2023-03-03 20:50:44,032 - mmseg - INFO - Multi-processing start method is `None` 2023-03-03 20:50:44,050 - mmseg - INFO - OpenCV num_threads is `128 2023-03-03 20:50:44,050 - mmseg - INFO - OMP num threads is 1 2023-03-03 20:50:44,123 - mmseg - INFO - Environment info: ------------------------------------------------------------ sys.platform: linux Python: 3.7.16 (default, Jan 17 2023, 22:20:44) [GCC 11.2.0] CUDA available: True GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/laizeqiang/miniconda3/envs/torch NVCC: Cuda compilation tools, release 11.6, V11.6.124 GCC: gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44) PyTorch: 1.13.1 PyTorch compiling details: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.6 - 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_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37 - CuDNN 8.3.2 (built against CUDA 11.5) - Magma 2.6.1 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.6, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.1, 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, USE_ROCM=OFF, TorchVision: 0.14.1 OpenCV: 4.7.0 MMCV: 1.7.1 MMCV Compiler: GCC 9.3 MMCV CUDA Compiler: 11.6 MMSegmentation: 0.30.0+c844fc6 ------------------------------------------------------------ 2023-03-03 20:50:44,123 - mmseg - INFO - Distributed training: True 2023-03-03 20:50:44,773 - mmseg - INFO - Config: norm_cfg = dict(type='SyncBN', requires_grad=True) model = dict( type='EncoderDecoderDiffusion', pretrained= 'work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth', backbone=dict( type='ResNetV1cCustomInitWeights', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), dilations=(1, 1, 2, 4), strides=(1, 2, 1, 1), norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False, style='pytorch', contract_dilation=True), decode_head=dict( type='DepthwiseSeparableASPPHeadUnetFCHeadMultiStep', pretrained= 'work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth', dim=128, out_dim=256, unet_channels=528, dim_mults=[1, 1, 1], cat_embedding_dim=16, ignore_index=0, diffusion_timesteps=100, collect_timesteps=[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 99], in_channels=2048, in_index=3, channels=512, dilations=(1, 12, 24, 36), c1_in_channels=256, c1_channels=48, dropout_ratio=0.1, num_classes=20, norm_cfg=dict(type='SyncBN', requires_grad=True), align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), auxiliary_head=None, train_cfg=dict(), test_cfg=dict(mode='whole'), freeze_parameters=['backbone', 'decode_head']) dataset_type = 'Cityscapes20Dataset' data_root = 'data/cityscapes/' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) crop_size = (512, 1024) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotationsCityscapes20'), dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), dict(type='RandomCrop', crop_size=(512, 1024), 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=(512, 1024), pad_val=0, seg_pad_val=0), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg']) ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(2048, 1024), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), 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=2, train=dict( type='Cityscapes20Dataset', data_root='data/cityscapes/', img_dir='leftImg8bit/train', ann_dir='gtFine/train', pipeline=[ dict(type='LoadImageFromFile'), dict(type='LoadAnnotationsCityscapes20'), dict( type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), dict(type='RandomCrop', crop_size=(512, 1024), 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=(512, 1024), pad_val=0, seg_pad_val=0), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg']) ]), val=dict( type='Cityscapes20Dataset', data_root='data/cityscapes/', img_dir='leftImg8bit/val', ann_dir='gtFine/val', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(2048, 1024), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), 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='Cityscapes20Dataset', data_root='data/cityscapes/', img_dir='leftImg8bit/val', ann_dir='gtFine/val', pipeline=[ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(2048, 1024), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), 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 = None workflow = [('train', 1)] cudnn_benchmark = True optimizer = dict( type='AdamW', lr=0.00015, betas=[0.9, 0.96], weight_decay=0.045) optimizer_config = dict() lr_config = dict( policy='step', warmup='linear', warmup_iters=1000, warmup_ratio=1e-06, step=20000, gamma=0.5, min_lr=1e-06, by_epoch=False) runner = dict(type='IterBasedRunner', max_iters=160000) checkpoint_config = dict(by_epoch=False, interval=16000, max_keep_ckpts=1) evaluation = dict( interval=16000, metric='mIoU', pre_eval=True, save_best='mIoU') checkpoint = 'work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth' custom_hooks = [ dict( type='ConstantMomentumEMAHook', momentum=0.01, interval=25, eval_interval=16000, auto_resume=True, priority=49) ] work_dir = './work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune' gpu_ids = range(0, 8) auto_resume = True 2023-03-03 20:50:49,172 - mmseg - INFO - Set random seed to 1494050190, deterministic: False 2023-03-03 20:50:50,248 - mmseg - INFO - Parameters in backbone freezed! 2023-03-03 20:50:50,249 - mmseg - INFO - Trainable parameters in DepthwiseSeparableASPPHeadUnetFCHeadMultiStep: ['unet.init_conv.weight', 'unet.init_conv.bias', 'unet.time_mlp.1.weight', 'unet.time_mlp.1.bias', 'unet.time_mlp.3.weight', 'unet.time_mlp.3.bias', 'unet.downs.0.0.mlp.1.weight', 'unet.downs.0.0.mlp.1.bias', 'unet.downs.0.0.block1.proj.weight', 'unet.downs.0.0.block1.proj.bias', 'unet.downs.0.0.block1.norm.weight', 'unet.downs.0.0.block1.norm.bias', 'unet.downs.0.0.block2.proj.weight', 'unet.downs.0.0.block2.proj.bias', 'unet.downs.0.0.block2.norm.weight', 'unet.downs.0.0.block2.norm.bias', 'unet.downs.0.1.mlp.1.weight', 'unet.downs.0.1.mlp.1.bias', 'unet.downs.0.1.block1.proj.weight', 'unet.downs.0.1.block1.proj.bias', 'unet.downs.0.1.block1.norm.weight', 'unet.downs.0.1.block1.norm.bias', 'unet.downs.0.1.block2.proj.weight', 'unet.downs.0.1.block2.proj.bias', 'unet.downs.0.1.block2.norm.weight', 'unet.downs.0.1.block2.norm.bias', 'unet.downs.0.2.fn.fn.to_qkv.weight', 'unet.downs.0.2.fn.fn.to_out.0.weight', 'unet.downs.0.2.fn.fn.to_out.0.bias', 'unet.downs.0.2.fn.fn.to_out.1.g', 'unet.downs.0.2.fn.norm.g', 'unet.downs.0.3.weight', 'unet.downs.0.3.bias', 'unet.downs.1.0.mlp.1.weight', 'unet.downs.1.0.mlp.1.bias', 'unet.downs.1.0.block1.proj.weight', 'unet.downs.1.0.block1.proj.bias', 'unet.downs.1.0.block1.norm.weight', 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'unet.mid_block1.block2.norm.weight', 'unet.mid_block1.block2.norm.bias', 'unet.mid_attn.fn.fn.to_qkv.weight', 'unet.mid_attn.fn.fn.to_out.weight', 'unet.mid_attn.fn.fn.to_out.bias', 'unet.mid_attn.fn.norm.g', 'unet.mid_block2.mlp.1.weight', 'unet.mid_block2.mlp.1.bias', 'unet.mid_block2.block1.proj.weight', 'unet.mid_block2.block1.proj.bias', 'unet.mid_block2.block1.norm.weight', 'unet.mid_block2.block1.norm.bias', 'unet.mid_block2.block2.proj.weight', 'unet.mid_block2.block2.proj.bias', 'unet.mid_block2.block2.norm.weight', 'unet.mid_block2.block2.norm.bias', 'unet.final_res_block.mlp.1.weight', 'unet.final_res_block.mlp.1.bias', 'unet.final_res_block.block1.proj.weight', 'unet.final_res_block.block1.proj.bias', 'unet.final_res_block.block1.norm.weight', 'unet.final_res_block.block1.norm.bias', 'unet.final_res_block.block2.proj.weight', 'unet.final_res_block.block2.proj.bias', 'unet.final_res_block.block2.norm.weight', 'unet.final_res_block.block2.norm.bias', 'unet.final_res_block.res_conv.weight', 'unet.final_res_block.res_conv.bias', 'unet.final_conv.weight', 'unet.final_conv.bias', 'conv_seg_new.weight', 'conv_seg_new.bias'] 2023-03-03 20:50:50,249 - mmseg - INFO - Parameters in decode_head freezed! 2023-03-03 20:50:50,273 - mmseg - INFO - load checkpoint from local path: work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth 2023-03-03 20:50:51,238 - mmseg - WARNING - The model and loaded state dict do not match exactly unexpected key in source state_dict: decode_head.image_pool.1.conv.weight, decode_head.image_pool.1.bn.weight, decode_head.image_pool.1.bn.bias, decode_head.image_pool.1.bn.running_mean, decode_head.image_pool.1.bn.running_var, decode_head.image_pool.1.bn.num_batches_tracked, decode_head.aspp_modules.0.conv.weight, decode_head.aspp_modules.0.bn.weight, decode_head.aspp_modules.0.bn.bias, decode_head.aspp_modules.0.bn.running_mean, decode_head.aspp_modules.0.bn.running_var, decode_head.aspp_modules.0.bn.num_batches_tracked, decode_head.aspp_modules.1.depthwise_conv.conv.weight, decode_head.aspp_modules.1.depthwise_conv.bn.weight, decode_head.aspp_modules.1.depthwise_conv.bn.bias, decode_head.aspp_modules.1.depthwise_conv.bn.running_mean, decode_head.aspp_modules.1.depthwise_conv.bn.running_var, decode_head.aspp_modules.1.depthwise_conv.bn.num_batches_tracked, decode_head.aspp_modules.1.pointwise_conv.conv.weight, decode_head.aspp_modules.1.pointwise_conv.bn.weight, decode_head.aspp_modules.1.pointwise_conv.bn.bias, decode_head.aspp_modules.1.pointwise_conv.bn.running_mean, decode_head.aspp_modules.1.pointwise_conv.bn.running_var, decode_head.aspp_modules.1.pointwise_conv.bn.num_batches_tracked, decode_head.aspp_modules.2.depthwise_conv.conv.weight, decode_head.aspp_modules.2.depthwise_conv.bn.weight, decode_head.aspp_modules.2.depthwise_conv.bn.bias, decode_head.aspp_modules.2.depthwise_conv.bn.running_mean, 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decode_head.unet.mid_block2.block2.proj.weight, decode_head.unet.mid_block2.block2.proj.bias, decode_head.unet.mid_block2.block2.norm.weight, decode_head.unet.mid_block2.block2.norm.bias, decode_head.unet.final_res_block.mlp.1.weight, decode_head.unet.final_res_block.mlp.1.bias, decode_head.unet.final_res_block.block1.proj.weight, decode_head.unet.final_res_block.block1.proj.bias, decode_head.unet.final_res_block.block1.norm.weight, decode_head.unet.final_res_block.block1.norm.bias, decode_head.unet.final_res_block.block2.proj.weight, decode_head.unet.final_res_block.block2.proj.bias, decode_head.unet.final_res_block.block2.norm.weight, decode_head.unet.final_res_block.block2.norm.bias, decode_head.unet.final_res_block.res_conv.weight, decode_head.unet.final_res_block.res_conv.bias, decode_head.unet.final_conv.weight, decode_head.unet.final_conv.bias, decode_head.conv_seg_new.weight, decode_head.conv_seg_new.bias, decode_head.embed.weight 2023-03-03 20:50:51,253 - mmseg - INFO - load checkpoint from local path: work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth 2023-03-03 20:50:51,752 - mmseg - WARNING - The model and loaded state dict do not match exactly unexpected key in source state_dict: backbone.stem.0.weight, backbone.stem.1.weight, backbone.stem.1.bias, backbone.stem.1.running_mean, backbone.stem.1.running_var, backbone.stem.1.num_batches_tracked, backbone.stem.3.weight, backbone.stem.4.weight, backbone.stem.4.bias, backbone.stem.4.running_mean, backbone.stem.4.running_var, backbone.stem.4.num_batches_tracked, backbone.stem.6.weight, backbone.stem.7.weight, backbone.stem.7.bias, backbone.stem.7.running_mean, backbone.stem.7.running_var, backbone.stem.7.num_batches_tracked, backbone.layer1.0.conv1.weight, backbone.layer1.0.bn1.weight, backbone.layer1.0.bn1.bias, backbone.layer1.0.bn1.running_mean, backbone.layer1.0.bn1.running_var, backbone.layer1.0.bn1.num_batches_tracked, 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backbone.layer3.1.bn3.weight, backbone.layer3.1.bn3.bias, backbone.layer3.1.bn3.running_mean, backbone.layer3.1.bn3.running_var, backbone.layer3.1.bn3.num_batches_tracked, backbone.layer3.2.conv1.weight, backbone.layer3.2.bn1.weight, backbone.layer3.2.bn1.bias, backbone.layer3.2.bn1.running_mean, backbone.layer3.2.bn1.running_var, backbone.layer3.2.bn1.num_batches_tracked, backbone.layer3.2.conv2.weight, backbone.layer3.2.bn2.weight, backbone.layer3.2.bn2.bias, backbone.layer3.2.bn2.running_mean, backbone.layer3.2.bn2.running_var, backbone.layer3.2.bn2.num_batches_tracked, backbone.layer3.2.conv3.weight, backbone.layer3.2.bn3.weight, backbone.layer3.2.bn3.bias, backbone.layer3.2.bn3.running_mean, backbone.layer3.2.bn3.running_var, backbone.layer3.2.bn3.num_batches_tracked, backbone.layer3.3.conv1.weight, backbone.layer3.3.bn1.weight, backbone.layer3.3.bn1.bias, backbone.layer3.3.bn1.running_mean, backbone.layer3.3.bn1.running_var, backbone.layer3.3.bn1.num_batches_tracked, 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backbone.layer3.4.bn3.num_batches_tracked, backbone.layer3.5.conv1.weight, backbone.layer3.5.bn1.weight, backbone.layer3.5.bn1.bias, backbone.layer3.5.bn1.running_mean, backbone.layer3.5.bn1.running_var, backbone.layer3.5.bn1.num_batches_tracked, backbone.layer3.5.conv2.weight, backbone.layer3.5.bn2.weight, backbone.layer3.5.bn2.bias, backbone.layer3.5.bn2.running_mean, backbone.layer3.5.bn2.running_var, backbone.layer3.5.bn2.num_batches_tracked, backbone.layer3.5.conv3.weight, backbone.layer3.5.bn3.weight, backbone.layer3.5.bn3.bias, backbone.layer3.5.bn3.running_mean, backbone.layer3.5.bn3.running_var, backbone.layer3.5.bn3.num_batches_tracked, backbone.layer4.0.conv1.weight, backbone.layer4.0.bn1.weight, backbone.layer4.0.bn1.bias, backbone.layer4.0.bn1.running_mean, backbone.layer4.0.bn1.running_var, backbone.layer4.0.bn1.num_batches_tracked, backbone.layer4.0.conv2.weight, backbone.layer4.0.bn2.weight, backbone.layer4.0.bn2.bias, backbone.layer4.0.bn2.running_mean, backbone.layer4.0.bn2.running_var, backbone.layer4.0.bn2.num_batches_tracked, backbone.layer4.0.conv3.weight, backbone.layer4.0.bn3.weight, backbone.layer4.0.bn3.bias, backbone.layer4.0.bn3.running_mean, backbone.layer4.0.bn3.running_var, backbone.layer4.0.bn3.num_batches_tracked, backbone.layer4.0.downsample.0.weight, backbone.layer4.0.downsample.1.weight, backbone.layer4.0.downsample.1.bias, backbone.layer4.0.downsample.1.running_mean, backbone.layer4.0.downsample.1.running_var, backbone.layer4.0.downsample.1.num_batches_tracked, backbone.layer4.1.conv1.weight, backbone.layer4.1.bn1.weight, backbone.layer4.1.bn1.bias, backbone.layer4.1.bn1.running_mean, backbone.layer4.1.bn1.running_var, backbone.layer4.1.bn1.num_batches_tracked, backbone.layer4.1.conv2.weight, backbone.layer4.1.bn2.weight, backbone.layer4.1.bn2.bias, backbone.layer4.1.bn2.running_mean, backbone.layer4.1.bn2.running_var, backbone.layer4.1.bn2.num_batches_tracked, backbone.layer4.1.conv3.weight, backbone.layer4.1.bn3.weight, backbone.layer4.1.bn3.bias, backbone.layer4.1.bn3.running_mean, backbone.layer4.1.bn3.running_var, backbone.layer4.1.bn3.num_batches_tracked, backbone.layer4.2.conv1.weight, backbone.layer4.2.bn1.weight, backbone.layer4.2.bn1.bias, backbone.layer4.2.bn1.running_mean, backbone.layer4.2.bn1.running_var, backbone.layer4.2.bn1.num_batches_tracked, backbone.layer4.2.conv2.weight, backbone.layer4.2.bn2.weight, backbone.layer4.2.bn2.bias, backbone.layer4.2.bn2.running_mean, backbone.layer4.2.bn2.running_var, backbone.layer4.2.bn2.num_batches_tracked, backbone.layer4.2.conv3.weight, backbone.layer4.2.bn3.weight, backbone.layer4.2.bn3.bias, backbone.layer4.2.bn3.running_mean, backbone.layer4.2.bn3.running_var, backbone.layer4.2.bn3.num_batches_tracked missing keys in source state_dict: log_cumprod_at, log_cumprod_bt 2023-03-03 20:50:51,779 - mmseg - INFO - EncoderDecoderDiffusion( (backbone): ResNetV1cCustomInitWeights( (stem): Sequential( (0): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (1): SyncBatchNorm(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (2): ReLU(inplace=True) (3): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (4): SyncBatchNorm(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (5): ReLU(inplace=True) (6): Conv2d(32, 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) ) (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False) (layer1): ResLayer( (0): Bottleneck( (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (layer2): ResLayer( (0): Bottleneck( (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (3): Bottleneck( (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (layer3): ResLayer( (0): Bottleneck( (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (1): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), bias=False) (bn2): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), bias=False) (bn2): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (3): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), bias=False) (bn2): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (4): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), bias=False) (bn2): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (5): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), bias=False) (bn2): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (layer4): ResLayer( (0): Bottleneck( (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(2, 2), dilation=(2, 2), bias=False) (bn2): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (1): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(4, 4), dilation=(4, 4), bias=False) (bn2): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(4, 4), dilation=(4, 4), bias=False) (bn2): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) ) init_cfg={'type': 'Pretrained', 'checkpoint': 'work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth'} (decode_head): DepthwiseSeparableASPPHeadUnetFCHeadMultiStep( input_transform=None, ignore_index=0, align_corners=False (loss_decode): CrossEntropyLoss(avg_non_ignore=False) (conv_seg): None (dropout): Dropout2d(p=0.1, inplace=False) (image_pool): Sequential( (0): AdaptiveAvgPool2d(output_size=1) (1): ConvModule( (conv): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) ) (aspp_modules): DepthwiseSeparableASPPModule( (0): ConvModule( (conv): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (1): DepthwiseSeparableConvModule( (depthwise_conv): ConvModule( (conv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(12, 12), dilation=(12, 12), groups=2048, bias=False) (bn): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (pointwise_conv): ConvModule( (conv): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) ) (2): DepthwiseSeparableConvModule( (depthwise_conv): ConvModule( (conv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(24, 24), dilation=(24, 24), groups=2048, bias=False) (bn): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (pointwise_conv): ConvModule( (conv): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) ) (3): DepthwiseSeparableConvModule( (depthwise_conv): ConvModule( (conv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(36, 36), dilation=(36, 36), groups=2048, bias=False) (bn): SyncBatchNorm(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (pointwise_conv): ConvModule( (conv): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) ) ) (bottleneck): ConvModule( (conv): Conv2d(2560, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (c1_bottleneck): ConvModule( (conv): Conv2d(256, 48, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(48, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (sep_bottleneck): Sequential( (0): DepthwiseSeparableConvModule( (depthwise_conv): ConvModule( (conv): Conv2d(560, 560, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=560, bias=False) (bn): SyncBatchNorm(560, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (pointwise_conv): ConvModule( (conv): Conv2d(560, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) ) (1): DepthwiseSeparableConvModule( (depthwise_conv): ConvModule( (conv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512, bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) (pointwise_conv): ConvModule( (conv): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn): SyncBatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (activate): ReLU(inplace=True) ) ) ) (unet): Unet( (init_conv): Conv2d(528, 128, kernel_size=(7, 7), stride=(1, 1), padding=(3, 3)) (time_mlp): Sequential( (0): SinusoidalPosEmb() (1): Linear(in_features=128, out_features=512, bias=True) (2): GELU(approximate='none') (3): Linear(in_features=512, out_features=512, bias=True) ) (downs): ModuleList( (0): ModuleList( (0): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (2): Residual( (fn): PreNorm( (fn): LinearAttention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Sequential( (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (1): LayerNorm() ) ) (norm): LayerNorm() ) ) (3): Conv2d(128, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1)) ) (1): ModuleList( (0): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (2): Residual( (fn): PreNorm( (fn): LinearAttention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Sequential( (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (1): LayerNorm() ) ) (norm): LayerNorm() ) ) (3): Conv2d(128, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1)) ) (2): ModuleList( (0): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (2): Residual( (fn): PreNorm( (fn): LinearAttention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Sequential( (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (1): LayerNorm() ) ) (norm): LayerNorm() ) ) (3): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) ) ) (ups): ModuleList( (0): ModuleList( (0): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (2): Residual( (fn): PreNorm( (fn): LinearAttention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Sequential( (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (1): LayerNorm() ) ) (norm): LayerNorm() ) ) (3): Sequential( (0): Upsample(scale_factor=2.0, mode=nearest) (1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) ) ) (1): ModuleList( (0): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (2): Residual( (fn): PreNorm( (fn): LinearAttention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Sequential( (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (1): LayerNorm() ) ) (norm): LayerNorm() ) ) (3): Sequential( (0): Upsample(scale_factor=2.0, mode=nearest) (1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) ) ) (2): ModuleList( (0): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (2): Residual( (fn): PreNorm( (fn): LinearAttention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Sequential( (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) (1): LayerNorm() ) ) (norm): LayerNorm() ) ) (3): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) ) ) (mid_block1): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (mid_attn): Residual( (fn): PreNorm( (fn): Attention( (to_qkv): Conv2d(128, 384, kernel_size=(1, 1), stride=(1, 1), bias=False) (to_out): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1)) ) (norm): LayerNorm() ) ) (mid_block2): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Identity() ) (final_res_block): ResnetBlock( (mlp): Sequential( (0): SiLU() (1): Linear(in_features=512, out_features=256, bias=True) ) (block1): Block( (proj): WeightStandardizedConv2d(256, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (block2): Block( (proj): WeightStandardizedConv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) (norm): GroupNorm(8, 128, eps=1e-05, affine=True) (act): SiLU() ) (res_conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1)) ) (final_conv): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1)) ) (conv_seg_new): Conv2d(256, 20, kernel_size=(1, 1), stride=(1, 1)) (embed): Embedding(20, 16) ) init_cfg={'type': 'Pretrained', 'checkpoint': 'work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_single_step_ade_pretrained_freeze_embed_80k_cityscapes20/best_mIoU_iter_72000.pth'} ) 2023-03-03 20:50:51,863 - mmseg - INFO - Loaded 2975 images 2023-03-03 20:50:55,607 - mmseg - INFO - Loaded 500 images 2023-03-03 20:50:55,610 - mmseg - INFO - Start running, host: laizeqiang@SH-IDC1-10-140-37-159, work_dir: /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune 2023-03-03 20:50:55,610 - mmseg - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) StepLrUpdaterHook (49 ) ConstantMomentumEMAHook (NORMAL ) CheckpointHook (LOW ) DistEvalHookMultiSteps (VERY_LOW ) TextLoggerHook -------------------- before_train_epoch: (VERY_HIGH ) StepLrUpdaterHook (LOW ) IterTimerHook (LOW ) DistEvalHookMultiSteps (VERY_LOW ) TextLoggerHook -------------------- before_train_iter: (VERY_HIGH ) StepLrUpdaterHook (49 ) ConstantMomentumEMAHook (LOW ) IterTimerHook (LOW ) DistEvalHookMultiSteps -------------------- after_train_iter: (ABOVE_NORMAL) OptimizerHook (49 ) ConstantMomentumEMAHook (NORMAL ) CheckpointHook (LOW ) IterTimerHook (LOW ) DistEvalHookMultiSteps (VERY_LOW ) TextLoggerHook -------------------- after_train_epoch: (NORMAL ) CheckpointHook (LOW ) DistEvalHookMultiSteps (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 -------------------- 2023-03-03 20:50:55,610 - mmseg - INFO - workflow: [('train', 1)], max: 160000 iters 2023-03-03 20:50:55,647 - mmseg - INFO - Checkpoints will be saved to /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune by HardDiskBackend. 2023-03-03 20:51:07,814 - mmseg - INFO - Swap parameters (before train) before iter [1] 2023-03-03 20:51:43,492 - mmseg - INFO - Iter [50/160000] lr: 7.350e-06, eta: 1 day, 7:57:14, time: 0.719, data_time: 0.014, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7292, loss: 0.0830 2023-03-03 20:51:55,765 - mmseg - INFO - Iter [100/160000] lr: 1.485e-05, eta: 21:25:25, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6265, loss: 0.0849 2023-03-03 20:52:08,043 - mmseg - INFO - Iter [150/160000] lr: 2.235e-05, eta: 17:54:46, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6655, loss: 0.0848 2023-03-03 20:52:22,707 - mmseg - INFO - Iter [200/160000] lr: 2.985e-05, eta: 16:41:04, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.5656, loss: 0.0879 2023-03-03 20:52:34,881 - mmseg - INFO - Iter [250/160000] lr: 3.735e-05, eta: 15:30:15, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.6773, loss: 0.0838 2023-03-03 20:52:47,425 - mmseg - INFO - Iter [300/160000] lr: 4.485e-05, eta: 14:46:15, time: 0.251, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6962, loss: 0.0836 2023-03-03 20:52:59,741 - mmseg - INFO - Iter [350/160000] lr: 5.235e-05, eta: 14:13:02, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6240, loss: 0.0855 2023-03-03 20:53:14,269 - mmseg - INFO - Iter [400/160000] lr: 5.985e-05, eta: 14:02:46, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7153, loss: 0.0829 2023-03-03 20:53:26,540 - mmseg - INFO - Iter [450/160000] lr: 6.735e-05, eta: 13:41:25, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5895, loss: 0.0863 2023-03-03 20:53:38,707 - mmseg - INFO - Iter [500/160000] lr: 7.485e-05, eta: 13:23:44, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0884, decode.acc_seg: 96.5290, loss: 0.0884 2023-03-03 20:53:50,880 - mmseg - INFO - Iter [550/160000] lr: 8.235e-05, eta: 13:09:15, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5200, loss: 0.0874 2023-03-03 20:54:05,403 - mmseg - INFO - Iter [600/160000] lr: 8.985e-05, eta: 13:07:33, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8284, loss: 0.0801 2023-03-03 20:54:17,687 - mmseg - INFO - Iter [650/160000] lr: 9.735e-05, eta: 12:56:56, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6587, loss: 0.0842 2023-03-03 20:54:29,800 - mmseg - INFO - Iter [700/160000] lr: 1.049e-04, eta: 12:47:09, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0895, decode.acc_seg: 96.4998, loss: 0.0895 2023-03-03 20:54:44,294 - mmseg - INFO - Iter [750/160000] lr: 1.124e-04, eta: 12:47:04, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6091, loss: 0.0856 2023-03-03 20:54:56,464 - mmseg - INFO - Iter [800/160000] lr: 1.199e-04, eta: 12:39:16, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0922, decode.acc_seg: 96.3591, loss: 0.0922 2023-03-03 20:55:08,680 - mmseg - INFO - Iter [850/160000] lr: 1.274e-04, eta: 12:32:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0904, decode.acc_seg: 96.4194, loss: 0.0904 2023-03-03 20:55:20,741 - mmseg - INFO - Iter [900/160000] lr: 1.349e-04, eta: 12:26:00, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0887, decode.acc_seg: 96.5465, loss: 0.0887 2023-03-03 20:55:35,409 - mmseg - INFO - Iter [950/160000] lr: 1.424e-04, eta: 12:27:27, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0891, decode.acc_seg: 96.5368, loss: 0.0891 2023-03-03 20:55:47,581 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 20:55:47,582 - mmseg - INFO - Iter [1000/160000] lr: 1.499e-04, eta: 12:22:06, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6000, loss: 0.0861 2023-03-03 20:55:59,915 - mmseg - INFO - Iter [1050/160000] lr: 1.500e-04, eta: 12:17:40, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6149, loss: 0.0854 2023-03-03 20:56:12,107 - mmseg - INFO - Iter [1100/160000] lr: 1.500e-04, eta: 12:13:16, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.4998, loss: 0.0879 2023-03-03 20:56:26,626 - mmseg - INFO - Iter [1150/160000] lr: 1.500e-04, eta: 12:14:34, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.4808, loss: 0.0879 2023-03-03 20:56:38,761 - mmseg - INFO - Iter [1200/160000] lr: 1.500e-04, eta: 12:10:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.5655, loss: 0.0866 2023-03-03 20:56:50,933 - mmseg - INFO - Iter [1250/160000] lr: 1.500e-04, eta: 12:06:50, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0887, decode.acc_seg: 96.5271, loss: 0.0887 2023-03-03 20:57:03,276 - mmseg - INFO - Iter [1300/160000] lr: 1.500e-04, eta: 12:03:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0897, decode.acc_seg: 96.4752, loss: 0.0897 2023-03-03 20:57:17,730 - mmseg - INFO - Iter [1350/160000] lr: 1.500e-04, eta: 12:05:03, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6396, loss: 0.0847 2023-03-03 20:57:30,068 - mmseg - INFO - Iter [1400/160000] lr: 1.500e-04, eta: 12:02:15, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0892, decode.acc_seg: 96.4621, loss: 0.0892 2023-03-03 20:57:42,100 - mmseg - INFO - Iter [1450/160000] lr: 1.500e-04, eta: 11:59:03, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6465, loss: 0.0849 2023-03-03 20:57:56,521 - mmseg - INFO - Iter [1500/160000] lr: 1.500e-04, eta: 12:00:15, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.5592, loss: 0.0866 2023-03-03 20:58:08,674 - mmseg - INFO - Iter [1550/160000] lr: 1.500e-04, eta: 11:57:30, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0900, decode.acc_seg: 96.4487, loss: 0.0900 2023-03-03 20:58:20,784 - mmseg - INFO - Iter [1600/160000] lr: 1.500e-04, eta: 11:54:50, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6012, loss: 0.0862 2023-03-03 20:58:32,982 - mmseg - INFO - Iter [1650/160000] lr: 1.500e-04, eta: 11:52:27, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0887, decode.acc_seg: 96.5394, loss: 0.0887 2023-03-03 20:58:47,485 - mmseg - INFO - Iter [1700/160000] lr: 1.500e-04, eta: 11:53:48, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0867, decode.acc_seg: 96.5810, loss: 0.0867 2023-03-03 20:58:59,713 - mmseg - INFO - Iter [1750/160000] lr: 1.500e-04, eta: 11:51:37, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0909, decode.acc_seg: 96.4120, loss: 0.0909 2023-03-03 20:59:11,988 - mmseg - INFO - Iter [1800/160000] lr: 1.500e-04, eta: 11:49:37, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6045, loss: 0.0862 2023-03-03 20:59:24,204 - mmseg - INFO - Iter [1850/160000] lr: 1.500e-04, eta: 11:47:37, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.6763, loss: 0.0838 2023-03-03 20:59:38,716 - mmseg - INFO - Iter [1900/160000] lr: 1.500e-04, eta: 11:48:54, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.5422, loss: 0.0868 2023-03-03 20:59:50,930 - mmseg - INFO - Iter [1950/160000] lr: 1.500e-04, eta: 11:47:01, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.5778, loss: 0.0864 2023-03-03 21:00:03,141 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:00:03,141 - mmseg - INFO - Iter [2000/160000] lr: 1.500e-04, eta: 11:45:12, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0867, decode.acc_seg: 96.5497, loss: 0.0867 2023-03-03 21:00:17,534 - mmseg - INFO - Iter [2050/160000] lr: 1.500e-04, eta: 11:46:15, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0916, decode.acc_seg: 96.3901, loss: 0.0916 2023-03-03 21:00:29,651 - mmseg - INFO - Iter [2100/160000] lr: 1.500e-04, eta: 11:44:24, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6661, loss: 0.0853 2023-03-03 21:00:41,690 - mmseg - INFO - Iter [2150/160000] lr: 1.500e-04, eta: 11:42:32, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6783, loss: 0.0846 2023-03-03 21:00:53,888 - mmseg - INFO - Iter [2200/160000] lr: 1.500e-04, eta: 11:40:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0906, decode.acc_seg: 96.4523, loss: 0.0906 2023-03-03 21:01:08,548 - mmseg - INFO - Iter [2250/160000] lr: 1.500e-04, eta: 11:42:16, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0877, decode.acc_seg: 96.5142, loss: 0.0877 2023-03-03 21:01:20,674 - mmseg - INFO - Iter [2300/160000] lr: 1.500e-04, eta: 11:40:39, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6346, loss: 0.0852 2023-03-03 21:01:32,901 - mmseg - INFO - Iter [2350/160000] lr: 1.500e-04, eta: 11:39:11, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5614, loss: 0.0871 2023-03-03 21:01:45,099 - mmseg - INFO - Iter [2400/160000] lr: 1.500e-04, eta: 11:37:45, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5716, loss: 0.0871 2023-03-03 21:01:59,599 - mmseg - INFO - Iter [2450/160000] lr: 1.500e-04, eta: 11:38:50, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0900, decode.acc_seg: 96.4403, loss: 0.0900 2023-03-03 21:02:11,949 - mmseg - INFO - Iter [2500/160000] lr: 1.500e-04, eta: 11:37:37, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.6242, loss: 0.0870 2023-03-03 21:02:24,079 - mmseg - INFO - Iter [2550/160000] lr: 1.500e-04, eta: 11:36:12, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5839, loss: 0.0871 2023-03-03 21:02:36,191 - mmseg - INFO - Iter [2600/160000] lr: 1.500e-04, eta: 11:34:49, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0893, decode.acc_seg: 96.4861, loss: 0.0893 2023-03-03 21:02:50,669 - mmseg - INFO - Iter [2650/160000] lr: 1.500e-04, eta: 11:35:49, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6495, loss: 0.0851 2023-03-03 21:03:02,794 - mmseg - INFO - Iter [2700/160000] lr: 1.500e-04, eta: 11:34:29, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0928, decode.acc_seg: 96.3455, loss: 0.0928 2023-03-03 21:03:14,921 - mmseg - INFO - Iter [2750/160000] lr: 1.500e-04, eta: 11:33:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0906, decode.acc_seg: 96.4430, loss: 0.0906 2023-03-03 21:03:29,327 - mmseg - INFO - Iter [2800/160000] lr: 1.500e-04, eta: 11:34:05, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.5358, loss: 0.0882 2023-03-03 21:03:41,574 - mmseg - INFO - Iter [2850/160000] lr: 1.500e-04, eta: 11:32:57, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6567, loss: 0.0849 2023-03-03 21:03:53,694 - mmseg - INFO - Iter [2900/160000] lr: 1.500e-04, eta: 11:31:43, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6441, loss: 0.0845 2023-03-03 21:04:05,829 - mmseg - INFO - Iter [2950/160000] lr: 1.500e-04, eta: 11:30:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5788, loss: 0.0874 2023-03-03 21:04:20,283 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:04:20,283 - mmseg - INFO - Iter [3000/160000] lr: 1.500e-04, eta: 11:31:26, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6327, loss: 0.0859 2023-03-03 21:04:32,616 - mmseg - INFO - Iter [3050/160000] lr: 1.500e-04, eta: 11:30:27, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0892, decode.acc_seg: 96.5227, loss: 0.0892 2023-03-03 21:04:44,841 - mmseg - INFO - Iter [3100/160000] lr: 1.500e-04, eta: 11:29:25, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7180, loss: 0.0834 2023-03-03 21:04:56,891 - mmseg - INFO - Iter [3150/160000] lr: 1.500e-04, eta: 11:28:15, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0902, decode.acc_seg: 96.4510, loss: 0.0902 2023-03-03 21:05:11,340 - mmseg - INFO - Iter [3200/160000] lr: 1.500e-04, eta: 11:29:05, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6911, loss: 0.0836 2023-03-03 21:05:23,367 - mmseg - INFO - Iter [3250/160000] lr: 1.500e-04, eta: 11:27:56, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5393, loss: 0.0875 2023-03-03 21:05:35,426 - mmseg - INFO - Iter [3300/160000] lr: 1.500e-04, eta: 11:26:50, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6884, loss: 0.0840 2023-03-03 21:05:49,934 - mmseg - INFO - Iter [3350/160000] lr: 1.500e-04, eta: 11:27:41, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.5472, loss: 0.0864 2023-03-03 21:06:02,042 - mmseg - INFO - Iter [3400/160000] lr: 1.500e-04, eta: 11:26:38, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0908, decode.acc_seg: 96.4675, loss: 0.0908 2023-03-03 21:06:14,195 - mmseg - INFO - Iter [3450/160000] lr: 1.500e-04, eta: 11:25:39, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.5880, loss: 0.0862 2023-03-03 21:06:26,301 - mmseg - INFO - Iter [3500/160000] lr: 1.500e-04, eta: 11:24:41, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.5056, loss: 0.0872 2023-03-03 21:06:40,698 - mmseg - INFO - Iter [3550/160000] lr: 1.500e-04, eta: 11:25:24, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.5889, loss: 0.0855 2023-03-03 21:06:52,899 - mmseg - INFO - Iter [3600/160000] lr: 1.500e-04, eta: 11:24:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6356, loss: 0.0835 2023-03-03 21:07:05,046 - mmseg - INFO - Iter [3650/160000] lr: 1.500e-04, eta: 11:23:34, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0884, decode.acc_seg: 96.5334, loss: 0.0884 2023-03-03 21:07:17,322 - mmseg - INFO - Iter [3700/160000] lr: 1.500e-04, eta: 11:22:46, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0913, decode.acc_seg: 96.4363, loss: 0.0913 2023-03-03 21:07:31,847 - mmseg - INFO - Iter [3750/160000] lr: 1.500e-04, eta: 11:23:32, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0896, decode.acc_seg: 96.5275, loss: 0.0896 2023-03-03 21:07:43,870 - mmseg - INFO - Iter [3800/160000] lr: 1.500e-04, eta: 11:22:33, time: 0.240, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6546, loss: 0.0844 2023-03-03 21:07:55,961 - mmseg - INFO - Iter [3850/160000] lr: 1.500e-04, eta: 11:21:39, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6063, loss: 0.0862 2023-03-03 21:08:08,191 - mmseg - INFO - Iter [3900/160000] lr: 1.500e-04, eta: 11:20:51, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5201, loss: 0.0880 2023-03-03 21:08:22,711 - mmseg - INFO - Iter [3950/160000] lr: 1.500e-04, eta: 11:21:35, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.5829, loss: 0.0862 2023-03-03 21:08:34,830 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:08:34,830 - mmseg - INFO - Iter [4000/160000] lr: 1.500e-04, eta: 11:20:43, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6129, loss: 0.0863 2023-03-03 21:08:46,975 - mmseg - INFO - Iter [4050/160000] lr: 1.500e-04, eta: 11:19:54, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5448, loss: 0.0878 2023-03-03 21:09:01,588 - mmseg - INFO - Iter [4100/160000] lr: 1.500e-04, eta: 11:20:39, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0895, decode.acc_seg: 96.4840, loss: 0.0895 2023-03-03 21:09:13,790 - mmseg - INFO - Iter [4150/160000] lr: 1.500e-04, eta: 11:19:52, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5558, loss: 0.0874 2023-03-03 21:09:25,819 - mmseg - INFO - Iter [4200/160000] lr: 1.500e-04, eta: 11:19:00, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6738, loss: 0.0841 2023-03-03 21:09:38,096 - mmseg - INFO - Iter [4250/160000] lr: 1.500e-04, eta: 11:18:17, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5889, loss: 0.0870 2023-03-03 21:09:52,581 - mmseg - INFO - Iter [4300/160000] lr: 1.500e-04, eta: 11:18:56, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0885, decode.acc_seg: 96.5200, loss: 0.0885 2023-03-03 21:10:04,843 - mmseg - INFO - Iter [4350/160000] lr: 1.500e-04, eta: 11:18:13, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6312, loss: 0.0858 2023-03-03 21:10:17,033 - mmseg - INFO - Iter [4400/160000] lr: 1.500e-04, eta: 11:17:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0916, decode.acc_seg: 96.4156, loss: 0.0916 2023-03-03 21:10:29,160 - mmseg - INFO - Iter [4450/160000] lr: 1.500e-04, eta: 11:16:43, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5481, loss: 0.0876 2023-03-03 21:10:43,763 - mmseg - INFO - Iter [4500/160000] lr: 1.500e-04, eta: 11:17:23, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0887, decode.acc_seg: 96.5202, loss: 0.0887 2023-03-03 21:10:55,892 - mmseg - INFO - Iter [4550/160000] lr: 1.500e-04, eta: 11:16:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6872, loss: 0.0837 2023-03-03 21:11:07,933 - mmseg - INFO - Iter [4600/160000] lr: 1.500e-04, eta: 11:15:51, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7661, loss: 0.0823 2023-03-03 21:11:20,195 - mmseg - INFO - Iter [4650/160000] lr: 1.500e-04, eta: 11:15:12, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5533, loss: 0.0870 2023-03-03 21:11:34,746 - mmseg - INFO - Iter [4700/160000] lr: 1.500e-04, eta: 11:15:49, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5705, loss: 0.0878 2023-03-03 21:11:46,889 - mmseg - INFO - Iter [4750/160000] lr: 1.500e-04, eta: 11:15:06, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5428, loss: 0.0869 2023-03-03 21:11:58,957 - mmseg - INFO - Iter [4800/160000] lr: 1.500e-04, eta: 11:14:21, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6563, loss: 0.0836 2023-03-03 21:12:13,431 - mmseg - INFO - Iter [4850/160000] lr: 1.500e-04, eta: 11:14:54, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.6095, loss: 0.0882 2023-03-03 21:12:25,543 - mmseg - INFO - Iter [4900/160000] lr: 1.500e-04, eta: 11:14:11, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5892, loss: 0.0874 2023-03-03 21:12:37,701 - mmseg - INFO - Iter [4950/160000] lr: 1.500e-04, eta: 11:13:31, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5685, loss: 0.0870 2023-03-03 21:12:50,002 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:12:50,002 - mmseg - INFO - Iter [5000/160000] lr: 1.500e-04, eta: 11:12:55, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6508, loss: 0.0856 2023-03-03 21:13:04,568 - mmseg - INFO - Iter [5050/160000] lr: 1.500e-04, eta: 11:13:29, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5186, loss: 0.0871 2023-03-03 21:13:16,830 - mmseg - INFO - Iter [5100/160000] lr: 1.500e-04, eta: 11:12:52, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0884, decode.acc_seg: 96.5316, loss: 0.0884 2023-03-03 21:13:29,034 - mmseg - INFO - Iter [5150/160000] lr: 1.500e-04, eta: 11:12:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5763, loss: 0.0871 2023-03-03 21:13:41,242 - mmseg - INFO - Iter [5200/160000] lr: 1.500e-04, eta: 11:11:37, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6125, loss: 0.0866 2023-03-03 21:13:55,767 - mmseg - INFO - Iter [5250/160000] lr: 1.500e-04, eta: 11:12:09, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6243, loss: 0.0866 2023-03-03 21:14:07,885 - mmseg - INFO - Iter [5300/160000] lr: 1.500e-04, eta: 11:11:29, time: 0.242, data_time: 0.007, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6459, loss: 0.0851 2023-03-03 21:14:20,120 - mmseg - INFO - Iter [5350/160000] lr: 1.500e-04, eta: 11:10:53, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.5992, loss: 0.0859 2023-03-03 21:14:34,653 - mmseg - INFO - Iter [5400/160000] lr: 1.500e-04, eta: 11:11:24, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6175, loss: 0.0854 2023-03-03 21:14:46,748 - mmseg - INFO - Iter [5450/160000] lr: 1.500e-04, eta: 11:10:44, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0891, decode.acc_seg: 96.4998, loss: 0.0891 2023-03-03 21:14:58,957 - mmseg - INFO - Iter [5500/160000] lr: 1.500e-04, eta: 11:10:08, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6216, loss: 0.0857 2023-03-03 21:15:11,097 - mmseg - INFO - Iter [5550/160000] lr: 1.500e-04, eta: 11:09:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0893, decode.acc_seg: 96.4717, loss: 0.0893 2023-03-03 21:15:25,517 - mmseg - INFO - Iter [5600/160000] lr: 1.500e-04, eta: 11:09:57, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6229, loss: 0.0863 2023-03-03 21:15:37,649 - mmseg - INFO - Iter [5650/160000] lr: 1.500e-04, eta: 11:09:20, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5355, loss: 0.0878 2023-03-03 21:15:49,904 - mmseg - INFO - Iter [5700/160000] lr: 1.500e-04, eta: 11:08:47, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0905, decode.acc_seg: 96.4724, loss: 0.0905 2023-03-03 21:16:02,226 - mmseg - INFO - Iter [5750/160000] lr: 1.500e-04, eta: 11:08:15, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6681, loss: 0.0848 2023-03-03 21:16:16,648 - mmseg - INFO - Iter [5800/160000] lr: 1.500e-04, eta: 11:08:40, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6324, loss: 0.0862 2023-03-03 21:16:28,772 - mmseg - INFO - Iter [5850/160000] lr: 1.500e-04, eta: 11:08:04, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6621, loss: 0.0842 2023-03-03 21:16:40,793 - mmseg - INFO - Iter [5900/160000] lr: 1.500e-04, eta: 11:07:25, time: 0.240, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7014, loss: 0.0836 2023-03-03 21:16:52,933 - mmseg - INFO - Iter [5950/160000] lr: 1.500e-04, eta: 11:06:50, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6234, loss: 0.0846 2023-03-03 21:17:07,497 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:17:07,497 - mmseg - INFO - Iter [6000/160000] lr: 1.500e-04, eta: 11:07:18, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0897, decode.acc_seg: 96.5278, loss: 0.0897 2023-03-03 21:17:19,611 - mmseg - INFO - Iter [6050/160000] lr: 1.500e-04, eta: 11:06:42, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0884, decode.acc_seg: 96.4724, loss: 0.0884 2023-03-03 21:17:31,831 - mmseg - INFO - Iter [6100/160000] lr: 1.500e-04, eta: 11:06:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0904, decode.acc_seg: 96.4540, loss: 0.0904 2023-03-03 21:17:46,620 - mmseg - INFO - Iter [6150/160000] lr: 1.500e-04, eta: 11:06:42, time: 0.296, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6372, loss: 0.0850 2023-03-03 21:17:58,835 - mmseg - INFO - Iter [6200/160000] lr: 1.500e-04, eta: 11:06:09, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7223, loss: 0.0829 2023-03-03 21:18:11,040 - mmseg - INFO - Iter [6250/160000] lr: 1.500e-04, eta: 11:05:37, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6024, loss: 0.0857 2023-03-03 21:18:23,270 - mmseg - INFO - Iter [6300/160000] lr: 1.500e-04, eta: 11:05:05, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5851, loss: 0.0863 2023-03-03 21:18:37,743 - mmseg - INFO - Iter [6350/160000] lr: 1.500e-04, eta: 11:05:28, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7081, loss: 0.0829 2023-03-03 21:18:49,937 - mmseg - INFO - Iter [6400/160000] lr: 1.500e-04, eta: 11:04:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0892, decode.acc_seg: 96.4846, loss: 0.0892 2023-03-03 21:19:02,107 - mmseg - INFO - Iter [6450/160000] lr: 1.500e-04, eta: 11:04:24, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0902, decode.acc_seg: 96.4275, loss: 0.0902 2023-03-03 21:19:14,172 - mmseg - INFO - Iter [6500/160000] lr: 1.500e-04, eta: 11:03:49, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.6021, loss: 0.0868 2023-03-03 21:19:28,640 - mmseg - INFO - Iter [6550/160000] lr: 1.500e-04, eta: 11:04:11, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0888, decode.acc_seg: 96.5381, loss: 0.0888 2023-03-03 21:19:40,841 - mmseg - INFO - Iter [6600/160000] lr: 1.500e-04, eta: 11:03:40, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6714, loss: 0.0842 2023-03-03 21:19:52,920 - mmseg - INFO - Iter [6650/160000] lr: 1.500e-04, eta: 11:03:06, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.5869, loss: 0.0856 2023-03-03 21:20:07,311 - mmseg - INFO - Iter [6700/160000] lr: 1.500e-04, eta: 11:03:25, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5542, loss: 0.0880 2023-03-03 21:20:19,650 - mmseg - INFO - Iter [6750/160000] lr: 1.500e-04, eta: 11:02:58, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0889, decode.acc_seg: 96.4720, loss: 0.0889 2023-03-03 21:20:31,814 - mmseg - INFO - Iter [6800/160000] lr: 1.500e-04, eta: 11:02:27, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0892, decode.acc_seg: 96.4752, loss: 0.0892 2023-03-03 21:20:43,957 - mmseg - INFO - Iter [6850/160000] lr: 1.500e-04, eta: 11:01:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0889, decode.acc_seg: 96.5250, loss: 0.0889 2023-03-03 21:20:58,398 - mmseg - INFO - Iter [6900/160000] lr: 1.500e-04, eta: 11:02:15, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6364, loss: 0.0853 2023-03-03 21:21:10,598 - mmseg - INFO - Iter [6950/160000] lr: 1.500e-04, eta: 11:01:45, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6397, loss: 0.0851 2023-03-03 21:21:22,814 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:21:22,814 - mmseg - INFO - Iter [7000/160000] lr: 1.500e-04, eta: 11:01:15, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5576, loss: 0.0875 2023-03-03 21:21:34,943 - mmseg - INFO - Iter [7050/160000] lr: 1.500e-04, eta: 11:00:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6024, loss: 0.0862 2023-03-03 21:21:49,503 - mmseg - INFO - Iter [7100/160000] lr: 1.500e-04, eta: 11:01:06, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.5558, loss: 0.0872 2023-03-03 21:22:01,622 - mmseg - INFO - Iter [7150/160000] lr: 1.500e-04, eta: 11:00:35, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0881, decode.acc_seg: 96.5122, loss: 0.0881 2023-03-03 21:22:13,829 - mmseg - INFO - Iter [7200/160000] lr: 1.500e-04, eta: 11:00:06, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7263, loss: 0.0829 2023-03-03 21:22:26,026 - mmseg - INFO - Iter [7250/160000] lr: 1.500e-04, eta: 10:59:36, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5720, loss: 0.0869 2023-03-03 21:22:40,470 - mmseg - INFO - Iter [7300/160000] lr: 1.500e-04, eta: 10:59:55, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6236, loss: 0.0851 2023-03-03 21:22:52,811 - mmseg - INFO - Iter [7350/160000] lr: 1.500e-04, eta: 10:59:28, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5997, loss: 0.0861 2023-03-03 21:23:05,043 - mmseg - INFO - Iter [7400/160000] lr: 1.500e-04, eta: 10:59:01, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5529, loss: 0.0875 2023-03-03 21:23:19,624 - mmseg - INFO - Iter [7450/160000] lr: 1.500e-04, eta: 10:59:21, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6406, loss: 0.0849 2023-03-03 21:23:31,908 - mmseg - INFO - Iter [7500/160000] lr: 1.500e-04, eta: 10:58:54, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.6356, loss: 0.0869 2023-03-03 21:23:44,035 - mmseg - INFO - Iter [7550/160000] lr: 1.500e-04, eta: 10:58:24, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0910, decode.acc_seg: 96.4708, loss: 0.0910 2023-03-03 21:23:56,219 - mmseg - INFO - Iter [7600/160000] lr: 1.500e-04, eta: 10:57:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5483, loss: 0.0861 2023-03-03 21:24:10,838 - mmseg - INFO - Iter [7650/160000] lr: 1.500e-04, eta: 10:58:16, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5773, loss: 0.0875 2023-03-03 21:24:23,116 - mmseg - INFO - Iter [7700/160000] lr: 1.500e-04, eta: 10:57:50, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5920, loss: 0.0870 2023-03-03 21:24:35,247 - mmseg - INFO - Iter [7750/160000] lr: 1.500e-04, eta: 10:57:20, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7348, loss: 0.0832 2023-03-03 21:24:47,442 - mmseg - INFO - Iter [7800/160000] lr: 1.500e-04, eta: 10:56:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0906, decode.acc_seg: 96.4472, loss: 0.0906 2023-03-03 21:25:01,948 - mmseg - INFO - Iter [7850/160000] lr: 1.500e-04, eta: 10:57:10, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0899, decode.acc_seg: 96.4767, loss: 0.0899 2023-03-03 21:25:14,060 - mmseg - INFO - Iter [7900/160000] lr: 1.500e-04, eta: 10:56:40, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6561, loss: 0.0850 2023-03-03 21:25:26,194 - mmseg - INFO - Iter [7950/160000] lr: 1.500e-04, eta: 10:56:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.5866, loss: 0.0859 2023-03-03 21:25:40,683 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:25:40,683 - mmseg - INFO - Iter [8000/160000] lr: 1.500e-04, eta: 10:56:28, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0907, decode.acc_seg: 96.4280, loss: 0.0907 2023-03-03 21:25:52,845 - mmseg - INFO - Iter [8050/160000] lr: 1.500e-04, eta: 10:56:00, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7444, loss: 0.0822 2023-03-03 21:26:04,910 - mmseg - INFO - Iter [8100/160000] lr: 1.500e-04, eta: 10:55:31, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0911, decode.acc_seg: 96.4065, loss: 0.0911 2023-03-03 21:26:17,058 - mmseg - INFO - Iter [8150/160000] lr: 1.500e-04, eta: 10:55:03, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0895, decode.acc_seg: 96.5128, loss: 0.0895 2023-03-03 21:26:31,627 - mmseg - INFO - Iter [8200/160000] lr: 1.500e-04, eta: 10:55:20, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0865, decode.acc_seg: 96.5619, loss: 0.0865 2023-03-03 21:26:43,708 - mmseg - INFO - Iter [8250/160000] lr: 1.500e-04, eta: 10:54:51, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5782, loss: 0.0869 2023-03-03 21:26:55,778 - mmseg - INFO - Iter [8300/160000] lr: 1.500e-04, eta: 10:54:22, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6366, loss: 0.0854 2023-03-03 21:27:07,899 - mmseg - INFO - Iter [8350/160000] lr: 1.500e-04, eta: 10:53:54, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0888, decode.acc_seg: 96.4192, loss: 0.0888 2023-03-03 21:27:22,398 - mmseg - INFO - Iter [8400/160000] lr: 1.500e-04, eta: 10:54:10, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.5936, loss: 0.0868 2023-03-03 21:27:34,527 - mmseg - INFO - Iter [8450/160000] lr: 1.500e-04, eta: 10:53:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0885, decode.acc_seg: 96.5391, loss: 0.0885 2023-03-03 21:27:46,764 - mmseg - INFO - Iter [8500/160000] lr: 1.500e-04, eta: 10:53:17, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.4932, loss: 0.0883 2023-03-03 21:27:58,971 - mmseg - INFO - Iter [8550/160000] lr: 1.500e-04, eta: 10:52:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7237, loss: 0.0831 2023-03-03 21:28:13,499 - mmseg - INFO - Iter [8600/160000] lr: 1.500e-04, eta: 10:53:06, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6515, loss: 0.0848 2023-03-03 21:28:25,699 - mmseg - INFO - Iter [8650/160000] lr: 1.500e-04, eta: 10:52:40, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5722, loss: 0.0871 2023-03-03 21:28:37,804 - mmseg - INFO - Iter [8700/160000] lr: 1.500e-04, eta: 10:52:13, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6570, loss: 0.0861 2023-03-03 21:28:52,375 - mmseg - INFO - Iter [8750/160000] lr: 1.500e-04, eta: 10:52:28, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6637, loss: 0.0840 2023-03-03 21:29:04,562 - mmseg - INFO - Iter [8800/160000] lr: 1.500e-04, eta: 10:52:02, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6056, loss: 0.0855 2023-03-03 21:29:16,766 - mmseg - INFO - Iter [8850/160000] lr: 1.500e-04, eta: 10:51:37, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0890, decode.acc_seg: 96.5055, loss: 0.0890 2023-03-03 21:29:28,870 - mmseg - INFO - Iter [8900/160000] lr: 1.500e-04, eta: 10:51:10, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6872, loss: 0.0840 2023-03-03 21:29:43,405 - mmseg - INFO - Iter [8950/160000] lr: 1.500e-04, eta: 10:51:24, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5754, loss: 0.0875 2023-03-03 21:29:55,634 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:29:55,635 - mmseg - INFO - Iter [9000/160000] lr: 1.500e-04, eta: 10:50:59, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.6012, loss: 0.0869 2023-03-03 21:30:07,902 - mmseg - INFO - Iter [9050/160000] lr: 1.500e-04, eta: 10:50:35, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6855, loss: 0.0843 2023-03-03 21:30:20,057 - mmseg - INFO - Iter [9100/160000] lr: 1.500e-04, eta: 10:50:09, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.5192, loss: 0.0883 2023-03-03 21:30:34,612 - mmseg - INFO - Iter [9150/160000] lr: 1.500e-04, eta: 10:50:23, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0894, decode.acc_seg: 96.4948, loss: 0.0894 2023-03-03 21:30:46,972 - mmseg - INFO - Iter [9200/160000] lr: 1.500e-04, eta: 10:50:00, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6634, loss: 0.0843 2023-03-03 21:30:59,225 - mmseg - INFO - Iter [9250/160000] lr: 1.500e-04, eta: 10:49:37, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6597, loss: 0.0846 2023-03-03 21:31:11,496 - mmseg - INFO - Iter [9300/160000] lr: 1.500e-04, eta: 10:49:13, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7620, loss: 0.0813 2023-03-03 21:31:26,057 - mmseg - INFO - Iter [9350/160000] lr: 1.500e-04, eta: 10:49:27, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6374, loss: 0.0854 2023-03-03 21:31:38,256 - mmseg - INFO - Iter [9400/160000] lr: 1.500e-04, eta: 10:49:02, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0931, decode.acc_seg: 96.3733, loss: 0.0931 2023-03-03 21:31:50,381 - mmseg - INFO - Iter [9450/160000] lr: 1.500e-04, eta: 10:48:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6444, loss: 0.0853 2023-03-03 21:32:04,957 - mmseg - INFO - Iter [9500/160000] lr: 1.500e-04, eta: 10:48:49, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0915, decode.acc_seg: 96.4865, loss: 0.0915 2023-03-03 21:32:17,085 - mmseg - INFO - Iter [9550/160000] lr: 1.500e-04, eta: 10:48:24, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0888, decode.acc_seg: 96.5056, loss: 0.0888 2023-03-03 21:32:29,196 - mmseg - INFO - Iter [9600/160000] lr: 1.500e-04, eta: 10:47:58, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0873, decode.acc_seg: 96.5457, loss: 0.0873 2023-03-03 21:32:41,288 - mmseg - INFO - Iter [9650/160000] lr: 1.500e-04, eta: 10:47:32, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5506, loss: 0.0870 2023-03-03 21:32:55,847 - mmseg - INFO - Iter [9700/160000] lr: 1.500e-04, eta: 10:47:44, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5707, loss: 0.0871 2023-03-03 21:33:08,105 - mmseg - INFO - Iter [9750/160000] lr: 1.500e-04, eta: 10:47:21, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6382, loss: 0.0850 2023-03-03 21:33:20,196 - mmseg - INFO - Iter [9800/160000] lr: 1.500e-04, eta: 10:46:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0896, decode.acc_seg: 96.4497, loss: 0.0896 2023-03-03 21:33:32,316 - mmseg - INFO - Iter [9850/160000] lr: 1.500e-04, eta: 10:46:30, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5714, loss: 0.0870 2023-03-03 21:33:46,801 - mmseg - INFO - Iter [9900/160000] lr: 1.500e-04, eta: 10:46:41, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5598, loss: 0.0878 2023-03-03 21:33:58,976 - mmseg - INFO - Iter [9950/160000] lr: 1.500e-04, eta: 10:46:17, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5835, loss: 0.0861 2023-03-03 21:34:11,115 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:34:11,115 - mmseg - INFO - Iter [10000/160000] lr: 1.500e-04, eta: 10:45:52, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.5136, loss: 0.0879 2023-03-03 21:34:25,683 - mmseg - INFO - Iter [10050/160000] lr: 1.500e-04, eta: 10:46:04, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7485, loss: 0.0828 2023-03-03 21:34:37,714 - mmseg - INFO - Iter [10100/160000] lr: 1.500e-04, eta: 10:45:38, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0887, decode.acc_seg: 96.4579, loss: 0.0887 2023-03-03 21:34:49,891 - mmseg - INFO - Iter [10150/160000] lr: 1.500e-04, eta: 10:45:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6850, loss: 0.0842 2023-03-03 21:35:02,073 - mmseg - INFO - Iter [10200/160000] lr: 1.500e-04, eta: 10:44:50, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0903, decode.acc_seg: 96.4438, loss: 0.0903 2023-03-03 21:35:16,477 - mmseg - INFO - Iter [10250/160000] lr: 1.500e-04, eta: 10:44:59, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6359, loss: 0.0857 2023-03-03 21:35:28,599 - mmseg - INFO - Iter [10300/160000] lr: 1.500e-04, eta: 10:44:34, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0890, decode.acc_seg: 96.4706, loss: 0.0890 2023-03-03 21:35:40,734 - mmseg - INFO - Iter [10350/160000] lr: 1.500e-04, eta: 10:44:10, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.5808, loss: 0.0872 2023-03-03 21:35:52,995 - mmseg - INFO - Iter [10400/160000] lr: 1.500e-04, eta: 10:43:48, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5235, loss: 0.0880 2023-03-03 21:36:07,377 - mmseg - INFO - Iter [10450/160000] lr: 1.500e-04, eta: 10:43:56, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.6031, loss: 0.0870 2023-03-03 21:36:19,600 - mmseg - INFO - Iter [10500/160000] lr: 1.500e-04, eta: 10:43:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.5493, loss: 0.0882 2023-03-03 21:36:31,619 - mmseg - INFO - Iter [10550/160000] lr: 1.500e-04, eta: 10:43:08, time: 0.240, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6726, loss: 0.0840 2023-03-03 21:36:43,792 - mmseg - INFO - Iter [10600/160000] lr: 1.500e-04, eta: 10:42:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6363, loss: 0.0855 2023-03-03 21:36:58,169 - mmseg - INFO - Iter [10650/160000] lr: 1.500e-04, eta: 10:42:52, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6815, loss: 0.0846 2023-03-03 21:37:10,359 - mmseg - INFO - Iter [10700/160000] lr: 1.500e-04, eta: 10:42:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6419, loss: 0.0850 2023-03-03 21:37:22,441 - mmseg - INFO - Iter [10750/160000] lr: 1.500e-04, eta: 10:42:05, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5553, loss: 0.0875 2023-03-03 21:37:36,873 - mmseg - INFO - Iter [10800/160000] lr: 1.500e-04, eta: 10:42:13, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0890, decode.acc_seg: 96.5045, loss: 0.0890 2023-03-03 21:37:48,951 - mmseg - INFO - Iter [10850/160000] lr: 1.500e-04, eta: 10:41:48, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6318, loss: 0.0854 2023-03-03 21:38:01,081 - mmseg - INFO - Iter [10900/160000] lr: 1.500e-04, eta: 10:41:25, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0889, decode.acc_seg: 96.5193, loss: 0.0889 2023-03-03 21:38:13,226 - mmseg - INFO - Iter [10950/160000] lr: 1.500e-04, eta: 10:41:02, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7022, loss: 0.0835 2023-03-03 21:38:27,681 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:38:27,681 - mmseg - INFO - Iter [11000/160000] lr: 1.500e-04, eta: 10:41:10, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6997, loss: 0.0845 2023-03-03 21:38:39,867 - mmseg - INFO - Iter [11050/160000] lr: 1.500e-04, eta: 10:40:47, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.7048, loss: 0.0850 2023-03-03 21:38:52,025 - mmseg - INFO - Iter [11100/160000] lr: 1.500e-04, eta: 10:40:24, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6253, loss: 0.0859 2023-03-03 21:39:04,097 - mmseg - INFO - Iter [11150/160000] lr: 1.500e-04, eta: 10:40:00, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0873, decode.acc_seg: 96.5568, loss: 0.0873 2023-03-03 21:39:18,555 - mmseg - INFO - Iter [11200/160000] lr: 1.500e-04, eta: 10:40:08, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6769, loss: 0.0843 2023-03-03 21:39:30,887 - mmseg - INFO - Iter [11250/160000] lr: 1.500e-04, eta: 10:39:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0885, decode.acc_seg: 96.5334, loss: 0.0885 2023-03-03 21:39:43,110 - mmseg - INFO - Iter [11300/160000] lr: 1.500e-04, eta: 10:39:25, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.5363, loss: 0.0882 2023-03-03 21:39:57,777 - mmseg - INFO - Iter [11350/160000] lr: 1.500e-04, eta: 10:39:36, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6305, loss: 0.0852 2023-03-03 21:40:09,958 - mmseg - INFO - Iter [11400/160000] lr: 1.500e-04, eta: 10:39:13, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6409, loss: 0.0861 2023-03-03 21:40:22,226 - mmseg - INFO - Iter [11450/160000] lr: 1.500e-04, eta: 10:38:52, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5775, loss: 0.0876 2023-03-03 21:40:34,439 - mmseg - INFO - Iter [11500/160000] lr: 1.500e-04, eta: 10:38:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0921, decode.acc_seg: 96.4413, loss: 0.0921 2023-03-03 21:40:48,902 - mmseg - INFO - Iter [11550/160000] lr: 1.500e-04, eta: 10:38:38, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.5499, loss: 0.0866 2023-03-03 21:41:01,087 - mmseg - INFO - Iter [11600/160000] lr: 1.500e-04, eta: 10:38:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0890, decode.acc_seg: 96.5062, loss: 0.0890 2023-03-03 21:41:13,262 - mmseg - INFO - Iter [11650/160000] lr: 1.500e-04, eta: 10:37:53, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6629, loss: 0.0849 2023-03-03 21:41:25,349 - mmseg - INFO - Iter [11700/160000] lr: 1.500e-04, eta: 10:37:30, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0865, decode.acc_seg: 96.5948, loss: 0.0865 2023-03-03 21:41:39,990 - mmseg - INFO - Iter [11750/160000] lr: 1.500e-04, eta: 10:37:39, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0881, decode.acc_seg: 96.5473, loss: 0.0881 2023-03-03 21:41:52,166 - mmseg - INFO - Iter [11800/160000] lr: 1.500e-04, eta: 10:37:17, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.5582, loss: 0.0856 2023-03-03 21:42:04,371 - mmseg - INFO - Iter [11850/160000] lr: 1.500e-04, eta: 10:36:55, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6545, loss: 0.0858 2023-03-03 21:42:16,580 - mmseg - INFO - Iter [11900/160000] lr: 1.500e-04, eta: 10:36:34, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6138, loss: 0.0852 2023-03-03 21:42:31,200 - mmseg - INFO - Iter [11950/160000] lr: 1.500e-04, eta: 10:36:42, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7148, loss: 0.0834 2023-03-03 21:42:43,288 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:42:43,288 - mmseg - INFO - Iter [12000/160000] lr: 1.500e-04, eta: 10:36:20, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6035, loss: 0.0862 2023-03-03 21:42:55,460 - mmseg - INFO - Iter [12050/160000] lr: 1.500e-04, eta: 10:35:58, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.6113, loss: 0.0864 2023-03-03 21:43:09,928 - mmseg - INFO - Iter [12100/160000] lr: 1.500e-04, eta: 10:36:04, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0916, decode.acc_seg: 96.4070, loss: 0.0916 2023-03-03 21:43:22,125 - mmseg - INFO - Iter [12150/160000] lr: 1.500e-04, eta: 10:35:43, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5113, loss: 0.0880 2023-03-03 21:43:34,227 - mmseg - INFO - Iter [12200/160000] lr: 1.500e-04, eta: 10:35:20, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6760, loss: 0.0846 2023-03-03 21:43:46,332 - mmseg - INFO - Iter [12250/160000] lr: 1.500e-04, eta: 10:34:58, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.5705, loss: 0.0854 2023-03-03 21:44:00,880 - mmseg - INFO - Iter [12300/160000] lr: 1.500e-04, eta: 10:35:05, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0891, decode.acc_seg: 96.5038, loss: 0.0891 2023-03-03 21:44:13,098 - mmseg - INFO - Iter [12350/160000] lr: 1.500e-04, eta: 10:34:43, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6507, loss: 0.0851 2023-03-03 21:44:25,254 - mmseg - INFO - Iter [12400/160000] lr: 1.500e-04, eta: 10:34:22, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0899, decode.acc_seg: 96.4400, loss: 0.0899 2023-03-03 21:44:37,542 - mmseg - INFO - Iter [12450/160000] lr: 1.500e-04, eta: 10:34:02, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6577, loss: 0.0848 2023-03-03 21:44:51,930 - mmseg - INFO - Iter [12500/160000] lr: 1.500e-04, eta: 10:34:06, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.7162, loss: 0.0849 2023-03-03 21:45:04,047 - mmseg - INFO - Iter [12550/160000] lr: 1.500e-04, eta: 10:33:44, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6908, loss: 0.0840 2023-03-03 21:45:16,232 - mmseg - INFO - Iter [12600/160000] lr: 1.500e-04, eta: 10:33:23, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5615, loss: 0.0876 2023-03-03 21:45:30,770 - mmseg - INFO - Iter [12650/160000] lr: 1.500e-04, eta: 10:33:29, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0886, decode.acc_seg: 96.4750, loss: 0.0886 2023-03-03 21:45:43,056 - mmseg - INFO - Iter [12700/160000] lr: 1.500e-04, eta: 10:33:09, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0893, decode.acc_seg: 96.4708, loss: 0.0893 2023-03-03 21:45:55,097 - mmseg - INFO - Iter [12750/160000] lr: 1.500e-04, eta: 10:32:47, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6759, loss: 0.0845 2023-03-03 21:46:07,242 - mmseg - INFO - Iter [12800/160000] lr: 1.500e-04, eta: 10:32:25, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.5908, loss: 0.0859 2023-03-03 21:46:21,909 - mmseg - INFO - Iter [12850/160000] lr: 1.500e-04, eta: 10:32:33, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.6015, loss: 0.0864 2023-03-03 21:46:34,120 - mmseg - INFO - Iter [12900/160000] lr: 1.500e-04, eta: 10:32:12, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.6048, loss: 0.0870 2023-03-03 21:46:46,238 - mmseg - INFO - Iter [12950/160000] lr: 1.500e-04, eta: 10:31:50, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6494, loss: 0.0850 2023-03-03 21:46:58,369 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:46:58,369 - mmseg - INFO - Iter [13000/160000] lr: 1.500e-04, eta: 10:31:29, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6466, loss: 0.0856 2023-03-03 21:47:13,033 - mmseg - INFO - Iter [13050/160000] lr: 1.500e-04, eta: 10:31:36, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.5088, loss: 0.0882 2023-03-03 21:47:25,138 - mmseg - INFO - Iter [13100/160000] lr: 1.500e-04, eta: 10:31:14, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6143, loss: 0.0858 2023-03-03 21:47:37,182 - mmseg - INFO - Iter [13150/160000] lr: 1.500e-04, eta: 10:30:52, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.6724, loss: 0.0871 2023-03-03 21:47:49,165 - mmseg - INFO - Iter [13200/160000] lr: 1.500e-04, eta: 10:30:29, time: 0.240, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6361, loss: 0.0848 2023-03-03 21:48:03,697 - mmseg - INFO - Iter [13250/160000] lr: 1.500e-04, eta: 10:30:34, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7058, loss: 0.0839 2023-03-03 21:48:15,786 - mmseg - INFO - Iter [13300/160000] lr: 1.500e-04, eta: 10:30:12, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7156, loss: 0.0837 2023-03-03 21:48:27,872 - mmseg - INFO - Iter [13350/160000] lr: 1.500e-04, eta: 10:29:51, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.5969, loss: 0.0862 2023-03-03 21:48:42,267 - mmseg - INFO - Iter [13400/160000] lr: 1.500e-04, eta: 10:29:54, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6911, loss: 0.0839 2023-03-03 21:48:54,363 - mmseg - INFO - Iter [13450/160000] lr: 1.500e-04, eta: 10:29:33, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.5580, loss: 0.0862 2023-03-03 21:49:06,424 - mmseg - INFO - Iter [13500/160000] lr: 1.500e-04, eta: 10:29:11, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6208, loss: 0.0851 2023-03-03 21:49:18,609 - mmseg - INFO - Iter [13550/160000] lr: 1.500e-04, eta: 10:28:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6252, loss: 0.0862 2023-03-03 21:49:33,151 - mmseg - INFO - Iter [13600/160000] lr: 1.500e-04, eta: 10:28:56, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6334, loss: 0.0859 2023-03-03 21:49:45,603 - mmseg - INFO - Iter [13650/160000] lr: 1.500e-04, eta: 10:28:38, time: 0.249, data_time: 0.007, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6425, loss: 0.0856 2023-03-03 21:49:57,741 - mmseg - INFO - Iter [13700/160000] lr: 1.500e-04, eta: 10:28:17, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6500, loss: 0.0851 2023-03-03 21:50:09,843 - mmseg - INFO - Iter [13750/160000] lr: 1.500e-04, eta: 10:27:56, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6902, loss: 0.0837 2023-03-03 21:50:24,484 - mmseg - INFO - Iter [13800/160000] lr: 1.500e-04, eta: 10:28:02, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6423, loss: 0.0851 2023-03-03 21:50:36,491 - mmseg - INFO - Iter [13850/160000] lr: 1.500e-04, eta: 10:27:39, time: 0.240, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0897, decode.acc_seg: 96.4968, loss: 0.0897 2023-03-03 21:50:48,578 - mmseg - INFO - Iter [13900/160000] lr: 1.500e-04, eta: 10:27:18, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5707, loss: 0.0869 2023-03-03 21:51:00,791 - mmseg - INFO - Iter [13950/160000] lr: 1.500e-04, eta: 10:26:58, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6995, loss: 0.0839 2023-03-03 21:51:15,176 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:51:15,176 - mmseg - INFO - Iter [14000/160000] lr: 1.500e-04, eta: 10:27:01, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6834, loss: 0.0846 2023-03-03 21:51:27,312 - mmseg - INFO - Iter [14050/160000] lr: 1.500e-04, eta: 10:26:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0894, decode.acc_seg: 96.5127, loss: 0.0894 2023-03-03 21:51:39,524 - mmseg - INFO - Iter [14100/160000] lr: 1.500e-04, eta: 10:26:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6208, loss: 0.0861 2023-03-03 21:51:54,062 - mmseg - INFO - Iter [14150/160000] lr: 1.500e-04, eta: 10:26:25, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.6011, loss: 0.0871 2023-03-03 21:52:06,260 - mmseg - INFO - Iter [14200/160000] lr: 1.500e-04, eta: 10:26:05, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6576, loss: 0.0847 2023-03-03 21:52:18,397 - mmseg - INFO - Iter [14250/160000] lr: 1.500e-04, eta: 10:25:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7883, loss: 0.0820 2023-03-03 21:52:30,752 - mmseg - INFO - Iter [14300/160000] lr: 1.500e-04, eta: 10:25:26, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0877, decode.acc_seg: 96.5363, loss: 0.0877 2023-03-03 21:52:45,158 - mmseg - INFO - Iter [14350/160000] lr: 1.500e-04, eta: 10:25:29, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6568, loss: 0.0844 2023-03-03 21:52:57,277 - mmseg - INFO - Iter [14400/160000] lr: 1.500e-04, eta: 10:25:08, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0905, decode.acc_seg: 96.4395, loss: 0.0905 2023-03-03 21:53:09,533 - mmseg - INFO - Iter [14450/160000] lr: 1.500e-04, eta: 10:24:49, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.6205, loss: 0.0864 2023-03-03 21:53:21,759 - mmseg - INFO - Iter [14500/160000] lr: 1.500e-04, eta: 10:24:30, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0867, decode.acc_seg: 96.5797, loss: 0.0867 2023-03-03 21:53:36,338 - mmseg - INFO - Iter [14550/160000] lr: 1.500e-04, eta: 10:24:34, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0889, decode.acc_seg: 96.5122, loss: 0.0889 2023-03-03 21:53:48,639 - mmseg - INFO - Iter [14600/160000] lr: 1.500e-04, eta: 10:24:15, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6326, loss: 0.0856 2023-03-03 21:54:00,774 - mmseg - INFO - Iter [14650/160000] lr: 1.500e-04, eta: 10:23:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0907, decode.acc_seg: 96.4518, loss: 0.0907 2023-03-03 21:54:15,170 - mmseg - INFO - Iter [14700/160000] lr: 1.500e-04, eta: 10:23:57, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6593, loss: 0.0844 2023-03-03 21:54:27,454 - mmseg - INFO - Iter [14750/160000] lr: 1.500e-04, eta: 10:23:38, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7725, loss: 0.0822 2023-03-03 21:54:39,677 - mmseg - INFO - Iter [14800/160000] lr: 1.500e-04, eta: 10:23:19, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0896, decode.acc_seg: 96.4863, loss: 0.0896 2023-03-03 21:54:51,843 - mmseg - INFO - Iter [14850/160000] lr: 1.500e-04, eta: 10:22:59, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.5499, loss: 0.0879 2023-03-03 21:55:06,288 - mmseg - INFO - Iter [14900/160000] lr: 1.500e-04, eta: 10:23:01, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6074, loss: 0.0856 2023-03-03 21:55:18,327 - mmseg - INFO - Iter [14950/160000] lr: 1.500e-04, eta: 10:22:40, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6798, loss: 0.0845 2023-03-03 21:55:30,430 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:55:30,430 - mmseg - INFO - Iter [15000/160000] lr: 1.500e-04, eta: 10:22:20, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6116, loss: 0.0857 2023-03-03 21:55:42,520 - mmseg - INFO - Iter [15050/160000] lr: 1.500e-04, eta: 10:21:59, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6265, loss: 0.0859 2023-03-03 21:55:57,131 - mmseg - INFO - Iter [15100/160000] lr: 1.500e-04, eta: 10:22:03, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6263, loss: 0.0853 2023-03-03 21:56:09,346 - mmseg - INFO - Iter [15150/160000] lr: 1.500e-04, eta: 10:21:44, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7124, loss: 0.0836 2023-03-03 21:56:21,383 - mmseg - INFO - Iter [15200/160000] lr: 1.500e-04, eta: 10:21:23, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0889, decode.acc_seg: 96.5495, loss: 0.0889 2023-03-03 21:56:33,577 - mmseg - INFO - Iter [15250/160000] lr: 1.500e-04, eta: 10:21:04, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6157, loss: 0.0850 2023-03-03 21:56:47,958 - mmseg - INFO - Iter [15300/160000] lr: 1.500e-04, eta: 10:21:05, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0873, decode.acc_seg: 96.5674, loss: 0.0873 2023-03-03 21:57:00,023 - mmseg - INFO - Iter [15350/160000] lr: 1.500e-04, eta: 10:20:45, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0891, decode.acc_seg: 96.4925, loss: 0.0891 2023-03-03 21:57:12,267 - mmseg - INFO - Iter [15400/160000] lr: 1.500e-04, eta: 10:20:26, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5931, loss: 0.0863 2023-03-03 21:57:26,753 - mmseg - INFO - Iter [15450/160000] lr: 1.500e-04, eta: 10:20:28, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6598, loss: 0.0842 2023-03-03 21:57:38,780 - mmseg - INFO - Iter [15500/160000] lr: 1.500e-04, eta: 10:20:07, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7128, loss: 0.0829 2023-03-03 21:57:50,895 - mmseg - INFO - Iter [15550/160000] lr: 1.500e-04, eta: 10:19:47, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.6100, loss: 0.0872 2023-03-03 21:58:02,991 - mmseg - INFO - Iter [15600/160000] lr: 1.500e-04, eta: 10:19:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6351, loss: 0.0858 2023-03-03 21:58:17,474 - mmseg - INFO - Iter [15650/160000] lr: 1.500e-04, eta: 10:19:29, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6584, loss: 0.0849 2023-03-03 21:58:29,590 - mmseg - INFO - Iter [15700/160000] lr: 1.500e-04, eta: 10:19:09, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.5841, loss: 0.0862 2023-03-03 21:58:41,998 - mmseg - INFO - Iter [15750/160000] lr: 1.500e-04, eta: 10:18:52, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5311, loss: 0.0876 2023-03-03 21:58:54,257 - mmseg - INFO - Iter [15800/160000] lr: 1.500e-04, eta: 10:18:34, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5159, loss: 0.0863 2023-03-03 21:59:08,792 - mmseg - INFO - Iter [15850/160000] lr: 1.500e-04, eta: 10:18:36, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0891, decode.acc_seg: 96.4874, loss: 0.0891 2023-03-03 21:59:21,008 - mmseg - INFO - Iter [15900/160000] lr: 1.500e-04, eta: 10:18:17, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5625, loss: 0.0876 2023-03-03 21:59:33,102 - mmseg - INFO - Iter [15950/160000] lr: 1.500e-04, eta: 10:17:57, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6000, loss: 0.0863 2023-03-03 21:59:47,584 - mmseg - INFO - Swap parameters (after train) after iter [16000] 2023-03-03 21:59:47,600 - mmseg - INFO - Saving checkpoint at 16000 iterations 2023-03-03 21:59:49,043 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 21:59:49,043 - mmseg - INFO - Iter [16000/160000] lr: 1.500e-04, eta: 10:18:12, time: 0.319, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7076, loss: 0.0835 2023-03-03 22:14:59,929 - mmseg - INFO - per class results: 2023-03-03 22:14:59,930 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.49,98.49,98.49,98.49,98.49,98.49,98.49,98.49,98.49,98.49,98.49 | | sidewalk | 87.23,87.24,87.24,87.24,87.25,87.25,87.25,87.25,87.25,87.26,87.26 | | building | 93.28,93.27,93.27,93.27,93.27,93.27,93.27,93.27,93.27,93.27,93.27 | | wall | 53.01,52.99,52.98,52.96,53.0,52.98,52.91,52.92,52.92,52.92,53.03 | | fence | 63.49,63.5,63.47,63.47,63.44,63.43,63.45,63.43,63.45,63.44,63.43 | | pole | 70.56,70.55,70.55,70.56,70.55,70.55,70.55,70.54,70.54,70.54,70.54 | | traffic light | 75.11,75.1,75.08,75.06,75.07,75.07,75.02,75.02,75.02,74.99,75.03 | | traffic sign | 83.12,83.12,83.12,83.12,83.11,83.11,83.12,83.13,83.11,83.1,83.14 | | vegetation | 92.91,92.91,92.91,92.91,92.91,92.91,92.9,92.9,92.9,92.9,92.9 | | terrain | 65.0,65.01,65.01,65.03,65.02,65.04,65.04,65.02,65.01,65.02,65.06 | | sky | 95.14,95.13,95.13,95.13,95.13,95.13,95.12,95.11,95.11,95.1,95.11 | | person | 84.63,84.63,84.63,84.64,84.62,84.62,84.62,84.61,84.6,84.6,84.63 | | rider | 66.51,66.49,66.49,66.51,66.46,66.47,66.48,66.44,66.39,66.37,66.47 | | car | 95.92,95.92,95.92,95.92,95.92,95.92,95.92,95.92,95.92,95.92,95.92 | | truck | 83.76,83.79,83.76,83.78,83.74,83.73,83.71,83.68,83.65,83.64,83.55 | | bus | 92.07,92.06,92.06,92.07,92.07,92.07,92.07,92.07,92.07,92.06,92.03 | | train | 86.2,86.2,86.16,86.26,86.05,86.07,86.06,86.11,86.1,86.1,86.02 | | motorcycle | 68.96,68.97,68.96,68.98,68.97,69.0,69.0,68.95,68.87,68.91,69.1 | | bicycle | 79.72,79.72,79.73,79.74,79.74,79.73,79.72,79.73,79.72,79.72,79.71 | +---------------+-------------------------------------------------------------------+ 2023-03-03 22:14:59,930 - mmseg - INFO - Summary: 2023-03-03 22:14:59,931 - mmseg - INFO - +-----------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +-----------------------------------------------------------------+ | 80.79,80.8,80.79,80.8,80.78,80.78,80.77,80.77,80.76,80.76,80.77 | +-----------------------------------------------------------------+ 2023-03-03 22:15:01,307 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_16000.pth. 2023-03-03 22:15:01,307 - mmseg - INFO - Best mIoU is 0.8077 at 16000 iter. 2023-03-03 22:15:01,307 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:15:01,307 - mmseg - INFO - Iter(val) [63] mIoU: [0.8079, 0.808, 0.8079, 0.808, 0.8078, 0.8078, 0.8077, 0.8077, 0.8076, 0.8076, 0.8077], copy_paste: 80.79,80.8,80.79,80.8,80.78,80.78,80.77,80.77,80.76,80.76,80.77 2023-03-03 22:15:01,312 - mmseg - INFO - Swap parameters (before train) before iter [16001] 2023-03-03 22:15:13,800 - mmseg - INFO - Iter [16050/160000] lr: 1.500e-04, eta: 12:34:18, time: 18.495, data_time: 18.254, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6977, loss: 0.0841 2023-03-03 22:15:26,440 - mmseg - INFO - Iter [16100/160000] lr: 1.500e-04, eta: 12:33:34, time: 0.253, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6329, loss: 0.0851 2023-03-03 22:15:38,884 - mmseg - INFO - Iter [16150/160000] lr: 1.500e-04, eta: 12:32:50, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0903, decode.acc_seg: 96.5161, loss: 0.0903 2023-03-03 22:15:53,490 - mmseg - INFO - Iter [16200/160000] lr: 1.500e-04, eta: 12:32:24, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0898, decode.acc_seg: 96.5105, loss: 0.0898 2023-03-03 22:16:05,905 - mmseg - INFO - Iter [16250/160000] lr: 1.500e-04, eta: 12:31:39, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0867, decode.acc_seg: 96.5689, loss: 0.0867 2023-03-03 22:16:18,197 - mmseg - INFO - Iter [16300/160000] lr: 1.500e-04, eta: 12:30:54, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0907, decode.acc_seg: 96.3994, loss: 0.0907 2023-03-03 22:16:30,637 - mmseg - INFO - Iter [16350/160000] lr: 1.500e-04, eta: 12:30:10, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6463, loss: 0.0850 2023-03-03 22:16:45,200 - mmseg - INFO - Iter [16400/160000] lr: 1.500e-04, eta: 12:29:44, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6574, loss: 0.0856 2023-03-03 22:16:57,400 - mmseg - INFO - Iter [16450/160000] lr: 1.500e-04, eta: 12:28:59, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6082, loss: 0.0862 2023-03-03 22:17:09,683 - mmseg - INFO - Iter [16500/160000] lr: 1.500e-04, eta: 12:28:14, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0902, decode.acc_seg: 96.4656, loss: 0.0902 2023-03-03 22:17:21,877 - mmseg - INFO - Iter [16550/160000] lr: 1.500e-04, eta: 12:27:28, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5984, loss: 0.0861 2023-03-03 22:17:36,562 - mmseg - INFO - Iter [16600/160000] lr: 1.500e-04, eta: 12:27:04, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.6011, loss: 0.0868 2023-03-03 22:17:48,761 - mmseg - INFO - Iter [16650/160000] lr: 1.500e-04, eta: 12:26:19, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.5105, loss: 0.0882 2023-03-03 22:18:00,908 - mmseg - INFO - Iter [16700/160000] lr: 1.500e-04, eta: 12:25:34, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5595, loss: 0.0878 2023-03-03 22:18:15,423 - mmseg - INFO - Iter [16750/160000] lr: 1.500e-04, eta: 12:25:09, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.5198, loss: 0.0883 2023-03-03 22:18:27,739 - mmseg - INFO - Iter [16800/160000] lr: 1.500e-04, eta: 12:24:25, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6509, loss: 0.0848 2023-03-03 22:18:40,062 - mmseg - INFO - Iter [16850/160000] lr: 1.500e-04, eta: 12:23:42, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7623, loss: 0.0819 2023-03-03 22:18:52,370 - mmseg - INFO - Iter [16900/160000] lr: 1.500e-04, eta: 12:22:58, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5381, loss: 0.0876 2023-03-03 22:19:06,906 - mmseg - INFO - Iter [16950/160000] lr: 1.500e-04, eta: 12:22:34, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7555, loss: 0.0819 2023-03-03 22:19:19,175 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:19:19,175 - mmseg - INFO - Iter [17000/160000] lr: 1.500e-04, eta: 12:21:51, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6464, loss: 0.0849 2023-03-03 22:19:31,328 - mmseg - INFO - Iter [17050/160000] lr: 1.500e-04, eta: 12:21:06, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0891, decode.acc_seg: 96.5023, loss: 0.0891 2023-03-03 22:19:43,471 - mmseg - INFO - Iter [17100/160000] lr: 1.500e-04, eta: 12:20:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0877, decode.acc_seg: 96.5513, loss: 0.0877 2023-03-03 22:19:58,000 - mmseg - INFO - Iter [17150/160000] lr: 1.500e-04, eta: 12:19:58, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6672, loss: 0.0840 2023-03-03 22:20:10,253 - mmseg - INFO - Iter [17200/160000] lr: 1.500e-04, eta: 12:19:16, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6242, loss: 0.0857 2023-03-03 22:20:22,386 - mmseg - INFO - Iter [17250/160000] lr: 1.500e-04, eta: 12:18:32, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6813, loss: 0.0836 2023-03-03 22:20:36,852 - mmseg - INFO - Iter [17300/160000] lr: 1.500e-04, eta: 12:18:08, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0908, decode.acc_seg: 96.4317, loss: 0.0908 2023-03-03 22:20:48,977 - mmseg - INFO - Iter [17350/160000] lr: 1.500e-04, eta: 12:17:24, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0865, decode.acc_seg: 96.5954, loss: 0.0865 2023-03-03 22:21:01,177 - mmseg - INFO - Iter [17400/160000] lr: 1.500e-04, eta: 12:16:42, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5860, loss: 0.0861 2023-03-03 22:21:13,323 - mmseg - INFO - Iter [17450/160000] lr: 1.500e-04, eta: 12:15:59, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6410, loss: 0.0844 2023-03-03 22:21:27,819 - mmseg - INFO - Iter [17500/160000] lr: 1.500e-04, eta: 12:15:35, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6851, loss: 0.0840 2023-03-03 22:21:39,957 - mmseg - INFO - Iter [17550/160000] lr: 1.500e-04, eta: 12:14:53, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5545, loss: 0.0874 2023-03-03 22:21:52,155 - mmseg - INFO - Iter [17600/160000] lr: 1.500e-04, eta: 12:14:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7312, loss: 0.0828 2023-03-03 22:22:04,500 - mmseg - INFO - Iter [17650/160000] lr: 1.500e-04, eta: 12:13:30, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6241, loss: 0.0863 2023-03-03 22:22:19,008 - mmseg - INFO - Iter [17700/160000] lr: 1.500e-04, eta: 12:13:07, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5025, loss: 0.0878 2023-03-03 22:22:31,165 - mmseg - INFO - Iter [17750/160000] lr: 1.500e-04, eta: 12:12:25, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7520, loss: 0.0821 2023-03-03 22:22:43,320 - mmseg - INFO - Iter [17800/160000] lr: 1.500e-04, eta: 12:11:43, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.7074, loss: 0.0840 2023-03-03 22:22:55,488 - mmseg - INFO - Iter [17850/160000] lr: 1.500e-04, eta: 12:11:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7206, loss: 0.0834 2023-03-03 22:23:10,119 - mmseg - INFO - Iter [17900/160000] lr: 1.500e-04, eta: 12:10:40, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7240, loss: 0.0828 2023-03-03 22:23:22,227 - mmseg - INFO - Iter [17950/160000] lr: 1.500e-04, eta: 12:09:58, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0894, decode.acc_seg: 96.4990, loss: 0.0894 2023-03-03 22:23:34,468 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:23:34,468 - mmseg - INFO - Iter [18000/160000] lr: 1.500e-04, eta: 12:09:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8155, loss: 0.0802 2023-03-03 22:23:49,110 - mmseg - INFO - Iter [18050/160000] lr: 1.500e-04, eta: 12:08:56, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5579, loss: 0.0880 2023-03-03 22:24:01,194 - mmseg - INFO - Iter [18100/160000] lr: 1.500e-04, eta: 12:08:15, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0873, decode.acc_seg: 96.6029, loss: 0.0873 2023-03-03 22:24:13,394 - mmseg - INFO - Iter [18150/160000] lr: 1.500e-04, eta: 12:07:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6433, loss: 0.0851 2023-03-03 22:24:25,482 - mmseg - INFO - Iter [18200/160000] lr: 1.500e-04, eta: 12:06:53, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7007, loss: 0.0831 2023-03-03 22:24:39,897 - mmseg - INFO - Iter [18250/160000] lr: 1.500e-04, eta: 12:06:30, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6781, loss: 0.0856 2023-03-03 22:24:52,028 - mmseg - INFO - Iter [18300/160000] lr: 1.500e-04, eta: 12:05:50, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5813, loss: 0.0874 2023-03-03 22:25:04,143 - mmseg - INFO - Iter [18350/160000] lr: 1.500e-04, eta: 12:05:09, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5674, loss: 0.0876 2023-03-03 22:25:16,200 - mmseg - INFO - Iter [18400/160000] lr: 1.500e-04, eta: 12:04:29, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6671, loss: 0.0850 2023-03-03 22:25:30,656 - mmseg - INFO - Iter [18450/160000] lr: 1.500e-04, eta: 12:04:07, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0920, decode.acc_seg: 96.4383, loss: 0.0920 2023-03-03 22:25:42,864 - mmseg - INFO - Iter [18500/160000] lr: 1.500e-04, eta: 12:03:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6229, loss: 0.0863 2023-03-03 22:25:54,977 - mmseg - INFO - Iter [18550/160000] lr: 1.500e-04, eta: 12:02:47, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6757, loss: 0.0850 2023-03-03 22:26:07,202 - mmseg - INFO - Iter [18600/160000] lr: 1.500e-04, eta: 12:02:08, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5955, loss: 0.0869 2023-03-03 22:26:21,767 - mmseg - INFO - Iter [18650/160000] lr: 1.500e-04, eta: 12:01:47, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5987, loss: 0.0869 2023-03-03 22:26:34,003 - mmseg - INFO - Iter [18700/160000] lr: 1.500e-04, eta: 12:01:09, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6607, loss: 0.0844 2023-03-03 22:26:46,280 - mmseg - INFO - Iter [18750/160000] lr: 1.500e-04, eta: 12:00:30, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0917, decode.acc_seg: 96.3873, loss: 0.0917 2023-03-03 22:27:00,871 - mmseg - INFO - Iter [18800/160000] lr: 1.500e-04, eta: 12:00:10, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5965, loss: 0.0861 2023-03-03 22:27:13,083 - mmseg - INFO - Iter [18850/160000] lr: 1.500e-04, eta: 11:59:31, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6443, loss: 0.0840 2023-03-03 22:27:25,219 - mmseg - INFO - Iter [18900/160000] lr: 1.500e-04, eta: 11:58:52, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.5939, loss: 0.0866 2023-03-03 22:27:37,410 - mmseg - INFO - Iter [18950/160000] lr: 1.500e-04, eta: 11:58:14, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6737, loss: 0.0842 2023-03-03 22:27:51,936 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:27:51,936 - mmseg - INFO - Iter [19000/160000] lr: 1.500e-04, eta: 11:57:53, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0886, decode.acc_seg: 96.5514, loss: 0.0886 2023-03-03 22:28:04,142 - mmseg - INFO - Iter [19050/160000] lr: 1.500e-04, eta: 11:57:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5959, loss: 0.0861 2023-03-03 22:28:16,222 - mmseg - INFO - Iter [19100/160000] lr: 1.500e-04, eta: 11:56:37, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0873, decode.acc_seg: 96.5456, loss: 0.0873 2023-03-03 22:28:28,528 - mmseg - INFO - Iter [19150/160000] lr: 1.500e-04, eta: 11:56:00, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6617, loss: 0.0843 2023-03-03 22:28:43,049 - mmseg - INFO - Iter [19200/160000] lr: 1.500e-04, eta: 11:55:39, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6791, loss: 0.0842 2023-03-03 22:28:55,283 - mmseg - INFO - Iter [19250/160000] lr: 1.500e-04, eta: 11:55:02, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0871, decode.acc_seg: 96.5762, loss: 0.0871 2023-03-03 22:29:07,424 - mmseg - INFO - Iter [19300/160000] lr: 1.500e-04, eta: 11:54:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5574, loss: 0.0880 2023-03-03 22:29:22,004 - mmseg - INFO - Iter [19350/160000] lr: 1.500e-04, eta: 11:54:04, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0877, decode.acc_seg: 96.5296, loss: 0.0877 2023-03-03 22:29:34,216 - mmseg - INFO - Iter [19400/160000] lr: 1.500e-04, eta: 11:53:27, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8210, loss: 0.0809 2023-03-03 22:29:46,335 - mmseg - INFO - Iter [19450/160000] lr: 1.500e-04, eta: 11:52:49, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6105, loss: 0.0854 2023-03-03 22:29:58,635 - mmseg - INFO - Iter [19500/160000] lr: 1.500e-04, eta: 11:52:13, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5284, loss: 0.0878 2023-03-03 22:30:13,097 - mmseg - INFO - Iter [19550/160000] lr: 1.500e-04, eta: 11:51:52, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6420, loss: 0.0847 2023-03-03 22:30:25,353 - mmseg - INFO - Iter [19600/160000] lr: 1.500e-04, eta: 11:51:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6625, loss: 0.0835 2023-03-03 22:30:37,637 - mmseg - INFO - Iter [19650/160000] lr: 1.500e-04, eta: 11:50:40, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.5330, loss: 0.0883 2023-03-03 22:30:49,856 - mmseg - INFO - Iter [19700/160000] lr: 1.500e-04, eta: 11:50:04, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6613, loss: 0.0852 2023-03-03 22:31:04,369 - mmseg - INFO - Iter [19750/160000] lr: 1.500e-04, eta: 11:49:44, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0878, decode.acc_seg: 96.5430, loss: 0.0878 2023-03-03 22:31:16,698 - mmseg - INFO - Iter [19800/160000] lr: 1.500e-04, eta: 11:49:08, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7030, loss: 0.0836 2023-03-03 22:31:28,790 - mmseg - INFO - Iter [19850/160000] lr: 1.500e-04, eta: 11:48:31, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.5648, loss: 0.0872 2023-03-03 22:31:40,917 - mmseg - INFO - Iter [19900/160000] lr: 1.500e-04, eta: 11:47:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7267, loss: 0.0831 2023-03-03 22:31:55,455 - mmseg - INFO - Iter [19950/160000] lr: 1.500e-04, eta: 11:47:35, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6275, loss: 0.0846 2023-03-03 22:32:07,805 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:32:07,805 - mmseg - INFO - Iter [20000/160000] lr: 1.500e-04, eta: 11:47:00, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0893, decode.acc_seg: 96.5491, loss: 0.0893 2023-03-03 22:32:19,937 - mmseg - INFO - Iter [20050/160000] lr: 7.500e-05, eta: 11:46:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6506, loss: 0.0850 2023-03-03 22:32:34,562 - mmseg - INFO - Iter [20100/160000] lr: 7.500e-05, eta: 11:46:05, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7107, loss: 0.0833 2023-03-03 22:32:46,699 - mmseg - INFO - Iter [20150/160000] lr: 7.500e-05, eta: 11:45:29, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6676, loss: 0.0848 2023-03-03 22:32:58,929 - mmseg - INFO - Iter [20200/160000] lr: 7.500e-05, eta: 11:44:54, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.6103, loss: 0.0860 2023-03-03 22:33:11,091 - mmseg - INFO - Iter [20250/160000] lr: 7.500e-05, eta: 11:44:19, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6304, loss: 0.0859 2023-03-03 22:33:25,557 - mmseg - INFO - Iter [20300/160000] lr: 7.500e-05, eta: 11:43:59, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7670, loss: 0.0817 2023-03-03 22:33:37,748 - mmseg - INFO - Iter [20350/160000] lr: 7.500e-05, eta: 11:43:24, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5745, loss: 0.0863 2023-03-03 22:33:49,964 - mmseg - INFO - Iter [20400/160000] lr: 7.500e-05, eta: 11:42:49, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7183, loss: 0.0831 2023-03-03 22:34:02,098 - mmseg - INFO - Iter [20450/160000] lr: 7.500e-05, eta: 11:42:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5709, loss: 0.0875 2023-03-03 22:34:16,691 - mmseg - INFO - Iter [20500/160000] lr: 7.500e-05, eta: 11:41:55, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6664, loss: 0.0848 2023-03-03 22:34:28,935 - mmseg - INFO - Iter [20550/160000] lr: 7.500e-05, eta: 11:41:21, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7641, loss: 0.0826 2023-03-03 22:34:41,130 - mmseg 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INFO - Iter [20850/160000] lr: 7.500e-05, eta: 11:38:26, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.6130, loss: 0.0870 2023-03-03 22:35:59,052 - mmseg - INFO - Iter [20900/160000] lr: 7.500e-05, eta: 11:37:52, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6579, loss: 0.0852 2023-03-03 22:36:11,301 - mmseg - INFO - Iter [20950/160000] lr: 7.500e-05, eta: 11:37:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7731, loss: 0.0820 2023-03-03 22:36:23,559 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:36:23,559 - mmseg - INFO - Iter [21000/160000] lr: 7.500e-05, eta: 11:36:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6708, loss: 0.0850 2023-03-03 22:36:38,039 - mmseg - INFO - Iter [21050/160000] lr: 7.500e-05, eta: 11:36:26, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0890, decode.acc_seg: 96.5287, loss: 0.0890 2023-03-03 22:36:50,270 - mmseg - INFO - Iter [21100/160000] lr: 7.500e-05, eta: 11:35:52, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6293, loss: 0.0857 2023-03-03 22:37:02,441 - mmseg - INFO - Iter [21150/160000] lr: 7.500e-05, eta: 11:35:19, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6486, loss: 0.0848 2023-03-03 22:37:14,598 - mmseg - INFO - Iter [21200/160000] lr: 7.500e-05, eta: 11:34:45, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6680, loss: 0.0845 2023-03-03 22:37:29,013 - mmseg - INFO - Iter [21250/160000] lr: 7.500e-05, eta: 11:34:26, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7499, loss: 0.0829 2023-03-03 22:37:41,265 - mmseg - INFO - Iter [21300/160000] lr: 7.500e-05, eta: 11:33:53, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.6802, loss: 0.0829 2023-03-03 22:37:53,407 - mmseg - INFO - Iter [21350/160000] lr: 7.500e-05, eta: 11:33:19, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7234, loss: 0.0825 2023-03-03 22:38:08,064 - mmseg - INFO - Iter [21400/160000] lr: 7.500e-05, eta: 11:33:02, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6851, loss: 0.0852 2023-03-03 22:38:20,171 - mmseg - INFO - Iter [21450/160000] lr: 7.500e-05, eta: 11:32:28, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7944, loss: 0.0821 2023-03-03 22:38:32,267 - mmseg - INFO - Iter [21500/160000] lr: 7.500e-05, eta: 11:31:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.5465, loss: 0.0883 2023-03-03 22:38:44,487 - mmseg - INFO - Iter [21550/160000] lr: 7.500e-05, eta: 11:31:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.6885, loss: 0.0831 2023-03-03 22:38:59,019 - mmseg - INFO - Iter [21600/160000] lr: 7.500e-05, eta: 11:31:04, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6596, loss: 0.0847 2023-03-03 22:39:11,185 - mmseg - INFO - Iter [21650/160000] lr: 7.500e-05, eta: 11:30:31, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7758, loss: 0.0832 2023-03-03 22:39:23,431 - mmseg - INFO - Iter [21700/160000] lr: 7.500e-05, eta: 11:29:59, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6337, loss: 0.0866 2023-03-03 22:39:35,606 - mmseg - INFO - Iter [21750/160000] lr: 7.500e-05, eta: 11:29:26, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7283, loss: 0.0829 2023-03-03 22:39:50,130 - mmseg - INFO - Iter [21800/160000] lr: 7.500e-05, eta: 11:29:08, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7178, loss: 0.0821 2023-03-03 22:40:02,321 - mmseg - INFO - Iter [21850/160000] lr: 7.500e-05, eta: 11:28:36, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.7115, loss: 0.0848 2023-03-03 22:40:14,472 - mmseg - INFO - Iter [21900/160000] lr: 7.500e-05, eta: 11:28:03, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7667, loss: 0.0812 2023-03-03 22:40:28,994 - mmseg - INFO - Iter [21950/160000] lr: 7.500e-05, eta: 11:27:45, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6282, loss: 0.0849 2023-03-03 22:40:41,410 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:40:41,410 - mmseg - INFO - Iter [22000/160000] lr: 7.500e-05, eta: 11:27:15, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0881, decode.acc_seg: 96.5246, loss: 0.0881 2023-03-03 22:40:53,610 - mmseg - INFO - Iter [22050/160000] lr: 7.500e-05, eta: 11:26:43, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7235, loss: 0.0832 2023-03-03 22:41:05,777 - mmseg - INFO - Iter [22100/160000] lr: 7.500e-05, eta: 11:26:10, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6143, loss: 0.0852 2023-03-03 22:41:20,285 - mmseg - INFO - Iter [22150/160000] lr: 7.500e-05, eta: 11:25:53, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7318, loss: 0.0819 2023-03-03 22:41:32,483 - mmseg - INFO - Iter [22200/160000] lr: 7.500e-05, eta: 11:25:21, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0882, decode.acc_seg: 96.5523, loss: 0.0882 2023-03-03 22:41:44,777 - mmseg - INFO - Iter [22250/160000] lr: 7.500e-05, eta: 11:24:50, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6985, loss: 0.0835 2023-03-03 22:41:57,011 - mmseg - INFO - Iter [22300/160000] lr: 7.500e-05, eta: 11:24:18, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.7030, loss: 0.0870 2023-03-03 22:42:11,620 - mmseg - INFO - Iter [22350/160000] lr: 7.500e-05, eta: 11:24:02, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7581, loss: 0.0829 2023-03-03 22:42:23,740 - mmseg - INFO - Iter [22400/160000] lr: 7.500e-05, eta: 11:23:30, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7032, loss: 0.0837 2023-03-03 22:42:35,935 - mmseg - INFO - Iter [22450/160000] lr: 7.500e-05, eta: 11:22:58, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5576, loss: 0.0875 2023-03-03 22:42:48,014 - mmseg - INFO - Iter [22500/160000] lr: 7.500e-05, eta: 11:22:26, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.7108, loss: 0.0844 2023-03-03 22:43:02,526 - mmseg - INFO - Iter [22550/160000] lr: 7.500e-05, eta: 11:22:09, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.6928, loss: 0.0834 2023-03-03 22:43:14,846 - mmseg - INFO - Iter [22600/160000] lr: 7.500e-05, eta: 11:21:38, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0867, decode.acc_seg: 96.6005, loss: 0.0867 2023-03-03 22:43:27,019 - mmseg - INFO - Iter [22650/160000] lr: 7.500e-05, eta: 11:21:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6934, loss: 0.0842 2023-03-03 22:43:41,702 - mmseg - INFO - Iter [22700/160000] lr: 7.500e-05, eta: 11:20:51, time: 0.294, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6718, loss: 0.0845 2023-03-03 22:43:53,913 - mmseg - INFO - Iter [22750/160000] lr: 7.500e-05, eta: 11:20:20, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7214, loss: 0.0833 2023-03-03 22:44:06,149 - mmseg - INFO - Iter [22800/160000] lr: 7.500e-05, eta: 11:19:49, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7520, loss: 0.0830 2023-03-03 22:44:18,276 - mmseg - INFO - Iter [22850/160000] lr: 7.500e-05, eta: 11:19:18, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6144, loss: 0.0858 2023-03-03 22:44:32,879 - mmseg - INFO - Iter [22900/160000] lr: 7.500e-05, eta: 11:19:01, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6321, loss: 0.0843 2023-03-03 22:44:45,158 - mmseg - INFO - Iter [22950/160000] lr: 7.500e-05, eta: 11:18:31, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7315, loss: 0.0827 2023-03-03 22:44:57,405 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:44:57,406 - mmseg - INFO - Iter [23000/160000] lr: 7.500e-05, eta: 11:18:01, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6612, loss: 0.0849 2023-03-03 22:45:09,592 - mmseg - INFO - Iter [23050/160000] lr: 7.500e-05, eta: 11:17:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6371, loss: 0.0850 2023-03-03 22:45:24,099 - mmseg - INFO - Iter [23100/160000] lr: 7.500e-05, eta: 11:17:13, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6678, loss: 0.0851 2023-03-03 22:45:36,466 - mmseg - INFO - Iter [23150/160000] lr: 7.500e-05, eta: 11:16:44, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6034, loss: 0.0852 2023-03-03 22:45:48,661 - mmseg - INFO - Iter [23200/160000] lr: 7.500e-05, eta: 11:16:13, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7232, loss: 0.0832 2023-03-03 22:46:00,864 - mmseg - INFO - Iter [23250/160000] lr: 7.500e-05, eta: 11:15:43, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6597, loss: 0.0849 2023-03-03 22:46:15,457 - mmseg - INFO - Iter [23300/160000] lr: 7.500e-05, eta: 11:15:27, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6468, loss: 0.0842 2023-03-03 22:46:27,577 - mmseg - INFO - Iter [23350/160000] lr: 7.500e-05, eta: 11:14:56, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6296, loss: 0.0866 2023-03-03 22:46:39,643 - mmseg - INFO - Iter [23400/160000] lr: 7.500e-05, eta: 11:14:25, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.6020, loss: 0.0868 2023-03-03 22:46:54,186 - mmseg - INFO - Iter [23450/160000] lr: 7.500e-05, eta: 11:14:09, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7260, loss: 0.0828 2023-03-03 22:47:06,284 - mmseg - INFO - Iter [23500/160000] lr: 7.500e-05, eta: 11:13:39, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.5730, loss: 0.0860 2023-03-03 22:47:18,418 - mmseg - INFO - Iter [23550/160000] lr: 7.500e-05, eta: 11:13:08, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7149, loss: 0.0831 2023-03-03 22:47:30,570 - mmseg - INFO - Iter [23600/160000] lr: 7.500e-05, eta: 11:12:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6419, loss: 0.0858 2023-03-03 22:47:45,099 - mmseg - INFO - Iter [23650/160000] lr: 7.500e-05, eta: 11:12:22, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6983, loss: 0.0835 2023-03-03 22:47:57,234 - mmseg - INFO - Iter [23700/160000] lr: 7.500e-05, eta: 11:11:52, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6827, loss: 0.0845 2023-03-03 22:48:09,368 - mmseg - INFO - Iter [23750/160000] lr: 7.500e-05, eta: 11:11:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7516, loss: 0.0822 2023-03-03 22:48:21,627 - mmseg - INFO - Iter [23800/160000] lr: 7.500e-05, eta: 11:10:53, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7545, loss: 0.0812 2023-03-03 22:48:36,117 - mmseg - INFO - Iter [23850/160000] lr: 7.500e-05, eta: 11:10:36, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0924, decode.acc_seg: 96.4855, loss: 0.0924 2023-03-03 22:48:48,375 - mmseg - INFO - Iter [23900/160000] lr: 7.500e-05, eta: 11:10:07, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7475, loss: 0.0832 2023-03-03 22:49:00,508 - mmseg - INFO - Iter [23950/160000] lr: 7.500e-05, eta: 11:09:37, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.5305, loss: 0.0879 2023-03-03 22:49:14,938 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:49:14,938 - mmseg - INFO - Iter [24000/160000] lr: 7.500e-05, eta: 11:09:21, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7066, loss: 0.0838 2023-03-03 22:49:27,056 - mmseg - INFO - Iter [24050/160000] lr: 7.500e-05, eta: 11:08:51, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8120, loss: 0.0816 2023-03-03 22:49:39,355 - mmseg - INFO - Iter [24100/160000] lr: 7.500e-05, eta: 11:08:22, time: 0.246, data_time: 0.007, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7453, loss: 0.0824 2023-03-03 22:49:51,616 - mmseg - INFO - Iter [24150/160000] lr: 7.500e-05, eta: 11:07:53, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6584, loss: 0.0845 2023-03-03 22:50:06,065 - mmseg - INFO - Iter [24200/160000] lr: 7.500e-05, eta: 11:07:37, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6937, loss: 0.0839 2023-03-03 22:50:18,275 - mmseg - INFO - Iter [24250/160000] lr: 7.500e-05, eta: 11:07:08, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.6743, loss: 0.0832 2023-03-03 22:50:30,536 - mmseg - INFO - Iter [24300/160000] lr: 7.500e-05, eta: 11:06:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7335, loss: 0.0827 2023-03-03 22:50:42,759 - mmseg - INFO - Iter [24350/160000] lr: 7.500e-05, eta: 11:06:11, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0894, decode.acc_seg: 96.5234, loss: 0.0894 2023-03-03 22:50:57,290 - mmseg - INFO - Iter [24400/160000] lr: 7.500e-05, eta: 11:05:55, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.6909, loss: 0.0831 2023-03-03 22:51:09,517 - mmseg - INFO - Iter [24450/160000] lr: 7.500e-05, eta: 11:05:26, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7283, loss: 0.0837 2023-03-03 22:51:21,645 - mmseg - INFO - Iter [24500/160000] lr: 7.500e-05, eta: 11:04:57, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8147, loss: 0.0807 2023-03-03 22:51:33,743 - mmseg - INFO - Iter [24550/160000] lr: 7.500e-05, eta: 11:04:28, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.5619, loss: 0.0876 2023-03-03 22:51:48,237 - mmseg - INFO - Iter [24600/160000] lr: 7.500e-05, eta: 11:04:12, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.6917, loss: 0.0834 2023-03-03 22:52:00,518 - mmseg - INFO - Iter [24650/160000] lr: 7.500e-05, eta: 11:03:44, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.6732, loss: 0.0833 2023-03-03 22:52:12,831 - mmseg - INFO - Iter [24700/160000] lr: 7.500e-05, eta: 11:03:16, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8017, loss: 0.0805 2023-03-03 22:52:27,370 - mmseg - INFO - Iter [24750/160000] lr: 7.500e-05, eta: 11:03:00, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6996, loss: 0.0839 2023-03-03 22:52:39,501 - mmseg - INFO - Iter [24800/160000] lr: 7.500e-05, eta: 11:02:32, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7127, loss: 0.0829 2023-03-03 22:52:51,595 - mmseg - INFO - Iter [24850/160000] lr: 7.500e-05, eta: 11:02:03, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.6680, loss: 0.0834 2023-03-03 22:53:03,680 - mmseg - INFO - Iter [24900/160000] lr: 7.500e-05, eta: 11:01:34, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6477, loss: 0.0849 2023-03-03 22:53:18,132 - mmseg - INFO - Iter [24950/160000] lr: 7.500e-05, eta: 11:01:18, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7772, loss: 0.0824 2023-03-03 22:53:30,495 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:53:30,496 - mmseg - INFO - Iter [25000/160000] lr: 7.500e-05, eta: 11:00:51, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6154, loss: 0.0851 2023-03-03 22:53:42,687 - mmseg - INFO - Iter [25050/160000] lr: 7.500e-05, eta: 11:00:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7622, loss: 0.0818 2023-03-03 22:53:55,014 - mmseg - INFO - Iter [25100/160000] lr: 7.500e-05, eta: 10:59:55, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.5919, loss: 0.0860 2023-03-03 22:54:09,569 - mmseg - INFO - Iter [25150/160000] lr: 7.500e-05, eta: 10:59:40, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6808, loss: 0.0844 2023-03-03 22:54:21,926 - mmseg - INFO - Iter [25200/160000] lr: 7.500e-05, eta: 10:59:13, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7482, loss: 0.0827 2023-03-03 22:54:34,048 - mmseg - INFO - Iter [25250/160000] lr: 7.500e-05, eta: 10:58:44, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8046, loss: 0.0808 2023-03-03 22:54:48,469 - mmseg - INFO - Iter [25300/160000] lr: 7.500e-05, eta: 10:58:28, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6471, loss: 0.0849 2023-03-03 22:55:00,814 - mmseg - INFO - Iter [25350/160000] lr: 7.500e-05, eta: 10:58:01, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6703, loss: 0.0845 2023-03-03 22:55:13,004 - mmseg - INFO - Iter [25400/160000] lr: 7.500e-05, eta: 10:57:34, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8176, loss: 0.0814 2023-03-03 22:55:25,215 - mmseg - INFO - Iter [25450/160000] lr: 7.500e-05, eta: 10:57:06, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.6327, loss: 0.0868 2023-03-03 22:55:39,696 - mmseg - INFO - Iter [25500/160000] lr: 7.500e-05, eta: 10:56:51, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0881, decode.acc_seg: 96.5957, loss: 0.0881 2023-03-03 22:55:51,862 - mmseg - INFO - Iter [25550/160000] lr: 7.500e-05, eta: 10:56:23, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7422, loss: 0.0828 2023-03-03 22:56:04,108 - mmseg - INFO - Iter [25600/160000] lr: 7.500e-05, eta: 10:55:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7504, loss: 0.0824 2023-03-03 22:56:16,187 - mmseg - INFO - Iter [25650/160000] lr: 7.500e-05, eta: 10:55:28, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6048, loss: 0.0856 2023-03-03 22:56:30,894 - mmseg - INFO - Iter [25700/160000] lr: 7.500e-05, eta: 10:55:13, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6694, loss: 0.0849 2023-03-03 22:56:43,036 - mmseg - INFO - Iter [25750/160000] lr: 7.500e-05, eta: 10:54:46, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6637, loss: 0.0861 2023-03-03 22:56:55,211 - mmseg - INFO - Iter [25800/160000] lr: 7.500e-05, eta: 10:54:18, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6870, loss: 0.0837 2023-03-03 22:57:07,394 - mmseg - INFO - Iter [25850/160000] lr: 7.500e-05, eta: 10:53:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6917, loss: 0.0835 2023-03-03 22:57:21,945 - mmseg - INFO - Iter [25900/160000] lr: 7.500e-05, eta: 10:53:36, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7365, loss: 0.0829 2023-03-03 22:57:34,165 - mmseg - INFO - Iter [25950/160000] lr: 7.500e-05, eta: 10:53:09, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6465, loss: 0.0845 2023-03-03 22:57:46,262 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 22:57:46,262 - mmseg - INFO - Iter [26000/160000] lr: 7.500e-05, eta: 10:52:41, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6017, loss: 0.0863 2023-03-03 22:58:00,747 - mmseg - INFO - Iter [26050/160000] lr: 7.500e-05, eta: 10:52:26, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7612, loss: 0.0824 2023-03-03 22:58:12,971 - mmseg - INFO - Iter [26100/160000] lr: 7.500e-05, eta: 10:51:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7824, loss: 0.0816 2023-03-03 22:58:25,178 - mmseg - INFO - Iter [26150/160000] lr: 7.500e-05, eta: 10:51:32, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6715, loss: 0.0847 2023-03-03 22:58:37,284 - mmseg - INFO - Iter [26200/160000] lr: 7.500e-05, eta: 10:51:05, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6916, loss: 0.0839 2023-03-03 22:58:51,816 - mmseg - INFO - Iter [26250/160000] lr: 7.500e-05, eta: 10:50:50, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0874, decode.acc_seg: 96.5233, loss: 0.0874 2023-03-03 22:59:04,077 - mmseg - INFO - Iter [26300/160000] lr: 7.500e-05, eta: 10:50:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.6416, loss: 0.0860 2023-03-03 22:59:16,370 - mmseg - INFO - Iter [26350/160000] lr: 7.500e-05, eta: 10:49:57, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6370, loss: 0.0849 2023-03-03 22:59:28,490 - mmseg - INFO - Iter [26400/160000] lr: 7.500e-05, eta: 10:49:30, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8837, loss: 0.0798 2023-03-03 22:59:43,099 - mmseg - INFO - Iter [26450/160000] lr: 7.500e-05, eta: 10:49:16, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6927, loss: 0.0849 2023-03-03 22:59:55,308 - mmseg - INFO - Iter [26500/160000] lr: 7.500e-05, eta: 10:48:49, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7159, loss: 0.0826 2023-03-03 23:00:07,493 - mmseg - INFO - Iter [26550/160000] lr: 7.500e-05, eta: 10:48:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7343, loss: 0.0829 2023-03-03 23:00:21,920 - mmseg - INFO - Iter [26600/160000] lr: 7.500e-05, eta: 10:48:07, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7551, loss: 0.0827 2023-03-03 23:00:34,072 - mmseg - INFO - Iter [26650/160000] lr: 7.500e-05, eta: 10:47:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0877, decode.acc_seg: 96.5051, loss: 0.0877 2023-03-03 23:00:46,218 - mmseg - INFO - Iter [26700/160000] lr: 7.500e-05, eta: 10:47:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7547, loss: 0.0818 2023-03-03 23:00:58,444 - mmseg - INFO - Iter [26750/160000] lr: 7.500e-05, eta: 10:46:48, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6351, loss: 0.0855 2023-03-03 23:01:12,899 - mmseg - INFO - Iter [26800/160000] lr: 7.500e-05, eta: 10:46:32, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7342, loss: 0.0826 2023-03-03 23:01:25,124 - mmseg - INFO - Iter [26850/160000] lr: 7.500e-05, eta: 10:46:06, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6667, loss: 0.0839 2023-03-03 23:01:37,233 - mmseg - INFO - Iter [26900/160000] lr: 7.500e-05, eta: 10:45:40, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7804, loss: 0.0821 2023-03-03 23:01:49,420 - mmseg - INFO - Iter [26950/160000] lr: 7.500e-05, eta: 10:45:13, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7753, loss: 0.0813 2023-03-03 23:02:03,919 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:02:03,919 - mmseg - INFO - Iter [27000/160000] lr: 7.500e-05, eta: 10:44:59, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6690, loss: 0.0840 2023-03-03 23:02:16,068 - mmseg - INFO - Iter [27050/160000] lr: 7.500e-05, eta: 10:44:32, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6802, loss: 0.0840 2023-03-03 23:02:28,319 - mmseg - INFO - Iter [27100/160000] lr: 7.500e-05, eta: 10:44:06, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.5811, loss: 0.0862 2023-03-03 23:02:40,450 - mmseg - INFO - Iter [27150/160000] lr: 7.500e-05, eta: 10:43:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7345, loss: 0.0825 2023-03-03 23:02:54,968 - mmseg - INFO - Iter [27200/160000] lr: 7.500e-05, eta: 10:43:25, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6569, loss: 0.0854 2023-03-03 23:03:07,147 - mmseg - INFO - Iter [27250/160000] lr: 7.500e-05, eta: 10:42:59, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7864, loss: 0.0822 2023-03-03 23:03:19,350 - mmseg - INFO - Iter [27300/160000] lr: 7.500e-05, eta: 10:42:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7149, loss: 0.0830 2023-03-03 23:03:33,898 - mmseg - INFO - Iter [27350/160000] lr: 7.500e-05, eta: 10:42:19, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.5850, loss: 0.0859 2023-03-03 23:03:45,960 - mmseg - INFO - Iter [27400/160000] lr: 7.500e-05, eta: 10:41:53, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7421, loss: 0.0819 2023-03-03 23:03:58,099 - mmseg - INFO - Iter [27450/160000] lr: 7.500e-05, eta: 10:41:27, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8155, loss: 0.0806 2023-03-03 23:04:10,225 - mmseg - INFO - Iter [27500/160000] lr: 7.500e-05, eta: 10:41:01, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.6683, loss: 0.0829 2023-03-03 23:04:24,807 - mmseg - INFO - Iter [27550/160000] lr: 7.500e-05, eta: 10:40:46, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7385, loss: 0.0833 2023-03-03 23:04:36,928 - mmseg - INFO - Iter [27600/160000] lr: 7.500e-05, eta: 10:40:20, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7560, loss: 0.0815 2023-03-03 23:04:49,106 - mmseg - INFO - Iter [27650/160000] lr: 7.500e-05, eta: 10:39:55, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7508, loss: 0.0830 2023-03-03 23:05:01,304 - mmseg - INFO - Iter [27700/160000] lr: 7.500e-05, eta: 10:39:29, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7713, loss: 0.0821 2023-03-03 23:05:15,844 - mmseg - INFO - Iter [27750/160000] lr: 7.500e-05, eta: 10:39:15, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.6942, loss: 0.0827 2023-03-03 23:05:28,261 - mmseg - INFO - Iter [27800/160000] lr: 7.500e-05, eta: 10:38:51, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6106, loss: 0.0861 2023-03-03 23:05:40,564 - mmseg - INFO - Iter [27850/160000] lr: 7.500e-05, eta: 10:38:26, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6727, loss: 0.0850 2023-03-03 23:05:52,724 - mmseg - INFO - Iter [27900/160000] lr: 7.500e-05, eta: 10:38:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.6729, loss: 0.0828 2023-03-03 23:06:07,279 - mmseg - INFO - Iter [27950/160000] lr: 7.500e-05, eta: 10:37:46, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7457, loss: 0.0823 2023-03-03 23:06:19,622 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:06:19,622 - mmseg - INFO - Iter [28000/160000] lr: 7.500e-05, eta: 10:37:21, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.6784, loss: 0.0827 2023-03-03 23:06:31,769 - mmseg - INFO - Iter [28050/160000] lr: 7.500e-05, eta: 10:36:56, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7410, loss: 0.0830 2023-03-03 23:06:46,323 - mmseg - INFO - Iter [28100/160000] lr: 7.500e-05, eta: 10:36:42, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7290, loss: 0.0827 2023-03-03 23:06:58,623 - mmseg - INFO - Iter [28150/160000] lr: 7.500e-05, eta: 10:36:17, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6601, loss: 0.0861 2023-03-03 23:07:10,802 - mmseg - INFO - Iter [28200/160000] lr: 7.500e-05, eta: 10:35:52, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7085, loss: 0.0833 2023-03-03 23:07:22,868 - mmseg - INFO - Iter [28250/160000] lr: 7.500e-05, eta: 10:35:26, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7388, loss: 0.0838 2023-03-03 23:07:37,593 - mmseg - INFO - Iter [28300/160000] lr: 7.500e-05, eta: 10:35:13, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8091, loss: 0.0805 2023-03-03 23:07:49,911 - mmseg - INFO - Iter [28350/160000] lr: 7.500e-05, eta: 10:34:48, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.9119, loss: 0.0790 2023-03-03 23:08:02,211 - mmseg - INFO - Iter [28400/160000] lr: 7.500e-05, eta: 10:34:24, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7936, loss: 0.0817 2023-03-03 23:08:14,410 - mmseg - INFO - Iter [28450/160000] lr: 7.500e-05, eta: 10:33:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7024, loss: 0.0828 2023-03-03 23:08:29,014 - mmseg - INFO - Iter [28500/160000] lr: 7.500e-05, eta: 10:33:45, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7737, loss: 0.0823 2023-03-03 23:08:41,383 - mmseg - INFO - Iter [28550/160000] lr: 7.500e-05, eta: 10:33:21, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6777, loss: 0.0842 2023-03-03 23:08:53,600 - mmseg - INFO - Iter [28600/160000] lr: 7.500e-05, eta: 10:32:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.7045, loss: 0.0842 2023-03-03 23:09:07,992 - mmseg - INFO - Iter [28650/160000] lr: 7.500e-05, eta: 10:32:42, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7049, loss: 0.0830 2023-03-03 23:09:20,214 - mmseg - INFO - Iter [28700/160000] lr: 7.500e-05, eta: 10:32:17, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.5372, loss: 0.0868 2023-03-03 23:09:32,402 - mmseg - INFO - Iter [28750/160000] lr: 7.500e-05, eta: 10:31:52, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7523, loss: 0.0818 2023-03-03 23:09:44,735 - mmseg - INFO - Iter [28800/160000] lr: 7.500e-05, eta: 10:31:28, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6168, loss: 0.0853 2023-03-03 23:09:59,287 - mmseg - INFO - Iter [28850/160000] lr: 7.500e-05, eta: 10:31:14, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7153, loss: 0.0830 2023-03-03 23:10:11,410 - mmseg - INFO - Iter [28900/160000] lr: 7.500e-05, eta: 10:30:49, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6278, loss: 0.0861 2023-03-03 23:10:23,525 - mmseg - INFO - Iter [28950/160000] lr: 7.500e-05, eta: 10:30:24, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6482, loss: 0.0847 2023-03-03 23:10:35,848 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:10:35,848 - mmseg - INFO - Iter [29000/160000] lr: 7.500e-05, eta: 10:30:00, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7107, loss: 0.0827 2023-03-03 23:10:50,320 - mmseg - INFO - Iter [29050/160000] lr: 7.500e-05, eta: 10:29:46, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6885, loss: 0.0845 2023-03-03 23:11:02,471 - mmseg - INFO - Iter [29100/160000] lr: 7.500e-05, eta: 10:29:21, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6494, loss: 0.0845 2023-03-03 23:11:14,540 - mmseg - INFO - Iter [29150/160000] lr: 7.500e-05, eta: 10:28:56, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0893, decode.acc_seg: 96.5328, loss: 0.0893 2023-03-03 23:11:26,892 - mmseg - INFO - Iter [29200/160000] lr: 7.500e-05, eta: 10:28:33, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6441, loss: 0.0853 2023-03-03 23:11:41,403 - mmseg - INFO - Iter [29250/160000] lr: 7.500e-05, eta: 10:28:19, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6279, loss: 0.0861 2023-03-03 23:11:53,542 - mmseg - INFO - Iter [29300/160000] lr: 7.500e-05, eta: 10:27:54, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6754, loss: 0.0843 2023-03-03 23:12:05,825 - mmseg - INFO - Iter [29350/160000] lr: 7.500e-05, eta: 10:27:30, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7041, loss: 0.0826 2023-03-03 23:12:20,421 - mmseg - INFO - Iter [29400/160000] lr: 7.500e-05, eta: 10:27:17, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7185, loss: 0.0829 2023-03-03 23:12:32,646 - mmseg - INFO - Iter [29450/160000] lr: 7.500e-05, eta: 10:26:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5485, loss: 0.0869 2023-03-03 23:12:44,778 - mmseg - INFO - Iter [29500/160000] lr: 7.500e-05, eta: 10:26:28, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7800, loss: 0.0821 2023-03-03 23:12:57,034 - mmseg - INFO - Iter [29550/160000] lr: 7.500e-05, eta: 10:26:04, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6087, loss: 0.0862 2023-03-03 23:13:11,489 - mmseg - INFO - Iter [29600/160000] lr: 7.500e-05, eta: 10:25:50, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.7028, loss: 0.0840 2023-03-03 23:13:23,647 - mmseg - INFO - Iter [29650/160000] lr: 7.500e-05, eta: 10:25:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0867, decode.acc_seg: 96.6018, loss: 0.0867 2023-03-03 23:13:35,811 - mmseg - INFO - Iter [29700/160000] lr: 7.500e-05, eta: 10:25:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6420, loss: 0.0853 2023-03-03 23:13:48,031 - mmseg - INFO - Iter [29750/160000] lr: 7.500e-05, eta: 10:24:38, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6408, loss: 0.0852 2023-03-03 23:14:02,702 - mmseg - INFO - Iter [29800/160000] lr: 7.500e-05, eta: 10:24:25, time: 0.294, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7690, loss: 0.0811 2023-03-03 23:14:14,865 - mmseg - INFO - Iter [29850/160000] lr: 7.500e-05, eta: 10:24:01, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7279, loss: 0.0830 2023-03-03 23:14:27,099 - mmseg - INFO - Iter [29900/160000] lr: 7.500e-05, eta: 10:23:37, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7628, loss: 0.0816 2023-03-03 23:14:41,644 - mmseg - INFO - Iter [29950/160000] lr: 7.500e-05, eta: 10:23:23, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6758, loss: 0.0851 2023-03-03 23:14:53,810 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:14:53,811 - mmseg - INFO - Iter [30000/160000] lr: 7.500e-05, eta: 10:22:59, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8133, loss: 0.0812 2023-03-03 23:15:05,941 - mmseg - INFO - Iter [30050/160000] lr: 7.500e-05, eta: 10:22:35, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6328, loss: 0.0851 2023-03-03 23:15:18,103 - mmseg - INFO - Iter [30100/160000] lr: 7.500e-05, eta: 10:22:11, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6725, loss: 0.0841 2023-03-03 23:15:32,595 - mmseg - INFO - Iter [30150/160000] lr: 7.500e-05, eta: 10:21:57, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.6524, loss: 0.0870 2023-03-03 23:15:44,869 - mmseg - INFO - Iter [30200/160000] lr: 7.500e-05, eta: 10:21:34, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7508, loss: 0.0824 2023-03-03 23:15:57,163 - mmseg - INFO - Iter [30250/160000] lr: 7.500e-05, eta: 10:21:11, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7279, loss: 0.0835 2023-03-03 23:16:09,286 - mmseg - INFO - Iter [30300/160000] lr: 7.500e-05, eta: 10:20:47, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0897, decode.acc_seg: 96.5454, loss: 0.0897 2023-03-03 23:16:23,685 - mmseg - INFO - Iter [30350/160000] lr: 7.500e-05, eta: 10:20:33, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.5666, loss: 0.0868 2023-03-03 23:16:35,938 - mmseg - INFO - Iter [30400/160000] lr: 7.500e-05, eta: 10:20:09, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7180, loss: 0.0824 2023-03-03 23:16:48,095 - mmseg - INFO - Iter [30450/160000] lr: 7.500e-05, eta: 10:19:45, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6825, loss: 0.0843 2023-03-03 23:17:00,184 - mmseg - INFO - Iter [30500/160000] lr: 7.500e-05, eta: 10:19:22, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0905, decode.acc_seg: 96.6444, loss: 0.0905 2023-03-03 23:17:14,732 - mmseg - INFO - Iter [30550/160000] lr: 7.500e-05, eta: 10:19:08, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6456, loss: 0.0850 2023-03-03 23:17:26,939 - mmseg - INFO - Iter [30600/160000] lr: 7.500e-05, eta: 10:18:45, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.7048, loss: 0.0843 2023-03-03 23:17:39,190 - mmseg - INFO - Iter [30650/160000] lr: 7.500e-05, eta: 10:18:21, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7709, loss: 0.0811 2023-03-03 23:17:53,594 - mmseg - INFO - Iter [30700/160000] lr: 7.500e-05, eta: 10:18:07, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7588, loss: 0.0820 2023-03-03 23:18:05,767 - mmseg - INFO - Iter [30750/160000] lr: 7.500e-05, eta: 10:17:44, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7427, loss: 0.0821 2023-03-03 23:18:17,868 - mmseg - INFO - Iter [30800/160000] lr: 7.500e-05, eta: 10:17:20, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7178, loss: 0.0833 2023-03-03 23:18:29,974 - mmseg - INFO - Iter [30850/160000] lr: 7.500e-05, eta: 10:16:56, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7268, loss: 0.0829 2023-03-03 23:18:44,560 - mmseg - INFO - Iter [30900/160000] lr: 7.500e-05, eta: 10:16:43, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6937, loss: 0.0841 2023-03-03 23:18:56,719 - mmseg - INFO - Iter [30950/160000] lr: 7.500e-05, eta: 10:16:20, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6221, loss: 0.0850 2023-03-03 23:19:08,817 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:19:08,817 - mmseg - INFO - Iter [31000/160000] lr: 7.500e-05, eta: 10:15:56, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6543, loss: 0.0856 2023-03-03 23:19:20,975 - mmseg - INFO - Iter [31050/160000] lr: 7.500e-05, eta: 10:15:33, time: 0.243, data_time: 0.010, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6492, loss: 0.0843 2023-03-03 23:19:35,505 - mmseg - INFO - Iter [31100/160000] lr: 7.500e-05, eta: 10:15:19, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7395, loss: 0.0825 2023-03-03 23:19:47,772 - mmseg - INFO - Iter [31150/160000] lr: 7.500e-05, eta: 10:14:57, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6818, loss: 0.0849 2023-03-03 23:19:59,968 - mmseg - INFO - Iter [31200/160000] lr: 7.500e-05, eta: 10:14:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7110, loss: 0.0839 2023-03-03 23:20:14,407 - mmseg - INFO - Iter [31250/160000] lr: 7.500e-05, eta: 10:14:20, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.6999, loss: 0.0828 2023-03-03 23:20:26,635 - mmseg - INFO - Iter [31300/160000] lr: 7.500e-05, eta: 10:13:57, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6662, loss: 0.0845 2023-03-03 23:20:38,793 - mmseg - INFO - Iter [31350/160000] lr: 7.500e-05, eta: 10:13:34, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7468, loss: 0.0829 2023-03-03 23:20:50,982 - mmseg - INFO - Iter [31400/160000] lr: 7.500e-05, eta: 10:13:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6468, loss: 0.0844 2023-03-03 23:21:05,537 - mmseg - INFO - Iter [31450/160000] lr: 7.500e-05, eta: 10:12:57, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7654, loss: 0.0816 2023-03-03 23:21:17,726 - mmseg - INFO - Iter [31500/160000] lr: 7.500e-05, eta: 10:12:34, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6133, loss: 0.0859 2023-03-03 23:21:29,894 - mmseg - INFO - Iter [31550/160000] lr: 7.500e-05, eta: 10:12:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.6951, loss: 0.0827 2023-03-03 23:21:42,018 - mmseg - INFO - Iter [31600/160000] lr: 7.500e-05, eta: 10:11:48, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6671, loss: 0.0850 2023-03-03 23:21:56,483 - mmseg - INFO - Iter [31650/160000] lr: 7.500e-05, eta: 10:11:35, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7601, loss: 0.0821 2023-03-03 23:22:08,622 - mmseg - INFO - Iter [31700/160000] lr: 7.500e-05, eta: 10:11:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7128, loss: 0.0831 2023-03-03 23:22:20,736 - mmseg - INFO - Iter [31750/160000] lr: 7.500e-05, eta: 10:10:49, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6636, loss: 0.0845 2023-03-03 23:22:32,956 - mmseg - INFO - Iter [31800/160000] lr: 7.500e-05, eta: 10:10:26, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7442, loss: 0.0838 2023-03-03 23:22:47,630 - mmseg - INFO - Iter [31850/160000] lr: 7.500e-05, eta: 10:10:13, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.5330, loss: 0.0883 2023-03-03 23:22:59,820 - mmseg - INFO - Iter [31900/160000] lr: 7.500e-05, eta: 10:09:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7287, loss: 0.0833 2023-03-03 23:23:12,012 - mmseg - INFO - Iter [31950/160000] lr: 7.500e-05, eta: 10:09:28, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7672, loss: 0.0825 2023-03-03 23:23:26,495 - mmseg - INFO - Swap parameters (after train) after iter [32000] 2023-03-03 23:23:26,510 - mmseg - INFO - Saving checkpoint at 32000 iterations 2023-03-03 23:23:27,877 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:23:27,877 - mmseg - INFO - Iter [32000/160000] lr: 7.500e-05, eta: 10:09:20, time: 0.317, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5109, loss: 0.0880 2023-03-03 23:38:21,799 - mmseg - INFO - per class results: 2023-03-03 23:38:21,800 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.53,98.53,98.53,98.53,98.53,98.53,98.53,98.53,98.53,98.53,98.53 | | sidewalk | 87.49,87.5,87.51,87.51,87.52,87.52,87.52,87.52,87.53,87.53,87.51 | | building | 93.3,93.31,93.31,93.31,93.31,93.31,93.31,93.32,93.32,93.32,93.32 | | wall | 53.61,53.62,53.66,53.68,53.7,53.74,53.79,53.85,53.87,53.89,53.92 | | fence | 63.82,63.81,63.83,63.87,63.88,63.94,63.95,63.97,64.01,64.0,63.99 | | pole | 70.87,70.88,70.88,70.88,70.88,70.89,70.89,70.89,70.88,70.88,70.88 | | traffic light | 75.36,75.35,75.34,75.34,75.33,75.3,75.32,75.32,75.3,75.29,75.3 | | traffic sign | 83.28,83.28,83.28,83.29,83.29,83.29,83.29,83.29,83.29,83.28,83.3 | | vegetation | 92.94,92.94,92.94,92.94,92.94,92.94,92.94,92.95,92.95,92.95,92.94 | | terrain | 65.54,65.55,65.55,65.56,65.54,65.57,65.55,65.55,65.56,65.54,65.52 | | sky | 95.19,95.19,95.19,95.19,95.2,95.2,95.2,95.19,95.2,95.21,95.21 | | person | 84.71,84.7,84.7,84.71,84.7,84.71,84.7,84.71,84.7,84.69,84.73 | | rider | 66.7,66.69,66.69,66.71,66.69,66.73,66.73,66.73,66.67,66.63,66.82 | | car | 95.95,95.96,95.96,95.97,95.97,95.97,95.97,95.97,95.97,95.97,95.96 | | truck | 84.24,84.35,84.36,84.55,84.54,84.59,84.56,84.54,84.61,84.7,84.41 | | bus | 92.24,92.27,92.26,92.28,92.27,92.3,92.29,92.29,92.29,92.3,92.3 | | train | 86.23,86.26,86.27,86.3,86.29,86.25,86.25,86.19,86.28,86.29,86.37 | | motorcycle | 69.14,69.15,69.17,69.18,69.24,69.2,69.22,69.22,69.27,69.26,69.28 | | bicycle | 79.82,79.82,79.82,79.82,79.83,79.83,79.83,79.81,79.83,79.83,79.82 | +---------------+-------------------------------------------------------------------+ 2023-03-03 23:38:21,800 - mmseg - INFO - Summary: 2023-03-03 23:38:21,800 - mmseg - INFO - +------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +------------------------------------------------------------------+ | 81.0,81.01,81.01,81.03,81.03,81.04,81.04,81.04,81.06,81.06,81.06 | +------------------------------------------------------------------+ 2023-03-03 23:38:21,847 - mmseg - INFO - The previous best checkpoint /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune/best_mIoU_iter_16000.pth was removed 2023-03-03 23:38:23,124 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_32000.pth. 2023-03-03 23:38:23,125 - mmseg - INFO - Best mIoU is 0.8106 at 32000 iter. 2023-03-03 23:38:23,125 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:38:23,125 - mmseg - INFO - Iter(val) [63] mIoU: [0.81, 0.8101, 0.8101, 0.8103, 0.8103, 0.8104, 0.8104, 0.8104, 0.8106, 0.8106, 0.8106], copy_paste: 81.0,81.01,81.01,81.03,81.03,81.04,81.04,81.04,81.06,81.06,81.06 2023-03-03 23:38:23,133 - mmseg - INFO - Swap parameters (before train) before iter [32001] 2023-03-03 23:38:35,611 - mmseg - INFO - Iter [32050/160000] lr: 7.500e-05, eta: 11:08:33, time: 18.155, data_time: 17.914, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.7917, loss: 0.0802 2023-03-03 23:38:47,996 - mmseg - INFO - Iter [32100/160000] lr: 7.500e-05, eta: 11:08:04, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7416, loss: 0.0824 2023-03-03 23:39:00,290 - mmseg - INFO - Iter [32150/160000] lr: 7.500e-05, eta: 11:07:35, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7310, loss: 0.0825 2023-03-03 23:39:14,901 - mmseg - INFO - Iter [32200/160000] lr: 7.500e-05, eta: 11:07:15, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6540, loss: 0.0848 2023-03-03 23:39:27,069 - mmseg - INFO - Iter [32250/160000] lr: 7.500e-05, eta: 11:06:45, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0916, decode.acc_seg: 96.4314, loss: 0.0916 2023-03-03 23:39:39,314 - mmseg - INFO - Iter [32300/160000] lr: 7.500e-05, eta: 11:06:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6608, loss: 0.0856 2023-03-03 23:39:51,452 - mmseg - INFO - Iter [32350/160000] lr: 7.500e-05, eta: 11:05:47, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7705, loss: 0.0816 2023-03-03 23:40:06,045 - mmseg - INFO - Iter [32400/160000] lr: 7.500e-05, eta: 11:05:27, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7559, loss: 0.0815 2023-03-03 23:40:18,326 - mmseg - INFO - Iter [32450/160000] lr: 7.500e-05, eta: 11:04:58, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7422, loss: 0.0835 2023-03-03 23:40:30,526 - mmseg - INFO - Iter [32500/160000] lr: 7.500e-05, eta: 11:04:29, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6699, loss: 0.0842 2023-03-03 23:40:42,709 - mmseg - INFO - Iter [32550/160000] lr: 7.500e-05, eta: 11:04:00, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7172, loss: 0.0828 2023-03-03 23:40:57,403 - mmseg - INFO - Iter [32600/160000] lr: 7.500e-05, eta: 11:03:40, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6355, loss: 0.0857 2023-03-03 23:41:09,634 - mmseg - INFO - Iter [32650/160000] lr: 7.500e-05, eta: 11:03:12, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6659, loss: 0.0853 2023-03-03 23:41:21,940 - mmseg - INFO - Iter [32700/160000] lr: 7.500e-05, eta: 11:02:43, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6899, loss: 0.0839 2023-03-03 23:41:36,513 - mmseg - INFO - Iter [32750/160000] lr: 7.500e-05, eta: 11:02:23, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8647, loss: 0.0780 2023-03-03 23:41:48,835 - mmseg - INFO - Iter [32800/160000] lr: 7.500e-05, eta: 11:01:55, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7592, loss: 0.0815 2023-03-03 23:42:00,992 - mmseg - INFO - Iter [32850/160000] lr: 7.500e-05, eta: 11:01:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6571, loss: 0.0849 2023-03-03 23:42:13,352 - mmseg - INFO - Iter [32900/160000] lr: 7.500e-05, eta: 11:00:58, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.5853, loss: 0.0872 2023-03-03 23:42:28,098 - mmseg - INFO - Iter [32950/160000] lr: 7.500e-05, eta: 11:00:39, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7388, loss: 0.0824 2023-03-03 23:42:40,344 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:42:40,344 - mmseg - INFO - Iter [33000/160000] lr: 7.500e-05, eta: 11:00:10, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.5824, loss: 0.0854 2023-03-03 23:42:52,575 - mmseg - INFO - Iter [33050/160000] lr: 7.500e-05, eta: 10:59:42, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.7437, loss: 0.0843 2023-03-03 23:43:04,883 - mmseg - INFO - Iter [33100/160000] lr: 7.500e-05, eta: 10:59:14, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6305, loss: 0.0858 2023-03-03 23:43:19,426 - mmseg - INFO - Iter [33150/160000] lr: 7.500e-05, eta: 10:58:54, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7213, loss: 0.0817 2023-03-03 23:43:31,899 - mmseg - INFO - Iter [33200/160000] lr: 7.500e-05, eta: 10:58:27, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7164, loss: 0.0835 2023-03-03 23:43:44,223 - mmseg - INFO - Iter [33250/160000] lr: 7.500e-05, eta: 10:57:59, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7856, loss: 0.0813 2023-03-03 23:43:58,679 - mmseg - INFO - Iter [33300/160000] lr: 7.500e-05, eta: 10:57:39, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6025, loss: 0.0862 2023-03-03 23:44:10,857 - mmseg - INFO - Iter [33350/160000] lr: 7.500e-05, eta: 10:57:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7615, loss: 0.0812 2023-03-03 23:44:23,139 - mmseg - INFO - Iter [33400/160000] lr: 7.500e-05, eta: 10:56:42, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7246, loss: 0.0834 2023-03-03 23:44:35,272 - mmseg - INFO - Iter [33450/160000] lr: 7.500e-05, eta: 10:56:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0877, decode.acc_seg: 96.5822, loss: 0.0877 2023-03-03 23:44:49,850 - mmseg - INFO - Iter [33500/160000] lr: 7.500e-05, eta: 10:55:55, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0923, decode.acc_seg: 96.5407, loss: 0.0923 2023-03-03 23:45:02,250 - mmseg - INFO - Iter [33550/160000] lr: 7.500e-05, eta: 10:55:27, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.6990, loss: 0.0827 2023-03-03 23:45:14,482 - mmseg - INFO - Iter [33600/160000] lr: 7.500e-05, eta: 10:54:59, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8680, loss: 0.0792 2023-03-03 23:45:26,626 - mmseg - INFO - Iter [33650/160000] lr: 7.500e-05, eta: 10:54:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7267, loss: 0.0829 2023-03-03 23:45:41,252 - mmseg - INFO - Iter [33700/160000] lr: 7.500e-05, eta: 10:54:12, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7572, loss: 0.0827 2023-03-03 23:45:53,341 - mmseg - INFO - Iter [33750/160000] lr: 7.500e-05, eta: 10:53:43, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7645, loss: 0.0818 2023-03-03 23:46:05,603 - mmseg - INFO - Iter [33800/160000] lr: 7.500e-05, eta: 10:53:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6774, loss: 0.0839 2023-03-03 23:46:17,763 - mmseg - INFO - Iter [33850/160000] lr: 7.500e-05, eta: 10:52:47, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7105, loss: 0.0834 2023-03-03 23:46:32,227 - mmseg - INFO - Iter [33900/160000] lr: 7.500e-05, eta: 10:52:28, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7487, loss: 0.0834 2023-03-03 23:46:44,354 - mmseg - INFO - Iter [33950/160000] lr: 7.500e-05, eta: 10:52:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6531, loss: 0.0850 2023-03-03 23:46:56,655 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:46:56,655 - mmseg - INFO - Iter [34000/160000] lr: 7.500e-05, eta: 10:51:32, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7412, loss: 0.0825 2023-03-03 23:47:11,077 - mmseg - INFO - Iter [34050/160000] lr: 7.500e-05, eta: 10:51:13, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6132, loss: 0.0866 2023-03-03 23:47:23,327 - mmseg - INFO - Iter [34100/160000] lr: 7.500e-05, eta: 10:50:45, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7275, loss: 0.0833 2023-03-03 23:47:35,536 - mmseg - INFO - Iter [34150/160000] lr: 7.500e-05, eta: 10:50:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7270, loss: 0.0828 2023-03-03 23:47:47,727 - mmseg - INFO - Iter [34200/160000] lr: 7.500e-05, eta: 10:49:50, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6714, loss: 0.0836 2023-03-03 23:48:02,180 - mmseg - INFO - Iter [34250/160000] lr: 7.500e-05, eta: 10:49:31, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6671, loss: 0.0844 2023-03-03 23:48:14,235 - mmseg - INFO - Iter [34300/160000] lr: 7.500e-05, eta: 10:49:03, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.5723, loss: 0.0864 2023-03-03 23:48:26,445 - mmseg - INFO - Iter [34350/160000] lr: 7.500e-05, eta: 10:48:35, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7627, loss: 0.0818 2023-03-03 23:48:38,648 - mmseg - INFO - Iter [34400/160000] lr: 7.500e-05, eta: 10:48:08, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6819, loss: 0.0836 2023-03-03 23:48:53,292 - mmseg - INFO - Iter [34450/160000] lr: 7.500e-05, eta: 10:47:49, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7533, loss: 0.0830 2023-03-03 23:49:05,378 - mmseg - INFO - Iter [34500/160000] lr: 7.500e-05, eta: 10:47:21, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0883, decode.acc_seg: 96.5873, loss: 0.0883 2023-03-03 23:49:17,473 - mmseg - INFO - Iter [34550/160000] lr: 7.500e-05, eta: 10:46:53, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6848, loss: 0.0844 2023-03-03 23:49:32,033 - mmseg - INFO - Iter [34600/160000] lr: 7.500e-05, eta: 10:46:35, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7229, loss: 0.0839 2023-03-03 23:49:44,211 - mmseg 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INFO - Iter [34900/160000] lr: 7.500e-05, eta: 10:44:00, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7283, loss: 0.0838 2023-03-03 23:50:59,796 - mmseg - INFO - Iter [34950/160000] lr: 7.500e-05, eta: 10:43:33, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0865, decode.acc_seg: 96.5968, loss: 0.0865 2023-03-03 23:51:14,406 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:51:14,406 - mmseg - INFO - Iter [35000/160000] lr: 7.500e-05, eta: 10:43:15, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7376, loss: 0.0833 2023-03-03 23:51:26,597 - mmseg - INFO - Iter [35050/160000] lr: 7.500e-05, eta: 10:42:48, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0872, decode.acc_seg: 96.5501, loss: 0.0872 2023-03-03 23:51:38,751 - mmseg - INFO - Iter [35100/160000] lr: 7.500e-05, eta: 10:42:20, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7780, loss: 0.0824 2023-03-03 23:51:50,854 - mmseg - INFO - Iter [35150/160000] lr: 7.500e-05, eta: 10:41:53, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6777, loss: 0.0847 2023-03-03 23:52:05,505 - mmseg - INFO - Iter [35200/160000] lr: 7.500e-05, eta: 10:41:35, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6586, loss: 0.0848 2023-03-03 23:52:17,545 - mmseg - INFO - Iter [35250/160000] lr: 7.500e-05, eta: 10:41:08, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7726, loss: 0.0822 2023-03-03 23:52:29,789 - mmseg - INFO - Iter [35300/160000] lr: 7.500e-05, eta: 10:40:41, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6741, loss: 0.0846 2023-03-03 23:52:44,329 - mmseg - INFO - Iter [35350/160000] lr: 7.500e-05, eta: 10:40:23, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.5978, loss: 0.0858 2023-03-03 23:52:56,455 - mmseg - INFO - Iter [35400/160000] lr: 7.500e-05, eta: 10:39:56, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7622, loss: 0.0820 2023-03-03 23:53:08,734 - mmseg - INFO - Iter [35450/160000] lr: 7.500e-05, eta: 10:39:29, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7313, loss: 0.0831 2023-03-03 23:53:21,058 - mmseg - INFO - Iter [35500/160000] lr: 7.500e-05, eta: 10:39:03, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6767, loss: 0.0835 2023-03-03 23:53:35,518 - mmseg - INFO - Iter [35550/160000] lr: 7.500e-05, eta: 10:38:44, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7824, loss: 0.0819 2023-03-03 23:53:47,739 - mmseg - INFO - Iter [35600/160000] lr: 7.500e-05, eta: 10:38:18, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7095, loss: 0.0830 2023-03-03 23:54:00,097 - mmseg - INFO - Iter [35650/160000] lr: 7.500e-05, eta: 10:37:52, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7759, loss: 0.0818 2023-03-03 23:54:12,206 - mmseg - INFO - Iter [35700/160000] lr: 7.500e-05, eta: 10:37:25, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7027, loss: 0.0834 2023-03-03 23:54:26,743 - mmseg - INFO - Iter [35750/160000] lr: 7.500e-05, eta: 10:37:07, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6993, loss: 0.0839 2023-03-03 23:54:39,076 - mmseg - INFO - Iter [35800/160000] lr: 7.500e-05, eta: 10:36:41, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6469, loss: 0.0852 2023-03-03 23:54:51,137 - mmseg - INFO - Iter [35850/160000] lr: 7.500e-05, eta: 10:36:14, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7075, loss: 0.0829 2023-03-03 23:55:05,647 - mmseg - INFO - Iter [35900/160000] lr: 7.500e-05, eta: 10:35:55, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7067, loss: 0.0828 2023-03-03 23:55:17,928 - mmseg - INFO - Iter [35950/160000] lr: 7.500e-05, eta: 10:35:29, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7356, loss: 0.0828 2023-03-03 23:55:30,336 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:55:30,336 - mmseg - INFO - Iter [36000/160000] lr: 7.500e-05, eta: 10:35:04, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.7075, loss: 0.0851 2023-03-03 23:55:42,659 - mmseg - INFO - Iter [36050/160000] lr: 7.500e-05, eta: 10:34:38, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7470, loss: 0.0820 2023-03-03 23:55:57,233 - mmseg - INFO - Iter [36100/160000] lr: 7.500e-05, eta: 10:34:20, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0879, decode.acc_seg: 96.5257, loss: 0.0879 2023-03-03 23:56:09,369 - mmseg - INFO - Iter [36150/160000] lr: 7.500e-05, eta: 10:33:54, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6928, loss: 0.0847 2023-03-03 23:56:21,459 - mmseg - INFO - Iter [36200/160000] lr: 7.500e-05, eta: 10:33:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6955, loss: 0.0843 2023-03-03 23:56:33,754 - mmseg - INFO - Iter [36250/160000] lr: 7.500e-05, eta: 10:33:01, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.6110, loss: 0.0870 2023-03-03 23:56:48,241 - mmseg - INFO - Iter [36300/160000] lr: 7.500e-05, eta: 10:32:43, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6793, loss: 0.0842 2023-03-03 23:57:00,550 - mmseg - INFO - Iter [36350/160000] lr: 7.500e-05, eta: 10:32:17, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6669, loss: 0.0855 2023-03-03 23:57:12,721 - mmseg - INFO - Iter [36400/160000] lr: 7.500e-05, eta: 10:31:51, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.5945, loss: 0.0859 2023-03-03 23:57:24,801 - mmseg - INFO - Iter [36450/160000] lr: 7.500e-05, eta: 10:31:25, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8254, loss: 0.0804 2023-03-03 23:57:39,338 - mmseg - INFO - Iter [36500/160000] lr: 7.500e-05, eta: 10:31:07, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0868, decode.acc_seg: 96.6097, loss: 0.0868 2023-03-03 23:57:51,401 - mmseg - INFO - Iter [36550/160000] lr: 7.500e-05, eta: 10:30:40, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7161, loss: 0.0827 2023-03-03 23:58:03,447 - mmseg - INFO - Iter [36600/160000] lr: 7.500e-05, eta: 10:30:14, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7990, loss: 0.0826 2023-03-03 23:58:17,887 - mmseg - INFO - Iter [36650/160000] lr: 7.500e-05, eta: 10:29:56, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.7052, loss: 0.0843 2023-03-03 23:58:30,032 - mmseg - INFO - Iter [36700/160000] lr: 7.500e-05, eta: 10:29:30, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6905, loss: 0.0840 2023-03-03 23:58:42,082 - mmseg - INFO - Iter [36750/160000] lr: 7.500e-05, eta: 10:29:03, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.7178, loss: 0.0846 2023-03-03 23:58:54,227 - mmseg - INFO - Iter [36800/160000] lr: 7.500e-05, eta: 10:28:38, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6143, loss: 0.0851 2023-03-03 23:59:08,712 - mmseg - INFO - Iter [36850/160000] lr: 7.500e-05, eta: 10:28:20, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7698, loss: 0.0821 2023-03-03 23:59:20,848 - mmseg - INFO - Iter [36900/160000] lr: 7.500e-05, eta: 10:27:54, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8781, loss: 0.0796 2023-03-03 23:59:33,052 - mmseg - INFO - Iter [36950/160000] lr: 7.500e-05, eta: 10:27:28, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8070, loss: 0.0808 2023-03-03 23:59:45,574 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-03 23:59:45,574 - mmseg - INFO - Iter [37000/160000] lr: 7.500e-05, eta: 10:27:03, time: 0.250, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0894, decode.acc_seg: 96.5712, loss: 0.0894 2023-03-04 00:00:00,164 - mmseg - INFO - Iter [37050/160000] lr: 7.500e-05, eta: 10:26:46, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6417, loss: 0.0855 2023-03-04 00:00:12,399 - mmseg - INFO - Iter [37100/160000] lr: 7.500e-05, eta: 10:26:20, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7429, loss: 0.0817 2023-03-04 00:00:24,581 - mmseg - INFO - Iter [37150/160000] lr: 7.500e-05, eta: 10:25:55, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7494, loss: 0.0816 2023-03-04 00:00:36,683 - mmseg - INFO - Iter [37200/160000] lr: 7.500e-05, eta: 10:25:29, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6907, loss: 0.0837 2023-03-04 00:00:51,106 - mmseg - INFO - Iter [37250/160000] lr: 7.500e-05, eta: 10:25:11, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0864, decode.acc_seg: 96.5441, loss: 0.0864 2023-03-04 00:01:03,244 - mmseg - INFO - Iter [37300/160000] lr: 7.500e-05, eta: 10:24:45, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7941, loss: 0.0809 2023-03-04 00:01:15,475 - mmseg - INFO - Iter [37350/160000] lr: 7.500e-05, eta: 10:24:20, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7637, loss: 0.0834 2023-03-04 00:01:30,136 - mmseg - INFO - Iter [37400/160000] lr: 7.500e-05, eta: 10:24:03, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7202, loss: 0.0828 2023-03-04 00:01:42,349 - mmseg - INFO - Iter [37450/160000] lr: 7.500e-05, eta: 10:23:38, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7456, loss: 0.0836 2023-03-04 00:01:54,452 - mmseg - INFO - Iter [37500/160000] lr: 7.500e-05, eta: 10:23:12, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7727, loss: 0.0822 2023-03-04 00:02:06,750 - mmseg - INFO - Iter [37550/160000] lr: 7.500e-05, eta: 10:22:47, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7558, loss: 0.0829 2023-03-04 00:02:21,323 - mmseg - INFO - Iter [37600/160000] lr: 7.500e-05, eta: 10:22:29, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6073, loss: 0.0855 2023-03-04 00:02:33,400 - mmseg - INFO - Iter [37650/160000] lr: 7.500e-05, eta: 10:22:04, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7007, loss: 0.0833 2023-03-04 00:02:45,550 - mmseg - INFO - Iter [37700/160000] lr: 7.500e-05, eta: 10:21:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7869, loss: 0.0818 2023-03-04 00:02:57,719 - mmseg - INFO - Iter [37750/160000] lr: 7.500e-05, eta: 10:21:13, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6228, loss: 0.0861 2023-03-04 00:03:12,142 - mmseg - INFO - Iter [37800/160000] lr: 7.500e-05, eta: 10:20:55, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7237, loss: 0.0831 2023-03-04 00:03:24,357 - mmseg - INFO - Iter [37850/160000] lr: 7.500e-05, eta: 10:20:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7296, loss: 0.0822 2023-03-04 00:03:36,525 - mmseg - INFO - Iter [37900/160000] lr: 7.500e-05, eta: 10:20:05, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7325, loss: 0.0841 2023-03-04 00:03:51,013 - mmseg - INFO - Iter [37950/160000] lr: 7.500e-05, eta: 10:19:48, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7679, loss: 0.0824 2023-03-04 00:04:03,192 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:04:03,192 - mmseg - INFO - Iter [38000/160000] lr: 7.500e-05, eta: 10:19:23, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0870, decode.acc_seg: 96.5812, loss: 0.0870 2023-03-04 00:04:15,335 - mmseg - INFO - Iter [38050/160000] lr: 7.500e-05, eta: 10:18:57, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7106, loss: 0.0833 2023-03-04 00:04:27,683 - mmseg - INFO - Iter [38100/160000] lr: 7.500e-05, eta: 10:18:33, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7941, loss: 0.0803 2023-03-04 00:04:42,261 - mmseg - INFO - Iter [38150/160000] lr: 7.500e-05, eta: 10:18:16, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7160, loss: 0.0820 2023-03-04 00:04:54,549 - mmseg - INFO - Iter [38200/160000] lr: 7.500e-05, eta: 10:17:51, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6620, loss: 0.0842 2023-03-04 00:05:06,847 - mmseg - INFO - Iter [38250/160000] lr: 7.500e-05, eta: 10:17:27, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7691, loss: 0.0828 2023-03-04 00:05:18,927 - mmseg - INFO - Iter [38300/160000] lr: 7.500e-05, eta: 10:17:01, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6441, loss: 0.0839 2023-03-04 00:05:33,451 - mmseg - INFO - Iter [38350/160000] lr: 7.500e-05, eta: 10:16:44, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.7133, loss: 0.0843 2023-03-04 00:05:45,645 - mmseg - INFO - Iter [38400/160000] lr: 7.500e-05, eta: 10:16:19, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7696, loss: 0.0826 2023-03-04 00:05:57,781 - mmseg - INFO - Iter [38450/160000] lr: 7.500e-05, eta: 10:15:54, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0862, decode.acc_seg: 96.6307, loss: 0.0862 2023-03-04 00:06:09,952 - mmseg - INFO - