diff --git "a/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.log" "b/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.log" new file mode 100644--- /dev/null +++ "b/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.log" @@ -0,0 +1,5854 @@ +2022-05-06 01:40:10,723 - mmseg - INFO - Environment info: +------------------------------------------------------------ +sys.platform: linux +Python: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0] +CUDA available: True +GPU 0,1,2,3,4,5,6,7: A100-SXM-80GB +CUDA_HOME: /mnt/lustre/share/cuda-11.1 +NVCC: Build cuda_11.1.TC455_06.29069683_0 +GCC: gcc (GCC) 5.4.0 +PyTorch: 1.9.0+cu111 +PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.1 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 + - CuDNN 8.0.5 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, + +TorchVision: 0.10.0+cu111 +OpenCV: 4.5.5 +MMCV: 1.4.2 +MMCV Compiler: GCC 7.3 +MMCV CUDA Compiler: 11.1 +MMSegmentation: 0.20.2+ +------------------------------------------------------------ + +2022-05-06 01:40:10,725 - mmseg - INFO - Distributed training: True +2022-05-06 01:40:11,316 - mmseg - INFO - Config: +num_things_classes = 29 +num_stuff_classes = 30 +num_classes = 59 +norm_cfg = dict(type='SyncBN', requires_grad=True) +model = dict( + type='EncoderDecoderMask2Former', + pretrained='pretrained/beit_large_patch16_224_pt22k_ft22k.pth', + backbone=dict( + type='BEiTAdapter', + patch_size=16, + embed_dim=1024, + depth=24, + num_heads=16, + mlp_ratio=4, + qkv_bias=True, + use_abs_pos_emb=False, + use_rel_pos_bias=True, + img_size=480, + init_values=1e-06, + drop_path_rate=0.3, + conv_inplane=64, + n_points=4, + deform_num_heads=16, + interact_with_ffn=True, + interact_ffn_ratio=0.25, + interact_deform_ratio=0.5, + extract_with_ffn=True, + extract_ffn_ratio=0.25, + extract_deform_ratio=0.5, + num_extract_block=2, + add_vit_feature=True, + interact_indexes=[[0, 5], [6, 11], [12, 17], [18, 23]]), + decode_head=dict( + type='Mask2FormerHead', + in_channels=[1024, 1024, 1024, 1024], + feat_channels=1024, + out_channels=1024, + in_index=[0, 1, 2, 3], + num_things_classes=29, + num_stuff_classes=30, + num_queries=100, + num_transformer_feat_level=3, + pixel_decoder=dict( + type='MSDeformAttnPixelDecoder', + num_outs=3, + norm_cfg=dict(type='GN', num_groups=32), + act_cfg=dict(type='ReLU'), + encoder=dict( + type='DetrTransformerEncoder', + num_layers=6, + transformerlayers=dict( + type='BaseTransformerLayer', + attn_cfgs=dict( + type='MultiScaleDeformableAttention', + embed_dims=1024, + num_heads=32, + num_levels=3, + num_points=4, + im2col_step=64, + dropout=0.0, + batch_first=False, + norm_cfg=None, + init_cfg=None), + ffn_cfgs=dict( + type='FFN', + embed_dims=1024, + feedforward_channels=4096, + num_fcs=2, + ffn_drop=0.0, + act_cfg=dict(type='ReLU', inplace=True)), + operation_order=('self_attn', 'norm', 'ffn', 'norm')), + init_cfg=None), + positional_encoding=dict( + type='SinePositionalEncoding', num_feats=512, normalize=True), + init_cfg=None), + enforce_decoder_input_project=False, + positional_encoding=dict( + type='SinePositionalEncoding', num_feats=512, normalize=True), + transformer_decoder=dict( + type='DetrTransformerDecoder', + return_intermediate=True, + num_layers=9, + transformerlayers=dict( + type='DetrTransformerDecoderLayer', + attn_cfgs=dict( + type='MultiheadAttention', + embed_dims=1024, + num_heads=32, + attn_drop=0.0, + proj_drop=0.0, + dropout_layer=None, + batch_first=False), + ffn_cfgs=dict( + embed_dims=1024, + feedforward_channels=4096, + num_fcs=2, + act_cfg=dict(type='ReLU', inplace=True), + ffn_drop=0.0, + dropout_layer=None, + add_identity=True), + feedforward_channels=4096, + operation_order=('cross_attn', 'norm', 'self_attn', 'norm', + 'ffn', 'norm')), + init_cfg=None), + loss_cls=dict( + type='CrossEntropyLoss', + use_sigmoid=False, + loss_weight=2.0, + reduction='mean', + class_weight=[ + 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, + 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.1 + ]), + loss_mask=dict( + type='CrossEntropyLoss', + use_sigmoid=True, + reduction='mean', + loss_weight=5.0), + loss_dice=dict( + type='DiceLoss', + use_sigmoid=True, + activate=True, + reduction='mean', + naive_dice=True, + eps=1.0, + loss_weight=5.0)), + train_cfg=dict( + num_points=12544, + oversample_ratio=3.0, + importance_sample_ratio=0.75, + assigner=dict( + type='MaskHungarianAssigner', + cls_cost=dict(type='ClassificationCost', weight=2.0), + mask_cost=dict( + type='CrossEntropyLossCost', weight=5.0, use_sigmoid=True), + dice_cost=dict( + type='DiceCost', weight=5.0, pred_act=True, eps=1.0)), + sampler=dict(type='MaskPseudoSampler')), + test_cfg=dict( + panoptic_on=True, + semantic_on=False, + instance_on=True, + max_per_image=100, + iou_thr=0.8, + filter_low_score=True, + mode='slide', + crop_size=(480, 480), + stride=(320, 320)), + init_cfg=None) +find_unused_parameters = True +dataset_type = 'PascalContextDataset59' +data_root = 'data/VOCdevkit/VOC2010/' +img_norm_cfg = dict( + mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) +img_scale = (520, 520) +crop_size = (480, 480) +train_pipeline = [ + dict(type='LoadImageFromFile'), + dict(type='LoadAnnotations', reduce_zero_label=True), + dict(type='Resize', img_scale=(520, 520), ratio_range=(0.5, 2.0)), + dict(type='RandomCrop', crop_size=(480, 480), cat_max_ratio=0.75), + dict(type='RandomFlip', prob=0.5), + dict(type='PhotoMetricDistortion'), + dict( + type='Normalize', + mean=[123.675, 116.28, 103.53], + std=[58.395, 57.12, 57.375], + to_rgb=True), + dict(type='Pad', size=(480, 480), pad_val=0, seg_pad_val=255), + dict(type='ToMask'), + dict(type='DefaultFormatBundle'), + dict( + type='Collect', + keys=['img', 'gt_semantic_seg', 'gt_masks', 'gt_labels']) +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(4096, 520), + flip=False, + transforms=[ + dict(type='Resize', keep_ratio=True), + dict(type='ResizeToMultiple', size_divisor=32), + dict(type='RandomFlip'), + dict( + type='Normalize', + mean=[123.675, 116.28, 103.53], + std=[58.395, 57.12, 57.375], + to_rgb=True), + dict(type='ImageToTensor', keys=['img']), + dict(type='Collect', keys=['img']) + ]) +] +data = dict( + samples_per_gpu=2, + workers_per_gpu=4, + train=dict( + type='PascalContextDataset59', + data_root='data/VOCdevkit/VOC2010/', + img_dir='JPEGImages', + ann_dir='SegmentationClassContext', + split='ImageSets/SegmentationContext/train.txt', + pipeline=[ + dict(type='LoadImageFromFile'), + dict(type='LoadAnnotations', reduce_zero_label=True), + dict(type='Resize', img_scale=(520, 520), ratio_range=(0.5, 2.0)), + dict(type='RandomCrop', crop_size=(480, 480), cat_max_ratio=0.75), + dict(type='RandomFlip', prob=0.5), + dict(type='PhotoMetricDistortion'), + dict( + type='Normalize', + mean=[123.675, 116.28, 103.53], + std=[58.395, 57.12, 57.375], + to_rgb=True), + dict(type='Pad', size=(480, 480), pad_val=0, seg_pad_val=255), + dict(type='ToMask'), + dict(type='DefaultFormatBundle'), + dict( + type='Collect', + keys=['img', 'gt_semantic_seg', 'gt_masks', 'gt_labels']) + ]), + val=dict( + type='PascalContextDataset59', + data_root='data/VOCdevkit/VOC2010/', + img_dir='JPEGImages', + ann_dir='SegmentationClassContext', + split='ImageSets/SegmentationContext/val.txt', + pipeline=[ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(4096, 520), + flip=False, + transforms=[ + dict(type='Resize', keep_ratio=True), + dict(type='ResizeToMultiple', size_divisor=32), + dict(type='RandomFlip'), + dict( + type='Normalize', + mean=[123.675, 116.28, 103.53], + std=[58.395, 57.12, 57.375], + to_rgb=True), + dict(type='ImageToTensor', keys=['img']), + dict(type='Collect', keys=['img']) + ]) + ]), + test=dict( + type='PascalContextDataset59', + data_root='data/VOCdevkit/VOC2010/', + img_dir='JPEGImages', + ann_dir='SegmentationClassContext', + split='ImageSets/SegmentationContext/val.txt', + pipeline=[ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + img_scale=(4096, 520), + flip=False, + transforms=[ + dict(type='Resize', keep_ratio=True), + dict(type='ResizeToMultiple', size_divisor=32), + dict(type='RandomFlip'), + dict( + type='Normalize', + mean=[123.675, 116.28, 103.53], + std=[58.395, 57.12, 57.375], + to_rgb=True), + dict(type='ImageToTensor', keys=['img']), + dict(type='Collect', keys=['img']) + ]) + ])) +log_config = dict( + interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)]) +dist_params = dict(backend='nccl') +log_level = 'INFO' +load_from = None +resume_from = 'work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/iter_4000.pth' +workflow = [('train', 1)] +cudnn_benchmark = True +optimizer = dict( + type='AdamW', + lr=2e-05, + betas=(0.9, 0.999), + weight_decay=0.05, + constructor='LayerDecayOptimizerConstructor', + paramwise_cfg=dict(num_layers=24, layer_decay_rate=0.9)) +optimizer_config = dict() +lr_config = dict( + policy='poly', + warmup='linear', + warmup_iters=1500, + warmup_ratio=1e-06, + power=1.0, + min_lr=0.0, + by_epoch=False) +runner = dict(type='IterBasedRunner', max_iters=40000) +checkpoint_config = dict(by_epoch=False, interval=1000, max_keep_ckpts=1) +evaluation = dict( + interval=4000, metric='mIoU', pre_eval=True, save_best='mIoU') +work_dir = './work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss' +gpu_ids = range(0, 8) +auto_resume = False + +2022-05-06 01:40:19,856 - mmseg - INFO - Set random seed to 490080055, deterministic: False +2022-05-06 01:40:35,566 - mmseg - WARNING - The model and loaded state dict do not match exactly + +unexpected key in source state_dict: fc_norm.weight, fc_norm.bias, head.weight, head.bias + +missing keys in source state_dict: blocks.0.attn.relative_position_index, blocks.1.attn.relative_position_index, blocks.2.attn.relative_position_index, blocks.3.attn.relative_position_index, blocks.4.attn.relative_position_index, blocks.5.attn.relative_position_index, blocks.6.attn.relative_position_index, blocks.7.attn.relative_position_index, blocks.8.attn.relative_position_index, blocks.9.attn.relative_position_index, blocks.10.attn.relative_position_index, blocks.11.attn.relative_position_index, blocks.12.attn.relative_position_index, blocks.13.attn.relative_position_index, blocks.14.attn.relative_position_index, blocks.15.attn.relative_position_index, blocks.16.attn.relative_position_index, blocks.17.attn.relative_position_index, blocks.18.attn.relative_position_index, blocks.19.attn.relative_position_index, blocks.20.attn.relative_position_index, blocks.21.attn.relative_position_index, blocks.22.attn.relative_position_index, blocks.23.attn.relative_position_index + +Name of parameter - Initialization information + +backbone.cls_token - torch.Size([1, 1, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.level_embed - torch.Size([3, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.patch_embed.proj.weight - torch.Size([1024, 3, 16, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.patch_embed.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.0.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.1.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.2.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.3.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.4.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.5.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.6.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.7.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.8.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.9.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.10.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.11.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.12.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.13.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.14.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.15.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.16.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.17.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.18.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.19.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.20.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.21.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.22.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.gamma_1 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.gamma_2 - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.attn.q_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.attn.v_bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.attn.relative_position_bias_table - torch.Size([3484, 16]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.attn.qkv.weight - torch.Size([3072, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.attn.proj.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.attn.proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.mlp.fc1.weight - torch.Size([4096, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.mlp.fc1.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.mlp.fc2.weight - torch.Size([1024, 4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.blocks.23.mlp.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.0.weight - torch.Size([64, 3, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.1.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.1.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.3.weight - torch.Size([64, 64, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.4.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.4.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.6.weight - torch.Size([64, 64, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.7.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.stem.7.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv2.0.weight - torch.Size([128, 64, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv2.1.weight - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv2.1.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv3.0.weight - torch.Size([256, 128, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv3.1.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv3.1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv4.0.weight - torch.Size([256, 256, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv4.1.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.conv4.1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc1.weight - torch.Size([1024, 64, 1, 1]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc2.weight - torch.Size([1024, 128, 1, 1]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc3.weight - torch.Size([1024, 256, 1, 1]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc3.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc4.weight - torch.Size([1024, 256, 1, 1]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.conv_branch.fc4.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.sampling_offsets.weight - torch.Size([128, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.sampling_offsets.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.attention_weights.weight - torch.Size([64, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.attention_weights.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.extract.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.gamma - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.sampling_offsets.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.sampling_offsets.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.attention_weights.weight - torch.Size([192, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.attention_weights.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.insert.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn.fc1.weight - torch.Size([256, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn.fc1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn.dwconv.dwconv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn.fc2.weight - torch.Size([1024, 256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.0.ffn_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.sampling_offsets.weight - torch.Size([128, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.sampling_offsets.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.attention_weights.weight - torch.Size([64, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.attention_weights.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.extract.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.gamma - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.sampling_offsets.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.sampling_offsets.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.attention_weights.weight - torch.Size([192, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.attention_weights.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.insert.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn.fc1.weight - torch.Size([256, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn.fc1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn.dwconv.dwconv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn.fc2.weight - torch.Size([1024, 256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.1.ffn_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.sampling_offsets.weight - torch.Size([128, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.sampling_offsets.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.attention_weights.weight - torch.Size([64, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.attention_weights.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.extract.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.gamma - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.sampling_offsets.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.sampling_offsets.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.attention_weights.weight - torch.Size([192, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.attention_weights.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.insert.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn.fc1.weight - torch.Size([256, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn.fc1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn.dwconv.dwconv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn.fc2.weight - torch.Size([1024, 256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.2.ffn_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.sampling_offsets.weight - torch.Size([128, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.sampling_offsets.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.attention_weights.weight - torch.Size([64, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.attention_weights.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.extract.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.gamma - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.sampling_offsets.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.sampling_offsets.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.attention_weights.weight - torch.Size([192, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.attention_weights.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.insert.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn.fc1.weight - torch.Size([256, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn.fc1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn.dwconv.dwconv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn.fc2.weight - torch.Size([1024, 256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.interact_blocks.3.ffn_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.sampling_offsets.weight - torch.Size([128, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.sampling_offsets.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.attention_weights.weight - torch.Size([64, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.attention_weights.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.extract.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn.fc1.weight - torch.Size([256, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn.fc1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn.dwconv.dwconv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn.fc2.weight - torch.Size([1024, 256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.0.ffn_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.query_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.query_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.feat_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.feat_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.sampling_offsets.weight - torch.Size([128, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.sampling_offsets.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.attention_weights.weight - torch.Size([64, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.attention_weights.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.value_proj.weight - torch.Size([512, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.value_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.output_proj.weight - torch.Size([1024, 512]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.extract.attn.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn.fc1.weight - torch.Size([256, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn.fc1.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn.dwconv.dwconv.weight - torch.Size([256, 1, 3, 3]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn.dwconv.dwconv.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn.fc2.weight - torch.Size([1024, 256]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn.fc2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.extract_blocks.1.ffn_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.up.weight - torch.Size([1024, 1024, 2, 2]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.up.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm3.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm3.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm4.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +backbone.norm4.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.conv_seg.weight - torch.Size([59, 1024, 1, 1]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.conv_seg.bias - torch.Size([59]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.0.conv.weight - torch.Size([1024, 1024, 1, 1]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.input_convs.0.conv.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.0.gn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.0.gn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.1.conv.weight - torch.Size([1024, 1024, 1, 1]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.input_convs.1.conv.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.1.gn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.1.gn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.2.conv.weight - torch.Size([1024, 1024, 1, 1]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.input_convs.2.conv.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.2.gn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.input_convs.2.gn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.sampling_offsets.weight - torch.Size([768, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.sampling_offsets.bias - torch.Size([768]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.attention_weights.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.attention_weights.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.value_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.value_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.output_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.0.attentions.0.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.0.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.0.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.0.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.sampling_offsets.weight - torch.Size([768, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.sampling_offsets.bias - torch.Size([768]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.attention_weights.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.attention_weights.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.value_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.value_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.output_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.1.attentions.0.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.1.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.1.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.1.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.sampling_offsets.weight - torch.Size([768, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.sampling_offsets.bias - torch.Size([768]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.attention_weights.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.attention_weights.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.value_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.value_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.output_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.2.attentions.0.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.2.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.2.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.2.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.sampling_offsets.weight - torch.Size([768, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.sampling_offsets.bias - torch.Size([768]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.attention_weights.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.attention_weights.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.value_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.value_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.output_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.3.attentions.0.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.3.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.3.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.3.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.sampling_offsets.weight - torch.Size([768, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.sampling_offsets.bias - torch.Size([768]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.attention_weights.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.attention_weights.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.value_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.value_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.output_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.4.attentions.0.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.4.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.4.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.4.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.sampling_offsets.weight - torch.Size([768, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.sampling_offsets.bias - torch.Size([768]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.attention_weights.weight - torch.Size([384, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.attention_weights.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.value_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.value_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.output_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.5.attentions.0.output_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.5.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.encoder.layers.5.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.encoder.layers.5.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.level_encoding.weight - torch.Size([3, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.lateral_convs.0.conv.weight - torch.Size([1024, 1024, 1, 1]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.lateral_convs.0.gn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.lateral_convs.0.gn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.output_convs.0.conv.weight - torch.Size([1024, 1024, 3, 3]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.output_convs.0.gn.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.output_convs.0.gn.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.pixel_decoder.mask_feature.weight - torch.Size([1024, 1024, 1, 1]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.pixel_decoder.mask_feature.bias - torch.Size([1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.0.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.0.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.1.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.1.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.1.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.1.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.1.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.1.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.1.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.2.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.2.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.2.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.2.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.2.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.2.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.2.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.3.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.3.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.3.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.3.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.3.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.3.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.3.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.4.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.4.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.4.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.4.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.4.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.4.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.4.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.5.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.5.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.5.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.5.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.5.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.5.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.5.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.6.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.6.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.6.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.6.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.6.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.6.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.6.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.7.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.7.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.7.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.7.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.7.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.7.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.7.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.attentions.0.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.8.attentions.0.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.attentions.0.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.8.attentions.0.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.attentions.1.attn.in_proj_weight - torch.Size([3072, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.8.attentions.1.attn.in_proj_bias - torch.Size([3072]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.attentions.1.attn.out_proj.weight - torch.Size([1024, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.8.attentions.1.attn.out_proj.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.ffns.0.layers.0.0.weight - torch.Size([4096, 1024]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.8.ffns.0.layers.0.0.bias - torch.Size([4096]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.ffns.0.layers.1.weight - torch.Size([1024, 4096]): +Initialized by user-defined `init_weights` in Mask2FormerHead + +decode_head.transformer_decoder.layers.8.ffns.0.layers.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.norms.0.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.norms.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.norms.1.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.norms.1.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.norms.2.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.layers.8.norms.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.post_norm.weight - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.transformer_decoder.post_norm.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.query_embed.weight - torch.Size([100, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.query_feat.weight - torch.Size([100, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.level_embed.weight - torch.Size([3, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.cls_embed.weight - torch.Size([60, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.cls_embed.bias - torch.Size([60]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.mask_embed.0.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.mask_embed.0.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.mask_embed.2.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.mask_embed.2.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.mask_embed.4.weight - torch.Size([1024, 1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former + +decode_head.mask_embed.4.bias - torch.Size([1024]): +The value is the same before and after calling `init_weights` of EncoderDecoderMask2Former +2022-05-06 01:40:38,805 - mmseg - INFO - EncoderDecoderMask2Former( + (backbone): BEiTAdapter( + (patch_embed): PatchEmbed( + (proj): Conv2d(3, 1024, kernel_size=(16, 16), stride=(16, 16)) + ) + (pos_drop): Dropout(p=0.0, inplace=False) + (blocks): ModuleList( + (0): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): Identity() + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (1): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.013043479062616825) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (2): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.02608695812523365) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (3): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.03913043811917305) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (4): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.0521739162504673) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (5): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.06521739810705185) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (6): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.0782608762383461) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (7): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.09130435436964035) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (8): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.1043478325009346) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (9): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.11739131063222885) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (10): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.1304347962141037) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (11): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.14347827434539795) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (12): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.1565217524766922) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (13): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.16956523060798645) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (14): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.1826087087392807) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (15): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.19565218687057495) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (16): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.2086956650018692) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (17): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.22173914313316345) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (18): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.2347826212644577) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (19): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.24782609939575195) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (20): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.260869562625885) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (21): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.27391305565834045) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (22): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.2869565188884735) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + (23): Block( + (norm1): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): Attention( + (qkv): Linear(in_features=1024, out_features=3072, bias=False) + (attn_drop): Dropout(p=0.0, inplace=False) + (proj): Linear(in_features=1024, out_features=1024, bias=True) + (proj_drop): Dropout(p=0.0, inplace=False) + ) + (drop_path): DropPath(p=0.30000001192092896) + (norm2): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (mlp): Mlp( + (fc1): Linear(in_features=1024, out_features=4096, bias=True) + (act): GELU() + (fc2): Linear(in_features=4096, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + ) + ) + (conv_branch): ConvBranch( + (stem): Sequential( + (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) + (1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (2): ReLU(inplace=True) + (3): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) + (4): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (5): ReLU(inplace=True) + (6): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) + (7): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (8): ReLU(inplace=True) + (9): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False) + ) + (conv2): Sequential( + (0): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) + (1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (2): ReLU(inplace=True) + ) + (conv3): Sequential( + (0): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) + (1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (2): ReLU(inplace=True) + ) + (conv4): Sequential( + (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) + (1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (2): ReLU(inplace=True) + ) + (fc1): Conv2d(64, 1024, kernel_size=(1, 1), stride=(1, 1)) + (fc2): Conv2d(128, 1024, kernel_size=(1, 1), stride=(1, 1)) + (fc3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1)) + (fc4): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1)) + ) + (interact_blocks): Sequential( + (0): InteractBlock( + (extract): ExtractLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=128, bias=True) + (attention_weights): Linear(in_features=1024, out_features=64, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (insert): InsertLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=384, bias=True) + (attention_weights): Linear(in_features=1024, out_features=192, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (ffn): ConvFFN( + (fc1): Linear(in_features=1024, out_features=256, bias=True) + (dwconv): DWConv( + (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256) + ) + (act): GELU() + (fc2): Linear(in_features=256, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + (ffn_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (drop_path): DropPath() + ) + (1): InteractBlock( + (extract): ExtractLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=128, bias=True) + (attention_weights): Linear(in_features=1024, out_features=64, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (insert): InsertLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=384, bias=True) + (attention_weights): Linear(in_features=1024, out_features=192, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (ffn): ConvFFN( + (fc1): Linear(in_features=1024, out_features=256, bias=True) + (dwconv): DWConv( + (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256) + ) + (act): GELU() + (fc2): Linear(in_features=256, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + (ffn_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (drop_path): DropPath() + ) + (2): InteractBlock( + (extract): ExtractLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=128, bias=True) + (attention_weights): Linear(in_features=1024, out_features=64, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (insert): InsertLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=384, bias=True) + (attention_weights): Linear(in_features=1024, out_features=192, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (ffn): ConvFFN( + (fc1): Linear(in_features=1024, out_features=256, bias=True) + (dwconv): DWConv( + (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256) + ) + (act): GELU() + (fc2): Linear(in_features=256, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + (ffn_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (drop_path): DropPath() + ) + (3): InteractBlock( + (extract): ExtractLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=128, bias=True) + (attention_weights): Linear(in_features=1024, out_features=64, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (insert): InsertLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=384, bias=True) + (attention_weights): Linear(in_features=1024, out_features=192, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (ffn): ConvFFN( + (fc1): Linear(in_features=1024, out_features=256, bias=True) + (dwconv): DWConv( + (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256) + ) + (act): GELU() + (fc2): Linear(in_features=256, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + (ffn_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (drop_path): DropPath() + ) + ) + (extract_blocks): Sequential( + (0): ExtractBlock( + (extract): ExtractLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=128, bias=True) + (attention_weights): Linear(in_features=1024, out_features=64, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (ffn): ConvFFN( + (fc1): Linear(in_features=1024, out_features=256, bias=True) + (dwconv): DWConv( + (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256) + ) + (act): GELU() + (fc2): Linear(in_features=256, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + (ffn_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (drop_path): Identity() + ) + (1): ExtractBlock( + (extract): ExtractLayer( + (query_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (feat_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (attn): MSDeformAttn( + (sampling_offsets): Linear(in_features=1024, out_features=128, bias=True) + (attention_weights): Linear(in_features=1024, out_features=64, bias=True) + (value_proj): Linear(in_features=1024, out_features=512, bias=True) + (output_proj): Linear(in_features=512, out_features=1024, bias=True) + ) + ) + (ffn): ConvFFN( + (fc1): Linear(in_features=1024, out_features=256, bias=True) + (dwconv): DWConv( + (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256) + ) + (act): GELU() + (fc2): Linear(in_features=256, out_features=1024, bias=True) + (drop): Dropout(p=0.0, inplace=False) + ) + (ffn_norm): LayerNorm((1024,), eps=1e-06, elementwise_affine=True) + (drop_path): Identity() + ) + ) + (up): ConvTranspose2d(1024, 1024, kernel_size=(2, 2), stride=(2, 2)) + (norm1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (norm2): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (norm3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + (norm4): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) + ) + (decode_head): Mask2FormerHead( + input_transform=multiple_select, ignore_index=255, align_corners=False + (loss_decode): CrossEntropyLoss(avg_non_ignore=False) + (conv_seg): Conv2d(1024, 59, kernel_size=(1, 1), stride=(1, 1)) + (dropout): Dropout2d(p=0.1, inplace=False) + (pixel_decoder): MSDeformAttnPixelDecoder( + (input_convs): ModuleList( + (0): ConvModule( + (conv): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1)) + (gn): GroupNorm(32, 1024, eps=1e-05, affine=True) + ) + (1): ConvModule( + (conv): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1)) + (gn): GroupNorm(32, 1024, eps=1e-05, affine=True) + ) + (2): ConvModule( + (conv): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1)) + (gn): GroupNorm(32, 1024, eps=1e-05, affine=True) + ) + ) + (encoder): DetrTransformerEncoder( + (layers): ModuleList( + (0): BaseTransformerLayer( + (attentions): ModuleList( + (0): MultiScaleDeformableAttention( + (dropout): Dropout(p=0.0, inplace=False) + (sampling_offsets): Linear(in_features=1024, out_features=768, bias=True) + (attention_weights): Linear(in_features=1024, out_features=384, bias=True) + (value_proj): Linear(in_features=1024, out_features=1024, bias=True) + (output_proj): Linear(in_features=1024, out_features=1024, bias=True) + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (1): BaseTransformerLayer( + (attentions): ModuleList( + (0): MultiScaleDeformableAttention( + (dropout): Dropout(p=0.0, inplace=False) + (sampling_offsets): Linear(in_features=1024, out_features=768, bias=True) + (attention_weights): Linear(in_features=1024, out_features=384, bias=True) + (value_proj): Linear(in_features=1024, out_features=1024, bias=True) + (output_proj): Linear(in_features=1024, out_features=1024, bias=True) + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (2): BaseTransformerLayer( + (attentions): ModuleList( + (0): MultiScaleDeformableAttention( + (dropout): Dropout(p=0.0, inplace=False) + (sampling_offsets): Linear(in_features=1024, out_features=768, bias=True) + (attention_weights): Linear(in_features=1024, out_features=384, bias=True) + (value_proj): Linear(in_features=1024, out_features=1024, bias=True) + (output_proj): Linear(in_features=1024, out_features=1024, bias=True) + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (3): BaseTransformerLayer( + (attentions): ModuleList( + (0): MultiScaleDeformableAttention( + (dropout): Dropout(p=0.0, inplace=False) + (sampling_offsets): Linear(in_features=1024, out_features=768, bias=True) + (attention_weights): Linear(in_features=1024, out_features=384, bias=True) + (value_proj): Linear(in_features=1024, out_features=1024, bias=True) + (output_proj): Linear(in_features=1024, out_features=1024, bias=True) + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (4): BaseTransformerLayer( + (attentions): ModuleList( + (0): MultiScaleDeformableAttention( + (dropout): Dropout(p=0.0, inplace=False) + (sampling_offsets): Linear(in_features=1024, out_features=768, bias=True) + (attention_weights): Linear(in_features=1024, out_features=384, bias=True) + (value_proj): Linear(in_features=1024, out_features=1024, bias=True) + (output_proj): Linear(in_features=1024, out_features=1024, bias=True) + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (5): BaseTransformerLayer( + (attentions): ModuleList( + (0): MultiScaleDeformableAttention( + (dropout): Dropout(p=0.0, inplace=False) + (sampling_offsets): Linear(in_features=1024, out_features=768, bias=True) + (attention_weights): Linear(in_features=1024, out_features=384, bias=True) + (value_proj): Linear(in_features=1024, out_features=1024, bias=True) + (output_proj): Linear(in_features=1024, out_features=1024, bias=True) + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + ) + ) + (postional_encoding): SinePositionalEncoding(num_feats=512, temperature=10000, normalize=True, scale=6.283185307179586, eps=1e-06) + (level_encoding): Embedding(3, 1024) + (lateral_convs): ModuleList( + (0): ConvModule( + (conv): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) + (gn): GroupNorm(32, 1024, eps=1e-05, affine=True) + ) + ) + (output_convs): ModuleList( + (0): ConvModule( + (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) + (gn): GroupNorm(32, 1024, eps=1e-05, affine=True) + (activate): ReLU(inplace=True) + ) + ) + (mask_feature): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1)) + ) + (transformer_decoder): DetrTransformerDecoder( + (layers): ModuleList( + (0): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (1): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (2): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (3): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (4): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (5): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (6): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (7): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + (8): DetrTransformerDecoderLayer( + (attentions): ModuleList( + (0): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + (1): MultiheadAttention( + (attn): MultiheadAttention( + (out_proj): NonDynamicallyQuantizableLinear(in_features=1024, out_features=1024, bias=True) + ) + (proj_drop): Dropout(p=0.0, inplace=False) + (dropout_layer): Identity() + ) + ) + (ffns): ModuleList( + (0): FFN( + (activate): ReLU(inplace=True) + (layers): Sequential( + (0): Sequential( + (0): Linear(in_features=1024, out_features=4096, bias=True) + (1): ReLU(inplace=True) + (2): Dropout(p=0.0, inplace=False) + ) + (1): Linear(in_features=4096, out_features=1024, bias=True) + (2): Dropout(p=0.0, inplace=False) + ) + (dropout_layer): Identity() + ) + ) + (norms): ModuleList( + (0): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + (2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + ) + ) + (post_norm): LayerNorm((1024,), eps=1e-05, elementwise_affine=True) + ) + (decoder_input_projs): ModuleList( + (0): Identity() + (1): Identity() + (2): Identity() + ) + (decoder_positional_encoding): SinePositionalEncoding(num_feats=512, temperature=10000, normalize=True, scale=6.283185307179586, eps=1e-06) + (query_embed): Embedding(100, 1024) + (query_feat): Embedding(100, 1024) + (level_embed): Embedding(3, 1024) + (cls_embed): Linear(in_features=1024, out_features=60, bias=True) + (mask_embed): Sequential( + (0): Linear(in_features=1024, out_features=1024, bias=True) + (1): ReLU(inplace=True) + (2): Linear(in_features=1024, out_features=1024, bias=True) + (3): ReLU(inplace=True) + (4): Linear(in_features=1024, out_features=1024, bias=True) + ) + (loss_cls): CrossEntropyLoss(avg_non_ignore=False) + (loss_mask): CrossEntropyLoss(avg_non_ignore=False) + (loss_dice): DiceLoss() + ) +) +2022-05-06 01:40:38,821 - mmseg - INFO - Loaded 4996 images +2022-05-06 01:40:40,237 - mmseg - INFO - Loaded 5104 images +2022-05-06 01:40:40,238 - mmseg - INFO - load checkpoint from local path: work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/iter_4000.pth +2022-05-06 01:42:00,852 - mmseg - INFO - resumed from epoch: 13, iter 3999 +2022-05-06 01:42:00,869 - mmseg - INFO - Start running, host: chenzhe.vendor@SH-IDC1-10-140-0-234, work_dir: /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss +2022-05-06 01:42:00,871 - mmseg - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) PolyLrUpdaterHook +(NORMAL ) CheckpointHook +(LOW ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_epoch: +(VERY_HIGH ) PolyLrUpdaterHook +(LOW ) IterTimerHook +(LOW ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_train_iter: +(VERY_HIGH ) PolyLrUpdaterHook +(LOW ) IterTimerHook +(LOW ) DistEvalHook + -------------------- +after_train_iter: +(ABOVE_NORMAL) OptimizerHook +(NORMAL ) CheckpointHook +(LOW ) IterTimerHook +(LOW ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +after_train_epoch: +(NORMAL ) CheckpointHook +(LOW ) DistEvalHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_epoch: +(LOW ) IterTimerHook +(VERY_LOW ) TextLoggerHook + -------------------- +before_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_iter: +(LOW ) IterTimerHook + -------------------- +after_val_epoch: +(VERY_LOW ) TextLoggerHook + -------------------- +after_run: +(VERY_LOW ) TextLoggerHook + -------------------- +2022-05-06 01:42:00,872 - mmseg - INFO - workflow: [('train', 1)], max: 40000 iters +2022-05-06 01:42:00,873 - mmseg - INFO - Checkpoints will be saved to /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss by HardDiskBackend. +2022-05-06 01:42:42,334 - mmseg - INFO - Saving checkpoint at 4000 iterations +2022-05-06 01:43:09,355 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 01:43:09,356 - mmseg - INFO - Iter [4000/40000] lr: 1.292e-06, eta: 700 days, 8:23:11, time: 33.617, data_time: 0.179, memory: 53770, decode.loss_cls: 0.5925, decode.loss_mask: 0.7587, decode.loss_dice: 0.9759, decode.d0.loss_cls: 7.1536, decode.d0.loss_mask: 0.7683, decode.d0.loss_dice: 1.1969, decode.d1.loss_cls: 1.1102, decode.d1.loss_mask: 0.7451, decode.d1.loss_dice: 1.0094, decode.d2.loss_cls: 0.8161, decode.d2.loss_mask: 0.7437, decode.d2.loss_dice: 0.9495, decode.d3.loss_cls: 0.7907, decode.d3.loss_mask: 0.7084, decode.d3.loss_dice: 0.9279, decode.d4.loss_cls: 0.6738, decode.d4.loss_mask: 0.7491, decode.d4.loss_dice: 0.9638, decode.d5.loss_cls: 0.6722, decode.d5.loss_mask: 0.7047, decode.d5.loss_dice: 0.9414, decode.d6.loss_cls: 0.6934, decode.d6.loss_mask: 0.7140, decode.d6.loss_dice: 0.9363, decode.d7.loss_cls: 0.6284, decode.d7.loss_mask: 0.7136, decode.d7.loss_dice: 0.9326, decode.d8.loss_cls: 0.6601, decode.d8.loss_mask: 0.7372, decode.d8.loss_dice: 0.9499, loss: 30.9175 +2022-05-06 01:47:59,263 - mmseg - INFO - per class results: +2022-05-06 01:47:59,279 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 91.56 | 95.58 | +| bag | 31.03 | 43.39 | +| bed | 26.02 | 39.34 | +| bedclothes | 38.46 | 47.29 | +| bench | 3.44 | 3.61 | +| bicycle | 81.47 | 91.94 | +| bird | 94.4 | 96.95 | +| boat | 82.82 | 89.23 | +| book | 51.17 | 82.37 | +| bottle | 86.21 | 96.04 | +| building | 63.18 | 77.63 | +| bus | 91.91 | 97.36 | +| cabinet | 47.89 | 70.4 | +| car | 91.92 | 96.33 | +| cat | 94.04 | 97.38 | +| ceiling | 60.6 | 78.24 | +| chair | 63.31 | 80.77 | +| cloth | 32.66 | 54.18 | +| computer | 48.47 | 60.48 | +| cow | 94.59 | 96.27 | +| cup | 40.27 | 66.44 | +| curtain | 57.67 | 78.59 | +| dog | 91.08 | 96.57 | +| door | 33.47 | 64.74 | +| fence | 41.62 | 51.24 | +| floor | 76.31 | 90.27 | +| flower | 34.14 | 41.32 | +| food | 19.2 | 23.55 | +| grass | 82.16 | 88.6 | +| ground | 55.34 | 65.93 | +| horse | 94.35 | 97.24 | +| keyboard | 77.23 | 89.62 | +| light | 54.57 | 70.16 | +| motorbike | 89.97 | 95.6 | +| mountain | 51.41 | 81.78 | +| mouse | 62.86 | 69.64 | +| person | 90.22 | 95.43 | +| plate | 14.2 | 16.69 | +| platform | 44.69 | 58.4 | +| pottedplant | 81.05 | 90.82 | +| road | 54.18 | 78.94 | +| rock | 48.63 | 58.58 | +| sheep | 94.51 | 97.98 | +| shelves | 31.56 | 46.11 | +| sidewalk | 24.85 | 56.67 | +| sign | 48.49 | 69.44 | +| sky | 94.52 | 96.54 | +| snow | 75.87 | 84.85 | +| sofa | 61.27 | 74.04 | +| table | 66.46 | 83.54 | +| track | 66.73 | 77.28 | +| train | 92.43 | 96.96 | +| tree | 80.54 | 89.34 | +| truck | 28.05 | 33.12 | +| tvmonitor | 85.35 | 92.01 | +| wall | 70.76 | 81.05 | +| water | 91.93 | 96.7 | +| window | 43.27 | 54.84 | +| wood | 29.91 | 44.62 | ++-------------+-------+-------+ +2022-05-06 01:47:59,280 - mmseg - INFO - Summary: +2022-05-06 01:47:59,280 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 85.07 | 61.97 | 73.56 | ++-------+-------+-------+ +2022-05-06 01:48:23,879 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_4000.pth. +2022-05-06 01:48:23,890 - mmseg - INFO - Best mIoU is 0.6197 at 4000 iter. +2022-05-06 01:48:23,917 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 01:48:23,917 - mmseg - INFO - Iter(val) [638] aAcc: 0.8507, mIoU: 0.6197, mAcc: 0.7356, IoU.aeroplane: 0.9156, IoU.bag: 0.3103, IoU.bed: 0.2602, IoU.bedclothes: 0.3846, IoU.bench: 0.0344, IoU.bicycle: 0.8147, IoU.bird: 0.9440, IoU.boat: 0.8282, IoU.book: 0.5117, IoU.bottle: 0.8621, IoU.building: 0.6318, IoU.bus: 0.9191, IoU.cabinet: 0.4789, IoU.car: 0.9192, IoU.cat: 0.9404, IoU.ceiling: 0.6060, IoU.chair: 0.6331, IoU.cloth: 0.3266, IoU.computer: 0.4847, IoU.cow: 0.9459, IoU.cup: 0.4027, IoU.curtain: 0.5767, IoU.dog: 0.9108, IoU.door: 0.3347, IoU.fence: 0.4162, IoU.floor: 0.7631, IoU.flower: 0.3414, IoU.food: 0.1920, IoU.grass: 0.8216, IoU.ground: 0.5534, IoU.horse: 0.9435, IoU.keyboard: 0.7723, IoU.light: 0.5457, IoU.motorbike: 0.8997, IoU.mountain: 0.5141, IoU.mouse: 0.6286, IoU.person: 0.9022, IoU.plate: 0.1420, IoU.platform: 0.4469, IoU.pottedplant: 0.8105, IoU.road: 0.5418, IoU.rock: 0.4863, IoU.sheep: 0.9451, IoU.shelves: 0.3156, IoU.sidewalk: 0.2485, IoU.sign: 0.4849, IoU.sky: 0.9452, IoU.snow: 0.7587, IoU.sofa: 0.6127, IoU.table: 0.6646, IoU.track: 0.6673, IoU.train: 0.9243, IoU.tree: 0.8054, IoU.truck: 0.2805, IoU.tvmonitor: 0.8535, IoU.wall: 0.7076, IoU.water: 0.9193, IoU.window: 0.4327, IoU.wood: 0.2991, Acc.aeroplane: 0.9558, Acc.bag: 0.4339, Acc.bed: 0.3934, Acc.bedclothes: 0.4729, Acc.bench: 0.0361, Acc.bicycle: 0.9194, Acc.bird: 0.9695, Acc.boat: 0.8923, Acc.book: 0.8237, Acc.bottle: 0.9604, Acc.building: 0.7763, Acc.bus: 0.9736, Acc.cabinet: 0.7040, Acc.car: 0.9633, Acc.cat: 0.9738, Acc.ceiling: 0.7824, Acc.chair: 0.8077, Acc.cloth: 0.5418, Acc.computer: 0.6048, Acc.cow: 0.9627, Acc.cup: 0.6644, Acc.curtain: 0.7859, Acc.dog: 0.9657, Acc.door: 0.6474, Acc.fence: 0.5124, Acc.floor: 0.9027, Acc.flower: 0.4132, Acc.food: 0.2355, Acc.grass: 0.8860, Acc.ground: 0.6593, Acc.horse: 0.9724, Acc.keyboard: 0.8962, Acc.light: 0.7016, Acc.motorbike: 0.9560, Acc.mountain: 0.8178, Acc.mouse: 0.6964, Acc.person: 0.9543, Acc.plate: 0.1669, Acc.platform: 0.5840, Acc.pottedplant: 0.9082, Acc.road: 0.7894, Acc.rock: 0.5858, Acc.sheep: 0.9798, Acc.shelves: 0.4611, Acc.sidewalk: 0.5667, Acc.sign: 0.6944, Acc.sky: 0.9654, Acc.snow: 0.8485, Acc.sofa: 0.7404, Acc.table: 0.8354, Acc.track: 0.7728, Acc.train: 0.9696, Acc.tree: 0.8934, Acc.truck: 0.3312, Acc.tvmonitor: 0.9201, Acc.wall: 0.8105, Acc.water: 0.9670, Acc.window: 0.5484, Acc.wood: 0.4462 +2022-05-06 01:48:58,914 - mmseg - INFO - Iter [4050/40000] lr: 1.290e-06, eta: 16 days, 13:33:45, time: 6.991, data_time: 6.302, memory: 53770, decode.loss_cls: 0.6824, decode.loss_mask: 0.7964, decode.loss_dice: 1.0474, decode.d0.loss_cls: 7.1737, decode.d0.loss_mask: 0.7623, decode.d0.loss_dice: 1.2241, decode.d1.loss_cls: 0.8665, decode.d1.loss_mask: 0.8020, decode.d1.loss_dice: 1.1129, decode.d2.loss_cls: 0.7201, decode.d2.loss_mask: 0.7977, decode.d2.loss_dice: 1.0667, decode.d3.loss_cls: 0.6983, decode.d3.loss_mask: 0.7915, decode.d3.loss_dice: 1.0423, decode.d4.loss_cls: 0.6885, decode.d4.loss_mask: 0.7946, decode.d4.loss_dice: 1.0542, decode.d5.loss_cls: 0.6788, decode.d5.loss_mask: 0.8013, decode.d5.loss_dice: 1.0552, decode.d6.loss_cls: 0.6708, decode.d6.loss_mask: 0.8009, decode.d6.loss_dice: 1.0428, decode.d7.loss_cls: 0.6716, decode.d7.loss_mask: 0.7978, decode.d7.loss_dice: 1.0436, decode.d8.loss_cls: 0.6696, decode.d8.loss_mask: 0.7984, decode.d8.loss_dice: 1.0559, loss: 32.2080 +2022-05-06 01:49:32,866 - mmseg - INFO - Iter [4100/40000] lr: 1.289e-06, eta: 8 days, 11:49:23, time: 0.679, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6713, decode.loss_mask: 0.7733, decode.loss_dice: 1.0444, decode.d0.loss_cls: 7.1485, decode.d0.loss_mask: 0.7443, decode.d0.loss_dice: 1.2208, decode.d1.loss_cls: 0.8774, decode.d1.loss_mask: 0.7802, decode.d1.loss_dice: 1.1090, decode.d2.loss_cls: 0.7172, decode.d2.loss_mask: 0.7715, decode.d2.loss_dice: 1.0609, decode.d3.loss_cls: 0.6890, decode.d3.loss_mask: 0.7716, decode.d3.loss_dice: 1.0403, decode.d4.loss_cls: 0.6915, decode.d4.loss_mask: 0.7729, decode.d4.loss_dice: 1.0438, decode.d5.loss_cls: 0.6885, decode.d5.loss_mask: 0.7657, decode.d5.loss_dice: 1.0391, decode.d6.loss_cls: 0.6800, decode.d6.loss_mask: 0.7643, decode.d6.loss_dice: 1.0372, decode.d7.loss_cls: 0.6784, decode.d7.loss_mask: 0.7625, decode.d7.loss_dice: 1.0416, decode.d8.loss_cls: 0.6759, decode.d8.loss_mask: 0.7656, decode.d8.loss_dice: 1.0445, loss: 31.8712 +2022-05-06 01:50:06,578 - mmseg - INFO - Iter [4150/40000] lr: 1.287e-06, eta: 5 days, 18:21:53, time: 0.674, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6777, decode.loss_mask: 0.7602, decode.loss_dice: 1.0557, decode.d0.loss_cls: 7.1080, decode.d0.loss_mask: 0.7478, decode.d0.loss_dice: 1.2541, decode.d1.loss_cls: 0.8632, decode.d1.loss_mask: 0.7764, decode.d1.loss_dice: 1.1272, decode.d2.loss_cls: 0.7267, decode.d2.loss_mask: 0.7671, decode.d2.loss_dice: 1.0762, decode.d3.loss_cls: 0.6929, decode.d3.loss_mask: 0.7686, decode.d3.loss_dice: 1.0537, decode.d4.loss_cls: 0.6850, decode.d4.loss_mask: 0.7676, decode.d4.loss_dice: 1.0553, decode.d5.loss_cls: 0.6779, decode.d5.loss_mask: 0.7708, decode.d5.loss_dice: 1.0533, decode.d6.loss_cls: 0.6755, decode.d6.loss_mask: 0.7672, decode.d6.loss_dice: 1.0443, decode.d7.loss_cls: 0.6745, decode.d7.loss_mask: 0.7649, decode.d7.loss_dice: 1.0559, decode.d8.loss_cls: 0.6749, decode.d8.loss_mask: 0.7659, decode.d8.loss_dice: 1.0617, loss: 31.9501 +2022-05-06 01:50:39,924 - mmseg - INFO - Iter [4200/40000] lr: 1.285e-06, eta: 4 days, 9:27:02, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.6890, decode.loss_mask: 0.7860, decode.loss_dice: 1.0150, decode.d0.loss_cls: 7.0659, decode.d0.loss_mask: 0.7552, decode.d0.loss_dice: 1.2009, decode.d1.loss_cls: 0.8581, decode.d1.loss_mask: 0.7959, decode.d1.loss_dice: 1.0939, decode.d2.loss_cls: 0.7398, decode.d2.loss_mask: 0.7874, decode.d2.loss_dice: 1.0392, decode.d3.loss_cls: 0.7088, decode.d3.loss_mask: 0.7884, decode.d3.loss_dice: 1.0254, decode.d4.loss_cls: 0.6908, decode.d4.loss_mask: 0.7864, decode.d4.loss_dice: 1.0272, decode.d5.loss_cls: 0.6865, decode.d5.loss_mask: 0.7863, decode.d5.loss_dice: 1.0241, decode.d6.loss_cls: 0.6754, decode.d6.loss_mask: 0.7875, decode.d6.loss_dice: 1.0201, decode.d7.loss_cls: 0.6783, decode.d7.loss_mask: 0.7890, decode.d7.loss_dice: 1.0184, decode.d8.loss_cls: 0.6828, decode.d8.loss_mask: 0.7877, decode.d8.loss_dice: 1.0256, loss: 31.8150 +2022-05-06 01:51:13,708 - mmseg - INFO - Iter [4250/40000] lr: 1.283e-06, eta: 3 days, 13:39:47, time: 0.676, data_time: 0.008, memory: 53770, decode.loss_cls: 0.7078, decode.loss_mask: 0.7808, decode.loss_dice: 1.0559, decode.d0.loss_cls: 7.0703, decode.d0.loss_mask: 0.7572, decode.d0.loss_dice: 1.2509, decode.d1.loss_cls: 0.8937, decode.d1.loss_mask: 0.7879, decode.d1.loss_dice: 1.1236, decode.d2.loss_cls: 0.7691, decode.d2.loss_mask: 0.7765, decode.d2.loss_dice: 1.0763, decode.d3.loss_cls: 0.7399, decode.d3.loss_mask: 0.7715, decode.d3.loss_dice: 1.0517, decode.d4.loss_cls: 0.7338, decode.d4.loss_mask: 0.7737, decode.d4.loss_dice: 1.0573, decode.d5.loss_cls: 0.7212, decode.d5.loss_mask: 0.7698, decode.d5.loss_dice: 1.0494, decode.d6.loss_cls: 0.7126, decode.d6.loss_mask: 0.7720, decode.d6.loss_dice: 1.0527, decode.d7.loss_cls: 0.7113, decode.d7.loss_mask: 0.7685, decode.d7.loss_dice: 1.0441, decode.d8.loss_cls: 0.7087, decode.d8.loss_mask: 0.7704, decode.d8.loss_dice: 1.0505, loss: 32.3089 +2022-05-06 01:51:47,530 - mmseg - INFO - Iter [4300/40000] lr: 1.281e-06, eta: 3 days, 0:26:52, time: 0.676, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6607, decode.loss_mask: 0.7790, decode.loss_dice: 1.0204, decode.d0.loss_cls: 7.0398, decode.d0.loss_mask: 0.7447, decode.d0.loss_dice: 1.1978, decode.d1.loss_cls: 0.8251, decode.d1.loss_mask: 0.7939, decode.d1.loss_dice: 1.0955, decode.d2.loss_cls: 0.6922, decode.d2.loss_mask: 0.7835, decode.d2.loss_dice: 1.0423, decode.d3.loss_cls: 0.6655, decode.d3.loss_mask: 0.7756, decode.d3.loss_dice: 1.0270, decode.d4.loss_cls: 0.6479, decode.d4.loss_mask: 0.7752, decode.d4.loss_dice: 1.0340, decode.d5.loss_cls: 0.6530, decode.d5.loss_mask: 0.7736, decode.d5.loss_dice: 1.0281, decode.d6.loss_cls: 0.6426, decode.d6.loss_mask: 0.7712, decode.d6.loss_dice: 1.0208, decode.d7.loss_cls: 0.6444, decode.d7.loss_mask: 0.7745, decode.d7.loss_dice: 1.0255, decode.d8.loss_cls: 0.6493, decode.d8.loss_mask: 0.7759, decode.d8.loss_dice: 1.0195, loss: 31.3785 +2022-05-06 01:52:24,405 - mmseg - INFO - Iter [4350/40000] lr: 1.280e-06, eta: 2 days, 15:04:48, time: 0.737, data_time: 0.056, memory: 53770, decode.loss_cls: 0.6738, decode.loss_mask: 0.7830, decode.loss_dice: 1.0346, decode.d0.loss_cls: 7.0146, decode.d0.loss_mask: 0.7660, decode.d0.loss_dice: 1.2234, decode.d1.loss_cls: 0.8398, decode.d1.loss_mask: 0.8045, decode.d1.loss_dice: 1.1024, decode.d2.loss_cls: 0.7104, decode.d2.loss_mask: 0.7872, decode.d2.loss_dice: 1.0515, decode.d3.loss_cls: 0.6903, decode.d3.loss_mask: 0.7896, decode.d3.loss_dice: 1.0338, decode.d4.loss_cls: 0.6747, decode.d4.loss_mask: 0.7834, decode.d4.loss_dice: 1.0325, decode.d5.loss_cls: 0.6666, decode.d5.loss_mask: 0.7878, decode.d5.loss_dice: 1.0256, decode.d6.loss_cls: 0.6674, decode.d6.loss_mask: 0.7805, decode.d6.loss_dice: 1.0211, decode.d7.loss_cls: 0.6663, decode.d7.loss_mask: 0.7810, decode.d7.loss_dice: 1.0265, decode.d8.loss_cls: 0.6624, decode.d8.loss_mask: 0.7883, decode.d8.loss_dice: 1.0297, loss: 31.6986 +2022-05-06 01:52:58,168 - mmseg - INFO - Iter [4400/40000] lr: 1.278e-06, eta: 2 days, 7:58:14, time: 0.676, data_time: 0.010, memory: 53770, decode.loss_cls: 0.6486, decode.loss_mask: 0.7470, decode.loss_dice: 1.0384, decode.d0.loss_cls: 6.9723, decode.d0.loss_mask: 0.7213, decode.d0.loss_dice: 1.2202, decode.d1.loss_cls: 0.8393, decode.d1.loss_mask: 0.7453, decode.d1.loss_dice: 1.0972, decode.d2.loss_cls: 0.7102, decode.d2.loss_mask: 0.7410, decode.d2.loss_dice: 1.0449, decode.d3.loss_cls: 0.6818, decode.d3.loss_mask: 0.7335, decode.d3.loss_dice: 1.0373, decode.d4.loss_cls: 0.6618, decode.d4.loss_mask: 0.7390, decode.d4.loss_dice: 1.0376, decode.d5.loss_cls: 0.6498, decode.d5.loss_mask: 0.7342, decode.d5.loss_dice: 1.0363, decode.d6.loss_cls: 0.6431, decode.d6.loss_mask: 0.7328, decode.d6.loss_dice: 1.0254, decode.d7.loss_cls: 0.6488, decode.d7.loss_mask: 0.7388, decode.d7.loss_dice: 1.0281, decode.d8.loss_cls: 0.6549, decode.d8.loss_mask: 0.7397, decode.d8.loss_dice: 1.0332, loss: 31.0817 +2022-05-06 01:53:32,090 - mmseg - INFO - Iter [4450/40000] lr: 1.276e-06, eta: 2 days, 2:26:17, time: 0.678, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6466, decode.loss_mask: 0.7993, decode.loss_dice: 1.0322, decode.d0.loss_cls: 6.9437, decode.d0.loss_mask: 0.7649, decode.d0.loss_dice: 1.1926, decode.d1.loss_cls: 0.8118, decode.d1.loss_mask: 0.8046, decode.d1.loss_dice: 1.0916, decode.d2.loss_cls: 0.6841, decode.d2.loss_mask: 0.8002, decode.d2.loss_dice: 1.0444, decode.d3.loss_cls: 0.6572, decode.d3.loss_mask: 0.7949, decode.d3.loss_dice: 1.0387, decode.d4.loss_cls: 0.6544, decode.d4.loss_mask: 0.7883, decode.d4.loss_dice: 1.0380, decode.d5.loss_cls: 0.6490, decode.d5.loss_mask: 0.7911, decode.d5.loss_dice: 1.0341, decode.d6.loss_cls: 0.6456, decode.d6.loss_mask: 0.7895, decode.d6.loss_dice: 1.0223, decode.d7.loss_cls: 0.6469, decode.d7.loss_mask: 0.7911, decode.d7.loss_dice: 1.0271, decode.d8.loss_cls: 0.6452, decode.d8.loss_mask: 0.7923, decode.d8.loss_dice: 1.0343, loss: 31.4560 +2022-05-06 01:54:05,215 - mmseg - INFO - Iter [4500/40000] lr: 1.274e-06, eta: 1 day, 21:59:33, time: 0.663, data_time: 0.009, memory: 53770, decode.loss_cls: 0.6767, decode.loss_mask: 0.7676, decode.loss_dice: 1.0107, decode.d0.loss_cls: 6.9323, decode.d0.loss_mask: 0.7287, decode.d0.loss_dice: 1.1766, decode.d1.loss_cls: 0.8508, decode.d1.loss_mask: 0.7750, decode.d1.loss_dice: 1.0688, decode.d2.loss_cls: 0.7261, decode.d2.loss_mask: 0.7615, decode.d2.loss_dice: 1.0127, decode.d3.loss_cls: 0.6930, decode.d3.loss_mask: 0.7502, decode.d3.loss_dice: 0.9954, decode.d4.loss_cls: 0.6754, decode.d4.loss_mask: 0.7615, decode.d4.loss_dice: 1.0073, decode.d5.loss_cls: 0.6708, decode.d5.loss_mask: 0.7647, decode.d5.loss_dice: 1.0076, decode.d6.loss_cls: 0.6659, decode.d6.loss_mask: 0.7538, decode.d6.loss_dice: 0.9978, decode.d7.loss_cls: 0.6614, decode.d7.loss_mask: 0.7622, decode.d7.loss_dice: 1.0090, decode.d8.loss_cls: 0.6699, decode.d8.loss_mask: 0.7661, decode.d8.loss_dice: 1.0078, loss: 31.1073 +2022-05-06 01:54:39,278 - mmseg - INFO - Iter [4550/40000] lr: 1.273e-06, eta: 1 day, 18:22:08, time: 0.681, data_time: 0.010, memory: 53770, decode.loss_cls: 0.6808, decode.loss_mask: 0.7842, decode.loss_dice: 1.0512, decode.d0.loss_cls: 6.8922, decode.d0.loss_mask: 0.7383, decode.d0.loss_dice: 1.2280, decode.d1.loss_cls: 0.8451, decode.d1.loss_mask: 0.7813, decode.d1.loss_dice: 1.1172, decode.d2.loss_cls: 0.7175, decode.d2.loss_mask: 0.7783, decode.d2.loss_dice: 1.0748, decode.d3.loss_cls: 0.6837, decode.d3.loss_mask: 0.7799, decode.d3.loss_dice: 1.0441, decode.d4.loss_cls: 0.6764, decode.d4.loss_mask: 0.7757, decode.d4.loss_dice: 1.0557, decode.d5.loss_cls: 0.6703, decode.d5.loss_mask: 0.7730, decode.d5.loss_dice: 1.0544, decode.d6.loss_cls: 0.6687, decode.d6.loss_mask: 0.7757, decode.d6.loss_dice: 1.0445, decode.d7.loss_cls: 0.6686, decode.d7.loss_mask: 0.7762, decode.d7.loss_dice: 1.0518, decode.d8.loss_cls: 0.6659, decode.d8.loss_mask: 0.7814, decode.d8.loss_dice: 1.0521, loss: 31.6867 +2022-05-06 01:55:13,656 - mmseg - INFO - Iter [4600/40000] lr: 1.271e-06, eta: 1 day, 15:21:06, time: 0.688, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6677, decode.loss_mask: 0.7904, decode.loss_dice: 1.0106, decode.d0.loss_cls: 6.8812, decode.d0.loss_mask: 0.7737, decode.d0.loss_dice: 1.1744, decode.d1.loss_cls: 0.8401, decode.d1.loss_mask: 0.8125, decode.d1.loss_dice: 1.0625, decode.d2.loss_cls: 0.7253, decode.d2.loss_mask: 0.7874, decode.d2.loss_dice: 1.0123, decode.d3.loss_cls: 0.6885, decode.d3.loss_mask: 0.7858, decode.d3.loss_dice: 0.9957, decode.d4.loss_cls: 0.6772, decode.d4.loss_mask: 0.7886, decode.d4.loss_dice: 1.0034, decode.d5.loss_cls: 0.6663, decode.d5.loss_mask: 0.7878, decode.d5.loss_dice: 1.0010, decode.d6.loss_cls: 0.6601, decode.d6.loss_mask: 0.7917, decode.d6.loss_dice: 0.9989, decode.d7.loss_cls: 0.6680, decode.d7.loss_mask: 0.7890, decode.d7.loss_dice: 1.0042, decode.d8.loss_cls: 0.6615, decode.d8.loss_mask: 0.7875, decode.d8.loss_dice: 1.0119, loss: 31.3051 +2022-05-06 01:55:50,051 - mmseg - INFO - Iter [4650/40000] lr: 1.269e-06, eta: 1 day, 12:49:37, time: 0.728, data_time: 0.061, memory: 53770, decode.loss_cls: 0.6330, decode.loss_mask: 0.7497, decode.loss_dice: 1.0390, decode.d0.loss_cls: 6.8445, decode.d0.loss_mask: 0.7220, decode.d0.loss_dice: 1.1897, decode.d1.loss_cls: 0.8018, decode.d1.loss_mask: 0.7488, decode.d1.loss_dice: 1.0927, decode.d2.loss_cls: 0.6822, decode.d2.loss_mask: 0.7308, decode.d2.loss_dice: 1.0446, decode.d3.loss_cls: 0.6523, decode.d3.loss_mask: 0.7318, decode.d3.loss_dice: 1.0290, decode.d4.loss_cls: 0.6323, decode.d4.loss_mask: 0.7402, decode.d4.loss_dice: 1.0397, decode.d5.loss_cls: 0.6414, decode.d5.loss_mask: 0.7305, decode.d5.loss_dice: 1.0341, decode.d6.loss_cls: 0.6357, decode.d6.loss_mask: 0.7365, decode.d6.loss_dice: 1.0248, decode.d7.loss_cls: 0.6287, decode.d7.loss_mask: 0.7345, decode.d7.loss_dice: 1.0315, decode.d8.loss_cls: 0.6310, decode.d8.loss_mask: 0.7394, decode.d8.loss_dice: 1.0354, loss: 30.7077 +2022-05-06 01:56:23,437 - mmseg - INFO - Iter [4700/40000] lr: 1.267e-06, eta: 1 day, 10:37:08, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6057, decode.loss_mask: 0.7419, decode.loss_dice: 0.9614, decode.d0.loss_cls: 6.8001, decode.d0.loss_mask: 0.7348, decode.d0.loss_dice: 1.1489, decode.d1.loss_cls: 0.7640, decode.d1.loss_mask: 0.7640, decode.d1.loss_dice: 1.0357, decode.d2.loss_cls: 0.6421, decode.d2.loss_mask: 0.7526, decode.d2.loss_dice: 0.9792, decode.d3.loss_cls: 0.6232, decode.d3.loss_mask: 0.7472, decode.d3.loss_dice: 0.9663, decode.d4.loss_cls: 0.6186, decode.d4.loss_mask: 0.7447, decode.d4.loss_dice: 0.9631, decode.d5.loss_cls: 0.6155, decode.d5.loss_mask: 0.7461, decode.d5.loss_dice: 0.9634, decode.d6.loss_cls: 0.6014, decode.d6.loss_mask: 0.7483, decode.d6.loss_dice: 0.9623, decode.d7.loss_cls: 0.5999, decode.d7.loss_mask: 0.7451, decode.d7.loss_dice: 0.9644, decode.d8.loss_cls: 0.5958, decode.d8.loss_mask: 0.7482, decode.d8.loss_dice: 0.9565, loss: 29.8404 +2022-05-06 01:56:57,027 - mmseg - INFO - Iter [4750/40000] lr: 1.265e-06, eta: 1 day, 8:42:22, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.6105, decode.loss_mask: 0.7537, decode.loss_dice: 1.0003, decode.d0.loss_cls: 6.7636, decode.d0.loss_mask: 0.7314, decode.d0.loss_dice: 1.1608, decode.d1.loss_cls: 0.7718, decode.d1.loss_mask: 0.7596, decode.d1.loss_dice: 1.0639, decode.d2.loss_cls: 0.6537, decode.d2.loss_mask: 0.7472, decode.d2.loss_dice: 1.0233, decode.d3.loss_cls: 0.6343, decode.d3.loss_mask: 0.7455, decode.d3.loss_dice: 0.9990, decode.d4.loss_cls: 0.6246, decode.d4.loss_mask: 0.7458, decode.d4.loss_dice: 1.0048, decode.d5.loss_cls: 0.6186, decode.d5.loss_mask: 0.7437, decode.d5.loss_dice: 0.9963, decode.d6.loss_cls: 0.6085, decode.d6.loss_mask: 0.7464, decode.d6.loss_dice: 0.9994, decode.d7.loss_cls: 0.6095, decode.d7.loss_mask: 0.7461, decode.d7.loss_dice: 1.0015, decode.d8.loss_cls: 0.6069, decode.d8.loss_mask: 0.7496, decode.d8.loss_dice: 1.0022, loss: 30.2225 +2022-05-06 01:57:30,227 - mmseg - INFO - Iter [4800/40000] lr: 1.264e-06, eta: 1 day, 7:01:34, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.6677, decode.loss_mask: 0.7711, decode.loss_dice: 1.0411, decode.d0.loss_cls: 6.7545, decode.d0.loss_mask: 0.7465, decode.d0.loss_dice: 1.2216, decode.d1.loss_cls: 0.8336, decode.d1.loss_mask: 0.7876, decode.d1.loss_dice: 1.1027, decode.d2.loss_cls: 0.7177, decode.d2.loss_mask: 0.7756, decode.d2.loss_dice: 1.0556, decode.d3.loss_cls: 0.6790, decode.d3.loss_mask: 0.7828, decode.d3.loss_dice: 1.0464, decode.d4.loss_cls: 0.6646, decode.d4.loss_mask: 0.7759, decode.d4.loss_dice: 1.0465, decode.d5.loss_cls: 0.6667, decode.d5.loss_mask: 0.7773, decode.d5.loss_dice: 1.0434, decode.d6.loss_cls: 0.6519, decode.d6.loss_mask: 0.7813, decode.d6.loss_dice: 1.0333, decode.d7.loss_cls: 0.6614, decode.d7.loss_mask: 0.7759, decode.d7.loss_dice: 1.0372, decode.d8.loss_cls: 0.6621, decode.d8.loss_mask: 0.7785, decode.d8.loss_dice: 1.0383, loss: 31.3778 +2022-05-06 01:58:04,311 - mmseg - INFO - Iter [4850/40000] lr: 1.262e-06, eta: 1 day, 5:33:10, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.6183, decode.loss_mask: 0.7703, decode.loss_dice: 1.0101, decode.d0.loss_cls: 6.7423, decode.d0.loss_mask: 0.7420, decode.d0.loss_dice: 1.1773, decode.d1.loss_cls: 0.7908, decode.d1.loss_mask: 0.7783, decode.d1.loss_dice: 1.0733, decode.d2.loss_cls: 0.6726, decode.d2.loss_mask: 0.7662, decode.d2.loss_dice: 1.0255, decode.d3.loss_cls: 0.6368, decode.d3.loss_mask: 0.7659, decode.d3.loss_dice: 1.0120, decode.d4.loss_cls: 0.6277, decode.d4.loss_mask: 0.7698, decode.d4.loss_dice: 1.0153, decode.d5.loss_cls: 0.6234, decode.d5.loss_mask: 0.7669, decode.d5.loss_dice: 1.0087, decode.d6.loss_cls: 0.6172, decode.d6.loss_mask: 0.7686, decode.d6.loss_dice: 1.0076, decode.d7.loss_cls: 0.6111, decode.d7.loss_mask: 0.7740, decode.d7.loss_dice: 1.0103, decode.d8.loss_cls: 0.6041, decode.d8.loss_mask: 0.7715, decode.d8.loss_dice: 1.0153, loss: 30.5733 +2022-05-06 01:58:38,317 - mmseg - INFO - Iter [4900/40000] lr: 1.260e-06, eta: 1 day, 4:14:28, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.6061, decode.loss_mask: 0.7276, decode.loss_dice: 0.9881, decode.d0.loss_cls: 6.6974, decode.d0.loss_mask: 0.7051, decode.d0.loss_dice: 1.1562, decode.d1.loss_cls: 0.7700, decode.d1.loss_mask: 0.7492, decode.d1.loss_dice: 1.0573, decode.d2.loss_cls: 0.6510, decode.d2.loss_mask: 0.7338, decode.d2.loss_dice: 1.0043, decode.d3.loss_cls: 0.6252, decode.d3.loss_mask: 0.7356, decode.d3.loss_dice: 0.9909, decode.d4.loss_cls: 0.6194, decode.d4.loss_mask: 0.7313, decode.d4.loss_dice: 0.9947, decode.d5.loss_cls: 0.6052, decode.d5.loss_mask: 0.7216, decode.d5.loss_dice: 0.9963, decode.d6.loss_cls: 0.5969, decode.d6.loss_mask: 0.7214, decode.d6.loss_dice: 0.9865, decode.d7.loss_cls: 0.6034, decode.d7.loss_mask: 0.7224, decode.d7.loss_dice: 0.9961, decode.d8.loss_cls: 0.6009, decode.d8.loss_mask: 0.7236, decode.d8.loss_dice: 0.9901, loss: 29.8077 +2022-05-06 01:59:14,412 - mmseg - INFO - Iter [4950/40000] lr: 1.258e-06, eta: 1 day, 3:05:16, time: 0.722, data_time: 0.057, memory: 53770, decode.loss_cls: 0.6091, decode.loss_mask: 0.7319, decode.loss_dice: 0.9825, decode.d0.loss_cls: 6.6972, decode.d0.loss_mask: 0.7201, decode.d0.loss_dice: 1.1483, decode.d1.loss_cls: 0.7737, decode.d1.loss_mask: 0.7383, decode.d1.loss_dice: 1.0375, decode.d2.loss_cls: 0.6590, decode.d2.loss_mask: 0.7289, decode.d2.loss_dice: 0.9974, decode.d3.loss_cls: 0.6327, decode.d3.loss_mask: 0.7319, decode.d3.loss_dice: 0.9841, decode.d4.loss_cls: 0.6248, decode.d4.loss_mask: 0.7297, decode.d4.loss_dice: 0.9878, decode.d5.loss_cls: 0.6185, decode.d5.loss_mask: 0.7264, decode.d5.loss_dice: 0.9809, decode.d6.loss_cls: 0.6096, decode.d6.loss_mask: 0.7233, decode.d6.loss_dice: 0.9731, decode.d7.loss_cls: 0.6110, decode.d7.loss_mask: 0.7226, decode.d7.loss_dice: 0.9735, decode.d8.loss_cls: 0.6041, decode.d8.loss_mask: 0.7269, decode.d8.loss_dice: 0.9816, loss: 29.7663 +2022-05-06 01:59:48,128 - mmseg - INFO - Saving checkpoint at 5000 iterations +2022-05-06 02:00:14,762 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 02:00:14,770 - mmseg - INFO - Iter [5000/40000] lr: 1.256e-06, eta: 1 day, 2:16:59, time: 1.205, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5825, decode.loss_mask: 0.7487, decode.loss_dice: 0.9900, decode.d0.loss_cls: 6.6466, decode.d0.loss_mask: 0.7281, decode.d0.loss_dice: 1.1420, decode.d1.loss_cls: 0.7414, decode.d1.loss_mask: 0.7628, decode.d1.loss_dice: 1.0528, decode.d2.loss_cls: 0.6354, decode.d2.loss_mask: 0.7539, decode.d2.loss_dice: 1.0113, decode.d3.loss_cls: 0.5958, decode.d3.loss_mask: 0.7514, decode.d3.loss_dice: 0.9917, decode.d4.loss_cls: 0.5916, decode.d4.loss_mask: 0.7564, decode.d4.loss_dice: 0.9926, decode.d5.loss_cls: 0.5797, decode.d5.loss_mask: 0.7553, decode.d5.loss_dice: 0.9951, decode.d6.loss_cls: 0.5746, decode.d6.loss_mask: 0.7549, decode.d6.loss_dice: 0.9941, decode.d7.loss_cls: 0.5790, decode.d7.loss_mask: 0.7525, decode.d7.loss_dice: 0.9878, decode.d8.loss_cls: 0.5713, decode.d8.loss_mask: 0.7511, decode.d8.loss_dice: 0.9935, loss: 29.7636 +2022-05-06 02:00:49,483 - mmseg - INFO - Iter [5050/40000] lr: 1.255e-06, eta: 1 day, 1:19:07, time: 0.697, data_time: 0.010, memory: 53770, decode.loss_cls: 0.5738, decode.loss_mask: 0.7295, decode.loss_dice: 0.9702, decode.d0.loss_cls: 6.6169, decode.d0.loss_mask: 0.7123, decode.d0.loss_dice: 1.1285, decode.d1.loss_cls: 0.7206, decode.d1.loss_mask: 0.7478, decode.d1.loss_dice: 1.0237, decode.d2.loss_cls: 0.6008, decode.d2.loss_mask: 0.7379, decode.d2.loss_dice: 0.9829, decode.d3.loss_cls: 0.5762, decode.d3.loss_mask: 0.7339, decode.d3.loss_dice: 0.9664, decode.d4.loss_cls: 0.5726, decode.d4.loss_mask: 0.7312, decode.d4.loss_dice: 0.9741, decode.d5.loss_cls: 0.5662, decode.d5.loss_mask: 0.7306, decode.d5.loss_dice: 0.9665, decode.d6.loss_cls: 0.5622, decode.d6.loss_mask: 0.7336, decode.d6.loss_dice: 0.9608, decode.d7.loss_cls: 0.5581, decode.d7.loss_mask: 0.7332, decode.d7.loss_dice: 0.9643, decode.d8.loss_cls: 0.5635, decode.d8.loss_mask: 0.7314, decode.d8.loss_dice: 0.9604, loss: 29.1301 +2022-05-06 02:01:23,736 - mmseg - INFO - Iter [5100/40000] lr: 1.253e-06, eta: 1 day, 0:26:09, time: 0.685, data_time: 0.008, memory: 53770, decode.loss_cls: 0.6063, decode.loss_mask: 0.7593, decode.loss_dice: 1.0044, decode.d0.loss_cls: 6.5914, decode.d0.loss_mask: 0.7386, decode.d0.loss_dice: 1.1727, decode.d1.loss_cls: 0.7788, decode.d1.loss_mask: 0.7674, decode.d1.loss_dice: 1.0682, decode.d2.loss_cls: 0.6700, decode.d2.loss_mask: 0.7612, decode.d2.loss_dice: 1.0235, decode.d3.loss_cls: 0.6384, decode.d3.loss_mask: 0.7508, decode.d3.loss_dice: 1.0067, decode.d4.loss_cls: 0.6287, decode.d4.loss_mask: 0.7497, decode.d4.loss_dice: 1.0091, decode.d5.loss_cls: 0.6187, decode.d5.loss_mask: 0.7497, decode.d5.loss_dice: 1.0073, decode.d6.loss_cls: 0.6090, decode.d6.loss_mask: 0.7487, decode.d6.loss_dice: 1.0019, decode.d7.loss_cls: 0.6083, decode.d7.loss_mask: 0.7527, decode.d7.loss_dice: 1.0050, decode.d8.loss_cls: 0.6105, decode.d8.loss_mask: 0.7560, decode.d8.loss_dice: 1.0021, loss: 30.1952 +2022-05-06 02:01:58,106 - mmseg - INFO - Iter [5150/40000] lr: 1.251e-06, eta: 23:37:48, time: 0.687, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5823, decode.loss_mask: 0.7321, decode.loss_dice: 0.9751, decode.d0.loss_cls: 6.5714, decode.d0.loss_mask: 0.7037, decode.d0.loss_dice: 1.1433, decode.d1.loss_cls: 0.7398, decode.d1.loss_mask: 0.7420, decode.d1.loss_dice: 1.0338, decode.d2.loss_cls: 0.6223, decode.d2.loss_mask: 0.7354, decode.d2.loss_dice: 0.9885, decode.d3.loss_cls: 0.5908, decode.d3.loss_mask: 0.7294, decode.d3.loss_dice: 0.9767, decode.d4.loss_cls: 0.5849, decode.d4.loss_mask: 0.7240, decode.d4.loss_dice: 0.9716, decode.d5.loss_cls: 0.5847, decode.d5.loss_mask: 0.7181, decode.d5.loss_dice: 0.9708, decode.d6.loss_cls: 0.5726, decode.d6.loss_mask: 0.7244, decode.d6.loss_dice: 0.9678, decode.d7.loss_cls: 0.5757, decode.d7.loss_mask: 0.7239, decode.d7.loss_dice: 0.9711, decode.d8.loss_cls: 0.5727, decode.d8.loss_mask: 0.7244, decode.d8.loss_dice: 0.9735, loss: 29.2267 +2022-05-06 02:02:31,592 - mmseg - INFO - Iter [5200/40000] lr: 1.249e-06, eta: 22:53:00, time: 0.670, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5915, decode.loss_mask: 0.7403, decode.loss_dice: 0.9482, decode.d0.loss_cls: 6.5177, decode.d0.loss_mask: 0.7263, decode.d0.loss_dice: 1.1201, decode.d1.loss_cls: 0.7388, decode.d1.loss_mask: 0.7542, decode.d1.loss_dice: 1.0161, decode.d2.loss_cls: 0.6276, decode.d2.loss_mask: 0.7386, decode.d2.loss_dice: 0.9670, decode.d3.loss_cls: 0.5976, decode.d3.loss_mask: 0.7383, decode.d3.loss_dice: 0.9483, decode.d4.loss_cls: 0.6009, decode.d4.loss_mask: 0.7285, decode.d4.loss_dice: 0.9505, decode.d5.loss_cls: 0.5920, decode.d5.loss_mask: 0.7348, decode.d5.loss_dice: 0.9491, decode.d6.loss_cls: 0.5901, decode.d6.loss_mask: 0.7343, decode.d6.loss_dice: 0.9418, decode.d7.loss_cls: 0.5879, decode.d7.loss_mask: 0.7334, decode.d7.loss_dice: 0.9451, decode.d8.loss_cls: 0.5832, decode.d8.loss_mask: 0.7431, decode.d8.loss_dice: 0.9416, loss: 29.1269 +2022-05-06 02:03:07,667 - mmseg - INFO - Iter [5250/40000] lr: 1.247e-06, eta: 22:12:55, time: 0.721, data_time: 0.061, memory: 53770, decode.loss_cls: 0.6131, decode.loss_mask: 0.7296, decode.loss_dice: 0.9935, decode.d0.loss_cls: 6.4977, decode.d0.loss_mask: 0.7223, decode.d0.loss_dice: 1.1681, decode.d1.loss_cls: 0.7824, decode.d1.loss_mask: 0.7485, decode.d1.loss_dice: 1.0631, decode.d2.loss_cls: 0.6638, decode.d2.loss_mask: 0.7278, decode.d2.loss_dice: 1.0090, decode.d3.loss_cls: 0.6289, decode.d3.loss_mask: 0.7317, decode.d3.loss_dice: 0.9909, decode.d4.loss_cls: 0.6214, decode.d4.loss_mask: 0.7317, decode.d4.loss_dice: 0.9935, decode.d5.loss_cls: 0.6140, decode.d5.loss_mask: 0.7310, decode.d5.loss_dice: 0.9879, decode.d6.loss_cls: 0.6063, decode.d6.loss_mask: 0.7300, decode.d6.loss_dice: 0.9849, decode.d7.loss_cls: 0.6131, decode.d7.loss_mask: 0.7230, decode.d7.loss_dice: 0.9983, decode.d8.loss_cls: 0.6166, decode.d8.loss_mask: 0.7251, decode.d8.loss_dice: 0.9924, loss: 29.7399 +2022-05-06 02:03:41,049 - mmseg - INFO - Iter [5300/40000] lr: 1.246e-06, eta: 21:34:42, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5558, decode.loss_mask: 0.7108, decode.loss_dice: 0.9593, decode.d0.loss_cls: 6.4809, decode.d0.loss_mask: 0.7049, decode.d0.loss_dice: 1.1335, decode.d1.loss_cls: 0.7250, decode.d1.loss_mask: 0.7215, decode.d1.loss_dice: 1.0151, decode.d2.loss_cls: 0.6071, decode.d2.loss_mask: 0.7113, decode.d2.loss_dice: 0.9718, decode.d3.loss_cls: 0.5812, decode.d3.loss_mask: 0.7002, decode.d3.loss_dice: 0.9498, decode.d4.loss_cls: 0.5763, decode.d4.loss_mask: 0.7015, decode.d4.loss_dice: 0.9616, decode.d5.loss_cls: 0.5659, decode.d5.loss_mask: 0.7049, decode.d5.loss_dice: 0.9559, decode.d6.loss_cls: 0.5663, decode.d6.loss_mask: 0.7027, decode.d6.loss_dice: 0.9474, decode.d7.loss_cls: 0.5590, decode.d7.loss_mask: 0.7012, decode.d7.loss_dice: 0.9514, decode.d8.loss_cls: 0.5591, decode.d8.loss_mask: 0.7089, decode.d8.loss_dice: 0.9568, loss: 28.6472 +2022-05-06 02:04:14,425 - mmseg - INFO - Iter [5350/40000] lr: 1.244e-06, eta: 20:59:15, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5756, decode.loss_mask: 0.7013, decode.loss_dice: 0.9780, decode.d0.loss_cls: 6.4375, decode.d0.loss_mask: 0.6929, decode.d0.loss_dice: 1.1382, decode.d1.loss_cls: 0.7355, decode.d1.loss_mask: 0.7185, decode.d1.loss_dice: 1.0468, decode.d2.loss_cls: 0.6262, decode.d2.loss_mask: 0.7014, decode.d2.loss_dice: 1.0075, decode.d3.loss_cls: 0.5947, decode.d3.loss_mask: 0.6973, decode.d3.loss_dice: 0.9824, decode.d4.loss_cls: 0.5971, decode.d4.loss_mask: 0.6950, decode.d4.loss_dice: 0.9810, decode.d5.loss_cls: 0.5879, decode.d5.loss_mask: 0.6955, decode.d5.loss_dice: 0.9741, decode.d6.loss_cls: 0.5857, decode.d6.loss_mask: 0.6921, decode.d6.loss_dice: 0.9726, decode.d7.loss_cls: 0.5782, decode.d7.loss_mask: 0.6998, decode.d7.loss_dice: 0.9769, decode.d8.loss_cls: 0.5743, decode.d8.loss_mask: 0.7008, decode.d8.loss_dice: 0.9755, loss: 28.9204 +2022-05-06 02:04:48,243 - mmseg - INFO - Iter [5400/40000] lr: 1.242e-06, eta: 20:26:28, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5946, decode.loss_mask: 0.7305, decode.loss_dice: 0.9870, decode.d0.loss_cls: 6.4252, decode.d0.loss_mask: 0.7181, decode.d0.loss_dice: 1.1630, decode.d1.loss_cls: 0.7536, decode.d1.loss_mask: 0.7465, decode.d1.loss_dice: 1.0541, decode.d2.loss_cls: 0.6407, decode.d2.loss_mask: 0.7362, decode.d2.loss_dice: 1.0057, decode.d3.loss_cls: 0.6074, decode.d3.loss_mask: 0.7307, decode.d3.loss_dice: 0.9828, decode.d4.loss_cls: 0.5985, decode.d4.loss_mask: 0.7327, decode.d4.loss_dice: 0.9868, decode.d5.loss_cls: 0.5998, decode.d5.loss_mask: 0.7280, decode.d5.loss_dice: 0.9863, decode.d6.loss_cls: 0.5937, decode.d6.loss_mask: 0.7287, decode.d6.loss_dice: 0.9775, decode.d7.loss_cls: 0.5969, decode.d7.loss_mask: 0.7309, decode.d7.loss_dice: 0.9815, decode.d8.loss_cls: 0.5910, decode.d8.loss_mask: 0.7283, decode.d8.loss_dice: 0.9873, loss: 29.4242 +2022-05-06 02:05:21,961 - mmseg - INFO - Iter [5450/40000] lr: 1.240e-06, eta: 19:55:53, time: 0.674, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5703, decode.loss_mask: 0.7071, decode.loss_dice: 0.9286, decode.d0.loss_cls: 6.3873, decode.d0.loss_mask: 0.6895, decode.d0.loss_dice: 1.0827, decode.d1.loss_cls: 0.7128, decode.d1.loss_mask: 0.7195, decode.d1.loss_dice: 0.9890, decode.d2.loss_cls: 0.6128, decode.d2.loss_mask: 0.7053, decode.d2.loss_dice: 0.9418, decode.d3.loss_cls: 0.5892, decode.d3.loss_mask: 0.7045, decode.d3.loss_dice: 0.9218, decode.d4.loss_cls: 0.5771, decode.d4.loss_mask: 0.7052, decode.d4.loss_dice: 0.9328, decode.d5.loss_cls: 0.5688, decode.d5.loss_mask: 0.7029, decode.d5.loss_dice: 0.9233, decode.d6.loss_cls: 0.5651, decode.d6.loss_mask: 0.7010, decode.d6.loss_dice: 0.9212, decode.d7.loss_cls: 0.5633, decode.d7.loss_mask: 0.7025, decode.d7.loss_dice: 0.9277, decode.d8.loss_cls: 0.5648, decode.d8.loss_mask: 0.7094, decode.d8.loss_dice: 0.9262, loss: 28.2537 +2022-05-06 02:05:55,587 - mmseg - INFO - Iter [5500/40000] lr: 1.238e-06, eta: 19:27:15, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5562, decode.loss_mask: 0.7409, decode.loss_dice: 0.9705, decode.d0.loss_cls: 6.3472, decode.d0.loss_mask: 0.7235, decode.d0.loss_dice: 1.1171, decode.d1.loss_cls: 0.7100, decode.d1.loss_mask: 0.7647, decode.d1.loss_dice: 1.0255, decode.d2.loss_cls: 0.5945, decode.d2.loss_mask: 0.7544, decode.d2.loss_dice: 0.9814, decode.d3.loss_cls: 0.5660, decode.d3.loss_mask: 0.7457, decode.d3.loss_dice: 0.9710, decode.d4.loss_cls: 0.5632, decode.d4.loss_mask: 0.7453, decode.d4.loss_dice: 0.9791, decode.d5.loss_cls: 0.5660, decode.d5.loss_mask: 0.7399, decode.d5.loss_dice: 0.9704, decode.d6.loss_cls: 0.5632, decode.d6.loss_mask: 0.7388, decode.d6.loss_dice: 0.9658, decode.d7.loss_cls: 0.5556, decode.d7.loss_mask: 0.7428, decode.d7.loss_dice: 0.9654, decode.d8.loss_cls: 0.5487, decode.d8.loss_mask: 0.7476, decode.d8.loss_dice: 0.9745, loss: 28.9349 +2022-05-06 02:06:29,586 - mmseg - INFO - Iter [5550/40000] lr: 1.237e-06, eta: 19:00:34, time: 0.680, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5771, decode.loss_mask: 0.7084, decode.loss_dice: 0.9421, decode.d0.loss_cls: 6.3364, decode.d0.loss_mask: 0.6841, decode.d0.loss_dice: 1.0997, decode.d1.loss_cls: 0.7203, decode.d1.loss_mask: 0.7206, decode.d1.loss_dice: 0.9992, decode.d2.loss_cls: 0.6076, decode.d2.loss_mask: 0.7030, decode.d2.loss_dice: 0.9565, decode.d3.loss_cls: 0.5802, decode.d3.loss_mask: 0.7013, decode.d3.loss_dice: 0.9391, decode.d4.loss_cls: 0.5746, decode.d4.loss_mask: 0.7046, decode.d4.loss_dice: 0.9417, decode.d5.loss_cls: 0.5715, decode.d5.loss_mask: 0.7033, decode.d5.loss_dice: 0.9412, decode.d6.loss_cls: 0.5733, decode.d6.loss_mask: 0.6986, decode.d6.loss_dice: 0.9355, decode.d7.loss_cls: 0.5699, decode.d7.loss_mask: 0.7025, decode.d7.loss_dice: 0.9421, decode.d8.loss_cls: 0.5615, decode.d8.loss_mask: 0.7058, decode.d8.loss_dice: 0.9476, loss: 28.3494 +2022-05-06 02:07:06,380 - mmseg - INFO - Iter [5600/40000] lr: 1.235e-06, eta: 18:36:31, time: 0.736, data_time: 0.059, memory: 53770, decode.loss_cls: 0.5156, decode.loss_mask: 0.6858, decode.loss_dice: 0.9564, decode.d0.loss_cls: 6.3180, decode.d0.loss_mask: 0.6628, decode.d0.loss_dice: 1.1139, decode.d1.loss_cls: 0.6842, decode.d1.loss_mask: 0.6910, decode.d1.loss_dice: 1.0177, decode.d2.loss_cls: 0.5629, decode.d2.loss_mask: 0.6874, decode.d2.loss_dice: 0.9815, decode.d3.loss_cls: 0.5468, decode.d3.loss_mask: 0.6863, decode.d3.loss_dice: 0.9625, decode.d4.loss_cls: 0.5321, decode.d4.loss_mask: 0.6788, decode.d4.loss_dice: 0.9615, decode.d5.loss_cls: 0.5341, decode.d5.loss_mask: 0.6769, decode.d5.loss_dice: 0.9537, decode.d6.loss_cls: 0.5285, decode.d6.loss_mask: 0.6741, decode.d6.loss_dice: 0.9521, decode.d7.loss_cls: 0.5180, decode.d7.loss_mask: 0.6780, decode.d7.loss_dice: 0.9523, decode.d8.loss_cls: 0.5187, decode.d8.loss_mask: 0.6843, decode.d8.loss_dice: 0.9547, loss: 27.8706 +2022-05-06 02:07:39,751 - mmseg - INFO - Iter [5650/40000] lr: 1.233e-06, eta: 18:12:42, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5357, decode.loss_mask: 0.6972, decode.loss_dice: 0.9280, decode.d0.loss_cls: 6.2656, decode.d0.loss_mask: 0.6872, decode.d0.loss_dice: 1.1046, decode.d1.loss_cls: 0.6793, decode.d1.loss_mask: 0.7140, decode.d1.loss_dice: 0.9956, decode.d2.loss_cls: 0.5874, decode.d2.loss_mask: 0.6983, decode.d2.loss_dice: 0.9539, decode.d3.loss_cls: 0.5620, decode.d3.loss_mask: 0.6909, decode.d3.loss_dice: 0.9367, decode.d4.loss_cls: 0.5469, decode.d4.loss_mask: 0.6956, decode.d4.loss_dice: 0.9450, decode.d5.loss_cls: 0.5475, decode.d5.loss_mask: 0.6906, decode.d5.loss_dice: 0.9339, decode.d6.loss_cls: 0.5327, decode.d6.loss_mask: 0.6963, decode.d6.loss_dice: 0.9291, decode.d7.loss_cls: 0.5325, decode.d7.loss_mask: 0.6975, decode.d7.loss_dice: 0.9342, decode.d8.loss_cls: 0.5378, decode.d8.loss_mask: 0.6943, decode.d8.loss_dice: 0.9304, loss: 27.8808 +2022-05-06 02:08:13,741 - mmseg - INFO - Iter [5700/40000] lr: 1.231e-06, eta: 17:50:28, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5444, decode.loss_mask: 0.7199, decode.loss_dice: 0.9257, decode.d0.loss_cls: 6.2457, decode.d0.loss_mask: 0.7111, decode.d0.loss_dice: 1.0801, decode.d1.loss_cls: 0.6840, decode.d1.loss_mask: 0.7429, decode.d1.loss_dice: 0.9767, decode.d2.loss_cls: 0.5772, decode.d2.loss_mask: 0.7343, decode.d2.loss_dice: 0.9349, decode.d3.loss_cls: 0.5549, decode.d3.loss_mask: 0.7264, decode.d3.loss_dice: 0.9240, decode.d4.loss_cls: 0.5454, decode.d4.loss_mask: 0.7228, decode.d4.loss_dice: 0.9345, decode.d5.loss_cls: 0.5523, decode.d5.loss_mask: 0.7129, decode.d5.loss_dice: 0.9222, decode.d6.loss_cls: 0.5458, decode.d6.loss_mask: 0.7163, decode.d6.loss_dice: 0.9193, decode.d7.loss_cls: 0.5409, decode.d7.loss_mask: 0.7162, decode.d7.loss_dice: 0.9250, decode.d8.loss_cls: 0.5419, decode.d8.loss_mask: 0.7174, decode.d8.loss_dice: 0.9203, loss: 28.0155 +2022-05-06 02:08:47,038 - mmseg - INFO - Iter [5750/40000] lr: 1.229e-06, eta: 17:29:13, time: 0.665, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5545, decode.loss_mask: 0.7079, decode.loss_dice: 0.9408, decode.d0.loss_cls: 6.2014, decode.d0.loss_mask: 0.6942, decode.d0.loss_dice: 1.0977, decode.d1.loss_cls: 0.6790, decode.d1.loss_mask: 0.7126, decode.d1.loss_dice: 0.9967, decode.d2.loss_cls: 0.5861, decode.d2.loss_mask: 0.7028, decode.d2.loss_dice: 0.9506, decode.d3.loss_cls: 0.5678, decode.d3.loss_mask: 0.7044, decode.d3.loss_dice: 0.9333, decode.d4.loss_cls: 0.5670, decode.d4.loss_mask: 0.7017, decode.d4.loss_dice: 0.9448, decode.d5.loss_cls: 0.5439, decode.d5.loss_mask: 0.7062, decode.d5.loss_dice: 0.9443, decode.d6.loss_cls: 0.5492, decode.d6.loss_mask: 0.6999, decode.d6.loss_dice: 0.9331, decode.d7.loss_cls: 0.5467, decode.d7.loss_mask: 0.7058, decode.d7.loss_dice: 0.9423, decode.d8.loss_cls: 0.5474, decode.d8.loss_mask: 0.7047, decode.d8.loss_dice: 0.9442, loss: 28.0109 +2022-05-06 02:09:20,840 - mmseg - INFO - Iter [5800/40000] lr: 1.228e-06, eta: 17:09:19, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.5515, decode.loss_mask: 0.7004, decode.loss_dice: 0.9456, decode.d0.loss_cls: 6.1972, decode.d0.loss_mask: 0.6888, decode.d0.loss_dice: 1.1119, decode.d1.loss_cls: 0.6838, decode.d1.loss_mask: 0.7248, decode.d1.loss_dice: 1.0181, decode.d2.loss_cls: 0.5917, decode.d2.loss_mask: 0.7014, decode.d2.loss_dice: 0.9688, decode.d3.loss_cls: 0.5625, decode.d3.loss_mask: 0.6983, decode.d3.loss_dice: 0.9492, decode.d4.loss_cls: 0.5631, decode.d4.loss_mask: 0.6933, decode.d4.loss_dice: 0.9472, decode.d5.loss_cls: 0.5492, decode.d5.loss_mask: 0.6904, decode.d5.loss_dice: 0.9405, decode.d6.loss_cls: 0.5394, decode.d6.loss_mask: 0.6931, decode.d6.loss_dice: 0.9416, decode.d7.loss_cls: 0.5468, decode.d7.loss_mask: 0.6958, decode.d7.loss_dice: 0.9462, decode.d8.loss_cls: 0.5471, decode.d8.loss_mask: 0.6894, decode.d8.loss_dice: 0.9429, loss: 28.0202 +2022-05-06 02:09:54,487 - mmseg - INFO - Iter [5850/40000] lr: 1.226e-06, eta: 16:50:23, time: 0.672, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5352, decode.loss_mask: 0.7275, decode.loss_dice: 0.9607, decode.d0.loss_cls: 6.1760, decode.d0.loss_mask: 0.7127, decode.d0.loss_dice: 1.1125, decode.d1.loss_cls: 0.6609, decode.d1.loss_mask: 0.7398, decode.d1.loss_dice: 1.0186, decode.d2.loss_cls: 0.5739, decode.d2.loss_mask: 0.7303, decode.d2.loss_dice: 0.9712, decode.d3.loss_cls: 0.5560, decode.d3.loss_mask: 0.7229, decode.d3.loss_dice: 0.9546, decode.d4.loss_cls: 0.5405, decode.d4.loss_mask: 0.7225, decode.d4.loss_dice: 0.9570, decode.d5.loss_cls: 0.5430, decode.d5.loss_mask: 0.7238, decode.d5.loss_dice: 0.9545, decode.d6.loss_cls: 0.5389, decode.d6.loss_mask: 0.7211, decode.d6.loss_dice: 0.9556, decode.d7.loss_cls: 0.5434, decode.d7.loss_mask: 0.7168, decode.d7.loss_dice: 0.9562, decode.d8.loss_cls: 0.5423, decode.d8.loss_mask: 0.7256, decode.d8.loss_dice: 0.9587, loss: 28.2528 +2022-05-06 02:10:30,815 - mmseg - INFO - Iter [5900/40000] lr: 1.224e-06, eta: 16:33:14, time: 0.727, data_time: 0.059, memory: 53770, decode.loss_cls: 0.5296, decode.loss_mask: 0.6719, decode.loss_dice: 0.9367, decode.d0.loss_cls: 6.1106, decode.d0.loss_mask: 0.6711, decode.d0.loss_dice: 1.0894, decode.d1.loss_cls: 0.6891, decode.d1.loss_mask: 0.6940, decode.d1.loss_dice: 0.9888, decode.d2.loss_cls: 0.5813, decode.d2.loss_mask: 0.6768, decode.d2.loss_dice: 0.9462, decode.d3.loss_cls: 0.5489, decode.d3.loss_mask: 0.6748, decode.d3.loss_dice: 0.9307, decode.d4.loss_cls: 0.5497, decode.d4.loss_mask: 0.6696, decode.d4.loss_dice: 0.9343, decode.d5.loss_cls: 0.5422, decode.d5.loss_mask: 0.6700, decode.d5.loss_dice: 0.9329, decode.d6.loss_cls: 0.5281, decode.d6.loss_mask: 0.6734, decode.d6.loss_dice: 0.9332, decode.d7.loss_cls: 0.5319, decode.d7.loss_mask: 0.6735, decode.d7.loss_dice: 0.9365, decode.d8.loss_cls: 0.5263, decode.d8.loss_mask: 0.6761, decode.d8.loss_dice: 0.9359, loss: 27.4536 +2022-05-06 02:11:04,477 - mmseg - INFO - Iter [5950/40000] lr: 1.222e-06, eta: 16:16:09, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5202, decode.loss_mask: 0.7139, decode.loss_dice: 0.9460, decode.d0.loss_cls: 6.1151, decode.d0.loss_mask: 0.6973, decode.d0.loss_dice: 1.0929, decode.d1.loss_cls: 0.6675, decode.d1.loss_mask: 0.7305, decode.d1.loss_dice: 1.0020, decode.d2.loss_cls: 0.5510, decode.d2.loss_mask: 0.7095, decode.d2.loss_dice: 0.9571, decode.d3.loss_cls: 0.5253, decode.d3.loss_mask: 0.7084, decode.d3.loss_dice: 0.9420, decode.d4.loss_cls: 0.5144, decode.d4.loss_mask: 0.7103, decode.d4.loss_dice: 0.9451, decode.d5.loss_cls: 0.5249, decode.d5.loss_mask: 0.7016, decode.d5.loss_dice: 0.9360, decode.d6.loss_cls: 0.5252, decode.d6.loss_mask: 0.7108, decode.d6.loss_dice: 0.9370, decode.d7.loss_cls: 0.5182, decode.d7.loss_mask: 0.7113, decode.d7.loss_dice: 0.9459, decode.d8.loss_cls: 0.5150, decode.d8.loss_mask: 0.7131, decode.d8.loss_dice: 0.9409, loss: 27.7284 +2022-05-06 02:11:38,256 - mmseg - INFO - Saving checkpoint at 6000 iterations +2022-05-06 02:12:02,872 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 02:12:02,879 - mmseg - INFO - Iter [6000/40000] lr: 1.220e-06, eta: 16:06:53, time: 1.166, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5174, decode.loss_mask: 0.6927, decode.loss_dice: 0.9324, decode.d0.loss_cls: 6.0778, decode.d0.loss_mask: 0.6853, decode.d0.loss_dice: 1.0710, decode.d1.loss_cls: 0.6451, decode.d1.loss_mask: 0.7097, decode.d1.loss_dice: 0.9836, decode.d2.loss_cls: 0.5605, decode.d2.loss_mask: 0.6953, decode.d2.loss_dice: 0.9449, decode.d3.loss_cls: 0.5322, decode.d3.loss_mask: 0.6872, decode.d3.loss_dice: 0.9253, decode.d4.loss_cls: 0.5251, decode.d4.loss_mask: 0.6870, decode.d4.loss_dice: 0.9240, decode.d5.loss_cls: 0.5198, decode.d5.loss_mask: 0.6864, decode.d5.loss_dice: 0.9270, decode.d6.loss_cls: 0.5175, decode.d6.loss_mask: 0.6891, decode.d6.loss_dice: 0.9153, decode.d7.loss_cls: 0.5202, decode.d7.loss_mask: 0.6858, decode.d7.loss_dice: 0.9209, decode.d8.loss_cls: 0.5079, decode.d8.loss_mask: 0.6889, decode.d8.loss_dice: 0.9261, loss: 27.3014 +2022-05-06 02:12:37,031 - mmseg - INFO - Iter [6050/40000] lr: 1.219e-06, eta: 15:51:22, time: 0.685, data_time: 0.013, memory: 53770, decode.loss_cls: 0.5105, decode.loss_mask: 0.6880, decode.loss_dice: 0.9299, decode.d0.loss_cls: 6.0570, decode.d0.loss_mask: 0.6760, decode.d0.loss_dice: 1.0933, decode.d1.loss_cls: 0.6599, decode.d1.loss_mask: 0.6948, decode.d1.loss_dice: 0.9924, decode.d2.loss_cls: 0.5548, decode.d2.loss_mask: 0.6969, decode.d2.loss_dice: 0.9504, decode.d3.loss_cls: 0.5300, decode.d3.loss_mask: 0.6913, decode.d3.loss_dice: 0.9326, decode.d4.loss_cls: 0.5304, decode.d4.loss_mask: 0.6868, decode.d4.loss_dice: 0.9370, decode.d5.loss_cls: 0.5181, decode.d5.loss_mask: 0.6887, decode.d5.loss_dice: 0.9310, decode.d6.loss_cls: 0.5073, decode.d6.loss_mask: 0.6872, decode.d6.loss_dice: 0.9304, decode.d7.loss_cls: 0.5078, decode.d7.loss_mask: 0.6887, decode.d7.loss_dice: 0.9304, decode.d8.loss_cls: 0.5140, decode.d8.loss_mask: 0.6881, decode.d8.loss_dice: 0.9280, loss: 27.3318 +2022-05-06 02:13:10,981 - mmseg - INFO - Iter [6100/40000] lr: 1.217e-06, eta: 15:36:29, time: 0.679, data_time: 0.010, memory: 53770, decode.loss_cls: 0.5371, decode.loss_mask: 0.6801, decode.loss_dice: 0.9134, decode.d0.loss_cls: 6.0386, decode.d0.loss_mask: 0.6825, decode.d0.loss_dice: 1.0744, decode.d1.loss_cls: 0.6856, decode.d1.loss_mask: 0.7042, decode.d1.loss_dice: 0.9763, decode.d2.loss_cls: 0.5861, decode.d2.loss_mask: 0.6871, decode.d2.loss_dice: 0.9339, decode.d3.loss_cls: 0.5647, decode.d3.loss_mask: 0.6864, decode.d3.loss_dice: 0.9219, decode.d4.loss_cls: 0.5528, decode.d4.loss_mask: 0.6838, decode.d4.loss_dice: 0.9291, decode.d5.loss_cls: 0.5493, decode.d5.loss_mask: 0.6817, decode.d5.loss_dice: 0.9142, decode.d6.loss_cls: 0.5419, decode.d6.loss_mask: 0.6802, decode.d6.loss_dice: 0.9068, decode.d7.loss_cls: 0.5354, decode.d7.loss_mask: 0.6792, decode.d7.loss_dice: 0.9146, decode.d8.loss_cls: 0.5324, decode.d8.loss_mask: 0.6808, decode.d8.loss_dice: 0.9149, loss: 27.3696 +2022-05-06 02:13:44,887 - mmseg - INFO - Iter [6150/40000] lr: 1.215e-06, eta: 15:22:16, time: 0.678, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4983, decode.loss_mask: 0.7018, decode.loss_dice: 0.9153, decode.d0.loss_cls: 5.9740, decode.d0.loss_mask: 0.6972, decode.d0.loss_dice: 1.0859, decode.d1.loss_cls: 0.6594, decode.d1.loss_mask: 0.7093, decode.d1.loss_dice: 0.9774, decode.d2.loss_cls: 0.5463, decode.d2.loss_mask: 0.7004, decode.d2.loss_dice: 0.9244, decode.d3.loss_cls: 0.5291, decode.d3.loss_mask: 0.7005, decode.d3.loss_dice: 0.9097, decode.d4.loss_cls: 0.5199, decode.d4.loss_mask: 0.6911, decode.d4.loss_dice: 0.9177, decode.d5.loss_cls: 0.5145, decode.d5.loss_mask: 0.6964, decode.d5.loss_dice: 0.9091, decode.d6.loss_cls: 0.5033, decode.d6.loss_mask: 0.6975, decode.d6.loss_dice: 0.9087, decode.d7.loss_cls: 0.5062, decode.d7.loss_mask: 0.7030, decode.d7.loss_dice: 0.9077, decode.d8.loss_cls: 0.5073, decode.d8.loss_mask: 0.7045, decode.d8.loss_dice: 0.9114, loss: 27.1273 +2022-05-06 02:14:21,270 - mmseg - INFO - Iter [6200/40000] lr: 1.213e-06, eta: 15:09:18, time: 0.728, data_time: 0.061, memory: 53770, decode.loss_cls: 0.5435, decode.loss_mask: 0.6898, decode.loss_dice: 0.9510, decode.d0.loss_cls: 5.9858, decode.d0.loss_mask: 0.6800, decode.d0.loss_dice: 1.1044, decode.d1.loss_cls: 0.6724, decode.d1.loss_mask: 0.7046, decode.d1.loss_dice: 1.0034, decode.d2.loss_cls: 0.5665, decode.d2.loss_mask: 0.6932, decode.d2.loss_dice: 0.9690, decode.d3.loss_cls: 0.5557, decode.d3.loss_mask: 0.6838, decode.d3.loss_dice: 0.9517, decode.d4.loss_cls: 0.5429, decode.d4.loss_mask: 0.6828, decode.d4.loss_dice: 0.9571, decode.d5.loss_cls: 0.5471, decode.d5.loss_mask: 0.6835, decode.d5.loss_dice: 0.9496, decode.d6.loss_cls: 0.5379, decode.d6.loss_mask: 0.6857, decode.d6.loss_dice: 0.9427, decode.d7.loss_cls: 0.5321, decode.d7.loss_mask: 0.6909, decode.d7.loss_dice: 0.9558, decode.d8.loss_cls: 0.5441, decode.d8.loss_mask: 