 06:04:22 - mmengine - INFO - Epoch(train) [6][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:32:31 time: 0.4985 data_time: 0.0515 memory: 6151 grad_norm: 4.1446 loss: 0.8102 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0491 loss_cls: 0.2249 acc: 94.6777 loss_bbox: 0.2527 loss_mask: 0.2568 +2024/10/28 06:04:47 - mmengine - INFO - Epoch(train) [6][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:31:48 time: 0.4977 data_time: 0.0527 memory: 6206 grad_norm: 4.2303 loss: 0.8507 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0445 loss_cls: 0.2400 acc: 91.3574 loss_bbox: 0.2607 loss_mask: 0.2740 +2024/10/28 06:05:11 - mmengine - INFO - Epoch(train) [6][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:31:06 time: 0.4963 data_time: 0.0504 memory: 6236 grad_norm: 3.9650 loss: 0.8354 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0457 loss_cls: 0.2373 acc: 89.8926 loss_bbox: 0.2543 loss_mask: 0.2678 +2024/10/28 06:05:37 - mmengine - INFO - Epoch(train) [6][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:30:24 time: 0.5093 data_time: 0.0626 memory: 6188 grad_norm: 4.2718 loss: 0.8863 loss_rpn_cls: 0.0351 loss_rpn_bbox: 0.0533 loss_cls: 0.2548 acc: 96.0449 loss_bbox: 0.2725 loss_mask: 0.2706 +2024/10/28 06:06:02 - mmengine - INFO - Epoch(train) [6][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:29:42 time: 0.4945 data_time: 0.0510 memory: 6283 grad_norm: 4.1211 loss: 0.8051 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0458 loss_cls: 0.2256 acc: 88.5254 loss_bbox: 0.2432 loss_mask: 0.2552 +2024/10/28 06:06:31 - mmengine - INFO - Epoch(train) [6][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:29:04 time: 0.5818 data_time: 0.1346 memory: 6109 grad_norm: 4.0914 loss: 0.8033 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0438 loss_cls: 0.2266 acc: 92.7734 loss_bbox: 0.2346 loss_mask: 0.2678 +2024/10/28 06:06:56 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 06:06:56 - mmengine - INFO - Epoch(train) [6][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:28:22 time: 0.5020 data_time: 0.0585 memory: 6315 grad_norm: 4.2396 loss: 0.8462 loss_rpn_cls: 0.0343 loss_rpn_bbox: 0.0476 loss_cls: 0.2428 acc: 92.3828 loss_bbox: 0.2602 loss_mask: 0.2614 +2024/10/28 06:07:21 - mmengine - INFO - Epoch(train) [6][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:27:39 time: 0.4960 data_time: 0.0564 memory: 6259 grad_norm: 4.1923 loss: 0.8970 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0555 loss_cls: 0.2459 acc: 91.6992 loss_bbox: 0.2867 loss_mask: 0.2765 +2024/10/28 06:07:46 - mmengine - INFO - Epoch(train) [6][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:26:58 time: 0.5036 data_time: 0.0534 memory: 6144 grad_norm: 4.0546 loss: 0.8030 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0418 loss_cls: 0.2310 acc: 87.2559 loss_bbox: 0.2469 loss_mask: 0.2529 +2024/10/28 06:08:11 - mmengine - INFO - Epoch(train) [6][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:26:16 time: 0.5010 data_time: 0.0569 memory: 6223 grad_norm: 3.9768 loss: 0.8396 loss_rpn_cls: 0.0369 loss_rpn_bbox: 0.0469 loss_cls: 0.2417 acc: 94.5801 loss_bbox: 0.2537 loss_mask: 0.2604 +2024/10/28 06:08:36 - mmengine - INFO - Epoch(train) [6][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:25:34 time: 0.5054 data_time: 0.0595 memory: 6283 grad_norm: 4.0665 loss: 0.8339 loss_rpn_cls: 0.0360 loss_rpn_bbox: 0.0503 loss_cls: 0.2404 acc: 94.6777 loss_bbox: 0.2493 loss_mask: 0.2579 +2024/10/28 06:09:01 - mmengine - INFO - Epoch(train) [6][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:24:51 time: 0.4911 data_time: 0.0492 memory: 6109 grad_norm: 3.9756 loss: 0.8274 loss_rpn_cls: 0.0312 loss_rpn_bbox: 0.0440 loss_cls: 0.2367 acc: 90.7227 loss_bbox: 0.2440 loss_mask: 0.2716 +2024/10/28 06:09:26 - mmengine - INFO - Epoch(train) [6][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:24:09 time: 0.4973 data_time: 0.0460 memory: 6203 grad_norm: 4.0832 loss: 0.7534 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0418 loss_cls: 0.2166 acc: 95.4102 loss_bbox: 0.2261 loss_mask: 0.2399 +2024/10/28 06:09:51 - mmengine - INFO - Epoch(train) [6][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:23:28 time: 0.5069 data_time: 0.0588 memory: 5997 grad_norm: 4.0583 loss: 0.8193 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0464 loss_cls: 0.2289 acc: 97.2168 loss_bbox: 0.2527 loss_mask: 0.2608 +2024/10/28 06:10:16 - mmengine - INFO - Epoch(train) [6][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:22:46 time: 0.5077 data_time: 0.0537 memory: 6165 grad_norm: 4.0682 loss: 0.8696 loss_rpn_cls: 0.0393 loss_rpn_bbox: 0.0548 loss_cls: 0.2465 acc: 92.7734 loss_bbox: 0.2598 loss_mask: 0.2692 +2024/10/28 06:10:42 - mmengine - INFO - Epoch(train) [6][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:22:05 time: 0.5117 data_time: 0.0546 memory: 6093 grad_norm: 4.1258 loss: 0.8324 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0459 loss_cls: 0.2370 acc: 94.4336 loss_bbox: 0.2525 loss_mask: 0.2644 +2024/10/28 06:11:07 - mmengine - INFO - Epoch(train) [6][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:21:23 time: 0.4930 data_time: 0.0531 memory: 6118 grad_norm: 4.4299 loss: 0.8338 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0457 loss_cls: 0.2469 acc: 91.8945 loss_bbox: 0.2514 loss_mask: 0.2582 +2024/10/28 06:11:32 - mmengine - INFO - Epoch(train) [6][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:20:42 time: 0.5063 data_time: 0.0538 memory: 6384 grad_norm: 4.0762 loss: 0.8522 loss_rpn_cls: 0.0392 loss_rpn_bbox: 0.0522 loss_cls: 0.2286 acc: 94.7754 loss_bbox: 0.2647 loss_mask: 0.2676 +2024/10/28 06:11:58 - mmengine - INFO - Epoch(train) [6][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:20:01 time: 0.5121 data_time: 0.0506 memory: 6149 grad_norm: 4.1156 loss: 0.8529 loss_rpn_cls: 0.0330 loss_rpn_bbox: 0.0474 loss_cls: 0.2477 acc: 95.6543 loss_bbox: 0.2593 loss_mask: 0.2655 +2024/10/28 06:12:23 - mmengine - INFO - Epoch(train) [6][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:19:20 time: 0.5127 data_time: 0.0517 memory: 6142 grad_norm: 4.2424 loss: 0.8450 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0520 loss_cls: 0.2390 acc: 93.0176 loss_bbox: 0.2529 loss_mask: 0.2710 +2024/10/28 06:12:49 - mmengine - INFO - Epoch(train) [6][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:18:39 time: 0.5081 data_time: 0.0540 memory: 6307 grad_norm: 3.9836 loss: 0.8750 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0494 loss_cls: 0.2529 acc: 87.6953 loss_bbox: 0.2641 loss_mask: 0.2753 +2024/10/28 06:13:13 - mmengine - INFO - Epoch(train) [6][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:17:57 time: 0.4973 data_time: 0.0487 memory: 6326 grad_norm: 3.8090 loss: 0.7897 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0454 loss_cls: 0.2147 acc: 90.9668 loss_bbox: 0.2436 loss_mask: 0.2544 +2024/10/28 06:13:38 - mmengine - INFO - Epoch(train) [6][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:17:15 time: 0.4960 data_time: 0.0471 memory: 6097 grad_norm: 3.9635 loss: 0.7942 loss_rpn_cls: 0.0322 loss_rpn_bbox: 0.0468 loss_cls: 0.2255 acc: 94.8242 loss_bbox: 0.2342 loss_mask: 0.2555 +2024/10/28 06:14:03 - mmengine - INFO - Epoch(train) [6][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:16:34 time: 0.5034 data_time: 0.0586 memory: 6367 grad_norm: 4.0729 loss: 0.9034 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0553 loss_cls: 0.2531 acc: 90.5762 loss_bbox: 0.2811 loss_mask: 0.2786 +2024/10/28 06:14:31 - mmengine - INFO - Epoch(train) [6][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:15:55 time: 0.5580 data_time: 0.1060 memory: 6197 grad_norm: 3.9713 loss: 0.8853 loss_rpn_cls: 0.0344 loss_rpn_bbox: 0.0531 loss_cls: 0.2490 acc: 88.1348 loss_bbox: 0.2677 loss_mask: 0.2811 +2024/10/28 06:14:57 - mmengine - INFO - Epoch(train) [6][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:15:14 time: 0.5097 data_time: 0.0511 memory: 6286 grad_norm: 4.1676 loss: 0.8443 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0475 loss_cls: 0.2329 acc: 90.1855 loss_bbox: 0.2523 loss_mask: 0.2804 +2024/10/28 06:15:22 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 06:15:22 - mmengine - INFO - Epoch(train) [6][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:14:33 time: 0.4939 data_time: 0.0531 memory: 6185 grad_norm: 4.1302 loss: 0.8028 loss_rpn_cls: 0.0338 loss_rpn_bbox: 0.0460 loss_cls: 0.2285 acc: 98.0469 loss_bbox: 0.2340 loss_mask: 0.2605 +2024/10/28 06:15:47 - mmengine - INFO - Epoch(train) [6][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:13:52 time: 0.5040 data_time: 0.0574 memory: 6202 grad_norm: 4.0495 loss: 0.8457 loss_rpn_cls: 0.0358 loss_rpn_bbox: 0.0528 loss_cls: 0.2370 acc: 92.3340 loss_bbox: 0.2541 loss_mask: 0.2661 +2024/10/28 06:16:11 - mmengine - INFO - Epoch(train) [6][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:13:10 time: 0.4895 data_time: 0.0516 memory: 6207 grad_norm: 4.1327 loss: 0.8527 loss_rpn_cls: 0.0375 loss_rpn_bbox: 0.0517 loss_cls: 0.2412 acc: 87.3535 loss_bbox: 0.2551 loss_mask: 0.2671 +2024/10/28 06:16:37 - mmengine - INFO - Epoch(train) [6][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:12:29 time: 0.5102 data_time: 0.0517 memory: 6109 grad_norm: 3.8923 loss: 0.8315 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0468 loss_cls: 0.2407 acc: 93.3594 loss_bbox: 0.2499 loss_mask: 0.2632 +2024/10/28 06:17:01 - mmengine - INFO - Epoch(train) [6][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:11:47 time: 0.4929 data_time: 0.0393 memory: 6167 grad_norm: 3.9187 loss: 0.7830 loss_rpn_cls: 0.0288 loss_rpn_bbox: 0.0450 loss_cls: 0.2231 acc: 92.0898 loss_bbox: 0.2319 loss_mask: 0.2543 +2024/10/28 06:17:29 - mmengine - INFO - Epoch(train) [6][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:11:09 time: 0.5565 data_time: 0.1074 memory: 6199 grad_norm: 3.8966 loss: 0.7746 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0449 loss_cls: 0.2251 acc: 87.3535 loss_bbox: 0.2258 loss_mask: 0.2455 +2024/10/28 06:17:54 - mmengine - INFO - Epoch(train) [6][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:10:28 time: 0.4989 data_time: 0.0489 memory: 6235 grad_norm: 4.0223 loss: 0.8188 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0455 loss_cls: 0.2249 acc: 94.8242 loss_bbox: 0.2512 loss_mask: 0.2658 +2024/10/28 06:18:19 - mmengine - INFO - Epoch(train) [6][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:09:46 time: 0.4883 data_time: 0.0429 memory: 6244 grad_norm: 4.0635 loss: 0.7527 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0413 loss_cls: 0.2094 acc: 93.4570 loss_bbox: 0.2218 loss_mask: 0.2499 +2024/10/28 06:18:43 - mmengine - INFO - Epoch(train) [6][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:09:05 time: 0.4917 data_time: 0.0491 memory: 6138 grad_norm: 4.2865 loss: 0.8508 loss_rpn_cls: 0.0390 loss_rpn_bbox: 0.0513 loss_cls: 0.2460 acc: 87.8906 loss_bbox: 0.2487 loss_mask: 0.2658 +2024/10/28 06:19:07 - mmengine - INFO - Epoch(train) [6][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:08:22 time: 0.4750 data_time: 0.0462 memory: 6151 grad_norm: 3.8437 loss: 0.8039 loss_rpn_cls: 0.0309 loss_rpn_bbox: 0.0472 loss_cls: 0.2253 acc: 92.9688 loss_bbox: 0.2281 loss_mask: 0.2724 +2024/10/28 06:19:31 - mmengine - INFO - Epoch(train) [6][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:07:41 time: 0.4883 data_time: 0.0522 memory: 6288 grad_norm: 3.9742 loss: 0.8166 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0478 loss_cls: 0.2212 acc: 96.3867 loss_bbox: 0.2540 loss_mask: 0.2619 +2024/10/28 06:19:56 - mmengine - INFO - Epoch(train) [6][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:07:00 time: 0.4995 data_time: 0.0493 memory: 6211 grad_norm: 4.0215 loss: 0.8089 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0483 loss_cls: 0.2313 acc: 96.2891 loss_bbox: 0.2411 loss_mask: 0.2516 +2024/10/28 06:20:22 - mmengine - INFO - Epoch(train) [6][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:06:19 time: 0.5119 data_time: 0.0577 memory: 6122 grad_norm: 4.2156 loss: 0.8304 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0456 loss_cls: 0.2388 acc: 94.4336 loss_bbox: 0.2588 loss_mask: 0.2583 +2024/10/28 06:20:47 - mmengine - INFO - Epoch(train) [6][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:05:38 time: 0.4933 data_time: 0.0532 memory: 6237 grad_norm: 4.0213 loss: 0.8256 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0523 loss_cls: 0.2282 acc: 94.5801 loss_bbox: 0.2409 loss_mask: 0.2677 +2024/10/28 06:21:12 - mmengine - INFO - Epoch(train) [6][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:04:58 time: 0.5036 data_time: 0.0506 memory: 6353 grad_norm: 4.0458 loss: 0.8050 loss_rpn_cls: 0.0341 loss_rpn_bbox: 0.0507 loss_cls: 0.2228 acc: 91.7969 loss_bbox: 0.2401 loss_mask: 0.2573 +2024/10/28 06:21:37 - mmengine - INFO - Epoch(train) [6][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:04:17 time: 0.5069 data_time: 0.0496 memory: 6275 grad_norm: 4.0290 loss: 0.8312 loss_rpn_cls: 0.0280 loss_rpn_bbox: 0.0442 loss_cls: 0.2371 acc: 86.6699 loss_bbox: 0.2564 loss_mask: 0.2654 +2024/10/28 06:22:02 - mmengine - INFO - Epoch(train) [6][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:03:36 time: 0.4937 data_time: 0.0549 memory: 6275 grad_norm: 3.7822 loss: 0.8182 loss_rpn_cls: 0.0361 loss_rpn_bbox: 0.0443 loss_cls: 0.2332 acc: 84.7656 loss_bbox: 0.2466 loss_mask: 0.2580 +2024/10/28 06:22:27 - mmengine - INFO - Epoch(train) [6][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:02:55 time: 0.5020 data_time: 0.0544 memory: 6318 grad_norm: 4.1055 loss: 0.8751 loss_rpn_cls: 0.0336 loss_rpn_bbox: 0.0508 loss_cls: 0.2519 acc: 91.2598 loss_bbox: 0.2674 loss_mask: 0.2714 +2024/10/28 06:22:52 - mmengine - INFO - Epoch(train) [6][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:02:14 time: 0.4956 data_time: 0.0453 memory: 6203 grad_norm: 3.9334 loss: 0.7824 loss_rpn_cls: 0.0293 loss_rpn_bbox: 0.0406 loss_cls: 0.2213 acc: 93.4082 loss_bbox: 0.2398 loss_mask: 0.2513 +2024/10/28 06:23:16 - mmengine - INFO - Epoch(train) [6][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:01:33 time: 0.4962 data_time: 0.0530 memory: 6221 grad_norm: 4.3323 loss: 0.8610 loss_rpn_cls: 0.0311 loss_rpn_bbox: 0.0466 loss_cls: 0.2497 acc: 95.3125 loss_bbox: 0.2566 loss_mask: 0.2771 +2024/10/28 06:23:37 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 06:23:37 - mmengine - INFO - Saving checkpoint at 6 epochs +2024/10/28 06:23:47 - mmengine - INFO - Epoch(val) [6][ 50/1250] eta: 0:02:13 time: 0.1111 data_time: 0.0056 memory: 6741 +2024/10/28 06:23:53 - mmengine - INFO - Epoch(val) [6][ 100/1250] eta: 0:02:06 time: 0.1087 data_time: 0.0035 memory: 1114 +2024/10/28 06:23:58 - mmengine - INFO - Epoch(val) [6][ 150/1250] eta: 0:02:00 time: 0.1079 data_time: 0.0042 memory: 1114 +2024/10/28 06:24:04 - mmengine - INFO - Epoch(val) [6][ 200/1250] eta: 0:01:56 time: 0.1159 data_time: 0.0053 memory: 1114 +2024/10/28 06:24:09 - mmengine - INFO - Epoch(val) [6][ 250/1250] eta: 0:01:50 time: 0.1086 data_time: 0.0038 memory: 1221 +2024/10/28 06:24:15 - mmengine - INFO - Epoch(val) [6][ 300/1250] eta: 0:01:45 time: 0.1156 data_time: 0.0046 memory: 1114 +2024/10/28 06:24:20 - mmengine - INFO - Epoch(val) [6][ 350/1250] eta: 0:01:39 time: 0.1078 data_time: 0.0044 memory: 1117 +2024/10/28 06:24:26 - mmengine - INFO - Epoch(val) [6][ 400/1250] eta: 0:01:33 time: 0.1066 data_time: 0.0046 memory: 1114 +2024/10/28 06:24:31 - mmengine - INFO - Epoch(val) [6][ 450/1250] eta: 0:01:27 time: 0.1072 data_time: 0.0045 memory: 1082 +2024/10/28 06:24:37 - mmengine - INFO - Epoch(val) [6][ 500/1250] eta: 0:01:22 time: 0.1090 data_time: 0.0051 memory: 1082 +2024/10/28 06:24:42 - mmengine - INFO - Epoch(val) [6][ 550/1250] eta: 0:01:16 time: 0.1088 data_time: 0.0052 memory: 1176 +2024/10/28 06:24:48 - mmengine - INFO - Epoch(val) [6][ 600/1250] eta: 0:01:11 time: 0.1120 data_time: 0.0066 memory: 1114 +2024/10/28 06:24:53 - mmengine - INFO - Epoch(val) [6][ 650/1250] eta: 0:01:05 time: 0.1059 data_time: 0.0044 memory: 1209 +2024/10/28 06:24:59 - mmengine - INFO - Epoch(val) [6][ 700/1250] eta: 0:01:00 time: 0.1134 data_time: 0.0062 memory: 1082 +2024/10/28 06:25:04 - mmengine - INFO - Epoch(val) [6][ 750/1250] eta: 0:00:55 time: 0.1143 data_time: 0.0067 memory: 1082 +2024/10/28 06:25:10 - mmengine - INFO - Epoch(val) [6][ 800/1250] eta: 0:00:49 time: 0.1095 data_time: 0.0051 memory: 1114 +2024/10/28 06:25:15 - mmengine - INFO - Epoch(val) [6][ 850/1250] eta: 0:00:44 time: 0.1090 data_time: 0.0055 memory: 1176 +2024/10/28 06:25:21 - mmengine - INFO - Epoch(val) [6][ 900/1250] eta: 0:00:38 time: 0.1112 data_time: 0.0058 memory: 1114 +2024/10/28 06:25:27 - mmengine - INFO - Epoch(val) [6][ 950/1250] eta: 0:00:33 time: 0.1145 data_time: 0.0076 memory: 1219 +2024/10/28 06:25:32 - mmengine - INFO - Epoch(val) [6][1000/1250] eta: 0:00:27 time: 0.1061 data_time: 0.0056 memory: 1034 +2024/10/28 06:25:38 - mmengine - INFO - Epoch(val) [6][1050/1250] eta: 0:00:22 time: 0.1169 data_time: 0.0074 memory: 1114 +2024/10/28 06:25:43 - mmengine - INFO - Epoch(val) [6][1100/1250] eta: 0:00:16 time: 0.1107 data_time: 0.0049 memory: 1114 +2024/10/28 06:25:49 - mmengine - INFO - Epoch(val) [6][1150/1250] eta: 0:00:11 time: 0.1112 data_time: 0.0061 memory: 1114 +2024/10/28 06:25:54 - mmengine - INFO - Epoch(val) [6][1200/1250] eta: 0:00:05 time: 0.1089 data_time: 0.0047 memory: 1114 +2024/10/28 06:26:00 - mmengine - INFO - Epoch(val) [6][1250/1250] eta: 0:00:00 time: 0.1080 data_time: 0.0056 memory: 1114 +2024/10/28 06:26:14 - mmengine - INFO - Evaluating bbox... +2024/10/28 06:26:44 - mmengine - INFO - bbox_mAP_copypaste: 0.329 0.536 0.357 0.176 0.360 0.450 +2024/10/28 06:26:44 - mmengine - INFO - Evaluating segm... +2024/10/28 06:27:20 - mmengine - INFO - segm_mAP_copypaste: 0.311 0.512 0.326 0.131 0.333 0.476 +2024/10/28 06:27:21 - mmengine - INFO - Epoch(val) [6][1250/1250] coco/bbox_mAP: 0.3290 coco/bbox_mAP_50: 0.5360 coco/bbox_mAP_75: 0.3570 coco/bbox_mAP_s: 0.1760 coco/bbox_mAP_m: 0.3600 coco/bbox_mAP_l: 0.4500 coco/segm_mAP: 0.3110 coco/segm_mAP_50: 0.5120 coco/segm_mAP_75: 0.3260 coco/segm_mAP_s: 0.1310 coco/segm_mAP_m: 0.3330 coco/segm_mAP_l: 0.4760 data_time: 0.0053 time: 0.1104 +2024/10/28 06:27:39 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 06:28:07 - mmengine - INFO - Epoch(train) [7][ 50/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:00:55 time: 0.9095 data_time: 0.0408 memory: 6221 grad_norm: 4.0536 loss: 0.7991 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0475 loss_cls: 0.2185 acc: 91.5039 loss_bbox: 0.2488 loss_mask: 0.2539 +2024/10/28 06:28:53 - mmengine - INFO - Epoch(train) [7][ 100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:00:35 time: 0.9143 data_time: 0.0494 memory: 6156 grad_norm: 3.9669 loss: 0.8690 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0528 loss_cls: 0.2402 acc: 84.7656 loss_bbox: 0.2774 loss_mask: 0.2666 +2024/10/28 06:29:39 - mmengine - INFO - Epoch(train) [7][ 150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 8:00:15 time: 0.9265 data_time: 0.0412 memory: 6176 grad_norm: 4.0441 loss: 0.8017 loss_rpn_cls: 0.0260 loss_rpn_bbox: 0.0438 loss_cls: 0.2187 acc: 96.6797 loss_bbox: 0.2470 loss_mask: 0.2662 +2024/10/28 06:30:26 - mmengine - INFO - Epoch(train) [7][ 200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:59:56 time: 0.9314 data_time: 0.0390 memory: 6283 grad_norm: 4.2064 loss: 0.8126 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0482 loss_cls: 0.2415 acc: 91.9922 loss_bbox: 0.2458 loss_mask: 0.2465 +2024/10/28 06:31:14 - mmengine - INFO - Epoch(train) [7][ 250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:59:38 time: 0.9530 data_time: 0.0418 memory: 6397 grad_norm: 4.0815 loss: 0.8077 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0458 loss_cls: 0.2314 acc: 97.9492 loss_bbox: 0.2493 loss_mask: 0.2528 +2024/10/28 06:31:59 - mmengine - INFO - Epoch(train) [7][ 300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:59:17 time: 0.9045 data_time: 0.0373 memory: 6138 grad_norm: 4.0122 loss: 0.7574 loss_rpn_cls: 0.0237 loss_rpn_bbox: 0.0396 loss_cls: 0.2158 acc: 88.5254 loss_bbox: 0.2358 loss_mask: 0.2425 +2024/10/28 06:32:45 - mmengine - INFO - Epoch(train) [7][ 350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:58:57 time: 0.9205 data_time: 0.0396 memory: 6139 grad_norm: 3.9493 loss: 0.8037 loss_rpn_cls: 0.0365 loss_rpn_bbox: 0.0458 loss_cls: 0.2141 acc: 93.7500 loss_bbox: 0.2450 loss_mask: 0.2624 +2024/10/28 06:33:30 - mmengine - INFO - Epoch(train) [7][ 400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:58:36 time: 0.9103 data_time: 0.0425 memory: 6252 grad_norm: 3.9679 loss: 0.8152 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0456 loss_cls: 0.2236 acc: 87.5000 loss_bbox: 0.2447 loss_mask: 0.2705 +2024/10/28 06:34:16 - mmengine - INFO - Epoch(train) [7][ 450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:58:16 time: 0.9116 data_time: 0.0397 memory: 6316 grad_norm: 4.0292 loss: 0.7535 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0409 loss_cls: 0.2085 acc: 97.7051 loss_bbox: 0.2311 loss_mask: 0.2479 +2024/10/28 06:35:02 - mmengine - INFO - Epoch(train) [7][ 500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:57:55 time: 0.9132 data_time: 0.0419 memory: 6219 grad_norm: 4.0991 loss: 0.8192 loss_rpn_cls: 0.0287 loss_rpn_bbox: 0.0455 loss_cls: 0.2320 acc: 95.0195 loss_bbox: 0.2603 loss_mask: 0.2527 +2024/10/28 06:35:52 - mmengine - INFO - Epoch(train) [7][ 550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:57:39 time: 0.9999 data_time: 0.1131 memory: 6296 grad_norm: 3.9075 loss: 0.7637 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0447 loss_cls: 0.2085 acc: 94.2383 loss_bbox: 0.2274 loss_mask: 0.2537 +2024/10/28 06:36:39 - mmengine - INFO - Epoch(train) [7][ 600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:57:20 time: 0.9565 data_time: 0.0428 memory: 6165 grad_norm: 3.9347 loss: 0.7811 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0484 loss_cls: 0.2117 acc: 98.3887 loss_bbox: 0.2352 loss_mask: 0.2554 +2024/10/28 06:37:26 - mmengine - INFO - Epoch(train) [7][ 650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:57:01 time: 0.9401 data_time: 0.0502 memory: 6236 grad_norm: 3.9548 loss: 0.8513 loss_rpn_cls: 0.0348 loss_rpn_bbox: 0.0514 loss_cls: 0.2422 acc: 93.2129 loss_bbox: 0.2611 loss_mask: 0.2619 +2024/10/28 06:38:11 - mmengine - INFO - Epoch(train) [7][ 700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:56:39 time: 0.8983 data_time: 0.0480 memory: 6351 grad_norm: 3.8091 loss: 0.7907 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0452 loss_cls: 0.2258 acc: 89.7949 loss_bbox: 0.2422 loss_mask: 0.2484 +2024/10/28 06:38:55 - mmengine - INFO - Epoch(train) [7][ 750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:56:16 time: 0.8691 data_time: 0.0478 memory: 6069 grad_norm: 3.7560 loss: 0.7888 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0446 loss_cls: 0.2142 acc: 93.4082 loss_bbox: 0.2420 loss_mask: 0.2595 +2024/10/28 06:39:42 - mmengine - INFO - Epoch(train) [7][ 800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:55:57 time: 0.9435 data_time: 0.0475 memory: 6330 grad_norm: 4.0618 loss: 0.8330 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0507 loss_cls: 0.2382 acc: 97.2656 loss_bbox: 0.2554 loss_mask: 0.2573 +2024/10/28 06:40:26 - mmengine - INFO - Epoch(train) [7][ 850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:55:34 time: 0.8793 data_time: 0.0458 memory: 6342 grad_norm: 4.1765 loss: 0.8070 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0462 loss_cls: 0.2278 acc: 92.4316 loss_bbox: 0.2419 loss_mask: 0.2602 +2024/10/28 06:41:11 - mmengine - INFO - Epoch(train) [7][ 900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:55:13 time: 0.8971 data_time: 0.0520 memory: 6227 grad_norm: 3.9630 loss: 0.7926 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0462 loss_cls: 0.2187 acc: 92.4316 loss_bbox: 0.2426 loss_mask: 0.2580 +2024/10/28 06:41:56 - mmengine - INFO - Epoch(train) [7][ 950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:54:51 time: 0.9125 data_time: 0.0513 memory: 6359 grad_norm: 4.0762 loss: 0.8411 loss_rpn_cls: 0.0319 loss_rpn_bbox: 0.0495 loss_cls: 0.2416 acc: 93.3105 loss_bbox: 0.2585 loss_mask: 0.2596 +2024/10/28 06:42:47 - mmengine - INFO - Epoch(train) [7][1000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:54:35 time: 1.0137 data_time: 0.0586 memory: 6295 grad_norm: 4.0483 loss: 0.8468 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0495 loss_cls: 0.2382 acc: 95.8984 loss_bbox: 0.2606 loss_mask: 0.2686 +2024/10/28 06:43:05 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 06:43:34 - mmengine - INFO - Epoch(train) [7][1050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:54:15 time: 0.9329 data_time: 0.0464 memory: 6157 grad_norm: 4.0700 loss: 0.7870 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0454 loss_cls: 0.2123 acc: 92.6270 loss_bbox: 0.2439 loss_mask: 0.2537 +2024/10/28 06:44:20 - mmengine - INFO - Epoch(train) [7][1100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:53:55 time: 0.9350 data_time: 0.0490 memory: 6075 grad_norm: 4.1435 loss: 0.8546 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0487 loss_cls: 0.2415 acc: 91.4551 loss_bbox: 0.2630 loss_mask: 0.2705 +2024/10/28 06:45:06 - mmengine - INFO - Epoch(train) [7][1150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:53:33 time: 0.9051 data_time: 0.0432 memory: 6183 grad_norm: 3.9914 loss: 0.7860 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0426 loss_cls: 0.2104 acc: 91.7969 loss_bbox: 0.2396 loss_mask: 0.2651 +2024/10/28 06:45:52 - mmengine - INFO - Epoch(train) [7][1200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:53:12 time: 0.9285 data_time: 0.0462 memory: 6213 grad_norm: 4.1929 loss: 0.7777 loss_rpn_cls: 0.0266 loss_rpn_bbox: 0.0421 loss_cls: 0.2165 acc: 93.9941 loss_bbox: 0.2323 loss_mask: 0.2603 +2024/10/28 06:46:37 - mmengine - INFO - Epoch(train) [7][1250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:52:50 time: 0.8930 data_time: 0.0501 memory: 6392 grad_norm: 4.0426 loss: 0.8419 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0479 loss_cls: 0.2341 acc: 94.0430 loss_bbox: 0.2561 loss_mask: 0.2733 +2024/10/28 06:47:25 - mmengine - INFO - Epoch(train) [7][1300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:52:31 time: 0.9543 data_time: 0.0509 memory: 6219 grad_norm: 4.0398 loss: 0.7978 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0473 loss_cls: 0.2256 acc: 94.9219 loss_bbox: 0.2387 loss_mask: 0.2548 +2024/10/28 06:48:11 - mmengine - INFO - Epoch(train) [7][1350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:52:10 time: 0.9285 data_time: 0.0445 memory: 6134 grad_norm: 4.2162 loss: 0.7687 loss_rpn_cls: 0.0252 loss_rpn_bbox: 0.0423 loss_cls: 0.2181 acc: 96.4844 loss_bbox: 0.2313 loss_mask: 0.2518 +2024/10/28 06:49:01 - mmengine - INFO - Epoch(train) [7][1400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:51:53 time: 1.0079 data_time: 0.0537 memory: 6309 grad_norm: 4.0354 loss: 0.8367 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0501 loss_cls: 0.2372 acc: 92.0898 loss_bbox: 0.2548 loss_mask: 0.2633 +2024/10/28 06:49:52 - mmengine - INFO - Epoch(train) [7][1450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:51:36 time: 1.0172 data_time: 0.1348 memory: 6236 grad_norm: 4.1465 loss: 0.7947 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0430 loss_cls: 0.2275 acc: 94.2871 loss_bbox: 0.2424 loss_mask: 0.2532 +2024/10/28 06:50:36 - mmengine - INFO - Epoch(train) [7][1500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:51:12 time: 0.8663 data_time: 0.0450 memory: 6066 grad_norm: 3.9795 loss: 0.7338 loss_rpn_cls: 0.0269 loss_rpn_bbox: 0.0374 loss_cls: 0.1968 acc: 91.8457 loss_bbox: 0.2247 loss_mask: 0.2480 +2024/10/28 06:51:23 - mmengine - INFO - Epoch(train) [7][1550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:50:52 time: 0.9407 data_time: 0.0492 memory: 6135 grad_norm: 4.0151 loss: 0.7779 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0436 loss_cls: 0.2125 acc: 93.2617 loss_bbox: 0.2409 loss_mask: 0.2501 +2024/10/28 06:52:09 - mmengine - INFO - Epoch(train) [7][1600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:50:31 time: 0.9380 data_time: 0.0507 memory: 6368 grad_norm: 3.8702 loss: 0.8436 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0483 loss_cls: 0.2280 acc: 90.9180 loss_bbox: 0.2656 loss_mask: 0.2704 +2024/10/28 06:52:54 - mmengine - INFO - Epoch(train) [7][1650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:50:08 time: 0.8820 data_time: 0.0474 memory: 6077 grad_norm: 3.7970 loss: 0.8150 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0456 loss_cls: 0.2293 acc: 92.2852 loss_bbox: 0.2506 loss_mask: 0.2569 +2024/10/28 06:53:38 - mmengine - INFO - Epoch(train) [7][1700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:49:45 time: 0.8962 data_time: 0.0479 memory: 6260 grad_norm: 4.0135 loss: 0.7623 loss_rpn_cls: 0.0259 loss_rpn_bbox: 0.0426 loss_cls: 0.2049 acc: 93.0664 loss_bbox: 0.2357 loss_mask: 0.2531 +2024/10/28 06:54:28 - mmengine - INFO - Epoch(train) [7][1750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:49:26 time: 0.9827 data_time: 0.0468 memory: 6150 grad_norm: 4.0643 loss: 0.8103 loss_rpn_cls: 0.0297 loss_rpn_bbox: 0.0474 loss_cls: 0.2179 acc: 86.6699 loss_bbox: 0.2438 loss_mask: 0.2715 +2024/10/28 06:55:13 - mmengine - INFO - Epoch(train) [7][1800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:49:04 time: 0.9021 data_time: 0.0505 memory: 6278 grad_norm: 4.0255 loss: 0.7791 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0412 loss_cls: 0.2144 acc: 93.8965 loss_bbox: 0.2390 loss_mask: 0.2572 +2024/10/28 06:55:58 - mmengine - INFO - Epoch(train) [7][1850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:48:42 time: 0.9160 data_time: 0.0516 memory: 6087 grad_norm: 3.9484 loss: 0.8243 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0496 loss_cls: 0.2294 acc: 89.0625 loss_bbox: 0.2544 loss_mask: 0.2592 +2024/10/28 06:56:44 - mmengine - INFO - Epoch(train) [7][1900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:48:20 time: 0.9166 data_time: 0.0549 memory: 6284 grad_norm: 3.9879 loss: 0.8373 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0503 loss_cls: 0.2332 acc: 89.8926 loss_bbox: 0.2560 loss_mask: 0.2663 +2024/10/28 06:57:28 - mmengine - INFO - Epoch(train) [7][1950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:47:56 time: 0.8759 data_time: 0.0488 memory: 6227 grad_norm: 4.0480 loss: 0.7708 loss_rpn_cls: 0.0296 loss_rpn_bbox: 0.0439 loss_cls: 0.2167 acc: 93.7012 loss_bbox: 0.2277 loss_mask: 0.2528 +2024/10/28 06:58:14 - mmengine - INFO - Epoch(train) [7][2000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:47:34 time: 0.9178 data_time: 0.0560 memory: 6137 grad_norm: 3.9420 loss: 0.8554 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0486 loss_cls: 0.2361 acc: 90.3320 loss_bbox: 0.2724 loss_mask: 0.2670 +2024/10/28 06:58:34 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 06:59:01 - mmengine - INFO - Epoch(train) [7][2050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:47:13 time: 0.9365 data_time: 0.0485 memory: 6197 grad_norm: 4.0450 loss: 0.7953 loss_rpn_cls: 0.0288 loss_rpn_bbox: 0.0425 loss_cls: 0.2259 acc: 95.3125 loss_bbox: 0.2424 loss_mask: 0.2557 +2024/10/28 06:59:53 - mmengine - INFO - Epoch(train) [7][2100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:46:57 time: 1.0476 data_time: 0.1265 memory: 6048 grad_norm: 3.9643 loss: 0.7400 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0388 loss_cls: 0.2004 acc: 96.2891 loss_bbox: 0.2160 loss_mask: 0.2544 +2024/10/28 07:00:41 - mmengine - INFO - Epoch(train) [7][2150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:46:36 time: 0.9509 data_time: 0.0546 memory: 6281 grad_norm: 4.0646 loss: 0.8716 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0552 loss_cls: 0.2560 acc: 85.0586 loss_bbox: 0.2689 loss_mask: 0.2587 +2024/10/28 07:01:25 - mmengine - INFO - Epoch(train) [7][2200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:46:12 time: 0.8901 data_time: 0.0487 memory: 6254 grad_norm: 4.0302 loss: 0.8070 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0484 loss_cls: 0.2215 acc: 87.9883 loss_bbox: 0.2416 loss_mask: 0.2628 +2024/10/28 07:02:12 - mmengine - INFO - Epoch(train) [7][2250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:45:51 time: 0.9325 data_time: 0.0521 memory: 6254 grad_norm: 4.0536 loss: 0.7824 loss_rpn_cls: 0.0269 loss_rpn_bbox: 0.0447 loss_cls: 0.2132 acc: 97.9980 loss_bbox: 0.2325 loss_mask: 0.2650 +2024/10/28 07:03:00 - mmengine - INFO - Epoch(train) [7][2300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:45:31 time: 0.9642 data_time: 0.0600 memory: 6345 grad_norm: 4.3410 loss: 0.8644 loss_rpn_cls: 0.0384 loss_rpn_bbox: 0.0529 loss_cls: 0.2337 acc: 92.6270 loss_bbox: 0.2677 loss_mask: 0.2718 +2024/10/28 07:03:45 - mmengine - INFO - Epoch(train) [7][2350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:45:07 time: 0.8952 data_time: 0.0529 memory: 6102 grad_norm: 3.8671 loss: 0.8057 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0465 loss_cls: 0.2263 acc: 92.9688 loss_bbox: 0.2350 loss_mask: 0.2662 +2024/10/28 07:04:31 - mmengine - INFO - Epoch(train) [7][2400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:44:45 time: 0.9184 data_time: 0.0504 memory: 6222 grad_norm: 3.8649 loss: 0.7952 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0457 loss_cls: 0.2181 acc: 93.0176 loss_bbox: 0.2460 loss_mask: 0.2550 +2024/10/28 07:05:17 - mmengine - INFO - Epoch(train) [7][2450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:44:22 time: 0.9201 data_time: 0.0525 memory: 6240 grad_norm: 4.1754 loss: 0.8667 loss_rpn_cls: 0.0287 loss_rpn_bbox: 0.0500 loss_cls: 0.2485 acc: 89.0625 loss_bbox: 0.2742 loss_mask: 0.2652 +2024/10/28 07:06:03 - mmengine - INFO - Epoch(train) [7][2500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:44:00 time: 0.9228 data_time: 0.0492 memory: 6377 grad_norm: 4.1601 loss: 0.8000 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0432 loss_cls: 0.2335 acc: 91.3086 loss_bbox: 0.2432 loss_mask: 0.2530 +2024/10/28 07:06:53 - mmengine - INFO - Epoch(train) [7][2550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:43:41 time: 1.0032 data_time: 0.1009 memory: 6304 grad_norm: 3.8033 loss: 0.8294 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0490 loss_cls: 0.2293 acc: 91.8457 loss_bbox: 0.2506 loss_mask: 0.2681 +2024/10/28 07:07:39 - mmengine - INFO - Epoch(train) [7][2600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:43:19 time: 0.9234 data_time: 0.0472 memory: 6255 grad_norm: 3.9754 loss: 0.7825 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0410 loss_cls: 0.2241 acc: 92.4316 loss_bbox: 0.2453 loss_mask: 0.2472 +2024/10/28 07:08:24 - mmengine - INFO - Epoch(train) [7][2650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:42:55 time: 0.8847 data_time: 0.0574 memory: 6191 grad_norm: 3.9697 loss: 0.8300 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0456 loss_cls: 0.2261 acc: 93.4082 loss_bbox: 0.2594 loss_mask: 0.2717 +2024/10/28 07:09:09 - mmengine - INFO - Epoch(train) [7][2700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:42:32 time: 0.9111 data_time: 0.0563 memory: 6234 grad_norm: 3.9146 loss: 0.8453 loss_rpn_cls: 0.0309 loss_rpn_bbox: 0.0519 loss_cls: 0.2333 acc: 91.9922 loss_bbox: 0.2609 loss_mask: 0.2683 +2024/10/28 07:09:54 - mmengine - INFO - Epoch(train) [7][2750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:42:08 time: 0.9010 data_time: 0.0502 memory: 6353 grad_norm: 4.0533 loss: 0.8199 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0456 loss_cls: 0.2290 acc: 89.4531 loss_bbox: 0.2532 loss_mask: 0.2611 +2024/10/28 07:10:39 - mmengine - INFO - Epoch(train) [7][2800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:41:45 time: 0.9050 data_time: 0.0451 memory: 6171 grad_norm: 4.2281 loss: 0.8127 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0463 loss_cls: 0.2300 acc: 93.3105 loss_bbox: 0.2413 loss_mask: 0.2637 +2024/10/28 07:11:24 - mmengine - INFO - Epoch(train) [7][2850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:41:21 time: 0.8958 data_time: 0.0456 memory: 6245 grad_norm: 3.8905 loss: 0.8027 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0442 loss_cls: 0.2228 acc: 97.8516 loss_bbox: 0.2367 loss_mask: 0.2686 +2024/10/28 07:12:13 - mmengine - INFO - Epoch(train) [7][2900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:41:01 time: 0.9743 data_time: 0.0479 memory: 6272 grad_norm: 3.9036 loss: 0.8065 loss_rpn_cls: 0.0346 loss_rpn_bbox: 0.0473 loss_cls: 0.2212 acc: 93.8477 loss_bbox: 0.2513 loss_mask: 0.2522 +2024/10/28 07:13:02 - mmengine - INFO - Epoch(train) [7][2950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:40:40 time: 0.9747 data_time: 0.0529 memory: 6203 grad_norm: 4.1286 loss: 0.8601 loss_rpn_cls: 0.0366 loss_rpn_bbox: 0.0540 loss_cls: 0.2397 acc: 92.7734 loss_bbox: 0.2684 loss_mask: 0.2615 +2024/10/28 07:13:45 - mmengine - INFO - Epoch(train) [7][3000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:40:15 time: 0.8727 data_time: 0.0507 memory: 6311 grad_norm: 4.1346 loss: 0.8323 loss_rpn_cls: 0.0318 loss_rpn_bbox: 0.0483 loss_cls: 0.2334 acc: 88.6719 loss_bbox: 0.2561 loss_mask: 0.2627 +2024/10/28 07:14:04 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 07:14:31 - mmengine - INFO - Epoch(train) [7][3050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:39:52 time: 0.9159 data_time: 0.0487 memory: 6208 grad_norm: 3.9489 loss: 0.7902 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0448 loss_cls: 0.2170 acc: 95.2148 loss_bbox: 0.2352 loss_mask: 0.2683 +2024/10/28 07:15:15 - mmengine - INFO - Epoch(train) [7][3100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:39:27 time: 0.8738 data_time: 0.0479 memory: 6219 grad_norm: 3.7622 loss: 0.8167 loss_rpn_cls: 0.0319 loss_rpn_bbox: 0.0464 loss_cls: 0.2278 acc: 92.7734 loss_bbox: 0.2543 loss_mask: 0.2563 +2024/10/28 07:16:03 - mmengine - INFO - Epoch(train) [7][3150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:39:06 time: 0.9612 data_time: 0.0502 memory: 6056 grad_norm: 4.0173 loss: 0.8150 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0446 loss_cls: 0.2324 acc: 87.6465 loss_bbox: 0.2442 loss_mask: 0.2651 +2024/10/28 07:16:53 - mmengine - INFO - Epoch(train) [7][3200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:38:46 time: 0.9952 data_time: 0.0926 memory: 6234 grad_norm: 3.9281 loss: 0.7831 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0454 loss_cls: 0.2125 acc: 86.7676 loss_bbox: 0.2329 loss_mask: 0.2595 +2024/10/28 07:17:39 - mmengine - INFO - Epoch(train) [7][3250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:38:22 time: 0.9205 data_time: 0.0569 memory: 6264 grad_norm: 4.0012 loss: 0.8412 loss_rpn_cls: 0.0340 loss_rpn_bbox: 0.0529 loss_cls: 0.2339 acc: 92.5293 loss_bbox: 0.2544 loss_mask: 0.2660 +2024/10/28 07:18:26 - mmengine - INFO - Epoch(train) [7][3300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:38:01 time: 0.9567 data_time: 0.0461 memory: 6142 grad_norm: 3.9800 loss: 0.7672 loss_rpn_cls: 0.0257 loss_rpn_bbox: 0.0416 loss_cls: 0.2103 acc: 95.4102 loss_bbox: 0.2319 loss_mask: 0.2577 +2024/10/28 07:19:11 - mmengine - INFO - Epoch(train) [7][3350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:37:36 time: 0.8914 data_time: 0.0481 memory: 6121 grad_norm: 3.9601 loss: 0.7945 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0453 loss_cls: 0.2169 acc: 93.7012 loss_bbox: 0.2364 loss_mask: 0.2659 +2024/10/28 07:19:57 - mmengine - INFO - Epoch(train) [7][3400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:37:13 time: 0.9140 data_time: 0.0446 memory: 6331 grad_norm: 3.8395 loss: 0.7680 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0411 loss_cls: 0.2151 acc: 96.4844 loss_bbox: 0.2303 loss_mask: 0.2498 +2024/10/28 07:20:43 - mmengine - INFO - Epoch(train) [7][3450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:36:49 time: 0.9228 data_time: 0.0470 memory: 6132 grad_norm: 3.9264 loss: 0.8165 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0438 loss_cls: 0.2308 acc: 97.3145 loss_bbox: 0.2482 loss_mask: 0.2645 +2024/10/28 07:21:31 - mmengine - INFO - Epoch(train) [7][3500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:36:28 time: 0.9616 data_time: 0.0628 memory: 6243 grad_norm: 3.8748 loss: 0.8115 loss_rpn_cls: 0.0317 loss_rpn_bbox: 0.0499 loss_cls: 0.2208 acc: 92.0898 loss_bbox: 0.2469 loss_mask: 0.2622 +2024/10/28 07:22:19 - mmengine - INFO - Epoch(train) [7][3550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:36:06 time: 0.9560 data_time: 0.0527 memory: 6419 grad_norm: 4.1426 loss: 0.8539 loss_rpn_cls: 0.0357 loss_rpn_bbox: 0.0518 loss_cls: 0.2365 acc: 93.2129 loss_bbox: 0.2616 loss_mask: 0.2683 +2024/10/28 07:23:04 - mmengine - INFO - Epoch(train) [7][3600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:35:41 time: 0.8962 data_time: 0.0474 memory: 6298 grad_norm: 4.0013 loss: 0.8017 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0432 loss_cls: 0.2370 acc: 92.3828 loss_bbox: 0.2404 loss_mask: 0.2527 +2024/10/28 07:23:52 - mmengine - INFO - Epoch(train) [7][3650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:35:20 time: 0.9763 data_time: 0.0853 memory: 6154 grad_norm: 3.8439 loss: 0.7867 loss_rpn_cls: 0.0242 loss_rpn_bbox: 0.0415 loss_cls: 0.2275 acc: 87.0117 loss_bbox: 0.2329 loss_mask: 0.2607 +2024/10/28 07:24:40 - mmengine - INFO - Epoch(train) [7][3700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:34:58 time: 0.9512 data_time: 0.0524 memory: 6278 grad_norm: 3.9560 loss: 0.7949 loss_rpn_cls: 0.0248 loss_rpn_bbox: 0.0454 loss_cls: 0.2245 acc: 92.3828 loss_bbox: 0.2463 loss_mask: 0.2538 +2024/10/28 07:25:26 - mmengine - INFO - Epoch(train) [7][3750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:34:34 time: 0.9159 data_time: 0.0478 memory: 6294 grad_norm: 3.8892 loss: 0.7269 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0410 loss_cls: 0.1884 acc: 93.8965 loss_bbox: 0.2231 loss_mask: 0.2508 +2024/10/28 07:26:13 - mmengine - INFO - Epoch(train) [7][3800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:34:11 time: 0.9365 data_time: 0.0434 memory: 6127 grad_norm: 3.7824 loss: 0.7813 loss_rpn_cls: 0.0260 loss_rpn_bbox: 0.0408 loss_cls: 0.2193 acc: 93.8965 loss_bbox: 0.2336 loss_mask: 0.2616 +2024/10/28 07:26:58 - mmengine - INFO - Epoch(train) [7][3850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:33:47 time: 0.9129 data_time: 0.0564 memory: 6287 grad_norm: 3.9165 loss: 0.8619 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0456 loss_cls: 0.2522 acc: 90.5762 loss_bbox: 0.2645 loss_mask: 0.2658 +2024/10/28 07:27:46 - mmengine - INFO - Epoch(train) [7][3900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:33:25 time: 0.9630 data_time: 0.0542 memory: 6334 grad_norm: 3.9174 loss: 0.8332 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0482 loss_cls: 0.2334 acc: 89.2578 loss_bbox: 0.2572 loss_mask: 0.2610 +2024/10/28 07:28:32 - mmengine - INFO - Epoch(train) [7][3950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:33:01 time: 0.9113 data_time: 0.0479 memory: 6259 grad_norm: 4.0098 loss: 0.8475 loss_rpn_cls: 0.0312 loss_rpn_bbox: 0.0454 loss_cls: 0.2518 acc: 91.3574 loss_bbox: 0.2594 loss_mask: 0.2598 +2024/10/28 07:29:16 - mmengine - INFO - Epoch(train) [7][4000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:32:35 time: 0.8758 data_time: 0.0411 memory: 6296 grad_norm: 4.1300 loss: 0.8152 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0438 loss_cls: 0.2362 acc: 96.1426 loss_bbox: 0.2436 loss_mask: 0.2595 +2024/10/28 07:29:34 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 07:30:03 - mmengine - INFO - Epoch(train) [7][4050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:32:12 time: 0.9510 data_time: 0.0500 memory: 6408 grad_norm: 3.9794 loss: 0.8507 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0496 loss_cls: 0.2398 acc: 92.9688 loss_bbox: 0.2628 loss_mask: 0.2684 +2024/10/28 07:30:57 - mmengine - INFO - Epoch(train) [7][4100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:31:54 time: 1.0649 data_time: 0.0894 memory: 6190 grad_norm: 3.9482 loss: 0.8816 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0538 loss_cls: 0.2449 acc: 92.9688 loss_bbox: 0.2810 loss_mask: 0.2686 +2024/10/28 07:31:41 - mmengine - INFO - Epoch(train) [7][4150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:31:29 time: 0.8886 data_time: 0.0448 memory: 6300 grad_norm: 3.8301 loss: 0.8509 loss_rpn_cls: 0.0331 loss_rpn_bbox: 0.0527 loss_cls: 0.2397 acc: 88.6230 loss_bbox: 0.2597 loss_mask: 0.2656 +2024/10/28 07:32:27 - mmengine - INFO - Epoch(train) [7][4200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:31:05 time: 0.9260 data_time: 0.0504 memory: 6213 grad_norm: 4.0480 loss: 0.7987 loss_rpn_cls: 0.0253 loss_rpn_bbox: 0.0451 loss_cls: 0.2242 acc: 89.6973 loss_bbox: 0.2505 loss_mask: 0.2535 +2024/10/28 07:33:11 - mmengine - INFO - Epoch(train) [7][4250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:30:39 time: 0.8681 data_time: 0.0517 memory: 6195 grad_norm: 3.8644 loss: 0.7866 loss_rpn_cls: 0.0340 loss_rpn_bbox: 0.0464 loss_cls: 0.2130 acc: 95.8984 loss_bbox: 0.2392 loss_mask: 0.2540 +2024/10/28 07:33:59 - mmengine - INFO - Epoch(train) [7][4300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:30:16 time: 0.9648 data_time: 0.0614 memory: 6256 grad_norm: 3.9272 loss: 0.8278 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0484 loss_cls: 0.2367 acc: 86.5723 loss_bbox: 0.2493 loss_mask: 0.2599 +2024/10/28 07:34:45 - mmengine - INFO - Epoch(train) [7][4350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:29:52 time: 0.9205 data_time: 0.0503 memory: 6237 grad_norm: 3.9976 loss: 0.7706 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0411 loss_cls: 0.2172 acc: 92.6270 loss_bbox: 0.2289 loss_mask: 0.2525 +2024/10/28 07:35:31 - mmengine - INFO - Epoch(train) [7][4400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:29:28 time: 0.9122 data_time: 0.0399 memory: 5985 grad_norm: 3.9687 loss: 0.7869 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0419 loss_cls: 0.2235 acc: 91.5039 loss_bbox: 0.2329 loss_mask: 0.2553 +2024/10/28 07:36:17 - mmengine - INFO - Epoch(train) [7][4450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:29:04 time: 0.9272 data_time: 0.0390 memory: 6165 grad_norm: 3.8868 loss: 0.7343 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0416 loss_cls: 0.2083 acc: 88.6230 loss_bbox: 0.2201 loss_mask: 0.2366 +2024/10/28 07:37:04 - mmengine - INFO - Epoch(train) [7][4500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:28:40 time: 0.9332 data_time: 0.0499 memory: 6239 grad_norm: 3.8744 loss: 0.8510 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0484 loss_cls: 0.2350 acc: 85.8398 loss_bbox: 0.2706 loss_mask: 0.2642 +2024/10/28 07:37:53 - mmengine - INFO - Epoch(train) [7][4550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:28:18 time: 0.9796 data_time: 0.0762 memory: 6220 grad_norm: 3.8457 loss: 0.8012 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0505 loss_cls: 0.2211 acc: 91.9434 loss_bbox: 0.2414 loss_mask: 0.2605 +2024/10/28 07:38:38 - mmengine - INFO - Epoch(train) [7][4600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:27:53 time: 0.9042 data_time: 0.0430 memory: 6291 grad_norm: 3.7827 loss: 0.7758 loss_rpn_cls: 0.0252 loss_rpn_bbox: 0.0412 loss_cls: 0.2128 acc: 88.5254 loss_bbox: 0.2353 loss_mask: 0.2614 +2024/10/28 07:39:24 - mmengine - INFO - Epoch(train) [7][4650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:27:29 time: 0.9307 data_time: 0.0469 memory: 6410 grad_norm: 3.8672 loss: 0.7979 loss_rpn_cls: 0.0405 loss_rpn_bbox: 0.0440 loss_cls: 0.2230 acc: 94.6777 loss_bbox: 0.2348 loss_mask: 0.2556 +2024/10/28 07:40:10 - mmengine - INFO - Epoch(train) [7][4700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:27:04 time: 0.9193 data_time: 0.0501 memory: 6194 grad_norm: 4.1565 loss: 0.8428 loss_rpn_cls: 0.0330 loss_rpn_bbox: 0.0486 loss_cls: 0.2360 acc: 93.0664 loss_bbox: 0.2561 loss_mask: 0.2691 +2024/10/28 07:40:57 - mmengine - INFO - Epoch(train) [7][4750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:26:40 time: 0.9337 data_time: 0.0458 memory: 6345 grad_norm: 3.8909 loss: 0.8137 loss_rpn_cls: 0.0311 loss_rpn_bbox: 0.0443 loss_cls: 0.2320 acc: 84.5215 loss_bbox: 0.2525 loss_mask: 0.2538 +2024/10/28 07:41:44 - mmengine - INFO - Epoch(train) [7][4800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:26:16 time: 0.9354 data_time: 0.0449 memory: 6276 grad_norm: 3.8520 loss: 0.7715 loss_rpn_cls: 0.0347 loss_rpn_bbox: 0.0469 loss_cls: 0.2135 acc: 93.0176 loss_bbox: 0.2307 loss_mask: 0.2457 +2024/10/28 07:42:32 - mmengine - INFO - Epoch(train) [7][4850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:25:53 time: 0.9718 data_time: 0.0528 memory: 6177 grad_norm: 4.0005 loss: 0.8253 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0457 loss_cls: 0.2368 acc: 97.0215 loss_bbox: 0.2450 loss_mask: 0.2706 +2024/10/28 07:43:18 - mmengine - INFO - Epoch(train) [7][4900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:25:28 time: 0.9160 data_time: 0.0430 memory: 6395 grad_norm: 3.9435 loss: 0.8155 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0488 loss_cls: 0.2317 acc: 97.1680 loss_bbox: 0.2423 loss_mask: 0.2611 +2024/10/28 07:44:02 - mmengine - INFO - Epoch(train) [7][4950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:25:02 time: 0.8768 data_time: 0.0559 memory: 6231 grad_norm: 4.0240 loss: 0.8139 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0441 loss_cls: 0.2283 acc: 88.6230 loss_bbox: 0.2507 loss_mask: 0.2617 +2024/10/28 07:44:50 - mmengine - INFO - Epoch(train) [7][5000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:24:38 time: 0.9562 data_time: 0.0961 memory: 6197 grad_norm: 3.8248 loss: 0.8595 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0471 loss_cls: 0.2477 acc: 92.7734 loss_bbox: 0.2714 loss_mask: 0.2656 +2024/10/28 07:45:08 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 07:45:37 - mmengine - INFO - Epoch(train) [7][5050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:24:14 time: 0.9367 data_time: 0.0445 memory: 6358 grad_norm: 3.9065 loss: 0.8772 loss_rpn_cls: 0.0382 loss_rpn_bbox: 0.0514 loss_cls: 0.2562 acc: 91.4551 loss_bbox: 0.2682 loss_mask: 0.2633 +2024/10/28 07:46:23 - mmengine - INFO - Epoch(train) [7][5100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:23:50 time: 0.9277 data_time: 0.0475 memory: 6085 grad_norm: 3.9438 loss: 0.8242 loss_rpn_cls: 0.0355 loss_rpn_bbox: 0.0489 loss_cls: 0.2301 acc: 89.3555 loss_bbox: 0.2448 loss_mask: 0.2649 +2024/10/28 07:47:10 - mmengine - INFO - Epoch(train) [7][5150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:23:25 time: 0.9348 data_time: 0.0451 memory: 6185 grad_norm: 3.9902 loss: 0.8158 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0481 loss_cls: 0.2320 acc: 89.8438 loss_bbox: 0.2503 loss_mask: 0.2546 +2024/10/28 07:47:56 - mmengine - INFO - Epoch(train) [7][5200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:23:00 time: 0.9223 data_time: 0.0462 memory: 6235 grad_norm: 3.9179 loss: 0.8314 loss_rpn_cls: 0.0327 loss_rpn_bbox: 0.0486 loss_cls: 0.2313 acc: 91.1621 loss_bbox: 0.2522 loss_mask: 0.2666 +2024/10/28 07:48:40 - mmengine - INFO - Epoch(train) [7][5250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:22:34 time: 0.8753 data_time: 0.0429 memory: 6295 grad_norm: 3.9878 loss: 0.7968 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0468 loss_cls: 0.2214 acc: 90.0391 loss_bbox: 0.2400 loss_mask: 0.2581 +2024/10/28 07:49:27 - mmengine - INFO - Epoch(train) [7][5300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:22:09 time: 0.9436 data_time: 0.0456 memory: 6194 grad_norm: 3.8229 loss: 0.8512 loss_rpn_cls: 0.0337 loss_rpn_bbox: 0.0519 loss_cls: 0.2476 acc: 96.3867 loss_bbox: 0.2581 loss_mask: 0.2598 +2024/10/28 07:50:14 - mmengine - INFO - Epoch(train) [7][5350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:21:45 time: 0.9371 data_time: 0.0547 memory: 6304 grad_norm: 3.8271 loss: 0.8639 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0480 loss_cls: 0.2503 acc: 91.2109 loss_bbox: 0.2614 loss_mask: 0.2739 +2024/10/28 07:51:03 - mmengine - INFO - Epoch(train) [7][5400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:21:22 time: 0.9842 data_time: 0.0446 memory: 6282 grad_norm: 4.0457 loss: 0.8421 loss_rpn_cls: 0.0312 loss_rpn_bbox: 0.0443 loss_cls: 0.2486 acc: 92.2852 loss_bbox: 0.2544 loss_mask: 0.2637 +2024/10/28 07:51:53 - mmengine - INFO - Epoch(train) [7][5450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:21:00 time: 0.9959 data_time: 0.0875 memory: 6301 grad_norm: 4.0454 loss: 0.7828 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0447 loss_cls: 0.2263 acc: 94.7266 loss_bbox: 0.2355 loss_mask: 0.2473 +2024/10/28 07:52:39 - mmengine - INFO - Epoch(train) [7][5500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:20:35 time: 0.9199 data_time: 0.0460 memory: 6385 grad_norm: 4.0206 loss: 0.8467 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0465 loss_cls: 0.2456 acc: 91.6504 loss_bbox: 0.2582 loss_mask: 0.2650 +2024/10/28 07:53:23 - mmengine - INFO - Epoch(train) [7][5550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:20:08 time: 0.8849 data_time: 0.0475 memory: 6240 grad_norm: 3.9243 loss: 0.8032 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0433 loss_cls: 0.2298 acc: 91.0156 loss_bbox: 0.2446 loss_mask: 0.2551 +2024/10/28 07:54:09 - mmengine - INFO - Epoch(train) [7][5600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:19:43 time: 0.9155 data_time: 0.0418 memory: 6142 grad_norm: 4.1442 loss: 0.7982 loss_rpn_cls: 0.0280 loss_rpn_bbox: 0.0445 loss_cls: 0.2284 acc: 90.6250 loss_bbox: 0.2458 loss_mask: 0.2516 +2024/10/28 07:54:57 - mmengine - INFO - Epoch(train) [7][5650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:19:19 time: 0.9707 data_time: 0.0439 memory: 6240 grad_norm: 3.9774 loss: 0.8233 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0486 loss_cls: 0.2208 acc: 93.5059 loss_bbox: 0.2553 loss_mask: 0.2680 +2024/10/28 07:55:43 - mmengine - INFO - Epoch(train) [7][5700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:18:53 time: 0.9038 data_time: 0.0396 memory: 5951 grad_norm: 3.9591 loss: 0.7712 loss_rpn_cls: 0.0300 loss_rpn_bbox: 0.0457 loss_cls: 0.2129 acc: 94.7266 loss_bbox: 0.2308 loss_mask: 0.2518 +2024/10/28 07:56:26 - mmengine - INFO - Epoch(train) [7][5750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:18:26 time: 0.8792 data_time: 0.0442 memory: 6343 grad_norm: 4.1857 loss: 0.8880 loss_rpn_cls: 0.0347 loss_rpn_bbox: 0.0506 loss_cls: 0.2566 acc: 96.2891 loss_bbox: 0.2728 loss_mask: 0.2735 +2024/10/28 07:57:12 - mmengine - INFO - Epoch(train) [7][5800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:18:00 time: 0.9076 data_time: 0.0435 memory: 6268 grad_norm: 3.9106 loss: 0.8345 loss_rpn_cls: 0.0324 loss_rpn_bbox: 0.0471 loss_cls: 0.2303 acc: 95.8984 loss_bbox: 0.2624 loss_mask: 0.2623 +2024/10/28 07:57:59 - mmengine - INFO - Epoch(train) [7][5850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:17:35 time: 0.9359 data_time: 0.0426 memory: 6414 grad_norm: 3.9478 loss: 0.8273 loss_rpn_cls: 0.0362 loss_rpn_bbox: 0.0465 loss_cls: 0.2428 acc: 93.3594 loss_bbox: 0.2538 loss_mask: 0.2480 +2024/10/28 07:58:44 - mmengine - INFO - Epoch(train) [7][5900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:17:09 time: 0.9002 data_time: 0.0410 memory: 6275 grad_norm: 3.8516 loss: 0.8409 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0480 loss_cls: 0.2442 acc: 93.1641 loss_bbox: 0.2614 loss_mask: 0.2548 +2024/10/28 07:59:29 - mmengine - INFO - Epoch(train) [7][5950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:16:43 time: 0.9068 data_time: 0.0416 memory: 6262 grad_norm: 4.1033 loss: 0.8716 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0473 loss_cls: 0.2544 acc: 95.5078 loss_bbox: 0.2723 loss_mask: 0.2705 +2024/10/28 08:00:17 - mmengine - INFO - Epoch(train) [7][6000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:16:18 time: 0.9510 data_time: 0.0487 memory: 6089 grad_norm: 3.8820 loss: 0.8126 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0444 loss_cls: 0.2332 acc: 96.0449 loss_bbox: 0.2488 loss_mask: 0.2555 +2024/10/28 08:00:35 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 08:01:02 - mmengine - INFO - Epoch(train) [7][6050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:15:52 time: 0.9019 data_time: 0.0446 memory: 6153 grad_norm: 3.8887 loss: 0.8062 loss_rpn_cls: 0.0252 loss_rpn_bbox: 0.0435 loss_cls: 0.2305 acc: 96.2891 loss_bbox: 0.2454 loss_mask: 0.2616 +2024/10/28 08:01:52 - mmengine - INFO - Epoch(train) [7][6100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:15:29 time: 1.0109 data_time: 0.1211 memory: 6175 grad_norm: 4.0475 loss: 0.8574 loss_rpn_cls: 0.0354 loss_rpn_bbox: 0.0517 loss_cls: 0.2397 acc: 90.7227 loss_bbox: 0.2648 loss_mask: 0.2659 +2024/10/28 08:02:40 - mmengine - INFO - Epoch(train) [7][6150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:15:05 time: 0.9511 data_time: 0.0530 memory: 6175 grad_norm: 4.1112 loss: 0.8605 loss_rpn_cls: 0.0372 loss_rpn_bbox: 0.0540 loss_cls: 0.2381 acc: 82.5195 loss_bbox: 0.2618 loss_mask: 0.2695 +2024/10/28 08:03:25 - mmengine - INFO - Epoch(train) [7][6200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:14:38 time: 0.9009 data_time: 0.0370 memory: 6197 grad_norm: 3.7797 loss: 0.7437 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0396 loss_cls: 0.2104 acc: 87.8418 loss_bbox: 0.2212 loss_mask: 0.2486 +2024/10/28 08:04:10 - mmengine - INFO - Epoch(train) [7][6250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:14:12 time: 0.9020 data_time: 0.0406 memory: 6197 grad_norm: 3.8357 loss: 0.7963 loss_rpn_cls: 0.0354 loss_rpn_bbox: 0.0462 loss_cls: 0.2063 acc: 87.7930 loss_bbox: 0.2414 loss_mask: 0.2670 +2024/10/28 08:04:56 - mmengine - INFO - Epoch(train) [7][6300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:13:46 time: 0.9246 data_time: 0.0390 memory: 6351 grad_norm: 3.9579 loss: 0.7828 loss_rpn_cls: 0.0263 loss_rpn_bbox: 0.0412 loss_cls: 0.2224 acc: 93.2129 loss_bbox: 0.2337 loss_mask: 0.2593 +2024/10/28 08:05:44 - mmengine - INFO - Epoch(train) [7][6350/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:13:21 time: 0.9600 data_time: 0.0438 memory: 6292 grad_norm: 3.8713 loss: 0.8123 loss_rpn_cls: 0.0336 loss_rpn_bbox: 0.0482 loss_cls: 0.2260 acc: 90.9668 loss_bbox: 0.2434 loss_mask: 0.2611 +2024/10/28 08:06:32 - mmengine - INFO - Epoch(train) [7][6400/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:12:56 time: 0.9472 data_time: 0.0417 memory: 6215 grad_norm: 3.9268 loss: 0.7946 loss_rpn_cls: 0.0329 loss_rpn_bbox: 0.0468 loss_cls: 0.2295 acc: 91.6992 loss_bbox: 0.2332 loss_mask: 0.2522 +2024/10/28 08:07:19 - mmengine - INFO - Epoch(train) [7][6450/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:12:31 time: 0.9450 data_time: 0.0581 memory: 6228 grad_norm: 3.7861 loss: 0.8273 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0504 loss_cls: 0.2281 acc: 88.4766 loss_bbox: 0.2583 loss_mask: 0.2601 +2024/10/28 08:08:05 - mmengine - INFO - Epoch(train) [7][6500/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:12:06 time: 0.9293 data_time: 0.0570 memory: 6299 grad_norm: 3.8990 loss: 0.7805 loss_rpn_cls: 0.0291 loss_rpn_bbox: 0.0434 loss_cls: 0.2265 acc: 92.7246 loss_bbox: 0.2329 loss_mask: 0.2486 +2024/10/28 08:08:52 - mmengine - INFO - Epoch(train) [7][6550/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:11:40 time: 0.9319 data_time: 0.0716 memory: 6307 grad_norm: 3.9441 loss: 0.8106 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0478 loss_cls: 0.2308 acc: 93.1152 loss_bbox: 0.2468 loss_mask: 0.2584 +2024/10/28 08:09:38 - mmengine - INFO - Epoch(train) [7][6600/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:11:14 time: 0.9190 data_time: 0.0519 memory: 6310 grad_norm: 3.9070 loss: 0.8029 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0424 loss_cls: 0.2301 acc: 95.4102 loss_bbox: 0.2379 loss_mask: 0.2587 +2024/10/28 08:10:28 - mmengine - INFO - Epoch(train) [7][6650/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:10:50 time: 0.9982 data_time: 0.0755 memory: 6317 grad_norm: 3.9170 loss: 0.9264 loss_rpn_cls: 0.0410 loss_rpn_bbox: 0.0638 loss_cls: 0.2685 acc: 96.8750 loss_bbox: 0.2805 loss_mask: 0.2726 +2024/10/28 08:11:13 - mmengine - INFO - Epoch(train) [7][6700/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:10:23 time: 0.9033 data_time: 0.0516 memory: 6199 grad_norm: 3.8727 loss: 0.8047 loss_rpn_cls: 0.0263 loss_rpn_bbox: 0.0442 loss_cls: 0.2279 acc: 97.8516 loss_bbox: 0.2358 loss_mask: 0.2705 +2024/10/28 08:11:59 - mmengine - INFO - Epoch(train) [7][6750/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:09:57 time: 0.9198 data_time: 0.0615 memory: 6209 grad_norm: 3.9640 loss: 0.8501 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0485 loss_cls: 0.2352 acc: 92.0410 loss_bbox: 0.2619 loss_mask: 0.2741 +2024/10/28 08:12:47 - mmengine - INFO - Epoch(train) [7][6800/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:09:32 time: 0.9530 data_time: 0.0526 memory: 6267 grad_norm: 3.7806 loss: 0.8049 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0456 loss_cls: 0.2277 acc: 95.6543 loss_bbox: 0.2403 loss_mask: 0.2645 +2024/10/28 08:13:32 - mmengine - INFO - Epoch(train) [7][6850/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:09:05 time: 0.9050 data_time: 0.0645 memory: 6135 grad_norm: 4.0963 loss: 0.7813 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0439 loss_cls: 0.2265 acc: 86.1328 loss_bbox: 0.2358 loss_mask: 0.2464 +2024/10/28 08:14:15 - mmengine - INFO - Epoch(train) [7][6900/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:08:37 time: 0.8686 data_time: 0.0648 memory: 6147 grad_norm: 3.7514 loss: 0.8194 loss_rpn_cls: 0.0293 loss_rpn_bbox: 0.0461 loss_cls: 0.2283 acc: 89.3066 loss_bbox: 0.2480 loss_mask: 0.2676 +2024/10/28 08:15:01 - mmengine - INFO - Epoch(train) [7][6950/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:08:10 time: 0.9197 data_time: 0.0622 memory: 6266 grad_norm: 3.9134 loss: 0.7997 loss_rpn_cls: 0.0269 loss_rpn_bbox: 0.0444 loss_cls: 0.2235 acc: 90.3809 loss_bbox: 0.2408 loss_mask: 0.2641 +2024/10/28 08:15:54 - mmengine - INFO - Epoch(train) [7][7000/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:07:49 time: 1.0569 data_time: 0.1445 memory: 6222 grad_norm: 4.0301 loss: 0.8419 loss_rpn_cls: 0.0321 loss_rpn_bbox: 0.0498 loss_cls: 0.2425 acc: 92.8711 loss_bbox: 0.2495 loss_mask: 0.2680 +2024/10/28 08:16:12 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 08:16:42 - mmengine - INFO - Epoch(train) [7][7050/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:07:24 time: 0.9670 data_time: 0.0577 memory: 6227 grad_norm: 3.8511 loss: 0.8157 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0466 loss_cls: 0.2248 acc: 96.3867 loss_bbox: 0.2486 loss_mask: 0.2651 +2024/10/28 08:17:30 - mmengine - INFO - Epoch(train) [7][7100/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:06:58 time: 0.9469 data_time: 0.0573 memory: 6339 grad_norm: 3.8230 loss: 0.8217 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0490 loss_cls: 0.2315 acc: 97.2168 loss_bbox: 0.2462 loss_mask: 0.2599 +2024/10/28 08:18:18 - mmengine - INFO - Epoch(train) [7][7150/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:06:33 time: 0.9683 data_time: 0.0514 memory: 6139 grad_norm: 3.9646 loss: 0.8643 loss_rpn_cls: 0.0334 loss_rpn_bbox: 0.0488 loss_cls: 0.2441 acc: 92.6270 loss_bbox: 0.2695 loss_mask: 0.2685 +2024/10/28 08:19:05 - mmengine - INFO - Epoch(train) [7][7200/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:06:07 time: 0.9377 data_time: 0.0521 memory: 6082 grad_norm: 3.9324 loss: 0.8589 loss_rpn_cls: 0.0345 loss_rpn_bbox: 0.0493 loss_cls: 0.2522 acc: 91.6016 loss_bbox: 0.2534 loss_mask: 0.2694 +2024/10/28 08:19:52 - mmengine - INFO - Epoch(train) [7][7250/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:05:41 time: 0.9398 data_time: 0.0563 memory: 6198 grad_norm: 3.8047 loss: 0.8227 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0459 loss_cls: 0.2374 acc: 97.8516 loss_bbox: 0.2484 loss_mask: 0.2579 +2024/10/28 08:20:39 - mmengine - INFO - Epoch(train) [7][7300/7330] base_lr: 2.0000e-04 lr: 2.0000e-04 eta: 7:05:15 time: 0.9396 data_time: 0.0467 memory: 6176 grad_norm: 4.0783 loss: 0.8094 loss_rpn_cls: 0.0337 loss_rpn_bbox: 0.0471 loss_cls: 0.2311 acc: 94.0430 loss_bbox: 0.2465 loss_mask: 0.2511 +2024/10/28 08:21:14 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 08:21:14 - mmengine - INFO - Saving checkpoint at 7 epochs +2024/10/28 08:21:27 - mmengine - INFO - Epoch(val) [7][ 50/1250] eta: 0:03:17 time: 0.1644 data_time: 0.0072 memory: 7587 +2024/10/28 08:21:36 - mmengine - INFO - Epoch(val) [7][ 100/1250] eta: 0:03:10 time: 0.1677 data_time: 0.0049 memory: 1114 +2024/10/28 08:21:44 - mmengine - INFO - Epoch(val) [7][ 150/1250] eta: 0:03:03 time: 0.1693 data_time: 0.0055 memory: 1102 +2024/10/28 08:21:52 - mmengine - INFO - Epoch(val) [7][ 200/1250] eta: 0:02:55 time: 0.1654 data_time: 0.0074 memory: 1114 +2024/10/28 08:22:00 - mmengine - INFO - Epoch(val) [7][ 250/1250] eta: 0:02:45 time: 0.1594 data_time: 0.0056 memory: 1221 +2024/10/28 08:22:08 - mmengine - INFO - Epoch(val) [7][ 300/1250] eta: 0:02:34 time: 0.1466 data_time: 0.0063 memory: 1114 +2024/10/28 08:22:13 - mmengine - INFO - Epoch(val) [7][ 350/1250] eta: 0:02:19 time: 0.1123 data_time: 0.0055 memory: 1117 +2024/10/28 08:22:19 - mmengine - INFO - Epoch(val) [7][ 400/1250] eta: 0:02:06 time: 0.1099 data_time: 0.0046 memory: 1082 +2024/10/28 08:22:24 - mmengine - INFO - Epoch(val) [7][ 450/1250] eta: 0:01:56 time: 0.1118 data_time: 0.0048 memory: 1114 +2024/10/28 08:22:30 - mmengine - INFO - Epoch(val) [7][ 500/1250] eta: 0:01:46 time: 0.1124 data_time: 0.0061 memory: 1134 +2024/10/28 08:22:36 - mmengine - INFO - Epoch(val) [7][ 550/1250] eta: 0:01:37 time: 0.1115 data_time: 0.0057 memory: 1176 +2024/10/28 08:22:41 - mmengine - INFO - Epoch(val) [7][ 600/1250] eta: 0:01:29 time: 0.1190 data_time: 0.0078 memory: 1114 +2024/10/28 08:22:47 - mmengine - INFO - Epoch(val) [7][ 650/1250] eta: 0:01:21 time: 0.1093 data_time: 0.0046 memory: 1219 +2024/10/28 08:22:53 - mmengine - INFO - Epoch(val) [7][ 700/1250] eta: 0:01:13 time: 0.1194 data_time: 0.0062 memory: 1114 +2024/10/28 08:22:59 - mmengine - INFO - Epoch(val) [7][ 750/1250] eta: 0:01:06 time: 0.1195 data_time: 0.0076 memory: 1114 +2024/10/28 08:23:05 - mmengine - INFO - Epoch(val) [7][ 800/1250] eta: 0:00:59 time: 0.1141 data_time: 0.0055 memory: 1160 +2024/10/28 08:23:10 - mmengine - INFO - Epoch(val) [7][ 850/1250] eta: 0:00:52 time: 0.1136 data_time: 0.0058 memory: 1145 +2024/10/28 08:23:16 - mmengine - INFO - Epoch(val) [7][ 900/1250] eta: 0:00:45 time: 0.1150 data_time: 0.0056 memory: 1114 +2024/10/28 08:23:22 - mmengine - INFO - Epoch(val) [7][ 950/1250] eta: 0:00:38 time: 0.1183 data_time: 0.0077 memory: 1219 +2024/10/28 08:23:27 - mmengine - INFO - Epoch(val) [7][1000/1250] eta: 0:00:32 time: 0.1101 data_time: 0.0053 memory: 1058 +2024/10/28 08:23:33 - mmengine - INFO - Epoch(val) [7][1050/1250] eta: 0:00:25 time: 0.1176 data_time: 0.0063 memory: 1114 +2024/10/28 08:23:39 - mmengine - INFO - Epoch(val) [7][1100/1250] eta: 0:00:19 time: 0.1116 data_time: 0.0046 memory: 1114 +2024/10/28 08:23:45 - mmengine - INFO - Epoch(val) [7][1150/1250] eta: 0:00:12 time: 0.1146 data_time: 0.0061 memory: 1114 +2024/10/28 08:23:50 - mmengine - INFO - Epoch(val) [7][1200/1250] eta: 0:00:06 time: 0.1140 data_time: 0.0049 memory: 1176 +2024/10/28 08:23:56 - mmengine - INFO - Epoch(val) [7][1250/1250] eta: 0:00:00 time: 0.1101 data_time: 0.0047 memory: 1114 +2024/10/28 08:24:07 - mmengine - INFO - Evaluating bbox... +2024/10/28 08:24:41 - mmengine - INFO - bbox_mAP_copypaste: 0.329 0.539 0.359 0.167 0.358 0.445 +2024/10/28 08:24:41 - mmengine - INFO - Evaluating segm... +2024/10/28 08:25:18 - mmengine - INFO - segm_mAP_copypaste: 0.311 0.511 0.329 0.120 0.334 0.476 +2024/10/28 08:25:19 - mmengine - INFO - Epoch(val) [7][1250/1250] coco/bbox_mAP: 0.3290 coco/bbox_mAP_50: 0.5390 coco/bbox_mAP_75: 0.3590 coco/bbox_mAP_s: 0.1670 coco/bbox_mAP_m: 0.3580 coco/bbox_mAP_l: 0.4450 coco/segm_mAP: 0.3110 coco/segm_mAP_50: 0.5110 coco/segm_mAP_75: 0.3290 coco/segm_mAP_s: 0.1200 coco/segm_mAP_m: 0.3340 coco/segm_mAP_l: 0.4760 data_time: 0.0058 time: 0.1255 +2024/10/28 08:26:07 - mmengine - INFO - Epoch(train) [8][ 50/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:04:39 time: 0.9538 data_time: 0.0481 memory: 6130 grad_norm: 3.8122 loss: 0.7805 loss_rpn_cls: 0.0284 loss_rpn_bbox: 0.0449 loss_cls: 0.2098 acc: 91.2109 loss_bbox: 0.2406 loss_mask: 0.2567 +2024/10/28 08:26:55 - mmengine - INFO - Epoch(train) [8][ 100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:04:14 time: 0.9647 data_time: 0.0477 memory: 6217 grad_norm: 3.9785 loss: 0.8218 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0474 loss_cls: 0.2238 acc: 92.4316 loss_bbox: 0.2584 loss_mask: 0.2665 +2024/10/28 08:27:41 - mmengine - INFO - Epoch(train) [8][ 150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:03:47 time: 0.9238 data_time: 0.0523 memory: 6297 grad_norm: 3.7049 loss: 0.8044 loss_rpn_cls: 0.0281 loss_rpn_bbox: 0.0470 loss_cls: 0.2193 acc: 91.4062 loss_bbox: 0.2428 loss_mask: 0.2672 +2024/10/28 08:28:29 - mmengine - INFO - Epoch(train) [8][ 200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:03:21 time: 0.9506 data_time: 0.0499 memory: 6231 grad_norm: 3.8029 loss: 0.7454 loss_rpn_cls: 0.0242 loss_rpn_bbox: 0.0406 loss_cls: 0.2003 acc: 95.9961 loss_bbox: 0.2315 loss_mask: 0.2488 +2024/10/28 08:29:15 - mmengine - INFO - Epoch(train) [8][ 250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:02:55 time: 0.9351 data_time: 0.0450 memory: 6270 grad_norm: 3.8625 loss: 0.7839 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0461 loss_cls: 0.2109 acc: 91.6016 loss_bbox: 0.2353 loss_mask: 0.2553 +2024/10/28 08:30:03 - mmengine - INFO - Epoch(train) [8][ 300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:02:29 time: 0.9594 data_time: 0.0530 memory: 6290 grad_norm: 3.8794 loss: 0.7714 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0428 loss_cls: 0.2053 acc: 91.7969 loss_bbox: 0.2394 loss_mask: 0.2562 +2024/10/28 08:30:55 - mmengine - INFO - Epoch(train) [8][ 350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:02:06 time: 1.0309 data_time: 0.0773 memory: 6232 grad_norm: 3.7897 loss: 0.7512 loss_rpn_cls: 0.0265 loss_rpn_bbox: 0.0432 loss_cls: 0.2066 acc: 96.7773 loss_bbox: 0.2334 loss_mask: 0.2414 +2024/10/28 08:31:41 - mmengine - INFO - Epoch(train) [8][ 400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:01:39 time: 0.9257 data_time: 0.0463 memory: 6328 grad_norm: 3.8436 loss: 0.8108 loss_rpn_cls: 0.0291 loss_rpn_bbox: 0.0485 loss_cls: 0.2245 acc: 89.6484 loss_bbox: 0.2559 loss_mask: 0.2527 +2024/10/28 08:32:27 - mmengine - INFO - Epoch(train) [8][ 450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:01:12 time: 0.9108 data_time: 0.0431 memory: 6193 grad_norm: 3.6866 loss: 0.7615 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0422 loss_cls: 0.2097 acc: 90.9180 loss_bbox: 0.2342 loss_mask: 0.2492 +2024/10/28 08:33:13 - mmengine - INFO - Epoch(train) [8][ 500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:00:44 time: 0.9191 data_time: 0.0530 memory: 6419 grad_norm: 3.7408 loss: 0.8207 loss_rpn_cls: 0.0288 loss_rpn_bbox: 0.0471 loss_cls: 0.2388 acc: 96.7285 loss_bbox: 0.2527 loss_mask: 0.2533 +2024/10/28 08:33:59 - mmengine - INFO - Epoch(train) [8][ 550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 7:00:18 time: 0.9327 data_time: 0.0428 memory: 6221 grad_norm: 3.9006 loss: 0.7752 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0433 loss_cls: 0.2118 acc: 93.7012 loss_bbox: 0.2403 loss_mask: 0.2571 +2024/10/28 08:34:44 - mmengine - INFO - Epoch(train) [8][ 600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:59:50 time: 0.9015 data_time: 0.0417 memory: 6262 grad_norm: 3.8398 loss: 0.7654 loss_rpn_cls: 0.0247 loss_rpn_bbox: 0.0440 loss_cls: 0.2018 acc: 92.3828 loss_bbox: 0.2393 loss_mask: 0.2556 +2024/10/28 08:35:31 - mmengine - INFO - Epoch(train) [8][ 650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:59:23 time: 0.9240 data_time: 0.0448 memory: 6225 grad_norm: 3.7907 loss: 0.8231 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0452 loss_cls: 0.2315 acc: 92.6270 loss_bbox: 0.2519 loss_mask: 0.2643 +2024/10/28 08:36:08 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 08:36:19 - mmengine - INFO - Epoch(train) [8][ 700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:58:57 time: 0.9735 data_time: 0.0416 memory: 6420 grad_norm: 3.9439 loss: 0.7977 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0468 loss_cls: 0.2188 acc: 93.3594 loss_bbox: 0.2482 loss_mask: 0.2584 +2024/10/28 08:37:04 - mmengine - INFO - Epoch(train) [8][ 750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:58:29 time: 0.8865 data_time: 0.0375 memory: 6098 grad_norm: 3.9472 loss: 0.7855 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0439 loss_cls: 0.2144 acc: 85.4492 loss_bbox: 0.2440 loss_mask: 0.2560 +2024/10/28 08:37:50 - mmengine - INFO - Epoch(train) [8][ 800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:58:01 time: 0.9198 data_time: 0.0698 memory: 6186 grad_norm: 3.7909 loss: 0.7499 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0416 loss_cls: 0.2081 acc: 95.8008 loss_bbox: 0.2268 loss_mask: 0.2479 +2024/10/28 08:38:38 - mmengine - INFO - Epoch(train) [8][ 850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:57:35 time: 0.9586 data_time: 0.0624 memory: 6328 grad_norm: 3.8848 loss: 0.8070 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0488 loss_cls: 0.2238 acc: 95.2148 loss_bbox: 0.2480 loss_mask: 0.2558 +2024/10/28 08:39:25 - mmengine - INFO - Epoch(train) [8][ 900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:57:09 time: 0.9547 data_time: 0.0727 memory: 6124 grad_norm: 3.9029 loss: 0.8070 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0460 loss_cls: 0.2262 acc: 93.1641 loss_bbox: 0.2527 loss_mask: 0.2566 +2024/10/28 08:40:10 - mmengine - INFO - Epoch(train) [8][ 950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:56:40 time: 0.8887 data_time: 0.0649 memory: 6317 grad_norm: 3.9190 loss: 0.8193 loss_rpn_cls: 0.0364 loss_rpn_bbox: 0.0498 loss_cls: 0.2376 acc: 89.9902 loss_bbox: 0.2446 loss_mask: 0.2507 +2024/10/28 08:40:58 - mmengine - INFO - Epoch(train) [8][1000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:56:15 time: 0.9725 data_time: 0.0730 memory: 6420 grad_norm: 3.7994 loss: 0.8669 loss_rpn_cls: 0.0340 loss_rpn_bbox: 0.0528 loss_cls: 0.2410 acc: 91.0156 loss_bbox: 0.2734 loss_mask: 0.2659 +2024/10/28 08:41:48 - mmengine - INFO - Epoch(train) [8][1050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:55:49 time: 0.9848 data_time: 0.0614 memory: 6237 grad_norm: 3.8258 loss: 0.8092 loss_rpn_cls: 0.0276 loss_rpn_bbox: 0.0502 loss_cls: 0.2176 acc: 93.3594 loss_bbox: 0.2485 loss_mask: 0.2653 +2024/10/28 08:42:38 - mmengine - INFO - Epoch(train) [8][1100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:55:25 time: 1.0072 data_time: 0.0435 memory: 6305 grad_norm: 3.8627 loss: 0.8167 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0466 loss_cls: 0.2307 acc: 96.3379 loss_bbox: 0.2518 loss_mask: 0.2573 +2024/10/28 08:43:24 - mmengine - INFO - Epoch(train) [8][1150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:54:57 time: 0.9164 data_time: 0.0420 memory: 6320 grad_norm: 3.8614 loss: 0.7761 loss_rpn_cls: 0.0266 loss_rpn_bbox: 0.0401 loss_cls: 0.2088 acc: 95.3613 loss_bbox: 0.2454 loss_mask: 0.2551 +2024/10/28 08:44:08 - mmengine - INFO - Epoch(train) [8][1200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:54:28 time: 0.8872 data_time: 0.0414 memory: 6150 grad_norm: 3.9060 loss: 0.7844 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0441 loss_cls: 0.2219 acc: 92.2852 loss_bbox: 0.2360 loss_mask: 0.2569 +2024/10/28 08:44:53 - mmengine - INFO - Epoch(train) [8][1250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:54:00 time: 0.9002 data_time: 0.0383 memory: 6194 grad_norm: 3.6818 loss: 0.7479 loss_rpn_cls: 0.0259 loss_rpn_bbox: 0.0394 loss_cls: 0.2014 acc: 86.7676 loss_bbox: 0.2385 loss_mask: 0.2426 +2024/10/28 08:45:41 - mmengine - INFO - Epoch(train) [8][1300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:53:33 time: 0.9543 data_time: 0.0428 memory: 6420 grad_norm: 3.8892 loss: 0.7557 loss_rpn_cls: 0.0293 loss_rpn_bbox: 0.0437 loss_cls: 0.2086 acc: 98.5840 loss_bbox: 0.2263 loss_mask: 0.2478 +2024/10/28 08:46:25 - mmengine - INFO - Epoch(train) [8][1350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:53:04 time: 0.8896 data_time: 0.0426 memory: 6188 grad_norm: 3.8075 loss: 0.7786 loss_rpn_cls: 0.0259 loss_rpn_bbox: 0.0429 loss_cls: 0.2043 acc: 90.6250 loss_bbox: 0.2357 loss_mask: 0.2698 +2024/10/28 08:47:10 - mmengine - INFO - Epoch(train) [8][1400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:52:36 time: 0.9013 data_time: 0.0499 memory: 6305 grad_norm: 3.8692 loss: 0.8461 loss_rpn_cls: 0.0337 loss_rpn_bbox: 0.0495 loss_cls: 0.2302 acc: 90.9180 loss_bbox: 0.2665 loss_mask: 0.2661 +2024/10/28 08:47:57 - mmengine - INFO - Epoch(train) [8][1450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:52:08 time: 0.9304 data_time: 0.0416 memory: 6275 grad_norm: 3.7320 loss: 0.8095 loss_rpn_cls: 0.0256 loss_rpn_bbox: 0.0411 loss_cls: 0.2272 acc: 91.7969 loss_bbox: 0.2458 loss_mask: 0.2697 +2024/10/28 08:48:46 - mmengine - INFO - Epoch(train) [8][1500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:51:43 time: 0.9835 data_time: 0.0470 memory: 6255 grad_norm: 3.8470 loss: 0.7778 loss_rpn_cls: 0.0291 loss_rpn_bbox: 0.0468 loss_cls: 0.2230 acc: 90.3809 loss_bbox: 0.2366 loss_mask: 0.2422 +2024/10/28 08:49:33 - mmengine - INFO - Epoch(train) [8][1550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:51:15 time: 0.9369 data_time: 0.0415 memory: 6209 grad_norm: 3.8148 loss: 0.7672 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0468 loss_cls: 0.2153 acc: 88.5742 loss_bbox: 0.2294 loss_mask: 0.2502 +2024/10/28 08:50:19 - mmengine - INFO - Epoch(train) [8][1600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:50:47 time: 0.9134 data_time: 0.0414 memory: 6227 grad_norm: 3.8567 loss: 0.8109 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0447 loss_cls: 0.2242 acc: 95.3613 loss_bbox: 0.2589 loss_mask: 0.2570 +2024/10/28 08:51:05 - mmengine - INFO - Epoch(train) [8][1650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:50:19 time: 0.9193 data_time: 0.0432 memory: 6234 grad_norm: 3.8380 loss: 0.8411 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0513 loss_cls: 0.2407 acc: 88.7695 loss_bbox: 0.2616 loss_mask: 0.2584 +2024/10/28 08:51:43 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 08:51:52 - mmengine - INFO - Epoch(train) [8][1700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:49:52 time: 0.9481 data_time: 0.0440 memory: 6129 grad_norm: 4.0293 loss: 0.7970 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0504 loss_cls: 0.2167 acc: 93.3105 loss_bbox: 0.2480 loss_mask: 0.2565 +2024/10/28 08:52:33 - mmengine - INFO - Epoch(train) [8][1750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:49:21 time: 0.8227 data_time: 0.0400 memory: 6218 grad_norm: 3.8493 loss: 0.7668 loss_rpn_cls: 0.0246 loss_rpn_bbox: 0.0412 loss_cls: 0.2056 acc: 95.8984 loss_bbox: 0.2394 loss_mask: 0.2561 +2024/10/28 08:53:17 - mmengine - INFO - Epoch(train) [8][1800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:48:51 time: 0.8855 data_time: 0.0384 memory: 6083 grad_norm: 3.9578 loss: 0.7655 loss_rpn_cls: 0.0262 loss_rpn_bbox: 0.0418 loss_cls: 0.2175 acc: 93.1152 loss_bbox: 0.2313 loss_mask: 0.2488 +2024/10/28 08:54:05 - mmengine - INFO - Epoch(train) [8][1850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:48:24 time: 0.9487 data_time: 0.0474 memory: 6175 grad_norm: 4.0512 loss: 0.8244 loss_rpn_cls: 0.0273 loss_rpn_bbox: 0.0516 loss_cls: 0.2238 acc: 95.7520 loss_bbox: 0.2553 loss_mask: 0.2665 +2024/10/28 08:54:52 - mmengine - INFO - Epoch(train) [8][1900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:47:57 time: 0.9355 data_time: 0.0496 memory: 6335 grad_norm: 3.6298 loss: 0.8029 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0466 loss_cls: 0.2135 acc: 92.2852 loss_bbox: 0.2525 loss_mask: 0.2565 +2024/10/28 08:55:39 - mmengine - INFO - Epoch(train) [8][1950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:47:29 time: 0.9368 data_time: 0.0530 memory: 6419 grad_norm: 3.8262 loss: 0.7600 loss_rpn_cls: 0.0284 loss_rpn_bbox: 0.0404 loss_cls: 0.2168 acc: 90.0879 loss_bbox: 0.2328 loss_mask: 0.2416 +2024/10/28 08:56:26 - mmengine - INFO - Epoch(train) [8][2000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:47:02 time: 0.9570 data_time: 0.0541 memory: 6248 grad_norm: 3.8795 loss: 0.8249 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0472 loss_cls: 0.2275 acc: 93.7500 loss_bbox: 0.2527 loss_mask: 0.2643 +2024/10/28 08:57:11 - mmengine - INFO - Epoch(train) [8][2050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:46:33 time: 0.8900 data_time: 0.0503 memory: 6191 grad_norm: 3.9012 loss: 0.7514 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0412 loss_cls: 0.2156 acc: 95.5566 loss_bbox: 0.2236 loss_mask: 0.2468 +2024/10/28 08:57:58 - mmengine - INFO - Epoch(train) [8][2100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:46:05 time: 0.9411 data_time: 0.0529 memory: 6152 grad_norm: 3.6420 loss: 0.7707 loss_rpn_cls: 0.0266 loss_rpn_bbox: 0.0411 loss_cls: 0.2165 acc: 95.8008 loss_bbox: 0.2369 loss_mask: 0.2496 +2024/10/28 08:58:45 - mmengine - INFO - Epoch(train) [8][2150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:45:37 time: 0.9364 data_time: 0.0564 memory: 6294 grad_norm: 3.8409 loss: 0.7923 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0451 loss_cls: 0.2173 acc: 90.9180 loss_bbox: 0.2456 loss_mask: 0.2539 +2024/10/28 08:59:33 - mmengine - INFO - Epoch(train) [8][2200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:45:10 time: 0.9608 data_time: 0.0572 memory: 6259 grad_norm: 3.7447 loss: 0.8284 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0511 loss_cls: 0.2283 acc: 90.8691 loss_bbox: 0.2557 loss_mask: 0.2600 +2024/10/28 09:00:22 - mmengine - INFO - Epoch(train) [8][2250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:44:44 time: 0.9829 data_time: 0.0525 memory: 6276 grad_norm: 3.7529 loss: 0.7623 loss_rpn_cls: 0.0270 loss_rpn_bbox: 0.0398 loss_cls: 0.2072 acc: 95.0195 loss_bbox: 0.2383 loss_mask: 0.2500 +2024/10/28 09:01:09 - mmengine - INFO - Epoch(train) [8][2300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:44:16 time: 0.9418 data_time: 0.0427 memory: 6186 grad_norm: 3.6814 loss: 0.8614 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0500 loss_cls: 0.2364 acc: 92.7246 loss_bbox: 0.2752 loss_mask: 0.2693 +2024/10/28 09:01:58 - mmengine - INFO - Epoch(train) [8][2350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:43:49 time: 0.9764 data_time: 0.0482 memory: 6239 grad_norm: 3.9678 loss: 0.8684 loss_rpn_cls: 0.0363 loss_rpn_bbox: 0.0489 loss_cls: 0.2470 acc: 92.0410 loss_bbox: 0.2693 loss_mask: 0.2670 +2024/10/28 09:02:45 - mmengine - INFO - Epoch(train) [8][2400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:43:21 time: 0.9404 data_time: 0.0480 memory: 6284 grad_norm: 3.5261 loss: 0.8123 loss_rpn_cls: 0.0391 loss_rpn_bbox: 0.0511 loss_cls: 0.2238 acc: 92.3340 loss_bbox: 0.2366 loss_mask: 0.2617 +2024/10/28 09:03:32 - mmengine - INFO - Epoch(train) [8][2450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:42:53 time: 0.9368 data_time: 0.0528 memory: 6403 grad_norm: 3.7497 loss: 0.7722 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0427 loss_cls: 0.2141 acc: 95.6055 loss_bbox: 0.2390 loss_mask: 0.2458 +2024/10/28 09:04:19 - mmengine - INFO - Epoch(train) [8][2500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:42:26 time: 0.9514 data_time: 0.0575 memory: 6348 grad_norm: 3.9781 loss: 0.8059 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0498 loss_cls: 0.2311 acc: 94.4336 loss_bbox: 0.2362 loss_mask: 0.2548 +2024/10/28 09:05:03 - mmengine - INFO - Epoch(train) [8][2550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:41:56 time: 0.8729 data_time: 0.0541 memory: 6319 grad_norm: 3.9391 loss: 0.8076 loss_rpn_cls: 0.0263 loss_rpn_bbox: 0.0444 loss_cls: 0.2213 acc: 96.8750 loss_bbox: 0.2457 loss_mask: 0.2699 +2024/10/28 09:05:52 - mmengine - INFO - Epoch(train) [8][2600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:41:29 time: 0.9805 data_time: 0.0886 memory: 6181 grad_norm: 3.7825 loss: 0.7982 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0429 loss_cls: 0.2194 acc: 97.8516 loss_bbox: 0.2412 loss_mask: 0.2663 +2024/10/28 09:06:42 - mmengine - INFO - Epoch(train) [8][2650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:41:03 time: 1.0025 data_time: 0.0657 memory: 6185 grad_norm: 3.9852 loss: 0.7918 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0483 loss_cls: 0.2202 acc: 90.0879 loss_bbox: 0.2442 loss_mask: 0.2538 +2024/10/28 09:07:21 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 09:07:30 - mmengine - INFO - Epoch(train) [8][2700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:40:36 time: 0.9664 data_time: 0.0646 memory: 6187 grad_norm: 3.9156 loss: 0.8300 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0473 loss_cls: 0.2382 acc: 92.1387 loss_bbox: 0.2509 loss_mask: 0.2605 +2024/10/28 09:08:16 - mmengine - INFO - Epoch(train) [8][2750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:40:07 time: 0.9092 data_time: 0.0500 memory: 6278 grad_norm: 3.9584 loss: 0.7348 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0395 loss_cls: 0.2013 acc: 90.6738 loss_bbox: 0.2225 loss_mask: 0.2472 +2024/10/28 09:09:04 - mmengine - INFO - Epoch(train) [8][2800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:39:39 time: 0.9542 data_time: 0.0623 memory: 6226 grad_norm: 4.0133 loss: 0.7964 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0495 loss_cls: 0.2257 acc: 97.1191 loss_bbox: 0.2450 loss_mask: 0.2455 +2024/10/28 09:09:51 - mmengine - INFO - Epoch(train) [8][2850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:39:11 time: 0.9506 data_time: 0.0748 memory: 6165 grad_norm: 4.0118 loss: 0.8168 loss_rpn_cls: 0.0262 loss_rpn_bbox: 0.0456 loss_cls: 0.2339 acc: 90.0879 loss_bbox: 0.2478 loss_mask: 0.2633 +2024/10/28 09:10:38 - mmengine - INFO - Epoch(train) [8][2900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:38:43 time: 0.9406 data_time: 0.0681 memory: 6302 grad_norm: 3.9125 loss: 0.8775 loss_rpn_cls: 0.0314 loss_rpn_bbox: 0.0504 loss_cls: 0.2488 acc: 91.3574 loss_bbox: 0.2779 loss_mask: 0.2690 +2024/10/28 09:11:25 - mmengine - INFO - Epoch(train) [8][2950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:38:15 time: 0.9432 data_time: 0.0654 memory: 6205 grad_norm: 3.6360 loss: 0.8040 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0458 loss_cls: 0.2219 acc: 97.2656 loss_bbox: 0.2485 loss_mask: 0.2608 +2024/10/28 09:12:15 - mmengine - INFO - Epoch(train) [8][3000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:37:48 time: 0.9996 data_time: 0.0705 memory: 6351 grad_norm: 3.7644 loss: 0.8057 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0457 loss_cls: 0.2238 acc: 92.3828 loss_bbox: 0.2457 loss_mask: 0.2594 +2024/10/28 09:13:02 - mmengine - INFO - Epoch(train) [8][3050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:37:20 time: 0.9364 data_time: 0.0687 memory: 6335 grad_norm: 3.8479 loss: 0.7980 loss_rpn_cls: 0.0296 loss_rpn_bbox: 0.0440 loss_cls: 0.2259 acc: 90.4785 loss_bbox: 0.2442 loss_mask: 0.2544 +2024/10/28 09:13:51 - mmengine - INFO - Epoch(train) [8][3100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:36:52 time: 0.9713 data_time: 0.1135 memory: 6213 grad_norm: 3.6208 loss: 0.8002 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0437 loss_cls: 0.2225 acc: 92.3340 loss_bbox: 0.2423 loss_mask: 0.2623 +2024/10/28 09:14:39 - mmengine - INFO - Epoch(train) [8][3150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:36:24 time: 0.9559 data_time: 0.0590 memory: 6134 grad_norm: 3.7813 loss: 0.8045 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0506 loss_cls: 0.2166 acc: 95.1660 loss_bbox: 0.2433 loss_mask: 0.2651 +2024/10/28 09:15:26 - mmengine - INFO - Epoch(train) [8][3200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:35:56 time: 0.9549 data_time: 0.0537 memory: 6403 grad_norm: 3.7448 loss: 0.7600 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0446 loss_cls: 0.2059 acc: 92.3828 loss_bbox: 0.2270 loss_mask: 0.2539 +2024/10/28 09:16:13 - mmengine - INFO - Epoch(train) [8][3250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:35:28 time: 0.9326 data_time: 0.0577 memory: 6163 grad_norm: 3.7525 loss: 0.7834 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0440 loss_cls: 0.2100 acc: 87.7441 loss_bbox: 0.2406 loss_mask: 0.2586 +2024/10/28 09:17:01 - mmengine - INFO - Epoch(train) [8][3300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:35:00 time: 0.9646 data_time: 0.0515 memory: 6284 grad_norm: 3.9220 loss: 0.6920 loss_rpn_cls: 0.0247 loss_rpn_bbox: 0.0387 loss_cls: 0.1855 acc: 91.6016 loss_bbox: 0.2072 loss_mask: 0.2360 +2024/10/28 09:17:53 - mmengine - INFO - Epoch(train) [8][3350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:34:34 time: 1.0301 data_time: 0.1137 memory: 6176 grad_norm: 3.7888 loss: 0.7949 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0447 loss_cls: 0.2152 acc: 88.2324 loss_bbox: 0.2456 loss_mask: 0.2593 +2024/10/28 09:18:41 - mmengine - INFO - Epoch(train) [8][3400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:34:06 time: 0.9627 data_time: 0.0583 memory: 6097 grad_norm: 4.1696 loss: 0.8187 loss_rpn_cls: 0.0333 loss_rpn_bbox: 0.0478 loss_cls: 0.2316 acc: 94.4336 loss_bbox: 0.2499 loss_mask: 0.2562 +2024/10/28 09:19:30 - mmengine - INFO - Epoch(train) [8][3450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:33:39 time: 0.9845 data_time: 0.0573 memory: 6333 grad_norm: 3.9276 loss: 0.8500 loss_rpn_cls: 0.0338 loss_rpn_bbox: 0.0473 loss_cls: 0.2360 acc: 91.9434 loss_bbox: 0.2654 loss_mask: 0.2676 +2024/10/28 09:20:16 - mmengine - INFO - Epoch(train) [8][3500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:33:10 time: 0.9152 data_time: 0.0622 memory: 6386 grad_norm: 3.7339 loss: 0.7901 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0437 loss_cls: 0.2196 acc: 89.7461 loss_bbox: 0.2474 loss_mask: 0.2511 +2024/10/28 09:21:03 - mmengine - INFO - Epoch(train) [8][3550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:32:41 time: 0.9384 data_time: 0.0515 memory: 6058 grad_norm: 3.6279 loss: 0.7704 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0374 loss_cls: 0.2145 acc: 93.5547 loss_bbox: 0.2388 loss_mask: 0.2514 +2024/10/28 09:21:50 - mmengine - INFO - Epoch(train) [8][3600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:32:12 time: 0.9385 data_time: 0.1094 memory: 6123 grad_norm: 3.7785 loss: 0.8173 loss_rpn_cls: 0.0280 loss_rpn_bbox: 0.0456 loss_cls: 0.2261 acc: 95.1660 loss_bbox: 0.2538 loss_mask: 0.2637 +2024/10/28 09:22:35 - mmengine - INFO - Epoch(train) [8][3650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:31:42 time: 0.9042 data_time: 0.0549 memory: 6420 grad_norm: 3.9233 loss: 0.8073 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0427 loss_cls: 0.2319 acc: 84.2773 loss_bbox: 0.2488 loss_mask: 0.2554 +2024/10/28 09:23:12 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 09:23:20 - mmengine - INFO - Epoch(train) [8][3700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:31:12 time: 0.8940 data_time: 0.0549 memory: 6168 grad_norm: 3.8235 loss: 0.8151 loss_rpn_cls: 0.0266 loss_rpn_bbox: 0.0409 loss_cls: 0.2384 acc: 96.0938 loss_bbox: 0.2499 loss_mask: 0.2593 +2024/10/28 09:24:07 - mmengine - INFO - Epoch(train) [8][3750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:30:43 time: 0.9386 data_time: 0.0531 memory: 6305 grad_norm: 3.8935 loss: 0.8011 loss_rpn_cls: 0.0279 loss_rpn_bbox: 0.0444 loss_cls: 0.2239 acc: 88.9160 loss_bbox: 0.2413 loss_mask: 0.2636 +2024/10/28 09:24:53 - mmengine - INFO - Epoch(train) [8][3800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:30:14 time: 0.9266 data_time: 0.0529 memory: 6153 grad_norm: 3.7345 loss: 0.7353 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0375 loss_cls: 0.1960 acc: 94.9219 loss_bbox: 0.2215 loss_mask: 0.2526 +2024/10/28 09:25:41 - mmengine - INFO - Epoch(train) [8][3850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:29:46 time: 0.9565 data_time: 0.0547 memory: 6388 grad_norm: 3.8864 loss: 0.7816 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0426 loss_cls: 0.2226 acc: 96.8262 loss_bbox: 0.2434 loss_mask: 0.2474 +2024/10/28 09:26:30 - mmengine - INFO - Epoch(train) [8][3900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:29:18 time: 0.9920 data_time: 0.0570 memory: 6039 grad_norm: 3.7850 loss: 0.8068 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0425 loss_cls: 0.2247 acc: 85.4492 loss_bbox: 0.2485 loss_mask: 0.2630 +2024/10/28 09:27:18 - mmengine - INFO - Epoch(train) [8][3950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:28:50 time: 0.9590 data_time: 0.0628 memory: 6232 grad_norm: 3.7967 loss: 0.8495 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0486 loss_cls: 0.2435 acc: 91.1621 loss_bbox: 0.2640 loss_mask: 0.2618 +2024/10/28 09:28:04 - mmengine - INFO - Epoch(train) [8][4000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:28:20 time: 0.9145 data_time: 0.0516 memory: 6212 grad_norm: 3.7574 loss: 0.7769 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0473 loss_cls: 0.2151 acc: 88.2812 loss_bbox: 0.2466 loss_mask: 0.2411 +2024/10/28 09:28:51 - mmengine - INFO - Epoch(train) [8][4050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:27:51 time: 0.9373 data_time: 0.0573 memory: 6298 grad_norm: 3.7555 loss: 0.7762 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0415 loss_cls: 0.2203 acc: 94.1406 loss_bbox: 0.2363 loss_mask: 0.2514 +2024/10/28 09:29:38 - mmengine - INFO - Epoch(train) [8][4100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:27:22 time: 0.9414 data_time: 0.0492 memory: 6282 grad_norm: 3.8405 loss: 0.8284 loss_rpn_cls: 0.0353 loss_rpn_bbox: 0.0518 loss_cls: 0.2301 acc: 94.6289 loss_bbox: 0.2534 loss_mask: 0.2579 +2024/10/28 09:30:24 - mmengine - INFO - Epoch(train) [8][4150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:26:52 time: 0.9198 data_time: 0.0476 memory: 6321 grad_norm: 3.7510 loss: 0.7868 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0467 loss_cls: 0.2161 acc: 94.9219 loss_bbox: 0.2365 loss_mask: 0.2571 +2024/10/28 09:31:10 - mmengine - INFO - Epoch(train) [8][4200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:26:23 time: 0.9208 data_time: 0.0464 memory: 6146 grad_norm: 3.8433 loss: 0.7768 loss_rpn_cls: 0.0296 loss_rpn_bbox: 0.0420 loss_cls: 0.2129 acc: 98.1934 loss_bbox: 0.2326 loss_mask: 0.2597 +2024/10/28 09:31:56 - mmengine - INFO - Epoch(train) [8][4250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:25:53 time: 0.9209 data_time: 0.0459 memory: 6421 grad_norm: 3.8452 loss: 0.7787 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0454 loss_cls: 0.2132 acc: 92.6758 loss_bbox: 0.2350 loss_mask: 0.2608 +2024/10/28 09:32:42 - mmengine - INFO - Epoch(train) [8][4300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:25:23 time: 0.9204 data_time: 0.0598 memory: 6203 grad_norm: 3.6434 loss: 0.7703 loss_rpn_cls: 0.0262 loss_rpn_bbox: 0.0413 loss_cls: 0.2106 acc: 98.0957 loss_bbox: 0.2406 loss_mask: 0.2516 +2024/10/28 09:33:27 - mmengine - INFO - Epoch(train) [8][4350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:24:53 time: 0.9000 data_time: 0.0482 memory: 6408 grad_norm: 4.0114 loss: 0.8535 loss_rpn_cls: 0.0339 loss_rpn_bbox: 0.0478 loss_cls: 0.2382 acc: 85.9375 loss_bbox: 0.2702 loss_mask: 0.2633 +2024/10/28 09:34:12 - mmengine - INFO - Epoch(train) [8][4400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:24:22 time: 0.9006 data_time: 0.0391 memory: 6079 grad_norm: 3.8276 loss: 0.7756 loss_rpn_cls: 0.0323 loss_rpn_bbox: 0.0444 loss_cls: 0.2127 acc: 92.8711 loss_bbox: 0.2316 loss_mask: 0.2546 +2024/10/28 09:35:00 - mmengine - INFO - Epoch(train) [8][4450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:23:54 time: 0.9543 data_time: 0.0538 memory: 6201 grad_norm: 3.7536 loss: 0.7813 loss_rpn_cls: 0.0278 loss_rpn_bbox: 0.0415 loss_cls: 0.2184 acc: 97.8516 loss_bbox: 0.2352 loss_mask: 0.2585 +2024/10/28 09:35:48 - mmengine - INFO - Epoch(train) [8][4500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:23:25 time: 0.9619 data_time: 0.0560 memory: 6337 grad_norm: 4.0054 loss: 0.8684 loss_rpn_cls: 0.0340 loss_rpn_bbox: 0.0508 loss_cls: 0.2440 acc: 95.8496 loss_bbox: 0.2725 loss_mask: 0.2671 +2024/10/28 09:36:37 - mmengine - INFO - Epoch(train) [8][4550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:22:57 time: 0.9774 data_time: 0.0470 memory: 6217 grad_norm: 3.7853 loss: 0.7720 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0422 loss_cls: 0.2178 acc: 89.3555 loss_bbox: 0.2376 loss_mask: 0.2473 +2024/10/28 09:37:24 - mmengine - INFO - Epoch(train) [8][4600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:22:27 time: 0.9400 data_time: 0.0526 memory: 6293 grad_norm: 3.7637 loss: 0.8551 loss_rpn_cls: 0.0291 loss_rpn_bbox: 0.0482 loss_cls: 0.2512 acc: 94.5801 loss_bbox: 0.2650 loss_mask: 0.2615 +2024/10/28 09:38:09 - mmengine - INFO - Epoch(train) [8][4650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:21:57 time: 0.8937 data_time: 0.0454 memory: 6260 grad_norm: 3.8812 loss: 0.7514 loss_rpn_cls: 0.0296 loss_rpn_bbox: 0.0417 loss_cls: 0.2044 acc: 96.0449 loss_bbox: 0.2212 loss_mask: 0.2546 +2024/10/28 09:38:46 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 09:38:56 - mmengine - INFO - Epoch(train) [8][4700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:21:27 time: 0.9418 data_time: 0.0509 memory: 6270 grad_norm: 4.1286 loss: 0.7726 loss_rpn_cls: 0.0270 loss_rpn_bbox: 0.0459 loss_cls: 0.2156 acc: 91.1621 loss_bbox: 0.2370 loss_mask: 0.2471 +2024/10/28 09:39:41 - mmengine - INFO - Epoch(train) [8][4750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:20:57 time: 0.9154 data_time: 0.0481 memory: 6170 grad_norm: 3.8151 loss: 0.7803 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0460 loss_cls: 0.2058 acc: 90.9668 loss_bbox: 0.2394 loss_mask: 0.2591 +2024/10/28 09:40:28 - mmengine - INFO - Epoch(train) [8][4800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:20:27 time: 0.9345 data_time: 0.0439 memory: 6132 grad_norm: 3.7747 loss: 0.6964 loss_rpn_cls: 0.0208 loss_rpn_bbox: 0.0362 loss_cls: 0.1877 acc: 94.2871 loss_bbox: 0.2080 loss_mask: 0.2436 +2024/10/28 09:41:14 - mmengine - INFO - Epoch(train) [8][4850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:19:58 time: 0.9267 data_time: 0.0509 memory: 6131 grad_norm: 3.8228 loss: 0.8048 loss_rpn_cls: 0.0335 loss_rpn_bbox: 0.0474 loss_cls: 0.2275 acc: 92.5781 loss_bbox: 0.2498 loss_mask: 0.2467 +2024/10/28 09:42:04 - mmengine - INFO - Epoch(train) [8][4900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:19:29 time: 0.9908 data_time: 0.0523 memory: 6174 grad_norm: 3.6847 loss: 0.7747 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0448 loss_cls: 0.2207 acc: 97.4121 loss_bbox: 0.2393 loss_mask: 0.2438 +2024/10/28 09:42:52 - mmengine - INFO - Epoch(train) [8][4950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:19:00 time: 0.9527 data_time: 0.0777 memory: 6223 grad_norm: 3.7464 loss: 0.8441 loss_rpn_cls: 0.0308 loss_rpn_bbox: 0.0463 loss_cls: 0.2349 acc: 95.4590 loss_bbox: 0.2664 loss_mask: 0.2657 +2024/10/28 09:43:39 - mmengine - INFO - Epoch(train) [8][5000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:18:31 time: 0.9469 data_time: 0.0530 memory: 6316 grad_norm: 4.0138 loss: 0.8364 loss_rpn_cls: 0.0332 loss_rpn_bbox: 0.0488 loss_cls: 0.2449 acc: 95.1660 loss_bbox: 0.2543 loss_mask: 0.2554 +2024/10/28 09:44:24 - mmengine - INFO - Epoch(train) [8][5050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:18:00 time: 0.9031 data_time: 0.0507 memory: 6208 grad_norm: 4.0170 loss: 0.7583 loss_rpn_cls: 0.0265 loss_rpn_bbox: 0.0454 loss_cls: 0.2131 acc: 96.8750 loss_bbox: 0.2278 loss_mask: 0.2455 +2024/10/28 09:45:11 - mmengine - INFO - Epoch(train) [8][5100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:17:30 time: 0.9395 data_time: 0.0571 memory: 6349 grad_norm: 3.9897 loss: 0.8353 loss_rpn_cls: 0.0287 loss_rpn_bbox: 0.0468 loss_cls: 0.2344 acc: 95.2148 loss_bbox: 0.2614 loss_mask: 0.2640 +2024/10/28 09:45:59 - mmengine - INFO - Epoch(train) [8][5150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:17:01 time: 0.9577 data_time: 0.0490 memory: 6127 grad_norm: 3.7703 loss: 0.8345 loss_rpn_cls: 0.0343 loss_rpn_bbox: 0.0502 loss_cls: 0.2321 acc: 89.8926 loss_bbox: 0.2502 loss_mask: 0.2677 +2024/10/28 09:46:47 - mmengine - INFO - Epoch(train) [8][5200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:16:32 time: 0.9578 data_time: 0.0468 memory: 6363 grad_norm: 3.8310 loss: 0.7865 loss_rpn_cls: 0.0265 loss_rpn_bbox: 0.0472 loss_cls: 0.2160 acc: 91.3086 loss_bbox: 0.2502 loss_mask: 0.2466 +2024/10/28 09:47:32 - mmengine - INFO - Epoch(train) [8][5250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:16:01 time: 0.8952 data_time: 0.0615 memory: 6384 grad_norm: 3.8645 loss: 0.8307 loss_rpn_cls: 0.0303 loss_rpn_bbox: 0.0469 loss_cls: 0.2360 acc: 91.9922 loss_bbox: 0.2579 loss_mask: 0.2596 +2024/10/28 09:48:22 - mmengine - INFO - Epoch(train) [8][5300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:15:33 time: 0.9993 data_time: 0.0512 memory: 6189 grad_norm: 3.6209 loss: 0.7633 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0447 loss_cls: 0.2136 acc: 91.4062 loss_bbox: 0.2290 loss_mask: 0.2454 +2024/10/28 09:49:09 - mmengine - INFO - Epoch(train) [8][5350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:15:03 time: 0.9462 data_time: 0.0522 memory: 6280 grad_norm: 3.7020 loss: 0.7381 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0390 loss_cls: 0.2007 acc: 96.7773 loss_bbox: 0.2238 loss_mask: 0.2487 +2024/10/28 09:49:54 - mmengine - INFO - Epoch(train) [8][5400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:14:32 time: 0.8937 data_time: 0.0509 memory: 6230 grad_norm: 3.7821 loss: 0.7929 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0437 loss_cls: 0.2295 acc: 91.6992 loss_bbox: 0.2379 loss_mask: 0.2563 +2024/10/28 09:50:40 - mmengine - INFO - Epoch(train) [8][5450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:14:02 time: 0.9328 data_time: 0.0535 memory: 6331 grad_norm: 3.9419 loss: 0.8122 loss_rpn_cls: 0.0315 loss_rpn_bbox: 0.0472 loss_cls: 0.2177 acc: 90.9180 loss_bbox: 0.2527 loss_mask: 0.2631 +2024/10/28 09:51:26 - mmengine - INFO - Epoch(train) [8][5500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:13:32 time: 0.9235 data_time: 0.0596 memory: 6195 grad_norm: 4.0817 loss: 0.7661 loss_rpn_cls: 0.0284 loss_rpn_bbox: 0.0402 loss_cls: 0.2091 acc: 93.4082 loss_bbox: 0.2317 loss_mask: 0.2567 +2024/10/28 09:52:12 - mmengine - INFO - Epoch(train) [8][5550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:13:01 time: 0.9182 data_time: 0.0528 memory: 6339 grad_norm: 3.9249 loss: 0.7680 loss_rpn_cls: 0.0281 loss_rpn_bbox: 0.0406 loss_cls: 0.2148 acc: 93.6523 loss_bbox: 0.2359 loss_mask: 0.2485 +2024/10/28 09:52:59 - mmengine - INFO - Epoch(train) [8][5600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:12:31 time: 0.9359 data_time: 0.0507 memory: 6097 grad_norm: 3.8376 loss: 0.7471 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0406 loss_cls: 0.2044 acc: 93.5547 loss_bbox: 0.2252 loss_mask: 0.2486 +2024/10/28 09:53:47 - mmengine - INFO - Epoch(train) [8][5650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:12:01 time: 0.9527 data_time: 0.0502 memory: 6335 grad_norm: 3.8630 loss: 0.8388 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0472 loss_cls: 0.2404 acc: 94.0918 loss_bbox: 0.2556 loss_mask: 0.2649 +2024/10/28 09:54:25 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 09:54:35 - mmengine - INFO - Epoch(train) [8][5700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:11:32 time: 0.9728 data_time: 0.0473 memory: 6293 grad_norm: 3.6930 loss: 0.8321 loss_rpn_cls: 0.0330 loss_rpn_bbox: 0.0429 loss_cls: 0.2318 acc: 91.7969 loss_bbox: 0.2531 loss_mask: 0.2713 +2024/10/28 09:55:22 - mmengine - INFO - Epoch(train) [8][5750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:11:02 time: 0.9356 data_time: 0.0427 memory: 6056 grad_norm: 3.8205 loss: 0.7652 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0400 loss_cls: 0.2163 acc: 97.8027 loss_bbox: 0.2287 loss_mask: 0.2531 +2024/10/28 09:56:10 - mmengine - INFO - Epoch(train) [8][5800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:10:32 time: 0.9444 data_time: 0.0512 memory: 6297 grad_norm: 3.7813 loss: 0.7959 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0448 loss_cls: 0.2271 acc: 89.7949 loss_bbox: 0.2416 loss_mask: 0.2521 +2024/10/28 09:56:58 - mmengine - INFO - Epoch(train) [8][5850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:10:03 time: 0.9732 data_time: 0.0625 memory: 6190 grad_norm: 3.6782 loss: 0.7725 loss_rpn_cls: 0.0278 loss_rpn_bbox: 0.0417 loss_cls: 0.2122 acc: 88.1836 loss_bbox: 0.2400 loss_mask: 0.2508 +2024/10/28 09:57:46 - mmengine - INFO - Epoch(train) [8][5900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:09:33 time: 0.9488 data_time: 0.0596 memory: 6313 grad_norm: 3.7849 loss: 0.9024 loss_rpn_cls: 0.0326 loss_rpn_bbox: 0.0538 loss_cls: 0.2640 acc: 92.5781 loss_bbox: 0.2804 loss_mask: 0.2717 +2024/10/28 09:58:32 - mmengine - INFO - Epoch(train) [8][5950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:09:02 time: 0.9257 data_time: 0.0445 memory: 6270 grad_norm: 3.8770 loss: 0.7607 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0414 loss_cls: 0.2190 acc: 94.2871 loss_bbox: 0.2311 loss_mask: 0.2403 +2024/10/28 09:59:18 - mmengine - INFO - Epoch(train) [8][6000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:08:32 time: 0.9199 data_time: 0.0539 memory: 6319 grad_norm: 3.6935 loss: 0.8092 loss_rpn_cls: 0.0319 loss_rpn_bbox: 0.0506 loss_cls: 0.2286 acc: 90.3809 loss_bbox: 0.2461 loss_mask: 0.2519 +2024/10/28 10:00:04 - mmengine - INFO - Epoch(train) [8][6050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:08:01 time: 0.9255 data_time: 0.0562 memory: 6331 grad_norm: 3.7660 loss: 0.8104 loss_rpn_cls: 0.0356 loss_rpn_bbox: 0.0477 loss_cls: 0.2276 acc: 96.7773 loss_bbox: 0.2437 loss_mask: 0.2559 +2024/10/28 10:00:50 - mmengine - INFO - Epoch(train) [8][6100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:07:30 time: 0.9233 data_time: 0.0754 memory: 6197 grad_norm: 3.8338 loss: 0.8182 loss_rpn_cls: 0.0298 loss_rpn_bbox: 0.0472 loss_cls: 0.2276 acc: 98.3398 loss_bbox: 0.2542 loss_mask: 0.2593 +2024/10/28 10:01:37 - mmengine - INFO - Epoch(train) [8][6150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:07:00 time: 0.9307 data_time: 0.0397 memory: 6156 grad_norm: 3.6285 loss: 0.7628 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0382 loss_cls: 0.2171 acc: 92.5293 loss_bbox: 0.2256 loss_mask: 0.2549 +2024/10/28 10:02:23 - mmengine - INFO - Epoch(train) [8][6200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:06:29 time: 0.9274 data_time: 0.0485 memory: 6303 grad_norm: 3.8713 loss: 0.7859 loss_rpn_cls: 0.0320 loss_rpn_bbox: 0.0446 loss_cls: 0.2155 acc: 95.5566 loss_bbox: 0.2378 loss_mask: 0.2560 +2024/10/28 10:03:09 - mmengine - INFO - Epoch(train) [8][6250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:05:58 time: 0.9062 data_time: 0.0440 memory: 6222 grad_norm: 3.6490 loss: 0.7285 loss_rpn_cls: 0.0234 loss_rpn_bbox: 0.0372 loss_cls: 0.2111 acc: 94.9219 loss_bbox: 0.2208 loss_mask: 0.2359 +2024/10/28 10:03:52 - mmengine - INFO - Epoch(train) [8][6300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:05:26 time: 0.8773 data_time: 0.0409 memory: 6420 grad_norm: 4.0157 loss: 0.7960 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0452 loss_cls: 0.2311 acc: 90.0879 loss_bbox: 0.2412 loss_mask: 0.2534 +2024/10/28 10:04:38 - mmengine - INFO - Epoch(train) [8][6350/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:04:54 time: 0.9053 data_time: 0.0468 memory: 6030 grad_norm: 3.7801 loss: 0.7492 loss_rpn_cls: 0.0237 loss_rpn_bbox: 0.0383 loss_cls: 0.2109 acc: 93.4570 loss_bbox: 0.2222 loss_mask: 0.2540 +2024/10/28 10:05:24 - mmengine - INFO - Epoch(train) [8][6400/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:04:24 time: 0.9339 data_time: 0.0541 memory: 6250 grad_norm: 3.6795 loss: 0.7931 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0455 loss_cls: 0.2246 acc: 95.9473 loss_bbox: 0.2432 loss_mask: 0.2512 +2024/10/28 10:06:12 - mmengine - INFO - Epoch(train) [8][6450/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:03:54 time: 0.9596 data_time: 0.0504 memory: 6158 grad_norm: 3.5501 loss: 0.7952 loss_rpn_cls: 0.0306 loss_rpn_bbox: 0.0427 loss_cls: 0.2195 acc: 91.1621 loss_bbox: 0.2373 loss_mask: 0.2650 +2024/10/28 10:07:01 - mmengine - INFO - Epoch(train) [8][6500/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:03:24 time: 0.9637 data_time: 0.0526 memory: 6275 grad_norm: 3.9101 loss: 0.8673 loss_rpn_cls: 0.0325 loss_rpn_bbox: 0.0501 loss_cls: 0.2396 acc: 99.0723 loss_bbox: 0.2713 loss_mask: 0.2737 +2024/10/28 10:07:47 - mmengine - INFO - Epoch(train) [8][6550/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:02:53 time: 0.9298 data_time: 0.0450 memory: 6402 grad_norm: 3.7584 loss: 0.8101 loss_rpn_cls: 0.0313 loss_rpn_bbox: 0.0453 loss_cls: 0.2262 acc: 91.3086 loss_bbox: 0.2517 loss_mask: 0.2554 +2024/10/28 10:08:30 - mmengine - INFO - Epoch(train) [8][6600/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:02:21 time: 0.8638 data_time: 0.0444 memory: 6224 grad_norm: 4.2183 loss: 0.8250 loss_rpn_cls: 0.0301 loss_rpn_bbox: 0.0484 loss_cls: 0.2304 acc: 88.3789 loss_bbox: 0.2490 loss_mask: 0.2671 +2024/10/28 10:09:18 - mmengine - INFO - Epoch(train) [8][6650/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:01:50 time: 0.9510 data_time: 0.0477 memory: 6158 grad_norm: 3.7313 loss: 0.8113 loss_rpn_cls: 0.0329 loss_rpn_bbox: 0.0444 loss_cls: 0.2344 acc: 96.8750 loss_bbox: 0.2443 loss_mask: 0.2552 +2024/10/28 10:09:56 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 10:10:05 - mmengine - INFO - Epoch(train) [8][6700/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:01:20 time: 0.9377 data_time: 0.0438 memory: 6176 grad_norm: 3.8533 loss: 0.7807 loss_rpn_cls: 0.0253 loss_rpn_bbox: 0.0468 loss_cls: 0.2154 acc: 94.5312 loss_bbox: 0.2327 loss_mask: 0.2604 +2024/10/28 10:10:51 - mmengine - INFO - Epoch(train) [8][6750/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:00:49 time: 0.9195 data_time: 0.0745 memory: 6209 grad_norm: 3.7814 loss: 0.8122 loss_rpn_cls: 0.0280 loss_rpn_bbox: 0.0471 loss_cls: 0.2242 acc: 87.8906 loss_bbox: 0.2459 loss_mask: 0.2669 +2024/10/28 10:11:38 - mmengine - INFO - Epoch(train) [8][6800/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 6:00:18 time: 0.9514 data_time: 0.0431 memory: 6330 grad_norm: 3.6444 loss: 0.7089 loss_rpn_cls: 0.0234 loss_rpn_bbox: 0.0393 loss_cls: 0.1942 acc: 82.3242 loss_bbox: 0.2118 loss_mask: 0.2401 +2024/10/28 10:12:26 - mmengine - INFO - Epoch(train) [8][6850/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:59:48 time: 0.9588 data_time: 0.0466 memory: 6187 grad_norm: 3.8143 loss: 0.8024 loss_rpn_cls: 0.0331 loss_rpn_bbox: 0.0513 loss_cls: 0.2180 acc: 91.0156 loss_bbox: 0.2432 loss_mask: 0.2568 +2024/10/28 10:13:12 - mmengine - INFO - Epoch(train) [8][6900/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:59:17 time: 0.9110 data_time: 0.0510 memory: 6313 grad_norm: 3.7670 loss: 0.7995 loss_rpn_cls: 0.0295 loss_rpn_bbox: 0.0470 loss_cls: 0.2184 acc: 93.2617 loss_bbox: 0.2493 loss_mask: 0.2554 +2024/10/28 10:13:58 - mmengine - INFO - Epoch(train) [8][6950/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:58:45 time: 0.9251 data_time: 0.0562 memory: 6289 grad_norm: 3.8959 loss: 0.7718 loss_rpn_cls: 0.0260 loss_rpn_bbox: 0.0417 loss_cls: 0.2191 acc: 92.1387 loss_bbox: 0.2349 loss_mask: 0.2500 +2024/10/28 10:14:46 - mmengine - INFO - Epoch(train) [8][7000/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:58:15 time: 0.9606 data_time: 0.0624 memory: 6289 grad_norm: 3.6780 loss: 0.7989 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0437 loss_cls: 0.2193 acc: 97.5098 loss_bbox: 0.2526 loss_mask: 0.2548 +2024/10/28 10:15:32 - mmengine - INFO - Epoch(train) [8][7050/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:57:44 time: 0.9266 data_time: 0.0458 memory: 6252 grad_norm: 3.8371 loss: 0.8059 loss_rpn_cls: 0.0245 loss_rpn_bbox: 0.0430 loss_cls: 0.2304 acc: 95.8984 loss_bbox: 0.2482 loss_mask: 0.2597 +2024/10/28 10:16:18 - mmengine - INFO - Epoch(train) [8][7100/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:57:12 time: 0.9039 data_time: 0.0456 memory: 6311 grad_norm: 3.7648 loss: 0.7637 loss_rpn_cls: 0.0294 loss_rpn_bbox: 0.0409 loss_cls: 0.2129 acc: 91.5039 loss_bbox: 0.2311 loss_mask: 0.2493 +2024/10/28 10:17:05 - mmengine - INFO - Epoch(train) [8][7150/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:56:42 time: 0.9448 data_time: 0.0482 memory: 6420 grad_norm: 3.9200 loss: 0.8031 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0417 loss_cls: 0.2365 acc: 93.3105 loss_bbox: 0.2390 loss_mask: 0.2608 +2024/10/28 10:17:51 - mmengine - INFO - Epoch(train) [8][7200/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:56:10 time: 0.9241 data_time: 0.0530 memory: 6383 grad_norm: 3.7410 loss: 0.8556 loss_rpn_cls: 0.0328 loss_rpn_bbox: 0.0504 loss_cls: 0.2378 acc: 92.7246 loss_bbox: 0.2698 loss_mask: 0.2648 +2024/10/28 10:18:38 - mmengine - INFO - Epoch(train) [8][7250/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:55:39 time: 0.9378 data_time: 0.0437 memory: 6172 grad_norm: 4.0121 loss: 0.7518 loss_rpn_cls: 0.0235 loss_rpn_bbox: 0.0451 loss_cls: 0.2024 acc: 91.1621 loss_bbox: 0.2359 loss_mask: 0.2450 +2024/10/28 10:19:24 - mmengine - INFO - Epoch(train) [8][7300/7330] base_lr: 1.8660e-04 lr: 1.8660e-04 eta: 5:55:08 time: 0.9296 data_time: 0.0540 memory: 6192 grad_norm: 3.7696 loss: 0.8479 loss_rpn_cls: 0.0309 loss_rpn_bbox: 0.0497 loss_cls: 0.2400 acc: 94.5312 loss_bbox: 0.2636 loss_mask: 0.2637 +2024/10/28 10:19:52 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 10:19:52 - mmengine - INFO - Saving checkpoint at 8 epochs +2024/10/28 10:20:05 - mmengine - INFO - Epoch(val) [8][ 50/1250] eta: 0:03:16 time: 0.1639 data_time: 0.0070 memory: 6242 +2024/10/28 10:20:14 - mmengine - INFO - Epoch(val) [8][ 100/1250] eta: 0:03:12 time: 0.1708 data_time: 0.0187 memory: 1114 +2024/10/28 10:20:22 - mmengine - INFO - Epoch(val) [8][ 150/1250] eta: 0:03:03 time: 0.1645 data_time: 0.0069 memory: 1114 +2024/10/28 10:20:31 - mmengine - INFO - Epoch(val) [8][ 200/1250] eta: 0:02:57 time: 0.1756 data_time: 0.0121 memory: 1114 +2024/10/28 10:20:39 - mmengine - INFO - Epoch(val) [8][ 250/1250] eta: 0:02:46 time: 0.1601 data_time: 0.0063 memory: 1221 +2024/10/28 10:20:47 - mmengine - INFO - Epoch(val) [8][ 300/1250] eta: 0:02:39 time: 0.1716 data_time: 0.0083 memory: 1114 +2024/10/28 10:20:56 - mmengine - INFO - Epoch(val) [8][ 350/1250] eta: 0:02:30 time: 0.1648 data_time: 0.0063 memory: 1117 +2024/10/28 10:21:04 - mmengine - INFO - Epoch(val) [8][ 400/1250] eta: 0:02:22 time: 0.1689 data_time: 0.0048 memory: 1114 +2024/10/28 10:21:12 - mmengine - INFO - Epoch(val) [8][ 450/1250] eta: 0:02:13 time: 0.1658 data_time: 0.0050 memory: 1114 +2024/10/28 10:21:21 - mmengine - INFO - Epoch(val) [8][ 500/1250] eta: 0:02:05 time: 0.1680 data_time: 0.0055 memory: 1134 +2024/10/28 10:21:29 - mmengine - INFO - Epoch(val) [8][ 550/1250] eta: 0:01:56 time: 0.1588 data_time: 0.0048 memory: 1176 +2024/10/28 10:21:37 - mmengine - INFO - Epoch(val) [8][ 600/1250] eta: 0:01:48 time: 0.1722 data_time: 0.0070 memory: 1114 +2024/10/28 10:21:45 - mmengine - INFO - Epoch(val) [8][ 650/1250] eta: 0:01:39 time: 0.1593 data_time: 0.0046 memory: 1219 +2024/10/28 10:21:54 - mmengine - INFO - Epoch(val) [8][ 700/1250] eta: 0:01:31 time: 0.1671 data_time: 0.0056 memory: 1088 +2024/10/28 10:22:02 - mmengine - INFO - Epoch(val) [8][ 750/1250] eta: 0:01:23 time: 0.1695 data_time: 0.0067 memory: 1082 +2024/10/28 10:22:10 - mmengine - INFO - Epoch(val) [8][ 800/1250] eta: 0:01:14 time: 0.1594 data_time: 0.0051 memory: 1160 +2024/10/28 10:22:19 - mmengine - INFO - Epoch(val) [8][ 850/1250] eta: 0:01:06 time: 0.1705 data_time: 0.0056 memory: 1192 +2024/10/28 10:22:27 - mmengine - INFO - Epoch(val) [8][ 900/1250] eta: 0:00:58 time: 0.1669 data_time: 0.0053 memory: 1114 +2024/10/28 10:22:35 - mmengine - INFO - Epoch(val) [8][ 950/1250] eta: 0:00:49 time: 0.1663 data_time: 0.0071 memory: 1219 +2024/10/28 10:22:44 - mmengine - INFO - Epoch(val) [8][1000/1250] eta: 0:00:41 time: 0.1654 data_time: 0.0052 memory: 1115 +2024/10/28 10:22:52 - mmengine - INFO - Epoch(val) [8][1050/1250] eta: 0:00:33 time: 0.1685 data_time: 0.0063 memory: 1114 +2024/10/28 10:23:00 - mmengine - INFO - Epoch(val) [8][1100/1250] eta: 0:00:24 time: 0.1630 data_time: 0.0049 memory: 1114 +2024/10/28 10:23:08 - mmengine - INFO - Epoch(val) [8][1150/1250] eta: 0:00:16 time: 0.1655 data_time: 0.0061 memory: 1114 +2024/10/28 10:23:17 - mmengine - INFO - Epoch(val) [8][1200/1250] eta: 0:00:08 time: 0.1631 data_time: 0.0068 memory: 1176 +2024/10/28 10:23:25 - mmengine - INFO - Epoch(val) [8][1250/1250] eta: 0:00:00 time: 0.1642 data_time: 0.0052 memory: 1114 +2024/10/28 10:23:39 - mmengine - INFO - Evaluating bbox... +2024/10/28 10:24:11 - mmengine - INFO - bbox_mAP_copypaste: 0.339 0.543 0.367 0.178 0.374 0.463 +2024/10/28 10:24:11 - mmengine - INFO - Evaluating segm... +2024/10/28 10:24:50 - mmengine - INFO - segm_mAP_copypaste: 0.318 0.513 0.338 0.130 0.344 0.488 +2024/10/28 10:24:51 - mmengine - INFO - Epoch(val) [8][1250/1250] coco/bbox_mAP: 0.3390 coco/bbox_mAP_50: 0.5430 coco/bbox_mAP_75: 0.3670 coco/bbox_mAP_s: 0.1780 coco/bbox_mAP_m: 0.3740 coco/bbox_mAP_l: 0.4630 coco/segm_mAP: 0.3180 coco/segm_mAP_50: 0.5130 coco/segm_mAP_75: 0.3380 coco/segm_mAP_s: 0.1300 coco/segm_mAP_m: 0.3440 coco/segm_mAP_l: 0.4880 data_time: 0.0067 time: 0.1661 +2024/10/28 10:25:36 - mmengine - INFO - Epoch(train) [9][ 50/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:54:17 time: 0.8955 data_time: 0.0440 memory: 6260 grad_norm: 3.6274 loss: 0.7695 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0472 loss_cls: 0.2048 acc: 87.9883 loss_bbox: 0.2446 loss_mask: 0.2484 +2024/10/28 10:26:23 - mmengine - INFO - Epoch(train) [9][ 100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:53:46 time: 0.9297 data_time: 0.0428 memory: 6201 grad_norm: 3.6956 loss: 0.7457 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0396 loss_cls: 0.2034 acc: 95.8984 loss_bbox: 0.2316 loss_mask: 0.2444 +2024/10/28 10:27:09 - mmengine - INFO - Epoch(train) [9][ 150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:53:14 time: 0.9202 data_time: 0.0442 memory: 6178 grad_norm: 3.9455 loss: 0.7817 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0450 loss_cls: 0.2260 acc: 93.8477 loss_bbox: 0.2388 loss_mask: 0.2435 +2024/10/28 10:27:56 - mmengine - INFO - Epoch(train) [9][ 200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:52:43 time: 0.9423 data_time: 0.0482 memory: 6388 grad_norm: 3.6153 loss: 0.7849 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0475 loss_cls: 0.2168 acc: 90.2344 loss_bbox: 0.2448 loss_mask: 0.2509 +2024/10/28 10:28:44 - mmengine - INFO - Epoch(train) [9][ 250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:52:13 time: 0.9711 data_time: 0.0496 memory: 6277 grad_norm: 3.7546 loss: 0.7948 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0465 loss_cls: 0.2178 acc: 89.3555 loss_bbox: 0.2539 loss_mask: 0.2500 +2024/10/28 10:29:32 - mmengine - INFO - Epoch(train) [9][ 300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:51:42 time: 0.9443 data_time: 0.0485 memory: 6365 grad_norm: 3.6423 loss: 0.7332 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0399 loss_cls: 0.1982 acc: 94.7754 loss_bbox: 0.2233 loss_mask: 0.2482 +2024/10/28 10:30:19 - mmengine - INFO - Epoch(train) [9][ 350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:51:11 time: 0.9574 data_time: 0.0448 memory: 6143 grad_norm: 3.6275 loss: 0.7438 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0401 loss_cls: 0.2094 acc: 89.8438 loss_bbox: 0.2265 loss_mask: 0.2435 +2024/10/28 10:30:29 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 10:31:05 - mmengine - INFO - Epoch(train) [9][ 400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:50:40 time: 0.9163 data_time: 0.0418 memory: 6084 grad_norm: 3.5968 loss: 0.6926 loss_rpn_cls: 0.0216 loss_rpn_bbox: 0.0360 loss_cls: 0.1765 acc: 92.9688 loss_bbox: 0.2202 loss_mask: 0.2384 +2024/10/28 10:31:52 - mmengine - INFO - Epoch(train) [9][ 450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:50:08 time: 0.9383 data_time: 0.0698 memory: 6420 grad_norm: 3.6474 loss: 0.7977 loss_rpn_cls: 0.0247 loss_rpn_bbox: 0.0439 loss_cls: 0.2227 acc: 92.2363 loss_bbox: 0.2572 loss_mask: 0.2492 +2024/10/28 10:32:40 - mmengine - INFO - Epoch(train) [9][ 500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:49:38 time: 0.9633 data_time: 0.0722 memory: 6397 grad_norm: 3.4437 loss: 0.7588 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0464 loss_cls: 0.2046 acc: 96.2402 loss_bbox: 0.2370 loss_mask: 0.2450 +2024/10/28 10:33:26 - mmengine - INFO - Epoch(train) [9][ 550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:49:06 time: 0.9053 data_time: 0.0540 memory: 6189 grad_norm: 3.4296 loss: 0.6997 loss_rpn_cls: 0.0197 loss_rpn_bbox: 0.0366 loss_cls: 0.1832 acc: 96.6309 loss_bbox: 0.2178 loss_mask: 0.2423 +2024/10/28 10:34:11 - mmengine - INFO - Epoch(train) [9][ 600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:48:34 time: 0.9114 data_time: 0.0502 memory: 6174 grad_norm: 3.6422 loss: 0.7773 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0461 loss_cls: 0.2074 acc: 94.4824 loss_bbox: 0.2426 loss_mask: 0.2544 +2024/10/28 10:34:57 - mmengine - INFO - Epoch(train) [9][ 650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:48:02 time: 0.9078 data_time: 0.0426 memory: 6378 grad_norm: 3.5196 loss: 0.7460 loss_rpn_cls: 0.0223 loss_rpn_bbox: 0.0435 loss_cls: 0.1949 acc: 85.3027 loss_bbox: 0.2353 loss_mask: 0.2500 +2024/10/28 10:35:39 - mmengine - INFO - Epoch(train) [9][ 700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:47:28 time: 0.8547 data_time: 0.0438 memory: 6331 grad_norm: 3.8782 loss: 0.7565 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0415 loss_cls: 0.2118 acc: 93.5059 loss_bbox: 0.2344 loss_mask: 0.2439 +2024/10/28 10:36:23 - mmengine - INFO - Epoch(train) [9][ 750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:46:55 time: 0.8736 data_time: 0.0404 memory: 6035 grad_norm: 3.7611 loss: 0.6832 loss_rpn_cls: 0.0217 loss_rpn_bbox: 0.0373 loss_cls: 0.1854 acc: 98.1445 loss_bbox: 0.2016 loss_mask: 0.2372 +2024/10/28 10:37:11 - mmengine - INFO - Epoch(train) [9][ 800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:46:24 time: 0.9557 data_time: 0.0456 memory: 6205 grad_norm: 3.6979 loss: 0.7518 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0398 loss_cls: 0.2000 acc: 93.5059 loss_bbox: 0.2324 loss_mask: 0.2511 +2024/10/28 10:37:59 - mmengine - INFO - Epoch(train) [9][ 850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:45:54 time: 0.9618 data_time: 0.0515 memory: 6419 grad_norm: 3.7018 loss: 0.7691 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0462 loss_cls: 0.2066 acc: 90.6250 loss_bbox: 0.2416 loss_mask: 0.2485 +2024/10/28 10:38:46 - mmengine - INFO - Epoch(train) [9][ 900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:45:22 time: 0.9511 data_time: 0.0406 memory: 6245 grad_norm: 3.6135 loss: 0.7200 loss_rpn_cls: 0.0204 loss_rpn_bbox: 0.0394 loss_cls: 0.1895 acc: 92.9199 loss_bbox: 0.2266 loss_mask: 0.2441 +2024/10/28 10:39:32 - mmengine - INFO - Epoch(train) [9][ 950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:44:51 time: 0.9198 data_time: 0.0458 memory: 6113 grad_norm: 3.5712 loss: 0.7505 loss_rpn_cls: 0.0263 loss_rpn_bbox: 0.0425 loss_cls: 0.1964 acc: 95.5078 loss_bbox: 0.2324 loss_mask: 0.2529 +2024/10/28 10:40:20 - mmengine - INFO - Epoch(train) [9][1000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:44:19 time: 0.9514 data_time: 0.0487 memory: 6246 grad_norm: 3.4990 loss: 0.7160 loss_rpn_cls: 0.0250 loss_rpn_bbox: 0.0373 loss_cls: 0.1872 acc: 95.0195 loss_bbox: 0.2258 loss_mask: 0.2407 +2024/10/28 10:41:05 - mmengine - INFO - Epoch(train) [9][1050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:43:47 time: 0.9093 data_time: 0.0478 memory: 6285 grad_norm: 3.6980 loss: 0.7731 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0427 loss_cls: 0.2061 acc: 92.8711 loss_bbox: 0.2413 loss_mask: 0.2587 +2024/10/28 10:41:51 - mmengine - INFO - Epoch(train) [9][1100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:43:15 time: 0.9206 data_time: 0.0451 memory: 6310 grad_norm: 3.5837 loss: 0.7312 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0402 loss_cls: 0.2014 acc: 94.1406 loss_bbox: 0.2261 loss_mask: 0.2409 +2024/10/28 10:42:40 - mmengine - INFO - Epoch(train) [9][1150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:42:44 time: 0.9776 data_time: 0.0507 memory: 6294 grad_norm: 3.5518 loss: 0.8059 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0490 loss_cls: 0.2195 acc: 94.0430 loss_bbox: 0.2571 loss_mask: 0.2550 +2024/10/28 10:43:26 - mmengine - INFO - Epoch(train) [9][1200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:42:12 time: 0.9096 data_time: 0.0536 memory: 6269 grad_norm: 3.5715 loss: 0.7286 loss_rpn_cls: 0.0216 loss_rpn_bbox: 0.0380 loss_cls: 0.1998 acc: 95.5078 loss_bbox: 0.2262 loss_mask: 0.2430 +2024/10/28 10:44:12 - mmengine - INFO - Epoch(train) [9][1250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:41:40 time: 0.9210 data_time: 0.0613 memory: 6271 grad_norm: 3.8023 loss: 0.8134 loss_rpn_cls: 0.0299 loss_rpn_bbox: 0.0457 loss_cls: 0.2240 acc: 92.5293 loss_bbox: 0.2608 loss_mask: 0.2530 +2024/10/28 10:44:59 - mmengine - INFO - Epoch(train) [9][1300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:41:09 time: 0.9493 data_time: 0.0481 memory: 6164 grad_norm: 3.6311 loss: 0.7575 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0411 loss_cls: 0.2104 acc: 90.5273 loss_bbox: 0.2312 loss_mask: 0.2509 +2024/10/28 10:45:45 - mmengine - INFO - Epoch(train) [9][1350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:40:36 time: 0.9081 data_time: 0.0470 memory: 6188 grad_norm: 3.4928 loss: 0.7171 loss_rpn_cls: 0.0268 loss_rpn_bbox: 0.0417 loss_cls: 0.1894 acc: 92.5781 loss_bbox: 0.2257 loss_mask: 0.2335 +2024/10/28 10:45:54 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 10:46:30 - mmengine - INFO - Epoch(train) [9][1400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:40:04 time: 0.9029 data_time: 0.0457 memory: 6178 grad_norm: 3.6980 loss: 0.7599 loss_rpn_cls: 0.0242 loss_rpn_bbox: 0.0428 loss_cls: 0.2064 acc: 95.4102 loss_bbox: 0.2306 loss_mask: 0.2559 +2024/10/28 10:47:14 - mmengine - INFO - Epoch(train) [9][1450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:39:31 time: 0.8846 data_time: 0.0475 memory: 6315 grad_norm: 3.6249 loss: 0.6995 loss_rpn_cls: 0.0218 loss_rpn_bbox: 0.0407 loss_cls: 0.1866 acc: 91.1133 loss_bbox: 0.2133 loss_mask: 0.2370 +2024/10/28 10:48:00 - mmengine - INFO - Epoch(train) [9][1500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:38:58 time: 0.9086 data_time: 0.0483 memory: 6251 grad_norm: 3.8322 loss: 0.7550 loss_rpn_cls: 0.0235 loss_rpn_bbox: 0.0423 loss_cls: 0.2049 acc: 94.5801 loss_bbox: 0.2344 loss_mask: 0.2498 +2024/10/28 10:48:47 - mmengine - INFO - Epoch(train) [9][1550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:38:27 time: 0.9489 data_time: 0.0470 memory: 6225 grad_norm: 3.7672 loss: 0.7311 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0417 loss_cls: 0.1963 acc: 89.4531 loss_bbox: 0.2288 loss_mask: 0.2386 +2024/10/28 10:49:34 - mmengine - INFO - Epoch(train) [9][1600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:37:55 time: 0.9333 data_time: 0.0504 memory: 6254 grad_norm: 3.5322 loss: 0.7554 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0417 loss_cls: 0.2094 acc: 92.1875 loss_bbox: 0.2249 loss_mask: 0.2550 +2024/10/28 10:50:19 - mmengine - INFO - Epoch(train) [9][1650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:37:22 time: 0.9081 data_time: 0.0514 memory: 6349 grad_norm: 3.6765 loss: 0.7402 loss_rpn_cls: 0.0297 loss_rpn_bbox: 0.0472 loss_cls: 0.1862 acc: 95.2637 loss_bbox: 0.2284 loss_mask: 0.2488 +2024/10/28 10:51:04 - mmengine - INFO - Epoch(train) [9][1700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:36:50 time: 0.9053 data_time: 0.0485 memory: 6100 grad_norm: 3.7662 loss: 0.7241 loss_rpn_cls: 0.0235 loss_rpn_bbox: 0.0411 loss_cls: 0.1913 acc: 93.4570 loss_bbox: 0.2218 loss_mask: 0.2464 +2024/10/28 10:51:52 - mmengine - INFO - Epoch(train) [9][1750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:36:18 time: 0.9537 data_time: 0.1056 memory: 6108 grad_norm: 3.6391 loss: 0.7733 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0437 loss_cls: 0.2105 acc: 87.2559 loss_bbox: 0.2393 loss_mask: 0.2532 +2024/10/28 10:52:38 - mmengine - INFO - Epoch(train) [9][1800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:35:46 time: 0.9138 data_time: 0.0521 memory: 6245 grad_norm: 3.6983 loss: 0.7503 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0422 loss_cls: 0.2104 acc: 91.3574 loss_bbox: 0.2287 loss_mask: 0.2431 +2024/10/28 10:53:24 - mmengine - INFO - Epoch(train) [9][1850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:35:13 time: 0.9156 data_time: 0.0448 memory: 6252 grad_norm: 3.6197 loss: 0.6995 loss_rpn_cls: 0.0234 loss_rpn_bbox: 0.0411 loss_cls: 0.1882 acc: 93.3594 loss_bbox: 0.2177 loss_mask: 0.2292 +2024/10/28 10:54:10 - mmengine - INFO - Epoch(train) [9][1900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:34:41 time: 0.9223 data_time: 0.0515 memory: 6245 grad_norm: 3.6302 loss: 0.7987 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0440 loss_cls: 0.2199 acc: 89.2578 loss_bbox: 0.2550 loss_mask: 0.2521 +2024/10/28 10:54:58 - mmengine - INFO - Epoch(train) [9][1950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:34:10 time: 0.9594 data_time: 0.0521 memory: 6130 grad_norm: 3.5513 loss: 0.7472 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0409 loss_cls: 0.1977 acc: 90.0879 loss_bbox: 0.2423 loss_mask: 0.2415 +2024/10/28 10:55:45 - mmengine - INFO - Epoch(train) [9][2000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:33:38 time: 0.9386 data_time: 0.0505 memory: 6412 grad_norm: 3.6153 loss: 0.7518 loss_rpn_cls: 0.0269 loss_rpn_bbox: 0.0448 loss_cls: 0.2139 acc: 97.9004 loss_bbox: 0.2274 loss_mask: 0.2388 +2024/10/28 10:56:32 - mmengine - INFO - Epoch(train) [9][2050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:33:06 time: 0.9572 data_time: 0.0477 memory: 6138 grad_norm: 3.6570 loss: 0.7528 loss_rpn_cls: 0.0242 loss_rpn_bbox: 0.0391 loss_cls: 0.2001 acc: 94.7266 loss_bbox: 0.2385 loss_mask: 0.2509 +2024/10/28 10:57:18 - mmengine - INFO - Epoch(train) [9][2100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:32:33 time: 0.9037 data_time: 0.0474 memory: 6162 grad_norm: 3.7794 loss: 0.7292 loss_rpn_cls: 0.0240 loss_rpn_bbox: 0.0424 loss_cls: 0.1918 acc: 95.6543 loss_bbox: 0.2254 loss_mask: 0.2455 +2024/10/28 10:58:04 - mmengine - INFO - Epoch(train) [9][2150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:32:01 time: 0.9302 data_time: 0.0481 memory: 6175 grad_norm: 3.7584 loss: 0.7538 loss_rpn_cls: 0.0292 loss_rpn_bbox: 0.0415 loss_cls: 0.2004 acc: 95.5566 loss_bbox: 0.2371 loss_mask: 0.2456 +2024/10/28 10:58:52 - mmengine - INFO - Epoch(train) [9][2200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:31:30 time: 0.9653 data_time: 0.0641 memory: 6260 grad_norm: 3.6330 loss: 0.8072 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0481 loss_cls: 0.2208 acc: 89.4531 loss_bbox: 0.2553 loss_mask: 0.2562 +2024/10/28 10:59:38 - mmengine - INFO - Epoch(train) [9][2250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:30:57 time: 0.9096 data_time: 0.0544 memory: 6201 grad_norm: 3.7683 loss: 0.7439 loss_rpn_cls: 0.0257 loss_rpn_bbox: 0.0417 loss_cls: 0.2019 acc: 95.1660 loss_bbox: 0.2289 loss_mask: 0.2456 +2024/10/28 11:00:24 - mmengine - INFO - Epoch(train) [9][2300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:30:24 time: 0.9263 data_time: 0.0487 memory: 6140 grad_norm: 3.7322 loss: 0.8111 loss_rpn_cls: 0.0265 loss_rpn_bbox: 0.0468 loss_cls: 0.2167 acc: 92.3340 loss_bbox: 0.2571 loss_mask: 0.2640 +2024/10/28 11:01:10 - mmengine - INFO - Epoch(train) [9][2350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:29:52 time: 0.9195 data_time: 0.0493 memory: 6308 grad_norm: 3.5707 loss: 0.7717 loss_rpn_cls: 0.0257 loss_rpn_bbox: 0.0441 loss_cls: 0.2070 acc: 95.9961 loss_bbox: 0.2438 loss_mask: 0.2511 +2024/10/28 11:01:21 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:02:00 - mmengine - INFO - Epoch(train) [9][2400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:29:21 time: 0.9969 data_time: 0.0474 memory: 6119 grad_norm: 3.6316 loss: 0.7835 loss_rpn_cls: 0.0309 loss_rpn_bbox: 0.0468 loss_cls: 0.2155 acc: 96.0938 loss_bbox: 0.2353 loss_mask: 0.2549 +2024/10/28 11:02:46 - mmengine - INFO - Epoch(train) [9][2450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:28:48 time: 0.9137 data_time: 0.0470 memory: 6278 grad_norm: 3.5054 loss: 0.7636 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0435 loss_cls: 0.2127 acc: 96.2891 loss_bbox: 0.2378 loss_mask: 0.2425 +2024/10/28 11:03:33 - mmengine - INFO - Epoch(train) [9][2500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:28:16 time: 0.9432 data_time: 0.0532 memory: 6152 grad_norm: 3.6922 loss: 0.8041 loss_rpn_cls: 0.0299 loss_rpn_bbox: 0.0469 loss_cls: 0.2140 acc: 92.1875 loss_bbox: 0.2566 loss_mask: 0.2568 +2024/10/28 11:04:18 - mmengine - INFO - Epoch(train) [9][2550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:27:43 time: 0.9107 data_time: 0.0568 memory: 6232 grad_norm: 3.5428 loss: 0.7542 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0408 loss_cls: 0.2002 acc: 95.8008 loss_bbox: 0.2325 loss_mask: 0.2551 +2024/10/28 11:05:05 - mmengine - INFO - Epoch(train) [9][2600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:27:11 time: 0.9234 data_time: 0.0526 memory: 6331 grad_norm: 3.7537 loss: 0.7572 loss_rpn_cls: 0.0245 loss_rpn_bbox: 0.0423 loss_cls: 0.2062 acc: 91.4062 loss_bbox: 0.2374 loss_mask: 0.2468 +2024/10/28 11:05:53 - mmengine - INFO - Epoch(train) [9][2650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:26:39 time: 0.9675 data_time: 0.0751 memory: 6159 grad_norm: 3.6407 loss: 0.8075 loss_rpn_cls: 0.0305 loss_rpn_bbox: 0.0460 loss_cls: 0.2267 acc: 94.8242 loss_bbox: 0.2518 loss_mask: 0.2525 +2024/10/28 11:06:42 - mmengine - INFO - Epoch(train) [9][2700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:26:07 time: 0.9763 data_time: 0.0881 memory: 6243 grad_norm: 3.5487 loss: 0.7097 loss_rpn_cls: 0.0201 loss_rpn_bbox: 0.0424 loss_cls: 0.1829 acc: 94.3359 loss_bbox: 0.2243 loss_mask: 0.2401 +2024/10/28 11:07:26 - mmengine - INFO - Epoch(train) [9][2750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:25:34 time: 0.8743 data_time: 0.0491 memory: 6367 grad_norm: 3.6206 loss: 0.7199 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0364 loss_cls: 0.1935 acc: 95.9473 loss_bbox: 0.2249 loss_mask: 0.2412 +2024/10/28 11:08:11 - mmengine - INFO - Epoch(train) [9][2800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:25:01 time: 0.9135 data_time: 0.0518 memory: 6227 grad_norm: 3.5383 loss: 0.7885 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0473 loss_cls: 0.2251 acc: 96.7773 loss_bbox: 0.2478 loss_mask: 0.2428 +2024/10/28 11:08:58 - mmengine - INFO - Epoch(train) [9][2850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:24:28 time: 0.9268 data_time: 0.0451 memory: 6120 grad_norm: 3.7774 loss: 0.7295 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0411 loss_cls: 0.1980 acc: 93.7500 loss_bbox: 0.2177 loss_mask: 0.2473 +2024/10/28 11:09:41 - mmengine - INFO - Epoch(train) [9][2900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:23:54 time: 0.8743 data_time: 0.0473 memory: 6117 grad_norm: 3.5473 loss: 0.7356 loss_rpn_cls: 0.0245 loss_rpn_bbox: 0.0432 loss_cls: 0.2034 acc: 94.5801 loss_bbox: 0.2302 loss_mask: 0.2343 +2024/10/28 11:10:25 - mmengine - INFO - Epoch(train) [9][2950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:23:20 time: 0.8682 data_time: 0.0492 memory: 6166 grad_norm: 3.7985 loss: 0.7386 loss_rpn_cls: 0.0248 loss_rpn_bbox: 0.0398 loss_cls: 0.2014 acc: 93.4082 loss_bbox: 0.2254 loss_mask: 0.2472 +2024/10/28 11:11:10 - mmengine - INFO - Epoch(train) [9][3000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:22:47 time: 0.9124 data_time: 0.0481 memory: 6284 grad_norm: 3.6362 loss: 0.7346 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0407 loss_cls: 0.2015 acc: 96.4844 loss_bbox: 0.2254 loss_mask: 0.2444 +2024/10/28 11:11:56 - mmengine - INFO - Epoch(train) [9][3050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:22:14 time: 0.9200 data_time: 0.0477 memory: 6207 grad_norm: 3.6465 loss: 0.7098 loss_rpn_cls: 0.0233 loss_rpn_bbox: 0.0374 loss_cls: 0.1834 acc: 92.2852 loss_bbox: 0.2240 loss_mask: 0.2417 +2024/10/28 11:12:44 - mmengine - INFO - Epoch(train) [9][3100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:21:42 time: 0.9513 data_time: 0.0627 memory: 6364 grad_norm: 3.6253 loss: 0.8250 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0508 loss_cls: 0.2270 acc: 86.1816 loss_bbox: 0.2592 loss_mask: 0.2564 +2024/10/28 11:13:30 - mmengine - INFO - Epoch(train) [9][3150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:21:09 time: 0.9134 data_time: 0.0471 memory: 6211 grad_norm: 3.5524 loss: 0.7527 loss_rpn_cls: 0.0253 loss_rpn_bbox: 0.0409 loss_cls: 0.2062 acc: 91.0156 loss_bbox: 0.2324 loss_mask: 0.2480 +2024/10/28 11:14:13 - mmengine - INFO - Epoch(train) [9][3200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:20:35 time: 0.8761 data_time: 0.0465 memory: 6196 grad_norm: 3.5925 loss: 0.7306 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0406 loss_cls: 0.2014 acc: 89.0625 loss_bbox: 0.2242 loss_mask: 0.2393 +2024/10/28 11:15:02 - mmengine - INFO - Epoch(train) [9][3250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:20:03 time: 0.9677 data_time: 0.0437 memory: 6281 grad_norm: 3.6605 loss: 0.7182 loss_rpn_cls: 0.0250 loss_rpn_bbox: 0.0379 loss_cls: 0.1968 acc: 99.2676 loss_bbox: 0.2214 loss_mask: 0.2371 +2024/10/28 11:15:49 - mmengine - INFO - Epoch(train) [9][3300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:19:31 time: 0.9488 data_time: 0.1093 memory: 6173 grad_norm: 3.4490 loss: 0.7974 loss_rpn_cls: 0.0245 loss_rpn_bbox: 0.0447 loss_cls: 0.2279 acc: 97.3633 loss_bbox: 0.2530 loss_mask: 0.2472 +2024/10/28 11:16:31 - mmengine - INFO - Epoch(train) [9][3350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:18:56 time: 0.8427 data_time: 0.0485 memory: 6270 grad_norm: 3.5832 loss: 0.7489 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0417 loss_cls: 0.2133 acc: 96.0938 loss_bbox: 0.2281 loss_mask: 0.2414 +2024/10/28 11:16:41 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:17:17 - mmengine - INFO - Epoch(train) [9][3400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:18:23 time: 0.9168 data_time: 0.0489 memory: 6249 grad_norm: 3.4703 loss: 0.7237 loss_rpn_cls: 0.0250 loss_rpn_bbox: 0.0380 loss_cls: 0.1932 acc: 92.9199 loss_bbox: 0.2213 loss_mask: 0.2462 +2024/10/28 11:18:03 - mmengine - INFO - Epoch(train) [9][3450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:17:50 time: 0.9088 data_time: 0.0446 memory: 6156 grad_norm: 3.7582 loss: 0.7326 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0415 loss_cls: 0.1954 acc: 93.5059 loss_bbox: 0.2187 loss_mask: 0.2542 +2024/10/28 11:18:54 - mmengine - INFO - Epoch(train) [9][3500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:17:19 time: 1.0258 data_time: 0.1100 memory: 6342 grad_norm: 3.7739 loss: 0.7802 loss_rpn_cls: 0.0259 loss_rpn_bbox: 0.0447 loss_cls: 0.2205 acc: 89.9902 loss_bbox: 0.2446 loss_mask: 0.2445 +2024/10/28 11:19:42 - mmengine - INFO - Epoch(train) [9][3550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:16:47 time: 0.9569 data_time: 0.0548 memory: 6415 grad_norm: 3.8780 loss: 0.7666 loss_rpn_cls: 0.0248 loss_rpn_bbox: 0.0433 loss_cls: 0.2140 acc: 96.3379 loss_bbox: 0.2421 loss_mask: 0.2424 +2024/10/28 11:20:28 - mmengine - INFO - Epoch(train) [9][3600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:16:14 time: 0.9322 data_time: 0.0500 memory: 6354 grad_norm: 3.5793 loss: 0.7814 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0432 loss_cls: 0.2180 acc: 91.1133 loss_bbox: 0.2471 loss_mask: 0.2482 +2024/10/28 11:21:13 - mmengine - INFO - Epoch(train) [9][3650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:15:40 time: 0.8873 data_time: 0.0478 memory: 6419 grad_norm: 3.5036 loss: 0.7848 loss_rpn_cls: 0.0287 loss_rpn_bbox: 0.0439 loss_cls: 0.2151 acc: 90.3320 loss_bbox: 0.2461 loss_mask: 0.2510 +2024/10/28 11:22:01 - mmengine - INFO - Epoch(train) [9][3700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:15:08 time: 0.9691 data_time: 0.0474 memory: 6308 grad_norm: 3.6587 loss: 0.8011 loss_rpn_cls: 0.0279 loss_rpn_bbox: 0.0467 loss_cls: 0.2271 acc: 87.7930 loss_bbox: 0.2512 loss_mask: 0.2482 +2024/10/28 11:22:35 - mmengine - INFO - Epoch(train) [9][3750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:14:30 time: 0.6806 data_time: 0.1287 memory: 6334 grad_norm: 3.4587 loss: 0.8018 loss_rpn_cls: 0.0307 loss_rpn_bbox: 0.0466 loss_cls: 0.2156 acc: 93.1641 loss_bbox: 0.2487 loss_mask: 0.2603 +2024/10/28 11:23:00 - mmengine - INFO - Epoch(train) [9][3800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:13:48 time: 0.5010 data_time: 0.0504 memory: 6273 grad_norm: 3.7490 loss: 0.8450 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0474 loss_cls: 0.2330 acc: 91.4062 loss_bbox: 0.2696 loss_mask: 0.2660 +2024/10/28 11:23:26 - mmengine - INFO - Epoch(train) [9][3850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:13:07 time: 0.5061 data_time: 0.0449 memory: 6222 grad_norm: 3.7641 loss: 0.7461 loss_rpn_cls: 0.0316 loss_rpn_bbox: 0.0441 loss_cls: 0.2026 acc: 90.8203 loss_bbox: 0.2298 loss_mask: 0.2380 +2024/10/28 11:23:51 - mmengine - INFO - Epoch(train) [9][3900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:12:25 time: 0.5036 data_time: 0.0533 memory: 6412 grad_norm: 3.6075 loss: 0.8038 loss_rpn_cls: 0.0285 loss_rpn_bbox: 0.0491 loss_cls: 0.2143 acc: 90.4785 loss_bbox: 0.2562 loss_mask: 0.2557 +2024/10/28 11:24:16 - mmengine - INFO - Epoch(train) [9][3950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:11:43 time: 0.5020 data_time: 0.0436 memory: 6378 grad_norm: 3.7736 loss: 0.7117 loss_rpn_cls: 0.0240 loss_rpn_bbox: 0.0394 loss_cls: 0.1912 acc: 93.3105 loss_bbox: 0.2234 loss_mask: 0.2338 +2024/10/28 11:24:42 - mmengine - INFO - Epoch(train) [9][4000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:11:02 time: 0.5183 data_time: 0.0490 memory: 6335 grad_norm: 3.6296 loss: 0.7811 loss_rpn_cls: 0.0260 loss_rpn_bbox: 0.0437 loss_cls: 0.2140 acc: 94.1406 loss_bbox: 0.2497 loss_mask: 0.2477 +2024/10/28 11:25:07 - mmengine - INFO - Epoch(train) [9][4050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:10:21 time: 0.5061 data_time: 0.0568 memory: 6372 grad_norm: 3.6515 loss: 0.7949 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0443 loss_cls: 0.2158 acc: 92.1875 loss_bbox: 0.2587 loss_mask: 0.2510 +2024/10/28 11:25:33 - mmengine - INFO - Epoch(train) [9][4100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:09:39 time: 0.5142 data_time: 0.0459 memory: 6237 grad_norm: 3.7207 loss: 0.7685 loss_rpn_cls: 0.0273 loss_rpn_bbox: 0.0448 loss_cls: 0.2126 acc: 95.5566 loss_bbox: 0.2367 loss_mask: 0.2470 +2024/10/28 11:25:58 - mmengine - INFO - Epoch(train) [9][4150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:08:58 time: 0.5054 data_time: 0.0463 memory: 6034 grad_norm: 3.6822 loss: 0.7428 loss_rpn_cls: 0.0256 loss_rpn_bbox: 0.0443 loss_cls: 0.2005 acc: 93.2129 loss_bbox: 0.2243 loss_mask: 0.2482 +2024/10/28 11:26:24 - mmengine - INFO - Epoch(train) [9][4200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:08:16 time: 0.5076 data_time: 0.0511 memory: 6420 grad_norm: 3.5936 loss: 0.7711 loss_rpn_cls: 0.0323 loss_rpn_bbox: 0.0470 loss_cls: 0.2076 acc: 90.0879 loss_bbox: 0.2367 loss_mask: 0.2475 +2024/10/28 11:26:49 - mmengine - INFO - Epoch(train) [9][4250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:07:35 time: 0.5004 data_time: 0.0482 memory: 6263 grad_norm: 3.7123 loss: 0.7837 loss_rpn_cls: 0.0279 loss_rpn_bbox: 0.0457 loss_cls: 0.2211 acc: 93.0664 loss_bbox: 0.2463 loss_mask: 0.2427 +2024/10/28 11:27:14 - mmengine - INFO - Epoch(train) [9][4300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:06:54 time: 0.5164 data_time: 0.0442 memory: 6313 grad_norm: 3.5691 loss: 0.7870 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0435 loss_cls: 0.2240 acc: 95.3613 loss_bbox: 0.2429 loss_mask: 0.2480 +2024/10/28 11:27:40 - mmengine - INFO - Epoch(train) [9][4350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:06:12 time: 0.5068 data_time: 0.0477 memory: 6266 grad_norm: 3.5743 loss: 0.7669 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0456 loss_cls: 0.2091 acc: 88.0371 loss_bbox: 0.2339 loss_mask: 0.2494 +2024/10/28 11:27:45 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:28:05 - mmengine - INFO - Epoch(train) [9][4400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:05:31 time: 0.5150 data_time: 0.0588 memory: 6229 grad_norm: 3.6001 loss: 0.7737 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0496 loss_cls: 0.2119 acc: 94.6777 loss_bbox: 0.2365 loss_mask: 0.2499 +2024/10/28 11:28:32 - mmengine - INFO - Epoch(train) [9][4450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:04:50 time: 0.5265 data_time: 0.0621 memory: 6242 grad_norm: 3.7554 loss: 0.7753 loss_rpn_cls: 0.0270 loss_rpn_bbox: 0.0488 loss_cls: 0.2006 acc: 94.6289 loss_bbox: 0.2427 loss_mask: 0.2562 +2024/10/28 11:28:58 - mmengine - INFO - Epoch(train) [9][4500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:04:09 time: 0.5196 data_time: 0.0567 memory: 6249 grad_norm: 3.6856 loss: 0.7587 loss_rpn_cls: 0.0264 loss_rpn_bbox: 0.0395 loss_cls: 0.2038 acc: 91.3574 loss_bbox: 0.2387 loss_mask: 0.2503 +2024/10/28 11:29:23 - mmengine - INFO - Epoch(train) [9][4550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:03:28 time: 0.5103 data_time: 0.0506 memory: 6317 grad_norm: 3.4877 loss: 0.6966 loss_rpn_cls: 0.0234 loss_rpn_bbox: 0.0386 loss_cls: 0.1809 acc: 96.2891 loss_bbox: 0.2135 loss_mask: 0.2401 +2024/10/28 11:29:49 - mmengine - INFO - Epoch(train) [9][4600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:02:47 time: 0.5190 data_time: 0.0596 memory: 6339 grad_norm: 3.7058 loss: 0.8309 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0448 loss_cls: 0.2315 acc: 94.5801 loss_bbox: 0.2669 loss_mask: 0.2587 +2024/10/28 11:30:15 - mmengine - INFO - Epoch(train) [9][4650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:02:06 time: 0.5134 data_time: 0.0590 memory: 6170 grad_norm: 3.6970 loss: 0.7935 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0450 loss_cls: 0.2222 acc: 93.7988 loss_bbox: 0.2446 loss_mask: 0.2535 +2024/10/28 11:30:41 - mmengine - INFO - Epoch(train) [9][4700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:01:25 time: 0.5108 data_time: 0.0568 memory: 6255 grad_norm: 3.5328 loss: 0.7834 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0434 loss_cls: 0.2162 acc: 93.3105 loss_bbox: 0.2402 loss_mask: 0.2584 +2024/10/28 11:31:06 - mmengine - INFO - Epoch(train) [9][4750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:00:44 time: 0.5062 data_time: 0.0523 memory: 6150 grad_norm: 3.4805 loss: 0.7809 loss_rpn_cls: 0.0302 loss_rpn_bbox: 0.0438 loss_cls: 0.2101 acc: 89.0625 loss_bbox: 0.2358 loss_mask: 0.2610 +2024/10/28 11:31:31 - mmengine - INFO - Epoch(train) [9][4800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 5:00:03 time: 0.5096 data_time: 0.0457 memory: 6136 grad_norm: 3.4851 loss: 0.6804 loss_rpn_cls: 0.0202 loss_rpn_bbox: 0.0339 loss_cls: 0.1821 acc: 97.6074 loss_bbox: 0.1983 loss_mask: 0.2459 +2024/10/28 11:31:57 - mmengine - INFO - Epoch(train) [9][4850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:59:22 time: 0.5134 data_time: 0.0552 memory: 6342 grad_norm: 3.4759 loss: 0.7318 loss_rpn_cls: 0.0240 loss_rpn_bbox: 0.0415 loss_cls: 0.1894 acc: 96.8262 loss_bbox: 0.2302 loss_mask: 0.2467 +2024/10/28 11:32:23 - mmengine - INFO - Epoch(train) [9][4900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:58:41 time: 0.5252 data_time: 0.0580 memory: 6154 grad_norm: 3.6658 loss: 0.7889 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0463 loss_cls: 0.2086 acc: 92.4805 loss_bbox: 0.2441 loss_mask: 0.2608 +2024/10/28 11:32:49 - mmengine - INFO - Epoch(train) [9][4950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:58:00 time: 0.5201 data_time: 0.0509 memory: 6251 grad_norm: 3.7056 loss: 0.7255 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0346 loss_cls: 0.2013 acc: 94.9219 loss_bbox: 0.2220 loss_mask: 0.2449 +2024/10/28 11:33:15 - mmengine - INFO - Epoch(train) [9][5000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:57:19 time: 0.5151 data_time: 0.0548 memory: 6372 grad_norm: 3.4024 loss: 0.7421 loss_rpn_cls: 0.0263 loss_rpn_bbox: 0.0410 loss_cls: 0.2015 acc: 90.0879 loss_bbox: 0.2244 loss_mask: 0.2489 +2024/10/28 11:33:41 - mmengine - INFO - Epoch(train) [9][5050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:56:39 time: 0.5159 data_time: 0.0385 memory: 6189 grad_norm: 3.4793 loss: 0.6668 loss_rpn_cls: 0.0223 loss_rpn_bbox: 0.0359 loss_cls: 0.1754 acc: 95.0684 loss_bbox: 0.1969 loss_mask: 0.2364 +2024/10/28 11:34:06 - mmengine - INFO - Epoch(train) [9][5100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:55:58 time: 0.5056 data_time: 0.0463 memory: 6247 grad_norm: 3.6324 loss: 0.7586 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0393 loss_cls: 0.2147 acc: 92.2852 loss_bbox: 0.2345 loss_mask: 0.2450 +2024/10/28 11:34:32 - mmengine - INFO - Epoch(train) [9][5150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:55:17 time: 0.5099 data_time: 0.0522 memory: 6187 grad_norm: 3.7318 loss: 0.8449 loss_rpn_cls: 0.0361 loss_rpn_bbox: 0.0451 loss_cls: 0.2320 acc: 92.7246 loss_bbox: 0.2627 loss_mask: 0.2691 +2024/10/28 11:34:56 - mmengine - INFO - Epoch(train) [9][5200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:54:35 time: 0.4960 data_time: 0.0457 memory: 6231 grad_norm: 3.6582 loss: 0.7789 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0401 loss_cls: 0.2218 acc: 85.4492 loss_bbox: 0.2415 loss_mask: 0.2482 +2024/10/28 11:35:22 - mmengine - INFO - Epoch(train) [9][5250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:53:55 time: 0.5146 data_time: 0.0459 memory: 6390 grad_norm: 3.8271 loss: 0.7556 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0432 loss_cls: 0.2022 acc: 91.6992 loss_bbox: 0.2405 loss_mask: 0.2415 +2024/10/28 11:35:47 - mmengine - INFO - Epoch(train) [9][5300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:53:14 time: 0.4946 data_time: 0.0475 memory: 6197 grad_norm: 3.6853 loss: 0.8005 loss_rpn_cls: 0.0265 loss_rpn_bbox: 0.0471 loss_cls: 0.2183 acc: 94.0430 loss_bbox: 0.2488 loss_mask: 0.2598 +2024/10/28 11:36:12 - mmengine - INFO - Epoch(train) [9][5350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:52:33 time: 0.5056 data_time: 0.0494 memory: 6241 grad_norm: 3.6401 loss: 0.7907 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0476 loss_cls: 0.2159 acc: 97.3145 loss_bbox: 0.2518 loss_mask: 0.2499 +2024/10/28 11:36:17 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:36:37 - mmengine - INFO - Epoch(train) [9][5400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:51:52 time: 0.5026 data_time: 0.0413 memory: 6330 grad_norm: 3.5833 loss: 0.7806 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0426 loss_cls: 0.2172 acc: 87.4512 loss_bbox: 0.2436 loss_mask: 0.2524 +2024/10/28 11:37:03 - mmengine - INFO - Epoch(train) [9][5450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:51:11 time: 0.5066 data_time: 0.0469 memory: 6341 grad_norm: 3.6379 loss: 0.8135 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0471 loss_cls: 0.2249 acc: 93.3105 loss_bbox: 0.2502 loss_mask: 0.2630 +2024/10/28 11:37:31 - mmengine - INFO - Epoch(train) [9][5500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:50:31 time: 0.5693 data_time: 0.1148 memory: 6224 grad_norm: 3.5066 loss: 0.7779 loss_rpn_cls: 0.0298 loss_rpn_bbox: 0.0414 loss_cls: 0.2173 acc: 90.2832 loss_bbox: 0.2377 loss_mask: 0.2518 +2024/10/28 11:37:57 - mmengine - INFO - Epoch(train) [9][5550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:49:51 time: 0.5089 data_time: 0.0469 memory: 6360 grad_norm: 3.5685 loss: 0.7610 loss_rpn_cls: 0.0281 loss_rpn_bbox: 0.0440 loss_cls: 0.2130 acc: 91.4551 loss_bbox: 0.2393 loss_mask: 0.2366 +2024/10/28 11:38:22 - mmengine - INFO - Epoch(train) [9][5600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:49:10 time: 0.5100 data_time: 0.0500 memory: 6084 grad_norm: 3.6116 loss: 0.8025 loss_rpn_cls: 0.0264 loss_rpn_bbox: 0.0463 loss_cls: 0.2225 acc: 90.7227 loss_bbox: 0.2525 loss_mask: 0.2549 +2024/10/28 11:38:48 - mmengine - INFO - Epoch(train) [9][5650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:48:29 time: 0.5092 data_time: 0.0466 memory: 6260 grad_norm: 3.5306 loss: 0.7386 loss_rpn_cls: 0.0284 loss_rpn_bbox: 0.0416 loss_cls: 0.2022 acc: 93.6523 loss_bbox: 0.2242 loss_mask: 0.2423 +2024/10/28 11:39:12 - mmengine - INFO - Epoch(train) [9][5700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:47:48 time: 0.4921 data_time: 0.0489 memory: 6290 grad_norm: 3.5817 loss: 0.7837 loss_rpn_cls: 0.0289 loss_rpn_bbox: 0.0473 loss_cls: 0.2086 acc: 94.6289 loss_bbox: 0.2458 loss_mask: 0.2531 +2024/10/28 11:39:37 - mmengine - INFO - Epoch(train) [9][5750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:47:08 time: 0.5001 data_time: 0.0472 memory: 6193 grad_norm: 3.6980 loss: 0.7348 loss_rpn_cls: 0.0248 loss_rpn_bbox: 0.0418 loss_cls: 0.1975 acc: 96.2402 loss_bbox: 0.2287 loss_mask: 0.2420 +2024/10/28 11:40:03 - mmengine - INFO - Epoch(train) [9][5800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:46:27 time: 0.5101 data_time: 0.0519 memory: 6238 grad_norm: 3.6591 loss: 0.7508 loss_rpn_cls: 0.0304 loss_rpn_bbox: 0.0444 loss_cls: 0.2031 acc: 90.2344 loss_bbox: 0.2288 loss_mask: 0.2441 +2024/10/28 11:40:31 - mmengine - INFO - Epoch(train) [9][5850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:45:48 time: 0.5711 data_time: 0.0990 memory: 6278 grad_norm: 3.6248 loss: 0.8204 loss_rpn_cls: 0.0246 loss_rpn_bbox: 0.0455 loss_cls: 0.2272 acc: 90.7715 loss_bbox: 0.2620 loss_mask: 0.2611 +2024/10/28 11:40:56 - mmengine - INFO - Epoch(train) [9][5900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:45:07 time: 0.5002 data_time: 0.0389 memory: 6294 grad_norm: 3.7884 loss: 0.7199 loss_rpn_cls: 0.0259 loss_rpn_bbox: 0.0373 loss_cls: 0.1968 acc: 95.6055 loss_bbox: 0.2143 loss_mask: 0.2456 +2024/10/28 11:41:21 - mmengine - INFO - Epoch(train) [9][5950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:44:26 time: 0.4968 data_time: 0.0473 memory: 6255 grad_norm: 3.6805 loss: 0.8096 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0488 loss_cls: 0.2298 acc: 91.3574 loss_bbox: 0.2601 loss_mask: 0.2438 +2024/10/28 11:41:46 - mmengine - INFO - Epoch(train) [9][6000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:43:46 time: 0.5021 data_time: 0.0512 memory: 6308 grad_norm: 3.6573 loss: 0.7740 loss_rpn_cls: 0.0277 loss_rpn_bbox: 0.0469 loss_cls: 0.2033 acc: 95.9961 loss_bbox: 0.2427 loss_mask: 0.2534 +2024/10/28 11:42:11 - mmengine - INFO - Epoch(train) [9][6050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:43:05 time: 0.5006 data_time: 0.0435 memory: 6201 grad_norm: 3.6736 loss: 0.7721 loss_rpn_cls: 0.0329 loss_rpn_bbox: 0.0447 loss_cls: 0.2009 acc: 91.6504 loss_bbox: 0.2335 loss_mask: 0.2601 +2024/10/28 11:42:37 - mmengine - INFO - Epoch(train) [9][6100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:42:25 time: 0.5166 data_time: 0.0423 memory: 6392 grad_norm: 3.5151 loss: 0.7956 loss_rpn_cls: 0.0273 loss_rpn_bbox: 0.0468 loss_cls: 0.2099 acc: 93.5059 loss_bbox: 0.2465 loss_mask: 0.2651 +2024/10/28 11:43:02 - mmengine - INFO - Epoch(train) [9][6150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:41:44 time: 0.4952 data_time: 0.0417 memory: 6408 grad_norm: 3.7133 loss: 0.7601 loss_rpn_cls: 0.0230 loss_rpn_bbox: 0.0424 loss_cls: 0.2090 acc: 95.7031 loss_bbox: 0.2443 loss_mask: 0.2415 +2024/10/28 11:43:30 - mmengine - INFO - Epoch(train) [9][6200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:41:05 time: 0.5692 data_time: 0.0979 memory: 6130 grad_norm: 3.6283 loss: 0.7857 loss_rpn_cls: 0.0238 loss_rpn_bbox: 0.0410 loss_cls: 0.2169 acc: 89.0625 loss_bbox: 0.2539 loss_mask: 0.2501 +2024/10/28 11:43:55 - mmengine - INFO - Epoch(train) [9][6250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:40:24 time: 0.5038 data_time: 0.0490 memory: 6105 grad_norm: 3.6451 loss: 0.7868 loss_rpn_cls: 0.0270 loss_rpn_bbox: 0.0445 loss_cls: 0.2172 acc: 89.7949 loss_bbox: 0.2462 loss_mask: 0.2519 +2024/10/28 11:44:20 - mmengine - INFO - Epoch(train) [9][6300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:39:43 time: 0.4962 data_time: 0.0394 memory: 6114 grad_norm: 3.5381 loss: 0.7451 loss_rpn_cls: 0.0267 loss_rpn_bbox: 0.0411 loss_cls: 0.2053 acc: 93.2129 loss_bbox: 0.2339 loss_mask: 0.2381 +2024/10/28 11:44:45 - mmengine - INFO - Epoch(train) [9][6350/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:39:03 time: 0.5003 data_time: 0.0456 memory: 6315 grad_norm: 3.5153 loss: 0.7379 loss_rpn_cls: 0.0247 loss_rpn_bbox: 0.0405 loss_cls: 0.1971 acc: 94.0918 loss_bbox: 0.2269 loss_mask: 0.2487 +2024/10/28 11:44:50 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:45:10 - mmengine - INFO - Epoch(train) [9][6400/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:38:22 time: 0.5004 data_time: 0.0437 memory: 6404 grad_norm: 3.4310 loss: 0.7888 loss_rpn_cls: 0.0310 loss_rpn_bbox: 0.0470 loss_cls: 0.2168 acc: 93.6035 loss_bbox: 0.2504 loss_mask: 0.2436 +2024/10/28 11:45:35 - mmengine - INFO - Epoch(train) [9][6450/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:37:42 time: 0.4970 data_time: 0.0368 memory: 6189 grad_norm: 3.6294 loss: 0.7312 loss_rpn_cls: 0.0269 loss_rpn_bbox: 0.0388 loss_cls: 0.1994 acc: 98.7793 loss_bbox: 0.2183 loss_mask: 0.2478 +2024/10/28 11:46:01 - mmengine - INFO - Epoch(train) [9][6500/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:37:02 time: 0.5134 data_time: 0.0486 memory: 6274 grad_norm: 3.6970 loss: 0.7759 loss_rpn_cls: 0.0312 loss_rpn_bbox: 0.0466 loss_cls: 0.2137 acc: 91.6016 loss_bbox: 0.2412 loss_mask: 0.2432 +2024/10/28 11:46:26 - mmengine - INFO - Epoch(train) [9][6550/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:36:21 time: 0.4935 data_time: 0.0427 memory: 6265 grad_norm: 3.5215 loss: 0.7478 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0434 loss_cls: 0.2022 acc: 92.5293 loss_bbox: 0.2306 loss_mask: 0.2445 +2024/10/28 11:46:51 - mmengine - INFO - Epoch(train) [9][6600/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:35:41 time: 0.5053 data_time: 0.0479 memory: 6229 grad_norm: 3.5547 loss: 0.7727 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0470 loss_cls: 0.2021 acc: 95.8008 loss_bbox: 0.2411 loss_mask: 0.2543 +2024/10/28 11:47:16 - mmengine - INFO - Epoch(train) [9][6650/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:35:01 time: 0.4992 data_time: 0.0390 memory: 6119 grad_norm: 3.8624 loss: 0.7191 loss_rpn_cls: 0.0217 loss_rpn_bbox: 0.0405 loss_cls: 0.1999 acc: 94.9219 loss_bbox: 0.2178 loss_mask: 0.2392 +2024/10/28 11:47:41 - mmengine - INFO - Epoch(train) [9][6700/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:34:20 time: 0.5117 data_time: 0.0428 memory: 6374 grad_norm: 3.5758 loss: 0.8032 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0469 loss_cls: 0.2159 acc: 94.2383 loss_bbox: 0.2511 loss_mask: 0.2650 +2024/10/28 11:48:07 - mmengine - INFO - Epoch(train) [9][6750/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:33:40 time: 0.5143 data_time: 0.0414 memory: 6234 grad_norm: 3.6529 loss: 0.7706 loss_rpn_cls: 0.0282 loss_rpn_bbox: 0.0444 loss_cls: 0.2072 acc: 90.4297 loss_bbox: 0.2339 loss_mask: 0.2570 +2024/10/28 11:48:32 - mmengine - INFO - Epoch(train) [9][6800/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:33:00 time: 0.5074 data_time: 0.0377 memory: 6294 grad_norm: 3.7331 loss: 0.7327 loss_rpn_cls: 0.0249 loss_rpn_bbox: 0.0402 loss_cls: 0.2027 acc: 94.0918 loss_bbox: 0.2267 loss_mask: 0.2382 +2024/10/28 11:48:57 - mmengine - INFO - Epoch(train) [9][6850/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:32:20 time: 0.4996 data_time: 0.0460 memory: 6191 grad_norm: 3.5870 loss: 0.7928 loss_rpn_cls: 0.0286 loss_rpn_bbox: 0.0446 loss_cls: 0.2156 acc: 92.3828 loss_bbox: 0.2514 loss_mask: 0.2525 +2024/10/28 11:49:23 - mmengine - INFO - Epoch(train) [9][6900/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:31:40 time: 0.5136 data_time: 0.0411 memory: 6171 grad_norm: 3.7381 loss: 0.7815 loss_rpn_cls: 0.0255 loss_rpn_bbox: 0.0463 loss_cls: 0.2197 acc: 89.5508 loss_bbox: 0.2396 loss_mask: 0.2503 +2024/10/28 11:49:48 - mmengine - INFO - Epoch(train) [9][6950/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:31:00 time: 0.4999 data_time: 0.0406 memory: 6282 grad_norm: 3.7348 loss: 0.7852 loss_rpn_cls: 0.0290 loss_rpn_bbox: 0.0459 loss_cls: 0.2132 acc: 89.8438 loss_bbox: 0.2442 loss_mask: 0.2530 +2024/10/28 11:50:14 - mmengine - INFO - Epoch(train) [9][7000/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:30:20 time: 0.5075 data_time: 0.0397 memory: 6368 grad_norm: 3.7455 loss: 0.7381 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0409 loss_cls: 0.2023 acc: 90.9668 loss_bbox: 0.2280 loss_mask: 0.2418 +2024/10/28 11:50:39 - mmengine - INFO - Epoch(train) [9][7050/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:29:39 time: 0.5012 data_time: 0.0431 memory: 6421 grad_norm: 3.6774 loss: 0.7989 loss_rpn_cls: 0.0275 loss_rpn_bbox: 0.0462 loss_cls: 0.2155 acc: 94.7754 loss_bbox: 0.2555 loss_mask: 0.2541 +2024/10/28 11:51:04 - mmengine - INFO - Epoch(train) [9][7100/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:29:00 time: 0.5167 data_time: 0.0456 memory: 6284 grad_norm: 3.5324 loss: 0.7117 loss_rpn_cls: 0.0181 loss_rpn_bbox: 0.0372 loss_cls: 0.1944 acc: 90.2832 loss_bbox: 0.2248 loss_mask: 0.2371 +2024/10/28 11:51:32 - mmengine - INFO - Epoch(train) [9][7150/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:28:20 time: 0.5465 data_time: 0.0830 memory: 6276 grad_norm: 3.6007 loss: 0.7632 loss_rpn_cls: 0.0231 loss_rpn_bbox: 0.0407 loss_cls: 0.2047 acc: 92.4805 loss_bbox: 0.2450 loss_mask: 0.2497 +2024/10/28 11:51:58 - mmengine - INFO - Epoch(train) [9][7200/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:27:40 time: 0.5194 data_time: 0.0536 memory: 6341 grad_norm: 3.7217 loss: 0.7967 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0476 loss_cls: 0.2248 acc: 93.7500 loss_bbox: 0.2443 loss_mask: 0.2547 +2024/10/28 11:52:23 - mmengine - INFO - Epoch(train) [9][7250/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:27:00 time: 0.5060 data_time: 0.0449 memory: 6198 grad_norm: 3.5613 loss: 0.7754 loss_rpn_cls: 0.0253 loss_rpn_bbox: 0.0418 loss_cls: 0.2086 acc: 93.6035 loss_bbox: 0.2424 loss_mask: 0.2573 +2024/10/28 11:52:49 - mmengine - INFO - Epoch(train) [9][7300/7330] base_lr: 1.5000e-04 lr: 1.5000e-04 eta: 4:26:21 time: 0.5107 data_time: 0.0446 memory: 6146 grad_norm: 3.7752 loss: 0.7735 loss_rpn_cls: 0.0271 loss_rpn_bbox: 0.0425 loss_cls: 0.2155 acc: 92.4805 loss_bbox: 0.2363 loss_mask: 0.2523 +2024/10/28 11:53:04 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:53:04 - mmengine - INFO - Saving checkpoint at 9 epochs +2024/10/28 11:53:17 - mmengine - INFO - Epoch(val) [9][ 50/1250] eta: 0:02:16 time: 0.1140 data_time: 0.0053 memory: 6988 +2024/10/28 11:53:23 - mmengine - INFO - Epoch(val) [9][ 100/1250] eta: 0:02:09 time: 0.1104 data_time: 0.0036 memory: 1114 +2024/10/28 11:53:28 - mmengine - INFO - Epoch(val) [9][ 150/1250] eta: 0:02:02 time: 0.1103 data_time: 0.0039 memory: 1114 +2024/10/28 11:53:34 - mmengine - INFO - Epoch(val) [9][ 200/1250] eta: 0:01:58 time: 0.1161 data_time: 0.0053 memory: 1114 +2024/10/28 11:53:39 - mmengine - INFO - Epoch(val) [9][ 250/1250] eta: 0:01:52 time: 0.1104 data_time: 0.0046 memory: 1221 +2024/10/28 11:53:45 - mmengine - INFO - Epoch(val) [9][ 300/1250] eta: 0:01:46 time: 0.1117 data_time: 0.0050 memory: 1114 +2024/10/28 11:53:50 - mmengine - INFO - Epoch(val) [9][ 350/1250] eta: 0:01:40 time: 0.1094 data_time: 0.0043 memory: 1117 +2024/10/28 11:53:56 - mmengine - INFO - Epoch(val) [9][ 400/1250] eta: 0:01:34 time: 0.1079 data_time: 0.0036 memory: 1114 +2024/10/28 11:54:01 - mmengine - INFO - Epoch(val) [9][ 450/1250] eta: 0:01:28 time: 0.1092 data_time: 0.0037 memory: 1114 +2024/10/28 11:54:07 - mmengine - INFO - Epoch(val) [9][ 500/1250] eta: 0:01:23 time: 0.1117 data_time: 0.0040 memory: 1134 +2024/10/28 11:54:12 - mmengine - INFO - Epoch(val) [9][ 550/1250] eta: 0:01:17 time: 0.1080 data_time: 0.0034 memory: 1176 +2024/10/28 11:54:18 - mmengine - INFO - Epoch(val) [9][ 600/1250] eta: 0:01:12 time: 0.1146 data_time: 0.0047 memory: 1114 +2024/10/28 11:54:23 - mmengine - INFO - Epoch(val) [9][ 650/1250] eta: 0:01:06 time: 0.1095 data_time: 0.0034 memory: 1219 +2024/10/28 11:54:29 - mmengine - INFO - Epoch(val) [9][ 700/1250] eta: 0:01:01 time: 0.1152 data_time: 0.0044 memory: 1114 +2024/10/28 11:54:35 - mmengine - INFO - Epoch(val) [9][ 750/1250] eta: 0:00:55 time: 0.1129 data_time: 0.0048 memory: 1082 +2024/10/28 11:54:40 - mmengine - INFO - Epoch(val) [9][ 800/1250] eta: 0:00:50 time: 0.1097 data_time: 0.0038 memory: 1126 +2024/10/28 11:54:46 - mmengine - INFO - Epoch(val) [9][ 850/1250] eta: 0:00:44 time: 0.1096 data_time: 0.0040 memory: 1114 +2024/10/28 11:54:51 - mmengine - INFO - Epoch(val) [9][ 900/1250] eta: 0:00:38 time: 0.1089 data_time: 0.0030 memory: 1114 +2024/10/28 11:54:57 - mmengine - INFO - Epoch(val) [9][ 950/1250] eta: 0:00:33 time: 0.1129 data_time: 0.0050 memory: 1219 +2024/10/28 11:55:02 - mmengine - INFO - Epoch(val) [9][1000/1250] eta: 0:00:27 time: 0.1078 data_time: 0.0037 memory: 1119 +2024/10/28 11:55:08 - mmengine - INFO - Epoch(val) [9][1050/1250] eta: 0:00:22 time: 0.1200 data_time: 0.0048 memory: 1114 +2024/10/28 11:55:14 - mmengine - INFO - Epoch(val) [9][1100/1250] eta: 0:00:16 time: 0.1107 data_time: 0.0033 memory: 1090 +2024/10/28 11:55:20 - mmengine - INFO - Epoch(val) [9][1150/1250] eta: 0:00:11 time: 0.1149 data_time: 0.0039 memory: 1114 +2024/10/28 11:55:25 - mmengine - INFO - Epoch(val) [9][1200/1250] eta: 0:00:05 time: 0.1138 data_time: 0.0032 memory: 1176 +2024/10/28 11:55:31 - mmengine - INFO - Epoch(val) [9][1250/1250] eta: 0:00:00 time: 0.1089 data_time: 0.0036 memory: 1114 +2024/10/28 11:55:43 - mmengine - INFO - Evaluating bbox... +2024/10/28 11:56:10 - mmengine - INFO - bbox_mAP_copypaste: 0.358 0.567 0.390 0.184 0.391 0.493 +2024/10/28 11:56:10 - mmengine - INFO - Evaluating segm... +2024/10/28 11:56:42 - mmengine - INFO - segm_mAP_copypaste: 0.336 0.541 0.360 0.138 0.360 0.510 +2024/10/28 11:56:42 - mmengine - INFO - Epoch(val) [9][1250/1250] coco/bbox_mAP: 0.3580 coco/bbox_mAP_50: 0.5670 coco/bbox_mAP_75: 0.3900 coco/bbox_mAP_s: 0.1840 coco/bbox_mAP_m: 0.3910 coco/bbox_mAP_l: 0.4930 coco/segm_mAP: 0.3360 coco/segm_mAP_50: 0.5410 coco/segm_mAP_75: 0.3600 coco/segm_mAP_s: 0.1380 coco/segm_mAP_m: 0.3600 coco/segm_mAP_l: 0.5100 data_time: 0.0041 time: 0.1116 +2024/10/28 11:57:12 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 11:57:32 - mmengine - INFO - Epoch(train) [10][ 50/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:25:25 time: 0.9983 data_time: 0.0488 memory: 6196 grad_norm: 3.5195 loss: 0.7487 loss_rpn_cls: 0.0264 loss_rpn_bbox: 0.0458 loss_cls: 0.1982 acc: 93.9941 loss_bbox: 0.2324 loss_mask: 0.2459 +2024/10/28 11:58:20 - mmengine - INFO - Epoch(train) [10][ 100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:24:53 time: 0.9577 data_time: 0.0337 memory: 6166 grad_norm: 3.4426 loss: 0.6691 loss_rpn_cls: 0.0204 loss_rpn_bbox: 0.0379 loss_cls: 0.1727 acc: 93.3594 loss_bbox: 0.2096 loss_mask: 0.2285 +2024/10/28 11:59:11 - mmengine - INFO - Epoch(train) [10][ 150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:24:21 time: 1.0191 data_time: 0.0462 memory: 6231 grad_norm: 3.4129 loss: 0.7829 loss_rpn_cls: 0.0264 loss_rpn_bbox: 0.0460 loss_cls: 0.2082 acc: 90.7715 loss_bbox: 0.2560 loss_mask: 0.2463 +2024/10/28 12:00:01 - mmengine - INFO - Epoch(train) [10][ 200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:23:49 time: 0.9931 data_time: 0.0501 memory: 6081 grad_norm: 3.4092 loss: 0.7271 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0411 loss_cls: 0.1885 acc: 93.0664 loss_bbox: 0.2280 loss_mask: 0.2458 +2024/10/28 12:00:55 - mmengine - INFO - Epoch(train) [10][ 250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:23:19 time: 1.0767 data_time: 0.0579 memory: 6225 grad_norm: 3.4172 loss: 0.7612 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0462 loss_cls: 0.1986 acc: 96.3379 loss_bbox: 0.2423 loss_mask: 0.2497 +2024/10/28 12:01:47 - mmengine - INFO - Epoch(train) [10][ 300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:22:48 time: 1.0443 data_time: 0.0505 memory: 6196 grad_norm: 3.3735 loss: 0.7282 loss_rpn_cls: 0.0200 loss_rpn_bbox: 0.0399 loss_cls: 0.1940 acc: 94.0918 loss_bbox: 0.2331 loss_mask: 0.2412 +2024/10/28 12:02:36 - mmengine - INFO - Epoch(train) [10][ 350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:22:15 time: 0.9726 data_time: 0.0536 memory: 6183 grad_norm: 3.3458 loss: 0.7188 loss_rpn_cls: 0.0232 loss_rpn_bbox: 0.0416 loss_cls: 0.1854 acc: 88.2324 loss_bbox: 0.2255 loss_mask: 0.2431 +2024/10/28 12:03:27 - mmengine - INFO - Epoch(train) [10][ 400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:21:44 time: 1.0201 data_time: 0.0506 memory: 6274 grad_norm: 3.5375 loss: 0.7153 loss_rpn_cls: 0.0230 loss_rpn_bbox: 0.0412 loss_cls: 0.1812 acc: 93.7988 loss_bbox: 0.2203 loss_mask: 0.2496 +2024/10/28 12:04:12 - mmengine - INFO - Epoch(train) [10][ 450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:21:10 time: 0.9144 data_time: 0.0545 memory: 6126 grad_norm: 3.3597 loss: 0.6728 loss_rpn_cls: 0.0207 loss_rpn_bbox: 0.0359 loss_cls: 0.1725 acc: 95.9473 loss_bbox: 0.2127 loss_mask: 0.2310 +2024/10/28 12:05:04 - mmengine - INFO - Epoch(train) [10][ 500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:20:39 time: 1.0332 data_time: 0.0498 memory: 6420 grad_norm: 3.5493 loss: 0.6794 loss_rpn_cls: 0.0214 loss_rpn_bbox: 0.0367 loss_cls: 0.1774 acc: 94.1406 loss_bbox: 0.2139 loss_mask: 0.2301 +2024/10/28 12:05:58 - mmengine - INFO - Epoch(train) [10][ 550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:20:08 time: 1.0758 data_time: 0.0652 memory: 6398 grad_norm: 3.2637 loss: 0.6817 loss_rpn_cls: 0.0191 loss_rpn_bbox: 0.0371 loss_cls: 0.1755 acc: 92.3340 loss_bbox: 0.2198 loss_mask: 0.2301 +2024/10/28 12:06:52 - mmengine - INFO - Epoch(train) [10][ 600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:19:37 time: 1.0868 data_time: 0.0460 memory: 6270 grad_norm: 3.4541 loss: 0.7035 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0383 loss_cls: 0.1815 acc: 91.2109 loss_bbox: 0.2168 loss_mask: 0.2441 +2024/10/28 12:07:42 - mmengine - INFO - Epoch(train) [10][ 650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:19:05 time: 1.0038 data_time: 0.0514 memory: 6175 grad_norm: 3.4327 loss: 0.6760 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0364 loss_cls: 0.1774 acc: 89.0137 loss_bbox: 0.2105 loss_mask: 0.2332 +2024/10/28 12:08:35 - mmengine - INFO - Epoch(train) [10][ 700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:18:34 time: 1.0563 data_time: 0.0472 memory: 6065 grad_norm: 3.2498 loss: 0.6876 loss_rpn_cls: 0.0240 loss_rpn_bbox: 0.0372 loss_cls: 0.1800 acc: 97.3633 loss_bbox: 0.2128 loss_mask: 0.2335 +2024/10/28 12:09:26 - mmengine - INFO - Epoch(train) [10][ 750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:18:02 time: 1.0082 data_time: 0.0509 memory: 6285 grad_norm: 3.3729 loss: 0.7582 loss_rpn_cls: 0.0242 loss_rpn_bbox: 0.0436 loss_cls: 0.1958 acc: 95.8008 loss_bbox: 0.2445 loss_mask: 0.2501 +2024/10/28 12:10:14 - mmengine - INFO - Epoch(train) [10][ 800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:17:30 time: 0.9672 data_time: 0.0479 memory: 6228 grad_norm: 3.4427 loss: 0.7211 loss_rpn_cls: 0.0223 loss_rpn_bbox: 0.0411 loss_cls: 0.1973 acc: 92.7246 loss_bbox: 0.2296 loss_mask: 0.2308 +2024/10/28 12:11:04 - mmengine - INFO - Epoch(train) [10][ 850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:16:57 time: 0.9947 data_time: 0.0440 memory: 6184 grad_norm: 3.5283 loss: 0.6437 loss_rpn_cls: 0.0219 loss_rpn_bbox: 0.0351 loss_cls: 0.1736 acc: 96.9238 loss_bbox: 0.1994 loss_mask: 0.2138 +2024/10/28 12:11:58 - mmengine - INFO - Epoch(train) [10][ 900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:16:26 time: 1.0826 data_time: 0.1008 memory: 6283 grad_norm: 3.6280 loss: 0.7151 loss_rpn_cls: 0.0213 loss_rpn_bbox: 0.0397 loss_cls: 0.1981 acc: 90.8203 loss_bbox: 0.2221 loss_mask: 0.2339 +2024/10/28 12:12:51 - mmengine - INFO - Epoch(train) [10][ 950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:15:55 time: 1.0735 data_time: 0.0474 memory: 6117 grad_norm: 3.3620 loss: 0.7143 loss_rpn_cls: 0.0203 loss_rpn_bbox: 0.0384 loss_cls: 0.1820 acc: 93.5059 loss_bbox: 0.2299 loss_mask: 0.2437 +2024/10/28 12:13:43 - mmengine - INFO - Epoch(train) [10][1000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:15:24 time: 1.0353 data_time: 0.0528 memory: 6346 grad_norm: 3.5200 loss: 0.6909 loss_rpn_cls: 0.0221 loss_rpn_bbox: 0.0364 loss_cls: 0.1821 acc: 93.7500 loss_bbox: 0.2146 loss_mask: 0.2358 +2024/10/28 12:14:13 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 12:14:34 - mmengine - INFO - Epoch(train) [10][1050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:14:52 time: 1.0210 data_time: 0.0542 memory: 6394 grad_norm: 3.2722 loss: 0.6961 loss_rpn_cls: 0.0212 loss_rpn_bbox: 0.0396 loss_cls: 0.1834 acc: 93.7500 loss_bbox: 0.2136 loss_mask: 0.2383 +2024/10/28 12:15:23 - mmengine - INFO - Epoch(train) [10][1100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:14:19 time: 0.9741 data_time: 0.0488 memory: 6182 grad_norm: 3.4020 loss: 0.6782 loss_rpn_cls: 0.0171 loss_rpn_bbox: 0.0359 loss_cls: 0.1689 acc: 94.2383 loss_bbox: 0.2131 loss_mask: 0.2432 +2024/10/28 12:16:17 - mmengine - INFO - Epoch(train) [10][1150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:13:48 time: 1.0903 data_time: 0.0628 memory: 6197 grad_norm: 3.5391 loss: 0.7046 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0442 loss_cls: 0.1767 acc: 93.7988 loss_bbox: 0.2161 loss_mask: 0.2415 +2024/10/28 12:17:08 - mmengine - INFO - Epoch(train) [10][1200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:13:16 time: 1.0167 data_time: 0.0541 memory: 6243 grad_norm: 3.4534 loss: 0.7180 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0416 loss_cls: 0.1868 acc: 95.7031 loss_bbox: 0.2312 loss_mask: 0.2357 +2024/10/28 12:17:59 - mmengine - INFO - Epoch(train) [10][1250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:12:44 time: 1.0152 data_time: 0.0546 memory: 6292 grad_norm: 3.3916 loss: 0.7582 loss_rpn_cls: 0.0225 loss_rpn_bbox: 0.0440 loss_cls: 0.1970 acc: 93.8477 loss_bbox: 0.2405 loss_mask: 0.2542 +2024/10/28 12:18:46 - mmengine - INFO - Epoch(train) [10][1300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:12:10 time: 0.9331 data_time: 0.0454 memory: 6229 grad_norm: 3.3443 loss: 0.6798 loss_rpn_cls: 0.0196 loss_rpn_bbox: 0.0410 loss_cls: 0.1713 acc: 98.9746 loss_bbox: 0.2088 loss_mask: 0.2391 +2024/10/28 12:19:34 - mmengine - INFO - Epoch(train) [10][1350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:11:37 time: 0.9739 data_time: 0.0450 memory: 6346 grad_norm: 3.4723 loss: 0.6735 loss_rpn_cls: 0.0201 loss_rpn_bbox: 0.0365 loss_cls: 0.1716 acc: 97.6074 loss_bbox: 0.2163 loss_mask: 0.2290 +2024/10/28 12:20:25 - mmengine - INFO - Epoch(train) [10][1400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:11:05 time: 1.0148 data_time: 0.0468 memory: 6172 grad_norm: 3.5903 loss: 0.7195 loss_rpn_cls: 0.0223 loss_rpn_bbox: 0.0452 loss_cls: 0.1872 acc: 93.7012 loss_bbox: 0.2230 loss_mask: 0.2417 +2024/10/28 12:21:15 - mmengine - INFO - Epoch(train) [10][1450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:10:33 time: 0.9983 data_time: 0.0454 memory: 6211 grad_norm: 3.3433 loss: 0.6836 loss_rpn_cls: 0.0193 loss_rpn_bbox: 0.0373 loss_cls: 0.1811 acc: 89.8926 loss_bbox: 0.2125 loss_mask: 0.2335 +2024/10/28 12:22:08 - mmengine - INFO - Epoch(train) [10][1500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:10:01 time: 1.0484 data_time: 0.0493 memory: 6260 grad_norm: 3.3811 loss: 0.6905 loss_rpn_cls: 0.0203 loss_rpn_bbox: 0.0375 loss_cls: 0.1855 acc: 95.7031 loss_bbox: 0.2194 loss_mask: 0.2278 +2024/10/28 12:22:58 - mmengine - INFO - Epoch(train) [10][1550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:09:29 time: 1.0138 data_time: 0.0462 memory: 6187 grad_norm: 3.6199 loss: 0.7045 loss_rpn_cls: 0.0217 loss_rpn_bbox: 0.0411 loss_cls: 0.1946 acc: 90.5762 loss_bbox: 0.2169 loss_mask: 0.2301 +2024/10/28 12:23:49 - mmengine - INFO - Epoch(train) [10][1600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:08:56 time: 1.0123 data_time: 0.0492 memory: 6205 grad_norm: 3.2995 loss: 0.7283 loss_rpn_cls: 0.0202 loss_rpn_bbox: 0.0397 loss_cls: 0.1923 acc: 90.0391 loss_bbox: 0.2341 loss_mask: 0.2419 +2024/10/28 12:24:38 - mmengine - INFO - Epoch(train) [10][1650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:08:23 time: 0.9896 data_time: 0.0435 memory: 6326 grad_norm: 3.5427 loss: 0.7336 loss_rpn_cls: 0.0248 loss_rpn_bbox: 0.0400 loss_cls: 0.1918 acc: 93.8477 loss_bbox: 0.2315 loss_mask: 0.2455 +2024/10/28 12:25:27 - mmengine - INFO - Epoch(train) [10][1700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:07:50 time: 0.9751 data_time: 0.0382 memory: 6214 grad_norm: 3.3745 loss: 0.6519 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0363 loss_cls: 0.1688 acc: 95.2148 loss_bbox: 0.1989 loss_mask: 0.2250 +2024/10/28 12:26:18 - mmengine - INFO - Epoch(train) [10][1750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:07:18 time: 1.0131 data_time: 0.0460 memory: 6182 grad_norm: 3.3168 loss: 0.7383 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0431 loss_cls: 0.1957 acc: 95.5566 loss_bbox: 0.2246 loss_mask: 0.2513 +2024/10/28 12:27:08 - mmengine - INFO - Epoch(train) [10][1800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:06:45 time: 1.0136 data_time: 0.0527 memory: 6266 grad_norm: 3.4253 loss: 0.6990 loss_rpn_cls: 0.0232 loss_rpn_bbox: 0.0422 loss_cls: 0.1797 acc: 96.8262 loss_bbox: 0.2188 loss_mask: 0.2350 +2024/10/28 12:28:01 - mmengine - INFO - Epoch(train) [10][1850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:06:14 time: 1.0544 data_time: 0.0573 memory: 6147 grad_norm: 3.4825 loss: 0.7501 loss_rpn_cls: 0.0230 loss_rpn_bbox: 0.0436 loss_cls: 0.1983 acc: 93.4570 loss_bbox: 0.2411 loss_mask: 0.2441 +2024/10/28 12:28:51 - mmengine - INFO - Epoch(train) [10][1900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:05:41 time: 0.9919 data_time: 0.0418 memory: 6238 grad_norm: 3.5462 loss: 0.6543 loss_rpn_cls: 0.0192 loss_rpn_bbox: 0.0359 loss_cls: 0.1677 acc: 91.1621 loss_bbox: 0.1983 loss_mask: 0.2332 +2024/10/28 12:29:41 - mmengine - INFO - Epoch(train) [10][1950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:05:08 time: 1.0014 data_time: 0.0450 memory: 6121 grad_norm: 3.4205 loss: 0.6745 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0381 loss_cls: 0.1823 acc: 92.3340 loss_bbox: 0.2054 loss_mask: 0.2313 +2024/10/28 12:30:31 - mmengine - INFO - Epoch(train) [10][2000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:04:35 time: 0.9971 data_time: 0.0460 memory: 6047 grad_norm: 3.3527 loss: 0.6955 loss_rpn_cls: 0.0206 loss_rpn_bbox: 0.0409 loss_cls: 0.1875 acc: 94.8242 loss_bbox: 0.2135 loss_mask: 0.2330 +2024/10/28 12:31:02 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 12:31:23 - mmengine - INFO - Epoch(train) [10][2050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:04:03 time: 1.0533 data_time: 0.0505 memory: 6420 grad_norm: 3.3809 loss: 0.7186 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0399 loss_cls: 0.1927 acc: 90.8691 loss_bbox: 0.2238 loss_mask: 0.2392 +2024/10/28 12:32:15 - mmengine - INFO - Epoch(train) [10][2100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:03:31 time: 1.0321 data_time: 0.0575 memory: 6254 grad_norm: 3.3913 loss: 0.7614 loss_rpn_cls: 0.0262 loss_rpn_bbox: 0.0469 loss_cls: 0.2000 acc: 89.6484 loss_bbox: 0.2422 loss_mask: 0.2462 +2024/10/28 12:33:04 - mmengine - INFO - Epoch(train) [10][2150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:02:58 time: 0.9784 data_time: 0.0454 memory: 6369 grad_norm: 3.2883 loss: 0.7058 loss_rpn_cls: 0.0211 loss_rpn_bbox: 0.0385 loss_cls: 0.1856 acc: 92.9199 loss_bbox: 0.2179 loss_mask: 0.2428 +2024/10/28 12:33:59 - mmengine - INFO - Epoch(train) [10][2200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:02:26 time: 1.0932 data_time: 0.0875 memory: 6243 grad_norm: 3.3979 loss: 0.7255 loss_rpn_cls: 0.0250 loss_rpn_bbox: 0.0454 loss_cls: 0.1828 acc: 95.0684 loss_bbox: 0.2314 loss_mask: 0.2410 +2024/10/28 12:34:51 - mmengine - INFO - Epoch(train) [10][2250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:01:54 time: 1.0446 data_time: 0.0403 memory: 6209 grad_norm: 3.3824 loss: 0.6920 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0366 loss_cls: 0.1824 acc: 91.1621 loss_bbox: 0.2174 loss_mask: 0.2371 +2024/10/28 12:35:37 - mmengine - INFO - Epoch(train) [10][2300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:01:20 time: 0.9258 data_time: 0.0408 memory: 6350 grad_norm: 3.4552 loss: 0.6796 loss_rpn_cls: 0.0199 loss_rpn_bbox: 0.0352 loss_cls: 0.1837 acc: 91.9922 loss_bbox: 0.2089 loss_mask: 0.2319 +2024/10/28 12:36:28 - mmengine - INFO - Epoch(train) [10][2350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:00:47 time: 1.0115 data_time: 0.0486 memory: 6329 grad_norm: 3.5233 loss: 0.7626 loss_rpn_cls: 0.0232 loss_rpn_bbox: 0.0469 loss_cls: 0.2052 acc: 95.2148 loss_bbox: 0.2431 loss_mask: 0.2441 +2024/10/28 12:37:15 - mmengine - INFO - Epoch(train) [10][2400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 4:00:13 time: 0.9545 data_time: 0.0403 memory: 6303 grad_norm: 3.4393 loss: 0.6929 loss_rpn_cls: 0.0198 loss_rpn_bbox: 0.0358 loss_cls: 0.1766 acc: 94.6777 loss_bbox: 0.2198 loss_mask: 0.2408 +2024/10/28 12:38:07 - mmengine - INFO - Epoch(train) [10][2450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:59:41 time: 1.0232 data_time: 0.0419 memory: 6186 grad_norm: 3.3859 loss: 0.7248 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0440 loss_cls: 0.1863 acc: 89.3555 loss_bbox: 0.2256 loss_mask: 0.2463 +2024/10/28 12:38:59 - mmengine - INFO - Epoch(train) [10][2500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:59:08 time: 1.0451 data_time: 0.0422 memory: 6199 grad_norm: 3.6167 loss: 0.6881 loss_rpn_cls: 0.0220 loss_rpn_bbox: 0.0390 loss_cls: 0.1742 acc: 88.8184 loss_bbox: 0.2152 loss_mask: 0.2376 +2024/10/28 12:39:47 - mmengine - INFO - Epoch(train) [10][2550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:58:35 time: 0.9667 data_time: 0.0446 memory: 5919 grad_norm: 3.4233 loss: 0.7155 loss_rpn_cls: 0.0208 loss_rpn_bbox: 0.0408 loss_cls: 0.1879 acc: 92.6758 loss_bbox: 0.2224 loss_mask: 0.2436 +2024/10/28 12:40:39 - mmengine - INFO - Epoch(train) [10][2600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:58:02 time: 1.0440 data_time: 0.0389 memory: 6384 grad_norm: 3.4620 loss: 0.6786 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0359 loss_cls: 0.1779 acc: 96.4844 loss_bbox: 0.2129 loss_mask: 0.2334 +2024/10/28 12:41:29 - mmengine - INFO - Epoch(train) [10][2650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:57:29 time: 0.9862 data_time: 0.0419 memory: 6411 grad_norm: 3.5591 loss: 0.6977 loss_rpn_cls: 0.0193 loss_rpn_bbox: 0.0379 loss_cls: 0.1944 acc: 94.0918 loss_bbox: 0.2154 loss_mask: 0.2307 +2024/10/28 12:42:21 - mmengine - INFO - Epoch(train) [10][2700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:56:56 time: 1.0405 data_time: 0.0480 memory: 6256 grad_norm: 3.4921 loss: 0.8001 loss_rpn_cls: 0.0261 loss_rpn_bbox: 0.0481 loss_cls: 0.2094 acc: 94.8242 loss_bbox: 0.2527 loss_mask: 0.2638 +2024/10/28 12:43:13 - mmengine - INFO - Epoch(train) [10][2750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:56:24 time: 1.0536 data_time: 0.0460 memory: 6221 grad_norm: 3.6156 loss: 0.7210 loss_rpn_cls: 0.0218 loss_rpn_bbox: 0.0420 loss_cls: 0.1920 acc: 90.1367 loss_bbox: 0.2323 loss_mask: 0.2329 +2024/10/28 12:44:05 - mmengine - INFO - Epoch(train) [10][2800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:55:51 time: 1.0230 data_time: 0.0423 memory: 6311 grad_norm: 3.4918 loss: 0.7271 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0392 loss_cls: 0.1849 acc: 91.6992 loss_bbox: 0.2336 loss_mask: 0.2443 +2024/10/28 12:44:57 - mmengine - INFO - Epoch(train) [10][2850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:55:19 time: 1.0553 data_time: 0.0602 memory: 6228 grad_norm: 3.4951 loss: 0.6879 loss_rpn_cls: 0.0205 loss_rpn_bbox: 0.0400 loss_cls: 0.1745 acc: 95.3613 loss_bbox: 0.2119 loss_mask: 0.2410 +2024/10/28 12:45:45 - mmengine - INFO - Epoch(train) [10][2900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:54:45 time: 0.9607 data_time: 0.0390 memory: 6169 grad_norm: 3.4118 loss: 0.6543 loss_rpn_cls: 0.0163 loss_rpn_bbox: 0.0348 loss_cls: 0.1739 acc: 92.0898 loss_bbox: 0.2022 loss_mask: 0.2272 +2024/10/28 12:46:37 - mmengine - INFO - Epoch(train) [10][2950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:54:12 time: 1.0309 data_time: 0.0493 memory: 6307 grad_norm: 3.3855 loss: 0.7762 loss_rpn_cls: 0.0270 loss_rpn_bbox: 0.0451 loss_cls: 0.2064 acc: 95.9473 loss_bbox: 0.2440 loss_mask: 0.2536 +2024/10/28 12:47:26 - mmengine - INFO - Epoch(train) [10][3000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:53:38 time: 0.9732 data_time: 0.0424 memory: 6255 grad_norm: 3.4726 loss: 0.7400 loss_rpn_cls: 0.0235 loss_rpn_bbox: 0.0423 loss_cls: 0.1946 acc: 93.7012 loss_bbox: 0.2332 loss_mask: 0.2464 +2024/10/28 12:47:56 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 12:48:14 - mmengine - INFO - Epoch(train) [10][3050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:53:05 time: 0.9770 data_time: 0.0451 memory: 6325 grad_norm: 3.3729 loss: 0.7374 loss_rpn_cls: 0.0223 loss_rpn_bbox: 0.0425 loss_cls: 0.1907 acc: 96.3379 loss_bbox: 0.2308 loss_mask: 0.2511 +2024/10/28 12:49:04 - mmengine - INFO - Epoch(train) [10][3100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:52:31 time: 0.9988 data_time: 0.0531 memory: 6260 grad_norm: 3.3178 loss: 0.7338 loss_rpn_cls: 0.0220 loss_rpn_bbox: 0.0431 loss_cls: 0.1905 acc: 89.6484 loss_bbox: 0.2386 loss_mask: 0.2395 +2024/10/28 12:49:55 - mmengine - INFO - Epoch(train) [10][3150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:51:58 time: 1.0119 data_time: 0.0864 memory: 6133 grad_norm: 3.5422 loss: 0.6400 loss_rpn_cls: 0.0193 loss_rpn_bbox: 0.0327 loss_cls: 0.1650 acc: 95.0195 loss_bbox: 0.1990 loss_mask: 0.2240 +2024/10/28 12:50:44 - mmengine - INFO - Epoch(train) [10][3200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:51:24 time: 0.9808 data_time: 0.0408 memory: 6128 grad_norm: 3.4042 loss: 0.6687 loss_rpn_cls: 0.0209 loss_rpn_bbox: 0.0371 loss_cls: 0.1777 acc: 91.3086 loss_bbox: 0.2049 loss_mask: 0.2281 +2024/10/28 12:51:34 - mmengine - INFO - Epoch(train) [10][3250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:50:51 time: 0.9906 data_time: 0.0445 memory: 6207 grad_norm: 3.3959 loss: 0.6989 loss_rpn_cls: 0.0187 loss_rpn_bbox: 0.0415 loss_cls: 0.1767 acc: 93.9941 loss_bbox: 0.2235 loss_mask: 0.2385 +2024/10/28 12:52:25 - mmengine - INFO - Epoch(train) [10][3300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:50:18 time: 1.0275 data_time: 0.0468 memory: 6260 grad_norm: 3.5669 loss: 0.7514 loss_rpn_cls: 0.0250 loss_rpn_bbox: 0.0443 loss_cls: 0.1903 acc: 92.9688 loss_bbox: 0.2395 loss_mask: 0.2522 +2024/10/28 12:53:14 - mmengine - INFO - Epoch(train) [10][3350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:49:44 time: 0.9736 data_time: 0.0480 memory: 6288 grad_norm: 3.6547 loss: 0.7186 loss_rpn_cls: 0.0219 loss_rpn_bbox: 0.0385 loss_cls: 0.1908 acc: 92.0410 loss_bbox: 0.2296 loss_mask: 0.2378 +2024/10/28 12:54:07 - mmengine - INFO - Epoch(train) [10][3400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:49:12 time: 1.0739 data_time: 0.0481 memory: 6145 grad_norm: 3.4035 loss: 0.7019 loss_rpn_cls: 0.0264 loss_rpn_bbox: 0.0417 loss_cls: 0.1782 acc: 92.8711 loss_bbox: 0.2165 loss_mask: 0.2390 +2024/10/28 12:54:55 - mmengine - INFO - Epoch(train) [10][3450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:48:37 time: 0.9498 data_time: 0.0443 memory: 6195 grad_norm: 3.3780 loss: 0.6823 loss_rpn_cls: 0.0216 loss_rpn_bbox: 0.0364 loss_cls: 0.1800 acc: 90.6250 loss_bbox: 0.2087 loss_mask: 0.2356 +2024/10/28 12:55:44 - mmengine - INFO - Epoch(train) [10][3500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:48:03 time: 0.9731 data_time: 0.0499 memory: 6146 grad_norm: 3.4526 loss: 0.7214 loss_rpn_cls: 0.0216 loss_rpn_bbox: 0.0425 loss_cls: 0.1880 acc: 90.0391 loss_bbox: 0.2286 loss_mask: 0.2407 +2024/10/28 12:56:32 - mmengine - INFO - Epoch(train) [10][3550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:47:30 time: 0.9746 data_time: 0.0471 memory: 6270 grad_norm: 3.4782 loss: 0.7538 loss_rpn_cls: 0.0256 loss_rpn_bbox: 0.0413 loss_cls: 0.2021 acc: 93.1152 loss_bbox: 0.2382 loss_mask: 0.2466 +2024/10/28 12:57:23 - mmengine - INFO - Epoch(train) [10][3600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:46:56 time: 1.0228 data_time: 0.0419 memory: 6150 grad_norm: 3.4319 loss: 0.7131 loss_rpn_cls: 0.0243 loss_rpn_bbox: 0.0398 loss_cls: 0.1802 acc: 90.5273 loss_bbox: 0.2276 loss_mask: 0.2411 +2024/10/28 12:58:15 - mmengine - INFO - Epoch(train) [10][3650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:46:23 time: 1.0285 data_time: 0.0467 memory: 6326 grad_norm: 3.4200 loss: 0.6951 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0411 loss_cls: 0.1853 acc: 94.9219 loss_bbox: 0.2125 loss_mask: 0.2324 +2024/10/28 12:59:05 - mmengine - INFO - Epoch(train) [10][3700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:45:49 time: 0.9963 data_time: 0.0550 memory: 6233 grad_norm: 3.5045 loss: 0.7181 loss_rpn_cls: 0.0245 loss_rpn_bbox: 0.0381 loss_cls: 0.1906 acc: 93.3105 loss_bbox: 0.2288 loss_mask: 0.2361 +2024/10/28 12:59:59 - mmengine - INFO - Epoch(train) [10][3750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:45:17 time: 1.0838 data_time: 0.0537 memory: 6282 grad_norm: 3.5718 loss: 0.7692 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0445 loss_cls: 0.2024 acc: 88.7695 loss_bbox: 0.2451 loss_mask: 0.2527 +2024/10/28 13:00:48 - mmengine - INFO - Epoch(train) [10][3800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:44:43 time: 0.9730 data_time: 0.0431 memory: 6239 grad_norm: 3.6244 loss: 0.6833 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0388 loss_cls: 0.1773 acc: 96.3379 loss_bbox: 0.2046 loss_mask: 0.2390 +2024/10/28 13:01:37 - mmengine - INFO - Epoch(train) [10][3850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:44:09 time: 0.9887 data_time: 0.0493 memory: 6268 grad_norm: 3.4225 loss: 0.6576 loss_rpn_cls: 0.0163 loss_rpn_bbox: 0.0325 loss_cls: 0.1724 acc: 95.6543 loss_bbox: 0.2130 loss_mask: 0.2234 +2024/10/28 13:02:25 - mmengine - INFO - Epoch(train) [10][3900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:43:35 time: 0.9632 data_time: 0.0474 memory: 6131 grad_norm: 3.2980 loss: 0.7250 loss_rpn_cls: 0.0240 loss_rpn_bbox: 0.0412 loss_cls: 0.1949 acc: 94.9219 loss_bbox: 0.2305 loss_mask: 0.2343 +2024/10/28 13:03:15 - mmengine - INFO - Epoch(train) [10][3950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:43:01 time: 0.9892 data_time: 0.0603 memory: 6308 grad_norm: 3.5252 loss: 0.7349 loss_rpn_cls: 0.0254 loss_rpn_bbox: 0.0406 loss_cls: 0.1972 acc: 92.9688 loss_bbox: 0.2323 loss_mask: 0.2395 +2024/10/28 13:04:04 - mmengine - INFO - Epoch(train) [10][4000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:42:27 time: 0.9781 data_time: 0.0539 memory: 6317 grad_norm: 3.4220 loss: 0.7548 loss_rpn_cls: 0.0225 loss_rpn_bbox: 0.0413 loss_cls: 0.2043 acc: 94.0430 loss_bbox: 0.2381 loss_mask: 0.2487 +2024/10/28 13:04:38 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 13:04:59 - mmengine - INFO - Epoch(train) [10][4050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:41:54 time: 1.1018 data_time: 0.1278 memory: 6266 grad_norm: 3.4375 loss: 0.7134 loss_rpn_cls: 0.0207 loss_rpn_bbox: 0.0412 loss_cls: 0.1868 acc: 94.4824 loss_bbox: 0.2285 loss_mask: 0.2361 +2024/10/28 13:05:47 - mmengine - INFO - Epoch(train) [10][4100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:41:20 time: 0.9751 data_time: 0.0560 memory: 6420 grad_norm: 3.3389 loss: 0.7769 loss_rpn_cls: 0.0241 loss_rpn_bbox: 0.0425 loss_cls: 0.2106 acc: 91.0156 loss_bbox: 0.2459 loss_mask: 0.2538 +2024/10/28 13:06:38 - mmengine - INFO - Epoch(train) [10][4150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:40:47 time: 1.0152 data_time: 0.0523 memory: 6296 grad_norm: 3.5293 loss: 0.7371 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0426 loss_cls: 0.1951 acc: 91.0645 loss_bbox: 0.2318 loss_mask: 0.2450 +2024/10/28 13:07:27 - mmengine - INFO - Epoch(train) [10][4200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:40:12 time: 0.9856 data_time: 0.0527 memory: 6078 grad_norm: 3.4218 loss: 0.7401 loss_rpn_cls: 0.0207 loss_rpn_bbox: 0.0395 loss_cls: 0.1957 acc: 93.4082 loss_bbox: 0.2315 loss_mask: 0.2529 +2024/10/28 13:08:21 - mmengine - INFO - Epoch(train) [10][4250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:39:39 time: 1.0651 data_time: 0.0575 memory: 6225 grad_norm: 3.5167 loss: 0.7349 loss_rpn_cls: 0.0220 loss_rpn_bbox: 0.0432 loss_cls: 0.1903 acc: 92.9688 loss_bbox: 0.2331 loss_mask: 0.2464 +2024/10/28 13:09:09 - mmengine - INFO - Epoch(train) [10][4300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:39:05 time: 0.9747 data_time: 0.0406 memory: 6354 grad_norm: 3.4188 loss: 0.6733 loss_rpn_cls: 0.0210 loss_rpn_bbox: 0.0374 loss_cls: 0.1757 acc: 94.7266 loss_bbox: 0.2088 loss_mask: 0.2304 +2024/10/28 13:10:01 - mmengine - INFO - Epoch(train) [10][4350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:38:32 time: 1.0274 data_time: 0.0453 memory: 6209 grad_norm: 3.3305 loss: 0.6989 loss_rpn_cls: 0.0221 loss_rpn_bbox: 0.0402 loss_cls: 0.1854 acc: 97.2168 loss_bbox: 0.2172 loss_mask: 0.2339 +2024/10/28 13:10:53 - mmengine - INFO - Epoch(train) [10][4400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:37:58 time: 1.0465 data_time: 0.0446 memory: 6245 grad_norm: 3.4594 loss: 0.6975 loss_rpn_cls: 0.0241 loss_rpn_bbox: 0.0371 loss_cls: 0.1771 acc: 96.7285 loss_bbox: 0.2139 loss_mask: 0.2453 +2024/10/28 13:11:44 - mmengine - INFO - Epoch(train) [10][4450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:37:24 time: 1.0184 data_time: 0.0447 memory: 6275 grad_norm: 3.5962 loss: 0.7249 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0410 loss_cls: 0.1931 acc: 94.6777 loss_bbox: 0.2288 loss_mask: 0.2383 +2024/10/28 13:12:31 - mmengine - INFO - Epoch(train) [10][4500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:36:50 time: 0.9469 data_time: 0.0529 memory: 6315 grad_norm: 3.5792 loss: 0.7515 loss_rpn_cls: 0.0234 loss_rpn_bbox: 0.0406 loss_cls: 0.2037 acc: 91.3086 loss_bbox: 0.2450 loss_mask: 0.2388 +2024/10/28 13:13:19 - mmengine - INFO - Epoch(train) [10][4550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:36:15 time: 0.9584 data_time: 0.0481 memory: 6301 grad_norm: 3.4413 loss: 0.6849 loss_rpn_cls: 0.0232 loss_rpn_bbox: 0.0384 loss_cls: 0.1703 acc: 96.4844 loss_bbox: 0.2116 loss_mask: 0.2414 +2024/10/28 13:14:12 - mmengine - INFO - Epoch(train) [10][4600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:35:42 time: 1.0555 data_time: 0.0508 memory: 6160 grad_norm: 3.4456 loss: 0.6920 loss_rpn_cls: 0.0222 loss_rpn_bbox: 0.0398 loss_cls: 0.1770 acc: 98.2910 loss_bbox: 0.2176 loss_mask: 0.2354 +2024/10/28 13:15:01 - mmengine - INFO - Epoch(train) [10][4650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:35:08 time: 0.9729 data_time: 0.0478 memory: 6272 grad_norm: 3.3982 loss: 0.7260 loss_rpn_cls: 0.0210 loss_rpn_bbox: 0.0405 loss_cls: 0.1859 acc: 90.7715 loss_bbox: 0.2341 loss_mask: 0.2445 +2024/10/28 13:15:51 - mmengine - INFO - Epoch(train) [10][4700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:34:33 time: 0.9976 data_time: 0.0504 memory: 6167 grad_norm: 3.4851 loss: 0.7643 loss_rpn_cls: 0.0283 loss_rpn_bbox: 0.0457 loss_cls: 0.2030 acc: 92.6758 loss_bbox: 0.2411 loss_mask: 0.2462 +2024/10/28 13:16:46 - mmengine - INFO - Epoch(train) [10][4750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:34:01 time: 1.1058 data_time: 0.0602 memory: 6311 grad_norm: 3.4860 loss: 0.7516 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0426 loss_cls: 0.1976 acc: 92.0410 loss_bbox: 0.2412 loss_mask: 0.2451 +2024/10/28 13:17:39 - mmengine - INFO - Epoch(train) [10][4800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:33:27 time: 1.0605 data_time: 0.0516 memory: 6225 grad_norm: 3.5596 loss: 0.7275 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0395 loss_cls: 0.1944 acc: 92.0898 loss_bbox: 0.2281 loss_mask: 0.2426 +2024/10/28 13:18:31 - mmengine - INFO - Epoch(train) [10][4850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:32:53 time: 1.0381 data_time: 0.0511 memory: 6410 grad_norm: 3.3700 loss: 0.6726 loss_rpn_cls: 0.0218 loss_rpn_bbox: 0.0423 loss_cls: 0.1786 acc: 93.5547 loss_bbox: 0.2107 loss_mask: 0.2192 +2024/10/28 13:19:20 - mmengine - INFO - Epoch(train) [10][4900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:32:19 time: 0.9891 data_time: 0.0481 memory: 6151 grad_norm: 3.4062 loss: 0.6952 loss_rpn_cls: 0.0190 loss_rpn_bbox: 0.0374 loss_cls: 0.1854 acc: 93.6523 loss_bbox: 0.2111 loss_mask: 0.2424 +2024/10/28 13:20:12 - mmengine - INFO - Epoch(train) [10][4950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:31:45 time: 1.0297 data_time: 0.0560 memory: 6301 grad_norm: 3.4005 loss: 0.7391 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0426 loss_cls: 0.2023 acc: 93.1641 loss_bbox: 0.2387 loss_mask: 0.2319 +2024/10/28 13:21:05 - mmengine - INFO - Epoch(train) [10][5000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:31:12 time: 1.0715 data_time: 0.0584 memory: 6331 grad_norm: 3.3796 loss: 0.7189 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0421 loss_cls: 0.1898 acc: 93.0176 loss_bbox: 0.2281 loss_mask: 0.2359 +2024/10/28 13:21:38 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 13:21:57 - mmengine - INFO - Epoch(train) [10][5050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:30:38 time: 1.0270 data_time: 0.0601 memory: 6265 grad_norm: 3.5720 loss: 0.7064 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0419 loss_cls: 0.1780 acc: 96.1426 loss_bbox: 0.2270 loss_mask: 0.2356 +2024/10/28 13:22:46 - mmengine - INFO - Epoch(train) [10][5100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:30:03 time: 0.9801 data_time: 0.0576 memory: 6235 grad_norm: 3.6291 loss: 0.7652 loss_rpn_cls: 0.0250 loss_rpn_bbox: 0.0454 loss_cls: 0.2048 acc: 86.6211 loss_bbox: 0.2371 loss_mask: 0.2529 +2024/10/28 13:23:33 - mmengine - INFO - Epoch(train) [10][5150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:29:28 time: 0.9455 data_time: 0.0505 memory: 6276 grad_norm: 3.3478 loss: 0.7105 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0380 loss_cls: 0.1807 acc: 93.3105 loss_bbox: 0.2264 loss_mask: 0.2425 +2024/10/28 13:24:23 - mmengine - INFO - Epoch(train) [10][5200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:28:54 time: 0.9961 data_time: 0.0660 memory: 6403 grad_norm: 3.4188 loss: 0.7891 loss_rpn_cls: 0.0240 loss_rpn_bbox: 0.0496 loss_cls: 0.2050 acc: 95.9473 loss_bbox: 0.2549 loss_mask: 0.2557 +2024/10/28 13:25:12 - mmengine - INFO - Epoch(train) [10][5250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:28:20 time: 0.9915 data_time: 0.0586 memory: 6176 grad_norm: 3.3724 loss: 0.7204 loss_rpn_cls: 0.0212 loss_rpn_bbox: 0.0399 loss_cls: 0.1871 acc: 97.9492 loss_bbox: 0.2355 loss_mask: 0.2367 +2024/10/28 13:26:05 - mmengine - INFO - Epoch(train) [10][5300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:27:46 time: 1.0416 data_time: 0.0552 memory: 6197 grad_norm: 3.4791 loss: 0.7507 loss_rpn_cls: 0.0256 loss_rpn_bbox: 0.0431 loss_cls: 0.2002 acc: 92.4316 loss_bbox: 0.2389 loss_mask: 0.2429 +2024/10/28 13:26:54 - mmengine - INFO - Epoch(train) [10][5350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:27:11 time: 0.9787 data_time: 0.0693 memory: 6366 grad_norm: 3.4029 loss: 0.7011 loss_rpn_cls: 0.0183 loss_rpn_bbox: 0.0366 loss_cls: 0.1893 acc: 93.9941 loss_bbox: 0.2195 loss_mask: 0.2374 +2024/10/28 13:27:41 - mmengine - INFO - Epoch(train) [10][5400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:26:36 time: 0.9589 data_time: 0.0537 memory: 6420 grad_norm: 3.4398 loss: 0.7219 loss_rpn_cls: 0.0251 loss_rpn_bbox: 0.0392 loss_cls: 0.1923 acc: 88.2812 loss_bbox: 0.2260 loss_mask: 0.2393 +2024/10/28 13:28:33 - mmengine - INFO - Epoch(train) [10][5450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:26:02 time: 1.0400 data_time: 0.0520 memory: 6299 grad_norm: 3.4086 loss: 0.7172 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0389 loss_cls: 0.1814 acc: 94.6777 loss_bbox: 0.2292 loss_mask: 0.2449 +2024/10/28 13:29:25 - mmengine - INFO - Epoch(train) [10][5500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:25:28 time: 1.0267 data_time: 0.0539 memory: 6275 grad_norm: 3.5345 loss: 0.7375 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0412 loss_cls: 0.1973 acc: 92.9688 loss_bbox: 0.2356 loss_mask: 0.2394 +2024/10/28 13:30:17 - mmengine - INFO - Epoch(train) [10][5550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:24:54 time: 1.0454 data_time: 0.0548 memory: 6197 grad_norm: 3.4606 loss: 0.7543 loss_rpn_cls: 0.0235 loss_rpn_bbox: 0.0446 loss_cls: 0.2018 acc: 95.8496 loss_bbox: 0.2415 loss_mask: 0.2428 +2024/10/28 13:31:07 - mmengine - INFO - Epoch(train) [10][5600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:24:20 time: 1.0050 data_time: 0.0457 memory: 6118 grad_norm: 3.7255 loss: 0.6959 loss_rpn_cls: 0.0234 loss_rpn_bbox: 0.0390 loss_cls: 0.1822 acc: 93.6523 loss_bbox: 0.2182 loss_mask: 0.2332 +2024/10/28 13:31:57 - mmengine - INFO - Epoch(train) [10][5650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:23:45 time: 0.9885 data_time: 0.0497 memory: 6408 grad_norm: 3.3346 loss: 0.7120 loss_rpn_cls: 0.0205 loss_rpn_bbox: 0.0410 loss_cls: 0.1914 acc: 95.1172 loss_bbox: 0.2188 loss_mask: 0.2404 +2024/10/28 13:32:45 - mmengine - INFO - Epoch(train) [10][5700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:23:10 time: 0.9633 data_time: 0.0485 memory: 6142 grad_norm: 3.3298 loss: 0.7061 loss_rpn_cls: 0.0224 loss_rpn_bbox: 0.0373 loss_cls: 0.1770 acc: 93.7500 loss_bbox: 0.2210 loss_mask: 0.2484 +2024/10/28 13:33:30 - mmengine - INFO - Epoch(train) [10][5750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:22:34 time: 0.9081 data_time: 0.0461 memory: 6208 grad_norm: 3.5695 loss: 0.6868 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0346 loss_cls: 0.1884 acc: 96.9727 loss_bbox: 0.2110 loss_mask: 0.2333 +2024/10/28 13:34:22 - mmengine - INFO - Epoch(train) [10][5800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:22:00 time: 1.0339 data_time: 0.0488 memory: 6256 grad_norm: 3.6318 loss: 0.7647 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0436 loss_cls: 0.2107 acc: 93.0664 loss_bbox: 0.2419 loss_mask: 0.2457 +2024/10/28 13:35:11 - mmengine - INFO - Epoch(train) [10][5850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:21:25 time: 0.9872 data_time: 0.0511 memory: 6259 grad_norm: 3.5766 loss: 0.7455 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0434 loss_cls: 0.2009 acc: 89.9902 loss_bbox: 0.2385 loss_mask: 0.2387 +2024/10/28 13:36:00 - mmengine - INFO - Epoch(train) [10][5900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:20:50 time: 0.9665 data_time: 0.0509 memory: 6256 grad_norm: 3.3223 loss: 0.7697 loss_rpn_cls: 0.0259 loss_rpn_bbox: 0.0437 loss_cls: 0.2039 acc: 94.1406 loss_bbox: 0.2403 loss_mask: 0.2558 +2024/10/28 13:36:51 - mmengine - INFO - Epoch(train) [10][5950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:20:16 time: 1.0207 data_time: 0.0496 memory: 6419 grad_norm: 3.7760 loss: 0.7930 loss_rpn_cls: 0.0248 loss_rpn_bbox: 0.0451 loss_cls: 0.2162 acc: 89.5508 loss_bbox: 0.2521 loss_mask: 0.2548 +2024/10/28 13:37:42 - mmengine - INFO - Epoch(train) [10][6000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:19:42 time: 1.0233 data_time: 0.0543 memory: 6308 grad_norm: 3.3710 loss: 0.7296 loss_rpn_cls: 0.0236 loss_rpn_bbox: 0.0418 loss_cls: 0.2003 acc: 91.7969 loss_bbox: 0.2270 loss_mask: 0.2368 +2024/10/28 13:38:09 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 13:38:28 - mmengine - INFO - Epoch(train) [10][6050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:19:06 time: 0.9296 data_time: 0.0441 memory: 6183 grad_norm: 3.4727 loss: 0.6797 loss_rpn_cls: 0.0222 loss_rpn_bbox: 0.0360 loss_cls: 0.1762 acc: 92.1387 loss_bbox: 0.2128 loss_mask: 0.2326 +2024/10/28 13:39:16 - mmengine - INFO - Epoch(train) [10][6100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:18:31 time: 0.9608 data_time: 0.0453 memory: 6278 grad_norm: 3.4945 loss: 0.7018 loss_rpn_cls: 0.0221 loss_rpn_bbox: 0.0427 loss_cls: 0.1822 acc: 92.9199 loss_bbox: 0.2138 loss_mask: 0.2409 +2024/10/28 13:40:06 - mmengine - INFO - Epoch(train) [10][6150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:17:56 time: 0.9884 data_time: 0.0479 memory: 6060 grad_norm: 3.3447 loss: 0.6833 loss_rpn_cls: 0.0182 loss_rpn_bbox: 0.0358 loss_cls: 0.1841 acc: 92.6758 loss_bbox: 0.2149 loss_mask: 0.2304 +2024/10/28 13:40:55 - mmengine - INFO - Epoch(train) [10][6200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:17:21 time: 0.9755 data_time: 0.0772 memory: 6217 grad_norm: 3.4872 loss: 0.6870 loss_rpn_cls: 0.0213 loss_rpn_bbox: 0.0398 loss_cls: 0.1776 acc: 95.9961 loss_bbox: 0.2127 loss_mask: 0.2355 +2024/10/28 13:41:45 - mmengine - INFO - Epoch(train) [10][6250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:16:46 time: 0.9982 data_time: 0.0453 memory: 6286 grad_norm: 3.4186 loss: 0.7342 loss_rpn_cls: 0.0245 loss_rpn_bbox: 0.0408 loss_cls: 0.1918 acc: 92.5781 loss_bbox: 0.2317 loss_mask: 0.2455 +2024/10/28 13:42:35 - mmengine - INFO - Epoch(train) [10][6300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:16:12 time: 1.0138 data_time: 0.0484 memory: 6249 grad_norm: 3.5528 loss: 0.7206 loss_rpn_cls: 0.0242 loss_rpn_bbox: 0.0439 loss_cls: 0.1862 acc: 94.1406 loss_bbox: 0.2279 loss_mask: 0.2385 +2024/10/28 13:43:24 - mmengine - INFO - Epoch(train) [10][6350/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:15:37 time: 0.9730 data_time: 0.0449 memory: 5979 grad_norm: 3.4917 loss: 0.6519 loss_rpn_cls: 0.0174 loss_rpn_bbox: 0.0322 loss_cls: 0.1699 acc: 94.6777 loss_bbox: 0.1965 loss_mask: 0.2360 +2024/10/28 13:44:15 - mmengine - INFO - Epoch(train) [10][6400/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:15:02 time: 1.0276 data_time: 0.0464 memory: 6146 grad_norm: 3.3814 loss: 0.7155 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0426 loss_cls: 0.1845 acc: 93.7012 loss_bbox: 0.2214 loss_mask: 0.2442 +2024/10/28 13:45:04 - mmengine - INFO - Epoch(train) [10][6450/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:14:27 time: 0.9675 data_time: 0.0392 memory: 6319 grad_norm: 3.4632 loss: 0.6953 loss_rpn_cls: 0.0200 loss_rpn_bbox: 0.0396 loss_cls: 0.1845 acc: 93.9941 loss_bbox: 0.2176 loss_mask: 0.2335 +2024/10/28 13:45:55 - mmengine - INFO - Epoch(train) [10][6500/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:13:52 time: 1.0347 data_time: 0.1015 memory: 6097 grad_norm: 3.6666 loss: 0.6804 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0341 loss_cls: 0.1755 acc: 93.6523 loss_bbox: 0.2088 loss_mask: 0.2391 +2024/10/28 13:46:48 - mmengine - INFO - Epoch(train) [10][6550/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:13:18 time: 1.0439 data_time: 0.0497 memory: 6352 grad_norm: 3.4610 loss: 0.7198 loss_rpn_cls: 0.0233 loss_rpn_bbox: 0.0438 loss_cls: 0.1827 acc: 96.5332 loss_bbox: 0.2298 loss_mask: 0.2403 +2024/10/28 13:47:36 - mmengine - INFO - Epoch(train) [10][6600/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:12:43 time: 0.9628 data_time: 0.0471 memory: 6313 grad_norm: 3.4792 loss: 0.7183 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0405 loss_cls: 0.1831 acc: 89.9902 loss_bbox: 0.2402 loss_mask: 0.2359 +2024/10/28 13:48:27 - mmengine - INFO - Epoch(train) [10][6650/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:12:08 time: 1.0266 data_time: 0.0478 memory: 6348 grad_norm: 3.5227 loss: 0.6914 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0395 loss_cls: 0.1758 acc: 95.2148 loss_bbox: 0.2199 loss_mask: 0.2378 +2024/10/28 13:49:14 - mmengine - INFO - Epoch(train) [10][6700/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:11:32 time: 0.9422 data_time: 0.0529 memory: 6230 grad_norm: 3.4718 loss: 0.7460 loss_rpn_cls: 0.0263 loss_rpn_bbox: 0.0400 loss_cls: 0.2015 acc: 88.7695 loss_bbox: 0.2350 loss_mask: 0.2431 +2024/10/28 13:50:05 - mmengine - INFO - Epoch(train) [10][6750/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:10:58 time: 1.0204 data_time: 0.0549 memory: 6392 grad_norm: 3.8052 loss: 0.7077 loss_rpn_cls: 0.0224 loss_rpn_bbox: 0.0396 loss_cls: 0.1771 acc: 96.0449 loss_bbox: 0.2217 loss_mask: 0.2468 +2024/10/28 13:50:59 - mmengine - INFO - Epoch(train) [10][6800/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:10:23 time: 1.0752 data_time: 0.0588 memory: 6191 grad_norm: 3.4503 loss: 0.7410 loss_rpn_cls: 0.0225 loss_rpn_bbox: 0.0454 loss_cls: 0.1980 acc: 98.1934 loss_bbox: 0.2351 loss_mask: 0.2400 +2024/10/28 13:51:48 - mmengine - INFO - Epoch(train) [10][6850/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:09:48 time: 0.9734 data_time: 0.0443 memory: 6254 grad_norm: 3.4599 loss: 0.7351 loss_rpn_cls: 0.0222 loss_rpn_bbox: 0.0401 loss_cls: 0.1905 acc: 92.6758 loss_bbox: 0.2304 loss_mask: 0.2519 +2024/10/28 13:52:39 - mmengine - INFO - Epoch(train) [10][6900/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:09:13 time: 1.0315 data_time: 0.0453 memory: 6237 grad_norm: 3.4861 loss: 0.6823 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0364 loss_cls: 0.1805 acc: 92.8223 loss_bbox: 0.2115 loss_mask: 0.2355 +2024/10/28 13:53:32 - mmengine - INFO - Epoch(train) [10][6950/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:08:39 time: 1.0525 data_time: 0.0511 memory: 6319 grad_norm: 3.5153 loss: 0.7888 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0501 loss_cls: 0.2131 acc: 88.7695 loss_bbox: 0.2493 loss_mask: 0.2491 +2024/10/28 13:54:23 - mmengine - INFO - Epoch(train) [10][7000/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:08:04 time: 1.0247 data_time: 0.0436 memory: 6224 grad_norm: 3.5308 loss: 0.7532 loss_rpn_cls: 0.0237 loss_rpn_bbox: 0.0430 loss_cls: 0.2050 acc: 95.2637 loss_bbox: 0.2340 loss_mask: 0.2475 +2024/10/28 13:54:53 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 13:55:11 - mmengine - INFO - Epoch(train) [10][7050/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:07:28 time: 0.9563 data_time: 0.0454 memory: 6121 grad_norm: 3.5984 loss: 0.7755 loss_rpn_cls: 0.0262 loss_rpn_bbox: 0.0430 loss_cls: 0.2124 acc: 89.1113 loss_bbox: 0.2478 loss_mask: 0.2462 +2024/10/28 13:56:03 - mmengine - INFO - Epoch(train) [10][7100/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:06:54 time: 1.0451 data_time: 0.0465 memory: 6297 grad_norm: 3.5713 loss: 0.7676 loss_rpn_cls: 0.0272 loss_rpn_bbox: 0.0457 loss_cls: 0.2066 acc: 95.4102 loss_bbox: 0.2444 loss_mask: 0.2436 +2024/10/28 13:56:58 - mmengine - INFO - Epoch(train) [10][7150/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:06:20 time: 1.0995 data_time: 0.0903 memory: 6256 grad_norm: 3.5023 loss: 0.6853 loss_rpn_cls: 0.0219 loss_rpn_bbox: 0.0388 loss_cls: 0.1680 acc: 94.7266 loss_bbox: 0.2166 loss_mask: 0.2400 +2024/10/28 13:57:48 - mmengine - INFO - Epoch(train) [10][7200/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:05:44 time: 0.9881 data_time: 0.0503 memory: 6421 grad_norm: 3.4106 loss: 0.7749 loss_rpn_cls: 0.0258 loss_rpn_bbox: 0.0451 loss_cls: 0.2054 acc: 93.1641 loss_bbox: 0.2480 loss_mask: 0.2507 +2024/10/28 13:58:41 - mmengine - INFO - Epoch(train) [10][7250/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:05:10 time: 1.0713 data_time: 0.0495 memory: 6286 grad_norm: 3.4407 loss: 0.7576 loss_rpn_cls: 0.0232 loss_rpn_bbox: 0.0453 loss_cls: 0.2013 acc: 90.3320 loss_bbox: 0.2415 loss_mask: 0.2463 +2024/10/28 13:59:31 - mmengine - INFO - Epoch(train) [10][7300/7330] base_lr: 1.0000e-04 lr: 1.0000e-04 eta: 3:04:35 time: 0.9997 data_time: 0.0487 memory: 6328 grad_norm: 3.4882 loss: 0.7503 loss_rpn_cls: 0.0244 loss_rpn_bbox: 0.0417 loss_cls: 0.2048 acc: 89.6973 loss_bbox: 0.2323 loss_mask: 0.2473 +2024/10/28 14:00:10 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 14:00:10 - mmengine - INFO - Saving checkpoint at 10 epochs +2024/10/28 14:00:24 - mmengine - INFO - Epoch(val) [10][ 50/1250] eta: 0:03:06 time: 0.1557 data_time: 0.0065 memory: 6076 +2024/10/28 14:00:32 - mmengine - INFO - Epoch(val) [10][ 100/1250] eta: 0:03:03 time: 0.1633 data_time: 0.0053 memory: 1114 +2024/10/28 14:00:40 - mmengine - INFO - Epoch(val) [10][ 150/1250] eta: 0:02:54 time: 0.1565 data_time: 0.0056 memory: 1108 +2024/10/28 14:00:48 - mmengine - INFO - Epoch(val) [10][ 200/1250] eta: 0:02:48 time: 0.1683 data_time: 0.0081 memory: 1114 +2024/10/28 14:00:57 - mmengine - INFO - Epoch(val) [10][ 250/1250] eta: 0:02:41 time: 0.1631 data_time: 0.0057 memory: 1221 +2024/10/28 14:01:05 - mmengine - INFO - Epoch(val) [10][ 300/1250] eta: 0:02:33 time: 0.1613 data_time: 0.0067 memory: 1114 +2024/10/28 14:01:12 - mmengine - INFO - Epoch(val) [10][ 350/1250] eta: 0:02:24 time: 0.1538 data_time: 0.0053 memory: 1105 +2024/10/28 14:01:20 - mmengine - INFO - Epoch(val) [10][ 400/1250] eta: 0:02:15 time: 0.1547 data_time: 0.0049 memory: 1114 +2024/10/28 14:01:28 - mmengine - INFO - Epoch(val) [10][ 450/1250] eta: 0:02:07 time: 0.1623 data_time: 0.0048 memory: 1114 +2024/10/28 14:01:36 - mmengine - INFO - Epoch(val) [10][ 500/1250] eta: 0:01:59 time: 0.1602 data_time: 0.0060 memory: 1107 +2024/10/28 14:01:44 - mmengine - INFO - Epoch(val) [10][ 550/1250] eta: 0:01:51 time: 0.1608 data_time: 0.0054 memory: 1135 +2024/10/28 14:01:53 - mmengine - INFO - Epoch(val) [10][ 600/1250] eta: 0:01:44 time: 0.1676 data_time: 0.0073 memory: 1114 +2024/10/28 14:02:01 - mmengine - INFO - Epoch(val) [10][ 650/1250] eta: 0:01:36 time: 0.1625 data_time: 0.0058 memory: 1160 +2024/10/28 14:02:09 - mmengine - INFO - Epoch(val) [10][ 700/1250] eta: 0:01:28 time: 0.1704 data_time: 0.0061 memory: 1082 +2024/10/28 14:02:17 - mmengine - INFO - Epoch(val) [10][ 750/1250] eta: 0:01:20 time: 0.1570 data_time: 0.0072 memory: 1082 +2024/10/28 14:02:25 - mmengine - INFO - Epoch(val) [10][ 800/1250] eta: 0:01:12 time: 0.1566 data_time: 0.0066 memory: 1122 +2024/10/28 14:02:33 - mmengine - INFO - Epoch(val) [10][ 850/1250] eta: 0:01:04 time: 0.1588 data_time: 0.0058 memory: 1114 +2024/10/28 14:02:41 - mmengine - INFO - Epoch(val) [10][ 900/1250] eta: 0:00:56 time: 0.1582 data_time: 0.0048 memory: 1082 +2024/10/28 14:02:49 - mmengine - INFO - Epoch(val) [10][ 950/1250] eta: 0:00:48 time: 0.1681 data_time: 0.0070 memory: 1219 +2024/10/28 14:02:57 - mmengine - INFO - Epoch(val) [10][1000/1250] eta: 0:00:40 time: 0.1541 data_time: 0.0056 memory: 1034 +2024/10/28 14:03:05 - mmengine - INFO - Epoch(val) [10][1050/1250] eta: 0:00:32 time: 0.1687 data_time: 0.0065 memory: 1114 +2024/10/28 14:03:13 - mmengine - INFO - Epoch(val) [10][1100/1250] eta: 0:00:24 time: 0.1543 data_time: 0.0040 memory: 1102 +2024/10/28 14:03:21 - mmengine - INFO - Epoch(val) [10][1150/1250] eta: 0:00:16 time: 0.1663 data_time: 0.0059 memory: 1114 +2024/10/28 14:03:29 - mmengine - INFO - Epoch(val) [10][1200/1250] eta: 0:00:08 time: 0.1573 data_time: 0.0057 memory: 1114 +2024/10/28 14:03:37 - mmengine - INFO - Epoch(val) [10][1250/1250] eta: 0:00:00 time: 0.1538 data_time: 0.0045 memory: 1114 +2024/10/28 14:03:47 - mmengine - INFO - Evaluating bbox... +2024/10/28 14:04:15 - mmengine - INFO - bbox_mAP_copypaste: 0.379 0.591 0.414 0.207 0.415 0.512 +2024/10/28 14:04:15 - mmengine - INFO - Evaluating segm... +2024/10/28 14:04:46 - mmengine - INFO - segm_mAP_copypaste: 0.353 0.564 0.377 0.158 0.382 0.531 +2024/10/28 14:04:47 - mmengine - INFO - Epoch(val) [10][1250/1250] coco/bbox_mAP: 0.3790 coco/bbox_mAP_50: 0.5910 coco/bbox_mAP_75: 0.4140 coco/bbox_mAP_s: 0.2070 coco/bbox_mAP_m: 0.4150 coco/bbox_mAP_l: 0.5120 coco/segm_mAP: 0.3530 coco/segm_mAP_50: 0.5640 coco/segm_mAP_75: 0.3770 coco/segm_mAP_s: 0.1580 coco/segm_mAP_m: 0.3820 coco/segm_mAP_l: 0.5310 data_time: 0.0059 time: 0.1605 +2024/10/28 14:05:38 - mmengine - INFO - Epoch(train) [11][ 50/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:03:40 time: 1.0169 data_time: 0.0454 memory: 6197 grad_norm: 3.1052 loss: 0.6687 loss_rpn_cls: 0.0189 loss_rpn_bbox: 0.0339 loss_cls: 0.1728 acc: 89.4531 loss_bbox: 0.2093 loss_mask: 0.2338 +2024/10/28 14:06:24 - mmengine - INFO - Epoch(train) [11][ 100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:03:04 time: 0.9305 data_time: 0.0610 memory: 6190 grad_norm: 3.1064 loss: 0.7160 loss_rpn_cls: 0.0206 loss_rpn_bbox: 0.0396 loss_cls: 0.1902 acc: 92.0898 loss_bbox: 0.2329 loss_mask: 0.2327 +2024/10/28 14:07:21 - mmengine - INFO - Epoch(train) [11][ 150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:02:30 time: 1.1249 data_time: 0.0514 memory: 6251 grad_norm: 3.2732 loss: 0.7155 loss_rpn_cls: 0.0204 loss_rpn_bbox: 0.0394 loss_cls: 0.1859 acc: 90.5273 loss_bbox: 0.2296 loss_mask: 0.2402 +2024/10/28 14:08:11 - mmengine - INFO - Epoch(train) [11][ 200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:01:55 time: 1.0050 data_time: 0.0596 memory: 6279 grad_norm: 3.1466 loss: 0.6963 loss_rpn_cls: 0.0191 loss_rpn_bbox: 0.0382 loss_cls: 0.1749 acc: 90.5762 loss_bbox: 0.2266 loss_mask: 0.2375 +2024/10/28 14:09:03 - mmengine - INFO - Epoch(train) [11][ 250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:01:20 time: 1.0380 data_time: 0.0567 memory: 6318 grad_norm: 3.1455 loss: 0.7160 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0436 loss_cls: 0.1780 acc: 94.1895 loss_bbox: 0.2300 loss_mask: 0.2417 +2024/10/28 14:09:55 - mmengine - INFO - Epoch(train) [11][ 300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:00:45 time: 1.0459 data_time: 0.0942 memory: 6404 grad_norm: 3.3195 loss: 0.6369 loss_rpn_cls: 0.0148 loss_rpn_bbox: 0.0341 loss_cls: 0.1528 acc: 90.3809 loss_bbox: 0.2116 loss_mask: 0.2235 +2024/10/28 14:10:46 - mmengine - INFO - Epoch(train) [11][ 350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 3:00:10 time: 1.0259 data_time: 0.0629 memory: 6386 grad_norm: 3.2243 loss: 0.7051 loss_rpn_cls: 0.0205 loss_rpn_bbox: 0.0418 loss_cls: 0.1770 acc: 96.1426 loss_bbox: 0.2263 loss_mask: 0.2394 +2024/10/28 14:11:38 - mmengine - INFO - Epoch(train) [11][ 400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:59:35 time: 1.0403 data_time: 0.0642 memory: 6233 grad_norm: 3.2354 loss: 0.6761 loss_rpn_cls: 0.0202 loss_rpn_bbox: 0.0382 loss_cls: 0.1730 acc: 94.1895 loss_bbox: 0.2148 loss_mask: 0.2300 +2024/10/28 14:12:31 - mmengine - INFO - Epoch(train) [11][ 450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:59:00 time: 1.0541 data_time: 0.0513 memory: 6140 grad_norm: 3.4089 loss: 0.6685 loss_rpn_cls: 0.0183 loss_rpn_bbox: 0.0385 loss_cls: 0.1628 acc: 91.4551 loss_bbox: 0.2116 loss_mask: 0.2373 +2024/10/28 14:13:23 - mmengine - INFO - Epoch(train) [11][ 500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:58:25 time: 1.0474 data_time: 0.0603 memory: 6173 grad_norm: 3.2280 loss: 0.6535 loss_rpn_cls: 0.0173 loss_rpn_bbox: 0.0362 loss_cls: 0.1719 acc: 96.4355 loss_bbox: 0.2118 loss_mask: 0.2164 +2024/10/28 14:14:12 - mmengine - INFO - Epoch(train) [11][ 550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:57:49 time: 0.9783 data_time: 0.0542 memory: 6208 grad_norm: 3.3049 loss: 0.6915 loss_rpn_cls: 0.0200 loss_rpn_bbox: 0.0413 loss_cls: 0.1764 acc: 96.1914 loss_bbox: 0.2245 loss_mask: 0.2293 +2024/10/28 14:15:04 - mmengine - INFO - Epoch(train) [11][ 600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:57:14 time: 1.0370 data_time: 0.0612 memory: 6359 grad_norm: 3.2384 loss: 0.6468 loss_rpn_cls: 0.0190 loss_rpn_bbox: 0.0357 loss_cls: 0.1634 acc: 95.2637 loss_bbox: 0.2051 loss_mask: 0.2235 +2024/10/28 14:15:56 - mmengine - INFO - Epoch(train) [11][ 650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:56:39 time: 1.0431 data_time: 0.0678 memory: 6381 grad_norm: 3.4136 loss: 0.6469 loss_rpn_cls: 0.0199 loss_rpn_bbox: 0.0406 loss_cls: 0.1557 acc: 89.5996 loss_bbox: 0.2022 loss_mask: 0.2285 +2024/10/28 14:16:49 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 14:16:49 - mmengine - INFO - Epoch(train) [11][ 700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:56:04 time: 1.0620 data_time: 0.0590 memory: 6366 grad_norm: 3.2396 loss: 0.6513 loss_rpn_cls: 0.0181 loss_rpn_bbox: 0.0357 loss_cls: 0.1605 acc: 93.0664 loss_bbox: 0.2097 loss_mask: 0.2274 +2024/10/28 14:17:37 - mmengine - INFO - Epoch(train) [11][ 750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:55:28 time: 0.9567 data_time: 0.0538 memory: 6342 grad_norm: 3.2909 loss: 0.6566 loss_rpn_cls: 0.0180 loss_rpn_bbox: 0.0351 loss_cls: 0.1646 acc: 96.9727 loss_bbox: 0.2107 loss_mask: 0.2282 +2024/10/28 14:18:28 - mmengine - INFO - Epoch(train) [11][ 800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:54:53 time: 1.0207 data_time: 0.0601 memory: 6337 grad_norm: 3.2803 loss: 0.7125 loss_rpn_cls: 0.0217 loss_rpn_bbox: 0.0404 loss_cls: 0.1835 acc: 99.2676 loss_bbox: 0.2267 loss_mask: 0.2403 +2024/10/28 14:19:17 - mmengine - INFO - Epoch(train) [11][ 850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:54:17 time: 0.9827 data_time: 0.0535 memory: 6297 grad_norm: 3.3918 loss: 0.6698 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0372 loss_cls: 0.1672 acc: 91.7969 loss_bbox: 0.2146 loss_mask: 0.2314 +2024/10/28 14:20:08 - mmengine - INFO - Epoch(train) [11][ 900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:53:41 time: 1.0034 data_time: 0.0500 memory: 6253 grad_norm: 3.2442 loss: 0.6731 loss_rpn_cls: 0.0197 loss_rpn_bbox: 0.0363 loss_cls: 0.1682 acc: 92.5293 loss_bbox: 0.2108 loss_mask: 0.2380 +2024/10/28 14:20:57 - mmengine - INFO - Epoch(train) [11][ 950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:53:06 time: 0.9914 data_time: 0.0451 memory: 6348 grad_norm: 3.2116 loss: 0.6931 loss_rpn_cls: 0.0226 loss_rpn_bbox: 0.0384 loss_cls: 0.1815 acc: 90.1855 loss_bbox: 0.2252 loss_mask: 0.2253 +2024/10/28 14:21:50 - mmengine - INFO - Epoch(train) [11][1000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:52:31 time: 1.0483 data_time: 0.0494 memory: 6246 grad_norm: 3.2517 loss: 0.7197 loss_rpn_cls: 0.0188 loss_rpn_bbox: 0.0464 loss_cls: 0.1851 acc: 95.0684 loss_bbox: 0.2368 loss_mask: 0.2326 +2024/10/28 14:22:30 - mmengine - INFO - Epoch(train) [11][1050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:51:53 time: 0.8097 data_time: 0.0400 memory: 6347 grad_norm: 3.3030 loss: 0.6823 loss_rpn_cls: 0.0210 loss_rpn_bbox: 0.0395 loss_cls: 0.1765 acc: 94.2383 loss_bbox: 0.2116 loss_mask: 0.2337 +2024/10/28 14:22:56 - mmengine - INFO - Epoch(train) [11][1100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:51:13 time: 0.5177 data_time: 0.0394 memory: 6101 grad_norm: 3.2011 loss: 0.6437 loss_rpn_cls: 0.0200 loss_rpn_bbox: 0.0363 loss_cls: 0.1584 acc: 94.2871 loss_bbox: 0.2006 loss_mask: 0.2284 +2024/10/28 14:23:21 - mmengine - INFO - Epoch(train) [11][1150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:50:33 time: 0.5083 data_time: 0.0357 memory: 6161 grad_norm: 3.3599 loss: 0.6519 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0372 loss_cls: 0.1637 acc: 94.5312 loss_bbox: 0.2054 loss_mask: 0.2261 +2024/10/28 14:23:46 - mmengine - INFO - Epoch(train) [11][1200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:49:53 time: 0.5004 data_time: 0.0355 memory: 6215 grad_norm: 3.3694 loss: 0.6878 loss_rpn_cls: 0.0231 loss_rpn_bbox: 0.0376 loss_cls: 0.1750 acc: 91.9434 loss_bbox: 0.2190 loss_mask: 0.2331 +2024/10/28 14:24:13 - mmengine - INFO - Epoch(train) [11][1250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:49:13 time: 0.5291 data_time: 0.0643 memory: 6394 grad_norm: 3.2546 loss: 0.7141 loss_rpn_cls: 0.0163 loss_rpn_bbox: 0.0387 loss_cls: 0.1758 acc: 88.6230 loss_bbox: 0.2374 loss_mask: 0.2459 +2024/10/28 14:24:39 - mmengine - INFO - Epoch(train) [11][1300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:48:33 time: 0.5205 data_time: 0.0521 memory: 6378 grad_norm: 3.2113 loss: 0.7313 loss_rpn_cls: 0.0222 loss_rpn_bbox: 0.0431 loss_cls: 0.1918 acc: 93.7988 loss_bbox: 0.2365 loss_mask: 0.2377 +2024/10/28 14:25:05 - mmengine - INFO - Epoch(train) [11][1350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:47:53 time: 0.5162 data_time: 0.0426 memory: 6324 grad_norm: 3.2525 loss: 0.6572 loss_rpn_cls: 0.0197 loss_rpn_bbox: 0.0372 loss_cls: 0.1793 acc: 91.7969 loss_bbox: 0.2023 loss_mask: 0.2187 +2024/10/28 14:25:32 - mmengine - INFO - Epoch(train) [11][1400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:47:13 time: 0.5362 data_time: 0.0599 memory: 6239 grad_norm: 3.2082 loss: 0.6726 loss_rpn_cls: 0.0174 loss_rpn_bbox: 0.0386 loss_cls: 0.1706 acc: 97.2656 loss_bbox: 0.2106 loss_mask: 0.2353 +2024/10/28 14:25:57 - mmengine - INFO - Epoch(train) [11][1450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:46:33 time: 0.5168 data_time: 0.0413 memory: 6304 grad_norm: 3.4168 loss: 0.6602 loss_rpn_cls: 0.0212 loss_rpn_bbox: 0.0378 loss_cls: 0.1696 acc: 99.0723 loss_bbox: 0.2084 loss_mask: 0.2232 +2024/10/28 14:26:24 - mmengine - INFO - Epoch(train) [11][1500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:45:53 time: 0.5211 data_time: 0.0434 memory: 6261 grad_norm: 3.1319 loss: 0.7055 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0371 loss_cls: 0.1847 acc: 92.4316 loss_bbox: 0.2294 loss_mask: 0.2368 +2024/10/28 14:26:49 - mmengine - INFO - Epoch(train) [11][1550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:45:13 time: 0.5166 data_time: 0.0423 memory: 6276 grad_norm: 3.2928 loss: 0.6782 loss_rpn_cls: 0.0181 loss_rpn_bbox: 0.0344 loss_cls: 0.1738 acc: 91.1133 loss_bbox: 0.2176 loss_mask: 0.2344 +2024/10/28 14:27:15 - mmengine - INFO - Epoch(train) [11][1600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:44:33 time: 0.5065 data_time: 0.0386 memory: 6282 grad_norm: 3.2499 loss: 0.6599 loss_rpn_cls: 0.0199 loss_rpn_bbox: 0.0362 loss_cls: 0.1652 acc: 90.2344 loss_bbox: 0.2080 loss_mask: 0.2306 +2024/10/28 14:27:41 - mmengine - INFO - Epoch(train) [11][1650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:43:53 time: 0.5210 data_time: 0.0436 memory: 6215 grad_norm: 3.2054 loss: 0.6901 loss_rpn_cls: 0.0222 loss_rpn_bbox: 0.0402 loss_cls: 0.1723 acc: 91.8457 loss_bbox: 0.2206 loss_mask: 0.2349 +2024/10/28 14:28:07 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 14:28:07 - mmengine - INFO - Epoch(train) [11][1700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:43:14 time: 0.5232 data_time: 0.0557 memory: 6189 grad_norm: 3.2334 loss: 0.7070 loss_rpn_cls: 0.0188 loss_rpn_bbox: 0.0412 loss_cls: 0.1808 acc: 95.8984 loss_bbox: 0.2300 loss_mask: 0.2362 +2024/10/28 14:28:33 - mmengine - INFO - Epoch(train) [11][1750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:42:34 time: 0.5241 data_time: 0.0507 memory: 6199 grad_norm: 3.2248 loss: 0.6181 loss_rpn_cls: 0.0179 loss_rpn_bbox: 0.0359 loss_cls: 0.1552 acc: 94.5312 loss_bbox: 0.1909 loss_mask: 0.2182 +2024/10/28 14:29:00 - mmengine - INFO - Epoch(train) [11][1800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:41:54 time: 0.5358 data_time: 0.0655 memory: 6217 grad_norm: 3.3277 loss: 0.7574 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0461 loss_cls: 0.1962 acc: 97.1680 loss_bbox: 0.2488 loss_mask: 0.2435 +2024/10/28 14:29:26 - mmengine - INFO - Epoch(train) [11][1850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:41:14 time: 0.5226 data_time: 0.0531 memory: 6189 grad_norm: 3.2412 loss: 0.6296 loss_rpn_cls: 0.0170 loss_rpn_bbox: 0.0357 loss_cls: 0.1569 acc: 98.6816 loss_bbox: 0.1958 loss_mask: 0.2241 +2024/10/28 14:29:52 - mmengine - INFO - Epoch(train) [11][1900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:40:35 time: 0.5187 data_time: 0.0521 memory: 6209 grad_norm: 3.2450 loss: 0.6737 loss_rpn_cls: 0.0159 loss_rpn_bbox: 0.0360 loss_cls: 0.1696 acc: 86.4258 loss_bbox: 0.2196 loss_mask: 0.2326 +2024/10/28 14:30:18 - mmengine - INFO - Epoch(train) [11][1950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:39:55 time: 0.5210 data_time: 0.0594 memory: 6233 grad_norm: 3.2233 loss: 0.6463 loss_rpn_cls: 0.0180 loss_rpn_bbox: 0.0363 loss_cls: 0.1597 acc: 92.5293 loss_bbox: 0.2070 loss_mask: 0.2253 +2024/10/28 14:30:44 - mmengine - INFO - Epoch(train) [11][2000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:39:15 time: 0.5246 data_time: 0.0530 memory: 6251 grad_norm: 3.2408 loss: 0.6302 loss_rpn_cls: 0.0172 loss_rpn_bbox: 0.0345 loss_cls: 0.1553 acc: 98.6816 loss_bbox: 0.1992 loss_mask: 0.2240 +2024/10/28 14:31:11 - mmengine - INFO - Epoch(train) [11][2050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:38:36 time: 0.5328 data_time: 0.0587 memory: 6273 grad_norm: 3.2999 loss: 0.6275 loss_rpn_cls: 0.0148 loss_rpn_bbox: 0.0354 loss_cls: 0.1563 acc: 97.1191 loss_bbox: 0.1991 loss_mask: 0.2220 +2024/10/28 14:31:37 - mmengine - INFO - Epoch(train) [11][2100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:37:56 time: 0.5235 data_time: 0.0636 memory: 6268 grad_norm: 3.3011 loss: 0.6513 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0358 loss_cls: 0.1629 acc: 96.5820 loss_bbox: 0.2140 loss_mask: 0.2200 +2024/10/28 14:32:03 - mmengine - INFO - Epoch(train) [11][2150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:37:16 time: 0.5097 data_time: 0.0512 memory: 6325 grad_norm: 3.3650 loss: 0.6341 loss_rpn_cls: 0.0144 loss_rpn_bbox: 0.0339 loss_cls: 0.1590 acc: 96.3867 loss_bbox: 0.2026 loss_mask: 0.2242 +2024/10/28 14:32:31 - mmengine - INFO - Epoch(train) [11][2200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:36:37 time: 0.5664 data_time: 0.1036 memory: 6394 grad_norm: 3.2346 loss: 0.6756 loss_rpn_cls: 0.0183 loss_rpn_bbox: 0.0356 loss_cls: 0.1773 acc: 95.6543 loss_bbox: 0.2149 loss_mask: 0.2296 +2024/10/28 14:32:57 - mmengine - INFO - Epoch(train) [11][2250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:35:57 time: 0.5315 data_time: 0.0674 memory: 6219 grad_norm: 3.3446 loss: 0.7144 loss_rpn_cls: 0.0237 loss_rpn_bbox: 0.0431 loss_cls: 0.1842 acc: 96.3867 loss_bbox: 0.2300 loss_mask: 0.2334 +2024/10/28 14:33:24 - mmengine - INFO - Epoch(train) [11][2300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:35:18 time: 0.5227 data_time: 0.0595 memory: 6367 grad_norm: 3.0986 loss: 0.6654 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0377 loss_cls: 0.1650 acc: 96.4355 loss_bbox: 0.2148 loss_mask: 0.2293 +2024/10/28 14:33:49 - mmengine - INFO - Epoch(train) [11][2350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:34:38 time: 0.5130 data_time: 0.0497 memory: 6406 grad_norm: 3.2939 loss: 0.6518 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0366 loss_cls: 0.1606 acc: 90.5762 loss_bbox: 0.2054 loss_mask: 0.2308 +2024/10/28 14:34:15 - mmengine - INFO - Epoch(train) [11][2400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:33:59 time: 0.5142 data_time: 0.0480 memory: 6288 grad_norm: 3.3060 loss: 0.6527 loss_rpn_cls: 0.0169 loss_rpn_bbox: 0.0336 loss_cls: 0.1629 acc: 91.9922 loss_bbox: 0.2085 loss_mask: 0.2309 +2024/10/28 14:34:41 - mmengine - INFO - Epoch(train) [11][2450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:33:19 time: 0.5203 data_time: 0.0567 memory: 6300 grad_norm: 3.4284 loss: 0.6404 loss_rpn_cls: 0.0174 loss_rpn_bbox: 0.0375 loss_cls: 0.1624 acc: 97.2656 loss_bbox: 0.1979 loss_mask: 0.2252 +2024/10/28 14:35:07 - mmengine - INFO - Epoch(train) [11][2500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:32:39 time: 0.5136 data_time: 0.0583 memory: 6055 grad_norm: 3.2367 loss: 0.6378 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0368 loss_cls: 0.1615 acc: 96.2402 loss_bbox: 0.1962 loss_mask: 0.2255 +2024/10/28 14:35:33 - mmengine - INFO - Epoch(train) [11][2550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:32:00 time: 0.5237 data_time: 0.0539 memory: 6297 grad_norm: 3.4407 loss: 0.6937 loss_rpn_cls: 0.0198 loss_rpn_bbox: 0.0399 loss_cls: 0.1777 acc: 99.6094 loss_bbox: 0.2270 loss_mask: 0.2293 +2024/10/28 14:35:59 - mmengine - INFO - Epoch(train) [11][2600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:31:20 time: 0.5155 data_time: 0.0540 memory: 6419 grad_norm: 3.2563 loss: 0.6621 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0378 loss_cls: 0.1667 acc: 91.9922 loss_bbox: 0.2153 loss_mask: 0.2228 +2024/10/28 14:36:25 - mmengine - INFO - Epoch(train) [11][2650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:30:41 time: 0.5244 data_time: 0.0528 memory: 6180 grad_norm: 3.2064 loss: 0.6604 loss_rpn_cls: 0.0180 loss_rpn_bbox: 0.0376 loss_cls: 0.1676 acc: 87.2070 loss_bbox: 0.2157 loss_mask: 0.2214 +2024/10/28 14:36:51 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 14:36:51 - mmengine - INFO - Epoch(train) [11][2700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:30:01 time: 0.5164 data_time: 0.0439 memory: 6235 grad_norm: 3.2856 loss: 0.6152 loss_rpn_cls: 0.0156 loss_rpn_bbox: 0.0323 loss_cls: 0.1540 acc: 95.9473 loss_bbox: 0.1883 loss_mask: 0.2250 +2024/10/28 14:37:18 - mmengine - INFO - Epoch(train) [11][2750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:29:22 time: 0.5459 data_time: 0.0598 memory: 6332 grad_norm: 3.2830 loss: 0.6592 loss_rpn_cls: 0.0161 loss_rpn_bbox: 0.0370 loss_cls: 0.1652 acc: 98.8281 loss_bbox: 0.2154 loss_mask: 0.2255 +2024/10/28 14:37:44 - mmengine - INFO - Epoch(train) [11][2800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:28:43 time: 0.5127 data_time: 0.0504 memory: 6191 grad_norm: 3.2551 loss: 0.6542 loss_rpn_cls: 0.0188 loss_rpn_bbox: 0.0380 loss_cls: 0.1671 acc: 92.2363 loss_bbox: 0.2072 loss_mask: 0.2231 +2024/10/28 14:38:10 - mmengine - INFO - Epoch(train) [11][2850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:28:03 time: 0.5285 data_time: 0.0482 memory: 6252 grad_norm: 3.0896 loss: 0.6366 loss_rpn_cls: 0.0168 loss_rpn_bbox: 0.0327 loss_cls: 0.1527 acc: 97.0703 loss_bbox: 0.2044 loss_mask: 0.2300 +2024/10/28 14:38:36 - mmengine - INFO - Epoch(train) [11][2900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:27:24 time: 0.5248 data_time: 0.0508 memory: 6321 grad_norm: 3.3086 loss: 0.6790 loss_rpn_cls: 0.0182 loss_rpn_bbox: 0.0372 loss_cls: 0.1718 acc: 96.3379 loss_bbox: 0.2137 loss_mask: 0.2382 +2024/10/28 14:39:03 - mmengine - INFO - Epoch(train) [11][2950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:26:45 time: 0.5363 data_time: 0.0774 memory: 6398 grad_norm: 3.2687 loss: 0.6877 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0366 loss_cls: 0.1731 acc: 92.2363 loss_bbox: 0.2276 loss_mask: 0.2327 +2024/10/28 14:39:32 - mmengine - INFO - Epoch(train) [11][3000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:26:06 time: 0.5837 data_time: 0.1073 memory: 6115 grad_norm: 3.0802 loss: 0.6152 loss_rpn_cls: 0.0154 loss_rpn_bbox: 0.0349 loss_cls: 0.1512 acc: 93.7012 loss_bbox: 0.1920 loss_mask: 0.2216 +2024/10/28 14:39:58 - mmengine - INFO - Epoch(train) [11][3050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:25:26 time: 0.5126 data_time: 0.0577 memory: 6345 grad_norm: 3.3769 loss: 0.7040 loss_rpn_cls: 0.0197 loss_rpn_bbox: 0.0417 loss_cls: 0.1788 acc: 93.5547 loss_bbox: 0.2284 loss_mask: 0.2354 +2024/10/28 14:40:24 - mmengine - INFO - Epoch(train) [11][3100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:24:47 time: 0.5236 data_time: 0.0595 memory: 6264 grad_norm: 3.3721 loss: 0.6625 loss_rpn_cls: 0.0176 loss_rpn_bbox: 0.0405 loss_cls: 0.1704 acc: 92.0898 loss_bbox: 0.2109 loss_mask: 0.2231 +2024/10/28 14:40:50 - mmengine - INFO - Epoch(train) [11][3150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:24:08 time: 0.5148 data_time: 0.0515 memory: 6337 grad_norm: 3.3956 loss: 0.6700 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0388 loss_cls: 0.1703 acc: 95.9473 loss_bbox: 0.2102 loss_mask: 0.2332 +2024/10/28 14:41:16 - mmengine - INFO - Epoch(train) [11][3200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:23:28 time: 0.5161 data_time: 0.0544 memory: 6260 grad_norm: 3.2338 loss: 0.7030 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0401 loss_cls: 0.1804 acc: 92.9688 loss_bbox: 0.2252 loss_mask: 0.2389 +2024/10/28 14:41:42 - mmengine - INFO - Epoch(train) [11][3250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:22:49 time: 0.5232 data_time: 0.0539 memory: 6179 grad_norm: 3.3920 loss: 0.6468 loss_rpn_cls: 0.0173 loss_rpn_bbox: 0.0359 loss_cls: 0.1677 acc: 96.9727 loss_bbox: 0.2067 loss_mask: 0.2192 +2024/10/28 14:42:08 - mmengine - INFO - Epoch(train) [11][3300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:22:10 time: 0.5230 data_time: 0.0506 memory: 6355 grad_norm: 3.3744 loss: 0.6790 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0353 loss_cls: 0.1676 acc: 95.7031 loss_bbox: 0.2213 loss_mask: 0.2373 +2024/10/28 14:42:34 - mmengine - INFO - Epoch(train) [11][3350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:21:31 time: 0.5226 data_time: 0.0540 memory: 6180 grad_norm: 3.2255 loss: 0.6319 loss_rpn_cls: 0.0163 loss_rpn_bbox: 0.0349 loss_cls: 0.1530 acc: 94.8242 loss_bbox: 0.2078 loss_mask: 0.2198 +2024/10/28 14:43:00 - mmengine - INFO - Epoch(train) [11][3400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:20:51 time: 0.5197 data_time: 0.0532 memory: 6274 grad_norm: 3.3260 loss: 0.6579 loss_rpn_cls: 0.0191 loss_rpn_bbox: 0.0391 loss_cls: 0.1603 acc: 93.0176 loss_bbox: 0.2063 loss_mask: 0.2331 +2024/10/28 14:43:26 - mmengine - INFO - Epoch(train) [11][3450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:20:12 time: 0.5173 data_time: 0.0528 memory: 6221 grad_norm: 3.3258 loss: 0.6867 loss_rpn_cls: 0.0212 loss_rpn_bbox: 0.0389 loss_cls: 0.1721 acc: 91.1133 loss_bbox: 0.2218 loss_mask: 0.2327 +2024/10/28 14:43:53 - mmengine - INFO - Epoch(train) [11][3500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:19:33 time: 0.5399 data_time: 0.0549 memory: 6351 grad_norm: 3.2446 loss: 0.6436 loss_rpn_cls: 0.0187 loss_rpn_bbox: 0.0320 loss_cls: 0.1596 acc: 91.7480 loss_bbox: 0.2090 loss_mask: 0.2243 +2024/10/28 14:44:19 - mmengine - INFO - Epoch(train) [11][3550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:18:54 time: 0.5230 data_time: 0.0655 memory: 6196 grad_norm: 3.2773 loss: 0.7252 loss_rpn_cls: 0.0229 loss_rpn_bbox: 0.0420 loss_cls: 0.1873 acc: 95.8984 loss_bbox: 0.2307 loss_mask: 0.2422 +2024/10/28 14:44:45 - mmengine - INFO - Epoch(train) [11][3600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:18:15 time: 0.5155 data_time: 0.0471 memory: 6355 grad_norm: 3.3600 loss: 0.6641 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0377 loss_cls: 0.1702 acc: 94.4336 loss_bbox: 0.2094 loss_mask: 0.2274 +2024/10/28 14:45:11 - mmengine - INFO - Epoch(train) [11][3650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:17:36 time: 0.5264 data_time: 0.0579 memory: 6301 grad_norm: 3.2962 loss: 0.7105 loss_rpn_cls: 0.0206 loss_rpn_bbox: 0.0384 loss_cls: 0.1817 acc: 95.8496 loss_bbox: 0.2285 loss_mask: 0.2413 +2024/10/28 14:45:37 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 14:45:37 - mmengine - INFO - Epoch(train) [11][3700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:16:56 time: 0.5087 data_time: 0.0517 memory: 6348 grad_norm: 3.2374 loss: 0.6801 loss_rpn_cls: 0.0182 loss_rpn_bbox: 0.0374 loss_cls: 0.1703 acc: 97.3633 loss_bbox: 0.2187 loss_mask: 0.2355 +2024/10/28 14:46:03 - mmengine - INFO - Epoch(train) [11][3750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:16:17 time: 0.5189 data_time: 0.0465 memory: 6402 grad_norm: 3.4220 loss: 0.6378 loss_rpn_cls: 0.0166 loss_rpn_bbox: 0.0352 loss_cls: 0.1585 acc: 94.9219 loss_bbox: 0.2052 loss_mask: 0.2222 +2024/10/28 14:46:31 - mmengine - INFO - Epoch(train) [11][3800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:15:39 time: 0.5674 data_time: 0.1148 memory: 6419 grad_norm: 3.2682 loss: 0.6455 loss_rpn_cls: 0.0166 loss_rpn_bbox: 0.0376 loss_cls: 0.1680 acc: 91.9434 loss_bbox: 0.2074 loss_mask: 0.2158 +2024/10/28 14:46:57 - mmengine - INFO - Epoch(train) [11][3850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:14:59 time: 0.5178 data_time: 0.0459 memory: 6211 grad_norm: 3.3470 loss: 0.6220 loss_rpn_cls: 0.0158 loss_rpn_bbox: 0.0334 loss_cls: 0.1572 acc: 97.9980 loss_bbox: 0.1978 loss_mask: 0.2178 +2024/10/28 14:47:22 - mmengine - INFO - Epoch(train) [11][3900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:14:20 time: 0.5021 data_time: 0.0538 memory: 6310 grad_norm: 3.3668 loss: 0.6951 loss_rpn_cls: 0.0187 loss_rpn_bbox: 0.0376 loss_cls: 0.1715 acc: 93.6523 loss_bbox: 0.2203 loss_mask: 0.2470 +2024/10/28 14:47:48 - mmengine - INFO - Epoch(train) [11][3950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:13:41 time: 0.5217 data_time: 0.0492 memory: 6298 grad_norm: 3.4269 loss: 0.6834 loss_rpn_cls: 0.0162 loss_rpn_bbox: 0.0388 loss_cls: 0.1704 acc: 95.8984 loss_bbox: 0.2226 loss_mask: 0.2355 +2024/10/28 14:48:14 - mmengine - INFO - Epoch(train) [11][4000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:13:02 time: 0.5137 data_time: 0.0544 memory: 6205 grad_norm: 3.2332 loss: 0.6789 loss_rpn_cls: 0.0206 loss_rpn_bbox: 0.0419 loss_cls: 0.1743 acc: 89.8438 loss_bbox: 0.2091 loss_mask: 0.2331 +2024/10/28 14:48:40 - mmengine - INFO - Epoch(train) [11][4050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:12:23 time: 0.5216 data_time: 0.0579 memory: 6194 grad_norm: 3.2026 loss: 0.6741 loss_rpn_cls: 0.0153 loss_rpn_bbox: 0.0367 loss_cls: 0.1674 acc: 94.8242 loss_bbox: 0.2166 loss_mask: 0.2381 +2024/10/28 14:49:06 - mmengine - INFO - Epoch(train) [11][4100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:11:44 time: 0.5169 data_time: 0.0500 memory: 6255 grad_norm: 3.2961 loss: 0.6456 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0353 loss_cls: 0.1606 acc: 94.2871 loss_bbox: 0.2038 loss_mask: 0.2285 +2024/10/28 14:49:32 - mmengine - INFO - Epoch(train) [11][4150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:11:05 time: 0.5241 data_time: 0.0592 memory: 6317 grad_norm: 3.3122 loss: 0.6529 loss_rpn_cls: 0.0158 loss_rpn_bbox: 0.0393 loss_cls: 0.1588 acc: 98.4375 loss_bbox: 0.2084 loss_mask: 0.2306 +2024/10/28 14:49:58 - mmengine - INFO - Epoch(train) [11][4200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:10:26 time: 0.5155 data_time: 0.0550 memory: 6183 grad_norm: 3.2877 loss: 0.6823 loss_rpn_cls: 0.0224 loss_rpn_bbox: 0.0397 loss_cls: 0.1720 acc: 94.1895 loss_bbox: 0.2161 loss_mask: 0.2322 +2024/10/28 14:50:24 - mmengine - INFO - Epoch(train) [11][4250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:09:47 time: 0.5325 data_time: 0.0430 memory: 6172 grad_norm: 3.2729 loss: 0.6021 loss_rpn_cls: 0.0153 loss_rpn_bbox: 0.0311 loss_cls: 0.1452 acc: 94.1895 loss_bbox: 0.1946 loss_mask: 0.2159 +2024/10/28 14:50:51 - mmengine - INFO - Epoch(train) [11][4300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:09:08 time: 0.5251 data_time: 0.0501 memory: 6139 grad_norm: 3.3120 loss: 0.5963 loss_rpn_cls: 0.0149 loss_rpn_bbox: 0.0326 loss_cls: 0.1457 acc: 91.3086 loss_bbox: 0.1895 loss_mask: 0.2136 +2024/10/28 14:51:17 - mmengine - INFO - Epoch(train) [11][4350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:08:30 time: 0.5169 data_time: 0.0470 memory: 6172 grad_norm: 3.3876 loss: 0.6236 loss_rpn_cls: 0.0148 loss_rpn_bbox: 0.0308 loss_cls: 0.1596 acc: 94.3359 loss_bbox: 0.1969 loss_mask: 0.2215 +2024/10/28 14:51:42 - mmengine - INFO - Epoch(train) [11][4400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:07:51 time: 0.5147 data_time: 0.0505 memory: 6160 grad_norm: 3.2726 loss: 0.6873 loss_rpn_cls: 0.0173 loss_rpn_bbox: 0.0405 loss_cls: 0.1692 acc: 98.6816 loss_bbox: 0.2258 loss_mask: 0.2345 +2024/10/28 14:52:09 - mmengine - INFO - Epoch(train) [11][4450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:07:12 time: 0.5247 data_time: 0.0530 memory: 6420 grad_norm: 3.3206 loss: 0.6700 loss_rpn_cls: 0.0209 loss_rpn_bbox: 0.0366 loss_cls: 0.1687 acc: 96.0449 loss_bbox: 0.2116 loss_mask: 0.2322 +2024/10/28 14:52:34 - mmengine - INFO - Epoch(train) [11][4500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:06:33 time: 0.5048 data_time: 0.0420 memory: 6270 grad_norm: 3.2984 loss: 0.6862 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0360 loss_cls: 0.1770 acc: 96.0449 loss_bbox: 0.2246 loss_mask: 0.2301 +2024/10/28 14:53:00 - mmengine - INFO - Epoch(train) [11][4550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:05:54 time: 0.5228 data_time: 0.0465 memory: 6192 grad_norm: 3.2411 loss: 0.6851 loss_rpn_cls: 0.0207 loss_rpn_bbox: 0.0384 loss_cls: 0.1828 acc: 93.0664 loss_bbox: 0.2132 loss_mask: 0.2301 +2024/10/28 14:53:26 - mmengine - INFO - Epoch(train) [11][4600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:05:15 time: 0.5152 data_time: 0.0474 memory: 6314 grad_norm: 3.1822 loss: 0.7127 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0404 loss_cls: 0.1850 acc: 94.9219 loss_bbox: 0.2242 loss_mask: 0.2402 +2024/10/28 14:53:51 - mmengine - INFO - Epoch(train) [11][4650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:04:36 time: 0.5114 data_time: 0.0459 memory: 6243 grad_norm: 3.4637 loss: 0.6648 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0352 loss_cls: 0.1749 acc: 92.1875 loss_bbox: 0.2106 loss_mask: 0.2264 +2024/10/28 14:54:17 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 14:54:17 - mmengine - INFO - Epoch(train) [11][4700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:03:57 time: 0.5232 data_time: 0.0535 memory: 6294 grad_norm: 3.2737 loss: 0.7116 loss_rpn_cls: 0.0227 loss_rpn_bbox: 0.0421 loss_cls: 0.1812 acc: 93.6523 loss_bbox: 0.2378 loss_mask: 0.2278 +2024/10/28 14:54:43 - mmengine - INFO - Epoch(train) [11][4750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:03:19 time: 0.5093 data_time: 0.0441 memory: 6421 grad_norm: 3.2987 loss: 0.6495 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0397 loss_cls: 0.1588 acc: 94.1406 loss_bbox: 0.2062 loss_mask: 0.2253 +2024/10/28 14:55:08 - mmengine - INFO - Epoch(train) [11][4800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:02:40 time: 0.5093 data_time: 0.0406 memory: 6328 grad_norm: 3.1922 loss: 0.6692 loss_rpn_cls: 0.0218 loss_rpn_bbox: 0.0357 loss_cls: 0.1750 acc: 90.9668 loss_bbox: 0.2089 loss_mask: 0.2278 +2024/10/28 14:55:33 - mmengine - INFO - Epoch(train) [11][4850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:02:01 time: 0.5011 data_time: 0.0449 memory: 6348 grad_norm: 3.2486 loss: 0.7239 loss_rpn_cls: 0.0207 loss_rpn_bbox: 0.0385 loss_cls: 0.1875 acc: 96.2402 loss_bbox: 0.2348 loss_mask: 0.2423 +2024/10/28 14:56:00 - mmengine - INFO - Epoch(train) [11][4900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:01:22 time: 0.5350 data_time: 0.0599 memory: 6357 grad_norm: 3.4034 loss: 0.6953 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0393 loss_cls: 0.1715 acc: 94.9707 loss_bbox: 0.2256 loss_mask: 0.2403 +2024/10/28 14:56:25 - mmengine - INFO - Epoch(train) [11][4950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:00:43 time: 0.4986 data_time: 0.0412 memory: 6213 grad_norm: 3.3352 loss: 0.6699 loss_rpn_cls: 0.0168 loss_rpn_bbox: 0.0360 loss_cls: 0.1740 acc: 93.8477 loss_bbox: 0.2069 loss_mask: 0.2363 +2024/10/28 14:56:51 - mmengine - INFO - Epoch(train) [11][5000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 2:00:05 time: 0.5177 data_time: 0.0430 memory: 6283 grad_norm: 3.2580 loss: 0.7156 loss_rpn_cls: 0.0172 loss_rpn_bbox: 0.0396 loss_cls: 0.1866 acc: 91.3086 loss_bbox: 0.2268 loss_mask: 0.2454 +2024/10/28 14:57:18 - mmengine - INFO - Epoch(train) [11][5050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:59:26 time: 0.5294 data_time: 0.0553 memory: 6232 grad_norm: 3.2737 loss: 0.6358 loss_rpn_cls: 0.0180 loss_rpn_bbox: 0.0347 loss_cls: 0.1581 acc: 92.9199 loss_bbox: 0.1979 loss_mask: 0.2271 +2024/10/28 14:57:43 - mmengine - INFO - Epoch(train) [11][5100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:58:47 time: 0.5180 data_time: 0.0530 memory: 6278 grad_norm: 3.3760 loss: 0.6425 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0355 loss_cls: 0.1558 acc: 97.0703 loss_bbox: 0.2067 loss_mask: 0.2267 +2024/10/28 14:58:10 - mmengine - INFO - Epoch(train) [11][5150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:58:09 time: 0.5353 data_time: 0.0731 memory: 6224 grad_norm: 3.1861 loss: 0.7190 loss_rpn_cls: 0.0228 loss_rpn_bbox: 0.0463 loss_cls: 0.1908 acc: 92.3340 loss_bbox: 0.2284 loss_mask: 0.2307 +2024/10/28 14:58:36 - mmengine - INFO - Epoch(train) [11][5200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:57:30 time: 0.5144 data_time: 0.0598 memory: 6271 grad_norm: 3.4135 loss: 0.6842 loss_rpn_cls: 0.0189 loss_rpn_bbox: 0.0374 loss_cls: 0.1770 acc: 93.0176 loss_bbox: 0.2147 loss_mask: 0.2362 +2024/10/28 14:59:03 - mmengine - INFO - Epoch(train) [11][5250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:56:52 time: 0.5351 data_time: 0.0643 memory: 6270 grad_norm: 3.4070 loss: 0.6474 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0369 loss_cls: 0.1631 acc: 96.4844 loss_bbox: 0.2077 loss_mask: 0.2211 +2024/10/28 14:59:32 - mmengine - INFO - Epoch(train) [11][5300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:56:13 time: 0.5822 data_time: 0.1173 memory: 6179 grad_norm: 3.2817 loss: 0.6652 loss_rpn_cls: 0.0179 loss_rpn_bbox: 0.0363 loss_cls: 0.1697 acc: 94.1895 loss_bbox: 0.2158 loss_mask: 0.2255 +2024/10/28 14:59:59 - mmengine - INFO - Epoch(train) [11][5350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:55:35 time: 0.5334 data_time: 0.0554 memory: 6181 grad_norm: 3.2689 loss: 0.6099 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0345 loss_cls: 0.1546 acc: 95.9473 loss_bbox: 0.1887 loss_mask: 0.2138 +2024/10/28 15:00:25 - mmengine - INFO - Epoch(train) [11][5400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:54:56 time: 0.5256 data_time: 0.0598 memory: 6273 grad_norm: 3.2617 loss: 0.6708 loss_rpn_cls: 0.0201 loss_rpn_bbox: 0.0382 loss_cls: 0.1637 acc: 94.4336 loss_bbox: 0.2123 loss_mask: 0.2366 +2024/10/28 15:00:51 - mmengine - INFO - Epoch(train) [11][5450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:54:18 time: 0.5337 data_time: 0.0672 memory: 6268 grad_norm: 3.2665 loss: 0.6727 loss_rpn_cls: 0.0252 loss_rpn_bbox: 0.0381 loss_cls: 0.1686 acc: 93.7012 loss_bbox: 0.2089 loss_mask: 0.2319 +2024/10/28 15:01:17 - mmengine - INFO - Epoch(train) [11][5500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:53:39 time: 0.5111 data_time: 0.0605 memory: 6420 grad_norm: 3.4962 loss: 0.6759 loss_rpn_cls: 0.0214 loss_rpn_bbox: 0.0393 loss_cls: 0.1710 acc: 96.1914 loss_bbox: 0.2166 loss_mask: 0.2275 +2024/10/28 15:01:44 - mmengine - INFO - Epoch(train) [11][5550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:53:01 time: 0.5307 data_time: 0.0596 memory: 6233 grad_norm: 3.2522 loss: 0.6878 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0348 loss_cls: 0.1773 acc: 95.6055 loss_bbox: 0.2193 loss_mask: 0.2379 +2024/10/28 15:02:10 - mmengine - INFO - Epoch(train) [11][5600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:52:22 time: 0.5203 data_time: 0.0537 memory: 6176 grad_norm: 3.2450 loss: 0.6359 loss_rpn_cls: 0.0192 loss_rpn_bbox: 0.0349 loss_cls: 0.1571 acc: 96.3867 loss_bbox: 0.1991 loss_mask: 0.2257 +2024/10/28 15:02:35 - mmengine - INFO - Epoch(train) [11][5650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:51:44 time: 0.5094 data_time: 0.0550 memory: 6162 grad_norm: 3.3257 loss: 0.6713 loss_rpn_cls: 0.0199 loss_rpn_bbox: 0.0369 loss_cls: 0.1779 acc: 93.7012 loss_bbox: 0.2132 loss_mask: 0.2234 +2024/10/28 15:03:01 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 15:03:01 - mmengine - INFO - Epoch(train) [11][5700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:51:05 time: 0.5230 data_time: 0.0552 memory: 6227 grad_norm: 3.2879 loss: 0.6543 loss_rpn_cls: 0.0197 loss_rpn_bbox: 0.0359 loss_cls: 0.1664 acc: 95.6543 loss_bbox: 0.2003 loss_mask: 0.2321 +2024/10/28 15:03:33 - mmengine - INFO - Epoch(train) [11][5750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:50:28 time: 0.6346 data_time: 0.1659 memory: 6270 grad_norm: 3.2274 loss: 0.6488 loss_rpn_cls: 0.0199 loss_rpn_bbox: 0.0365 loss_cls: 0.1720 acc: 93.3594 loss_bbox: 0.2052 loss_mask: 0.2152 +2024/10/28 15:03:59 - mmengine - INFO - Epoch(train) [11][5800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:49:49 time: 0.5230 data_time: 0.0617 memory: 6420 grad_norm: 3.2696 loss: 0.7202 loss_rpn_cls: 0.0232 loss_rpn_bbox: 0.0412 loss_cls: 0.1839 acc: 90.6250 loss_bbox: 0.2308 loss_mask: 0.2411 +2024/10/28 15:04:25 - mmengine - INFO - Epoch(train) [11][5850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:49:11 time: 0.5153 data_time: 0.0526 memory: 6159 grad_norm: 3.2235 loss: 0.6679 loss_rpn_cls: 0.0214 loss_rpn_bbox: 0.0364 loss_cls: 0.1722 acc: 93.3594 loss_bbox: 0.2132 loss_mask: 0.2246 +2024/10/28 15:04:51 - mmengine - INFO - Epoch(train) [11][5900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:48:32 time: 0.5283 data_time: 0.0559 memory: 6380 grad_norm: 3.3451 loss: 0.6728 loss_rpn_cls: 0.0194 loss_rpn_bbox: 0.0390 loss_cls: 0.1728 acc: 93.9453 loss_bbox: 0.2169 loss_mask: 0.2247 +2024/10/28 15:05:17 - mmengine - INFO - Epoch(train) [11][5950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:47:54 time: 0.5184 data_time: 0.0535 memory: 6170 grad_norm: 3.3333 loss: 0.6314 loss_rpn_cls: 0.0197 loss_rpn_bbox: 0.0356 loss_cls: 0.1576 acc: 91.9434 loss_bbox: 0.1963 loss_mask: 0.2223 +2024/10/28 15:05:44 - mmengine - INFO - Epoch(train) [11][6000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:47:16 time: 0.5314 data_time: 0.0590 memory: 6388 grad_norm: 3.4100 loss: 0.6573 loss_rpn_cls: 0.0200 loss_rpn_bbox: 0.0372 loss_cls: 0.1657 acc: 98.2910 loss_bbox: 0.2043 loss_mask: 0.2300 +2024/10/28 15:06:11 - mmengine - INFO - Epoch(train) [11][6050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:46:37 time: 0.5444 data_time: 0.0701 memory: 6168 grad_norm: 3.5208 loss: 0.6696 loss_rpn_cls: 0.0181 loss_rpn_bbox: 0.0363 loss_cls: 0.1675 acc: 95.0195 loss_bbox: 0.2161 loss_mask: 0.2317 +2024/10/28 15:06:38 - mmengine - INFO - Epoch(train) [11][6100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:45:59 time: 0.5290 data_time: 0.0641 memory: 6178 grad_norm: 3.3055 loss: 0.6962 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0377 loss_cls: 0.1731 acc: 98.5840 loss_bbox: 0.2253 loss_mask: 0.2426 +2024/10/28 15:07:04 - mmengine - INFO - Epoch(train) [11][6150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:45:21 time: 0.5277 data_time: 0.0430 memory: 6265 grad_norm: 3.3191 loss: 0.6641 loss_rpn_cls: 0.0188 loss_rpn_bbox: 0.0378 loss_cls: 0.1672 acc: 94.0918 loss_bbox: 0.2135 loss_mask: 0.2267 +2024/10/28 15:07:31 - mmengine - INFO - Epoch(train) [11][6200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:44:42 time: 0.5335 data_time: 0.0645 memory: 6235 grad_norm: 3.3146 loss: 0.6014 loss_rpn_cls: 0.0152 loss_rpn_bbox: 0.0317 loss_cls: 0.1494 acc: 96.0449 loss_bbox: 0.1848 loss_mask: 0.2203 +2024/10/28 15:07:56 - mmengine - INFO - Epoch(train) [11][6250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:44:04 time: 0.5088 data_time: 0.0504 memory: 6394 grad_norm: 3.4107 loss: 0.7020 loss_rpn_cls: 0.0170 loss_rpn_bbox: 0.0407 loss_cls: 0.1829 acc: 93.5547 loss_bbox: 0.2285 loss_mask: 0.2329 +2024/10/28 15:08:21 - mmengine - INFO - Epoch(train) [11][6300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:43:26 time: 0.4998 data_time: 0.0418 memory: 6256 grad_norm: 3.3132 loss: 0.6629 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0395 loss_cls: 0.1671 acc: 92.4805 loss_bbox: 0.2115 loss_mask: 0.2252 +2024/10/28 15:08:47 - mmengine - INFO - Epoch(train) [11][6350/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:42:47 time: 0.5155 data_time: 0.0406 memory: 6187 grad_norm: 3.3440 loss: 0.6761 loss_rpn_cls: 0.0192 loss_rpn_bbox: 0.0363 loss_cls: 0.1687 acc: 97.5098 loss_bbox: 0.2156 loss_mask: 0.2363 +2024/10/28 15:09:13 - mmengine - INFO - Epoch(train) [11][6400/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:42:09 time: 0.5235 data_time: 0.0558 memory: 6265 grad_norm: 3.5310 loss: 0.7438 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0456 loss_cls: 0.1981 acc: 90.6250 loss_bbox: 0.2474 loss_mask: 0.2342 +2024/10/28 15:09:40 - mmengine - INFO - Epoch(train) [11][6450/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:41:31 time: 0.5350 data_time: 0.0644 memory: 6380 grad_norm: 3.4132 loss: 0.7294 loss_rpn_cls: 0.0239 loss_rpn_bbox: 0.0430 loss_cls: 0.1866 acc: 93.0664 loss_bbox: 0.2366 loss_mask: 0.2393 +2024/10/28 15:10:06 - mmengine - INFO - Epoch(train) [11][6500/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:40:53 time: 0.5274 data_time: 0.0587 memory: 6219 grad_norm: 3.3843 loss: 0.6926 loss_rpn_cls: 0.0209 loss_rpn_bbox: 0.0385 loss_cls: 0.1711 acc: 88.8672 loss_bbox: 0.2241 loss_mask: 0.2380 +2024/10/28 15:10:32 - mmengine - INFO - Epoch(train) [11][6550/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:40:15 time: 0.5124 data_time: 0.0544 memory: 6388 grad_norm: 3.4436 loss: 0.7013 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0427 loss_cls: 0.1838 acc: 94.7266 loss_bbox: 0.2221 loss_mask: 0.2343 +2024/10/28 15:10:58 - mmengine - INFO - Epoch(train) [11][6600/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:39:36 time: 0.5194 data_time: 0.0496 memory: 6275 grad_norm: 3.3118 loss: 0.6631 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0358 loss_cls: 0.1668 acc: 94.2383 loss_bbox: 0.2120 loss_mask: 0.2309 +2024/10/28 15:11:24 - mmengine - INFO - Epoch(train) [11][6650/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:38:58 time: 0.5171 data_time: 0.0455 memory: 6264 grad_norm: 3.1624 loss: 0.6531 loss_rpn_cls: 0.0184 loss_rpn_bbox: 0.0361 loss_cls: 0.1658 acc: 89.1113 loss_bbox: 0.2055 loss_mask: 0.2274 +2024/10/28 15:11:49 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 15:11:49 - mmengine - INFO - Epoch(train) [11][6700/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:38:20 time: 0.5126 data_time: 0.0483 memory: 6301 grad_norm: 3.4306 loss: 0.6853 loss_rpn_cls: 0.0191 loss_rpn_bbox: 0.0412 loss_cls: 0.1751 acc: 91.6504 loss_bbox: 0.2213 loss_mask: 0.2286 +2024/10/28 15:12:15 - mmengine - INFO - Epoch(train) [11][6750/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:37:42 time: 0.5205 data_time: 0.0444 memory: 6109 grad_norm: 3.2400 loss: 0.6298 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0339 loss_cls: 0.1601 acc: 98.1445 loss_bbox: 0.2001 loss_mask: 0.2174 +2024/10/28 15:12:41 - mmengine - INFO - Epoch(train) [11][6800/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:37:04 time: 0.5137 data_time: 0.0429 memory: 6278 grad_norm: 3.3765 loss: 0.6641 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0362 loss_cls: 0.1640 acc: 96.6309 loss_bbox: 0.2117 loss_mask: 0.2355 +2024/10/28 15:13:07 - mmengine - INFO - Epoch(train) [11][6850/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:36:25 time: 0.5200 data_time: 0.0424 memory: 6182 grad_norm: 3.4122 loss: 0.6087 loss_rpn_cls: 0.0154 loss_rpn_bbox: 0.0323 loss_cls: 0.1579 acc: 94.7754 loss_bbox: 0.1908 loss_mask: 0.2123 +2024/10/28 15:13:32 - mmengine - INFO - Epoch(train) [11][6900/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:35:47 time: 0.5099 data_time: 0.0493 memory: 6248 grad_norm: 3.3476 loss: 0.6679 loss_rpn_cls: 0.0177 loss_rpn_bbox: 0.0364 loss_cls: 0.1714 acc: 92.4316 loss_bbox: 0.2062 loss_mask: 0.2362 +2024/10/28 15:13:58 - mmengine - INFO - Epoch(train) [11][6950/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:35:09 time: 0.5155 data_time: 0.0474 memory: 6335 grad_norm: 3.3693 loss: 0.6715 loss_rpn_cls: 0.0198 loss_rpn_bbox: 0.0385 loss_cls: 0.1670 acc: 91.1133 loss_bbox: 0.2130 loss_mask: 0.2331 +2024/10/28 15:14:23 - mmengine - INFO - Epoch(train) [11][7000/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:34:31 time: 0.4979 data_time: 0.0468 memory: 6209 grad_norm: 3.3219 loss: 0.6531 loss_rpn_cls: 0.0204 loss_rpn_bbox: 0.0362 loss_cls: 0.1653 acc: 95.5078 loss_bbox: 0.2065 loss_mask: 0.2248 +2024/10/28 15:14:49 - mmengine - INFO - Epoch(train) [11][7050/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:33:53 time: 0.5227 data_time: 0.0505 memory: 6260 grad_norm: 3.5291 loss: 0.7279 loss_rpn_cls: 0.0205 loss_rpn_bbox: 0.0383 loss_cls: 0.1868 acc: 88.8672 loss_bbox: 0.2384 loss_mask: 0.2439 +2024/10/28 15:15:15 - mmengine - INFO - Epoch(train) [11][7100/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:33:15 time: 0.5102 data_time: 0.0529 memory: 6369 grad_norm: 3.3495 loss: 0.7041 loss_rpn_cls: 0.0199 loss_rpn_bbox: 0.0407 loss_cls: 0.1779 acc: 96.2402 loss_bbox: 0.2288 loss_mask: 0.2367 +2024/10/28 15:15:40 - mmengine - INFO - Epoch(train) [11][7150/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:32:37 time: 0.5056 data_time: 0.0514 memory: 6194 grad_norm: 3.3434 loss: 0.6746 loss_rpn_cls: 0.0220 loss_rpn_bbox: 0.0396 loss_cls: 0.1670 acc: 97.2168 loss_bbox: 0.2130 loss_mask: 0.2330 +2024/10/28 15:16:05 - mmengine - INFO - Epoch(train) [11][7200/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:31:59 time: 0.4995 data_time: 0.0512 memory: 6178 grad_norm: 3.3231 loss: 0.6867 loss_rpn_cls: 0.0203 loss_rpn_bbox: 0.0395 loss_cls: 0.1743 acc: 96.1426 loss_bbox: 0.2206 loss_mask: 0.2320 +2024/10/28 15:16:32 - mmengine - INFO - Epoch(train) [11][7250/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:31:21 time: 0.5364 data_time: 0.0767 memory: 6284 grad_norm: 3.3444 loss: 0.6863 loss_rpn_cls: 0.0214 loss_rpn_bbox: 0.0408 loss_cls: 0.1725 acc: 90.9180 loss_bbox: 0.2194 loss_mask: 0.2321 +2024/10/28 15:16:57 - mmengine - INFO - Epoch(train) [11][7300/7330] base_lr: 5.0000e-05 lr: 5.0000e-05 eta: 1:30:43 time: 0.4966 data_time: 0.0522 memory: 6135 grad_norm: 3.1908 loss: 0.6729 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0391 loss_cls: 0.1733 acc: 91.4062 loss_bbox: 0.2122 loss_mask: 0.2297 +2024/10/28 15:17:12 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 15:17:12 - mmengine - INFO - Saving checkpoint at 11 epochs +2024/10/28 15:17:23 - mmengine - INFO - Epoch(val) [11][ 50/1250] eta: 0:02:12 time: 0.1108 data_time: 0.0055 memory: 8016 +2024/10/28 15:17:28 - mmengine - INFO - Epoch(val) [11][ 100/1250] eta: 0:02:04 time: 0.1063 data_time: 0.0034 memory: 1114 +2024/10/28 15:17:34 - mmengine - INFO - Epoch(val) [11][ 150/1250] eta: 0:01:58 time: 0.1071 data_time: 0.0037 memory: 1108 +2024/10/28 15:17:39 - mmengine - INFO - Epoch(val) [11][ 200/1250] eta: 0:01:54 time: 0.1123 data_time: 0.0055 memory: 1114 +2024/10/28 15:17:45 - mmengine - INFO - Epoch(val) [11][ 250/1250] eta: 0:01:48 time: 0.1057 data_time: 0.0039 memory: 1221 +2024/10/28 15:17:50 - mmengine - INFO - Epoch(val) [11][ 300/1250] eta: 0:01:42 time: 0.1062 data_time: 0.0044 memory: 1114 +2024/10/28 15:17:55 - mmengine - INFO - Epoch(val) [11][ 350/1250] eta: 0:01:36 time: 0.1046 data_time: 0.0034 memory: 1061 +2024/10/28 15:18:00 - mmengine - INFO - Epoch(val) [11][ 400/1250] eta: 0:01:30 time: 0.1035 data_time: 0.0035 memory: 1114 +2024/10/28 15:18:06 - mmengine - INFO - Epoch(val) [11][ 450/1250] eta: 0:01:25 time: 0.1042 data_time: 0.0033 memory: 1114 +2024/10/28 15:18:11 - mmengine - INFO - Epoch(val) [11][ 500/1250] eta: 0:01:19 time: 0.1058 data_time: 0.0038 memory: 1134 +2024/10/28 15:18:16 - mmengine - INFO - Epoch(val) [11][ 550/1250] eta: 0:01:14 time: 0.1048 data_time: 0.0034 memory: 1166 +2024/10/28 15:18:22 - mmengine - INFO - Epoch(val) [11][ 600/1250] eta: 0:01:09 time: 0.1102 data_time: 0.0049 memory: 1114 +2024/10/28 15:18:27 - mmengine - INFO - Epoch(val) [11][ 650/1250] eta: 0:01:04 time: 0.1058 data_time: 0.0040 memory: 1114 +2024/10/28 15:18:32 - mmengine - INFO - Epoch(val) [11][ 700/1250] eta: 0:00:58 time: 0.1089 data_time: 0.0042 memory: 1082 +2024/10/28 15:18:38 - mmengine - INFO - Epoch(val) [11][ 750/1250] eta: 0:00:53 time: 0.1114 data_time: 0.0050 memory: 1082 +2024/10/28 15:18:43 - mmengine - INFO - Epoch(val) [11][ 800/1250] eta: 0:00:48 time: 0.1079 data_time: 0.0041 memory: 1114 +2024/10/28 15:18:49 - mmengine - INFO - Epoch(val) [11][ 850/1250] eta: 0:00:42 time: 0.1074 data_time: 0.0038 memory: 1084 +2024/10/28 15:18:54 - mmengine - INFO - Epoch(val) [11][ 900/1250] eta: 0:00:37 time: 0.1066 data_time: 0.0031 memory: 1080 +2024/10/28 15:19:00 - mmengine - INFO - Epoch(val) [11][ 950/1250] eta: 0:00:32 time: 0.1126 data_time: 0.0053 memory: 1165 +2024/10/28 15:19:05 - mmengine - INFO - Epoch(val) [11][1000/1250] eta: 0:00:26 time: 0.1056 data_time: 0.0037 memory: 1034 +2024/10/28 15:19:11 - mmengine - INFO - Epoch(val) [11][1050/1250] eta: 0:00:21 time: 0.1122 data_time: 0.0052 memory: 1114 +2024/10/28 15:19:16 - mmengine - INFO - Epoch(val) [11][1100/1250] eta: 0:00:16 time: 0.1132 data_time: 0.0034 memory: 1114 +2024/10/28 15:19:22 - mmengine - INFO - Epoch(val) [11][1150/1250] eta: 0:00:10 time: 0.1103 data_time: 0.0063 memory: 1114 +2024/10/28 15:19:27 - mmengine - INFO - Epoch(val) [11][1200/1250] eta: 0:00:05 time: 0.1059 data_time: 0.0042 memory: 1114 +2024/10/28 15:19:32 - mmengine - INFO - Epoch(val) [11][1250/1250] eta: 0:00:00 time: 0.1051 data_time: 0.0044 memory: 1114 +2024/10/28 15:19:41 - mmengine - INFO - Evaluating bbox... +2024/10/28 15:20:08 - mmengine - INFO - bbox_mAP_copypaste: 0.400 0.611 0.432 0.218 0.431 0.543 +2024/10/28 15:20:08 - mmengine - INFO - Evaluating segm... +2024/10/28 15:20:41 - mmengine - INFO - segm_mAP_copypaste: 0.367 0.582 0.390 0.162 0.396 0.552 +2024/10/28 15:20:42 - mmengine - INFO - Epoch(val) [11][1250/1250] coco/bbox_mAP: 0.4000 coco/bbox_mAP_50: 0.6110 coco/bbox_mAP_75: 0.4320 coco/bbox_mAP_s: 0.2180 coco/bbox_mAP_m: 0.4310 coco/bbox_mAP_l: 0.5430 coco/segm_mAP: 0.3670 coco/segm_mAP_50: 0.5820 coco/segm_mAP_75: 0.3900 coco/segm_mAP_s: 0.1620 coco/segm_mAP_m: 0.3960 coco/segm_mAP_l: 0.5520 data_time: 0.0042 time: 0.1078 +2024/10/28 15:21:36 - mmengine - INFO - Epoch(train) [12][ 50/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:29:44 time: 1.0910 data_time: 0.0431 memory: 6266 grad_norm: 2.9718 loss: 0.6048 loss_rpn_cls: 0.0135 loss_rpn_bbox: 0.0361 loss_cls: 0.1511 acc: 92.5293 loss_bbox: 0.1929 loss_mask: 0.2112 +2024/10/28 15:22:28 - mmengine - INFO - Epoch(train) [12][ 100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:29:09 time: 1.0244 data_time: 0.0389 memory: 6211 grad_norm: 3.1787 loss: 0.5675 loss_rpn_cls: 0.0149 loss_rpn_bbox: 0.0312 loss_cls: 0.1359 acc: 95.4102 loss_bbox: 0.1773 loss_mask: 0.2081 +2024/10/28 15:23:19 - mmengine - INFO - Epoch(train) [12][ 150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:28:33 time: 1.0296 data_time: 0.0405 memory: 6229 grad_norm: 3.0186 loss: 0.6142 loss_rpn_cls: 0.0143 loss_rpn_bbox: 0.0318 loss_cls: 0.1414 acc: 93.8477 loss_bbox: 0.1979 loss_mask: 0.2287 +2024/10/28 15:24:11 - mmengine - INFO - Epoch(train) [12][ 200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:27:57 time: 1.0302 data_time: 0.0386 memory: 6343 grad_norm: 3.2038 loss: 0.6415 loss_rpn_cls: 0.0164 loss_rpn_bbox: 0.0358 loss_cls: 0.1546 acc: 97.4121 loss_bbox: 0.2052 loss_mask: 0.2296 +2024/10/28 15:25:02 - mmengine - INFO - Epoch(train) [12][ 250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:27:22 time: 1.0274 data_time: 0.0490 memory: 6233 grad_norm: 2.9647 loss: 0.6593 loss_rpn_cls: 0.0180 loss_rpn_bbox: 0.0384 loss_cls: 0.1631 acc: 93.6523 loss_bbox: 0.2127 loss_mask: 0.2270 +2024/10/28 15:25:55 - mmengine - INFO - Epoch(train) [12][ 300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:26:46 time: 1.0518 data_time: 0.1252 memory: 6231 grad_norm: 3.0535 loss: 0.6231 loss_rpn_cls: 0.0141 loss_rpn_bbox: 0.0352 loss_cls: 0.1489 acc: 98.6328 loss_bbox: 0.2025 loss_mask: 0.2224 +2024/10/28 15:26:44 - mmengine - INFO - Epoch(train) [12][ 350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:26:10 time: 0.9875 data_time: 0.0468 memory: 6139 grad_norm: 3.0769 loss: 0.6759 loss_rpn_cls: 0.0201 loss_rpn_bbox: 0.0401 loss_cls: 0.1700 acc: 94.9707 loss_bbox: 0.2169 loss_mask: 0.2289 +2024/10/28 15:27:04 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 15:27:34 - mmengine - INFO - Epoch(train) [12][ 400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:25:34 time: 1.0078 data_time: 0.0453 memory: 6363 grad_norm: 3.0551 loss: 0.6309 loss_rpn_cls: 0.0163 loss_rpn_bbox: 0.0311 loss_cls: 0.1616 acc: 95.3125 loss_bbox: 0.2031 loss_mask: 0.2189 +2024/10/28 15:28:24 - mmengine - INFO - Epoch(train) [12][ 450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:24:58 time: 0.9976 data_time: 0.0397 memory: 6315 grad_norm: 2.8788 loss: 0.5842 loss_rpn_cls: 0.0134 loss_rpn_bbox: 0.0312 loss_cls: 0.1413 acc: 92.7734 loss_bbox: 0.1887 loss_mask: 0.2096 +2024/10/28 15:29:17 - mmengine - INFO - Epoch(train) [12][ 500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:24:22 time: 1.0656 data_time: 0.0432 memory: 6289 grad_norm: 3.0895 loss: 0.6747 loss_rpn_cls: 0.0168 loss_rpn_bbox: 0.0370 loss_cls: 0.1654 acc: 93.5547 loss_bbox: 0.2182 loss_mask: 0.2373 +2024/10/28 15:30:08 - mmengine - INFO - Epoch(train) [12][ 550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:23:46 time: 1.0009 data_time: 0.0411 memory: 6266 grad_norm: 3.1241 loss: 0.5871 loss_rpn_cls: 0.0118 loss_rpn_bbox: 0.0297 loss_cls: 0.1483 acc: 92.3340 loss_bbox: 0.1865 loss_mask: 0.2108 +2024/10/28 15:31:00 - mmengine - INFO - Epoch(train) [12][ 600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:23:11 time: 1.0516 data_time: 0.0459 memory: 6107 grad_norm: 3.0172 loss: 0.6311 loss_rpn_cls: 0.0191 loss_rpn_bbox: 0.0378 loss_cls: 0.1578 acc: 95.3613 loss_bbox: 0.2016 loss_mask: 0.2147 +2024/10/28 15:31:46 - mmengine - INFO - Epoch(train) [12][ 650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:22:34 time: 0.9234 data_time: 0.0444 memory: 6218 grad_norm: 3.0034 loss: 0.6617 loss_rpn_cls: 0.0182 loss_rpn_bbox: 0.0360 loss_cls: 0.1680 acc: 95.7520 loss_bbox: 0.2116 loss_mask: 0.2280 +2024/10/28 15:32:34 - mmengine - INFO - Epoch(train) [12][ 700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:21:58 time: 0.9489 data_time: 0.0401 memory: 6420 grad_norm: 3.0085 loss: 0.6201 loss_rpn_cls: 0.0143 loss_rpn_bbox: 0.0310 loss_cls: 0.1528 acc: 93.7988 loss_bbox: 0.2003 loss_mask: 0.2217 +2024/10/28 15:33:22 - mmengine - INFO - Epoch(train) [12][ 750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:21:22 time: 0.9674 data_time: 0.0479 memory: 6232 grad_norm: 3.0507 loss: 0.6426 loss_rpn_cls: 0.0177 loss_rpn_bbox: 0.0399 loss_cls: 0.1655 acc: 93.3594 loss_bbox: 0.2055 loss_mask: 0.2142 +2024/10/28 15:34:18 - mmengine - INFO - Epoch(train) [12][ 800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:20:46 time: 1.1213 data_time: 0.0495 memory: 6262 grad_norm: 3.1891 loss: 0.6909 loss_rpn_cls: 0.0191 loss_rpn_bbox: 0.0416 loss_cls: 0.1785 acc: 95.4590 loss_bbox: 0.2230 loss_mask: 0.2286 +2024/10/28 15:35:09 - mmengine - INFO - Epoch(train) [12][ 850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:20:10 time: 1.0133 data_time: 0.0498 memory: 6329 grad_norm: 3.0766 loss: 0.6683 loss_rpn_cls: 0.0214 loss_rpn_bbox: 0.0404 loss_cls: 0.1680 acc: 93.6523 loss_bbox: 0.2123 loss_mask: 0.2262 +2024/10/28 15:36:02 - mmengine - INFO - Epoch(train) [12][ 900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:19:34 time: 1.0679 data_time: 0.0467 memory: 6388 grad_norm: 3.1286 loss: 0.6094 loss_rpn_cls: 0.0139 loss_rpn_bbox: 0.0335 loss_cls: 0.1448 acc: 95.3125 loss_bbox: 0.1977 loss_mask: 0.2195 +2024/10/28 15:36:56 - mmengine - INFO - Epoch(train) [12][ 950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:18:59 time: 1.0841 data_time: 0.1240 memory: 6197 grad_norm: 3.1069 loss: 0.6445 loss_rpn_cls: 0.0187 loss_rpn_bbox: 0.0379 loss_cls: 0.1613 acc: 98.1934 loss_bbox: 0.2118 loss_mask: 0.2148 +2024/10/28 15:37:48 - mmengine - INFO - Epoch(train) [12][1000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:18:23 time: 1.0370 data_time: 0.0552 memory: 6196 grad_norm: 3.0615 loss: 0.6881 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0401 loss_cls: 0.1659 acc: 97.6562 loss_bbox: 0.2253 loss_mask: 0.2401 +2024/10/28 15:38:38 - mmengine - INFO - Epoch(train) [12][1050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:17:46 time: 1.0014 data_time: 0.0621 memory: 6142 grad_norm: 3.0809 loss: 0.6671 loss_rpn_cls: 0.0201 loss_rpn_bbox: 0.0408 loss_cls: 0.1610 acc: 95.0195 loss_bbox: 0.2168 loss_mask: 0.2285 +2024/10/28 15:39:26 - mmengine - INFO - Epoch(train) [12][1100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:17:10 time: 0.9575 data_time: 0.0450 memory: 6232 grad_norm: 3.1250 loss: 0.6137 loss_rpn_cls: 0.0146 loss_rpn_bbox: 0.0319 loss_cls: 0.1553 acc: 90.6738 loss_bbox: 0.1880 loss_mask: 0.2239 +2024/10/28 15:40:16 - mmengine - INFO - Epoch(train) [12][1150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:16:34 time: 0.9914 data_time: 0.0460 memory: 6323 grad_norm: 3.0114 loss: 0.6085 loss_rpn_cls: 0.0153 loss_rpn_bbox: 0.0348 loss_cls: 0.1437 acc: 92.3828 loss_bbox: 0.1963 loss_mask: 0.2184 +2024/10/28 15:41:08 - mmengine - INFO - Epoch(train) [12][1200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:15:58 time: 1.0468 data_time: 0.0498 memory: 6276 grad_norm: 3.2563 loss: 0.6098 loss_rpn_cls: 0.0157 loss_rpn_bbox: 0.0351 loss_cls: 0.1460 acc: 92.2852 loss_bbox: 0.1929 loss_mask: 0.2201 +2024/10/28 15:42:00 - mmengine - INFO - Epoch(train) [12][1250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:15:22 time: 1.0284 data_time: 0.0570 memory: 6192 grad_norm: 3.1102 loss: 0.6515 loss_rpn_cls: 0.0157 loss_rpn_bbox: 0.0366 loss_cls: 0.1562 acc: 94.9707 loss_bbox: 0.2124 loss_mask: 0.2305 +2024/10/28 15:42:48 - mmengine - INFO - Epoch(train) [12][1300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:14:45 time: 0.9668 data_time: 0.0482 memory: 6301 grad_norm: 3.1925 loss: 0.6101 loss_rpn_cls: 0.0176 loss_rpn_bbox: 0.0355 loss_cls: 0.1489 acc: 95.3125 loss_bbox: 0.1933 loss_mask: 0.2147 +2024/10/28 15:43:37 - mmengine - INFO - Epoch(train) [12][1350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:14:09 time: 0.9811 data_time: 0.0436 memory: 6067 grad_norm: 3.0737 loss: 0.5702 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0343 loss_cls: 0.1318 acc: 93.5547 loss_bbox: 0.1766 loss_mask: 0.2108 +2024/10/28 15:43:58 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 15:44:28 - mmengine - INFO - Epoch(train) [12][1400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:13:33 time: 1.0228 data_time: 0.0540 memory: 6257 grad_norm: 3.1420 loss: 0.6608 loss_rpn_cls: 0.0171 loss_rpn_bbox: 0.0390 loss_cls: 0.1609 acc: 96.9727 loss_bbox: 0.2170 loss_mask: 0.2267 +2024/10/28 15:45:18 - mmengine - INFO - Epoch(train) [12][1450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:12:56 time: 0.9927 data_time: 0.0477 memory: 6420 grad_norm: 3.2119 loss: 0.6528 loss_rpn_cls: 0.0176 loss_rpn_bbox: 0.0354 loss_cls: 0.1507 acc: 95.8984 loss_bbox: 0.2141 loss_mask: 0.2351 +2024/10/28 15:46:09 - mmengine - INFO - Epoch(train) [12][1500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:12:20 time: 1.0163 data_time: 0.0439 memory: 6126 grad_norm: 3.2188 loss: 0.5972 loss_rpn_cls: 0.0128 loss_rpn_bbox: 0.0342 loss_cls: 0.1418 acc: 97.7539 loss_bbox: 0.1905 loss_mask: 0.2180 +2024/10/28 15:47:00 - mmengine - INFO - Epoch(train) [12][1550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:11:44 time: 1.0286 data_time: 0.0470 memory: 6343 grad_norm: 3.2498 loss: 0.6298 loss_rpn_cls: 0.0148 loss_rpn_bbox: 0.0329 loss_cls: 0.1543 acc: 93.9453 loss_bbox: 0.2088 loss_mask: 0.2190 +2024/10/28 15:47:52 - mmengine - INFO - Epoch(train) [12][1600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:11:08 time: 1.0433 data_time: 0.0450 memory: 6271 grad_norm: 3.0959 loss: 0.6176 loss_rpn_cls: 0.0159 loss_rpn_bbox: 0.0369 loss_cls: 0.1502 acc: 94.2871 loss_bbox: 0.1959 loss_mask: 0.2187 +2024/10/28 15:48:44 - mmengine - INFO - Epoch(train) [12][1650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:10:32 time: 1.0312 data_time: 0.0543 memory: 6274 grad_norm: 3.1827 loss: 0.6609 loss_rpn_cls: 0.0189 loss_rpn_bbox: 0.0381 loss_cls: 0.1641 acc: 91.2598 loss_bbox: 0.2117 loss_mask: 0.2280 +2024/10/28 15:49:33 - mmengine - INFO - Epoch(train) [12][1700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:09:55 time: 0.9873 data_time: 0.0451 memory: 6318 grad_norm: 3.0997 loss: 0.6205 loss_rpn_cls: 0.0153 loss_rpn_bbox: 0.0351 loss_cls: 0.1479 acc: 94.7754 loss_bbox: 0.1999 loss_mask: 0.2223 +2024/10/28 15:50:25 - mmengine - INFO - Epoch(train) [12][1750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:09:19 time: 1.0403 data_time: 0.0447 memory: 6276 grad_norm: 3.0944 loss: 0.6418 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0361 loss_cls: 0.1628 acc: 97.5098 loss_bbox: 0.2083 loss_mask: 0.2160 +2024/10/28 15:51:19 - mmengine - INFO - Epoch(train) [12][1800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:08:43 time: 1.0746 data_time: 0.0645 memory: 6331 grad_norm: 3.1088 loss: 0.6502 loss_rpn_cls: 0.0169 loss_rpn_bbox: 0.0378 loss_cls: 0.1585 acc: 95.4590 loss_bbox: 0.2108 loss_mask: 0.2263 +2024/10/28 15:52:11 - mmengine - INFO - Epoch(train) [12][1850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:08:06 time: 1.0441 data_time: 0.0544 memory: 6229 grad_norm: 2.9979 loss: 0.6490 loss_rpn_cls: 0.0172 loss_rpn_bbox: 0.0381 loss_cls: 0.1607 acc: 94.4824 loss_bbox: 0.2116 loss_mask: 0.2213 +2024/10/28 15:53:03 - mmengine - INFO - Epoch(train) [12][1900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:07:30 time: 1.0435 data_time: 0.0527 memory: 6385 grad_norm: 3.1270 loss: 0.6334 loss_rpn_cls: 0.0151 loss_rpn_bbox: 0.0351 loss_cls: 0.1648 acc: 97.0703 loss_bbox: 0.1997 loss_mask: 0.2187 +2024/10/28 15:53:57 - mmengine - INFO - Epoch(train) [12][1950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:06:54 time: 1.0827 data_time: 0.0876 memory: 6182 grad_norm: 3.1484 loss: 0.6691 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0381 loss_cls: 0.1705 acc: 92.0410 loss_bbox: 0.2146 loss_mask: 0.2284 +2024/10/28 15:54:46 - mmengine - INFO - Epoch(train) [12][2000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:06:17 time: 0.9782 data_time: 0.0521 memory: 6280 grad_norm: 3.1858 loss: 0.6642 loss_rpn_cls: 0.0156 loss_rpn_bbox: 0.0395 loss_cls: 0.1634 acc: 96.4844 loss_bbox: 0.2223 loss_mask: 0.2235 +2024/10/28 15:55:36 - mmengine - INFO - Epoch(train) [12][2050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:05:41 time: 0.9986 data_time: 0.0523 memory: 6170 grad_norm: 3.0958 loss: 0.6559 loss_rpn_cls: 0.0177 loss_rpn_bbox: 0.0394 loss_cls: 0.1615 acc: 93.7500 loss_bbox: 0.2156 loss_mask: 0.2217 +2024/10/28 15:56:29 - mmengine - INFO - Epoch(train) [12][2100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:05:04 time: 1.0446 data_time: 0.0426 memory: 6184 grad_norm: 2.9955 loss: 0.5738 loss_rpn_cls: 0.0115 loss_rpn_bbox: 0.0303 loss_cls: 0.1359 acc: 92.6758 loss_bbox: 0.1786 loss_mask: 0.2176 +2024/10/28 15:57:19 - mmengine - INFO - Epoch(train) [12][2150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:04:28 time: 0.9997 data_time: 0.0577 memory: 6174 grad_norm: 3.1503 loss: 0.6550 loss_rpn_cls: 0.0164 loss_rpn_bbox: 0.0387 loss_cls: 0.1668 acc: 94.4824 loss_bbox: 0.2164 loss_mask: 0.2168 +2024/10/28 15:58:12 - mmengine - INFO - Epoch(train) [12][2200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:03:52 time: 1.0778 data_time: 0.0557 memory: 6242 grad_norm: 3.1463 loss: 0.6607 loss_rpn_cls: 0.0185 loss_rpn_bbox: 0.0378 loss_cls: 0.1682 acc: 92.3828 loss_bbox: 0.2057 loss_mask: 0.2305 +2024/10/28 15:59:07 - mmengine - INFO - Epoch(train) [12][2250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:03:15 time: 1.0898 data_time: 0.0562 memory: 6403 grad_norm: 3.1433 loss: 0.6774 loss_rpn_cls: 0.0165 loss_rpn_bbox: 0.0399 loss_cls: 0.1644 acc: 96.6309 loss_bbox: 0.2287 loss_mask: 0.2279 +2024/10/28 16:00:00 - mmengine - INFO - Epoch(train) [12][2300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:02:39 time: 1.0550 data_time: 0.0528 memory: 6330 grad_norm: 3.0617 loss: 0.6672 loss_rpn_cls: 0.0174 loss_rpn_bbox: 0.0367 loss_cls: 0.1669 acc: 99.0234 loss_bbox: 0.2189 loss_mask: 0.2273 +2024/10/28 16:00:49 - mmengine - INFO - Epoch(train) [12][2350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:02:02 time: 0.9806 data_time: 0.0392 memory: 6337 grad_norm: 3.0967 loss: 0.5956 loss_rpn_cls: 0.0135 loss_rpn_bbox: 0.0315 loss_cls: 0.1415 acc: 94.1895 loss_bbox: 0.1916 loss_mask: 0.2176 +2024/10/28 16:01:08 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 16:01:37 - mmengine - INFO - Epoch(train) [12][2400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:01:25 time: 0.9714 data_time: 0.0421 memory: 6115 grad_norm: 3.0490 loss: 0.6081 loss_rpn_cls: 0.0154 loss_rpn_bbox: 0.0344 loss_cls: 0.1474 acc: 92.4316 loss_bbox: 0.1938 loss_mask: 0.2172 +2024/10/28 16:02:28 - mmengine - INFO - Epoch(train) [12][2450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:00:49 time: 1.0098 data_time: 0.0546 memory: 6141 grad_norm: 3.0253 loss: 0.6172 loss_rpn_cls: 0.0157 loss_rpn_bbox: 0.0361 loss_cls: 0.1487 acc: 97.4609 loss_bbox: 0.1926 loss_mask: 0.2241 +2024/10/28 16:03:18 - mmengine - INFO - Epoch(train) [12][2500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 1:00:12 time: 0.9950 data_time: 0.0491 memory: 6219 grad_norm: 3.1389 loss: 0.6167 loss_rpn_cls: 0.0162 loss_rpn_bbox: 0.0338 loss_cls: 0.1501 acc: 92.1875 loss_bbox: 0.2006 loss_mask: 0.2160 +2024/10/28 16:04:09 - mmengine - INFO - Epoch(train) [12][2550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:59:36 time: 1.0265 data_time: 0.0423 memory: 6389 grad_norm: 3.2066 loss: 0.6407 loss_rpn_cls: 0.0149 loss_rpn_bbox: 0.0359 loss_cls: 0.1575 acc: 94.4824 loss_bbox: 0.2034 loss_mask: 0.2288 +2024/10/28 16:04:59 - mmengine - INFO - Epoch(train) [12][2600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:58:59 time: 0.9974 data_time: 0.0463 memory: 6312 grad_norm: 3.1723 loss: 0.6470 loss_rpn_cls: 0.0155 loss_rpn_bbox: 0.0360 loss_cls: 0.1559 acc: 95.2637 loss_bbox: 0.2172 loss_mask: 0.2224 +2024/10/28 16:05:47 - mmengine - INFO - Epoch(train) [12][2650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:58:22 time: 0.9642 data_time: 0.0502 memory: 6180 grad_norm: 3.1267 loss: 0.6440 loss_rpn_cls: 0.0165 loss_rpn_bbox: 0.0329 loss_cls: 0.1626 acc: 95.0195 loss_bbox: 0.2081 loss_mask: 0.2240 +2024/10/28 16:06:40 - mmengine - INFO - Epoch(train) [12][2700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:57:46 time: 1.0620 data_time: 0.0559 memory: 6361 grad_norm: 3.0521 loss: 0.6457 loss_rpn_cls: 0.0174 loss_rpn_bbox: 0.0360 loss_cls: 0.1598 acc: 92.0410 loss_bbox: 0.2089 loss_mask: 0.2236 +2024/10/28 16:07:27 - mmengine - INFO - Epoch(train) [12][2750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:57:09 time: 0.9418 data_time: 0.0452 memory: 6260 grad_norm: 3.0104 loss: 0.6196 loss_rpn_cls: 0.0157 loss_rpn_bbox: 0.0324 loss_cls: 0.1481 acc: 97.0703 loss_bbox: 0.1957 loss_mask: 0.2277 +2024/10/28 16:08:17 - mmengine - INFO - Epoch(train) [12][2800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:56:32 time: 0.9881 data_time: 0.0577 memory: 6241 grad_norm: 3.0324 loss: 0.6362 loss_rpn_cls: 0.0161 loss_rpn_bbox: 0.0364 loss_cls: 0.1579 acc: 89.2578 loss_bbox: 0.2088 loss_mask: 0.2169 +2024/10/28 16:09:07 - mmengine - INFO - Epoch(train) [12][2850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:55:55 time: 1.0087 data_time: 0.0540 memory: 6172 grad_norm: 3.1250 loss: 0.6219 loss_rpn_cls: 0.0157 loss_rpn_bbox: 0.0346 loss_cls: 0.1507 acc: 96.3379 loss_bbox: 0.2009 loss_mask: 0.2200 +2024/10/28 16:09:55 - mmengine - INFO - Epoch(train) [12][2900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:55:18 time: 0.9652 data_time: 0.0490 memory: 6269 grad_norm: 3.0829 loss: 0.6288 loss_rpn_cls: 0.0153 loss_rpn_bbox: 0.0346 loss_cls: 0.1520 acc: 90.5762 loss_bbox: 0.2082 loss_mask: 0.2188 +2024/10/28 16:10:48 - mmengine - INFO - Epoch(train) [12][2950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:54:42 time: 1.0484 data_time: 0.0547 memory: 6256 grad_norm: 3.1946 loss: 0.6503 loss_rpn_cls: 0.0160 loss_rpn_bbox: 0.0392 loss_cls: 0.1599 acc: 89.6973 loss_bbox: 0.2096 loss_mask: 0.2257 +2024/10/28 16:11:37 - mmengine - INFO - Epoch(train) [12][3000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:54:05 time: 0.9919 data_time: 0.0557 memory: 6192 grad_norm: 3.1253 loss: 0.6874 loss_rpn_cls: 0.0179 loss_rpn_bbox: 0.0425 loss_cls: 0.1694 acc: 95.9473 loss_bbox: 0.2264 loss_mask: 0.2313 +2024/10/28 16:12:25 - mmengine - INFO - Epoch(train) [12][3050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:53:28 time: 0.9530 data_time: 0.0499 memory: 6259 grad_norm: 3.2275 loss: 0.6457 loss_rpn_cls: 0.0158 loss_rpn_bbox: 0.0371 loss_cls: 0.1560 acc: 94.2383 loss_bbox: 0.2043 loss_mask: 0.2325 +2024/10/28 16:13:15 - mmengine - INFO - Epoch(train) [12][3100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:52:51 time: 0.9917 data_time: 0.0594 memory: 6192 grad_norm: 3.2394 loss: 0.6792 loss_rpn_cls: 0.0193 loss_rpn_bbox: 0.0385 loss_cls: 0.1685 acc: 93.6523 loss_bbox: 0.2259 loss_mask: 0.2269 +2024/10/28 16:14:04 - mmengine - INFO - Epoch(train) [12][3150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:52:14 time: 0.9931 data_time: 0.0531 memory: 6261 grad_norm: 3.0337 loss: 0.6512 loss_rpn_cls: 0.0183 loss_rpn_bbox: 0.0399 loss_cls: 0.1572 acc: 93.4082 loss_bbox: 0.2116 loss_mask: 0.2241 +2024/10/28 16:14:50 - mmengine - INFO - Epoch(train) [12][3200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:51:37 time: 0.9231 data_time: 0.0507 memory: 6241 grad_norm: 3.1390 loss: 0.5825 loss_rpn_cls: 0.0116 loss_rpn_bbox: 0.0295 loss_cls: 0.1416 acc: 95.2637 loss_bbox: 0.1893 loss_mask: 0.2105 +2024/10/28 16:15:41 - mmengine - INFO - Epoch(train) [12][3250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:51:00 time: 1.0046 data_time: 0.0554 memory: 6371 grad_norm: 3.0930 loss: 0.6165 loss_rpn_cls: 0.0173 loss_rpn_bbox: 0.0355 loss_cls: 0.1533 acc: 97.0215 loss_bbox: 0.1991 loss_mask: 0.2113 +2024/10/28 16:16:33 - mmengine - INFO - Epoch(train) [12][3300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:50:23 time: 1.0383 data_time: 0.0489 memory: 6251 grad_norm: 3.1159 loss: 0.6113 loss_rpn_cls: 0.0150 loss_rpn_bbox: 0.0357 loss_cls: 0.1429 acc: 94.0918 loss_bbox: 0.1986 loss_mask: 0.2192 +2024/10/28 16:17:20 - mmengine - INFO - Epoch(train) [12][3350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:49:46 time: 0.9392 data_time: 0.0534 memory: 6286 grad_norm: 3.0505 loss: 0.6331 loss_rpn_cls: 0.0182 loss_rpn_bbox: 0.0361 loss_cls: 0.1498 acc: 91.8457 loss_bbox: 0.1962 loss_mask: 0.2328 +2024/10/28 16:17:40 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 16:18:11 - mmengine - INFO - Epoch(train) [12][3400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:49:09 time: 1.0238 data_time: 0.0519 memory: 6291 grad_norm: 3.0695 loss: 0.6168 loss_rpn_cls: 0.0151 loss_rpn_bbox: 0.0348 loss_cls: 0.1482 acc: 94.5801 loss_bbox: 0.1986 loss_mask: 0.2201 +2024/10/28 16:19:02 - mmengine - INFO - Epoch(train) [12][3450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:48:32 time: 1.0342 data_time: 0.0642 memory: 6286 grad_norm: 3.2182 loss: 0.6564 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0353 loss_cls: 0.1640 acc: 93.8477 loss_bbox: 0.2080 loss_mask: 0.2326 +2024/10/28 16:19:55 - mmengine - INFO - Epoch(train) [12][3500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:47:56 time: 1.0480 data_time: 0.1029 memory: 6347 grad_norm: 3.1508 loss: 0.6688 loss_rpn_cls: 0.0206 loss_rpn_bbox: 0.0368 loss_cls: 0.1663 acc: 96.6309 loss_bbox: 0.2165 loss_mask: 0.2284 +2024/10/28 16:20:42 - mmengine - INFO - Epoch(train) [12][3550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:47:18 time: 0.9364 data_time: 0.0534 memory: 6303 grad_norm: 3.0708 loss: 0.6292 loss_rpn_cls: 0.0159 loss_rpn_bbox: 0.0393 loss_cls: 0.1548 acc: 97.1680 loss_bbox: 0.1987 loss_mask: 0.2204 +2024/10/28 16:21:33 - mmengine - INFO - Epoch(train) [12][3600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:46:41 time: 1.0221 data_time: 0.0582 memory: 6420 grad_norm: 3.2262 loss: 0.7036 loss_rpn_cls: 0.0193 loss_rpn_bbox: 0.0413 loss_cls: 0.1758 acc: 91.9434 loss_bbox: 0.2318 loss_mask: 0.2354 +2024/10/28 16:22:27 - mmengine - INFO - Epoch(train) [12][3650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:46:05 time: 1.0904 data_time: 0.0484 memory: 6367 grad_norm: 3.0900 loss: 0.5977 loss_rpn_cls: 0.0144 loss_rpn_bbox: 0.0361 loss_cls: 0.1447 acc: 98.8281 loss_bbox: 0.1909 loss_mask: 0.2116 +2024/10/28 16:23:19 - mmengine - INFO - Epoch(train) [12][3700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:45:28 time: 1.0368 data_time: 0.0462 memory: 6292 grad_norm: 3.0748 loss: 0.5687 loss_rpn_cls: 0.0127 loss_rpn_bbox: 0.0302 loss_cls: 0.1344 acc: 92.4805 loss_bbox: 0.1834 loss_mask: 0.2080 +2024/10/28 16:24:09 - mmengine - INFO - Epoch(train) [12][3750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:44:51 time: 0.9968 data_time: 0.0650 memory: 6356 grad_norm: 3.2608 loss: 0.6897 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0394 loss_cls: 0.1722 acc: 91.6016 loss_bbox: 0.2249 loss_mask: 0.2337 +2024/10/28 16:25:03 - mmengine - INFO - Epoch(train) [12][3800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:44:14 time: 1.0746 data_time: 0.0547 memory: 6264 grad_norm: 3.1840 loss: 0.6724 loss_rpn_cls: 0.0177 loss_rpn_bbox: 0.0370 loss_cls: 0.1689 acc: 96.3379 loss_bbox: 0.2196 loss_mask: 0.2292 +2024/10/28 16:25:56 - mmengine - INFO - Epoch(train) [12][3850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:43:37 time: 1.0625 data_time: 0.1040 memory: 6299 grad_norm: 3.1350 loss: 0.6628 loss_rpn_cls: 0.0181 loss_rpn_bbox: 0.0397 loss_cls: 0.1724 acc: 91.2598 loss_bbox: 0.2094 loss_mask: 0.2233 +2024/10/28 16:26:44 - mmengine - INFO - Epoch(train) [12][3900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:43:00 time: 0.9576 data_time: 0.0579 memory: 6386 grad_norm: 3.1695 loss: 0.6497 loss_rpn_cls: 0.0159 loss_rpn_bbox: 0.0356 loss_cls: 0.1559 acc: 94.9219 loss_bbox: 0.2149 loss_mask: 0.2274 +2024/10/28 16:27:30 - mmengine - INFO - Epoch(train) [12][3950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:42:22 time: 0.9217 data_time: 0.0487 memory: 6171 grad_norm: 2.9511 loss: 0.5967 loss_rpn_cls: 0.0136 loss_rpn_bbox: 0.0322 loss_cls: 0.1445 acc: 93.8965 loss_bbox: 0.1879 loss_mask: 0.2185 +2024/10/28 16:28:24 - mmengine - INFO - Epoch(train) [12][4000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:41:45 time: 1.0776 data_time: 0.0591 memory: 6337 grad_norm: 3.1605 loss: 0.6378 loss_rpn_cls: 0.0200 loss_rpn_bbox: 0.0371 loss_cls: 0.1543 acc: 94.9219 loss_bbox: 0.2056 loss_mask: 0.2208 +2024/10/28 16:29:14 - mmengine - INFO - Epoch(train) [12][4050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:41:08 time: 1.0042 data_time: 0.0511 memory: 6397 grad_norm: 3.1259 loss: 0.6446 loss_rpn_cls: 0.0195 loss_rpn_bbox: 0.0373 loss_cls: 0.1535 acc: 99.1699 loss_bbox: 0.2062 loss_mask: 0.2281 +2024/10/28 16:30:05 - mmengine - INFO - Epoch(train) [12][4100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:40:31 time: 1.0149 data_time: 0.0589 memory: 6419 grad_norm: 3.1192 loss: 0.6764 loss_rpn_cls: 0.0179 loss_rpn_bbox: 0.0419 loss_cls: 0.1680 acc: 92.2852 loss_bbox: 0.2233 loss_mask: 0.2253 +2024/10/28 16:30:56 - mmengine - INFO - Epoch(train) [12][4150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:39:54 time: 1.0162 data_time: 0.0782 memory: 6269 grad_norm: 3.1794 loss: 0.6992 loss_rpn_cls: 0.0169 loss_rpn_bbox: 0.0390 loss_cls: 0.1745 acc: 90.1367 loss_bbox: 0.2357 loss_mask: 0.2331 +2024/10/28 16:31:48 - mmengine - INFO - Epoch(train) [12][4200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:39:17 time: 1.0564 data_time: 0.0550 memory: 6264 grad_norm: 3.0746 loss: 0.6145 loss_rpn_cls: 0.0172 loss_rpn_bbox: 0.0336 loss_cls: 0.1472 acc: 91.1133 loss_bbox: 0.1963 loss_mask: 0.2202 +2024/10/28 16:32:39 - mmengine - INFO - Epoch(train) [12][4250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:38:40 time: 1.0191 data_time: 0.0492 memory: 6282 grad_norm: 3.0448 loss: 0.5980 loss_rpn_cls: 0.0144 loss_rpn_bbox: 0.0308 loss_cls: 0.1435 acc: 93.5547 loss_bbox: 0.1961 loss_mask: 0.2132 +2024/10/28 16:33:26 - mmengine - INFO - Epoch(train) [12][4300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:38:02 time: 0.9317 data_time: 0.0454 memory: 6302 grad_norm: 3.0661 loss: 0.6157 loss_rpn_cls: 0.0142 loss_rpn_bbox: 0.0318 loss_cls: 0.1511 acc: 91.1133 loss_bbox: 0.1960 loss_mask: 0.2226 +2024/10/28 16:34:12 - mmengine - INFO - Epoch(train) [12][4350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:37:25 time: 0.9283 data_time: 0.0520 memory: 6260 grad_norm: 3.1823 loss: 0.6340 loss_rpn_cls: 0.0166 loss_rpn_bbox: 0.0366 loss_cls: 0.1516 acc: 99.3652 loss_bbox: 0.2046 loss_mask: 0.2246 +2024/10/28 16:34:36 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 16:35:05 - mmengine - INFO - Epoch(train) [12][4400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:36:48 time: 1.0453 data_time: 0.0508 memory: 6269 grad_norm: 3.2172 loss: 0.6353 loss_rpn_cls: 0.0193 loss_rpn_bbox: 0.0369 loss_cls: 0.1527 acc: 94.7266 loss_bbox: 0.2069 loss_mask: 0.2195 +2024/10/28 16:35:57 - mmengine - INFO - Epoch(train) [12][4450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:36:11 time: 1.0534 data_time: 0.0731 memory: 6374 grad_norm: 3.2139 loss: 0.6472 loss_rpn_cls: 0.0164 loss_rpn_bbox: 0.0372 loss_cls: 0.1584 acc: 94.2871 loss_bbox: 0.2102 loss_mask: 0.2250 +2024/10/28 16:36:47 - mmengine - INFO - Epoch(train) [12][4500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:35:33 time: 0.9916 data_time: 0.0557 memory: 6304 grad_norm: 3.1004 loss: 0.6356 loss_rpn_cls: 0.0147 loss_rpn_bbox: 0.0357 loss_cls: 0.1528 acc: 95.8984 loss_bbox: 0.2099 loss_mask: 0.2226 +2024/10/28 16:37:35 - mmengine - INFO - Epoch(train) [12][4550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:34:56 time: 0.9674 data_time: 0.0511 memory: 6096 grad_norm: 3.1834 loss: 0.6280 loss_rpn_cls: 0.0171 loss_rpn_bbox: 0.0363 loss_cls: 0.1565 acc: 95.5566 loss_bbox: 0.2011 loss_mask: 0.2170 +2024/10/28 16:38:23 - mmengine - INFO - Epoch(train) [12][4600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:34:19 time: 0.9573 data_time: 0.0551 memory: 6221 grad_norm: 3.1879 loss: 0.5793 loss_rpn_cls: 0.0146 loss_rpn_bbox: 0.0340 loss_cls: 0.1388 acc: 96.3867 loss_bbox: 0.1789 loss_mask: 0.2130 +2024/10/28 16:39:13 - mmengine - INFO - Epoch(train) [12][4650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:33:41 time: 1.0014 data_time: 0.0582 memory: 6199 grad_norm: 3.3099 loss: 0.6781 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0426 loss_cls: 0.1692 acc: 94.8242 loss_bbox: 0.2169 loss_mask: 0.2316 +2024/10/28 16:40:04 - mmengine - INFO - Epoch(train) [12][4700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:33:04 time: 1.0081 data_time: 0.0492 memory: 6185 grad_norm: 3.1852 loss: 0.6494 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0379 loss_cls: 0.1549 acc: 95.7520 loss_bbox: 0.2080 loss_mask: 0.2308 +2024/10/28 16:41:00 - mmengine - INFO - Epoch(train) [12][4750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:32:27 time: 1.1346 data_time: 0.0919 memory: 6353 grad_norm: 3.2207 loss: 0.6660 loss_rpn_cls: 0.0148 loss_rpn_bbox: 0.0388 loss_cls: 0.1630 acc: 93.7012 loss_bbox: 0.2280 loss_mask: 0.2213 +2024/10/28 16:41:47 - mmengine - INFO - Epoch(train) [12][4800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:31:49 time: 0.9372 data_time: 0.0420 memory: 6233 grad_norm: 3.1342 loss: 0.6251 loss_rpn_cls: 0.0163 loss_rpn_bbox: 0.0339 loss_cls: 0.1525 acc: 94.9219 loss_bbox: 0.1973 loss_mask: 0.2251 +2024/10/28 16:42:34 - mmengine - INFO - Epoch(train) [12][4850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:31:12 time: 0.9330 data_time: 0.0411 memory: 6398 grad_norm: 3.0915 loss: 0.5924 loss_rpn_cls: 0.0127 loss_rpn_bbox: 0.0338 loss_cls: 0.1362 acc: 94.2383 loss_bbox: 0.1968 loss_mask: 0.2129 +2024/10/28 16:43:25 - mmengine - INFO - Epoch(train) [12][4900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:30:34 time: 1.0310 data_time: 0.0482 memory: 6420 grad_norm: 3.2062 loss: 0.6909 loss_rpn_cls: 0.0202 loss_rpn_bbox: 0.0421 loss_cls: 0.1697 acc: 96.7285 loss_bbox: 0.2236 loss_mask: 0.2352 +2024/10/28 16:44:10 - mmengine - INFO - Epoch(train) [12][4950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:29:57 time: 0.8983 data_time: 0.0421 memory: 6145 grad_norm: 3.1017 loss: 0.6520 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0396 loss_cls: 0.1586 acc: 97.1680 loss_bbox: 0.2105 loss_mask: 0.2266 +2024/10/28 16:45:01 - mmengine - INFO - Epoch(train) [12][5000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:29:19 time: 1.0085 data_time: 0.0481 memory: 6310 grad_norm: 3.1918 loss: 0.6534 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0371 loss_cls: 0.1577 acc: 96.6797 loss_bbox: 0.2120 loss_mask: 0.2298 +2024/10/28 16:45:48 - mmengine - INFO - Epoch(train) [12][5050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:28:42 time: 0.9493 data_time: 0.0510 memory: 6175 grad_norm: 3.1532 loss: 0.6396 loss_rpn_cls: 0.0162 loss_rpn_bbox: 0.0366 loss_cls: 0.1609 acc: 93.1152 loss_bbox: 0.2029 loss_mask: 0.2229 +2024/10/28 16:46:40 - mmengine - INFO - Epoch(train) [12][5100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:28:05 time: 1.0276 data_time: 0.0549 memory: 6339 grad_norm: 2.9382 loss: 0.6312 loss_rpn_cls: 0.0171 loss_rpn_bbox: 0.0372 loss_cls: 0.1548 acc: 94.4824 loss_bbox: 0.2021 loss_mask: 0.2199 +2024/10/28 16:47:33 - mmengine - INFO - Epoch(train) [12][5150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:27:27 time: 1.0673 data_time: 0.0597 memory: 6163 grad_norm: 3.3004 loss: 0.6861 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0424 loss_cls: 0.1747 acc: 89.5020 loss_bbox: 0.2224 loss_mask: 0.2280 +2024/10/28 16:48:22 - mmengine - INFO - Epoch(train) [12][5200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:26:50 time: 0.9801 data_time: 0.0573 memory: 6268 grad_norm: 3.2092 loss: 0.6588 loss_rpn_cls: 0.0165 loss_rpn_bbox: 0.0399 loss_cls: 0.1590 acc: 92.2852 loss_bbox: 0.2062 loss_mask: 0.2371 +2024/10/28 16:49:12 - mmengine - INFO - Epoch(train) [12][5250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:26:12 time: 0.9932 data_time: 0.0543 memory: 6209 grad_norm: 2.9737 loss: 0.6062 loss_rpn_cls: 0.0151 loss_rpn_bbox: 0.0333 loss_cls: 0.1401 acc: 95.9473 loss_bbox: 0.1956 loss_mask: 0.2220 +2024/10/28 16:50:04 - mmengine - INFO - Epoch(train) [12][5300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:25:35 time: 1.0552 data_time: 0.0521 memory: 6207 grad_norm: 3.1989 loss: 0.6175 loss_rpn_cls: 0.0144 loss_rpn_bbox: 0.0361 loss_cls: 0.1485 acc: 93.0176 loss_bbox: 0.1934 loss_mask: 0.2251 +2024/10/28 16:50:55 - mmengine - INFO - Epoch(train) [12][5350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:24:57 time: 1.0056 data_time: 0.0777 memory: 6207 grad_norm: 3.2527 loss: 0.5703 loss_rpn_cls: 0.0143 loss_rpn_bbox: 0.0303 loss_cls: 0.1411 acc: 92.4316 loss_bbox: 0.1783 loss_mask: 0.2064 +2024/10/28 16:51:13 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 16:51:42 - mmengine - INFO - Epoch(train) [12][5400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:24:20 time: 0.9522 data_time: 0.0520 memory: 6091 grad_norm: 3.0965 loss: 0.6164 loss_rpn_cls: 0.0143 loss_rpn_bbox: 0.0349 loss_cls: 0.1430 acc: 94.9219 loss_bbox: 0.1956 loss_mask: 0.2285 +2024/10/28 16:52:35 - mmengine - INFO - Epoch(train) [12][5450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:23:42 time: 1.0461 data_time: 0.0577 memory: 6180 grad_norm: 3.2084 loss: 0.6458 loss_rpn_cls: 0.0183 loss_rpn_bbox: 0.0401 loss_cls: 0.1591 acc: 94.1406 loss_bbox: 0.2069 loss_mask: 0.2214 +2024/10/28 16:53:23 - mmengine - INFO - Epoch(train) [12][5500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:23:04 time: 0.9699 data_time: 0.0444 memory: 6294 grad_norm: 3.1404 loss: 0.6539 loss_rpn_cls: 0.0157 loss_rpn_bbox: 0.0330 loss_cls: 0.1643 acc: 93.7988 loss_bbox: 0.2157 loss_mask: 0.2253 +2024/10/28 16:54:14 - mmengine - INFO - Epoch(train) [12][5550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:22:27 time: 1.0245 data_time: 0.0457 memory: 6308 grad_norm: 3.2020 loss: 0.6724 loss_rpn_cls: 0.0194 loss_rpn_bbox: 0.0394 loss_cls: 0.1673 acc: 92.1875 loss_bbox: 0.2154 loss_mask: 0.2309 +2024/10/28 16:55:05 - mmengine - INFO - Epoch(train) [12][5600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:21:49 time: 1.0019 data_time: 0.0490 memory: 6150 grad_norm: 3.0834 loss: 0.6573 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0394 loss_cls: 0.1605 acc: 92.9199 loss_bbox: 0.2107 loss_mask: 0.2299 +2024/10/28 16:55:54 - mmengine - INFO - Epoch(train) [12][5650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:21:12 time: 0.9927 data_time: 0.0621 memory: 6273 grad_norm: 3.1848 loss: 0.6230 loss_rpn_cls: 0.0151 loss_rpn_bbox: 0.0333 loss_cls: 0.1506 acc: 91.0156 loss_bbox: 0.1997 loss_mask: 0.2243 +2024/10/28 16:56:44 - mmengine - INFO - Epoch(train) [12][5700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:20:34 time: 0.9974 data_time: 0.0549 memory: 6192 grad_norm: 2.9730 loss: 0.5996 loss_rpn_cls: 0.0143 loss_rpn_bbox: 0.0345 loss_cls: 0.1369 acc: 95.1172 loss_bbox: 0.1850 loss_mask: 0.2289 +2024/10/28 16:57:34 - mmengine - INFO - Epoch(train) [12][5750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:19:56 time: 1.0027 data_time: 0.0514 memory: 6272 grad_norm: 3.1856 loss: 0.6269 loss_rpn_cls: 0.0171 loss_rpn_bbox: 0.0348 loss_cls: 0.1502 acc: 98.1445 loss_bbox: 0.2054 loss_mask: 0.2194 +2024/10/28 16:58:26 - mmengine - INFO - Epoch(train) [12][5800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:19:19 time: 1.0360 data_time: 0.0535 memory: 6367 grad_norm: 3.1789 loss: 0.6695 loss_rpn_cls: 0.0161 loss_rpn_bbox: 0.0371 loss_cls: 0.1607 acc: 91.6992 loss_bbox: 0.2157 loss_mask: 0.2399 +2024/10/28 16:59:16 - mmengine - INFO - Epoch(train) [12][5850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:18:41 time: 1.0016 data_time: 0.0507 memory: 6280 grad_norm: 3.0038 loss: 0.6062 loss_rpn_cls: 0.0132 loss_rpn_bbox: 0.0301 loss_cls: 0.1456 acc: 91.8457 loss_bbox: 0.1949 loss_mask: 0.2223 +2024/10/28 17:00:06 - mmengine - INFO - Epoch(train) [12][5900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:18:03 time: 1.0052 data_time: 0.0610 memory: 6389 grad_norm: 3.0454 loss: 0.6764 loss_rpn_cls: 0.0175 loss_rpn_bbox: 0.0421 loss_cls: 0.1646 acc: 94.6289 loss_bbox: 0.2196 loss_mask: 0.2326 +2024/10/28 17:00:58 - mmengine - INFO - Epoch(train) [12][5950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:17:26 time: 1.0278 data_time: 0.0561 memory: 6266 grad_norm: 3.1149 loss: 0.6221 loss_rpn_cls: 0.0155 loss_rpn_bbox: 0.0346 loss_cls: 0.1470 acc: 92.7734 loss_bbox: 0.2082 loss_mask: 0.2167 +2024/10/28 17:01:49 - mmengine - INFO - Epoch(train) [12][6000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:16:48 time: 1.0315 data_time: 0.0546 memory: 6223 grad_norm: 3.0806 loss: 0.5971 loss_rpn_cls: 0.0143 loss_rpn_bbox: 0.0357 loss_cls: 0.1446 acc: 97.8027 loss_bbox: 0.1906 loss_mask: 0.2119 +2024/10/28 17:02:40 - mmengine - INFO - Epoch(train) [12][6050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:16:10 time: 1.0043 data_time: 0.0546 memory: 6262 grad_norm: 3.1415 loss: 0.6520 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0371 loss_cls: 0.1578 acc: 96.5820 loss_bbox: 0.2107 loss_mask: 0.2298 +2024/10/28 17:03:33 - mmengine - INFO - Epoch(train) [12][6100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:15:33 time: 1.0756 data_time: 0.0573 memory: 6291 grad_norm: 3.0887 loss: 0.5724 loss_rpn_cls: 0.0120 loss_rpn_bbox: 0.0311 loss_cls: 0.1386 acc: 94.0918 loss_bbox: 0.1823 loss_mask: 0.2085 +2024/10/28 17:04:26 - mmengine - INFO - Epoch(train) [12][6150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:14:55 time: 1.0436 data_time: 0.0629 memory: 6294 grad_norm: 3.0050 loss: 0.6561 loss_rpn_cls: 0.0172 loss_rpn_bbox: 0.0388 loss_cls: 0.1590 acc: 93.9941 loss_bbox: 0.2111 loss_mask: 0.2299 +2024/10/28 17:05:17 - mmengine - INFO - Epoch(train) [12][6200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:14:17 time: 1.0211 data_time: 0.0540 memory: 6301 grad_norm: 3.2038 loss: 0.6204 loss_rpn_cls: 0.0168 loss_rpn_bbox: 0.0347 loss_cls: 0.1505 acc: 96.0449 loss_bbox: 0.2006 loss_mask: 0.2178 +2024/10/28 17:06:07 - mmengine - INFO - Epoch(train) [12][6250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:13:39 time: 1.0173 data_time: 0.0488 memory: 6115 grad_norm: 3.2450 loss: 0.5953 loss_rpn_cls: 0.0151 loss_rpn_bbox: 0.0325 loss_cls: 0.1444 acc: 96.9727 loss_bbox: 0.1885 loss_mask: 0.2148 +2024/10/28 17:07:00 - mmengine - INFO - Epoch(train) [12][6300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:13:02 time: 1.0498 data_time: 0.0511 memory: 6339 grad_norm: 3.1515 loss: 0.6234 loss_rpn_cls: 0.0146 loss_rpn_bbox: 0.0342 loss_cls: 0.1531 acc: 92.4316 loss_bbox: 0.1999 loss_mask: 0.2216 +2024/10/28 17:07:52 - mmengine - INFO - Epoch(train) [12][6350/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:12:24 time: 1.0372 data_time: 0.0562 memory: 6207 grad_norm: 3.3383 loss: 0.6211 loss_rpn_cls: 0.0190 loss_rpn_bbox: 0.0368 loss_cls: 0.1511 acc: 91.5527 loss_bbox: 0.1934 loss_mask: 0.2208 +2024/10/28 17:08:11 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 17:08:44 - mmengine - INFO - Epoch(train) [12][6400/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:11:46 time: 1.0384 data_time: 0.0638 memory: 6253 grad_norm: 3.2611 loss: 0.6192 loss_rpn_cls: 0.0178 loss_rpn_bbox: 0.0364 loss_cls: 0.1508 acc: 92.7734 loss_bbox: 0.2022 loss_mask: 0.2120 +2024/10/28 17:09:36 - mmengine - INFO - Epoch(train) [12][6450/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:11:08 time: 1.0451 data_time: 0.0616 memory: 6241 grad_norm: 3.0774 loss: 0.7017 loss_rpn_cls: 0.0202 loss_rpn_bbox: 0.0395 loss_cls: 0.1718 acc: 91.0156 loss_bbox: 0.2364 loss_mask: 0.2338 +2024/10/28 17:10:29 - mmengine - INFO - Epoch(train) [12][6500/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:10:30 time: 1.0674 data_time: 0.0586 memory: 6187 grad_norm: 3.1656 loss: 0.6719 loss_rpn_cls: 0.0182 loss_rpn_bbox: 0.0357 loss_cls: 0.1659 acc: 93.6035 loss_bbox: 0.2150 loss_mask: 0.2371 +2024/10/28 17:11:22 - mmengine - INFO - Epoch(train) [12][6550/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:09:52 time: 1.0462 data_time: 0.0574 memory: 6162 grad_norm: 3.3894 loss: 0.6627 loss_rpn_cls: 0.0207 loss_rpn_bbox: 0.0401 loss_cls: 0.1646 acc: 89.5996 loss_bbox: 0.2116 loss_mask: 0.2257 +2024/10/28 17:12:10 - mmengine - INFO - Epoch(train) [12][6600/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:09:14 time: 0.9669 data_time: 0.0547 memory: 6172 grad_norm: 3.1274 loss: 0.6244 loss_rpn_cls: 0.0186 loss_rpn_bbox: 0.0365 loss_cls: 0.1510 acc: 94.2871 loss_bbox: 0.2003 loss_mask: 0.2179 +2024/10/28 17:13:00 - mmengine - INFO - Epoch(train) [12][6650/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:08:37 time: 0.9906 data_time: 0.0519 memory: 6197 grad_norm: 3.1864 loss: 0.6128 loss_rpn_cls: 0.0158 loss_rpn_bbox: 0.0332 loss_cls: 0.1516 acc: 92.1875 loss_bbox: 0.1921 loss_mask: 0.2201 +2024/10/28 17:13:52 - mmengine - INFO - Epoch(train) [12][6700/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:07:59 time: 1.0566 data_time: 0.0581 memory: 6354 grad_norm: 3.0194 loss: 0.6194 loss_rpn_cls: 0.0158 loss_rpn_bbox: 0.0339 loss_cls: 0.1439 acc: 92.9199 loss_bbox: 0.2032 loss_mask: 0.2227 +2024/10/28 17:14:46 - mmengine - INFO - Epoch(train) [12][6750/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:07:21 time: 1.0672 data_time: 0.0631 memory: 6331 grad_norm: 3.2611 loss: 0.6846 loss_rpn_cls: 0.0192 loss_rpn_bbox: 0.0388 loss_cls: 0.1723 acc: 98.2422 loss_bbox: 0.2204 loss_mask: 0.2338 +2024/10/28 17:15:35 - mmengine - INFO - Epoch(train) [12][6800/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:06:43 time: 0.9927 data_time: 0.0534 memory: 6281 grad_norm: 3.2329 loss: 0.6259 loss_rpn_cls: 0.0147 loss_rpn_bbox: 0.0347 loss_cls: 0.1543 acc: 93.6035 loss_bbox: 0.2048 loss_mask: 0.2174 +2024/10/28 17:16:24 - mmengine - INFO - Epoch(train) [12][6850/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:06:05 time: 0.9639 data_time: 0.0547 memory: 6254 grad_norm: 3.2588 loss: 0.6056 loss_rpn_cls: 0.0144 loss_rpn_bbox: 0.0321 loss_cls: 0.1500 acc: 94.9707 loss_bbox: 0.2003 loss_mask: 0.2088 +2024/10/28 17:17:14 - mmengine - INFO - Epoch(train) [12][6900/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:05:27 time: 0.9992 data_time: 0.0535 memory: 6253 grad_norm: 3.1071 loss: 0.6339 loss_rpn_cls: 0.0162 loss_rpn_bbox: 0.0336 loss_cls: 0.1514 acc: 93.5059 loss_bbox: 0.2062 loss_mask: 0.2264 +2024/10/28 17:18:06 - mmengine - INFO - Epoch(train) [12][6950/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:04:49 time: 1.0379 data_time: 0.0519 memory: 6249 grad_norm: 3.2277 loss: 0.6909 loss_rpn_cls: 0.0183 loss_rpn_bbox: 0.0439 loss_cls: 0.1722 acc: 94.1406 loss_bbox: 0.2277 loss_mask: 0.2289 +2024/10/28 17:18:57 - mmengine - INFO - Epoch(train) [12][7000/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:04:11 time: 1.0301 data_time: 0.0473 memory: 6308 grad_norm: 3.2846 loss: 0.6437 loss_rpn_cls: 0.0167 loss_rpn_bbox: 0.0372 loss_cls: 0.1617 acc: 94.9219 loss_bbox: 0.2045 loss_mask: 0.2236 +2024/10/28 17:19:46 - mmengine - INFO - Epoch(train) [12][7050/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:03:33 time: 0.9883 data_time: 0.0451 memory: 6377 grad_norm: 3.0548 loss: 0.6213 loss_rpn_cls: 0.0202 loss_rpn_bbox: 0.0354 loss_cls: 0.1526 acc: 94.3848 loss_bbox: 0.1949 loss_mask: 0.2181 +2024/10/28 17:20:37 - mmengine - INFO - Epoch(train) [12][7100/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:02:55 time: 1.0117 data_time: 0.0398 memory: 6222 grad_norm: 3.1201 loss: 0.6069 loss_rpn_cls: 0.0150 loss_rpn_bbox: 0.0333 loss_cls: 0.1390 acc: 94.6289 loss_bbox: 0.1963 loss_mask: 0.2232 +2024/10/28 17:21:27 - mmengine - INFO - Epoch(train) [12][7150/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:02:17 time: 0.9940 data_time: 0.0413 memory: 6314 grad_norm: 3.1901 loss: 0.6457 loss_rpn_cls: 0.0177 loss_rpn_bbox: 0.0392 loss_cls: 0.1624 acc: 91.4062 loss_bbox: 0.2075 loss_mask: 0.2189 +2024/10/28 17:22:17 - mmengine - INFO - Epoch(train) [12][7200/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:01:39 time: 1.0008 data_time: 0.0384 memory: 6234 grad_norm: 3.2297 loss: 0.6222 loss_rpn_cls: 0.0160 loss_rpn_bbox: 0.0363 loss_cls: 0.1487 acc: 93.6523 loss_bbox: 0.2020 loss_mask: 0.2192 +2024/10/28 17:22:43 - mmengine - INFO - Epoch(train) [12][7250/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:01:00 time: 0.5329 data_time: 0.0396 memory: 6296 grad_norm: 3.1588 loss: 0.5813 loss_rpn_cls: 0.0141 loss_rpn_bbox: 0.0321 loss_cls: 0.1353 acc: 94.2383 loss_bbox: 0.1873 loss_mask: 0.2126 +2024/10/28 17:23:09 - mmengine - INFO - Epoch(train) [12][7300/7330] base_lr: 1.3397e-05 lr: 1.3397e-05 eta: 0:00:22 time: 0.5020 data_time: 0.0424 memory: 6309 grad_norm: 3.2292 loss: 0.6626 loss_rpn_cls: 0.0161 loss_rpn_bbox: 0.0363 loss_cls: 0.1600 acc: 94.8242 loss_bbox: 0.2188 loss_mask: 0.2314 +2024/10/28 17:23:30 - mmengine - INFO - Exp name: mask-rcnn_mobilemamba_b1_fpn_1x_coco_20241027_215649 +2024/10/28 17:23:30 - mmengine - INFO - Saving checkpoint at 12 epochs +2024/10/28 17:23:40 - mmengine - INFO - Epoch(val) [12][ 50/1250] eta: 0:02:12 time: 0.1102 data_time: 0.0057 memory: 7252 +2024/10/28 17:23:46 - mmengine - INFO - Epoch(val) [12][ 100/1250] eta: 0:02:05 time: 0.1073 data_time: 0.0034 memory: 1114 +2024/10/28 17:23:51 - mmengine - INFO - Epoch(val) [12][ 150/1250] eta: 0:01:58 time: 0.1067 data_time: 0.0036 memory: 1049 +2024/10/28 17:23:57 - mmengine - INFO - Epoch(val) [12][ 200/1250] eta: 0:01:54 time: 0.1128 data_time: 0.0049 memory: 1082 +2024/10/28 17:24:02 - mmengine - INFO - Epoch(val) [12][ 250/1250] eta: 0:01:49 time: 0.1083 data_time: 0.0043 memory: 1221 +2024/10/28 17:24:08 - mmengine - INFO - Epoch(val) [12][ 300/1250] eta: 0:01:43 time: 0.1084 data_time: 0.0045 memory: 1114 +2024/10/28 17:24:13 - mmengine - INFO - Epoch(val) [12][ 350/1250] eta: 0:01:37 time: 0.1055 data_time: 0.0036 memory: 1066 +2024/10/28 17:24:18 - mmengine - INFO - Epoch(val) [12][ 400/1250] eta: 0:01:32 time: 0.1070 data_time: 0.0038 memory: 1114 +2024/10/28 17:24:23 - mmengine - INFO - Epoch(val) [12][ 450/1250] eta: 0:01:26 time: 0.1054 data_time: 0.0036 memory: 1082 +2024/10/28 17:24:29 - mmengine - INFO - Epoch(val) [12][ 500/1250] eta: 0:01:21 time: 0.1091 data_time: 0.0044 memory: 1082 +2024/10/28 17:24:34 - mmengine - INFO - Epoch(val) [12][ 550/1250] eta: 0:01:15 time: 0.1071 data_time: 0.0048 memory: 1131 +2024/10/28 17:24:40 - mmengine - INFO - Epoch(val) [12][ 600/1250] eta: 0:01:10 time: 0.1126 data_time: 0.0059 memory: 1114 +2024/10/28 17:24:45 - mmengine - INFO - Epoch(val) [12][ 650/1250] eta: 0:01:04 time: 0.1045 data_time: 0.0043 memory: 1120 +2024/10/28 17:24:51 - mmengine - INFO - Epoch(val) [12][ 700/1250] eta: 0:00:59 time: 0.1096 data_time: 0.0045 memory: 1088 +2024/10/28 17:24:56 - mmengine - INFO - Epoch(val) [12][ 750/1250] eta: 0:00:54 time: 0.1093 data_time: 0.0050 memory: 1114 +2024/10/28 17:25:01 - mmengine - INFO - Epoch(val) [12][ 800/1250] eta: 0:00:48 time: 0.1041 data_time: 0.0033 memory: 1114 +2024/10/28 17:25:07 - mmengine - INFO - Epoch(val) [12][ 850/1250] eta: 0:00:43 time: 0.1063 data_time: 0.0034 memory: 1088 +2024/10/28 17:25:12 - mmengine - INFO - Epoch(val) [12][ 900/1250] eta: 0:00:37 time: 0.1059 data_time: 0.0033 memory: 1082 +2024/10/28 17:25:17 - mmengine - INFO - Epoch(val) [12][ 950/1250] eta: 0:00:32 time: 0.1100 data_time: 0.0051 memory: 1219 +2024/10/28 17:25:23 - mmengine - INFO - Epoch(val) [12][1000/1250] eta: 0:00:26 time: 0.1036 data_time: 0.0035 memory: 1028 +2024/10/28 17:25:28 - mmengine - INFO - Epoch(val) [12][1050/1250] eta: 0:00:21 time: 0.1104 data_time: 0.0045 memory: 1114 +2024/10/28 17:25:33 - mmengine - INFO - Epoch(val) [12][1100/1250] eta: 0:00:16 time: 0.1077 data_time: 0.0035 memory: 1082 +2024/10/28 17:25:39 - mmengine - INFO - Epoch(val) [12][1150/1250] eta: 0:00:10 time: 0.1106 data_time: 0.0047 memory: 1114 +2024/10/28 17:25:44 - mmengine - INFO - Epoch(val) [12][1200/1250] eta: 0:00:05 time: 0.1095 data_time: 0.0040 memory: 1114 +2024/10/28 17:25:50 - mmengine - INFO - Epoch(val) [12][1250/1250] eta: 0:00:00 time: 0.1047 data_time: 0.0038 memory: 1114 +2024/10/28 17:25:57 - mmengine - INFO - Evaluating bbox... +2024/10/28 17:26:22 - mmengine - INFO - bbox_mAP_copypaste: 0.406 0.618 0.438 0.224 0.435 0.559 +2024/10/28 17:26:22 - mmengine - INFO - Evaluating segm... +2024/10/28 17:26:48 - mmengine - INFO - segm_mAP_copypaste: 0.374 0.589 0.399 0.171 0.399 0.564 +2024/10/28 17:26:48 - mmengine - INFO - Epoch(val) [12][1250/1250] coco/bbox_mAP: 0.4060 coco/bbox_mAP_50: 0.6180 coco/bbox_mAP_75: 0.4380 coco/bbox_mAP_s: 0.2240 coco/bbox_mAP_m: 0.4350 coco/bbox_mAP_l: 0.5590 coco/segm_mAP: 0.3740 coco/segm_mAP_50: 0.5890 coco/segm_mAP_75: 0.3990 coco/segm_mAP_s: 0.1710 coco/segm_mAP_m: 0.3990 coco/segm_mAP_l: 0.5640 data_time: 0.0042 time: 0.1078