0.6884, decode.d8.loss_dice: 0.9541, loss: 27.6494 +2022-05-06 02:14:54,957 - mmseg - INFO - Iter [6250/40000] lr: 1.211e-06, eta: 14:56:11, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4851, decode.loss_mask: 0.6912, decode.loss_dice: 0.9130, decode.d0.loss_cls: 5.9110, decode.d0.loss_mask: 0.6982, decode.d0.loss_dice: 1.0677, decode.d1.loss_cls: 0.6187, decode.d1.loss_mask: 0.7123, decode.d1.loss_dice: 0.9724, decode.d2.loss_cls: 0.5221, decode.d2.loss_mask: 0.6893, decode.d2.loss_dice: 0.9331, decode.d3.loss_cls: 0.4954, decode.d3.loss_mask: 0.6929, decode.d3.loss_dice: 0.9205, decode.d4.loss_cls: 0.4902, decode.d4.loss_mask: 0.6934, decode.d4.loss_dice: 0.9253, decode.d5.loss_cls: 0.4857, decode.d5.loss_mask: 0.6881, decode.d5.loss_dice: 0.9182, decode.d6.loss_cls: 0.4807, decode.d6.loss_mask: 0.6936, decode.d6.loss_dice: 0.9129, decode.d7.loss_cls: 0.4846, decode.d7.loss_mask: 0.6920, decode.d7.loss_dice: 0.9117, decode.d8.loss_cls: 0.4862, decode.d8.loss_mask: 0.6942, decode.d8.loss_dice: 0.9106, loss: 26.7902 +2022-05-06 02:15:28,843 - mmseg - INFO - Iter [6300/40000] lr: 1.210e-06, eta: 14:43:42, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5289, decode.loss_mask: 0.7027, decode.loss_dice: 0.9210, decode.d0.loss_cls: 5.9187, decode.d0.loss_mask: 0.6950, decode.d0.loss_dice: 1.0700, decode.d1.loss_cls: 0.6716, decode.d1.loss_mask: 0.7250, decode.d1.loss_dice: 0.9859, decode.d2.loss_cls: 0.5745, decode.d2.loss_mask: 0.7088, decode.d2.loss_dice: 0.9350, decode.d3.loss_cls: 0.5494, decode.d3.loss_mask: 0.6982, decode.d3.loss_dice: 0.9161, decode.d4.loss_cls: 0.5409, decode.d4.loss_mask: 0.7020, decode.d4.loss_dice: 0.9198, decode.d5.loss_cls: 0.5340, decode.d5.loss_mask: 0.6991, decode.d5.loss_dice: 0.9256, decode.d6.loss_cls: 0.5269, decode.d6.loss_mask: 0.7042, decode.d6.loss_dice: 0.9176, decode.d7.loss_cls: 0.5257, decode.d7.loss_mask: 0.7027, decode.d7.loss_dice: 0.9216, decode.d8.loss_cls: 0.5297, decode.d8.loss_mask: 0.7054, decode.d8.loss_dice: 0.9197, loss: 27.3757 +2022-05-06 02:16:02,687 - mmseg - INFO - Iter [6350/40000] lr: 1.208e-06, eta: 14:31:42, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4973, decode.loss_mask: 0.6864, decode.loss_dice: 0.9095, decode.d0.loss_cls: 5.8894, decode.d0.loss_mask: 0.6723, decode.d0.loss_dice: 1.0695, decode.d1.loss_cls: 0.6466, decode.d1.loss_mask: 0.6923, decode.d1.loss_dice: 0.9642, decode.d2.loss_cls: 0.5554, decode.d2.loss_mask: 0.6867, decode.d2.loss_dice: 0.9315, decode.d3.loss_cls: 0.5161, decode.d3.loss_mask: 0.6822, decode.d3.loss_dice: 0.9099, decode.d4.loss_cls: 0.5099, decode.d4.loss_mask: 0.6819, decode.d4.loss_dice: 0.9204, decode.d5.loss_cls: 0.4976, decode.d5.loss_mask: 0.6841, decode.d5.loss_dice: 0.9107, decode.d6.loss_cls: 0.4950, decode.d6.loss_mask: 0.6815, decode.d6.loss_dice: 0.9056, decode.d7.loss_cls: 0.4987, decode.d7.loss_mask: 0.6839, decode.d7.loss_dice: 0.9034, decode.d8.loss_cls: 0.4952, decode.d8.loss_mask: 0.6838, decode.d8.loss_dice: 0.9077, loss: 26.7687 +2022-05-06 02:16:36,653 - mmseg - INFO - Iter [6400/40000] lr: 1.206e-06, eta: 14:20:12, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4824, decode.loss_mask: 0.6615, decode.loss_dice: 0.8911, decode.d0.loss_cls: 5.8500, decode.d0.loss_mask: 0.6696, decode.d0.loss_dice: 1.0498, decode.d1.loss_cls: 0.6328, decode.d1.loss_mask: 0.6766, decode.d1.loss_dice: 0.9381, decode.d2.loss_cls: 0.5228, decode.d2.loss_mask: 0.6665, decode.d2.loss_dice: 0.9013, decode.d3.loss_cls: 0.4968, decode.d3.loss_mask: 0.6641, decode.d3.loss_dice: 0.9007, decode.d4.loss_cls: 0.4923, decode.d4.loss_mask: 0.6639, decode.d4.loss_dice: 0.8988, decode.d5.loss_cls: 0.4835, decode.d5.loss_mask: 0.6611, decode.d5.loss_dice: 0.8960, decode.d6.loss_cls: 0.4785, decode.d6.loss_mask: 0.6570, decode.d6.loss_dice: 0.8933, decode.d7.loss_cls: 0.4812, decode.d7.loss_mask: 0.6541, decode.d7.loss_dice: 0.8927, decode.d8.loss_cls: 0.4768, decode.d8.loss_mask: 0.6612, decode.d8.loss_dice: 0.8917, loss: 26.1864 +2022-05-06 02:17:10,210 - mmseg - INFO - Iter [6450/40000] lr: 1.204e-06, eta: 14:09:03, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5229, decode.loss_mask: 0.6437, decode.loss_dice: 0.9283, decode.d0.loss_cls: 5.8246, decode.d0.loss_mask: 0.6468, decode.d0.loss_dice: 1.0892, decode.d1.loss_cls: 0.6650, decode.d1.loss_mask: 0.6557, decode.d1.loss_dice: 0.9877, decode.d2.loss_cls: 0.5644, decode.d2.loss_mask: 0.6499, decode.d2.loss_dice: 0.9507, decode.d3.loss_cls: 0.5288, decode.d3.loss_mask: 0.6500, decode.d3.loss_dice: 0.9381, decode.d4.loss_cls: 0.5278, decode.d4.loss_mask: 0.6431, decode.d4.loss_dice: 0.9402, decode.d5.loss_cls: 0.5211, decode.d5.loss_mask: 0.6431, decode.d5.loss_dice: 0.9374, decode.d6.loss_cls: 0.5129, decode.d6.loss_mask: 0.6391, decode.d6.loss_dice: 0.9267, decode.d7.loss_cls: 0.5198, decode.d7.loss_mask: 0.6434, decode.d7.loss_dice: 0.9303, decode.d8.loss_cls: 0.5231, decode.d8.loss_mask: 0.6406, decode.d8.loss_dice: 0.9230, loss: 26.7174 +2022-05-06 02:17:46,244 - mmseg - INFO - Iter [6500/40000] lr: 1.203e-06, eta: 13:58:52, time: 0.721, data_time: 0.059, memory: 53770, decode.loss_cls: 0.5458, decode.loss_mask: 0.6815, decode.loss_dice: 0.9289, decode.d0.loss_cls: 5.8096, decode.d0.loss_mask: 0.6749, decode.d0.loss_dice: 1.0934, decode.d1.loss_cls: 0.6895, decode.d1.loss_mask: 0.6914, decode.d1.loss_dice: 0.9974, decode.d2.loss_cls: 0.5892, decode.d2.loss_mask: 0.6754, decode.d2.loss_dice: 0.9459, decode.d3.loss_cls: 0.5637, decode.d3.loss_mask: 0.6799, decode.d3.loss_dice: 0.9325, decode.d4.loss_cls: 0.5673, decode.d4.loss_mask: 0.6768, decode.d4.loss_dice: 0.9324, decode.d5.loss_cls: 0.5618, decode.d5.loss_mask: 0.6761, decode.d5.loss_dice: 0.9326, decode.d6.loss_cls: 0.5414, decode.d6.loss_mask: 0.6813, decode.d6.loss_dice: 0.9212, decode.d7.loss_cls: 0.5483, decode.d7.loss_mask: 0.6812, decode.d7.loss_dice: 0.9319, decode.d8.loss_cls: 0.5522, decode.d8.loss_mask: 0.6782, decode.d8.loss_dice: 0.9296, loss: 27.3114 +2022-05-06 02:18:20,040 - mmseg - INFO - Iter [6550/40000] lr: 1.201e-06, eta: 13:48:35, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4831, decode.loss_mask: 0.6717, decode.loss_dice: 0.9217, decode.d0.loss_cls: 5.7584, decode.d0.loss_mask: 0.6703, decode.d0.loss_dice: 1.0687, decode.d1.loss_cls: 0.6084, decode.d1.loss_mask: 0.6945, decode.d1.loss_dice: 0.9875, decode.d2.loss_cls: 0.5159, decode.d2.loss_mask: 0.6801, decode.d2.loss_dice: 0.9478, decode.d3.loss_cls: 0.5003, decode.d3.loss_mask: 0.6745, decode.d3.loss_dice: 0.9245, decode.d4.loss_cls: 0.5004, decode.d4.loss_mask: 0.6747, decode.d4.loss_dice: 0.9319, decode.d5.loss_cls: 0.4819, decode.d5.loss_mask: 0.6686, decode.d5.loss_dice: 0.9274, decode.d6.loss_cls: 0.4833, decode.d6.loss_mask: 0.6703, decode.d6.loss_dice: 0.9246, decode.d7.loss_cls: 0.4883, decode.d7.loss_mask: 0.6692, decode.d7.loss_dice: 0.9203, decode.d8.loss_cls: 0.4924, decode.d8.loss_mask: 0.6711, decode.d8.loss_dice: 0.9254, loss: 26.5370 +2022-05-06 02:18:54,028 - mmseg - INFO - Iter [6600/40000] lr: 1.199e-06, eta: 13:38:43, time: 0.681, data_time: 0.010, memory: 53770, decode.loss_cls: 0.4833, decode.loss_mask: 0.6554, decode.loss_dice: 0.8709, decode.d0.loss_cls: 5.7445, decode.d0.loss_mask: 0.6571, decode.d0.loss_dice: 1.0275, decode.d1.loss_cls: 0.6212, decode.d1.loss_mask: 0.6645, decode.d1.loss_dice: 0.9361, decode.d2.loss_cls: 0.5259, decode.d2.loss_mask: 0.6559, decode.d2.loss_dice: 0.8917, decode.d3.loss_cls: 0.4946, decode.d3.loss_mask: 0.6512, decode.d3.loss_dice: 0.8760, decode.d4.loss_cls: 0.4941, decode.d4.loss_mask: 0.6472, decode.d4.loss_dice: 0.8757, decode.d5.loss_cls: 0.4877, decode.d5.loss_mask: 0.6509, decode.d5.loss_dice: 0.8723, decode.d6.loss_cls: 0.4843, decode.d6.loss_mask: 0.6497, decode.d6.loss_dice: 0.8685, decode.d7.loss_cls: 0.4801, decode.d7.loss_mask: 0.6547, decode.d7.loss_dice: 0.8713, decode.d8.loss_cls: 0.4841, decode.d8.loss_mask: 0.6522, decode.d8.loss_dice: 0.8699, loss: 25.7988 +2022-05-06 02:19:27,898 - mmseg - INFO - Iter [6650/40000] lr: 1.197e-06, eta: 13:29:11, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4784, decode.loss_mask: 0.6771, decode.loss_dice: 0.8742, decode.d0.loss_cls: 5.7104, decode.d0.loss_mask: 0.6781, decode.d0.loss_dice: 1.0401, decode.d1.loss_cls: 0.6324, decode.d1.loss_mask: 0.6962, decode.d1.loss_dice: 0.9416, decode.d2.loss_cls: 0.5318, decode.d2.loss_mask: 0.6843, decode.d2.loss_dice: 0.8942, decode.d3.loss_cls: 0.5012, decode.d3.loss_mask: 0.6798, decode.d3.loss_dice: 0.8796, decode.d4.loss_cls: 0.4894, decode.d4.loss_mask: 0.6775, decode.d4.loss_dice: 0.8854, decode.d5.loss_cls: 0.4847, decode.d5.loss_mask: 0.6734, decode.d5.loss_dice: 0.8803, decode.d6.loss_cls: 0.4777, decode.d6.loss_mask: 0.6753, decode.d6.loss_dice: 0.8731, decode.d7.loss_cls: 0.4743, decode.d7.loss_mask: 0.6775, decode.d7.loss_dice: 0.8791, decode.d8.loss_cls: 0.4776, decode.d8.loss_mask: 0.6759, decode.d8.loss_dice: 0.8729, loss: 26.0736 +2022-05-06 02:20:01,409 - mmseg - INFO - Iter [6700/40000] lr: 1.195e-06, eta: 13:19:54, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.5085, decode.loss_mask: 0.6571, decode.loss_dice: 0.8885, decode.d0.loss_cls: 5.6733, decode.d0.loss_mask: 0.6489, decode.d0.loss_dice: 1.0310, decode.d1.loss_cls: 0.6430, decode.d1.loss_mask: 0.6718, decode.d1.loss_dice: 0.9442, decode.d2.loss_cls: 0.5459, decode.d2.loss_mask: 0.6625, decode.d2.loss_dice: 0.9099, decode.d3.loss_cls: 0.5265, decode.d3.loss_mask: 0.6594, decode.d3.loss_dice: 0.8839, decode.d4.loss_cls: 0.5184, decode.d4.loss_mask: 0.6590, decode.d4.loss_dice: 0.8857, decode.d5.loss_cls: 0.5203, decode.d5.loss_mask: 0.6584, decode.d5.loss_dice: 0.8796, decode.d6.loss_cls: 0.5139, decode.d6.loss_mask: 0.6567, decode.d6.loss_dice: 0.8731, decode.d7.loss_cls: 0.5041, decode.d7.loss_mask: 0.6605, decode.d7.loss_dice: 0.8788, decode.d8.loss_cls: 0.5080, decode.d8.loss_mask: 0.6559, decode.d8.loss_dice: 0.8853, loss: 26.1123 +2022-05-06 02:20:35,552 - mmseg - INFO - Iter [6750/40000] lr: 1.194e-06, eta: 13:11:03, time: 0.683, data_time: 0.008, memory: 53770, decode.loss_cls: 0.5065, decode.loss_mask: 0.6813, decode.loss_dice: 0.8918, decode.d0.loss_cls: 5.6737, decode.d0.loss_mask: 0.6849, decode.d0.loss_dice: 1.0427, decode.d1.loss_cls: 0.6356, decode.d1.loss_mask: 0.6937, decode.d1.loss_dice: 0.9420, decode.d2.loss_cls: 0.5295, decode.d2.loss_mask: 0.6870, decode.d2.loss_dice: 0.9116, decode.d3.loss_cls: 0.4983, decode.d3.loss_mask: 0.6825, decode.d3.loss_dice: 0.8904, decode.d4.loss_cls: 0.5015, decode.d4.loss_mask: 0.6794, decode.d4.loss_dice: 0.8951, decode.d5.loss_cls: 0.4945, decode.d5.loss_mask: 0.6782, decode.d5.loss_dice: 0.8894, decode.d6.loss_cls: 0.4912, decode.d6.loss_mask: 0.6818, decode.d6.loss_dice: 0.8889, decode.d7.loss_cls: 0.4943, decode.d7.loss_mask: 0.6781, decode.d7.loss_dice: 0.8944, decode.d8.loss_cls: 0.4939, decode.d8.loss_mask: 0.6799, decode.d8.loss_dice: 0.8959, loss: 26.2881 +2022-05-06 02:21:09,362 - mmseg - INFO - Iter [6800/40000] lr: 1.192e-06, eta: 13:02:27, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4807, decode.loss_mask: 0.6653, decode.loss_dice: 0.9151, decode.d0.loss_cls: 5.6345, decode.d0.loss_mask: 0.6591, decode.d0.loss_dice: 1.0620, decode.d1.loss_cls: 0.6238, decode.d1.loss_mask: 0.6774, decode.d1.loss_dice: 0.9826, decode.d2.loss_cls: 0.5178, decode.d2.loss_mask: 0.6713, decode.d2.loss_dice: 0.9326, decode.d3.loss_cls: 0.4927, decode.d3.loss_mask: 0.6739, decode.d3.loss_dice: 0.9184, decode.d4.loss_cls: 0.4879, decode.d4.loss_mask: 0.6711, decode.d4.loss_dice: 0.9259, decode.d5.loss_cls: 0.4787, decode.d5.loss_mask: 0.6668, decode.d5.loss_dice: 0.9285, decode.d6.loss_cls: 0.4800, decode.d6.loss_mask: 0.6630, decode.d6.loss_dice: 0.9151, decode.d7.loss_cls: 0.4847, decode.d7.loss_mask: 0.6655, decode.d7.loss_dice: 0.9119, decode.d8.loss_cls: 0.4834, decode.d8.loss_mask: 0.6746, decode.d8.loss_dice: 0.9088, loss: 26.2528 +2022-05-06 02:21:45,884 - mmseg - INFO - Iter [6850/40000] lr: 1.190e-06, eta: 12:54:39, time: 0.730, data_time: 0.058, memory: 53770, decode.loss_cls: 0.4665, decode.loss_mask: 0.6711, decode.loss_dice: 0.8955, decode.d0.loss_cls: 5.6112, decode.d0.loss_mask: 0.6728, decode.d0.loss_dice: 1.0532, decode.d1.loss_cls: 0.6052, decode.d1.loss_mask: 0.6869, decode.d1.loss_dice: 0.9570, decode.d2.loss_cls: 0.5026, decode.d2.loss_mask: 0.6800, decode.d2.loss_dice: 0.9127, decode.d3.loss_cls: 0.4853, decode.d3.loss_mask: 0.6710, decode.d3.loss_dice: 0.8980, decode.d4.loss_cls: 0.4792, decode.d4.loss_mask: 0.6688, decode.d4.loss_dice: 0.8986, decode.d5.loss_cls: 0.4769, decode.d5.loss_mask: 0.6678, decode.d5.loss_dice: 0.8907, decode.d6.loss_cls: 0.4738, decode.d6.loss_mask: 0.6633, decode.d6.loss_dice: 0.8841, decode.d7.loss_cls: 0.4709, decode.d7.loss_mask: 0.6659, decode.d7.loss_dice: 0.8868, decode.d8.loss_cls: 0.4739, decode.d8.loss_mask: 0.6652, decode.d8.loss_dice: 0.8904, loss: 25.9253 +2022-05-06 02:22:19,625 - mmseg - INFO - Iter [6900/40000] lr: 1.188e-06, eta: 12:46:33, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4613, decode.loss_mask: 0.6503, decode.loss_dice: 0.8783, decode.d0.loss_cls: 5.5769, decode.d0.loss_mask: 0.6516, decode.d0.loss_dice: 1.0211, decode.d1.loss_cls: 0.5884, decode.d1.loss_mask: 0.6683, decode.d1.loss_dice: 0.9417, decode.d2.loss_cls: 0.4994, decode.d2.loss_mask: 0.6572, decode.d2.loss_dice: 0.9034, decode.d3.loss_cls: 0.4769, decode.d3.loss_mask: 0.6525, decode.d3.loss_dice: 0.8834, decode.d4.loss_cls: 0.4608, decode.d4.loss_mask: 0.6486, decode.d4.loss_dice: 0.8902, decode.d5.loss_cls: 0.4655, decode.d5.loss_mask: 0.6431, decode.d5.loss_dice: 0.8802, decode.d6.loss_cls: 0.4614, decode.d6.loss_mask: 0.6489, decode.d6.loss_dice: 0.8728, decode.d7.loss_cls: 0.4588, decode.d7.loss_mask: 0.6484, decode.d7.loss_dice: 0.8778, decode.d8.loss_cls: 0.4556, decode.d8.loss_mask: 0.6517, decode.d8.loss_dice: 0.8820, loss: 25.4565 +2022-05-06 02:22:53,255 - mmseg - INFO - Iter [6950/40000] lr: 1.186e-06, eta: 12:38:43, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4252, decode.loss_mask: 0.6540, decode.loss_dice: 0.8623, decode.d0.loss_cls: 5.5328, decode.d0.loss_mask: 0.6557, decode.d0.loss_dice: 1.0037, decode.d1.loss_cls: 0.5533, decode.d1.loss_mask: 0.6686, decode.d1.loss_dice: 0.9247, decode.d2.loss_cls: 0.4780, decode.d2.loss_mask: 0.6587, decode.d2.loss_dice: 0.8871, decode.d3.loss_cls: 0.4482, decode.d3.loss_mask: 0.6562, decode.d3.loss_dice: 0.8668, decode.d4.loss_cls: 0.4404, decode.d4.loss_mask: 0.6542, decode.d4.loss_dice: 0.8711, decode.d5.loss_cls: 0.4266, decode.d5.loss_mask: 0.6489, decode.d5.loss_dice: 0.8624, decode.d6.loss_cls: 0.4223, decode.d6.loss_mask: 0.6501, decode.d6.loss_dice: 0.8543, decode.d7.loss_cls: 0.4238, decode.d7.loss_mask: 0.6517, decode.d7.loss_dice: 0.8563, decode.d8.loss_cls: 0.4196, decode.d8.loss_mask: 0.6510, decode.d8.loss_dice: 0.8661, loss: 24.9740 +2022-05-06 02:23:27,255 - mmseg - INFO - Saving checkpoint at 7000 iterations +2022-05-06 02:23:53,764 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 02:23:53,766 - mmseg - INFO - Iter [7000/40000] lr: 1.185e-06, eta: 12:36:01, time: 1.208, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4839, decode.loss_mask: 0.6377, decode.loss_dice: 0.8493, decode.d0.loss_cls: 5.5182, decode.d0.loss_mask: 0.6531, decode.d0.loss_dice: 1.0057, decode.d1.loss_cls: 0.6295, decode.d1.loss_mask: 0.6617, decode.d1.loss_dice: 0.9094, decode.d2.loss_cls: 0.5293, decode.d2.loss_mask: 0.6469, decode.d2.loss_dice: 0.8716, decode.d3.loss_cls: 0.4963, decode.d3.loss_mask: 0.6411, decode.d3.loss_dice: 0.8560, decode.d4.loss_cls: 0.4902, decode.d4.loss_mask: 0.6384, decode.d4.loss_dice: 0.8560, decode.d5.loss_cls: 0.4852, decode.d5.loss_mask: 0.6365, decode.d5.loss_dice: 0.8535, decode.d6.loss_cls: 0.4763, decode.d6.loss_mask: 0.6411, decode.d6.loss_dice: 0.8484, decode.d7.loss_cls: 0.4788, decode.d7.loss_mask: 0.6381, decode.d7.loss_dice: 0.8567, decode.d8.loss_cls: 0.4797, decode.d8.loss_mask: 0.6416, decode.d8.loss_dice: 0.8544, loss: 25.2646 +2022-05-06 02:24:27,899 - mmseg - INFO - Iter [7050/40000] lr: 1.183e-06, eta: 12:28:39, time: 0.685, data_time: 0.010, memory: 53770, decode.loss_cls: 0.4496, decode.loss_mask: 0.6904, decode.loss_dice: 0.8808, decode.d0.loss_cls: 5.4962, decode.d0.loss_mask: 0.6794, decode.d0.loss_dice: 1.0199, decode.d1.loss_cls: 0.5886, decode.d1.loss_mask: 0.6911, decode.d1.loss_dice: 0.9204, decode.d2.loss_cls: 0.5045, decode.d2.loss_mask: 0.6862, decode.d2.loss_dice: 0.8791, decode.d3.loss_cls: 0.4735, decode.d3.loss_mask: 0.6821, decode.d3.loss_dice: 0.8680, decode.d4.loss_cls: 0.4602, decode.d4.loss_mask: 0.6818, decode.d4.loss_dice: 0.8731, decode.d5.loss_cls: 0.4573, decode.d5.loss_mask: 0.6823, decode.d5.loss_dice: 0.8662, decode.d6.loss_cls: 0.4552, decode.d6.loss_mask: 0.6791, decode.d6.loss_dice: 0.8699, decode.d7.loss_cls: 0.4437, decode.d7.loss_mask: 0.6826, decode.d7.loss_dice: 0.8776, decode.d8.loss_cls: 0.4493, decode.d8.loss_mask: 0.6875, decode.d8.loss_dice: 0.8804, loss: 25.5559 +2022-05-06 02:25:01,516 - mmseg - INFO - Iter [7100/40000] lr: 1.181e-06, eta: 12:21:25, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4787, decode.loss_mask: 0.6700, decode.loss_dice: 0.8983, decode.d0.loss_cls: 5.4659, decode.d0.loss_mask: 0.6660, decode.d0.loss_dice: 1.0492, decode.d1.loss_cls: 0.6021, decode.d1.loss_mask: 0.6887, decode.d1.loss_dice: 0.9500, decode.d2.loss_cls: 0.5196, decode.d2.loss_mask: 0.6777, decode.d2.loss_dice: 0.9166, decode.d3.loss_cls: 0.4893, decode.d3.loss_mask: 0.6735, decode.d3.loss_dice: 0.8978, decode.d4.loss_cls: 0.4815, decode.d4.loss_mask: 0.6744, decode.d4.loss_dice: 0.9009, decode.d5.loss_cls: 0.4787, decode.d5.loss_mask: 0.6714, decode.d5.loss_dice: 0.8922, decode.d6.loss_cls: 0.4687, decode.d6.loss_mask: 0.6708, decode.d6.loss_dice: 0.8921, decode.d7.loss_cls: 0.4781, decode.d7.loss_mask: 0.6706, decode.d7.loss_dice: 0.8946, decode.d8.loss_cls: 0.4742, decode.d8.loss_mask: 0.6713, decode.d8.loss_dice: 0.8957, loss: 25.8588 +2022-05-06 02:25:38,925 - mmseg - INFO - Iter [7150/40000] lr: 1.179e-06, eta: 12:15:02, time: 0.748, data_time: 0.061, memory: 53770, decode.loss_cls: 0.4566, decode.loss_mask: 0.6798, decode.loss_dice: 0.8801, decode.d0.loss_cls: 5.4577, decode.d0.loss_mask: 0.6846, decode.d0.loss_dice: 1.0314, decode.d1.loss_cls: 0.5728, decode.d1.loss_mask: 0.7062, decode.d1.loss_dice: 0.9478, decode.d2.loss_cls: 0.4852, decode.d2.loss_mask: 0.6905, decode.d2.loss_dice: 0.9019, decode.d3.loss_cls: 0.4732, decode.d3.loss_mask: 0.6840, decode.d3.loss_dice: 0.8798, decode.d4.loss_cls: 0.4601, decode.d4.loss_mask: 0.6822, decode.d4.loss_dice: 0.8896, decode.d5.loss_cls: 0.4571, decode.d5.loss_mask: 0.6801, decode.d5.loss_dice: 0.8844, decode.d6.loss_cls: 0.4527, decode.d6.loss_mask: 0.6828, decode.d6.loss_dice: 0.8790, decode.d7.loss_cls: 0.4534, decode.d7.loss_mask: 0.6761, decode.d7.loss_dice: 0.8832, decode.d8.loss_cls: 0.4499, decode.d8.loss_mask: 0.6785, decode.d8.loss_dice: 0.8816, loss: 25.6221 +2022-05-06 02:26:12,352 - mmseg - INFO - Iter [7200/40000] lr: 1.177e-06, eta: 12:08:10, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4528, decode.loss_mask: 0.6316, decode.loss_dice: 0.8776, decode.d0.loss_cls: 5.4103, decode.d0.loss_mask: 0.6409, decode.d0.loss_dice: 1.0250, decode.d1.loss_cls: 0.5997, decode.d1.loss_mask: 0.6477, decode.d1.loss_dice: 0.9245, decode.d2.loss_cls: 0.5098, decode.d2.loss_mask: 0.6359, decode.d2.loss_dice: 0.8846, decode.d3.loss_cls: 0.4727, decode.d3.loss_mask: 0.6295, decode.d3.loss_dice: 0.8818, decode.d4.loss_cls: 0.4672, decode.d4.loss_mask: 0.6329, decode.d4.loss_dice: 0.8831, decode.d5.loss_cls: 0.4576, decode.d5.loss_mask: 0.6295, decode.d5.loss_dice: 0.8738, decode.d6.loss_cls: 0.4531, decode.d6.loss_mask: 0.6349, decode.d6.loss_dice: 0.8687, decode.d7.loss_cls: 0.4606, decode.d7.loss_mask: 0.6305, decode.d7.loss_dice: 0.8780, decode.d8.loss_cls: 0.4601, decode.d8.loss_mask: 0.6322, decode.d8.loss_dice: 0.8699, loss: 25.0567 +2022-05-06 02:26:47,016 - mmseg - INFO - Iter [7250/40000] lr: 1.176e-06, eta: 12:01:41, time: 0.693, data_time: 0.011, memory: 53770, decode.loss_cls: 0.4603, decode.loss_mask: 0.6721, decode.loss_dice: 0.9041, decode.d0.loss_cls: 5.3799, decode.d0.loss_mask: 0.6604, decode.d0.loss_dice: 1.0301, decode.d1.loss_cls: 0.6029, decode.d1.loss_mask: 0.6838, decode.d1.loss_dice: 0.9622, decode.d2.loss_cls: 0.4996, decode.d2.loss_mask: 0.6720, decode.d2.loss_dice: 0.9247, decode.d3.loss_cls: 0.4840, decode.d3.loss_mask: 0.6689, decode.d3.loss_dice: 0.9023, decode.d4.loss_cls: 0.4694, decode.d4.loss_mask: 0.6677, decode.d4.loss_dice: 0.9048, decode.d5.loss_cls: 0.4552, decode.d5.loss_mask: 0.6698, decode.d5.loss_dice: 0.9063, decode.d6.loss_cls: 0.4575, decode.d6.loss_mask: 0.6655, decode.d6.loss_dice: 0.9006, decode.d7.loss_cls: 0.4499, decode.d7.loss_mask: 0.6687, decode.d7.loss_dice: 0.9030, decode.d8.loss_cls: 0.4606, decode.d8.loss_mask: 0.6686, decode.d8.loss_dice: 0.9007, loss: 25.6558 +2022-05-06 02:27:20,718 - mmseg - INFO - Iter [7300/40000] lr: 1.174e-06, eta: 11:55:14, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4870, decode.loss_mask: 0.6447, decode.loss_dice: 0.8645, decode.d0.loss_cls: 5.3704, decode.d0.loss_mask: 0.6549, decode.d0.loss_dice: 1.0306, decode.d1.loss_cls: 0.6341, decode.d1.loss_mask: 0.6603, decode.d1.loss_dice: 0.9268, decode.d2.loss_cls: 0.5288, decode.d2.loss_mask: 0.6468, decode.d2.loss_dice: 0.8790, decode.d3.loss_cls: 0.5026, decode.d3.loss_mask: 0.6423, decode.d3.loss_dice: 0.8657, decode.d4.loss_cls: 0.5016, decode.d4.loss_mask: 0.6374, decode.d4.loss_dice: 0.8635, decode.d5.loss_cls: 0.4865, decode.d5.loss_mask: 0.6414, decode.d5.loss_dice: 0.8600, decode.d6.loss_cls: 0.4831, decode.d6.loss_mask: 0.6381, decode.d6.loss_dice: 0.8583, decode.d7.loss_cls: 0.4825, decode.d7.loss_mask: 0.6468, decode.d7.loss_dice: 0.8615, decode.d8.loss_cls: 0.4827, decode.d8.loss_mask: 0.6444, decode.d8.loss_dice: 0.8599, loss: 25.2864 +2022-05-06 02:27:54,338 - mmseg - INFO - Iter [7350/40000] lr: 1.172e-06, eta: 11:48:57, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4708, decode.loss_mask: 0.6499, decode.loss_dice: 0.8758, decode.d0.loss_cls: 5.3473, decode.d0.loss_mask: 0.6570, decode.d0.loss_dice: 1.0298, decode.d1.loss_cls: 0.6174, decode.d1.loss_mask: 0.6710, decode.d1.loss_dice: 0.9391, decode.d2.loss_cls: 0.5015, decode.d2.loss_mask: 0.6611, decode.d2.loss_dice: 0.8993, decode.d3.loss_cls: 0.4821, decode.d3.loss_mask: 0.6570, decode.d3.loss_dice: 0.8832, decode.d4.loss_cls: 0.4748, decode.d4.loss_mask: 0.6498, decode.d4.loss_dice: 0.8818, decode.d5.loss_cls: 0.4784, decode.d5.loss_mask: 0.6474, decode.d5.loss_dice: 0.8821, decode.d6.loss_cls: 0.4706, decode.d6.loss_mask: 0.6502, decode.d6.loss_dice: 0.8772, decode.d7.loss_cls: 0.4707, decode.d7.loss_mask: 0.6506, decode.d7.loss_dice: 0.8818, decode.d8.loss_cls: 0.4712, decode.d8.loss_mask: 0.6482, decode.d8.loss_dice: 0.8742, loss: 25.3512 +2022-05-06 02:28:28,059 - mmseg - INFO - Iter [7400/40000] lr: 1.170e-06, eta: 11:42:51, time: 0.674, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4500, decode.loss_mask: 0.6461, decode.loss_dice: 0.8249, decode.d0.loss_cls: 5.3191, decode.d0.loss_mask: 0.6588, decode.d0.loss_dice: 0.9784, decode.d1.loss_cls: 0.5824, decode.d1.loss_mask: 0.6687, decode.d1.loss_dice: 0.8792, decode.d2.loss_cls: 0.4860, decode.d2.loss_mask: 0.6498, decode.d2.loss_dice: 0.8399, decode.d3.loss_cls: 0.4588, decode.d3.loss_mask: 0.6498, decode.d3.loss_dice: 0.8290, decode.d4.loss_cls: 0.4544, decode.d4.loss_mask: 0.6468, decode.d4.loss_dice: 0.8305, decode.d5.loss_cls: 0.4485, decode.d5.loss_mask: 0.6496, decode.d5.loss_dice: 0.8250, decode.d6.loss_cls: 0.4455, decode.d6.loss_mask: 0.6460, decode.d6.loss_dice: 0.8205, decode.d7.loss_cls: 0.4522, decode.d7.loss_mask: 0.6475, decode.d7.loss_dice: 0.8265, decode.d8.loss_cls: 0.4514, decode.d8.loss_mask: 0.6476, decode.d8.loss_dice: 0.8222, loss: 24.5351 +2022-05-06 02:29:03,862 - mmseg - INFO - Iter [7450/40000] lr: 1.168e-06, eta: 11:37:14, time: 0.716, data_time: 0.060, memory: 53770, decode.loss_cls: 0.4555, decode.loss_mask: 0.6632, decode.loss_dice: 0.8930, decode.d0.loss_cls: 5.2875, decode.d0.loss_mask: 0.6613, decode.d0.loss_dice: 1.0299, decode.d1.loss_cls: 0.5883, decode.d1.loss_mask: 0.6753, decode.d1.loss_dice: 0.9377, decode.d2.loss_cls: 0.4842, decode.d2.loss_mask: 0.6629, decode.d2.loss_dice: 0.9078, decode.d3.loss_cls: 0.4580, decode.d3.loss_mask: 0.6617, decode.d3.loss_dice: 0.8881, decode.d4.loss_cls: 0.4548, decode.d4.loss_mask: 0.6599, decode.d4.loss_dice: 0.8857, decode.d5.loss_cls: 0.4416, decode.d5.loss_mask: 0.6658, decode.d5.loss_dice: 0.8871, decode.d6.loss_cls: 0.4457, decode.d6.loss_mask: 0.6637, decode.d6.loss_dice: 0.8837, decode.d7.loss_cls: 0.4452, decode.d7.loss_mask: 0.6612, decode.d7.loss_dice: 0.8874, decode.d8.loss_cls: 0.4426, decode.d8.loss_mask: 0.6651, decode.d8.loss_dice: 0.8881, loss: 25.2321 +2022-05-06 02:29:37,268 - mmseg - INFO - Iter [7500/40000] lr: 1.167e-06, eta: 11:31:23, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4226, decode.loss_mask: 0.6357, decode.loss_dice: 0.8697, decode.d0.loss_cls: 5.2504, decode.d0.loss_mask: 0.6450, decode.d0.loss_dice: 1.0084, decode.d1.loss_cls: 0.5671, decode.d1.loss_mask: 0.6604, decode.d1.loss_dice: 0.9156, decode.d2.loss_cls: 0.4709, decode.d2.loss_mask: 0.6426, decode.d2.loss_dice: 0.8810, decode.d3.loss_cls: 0.4428, decode.d3.loss_mask: 0.6448, decode.d3.loss_dice: 0.8763, decode.d4.loss_cls: 0.4345, decode.d4.loss_mask: 0.6465, decode.d4.loss_dice: 0.8704, decode.d5.loss_cls: 0.4311, decode.d5.loss_mask: 0.6415, decode.d5.loss_dice: 0.8701, decode.d6.loss_cls: 0.4249, decode.d6.loss_mask: 0.6378, decode.d6.loss_dice: 0.8687, decode.d7.loss_cls: 0.4345, decode.d7.loss_mask: 0.6336, decode.d7.loss_dice: 0.8659, decode.d8.loss_cls: 0.4252, decode.d8.loss_mask: 0.6327, decode.d8.loss_dice: 0.8626, loss: 24.6134 +2022-05-06 02:30:10,946 - mmseg - INFO - Iter [7550/40000] lr: 1.165e-06, eta: 11:25:44, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4508, decode.loss_mask: 0.6071, decode.loss_dice: 0.8676, decode.d0.loss_cls: 5.2334, decode.d0.loss_mask: 0.6099, decode.d0.loss_dice: 1.0218, decode.d1.loss_cls: 0.6072, decode.d1.loss_mask: 0.6241, decode.d1.loss_dice: 0.9201, decode.d2.loss_cls: 0.5079, decode.d2.loss_mask: 0.6135, decode.d2.loss_dice: 0.8879, decode.d3.loss_cls: 0.4779, decode.d3.loss_mask: 0.6071, decode.d3.loss_dice: 0.8691, decode.d4.loss_cls: 0.4672, decode.d4.loss_mask: 0.6020, decode.d4.loss_dice: 0.8723, decode.d5.loss_cls: 0.4624, decode.d5.loss_mask: 0.6056, decode.d5.loss_dice: 0.8752, decode.d6.loss_cls: 0.4584, decode.d6.loss_mask: 0.6059, decode.d6.loss_dice: 0.8656, decode.d7.loss_cls: 0.4573, decode.d7.loss_mask: 0.6064, decode.d7.loss_dice: 0.8674, decode.d8.loss_cls: 0.4485, decode.d8.loss_mask: 0.6019, decode.d8.loss_dice: 0.8674, loss: 24.5691 +2022-05-06 02:30:45,040 - mmseg - INFO - Iter [7600/40000] lr: 1.163e-06, eta: 11:20:17, time: 0.682, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4177, decode.loss_mask: 0.6266, decode.loss_dice: 0.8424, decode.d0.loss_cls: 5.1645, decode.d0.loss_mask: 0.6430, decode.d0.loss_dice: 0.9939, decode.d1.loss_cls: 0.5401, decode.d1.loss_mask: 0.6428, decode.d1.loss_dice: 0.9037, decode.d2.loss_cls: 0.4446, decode.d2.loss_mask: 0.6323, decode.d2.loss_dice: 0.8627, decode.d3.loss_cls: 0.4276, decode.d3.loss_mask: 0.6253, decode.d3.loss_dice: 0.8482, decode.d4.loss_cls: 0.4271, decode.d4.loss_mask: 0.6324, decode.d4.loss_dice: 0.8495, decode.d5.loss_cls: 0.4143, decode.d5.loss_mask: 0.6310, decode.d5.loss_dice: 0.8495, decode.d6.loss_cls: 0.4106, decode.d6.loss_mask: 0.6308, decode.d6.loss_dice: 0.8423, decode.d7.loss_cls: 0.4077, decode.d7.loss_mask: 0.6302, decode.d7.loss_dice: 0.8428, decode.d8.loss_cls: 0.4057, decode.d8.loss_mask: 0.6298, decode.d8.loss_dice: 0.8389, loss: 24.0578 +2022-05-06 02:31:19,624 - mmseg - INFO - Iter [7650/40000] lr: 1.161e-06, eta: 11:15:02, time: 0.692, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4583, decode.loss_mask: 0.6235, decode.loss_dice: 0.8389, decode.d0.loss_cls: 5.1864, decode.d0.loss_mask: 0.6430, decode.d0.loss_dice: 0.9891, decode.d1.loss_cls: 0.5824, decode.d1.loss_mask: 0.6491, decode.d1.loss_dice: 0.8976, decode.d2.loss_cls: 0.4885, decode.d2.loss_mask: 0.6342, decode.d2.loss_dice: 0.8661, decode.d3.loss_cls: 0.4621, decode.d3.loss_mask: 0.6321, decode.d3.loss_dice: 0.8472, decode.d4.loss_cls: 0.4668, decode.d4.loss_mask: 0.6280, decode.d4.loss_dice: 0.8424, decode.d5.loss_cls: 0.4565, decode.d5.loss_mask: 0.6269, decode.d5.loss_dice: 0.8413, decode.d6.loss_cls: 0.4535, decode.d6.loss_mask: 0.6267, decode.d6.loss_dice: 0.8358, decode.d7.loss_cls: 0.4524, decode.d7.loss_mask: 0.6272, decode.d7.loss_dice: 0.8409, decode.d8.loss_cls: 0.4568, decode.d8.loss_mask: 0.6219, decode.d8.loss_dice: 0.8454, loss: 24.4212 +2022-05-06 02:31:53,567 - mmseg - INFO - Iter [7700/40000] lr: 1.159e-06, eta: 11:09:49, time: 0.679, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4416, decode.loss_mask: 0.6372, decode.loss_dice: 0.8598, decode.d0.loss_cls: 5.1459, decode.d0.loss_mask: 0.6526, decode.d0.loss_dice: 1.0011, decode.d1.loss_cls: 0.5797, decode.d1.loss_mask: 0.6587, decode.d1.loss_dice: 0.9110, decode.d2.loss_cls: 0.4874, decode.d2.loss_mask: 0.6410, decode.d2.loss_dice: 0.8730, decode.d3.loss_cls: 0.4596, decode.d3.loss_mask: 0.6379, decode.d3.loss_dice: 0.8621, decode.d4.loss_cls: 0.4628, decode.d4.loss_mask: 0.6388, decode.d4.loss_dice: 0.8696, decode.d5.loss_cls: 0.4462, decode.d5.loss_mask: 0.6347, decode.d5.loss_dice: 0.8616, decode.d6.loss_cls: 0.4474, decode.d6.loss_mask: 0.6349, decode.d6.loss_dice: 0.8552, decode.d7.loss_cls: 0.4474, decode.d7.loss_mask: 0.6372, decode.d7.loss_dice: 0.8566, decode.d8.loss_cls: 0.4467, decode.d8.loss_mask: 0.6337, decode.d8.loss_dice: 0.8591, loss: 24.5804 +2022-05-06 02:32:30,786 - mmseg - INFO - Iter [7750/40000] lr: 1.158e-06, eta: 11:05:12, time: 0.744, data_time: 0.063, memory: 53770, decode.loss_cls: 0.4555, decode.loss_mask: 0.6426, decode.loss_dice: 0.8502, decode.d0.loss_cls: 5.1616, decode.d0.loss_mask: 0.6570, decode.d0.loss_dice: 1.0032, decode.d1.loss_cls: 0.5883, decode.d1.loss_mask: 0.6668, decode.d1.loss_dice: 0.9100, decode.d2.loss_cls: 0.4928, decode.d2.loss_mask: 0.6488, decode.d2.loss_dice: 0.8745, decode.d3.loss_cls: 0.4786, decode.d3.loss_mask: 0.6464, decode.d3.loss_dice: 0.8583, decode.d4.loss_cls: 0.4668, decode.d4.loss_mask: 0.6461, decode.d4.loss_dice: 0.8599, decode.d5.loss_cls: 0.4568, decode.d5.loss_mask: 0.6448, decode.d5.loss_dice: 0.8534, decode.d6.loss_cls: 0.4526, decode.d6.loss_mask: 0.6367, decode.d6.loss_dice: 0.8553, decode.d7.loss_cls: 0.4535, decode.d7.loss_mask: 0.6456, decode.d7.loss_dice: 0.8611, decode.d8.loss_cls: 0.4519, decode.d8.loss_mask: 0.6452, decode.d8.loss_dice: 0.8581, loss: 24.7225 +2022-05-06 02:33:04,962 - mmseg - INFO - Iter [7800/40000] lr: 1.156e-06, eta: 11:00:15, time: 0.683, data_time: 0.011, memory: 53770, decode.loss_cls: 0.4351, decode.loss_mask: 0.6179, decode.loss_dice: 0.8559, decode.d0.loss_cls: 5.0991, decode.d0.loss_mask: 0.6324, decode.d0.loss_dice: 0.9985, decode.d1.loss_cls: 0.5674, decode.d1.loss_mask: 0.6401, decode.d1.loss_dice: 0.9116, decode.d2.loss_cls: 0.4827, decode.d2.loss_mask: 0.6281, decode.d2.loss_dice: 0.8666, decode.d3.loss_cls: 0.4485, decode.d3.loss_mask: 0.6218, decode.d3.loss_dice: 0.8509, decode.d4.loss_cls: 0.4419, decode.d4.loss_mask: 0.6137, decode.d4.loss_dice: 0.8554, decode.d5.loss_cls: 0.4369, decode.d5.loss_mask: 0.6192, decode.d5.loss_dice: 0.8555, decode.d6.loss_cls: 0.4242, decode.d6.loss_mask: 0.6217, decode.d6.loss_dice: 0.8469, decode.d7.loss_cls: 0.4292, decode.d7.loss_mask: 0.6194, decode.d7.loss_dice: 0.8530, decode.d8.loss_cls: 0.4388, decode.d8.loss_mask: 0.6192, decode.d8.loss_dice: 0.8488, loss: 24.1802 +2022-05-06 02:33:38,567 - mmseg - INFO - Iter [7850/40000] lr: 1.154e-06, eta: 10:55:21, time: 0.672, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4171, decode.loss_mask: 0.6542, decode.loss_dice: 0.8484, decode.d0.loss_cls: 5.0705, decode.d0.loss_mask: 0.6579, decode.d0.loss_dice: 0.9911, decode.d1.loss_cls: 0.5341, decode.d1.loss_mask: 0.6657, decode.d1.loss_dice: 0.9004, decode.d2.loss_cls: 0.4459, decode.d2.loss_mask: 0.6573, decode.d2.loss_dice: 0.8705, decode.d3.loss_cls: 0.4292, decode.d3.loss_mask: 0.6514, decode.d3.loss_dice: 0.8508, decode.d4.loss_cls: 0.4225, decode.d4.loss_mask: 0.6546, decode.d4.loss_dice: 0.8525, decode.d5.loss_cls: 0.4146, decode.d5.loss_mask: 0.6509, decode.d5.loss_dice: 0.8497, decode.d6.loss_cls: 0.4159, decode.d6.loss_mask: 0.6525, decode.d6.loss_dice: 0.8430, decode.d7.loss_cls: 0.4147, decode.d7.loss_mask: 0.6508, decode.d7.loss_dice: 0.8443, decode.d8.loss_cls: 0.4129, decode.d8.loss_mask: 0.6490, decode.d8.loss_dice: 0.8465, loss: 24.2189 +2022-05-06 02:34:11,957 - mmseg - INFO - Iter [7900/40000] lr: 1.152e-06, eta: 10:50:31, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4008, decode.loss_mask: 0.6447, decode.loss_dice: 0.8328, decode.d0.loss_cls: 5.0358, decode.d0.loss_mask: 0.6522, decode.d0.loss_dice: 0.9705, decode.d1.loss_cls: 0.5349, decode.d1.loss_mask: 0.6578, decode.d1.loss_dice: 0.8808, decode.d2.loss_cls: 0.4589, decode.d2.loss_mask: 0.6472, decode.d2.loss_dice: 0.8427, decode.d3.loss_cls: 0.4209, decode.d3.loss_mask: 0.6454, decode.d3.loss_dice: 0.8273, decode.d4.loss_cls: 0.4135, decode.d4.loss_mask: 0.6393, decode.d4.loss_dice: 0.8283, decode.d5.loss_cls: 0.4092, decode.d5.loss_mask: 0.6433, decode.d5.loss_dice: 0.8251, decode.d6.loss_cls: 0.4043, decode.d6.loss_mask: 0.6420, decode.d6.loss_dice: 0.8254, decode.d7.loss_cls: 0.4095, decode.d7.loss_mask: 0.6404, decode.d7.loss_dice: 0.8255, decode.d8.loss_cls: 0.4034, decode.d8.loss_mask: 0.6440, decode.d8.loss_dice: 0.8346, loss: 23.8406 +2022-05-06 02:34:45,998 - mmseg - INFO - Iter [7950/40000] lr: 1.150e-06, eta: 10:45:53, time: 0.680, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4310, decode.loss_mask: 0.6000, decode.loss_dice: 0.8218, decode.d0.loss_cls: 5.0295, decode.d0.loss_mask: 0.6201, decode.d0.loss_dice: 0.9843, decode.d1.loss_cls: 0.5608, decode.d1.loss_mask: 0.6215, decode.d1.loss_dice: 0.8878, decode.d2.loss_cls: 0.4795, decode.d2.loss_mask: 0.6036, decode.d2.loss_dice: 0.8480, decode.d3.loss_cls: 0.4536, decode.d3.loss_mask: 0.5982, decode.d3.loss_dice: 0.8331, decode.d4.loss_cls: 0.4494, decode.d4.loss_mask: 0.6040, decode.d4.loss_dice: 0.8308, decode.d5.loss_cls: 0.4428, decode.d5.loss_mask: 0.5996, decode.d5.loss_dice: 0.8230, decode.d6.loss_cls: 0.4366, decode.d6.loss_mask: 0.6007, decode.d6.loss_dice: 0.8197, decode.d7.loss_cls: 0.4369, decode.d7.loss_mask: 0.6016, decode.d7.loss_dice: 0.8228, decode.d8.loss_cls: 0.4339, decode.d8.loss_mask: 0.6023, decode.d8.loss_dice: 0.8196, loss: 23.6966 +2022-05-06 02:35:20,625 - mmseg - INFO - Saving checkpoint at 8000 iterations +2022-05-06 02:35:48,074 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 02:35:48,081 - mmseg - INFO - Iter [8000/40000] lr: 1.149e-06, eta: 10:45:05, time: 1.239, data_time: 0.010, memory: 53770, decode.loss_cls: 0.4212, decode.loss_mask: 0.6033, decode.loss_dice: 0.8220, decode.d0.loss_cls: 4.9653, decode.d0.loss_mask: 0.6222, decode.d0.loss_dice: 0.9692, decode.d1.loss_cls: 0.5489, decode.d1.loss_mask: 0.6179, decode.d1.loss_dice: 0.8726, decode.d2.loss_cls: 0.4616, decode.d2.loss_mask: 0.6011, decode.d2.loss_dice: 0.8363, decode.d3.loss_cls: 0.4393, decode.d3.loss_mask: 0.6001, decode.d3.loss_dice: 0.8251, decode.d4.loss_cls: 0.4306, decode.d4.loss_mask: 0.5998, decode.d4.loss_dice: 0.8209, decode.d5.loss_cls: 0.4204, decode.d5.loss_mask: 0.6032, decode.d5.loss_dice: 0.8196, decode.d6.loss_cls: 0.4250, decode.d6.loss_mask: 0.6013, decode.d6.loss_dice: 0.8151, decode.d7.loss_cls: 0.4185, decode.d7.loss_mask: 0.6013, decode.d7.loss_dice: 0.8190, decode.d8.loss_cls: 0.4276, decode.d8.loss_mask: 0.6024, decode.d8.loss_dice: 0.8182, loss: 23.4291 +2022-05-06 02:40:09,597 - mmseg - INFO - per class results: +2022-05-06 02:40:09,614 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.19 | 96.29 | +| bag | 45.18 | 80.42 | +| bed | 34.95 | 59.57 | +| bedclothes | 33.35 | 39.75 | +| bench | 29.41 | 39.3 | +| bicycle | 83.69 | 91.04 | +| bird | 94.96 | 97.03 | +| boat | 85.9 | 91.91 | +| book | 56.93 | 66.43 | +| bottle | 90.29 | 96.6 | +| building | 64.96 | 83.72 | +| bus | 93.81 | 97.06 | +| cabinet | 55.09 | 71.83 | +| car | 93.42 | 97.16 | +| cat | 94.95 | 97.21 | +| ceiling | 59.62 | 71.54 | +| chair | 67.2 | 81.25 | +| cloth | 33.79 | 54.3 | +| computer | 64.17 | 78.77 | +| cow | 95.76 | 97.39 | +| cup | 51.95 | 70.0 | +| curtain | 62.54 | 73.38 | +| dog | 92.19 | 95.73 | +| door | 42.39 | 62.72 | +| fence | 45.7 | 58.09 | +| floor | 75.42 | 84.16 | +| flower | 40.95 | 62.54 | +| food | 36.21 | 47.78 | +| grass | 82.57 | 90.04 | +| ground | 57.91 | 73.3 | +| horse | 95.12 | 97.4 | +| keyboard | 89.1 | 94.12 | +| light | 60.14 | 80.4 | +| motorbike | 91.43 | 96.44 | +| mountain | 53.46 | 76.67 | +| mouse | 83.98 | 89.37 | +| person | 90.76 | 94.26 | +| plate | 24.83 | 29.22 | +| platform | 45.94 | 54.12 | +| pottedplant | 81.51 | 91.45 | +| road | 56.8 | 74.46 | +| rock | 48.19 | 60.34 | +| sheep | 95.08 | 97.45 | +| shelves | 44.15 | 58.36 | +| sidewalk | 29.75 | 60.38 | +| sign | 48.52 | 57.5 | +| sky | 94.73 | 96.64 | +| snow | 78.13 | 88.22 | +| sofa | 64.3 | 82.51 | +| table | 69.98 | 87.48 | +| track | 70.88 | 79.98 | +| train | 93.36 | 97.51 | +| tree | 81.26 | 89.94 | +| truck | 51.45 | 66.88 | +| tvmonitor | 90.84 | 92.97 | +| wall | 72.58 | 81.57 | +| water | 91.65 | 95.14 | +| window | 42.96 | 51.99 | +| wood | 27.19 | 45.93 | ++-------------+-------+-------+ +2022-05-06 02:40:09,615 - mmseg - INFO - Summary: +2022-05-06 02:40:09,615 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.12 | 66.53 | 77.54 | ++-------+-------+-------+ +2022-05-06 02:40:09,617 - mmseg - INFO - The previous best checkpoint /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/best_mIoU_iter_4000.pth was removed +2022-05-06 02:40:36,203 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_8000.pth. +2022-05-06 02:40:36,214 - mmseg - INFO - Best mIoU is 0.6653 at 8000 iter. +2022-05-06 02:40:36,249 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 02:40:36,249 - mmseg - INFO - Iter(val) [638] aAcc: 0.8612, mIoU: 0.6653, mAcc: 0.7754, IoU.aeroplane: 0.9219, IoU.bag: 0.4518, IoU.bed: 0.3495, IoU.bedclothes: 0.3335, IoU.bench: 0.2941, IoU.bicycle: 0.8369, IoU.bird: 0.9496, IoU.boat: 0.8590, IoU.book: 0.5693, IoU.bottle: 0.9029, IoU.building: 0.6496, IoU.bus: 0.9381, IoU.cabinet: 0.5509, IoU.car: 0.9342, IoU.cat: 0.9495, IoU.ceiling: 0.5962, IoU.chair: 0.6720, IoU.cloth: 0.3379, IoU.computer: 0.6417, IoU.cow: 0.9576, IoU.cup: 0.5195, IoU.curtain: 0.6254, IoU.dog: 0.9219, IoU.door: 0.4239, IoU.fence: 0.4570, IoU.floor: 0.7542, IoU.flower: 0.4095, IoU.food: 0.3621, IoU.grass: 0.8257, IoU.ground: 0.5791, IoU.horse: 0.9512, IoU.keyboard: 0.8910, IoU.light: 0.6014, IoU.motorbike: 0.9143, IoU.mountain: 0.5346, IoU.mouse: 0.8398, IoU.person: 0.9076, IoU.plate: 0.2483, IoU.platform: 0.4594, IoU.pottedplant: 0.8151, IoU.road: 0.5680, IoU.rock: 0.4819, IoU.sheep: 0.9508, IoU.shelves: 0.4415, IoU.sidewalk: 0.2975, IoU.sign: 0.4852, IoU.sky: 0.9473, IoU.snow: 0.7813, IoU.sofa: 0.6430, IoU.table: 0.6998, IoU.track: 0.7088, IoU.train: 0.9336, IoU.tree: 0.8126, IoU.truck: 0.5145, IoU.tvmonitor: 0.9084, IoU.wall: 0.7258, IoU.water: 0.9165, IoU.window: 0.4296, IoU.wood: 0.2719, Acc.aeroplane: 0.9629, Acc.bag: 0.8042, Acc.bed: 0.5957, Acc.bedclothes: 0.3975, Acc.bench: 0.3930, Acc.bicycle: 0.9104, Acc.bird: 0.9703, Acc.boat: 0.9191, Acc.book: 0.6643, Acc.bottle: 0.9660, Acc.building: 0.8372, Acc.bus: 0.9706, Acc.cabinet: 0.7183, Acc.car: 0.9716, Acc.cat: 0.9721, Acc.ceiling: 0.7154, Acc.chair: 0.8125, Acc.cloth: 0.5430, Acc.computer: 0.7877, Acc.cow: 0.9739, Acc.cup: 0.7000, Acc.curtain: 0.7338, Acc.dog: 0.9573, Acc.door: 0.6272, Acc.fence: 0.5809, Acc.floor: 0.8416, Acc.flower: 0.6254, Acc.food: 0.4778, Acc.grass: 0.9004, Acc.ground: 0.7330, Acc.horse: 0.9740, Acc.keyboard: 0.9412, Acc.light: 0.8040, Acc.motorbike: 0.9644, Acc.mountain: 0.7667, Acc.mouse: 0.8937, Acc.person: 0.9426, Acc.plate: 0.2922, Acc.platform: 0.5412, Acc.pottedplant: 0.9145, Acc.road: 0.7446, Acc.rock: 0.6034, Acc.sheep: 0.9745, Acc.shelves: 0.5836, Acc.sidewalk: 0.6038, Acc.sign: 0.5750, Acc.sky: 0.9664, Acc.snow: 0.8822, Acc.sofa: 0.8251, Acc.table: 0.8748, Acc.track: 0.7998, Acc.train: 0.9751, Acc.tree: 0.8994, Acc.truck: 0.6688, Acc.tvmonitor: 0.9297, Acc.wall: 0.8157, Acc.water: 0.9514, Acc.window: 0.5199, Acc.wood: 0.4593 +2022-05-06 02:41:10,452 - mmseg - INFO - Iter [8050/40000] lr: 1.147e-06, eta: 11:18:31, time: 6.450, data_time: 5.776, memory: 53770, decode.loss_cls: 0.4468, decode.loss_mask: 0.6465, decode.loss_dice: 0.8891, decode.d0.loss_cls: 4.9640, decode.d0.loss_mask: 0.6690, decode.d0.loss_dice: 1.0436, decode.d1.loss_cls: 0.5624, decode.d1.loss_mask: 0.6673, decode.d1.loss_dice: 0.9483, decode.d2.loss_cls: 0.4895, decode.d2.loss_mask: 0.6514, decode.d2.loss_dice: 0.9079, decode.d3.loss_cls: 0.4625, decode.d3.loss_mask: 0.6529, decode.d3.loss_dice: 0.8931, decode.d4.loss_cls: 0.4520, decode.d4.loss_mask: 0.6535, decode.d4.loss_dice: 0.8984, decode.d5.loss_cls: 0.4527, decode.d5.loss_mask: 0.6452, decode.d5.loss_dice: 0.8943, decode.d6.loss_cls: 0.4433, decode.d6.loss_mask: 0.6477, decode.d6.loss_dice: 0.8846, decode.d7.loss_cls: 0.4419, decode.d7.loss_mask: 0.6482, decode.d7.loss_dice: 0.8881, decode.d8.loss_cls: 0.4414, decode.d8.loss_mask: 0.6464, decode.d8.loss_dice: 0.8883, loss: 24.8204 +2022-05-06 02:41:47,203 - mmseg - INFO - Iter [8100/40000] lr: 1.145e-06, eta: 11:13:58, time: 0.735, data_time: 0.055, memory: 53770, decode.loss_cls: 0.4002, decode.loss_mask: 0.6055, decode.loss_dice: 0.8088, decode.d0.loss_cls: 4.9272, decode.d0.loss_mask: 0.6158, decode.d0.loss_dice: 0.9464, decode.d1.loss_cls: 0.5196, decode.d1.loss_mask: 0.6246, decode.d1.loss_dice: 0.8626, decode.d2.loss_cls: 0.4462, decode.d2.loss_mask: 0.6107, decode.d2.loss_dice: 0.8200, decode.d3.loss_cls: 0.4185, decode.d3.loss_mask: 0.6050, decode.d3.loss_dice: 0.8063, decode.d4.loss_cls: 0.4082, decode.d4.loss_mask: 0.6040, decode.d4.loss_dice: 0.8090, decode.d5.loss_cls: 0.4001, decode.d5.loss_mask: 0.6043, decode.d5.loss_dice: 0.8067, decode.d6.loss_cls: 0.3958, decode.d6.loss_mask: 0.6018, decode.d6.loss_dice: 0.7970, decode.d7.loss_cls: 0.3908, decode.d7.loss_mask: 0.6075, decode.d7.loss_dice: 0.8082, decode.d8.loss_cls: 0.3953, decode.d8.loss_mask: 0.6032, decode.d8.loss_dice: 0.8078, loss: 23.0570 +2022-05-06 02:42:20,875 - mmseg - INFO - Iter [8150/40000] lr: 1.143e-06, eta: 11:09:06, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4164, decode.loss_mask: 0.6030, decode.loss_dice: 0.8360, decode.d0.loss_cls: 4.9284, decode.d0.loss_mask: 0.6247, decode.d0.loss_dice: 0.9815, decode.d1.loss_cls: 0.5428, decode.d1.loss_mask: 0.6221, decode.d1.loss_dice: 0.8932, decode.d2.loss_cls: 0.4482, decode.d2.loss_mask: 0.6121, decode.d2.loss_dice: 0.8553, decode.d3.loss_cls: 0.4239, decode.d3.loss_mask: 0.6080, decode.d3.loss_dice: 0.8408, decode.d4.loss_cls: 0.4235, decode.d4.loss_mask: 0.6067, decode.d4.loss_dice: 0.8393, decode.d5.loss_cls: 0.4178, decode.d5.loss_mask: 0.6052, decode.d5.loss_dice: 0.8361, decode.d6.loss_cls: 0.4176, decode.d6.loss_mask: 0.5994, decode.d6.loss_dice: 0.8305, decode.d7.loss_cls: 0.4189, decode.d7.loss_mask: 0.6023, decode.d7.loss_dice: 0.8358, decode.d8.loss_cls: 0.4205, decode.d8.loss_mask: 0.5998, decode.d8.loss_dice: 0.8340, loss: 23.5237 +2022-05-06 02:42:54,953 - mmseg - INFO - Iter [8200/40000] lr: 1.141e-06, eta: 11:04:24, time: 0.682, data_time: 0.011, memory: 53770, decode.loss_cls: 0.3967, decode.loss_mask: 0.6090, decode.loss_dice: 0.8370, decode.d0.loss_cls: 4.8982, decode.d0.loss_mask: 0.6287, decode.d0.loss_dice: 0.9772, decode.d1.loss_cls: 0.5353, decode.d1.loss_mask: 0.6293, decode.d1.loss_dice: 0.8976, decode.d2.loss_cls: 0.4496, decode.d2.loss_mask: 0.6138, decode.d2.loss_dice: 0.8524, decode.d3.loss_cls: 0.4078, decode.d3.loss_mask: 0.6145, decode.d3.loss_dice: 0.8365, decode.d4.loss_cls: 0.4020, decode.d4.loss_mask: 0.6118, decode.d4.loss_dice: 0.8357, decode.d5.loss_cls: 0.3996, decode.d5.loss_mask: 0.6090, decode.d5.loss_dice: 0.8372, decode.d6.loss_cls: 0.3987, decode.d6.loss_mask: 0.6059, decode.d6.loss_dice: 0.8312, decode.d7.loss_cls: 0.3971, decode.d7.loss_mask: 0.6081, decode.d7.loss_dice: 0.8390, decode.d8.loss_cls: 0.3956, decode.d8.loss_mask: 0.6108, decode.d8.loss_dice: 0.8412, loss: 23.4068 +2022-05-06 02:43:28,526 - mmseg - INFO - Iter [8250/40000] lr: 1.140e-06, eta: 10:59:44, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4341, decode.loss_mask: 0.6188, decode.loss_dice: 0.8236, decode.d0.loss_cls: 4.8712, decode.d0.loss_mask: 0.6309, decode.d0.loss_dice: 0.9856, decode.d1.loss_cls: 0.5630, decode.d1.loss_mask: 0.6325, decode.d1.loss_dice: 0.8847, decode.d2.loss_cls: 0.4696, decode.d2.loss_mask: 0.6176, decode.d2.loss_dice: 0.8489, decode.d3.loss_cls: 0.4386, decode.d3.loss_mask: 0.6160, decode.d3.loss_dice: 0.8347, decode.d4.loss_cls: 0.4386, decode.d4.loss_mask: 0.6127, decode.d4.loss_dice: 0.8371, decode.d5.loss_cls: 0.4385, decode.d5.loss_mask: 0.6149, decode.d5.loss_dice: 0.8308, decode.d6.loss_cls: 0.4357, decode.d6.loss_mask: 0.6161, decode.d6.loss_dice: 0.8252, decode.d7.loss_cls: 0.4345, decode.d7.loss_mask: 0.6155, decode.d7.loss_dice: 0.8261, decode.d8.loss_cls: 0.4274, decode.d8.loss_mask: 0.6186, decode.d8.loss_dice: 0.8278, loss: 23.6693 +2022-05-06 02:44:02,258 - mmseg - INFO - Iter [8300/40000] lr: 1.138e-06, eta: 10:55:11, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3981, decode.loss_mask: 0.6214, decode.loss_dice: 0.8453, decode.d0.loss_cls: 4.8172, decode.d0.loss_mask: 0.6297, decode.d0.loss_dice: 0.9846, decode.d1.loss_cls: 0.5152, decode.d1.loss_mask: 0.6334, decode.d1.loss_dice: 0.9050, decode.d2.loss_cls: 0.4411, decode.d2.loss_mask: 0.6243, decode.d2.loss_dice: 0.8651, decode.d3.loss_cls: 0.4144, decode.d3.loss_mask: 0.6224, decode.d3.loss_dice: 0.8501, decode.d4.loss_cls: 0.4157, decode.d4.loss_mask: 0.6236, decode.d4.loss_dice: 0.8488, decode.d5.loss_cls: 0.4085, decode.d5.loss_mask: 0.6239, decode.d5.loss_dice: 0.8496, decode.d6.loss_cls: 0.4056, decode.d6.loss_mask: 0.6219, decode.d6.loss_dice: 0.8422, decode.d7.loss_cls: 0.4051, decode.d7.loss_mask: 0.6199, decode.d7.loss_dice: 0.8475, decode.d8.loss_cls: 0.3983, decode.d8.loss_mask: 0.6203, decode.d8.loss_dice: 0.8408, loss: 23.5391 +2022-05-06 02:44:35,639 - mmseg - INFO - Iter [8350/40000] lr: 1.136e-06, eta: 10:50:41, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4119, decode.loss_mask: 0.6224, decode.loss_dice: 0.8269, decode.d0.loss_cls: 4.8043, decode.d0.loss_mask: 0.6355, decode.d0.loss_dice: 0.9772, decode.d1.loss_cls: 0.5460, decode.d1.loss_mask: 0.6420, decode.d1.loss_dice: 0.8886, decode.d2.loss_cls: 0.4646, decode.d2.loss_mask: 0.6289, decode.d2.loss_dice: 0.8559, decode.d3.loss_cls: 0.4430, decode.d3.loss_mask: 0.6241, decode.d3.loss_dice: 0.8338, decode.d4.loss_cls: 0.4252, decode.d4.loss_mask: 0.6263, decode.d4.loss_dice: 0.8344, decode.d5.loss_cls: 0.4194, decode.d5.loss_mask: 0.6221, decode.d5.loss_dice: 0.8323, decode.d6.loss_cls: 0.4190, decode.d6.loss_mask: 0.6187, decode.d6.loss_dice: 0.8257, decode.d7.loss_cls: 0.4160, decode.d7.loss_mask: 0.6172, decode.d7.loss_dice: 0.8265, decode.d8.loss_cls: 0.4179, decode.d8.loss_mask: 0.6206, decode.d8.loss_dice: 0.8250, loss: 23.5514 +2022-05-06 02:45:11,785 - mmseg - INFO - Iter [8400/40000] lr: 1.134e-06, eta: 10:46:36, time: 0.723, data_time: 0.061, memory: 53770, decode.loss_cls: 0.3981, decode.loss_mask: 0.6285, decode.loss_dice: 0.8083, decode.d0.loss_cls: 4.7647, decode.d0.loss_mask: 0.6457, decode.d0.loss_dice: 0.9646, decode.d1.loss_cls: 0.5325, decode.d1.loss_mask: 0.6488, decode.d1.loss_dice: 0.8650, decode.d2.loss_cls: 0.4434, decode.d2.loss_mask: 0.6329, decode.d2.loss_dice: 0.8330, decode.d3.loss_cls: 0.4177, decode.d3.loss_mask: 0.6318, decode.d3.loss_dice: 0.8134, decode.d4.loss_cls: 0.4139, decode.d4.loss_mask: 0.6312, decode.d4.loss_dice: 0.8192, decode.d5.loss_cls: 0.3981, decode.d5.loss_mask: 0.6305, decode.d5.loss_dice: 0.8150, decode.d6.loss_cls: 0.3945, decode.d6.loss_mask: 0.6274, decode.d6.loss_dice: 0.8061, decode.d7.loss_cls: 0.3959, decode.d7.loss_mask: 0.6274, decode.d7.loss_dice: 0.8080, decode.d8.loss_cls: 0.3965, decode.d8.loss_mask: 0.6290, decode.d8.loss_dice: 0.8085, loss: 23.2295 +2022-05-06 02:45:45,405 - mmseg - INFO - Iter [8450/40000] lr: 1.133e-06, eta: 10:42:17, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4194, decode.loss_mask: 0.6167, decode.loss_dice: 0.8683, decode.d0.loss_cls: 4.7711, decode.d0.loss_mask: 0.6314, decode.d0.loss_dice: 1.0088, decode.d1.loss_cls: 0.5499, decode.d1.loss_mask: 0.6353, decode.d1.loss_dice: 0.9164, decode.d2.loss_cls: 0.4588, decode.d2.loss_mask: 0.6210, decode.d2.loss_dice: 0.8902, decode.d3.loss_cls: 0.4364, decode.d3.loss_mask: 0.6167, decode.d3.loss_dice: 0.8671, decode.d4.loss_cls: 0.4183, decode.d4.loss_mask: 0.6195, decode.d4.loss_dice: 0.8723, decode.d5.loss_cls: 0.4146, decode.d5.loss_mask: 0.6196, decode.d5.loss_dice: 0.8730, decode.d6.loss_cls: 0.4123, decode.d6.loss_mask: 0.6170, decode.d6.loss_dice: 0.8681, decode.d7.loss_cls: 0.4169, decode.d7.loss_mask: 0.6203, decode.d7.loss_dice: 0.8703, decode.d8.loss_cls: 0.4148, decode.d8.loss_mask: 0.6169, decode.d8.loss_dice: 0.8705, loss: 23.8317 +2022-05-06 02:46:19,544 - mmseg - INFO - Iter [8500/40000] lr: 1.131e-06, eta: 10:38:08, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4056, decode.loss_mask: 0.6123, decode.loss_dice: 0.8261, decode.d0.loss_cls: 4.7259, decode.d0.loss_mask: 0.6285, decode.d0.loss_dice: 0.9669, decode.d1.loss_cls: 0.5191, decode.d1.loss_mask: 0.6336, decode.d1.loss_dice: 0.8910, decode.d2.loss_cls: 0.4415, decode.d2.loss_mask: 0.6201, decode.d2.loss_dice: 0.8484, decode.d3.loss_cls: 0.4186, decode.d3.loss_mask: 0.6191, decode.d3.loss_dice: 0.8368, decode.d4.loss_cls: 0.4150, decode.d4.loss_mask: 0.6145, decode.d4.loss_dice: 0.8327, decode.d5.loss_cls: 0.4103, decode.d5.loss_mask: 0.6116, decode.d5.loss_dice: 0.8235, decode.d6.loss_cls: 0.4093, decode.d6.loss_mask: 0.6100, decode.d6.loss_dice: 0.8214, decode.d7.loss_cls: 0.4128, decode.d7.loss_mask: 0.6116, decode.d7.loss_dice: 0.8299, decode.d8.loss_cls: 0.4031, decode.d8.loss_mask: 0.6126, decode.d8.loss_dice: 0.8282, loss: 23.2399 +2022-05-06 02:46:53,177 - mmseg - INFO - Iter [8550/40000] lr: 1.129e-06, eta: 10:34:00, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4077, decode.loss_mask: 0.6311, decode.loss_dice: 0.8450, decode.d0.loss_cls: 4.7063, decode.d0.loss_mask: 0.6363, decode.d0.loss_dice: 0.9910, decode.d1.loss_cls: 0.5221, decode.d1.loss_mask: 0.6420, decode.d1.loss_dice: 0.8932, decode.d2.loss_cls: 0.4396, decode.d2.loss_mask: 0.6335, decode.d2.loss_dice: 0.8621, decode.d3.loss_cls: 0.4096, decode.d3.loss_mask: 0.6292, decode.d3.loss_dice: 0.8468, decode.d4.loss_cls: 0.4065, decode.d4.loss_mask: 0.6250, decode.d4.loss_dice: 0.8464, decode.d5.loss_cls: 0.4098, decode.d5.loss_mask: 0.6276, decode.d5.loss_dice: 0.8429, decode.d6.loss_cls: 0.4086, decode.d6.loss_mask: 0.6280, decode.d6.loss_dice: 0.8392, decode.d7.loss_cls: 0.4089, decode.d7.loss_mask: 0.6296, decode.d7.loss_dice: 0.8443, decode.d8.loss_cls: 0.4083, decode.d8.loss_mask: 0.6272, decode.d8.loss_dice: 0.8416, loss: 23.4896 +2022-05-06 02:47:27,332 - mmseg - INFO - Iter [8600/40000] lr: 1.127e-06, eta: 10:29:59, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4061, decode.loss_mask: 0.6232, decode.loss_dice: 0.8398, decode.d0.loss_cls: 4.6966, decode.d0.loss_mask: 0.6329, decode.d0.loss_dice: 0.9761, decode.d1.loss_cls: 0.5328, decode.d1.loss_mask: 0.6408, decode.d1.loss_dice: 0.9002, decode.d2.loss_cls: 0.4326, decode.d2.loss_mask: 0.6322, decode.d2.loss_dice: 0.8664, decode.d3.loss_cls: 0.4167, decode.d3.loss_mask: 0.6220, decode.d3.loss_dice: 0.8418, decode.d4.loss_cls: 0.4079, decode.d4.loss_mask: 0.6185, decode.d4.loss_dice: 0.8432, decode.d5.loss_cls: 0.4059, decode.d5.loss_mask: 0.6207, decode.d5.loss_dice: 0.8353, decode.d6.loss_cls: 0.4025, decode.d6.loss_mask: 0.6191, decode.d6.loss_dice: 0.8322, decode.d7.loss_cls: 0.4029, decode.d7.loss_mask: 0.6195, decode.d7.loss_dice: 0.8360, decode.d8.loss_cls: 0.3971, decode.d8.loss_mask: 0.6236, decode.d8.loss_dice: 0.8409, loss: 23.3653 +2022-05-06 02:48:00,833 - mmseg - INFO - Iter [8650/40000] lr: 1.125e-06, eta: 10:25:59, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4110, decode.loss_mask: 0.5989, decode.loss_dice: 0.8414, decode.d0.loss_cls: 4.6493, decode.d0.loss_mask: 0.6238, decode.d0.loss_dice: 0.9853, decode.d1.loss_cls: 0.5466, decode.d1.loss_mask: 0.6158, decode.d1.loss_dice: 0.9028, decode.d2.loss_cls: 0.4614, decode.d2.loss_mask: 0.6035, decode.d2.loss_dice: 0.8586, decode.d3.loss_cls: 0.4311, decode.d3.loss_mask: 0.5979, decode.d3.loss_dice: 0.8411, decode.d4.loss_cls: 0.4264, decode.d4.loss_mask: 0.5966, decode.d4.loss_dice: 0.8430, decode.d5.loss_cls: 0.4095, decode.d5.loss_mask: 0.5951, decode.d5.loss_dice: 0.8413, decode.d6.loss_cls: 0.4072, decode.d6.loss_mask: 0.5977, decode.d6.loss_dice: 0.8363, decode.d7.loss_cls: 0.4083, decode.d7.loss_mask: 0.5966, decode.d7.loss_dice: 0.8423, decode.d8.loss_cls: 0.4174, decode.d8.loss_mask: 0.5963, decode.d8.loss_dice: 0.8405, loss: 23.2228 +2022-05-06 02:48:36,804 - mmseg - INFO - Iter [8700/40000] lr: 1.124e-06, eta: 10:22:20, time: 0.720, data_time: 0.058, memory: 53770, decode.loss_cls: 0.3785, decode.loss_mask: 0.5899, decode.loss_dice: 0.7977, decode.d0.loss_cls: 4.6320, decode.d0.loss_mask: 0.6179, decode.d0.loss_dice: 0.9440, decode.d1.loss_cls: 0.5255, decode.d1.loss_mask: 0.6137, decode.d1.loss_dice: 0.8501, decode.d2.loss_cls: 0.4247, decode.d2.loss_mask: 0.6005, decode.d2.loss_dice: 0.8187, decode.d3.loss_cls: 0.4007, decode.d3.loss_mask: 0.5980, decode.d3.loss_dice: 0.8008, decode.d4.loss_cls: 0.3930, decode.d4.loss_mask: 0.5911, decode.d4.loss_dice: 0.8011, decode.d5.loss_cls: 0.3798, decode.d5.loss_mask: 0.5968, decode.d5.loss_dice: 0.7984, decode.d6.loss_cls: 0.3738, decode.d6.loss_mask: 0.5953, decode.d6.loss_dice: 0.7921, decode.d7.loss_cls: 0.3791, decode.d7.loss_mask: 0.5926, decode.d7.loss_dice: 0.8000, decode.d8.loss_cls: 0.3798, decode.d8.loss_mask: 0.5923, decode.d8.loss_dice: 0.7962, loss: 22.4540 +2022-05-06 02:49:10,810 - mmseg - INFO - Iter [8750/40000] lr: 1.122e-06, eta: 10:18:32, time: 0.680, data_time: 0.008, memory: 53770, decode.loss_cls: 0.4096, decode.loss_mask: 0.6119, decode.loss_dice: 0.8129, decode.d0.loss_cls: 4.5893, decode.d0.loss_mask: 0.6325, decode.d0.loss_dice: 0.9637, decode.d1.loss_cls: 0.5500, decode.d1.loss_mask: 0.6223, decode.d1.loss_dice: 0.8722, decode.d2.loss_cls: 0.4573, decode.d2.loss_mask: 0.6191, decode.d2.loss_dice: 0.8436, decode.d3.loss_cls: 0.4178, decode.d3.loss_mask: 0.6146, decode.d3.loss_dice: 0.8250, decode.d4.loss_cls: 0.4194, decode.d4.loss_mask: 0.6097, decode.d4.loss_dice: 0.8205, decode.d5.loss_cls: 0.4105, decode.d5.loss_mask: 0.6100, decode.d5.loss_dice: 0.8193, decode.d6.loss_cls: 0.4055, decode.d6.loss_mask: 0.6068, decode.d6.loss_dice: 0.8148, decode.d7.loss_cls: 0.4134, decode.d7.loss_mask: 0.6058, decode.d7.loss_dice: 0.8162, decode.d8.loss_cls: 0.4055, decode.d8.loss_mask: 0.6090, decode.d8.loss_dice: 0.8162, loss: 23.0243 +2022-05-06 02:49:44,341 - mmseg - INFO - Iter [8800/40000] lr: 1.120e-06, eta: 10:14:44, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3491, decode.loss_mask: 0.5986, decode.loss_dice: 0.8146, decode.d0.loss_cls: 4.5681, decode.d0.loss_mask: 0.6087, decode.d0.loss_dice: 0.9413, decode.d1.loss_cls: 0.4796, decode.d1.loss_mask: 0.6160, decode.d1.loss_dice: 0.8627, decode.d2.loss_cls: 0.3952, decode.d2.loss_mask: 0.6027, decode.d2.loss_dice: 0.8267, decode.d3.loss_cls: 0.3697, decode.d3.loss_mask: 0.5982, decode.d3.loss_dice: 0.8134, decode.d4.loss_cls: 0.3589, decode.d4.loss_mask: 0.5958, decode.d4.loss_dice: 0.8130, decode.d5.loss_cls: 0.3522, decode.d5.loss_mask: 0.5959, decode.d5.loss_dice: 0.8108, decode.d6.loss_cls: 0.3428, decode.d6.loss_mask: 0.5979, decode.d6.loss_dice: 0.8124, decode.d7.loss_cls: 0.3487, decode.d7.loss_mask: 0.5979, decode.d7.loss_dice: 0.8093, decode.d8.loss_cls: 0.3408, decode.d8.loss_mask: 0.5984, decode.d8.loss_dice: 0.8127, loss: 22.2322 +2022-05-06 02:50:18,552 - mmseg - INFO - Iter [8850/40000] lr: 1.118e-06, eta: 10:11:05, time: 0.684, data_time: 0.008, memory: 53770, decode.loss_cls: 0.3899, decode.loss_mask: 0.6074, decode.loss_dice: 0.8373, decode.d0.loss_cls: 4.5798, decode.d0.loss_mask: 0.6305, decode.d0.loss_dice: 0.9724, decode.d1.loss_cls: 0.5228, decode.d1.loss_mask: 0.6312, decode.d1.loss_dice: 0.8894, decode.d2.loss_cls: 0.4377, decode.d2.loss_mask: 0.6171, decode.d2.loss_dice: 0.8518, decode.d3.loss_cls: 0.4051, decode.d3.loss_mask: 0.6133, decode.d3.loss_dice: 0.8363, decode.d4.loss_cls: 0.4011, decode.d4.loss_mask: 0.6066, decode.d4.loss_dice: 0.8457, decode.d5.loss_cls: 0.3878, decode.d5.loss_mask: 0.6090, decode.d5.loss_dice: 0.8474, decode.d6.loss_cls: 0.3897, decode.d6.loss_mask: 0.6099, decode.d6.loss_dice: 0.8397, decode.d7.loss_cls: 0.3872, decode.d7.loss_mask: 0.6113, decode.d7.loss_dice: 0.8459, decode.d8.loss_cls: 0.3862, decode.d8.loss_mask: 0.6091, decode.d8.loss_dice: 0.8476, loss: 23.0461 +2022-05-06 02:50:52,424 - mmseg - INFO - Iter [8900/40000] lr: 1.116e-06, eta: 10:07:28, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3851, decode.loss_mask: 0.6172, decode.loss_dice: 0.8190, decode.d0.loss_cls: 4.5362, decode.d0.loss_mask: 0.6377, decode.d0.loss_dice: 0.9583, decode.d1.loss_cls: 0.5334, decode.d1.loss_mask: 0.6374, decode.d1.loss_dice: 0.8732, decode.d2.loss_cls: 0.4382, decode.d2.loss_mask: 0.6208, decode.d2.loss_dice: 0.8388, decode.d3.loss_cls: 0.4030, decode.d3.loss_mask: 0.6187, decode.d3.loss_dice: 0.8239, decode.d4.loss_cls: 0.3964, decode.d4.loss_mask: 0.6164, decode.d4.loss_dice: 0.8205, decode.d5.loss_cls: 0.3893, decode.d5.loss_mask: 0.6151, decode.d5.loss_dice: 0.8236, decode.d6.loss_cls: 0.3791, decode.d6.loss_mask: 0.6171, decode.d6.loss_dice: 0.8196, decode.d7.loss_cls: 0.3804, decode.d7.loss_mask: 0.6128, decode.d7.loss_dice: 0.8191, decode.d8.loss_cls: 0.3822, decode.d8.loss_mask: 0.6145, decode.d8.loss_dice: 0.8201, loss: 22.8472 +2022-05-06 02:51:26,006 - mmseg - INFO - Iter [8950/40000] lr: 1.115e-06, eta: 10:03:52, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3816, decode.loss_mask: 0.5968, decode.loss_dice: 0.8138, decode.d0.loss_cls: 4.4996, decode.d0.loss_mask: 0.6123, decode.d0.loss_dice: 0.9566, decode.d1.loss_cls: 0.5087, decode.d1.loss_mask: 0.6080, decode.d1.loss_dice: 0.8587, decode.d2.loss_cls: 0.4211, decode.d2.loss_mask: 0.5976, decode.d2.loss_dice: 0.8252, decode.d3.loss_cls: 0.3915, decode.d3.loss_mask: 0.5891, decode.d3.loss_dice: 0.8119, decode.d4.loss_cls: 0.3834, decode.d4.loss_mask: 0.5888, decode.d4.loss_dice: 0.8164, decode.d5.loss_cls: 0.3795, decode.d5.loss_mask: 0.5917, decode.d5.loss_dice: 0.8118, decode.d6.loss_cls: 0.3722, decode.d6.loss_mask: 0.5895, decode.d6.loss_dice: 0.8051, decode.d7.loss_cls: 0.3725, decode.d7.loss_mask: 0.5902, decode.d7.loss_dice: 0.8128, decode.d8.loss_cls: 0.3745, decode.d8.loss_mask: 0.5935, decode.d8.loss_dice: 0.8146, loss: 22.3689 +2022-05-06 02:52:02,060 - mmseg - INFO - Saving checkpoint at 9000 iterations +2022-05-06 02:52:27,521 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 02:52:27,525 - mmseg - INFO - Iter [9000/40000] lr: 1.113e-06, eta: 10:03:12, time: 1.225, data_time: 0.058, memory: 53770, decode.loss_cls: 0.4046, decode.loss_mask: 0.5933, decode.loss_dice: 0.7997, decode.d0.loss_cls: 4.5010, decode.d0.loss_mask: 0.6132, decode.d0.loss_dice: 0.9563, decode.d1.loss_cls: 0.5539, decode.d1.loss_mask: 0.6090, decode.d1.loss_dice: 0.8642, decode.d2.loss_cls: 0.4703, decode.d2.loss_mask: 0.5960, decode.d2.loss_dice: 0.8188, decode.d3.loss_cls: 0.4379, decode.d3.loss_mask: 0.5924, decode.d3.loss_dice: 0.8016, decode.d4.loss_cls: 0.4294, decode.d4.loss_mask: 0.5936, decode.d4.loss_dice: 0.8020, decode.d5.loss_cls: 0.4168, decode.d5.loss_mask: 0.5923, decode.d5.loss_dice: 0.8041, decode.d6.loss_cls: 0.4070, decode.d6.loss_mask: 0.5949, decode.d6.loss_dice: 0.8015, decode.d7.loss_cls: 0.4096, decode.d7.loss_mask: 0.5924, decode.d7.loss_dice: 0.8006, decode.d8.loss_cls: 0.4128, decode.d8.loss_mask: 0.5926, decode.d8.loss_dice: 0.8001, loss: 22.6621 +2022-05-06 02:53:01,621 - mmseg - INFO - Iter [9050/40000] lr: 1.111e-06, eta: 9:59:46, time: 0.686, data_time: 0.014, memory: 53770, decode.loss_cls: 0.3832, decode.loss_mask: 0.5983, decode.loss_dice: 0.8036, decode.d0.loss_cls: 4.4684, decode.d0.loss_mask: 0.6095, decode.d0.loss_dice: 0.9505, decode.d1.loss_cls: 0.5268, decode.d1.loss_mask: 0.6132, decode.d1.loss_dice: 0.8554, decode.d2.loss_cls: 0.4257, decode.d2.loss_mask: 0.6037, decode.d2.loss_dice: 0.8200, decode.d3.loss_cls: 0.3914, decode.d3.loss_mask: 0.6014, decode.d3.loss_dice: 0.8106, decode.d4.loss_cls: 0.3869, decode.d4.loss_mask: 0.5978, decode.d4.loss_dice: 0.8075, decode.d5.loss_cls: 0.3856, decode.d5.loss_mask: 0.5979, decode.d5.loss_dice: 0.8082, decode.d6.loss_cls: 0.3804, decode.d6.loss_mask: 0.5957, decode.d6.loss_dice: 0.8012, decode.d7.loss_cls: 0.3885, decode.d7.loss_mask: 0.5946, decode.d7.loss_dice: 0.8041, decode.d8.loss_cls: 0.3835, decode.d8.loss_mask: 0.5975, decode.d8.loss_dice: 0.8063, loss: 22.3974 +2022-05-06 02:53:35,786 - mmseg - INFO - Iter [9100/40000] lr: 1.109e-06, eta: 9:56:23, time: 0.684, data_time: 0.010, memory: 53770, decode.loss_cls: 0.3481, decode.loss_mask: 0.5944, decode.loss_dice: 0.7717, decode.d0.loss_cls: 4.3976, decode.d0.loss_mask: 0.6207, decode.d0.loss_dice: 0.9135, decode.d1.loss_cls: 0.4672, decode.d1.loss_mask: 0.6062, decode.d1.loss_dice: 0.8256, decode.d2.loss_cls: 0.3833, decode.d2.loss_mask: 0.5954, decode.d2.loss_dice: 0.7909, decode.d3.loss_cls: 0.3579, decode.d3.loss_mask: 0.5902, decode.d3.loss_dice: 0.7799, decode.d4.loss_cls: 0.3510, decode.d4.loss_mask: 0.5901, decode.d4.loss_dice: 0.7743, decode.d5.loss_cls: 0.3407, decode.d5.loss_mask: 0.5900, decode.d5.loss_dice: 0.7723, decode.d6.loss_cls: 0.3411, decode.d6.loss_mask: 0.5892, decode.d6.loss_dice: 0.7690, decode.d7.loss_cls: 0.3405, decode.d7.loss_mask: 0.5872, decode.d7.loss_dice: 0.7672, decode.d8.loss_cls: 0.3442, decode.d8.loss_mask: 0.5889, decode.d8.loss_dice: 0.7718, loss: 21.5601 +2022-05-06 02:54:09,840 - mmseg - INFO - Iter [9150/40000] lr: 1.107e-06, eta: 9:53:03, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3578, decode.loss_mask: 0.6001, decode.loss_dice: 0.7897, decode.d0.loss_cls: 4.3971, decode.d0.loss_mask: 0.6220, decode.d0.loss_dice: 0.9427, decode.d1.loss_cls: 0.4923, decode.d1.loss_mask: 0.6169, decode.d1.loss_dice: 0.8388, decode.d2.loss_cls: 0.4078, decode.d2.loss_mask: 0.6031, decode.d2.loss_dice: 0.8060, decode.d3.loss_cls: 0.3835, decode.d3.loss_mask: 0.5992, decode.d3.loss_dice: 0.7890, decode.d4.loss_cls: 0.3691, decode.d4.loss_mask: 0.6009, decode.d4.loss_dice: 0.7963, decode.d5.loss_cls: 0.3607, decode.d5.loss_mask: 0.5999, decode.d5.loss_dice: 0.7928, decode.d6.loss_cls: 0.3649, decode.d6.loss_mask: 0.5979, decode.d6.loss_dice: 0.7857, decode.d7.loss_cls: 0.3625, decode.d7.loss_mask: 0.5975, decode.d7.loss_dice: 0.7898, decode.d8.loss_cls: 0.3612, decode.d8.loss_mask: 0.5986, decode.d8.loss_dice: 0.7924, loss: 22.0160 +2022-05-06 02:54:43,927 - mmseg - INFO - Iter [9200/40000] lr: 1.106e-06, eta: 9:49:45, time: 0.682, data_time: 0.010, memory: 53770, decode.loss_cls: 0.3819, decode.loss_mask: 0.5767, decode.loss_dice: 0.8324, decode.d0.loss_cls: 4.3841, decode.d0.loss_mask: 0.6045, decode.d0.loss_dice: 0.9743, decode.d1.loss_cls: 0.5062, decode.d1.loss_mask: 0.5988, decode.d1.loss_dice: 0.8851, decode.d2.loss_cls: 0.4293, decode.d2.loss_mask: 0.5844, decode.d2.loss_dice: 0.8498, decode.d3.loss_cls: 0.4034, decode.d3.loss_mask: 0.5757, decode.d3.loss_dice: 0.8340, decode.d4.loss_cls: 0.3890, decode.d4.loss_mask: 0.5777, decode.d4.loss_dice: 0.8366, decode.d5.loss_cls: 0.3900, decode.d5.loss_mask: 0.5760, decode.d5.loss_dice: 0.8334, decode.d6.loss_cls: 0.3865, decode.d6.loss_mask: 0.5758, decode.d6.loss_dice: 0.8244, decode.d7.loss_cls: 0.3773, decode.d7.loss_mask: 0.5762, decode.d7.loss_dice: 0.8302, decode.d8.loss_cls: 0.3746, decode.d8.loss_mask: 0.5761, decode.d8.loss_dice: 0.8339, loss: 22.3785 +2022-05-06 02:55:18,106 - mmseg - INFO - Iter [9250/40000] lr: 1.104e-06, eta: 9:46:32, time: 0.684, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3970, decode.loss_mask: 0.6251, decode.loss_dice: 0.8507, decode.d0.loss_cls: 4.3870, decode.d0.loss_mask: 0.6414, decode.d0.loss_dice: 0.9890, decode.d1.loss_cls: 0.5080, decode.d1.loss_mask: 0.6506, decode.d1.loss_dice: 0.9037, decode.d2.loss_cls: 0.4377, decode.d2.loss_mask: 0.6353, decode.d2.loss_dice: 0.8662, decode.d3.loss_cls: 0.4065, decode.d3.loss_mask: 0.6320, decode.d3.loss_dice: 0.8543, decode.d4.loss_cls: 0.4013, decode.d4.loss_mask: 0.6294, decode.d4.loss_dice: 0.8587, decode.d5.loss_cls: 0.4019, decode.d5.loss_mask: 0.6224, decode.d5.loss_dice: 0.8505, decode.d6.loss_cls: 0.3833, decode.d6.loss_mask: 0.6258, decode.d6.loss_dice: 0.8485, decode.d7.loss_cls: 0.3862, decode.d7.loss_mask: 0.6248, decode.d7.loss_dice: 0.8495, decode.d8.loss_cls: 0.3927, decode.d8.loss_mask: 0.6313, decode.d8.loss_dice: 0.8477, loss: 23.1386 +2022-05-06 02:55:51,634 - mmseg - INFO - Iter [9300/40000] lr: 1.102e-06, eta: 9:43:17, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.4068, decode.loss_mask: 0.6132, decode.loss_dice: 0.8358, decode.d0.loss_cls: 4.3446, decode.d0.loss_mask: 0.6266, decode.d0.loss_dice: 0.9762, decode.d1.loss_cls: 0.5281, decode.d1.loss_mask: 0.6371, decode.d1.loss_dice: 0.8899, decode.d2.loss_cls: 0.4399, decode.d2.loss_mask: 0.6216, decode.d2.loss_dice: 0.8529, decode.d3.loss_cls: 0.4123, decode.d3.loss_mask: 0.6160, decode.d3.loss_dice: 0.8452, decode.d4.loss_cls: 0.4062, decode.d4.loss_mask: 0.6183, decode.d4.loss_dice: 0.8481, decode.d5.loss_cls: 0.4031, decode.d5.loss_mask: 0.6144, decode.d5.loss_dice: 0.8378, decode.d6.loss_cls: 0.3987, decode.d6.loss_mask: 0.6139, decode.d6.loss_dice: 0.8341, decode.d7.loss_cls: 0.3976, decode.d7.loss_mask: 0.6126, decode.d7.loss_dice: 0.8400, decode.d8.loss_cls: 0.3995, decode.d8.loss_mask: 0.6166, decode.d8.loss_dice: 0.8363, loss: 22.9235 +2022-05-06 02:56:28,369 - mmseg - INFO - Iter [9350/40000] lr: 1.100e-06, eta: 9:40:24, time: 0.734, data_time: 0.061, memory: 53770, decode.loss_cls: 0.3915, decode.loss_mask: 0.5704, decode.loss_dice: 0.8164, decode.d0.loss_cls: 4.3207, decode.d0.loss_mask: 0.5841, decode.d0.loss_dice: 0.9743, decode.d1.loss_cls: 0.5379, decode.d1.loss_mask: 0.5860, decode.d1.loss_dice: 0.8841, decode.d2.loss_cls: 0.4234, decode.d2.loss_mask: 0.5779, decode.d2.loss_dice: 0.8410, decode.d3.loss_cls: 0.4034, decode.d3.loss_mask: 0.5676, decode.d3.loss_dice: 0.8223, decode.d4.loss_cls: 0.4010, decode.d4.loss_mask: 0.5703, decode.d4.loss_dice: 0.8166, decode.d5.loss_cls: 0.3882, decode.d5.loss_mask: 0.5700, decode.d5.loss_dice: 0.8183, decode.d6.loss_cls: 0.3796, decode.d6.loss_mask: 0.5737, decode.d6.loss_dice: 0.8128, decode.d7.loss_cls: 0.3784, decode.d7.loss_mask: 0.5736, decode.d7.loss_dice: 0.8190, decode.d8.loss_cls: 0.3891, decode.d8.loss_mask: 0.5726, decode.d8.loss_dice: 0.8208, loss: 22.1851 +2022-05-06 02:57:02,259 - mmseg - INFO - Iter [9400/40000] lr: 1.098e-06, eta: 9:37:17, time: 0.678, data_time: 0.010, memory: 53770, decode.loss_cls: 0.3414, decode.loss_mask: 0.5917, decode.loss_dice: 0.7908, decode.d0.loss_cls: 4.2548, decode.d0.loss_mask: 0.6100, decode.d0.loss_dice: 0.9281, decode.d1.loss_cls: 0.4576, decode.d1.loss_mask: 0.6103, decode.d1.loss_dice: 0.8390, decode.d2.loss_cls: 0.3860, decode.d2.loss_mask: 0.5996, decode.d2.loss_dice: 0.8063, decode.d3.loss_cls: 0.3569, decode.d3.loss_mask: 0.5945, decode.d3.loss_dice: 0.7954, decode.d4.loss_cls: 0.3476, decode.d4.loss_mask: 0.5911, decode.d4.loss_dice: 0.7947, decode.d5.loss_cls: 0.3435, decode.d5.loss_mask: 0.5902, decode.d5.loss_dice: 0.7954, decode.d6.loss_cls: 0.3408, decode.d6.loss_mask: 0.5908, decode.d6.loss_dice: 0.7875, decode.d7.loss_cls: 0.3394, decode.d7.loss_mask: 0.5882, decode.d7.loss_dice: 0.7910, decode.d8.loss_cls: 0.3381, decode.d8.loss_mask: 0.5921, decode.d8.loss_dice: 0.7893, loss: 21.5820 +2022-05-06 02:57:35,821 - mmseg - INFO - Iter [9450/40000] lr: 1.097e-06, eta: 9:34:12, time: 0.671, data_time: 0.008, memory: 53770, decode.loss_cls: 0.3308, decode.loss_mask: 0.5941, decode.loss_dice: 0.7646, decode.d0.loss_cls: 4.2490, decode.d0.loss_mask: 0.6113, decode.d0.loss_dice: 0.8978, decode.d1.loss_cls: 0.4733, decode.d1.loss_mask: 0.6050, decode.d1.loss_dice: 0.8064, decode.d2.loss_cls: 0.3831, decode.d2.loss_mask: 0.6022, decode.d2.loss_dice: 0.7788, decode.d3.loss_cls: 0.3457, decode.d3.loss_mask: 0.5940, decode.d3.loss_dice: 0.7718, decode.d4.loss_cls: 0.3409, decode.d4.loss_mask: 0.5933, decode.d4.loss_dice: 0.7667, decode.d5.loss_cls: 0.3440, decode.d5.loss_mask: 0.5948, decode.d5.loss_dice: 0.7554, decode.d6.loss_cls: 0.3334, decode.d6.loss_mask: 0.5908, decode.d6.loss_dice: 0.7591, decode.d7.loss_cls: 0.3313, decode.d7.loss_mask: 0.5935, decode.d7.loss_dice: 0.7591, decode.d8.loss_cls: 0.3287, decode.d8.loss_mask: 0.5922, decode.d8.loss_dice: 0.7612, loss: 21.2523 +2022-05-06 02:58:09,728 - mmseg - INFO - Iter [9500/40000] lr: 1.095e-06, eta: 9:31:11, time: 0.678, data_time: 0.008, memory: 53770, decode.loss_cls: 0.3686, decode.loss_mask: 0.5800, decode.loss_dice: 0.8102, decode.d0.loss_cls: 4.2110, decode.d0.loss_mask: 0.5908, decode.d0.loss_dice: 0.9359, decode.d1.loss_cls: 0.4971, decode.d1.loss_mask: 0.5968, decode.d1.loss_dice: 0.8631, decode.d2.loss_cls: 0.4124, decode.d2.loss_mask: 0.5850, decode.d2.loss_dice: 0.8230, decode.d3.loss_cls: 0.3723, decode.d3.loss_mask: 0.5797, decode.d3.loss_dice: 0.8109, decode.d4.loss_cls: 0.3740, decode.d4.loss_mask: 0.5831, decode.d4.loss_dice: 0.8102, decode.d5.loss_cls: 0.3664, decode.d5.loss_mask: 0.5811, decode.d5.loss_dice: 0.8064, decode.d6.loss_cls: 0.3603, decode.d6.loss_mask: 0.5777, decode.d6.loss_dice: 0.8070, decode.d7.loss_cls: 0.3598, decode.d7.loss_mask: 0.5808, decode.d7.loss_dice: 0.8124, decode.d8.loss_cls: 0.3660, decode.d8.loss_mask: 0.5799, decode.d8.loss_dice: 0.8067, loss: 21.8085 +2022-05-06 02:58:43,590 - mmseg - INFO - Iter [9550/40000] lr: 1.093e-06, eta: 9:28:12, time: 0.677, data_time: 0.008, memory: 53770, decode.loss_cls: 0.3552, decode.loss_mask: 0.5988, decode.loss_dice: 0.7866, decode.d0.loss_cls: 4.2108, decode.d0.loss_mask: 0.6201, decode.d0.loss_dice: 0.9277, decode.d1.loss_cls: 0.4671, decode.d1.loss_mask: 0.6233, decode.d1.loss_dice: 0.8417, decode.d2.loss_cls: 0.3855, decode.d2.loss_mask: 0.6075, decode.d2.loss_dice: 0.8123, decode.d3.loss_cls: 0.3694, decode.d3.loss_mask: 0.5998, decode.d3.loss_dice: 0.7948, decode.d4.loss_cls: 0.3682, decode.d4.loss_mask: 0.5964, decode.d4.loss_dice: 0.7923, decode.d5.loss_cls: 0.3580, decode.d5.loss_mask: 0.5926, decode.d5.loss_dice: 0.7918, decode.d6.loss_cls: 0.3527, decode.d6.loss_mask: 0.5973, decode.d6.loss_dice: 0.7870, decode.d7.loss_cls: 0.3485, decode.d7.loss_mask: 0.5971, decode.d7.loss_dice: 0.7902, decode.d8.loss_cls: 0.3547, decode.d8.loss_mask: 0.5965, decode.d8.loss_dice: 0.7850, loss: 21.7088 +2022-05-06 02:59:17,290 - mmseg - INFO - Iter [9600/40000] lr: 1.091e-06, eta: 9:25:15, time: 0.674, data_time: 0.010, memory: 53770, decode.loss_cls: 0.3704, decode.loss_mask: 0.5869, decode.loss_dice: 0.8069, decode.d0.loss_cls: 4.1994, decode.d0.loss_mask: 0.6067, decode.d0.loss_dice: 0.9649, decode.d1.loss_cls: 0.5005, decode.d1.loss_mask: 0.5968, decode.d1.loss_dice: 0.8577, decode.d2.loss_cls: 0.4087, decode.d2.loss_mask: 0.5890, decode.d2.loss_dice: 0.8236, decode.d3.loss_cls: 0.3728, decode.d3.loss_mask: 0.5859, decode.d3.loss_dice: 0.8216, decode.d4.loss_cls: 0.3791, decode.d4.loss_mask: 0.5812, decode.d4.loss_dice: 0.8153, decode.d5.loss_cls: 0.3677, decode.d5.loss_mask: 0.5832, decode.d5.loss_dice: 0.8109, decode.d6.loss_cls: 0.3661, decode.d6.loss_mask: 0.5817, decode.d6.loss_dice: 0.8063, decode.d7.loss_cls: 0.3628, decode.d7.loss_mask: 0.5845, decode.d7.loss_dice: 0.8037, decode.d8.loss_cls: 0.3650, decode.d8.loss_mask: 0.5832, decode.d8.loss_dice: 0.8083, loss: 21.8905 +2022-05-06 02:59:53,952 - mmseg - INFO - Iter [9650/40000] lr: 1.089e-06, eta: 9:22:37, time: 0.733, data_time: 0.059, memory: 53770, decode.loss_cls: 0.3428, decode.loss_mask: 0.5715, decode.loss_dice: 0.8001, decode.d0.loss_cls: 4.1637, decode.d0.loss_mask: 0.6035, decode.d0.loss_dice: 0.9489, decode.d1.loss_cls: 0.4582, decode.d1.loss_mask: 0.5998, decode.d1.loss_dice: 0.8586, decode.d2.loss_cls: 0.3898, decode.d2.loss_mask: 0.5821, decode.d2.loss_dice: 0.8213, decode.d3.loss_cls: 0.3607, decode.d3.loss_mask: 0.5746, decode.d3.loss_dice: 0.8049, decode.d4.loss_cls: 0.3537, decode.d4.loss_mask: 0.5720, decode.d4.loss_dice: 0.8061, decode.d5.loss_cls: 0.3464, decode.d5.loss_mask: 0.5738, decode.d5.loss_dice: 0.8045, decode.d6.loss_cls: 0.3410, decode.d6.loss_mask: 0.5729, decode.d6.loss_dice: 0.7997, decode.d7.loss_cls: 0.3435, decode.d7.loss_mask: 0.5690, decode.d7.loss_dice: 0.8044, decode.d8.loss_cls: 0.3475, decode.d8.loss_mask: 0.5706, decode.d8.loss_dice: 0.8035, loss: 21.4892 +2022-05-06 03:00:27,755 - mmseg - INFO - Iter [9700/40000] lr: 1.088e-06, eta: 9:19:45, time: 0.676, data_time: 0.008, memory: 53770, decode.loss_cls: 0.3294, decode.loss_mask: 0.5645, decode.loss_dice: 0.7535, decode.d0.loss_cls: 4.1219, decode.d0.loss_mask: 0.5832, decode.d0.loss_dice: 0.8885, decode.d1.loss_cls: 0.4743, decode.d1.loss_mask: 0.5809, decode.d1.loss_dice: 0.8053, decode.d2.loss_cls: 0.3930, decode.d2.loss_mask: 0.5677, decode.d2.loss_dice: 0.7747, decode.d3.loss_cls: 0.3528, decode.d3.loss_mask: 0.5627, decode.d3.loss_dice: 0.7614, decode.d4.loss_cls: 0.3501, decode.d4.loss_mask: 0.5600, decode.d4.loss_dice: 0.7573, decode.d5.loss_cls: 0.3384, decode.d5.loss_mask: 0.5614, decode.d5.loss_dice: 0.7626, decode.d6.loss_cls: 0.3348, decode.d6.loss_mask: 0.5603, decode.d6.loss_dice: 0.7553, decode.d7.loss_cls: 0.3374, decode.d7.loss_mask: 0.5592, decode.d7.loss_dice: 0.7540, decode.d8.loss_cls: 0.3314, decode.d8.loss_mask: 0.5592, decode.d8.loss_dice: 0.7482, loss: 20.7834 +2022-05-06 03:01:01,498 - mmseg - INFO - Iter [9750/40000] lr: 1.086e-06, eta: 9:16:56, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3758, decode.loss_mask: 0.5615, decode.loss_dice: 0.7949, decode.d0.loss_cls: 4.1381, decode.d0.loss_mask: 0.5855, decode.d0.loss_dice: 0.9352, decode.d1.loss_cls: 0.5006, decode.d1.loss_mask: 0.5825, decode.d1.loss_dice: 0.8412, decode.d2.loss_cls: 0.4257, decode.d2.loss_mask: 0.5690, decode.d2.loss_dice: 0.8043, decode.d3.loss_cls: 0.3960, decode.d3.loss_mask: 0.5658, decode.d3.loss_dice: 0.7965, decode.d4.loss_cls: 0.3844, decode.d4.loss_mask: 0.5648, decode.d4.loss_dice: 0.7944, decode.d5.loss_cls: 0.3837, decode.d5.loss_mask: 0.5629, decode.d5.loss_dice: 0.7890, decode.d6.loss_cls: 0.3777, decode.d6.loss_mask: 0.5610, decode.d6.loss_dice: 0.7908, decode.d7.loss_cls: 0.3775, decode.d7.loss_mask: 0.5650, decode.d7.loss_dice: 0.7858, decode.d8.loss_cls: 0.3761, decode.d8.loss_mask: 0.5623, decode.d8.loss_dice: 0.7887, loss: 21.5369 +2022-05-06 03:01:35,198 - mmseg - INFO - Iter [9800/40000] lr: 1.084e-06, eta: 9:14:08, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3707, decode.loss_mask: 0.5835, decode.loss_dice: 0.7858, decode.d0.loss_cls: 4.1037, decode.d0.loss_mask: 0.5984, decode.d0.loss_dice: 0.9272, decode.d1.loss_cls: 0.4966, decode.d1.loss_mask: 0.6046, decode.d1.loss_dice: 0.8400, decode.d2.loss_cls: 0.4259, decode.d2.loss_mask: 0.5932, decode.d2.loss_dice: 0.8079, decode.d3.loss_cls: 0.3980, decode.d3.loss_mask: 0.5825, decode.d3.loss_dice: 0.7853, decode.d4.loss_cls: 0.3873, decode.d4.loss_mask: 0.5823, decode.d4.loss_dice: 0.7881, decode.d5.loss_cls: 0.3800, decode.d5.loss_mask: 0.5842, decode.d5.loss_dice: 0.7851, decode.d6.loss_cls: 0.3725, decode.d6.loss_mask: 0.5841, decode.d6.loss_dice: 0.7832, decode.d7.loss_cls: 0.3713, decode.d7.loss_mask: 0.5860, decode.d7.loss_dice: 0.7852, decode.d8.loss_cls: 0.3768, decode.d8.loss_mask: 0.5796, decode.d8.loss_dice: 0.7810, loss: 21.6297 +2022-05-06 03:02:08,542 - mmseg - INFO - Iter [9850/40000] lr: 1.082e-06, eta: 9:11:21, time: 0.666, data_time: 0.008, memory: 53770, decode.loss_cls: 0.3466, decode.loss_mask: 0.5907, decode.loss_dice: 0.7972, decode.d0.loss_cls: 4.0936, decode.d0.loss_mask: 0.6186, decode.d0.loss_dice: 0.9253, decode.d1.loss_cls: 0.4760, decode.d1.loss_mask: 0.6134, decode.d1.loss_dice: 0.8408, decode.d2.loss_cls: 0.3924, decode.d2.loss_mask: 0.6000, decode.d2.loss_dice: 0.8100, decode.d3.loss_cls: 0.3627, decode.d3.loss_mask: 0.5973, decode.d3.loss_dice: 0.7992, decode.d4.loss_cls: 0.3533, decode.d4.loss_mask: 0.5985, decode.d4.loss_dice: 0.8007, decode.d5.loss_cls: 0.3559, decode.d5.loss_mask: 0.5934, decode.d5.loss_dice: 0.8015, decode.d6.loss_cls: 0.3432, decode.d6.loss_mask: 0.5938, decode.d6.loss_dice: 0.7969, decode.d7.loss_cls: 0.3367, decode.d7.loss_mask: 0.5942, decode.d7.loss_dice: 0.8017, decode.d8.loss_cls: 0.3465, decode.d8.loss_mask: 0.5946, decode.d8.loss_dice: 0.7977, loss: 21.5724 +2022-05-06 03:02:42,148 - mmseg - INFO - Iter [9900/40000] lr: 1.080e-06, eta: 9:08:38, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3550, decode.loss_mask: 0.5842, decode.loss_dice: 0.8049, decode.d0.loss_cls: 4.0289, decode.d0.loss_mask: 0.6108, decode.d0.loss_dice: 0.9505, decode.d1.loss_cls: 0.4704, decode.d1.loss_mask: 0.6072, decode.d1.loss_dice: 0.8585, decode.d2.loss_cls: 0.3887, decode.d2.loss_mask: 0.5945, decode.d2.loss_dice: 0.8294, decode.d3.loss_cls: 0.3713, decode.d3.loss_mask: 0.5887, decode.d3.loss_dice: 0.8129, decode.d4.loss_cls: 0.3703, decode.d4.loss_mask: 0.5876, decode.d4.loss_dice: 0.8116, decode.d5.loss_cls: 0.3581, decode.d5.loss_mask: 0.5872, decode.d5.loss_dice: 0.8071, decode.d6.loss_cls: 0.3452, decode.d6.loss_mask: 0.5858, decode.d6.loss_dice: 0.8033, decode.d7.loss_cls: 0.3521, decode.d7.loss_mask: 0.5880, decode.d7.loss_dice: 0.8010, decode.d8.loss_cls: 0.3565, decode.d8.loss_mask: 0.5845, decode.d8.loss_dice: 0.8066, loss: 21.6005 +2022-05-06 03:03:18,406 - mmseg - INFO - Iter [9950/40000] lr: 1.079e-06, eta: 9:06:10, time: 0.724, data_time: 0.058, memory: 53770, decode.loss_cls: 0.3322, decode.loss_mask: 0.5812, decode.loss_dice: 0.7827, decode.d0.loss_cls: 3.9976, decode.d0.loss_mask: 0.6066, decode.d0.loss_dice: 0.9210, decode.d1.loss_cls: 0.4515, decode.d1.loss_mask: 0.6010, decode.d1.loss_dice: 0.8366, decode.d2.loss_cls: 0.3720, decode.d2.loss_mask: 0.5876, decode.d2.loss_dice: 0.8090, decode.d3.loss_cls: 0.3532, decode.d3.loss_mask: 0.5833, decode.d3.loss_dice: 0.7889, decode.d4.loss_cls: 0.3430, decode.d4.loss_mask: 0.5802, decode.d4.loss_dice: 0.7906, decode.d5.loss_cls: 0.3356, decode.d5.loss_mask: 0.5803, decode.d5.loss_dice: 0.7833, decode.d6.loss_cls: 0.3303, decode.d6.loss_mask: 0.5774, decode.d6.loss_dice: 0.7908, decode.d7.loss_cls: 0.3316, decode.d7.loss_mask: 0.5766, decode.d7.loss_dice: 0.7867, decode.d8.loss_cls: 0.3275, decode.d8.loss_mask: 0.5829, decode.d8.loss_dice: 0.7849, loss: 21.1060 +2022-05-06 03:03:52,136 - mmseg - INFO - Saving checkpoint at 10000 iterations +2022-05-06 03:04:18,876 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 03:04:18,883 - mmseg - INFO - Iter [10000/40000] lr: 1.077e-06, eta: 9:05:45, time: 1.208, data_time: 0.010, memory: 53770, decode.loss_cls: 0.3513, decode.loss_mask: 0.5671, decode.loss_dice: 0.7766, decode.d0.loss_cls: 3.9810, decode.d0.loss_mask: 0.5965, decode.d0.loss_dice: 0.9246, decode.d1.loss_cls: 0.4737, decode.d1.loss_mask: 0.5887, decode.d1.loss_dice: 0.8387, decode.d2.loss_cls: 0.3953, decode.d2.loss_mask: 0.5795, decode.d2.loss_dice: 0.7965, decode.d3.loss_cls: 0.3677, decode.d3.loss_mask: 0.5753, decode.d3.loss_dice: 0.7887, decode.d4.loss_cls: 0.3598, decode.d4.loss_mask: 0.5726, decode.d4.loss_dice: 0.7786, decode.d5.loss_cls: 0.3499, decode.d5.loss_mask: 0.5748, decode.d5.loss_dice: 0.7808, decode.d6.loss_cls: 0.3494, decode.d6.loss_mask: 0.5713, decode.d6.loss_dice: 0.7744, decode.d7.loss_cls: 0.3463, decode.d7.loss_mask: 0.5706, decode.d7.loss_dice: 0.7758, decode.d8.loss_cls: 0.3458, decode.d8.loss_mask: 0.5714, decode.d8.loss_dice: 0.7791, loss: 21.1020 +2022-05-06 03:04:53,513 - mmseg - INFO - Iter [10050/40000] lr: 1.075e-06, eta: 9:03:12, time: 0.695, data_time: 0.011, memory: 53770, decode.loss_cls: 0.3453, decode.loss_mask: 0.5597, decode.loss_dice: 0.7494, decode.d0.loss_cls: 3.9780, decode.d0.loss_mask: 0.5881, decode.d0.loss_dice: 0.8961, decode.d1.loss_cls: 0.4754, decode.d1.loss_mask: 0.5861, decode.d1.loss_dice: 0.8022, decode.d2.loss_cls: 0.3831, decode.d2.loss_mask: 0.5736, decode.d2.loss_dice: 0.7732, decode.d3.loss_cls: 0.3637, decode.d3.loss_mask: 0.5717, decode.d3.loss_dice: 0.7575, decode.d4.loss_cls: 0.3502, decode.d4.loss_mask: 0.5674, decode.d4.loss_dice: 0.7582, decode.d5.loss_cls: 0.3589, decode.d5.loss_mask: 0.5630, decode.d5.loss_dice: 0.7516, decode.d6.loss_cls: 0.3435, decode.d6.loss_mask: 0.5623, decode.d6.loss_dice: 0.7514, decode.d7.loss_cls: 0.3431, decode.d7.loss_mask: 0.5654, decode.d7.loss_dice: 0.7550, decode.d8.loss_cls: 0.3497, decode.d8.loss_mask: 0.5645, decode.d8.loss_dice: 0.7515, loss: 20.7390 +2022-05-06 03:05:27,664 - mmseg - INFO - Iter [10100/40000] lr: 1.073e-06, eta: 9:00:39, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3409, decode.loss_mask: 0.5842, decode.loss_dice: 0.7865, decode.d0.loss_cls: 3.9612, decode.d0.loss_mask: 0.6025, decode.d0.loss_dice: 0.9222, decode.d1.loss_cls: 0.4757, decode.d1.loss_mask: 0.5994, decode.d1.loss_dice: 0.8247, decode.d2.loss_cls: 0.4005, decode.d2.loss_mask: 0.5857, decode.d2.loss_dice: 0.8016, decode.d3.loss_cls: 0.3722, decode.d3.loss_mask: 0.5860, decode.d3.loss_dice: 0.7875, decode.d4.loss_cls: 0.3536, decode.d4.loss_mask: 0.5857, decode.d4.loss_dice: 0.7918, decode.d5.loss_cls: 0.3487, decode.d5.loss_mask: 0.5830, decode.d5.loss_dice: 0.7857, decode.d6.loss_cls: 0.3370, decode.d6.loss_mask: 0.5819, decode.d6.loss_dice: 0.7813, decode.d7.loss_cls: 0.3425, decode.d7.loss_mask: 0.5845, decode.d7.loss_dice: 0.7876, decode.d8.loss_cls: 0.3351, decode.d8.loss_mask: 0.5855, decode.d8.loss_dice: 0.7854, loss: 21.2004 +2022-05-06 03:06:01,491 - mmseg - INFO - Iter [10150/40000] lr: 1.071e-06, eta: 8:58:05, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3879, decode.loss_mask: 0.6056, decode.loss_dice: 0.8331, decode.d0.loss_cls: 3.9676, decode.d0.loss_mask: 0.6340, decode.d0.loss_dice: 0.9687, decode.d1.loss_cls: 0.5134, decode.d1.loss_mask: 0.6262, decode.d1.loss_dice: 0.8838, decode.d2.loss_cls: 0.4216, decode.d2.loss_mask: 0.6121, decode.d2.loss_dice: 0.8512, decode.d3.loss_cls: 0.4066, decode.d3.loss_mask: 0.6041, decode.d3.loss_dice: 0.8266, decode.d4.loss_cls: 0.3936, decode.d4.loss_mask: 0.6058, decode.d4.loss_dice: 0.8369, decode.d5.loss_cls: 0.3837, decode.d5.loss_mask: 0.6053, decode.d5.loss_dice: 0.8312, decode.d6.loss_cls: 0.3861, decode.d6.loss_mask: 0.6059, decode.d6.loss_dice: 0.8289, decode.d7.loss_cls: 0.3845, decode.d7.loss_mask: 0.6033, decode.d7.loss_dice: 0.8255, decode.d8.loss_cls: 0.3841, decode.d8.loss_mask: 0.6069, decode.d8.loss_dice: 0.8331, loss: 22.2572 +2022-05-06 03:06:34,837 - mmseg - INFO - Iter [10200/40000] lr: 1.070e-06, eta: 8:55:31, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3350, decode.loss_mask: 0.5870, decode.loss_dice: 0.7712, decode.d0.loss_cls: 3.8950, decode.d0.loss_mask: 0.6030, decode.d0.loss_dice: 0.9150, decode.d1.loss_cls: 0.4542, decode.d1.loss_mask: 0.5967, decode.d1.loss_dice: 0.8211, decode.d2.loss_cls: 0.3794, decode.d2.loss_mask: 0.5890, decode.d2.loss_dice: 0.7916, decode.d3.loss_cls: 0.3431, decode.d3.loss_mask: 0.5849, decode.d3.loss_dice: 0.7719, decode.d4.loss_cls: 0.3403, decode.d4.loss_mask: 0.5814, decode.d4.loss_dice: 0.7739, decode.d5.loss_cls: 0.3311, decode.d5.loss_mask: 0.5829, decode.d5.loss_dice: 0.7759, decode.d6.loss_cls: 0.3282, decode.d6.loss_mask: 0.5826, decode.d6.loss_dice: 0.7698, decode.d7.loss_cls: 0.3289, decode.d7.loss_mask: 0.5855, decode.d7.loss_dice: 0.7682, decode.d8.loss_cls: 0.3328, decode.d8.loss_mask: 0.5826, decode.d8.loss_dice: 0.7736, loss: 20.8757 +2022-05-06 03:07:10,840 - mmseg - INFO - Iter [10250/40000] lr: 1.068e-06, eta: 8:53:12, time: 0.720, data_time: 0.062, memory: 53770, decode.loss_cls: 0.3691, decode.loss_mask: 0.5669, decode.loss_dice: 0.7726, decode.d0.loss_cls: 3.8865, decode.d0.loss_mask: 0.5930, decode.d0.loss_dice: 0.9184, decode.d1.loss_cls: 0.4893, decode.d1.loss_mask: 0.5871, decode.d1.loss_dice: 0.8260, decode.d2.loss_cls: 0.4107, decode.d2.loss_mask: 0.5744, decode.d2.loss_dice: 0.7865, decode.d3.loss_cls: 0.3723, decode.d3.loss_mask: 0.5693, decode.d3.loss_dice: 0.7767, decode.d4.loss_cls: 0.3695, decode.d4.loss_mask: 0.5646, decode.d4.loss_dice: 0.7757, decode.d5.loss_cls: 0.3685, decode.d5.loss_mask: 0.5653, decode.d5.loss_dice: 0.7680, decode.d6.loss_cls: 0.3576, decode.d6.loss_mask: 0.5612, decode.d6.loss_dice: 0.7643, decode.d7.loss_cls: 0.3525, decode.d7.loss_mask: 0.5664, decode.d7.loss_dice: 0.7675, decode.d8.loss_cls: 0.3622, decode.d8.loss_mask: 0.5678, decode.d8.loss_dice: 0.7718, loss: 20.9815 +2022-05-06 03:07:44,509 - mmseg - INFO - Iter [10300/40000] lr: 1.066e-06, eta: 8:50:44, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3363, decode.loss_mask: 0.5636, decode.loss_dice: 0.7709, decode.d0.loss_cls: 3.8821, decode.d0.loss_mask: 0.5925, decode.d0.loss_dice: 0.9227, decode.d1.loss_cls: 0.4474, decode.d1.loss_mask: 0.5782, decode.d1.loss_dice: 0.8236, decode.d2.loss_cls: 0.3785, decode.d2.loss_mask: 0.5658, decode.d2.loss_dice: 0.7918, decode.d3.loss_cls: 0.3553, decode.d3.loss_mask: 0.5626, decode.d3.loss_dice: 0.7818, decode.d4.loss_cls: 0.3504, decode.d4.loss_mask: 0.5615, decode.d4.loss_dice: 0.7775, decode.d5.loss_cls: 0.3448, decode.d5.loss_mask: 0.5593, decode.d5.loss_dice: 0.7742, decode.d6.loss_cls: 0.3402, decode.d6.loss_mask: 0.5594, decode.d6.loss_dice: 0.7744, decode.d7.loss_cls: 0.3381, decode.d7.loss_mask: 0.5575, decode.d7.loss_dice: 0.7718, decode.d8.loss_cls: 0.3362, decode.d8.loss_mask: 0.5614, decode.d8.loss_dice: 0.7699, loss: 20.7296 +2022-05-06 03:08:18,173 - mmseg - INFO - Iter [10350/40000] lr: 1.064e-06, eta: 8:48:17, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3164, decode.loss_mask: 0.5663, decode.loss_dice: 0.7585, decode.d0.loss_cls: 3.8329, decode.d0.loss_mask: 0.5892, decode.d0.loss_dice: 0.8878, decode.d1.loss_cls: 0.4369, decode.d1.loss_mask: 0.5874, decode.d1.loss_dice: 0.8046, decode.d2.loss_cls: 0.3555, decode.d2.loss_mask: 0.5696, decode.d2.loss_dice: 0.7719, decode.d3.loss_cls: 0.3251, decode.d3.loss_mask: 0.5693, decode.d3.loss_dice: 0.7647, decode.d4.loss_cls: 0.3229, decode.d4.loss_mask: 0.5612, decode.d4.loss_dice: 0.7604, decode.d5.loss_cls: 0.3140, decode.d5.loss_mask: 0.5638, decode.d5.loss_dice: 0.7605, decode.d6.loss_cls: 0.3030, decode.d6.loss_mask: 0.5659, decode.d6.loss_dice: 0.7567, decode.d7.loss_cls: 0.3032, decode.d7.loss_mask: 0.5621, decode.d7.loss_dice: 0.7557, decode.d8.loss_cls: 0.3103, decode.d8.loss_mask: 0.5671, decode.d8.loss_dice: 0.7554, loss: 20.2984 +2022-05-06 03:08:52,156 - mmseg - INFO - Iter [10400/40000] lr: 1.063e-06, eta: 8:45:54, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3478, decode.loss_mask: 0.5647, decode.loss_dice: 0.7814, decode.d0.loss_cls: 3.8464, decode.d0.loss_mask: 0.5932, decode.d0.loss_dice: 0.9345, decode.d1.loss_cls: 0.4796, decode.d1.loss_mask: 0.5895, decode.d1.loss_dice: 0.8350, decode.d2.loss_cls: 0.3941, decode.d2.loss_mask: 0.5736, decode.d2.loss_dice: 0.7936, decode.d3.loss_cls: 0.3688, decode.d3.loss_mask: 0.5660, decode.d3.loss_dice: 0.7813, decode.d4.loss_cls: 0.3571, decode.d4.loss_mask: 0.5669, decode.d4.loss_dice: 0.7785, decode.d5.loss_cls: 0.3461, decode.d5.loss_mask: 0.5669, decode.d5.loss_dice: 0.7805, decode.d6.loss_cls: 0.3446, decode.d6.loss_mask: 0.5628, decode.d6.loss_dice: 0.7802, decode.d7.loss_cls: 0.3442, decode.d7.loss_mask: 0.5668, decode.d7.loss_dice: 0.7788, decode.d8.loss_cls: 0.3429, decode.d8.loss_mask: 0.5679, decode.d8.loss_dice: 0.7813, loss: 20.9150 +2022-05-06 03:09:26,613 - mmseg - INFO - Iter [10450/40000] lr: 1.061e-06, eta: 8:43:34, time: 0.689, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3563, decode.loss_mask: 0.5500, decode.loss_dice: 0.7730, decode.d0.loss_cls: 3.7904, decode.d0.loss_mask: 0.5847, decode.d0.loss_dice: 0.9132, decode.d1.loss_cls: 0.4754, decode.d1.loss_mask: 0.5775, decode.d1.loss_dice: 0.8270, decode.d2.loss_cls: 0.3974, decode.d2.loss_mask: 0.5604, decode.d2.loss_dice: 0.7912, decode.d3.loss_cls: 0.3819, decode.d3.loss_mask: 0.5534, decode.d3.loss_dice: 0.7743, decode.d4.loss_cls: 0.3636, decode.d4.loss_mask: 0.5547, decode.d4.loss_dice: 0.7732, decode.d5.loss_cls: 0.3571, decode.d5.loss_mask: 0.5518, decode.d5.loss_dice: 0.7680, decode.d6.loss_cls: 0.3506, decode.d6.loss_mask: 0.5487, decode.d6.loss_dice: 0.7686, decode.d7.loss_cls: 0.3510, decode.d7.loss_mask: 0.5491, decode.d7.loss_dice: 0.7698, decode.d8.loss_cls: 0.3472, decode.d8.loss_mask: 0.5503, decode.d8.loss_dice: 0.7722, loss: 20.6821 +2022-05-06 03:10:00,458 - mmseg - INFO - Iter [10500/40000] lr: 1.059e-06, eta: 8:41:13, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3356, decode.loss_mask: 0.5508, decode.loss_dice: 0.7611, decode.d0.loss_cls: 3.7621, decode.d0.loss_mask: 0.5740, decode.d0.loss_dice: 0.8838, decode.d1.loss_cls: 0.4570, decode.d1.loss_mask: 0.5703, decode.d1.loss_dice: 0.8065, decode.d2.loss_cls: 0.3810, decode.d2.loss_mask: 0.5601, decode.d2.loss_dice: 0.7709, decode.d3.loss_cls: 0.3616, decode.d3.loss_mask: 0.5537, decode.d3.loss_dice: 0.7514, decode.d4.loss_cls: 0.3493, decode.d4.loss_mask: 0.5516, decode.d4.loss_dice: 0.7564, decode.d5.loss_cls: 0.3424, decode.d5.loss_mask: 0.5540, decode.d5.loss_dice: 0.7570, decode.d6.loss_cls: 0.3347, decode.d6.loss_mask: 0.5558, decode.d6.loss_dice: 0.7564, decode.d7.loss_cls: 0.3388, decode.d7.loss_mask: 0.5571, decode.d7.loss_dice: 0.7594, decode.d8.loss_cls: 0.3388, decode.d8.loss_mask: 0.5545, decode.d8.loss_dice: 0.7571, loss: 20.3431 +2022-05-06 03:10:34,102 - mmseg - INFO - Iter [10550/40000] lr: 1.057e-06, eta: 8:38:53, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3397, decode.loss_mask: 0.5924, decode.loss_dice: 0.8029, decode.d0.loss_cls: 3.7693, decode.d0.loss_mask: 0.6142, decode.d0.loss_dice: 0.9374, decode.d1.loss_cls: 0.4848, decode.d1.loss_mask: 0.6077, decode.d1.loss_dice: 0.8504, decode.d2.loss_cls: 0.3828, decode.d2.loss_mask: 0.5963, decode.d2.loss_dice: 0.8196, decode.d3.loss_cls: 0.3580, decode.d3.loss_mask: 0.5896, decode.d3.loss_dice: 0.8020, decode.d4.loss_cls: 0.3528, decode.d4.loss_mask: 0.5852, decode.d4.loss_dice: 0.8027, decode.d5.loss_cls: 0.3389, decode.d5.loss_mask: 0.5840, decode.d5.loss_dice: 0.7997, decode.d6.loss_cls: 0.3332, decode.d6.loss_mask: 0.5880, decode.d6.loss_dice: 0.8009, decode.d7.loss_cls: 0.3304, decode.d7.loss_mask: 0.5882, decode.d7.loss_dice: 0.7981, decode.d8.loss_cls: 0.3353, decode.d8.loss_mask: 0.5940, decode.d8.loss_dice: 0.8002, loss: 21.1789 +2022-05-06 03:11:10,774 - mmseg - INFO - Iter [10600/40000] lr: 1.055e-06, eta: 8:36:48, time: 0.734, data_time: 0.063, memory: 53770, decode.loss_cls: 0.3286, decode.loss_mask: 0.5605, decode.loss_dice: 0.7823, decode.d0.loss_cls: 3.7263, decode.d0.loss_mask: 0.5904, decode.d0.loss_dice: 0.9241, decode.d1.loss_cls: 0.4563, decode.d1.loss_mask: 0.5789, decode.d1.loss_dice: 0.8351, decode.d2.loss_cls: 0.3785, decode.d2.loss_mask: 0.5631, decode.d2.loss_dice: 0.7991, decode.d3.loss_cls: 0.3495, decode.d3.loss_mask: 0.5629, decode.d3.loss_dice: 0.7836, decode.d4.loss_cls: 0.3422, decode.d4.loss_mask: 0.5654, decode.d4.loss_dice: 0.7819, decode.d5.loss_cls: 0.3309, decode.d5.loss_mask: 0.5636, decode.d5.loss_dice: 0.7874, decode.d6.loss_cls: 0.3187, decode.d6.loss_mask: 0.5619, decode.d6.loss_dice: 0.7835, decode.d7.loss_cls: 0.3233, decode.d7.loss_mask: 0.5641, decode.d7.loss_dice: 0.7837, decode.d8.loss_cls: 0.3217, decode.d8.loss_mask: 0.5642, decode.d8.loss_dice: 0.7843, loss: 20.5957 +2022-05-06 03:11:44,352 - mmseg - INFO - Iter [10650/40000] lr: 1.054e-06, eta: 8:34:31, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3345, decode.loss_mask: 0.5507, decode.loss_dice: 0.7710, decode.d0.loss_cls: 3.6972, decode.d0.loss_mask: 0.5864, decode.d0.loss_dice: 0.9276, decode.d1.loss_cls: 0.4725, decode.d1.loss_mask: 0.5707, decode.d1.loss_dice: 0.8260, decode.d2.loss_cls: 0.3775, decode.d2.loss_mask: 0.5582, decode.d2.loss_dice: 0.7931, decode.d3.loss_cls: 0.3517, decode.d3.loss_mask: 0.5573, decode.d3.loss_dice: 0.7754, decode.d4.loss_cls: 0.3485, decode.d4.loss_mask: 0.5539, decode.d4.loss_dice: 0.7787, decode.d5.loss_cls: 0.3395, decode.d5.loss_mask: 0.5495, decode.d5.loss_dice: 0.7719, decode.d6.loss_cls: 0.3352, decode.d6.loss_mask: 0.5482, decode.d6.loss_dice: 0.7726, decode.d7.loss_cls: 0.3349, decode.d7.loss_mask: 0.5479, decode.d7.loss_dice: 0.7762, decode.d8.loss_cls: 0.3347, decode.d8.loss_mask: 0.5524, decode.d8.loss_dice: 0.7752, loss: 20.4694 +2022-05-06 03:12:18,204 - mmseg - INFO - Iter [10700/40000] lr: 1.052e-06, eta: 8:32:16, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3212, decode.loss_mask: 0.5642, decode.loss_dice: 0.7555, decode.d0.loss_cls: 3.6754, decode.d0.loss_mask: 0.5932, decode.d0.loss_dice: 0.8966, decode.d1.loss_cls: 0.4531, decode.d1.loss_mask: 0.5851, decode.d1.loss_dice: 0.8183, decode.d2.loss_cls: 0.3716, decode.d2.loss_mask: 0.5667, decode.d2.loss_dice: 0.7758, decode.d3.loss_cls: 0.3391, decode.d3.loss_mask: 0.5668, decode.d3.loss_dice: 0.7683, decode.d4.loss_cls: 0.3253, decode.d4.loss_mask: 0.5691, decode.d4.loss_dice: 0.7661, decode.d5.loss_cls: 0.3263, decode.d5.loss_mask: 0.5672, decode.d5.loss_dice: 0.7680, decode.d6.loss_cls: 0.3145, decode.d6.loss_mask: 0.5694, decode.d6.loss_dice: 0.7653, decode.d7.loss_cls: 0.3128, decode.d7.loss_mask: 0.5637, decode.d7.loss_dice: 0.7639, decode.d8.loss_cls: 0.3129, decode.d8.loss_mask: 0.5662, decode.d8.loss_dice: 0.7616, loss: 20.3036 +2022-05-06 03:12:52,142 - mmseg - INFO - Iter [10750/40000] lr: 1.050e-06, eta: 8:30:04, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3335, decode.loss_mask: 0.5717, decode.loss_dice: 0.7554, decode.d0.loss_cls: 3.6642, decode.d0.loss_mask: 0.6001, decode.d0.loss_dice: 0.9021, decode.d1.loss_cls: 0.4536, decode.d1.loss_mask: 0.5866, decode.d1.loss_dice: 0.8132, decode.d2.loss_cls: 0.3772, decode.d2.loss_mask: 0.5733, decode.d2.loss_dice: 0.7710, decode.d3.loss_cls: 0.3450, decode.d3.loss_mask: 0.5724, decode.d3.loss_dice: 0.7587, decode.d4.loss_cls: 0.3333, decode.d4.loss_mask: 0.5693, decode.d4.loss_dice: 0.7627, decode.d5.loss_cls: 0.3376, decode.d5.loss_mask: 0.5695, decode.d5.loss_dice: 0.7624, decode.d6.loss_cls: 0.3258, decode.d6.loss_mask: 0.5679, decode.d6.loss_dice: 0.7617, decode.d7.loss_cls: 0.3293, decode.d7.loss_mask: 0.5671, decode.d7.loss_dice: 0.7568, decode.d8.loss_cls: 0.3310, decode.d8.loss_mask: 0.5701, decode.d8.loss_dice: 0.7573, loss: 20.3794 +2022-05-06 03:13:26,004 - mmseg - INFO - Iter [10800/40000] lr: 1.048e-06, eta: 8:27:52, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3125, decode.loss_mask: 0.5495, decode.loss_dice: 0.7524, decode.d0.loss_cls: 3.6420, decode.d0.loss_mask: 0.5789, decode.d0.loss_dice: 0.8815, decode.d1.loss_cls: 0.4398, decode.d1.loss_mask: 0.5693, decode.d1.loss_dice: 0.7936, decode.d2.loss_cls: 0.3513, decode.d2.loss_mask: 0.5542, decode.d2.loss_dice: 0.7679, decode.d3.loss_cls: 0.3216, decode.d3.loss_mask: 0.5513, decode.d3.loss_dice: 0.7554, decode.d4.loss_cls: 0.3172, decode.d4.loss_mask: 0.5479, decode.d4.loss_dice: 0.7574, decode.d5.loss_cls: 0.3111, decode.d5.loss_mask: 0.5499, decode.d5.loss_dice: 0.7552, decode.d6.loss_cls: 0.3066, decode.d6.loss_mask: 0.5514, decode.d6.loss_dice: 0.7450, decode.d7.loss_cls: 0.3076, decode.d7.loss_mask: 0.5469, decode.d7.loss_dice: 0.7498, decode.d8.loss_cls: 0.3082, decode.d8.loss_mask: 0.5497, decode.d8.loss_dice: 0.7557, loss: 19.8806 +2022-05-06 03:13:59,628 - mmseg - INFO - Iter [10850/40000] lr: 1.046e-06, eta: 8:25:41, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3562, decode.loss_mask: 0.5635, decode.loss_dice: 0.7763, decode.d0.loss_cls: 3.6615, decode.d0.loss_mask: 0.5921, decode.d0.loss_dice: 0.9179, decode.d1.loss_cls: 0.4879, decode.d1.loss_mask: 0.5808, decode.d1.loss_dice: 0.8309, decode.d2.loss_cls: 0.4052, decode.d2.loss_mask: 0.5708, decode.d2.loss_dice: 0.8022, decode.d3.loss_cls: 0.3744, decode.d3.loss_mask: 0.5614, decode.d3.loss_dice: 0.7835, decode.d4.loss_cls: 0.3649, decode.d4.loss_mask: 0.5620, decode.d4.loss_dice: 0.7822, decode.d5.loss_cls: 0.3558, decode.d5.loss_mask: 0.5627, decode.d5.loss_dice: 0.7825, decode.d6.loss_cls: 0.3552, decode.d6.loss_mask: 0.5624, decode.d6.loss_dice: 0.7765, decode.d7.loss_cls: 0.3582, decode.d7.loss_mask: 0.5640, decode.d7.loss_dice: 0.7736, decode.d8.loss_cls: 0.3578, decode.d8.loss_mask: 0.5635, decode.d8.loss_dice: 0.7738, loss: 20.7596 +2022-05-06 03:14:36,256 - mmseg - INFO - Iter [10900/40000] lr: 1.045e-06, eta: 8:23:44, time: 0.733, data_time: 0.061, memory: 53770, decode.loss_cls: 0.3174, decode.loss_mask: 0.5427, decode.loss_dice: 0.7271, decode.d0.loss_cls: 3.5630, decode.d0.loss_mask: 0.5755, decode.d0.loss_dice: 0.8695, decode.d1.loss_cls: 0.4404, decode.d1.loss_mask: 0.5624, decode.d1.loss_dice: 0.7818, decode.d2.loss_cls: 0.3613, decode.d2.loss_mask: 0.5531, decode.d2.loss_dice: 0.7523, decode.d3.loss_cls: 0.3336, decode.d3.loss_mask: 0.5474, decode.d3.loss_dice: 0.7322, decode.d4.loss_cls: 0.3204, decode.d4.loss_mask: 0.5477, decode.d4.loss_dice: 0.7354, decode.d5.loss_cls: 0.3187, decode.d5.loss_mask: 0.5444, decode.d5.loss_dice: 0.7308, decode.d6.loss_cls: 0.3120, decode.d6.loss_mask: 0.5398, decode.d6.loss_dice: 0.7288, decode.d7.loss_cls: 0.3106, decode.d7.loss_mask: 0.5408, decode.d7.loss_dice: 0.7301, decode.d8.loss_cls: 0.3201, decode.d8.loss_mask: 0.5388, decode.d8.loss_dice: 0.7334, loss: 19.6116 +2022-05-06 03:15:10,128 - mmseg - INFO - Iter [10950/40000] lr: 1.043e-06, eta: 8:21:36, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3093, decode.loss_mask: 0.5505, decode.loss_dice: 0.7630, decode.d0.loss_cls: 3.5879, decode.d0.loss_mask: 0.5726, decode.d0.loss_dice: 0.9088, decode.d1.loss_cls: 0.4520, decode.d1.loss_mask: 0.5664, decode.d1.loss_dice: 0.8204, decode.d2.loss_cls: 0.3596, decode.d2.loss_mask: 0.5537, decode.d2.loss_dice: 0.7803, decode.d3.loss_cls: 0.3271, decode.d3.loss_mask: 0.5522, decode.d3.loss_dice: 0.7711, decode.d4.loss_cls: 0.3226, decode.d4.loss_mask: 0.5510, decode.d4.loss_dice: 0.7733, decode.d5.loss_cls: 0.3141, decode.d5.loss_mask: 0.5502, decode.d5.loss_dice: 0.7668, decode.d6.loss_cls: 0.3123, decode.d6.loss_mask: 0.5490, decode.d6.loss_dice: 0.7590, decode.d7.loss_cls: 0.3094, decode.d7.loss_mask: 0.5484, decode.d7.loss_dice: 0.7635, decode.d8.loss_cls: 0.3108, decode.d8.loss_mask: 0.5512, decode.d8.loss_dice: 0.7625, loss: 20.0190 +2022-05-06 03:15:43,669 - mmseg - INFO - Saving checkpoint at 11000 iterations +2022-05-06 03:16:08,525 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 03:16:08,533 - mmseg - INFO - Iter [11000/40000] lr: 1.041e-06, eta: 8:21:12, time: 1.167, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3225, decode.loss_mask: 0.5838, decode.loss_dice: 0.7722, decode.d0.loss_cls: 3.5638, decode.d0.loss_mask: 0.6091, decode.d0.loss_dice: 0.9170, decode.d1.loss_cls: 0.4517, decode.d1.loss_mask: 0.5980, decode.d1.loss_dice: 0.8334, decode.d2.loss_cls: 0.3705, decode.d2.loss_mask: 0.5884, decode.d2.loss_dice: 0.7931, decode.d3.loss_cls: 0.3423, decode.d3.loss_mask: 0.5823, decode.d3.loss_dice: 0.7775, decode.d4.loss_cls: 0.3393, decode.d4.loss_mask: 0.5767, decode.d4.loss_dice: 0.7809, decode.d5.loss_cls: 0.3229, decode.d5.loss_mask: 0.5810, decode.d5.loss_dice: 0.7844, decode.d6.loss_cls: 0.3140, decode.d6.loss_mask: 0.5811, decode.d6.loss_dice: 0.7793, decode.d7.loss_cls: 0.3162, decode.d7.loss_mask: 0.5783, decode.d7.loss_dice: 0.7767, decode.d8.loss_cls: 0.3244, decode.d8.loss_mask: 0.5793, decode.d8.loss_dice: 0.7764, loss: 20.5162 +2022-05-06 03:16:42,805 - mmseg - INFO - Iter [11050/40000] lr: 1.039e-06, eta: 8:19:08, time: 0.687, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3165, decode.loss_mask: 0.5471, decode.loss_dice: 0.7581, decode.d0.loss_cls: 3.5399, decode.d0.loss_mask: 0.5709, decode.d0.loss_dice: 0.8866, decode.d1.loss_cls: 0.4391, decode.d1.loss_mask: 0.5650, decode.d1.loss_dice: 0.8095, decode.d2.loss_cls: 0.3642, decode.d2.loss_mask: 0.5528, decode.d2.loss_dice: 0.7705, decode.d3.loss_cls: 0.3431, decode.d3.loss_mask: 0.5466, decode.d3.loss_dice: 0.7597, decode.d4.loss_cls: 0.3366, decode.d4.loss_mask: 0.5442, decode.d4.loss_dice: 0.7537, decode.d5.loss_cls: 0.3302, decode.d5.loss_mask: 0.5444, decode.d5.loss_dice: 0.7528, decode.d6.loss_cls: 0.3206, decode.d6.loss_mask: 0.5433, decode.d6.loss_dice: 0.7494, decode.d7.loss_cls: 0.3170, decode.d7.loss_mask: 0.5489, decode.d7.loss_dice: 0.7556, decode.d8.loss_cls: 0.3187, decode.d8.loss_mask: 0.5477, decode.d8.loss_dice: 0.7615, loss: 19.8944 +2022-05-06 03:17:16,169 - mmseg - INFO - Iter [11100/40000] lr: 1.037e-06, eta: 8:17:02, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3306, decode.loss_mask: 0.5716, decode.loss_dice: 0.7498, decode.d0.loss_cls: 3.5266, decode.d0.loss_mask: 0.6033, decode.d0.loss_dice: 0.8913, decode.d1.loss_cls: 0.4652, decode.d1.loss_mask: 0.5898, decode.d1.loss_dice: 0.7978, decode.d2.loss_cls: 0.3818, decode.d2.loss_mask: 0.5794, decode.d2.loss_dice: 0.7661, decode.d3.loss_cls: 0.3522, decode.d3.loss_mask: 0.5759, decode.d3.loss_dice: 0.7539, decode.d4.loss_cls: 0.3441, decode.d4.loss_mask: 0.5743, decode.d4.loss_dice: 0.7528, decode.d5.loss_cls: 0.3302, decode.d5.loss_mask: 0.5747, decode.d5.loss_dice: 0.7549, decode.d6.loss_cls: 0.3277, decode.d6.loss_mask: 0.5748, decode.d6.loss_dice: 0.7502, decode.d7.loss_cls: 0.3225, decode.d7.loss_mask: 0.5755, decode.d7.loss_dice: 0.7582, decode.d8.loss_cls: 0.3262, decode.d8.loss_mask: 0.5747, decode.d8.loss_dice: 0.7588, loss: 20.2346 +2022-05-06 03:17:50,148 - mmseg - INFO - Iter [11150/40000] lr: 1.036e-06, eta: 8:14:59, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3318, decode.loss_mask: 0.5679, decode.loss_dice: 0.7671, decode.d0.loss_cls: 3.5344, decode.d0.loss_mask: 0.5931, decode.d0.loss_dice: 0.9233, decode.d1.loss_cls: 0.4535, decode.d1.loss_mask: 0.5857, decode.d1.loss_dice: 0.8315, decode.d2.loss_cls: 0.3687, decode.d2.loss_mask: 0.5708, decode.d2.loss_dice: 0.7925, decode.d3.loss_cls: 0.3566, decode.d3.loss_mask: 0.5672, decode.d3.loss_dice: 0.7744, decode.d4.loss_cls: 0.3536, decode.d4.loss_mask: 0.5632, decode.d4.loss_dice: 0.7742, decode.d5.loss_cls: 0.3354, decode.d5.loss_mask: 0.5664, decode.d5.loss_dice: 0.7748, decode.d6.loss_cls: 0.3260, decode.d6.loss_mask: 0.5689, decode.d6.loss_dice: 0.7687, decode.d7.loss_cls: 0.3281, decode.d7.loss_mask: 0.5706, decode.d7.loss_dice: 0.7705, decode.d8.loss_cls: 0.3279, decode.d8.loss_mask: 0.5695, decode.d8.loss_dice: 0.7679, loss: 20.3845 +2022-05-06 03:18:26,158 - mmseg - INFO - Iter [11200/40000] lr: 1.034e-06, eta: 8:13:06, time: 0.721, data_time: 0.057, memory: 53770, decode.loss_cls: 0.2798, decode.loss_mask: 0.5404, decode.loss_dice: 0.7115, decode.d0.loss_cls: 3.4629, decode.d0.loss_mask: 0.5790, decode.d0.loss_dice: 0.8455, decode.d1.loss_cls: 0.3991, decode.d1.loss_mask: 0.5647, decode.d1.loss_dice: 0.7614, decode.d2.loss_cls: 0.3331, decode.d2.loss_mask: 0.5497, decode.d2.loss_dice: 0.7311, decode.d3.loss_cls: 0.2993, decode.d3.loss_mask: 0.5446, decode.d3.loss_dice: 0.7196, decode.d4.loss_cls: 0.2905, decode.d4.loss_mask: 0.5430, decode.d4.loss_dice: 0.7200, decode.d5.loss_cls: 0.2830, decode.d5.loss_mask: 0.5440, decode.d5.loss_dice: 0.7135, decode.d6.loss_cls: 0.2750, decode.d6.loss_mask: 0.5387, decode.d6.loss_dice: 0.7084, decode.d7.loss_cls: 0.2725, decode.d7.loss_mask: 0.5414, decode.d7.loss_dice: 0.7129, decode.d8.loss_cls: 0.2805, decode.d8.loss_mask: 0.5398, decode.d8.loss_dice: 0.7114, loss: 18.9961 +2022-05-06 03:18:59,509 - mmseg - INFO - Iter [11250/40000] lr: 1.032e-06, eta: 8:11:03, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3030, decode.loss_mask: 0.5338, decode.loss_dice: 0.7454, decode.d0.loss_cls: 3.4372, decode.d0.loss_mask: 0.5668, decode.d0.loss_dice: 0.8881, decode.d1.loss_cls: 0.4391, decode.d1.loss_mask: 0.5536, decode.d1.loss_dice: 0.8011, decode.d2.loss_cls: 0.3518, decode.d2.loss_mask: 0.5375, decode.d2.loss_dice: 0.7720, decode.d3.loss_cls: 0.3187, decode.d3.loss_mask: 0.5391, decode.d3.loss_dice: 0.7573, decode.d4.loss_cls: 0.3122, decode.d4.loss_mask: 0.5377, decode.d4.loss_dice: 0.7585, decode.d5.loss_cls: 0.3009, decode.d5.loss_mask: 0.5345, decode.d5.loss_dice: 0.7527, decode.d6.loss_cls: 0.2958, decode.d6.loss_mask: 0.5311, decode.d6.loss_dice: 0.7486, decode.d7.loss_cls: 0.2974, decode.d7.loss_mask: 0.5316, decode.d7.loss_dice: 0.7468, decode.d8.loss_cls: 0.3042, decode.d8.loss_mask: 0.5313, decode.d8.loss_dice: 0.7393, loss: 19.4673 +2022-05-06 03:19:33,662 - mmseg - INFO - Iter [11300/40000] lr: 1.030e-06, eta: 8:09:04, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2984, decode.loss_mask: 0.5441, decode.loss_dice: 0.7496, decode.d0.loss_cls: 3.4372, decode.d0.loss_mask: 0.5741, decode.d0.loss_dice: 0.8841, decode.d1.loss_cls: 0.4159, decode.d1.loss_mask: 0.5651, decode.d1.loss_dice: 0.8019, decode.d2.loss_cls: 0.3447, decode.d2.loss_mask: 0.5498, decode.d2.loss_dice: 0.7689, decode.d3.loss_cls: 0.3169, decode.d3.loss_mask: 0.5434, decode.d3.loss_dice: 0.7531, decode.d4.loss_cls: 0.3085, decode.d4.loss_mask: 0.5431, decode.d4.loss_dice: 0.7547, decode.d5.loss_cls: 0.3024, decode.d5.loss_mask: 0.5429, decode.d5.loss_dice: 0.7482, decode.d6.loss_cls: 0.2967, decode.d6.loss_mask: 0.5456, decode.d6.loss_dice: 0.7448, decode.d7.loss_cls: 0.2962, decode.d7.loss_mask: 0.5453, decode.d7.loss_dice: 0.7494, decode.d8.loss_cls: 0.2939, decode.d8.loss_mask: 0.5425, decode.d8.loss_dice: 0.7489, loss: 19.5104 +2022-05-06 03:20:07,362 - mmseg - INFO - Iter [11350/40000] lr: 1.028e-06, eta: 8:07:05, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2933, decode.loss_mask: 0.5449, decode.loss_dice: 0.7486, decode.d0.loss_cls: 3.4253, decode.d0.loss_mask: 0.5728, decode.d0.loss_dice: 0.8867, decode.d1.loss_cls: 0.4254, decode.d1.loss_mask: 0.5621, decode.d1.loss_dice: 0.7950, decode.d2.loss_cls: 0.3437, decode.d2.loss_mask: 0.5490, decode.d2.loss_dice: 0.7568, decode.d3.loss_cls: 0.3138, decode.d3.loss_mask: 0.5475, decode.d3.loss_dice: 0.7521, decode.d4.loss_cls: 0.3092, decode.d4.loss_mask: 0.5418, decode.d4.loss_dice: 0.7521, decode.d5.loss_cls: 0.3053, decode.d5.loss_mask: 0.5459, decode.d5.loss_dice: 0.7486, decode.d6.loss_cls: 0.3052, decode.d6.loss_mask: 0.5435, decode.d6.loss_dice: 0.7452, decode.d7.loss_cls: 0.3031, decode.d7.loss_mask: 0.5448, decode.d7.loss_dice: 0.7531, decode.d8.loss_cls: 0.2988, decode.d8.loss_mask: 0.5468, decode.d8.loss_dice: 0.7500, loss: 19.5105 +2022-05-06 03:20:41,339 - mmseg - INFO - Iter [11400/40000] lr: 1.027e-06, eta: 8:05:09, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3001, decode.loss_mask: 0.5539, decode.loss_dice: 0.7729, decode.d0.loss_cls: 3.3822, decode.d0.loss_mask: 0.5734, decode.d0.loss_dice: 0.8960, decode.d1.loss_cls: 0.4303, decode.d1.loss_mask: 0.5708, decode.d1.loss_dice: 0.8140, decode.d2.loss_cls: 0.3426, decode.d2.loss_mask: 0.5642, decode.d2.loss_dice: 0.7867, decode.d3.loss_cls: 0.3221, decode.d3.loss_mask: 0.5577, decode.d3.loss_dice: 0.7684, decode.d4.loss_cls: 0.3075, decode.d4.loss_mask: 0.5561, decode.d4.loss_dice: 0.7681, decode.d5.loss_cls: 0.3024, decode.d5.loss_mask: 0.5561, decode.d5.loss_dice: 0.7689, decode.d6.loss_cls: 0.2915, decode.d6.loss_mask: 0.5565, decode.d6.loss_dice: 0.7689, decode.d7.loss_cls: 0.2912, decode.d7.loss_mask: 0.5567, decode.d7.loss_dice: 0.7707, decode.d8.loss_cls: 0.2953, decode.d8.loss_mask: 0.5572, decode.d8.loss_dice: 0.7675, loss: 19.7497 +2022-05-06 03:21:15,661 - mmseg - INFO - Iter [11450/40000] lr: 1.025e-06, eta: 8:03:14, time: 0.686, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3096, decode.loss_mask: 0.5519, decode.loss_dice: 0.7468, decode.d0.loss_cls: 3.4107, decode.d0.loss_mask: 0.5834, decode.d0.loss_dice: 0.8853, decode.d1.loss_cls: 0.4415, decode.d1.loss_mask: 0.5706, decode.d1.loss_dice: 0.8014, decode.d2.loss_cls: 0.3718, decode.d2.loss_mask: 0.5601, decode.d2.loss_dice: 0.7674, decode.d3.loss_cls: 0.3360, decode.d3.loss_mask: 0.5513, decode.d3.loss_dice: 0.7489, decode.d4.loss_cls: 0.3247, decode.d4.loss_mask: 0.5505, decode.d4.loss_dice: 0.7526, decode.d5.loss_cls: 0.3201, decode.d5.loss_mask: 0.5528, decode.d5.loss_dice: 0.7443, decode.d6.loss_cls: 0.3133, decode.d6.loss_mask: 0.5532, decode.d6.loss_dice: 0.7442, decode.d7.loss_cls: 0.3141, decode.d7.loss_mask: 0.5521, decode.d7.loss_dice: 0.7472, decode.d8.loss_cls: 0.3169, decode.d8.loss_mask: 0.5498, decode.d8.loss_dice: 0.7507, loss: 19.7234 +2022-05-06 03:21:52,364 - mmseg - INFO - Iter [11500/40000] lr: 1.023e-06, eta: 8:01:30, time: 0.734, data_time: 0.052, memory: 53770, decode.loss_cls: 0.2987, decode.loss_mask: 0.5784, decode.loss_dice: 0.7571, decode.d0.loss_cls: 3.3759, decode.d0.loss_mask: 0.6003, decode.d0.loss_dice: 0.8768, decode.d1.loss_cls: 0.4133, decode.d1.loss_mask: 0.5910, decode.d1.loss_dice: 0.8028, decode.d2.loss_cls: 0.3450, decode.d2.loss_mask: 0.5761, decode.d2.loss_dice: 0.7664, decode.d3.loss_cls: 0.3175, decode.d3.loss_mask: 0.5720, decode.d3.loss_dice: 0.7605, decode.d4.loss_cls: 0.3050, decode.d4.loss_mask: 0.5745, decode.d4.loss_dice: 0.7643, decode.d5.loss_cls: 0.2958, decode.d5.loss_mask: 0.5765, decode.d5.loss_dice: 0.7524, decode.d6.loss_cls: 0.2881, decode.d6.loss_mask: 0.5783, decode.d6.loss_dice: 0.7556, decode.d7.loss_cls: 0.2885, decode.d7.loss_mask: 0.5755, decode.d7.loss_dice: 0.7528, decode.d8.loss_cls: 0.2947, decode.d8.loss_mask: 0.5769, decode.d8.loss_dice: 0.7535, loss: 19.7644 +2022-05-06 03:22:26,115 - mmseg - INFO - Iter [11550/40000] lr: 1.021e-06, eta: 7:59:35, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2879, decode.loss_mask: 0.5357, decode.loss_dice: 0.7313, decode.d0.loss_cls: 3.3343, decode.d0.loss_mask: 0.5666, decode.d0.loss_dice: 0.8844, decode.d1.loss_cls: 0.4318, decode.d1.loss_mask: 0.5507, decode.d1.loss_dice: 0.7879, decode.d2.loss_cls: 0.3327, decode.d2.loss_mask: 0.5449, decode.d2.loss_dice: 0.7584, decode.d3.loss_cls: 0.3113, decode.d3.loss_mask: 0.5354, decode.d3.loss_dice: 0.7362, decode.d4.loss_cls: 0.3003, decode.d4.loss_mask: 0.5336, decode.d4.loss_dice: 0.7387, decode.d5.loss_cls: 0.2884, decode.d5.loss_mask: 0.5340, decode.d5.loss_dice: 0.7324, decode.d6.loss_cls: 0.2803, decode.d6.loss_mask: 0.5378, decode.d6.loss_dice: 0.7329, decode.d7.loss_cls: 0.2827, decode.d7.loss_mask: 0.5365, decode.d7.loss_dice: 0.7378, decode.d8.loss_cls: 0.2912, decode.d8.loss_mask: 0.5320, decode.d8.loss_dice: 0.7305, loss: 19.1187 +2022-05-06 03:22:59,572 - mmseg - INFO - Iter [11600/40000] lr: 1.019e-06, eta: 7:57:41, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3032, decode.loss_mask: 0.5438, decode.loss_dice: 0.7401, decode.d0.loss_cls: 3.3017, decode.d0.loss_mask: 0.5694, decode.d0.loss_dice: 0.8680, decode.d1.loss_cls: 0.4105, decode.d1.loss_mask: 0.5655, decode.d1.loss_dice: 0.7892, decode.d2.loss_cls: 0.3472, decode.d2.loss_mask: 0.5522, decode.d2.loss_dice: 0.7542, decode.d3.loss_cls: 0.3210, decode.d3.loss_mask: 0.5474, decode.d3.loss_dice: 0.7397, decode.d4.loss_cls: 0.3119, decode.d4.loss_mask: 0.5480, decode.d4.loss_dice: 0.7463, decode.d5.loss_cls: 0.3090, decode.d5.loss_mask: 0.5489, decode.d5.loss_dice: 0.7445, decode.d6.loss_cls: 0.3122, decode.d6.loss_mask: 0.5426, decode.d6.loss_dice: 0.7352, decode.d7.loss_cls: 0.3047, decode.d7.loss_mask: 0.5417, decode.d7.loss_dice: 0.7381, decode.d8.loss_cls: 0.2973, decode.d8.loss_mask: 0.5433, decode.d8.loss_dice: 0.7385, loss: 19.3153 +2022-05-06 03:23:33,691 - mmseg - INFO - Iter [11650/40000] lr: 1.018e-06, eta: 7:55:50, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3011, decode.loss_mask: 0.5469, decode.loss_dice: 0.7491, decode.d0.loss_cls: 3.2946, decode.d0.loss_mask: 0.5708, decode.d0.loss_dice: 0.8805, decode.d1.loss_cls: 0.4369, decode.d1.loss_mask: 0.5631, decode.d1.loss_dice: 0.7938, decode.d2.loss_cls: 0.3597, decode.d2.loss_mask: 0.5544, decode.d2.loss_dice: 0.7686, decode.d3.loss_cls: 0.3290, decode.d3.loss_mask: 0.5459, decode.d3.loss_dice: 0.7552, decode.d4.loss_cls: 0.3169, decode.d4.loss_mask: 0.5460, decode.d4.loss_dice: 0.7590, decode.d5.loss_cls: 0.3099, decode.d5.loss_mask: 0.5462, decode.d5.loss_dice: 0.7556, decode.d6.loss_cls: 0.2983, decode.d6.loss_mask: 0.5458, decode.d6.loss_dice: 0.7505, decode.d7.loss_cls: 0.2985, decode.d7.loss_mask: 0.5457, decode.d7.loss_dice: 0.7469, decode.d8.loss_cls: 0.2975, decode.d8.loss_mask: 0.5443, decode.d8.loss_dice: 0.7506, loss: 19.4613 +2022-05-06 03:24:07,075 - mmseg - INFO - Iter [11700/40000] lr: 1.016e-06, eta: 7:53:57, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2993, decode.loss_mask: 0.5342, decode.loss_dice: 0.7553, decode.d0.loss_cls: 3.2726, decode.d0.loss_mask: 0.5649, decode.d0.loss_dice: 0.8721, decode.d1.loss_cls: 0.4197, decode.d1.loss_mask: 0.5487, decode.d1.loss_dice: 0.7995, decode.d2.loss_cls: 0.3380, decode.d2.loss_mask: 0.5403, decode.d2.loss_dice: 0.7712, decode.d3.loss_cls: 0.3088, decode.d3.loss_mask: 0.5351, decode.d3.loss_dice: 0.7524, decode.d4.loss_cls: 0.3047, decode.d4.loss_mask: 0.5359, decode.d4.loss_dice: 0.7630, decode.d5.loss_cls: 0.3040, decode.d5.loss_mask: 0.5341, decode.d5.loss_dice: 0.7483, decode.d6.loss_cls: 0.2964, decode.d6.loss_mask: 0.5334, decode.d6.loss_dice: 0.7546, decode.d7.loss_cls: 0.2988, decode.d7.loss_mask: 0.5337, decode.d7.loss_dice: 0.7494, decode.d8.loss_cls: 0.2967, decode.d8.loss_mask: 0.5322, decode.d8.loss_dice: 0.7450, loss: 19.2427 +2022-05-06 03:24:41,292 - mmseg - INFO - Iter [11750/40000] lr: 1.014e-06, eta: 7:52:09, time: 0.684, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3073, decode.loss_mask: 0.5482, decode.loss_dice: 0.7274, decode.d0.loss_cls: 3.2678, decode.d0.loss_mask: 0.5712, decode.d0.loss_dice: 0.8669, decode.d1.loss_cls: 0.4278, decode.d1.loss_mask: 0.5625, decode.d1.loss_dice: 0.7781, decode.d2.loss_cls: 0.3387, decode.d2.loss_mask: 0.5545, decode.d2.loss_dice: 0.7468, decode.d3.loss_cls: 0.3184, decode.d3.loss_mask: 0.5518, decode.d3.loss_dice: 0.7309, decode.d4.loss_cls: 0.3136, decode.d4.loss_mask: 0.5517, decode.d4.loss_dice: 0.7376, decode.d5.loss_cls: 0.3085, decode.d5.loss_mask: 0.5474, decode.d5.loss_dice: 0.7322, decode.d6.loss_cls: 0.3006, decode.d6.loss_mask: 0.5473, decode.d6.loss_dice: 0.7281, decode.d7.loss_cls: 0.2990, decode.d7.loss_mask: 0.5479, decode.d7.loss_dice: 0.7262, decode.d8.loss_cls: 0.3019, decode.d8.loss_mask: 0.5488, decode.d8.loss_dice: 0.7288, loss: 19.2177 +2022-05-06 03:25:17,606 - mmseg - INFO - Iter [11800/40000] lr: 1.012e-06, eta: 7:50:28, time: 0.726, data_time: 0.056, memory: 53770, decode.loss_cls: 0.3016, decode.loss_mask: 0.5480, decode.loss_dice: 0.7641, decode.d0.loss_cls: 3.2970, decode.d0.loss_mask: 0.5806, decode.d0.loss_dice: 0.9028, decode.d1.loss_cls: 0.4517, decode.d1.loss_mask: 0.5764, decode.d1.loss_dice: 0.8198, decode.d2.loss_cls: 0.3470, decode.d2.loss_mask: 0.5591, decode.d2.loss_dice: 0.7905, decode.d3.loss_cls: 0.3183, decode.d3.loss_mask: 0.5520, decode.d3.loss_dice: 0.7758, decode.d4.loss_cls: 0.3158, decode.d4.loss_mask: 0.5491, decode.d4.loss_dice: 0.7764, decode.d5.loss_cls: 0.3160, decode.d5.loss_mask: 0.5433, decode.d5.loss_dice: 0.7711, decode.d6.loss_cls: 0.3006, decode.d6.loss_mask: 0.5502, decode.d6.loss_dice: 0.7710, decode.d7.loss_cls: 0.3030, decode.d7.loss_mask: 0.5459, decode.d7.loss_dice: 0.7703, decode.d8.loss_cls: 0.2989, decode.d8.loss_mask: 0.5467, decode.d8.loss_dice: 0.7690, loss: 19.7119 +2022-05-06 03:25:51,403 - mmseg - INFO - Iter [11850/40000] lr: 1.010e-06, eta: 7:48:40, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2738, decode.loss_mask: 0.5235, decode.loss_dice: 0.7224, decode.d0.loss_cls: 3.2278, decode.d0.loss_mask: 0.5560, decode.d0.loss_dice: 0.8593, decode.d1.loss_cls: 0.4300, decode.d1.loss_mask: 0.5411, decode.d1.loss_dice: 0.7737, decode.d2.loss_cls: 0.3307, decode.d2.loss_mask: 0.5302, decode.d2.loss_dice: 0.7452, decode.d3.loss_cls: 0.2964, decode.d3.loss_mask: 0.5242, decode.d3.loss_dice: 0.7264, decode.d4.loss_cls: 0.2987, decode.d4.loss_mask: 0.5251, decode.d4.loss_dice: 0.7299, decode.d5.loss_cls: 0.2836, decode.d5.loss_mask: 0.5270, decode.d5.loss_dice: 0.7298, decode.d6.loss_cls: 0.2662, decode.d6.loss_mask: 0.5280, decode.d6.loss_dice: 0.7309, decode.d7.loss_cls: 0.2672, decode.d7.loss_mask: 0.5252, decode.d7.loss_dice: 0.7284, decode.d8.loss_cls: 0.2754, decode.d8.loss_mask: 0.5252, decode.d8.loss_dice: 0.7263, loss: 18.7273 +2022-05-06 03:26:25,591 - mmseg - INFO - Iter [11900/40000] lr: 1.009e-06, eta: 7:46:54, time: 0.684, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3174, decode.loss_mask: 0.5410, decode.loss_dice: 0.7434, decode.d0.loss_cls: 3.2108, decode.d0.loss_mask: 0.5754, decode.d0.loss_dice: 0.8822, decode.d1.loss_cls: 0.4368, decode.d1.loss_mask: 0.5644, decode.d1.loss_dice: 0.7920, decode.d2.loss_cls: 0.3563, decode.d2.loss_mask: 0.5504, decode.d2.loss_dice: 0.7568, decode.d3.loss_cls: 0.3302, decode.d3.loss_mask: 0.5453, decode.d3.loss_dice: 0.7492, decode.d4.loss_cls: 0.3209, decode.d4.loss_mask: 0.5434, decode.d4.loss_dice: 0.7510, decode.d5.loss_cls: 0.3210, decode.d5.loss_mask: 0.5449, decode.d5.loss_dice: 0.7465, decode.d6.loss_cls: 0.3128, decode.d6.loss_mask: 0.5401, decode.d6.loss_dice: 0.7474, decode.d7.loss_cls: 0.3138, decode.d7.loss_mask: 0.5423, decode.d7.loss_dice: 0.7469, decode.d8.loss_cls: 0.3143, decode.d8.loss_mask: 0.5420, decode.d8.loss_dice: 0.7440, loss: 19.3827 +2022-05-06 03:26:59,327 - mmseg - INFO - Iter [11950/40000] lr: 1.007e-06, eta: 7:45:07, time: 0.675, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2725, decode.loss_mask: 0.5339, decode.loss_dice: 0.7427, decode.d0.loss_cls: 3.1793, decode.d0.loss_mask: 0.5642, decode.d0.loss_dice: 0.8787, decode.d1.loss_cls: 0.3913, decode.d1.loss_mask: 0.5546, decode.d1.loss_dice: 0.7903, decode.d2.loss_cls: 0.3094, decode.d2.loss_mask: 0.5455, decode.d2.loss_dice: 0.7558, decode.d3.loss_cls: 0.2808, decode.d3.loss_mask: 0.5388, decode.d3.loss_dice: 0.7445, decode.d4.loss_cls: 0.2755, decode.d4.loss_mask: 0.5362, decode.d4.loss_dice: 0.7460, decode.d5.loss_cls: 0.2682, decode.d5.loss_mask: 0.5363, decode.d5.loss_dice: 0.7473, decode.d6.loss_cls: 0.2619, decode.d6.loss_mask: 0.5369, decode.d6.loss_dice: 0.7442, decode.d7.loss_cls: 0.2657, decode.d7.loss_mask: 0.5393, decode.d7.loss_dice: 0.7475, decode.d8.loss_cls: 0.2646, decode.d8.loss_mask: 0.5380, decode.d8.loss_dice: 0.7464, loss: 18.8361 +2022-05-06 03:27:33,370 - mmseg - INFO - Saving checkpoint at 12000 iterations +2022-05-06 03:27:58,459 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 03:27:58,462 - mmseg - INFO - Iter [12000/40000] lr: 1.005e-06, eta: 7:44:50, time: 1.181, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2937, decode.loss_mask: 0.5246, decode.loss_dice: 0.7406, decode.d0.loss_cls: 3.1665, decode.d0.loss_mask: 0.5536, decode.d0.loss_dice: 0.8821, decode.d1.loss_cls: 0.4277, decode.d1.loss_mask: 0.5354, decode.d1.loss_dice: 0.7930, decode.d2.loss_cls: 0.3476, decode.d2.loss_mask: 0.5244, decode.d2.loss_dice: 0.7670, decode.d3.loss_cls: 0.3217, decode.d3.loss_mask: 0.5189, decode.d3.loss_dice: 0.7538, decode.d4.loss_cls: 0.3083, decode.d4.loss_mask: 0.5202, decode.d4.loss_dice: 0.7520, decode.d5.loss_cls: 0.2979, decode.d5.loss_mask: 0.5198, decode.d5.loss_dice: 0.7465, decode.d6.loss_cls: 0.2998, decode.d6.loss_mask: 0.5203, decode.d6.loss_dice: 0.7463, decode.d7.loss_cls: 0.2961, decode.d7.loss_mask: 0.5232, decode.d7.loss_dice: 0.7451, decode.d8.loss_cls: 0.2977, decode.d8.loss_mask: 0.5189, decode.d8.loss_dice: 0.7427, loss: 18.9852 +2022-05-06 03:32:19,676 - mmseg - INFO - per class results: +2022-05-06 03:32:19,695 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.47 | 95.89 | +| bag | 52.58 | 71.38 | +| bed | 36.8 | 43.31 | +| bedclothes | 48.12 | 75.67 | +| bench | 25.65 | 36.26 | +| bicycle | 84.93 | 92.35 | +| bird | 95.33 | 97.61 | +| boat | 87.08 | 93.48 | +| book | 61.86 | 78.01 | +| bottle | 89.5 | 95.41 | +| building | 66.46 | 78.67 | +| bus | 94.85 | 97.21 | +| cabinet | 53.49 | 73.72 | +| car | 93.51 | 97.09 | +| cat | 94.43 | 98.0 | +| ceiling | 62.47 | 77.51 | +| chair | 64.86 | 85.0 | +| cloth | 31.1 | 41.37 | +| computer | 58.3 | 70.32 | +| cow | 95.77 | 97.51 | +| cup | 49.11 | 61.13 | +| curtain | 57.1 | 75.38 | +| dog | 92.39 | 96.86 | +| door | 40.86 | 58.8 | +| fence | 46.35 | 64.66 | +| floor | 75.67 | 84.93 | +| flower | 46.28 | 60.59 | +| food | 40.1 | 49.09 | +| grass | 82.69 | 90.12 | +| ground | 58.51 | 72.85 | +| horse | 94.96 | 97.27 | +| keyboard | 86.98 | 93.69 | +| light | 61.14 | 80.28 | +| motorbike | 92.42 | 96.71 | +| mountain | 54.67 | 73.52 | +| mouse | 86.47 | 89.61 | +| person | 91.4 | 96.11 | +| plate | 25.7 | 30.2 | +| platform | 49.17 | 72.19 | +| pottedplant | 82.09 | 89.59 | +| road | 56.66 | 75.24 | +| rock | 54.24 | 65.82 | +| sheep | 94.22 | 97.78 | +| shelves | 39.57 | 48.94 | +| sidewalk | 31.58 | 58.86 | +| sign | 55.02 | 73.97 | +| sky | 94.47 | 96.77 | +| snow | 78.71 | 89.91 | +| sofa | 60.02 | 67.38 | +| table | 71.65 | 89.31 | +| track | 70.47 | 79.21 | +| train | 93.19 | 98.27 | +| tree | 81.79 | 90.77 | +| truck | 56.62 | 67.4 | +| tvmonitor | 91.09 | 93.4 | +| wall | 73.1 | 85.55 | +| water | 92.7 | 96.46 | +| window | 43.51 | 55.61 | +| wood | 24.78 | 30.74 | ++-------------+-------+-------+ +2022-05-06 03:32:19,695 - mmseg - INFO - Summary: +2022-05-06 03:32:19,695 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.55 | 67.24 | 77.81 | ++-------+-------+-------+ +2022-05-06 03:32:19,697 - mmseg - INFO - The previous best checkpoint /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/best_mIoU_iter_8000.pth was removed +2022-05-06 03:32:44,506 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_12000.pth. +2022-05-06 03:32:44,517 - mmseg - INFO - Best mIoU is 0.6724 at 12000 iter. +2022-05-06 03:32:44,552 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 03:32:44,552 - mmseg - INFO - Iter(val) [638] aAcc: 0.8655, mIoU: 0.6724, mAcc: 0.7781, IoU.aeroplane: 0.9247, IoU.bag: 0.5258, IoU.bed: 0.3680, IoU.bedclothes: 0.4812, IoU.bench: 0.2565, IoU.bicycle: 0.8493, IoU.bird: 0.9533, IoU.boat: 0.8708, IoU.book: 0.6186, IoU.bottle: 0.8950, IoU.building: 0.6646, IoU.bus: 0.9485, IoU.cabinet: 0.5349, IoU.car: 0.9351, IoU.cat: 0.9443, IoU.ceiling: 0.6247, IoU.chair: 0.6486, IoU.cloth: 0.3110, IoU.computer: 0.5830, IoU.cow: 0.9577, IoU.cup: 0.4911, IoU.curtain: 0.5710, IoU.dog: 0.9239, IoU.door: 0.4086, IoU.fence: 0.4635, IoU.floor: 0.7567, IoU.flower: 0.4628, IoU.food: 0.4010, IoU.grass: 0.8269, IoU.ground: 0.5851, IoU.horse: 0.9496, IoU.keyboard: 0.8698, IoU.light: 0.6114, IoU.motorbike: 0.9242, IoU.mountain: 0.5467, IoU.mouse: 0.8647, IoU.person: 0.9140, IoU.plate: 0.2570, IoU.platform: 0.4917, IoU.pottedplant: 0.8209, IoU.road: 0.5666, IoU.rock: 0.5424, IoU.sheep: 0.9422, IoU.shelves: 0.3957, IoU.sidewalk: 0.3158, IoU.sign: 0.5502, IoU.sky: 0.9447, IoU.snow: 0.7871, IoU.sofa: 0.6002, IoU.table: 0.7165, IoU.track: 0.7047, IoU.train: 0.9319, IoU.tree: 0.8179, IoU.truck: 0.5662, IoU.tvmonitor: 0.9109, IoU.wall: 0.7310, IoU.water: 0.9270, IoU.window: 0.4351, IoU.wood: 0.2478, Acc.aeroplane: 0.9589, Acc.bag: 0.7138, Acc.bed: 0.4331, Acc.bedclothes: 0.7567, Acc.bench: 0.3626, Acc.bicycle: 0.9235, Acc.bird: 0.9761, Acc.boat: 0.9348, Acc.book: 0.7801, Acc.bottle: 0.9541, Acc.building: 0.7867, Acc.bus: 0.9721, Acc.cabinet: 0.7372, Acc.car: 0.9709, Acc.cat: 0.9800, Acc.ceiling: 0.7751, Acc.chair: 0.8500, Acc.cloth: 0.4137, Acc.computer: 0.7032, Acc.cow: 0.9751, Acc.cup: 0.6113, Acc.curtain: 0.7538, Acc.dog: 0.9686, Acc.door: 0.5880, Acc.fence: 0.6466, Acc.floor: 0.8493, Acc.flower: 0.6059, Acc.food: 0.4909, Acc.grass: 0.9012, Acc.ground: 0.7285, Acc.horse: 0.9727, Acc.keyboard: 0.9369, Acc.light: 0.8028, Acc.motorbike: 0.9671, Acc.mountain: 0.7352, Acc.mouse: 0.8961, Acc.person: 0.9611, Acc.plate: 0.3020, Acc.platform: 0.7219, Acc.pottedplant: 0.8959, Acc.road: 0.7524, Acc.rock: 0.6582, Acc.sheep: 0.9778, Acc.shelves: 0.4894, Acc.sidewalk: 0.5886, Acc.sign: 0.7397, Acc.sky: 0.9677, Acc.snow: 0.8991, Acc.sofa: 0.6738, Acc.table: 0.8931, Acc.track: 0.7921, Acc.train: 0.9827, Acc.tree: 0.9077, Acc.truck: 0.6740, Acc.tvmonitor: 0.9340, Acc.wall: 0.8555, Acc.water: 0.9646, Acc.window: 0.5561, Acc.wood: 0.3074 +2022-05-06 03:33:19,033 - mmseg - INFO - Iter [12050/40000] lr: 1.003e-06, eta: 7:59:41, time: 6.413, data_time: 5.734, memory: 53770, decode.loss_cls: 0.2800, decode.loss_mask: 0.5296, decode.loss_dice: 0.7015, decode.d0.loss_cls: 3.1563, decode.d0.loss_mask: 0.5629, decode.d0.loss_dice: 0.8404, decode.d1.loss_cls: 0.4089, decode.d1.loss_mask: 0.5496, decode.d1.loss_dice: 0.7515, decode.d2.loss_cls: 0.3322, decode.d2.loss_mask: 0.5347, decode.d2.loss_dice: 0.7173, decode.d3.loss_cls: 0.2932, decode.d3.loss_mask: 0.5305, decode.d3.loss_dice: 0.7032, decode.d4.loss_cls: 0.2848, decode.d4.loss_mask: 0.5324, decode.d4.loss_dice: 0.7118, decode.d5.loss_cls: 0.2780, decode.d5.loss_mask: 0.5312, decode.d5.loss_dice: 0.7063, decode.d6.loss_cls: 0.2740, decode.d6.loss_mask: 0.5267, decode.d6.loss_dice: 0.6979, decode.d7.loss_cls: 0.2754, decode.d7.loss_mask: 0.5234, decode.d7.loss_dice: 0.7014, decode.d8.loss_cls: 0.2826, decode.d8.loss_mask: 0.5271, decode.d8.loss_dice: 0.7011, loss: 18.4460 +2022-05-06 03:33:52,735 - mmseg - INFO - Iter [12100/40000] lr: 1.002e-06, eta: 7:57:48, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2914, decode.loss_mask: 0.5413, decode.loss_dice: 0.7576, decode.d0.loss_cls: 3.1744, decode.d0.loss_mask: 0.5710, decode.d0.loss_dice: 0.9045, decode.d1.loss_cls: 0.4192, decode.d1.loss_mask: 0.5601, decode.d1.loss_dice: 0.8084, decode.d2.loss_cls: 0.3447, decode.d2.loss_mask: 0.5456, decode.d2.loss_dice: 0.7820, decode.d3.loss_cls: 0.3185, decode.d3.loss_mask: 0.5433, decode.d3.loss_dice: 0.7625, decode.d4.loss_cls: 0.3017, decode.d4.loss_mask: 0.5418, decode.d4.loss_dice: 0.7616, decode.d5.loss_cls: 0.2957, decode.d5.loss_mask: 0.5410, decode.d5.loss_dice: 0.7607, decode.d6.loss_cls: 0.2923, decode.d6.loss_mask: 0.5411, decode.d6.loss_dice: 0.7583, decode.d7.loss_cls: 0.2881, decode.d7.loss_mask: 0.5418, decode.d7.loss_dice: 0.7567, decode.d8.loss_cls: 0.2831, decode.d8.loss_mask: 0.5408, decode.d8.loss_dice: 0.7547, loss: 19.2839 +2022-05-06 03:34:29,722 - mmseg - INFO - Iter [12150/40000] lr: 9.997e-07, eta: 7:56:07, time: 0.740, data_time: 0.061, memory: 53770, decode.loss_cls: 0.2798, decode.loss_mask: 0.5281, decode.loss_dice: 0.6775, decode.d0.loss_cls: 3.1130, decode.d0.loss_mask: 0.5630, decode.d0.loss_dice: 0.8184, decode.d1.loss_cls: 0.4149, decode.d1.loss_mask: 0.5474, decode.d1.loss_dice: 0.7296, decode.d2.loss_cls: 0.3400, decode.d2.loss_mask: 0.5336, decode.d2.loss_dice: 0.6931, decode.d3.loss_cls: 0.3001, decode.d3.loss_mask: 0.5343, decode.d3.loss_dice: 0.6866, decode.d4.loss_cls: 0.2891, decode.d4.loss_mask: 0.5294, decode.d4.loss_dice: 0.6876, decode.d5.loss_cls: 0.2769, decode.d5.loss_mask: 0.5338, decode.d5.loss_dice: 0.6849, decode.d6.loss_cls: 0.2736, decode.d6.loss_mask: 0.5292, decode.d6.loss_dice: 0.6766, decode.d7.loss_cls: 0.2734, decode.d7.loss_mask: 0.5272, decode.d7.loss_dice: 0.6825, decode.d8.loss_cls: 0.2736, decode.d8.loss_mask: 0.5276, decode.d8.loss_dice: 0.6802, loss: 18.2050 +2022-05-06 03:35:03,994 - mmseg - INFO - Iter [12200/40000] lr: 9.979e-07, eta: 7:54:18, time: 0.686, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2957, decode.loss_mask: 0.5274, decode.loss_dice: 0.7552, decode.d0.loss_cls: 3.1028, decode.d0.loss_mask: 0.5621, decode.d0.loss_dice: 0.8926, decode.d1.loss_cls: 0.4297, decode.d1.loss_mask: 0.5414, decode.d1.loss_dice: 0.8143, decode.d2.loss_cls: 0.3414, decode.d2.loss_mask: 0.5332, decode.d2.loss_dice: 0.7855, decode.d3.loss_cls: 0.3169, decode.d3.loss_mask: 0.5269, decode.d3.loss_dice: 0.7645, decode.d4.loss_cls: 0.3095, decode.d4.loss_mask: 0.5279, decode.d4.loss_dice: 0.7694, decode.d5.loss_cls: 0.3019, decode.d5.loss_mask: 0.5268, decode.d5.loss_dice: 0.7667, decode.d6.loss_cls: 0.2946, decode.d6.loss_mask: 0.5287, decode.d6.loss_dice: 0.7545, decode.d7.loss_cls: 0.2988, decode.d7.loss_mask: 0.5268, decode.d7.loss_dice: 0.7580, decode.d8.loss_cls: 0.2920, decode.d8.loss_mask: 0.5273, decode.d8.loss_dice: 0.7603, loss: 19.1329 +2022-05-06 03:35:38,001 - mmseg - INFO - Iter [12250/40000] lr: 9.961e-07, eta: 7:52:29, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.3122, decode.loss_mask: 0.5480, decode.loss_dice: 0.7398, decode.d0.loss_cls: 3.1166, decode.d0.loss_mask: 0.5820, decode.d0.loss_dice: 0.8685, decode.d1.loss_cls: 0.4447, decode.d1.loss_mask: 0.5622, decode.d1.loss_dice: 0.7836, decode.d2.loss_cls: 0.3557, decode.d2.loss_mask: 0.5531, decode.d2.loss_dice: 0.7545, decode.d3.loss_cls: 0.3335, decode.d3.loss_mask: 0.5490, decode.d3.loss_dice: 0.7410, decode.d4.loss_cls: 0.3287, decode.d4.loss_mask: 0.5437, decode.d4.loss_dice: 0.7402, decode.d5.loss_cls: 0.3192, decode.d5.loss_mask: 0.5444, decode.d5.loss_dice: 0.7383, decode.d6.loss_cls: 0.3116, decode.d6.loss_mask: 0.5460, decode.d6.loss_dice: 0.7339, decode.d7.loss_cls: 0.3129, decode.d7.loss_mask: 0.5465, decode.d7.loss_dice: 0.7347, decode.d8.loss_cls: 0.3126, decode.d8.loss_mask: 0.5499, decode.d8.loss_dice: 0.7391, loss: 19.2461 +2022-05-06 03:36:11,830 - mmseg - INFO - Iter [12300/40000] lr: 9.943e-07, eta: 7:50:41, time: 0.676, data_time: 0.011, memory: 53770, decode.loss_cls: 0.2969, decode.loss_mask: 0.5565, decode.loss_dice: 0.7447, decode.d0.loss_cls: 3.0606, decode.d0.loss_mask: 0.5911, decode.d0.loss_dice: 0.8953, decode.d1.loss_cls: 0.4312, decode.d1.loss_mask: 0.5724, decode.d1.loss_dice: 0.7975, decode.d2.loss_cls: 0.3478, decode.d2.loss_mask: 0.5598, decode.d2.loss_dice: 0.7676, decode.d3.loss_cls: 0.3106, decode.d3.loss_mask: 0.5547, decode.d3.loss_dice: 0.7577, decode.d4.loss_cls: 0.3125, decode.d4.loss_mask: 0.5558, decode.d4.loss_dice: 0.7559, decode.d5.loss_cls: 0.2984, decode.d5.loss_mask: 0.5553, decode.d5.loss_dice: 0.7562, decode.d6.loss_cls: 0.2972, decode.d6.loss_mask: 0.5542, decode.d6.loss_dice: 0.7538, decode.d7.loss_cls: 0.2951, decode.d7.loss_mask: 0.5547, decode.d7.loss_dice: 0.7517, decode.d8.loss_cls: 0.2965, decode.d8.loss_mask: 0.5527, decode.d8.loss_dice: 0.7529, loss: 19.2872 +2022-05-06 03:36:45,528 - mmseg - INFO - Iter [12350/40000] lr: 9.925e-07, eta: 7:48:53, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2729, decode.loss_mask: 0.5495, decode.loss_dice: 0.7154, decode.d0.loss_cls: 3.0055, decode.d0.loss_mask: 0.5874, decode.d0.loss_dice: 0.8335, decode.d1.loss_cls: 0.3891, decode.d1.loss_mask: 0.5674, decode.d1.loss_dice: 0.7626, decode.d2.loss_cls: 0.3137, decode.d2.loss_mask: 0.5604, decode.d2.loss_dice: 0.7299, decode.d3.loss_cls: 0.2893, decode.d3.loss_mask: 0.5579, decode.d3.loss_dice: 0.7161, decode.d4.loss_cls: 0.2731, decode.d4.loss_mask: 0.5586, decode.d4.loss_dice: 0.7252, decode.d5.loss_cls: 0.2761, decode.d5.loss_mask: 0.5523, decode.d5.loss_dice: 0.7144, decode.d6.loss_cls: 0.2712, decode.d6.loss_mask: 0.5476, decode.d6.loss_dice: 0.7091, decode.d7.loss_cls: 0.2737, decode.d7.loss_mask: 0.5481, decode.d7.loss_dice: 0.7126, decode.d8.loss_cls: 0.2671, decode.d8.loss_mask: 0.5479, decode.d8.loss_dice: 0.7123, loss: 18.5399 +2022-05-06 03:37:19,044 - mmseg - INFO - Iter [12400/40000] lr: 9.907e-07, eta: 7:47:05, time: 0.670, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2978, decode.loss_mask: 0.5452, decode.loss_dice: 0.7640, decode.d0.loss_cls: 3.0598, decode.d0.loss_mask: 0.5753, decode.d0.loss_dice: 0.9022, decode.d1.loss_cls: 0.4075, decode.d1.loss_mask: 0.5648, decode.d1.loss_dice: 0.8136, decode.d2.loss_cls: 0.3449, decode.d2.loss_mask: 0.5495, decode.d2.loss_dice: 0.7857, decode.d3.loss_cls: 0.3129, decode.d3.loss_mask: 0.5487, decode.d3.loss_dice: 0.7682, decode.d4.loss_cls: 0.3053, decode.d4.loss_mask: 0.5490, decode.d4.loss_dice: 0.7662, decode.d5.loss_cls: 0.3032, decode.d5.loss_mask: 0.5441, decode.d5.loss_dice: 0.7622, decode.d6.loss_cls: 0.2931, decode.d6.loss_mask: 0.5461, decode.d6.loss_dice: 0.7627, decode.d7.loss_cls: 0.2947, decode.d7.loss_mask: 0.5463, decode.d7.loss_dice: 0.7651, decode.d8.loss_cls: 0.2916, decode.d8.loss_mask: 0.5442, decode.d8.loss_dice: 0.7628, loss: 19.2770 +2022-05-06 03:37:55,194 - mmseg - INFO - Iter [12450/40000] lr: 9.889e-07, eta: 7:45:26, time: 0.723, data_time: 0.058, memory: 53770, decode.loss_cls: 0.2625, decode.loss_mask: 0.5017, decode.loss_dice: 0.7127, decode.d0.loss_cls: 3.0331, decode.d0.loss_mask: 0.5301, decode.d0.loss_dice: 0.8488, decode.d1.loss_cls: 0.3980, decode.d1.loss_mask: 0.5200, decode.d1.loss_dice: 0.7680, decode.d2.loss_cls: 0.3126, decode.d2.loss_mask: 0.5075, decode.d2.loss_dice: 0.7374, decode.d3.loss_cls: 0.2850, decode.d3.loss_mask: 0.5009, decode.d3.loss_dice: 0.7194, decode.d4.loss_cls: 0.2792, decode.d4.loss_mask: 0.5029, decode.d4.loss_dice: 0.7207, decode.d5.loss_cls: 0.2656, decode.d5.loss_mask: 0.5015, decode.d5.loss_dice: 0.7167, decode.d6.loss_cls: 0.2596, decode.d6.loss_mask: 0.4998, decode.d6.loss_dice: 0.7118, decode.d7.loss_cls: 0.2620, decode.d7.loss_mask: 0.5004, decode.d7.loss_dice: 0.7173, decode.d8.loss_cls: 0.2592, decode.d8.loss_mask: 0.5010, decode.d8.loss_dice: 0.7167, loss: 18.0520 +2022-05-06 03:38:28,599 - mmseg - INFO - Iter [12500/40000] lr: 9.871e-07, eta: 7:43:40, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2736, decode.loss_mask: 0.5295, decode.loss_dice: 0.7192, decode.d0.loss_cls: 3.0046, decode.d0.loss_mask: 0.5604, decode.d0.loss_dice: 0.8405, decode.d1.loss_cls: 0.3944, decode.d1.loss_mask: 0.5514, decode.d1.loss_dice: 0.7705, decode.d2.loss_cls: 0.3199, decode.d2.loss_mask: 0.5358, decode.d2.loss_dice: 0.7349, decode.d3.loss_cls: 0.2811, decode.d3.loss_mask: 0.5324, decode.d3.loss_dice: 0.7279, decode.d4.loss_cls: 0.2844, decode.d4.loss_mask: 0.5300, decode.d4.loss_dice: 0.7262, decode.d5.loss_cls: 0.2706, decode.d5.loss_mask: 0.5262, decode.d5.loss_dice: 0.7269, decode.d6.loss_cls: 0.2686, decode.d6.loss_mask: 0.5247, decode.d6.loss_dice: 0.7208, decode.d7.loss_cls: 0.2645, decode.d7.loss_mask: 0.5295, decode.d7.loss_dice: 0.7249, decode.d8.loss_cls: 0.2642, decode.d8.loss_mask: 0.5325, decode.d8.loss_dice: 0.7222, loss: 18.3922 +2022-05-06 03:39:02,149 - mmseg - INFO - Iter [12550/40000] lr: 9.854e-07, eta: 7:41:54, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2770, decode.loss_mask: 0.5388, decode.loss_dice: 0.7440, decode.d0.loss_cls: 2.9710, decode.d0.loss_mask: 0.5669, decode.d0.loss_dice: 0.8640, decode.d1.loss_cls: 0.3994, decode.d1.loss_mask: 0.5541, decode.d1.loss_dice: 0.7842, decode.d2.loss_cls: 0.3245, decode.d2.loss_mask: 0.5440, decode.d2.loss_dice: 0.7625, decode.d3.loss_cls: 0.2879, decode.d3.loss_mask: 0.5416, decode.d3.loss_dice: 0.7464, decode.d4.loss_cls: 0.2880, decode.d4.loss_mask: 0.5410, decode.d4.loss_dice: 0.7462, decode.d5.loss_cls: 0.2790, decode.d5.loss_mask: 0.5383, decode.d5.loss_dice: 0.7427, decode.d6.loss_cls: 0.2745, decode.d6.loss_mask: 0.5385, decode.d6.loss_dice: 0.7425, decode.d7.loss_cls: 0.2689, decode.d7.loss_mask: 0.5361, decode.d7.loss_dice: 0.7450, decode.d8.loss_cls: 0.2791, decode.d8.loss_mask: 0.5347, decode.d8.loss_dice: 0.7466, loss: 18.7074 +2022-05-06 03:39:35,926 - mmseg - INFO - Iter [12600/40000] lr: 9.836e-07, eta: 7:40:11, time: 0.675, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2754, decode.loss_mask: 0.5342, decode.loss_dice: 0.7405, decode.d0.loss_cls: 2.9536, decode.d0.loss_mask: 0.5589, decode.d0.loss_dice: 0.8728, decode.d1.loss_cls: 0.4060, decode.d1.loss_mask: 0.5500, decode.d1.loss_dice: 0.7893, decode.d2.loss_cls: 0.3275, decode.d2.loss_mask: 0.5451, decode.d2.loss_dice: 0.7557, decode.d3.loss_cls: 0.2894, decode.d3.loss_mask: 0.5422, decode.d3.loss_dice: 0.7509, decode.d4.loss_cls: 0.2838, decode.d4.loss_mask: 0.5392, decode.d4.loss_dice: 0.7445, decode.d5.loss_cls: 0.2804, decode.d5.loss_mask: 0.5383, decode.d5.loss_dice: 0.7497, decode.d6.loss_cls: 0.2768, decode.d6.loss_mask: 0.5382, decode.d6.loss_dice: 0.7410, decode.d7.loss_cls: 0.2808, decode.d7.loss_mask: 0.5360, decode.d7.loss_dice: 0.7421, decode.d8.loss_cls: 0.2797, decode.d8.loss_mask: 0.5339, decode.d8.loss_dice: 0.7389, loss: 18.6947 +2022-05-06 03:40:09,679 - mmseg - INFO - Iter [12650/40000] lr: 9.818e-07, eta: 7:38:28, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2851, decode.loss_mask: 0.5301, decode.loss_dice: 0.7312, decode.d0.loss_cls: 2.9794, decode.d0.loss_mask: 0.5574, decode.d0.loss_dice: 0.8596, decode.d1.loss_cls: 0.4313, decode.d1.loss_mask: 0.5411, decode.d1.loss_dice: 0.7719, decode.d2.loss_cls: 0.3455, decode.d2.loss_mask: 0.5290, decode.d2.loss_dice: 0.7420, decode.d3.loss_cls: 0.3092, decode.d3.loss_mask: 0.5232, decode.d3.loss_dice: 0.7301, decode.d4.loss_cls: 0.3134, decode.d4.loss_mask: 0.5216, decode.d4.loss_dice: 0.7288, decode.d5.loss_cls: 0.3032, decode.d5.loss_mask: 0.5248, decode.d5.loss_dice: 0.7300, decode.d6.loss_cls: 0.2961, decode.d6.loss_mask: 0.5229, decode.d6.loss_dice: 0.7221, decode.d7.loss_cls: 0.2841, decode.d7.loss_mask: 0.5245, decode.d7.loss_dice: 0.7306, decode.d8.loss_cls: 0.2874, decode.d8.loss_mask: 0.5290, decode.d8.loss_dice: 0.7294, loss: 18.6141 +2022-05-06 03:40:43,305 - mmseg - INFO - Iter [12700/40000] lr: 9.800e-07, eta: 7:36:45, time: 0.673, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2708, decode.loss_mask: 0.5332, decode.loss_dice: 0.7246, decode.d0.loss_cls: 2.9299, decode.d0.loss_mask: 0.5669, decode.d0.loss_dice: 0.8530, decode.d1.loss_cls: 0.3932, decode.d1.loss_mask: 0.5508, decode.d1.loss_dice: 0.7690, decode.d2.loss_cls: 0.2986, decode.d2.loss_mask: 0.5366, decode.d2.loss_dice: 0.7421, decode.d3.loss_cls: 0.2773, decode.d3.loss_mask: 0.5339, decode.d3.loss_dice: 0.7285, decode.d4.loss_cls: 0.2749, decode.d4.loss_mask: 0.5312, decode.d4.loss_dice: 0.7281, decode.d5.loss_cls: 0.2721, decode.d5.loss_mask: 0.5296, decode.d5.loss_dice: 0.7264, decode.d6.loss_cls: 0.2737, decode.d6.loss_mask: 0.5309, decode.d6.loss_dice: 0.7212, decode.d7.loss_cls: 0.2644, decode.d7.loss_mask: 0.5325, decode.d7.loss_dice: 0.7208, decode.d8.loss_cls: 0.2732, decode.d8.loss_mask: 0.5329, decode.d8.loss_dice: 0.7182, loss: 18.3384 +2022-05-06 03:41:19,347 - mmseg - INFO - Iter [12750/40000] lr: 9.782e-07, eta: 7:35:11, time: 0.721, data_time: 0.061, memory: 53770, decode.loss_cls: 0.2737, decode.loss_mask: 0.5182, decode.loss_dice: 0.7011, decode.d0.loss_cls: 2.8928, decode.d0.loss_mask: 0.5551, decode.d0.loss_dice: 0.8340, decode.d1.loss_cls: 0.3961, decode.d1.loss_mask: 0.5370, decode.d1.loss_dice: 0.7460, decode.d2.loss_cls: 0.3215, decode.d2.loss_mask: 0.5268, decode.d2.loss_dice: 0.7176, decode.d3.loss_cls: 0.2943, decode.d3.loss_mask: 0.5223, decode.d3.loss_dice: 0.7089, decode.d4.loss_cls: 0.2808, decode.d4.loss_mask: 0.5200, decode.d4.loss_dice: 0.7103, decode.d5.loss_cls: 0.2743, decode.d5.loss_mask: 0.5223, decode.d5.loss_dice: 0.7037, decode.d6.loss_cls: 0.2685, decode.d6.loss_mask: 0.5173, decode.d6.loss_dice: 0.7001, decode.d7.loss_cls: 0.2723, decode.d7.loss_mask: 0.5147, decode.d7.loss_dice: 0.6994, decode.d8.loss_cls: 0.2729, decode.d8.loss_mask: 0.5177, decode.d8.loss_dice: 0.7004, loss: 18.0202 +2022-05-06 03:41:52,707 - mmseg - INFO - Iter [12800/40000] lr: 9.764e-07, eta: 7:33:29, time: 0.667, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2689, decode.loss_mask: 0.5227, decode.loss_dice: 0.7198, decode.d0.loss_cls: 2.9059, decode.d0.loss_mask: 0.5535, decode.d0.loss_dice: 0.8535, decode.d1.loss_cls: 0.4129, decode.d1.loss_mask: 0.5385, decode.d1.loss_dice: 0.7701, decode.d2.loss_cls: 0.3222, decode.d2.loss_mask: 0.5298, decode.d2.loss_dice: 0.7448, decode.d3.loss_cls: 0.2910, decode.d3.loss_mask: 0.5251, decode.d3.loss_dice: 0.7252, decode.d4.loss_cls: 0.2889, decode.d4.loss_mask: 0.5235, decode.d4.loss_dice: 0.7220, decode.d5.loss_cls: 0.2774, decode.d5.loss_mask: 0.5250, decode.d5.loss_dice: 0.7241, decode.d6.loss_cls: 0.2651, decode.d6.loss_mask: 0.5242, decode.d6.loss_dice: 0.7192, decode.d7.loss_cls: 0.2712, decode.d7.loss_mask: 0.5248, decode.d7.loss_dice: 0.7187, decode.d8.loss_cls: 0.2726, decode.d8.loss_mask: 0.5236, decode.d8.loss_dice: 0.7179, loss: 18.2818 +2022-05-06 03:42:26,274 - mmseg - INFO - Iter [12850/40000] lr: 9.746e-07, eta: 7:31:49, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2635, decode.loss_mask: 0.5265, decode.loss_dice: 0.7294, decode.d0.loss_cls: 2.9141, decode.d0.loss_mask: 0.5517, decode.d0.loss_dice: 0.8618, decode.d1.loss_cls: 0.4121, decode.d1.loss_mask: 0.5389, decode.d1.loss_dice: 0.7728, decode.d2.loss_cls: 0.3080, decode.d2.loss_mask: 0.5294, decode.d2.loss_dice: 0.7494, decode.d3.loss_cls: 0.2874, decode.d3.loss_mask: 0.5258, decode.d3.loss_dice: 0.7391, decode.d4.loss_cls: 0.2702, decode.d4.loss_mask: 0.5266, decode.d4.loss_dice: 0.7346, decode.d5.loss_cls: 0.2710, decode.d5.loss_mask: 0.5231, decode.d5.loss_dice: 0.7280, decode.d6.loss_cls: 0.2581, decode.d6.loss_mask: 0.5248, decode.d6.loss_dice: 0.7276, decode.d7.loss_cls: 0.2641, decode.d7.loss_mask: 0.5225, decode.d7.loss_dice: 0.7282, decode.d8.loss_cls: 0.2614, decode.d8.loss_mask: 0.5247, decode.d8.loss_dice: 0.7286, loss: 18.3035 +2022-05-06 03:43:00,038 - mmseg - INFO - Iter [12900/40000] lr: 9.728e-07, eta: 7:30:09, time: 0.675, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2684, decode.loss_mask: 0.5334, decode.loss_dice: 0.7292, decode.d0.loss_cls: 2.8479, decode.d0.loss_mask: 0.5637, decode.d0.loss_dice: 0.8500, decode.d1.loss_cls: 0.3926, decode.d1.loss_mask: 0.5498, decode.d1.loss_dice: 0.7738, decode.d2.loss_cls: 0.3174, decode.d2.loss_mask: 0.5364, decode.d2.loss_dice: 0.7450, decode.d3.loss_cls: 0.2855, decode.d3.loss_mask: 0.5283, decode.d3.loss_dice: 0.7404, decode.d4.loss_cls: 0.2815, decode.d4.loss_mask: 0.5289, decode.d4.loss_dice: 0.7342, decode.d5.loss_cls: 0.2777, decode.d5.loss_mask: 0.5297, decode.d5.loss_dice: 0.7345, decode.d6.loss_cls: 0.2759, decode.d6.loss_mask: 0.5289, decode.d6.loss_dice: 0.7270, decode.d7.loss_cls: 0.2733, decode.d7.loss_mask: 0.5316, decode.d7.loss_dice: 0.7278, decode.d8.loss_cls: 0.2710, decode.d8.loss_mask: 0.5317, decode.d8.loss_dice: 0.7299, loss: 18.3454 +2022-05-06 03:43:34,580 - mmseg - INFO - Iter [12950/40000] lr: 9.710e-07, eta: 7:28:33, time: 0.691, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2739, decode.loss_mask: 0.5314, decode.loss_dice: 0.7267, decode.d0.loss_cls: 2.8589, decode.d0.loss_mask: 0.5611, decode.d0.loss_dice: 0.8639, decode.d1.loss_cls: 0.3968, decode.d1.loss_mask: 0.5525, decode.d1.loss_dice: 0.7787, decode.d2.loss_cls: 0.3124, decode.d2.loss_mask: 0.5386, decode.d2.loss_dice: 0.7533, decode.d3.loss_cls: 0.2830, decode.d3.loss_mask: 0.5327, decode.d3.loss_dice: 0.7388, decode.d4.loss_cls: 0.2800, decode.d4.loss_mask: 0.5309, decode.d4.loss_dice: 0.7343, decode.d5.loss_cls: 0.2750, decode.d5.loss_mask: 0.5309, decode.d5.loss_dice: 0.7286, decode.d6.loss_cls: 0.2651, decode.d6.loss_mask: 0.5296, decode.d6.loss_dice: 0.7252, decode.d7.loss_cls: 0.2638, decode.d7.loss_mask: 0.5315, decode.d7.loss_dice: 0.7278, decode.d8.loss_cls: 0.2689, decode.d8.loss_mask: 0.5328, decode.d8.loss_dice: 0.7321, loss: 18.3591 +2022-05-06 03:44:08,269 - mmseg - INFO - Saving checkpoint at 13000 iterations +2022-05-06 03:44:34,598 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 03:44:34,605 - mmseg - INFO - Iter [13000/40000] lr: 9.692e-07, eta: 7:28:14, time: 1.198, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2333, decode.loss_mask: 0.5225, decode.loss_dice: 0.6832, decode.d0.loss_cls: 2.8413, decode.d0.loss_mask: 0.5588, decode.d0.loss_dice: 0.8059, decode.d1.loss_cls: 0.3755, decode.d1.loss_mask: 0.5429, decode.d1.loss_dice: 0.7279, decode.d2.loss_cls: 0.2957, decode.d2.loss_mask: 0.5300, decode.d2.loss_dice: 0.7004, decode.d3.loss_cls: 0.2692, decode.d3.loss_mask: 0.5225, decode.d3.loss_dice: 0.6855, decode.d4.loss_cls: 0.2584, decode.d4.loss_mask: 0.5246, decode.d4.loss_dice: 0.6864, decode.d5.loss_cls: 0.2458, decode.d5.loss_mask: 0.5211, decode.d5.loss_dice: 0.6868, decode.d6.loss_cls: 0.2413, decode.d6.loss_mask: 0.5198, decode.d6.loss_dice: 0.6792, decode.d7.loss_cls: 0.2344, decode.d7.loss_mask: 0.5224, decode.d7.loss_dice: 0.6868, decode.d8.loss_cls: 0.2314, decode.d8.loss_mask: 0.5194, decode.d8.loss_dice: 0.6923, loss: 17.5446 +2022-05-06 03:45:11,423 - mmseg - INFO - Iter [13050/40000] lr: 9.674e-07, eta: 7:26:46, time: 0.739, data_time: 0.059, memory: 53770, decode.loss_cls: 0.2823, decode.loss_mask: 0.5317, decode.loss_dice: 0.7417, decode.d0.loss_cls: 2.8645, decode.d0.loss_mask: 0.5754, decode.d0.loss_dice: 0.8862, decode.d1.loss_cls: 0.4238, decode.d1.loss_mask: 0.5577, decode.d1.loss_dice: 0.7875, decode.d2.loss_cls: 0.3502, decode.d2.loss_mask: 0.5409, decode.d2.loss_dice: 0.7615, decode.d3.loss_cls: 0.3227, decode.d3.loss_mask: 0.5361, decode.d3.loss_dice: 0.7421, decode.d4.loss_cls: 0.3031, decode.d4.loss_mask: 0.5368, decode.d4.loss_dice: 0.7440, decode.d5.loss_cls: 0.2976, decode.d5.loss_mask: 0.5308, decode.d5.loss_dice: 0.7360, decode.d6.loss_cls: 0.2858, decode.d6.loss_mask: 0.5363, decode.d6.loss_dice: 0.7389, decode.d7.loss_cls: 0.2854, decode.d7.loss_mask: 0.5351, decode.d7.loss_dice: 0.7441, decode.d8.loss_cls: 0.2821, decode.d8.loss_mask: 0.5327, decode.d8.loss_dice: 0.7457, loss: 18.7387 +2022-05-06 03:45:45,057 - mmseg - INFO - Iter [13100/40000] lr: 9.656e-07, eta: 7:25:09, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2464, decode.loss_mask: 0.5199, decode.loss_dice: 0.7094, decode.d0.loss_cls: 2.8147, decode.d0.loss_mask: 0.5474, decode.d0.loss_dice: 0.8322, decode.d1.loss_cls: 0.3878, decode.d1.loss_mask: 0.5340, decode.d1.loss_dice: 0.7530, decode.d2.loss_cls: 0.3135, decode.d2.loss_mask: 0.5219, decode.d2.loss_dice: 0.7185, decode.d3.loss_cls: 0.2780, decode.d3.loss_mask: 0.5152, decode.d3.loss_dice: 0.7108, decode.d4.loss_cls: 0.2598, decode.d4.loss_mask: 0.5154, decode.d4.loss_dice: 0.7137, decode.d5.loss_cls: 0.2604, decode.d5.loss_mask: 0.5167, decode.d5.loss_dice: 0.7082, decode.d6.loss_cls: 0.2613, decode.d6.loss_mask: 0.5189, decode.d6.loss_dice: 0.7039, decode.d7.loss_cls: 0.2542, decode.d7.loss_mask: 0.5166, decode.d7.loss_dice: 0.7106, decode.d8.loss_cls: 0.2463, decode.d8.loss_mask: 0.5184, decode.d8.loss_dice: 0.7130, loss: 17.8202 +2022-05-06 03:46:18,421 - mmseg - INFO - Iter [13150/40000] lr: 9.638e-07, eta: 7:23:31, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2788, decode.loss_mask: 0.5320, decode.loss_dice: 0.7361, decode.d0.loss_cls: 2.8198, decode.d0.loss_mask: 0.5707, decode.d0.loss_dice: 0.8708, decode.d1.loss_cls: 0.4118, decode.d1.loss_mask: 0.5528, decode.d1.loss_dice: 0.7832, decode.d2.loss_cls: 0.3381, decode.d2.loss_mask: 0.5412, decode.d2.loss_dice: 0.7588, decode.d3.loss_cls: 0.3070, decode.d3.loss_mask: 0.5377, decode.d3.loss_dice: 0.7377, decode.d4.loss_cls: 0.3005, decode.d4.loss_mask: 0.5362, decode.d4.loss_dice: 0.7423, decode.d5.loss_cls: 0.2845, decode.d5.loss_mask: 0.5339, decode.d5.loss_dice: 0.7434, decode.d6.loss_cls: 0.2768, decode.d6.loss_mask: 0.5327, decode.d6.loss_dice: 0.7359, decode.d7.loss_cls: 0.2825, decode.d7.loss_mask: 0.5311, decode.d7.loss_dice: 0.7373, decode.d8.loss_cls: 0.2760, decode.d8.loss_mask: 0.5327, decode.d8.loss_dice: 0.7352, loss: 18.5575 +2022-05-06 03:46:51,612 - mmseg - INFO - Iter [13200/40000] lr: 9.620e-07, eta: 7:21:54, time: 0.663, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2589, decode.loss_mask: 0.5149, decode.loss_dice: 0.6830, decode.d0.loss_cls: 2.7776, decode.d0.loss_mask: 0.5424, decode.d0.loss_dice: 0.8034, decode.d1.loss_cls: 0.3812, decode.d1.loss_mask: 0.5361, decode.d1.loss_dice: 0.7282, decode.d2.loss_cls: 0.2916, decode.d2.loss_mask: 0.5180, decode.d2.loss_dice: 0.6974, decode.d3.loss_cls: 0.2696, decode.d3.loss_mask: 0.5162, decode.d3.loss_dice: 0.6878, decode.d4.loss_cls: 0.2629, decode.d4.loss_mask: 0.5148, decode.d4.loss_dice: 0.6854, decode.d5.loss_cls: 0.2581, decode.d5.loss_mask: 0.5162, decode.d5.loss_dice: 0.6892, decode.d6.loss_cls: 0.2524, decode.d6.loss_mask: 0.5167, decode.d6.loss_dice: 0.6832, decode.d7.loss_cls: 0.2550, decode.d7.loss_mask: 0.5144, decode.d7.loss_dice: 0.6901, decode.d8.loss_cls: 0.2569, decode.d8.loss_mask: 0.5180, decode.d8.loss_dice: 0.6927, loss: 17.5126 +2022-05-06 03:47:25,473 - mmseg - INFO - Iter [13250/40000] lr: 9.602e-07, eta: 7:20:19, time: 0.678, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2887, decode.loss_mask: 0.5275, decode.loss_dice: 0.7352, decode.d0.loss_cls: 2.7798, decode.d0.loss_mask: 0.5568, decode.d0.loss_dice: 0.8524, decode.d1.loss_cls: 0.4189, decode.d1.loss_mask: 0.5430, decode.d1.loss_dice: 0.7712, decode.d2.loss_cls: 0.3391, decode.d2.loss_mask: 0.5327, decode.d2.loss_dice: 0.7423, decode.d3.loss_cls: 0.3080, decode.d3.loss_mask: 0.5291, decode.d3.loss_dice: 0.7269, decode.d4.loss_cls: 0.2948, decode.d4.loss_mask: 0.5287, decode.d4.loss_dice: 0.7391, decode.d5.loss_cls: 0.2878, decode.d5.loss_mask: 0.5305, decode.d5.loss_dice: 0.7360, decode.d6.loss_cls: 0.2858, decode.d6.loss_mask: 0.5309, decode.d6.loss_dice: 0.7327, decode.d7.loss_cls: 0.2886, decode.d7.loss_mask: 0.5311, decode.d7.loss_dice: 0.7314, decode.d8.loss_cls: 0.2853, decode.d8.loss_mask: 0.5283, decode.d8.loss_dice: 0.7323, loss: 18.4154 +2022-05-06 03:47:58,668 - mmseg - INFO - Iter [13300/40000] lr: 9.584e-07, eta: 7:18:44, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2460, decode.loss_mask: 0.5205, decode.loss_dice: 0.7033, decode.d0.loss_cls: 2.7520, decode.d0.loss_mask: 0.5561, decode.d0.loss_dice: 0.8312, decode.d1.loss_cls: 0.3591, decode.d1.loss_mask: 0.5399, decode.d1.loss_dice: 0.7450, decode.d2.loss_cls: 0.2956, decode.d2.loss_mask: 0.5216, decode.d2.loss_dice: 0.7189, decode.d3.loss_cls: 0.2679, decode.d3.loss_mask: 0.5201, decode.d3.loss_dice: 0.7083, decode.d4.loss_cls: 0.2592, decode.d4.loss_mask: 0.5182, decode.d4.loss_dice: 0.7083, decode.d5.loss_cls: 0.2498, decode.d5.loss_mask: 0.5150, decode.d5.loss_dice: 0.7077, decode.d6.loss_cls: 0.2528, decode.d6.loss_mask: 0.5143, decode.d6.loss_dice: 0.7052, decode.d7.loss_cls: 0.2510, decode.d7.loss_mask: 0.5180, decode.d7.loss_dice: 0.7060, decode.d8.loss_cls: 0.2405, decode.d8.loss_mask: 0.5183, decode.d8.loss_dice: 0.7081, loss: 17.6581 +2022-05-06 03:48:32,403 - mmseg - INFO - Iter [13350/40000] lr: 9.566e-07, eta: 7:17:10, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2744, decode.loss_mask: 0.5281, decode.loss_dice: 0.7183, decode.d0.loss_cls: 2.7390, decode.d0.loss_mask: 0.5576, decode.d0.loss_dice: 0.8566, decode.d1.loss_cls: 0.4191, decode.d1.loss_mask: 0.5365, decode.d1.loss_dice: 0.7617, decode.d2.loss_cls: 0.3301, decode.d2.loss_mask: 0.5273, decode.d2.loss_dice: 0.7317, decode.d3.loss_cls: 0.2960, decode.d3.loss_mask: 0.5231, decode.d3.loss_dice: 0.7261, decode.d4.loss_cls: 0.2850, decode.d4.loss_mask: 0.5229, decode.d4.loss_dice: 0.7198, decode.d5.loss_cls: 0.2803, decode.d5.loss_mask: 0.5232, decode.d5.loss_dice: 0.7166, decode.d6.loss_cls: 0.2734, decode.d6.loss_mask: 0.5226, decode.d6.loss_dice: 0.7184, decode.d7.loss_cls: 0.2699, decode.d7.loss_mask: 0.5233, decode.d7.loss_dice: 0.7153, decode.d8.loss_cls: 0.2751, decode.d8.loss_mask: 0.5256, decode.d8.loss_dice: 0.7161, loss: 18.1130 +2022-05-06 03:49:08,780 - mmseg - INFO - Iter [13400/40000] lr: 9.548e-07, eta: 7:15:44, time: 0.728, data_time: 0.055, memory: 53770, decode.loss_cls: 0.2683, decode.loss_mask: 0.5146, decode.loss_dice: 0.7231, decode.d0.loss_cls: 2.7238, decode.d0.loss_mask: 0.5623, decode.d0.loss_dice: 0.8593, decode.d1.loss_cls: 0.3989, decode.d1.loss_mask: 0.5356, decode.d1.loss_dice: 0.7748, decode.d2.loss_cls: 0.3174, decode.d2.loss_mask: 0.5206, decode.d2.loss_dice: 0.7410, decode.d3.loss_cls: 0.2829, decode.d3.loss_mask: 0.5162, decode.d3.loss_dice: 0.7300, decode.d4.loss_cls: 0.2801, decode.d4.loss_mask: 0.5144, decode.d4.loss_dice: 0.7288, decode.d5.loss_cls: 0.2697, decode.d5.loss_mask: 0.5166, decode.d5.loss_dice: 0.7245, decode.d6.loss_cls: 0.2670, decode.d6.loss_mask: 0.5148, decode.d6.loss_dice: 0.7204, decode.d7.loss_cls: 0.2627, decode.d7.loss_mask: 0.5151, decode.d7.loss_dice: 0.7245, decode.d8.loss_cls: 0.2653, decode.d8.loss_mask: 0.5165, decode.d8.loss_dice: 0.7279, loss: 18.0169 +2022-05-06 03:49:42,460 - mmseg - INFO - Iter [13450/40000] lr: 9.530e-07, eta: 7:14:12, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2417, decode.loss_mask: 0.4962, decode.loss_dice: 0.6827, decode.d0.loss_cls: 2.6996, decode.d0.loss_mask: 0.5294, decode.d0.loss_dice: 0.8139, decode.d1.loss_cls: 0.3632, decode.d1.loss_mask: 0.5119, decode.d1.loss_dice: 0.7317, decode.d2.loss_cls: 0.2873, decode.d2.loss_mask: 0.5010, decode.d2.loss_dice: 0.6989, decode.d3.loss_cls: 0.2599, decode.d3.loss_mask: 0.4963, decode.d3.loss_dice: 0.6839, decode.d4.loss_cls: 0.2525, decode.d4.loss_mask: 0.4956, decode.d4.loss_dice: 0.6860, decode.d5.loss_cls: 0.2498, decode.d5.loss_mask: 0.4932, decode.d5.loss_dice: 0.6845, decode.d6.loss_cls: 0.2413, decode.d6.loss_mask: 0.4899, decode.d6.loss_dice: 0.6821, decode.d7.loss_cls: 0.2354, decode.d7.loss_mask: 0.4921, decode.d7.loss_dice: 0.6862, decode.d8.loss_cls: 0.2345, decode.d8.loss_mask: 0.4936, decode.d8.loss_dice: 0.6847, loss: 17.0990 +2022-05-06 03:50:16,300 - mmseg - INFO - Iter [13500/40000] lr: 9.513e-07, eta: 7:12:40, time: 0.678, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2385, decode.loss_mask: 0.5162, decode.loss_dice: 0.6739, decode.d0.loss_cls: 2.7005, decode.d0.loss_mask: 0.5460, decode.d0.loss_dice: 0.8031, decode.d1.loss_cls: 0.3674, decode.d1.loss_mask: 0.5313, decode.d1.loss_dice: 0.7195, decode.d2.loss_cls: 0.2837, decode.d2.loss_mask: 0.5240, decode.d2.loss_dice: 0.6883, decode.d3.loss_cls: 0.2515, decode.d3.loss_mask: 0.5197, decode.d3.loss_dice: 0.6797, decode.d4.loss_cls: 0.2401, decode.d4.loss_mask: 0.5170, decode.d4.loss_dice: 0.6767, decode.d5.loss_cls: 0.2389, decode.d5.loss_mask: 0.5184, decode.d5.loss_dice: 0.6816, decode.d6.loss_cls: 0.2379, decode.d6.loss_mask: 0.5148, decode.d6.loss_dice: 0.6768, decode.d7.loss_cls: 0.2313, decode.d7.loss_mask: 0.5170, decode.d7.loss_dice: 0.6800, decode.d8.loss_cls: 0.2349, decode.d8.loss_mask: 0.5160, decode.d8.loss_dice: 0.6757, loss: 17.2006 +2022-05-06 03:50:49,622 - mmseg - INFO - Iter [13550/40000] lr: 9.495e-07, eta: 7:11:08, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2497, decode.loss_mask: 0.5350, decode.loss_dice: 0.7174, decode.d0.loss_cls: 2.7179, decode.d0.loss_mask: 0.5700, decode.d0.loss_dice: 0.8422, decode.d1.loss_cls: 0.3727, decode.d1.loss_mask: 0.5497, decode.d1.loss_dice: 0.7668, decode.d2.loss_cls: 0.3022, decode.d2.loss_mask: 0.5413, decode.d2.loss_dice: 0.7394, decode.d3.loss_cls: 0.2707, decode.d3.loss_mask: 0.5366, decode.d3.loss_dice: 0.7237, decode.d4.loss_cls: 0.2597, decode.d4.loss_mask: 0.5388, decode.d4.loss_dice: 0.7265, decode.d5.loss_cls: 0.2603, decode.d5.loss_mask: 0.5342, decode.d5.loss_dice: 0.7197, decode.d6.loss_cls: 0.2433, decode.d6.loss_mask: 0.5344, decode.d6.loss_dice: 0.7181, decode.d7.loss_cls: 0.2480, decode.d7.loss_mask: 0.5372, decode.d7.loss_dice: 0.7206, decode.d8.loss_cls: 0.2505, decode.d8.loss_mask: 0.5393, decode.d8.loss_dice: 0.7169, loss: 17.9827 +2022-05-06 03:51:23,181 - mmseg - INFO - Iter [13600/40000] lr: 9.477e-07, eta: 7:09:37, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2445, decode.loss_mask: 0.5067, decode.loss_dice: 0.6885, decode.d0.loss_cls: 2.6458, decode.d0.loss_mask: 0.5408, decode.d0.loss_dice: 0.8158, decode.d1.loss_cls: 0.3861, decode.d1.loss_mask: 0.5247, decode.d1.loss_dice: 0.7435, decode.d2.loss_cls: 0.2959, decode.d2.loss_mask: 0.5149, decode.d2.loss_dice: 0.7132, decode.d3.loss_cls: 0.2661, decode.d3.loss_mask: 0.5082, decode.d3.loss_dice: 0.6990, decode.d4.loss_cls: 0.2543, decode.d4.loss_mask: 0.5058, decode.d4.loss_dice: 0.6966, decode.d5.loss_cls: 0.2474, decode.d5.loss_mask: 0.5064, decode.d5.loss_dice: 0.6901, decode.d6.loss_cls: 0.2398, decode.d6.loss_mask: 0.5038, decode.d6.loss_dice: 0.6886, decode.d7.loss_cls: 0.2370, decode.d7.loss_mask: 0.5029, decode.d7.loss_dice: 0.6908, decode.d8.loss_cls: 0.2432, decode.d8.loss_mask: 0.5024, decode.d8.loss_dice: 0.6868, loss: 17.2897 +2022-05-06 03:51:57,508 - mmseg - INFO - Iter [13650/40000] lr: 9.459e-07, eta: 7:08:08, time: 0.685, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2581, decode.loss_mask: 0.5277, decode.loss_dice: 0.7190, decode.d0.loss_cls: 2.6701, decode.d0.loss_mask: 0.5605, decode.d0.loss_dice: 0.8373, decode.d1.loss_cls: 0.3816, decode.d1.loss_mask: 0.5452, decode.d1.loss_dice: 0.7596, decode.d2.loss_cls: 0.3131, decode.d2.loss_mask: 0.5330, decode.d2.loss_dice: 0.7323, decode.d3.loss_cls: 0.2842, decode.d3.loss_mask: 0.5259, decode.d3.loss_dice: 0.7188, decode.d4.loss_cls: 0.2827, decode.d4.loss_mask: 0.5286, decode.d4.loss_dice: 0.7215, decode.d5.loss_cls: 0.2653, decode.d5.loss_mask: 0.5288, decode.d5.loss_dice: 0.7269, decode.d6.loss_cls: 0.2553, decode.d6.loss_mask: 0.5260, decode.d6.loss_dice: 0.7214, decode.d7.loss_cls: 0.2556, decode.d7.loss_mask: 0.5263, decode.d7.loss_dice: 0.7231, decode.d8.loss_cls: 0.2579, decode.d8.loss_mask: 0.5257, decode.d8.loss_dice: 0.7195, loss: 17.9310 +2022-05-06 03:52:33,880 - mmseg - INFO - Iter [13700/40000] lr: 9.441e-07, eta: 7:06:46, time: 0.729, data_time: 0.063, memory: 53770, decode.loss_cls: 0.2437, decode.loss_mask: 0.5026, decode.loss_dice: 0.7223, decode.d0.loss_cls: 2.6493, decode.d0.loss_mask: 0.5297, decode.d0.loss_dice: 0.8415, decode.d1.loss_cls: 0.3847, decode.d1.loss_mask: 0.5183, decode.d1.loss_dice: 0.7618, decode.d2.loss_cls: 0.2885, decode.d2.loss_mask: 0.5062, decode.d2.loss_dice: 0.7421, decode.d3.loss_cls: 0.2721, decode.d3.loss_mask: 0.5019, decode.d3.loss_dice: 0.7255, decode.d4.loss_cls: 0.2515, decode.d4.loss_mask: 0.5049, decode.d4.loss_dice: 0.7274, decode.d5.loss_cls: 0.2489, decode.d5.loss_mask: 0.5052, decode.d5.loss_dice: 0.7283, decode.d6.loss_cls: 0.2366, decode.d6.loss_mask: 0.5044, decode.d6.loss_dice: 0.7257, decode.d7.loss_cls: 0.2378, decode.d7.loss_mask: 0.5045, decode.d7.loss_dice: 0.7247, decode.d8.loss_cls: 0.2412, decode.d8.loss_mask: 0.5049, decode.d8.loss_dice: 0.7266, loss: 17.5626 +2022-05-06 03:53:07,603 - mmseg - INFO - Iter [13750/40000] lr: 9.423e-07, eta: 7:05:17, time: 0.675, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2539, decode.loss_mask: 0.5103, decode.loss_dice: 0.7149, decode.d0.loss_cls: 2.6462, decode.d0.loss_mask: 0.5472, decode.d0.loss_dice: 0.8469, decode.d1.loss_cls: 0.3790, decode.d1.loss_mask: 0.5246, decode.d1.loss_dice: 0.7641, decode.d2.loss_cls: 0.2897, decode.d2.loss_mask: 0.5138, decode.d2.loss_dice: 0.7308, decode.d3.loss_cls: 0.2711, decode.d3.loss_mask: 0.5102, decode.d3.loss_dice: 0.7131, decode.d4.loss_cls: 0.2598, decode.d4.loss_mask: 0.5106, decode.d4.loss_dice: 0.7166, decode.d5.loss_cls: 0.2528, decode.d5.loss_mask: 0.5104, decode.d5.loss_dice: 0.7112, decode.d6.loss_cls: 0.2566, decode.d6.loss_mask: 0.5098, decode.d6.loss_dice: 0.7096, decode.d7.loss_cls: 0.2475, decode.d7.loss_mask: 0.5102, decode.d7.loss_dice: 0.7158, decode.d8.loss_cls: 0.2478, decode.d8.loss_mask: 0.5113, decode.d8.loss_dice: 0.7186, loss: 17.6042 +2022-05-06 03:53:40,822 - mmseg - INFO - Iter [13800/40000] lr: 9.405e-07, eta: 7:03:47, time: 0.664, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2399, decode.loss_mask: 0.5195, decode.loss_dice: 0.7099, decode.d0.loss_cls: 2.6126, decode.d0.loss_mask: 0.5478, decode.d0.loss_dice: 0.8334, decode.d1.loss_cls: 0.3816, decode.d1.loss_mask: 0.5378, decode.d1.loss_dice: 0.7553, decode.d2.loss_cls: 0.2973, decode.d2.loss_mask: 0.5176, decode.d2.loss_dice: 0.7214, decode.d3.loss_cls: 0.2636, decode.d3.loss_mask: 0.5183, decode.d3.loss_dice: 0.7102, decode.d4.loss_cls: 0.2563, decode.d4.loss_mask: 0.5160, decode.d4.loss_dice: 0.7139, decode.d5.loss_cls: 0.2553, decode.d5.loss_mask: 0.5149, decode.d5.loss_dice: 0.7077, decode.d6.loss_cls: 0.2451, decode.d6.loss_mask: 0.5145, decode.d6.loss_dice: 0.7033, decode.d7.loss_cls: 0.2427, decode.d7.loss_mask: 0.5156, decode.d7.loss_dice: 0.7125, decode.d8.loss_cls: 0.2386, decode.d8.loss_mask: 0.5214, decode.d8.loss_dice: 0.7102, loss: 17.5342 +2022-05-06 03:54:14,689 - mmseg - INFO - Iter [13850/40000] lr: 9.387e-07, eta: 7:02:20, time: 0.677, data_time: 0.008, memory: 53770, decode.loss_cls: 0.2527, decode.loss_mask: 0.5474, decode.loss_dice: 0.7078, decode.d0.loss_cls: 2.5770, decode.d0.loss_mask: 0.5865, decode.d0.loss_dice: 0.8471, decode.d1.loss_cls: 0.3740, decode.d1.loss_mask: 0.5672, decode.d1.loss_dice: 0.7675, decode.d2.loss_cls: 0.3009, decode.d2.loss_mask: 0.5516, decode.d2.loss_dice: 0.7314, decode.d3.loss_cls: 0.2718, decode.d3.loss_mask: 0.5512, decode.d3.loss_dice: 0.7139, decode.d4.loss_cls: 0.2607, decode.d4.loss_mask: 0.5483, decode.d4.loss_dice: 0.7158, decode.d5.loss_cls: 0.2492, decode.d5.loss_mask: 0.5466, decode.d5.loss_dice: 0.7139, decode.d6.loss_cls: 0.2498, decode.d6.loss_mask: 0.5482, decode.d6.loss_dice: 0.7096, decode.d7.loss_cls: 0.2456, decode.d7.loss_mask: 0.5466, decode.d7.loss_dice: 0.7114, decode.d8.loss_cls: 0.2516, decode.d8.loss_mask: 0.5466, decode.d8.loss_dice: 0.7111, loss: 17.9032 +2022-05-06 03:54:48,697 - mmseg - INFO - Iter [13900/40000] lr: 9.369e-07, eta: 7:00:54, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2683, decode.loss_mask: 0.5084, decode.loss_dice: 0.7147, decode.d0.loss_cls: 2.5757, decode.d0.loss_mask: 0.5537, decode.d0.loss_dice: 0.8457, decode.d1.loss_cls: 0.4035, decode.d1.loss_mask: 0.5297, decode.d1.loss_dice: 0.7605, decode.d2.loss_cls: 0.3143, decode.d2.loss_mask: 0.5193, decode.d2.loss_dice: 0.7317, decode.d3.loss_cls: 0.2871, decode.d3.loss_mask: 0.5129, decode.d3.loss_dice: 0.7216, decode.d4.loss_cls: 0.2758, decode.d4.loss_mask: 0.5115, decode.d4.loss_dice: 0.7195, decode.d5.loss_cls: 0.2708, decode.d5.loss_mask: 0.5109, decode.d5.loss_dice: 0.7129, decode.d6.loss_cls: 0.2684, decode.d6.loss_mask: 0.5115, decode.d6.loss_dice: 0.7138, decode.d7.loss_cls: 0.2639, decode.d7.loss_mask: 0.5120, decode.d7.loss_dice: 0.7132, decode.d8.loss_cls: 0.2712, decode.d8.loss_mask: 0.5118, decode.d8.loss_dice: 0.7116, loss: 17.7258 +2022-05-06 03:55:22,966 - mmseg - INFO - Iter [13950/40000] lr: 9.351e-07, eta: 6:59:28, time: 0.685, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2625, decode.loss_mask: 0.5003, decode.loss_dice: 0.6919, decode.d0.loss_cls: 2.6106, decode.d0.loss_mask: 0.5322, decode.d0.loss_dice: 0.8268, decode.d1.loss_cls: 0.3847, decode.d1.loss_mask: 0.5158, decode.d1.loss_dice: 0.7470, decode.d2.loss_cls: 0.3030, decode.d2.loss_mask: 0.5046, decode.d2.loss_dice: 0.7164, decode.d3.loss_cls: 0.2708, decode.d3.loss_mask: 0.4992, decode.d3.loss_dice: 0.7041, decode.d4.loss_cls: 0.2673, decode.d4.loss_mask: 0.4986, decode.d4.loss_dice: 0.7056, decode.d5.loss_cls: 0.2711, decode.d5.loss_mask: 0.4976, decode.d5.loss_dice: 0.6987, decode.d6.loss_cls: 0.2606, decode.d6.loss_mask: 0.4984, decode.d6.loss_dice: 0.6933, decode.d7.loss_cls: 0.2587, decode.d7.loss_mask: 0.4973, decode.d7.loss_dice: 0.6957, decode.d8.loss_cls: 0.2650, decode.d8.loss_mask: 0.4963, decode.d8.loss_dice: 0.6959, loss: 17.3699 +2022-05-06 03:55:58,950 - mmseg - INFO - Saving checkpoint at 14000 iterations +2022-05-06 03:56:23,780 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 03:56:23,789 - mmseg - INFO - Iter [14000/40000] lr: 9.333e-07, eta: 6:59:12, time: 1.214, data_time: 0.057, memory: 53770, decode.loss_cls: 0.2521, decode.loss_mask: 0.4909, decode.loss_dice: 0.7047, decode.d0.loss_cls: 2.5853, decode.d0.loss_mask: 0.5243, decode.d0.loss_dice: 0.8389, decode.d1.loss_cls: 0.3859, decode.d1.loss_mask: 0.5064, decode.d1.loss_dice: 0.7600, decode.d2.loss_cls: 0.2990, decode.d2.loss_mask: 0.4957, decode.d2.loss_dice: 0.7304, decode.d3.loss_cls: 0.2690, decode.d3.loss_mask: 0.4909, decode.d3.loss_dice: 0.7160, decode.d4.loss_cls: 0.2609, decode.d4.loss_mask: 0.4906, decode.d4.loss_dice: 0.7135, decode.d5.loss_cls: 0.2474, decode.d5.loss_mask: 0.4894, decode.d5.loss_dice: 0.7090, decode.d6.loss_cls: 0.2433, decode.d6.loss_mask: 0.4924, decode.d6.loss_dice: 0.7114, decode.d7.loss_cls: 0.2426, decode.d7.loss_mask: 0.4912, decode.d7.loss_dice: 0.7130, decode.d8.loss_cls: 0.2480, decode.d8.loss_mask: 0.4914, decode.d8.loss_dice: 0.7097, loss: 17.3035 +2022-05-06 03:56:58,312 - mmseg - INFO - Iter [14050/40000] lr: 9.315e-07, eta: 6:57:48, time: 0.692, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2303, decode.loss_mask: 0.4990, decode.loss_dice: 0.6783, decode.d0.loss_cls: 2.5037, decode.d0.loss_mask: 0.5351, decode.d0.loss_dice: 0.8072, decode.d1.loss_cls: 0.3709, decode.d1.loss_mask: 0.5156, decode.d1.loss_dice: 0.7196, decode.d2.loss_cls: 0.2765, decode.d2.loss_mask: 0.5038, decode.d2.loss_dice: 0.7021, decode.d3.loss_cls: 0.2446, decode.d3.loss_mask: 0.4999, decode.d3.loss_dice: 0.6887, decode.d4.loss_cls: 0.2367, decode.d4.loss_mask: 0.4993, decode.d4.loss_dice: 0.6858, decode.d5.loss_cls: 0.2308, decode.d5.loss_mask: 0.5001, decode.d5.loss_dice: 0.6826, decode.d6.loss_cls: 0.2291, decode.d6.loss_mask: 0.4971, decode.d6.loss_dice: 0.6818, decode.d7.loss_cls: 0.2205, decode.d7.loss_mask: 0.5004, decode.d7.loss_dice: 0.6811, decode.d8.loss_cls: 0.2236, decode.d8.loss_mask: 0.4995, decode.d8.loss_dice: 0.6827, loss: 16.8265 +2022-05-06 03:57:31,781 - mmseg - INFO - Iter [14100/40000] lr: 9.297e-07, eta: 6:56:22, time: 0.670, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2564, decode.loss_mask: 0.5084, decode.loss_dice: 0.7174, decode.d0.loss_cls: 2.5622, decode.d0.loss_mask: 0.5438, decode.d0.loss_dice: 0.8576, decode.d1.loss_cls: 0.3860, decode.d1.loss_mask: 0.5279, decode.d1.loss_dice: 0.7690, decode.d2.loss_cls: 0.2932, decode.d2.loss_mask: 0.5143, decode.d2.loss_dice: 0.7389, decode.d3.loss_cls: 0.2820, decode.d3.loss_mask: 0.5082, decode.d3.loss_dice: 0.7245, decode.d4.loss_cls: 0.2642, decode.d4.loss_mask: 0.5069, decode.d4.loss_dice: 0.7288, decode.d5.loss_cls: 0.2589, decode.d5.loss_mask: 0.5024, decode.d5.loss_dice: 0.7207, decode.d6.loss_cls: 0.2549, decode.d6.loss_mask: 0.5052, decode.d6.loss_dice: 0.7223, decode.d7.loss_cls: 0.2516, decode.d7.loss_mask: 0.5076, decode.d7.loss_dice: 0.7212, decode.d8.loss_cls: 0.2544, decode.d8.loss_mask: 0.5072, decode.d8.loss_dice: 0.7212, loss: 17.6177 +2022-05-06 03:58:05,869 - mmseg - INFO - Iter [14150/40000] lr: 9.279e-07, eta: 6:54:58, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2377, decode.loss_mask: 0.5036, decode.loss_dice: 0.6894, decode.d0.loss_cls: 2.5614, decode.d0.loss_mask: 0.5451, decode.d0.loss_dice: 0.8297, decode.d1.loss_cls: 0.3750, decode.d1.loss_mask: 0.5196, decode.d1.loss_dice: 0.7348, decode.d2.loss_cls: 0.2901, decode.d2.loss_mask: 0.5095, decode.d2.loss_dice: 0.7146, decode.d3.loss_cls: 0.2550, decode.d3.loss_mask: 0.5041, decode.d3.loss_dice: 0.6946, decode.d4.loss_cls: 0.2504, decode.d4.loss_mask: 0.5042, decode.d4.loss_dice: 0.6956, decode.d5.loss_cls: 0.2475, decode.d5.loss_mask: 0.5023, decode.d5.loss_dice: 0.6914, decode.d6.loss_cls: 0.2366, decode.d6.loss_mask: 0.5067, decode.d6.loss_dice: 0.6915, decode.d7.loss_cls: 0.2376, decode.d7.loss_mask: 0.5013, decode.d7.loss_dice: 0.6939, decode.d8.loss_cls: 0.2362, decode.d8.loss_mask: 0.5055, decode.d8.loss_dice: 0.6907, loss: 17.1555 +2022-05-06 03:58:40,378 - mmseg - INFO - Iter [14200/40000] lr: 9.261e-07, eta: 6:53:35, time: 0.690, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2309, decode.loss_mask: 0.5005, decode.loss_dice: 0.6747, decode.d0.loss_cls: 2.5257, decode.d0.loss_mask: 0.5386, decode.d0.loss_dice: 0.8068, decode.d1.loss_cls: 0.3712, decode.d1.loss_mask: 0.5216, decode.d1.loss_dice: 0.7266, decode.d2.loss_cls: 0.2853, decode.d2.loss_mask: 0.5113, decode.d2.loss_dice: 0.6937, decode.d3.loss_cls: 0.2511, decode.d3.loss_mask: 0.5068, decode.d3.loss_dice: 0.6790, decode.d4.loss_cls: 0.2460, decode.d4.loss_mask: 0.5043, decode.d4.loss_dice: 0.6787, decode.d5.loss_cls: 0.2372, decode.d5.loss_mask: 0.5056, decode.d5.loss_dice: 0.6768, decode.d6.loss_cls: 0.2366, decode.d6.loss_mask: 0.5033, decode.d6.loss_dice: 0.6744, decode.d7.loss_cls: 0.2342, decode.d7.loss_mask: 0.5044, decode.d7.loss_dice: 0.6768, decode.d8.loss_cls: 0.2349, decode.d8.loss_mask: 0.5036, decode.d8.loss_dice: 0.6764, loss: 16.9171 +2022-05-06 03:59:14,207 - mmseg - INFO - Iter [14250/40000] lr: 9.243e-07, eta: 6:52:11, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2479, decode.loss_mask: 0.4846, decode.loss_dice: 0.6890, decode.d0.loss_cls: 2.5198, decode.d0.loss_mask: 0.5229, decode.d0.loss_dice: 0.8243, decode.d1.loss_cls: 0.3715, decode.d1.loss_mask: 0.5045, decode.d1.loss_dice: 0.7406, decode.d2.loss_cls: 0.2855, decode.d2.loss_mask: 0.4928, decode.d2.loss_dice: 0.7141, decode.d3.loss_cls: 0.2582, decode.d3.loss_mask: 0.4866, decode.d3.loss_dice: 0.7007, decode.d4.loss_cls: 0.2479, decode.d4.loss_mask: 0.4852, decode.d4.loss_dice: 0.6958, decode.d5.loss_cls: 0.2513, decode.d5.loss_mask: 0.4839, decode.d5.loss_dice: 0.6926, decode.d6.loss_cls: 0.2472, decode.d6.loss_mask: 0.4826, decode.d6.loss_dice: 0.6905, decode.d7.loss_cls: 0.2441, decode.d7.loss_mask: 0.4839, decode.d7.loss_dice: 0.6905, decode.d8.loss_cls: 0.2459, decode.d8.loss_mask: 0.4856, decode.d8.loss_dice: 0.6907, loss: 16.9609 +2022-05-06 03:59:50,409 - mmseg - INFO - Iter [14300/40000] lr: 9.225e-07, eta: 6:50:54, time: 0.724, data_time: 0.061, memory: 53770, decode.loss_cls: 0.2531, decode.loss_mask: 0.5156, decode.loss_dice: 0.7239, decode.d0.loss_cls: 2.5326, decode.d0.loss_mask: 0.5457, decode.d0.loss_dice: 0.8367, decode.d1.loss_cls: 0.3832, decode.d1.loss_mask: 0.5327, decode.d1.loss_dice: 0.7594, decode.d2.loss_cls: 0.2992, decode.d2.loss_mask: 0.5196, decode.d2.loss_dice: 0.7360, decode.d3.loss_cls: 0.2735, decode.d3.loss_mask: 0.5186, decode.d3.loss_dice: 0.7246, decode.d4.loss_cls: 0.2640, decode.d4.loss_mask: 0.5163, decode.d4.loss_dice: 0.7248, decode.d5.loss_cls: 0.2650, decode.d5.loss_mask: 0.5195, decode.d5.loss_dice: 0.7241, decode.d6.loss_cls: 0.2544, decode.d6.loss_mask: 0.5180, decode.d6.loss_dice: 0.7209, decode.d7.loss_cls: 0.2496, decode.d7.loss_mask: 0.5186, decode.d7.loss_dice: 0.7236, decode.d8.loss_cls: 0.2504, decode.d8.loss_mask: 0.5182, decode.d8.loss_dice: 0.7274, loss: 17.6493 +2022-05-06 04:00:24,863 - mmseg - INFO - Iter [14350/40000] lr: 9.207e-07, eta: 6:49:32, time: 0.689, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2209, decode.loss_mask: 0.5018, decode.loss_dice: 0.6845, decode.d0.loss_cls: 2.5010, decode.d0.loss_mask: 0.5354, decode.d0.loss_dice: 0.8042, decode.d1.loss_cls: 0.3570, decode.d1.loss_mask: 0.5143, decode.d1.loss_dice: 0.7292, decode.d2.loss_cls: 0.2796, decode.d2.loss_mask: 0.5057, decode.d2.loss_dice: 0.7003, decode.d3.loss_cls: 0.2385, decode.d3.loss_mask: 0.5030, decode.d3.loss_dice: 0.6889, decode.d4.loss_cls: 0.2294, decode.d4.loss_mask: 0.5034, decode.d4.loss_dice: 0.6906, decode.d5.loss_cls: 0.2328, decode.d5.loss_mask: 0.4987, decode.d5.loss_dice: 0.6847, decode.d6.loss_cls: 0.2271, decode.d6.loss_mask: 0.5007, decode.d6.loss_dice: 0.6811, decode.d7.loss_cls: 0.2240, decode.d7.loss_mask: 0.5015, decode.d7.loss_dice: 0.6821, decode.d8.loss_cls: 0.2209, decode.d8.loss_mask: 0.4993, decode.d8.loss_dice: 0.6821, loss: 16.8227 +2022-05-06 04:00:58,528 - mmseg - INFO - Iter [14400/40000] lr: 9.189e-07, eta: 6:48:09, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2277, decode.loss_mask: 0.5015, decode.loss_dice: 0.7114, decode.d0.loss_cls: 2.4550, decode.d0.loss_mask: 0.5353, decode.d0.loss_dice: 0.8285, decode.d1.loss_cls: 0.3622, decode.d1.loss_mask: 0.5173, decode.d1.loss_dice: 0.7500, decode.d2.loss_cls: 0.2750, decode.d2.loss_mask: 0.5068, decode.d2.loss_dice: 0.7241, decode.d3.loss_cls: 0.2563, decode.d3.loss_mask: 0.5005, decode.d3.loss_dice: 0.7029, decode.d4.loss_cls: 0.2432, decode.d4.loss_mask: 0.4975, decode.d4.loss_dice: 0.7085, decode.d5.loss_cls: 0.2353, decode.d5.loss_mask: 0.5006, decode.d5.loss_dice: 0.7043, decode.d6.loss_cls: 0.2336, decode.d6.loss_mask: 0.4978, decode.d6.loss_dice: 0.7032, decode.d7.loss_cls: 0.2295, decode.d7.loss_mask: 0.5000, decode.d7.loss_dice: 0.7072, decode.d8.loss_cls: 0.2283, decode.d8.loss_mask: 0.5027, decode.d8.loss_dice: 0.7105, loss: 17.0566 +2022-05-06 04:01:32,125 - mmseg - INFO - Iter [14450/40000] lr: 9.172e-07, eta: 6:46:47, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2317, decode.loss_mask: 0.4898, decode.loss_dice: 0.6778, decode.d0.loss_cls: 2.4607, decode.d0.loss_mask: 0.5231, decode.d0.loss_dice: 0.8020, decode.d1.loss_cls: 0.3696, decode.d1.loss_mask: 0.5040, decode.d1.loss_dice: 0.7228, decode.d2.loss_cls: 0.2881, decode.d2.loss_mask: 0.4931, decode.d2.loss_dice: 0.6923, decode.d3.loss_cls: 0.2580, decode.d3.loss_mask: 0.4921, decode.d3.loss_dice: 0.6814, decode.d4.loss_cls: 0.2400, decode.d4.loss_mask: 0.4912, decode.d4.loss_dice: 0.6822, decode.d5.loss_cls: 0.2434, decode.d5.loss_mask: 0.4890, decode.d5.loss_dice: 0.6805, decode.d6.loss_cls: 0.2272, decode.d6.loss_mask: 0.4900, decode.d6.loss_dice: 0.6805, decode.d7.loss_cls: 0.2236, decode.d7.loss_mask: 0.4888, decode.d7.loss_dice: 0.6846, decode.d8.loss_cls: 0.2340, decode.d8.loss_mask: 0.4888, decode.d8.loss_dice: 0.6799, loss: 16.7100 +2022-05-06 04:02:05,946 - mmseg - INFO - Iter [14500/40000] lr: 9.154e-07, eta: 6:45:25, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2490, decode.loss_mask: 0.4943, decode.loss_dice: 0.7059, decode.d0.loss_cls: 2.4829, decode.d0.loss_mask: 0.5367, decode.d0.loss_dice: 0.8424, decode.d1.loss_cls: 0.3874, decode.d1.loss_mask: 0.5132, decode.d1.loss_dice: 0.7572, decode.d2.loss_cls: 0.3131, decode.d2.loss_mask: 0.4973, decode.d2.loss_dice: 0.7232, decode.d3.loss_cls: 0.2788, decode.d3.loss_mask: 0.4944, decode.d3.loss_dice: 0.7106, decode.d4.loss_cls: 0.2693, decode.d4.loss_mask: 0.4942, decode.d4.loss_dice: 0.7086, decode.d5.loss_cls: 0.2581, decode.d5.loss_mask: 0.4948, decode.d5.loss_dice: 0.7064, decode.d6.loss_cls: 0.2481, decode.d6.loss_mask: 0.4918, decode.d6.loss_dice: 0.7028, decode.d7.loss_cls: 0.2424, decode.d7.loss_mask: 0.4930, decode.d7.loss_dice: 0.7053, decode.d8.loss_cls: 0.2509, decode.d8.loss_mask: 0.4937, decode.d8.loss_dice: 0.7016, loss: 17.2474 +2022-05-06 04:02:40,133 - mmseg - INFO - Iter [14550/40000] lr: 9.136e-07, eta: 6:44:05, time: 0.684, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2250, decode.loss_mask: 0.5043, decode.loss_dice: 0.6751, decode.d0.loss_cls: 2.4193, decode.d0.loss_mask: 0.5332, decode.d0.loss_dice: 0.7913, decode.d1.loss_cls: 0.3661, decode.d1.loss_mask: 0.5257, decode.d1.loss_dice: 0.7224, decode.d2.loss_cls: 0.2800, decode.d2.loss_mask: 0.5116, decode.d2.loss_dice: 0.6886, decode.d3.loss_cls: 0.2493, decode.d3.loss_mask: 0.5053, decode.d3.loss_dice: 0.6796, decode.d4.loss_cls: 0.2372, decode.d4.loss_mask: 0.5052, decode.d4.loss_dice: 0.6808, decode.d5.loss_cls: 0.2336, decode.d5.loss_mask: 0.5014, decode.d5.loss_dice: 0.6757, decode.d6.loss_cls: 0.2262, decode.d6.loss_mask: 0.5006, decode.d6.loss_dice: 0.6717, decode.d7.loss_cls: 0.2237, decode.d7.loss_mask: 0.5019, decode.d7.loss_dice: 0.6807, decode.d8.loss_cls: 0.2263, decode.d8.loss_mask: 0.5030, decode.d8.loss_dice: 0.6761, loss: 16.7212 +2022-05-06 04:03:13,746 - mmseg - INFO - Iter [14600/40000] lr: 9.118e-07, eta: 6:42:43, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2493, decode.loss_mask: 0.4997, decode.loss_dice: 0.7029, decode.d0.loss_cls: 2.4575, decode.d0.loss_mask: 0.5379, decode.d0.loss_dice: 0.8314, decode.d1.loss_cls: 0.3843, decode.d1.loss_mask: 0.5197, decode.d1.loss_dice: 0.7497, decode.d2.loss_cls: 0.3056, decode.d2.loss_mask: 0.5049, decode.d2.loss_dice: 0.7234, decode.d3.loss_cls: 0.2742, decode.d3.loss_mask: 0.4999, decode.d3.loss_dice: 0.7047, decode.d4.loss_cls: 0.2649, decode.d4.loss_mask: 0.4977, decode.d4.loss_dice: 0.7038, decode.d5.loss_cls: 0.2572, decode.d5.loss_mask: 0.5012, decode.d5.loss_dice: 0.7015, decode.d6.loss_cls: 0.2533, decode.d6.loss_mask: 0.5024, decode.d6.loss_dice: 0.7005, decode.d7.loss_cls: 0.2526, decode.d7.loss_mask: 0.4998, decode.d7.loss_dice: 0.6974, decode.d8.loss_cls: 0.2494, decode.d8.loss_mask: 0.4981, decode.d8.loss_dice: 0.7039, loss: 17.2289 +2022-05-06 04:03:50,361 - mmseg - INFO - Iter [14650/40000] lr: 9.100e-07, eta: 6:41:30, time: 0.732, data_time: 0.057, memory: 53770, decode.loss_cls: 0.2260, decode.loss_mask: 0.4916, decode.loss_dice: 0.6741, decode.d0.loss_cls: 2.3805, decode.d0.loss_mask: 0.5260, decode.d0.loss_dice: 0.7852, decode.d1.loss_cls: 0.3451, decode.d1.loss_mask: 0.5073, decode.d1.loss_dice: 0.7072, decode.d2.loss_cls: 0.2763, decode.d2.loss_mask: 0.5007, decode.d2.loss_dice: 0.6810, decode.d3.loss_cls: 0.2461, decode.d3.loss_mask: 0.4976, decode.d3.loss_dice: 0.6738, decode.d4.loss_cls: 0.2365, decode.d4.loss_mask: 0.4958, decode.d4.loss_dice: 0.6743, decode.d5.loss_cls: 0.2358, decode.d5.loss_mask: 0.4936, decode.d5.loss_dice: 0.6671, decode.d6.loss_cls: 0.2272, decode.d6.loss_mask: 0.4928, decode.d6.loss_dice: 0.6695, decode.d7.loss_cls: 0.2292, decode.d7.loss_mask: 0.4910, decode.d7.loss_dice: 0.6655, decode.d8.loss_cls: 0.2282, decode.d8.loss_mask: 0.4915, decode.d8.loss_dice: 0.6640, loss: 16.4807 +2022-05-06 04:04:23,721 - mmseg - INFO - Iter [14700/40000] lr: 9.082e-07, eta: 6:40:09, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2487, decode.loss_mask: 0.5024, decode.loss_dice: 0.7168, decode.d0.loss_cls: 2.4332, decode.d0.loss_mask: 0.5342, decode.d0.loss_dice: 0.8479, decode.d1.loss_cls: 0.3878, decode.d1.loss_mask: 0.5166, decode.d1.loss_dice: 0.7654, decode.d2.loss_cls: 0.3065, decode.d2.loss_mask: 0.5067, decode.d2.loss_dice: 0.7382, decode.d3.loss_cls: 0.2763, decode.d3.loss_mask: 0.4991, decode.d3.loss_dice: 0.7227, decode.d4.loss_cls: 0.2666, decode.d4.loss_mask: 0.5016, decode.d4.loss_dice: 0.7247, decode.d5.loss_cls: 0.2660, decode.d5.loss_mask: 0.5019, decode.d5.loss_dice: 0.7196, decode.d6.loss_cls: 0.2482, decode.d6.loss_mask: 0.5005, decode.d6.loss_dice: 0.7189, decode.d7.loss_cls: 0.2555, decode.d7.loss_mask: 0.4978, decode.d7.loss_dice: 0.7174, decode.d8.loss_cls: 0.2486, decode.d8.loss_mask: 0.5034, decode.d8.loss_dice: 0.7174, loss: 17.3905 +2022-05-06 04:04:57,723 - mmseg - INFO - Iter [14750/40000] lr: 9.064e-07, eta: 6:38:50, time: 0.680, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2463, decode.loss_mask: 0.5003, decode.loss_dice: 0.7103, decode.d0.loss_cls: 2.4488, decode.d0.loss_mask: 0.5424, decode.d0.loss_dice: 0.8443, decode.d1.loss_cls: 0.3916, decode.d1.loss_mask: 0.5222, decode.d1.loss_dice: 0.7633, decode.d2.loss_cls: 0.3039, decode.d2.loss_mask: 0.5085, decode.d2.loss_dice: 0.7307, decode.d3.loss_cls: 0.2722, decode.d3.loss_mask: 0.5075, decode.d3.loss_dice: 0.7141, decode.d4.loss_cls: 0.2595, decode.d4.loss_mask: 0.5054, decode.d4.loss_dice: 0.7155, decode.d5.loss_cls: 0.2611, decode.d5.loss_mask: 0.5041, decode.d5.loss_dice: 0.7103, decode.d6.loss_cls: 0.2437, decode.d6.loss_mask: 0.5036, decode.d6.loss_dice: 0.7070, decode.d7.loss_cls: 0.2394, decode.d7.loss_mask: 0.5044, decode.d7.loss_dice: 0.7087, decode.d8.loss_cls: 0.2424, decode.d8.loss_mask: 0.4993, decode.d8.loss_dice: 0.7107, loss: 17.3213 +2022-05-06 04:05:31,193 - mmseg - INFO - Iter [14800/40000] lr: 9.046e-07, eta: 6:37:30, time: 0.670, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2459, decode.loss_mask: 0.5061, decode.loss_dice: 0.7190, decode.d0.loss_cls: 2.4041, decode.d0.loss_mask: 0.5413, decode.d0.loss_dice: 0.8444, decode.d1.loss_cls: 0.3832, decode.d1.loss_mask: 0.5227, decode.d1.loss_dice: 0.7660, decode.d2.loss_cls: 0.2856, decode.d2.loss_mask: 0.5133, decode.d2.loss_dice: 0.7347, decode.d3.loss_cls: 0.2658, decode.d3.loss_mask: 0.5068, decode.d3.loss_dice: 0.7189, decode.d4.loss_cls: 0.2555, decode.d4.loss_mask: 0.5050, decode.d4.loss_dice: 0.7240, decode.d5.loss_cls: 0.2519, decode.d5.loss_mask: 0.5062, decode.d5.loss_dice: 0.7187, decode.d6.loss_cls: 0.2511, decode.d6.loss_mask: 0.5043, decode.d6.loss_dice: 0.7196, decode.d7.loss_cls: 0.2436, decode.d7.loss_mask: 0.5049, decode.d7.loss_dice: 0.7196, decode.d8.loss_cls: 0.2370, decode.d8.loss_mask: 0.5030, decode.d8.loss_dice: 0.7180, loss: 17.3200 +2022-05-06 04:06:05,240 - mmseg - INFO - Iter [14850/40000] lr: 9.028e-07, eta: 6:36:12, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2177, decode.loss_mask: 0.4986, decode.loss_dice: 0.6725, decode.d0.loss_cls: 2.3837, decode.d0.loss_mask: 0.5336, decode.d0.loss_dice: 0.8007, decode.d1.loss_cls: 0.3563, decode.d1.loss_mask: 0.5149, decode.d1.loss_dice: 0.7187, decode.d2.loss_cls: 0.2677, decode.d2.loss_mask: 0.5056, decode.d2.loss_dice: 0.6926, decode.d3.loss_cls: 0.2378, decode.d3.loss_mask: 0.5040, decode.d3.loss_dice: 0.6805, decode.d4.loss_cls: 0.2330, decode.d4.loss_mask: 0.5001, decode.d4.loss_dice: 0.6803, decode.d5.loss_cls: 0.2269, decode.d5.loss_mask: 0.4996, decode.d5.loss_dice: 0.6733, decode.d6.loss_cls: 0.2201, decode.d6.loss_mask: 0.4998, decode.d6.loss_dice: 0.6763, decode.d7.loss_cls: 0.2163, decode.d7.loss_mask: 0.4981, decode.d7.loss_dice: 0.6740, decode.d8.loss_cls: 0.2173, decode.d8.loss_mask: 0.4985, decode.d8.loss_dice: 0.6755, loss: 16.5741 +2022-05-06 04:06:39,116 - mmseg - INFO - Iter [14900/40000] lr: 9.010e-07, eta: 6:34:54, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2178, decode.loss_mask: 0.4865, decode.loss_dice: 0.6880, decode.d0.loss_cls: 2.3694, decode.d0.loss_mask: 0.5186, decode.d0.loss_dice: 0.8033, decode.d1.loss_cls: 0.3430, decode.d1.loss_mask: 0.5017, decode.d1.loss_dice: 0.7303, decode.d2.loss_cls: 0.2626, decode.d2.loss_mask: 0.4903, decode.d2.loss_dice: 0.7029, decode.d3.loss_cls: 0.2376, decode.d3.loss_mask: 0.4871, decode.d3.loss_dice: 0.6973, decode.d4.loss_cls: 0.2343, decode.d4.loss_mask: 0.4839, decode.d4.loss_dice: 0.6932, decode.d5.loss_cls: 0.2261, decode.d5.loss_mask: 0.4813, decode.d5.loss_dice: 0.6924, decode.d6.loss_cls: 0.2220, decode.d6.loss_mask: 0.4837, decode.d6.loss_dice: 0.6904, decode.d7.loss_cls: 0.2195, decode.d7.loss_mask: 0.4861, decode.d7.loss_dice: 0.6893, decode.d8.loss_cls: 0.2218, decode.d8.loss_mask: 0.4836, decode.d8.loss_dice: 0.6902, loss: 16.5344 +2022-05-06 04:07:15,809 - mmseg - INFO - Iter [14950/40000] lr: 8.992e-07, eta: 6:33:43, time: 0.734, data_time: 0.062, memory: 53770, decode.loss_cls: 0.2236, decode.loss_mask: 0.4985, decode.loss_dice: 0.6818, decode.d0.loss_cls: 2.3219, decode.d0.loss_mask: 0.5370, decode.d0.loss_dice: 0.8012, decode.d1.loss_cls: 0.3602, decode.d1.loss_mask: 0.5173, decode.d1.loss_dice: 0.7195, decode.d2.loss_cls: 0.2738, decode.d2.loss_mask: 0.5047, decode.d2.loss_dice: 0.7005, decode.d3.loss_cls: 0.2409, decode.d3.loss_mask: 0.4996, decode.d3.loss_dice: 0.6858, decode.d4.loss_cls: 0.2378, decode.d4.loss_mask: 0.5011, decode.d4.loss_dice: 0.6828, decode.d5.loss_cls: 0.2281, decode.d5.loss_mask: 0.4975, decode.d5.loss_dice: 0.6858, decode.d6.loss_cls: 0.2278, decode.d6.loss_mask: 0.4960, decode.d6.loss_dice: 0.6803, decode.d7.loss_cls: 0.2226, decode.d7.loss_mask: 0.4966, decode.d7.loss_dice: 0.6877, decode.d8.loss_cls: 0.2280, decode.d8.loss_mask: 0.4973, decode.d8.loss_dice: 0.6835, loss: 16.6194 +2022-05-06 04:07:49,259 - mmseg - INFO - Saving checkpoint at 15000 iterations +2022-05-06 04:08:14,937 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 04:08:14,945 - mmseg - INFO - Iter [15000/40000] lr: 8.974e-07, eta: 6:33:22, time: 1.180, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2242, decode.loss_mask: 0.4952, decode.loss_dice: 0.6948, decode.d0.loss_cls: 2.3867, decode.d0.loss_mask: 0.5368, decode.d0.loss_dice: 0.8174, decode.d1.loss_cls: 0.3683, decode.d1.loss_mask: 0.5095, decode.d1.loss_dice: 0.7418, decode.d2.loss_cls: 0.2824, decode.d2.loss_mask: 0.4981, decode.d2.loss_dice: 0.7157, decode.d3.loss_cls: 0.2547, decode.d3.loss_mask: 0.4934, decode.d3.loss_dice: 0.6957, decode.d4.loss_cls: 0.2459, decode.d4.loss_mask: 0.4933, decode.d4.loss_dice: 0.6917, decode.d5.loss_cls: 0.2321, decode.d5.loss_mask: 0.4922, decode.d5.loss_dice: 0.6936, decode.d6.loss_cls: 0.2294, decode.d6.loss_mask: 0.4900, decode.d6.loss_dice: 0.6925, decode.d7.loss_cls: 0.2279, decode.d7.loss_mask: 0.4928, decode.d7.loss_dice: 0.6964, decode.d8.loss_cls: 0.2308, decode.d8.loss_mask: 0.4923, decode.d8.loss_dice: 0.6979, loss: 16.8135 +2022-05-06 04:08:50,212 - mmseg - INFO - Iter [15050/40000] lr: 8.956e-07, eta: 6:32:08, time: 0.708, data_time: 0.011, memory: 53770, decode.loss_cls: 0.2222, decode.loss_mask: 0.5081, decode.loss_dice: 0.7038, decode.d0.loss_cls: 2.3566, decode.d0.loss_mask: 0.5451, decode.d0.loss_dice: 0.8293, decode.d1.loss_cls: 0.3454, decode.d1.loss_mask: 0.5279, decode.d1.loss_dice: 0.7524, decode.d2.loss_cls: 0.2547, decode.d2.loss_mask: 0.5150, decode.d2.loss_dice: 0.7256, decode.d3.loss_cls: 0.2466, decode.d3.loss_mask: 0.5108, decode.d3.loss_dice: 0.7084, decode.d4.loss_cls: 0.2397, decode.d4.loss_mask: 0.5094, decode.d4.loss_dice: 0.7105, decode.d5.loss_cls: 0.2275, decode.d5.loss_mask: 0.5077, decode.d5.loss_dice: 0.7061, decode.d6.loss_cls: 0.2195, decode.d6.loss_mask: 0.5075, decode.d6.loss_dice: 0.7021, decode.d7.loss_cls: 0.2173, decode.d7.loss_mask: 0.5067, decode.d7.loss_dice: 0.7018, decode.d8.loss_cls: 0.2168, decode.d8.loss_mask: 0.5073, decode.d8.loss_dice: 0.7021, loss: 16.9338 +2022-05-06 04:09:23,924 - mmseg - INFO - Iter [15100/40000] lr: 8.938e-07, eta: 6:30:51, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1966, decode.loss_mask: 0.4751, decode.loss_dice: 0.6604, decode.d0.loss_cls: 2.3321, decode.d0.loss_mask: 0.5155, decode.d0.loss_dice: 0.7876, decode.d1.loss_cls: 0.3325, decode.d1.loss_mask: 0.4897, decode.d1.loss_dice: 0.7065, decode.d2.loss_cls: 0.2552, decode.d2.loss_mask: 0.4842, decode.d2.loss_dice: 0.6822, decode.d3.loss_cls: 0.2272, decode.d3.loss_mask: 0.4761, decode.d3.loss_dice: 0.6614, decode.d4.loss_cls: 0.2129, decode.d4.loss_mask: 0.4767, decode.d4.loss_dice: 0.6654, decode.d5.loss_cls: 0.2057, decode.d5.loss_mask: 0.4746, decode.d5.loss_dice: 0.6617, decode.d6.loss_cls: 0.1960, decode.d6.loss_mask: 0.4761, decode.d6.loss_dice: 0.6601, decode.d7.loss_cls: 0.1975, decode.d7.loss_mask: 0.4734, decode.d7.loss_dice: 0.6607, decode.d8.loss_cls: 0.1980, decode.d8.loss_mask: 0.4731, decode.d8.loss_dice: 0.6558, loss: 15.9700 +2022-05-06 04:09:57,637 - mmseg - INFO - Iter [15150/40000] lr: 8.920e-07, eta: 6:29:34, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2317, decode.loss_mask: 0.5017, decode.loss_dice: 0.6801, decode.d0.loss_cls: 2.3644, decode.d0.loss_mask: 0.5329, decode.d0.loss_dice: 0.8153, decode.d1.loss_cls: 0.3733, decode.d1.loss_mask: 0.5209, decode.d1.loss_dice: 0.7243, decode.d2.loss_cls: 0.2863, decode.d2.loss_mask: 0.5071, decode.d2.loss_dice: 0.6970, decode.d3.loss_cls: 0.2498, decode.d3.loss_mask: 0.5050, decode.d3.loss_dice: 0.6821, decode.d4.loss_cls: 0.2408, decode.d4.loss_mask: 0.5026, decode.d4.loss_dice: 0.6860, decode.d5.loss_cls: 0.2325, decode.d5.loss_mask: 0.5026, decode.d5.loss_dice: 0.6879, decode.d6.loss_cls: 0.2339, decode.d6.loss_mask: 0.5001, decode.d6.loss_dice: 0.6838, decode.d7.loss_cls: 0.2292, decode.d7.loss_mask: 0.4998, decode.d7.loss_dice: 0.6815, decode.d8.loss_cls: 0.2352, decode.d8.loss_mask: 0.5016, decode.d8.loss_dice: 0.6838, loss: 16.7731 +2022-05-06 04:10:31,498 - mmseg - INFO - Iter [15200/40000] lr: 8.902e-07, eta: 6:28:18, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2240, decode.loss_mask: 0.5013, decode.loss_dice: 0.6661, decode.d0.loss_cls: 2.2919, decode.d0.loss_mask: 0.5337, decode.d0.loss_dice: 0.7790, decode.d1.loss_cls: 0.3393, decode.d1.loss_mask: 0.5135, decode.d1.loss_dice: 0.7079, decode.d2.loss_cls: 0.2702, decode.d2.loss_mask: 0.5064, decode.d2.loss_dice: 0.6821, decode.d3.loss_cls: 0.2368, decode.d3.loss_mask: 0.5025, decode.d3.loss_dice: 0.6699, decode.d4.loss_cls: 0.2293, decode.d4.loss_mask: 0.4963, decode.d4.loss_dice: 0.6669, decode.d5.loss_cls: 0.2237, decode.d5.loss_mask: 0.4988, decode.d5.loss_dice: 0.6732, decode.d6.loss_cls: 0.2170, decode.d6.loss_mask: 0.5007, decode.d6.loss_dice: 0.6671, decode.d7.loss_cls: 0.2167, decode.d7.loss_mask: 0.5005, decode.d7.loss_dice: 0.6673, decode.d8.loss_cls: 0.2192, decode.d8.loss_mask: 0.5032, decode.d8.loss_dice: 0.6699, loss: 16.3745 +2022-05-06 04:11:07,557 - mmseg - INFO - Iter [15250/40000] lr: 8.884e-07, eta: 6:27:07, time: 0.721, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1974, decode.loss_mask: 0.4961, decode.loss_dice: 0.6750, decode.d0.loss_cls: 2.2843, decode.d0.loss_mask: 0.5324, decode.d0.loss_dice: 0.7993, decode.d1.loss_cls: 0.3357, decode.d1.loss_mask: 0.5184, decode.d1.loss_dice: 0.7175, decode.d2.loss_cls: 0.2484, decode.d2.loss_mask: 0.5041, decode.d2.loss_dice: 0.6939, decode.d3.loss_cls: 0.2203, decode.d3.loss_mask: 0.5006, decode.d3.loss_dice: 0.6802, decode.d4.loss_cls: 0.2054, decode.d4.loss_mask: 0.5000, decode.d4.loss_dice: 0.6817, decode.d5.loss_cls: 0.2012, decode.d5.loss_mask: 0.4998, decode.d5.loss_dice: 0.6800, decode.d6.loss_cls: 0.1988, decode.d6.loss_mask: 0.4972, decode.d6.loss_dice: 0.6813, decode.d7.loss_cls: 0.2026, decode.d7.loss_mask: 0.4958, decode.d7.loss_dice: 0.6775, decode.d8.loss_cls: 0.2022, decode.d8.loss_mask: 0.4949, decode.d8.loss_dice: 0.6788, loss: 16.3007 +2022-05-06 04:11:41,845 - mmseg - INFO - Iter [15300/40000] lr: 8.866e-07, eta: 6:25:53, time: 0.686, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2236, decode.loss_mask: 0.4874, decode.loss_dice: 0.6737, decode.d0.loss_cls: 2.2790, decode.d0.loss_mask: 0.5313, decode.d0.loss_dice: 0.8034, decode.d1.loss_cls: 0.3412, decode.d1.loss_mask: 0.5064, decode.d1.loss_dice: 0.7220, decode.d2.loss_cls: 0.2508, decode.d2.loss_mask: 0.4918, decode.d2.loss_dice: 0.6931, decode.d3.loss_cls: 0.2317, decode.d3.loss_mask: 0.4933, decode.d3.loss_dice: 0.6819, decode.d4.loss_cls: 0.2249, decode.d4.loss_mask: 0.4905, decode.d4.loss_dice: 0.6793, decode.d5.loss_cls: 0.2191, decode.d5.loss_mask: 0.4903, decode.d5.loss_dice: 0.6801, decode.d6.loss_cls: 0.2169, decode.d6.loss_mask: 0.4878, decode.d6.loss_dice: 0.6745, decode.d7.loss_cls: 0.2237, decode.d7.loss_mask: 0.4865, decode.d7.loss_dice: 0.6727, decode.d8.loss_cls: 0.2170, decode.d8.loss_mask: 0.4886, decode.d8.loss_dice: 0.6770, loss: 16.3396 +2022-05-06 04:12:15,108 - mmseg - INFO - Iter [15350/40000] lr: 8.848e-07, eta: 6:24:36, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2045, decode.loss_mask: 0.5176, decode.loss_dice: 0.6741, decode.d0.loss_cls: 2.2925, decode.d0.loss_mask: 0.5559, decode.d0.loss_dice: 0.8050, decode.d1.loss_cls: 0.3397, decode.d1.loss_mask: 0.5371, decode.d1.loss_dice: 0.7246, decode.d2.loss_cls: 0.2623, decode.d2.loss_mask: 0.5229, decode.d2.loss_dice: 0.7030, decode.d3.loss_cls: 0.2288, decode.d3.loss_mask: 0.5192, decode.d3.loss_dice: 0.6862, decode.d4.loss_cls: 0.2135, decode.d4.loss_mask: 0.5200, decode.d4.loss_dice: 0.6804, decode.d5.loss_cls: 0.2091, decode.d5.loss_mask: 0.5182, decode.d5.loss_dice: 0.6798, decode.d6.loss_cls: 0.2008, decode.d6.loss_mask: 0.5182, decode.d6.loss_dice: 0.6791, decode.d7.loss_cls: 0.2030, decode.d7.loss_mask: 0.5199, decode.d7.loss_dice: 0.6796, decode.d8.loss_cls: 0.2014, decode.d8.loss_mask: 0.5205, decode.d8.loss_dice: 0.6809, loss: 16.5978 +2022-05-06 04:12:48,696 - mmseg - INFO - Iter [15400/40000] lr: 8.831e-07, eta: 6:23:21, time: 0.673, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2256, decode.loss_mask: 0.4797, decode.loss_dice: 0.6750, decode.d0.loss_cls: 2.3121, decode.d0.loss_mask: 0.5223, decode.d0.loss_dice: 0.7962, decode.d1.loss_cls: 0.3556, decode.d1.loss_mask: 0.5017, decode.d1.loss_dice: 0.7164, decode.d2.loss_cls: 0.2815, decode.d2.loss_mask: 0.4862, decode.d2.loss_dice: 0.6872, decode.d3.loss_cls: 0.2508, decode.d3.loss_mask: 0.4830, decode.d3.loss_dice: 0.6755, decode.d4.loss_cls: 0.2481, decode.d4.loss_mask: 0.4814, decode.d4.loss_dice: 0.6744, decode.d5.loss_cls: 0.2423, decode.d5.loss_mask: 0.4813, decode.d5.loss_dice: 0.6787, decode.d6.loss_cls: 0.2251, decode.d6.loss_mask: 0.4800, decode.d6.loss_dice: 0.6731, decode.d7.loss_cls: 0.2220, decode.d7.loss_mask: 0.4792, decode.d7.loss_dice: 0.6761, decode.d8.loss_cls: 0.2200, decode.d8.loss_mask: 0.4803, decode.d8.loss_dice: 0.6732, loss: 16.3841 +2022-05-06 04:13:22,835 - mmseg - INFO - Iter [15450/40000] lr: 8.813e-07, eta: 6:22:07, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2263, decode.loss_mask: 0.5020, decode.loss_dice: 0.6900, decode.d0.loss_cls: 2.2817, decode.d0.loss_mask: 0.5313, decode.d0.loss_dice: 0.8038, decode.d1.loss_cls: 0.3417, decode.d1.loss_mask: 0.5159, decode.d1.loss_dice: 0.7302, decode.d2.loss_cls: 0.2741, decode.d2.loss_mask: 0.5026, decode.d2.loss_dice: 0.7000, decode.d3.loss_cls: 0.2425, decode.d3.loss_mask: 0.5019, decode.d3.loss_dice: 0.6856, decode.d4.loss_cls: 0.2353, decode.d4.loss_mask: 0.5012, decode.d4.loss_dice: 0.6855, decode.d5.loss_cls: 0.2287, decode.d5.loss_mask: 0.5014, decode.d5.loss_dice: 0.6908, decode.d6.loss_cls: 0.2287, decode.d6.loss_mask: 0.5009, decode.d6.loss_dice: 0.6888, decode.d7.loss_cls: 0.2234, decode.d7.loss_mask: 0.5023, decode.d7.loss_dice: 0.6874, decode.d8.loss_cls: 0.2302, decode.d8.loss_mask: 0.4981, decode.d8.loss_dice: 0.6867, loss: 16.6190 +2022-05-06 04:13:56,837 - mmseg - INFO - Iter [15500/40000] lr: 8.795e-07, eta: 6:20:53, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2127, decode.loss_mask: 0.5041, decode.loss_dice: 0.6958, decode.d0.loss_cls: 2.2665, decode.d0.loss_mask: 0.5454, decode.d0.loss_dice: 0.8178, decode.d1.loss_cls: 0.3481, decode.d1.loss_mask: 0.5211, decode.d1.loss_dice: 0.7369, decode.d2.loss_cls: 0.2660, decode.d2.loss_mask: 0.5094, decode.d2.loss_dice: 0.7083, decode.d3.loss_cls: 0.2380, decode.d3.loss_mask: 0.5092, decode.d3.loss_dice: 0.6973, decode.d4.loss_cls: 0.2283, decode.d4.loss_mask: 0.5067, decode.d4.loss_dice: 0.6978, decode.d5.loss_cls: 0.2244, decode.d5.loss_mask: 0.5028, decode.d5.loss_dice: 0.6945, decode.d6.loss_cls: 0.2182, decode.d6.loss_mask: 0.5016, decode.d6.loss_dice: 0.6928, decode.d7.loss_cls: 0.2154, decode.d7.loss_mask: 0.5021, decode.d7.loss_dice: 0.6910, decode.d8.loss_cls: 0.2123, decode.d8.loss_mask: 0.5032, decode.d8.loss_dice: 0.6975, loss: 16.6651 +2022-05-06 04:14:32,975 - mmseg - INFO - Iter [15550/40000] lr: 8.777e-07, eta: 6:19:44, time: 0.723, data_time: 0.058, memory: 53770, decode.loss_cls: 0.2022, decode.loss_mask: 0.4846, decode.loss_dice: 0.6699, decode.d0.loss_cls: 2.2126, decode.d0.loss_mask: 0.5222, decode.d0.loss_dice: 0.7843, decode.d1.loss_cls: 0.3246, decode.d1.loss_mask: 0.5043, decode.d1.loss_dice: 0.7127, decode.d2.loss_cls: 0.2549, decode.d2.loss_mask: 0.4871, decode.d2.loss_dice: 0.6859, decode.d3.loss_cls: 0.2289, decode.d3.loss_mask: 0.4837, decode.d3.loss_dice: 0.6748, decode.d4.loss_cls: 0.2210, decode.d4.loss_mask: 0.4872, decode.d4.loss_dice: 0.6781, decode.d5.loss_cls: 0.2204, decode.d5.loss_mask: 0.4824, decode.d5.loss_dice: 0.6683, decode.d6.loss_cls: 0.2032, decode.d6.loss_mask: 0.4835, decode.d6.loss_dice: 0.6702, decode.d7.loss_cls: 0.2003, decode.d7.loss_mask: 0.4879, decode.d7.loss_dice: 0.6747, decode.d8.loss_cls: 0.1998, decode.d8.loss_mask: 0.4858, decode.d8.loss_dice: 0.6735, loss: 16.0691 +2022-05-06 04:15:07,135 - mmseg - INFO - Iter [15600/40000] lr: 8.759e-07, eta: 6:18:32, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2115, decode.loss_mask: 0.4798, decode.loss_dice: 0.6645, decode.d0.loss_cls: 2.2658, decode.d0.loss_mask: 0.5138, decode.d0.loss_dice: 0.7938, decode.d1.loss_cls: 0.3406, decode.d1.loss_mask: 0.4972, decode.d1.loss_dice: 0.7115, decode.d2.loss_cls: 0.2766, decode.d2.loss_mask: 0.4837, decode.d2.loss_dice: 0.6769, decode.d3.loss_cls: 0.2383, decode.d3.loss_mask: 0.4757, decode.d3.loss_dice: 0.6670, decode.d4.loss_cls: 0.2345, decode.d4.loss_mask: 0.4764, decode.d4.loss_dice: 0.6671, decode.d5.loss_cls: 0.2270, decode.d5.loss_mask: 0.4779, decode.d5.loss_dice: 0.6657, decode.d6.loss_cls: 0.2189, decode.d6.loss_mask: 0.4773, decode.d6.loss_dice: 0.6639, decode.d7.loss_cls: 0.2187, decode.d7.loss_mask: 0.4773, decode.d7.loss_dice: 0.6681, decode.d8.loss_cls: 0.2165, decode.d8.loss_mask: 0.4789, decode.d8.loss_dice: 0.6670, loss: 16.1317 +2022-05-06 04:15:40,946 - mmseg - INFO - Iter [15650/40000] lr: 8.741e-07, eta: 6:17:18, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2296, decode.loss_mask: 0.4959, decode.loss_dice: 0.6894, decode.d0.loss_cls: 2.2320, decode.d0.loss_mask: 0.5263, decode.d0.loss_dice: 0.8181, decode.d1.loss_cls: 0.3496, decode.d1.loss_mask: 0.5128, decode.d1.loss_dice: 0.7323, decode.d2.loss_cls: 0.2728, decode.d2.loss_mask: 0.5007, decode.d2.loss_dice: 0.6977, decode.d3.loss_cls: 0.2493, decode.d3.loss_mask: 0.4932, decode.d3.loss_dice: 0.6892, decode.d4.loss_cls: 0.2356, decode.d4.loss_mask: 0.4935, decode.d4.loss_dice: 0.6919, decode.d5.loss_cls: 0.2343, decode.d5.loss_mask: 0.4914, decode.d5.loss_dice: 0.6858, decode.d6.loss_cls: 0.2250, decode.d6.loss_mask: 0.4934, decode.d6.loss_dice: 0.6838, decode.d7.loss_cls: 0.2317, decode.d7.loss_mask: 0.4924, decode.d7.loss_dice: 0.6806, decode.d8.loss_cls: 0.2232, decode.d8.loss_mask: 0.4973, decode.d8.loss_dice: 0.6877, loss: 16.5365 +2022-05-06 04:16:14,642 - mmseg - INFO - Iter [15700/40000] lr: 8.723e-07, eta: 6:16:05, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2045, decode.loss_mask: 0.4868, decode.loss_dice: 0.6809, decode.d0.loss_cls: 2.2363, decode.d0.loss_mask: 0.5239, decode.d0.loss_dice: 0.8047, decode.d1.loss_cls: 0.3258, decode.d1.loss_mask: 0.5066, decode.d1.loss_dice: 0.7222, decode.d2.loss_cls: 0.2505, decode.d2.loss_mask: 0.4921, decode.d2.loss_dice: 0.6993, decode.d3.loss_cls: 0.2206, decode.d3.loss_mask: 0.4904, decode.d3.loss_dice: 0.6845, decode.d4.loss_cls: 0.2172, decode.d4.loss_mask: 0.4871, decode.d4.loss_dice: 0.6854, decode.d5.loss_cls: 0.2155, decode.d5.loss_mask: 0.4876, decode.d5.loss_dice: 0.6840, decode.d6.loss_cls: 0.2062, decode.d6.loss_mask: 0.4870, decode.d6.loss_dice: 0.6839, decode.d7.loss_cls: 0.2022, decode.d7.loss_mask: 0.4899, decode.d7.loss_dice: 0.6853, decode.d8.loss_cls: 0.2032, decode.d8.loss_mask: 0.4890, decode.d8.loss_dice: 0.6838, loss: 16.2363 +2022-05-06 04:16:48,685 - mmseg - INFO - Iter [15750/40000] lr: 8.705e-07, eta: 6:14:53, time: 0.681, data_time: 0.011, memory: 53770, decode.loss_cls: 0.2286, decode.loss_mask: 0.4874, decode.loss_dice: 0.6773, decode.d0.loss_cls: 2.2159, decode.d0.loss_mask: 0.5251, decode.d0.loss_dice: 0.8122, decode.d1.loss_cls: 0.3683, decode.d1.loss_mask: 0.5026, decode.d1.loss_dice: 0.7261, decode.d2.loss_cls: 0.2788, decode.d2.loss_mask: 0.4921, decode.d2.loss_dice: 0.6955, decode.d3.loss_cls: 0.2495, decode.d3.loss_mask: 0.4908, decode.d3.loss_dice: 0.6897, decode.d4.loss_cls: 0.2382, decode.d4.loss_mask: 0.4873, decode.d4.loss_dice: 0.6834, decode.d5.loss_cls: 0.2278, decode.d5.loss_mask: 0.4876, decode.d5.loss_dice: 0.6831, decode.d6.loss_cls: 0.2315, decode.d6.loss_mask: 0.4852, decode.d6.loss_dice: 0.6794, decode.d7.loss_cls: 0.2241, decode.d7.loss_mask: 0.4861, decode.d7.loss_dice: 0.6826, decode.d8.loss_cls: 0.2235, decode.d8.loss_mask: 0.4863, decode.d8.loss_dice: 0.6770, loss: 16.4231 +2022-05-06 04:17:22,381 - mmseg - INFO - Iter [15800/40000] lr: 8.687e-07, eta: 6:13:41, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2054, decode.loss_mask: 0.4783, decode.loss_dice: 0.6646, decode.d0.loss_cls: 2.2030, decode.d0.loss_mask: 0.5142, decode.d0.loss_dice: 0.7962, decode.d1.loss_cls: 0.3227, decode.d1.loss_mask: 0.4994, decode.d1.loss_dice: 0.7176, decode.d2.loss_cls: 0.2523, decode.d2.loss_mask: 0.4879, decode.d2.loss_dice: 0.6867, decode.d3.loss_cls: 0.2255, decode.d3.loss_mask: 0.4800, decode.d3.loss_dice: 0.6729, decode.d4.loss_cls: 0.2158, decode.d4.loss_mask: 0.4811, decode.d4.loss_dice: 0.6727, decode.d5.loss_cls: 0.2104, decode.d5.loss_mask: 0.4797, decode.d5.loss_dice: 0.6684, decode.d6.loss_cls: 0.2073, decode.d6.loss_mask: 0.4800, decode.d6.loss_dice: 0.6622, decode.d7.loss_cls: 0.2053, decode.d7.loss_mask: 0.4802, decode.d7.loss_dice: 0.6581, decode.d8.loss_cls: 0.2007, decode.d8.loss_mask: 0.4806, decode.d8.loss_dice: 0.6648, loss: 15.9742 +2022-05-06 04:17:56,400 - mmseg - INFO - Iter [15850/40000] lr: 8.669e-07, eta: 6:12:30, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1852, decode.loss_mask: 0.4787, decode.loss_dice: 0.6506, decode.d0.loss_cls: 2.2076, decode.d0.loss_mask: 0.5180, decode.d0.loss_dice: 0.7715, decode.d1.loss_cls: 0.3124, decode.d1.loss_mask: 0.4940, decode.d1.loss_dice: 0.6938, decode.d2.loss_cls: 0.2250, decode.d2.loss_mask: 0.4839, decode.d2.loss_dice: 0.6699, decode.d3.loss_cls: 0.2044, decode.d3.loss_mask: 0.4832, decode.d3.loss_dice: 0.6599, decode.d4.loss_cls: 0.2002, decode.d4.loss_mask: 0.4854, decode.d4.loss_dice: 0.6531, decode.d5.loss_cls: 0.1944, decode.d5.loss_mask: 0.4829, decode.d5.loss_dice: 0.6480, decode.d6.loss_cls: 0.1876, decode.d6.loss_mask: 0.4799, decode.d6.loss_dice: 0.6481, decode.d7.loss_cls: 0.1843, decode.d7.loss_mask: 0.4772, decode.d7.loss_dice: 0.6487, decode.d8.loss_cls: 0.1848, decode.d8.loss_mask: 0.4780, decode.d8.loss_dice: 0.6549, loss: 15.6457 +2022-05-06 04:18:32,475 - mmseg - INFO - Iter [15900/40000] lr: 8.651e-07, eta: 6:11:23, time: 0.722, data_time: 0.059, memory: 53770, decode.loss_cls: 0.2330, decode.loss_mask: 0.4845, decode.loss_dice: 0.6903, decode.d0.loss_cls: 2.2218, decode.d0.loss_mask: 0.5274, decode.d0.loss_dice: 0.8118, decode.d1.loss_cls: 0.3540, decode.d1.loss_mask: 0.5013, decode.d1.loss_dice: 0.7290, decode.d2.loss_cls: 0.2724, decode.d2.loss_mask: 0.4902, decode.d2.loss_dice: 0.7067, decode.d3.loss_cls: 0.2403, decode.d3.loss_mask: 0.4886, decode.d3.loss_dice: 0.6968, decode.d4.loss_cls: 0.2414, decode.d4.loss_mask: 0.4883, decode.d4.loss_dice: 0.6894, decode.d5.loss_cls: 0.2403, decode.d5.loss_mask: 0.4847, decode.d5.loss_dice: 0.6866, decode.d6.loss_cls: 0.2297, decode.d6.loss_mask: 0.4861, decode.d6.loss_dice: 0.6862, decode.d7.loss_cls: 0.2281, decode.d7.loss_mask: 0.4854, decode.d7.loss_dice: 0.6870, decode.d8.loss_cls: 0.2290, decode.d8.loss_mask: 0.4857, decode.d8.loss_dice: 0.6847, loss: 16.4810 +2022-05-06 04:19:06,216 - mmseg - INFO - Iter [15950/40000] lr: 8.633e-07, eta: 6:10:11, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2175, decode.loss_mask: 0.4948, decode.loss_dice: 0.6815, decode.d0.loss_cls: 2.1819, decode.d0.loss_mask: 0.5317, decode.d0.loss_dice: 0.8130, decode.d1.loss_cls: 0.3411, decode.d1.loss_mask: 0.5074, decode.d1.loss_dice: 0.7216, decode.d2.loss_cls: 0.2562, decode.d2.loss_mask: 0.4975, decode.d2.loss_dice: 0.6985, decode.d3.loss_cls: 0.2308, decode.d3.loss_mask: 0.4954, decode.d3.loss_dice: 0.6827, decode.d4.loss_cls: 0.2269, decode.d4.loss_mask: 0.4931, decode.d4.loss_dice: 0.6826, decode.d5.loss_cls: 0.2167, decode.d5.loss_mask: 0.4913, decode.d5.loss_dice: 0.6821, decode.d6.loss_cls: 0.2140, decode.d6.loss_mask: 0.4915, decode.d6.loss_dice: 0.6796, decode.d7.loss_cls: 0.2163, decode.d7.loss_mask: 0.4907, decode.d7.loss_dice: 0.6828, decode.d8.loss_cls: 0.2144, decode.d8.loss_mask: 0.4920, decode.d8.loss_dice: 0.6819, loss: 16.3077 +2022-05-06 04:19:39,765 - mmseg - INFO - Saving checkpoint at 16000 iterations +2022-05-06 04:20:04,696 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 04:20:04,702 - mmseg - INFO - Iter [16000/40000] lr: 8.615e-07, eta: 6:09:50, time: 1.168, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2093, decode.loss_mask: 0.4872, decode.loss_dice: 0.6788, decode.d0.loss_cls: 2.1714, decode.d0.loss_mask: 0.5215, decode.d0.loss_dice: 0.7968, decode.d1.loss_cls: 0.3088, decode.d1.loss_mask: 0.5045, decode.d1.loss_dice: 0.7290, decode.d2.loss_cls: 0.2566, decode.d2.loss_mask: 0.4930, decode.d2.loss_dice: 0.6971, decode.d3.loss_cls: 0.2334, decode.d3.loss_mask: 0.4851, decode.d3.loss_dice: 0.6841, decode.d4.loss_cls: 0.2171, decode.d4.loss_mask: 0.4882, decode.d4.loss_dice: 0.6843, decode.d5.loss_cls: 0.2166, decode.d5.loss_mask: 0.4867, decode.d5.loss_dice: 0.6754, decode.d6.loss_cls: 0.2124, decode.d6.loss_mask: 0.4875, decode.d6.loss_dice: 0.6725, decode.d7.loss_cls: 0.2122, decode.d7.loss_mask: 0.4867, decode.d7.loss_dice: 0.6748, decode.d8.loss_cls: 0.2109, decode.d8.loss_mask: 0.4853, decode.d8.loss_dice: 0.6792, loss: 16.1464 +2022-05-06 04:24:24,352 - mmseg - INFO - per class results: +2022-05-06 04:24:24,358 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.51 | 96.79 | +| bag | 50.01 | 77.27 | +| bed | 31.46 | 44.49 | +| bedclothes | 42.41 | 74.06 | +| bench | 25.97 | 33.97 | +| bicycle | 84.91 | 91.96 | +| bird | 95.04 | 97.62 | +| boat | 85.85 | 94.46 | +| book | 60.67 | 78.37 | +| bottle | 90.27 | 97.11 | +| building | 67.11 | 78.14 | +| bus | 95.5 | 97.25 | +| cabinet | 53.25 | 69.99 | +| car | 94.01 | 97.2 | +| cat | 94.59 | 97.27 | +| ceiling | 62.0 | 83.16 | +| chair | 65.41 | 82.1 | +| cloth | 20.8 | 24.26 | +| computer | 57.07 | 76.76 | +| cow | 96.19 | 97.75 | +| cup | 49.95 | 68.52 | +| curtain | 57.65 | 79.82 | +| dog | 93.0 | 97.51 | +| door | 40.65 | 60.19 | +| fence | 48.08 | 64.39 | +| floor | 75.02 | 86.49 | +| flower | 49.05 | 60.54 | +| food | 45.93 | 62.21 | +| grass | 82.63 | 91.28 | +| ground | 57.71 | 71.1 | +| horse | 95.13 | 97.65 | +| keyboard | 90.88 | 95.18 | +| light | 60.19 | 80.41 | +| motorbike | 91.62 | 96.71 | +| mountain | 55.6 | 71.44 | +| mouse | 86.65 | 92.8 | +| person | 90.56 | 94.2 | +| plate | 31.86 | 42.49 | +| platform | 49.29 | 63.27 | +| pottedplant | 83.52 | 91.89 | +| road | 55.71 | 74.02 | +| rock | 54.58 | 65.49 | +| sheep | 95.58 | 98.27 | +| shelves | 37.22 | 49.19 | +| sidewalk | 31.36 | 47.28 | +| sign | 53.2 | 66.96 | +| sky | 94.48 | 97.02 | +| snow | 80.98 | 91.78 | +| sofa | 60.2 | 78.79 | +| table | 70.91 | 83.08 | +| track | 72.48 | 82.87 | +| train | 93.26 | 97.68 | +| tree | 81.53 | 91.89 | +| truck | 52.34 | 66.73 | +| tvmonitor | 90.74 | 94.54 | +| wall | 73.1 | 83.49 | +| water | 92.02 | 96.64 | +| window | 42.63 | 57.91 | +| wood | 29.3 | 42.31 | ++-------------+-------+-------+ +2022-05-06 04:24:24,358 - mmseg - INFO - Summary: +2022-05-06 04:24:24,358 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.37 | 67.15 | 78.37 | ++-------+-------+-------+ +2022-05-06 04:24:24,375 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 04:24:24,376 - mmseg - INFO - Iter(val) [638] aAcc: 0.8637, mIoU: 0.6715, mAcc: 0.7837, IoU.aeroplane: 0.9251, IoU.bag: 0.5001, IoU.bed: 0.3146, IoU.bedclothes: 0.4241, IoU.bench: 0.2597, IoU.bicycle: 0.8491, IoU.bird: 0.9504, IoU.boat: 0.8585, IoU.book: 0.6067, IoU.bottle: 0.9027, IoU.building: 0.6711, IoU.bus: 0.9550, IoU.cabinet: 0.5325, IoU.car: 0.9401, IoU.cat: 0.9459, IoU.ceiling: 0.6200, IoU.chair: 0.6541, IoU.cloth: 0.2080, IoU.computer: 0.5707, IoU.cow: 0.9619, IoU.cup: 0.4995, IoU.curtain: 0.5765, IoU.dog: 0.9300, IoU.door: 0.4065, IoU.fence: 0.4808, IoU.floor: 0.7502, IoU.flower: 0.4905, IoU.food: 0.4593, IoU.grass: 0.8263, IoU.ground: 0.5771, IoU.horse: 0.9513, IoU.keyboard: 0.9088, IoU.light: 0.6019, IoU.motorbike: 0.9162, IoU.mountain: 0.5560, IoU.mouse: 0.8665, IoU.person: 0.9056, IoU.plate: 0.3186, IoU.platform: 0.4929, IoU.pottedplant: 0.8352, IoU.road: 0.5571, IoU.rock: 0.5458, IoU.sheep: 0.9558, IoU.shelves: 0.3722, IoU.sidewalk: 0.3136, IoU.sign: 0.5320, IoU.sky: 0.9448, IoU.snow: 0.8098, IoU.sofa: 0.6020, IoU.table: 0.7091, IoU.track: 0.7248, IoU.train: 0.9326, IoU.tree: 0.8153, IoU.truck: 0.5234, IoU.tvmonitor: 0.9074, IoU.wall: 0.7310, IoU.water: 0.9202, IoU.window: 0.4263, IoU.wood: 0.2930, Acc.aeroplane: 0.9679, Acc.bag: 0.7727, Acc.bed: 0.4449, Acc.bedclothes: 0.7406, Acc.bench: 0.3397, Acc.bicycle: 0.9196, Acc.bird: 0.9762, Acc.boat: 0.9446, Acc.book: 0.7837, Acc.bottle: 0.9711, Acc.building: 0.7814, Acc.bus: 0.9725, Acc.cabinet: 0.6999, Acc.car: 0.9720, Acc.cat: 0.9727, Acc.ceiling: 0.8316, Acc.chair: 0.8210, Acc.cloth: 0.2426, Acc.computer: 0.7676, Acc.cow: 0.9775, Acc.cup: 0.6852, Acc.curtain: 0.7982, Acc.dog: 0.9751, Acc.door: 0.6019, Acc.fence: 0.6439, Acc.floor: 0.8649, Acc.flower: 0.6054, Acc.food: 0.6221, Acc.grass: 0.9128, Acc.ground: 0.7110, Acc.horse: 0.9765, Acc.keyboard: 0.9518, Acc.light: 0.8041, Acc.motorbike: 0.9671, Acc.mountain: 0.7144, Acc.mouse: 0.9280, Acc.person: 0.9420, Acc.plate: 0.4249, Acc.platform: 0.6327, Acc.pottedplant: 0.9189, Acc.road: 0.7402, Acc.rock: 0.6549, Acc.sheep: 0.9827, Acc.shelves: 0.4919, Acc.sidewalk: 0.4728, Acc.sign: 0.6696, Acc.sky: 0.9702, Acc.snow: 0.9178, Acc.sofa: 0.7879, Acc.table: 0.8308, Acc.track: 0.8287, Acc.train: 0.9768, Acc.tree: 0.9189, Acc.truck: 0.6673, Acc.tvmonitor: 0.9454, Acc.wall: 0.8349, Acc.water: 0.9664, Acc.window: 0.5791, Acc.wood: 0.4231 +2022-05-06 04:24:58,663 - mmseg - INFO - Iter [16050/40000] lr: 8.597e-07, eta: 6:17:16, time: 5.881, data_time: 5.203, memory: 53770, decode.loss_cls: 0.2006, decode.loss_mask: 0.4897, decode.loss_dice: 0.6615, decode.d0.loss_cls: 2.1785, decode.d0.loss_mask: 0.5279, decode.d0.loss_dice: 0.7802, decode.d1.loss_cls: 0.3323, decode.d1.loss_mask: 0.5088, decode.d1.loss_dice: 0.7066, decode.d2.loss_cls: 0.2433, decode.d2.loss_mask: 0.4983, decode.d2.loss_dice: 0.6759, decode.d3.loss_cls: 0.2167, decode.d3.loss_mask: 0.4926, decode.d3.loss_dice: 0.6578, decode.d4.loss_cls: 0.2103, decode.d4.loss_mask: 0.4917, decode.d4.loss_dice: 0.6645, decode.d5.loss_cls: 0.2082, decode.d5.loss_mask: 0.4928, decode.d5.loss_dice: 0.6675, decode.d6.loss_cls: 0.2024, decode.d6.loss_mask: 0.4921, decode.d6.loss_dice: 0.6584, decode.d7.loss_cls: 0.1976, decode.d7.loss_mask: 0.4892, decode.d7.loss_dice: 0.6638, decode.d8.loss_cls: 0.2028, decode.d8.loss_mask: 0.4909, decode.d8.loss_dice: 0.6628, loss: 15.9660 +2022-05-06 04:25:32,377 - mmseg - INFO - Iter [16100/40000] lr: 8.579e-07, eta: 6:16:02, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2130, decode.loss_mask: 0.4957, decode.loss_dice: 0.6789, decode.d0.loss_cls: 2.1638, decode.d0.loss_mask: 0.5328, decode.d0.loss_dice: 0.7962, decode.d1.loss_cls: 0.3624, decode.d1.loss_mask: 0.5127, decode.d1.loss_dice: 0.7212, decode.d2.loss_cls: 0.2751, decode.d2.loss_mask: 0.5034, decode.d2.loss_dice: 0.6956, decode.d3.loss_cls: 0.2372, decode.d3.loss_mask: 0.4988, decode.d3.loss_dice: 0.6831, decode.d4.loss_cls: 0.2302, decode.d4.loss_mask: 0.4968, decode.d4.loss_dice: 0.6892, decode.d5.loss_cls: 0.2271, decode.d5.loss_mask: 0.4932, decode.d5.loss_dice: 0.6793, decode.d6.loss_cls: 0.2184, decode.d6.loss_mask: 0.4960, decode.d6.loss_dice: 0.6792, decode.d7.loss_cls: 0.2182, decode.d7.loss_mask: 0.4961, decode.d7.loss_dice: 0.6780, decode.d8.loss_cls: 0.2173, decode.d8.loss_mask: 0.4933, decode.d8.loss_dice: 0.6766, loss: 16.3587 +2022-05-06 04:26:06,094 - mmseg - INFO - Iter [16150/40000] lr: 8.561e-07, eta: 6:14:48, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2126, decode.loss_mask: 0.4779, decode.loss_dice: 0.6369, decode.d0.loss_cls: 2.1749, decode.d0.loss_mask: 0.5193, decode.d0.loss_dice: 0.7634, decode.d1.loss_cls: 0.3418, decode.d1.loss_mask: 0.4908, decode.d1.loss_dice: 0.6864, decode.d2.loss_cls: 0.2621, decode.d2.loss_mask: 0.4839, decode.d2.loss_dice: 0.6578, decode.d3.loss_cls: 0.2290, decode.d3.loss_mask: 0.4826, decode.d3.loss_dice: 0.6402, decode.d4.loss_cls: 0.2205, decode.d4.loss_mask: 0.4780, decode.d4.loss_dice: 0.6393, decode.d5.loss_cls: 0.2228, decode.d5.loss_mask: 0.4752, decode.d5.loss_dice: 0.6387, decode.d6.loss_cls: 0.2099, decode.d6.loss_mask: 0.4770, decode.d6.loss_dice: 0.6388, decode.d7.loss_cls: 0.2035, decode.d7.loss_mask: 0.4783, decode.d7.loss_dice: 0.6416, decode.d8.loss_cls: 0.2074, decode.d8.loss_mask: 0.4813, decode.d8.loss_dice: 0.6397, loss: 15.7115 +2022-05-06 04:26:42,356 - mmseg - INFO - Iter [16200/40000] lr: 8.543e-07, eta: 6:13:40, time: 0.725, data_time: 0.061, memory: 53770, decode.loss_cls: 0.1795, decode.loss_mask: 0.4649, decode.loss_dice: 0.6444, decode.d0.loss_cls: 2.1539, decode.d0.loss_mask: 0.4923, decode.d0.loss_dice: 0.7527, decode.d1.loss_cls: 0.3018, decode.d1.loss_mask: 0.4762, decode.d1.loss_dice: 0.6827, decode.d2.loss_cls: 0.2170, decode.d2.loss_mask: 0.4679, decode.d2.loss_dice: 0.6565, decode.d3.loss_cls: 0.1926, decode.d3.loss_mask: 0.4663, decode.d3.loss_dice: 0.6509, decode.d4.loss_cls: 0.1851, decode.d4.loss_mask: 0.4655, decode.d4.loss_dice: 0.6520, decode.d5.loss_cls: 0.1791, decode.d5.loss_mask: 0.4659, decode.d5.loss_dice: 0.6454, decode.d6.loss_cls: 0.1763, decode.d6.loss_mask: 0.4639, decode.d6.loss_dice: 0.6470, decode.d7.loss_cls: 0.1778, decode.d7.loss_mask: 0.4644, decode.d7.loss_dice: 0.6419, decode.d8.loss_cls: 0.1728, decode.d8.loss_mask: 0.4641, decode.d8.loss_dice: 0.6408, loss: 15.2419 +2022-05-06 04:27:16,028 - mmseg - INFO - Iter [16250/40000] lr: 8.525e-07, eta: 6:12:27, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1970, decode.loss_mask: 0.4945, decode.loss_dice: 0.6661, decode.d0.loss_cls: 2.1193, decode.d0.loss_mask: 0.5435, decode.d0.loss_dice: 0.7899, decode.d1.loss_cls: 0.3330, decode.d1.loss_mask: 0.5153, decode.d1.loss_dice: 0.7178, decode.d2.loss_cls: 0.2547, decode.d2.loss_mask: 0.5005, decode.d2.loss_dice: 0.6831, decode.d3.loss_cls: 0.2211, decode.d3.loss_mask: 0.5005, decode.d3.loss_dice: 0.6751, decode.d4.loss_cls: 0.2107, decode.d4.loss_mask: 0.4969, decode.d4.loss_dice: 0.6767, decode.d5.loss_cls: 0.2022, decode.d5.loss_mask: 0.4994, decode.d5.loss_dice: 0.6738, decode.d6.loss_cls: 0.1994, decode.d6.loss_mask: 0.4959, decode.d6.loss_dice: 0.6693, decode.d7.loss_cls: 0.2006, decode.d7.loss_mask: 0.4957, decode.d7.loss_dice: 0.6674, decode.d8.loss_cls: 0.2004, decode.d8.loss_mask: 0.4954, decode.d8.loss_dice: 0.6646, loss: 16.0598 +2022-05-06 04:27:49,821 - mmseg - INFO - Iter [16300/40000] lr: 8.507e-07, eta: 6:11:14, time: 0.676, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1981, decode.loss_mask: 0.4766, decode.loss_dice: 0.6686, decode.d0.loss_cls: 2.1254, decode.d0.loss_mask: 0.5090, decode.d0.loss_dice: 0.7821, decode.d1.loss_cls: 0.3035, decode.d1.loss_mask: 0.4869, decode.d1.loss_dice: 0.7110, decode.d2.loss_cls: 0.2367, decode.d2.loss_mask: 0.4749, decode.d2.loss_dice: 0.6791, decode.d3.loss_cls: 0.2137, decode.d3.loss_mask: 0.4713, decode.d3.loss_dice: 0.6762, decode.d4.loss_cls: 0.2039, decode.d4.loss_mask: 0.4732, decode.d4.loss_dice: 0.6768, decode.d5.loss_cls: 0.2032, decode.d5.loss_mask: 0.4717, decode.d5.loss_dice: 0.6701, decode.d6.loss_cls: 0.1971, decode.d6.loss_mask: 0.4759, decode.d6.loss_dice: 0.6665, decode.d7.loss_cls: 0.1966, decode.d7.loss_mask: 0.4744, decode.d7.loss_dice: 0.6660, decode.d8.loss_cls: 0.1953, decode.d8.loss_mask: 0.4751, decode.d8.loss_dice: 0.6661, loss: 15.7250 +2022-05-06 04:28:23,836 - mmseg - INFO - Iter [16350/40000] lr: 8.490e-07, eta: 6:10:02, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2199, decode.loss_mask: 0.4545, decode.loss_dice: 0.6539, decode.d0.loss_cls: 2.1751, decode.d0.loss_mask: 0.4866, decode.d0.loss_dice: 0.7821, decode.d1.loss_cls: 0.3486, decode.d1.loss_mask: 0.4693, decode.d1.loss_dice: 0.6949, decode.d2.loss_cls: 0.2638, decode.d2.loss_mask: 0.4600, decode.d2.loss_dice: 0.6696, decode.d3.loss_cls: 0.2374, decode.d3.loss_mask: 0.4565, decode.d3.loss_dice: 0.6620, decode.d4.loss_cls: 0.2308, decode.d4.loss_mask: 0.4578, decode.d4.loss_dice: 0.6607, decode.d5.loss_cls: 0.2280, decode.d5.loss_mask: 0.4542, decode.d5.loss_dice: 0.6588, decode.d6.loss_cls: 0.2197, decode.d6.loss_mask: 0.4533, decode.d6.loss_dice: 0.6557, decode.d7.loss_cls: 0.2217, decode.d7.loss_mask: 0.4539, decode.d7.loss_dice: 0.6618, decode.d8.loss_cls: 0.2190, decode.d8.loss_mask: 0.4536, decode.d8.loss_dice: 0.6536, loss: 15.7165 +2022-05-06 04:28:57,670 - mmseg - INFO - Iter [16400/40000] lr: 8.472e-07, eta: 6:08:50, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2179, decode.loss_mask: 0.4934, decode.loss_dice: 0.6656, decode.d0.loss_cls: 2.1505, decode.d0.loss_mask: 0.5310, decode.d0.loss_dice: 0.7951, decode.d1.loss_cls: 0.3410, decode.d1.loss_mask: 0.5107, decode.d1.loss_dice: 0.7202, decode.d2.loss_cls: 0.2634, decode.d2.loss_mask: 0.4981, decode.d2.loss_dice: 0.6937, decode.d3.loss_cls: 0.2375, decode.d3.loss_mask: 0.4971, decode.d3.loss_dice: 0.6805, decode.d4.loss_cls: 0.2288, decode.d4.loss_mask: 0.4932, decode.d4.loss_dice: 0.6756, decode.d5.loss_cls: 0.2210, decode.d5.loss_mask: 0.4932, decode.d5.loss_dice: 0.6686, decode.d6.loss_cls: 0.2196, decode.d6.loss_mask: 0.4915, decode.d6.loss_dice: 0.6677, decode.d7.loss_cls: 0.2173, decode.d7.loss_mask: 0.4927, decode.d7.loss_dice: 0.6753, decode.d8.loss_cls: 0.2098, decode.d8.loss_mask: 0.4921, decode.d8.loss_dice: 0.6681, loss: 16.2105 +2022-05-06 04:29:31,133 - mmseg - INFO - Iter [16450/40000] lr: 8.454e-07, eta: 6:07:38, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2083, decode.loss_mask: 0.4834, decode.loss_dice: 0.6676, decode.d0.loss_cls: 2.1125, decode.d0.loss_mask: 0.5217, decode.d0.loss_dice: 0.7805, decode.d1.loss_cls: 0.3306, decode.d1.loss_mask: 0.4977, decode.d1.loss_dice: 0.7088, decode.d2.loss_cls: 0.2443, decode.d2.loss_mask: 0.4891, decode.d2.loss_dice: 0.6729, decode.d3.loss_cls: 0.2275, decode.d3.loss_mask: 0.4872, decode.d3.loss_dice: 0.6624, decode.d4.loss_cls: 0.2211, decode.d4.loss_mask: 0.4849, decode.d4.loss_dice: 0.6607, decode.d5.loss_cls: 0.2130, decode.d5.loss_mask: 0.4867, decode.d5.loss_dice: 0.6606, decode.d6.loss_cls: 0.2119, decode.d6.loss_mask: 0.4838, decode.d6.loss_dice: 0.6602, decode.d7.loss_cls: 0.2067, decode.d7.loss_mask: 0.4850, decode.d7.loss_dice: 0.6585, decode.d8.loss_cls: 0.2022, decode.d8.loss_mask: 0.4841, decode.d8.loss_dice: 0.6637, loss: 15.8775 +2022-05-06 04:30:07,599 - mmseg - INFO - Iter [16500/40000] lr: 8.436e-07, eta: 6:06:32, time: 0.729, data_time: 0.059, memory: 53770, decode.loss_cls: 0.2115, decode.loss_mask: 0.4780, decode.loss_dice: 0.6721, decode.d0.loss_cls: 2.1352, decode.d0.loss_mask: 0.5182, decode.d0.loss_dice: 0.8017, decode.d1.loss_cls: 0.3490, decode.d1.loss_mask: 0.4913, decode.d1.loss_dice: 0.7109, decode.d2.loss_cls: 0.2657, decode.d2.loss_mask: 0.4796, decode.d2.loss_dice: 0.6892, decode.d3.loss_cls: 0.2374, decode.d3.loss_mask: 0.4789, decode.d3.loss_dice: 0.6731, decode.d4.loss_cls: 0.2262, decode.d4.loss_mask: 0.4790, decode.d4.loss_dice: 0.6777, decode.d5.loss_cls: 0.2151, decode.d5.loss_mask: 0.4811, decode.d5.loss_dice: 0.6714, decode.d6.loss_cls: 0.2167, decode.d6.loss_mask: 0.4764, decode.d6.loss_dice: 0.6684, decode.d7.loss_cls: 0.2149, decode.d7.loss_mask: 0.4755, decode.d7.loss_dice: 0.6699, decode.d8.loss_cls: 0.2068, decode.d8.loss_mask: 0.4785, decode.d8.loss_dice: 0.6733, loss: 16.0224 +2022-05-06 04:30:40,852 - mmseg - INFO - Iter [16550/40000] lr: 8.418e-07, eta: 6:05:20, time: 0.665, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1983, decode.loss_mask: 0.4803, decode.loss_dice: 0.6619, decode.d0.loss_cls: 2.1157, decode.d0.loss_mask: 0.5204, decode.d0.loss_dice: 0.7850, decode.d1.loss_cls: 0.3363, decode.d1.loss_mask: 0.4919, decode.d1.loss_dice: 0.7052, decode.d2.loss_cls: 0.2613, decode.d2.loss_mask: 0.4847, decode.d2.loss_dice: 0.6748, decode.d3.loss_cls: 0.2250, decode.d3.loss_mask: 0.4826, decode.d3.loss_dice: 0.6662, decode.d4.loss_cls: 0.2169, decode.d4.loss_mask: 0.4797, decode.d4.loss_dice: 0.6644, decode.d5.loss_cls: 0.2109, decode.d5.loss_mask: 0.4789, decode.d5.loss_dice: 0.6569, decode.d6.loss_cls: 0.2060, decode.d6.loss_mask: 0.4783, decode.d6.loss_dice: 0.6605, decode.d7.loss_cls: 0.2042, decode.d7.loss_mask: 0.4778, decode.d7.loss_dice: 0.6602, decode.d8.loss_cls: 0.1996, decode.d8.loss_mask: 0.4785, decode.d8.loss_dice: 0.6621, loss: 15.8244 +2022-05-06 04:31:14,215 - mmseg - INFO - Iter [16600/40000] lr: 8.400e-07, eta: 6:04:08, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2005, decode.loss_mask: 0.4630, decode.loss_dice: 0.6512, decode.d0.loss_cls: 2.1171, decode.d0.loss_mask: 0.4982, decode.d0.loss_dice: 0.7705, decode.d1.loss_cls: 0.3370, decode.d1.loss_mask: 0.4740, decode.d1.loss_dice: 0.6939, decode.d2.loss_cls: 0.2575, decode.d2.loss_mask: 0.4643, decode.d2.loss_dice: 0.6600, decode.d3.loss_cls: 0.2239, decode.d3.loss_mask: 0.4615, decode.d3.loss_dice: 0.6518, decode.d4.loss_cls: 0.2175, decode.d4.loss_mask: 0.4611, decode.d4.loss_dice: 0.6514, decode.d5.loss_cls: 0.2106, decode.d5.loss_mask: 0.4619, decode.d5.loss_dice: 0.6521, decode.d6.loss_cls: 0.2048, decode.d6.loss_mask: 0.4612, decode.d6.loss_dice: 0.6504, decode.d7.loss_cls: 0.1974, decode.d7.loss_mask: 0.4642, decode.d7.loss_dice: 0.6519, decode.d8.loss_cls: 0.2078, decode.d8.loss_mask: 0.4648, decode.d8.loss_dice: 0.6521, loss: 15.5337 +2022-05-06 04:31:47,707 - mmseg - INFO - Iter [16650/40000] lr: 8.382e-07, eta: 6:02:57, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1973, decode.loss_mask: 0.4740, decode.loss_dice: 0.6684, decode.d0.loss_cls: 2.1032, decode.d0.loss_mask: 0.5113, decode.d0.loss_dice: 0.7853, decode.d1.loss_cls: 0.3195, decode.d1.loss_mask: 0.4906, decode.d1.loss_dice: 0.7077, decode.d2.loss_cls: 0.2425, decode.d2.loss_mask: 0.4791, decode.d2.loss_dice: 0.6845, decode.d3.loss_cls: 0.2173, decode.d3.loss_mask: 0.4743, decode.d3.loss_dice: 0.6739, decode.d4.loss_cls: 0.2107, decode.d4.loss_mask: 0.4722, decode.d4.loss_dice: 0.6742, decode.d5.loss_cls: 0.2043, decode.d5.loss_mask: 0.4712, decode.d5.loss_dice: 0.6691, decode.d6.loss_cls: 0.1986, decode.d6.loss_mask: 0.4710, decode.d6.loss_dice: 0.6691, decode.d7.loss_cls: 0.2012, decode.d7.loss_mask: 0.4708, decode.d7.loss_dice: 0.6648, decode.d8.loss_cls: 0.2016, decode.d8.loss_mask: 0.4737, decode.d8.loss_dice: 0.6701, loss: 15.7513 +2022-05-06 04:32:21,109 - mmseg - INFO - Iter [16700/40000] lr: 8.364e-07, eta: 6:01:46, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1919, decode.loss_mask: 0.4682, decode.loss_dice: 0.6567, decode.d0.loss_cls: 2.0484, decode.d0.loss_mask: 0.5150, decode.d0.loss_dice: 0.7753, decode.d1.loss_cls: 0.3142, decode.d1.loss_mask: 0.4858, decode.d1.loss_dice: 0.7017, decode.d2.loss_cls: 0.2397, decode.d2.loss_mask: 0.4734, decode.d2.loss_dice: 0.6755, decode.d3.loss_cls: 0.2160, decode.d3.loss_mask: 0.4701, decode.d3.loss_dice: 0.6602, decode.d4.loss_cls: 0.2010, decode.d4.loss_mask: 0.4711, decode.d4.loss_dice: 0.6630, decode.d5.loss_cls: 0.1937, decode.d5.loss_mask: 0.4691, decode.d5.loss_dice: 0.6598, decode.d6.loss_cls: 0.1919, decode.d6.loss_mask: 0.4682, decode.d6.loss_dice: 0.6551, decode.d7.loss_cls: 0.1927, decode.d7.loss_mask: 0.4693, decode.d7.loss_dice: 0.6534, decode.d8.loss_cls: 0.1886, decode.d8.loss_mask: 0.4694, decode.d8.loss_dice: 0.6589, loss: 15.4973 +2022-05-06 04:32:54,545 - mmseg - INFO - Iter [16750/40000] lr: 8.346e-07, eta: 6:00:36, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2011, decode.loss_mask: 0.4935, decode.loss_dice: 0.6498, decode.d0.loss_cls: 2.0558, decode.d0.loss_mask: 0.5357, decode.d0.loss_dice: 0.7847, decode.d1.loss_cls: 0.3241, decode.d1.loss_mask: 0.5118, decode.d1.loss_dice: 0.7014, decode.d2.loss_cls: 0.2460, decode.d2.loss_mask: 0.5001, decode.d2.loss_dice: 0.6698, decode.d3.loss_cls: 0.2151, decode.d3.loss_mask: 0.4936, decode.d3.loss_dice: 0.6624, decode.d4.loss_cls: 0.2098, decode.d4.loss_mask: 0.4946, decode.d4.loss_dice: 0.6613, decode.d5.loss_cls: 0.2059, decode.d5.loss_mask: 0.4919, decode.d5.loss_dice: 0.6555, decode.d6.loss_cls: 0.1983, decode.d6.loss_mask: 0.4936, decode.d6.loss_dice: 0.6550, decode.d7.loss_cls: 0.2023, decode.d7.loss_mask: 0.4913, decode.d7.loss_dice: 0.6523, decode.d8.loss_cls: 0.2051, decode.d8.loss_mask: 0.4907, decode.d8.loss_dice: 0.6524, loss: 15.8050 +2022-05-06 04:33:30,983 - mmseg - INFO - Iter [16800/40000] lr: 8.328e-07, eta: 5:59:31, time: 0.729, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1996, decode.loss_mask: 0.4763, decode.loss_dice: 0.6478, decode.d0.loss_cls: 2.1005, decode.d0.loss_mask: 0.5248, decode.d0.loss_dice: 0.7636, decode.d1.loss_cls: 0.3322, decode.d1.loss_mask: 0.4939, decode.d1.loss_dice: 0.6897, decode.d2.loss_cls: 0.2521, decode.d2.loss_mask: 0.4850, decode.d2.loss_dice: 0.6624, decode.d3.loss_cls: 0.2215, decode.d3.loss_mask: 0.4801, decode.d3.loss_dice: 0.6544, decode.d4.loss_cls: 0.2145, decode.d4.loss_mask: 0.4766, decode.d4.loss_dice: 0.6514, decode.d5.loss_cls: 0.2035, decode.d5.loss_mask: 0.4775, decode.d5.loss_dice: 0.6516, decode.d6.loss_cls: 0.1953, decode.d6.loss_mask: 0.4743, decode.d6.loss_dice: 0.6478, decode.d7.loss_cls: 0.1945, decode.d7.loss_mask: 0.4750, decode.d7.loss_dice: 0.6463, decode.d8.loss_cls: 0.1957, decode.d8.loss_mask: 0.4758, decode.d8.loss_dice: 0.6479, loss: 15.6119 +2022-05-06 04:34:05,109 - mmseg - INFO - Iter [16850/40000] lr: 8.310e-07, eta: 5:58:22, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1867, decode.loss_mask: 0.4577, decode.loss_dice: 0.6451, decode.d0.loss_cls: 2.0566, decode.d0.loss_mask: 0.4989, decode.d0.loss_dice: 0.7661, decode.d1.loss_cls: 0.3238, decode.d1.loss_mask: 0.4743, decode.d1.loss_dice: 0.6859, decode.d2.loss_cls: 0.2360, decode.d2.loss_mask: 0.4657, decode.d2.loss_dice: 0.6611, decode.d3.loss_cls: 0.2025, decode.d3.loss_mask: 0.4606, decode.d3.loss_dice: 0.6466, decode.d4.loss_cls: 0.1982, decode.d4.loss_mask: 0.4612, decode.d4.loss_dice: 0.6455, decode.d5.loss_cls: 0.1930, decode.d5.loss_mask: 0.4589, decode.d5.loss_dice: 0.6454, decode.d6.loss_cls: 0.1902, decode.d6.loss_mask: 0.4585, decode.d6.loss_dice: 0.6462, decode.d7.loss_cls: 0.1846, decode.d7.loss_mask: 0.4587, decode.d7.loss_dice: 0.6474, decode.d8.loss_cls: 0.1919, decode.d8.loss_mask: 0.4579, decode.d8.loss_dice: 0.6453, loss: 15.2506 +2022-05-06 04:34:38,630 - mmseg - INFO - Iter [16900/40000] lr: 8.292e-07, eta: 5:57:12, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1974, decode.loss_mask: 0.4449, decode.loss_dice: 0.6561, decode.d0.loss_cls: 2.1085, decode.d0.loss_mask: 0.4841, decode.d0.loss_dice: 0.7831, decode.d1.loss_cls: 0.3306, decode.d1.loss_mask: 0.4645, decode.d1.loss_dice: 0.7001, decode.d2.loss_cls: 0.2545, decode.d2.loss_mask: 0.4571, decode.d2.loss_dice: 0.6770, decode.d3.loss_cls: 0.2161, decode.d3.loss_mask: 0.4525, decode.d3.loss_dice: 0.6652, decode.d4.loss_cls: 0.2001, decode.d4.loss_mask: 0.4497, decode.d4.loss_dice: 0.6661, decode.d5.loss_cls: 0.1966, decode.d5.loss_mask: 0.4508, decode.d5.loss_dice: 0.6645, decode.d6.loss_cls: 0.1902, decode.d6.loss_mask: 0.4464, decode.d6.loss_dice: 0.6616, decode.d7.loss_cls: 0.1927, decode.d7.loss_mask: 0.4470, decode.d7.loss_dice: 0.6610, decode.d8.loss_cls: 0.1955, decode.d8.loss_mask: 0.4469, decode.d8.loss_dice: 0.6580, loss: 15.4187 +2022-05-06 04:35:11,949 - mmseg - INFO - Iter [16950/40000] lr: 8.274e-07, eta: 5:56:03, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1904, decode.loss_mask: 0.4494, decode.loss_dice: 0.6501, decode.d0.loss_cls: 2.0764, decode.d0.loss_mask: 0.4861, decode.d0.loss_dice: 0.7671, decode.d1.loss_cls: 0.3215, decode.d1.loss_mask: 0.4737, decode.d1.loss_dice: 0.6993, decode.d2.loss_cls: 0.2438, decode.d2.loss_mask: 0.4589, decode.d2.loss_dice: 0.6676, decode.d3.loss_cls: 0.2139, decode.d3.loss_mask: 0.4520, decode.d3.loss_dice: 0.6554, decode.d4.loss_cls: 0.2063, decode.d4.loss_mask: 0.4503, decode.d4.loss_dice: 0.6600, decode.d5.loss_cls: 0.1995, decode.d5.loss_mask: 0.4489, decode.d5.loss_dice: 0.6574, decode.d6.loss_cls: 0.1908, decode.d6.loss_mask: 0.4537, decode.d6.loss_dice: 0.6536, decode.d7.loss_cls: 0.1906, decode.d7.loss_mask: 0.4490, decode.d7.loss_dice: 0.6502, decode.d8.loss_cls: 0.1949, decode.d8.loss_mask: 0.4493, decode.d8.loss_dice: 0.6560, loss: 15.3161 +2022-05-06 04:35:45,470 - mmseg - INFO - Saving checkpoint at 17000 iterations +2022-05-06 04:36:11,432 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 04:36:11,439 - mmseg - INFO - Iter [17000/40000] lr: 8.256e-07, eta: 5:55:39, time: 1.187, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1981, decode.loss_mask: 0.4857, decode.loss_dice: 0.6555, decode.d0.loss_cls: 2.0445, decode.d0.loss_mask: 0.5288, decode.d0.loss_dice: 0.7625, decode.d1.loss_cls: 0.3081, decode.d1.loss_mask: 0.5014, decode.d1.loss_dice: 0.6979, decode.d2.loss_cls: 0.2451, decode.d2.loss_mask: 0.4918, decode.d2.loss_dice: 0.6733, decode.d3.loss_cls: 0.2160, decode.d3.loss_mask: 0.4901, decode.d3.loss_dice: 0.6596, decode.d4.loss_cls: 0.2060, decode.d4.loss_mask: 0.4880, decode.d4.loss_dice: 0.6601, decode.d5.loss_cls: 0.2011, decode.d5.loss_mask: 0.4863, decode.d5.loss_dice: 0.6597, decode.d6.loss_cls: 0.1975, decode.d6.loss_mask: 0.4863, decode.d6.loss_dice: 0.6585, decode.d7.loss_cls: 0.1967, decode.d7.loss_mask: 0.4852, decode.d7.loss_dice: 0.6539, decode.d8.loss_cls: 0.2010, decode.d8.loss_mask: 0.4865, decode.d8.loss_dice: 0.6594, loss: 15.6847 +2022-05-06 04:36:45,947 - mmseg - INFO - Iter [17050/40000] lr: 8.238e-07, eta: 5:54:32, time: 0.693, data_time: 0.011, memory: 53770, decode.loss_cls: 0.2083, decode.loss_mask: 0.4884, decode.loss_dice: 0.6942, decode.d0.loss_cls: 2.0702, decode.d0.loss_mask: 0.5355, decode.d0.loss_dice: 0.8087, decode.d1.loss_cls: 0.3530, decode.d1.loss_mask: 0.5073, decode.d1.loss_dice: 0.7289, decode.d2.loss_cls: 0.2622, decode.d2.loss_mask: 0.4975, decode.d2.loss_dice: 0.7080, decode.d3.loss_cls: 0.2297, decode.d3.loss_mask: 0.4958, decode.d3.loss_dice: 0.6966, decode.d4.loss_cls: 0.2240, decode.d4.loss_mask: 0.4926, decode.d4.loss_dice: 0.6945, decode.d5.loss_cls: 0.2150, decode.d5.loss_mask: 0.4901, decode.d5.loss_dice: 0.6977, decode.d6.loss_cls: 0.2048, decode.d6.loss_mask: 0.4892, decode.d6.loss_dice: 0.6987, decode.d7.loss_cls: 0.2051, decode.d7.loss_mask: 0.4897, decode.d7.loss_dice: 0.6981, decode.d8.loss_cls: 0.2063, decode.d8.loss_mask: 0.4873, decode.d8.loss_dice: 0.6930, loss: 16.2704 +2022-05-06 04:37:20,011 - mmseg - INFO - Iter [17100/40000] lr: 8.220e-07, eta: 5:53:25, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1918, decode.loss_mask: 0.4849, decode.loss_dice: 0.6290, decode.d0.loss_cls: 2.0000, decode.d0.loss_mask: 0.5293, decode.d0.loss_dice: 0.7480, decode.d1.loss_cls: 0.3109, decode.d1.loss_mask: 0.5035, decode.d1.loss_dice: 0.6762, decode.d2.loss_cls: 0.2471, decode.d2.loss_mask: 0.4891, decode.d2.loss_dice: 0.6500, decode.d3.loss_cls: 0.2098, decode.d3.loss_mask: 0.4850, decode.d3.loss_dice: 0.6438, decode.d4.loss_cls: 0.1973, decode.d4.loss_mask: 0.4832, decode.d4.loss_dice: 0.6440, decode.d5.loss_cls: 0.2035, decode.d5.loss_mask: 0.4816, decode.d5.loss_dice: 0.6370, decode.d6.loss_cls: 0.1931, decode.d6.loss_mask: 0.4839, decode.d6.loss_dice: 0.6326, decode.d7.loss_cls: 0.1910, decode.d7.loss_mask: 0.4863, decode.d7.loss_dice: 0.6370, decode.d8.loss_cls: 0.1898, decode.d8.loss_mask: 0.4835, decode.d8.loss_dice: 0.6363, loss: 15.3785 +2022-05-06 04:37:56,205 - mmseg - INFO - Iter [17150/40000] lr: 8.202e-07, eta: 5:52:21, time: 0.724, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1802, decode.loss_mask: 0.4875, decode.loss_dice: 0.6639, decode.d0.loss_cls: 2.0498, decode.d0.loss_mask: 0.5242, decode.d0.loss_dice: 0.7695, decode.d1.loss_cls: 0.2974, decode.d1.loss_mask: 0.4994, decode.d1.loss_dice: 0.6981, decode.d2.loss_cls: 0.2382, decode.d2.loss_mask: 0.4909, decode.d2.loss_dice: 0.6749, decode.d3.loss_cls: 0.2027, decode.d3.loss_mask: 0.4861, decode.d3.loss_dice: 0.6664, decode.d4.loss_cls: 0.1976, decode.d4.loss_mask: 0.4863, decode.d4.loss_dice: 0.6749, decode.d5.loss_cls: 0.1854, decode.d5.loss_mask: 0.4868, decode.d5.loss_dice: 0.6721, decode.d6.loss_cls: 0.1821, decode.d6.loss_mask: 0.4842, decode.d6.loss_dice: 0.6668, decode.d7.loss_cls: 0.1764, decode.d7.loss_mask: 0.4842, decode.d7.loss_dice: 0.6658, decode.d8.loss_cls: 0.1783, decode.d8.loss_mask: 0.4835, decode.d8.loss_dice: 0.6652, loss: 15.6190 +2022-05-06 04:38:29,769 - mmseg - INFO - Iter [17200/40000] lr: 8.184e-07, eta: 5:51:13, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1796, decode.loss_mask: 0.4615, decode.loss_dice: 0.6227, decode.d0.loss_cls: 1.9962, decode.d0.loss_mask: 0.4997, decode.d0.loss_dice: 0.7451, decode.d1.loss_cls: 0.3032, decode.d1.loss_mask: 0.4732, decode.d1.loss_dice: 0.6599, decode.d2.loss_cls: 0.2329, decode.d2.loss_mask: 0.4651, decode.d2.loss_dice: 0.6427, decode.d3.loss_cls: 0.2062, decode.d3.loss_mask: 0.4599, decode.d3.loss_dice: 0.6286, decode.d4.loss_cls: 0.1936, decode.d4.loss_mask: 0.4605, decode.d4.loss_dice: 0.6275, decode.d5.loss_cls: 0.1894, decode.d5.loss_mask: 0.4606, decode.d5.loss_dice: 0.6248, decode.d6.loss_cls: 0.1827, decode.d6.loss_mask: 0.4586, decode.d6.loss_dice: 0.6224, decode.d7.loss_cls: 0.1806, decode.d7.loss_mask: 0.4599, decode.d7.loss_dice: 0.6223, decode.d8.loss_cls: 0.1815, decode.d8.loss_mask: 0.4578, decode.d8.loss_dice: 0.6241, loss: 14.9227 +2022-05-06 04:39:03,617 - mmseg - INFO - Iter [17250/40000] lr: 8.166e-07, eta: 5:50:05, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1961, decode.loss_mask: 0.4738, decode.loss_dice: 0.6558, decode.d0.loss_cls: 2.0272, decode.d0.loss_mask: 0.5127, decode.d0.loss_dice: 0.7745, decode.d1.loss_cls: 0.3036, decode.d1.loss_mask: 0.4887, decode.d1.loss_dice: 0.7006, decode.d2.loss_cls: 0.2359, decode.d2.loss_mask: 0.4774, decode.d2.loss_dice: 0.6817, decode.d3.loss_cls: 0.2066, decode.d3.loss_mask: 0.4761, decode.d3.loss_dice: 0.6635, decode.d4.loss_cls: 0.2039, decode.d4.loss_mask: 0.4750, decode.d4.loss_dice: 0.6667, decode.d5.loss_cls: 0.2007, decode.d5.loss_mask: 0.4746, decode.d5.loss_dice: 0.6645, decode.d6.loss_cls: 0.1960, decode.d6.loss_mask: 0.4733, decode.d6.loss_dice: 0.6593, decode.d7.loss_cls: 0.1925, decode.d7.loss_mask: 0.4728, decode.d7.loss_dice: 0.6628, decode.d8.loss_cls: 0.1957, decode.d8.loss_mask: 0.4744, decode.d8.loss_dice: 0.6593, loss: 15.5457 +2022-05-06 04:39:37,296 - mmseg - INFO - Iter [17300/40000] lr: 8.149e-07, eta: 5:48:58, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1835, decode.loss_mask: 0.4629, decode.loss_dice: 0.6608, decode.d0.loss_cls: 2.0262, decode.d0.loss_mask: 0.5027, decode.d0.loss_dice: 0.7819, decode.d1.loss_cls: 0.3152, decode.d1.loss_mask: 0.4778, decode.d1.loss_dice: 0.7049, decode.d2.loss_cls: 0.2249, decode.d2.loss_mask: 0.4726, decode.d2.loss_dice: 0.6832, decode.d3.loss_cls: 0.1979, decode.d3.loss_mask: 0.4672, decode.d3.loss_dice: 0.6654, decode.d4.loss_cls: 0.1908, decode.d4.loss_mask: 0.4625, decode.d4.loss_dice: 0.6649, decode.d5.loss_cls: 0.1784, decode.d5.loss_mask: 0.4634, decode.d5.loss_dice: 0.6663, decode.d6.loss_cls: 0.1752, decode.d6.loss_mask: 0.4616, decode.d6.loss_dice: 0.6592, decode.d7.loss_cls: 0.1815, decode.d7.loss_mask: 0.4623, decode.d7.loss_dice: 0.6591, decode.d8.loss_cls: 0.1836, decode.d8.loss_mask: 0.4649, decode.d8.loss_dice: 0.6607, loss: 15.3616 +2022-05-06 04:40:11,170 - mmseg - INFO - Iter [17350/40000] lr: 8.131e-07, eta: 5:47:51, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.2008, decode.loss_mask: 0.4742, decode.loss_dice: 0.6511, decode.d0.loss_cls: 2.0626, decode.d0.loss_mask: 0.5165, decode.d0.loss_dice: 0.7795, decode.d1.loss_cls: 0.3434, decode.d1.loss_mask: 0.4916, decode.d1.loss_dice: 0.6947, decode.d2.loss_cls: 0.2576, decode.d2.loss_mask: 0.4789, decode.d2.loss_dice: 0.6677, decode.d3.loss_cls: 0.2274, decode.d3.loss_mask: 0.4767, decode.d3.loss_dice: 0.6544, decode.d4.loss_cls: 0.2103, decode.d4.loss_mask: 0.4765, decode.d4.loss_dice: 0.6579, decode.d5.loss_cls: 0.2131, decode.d5.loss_mask: 0.4727, decode.d5.loss_dice: 0.6529, decode.d6.loss_cls: 0.2029, decode.d6.loss_mask: 0.4725, decode.d6.loss_dice: 0.6502, decode.d7.loss_cls: 0.2002, decode.d7.loss_mask: 0.4738, decode.d7.loss_dice: 0.6524, decode.d8.loss_cls: 0.1945, decode.d8.loss_mask: 0.4736, decode.d8.loss_dice: 0.6518, loss: 15.6326 +2022-05-06 04:40:44,296 - mmseg - INFO - Iter [17400/40000] lr: 8.113e-07, eta: 5:46:43, time: 0.662, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1740, decode.loss_mask: 0.4674, decode.loss_dice: 0.6349, decode.d0.loss_cls: 1.9632, decode.d0.loss_mask: 0.5030, decode.d0.loss_dice: 0.7478, decode.d1.loss_cls: 0.2898, decode.d1.loss_mask: 0.4807, decode.d1.loss_dice: 0.6689, decode.d2.loss_cls: 0.2184, decode.d2.loss_mask: 0.4705, decode.d2.loss_dice: 0.6426, decode.d3.loss_cls: 0.1913, decode.d3.loss_mask: 0.4696, decode.d3.loss_dice: 0.6390, decode.d4.loss_cls: 0.1841, decode.d4.loss_mask: 0.4683, decode.d4.loss_dice: 0.6367, decode.d5.loss_cls: 0.1769, decode.d5.loss_mask: 0.4686, decode.d5.loss_dice: 0.6355, decode.d6.loss_cls: 0.1676, decode.d6.loss_mask: 0.4672, decode.d6.loss_dice: 0.6354, decode.d7.loss_cls: 0.1693, decode.d7.loss_mask: 0.4666, decode.d7.loss_dice: 0.6335, decode.d8.loss_cls: 0.1729, decode.d8.loss_mask: 0.4675, decode.d8.loss_dice: 0.6337, loss: 14.9445 +2022-05-06 04:41:20,387 - mmseg - INFO - Iter [17450/40000] lr: 8.095e-07, eta: 5:45:40, time: 0.722, data_time: 0.060, memory: 53770, decode.loss_cls: 0.2054, decode.loss_mask: 0.4646, decode.loss_dice: 0.6519, decode.d0.loss_cls: 2.0270, decode.d0.loss_mask: 0.5096, decode.d0.loss_dice: 0.7824, decode.d1.loss_cls: 0.3275, decode.d1.loss_mask: 0.4810, decode.d1.loss_dice: 0.6936, decode.d2.loss_cls: 0.2576, decode.d2.loss_mask: 0.4707, decode.d2.loss_dice: 0.6736, decode.d3.loss_cls: 0.2214, decode.d3.loss_mask: 0.4667, decode.d3.loss_dice: 0.6604, decode.d4.loss_cls: 0.2138, decode.d4.loss_mask: 0.4647, decode.d4.loss_dice: 0.6554, decode.d5.loss_cls: 0.2079, decode.d5.loss_mask: 0.4639, decode.d5.loss_dice: 0.6521, decode.d6.loss_cls: 0.2082, decode.d6.loss_mask: 0.4634, decode.d6.loss_dice: 0.6504, decode.d7.loss_cls: 0.2093, decode.d7.loss_mask: 0.4660, decode.d7.loss_dice: 0.6537, decode.d8.loss_cls: 0.2073, decode.d8.loss_mask: 0.4647, decode.d8.loss_dice: 0.6528, loss: 15.5270 +2022-05-06 04:41:54,065 - mmseg - INFO - Iter [17500/40000] lr: 8.077e-07, eta: 5:44:34, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2004, decode.loss_mask: 0.4511, decode.loss_dice: 0.6576, decode.d0.loss_cls: 2.0281, decode.d0.loss_mask: 0.4891, decode.d0.loss_dice: 0.7793, decode.d1.loss_cls: 0.3206, decode.d1.loss_mask: 0.4667, decode.d1.loss_dice: 0.6998, decode.d2.loss_cls: 0.2413, decode.d2.loss_mask: 0.4579, decode.d2.loss_dice: 0.6805, decode.d3.loss_cls: 0.2208, decode.d3.loss_mask: 0.4562, decode.d3.loss_dice: 0.6639, decode.d4.loss_cls: 0.2089, decode.d4.loss_mask: 0.4542, decode.d4.loss_dice: 0.6649, decode.d5.loss_cls: 0.2090, decode.d5.loss_mask: 0.4518, decode.d5.loss_dice: 0.6601, decode.d6.loss_cls: 0.2030, decode.d6.loss_mask: 0.4516, decode.d6.loss_dice: 0.6572, decode.d7.loss_cls: 0.2018, decode.d7.loss_mask: 0.4517, decode.d7.loss_dice: 0.6580, decode.d8.loss_cls: 0.2036, decode.d8.loss_mask: 0.4525, decode.d8.loss_dice: 0.6568, loss: 15.3987 +2022-05-06 04:42:27,579 - mmseg - INFO - Iter [17550/40000] lr: 8.059e-07, eta: 5:43:27, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1974, decode.loss_mask: 0.4835, decode.loss_dice: 0.6567, decode.d0.loss_cls: 2.0044, decode.d0.loss_mask: 0.5204, decode.d0.loss_dice: 0.7777, decode.d1.loss_cls: 0.3195, decode.d1.loss_mask: 0.5005, decode.d1.loss_dice: 0.6989, decode.d2.loss_cls: 0.2384, decode.d2.loss_mask: 0.4964, decode.d2.loss_dice: 0.6766, decode.d3.loss_cls: 0.2188, decode.d3.loss_mask: 0.4920, decode.d3.loss_dice: 0.6618, decode.d4.loss_cls: 0.2065, decode.d4.loss_mask: 0.4886, decode.d4.loss_dice: 0.6650, decode.d5.loss_cls: 0.2028, decode.d5.loss_mask: 0.4876, decode.d5.loss_dice: 0.6560, decode.d6.loss_cls: 0.1985, decode.d6.loss_mask: 0.4851, decode.d6.loss_dice: 0.6536, decode.d7.loss_cls: 0.1955, decode.d7.loss_mask: 0.4863, decode.d7.loss_dice: 0.6556, decode.d8.loss_cls: 0.1952, decode.d8.loss_mask: 0.4853, decode.d8.loss_dice: 0.6528, loss: 15.6574 +2022-05-06 04:43:01,452 - mmseg - INFO - Iter [17600/40000] lr: 8.041e-07, eta: 5:42:21, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1783, decode.loss_mask: 0.4611, decode.loss_dice: 0.6325, decode.d0.loss_cls: 1.9737, decode.d0.loss_mask: 0.5027, decode.d0.loss_dice: 0.7473, decode.d1.loss_cls: 0.3014, decode.d1.loss_mask: 0.4792, decode.d1.loss_dice: 0.6736, decode.d2.loss_cls: 0.2370, decode.d2.loss_mask: 0.4682, decode.d2.loss_dice: 0.6412, decode.d3.loss_cls: 0.2024, decode.d3.loss_mask: 0.4660, decode.d3.loss_dice: 0.6307, decode.d4.loss_cls: 0.1891, decode.d4.loss_mask: 0.4645, decode.d4.loss_dice: 0.6325, decode.d5.loss_cls: 0.1881, decode.d5.loss_mask: 0.4640, decode.d5.loss_dice: 0.6319, decode.d6.loss_cls: 0.1754, decode.d6.loss_mask: 0.4608, decode.d6.loss_dice: 0.6294, decode.d7.loss_cls: 0.1837, decode.d7.loss_mask: 0.4628, decode.d7.loss_dice: 0.6303, decode.d8.loss_cls: 0.1817, decode.d8.loss_mask: 0.4618, decode.d8.loss_dice: 0.6317, loss: 14.9833 +2022-05-06 04:43:35,354 - mmseg - INFO - Iter [17650/40000] lr: 8.023e-07, eta: 5:41:16, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1711, decode.loss_mask: 0.4700, decode.loss_dice: 0.6407, decode.d0.loss_cls: 1.9512, decode.d0.loss_mask: 0.5017, decode.d0.loss_dice: 0.7459, decode.d1.loss_cls: 0.3016, decode.d1.loss_mask: 0.4769, decode.d1.loss_dice: 0.6737, decode.d2.loss_cls: 0.2174, decode.d2.loss_mask: 0.4723, decode.d2.loss_dice: 0.6526, decode.d3.loss_cls: 0.1846, decode.d3.loss_mask: 0.4694, decode.d3.loss_dice: 0.6412, decode.d4.loss_cls: 0.1819, decode.d4.loss_mask: 0.4701, decode.d4.loss_dice: 0.6412, decode.d5.loss_cls: 0.1859, decode.d5.loss_mask: 0.4670, decode.d5.loss_dice: 0.6335, decode.d6.loss_cls: 0.1747, decode.d6.loss_mask: 0.4673, decode.d6.loss_dice: 0.6337, decode.d7.loss_cls: 0.1714, decode.d7.loss_mask: 0.4655, decode.d7.loss_dice: 0.6361, decode.d8.loss_cls: 0.1726, decode.d8.loss_mask: 0.4669, decode.d8.loss_dice: 0.6348, loss: 14.9731 +2022-05-06 04:44:09,650 - mmseg - INFO - Iter [17700/40000] lr: 8.005e-07, eta: 5:40:11, time: 0.686, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1924, decode.loss_mask: 0.4555, decode.loss_dice: 0.6394, decode.d0.loss_cls: 1.9587, decode.d0.loss_mask: 0.4939, decode.d0.loss_dice: 0.7460, decode.d1.loss_cls: 0.3175, decode.d1.loss_mask: 0.4731, decode.d1.loss_dice: 0.6809, decode.d2.loss_cls: 0.2424, decode.d2.loss_mask: 0.4630, decode.d2.loss_dice: 0.6584, decode.d3.loss_cls: 0.2091, decode.d3.loss_mask: 0.4592, decode.d3.loss_dice: 0.6450, decode.d4.loss_cls: 0.2081, decode.d4.loss_mask: 0.4556, decode.d4.loss_dice: 0.6412, decode.d5.loss_cls: 0.2001, decode.d5.loss_mask: 0.4544, decode.d5.loss_dice: 0.6478, decode.d6.loss_cls: 0.1950, decode.d6.loss_mask: 0.4559, decode.d6.loss_dice: 0.6480, decode.d7.loss_cls: 0.1904, decode.d7.loss_mask: 0.4562, decode.d7.loss_dice: 0.6425, decode.d8.loss_cls: 0.1936, decode.d8.loss_mask: 0.4567, decode.d8.loss_dice: 0.6421, loss: 15.1223 +2022-05-06 04:44:45,842 - mmseg - INFO - Iter [17750/40000] lr: 7.987e-07, eta: 5:39:10, time: 0.723, data_time: 0.056, memory: 53770, decode.loss_cls: 0.2036, decode.loss_mask: 0.4609, decode.loss_dice: 0.6671, decode.d0.loss_cls: 1.9882, decode.d0.loss_mask: 0.5003, decode.d0.loss_dice: 0.7717, decode.d1.loss_cls: 0.3264, decode.d1.loss_mask: 0.4738, decode.d1.loss_dice: 0.7013, decode.d2.loss_cls: 0.2381, decode.d2.loss_mask: 0.4638, decode.d2.loss_dice: 0.6818, decode.d3.loss_cls: 0.2189, decode.d3.loss_mask: 0.4619, decode.d3.loss_dice: 0.6698, decode.d4.loss_cls: 0.2182, decode.d4.loss_mask: 0.4633, decode.d4.loss_dice: 0.6699, decode.d5.loss_cls: 0.2074, decode.d5.loss_mask: 0.4612, decode.d5.loss_dice: 0.6687, decode.d6.loss_cls: 0.2038, decode.d6.loss_mask: 0.4605, decode.d6.loss_dice: 0.6683, decode.d7.loss_cls: 0.1976, decode.d7.loss_mask: 0.4598, decode.d7.loss_dice: 0.6696, decode.d8.loss_cls: 0.2024, decode.d8.loss_mask: 0.4598, decode.d8.loss_dice: 0.6625, loss: 15.5006 +2022-05-06 04:45:20,198 - mmseg - INFO - Iter [17800/40000] lr: 7.969e-07, eta: 5:38:06, time: 0.688, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1823, decode.loss_mask: 0.4644, decode.loss_dice: 0.6321, decode.d0.loss_cls: 1.9730, decode.d0.loss_mask: 0.4981, decode.d0.loss_dice: 0.7474, decode.d1.loss_cls: 0.2984, decode.d1.loss_mask: 0.4787, decode.d1.loss_dice: 0.6732, decode.d2.loss_cls: 0.2228, decode.d2.loss_mask: 0.4671, decode.d2.loss_dice: 0.6447, decode.d3.loss_cls: 0.2031, decode.d3.loss_mask: 0.4630, decode.d3.loss_dice: 0.6353, decode.d4.loss_cls: 0.1997, decode.d4.loss_mask: 0.4648, decode.d4.loss_dice: 0.6325, decode.d5.loss_cls: 0.1873, decode.d5.loss_mask: 0.4646, decode.d5.loss_dice: 0.6341, decode.d6.loss_cls: 0.1871, decode.d6.loss_mask: 0.4636, decode.d6.loss_dice: 0.6263, decode.d7.loss_cls: 0.1852, decode.d7.loss_mask: 0.4620, decode.d7.loss_dice: 0.6274, decode.d8.loss_cls: 0.1811, decode.d8.loss_mask: 0.4637, decode.d8.loss_dice: 0.6357, loss: 14.9988 +2022-05-06 04:45:54,256 - mmseg - INFO - Iter [17850/40000] lr: 7.951e-07, eta: 5:37:02, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1884, decode.loss_mask: 0.4536, decode.loss_dice: 0.6321, decode.d0.loss_cls: 1.9897, decode.d0.loss_mask: 0.5055, decode.d0.loss_dice: 0.7543, decode.d1.loss_cls: 0.3245, decode.d1.loss_mask: 0.4750, decode.d1.loss_dice: 0.6790, decode.d2.loss_cls: 0.2312, decode.d2.loss_mask: 0.4611, decode.d2.loss_dice: 0.6472, decode.d3.loss_cls: 0.2006, decode.d3.loss_mask: 0.4573, decode.d3.loss_dice: 0.6410, decode.d4.loss_cls: 0.1995, decode.d4.loss_mask: 0.4561, decode.d4.loss_dice: 0.6384, decode.d5.loss_cls: 0.1911, decode.d5.loss_mask: 0.4542, decode.d5.loss_dice: 0.6321, decode.d6.loss_cls: 0.1840, decode.d6.loss_mask: 0.4548, decode.d6.loss_dice: 0.6279, decode.d7.loss_cls: 0.1848, decode.d7.loss_mask: 0.4514, decode.d7.loss_dice: 0.6305, decode.d8.loss_cls: 0.1864, decode.d8.loss_mask: 0.4547, decode.d8.loss_dice: 0.6353, loss: 15.0216 +2022-05-06 04:46:28,562 - mmseg - INFO - Iter [17900/40000] lr: 7.933e-07, eta: 5:35:58, time: 0.686, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1730, decode.loss_mask: 0.4580, decode.loss_dice: 0.6433, decode.d0.loss_cls: 1.9399, decode.d0.loss_mask: 0.4956, decode.d0.loss_dice: 0.7564, decode.d1.loss_cls: 0.2903, decode.d1.loss_mask: 0.4768, decode.d1.loss_dice: 0.6878, decode.d2.loss_cls: 0.2253, decode.d2.loss_mask: 0.4652, decode.d2.loss_dice: 0.6612, decode.d3.loss_cls: 0.1912, decode.d3.loss_mask: 0.4615, decode.d3.loss_dice: 0.6466, decode.d4.loss_cls: 0.1875, decode.d4.loss_mask: 0.4585, decode.d4.loss_dice: 0.6474, decode.d5.loss_cls: 0.1853, decode.d5.loss_mask: 0.4562, decode.d5.loss_dice: 0.6434, decode.d6.loss_cls: 0.1737, decode.d6.loss_mask: 0.4590, decode.d6.loss_dice: 0.6462, decode.d7.loss_cls: 0.1717, decode.d7.loss_mask: 0.4585, decode.d7.loss_dice: 0.6476, decode.d8.loss_cls: 0.1799, decode.d8.loss_mask: 0.4554, decode.d8.loss_dice: 0.6409, loss: 14.9835 +2022-05-06 04:47:02,425 - mmseg - INFO - Iter [17950/40000] lr: 7.915e-07, eta: 5:34:54, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1722, decode.loss_mask: 0.4826, decode.loss_dice: 0.6574, decode.d0.loss_cls: 1.9928, decode.d0.loss_mask: 0.5182, decode.d0.loss_dice: 0.7733, decode.d1.loss_cls: 0.3006, decode.d1.loss_mask: 0.4964, decode.d1.loss_dice: 0.6903, decode.d2.loss_cls: 0.2313, decode.d2.loss_mask: 0.4853, decode.d2.loss_dice: 0.6643, decode.d3.loss_cls: 0.1973, decode.d3.loss_mask: 0.4829, decode.d3.loss_dice: 0.6537, decode.d4.loss_cls: 0.1890, decode.d4.loss_mask: 0.4838, decode.d4.loss_dice: 0.6557, decode.d5.loss_cls: 0.1885, decode.d5.loss_mask: 0.4813, decode.d5.loss_dice: 0.6549, decode.d6.loss_cls: 0.1852, decode.d6.loss_mask: 0.4808, decode.d6.loss_dice: 0.6508, decode.d7.loss_cls: 0.1845, decode.d7.loss_mask: 0.4811, decode.d7.loss_dice: 0.6557, decode.d8.loss_cls: 0.1802, decode.d8.loss_mask: 0.4808, decode.d8.loss_dice: 0.6581, loss: 15.4091 +2022-05-06 04:47:36,107 - mmseg - INFO - Saving checkpoint at 18000 iterations +2022-05-06 04:48:01,026 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 04:48:01,028 - mmseg - INFO - Iter [18000/40000] lr: 7.897e-07, eta: 5:34:29, time: 1.170, data_time: 0.009, memory: 53770, decode.loss_cls: 0.2025, decode.loss_mask: 0.4670, decode.loss_dice: 0.6565, decode.d0.loss_cls: 1.9871, decode.d0.loss_mask: 0.5087, decode.d0.loss_dice: 0.7857, decode.d1.loss_cls: 0.3316, decode.d1.loss_mask: 0.4888, decode.d1.loss_dice: 0.7186, decode.d2.loss_cls: 0.2546, decode.d2.loss_mask: 0.4734, decode.d2.loss_dice: 0.6865, decode.d3.loss_cls: 0.2268, decode.d3.loss_mask: 0.4676, decode.d3.loss_dice: 0.6694, decode.d4.loss_cls: 0.2149, decode.d4.loss_mask: 0.4681, decode.d4.loss_dice: 0.6662, decode.d5.loss_cls: 0.2061, decode.d5.loss_mask: 0.4677, decode.d5.loss_dice: 0.6635, decode.d6.loss_cls: 0.1998, decode.d6.loss_mask: 0.4654, decode.d6.loss_dice: 0.6605, decode.d7.loss_cls: 0.1961, decode.d7.loss_mask: 0.4683, decode.d7.loss_dice: 0.6611, decode.d8.loss_cls: 0.2025, decode.d8.loss_mask: 0.4680, decode.d8.loss_dice: 0.6593, loss: 15.5924 +2022-05-06 04:48:37,562 - mmseg - INFO - Iter [18050/40000] lr: 7.879e-07, eta: 5:33:29, time: 0.733, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1657, decode.loss_mask: 0.4679, decode.loss_dice: 0.6243, decode.d0.loss_cls: 1.9076, decode.d0.loss_mask: 0.5082, decode.d0.loss_dice: 0.7457, decode.d1.loss_cls: 0.2963, decode.d1.loss_mask: 0.4835, decode.d1.loss_dice: 0.6700, decode.d2.loss_cls: 0.2089, decode.d2.loss_mask: 0.4757, decode.d2.loss_dice: 0.6435, decode.d3.loss_cls: 0.1818, decode.d3.loss_mask: 0.4720, decode.d3.loss_dice: 0.6333, decode.d4.loss_cls: 0.1733, decode.d4.loss_mask: 0.4678, decode.d4.loss_dice: 0.6315, decode.d5.loss_cls: 0.1654, decode.d5.loss_mask: 0.4705, decode.d5.loss_dice: 0.6295, decode.d6.loss_cls: 0.1636, decode.d6.loss_mask: 0.4671, decode.d6.loss_dice: 0.6224, decode.d7.loss_cls: 0.1601, decode.d7.loss_mask: 0.4693, decode.d7.loss_dice: 0.6242, decode.d8.loss_cls: 0.1605, decode.d8.loss_mask: 0.4693, decode.d8.loss_dice: 0.6285, loss: 14.7873 +2022-05-06 04:49:11,139 - mmseg - INFO - Iter [18100/40000] lr: 7.861e-07, eta: 5:32:25, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1745, decode.loss_mask: 0.4556, decode.loss_dice: 0.6190, decode.d0.loss_cls: 1.9509, decode.d0.loss_mask: 0.4923, decode.d0.loss_dice: 0.7424, decode.d1.loss_cls: 0.3044, decode.d1.loss_mask: 0.4721, decode.d1.loss_dice: 0.6595, decode.d2.loss_cls: 0.2215, decode.d2.loss_mask: 0.4621, decode.d2.loss_dice: 0.6360, decode.d3.loss_cls: 0.1923, decode.d3.loss_mask: 0.4597, decode.d3.loss_dice: 0.6248, decode.d4.loss_cls: 0.1853, decode.d4.loss_mask: 0.4546, decode.d4.loss_dice: 0.6220, decode.d5.loss_cls: 0.1792, decode.d5.loss_mask: 0.4549, decode.d5.loss_dice: 0.6247, decode.d6.loss_cls: 0.1778, decode.d6.loss_mask: 0.4539, decode.d6.loss_dice: 0.6194, decode.d7.loss_cls: 0.1700, decode.d7.loss_mask: 0.4555, decode.d7.loss_dice: 0.6217, decode.d8.loss_cls: 0.1741, decode.d8.loss_mask: 0.4534, decode.d8.loss_dice: 0.6244, loss: 14.7381 +2022-05-06 04:49:45,130 - mmseg - INFO - Iter [18150/40000] lr: 7.843e-07, eta: 5:31:22, time: 0.680, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1706, decode.loss_mask: 0.4530, decode.loss_dice: 0.6429, decode.d0.loss_cls: 1.9298, decode.d0.loss_mask: 0.4936, decode.d0.loss_dice: 0.7514, decode.d1.loss_cls: 0.2945, decode.d1.loss_mask: 0.4683, decode.d1.loss_dice: 0.6831, decode.d2.loss_cls: 0.2132, decode.d2.loss_mask: 0.4567, decode.d2.loss_dice: 0.6650, decode.d3.loss_cls: 0.1944, decode.d3.loss_mask: 0.4514, decode.d3.loss_dice: 0.6524, decode.d4.loss_cls: 0.1882, decode.d4.loss_mask: 0.4513, decode.d4.loss_dice: 0.6493, decode.d5.loss_cls: 0.1772, decode.d5.loss_mask: 0.4533, decode.d5.loss_dice: 0.6505, decode.d6.loss_cls: 0.1743, decode.d6.loss_mask: 0.4544, decode.d6.loss_dice: 0.6469, decode.d7.loss_cls: 0.1696, decode.d7.loss_mask: 0.4521, decode.d7.loss_dice: 0.6434, decode.d8.loss_cls: 0.1679, decode.d8.loss_mask: 0.4498, decode.d8.loss_dice: 0.6479, loss: 14.8964 +2022-05-06 04:50:19,082 - mmseg - INFO - Iter [18200/40000] lr: 7.825e-07, eta: 5:30:18, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1723, decode.loss_mask: 0.4501, decode.loss_dice: 0.6366, decode.d0.loss_cls: 1.9126, decode.d0.loss_mask: 0.4921, decode.d0.loss_dice: 0.7521, decode.d1.loss_cls: 0.3214, decode.d1.loss_mask: 0.4630, decode.d1.loss_dice: 0.6742, decode.d2.loss_cls: 0.2426, decode.d2.loss_mask: 0.4528, decode.d2.loss_dice: 0.6474, decode.d3.loss_cls: 0.1971, decode.d3.loss_mask: 0.4498, decode.d3.loss_dice: 0.6388, decode.d4.loss_cls: 0.1893, decode.d4.loss_mask: 0.4496, decode.d4.loss_dice: 0.6354, decode.d5.loss_cls: 0.1790, decode.d5.loss_mask: 0.4479, decode.d5.loss_dice: 0.6360, decode.d6.loss_cls: 0.1749, decode.d6.loss_mask: 0.4480, decode.d6.loss_dice: 0.6342, decode.d7.loss_cls: 0.1735, decode.d7.loss_mask: 0.4481, decode.d7.loss_dice: 0.6351, decode.d8.loss_cls: 0.1752, decode.d8.loss_mask: 0.4471, decode.d8.loss_dice: 0.6341, loss: 14.8104 +2022-05-06 04:50:52,892 - mmseg - INFO - Iter [18250/40000] lr: 7.807e-07, eta: 5:29:15, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1851, decode.loss_mask: 0.4670, decode.loss_dice: 0.6206, decode.d0.loss_cls: 1.9294, decode.d0.loss_mask: 0.5112, decode.d0.loss_dice: 0.7389, decode.d1.loss_cls: 0.3044, decode.d1.loss_mask: 0.4826, decode.d1.loss_dice: 0.6659, decode.d2.loss_cls: 0.2248, decode.d2.loss_mask: 0.4707, decode.d2.loss_dice: 0.6309, decode.d3.loss_cls: 0.1918, decode.d3.loss_mask: 0.4676, decode.d3.loss_dice: 0.6276, decode.d4.loss_cls: 0.1996, decode.d4.loss_mask: 0.4652, decode.d4.loss_dice: 0.6259, decode.d5.loss_cls: 0.1866, decode.d5.loss_mask: 0.4670, decode.d5.loss_dice: 0.6241, decode.d6.loss_cls: 0.1789, decode.d6.loss_mask: 0.4690, decode.d6.loss_dice: 0.6231, decode.d7.loss_cls: 0.1857, decode.d7.loss_mask: 0.4671, decode.d7.loss_dice: 0.6175, decode.d8.loss_cls: 0.1814, decode.d8.loss_mask: 0.4661, decode.d8.loss_dice: 0.6226, loss: 14.8982 +2022-05-06 04:51:26,460 - mmseg - INFO - Iter [18300/40000] lr: 7.790e-07, eta: 5:28:12, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1776, decode.loss_mask: 0.4429, decode.loss_dice: 0.6187, decode.d0.loss_cls: 1.9320, decode.d0.loss_mask: 0.4890, decode.d0.loss_dice: 0.7399, decode.d1.loss_cls: 0.3031, decode.d1.loss_mask: 0.4581, decode.d1.loss_dice: 0.6575, decode.d2.loss_cls: 0.2234, decode.d2.loss_mask: 0.4499, decode.d2.loss_dice: 0.6363, decode.d3.loss_cls: 0.1897, decode.d3.loss_mask: 0.4434, decode.d3.loss_dice: 0.6298, decode.d4.loss_cls: 0.1813, decode.d4.loss_mask: 0.4440, decode.d4.loss_dice: 0.6247, decode.d5.loss_cls: 0.1735, decode.d5.loss_mask: 0.4405, decode.d5.loss_dice: 0.6244, decode.d6.loss_cls: 0.1769, decode.d6.loss_mask: 0.4414, decode.d6.loss_dice: 0.6172, decode.d7.loss_cls: 0.1661, decode.d7.loss_mask: 0.4456, decode.d7.loss_dice: 0.6215, decode.d8.loss_cls: 0.1725, decode.d8.loss_mask: 0.4431, decode.d8.loss_dice: 0.6197, loss: 14.5833 +2022-05-06 04:52:00,207 - mmseg - INFO - Iter [18350/40000] lr: 7.772e-07, eta: 5:27:09, time: 0.675, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1964, decode.loss_mask: 0.4720, decode.loss_dice: 0.6653, decode.d0.loss_cls: 1.9570, decode.d0.loss_mask: 0.5077, decode.d0.loss_dice: 0.7727, decode.d1.loss_cls: 0.3114, decode.d1.loss_mask: 0.4875, decode.d1.loss_dice: 0.7053, decode.d2.loss_cls: 0.2451, decode.d2.loss_mask: 0.4749, decode.d2.loss_dice: 0.6793, decode.d3.loss_cls: 0.2183, decode.d3.loss_mask: 0.4688, decode.d3.loss_dice: 0.6712, decode.d4.loss_cls: 0.2028, decode.d4.loss_mask: 0.4671, decode.d4.loss_dice: 0.6680, decode.d5.loss_cls: 0.2001, decode.d5.loss_mask: 0.4678, decode.d5.loss_dice: 0.6691, decode.d6.loss_cls: 0.1970, decode.d6.loss_mask: 0.4690, decode.d6.loss_dice: 0.6706, decode.d7.loss_cls: 0.1927, decode.d7.loss_mask: 0.4684, decode.d7.loss_dice: 0.6691, decode.d8.loss_cls: 0.1958, decode.d8.loss_mask: 0.4692, decode.d8.loss_dice: 0.6746, loss: 15.5142 +2022-05-06 04:52:36,306 - mmseg - INFO - Iter [18400/40000] lr: 7.754e-07, eta: 5:26:10, time: 0.722, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1605, decode.loss_mask: 0.4634, decode.loss_dice: 0.6284, decode.d0.loss_cls: 1.8764, decode.d0.loss_mask: 0.4983, decode.d0.loss_dice: 0.7364, decode.d1.loss_cls: 0.2894, decode.d1.loss_mask: 0.4764, decode.d1.loss_dice: 0.6662, decode.d2.loss_cls: 0.2158, decode.d2.loss_mask: 0.4695, decode.d2.loss_dice: 0.6391, decode.d3.loss_cls: 0.1857, decode.d3.loss_mask: 0.4626, decode.d3.loss_dice: 0.6247, decode.d4.loss_cls: 0.1805, decode.d4.loss_mask: 0.4627, decode.d4.loss_dice: 0.6290, decode.d5.loss_cls: 0.1786, decode.d5.loss_mask: 0.4645, decode.d5.loss_dice: 0.6296, decode.d6.loss_cls: 0.1704, decode.d6.loss_mask: 0.4655, decode.d6.loss_dice: 0.6271, decode.d7.loss_cls: 0.1639, decode.d7.loss_mask: 0.4656, decode.d7.loss_dice: 0.6356, decode.d8.loss_cls: 0.1671, decode.d8.loss_mask: 0.4642, decode.d8.loss_dice: 0.6252, loss: 14.7224 +2022-05-06 04:53:09,657 - mmseg - INFO - Iter [18450/40000] lr: 7.736e-07, eta: 5:25:06, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1776, decode.loss_mask: 0.4618, decode.loss_dice: 0.6326, decode.d0.loss_cls: 1.9070, decode.d0.loss_mask: 0.5059, decode.d0.loss_dice: 0.7535, decode.d1.loss_cls: 0.3104, decode.d1.loss_mask: 0.4781, decode.d1.loss_dice: 0.6735, decode.d2.loss_cls: 0.2265, decode.d2.loss_mask: 0.4678, decode.d2.loss_dice: 0.6480, decode.d3.loss_cls: 0.1904, decode.d3.loss_mask: 0.4638, decode.d3.loss_dice: 0.6396, decode.d4.loss_cls: 0.1825, decode.d4.loss_mask: 0.4626, decode.d4.loss_dice: 0.6439, decode.d5.loss_cls: 0.1882, decode.d5.loss_mask: 0.4583, decode.d5.loss_dice: 0.6372, decode.d6.loss_cls: 0.1765, decode.d6.loss_mask: 0.4609, decode.d6.loss_dice: 0.6357, decode.d7.loss_cls: 0.1683, decode.d7.loss_mask: 0.4588, decode.d7.loss_dice: 0.6355, decode.d8.loss_cls: 0.1727, decode.d8.loss_mask: 0.4604, decode.d8.loss_dice: 0.6345, loss: 14.9125 +2022-05-06 04:53:43,774 - mmseg - INFO - Iter [18500/40000] lr: 7.718e-07, eta: 5:24:05, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1796, decode.loss_mask: 0.4418, decode.loss_dice: 0.6177, decode.d0.loss_cls: 1.9018, decode.d0.loss_mask: 0.4730, decode.d0.loss_dice: 0.7278, decode.d1.loss_cls: 0.3015, decode.d1.loss_mask: 0.4539, decode.d1.loss_dice: 0.6659, decode.d2.loss_cls: 0.2169, decode.d2.loss_mask: 0.4476, decode.d2.loss_dice: 0.6384, decode.d3.loss_cls: 0.1949, decode.d3.loss_mask: 0.4420, decode.d3.loss_dice: 0.6211, decode.d4.loss_cls: 0.1903, decode.d4.loss_mask: 0.4430, decode.d4.loss_dice: 0.6245, decode.d5.loss_cls: 0.1841, decode.d5.loss_mask: 0.4425, decode.d5.loss_dice: 0.6223, decode.d6.loss_cls: 0.1814, decode.d6.loss_mask: 0.4408, decode.d6.loss_dice: 0.6190, decode.d7.loss_cls: 0.1741, decode.d7.loss_mask: 0.4431, decode.d7.loss_dice: 0.6184, decode.d8.loss_cls: 0.1768, decode.d8.loss_mask: 0.4411, decode.d8.loss_dice: 0.6170, loss: 14.5424 +2022-05-06 04:54:18,026 - mmseg - INFO - Iter [18550/40000] lr: 7.700e-07, eta: 5:23:03, time: 0.685, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1797, decode.loss_mask: 0.4675, decode.loss_dice: 0.6486, decode.d0.loss_cls: 1.9218, decode.d0.loss_mask: 0.5061, decode.d0.loss_dice: 0.7678, decode.d1.loss_cls: 0.3081, decode.d1.loss_mask: 0.4809, decode.d1.loss_dice: 0.6879, decode.d2.loss_cls: 0.2350, decode.d2.loss_mask: 0.4680, decode.d2.loss_dice: 0.6654, decode.d3.loss_cls: 0.2028, decode.d3.loss_mask: 0.4672, decode.d3.loss_dice: 0.6595, decode.d4.loss_cls: 0.1966, decode.d4.loss_mask: 0.4663, decode.d4.loss_dice: 0.6590, decode.d5.loss_cls: 0.1883, decode.d5.loss_mask: 0.4654, decode.d5.loss_dice: 0.6575, decode.d6.loss_cls: 0.1824, decode.d6.loss_mask: 0.4620, decode.d6.loss_dice: 0.6502, decode.d7.loss_cls: 0.1770, decode.d7.loss_mask: 0.4648, decode.d7.loss_dice: 0.6559, decode.d8.loss_cls: 0.1800, decode.d8.loss_mask: 0.4639, decode.d8.loss_dice: 0.6586, loss: 15.1942 +2022-05-06 04:54:51,964 - mmseg - INFO - Iter [18600/40000] lr: 7.682e-07, eta: 5:22:02, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1738, decode.loss_mask: 0.4582, decode.loss_dice: 0.6383, decode.d0.loss_cls: 1.8908, decode.d0.loss_mask: 0.4939, decode.d0.loss_dice: 0.7446, decode.d1.loss_cls: 0.2925, decode.d1.loss_mask: 0.4745, decode.d1.loss_dice: 0.6772, decode.d2.loss_cls: 0.2242, decode.d2.loss_mask: 0.4657, decode.d2.loss_dice: 0.6512, decode.d3.loss_cls: 0.1932, decode.d3.loss_mask: 0.4646, decode.d3.loss_dice: 0.6431, decode.d4.loss_cls: 0.1804, decode.d4.loss_mask: 0.4649, decode.d4.loss_dice: 0.6437, decode.d5.loss_cls: 0.1766, decode.d5.loss_mask: 0.4618, decode.d5.loss_dice: 0.6447, decode.d6.loss_cls: 0.1657, decode.d6.loss_mask: 0.4622, decode.d6.loss_dice: 0.6377, decode.d7.loss_cls: 0.1664, decode.d7.loss_mask: 0.4600, decode.d7.loss_dice: 0.6381, decode.d8.loss_cls: 0.1691, decode.d8.loss_mask: 0.4582, decode.d8.loss_dice: 0.6383, loss: 14.8535 +2022-05-06 04:55:25,399 - mmseg - INFO - Iter [18650/40000] lr: 7.664e-07, eta: 5:20:59, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1825, decode.loss_mask: 0.4630, decode.loss_dice: 0.6318, decode.d0.loss_cls: 1.9347, decode.d0.loss_mask: 0.5007, decode.d0.loss_dice: 0.7482, decode.d1.loss_cls: 0.2992, decode.d1.loss_mask: 0.4772, decode.d1.loss_dice: 0.6751, decode.d2.loss_cls: 0.2261, decode.d2.loss_mask: 0.4677, decode.d2.loss_dice: 0.6524, decode.d3.loss_cls: 0.2023, decode.d3.loss_mask: 0.4649, decode.d3.loss_dice: 0.6397, decode.d4.loss_cls: 0.2046, decode.d4.loss_mask: 0.4669, decode.d4.loss_dice: 0.6403, decode.d5.loss_cls: 0.1965, decode.d5.loss_mask: 0.4645, decode.d5.loss_dice: 0.6397, decode.d6.loss_cls: 0.1863, decode.d6.loss_mask: 0.4634, decode.d6.loss_dice: 0.6320, decode.d7.loss_cls: 0.1871, decode.d7.loss_mask: 0.4616, decode.d7.loss_dice: 0.6302, decode.d8.loss_cls: 0.1777, decode.d8.loss_mask: 0.4643, decode.d8.loss_dice: 0.6391, loss: 15.0198 +2022-05-06 04:56:01,245 - mmseg - INFO - Iter [18700/40000] lr: 7.646e-07, eta: 5:20:01, time: 0.717, data_time: 0.056, memory: 53770, decode.loss_cls: 0.1731, decode.loss_mask: 0.4625, decode.loss_dice: 0.6433, decode.d0.loss_cls: 1.8625, decode.d0.loss_mask: 0.5019, decode.d0.loss_dice: 0.7529, decode.d1.loss_cls: 0.2862, decode.d1.loss_mask: 0.4782, decode.d1.loss_dice: 0.6826, decode.d2.loss_cls: 0.2186, decode.d2.loss_mask: 0.4666, decode.d2.loss_dice: 0.6599, decode.d3.loss_cls: 0.1861, decode.d3.loss_mask: 0.4635, decode.d3.loss_dice: 0.6495, decode.d4.loss_cls: 0.1786, decode.d4.loss_mask: 0.4632, decode.d4.loss_dice: 0.6530, decode.d5.loss_cls: 0.1721, decode.d5.loss_mask: 0.4624, decode.d5.loss_dice: 0.6468, decode.d6.loss_cls: 0.1695, decode.d6.loss_mask: 0.4593, decode.d6.loss_dice: 0.6405, decode.d7.loss_cls: 0.1713, decode.d7.loss_mask: 0.4598, decode.d7.loss_dice: 0.6420, decode.d8.loss_cls: 0.1731, decode.d8.loss_mask: 0.4613, decode.d8.loss_dice: 0.6441, loss: 14.8845 +2022-05-06 04:56:34,915 - mmseg - INFO - Iter [18750/40000] lr: 7.628e-07, eta: 5:18:59, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1537, decode.loss_mask: 0.4655, decode.loss_dice: 0.5934, decode.d0.loss_cls: 1.8479, decode.d0.loss_mask: 0.5052, decode.d0.loss_dice: 0.7012, decode.d1.loss_cls: 0.2648, decode.d1.loss_mask: 0.4809, decode.d1.loss_dice: 0.6377, decode.d2.loss_cls: 0.1988, decode.d2.loss_mask: 0.4708, decode.d2.loss_dice: 0.6075, decode.d3.loss_cls: 0.1661, decode.d3.loss_mask: 0.4690, decode.d3.loss_dice: 0.6023, decode.d4.loss_cls: 0.1587, decode.d4.loss_mask: 0.4665, decode.d4.loss_dice: 0.6026, decode.d5.loss_cls: 0.1543, decode.d5.loss_mask: 0.4652, decode.d5.loss_dice: 0.5989, decode.d6.loss_cls: 0.1467, decode.d6.loss_mask: 0.4651, decode.d6.loss_dice: 0.6014, decode.d7.loss_cls: 0.1468, decode.d7.loss_mask: 0.4644, decode.d7.loss_dice: 0.5999, decode.d8.loss_cls: 0.1469, decode.d8.loss_mask: 0.4661, decode.d8.loss_dice: 0.5981, loss: 14.2467 +2022-05-06 04:57:07,966 - mmseg - INFO - Iter [18800/40000] lr: 7.610e-07, eta: 5:17:57, time: 0.661, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1705, decode.loss_mask: 0.4599, decode.loss_dice: 0.6373, decode.d0.loss_cls: 1.8933, decode.d0.loss_mask: 0.5011, decode.d0.loss_dice: 0.7538, decode.d1.loss_cls: 0.2846, decode.d1.loss_mask: 0.4746, decode.d1.loss_dice: 0.6731, decode.d2.loss_cls: 0.2104, decode.d2.loss_mask: 0.4684, decode.d2.loss_dice: 0.6532, decode.d3.loss_cls: 0.1831, decode.d3.loss_mask: 0.4610, decode.d3.loss_dice: 0.6465, decode.d4.loss_cls: 0.1775, decode.d4.loss_mask: 0.4611, decode.d4.loss_dice: 0.6470, decode.d5.loss_cls: 0.1715, decode.d5.loss_mask: 0.4616, decode.d5.loss_dice: 0.6431, decode.d6.loss_cls: 0.1710, decode.d6.loss_mask: 0.4612, decode.d6.loss_dice: 0.6403, decode.d7.loss_cls: 0.1708, decode.d7.loss_mask: 0.4619, decode.d7.loss_dice: 0.6409, decode.d8.loss_cls: 0.1703, decode.d8.loss_mask: 0.4598, decode.d8.loss_dice: 0.6376, loss: 14.8461 +2022-05-06 04:57:41,644 - mmseg - INFO - Iter [18850/40000] lr: 7.592e-07, eta: 5:16:56, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1565, decode.loss_mask: 0.4528, decode.loss_dice: 0.6215, decode.d0.loss_cls: 1.9142, decode.d0.loss_mask: 0.4951, decode.d0.loss_dice: 0.7363, decode.d1.loss_cls: 0.2921, decode.d1.loss_mask: 0.4722, decode.d1.loss_dice: 0.6677, decode.d2.loss_cls: 0.2160, decode.d2.loss_mask: 0.4575, decode.d2.loss_dice: 0.6338, decode.d3.loss_cls: 0.1809, decode.d3.loss_mask: 0.4546, decode.d3.loss_dice: 0.6238, decode.d4.loss_cls: 0.1740, decode.d4.loss_mask: 0.4547, decode.d4.loss_dice: 0.6247, decode.d5.loss_cls: 0.1685, decode.d5.loss_mask: 0.4530, decode.d5.loss_dice: 0.6276, decode.d6.loss_cls: 0.1581, decode.d6.loss_mask: 0.4532, decode.d6.loss_dice: 0.6203, decode.d7.loss_cls: 0.1537, decode.d7.loss_mask: 0.4554, decode.d7.loss_dice: 0.6256, decode.d8.loss_cls: 0.1598, decode.d8.loss_mask: 0.4550, decode.d8.loss_dice: 0.6269, loss: 14.5855 +2022-05-06 04:58:15,759 - mmseg - INFO - Iter [18900/40000] lr: 7.574e-07, eta: 5:15:56, time: 0.682, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1851, decode.loss_mask: 0.4470, decode.loss_dice: 0.6617, decode.d0.loss_cls: 1.9229, decode.d0.loss_mask: 0.4824, decode.d0.loss_dice: 0.7848, decode.d1.loss_cls: 0.3268, decode.d1.loss_mask: 0.4584, decode.d1.loss_dice: 0.7025, decode.d2.loss_cls: 0.2402, decode.d2.loss_mask: 0.4503, decode.d2.loss_dice: 0.6796, decode.d3.loss_cls: 0.2123, decode.d3.loss_mask: 0.4469, decode.d3.loss_dice: 0.6674, decode.d4.loss_cls: 0.1989, decode.d4.loss_mask: 0.4451, decode.d4.loss_dice: 0.6697, decode.d5.loss_cls: 0.1971, decode.d5.loss_mask: 0.4451, decode.d5.loss_dice: 0.6653, decode.d6.loss_cls: 0.1895, decode.d6.loss_mask: 0.4460, decode.d6.loss_dice: 0.6613, decode.d7.loss_cls: 0.1811, decode.d7.loss_mask: 0.4472, decode.d7.loss_dice: 0.6623, decode.d8.loss_cls: 0.1819, decode.d8.loss_mask: 0.4462, decode.d8.loss_dice: 0.6626, loss: 15.1677 +2022-05-06 04:58:49,152 - mmseg - INFO - Iter [18950/40000] lr: 7.556e-07, eta: 5:14:55, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1630, decode.loss_mask: 0.4386, decode.loss_dice: 0.6261, decode.d0.loss_cls: 1.8723, decode.d0.loss_mask: 0.4687, decode.d0.loss_dice: 0.7426, decode.d1.loss_cls: 0.3017, decode.d1.loss_mask: 0.4522, decode.d1.loss_dice: 0.6641, decode.d2.loss_cls: 0.2191, decode.d2.loss_mask: 0.4431, decode.d2.loss_dice: 0.6398, decode.d3.loss_cls: 0.1909, decode.d3.loss_mask: 0.4381, decode.d3.loss_dice: 0.6339, decode.d4.loss_cls: 0.1824, decode.d4.loss_mask: 0.4390, decode.d4.loss_dice: 0.6346, decode.d5.loss_cls: 0.1749, decode.d5.loss_mask: 0.4379, decode.d5.loss_dice: 0.6300, decode.d6.loss_cls: 0.1679, decode.d6.loss_mask: 0.4380, decode.d6.loss_dice: 0.6280, decode.d7.loss_cls: 0.1681, decode.d7.loss_mask: 0.4353, decode.d7.loss_dice: 0.6282, decode.d8.loss_cls: 0.1687, decode.d8.loss_mask: 0.4357, decode.d8.loss_dice: 0.6252, loss: 14.4880 +2022-05-06 04:59:25,209 - mmseg - INFO - Saving checkpoint at 19000 iterations +2022-05-06 04:59:51,277 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 04:59:51,281 - mmseg - INFO - Iter [19000/40000] lr: 7.538e-07, eta: 5:14:34, time: 1.240, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1678, decode.loss_mask: 0.4321, decode.loss_dice: 0.6212, decode.d0.loss_cls: 1.8880, decode.d0.loss_mask: 0.4687, decode.d0.loss_dice: 0.7262, decode.d1.loss_cls: 0.2923, decode.d1.loss_mask: 0.4451, decode.d1.loss_dice: 0.6583, decode.d2.loss_cls: 0.2213, decode.d2.loss_mask: 0.4366, decode.d2.loss_dice: 0.6333, decode.d3.loss_cls: 0.1921, decode.d3.loss_mask: 0.4368, decode.d3.loss_dice: 0.6242, decode.d4.loss_cls: 0.1822, decode.d4.loss_mask: 0.4363, decode.d4.loss_dice: 0.6265, decode.d5.loss_cls: 0.1769, decode.d5.loss_mask: 0.4325, decode.d5.loss_dice: 0.6171, decode.d6.loss_cls: 0.1704, decode.d6.loss_mask: 0.4332, decode.d6.loss_dice: 0.6138, decode.d7.loss_cls: 0.1664, decode.d7.loss_mask: 0.4326, decode.d7.loss_dice: 0.6226, decode.d8.loss_cls: 0.1706, decode.d8.loss_mask: 0.4315, decode.d8.loss_dice: 0.6197, loss: 14.3763 +2022-05-06 05:00:25,066 - mmseg - INFO - Iter [19050/40000] lr: 7.520e-07, eta: 5:13:33, time: 0.678, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1721, decode.loss_mask: 0.4592, decode.loss_dice: 0.6400, decode.d0.loss_cls: 1.8708, decode.d0.loss_mask: 0.4943, decode.d0.loss_dice: 0.7426, decode.d1.loss_cls: 0.2958, decode.d1.loss_mask: 0.4672, decode.d1.loss_dice: 0.6718, decode.d2.loss_cls: 0.2234, decode.d2.loss_mask: 0.4622, decode.d2.loss_dice: 0.6541, decode.d3.loss_cls: 0.1891, decode.d3.loss_mask: 0.4577, decode.d3.loss_dice: 0.6401, decode.d4.loss_cls: 0.1805, decode.d4.loss_mask: 0.4608, decode.d4.loss_dice: 0.6465, decode.d5.loss_cls: 0.1766, decode.d5.loss_mask: 0.4597, decode.d5.loss_dice: 0.6387, decode.d6.loss_cls: 0.1677, decode.d6.loss_mask: 0.4610, decode.d6.loss_dice: 0.6365, decode.d7.loss_cls: 0.1674, decode.d7.loss_mask: 0.4606, decode.d7.loss_dice: 0.6369, decode.d8.loss_cls: 0.1755, decode.d8.loss_mask: 0.4602, decode.d8.loss_dice: 0.6412, loss: 14.8103 +2022-05-06 05:00:58,460 - mmseg - INFO - Iter [19100/40000] lr: 7.502e-07, eta: 5:12:33, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1732, decode.loss_mask: 0.4346, decode.loss_dice: 0.6274, decode.d0.loss_cls: 1.8558, decode.d0.loss_mask: 0.4746, decode.d0.loss_dice: 0.7439, decode.d1.loss_cls: 0.2850, decode.d1.loss_mask: 0.4490, decode.d1.loss_dice: 0.6707, decode.d2.loss_cls: 0.2139, decode.d2.loss_mask: 0.4414, decode.d2.loss_dice: 0.6435, decode.d3.loss_cls: 0.1967, decode.d3.loss_mask: 0.4381, decode.d3.loss_dice: 0.6356, decode.d4.loss_cls: 0.1858, decode.d4.loss_mask: 0.4366, decode.d4.loss_dice: 0.6363, decode.d5.loss_cls: 0.1788, decode.d5.loss_mask: 0.4369, decode.d5.loss_dice: 0.6376, decode.d6.loss_cls: 0.1724, decode.d6.loss_mask: 0.4342, decode.d6.loss_dice: 0.6269, decode.d7.loss_cls: 0.1739, decode.d7.loss_mask: 0.4334, decode.d7.loss_dice: 0.6296, decode.d8.loss_cls: 0.1720, decode.d8.loss_mask: 0.4349, decode.d8.loss_dice: 0.6310, loss: 14.5038 +2022-05-06 05:01:31,994 - mmseg - INFO - Iter [19150/40000] lr: 7.484e-07, eta: 5:11:32, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1756, decode.loss_mask: 0.4483, decode.loss_dice: 0.6275, decode.d0.loss_cls: 1.8334, decode.d0.loss_mask: 0.4858, decode.d0.loss_dice: 0.7386, decode.d1.loss_cls: 0.3054, decode.d1.loss_mask: 0.4634, decode.d1.loss_dice: 0.6689, decode.d2.loss_cls: 0.2062, decode.d2.loss_mask: 0.4527, decode.d2.loss_dice: 0.6490, decode.d3.loss_cls: 0.1913, decode.d3.loss_mask: 0.4482, decode.d3.loss_dice: 0.6321, decode.d4.loss_cls: 0.1819, decode.d4.loss_mask: 0.4518, decode.d4.loss_dice: 0.6365, decode.d5.loss_cls: 0.1775, decode.d5.loss_mask: 0.4495, decode.d5.loss_dice: 0.6384, decode.d6.loss_cls: 0.1764, decode.d6.loss_mask: 0.4490, decode.d6.loss_dice: 0.6264, decode.d7.loss_cls: 0.1721, decode.d7.loss_mask: 0.4485, decode.d7.loss_dice: 0.6330, decode.d8.loss_cls: 0.1715, decode.d8.loss_mask: 0.4473, decode.d8.loss_dice: 0.6329, loss: 14.6191 +2022-05-06 05:02:05,556 - mmseg - INFO - Iter [19200/40000] lr: 7.466e-07, eta: 5:10:32, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1751, decode.loss_mask: 0.4513, decode.loss_dice: 0.6307, decode.d0.loss_cls: 1.8515, decode.d0.loss_mask: 0.4960, decode.d0.loss_dice: 0.7447, decode.d1.loss_cls: 0.3174, decode.d1.loss_mask: 0.4668, decode.d1.loss_dice: 0.6751, decode.d2.loss_cls: 0.2262, decode.d2.loss_mask: 0.4567, decode.d2.loss_dice: 0.6496, decode.d3.loss_cls: 0.2017, decode.d3.loss_mask: 0.4526, decode.d3.loss_dice: 0.6383, decode.d4.loss_cls: 0.1869, decode.d4.loss_mask: 0.4524, decode.d4.loss_dice: 0.6371, decode.d5.loss_cls: 0.1803, decode.d5.loss_mask: 0.4520, decode.d5.loss_dice: 0.6347, decode.d6.loss_cls: 0.1733, decode.d6.loss_mask: 0.4499, decode.d6.loss_dice: 0.6298, decode.d7.loss_cls: 0.1734, decode.d7.loss_mask: 0.4508, decode.d7.loss_dice: 0.6269, decode.d8.loss_cls: 0.1755, decode.d8.loss_mask: 0.4536, decode.d8.loss_dice: 0.6368, loss: 14.7472 +2022-05-06 05:02:39,345 - mmseg - INFO - Iter [19250/40000] lr: 7.449e-07, eta: 5:09:32, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1721, decode.loss_mask: 0.4387, decode.loss_dice: 0.6422, decode.d0.loss_cls: 1.9033, decode.d0.loss_mask: 0.4721, decode.d0.loss_dice: 0.7574, decode.d1.loss_cls: 0.3230, decode.d1.loss_mask: 0.4496, decode.d1.loss_dice: 0.6841, decode.d2.loss_cls: 0.2315, decode.d2.loss_mask: 0.4420, decode.d2.loss_dice: 0.6609, decode.d3.loss_cls: 0.1990, decode.d3.loss_mask: 0.4386, decode.d3.loss_dice: 0.6466, decode.d4.loss_cls: 0.1850, decode.d4.loss_mask: 0.4378, decode.d4.loss_dice: 0.6469, decode.d5.loss_cls: 0.1850, decode.d5.loss_mask: 0.4366, decode.d5.loss_dice: 0.6449, decode.d6.loss_cls: 0.1679, decode.d6.loss_mask: 0.4380, decode.d6.loss_dice: 0.6442, decode.d7.loss_cls: 0.1681, decode.d7.loss_mask: 0.4379, decode.d7.loss_dice: 0.6432, decode.d8.loss_cls: 0.1680, decode.d8.loss_mask: 0.4386, decode.d8.loss_dice: 0.6434, loss: 14.7464 +2022-05-06 05:03:15,386 - mmseg - INFO - Iter [19300/40000] lr: 7.431e-07, eta: 5:08:36, time: 0.721, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1825, decode.loss_mask: 0.4549, decode.loss_dice: 0.6146, decode.d0.loss_cls: 1.9071, decode.d0.loss_mask: 0.4911, decode.d0.loss_dice: 0.7201, decode.d1.loss_cls: 0.3109, decode.d1.loss_mask: 0.4719, decode.d1.loss_dice: 0.6540, decode.d2.loss_cls: 0.2217, decode.d2.loss_mask: 0.4579, decode.d2.loss_dice: 0.6265, decode.d3.loss_cls: 0.2032, decode.d3.loss_mask: 0.4553, decode.d3.loss_dice: 0.6159, decode.d4.loss_cls: 0.1881, decode.d4.loss_mask: 0.4559, decode.d4.loss_dice: 0.6236, decode.d5.loss_cls: 0.1842, decode.d5.loss_mask: 0.4525, decode.d5.loss_dice: 0.6152, decode.d6.loss_cls: 0.1853, decode.d6.loss_mask: 0.4532, decode.d6.loss_dice: 0.6095, decode.d7.loss_cls: 0.1815, decode.d7.loss_mask: 0.4540, decode.d7.loss_dice: 0.6103, decode.d8.loss_cls: 0.1774, decode.d8.loss_mask: 0.4523, decode.d8.loss_dice: 0.6197, loss: 14.6504 +2022-05-06 05:03:49,118 - mmseg - INFO - Iter [19350/40000] lr: 7.413e-07, eta: 5:07:36, time: 0.675, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1648, decode.loss_mask: 0.4480, decode.loss_dice: 0.6182, decode.d0.loss_cls: 1.8734, decode.d0.loss_mask: 0.4880, decode.d0.loss_dice: 0.7376, decode.d1.loss_cls: 0.2958, decode.d1.loss_mask: 0.4609, decode.d1.loss_dice: 0.6625, decode.d2.loss_cls: 0.2163, decode.d2.loss_mask: 0.4518, decode.d2.loss_dice: 0.6344, decode.d3.loss_cls: 0.1843, decode.d3.loss_mask: 0.4469, decode.d3.loss_dice: 0.6223, decode.d4.loss_cls: 0.1756, decode.d4.loss_mask: 0.4466, decode.d4.loss_dice: 0.6239, decode.d5.loss_cls: 0.1681, decode.d5.loss_mask: 0.4446, decode.d5.loss_dice: 0.6229, decode.d6.loss_cls: 0.1678, decode.d6.loss_mask: 0.4474, decode.d6.loss_dice: 0.6229, decode.d7.loss_cls: 0.1659, decode.d7.loss_mask: 0.4464, decode.d7.loss_dice: 0.6251, decode.d8.loss_cls: 0.1631, decode.d8.loss_mask: 0.4475, decode.d8.loss_dice: 0.6241, loss: 14.4970 +2022-05-06 05:04:22,566 - mmseg - INFO - Iter [19400/40000] lr: 7.395e-07, eta: 5:06:36, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1623, decode.loss_mask: 0.4421, decode.loss_dice: 0.6347, decode.d0.loss_cls: 1.8488, decode.d0.loss_mask: 0.4863, decode.d0.loss_dice: 0.7531, decode.d1.loss_cls: 0.2818, decode.d1.loss_mask: 0.4650, decode.d1.loss_dice: 0.6775, decode.d2.loss_cls: 0.2122, decode.d2.loss_mask: 0.4528, decode.d2.loss_dice: 0.6578, decode.d3.loss_cls: 0.1826, decode.d3.loss_mask: 0.4483, decode.d3.loss_dice: 0.6447, decode.d4.loss_cls: 0.1717, decode.d4.loss_mask: 0.4452, decode.d4.loss_dice: 0.6418, decode.d5.loss_cls: 0.1640, decode.d5.loss_mask: 0.4448, decode.d5.loss_dice: 0.6400, decode.d6.loss_cls: 0.1570, decode.d6.loss_mask: 0.4430, decode.d6.loss_dice: 0.6301, decode.d7.loss_cls: 0.1561, decode.d7.loss_mask: 0.4432, decode.d7.loss_dice: 0.6373, decode.d8.loss_cls: 0.1550, decode.d8.loss_mask: 0.4430, decode.d8.loss_dice: 0.6367, loss: 14.5589 +2022-05-06 05:04:56,220 - mmseg - INFO - Iter [19450/40000] lr: 7.377e-07, eta: 5:05:37, time: 0.673, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1785, decode.loss_mask: 0.4670, decode.loss_dice: 0.6198, decode.d0.loss_cls: 1.8097, decode.d0.loss_mask: 0.5044, decode.d0.loss_dice: 0.7414, decode.d1.loss_cls: 0.2965, decode.d1.loss_mask: 0.4835, decode.d1.loss_dice: 0.6695, decode.d2.loss_cls: 0.2190, decode.d2.loss_mask: 0.4739, decode.d2.loss_dice: 0.6484, decode.d3.loss_cls: 0.1907, decode.d3.loss_mask: 0.4712, decode.d3.loss_dice: 0.6317, decode.d4.loss_cls: 0.1917, decode.d4.loss_mask: 0.4691, decode.d4.loss_dice: 0.6287, decode.d5.loss_cls: 0.1854, decode.d5.loss_mask: 0.4680, decode.d5.loss_dice: 0.6328, decode.d6.loss_cls: 0.1809, decode.d6.loss_mask: 0.4669, decode.d6.loss_dice: 0.6239, decode.d7.loss_cls: 0.1833, decode.d7.loss_mask: 0.4649, decode.d7.loss_dice: 0.6304, decode.d8.loss_cls: 0.1803, decode.d8.loss_mask: 0.4659, decode.d8.loss_dice: 0.6267, loss: 14.8042 +2022-05-06 05:05:30,332 - mmseg - INFO - Iter [19500/40000] lr: 7.359e-07, eta: 5:04:38, time: 0.681, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1640, decode.loss_mask: 0.4544, decode.loss_dice: 0.6232, decode.d0.loss_cls: 1.8459, decode.d0.loss_mask: 0.4889, decode.d0.loss_dice: 0.7239, decode.d1.loss_cls: 0.2908, decode.d1.loss_mask: 0.4648, decode.d1.loss_dice: 0.6529, decode.d2.loss_cls: 0.2144, decode.d2.loss_mask: 0.4541, decode.d2.loss_dice: 0.6340, decode.d3.loss_cls: 0.1893, decode.d3.loss_mask: 0.4506, decode.d3.loss_dice: 0.6192, decode.d4.loss_cls: 0.1725, decode.d4.loss_mask: 0.4536, decode.d4.loss_dice: 0.6286, decode.d5.loss_cls: 0.1780, decode.d5.loss_mask: 0.4521, decode.d5.loss_dice: 0.6186, decode.d6.loss_cls: 0.1654, decode.d6.loss_mask: 0.4517, decode.d6.loss_dice: 0.6147, decode.d7.loss_cls: 0.1607, decode.d7.loss_mask: 0.4545, decode.d7.loss_dice: 0.6198, decode.d8.loss_cls: 0.1642, decode.d8.loss_mask: 0.4538, decode.d8.loss_dice: 0.6189, loss: 14.4777 +2022-05-06 05:06:04,285 - mmseg - INFO - Iter [19550/40000] lr: 7.341e-07, eta: 5:03:40, time: 0.680, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1565, decode.loss_mask: 0.4533, decode.loss_dice: 0.6208, decode.d0.loss_cls: 1.8261, decode.d0.loss_mask: 0.4932, decode.d0.loss_dice: 0.7177, decode.d1.loss_cls: 0.2796, decode.d1.loss_mask: 0.4697, decode.d1.loss_dice: 0.6572, decode.d2.loss_cls: 0.2037, decode.d2.loss_mask: 0.4585, decode.d2.loss_dice: 0.6279, decode.d3.loss_cls: 0.1778, decode.d3.loss_mask: 0.4536, decode.d3.loss_dice: 0.6157, decode.d4.loss_cls: 0.1674, decode.d4.loss_mask: 0.4546, decode.d4.loss_dice: 0.6200, decode.d5.loss_cls: 0.1697, decode.d5.loss_mask: 0.4535, decode.d5.loss_dice: 0.6191, decode.d6.loss_cls: 0.1675, decode.d6.loss_mask: 0.4508, decode.d6.loss_dice: 0.6117, decode.d7.loss_cls: 0.1563, decode.d7.loss_mask: 0.4527, decode.d7.loss_dice: 0.6179, decode.d8.loss_cls: 0.1558, decode.d8.loss_mask: 0.4526, decode.d8.loss_dice: 0.6169, loss: 14.3777 +2022-05-06 05:06:40,574 - mmseg - INFO - Iter [19600/40000] lr: 7.323e-07, eta: 5:02:45, time: 0.726, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1660, decode.loss_mask: 0.4542, decode.loss_dice: 0.6218, decode.d0.loss_cls: 1.8415, decode.d0.loss_mask: 0.4916, decode.d0.loss_dice: 0.7387, decode.d1.loss_cls: 0.2687, decode.d1.loss_mask: 0.4714, decode.d1.loss_dice: 0.6674, decode.d2.loss_cls: 0.2075, decode.d2.loss_mask: 0.4639, decode.d2.loss_dice: 0.6429, decode.d3.loss_cls: 0.1830, decode.d3.loss_mask: 0.4616, decode.d3.loss_dice: 0.6268, decode.d4.loss_cls: 0.1746, decode.d4.loss_mask: 0.4580, decode.d4.loss_dice: 0.6272, decode.d5.loss_cls: 0.1650, decode.d5.loss_mask: 0.4565, decode.d5.loss_dice: 0.6291, decode.d6.loss_cls: 0.1613, decode.d6.loss_mask: 0.4561, decode.d6.loss_dice: 0.6245, decode.d7.loss_cls: 0.1568, decode.d7.loss_mask: 0.4563, decode.d7.loss_dice: 0.6274, decode.d8.loss_cls: 0.1608, decode.d8.loss_mask: 0.4550, decode.d8.loss_dice: 0.6280, loss: 14.5436 +2022-05-06 05:07:14,242 - mmseg - INFO - Iter [19650/40000] lr: 7.305e-07, eta: 5:01:46, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1546, decode.loss_mask: 0.4532, decode.loss_dice: 0.6285, decode.d0.loss_cls: 1.8232, decode.d0.loss_mask: 0.4934, decode.d0.loss_dice: 0.7356, decode.d1.loss_cls: 0.2765, decode.d1.loss_mask: 0.4678, decode.d1.loss_dice: 0.6652, decode.d2.loss_cls: 0.2082, decode.d2.loss_mask: 0.4617, decode.d2.loss_dice: 0.6470, decode.d3.loss_cls: 0.1840, decode.d3.loss_mask: 0.4557, decode.d3.loss_dice: 0.6311, decode.d4.loss_cls: 0.1783, decode.d4.loss_mask: 0.4521, decode.d4.loss_dice: 0.6295, decode.d5.loss_cls: 0.1734, decode.d5.loss_mask: 0.4528, decode.d5.loss_dice: 0.6325, decode.d6.loss_cls: 0.1640, decode.d6.loss_mask: 0.4529, decode.d6.loss_dice: 0.6297, decode.d7.loss_cls: 0.1640, decode.d7.loss_mask: 0.4514, decode.d7.loss_dice: 0.6329, decode.d8.loss_cls: 0.1616, decode.d8.loss_mask: 0.4511, decode.d8.loss_dice: 0.6304, loss: 14.5421 +2022-05-06 05:07:47,668 - mmseg - INFO - Iter [19700/40000] lr: 7.287e-07, eta: 5:00:47, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1420, decode.loss_mask: 0.4555, decode.loss_dice: 0.5920, decode.d0.loss_cls: 1.7653, decode.d0.loss_mask: 0.4962, decode.d0.loss_dice: 0.7107, decode.d1.loss_cls: 0.2535, decode.d1.loss_mask: 0.4697, decode.d1.loss_dice: 0.6316, decode.d2.loss_cls: 0.1833, decode.d2.loss_mask: 0.4603, decode.d2.loss_dice: 0.6100, decode.d3.loss_cls: 0.1560, decode.d3.loss_mask: 0.4582, decode.d3.loss_dice: 0.5979, decode.d4.loss_cls: 0.1544, decode.d4.loss_mask: 0.4577, decode.d4.loss_dice: 0.6037, decode.d5.loss_cls: 0.1501, decode.d5.loss_mask: 0.4581, decode.d5.loss_dice: 0.5970, decode.d6.loss_cls: 0.1469, decode.d6.loss_mask: 0.4575, decode.d6.loss_dice: 0.5892, decode.d7.loss_cls: 0.1431, decode.d7.loss_mask: 0.4549, decode.d7.loss_dice: 0.5931, decode.d8.loss_cls: 0.1413, decode.d8.loss_mask: 0.4571, decode.d8.loss_dice: 0.5946, loss: 13.9811 +2022-05-06 05:08:21,767 - mmseg - INFO - Iter [19750/40000] lr: 7.269e-07, eta: 4:59:49, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1659, decode.loss_mask: 0.4494, decode.loss_dice: 0.6326, decode.d0.loss_cls: 1.7976, decode.d0.loss_mask: 0.4879, decode.d0.loss_dice: 0.7266, decode.d1.loss_cls: 0.3073, decode.d1.loss_mask: 0.4660, decode.d1.loss_dice: 0.6665, decode.d2.loss_cls: 0.2210, decode.d2.loss_mask: 0.4557, decode.d2.loss_dice: 0.6478, decode.d3.loss_cls: 0.1907, decode.d3.loss_mask: 0.4522, decode.d3.loss_dice: 0.6320, decode.d4.loss_cls: 0.1866, decode.d4.loss_mask: 0.4533, decode.d4.loss_dice: 0.6380, decode.d5.loss_cls: 0.1764, decode.d5.loss_mask: 0.4504, decode.d5.loss_dice: 0.6318, decode.d6.loss_cls: 0.1721, decode.d6.loss_mask: 0.4479, decode.d6.loss_dice: 0.6284, decode.d7.loss_cls: 0.1675, decode.d7.loss_mask: 0.4513, decode.d7.loss_dice: 0.6308, decode.d8.loss_cls: 0.1687, decode.d8.loss_mask: 0.4491, decode.d8.loss_dice: 0.6287, loss: 14.5804 +2022-05-06 05:08:55,004 - mmseg - INFO - Iter [19800/40000] lr: 7.251e-07, eta: 4:58:51, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1759, decode.loss_mask: 0.4615, decode.loss_dice: 0.6227, decode.d0.loss_cls: 1.8564, decode.d0.loss_mask: 0.5033, decode.d0.loss_dice: 0.7338, decode.d1.loss_cls: 0.2874, decode.d1.loss_mask: 0.4803, decode.d1.loss_dice: 0.6648, decode.d2.loss_cls: 0.2130, decode.d2.loss_mask: 0.4662, decode.d2.loss_dice: 0.6437, decode.d3.loss_cls: 0.1943, decode.d3.loss_mask: 0.4633, decode.d3.loss_dice: 0.6327, decode.d4.loss_cls: 0.1910, decode.d4.loss_mask: 0.4614, decode.d4.loss_dice: 0.6302, decode.d5.loss_cls: 0.1827, decode.d5.loss_mask: 0.4586, decode.d5.loss_dice: 0.6251, decode.d6.loss_cls: 0.1781, decode.d6.loss_mask: 0.4592, decode.d6.loss_dice: 0.6250, decode.d7.loss_cls: 0.1707, decode.d7.loss_mask: 0.4601, decode.d7.loss_dice: 0.6282, decode.d8.loss_cls: 0.1734, decode.d8.loss_mask: 0.4583, decode.d8.loss_dice: 0.6251, loss: 14.7265 +2022-05-06 05:09:28,464 - mmseg - INFO - Iter [19850/40000] lr: 7.233e-07, eta: 4:57:52, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1387, decode.loss_mask: 0.4489, decode.loss_dice: 0.5868, decode.d0.loss_cls: 1.7977, decode.d0.loss_mask: 0.4820, decode.d0.loss_dice: 0.6872, decode.d1.loss_cls: 0.2598, decode.d1.loss_mask: 0.4608, decode.d1.loss_dice: 0.6217, decode.d2.loss_cls: 0.1857, decode.d2.loss_mask: 0.4522, decode.d2.loss_dice: 0.6011, decode.d3.loss_cls: 0.1563, decode.d3.loss_mask: 0.4506, decode.d3.loss_dice: 0.5958, decode.d4.loss_cls: 0.1522, decode.d4.loss_mask: 0.4516, decode.d4.loss_dice: 0.5909, decode.d5.loss_cls: 0.1448, decode.d5.loss_mask: 0.4463, decode.d5.loss_dice: 0.5910, decode.d6.loss_cls: 0.1381, decode.d6.loss_mask: 0.4481, decode.d6.loss_dice: 0.5893, decode.d7.loss_cls: 0.1359, decode.d7.loss_mask: 0.4473, decode.d7.loss_dice: 0.5951, decode.d8.loss_cls: 0.1386, decode.d8.loss_mask: 0.4481, decode.d8.loss_dice: 0.5910, loss: 13.8338 +2022-05-06 05:10:02,619 - mmseg - INFO - Iter [19900/40000] lr: 7.215e-07, eta: 4:56:55, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1891, decode.loss_mask: 0.4339, decode.loss_dice: 0.6447, decode.d0.loss_cls: 1.8680, decode.d0.loss_mask: 0.4717, decode.d0.loss_dice: 0.7585, decode.d1.loss_cls: 0.3197, decode.d1.loss_mask: 0.4473, decode.d1.loss_dice: 0.6817, decode.d2.loss_cls: 0.2319, decode.d2.loss_mask: 0.4385, decode.d2.loss_dice: 0.6619, decode.d3.loss_cls: 0.2011, decode.d3.loss_mask: 0.4369, decode.d3.loss_dice: 0.6544, decode.d4.loss_cls: 0.1972, decode.d4.loss_mask: 0.4349, decode.d4.loss_dice: 0.6488, decode.d5.loss_cls: 0.1927, decode.d5.loss_mask: 0.4345, decode.d5.loss_dice: 0.6402, decode.d6.loss_cls: 0.1848, decode.d6.loss_mask: 0.4346, decode.d6.loss_dice: 0.6409, decode.d7.loss_cls: 0.1883, decode.d7.loss_mask: 0.4321, decode.d7.loss_dice: 0.6423, decode.d8.loss_cls: 0.1938, decode.d8.loss_mask: 0.4324, decode.d8.loss_dice: 0.6379, loss: 14.7749 +2022-05-06 05:10:38,920 - mmseg - INFO - Iter [19950/40000] lr: 7.197e-07, eta: 4:56:01, time: 0.726, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1614, decode.loss_mask: 0.4376, decode.loss_dice: 0.6074, decode.d0.loss_cls: 1.8016, decode.d0.loss_mask: 0.4837, decode.d0.loss_dice: 0.7164, decode.d1.loss_cls: 0.2825, decode.d1.loss_mask: 0.4551, decode.d1.loss_dice: 0.6544, decode.d2.loss_cls: 0.2028, decode.d2.loss_mask: 0.4416, decode.d2.loss_dice: 0.6307, decode.d3.loss_cls: 0.1784, decode.d3.loss_mask: 0.4415, decode.d3.loss_dice: 0.6177, decode.d4.loss_cls: 0.1708, decode.d4.loss_mask: 0.4388, decode.d4.loss_dice: 0.6196, decode.d5.loss_cls: 0.1656, decode.d5.loss_mask: 0.4384, decode.d5.loss_dice: 0.6124, decode.d6.loss_cls: 0.1637, decode.d6.loss_mask: 0.4383, decode.d6.loss_dice: 0.6095, decode.d7.loss_cls: 0.1644, decode.d7.loss_mask: 0.4352, decode.d7.loss_dice: 0.6090, decode.d8.loss_cls: 0.1642, decode.d8.loss_mask: 0.4366, decode.d8.loss_dice: 0.6080, loss: 14.1875 +2022-05-06 05:11:12,729 - mmseg - INFO - Saving checkpoint at 20000 iterations +2022-05-06 05:11:40,320 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 05:11:40,322 - mmseg - INFO - Iter [20000/40000] lr: 7.179e-07, eta: 4:55:38, time: 1.226, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1470, decode.loss_mask: 0.4392, decode.loss_dice: 0.6054, decode.d0.loss_cls: 1.8012, decode.d0.loss_mask: 0.4734, decode.d0.loss_dice: 0.7078, decode.d1.loss_cls: 0.2757, decode.d1.loss_mask: 0.4535, decode.d1.loss_dice: 0.6450, decode.d2.loss_cls: 0.1875, decode.d2.loss_mask: 0.4464, decode.d2.loss_dice: 0.6246, decode.d3.loss_cls: 0.1660, decode.d3.loss_mask: 0.4421, decode.d3.loss_dice: 0.6094, decode.d4.loss_cls: 0.1520, decode.d4.loss_mask: 0.4410, decode.d4.loss_dice: 0.6109, decode.d5.loss_cls: 0.1471, decode.d5.loss_mask: 0.4411, decode.d5.loss_dice: 0.6063, decode.d6.loss_cls: 0.1419, decode.d6.loss_mask: 0.4406, decode.d6.loss_dice: 0.6050, decode.d7.loss_cls: 0.1439, decode.d7.loss_mask: 0.4403, decode.d7.loss_dice: 0.6037, decode.d8.loss_cls: 0.1444, decode.d8.loss_mask: 0.4406, decode.d8.loss_dice: 0.6046, loss: 13.9877 +2022-05-06 05:16:00,752 - mmseg - INFO - per class results: +2022-05-06 05:16:00,755 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.69 | 95.7 | +| bag | 45.57 | 71.7 | +| bed | 36.46 | 46.27 | +| bedclothes | 45.35 | 64.1 | +| bench | 27.85 | 38.82 | +| bicycle | 85.39 | 92.97 | +| bird | 95.09 | 97.88 | +| boat | 87.88 | 93.38 | +| book | 59.92 | 76.19 | +| bottle | 89.74 | 96.7 | +| building | 65.39 | 76.21 | +| bus | 94.97 | 97.32 | +| cabinet | 52.91 | 64.79 | +| car | 93.56 | 96.94 | +| cat | 94.59 | 98.45 | +| ceiling | 61.58 | 81.16 | +| chair | 65.59 | 81.58 | +| cloth | 30.1 | 42.28 | +| computer | 61.12 | 72.87 | +| cow | 95.98 | 97.66 | +| cup | 50.6 | 68.13 | +| curtain | 60.86 | 72.93 | +| dog | 92.85 | 97.33 | +| door | 39.08 | 59.78 | +| fence | 46.14 | 59.54 | +| floor | 74.24 | 90.44 | +| flower | 46.68 | 61.7 | +| food | 42.81 | 54.99 | +| grass | 82.98 | 90.83 | +| ground | 57.4 | 72.58 | +| horse | 95.36 | 97.6 | +| keyboard | 88.11 | 95.86 | +| light | 60.38 | 81.67 | +| motorbike | 92.45 | 97.33 | +| mountain | 51.21 | 74.54 | +| mouse | 90.13 | 93.18 | +| person | 91.71 | 96.34 | +| plate | 32.63 | 46.73 | +| platform | 49.92 | 59.37 | +| pottedplant | 83.94 | 91.88 | +| road | 54.89 | 69.94 | +| rock | 47.82 | 54.38 | +| sheep | 95.42 | 97.96 | +| shelves | 40.8 | 63.84 | +| sidewalk | 28.85 | 51.04 | +| sign | 56.92 | 71.58 | +| sky | 94.88 | 97.06 | +| snow | 80.01 | 88.37 | +| sofa | 62.11 | 72.36 | +| table | 71.14 | 82.01 | +| track | 72.82 | 82.83 | +| train | 93.05 | 96.99 | +| tree | 81.87 | 89.59 | +| truck | 55.78 | 65.21 | +| tvmonitor | 91.0 | 93.92 | +| wall | 71.91 | 86.13 | +| water | 92.71 | 95.89 | +| window | 45.87 | 66.26 | +| wood | 29.27 | 38.83 | ++-------------+-------+-------+ +2022-05-06 05:16:00,755 - mmseg - INFO - Summary: +2022-05-06 05:16:00,755 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.38 | 67.43 | 78.13 | ++-------+-------+-------+ +2022-05-06 05:16:00,758 - mmseg - INFO - The previous best checkpoint /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/best_mIoU_iter_12000.pth was removed +2022-05-06 05:16:27,225 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_20000.pth. +2022-05-06 05:16:27,235 - mmseg - INFO - Best mIoU is 0.6743 at 20000 iter. +2022-05-06 05:16:27,272 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 05:16:27,272 - mmseg - INFO - Iter(val) [638] aAcc: 0.8638, mIoU: 0.6743, mAcc: 0.7813, IoU.aeroplane: 0.9269, IoU.bag: 0.4557, IoU.bed: 0.3646, IoU.bedclothes: 0.4535, IoU.bench: 0.2785, IoU.bicycle: 0.8539, IoU.bird: 0.9509, IoU.boat: 0.8788, IoU.book: 0.5992, IoU.bottle: 0.8974, IoU.building: 0.6539, IoU.bus: 0.9497, IoU.cabinet: 0.5291, IoU.car: 0.9356, IoU.cat: 0.9459, IoU.ceiling: 0.6158, IoU.chair: 0.6559, IoU.cloth: 0.3010, IoU.computer: 0.6112, IoU.cow: 0.9598, IoU.cup: 0.5060, IoU.curtain: 0.6086, IoU.dog: 0.9285, IoU.door: 0.3908, IoU.fence: 0.4614, IoU.floor: 0.7424, IoU.flower: 0.4668, IoU.food: 0.4281, IoU.grass: 0.8298, IoU.ground: 0.5740, IoU.horse: 0.9536, IoU.keyboard: 0.8811, IoU.light: 0.6038, IoU.motorbike: 0.9245, IoU.mountain: 0.5121, IoU.mouse: 0.9013, IoU.person: 0.9171, IoU.plate: 0.3263, IoU.platform: 0.4992, IoU.pottedplant: 0.8394, IoU.road: 0.5489, IoU.rock: 0.4782, IoU.sheep: 0.9542, IoU.shelves: 0.4080, IoU.sidewalk: 0.2885, IoU.sign: 0.5692, IoU.sky: 0.9488, IoU.snow: 0.8001, IoU.sofa: 0.6211, IoU.table: 0.7114, IoU.track: 0.7282, IoU.train: 0.9305, IoU.tree: 0.8187, IoU.truck: 0.5578, IoU.tvmonitor: 0.9100, IoU.wall: 0.7191, IoU.water: 0.9271, IoU.window: 0.4587, IoU.wood: 0.2927, Acc.aeroplane: 0.9570, Acc.bag: 0.7170, Acc.bed: 0.4627, Acc.bedclothes: 0.6410, Acc.bench: 0.3882, Acc.bicycle: 0.9297, Acc.bird: 0.9788, Acc.boat: 0.9338, Acc.book: 0.7619, Acc.bottle: 0.9670, Acc.building: 0.7621, Acc.bus: 0.9732, Acc.cabinet: 0.6479, Acc.car: 0.9694, Acc.cat: 0.9845, Acc.ceiling: 0.8116, Acc.chair: 0.8158, Acc.cloth: 0.4228, Acc.computer: 0.7287, Acc.cow: 0.9766, Acc.cup: 0.6813, Acc.curtain: 0.7293, Acc.dog: 0.9733, Acc.door: 0.5978, Acc.fence: 0.5954, Acc.floor: 0.9044, Acc.flower: 0.6170, Acc.food: 0.5499, Acc.grass: 0.9083, Acc.ground: 0.7258, Acc.horse: 0.9760, Acc.keyboard: 0.9586, Acc.light: 0.8167, Acc.motorbike: 0.9733, Acc.mountain: 0.7454, Acc.mouse: 0.9318, Acc.person: 0.9634, Acc.plate: 0.4673, Acc.platform: 0.5937, Acc.pottedplant: 0.9188, Acc.road: 0.6994, Acc.rock: 0.5438, Acc.sheep: 0.9796, Acc.shelves: 0.6384, Acc.sidewalk: 0.5104, Acc.sign: 0.7158, Acc.sky: 0.9706, Acc.snow: 0.8837, Acc.sofa: 0.7236, Acc.table: 0.8201, Acc.track: 0.8283, Acc.train: 0.9699, Acc.tree: 0.8959, Acc.truck: 0.6521, Acc.tvmonitor: 0.9392, Acc.wall: 0.8613, Acc.water: 0.9589, Acc.window: 0.6626, Acc.wood: 0.3883 +2022-05-06 05:17:01,442 - mmseg - INFO - Iter [20050/40000] lr: 7.161e-07, eta: 5:00:38, time: 6.424, data_time: 5.750, memory: 53770, decode.loss_cls: 0.1766, decode.loss_mask: 0.4616, decode.loss_dice: 0.6205, decode.d0.loss_cls: 1.7873, decode.d0.loss_mask: 0.5037, decode.d0.loss_dice: 0.7221, decode.d1.loss_cls: 0.2926, decode.d1.loss_mask: 0.4753, decode.d1.loss_dice: 0.6530, decode.d2.loss_cls: 0.2146, decode.d2.loss_mask: 0.4654, decode.d2.loss_dice: 0.6329, decode.d3.loss_cls: 0.1929, decode.d3.loss_mask: 0.4602, decode.d3.loss_dice: 0.6327, decode.d4.loss_cls: 0.1945, decode.d4.loss_mask: 0.4587, decode.d4.loss_dice: 0.6233, decode.d5.loss_cls: 0.1894, decode.d5.loss_mask: 0.4591, decode.d5.loss_dice: 0.6215, decode.d6.loss_cls: 0.1829, decode.d6.loss_mask: 0.4580, decode.d6.loss_dice: 0.6202, decode.d7.loss_cls: 0.1707, decode.d7.loss_mask: 0.4622, decode.d7.loss_dice: 0.6226, decode.d8.loss_cls: 0.1765, decode.d8.loss_mask: 0.4612, decode.d8.loss_dice: 0.6191, loss: 14.6113 +2022-05-06 05:17:35,018 - mmseg - INFO - Iter [20100/40000] lr: 7.143e-07, eta: 4:59:38, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1643, decode.loss_mask: 0.4471, decode.loss_dice: 0.6126, decode.d0.loss_cls: 1.7834, decode.d0.loss_mask: 0.4901, decode.d0.loss_dice: 0.7327, decode.d1.loss_cls: 0.2773, decode.d1.loss_mask: 0.4611, decode.d1.loss_dice: 0.6536, decode.d2.loss_cls: 0.2155, decode.d2.loss_mask: 0.4509, decode.d2.loss_dice: 0.6273, decode.d3.loss_cls: 0.1822, decode.d3.loss_mask: 0.4443, decode.d3.loss_dice: 0.6148, decode.d4.loss_cls: 0.1745, decode.d4.loss_mask: 0.4460, decode.d4.loss_dice: 0.6198, decode.d5.loss_cls: 0.1664, decode.d5.loss_mask: 0.4470, decode.d5.loss_dice: 0.6172, decode.d6.loss_cls: 0.1674, decode.d6.loss_mask: 0.4476, decode.d6.loss_dice: 0.6175, decode.d7.loss_cls: 0.1592, decode.d7.loss_mask: 0.4452, decode.d7.loss_dice: 0.6199, decode.d8.loss_cls: 0.1622, decode.d8.loss_mask: 0.4471, decode.d8.loss_dice: 0.6170, loss: 14.3112 +2022-05-06 05:18:08,999 - mmseg - INFO - Iter [20150/40000] lr: 7.125e-07, eta: 4:58:39, time: 0.680, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1858, decode.loss_mask: 0.4582, decode.loss_dice: 0.6293, decode.d0.loss_cls: 1.8352, decode.d0.loss_mask: 0.5020, decode.d0.loss_dice: 0.7375, decode.d1.loss_cls: 0.3134, decode.d1.loss_mask: 0.4751, decode.d1.loss_dice: 0.6716, decode.d2.loss_cls: 0.2313, decode.d2.loss_mask: 0.4654, decode.d2.loss_dice: 0.6416, decode.d3.loss_cls: 0.2004, decode.d3.loss_mask: 0.4633, decode.d3.loss_dice: 0.6363, decode.d4.loss_cls: 0.1833, decode.d4.loss_mask: 0.4628, decode.d4.loss_dice: 0.6409, decode.d5.loss_cls: 0.1855, decode.d5.loss_mask: 0.4605, decode.d5.loss_dice: 0.6347, decode.d6.loss_cls: 0.1786, decode.d6.loss_mask: 0.4560, decode.d6.loss_dice: 0.6301, decode.d7.loss_cls: 0.1739, decode.d7.loss_mask: 0.4579, decode.d7.loss_dice: 0.6367, decode.d8.loss_cls: 0.1809, decode.d8.loss_mask: 0.4564, decode.d8.loss_dice: 0.6328, loss: 14.8174 +2022-05-06 05:18:42,742 - mmseg - INFO - Iter [20200/40000] lr: 7.108e-07, eta: 4:57:40, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1633, decode.loss_mask: 0.4488, decode.loss_dice: 0.6435, decode.d0.loss_cls: 1.8242, decode.d0.loss_mask: 0.4895, decode.d0.loss_dice: 0.7530, decode.d1.loss_cls: 0.2943, decode.d1.loss_mask: 0.4632, decode.d1.loss_dice: 0.6821, decode.d2.loss_cls: 0.2221, decode.d2.loss_mask: 0.4529, decode.d2.loss_dice: 0.6596, decode.d3.loss_cls: 0.1832, decode.d3.loss_mask: 0.4509, decode.d3.loss_dice: 0.6508, decode.d4.loss_cls: 0.1830, decode.d4.loss_mask: 0.4502, decode.d4.loss_dice: 0.6521, decode.d5.loss_cls: 0.1794, decode.d5.loss_mask: 0.4498, decode.d5.loss_dice: 0.6518, decode.d6.loss_cls: 0.1694, decode.d6.loss_mask: 0.4497, decode.d6.loss_dice: 0.6487, decode.d7.loss_cls: 0.1603, decode.d7.loss_mask: 0.4495, decode.d7.loss_dice: 0.6540, decode.d8.loss_cls: 0.1653, decode.d8.loss_mask: 0.4475, decode.d8.loss_dice: 0.6476, loss: 14.7396 +2022-05-06 05:19:19,155 - mmseg - INFO - Iter [20250/40000] lr: 7.090e-07, eta: 4:56:44, time: 0.728, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1612, decode.loss_mask: 0.4303, decode.loss_dice: 0.6171, decode.d0.loss_cls: 1.7662, decode.d0.loss_mask: 0.4700, decode.d0.loss_dice: 0.7348, decode.d1.loss_cls: 0.2733, decode.d1.loss_mask: 0.4480, decode.d1.loss_dice: 0.6602, decode.d2.loss_cls: 0.2061, decode.d2.loss_mask: 0.4362, decode.d2.loss_dice: 0.6337, decode.d3.loss_cls: 0.1802, decode.d3.loss_mask: 0.4333, decode.d3.loss_dice: 0.6218, decode.d4.loss_cls: 0.1669, decode.d4.loss_mask: 0.4291, decode.d4.loss_dice: 0.6228, decode.d5.loss_cls: 0.1615, decode.d5.loss_mask: 0.4291, decode.d5.loss_dice: 0.6205, decode.d6.loss_cls: 0.1623, decode.d6.loss_mask: 0.4298, decode.d6.loss_dice: 0.6197, decode.d7.loss_cls: 0.1583, decode.d7.loss_mask: 0.4315, decode.d7.loss_dice: 0.6182, decode.d8.loss_cls: 0.1616, decode.d8.loss_mask: 0.4297, decode.d8.loss_dice: 0.6162, loss: 14.1297 +2022-05-06 05:19:53,030 - mmseg - INFO - Iter [20300/40000] lr: 7.072e-07, eta: 4:55:46, time: 0.677, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1712, decode.loss_mask: 0.4369, decode.loss_dice: 0.6307, decode.d0.loss_cls: 1.7876, decode.d0.loss_mask: 0.4769, decode.d0.loss_dice: 0.7440, decode.d1.loss_cls: 0.2976, decode.d1.loss_mask: 0.4482, decode.d1.loss_dice: 0.6778, decode.d2.loss_cls: 0.2154, decode.d2.loss_mask: 0.4383, decode.d2.loss_dice: 0.6517, decode.d3.loss_cls: 0.1865, decode.d3.loss_mask: 0.4387, decode.d3.loss_dice: 0.6342, decode.d4.loss_cls: 0.1771, decode.d4.loss_mask: 0.4398, decode.d4.loss_dice: 0.6349, decode.d5.loss_cls: 0.1724, decode.d5.loss_mask: 0.4382, decode.d5.loss_dice: 0.6377, decode.d6.loss_cls: 0.1733, decode.d6.loss_mask: 0.4372, decode.d6.loss_dice: 0.6350, decode.d7.loss_cls: 0.1737, decode.d7.loss_mask: 0.4376, decode.d7.loss_dice: 0.6328, decode.d8.loss_cls: 0.1737, decode.d8.loss_mask: 0.4374, decode.d8.loss_dice: 0.6339, loss: 14.4703 +2022-05-06 05:20:26,806 - mmseg - INFO - Iter [20350/40000] lr: 7.054e-07, eta: 4:54:47, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1463, decode.loss_mask: 0.4350, decode.loss_dice: 0.6097, decode.d0.loss_cls: 1.8010, decode.d0.loss_mask: 0.4772, decode.d0.loss_dice: 0.7209, decode.d1.loss_cls: 0.2733, decode.d1.loss_mask: 0.4533, decode.d1.loss_dice: 0.6487, decode.d2.loss_cls: 0.2108, decode.d2.loss_mask: 0.4409, decode.d2.loss_dice: 0.6204, decode.d3.loss_cls: 0.1764, decode.d3.loss_mask: 0.4379, decode.d3.loss_dice: 0.6129, decode.d4.loss_cls: 0.1709, decode.d4.loss_mask: 0.4395, decode.d4.loss_dice: 0.6111, decode.d5.loss_cls: 0.1659, decode.d5.loss_mask: 0.4354, decode.d5.loss_dice: 0.6066, decode.d6.loss_cls: 0.1555, decode.d6.loss_mask: 0.4367, decode.d6.loss_dice: 0.6069, decode.d7.loss_cls: 0.1505, decode.d7.loss_mask: 0.4357, decode.d7.loss_dice: 0.6084, decode.d8.loss_cls: 0.1494, decode.d8.loss_mask: 0.4369, decode.d8.loss_dice: 0.6097, loss: 14.0837 +2022-05-06 05:21:00,090 - mmseg - INFO - Iter [20400/40000] lr: 7.036e-07, eta: 4:53:48, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1731, decode.loss_mask: 0.4477, decode.loss_dice: 0.6303, decode.d0.loss_cls: 1.8240, decode.d0.loss_mask: 0.4870, decode.d0.loss_dice: 0.7434, decode.d1.loss_cls: 0.2960, decode.d1.loss_mask: 0.4595, decode.d1.loss_dice: 0.6660, decode.d2.loss_cls: 0.2237, decode.d2.loss_mask: 0.4526, decode.d2.loss_dice: 0.6469, decode.d3.loss_cls: 0.1959, decode.d3.loss_mask: 0.4496, decode.d3.loss_dice: 0.6311, decode.d4.loss_cls: 0.1847, decode.d4.loss_mask: 0.4472, decode.d4.loss_dice: 0.6309, decode.d5.loss_cls: 0.1810, decode.d5.loss_mask: 0.4475, decode.d5.loss_dice: 0.6341, decode.d6.loss_cls: 0.1746, decode.d6.loss_mask: 0.4450, decode.d6.loss_dice: 0.6321, decode.d7.loss_cls: 0.1702, decode.d7.loss_mask: 0.4485, decode.d7.loss_dice: 0.6284, decode.d8.loss_cls: 0.1739, decode.d8.loss_mask: 0.4473, decode.d8.loss_dice: 0.6292, loss: 14.6013 +2022-05-06 05:21:33,817 - mmseg - INFO - Iter [20450/40000] lr: 7.018e-07, eta: 4:52:50, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1535, decode.loss_mask: 0.4594, decode.loss_dice: 0.6259, decode.d0.loss_cls: 1.7864, decode.d0.loss_mask: 0.4979, decode.d0.loss_dice: 0.7354, decode.d1.loss_cls: 0.2901, decode.d1.loss_mask: 0.4738, decode.d1.loss_dice: 0.6687, decode.d2.loss_cls: 0.2036, decode.d2.loss_mask: 0.4665, decode.d2.loss_dice: 0.6464, decode.d3.loss_cls: 0.1799, decode.d3.loss_mask: 0.4604, decode.d3.loss_dice: 0.6279, decode.d4.loss_cls: 0.1743, decode.d4.loss_mask: 0.4581, decode.d4.loss_dice: 0.6282, decode.d5.loss_cls: 0.1613, decode.d5.loss_mask: 0.4577, decode.d5.loss_dice: 0.6266, decode.d6.loss_cls: 0.1612, decode.d6.loss_mask: 0.4582, decode.d6.loss_dice: 0.6232, decode.d7.loss_cls: 0.1606, decode.d7.loss_mask: 0.4580, decode.d7.loss_dice: 0.6256, decode.d8.loss_cls: 0.1566, decode.d8.loss_mask: 0.4574, decode.d8.loss_dice: 0.6253, loss: 14.5083 +2022-05-06 05:22:07,285 - mmseg - INFO - Iter [20500/40000] lr: 7.000e-07, eta: 4:51:51, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1683, decode.loss_mask: 0.4490, decode.loss_dice: 0.6513, decode.d0.loss_cls: 1.8141, decode.d0.loss_mask: 0.4849, decode.d0.loss_dice: 0.7697, decode.d1.loss_cls: 0.2906, decode.d1.loss_mask: 0.4664, decode.d1.loss_dice: 0.6967, decode.d2.loss_cls: 0.2253, decode.d2.loss_mask: 0.4537, decode.d2.loss_dice: 0.6717, decode.d3.loss_cls: 0.1888, decode.d3.loss_mask: 0.4523, decode.d3.loss_dice: 0.6591, decode.d4.loss_cls: 0.1796, decode.d4.loss_mask: 0.4554, decode.d4.loss_dice: 0.6615, decode.d5.loss_cls: 0.1741, decode.d5.loss_mask: 0.4521, decode.d5.loss_dice: 0.6620, decode.d6.loss_cls: 0.1687, decode.d6.loss_mask: 0.4510, decode.d6.loss_dice: 0.6586, decode.d7.loss_cls: 0.1632, decode.d7.loss_mask: 0.4487, decode.d7.loss_dice: 0.6548, decode.d8.loss_cls: 0.1645, decode.d8.loss_mask: 0.4491, decode.d8.loss_dice: 0.6539, loss: 14.8392 +2022-05-06 05:22:43,279 - mmseg - INFO - Iter [20550/40000] lr: 6.982e-07, eta: 4:50:56, time: 0.720, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1437, decode.loss_mask: 0.4533, decode.loss_dice: 0.6023, decode.d0.loss_cls: 1.7366, decode.d0.loss_mask: 0.4958, decode.d0.loss_dice: 0.7029, decode.d1.loss_cls: 0.2549, decode.d1.loss_mask: 0.4707, decode.d1.loss_dice: 0.6365, decode.d2.loss_cls: 0.1940, decode.d2.loss_mask: 0.4610, decode.d2.loss_dice: 0.6137, decode.d3.loss_cls: 0.1622, decode.d3.loss_mask: 0.4584, decode.d3.loss_dice: 0.6078, decode.d4.loss_cls: 0.1569, decode.d4.loss_mask: 0.4556, decode.d4.loss_dice: 0.6061, decode.d5.loss_cls: 0.1574, decode.d5.loss_mask: 0.4532, decode.d5.loss_dice: 0.6029, decode.d6.loss_cls: 0.1463, decode.d6.loss_mask: 0.4536, decode.d6.loss_dice: 0.6037, decode.d7.loss_cls: 0.1447, decode.d7.loss_mask: 0.4532, decode.d7.loss_dice: 0.6032, decode.d8.loss_cls: 0.1451, decode.d8.loss_mask: 0.4534, decode.d8.loss_dice: 0.5975, loss: 14.0265 +2022-05-06 05:23:16,686 - mmseg - INFO - Iter [20600/40000] lr: 6.964e-07, eta: 4:49:58, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1505, decode.loss_mask: 0.4274, decode.loss_dice: 0.6035, decode.d0.loss_cls: 1.7870, decode.d0.loss_mask: 0.4644, decode.d0.loss_dice: 0.7186, decode.d1.loss_cls: 0.2688, decode.d1.loss_mask: 0.4378, decode.d1.loss_dice: 0.6400, decode.d2.loss_cls: 0.1988, decode.d2.loss_mask: 0.4292, decode.d2.loss_dice: 0.6179, decode.d3.loss_cls: 0.1776, decode.d3.loss_mask: 0.4271, decode.d3.loss_dice: 0.6072, decode.d4.loss_cls: 0.1654, decode.d4.loss_mask: 0.4288, decode.d4.loss_dice: 0.6106, decode.d5.loss_cls: 0.1641, decode.d5.loss_mask: 0.4279, decode.d5.loss_dice: 0.6029, decode.d6.loss_cls: 0.1572, decode.d6.loss_mask: 0.4260, decode.d6.loss_dice: 0.6073, decode.d7.loss_cls: 0.1491, decode.d7.loss_mask: 0.4267, decode.d7.loss_dice: 0.6055, decode.d8.loss_cls: 0.1525, decode.d8.loss_mask: 0.4281, decode.d8.loss_dice: 0.6055, loss: 13.9135 +2022-05-06 05:23:50,223 - mmseg - INFO - Iter [20650/40000] lr: 6.946e-07, eta: 4:49:00, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1562, decode.loss_mask: 0.4376, decode.loss_dice: 0.6214, decode.d0.loss_cls: 1.8161, decode.d0.loss_mask: 0.4808, decode.d0.loss_dice: 0.7339, decode.d1.loss_cls: 0.2771, decode.d1.loss_mask: 0.4581, decode.d1.loss_dice: 0.6696, decode.d2.loss_cls: 0.2136, decode.d2.loss_mask: 0.4452, decode.d2.loss_dice: 0.6365, decode.d3.loss_cls: 0.1814, decode.d3.loss_mask: 0.4410, decode.d3.loss_dice: 0.6234, decode.d4.loss_cls: 0.1675, decode.d4.loss_mask: 0.4419, decode.d4.loss_dice: 0.6282, decode.d5.loss_cls: 0.1581, decode.d5.loss_mask: 0.4414, decode.d5.loss_dice: 0.6277, decode.d6.loss_cls: 0.1585, decode.d6.loss_mask: 0.4390, decode.d6.loss_dice: 0.6251, decode.d7.loss_cls: 0.1553, decode.d7.loss_mask: 0.4380, decode.d7.loss_dice: 0.6230, decode.d8.loss_cls: 0.1543, decode.d8.loss_mask: 0.4382, decode.d8.loss_dice: 0.6199, loss: 14.3082 +2022-05-06 05:24:23,766 - mmseg - INFO - Iter [20700/40000] lr: 6.928e-07, eta: 4:48:02, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1531, decode.loss_mask: 0.4344, decode.loss_dice: 0.6110, decode.d0.loss_cls: 1.7547, decode.d0.loss_mask: 0.4748, decode.d0.loss_dice: 0.7120, decode.d1.loss_cls: 0.2711, decode.d1.loss_mask: 0.4494, decode.d1.loss_dice: 0.6459, decode.d2.loss_cls: 0.1952, decode.d2.loss_mask: 0.4393, decode.d2.loss_dice: 0.6254, decode.d3.loss_cls: 0.1672, decode.d3.loss_mask: 0.4381, decode.d3.loss_dice: 0.6148, decode.d4.loss_cls: 0.1639, decode.d4.loss_mask: 0.4350, decode.d4.loss_dice: 0.6162, decode.d5.loss_cls: 0.1555, decode.d5.loss_mask: 0.4329, decode.d5.loss_dice: 0.6128, decode.d6.loss_cls: 0.1577, decode.d6.loss_mask: 0.4311, decode.d6.loss_dice: 0.6073, decode.d7.loss_cls: 0.1575, decode.d7.loss_mask: 0.4322, decode.d7.loss_dice: 0.6077, decode.d8.loss_cls: 0.1497, decode.d8.loss_mask: 0.4354, decode.d8.loss_dice: 0.6091, loss: 13.9904 +2022-05-06 05:24:57,623 - mmseg - INFO - Iter [20750/40000] lr: 6.910e-07, eta: 4:47:04, time: 0.676, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1542, decode.loss_mask: 0.4338, decode.loss_dice: 0.5973, decode.d0.loss_cls: 1.7291, decode.d0.loss_mask: 0.4739, decode.d0.loss_dice: 0.7023, decode.d1.loss_cls: 0.2785, decode.d1.loss_mask: 0.4475, decode.d1.loss_dice: 0.6362, decode.d2.loss_cls: 0.2085, decode.d2.loss_mask: 0.4398, decode.d2.loss_dice: 0.6150, decode.d3.loss_cls: 0.1801, decode.d3.loss_mask: 0.4379, decode.d3.loss_dice: 0.6015, decode.d4.loss_cls: 0.1718, decode.d4.loss_mask: 0.4355, decode.d4.loss_dice: 0.6058, decode.d5.loss_cls: 0.1661, decode.d5.loss_mask: 0.4351, decode.d5.loss_dice: 0.6002, decode.d6.loss_cls: 0.1598, decode.d6.loss_mask: 0.4347, decode.d6.loss_dice: 0.5940, decode.d7.loss_cls: 0.1600, decode.d7.loss_mask: 0.4339, decode.d7.loss_dice: 0.5926, decode.d8.loss_cls: 0.1557, decode.d8.loss_mask: 0.4337, decode.d8.loss_dice: 0.5974, loss: 13.9120 +2022-05-06 05:25:31,330 - mmseg - INFO - Iter [20800/40000] lr: 6.892e-07, eta: 4:46:07, time: 0.676, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1828, decode.loss_mask: 0.4369, decode.loss_dice: 0.6100, decode.d0.loss_cls: 1.8172, decode.d0.loss_mask: 0.4746, decode.d0.loss_dice: 0.7203, decode.d1.loss_cls: 0.3063, decode.d1.loss_mask: 0.4521, decode.d1.loss_dice: 0.6457, decode.d2.loss_cls: 0.2249, decode.d2.loss_mask: 0.4448, decode.d2.loss_dice: 0.6314, decode.d3.loss_cls: 0.1995, decode.d3.loss_mask: 0.4410, decode.d3.loss_dice: 0.6208, decode.d4.loss_cls: 0.1952, decode.d4.loss_mask: 0.4396, decode.d4.loss_dice: 0.6200, decode.d5.loss_cls: 0.1874, decode.d5.loss_mask: 0.4372, decode.d5.loss_dice: 0.6098, decode.d6.loss_cls: 0.1837, decode.d6.loss_mask: 0.4371, decode.d6.loss_dice: 0.6102, decode.d7.loss_cls: 0.1814, decode.d7.loss_mask: 0.4391, decode.d7.loss_dice: 0.6090, decode.d8.loss_cls: 0.1798, decode.d8.loss_mask: 0.4391, decode.d8.loss_dice: 0.6094, loss: 14.3864 +2022-05-06 05:26:07,748 - mmseg - INFO - Iter [20850/40000] lr: 6.874e-07, eta: 4:45:13, time: 0.728, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1597, decode.loss_mask: 0.4535, decode.loss_dice: 0.6270, decode.d0.loss_cls: 1.7708, decode.d0.loss_mask: 0.4960, decode.d0.loss_dice: 0.7351, decode.d1.loss_cls: 0.2783, decode.d1.loss_mask: 0.4733, decode.d1.loss_dice: 0.6627, decode.d2.loss_cls: 0.2108, decode.d2.loss_mask: 0.4626, decode.d2.loss_dice: 0.6419, decode.d3.loss_cls: 0.1825, decode.d3.loss_mask: 0.4585, decode.d3.loss_dice: 0.6286, decode.d4.loss_cls: 0.1689, decode.d4.loss_mask: 0.4558, decode.d4.loss_dice: 0.6324, decode.d5.loss_cls: 0.1595, decode.d5.loss_mask: 0.4560, decode.d5.loss_dice: 0.6274, decode.d6.loss_cls: 0.1620, decode.d6.loss_mask: 0.4520, decode.d6.loss_dice: 0.6232, decode.d7.loss_cls: 0.1572, decode.d7.loss_mask: 0.4530, decode.d7.loss_dice: 0.6246, decode.d8.loss_cls: 0.1598, decode.d8.loss_mask: 0.4533, decode.d8.loss_dice: 0.6251, loss: 14.4515 +2022-05-06 05:26:41,198 - mmseg - INFO - Iter [20900/40000] lr: 6.856e-07, eta: 4:44:16, time: 0.669, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1649, decode.loss_mask: 0.4423, decode.loss_dice: 0.6153, decode.d0.loss_cls: 1.7670, decode.d0.loss_mask: 0.4849, decode.d0.loss_dice: 0.7279, decode.d1.loss_cls: 0.2812, decode.d1.loss_mask: 0.4591, decode.d1.loss_dice: 0.6546, decode.d2.loss_cls: 0.2085, decode.d2.loss_mask: 0.4500, decode.d2.loss_dice: 0.6324, decode.d3.loss_cls: 0.1826, decode.d3.loss_mask: 0.4431, decode.d3.loss_dice: 0.6175, decode.d4.loss_cls: 0.1765, decode.d4.loss_mask: 0.4436, decode.d4.loss_dice: 0.6218, decode.d5.loss_cls: 0.1701, decode.d5.loss_mask: 0.4446, decode.d5.loss_dice: 0.6194, decode.d6.loss_cls: 0.1702, decode.d6.loss_mask: 0.4447, decode.d6.loss_dice: 0.6167, decode.d7.loss_cls: 0.1640, decode.d7.loss_mask: 0.4423, decode.d7.loss_dice: 0.6140, decode.d8.loss_cls: 0.1605, decode.d8.loss_mask: 0.4430, decode.d8.loss_dice: 0.6162, loss: 14.2788 +2022-05-06 05:27:14,704 - mmseg - INFO - Iter [20950/40000] lr: 6.838e-07, eta: 4:43:19, time: 0.670, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1640, decode.loss_mask: 0.4543, decode.loss_dice: 0.6388, decode.d0.loss_cls: 1.7796, decode.d0.loss_mask: 0.4911, decode.d0.loss_dice: 0.7423, decode.d1.loss_cls: 0.2827, decode.d1.loss_mask: 0.4669, decode.d1.loss_dice: 0.6736, decode.d2.loss_cls: 0.2114, decode.d2.loss_mask: 0.4573, decode.d2.loss_dice: 0.6516, decode.d3.loss_cls: 0.1830, decode.d3.loss_mask: 0.4577, decode.d3.loss_dice: 0.6441, decode.d4.loss_cls: 0.1788, decode.d4.loss_mask: 0.4575, decode.d4.loss_dice: 0.6377, decode.d5.loss_cls: 0.1752, decode.d5.loss_mask: 0.4542, decode.d5.loss_dice: 0.6374, decode.d6.loss_cls: 0.1696, decode.d6.loss_mask: 0.4555, decode.d6.loss_dice: 0.6303, decode.d7.loss_cls: 0.1697, decode.d7.loss_mask: 0.4542, decode.d7.loss_dice: 0.6348, decode.d8.loss_cls: 0.1664, decode.d8.loss_mask: 0.4556, decode.d8.loss_dice: 0.6395, loss: 14.6149 +2022-05-06 05:27:48,245 - mmseg - INFO - Saving checkpoint at 21000 iterations +2022-05-06 05:28:13,771 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 05:28:13,777 - mmseg - INFO - Iter [21000/40000] lr: 6.820e-07, eta: 4:42:50, time: 1.179, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1555, decode.loss_mask: 0.4445, decode.loss_dice: 0.5993, decode.d0.loss_cls: 1.6998, decode.d0.loss_mask: 0.4953, decode.d0.loss_dice: 0.7096, decode.d1.loss_cls: 0.2593, decode.d1.loss_mask: 0.4650, decode.d1.loss_dice: 0.6405, decode.d2.loss_cls: 0.1917, decode.d2.loss_mask: 0.4528, decode.d2.loss_dice: 0.6106, decode.d3.loss_cls: 0.1702, decode.d3.loss_mask: 0.4515, decode.d3.loss_dice: 0.6015, decode.d4.loss_cls: 0.1595, decode.d4.loss_mask: 0.4518, decode.d4.loss_dice: 0.6052, decode.d5.loss_cls: 0.1551, decode.d5.loss_mask: 0.4462, decode.d5.loss_dice: 0.5990, decode.d6.loss_cls: 0.1493, decode.d6.loss_mask: 0.4461, decode.d6.loss_dice: 0.6005, decode.d7.loss_cls: 0.1518, decode.d7.loss_mask: 0.4476, decode.d7.loss_dice: 0.5979, decode.d8.loss_cls: 0.1521, decode.d8.loss_mask: 0.4454, decode.d8.loss_dice: 0.5962, loss: 13.9509 +2022-05-06 05:28:47,844 - mmseg - INFO - Iter [21050/40000] lr: 6.802e-07, eta: 4:41:54, time: 0.683, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1589, decode.loss_mask: 0.4510, decode.loss_dice: 0.6144, decode.d0.loss_cls: 1.7317, decode.d0.loss_mask: 0.5008, decode.d0.loss_dice: 0.7275, decode.d1.loss_cls: 0.2747, decode.d1.loss_mask: 0.4658, decode.d1.loss_dice: 0.6620, decode.d2.loss_cls: 0.2094, decode.d2.loss_mask: 0.4571, decode.d2.loss_dice: 0.6409, decode.d3.loss_cls: 0.1835, decode.d3.loss_mask: 0.4548, decode.d3.loss_dice: 0.6228, decode.d4.loss_cls: 0.1714, decode.d4.loss_mask: 0.4528, decode.d4.loss_dice: 0.6250, decode.d5.loss_cls: 0.1602, decode.d5.loss_mask: 0.4502, decode.d5.loss_dice: 0.6239, decode.d6.loss_cls: 0.1566, decode.d6.loss_mask: 0.4478, decode.d6.loss_dice: 0.6169, decode.d7.loss_cls: 0.1583, decode.d7.loss_mask: 0.4494, decode.d7.loss_dice: 0.6180, decode.d8.loss_cls: 0.1574, decode.d8.loss_mask: 0.4498, decode.d8.loss_dice: 0.6193, loss: 14.3121 +2022-05-06 05:29:21,179 - mmseg - INFO - Iter [21100/40000] lr: 6.784e-07, eta: 4:40:57, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1415, decode.loss_mask: 0.4371, decode.loss_dice: 0.6239, decode.d0.loss_cls: 1.7395, decode.d0.loss_mask: 0.4808, decode.d0.loss_dice: 0.7367, decode.d1.loss_cls: 0.2794, decode.d1.loss_mask: 0.4523, decode.d1.loss_dice: 0.6739, decode.d2.loss_cls: 0.1975, decode.d2.loss_mask: 0.4418, decode.d2.loss_dice: 0.6467, decode.d3.loss_cls: 0.1666, decode.d3.loss_mask: 0.4404, decode.d3.loss_dice: 0.6340, decode.d4.loss_cls: 0.1558, decode.d4.loss_mask: 0.4373, decode.d4.loss_dice: 0.6302, decode.d5.loss_cls: 0.1503, decode.d5.loss_mask: 0.4396, decode.d5.loss_dice: 0.6305, decode.d6.loss_cls: 0.1481, decode.d6.loss_mask: 0.4353, decode.d6.loss_dice: 0.6215, decode.d7.loss_cls: 0.1442, decode.d7.loss_mask: 0.4367, decode.d7.loss_dice: 0.6194, decode.d8.loss_cls: 0.1411, decode.d8.loss_mask: 0.4372, decode.d8.loss_dice: 0.6217, loss: 14.1411 +2022-05-06 05:29:55,165 - mmseg - INFO - Iter [21150/40000] lr: 6.767e-07, eta: 4:40:00, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1542, decode.loss_mask: 0.4277, decode.loss_dice: 0.6022, decode.d0.loss_cls: 1.7465, decode.d0.loss_mask: 0.4634, decode.d0.loss_dice: 0.7068, decode.d1.loss_cls: 0.2663, decode.d1.loss_mask: 0.4385, decode.d1.loss_dice: 0.6373, decode.d2.loss_cls: 0.2022, decode.d2.loss_mask: 0.4291, decode.d2.loss_dice: 0.6147, decode.d3.loss_cls: 0.1679, decode.d3.loss_mask: 0.4291, decode.d3.loss_dice: 0.6153, decode.d4.loss_cls: 0.1621, decode.d4.loss_mask: 0.4269, decode.d4.loss_dice: 0.6123, decode.d5.loss_cls: 0.1576, decode.d5.loss_mask: 0.4273, decode.d5.loss_dice: 0.6042, decode.d6.loss_cls: 0.1554, decode.d6.loss_mask: 0.4284, decode.d6.loss_dice: 0.5995, decode.d7.loss_cls: 0.1548, decode.d7.loss_mask: 0.4274, decode.d7.loss_dice: 0.6001, decode.d8.loss_cls: 0.1540, decode.d8.loss_mask: 0.4278, decode.d8.loss_dice: 0.6022, loss: 13.8411 +2022-05-06 05:30:31,507 - mmseg - INFO - Iter [21200/40000] lr: 6.749e-07, eta: 4:39:07, time: 0.727, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1611, decode.loss_mask: 0.4390, decode.loss_dice: 0.6139, decode.d0.loss_cls: 1.7540, decode.d0.loss_mask: 0.4833, decode.d0.loss_dice: 0.7224, decode.d1.loss_cls: 0.2877, decode.d1.loss_mask: 0.4581, decode.d1.loss_dice: 0.6536, decode.d2.loss_cls: 0.2140, decode.d2.loss_mask: 0.4477, decode.d2.loss_dice: 0.6274, decode.d3.loss_cls: 0.1722, decode.d3.loss_mask: 0.4436, decode.d3.loss_dice: 0.6206, decode.d4.loss_cls: 0.1693, decode.d4.loss_mask: 0.4428, decode.d4.loss_dice: 0.6224, decode.d5.loss_cls: 0.1603, decode.d5.loss_mask: 0.4421, decode.d5.loss_dice: 0.6220, decode.d6.loss_cls: 0.1527, decode.d6.loss_mask: 0.4409, decode.d6.loss_dice: 0.6134, decode.d7.loss_cls: 0.1546, decode.d7.loss_mask: 0.4399, decode.d7.loss_dice: 0.6190, decode.d8.loss_cls: 0.1576, decode.d8.loss_mask: 0.4411, decode.d8.loss_dice: 0.6173, loss: 14.1943 +2022-05-06 05:31:05,551 - mmseg - INFO - Iter [21250/40000] lr: 6.731e-07, eta: 4:38:11, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1478, decode.loss_mask: 0.4409, decode.loss_dice: 0.5860, decode.d0.loss_cls: 1.7114, decode.d0.loss_mask: 0.4844, decode.d0.loss_dice: 0.6873, decode.d1.loss_cls: 0.2521, decode.d1.loss_mask: 0.4549, decode.d1.loss_dice: 0.6197, decode.d2.loss_cls: 0.1905, decode.d2.loss_mask: 0.4459, decode.d2.loss_dice: 0.6026, decode.d3.loss_cls: 0.1657, decode.d3.loss_mask: 0.4395, decode.d3.loss_dice: 0.5892, decode.d4.loss_cls: 0.1622, decode.d4.loss_mask: 0.4388, decode.d4.loss_dice: 0.5887, decode.d5.loss_cls: 0.1477, decode.d5.loss_mask: 0.4434, decode.d5.loss_dice: 0.5915, decode.d6.loss_cls: 0.1499, decode.d6.loss_mask: 0.4414, decode.d6.loss_dice: 0.5848, decode.d7.loss_cls: 0.1462, decode.d7.loss_mask: 0.4421, decode.d7.loss_dice: 0.5845, decode.d8.loss_cls: 0.1519, decode.d8.loss_mask: 0.4375, decode.d8.loss_dice: 0.5840, loss: 13.7125 +2022-05-06 05:31:39,569 - mmseg - INFO - Iter [21300/40000] lr: 6.713e-07, eta: 4:37:15, time: 0.680, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1588, decode.loss_mask: 0.4232, decode.loss_dice: 0.6064, decode.d0.loss_cls: 1.7358, decode.d0.loss_mask: 0.4607, decode.d0.loss_dice: 0.7122, decode.d1.loss_cls: 0.2732, decode.d1.loss_mask: 0.4406, decode.d1.loss_dice: 0.6419, decode.d2.loss_cls: 0.1989, decode.d2.loss_mask: 0.4277, decode.d2.loss_dice: 0.6171, decode.d3.loss_cls: 0.1737, decode.d3.loss_mask: 0.4226, decode.d3.loss_dice: 0.6146, decode.d4.loss_cls: 0.1606, decode.d4.loss_mask: 0.4243, decode.d4.loss_dice: 0.6124, decode.d5.loss_cls: 0.1607, decode.d5.loss_mask: 0.4215, decode.d5.loss_dice: 0.6106, decode.d6.loss_cls: 0.1576, decode.d6.loss_mask: 0.4220, decode.d6.loss_dice: 0.6029, decode.d7.loss_cls: 0.1556, decode.d7.loss_mask: 0.4219, decode.d7.loss_dice: 0.6039, decode.d8.loss_cls: 0.1569, decode.d8.loss_mask: 0.4236, decode.d8.loss_dice: 0.6047, loss: 13.8465 +2022-05-06 05:32:13,618 - mmseg - INFO - Iter [21350/40000] lr: 6.695e-07, eta: 4:36:19, time: 0.682, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1583, decode.loss_mask: 0.4287, decode.loss_dice: 0.6150, decode.d0.loss_cls: 1.7880, decode.d0.loss_mask: 0.4667, decode.d0.loss_dice: 0.7251, decode.d1.loss_cls: 0.3020, decode.d1.loss_mask: 0.4433, decode.d1.loss_dice: 0.6594, decode.d2.loss_cls: 0.2071, decode.d2.loss_mask: 0.4355, decode.d2.loss_dice: 0.6378, decode.d3.loss_cls: 0.1856, decode.d3.loss_mask: 0.4290, decode.d3.loss_dice: 0.6194, decode.d4.loss_cls: 0.1651, decode.d4.loss_mask: 0.4296, decode.d4.loss_dice: 0.6194, decode.d5.loss_cls: 0.1681, decode.d5.loss_mask: 0.4301, decode.d5.loss_dice: 0.6191, decode.d6.loss_cls: 0.1550, decode.d6.loss_mask: 0.4287, decode.d6.loss_dice: 0.6177, decode.d7.loss_cls: 0.1498, decode.d7.loss_mask: 0.4295, decode.d7.loss_dice: 0.6190, decode.d8.loss_cls: 0.1573, decode.d8.loss_mask: 0.4304, decode.d8.loss_dice: 0.6164, loss: 14.1361 +2022-05-06 05:32:47,142 - mmseg - INFO - Iter [21400/40000] lr: 6.677e-07, eta: 4:35:23, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1340, decode.loss_mask: 0.4448, decode.loss_dice: 0.5960, decode.d0.loss_cls: 1.7144, decode.d0.loss_mask: 0.4894, decode.d0.loss_dice: 0.6963, decode.d1.loss_cls: 0.2531, decode.d1.loss_mask: 0.4641, decode.d1.loss_dice: 0.6406, decode.d2.loss_cls: 0.1805, decode.d2.loss_mask: 0.4539, decode.d2.loss_dice: 0.6115, decode.d3.loss_cls: 0.1530, decode.d3.loss_mask: 0.4494, decode.d3.loss_dice: 0.5991, decode.d4.loss_cls: 0.1488, decode.d4.loss_mask: 0.4469, decode.d4.loss_dice: 0.6007, decode.d5.loss_cls: 0.1428, decode.d5.loss_mask: 0.4469, decode.d5.loss_dice: 0.5971, decode.d6.loss_cls: 0.1391, decode.d6.loss_mask: 0.4471, decode.d6.loss_dice: 0.5960, decode.d7.loss_cls: 0.1376, decode.d7.loss_mask: 0.4449, decode.d7.loss_dice: 0.6002, decode.d8.loss_cls: 0.1390, decode.d8.loss_mask: 0.4462, decode.d8.loss_dice: 0.5946, loss: 13.8079 +2022-05-06 05:33:21,014 - mmseg - INFO - Iter [21450/40000] lr: 6.659e-07, eta: 4:34:27, time: 0.677, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1465, decode.loss_mask: 0.4419, decode.loss_dice: 0.6342, decode.d0.loss_cls: 1.7604, decode.d0.loss_mask: 0.4856, decode.d0.loss_dice: 0.7434, decode.d1.loss_cls: 0.2863, decode.d1.loss_mask: 0.4527, decode.d1.loss_dice: 0.6705, decode.d2.loss_cls: 0.2038, decode.d2.loss_mask: 0.4484, decode.d2.loss_dice: 0.6460, decode.d3.loss_cls: 0.1766, decode.d3.loss_mask: 0.4445, decode.d3.loss_dice: 0.6376, decode.d4.loss_cls: 0.1670, decode.d4.loss_mask: 0.4439, decode.d4.loss_dice: 0.6348, decode.d5.loss_cls: 0.1599, decode.d5.loss_mask: 0.4432, decode.d5.loss_dice: 0.6348, decode.d6.loss_cls: 0.1530, decode.d6.loss_mask: 0.4401, decode.d6.loss_dice: 0.6312, decode.d7.loss_cls: 0.1522, decode.d7.loss_mask: 0.4424, decode.d7.loss_dice: 0.6343, decode.d8.loss_cls: 0.1496, decode.d8.loss_mask: 0.4411, decode.d8.loss_dice: 0.6300, loss: 14.3356 +2022-05-06 05:33:57,154 - mmseg - INFO - Iter [21500/40000] lr: 6.641e-07, eta: 4:33:34, time: 0.723, data_time: 0.056, memory: 53770, decode.loss_cls: 0.1432, decode.loss_mask: 0.4410, decode.loss_dice: 0.6288, decode.d0.loss_cls: 1.7474, decode.d0.loss_mask: 0.4842, decode.d0.loss_dice: 0.7476, decode.d1.loss_cls: 0.2706, decode.d1.loss_mask: 0.4580, decode.d1.loss_dice: 0.6671, decode.d2.loss_cls: 0.1894, decode.d2.loss_mask: 0.4488, decode.d2.loss_dice: 0.6433, decode.d3.loss_cls: 0.1616, decode.d3.loss_mask: 0.4465, decode.d3.loss_dice: 0.6331, decode.d4.loss_cls: 0.1485, decode.d4.loss_mask: 0.4449, decode.d4.loss_dice: 0.6358, decode.d5.loss_cls: 0.1448, decode.d5.loss_mask: 0.4419, decode.d5.loss_dice: 0.6366, decode.d6.loss_cls: 0.1422, decode.d6.loss_mask: 0.4403, decode.d6.loss_dice: 0.6282, decode.d7.loss_cls: 0.1362, decode.d7.loss_mask: 0.4402, decode.d7.loss_dice: 0.6263, decode.d8.loss_cls: 0.1425, decode.d8.loss_mask: 0.4397, decode.d8.loss_dice: 0.6288, loss: 14.1874 +2022-05-06 05:34:30,448 - mmseg - INFO - Iter [21550/40000] lr: 6.623e-07, eta: 4:32:38, time: 0.666, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1292, decode.loss_mask: 0.4446, decode.loss_dice: 0.6129, decode.d0.loss_cls: 1.7328, decode.d0.loss_mask: 0.4827, decode.d0.loss_dice: 0.7132, decode.d1.loss_cls: 0.2585, decode.d1.loss_mask: 0.4579, decode.d1.loss_dice: 0.6461, decode.d2.loss_cls: 0.1695, decode.d2.loss_mask: 0.4515, decode.d2.loss_dice: 0.6187, decode.d3.loss_cls: 0.1515, decode.d3.loss_mask: 0.4455, decode.d3.loss_dice: 0.6119, decode.d4.loss_cls: 0.1420, decode.d4.loss_mask: 0.4471, decode.d4.loss_dice: 0.6106, decode.d5.loss_cls: 0.1370, decode.d5.loss_mask: 0.4453, decode.d5.loss_dice: 0.6069, decode.d6.loss_cls: 0.1313, decode.d6.loss_mask: 0.4447, decode.d6.loss_dice: 0.6060, decode.d7.loss_cls: 0.1256, decode.d7.loss_mask: 0.4453, decode.d7.loss_dice: 0.6084, decode.d8.loss_cls: 0.1297, decode.d8.loss_mask: 0.4470, decode.d8.loss_dice: 0.6082, loss: 13.8618 +2022-05-06 05:35:03,744 - mmseg - INFO - Iter [21600/40000] lr: 6.605e-07, eta: 4:31:42, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1319, decode.loss_mask: 0.4181, decode.loss_dice: 0.5955, decode.d0.loss_cls: 1.7456, decode.d0.loss_mask: 0.4540, decode.d0.loss_dice: 0.7031, decode.d1.loss_cls: 0.2618, decode.d1.loss_mask: 0.4310, decode.d1.loss_dice: 0.6353, decode.d2.loss_cls: 0.1788, decode.d2.loss_mask: 0.4208, decode.d2.loss_dice: 0.6113, decode.d3.loss_cls: 0.1422, decode.d3.loss_mask: 0.4212, decode.d3.loss_dice: 0.6052, decode.d4.loss_cls: 0.1399, decode.d4.loss_mask: 0.4215, decode.d4.loss_dice: 0.6014, decode.d5.loss_cls: 0.1361, decode.d5.loss_mask: 0.4187, decode.d5.loss_dice: 0.5972, decode.d6.loss_cls: 0.1298, decode.d6.loss_mask: 0.4186, decode.d6.loss_dice: 0.5979, decode.d7.loss_cls: 0.1336, decode.d7.loss_mask: 0.4176, decode.d7.loss_dice: 0.5973, decode.d8.loss_cls: 0.1336, decode.d8.loss_mask: 0.4198, decode.d8.loss_dice: 0.5910, loss: 13.5096 +2022-05-06 05:35:37,490 - mmseg - INFO - Iter [21650/40000] lr: 6.587e-07, eta: 4:30:47, time: 0.676, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1591, decode.loss_mask: 0.4238, decode.loss_dice: 0.6097, decode.d0.loss_cls: 1.7093, decode.d0.loss_mask: 0.4666, decode.d0.loss_dice: 0.7291, decode.d1.loss_cls: 0.2784, decode.d1.loss_mask: 0.4377, decode.d1.loss_dice: 0.6517, decode.d2.loss_cls: 0.2085, decode.d2.loss_mask: 0.4265, decode.d2.loss_dice: 0.6279, decode.d3.loss_cls: 0.1786, decode.d3.loss_mask: 0.4262, decode.d3.loss_dice: 0.6171, decode.d4.loss_cls: 0.1743, decode.d4.loss_mask: 0.4293, decode.d4.loss_dice: 0.6200, decode.d5.loss_cls: 0.1747, decode.d5.loss_mask: 0.4272, decode.d5.loss_dice: 0.6128, decode.d6.loss_cls: 0.1694, decode.d6.loss_mask: 0.4246, decode.d6.loss_dice: 0.6090, decode.d7.loss_cls: 0.1637, decode.d7.loss_mask: 0.4260, decode.d7.loss_dice: 0.6107, decode.d8.loss_cls: 0.1645, decode.d8.loss_mask: 0.4244, decode.d8.loss_dice: 0.6111, loss: 13.9919 +2022-05-06 05:36:11,334 - mmseg - INFO - Iter [21700/40000] lr: 6.569e-07, eta: 4:29:52, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1483, decode.loss_mask: 0.4346, decode.loss_dice: 0.5948, decode.d0.loss_cls: 1.7037, decode.d0.loss_mask: 0.4753, decode.d0.loss_dice: 0.7046, decode.d1.loss_cls: 0.2761, decode.d1.loss_mask: 0.4499, decode.d1.loss_dice: 0.6303, decode.d2.loss_cls: 0.2014, decode.d2.loss_mask: 0.4394, decode.d2.loss_dice: 0.6030, decode.d3.loss_cls: 0.1685, decode.d3.loss_mask: 0.4357, decode.d3.loss_dice: 0.5980, decode.d4.loss_cls: 0.1621, decode.d4.loss_mask: 0.4330, decode.d4.loss_dice: 0.5998, decode.d5.loss_cls: 0.1577, decode.d5.loss_mask: 0.4300, decode.d5.loss_dice: 0.5930, decode.d6.loss_cls: 0.1513, decode.d6.loss_mask: 0.4330, decode.d6.loss_dice: 0.5919, decode.d7.loss_cls: 0.1502, decode.d7.loss_mask: 0.4327, decode.d7.loss_dice: 0.5923, decode.d8.loss_cls: 0.1523, decode.d8.loss_mask: 0.4330, decode.d8.loss_dice: 0.5932, loss: 13.7690 +2022-05-06 05:36:45,104 - mmseg - INFO - Iter [21750/40000] lr: 6.551e-07, eta: 4:28:57, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1514, decode.loss_mask: 0.4472, decode.loss_dice: 0.6076, decode.d0.loss_cls: 1.7049, decode.d0.loss_mask: 0.4918, decode.d0.loss_dice: 0.7025, decode.d1.loss_cls: 0.2719, decode.d1.loss_mask: 0.4648, decode.d1.loss_dice: 0.6427, decode.d2.loss_cls: 0.1974, decode.d2.loss_mask: 0.4544, decode.d2.loss_dice: 0.6259, decode.d3.loss_cls: 0.1775, decode.d3.loss_mask: 0.4478, decode.d3.loss_dice: 0.6142, decode.d4.loss_cls: 0.1610, decode.d4.loss_mask: 0.4498, decode.d4.loss_dice: 0.6147, decode.d5.loss_cls: 0.1584, decode.d5.loss_mask: 0.4479, decode.d5.loss_dice: 0.6073, decode.d6.loss_cls: 0.1553, decode.d6.loss_mask: 0.4473, decode.d6.loss_dice: 0.6027, decode.d7.loss_cls: 0.1515, decode.d7.loss_mask: 0.4481, decode.d7.loss_dice: 0.6086, decode.d8.loss_cls: 0.1512, decode.d8.loss_mask: 0.4452, decode.d8.loss_dice: 0.6089, loss: 14.0603 +2022-05-06 05:37:21,409 - mmseg - INFO - Iter [21800/40000] lr: 6.533e-07, eta: 4:28:05, time: 0.726, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1447, decode.loss_mask: 0.4276, decode.loss_dice: 0.5930, decode.d0.loss_cls: 1.6899, decode.d0.loss_mask: 0.4722, decode.d0.loss_dice: 0.7037, decode.d1.loss_cls: 0.2691, decode.d1.loss_mask: 0.4429, decode.d1.loss_dice: 0.6310, decode.d2.loss_cls: 0.1965, decode.d2.loss_mask: 0.4331, decode.d2.loss_dice: 0.6135, decode.d3.loss_cls: 0.1561, decode.d3.loss_mask: 0.4305, decode.d3.loss_dice: 0.6001, decode.d4.loss_cls: 0.1512, decode.d4.loss_mask: 0.4302, decode.d4.loss_dice: 0.6036, decode.d5.loss_cls: 0.1452, decode.d5.loss_mask: 0.4268, decode.d5.loss_dice: 0.5962, decode.d6.loss_cls: 0.1438, decode.d6.loss_mask: 0.4268, decode.d6.loss_dice: 0.5889, decode.d7.loss_cls: 0.1461, decode.d7.loss_mask: 0.4251, decode.d7.loss_dice: 0.5912, decode.d8.loss_cls: 0.1475, decode.d8.loss_mask: 0.4245, decode.d8.loss_dice: 0.5939, loss: 13.6451 +2022-05-06 05:37:54,787 - mmseg - INFO - Iter [21850/40000] lr: 6.515e-07, eta: 4:27:10, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1203, decode.loss_mask: 0.4141, decode.loss_dice: 0.5786, decode.d0.loss_cls: 1.6960, decode.d0.loss_mask: 0.4541, decode.d0.loss_dice: 0.6825, decode.d1.loss_cls: 0.2381, decode.d1.loss_mask: 0.4283, decode.d1.loss_dice: 0.6125, decode.d2.loss_cls: 0.1702, decode.d2.loss_mask: 0.4190, decode.d2.loss_dice: 0.5915, decode.d3.loss_cls: 0.1362, decode.d3.loss_mask: 0.4185, decode.d3.loss_dice: 0.5868, decode.d4.loss_cls: 0.1343, decode.d4.loss_mask: 0.4173, decode.d4.loss_dice: 0.5847, decode.d5.loss_cls: 0.1309, decode.d5.loss_mask: 0.4171, decode.d5.loss_dice: 0.5792, decode.d6.loss_cls: 0.1261, decode.d6.loss_mask: 0.4142, decode.d6.loss_dice: 0.5773, decode.d7.loss_cls: 0.1255, decode.d7.loss_mask: 0.4128, decode.d7.loss_dice: 0.5752, decode.d8.loss_cls: 0.1228, decode.d8.loss_mask: 0.4132, decode.d8.loss_dice: 0.5737, loss: 13.1509 +2022-05-06 05:38:28,828 - mmseg - INFO - Iter [21900/40000] lr: 6.497e-07, eta: 4:26:15, time: 0.681, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1507, decode.loss_mask: 0.4259, decode.loss_dice: 0.5823, decode.d0.loss_cls: 1.6804, decode.d0.loss_mask: 0.4684, decode.d0.loss_dice: 0.6890, decode.d1.loss_cls: 0.2689, decode.d1.loss_mask: 0.4389, decode.d1.loss_dice: 0.6198, decode.d2.loss_cls: 0.1965, decode.d2.loss_mask: 0.4296, decode.d2.loss_dice: 0.5978, decode.d3.loss_cls: 0.1675, decode.d3.loss_mask: 0.4281, decode.d3.loss_dice: 0.5874, decode.d4.loss_cls: 0.1547, decode.d4.loss_mask: 0.4291, decode.d4.loss_dice: 0.5881, decode.d5.loss_cls: 0.1562, decode.d5.loss_mask: 0.4286, decode.d5.loss_dice: 0.5830, decode.d6.loss_cls: 0.1483, decode.d6.loss_mask: 0.4267, decode.d6.loss_dice: 0.5798, decode.d7.loss_cls: 0.1498, decode.d7.loss_mask: 0.4264, decode.d7.loss_dice: 0.5835, decode.d8.loss_cls: 0.1516, decode.d8.loss_mask: 0.4250, decode.d8.loss_dice: 0.5800, loss: 13.5424 +2022-05-06 05:39:02,520 - mmseg - INFO - Iter [21950/40000] lr: 6.479e-07, eta: 4:25:21, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1455, decode.loss_mask: 0.4194, decode.loss_dice: 0.5931, decode.d0.loss_cls: 1.7584, decode.d0.loss_mask: 0.4609, decode.d0.loss_dice: 0.6962, decode.d1.loss_cls: 0.2699, decode.d1.loss_mask: 0.4343, decode.d1.loss_dice: 0.6361, decode.d2.loss_cls: 0.1848, decode.d2.loss_mask: 0.4234, decode.d2.loss_dice: 0.6109, decode.d3.loss_cls: 0.1625, decode.d3.loss_mask: 0.4206, decode.d3.loss_dice: 0.6015, decode.d4.loss_cls: 0.1543, decode.d4.loss_mask: 0.4201, decode.d4.loss_dice: 0.6022, decode.d5.loss_cls: 0.1487, decode.d5.loss_mask: 0.4183, decode.d5.loss_dice: 0.6024, decode.d6.loss_cls: 0.1461, decode.d6.loss_mask: 0.4199, decode.d6.loss_dice: 0.5974, decode.d7.loss_cls: 0.1436, decode.d7.loss_mask: 0.4164, decode.d7.loss_dice: 0.5941, decode.d8.loss_cls: 0.1440, decode.d8.loss_mask: 0.4175, decode.d8.loss_dice: 0.5922, loss: 13.6349 +2022-05-06 05:39:36,598 - mmseg - INFO - Saving checkpoint at 22000 iterations +2022-05-06 05:40:01,453 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 05:40:01,456 - mmseg - INFO - Iter [22000/40000] lr: 6.461e-07, eta: 4:24:51, time: 1.178, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1416, decode.loss_mask: 0.4304, decode.loss_dice: 0.5980, decode.d0.loss_cls: 1.7162, decode.d0.loss_mask: 0.4721, decode.d0.loss_dice: 0.7085, decode.d1.loss_cls: 0.2683, decode.d1.loss_mask: 0.4437, decode.d1.loss_dice: 0.6371, decode.d2.loss_cls: 0.1961, decode.d2.loss_mask: 0.4384, decode.d2.loss_dice: 0.6195, decode.d3.loss_cls: 0.1622, decode.d3.loss_mask: 0.4321, decode.d3.loss_dice: 0.6083, decode.d4.loss_cls: 0.1569, decode.d4.loss_mask: 0.4322, decode.d4.loss_dice: 0.6094, decode.d5.loss_cls: 0.1489, decode.d5.loss_mask: 0.4306, decode.d5.loss_dice: 0.6073, decode.d6.loss_cls: 0.1426, decode.d6.loss_mask: 0.4299, decode.d6.loss_dice: 0.6015, decode.d7.loss_cls: 0.1437, decode.d7.loss_mask: 0.4299, decode.d7.loss_dice: 0.6059, decode.d8.loss_cls: 0.1433, decode.d8.loss_mask: 0.4290, decode.d8.loss_dice: 0.6028, loss: 13.7866 +2022-05-06 05:40:35,502 - mmseg - INFO - Iter [22050/40000] lr: 6.443e-07, eta: 4:23:57, time: 0.683, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1623, decode.loss_mask: 0.4426, decode.loss_dice: 0.6019, decode.d0.loss_cls: 1.7282, decode.d0.loss_mask: 0.4890, decode.d0.loss_dice: 0.7066, decode.d1.loss_cls: 0.2772, decode.d1.loss_mask: 0.4634, decode.d1.loss_dice: 0.6470, decode.d2.loss_cls: 0.2034, decode.d2.loss_mask: 0.4501, decode.d2.loss_dice: 0.6154, decode.d3.loss_cls: 0.1770, decode.d3.loss_mask: 0.4453, decode.d3.loss_dice: 0.6100, decode.d4.loss_cls: 0.1791, decode.d4.loss_mask: 0.4433, decode.d4.loss_dice: 0.6088, decode.d5.loss_cls: 0.1734, decode.d5.loss_mask: 0.4438, decode.d5.loss_dice: 0.6086, decode.d6.loss_cls: 0.1701, decode.d6.loss_mask: 0.4433, decode.d6.loss_dice: 0.6023, decode.d7.loss_cls: 0.1659, decode.d7.loss_mask: 0.4436, decode.d7.loss_dice: 0.6053, decode.d8.loss_cls: 0.1676, decode.d8.loss_mask: 0.4423, decode.d8.loss_dice: 0.6032, loss: 14.1199 +2022-05-06 05:41:11,517 - mmseg - INFO - Iter [22100/40000] lr: 6.426e-07, eta: 4:23:05, time: 0.720, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1701, decode.loss_mask: 0.4253, decode.loss_dice: 0.6224, decode.d0.loss_cls: 1.7544, decode.d0.loss_mask: 0.4649, decode.d0.loss_dice: 0.7380, decode.d1.loss_cls: 0.3082, decode.d1.loss_mask: 0.4382, decode.d1.loss_dice: 0.6588, decode.d2.loss_cls: 0.2199, decode.d2.loss_mask: 0.4298, decode.d2.loss_dice: 0.6420, decode.d3.loss_cls: 0.1870, decode.d3.loss_mask: 0.4285, decode.d3.loss_dice: 0.6317, decode.d4.loss_cls: 0.1775, decode.d4.loss_mask: 0.4268, decode.d4.loss_dice: 0.6303, decode.d5.loss_cls: 0.1734, decode.d5.loss_mask: 0.4278, decode.d5.loss_dice: 0.6282, decode.d6.loss_cls: 0.1741, decode.d6.loss_mask: 0.4259, decode.d6.loss_dice: 0.6223, decode.d7.loss_cls: 0.1724, decode.d7.loss_mask: 0.4233, decode.d7.loss_dice: 0.6220, decode.d8.loss_cls: 0.1760, decode.d8.loss_mask: 0.4240, decode.d8.loss_dice: 0.6231, loss: 14.2463 +2022-05-06 05:41:45,135 - mmseg - INFO - Iter [22150/40000] lr: 6.408e-07, eta: 4:22:11, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1425, decode.loss_mask: 0.4302, decode.loss_dice: 0.6225, decode.d0.loss_cls: 1.7359, decode.d0.loss_mask: 0.4665, decode.d0.loss_dice: 0.7318, decode.d1.loss_cls: 0.2665, decode.d1.loss_mask: 0.4419, decode.d1.loss_dice: 0.6567, decode.d2.loss_cls: 0.1825, decode.d2.loss_mask: 0.4356, decode.d2.loss_dice: 0.6371, decode.d3.loss_cls: 0.1609, decode.d3.loss_mask: 0.4312, decode.d3.loss_dice: 0.6273, decode.d4.loss_cls: 0.1478, decode.d4.loss_mask: 0.4320, decode.d4.loss_dice: 0.6254, decode.d5.loss_cls: 0.1436, decode.d5.loss_mask: 0.4299, decode.d5.loss_dice: 0.6242, decode.d6.loss_cls: 0.1484, decode.d6.loss_mask: 0.4294, decode.d6.loss_dice: 0.6200, decode.d7.loss_cls: 0.1384, decode.d7.loss_mask: 0.4310, decode.d7.loss_dice: 0.6197, decode.d8.loss_cls: 0.1338, decode.d8.loss_mask: 0.4305, decode.d8.loss_dice: 0.6247, loss: 13.9477 +2022-05-06 05:42:18,555 - mmseg - INFO - Iter [22200/40000] lr: 6.390e-07, eta: 4:21:16, time: 0.669, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1369, decode.loss_mask: 0.4231, decode.loss_dice: 0.5778, decode.d0.loss_cls: 1.6892, decode.d0.loss_mask: 0.4654, decode.d0.loss_dice: 0.6751, decode.d1.loss_cls: 0.2621, decode.d1.loss_mask: 0.4359, decode.d1.loss_dice: 0.6160, decode.d2.loss_cls: 0.1902, decode.d2.loss_mask: 0.4300, decode.d2.loss_dice: 0.5936, decode.d3.loss_cls: 0.1588, decode.d3.loss_mask: 0.4255, decode.d3.loss_dice: 0.5833, decode.d4.loss_cls: 0.1541, decode.d4.loss_mask: 0.4236, decode.d4.loss_dice: 0.5826, decode.d5.loss_cls: 0.1418, decode.d5.loss_mask: 0.4244, decode.d5.loss_dice: 0.5796, decode.d6.loss_cls: 0.1334, decode.d6.loss_mask: 0.4244, decode.d6.loss_dice: 0.5806, decode.d7.loss_cls: 0.1354, decode.d7.loss_mask: 0.4248, decode.d7.loss_dice: 0.5800, decode.d8.loss_cls: 0.1368, decode.d8.loss_mask: 0.4233, decode.d8.loss_dice: 0.5758, loss: 13.3833 +2022-05-06 05:42:52,622 - mmseg - INFO - Iter [22250/40000] lr: 6.372e-07, eta: 4:20:22, time: 0.681, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1420, decode.loss_mask: 0.4142, decode.loss_dice: 0.6044, decode.d0.loss_cls: 1.7009, decode.d0.loss_mask: 0.4592, decode.d0.loss_dice: 0.7116, decode.d1.loss_cls: 0.2633, decode.d1.loss_mask: 0.4294, decode.d1.loss_dice: 0.6410, decode.d2.loss_cls: 0.1758, decode.d2.loss_mask: 0.4206, decode.d2.loss_dice: 0.6237, decode.d3.loss_cls: 0.1555, decode.d3.loss_mask: 0.4169, decode.d3.loss_dice: 0.6132, decode.d4.loss_cls: 0.1508, decode.d4.loss_mask: 0.4158, decode.d4.loss_dice: 0.6101, decode.d5.loss_cls: 0.1454, decode.d5.loss_mask: 0.4155, decode.d5.loss_dice: 0.6095, decode.d6.loss_cls: 0.1403, decode.d6.loss_mask: 0.4165, decode.d6.loss_dice: 0.6061, decode.d7.loss_cls: 0.1405, decode.d7.loss_mask: 0.4167, decode.d7.loss_dice: 0.6024, decode.d8.loss_cls: 0.1408, decode.d8.loss_mask: 0.4145, decode.d8.loss_dice: 0.6050, loss: 13.6015 +2022-05-06 05:43:25,831 - mmseg - INFO - Iter [22300/40000] lr: 6.354e-07, eta: 4:19:28, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1261, decode.loss_mask: 0.4308, decode.loss_dice: 0.5892, decode.d0.loss_cls: 1.6669, decode.d0.loss_mask: 0.4737, decode.d0.loss_dice: 0.6961, decode.d1.loss_cls: 0.2382, decode.d1.loss_mask: 0.4446, decode.d1.loss_dice: 0.6290, decode.d2.loss_cls: 0.1667, decode.d2.loss_mask: 0.4370, decode.d2.loss_dice: 0.6066, decode.d3.loss_cls: 0.1470, decode.d3.loss_mask: 0.4322, decode.d3.loss_dice: 0.5941, decode.d4.loss_cls: 0.1359, decode.d4.loss_mask: 0.4309, decode.d4.loss_dice: 0.5957, decode.d5.loss_cls: 0.1251, decode.d5.loss_mask: 0.4310, decode.d5.loss_dice: 0.5949, decode.d6.loss_cls: 0.1289, decode.d6.loss_mask: 0.4295, decode.d6.loss_dice: 0.5933, decode.d7.loss_cls: 0.1244, decode.d7.loss_mask: 0.4306, decode.d7.loss_dice: 0.5891, decode.d8.loss_cls: 0.1245, decode.d8.loss_mask: 0.4319, decode.d8.loss_dice: 0.5960, loss: 13.4400 +2022-05-06 05:43:59,559 - mmseg - INFO - Iter [22350/40000] lr: 6.336e-07, eta: 4:18:34, time: 0.675, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1479, decode.loss_mask: 0.4291, decode.loss_dice: 0.5826, decode.d0.loss_cls: 1.6893, decode.d0.loss_mask: 0.4730, decode.d0.loss_dice: 0.6919, decode.d1.loss_cls: 0.2532, decode.d1.loss_mask: 0.4451, decode.d1.loss_dice: 0.6251, decode.d2.loss_cls: 0.1843, decode.d2.loss_mask: 0.4341, decode.d2.loss_dice: 0.6028, decode.d3.loss_cls: 0.1651, decode.d3.loss_mask: 0.4313, decode.d3.loss_dice: 0.5885, decode.d4.loss_cls: 0.1582, decode.d4.loss_mask: 0.4326, decode.d4.loss_dice: 0.5883, decode.d5.loss_cls: 0.1533, decode.d5.loss_mask: 0.4294, decode.d5.loss_dice: 0.5849, decode.d6.loss_cls: 0.1509, decode.d6.loss_mask: 0.4294, decode.d6.loss_dice: 0.5810, decode.d7.loss_cls: 0.1464, decode.d7.loss_mask: 0.4313, decode.d7.loss_dice: 0.5842, decode.d8.loss_cls: 0.1484, decode.d8.loss_mask: 0.4274, decode.d8.loss_dice: 0.5835, loss: 13.5727 +2022-05-06 05:44:33,058 - mmseg - INFO - Iter [22400/40000] lr: 6.318e-07, eta: 4:17:40, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1634, decode.loss_mask: 0.4273, decode.loss_dice: 0.5979, decode.d0.loss_cls: 1.6974, decode.d0.loss_mask: 0.4732, decode.d0.loss_dice: 0.7140, decode.d1.loss_cls: 0.2759, decode.d1.loss_mask: 0.4396, decode.d1.loss_dice: 0.6415, decode.d2.loss_cls: 0.2070, decode.d2.loss_mask: 0.4302, decode.d2.loss_dice: 0.6161, decode.d3.loss_cls: 0.1785, decode.d3.loss_mask: 0.4288, decode.d3.loss_dice: 0.6052, decode.d4.loss_cls: 0.1703, decode.d4.loss_mask: 0.4288, decode.d4.loss_dice: 0.6011, decode.d5.loss_cls: 0.1627, decode.d5.loss_mask: 0.4280, decode.d5.loss_dice: 0.6063, decode.d6.loss_cls: 0.1553, decode.d6.loss_mask: 0.4278, decode.d6.loss_dice: 0.6014, decode.d7.loss_cls: 0.1571, decode.d7.loss_mask: 0.4279, decode.d7.loss_dice: 0.6020, decode.d8.loss_cls: 0.1593, decode.d8.loss_mask: 0.4279, decode.d8.loss_dice: 0.5981, loss: 13.8502 +2022-05-06 05:45:09,412 - mmseg - INFO - Iter [22450/40000] lr: 6.300e-07, eta: 4:16:49, time: 0.727, data_time: 0.055, memory: 53770, decode.loss_cls: 0.1434, decode.loss_mask: 0.4233, decode.loss_dice: 0.5726, decode.d0.loss_cls: 1.6603, decode.d0.loss_mask: 0.4643, decode.d0.loss_dice: 0.6758, decode.d1.loss_cls: 0.2533, decode.d1.loss_mask: 0.4370, decode.d1.loss_dice: 0.6098, decode.d2.loss_cls: 0.1806, decode.d2.loss_mask: 0.4282, decode.d2.loss_dice: 0.5838, decode.d3.loss_cls: 0.1557, decode.d3.loss_mask: 0.4266, decode.d3.loss_dice: 0.5778, decode.d4.loss_cls: 0.1518, decode.d4.loss_mask: 0.4247, decode.d4.loss_dice: 0.5777, decode.d5.loss_cls: 0.1464, decode.d5.loss_mask: 0.4234, decode.d5.loss_dice: 0.5734, decode.d6.loss_cls: 0.1357, decode.d6.loss_mask: 0.4224, decode.d6.loss_dice: 0.5772, decode.d7.loss_cls: 0.1376, decode.d7.loss_mask: 0.4224, decode.d7.loss_dice: 0.5755, decode.d8.loss_cls: 0.1450, decode.d8.loss_mask: 0.4223, decode.d8.loss_dice: 0.5743, loss: 13.3023 +2022-05-06 05:45:42,733 - mmseg - INFO - Iter [22500/40000] lr: 6.282e-07, eta: 4:15:55, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1367, decode.loss_mask: 0.4298, decode.loss_dice: 0.5766, decode.d0.loss_cls: 1.7010, decode.d0.loss_mask: 0.4737, decode.d0.loss_dice: 0.6862, decode.d1.loss_cls: 0.2639, decode.d1.loss_mask: 0.4431, decode.d1.loss_dice: 0.6198, decode.d2.loss_cls: 0.1844, decode.d2.loss_mask: 0.4348, decode.d2.loss_dice: 0.5945, decode.d3.loss_cls: 0.1539, decode.d3.loss_mask: 0.4311, decode.d3.loss_dice: 0.5801, decode.d4.loss_cls: 0.1450, decode.d4.loss_mask: 0.4302, decode.d4.loss_dice: 0.5826, decode.d5.loss_cls: 0.1377, decode.d5.loss_mask: 0.4288, decode.d5.loss_dice: 0.5791, decode.d6.loss_cls: 0.1361, decode.d6.loss_mask: 0.4287, decode.d6.loss_dice: 0.5791, decode.d7.loss_cls: 0.1357, decode.d7.loss_mask: 0.4291, decode.d7.loss_dice: 0.5815, decode.d8.loss_cls: 0.1289, decode.d8.loss_mask: 0.4305, decode.d8.loss_dice: 0.5839, loss: 13.4469 +2022-05-06 05:46:16,306 - mmseg - INFO - Iter [22550/40000] lr: 6.264e-07, eta: 4:15:02, time: 0.672, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1585, decode.loss_mask: 0.4164, decode.loss_dice: 0.6141, decode.d0.loss_cls: 1.7048, decode.d0.loss_mask: 0.4621, decode.d0.loss_dice: 0.7245, decode.d1.loss_cls: 0.2823, decode.d1.loss_mask: 0.4346, decode.d1.loss_dice: 0.6544, decode.d2.loss_cls: 0.2054, decode.d2.loss_mask: 0.4259, decode.d2.loss_dice: 0.6274, decode.d3.loss_cls: 0.1806, decode.d3.loss_mask: 0.4210, decode.d3.loss_dice: 0.6131, decode.d4.loss_cls: 0.1736, decode.d4.loss_mask: 0.4189, decode.d4.loss_dice: 0.6141, decode.d5.loss_cls: 0.1681, decode.d5.loss_mask: 0.4173, decode.d5.loss_dice: 0.6094, decode.d6.loss_cls: 0.1603, decode.d6.loss_mask: 0.4162, decode.d6.loss_dice: 0.6067, decode.d7.loss_cls: 0.1602, decode.d7.loss_mask: 0.4180, decode.d7.loss_dice: 0.6128, decode.d8.loss_cls: 0.1569, decode.d8.loss_mask: 0.4165, decode.d8.loss_dice: 0.6131, loss: 13.8871 +2022-05-06 05:46:49,860 - mmseg - INFO - Iter [22600/40000] lr: 6.246e-07, eta: 4:14:08, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1397, decode.loss_mask: 0.4418, decode.loss_dice: 0.5963, decode.d0.loss_cls: 1.6647, decode.d0.loss_mask: 0.4799, decode.d0.loss_dice: 0.6831, decode.d1.loss_cls: 0.2519, decode.d1.loss_mask: 0.4558, decode.d1.loss_dice: 0.6349, decode.d2.loss_cls: 0.1925, decode.d2.loss_mask: 0.4482, decode.d2.loss_dice: 0.6075, decode.d3.loss_cls: 0.1648, decode.d3.loss_mask: 0.4453, decode.d3.loss_dice: 0.5993, decode.d4.loss_cls: 0.1529, decode.d4.loss_mask: 0.4424, decode.d4.loss_dice: 0.5971, decode.d5.loss_cls: 0.1486, decode.d5.loss_mask: 0.4414, decode.d5.loss_dice: 0.5985, decode.d6.loss_cls: 0.1413, decode.d6.loss_mask: 0.4414, decode.d6.loss_dice: 0.5922, decode.d7.loss_cls: 0.1401, decode.d7.loss_mask: 0.4425, decode.d7.loss_dice: 0.5967, decode.d8.loss_cls: 0.1422, decode.d8.loss_mask: 0.4429, decode.d8.loss_dice: 0.5952, loss: 13.7210 +2022-05-06 05:47:23,608 - mmseg - INFO - Iter [22650/40000] lr: 6.228e-07, eta: 4:13:15, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1243, decode.loss_mask: 0.4089, decode.loss_dice: 0.5851, decode.d0.loss_cls: 1.7450, decode.d0.loss_mask: 0.4464, decode.d0.loss_dice: 0.6869, decode.d1.loss_cls: 0.2508, decode.d1.loss_mask: 0.4200, decode.d1.loss_dice: 0.6211, decode.d2.loss_cls: 0.1754, decode.d2.loss_mask: 0.4146, decode.d2.loss_dice: 0.5979, decode.d3.loss_cls: 0.1492, decode.d3.loss_mask: 0.4090, decode.d3.loss_dice: 0.5879, decode.d4.loss_cls: 0.1367, decode.d4.loss_mask: 0.4090, decode.d4.loss_dice: 0.5876, decode.d5.loss_cls: 0.1307, decode.d5.loss_mask: 0.4079, decode.d5.loss_dice: 0.5863, decode.d6.loss_cls: 0.1259, decode.d6.loss_mask: 0.4071, decode.d6.loss_dice: 0.5811, decode.d7.loss_cls: 0.1214, decode.d7.loss_mask: 0.4081, decode.d7.loss_dice: 0.5858, decode.d8.loss_cls: 0.1286, decode.d8.loss_mask: 0.4067, decode.d8.loss_dice: 0.5802, loss: 13.2255 +2022-05-06 05:47:57,193 - mmseg - INFO - Iter [22700/40000] lr: 6.210e-07, eta: 4:12:22, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1319, decode.loss_mask: 0.4268, decode.loss_dice: 0.5824, decode.d0.loss_cls: 1.6722, decode.d0.loss_mask: 0.4718, decode.d0.loss_dice: 0.6957, decode.d1.loss_cls: 0.2597, decode.d1.loss_mask: 0.4462, decode.d1.loss_dice: 0.6251, decode.d2.loss_cls: 0.1802, decode.d2.loss_mask: 0.4371, decode.d2.loss_dice: 0.5996, decode.d3.loss_cls: 0.1562, decode.d3.loss_mask: 0.4319, decode.d3.loss_dice: 0.5860, decode.d4.loss_cls: 0.1490, decode.d4.loss_mask: 0.4325, decode.d4.loss_dice: 0.5887, decode.d5.loss_cls: 0.1409, decode.d5.loss_mask: 0.4294, decode.d5.loss_dice: 0.5884, decode.d6.loss_cls: 0.1329, decode.d6.loss_mask: 0.4284, decode.d6.loss_dice: 0.5870, decode.d7.loss_cls: 0.1352, decode.d7.loss_mask: 0.4264, decode.d7.loss_dice: 0.5827, decode.d8.loss_cls: 0.1303, decode.d8.loss_mask: 0.4267, decode.d8.loss_dice: 0.5819, loss: 13.4631 +2022-05-06 05:48:32,970 - mmseg - INFO - Iter [22750/40000] lr: 6.192e-07, eta: 4:11:31, time: 0.716, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1311, decode.loss_mask: 0.4268, decode.loss_dice: 0.5674, decode.d0.loss_cls: 1.7000, decode.d0.loss_mask: 0.4646, decode.d0.loss_dice: 0.6662, decode.d1.loss_cls: 0.2432, decode.d1.loss_mask: 0.4375, decode.d1.loss_dice: 0.6050, decode.d2.loss_cls: 0.1775, decode.d2.loss_mask: 0.4291, decode.d2.loss_dice: 0.5812, decode.d3.loss_cls: 0.1539, decode.d3.loss_mask: 0.4277, decode.d3.loss_dice: 0.5796, decode.d4.loss_cls: 0.1441, decode.d4.loss_mask: 0.4282, decode.d4.loss_dice: 0.5778, decode.d5.loss_cls: 0.1373, decode.d5.loss_mask: 0.4289, decode.d5.loss_dice: 0.5750, decode.d6.loss_cls: 0.1343, decode.d6.loss_mask: 0.4266, decode.d6.loss_dice: 0.5708, decode.d7.loss_cls: 0.1324, decode.d7.loss_mask: 0.4264, decode.d7.loss_dice: 0.5710, decode.d8.loss_cls: 0.1344, decode.d8.loss_mask: 0.4261, decode.d8.loss_dice: 0.5705, loss: 13.2744 +2022-05-06 05:49:06,586 - mmseg - INFO - Iter [22800/40000] lr: 6.174e-07, eta: 4:10:38, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1230, decode.loss_mask: 0.4326, decode.loss_dice: 0.5946, decode.d0.loss_cls: 1.7079, decode.d0.loss_mask: 0.4831, decode.d0.loss_dice: 0.7052, decode.d1.loss_cls: 0.2305, decode.d1.loss_mask: 0.4517, decode.d1.loss_dice: 0.6403, decode.d2.loss_cls: 0.1578, decode.d2.loss_mask: 0.4408, decode.d2.loss_dice: 0.6192, decode.d3.loss_cls: 0.1389, decode.d3.loss_mask: 0.4353, decode.d3.loss_dice: 0.6034, decode.d4.loss_cls: 0.1336, decode.d4.loss_mask: 0.4328, decode.d4.loss_dice: 0.5984, decode.d5.loss_cls: 0.1284, decode.d5.loss_mask: 0.4324, decode.d5.loss_dice: 0.6013, decode.d6.loss_cls: 0.1234, decode.d6.loss_mask: 0.4327, decode.d6.loss_dice: 0.6003, decode.d7.loss_cls: 0.1180, decode.d7.loss_mask: 0.4316, decode.d7.loss_dice: 0.6016, decode.d8.loss_cls: 0.1221, decode.d8.loss_mask: 0.4335, decode.d8.loss_dice: 0.6020, loss: 13.5561 +2022-05-06 05:49:40,268 - mmseg - INFO - Iter [22850/40000] lr: 6.156e-07, eta: 4:09:45, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1439, decode.loss_mask: 0.4334, decode.loss_dice: 0.5985, decode.d0.loss_cls: 1.6612, decode.d0.loss_mask: 0.4745, decode.d0.loss_dice: 0.7123, decode.d1.loss_cls: 0.2528, decode.d1.loss_mask: 0.4443, decode.d1.loss_dice: 0.6418, decode.d2.loss_cls: 0.1855, decode.d2.loss_mask: 0.4360, decode.d2.loss_dice: 0.6143, decode.d3.loss_cls: 0.1612, decode.d3.loss_mask: 0.4350, decode.d3.loss_dice: 0.6076, decode.d4.loss_cls: 0.1583, decode.d4.loss_mask: 0.4353, decode.d4.loss_dice: 0.6051, decode.d5.loss_cls: 0.1519, decode.d5.loss_mask: 0.4337, decode.d5.loss_dice: 0.6028, decode.d6.loss_cls: 0.1419, decode.d6.loss_mask: 0.4333, decode.d6.loss_dice: 0.6017, decode.d7.loss_cls: 0.1401, decode.d7.loss_mask: 0.4357, decode.d7.loss_dice: 0.6023, decode.d8.loss_cls: 0.1385, decode.d8.loss_mask: 0.4358, decode.d8.loss_dice: 0.6022, loss: 13.7210 +2022-05-06 05:50:14,270 - mmseg - INFO - Iter [22900/40000] lr: 6.138e-07, eta: 4:08:52, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1365, decode.loss_mask: 0.4256, decode.loss_dice: 0.5707, decode.d0.loss_cls: 1.6633, decode.d0.loss_mask: 0.4666, decode.d0.loss_dice: 0.6754, decode.d1.loss_cls: 0.2457, decode.d1.loss_mask: 0.4403, decode.d1.loss_dice: 0.6085, decode.d2.loss_cls: 0.1825, decode.d2.loss_mask: 0.4334, decode.d2.loss_dice: 0.5870, decode.d3.loss_cls: 0.1520, decode.d3.loss_mask: 0.4290, decode.d3.loss_dice: 0.5771, decode.d4.loss_cls: 0.1388, decode.d4.loss_mask: 0.4253, decode.d4.loss_dice: 0.5762, decode.d5.loss_cls: 0.1398, decode.d5.loss_mask: 0.4269, decode.d5.loss_dice: 0.5754, decode.d6.loss_cls: 0.1370, decode.d6.loss_mask: 0.4261, decode.d6.loss_dice: 0.5739, decode.d7.loss_cls: 0.1369, decode.d7.loss_mask: 0.4252, decode.d7.loss_dice: 0.5735, decode.d8.loss_cls: 0.1350, decode.d8.loss_mask: 0.4250, decode.d8.loss_dice: 0.5757, loss: 13.2843 +2022-05-06 05:50:48,241 - mmseg - INFO - Iter [22950/40000] lr: 6.120e-07, eta: 4:08:00, time: 0.679, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1366, decode.loss_mask: 0.4131, decode.loss_dice: 0.5782, decode.d0.loss_cls: 1.6297, decode.d0.loss_mask: 0.4545, decode.d0.loss_dice: 0.6876, decode.d1.loss_cls: 0.2414, decode.d1.loss_mask: 0.4282, decode.d1.loss_dice: 0.6159, decode.d2.loss_cls: 0.1823, decode.d2.loss_mask: 0.4179, decode.d2.loss_dice: 0.5930, decode.d3.loss_cls: 0.1563, decode.d3.loss_mask: 0.4172, decode.d3.loss_dice: 0.5827, decode.d4.loss_cls: 0.1446, decode.d4.loss_mask: 0.4152, decode.d4.loss_dice: 0.5885, decode.d5.loss_cls: 0.1430, decode.d5.loss_mask: 0.4133, decode.d5.loss_dice: 0.5788, decode.d6.loss_cls: 0.1356, decode.d6.loss_mask: 0.4145, decode.d6.loss_dice: 0.5780, decode.d7.loss_cls: 0.1359, decode.d7.loss_mask: 0.4139, decode.d7.loss_dice: 0.5795, decode.d8.loss_cls: 0.1369, decode.d8.loss_mask: 0.4145, decode.d8.loss_dice: 0.5745, loss: 13.2013 +2022-05-06 05:51:21,816 - mmseg - INFO - Saving checkpoint at 23000 iterations +2022-05-06 05:51:48,586 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 05:51:48,594 - mmseg - INFO - Iter [23000/40000] lr: 6.102e-07, eta: 4:07:31, time: 1.205, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1394, decode.loss_mask: 0.4174, decode.loss_dice: 0.5783, decode.d0.loss_cls: 1.6482, decode.d0.loss_mask: 0.4580, decode.d0.loss_dice: 0.6928, decode.d1.loss_cls: 0.2654, decode.d1.loss_mask: 0.4330, decode.d1.loss_dice: 0.6161, decode.d2.loss_cls: 0.1848, decode.d2.loss_mask: 0.4241, decode.d2.loss_dice: 0.5930, decode.d3.loss_cls: 0.1573, decode.d3.loss_mask: 0.4208, decode.d3.loss_dice: 0.5799, decode.d4.loss_cls: 0.1521, decode.d4.loss_mask: 0.4221, decode.d4.loss_dice: 0.5819, decode.d5.loss_cls: 0.1431, decode.d5.loss_mask: 0.4205, decode.d5.loss_dice: 0.5824, decode.d6.loss_cls: 0.1370, decode.d6.loss_mask: 0.4188, decode.d6.loss_dice: 0.5777, decode.d7.loss_cls: 0.1358, decode.d7.loss_mask: 0.4178, decode.d7.loss_dice: 0.5799, decode.d8.loss_cls: 0.1361, decode.d8.loss_mask: 0.4183, decode.d8.loss_dice: 0.5792, loss: 13.3114 +2022-05-06 05:52:25,313 - mmseg - INFO - Iter [23050/40000] lr: 6.085e-07, eta: 4:06:41, time: 0.737, data_time: 0.064, memory: 53770, decode.loss_cls: 0.1388, decode.loss_mask: 0.4360, decode.loss_dice: 0.5994, decode.d0.loss_cls: 1.7100, decode.d0.loss_mask: 0.4780, decode.d0.loss_dice: 0.7016, decode.d1.loss_cls: 0.2623, decode.d1.loss_mask: 0.4499, decode.d1.loss_dice: 0.6376, decode.d2.loss_cls: 0.1926, decode.d2.loss_mask: 0.4378, decode.d2.loss_dice: 0.6094, decode.d3.loss_cls: 0.1599, decode.d3.loss_mask: 0.4360, decode.d3.loss_dice: 0.6058, decode.d4.loss_cls: 0.1488, decode.d4.loss_mask: 0.4343, decode.d4.loss_dice: 0.6099, decode.d5.loss_cls: 0.1349, decode.d5.loss_mask: 0.4350, decode.d5.loss_dice: 0.6100, decode.d6.loss_cls: 0.1330, decode.d6.loss_mask: 0.4363, decode.d6.loss_dice: 0.6025, decode.d7.loss_cls: 0.1369, decode.d7.loss_mask: 0.4352, decode.d7.loss_dice: 0.6014, decode.d8.loss_cls: 0.1354, decode.d8.loss_mask: 0.4374, decode.d8.loss_dice: 0.6034, loss: 13.7496 +2022-05-06 05:52:58,899 - mmseg - INFO - Iter [23100/40000] lr: 6.067e-07, eta: 4:05:49, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1447, decode.loss_mask: 0.4246, decode.loss_dice: 0.6007, decode.d0.loss_cls: 1.6694, decode.d0.loss_mask: 0.4635, decode.d0.loss_dice: 0.6934, decode.d1.loss_cls: 0.2705, decode.d1.loss_mask: 0.4419, decode.d1.loss_dice: 0.6342, decode.d2.loss_cls: 0.1852, decode.d2.loss_mask: 0.4327, decode.d2.loss_dice: 0.6167, decode.d3.loss_cls: 0.1677, decode.d3.loss_mask: 0.4287, decode.d3.loss_dice: 0.6089, decode.d4.loss_cls: 0.1588, decode.d4.loss_mask: 0.4285, decode.d4.loss_dice: 0.6042, decode.d5.loss_cls: 0.1550, decode.d5.loss_mask: 0.4250, decode.d5.loss_dice: 0.6010, decode.d6.loss_cls: 0.1454, decode.d6.loss_mask: 0.4259, decode.d6.loss_dice: 0.6016, decode.d7.loss_cls: 0.1431, decode.d7.loss_mask: 0.4262, decode.d7.loss_dice: 0.5974, decode.d8.loss_cls: 0.1453, decode.d8.loss_mask: 0.4241, decode.d8.loss_dice: 0.5966, loss: 13.6609 +2022-05-06 05:53:32,367 - mmseg - INFO - Iter [23150/40000] lr: 6.049e-07, eta: 4:04:56, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1464, decode.loss_mask: 0.4283, decode.loss_dice: 0.6050, decode.d0.loss_cls: 1.6776, decode.d0.loss_mask: 0.4638, decode.d0.loss_dice: 0.7125, decode.d1.loss_cls: 0.2670, decode.d1.loss_mask: 0.4437, decode.d1.loss_dice: 0.6469, decode.d2.loss_cls: 0.1870, decode.d2.loss_mask: 0.4359, decode.d2.loss_dice: 0.6233, decode.d3.loss_cls: 0.1603, decode.d3.loss_mask: 0.4306, decode.d3.loss_dice: 0.6137, decode.d4.loss_cls: 0.1537, decode.d4.loss_mask: 0.4287, decode.d4.loss_dice: 0.6135, decode.d5.loss_cls: 0.1505, decode.d5.loss_mask: 0.4267, decode.d5.loss_dice: 0.6094, decode.d6.loss_cls: 0.1502, decode.d6.loss_mask: 0.4278, decode.d6.loss_dice: 0.6064, decode.d7.loss_cls: 0.1472, decode.d7.loss_mask: 0.4270, decode.d7.loss_dice: 0.6057, decode.d8.loss_cls: 0.1455, decode.d8.loss_mask: 0.4275, decode.d8.loss_dice: 0.6081, loss: 13.7698 +2022-05-06 05:54:06,217 - mmseg - INFO - Iter [23200/40000] lr: 6.031e-07, eta: 4:04:04, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1413, decode.loss_mask: 0.4037, decode.loss_dice: 0.5615, decode.d0.loss_cls: 1.6704, decode.d0.loss_mask: 0.4415, decode.d0.loss_dice: 0.6643, decode.d1.loss_cls: 0.2539, decode.d1.loss_mask: 0.4173, decode.d1.loss_dice: 0.5980, decode.d2.loss_cls: 0.1790, decode.d2.loss_mask: 0.4081, decode.d2.loss_dice: 0.5785, decode.d3.loss_cls: 0.1583, decode.d3.loss_mask: 0.4037, decode.d3.loss_dice: 0.5704, decode.d4.loss_cls: 0.1533, decode.d4.loss_mask: 0.4048, decode.d4.loss_dice: 0.5656, decode.d5.loss_cls: 0.1429, decode.d5.loss_mask: 0.4035, decode.d5.loss_dice: 0.5684, decode.d6.loss_cls: 0.1437, decode.d6.loss_mask: 0.4035, decode.d6.loss_dice: 0.5596, decode.d7.loss_cls: 0.1366, decode.d7.loss_mask: 0.4030, decode.d7.loss_dice: 0.5619, decode.d8.loss_cls: 0.1403, decode.d8.loss_mask: 0.4038, decode.d8.loss_dice: 0.5605, loss: 13.0013 +2022-05-06 05:54:40,129 - mmseg - INFO - Iter [23250/40000] lr: 6.013e-07, eta: 4:03:12, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1341, decode.loss_mask: 0.4206, decode.loss_dice: 0.5760, decode.d0.loss_cls: 1.6253, decode.d0.loss_mask: 0.4596, decode.d0.loss_dice: 0.6818, decode.d1.loss_cls: 0.2518, decode.d1.loss_mask: 0.4325, decode.d1.loss_dice: 0.6071, decode.d2.loss_cls: 0.1789, decode.d2.loss_mask: 0.4222, decode.d2.loss_dice: 0.5834, decode.d3.loss_cls: 0.1544, decode.d3.loss_mask: 0.4202, decode.d3.loss_dice: 0.5796, decode.d4.loss_cls: 0.1465, decode.d4.loss_mask: 0.4208, decode.d4.loss_dice: 0.5771, decode.d5.loss_cls: 0.1454, decode.d5.loss_mask: 0.4215, decode.d5.loss_dice: 0.5759, decode.d6.loss_cls: 0.1380, decode.d6.loss_mask: 0.4229, decode.d6.loss_dice: 0.5715, decode.d7.loss_cls: 0.1353, decode.d7.loss_mask: 0.4220, decode.d7.loss_dice: 0.5726, decode.d8.loss_cls: 0.1343, decode.d8.loss_mask: 0.4187, decode.d8.loss_dice: 0.5765, loss: 13.2065 +2022-05-06 05:55:13,357 - mmseg - INFO - Iter [23300/40000] lr: 5.995e-07, eta: 4:02:20, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1379, decode.loss_mask: 0.4359, decode.loss_dice: 0.6058, decode.d0.loss_cls: 1.6736, decode.d0.loss_mask: 0.4764, decode.d0.loss_dice: 0.7088, decode.d1.loss_cls: 0.2635, decode.d1.loss_mask: 0.4525, decode.d1.loss_dice: 0.6493, decode.d2.loss_cls: 0.1856, decode.d2.loss_mask: 0.4407, decode.d2.loss_dice: 0.6202, decode.d3.loss_cls: 0.1564, decode.d3.loss_mask: 0.4373, decode.d3.loss_dice: 0.6135, decode.d4.loss_cls: 0.1567, decode.d4.loss_mask: 0.4362, decode.d4.loss_dice: 0.6138, decode.d5.loss_cls: 0.1419, decode.d5.loss_mask: 0.4349, decode.d5.loss_dice: 0.6126, decode.d6.loss_cls: 0.1388, decode.d6.loss_mask: 0.4346, decode.d6.loss_dice: 0.6030, decode.d7.loss_cls: 0.1358, decode.d7.loss_mask: 0.4327, decode.d7.loss_dice: 0.6061, decode.d8.loss_cls: 0.1370, decode.d8.loss_mask: 0.4315, decode.d8.loss_dice: 0.6047, loss: 13.7779 +2022-05-06 05:55:49,370 - mmseg - INFO - Iter [23350/40000] lr: 5.977e-07, eta: 4:01:30, time: 0.720, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1322, decode.loss_mask: 0.4206, decode.loss_dice: 0.5720, decode.d0.loss_cls: 1.6199, decode.d0.loss_mask: 0.4573, decode.d0.loss_dice: 0.6645, decode.d1.loss_cls: 0.2413, decode.d1.loss_mask: 0.4317, decode.d1.loss_dice: 0.6113, decode.d2.loss_cls: 0.1676, decode.d2.loss_mask: 0.4237, decode.d2.loss_dice: 0.5889, decode.d3.loss_cls: 0.1424, decode.d3.loss_mask: 0.4210, decode.d3.loss_dice: 0.5782, decode.d4.loss_cls: 0.1373, decode.d4.loss_mask: 0.4209, decode.d4.loss_dice: 0.5795, decode.d5.loss_cls: 0.1309, decode.d5.loss_mask: 0.4200, decode.d5.loss_dice: 0.5774, decode.d6.loss_cls: 0.1282, decode.d6.loss_mask: 0.4194, decode.d6.loss_dice: 0.5749, decode.d7.loss_cls: 0.1229, decode.d7.loss_mask: 0.4203, decode.d7.loss_dice: 0.5766, decode.d8.loss_cls: 0.1285, decode.d8.loss_mask: 0.4188, decode.d8.loss_dice: 0.5723, loss: 13.1009 +2022-05-06 05:56:22,857 - mmseg - INFO - Iter [23400/40000] lr: 5.959e-07, eta: 4:00:37, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1377, decode.loss_mask: 0.4220, decode.loss_dice: 0.5962, decode.d0.loss_cls: 1.6658, decode.d0.loss_mask: 0.4705, decode.d0.loss_dice: 0.7040, decode.d1.loss_cls: 0.2620, decode.d1.loss_mask: 0.4360, decode.d1.loss_dice: 0.6394, decode.d2.loss_cls: 0.1806, decode.d2.loss_mask: 0.4287, decode.d2.loss_dice: 0.6148, decode.d3.loss_cls: 0.1582, decode.d3.loss_mask: 0.4246, decode.d3.loss_dice: 0.5977, decode.d4.loss_cls: 0.1406, decode.d4.loss_mask: 0.4252, decode.d4.loss_dice: 0.6005, decode.d5.loss_cls: 0.1413, decode.d5.loss_mask: 0.4227, decode.d5.loss_dice: 0.5990, decode.d6.loss_cls: 0.1364, decode.d6.loss_mask: 0.4221, decode.d6.loss_dice: 0.5924, decode.d7.loss_cls: 0.1349, decode.d7.loss_mask: 0.4228, decode.d7.loss_dice: 0.5945, decode.d8.loss_cls: 0.1347, decode.d8.loss_mask: 0.4205, decode.d8.loss_dice: 0.5953, loss: 13.5211 +2022-05-06 05:56:56,427 - mmseg - INFO - Iter [23450/40000] lr: 5.941e-07, eta: 3:59:46, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1260, decode.loss_mask: 0.4181, decode.loss_dice: 0.5674, decode.d0.loss_cls: 1.6381, decode.d0.loss_mask: 0.4619, decode.d0.loss_dice: 0.6625, decode.d1.loss_cls: 0.2425, decode.d1.loss_mask: 0.4281, decode.d1.loss_dice: 0.5961, decode.d2.loss_cls: 0.1714, decode.d2.loss_mask: 0.4193, decode.d2.loss_dice: 0.5805, decode.d3.loss_cls: 0.1433, decode.d3.loss_mask: 0.4182, decode.d3.loss_dice: 0.5700, decode.d4.loss_cls: 0.1390, decode.d4.loss_mask: 0.4170, decode.d4.loss_dice: 0.5680, decode.d5.loss_cls: 0.1357, decode.d5.loss_mask: 0.4170, decode.d5.loss_dice: 0.5665, decode.d6.loss_cls: 0.1236, decode.d6.loss_mask: 0.4177, decode.d6.loss_dice: 0.5684, decode.d7.loss_cls: 0.1241, decode.d7.loss_mask: 0.4187, decode.d7.loss_dice: 0.5681, decode.d8.loss_cls: 0.1271, decode.d8.loss_mask: 0.4181, decode.d8.loss_dice: 0.5681, loss: 13.0204 +2022-05-06 05:57:29,828 - mmseg - INFO - Iter [23500/40000] lr: 5.923e-07, eta: 3:58:54, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1342, decode.loss_mask: 0.4091, decode.loss_dice: 0.5788, decode.d0.loss_cls: 1.6604, decode.d0.loss_mask: 0.4497, decode.d0.loss_dice: 0.6930, decode.d1.loss_cls: 0.2582, decode.d1.loss_mask: 0.4247, decode.d1.loss_dice: 0.6170, decode.d2.loss_cls: 0.1912, decode.d2.loss_mask: 0.4151, decode.d2.loss_dice: 0.5922, decode.d3.loss_cls: 0.1620, decode.d3.loss_mask: 0.4119, decode.d3.loss_dice: 0.5849, decode.d4.loss_cls: 0.1497, decode.d4.loss_mask: 0.4103, decode.d4.loss_dice: 0.5859, decode.d5.loss_cls: 0.1497, decode.d5.loss_mask: 0.4105, decode.d5.loss_dice: 0.5829, decode.d6.loss_cls: 0.1398, decode.d6.loss_mask: 0.4085, decode.d6.loss_dice: 0.5800, decode.d7.loss_cls: 0.1409, decode.d7.loss_mask: 0.4081, decode.d7.loss_dice: 0.5774, decode.d8.loss_cls: 0.1360, decode.d8.loss_mask: 0.4104, decode.d8.loss_dice: 0.5780, loss: 13.2506 +2022-05-06 05:58:03,302 - mmseg - INFO - Iter [23550/40000] lr: 5.905e-07, eta: 3:58:02, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1507, decode.loss_mask: 0.4027, decode.loss_dice: 0.5821, decode.d0.loss_cls: 1.6947, decode.d0.loss_mask: 0.4445, decode.d0.loss_dice: 0.6876, decode.d1.loss_cls: 0.2634, decode.d1.loss_mask: 0.4205, decode.d1.loss_dice: 0.6171, decode.d2.loss_cls: 0.1964, decode.d2.loss_mask: 0.4124, decode.d2.loss_dice: 0.5922, decode.d3.loss_cls: 0.1673, decode.d3.loss_mask: 0.4091, decode.d3.loss_dice: 0.5769, decode.d4.loss_cls: 0.1634, decode.d4.loss_mask: 0.4069, decode.d4.loss_dice: 0.5766, decode.d5.loss_cls: 0.1563, decode.d5.loss_mask: 0.4062, decode.d5.loss_dice: 0.5737, decode.d6.loss_cls: 0.1520, decode.d6.loss_mask: 0.4060, decode.d6.loss_dice: 0.5725, decode.d7.loss_cls: 0.1528, decode.d7.loss_mask: 0.4043, decode.d7.loss_dice: 0.5751, decode.d8.loss_cls: 0.1494, decode.d8.loss_mask: 0.4029, decode.d8.loss_dice: 0.5739, loss: 13.2895 +2022-05-06 05:58:36,569 - mmseg - INFO - Iter [23600/40000] lr: 5.887e-07, eta: 3:57:10, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1470, decode.loss_mask: 0.4254, decode.loss_dice: 0.5747, decode.d0.loss_cls: 1.6320, decode.d0.loss_mask: 0.4635, decode.d0.loss_dice: 0.6724, decode.d1.loss_cls: 0.2582, decode.d1.loss_mask: 0.4403, decode.d1.loss_dice: 0.6103, decode.d2.loss_cls: 0.1902, decode.d2.loss_mask: 0.4287, decode.d2.loss_dice: 0.5897, decode.d3.loss_cls: 0.1629, decode.d3.loss_mask: 0.4241, decode.d3.loss_dice: 0.5790, decode.d4.loss_cls: 0.1603, decode.d4.loss_mask: 0.4227, decode.d4.loss_dice: 0.5776, decode.d5.loss_cls: 0.1533, decode.d5.loss_mask: 0.4243, decode.d5.loss_dice: 0.5773, decode.d6.loss_cls: 0.1489, decode.d6.loss_mask: 0.4228, decode.d6.loss_dice: 0.5721, decode.d7.loss_cls: 0.1463, decode.d7.loss_mask: 0.4223, decode.d7.loss_dice: 0.5770, decode.d8.loss_cls: 0.1443, decode.d8.loss_mask: 0.4255, decode.d8.loss_dice: 0.5744, loss: 13.3474 +2022-05-06 05:59:10,026 - mmseg - INFO - Iter [23650/40000] lr: 5.869e-07, eta: 3:56:18, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1319, decode.loss_mask: 0.4276, decode.loss_dice: 0.5908, decode.d0.loss_cls: 1.6422, decode.d0.loss_mask: 0.4743, decode.d0.loss_dice: 0.6977, decode.d1.loss_cls: 0.2430, decode.d1.loss_mask: 0.4412, decode.d1.loss_dice: 0.6251, decode.d2.loss_cls: 0.1730, decode.d2.loss_mask: 0.4321, decode.d2.loss_dice: 0.6103, decode.d3.loss_cls: 0.1492, decode.d3.loss_mask: 0.4290, decode.d3.loss_dice: 0.5935, decode.d4.loss_cls: 0.1451, decode.d4.loss_mask: 0.4286, decode.d4.loss_dice: 0.5929, decode.d5.loss_cls: 0.1387, decode.d5.loss_mask: 0.4311, decode.d5.loss_dice: 0.5927, decode.d6.loss_cls: 0.1347, decode.d6.loss_mask: 0.4283, decode.d6.loss_dice: 0.5921, decode.d7.loss_cls: 0.1355, decode.d7.loss_mask: 0.4285, decode.d7.loss_dice: 0.5922, decode.d8.loss_cls: 0.1281, decode.d8.loss_mask: 0.4283, decode.d8.loss_dice: 0.5902, loss: 13.4478 +2022-05-06 05:59:47,090 - mmseg - INFO - Iter [23700/40000] lr: 5.851e-07, eta: 3:55:30, time: 0.741, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1539, decode.loss_mask: 0.4293, decode.loss_dice: 0.5858, decode.d0.loss_cls: 1.6545, decode.d0.loss_mask: 0.4682, decode.d0.loss_dice: 0.6981, decode.d1.loss_cls: 0.2545, decode.d1.loss_mask: 0.4428, decode.d1.loss_dice: 0.6295, decode.d2.loss_cls: 0.1893, decode.d2.loss_mask: 0.4355, decode.d2.loss_dice: 0.6080, decode.d3.loss_cls: 0.1652, decode.d3.loss_mask: 0.4324, decode.d3.loss_dice: 0.5904, decode.d4.loss_cls: 0.1601, decode.d4.loss_mask: 0.4343, decode.d4.loss_dice: 0.5916, decode.d5.loss_cls: 0.1476, decode.d5.loss_mask: 0.4321, decode.d5.loss_dice: 0.5915, decode.d6.loss_cls: 0.1492, decode.d6.loss_mask: 0.4297, decode.d6.loss_dice: 0.5871, decode.d7.loss_cls: 0.1508, decode.d7.loss_mask: 0.4299, decode.d7.loss_dice: 0.5850, decode.d8.loss_cls: 0.1505, decode.d8.loss_mask: 0.4291, decode.d8.loss_dice: 0.5865, loss: 13.5925 +2022-05-06 06:00:21,959 - mmseg - INFO - Iter [23750/40000] lr: 5.833e-07, eta: 3:54:39, time: 0.697, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1220, decode.loss_mask: 0.4155, decode.loss_dice: 0.5799, decode.d0.loss_cls: 1.6084, decode.d0.loss_mask: 0.4532, decode.d0.loss_dice: 0.6750, decode.d1.loss_cls: 0.2425, decode.d1.loss_mask: 0.4309, decode.d1.loss_dice: 0.6139, decode.d2.loss_cls: 0.1615, decode.d2.loss_mask: 0.4186, decode.d2.loss_dice: 0.5941, decode.d3.loss_cls: 0.1399, decode.d3.loss_mask: 0.4150, decode.d3.loss_dice: 0.5831, decode.d4.loss_cls: 0.1391, decode.d4.loss_mask: 0.4159, decode.d4.loss_dice: 0.5811, decode.d5.loss_cls: 0.1344, decode.d5.loss_mask: 0.4137, decode.d5.loss_dice: 0.5806, decode.d6.loss_cls: 0.1245, decode.d6.loss_mask: 0.4132, decode.d6.loss_dice: 0.5785, decode.d7.loss_cls: 0.1246, decode.d7.loss_mask: 0.4139, decode.d7.loss_dice: 0.5771, decode.d8.loss_cls: 0.1210, decode.d8.loss_mask: 0.4146, decode.d8.loss_dice: 0.5823, loss: 13.0680 +2022-05-06 06:00:55,507 - mmseg - INFO - Iter [23800/40000] lr: 5.815e-07, eta: 3:53:48, time: 0.670, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1530, decode.loss_mask: 0.4227, decode.loss_dice: 0.5822, decode.d0.loss_cls: 1.6588, decode.d0.loss_mask: 0.4615, decode.d0.loss_dice: 0.6896, decode.d1.loss_cls: 0.2718, decode.d1.loss_mask: 0.4365, decode.d1.loss_dice: 0.6193, decode.d2.loss_cls: 0.1915, decode.d2.loss_mask: 0.4248, decode.d2.loss_dice: 0.6021, decode.d3.loss_cls: 0.1653, decode.d3.loss_mask: 0.4254, decode.d3.loss_dice: 0.5903, decode.d4.loss_cls: 0.1588, decode.d4.loss_mask: 0.4247, decode.d4.loss_dice: 0.5925, decode.d5.loss_cls: 0.1549, decode.d5.loss_mask: 0.4247, decode.d5.loss_dice: 0.5871, decode.d6.loss_cls: 0.1524, decode.d6.loss_mask: 0.4215, decode.d6.loss_dice: 0.5843, decode.d7.loss_cls: 0.1480, decode.d7.loss_mask: 0.4230, decode.d7.loss_dice: 0.5839, decode.d8.loss_cls: 0.1534, decode.d8.loss_mask: 0.4221, decode.d8.loss_dice: 0.5813, loss: 13.5073 +2022-05-06 06:01:28,648 - mmseg - INFO - Iter [23850/40000] lr: 5.797e-07, eta: 3:52:56, time: 0.663, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1545, decode.loss_mask: 0.4199, decode.loss_dice: 0.5945, decode.d0.loss_cls: 1.6306, decode.d0.loss_mask: 0.4593, decode.d0.loss_dice: 0.6983, decode.d1.loss_cls: 0.2641, decode.d1.loss_mask: 0.4357, decode.d1.loss_dice: 0.6312, decode.d2.loss_cls: 0.1931, decode.d2.loss_mask: 0.4261, decode.d2.loss_dice: 0.6125, decode.d3.loss_cls: 0.1729, decode.d3.loss_mask: 0.4235, decode.d3.loss_dice: 0.6013, decode.d4.loss_cls: 0.1655, decode.d4.loss_mask: 0.4195, decode.d4.loss_dice: 0.5974, decode.d5.loss_cls: 0.1584, decode.d5.loss_mask: 0.4196, decode.d5.loss_dice: 0.6018, decode.d6.loss_cls: 0.1507, decode.d6.loss_mask: 0.4194, decode.d6.loss_dice: 0.5972, decode.d7.loss_cls: 0.1526, decode.d7.loss_mask: 0.4197, decode.d7.loss_dice: 0.5905, decode.d8.loss_cls: 0.1545, decode.d8.loss_mask: 0.4191, decode.d8.loss_dice: 0.5939, loss: 13.5774 +2022-05-06 06:02:02,302 - mmseg - INFO - Iter [23900/40000] lr: 5.779e-07, eta: 3:52:05, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1274, decode.loss_mask: 0.4285, decode.loss_dice: 0.5742, decode.d0.loss_cls: 1.6530, decode.d0.loss_mask: 0.4739, decode.d0.loss_dice: 0.6819, decode.d1.loss_cls: 0.2465, decode.d1.loss_mask: 0.4438, decode.d1.loss_dice: 0.6117, decode.d2.loss_cls: 0.1688, decode.d2.loss_mask: 0.4358, decode.d2.loss_dice: 0.5918, decode.d3.loss_cls: 0.1483, decode.d3.loss_mask: 0.4346, decode.d3.loss_dice: 0.5837, decode.d4.loss_cls: 0.1415, decode.d4.loss_mask: 0.4320, decode.d4.loss_dice: 0.5827, decode.d5.loss_cls: 0.1352, decode.d5.loss_mask: 0.4301, decode.d5.loss_dice: 0.5795, decode.d6.loss_cls: 0.1312, decode.d6.loss_mask: 0.4313, decode.d6.loss_dice: 0.5769, decode.d7.loss_cls: 0.1271, decode.d7.loss_mask: 0.4293, decode.d7.loss_dice: 0.5777, decode.d8.loss_cls: 0.1230, decode.d8.loss_mask: 0.4306, decode.d8.loss_dice: 0.5791, loss: 13.3109 +2022-05-06 06:02:35,914 - mmseg - INFO - Iter [23950/40000] lr: 5.761e-07, eta: 3:51:14, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1104, decode.loss_mask: 0.4228, decode.loss_dice: 0.5783, decode.d0.loss_cls: 1.6511, decode.d0.loss_mask: 0.4675, decode.d0.loss_dice: 0.6759, decode.d1.loss_cls: 0.2487, decode.d1.loss_mask: 0.4395, decode.d1.loss_dice: 0.6141, decode.d2.loss_cls: 0.1621, decode.d2.loss_mask: 0.4266, decode.d2.loss_dice: 0.5978, decode.d3.loss_cls: 0.1362, decode.d3.loss_mask: 0.4262, decode.d3.loss_dice: 0.5862, decode.d4.loss_cls: 0.1268, decode.d4.loss_mask: 0.4251, decode.d4.loss_dice: 0.5860, decode.d5.loss_cls: 0.1183, decode.d5.loss_mask: 0.4223, decode.d5.loss_dice: 0.5838, decode.d6.loss_cls: 0.1156, decode.d6.loss_mask: 0.4198, decode.d6.loss_dice: 0.5790, decode.d7.loss_cls: 0.1141, decode.d7.loss_mask: 0.4204, decode.d7.loss_dice: 0.5830, decode.d8.loss_cls: 0.1111, decode.d8.loss_mask: 0.4211, decode.d8.loss_dice: 0.5810, loss: 13.1508 +2022-05-06 06:03:12,295 - mmseg - INFO - Saving checkpoint at 24000 iterations +2022-05-06 06:03:37,425 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:03:37,431 - mmseg - INFO - Iter [24000/40000] lr: 5.744e-07, eta: 3:50:46, time: 1.228, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1233, decode.loss_mask: 0.4259, decode.loss_dice: 0.5752, decode.d0.loss_cls: 1.6128, decode.d0.loss_mask: 0.4763, decode.d0.loss_dice: 0.6890, decode.d1.loss_cls: 0.2239, decode.d1.loss_mask: 0.4404, decode.d1.loss_dice: 0.6192, decode.d2.loss_cls: 0.1702, decode.d2.loss_mask: 0.4343, decode.d2.loss_dice: 0.5941, decode.d3.loss_cls: 0.1485, decode.d3.loss_mask: 0.4284, decode.d3.loss_dice: 0.5806, decode.d4.loss_cls: 0.1359, decode.d4.loss_mask: 0.4300, decode.d4.loss_dice: 0.5861, decode.d5.loss_cls: 0.1322, decode.d5.loss_mask: 0.4286, decode.d5.loss_dice: 0.5793, decode.d6.loss_cls: 0.1312, decode.d6.loss_mask: 0.4264, decode.d6.loss_dice: 0.5760, decode.d7.loss_cls: 0.1242, decode.d7.loss_mask: 0.4274, decode.d7.loss_dice: 0.5773, decode.d8.loss_cls: 0.1244, decode.d8.loss_mask: 0.4278, decode.d8.loss_dice: 0.5807, loss: 13.2298 +2022-05-06 06:07:58,039 - mmseg - INFO - per class results: +2022-05-06 06:07:58,058 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 93.15 | 96.62 | +| bag | 48.53 | 67.96 | +| bed | 37.19 | 44.35 | +| bedclothes | 45.23 | 82.48 | +| bench | 28.92 | 32.86 | +| bicycle | 85.57 | 91.89 | +| bird | 95.17 | 97.52 | +| boat | 87.2 | 93.91 | +| book | 57.61 | 74.91 | +| bottle | 89.02 | 96.83 | +| building | 66.88 | 76.64 | +| bus | 94.95 | 96.7 | +| cabinet | 51.65 | 65.05 | +| car | 93.9 | 97.51 | +| cat | 94.6 | 97.86 | +| ceiling | 61.87 | 80.83 | +| chair | 62.01 | 87.32 | +| cloth | 22.0 | 26.03 | +| computer | 58.18 | 68.44 | +| cow | 96.05 | 97.86 | +| cup | 50.56 | 70.38 | +| curtain | 58.88 | 82.51 | +| dog | 92.67 | 97.51 | +| door | 40.47 | 65.41 | +| fence | 46.74 | 68.64 | +| floor | 74.95 | 86.97 | +| flower | 48.24 | 62.38 | +| food | 43.43 | 58.97 | +| grass | 83.15 | 92.39 | +| ground | 57.36 | 71.51 | +| horse | 95.3 | 97.7 | +| keyboard | 85.65 | 94.94 | +| light | 62.71 | 79.14 | +| motorbike | 91.94 | 97.42 | +| mountain | 56.12 | 72.78 | +| mouse | 87.15 | 90.75 | +| person | 91.85 | 96.07 | +| plate | 30.72 | 37.98 | +| platform | 44.87 | 56.55 | +| pottedplant | 82.55 | 89.77 | +| road | 53.63 | 69.25 | +| rock | 56.09 | 66.76 | +| sheep | 95.04 | 97.14 | +| shelves | 40.35 | 61.38 | +| sidewalk | 33.91 | 50.2 | +| sign | 57.82 | 69.07 | +| sky | 94.96 | 96.94 | +| snow | 79.27 | 87.73 | +| sofa | 59.96 | 66.22 | +| table | 70.42 | 81.71 | +| track | 72.79 | 83.5 | +| train | 93.23 | 97.14 | +| tree | 81.85 | 91.79 | +| truck | 54.57 | 63.62 | +| tvmonitor | 90.89 | 93.55 | +| wall | 72.07 | 84.2 | +| water | 92.9 | 96.42 | +| window | 45.12 | 61.78 | +| wood | 29.46 | 38.99 | ++-------------+-------+-------+ +2022-05-06 06:07:58,058 - mmseg - INFO - Summary: +2022-05-06 06:07:58,059 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.41 | 67.28 | 77.98 | ++-------+-------+-------+ +2022-05-06 06:07:58,073 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:07:58,074 - mmseg - INFO - Iter(val) [638] aAcc: 0.8641, mIoU: 0.6728, mAcc: 0.7798, IoU.aeroplane: 0.9315, IoU.bag: 0.4853, IoU.bed: 0.3719, IoU.bedclothes: 0.4523, IoU.bench: 0.2892, IoU.bicycle: 0.8557, IoU.bird: 0.9517, IoU.boat: 0.8720, IoU.book: 0.5761, IoU.bottle: 0.8902, IoU.building: 0.6688, IoU.bus: 0.9495, IoU.cabinet: 0.5165, IoU.car: 0.9390, IoU.cat: 0.9460, IoU.ceiling: 0.6187, IoU.chair: 0.6201, IoU.cloth: 0.2200, IoU.computer: 0.5818, IoU.cow: 0.9605, IoU.cup: 0.5056, IoU.curtain: 0.5888, IoU.dog: 0.9267, IoU.door: 0.4047, IoU.fence: 0.4674, IoU.floor: 0.7495, IoU.flower: 0.4824, IoU.food: 0.4343, IoU.grass: 0.8315, IoU.ground: 0.5736, IoU.horse: 0.9530, IoU.keyboard: 0.8565, IoU.light: 0.6271, IoU.motorbike: 0.9194, IoU.mountain: 0.5612, IoU.mouse: 0.8715, IoU.person: 0.9185, IoU.plate: 0.3072, IoU.platform: 0.4487, IoU.pottedplant: 0.8255, IoU.road: 0.5363, IoU.rock: 0.5609, IoU.sheep: 0.9504, IoU.shelves: 0.4035, IoU.sidewalk: 0.3391, IoU.sign: 0.5782, IoU.sky: 0.9496, IoU.snow: 0.7927, IoU.sofa: 0.5996, IoU.table: 0.7042, IoU.track: 0.7279, IoU.train: 0.9323, IoU.tree: 0.8185, IoU.truck: 0.5457, IoU.tvmonitor: 0.9089, IoU.wall: 0.7207, IoU.water: 0.9290, IoU.window: 0.4512, IoU.wood: 0.2946, Acc.aeroplane: 0.9662, Acc.bag: 0.6796, Acc.bed: 0.4435, Acc.bedclothes: 0.8248, Acc.bench: 0.3286, Acc.bicycle: 0.9189, Acc.bird: 0.9752, Acc.boat: 0.9391, Acc.book: 0.7491, Acc.bottle: 0.9683, Acc.building: 0.7664, Acc.bus: 0.9670, Acc.cabinet: 0.6505, Acc.car: 0.9751, Acc.cat: 0.9786, Acc.ceiling: 0.8083, Acc.chair: 0.8732, Acc.cloth: 0.2603, Acc.computer: 0.6844, Acc.cow: 0.9786, Acc.cup: 0.7038, Acc.curtain: 0.8251, Acc.dog: 0.9751, Acc.door: 0.6541, Acc.fence: 0.6864, Acc.floor: 0.8697, Acc.flower: 0.6238, Acc.food: 0.5897, Acc.grass: 0.9239, Acc.ground: 0.7151, Acc.horse: 0.9770, Acc.keyboard: 0.9494, Acc.light: 0.7914, Acc.motorbike: 0.9742, Acc.mountain: 0.7278, Acc.mouse: 0.9075, Acc.person: 0.9607, Acc.plate: 0.3798, Acc.platform: 0.5655, Acc.pottedplant: 0.8977, Acc.road: 0.6925, Acc.rock: 0.6676, Acc.sheep: 0.9714, Acc.shelves: 0.6138, Acc.sidewalk: 0.5020, Acc.sign: 0.6907, Acc.sky: 0.9694, Acc.snow: 0.8773, Acc.sofa: 0.6622, Acc.table: 0.8171, Acc.track: 0.8350, Acc.train: 0.9714, Acc.tree: 0.9179, Acc.truck: 0.6362, Acc.tvmonitor: 0.9355, Acc.wall: 0.8420, Acc.water: 0.9642, Acc.window: 0.6178, Acc.wood: 0.3899 +2022-05-06 06:08:31,429 - mmseg - INFO - Iter [24050/40000] lr: 5.726e-07, eta: 3:53:22, time: 5.882, data_time: 5.223, memory: 53770, decode.loss_cls: 0.1196, decode.loss_mask: 0.3991, decode.loss_dice: 0.5896, decode.d0.loss_cls: 1.6721, decode.d0.loss_mask: 0.4375, decode.d0.loss_dice: 0.6921, decode.d1.loss_cls: 0.2284, decode.d1.loss_mask: 0.4144, decode.d1.loss_dice: 0.6232, decode.d2.loss_cls: 0.1604, decode.d2.loss_mask: 0.4044, decode.d2.loss_dice: 0.5980, decode.d3.loss_cls: 0.1402, decode.d3.loss_mask: 0.4029, decode.d3.loss_dice: 0.5935, decode.d4.loss_cls: 0.1311, decode.d4.loss_mask: 0.4028, decode.d4.loss_dice: 0.5935, decode.d5.loss_cls: 0.1286, decode.d5.loss_mask: 0.4004, decode.d5.loss_dice: 0.5863, decode.d6.loss_cls: 0.1223, decode.d6.loss_mask: 0.3978, decode.d6.loss_dice: 0.5881, decode.d7.loss_cls: 0.1199, decode.d7.loss_mask: 0.3956, decode.d7.loss_dice: 0.5863, decode.d8.loss_cls: 0.1196, decode.d8.loss_mask: 0.3972, decode.d8.loss_dice: 0.5881, loss: 13.0331 +2022-05-06 06:09:05,386 - mmseg - INFO - Iter [24100/40000] lr: 5.708e-07, eta: 3:52:30, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1262, decode.loss_mask: 0.4102, decode.loss_dice: 0.5860, decode.d0.loss_cls: 1.6380, decode.d0.loss_mask: 0.4479, decode.d0.loss_dice: 0.6930, decode.d1.loss_cls: 0.2635, decode.d1.loss_mask: 0.4221, decode.d1.loss_dice: 0.6185, decode.d2.loss_cls: 0.1886, decode.d2.loss_mask: 0.4137, decode.d2.loss_dice: 0.5963, decode.d3.loss_cls: 0.1589, decode.d3.loss_mask: 0.4126, decode.d3.loss_dice: 0.5894, decode.d4.loss_cls: 0.1497, decode.d4.loss_mask: 0.4112, decode.d4.loss_dice: 0.5891, decode.d5.loss_cls: 0.1406, decode.d5.loss_mask: 0.4095, decode.d5.loss_dice: 0.5857, decode.d6.loss_cls: 0.1369, decode.d6.loss_mask: 0.4094, decode.d6.loss_dice: 0.5846, decode.d7.loss_cls: 0.1355, decode.d7.loss_mask: 0.4086, decode.d7.loss_dice: 0.5869, decode.d8.loss_cls: 0.1300, decode.d8.loss_mask: 0.4081, decode.d8.loss_dice: 0.5883, loss: 13.2389 +2022-05-06 06:09:38,789 - mmseg - INFO - Iter [24150/40000] lr: 5.690e-07, eta: 3:51:38, time: 0.669, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1263, decode.loss_mask: 0.4226, decode.loss_dice: 0.5808, decode.d0.loss_cls: 1.6075, decode.d0.loss_mask: 0.4617, decode.d0.loss_dice: 0.6846, decode.d1.loss_cls: 0.2298, decode.d1.loss_mask: 0.4342, decode.d1.loss_dice: 0.6169, decode.d2.loss_cls: 0.1745, decode.d2.loss_mask: 0.4262, decode.d2.loss_dice: 0.5951, decode.d3.loss_cls: 0.1470, decode.d3.loss_mask: 0.4219, decode.d3.loss_dice: 0.5843, decode.d4.loss_cls: 0.1391, decode.d4.loss_mask: 0.4227, decode.d4.loss_dice: 0.5836, decode.d5.loss_cls: 0.1371, decode.d5.loss_mask: 0.4202, decode.d5.loss_dice: 0.5777, decode.d6.loss_cls: 0.1287, decode.d6.loss_mask: 0.4195, decode.d6.loss_dice: 0.5750, decode.d7.loss_cls: 0.1264, decode.d7.loss_mask: 0.4206, decode.d7.loss_dice: 0.5768, decode.d8.loss_cls: 0.1212, decode.d8.loss_mask: 0.4238, decode.d8.loss_dice: 0.5815, loss: 13.1670 +2022-05-06 06:10:12,037 - mmseg - INFO - Iter [24200/40000] lr: 5.672e-07, eta: 3:50:46, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1189, decode.loss_mask: 0.4155, decode.loss_dice: 0.5669, decode.d0.loss_cls: 1.6162, decode.d0.loss_mask: 0.4579, decode.d0.loss_dice: 0.6778, decode.d1.loss_cls: 0.2535, decode.d1.loss_mask: 0.4267, decode.d1.loss_dice: 0.6063, decode.d2.loss_cls: 0.1884, decode.d2.loss_mask: 0.4216, decode.d2.loss_dice: 0.5867, decode.d3.loss_cls: 0.1409, decode.d3.loss_mask: 0.4180, decode.d3.loss_dice: 0.5712, decode.d4.loss_cls: 0.1364, decode.d4.loss_mask: 0.4155, decode.d4.loss_dice: 0.5765, decode.d5.loss_cls: 0.1287, decode.d5.loss_mask: 0.4164, decode.d5.loss_dice: 0.5752, decode.d6.loss_cls: 0.1251, decode.d6.loss_mask: 0.4147, decode.d6.loss_dice: 0.5706, decode.d7.loss_cls: 0.1177, decode.d7.loss_mask: 0.4169, decode.d7.loss_dice: 0.5712, decode.d8.loss_cls: 0.1165, decode.d8.loss_mask: 0.4151, decode.d8.loss_dice: 0.5693, loss: 13.0323 +2022-05-06 06:10:45,035 - mmseg - INFO - Iter [24250/40000] lr: 5.654e-07, eta: 3:49:54, time: 0.660, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1146, decode.loss_mask: 0.4335, decode.loss_dice: 0.5704, decode.d0.loss_cls: 1.6044, decode.d0.loss_mask: 0.4769, decode.d0.loss_dice: 0.6747, decode.d1.loss_cls: 0.2252, decode.d1.loss_mask: 0.4502, decode.d1.loss_dice: 0.6111, decode.d2.loss_cls: 0.1465, decode.d2.loss_mask: 0.4398, decode.d2.loss_dice: 0.5931, decode.d3.loss_cls: 0.1324, decode.d3.loss_mask: 0.4356, decode.d3.loss_dice: 0.5736, decode.d4.loss_cls: 0.1228, decode.d4.loss_mask: 0.4361, decode.d4.loss_dice: 0.5772, decode.d5.loss_cls: 0.1208, decode.d5.loss_mask: 0.4341, decode.d5.loss_dice: 0.5748, decode.d6.loss_cls: 0.1167, decode.d6.loss_mask: 0.4337, decode.d6.loss_dice: 0.5715, decode.d7.loss_cls: 0.1155, decode.d7.loss_mask: 0.4341, decode.d7.loss_dice: 0.5723, decode.d8.loss_cls: 0.1131, decode.d8.loss_mask: 0.4324, decode.d8.loss_dice: 0.5702, loss: 13.1074 +2022-05-06 06:11:21,488 - mmseg - INFO - Iter [24300/40000] lr: 5.636e-07, eta: 3:49:04, time: 0.729, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1329, decode.loss_mask: 0.4304, decode.loss_dice: 0.5805, decode.d0.loss_cls: 1.6481, decode.d0.loss_mask: 0.4670, decode.d0.loss_dice: 0.6740, decode.d1.loss_cls: 0.2569, decode.d1.loss_mask: 0.4447, decode.d1.loss_dice: 0.6059, decode.d2.loss_cls: 0.1838, decode.d2.loss_mask: 0.4368, decode.d2.loss_dice: 0.5897, decode.d3.loss_cls: 0.1447, decode.d3.loss_mask: 0.4349, decode.d3.loss_dice: 0.5817, decode.d4.loss_cls: 0.1468, decode.d4.loss_mask: 0.4334, decode.d4.loss_dice: 0.5810, decode.d5.loss_cls: 0.1446, decode.d5.loss_mask: 0.4298, decode.d5.loss_dice: 0.5762, decode.d6.loss_cls: 0.1396, decode.d6.loss_mask: 0.4309, decode.d6.loss_dice: 0.5805, decode.d7.loss_cls: 0.1382, decode.d7.loss_mask: 0.4297, decode.d7.loss_dice: 0.5798, decode.d8.loss_cls: 0.1332, decode.d8.loss_mask: 0.4326, decode.d8.loss_dice: 0.5834, loss: 13.3714 +2022-05-06 06:11:54,882 - mmseg - INFO - Iter [24350/40000] lr: 5.618e-07, eta: 3:48:12, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1266, decode.loss_mask: 0.4182, decode.loss_dice: 0.5698, decode.d0.loss_cls: 1.5695, decode.d0.loss_mask: 0.4641, decode.d0.loss_dice: 0.6644, decode.d1.loss_cls: 0.2302, decode.d1.loss_mask: 0.4316, decode.d1.loss_dice: 0.5942, decode.d2.loss_cls: 0.1559, decode.d2.loss_mask: 0.4241, decode.d2.loss_dice: 0.5746, decode.d3.loss_cls: 0.1347, decode.d3.loss_mask: 0.4232, decode.d3.loss_dice: 0.5671, decode.d4.loss_cls: 0.1286, decode.d4.loss_mask: 0.4199, decode.d4.loss_dice: 0.5675, decode.d5.loss_cls: 0.1326, decode.d5.loss_mask: 0.4199, decode.d5.loss_dice: 0.5675, decode.d6.loss_cls: 0.1248, decode.d6.loss_mask: 0.4178, decode.d6.loss_dice: 0.5666, decode.d7.loss_cls: 0.1229, decode.d7.loss_mask: 0.4185, decode.d7.loss_dice: 0.5636, decode.d8.loss_cls: 0.1245, decode.d8.loss_mask: 0.4192, decode.d8.loss_dice: 0.5662, loss: 12.9085 +2022-05-06 06:12:28,282 - mmseg - INFO - Iter [24400/40000] lr: 5.600e-07, eta: 3:47:21, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1301, decode.loss_mask: 0.4226, decode.loss_dice: 0.5752, decode.d0.loss_cls: 1.6345, decode.d0.loss_mask: 0.4669, decode.d0.loss_dice: 0.6849, decode.d1.loss_cls: 0.2402, decode.d1.loss_mask: 0.4385, decode.d1.loss_dice: 0.6108, decode.d2.loss_cls: 0.1757, decode.d2.loss_mask: 0.4265, decode.d2.loss_dice: 0.5882, decode.d3.loss_cls: 0.1456, decode.d3.loss_mask: 0.4236, decode.d3.loss_dice: 0.5806, decode.d4.loss_cls: 0.1442, decode.d4.loss_mask: 0.4208, decode.d4.loss_dice: 0.5776, decode.d5.loss_cls: 0.1375, decode.d5.loss_mask: 0.4217, decode.d5.loss_dice: 0.5731, decode.d6.loss_cls: 0.1320, decode.d6.loss_mask: 0.4222, decode.d6.loss_dice: 0.5704, decode.d7.loss_cls: 0.1289, decode.d7.loss_mask: 0.4226, decode.d7.loss_dice: 0.5728, decode.d8.loss_cls: 0.1297, decode.d8.loss_mask: 0.4208, decode.d8.loss_dice: 0.5712, loss: 13.1893 +2022-05-06 06:13:01,806 - mmseg - INFO - Iter [24450/40000] lr: 5.582e-07, eta: 3:46:29, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1173, decode.loss_mask: 0.4163, decode.loss_dice: 0.5866, decode.d0.loss_cls: 1.6494, decode.d0.loss_mask: 0.4581, decode.d0.loss_dice: 0.6891, decode.d1.loss_cls: 0.2393, decode.d1.loss_mask: 0.4298, decode.d1.loss_dice: 0.6260, decode.d2.loss_cls: 0.1583, decode.d2.loss_mask: 0.4204, decode.d2.loss_dice: 0.6021, decode.d3.loss_cls: 0.1370, decode.d3.loss_mask: 0.4197, decode.d3.loss_dice: 0.5921, decode.d4.loss_cls: 0.1274, decode.d4.loss_mask: 0.4179, decode.d4.loss_dice: 0.5951, decode.d5.loss_cls: 0.1231, decode.d5.loss_mask: 0.4168, decode.d5.loss_dice: 0.5930, decode.d6.loss_cls: 0.1206, decode.d6.loss_mask: 0.4160, decode.d6.loss_dice: 0.5866, decode.d7.loss_cls: 0.1156, decode.d7.loss_mask: 0.4158, decode.d7.loss_dice: 0.5891, decode.d8.loss_cls: 0.1212, decode.d8.loss_mask: 0.4158, decode.d8.loss_dice: 0.5873, loss: 13.1827 +2022-05-06 06:13:34,999 - mmseg - INFO - Iter [24500/40000] lr: 5.564e-07, eta: 3:45:38, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1270, decode.loss_mask: 0.4075, decode.loss_dice: 0.5520, decode.d0.loss_cls: 1.5756, decode.d0.loss_mask: 0.4442, decode.d0.loss_dice: 0.6450, decode.d1.loss_cls: 0.2341, decode.d1.loss_mask: 0.4202, decode.d1.loss_dice: 0.5865, decode.d2.loss_cls: 0.1656, decode.d2.loss_mask: 0.4119, decode.d2.loss_dice: 0.5707, decode.d3.loss_cls: 0.1408, decode.d3.loss_mask: 0.4085, decode.d3.loss_dice: 0.5595, decode.d4.loss_cls: 0.1311, decode.d4.loss_mask: 0.4091, decode.d4.loss_dice: 0.5535, decode.d5.loss_cls: 0.1310, decode.d5.loss_mask: 0.4067, decode.d5.loss_dice: 0.5549, decode.d6.loss_cls: 0.1236, decode.d6.loss_mask: 0.4065, decode.d6.loss_dice: 0.5530, decode.d7.loss_cls: 0.1225, decode.d7.loss_mask: 0.4068, decode.d7.loss_dice: 0.5530, decode.d8.loss_cls: 0.1222, decode.d8.loss_mask: 0.4056, decode.d8.loss_dice: 0.5521, loss: 12.6807 +2022-05-06 06:14:08,603 - mmseg - INFO - Iter [24550/40000] lr: 5.546e-07, eta: 3:44:46, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1353, decode.loss_mask: 0.4077, decode.loss_dice: 0.5952, decode.d0.loss_cls: 1.6610, decode.d0.loss_mask: 0.4480, decode.d0.loss_dice: 0.7023, decode.d1.loss_cls: 0.2729, decode.d1.loss_mask: 0.4253, decode.d1.loss_dice: 0.6376, decode.d2.loss_cls: 0.1794, decode.d2.loss_mask: 0.4155, decode.d2.loss_dice: 0.6137, decode.d3.loss_cls: 0.1470, decode.d3.loss_mask: 0.4136, decode.d3.loss_dice: 0.6047, decode.d4.loss_cls: 0.1416, decode.d4.loss_mask: 0.4128, decode.d4.loss_dice: 0.6013, decode.d5.loss_cls: 0.1400, decode.d5.loss_mask: 0.4120, decode.d5.loss_dice: 0.5994, decode.d6.loss_cls: 0.1319, decode.d6.loss_mask: 0.4096, decode.d6.loss_dice: 0.5941, decode.d7.loss_cls: 0.1345, decode.d7.loss_mask: 0.4083, decode.d7.loss_dice: 0.5972, decode.d8.loss_cls: 0.1347, decode.d8.loss_mask: 0.4084, decode.d8.loss_dice: 0.5966, loss: 13.3817 +2022-05-06 06:14:44,740 - mmseg - INFO - Iter [24600/40000] lr: 5.528e-07, eta: 3:43:57, time: 0.722, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1398, decode.loss_mask: 0.4346, decode.loss_dice: 0.5916, decode.d0.loss_cls: 1.6231, decode.d0.loss_mask: 0.4781, decode.d0.loss_dice: 0.6850, decode.d1.loss_cls: 0.2594, decode.d1.loss_mask: 0.4448, decode.d1.loss_dice: 0.6255, decode.d2.loss_cls: 0.1856, decode.d2.loss_mask: 0.4381, decode.d2.loss_dice: 0.6037, decode.d3.loss_cls: 0.1516, decode.d3.loss_mask: 0.4369, decode.d3.loss_dice: 0.5985, decode.d4.loss_cls: 0.1468, decode.d4.loss_mask: 0.4341, decode.d4.loss_dice: 0.5987, decode.d5.loss_cls: 0.1413, decode.d5.loss_mask: 0.4331, decode.d5.loss_dice: 0.5920, decode.d6.loss_cls: 0.1334, decode.d6.loss_mask: 0.4345, decode.d6.loss_dice: 0.5904, decode.d7.loss_cls: 0.1387, decode.d7.loss_mask: 0.4318, decode.d7.loss_dice: 0.5891, decode.d8.loss_cls: 0.1373, decode.d8.loss_mask: 0.4347, decode.d8.loss_dice: 0.5894, loss: 13.5214 +2022-05-06 06:15:18,389 - mmseg - INFO - Iter [24650/40000] lr: 5.510e-07, eta: 3:43:06, time: 0.674, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1141, decode.loss_mask: 0.4041, decode.loss_dice: 0.5687, decode.d0.loss_cls: 1.6247, decode.d0.loss_mask: 0.4443, decode.d0.loss_dice: 0.6700, decode.d1.loss_cls: 0.2369, decode.d1.loss_mask: 0.4174, decode.d1.loss_dice: 0.5992, decode.d2.loss_cls: 0.1606, decode.d2.loss_mask: 0.4072, decode.d2.loss_dice: 0.5793, decode.d3.loss_cls: 0.1388, decode.d3.loss_mask: 0.4046, decode.d3.loss_dice: 0.5669, decode.d4.loss_cls: 0.1386, decode.d4.loss_mask: 0.4029, decode.d4.loss_dice: 0.5695, decode.d5.loss_cls: 0.1257, decode.d5.loss_mask: 0.4021, decode.d5.loss_dice: 0.5675, decode.d6.loss_cls: 0.1208, decode.d6.loss_mask: 0.4018, decode.d6.loss_dice: 0.5640, decode.d7.loss_cls: 0.1181, decode.d7.loss_mask: 0.4034, decode.d7.loss_dice: 0.5696, decode.d8.loss_cls: 0.1193, decode.d8.loss_mask: 0.4046, decode.d8.loss_dice: 0.5695, loss: 12.8139 +2022-05-06 06:15:51,654 - mmseg - INFO - Iter [24700/40000] lr: 5.492e-07, eta: 3:42:15, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1145, decode.loss_mask: 0.4224, decode.loss_dice: 0.5779, decode.d0.loss_cls: 1.5894, decode.d0.loss_mask: 0.4615, decode.d0.loss_dice: 0.6757, decode.d1.loss_cls: 0.2424, decode.d1.loss_mask: 0.4374, decode.d1.loss_dice: 0.6104, decode.d2.loss_cls: 0.1598, decode.d2.loss_mask: 0.4269, decode.d2.loss_dice: 0.5915, decode.d3.loss_cls: 0.1273, decode.d3.loss_mask: 0.4254, decode.d3.loss_dice: 0.5809, decode.d4.loss_cls: 0.1191, decode.d4.loss_mask: 0.4256, decode.d4.loss_dice: 0.5856, decode.d5.loss_cls: 0.1242, decode.d5.loss_mask: 0.4240, decode.d5.loss_dice: 0.5841, decode.d6.loss_cls: 0.1156, decode.d6.loss_mask: 0.4230, decode.d6.loss_dice: 0.5830, decode.d7.loss_cls: 0.1174, decode.d7.loss_mask: 0.4218, decode.d7.loss_dice: 0.5799, decode.d8.loss_cls: 0.1106, decode.d8.loss_mask: 0.4240, decode.d8.loss_dice: 0.5807, loss: 13.0618 +2022-05-06 06:16:25,311 - mmseg - INFO - Iter [24750/40000] lr: 5.474e-07, eta: 3:41:24, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1306, decode.loss_mask: 0.4157, decode.loss_dice: 0.5811, decode.d0.loss_cls: 1.6062, decode.d0.loss_mask: 0.4547, decode.d0.loss_dice: 0.6780, decode.d1.loss_cls: 0.2463, decode.d1.loss_mask: 0.4291, decode.d1.loss_dice: 0.6063, decode.d2.loss_cls: 0.1754, decode.d2.loss_mask: 0.4202, decode.d2.loss_dice: 0.5864, decode.d3.loss_cls: 0.1421, decode.d3.loss_mask: 0.4166, decode.d3.loss_dice: 0.5802, decode.d4.loss_cls: 0.1421, decode.d4.loss_mask: 0.4154, decode.d4.loss_dice: 0.5798, decode.d5.loss_cls: 0.1389, decode.d5.loss_mask: 0.4136, decode.d5.loss_dice: 0.5769, decode.d6.loss_cls: 0.1347, decode.d6.loss_mask: 0.4154, decode.d6.loss_dice: 0.5762, decode.d7.loss_cls: 0.1315, decode.d7.loss_mask: 0.4153, decode.d7.loss_dice: 0.5766, decode.d8.loss_cls: 0.1293, decode.d8.loss_mask: 0.4148, decode.d8.loss_dice: 0.5783, loss: 13.1074 +2022-05-06 06:16:59,154 - mmseg - INFO - Iter [24800/40000] lr: 5.456e-07, eta: 3:40:33, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1140, decode.loss_mask: 0.4085, decode.loss_dice: 0.5617, decode.d0.loss_cls: 1.5966, decode.d0.loss_mask: 0.4518, decode.d0.loss_dice: 0.6580, decode.d1.loss_cls: 0.2044, decode.d1.loss_mask: 0.4239, decode.d1.loss_dice: 0.6051, decode.d2.loss_cls: 0.1575, decode.d2.loss_mask: 0.4114, decode.d2.loss_dice: 0.5783, decode.d3.loss_cls: 0.1366, decode.d3.loss_mask: 0.4107, decode.d3.loss_dice: 0.5697, decode.d4.loss_cls: 0.1232, decode.d4.loss_mask: 0.4098, decode.d4.loss_dice: 0.5714, decode.d5.loss_cls: 0.1168, decode.d5.loss_mask: 0.4080, decode.d5.loss_dice: 0.5662, decode.d6.loss_cls: 0.1142, decode.d6.loss_mask: 0.4095, decode.d6.loss_dice: 0.5618, decode.d7.loss_cls: 0.1122, decode.d7.loss_mask: 0.4098, decode.d7.loss_dice: 0.5636, decode.d8.loss_cls: 0.1120, decode.d8.loss_mask: 0.4089, decode.d8.loss_dice: 0.5629, loss: 12.7384 +2022-05-06 06:17:32,642 - mmseg - INFO - Iter [24850/40000] lr: 5.438e-07, eta: 3:39:43, time: 0.670, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1413, decode.loss_mask: 0.4053, decode.loss_dice: 0.5886, decode.d0.loss_cls: 1.6302, decode.d0.loss_mask: 0.4533, decode.d0.loss_dice: 0.7008, decode.d1.loss_cls: 0.2684, decode.d1.loss_mask: 0.4206, decode.d1.loss_dice: 0.6206, decode.d2.loss_cls: 0.1946, decode.d2.loss_mask: 0.4130, decode.d2.loss_dice: 0.5978, decode.d3.loss_cls: 0.1637, decode.d3.loss_mask: 0.4094, decode.d3.loss_dice: 0.5874, decode.d4.loss_cls: 0.1545, decode.d4.loss_mask: 0.4068, decode.d4.loss_dice: 0.5903, decode.d5.loss_cls: 0.1484, decode.d5.loss_mask: 0.4061, decode.d5.loss_dice: 0.5889, decode.d6.loss_cls: 0.1446, decode.d6.loss_mask: 0.4066, decode.d6.loss_dice: 0.5852, decode.d7.loss_cls: 0.1384, decode.d7.loss_mask: 0.4048, decode.d7.loss_dice: 0.5868, decode.d8.loss_cls: 0.1411, decode.d8.loss_mask: 0.4060, decode.d8.loss_dice: 0.5859, loss: 13.2894 +2022-05-06 06:18:06,425 - mmseg - INFO - Iter [24900/40000] lr: 5.420e-07, eta: 3:38:52, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1298, decode.loss_mask: 0.4261, decode.loss_dice: 0.5844, decode.d0.loss_cls: 1.6032, decode.d0.loss_mask: 0.4674, decode.d0.loss_dice: 0.6785, decode.d1.loss_cls: 0.2451, decode.d1.loss_mask: 0.4393, decode.d1.loss_dice: 0.6214, decode.d2.loss_cls: 0.1696, decode.d2.loss_mask: 0.4312, decode.d2.loss_dice: 0.6015, decode.d3.loss_cls: 0.1471, decode.d3.loss_mask: 0.4299, decode.d3.loss_dice: 0.5867, decode.d4.loss_cls: 0.1393, decode.d4.loss_mask: 0.4256, decode.d4.loss_dice: 0.5856, decode.d5.loss_cls: 0.1323, decode.d5.loss_mask: 0.4242, decode.d5.loss_dice: 0.5846, decode.d6.loss_cls: 0.1305, decode.d6.loss_mask: 0.4246, decode.d6.loss_dice: 0.5824, decode.d7.loss_cls: 0.1258, decode.d7.loss_mask: 0.4241, decode.d7.loss_dice: 0.5816, decode.d8.loss_cls: 0.1253, decode.d8.loss_mask: 0.4253, decode.d8.loss_dice: 0.5837, loss: 13.2559 +2022-05-06 06:18:42,951 - mmseg - INFO - Iter [24950/40000] lr: 5.403e-07, eta: 3:38:04, time: 0.730, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1202, decode.loss_mask: 0.4075, decode.loss_dice: 0.5670, decode.d0.loss_cls: 1.6067, decode.d0.loss_mask: 0.4501, decode.d0.loss_dice: 0.6692, decode.d1.loss_cls: 0.2415, decode.d1.loss_mask: 0.4189, decode.d1.loss_dice: 0.6011, decode.d2.loss_cls: 0.1694, decode.d2.loss_mask: 0.4093, decode.d2.loss_dice: 0.5808, decode.d3.loss_cls: 0.1416, decode.d3.loss_mask: 0.4086, decode.d3.loss_dice: 0.5704, decode.d4.loss_cls: 0.1241, decode.d4.loss_mask: 0.4092, decode.d4.loss_dice: 0.5677, decode.d5.loss_cls: 0.1266, decode.d5.loss_mask: 0.4071, decode.d5.loss_dice: 0.5682, decode.d6.loss_cls: 0.1200, decode.d6.loss_mask: 0.4081, decode.d6.loss_dice: 0.5650, decode.d7.loss_cls: 0.1195, decode.d7.loss_mask: 0.4067, decode.d7.loss_dice: 0.5698, decode.d8.loss_cls: 0.1235, decode.d8.loss_mask: 0.4061, decode.d8.loss_dice: 0.5640, loss: 12.8480 +2022-05-06 06:19:16,672 - mmseg - INFO - Saving checkpoint at 25000 iterations +2022-05-06 06:19:43,894 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:19:43,900 - mmseg - INFO - Iter [25000/40000] lr: 5.385e-07, eta: 3:37:32, time: 1.217, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1189, decode.loss_mask: 0.4130, decode.loss_dice: 0.5536, decode.d0.loss_cls: 1.6114, decode.d0.loss_mask: 0.4524, decode.d0.loss_dice: 0.6543, decode.d1.loss_cls: 0.2340, decode.d1.loss_mask: 0.4241, decode.d1.loss_dice: 0.5881, decode.d2.loss_cls: 0.1539, decode.d2.loss_mask: 0.4176, decode.d2.loss_dice: 0.5681, decode.d3.loss_cls: 0.1371, decode.d3.loss_mask: 0.4145, decode.d3.loss_dice: 0.5561, decode.d4.loss_cls: 0.1310, decode.d4.loss_mask: 0.4140, decode.d4.loss_dice: 0.5604, decode.d5.loss_cls: 0.1229, decode.d5.loss_mask: 0.4137, decode.d5.loss_dice: 0.5556, decode.d6.loss_cls: 0.1213, decode.d6.loss_mask: 0.4126, decode.d6.loss_dice: 0.5525, decode.d7.loss_cls: 0.1164, decode.d7.loss_mask: 0.4144, decode.d7.loss_dice: 0.5553, decode.d8.loss_cls: 0.1189, decode.d8.loss_mask: 0.4149, decode.d8.loss_dice: 0.5515, loss: 12.7524 +2022-05-06 06:20:19,208 - mmseg - INFO - Iter [25050/40000] lr: 5.367e-07, eta: 3:36:43, time: 0.708, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1137, decode.loss_mask: 0.4049, decode.loss_dice: 0.5530, decode.d0.loss_cls: 1.5909, decode.d0.loss_mask: 0.4468, decode.d0.loss_dice: 0.6516, decode.d1.loss_cls: 0.2223, decode.d1.loss_mask: 0.4156, decode.d1.loss_dice: 0.5842, decode.d2.loss_cls: 0.1553, decode.d2.loss_mask: 0.4084, decode.d2.loss_dice: 0.5685, decode.d3.loss_cls: 0.1274, decode.d3.loss_mask: 0.4061, decode.d3.loss_dice: 0.5579, decode.d4.loss_cls: 0.1206, decode.d4.loss_mask: 0.4051, decode.d4.loss_dice: 0.5557, decode.d5.loss_cls: 0.1236, decode.d5.loss_mask: 0.4056, decode.d5.loss_dice: 0.5551, decode.d6.loss_cls: 0.1181, decode.d6.loss_mask: 0.4066, decode.d6.loss_dice: 0.5513, decode.d7.loss_cls: 0.1144, decode.d7.loss_mask: 0.4041, decode.d7.loss_dice: 0.5489, decode.d8.loss_cls: 0.1167, decode.d8.loss_mask: 0.4048, decode.d8.loss_dice: 0.5539, loss: 12.5910 +2022-05-06 06:20:52,502 - mmseg - INFO - Iter [25100/40000] lr: 5.349e-07, eta: 3:35:53, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1162, decode.loss_mask: 0.4140, decode.loss_dice: 0.5692, decode.d0.loss_cls: 1.5927, decode.d0.loss_mask: 0.4541, decode.d0.loss_dice: 0.6606, decode.d1.loss_cls: 0.2377, decode.d1.loss_mask: 0.4279, decode.d1.loss_dice: 0.6046, decode.d2.loss_cls: 0.1562, decode.d2.loss_mask: 0.4189, decode.d2.loss_dice: 0.5834, decode.d3.loss_cls: 0.1278, decode.d3.loss_mask: 0.4159, decode.d3.loss_dice: 0.5712, decode.d4.loss_cls: 0.1207, decode.d4.loss_mask: 0.4144, decode.d4.loss_dice: 0.5754, decode.d5.loss_cls: 0.1198, decode.d5.loss_mask: 0.4143, decode.d5.loss_dice: 0.5713, decode.d6.loss_cls: 0.1159, decode.d6.loss_mask: 0.4132, decode.d6.loss_dice: 0.5672, decode.d7.loss_cls: 0.1141, decode.d7.loss_mask: 0.4143, decode.d7.loss_dice: 0.5686, decode.d8.loss_cls: 0.1123, decode.d8.loss_mask: 0.4137, decode.d8.loss_dice: 0.5702, loss: 12.8558 +2022-05-06 06:21:26,772 - mmseg - INFO - Iter [25150/40000] lr: 5.331e-07, eta: 3:35:03, time: 0.685, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1269, decode.loss_mask: 0.4162, decode.loss_dice: 0.5879, decode.d0.loss_cls: 1.6150, decode.d0.loss_mask: 0.4546, decode.d0.loss_dice: 0.6837, decode.d1.loss_cls: 0.2527, decode.d1.loss_mask: 0.4311, decode.d1.loss_dice: 0.6220, decode.d2.loss_cls: 0.1705, decode.d2.loss_mask: 0.4199, decode.d2.loss_dice: 0.6013, decode.d3.loss_cls: 0.1428, decode.d3.loss_mask: 0.4177, decode.d3.loss_dice: 0.5966, decode.d4.loss_cls: 0.1348, decode.d4.loss_mask: 0.4178, decode.d4.loss_dice: 0.5912, decode.d5.loss_cls: 0.1321, decode.d5.loss_mask: 0.4183, decode.d5.loss_dice: 0.5878, decode.d6.loss_cls: 0.1255, decode.d6.loss_mask: 0.4170, decode.d6.loss_dice: 0.5867, decode.d7.loss_cls: 0.1265, decode.d7.loss_mask: 0.4168, decode.d7.loss_dice: 0.5901, decode.d8.loss_cls: 0.1291, decode.d8.loss_mask: 0.4164, decode.d8.loss_dice: 0.5899, loss: 13.2190 +2022-05-06 06:22:00,710 - mmseg - INFO - Iter [25200/40000] lr: 5.313e-07, eta: 3:34:13, time: 0.679, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1199, decode.loss_mask: 0.4022, decode.loss_dice: 0.5701, decode.d0.loss_cls: 1.6049, decode.d0.loss_mask: 0.4429, decode.d0.loss_dice: 0.6796, decode.d1.loss_cls: 0.2347, decode.d1.loss_mask: 0.4137, decode.d1.loss_dice: 0.6030, decode.d2.loss_cls: 0.1690, decode.d2.loss_mask: 0.4059, decode.d2.loss_dice: 0.5857, decode.d3.loss_cls: 0.1353, decode.d3.loss_mask: 0.4029, decode.d3.loss_dice: 0.5771, decode.d4.loss_cls: 0.1316, decode.d4.loss_mask: 0.4053, decode.d4.loss_dice: 0.5786, decode.d5.loss_cls: 0.1260, decode.d5.loss_mask: 0.4022, decode.d5.loss_dice: 0.5768, decode.d6.loss_cls: 0.1170, decode.d6.loss_mask: 0.4033, decode.d6.loss_dice: 0.5749, decode.d7.loss_cls: 0.1164, decode.d7.loss_mask: 0.4015, decode.d7.loss_dice: 0.5763, decode.d8.loss_cls: 0.1198, decode.d8.loss_mask: 0.4017, decode.d8.loss_dice: 0.5720, loss: 12.8504 +2022-05-06 06:22:36,965 - mmseg - INFO - Iter [25250/40000] lr: 5.295e-07, eta: 3:33:24, time: 0.725, data_time: 0.061, memory: 53770, decode.loss_cls: 0.1141, decode.loss_mask: 0.4079, decode.loss_dice: 0.5715, decode.d0.loss_cls: 1.5822, decode.d0.loss_mask: 0.4507, decode.d0.loss_dice: 0.6762, decode.d1.loss_cls: 0.2199, decode.d1.loss_mask: 0.4233, decode.d1.loss_dice: 0.6171, decode.d2.loss_cls: 0.1590, decode.d2.loss_mask: 0.4161, decode.d2.loss_dice: 0.5840, decode.d3.loss_cls: 0.1279, decode.d3.loss_mask: 0.4126, decode.d3.loss_dice: 0.5764, decode.d4.loss_cls: 0.1240, decode.d4.loss_mask: 0.4100, decode.d4.loss_dice: 0.5750, decode.d5.loss_cls: 0.1220, decode.d5.loss_mask: 0.4091, decode.d5.loss_dice: 0.5717, decode.d6.loss_cls: 0.1150, decode.d6.loss_mask: 0.4073, decode.d6.loss_dice: 0.5671, decode.d7.loss_cls: 0.1128, decode.d7.loss_mask: 0.4068, decode.d7.loss_dice: 0.5701, decode.d8.loss_cls: 0.1109, decode.d8.loss_mask: 0.4072, decode.d8.loss_dice: 0.5741, loss: 12.8221 +2022-05-06 06:23:10,934 - mmseg - INFO - Iter [25300/40000] lr: 5.277e-07, eta: 3:32:34, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1222, decode.loss_mask: 0.4163, decode.loss_dice: 0.5722, decode.d0.loss_cls: 1.5984, decode.d0.loss_mask: 0.4611, decode.d0.loss_dice: 0.6705, decode.d1.loss_cls: 0.2345, decode.d1.loss_mask: 0.4336, decode.d1.loss_dice: 0.6053, decode.d2.loss_cls: 0.1719, decode.d2.loss_mask: 0.4254, decode.d2.loss_dice: 0.5868, decode.d3.loss_cls: 0.1418, decode.d3.loss_mask: 0.4200, decode.d3.loss_dice: 0.5779, decode.d4.loss_cls: 0.1323, decode.d4.loss_mask: 0.4197, decode.d4.loss_dice: 0.5785, decode.d5.loss_cls: 0.1296, decode.d5.loss_mask: 0.4190, decode.d5.loss_dice: 0.5822, decode.d6.loss_cls: 0.1243, decode.d6.loss_mask: 0.4182, decode.d6.loss_dice: 0.5765, decode.d7.loss_cls: 0.1238, decode.d7.loss_mask: 0.4173, decode.d7.loss_dice: 0.5748, decode.d8.loss_cls: 0.1210, decode.d8.loss_mask: 0.4164, decode.d8.loss_dice: 0.5750, loss: 13.0467 +2022-05-06 06:23:44,622 - mmseg - INFO - Iter [25350/40000] lr: 5.259e-07, eta: 3:31:44, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1274, decode.loss_mask: 0.4025, decode.loss_dice: 0.5742, decode.d0.loss_cls: 1.5846, decode.d0.loss_mask: 0.4374, decode.d0.loss_dice: 0.6673, decode.d1.loss_cls: 0.2548, decode.d1.loss_mask: 0.4176, decode.d1.loss_dice: 0.6125, decode.d2.loss_cls: 0.1804, decode.d2.loss_mask: 0.4080, decode.d2.loss_dice: 0.5890, decode.d3.loss_cls: 0.1461, decode.d3.loss_mask: 0.4047, decode.d3.loss_dice: 0.5794, decode.d4.loss_cls: 0.1410, decode.d4.loss_mask: 0.4053, decode.d4.loss_dice: 0.5790, decode.d5.loss_cls: 0.1327, decode.d5.loss_mask: 0.4035, decode.d5.loss_dice: 0.5781, decode.d6.loss_cls: 0.1331, decode.d6.loss_mask: 0.4004, decode.d6.loss_dice: 0.5752, decode.d7.loss_cls: 0.1262, decode.d7.loss_mask: 0.4015, decode.d7.loss_dice: 0.5785, decode.d8.loss_cls: 0.1309, decode.d8.loss_mask: 0.4025, decode.d8.loss_dice: 0.5710, loss: 12.9450 +2022-05-06 06:24:18,566 - mmseg - INFO - Iter [25400/40000] lr: 5.241e-07, eta: 3:30:54, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1272, decode.loss_mask: 0.4192, decode.loss_dice: 0.5656, decode.d0.loss_cls: 1.5938, decode.d0.loss_mask: 0.4576, decode.d0.loss_dice: 0.6666, decode.d1.loss_cls: 0.2451, decode.d1.loss_mask: 0.4309, decode.d1.loss_dice: 0.6062, decode.d2.loss_cls: 0.1742, decode.d2.loss_mask: 0.4238, decode.d2.loss_dice: 0.5869, decode.d3.loss_cls: 0.1480, decode.d3.loss_mask: 0.4205, decode.d3.loss_dice: 0.5788, decode.d4.loss_cls: 0.1387, decode.d4.loss_mask: 0.4179, decode.d4.loss_dice: 0.5739, decode.d5.loss_cls: 0.1348, decode.d5.loss_mask: 0.4193, decode.d5.loss_dice: 0.5705, decode.d6.loss_cls: 0.1223, decode.d6.loss_mask: 0.4238, decode.d6.loss_dice: 0.5673, decode.d7.loss_cls: 0.1284, decode.d7.loss_mask: 0.4196, decode.d7.loss_dice: 0.5691, decode.d8.loss_cls: 0.1252, decode.d8.loss_mask: 0.4198, decode.d8.loss_dice: 0.5686, loss: 13.0436 +2022-05-06 06:24:52,058 - mmseg - INFO - Iter [25450/40000] lr: 5.223e-07, eta: 3:30:04, time: 0.672, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1195, decode.loss_mask: 0.4088, decode.loss_dice: 0.5688, decode.d0.loss_cls: 1.5921, decode.d0.loss_mask: 0.4522, decode.d0.loss_dice: 0.6717, decode.d1.loss_cls: 0.2276, decode.d1.loss_mask: 0.4202, decode.d1.loss_dice: 0.6034, decode.d2.loss_cls: 0.1594, decode.d2.loss_mask: 0.4126, decode.d2.loss_dice: 0.5854, decode.d3.loss_cls: 0.1411, decode.d3.loss_mask: 0.4103, decode.d3.loss_dice: 0.5754, decode.d4.loss_cls: 0.1325, decode.d4.loss_mask: 0.4094, decode.d4.loss_dice: 0.5773, decode.d5.loss_cls: 0.1313, decode.d5.loss_mask: 0.4089, decode.d5.loss_dice: 0.5739, decode.d6.loss_cls: 0.1298, decode.d6.loss_mask: 0.4070, decode.d6.loss_dice: 0.5682, decode.d7.loss_cls: 0.1263, decode.d7.loss_mask: 0.4089, decode.d7.loss_dice: 0.5660, decode.d8.loss_cls: 0.1205, decode.d8.loss_mask: 0.4090, decode.d8.loss_dice: 0.5696, loss: 12.8871 +2022-05-06 06:25:25,966 - mmseg - INFO - Iter [25500/40000] lr: 5.205e-07, eta: 3:29:15, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1148, decode.loss_mask: 0.4155, decode.loss_dice: 0.5607, decode.d0.loss_cls: 1.5768, decode.d0.loss_mask: 0.4634, decode.d0.loss_dice: 0.6675, decode.d1.loss_cls: 0.2344, decode.d1.loss_mask: 0.4311, decode.d1.loss_dice: 0.6082, decode.d2.loss_cls: 0.1590, decode.d2.loss_mask: 0.4238, decode.d2.loss_dice: 0.5805, decode.d3.loss_cls: 0.1313, decode.d3.loss_mask: 0.4216, decode.d3.loss_dice: 0.5747, decode.d4.loss_cls: 0.1237, decode.d4.loss_mask: 0.4211, decode.d4.loss_dice: 0.5733, decode.d5.loss_cls: 0.1179, decode.d5.loss_mask: 0.4188, decode.d5.loss_dice: 0.5667, decode.d6.loss_cls: 0.1142, decode.d6.loss_mask: 0.4189, decode.d6.loss_dice: 0.5686, decode.d7.loss_cls: 0.1167, decode.d7.loss_mask: 0.4159, decode.d7.loss_dice: 0.5656, decode.d8.loss_cls: 0.1118, decode.d8.loss_mask: 0.4179, decode.d8.loss_dice: 0.5637, loss: 12.8780 +2022-05-06 06:26:02,117 - mmseg - INFO - Iter [25550/40000] lr: 5.187e-07, eta: 3:28:27, time: 0.724, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1195, decode.loss_mask: 0.4102, decode.loss_dice: 0.5741, decode.d0.loss_cls: 1.5992, decode.d0.loss_mask: 0.4533, decode.d0.loss_dice: 0.6783, decode.d1.loss_cls: 0.2322, decode.d1.loss_mask: 0.4249, decode.d1.loss_dice: 0.6099, decode.d2.loss_cls: 0.1625, decode.d2.loss_mask: 0.4173, decode.d2.loss_dice: 0.5948, decode.d3.loss_cls: 0.1338, decode.d3.loss_mask: 0.4170, decode.d3.loss_dice: 0.5834, decode.d4.loss_cls: 0.1302, decode.d4.loss_mask: 0.4132, decode.d4.loss_dice: 0.5780, decode.d5.loss_cls: 0.1276, decode.d5.loss_mask: 0.4120, decode.d5.loss_dice: 0.5794, decode.d6.loss_cls: 0.1218, decode.d6.loss_mask: 0.4129, decode.d6.loss_dice: 0.5723, decode.d7.loss_cls: 0.1240, decode.d7.loss_mask: 0.4106, decode.d7.loss_dice: 0.5740, decode.d8.loss_cls: 0.1242, decode.d8.loss_mask: 0.4129, decode.d8.loss_dice: 0.5726, loss: 12.9763 +2022-05-06 06:26:35,980 - mmseg - INFO - Iter [25600/40000] lr: 5.169e-07, eta: 3:27:37, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1208, decode.loss_mask: 0.4142, decode.loss_dice: 0.5657, decode.d0.loss_cls: 1.5872, decode.d0.loss_mask: 0.4499, decode.d0.loss_dice: 0.6631, decode.d1.loss_cls: 0.2435, decode.d1.loss_mask: 0.4240, decode.d1.loss_dice: 0.5991, decode.d2.loss_cls: 0.1686, decode.d2.loss_mask: 0.4226, decode.d2.loss_dice: 0.5846, decode.d3.loss_cls: 0.1409, decode.d3.loss_mask: 0.4177, decode.d3.loss_dice: 0.5717, decode.d4.loss_cls: 0.1349, decode.d4.loss_mask: 0.4182, decode.d4.loss_dice: 0.5746, decode.d5.loss_cls: 0.1275, decode.d5.loss_mask: 0.4156, decode.d5.loss_dice: 0.5666, decode.d6.loss_cls: 0.1229, decode.d6.loss_mask: 0.4156, decode.d6.loss_dice: 0.5644, decode.d7.loss_cls: 0.1221, decode.d7.loss_mask: 0.4122, decode.d7.loss_dice: 0.5677, decode.d8.loss_cls: 0.1191, decode.d8.loss_mask: 0.4171, decode.d8.loss_dice: 0.5660, loss: 12.9180 +2022-05-06 06:27:09,325 - mmseg - INFO - Iter [25650/40000] lr: 5.151e-07, eta: 3:26:47, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1286, decode.loss_mask: 0.3968, decode.loss_dice: 0.5612, decode.d0.loss_cls: 1.6165, decode.d0.loss_mask: 0.4343, decode.d0.loss_dice: 0.6679, decode.d1.loss_cls: 0.2616, decode.d1.loss_mask: 0.4084, decode.d1.loss_dice: 0.6006, decode.d2.loss_cls: 0.1753, decode.d2.loss_mask: 0.4003, decode.d2.loss_dice: 0.5750, decode.d3.loss_cls: 0.1442, decode.d3.loss_mask: 0.3973, decode.d3.loss_dice: 0.5717, decode.d4.loss_cls: 0.1426, decode.d4.loss_mask: 0.3966, decode.d4.loss_dice: 0.5673, decode.d5.loss_cls: 0.1443, decode.d5.loss_mask: 0.3954, decode.d5.loss_dice: 0.5630, decode.d6.loss_cls: 0.1319, decode.d6.loss_mask: 0.3956, decode.d6.loss_dice: 0.5631, decode.d7.loss_cls: 0.1276, decode.d7.loss_mask: 0.3961, decode.d7.loss_dice: 0.5618, decode.d8.loss_cls: 0.1300, decode.d8.loss_mask: 0.3962, decode.d8.loss_dice: 0.5598, loss: 12.8110 +2022-05-06 06:27:43,035 - mmseg - INFO - Iter [25700/40000] lr: 5.133e-07, eta: 3:25:58, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1157, decode.loss_mask: 0.4069, decode.loss_dice: 0.5579, decode.d0.loss_cls: 1.5795, decode.d0.loss_mask: 0.4461, decode.d0.loss_dice: 0.6541, decode.d1.loss_cls: 0.2226, decode.d1.loss_mask: 0.4169, decode.d1.loss_dice: 0.5915, decode.d2.loss_cls: 0.1599, decode.d2.loss_mask: 0.4107, decode.d2.loss_dice: 0.5698, decode.d3.loss_cls: 0.1391, decode.d3.loss_mask: 0.4086, decode.d3.loss_dice: 0.5633, decode.d4.loss_cls: 0.1250, decode.d4.loss_mask: 0.4080, decode.d4.loss_dice: 0.5674, decode.d5.loss_cls: 0.1235, decode.d5.loss_mask: 0.4056, decode.d5.loss_dice: 0.5568, decode.d6.loss_cls: 0.1183, decode.d6.loss_mask: 0.4053, decode.d6.loss_dice: 0.5591, decode.d7.loss_cls: 0.1279, decode.d7.loss_mask: 0.4052, decode.d7.loss_dice: 0.5615, decode.d8.loss_cls: 0.1198, decode.d8.loss_mask: 0.4044, decode.d8.loss_dice: 0.5564, loss: 12.6867 +2022-05-06 06:28:16,486 - mmseg - INFO - Iter [25750/40000] lr: 5.115e-07, eta: 3:25:08, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1242, decode.loss_mask: 0.3962, decode.loss_dice: 0.5720, decode.d0.loss_cls: 1.5605, decode.d0.loss_mask: 0.4309, decode.d0.loss_dice: 0.6632, decode.d1.loss_cls: 0.2465, decode.d1.loss_mask: 0.4100, decode.d1.loss_dice: 0.6062, decode.d2.loss_cls: 0.1807, decode.d2.loss_mask: 0.4037, decode.d2.loss_dice: 0.5878, decode.d3.loss_cls: 0.1442, decode.d3.loss_mask: 0.4004, decode.d3.loss_dice: 0.5793, decode.d4.loss_cls: 0.1313, decode.d4.loss_mask: 0.4008, decode.d4.loss_dice: 0.5801, decode.d5.loss_cls: 0.1288, decode.d5.loss_mask: 0.3979, decode.d5.loss_dice: 0.5778, decode.d6.loss_cls: 0.1280, decode.d6.loss_mask: 0.3962, decode.d6.loss_dice: 0.5669, decode.d7.loss_cls: 0.1296, decode.d7.loss_mask: 0.3952, decode.d7.loss_dice: 0.5666, decode.d8.loss_cls: 0.1252, decode.d8.loss_mask: 0.3955, decode.d8.loss_dice: 0.5702, loss: 12.7963 +2022-05-06 06:28:50,102 - mmseg - INFO - Iter [25800/40000] lr: 5.097e-07, eta: 3:24:19, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1137, decode.loss_mask: 0.4125, decode.loss_dice: 0.5602, decode.d0.loss_cls: 1.5614, decode.d0.loss_mask: 0.4610, decode.d0.loss_dice: 0.6647, decode.d1.loss_cls: 0.2384, decode.d1.loss_mask: 0.4284, decode.d1.loss_dice: 0.5964, decode.d2.loss_cls: 0.1547, decode.d2.loss_mask: 0.4211, decode.d2.loss_dice: 0.5689, decode.d3.loss_cls: 0.1287, decode.d3.loss_mask: 0.4162, decode.d3.loss_dice: 0.5668, decode.d4.loss_cls: 0.1236, decode.d4.loss_mask: 0.4174, decode.d4.loss_dice: 0.5631, decode.d5.loss_cls: 0.1131, decode.d5.loss_mask: 0.4176, decode.d5.loss_dice: 0.5619, decode.d6.loss_cls: 0.1115, decode.d6.loss_mask: 0.4140, decode.d6.loss_dice: 0.5550, decode.d7.loss_cls: 0.1127, decode.d7.loss_mask: 0.4115, decode.d7.loss_dice: 0.5553, decode.d8.loss_cls: 0.1175, decode.d8.loss_mask: 0.4124, decode.d8.loss_dice: 0.5573, loss: 12.7372 +2022-05-06 06:29:26,358 - mmseg - INFO - Iter [25850/40000] lr: 5.079e-07, eta: 3:23:31, time: 0.725, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1093, decode.loss_mask: 0.4005, decode.loss_dice: 0.5609, decode.d0.loss_cls: 1.5583, decode.d0.loss_mask: 0.4386, decode.d0.loss_dice: 0.6513, decode.d1.loss_cls: 0.2131, decode.d1.loss_mask: 0.4118, decode.d1.loss_dice: 0.5913, decode.d2.loss_cls: 0.1543, decode.d2.loss_mask: 0.4062, decode.d2.loss_dice: 0.5702, decode.d3.loss_cls: 0.1286, decode.d3.loss_mask: 0.4009, decode.d3.loss_dice: 0.5632, decode.d4.loss_cls: 0.1183, decode.d4.loss_mask: 0.4005, decode.d4.loss_dice: 0.5618, decode.d5.loss_cls: 0.1114, decode.d5.loss_mask: 0.4014, decode.d5.loss_dice: 0.5619, decode.d6.loss_cls: 0.1115, decode.d6.loss_mask: 0.3998, decode.d6.loss_dice: 0.5574, decode.d7.loss_cls: 0.1051, decode.d7.loss_mask: 0.4011, decode.d7.loss_dice: 0.5558, decode.d8.loss_cls: 0.1072, decode.d8.loss_mask: 0.4007, decode.d8.loss_dice: 0.5561, loss: 12.5084 +2022-05-06 06:30:00,333 - mmseg - INFO - Iter [25900/40000] lr: 5.062e-07, eta: 3:22:42, time: 0.679, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1138, decode.loss_mask: 0.3990, decode.loss_dice: 0.5594, decode.d0.loss_cls: 1.5692, decode.d0.loss_mask: 0.4399, decode.d0.loss_dice: 0.6571, decode.d1.loss_cls: 0.2368, decode.d1.loss_mask: 0.4127, decode.d1.loss_dice: 0.5977, decode.d2.loss_cls: 0.1605, decode.d2.loss_mask: 0.4049, decode.d2.loss_dice: 0.5822, decode.d3.loss_cls: 0.1321, decode.d3.loss_mask: 0.4020, decode.d3.loss_dice: 0.5641, decode.d4.loss_cls: 0.1250, decode.d4.loss_mask: 0.4021, decode.d4.loss_dice: 0.5679, decode.d5.loss_cls: 0.1140, decode.d5.loss_mask: 0.4007, decode.d5.loss_dice: 0.5672, decode.d6.loss_cls: 0.1167, decode.d6.loss_mask: 0.3998, decode.d6.loss_dice: 0.5613, decode.d7.loss_cls: 0.1119, decode.d7.loss_mask: 0.4006, decode.d7.loss_dice: 0.5661, decode.d8.loss_cls: 0.1126, decode.d8.loss_mask: 0.3995, decode.d8.loss_dice: 0.5636, loss: 12.6403 +2022-05-06 06:30:33,871 - mmseg - INFO - Iter [25950/40000] lr: 5.044e-07, eta: 3:21:53, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1294, decode.loss_mask: 0.4097, decode.loss_dice: 0.5737, decode.d0.loss_cls: 1.5796, decode.d0.loss_mask: 0.4467, decode.d0.loss_dice: 0.6691, decode.d1.loss_cls: 0.2416, decode.d1.loss_mask: 0.4251, decode.d1.loss_dice: 0.6067, decode.d2.loss_cls: 0.1743, decode.d2.loss_mask: 0.4137, decode.d2.loss_dice: 0.5885, decode.d3.loss_cls: 0.1457, decode.d3.loss_mask: 0.4106, decode.d3.loss_dice: 0.5783, decode.d4.loss_cls: 0.1402, decode.d4.loss_mask: 0.4086, decode.d4.loss_dice: 0.5802, decode.d5.loss_cls: 0.1329, decode.d5.loss_mask: 0.4093, decode.d5.loss_dice: 0.5764, decode.d6.loss_cls: 0.1284, decode.d6.loss_mask: 0.4075, decode.d6.loss_dice: 0.5721, decode.d7.loss_cls: 0.1305, decode.d7.loss_mask: 0.4090, decode.d7.loss_dice: 0.5726, decode.d8.loss_cls: 0.1274, decode.d8.loss_mask: 0.4093, decode.d8.loss_dice: 0.5750, loss: 12.9720 +2022-05-06 06:31:07,191 - mmseg - INFO - Saving checkpoint at 26000 iterations +2022-05-06 06:31:31,952 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:31:31,959 - mmseg - INFO - Iter [26000/40000] lr: 5.026e-07, eta: 3:21:19, time: 1.159, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1189, decode.loss_mask: 0.4199, decode.loss_dice: 0.5720, decode.d0.loss_cls: 1.5547, decode.d0.loss_mask: 0.4573, decode.d0.loss_dice: 0.6637, decode.d1.loss_cls: 0.2215, decode.d1.loss_mask: 0.4294, decode.d1.loss_dice: 0.6057, decode.d2.loss_cls: 0.1618, decode.d2.loss_mask: 0.4225, decode.d2.loss_dice: 0.5820, decode.d3.loss_cls: 0.1393, decode.d3.loss_mask: 0.4214, decode.d3.loss_dice: 0.5709, decode.d4.loss_cls: 0.1304, decode.d4.loss_mask: 0.4219, decode.d4.loss_dice: 0.5718, decode.d5.loss_cls: 0.1355, decode.d5.loss_mask: 0.4182, decode.d5.loss_dice: 0.5729, decode.d6.loss_cls: 0.1228, decode.d6.loss_mask: 0.4180, decode.d6.loss_dice: 0.5668, decode.d7.loss_cls: 0.1233, decode.d7.loss_mask: 0.4174, decode.d7.loss_dice: 0.5709, decode.d8.loss_cls: 0.1239, decode.d8.loss_mask: 0.4172, decode.d8.loss_dice: 0.5674, loss: 12.9195 +2022-05-06 06:32:06,225 - mmseg - INFO - Iter [26050/40000] lr: 5.008e-07, eta: 3:20:30, time: 0.688, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1281, decode.loss_mask: 0.4078, decode.loss_dice: 0.5853, decode.d0.loss_cls: 1.6075, decode.d0.loss_mask: 0.4490, decode.d0.loss_dice: 0.6854, decode.d1.loss_cls: 0.2497, decode.d1.loss_mask: 0.4216, decode.d1.loss_dice: 0.6238, decode.d2.loss_cls: 0.1777, decode.d2.loss_mask: 0.4125, decode.d2.loss_dice: 0.6024, decode.d3.loss_cls: 0.1482, decode.d3.loss_mask: 0.4113, decode.d3.loss_dice: 0.5909, decode.d4.loss_cls: 0.1398, decode.d4.loss_mask: 0.4088, decode.d4.loss_dice: 0.5894, decode.d5.loss_cls: 0.1344, decode.d5.loss_mask: 0.4078, decode.d5.loss_dice: 0.5865, decode.d6.loss_cls: 0.1298, decode.d6.loss_mask: 0.4072, decode.d6.loss_dice: 0.5807, decode.d7.loss_cls: 0.1271, decode.d7.loss_mask: 0.4065, decode.d7.loss_dice: 0.5833, decode.d8.loss_cls: 0.1299, decode.d8.loss_mask: 0.4093, decode.d8.loss_dice: 0.5851, loss: 13.1265 +2022-05-06 06:32:40,244 - mmseg - INFO - Iter [26100/40000] lr: 4.990e-07, eta: 3:19:42, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1231, decode.loss_mask: 0.4166, decode.loss_dice: 0.5583, decode.d0.loss_cls: 1.5830, decode.d0.loss_mask: 0.4630, decode.d0.loss_dice: 0.6587, decode.d1.loss_cls: 0.2393, decode.d1.loss_mask: 0.4343, decode.d1.loss_dice: 0.5976, decode.d2.loss_cls: 0.1714, decode.d2.loss_mask: 0.4248, decode.d2.loss_dice: 0.5756, decode.d3.loss_cls: 0.1457, decode.d3.loss_mask: 0.4198, decode.d3.loss_dice: 0.5625, decode.d4.loss_cls: 0.1318, decode.d4.loss_mask: 0.4189, decode.d4.loss_dice: 0.5651, decode.d5.loss_cls: 0.1286, decode.d5.loss_mask: 0.4166, decode.d5.loss_dice: 0.5630, decode.d6.loss_cls: 0.1270, decode.d6.loss_mask: 0.4154, decode.d6.loss_dice: 0.5566, decode.d7.loss_cls: 0.1271, decode.d7.loss_mask: 0.4171, decode.d7.loss_dice: 0.5573, decode.d8.loss_cls: 0.1162, decode.d8.loss_mask: 0.4180, decode.d8.loss_dice: 0.5637, loss: 12.8962 +2022-05-06 06:33:13,877 - mmseg - INFO - Iter [26150/40000] lr: 4.972e-07, eta: 3:18:53, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1193, decode.loss_mask: 0.4098, decode.loss_dice: 0.5887, decode.d0.loss_cls: 1.6159, decode.d0.loss_mask: 0.4580, decode.d0.loss_dice: 0.7079, decode.d1.loss_cls: 0.2391, decode.d1.loss_mask: 0.4250, decode.d1.loss_dice: 0.6280, decode.d2.loss_cls: 0.1644, decode.d2.loss_mask: 0.4186, decode.d2.loss_dice: 0.6042, decode.d3.loss_cls: 0.1351, decode.d3.loss_mask: 0.4126, decode.d3.loss_dice: 0.5942, decode.d4.loss_cls: 0.1320, decode.d4.loss_mask: 0.4118, decode.d4.loss_dice: 0.5913, decode.d5.loss_cls: 0.1306, decode.d5.loss_mask: 0.4114, decode.d5.loss_dice: 0.5895, decode.d6.loss_cls: 0.1219, decode.d6.loss_mask: 0.4104, decode.d6.loss_dice: 0.5901, decode.d7.loss_cls: 0.1244, decode.d7.loss_mask: 0.4097, decode.d7.loss_dice: 0.5860, decode.d8.loss_cls: 0.1168, decode.d8.loss_mask: 0.4100, decode.d8.loss_dice: 0.5901, loss: 13.1471 +2022-05-06 06:33:50,092 - mmseg - INFO - Iter [26200/40000] lr: 4.954e-07, eta: 3:18:05, time: 0.724, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1156, decode.loss_mask: 0.4090, decode.loss_dice: 0.5713, decode.d0.loss_cls: 1.5644, decode.d0.loss_mask: 0.4465, decode.d0.loss_dice: 0.6709, decode.d1.loss_cls: 0.2220, decode.d1.loss_mask: 0.4232, decode.d1.loss_dice: 0.6047, decode.d2.loss_cls: 0.1520, decode.d2.loss_mask: 0.4142, decode.d2.loss_dice: 0.5902, decode.d3.loss_cls: 0.1280, decode.d3.loss_mask: 0.4115, decode.d3.loss_dice: 0.5807, decode.d4.loss_cls: 0.1190, decode.d4.loss_mask: 0.4099, decode.d4.loss_dice: 0.5798, decode.d5.loss_cls: 0.1132, decode.d5.loss_mask: 0.4097, decode.d5.loss_dice: 0.5782, decode.d6.loss_cls: 0.1142, decode.d6.loss_mask: 0.4076, decode.d6.loss_dice: 0.5703, decode.d7.loss_cls: 0.1091, decode.d7.loss_mask: 0.4085, decode.d7.loss_dice: 0.5720, decode.d8.loss_cls: 0.1091, decode.d8.loss_mask: 0.4094, decode.d8.loss_dice: 0.5713, loss: 12.7855 +2022-05-06 06:34:23,389 - mmseg - INFO - Iter [26250/40000] lr: 4.936e-07, eta: 3:17:16, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1323, decode.loss_mask: 0.4132, decode.loss_dice: 0.5572, decode.d0.loss_cls: 1.5971, decode.d0.loss_mask: 0.4580, decode.d0.loss_dice: 0.6660, decode.d1.loss_cls: 0.2385, decode.d1.loss_mask: 0.4264, decode.d1.loss_dice: 0.5990, decode.d2.loss_cls: 0.1793, decode.d2.loss_mask: 0.4165, decode.d2.loss_dice: 0.5770, decode.d3.loss_cls: 0.1510, decode.d3.loss_mask: 0.4141, decode.d3.loss_dice: 0.5714, decode.d4.loss_cls: 0.1438, decode.d4.loss_mask: 0.4130, decode.d4.loss_dice: 0.5695, decode.d5.loss_cls: 0.1353, decode.d5.loss_mask: 0.4128, decode.d5.loss_dice: 0.5658, decode.d6.loss_cls: 0.1283, decode.d6.loss_mask: 0.4132, decode.d6.loss_dice: 0.5600, decode.d7.loss_cls: 0.1345, decode.d7.loss_mask: 0.4120, decode.d7.loss_dice: 0.5617, decode.d8.loss_cls: 0.1276, decode.d8.loss_mask: 0.4126, decode.d8.loss_dice: 0.5629, loss: 12.9499 +2022-05-06 06:34:57,195 - mmseg - INFO - Iter [26300/40000] lr: 4.918e-07, eta: 3:16:27, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1193, decode.loss_mask: 0.3977, decode.loss_dice: 0.5560, decode.d0.loss_cls: 1.5684, decode.d0.loss_mask: 0.4388, decode.d0.loss_dice: 0.6604, decode.d1.loss_cls: 0.2288, decode.d1.loss_mask: 0.4126, decode.d1.loss_dice: 0.6016, decode.d2.loss_cls: 0.1520, decode.d2.loss_mask: 0.4032, decode.d2.loss_dice: 0.5730, decode.d3.loss_cls: 0.1350, decode.d3.loss_mask: 0.4014, decode.d3.loss_dice: 0.5654, decode.d4.loss_cls: 0.1316, decode.d4.loss_mask: 0.3988, decode.d4.loss_dice: 0.5649, decode.d5.loss_cls: 0.1195, decode.d5.loss_mask: 0.3982, decode.d5.loss_dice: 0.5642, decode.d6.loss_cls: 0.1167, decode.d6.loss_mask: 0.3976, decode.d6.loss_dice: 0.5578, decode.d7.loss_cls: 0.1139, decode.d7.loss_mask: 0.3967, decode.d7.loss_dice: 0.5559, decode.d8.loss_cls: 0.1183, decode.d8.loss_mask: 0.3963, decode.d8.loss_dice: 0.5592, loss: 12.6032 +2022-05-06 06:35:30,992 - mmseg - INFO - Iter [26350/40000] lr: 4.900e-07, eta: 3:15:39, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1198, decode.loss_mask: 0.4076, decode.loss_dice: 0.5790, decode.d0.loss_cls: 1.6024, decode.d0.loss_mask: 0.4504, decode.d0.loss_dice: 0.6688, decode.d1.loss_cls: 0.2435, decode.d1.loss_mask: 0.4225, decode.d1.loss_dice: 0.6147, decode.d2.loss_cls: 0.1627, decode.d2.loss_mask: 0.4157, decode.d2.loss_dice: 0.5905, decode.d3.loss_cls: 0.1462, decode.d3.loss_mask: 0.4103, decode.d3.loss_dice: 0.5869, decode.d4.loss_cls: 0.1306, decode.d4.loss_mask: 0.4113, decode.d4.loss_dice: 0.5930, decode.d5.loss_cls: 0.1309, decode.d5.loss_mask: 0.4097, decode.d5.loss_dice: 0.5844, decode.d6.loss_cls: 0.1242, decode.d6.loss_mask: 0.4107, decode.d6.loss_dice: 0.5788, decode.d7.loss_cls: 0.1237, decode.d7.loss_mask: 0.4078, decode.d7.loss_dice: 0.5798, decode.d8.loss_cls: 0.1205, decode.d8.loss_mask: 0.4063, decode.d8.loss_dice: 0.5806, loss: 13.0132 +2022-05-06 06:36:04,453 - mmseg - INFO - Iter [26400/40000] lr: 4.882e-07, eta: 3:14:50, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1157, decode.loss_mask: 0.4176, decode.loss_dice: 0.5620, decode.d0.loss_cls: 1.5442, decode.d0.loss_mask: 0.4588, decode.d0.loss_dice: 0.6605, decode.d1.loss_cls: 0.2100, decode.d1.loss_mask: 0.4304, decode.d1.loss_dice: 0.5941, decode.d2.loss_cls: 0.1528, decode.d2.loss_mask: 0.4212, decode.d2.loss_dice: 0.5758, decode.d3.loss_cls: 0.1298, decode.d3.loss_mask: 0.4175, decode.d3.loss_dice: 0.5693, decode.d4.loss_cls: 0.1185, decode.d4.loss_mask: 0.4172, decode.d4.loss_dice: 0.5652, decode.d5.loss_cls: 0.1210, decode.d5.loss_mask: 0.4170, decode.d5.loss_dice: 0.5626, decode.d6.loss_cls: 0.1133, decode.d6.loss_mask: 0.4168, decode.d6.loss_dice: 0.5589, decode.d7.loss_cls: 0.1130, decode.d7.loss_mask: 0.4177, decode.d7.loss_dice: 0.5627, decode.d8.loss_cls: 0.1111, decode.d8.loss_mask: 0.4194, decode.d8.loss_dice: 0.5653, loss: 12.7396 +2022-05-06 06:36:38,565 - mmseg - INFO - Iter [26450/40000] lr: 4.864e-07, eta: 3:14:02, time: 0.682, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1073, decode.loss_mask: 0.4020, decode.loss_dice: 0.5771, decode.d0.loss_cls: 1.6092, decode.d0.loss_mask: 0.4449, decode.d0.loss_dice: 0.6830, decode.d1.loss_cls: 0.2550, decode.d1.loss_mask: 0.4173, decode.d1.loss_dice: 0.6182, decode.d2.loss_cls: 0.1681, decode.d2.loss_mask: 0.4087, decode.d2.loss_dice: 0.5915, decode.d3.loss_cls: 0.1296, decode.d3.loss_mask: 0.4069, decode.d3.loss_dice: 0.5771, decode.d4.loss_cls: 0.1274, decode.d4.loss_mask: 0.4069, decode.d4.loss_dice: 0.5781, decode.d5.loss_cls: 0.1201, decode.d5.loss_mask: 0.4051, decode.d5.loss_dice: 0.5781, decode.d6.loss_cls: 0.1147, decode.d6.loss_mask: 0.4041, decode.d6.loss_dice: 0.5778, decode.d7.loss_cls: 0.1171, decode.d7.loss_mask: 0.4020, decode.d7.loss_dice: 0.5775, decode.d8.loss_cls: 0.1153, decode.d8.loss_mask: 0.4011, decode.d8.loss_dice: 0.5733, loss: 12.8946 +2022-05-06 06:37:15,038 - mmseg - INFO - Iter [26500/40000] lr: 4.846e-07, eta: 3:13:15, time: 0.729, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1051, decode.loss_mask: 0.4031, decode.loss_dice: 0.5513, decode.d0.loss_cls: 1.5210, decode.d0.loss_mask: 0.4419, decode.d0.loss_dice: 0.6457, decode.d1.loss_cls: 0.2133, decode.d1.loss_mask: 0.4119, decode.d1.loss_dice: 0.5774, decode.d2.loss_cls: 0.1460, decode.d2.loss_mask: 0.4057, decode.d2.loss_dice: 0.5627, decode.d3.loss_cls: 0.1266, decode.d3.loss_mask: 0.4062, decode.d3.loss_dice: 0.5540, decode.d4.loss_cls: 0.1222, decode.d4.loss_mask: 0.4026, decode.d4.loss_dice: 0.5546, decode.d5.loss_cls: 0.1075, decode.d5.loss_mask: 0.4011, decode.d5.loss_dice: 0.5505, decode.d6.loss_cls: 0.1085, decode.d6.loss_mask: 0.4024, decode.d6.loss_dice: 0.5505, decode.d7.loss_cls: 0.1132, decode.d7.loss_mask: 0.4013, decode.d7.loss_dice: 0.5475, decode.d8.loss_cls: 0.1054, decode.d8.loss_mask: 0.4020, decode.d8.loss_dice: 0.5502, loss: 12.3917 +2022-05-06 06:37:48,284 - mmseg - INFO - Iter [26550/40000] lr: 4.828e-07, eta: 3:12:26, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0957, decode.loss_mask: 0.3882, decode.loss_dice: 0.5428, decode.d0.loss_cls: 1.5342, decode.d0.loss_mask: 0.4274, decode.d0.loss_dice: 0.6421, decode.d1.loss_cls: 0.2064, decode.d1.loss_mask: 0.3996, decode.d1.loss_dice: 0.5831, decode.d2.loss_cls: 0.1394, decode.d2.loss_mask: 0.3923, decode.d2.loss_dice: 0.5609, decode.d3.loss_cls: 0.1189, decode.d3.loss_mask: 0.3896, decode.d3.loss_dice: 0.5478, decode.d4.loss_cls: 0.1120, decode.d4.loss_mask: 0.3893, decode.d4.loss_dice: 0.5481, decode.d5.loss_cls: 0.1041, decode.d5.loss_mask: 0.3883, decode.d5.loss_dice: 0.5453, decode.d6.loss_cls: 0.0953, decode.d6.loss_mask: 0.3864, decode.d6.loss_dice: 0.5429, decode.d7.loss_cls: 0.0956, decode.d7.loss_mask: 0.3869, decode.d7.loss_dice: 0.5431, decode.d8.loss_cls: 0.0995, decode.d8.loss_mask: 0.3874, decode.d8.loss_dice: 0.5439, loss: 12.1365 +2022-05-06 06:38:22,237 - mmseg - INFO - Iter [26600/40000] lr: 4.810e-07, eta: 3:11:38, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1160, decode.loss_mask: 0.3886, decode.loss_dice: 0.5777, decode.d0.loss_cls: 1.6010, decode.d0.loss_mask: 0.4326, decode.d0.loss_dice: 0.6857, decode.d1.loss_cls: 0.2436, decode.d1.loss_mask: 0.4067, decode.d1.loss_dice: 0.6222, decode.d2.loss_cls: 0.1631, decode.d2.loss_mask: 0.3947, decode.d2.loss_dice: 0.6028, decode.d3.loss_cls: 0.1366, decode.d3.loss_mask: 0.3919, decode.d3.loss_dice: 0.5873, decode.d4.loss_cls: 0.1239, decode.d4.loss_mask: 0.3912, decode.d4.loss_dice: 0.5910, decode.d5.loss_cls: 0.1182, decode.d5.loss_mask: 0.3899, decode.d5.loss_dice: 0.5859, decode.d6.loss_cls: 0.1194, decode.d6.loss_mask: 0.3878, decode.d6.loss_dice: 0.5802, decode.d7.loss_cls: 0.1117, decode.d7.loss_mask: 0.3889, decode.d7.loss_dice: 0.5777, decode.d8.loss_cls: 0.1133, decode.d8.loss_mask: 0.3880, decode.d8.loss_dice: 0.5791, loss: 12.7963 +2022-05-06 06:38:55,450 - mmseg - INFO - Iter [26650/40000] lr: 4.792e-07, eta: 3:10:49, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1214, decode.loss_mask: 0.3902, decode.loss_dice: 0.5571, decode.d0.loss_cls: 1.6003, decode.d0.loss_mask: 0.4338, decode.d0.loss_dice: 0.6553, decode.d1.loss_cls: 0.2357, decode.d1.loss_mask: 0.4094, decode.d1.loss_dice: 0.5940, decode.d2.loss_cls: 0.1609, decode.d2.loss_mask: 0.3968, decode.d2.loss_dice: 0.5708, decode.d3.loss_cls: 0.1347, decode.d3.loss_mask: 0.3941, decode.d3.loss_dice: 0.5581, decode.d4.loss_cls: 0.1323, decode.d4.loss_mask: 0.3939, decode.d4.loss_dice: 0.5595, decode.d5.loss_cls: 0.1233, decode.d5.loss_mask: 0.3917, decode.d5.loss_dice: 0.5649, decode.d6.loss_cls: 0.1245, decode.d6.loss_mask: 0.3924, decode.d6.loss_dice: 0.5610, decode.d7.loss_cls: 0.1234, decode.d7.loss_mask: 0.3904, decode.d7.loss_dice: 0.5609, decode.d8.loss_cls: 0.1203, decode.d8.loss_mask: 0.3899, decode.d8.loss_dice: 0.5586, loss: 12.5997 +2022-05-06 06:39:29,116 - mmseg - INFO - Iter [26700/40000] lr: 4.774e-07, eta: 3:10:01, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0976, decode.loss_mask: 0.4049, decode.loss_dice: 0.5694, decode.d0.loss_cls: 1.5508, decode.d0.loss_mask: 0.4431, decode.d0.loss_dice: 0.6659, decode.d1.loss_cls: 0.2231, decode.d1.loss_mask: 0.4187, decode.d1.loss_dice: 0.6021, decode.d2.loss_cls: 0.1553, decode.d2.loss_mask: 0.4094, decode.d2.loss_dice: 0.5856, decode.d3.loss_cls: 0.1209, decode.d3.loss_mask: 0.4065, decode.d3.loss_dice: 0.5738, decode.d4.loss_cls: 0.1134, decode.d4.loss_mask: 0.4065, decode.d4.loss_dice: 0.5772, decode.d5.loss_cls: 0.1024, decode.d5.loss_mask: 0.4042, decode.d5.loss_dice: 0.5748, decode.d6.loss_cls: 0.1016, decode.d6.loss_mask: 0.4037, decode.d6.loss_dice: 0.5717, decode.d7.loss_cls: 0.0998, decode.d7.loss_mask: 0.4037, decode.d7.loss_dice: 0.5710, decode.d8.loss_cls: 0.1064, decode.d8.loss_mask: 0.4014, decode.d8.loss_dice: 0.5690, loss: 12.6336 +2022-05-06 06:40:02,651 - mmseg - INFO - Iter [26750/40000] lr: 4.756e-07, eta: 3:09:13, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1140, decode.loss_mask: 0.3918, decode.loss_dice: 0.5679, decode.d0.loss_cls: 1.5604, decode.d0.loss_mask: 0.4363, decode.d0.loss_dice: 0.6700, decode.d1.loss_cls: 0.2351, decode.d1.loss_mask: 0.4069, decode.d1.loss_dice: 0.6036, decode.d2.loss_cls: 0.1635, decode.d2.loss_mask: 0.3987, decode.d2.loss_dice: 0.5835, decode.d3.loss_cls: 0.1350, decode.d3.loss_mask: 0.3957, decode.d3.loss_dice: 0.5660, decode.d4.loss_cls: 0.1302, decode.d4.loss_mask: 0.3943, decode.d4.loss_dice: 0.5741, decode.d5.loss_cls: 0.1262, decode.d5.loss_mask: 0.3929, decode.d5.loss_dice: 0.5663, decode.d6.loss_cls: 0.1203, decode.d6.loss_mask: 0.3919, decode.d6.loss_dice: 0.5634, decode.d7.loss_cls: 0.1188, decode.d7.loss_mask: 0.3919, decode.d7.loss_dice: 0.5688, decode.d8.loss_cls: 0.1180, decode.d8.loss_mask: 0.3917, decode.d8.loss_dice: 0.5671, loss: 12.6441 +2022-05-06 06:40:38,621 - mmseg - INFO - Iter [26800/40000] lr: 4.738e-07, eta: 3:08:26, time: 0.719, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1037, decode.loss_mask: 0.3990, decode.loss_dice: 0.5470, decode.d0.loss_cls: 1.5403, decode.d0.loss_mask: 0.4412, decode.d0.loss_dice: 0.6441, decode.d1.loss_cls: 0.2235, decode.d1.loss_mask: 0.4120, decode.d1.loss_dice: 0.5854, decode.d2.loss_cls: 0.1503, decode.d2.loss_mask: 0.4046, decode.d2.loss_dice: 0.5611, decode.d3.loss_cls: 0.1257, decode.d3.loss_mask: 0.4019, decode.d3.loss_dice: 0.5500, decode.d4.loss_cls: 0.1205, decode.d4.loss_mask: 0.4014, decode.d4.loss_dice: 0.5498, decode.d5.loss_cls: 0.1106, decode.d5.loss_mask: 0.4009, decode.d5.loss_dice: 0.5478, decode.d6.loss_cls: 0.1087, decode.d6.loss_mask: 0.4001, decode.d6.loss_dice: 0.5490, decode.d7.loss_cls: 0.1052, decode.d7.loss_mask: 0.3989, decode.d7.loss_dice: 0.5514, decode.d8.loss_cls: 0.1083, decode.d8.loss_mask: 0.3974, decode.d8.loss_dice: 0.5448, loss: 12.3845 +2022-05-06 06:41:12,159 - mmseg - INFO - Iter [26850/40000] lr: 4.721e-07, eta: 3:07:38, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1242, decode.loss_mask: 0.4040, decode.loss_dice: 0.5835, decode.d0.loss_cls: 1.5652, decode.d0.loss_mask: 0.4423, decode.d0.loss_dice: 0.6755, decode.d1.loss_cls: 0.2406, decode.d1.loss_mask: 0.4167, decode.d1.loss_dice: 0.6136, decode.d2.loss_cls: 0.1756, decode.d2.loss_mask: 0.4085, decode.d2.loss_dice: 0.5914, decode.d3.loss_cls: 0.1402, decode.d3.loss_mask: 0.4041, decode.d3.loss_dice: 0.5835, decode.d4.loss_cls: 0.1326, decode.d4.loss_mask: 0.4051, decode.d4.loss_dice: 0.5828, decode.d5.loss_cls: 0.1308, decode.d5.loss_mask: 0.4042, decode.d5.loss_dice: 0.5829, decode.d6.loss_cls: 0.1302, decode.d6.loss_mask: 0.4028, decode.d6.loss_dice: 0.5791, decode.d7.loss_cls: 0.1246, decode.d7.loss_mask: 0.4015, decode.d7.loss_dice: 0.5794, decode.d8.loss_cls: 0.1274, decode.d8.loss_mask: 0.4028, decode.d8.loss_dice: 0.5808, loss: 12.9361 +2022-05-06 06:41:45,440 - mmseg - INFO - Iter [26900/40000] lr: 4.703e-07, eta: 3:06:49, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1036, decode.loss_mask: 0.3892, decode.loss_dice: 0.5602, decode.d0.loss_cls: 1.5759, decode.d0.loss_mask: 0.4322, decode.d0.loss_dice: 0.6596, decode.d1.loss_cls: 0.2150, decode.d1.loss_mask: 0.4060, decode.d1.loss_dice: 0.5988, decode.d2.loss_cls: 0.1490, decode.d2.loss_mask: 0.3951, decode.d2.loss_dice: 0.5786, decode.d3.loss_cls: 0.1251, decode.d3.loss_mask: 0.3929, decode.d3.loss_dice: 0.5702, decode.d4.loss_cls: 0.1148, decode.d4.loss_mask: 0.3945, decode.d4.loss_dice: 0.5711, decode.d5.loss_cls: 0.1165, decode.d5.loss_mask: 0.3916, decode.d5.loss_dice: 0.5655, decode.d6.loss_cls: 0.1028, decode.d6.loss_mask: 0.3906, decode.d6.loss_dice: 0.5614, decode.d7.loss_cls: 0.1007, decode.d7.loss_mask: 0.3905, decode.d7.loss_dice: 0.5604, decode.d8.loss_cls: 0.1075, decode.d8.loss_mask: 0.3898, decode.d8.loss_dice: 0.5621, loss: 12.4710 +2022-05-06 06:42:19,043 - mmseg - INFO - Iter [26950/40000] lr: 4.685e-07, eta: 3:06:01, time: 0.672, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0989, decode.loss_mask: 0.3998, decode.loss_dice: 0.5343, decode.d0.loss_cls: 1.5298, decode.d0.loss_mask: 0.4437, decode.d0.loss_dice: 0.6324, decode.d1.loss_cls: 0.2185, decode.d1.loss_mask: 0.4139, decode.d1.loss_dice: 0.5695, decode.d2.loss_cls: 0.1399, decode.d2.loss_mask: 0.4031, decode.d2.loss_dice: 0.5473, decode.d3.loss_cls: 0.1170, decode.d3.loss_mask: 0.4023, decode.d3.loss_dice: 0.5356, decode.d4.loss_cls: 0.1108, decode.d4.loss_mask: 0.4019, decode.d4.loss_dice: 0.5341, decode.d5.loss_cls: 0.1053, decode.d5.loss_mask: 0.4001, decode.d5.loss_dice: 0.5300, decode.d6.loss_cls: 0.0982, decode.d6.loss_mask: 0.3995, decode.d6.loss_dice: 0.5309, decode.d7.loss_cls: 0.0980, decode.d7.loss_mask: 0.3999, decode.d7.loss_dice: 0.5340, decode.d8.loss_cls: 0.0976, decode.d8.loss_mask: 0.3996, decode.d8.loss_dice: 0.5327, loss: 12.1585 +2022-05-06 06:42:52,910 - mmseg - INFO - Saving checkpoint at 27000 iterations +2022-05-06 06:43:18,221 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:43:18,229 - mmseg - INFO - Iter [27000/40000] lr: 4.667e-07, eta: 3:05:28, time: 1.181, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1061, decode.loss_mask: 0.4020, decode.loss_dice: 0.5589, decode.d0.loss_cls: 1.5308, decode.d0.loss_mask: 0.4515, decode.d0.loss_dice: 0.6622, decode.d1.loss_cls: 0.2163, decode.d1.loss_mask: 0.4199, decode.d1.loss_dice: 0.5930, decode.d2.loss_cls: 0.1486, decode.d2.loss_mask: 0.4074, decode.d2.loss_dice: 0.5745, decode.d3.loss_cls: 0.1215, decode.d3.loss_mask: 0.4053, decode.d3.loss_dice: 0.5680, decode.d4.loss_cls: 0.1085, decode.d4.loss_mask: 0.4065, decode.d4.loss_dice: 0.5646, decode.d5.loss_cls: 0.1029, decode.d5.loss_mask: 0.4067, decode.d5.loss_dice: 0.5645, decode.d6.loss_cls: 0.1035, decode.d6.loss_mask: 0.4046, decode.d6.loss_dice: 0.5579, decode.d7.loss_cls: 0.1037, decode.d7.loss_mask: 0.4038, decode.d7.loss_dice: 0.5571, decode.d8.loss_cls: 0.1057, decode.d8.loss_mask: 0.4005, decode.d8.loss_dice: 0.5586, loss: 12.5153 +2022-05-06 06:43:52,286 - mmseg - INFO - Iter [27050/40000] lr: 4.649e-07, eta: 3:04:40, time: 0.684, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1118, decode.loss_mask: 0.4105, decode.loss_dice: 0.5582, decode.d0.loss_cls: 1.5394, decode.d0.loss_mask: 0.4530, decode.d0.loss_dice: 0.6540, decode.d1.loss_cls: 0.2167, decode.d1.loss_mask: 0.4238, decode.d1.loss_dice: 0.5943, decode.d2.loss_cls: 0.1554, decode.d2.loss_mask: 0.4158, decode.d2.loss_dice: 0.5769, decode.d3.loss_cls: 0.1313, decode.d3.loss_mask: 0.4135, decode.d3.loss_dice: 0.5661, decode.d4.loss_cls: 0.1195, decode.d4.loss_mask: 0.4127, decode.d4.loss_dice: 0.5676, decode.d5.loss_cls: 0.1201, decode.d5.loss_mask: 0.4104, decode.d5.loss_dice: 0.5654, decode.d6.loss_cls: 0.1138, decode.d6.loss_mask: 0.4108, decode.d6.loss_dice: 0.5625, decode.d7.loss_cls: 0.1147, decode.d7.loss_mask: 0.4103, decode.d7.loss_dice: 0.5649, decode.d8.loss_cls: 0.1130, decode.d8.loss_mask: 0.4114, decode.d8.loss_dice: 0.5614, loss: 12.6793 +2022-05-06 06:44:28,296 - mmseg - INFO - Iter [27100/40000] lr: 4.631e-07, eta: 3:03:54, time: 0.720, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1229, decode.loss_mask: 0.3986, decode.loss_dice: 0.5808, decode.d0.loss_cls: 1.5781, decode.d0.loss_mask: 0.4446, decode.d0.loss_dice: 0.6848, decode.d1.loss_cls: 0.2261, decode.d1.loss_mask: 0.4140, decode.d1.loss_dice: 0.6218, decode.d2.loss_cls: 0.1523, decode.d2.loss_mask: 0.4044, decode.d2.loss_dice: 0.5972, decode.d3.loss_cls: 0.1342, decode.d3.loss_mask: 0.4025, decode.d3.loss_dice: 0.5862, decode.d4.loss_cls: 0.1265, decode.d4.loss_mask: 0.4006, decode.d4.loss_dice: 0.5855, decode.d5.loss_cls: 0.1187, decode.d5.loss_mask: 0.4004, decode.d5.loss_dice: 0.5805, decode.d6.loss_cls: 0.1205, decode.d6.loss_mask: 0.3990, decode.d6.loss_dice: 0.5738, decode.d7.loss_cls: 0.1187, decode.d7.loss_mask: 0.3985, decode.d7.loss_dice: 0.5763, decode.d8.loss_cls: 0.1227, decode.d8.loss_mask: 0.4003, decode.d8.loss_dice: 0.5760, loss: 12.8464 +2022-05-06 06:45:02,104 - mmseg - INFO - Iter [27150/40000] lr: 4.613e-07, eta: 3:03:06, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1168, decode.loss_mask: 0.4062, decode.loss_dice: 0.5478, decode.d0.loss_cls: 1.5347, decode.d0.loss_mask: 0.4491, decode.d0.loss_dice: 0.6361, decode.d1.loss_cls: 0.2280, decode.d1.loss_mask: 0.4201, decode.d1.loss_dice: 0.5805, decode.d2.loss_cls: 0.1621, decode.d2.loss_mask: 0.4145, decode.d2.loss_dice: 0.5669, decode.d3.loss_cls: 0.1368, decode.d3.loss_mask: 0.4109, decode.d3.loss_dice: 0.5538, decode.d4.loss_cls: 0.1315, decode.d4.loss_mask: 0.4085, decode.d4.loss_dice: 0.5535, decode.d5.loss_cls: 0.1241, decode.d5.loss_mask: 0.4074, decode.d5.loss_dice: 0.5546, decode.d6.loss_cls: 0.1210, decode.d6.loss_mask: 0.4073, decode.d6.loss_dice: 0.5527, decode.d7.loss_cls: 0.1187, decode.d7.loss_mask: 0.4052, decode.d7.loss_dice: 0.5497, decode.d8.loss_cls: 0.1163, decode.d8.loss_mask: 0.4079, decode.d8.loss_dice: 0.5479, loss: 12.5706 +2022-05-06 06:45:36,584 - mmseg - INFO - Iter [27200/40000] lr: 4.595e-07, eta: 3:02:19, time: 0.690, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1111, decode.loss_mask: 0.3940, decode.loss_dice: 0.5779, decode.d0.loss_cls: 1.5410, decode.d0.loss_mask: 0.4398, decode.d0.loss_dice: 0.6708, decode.d1.loss_cls: 0.2167, decode.d1.loss_mask: 0.4103, decode.d1.loss_dice: 0.6102, decode.d2.loss_cls: 0.1524, decode.d2.loss_mask: 0.4013, decode.d2.loss_dice: 0.5901, decode.d3.loss_cls: 0.1263, decode.d3.loss_mask: 0.4017, decode.d3.loss_dice: 0.5857, decode.d4.loss_cls: 0.1175, decode.d4.loss_mask: 0.3991, decode.d4.loss_dice: 0.5877, decode.d5.loss_cls: 0.1140, decode.d5.loss_mask: 0.3962, decode.d5.loss_dice: 0.5827, decode.d6.loss_cls: 0.1101, decode.d6.loss_mask: 0.3968, decode.d6.loss_dice: 0.5767, decode.d7.loss_cls: 0.1106, decode.d7.loss_mask: 0.3961, decode.d7.loss_dice: 0.5750, decode.d8.loss_cls: 0.1059, decode.d8.loss_mask: 0.3960, decode.d8.loss_dice: 0.5769, loss: 12.6706 +2022-05-06 06:46:10,507 - mmseg - INFO - Iter [27250/40000] lr: 4.577e-07, eta: 3:01:31, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1079, decode.loss_mask: 0.3865, decode.loss_dice: 0.5303, decode.d0.loss_cls: 1.5650, decode.d0.loss_mask: 0.4288, decode.d0.loss_dice: 0.6357, decode.d1.loss_cls: 0.2126, decode.d1.loss_mask: 0.4009, decode.d1.loss_dice: 0.5694, decode.d2.loss_cls: 0.1513, decode.d2.loss_mask: 0.3943, decode.d2.loss_dice: 0.5478, decode.d3.loss_cls: 0.1221, decode.d3.loss_mask: 0.3890, decode.d3.loss_dice: 0.5370, decode.d4.loss_cls: 0.1190, decode.d4.loss_mask: 0.3874, decode.d4.loss_dice: 0.5361, decode.d5.loss_cls: 0.1195, decode.d5.loss_mask: 0.3872, decode.d5.loss_dice: 0.5377, decode.d6.loss_cls: 0.1112, decode.d6.loss_mask: 0.3877, decode.d6.loss_dice: 0.5366, decode.d7.loss_cls: 0.1085, decode.d7.loss_mask: 0.3861, decode.d7.loss_dice: 0.5353, decode.d8.loss_cls: 0.1084, decode.d8.loss_mask: 0.3849, decode.d8.loss_dice: 0.5319, loss: 12.1562 +2022-05-06 06:46:43,846 - mmseg - INFO - Iter [27300/40000] lr: 4.559e-07, eta: 3:00:43, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1144, decode.loss_mask: 0.4014, decode.loss_dice: 0.5549, decode.d0.loss_cls: 1.5064, decode.d0.loss_mask: 0.4385, decode.d0.loss_dice: 0.6492, decode.d1.loss_cls: 0.2156, decode.d1.loss_mask: 0.4150, decode.d1.loss_dice: 0.5874, decode.d2.loss_cls: 0.1471, decode.d2.loss_mask: 0.4054, decode.d2.loss_dice: 0.5670, decode.d3.loss_cls: 0.1220, decode.d3.loss_mask: 0.4041, decode.d3.loss_dice: 0.5599, decode.d4.loss_cls: 0.1243, decode.d4.loss_mask: 0.4024, decode.d4.loss_dice: 0.5591, decode.d5.loss_cls: 0.1165, decode.d5.loss_mask: 0.4033, decode.d5.loss_dice: 0.5573, decode.d6.loss_cls: 0.1157, decode.d6.loss_mask: 0.4035, decode.d6.loss_dice: 0.5513, decode.d7.loss_cls: 0.1169, decode.d7.loss_mask: 0.4016, decode.d7.loss_dice: 0.5538, decode.d8.loss_cls: 0.1140, decode.d8.loss_mask: 0.4014, decode.d8.loss_dice: 0.5549, loss: 12.4641 +2022-05-06 06:47:17,757 - mmseg - INFO - Iter [27350/40000] lr: 4.541e-07, eta: 2:59:56, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1183, decode.loss_mask: 0.3935, decode.loss_dice: 0.5732, decode.d0.loss_cls: 1.5963, decode.d0.loss_mask: 0.4434, decode.d0.loss_dice: 0.6851, decode.d1.loss_cls: 0.2432, decode.d1.loss_mask: 0.4066, decode.d1.loss_dice: 0.6098, decode.d2.loss_cls: 0.1669, decode.d2.loss_mask: 0.4003, decode.d2.loss_dice: 0.5927, decode.d3.loss_cls: 0.1400, decode.d3.loss_mask: 0.3992, decode.d3.loss_dice: 0.5794, decode.d4.loss_cls: 0.1305, decode.d4.loss_mask: 0.3969, decode.d4.loss_dice: 0.5827, decode.d5.loss_cls: 0.1295, decode.d5.loss_mask: 0.3960, decode.d5.loss_dice: 0.5806, decode.d6.loss_cls: 0.1225, decode.d6.loss_mask: 0.3945, decode.d6.loss_dice: 0.5726, decode.d7.loss_cls: 0.1231, decode.d7.loss_mask: 0.3936, decode.d7.loss_dice: 0.5751, decode.d8.loss_cls: 0.1149, decode.d8.loss_mask: 0.3942, decode.d8.loss_dice: 0.5756, loss: 12.8302 +2022-05-06 06:47:53,697 - mmseg - INFO - Iter [27400/40000] lr: 4.523e-07, eta: 2:59:09, time: 0.719, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1177, decode.loss_mask: 0.3970, decode.loss_dice: 0.5791, decode.d0.loss_cls: 1.5629, decode.d0.loss_mask: 0.4446, decode.d0.loss_dice: 0.6882, decode.d1.loss_cls: 0.2387, decode.d1.loss_mask: 0.4157, decode.d1.loss_dice: 0.6208, decode.d2.loss_cls: 0.1725, decode.d2.loss_mask: 0.4045, decode.d2.loss_dice: 0.5973, decode.d3.loss_cls: 0.1464, decode.d3.loss_mask: 0.4020, decode.d3.loss_dice: 0.5859, decode.d4.loss_cls: 0.1346, decode.d4.loss_mask: 0.3997, decode.d4.loss_dice: 0.5898, decode.d5.loss_cls: 0.1306, decode.d5.loss_mask: 0.4001, decode.d5.loss_dice: 0.5858, decode.d6.loss_cls: 0.1239, decode.d6.loss_mask: 0.3994, decode.d6.loss_dice: 0.5803, decode.d7.loss_cls: 0.1194, decode.d7.loss_mask: 0.3985, decode.d7.loss_dice: 0.5767, decode.d8.loss_cls: 0.1203, decode.d8.loss_mask: 0.3983, decode.d8.loss_dice: 0.5823, loss: 12.9129 +2022-05-06 06:48:27,167 - mmseg - INFO - Iter [27450/40000] lr: 4.505e-07, eta: 2:58:22, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1009, decode.loss_mask: 0.3972, decode.loss_dice: 0.5483, decode.d0.loss_cls: 1.5224, decode.d0.loss_mask: 0.4396, decode.d0.loss_dice: 0.6533, decode.d1.loss_cls: 0.2160, decode.d1.loss_mask: 0.4097, decode.d1.loss_dice: 0.5796, decode.d2.loss_cls: 0.1527, decode.d2.loss_mask: 0.4019, decode.d2.loss_dice: 0.5590, decode.d3.loss_cls: 0.1188, decode.d3.loss_mask: 0.4008, decode.d3.loss_dice: 0.5501, decode.d4.loss_cls: 0.1178, decode.d4.loss_mask: 0.3989, decode.d4.loss_dice: 0.5495, decode.d5.loss_cls: 0.1106, decode.d5.loss_mask: 0.3978, decode.d5.loss_dice: 0.5460, decode.d6.loss_cls: 0.1028, decode.d6.loss_mask: 0.3985, decode.d6.loss_dice: 0.5471, decode.d7.loss_cls: 0.1051, decode.d7.loss_mask: 0.3977, decode.d7.loss_dice: 0.5483, decode.d8.loss_cls: 0.0993, decode.d8.loss_mask: 0.3979, decode.d8.loss_dice: 0.5502, loss: 12.3179 +2022-05-06 06:49:00,732 - mmseg - INFO - Iter [27500/40000] lr: 4.487e-07, eta: 2:57:34, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1041, decode.loss_mask: 0.3844, decode.loss_dice: 0.5609, decode.d0.loss_cls: 1.5431, decode.d0.loss_mask: 0.4257, decode.d0.loss_dice: 0.6669, decode.d1.loss_cls: 0.2280, decode.d1.loss_mask: 0.3977, decode.d1.loss_dice: 0.5965, decode.d2.loss_cls: 0.1529, decode.d2.loss_mask: 0.3914, decode.d2.loss_dice: 0.5741, decode.d3.loss_cls: 0.1248, decode.d3.loss_mask: 0.3876, decode.d3.loss_dice: 0.5637, decode.d4.loss_cls: 0.1189, decode.d4.loss_mask: 0.3863, decode.d4.loss_dice: 0.5652, decode.d5.loss_cls: 0.1138, decode.d5.loss_mask: 0.3846, decode.d5.loss_dice: 0.5642, decode.d6.loss_cls: 0.1000, decode.d6.loss_mask: 0.3847, decode.d6.loss_dice: 0.5628, decode.d7.loss_cls: 0.0994, decode.d7.loss_mask: 0.3847, decode.d7.loss_dice: 0.5606, decode.d8.loss_cls: 0.1033, decode.d8.loss_mask: 0.3836, decode.d8.loss_dice: 0.5596, loss: 12.3734 +2022-05-06 06:49:34,537 - mmseg - INFO - Iter [27550/40000] lr: 4.469e-07, eta: 2:56:47, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1040, decode.loss_mask: 0.4076, decode.loss_dice: 0.5466, decode.d0.loss_cls: 1.5360, decode.d0.loss_mask: 0.4531, decode.d0.loss_dice: 0.6434, decode.d1.loss_cls: 0.2067, decode.d1.loss_mask: 0.4233, decode.d1.loss_dice: 0.5829, decode.d2.loss_cls: 0.1486, decode.d2.loss_mask: 0.4130, decode.d2.loss_dice: 0.5624, decode.d3.loss_cls: 0.1236, decode.d3.loss_mask: 0.4105, decode.d3.loss_dice: 0.5527, decode.d4.loss_cls: 0.1175, decode.d4.loss_mask: 0.4090, decode.d4.loss_dice: 0.5499, decode.d5.loss_cls: 0.1129, decode.d5.loss_mask: 0.4060, decode.d5.loss_dice: 0.5486, decode.d6.loss_cls: 0.1111, decode.d6.loss_mask: 0.4057, decode.d6.loss_dice: 0.5514, decode.d7.loss_cls: 0.1099, decode.d7.loss_mask: 0.4070, decode.d7.loss_dice: 0.5487, decode.d8.loss_cls: 0.1108, decode.d8.loss_mask: 0.4057, decode.d8.loss_dice: 0.5457, loss: 12.4541 +2022-05-06 06:50:08,586 - mmseg - INFO - Iter [27600/40000] lr: 4.451e-07, eta: 2:56:00, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1064, decode.loss_mask: 0.4012, decode.loss_dice: 0.5484, decode.d0.loss_cls: 1.5605, decode.d0.loss_mask: 0.4434, decode.d0.loss_dice: 0.6529, decode.d1.loss_cls: 0.2151, decode.d1.loss_mask: 0.4110, decode.d1.loss_dice: 0.5883, decode.d2.loss_cls: 0.1439, decode.d2.loss_mask: 0.4045, decode.d2.loss_dice: 0.5641, decode.d3.loss_cls: 0.1192, decode.d3.loss_mask: 0.4018, decode.d3.loss_dice: 0.5559, decode.d4.loss_cls: 0.1124, decode.d4.loss_mask: 0.4001, decode.d4.loss_dice: 0.5516, decode.d5.loss_cls: 0.1083, decode.d5.loss_mask: 0.3998, decode.d5.loss_dice: 0.5516, decode.d6.loss_cls: 0.1042, decode.d6.loss_mask: 0.4029, decode.d6.loss_dice: 0.5514, decode.d7.loss_cls: 0.1137, decode.d7.loss_mask: 0.4008, decode.d7.loss_dice: 0.5486, decode.d8.loss_cls: 0.1032, decode.d8.loss_mask: 0.4006, decode.d8.loss_dice: 0.5517, loss: 12.4176 +2022-05-06 06:50:42,377 - mmseg - INFO - Iter [27650/40000] lr: 4.433e-07, eta: 2:55:13, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1209, decode.loss_mask: 0.3896, decode.loss_dice: 0.5772, decode.d0.loss_cls: 1.5788, decode.d0.loss_mask: 0.4368, decode.d0.loss_dice: 0.6834, decode.d1.loss_cls: 0.2202, decode.d1.loss_mask: 0.4048, decode.d1.loss_dice: 0.6166, decode.d2.loss_cls: 0.1621, decode.d2.loss_mask: 0.3950, decode.d2.loss_dice: 0.5891, decode.d3.loss_cls: 0.1434, decode.d3.loss_mask: 0.3945, decode.d3.loss_dice: 0.5841, decode.d4.loss_cls: 0.1295, decode.d4.loss_mask: 0.3931, decode.d4.loss_dice: 0.5871, decode.d5.loss_cls: 0.1276, decode.d5.loss_mask: 0.3925, decode.d5.loss_dice: 0.5855, decode.d6.loss_cls: 0.1191, decode.d6.loss_mask: 0.3942, decode.d6.loss_dice: 0.5822, decode.d7.loss_cls: 0.1228, decode.d7.loss_mask: 0.3920, decode.d7.loss_dice: 0.5782, decode.d8.loss_cls: 0.1262, decode.d8.loss_mask: 0.3915, decode.d8.loss_dice: 0.5798, loss: 12.7975 +2022-05-06 06:51:16,227 - mmseg - INFO - Iter [27700/40000] lr: 4.415e-07, eta: 2:54:26, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1163, decode.loss_mask: 0.4179, decode.loss_dice: 0.5436, decode.d0.loss_cls: 1.5025, decode.d0.loss_mask: 0.4596, decode.d0.loss_dice: 0.6349, decode.d1.loss_cls: 0.2221, decode.d1.loss_mask: 0.4334, decode.d1.loss_dice: 0.5826, decode.d2.loss_cls: 0.1559, decode.d2.loss_mask: 0.4231, decode.d2.loss_dice: 0.5616, decode.d3.loss_cls: 0.1319, decode.d3.loss_mask: 0.4203, decode.d3.loss_dice: 0.5502, decode.d4.loss_cls: 0.1245, decode.d4.loss_mask: 0.4190, decode.d4.loss_dice: 0.5455, decode.d5.loss_cls: 0.1228, decode.d5.loss_mask: 0.4175, decode.d5.loss_dice: 0.5487, decode.d6.loss_cls: 0.1170, decode.d6.loss_mask: 0.4174, decode.d6.loss_dice: 0.5452, decode.d7.loss_cls: 0.1170, decode.d7.loss_mask: 0.4166, decode.d7.loss_dice: 0.5430, decode.d8.loss_cls: 0.1162, decode.d8.loss_mask: 0.4174, decode.d8.loss_dice: 0.5453, loss: 12.5693 +2022-05-06 06:51:53,045 - mmseg - INFO - Iter [27750/40000] lr: 4.397e-07, eta: 2:53:40, time: 0.737, data_time: 0.061, memory: 53770, decode.loss_cls: 0.1045, decode.loss_mask: 0.4099, decode.loss_dice: 0.5801, decode.d0.loss_cls: 1.5305, decode.d0.loss_mask: 0.4549, decode.d0.loss_dice: 0.6786, decode.d1.loss_cls: 0.2114, decode.d1.loss_mask: 0.4224, decode.d1.loss_dice: 0.6128, decode.d2.loss_cls: 0.1466, decode.d2.loss_mask: 0.4134, decode.d2.loss_dice: 0.5975, decode.d3.loss_cls: 0.1252, decode.d3.loss_mask: 0.4110, decode.d3.loss_dice: 0.5863, decode.d4.loss_cls: 0.1185, decode.d4.loss_mask: 0.4109, decode.d4.loss_dice: 0.5817, decode.d5.loss_cls: 0.1105, decode.d5.loss_mask: 0.4116, decode.d5.loss_dice: 0.5831, decode.d6.loss_cls: 0.1033, decode.d6.loss_mask: 0.4097, decode.d6.loss_dice: 0.5826, decode.d7.loss_cls: 0.1027, decode.d7.loss_mask: 0.4098, decode.d7.loss_dice: 0.5823, decode.d8.loss_cls: 0.1067, decode.d8.loss_mask: 0.4087, decode.d8.loss_dice: 0.5792, loss: 12.7863 +2022-05-06 06:52:27,521 - mmseg - INFO - Iter [27800/40000] lr: 4.380e-07, eta: 2:52:54, time: 0.689, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1030, decode.loss_mask: 0.4017, decode.loss_dice: 0.5507, decode.d0.loss_cls: 1.5387, decode.d0.loss_mask: 0.4412, decode.d0.loss_dice: 0.6563, decode.d1.loss_cls: 0.2076, decode.d1.loss_mask: 0.4141, decode.d1.loss_dice: 0.5919, decode.d2.loss_cls: 0.1450, decode.d2.loss_mask: 0.4092, decode.d2.loss_dice: 0.5760, decode.d3.loss_cls: 0.1221, decode.d3.loss_mask: 0.4035, decode.d3.loss_dice: 0.5574, decode.d4.loss_cls: 0.1116, decode.d4.loss_mask: 0.4065, decode.d4.loss_dice: 0.5549, decode.d5.loss_cls: 0.1050, decode.d5.loss_mask: 0.4050, decode.d5.loss_dice: 0.5584, decode.d6.loss_cls: 0.1034, decode.d6.loss_mask: 0.4034, decode.d6.loss_dice: 0.5530, decode.d7.loss_cls: 0.1044, decode.d7.loss_mask: 0.4017, decode.d7.loss_dice: 0.5515, decode.d8.loss_cls: 0.1014, decode.d8.loss_mask: 0.4019, decode.d8.loss_dice: 0.5555, loss: 12.4358 +2022-05-06 06:53:01,831 - mmseg - INFO - Iter [27850/40000] lr: 4.362e-07, eta: 2:52:07, time: 0.686, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1021, decode.loss_mask: 0.3815, decode.loss_dice: 0.5184, decode.d0.loss_cls: 1.5382, decode.d0.loss_mask: 0.4255, decode.d0.loss_dice: 0.6095, decode.d1.loss_cls: 0.2004, decode.d1.loss_mask: 0.3979, decode.d1.loss_dice: 0.5505, decode.d2.loss_cls: 0.1393, decode.d2.loss_mask: 0.3899, decode.d2.loss_dice: 0.5319, decode.d3.loss_cls: 0.1114, decode.d3.loss_mask: 0.3876, decode.d3.loss_dice: 0.5266, decode.d4.loss_cls: 0.1095, decode.d4.loss_mask: 0.3848, decode.d4.loss_dice: 0.5238, decode.d5.loss_cls: 0.0998, decode.d5.loss_mask: 0.3879, decode.d5.loss_dice: 0.5266, decode.d6.loss_cls: 0.0994, decode.d6.loss_mask: 0.3844, decode.d6.loss_dice: 0.5210, decode.d7.loss_cls: 0.0966, decode.d7.loss_mask: 0.3859, decode.d7.loss_dice: 0.5205, decode.d8.loss_cls: 0.0957, decode.d8.loss_mask: 0.3834, decode.d8.loss_dice: 0.5244, loss: 11.8548 +2022-05-06 06:53:35,730 - mmseg - INFO - Iter [27900/40000] lr: 4.344e-07, eta: 2:51:20, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1142, decode.loss_mask: 0.3901, decode.loss_dice: 0.5487, decode.d0.loss_cls: 1.5521, decode.d0.loss_mask: 0.4298, decode.d0.loss_dice: 0.6447, decode.d1.loss_cls: 0.2293, decode.d1.loss_mask: 0.4025, decode.d1.loss_dice: 0.5848, decode.d2.loss_cls: 0.1644, decode.d2.loss_mask: 0.3916, decode.d2.loss_dice: 0.5648, decode.d3.loss_cls: 0.1299, decode.d3.loss_mask: 0.3910, decode.d3.loss_dice: 0.5534, decode.d4.loss_cls: 0.1261, decode.d4.loss_mask: 0.3904, decode.d4.loss_dice: 0.5523, decode.d5.loss_cls: 0.1219, decode.d5.loss_mask: 0.3910, decode.d5.loss_dice: 0.5501, decode.d6.loss_cls: 0.1188, decode.d6.loss_mask: 0.3890, decode.d6.loss_dice: 0.5476, decode.d7.loss_cls: 0.1142, decode.d7.loss_mask: 0.3901, decode.d7.loss_dice: 0.5501, decode.d8.loss_cls: 0.1129, decode.d8.loss_mask: 0.3881, decode.d8.loss_dice: 0.5461, loss: 12.3801 +2022-05-06 06:54:09,766 - mmseg - INFO - Iter [27950/40000] lr: 4.326e-07, eta: 2:50:33, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0998, decode.loss_mask: 0.4078, decode.loss_dice: 0.5619, decode.d0.loss_cls: 1.5333, decode.d0.loss_mask: 0.4496, decode.d0.loss_dice: 0.6589, decode.d1.loss_cls: 0.2042, decode.d1.loss_mask: 0.4218, decode.d1.loss_dice: 0.6022, decode.d2.loss_cls: 0.1439, decode.d2.loss_mask: 0.4135, decode.d2.loss_dice: 0.5757, decode.d3.loss_cls: 0.1203, decode.d3.loss_mask: 0.4110, decode.d3.loss_dice: 0.5668, decode.d4.loss_cls: 0.1179, decode.d4.loss_mask: 0.4098, decode.d4.loss_dice: 0.5657, decode.d5.loss_cls: 0.1054, decode.d5.loss_mask: 0.4101, decode.d5.loss_dice: 0.5646, decode.d6.loss_cls: 0.0991, decode.d6.loss_mask: 0.4091, decode.d6.loss_dice: 0.5630, decode.d7.loss_cls: 0.1014, decode.d7.loss_mask: 0.4077, decode.d7.loss_dice: 0.5614, decode.d8.loss_cls: 0.0981, decode.d8.loss_mask: 0.4083, decode.d8.loss_dice: 0.5628, loss: 12.5549 +2022-05-06 06:54:43,786 - mmseg - INFO - Saving checkpoint at 28000 iterations +2022-05-06 06:55:09,491 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:55:09,498 - mmseg - INFO - Iter [28000/40000] lr: 4.308e-07, eta: 2:49:59, time: 1.192, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1224, decode.loss_mask: 0.4027, decode.loss_dice: 0.5717, decode.d0.loss_cls: 1.5445, decode.d0.loss_mask: 0.4407, decode.d0.loss_dice: 0.6700, decode.d1.loss_cls: 0.2350, decode.d1.loss_mask: 0.4166, decode.d1.loss_dice: 0.6118, decode.d2.loss_cls: 0.1653, decode.d2.loss_mask: 0.4049, decode.d2.loss_dice: 0.5882, decode.d3.loss_cls: 0.1446, decode.d3.loss_mask: 0.4032, decode.d3.loss_dice: 0.5777, decode.d4.loss_cls: 0.1390, decode.d4.loss_mask: 0.4010, decode.d4.loss_dice: 0.5749, decode.d5.loss_cls: 0.1289, decode.d5.loss_mask: 0.4015, decode.d5.loss_dice: 0.5716, decode.d6.loss_cls: 0.1220, decode.d6.loss_mask: 0.4044, decode.d6.loss_dice: 0.5718, decode.d7.loss_cls: 0.1206, decode.d7.loss_mask: 0.4025, decode.d7.loss_dice: 0.5727, decode.d8.loss_cls: 0.1214, decode.d8.loss_mask: 0.4030, decode.d8.loss_dice: 0.5737, loss: 12.8083 +2022-05-06 06:59:29,913 - mmseg - INFO - per class results: +2022-05-06 06:59:29,918 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.95 | 96.29 | +| bag | 50.0 | 65.02 | +| bed | 37.17 | 43.96 | +| bedclothes | 45.82 | 69.35 | +| bench | 27.87 | 35.06 | +| bicycle | 85.21 | 92.55 | +| bird | 95.44 | 97.71 | +| boat | 87.24 | 93.3 | +| book | 57.76 | 73.06 | +| bottle | 89.63 | 95.85 | +| building | 67.38 | 79.45 | +| bus | 95.17 | 97.29 | +| cabinet | 52.7 | 64.3 | +| car | 93.62 | 97.01 | +| cat | 94.71 | 98.0 | +| ceiling | 61.68 | 82.57 | +| chair | 64.81 | 84.99 | +| cloth | 33.72 | 46.88 | +| computer | 57.82 | 72.74 | +| cow | 95.81 | 97.41 | +| cup | 52.0 | 66.43 | +| curtain | 60.53 | 77.71 | +| dog | 92.98 | 97.89 | +| door | 40.37 | 55.33 | +| fence | 46.14 | 60.38 | +| floor | 74.05 | 87.96 | +| flower | 38.93 | 53.12 | +| food | 44.5 | 59.37 | +| grass | 83.39 | 92.51 | +| ground | 57.93 | 72.47 | +| horse | 95.28 | 97.67 | +| keyboard | 89.63 | 96.64 | +| light | 61.53 | 80.89 | +| motorbike | 91.93 | 97.0 | +| mountain | 56.85 | 72.05 | +| mouse | 88.47 | 93.07 | +| person | 91.37 | 96.21 | +| plate | 33.89 | 47.13 | +| platform | 48.23 | 60.46 | +| pottedplant | 82.2 | 92.18 | +| road | 54.27 | 71.11 | +| rock | 55.76 | 65.66 | +| sheep | 95.25 | 97.95 | +| shelves | 41.02 | 57.86 | +| sidewalk | 35.04 | 45.25 | +| sign | 55.98 | 68.87 | +| sky | 94.72 | 96.92 | +| snow | 79.28 | 90.04 | +| sofa | 61.04 | 70.11 | +| table | 72.25 | 81.76 | +| track | 72.44 | 81.02 | +| train | 93.03 | 96.91 | +| tree | 82.18 | 90.74 | +| truck | 54.04 | 63.86 | +| tvmonitor | 90.7 | 94.19 | +| wall | 72.95 | 86.21 | +| water | 92.81 | 95.92 | +| window | 45.77 | 56.81 | +| wood | 27.05 | 38.89 | ++-------------+-------+-------+ +2022-05-06 06:59:29,918 - mmseg - INFO - Summary: +2022-05-06 06:59:29,918 - mmseg - INFO - ++------+-------+-------+ +| aAcc | mIoU | mAcc | ++------+-------+-------+ +| 86.7 | 67.67 | 77.79 | ++------+-------+-------+ +2022-05-06 06:59:29,921 - mmseg - INFO - The previous best checkpoint /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/best_mIoU_iter_20000.pth was removed +2022-05-06 06:59:56,235 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_28000.pth. +2022-05-06 06:59:56,245 - mmseg - INFO - Best mIoU is 0.6767 at 28000 iter. +2022-05-06 06:59:56,270 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 06:59:56,271 - mmseg - INFO - Iter(val) [638] aAcc: 0.8670, mIoU: 0.6767, mAcc: 0.7779, IoU.aeroplane: 0.9295, IoU.bag: 0.5000, IoU.bed: 0.3717, IoU.bedclothes: 0.4582, IoU.bench: 0.2787, IoU.bicycle: 0.8521, IoU.bird: 0.9544, IoU.boat: 0.8724, IoU.book: 0.5776, IoU.bottle: 0.8963, IoU.building: 0.6738, IoU.bus: 0.9517, IoU.cabinet: 0.5270, IoU.car: 0.9362, IoU.cat: 0.9471, IoU.ceiling: 0.6168, IoU.chair: 0.6481, IoU.cloth: 0.3372, IoU.computer: 0.5782, IoU.cow: 0.9581, IoU.cup: 0.5200, IoU.curtain: 0.6053, IoU.dog: 0.9298, IoU.door: 0.4037, IoU.fence: 0.4614, IoU.floor: 0.7405, IoU.flower: 0.3893, IoU.food: 0.4450, IoU.grass: 0.8339, IoU.ground: 0.5793, IoU.horse: 0.9528, IoU.keyboard: 0.8963, IoU.light: 0.6153, IoU.motorbike: 0.9193, IoU.mountain: 0.5685, IoU.mouse: 0.8847, IoU.person: 0.9137, IoU.plate: 0.3389, IoU.platform: 0.4823, IoU.pottedplant: 0.8220, IoU.road: 0.5427, IoU.rock: 0.5576, IoU.sheep: 0.9525, IoU.shelves: 0.4102, IoU.sidewalk: 0.3504, IoU.sign: 0.5598, IoU.sky: 0.9472, IoU.snow: 0.7928, IoU.sofa: 0.6104, IoU.table: 0.7225, IoU.track: 0.7244, IoU.train: 0.9303, IoU.tree: 0.8218, IoU.truck: 0.5404, IoU.tvmonitor: 0.9070, IoU.wall: 0.7295, IoU.water: 0.9281, IoU.window: 0.4577, IoU.wood: 0.2705, Acc.aeroplane: 0.9629, Acc.bag: 0.6502, Acc.bed: 0.4396, Acc.bedclothes: 0.6935, Acc.bench: 0.3506, Acc.bicycle: 0.9255, Acc.bird: 0.9771, Acc.boat: 0.9330, Acc.book: 0.7306, Acc.bottle: 0.9585, Acc.building: 0.7945, Acc.bus: 0.9729, Acc.cabinet: 0.6430, Acc.car: 0.9701, Acc.cat: 0.9800, Acc.ceiling: 0.8257, Acc.chair: 0.8499, Acc.cloth: 0.4688, Acc.computer: 0.7274, Acc.cow: 0.9741, Acc.cup: 0.6643, Acc.curtain: 0.7771, Acc.dog: 0.9789, Acc.door: 0.5533, Acc.fence: 0.6038, Acc.floor: 0.8796, Acc.flower: 0.5312, Acc.food: 0.5937, Acc.grass: 0.9251, Acc.ground: 0.7247, Acc.horse: 0.9767, Acc.keyboard: 0.9664, Acc.light: 0.8089, Acc.motorbike: 0.9700, Acc.mountain: 0.7205, Acc.mouse: 0.9307, Acc.person: 0.9621, Acc.plate: 0.4713, Acc.platform: 0.6046, Acc.pottedplant: 0.9218, Acc.road: 0.7111, Acc.rock: 0.6566, Acc.sheep: 0.9795, Acc.shelves: 0.5786, Acc.sidewalk: 0.4525, Acc.sign: 0.6887, Acc.sky: 0.9692, Acc.snow: 0.9004, Acc.sofa: 0.7011, Acc.table: 0.8176, Acc.track: 0.8102, Acc.train: 0.9691, Acc.tree: 0.9074, Acc.truck: 0.6386, Acc.tvmonitor: 0.9419, Acc.wall: 0.8621, Acc.water: 0.9592, Acc.window: 0.5681, Acc.wood: 0.3889 +2022-05-06 07:00:33,536 - mmseg - INFO - Iter [28050/40000] lr: 4.290e-07, eta: 2:51:37, time: 6.483, data_time: 5.795, memory: 53770, decode.loss_cls: 0.1097, decode.loss_mask: 0.3917, decode.loss_dice: 0.5462, decode.d0.loss_cls: 1.5089, decode.d0.loss_mask: 0.4336, decode.d0.loss_dice: 0.6342, decode.d1.loss_cls: 0.2090, decode.d1.loss_mask: 0.4058, decode.d1.loss_dice: 0.5799, decode.d2.loss_cls: 0.1501, decode.d2.loss_mask: 0.3988, decode.d2.loss_dice: 0.5629, decode.d3.loss_cls: 0.1229, decode.d3.loss_mask: 0.3950, decode.d3.loss_dice: 0.5508, decode.d4.loss_cls: 0.1131, decode.d4.loss_mask: 0.3953, decode.d4.loss_dice: 0.5508, decode.d5.loss_cls: 0.1121, decode.d5.loss_mask: 0.3930, decode.d5.loss_dice: 0.5458, decode.d6.loss_cls: 0.1032, decode.d6.loss_mask: 0.3936, decode.d6.loss_dice: 0.5468, decode.d7.loss_cls: 0.1069, decode.d7.loss_mask: 0.3934, decode.d7.loss_dice: 0.5465, decode.d8.loss_cls: 0.1021, decode.d8.loss_mask: 0.3921, decode.d8.loss_dice: 0.5476, loss: 12.2418 +2022-05-06 07:01:06,965 - mmseg - INFO - Iter [28100/40000] lr: 4.272e-07, eta: 2:50:49, time: 0.669, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1070, decode.loss_mask: 0.3935, decode.loss_dice: 0.5541, decode.d0.loss_cls: 1.5298, decode.d0.loss_mask: 0.4372, decode.d0.loss_dice: 0.6496, decode.d1.loss_cls: 0.2176, decode.d1.loss_mask: 0.4069, decode.d1.loss_dice: 0.5858, decode.d2.loss_cls: 0.1542, decode.d2.loss_mask: 0.3976, decode.d2.loss_dice: 0.5637, decode.d3.loss_cls: 0.1243, decode.d3.loss_mask: 0.3956, decode.d3.loss_dice: 0.5529, decode.d4.loss_cls: 0.1176, decode.d4.loss_mask: 0.3942, decode.d4.loss_dice: 0.5550, decode.d5.loss_cls: 0.1098, decode.d5.loss_mask: 0.3917, decode.d5.loss_dice: 0.5527, decode.d6.loss_cls: 0.1053, decode.d6.loss_mask: 0.3915, decode.d6.loss_dice: 0.5521, decode.d7.loss_cls: 0.1075, decode.d7.loss_mask: 0.3926, decode.d7.loss_dice: 0.5543, decode.d8.loss_cls: 0.1108, decode.d8.loss_mask: 0.3925, decode.d8.loss_dice: 0.5499, loss: 12.3476 +2022-05-06 07:01:40,619 - mmseg - INFO - Iter [28150/40000] lr: 4.254e-07, eta: 2:50:01, time: 0.673, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1192, decode.loss_mask: 0.3863, decode.loss_dice: 0.5596, decode.d0.loss_cls: 1.5410, decode.d0.loss_mask: 0.4314, decode.d0.loss_dice: 0.6587, decode.d1.loss_cls: 0.2239, decode.d1.loss_mask: 0.4061, decode.d1.loss_dice: 0.5956, decode.d2.loss_cls: 0.1563, decode.d2.loss_mask: 0.3935, decode.d2.loss_dice: 0.5739, decode.d3.loss_cls: 0.1381, decode.d3.loss_mask: 0.3918, decode.d3.loss_dice: 0.5667, decode.d4.loss_cls: 0.1320, decode.d4.loss_mask: 0.3879, decode.d4.loss_dice: 0.5628, decode.d5.loss_cls: 0.1274, decode.d5.loss_mask: 0.3858, decode.d5.loss_dice: 0.5572, decode.d6.loss_cls: 0.1220, decode.d6.loss_mask: 0.3892, decode.d6.loss_dice: 0.5565, decode.d7.loss_cls: 0.1217, decode.d7.loss_mask: 0.3890, decode.d7.loss_dice: 0.5589, decode.d8.loss_cls: 0.1156, decode.d8.loss_mask: 0.3878, decode.d8.loss_dice: 0.5607, loss: 12.4965 +2022-05-06 07:02:14,600 - mmseg - INFO - Iter [28200/40000] lr: 4.236e-07, eta: 2:49:14, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0984, decode.loss_mask: 0.3904, decode.loss_dice: 0.5412, decode.d0.loss_cls: 1.5597, decode.d0.loss_mask: 0.4324, decode.d0.loss_dice: 0.6378, decode.d1.loss_cls: 0.1975, decode.d1.loss_mask: 0.4046, decode.d1.loss_dice: 0.5781, decode.d2.loss_cls: 0.1388, decode.d2.loss_mask: 0.3972, decode.d2.loss_dice: 0.5619, decode.d3.loss_cls: 0.1171, decode.d3.loss_mask: 0.3947, decode.d3.loss_dice: 0.5468, decode.d4.loss_cls: 0.1127, decode.d4.loss_mask: 0.3942, decode.d4.loss_dice: 0.5485, decode.d5.loss_cls: 0.1030, decode.d5.loss_mask: 0.3931, decode.d5.loss_dice: 0.5480, decode.d6.loss_cls: 0.0980, decode.d6.loss_mask: 0.3930, decode.d6.loss_dice: 0.5428, decode.d7.loss_cls: 0.0996, decode.d7.loss_mask: 0.3933, decode.d7.loss_dice: 0.5424, decode.d8.loss_cls: 0.0946, decode.d8.loss_mask: 0.3922, decode.d8.loss_dice: 0.5452, loss: 12.1971 +2022-05-06 07:02:48,722 - mmseg - INFO - Iter [28250/40000] lr: 4.218e-07, eta: 2:48:26, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1158, decode.loss_mask: 0.3828, decode.loss_dice: 0.5462, decode.d0.loss_cls: 1.5461, decode.d0.loss_mask: 0.4251, decode.d0.loss_dice: 0.6463, decode.d1.loss_cls: 0.2242, decode.d1.loss_mask: 0.3966, decode.d1.loss_dice: 0.5811, decode.d2.loss_cls: 0.1512, decode.d2.loss_mask: 0.3896, decode.d2.loss_dice: 0.5584, decode.d3.loss_cls: 0.1261, decode.d3.loss_mask: 0.3871, decode.d3.loss_dice: 0.5542, decode.d4.loss_cls: 0.1205, decode.d4.loss_mask: 0.3843, decode.d4.loss_dice: 0.5552, decode.d5.loss_cls: 0.1103, decode.d5.loss_mask: 0.3836, decode.d5.loss_dice: 0.5532, decode.d6.loss_cls: 0.1148, decode.d6.loss_mask: 0.3825, decode.d6.loss_dice: 0.5452, decode.d7.loss_cls: 0.1110, decode.d7.loss_mask: 0.3831, decode.d7.loss_dice: 0.5492, decode.d8.loss_cls: 0.1136, decode.d8.loss_mask: 0.3818, decode.d8.loss_dice: 0.5447, loss: 12.2640 +2022-05-06 07:03:22,353 - mmseg - INFO - Iter [28300/40000] lr: 4.200e-07, eta: 2:47:39, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1119, decode.loss_mask: 0.3781, decode.loss_dice: 0.5581, decode.d0.loss_cls: 1.5171, decode.d0.loss_mask: 0.4188, decode.d0.loss_dice: 0.6590, decode.d1.loss_cls: 0.2176, decode.d1.loss_mask: 0.3878, decode.d1.loss_dice: 0.5877, decode.d2.loss_cls: 0.1484, decode.d2.loss_mask: 0.3812, decode.d2.loss_dice: 0.5722, decode.d3.loss_cls: 0.1295, decode.d3.loss_mask: 0.3805, decode.d3.loss_dice: 0.5650, decode.d4.loss_cls: 0.1186, decode.d4.loss_mask: 0.3785, decode.d4.loss_dice: 0.5614, decode.d5.loss_cls: 0.1168, decode.d5.loss_mask: 0.3788, decode.d5.loss_dice: 0.5576, decode.d6.loss_cls: 0.1146, decode.d6.loss_mask: 0.3774, decode.d6.loss_dice: 0.5575, decode.d7.loss_cls: 0.1082, decode.d7.loss_mask: 0.3781, decode.d7.loss_dice: 0.5615, decode.d8.loss_cls: 0.1112, decode.d8.loss_mask: 0.3774, decode.d8.loss_dice: 0.5577, loss: 12.2683 +2022-05-06 07:03:59,104 - mmseg - INFO - Iter [28350/40000] lr: 4.182e-07, eta: 2:46:53, time: 0.735, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1238, decode.loss_mask: 0.3999, decode.loss_dice: 0.5542, decode.d0.loss_cls: 1.5100, decode.d0.loss_mask: 0.4351, decode.d0.loss_dice: 0.6609, decode.d1.loss_cls: 0.2258, decode.d1.loss_mask: 0.4146, decode.d1.loss_dice: 0.5939, decode.d2.loss_cls: 0.1570, decode.d2.loss_mask: 0.4064, decode.d2.loss_dice: 0.5686, decode.d3.loss_cls: 0.1401, decode.d3.loss_mask: 0.4046, decode.d3.loss_dice: 0.5591, decode.d4.loss_cls: 0.1354, decode.d4.loss_mask: 0.4045, decode.d4.loss_dice: 0.5634, decode.d5.loss_cls: 0.1274, decode.d5.loss_mask: 0.4030, decode.d5.loss_dice: 0.5593, decode.d6.loss_cls: 0.1247, decode.d6.loss_mask: 0.4007, decode.d6.loss_dice: 0.5548, decode.d7.loss_cls: 0.1214, decode.d7.loss_mask: 0.4003, decode.d7.loss_dice: 0.5576, decode.d8.loss_cls: 0.1231, decode.d8.loss_mask: 0.3997, decode.d8.loss_dice: 0.5558, loss: 12.5853 +2022-05-06 07:04:33,118 - mmseg - INFO - Iter [28400/40000] lr: 4.164e-07, eta: 2:46:06, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1101, decode.loss_mask: 0.3922, decode.loss_dice: 0.5459, decode.d0.loss_cls: 1.4827, decode.d0.loss_mask: 0.4323, decode.d0.loss_dice: 0.6373, decode.d1.loss_cls: 0.2140, decode.d1.loss_mask: 0.4061, decode.d1.loss_dice: 0.5739, decode.d2.loss_cls: 0.1580, decode.d2.loss_mask: 0.3948, decode.d2.loss_dice: 0.5580, decode.d3.loss_cls: 0.1253, decode.d3.loss_mask: 0.3933, decode.d3.loss_dice: 0.5546, decode.d4.loss_cls: 0.1206, decode.d4.loss_mask: 0.3924, decode.d4.loss_dice: 0.5516, decode.d5.loss_cls: 0.1138, decode.d5.loss_mask: 0.3909, decode.d5.loss_dice: 0.5497, decode.d6.loss_cls: 0.1100, decode.d6.loss_mask: 0.3934, decode.d6.loss_dice: 0.5508, decode.d7.loss_cls: 0.1101, decode.d7.loss_mask: 0.3920, decode.d7.loss_dice: 0.5474, decode.d8.loss_cls: 0.1045, decode.d8.loss_mask: 0.3919, decode.d8.loss_dice: 0.5492, loss: 12.2467 +2022-05-06 07:05:06,965 - mmseg - INFO - Iter [28450/40000] lr: 4.146e-07, eta: 2:45:18, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1095, decode.loss_mask: 0.3925, decode.loss_dice: 0.5471, decode.d0.loss_cls: 1.5307, decode.d0.loss_mask: 0.4252, decode.d0.loss_dice: 0.6406, decode.d1.loss_cls: 0.2242, decode.d1.loss_mask: 0.4006, decode.d1.loss_dice: 0.5774, decode.d2.loss_cls: 0.1516, decode.d2.loss_mask: 0.3933, decode.d2.loss_dice: 0.5606, decode.d3.loss_cls: 0.1247, decode.d3.loss_mask: 0.3915, decode.d3.loss_dice: 0.5503, decode.d4.loss_cls: 0.1250, decode.d4.loss_mask: 0.3911, decode.d4.loss_dice: 0.5504, decode.d5.loss_cls: 0.1143, decode.d5.loss_mask: 0.3897, decode.d5.loss_dice: 0.5486, decode.d6.loss_cls: 0.1165, decode.d6.loss_mask: 0.3884, decode.d6.loss_dice: 0.5441, decode.d7.loss_cls: 0.1122, decode.d7.loss_mask: 0.3914, decode.d7.loss_dice: 0.5460, decode.d8.loss_cls: 0.1067, decode.d8.loss_mask: 0.3905, decode.d8.loss_dice: 0.5472, loss: 12.2820 +2022-05-06 07:05:41,092 - mmseg - INFO - Iter [28500/40000] lr: 4.128e-07, eta: 2:44:31, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1133, decode.loss_mask: 0.3956, decode.loss_dice: 0.5719, decode.d0.loss_cls: 1.5907, decode.d0.loss_mask: 0.4383, decode.d0.loss_dice: 0.6802, decode.d1.loss_cls: 0.2321, decode.d1.loss_mask: 0.4094, decode.d1.loss_dice: 0.6062, decode.d2.loss_cls: 0.1537, decode.d2.loss_mask: 0.3985, decode.d2.loss_dice: 0.5825, decode.d3.loss_cls: 0.1299, decode.d3.loss_mask: 0.3971, decode.d3.loss_dice: 0.5720, decode.d4.loss_cls: 0.1245, decode.d4.loss_mask: 0.3961, decode.d4.loss_dice: 0.5743, decode.d5.loss_cls: 0.1182, decode.d5.loss_mask: 0.3966, decode.d5.loss_dice: 0.5741, decode.d6.loss_cls: 0.1118, decode.d6.loss_mask: 0.3950, decode.d6.loss_dice: 0.5726, decode.d7.loss_cls: 0.1115, decode.d7.loss_mask: 0.3961, decode.d7.loss_dice: 0.5756, decode.d8.loss_cls: 0.1141, decode.d8.loss_mask: 0.3941, decode.d8.loss_dice: 0.5733, loss: 12.6996 +2022-05-06 07:06:15,056 - mmseg - INFO - Iter [28550/40000] lr: 4.110e-07, eta: 2:43:44, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1220, decode.loss_mask: 0.3934, decode.loss_dice: 0.5648, decode.d0.loss_cls: 1.6075, decode.d0.loss_mask: 0.4358, decode.d0.loss_dice: 0.6692, decode.d1.loss_cls: 0.2565, decode.d1.loss_mask: 0.4075, decode.d1.loss_dice: 0.6005, decode.d2.loss_cls: 0.1736, decode.d2.loss_mask: 0.4000, decode.d2.loss_dice: 0.5839, decode.d3.loss_cls: 0.1387, decode.d3.loss_mask: 0.3978, decode.d3.loss_dice: 0.5700, decode.d4.loss_cls: 0.1327, decode.d4.loss_mask: 0.3963, decode.d4.loss_dice: 0.5721, decode.d5.loss_cls: 0.1220, decode.d5.loss_mask: 0.3956, decode.d5.loss_dice: 0.5767, decode.d6.loss_cls: 0.1226, decode.d6.loss_mask: 0.3953, decode.d6.loss_dice: 0.5695, decode.d7.loss_cls: 0.1172, decode.d7.loss_mask: 0.3944, decode.d7.loss_dice: 0.5682, decode.d8.loss_cls: 0.1234, decode.d8.loss_mask: 0.3934, decode.d8.loss_dice: 0.5670, loss: 12.7674 +2022-05-06 07:06:48,397 - mmseg - INFO - Iter [28600/40000] lr: 4.092e-07, eta: 2:42:57, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1023, decode.loss_mask: 0.4094, decode.loss_dice: 0.5531, decode.d0.loss_cls: 1.4984, decode.d0.loss_mask: 0.4577, decode.d0.loss_dice: 0.6530, decode.d1.loss_cls: 0.2159, decode.d1.loss_mask: 0.4239, decode.d1.loss_dice: 0.5858, decode.d2.loss_cls: 0.1428, decode.d2.loss_mask: 0.4155, decode.d2.loss_dice: 0.5657, decode.d3.loss_cls: 0.1153, decode.d3.loss_mask: 0.4116, decode.d3.loss_dice: 0.5601, decode.d4.loss_cls: 0.1092, decode.d4.loss_mask: 0.4110, decode.d4.loss_dice: 0.5578, decode.d5.loss_cls: 0.1046, decode.d5.loss_mask: 0.4097, decode.d5.loss_dice: 0.5554, decode.d6.loss_cls: 0.0954, decode.d6.loss_mask: 0.4100, decode.d6.loss_dice: 0.5572, decode.d7.loss_cls: 0.0988, decode.d7.loss_mask: 0.4082, decode.d7.loss_dice: 0.5572, decode.d8.loss_cls: 0.1025, decode.d8.loss_mask: 0.4089, decode.d8.loss_dice: 0.5545, loss: 12.4508 +2022-05-06 07:07:24,539 - mmseg - INFO - Iter [28650/40000] lr: 4.074e-07, eta: 2:42:11, time: 0.723, data_time: 0.057, memory: 53770, decode.loss_cls: 0.1099, decode.loss_mask: 0.4018, decode.loss_dice: 0.5624, decode.d0.loss_cls: 1.5269, decode.d0.loss_mask: 0.4416, decode.d0.loss_dice: 0.6511, decode.d1.loss_cls: 0.2263, decode.d1.loss_mask: 0.4167, decode.d1.loss_dice: 0.5978, decode.d2.loss_cls: 0.1562, decode.d2.loss_mask: 0.4089, decode.d2.loss_dice: 0.5731, decode.d3.loss_cls: 0.1283, decode.d3.loss_mask: 0.4042, decode.d3.loss_dice: 0.5643, decode.d4.loss_cls: 0.1198, decode.d4.loss_mask: 0.4034, decode.d4.loss_dice: 0.5626, decode.d5.loss_cls: 0.1137, decode.d5.loss_mask: 0.4051, decode.d5.loss_dice: 0.5653, decode.d6.loss_cls: 0.1104, decode.d6.loss_mask: 0.4017, decode.d6.loss_dice: 0.5601, decode.d7.loss_cls: 0.1169, decode.d7.loss_mask: 0.4013, decode.d7.loss_dice: 0.5631, decode.d8.loss_cls: 0.1079, decode.d8.loss_mask: 0.4017, decode.d8.loss_dice: 0.5620, loss: 12.5643 +2022-05-06 07:07:58,089 - mmseg - INFO - Iter [28700/40000] lr: 4.056e-07, eta: 2:41:24, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1009, decode.loss_mask: 0.3903, decode.loss_dice: 0.5563, decode.d0.loss_cls: 1.5089, decode.d0.loss_mask: 0.4336, decode.d0.loss_dice: 0.6483, decode.d1.loss_cls: 0.2177, decode.d1.loss_mask: 0.4057, decode.d1.loss_dice: 0.6009, decode.d2.loss_cls: 0.1490, decode.d2.loss_mask: 0.3942, decode.d2.loss_dice: 0.5699, decode.d3.loss_cls: 0.1218, decode.d3.loss_mask: 0.3937, decode.d3.loss_dice: 0.5653, decode.d4.loss_cls: 0.1179, decode.d4.loss_mask: 0.3920, decode.d4.loss_dice: 0.5649, decode.d5.loss_cls: 0.1086, decode.d5.loss_mask: 0.3901, decode.d5.loss_dice: 0.5639, decode.d6.loss_cls: 0.1104, decode.d6.loss_mask: 0.3889, decode.d6.loss_dice: 0.5592, decode.d7.loss_cls: 0.1000, decode.d7.loss_mask: 0.3896, decode.d7.loss_dice: 0.5585, decode.d8.loss_cls: 0.1017, decode.d8.loss_mask: 0.3909, decode.d8.loss_dice: 0.5595, loss: 12.3527 +2022-05-06 07:08:31,892 - mmseg - INFO - Iter [28750/40000] lr: 4.039e-07, eta: 2:40:37, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1074, decode.loss_mask: 0.3957, decode.loss_dice: 0.5587, decode.d0.loss_cls: 1.5588, decode.d0.loss_mask: 0.4403, decode.d0.loss_dice: 0.6563, decode.d1.loss_cls: 0.2358, decode.d1.loss_mask: 0.4082, decode.d1.loss_dice: 0.5903, decode.d2.loss_cls: 0.1494, decode.d2.loss_mask: 0.4007, decode.d2.loss_dice: 0.5699, decode.d3.loss_cls: 0.1218, decode.d3.loss_mask: 0.4007, decode.d3.loss_dice: 0.5628, decode.d4.loss_cls: 0.1169, decode.d4.loss_mask: 0.3985, decode.d4.loss_dice: 0.5595, decode.d5.loss_cls: 0.1117, decode.d5.loss_mask: 0.3972, decode.d5.loss_dice: 0.5574, decode.d6.loss_cls: 0.1062, decode.d6.loss_mask: 0.3961, decode.d6.loss_dice: 0.5538, decode.d7.loss_cls: 0.1079, decode.d7.loss_mask: 0.3964, decode.d7.loss_dice: 0.5516, decode.d8.loss_cls: 0.1086, decode.d8.loss_mask: 0.3963, decode.d8.loss_dice: 0.5537, loss: 12.4685 +2022-05-06 07:09:05,120 - mmseg - INFO - Iter [28800/40000] lr: 4.021e-07, eta: 2:39:50, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0995, decode.loss_mask: 0.3973, decode.loss_dice: 0.5349, decode.d0.loss_cls: 1.5030, decode.d0.loss_mask: 0.4441, decode.d0.loss_dice: 0.6493, decode.d1.loss_cls: 0.2055, decode.d1.loss_mask: 0.4112, decode.d1.loss_dice: 0.5765, decode.d2.loss_cls: 0.1438, decode.d2.loss_mask: 0.4017, decode.d2.loss_dice: 0.5508, decode.d3.loss_cls: 0.1157, decode.d3.loss_mask: 0.3997, decode.d3.loss_dice: 0.5447, decode.d4.loss_cls: 0.1171, decode.d4.loss_mask: 0.3976, decode.d4.loss_dice: 0.5396, decode.d5.loss_cls: 0.1047, decode.d5.loss_mask: 0.3961, decode.d5.loss_dice: 0.5389, decode.d6.loss_cls: 0.1001, decode.d6.loss_mask: 0.3968, decode.d6.loss_dice: 0.5387, decode.d7.loss_cls: 0.0980, decode.d7.loss_mask: 0.3972, decode.d7.loss_dice: 0.5373, decode.d8.loss_cls: 0.0989, decode.d8.loss_mask: 0.3966, decode.d8.loss_dice: 0.5396, loss: 12.1750 +2022-05-06 07:09:38,880 - mmseg - INFO - Iter [28850/40000] lr: 4.003e-07, eta: 2:39:03, time: 0.675, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1045, decode.loss_mask: 0.3783, decode.loss_dice: 0.5498, decode.d0.loss_cls: 1.5447, decode.d0.loss_mask: 0.4180, decode.d0.loss_dice: 0.6412, decode.d1.loss_cls: 0.2078, decode.d1.loss_mask: 0.3946, decode.d1.loss_dice: 0.5874, decode.d2.loss_cls: 0.1399, decode.d2.loss_mask: 0.3839, decode.d2.loss_dice: 0.5666, decode.d3.loss_cls: 0.1183, decode.d3.loss_mask: 0.3807, decode.d3.loss_dice: 0.5556, decode.d4.loss_cls: 0.1102, decode.d4.loss_mask: 0.3783, decode.d4.loss_dice: 0.5544, decode.d5.loss_cls: 0.1016, decode.d5.loss_mask: 0.3802, decode.d5.loss_dice: 0.5561, decode.d6.loss_cls: 0.1008, decode.d6.loss_mask: 0.3796, decode.d6.loss_dice: 0.5528, decode.d7.loss_cls: 0.1058, decode.d7.loss_mask: 0.3790, decode.d7.loss_dice: 0.5461, decode.d8.loss_cls: 0.1069, decode.d8.loss_mask: 0.3787, decode.d8.loss_dice: 0.5478, loss: 12.1494 +2022-05-06 07:10:12,547 - mmseg - INFO - Iter [28900/40000] lr: 3.985e-07, eta: 2:38:16, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1038, decode.loss_mask: 0.3880, decode.loss_dice: 0.5489, decode.d0.loss_cls: 1.5589, decode.d0.loss_mask: 0.4235, decode.d0.loss_dice: 0.6407, decode.d1.loss_cls: 0.2141, decode.d1.loss_mask: 0.4042, decode.d1.loss_dice: 0.5882, decode.d2.loss_cls: 0.1461, decode.d2.loss_mask: 0.3947, decode.d2.loss_dice: 0.5610, decode.d3.loss_cls: 0.1169, decode.d3.loss_mask: 0.3931, decode.d3.loss_dice: 0.5580, decode.d4.loss_cls: 0.1074, decode.d4.loss_mask: 0.3891, decode.d4.loss_dice: 0.5589, decode.d5.loss_cls: 0.1049, decode.d5.loss_mask: 0.3881, decode.d5.loss_dice: 0.5541, decode.d6.loss_cls: 0.0989, decode.d6.loss_mask: 0.3898, decode.d6.loss_dice: 0.5510, decode.d7.loss_cls: 0.0983, decode.d7.loss_mask: 0.3883, decode.d7.loss_dice: 0.5519, decode.d8.loss_cls: 0.0999, decode.d8.loss_mask: 0.3896, decode.d8.loss_dice: 0.5552, loss: 12.2657 +2022-05-06 07:10:46,165 - mmseg - INFO - Iter [28950/40000] lr: 3.967e-07, eta: 2:37:29, time: 0.672, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0998, decode.loss_mask: 0.3864, decode.loss_dice: 0.5470, decode.d0.loss_cls: 1.4947, decode.d0.loss_mask: 0.4316, decode.d0.loss_dice: 0.6387, decode.d1.loss_cls: 0.2024, decode.d1.loss_mask: 0.4003, decode.d1.loss_dice: 0.5866, decode.d2.loss_cls: 0.1330, decode.d2.loss_mask: 0.3936, decode.d2.loss_dice: 0.5670, decode.d3.loss_cls: 0.1104, decode.d3.loss_mask: 0.3900, decode.d3.loss_dice: 0.5542, decode.d4.loss_cls: 0.1024, decode.d4.loss_mask: 0.3888, decode.d4.loss_dice: 0.5553, decode.d5.loss_cls: 0.1030, decode.d5.loss_mask: 0.3894, decode.d5.loss_dice: 0.5544, decode.d6.loss_cls: 0.1022, decode.d6.loss_mask: 0.3871, decode.d6.loss_dice: 0.5467, decode.d7.loss_cls: 0.0982, decode.d7.loss_mask: 0.3864, decode.d7.loss_dice: 0.5480, decode.d8.loss_cls: 0.0972, decode.d8.loss_mask: 0.3876, decode.d8.loss_dice: 0.5515, loss: 12.1341 +2022-05-06 07:11:22,235 - mmseg - INFO - Saving checkpoint at 29000 iterations +2022-05-06 07:11:49,510 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 07:11:49,513 - mmseg - INFO - Iter [29000/40000] lr: 3.949e-07, eta: 2:36:55, time: 1.265, data_time: 0.057, memory: 53770, decode.loss_cls: 0.0971, decode.loss_mask: 0.3846, decode.loss_dice: 0.5397, decode.d0.loss_cls: 1.4668, decode.d0.loss_mask: 0.4286, decode.d0.loss_dice: 0.6279, decode.d1.loss_cls: 0.2016, decode.d1.loss_mask: 0.4006, decode.d1.loss_dice: 0.5677, decode.d2.loss_cls: 0.1421, decode.d2.loss_mask: 0.3920, decode.d2.loss_dice: 0.5560, decode.d3.loss_cls: 0.1131, decode.d3.loss_mask: 0.3881, decode.d3.loss_dice: 0.5446, decode.d4.loss_cls: 0.1074, decode.d4.loss_mask: 0.3875, decode.d4.loss_dice: 0.5472, decode.d5.loss_cls: 0.0993, decode.d5.loss_mask: 0.3876, decode.d5.loss_dice: 0.5463, decode.d6.loss_cls: 0.0972, decode.d6.loss_mask: 0.3873, decode.d6.loss_dice: 0.5434, decode.d7.loss_cls: 0.1038, decode.d7.loss_mask: 0.3852, decode.d7.loss_dice: 0.5412, decode.d8.loss_cls: 0.0988, decode.d8.loss_mask: 0.3848, decode.d8.loss_dice: 0.5398, loss: 12.0072 +2022-05-06 07:12:24,135 - mmseg - INFO - Iter [29050/40000] lr: 3.931e-07, eta: 2:36:09, time: 0.695, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1140, decode.loss_mask: 0.3855, decode.loss_dice: 0.5668, decode.d0.loss_cls: 1.5574, decode.d0.loss_mask: 0.4221, decode.d0.loss_dice: 0.6608, decode.d1.loss_cls: 0.2257, decode.d1.loss_mask: 0.3974, decode.d1.loss_dice: 0.6041, decode.d2.loss_cls: 0.1570, decode.d2.loss_mask: 0.3893, decode.d2.loss_dice: 0.5795, decode.d3.loss_cls: 0.1314, decode.d3.loss_mask: 0.3866, decode.d3.loss_dice: 0.5694, decode.d4.loss_cls: 0.1253, decode.d4.loss_mask: 0.3856, decode.d4.loss_dice: 0.5721, decode.d5.loss_cls: 0.1204, decode.d5.loss_mask: 0.3857, decode.d5.loss_dice: 0.5697, decode.d6.loss_cls: 0.1196, decode.d6.loss_mask: 0.3860, decode.d6.loss_dice: 0.5677, decode.d7.loss_cls: 0.1134, decode.d7.loss_mask: 0.3857, decode.d7.loss_dice: 0.5685, decode.d8.loss_cls: 0.1164, decode.d8.loss_mask: 0.3865, decode.d8.loss_dice: 0.5655, loss: 12.5152 +2022-05-06 07:12:57,830 - mmseg - INFO - Iter [29100/40000] lr: 3.913e-07, eta: 2:35:22, time: 0.674, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0984, decode.loss_mask: 0.3981, decode.loss_dice: 0.5182, decode.d0.loss_cls: 1.4831, decode.d0.loss_mask: 0.4464, decode.d0.loss_dice: 0.6143, decode.d1.loss_cls: 0.1887, decode.d1.loss_mask: 0.4142, decode.d1.loss_dice: 0.5525, decode.d2.loss_cls: 0.1302, decode.d2.loss_mask: 0.4025, decode.d2.loss_dice: 0.5378, decode.d3.loss_cls: 0.1160, decode.d3.loss_mask: 0.3996, decode.d3.loss_dice: 0.5224, decode.d4.loss_cls: 0.1052, decode.d4.loss_mask: 0.3998, decode.d4.loss_dice: 0.5272, decode.d5.loss_cls: 0.1030, decode.d5.loss_mask: 0.3983, decode.d5.loss_dice: 0.5220, decode.d6.loss_cls: 0.0968, decode.d6.loss_mask: 0.3984, decode.d6.loss_dice: 0.5240, decode.d7.loss_cls: 0.0962, decode.d7.loss_mask: 0.3969, decode.d7.loss_dice: 0.5202, decode.d8.loss_cls: 0.0950, decode.d8.loss_mask: 0.3958, decode.d8.loss_dice: 0.5189, loss: 11.9201 +2022-05-06 07:13:31,404 - mmseg - INFO - Iter [29150/40000] lr: 3.895e-07, eta: 2:34:36, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1123, decode.loss_mask: 0.3942, decode.loss_dice: 0.5534, decode.d0.loss_cls: 1.5319, decode.d0.loss_mask: 0.4405, decode.d0.loss_dice: 0.6614, decode.d1.loss_cls: 0.2214, decode.d1.loss_mask: 0.4075, decode.d1.loss_dice: 0.5894, decode.d2.loss_cls: 0.1521, decode.d2.loss_mask: 0.4004, decode.d2.loss_dice: 0.5700, decode.d3.loss_cls: 0.1257, decode.d3.loss_mask: 0.3957, decode.d3.loss_dice: 0.5573, decode.d4.loss_cls: 0.1172, decode.d4.loss_mask: 0.3939, decode.d4.loss_dice: 0.5562, decode.d5.loss_cls: 0.1134, decode.d5.loss_mask: 0.3943, decode.d5.loss_dice: 0.5595, decode.d6.loss_cls: 0.1109, decode.d6.loss_mask: 0.3939, decode.d6.loss_dice: 0.5578, decode.d7.loss_cls: 0.1073, decode.d7.loss_mask: 0.3944, decode.d7.loss_dice: 0.5536, decode.d8.loss_cls: 0.1123, decode.d8.loss_mask: 0.3937, decode.d8.loss_dice: 0.5569, loss: 12.4284 +2022-05-06 07:14:05,411 - mmseg - INFO - Iter [29200/40000] lr: 3.877e-07, eta: 2:33:49, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1306, decode.loss_mask: 0.3912, decode.loss_dice: 0.5594, decode.d0.loss_cls: 1.5891, decode.d0.loss_mask: 0.4368, decode.d0.loss_dice: 0.6751, decode.d1.loss_cls: 0.2497, decode.d1.loss_mask: 0.4059, decode.d1.loss_dice: 0.6018, decode.d2.loss_cls: 0.1694, decode.d2.loss_mask: 0.3987, decode.d2.loss_dice: 0.5789, decode.d3.loss_cls: 0.1455, decode.d3.loss_mask: 0.3945, decode.d3.loss_dice: 0.5656, decode.d4.loss_cls: 0.1411, decode.d4.loss_mask: 0.3950, decode.d4.loss_dice: 0.5696, decode.d5.loss_cls: 0.1338, decode.d5.loss_mask: 0.3927, decode.d5.loss_dice: 0.5659, decode.d6.loss_cls: 0.1307, decode.d6.loss_mask: 0.3930, decode.d6.loss_dice: 0.5653, decode.d7.loss_cls: 0.1308, decode.d7.loss_mask: 0.3919, decode.d7.loss_dice: 0.5606, decode.d8.loss_cls: 0.1328, decode.d8.loss_mask: 0.3905, decode.d8.loss_dice: 0.5587, loss: 12.7448 +2022-05-06 07:14:38,802 - mmseg - INFO - Iter [29250/40000] lr: 3.859e-07, eta: 2:33:02, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1000, decode.loss_mask: 0.3902, decode.loss_dice: 0.5345, decode.d0.loss_cls: 1.4873, decode.d0.loss_mask: 0.4367, decode.d0.loss_dice: 0.6280, decode.d1.loss_cls: 0.2048, decode.d1.loss_mask: 0.4080, decode.d1.loss_dice: 0.5711, decode.d2.loss_cls: 0.1471, decode.d2.loss_mask: 0.3942, decode.d2.loss_dice: 0.5439, decode.d3.loss_cls: 0.1197, decode.d3.loss_mask: 0.3915, decode.d3.loss_dice: 0.5395, decode.d4.loss_cls: 0.1084, decode.d4.loss_mask: 0.3935, decode.d4.loss_dice: 0.5414, decode.d5.loss_cls: 0.1075, decode.d5.loss_mask: 0.3930, decode.d5.loss_dice: 0.5340, decode.d6.loss_cls: 0.1065, decode.d6.loss_mask: 0.3900, decode.d6.loss_dice: 0.5367, decode.d7.loss_cls: 0.1070, decode.d7.loss_mask: 0.3899, decode.d7.loss_dice: 0.5355, decode.d8.loss_cls: 0.1028, decode.d8.loss_mask: 0.3903, decode.d8.loss_dice: 0.5351, loss: 12.0678 +2022-05-06 07:15:15,099 - mmseg - INFO - Iter [29300/40000] lr: 3.841e-07, eta: 2:32:17, time: 0.726, data_time: 0.061, memory: 53770, decode.loss_cls: 0.1075, decode.loss_mask: 0.3831, decode.loss_dice: 0.5486, decode.d0.loss_cls: 1.5250, decode.d0.loss_mask: 0.4280, decode.d0.loss_dice: 0.6489, decode.d1.loss_cls: 0.2278, decode.d1.loss_mask: 0.3995, decode.d1.loss_dice: 0.5858, decode.d2.loss_cls: 0.1427, decode.d2.loss_mask: 0.3914, decode.d2.loss_dice: 0.5649, decode.d3.loss_cls: 0.1295, decode.d3.loss_mask: 0.3869, decode.d3.loss_dice: 0.5509, decode.d4.loss_cls: 0.1218, decode.d4.loss_mask: 0.3843, decode.d4.loss_dice: 0.5515, decode.d5.loss_cls: 0.1135, decode.d5.loss_mask: 0.3838, decode.d5.loss_dice: 0.5527, decode.d6.loss_cls: 0.1084, decode.d6.loss_mask: 0.3825, decode.d6.loss_dice: 0.5468, decode.d7.loss_cls: 0.1089, decode.d7.loss_mask: 0.3838, decode.d7.loss_dice: 0.5496, decode.d8.loss_cls: 0.1098, decode.d8.loss_mask: 0.3828, decode.d8.loss_dice: 0.5461, loss: 12.2470 +2022-05-06 07:15:49,201 - mmseg - INFO - Iter [29350/40000] lr: 3.823e-07, eta: 2:31:31, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1100, decode.loss_mask: 0.3918, decode.loss_dice: 0.5704, decode.d0.loss_cls: 1.5164, decode.d0.loss_mask: 0.4313, decode.d0.loss_dice: 0.6725, decode.d1.loss_cls: 0.2219, decode.d1.loss_mask: 0.4065, decode.d1.loss_dice: 0.6080, decode.d2.loss_cls: 0.1550, decode.d2.loss_mask: 0.3975, decode.d2.loss_dice: 0.5837, decode.d3.loss_cls: 0.1287, decode.d3.loss_mask: 0.3939, decode.d3.loss_dice: 0.5756, decode.d4.loss_cls: 0.1248, decode.d4.loss_mask: 0.3942, decode.d4.loss_dice: 0.5755, decode.d5.loss_cls: 0.1172, decode.d5.loss_mask: 0.3928, decode.d5.loss_dice: 0.5732, decode.d6.loss_cls: 0.1110, decode.d6.loss_mask: 0.3908, decode.d6.loss_dice: 0.5731, decode.d7.loss_cls: 0.1081, decode.d7.loss_mask: 0.3908, decode.d7.loss_dice: 0.5710, decode.d8.loss_cls: 0.1120, decode.d8.loss_mask: 0.3897, decode.d8.loss_dice: 0.5697, loss: 12.5570 +2022-05-06 07:16:22,927 - mmseg - INFO - Iter [29400/40000] lr: 3.805e-07, eta: 2:30:44, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1032, decode.loss_mask: 0.4044, decode.loss_dice: 0.5601, decode.d0.loss_cls: 1.5059, decode.d0.loss_mask: 0.4464, decode.d0.loss_dice: 0.6576, decode.d1.loss_cls: 0.2263, decode.d1.loss_mask: 0.4171, decode.d1.loss_dice: 0.5969, decode.d2.loss_cls: 0.1554, decode.d2.loss_mask: 0.4114, decode.d2.loss_dice: 0.5733, decode.d3.loss_cls: 0.1229, decode.d3.loss_mask: 0.4081, decode.d3.loss_dice: 0.5654, decode.d4.loss_cls: 0.1155, decode.d4.loss_mask: 0.4025, decode.d4.loss_dice: 0.5604, decode.d5.loss_cls: 0.1063, decode.d5.loss_mask: 0.4049, decode.d5.loss_dice: 0.5620, decode.d6.loss_cls: 0.1055, decode.d6.loss_mask: 0.4044, decode.d6.loss_dice: 0.5585, decode.d7.loss_cls: 0.1076, decode.d7.loss_mask: 0.4052, decode.d7.loss_dice: 0.5594, decode.d8.loss_cls: 0.0994, decode.d8.loss_mask: 0.4044, decode.d8.loss_dice: 0.5571, loss: 12.5076 +2022-05-06 07:16:56,685 - mmseg - INFO - Iter [29450/40000] lr: 3.787e-07, eta: 2:29:58, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0984, decode.loss_mask: 0.3927, decode.loss_dice: 0.5322, decode.d0.loss_cls: 1.5171, decode.d0.loss_mask: 0.4340, decode.d0.loss_dice: 0.6321, decode.d1.loss_cls: 0.2089, decode.d1.loss_mask: 0.4130, decode.d1.loss_dice: 0.5761, decode.d2.loss_cls: 0.1443, decode.d2.loss_mask: 0.4009, decode.d2.loss_dice: 0.5463, decode.d3.loss_cls: 0.1078, decode.d3.loss_mask: 0.3985, decode.d3.loss_dice: 0.5426, decode.d4.loss_cls: 0.0997, decode.d4.loss_mask: 0.3947, decode.d4.loss_dice: 0.5401, decode.d5.loss_cls: 0.0972, decode.d5.loss_mask: 0.3944, decode.d5.loss_dice: 0.5391, decode.d6.loss_cls: 0.0950, decode.d6.loss_mask: 0.3931, decode.d6.loss_dice: 0.5342, decode.d7.loss_cls: 0.0981, decode.d7.loss_mask: 0.3926, decode.d7.loss_dice: 0.5338, decode.d8.loss_cls: 0.0952, decode.d8.loss_mask: 0.3920, decode.d8.loss_dice: 0.5346, loss: 12.0787 +2022-05-06 07:17:30,885 - mmseg - INFO - Iter [29500/40000] lr: 3.769e-07, eta: 2:29:12, time: 0.684, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1027, decode.loss_mask: 0.3632, decode.loss_dice: 0.5140, decode.d0.loss_cls: 1.4986, decode.d0.loss_mask: 0.3999, decode.d0.loss_dice: 0.6077, decode.d1.loss_cls: 0.2172, decode.d1.loss_mask: 0.3749, decode.d1.loss_dice: 0.5487, decode.d2.loss_cls: 0.1476, decode.d2.loss_mask: 0.3681, decode.d2.loss_dice: 0.5298, decode.d3.loss_cls: 0.1227, decode.d3.loss_mask: 0.3650, decode.d3.loss_dice: 0.5179, decode.d4.loss_cls: 0.1143, decode.d4.loss_mask: 0.3650, decode.d4.loss_dice: 0.5197, decode.d5.loss_cls: 0.1116, decode.d5.loss_mask: 0.3632, decode.d5.loss_dice: 0.5167, decode.d6.loss_cls: 0.1069, decode.d6.loss_mask: 0.3641, decode.d6.loss_dice: 0.5129, decode.d7.loss_cls: 0.1075, decode.d7.loss_mask: 0.3630, decode.d7.loss_dice: 0.5109, decode.d8.loss_cls: 0.1047, decode.d8.loss_mask: 0.3626, decode.d8.loss_dice: 0.5107, loss: 11.6119 +2022-05-06 07:18:04,305 - mmseg - INFO - Iter [29550/40000] lr: 3.751e-07, eta: 2:28:25, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0996, decode.loss_mask: 0.3868, decode.loss_dice: 0.5559, decode.d0.loss_cls: 1.5291, decode.d0.loss_mask: 0.4314, decode.d0.loss_dice: 0.6557, decode.d1.loss_cls: 0.2035, decode.d1.loss_mask: 0.3983, decode.d1.loss_dice: 0.5895, decode.d2.loss_cls: 0.1441, decode.d2.loss_mask: 0.3894, decode.d2.loss_dice: 0.5691, decode.d3.loss_cls: 0.1211, decode.d3.loss_mask: 0.3876, decode.d3.loss_dice: 0.5611, decode.d4.loss_cls: 0.1115, decode.d4.loss_mask: 0.3874, decode.d4.loss_dice: 0.5556, decode.d5.loss_cls: 0.1077, decode.d5.loss_mask: 0.3872, decode.d5.loss_dice: 0.5541, decode.d6.loss_cls: 0.1068, decode.d6.loss_mask: 0.3873, decode.d6.loss_dice: 0.5539, decode.d7.loss_cls: 0.1032, decode.d7.loss_mask: 0.3870, decode.d7.loss_dice: 0.5507, decode.d8.loss_cls: 0.1050, decode.d8.loss_mask: 0.3859, decode.d8.loss_dice: 0.5485, loss: 12.2539 +2022-05-06 07:18:40,137 - mmseg - INFO - Iter [29600/40000] lr: 3.733e-07, eta: 2:27:40, time: 0.717, data_time: 0.057, memory: 53770, decode.loss_cls: 0.0993, decode.loss_mask: 0.4011, decode.loss_dice: 0.5535, decode.d0.loss_cls: 1.5016, decode.d0.loss_mask: 0.4435, decode.d0.loss_dice: 0.6446, decode.d1.loss_cls: 0.2009, decode.d1.loss_mask: 0.4145, decode.d1.loss_dice: 0.5812, decode.d2.loss_cls: 0.1390, decode.d2.loss_mask: 0.4075, decode.d2.loss_dice: 0.5669, decode.d3.loss_cls: 0.1158, decode.d3.loss_mask: 0.4052, decode.d3.loss_dice: 0.5614, decode.d4.loss_cls: 0.1050, decode.d4.loss_mask: 0.4030, decode.d4.loss_dice: 0.5606, decode.d5.loss_cls: 0.1027, decode.d5.loss_mask: 0.4026, decode.d5.loss_dice: 0.5547, decode.d6.loss_cls: 0.0954, decode.d6.loss_mask: 0.4022, decode.d6.loss_dice: 0.5494, decode.d7.loss_cls: 0.1010, decode.d7.loss_mask: 0.4013, decode.d7.loss_dice: 0.5494, decode.d8.loss_cls: 0.0973, decode.d8.loss_mask: 0.4021, decode.d8.loss_dice: 0.5511, loss: 12.3138 +2022-05-06 07:19:14,101 - mmseg - INFO - Iter [29650/40000] lr: 3.715e-07, eta: 2:26:54, time: 0.679, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0965, decode.loss_mask: 0.3798, decode.loss_dice: 0.5344, decode.d0.loss_cls: 1.4910, decode.d0.loss_mask: 0.4256, decode.d0.loss_dice: 0.6356, decode.d1.loss_cls: 0.2181, decode.d1.loss_mask: 0.3922, decode.d1.loss_dice: 0.5643, decode.d2.loss_cls: 0.1422, decode.d2.loss_mask: 0.3872, decode.d2.loss_dice: 0.5494, decode.d3.loss_cls: 0.1173, decode.d3.loss_mask: 0.3841, decode.d3.loss_dice: 0.5398, decode.d4.loss_cls: 0.1034, decode.d4.loss_mask: 0.3819, decode.d4.loss_dice: 0.5400, decode.d5.loss_cls: 0.0928, decode.d5.loss_mask: 0.3821, decode.d5.loss_dice: 0.5402, decode.d6.loss_cls: 0.0976, decode.d6.loss_mask: 0.3815, decode.d6.loss_dice: 0.5337, decode.d7.loss_cls: 0.0909, decode.d7.loss_mask: 0.3809, decode.d7.loss_dice: 0.5354, decode.d8.loss_cls: 0.0925, decode.d8.loss_mask: 0.3809, decode.d8.loss_dice: 0.5372, loss: 11.9284 +2022-05-06 07:19:47,814 - mmseg - INFO - Iter [29700/40000] lr: 3.698e-07, eta: 2:26:08, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1201, decode.loss_mask: 0.3866, decode.loss_dice: 0.5541, decode.d0.loss_cls: 1.5444, decode.d0.loss_mask: 0.4316, decode.d0.loss_dice: 0.6588, decode.d1.loss_cls: 0.2177, decode.d1.loss_mask: 0.4040, decode.d1.loss_dice: 0.5998, decode.d2.loss_cls: 0.1527, decode.d2.loss_mask: 0.3980, decode.d2.loss_dice: 0.5777, decode.d3.loss_cls: 0.1315, decode.d3.loss_mask: 0.3900, decode.d3.loss_dice: 0.5623, decode.d4.loss_cls: 0.1279, decode.d4.loss_mask: 0.3890, decode.d4.loss_dice: 0.5630, decode.d5.loss_cls: 0.1184, decode.d5.loss_mask: 0.3866, decode.d5.loss_dice: 0.5550, decode.d6.loss_cls: 0.1197, decode.d6.loss_mask: 0.3893, decode.d6.loss_dice: 0.5586, decode.d7.loss_cls: 0.1183, decode.d7.loss_mask: 0.3867, decode.d7.loss_dice: 0.5559, decode.d8.loss_cls: 0.1149, decode.d8.loss_mask: 0.3866, decode.d8.loss_dice: 0.5561, loss: 12.4555 +2022-05-06 07:20:21,613 - mmseg - INFO - Iter [29750/40000] lr: 3.680e-07, eta: 2:25:22, time: 0.676, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1016, decode.loss_mask: 0.3914, decode.loss_dice: 0.5311, decode.d0.loss_cls: 1.4992, decode.d0.loss_mask: 0.4303, decode.d0.loss_dice: 0.6364, decode.d1.loss_cls: 0.2117, decode.d1.loss_mask: 0.4049, decode.d1.loss_dice: 0.5643, decode.d2.loss_cls: 0.1460, decode.d2.loss_mask: 0.3947, decode.d2.loss_dice: 0.5462, decode.d3.loss_cls: 0.1204, decode.d3.loss_mask: 0.3940, decode.d3.loss_dice: 0.5385, decode.d4.loss_cls: 0.1078, decode.d4.loss_mask: 0.3945, decode.d4.loss_dice: 0.5359, decode.d5.loss_cls: 0.1034, decode.d5.loss_mask: 0.3930, decode.d5.loss_dice: 0.5306, decode.d6.loss_cls: 0.1039, decode.d6.loss_mask: 0.3912, decode.d6.loss_dice: 0.5310, decode.d7.loss_cls: 0.1022, decode.d7.loss_mask: 0.3924, decode.d7.loss_dice: 0.5306, decode.d8.loss_cls: 0.1031, decode.d8.loss_mask: 0.3939, decode.d8.loss_dice: 0.5341, loss: 12.0583 +2022-05-06 07:20:55,372 - mmseg - INFO - Iter [29800/40000] lr: 3.662e-07, eta: 2:24:36, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0897, decode.loss_mask: 0.3930, decode.loss_dice: 0.5416, decode.d0.loss_cls: 1.5028, decode.d0.loss_mask: 0.4326, decode.d0.loss_dice: 0.6260, decode.d1.loss_cls: 0.1947, decode.d1.loss_mask: 0.4046, decode.d1.loss_dice: 0.5687, decode.d2.loss_cls: 0.1392, decode.d2.loss_mask: 0.3975, decode.d2.loss_dice: 0.5478, decode.d3.loss_cls: 0.1027, decode.d3.loss_mask: 0.3956, decode.d3.loss_dice: 0.5395, decode.d4.loss_cls: 0.0983, decode.d4.loss_mask: 0.3943, decode.d4.loss_dice: 0.5418, decode.d5.loss_cls: 0.0950, decode.d5.loss_mask: 0.3939, decode.d5.loss_dice: 0.5413, decode.d6.loss_cls: 0.0886, decode.d6.loss_mask: 0.3944, decode.d6.loss_dice: 0.5374, decode.d7.loss_cls: 0.0908, decode.d7.loss_mask: 0.3934, decode.d7.loss_dice: 0.5374, decode.d8.loss_cls: 0.0944, decode.d8.loss_mask: 0.3924, decode.d8.loss_dice: 0.5390, loss: 12.0085 +2022-05-06 07:21:29,019 - mmseg - INFO - Iter [29850/40000] lr: 3.644e-07, eta: 2:23:50, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0966, decode.loss_mask: 0.3881, decode.loss_dice: 0.5445, decode.d0.loss_cls: 1.5075, decode.d0.loss_mask: 0.4253, decode.d0.loss_dice: 0.6391, decode.d1.loss_cls: 0.2020, decode.d1.loss_mask: 0.3993, decode.d1.loss_dice: 0.5792, decode.d2.loss_cls: 0.1345, decode.d2.loss_mask: 0.3913, decode.d2.loss_dice: 0.5552, decode.d3.loss_cls: 0.1077, decode.d3.loss_mask: 0.3896, decode.d3.loss_dice: 0.5458, decode.d4.loss_cls: 0.1012, decode.d4.loss_mask: 0.3896, decode.d4.loss_dice: 0.5452, decode.d5.loss_cls: 0.0980, decode.d5.loss_mask: 0.3886, decode.d5.loss_dice: 0.5441, decode.d6.loss_cls: 0.0891, decode.d6.loss_mask: 0.3881, decode.d6.loss_dice: 0.5445, decode.d7.loss_cls: 0.0924, decode.d7.loss_mask: 0.3877, decode.d7.loss_dice: 0.5431, decode.d8.loss_cls: 0.0877, decode.d8.loss_mask: 0.3884, decode.d8.loss_dice: 0.5449, loss: 12.0385 +2022-05-06 07:22:05,280 - mmseg - INFO - Iter [29900/40000] lr: 3.626e-07, eta: 2:23:05, time: 0.725, data_time: 0.058, memory: 53770, decode.loss_cls: 0.1133, decode.loss_mask: 0.4004, decode.loss_dice: 0.5368, decode.d0.loss_cls: 1.5176, decode.d0.loss_mask: 0.4438, decode.d0.loss_dice: 0.6288, decode.d1.loss_cls: 0.2318, decode.d1.loss_mask: 0.4111, decode.d1.loss_dice: 0.5649, decode.d2.loss_cls: 0.1567, decode.d2.loss_mask: 0.4050, decode.d2.loss_dice: 0.5515, decode.d3.loss_cls: 0.1280, decode.d3.loss_mask: 0.4043, decode.d3.loss_dice: 0.5427, decode.d4.loss_cls: 0.1221, decode.d4.loss_mask: 0.4014, decode.d4.loss_dice: 0.5394, decode.d5.loss_cls: 0.1187, decode.d5.loss_mask: 0.4003, decode.d5.loss_dice: 0.5382, decode.d6.loss_cls: 0.1134, decode.d6.loss_mask: 0.3997, decode.d6.loss_dice: 0.5356, decode.d7.loss_cls: 0.1180, decode.d7.loss_mask: 0.3987, decode.d7.loss_dice: 0.5336, decode.d8.loss_cls: 0.1111, decode.d8.loss_mask: 0.4012, decode.d8.loss_dice: 0.5386, loss: 12.3067 +2022-05-06 07:22:39,005 - mmseg - INFO - Iter [29950/40000] lr: 3.608e-07, eta: 2:22:19, time: 0.674, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1049, decode.loss_mask: 0.4002, decode.loss_dice: 0.5516, decode.d0.loss_cls: 1.5444, decode.d0.loss_mask: 0.4413, decode.d0.loss_dice: 0.6432, decode.d1.loss_cls: 0.2124, decode.d1.loss_mask: 0.4152, decode.d1.loss_dice: 0.5776, decode.d2.loss_cls: 0.1462, decode.d2.loss_mask: 0.4049, decode.d2.loss_dice: 0.5620, decode.d3.loss_cls: 0.1240, decode.d3.loss_mask: 0.4033, decode.d3.loss_dice: 0.5531, decode.d4.loss_cls: 0.1109, decode.d4.loss_mask: 0.4017, decode.d4.loss_dice: 0.5508, decode.d5.loss_cls: 0.1086, decode.d5.loss_mask: 0.4008, decode.d5.loss_dice: 0.5490, decode.d6.loss_cls: 0.1048, decode.d6.loss_mask: 0.4009, decode.d6.loss_dice: 0.5451, decode.d7.loss_cls: 0.0974, decode.d7.loss_mask: 0.4008, decode.d7.loss_dice: 0.5467, decode.d8.loss_cls: 0.0996, decode.d8.loss_mask: 0.4008, decode.d8.loss_dice: 0.5456, loss: 12.3480 +2022-05-06 07:23:12,581 - mmseg - INFO - Saving checkpoint at 30000 iterations +2022-05-06 07:23:40,201 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 07:23:40,208 - mmseg - INFO - Iter [30000/40000] lr: 3.590e-07, eta: 2:21:44, time: 1.222, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0921, decode.loss_mask: 0.3828, decode.loss_dice: 0.5351, decode.d0.loss_cls: 1.4881, decode.d0.loss_mask: 0.4245, decode.d0.loss_dice: 0.6239, decode.d1.loss_cls: 0.1999, decode.d1.loss_mask: 0.3980, decode.d1.loss_dice: 0.5723, decode.d2.loss_cls: 0.1356, decode.d2.loss_mask: 0.3866, decode.d2.loss_dice: 0.5501, decode.d3.loss_cls: 0.1111, decode.d3.loss_mask: 0.3862, decode.d3.loss_dice: 0.5401, decode.d4.loss_cls: 0.1051, decode.d4.loss_mask: 0.3845, decode.d4.loss_dice: 0.5368, decode.d5.loss_cls: 0.1020, decode.d5.loss_mask: 0.3833, decode.d5.loss_dice: 0.5375, decode.d6.loss_cls: 0.0955, decode.d6.loss_mask: 0.3844, decode.d6.loss_dice: 0.5377, decode.d7.loss_cls: 0.0948, decode.d7.loss_mask: 0.3842, decode.d7.loss_dice: 0.5363, decode.d8.loss_cls: 0.0951, decode.d8.loss_mask: 0.3832, decode.d8.loss_dice: 0.5369, loss: 11.9236 +2022-05-06 07:24:14,280 - mmseg - INFO - Iter [30050/40000] lr: 3.572e-07, eta: 2:20:58, time: 0.683, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1025, decode.loss_mask: 0.3802, decode.loss_dice: 0.5610, decode.d0.loss_cls: 1.5187, decode.d0.loss_mask: 0.4232, decode.d0.loss_dice: 0.6529, decode.d1.loss_cls: 0.2127, decode.d1.loss_mask: 0.3953, decode.d1.loss_dice: 0.5984, decode.d2.loss_cls: 0.1448, decode.d2.loss_mask: 0.3852, decode.d2.loss_dice: 0.5781, decode.d3.loss_cls: 0.1200, decode.d3.loss_mask: 0.3822, decode.d3.loss_dice: 0.5648, decode.d4.loss_cls: 0.1106, decode.d4.loss_mask: 0.3822, decode.d4.loss_dice: 0.5646, decode.d5.loss_cls: 0.1034, decode.d5.loss_mask: 0.3822, decode.d5.loss_dice: 0.5625, decode.d6.loss_cls: 0.0967, decode.d6.loss_mask: 0.3806, decode.d6.loss_dice: 0.5634, decode.d7.loss_cls: 0.0979, decode.d7.loss_mask: 0.3800, decode.d7.loss_dice: 0.5641, decode.d8.loss_cls: 0.1005, decode.d8.loss_mask: 0.3795, decode.d8.loss_dice: 0.5609, loss: 12.2490 +2022-05-06 07:24:47,699 - mmseg - INFO - Iter [30100/40000] lr: 3.554e-07, eta: 2:20:12, time: 0.669, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1057, decode.loss_mask: 0.3846, decode.loss_dice: 0.5430, decode.d0.loss_cls: 1.4839, decode.d0.loss_mask: 0.4281, decode.d0.loss_dice: 0.6431, decode.d1.loss_cls: 0.2134, decode.d1.loss_mask: 0.3992, decode.d1.loss_dice: 0.5762, decode.d2.loss_cls: 0.1466, decode.d2.loss_mask: 0.3922, decode.d2.loss_dice: 0.5572, decode.d3.loss_cls: 0.1326, decode.d3.loss_mask: 0.3859, decode.d3.loss_dice: 0.5440, decode.d4.loss_cls: 0.1236, decode.d4.loss_mask: 0.3859, decode.d4.loss_dice: 0.5446, decode.d5.loss_cls: 0.1152, decode.d5.loss_mask: 0.3854, decode.d5.loss_dice: 0.5488, decode.d6.loss_cls: 0.1087, decode.d6.loss_mask: 0.3833, decode.d6.loss_dice: 0.5425, decode.d7.loss_cls: 0.1051, decode.d7.loss_mask: 0.3839, decode.d7.loss_dice: 0.5391, decode.d8.loss_cls: 0.1099, decode.d8.loss_mask: 0.3845, decode.d8.loss_dice: 0.5438, loss: 12.1400 +2022-05-06 07:25:21,158 - mmseg - INFO - Iter [30150/40000] lr: 3.536e-07, eta: 2:19:26, time: 0.669, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0986, decode.loss_mask: 0.3952, decode.loss_dice: 0.5337, decode.d0.loss_cls: 1.4862, decode.d0.loss_mask: 0.4405, decode.d0.loss_dice: 0.6382, decode.d1.loss_cls: 0.2178, decode.d1.loss_mask: 0.4062, decode.d1.loss_dice: 0.5704, decode.d2.loss_cls: 0.1393, decode.d2.loss_mask: 0.3998, decode.d2.loss_dice: 0.5534, decode.d3.loss_cls: 0.1157, decode.d3.loss_mask: 0.3970, decode.d3.loss_dice: 0.5428, decode.d4.loss_cls: 0.1163, decode.d4.loss_mask: 0.3962, decode.d4.loss_dice: 0.5402, decode.d5.loss_cls: 0.1070, decode.d5.loss_mask: 0.3990, decode.d5.loss_dice: 0.5418, decode.d6.loss_cls: 0.1004, decode.d6.loss_mask: 0.3969, decode.d6.loss_dice: 0.5382, decode.d7.loss_cls: 0.0988, decode.d7.loss_mask: 0.3965, decode.d7.loss_dice: 0.5397, decode.d8.loss_cls: 0.0999, decode.d8.loss_mask: 0.3944, decode.d8.loss_dice: 0.5325, loss: 12.1326 +2022-05-06 07:25:54,849 - mmseg - INFO - Iter [30200/40000] lr: 3.518e-07, eta: 2:18:40, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0791, decode.loss_mask: 0.3949, decode.loss_dice: 0.5285, decode.d0.loss_cls: 1.4982, decode.d0.loss_mask: 0.4352, decode.d0.loss_dice: 0.6204, decode.d1.loss_cls: 0.1861, decode.d1.loss_mask: 0.4068, decode.d1.loss_dice: 0.5648, decode.d2.loss_cls: 0.1210, decode.d2.loss_mask: 0.4009, decode.d2.loss_dice: 0.5425, decode.d3.loss_cls: 0.0998, decode.d3.loss_mask: 0.3986, decode.d3.loss_dice: 0.5325, decode.d4.loss_cls: 0.0910, decode.d4.loss_mask: 0.3976, decode.d4.loss_dice: 0.5306, decode.d5.loss_cls: 0.0868, decode.d5.loss_mask: 0.3967, decode.d5.loss_dice: 0.5337, decode.d6.loss_cls: 0.0807, decode.d6.loss_mask: 0.3967, decode.d6.loss_dice: 0.5266, decode.d7.loss_cls: 0.0798, decode.d7.loss_mask: 0.3954, decode.d7.loss_dice: 0.5273, decode.d8.loss_cls: 0.0788, decode.d8.loss_mask: 0.3946, decode.d8.loss_dice: 0.5277, loss: 11.8534 +2022-05-06 07:26:30,918 - mmseg - INFO - Iter [30250/40000] lr: 3.500e-07, eta: 2:17:55, time: 0.721, data_time: 0.055, memory: 53770, decode.loss_cls: 0.0984, decode.loss_mask: 0.3769, decode.loss_dice: 0.5597, decode.d0.loss_cls: 1.5125, decode.d0.loss_mask: 0.4217, decode.d0.loss_dice: 0.6676, decode.d1.loss_cls: 0.2173, decode.d1.loss_mask: 0.3927, decode.d1.loss_dice: 0.5988, decode.d2.loss_cls: 0.1387, decode.d2.loss_mask: 0.3844, decode.d2.loss_dice: 0.5827, decode.d3.loss_cls: 0.1119, decode.d3.loss_mask: 0.3825, decode.d3.loss_dice: 0.5707, decode.d4.loss_cls: 0.1042, decode.d4.loss_mask: 0.3801, decode.d4.loss_dice: 0.5669, decode.d5.loss_cls: 0.0985, decode.d5.loss_mask: 0.3784, decode.d5.loss_dice: 0.5645, decode.d6.loss_cls: 0.0974, decode.d6.loss_mask: 0.3792, decode.d6.loss_dice: 0.5623, decode.d7.loss_cls: 0.0984, decode.d7.loss_mask: 0.3780, decode.d7.loss_dice: 0.5594, decode.d8.loss_cls: 0.0961, decode.d8.loss_mask: 0.3772, decode.d8.loss_dice: 0.5631, loss: 12.2202 +2022-05-06 07:27:05,121 - mmseg - INFO - Iter [30300/40000] lr: 3.482e-07, eta: 2:17:10, time: 0.684, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1065, decode.loss_mask: 0.3898, decode.loss_dice: 0.5544, decode.d0.loss_cls: 1.5241, decode.d0.loss_mask: 0.4279, decode.d0.loss_dice: 0.6500, decode.d1.loss_cls: 0.2187, decode.d1.loss_mask: 0.4043, decode.d1.loss_dice: 0.5918, decode.d2.loss_cls: 0.1465, decode.d2.loss_mask: 0.3952, decode.d2.loss_dice: 0.5737, decode.d3.loss_cls: 0.1250, decode.d3.loss_mask: 0.3933, decode.d3.loss_dice: 0.5604, decode.d4.loss_cls: 0.1199, decode.d4.loss_mask: 0.3901, decode.d4.loss_dice: 0.5605, decode.d5.loss_cls: 0.1142, decode.d5.loss_mask: 0.3904, decode.d5.loss_dice: 0.5584, decode.d6.loss_cls: 0.1069, decode.d6.loss_mask: 0.3888, decode.d6.loss_dice: 0.5559, decode.d7.loss_cls: 0.1083, decode.d7.loss_mask: 0.3890, decode.d7.loss_dice: 0.5529, decode.d8.loss_cls: 0.1035, decode.d8.loss_mask: 0.3892, decode.d8.loss_dice: 0.5564, loss: 12.3457 +2022-05-06 07:27:38,872 - mmseg - INFO - Iter [30350/40000] lr: 3.464e-07, eta: 2:16:24, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0896, decode.loss_mask: 0.3767, decode.loss_dice: 0.5371, decode.d0.loss_cls: 1.4794, decode.d0.loss_mask: 0.4169, decode.d0.loss_dice: 0.6283, decode.d1.loss_cls: 0.2176, decode.d1.loss_mask: 0.3919, decode.d1.loss_dice: 0.5685, decode.d2.loss_cls: 0.1351, decode.d2.loss_mask: 0.3826, decode.d2.loss_dice: 0.5517, decode.d3.loss_cls: 0.1091, decode.d3.loss_mask: 0.3813, decode.d3.loss_dice: 0.5460, decode.d4.loss_cls: 0.1046, decode.d4.loss_mask: 0.3803, decode.d4.loss_dice: 0.5447, decode.d5.loss_cls: 0.1012, decode.d5.loss_mask: 0.3781, decode.d5.loss_dice: 0.5414, decode.d6.loss_cls: 0.0908, decode.d6.loss_mask: 0.3774, decode.d6.loss_dice: 0.5399, decode.d7.loss_cls: 0.0908, decode.d7.loss_mask: 0.3767, decode.d7.loss_dice: 0.5407, decode.d8.loss_cls: 0.0905, decode.d8.loss_mask: 0.3774, decode.d8.loss_dice: 0.5386, loss: 11.8851 +2022-05-06 07:28:12,233 - mmseg - INFO - Iter [30400/40000] lr: 3.446e-07, eta: 2:15:39, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0998, decode.loss_mask: 0.3808, decode.loss_dice: 0.5303, decode.d0.loss_cls: 1.4912, decode.d0.loss_mask: 0.4244, decode.d0.loss_dice: 0.6365, decode.d1.loss_cls: 0.2092, decode.d1.loss_mask: 0.3951, decode.d1.loss_dice: 0.5648, decode.d2.loss_cls: 0.1399, decode.d2.loss_mask: 0.3868, decode.d2.loss_dice: 0.5502, decode.d3.loss_cls: 0.1215, decode.d3.loss_mask: 0.3837, decode.d3.loss_dice: 0.5387, decode.d4.loss_cls: 0.1124, decode.d4.loss_mask: 0.3817, decode.d4.loss_dice: 0.5391, decode.d5.loss_cls: 0.1075, decode.d5.loss_mask: 0.3797, decode.d5.loss_dice: 0.5364, decode.d6.loss_cls: 0.1013, decode.d6.loss_mask: 0.3811, decode.d6.loss_dice: 0.5350, decode.d7.loss_cls: 0.1001, decode.d7.loss_mask: 0.3806, decode.d7.loss_dice: 0.5313, decode.d8.loss_cls: 0.0961, decode.d8.loss_mask: 0.3814, decode.d8.loss_dice: 0.5356, loss: 11.9520 +2022-05-06 07:28:45,975 - mmseg - INFO - Iter [30450/40000] lr: 3.428e-07, eta: 2:14:53, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0917, decode.loss_mask: 0.3924, decode.loss_dice: 0.5474, decode.d0.loss_cls: 1.4742, decode.d0.loss_mask: 0.4364, decode.d0.loss_dice: 0.6415, decode.d1.loss_cls: 0.2017, decode.d1.loss_mask: 0.4074, decode.d1.loss_dice: 0.5838, decode.d2.loss_cls: 0.1291, decode.d2.loss_mask: 0.3985, decode.d2.loss_dice: 0.5624, decode.d3.loss_cls: 0.1093, decode.d3.loss_mask: 0.3947, decode.d3.loss_dice: 0.5541, decode.d4.loss_cls: 0.1037, decode.d4.loss_mask: 0.3943, decode.d4.loss_dice: 0.5530, decode.d5.loss_cls: 0.0945, decode.d5.loss_mask: 0.3943, decode.d5.loss_dice: 0.5517, decode.d6.loss_cls: 0.0890, decode.d6.loss_mask: 0.3945, decode.d6.loss_dice: 0.5480, decode.d7.loss_cls: 0.0869, decode.d7.loss_mask: 0.3950, decode.d7.loss_dice: 0.5494, decode.d8.loss_cls: 0.0901, decode.d8.loss_mask: 0.3942, decode.d8.loss_dice: 0.5477, loss: 12.1107 +2022-05-06 07:29:19,635 - mmseg - INFO - Iter [30500/40000] lr: 3.410e-07, eta: 2:14:08, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0968, decode.loss_mask: 0.3837, decode.loss_dice: 0.5348, decode.d0.loss_cls: 1.4637, decode.d0.loss_mask: 0.4230, decode.d0.loss_dice: 0.6338, decode.d1.loss_cls: 0.2061, decode.d1.loss_mask: 0.3949, decode.d1.loss_dice: 0.5696, decode.d2.loss_cls: 0.1369, decode.d2.loss_mask: 0.3884, decode.d2.loss_dice: 0.5555, decode.d3.loss_cls: 0.1098, decode.d3.loss_mask: 0.3869, decode.d3.loss_dice: 0.5411, decode.d4.loss_cls: 0.1016, decode.d4.loss_mask: 0.3842, decode.d4.loss_dice: 0.5423, decode.d5.loss_cls: 0.0982, decode.d5.loss_mask: 0.3844, decode.d5.loss_dice: 0.5383, decode.d6.loss_cls: 0.0953, decode.d6.loss_mask: 0.3829, decode.d6.loss_dice: 0.5358, decode.d7.loss_cls: 0.0949, decode.d7.loss_mask: 0.3837, decode.d7.loss_dice: 0.5371, decode.d8.loss_cls: 0.0919, decode.d8.loss_mask: 0.3828, decode.d8.loss_dice: 0.5348, loss: 11.9131 +2022-05-06 07:29:56,262 - mmseg - INFO - Iter [30550/40000] lr: 3.392e-07, eta: 2:13:23, time: 0.732, data_time: 0.061, memory: 53770, decode.loss_cls: 0.0961, decode.loss_mask: 0.3769, decode.loss_dice: 0.5447, decode.d0.loss_cls: 1.4909, decode.d0.loss_mask: 0.4151, decode.d0.loss_dice: 0.6385, decode.d1.loss_cls: 0.2115, decode.d1.loss_mask: 0.3900, decode.d1.loss_dice: 0.5791, decode.d2.loss_cls: 0.1349, decode.d2.loss_mask: 0.3864, decode.d2.loss_dice: 0.5634, decode.d3.loss_cls: 0.1169, decode.d3.loss_mask: 0.3816, decode.d3.loss_dice: 0.5528, decode.d4.loss_cls: 0.1063, decode.d4.loss_mask: 0.3811, decode.d4.loss_dice: 0.5530, decode.d5.loss_cls: 0.0975, decode.d5.loss_mask: 0.3804, decode.d5.loss_dice: 0.5524, decode.d6.loss_cls: 0.0935, decode.d6.loss_mask: 0.3788, decode.d6.loss_dice: 0.5503, decode.d7.loss_cls: 0.0953, decode.d7.loss_mask: 0.3784, decode.d7.loss_dice: 0.5472, decode.d8.loss_cls: 0.0940, decode.d8.loss_mask: 0.3774, decode.d8.loss_dice: 0.5463, loss: 12.0108 +2022-05-06 07:30:29,468 - mmseg - INFO - Iter [30600/40000] lr: 3.374e-07, eta: 2:12:38, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0892, decode.loss_mask: 0.3926, decode.loss_dice: 0.5308, decode.d0.loss_cls: 1.4688, decode.d0.loss_mask: 0.4345, decode.d0.loss_dice: 0.6133, decode.d1.loss_cls: 0.1740, decode.d1.loss_mask: 0.4048, decode.d1.loss_dice: 0.5571, decode.d2.loss_cls: 0.1264, decode.d2.loss_mask: 0.3986, decode.d2.loss_dice: 0.5435, decode.d3.loss_cls: 0.1017, decode.d3.loss_mask: 0.3962, decode.d3.loss_dice: 0.5373, decode.d4.loss_cls: 0.0945, decode.d4.loss_mask: 0.3954, decode.d4.loss_dice: 0.5335, decode.d5.loss_cls: 0.0934, decode.d5.loss_mask: 0.3934, decode.d5.loss_dice: 0.5346, decode.d6.loss_cls: 0.0908, decode.d6.loss_mask: 0.3940, decode.d6.loss_dice: 0.5307, decode.d7.loss_cls: 0.0862, decode.d7.loss_mask: 0.3920, decode.d7.loss_dice: 0.5275, decode.d8.loss_cls: 0.0817, decode.d8.loss_mask: 0.3930, decode.d8.loss_dice: 0.5306, loss: 11.8403 +2022-05-06 07:31:02,879 - mmseg - INFO - Iter [30650/40000] lr: 3.357e-07, eta: 2:11:52, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1094, decode.loss_mask: 0.3983, decode.loss_dice: 0.5553, decode.d0.loss_cls: 1.4979, decode.d0.loss_mask: 0.4443, decode.d0.loss_dice: 0.6550, decode.d1.loss_cls: 0.2074, decode.d1.loss_mask: 0.4106, decode.d1.loss_dice: 0.5828, decode.d2.loss_cls: 0.1587, decode.d2.loss_mask: 0.4036, decode.d2.loss_dice: 0.5711, decode.d3.loss_cls: 0.1253, decode.d3.loss_mask: 0.4005, decode.d3.loss_dice: 0.5593, decode.d4.loss_cls: 0.1157, decode.d4.loss_mask: 0.4013, decode.d4.loss_dice: 0.5569, decode.d5.loss_cls: 0.1123, decode.d5.loss_mask: 0.4003, decode.d5.loss_dice: 0.5588, decode.d6.loss_cls: 0.1090, decode.d6.loss_mask: 0.3988, decode.d6.loss_dice: 0.5512, decode.d7.loss_cls: 0.1084, decode.d7.loss_mask: 0.3987, decode.d7.loss_dice: 0.5543, decode.d8.loss_cls: 0.1105, decode.d8.loss_mask: 0.4000, decode.d8.loss_dice: 0.5541, loss: 12.4098 +2022-05-06 07:31:36,995 - mmseg - INFO - Iter [30700/40000] lr: 3.339e-07, eta: 2:11:07, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0883, decode.loss_mask: 0.3797, decode.loss_dice: 0.5357, decode.d0.loss_cls: 1.5266, decode.d0.loss_mask: 0.4222, decode.d0.loss_dice: 0.6285, decode.d1.loss_cls: 0.1978, decode.d1.loss_mask: 0.3935, decode.d1.loss_dice: 0.5640, decode.d2.loss_cls: 0.1332, decode.d2.loss_mask: 0.3846, decode.d2.loss_dice: 0.5462, decode.d3.loss_cls: 0.1090, decode.d3.loss_mask: 0.3816, decode.d3.loss_dice: 0.5410, decode.d4.loss_cls: 0.1050, decode.d4.loss_mask: 0.3821, decode.d4.loss_dice: 0.5367, decode.d5.loss_cls: 0.0955, decode.d5.loss_mask: 0.3813, decode.d5.loss_dice: 0.5389, decode.d6.loss_cls: 0.0916, decode.d6.loss_mask: 0.3807, decode.d6.loss_dice: 0.5338, decode.d7.loss_cls: 0.0853, decode.d7.loss_mask: 0.3813, decode.d7.loss_dice: 0.5353, decode.d8.loss_cls: 0.0868, decode.d8.loss_mask: 0.3804, decode.d8.loss_dice: 0.5366, loss: 11.8829 +2022-05-06 07:32:10,414 - mmseg - INFO - Iter [30750/40000] lr: 3.321e-07, eta: 2:10:22, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0856, decode.loss_mask: 0.3832, decode.loss_dice: 0.5441, decode.d0.loss_cls: 1.4629, decode.d0.loss_mask: 0.4307, decode.d0.loss_dice: 0.6397, decode.d1.loss_cls: 0.1957, decode.d1.loss_mask: 0.4010, decode.d1.loss_dice: 0.5801, decode.d2.loss_cls: 0.1246, decode.d2.loss_mask: 0.3921, decode.d2.loss_dice: 0.5614, decode.d3.loss_cls: 0.0997, decode.d3.loss_mask: 0.3880, decode.d3.loss_dice: 0.5492, decode.d4.loss_cls: 0.0960, decode.d4.loss_mask: 0.3857, decode.d4.loss_dice: 0.5497, decode.d5.loss_cls: 0.0872, decode.d5.loss_mask: 0.3877, decode.d5.loss_dice: 0.5499, decode.d6.loss_cls: 0.0856, decode.d6.loss_mask: 0.3862, decode.d6.loss_dice: 0.5447, decode.d7.loss_cls: 0.0857, decode.d7.loss_mask: 0.3862, decode.d7.loss_dice: 0.5439, decode.d8.loss_cls: 0.0871, decode.d8.loss_mask: 0.3847, decode.d8.loss_dice: 0.5487, loss: 11.9471 +2022-05-06 07:32:43,606 - mmseg - INFO - Iter [30800/40000] lr: 3.303e-07, eta: 2:09:36, time: 0.664, data_time: 0.011, memory: 53770, decode.loss_cls: 0.1045, decode.loss_mask: 0.3903, decode.loss_dice: 0.5306, decode.d0.loss_cls: 1.4883, decode.d0.loss_mask: 0.4299, decode.d0.loss_dice: 0.6308, decode.d1.loss_cls: 0.2137, decode.d1.loss_mask: 0.4052, decode.d1.loss_dice: 0.5717, decode.d2.loss_cls: 0.1427, decode.d2.loss_mask: 0.3981, decode.d2.loss_dice: 0.5502, decode.d3.loss_cls: 0.1217, decode.d3.loss_mask: 0.3955, decode.d3.loss_dice: 0.5391, decode.d4.loss_cls: 0.1133, decode.d4.loss_mask: 0.3945, decode.d4.loss_dice: 0.5375, decode.d5.loss_cls: 0.1103, decode.d5.loss_mask: 0.3935, decode.d5.loss_dice: 0.5344, decode.d6.loss_cls: 0.1082, decode.d6.loss_mask: 0.3910, decode.d6.loss_dice: 0.5298, decode.d7.loss_cls: 0.1052, decode.d7.loss_mask: 0.3922, decode.d7.loss_dice: 0.5314, decode.d8.loss_cls: 0.1052, decode.d8.loss_mask: 0.3899, decode.d8.loss_dice: 0.5331, loss: 12.0821 +2022-05-06 07:33:19,666 - mmseg - INFO - Iter [30850/40000] lr: 3.285e-07, eta: 2:08:52, time: 0.721, data_time: 0.056, memory: 53770, decode.loss_cls: 0.1004, decode.loss_mask: 0.3829, decode.loss_dice: 0.5311, decode.d0.loss_cls: 1.5233, decode.d0.loss_mask: 0.4258, decode.d0.loss_dice: 0.6416, decode.d1.loss_cls: 0.2247, decode.d1.loss_mask: 0.3992, decode.d1.loss_dice: 0.5730, decode.d2.loss_cls: 0.1486, decode.d2.loss_mask: 0.3892, decode.d2.loss_dice: 0.5487, decode.d3.loss_cls: 0.1251, decode.d3.loss_mask: 0.3874, decode.d3.loss_dice: 0.5427, decode.d4.loss_cls: 0.1137, decode.d4.loss_mask: 0.3871, decode.d4.loss_dice: 0.5416, decode.d5.loss_cls: 0.1107, decode.d5.loss_mask: 0.3865, decode.d5.loss_dice: 0.5384, decode.d6.loss_cls: 0.1050, decode.d6.loss_mask: 0.3848, decode.d6.loss_dice: 0.5363, decode.d7.loss_cls: 0.1050, decode.d7.loss_mask: 0.3834, decode.d7.loss_dice: 0.5388, decode.d8.loss_cls: 0.1035, decode.d8.loss_mask: 0.3824, decode.d8.loss_dice: 0.5338, loss: 12.0946 +2022-05-06 07:33:53,669 - mmseg - INFO - Iter [30900/40000] lr: 3.267e-07, eta: 2:08:07, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0911, decode.loss_mask: 0.3669, decode.loss_dice: 0.5130, decode.d0.loss_cls: 1.5083, decode.d0.loss_mask: 0.4046, decode.d0.loss_dice: 0.6084, decode.d1.loss_cls: 0.2056, decode.d1.loss_mask: 0.3772, decode.d1.loss_dice: 0.5455, decode.d2.loss_cls: 0.1279, decode.d2.loss_mask: 0.3705, decode.d2.loss_dice: 0.5256, decode.d3.loss_cls: 0.1050, decode.d3.loss_mask: 0.3681, decode.d3.loss_dice: 0.5157, decode.d4.loss_cls: 0.1009, decode.d4.loss_mask: 0.3667, decode.d4.loss_dice: 0.5141, decode.d5.loss_cls: 0.0971, decode.d5.loss_mask: 0.3670, decode.d5.loss_dice: 0.5148, decode.d6.loss_cls: 0.0860, decode.d6.loss_mask: 0.3667, decode.d6.loss_dice: 0.5131, decode.d7.loss_cls: 0.0858, decode.d7.loss_mask: 0.3667, decode.d7.loss_dice: 0.5116, decode.d8.loss_cls: 0.0862, decode.d8.loss_mask: 0.3656, decode.d8.loss_dice: 0.5129, loss: 11.4885 +2022-05-06 07:34:28,383 - mmseg - INFO - Iter [30950/40000] lr: 3.249e-07, eta: 2:07:22, time: 0.694, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0871, decode.loss_mask: 0.3821, decode.loss_dice: 0.5308, decode.d0.loss_cls: 1.4947, decode.d0.loss_mask: 0.4294, decode.d0.loss_dice: 0.6181, decode.d1.loss_cls: 0.1910, decode.d1.loss_mask: 0.3965, decode.d1.loss_dice: 0.5557, decode.d2.loss_cls: 0.1186, decode.d2.loss_mask: 0.3882, decode.d2.loss_dice: 0.5404, decode.d3.loss_cls: 0.1042, decode.d3.loss_mask: 0.3850, decode.d3.loss_dice: 0.5326, decode.d4.loss_cls: 0.0965, decode.d4.loss_mask: 0.3859, decode.d4.loss_dice: 0.5317, decode.d5.loss_cls: 0.0947, decode.d5.loss_mask: 0.3843, decode.d5.loss_dice: 0.5300, decode.d6.loss_cls: 0.0889, decode.d6.loss_mask: 0.3832, decode.d6.loss_dice: 0.5271, decode.d7.loss_cls: 0.0890, decode.d7.loss_mask: 0.3829, decode.d7.loss_dice: 0.5294, decode.d8.loss_cls: 0.0910, decode.d8.loss_mask: 0.3824, decode.d8.loss_dice: 0.5271, loss: 11.7786 +2022-05-06 07:35:02,580 - mmseg - INFO - Saving checkpoint at 31000 iterations +2022-05-06 07:35:28,646 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 07:35:28,649 - mmseg - INFO - Iter [31000/40000] lr: 3.231e-07, eta: 2:06:46, time: 1.203, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1080, decode.loss_mask: 0.3966, decode.loss_dice: 0.5457, decode.d0.loss_cls: 1.4957, decode.d0.loss_mask: 0.4417, decode.d0.loss_dice: 0.6435, decode.d1.loss_cls: 0.2166, decode.d1.loss_mask: 0.4135, decode.d1.loss_dice: 0.5786, decode.d2.loss_cls: 0.1494, decode.d2.loss_mask: 0.4044, decode.d2.loss_dice: 0.5628, decode.d3.loss_cls: 0.1247, decode.d3.loss_mask: 0.4012, decode.d3.loss_dice: 0.5543, decode.d4.loss_cls: 0.1195, decode.d4.loss_mask: 0.3996, decode.d4.loss_dice: 0.5524, decode.d5.loss_cls: 0.1136, decode.d5.loss_mask: 0.3968, decode.d5.loss_dice: 0.5513, decode.d6.loss_cls: 0.1077, decode.d6.loss_mask: 0.3974, decode.d6.loss_dice: 0.5462, decode.d7.loss_cls: 0.1079, decode.d7.loss_mask: 0.3963, decode.d7.loss_dice: 0.5465, decode.d8.loss_cls: 0.1083, decode.d8.loss_mask: 0.3968, decode.d8.loss_dice: 0.5468, loss: 12.3239 +2022-05-06 07:36:02,699 - mmseg - INFO - Iter [31050/40000] lr: 3.213e-07, eta: 2:06:01, time: 0.683, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0940, decode.loss_mask: 0.3794, decode.loss_dice: 0.5146, decode.d0.loss_cls: 1.4734, decode.d0.loss_mask: 0.4235, decode.d0.loss_dice: 0.6062, decode.d1.loss_cls: 0.2021, decode.d1.loss_mask: 0.3928, decode.d1.loss_dice: 0.5471, decode.d2.loss_cls: 0.1349, decode.d2.loss_mask: 0.3844, decode.d2.loss_dice: 0.5308, decode.d3.loss_cls: 0.1137, decode.d3.loss_mask: 0.3834, decode.d3.loss_dice: 0.5236, decode.d4.loss_cls: 0.1081, decode.d4.loss_mask: 0.3824, decode.d4.loss_dice: 0.5224, decode.d5.loss_cls: 0.0937, decode.d5.loss_mask: 0.3828, decode.d5.loss_dice: 0.5214, decode.d6.loss_cls: 0.0984, decode.d6.loss_mask: 0.3803, decode.d6.loss_dice: 0.5161, decode.d7.loss_cls: 0.0925, decode.d7.loss_mask: 0.3813, decode.d7.loss_dice: 0.5175, decode.d8.loss_cls: 0.0901, decode.d8.loss_mask: 0.3798, decode.d8.loss_dice: 0.5174, loss: 11.6882 +2022-05-06 07:36:35,944 - mmseg - INFO - Iter [31100/40000] lr: 3.195e-07, eta: 2:05:16, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0842, decode.loss_mask: 0.3806, decode.loss_dice: 0.5309, decode.d0.loss_cls: 1.4627, decode.d0.loss_mask: 0.4203, decode.d0.loss_dice: 0.6201, decode.d1.loss_cls: 0.1974, decode.d1.loss_mask: 0.3918, decode.d1.loss_dice: 0.5561, decode.d2.loss_cls: 0.1377, decode.d2.loss_mask: 0.3828, decode.d2.loss_dice: 0.5426, decode.d3.loss_cls: 0.1081, decode.d3.loss_mask: 0.3827, decode.d3.loss_dice: 0.5317, decode.d4.loss_cls: 0.0983, decode.d4.loss_mask: 0.3823, decode.d4.loss_dice: 0.5322, decode.d5.loss_cls: 0.0975, decode.d5.loss_mask: 0.3819, decode.d5.loss_dice: 0.5298, decode.d6.loss_cls: 0.0850, decode.d6.loss_mask: 0.3815, decode.d6.loss_dice: 0.5333, decode.d7.loss_cls: 0.0896, decode.d7.loss_mask: 0.3792, decode.d7.loss_dice: 0.5295, decode.d8.loss_cls: 0.0859, decode.d8.loss_mask: 0.3785, decode.d8.loss_dice: 0.5285, loss: 11.7428 +2022-05-06 07:37:11,795 - mmseg - INFO - Iter [31150/40000] lr: 3.177e-07, eta: 2:04:31, time: 0.717, data_time: 0.059, memory: 53770, decode.loss_cls: 0.1036, decode.loss_mask: 0.3902, decode.loss_dice: 0.5564, decode.d0.loss_cls: 1.5184, decode.d0.loss_mask: 0.4303, decode.d0.loss_dice: 0.6647, decode.d1.loss_cls: 0.2255, decode.d1.loss_mask: 0.4015, decode.d1.loss_dice: 0.5927, decode.d2.loss_cls: 0.1494, decode.d2.loss_mask: 0.3917, decode.d2.loss_dice: 0.5736, decode.d3.loss_cls: 0.1217, decode.d3.loss_mask: 0.3922, decode.d3.loss_dice: 0.5660, decode.d4.loss_cls: 0.1113, decode.d4.loss_mask: 0.3914, decode.d4.loss_dice: 0.5625, decode.d5.loss_cls: 0.1085, decode.d5.loss_mask: 0.3902, decode.d5.loss_dice: 0.5614, decode.d6.loss_cls: 0.1120, decode.d6.loss_mask: 0.3903, decode.d6.loss_dice: 0.5606, decode.d7.loss_cls: 0.1021, decode.d7.loss_mask: 0.3884, decode.d7.loss_dice: 0.5632, decode.d8.loss_cls: 0.1084, decode.d8.loss_mask: 0.3882, decode.d8.loss_dice: 0.5601, loss: 12.3763 +2022-05-06 07:37:45,537 - mmseg - INFO - Iter [31200/40000] lr: 3.159e-07, eta: 2:03:46, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1092, decode.loss_mask: 0.3837, decode.loss_dice: 0.5491, decode.d0.loss_cls: 1.5320, decode.d0.loss_mask: 0.4337, decode.d0.loss_dice: 0.6442, decode.d1.loss_cls: 0.2184, decode.d1.loss_mask: 0.4023, decode.d1.loss_dice: 0.5845, decode.d2.loss_cls: 0.1531, decode.d2.loss_mask: 0.3916, decode.d2.loss_dice: 0.5626, decode.d3.loss_cls: 0.1303, decode.d3.loss_mask: 0.3882, decode.d3.loss_dice: 0.5537, decode.d4.loss_cls: 0.1213, decode.d4.loss_mask: 0.3878, decode.d4.loss_dice: 0.5517, decode.d5.loss_cls: 0.1125, decode.d5.loss_mask: 0.3873, decode.d5.loss_dice: 0.5500, decode.d6.loss_cls: 0.1076, decode.d6.loss_mask: 0.3840, decode.d6.loss_dice: 0.5497, decode.d7.loss_cls: 0.1075, decode.d7.loss_mask: 0.3836, decode.d7.loss_dice: 0.5488, decode.d8.loss_cls: 0.1093, decode.d8.loss_mask: 0.3849, decode.d8.loss_dice: 0.5489, loss: 12.2714 +2022-05-06 07:38:19,214 - mmseg - INFO - Iter [31250/40000] lr: 3.141e-07, eta: 2:03:01, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0868, decode.loss_mask: 0.3859, decode.loss_dice: 0.5324, decode.d0.loss_cls: 1.4644, decode.d0.loss_mask: 0.4294, decode.d0.loss_dice: 0.6213, decode.d1.loss_cls: 0.2026, decode.d1.loss_mask: 0.3974, decode.d1.loss_dice: 0.5627, decode.d2.loss_cls: 0.1297, decode.d2.loss_mask: 0.3943, decode.d2.loss_dice: 0.5453, decode.d3.loss_cls: 0.1057, decode.d3.loss_mask: 0.3897, decode.d3.loss_dice: 0.5374, decode.d4.loss_cls: 0.0958, decode.d4.loss_mask: 0.3879, decode.d4.loss_dice: 0.5359, decode.d5.loss_cls: 0.0890, decode.d5.loss_mask: 0.3865, decode.d5.loss_dice: 0.5360, decode.d6.loss_cls: 0.0886, decode.d6.loss_mask: 0.3871, decode.d6.loss_dice: 0.5322, decode.d7.loss_cls: 0.0879, decode.d7.loss_mask: 0.3848, decode.d7.loss_dice: 0.5311, decode.d8.loss_cls: 0.0924, decode.d8.loss_mask: 0.3853, decode.d8.loss_dice: 0.5294, loss: 11.8346 +2022-05-06 07:38:52,832 - mmseg - INFO - Iter [31300/40000] lr: 3.123e-07, eta: 2:02:17, time: 0.672, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0985, decode.loss_mask: 0.3776, decode.loss_dice: 0.5467, decode.d0.loss_cls: 1.4829, decode.d0.loss_mask: 0.4195, decode.d0.loss_dice: 0.6424, decode.d1.loss_cls: 0.1975, decode.d1.loss_mask: 0.3900, decode.d1.loss_dice: 0.5783, decode.d2.loss_cls: 0.1330, decode.d2.loss_mask: 0.3826, decode.d2.loss_dice: 0.5605, decode.d3.loss_cls: 0.1169, decode.d3.loss_mask: 0.3819, decode.d3.loss_dice: 0.5516, decode.d4.loss_cls: 0.1095, decode.d4.loss_mask: 0.3806, decode.d4.loss_dice: 0.5530, decode.d5.loss_cls: 0.1054, decode.d5.loss_mask: 0.3787, decode.d5.loss_dice: 0.5504, decode.d6.loss_cls: 0.1030, decode.d6.loss_mask: 0.3789, decode.d6.loss_dice: 0.5501, decode.d7.loss_cls: 0.0985, decode.d7.loss_mask: 0.3782, decode.d7.loss_dice: 0.5494, decode.d8.loss_cls: 0.1000, decode.d8.loss_mask: 0.3795, decode.d8.loss_dice: 0.5471, loss: 12.0224 +2022-05-06 07:39:26,544 - mmseg - INFO - Iter [31350/40000] lr: 3.105e-07, eta: 2:01:32, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0886, decode.loss_mask: 0.3957, decode.loss_dice: 0.5382, decode.d0.loss_cls: 1.4487, decode.d0.loss_mask: 0.4427, decode.d0.loss_dice: 0.6311, decode.d1.loss_cls: 0.1861, decode.d1.loss_mask: 0.4124, decode.d1.loss_dice: 0.5696, decode.d2.loss_cls: 0.1228, decode.d2.loss_mask: 0.4040, decode.d2.loss_dice: 0.5516, decode.d3.loss_cls: 0.1012, decode.d3.loss_mask: 0.4004, decode.d3.loss_dice: 0.5424, decode.d4.loss_cls: 0.0930, decode.d4.loss_mask: 0.3985, decode.d4.loss_dice: 0.5443, decode.d5.loss_cls: 0.0953, decode.d5.loss_mask: 0.3978, decode.d5.loss_dice: 0.5434, decode.d6.loss_cls: 0.0904, decode.d6.loss_mask: 0.3963, decode.d6.loss_dice: 0.5338, decode.d7.loss_cls: 0.0865, decode.d7.loss_mask: 0.3957, decode.d7.loss_dice: 0.5401, decode.d8.loss_cls: 0.0870, decode.d8.loss_mask: 0.3957, decode.d8.loss_dice: 0.5388, loss: 11.9723 +2022-05-06 07:40:00,458 - mmseg - INFO - Iter [31400/40000] lr: 3.087e-07, eta: 2:00:47, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0908, decode.loss_mask: 0.3665, decode.loss_dice: 0.5201, decode.d0.loss_cls: 1.4667, decode.d0.loss_mask: 0.4086, decode.d0.loss_dice: 0.6159, decode.d1.loss_cls: 0.1997, decode.d1.loss_mask: 0.3796, decode.d1.loss_dice: 0.5516, decode.d2.loss_cls: 0.1247, decode.d2.loss_mask: 0.3735, decode.d2.loss_dice: 0.5391, decode.d3.loss_cls: 0.1072, decode.d3.loss_mask: 0.3699, decode.d3.loss_dice: 0.5318, decode.d4.loss_cls: 0.0998, decode.d4.loss_mask: 0.3698, decode.d4.loss_dice: 0.5303, decode.d5.loss_cls: 0.0983, decode.d5.loss_mask: 0.3684, decode.d5.loss_dice: 0.5261, decode.d6.loss_cls: 0.0889, decode.d6.loss_mask: 0.3695, decode.d6.loss_dice: 0.5240, decode.d7.loss_cls: 0.0896, decode.d7.loss_mask: 0.3682, decode.d7.loss_dice: 0.5243, decode.d8.loss_cls: 0.0880, decode.d8.loss_mask: 0.3679, decode.d8.loss_dice: 0.5276, loss: 11.5864 +2022-05-06 07:40:34,531 - mmseg - INFO - Iter [31450/40000] lr: 3.069e-07, eta: 2:00:02, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0946, decode.loss_mask: 0.3808, decode.loss_dice: 0.5297, decode.d0.loss_cls: 1.4878, decode.d0.loss_mask: 0.4270, decode.d0.loss_dice: 0.6148, decode.d1.loss_cls: 0.2178, decode.d1.loss_mask: 0.3985, decode.d1.loss_dice: 0.5593, decode.d2.loss_cls: 0.1484, decode.d2.loss_mask: 0.3894, decode.d2.loss_dice: 0.5417, decode.d3.loss_cls: 0.1191, decode.d3.loss_mask: 0.3863, decode.d3.loss_dice: 0.5320, decode.d4.loss_cls: 0.1116, decode.d4.loss_mask: 0.3838, decode.d4.loss_dice: 0.5324, decode.d5.loss_cls: 0.1058, decode.d5.loss_mask: 0.3838, decode.d5.loss_dice: 0.5270, decode.d6.loss_cls: 0.0962, decode.d6.loss_mask: 0.3834, decode.d6.loss_dice: 0.5286, decode.d7.loss_cls: 0.0978, decode.d7.loss_mask: 0.3826, decode.d7.loss_dice: 0.5312, decode.d8.loss_cls: 0.0981, decode.d8.loss_mask: 0.3826, decode.d8.loss_dice: 0.5318, loss: 11.9043 +2022-05-06 07:41:11,270 - mmseg - INFO - Iter [31500/40000] lr: 3.051e-07, eta: 1:59:19, time: 0.735, data_time: 0.057, memory: 53770, decode.loss_cls: 0.0833, decode.loss_mask: 0.3705, decode.loss_dice: 0.5145, decode.d0.loss_cls: 1.4607, decode.d0.loss_mask: 0.4126, decode.d0.loss_dice: 0.6012, decode.d1.loss_cls: 0.1813, decode.d1.loss_mask: 0.3845, decode.d1.loss_dice: 0.5476, decode.d2.loss_cls: 0.1273, decode.d2.loss_mask: 0.3752, decode.d2.loss_dice: 0.5260, decode.d3.loss_cls: 0.1016, decode.d3.loss_mask: 0.3744, decode.d3.loss_dice: 0.5234, decode.d4.loss_cls: 0.0902, decode.d4.loss_mask: 0.3734, decode.d4.loss_dice: 0.5195, decode.d5.loss_cls: 0.0866, decode.d5.loss_mask: 0.3697, decode.d5.loss_dice: 0.5156, decode.d6.loss_cls: 0.0850, decode.d6.loss_mask: 0.3697, decode.d6.loss_dice: 0.5107, decode.d7.loss_cls: 0.0837, decode.d7.loss_mask: 0.3701, decode.d7.loss_dice: 0.5132, decode.d8.loss_cls: 0.0799, decode.d8.loss_mask: 0.3703, decode.d8.loss_dice: 0.5134, loss: 11.4351 +2022-05-06 07:41:45,249 - mmseg - INFO - Iter [31550/40000] lr: 3.033e-07, eta: 1:58:34, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1025, decode.loss_mask: 0.3769, decode.loss_dice: 0.5193, decode.d0.loss_cls: 1.4832, decode.d0.loss_mask: 0.4135, decode.d0.loss_dice: 0.6133, decode.d1.loss_cls: 0.2019, decode.d1.loss_mask: 0.3855, decode.d1.loss_dice: 0.5523, decode.d2.loss_cls: 0.1378, decode.d2.loss_mask: 0.3818, decode.d2.loss_dice: 0.5342, decode.d3.loss_cls: 0.1133, decode.d3.loss_mask: 0.3788, decode.d3.loss_dice: 0.5246, decode.d4.loss_cls: 0.1047, decode.d4.loss_mask: 0.3789, decode.d4.loss_dice: 0.5251, decode.d5.loss_cls: 0.1010, decode.d5.loss_mask: 0.3759, decode.d5.loss_dice: 0.5221, decode.d6.loss_cls: 0.0972, decode.d6.loss_mask: 0.3749, decode.d6.loss_dice: 0.5204, decode.d7.loss_cls: 0.0987, decode.d7.loss_mask: 0.3759, decode.d7.loss_dice: 0.5225, decode.d8.loss_cls: 0.0993, decode.d8.loss_mask: 0.3771, decode.d8.loss_dice: 0.5225, loss: 11.7152 +2022-05-06 07:42:18,540 - mmseg - INFO - Iter [31600/40000] lr: 3.016e-07, eta: 1:57:49, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0849, decode.loss_mask: 0.3700, decode.loss_dice: 0.5181, decode.d0.loss_cls: 1.4497, decode.d0.loss_mask: 0.4065, decode.d0.loss_dice: 0.5997, decode.d1.loss_cls: 0.1838, decode.d1.loss_mask: 0.3829, decode.d1.loss_dice: 0.5534, decode.d2.loss_cls: 0.1174, decode.d2.loss_mask: 0.3770, decode.d2.loss_dice: 0.5360, decode.d3.loss_cls: 0.1004, decode.d3.loss_mask: 0.3724, decode.d3.loss_dice: 0.5254, decode.d4.loss_cls: 0.0954, decode.d4.loss_mask: 0.3735, decode.d4.loss_dice: 0.5240, decode.d5.loss_cls: 0.0941, decode.d5.loss_mask: 0.3693, decode.d5.loss_dice: 0.5187, decode.d6.loss_cls: 0.0875, decode.d6.loss_mask: 0.3691, decode.d6.loss_dice: 0.5201, decode.d7.loss_cls: 0.0907, decode.d7.loss_mask: 0.3690, decode.d7.loss_dice: 0.5158, decode.d8.loss_cls: 0.0893, decode.d8.loss_mask: 0.3692, decode.d8.loss_dice: 0.5171, loss: 11.4803 +2022-05-06 07:42:52,326 - mmseg - INFO - Iter [31650/40000] lr: 2.998e-07, eta: 1:57:05, time: 0.676, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0877, decode.loss_mask: 0.3870, decode.loss_dice: 0.5388, decode.d0.loss_cls: 1.4811, decode.d0.loss_mask: 0.4332, decode.d0.loss_dice: 0.6392, decode.d1.loss_cls: 0.2089, decode.d1.loss_mask: 0.4031, decode.d1.loss_dice: 0.5738, decode.d2.loss_cls: 0.1306, decode.d2.loss_mask: 0.3928, decode.d2.loss_dice: 0.5525, decode.d3.loss_cls: 0.1064, decode.d3.loss_mask: 0.3913, decode.d3.loss_dice: 0.5385, decode.d4.loss_cls: 0.1008, decode.d4.loss_mask: 0.3892, decode.d4.loss_dice: 0.5400, decode.d5.loss_cls: 0.0965, decode.d5.loss_mask: 0.3894, decode.d5.loss_dice: 0.5380, decode.d6.loss_cls: 0.0939, decode.d6.loss_mask: 0.3883, decode.d6.loss_dice: 0.5370, decode.d7.loss_cls: 0.0892, decode.d7.loss_mask: 0.3874, decode.d7.loss_dice: 0.5369, decode.d8.loss_cls: 0.0891, decode.d8.loss_mask: 0.3873, decode.d8.loss_dice: 0.5389, loss: 11.9668 +2022-05-06 07:43:26,057 - mmseg - INFO - Iter [31700/40000] lr: 2.980e-07, eta: 1:56:20, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1048, decode.loss_mask: 0.3829, decode.loss_dice: 0.5463, decode.d0.loss_cls: 1.5022, decode.d0.loss_mask: 0.4219, decode.d0.loss_dice: 0.6479, decode.d1.loss_cls: 0.2058, decode.d1.loss_mask: 0.3950, decode.d1.loss_dice: 0.5814, decode.d2.loss_cls: 0.1484, decode.d2.loss_mask: 0.3889, decode.d2.loss_dice: 0.5592, decode.d3.loss_cls: 0.1252, decode.d3.loss_mask: 0.3853, decode.d3.loss_dice: 0.5534, decode.d4.loss_cls: 0.1108, decode.d4.loss_mask: 0.3843, decode.d4.loss_dice: 0.5505, decode.d5.loss_cls: 0.1135, decode.d5.loss_mask: 0.3842, decode.d5.loss_dice: 0.5483, decode.d6.loss_cls: 0.1092, decode.d6.loss_mask: 0.3837, decode.d6.loss_dice: 0.5490, decode.d7.loss_cls: 0.1095, decode.d7.loss_mask: 0.3834, decode.d7.loss_dice: 0.5440, decode.d8.loss_cls: 0.1044, decode.d8.loss_mask: 0.3831, decode.d8.loss_dice: 0.5456, loss: 12.1520 +2022-05-06 07:43:59,715 - mmseg - INFO - Iter [31750/40000] lr: 2.962e-07, eta: 1:55:35, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0910, decode.loss_mask: 0.3908, decode.loss_dice: 0.5424, decode.d0.loss_cls: 1.4836, decode.d0.loss_mask: 0.4367, decode.d0.loss_dice: 0.6464, decode.d1.loss_cls: 0.2107, decode.d1.loss_mask: 0.4045, decode.d1.loss_dice: 0.5833, decode.d2.loss_cls: 0.1349, decode.d2.loss_mask: 0.3980, decode.d2.loss_dice: 0.5609, decode.d3.loss_cls: 0.1110, decode.d3.loss_mask: 0.3943, decode.d3.loss_dice: 0.5505, decode.d4.loss_cls: 0.1024, decode.d4.loss_mask: 0.3931, decode.d4.loss_dice: 0.5495, decode.d5.loss_cls: 0.0984, decode.d5.loss_mask: 0.3913, decode.d5.loss_dice: 0.5465, decode.d6.loss_cls: 0.0914, decode.d6.loss_mask: 0.3920, decode.d6.loss_dice: 0.5481, decode.d7.loss_cls: 0.0953, decode.d7.loss_mask: 0.3903, decode.d7.loss_dice: 0.5463, decode.d8.loss_cls: 0.0951, decode.d8.loss_mask: 0.3909, decode.d8.loss_dice: 0.5477, loss: 12.1170 +2022-05-06 07:44:35,497 - mmseg - INFO - Iter [31800/40000] lr: 2.944e-07, eta: 1:54:52, time: 0.715, data_time: 0.060, memory: 53770, decode.loss_cls: 0.0850, decode.loss_mask: 0.3668, decode.loss_dice: 0.5312, decode.d0.loss_cls: 1.4867, decode.d0.loss_mask: 0.4068, decode.d0.loss_dice: 0.6262, decode.d1.loss_cls: 0.1909, decode.d1.loss_mask: 0.3777, decode.d1.loss_dice: 0.5639, decode.d2.loss_cls: 0.1252, decode.d2.loss_mask: 0.3715, decode.d2.loss_dice: 0.5435, decode.d3.loss_cls: 0.1006, decode.d3.loss_mask: 0.3703, decode.d3.loss_dice: 0.5352, decode.d4.loss_cls: 0.0957, decode.d4.loss_mask: 0.3696, decode.d4.loss_dice: 0.5362, decode.d5.loss_cls: 0.0897, decode.d5.loss_mask: 0.3686, decode.d5.loss_dice: 0.5332, decode.d6.loss_cls: 0.0863, decode.d6.loss_mask: 0.3677, decode.d6.loss_dice: 0.5343, decode.d7.loss_cls: 0.0823, decode.d7.loss_mask: 0.3680, decode.d7.loss_dice: 0.5323, decode.d8.loss_cls: 0.0865, decode.d8.loss_mask: 0.3668, decode.d8.loss_dice: 0.5299, loss: 11.6288 +2022-05-06 07:45:08,958 - mmseg - INFO - Iter [31850/40000] lr: 2.926e-07, eta: 1:54:07, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0823, decode.loss_mask: 0.3813, decode.loss_dice: 0.5232, decode.d0.loss_cls: 1.4793, decode.d0.loss_mask: 0.4239, decode.d0.loss_dice: 0.6107, decode.d1.loss_cls: 0.1758, decode.d1.loss_mask: 0.3959, decode.d1.loss_dice: 0.5563, decode.d2.loss_cls: 0.1209, decode.d2.loss_mask: 0.3885, decode.d2.loss_dice: 0.5367, decode.d3.loss_cls: 0.1016, decode.d3.loss_mask: 0.3840, decode.d3.loss_dice: 0.5276, decode.d4.loss_cls: 0.0961, decode.d4.loss_mask: 0.3831, decode.d4.loss_dice: 0.5285, decode.d5.loss_cls: 0.0884, decode.d5.loss_mask: 0.3812, decode.d5.loss_dice: 0.5260, decode.d6.loss_cls: 0.0877, decode.d6.loss_mask: 0.3808, decode.d6.loss_dice: 0.5211, decode.d7.loss_cls: 0.0869, decode.d7.loss_mask: 0.3806, decode.d7.loss_dice: 0.5216, decode.d8.loss_cls: 0.0854, decode.d8.loss_mask: 0.3809, decode.d8.loss_dice: 0.5232, loss: 11.6598 +2022-05-06 07:45:42,713 - mmseg - INFO - Iter [31900/40000] lr: 2.908e-07, eta: 1:53:23, time: 0.675, data_time: 0.008, memory: 53770, decode.loss_cls: 0.1028, decode.loss_mask: 0.3768, decode.loss_dice: 0.5402, decode.d0.loss_cls: 1.4732, decode.d0.loss_mask: 0.4209, decode.d0.loss_dice: 0.6330, decode.d1.loss_cls: 0.2100, decode.d1.loss_mask: 0.3916, decode.d1.loss_dice: 0.5725, decode.d2.loss_cls: 0.1440, decode.d2.loss_mask: 0.3847, decode.d2.loss_dice: 0.5539, decode.d3.loss_cls: 0.1201, decode.d3.loss_mask: 0.3809, decode.d3.loss_dice: 0.5452, decode.d4.loss_cls: 0.1097, decode.d4.loss_mask: 0.3801, decode.d4.loss_dice: 0.5478, decode.d5.loss_cls: 0.1037, decode.d5.loss_mask: 0.3793, decode.d5.loss_dice: 0.5491, decode.d6.loss_cls: 0.1065, decode.d6.loss_mask: 0.3791, decode.d6.loss_dice: 0.5405, decode.d7.loss_cls: 0.1022, decode.d7.loss_mask: 0.3754, decode.d7.loss_dice: 0.5384, decode.d8.loss_cls: 0.1039, decode.d8.loss_mask: 0.3770, decode.d8.loss_dice: 0.5430, loss: 11.9857 +2022-05-06 07:46:17,028 - mmseg - INFO - Iter [31950/40000] lr: 2.890e-07, eta: 1:52:38, time: 0.686, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0939, decode.loss_mask: 0.3766, decode.loss_dice: 0.5219, decode.d0.loss_cls: 1.4597, decode.d0.loss_mask: 0.4145, decode.d0.loss_dice: 0.6147, decode.d1.loss_cls: 0.1926, decode.d1.loss_mask: 0.3885, decode.d1.loss_dice: 0.5572, decode.d2.loss_cls: 0.1403, decode.d2.loss_mask: 0.3796, decode.d2.loss_dice: 0.5390, decode.d3.loss_cls: 0.1109, decode.d3.loss_mask: 0.3771, decode.d3.loss_dice: 0.5301, decode.d4.loss_cls: 0.1026, decode.d4.loss_mask: 0.3756, decode.d4.loss_dice: 0.5280, decode.d5.loss_cls: 0.0980, decode.d5.loss_mask: 0.3747, decode.d5.loss_dice: 0.5278, decode.d6.loss_cls: 0.0995, decode.d6.loss_mask: 0.3746, decode.d6.loss_dice: 0.5258, decode.d7.loss_cls: 0.0950, decode.d7.loss_mask: 0.3746, decode.d7.loss_dice: 0.5221, decode.d8.loss_cls: 0.0903, decode.d8.loss_mask: 0.3751, decode.d8.loss_dice: 0.5247, loss: 11.6850 +2022-05-06 07:46:50,864 - mmseg - INFO - Saving checkpoint at 32000 iterations +2022-05-06 07:47:18,189 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 07:47:18,196 - mmseg - INFO - Iter [32000/40000] lr: 2.872e-07, eta: 1:52:02, time: 1.221, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0928, decode.loss_mask: 0.3805, decode.loss_dice: 0.5341, decode.d0.loss_cls: 1.4638, decode.d0.loss_mask: 0.4255, decode.d0.loss_dice: 0.6330, decode.d1.loss_cls: 0.1966, decode.d1.loss_mask: 0.3942, decode.d1.loss_dice: 0.5679, decode.d2.loss_cls: 0.1316, decode.d2.loss_mask: 0.3875, decode.d2.loss_dice: 0.5493, decode.d3.loss_cls: 0.1074, decode.d3.loss_mask: 0.3857, decode.d3.loss_dice: 0.5454, decode.d4.loss_cls: 0.1026, decode.d4.loss_mask: 0.3834, decode.d4.loss_dice: 0.5413, decode.d5.loss_cls: 0.0970, decode.d5.loss_mask: 0.3819, decode.d5.loss_dice: 0.5407, decode.d6.loss_cls: 0.0905, decode.d6.loss_mask: 0.3805, decode.d6.loss_dice: 0.5370, decode.d7.loss_cls: 0.0950, decode.d7.loss_mask: 0.3817, decode.d7.loss_dice: 0.5352, decode.d8.loss_cls: 0.0978, decode.d8.loss_mask: 0.3821, decode.d8.loss_dice: 0.5335, loss: 11.8756 +2022-05-06 07:51:38,438 - mmseg - INFO - per class results: +2022-05-06 07:51:38,445 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.94 | 96.23 | +| bag | 49.92 | 66.27 | +| bed | 36.15 | 50.67 | +| bedclothes | 44.98 | 66.52 | +| bench | 28.57 | 35.78 | +| bicycle | 85.17 | 92.0 | +| bird | 95.36 | 97.8 | +| boat | 87.07 | 92.83 | +| book | 57.87 | 67.65 | +| bottle | 89.98 | 95.73 | +| building | 67.51 | 81.78 | +| bus | 95.5 | 97.22 | +| cabinet | 50.83 | 66.55 | +| car | 93.85 | 97.24 | +| cat | 94.72 | 98.1 | +| ceiling | 59.82 | 75.19 | +| chair | 64.54 | 83.73 | +| cloth | 29.23 | 36.9 | +| computer | 56.57 | 66.09 | +| cow | 95.68 | 97.27 | +| cup | 49.97 | 63.7 | +| curtain | 61.84 | 78.92 | +| dog | 93.14 | 97.89 | +| door | 39.47 | 60.58 | +| fence | 46.84 | 59.5 | +| floor | 75.33 | 88.15 | +| flower | 41.29 | 51.98 | +| food | 44.72 | 55.12 | +| grass | 83.1 | 91.68 | +| ground | 55.27 | 67.34 | +| horse | 95.07 | 97.68 | +| keyboard | 91.71 | 95.71 | +| light | 63.13 | 77.47 | +| motorbike | 91.53 | 97.18 | +| mountain | 54.52 | 76.11 | +| mouse | 89.78 | 93.17 | +| person | 91.28 | 95.83 | +| plate | 33.67 | 44.01 | +| platform | 50.31 | 60.42 | +| pottedplant | 82.63 | 91.35 | +| road | 53.87 | 77.99 | +| rock | 50.5 | 58.0 | +| sheep | 95.12 | 98.07 | +| shelves | 42.86 | 63.85 | +| sidewalk | 33.2 | 49.28 | +| sign | 54.69 | 63.6 | +| sky | 94.83 | 97.32 | +| snow | 79.51 | 89.56 | +| sofa | 60.85 | 72.26 | +| table | 72.43 | 84.85 | +| track | 73.34 | 84.23 | +| train | 92.98 | 96.86 | +| tree | 81.65 | 91.01 | +| truck | 53.83 | 63.32 | +| tvmonitor | 90.93 | 94.25 | +| wall | 72.16 | 83.42 | +| water | 92.54 | 96.06 | +| window | 46.23 | 58.19 | +| wood | 28.28 | 37.37 | ++-------------+-------+-------+ +2022-05-06 07:51:38,445 - mmseg - INFO - Summary: +2022-05-06 07:51:38,445 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.42 | 67.47 | 77.37 | ++-------+-------+-------+ +2022-05-06 07:51:38,464 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 07:51:38,465 - mmseg - INFO - Iter(val) [638] aAcc: 0.8642, mIoU: 0.6747, mAcc: 0.7737, IoU.aeroplane: 0.9294, IoU.bag: 0.4992, IoU.bed: 0.3615, IoU.bedclothes: 0.4498, IoU.bench: 0.2857, IoU.bicycle: 0.8517, IoU.bird: 0.9536, IoU.boat: 0.8707, IoU.book: 0.5787, IoU.bottle: 0.8998, IoU.building: 0.6751, IoU.bus: 0.9550, IoU.cabinet: 0.5083, IoU.car: 0.9385, IoU.cat: 0.9472, IoU.ceiling: 0.5982, IoU.chair: 0.6454, IoU.cloth: 0.2923, IoU.computer: 0.5657, IoU.cow: 0.9568, IoU.cup: 0.4997, IoU.curtain: 0.6184, IoU.dog: 0.9314, IoU.door: 0.3947, IoU.fence: 0.4684, IoU.floor: 0.7533, IoU.flower: 0.4129, IoU.food: 0.4472, IoU.grass: 0.8310, IoU.ground: 0.5527, IoU.horse: 0.9507, IoU.keyboard: 0.9171, IoU.light: 0.6313, IoU.motorbike: 0.9153, IoU.mountain: 0.5452, IoU.mouse: 0.8978, IoU.person: 0.9128, IoU.plate: 0.3367, IoU.platform: 0.5031, IoU.pottedplant: 0.8263, IoU.road: 0.5387, IoU.rock: 0.5050, IoU.sheep: 0.9512, IoU.shelves: 0.4286, IoU.sidewalk: 0.3320, IoU.sign: 0.5469, IoU.sky: 0.9483, IoU.snow: 0.7951, IoU.sofa: 0.6085, IoU.table: 0.7243, IoU.track: 0.7334, IoU.train: 0.9298, IoU.tree: 0.8165, IoU.truck: 0.5383, IoU.tvmonitor: 0.9093, IoU.wall: 0.7216, IoU.water: 0.9254, IoU.window: 0.4623, IoU.wood: 0.2828, Acc.aeroplane: 0.9623, Acc.bag: 0.6627, Acc.bed: 0.5067, Acc.bedclothes: 0.6652, Acc.bench: 0.3578, Acc.bicycle: 0.9200, Acc.bird: 0.9780, Acc.boat: 0.9283, Acc.book: 0.6765, Acc.bottle: 0.9573, Acc.building: 0.8178, Acc.bus: 0.9722, Acc.cabinet: 0.6655, Acc.car: 0.9724, Acc.cat: 0.9810, Acc.ceiling: 0.7519, Acc.chair: 0.8373, Acc.cloth: 0.3690, Acc.computer: 0.6609, Acc.cow: 0.9727, Acc.cup: 0.6370, Acc.curtain: 0.7892, Acc.dog: 0.9789, Acc.door: 0.6058, Acc.fence: 0.5950, Acc.floor: 0.8815, Acc.flower: 0.5198, Acc.food: 0.5512, Acc.grass: 0.9168, Acc.ground: 0.6734, Acc.horse: 0.9768, Acc.keyboard: 0.9571, Acc.light: 0.7747, Acc.motorbike: 0.9718, Acc.mountain: 0.7611, Acc.mouse: 0.9317, Acc.person: 0.9583, Acc.plate: 0.4401, Acc.platform: 0.6042, Acc.pottedplant: 0.9135, Acc.road: 0.7799, Acc.rock: 0.5800, Acc.sheep: 0.9807, Acc.shelves: 0.6385, Acc.sidewalk: 0.4928, Acc.sign: 0.6360, Acc.sky: 0.9732, Acc.snow: 0.8956, Acc.sofa: 0.7226, Acc.table: 0.8485, Acc.track: 0.8423, Acc.train: 0.9686, Acc.tree: 0.9101, Acc.truck: 0.6332, Acc.tvmonitor: 0.9425, Acc.wall: 0.8342, Acc.water: 0.9606, Acc.window: 0.5819, Acc.wood: 0.3737 +2022-05-06 07:52:12,204 - mmseg - INFO - Iter [32050/40000] lr: 2.854e-07, eta: 1:52:31, time: 5.882, data_time: 5.216, memory: 53770, decode.loss_cls: 0.0904, decode.loss_mask: 0.3782, decode.loss_dice: 0.5372, decode.d0.loss_cls: 1.4611, decode.d0.loss_mask: 0.4242, decode.d0.loss_dice: 0.6285, decode.d1.loss_cls: 0.1958, decode.d1.loss_mask: 0.3942, decode.d1.loss_dice: 0.5641, decode.d2.loss_cls: 0.1299, decode.d2.loss_mask: 0.3857, decode.d2.loss_dice: 0.5497, decode.d3.loss_cls: 0.1124, decode.d3.loss_mask: 0.3821, decode.d3.loss_dice: 0.5393, decode.d4.loss_cls: 0.0977, decode.d4.loss_mask: 0.3830, decode.d4.loss_dice: 0.5421, decode.d5.loss_cls: 0.0966, decode.d5.loss_mask: 0.3807, decode.d5.loss_dice: 0.5428, decode.d6.loss_cls: 0.0926, decode.d6.loss_mask: 0.3793, decode.d6.loss_dice: 0.5387, decode.d7.loss_cls: 0.0896, decode.d7.loss_mask: 0.3785, decode.d7.loss_dice: 0.5393, decode.d8.loss_cls: 0.0860, decode.d8.loss_mask: 0.3770, decode.d8.loss_dice: 0.5377, loss: 11.8343 +2022-05-06 07:52:48,946 - mmseg - INFO - Iter [32100/40000] lr: 2.836e-07, eta: 1:51:47, time: 0.735, data_time: 0.060, memory: 53770, decode.loss_cls: 0.0881, decode.loss_mask: 0.3630, decode.loss_dice: 0.5183, decode.d0.loss_cls: 1.5028, decode.d0.loss_mask: 0.4091, decode.d0.loss_dice: 0.6178, decode.d1.loss_cls: 0.1970, decode.d1.loss_mask: 0.3773, decode.d1.loss_dice: 0.5561, decode.d2.loss_cls: 0.1213, decode.d2.loss_mask: 0.3689, decode.d2.loss_dice: 0.5344, decode.d3.loss_cls: 0.1045, decode.d3.loss_mask: 0.3654, decode.d3.loss_dice: 0.5286, decode.d4.loss_cls: 0.0959, decode.d4.loss_mask: 0.3647, decode.d4.loss_dice: 0.5288, decode.d5.loss_cls: 0.0925, decode.d5.loss_mask: 0.3636, decode.d5.loss_dice: 0.5237, decode.d6.loss_cls: 0.0882, decode.d6.loss_mask: 0.3628, decode.d6.loss_dice: 0.5239, decode.d7.loss_cls: 0.0864, decode.d7.loss_mask: 0.3619, decode.d7.loss_dice: 0.5197, decode.d8.loss_cls: 0.0917, decode.d8.loss_mask: 0.3631, decode.d8.loss_dice: 0.5198, loss: 11.5394 +2022-05-06 07:53:22,445 - mmseg - INFO - Iter [32150/40000] lr: 2.818e-07, eta: 1:51:02, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0832, decode.loss_mask: 0.3880, decode.loss_dice: 0.5341, decode.d0.loss_cls: 1.4646, decode.d0.loss_mask: 0.4342, decode.d0.loss_dice: 0.6326, decode.d1.loss_cls: 0.1875, decode.d1.loss_mask: 0.4045, decode.d1.loss_dice: 0.5759, decode.d2.loss_cls: 0.1334, decode.d2.loss_mask: 0.3921, decode.d2.loss_dice: 0.5483, decode.d3.loss_cls: 0.1016, decode.d3.loss_mask: 0.3919, decode.d3.loss_dice: 0.5414, decode.d4.loss_cls: 0.0983, decode.d4.loss_mask: 0.3905, decode.d4.loss_dice: 0.5385, decode.d5.loss_cls: 0.0919, decode.d5.loss_mask: 0.3882, decode.d5.loss_dice: 0.5400, decode.d6.loss_cls: 0.0830, decode.d6.loss_mask: 0.3896, decode.d6.loss_dice: 0.5369, decode.d7.loss_cls: 0.0812, decode.d7.loss_mask: 0.3893, decode.d7.loss_dice: 0.5347, decode.d8.loss_cls: 0.0816, decode.d8.loss_mask: 0.3890, decode.d8.loss_dice: 0.5352, loss: 11.8812 +2022-05-06 07:53:56,249 - mmseg - INFO - Iter [32200/40000] lr: 2.800e-07, eta: 1:50:17, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0865, decode.loss_mask: 0.3696, decode.loss_dice: 0.5264, decode.d0.loss_cls: 1.4447, decode.d0.loss_mask: 0.4107, decode.d0.loss_dice: 0.6231, decode.d1.loss_cls: 0.1849, decode.d1.loss_mask: 0.3850, decode.d1.loss_dice: 0.5602, decode.d2.loss_cls: 0.1187, decode.d2.loss_mask: 0.3776, decode.d2.loss_dice: 0.5434, decode.d3.loss_cls: 0.1020, decode.d3.loss_mask: 0.3728, decode.d3.loss_dice: 0.5332, decode.d4.loss_cls: 0.0912, decode.d4.loss_mask: 0.3717, decode.d4.loss_dice: 0.5312, decode.d5.loss_cls: 0.0859, decode.d5.loss_mask: 0.3718, decode.d5.loss_dice: 0.5313, decode.d6.loss_cls: 0.0852, decode.d6.loss_mask: 0.3720, decode.d6.loss_dice: 0.5243, decode.d7.loss_cls: 0.0849, decode.d7.loss_mask: 0.3706, decode.d7.loss_dice: 0.5280, decode.d8.loss_cls: 0.0837, decode.d8.loss_mask: 0.3704, decode.d8.loss_dice: 0.5310, loss: 11.5720 +2022-05-06 07:54:30,244 - mmseg - INFO - Iter [32250/40000] lr: 2.782e-07, eta: 1:49:33, time: 0.680, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0888, decode.loss_mask: 0.3689, decode.loss_dice: 0.5318, decode.d0.loss_cls: 1.5149, decode.d0.loss_mask: 0.4102, decode.d0.loss_dice: 0.6265, decode.d1.loss_cls: 0.2098, decode.d1.loss_mask: 0.3836, decode.d1.loss_dice: 0.5567, decode.d2.loss_cls: 0.1316, decode.d2.loss_mask: 0.3747, decode.d2.loss_dice: 0.5434, decode.d3.loss_cls: 0.1013, decode.d3.loss_mask: 0.3729, decode.d3.loss_dice: 0.5308, decode.d4.loss_cls: 0.0954, decode.d4.loss_mask: 0.3723, decode.d4.loss_dice: 0.5320, decode.d5.loss_cls: 0.0891, decode.d5.loss_mask: 0.3708, decode.d5.loss_dice: 0.5322, decode.d6.loss_cls: 0.0886, decode.d6.loss_mask: 0.3705, decode.d6.loss_dice: 0.5356, decode.d7.loss_cls: 0.0869, decode.d7.loss_mask: 0.3689, decode.d7.loss_dice: 0.5312, decode.d8.loss_cls: 0.0881, decode.d8.loss_mask: 0.3680, decode.d8.loss_dice: 0.5269, loss: 11.7024 +2022-05-06 07:55:05,304 - mmseg - INFO - Iter [32300/40000] lr: 2.764e-07, eta: 1:48:48, time: 0.700, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0973, decode.loss_mask: 0.3762, decode.loss_dice: 0.5297, decode.d0.loss_cls: 1.5010, decode.d0.loss_mask: 0.4180, decode.d0.loss_dice: 0.6270, decode.d1.loss_cls: 0.2284, decode.d1.loss_mask: 0.3882, decode.d1.loss_dice: 0.5604, decode.d2.loss_cls: 0.1451, decode.d2.loss_mask: 0.3812, decode.d2.loss_dice: 0.5420, decode.d3.loss_cls: 0.1210, decode.d3.loss_mask: 0.3796, decode.d3.loss_dice: 0.5346, decode.d4.loss_cls: 0.1128, decode.d4.loss_mask: 0.3788, decode.d4.loss_dice: 0.5367, decode.d5.loss_cls: 0.1062, decode.d5.loss_mask: 0.3766, decode.d5.loss_dice: 0.5346, decode.d6.loss_cls: 0.1050, decode.d6.loss_mask: 0.3772, decode.d6.loss_dice: 0.5308, decode.d7.loss_cls: 0.1093, decode.d7.loss_mask: 0.3761, decode.d7.loss_dice: 0.5278, decode.d8.loss_cls: 0.1018, decode.d8.loss_mask: 0.3762, decode.d8.loss_dice: 0.5300, loss: 11.9097 +2022-05-06 07:55:39,089 - mmseg - INFO - Iter [32350/40000] lr: 2.746e-07, eta: 1:48:04, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0929, decode.loss_mask: 0.3804, decode.loss_dice: 0.5244, decode.d0.loss_cls: 1.4926, decode.d0.loss_mask: 0.4260, decode.d0.loss_dice: 0.6182, decode.d1.loss_cls: 0.2072, decode.d1.loss_mask: 0.3954, decode.d1.loss_dice: 0.5560, decode.d2.loss_cls: 0.1338, decode.d2.loss_mask: 0.3860, decode.d2.loss_dice: 0.5412, decode.d3.loss_cls: 0.1069, decode.d3.loss_mask: 0.3824, decode.d3.loss_dice: 0.5263, decode.d4.loss_cls: 0.1012, decode.d4.loss_mask: 0.3830, decode.d4.loss_dice: 0.5263, decode.d5.loss_cls: 0.0979, decode.d5.loss_mask: 0.3808, decode.d5.loss_dice: 0.5225, decode.d6.loss_cls: 0.0956, decode.d6.loss_mask: 0.3806, decode.d6.loss_dice: 0.5224, decode.d7.loss_cls: 0.0957, decode.d7.loss_mask: 0.3806, decode.d7.loss_dice: 0.5208, decode.d8.loss_cls: 0.0934, decode.d8.loss_mask: 0.3796, decode.d8.loss_dice: 0.5229, loss: 11.7730 +2022-05-06 07:56:15,145 - mmseg - INFO - Iter [32400/40000] lr: 2.728e-07, eta: 1:47:20, time: 0.721, data_time: 0.058, memory: 53770, decode.loss_cls: 0.0925, decode.loss_mask: 0.3605, decode.loss_dice: 0.5201, decode.d0.loss_cls: 1.4661, decode.d0.loss_mask: 0.3998, decode.d0.loss_dice: 0.6018, decode.d1.loss_cls: 0.2017, decode.d1.loss_mask: 0.3755, decode.d1.loss_dice: 0.5526, decode.d2.loss_cls: 0.1343, decode.d2.loss_mask: 0.3677, decode.d2.loss_dice: 0.5340, decode.d3.loss_cls: 0.1060, decode.d3.loss_mask: 0.3661, decode.d3.loss_dice: 0.5263, decode.d4.loss_cls: 0.1014, decode.d4.loss_mask: 0.3660, decode.d4.loss_dice: 0.5249, decode.d5.loss_cls: 0.0963, decode.d5.loss_mask: 0.3631, decode.d5.loss_dice: 0.5215, decode.d6.loss_cls: 0.0878, decode.d6.loss_mask: 0.3619, decode.d6.loss_dice: 0.5184, decode.d7.loss_cls: 0.0920, decode.d7.loss_mask: 0.3620, decode.d7.loss_dice: 0.5200, decode.d8.loss_cls: 0.0866, decode.d8.loss_mask: 0.3619, decode.d8.loss_dice: 0.5212, loss: 11.4902 +2022-05-06 07:56:48,902 - mmseg - INFO - Iter [32450/40000] lr: 2.710e-07, eta: 1:46:35, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0940, decode.loss_mask: 0.3680, decode.loss_dice: 0.5394, decode.d0.loss_cls: 1.4876, decode.d0.loss_mask: 0.4045, decode.d0.loss_dice: 0.6269, decode.d1.loss_cls: 0.2084, decode.d1.loss_mask: 0.3798, decode.d1.loss_dice: 0.5625, decode.d2.loss_cls: 0.1372, decode.d2.loss_mask: 0.3730, decode.d2.loss_dice: 0.5458, decode.d3.loss_cls: 0.1089, decode.d3.loss_mask: 0.3718, decode.d3.loss_dice: 0.5391, decode.d4.loss_cls: 0.1004, decode.d4.loss_mask: 0.3694, decode.d4.loss_dice: 0.5377, decode.d5.loss_cls: 0.0962, decode.d5.loss_mask: 0.3679, decode.d5.loss_dice: 0.5359, decode.d6.loss_cls: 0.0930, decode.d6.loss_mask: 0.3685, decode.d6.loss_dice: 0.5389, decode.d7.loss_cls: 0.0886, decode.d7.loss_mask: 0.3702, decode.d7.loss_dice: 0.5359, decode.d8.loss_cls: 0.0907, decode.d8.loss_mask: 0.3676, decode.d8.loss_dice: 0.5342, loss: 11.7418 +2022-05-06 07:57:22,440 - mmseg - INFO - Iter [32500/40000] lr: 2.692e-07, eta: 1:45:50, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0873, decode.loss_mask: 0.3741, decode.loss_dice: 0.5202, decode.d0.loss_cls: 1.4990, decode.d0.loss_mask: 0.4149, decode.d0.loss_dice: 0.6228, decode.d1.loss_cls: 0.1999, decode.d1.loss_mask: 0.3870, decode.d1.loss_dice: 0.5605, decode.d2.loss_cls: 0.1269, decode.d2.loss_mask: 0.3777, decode.d2.loss_dice: 0.5370, decode.d3.loss_cls: 0.1009, decode.d3.loss_mask: 0.3756, decode.d3.loss_dice: 0.5313, decode.d4.loss_cls: 0.0963, decode.d4.loss_mask: 0.3753, decode.d4.loss_dice: 0.5299, decode.d5.loss_cls: 0.0921, decode.d5.loss_mask: 0.3735, decode.d5.loss_dice: 0.5247, decode.d6.loss_cls: 0.0873, decode.d6.loss_mask: 0.3745, decode.d6.loss_dice: 0.5206, decode.d7.loss_cls: 0.0878, decode.d7.loss_mask: 0.3733, decode.d7.loss_dice: 0.5229, decode.d8.loss_cls: 0.0874, decode.d8.loss_mask: 0.3735, decode.d8.loss_dice: 0.5234, loss: 11.6578 +2022-05-06 07:57:55,988 - mmseg - INFO - Iter [32550/40000] lr: 2.675e-07, eta: 1:45:06, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0958, decode.loss_mask: 0.3759, decode.loss_dice: 0.5251, decode.d0.loss_cls: 1.4504, decode.d0.loss_mask: 0.4160, decode.d0.loss_dice: 0.6151, decode.d1.loss_cls: 0.1820, decode.d1.loss_mask: 0.3851, decode.d1.loss_dice: 0.5608, decode.d2.loss_cls: 0.1358, decode.d2.loss_mask: 0.3799, decode.d2.loss_dice: 0.5370, decode.d3.loss_cls: 0.1112, decode.d3.loss_mask: 0.3775, decode.d3.loss_dice: 0.5280, decode.d4.loss_cls: 0.1029, decode.d4.loss_mask: 0.3756, decode.d4.loss_dice: 0.5289, decode.d5.loss_cls: 0.1016, decode.d5.loss_mask: 0.3764, decode.d5.loss_dice: 0.5304, decode.d6.loss_cls: 0.0969, decode.d6.loss_mask: 0.3762, decode.d6.loss_dice: 0.5241, decode.d7.loss_cls: 0.0967, decode.d7.loss_mask: 0.3738, decode.d7.loss_dice: 0.5241, decode.d8.loss_cls: 0.0973, decode.d8.loss_mask: 0.3743, decode.d8.loss_dice: 0.5240, loss: 11.6786 +2022-05-06 07:58:29,589 - mmseg - INFO - Iter [32600/40000] lr: 2.657e-07, eta: 1:44:21, time: 0.673, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0993, decode.loss_mask: 0.3681, decode.loss_dice: 0.5398, decode.d0.loss_cls: 1.4594, decode.d0.loss_mask: 0.4092, decode.d0.loss_dice: 0.6364, decode.d1.loss_cls: 0.2026, decode.d1.loss_mask: 0.3804, decode.d1.loss_dice: 0.5768, decode.d2.loss_cls: 0.1355, decode.d2.loss_mask: 0.3737, decode.d2.loss_dice: 0.5561, decode.d3.loss_cls: 0.1198, decode.d3.loss_mask: 0.3704, decode.d3.loss_dice: 0.5467, decode.d4.loss_cls: 0.1134, decode.d4.loss_mask: 0.3700, decode.d4.loss_dice: 0.5475, decode.d5.loss_cls: 0.1036, decode.d5.loss_mask: 0.3673, decode.d5.loss_dice: 0.5460, decode.d6.loss_cls: 0.1038, decode.d6.loss_mask: 0.3679, decode.d6.loss_dice: 0.5390, decode.d7.loss_cls: 0.0989, decode.d7.loss_mask: 0.3681, decode.d7.loss_dice: 0.5392, decode.d8.loss_cls: 0.1055, decode.d8.loss_mask: 0.3670, decode.d8.loss_dice: 0.5386, loss: 11.8498 +2022-05-06 07:59:03,836 - mmseg - INFO - Iter [32650/40000] lr: 2.639e-07, eta: 1:43:37, time: 0.685, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0916, decode.loss_mask: 0.3835, decode.loss_dice: 0.5316, decode.d0.loss_cls: 1.4694, decode.d0.loss_mask: 0.4289, decode.d0.loss_dice: 0.6198, decode.d1.loss_cls: 0.1825, decode.d1.loss_mask: 0.3973, decode.d1.loss_dice: 0.5602, decode.d2.loss_cls: 0.1271, decode.d2.loss_mask: 0.3910, decode.d2.loss_dice: 0.5450, decode.d3.loss_cls: 0.1095, decode.d3.loss_mask: 0.3887, decode.d3.loss_dice: 0.5330, decode.d4.loss_cls: 0.1067, decode.d4.loss_mask: 0.3869, decode.d4.loss_dice: 0.5317, decode.d5.loss_cls: 0.0969, decode.d5.loss_mask: 0.3848, decode.d5.loss_dice: 0.5333, decode.d6.loss_cls: 0.0997, decode.d6.loss_mask: 0.3837, decode.d6.loss_dice: 0.5263, decode.d7.loss_cls: 0.0951, decode.d7.loss_mask: 0.3823, decode.d7.loss_dice: 0.5297, decode.d8.loss_cls: 0.0909, decode.d8.loss_mask: 0.3829, decode.d8.loss_dice: 0.5323, loss: 11.8223 +2022-05-06 07:59:37,773 - mmseg - INFO - Iter [32700/40000] lr: 2.621e-07, eta: 1:42:52, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.1008, decode.loss_mask: 0.3771, decode.loss_dice: 0.5343, decode.d0.loss_cls: 1.4834, decode.d0.loss_mask: 0.4162, decode.d0.loss_dice: 0.6307, decode.d1.loss_cls: 0.2086, decode.d1.loss_mask: 0.3913, decode.d1.loss_dice: 0.5743, decode.d2.loss_cls: 0.1384, decode.d2.loss_mask: 0.3842, decode.d2.loss_dice: 0.5551, decode.d3.loss_cls: 0.1144, decode.d3.loss_mask: 0.3834, decode.d3.loss_dice: 0.5448, decode.d4.loss_cls: 0.1130, decode.d4.loss_mask: 0.3803, decode.d4.loss_dice: 0.5428, decode.d5.loss_cls: 0.1059, decode.d5.loss_mask: 0.3799, decode.d5.loss_dice: 0.5428, decode.d6.loss_cls: 0.1026, decode.d6.loss_mask: 0.3782, decode.d6.loss_dice: 0.5381, decode.d7.loss_cls: 0.1008, decode.d7.loss_mask: 0.3773, decode.d7.loss_dice: 0.5370, decode.d8.loss_cls: 0.1022, decode.d8.loss_mask: 0.3755, decode.d8.loss_dice: 0.5383, loss: 11.9516 +2022-05-06 08:00:14,377 - mmseg - INFO - Iter [32750/40000] lr: 2.603e-07, eta: 1:42:09, time: 0.733, data_time: 0.062, memory: 53770, decode.loss_cls: 0.0968, decode.loss_mask: 0.3833, decode.loss_dice: 0.5450, decode.d0.loss_cls: 1.4559, decode.d0.loss_mask: 0.4246, decode.d0.loss_dice: 0.6366, decode.d1.loss_cls: 0.2011, decode.d1.loss_mask: 0.3965, decode.d1.loss_dice: 0.5793, decode.d2.loss_cls: 0.1411, decode.d2.loss_mask: 0.3900, decode.d2.loss_dice: 0.5684, decode.d3.loss_cls: 0.1229, decode.d3.loss_mask: 0.3874, decode.d3.loss_dice: 0.5520, decode.d4.loss_cls: 0.1124, decode.d4.loss_mask: 0.3857, decode.d4.loss_dice: 0.5517, decode.d5.loss_cls: 0.1077, decode.d5.loss_mask: 0.3855, decode.d5.loss_dice: 0.5478, decode.d6.loss_cls: 0.1012, decode.d6.loss_mask: 0.3848, decode.d6.loss_dice: 0.5453, decode.d7.loss_cls: 0.1001, decode.d7.loss_mask: 0.3843, decode.d7.loss_dice: 0.5465, decode.d8.loss_cls: 0.0973, decode.d8.loss_mask: 0.3842, decode.d8.loss_dice: 0.5487, loss: 12.0642 +2022-05-06 08:00:48,452 - mmseg - INFO - Iter [32800/40000] lr: 2.585e-07, eta: 1:41:24, time: 0.681, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0830, decode.loss_mask: 0.3655, decode.loss_dice: 0.5093, decode.d0.loss_cls: 1.4678, decode.d0.loss_mask: 0.4096, decode.d0.loss_dice: 0.6021, decode.d1.loss_cls: 0.1943, decode.d1.loss_mask: 0.3808, decode.d1.loss_dice: 0.5402, decode.d2.loss_cls: 0.1241, decode.d2.loss_mask: 0.3695, decode.d2.loss_dice: 0.5242, decode.d3.loss_cls: 0.1047, decode.d3.loss_mask: 0.3688, decode.d3.loss_dice: 0.5152, decode.d4.loss_cls: 0.0947, decode.d4.loss_mask: 0.3676, decode.d4.loss_dice: 0.5094, decode.d5.loss_cls: 0.0880, decode.d5.loss_mask: 0.3680, decode.d5.loss_dice: 0.5157, decode.d6.loss_cls: 0.0893, decode.d6.loss_mask: 0.3673, decode.d6.loss_dice: 0.5110, decode.d7.loss_cls: 0.0856, decode.d7.loss_mask: 0.3649, decode.d7.loss_dice: 0.5077, decode.d8.loss_cls: 0.0871, decode.d8.loss_mask: 0.3660, decode.d8.loss_dice: 0.5092, loss: 11.3903 +2022-05-06 08:01:21,993 - mmseg - INFO - Iter [32850/40000] lr: 2.567e-07, eta: 1:40:40, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0858, decode.loss_mask: 0.3833, decode.loss_dice: 0.5333, decode.d0.loss_cls: 1.4553, decode.d0.loss_mask: 0.4201, decode.d0.loss_dice: 0.6146, decode.d1.loss_cls: 0.1830, decode.d1.loss_mask: 0.3974, decode.d1.loss_dice: 0.5605, decode.d2.loss_cls: 0.1275, decode.d2.loss_mask: 0.3865, decode.d2.loss_dice: 0.5424, decode.d3.loss_cls: 0.1035, decode.d3.loss_mask: 0.3853, decode.d3.loss_dice: 0.5339, decode.d4.loss_cls: 0.0923, decode.d4.loss_mask: 0.3855, decode.d4.loss_dice: 0.5394, decode.d5.loss_cls: 0.0923, decode.d5.loss_mask: 0.3850, decode.d5.loss_dice: 0.5357, decode.d6.loss_cls: 0.0909, decode.d6.loss_mask: 0.3829, decode.d6.loss_dice: 0.5300, decode.d7.loss_cls: 0.0893, decode.d7.loss_mask: 0.3834, decode.d7.loss_dice: 0.5365, decode.d8.loss_cls: 0.0870, decode.d8.loss_mask: 0.3829, decode.d8.loss_dice: 0.5314, loss: 11.7567 +2022-05-06 08:01:55,728 - mmseg - INFO - Iter [32900/40000] lr: 2.549e-07, eta: 1:39:55, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0901, decode.loss_mask: 0.3742, decode.loss_dice: 0.5172, decode.d0.loss_cls: 1.4502, decode.d0.loss_mask: 0.4146, decode.d0.loss_dice: 0.6102, decode.d1.loss_cls: 0.1880, decode.d1.loss_mask: 0.3887, decode.d1.loss_dice: 0.5472, decode.d2.loss_cls: 0.1336, decode.d2.loss_mask: 0.3792, decode.d2.loss_dice: 0.5263, decode.d3.loss_cls: 0.1044, decode.d3.loss_mask: 0.3763, decode.d3.loss_dice: 0.5199, decode.d4.loss_cls: 0.1036, decode.d4.loss_mask: 0.3741, decode.d4.loss_dice: 0.5208, decode.d5.loss_cls: 0.0948, decode.d5.loss_mask: 0.3735, decode.d5.loss_dice: 0.5178, decode.d6.loss_cls: 0.0964, decode.d6.loss_mask: 0.3757, decode.d6.loss_dice: 0.5161, decode.d7.loss_cls: 0.0928, decode.d7.loss_mask: 0.3751, decode.d7.loss_dice: 0.5192, decode.d8.loss_cls: 0.0890, decode.d8.loss_mask: 0.3733, decode.d8.loss_dice: 0.5164, loss: 11.5589 +2022-05-06 08:02:28,842 - mmseg - INFO - Iter [32950/40000] lr: 2.531e-07, eta: 1:39:11, time: 0.662, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0805, decode.loss_mask: 0.3783, decode.loss_dice: 0.5242, decode.d0.loss_cls: 1.4586, decode.d0.loss_mask: 0.4214, decode.d0.loss_dice: 0.6092, decode.d1.loss_cls: 0.1799, decode.d1.loss_mask: 0.3902, decode.d1.loss_dice: 0.5561, decode.d2.loss_cls: 0.1158, decode.d2.loss_mask: 0.3842, decode.d2.loss_dice: 0.5401, decode.d3.loss_cls: 0.0941, decode.d3.loss_mask: 0.3815, decode.d3.loss_dice: 0.5292, decode.d4.loss_cls: 0.0883, decode.d4.loss_mask: 0.3797, decode.d4.loss_dice: 0.5303, decode.d5.loss_cls: 0.0815, decode.d5.loss_mask: 0.3775, decode.d5.loss_dice: 0.5285, decode.d6.loss_cls: 0.0818, decode.d6.loss_mask: 0.3780, decode.d6.loss_dice: 0.5256, decode.d7.loss_cls: 0.0795, decode.d7.loss_mask: 0.3772, decode.d7.loss_dice: 0.5244, decode.d8.loss_cls: 0.0820, decode.d8.loss_mask: 0.3766, decode.d8.loss_dice: 0.5255, loss: 11.5796 +2022-05-06 08:03:02,533 - mmseg - INFO - Saving checkpoint at 33000 iterations +2022-05-06 08:03:29,549 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 08:03:29,552 - mmseg - INFO - Iter [33000/40000] lr: 2.513e-07, eta: 1:38:33, time: 1.212, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0912, decode.loss_mask: 0.3717, decode.loss_dice: 0.5368, decode.d0.loss_cls: 1.4959, decode.d0.loss_mask: 0.4148, decode.d0.loss_dice: 0.6294, decode.d1.loss_cls: 0.1908, decode.d1.loss_mask: 0.3884, decode.d1.loss_dice: 0.5753, decode.d2.loss_cls: 0.1230, decode.d2.loss_mask: 0.3821, decode.d2.loss_dice: 0.5550, decode.d3.loss_cls: 0.1070, decode.d3.loss_mask: 0.3769, decode.d3.loss_dice: 0.5420, decode.d4.loss_cls: 0.1015, decode.d4.loss_mask: 0.3773, decode.d4.loss_dice: 0.5425, decode.d5.loss_cls: 0.0955, decode.d5.loss_mask: 0.3752, decode.d5.loss_dice: 0.5410, decode.d6.loss_cls: 0.0910, decode.d6.loss_mask: 0.3747, decode.d6.loss_dice: 0.5379, decode.d7.loss_cls: 0.0923, decode.d7.loss_mask: 0.3739, decode.d7.loss_dice: 0.5342, decode.d8.loss_cls: 0.0853, decode.d8.loss_mask: 0.3733, decode.d8.loss_dice: 0.5341, loss: 11.8100 +2022-05-06 08:04:06,056 - mmseg - INFO - Iter [33050/40000] lr: 2.495e-07, eta: 1:37:50, time: 0.732, data_time: 0.060, memory: 53770, decode.loss_cls: 0.1022, decode.loss_mask: 0.3738, decode.loss_dice: 0.5248, decode.d0.loss_cls: 1.4922, decode.d0.loss_mask: 0.4210, decode.d0.loss_dice: 0.6245, decode.d1.loss_cls: 0.2024, decode.d1.loss_mask: 0.3907, decode.d1.loss_dice: 0.5615, decode.d2.loss_cls: 0.1362, decode.d2.loss_mask: 0.3813, decode.d2.loss_dice: 0.5397, decode.d3.loss_cls: 0.1160, decode.d3.loss_mask: 0.3772, decode.d3.loss_dice: 0.5318, decode.d4.loss_cls: 0.1104, decode.d4.loss_mask: 0.3772, decode.d4.loss_dice: 0.5317, decode.d5.loss_cls: 0.1088, decode.d5.loss_mask: 0.3762, decode.d5.loss_dice: 0.5269, decode.d6.loss_cls: 0.1011, decode.d6.loss_mask: 0.3735, decode.d6.loss_dice: 0.5273, decode.d7.loss_cls: 0.0971, decode.d7.loss_mask: 0.3741, decode.d7.loss_dice: 0.5281, decode.d8.loss_cls: 0.0981, decode.d8.loss_mask: 0.3736, decode.d8.loss_dice: 0.5285, loss: 11.8081 +2022-05-06 08:04:39,367 - mmseg - INFO - Iter [33100/40000] lr: 2.477e-07, eta: 1:37:05, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0843, decode.loss_mask: 0.3762, decode.loss_dice: 0.5386, decode.d0.loss_cls: 1.4573, decode.d0.loss_mask: 0.4196, decode.d0.loss_dice: 0.6313, decode.d1.loss_cls: 0.1775, decode.d1.loss_mask: 0.3869, decode.d1.loss_dice: 0.5663, decode.d2.loss_cls: 0.1265, decode.d2.loss_mask: 0.3785, decode.d2.loss_dice: 0.5443, decode.d3.loss_cls: 0.0958, decode.d3.loss_mask: 0.3767, decode.d3.loss_dice: 0.5419, decode.d4.loss_cls: 0.0902, decode.d4.loss_mask: 0.3750, decode.d4.loss_dice: 0.5410, decode.d5.loss_cls: 0.0847, decode.d5.loss_mask: 0.3743, decode.d5.loss_dice: 0.5418, decode.d6.loss_cls: 0.0792, decode.d6.loss_mask: 0.3749, decode.d6.loss_dice: 0.5384, decode.d7.loss_cls: 0.0792, decode.d7.loss_mask: 0.3753, decode.d7.loss_dice: 0.5381, decode.d8.loss_cls: 0.0803, decode.d8.loss_mask: 0.3742, decode.d8.loss_dice: 0.5385, loss: 11.6868 +2022-05-06 08:05:13,221 - mmseg - INFO - Iter [33150/40000] lr: 2.459e-07, eta: 1:36:21, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0835, decode.loss_mask: 0.3697, decode.loss_dice: 0.5056, decode.d0.loss_cls: 1.4270, decode.d0.loss_mask: 0.4103, decode.d0.loss_dice: 0.5935, decode.d1.loss_cls: 0.1923, decode.d1.loss_mask: 0.3838, decode.d1.loss_dice: 0.5376, decode.d2.loss_cls: 0.1238, decode.d2.loss_mask: 0.3758, decode.d2.loss_dice: 0.5209, decode.d3.loss_cls: 0.0965, decode.d3.loss_mask: 0.3724, decode.d3.loss_dice: 0.5043, decode.d4.loss_cls: 0.0986, decode.d4.loss_mask: 0.3705, decode.d4.loss_dice: 0.5076, decode.d5.loss_cls: 0.0886, decode.d5.loss_mask: 0.3702, decode.d5.loss_dice: 0.5089, decode.d6.loss_cls: 0.0863, decode.d6.loss_mask: 0.3707, decode.d6.loss_dice: 0.5077, decode.d7.loss_cls: 0.0804, decode.d7.loss_mask: 0.3698, decode.d7.loss_dice: 0.5045, decode.d8.loss_cls: 0.0784, decode.d8.loss_mask: 0.3697, decode.d8.loss_dice: 0.5067, loss: 11.3156 +2022-05-06 08:05:47,054 - mmseg - INFO - Iter [33200/40000] lr: 2.441e-07, eta: 1:35:37, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0841, decode.loss_mask: 0.3678, decode.loss_dice: 0.5235, decode.d0.loss_cls: 1.4897, decode.d0.loss_mask: 0.4067, decode.d0.loss_dice: 0.6138, decode.d1.loss_cls: 0.1910, decode.d1.loss_mask: 0.3822, decode.d1.loss_dice: 0.5585, decode.d2.loss_cls: 0.1246, decode.d2.loss_mask: 0.3735, decode.d2.loss_dice: 0.5355, decode.d3.loss_cls: 0.1031, decode.d3.loss_mask: 0.3718, decode.d3.loss_dice: 0.5269, decode.d4.loss_cls: 0.0962, decode.d4.loss_mask: 0.3710, decode.d4.loss_dice: 0.5251, decode.d5.loss_cls: 0.0897, decode.d5.loss_mask: 0.3701, decode.d5.loss_dice: 0.5287, decode.d6.loss_cls: 0.0874, decode.d6.loss_mask: 0.3690, decode.d6.loss_dice: 0.5243, decode.d7.loss_cls: 0.0837, decode.d7.loss_mask: 0.3698, decode.d7.loss_dice: 0.5235, decode.d8.loss_cls: 0.0821, decode.d8.loss_mask: 0.3684, decode.d8.loss_dice: 0.5236, loss: 11.5654 +2022-05-06 08:06:20,659 - mmseg - INFO - Iter [33250/40000] lr: 2.423e-07, eta: 1:34:53, time: 0.673, data_time: 0.010, memory: 53770, decode.loss_cls: 0.1020, decode.loss_mask: 0.3810, decode.loss_dice: 0.5445, decode.d0.loss_cls: 1.4682, decode.d0.loss_mask: 0.4257, decode.d0.loss_dice: 0.6366, decode.d1.loss_cls: 0.1953, decode.d1.loss_mask: 0.3990, decode.d1.loss_dice: 0.5786, decode.d2.loss_cls: 0.1366, decode.d2.loss_mask: 0.3885, decode.d2.loss_dice: 0.5563, decode.d3.loss_cls: 0.1113, decode.d3.loss_mask: 0.3860, decode.d3.loss_dice: 0.5495, decode.d4.loss_cls: 0.1061, decode.d4.loss_mask: 0.3827, decode.d4.loss_dice: 0.5473, decode.d5.loss_cls: 0.1035, decode.d5.loss_mask: 0.3830, decode.d5.loss_dice: 0.5489, decode.d6.loss_cls: 0.1009, decode.d6.loss_mask: 0.3838, decode.d6.loss_dice: 0.5466, decode.d7.loss_cls: 0.0990, decode.d7.loss_mask: 0.3818, decode.d7.loss_dice: 0.5443, decode.d8.loss_cls: 0.1011, decode.d8.loss_mask: 0.3821, decode.d8.loss_dice: 0.5444, loss: 12.0148 +2022-05-06 08:06:53,926 - mmseg - INFO - Iter [33300/40000] lr: 2.405e-07, eta: 1:34:09, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0947, decode.loss_mask: 0.3639, decode.loss_dice: 0.5187, decode.d0.loss_cls: 1.4658, decode.d0.loss_mask: 0.4064, decode.d0.loss_dice: 0.6110, decode.d1.loss_cls: 0.1963, decode.d1.loss_mask: 0.3773, decode.d1.loss_dice: 0.5525, decode.d2.loss_cls: 0.1329, decode.d2.loss_mask: 0.3715, decode.d2.loss_dice: 0.5343, decode.d3.loss_cls: 0.1149, decode.d3.loss_mask: 0.3681, decode.d3.loss_dice: 0.5215, decode.d4.loss_cls: 0.1052, decode.d4.loss_mask: 0.3659, decode.d4.loss_dice: 0.5204, decode.d5.loss_cls: 0.1031, decode.d5.loss_mask: 0.3645, decode.d5.loss_dice: 0.5204, decode.d6.loss_cls: 0.0984, decode.d6.loss_mask: 0.3653, decode.d6.loss_dice: 0.5199, decode.d7.loss_cls: 0.0934, decode.d7.loss_mask: 0.3651, decode.d7.loss_dice: 0.5185, decode.d8.loss_cls: 0.0966, decode.d8.loss_mask: 0.3651, decode.d8.loss_dice: 0.5211, loss: 11.5529 +2022-05-06 08:07:30,585 - mmseg - INFO - Iter [33350/40000] lr: 2.387e-07, eta: 1:33:25, time: 0.733, data_time: 0.058, memory: 53770, decode.loss_cls: 0.0924, decode.loss_mask: 0.3745, decode.loss_dice: 0.5254, decode.d0.loss_cls: 1.4821, decode.d0.loss_mask: 0.4186, decode.d0.loss_dice: 0.6181, decode.d1.loss_cls: 0.2059, decode.d1.loss_mask: 0.3877, decode.d1.loss_dice: 0.5586, decode.d2.loss_cls: 0.1371, decode.d2.loss_mask: 0.3795, decode.d2.loss_dice: 0.5404, decode.d3.loss_cls: 0.1106, decode.d3.loss_mask: 0.3778, decode.d3.loss_dice: 0.5286, decode.d4.loss_cls: 0.0980, decode.d4.loss_mask: 0.3758, decode.d4.loss_dice: 0.5290, decode.d5.loss_cls: 0.0919, decode.d5.loss_mask: 0.3768, decode.d5.loss_dice: 0.5335, decode.d6.loss_cls: 0.0892, decode.d6.loss_mask: 0.3764, decode.d6.loss_dice: 0.5276, decode.d7.loss_cls: 0.0873, decode.d7.loss_mask: 0.3758, decode.d7.loss_dice: 0.5289, decode.d8.loss_cls: 0.0929, decode.d8.loss_mask: 0.3753, decode.d8.loss_dice: 0.5319, loss: 11.7274 +2022-05-06 08:08:04,240 - mmseg - INFO - Iter [33400/40000] lr: 2.369e-07, eta: 1:32:41, time: 0.673, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0867, decode.loss_mask: 0.3793, decode.loss_dice: 0.5077, decode.d0.loss_cls: 1.4755, decode.d0.loss_mask: 0.4225, decode.d0.loss_dice: 0.5965, decode.d1.loss_cls: 0.1921, decode.d1.loss_mask: 0.3937, decode.d1.loss_dice: 0.5385, decode.d2.loss_cls: 0.1274, decode.d2.loss_mask: 0.3861, decode.d2.loss_dice: 0.5203, decode.d3.loss_cls: 0.1006, decode.d3.loss_mask: 0.3820, decode.d3.loss_dice: 0.5127, decode.d4.loss_cls: 0.1023, decode.d4.loss_mask: 0.3821, decode.d4.loss_dice: 0.5166, decode.d5.loss_cls: 0.0922, decode.d5.loss_mask: 0.3811, decode.d5.loss_dice: 0.5129, decode.d6.loss_cls: 0.0934, decode.d6.loss_mask: 0.3804, decode.d6.loss_dice: 0.5085, decode.d7.loss_cls: 0.0894, decode.d7.loss_mask: 0.3800, decode.d7.loss_dice: 0.5081, decode.d8.loss_cls: 0.0867, decode.d8.loss_mask: 0.3790, decode.d8.loss_dice: 0.5085, loss: 11.5425 +2022-05-06 08:08:38,259 - mmseg - INFO - Iter [33450/40000] lr: 2.351e-07, eta: 1:31:57, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0791, decode.loss_mask: 0.3755, decode.loss_dice: 0.5106, decode.d0.loss_cls: 1.3749, decode.d0.loss_mask: 0.4151, decode.d0.loss_dice: 0.5887, decode.d1.loss_cls: 0.1800, decode.d1.loss_mask: 0.3885, decode.d1.loss_dice: 0.5397, decode.d2.loss_cls: 0.1154, decode.d2.loss_mask: 0.3817, decode.d2.loss_dice: 0.5242, decode.d3.loss_cls: 0.1010, decode.d3.loss_mask: 0.3789, decode.d3.loss_dice: 0.5137, decode.d4.loss_cls: 0.0945, decode.d4.loss_mask: 0.3787, decode.d4.loss_dice: 0.5139, decode.d5.loss_cls: 0.0847, decode.d5.loss_mask: 0.3783, decode.d5.loss_dice: 0.5147, decode.d6.loss_cls: 0.0816, decode.d6.loss_mask: 0.3764, decode.d6.loss_dice: 0.5082, decode.d7.loss_cls: 0.0808, decode.d7.loss_mask: 0.3760, decode.d7.loss_dice: 0.5097, decode.d8.loss_cls: 0.0766, decode.d8.loss_mask: 0.3760, decode.d8.loss_dice: 0.5125, loss: 11.3298 +2022-05-06 08:09:12,070 - mmseg - INFO - Iter [33500/40000] lr: 2.334e-07, eta: 1:31:13, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0887, decode.loss_mask: 0.3792, decode.loss_dice: 0.5493, decode.d0.loss_cls: 1.4816, decode.d0.loss_mask: 0.4147, decode.d0.loss_dice: 0.6440, decode.d1.loss_cls: 0.2009, decode.d1.loss_mask: 0.3928, decode.d1.loss_dice: 0.5814, decode.d2.loss_cls: 0.1300, decode.d2.loss_mask: 0.3850, decode.d2.loss_dice: 0.5588, decode.d3.loss_cls: 0.1046, decode.d3.loss_mask: 0.3809, decode.d3.loss_dice: 0.5475, decode.d4.loss_cls: 0.0978, decode.d4.loss_mask: 0.3801, decode.d4.loss_dice: 0.5488, decode.d5.loss_cls: 0.0981, decode.d5.loss_mask: 0.3782, decode.d5.loss_dice: 0.5459, decode.d6.loss_cls: 0.0928, decode.d6.loss_mask: 0.3786, decode.d6.loss_dice: 0.5499, decode.d7.loss_cls: 0.0920, decode.d7.loss_mask: 0.3776, decode.d7.loss_dice: 0.5493, decode.d8.loss_cls: 0.0903, decode.d8.loss_mask: 0.3778, decode.d8.loss_dice: 0.5447, loss: 11.9415 +2022-05-06 08:09:46,209 - mmseg - INFO - Iter [33550/40000] lr: 2.316e-07, eta: 1:30:29, time: 0.683, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0942, decode.loss_mask: 0.3732, decode.loss_dice: 0.5301, decode.d0.loss_cls: 1.4706, decode.d0.loss_mask: 0.4213, decode.d0.loss_dice: 0.6260, decode.d1.loss_cls: 0.1963, decode.d1.loss_mask: 0.3853, decode.d1.loss_dice: 0.5638, decode.d2.loss_cls: 0.1295, decode.d2.loss_mask: 0.3786, decode.d2.loss_dice: 0.5437, decode.d3.loss_cls: 0.1150, decode.d3.loss_mask: 0.3762, decode.d3.loss_dice: 0.5362, decode.d4.loss_cls: 0.1046, decode.d4.loss_mask: 0.3763, decode.d4.loss_dice: 0.5320, decode.d5.loss_cls: 0.0968, decode.d5.loss_mask: 0.3746, decode.d5.loss_dice: 0.5309, decode.d6.loss_cls: 0.0942, decode.d6.loss_mask: 0.3734, decode.d6.loss_dice: 0.5298, decode.d7.loss_cls: 0.0922, decode.d7.loss_mask: 0.3723, decode.d7.loss_dice: 0.5269, decode.d8.loss_cls: 0.0930, decode.d8.loss_mask: 0.3729, decode.d8.loss_dice: 0.5283, loss: 11.7382 +2022-05-06 08:10:20,059 - mmseg - INFO - Iter [33600/40000] lr: 2.298e-07, eta: 1:29:46, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0882, decode.loss_mask: 0.3776, decode.loss_dice: 0.5510, decode.d0.loss_cls: 1.4919, decode.d0.loss_mask: 0.4180, decode.d0.loss_dice: 0.6381, decode.d1.loss_cls: 0.1978, decode.d1.loss_mask: 0.3908, decode.d1.loss_dice: 0.5826, decode.d2.loss_cls: 0.1228, decode.d2.loss_mask: 0.3833, decode.d2.loss_dice: 0.5628, decode.d3.loss_cls: 0.1108, decode.d3.loss_mask: 0.3805, decode.d3.loss_dice: 0.5570, decode.d4.loss_cls: 0.1001, decode.d4.loss_mask: 0.3782, decode.d4.loss_dice: 0.5504, decode.d5.loss_cls: 0.0966, decode.d5.loss_mask: 0.3773, decode.d5.loss_dice: 0.5493, decode.d6.loss_cls: 0.0899, decode.d6.loss_mask: 0.3776, decode.d6.loss_dice: 0.5493, decode.d7.loss_cls: 0.0900, decode.d7.loss_mask: 0.3763, decode.d7.loss_dice: 0.5476, decode.d8.loss_cls: 0.0906, decode.d8.loss_mask: 0.3779, decode.d8.loss_dice: 0.5517, loss: 11.9559 +2022-05-06 08:10:56,722 - mmseg - INFO - Iter [33650/40000] lr: 2.280e-07, eta: 1:29:02, time: 0.734, data_time: 0.061, memory: 53770, decode.loss_cls: 0.0788, decode.loss_mask: 0.3790, decode.loss_dice: 0.5293, decode.d0.loss_cls: 1.4570, decode.d0.loss_mask: 0.4206, decode.d0.loss_dice: 0.6207, decode.d1.loss_cls: 0.1928, decode.d1.loss_mask: 0.3901, decode.d1.loss_dice: 0.5604, decode.d2.loss_cls: 0.1160, decode.d2.loss_mask: 0.3845, decode.d2.loss_dice: 0.5472, decode.d3.loss_cls: 0.0952, decode.d3.loss_mask: 0.3829, decode.d3.loss_dice: 0.5373, decode.d4.loss_cls: 0.0827, decode.d4.loss_mask: 0.3826, decode.d4.loss_dice: 0.5389, decode.d5.loss_cls: 0.0877, decode.d5.loss_mask: 0.3806, decode.d5.loss_dice: 0.5327, decode.d6.loss_cls: 0.0800, decode.d6.loss_mask: 0.3796, decode.d6.loss_dice: 0.5270, decode.d7.loss_cls: 0.0783, decode.d7.loss_mask: 0.3798, decode.d7.loss_dice: 0.5298, decode.d8.loss_cls: 0.0771, decode.d8.loss_mask: 0.3797, decode.d8.loss_dice: 0.5288, loss: 11.6571 +2022-05-06 08:11:31,291 - mmseg - INFO - Iter [33700/40000] lr: 2.262e-07, eta: 1:28:19, time: 0.692, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0816, decode.loss_mask: 0.3859, decode.loss_dice: 0.5261, decode.d0.loss_cls: 1.4358, decode.d0.loss_mask: 0.4263, decode.d0.loss_dice: 0.6212, decode.d1.loss_cls: 0.1815, decode.d1.loss_mask: 0.3963, decode.d1.loss_dice: 0.5586, decode.d2.loss_cls: 0.1180, decode.d2.loss_mask: 0.3906, decode.d2.loss_dice: 0.5413, decode.d3.loss_cls: 0.0972, decode.d3.loss_mask: 0.3888, decode.d3.loss_dice: 0.5327, decode.d4.loss_cls: 0.0944, decode.d4.loss_mask: 0.3876, decode.d4.loss_dice: 0.5332, decode.d5.loss_cls: 0.0887, decode.d5.loss_mask: 0.3861, decode.d5.loss_dice: 0.5331, decode.d6.loss_cls: 0.0894, decode.d6.loss_mask: 0.3863, decode.d6.loss_dice: 0.5280, decode.d7.loss_cls: 0.0813, decode.d7.loss_mask: 0.3849, decode.d7.loss_dice: 0.5301, decode.d8.loss_cls: 0.0868, decode.d8.loss_mask: 0.3852, decode.d8.loss_dice: 0.5265, loss: 11.7034 +2022-05-06 08:12:05,199 - mmseg - INFO - Iter [33750/40000] lr: 2.244e-07, eta: 1:27:35, time: 0.678, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0725, decode.loss_mask: 0.3676, decode.loss_dice: 0.4977, decode.d0.loss_cls: 1.4377, decode.d0.loss_mask: 0.4047, decode.d0.loss_dice: 0.5808, decode.d1.loss_cls: 0.1735, decode.d1.loss_mask: 0.3809, decode.d1.loss_dice: 0.5276, decode.d2.loss_cls: 0.1106, decode.d2.loss_mask: 0.3735, decode.d2.loss_dice: 0.5097, decode.d3.loss_cls: 0.0863, decode.d3.loss_mask: 0.3720, decode.d3.loss_dice: 0.5020, decode.d4.loss_cls: 0.0794, decode.d4.loss_mask: 0.3707, decode.d4.loss_dice: 0.5013, decode.d5.loss_cls: 0.0811, decode.d5.loss_mask: 0.3696, decode.d5.loss_dice: 0.4986, decode.d6.loss_cls: 0.0724, decode.d6.loss_mask: 0.3694, decode.d6.loss_dice: 0.4994, decode.d7.loss_cls: 0.0698, decode.d7.loss_mask: 0.3684, decode.d7.loss_dice: 0.4970, decode.d8.loss_cls: 0.0715, decode.d8.loss_mask: 0.3685, decode.d8.loss_dice: 0.4954, loss: 11.1098 +2022-05-06 08:12:39,219 - mmseg - INFO - Iter [33800/40000] lr: 2.226e-07, eta: 1:26:51, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0780, decode.loss_mask: 0.3729, decode.loss_dice: 0.5172, decode.d0.loss_cls: 1.4443, decode.d0.loss_mask: 0.4107, decode.d0.loss_dice: 0.6094, decode.d1.loss_cls: 0.1957, decode.d1.loss_mask: 0.3869, decode.d1.loss_dice: 0.5503, decode.d2.loss_cls: 0.1140, decode.d2.loss_mask: 0.3789, decode.d2.loss_dice: 0.5329, decode.d3.loss_cls: 0.0922, decode.d3.loss_mask: 0.3745, decode.d3.loss_dice: 0.5236, decode.d4.loss_cls: 0.0869, decode.d4.loss_mask: 0.3769, decode.d4.loss_dice: 0.5245, decode.d5.loss_cls: 0.0853, decode.d5.loss_mask: 0.3734, decode.d5.loss_dice: 0.5184, decode.d6.loss_cls: 0.0818, decode.d6.loss_mask: 0.3730, decode.d6.loss_dice: 0.5162, decode.d7.loss_cls: 0.0754, decode.d7.loss_mask: 0.3725, decode.d7.loss_dice: 0.5166, decode.d8.loss_cls: 0.0765, decode.d8.loss_mask: 0.3733, decode.d8.loss_dice: 0.5176, loss: 11.4499 +2022-05-06 08:13:13,016 - mmseg - INFO - Iter [33850/40000] lr: 2.208e-07, eta: 1:26:07, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0895, decode.loss_mask: 0.3729, decode.loss_dice: 0.5010, decode.d0.loss_cls: 1.4386, decode.d0.loss_mask: 0.4151, decode.d0.loss_dice: 0.5946, decode.d1.loss_cls: 0.1937, decode.d1.loss_mask: 0.3883, decode.d1.loss_dice: 0.5379, decode.d2.loss_cls: 0.1206, decode.d2.loss_mask: 0.3806, decode.d2.loss_dice: 0.5128, decode.d3.loss_cls: 0.1018, decode.d3.loss_mask: 0.3773, decode.d3.loss_dice: 0.5023, decode.d4.loss_cls: 0.0956, decode.d4.loss_mask: 0.3768, decode.d4.loss_dice: 0.5058, decode.d5.loss_cls: 0.0912, decode.d5.loss_mask: 0.3740, decode.d5.loss_dice: 0.5033, decode.d6.loss_cls: 0.0899, decode.d6.loss_mask: 0.3736, decode.d6.loss_dice: 0.5018, decode.d7.loss_cls: 0.0857, decode.d7.loss_mask: 0.3744, decode.d7.loss_dice: 0.5025, decode.d8.loss_cls: 0.0877, decode.d8.loss_mask: 0.3725, decode.d8.loss_dice: 0.5015, loss: 11.3632 +2022-05-06 08:13:46,631 - mmseg - INFO - Iter [33900/40000] lr: 2.190e-07, eta: 1:25:24, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0919, decode.loss_mask: 0.3617, decode.loss_dice: 0.5365, decode.d0.loss_cls: 1.4828, decode.d0.loss_mask: 0.4021, decode.d0.loss_dice: 0.6316, decode.d1.loss_cls: 0.2091, decode.d1.loss_mask: 0.3731, decode.d1.loss_dice: 0.5652, decode.d2.loss_cls: 0.1316, decode.d2.loss_mask: 0.3677, decode.d2.loss_dice: 0.5456, decode.d3.loss_cls: 0.1155, decode.d3.loss_mask: 0.3641, decode.d3.loss_dice: 0.5356, decode.d4.loss_cls: 0.0991, decode.d4.loss_mask: 0.3648, decode.d4.loss_dice: 0.5369, decode.d5.loss_cls: 0.0998, decode.d5.loss_mask: 0.3629, decode.d5.loss_dice: 0.5345, decode.d6.loss_cls: 0.0948, decode.d6.loss_mask: 0.3623, decode.d6.loss_dice: 0.5332, decode.d7.loss_cls: 0.0901, decode.d7.loss_mask: 0.3606, decode.d7.loss_dice: 0.5302, decode.d8.loss_cls: 0.0961, decode.d8.loss_mask: 0.3617, decode.d8.loss_dice: 0.5313, loss: 11.6724 +2022-05-06 08:14:20,246 - mmseg - INFO - Iter [33950/40000] lr: 2.172e-07, eta: 1:24:40, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0943, decode.loss_mask: 0.3811, decode.loss_dice: 0.5231, decode.d0.loss_cls: 1.4795, decode.d0.loss_mask: 0.4176, decode.d0.loss_dice: 0.6195, decode.d1.loss_cls: 0.2125, decode.d1.loss_mask: 0.3957, decode.d1.loss_dice: 0.5632, decode.d2.loss_cls: 0.1448, decode.d2.loss_mask: 0.3909, decode.d2.loss_dice: 0.5405, decode.d3.loss_cls: 0.1143, decode.d3.loss_mask: 0.3867, decode.d3.loss_dice: 0.5330, decode.d4.loss_cls: 0.0998, decode.d4.loss_mask: 0.3855, decode.d4.loss_dice: 0.5348, decode.d5.loss_cls: 0.0950, decode.d5.loss_mask: 0.3835, decode.d5.loss_dice: 0.5291, decode.d6.loss_cls: 0.1003, decode.d6.loss_mask: 0.3807, decode.d6.loss_dice: 0.5238, decode.d7.loss_cls: 0.0965, decode.d7.loss_mask: 0.3817, decode.d7.loss_dice: 0.5256, decode.d8.loss_cls: 0.0951, decode.d8.loss_mask: 0.3820, decode.d8.loss_dice: 0.5290, loss: 11.8390 +2022-05-06 08:14:56,144 - mmseg - INFO - Saving checkpoint at 34000 iterations +2022-05-06 08:15:22,186 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 08:15:22,193 - mmseg - INFO - Iter [34000/40000] lr: 2.154e-07, eta: 1:24:02, time: 1.237, data_time: 0.058, memory: 53770, decode.loss_cls: 0.0968, decode.loss_mask: 0.3858, decode.loss_dice: 0.5398, decode.d0.loss_cls: 1.4751, decode.d0.loss_mask: 0.4312, decode.d0.loss_dice: 0.6308, decode.d1.loss_cls: 0.2015, decode.d1.loss_mask: 0.3996, decode.d1.loss_dice: 0.5682, decode.d2.loss_cls: 0.1373, decode.d2.loss_mask: 0.3931, decode.d2.loss_dice: 0.5496, decode.d3.loss_cls: 0.1120, decode.d3.loss_mask: 0.3897, decode.d3.loss_dice: 0.5401, decode.d4.loss_cls: 0.1063, decode.d4.loss_mask: 0.3885, decode.d4.loss_dice: 0.5453, decode.d5.loss_cls: 0.1007, decode.d5.loss_mask: 0.3865, decode.d5.loss_dice: 0.5392, decode.d6.loss_cls: 0.0922, decode.d6.loss_mask: 0.3877, decode.d6.loss_dice: 0.5395, decode.d7.loss_cls: 0.0952, decode.d7.loss_mask: 0.3877, decode.d7.loss_dice: 0.5353, decode.d8.loss_cls: 0.0963, decode.d8.loss_mask: 0.3867, decode.d8.loss_dice: 0.5345, loss: 11.9722 +2022-05-06 08:15:56,320 - mmseg - INFO - Iter [34050/40000] lr: 2.136e-07, eta: 1:23:18, time: 0.685, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0883, decode.loss_mask: 0.3551, decode.loss_dice: 0.5298, decode.d0.loss_cls: 1.4797, decode.d0.loss_mask: 0.3912, decode.d0.loss_dice: 0.6176, decode.d1.loss_cls: 0.2087, decode.d1.loss_mask: 0.3660, decode.d1.loss_dice: 0.5600, decode.d2.loss_cls: 0.1237, decode.d2.loss_mask: 0.3576, decode.d2.loss_dice: 0.5403, decode.d3.loss_cls: 0.1089, decode.d3.loss_mask: 0.3543, decode.d3.loss_dice: 0.5319, decode.d4.loss_cls: 0.1011, decode.d4.loss_mask: 0.3555, decode.d4.loss_dice: 0.5311, decode.d5.loss_cls: 0.0939, decode.d5.loss_mask: 0.3534, decode.d5.loss_dice: 0.5269, decode.d6.loss_cls: 0.0949, decode.d6.loss_mask: 0.3527, decode.d6.loss_dice: 0.5221, decode.d7.loss_cls: 0.0914, decode.d7.loss_mask: 0.3531, decode.d7.loss_dice: 0.5258, decode.d8.loss_cls: 0.0910, decode.d8.loss_mask: 0.3542, decode.d8.loss_dice: 0.5231, loss: 11.4833 +2022-05-06 08:16:30,533 - mmseg - INFO - Iter [34100/40000] lr: 2.118e-07, eta: 1:22:35, time: 0.684, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0880, decode.loss_mask: 0.3665, decode.loss_dice: 0.5120, decode.d0.loss_cls: 1.3943, decode.d0.loss_mask: 0.4079, decode.d0.loss_dice: 0.6055, decode.d1.loss_cls: 0.1957, decode.d1.loss_mask: 0.3787, decode.d1.loss_dice: 0.5431, decode.d2.loss_cls: 0.1244, decode.d2.loss_mask: 0.3727, decode.d2.loss_dice: 0.5256, decode.d3.loss_cls: 0.1074, decode.d3.loss_mask: 0.3712, decode.d3.loss_dice: 0.5180, decode.d4.loss_cls: 0.1043, decode.d4.loss_mask: 0.3692, decode.d4.loss_dice: 0.5172, decode.d5.loss_cls: 0.0985, decode.d5.loss_mask: 0.3677, decode.d5.loss_dice: 0.5134, decode.d6.loss_cls: 0.0933, decode.d6.loss_mask: 0.3686, decode.d6.loss_dice: 0.5143, decode.d7.loss_cls: 0.0977, decode.d7.loss_mask: 0.3663, decode.d7.loss_dice: 0.5081, decode.d8.loss_cls: 0.0972, decode.d8.loss_mask: 0.3669, decode.d8.loss_dice: 0.5084, loss: 11.4019 +2022-05-06 08:17:04,079 - mmseg - INFO - Iter [34150/40000] lr: 2.100e-07, eta: 1:21:51, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0852, decode.loss_mask: 0.3719, decode.loss_dice: 0.5065, decode.d0.loss_cls: 1.4511, decode.d0.loss_mask: 0.4158, decode.d0.loss_dice: 0.5996, decode.d1.loss_cls: 0.1791, decode.d1.loss_mask: 0.3861, decode.d1.loss_dice: 0.5449, decode.d2.loss_cls: 0.1234, decode.d2.loss_mask: 0.3783, decode.d2.loss_dice: 0.5266, decode.d3.loss_cls: 0.0952, decode.d3.loss_mask: 0.3761, decode.d3.loss_dice: 0.5123, decode.d4.loss_cls: 0.0881, decode.d4.loss_mask: 0.3740, decode.d4.loss_dice: 0.5141, decode.d5.loss_cls: 0.0854, decode.d5.loss_mask: 0.3735, decode.d5.loss_dice: 0.5087, decode.d6.loss_cls: 0.0867, decode.d6.loss_mask: 0.3745, decode.d6.loss_dice: 0.5083, decode.d7.loss_cls: 0.0848, decode.d7.loss_mask: 0.3730, decode.d7.loss_dice: 0.5123, decode.d8.loss_cls: 0.0800, decode.d8.loss_mask: 0.3725, decode.d8.loss_dice: 0.5120, loss: 11.4000 +2022-05-06 08:17:37,772 - mmseg - INFO - Iter [34200/40000] lr: 2.082e-07, eta: 1:21:08, time: 0.674, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0807, decode.loss_mask: 0.3733, decode.loss_dice: 0.5206, decode.d0.loss_cls: 1.4250, decode.d0.loss_mask: 0.4118, decode.d0.loss_dice: 0.6016, decode.d1.loss_cls: 0.1829, decode.d1.loss_mask: 0.3870, decode.d1.loss_dice: 0.5539, decode.d2.loss_cls: 0.1185, decode.d2.loss_mask: 0.3811, decode.d2.loss_dice: 0.5373, decode.d3.loss_cls: 0.0980, decode.d3.loss_mask: 0.3799, decode.d3.loss_dice: 0.5309, decode.d4.loss_cls: 0.0963, decode.d4.loss_mask: 0.3762, decode.d4.loss_dice: 0.5227, decode.d5.loss_cls: 0.0913, decode.d5.loss_mask: 0.3750, decode.d5.loss_dice: 0.5251, decode.d6.loss_cls: 0.0830, decode.d6.loss_mask: 0.3738, decode.d6.loss_dice: 0.5225, decode.d7.loss_cls: 0.0878, decode.d7.loss_mask: 0.3744, decode.d7.loss_dice: 0.5217, decode.d8.loss_cls: 0.0858, decode.d8.loss_mask: 0.3730, decode.d8.loss_dice: 0.5210, loss: 11.5120 +2022-05-06 08:18:11,347 - mmseg - INFO - Iter [34250/40000] lr: 2.064e-07, eta: 1:20:24, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0794, decode.loss_mask: 0.3778, decode.loss_dice: 0.5223, decode.d0.loss_cls: 1.5017, decode.d0.loss_mask: 0.4191, decode.d0.loss_dice: 0.6136, decode.d1.loss_cls: 0.1908, decode.d1.loss_mask: 0.3891, decode.d1.loss_dice: 0.5509, decode.d2.loss_cls: 0.1238, decode.d2.loss_mask: 0.3807, decode.d2.loss_dice: 0.5369, decode.d3.loss_cls: 0.0942, decode.d3.loss_mask: 0.3783, decode.d3.loss_dice: 0.5267, decode.d4.loss_cls: 0.0877, decode.d4.loss_mask: 0.3766, decode.d4.loss_dice: 0.5252, decode.d5.loss_cls: 0.0855, decode.d5.loss_mask: 0.3776, decode.d5.loss_dice: 0.5272, decode.d6.loss_cls: 0.0857, decode.d6.loss_mask: 0.3751, decode.d6.loss_dice: 0.5210, decode.d7.loss_cls: 0.0799, decode.d7.loss_mask: 0.3773, decode.d7.loss_dice: 0.5247, decode.d8.loss_cls: 0.0763, decode.d8.loss_mask: 0.3768, decode.d8.loss_dice: 0.5246, loss: 11.6067 +2022-05-06 08:18:47,916 - mmseg - INFO - Iter [34300/40000] lr: 2.046e-07, eta: 1:19:41, time: 0.731, data_time: 0.059, memory: 53770, decode.loss_cls: 0.0858, decode.loss_mask: 0.3767, decode.loss_dice: 0.5172, decode.d0.loss_cls: 1.4667, decode.d0.loss_mask: 0.4211, decode.d0.loss_dice: 0.6050, decode.d1.loss_cls: 0.1901, decode.d1.loss_mask: 0.3908, decode.d1.loss_dice: 0.5488, decode.d2.loss_cls: 0.1199, decode.d2.loss_mask: 0.3833, decode.d2.loss_dice: 0.5307, decode.d3.loss_cls: 0.0940, decode.d3.loss_mask: 0.3804, decode.d3.loss_dice: 0.5237, decode.d4.loss_cls: 0.0897, decode.d4.loss_mask: 0.3797, decode.d4.loss_dice: 0.5251, decode.d5.loss_cls: 0.0880, decode.d5.loss_mask: 0.3791, decode.d5.loss_dice: 0.5238, decode.d6.loss_cls: 0.0857, decode.d6.loss_mask: 0.3763, decode.d6.loss_dice: 0.5188, decode.d7.loss_cls: 0.0885, decode.d7.loss_mask: 0.3755, decode.d7.loss_dice: 0.5145, decode.d8.loss_cls: 0.0842, decode.d8.loss_mask: 0.3759, decode.d8.loss_dice: 0.5188, loss: 11.5580 +2022-05-06 08:19:22,145 - mmseg - INFO - Iter [34350/40000] lr: 2.028e-07, eta: 1:18:58, time: 0.685, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0859, decode.loss_mask: 0.3644, decode.loss_dice: 0.5102, decode.d0.loss_cls: 1.4429, decode.d0.loss_mask: 0.4090, decode.d0.loss_dice: 0.5975, decode.d1.loss_cls: 0.1942, decode.d1.loss_mask: 0.3794, decode.d1.loss_dice: 0.5452, decode.d2.loss_cls: 0.1384, decode.d2.loss_mask: 0.3684, decode.d2.loss_dice: 0.5279, decode.d3.loss_cls: 0.1101, decode.d3.loss_mask: 0.3654, decode.d3.loss_dice: 0.5134, decode.d4.loss_cls: 0.0993, decode.d4.loss_mask: 0.3644, decode.d4.loss_dice: 0.5166, decode.d5.loss_cls: 0.0943, decode.d5.loss_mask: 0.3651, decode.d5.loss_dice: 0.5145, decode.d6.loss_cls: 0.0899, decode.d6.loss_mask: 0.3650, decode.d6.loss_dice: 0.5140, decode.d7.loss_cls: 0.0809, decode.d7.loss_mask: 0.3647, decode.d7.loss_dice: 0.5149, decode.d8.loss_cls: 0.0834, decode.d8.loss_mask: 0.3646, decode.d8.loss_dice: 0.5081, loss: 11.3921 +2022-05-06 08:19:55,550 - mmseg - INFO - Iter [34400/40000] lr: 2.010e-07, eta: 1:18:14, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0967, decode.loss_mask: 0.3568, decode.loss_dice: 0.5331, decode.d0.loss_cls: 1.4831, decode.d0.loss_mask: 0.3997, decode.d0.loss_dice: 0.6257, decode.d1.loss_cls: 0.2130, decode.d1.loss_mask: 0.3715, decode.d1.loss_dice: 0.5690, decode.d2.loss_cls: 0.1424, decode.d2.loss_mask: 0.3649, decode.d2.loss_dice: 0.5509, decode.d3.loss_cls: 0.1174, decode.d3.loss_mask: 0.3599, decode.d3.loss_dice: 0.5402, decode.d4.loss_cls: 0.1077, decode.d4.loss_mask: 0.3589, decode.d4.loss_dice: 0.5378, decode.d5.loss_cls: 0.1090, decode.d5.loss_mask: 0.3593, decode.d5.loss_dice: 0.5415, decode.d6.loss_cls: 0.1017, decode.d6.loss_mask: 0.3572, decode.d6.loss_dice: 0.5359, decode.d7.loss_cls: 0.1000, decode.d7.loss_mask: 0.3575, decode.d7.loss_dice: 0.5324, decode.d8.loss_cls: 0.0958, decode.d8.loss_mask: 0.3570, decode.d8.loss_dice: 0.5357, loss: 11.7118 +2022-05-06 08:20:29,013 - mmseg - INFO - Iter [34450/40000] lr: 1.993e-07, eta: 1:17:31, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0903, decode.loss_mask: 0.3666, decode.loss_dice: 0.5160, decode.d0.loss_cls: 1.4527, decode.d0.loss_mask: 0.4071, decode.d0.loss_dice: 0.6044, decode.d1.loss_cls: 0.2052, decode.d1.loss_mask: 0.3767, decode.d1.loss_dice: 0.5442, decode.d2.loss_cls: 0.1294, decode.d2.loss_mask: 0.3701, decode.d2.loss_dice: 0.5281, decode.d3.loss_cls: 0.1029, decode.d3.loss_mask: 0.3679, decode.d3.loss_dice: 0.5179, decode.d4.loss_cls: 0.0980, decode.d4.loss_mask: 0.3695, decode.d4.loss_dice: 0.5157, decode.d5.loss_cls: 0.0954, decode.d5.loss_mask: 0.3656, decode.d5.loss_dice: 0.5133, decode.d6.loss_cls: 0.0918, decode.d6.loss_mask: 0.3663, decode.d6.loss_dice: 0.5139, decode.d7.loss_cls: 0.0907, decode.d7.loss_mask: 0.3661, decode.d7.loss_dice: 0.5144, decode.d8.loss_cls: 0.0898, decode.d8.loss_mask: 0.3651, decode.d8.loss_dice: 0.5138, loss: 11.4487 +2022-05-06 08:21:02,325 - mmseg - INFO - Iter [34500/40000] lr: 1.975e-07, eta: 1:16:47, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0874, decode.loss_mask: 0.3756, decode.loss_dice: 0.5296, decode.d0.loss_cls: 1.4337, decode.d0.loss_mask: 0.4179, decode.d0.loss_dice: 0.6291, decode.d1.loss_cls: 0.1968, decode.d1.loss_mask: 0.3898, decode.d1.loss_dice: 0.5679, decode.d2.loss_cls: 0.1300, decode.d2.loss_mask: 0.3807, decode.d2.loss_dice: 0.5486, decode.d3.loss_cls: 0.1031, decode.d3.loss_mask: 0.3803, decode.d3.loss_dice: 0.5405, decode.d4.loss_cls: 0.0945, decode.d4.loss_mask: 0.3767, decode.d4.loss_dice: 0.5359, decode.d5.loss_cls: 0.0927, decode.d5.loss_mask: 0.3762, decode.d5.loss_dice: 0.5342, decode.d6.loss_cls: 0.0872, decode.d6.loss_mask: 0.3768, decode.d6.loss_dice: 0.5301, decode.d7.loss_cls: 0.0872, decode.d7.loss_mask: 0.3752, decode.d7.loss_dice: 0.5324, decode.d8.loss_cls: 0.0882, decode.d8.loss_mask: 0.3767, decode.d8.loss_dice: 0.5363, loss: 11.7112 +2022-05-06 08:21:36,151 - mmseg - INFO - Iter [34550/40000] lr: 1.957e-07, eta: 1:16:04, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0820, decode.loss_mask: 0.3651, decode.loss_dice: 0.5323, decode.d0.loss_cls: 1.4244, decode.d0.loss_mask: 0.4016, decode.d0.loss_dice: 0.6200, decode.d1.loss_cls: 0.1735, decode.d1.loss_mask: 0.3752, decode.d1.loss_dice: 0.5708, decode.d2.loss_cls: 0.1177, decode.d2.loss_mask: 0.3689, decode.d2.loss_dice: 0.5448, decode.d3.loss_cls: 0.0997, decode.d3.loss_mask: 0.3665, decode.d3.loss_dice: 0.5330, decode.d4.loss_cls: 0.0908, decode.d4.loss_mask: 0.3648, decode.d4.loss_dice: 0.5339, decode.d5.loss_cls: 0.0853, decode.d5.loss_mask: 0.3669, decode.d5.loss_dice: 0.5328, decode.d6.loss_cls: 0.0841, decode.d6.loss_mask: 0.3661, decode.d6.loss_dice: 0.5287, decode.d7.loss_cls: 0.0864, decode.d7.loss_mask: 0.3648, decode.d7.loss_dice: 0.5322, decode.d8.loss_cls: 0.0821, decode.d8.loss_mask: 0.3650, decode.d8.loss_dice: 0.5313, loss: 11.4911 +2022-05-06 08:22:12,209 - mmseg - INFO - Iter [34600/40000] lr: 1.939e-07, eta: 1:15:21, time: 0.721, data_time: 0.060, memory: 53770, decode.loss_cls: 0.0749, decode.loss_mask: 0.3589, decode.loss_dice: 0.5186, decode.d0.loss_cls: 1.4587, decode.d0.loss_mask: 0.4019, decode.d0.loss_dice: 0.6139, decode.d1.loss_cls: 0.1731, decode.d1.loss_mask: 0.3738, decode.d1.loss_dice: 0.5568, decode.d2.loss_cls: 0.1152, decode.d2.loss_mask: 0.3664, decode.d2.loss_dice: 0.5328, decode.d3.loss_cls: 0.0923, decode.d3.loss_mask: 0.3640, decode.d3.loss_dice: 0.5218, decode.d4.loss_cls: 0.0856, decode.d4.loss_mask: 0.3630, decode.d4.loss_dice: 0.5244, decode.d5.loss_cls: 0.0867, decode.d5.loss_mask: 0.3609, decode.d5.loss_dice: 0.5204, decode.d6.loss_cls: 0.0781, decode.d6.loss_mask: 0.3607, decode.d6.loss_dice: 0.5180, decode.d7.loss_cls: 0.0745, decode.d7.loss_mask: 0.3603, decode.d7.loss_dice: 0.5190, decode.d8.loss_cls: 0.0823, decode.d8.loss_mask: 0.3596, decode.d8.loss_dice: 0.5163, loss: 11.3328 +2022-05-06 08:22:46,002 - mmseg - INFO - Iter [34650/40000] lr: 1.921e-07, eta: 1:14:38, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0825, decode.loss_mask: 0.3638, decode.loss_dice: 0.5083, decode.d0.loss_cls: 1.4149, decode.d0.loss_mask: 0.4071, decode.d0.loss_dice: 0.5927, decode.d1.loss_cls: 0.1863, decode.d1.loss_mask: 0.3769, decode.d1.loss_dice: 0.5385, decode.d2.loss_cls: 0.1139, decode.d2.loss_mask: 0.3714, decode.d2.loss_dice: 0.5231, decode.d3.loss_cls: 0.0882, decode.d3.loss_mask: 0.3693, decode.d3.loss_dice: 0.5142, decode.d4.loss_cls: 0.0913, decode.d4.loss_mask: 0.3677, decode.d4.loss_dice: 0.5112, decode.d5.loss_cls: 0.0873, decode.d5.loss_mask: 0.3666, decode.d5.loss_dice: 0.5130, decode.d6.loss_cls: 0.0849, decode.d6.loss_mask: 0.3656, decode.d6.loss_dice: 0.5089, decode.d7.loss_cls: 0.0775, decode.d7.loss_mask: 0.3653, decode.d7.loss_dice: 0.5118, decode.d8.loss_cls: 0.0840, decode.d8.loss_mask: 0.3635, decode.d8.loss_dice: 0.5084, loss: 11.2580 +2022-05-06 08:23:19,917 - mmseg - INFO - Iter [34700/40000] lr: 1.903e-07, eta: 1:13:55, time: 0.678, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0798, decode.loss_mask: 0.3858, decode.loss_dice: 0.5358, decode.d0.loss_cls: 1.4441, decode.d0.loss_mask: 0.4309, decode.d0.loss_dice: 0.6289, decode.d1.loss_cls: 0.1964, decode.d1.loss_mask: 0.4016, decode.d1.loss_dice: 0.5687, decode.d2.loss_cls: 0.1251, decode.d2.loss_mask: 0.3903, decode.d2.loss_dice: 0.5483, decode.d3.loss_cls: 0.0995, decode.d3.loss_mask: 0.3889, decode.d3.loss_dice: 0.5417, decode.d4.loss_cls: 0.0939, decode.d4.loss_mask: 0.3882, decode.d4.loss_dice: 0.5414, decode.d5.loss_cls: 0.0885, decode.d5.loss_mask: 0.3870, decode.d5.loss_dice: 0.5388, decode.d6.loss_cls: 0.0858, decode.d6.loss_mask: 0.3857, decode.d6.loss_dice: 0.5341, decode.d7.loss_cls: 0.0808, decode.d7.loss_mask: 0.3856, decode.d7.loss_dice: 0.5355, decode.d8.loss_cls: 0.0813, decode.d8.loss_mask: 0.3854, decode.d8.loss_dice: 0.5357, loss: 11.8134 +2022-05-06 08:23:53,372 - mmseg - INFO - Iter [34750/40000] lr: 1.885e-07, eta: 1:13:11, time: 0.670, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0825, decode.loss_mask: 0.3765, decode.loss_dice: 0.5268, decode.d0.loss_cls: 1.4498, decode.d0.loss_mask: 0.4217, decode.d0.loss_dice: 0.6231, decode.d1.loss_cls: 0.2060, decode.d1.loss_mask: 0.3902, decode.d1.loss_dice: 0.5606, decode.d2.loss_cls: 0.1281, decode.d2.loss_mask: 0.3831, decode.d2.loss_dice: 0.5434, decode.d3.loss_cls: 0.1028, decode.d3.loss_mask: 0.3794, decode.d3.loss_dice: 0.5351, decode.d4.loss_cls: 0.0932, decode.d4.loss_mask: 0.3773, decode.d4.loss_dice: 0.5365, decode.d5.loss_cls: 0.0877, decode.d5.loss_mask: 0.3779, decode.d5.loss_dice: 0.5337, decode.d6.loss_cls: 0.0907, decode.d6.loss_mask: 0.3767, decode.d6.loss_dice: 0.5260, decode.d7.loss_cls: 0.0902, decode.d7.loss_mask: 0.3757, decode.d7.loss_dice: 0.5284, decode.d8.loss_cls: 0.0895, decode.d8.loss_mask: 0.3774, decode.d8.loss_dice: 0.5278, loss: 11.6978 +2022-05-06 08:24:26,826 - mmseg - INFO - Iter [34800/40000] lr: 1.867e-07, eta: 1:12:28, time: 0.669, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0779, decode.loss_mask: 0.3738, decode.loss_dice: 0.5135, decode.d0.loss_cls: 1.4467, decode.d0.loss_mask: 0.4153, decode.d0.loss_dice: 0.6176, decode.d1.loss_cls: 0.1846, decode.d1.loss_mask: 0.3875, decode.d1.loss_dice: 0.5495, decode.d2.loss_cls: 0.1213, decode.d2.loss_mask: 0.3795, decode.d2.loss_dice: 0.5314, decode.d3.loss_cls: 0.0980, decode.d3.loss_mask: 0.3753, decode.d3.loss_dice: 0.5231, decode.d4.loss_cls: 0.0895, decode.d4.loss_mask: 0.3752, decode.d4.loss_dice: 0.5197, decode.d5.loss_cls: 0.0840, decode.d5.loss_mask: 0.3746, decode.d5.loss_dice: 0.5156, decode.d6.loss_cls: 0.0847, decode.d6.loss_mask: 0.3743, decode.d6.loss_dice: 0.5143, decode.d7.loss_cls: 0.0796, decode.d7.loss_mask: 0.3727, decode.d7.loss_dice: 0.5142, decode.d8.loss_cls: 0.0831, decode.d8.loss_mask: 0.3725, decode.d8.loss_dice: 0.5136, loss: 11.4623 +2022-05-06 08:25:00,776 - mmseg - INFO - Iter [34850/40000] lr: 1.849e-07, eta: 1:11:45, time: 0.679, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0747, decode.loss_mask: 0.3564, decode.loss_dice: 0.5034, decode.d0.loss_cls: 1.4429, decode.d0.loss_mask: 0.3935, decode.d0.loss_dice: 0.5899, decode.d1.loss_cls: 0.1776, decode.d1.loss_mask: 0.3673, decode.d1.loss_dice: 0.5306, decode.d2.loss_cls: 0.1260, decode.d2.loss_mask: 0.3608, decode.d2.loss_dice: 0.5098, decode.d3.loss_cls: 0.0947, decode.d3.loss_mask: 0.3595, decode.d3.loss_dice: 0.5060, decode.d4.loss_cls: 0.0893, decode.d4.loss_mask: 0.3585, decode.d4.loss_dice: 0.5028, decode.d5.loss_cls: 0.0855, decode.d5.loss_mask: 0.3577, decode.d5.loss_dice: 0.5056, decode.d6.loss_cls: 0.0815, decode.d6.loss_mask: 0.3576, decode.d6.loss_dice: 0.5014, decode.d7.loss_cls: 0.0814, decode.d7.loss_mask: 0.3559, decode.d7.loss_dice: 0.5009, decode.d8.loss_cls: 0.0787, decode.d8.loss_mask: 0.3562, decode.d8.loss_dice: 0.5018, loss: 11.1078 +2022-05-06 08:25:36,946 - mmseg - INFO - Iter [34900/40000] lr: 1.831e-07, eta: 1:11:02, time: 0.723, data_time: 0.055, memory: 53770, decode.loss_cls: 0.0890, decode.loss_mask: 0.3655, decode.loss_dice: 0.5231, decode.d0.loss_cls: 1.5048, decode.d0.loss_mask: 0.4057, decode.d0.loss_dice: 0.6264, decode.d1.loss_cls: 0.1966, decode.d1.loss_mask: 0.3794, decode.d1.loss_dice: 0.5586, decode.d2.loss_cls: 0.1242, decode.d2.loss_mask: 0.3719, decode.d2.loss_dice: 0.5418, decode.d3.loss_cls: 0.1025, decode.d3.loss_mask: 0.3696, decode.d3.loss_dice: 0.5305, decode.d4.loss_cls: 0.1009, decode.d4.loss_mask: 0.3674, decode.d4.loss_dice: 0.5301, decode.d5.loss_cls: 0.0942, decode.d5.loss_mask: 0.3670, decode.d5.loss_dice: 0.5271, decode.d6.loss_cls: 0.0872, decode.d6.loss_mask: 0.3651, decode.d6.loss_dice: 0.5245, decode.d7.loss_cls: 0.0866, decode.d7.loss_mask: 0.3643, decode.d7.loss_dice: 0.5235, decode.d8.loss_cls: 0.0841, decode.d8.loss_mask: 0.3656, decode.d8.loss_dice: 0.5259, loss: 11.6029 +2022-05-06 08:26:10,621 - mmseg - INFO - Iter [34950/40000] lr: 1.813e-07, eta: 1:10:19, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0746, decode.loss_mask: 0.3609, decode.loss_dice: 0.5167, decode.d0.loss_cls: 1.4406, decode.d0.loss_mask: 0.4017, decode.d0.loss_dice: 0.6064, decode.d1.loss_cls: 0.1864, decode.d1.loss_mask: 0.3717, decode.d1.loss_dice: 0.5509, decode.d2.loss_cls: 0.1216, decode.d2.loss_mask: 0.3644, decode.d2.loss_dice: 0.5320, decode.d3.loss_cls: 0.0877, decode.d3.loss_mask: 0.3624, decode.d3.loss_dice: 0.5256, decode.d4.loss_cls: 0.0873, decode.d4.loss_mask: 0.3604, decode.d4.loss_dice: 0.5224, decode.d5.loss_cls: 0.0810, decode.d5.loss_mask: 0.3608, decode.d5.loss_dice: 0.5191, decode.d6.loss_cls: 0.0779, decode.d6.loss_mask: 0.3610, decode.d6.loss_dice: 0.5197, decode.d7.loss_cls: 0.0736, decode.d7.loss_mask: 0.3606, decode.d7.loss_dice: 0.5179, decode.d8.loss_cls: 0.0746, decode.d8.loss_mask: 0.3602, decode.d8.loss_dice: 0.5191, loss: 11.2991 +2022-05-06 08:26:44,609 - mmseg - INFO - Saving checkpoint at 35000 iterations +2022-05-06 08:27:10,006 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 08:27:10,014 - mmseg - INFO - Iter [35000/40000] lr: 1.795e-07, eta: 1:09:40, time: 1.185, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0822, decode.loss_mask: 0.3773, decode.loss_dice: 0.5210, decode.d0.loss_cls: 1.4636, decode.d0.loss_mask: 0.4223, decode.d0.loss_dice: 0.6128, decode.d1.loss_cls: 0.1742, decode.d1.loss_mask: 0.3914, decode.d1.loss_dice: 0.5559, decode.d2.loss_cls: 0.1196, decode.d2.loss_mask: 0.3832, decode.d2.loss_dice: 0.5340, decode.d3.loss_cls: 0.0998, decode.d3.loss_mask: 0.3808, decode.d3.loss_dice: 0.5306, decode.d4.loss_cls: 0.0928, decode.d4.loss_mask: 0.3807, decode.d4.loss_dice: 0.5283, decode.d5.loss_cls: 0.0834, decode.d5.loss_mask: 0.3793, decode.d5.loss_dice: 0.5224, decode.d6.loss_cls: 0.0837, decode.d6.loss_mask: 0.3767, decode.d6.loss_dice: 0.5241, decode.d7.loss_cls: 0.0857, decode.d7.loss_mask: 0.3781, decode.d7.loss_dice: 0.5233, decode.d8.loss_cls: 0.0800, decode.d8.loss_mask: 0.3790, decode.d8.loss_dice: 0.5237, loss: 11.5902 +2022-05-06 08:27:44,014 - mmseg - INFO - Iter [35050/40000] lr: 1.777e-07, eta: 1:08:57, time: 0.682, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0813, decode.loss_mask: 0.3692, decode.loss_dice: 0.5130, decode.d0.loss_cls: 1.4072, decode.d0.loss_mask: 0.4100, decode.d0.loss_dice: 0.6006, decode.d1.loss_cls: 0.1819, decode.d1.loss_mask: 0.3838, decode.d1.loss_dice: 0.5466, decode.d2.loss_cls: 0.1256, decode.d2.loss_mask: 0.3768, decode.d2.loss_dice: 0.5266, decode.d3.loss_cls: 0.1027, decode.d3.loss_mask: 0.3743, decode.d3.loss_dice: 0.5191, decode.d4.loss_cls: 0.0902, decode.d4.loss_mask: 0.3738, decode.d4.loss_dice: 0.5181, decode.d5.loss_cls: 0.0890, decode.d5.loss_mask: 0.3714, decode.d5.loss_dice: 0.5180, decode.d6.loss_cls: 0.0839, decode.d6.loss_mask: 0.3708, decode.d6.loss_dice: 0.5152, decode.d7.loss_cls: 0.0830, decode.d7.loss_mask: 0.3710, decode.d7.loss_dice: 0.5133, decode.d8.loss_cls: 0.0829, decode.d8.loss_mask: 0.3707, decode.d8.loss_dice: 0.5133, loss: 11.3829 +2022-05-06 08:28:17,264 - mmseg - INFO - Iter [35100/40000] lr: 1.759e-07, eta: 1:08:14, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0821, decode.loss_mask: 0.3585, decode.loss_dice: 0.5024, decode.d0.loss_cls: 1.4510, decode.d0.loss_mask: 0.4035, decode.d0.loss_dice: 0.5944, decode.d1.loss_cls: 0.1738, decode.d1.loss_mask: 0.3742, decode.d1.loss_dice: 0.5374, decode.d2.loss_cls: 0.1224, decode.d2.loss_mask: 0.3638, decode.d2.loss_dice: 0.5124, decode.d3.loss_cls: 0.0981, decode.d3.loss_mask: 0.3604, decode.d3.loss_dice: 0.5054, decode.d4.loss_cls: 0.0973, decode.d4.loss_mask: 0.3602, decode.d4.loss_dice: 0.5029, decode.d5.loss_cls: 0.0889, decode.d5.loss_mask: 0.3596, decode.d5.loss_dice: 0.5022, decode.d6.loss_cls: 0.0863, decode.d6.loss_mask: 0.3592, decode.d6.loss_dice: 0.5037, decode.d7.loss_cls: 0.0824, decode.d7.loss_mask: 0.3590, decode.d7.loss_dice: 0.5012, decode.d8.loss_cls: 0.0839, decode.d8.loss_mask: 0.3588, decode.d8.loss_dice: 0.5052, loss: 11.1907 +2022-05-06 08:28:51,132 - mmseg - INFO - Iter [35150/40000] lr: 1.741e-07, eta: 1:07:31, time: 0.677, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0847, decode.loss_mask: 0.3751, decode.loss_dice: 0.5166, decode.d0.loss_cls: 1.4616, decode.d0.loss_mask: 0.4160, decode.d0.loss_dice: 0.5994, decode.d1.loss_cls: 0.1904, decode.d1.loss_mask: 0.3898, decode.d1.loss_dice: 0.5458, decode.d2.loss_cls: 0.1302, decode.d2.loss_mask: 0.3811, decode.d2.loss_dice: 0.5258, decode.d3.loss_cls: 0.1039, decode.d3.loss_mask: 0.3790, decode.d3.loss_dice: 0.5175, decode.d4.loss_cls: 0.0978, decode.d4.loss_mask: 0.3775, decode.d4.loss_dice: 0.5195, decode.d5.loss_cls: 0.0900, decode.d5.loss_mask: 0.3780, decode.d5.loss_dice: 0.5182, decode.d6.loss_cls: 0.0915, decode.d6.loss_mask: 0.3768, decode.d6.loss_dice: 0.5138, decode.d7.loss_cls: 0.0882, decode.d7.loss_mask: 0.3761, decode.d7.loss_dice: 0.5154, decode.d8.loss_cls: 0.0834, decode.d8.loss_mask: 0.3737, decode.d8.loss_dice: 0.5136, loss: 11.5306 +2022-05-06 08:29:27,085 - mmseg - INFO - Iter [35200/40000] lr: 1.723e-07, eta: 1:06:48, time: 0.719, data_time: 0.061, memory: 53770, decode.loss_cls: 0.0964, decode.loss_mask: 0.3559, decode.loss_dice: 0.5213, decode.d0.loss_cls: 1.4555, decode.d0.loss_mask: 0.3966, decode.d0.loss_dice: 0.6089, decode.d1.loss_cls: 0.1917, decode.d1.loss_mask: 0.3684, decode.d1.loss_dice: 0.5528, decode.d2.loss_cls: 0.1240, decode.d2.loss_mask: 0.3615, decode.d2.loss_dice: 0.5320, decode.d3.loss_cls: 0.1053, decode.d3.loss_mask: 0.3591, decode.d3.loss_dice: 0.5262, decode.d4.loss_cls: 0.0975, decode.d4.loss_mask: 0.3589, decode.d4.loss_dice: 0.5241, decode.d5.loss_cls: 0.0960, decode.d5.loss_mask: 0.3567, decode.d5.loss_dice: 0.5224, decode.d6.loss_cls: 0.0964, decode.d6.loss_mask: 0.3574, decode.d6.loss_dice: 0.5186, decode.d7.loss_cls: 0.0919, decode.d7.loss_mask: 0.3569, decode.d7.loss_dice: 0.5212, decode.d8.loss_cls: 0.0928, decode.d8.loss_mask: 0.3557, decode.d8.loss_dice: 0.5190, loss: 11.4211 +2022-05-06 08:30:00,551 - mmseg - INFO - Iter [35250/40000] lr: 1.705e-07, eta: 1:06:05, time: 0.669, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0791, decode.loss_mask: 0.3710, decode.loss_dice: 0.5023, decode.d0.loss_cls: 1.4341, decode.d0.loss_mask: 0.4120, decode.d0.loss_dice: 0.5995, decode.d1.loss_cls: 0.1793, decode.d1.loss_mask: 0.3832, decode.d1.loss_dice: 0.5316, decode.d2.loss_cls: 0.1152, decode.d2.loss_mask: 0.3784, decode.d2.loss_dice: 0.5181, decode.d3.loss_cls: 0.0940, decode.d3.loss_mask: 0.3744, decode.d3.loss_dice: 0.5088, decode.d4.loss_cls: 0.0841, decode.d4.loss_mask: 0.3739, decode.d4.loss_dice: 0.5107, decode.d5.loss_cls: 0.0819, decode.d5.loss_mask: 0.3727, decode.d5.loss_dice: 0.5088, decode.d6.loss_cls: 0.0806, decode.d6.loss_mask: 0.3711, decode.d6.loss_dice: 0.5058, decode.d7.loss_cls: 0.0773, decode.d7.loss_mask: 0.3725, decode.d7.loss_dice: 0.5077, decode.d8.loss_cls: 0.0824, decode.d8.loss_mask: 0.3718, decode.d8.loss_dice: 0.5048, loss: 11.2867 +2022-05-06 08:30:33,724 - mmseg - INFO - Iter [35300/40000] lr: 1.687e-07, eta: 1:05:22, time: 0.663, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0798, decode.loss_mask: 0.3670, decode.loss_dice: 0.5209, decode.d0.loss_cls: 1.4568, decode.d0.loss_mask: 0.4102, decode.d0.loss_dice: 0.6161, decode.d1.loss_cls: 0.1938, decode.d1.loss_mask: 0.3806, decode.d1.loss_dice: 0.5532, decode.d2.loss_cls: 0.1183, decode.d2.loss_mask: 0.3741, decode.d2.loss_dice: 0.5421, decode.d3.loss_cls: 0.1031, decode.d3.loss_mask: 0.3704, decode.d3.loss_dice: 0.5280, decode.d4.loss_cls: 0.0888, decode.d4.loss_mask: 0.3696, decode.d4.loss_dice: 0.5297, decode.d5.loss_cls: 0.0875, decode.d5.loss_mask: 0.3673, decode.d5.loss_dice: 0.5272, decode.d6.loss_cls: 0.0846, decode.d6.loss_mask: 0.3672, decode.d6.loss_dice: 0.5213, decode.d7.loss_cls: 0.0804, decode.d7.loss_mask: 0.3662, decode.d7.loss_dice: 0.5223, decode.d8.loss_cls: 0.0813, decode.d8.loss_mask: 0.3667, decode.d8.loss_dice: 0.5271, loss: 11.5016 +2022-05-06 08:31:06,919 - mmseg - INFO - Iter [35350/40000] lr: 1.669e-07, eta: 1:04:39, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0883, decode.loss_mask: 0.3610, decode.loss_dice: 0.5237, decode.d0.loss_cls: 1.4651, decode.d0.loss_mask: 0.4046, decode.d0.loss_dice: 0.6273, decode.d1.loss_cls: 0.2018, decode.d1.loss_mask: 0.3750, decode.d1.loss_dice: 0.5601, decode.d2.loss_cls: 0.1316, decode.d2.loss_mask: 0.3678, decode.d2.loss_dice: 0.5445, decode.d3.loss_cls: 0.1089, decode.d3.loss_mask: 0.3644, decode.d3.loss_dice: 0.5325, decode.d4.loss_cls: 0.0986, decode.d4.loss_mask: 0.3652, decode.d4.loss_dice: 0.5345, decode.d5.loss_cls: 0.0957, decode.d5.loss_mask: 0.3632, decode.d5.loss_dice: 0.5322, decode.d6.loss_cls: 0.0903, decode.d6.loss_mask: 0.3623, decode.d6.loss_dice: 0.5254, decode.d7.loss_cls: 0.0865, decode.d7.loss_mask: 0.3623, decode.d7.loss_dice: 0.5271, decode.d8.loss_cls: 0.0883, decode.d8.loss_mask: 0.3620, decode.d8.loss_dice: 0.5226, loss: 11.5729 +2022-05-06 08:31:40,868 - mmseg - INFO - Iter [35400/40000] lr: 1.652e-07, eta: 1:03:56, time: 0.678, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0891, decode.loss_mask: 0.3672, decode.loss_dice: 0.5192, decode.d0.loss_cls: 1.4618, decode.d0.loss_mask: 0.4087, decode.d0.loss_dice: 0.6204, decode.d1.loss_cls: 0.2057, decode.d1.loss_mask: 0.3816, decode.d1.loss_dice: 0.5553, decode.d2.loss_cls: 0.1321, decode.d2.loss_mask: 0.3723, decode.d2.loss_dice: 0.5389, decode.d3.loss_cls: 0.1048, decode.d3.loss_mask: 0.3700, decode.d3.loss_dice: 0.5256, decode.d4.loss_cls: 0.1038, decode.d4.loss_mask: 0.3686, decode.d4.loss_dice: 0.5281, decode.d5.loss_cls: 0.1011, decode.d5.loss_mask: 0.3656, decode.d5.loss_dice: 0.5221, decode.d6.loss_cls: 0.0930, decode.d6.loss_mask: 0.3673, decode.d6.loss_dice: 0.5211, decode.d7.loss_cls: 0.0892, decode.d7.loss_mask: 0.3662, decode.d7.loss_dice: 0.5172, decode.d8.loss_cls: 0.0890, decode.d8.loss_mask: 0.3669, decode.d8.loss_dice: 0.5179, loss: 11.5698 +2022-05-06 08:32:14,625 - mmseg - INFO - Iter [35450/40000] lr: 1.634e-07, eta: 1:03:14, time: 0.676, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0830, decode.loss_mask: 0.3694, decode.loss_dice: 0.5212, decode.d0.loss_cls: 1.4516, decode.d0.loss_mask: 0.4111, decode.d0.loss_dice: 0.6076, decode.d1.loss_cls: 0.1789, decode.d1.loss_mask: 0.3826, decode.d1.loss_dice: 0.5547, decode.d2.loss_cls: 0.1286, decode.d2.loss_mask: 0.3740, decode.d2.loss_dice: 0.5345, decode.d3.loss_cls: 0.1008, decode.d3.loss_mask: 0.3714, decode.d3.loss_dice: 0.5304, decode.d4.loss_cls: 0.0959, decode.d4.loss_mask: 0.3715, decode.d4.loss_dice: 0.5251, decode.d5.loss_cls: 0.0881, decode.d5.loss_mask: 0.3695, decode.d5.loss_dice: 0.5265, decode.d6.loss_cls: 0.0849, decode.d6.loss_mask: 0.3690, decode.d6.loss_dice: 0.5240, decode.d7.loss_cls: 0.0866, decode.d7.loss_mask: 0.3691, decode.d7.loss_dice: 0.5208, decode.d8.loss_cls: 0.0879, decode.d8.loss_mask: 0.3690, decode.d8.loss_dice: 0.5200, loss: 11.5075 +2022-05-06 08:32:47,802 - mmseg - INFO - Iter [35500/40000] lr: 1.616e-07, eta: 1:02:31, time: 0.664, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0880, decode.loss_mask: 0.3582, decode.loss_dice: 0.5247, decode.d0.loss_cls: 1.4438, decode.d0.loss_mask: 0.4013, decode.d0.loss_dice: 0.6207, decode.d1.loss_cls: 0.2002, decode.d1.loss_mask: 0.3698, decode.d1.loss_dice: 0.5567, decode.d2.loss_cls: 0.1241, decode.d2.loss_mask: 0.3631, decode.d2.loss_dice: 0.5448, decode.d3.loss_cls: 0.1075, decode.d3.loss_mask: 0.3614, decode.d3.loss_dice: 0.5305, decode.d4.loss_cls: 0.0960, decode.d4.loss_mask: 0.3597, decode.d4.loss_dice: 0.5321, decode.d5.loss_cls: 0.0938, decode.d5.loss_mask: 0.3603, decode.d5.loss_dice: 0.5293, decode.d6.loss_cls: 0.0902, decode.d6.loss_mask: 0.3593, decode.d6.loss_dice: 0.5330, decode.d7.loss_cls: 0.0895, decode.d7.loss_mask: 0.3586, decode.d7.loss_dice: 0.5279, decode.d8.loss_cls: 0.0901, decode.d8.loss_mask: 0.3571, decode.d8.loss_dice: 0.5296, loss: 11.5013 +2022-05-06 08:33:23,884 - mmseg - INFO - Iter [35550/40000] lr: 1.598e-07, eta: 1:01:48, time: 0.722, data_time: 0.055, memory: 53770, decode.loss_cls: 0.0837, decode.loss_mask: 0.3612, decode.loss_dice: 0.5199, decode.d0.loss_cls: 1.4499, decode.d0.loss_mask: 0.4024, decode.d0.loss_dice: 0.6137, decode.d1.loss_cls: 0.1855, decode.d1.loss_mask: 0.3735, decode.d1.loss_dice: 0.5568, decode.d2.loss_cls: 0.1286, decode.d2.loss_mask: 0.3665, decode.d2.loss_dice: 0.5356, decode.d3.loss_cls: 0.1023, decode.d3.loss_mask: 0.3659, decode.d3.loss_dice: 0.5273, decode.d4.loss_cls: 0.0943, decode.d4.loss_mask: 0.3640, decode.d4.loss_dice: 0.5300, decode.d5.loss_cls: 0.0885, decode.d5.loss_mask: 0.3630, decode.d5.loss_dice: 0.5250, decode.d6.loss_cls: 0.0847, decode.d6.loss_mask: 0.3609, decode.d6.loss_dice: 0.5187, decode.d7.loss_cls: 0.0851, decode.d7.loss_mask: 0.3631, decode.d7.loss_dice: 0.5192, decode.d8.loss_cls: 0.0855, decode.d8.loss_mask: 0.3620, decode.d8.loss_dice: 0.5169, loss: 11.4336 +2022-05-06 08:33:58,500 - mmseg - INFO - Iter [35600/40000] lr: 1.580e-07, eta: 1:01:06, time: 0.692, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0851, decode.loss_mask: 0.3586, decode.loss_dice: 0.5210, decode.d0.loss_cls: 1.4494, decode.d0.loss_mask: 0.3990, decode.d0.loss_dice: 0.6215, decode.d1.loss_cls: 0.1883, decode.d1.loss_mask: 0.3740, decode.d1.loss_dice: 0.5559, decode.d2.loss_cls: 0.1301, decode.d2.loss_mask: 0.3667, decode.d2.loss_dice: 0.5369, decode.d3.loss_cls: 0.1038, decode.d3.loss_mask: 0.3630, decode.d3.loss_dice: 0.5254, decode.d4.loss_cls: 0.0987, decode.d4.loss_mask: 0.3623, decode.d4.loss_dice: 0.5241, decode.d5.loss_cls: 0.0945, decode.d5.loss_mask: 0.3615, decode.d5.loss_dice: 0.5237, decode.d6.loss_cls: 0.0897, decode.d6.loss_mask: 0.3605, decode.d6.loss_dice: 0.5183, decode.d7.loss_cls: 0.0855, decode.d7.loss_mask: 0.3604, decode.d7.loss_dice: 0.5235, decode.d8.loss_cls: 0.0839, decode.d8.loss_mask: 0.3598, decode.d8.loss_dice: 0.5194, loss: 11.4445 +2022-05-06 08:34:31,596 - mmseg - INFO - Iter [35650/40000] lr: 1.562e-07, eta: 1:00:23, time: 0.661, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0996, decode.loss_mask: 0.3670, decode.loss_dice: 0.5218, decode.d0.loss_cls: 1.4096, decode.d0.loss_mask: 0.4065, decode.d0.loss_dice: 0.6095, decode.d1.loss_cls: 0.1905, decode.d1.loss_mask: 0.3796, decode.d1.loss_dice: 0.5523, decode.d2.loss_cls: 0.1389, decode.d2.loss_mask: 0.3718, decode.d2.loss_dice: 0.5369, decode.d3.loss_cls: 0.1112, decode.d3.loss_mask: 0.3701, decode.d3.loss_dice: 0.5248, decode.d4.loss_cls: 0.1060, decode.d4.loss_mask: 0.3707, decode.d4.loss_dice: 0.5245, decode.d5.loss_cls: 0.1024, decode.d5.loss_mask: 0.3693, decode.d5.loss_dice: 0.5227, decode.d6.loss_cls: 0.1003, decode.d6.loss_mask: 0.3681, decode.d6.loss_dice: 0.5238, decode.d7.loss_cls: 0.0936, decode.d7.loss_mask: 0.3675, decode.d7.loss_dice: 0.5230, decode.d8.loss_cls: 0.0983, decode.d8.loss_mask: 0.3674, decode.d8.loss_dice: 0.5211, loss: 11.5488 +2022-05-06 08:35:05,063 - mmseg - INFO - Iter [35700/40000] lr: 1.544e-07, eta: 0:59:40, time: 0.670, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0812, decode.loss_mask: 0.3669, decode.loss_dice: 0.5221, decode.d0.loss_cls: 1.4459, decode.d0.loss_mask: 0.4100, decode.d0.loss_dice: 0.6090, decode.d1.loss_cls: 0.1940, decode.d1.loss_mask: 0.3803, decode.d1.loss_dice: 0.5488, decode.d2.loss_cls: 0.1308, decode.d2.loss_mask: 0.3727, decode.d2.loss_dice: 0.5350, decode.d3.loss_cls: 0.1005, decode.d3.loss_mask: 0.3699, decode.d3.loss_dice: 0.5261, decode.d4.loss_cls: 0.0927, decode.d4.loss_mask: 0.3690, decode.d4.loss_dice: 0.5274, decode.d5.loss_cls: 0.0845, decode.d5.loss_mask: 0.3673, decode.d5.loss_dice: 0.5275, decode.d6.loss_cls: 0.0805, decode.d6.loss_mask: 0.3679, decode.d6.loss_dice: 0.5231, decode.d7.loss_cls: 0.0764, decode.d7.loss_mask: 0.3675, decode.d7.loss_dice: 0.5237, decode.d8.loss_cls: 0.0815, decode.d8.loss_mask: 0.3681, decode.d8.loss_dice: 0.5212, loss: 11.4714 +2022-05-06 08:35:38,452 - mmseg - INFO - Iter [35750/40000] lr: 1.526e-07, eta: 0:58:57, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0742, decode.loss_mask: 0.3774, decode.loss_dice: 0.5029, decode.d0.loss_cls: 1.4211, decode.d0.loss_mask: 0.4185, decode.d0.loss_dice: 0.5913, decode.d1.loss_cls: 0.1737, decode.d1.loss_mask: 0.3890, decode.d1.loss_dice: 0.5362, decode.d2.loss_cls: 0.1105, decode.d2.loss_mask: 0.3835, decode.d2.loss_dice: 0.5185, decode.d3.loss_cls: 0.0924, decode.d3.loss_mask: 0.3816, decode.d3.loss_dice: 0.5110, decode.d4.loss_cls: 0.0885, decode.d4.loss_mask: 0.3793, decode.d4.loss_dice: 0.5079, decode.d5.loss_cls: 0.0843, decode.d5.loss_mask: 0.3783, decode.d5.loss_dice: 0.5081, decode.d6.loss_cls: 0.0797, decode.d6.loss_mask: 0.3772, decode.d6.loss_dice: 0.5041, decode.d7.loss_cls: 0.0789, decode.d7.loss_mask: 0.3776, decode.d7.loss_dice: 0.5025, decode.d8.loss_cls: 0.0741, decode.d8.loss_mask: 0.3774, decode.d8.loss_dice: 0.5020, loss: 11.3018 +2022-05-06 08:36:11,821 - mmseg - INFO - Iter [35800/40000] lr: 1.508e-07, eta: 0:58:14, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0842, decode.loss_mask: 0.3551, decode.loss_dice: 0.4979, decode.d0.loss_cls: 1.4615, decode.d0.loss_mask: 0.3959, decode.d0.loss_dice: 0.5871, decode.d1.loss_cls: 0.1910, decode.d1.loss_mask: 0.3693, decode.d1.loss_dice: 0.5328, decode.d2.loss_cls: 0.1234, decode.d2.loss_mask: 0.3604, decode.d2.loss_dice: 0.5114, decode.d3.loss_cls: 0.0992, decode.d3.loss_mask: 0.3589, decode.d3.loss_dice: 0.5058, decode.d4.loss_cls: 0.0976, decode.d4.loss_mask: 0.3582, decode.d4.loss_dice: 0.5034, decode.d5.loss_cls: 0.0905, decode.d5.loss_mask: 0.3569, decode.d5.loss_dice: 0.5034, decode.d6.loss_cls: 0.0886, decode.d6.loss_mask: 0.3554, decode.d6.loss_dice: 0.4988, decode.d7.loss_cls: 0.0845, decode.d7.loss_mask: 0.3557, decode.d7.loss_dice: 0.4992, decode.d8.loss_cls: 0.0879, decode.d8.loss_mask: 0.3544, decode.d8.loss_dice: 0.4988, loss: 11.1672 +2022-05-06 08:36:48,049 - mmseg - INFO - Iter [35850/40000] lr: 1.490e-07, eta: 0:57:32, time: 0.724, data_time: 0.056, memory: 53770, decode.loss_cls: 0.0729, decode.loss_mask: 0.3627, decode.loss_dice: 0.5007, decode.d0.loss_cls: 1.4303, decode.d0.loss_mask: 0.4022, decode.d0.loss_dice: 0.5921, decode.d1.loss_cls: 0.1825, decode.d1.loss_mask: 0.3753, decode.d1.loss_dice: 0.5256, decode.d2.loss_cls: 0.1134, decode.d2.loss_mask: 0.3669, decode.d2.loss_dice: 0.5138, decode.d3.loss_cls: 0.0883, decode.d3.loss_mask: 0.3631, decode.d3.loss_dice: 0.5028, decode.d4.loss_cls: 0.0782, decode.d4.loss_mask: 0.3641, decode.d4.loss_dice: 0.5059, decode.d5.loss_cls: 0.0787, decode.d5.loss_mask: 0.3631, decode.d5.loss_dice: 0.5048, decode.d6.loss_cls: 0.0705, decode.d6.loss_mask: 0.3630, decode.d6.loss_dice: 0.5020, decode.d7.loss_cls: 0.0765, decode.d7.loss_mask: 0.3625, decode.d7.loss_dice: 0.4980, decode.d8.loss_cls: 0.0739, decode.d8.loss_mask: 0.3620, decode.d8.loss_dice: 0.5018, loss: 11.0976 +2022-05-06 08:37:21,282 - mmseg - INFO - Iter [35900/40000] lr: 1.472e-07, eta: 0:56:50, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0765, decode.loss_mask: 0.3710, decode.loss_dice: 0.5016, decode.d0.loss_cls: 1.4664, decode.d0.loss_mask: 0.4147, decode.d0.loss_dice: 0.5928, decode.d1.loss_cls: 0.1802, decode.d1.loss_mask: 0.3853, decode.d1.loss_dice: 0.5374, decode.d2.loss_cls: 0.1209, decode.d2.loss_mask: 0.3783, decode.d2.loss_dice: 0.5150, decode.d3.loss_cls: 0.0983, decode.d3.loss_mask: 0.3760, decode.d3.loss_dice: 0.5114, decode.d4.loss_cls: 0.0890, decode.d4.loss_mask: 0.3741, decode.d4.loss_dice: 0.5109, decode.d5.loss_cls: 0.0814, decode.d5.loss_mask: 0.3732, decode.d5.loss_dice: 0.5110, decode.d6.loss_cls: 0.0782, decode.d6.loss_mask: 0.3725, decode.d6.loss_dice: 0.5024, decode.d7.loss_cls: 0.0788, decode.d7.loss_mask: 0.3723, decode.d7.loss_dice: 0.5032, decode.d8.loss_cls: 0.0720, decode.d8.loss_mask: 0.3723, decode.d8.loss_dice: 0.5040, loss: 11.3208 +2022-05-06 08:37:54,795 - mmseg - INFO - Iter [35950/40000] lr: 1.454e-07, eta: 0:56:07, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0826, decode.loss_mask: 0.3553, decode.loss_dice: 0.5200, decode.d0.loss_cls: 1.4726, decode.d0.loss_mask: 0.3961, decode.d0.loss_dice: 0.6168, decode.d1.loss_cls: 0.1806, decode.d1.loss_mask: 0.3700, decode.d1.loss_dice: 0.5530, decode.d2.loss_cls: 0.1249, decode.d2.loss_mask: 0.3616, decode.d2.loss_dice: 0.5375, decode.d3.loss_cls: 0.1069, decode.d3.loss_mask: 0.3589, decode.d3.loss_dice: 0.5230, decode.d4.loss_cls: 0.0943, decode.d4.loss_mask: 0.3576, decode.d4.loss_dice: 0.5284, decode.d5.loss_cls: 0.0900, decode.d5.loss_mask: 0.3558, decode.d5.loss_dice: 0.5232, decode.d6.loss_cls: 0.0868, decode.d6.loss_mask: 0.3561, decode.d6.loss_dice: 0.5184, decode.d7.loss_cls: 0.0858, decode.d7.loss_mask: 0.3567, decode.d7.loss_dice: 0.5220, decode.d8.loss_cls: 0.0831, decode.d8.loss_mask: 0.3560, decode.d8.loss_dice: 0.5179, loss: 11.3919 +2022-05-06 08:38:28,730 - mmseg - INFO - Saving checkpoint at 36000 iterations +2022-05-06 08:38:56,077 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 08:38:56,079 - mmseg - INFO - Iter [36000/40000] lr: 1.436e-07, eta: 0:55:28, time: 1.224, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0869, decode.loss_mask: 0.3744, decode.loss_dice: 0.5126, decode.d0.loss_cls: 1.4137, decode.d0.loss_mask: 0.4162, decode.d0.loss_dice: 0.6088, decode.d1.loss_cls: 0.1829, decode.d1.loss_mask: 0.3865, decode.d1.loss_dice: 0.5431, decode.d2.loss_cls: 0.1238, decode.d2.loss_mask: 0.3781, decode.d2.loss_dice: 0.5284, decode.d3.loss_cls: 0.1027, decode.d3.loss_mask: 0.3756, decode.d3.loss_dice: 0.5199, decode.d4.loss_cls: 0.0919, decode.d4.loss_mask: 0.3747, decode.d4.loss_dice: 0.5188, decode.d5.loss_cls: 0.0908, decode.d5.loss_mask: 0.3745, decode.d5.loss_dice: 0.5152, decode.d6.loss_cls: 0.0840, decode.d6.loss_mask: 0.3758, decode.d6.loss_dice: 0.5148, decode.d7.loss_cls: 0.0846, decode.d7.loss_mask: 0.3753, decode.d7.loss_dice: 0.5177, decode.d8.loss_cls: 0.0842, decode.d8.loss_mask: 0.3739, decode.d8.loss_dice: 0.5154, loss: 11.4452 +2022-05-06 08:43:15,865 - mmseg - INFO - per class results: +2022-05-06 08:43:15,871 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.5 | 95.79 | +| bag | 51.26 | 69.15 | +| bed | 36.14 | 43.95 | +| bedclothes | 44.81 | 69.97 | +| bench | 33.0 | 42.78 | +| bicycle | 85.64 | 92.8 | +| bird | 95.47 | 97.66 | +| boat | 87.27 | 93.1 | +| book | 57.52 | 69.6 | +| bottle | 89.35 | 95.11 | +| building | 67.17 | 79.93 | +| bus | 94.97 | 97.22 | +| cabinet | 52.91 | 69.56 | +| car | 93.48 | 97.07 | +| cat | 94.6 | 98.06 | +| ceiling | 61.24 | 78.5 | +| chair | 65.67 | 83.88 | +| cloth | 29.0 | 39.79 | +| computer | 59.56 | 74.6 | +| cow | 96.08 | 97.69 | +| cup | 50.27 | 66.93 | +| curtain | 62.92 | 80.47 | +| dog | 92.87 | 97.91 | +| door | 39.4 | 63.22 | +| fence | 47.58 | 64.31 | +| floor | 75.2 | 86.36 | +| flower | 40.98 | 52.59 | +| food | 49.15 | 63.95 | +| grass | 83.09 | 92.44 | +| ground | 58.21 | 73.29 | +| horse | 95.26 | 97.77 | +| keyboard | 90.53 | 96.14 | +| light | 62.37 | 78.49 | +| motorbike | 92.13 | 96.9 | +| mountain | 56.02 | 74.59 | +| mouse | 89.08 | 92.3 | +| person | 91.31 | 96.38 | +| plate | 30.54 | 40.1 | +| platform | 52.8 | 67.24 | +| pottedplant | 82.51 | 91.06 | +| road | 53.26 | 67.56 | +| rock | 54.32 | 64.48 | +| sheep | 95.51 | 97.98 | +| shelves | 41.05 | 55.19 | +| sidewalk | 32.57 | 52.5 | +| sign | 55.5 | 66.86 | +| sky | 95.05 | 97.18 | +| snow | 79.58 | 91.88 | +| sofa | 59.84 | 68.83 | +| table | 72.81 | 84.03 | +| track | 73.55 | 83.63 | +| train | 93.03 | 97.06 | +| tree | 81.97 | 90.42 | +| truck | 52.22 | 63.07 | +| tvmonitor | 90.94 | 94.24 | +| wall | 72.62 | 83.71 | +| water | 93.1 | 96.37 | +| window | 45.69 | 59.23 | +| wood | 25.66 | 36.39 | ++-------------+-------+-------+ +2022-05-06 08:43:15,871 - mmseg - INFO - Summary: +2022-05-06 08:43:15,871 - mmseg - INFO - ++------+-------+-------+ +| aAcc | mIoU | mAcc | ++------+-------+-------+ +| 86.6 | 67.76 | 78.12 | ++------+-------+-------+ +2022-05-06 08:43:15,874 - mmseg - INFO - The previous best checkpoint /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/best_mIoU_iter_28000.pth was removed +2022-05-06 08:43:42,943 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_36000.pth. +2022-05-06 08:43:42,953 - mmseg - INFO - Best mIoU is 0.6776 at 36000 iter. +2022-05-06 08:43:42,978 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 08:43:42,979 - mmseg - INFO - Iter(val) [638] aAcc: 0.8660, mIoU: 0.6776, mAcc: 0.7812, IoU.aeroplane: 0.9250, IoU.bag: 0.5126, IoU.bed: 0.3614, IoU.bedclothes: 0.4481, IoU.bench: 0.3300, IoU.bicycle: 0.8564, IoU.bird: 0.9547, IoU.boat: 0.8727, IoU.book: 0.5752, IoU.bottle: 0.8935, IoU.building: 0.6717, IoU.bus: 0.9497, IoU.cabinet: 0.5291, IoU.car: 0.9348, IoU.cat: 0.9460, IoU.ceiling: 0.6124, IoU.chair: 0.6567, IoU.cloth: 0.2900, IoU.computer: 0.5956, IoU.cow: 0.9608, IoU.cup: 0.5027, IoU.curtain: 0.6292, IoU.dog: 0.9287, IoU.door: 0.3940, IoU.fence: 0.4758, IoU.floor: 0.7520, IoU.flower: 0.4098, IoU.food: 0.4915, IoU.grass: 0.8309, IoU.ground: 0.5821, IoU.horse: 0.9526, IoU.keyboard: 0.9053, IoU.light: 0.6237, IoU.motorbike: 0.9213, IoU.mountain: 0.5602, IoU.mouse: 0.8908, IoU.person: 0.9131, IoU.plate: 0.3054, IoU.platform: 0.5280, IoU.pottedplant: 0.8251, IoU.road: 0.5326, IoU.rock: 0.5432, IoU.sheep: 0.9551, IoU.shelves: 0.4105, IoU.sidewalk: 0.3257, IoU.sign: 0.5550, IoU.sky: 0.9505, IoU.snow: 0.7958, IoU.sofa: 0.5984, IoU.table: 0.7281, IoU.track: 0.7355, IoU.train: 0.9303, IoU.tree: 0.8197, IoU.truck: 0.5222, IoU.tvmonitor: 0.9094, IoU.wall: 0.7262, IoU.water: 0.9310, IoU.window: 0.4569, IoU.wood: 0.2566, Acc.aeroplane: 0.9579, Acc.bag: 0.6915, Acc.bed: 0.4395, Acc.bedclothes: 0.6997, Acc.bench: 0.4278, Acc.bicycle: 0.9280, Acc.bird: 0.9766, Acc.boat: 0.9310, Acc.book: 0.6960, Acc.bottle: 0.9511, Acc.building: 0.7993, Acc.bus: 0.9722, Acc.cabinet: 0.6956, Acc.car: 0.9707, Acc.cat: 0.9806, Acc.ceiling: 0.7850, Acc.chair: 0.8388, Acc.cloth: 0.3979, Acc.computer: 0.7460, Acc.cow: 0.9769, Acc.cup: 0.6693, Acc.curtain: 0.8047, Acc.dog: 0.9791, Acc.door: 0.6322, Acc.fence: 0.6431, Acc.floor: 0.8636, Acc.flower: 0.5259, Acc.food: 0.6395, Acc.grass: 0.9244, Acc.ground: 0.7329, Acc.horse: 0.9777, Acc.keyboard: 0.9614, Acc.light: 0.7849, Acc.motorbike: 0.9690, Acc.mountain: 0.7459, Acc.mouse: 0.9230, Acc.person: 0.9638, Acc.plate: 0.4010, Acc.platform: 0.6724, Acc.pottedplant: 0.9106, Acc.road: 0.6756, Acc.rock: 0.6448, Acc.sheep: 0.9798, Acc.shelves: 0.5519, Acc.sidewalk: 0.5250, Acc.sign: 0.6686, Acc.sky: 0.9718, Acc.snow: 0.9188, Acc.sofa: 0.6883, Acc.table: 0.8403, Acc.track: 0.8363, Acc.train: 0.9706, Acc.tree: 0.9042, Acc.truck: 0.6307, Acc.tvmonitor: 0.9424, Acc.wall: 0.8371, Acc.water: 0.9637, Acc.window: 0.5923, Acc.wood: 0.3639 +2022-05-06 08:44:17,189 - mmseg - INFO - Iter [36050/40000] lr: 1.418e-07, eta: 0:55:21, time: 6.424, data_time: 5.749, memory: 53770, decode.loss_cls: 0.0905, decode.loss_mask: 0.3555, decode.loss_dice: 0.5073, decode.d0.loss_cls: 1.4059, decode.d0.loss_mask: 0.3987, decode.d0.loss_dice: 0.5916, decode.d1.loss_cls: 0.1983, decode.d1.loss_mask: 0.3688, decode.d1.loss_dice: 0.5341, decode.d2.loss_cls: 0.1310, decode.d2.loss_mask: 0.3609, decode.d2.loss_dice: 0.5174, decode.d3.loss_cls: 0.1071, decode.d3.loss_mask: 0.3590, decode.d3.loss_dice: 0.5125, decode.d4.loss_cls: 0.0930, decode.d4.loss_mask: 0.3604, decode.d4.loss_dice: 0.5146, decode.d5.loss_cls: 0.0953, decode.d5.loss_mask: 0.3564, decode.d5.loss_dice: 0.5060, decode.d6.loss_cls: 0.0878, decode.d6.loss_mask: 0.3577, decode.d6.loss_dice: 0.5110, decode.d7.loss_cls: 0.0893, decode.d7.loss_mask: 0.3574, decode.d7.loss_dice: 0.5067, decode.d8.loss_cls: 0.0886, decode.d8.loss_mask: 0.3560, decode.d8.loss_dice: 0.5076, loss: 11.2263 +2022-05-06 08:44:50,875 - mmseg - INFO - Iter [36100/40000] lr: 1.400e-07, eta: 0:54:38, time: 0.674, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0966, decode.loss_mask: 0.3817, decode.loss_dice: 0.5325, decode.d0.loss_cls: 1.4450, decode.d0.loss_mask: 0.4159, decode.d0.loss_dice: 0.6277, decode.d1.loss_cls: 0.1862, decode.d1.loss_mask: 0.3897, decode.d1.loss_dice: 0.5676, decode.d2.loss_cls: 0.1342, decode.d2.loss_mask: 0.3848, decode.d2.loss_dice: 0.5511, decode.d3.loss_cls: 0.1017, decode.d3.loss_mask: 0.3821, decode.d3.loss_dice: 0.5419, decode.d4.loss_cls: 0.1013, decode.d4.loss_mask: 0.3797, decode.d4.loss_dice: 0.5387, decode.d5.loss_cls: 0.1004, decode.d5.loss_mask: 0.3818, decode.d5.loss_dice: 0.5381, decode.d6.loss_cls: 0.0996, decode.d6.loss_mask: 0.3826, decode.d6.loss_dice: 0.5350, decode.d7.loss_cls: 0.0970, decode.d7.loss_mask: 0.3801, decode.d7.loss_dice: 0.5303, decode.d8.loss_cls: 0.0970, decode.d8.loss_mask: 0.3813, decode.d8.loss_dice: 0.5349, loss: 11.8166 +2022-05-06 08:45:26,565 - mmseg - INFO - Iter [36150/40000] lr: 1.382e-07, eta: 0:53:55, time: 0.714, data_time: 0.058, memory: 53770, decode.loss_cls: 0.0730, decode.loss_mask: 0.3751, decode.loss_dice: 0.5204, decode.d0.loss_cls: 1.4300, decode.d0.loss_mask: 0.4142, decode.d0.loss_dice: 0.6109, decode.d1.loss_cls: 0.1875, decode.d1.loss_mask: 0.3899, decode.d1.loss_dice: 0.5578, decode.d2.loss_cls: 0.1172, decode.d2.loss_mask: 0.3826, decode.d2.loss_dice: 0.5364, decode.d3.loss_cls: 0.0901, decode.d3.loss_mask: 0.3799, decode.d3.loss_dice: 0.5252, decode.d4.loss_cls: 0.0812, decode.d4.loss_mask: 0.3782, decode.d4.loss_dice: 0.5239, decode.d5.loss_cls: 0.0802, decode.d5.loss_mask: 0.3771, decode.d5.loss_dice: 0.5222, decode.d6.loss_cls: 0.0727, decode.d6.loss_mask: 0.3760, decode.d6.loss_dice: 0.5216, decode.d7.loss_cls: 0.0734, decode.d7.loss_mask: 0.3745, decode.d7.loss_dice: 0.5189, decode.d8.loss_cls: 0.0734, decode.d8.loss_mask: 0.3748, decode.d8.loss_dice: 0.5191, loss: 11.4577 +2022-05-06 08:45:59,958 - mmseg - INFO - Iter [36200/40000] lr: 1.364e-07, eta: 0:53:12, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0729, decode.loss_mask: 0.3666, decode.loss_dice: 0.5199, decode.d0.loss_cls: 1.4472, decode.d0.loss_mask: 0.4059, decode.d0.loss_dice: 0.6105, decode.d1.loss_cls: 0.1661, decode.d1.loss_mask: 0.3779, decode.d1.loss_dice: 0.5551, decode.d2.loss_cls: 0.1068, decode.d2.loss_mask: 0.3719, decode.d2.loss_dice: 0.5347, decode.d3.loss_cls: 0.0861, decode.d3.loss_mask: 0.3698, decode.d3.loss_dice: 0.5229, decode.d4.loss_cls: 0.0881, decode.d4.loss_mask: 0.3669, decode.d4.loss_dice: 0.5227, decode.d5.loss_cls: 0.0818, decode.d5.loss_mask: 0.3668, decode.d5.loss_dice: 0.5192, decode.d6.loss_cls: 0.0713, decode.d6.loss_mask: 0.3662, decode.d6.loss_dice: 0.5191, decode.d7.loss_cls: 0.0705, decode.d7.loss_mask: 0.3664, decode.d7.loss_dice: 0.5211, decode.d8.loss_cls: 0.0701, decode.d8.loss_mask: 0.3660, decode.d8.loss_dice: 0.5203, loss: 11.3307 +2022-05-06 08:46:34,004 - mmseg - INFO - Iter [36250/40000] lr: 1.346e-07, eta: 0:52:29, time: 0.681, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0715, decode.loss_mask: 0.3694, decode.loss_dice: 0.5167, decode.d0.loss_cls: 1.4171, decode.d0.loss_mask: 0.4133, decode.d0.loss_dice: 0.6041, decode.d1.loss_cls: 0.1672, decode.d1.loss_mask: 0.3822, decode.d1.loss_dice: 0.5369, decode.d2.loss_cls: 0.1096, decode.d2.loss_mask: 0.3768, decode.d2.loss_dice: 0.5240, decode.d3.loss_cls: 0.0935, decode.d3.loss_mask: 0.3744, decode.d3.loss_dice: 0.5139, decode.d4.loss_cls: 0.0829, decode.d4.loss_mask: 0.3742, decode.d4.loss_dice: 0.5186, decode.d5.loss_cls: 0.0782, decode.d5.loss_mask: 0.3722, decode.d5.loss_dice: 0.5160, decode.d6.loss_cls: 0.0746, decode.d6.loss_mask: 0.3703, decode.d6.loss_dice: 0.5132, decode.d7.loss_cls: 0.0746, decode.d7.loss_mask: 0.3698, decode.d7.loss_dice: 0.5113, decode.d8.loss_cls: 0.0772, decode.d8.loss_mask: 0.3689, decode.d8.loss_dice: 0.5123, loss: 11.2851 +2022-05-06 08:47:07,793 - mmseg - INFO - Iter [36300/40000] lr: 1.328e-07, eta: 0:51:46, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0723, decode.loss_mask: 0.3630, decode.loss_dice: 0.5126, decode.d0.loss_cls: 1.4456, decode.d0.loss_mask: 0.4086, decode.d0.loss_dice: 0.6011, decode.d1.loss_cls: 0.1816, decode.d1.loss_mask: 0.3776, decode.d1.loss_dice: 0.5430, decode.d2.loss_cls: 0.1058, decode.d2.loss_mask: 0.3702, decode.d2.loss_dice: 0.5266, decode.d3.loss_cls: 0.0900, decode.d3.loss_mask: 0.3680, decode.d3.loss_dice: 0.5181, decode.d4.loss_cls: 0.0820, decode.d4.loss_mask: 0.3677, decode.d4.loss_dice: 0.5190, decode.d5.loss_cls: 0.0752, decode.d5.loss_mask: 0.3665, decode.d5.loss_dice: 0.5160, decode.d6.loss_cls: 0.0764, decode.d6.loss_mask: 0.3651, decode.d6.loss_dice: 0.5136, decode.d7.loss_cls: 0.0738, decode.d7.loss_mask: 0.3629, decode.d7.loss_dice: 0.5088, decode.d8.loss_cls: 0.0713, decode.d8.loss_mask: 0.3628, decode.d8.loss_dice: 0.5156, loss: 11.2607 +2022-05-06 08:47:41,361 - mmseg - INFO - Iter [36350/40000] lr: 1.311e-07, eta: 0:51:03, time: 0.671, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0885, decode.loss_mask: 0.3723, decode.loss_dice: 0.5296, decode.d0.loss_cls: 1.4183, decode.d0.loss_mask: 0.4127, decode.d0.loss_dice: 0.6244, decode.d1.loss_cls: 0.1855, decode.d1.loss_mask: 0.3849, decode.d1.loss_dice: 0.5703, decode.d2.loss_cls: 0.1269, decode.d2.loss_mask: 0.3771, decode.d2.loss_dice: 0.5521, decode.d3.loss_cls: 0.1114, decode.d3.loss_mask: 0.3743, decode.d3.loss_dice: 0.5373, decode.d4.loss_cls: 0.0960, decode.d4.loss_mask: 0.3742, decode.d4.loss_dice: 0.5405, decode.d5.loss_cls: 0.0952, decode.d5.loss_mask: 0.3727, decode.d5.loss_dice: 0.5337, decode.d6.loss_cls: 0.0913, decode.d6.loss_mask: 0.3734, decode.d6.loss_dice: 0.5332, decode.d7.loss_cls: 0.0886, decode.d7.loss_mask: 0.3721, decode.d7.loss_dice: 0.5325, decode.d8.loss_cls: 0.0889, decode.d8.loss_mask: 0.3714, decode.d8.loss_dice: 0.5378, loss: 11.6670 +2022-05-06 08:48:14,914 - mmseg - INFO - Iter [36400/40000] lr: 1.293e-07, eta: 0:50:20, time: 0.671, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0769, decode.loss_mask: 0.3703, decode.loss_dice: 0.5034, decode.d0.loss_cls: 1.4546, decode.d0.loss_mask: 0.4125, decode.d0.loss_dice: 0.6013, decode.d1.loss_cls: 0.1964, decode.d1.loss_mask: 0.3830, decode.d1.loss_dice: 0.5403, decode.d2.loss_cls: 0.1203, decode.d2.loss_mask: 0.3759, decode.d2.loss_dice: 0.5167, decode.d3.loss_cls: 0.0946, decode.d3.loss_mask: 0.3731, decode.d3.loss_dice: 0.5114, decode.d4.loss_cls: 0.0889, decode.d4.loss_mask: 0.3711, decode.d4.loss_dice: 0.5099, decode.d5.loss_cls: 0.0868, decode.d5.loss_mask: 0.3713, decode.d5.loss_dice: 0.5073, decode.d6.loss_cls: 0.0787, decode.d6.loss_mask: 0.3713, decode.d6.loss_dice: 0.5022, decode.d7.loss_cls: 0.0793, decode.d7.loss_mask: 0.3701, decode.d7.loss_dice: 0.5070, decode.d8.loss_cls: 0.0790, decode.d8.loss_mask: 0.3696, decode.d8.loss_dice: 0.5080, loss: 11.3310 +2022-05-06 08:48:51,421 - mmseg - INFO - Iter [36450/40000] lr: 1.275e-07, eta: 0:49:38, time: 0.730, data_time: 0.058, memory: 53770, decode.loss_cls: 0.0747, decode.loss_mask: 0.3684, decode.loss_dice: 0.5206, decode.d0.loss_cls: 1.4653, decode.d0.loss_mask: 0.4097, decode.d0.loss_dice: 0.6143, decode.d1.loss_cls: 0.1839, decode.d1.loss_mask: 0.3844, decode.d1.loss_dice: 0.5550, decode.d2.loss_cls: 0.1158, decode.d2.loss_mask: 0.3757, decode.d2.loss_dice: 0.5337, decode.d3.loss_cls: 0.0923, decode.d3.loss_mask: 0.3725, decode.d3.loss_dice: 0.5290, decode.d4.loss_cls: 0.0898, decode.d4.loss_mask: 0.3721, decode.d4.loss_dice: 0.5266, decode.d5.loss_cls: 0.0825, decode.d5.loss_mask: 0.3721, decode.d5.loss_dice: 0.5281, decode.d6.loss_cls: 0.0755, decode.d6.loss_mask: 0.3701, decode.d6.loss_dice: 0.5228, decode.d7.loss_cls: 0.0773, decode.d7.loss_mask: 0.3703, decode.d7.loss_dice: 0.5189, decode.d8.loss_cls: 0.0705, decode.d8.loss_mask: 0.3697, decode.d8.loss_dice: 0.5266, loss: 11.4683 +2022-05-06 08:49:25,571 - mmseg - INFO - Iter [36500/40000] lr: 1.257e-07, eta: 0:48:55, time: 0.683, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0852, decode.loss_mask: 0.3615, decode.loss_dice: 0.5202, decode.d0.loss_cls: 1.4263, decode.d0.loss_mask: 0.4070, decode.d0.loss_dice: 0.6127, decode.d1.loss_cls: 0.1873, decode.d1.loss_mask: 0.3741, decode.d1.loss_dice: 0.5534, decode.d2.loss_cls: 0.1252, decode.d2.loss_mask: 0.3671, decode.d2.loss_dice: 0.5325, decode.d3.loss_cls: 0.1037, decode.d3.loss_mask: 0.3634, decode.d3.loss_dice: 0.5254, decode.d4.loss_cls: 0.0917, decode.d4.loss_mask: 0.3617, decode.d4.loss_dice: 0.5265, decode.d5.loss_cls: 0.0822, decode.d5.loss_mask: 0.3623, decode.d5.loss_dice: 0.5235, decode.d6.loss_cls: 0.0890, decode.d6.loss_mask: 0.3610, decode.d6.loss_dice: 0.5199, decode.d7.loss_cls: 0.0904, decode.d7.loss_mask: 0.3610, decode.d7.loss_dice: 0.5179, decode.d8.loss_cls: 0.0874, decode.d8.loss_mask: 0.3596, decode.d8.loss_dice: 0.5188, loss: 11.3979 +2022-05-06 08:49:58,929 - mmseg - INFO - Iter [36550/40000] lr: 1.239e-07, eta: 0:48:12, time: 0.667, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0883, decode.loss_mask: 0.3719, decode.loss_dice: 0.5097, decode.d0.loss_cls: 1.4638, decode.d0.loss_mask: 0.4126, decode.d0.loss_dice: 0.6050, decode.d1.loss_cls: 0.1939, decode.d1.loss_mask: 0.3842, decode.d1.loss_dice: 0.5374, decode.d2.loss_cls: 0.1276, decode.d2.loss_mask: 0.3757, decode.d2.loss_dice: 0.5194, decode.d3.loss_cls: 0.1077, decode.d3.loss_mask: 0.3752, decode.d3.loss_dice: 0.5133, decode.d4.loss_cls: 0.0936, decode.d4.loss_mask: 0.3739, decode.d4.loss_dice: 0.5127, decode.d5.loss_cls: 0.0892, decode.d5.loss_mask: 0.3741, decode.d5.loss_dice: 0.5127, decode.d6.loss_cls: 0.0874, decode.d6.loss_mask: 0.3719, decode.d6.loss_dice: 0.5094, decode.d7.loss_cls: 0.0892, decode.d7.loss_mask: 0.3725, decode.d7.loss_dice: 0.5071, decode.d8.loss_cls: 0.0852, decode.d8.loss_mask: 0.3728, decode.d8.loss_dice: 0.5105, loss: 11.4484 +2022-05-06 08:50:33,160 - mmseg - INFO - Iter [36600/40000] lr: 1.221e-07, eta: 0:47:29, time: 0.685, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0874, decode.loss_mask: 0.3412, decode.loss_dice: 0.5103, decode.d0.loss_cls: 1.4671, decode.d0.loss_mask: 0.3824, decode.d0.loss_dice: 0.6078, decode.d1.loss_cls: 0.1971, decode.d1.loss_mask: 0.3538, decode.d1.loss_dice: 0.5469, decode.d2.loss_cls: 0.1266, decode.d2.loss_mask: 0.3468, decode.d2.loss_dice: 0.5263, decode.d3.loss_cls: 0.1040, decode.d3.loss_mask: 0.3458, decode.d3.loss_dice: 0.5231, decode.d4.loss_cls: 0.0970, decode.d4.loss_mask: 0.3441, decode.d4.loss_dice: 0.5170, decode.d5.loss_cls: 0.0914, decode.d5.loss_mask: 0.3415, decode.d5.loss_dice: 0.5161, decode.d6.loss_cls: 0.0879, decode.d6.loss_mask: 0.3408, decode.d6.loss_dice: 0.5153, decode.d7.loss_cls: 0.0892, decode.d7.loss_mask: 0.3405, decode.d7.loss_dice: 0.5130, decode.d8.loss_cls: 0.0857, decode.d8.loss_mask: 0.3401, decode.d8.loss_dice: 0.5134, loss: 11.1997 +2022-05-06 08:51:06,785 - mmseg - INFO - Iter [36650/40000] lr: 1.203e-07, eta: 0:46:46, time: 0.672, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0800, decode.loss_mask: 0.3744, decode.loss_dice: 0.5068, decode.d0.loss_cls: 1.4311, decode.d0.loss_mask: 0.4123, decode.d0.loss_dice: 0.5965, decode.d1.loss_cls: 0.1860, decode.d1.loss_mask: 0.3855, decode.d1.loss_dice: 0.5373, decode.d2.loss_cls: 0.1191, decode.d2.loss_mask: 0.3782, decode.d2.loss_dice: 0.5173, decode.d3.loss_cls: 0.0932, decode.d3.loss_mask: 0.3771, decode.d3.loss_dice: 0.5066, decode.d4.loss_cls: 0.0855, decode.d4.loss_mask: 0.3762, decode.d4.loss_dice: 0.5125, decode.d5.loss_cls: 0.0843, decode.d5.loss_mask: 0.3744, decode.d5.loss_dice: 0.5105, decode.d6.loss_cls: 0.0796, decode.d6.loss_mask: 0.3728, decode.d6.loss_dice: 0.5087, decode.d7.loss_cls: 0.0815, decode.d7.loss_mask: 0.3737, decode.d7.loss_dice: 0.5042, decode.d8.loss_cls: 0.0757, decode.d8.loss_mask: 0.3747, decode.d8.loss_dice: 0.5084, loss: 11.3241 +2022-05-06 08:51:40,567 - mmseg - INFO - Iter [36700/40000] lr: 1.185e-07, eta: 0:46:04, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0837, decode.loss_mask: 0.3595, decode.loss_dice: 0.5253, decode.d0.loss_cls: 1.4514, decode.d0.loss_mask: 0.4055, decode.d0.loss_dice: 0.6156, decode.d1.loss_cls: 0.1945, decode.d1.loss_mask: 0.3756, decode.d1.loss_dice: 0.5533, decode.d2.loss_cls: 0.1329, decode.d2.loss_mask: 0.3676, decode.d2.loss_dice: 0.5401, decode.d3.loss_cls: 0.1095, decode.d3.loss_mask: 0.3642, decode.d3.loss_dice: 0.5307, decode.d4.loss_cls: 0.0955, decode.d4.loss_mask: 0.3628, decode.d4.loss_dice: 0.5340, decode.d5.loss_cls: 0.0959, decode.d5.loss_mask: 0.3628, decode.d5.loss_dice: 0.5270, decode.d6.loss_cls: 0.0896, decode.d6.loss_mask: 0.3615, decode.d6.loss_dice: 0.5262, decode.d7.loss_cls: 0.0866, decode.d7.loss_mask: 0.3613, decode.d7.loss_dice: 0.5246, decode.d8.loss_cls: 0.0870, decode.d8.loss_mask: 0.3603, decode.d8.loss_dice: 0.5245, loss: 11.5090 +2022-05-06 08:52:14,073 - mmseg - INFO - Iter [36750/40000] lr: 1.167e-07, eta: 0:45:21, time: 0.670, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0773, decode.loss_mask: 0.3566, decode.loss_dice: 0.4949, decode.d0.loss_cls: 1.4124, decode.d0.loss_mask: 0.4002, decode.d0.loss_dice: 0.5836, decode.d1.loss_cls: 0.1673, decode.d1.loss_mask: 0.3716, decode.d1.loss_dice: 0.5293, decode.d2.loss_cls: 0.1035, decode.d2.loss_mask: 0.3641, decode.d2.loss_dice: 0.5065, decode.d3.loss_cls: 0.0857, decode.d3.loss_mask: 0.3622, decode.d3.loss_dice: 0.5012, decode.d4.loss_cls: 0.0789, decode.d4.loss_mask: 0.3592, decode.d4.loss_dice: 0.4967, decode.d5.loss_cls: 0.0751, decode.d5.loss_mask: 0.3582, decode.d5.loss_dice: 0.4965, decode.d6.loss_cls: 0.0762, decode.d6.loss_mask: 0.3588, decode.d6.loss_dice: 0.4964, decode.d7.loss_cls: 0.0724, decode.d7.loss_mask: 0.3591, decode.d7.loss_dice: 0.4968, decode.d8.loss_cls: 0.0732, decode.d8.loss_mask: 0.3566, decode.d8.loss_dice: 0.4971, loss: 10.9676 +2022-05-06 08:52:49,964 - mmseg - INFO - Iter [36800/40000] lr: 1.149e-07, eta: 0:44:39, time: 0.718, data_time: 0.058, memory: 53770, decode.loss_cls: 0.0831, decode.loss_mask: 0.3507, decode.loss_dice: 0.5236, decode.d0.loss_cls: 1.4626, decode.d0.loss_mask: 0.3938, decode.d0.loss_dice: 0.6146, decode.d1.loss_cls: 0.1992, decode.d1.loss_mask: 0.3652, decode.d1.loss_dice: 0.5566, decode.d2.loss_cls: 0.1275, decode.d2.loss_mask: 0.3577, decode.d2.loss_dice: 0.5358, decode.d3.loss_cls: 0.1016, decode.d3.loss_mask: 0.3541, decode.d3.loss_dice: 0.5292, decode.d4.loss_cls: 0.0926, decode.d4.loss_mask: 0.3528, decode.d4.loss_dice: 0.5282, decode.d5.loss_cls: 0.0907, decode.d5.loss_mask: 0.3533, decode.d5.loss_dice: 0.5243, decode.d6.loss_cls: 0.0814, decode.d6.loss_mask: 0.3523, decode.d6.loss_dice: 0.5249, decode.d7.loss_cls: 0.0824, decode.d7.loss_mask: 0.3525, decode.d7.loss_dice: 0.5233, decode.d8.loss_cls: 0.0835, decode.d8.loss_mask: 0.3521, decode.d8.loss_dice: 0.5210, loss: 11.3706 +2022-05-06 08:53:24,079 - mmseg - INFO - Iter [36850/40000] lr: 1.131e-07, eta: 0:43:56, time: 0.682, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0723, decode.loss_mask: 0.3602, decode.loss_dice: 0.5062, decode.d0.loss_cls: 1.4275, decode.d0.loss_mask: 0.4029, decode.d0.loss_dice: 0.6058, decode.d1.loss_cls: 0.1887, decode.d1.loss_mask: 0.3763, decode.d1.loss_dice: 0.5437, decode.d2.loss_cls: 0.1114, decode.d2.loss_mask: 0.3670, decode.d2.loss_dice: 0.5245, decode.d3.loss_cls: 0.0941, decode.d3.loss_mask: 0.3647, decode.d3.loss_dice: 0.5153, decode.d4.loss_cls: 0.0825, decode.d4.loss_mask: 0.3621, decode.d4.loss_dice: 0.5131, decode.d5.loss_cls: 0.0805, decode.d5.loss_mask: 0.3602, decode.d5.loss_dice: 0.5107, decode.d6.loss_cls: 0.0756, decode.d6.loss_mask: 0.3615, decode.d6.loss_dice: 0.5076, decode.d7.loss_cls: 0.0751, decode.d7.loss_mask: 0.3613, decode.d7.loss_dice: 0.5085, decode.d8.loss_cls: 0.0746, decode.d8.loss_mask: 0.3599, decode.d8.loss_dice: 0.5113, loss: 11.2051 +2022-05-06 08:53:58,172 - mmseg - INFO - Iter [36900/40000] lr: 1.113e-07, eta: 0:43:13, time: 0.682, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0714, decode.loss_mask: 0.3674, decode.loss_dice: 0.5099, decode.d0.loss_cls: 1.4408, decode.d0.loss_mask: 0.4150, decode.d0.loss_dice: 0.6050, decode.d1.loss_cls: 0.1718, decode.d1.loss_mask: 0.3846, decode.d1.loss_dice: 0.5454, decode.d2.loss_cls: 0.1156, decode.d2.loss_mask: 0.3773, decode.d2.loss_dice: 0.5258, decode.d3.loss_cls: 0.0848, decode.d3.loss_mask: 0.3737, decode.d3.loss_dice: 0.5209, decode.d4.loss_cls: 0.0801, decode.d4.loss_mask: 0.3725, decode.d4.loss_dice: 0.5164, decode.d5.loss_cls: 0.0765, decode.d5.loss_mask: 0.3698, decode.d5.loss_dice: 0.5137, decode.d6.loss_cls: 0.0779, decode.d6.loss_mask: 0.3697, decode.d6.loss_dice: 0.5117, decode.d7.loss_cls: 0.0756, decode.d7.loss_mask: 0.3676, decode.d7.loss_dice: 0.5092, decode.d8.loss_cls: 0.0755, decode.d8.loss_mask: 0.3679, decode.d8.loss_dice: 0.5112, loss: 11.3048 +2022-05-06 08:54:32,288 - mmseg - INFO - Iter [36950/40000] lr: 1.095e-07, eta: 0:42:31, time: 0.682, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0792, decode.loss_mask: 0.3670, decode.loss_dice: 0.5097, decode.d0.loss_cls: 1.4062, decode.d0.loss_mask: 0.4086, decode.d0.loss_dice: 0.5964, decode.d1.loss_cls: 0.1796, decode.d1.loss_mask: 0.3781, decode.d1.loss_dice: 0.5388, decode.d2.loss_cls: 0.1188, decode.d2.loss_mask: 0.3732, decode.d2.loss_dice: 0.5192, decode.d3.loss_cls: 0.0930, decode.d3.loss_mask: 0.3700, decode.d3.loss_dice: 0.5130, decode.d4.loss_cls: 0.0904, decode.d4.loss_mask: 0.3687, decode.d4.loss_dice: 0.5136, decode.d5.loss_cls: 0.0807, decode.d5.loss_mask: 0.3693, decode.d5.loss_dice: 0.5144, decode.d6.loss_cls: 0.0755, decode.d6.loss_mask: 0.3679, decode.d6.loss_dice: 0.5115, decode.d7.loss_cls: 0.0784, decode.d7.loss_mask: 0.3680, decode.d7.loss_dice: 0.5100, decode.d8.loss_cls: 0.0740, decode.d8.loss_mask: 0.3659, decode.d8.loss_dice: 0.5085, loss: 11.2476 +2022-05-06 08:55:05,588 - mmseg - INFO - Saving checkpoint at 37000 iterations +2022-05-06 08:55:30,964 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 08:55:30,966 - mmseg - INFO - Iter [37000/40000] lr: 1.077e-07, eta: 0:41:51, time: 1.172, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0855, decode.loss_mask: 0.3599, decode.loss_dice: 0.5165, decode.d0.loss_cls: 1.4982, decode.d0.loss_mask: 0.4093, decode.d0.loss_dice: 0.6204, decode.d1.loss_cls: 0.1895, decode.d1.loss_mask: 0.3744, decode.d1.loss_dice: 0.5519, decode.d2.loss_cls: 0.1248, decode.d2.loss_mask: 0.3671, decode.d2.loss_dice: 0.5305, decode.d3.loss_cls: 0.1005, decode.d3.loss_mask: 0.3620, decode.d3.loss_dice: 0.5205, decode.d4.loss_cls: 0.0931, decode.d4.loss_mask: 0.3620, decode.d4.loss_dice: 0.5214, decode.d5.loss_cls: 0.0873, decode.d5.loss_mask: 0.3628, decode.d5.loss_dice: 0.5173, decode.d6.loss_cls: 0.0883, decode.d6.loss_mask: 0.3595, decode.d6.loss_dice: 0.5183, decode.d7.loss_cls: 0.0874, decode.d7.loss_mask: 0.3602, decode.d7.loss_dice: 0.5181, decode.d8.loss_cls: 0.0838, decode.d8.loss_mask: 0.3603, decode.d8.loss_dice: 0.5179, loss: 11.4488 +2022-05-06 08:56:05,057 - mmseg - INFO - Iter [37050/40000] lr: 1.059e-07, eta: 0:41:08, time: 0.684, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0781, decode.loss_mask: 0.3526, decode.loss_dice: 0.5003, decode.d0.loss_cls: 1.3902, decode.d0.loss_mask: 0.3880, decode.d0.loss_dice: 0.5891, decode.d1.loss_cls: 0.1708, decode.d1.loss_mask: 0.3655, decode.d1.loss_dice: 0.5363, decode.d2.loss_cls: 0.1150, decode.d2.loss_mask: 0.3584, decode.d2.loss_dice: 0.5132, decode.d3.loss_cls: 0.0899, decode.d3.loss_mask: 0.3572, decode.d3.loss_dice: 0.5070, decode.d4.loss_cls: 0.0865, decode.d4.loss_mask: 0.3547, decode.d4.loss_dice: 0.5069, decode.d5.loss_cls: 0.0775, decode.d5.loss_mask: 0.3527, decode.d5.loss_dice: 0.5036, decode.d6.loss_cls: 0.0822, decode.d6.loss_mask: 0.3532, decode.d6.loss_dice: 0.4983, decode.d7.loss_cls: 0.0791, decode.d7.loss_mask: 0.3529, decode.d7.loss_dice: 0.4995, decode.d8.loss_cls: 0.0801, decode.d8.loss_mask: 0.3536, decode.d8.loss_dice: 0.4971, loss: 10.9895 +2022-05-06 08:56:40,765 - mmseg - INFO - Iter [37100/40000] lr: 1.041e-07, eta: 0:40:26, time: 0.714, data_time: 0.055, memory: 53770, decode.loss_cls: 0.0819, decode.loss_mask: 0.3609, decode.loss_dice: 0.4969, decode.d0.loss_cls: 1.4542, decode.d0.loss_mask: 0.4018, decode.d0.loss_dice: 0.5826, decode.d1.loss_cls: 0.1832, decode.d1.loss_mask: 0.3754, decode.d1.loss_dice: 0.5241, decode.d2.loss_cls: 0.1253, decode.d2.loss_mask: 0.3655, decode.d2.loss_dice: 0.5094, decode.d3.loss_cls: 0.1021, decode.d3.loss_mask: 0.3638, decode.d3.loss_dice: 0.4981, decode.d4.loss_cls: 0.0991, decode.d4.loss_mask: 0.3625, decode.d4.loss_dice: 0.5024, decode.d5.loss_cls: 0.0881, decode.d5.loss_mask: 0.3620, decode.d5.loss_dice: 0.4969, decode.d6.loss_cls: 0.0862, decode.d6.loss_mask: 0.3611, decode.d6.loss_dice: 0.4955, decode.d7.loss_cls: 0.0849, decode.d7.loss_mask: 0.3606, decode.d7.loss_dice: 0.4927, decode.d8.loss_cls: 0.0826, decode.d8.loss_mask: 0.3603, decode.d8.loss_dice: 0.4947, loss: 11.1548 +2022-05-06 08:57:14,590 - mmseg - INFO - Iter [37150/40000] lr: 1.023e-07, eta: 0:39:43, time: 0.676, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0777, decode.loss_mask: 0.3564, decode.loss_dice: 0.4967, decode.d0.loss_cls: 1.4384, decode.d0.loss_mask: 0.3974, decode.d0.loss_dice: 0.5920, decode.d1.loss_cls: 0.1747, decode.d1.loss_mask: 0.3695, decode.d1.loss_dice: 0.5328, decode.d2.loss_cls: 0.1166, decode.d2.loss_mask: 0.3609, decode.d2.loss_dice: 0.5109, decode.d3.loss_cls: 0.0962, decode.d3.loss_mask: 0.3584, decode.d3.loss_dice: 0.4991, decode.d4.loss_cls: 0.0826, decode.d4.loss_mask: 0.3593, decode.d4.loss_dice: 0.5050, decode.d5.loss_cls: 0.0871, decode.d5.loss_mask: 0.3567, decode.d5.loss_dice: 0.5008, decode.d6.loss_cls: 0.0782, decode.d6.loss_mask: 0.3579, decode.d6.loss_dice: 0.4985, decode.d7.loss_cls: 0.0794, decode.d7.loss_mask: 0.3568, decode.d7.loss_dice: 0.4950, decode.d8.loss_cls: 0.0753, decode.d8.loss_mask: 0.3568, decode.d8.loss_dice: 0.4977, loss: 11.0649 +2022-05-06 08:57:48,409 - mmseg - INFO - Iter [37200/40000] lr: 1.005e-07, eta: 0:39:01, time: 0.677, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0669, decode.loss_mask: 0.3746, decode.loss_dice: 0.4868, decode.d0.loss_cls: 1.3929, decode.d0.loss_mask: 0.4161, decode.d0.loss_dice: 0.5777, decode.d1.loss_cls: 0.1733, decode.d1.loss_mask: 0.3850, decode.d1.loss_dice: 0.5163, decode.d2.loss_cls: 0.1112, decode.d2.loss_mask: 0.3780, decode.d2.loss_dice: 0.5012, decode.d3.loss_cls: 0.0841, decode.d3.loss_mask: 0.3781, decode.d3.loss_dice: 0.4903, decode.d4.loss_cls: 0.0796, decode.d4.loss_mask: 0.3777, decode.d4.loss_dice: 0.4931, decode.d5.loss_cls: 0.0765, decode.d5.loss_mask: 0.3755, decode.d5.loss_dice: 0.4887, decode.d6.loss_cls: 0.0710, decode.d6.loss_mask: 0.3762, decode.d6.loss_dice: 0.4868, decode.d7.loss_cls: 0.0752, decode.d7.loss_mask: 0.3754, decode.d7.loss_dice: 0.4867, decode.d8.loss_cls: 0.0682, decode.d8.loss_mask: 0.3750, decode.d8.loss_dice: 0.4886, loss: 11.0266 +2022-05-06 08:58:22,053 - mmseg - INFO - Iter [37250/40000] lr: 9.875e-08, eta: 0:38:18, time: 0.672, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0832, decode.loss_mask: 0.3504, decode.loss_dice: 0.4998, decode.d0.loss_cls: 1.4566, decode.d0.loss_mask: 0.3886, decode.d0.loss_dice: 0.5778, decode.d1.loss_cls: 0.1712, decode.d1.loss_mask: 0.3631, decode.d1.loss_dice: 0.5269, decode.d2.loss_cls: 0.1136, decode.d2.loss_mask: 0.3556, decode.d2.loss_dice: 0.5088, decode.d3.loss_cls: 0.0968, decode.d3.loss_mask: 0.3534, decode.d3.loss_dice: 0.5022, decode.d4.loss_cls: 0.0896, decode.d4.loss_mask: 0.3508, decode.d4.loss_dice: 0.5030, decode.d5.loss_cls: 0.0924, decode.d5.loss_mask: 0.3528, decode.d5.loss_dice: 0.5001, decode.d6.loss_cls: 0.0800, decode.d6.loss_mask: 0.3521, decode.d6.loss_dice: 0.4993, decode.d7.loss_cls: 0.0806, decode.d7.loss_mask: 0.3509, decode.d7.loss_dice: 0.4972, decode.d8.loss_cls: 0.0824, decode.d8.loss_mask: 0.3508, decode.d8.loss_dice: 0.4983, loss: 11.0281 +2022-05-06 08:58:55,900 - mmseg - INFO - Iter [37300/40000] lr: 9.695e-08, eta: 0:37:36, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0815, decode.loss_mask: 0.3548, decode.loss_dice: 0.5022, decode.d0.loss_cls: 1.4574, decode.d0.loss_mask: 0.3975, decode.d0.loss_dice: 0.6027, decode.d1.loss_cls: 0.1784, decode.d1.loss_mask: 0.3675, decode.d1.loss_dice: 0.5401, decode.d2.loss_cls: 0.1099, decode.d2.loss_mask: 0.3594, decode.d2.loss_dice: 0.5255, decode.d3.loss_cls: 0.0919, decode.d3.loss_mask: 0.3588, decode.d3.loss_dice: 0.5117, decode.d4.loss_cls: 0.0882, decode.d4.loss_mask: 0.3568, decode.d4.loss_dice: 0.5100, decode.d5.loss_cls: 0.0852, decode.d5.loss_mask: 0.3566, decode.d5.loss_dice: 0.5102, decode.d6.loss_cls: 0.0810, decode.d6.loss_mask: 0.3558, decode.d6.loss_dice: 0.5046, decode.d7.loss_cls: 0.0795, decode.d7.loss_mask: 0.3547, decode.d7.loss_dice: 0.5021, decode.d8.loss_cls: 0.0839, decode.d8.loss_mask: 0.3541, decode.d8.loss_dice: 0.5030, loss: 11.1652 +2022-05-06 08:59:29,285 - mmseg - INFO - Iter [37350/40000] lr: 9.516e-08, eta: 0:36:53, time: 0.668, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0701, decode.loss_mask: 0.3780, decode.loss_dice: 0.5027, decode.d0.loss_cls: 1.4298, decode.d0.loss_mask: 0.4222, decode.d0.loss_dice: 0.5928, decode.d1.loss_cls: 0.1740, decode.d1.loss_mask: 0.3914, decode.d1.loss_dice: 0.5374, decode.d2.loss_cls: 0.1110, decode.d2.loss_mask: 0.3846, decode.d2.loss_dice: 0.5154, decode.d3.loss_cls: 0.0831, decode.d3.loss_mask: 0.3827, decode.d3.loss_dice: 0.5101, decode.d4.loss_cls: 0.0765, decode.d4.loss_mask: 0.3811, decode.d4.loss_dice: 0.5123, decode.d5.loss_cls: 0.0750, decode.d5.loss_mask: 0.3785, decode.d5.loss_dice: 0.5065, decode.d6.loss_cls: 0.0723, decode.d6.loss_mask: 0.3784, decode.d6.loss_dice: 0.5022, decode.d7.loss_cls: 0.0741, decode.d7.loss_mask: 0.3780, decode.d7.loss_dice: 0.5033, decode.d8.loss_cls: 0.0719, decode.d8.loss_mask: 0.3776, decode.d8.loss_dice: 0.5056, loss: 11.2785 +2022-05-06 09:00:05,612 - mmseg - INFO - Iter [37400/40000] lr: 9.336e-08, eta: 0:36:11, time: 0.726, data_time: 0.059, memory: 53770, decode.loss_cls: 0.0775, decode.loss_mask: 0.3750, decode.loss_dice: 0.5199, decode.d0.loss_cls: 1.4452, decode.d0.loss_mask: 0.4203, decode.d0.loss_dice: 0.6172, decode.d1.loss_cls: 0.1822, decode.d1.loss_mask: 0.3867, decode.d1.loss_dice: 0.5550, decode.d2.loss_cls: 0.1208, decode.d2.loss_mask: 0.3812, decode.d2.loss_dice: 0.5354, decode.d3.loss_cls: 0.0982, decode.d3.loss_mask: 0.3781, decode.d3.loss_dice: 0.5283, decode.d4.loss_cls: 0.0902, decode.d4.loss_mask: 0.3759, decode.d4.loss_dice: 0.5239, decode.d5.loss_cls: 0.0864, decode.d5.loss_mask: 0.3750, decode.d5.loss_dice: 0.5210, decode.d6.loss_cls: 0.0828, decode.d6.loss_mask: 0.3740, decode.d6.loss_dice: 0.5215, decode.d7.loss_cls: 0.0783, decode.d7.loss_mask: 0.3748, decode.d7.loss_dice: 0.5230, decode.d8.loss_cls: 0.0782, decode.d8.loss_mask: 0.3753, decode.d8.loss_dice: 0.5260, loss: 11.5273 +2022-05-06 09:00:39,349 - mmseg - INFO - Iter [37450/40000] lr: 9.157e-08, eta: 0:35:29, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0802, decode.loss_mask: 0.3636, decode.loss_dice: 0.5125, decode.d0.loss_cls: 1.4489, decode.d0.loss_mask: 0.4041, decode.d0.loss_dice: 0.5915, decode.d1.loss_cls: 0.1795, decode.d1.loss_mask: 0.3785, decode.d1.loss_dice: 0.5414, decode.d2.loss_cls: 0.1202, decode.d2.loss_mask: 0.3698, decode.d2.loss_dice: 0.5259, decode.d3.loss_cls: 0.1074, decode.d3.loss_mask: 0.3679, decode.d3.loss_dice: 0.5158, decode.d4.loss_cls: 0.0963, decode.d4.loss_mask: 0.3679, decode.d4.loss_dice: 0.5197, decode.d5.loss_cls: 0.0908, decode.d5.loss_mask: 0.3672, decode.d5.loss_dice: 0.5167, decode.d6.loss_cls: 0.0844, decode.d6.loss_mask: 0.3659, decode.d6.loss_dice: 0.5144, decode.d7.loss_cls: 0.0807, decode.d7.loss_mask: 0.3643, decode.d7.loss_dice: 0.5138, decode.d8.loss_cls: 0.0815, decode.d8.loss_mask: 0.3647, decode.d8.loss_dice: 0.5130, loss: 11.3487 +2022-05-06 09:01:12,758 - mmseg - INFO - Iter [37500/40000] lr: 8.977e-08, eta: 0:34:46, time: 0.669, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0758, decode.loss_mask: 0.3613, decode.loss_dice: 0.5253, decode.d0.loss_cls: 1.4507, decode.d0.loss_mask: 0.4075, decode.d0.loss_dice: 0.6176, decode.d1.loss_cls: 0.1794, decode.d1.loss_mask: 0.3762, decode.d1.loss_dice: 0.5615, decode.d2.loss_cls: 0.1155, decode.d2.loss_mask: 0.3682, decode.d2.loss_dice: 0.5398, decode.d3.loss_cls: 0.0900, decode.d3.loss_mask: 0.3659, decode.d3.loss_dice: 0.5322, decode.d4.loss_cls: 0.0907, decode.d4.loss_mask: 0.3647, decode.d4.loss_dice: 0.5343, decode.d5.loss_cls: 0.0832, decode.d5.loss_mask: 0.3641, decode.d5.loss_dice: 0.5306, decode.d6.loss_cls: 0.0862, decode.d6.loss_mask: 0.3635, decode.d6.loss_dice: 0.5293, decode.d7.loss_cls: 0.0800, decode.d7.loss_mask: 0.3618, decode.d7.loss_dice: 0.5226, decode.d8.loss_cls: 0.0789, decode.d8.loss_mask: 0.3607, decode.d8.loss_dice: 0.5261, loss: 11.4436 +2022-05-06 09:01:46,305 - mmseg - INFO - Iter [37550/40000] lr: 8.798e-08, eta: 0:34:04, time: 0.671, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0632, decode.loss_mask: 0.3672, decode.loss_dice: 0.5033, decode.d0.loss_cls: 1.4197, decode.d0.loss_mask: 0.4066, decode.d0.loss_dice: 0.5908, decode.d1.loss_cls: 0.1605, decode.d1.loss_mask: 0.3797, decode.d1.loss_dice: 0.5344, decode.d2.loss_cls: 0.1029, decode.d2.loss_mask: 0.3730, decode.d2.loss_dice: 0.5188, decode.d3.loss_cls: 0.0824, decode.d3.loss_mask: 0.3719, decode.d3.loss_dice: 0.5056, decode.d4.loss_cls: 0.0790, decode.d4.loss_mask: 0.3688, decode.d4.loss_dice: 0.5044, decode.d5.loss_cls: 0.0757, decode.d5.loss_mask: 0.3688, decode.d5.loss_dice: 0.5047, decode.d6.loss_cls: 0.0699, decode.d6.loss_mask: 0.3662, decode.d6.loss_dice: 0.5023, decode.d7.loss_cls: 0.0632, decode.d7.loss_mask: 0.3682, decode.d7.loss_dice: 0.5036, decode.d8.loss_cls: 0.0662, decode.d8.loss_mask: 0.3671, decode.d8.loss_dice: 0.5048, loss: 11.0930 +2022-05-06 09:02:19,668 - mmseg - INFO - Iter [37600/40000] lr: 8.618e-08, eta: 0:33:22, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0751, decode.loss_mask: 0.3486, decode.loss_dice: 0.4964, decode.d0.loss_cls: 1.4201, decode.d0.loss_mask: 0.3920, decode.d0.loss_dice: 0.5889, decode.d1.loss_cls: 0.1643, decode.d1.loss_mask: 0.3638, decode.d1.loss_dice: 0.5370, decode.d2.loss_cls: 0.1024, decode.d2.loss_mask: 0.3577, decode.d2.loss_dice: 0.5181, decode.d3.loss_cls: 0.0863, decode.d3.loss_mask: 0.3530, decode.d3.loss_dice: 0.5065, decode.d4.loss_cls: 0.0819, decode.d4.loss_mask: 0.3528, decode.d4.loss_dice: 0.5037, decode.d5.loss_cls: 0.0804, decode.d5.loss_mask: 0.3516, decode.d5.loss_dice: 0.4995, decode.d6.loss_cls: 0.0755, decode.d6.loss_mask: 0.3504, decode.d6.loss_dice: 0.5012, decode.d7.loss_cls: 0.0734, decode.d7.loss_mask: 0.3512, decode.d7.loss_dice: 0.4974, decode.d8.loss_cls: 0.0724, decode.d8.loss_mask: 0.3502, decode.d8.loss_dice: 0.4994, loss: 10.9510 +2022-05-06 09:02:52,919 - mmseg - INFO - Iter [37650/40000] lr: 8.439e-08, eta: 0:32:39, time: 0.665, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0609, decode.loss_mask: 0.3689, decode.loss_dice: 0.5074, decode.d0.loss_cls: 1.4646, decode.d0.loss_mask: 0.4096, decode.d0.loss_dice: 0.5913, decode.d1.loss_cls: 0.1791, decode.d1.loss_mask: 0.3810, decode.d1.loss_dice: 0.5403, decode.d2.loss_cls: 0.1078, decode.d2.loss_mask: 0.3748, decode.d2.loss_dice: 0.5199, decode.d3.loss_cls: 0.0778, decode.d3.loss_mask: 0.3734, decode.d3.loss_dice: 0.5156, decode.d4.loss_cls: 0.0706, decode.d4.loss_mask: 0.3710, decode.d4.loss_dice: 0.5156, decode.d5.loss_cls: 0.0652, decode.d5.loss_mask: 0.3702, decode.d5.loss_dice: 0.5143, decode.d6.loss_cls: 0.0624, decode.d6.loss_mask: 0.3721, decode.d6.loss_dice: 0.5132, decode.d7.loss_cls: 0.0601, decode.d7.loss_mask: 0.3700, decode.d7.loss_dice: 0.5073, decode.d8.loss_cls: 0.0571, decode.d8.loss_mask: 0.3691, decode.d8.loss_dice: 0.5111, loss: 11.2014 +2022-05-06 09:03:29,151 - mmseg - INFO - Iter [37700/40000] lr: 8.259e-08, eta: 0:31:57, time: 0.725, data_time: 0.060, memory: 53770, decode.loss_cls: 0.0755, decode.loss_mask: 0.3649, decode.loss_dice: 0.5079, decode.d0.loss_cls: 1.4324, decode.d0.loss_mask: 0.4045, decode.d0.loss_dice: 0.6017, decode.d1.loss_cls: 0.1752, decode.d1.loss_mask: 0.3763, decode.d1.loss_dice: 0.5403, decode.d2.loss_cls: 0.1125, decode.d2.loss_mask: 0.3707, decode.d2.loss_dice: 0.5209, decode.d3.loss_cls: 0.0924, decode.d3.loss_mask: 0.3693, decode.d3.loss_dice: 0.5168, decode.d4.loss_cls: 0.0837, decode.d4.loss_mask: 0.3680, decode.d4.loss_dice: 0.5148, decode.d5.loss_cls: 0.0817, decode.d5.loss_mask: 0.3672, decode.d5.loss_dice: 0.5126, decode.d6.loss_cls: 0.0791, decode.d6.loss_mask: 0.3664, decode.d6.loss_dice: 0.5103, decode.d7.loss_cls: 0.0769, decode.d7.loss_mask: 0.3660, decode.d7.loss_dice: 0.5119, decode.d8.loss_cls: 0.0751, decode.d8.loss_mask: 0.3651, decode.d8.loss_dice: 0.5089, loss: 11.2490 +2022-05-06 09:04:02,806 - mmseg - INFO - Iter [37750/40000] lr: 8.080e-08, eta: 0:31:15, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0775, decode.loss_mask: 0.3558, decode.loss_dice: 0.5101, decode.d0.loss_cls: 1.4614, decode.d0.loss_mask: 0.3981, decode.d0.loss_dice: 0.6047, decode.d1.loss_cls: 0.1868, decode.d1.loss_mask: 0.3678, decode.d1.loss_dice: 0.5459, decode.d2.loss_cls: 0.1177, decode.d2.loss_mask: 0.3596, decode.d2.loss_dice: 0.5243, decode.d3.loss_cls: 0.0930, decode.d3.loss_mask: 0.3594, decode.d3.loss_dice: 0.5196, decode.d4.loss_cls: 0.0819, decode.d4.loss_mask: 0.3599, decode.d4.loss_dice: 0.5219, decode.d5.loss_cls: 0.0827, decode.d5.loss_mask: 0.3582, decode.d5.loss_dice: 0.5166, decode.d6.loss_cls: 0.0784, decode.d6.loss_mask: 0.3575, decode.d6.loss_dice: 0.5139, decode.d7.loss_cls: 0.0772, decode.d7.loss_mask: 0.3559, decode.d7.loss_dice: 0.5131, decode.d8.loss_cls: 0.0767, decode.d8.loss_mask: 0.3553, decode.d8.loss_dice: 0.5128, loss: 11.2436 +2022-05-06 09:04:36,436 - mmseg - INFO - Iter [37800/40000] lr: 7.900e-08, eta: 0:30:33, time: 0.673, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0890, decode.loss_mask: 0.3621, decode.loss_dice: 0.5206, decode.d0.loss_cls: 1.4680, decode.d0.loss_mask: 0.4066, decode.d0.loss_dice: 0.6119, decode.d1.loss_cls: 0.1870, decode.d1.loss_mask: 0.3754, decode.d1.loss_dice: 0.5545, decode.d2.loss_cls: 0.1276, decode.d2.loss_mask: 0.3687, decode.d2.loss_dice: 0.5371, decode.d3.loss_cls: 0.1019, decode.d3.loss_mask: 0.3655, decode.d3.loss_dice: 0.5258, decode.d4.loss_cls: 0.1002, decode.d4.loss_mask: 0.3636, decode.d4.loss_dice: 0.5194, decode.d5.loss_cls: 0.0999, decode.d5.loss_mask: 0.3642, decode.d5.loss_dice: 0.5215, decode.d6.loss_cls: 0.0952, decode.d6.loss_mask: 0.3628, decode.d6.loss_dice: 0.5172, decode.d7.loss_cls: 0.0897, decode.d7.loss_mask: 0.3625, decode.d7.loss_dice: 0.5189, decode.d8.loss_cls: 0.0908, decode.d8.loss_mask: 0.3616, decode.d8.loss_dice: 0.5172, loss: 11.4862 +2022-05-06 09:05:09,984 - mmseg - INFO - Iter [37850/40000] lr: 7.721e-08, eta: 0:29:51, time: 0.671, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0681, decode.loss_mask: 0.3542, decode.loss_dice: 0.5149, decode.d0.loss_cls: 1.4370, decode.d0.loss_mask: 0.3951, decode.d0.loss_dice: 0.6069, decode.d1.loss_cls: 0.1844, decode.d1.loss_mask: 0.3676, decode.d1.loss_dice: 0.5506, decode.d2.loss_cls: 0.1105, decode.d2.loss_mask: 0.3610, decode.d2.loss_dice: 0.5322, decode.d3.loss_cls: 0.0826, decode.d3.loss_mask: 0.3579, decode.d3.loss_dice: 0.5265, decode.d4.loss_cls: 0.0741, decode.d4.loss_mask: 0.3580, decode.d4.loss_dice: 0.5221, decode.d5.loss_cls: 0.0728, decode.d5.loss_mask: 0.3565, decode.d5.loss_dice: 0.5197, decode.d6.loss_cls: 0.0726, decode.d6.loss_mask: 0.3555, decode.d6.loss_dice: 0.5182, decode.d7.loss_cls: 0.0721, decode.d7.loss_mask: 0.3555, decode.d7.loss_dice: 0.5182, decode.d8.loss_cls: 0.0661, decode.d8.loss_mask: 0.3550, decode.d8.loss_dice: 0.5171, loss: 11.1832 +2022-05-06 09:05:43,894 - mmseg - INFO - Iter [37900/40000] lr: 7.542e-08, eta: 0:29:09, time: 0.679, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0745, decode.loss_mask: 0.3480, decode.loss_dice: 0.4926, decode.d0.loss_cls: 1.4235, decode.d0.loss_mask: 0.3890, decode.d0.loss_dice: 0.5822, decode.d1.loss_cls: 0.1721, decode.d1.loss_mask: 0.3590, decode.d1.loss_dice: 0.5237, decode.d2.loss_cls: 0.1121, decode.d2.loss_mask: 0.3545, decode.d2.loss_dice: 0.5084, decode.d3.loss_cls: 0.0872, decode.d3.loss_mask: 0.3510, decode.d3.loss_dice: 0.5010, decode.d4.loss_cls: 0.0874, decode.d4.loss_mask: 0.3499, decode.d4.loss_dice: 0.5023, decode.d5.loss_cls: 0.0828, decode.d5.loss_mask: 0.3492, decode.d5.loss_dice: 0.4984, decode.d6.loss_cls: 0.0771, decode.d6.loss_mask: 0.3493, decode.d6.loss_dice: 0.4966, decode.d7.loss_cls: 0.0726, decode.d7.loss_mask: 0.3475, decode.d7.loss_dice: 0.4928, decode.d8.loss_cls: 0.0735, decode.d8.loss_mask: 0.3482, decode.d8.loss_dice: 0.4953, loss: 10.9015 +2022-05-06 09:06:17,597 - mmseg - INFO - Iter [37950/40000] lr: 7.362e-08, eta: 0:28:26, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0871, decode.loss_mask: 0.3734, decode.loss_dice: 0.5156, decode.d0.loss_cls: 1.4362, decode.d0.loss_mask: 0.4106, decode.d0.loss_dice: 0.6022, decode.d1.loss_cls: 0.1892, decode.d1.loss_mask: 0.3848, decode.d1.loss_dice: 0.5490, decode.d2.loss_cls: 0.1271, decode.d2.loss_mask: 0.3778, decode.d2.loss_dice: 0.5264, decode.d3.loss_cls: 0.0955, decode.d3.loss_mask: 0.3756, decode.d3.loss_dice: 0.5255, decode.d4.loss_cls: 0.0898, decode.d4.loss_mask: 0.3740, decode.d4.loss_dice: 0.5241, decode.d5.loss_cls: 0.0871, decode.d5.loss_mask: 0.3722, decode.d5.loss_dice: 0.5201, decode.d6.loss_cls: 0.0840, decode.d6.loss_mask: 0.3719, decode.d6.loss_dice: 0.5188, decode.d7.loss_cls: 0.0838, decode.d7.loss_mask: 0.3716, decode.d7.loss_dice: 0.5186, decode.d8.loss_cls: 0.0860, decode.d8.loss_mask: 0.3716, decode.d8.loss_dice: 0.5192, loss: 11.4688 +2022-05-06 09:06:51,104 - mmseg - INFO - Saving checkpoint at 38000 iterations +2022-05-06 09:07:18,174 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 09:07:18,181 - mmseg - INFO - Iter [38000/40000] lr: 7.183e-08, eta: 0:27:46, time: 1.209, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0769, decode.loss_mask: 0.3734, decode.loss_dice: 0.5108, decode.d0.loss_cls: 1.4001, decode.d0.loss_mask: 0.4128, decode.d0.loss_dice: 0.6029, decode.d1.loss_cls: 0.1717, decode.d1.loss_mask: 0.3894, decode.d1.loss_dice: 0.5436, decode.d2.loss_cls: 0.1159, decode.d2.loss_mask: 0.3805, decode.d2.loss_dice: 0.5265, decode.d3.loss_cls: 0.0905, decode.d3.loss_mask: 0.3775, decode.d3.loss_dice: 0.5199, decode.d4.loss_cls: 0.0873, decode.d4.loss_mask: 0.3760, decode.d4.loss_dice: 0.5223, decode.d5.loss_cls: 0.0806, decode.d5.loss_mask: 0.3751, decode.d5.loss_dice: 0.5180, decode.d6.loss_cls: 0.0774, decode.d6.loss_mask: 0.3741, decode.d6.loss_dice: 0.5126, decode.d7.loss_cls: 0.0726, decode.d7.loss_mask: 0.3733, decode.d7.loss_dice: 0.5134, decode.d8.loss_cls: 0.0735, decode.d8.loss_mask: 0.3733, decode.d8.loss_dice: 0.5153, loss: 11.3372 +2022-05-06 09:07:54,796 - mmseg - INFO - Iter [38050/40000] lr: 7.003e-08, eta: 0:27:04, time: 0.735, data_time: 0.059, memory: 53770, decode.loss_cls: 0.0872, decode.loss_mask: 0.3619, decode.loss_dice: 0.5228, decode.d0.loss_cls: 1.4232, decode.d0.loss_mask: 0.4016, decode.d0.loss_dice: 0.6148, decode.d1.loss_cls: 0.1859, decode.d1.loss_mask: 0.3745, decode.d1.loss_dice: 0.5547, decode.d2.loss_cls: 0.1269, decode.d2.loss_mask: 0.3691, decode.d2.loss_dice: 0.5363, decode.d3.loss_cls: 0.1122, decode.d3.loss_mask: 0.3656, decode.d3.loss_dice: 0.5271, decode.d4.loss_cls: 0.1059, decode.d4.loss_mask: 0.3628, decode.d4.loss_dice: 0.5265, decode.d5.loss_cls: 0.0915, decode.d5.loss_mask: 0.3645, decode.d5.loss_dice: 0.5268, decode.d6.loss_cls: 0.0895, decode.d6.loss_mask: 0.3629, decode.d6.loss_dice: 0.5246, decode.d7.loss_cls: 0.0876, decode.d7.loss_mask: 0.3621, decode.d7.loss_dice: 0.5238, decode.d8.loss_cls: 0.0917, decode.d8.loss_mask: 0.3637, decode.d8.loss_dice: 0.5251, loss: 11.4727 +2022-05-06 09:08:28,232 - mmseg - INFO - Iter [38100/40000] lr: 6.824e-08, eta: 0:26:22, time: 0.669, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0806, decode.loss_mask: 0.3691, decode.loss_dice: 0.5049, decode.d0.loss_cls: 1.4401, decode.d0.loss_mask: 0.4094, decode.d0.loss_dice: 0.5882, decode.d1.loss_cls: 0.1771, decode.d1.loss_mask: 0.3822, decode.d1.loss_dice: 0.5405, decode.d2.loss_cls: 0.1118, decode.d2.loss_mask: 0.3741, decode.d2.loss_dice: 0.5225, decode.d3.loss_cls: 0.0927, decode.d3.loss_mask: 0.3722, decode.d3.loss_dice: 0.5109, decode.d4.loss_cls: 0.0809, decode.d4.loss_mask: 0.3716, decode.d4.loss_dice: 0.5138, decode.d5.loss_cls: 0.0896, decode.d5.loss_mask: 0.3706, decode.d5.loss_dice: 0.5084, decode.d6.loss_cls: 0.0798, decode.d6.loss_mask: 0.3693, decode.d6.loss_dice: 0.5069, decode.d7.loss_cls: 0.0746, decode.d7.loss_mask: 0.3704, decode.d7.loss_dice: 0.5063, decode.d8.loss_cls: 0.0798, decode.d8.loss_mask: 0.3687, decode.d8.loss_dice: 0.5027, loss: 11.2697 +2022-05-06 09:09:01,850 - mmseg - INFO - Iter [38150/40000] lr: 6.644e-08, eta: 0:25:40, time: 0.672, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0743, decode.loss_mask: 0.3605, decode.loss_dice: 0.5201, decode.d0.loss_cls: 1.4337, decode.d0.loss_mask: 0.4007, decode.d0.loss_dice: 0.6041, decode.d1.loss_cls: 0.1728, decode.d1.loss_mask: 0.3736, decode.d1.loss_dice: 0.5504, decode.d2.loss_cls: 0.1161, decode.d2.loss_mask: 0.3661, decode.d2.loss_dice: 0.5340, decode.d3.loss_cls: 0.0940, decode.d3.loss_mask: 0.3643, decode.d3.loss_dice: 0.5260, decode.d4.loss_cls: 0.0823, decode.d4.loss_mask: 0.3628, decode.d4.loss_dice: 0.5269, decode.d5.loss_cls: 0.0818, decode.d5.loss_mask: 0.3618, decode.d5.loss_dice: 0.5233, decode.d6.loss_cls: 0.0740, decode.d6.loss_mask: 0.3613, decode.d6.loss_dice: 0.5196, decode.d7.loss_cls: 0.0732, decode.d7.loss_mask: 0.3606, decode.d7.loss_dice: 0.5213, decode.d8.loss_cls: 0.0756, decode.d8.loss_mask: 0.3606, decode.d8.loss_dice: 0.5189, loss: 11.2946 +2022-05-06 09:09:35,463 - mmseg - INFO - Iter [38200/40000] lr: 6.465e-08, eta: 0:24:58, time: 0.672, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0666, decode.loss_mask: 0.3576, decode.loss_dice: 0.5041, decode.d0.loss_cls: 1.4105, decode.d0.loss_mask: 0.4002, decode.d0.loss_dice: 0.6022, decode.d1.loss_cls: 0.1729, decode.d1.loss_mask: 0.3721, decode.d1.loss_dice: 0.5417, decode.d2.loss_cls: 0.1082, decode.d2.loss_mask: 0.3654, decode.d2.loss_dice: 0.5256, decode.d3.loss_cls: 0.0853, decode.d3.loss_mask: 0.3622, decode.d3.loss_dice: 0.5150, decode.d4.loss_cls: 0.0782, decode.d4.loss_mask: 0.3615, decode.d4.loss_dice: 0.5159, decode.d5.loss_cls: 0.0738, decode.d5.loss_mask: 0.3593, decode.d5.loss_dice: 0.5118, decode.d6.loss_cls: 0.0727, decode.d6.loss_mask: 0.3580, decode.d6.loss_dice: 0.5072, decode.d7.loss_cls: 0.0722, decode.d7.loss_mask: 0.3581, decode.d7.loss_dice: 0.5081, decode.d8.loss_cls: 0.0686, decode.d8.loss_mask: 0.3580, decode.d8.loss_dice: 0.5100, loss: 11.1030 +2022-05-06 09:10:09,483 - mmseg - INFO - Iter [38250/40000] lr: 6.285e-08, eta: 0:24:16, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0868, decode.loss_mask: 0.3499, decode.loss_dice: 0.5155, decode.d0.loss_cls: 1.4461, decode.d0.loss_mask: 0.3913, decode.d0.loss_dice: 0.6097, decode.d1.loss_cls: 0.1922, decode.d1.loss_mask: 0.3629, decode.d1.loss_dice: 0.5474, decode.d2.loss_cls: 0.1154, decode.d2.loss_mask: 0.3541, decode.d2.loss_dice: 0.5307, decode.d3.loss_cls: 0.0999, decode.d3.loss_mask: 0.3522, decode.d3.loss_dice: 0.5243, decode.d4.loss_cls: 0.0913, decode.d4.loss_mask: 0.3521, decode.d4.loss_dice: 0.5217, decode.d5.loss_cls: 0.0914, decode.d5.loss_mask: 0.3506, decode.d5.loss_dice: 0.5194, decode.d6.loss_cls: 0.0825, decode.d6.loss_mask: 0.3495, decode.d6.loss_dice: 0.5164, decode.d7.loss_cls: 0.0869, decode.d7.loss_mask: 0.3493, decode.d7.loss_dice: 0.5159, decode.d8.loss_cls: 0.0890, decode.d8.loss_mask: 0.3497, decode.d8.loss_dice: 0.5159, loss: 11.2598 +2022-05-06 09:10:43,251 - mmseg - INFO - Iter [38300/40000] lr: 6.106e-08, eta: 0:23:34, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0660, decode.loss_mask: 0.3506, decode.loss_dice: 0.5206, decode.d0.loss_cls: 1.4574, decode.d0.loss_mask: 0.3903, decode.d0.loss_dice: 0.6061, decode.d1.loss_cls: 0.1744, decode.d1.loss_mask: 0.3606, decode.d1.loss_dice: 0.5510, decode.d2.loss_cls: 0.1091, decode.d2.loss_mask: 0.3529, decode.d2.loss_dice: 0.5304, decode.d3.loss_cls: 0.0838, decode.d3.loss_mask: 0.3501, decode.d3.loss_dice: 0.5247, decode.d4.loss_cls: 0.0781, decode.d4.loss_mask: 0.3503, decode.d4.loss_dice: 0.5232, decode.d5.loss_cls: 0.0729, decode.d5.loss_mask: 0.3494, decode.d5.loss_dice: 0.5191, decode.d6.loss_cls: 0.0734, decode.d6.loss_mask: 0.3494, decode.d6.loss_dice: 0.5192, decode.d7.loss_cls: 0.0664, decode.d7.loss_mask: 0.3501, decode.d7.loss_dice: 0.5170, decode.d8.loss_cls: 0.0673, decode.d8.loss_mask: 0.3493, decode.d8.loss_dice: 0.5172, loss: 11.1306 +2022-05-06 09:11:19,224 - mmseg - INFO - Iter [38350/40000] lr: 5.926e-08, eta: 0:22:52, time: 0.719, data_time: 0.057, memory: 53770, decode.loss_cls: 0.0799, decode.loss_mask: 0.3632, decode.loss_dice: 0.5074, decode.d0.loss_cls: 1.3836, decode.d0.loss_mask: 0.4083, decode.d0.loss_dice: 0.5969, decode.d1.loss_cls: 0.1800, decode.d1.loss_mask: 0.3812, decode.d1.loss_dice: 0.5395, decode.d2.loss_cls: 0.1161, decode.d2.loss_mask: 0.3733, decode.d2.loss_dice: 0.5229, decode.d3.loss_cls: 0.0987, decode.d3.loss_mask: 0.3678, decode.d3.loss_dice: 0.5152, decode.d4.loss_cls: 0.0913, decode.d4.loss_mask: 0.3677, decode.d4.loss_dice: 0.5146, decode.d5.loss_cls: 0.0916, decode.d5.loss_mask: 0.3649, decode.d5.loss_dice: 0.5107, decode.d6.loss_cls: 0.0825, decode.d6.loss_mask: 0.3631, decode.d6.loss_dice: 0.5096, decode.d7.loss_cls: 0.0832, decode.d7.loss_mask: 0.3624, decode.d7.loss_dice: 0.5053, decode.d8.loss_cls: 0.0778, decode.d8.loss_mask: 0.3631, decode.d8.loss_dice: 0.5092, loss: 11.2312 +2022-05-06 09:11:52,575 - mmseg - INFO - Iter [38400/40000] lr: 5.747e-08, eta: 0:22:10, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0761, decode.loss_mask: 0.3552, decode.loss_dice: 0.4995, decode.d0.loss_cls: 1.4551, decode.d0.loss_mask: 0.3976, decode.d0.loss_dice: 0.5974, decode.d1.loss_cls: 0.1705, decode.d1.loss_mask: 0.3688, decode.d1.loss_dice: 0.5367, decode.d2.loss_cls: 0.1102, decode.d2.loss_mask: 0.3614, decode.d2.loss_dice: 0.5185, decode.d3.loss_cls: 0.0886, decode.d3.loss_mask: 0.3574, decode.d3.loss_dice: 0.5094, decode.d4.loss_cls: 0.0849, decode.d4.loss_mask: 0.3566, decode.d4.loss_dice: 0.5071, decode.d5.loss_cls: 0.0769, decode.d5.loss_mask: 0.3559, decode.d5.loss_dice: 0.5042, decode.d6.loss_cls: 0.0777, decode.d6.loss_mask: 0.3554, decode.d6.loss_dice: 0.5020, decode.d7.loss_cls: 0.0770, decode.d7.loss_mask: 0.3540, decode.d7.loss_dice: 0.4987, decode.d8.loss_cls: 0.0761, decode.d8.loss_mask: 0.3537, decode.d8.loss_dice: 0.5037, loss: 11.0865 +2022-05-06 09:12:26,591 - mmseg - INFO - Iter [38450/40000] lr: 5.567e-08, eta: 0:21:28, time: 0.680, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0788, decode.loss_mask: 0.3768, decode.loss_dice: 0.5078, decode.d0.loss_cls: 1.4481, decode.d0.loss_mask: 0.4211, decode.d0.loss_dice: 0.5975, decode.d1.loss_cls: 0.1754, decode.d1.loss_mask: 0.3884, decode.d1.loss_dice: 0.5435, decode.d2.loss_cls: 0.1117, decode.d2.loss_mask: 0.3823, decode.d2.loss_dice: 0.5259, decode.d3.loss_cls: 0.0910, decode.d3.loss_mask: 0.3792, decode.d3.loss_dice: 0.5135, decode.d4.loss_cls: 0.0867, decode.d4.loss_mask: 0.3771, decode.d4.loss_dice: 0.5139, decode.d5.loss_cls: 0.0857, decode.d5.loss_mask: 0.3761, decode.d5.loss_dice: 0.5118, decode.d6.loss_cls: 0.0776, decode.d6.loss_mask: 0.3770, decode.d6.loss_dice: 0.5088, decode.d7.loss_cls: 0.0719, decode.d7.loss_mask: 0.3780, decode.d7.loss_dice: 0.5102, decode.d8.loss_cls: 0.0783, decode.d8.loss_mask: 0.3782, decode.d8.loss_dice: 0.5098, loss: 11.3820 +2022-05-06 09:13:00,377 - mmseg - INFO - Iter [38500/40000] lr: 5.388e-08, eta: 0:20:46, time: 0.676, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0770, decode.loss_mask: 0.3548, decode.loss_dice: 0.5000, decode.d0.loss_cls: 1.4282, decode.d0.loss_mask: 0.3954, decode.d0.loss_dice: 0.5859, decode.d1.loss_cls: 0.1758, decode.d1.loss_mask: 0.3665, decode.d1.loss_dice: 0.5304, decode.d2.loss_cls: 0.1129, decode.d2.loss_mask: 0.3601, decode.d2.loss_dice: 0.5102, decode.d3.loss_cls: 0.0925, decode.d3.loss_mask: 0.3572, decode.d3.loss_dice: 0.4984, decode.d4.loss_cls: 0.0843, decode.d4.loss_mask: 0.3576, decode.d4.loss_dice: 0.5014, decode.d5.loss_cls: 0.0843, decode.d5.loss_mask: 0.3569, decode.d5.loss_dice: 0.5023, decode.d6.loss_cls: 0.0736, decode.d6.loss_mask: 0.3551, decode.d6.loss_dice: 0.4987, decode.d7.loss_cls: 0.0759, decode.d7.loss_mask: 0.3543, decode.d7.loss_dice: 0.4956, decode.d8.loss_cls: 0.0728, decode.d8.loss_mask: 0.3549, decode.d8.loss_dice: 0.5024, loss: 11.0153 +2022-05-06 09:13:33,965 - mmseg - INFO - Iter [38550/40000] lr: 5.208e-08, eta: 0:20:04, time: 0.671, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0891, decode.loss_mask: 0.3796, decode.loss_dice: 0.5266, decode.d0.loss_cls: 1.4488, decode.d0.loss_mask: 0.4270, decode.d0.loss_dice: 0.6244, decode.d1.loss_cls: 0.1870, decode.d1.loss_mask: 0.3980, decode.d1.loss_dice: 0.5688, decode.d2.loss_cls: 0.1208, decode.d2.loss_mask: 0.3893, decode.d2.loss_dice: 0.5455, decode.d3.loss_cls: 0.1053, decode.d3.loss_mask: 0.3851, decode.d3.loss_dice: 0.5341, decode.d4.loss_cls: 0.1016, decode.d4.loss_mask: 0.3846, decode.d4.loss_dice: 0.5386, decode.d5.loss_cls: 0.0948, decode.d5.loss_mask: 0.3823, decode.d5.loss_dice: 0.5282, decode.d6.loss_cls: 0.0996, decode.d6.loss_mask: 0.3813, decode.d6.loss_dice: 0.5276, decode.d7.loss_cls: 0.0872, decode.d7.loss_mask: 0.3805, decode.d7.loss_dice: 0.5277, decode.d8.loss_cls: 0.0933, decode.d8.loss_mask: 0.3784, decode.d8.loss_dice: 0.5266, loss: 11.7616 +2022-05-06 09:14:07,194 - mmseg - INFO - Iter [38600/40000] lr: 5.029e-08, eta: 0:19:22, time: 0.665, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0687, decode.loss_mask: 0.3590, decode.loss_dice: 0.4970, decode.d0.loss_cls: 1.4330, decode.d0.loss_mask: 0.4017, decode.d0.loss_dice: 0.5925, decode.d1.loss_cls: 0.1635, decode.d1.loss_mask: 0.3730, decode.d1.loss_dice: 0.5280, decode.d2.loss_cls: 0.1049, decode.d2.loss_mask: 0.3656, decode.d2.loss_dice: 0.5147, decode.d3.loss_cls: 0.0866, decode.d3.loss_mask: 0.3630, decode.d3.loss_dice: 0.5020, decode.d4.loss_cls: 0.0831, decode.d4.loss_mask: 0.3611, decode.d4.loss_dice: 0.4997, decode.d5.loss_cls: 0.0746, decode.d5.loss_mask: 0.3589, decode.d5.loss_dice: 0.4995, decode.d6.loss_cls: 0.0719, decode.d6.loss_mask: 0.3577, decode.d6.loss_dice: 0.4958, decode.d7.loss_cls: 0.0683, decode.d7.loss_mask: 0.3582, decode.d7.loss_dice: 0.4967, decode.d8.loss_cls: 0.0730, decode.d8.loss_mask: 0.3581, decode.d8.loss_dice: 0.4940, loss: 11.0036 +2022-05-06 09:14:43,424 - mmseg - INFO - Iter [38650/40000] lr: 4.849e-08, eta: 0:18:41, time: 0.725, data_time: 0.062, memory: 53770, decode.loss_cls: 0.0785, decode.loss_mask: 0.3600, decode.loss_dice: 0.5175, decode.d0.loss_cls: 1.4639, decode.d0.loss_mask: 0.4028, decode.d0.loss_dice: 0.6091, decode.d1.loss_cls: 0.1753, decode.d1.loss_mask: 0.3729, decode.d1.loss_dice: 0.5473, decode.d2.loss_cls: 0.1179, decode.d2.loss_mask: 0.3659, decode.d2.loss_dice: 0.5332, decode.d3.loss_cls: 0.0859, decode.d3.loss_mask: 0.3639, decode.d3.loss_dice: 0.5253, decode.d4.loss_cls: 0.0797, decode.d4.loss_mask: 0.3631, decode.d4.loss_dice: 0.5228, decode.d5.loss_cls: 0.0834, decode.d5.loss_mask: 0.3623, decode.d5.loss_dice: 0.5222, decode.d6.loss_cls: 0.0824, decode.d6.loss_mask: 0.3613, decode.d6.loss_dice: 0.5169, decode.d7.loss_cls: 0.0802, decode.d7.loss_mask: 0.3619, decode.d7.loss_dice: 0.5190, decode.d8.loss_cls: 0.0768, decode.d8.loss_mask: 0.3608, decode.d8.loss_dice: 0.5178, loss: 11.3299 +2022-05-06 09:15:17,376 - mmseg - INFO - Iter [38700/40000] lr: 4.670e-08, eta: 0:17:59, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0839, decode.loss_mask: 0.3709, decode.loss_dice: 0.5195, decode.d0.loss_cls: 1.4397, decode.d0.loss_mask: 0.4099, decode.d0.loss_dice: 0.6124, decode.d1.loss_cls: 0.1934, decode.d1.loss_mask: 0.3810, decode.d1.loss_dice: 0.5491, decode.d2.loss_cls: 0.1245, decode.d2.loss_mask: 0.3745, decode.d2.loss_dice: 0.5329, decode.d3.loss_cls: 0.0965, decode.d3.loss_mask: 0.3732, decode.d3.loss_dice: 0.5264, decode.d4.loss_cls: 0.1000, decode.d4.loss_mask: 0.3721, decode.d4.loss_dice: 0.5199, decode.d5.loss_cls: 0.0924, decode.d5.loss_mask: 0.3714, decode.d5.loss_dice: 0.5207, decode.d6.loss_cls: 0.0863, decode.d6.loss_mask: 0.3700, decode.d6.loss_dice: 0.5179, decode.d7.loss_cls: 0.0841, decode.d7.loss_mask: 0.3707, decode.d7.loss_dice: 0.5195, decode.d8.loss_cls: 0.0824, decode.d8.loss_mask: 0.3709, decode.d8.loss_dice: 0.5203, loss: 11.4864 +2022-05-06 09:15:50,613 - mmseg - INFO - Iter [38750/40000] lr: 4.490e-08, eta: 0:17:17, time: 0.665, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0671, decode.loss_mask: 0.3666, decode.loss_dice: 0.4898, decode.d0.loss_cls: 1.4243, decode.d0.loss_mask: 0.4054, decode.d0.loss_dice: 0.5781, decode.d1.loss_cls: 0.1791, decode.d1.loss_mask: 0.3800, decode.d1.loss_dice: 0.5260, decode.d2.loss_cls: 0.1186, decode.d2.loss_mask: 0.3733, decode.d2.loss_dice: 0.5039, decode.d3.loss_cls: 0.0838, decode.d3.loss_mask: 0.3710, decode.d3.loss_dice: 0.5025, decode.d4.loss_cls: 0.0802, decode.d4.loss_mask: 0.3680, decode.d4.loss_dice: 0.4939, decode.d5.loss_cls: 0.0729, decode.d5.loss_mask: 0.3686, decode.d5.loss_dice: 0.4957, decode.d6.loss_cls: 0.0664, decode.d6.loss_mask: 0.3671, decode.d6.loss_dice: 0.4923, decode.d7.loss_cls: 0.0664, decode.d7.loss_mask: 0.3674, decode.d7.loss_dice: 0.4916, decode.d8.loss_cls: 0.0688, decode.d8.loss_mask: 0.3663, decode.d8.loss_dice: 0.4938, loss: 11.0290 +2022-05-06 09:16:24,582 - mmseg - INFO - Iter [38800/40000] lr: 4.311e-08, eta: 0:16:35, time: 0.679, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0767, decode.loss_mask: 0.3583, decode.loss_dice: 0.4910, decode.d0.loss_cls: 1.4128, decode.d0.loss_mask: 0.4005, decode.d0.loss_dice: 0.5803, decode.d1.loss_cls: 0.1701, decode.d1.loss_mask: 0.3740, decode.d1.loss_dice: 0.5285, decode.d2.loss_cls: 0.1135, decode.d2.loss_mask: 0.3666, decode.d2.loss_dice: 0.5084, decode.d3.loss_cls: 0.0962, decode.d3.loss_mask: 0.3601, decode.d3.loss_dice: 0.5012, decode.d4.loss_cls: 0.0817, decode.d4.loss_mask: 0.3610, decode.d4.loss_dice: 0.4998, decode.d5.loss_cls: 0.0832, decode.d5.loss_mask: 0.3592, decode.d5.loss_dice: 0.4989, decode.d6.loss_cls: 0.0767, decode.d6.loss_mask: 0.3594, decode.d6.loss_dice: 0.4954, decode.d7.loss_cls: 0.0734, decode.d7.loss_mask: 0.3582, decode.d7.loss_dice: 0.4933, decode.d8.loss_cls: 0.0735, decode.d8.loss_mask: 0.3590, decode.d8.loss_dice: 0.4932, loss: 11.0043 +2022-05-06 09:16:58,256 - mmseg - INFO - Iter [38850/40000] lr: 4.132e-08, eta: 0:15:53, time: 0.674, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0824, decode.loss_mask: 0.3490, decode.loss_dice: 0.5045, decode.d0.loss_cls: 1.4357, decode.d0.loss_mask: 0.3895, decode.d0.loss_dice: 0.5835, decode.d1.loss_cls: 0.1683, decode.d1.loss_mask: 0.3627, decode.d1.loss_dice: 0.5367, decode.d2.loss_cls: 0.1086, decode.d2.loss_mask: 0.3546, decode.d2.loss_dice: 0.5193, decode.d3.loss_cls: 0.0898, decode.d3.loss_mask: 0.3537, decode.d3.loss_dice: 0.5127, decode.d4.loss_cls: 0.0789, decode.d4.loss_mask: 0.3530, decode.d4.loss_dice: 0.5133, decode.d5.loss_cls: 0.0835, decode.d5.loss_mask: 0.3524, decode.d5.loss_dice: 0.5067, decode.d6.loss_cls: 0.0774, decode.d6.loss_mask: 0.3504, decode.d6.loss_dice: 0.5034, decode.d7.loss_cls: 0.0796, decode.d7.loss_mask: 0.3512, decode.d7.loss_dice: 0.5031, decode.d8.loss_cls: 0.0765, decode.d8.loss_mask: 0.3491, decode.d8.loss_dice: 0.5023, loss: 11.0319 +2022-05-06 09:17:31,661 - mmseg - INFO - Iter [38900/40000] lr: 3.952e-08, eta: 0:15:12, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0850, decode.loss_mask: 0.3727, decode.loss_dice: 0.5083, decode.d0.loss_cls: 1.4269, decode.d0.loss_mask: 0.4144, decode.d0.loss_dice: 0.5916, decode.d1.loss_cls: 0.1847, decode.d1.loss_mask: 0.3878, decode.d1.loss_dice: 0.5403, decode.d2.loss_cls: 0.1200, decode.d2.loss_mask: 0.3801, decode.d2.loss_dice: 0.5262, decode.d3.loss_cls: 0.1023, decode.d3.loss_mask: 0.3776, decode.d3.loss_dice: 0.5187, decode.d4.loss_cls: 0.0943, decode.d4.loss_mask: 0.3770, decode.d4.loss_dice: 0.5161, decode.d5.loss_cls: 0.0925, decode.d5.loss_mask: 0.3751, decode.d5.loss_dice: 0.5125, decode.d6.loss_cls: 0.0939, decode.d6.loss_mask: 0.3740, decode.d6.loss_dice: 0.5097, decode.d7.loss_cls: 0.0913, decode.d7.loss_mask: 0.3733, decode.d7.loss_dice: 0.5094, decode.d8.loss_cls: 0.0846, decode.d8.loss_mask: 0.3731, decode.d8.loss_dice: 0.5069, loss: 11.4203 +2022-05-06 09:18:07,596 - mmseg - INFO - Iter [38950/40000] lr: 3.773e-08, eta: 0:14:30, time: 0.719, data_time: 0.059, memory: 53770, decode.loss_cls: 0.0984, decode.loss_mask: 0.3553, decode.loss_dice: 0.5220, decode.d0.loss_cls: 1.4380, decode.d0.loss_mask: 0.3919, decode.d0.loss_dice: 0.6107, decode.d1.loss_cls: 0.1973, decode.d1.loss_mask: 0.3681, decode.d1.loss_dice: 0.5575, decode.d2.loss_cls: 0.1350, decode.d2.loss_mask: 0.3612, decode.d2.loss_dice: 0.5388, decode.d3.loss_cls: 0.1186, decode.d3.loss_mask: 0.3566, decode.d3.loss_dice: 0.5268, decode.d4.loss_cls: 0.1076, decode.d4.loss_mask: 0.3559, decode.d4.loss_dice: 0.5325, decode.d5.loss_cls: 0.1037, decode.d5.loss_mask: 0.3566, decode.d5.loss_dice: 0.5325, decode.d6.loss_cls: 0.1029, decode.d6.loss_mask: 0.3555, decode.d6.loss_dice: 0.5236, decode.d7.loss_cls: 0.1006, decode.d7.loss_mask: 0.3559, decode.d7.loss_dice: 0.5256, decode.d8.loss_cls: 0.0969, decode.d8.loss_mask: 0.3549, decode.d8.loss_dice: 0.5234, loss: 11.5044 +2022-05-06 09:18:41,249 - mmseg - INFO - Saving checkpoint at 39000 iterations +2022-05-06 09:19:08,015 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 09:19:08,023 - mmseg - INFO - Iter [39000/40000] lr: 3.593e-08, eta: 0:13:49, time: 1.206, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0879, decode.loss_mask: 0.3464, decode.loss_dice: 0.5001, decode.d0.loss_cls: 1.4526, decode.d0.loss_mask: 0.3899, decode.d0.loss_dice: 0.5934, decode.d1.loss_cls: 0.1819, decode.d1.loss_mask: 0.3610, decode.d1.loss_dice: 0.5399, decode.d2.loss_cls: 0.1216, decode.d2.loss_mask: 0.3546, decode.d2.loss_dice: 0.5160, decode.d3.loss_cls: 0.1059, decode.d3.loss_mask: 0.3510, decode.d3.loss_dice: 0.5083, decode.d4.loss_cls: 0.0974, decode.d4.loss_mask: 0.3495, decode.d4.loss_dice: 0.5071, decode.d5.loss_cls: 0.0972, decode.d5.loss_mask: 0.3485, decode.d5.loss_dice: 0.5025, decode.d6.loss_cls: 0.0917, decode.d6.loss_mask: 0.3469, decode.d6.loss_dice: 0.5012, decode.d7.loss_cls: 0.0883, decode.d7.loss_mask: 0.3470, decode.d7.loss_dice: 0.5022, decode.d8.loss_cls: 0.0900, decode.d8.loss_mask: 0.3458, decode.d8.loss_dice: 0.4998, loss: 11.1257 +2022-05-06 09:19:42,415 - mmseg - INFO - Iter [39050/40000] lr: 3.414e-08, eta: 0:13:07, time: 0.690, data_time: 0.011, memory: 53770, decode.loss_cls: 0.0648, decode.loss_mask: 0.3571, decode.loss_dice: 0.4949, decode.d0.loss_cls: 1.4413, decode.d0.loss_mask: 0.3922, decode.d0.loss_dice: 0.5787, decode.d1.loss_cls: 0.1719, decode.d1.loss_mask: 0.3668, decode.d1.loss_dice: 0.5268, decode.d2.loss_cls: 0.1034, decode.d2.loss_mask: 0.3608, decode.d2.loss_dice: 0.5113, decode.d3.loss_cls: 0.0803, decode.d3.loss_mask: 0.3589, decode.d3.loss_dice: 0.5060, decode.d4.loss_cls: 0.0785, decode.d4.loss_mask: 0.3575, decode.d4.loss_dice: 0.5004, decode.d5.loss_cls: 0.0685, decode.d5.loss_mask: 0.3590, decode.d5.loss_dice: 0.5003, decode.d6.loss_cls: 0.0638, decode.d6.loss_mask: 0.3570, decode.d6.loss_dice: 0.4984, decode.d7.loss_cls: 0.0643, decode.d7.loss_mask: 0.3568, decode.d7.loss_dice: 0.5006, decode.d8.loss_cls: 0.0641, decode.d8.loss_mask: 0.3572, decode.d8.loss_dice: 0.5001, loss: 10.9417 +2022-05-06 09:20:16,490 - mmseg - INFO - Iter [39100/40000] lr: 3.234e-08, eta: 0:12:26, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0755, decode.loss_mask: 0.3477, decode.loss_dice: 0.4983, decode.d0.loss_cls: 1.4534, decode.d0.loss_mask: 0.3851, decode.d0.loss_dice: 0.5935, decode.d1.loss_cls: 0.1943, decode.d1.loss_mask: 0.3593, decode.d1.loss_dice: 0.5342, decode.d2.loss_cls: 0.1105, decode.d2.loss_mask: 0.3511, decode.d2.loss_dice: 0.5143, decode.d3.loss_cls: 0.0958, decode.d3.loss_mask: 0.3493, decode.d3.loss_dice: 0.5030, decode.d4.loss_cls: 0.0889, decode.d4.loss_mask: 0.3474, decode.d4.loss_dice: 0.5035, decode.d5.loss_cls: 0.0813, decode.d5.loss_mask: 0.3480, decode.d5.loss_dice: 0.5052, decode.d6.loss_cls: 0.0856, decode.d6.loss_mask: 0.3468, decode.d6.loss_dice: 0.5031, decode.d7.loss_cls: 0.0786, decode.d7.loss_mask: 0.3474, decode.d7.loss_dice: 0.5022, decode.d8.loss_cls: 0.0772, decode.d8.loss_mask: 0.3457, decode.d8.loss_dice: 0.4990, loss: 11.0251 +2022-05-06 09:20:50,583 - mmseg - INFO - Iter [39150/40000] lr: 3.055e-08, eta: 0:11:44, time: 0.682, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0870, decode.loss_mask: 0.3677, decode.loss_dice: 0.5200, decode.d0.loss_cls: 1.4557, decode.d0.loss_mask: 0.4097, decode.d0.loss_dice: 0.6122, decode.d1.loss_cls: 0.1975, decode.d1.loss_mask: 0.3822, decode.d1.loss_dice: 0.5514, decode.d2.loss_cls: 0.1296, decode.d2.loss_mask: 0.3726, decode.d2.loss_dice: 0.5368, decode.d3.loss_cls: 0.1049, decode.d3.loss_mask: 0.3706, decode.d3.loss_dice: 0.5259, decode.d4.loss_cls: 0.0990, decode.d4.loss_mask: 0.3681, decode.d4.loss_dice: 0.5255, decode.d5.loss_cls: 0.0937, decode.d5.loss_mask: 0.3702, decode.d5.loss_dice: 0.5240, decode.d6.loss_cls: 0.0916, decode.d6.loss_mask: 0.3691, decode.d6.loss_dice: 0.5236, decode.d7.loss_cls: 0.0853, decode.d7.loss_mask: 0.3676, decode.d7.loss_dice: 0.5213, decode.d8.loss_cls: 0.0862, decode.d8.loss_mask: 0.3652, decode.d8.loss_dice: 0.5198, loss: 11.5341 +2022-05-06 09:21:23,882 - mmseg - INFO - Iter [39200/40000] lr: 2.875e-08, eta: 0:11:03, time: 0.666, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0839, decode.loss_mask: 0.3677, decode.loss_dice: 0.5258, decode.d0.loss_cls: 1.4420, decode.d0.loss_mask: 0.4091, decode.d0.loss_dice: 0.6110, decode.d1.loss_cls: 0.1739, decode.d1.loss_mask: 0.3826, decode.d1.loss_dice: 0.5592, decode.d2.loss_cls: 0.1189, decode.d2.loss_mask: 0.3749, decode.d2.loss_dice: 0.5425, decode.d3.loss_cls: 0.0945, decode.d3.loss_mask: 0.3710, decode.d3.loss_dice: 0.5317, decode.d4.loss_cls: 0.0867, decode.d4.loss_mask: 0.3710, decode.d4.loss_dice: 0.5330, decode.d5.loss_cls: 0.0818, decode.d5.loss_mask: 0.3711, decode.d5.loss_dice: 0.5339, decode.d6.loss_cls: 0.0789, decode.d6.loss_mask: 0.3704, decode.d6.loss_dice: 0.5295, decode.d7.loss_cls: 0.0795, decode.d7.loss_mask: 0.3688, decode.d7.loss_dice: 0.5294, decode.d8.loss_cls: 0.0838, decode.d8.loss_mask: 0.3690, decode.d8.loss_dice: 0.5262, loss: 11.5017 +2022-05-06 09:21:57,485 - mmseg - INFO - Iter [39250/40000] lr: 2.696e-08, eta: 0:10:21, time: 0.672, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0675, decode.loss_mask: 0.3650, decode.loss_dice: 0.5058, decode.d0.loss_cls: 1.3924, decode.d0.loss_mask: 0.4028, decode.d0.loss_dice: 0.5917, decode.d1.loss_cls: 0.1600, decode.d1.loss_mask: 0.3769, decode.d1.loss_dice: 0.5388, decode.d2.loss_cls: 0.1053, decode.d2.loss_mask: 0.3690, decode.d2.loss_dice: 0.5192, decode.d3.loss_cls: 0.0854, decode.d3.loss_mask: 0.3679, decode.d3.loss_dice: 0.5135, decode.d4.loss_cls: 0.0849, decode.d4.loss_mask: 0.3660, decode.d4.loss_dice: 0.5119, decode.d5.loss_cls: 0.0759, decode.d5.loss_mask: 0.3659, decode.d5.loss_dice: 0.5076, decode.d6.loss_cls: 0.0737, decode.d6.loss_mask: 0.3642, decode.d6.loss_dice: 0.5060, decode.d7.loss_cls: 0.0689, decode.d7.loss_mask: 0.3655, decode.d7.loss_dice: 0.5069, decode.d8.loss_cls: 0.0666, decode.d8.loss_mask: 0.3639, decode.d8.loss_dice: 0.5061, loss: 11.0949 +2022-05-06 09:22:33,739 - mmseg - INFO - Iter [39300/40000] lr: 2.516e-08, eta: 0:09:39, time: 0.724, data_time: 0.059, memory: 53770, decode.loss_cls: 0.0895, decode.loss_mask: 0.3531, decode.loss_dice: 0.5183, decode.d0.loss_cls: 1.4356, decode.d0.loss_mask: 0.3912, decode.d0.loss_dice: 0.6158, decode.d1.loss_cls: 0.1898, decode.d1.loss_mask: 0.3635, decode.d1.loss_dice: 0.5575, decode.d2.loss_cls: 0.1247, decode.d2.loss_mask: 0.3578, decode.d2.loss_dice: 0.5401, decode.d3.loss_cls: 0.1081, decode.d3.loss_mask: 0.3579, decode.d3.loss_dice: 0.5321, decode.d4.loss_cls: 0.0993, decode.d4.loss_mask: 0.3558, decode.d4.loss_dice: 0.5315, decode.d5.loss_cls: 0.0950, decode.d5.loss_mask: 0.3550, decode.d5.loss_dice: 0.5287, decode.d6.loss_cls: 0.0954, decode.d6.loss_mask: 0.3527, decode.d6.loss_dice: 0.5224, decode.d7.loss_cls: 0.0910, decode.d7.loss_mask: 0.3533, decode.d7.loss_dice: 0.5266, decode.d8.loss_cls: 0.0896, decode.d8.loss_mask: 0.3521, decode.d8.loss_dice: 0.5253, loss: 11.4090 +2022-05-06 09:23:07,743 - mmseg - INFO - Iter [39350/40000] lr: 2.337e-08, eta: 0:08:58, time: 0.681, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0742, decode.loss_mask: 0.3612, decode.loss_dice: 0.5036, decode.d0.loss_cls: 1.4509, decode.d0.loss_mask: 0.4056, decode.d0.loss_dice: 0.5993, decode.d1.loss_cls: 0.1817, decode.d1.loss_mask: 0.3758, decode.d1.loss_dice: 0.5354, decode.d2.loss_cls: 0.1210, decode.d2.loss_mask: 0.3662, decode.d2.loss_dice: 0.5152, decode.d3.loss_cls: 0.0950, decode.d3.loss_mask: 0.3641, decode.d3.loss_dice: 0.5103, decode.d4.loss_cls: 0.0857, decode.d4.loss_mask: 0.3643, decode.d4.loss_dice: 0.5094, decode.d5.loss_cls: 0.0865, decode.d5.loss_mask: 0.3631, decode.d5.loss_dice: 0.5035, decode.d6.loss_cls: 0.0792, decode.d6.loss_mask: 0.3617, decode.d6.loss_dice: 0.4999, decode.d7.loss_cls: 0.0765, decode.d7.loss_mask: 0.3606, decode.d7.loss_dice: 0.5024, decode.d8.loss_cls: 0.0728, decode.d8.loss_mask: 0.3620, decode.d8.loss_dice: 0.5027, loss: 11.1897 +2022-05-06 09:23:41,086 - mmseg - INFO - Iter [39400/40000] lr: 2.157e-08, eta: 0:08:16, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0608, decode.loss_mask: 0.3721, decode.loss_dice: 0.5174, decode.d0.loss_cls: 1.4294, decode.d0.loss_mask: 0.4090, decode.d0.loss_dice: 0.5990, decode.d1.loss_cls: 0.1655, decode.d1.loss_mask: 0.3836, decode.d1.loss_dice: 0.5432, decode.d2.loss_cls: 0.1035, decode.d2.loss_mask: 0.3785, decode.d2.loss_dice: 0.5324, decode.d3.loss_cls: 0.0764, decode.d3.loss_mask: 0.3765, decode.d3.loss_dice: 0.5235, decode.d4.loss_cls: 0.0732, decode.d4.loss_mask: 0.3747, decode.d4.loss_dice: 0.5208, decode.d5.loss_cls: 0.0700, decode.d5.loss_mask: 0.3733, decode.d5.loss_dice: 0.5131, decode.d6.loss_cls: 0.0694, decode.d6.loss_mask: 0.3714, decode.d6.loss_dice: 0.5152, decode.d7.loss_cls: 0.0639, decode.d7.loss_mask: 0.3721, decode.d7.loss_dice: 0.5143, decode.d8.loss_cls: 0.0635, decode.d8.loss_mask: 0.3720, decode.d8.loss_dice: 0.5158, loss: 11.2534 +2022-05-06 09:24:14,980 - mmseg - INFO - Iter [39450/40000] lr: 1.978e-08, eta: 0:07:35, time: 0.677, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0818, decode.loss_mask: 0.3592, decode.loss_dice: 0.5165, decode.d0.loss_cls: 1.4236, decode.d0.loss_mask: 0.4005, decode.d0.loss_dice: 0.6089, decode.d1.loss_cls: 0.1672, decode.d1.loss_mask: 0.3736, decode.d1.loss_dice: 0.5514, decode.d2.loss_cls: 0.1136, decode.d2.loss_mask: 0.3650, decode.d2.loss_dice: 0.5286, decode.d3.loss_cls: 0.0919, decode.d3.loss_mask: 0.3628, decode.d3.loss_dice: 0.5220, decode.d4.loss_cls: 0.0881, decode.d4.loss_mask: 0.3606, decode.d4.loss_dice: 0.5177, decode.d5.loss_cls: 0.0832, decode.d5.loss_mask: 0.3611, decode.d5.loss_dice: 0.5161, decode.d6.loss_cls: 0.0791, decode.d6.loss_mask: 0.3598, decode.d6.loss_dice: 0.5159, decode.d7.loss_cls: 0.0819, decode.d7.loss_mask: 0.3587, decode.d7.loss_dice: 0.5157, decode.d8.loss_cls: 0.0759, decode.d8.loss_mask: 0.3586, decode.d8.loss_dice: 0.5153, loss: 11.2543 +2022-05-06 09:24:49,706 - mmseg - INFO - Iter [39500/40000] lr: 1.798e-08, eta: 0:06:53, time: 0.695, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0623, decode.loss_mask: 0.3564, decode.loss_dice: 0.4997, decode.d0.loss_cls: 1.4002, decode.d0.loss_mask: 0.3970, decode.d0.loss_dice: 0.5782, decode.d1.loss_cls: 0.1592, decode.d1.loss_mask: 0.3665, decode.d1.loss_dice: 0.5262, decode.d2.loss_cls: 0.1044, decode.d2.loss_mask: 0.3607, decode.d2.loss_dice: 0.5098, decode.d3.loss_cls: 0.0798, decode.d3.loss_mask: 0.3585, decode.d3.loss_dice: 0.5061, decode.d4.loss_cls: 0.0765, decode.d4.loss_mask: 0.3572, decode.d4.loss_dice: 0.5000, decode.d5.loss_cls: 0.0710, decode.d5.loss_mask: 0.3558, decode.d5.loss_dice: 0.4993, decode.d6.loss_cls: 0.0663, decode.d6.loss_mask: 0.3567, decode.d6.loss_dice: 0.4990, decode.d7.loss_cls: 0.0651, decode.d7.loss_mask: 0.3562, decode.d7.loss_dice: 0.4995, decode.d8.loss_cls: 0.0661, decode.d8.loss_mask: 0.3548, decode.d8.loss_dice: 0.4968, loss: 10.8853 +2022-05-06 09:25:23,541 - mmseg - INFO - Iter [39550/40000] lr: 1.619e-08, eta: 0:06:12, time: 0.677, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0690, decode.loss_mask: 0.3573, decode.loss_dice: 0.4909, decode.d0.loss_cls: 1.4442, decode.d0.loss_mask: 0.3972, decode.d0.loss_dice: 0.5720, decode.d1.loss_cls: 0.1787, decode.d1.loss_mask: 0.3717, decode.d1.loss_dice: 0.5242, decode.d2.loss_cls: 0.1126, decode.d2.loss_mask: 0.3641, decode.d2.loss_dice: 0.5039, decode.d3.loss_cls: 0.0872, decode.d3.loss_mask: 0.3626, decode.d3.loss_dice: 0.5011, decode.d4.loss_cls: 0.0802, decode.d4.loss_mask: 0.3599, decode.d4.loss_dice: 0.4966, decode.d5.loss_cls: 0.0776, decode.d5.loss_mask: 0.3581, decode.d5.loss_dice: 0.4928, decode.d6.loss_cls: 0.0754, decode.d6.loss_mask: 0.3578, decode.d6.loss_dice: 0.4909, decode.d7.loss_cls: 0.0750, decode.d7.loss_mask: 0.3566, decode.d7.loss_dice: 0.4906, decode.d8.loss_cls: 0.0714, decode.d8.loss_mask: 0.3576, decode.d8.loss_dice: 0.4916, loss: 10.9689 +2022-05-06 09:25:59,698 - mmseg - INFO - Iter [39600/40000] lr: 1.439e-08, eta: 0:05:30, time: 0.723, data_time: 0.059, memory: 53770, decode.loss_cls: 0.0620, decode.loss_mask: 0.3655, decode.loss_dice: 0.4789, decode.d0.loss_cls: 1.3871, decode.d0.loss_mask: 0.4096, decode.d0.loss_dice: 0.5660, decode.d1.loss_cls: 0.1484, decode.d1.loss_mask: 0.3805, decode.d1.loss_dice: 0.5137, decode.d2.loss_cls: 0.0926, decode.d2.loss_mask: 0.3735, decode.d2.loss_dice: 0.4964, decode.d3.loss_cls: 0.0743, decode.d3.loss_mask: 0.3706, decode.d3.loss_dice: 0.4860, decode.d4.loss_cls: 0.0723, decode.d4.loss_mask: 0.3704, decode.d4.loss_dice: 0.4861, decode.d5.loss_cls: 0.0707, decode.d5.loss_mask: 0.3690, decode.d5.loss_dice: 0.4825, decode.d6.loss_cls: 0.0644, decode.d6.loss_mask: 0.3672, decode.d6.loss_dice: 0.4807, decode.d7.loss_cls: 0.0611, decode.d7.loss_mask: 0.3665, decode.d7.loss_dice: 0.4824, decode.d8.loss_cls: 0.0597, decode.d8.loss_mask: 0.3658, decode.d8.loss_dice: 0.4810, loss: 10.7849 +2022-05-06 09:26:33,037 - mmseg - INFO - Iter [39650/40000] lr: 1.260e-08, eta: 0:04:49, time: 0.667, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0772, decode.loss_mask: 0.3526, decode.loss_dice: 0.5070, decode.d0.loss_cls: 1.4481, decode.d0.loss_mask: 0.3912, decode.d0.loss_dice: 0.6001, decode.d1.loss_cls: 0.1769, decode.d1.loss_mask: 0.3658, decode.d1.loss_dice: 0.5441, decode.d2.loss_cls: 0.1090, decode.d2.loss_mask: 0.3594, decode.d2.loss_dice: 0.5268, decode.d3.loss_cls: 0.0930, decode.d3.loss_mask: 0.3575, decode.d3.loss_dice: 0.5210, decode.d4.loss_cls: 0.0840, decode.d4.loss_mask: 0.3573, decode.d4.loss_dice: 0.5183, decode.d5.loss_cls: 0.0839, decode.d5.loss_mask: 0.3553, decode.d5.loss_dice: 0.5124, decode.d6.loss_cls: 0.0747, decode.d6.loss_mask: 0.3555, decode.d6.loss_dice: 0.5109, decode.d7.loss_cls: 0.0790, decode.d7.loss_mask: 0.3550, decode.d7.loss_dice: 0.5124, decode.d8.loss_cls: 0.0764, decode.d8.loss_mask: 0.3529, decode.d8.loss_dice: 0.5090, loss: 11.1667 +2022-05-06 09:27:06,519 - mmseg - INFO - Iter [39700/40000] lr: 1.080e-08, eta: 0:04:08, time: 0.670, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0842, decode.loss_mask: 0.3632, decode.loss_dice: 0.5185, decode.d0.loss_cls: 1.4350, decode.d0.loss_mask: 0.4039, decode.d0.loss_dice: 0.6071, decode.d1.loss_cls: 0.1758, decode.d1.loss_mask: 0.3772, decode.d1.loss_dice: 0.5509, decode.d2.loss_cls: 0.1128, decode.d2.loss_mask: 0.3715, decode.d2.loss_dice: 0.5346, decode.d3.loss_cls: 0.0915, decode.d3.loss_mask: 0.3670, decode.d3.loss_dice: 0.5206, decode.d4.loss_cls: 0.0911, decode.d4.loss_mask: 0.3660, decode.d4.loss_dice: 0.5202, decode.d5.loss_cls: 0.0887, decode.d5.loss_mask: 0.3647, decode.d5.loss_dice: 0.5173, decode.d6.loss_cls: 0.0801, decode.d6.loss_mask: 0.3648, decode.d6.loss_dice: 0.5168, decode.d7.loss_cls: 0.0771, decode.d7.loss_mask: 0.3654, decode.d7.loss_dice: 0.5172, decode.d8.loss_cls: 0.0859, decode.d8.loss_mask: 0.3640, decode.d8.loss_dice: 0.5158, loss: 11.3487 +2022-05-06 09:27:39,891 - mmseg - INFO - Iter [39750/40000] lr: 9.010e-09, eta: 0:03:26, time: 0.668, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0720, decode.loss_mask: 0.3591, decode.loss_dice: 0.4936, decode.d0.loss_cls: 1.4046, decode.d0.loss_mask: 0.3991, decode.d0.loss_dice: 0.5817, decode.d1.loss_cls: 0.1757, decode.d1.loss_mask: 0.3701, decode.d1.loss_dice: 0.5264, decode.d2.loss_cls: 0.1143, decode.d2.loss_mask: 0.3677, decode.d2.loss_dice: 0.5080, decode.d3.loss_cls: 0.0907, decode.d3.loss_mask: 0.3629, decode.d3.loss_dice: 0.4976, decode.d4.loss_cls: 0.0783, decode.d4.loss_mask: 0.3612, decode.d4.loss_dice: 0.4965, decode.d5.loss_cls: 0.0785, decode.d5.loss_mask: 0.3633, decode.d5.loss_dice: 0.5015, decode.d6.loss_cls: 0.0732, decode.d6.loss_mask: 0.3607, decode.d6.loss_dice: 0.4958, decode.d7.loss_cls: 0.0742, decode.d7.loss_mask: 0.3599, decode.d7.loss_dice: 0.4921, decode.d8.loss_cls: 0.0731, decode.d8.loss_mask: 0.3582, decode.d8.loss_dice: 0.4874, loss: 10.9773 +2022-05-06 09:28:14,111 - mmseg - INFO - Iter [39800/40000] lr: 7.215e-09, eta: 0:02:45, time: 0.684, data_time: 0.008, memory: 53770, decode.loss_cls: 0.0830, decode.loss_mask: 0.3607, decode.loss_dice: 0.4842, decode.d0.loss_cls: 1.4438, decode.d0.loss_mask: 0.4052, decode.d0.loss_dice: 0.5730, decode.d1.loss_cls: 0.1834, decode.d1.loss_mask: 0.3742, decode.d1.loss_dice: 0.5141, decode.d2.loss_cls: 0.1213, decode.d2.loss_mask: 0.3672, decode.d2.loss_dice: 0.5033, decode.d3.loss_cls: 0.1015, decode.d3.loss_mask: 0.3647, decode.d3.loss_dice: 0.4927, decode.d4.loss_cls: 0.0903, decode.d4.loss_mask: 0.3634, decode.d4.loss_dice: 0.4914, decode.d5.loss_cls: 0.0861, decode.d5.loss_mask: 0.3627, decode.d5.loss_dice: 0.4864, decode.d6.loss_cls: 0.0849, decode.d6.loss_mask: 0.3634, decode.d6.loss_dice: 0.4857, decode.d7.loss_cls: 0.0805, decode.d7.loss_mask: 0.3613, decode.d7.loss_dice: 0.4858, decode.d8.loss_cls: 0.0799, decode.d8.loss_mask: 0.3626, decode.d8.loss_dice: 0.4861, loss: 11.0428 +2022-05-06 09:28:47,848 - mmseg - INFO - Iter [39850/40000] lr: 5.420e-09, eta: 0:02:03, time: 0.675, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0650, decode.loss_mask: 0.3569, decode.loss_dice: 0.5154, decode.d0.loss_cls: 1.4609, decode.d0.loss_mask: 0.3991, decode.d0.loss_dice: 0.5972, decode.d1.loss_cls: 0.1756, decode.d1.loss_mask: 0.3707, decode.d1.loss_dice: 0.5445, decode.d2.loss_cls: 0.1106, decode.d2.loss_mask: 0.3632, decode.d2.loss_dice: 0.5276, decode.d3.loss_cls: 0.0817, decode.d3.loss_mask: 0.3609, decode.d3.loss_dice: 0.5194, decode.d4.loss_cls: 0.0781, decode.d4.loss_mask: 0.3596, decode.d4.loss_dice: 0.5170, decode.d5.loss_cls: 0.0686, decode.d5.loss_mask: 0.3598, decode.d5.loss_dice: 0.5154, decode.d6.loss_cls: 0.0635, decode.d6.loss_mask: 0.3571, decode.d6.loss_dice: 0.5142, decode.d7.loss_cls: 0.0634, decode.d7.loss_mask: 0.3567, decode.d7.loss_dice: 0.5139, decode.d8.loss_cls: 0.0608, decode.d8.loss_mask: 0.3564, decode.d8.loss_dice: 0.5127, loss: 11.1457 +2022-05-06 09:29:24,393 - mmseg - INFO - Iter [39900/40000] lr: 3.625e-09, eta: 0:01:22, time: 0.731, data_time: 0.060, memory: 53770, decode.loss_cls: 0.0916, decode.loss_mask: 0.3628, decode.loss_dice: 0.5301, decode.d0.loss_cls: 1.4611, decode.d0.loss_mask: 0.4035, decode.d0.loss_dice: 0.6303, decode.d1.loss_cls: 0.1892, decode.d1.loss_mask: 0.3760, decode.d1.loss_dice: 0.5652, decode.d2.loss_cls: 0.1274, decode.d2.loss_mask: 0.3672, decode.d2.loss_dice: 0.5455, decode.d3.loss_cls: 0.1038, decode.d3.loss_mask: 0.3655, decode.d3.loss_dice: 0.5352, decode.d4.loss_cls: 0.0975, decode.d4.loss_mask: 0.3656, decode.d4.loss_dice: 0.5363, decode.d5.loss_cls: 0.0923, decode.d5.loss_mask: 0.3629, decode.d5.loss_dice: 0.5333, decode.d6.loss_cls: 0.0895, decode.d6.loss_mask: 0.3643, decode.d6.loss_dice: 0.5337, decode.d7.loss_cls: 0.0893, decode.d7.loss_mask: 0.3642, decode.d7.loss_dice: 0.5362, decode.d8.loss_cls: 0.0927, decode.d8.loss_mask: 0.3627, decode.d8.loss_dice: 0.5299, loss: 11.6051 +2022-05-06 09:29:58,286 - mmseg - INFO - Iter [39950/40000] lr: 1.831e-09, eta: 0:00:41, time: 0.678, data_time: 0.010, memory: 53770, decode.loss_cls: 0.0650, decode.loss_mask: 0.3518, decode.loss_dice: 0.5112, decode.d0.loss_cls: 1.4197, decode.d0.loss_mask: 0.3935, decode.d0.loss_dice: 0.5985, decode.d1.loss_cls: 0.1672, decode.d1.loss_mask: 0.3647, decode.d1.loss_dice: 0.5451, decode.d2.loss_cls: 0.1060, decode.d2.loss_mask: 0.3573, decode.d2.loss_dice: 0.5263, decode.d3.loss_cls: 0.0930, decode.d3.loss_mask: 0.3549, decode.d3.loss_dice: 0.5171, decode.d4.loss_cls: 0.0783, decode.d4.loss_mask: 0.3538, decode.d4.loss_dice: 0.5187, decode.d5.loss_cls: 0.0756, decode.d5.loss_mask: 0.3537, decode.d5.loss_dice: 0.5154, decode.d6.loss_cls: 0.0706, decode.d6.loss_mask: 0.3537, decode.d6.loss_dice: 0.5151, decode.d7.loss_cls: 0.0674, decode.d7.loss_mask: 0.3515, decode.d7.loss_dice: 0.5109, decode.d8.loss_cls: 0.0675, decode.d8.loss_mask: 0.3513, decode.d8.loss_dice: 0.5105, loss: 11.0655 +2022-05-06 09:30:32,064 - mmseg - INFO - Saving checkpoint at 40000 iterations +2022-05-06 09:30:58,982 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 09:30:59,010 - mmseg - INFO - Iter [40000/40000] lr: 3.589e-11, eta: 0:00:00, time: 1.212, data_time: 0.009, memory: 53770, decode.loss_cls: 0.0667, decode.loss_mask: 0.3440, decode.loss_dice: 0.4828, decode.d0.loss_cls: 1.4537, decode.d0.loss_mask: 0.3870, decode.d0.loss_dice: 0.5800, decode.d1.loss_cls: 0.1767, decode.d1.loss_mask: 0.3580, decode.d1.loss_dice: 0.5150, decode.d2.loss_cls: 0.1187, decode.d2.loss_mask: 0.3492, decode.d2.loss_dice: 0.4967, decode.d3.loss_cls: 0.0924, decode.d3.loss_mask: 0.3462, decode.d3.loss_dice: 0.4905, decode.d4.loss_cls: 0.0875, decode.d4.loss_mask: 0.3443, decode.d4.loss_dice: 0.4859, decode.d5.loss_cls: 0.0761, decode.d5.loss_mask: 0.3445, decode.d5.loss_dice: 0.4839, decode.d6.loss_cls: 0.0755, decode.d6.loss_mask: 0.3426, decode.d6.loss_dice: 0.4844, decode.d7.loss_cls: 0.0704, decode.d7.loss_mask: 0.3438, decode.d7.loss_dice: 0.4856, decode.d8.loss_cls: 0.0734, decode.d8.loss_mask: 0.3441, decode.d8.loss_dice: 0.4852, loss: 10.7847 +2022-05-06 09:35:19,917 - mmseg - INFO - per class results: +2022-05-06 09:35:19,937 - mmseg - INFO - ++-------------+-------+-------+ +| Class | IoU | Acc | ++-------------+-------+-------+ +| aeroplane | 92.43 | 95.77 | +| bag | 50.76 | 68.35 | +| bed | 35.9 | 44.24 | +| bedclothes | 46.25 | 71.05 | +| bench | 29.82 | 37.0 | +| bicycle | 85.58 | 92.71 | +| bird | 95.39 | 97.72 | +| boat | 87.21 | 93.18 | +| book | 58.21 | 70.46 | +| bottle | 89.04 | 95.19 | +| building | 67.28 | 81.0 | +| bus | 95.01 | 97.31 | +| cabinet | 53.27 | 69.99 | +| car | 93.39 | 97.05 | +| cat | 94.47 | 98.05 | +| ceiling | 59.63 | 76.31 | +| chair | 64.52 | 83.43 | +| cloth | 30.79 | 41.56 | +| computer | 60.14 | 71.15 | +| cow | 96.03 | 97.67 | +| cup | 50.31 | 64.82 | +| curtain | 62.56 | 80.26 | +| dog | 93.03 | 97.9 | +| door | 40.17 | 61.27 | +| fence | 46.25 | 59.59 | +| floor | 75.06 | 87.53 | +| flower | 42.15 | 52.94 | +| food | 45.44 | 57.12 | +| grass | 83.21 | 92.23 | +| ground | 58.38 | 72.98 | +| horse | 95.3 | 97.82 | +| keyboard | 89.27 | 96.02 | +| light | 62.62 | 78.3 | +| motorbike | 92.05 | 97.06 | +| mountain | 56.55 | 73.28 | +| mouse | 89.96 | 93.63 | +| person | 91.34 | 96.52 | +| plate | 33.9 | 45.07 | +| platform | 50.58 | 63.69 | +| pottedplant | 82.39 | 90.53 | +| road | 54.29 | 70.06 | +| rock | 56.34 | 65.98 | +| sheep | 95.47 | 98.07 | +| shelves | 40.37 | 55.37 | +| sidewalk | 33.7 | 47.66 | +| sign | 55.68 | 66.4 | +| sky | 94.97 | 97.38 | +| snow | 80.64 | 91.51 | +| sofa | 58.71 | 67.64 | +| table | 72.56 | 84.05 | +| track | 73.5 | 83.52 | +| train | 93.03 | 97.21 | +| tree | 81.8 | 90.9 | +| truck | 52.97 | 62.71 | +| tvmonitor | 90.71 | 94.21 | +| wall | 72.6 | 83.58 | +| water | 92.99 | 96.54 | +| window | 46.55 | 59.19 | +| wood | 26.78 | 36.61 | ++-------------+-------+-------+ +2022-05-06 09:35:19,937 - mmseg - INFO - Summary: +2022-05-06 09:35:19,938 - mmseg - INFO - ++-------+-------+-------+ +| aAcc | mIoU | mAcc | ++-------+-------+-------+ +| 86.67 | 67.79 | 77.73 | ++-------+-------+-------+ +2022-05-06 09:35:19,940 - mmseg - INFO - The previous best checkpoint /mnt/lustre/chenzhe.vendor/workspace/ViT-Adapter/segmentation/work_dirs/mask2former_beit_adapter_large_480_40k_pascal_context_59_ss/best_mIoU_iter_36000.pth was removed +2022-05-06 09:35:45,646 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_40000.pth. +2022-05-06 09:35:45,656 - mmseg - INFO - Best mIoU is 0.6779 at 40000 iter. +2022-05-06 09:35:45,679 - mmseg - INFO - Exp name: mask2former_beit_adapter_large_480_40k_pascal_context_59_ss.py +2022-05-06 09:35:45,680 - mmseg - INFO - Iter(val) [638] aAcc: 0.8667, mIoU: 0.6779, mAcc: 0.7773, IoU.aeroplane: 0.9243, IoU.bag: 0.5076, IoU.bed: 0.3590, IoU.bedclothes: 0.4625, IoU.bench: 0.2982, IoU.bicycle: 0.8558, IoU.bird: 0.9539, IoU.boat: 0.8721, IoU.book: 0.5821, IoU.bottle: 0.8904, IoU.building: 0.6728, IoU.bus: 0.9501, IoU.cabinet: 0.5327, IoU.car: 0.9339, IoU.cat: 0.9447, IoU.ceiling: 0.5963, IoU.chair: 0.6452, IoU.cloth: 0.3079, IoU.computer: 0.6014, IoU.cow: 0.9603, IoU.cup: 0.5031, IoU.curtain: 0.6256, IoU.dog: 0.9303, IoU.door: 0.4017, IoU.fence: 0.4625, IoU.floor: 0.7506, IoU.flower: 0.4215, IoU.food: 0.4544, IoU.grass: 0.8321, IoU.ground: 0.5838, IoU.horse: 0.9530, IoU.keyboard: 0.8927, IoU.light: 0.6262, IoU.motorbike: 0.9205, IoU.mountain: 0.5655, IoU.mouse: 0.8996, IoU.person: 0.9134, IoU.plate: 0.3390, IoU.platform: 0.5058, IoU.pottedplant: 0.8239, IoU.road: 0.5429, IoU.rock: 0.5634, IoU.sheep: 0.9547, IoU.shelves: 0.4037, IoU.sidewalk: 0.3370, IoU.sign: 0.5568, IoU.sky: 0.9497, IoU.snow: 0.8064, IoU.sofa: 0.5871, IoU.table: 0.7256, IoU.track: 0.7350, IoU.train: 0.9303, IoU.tree: 0.8180, IoU.truck: 0.5297, IoU.tvmonitor: 0.9071, IoU.wall: 0.7260, IoU.water: 0.9299, IoU.window: 0.4655, IoU.wood: 0.2678, Acc.aeroplane: 0.9577, Acc.bag: 0.6835, Acc.bed: 0.4424, Acc.bedclothes: 0.7105, Acc.bench: 0.3700, Acc.bicycle: 0.9271, Acc.bird: 0.9772, Acc.boat: 0.9318, Acc.book: 0.7046, Acc.bottle: 0.9519, Acc.building: 0.8100, Acc.bus: 0.9731, Acc.cabinet: 0.6999, Acc.car: 0.9705, Acc.cat: 0.9805, Acc.ceiling: 0.7631, Acc.chair: 0.8343, Acc.cloth: 0.4156, Acc.computer: 0.7115, Acc.cow: 0.9767, Acc.cup: 0.6482, Acc.curtain: 0.8026, Acc.dog: 0.9790, Acc.door: 0.6127, Acc.fence: 0.5959, Acc.floor: 0.8753, Acc.flower: 0.5294, Acc.food: 0.5712, Acc.grass: 0.9223, Acc.ground: 0.7298, Acc.horse: 0.9782, Acc.keyboard: 0.9602, Acc.light: 0.7830, Acc.motorbike: 0.9706, Acc.mountain: 0.7328, Acc.mouse: 0.9363, Acc.person: 0.9652, Acc.plate: 0.4507, Acc.platform: 0.6369, Acc.pottedplant: 0.9053, Acc.road: 0.7006, Acc.rock: 0.6598, Acc.sheep: 0.9807, Acc.shelves: 0.5537, Acc.sidewalk: 0.4766, Acc.sign: 0.6640, Acc.sky: 0.9738, Acc.snow: 0.9151, Acc.sofa: 0.6764, Acc.table: 0.8405, Acc.track: 0.8352, Acc.train: 0.9721, Acc.tree: 0.9090, Acc.truck: 0.6271, Acc.tvmonitor: 0.9421, Acc.wall: 0.8358, Acc.water: 0.9654, Acc.window: 0.5919, Acc.wood: 0.3661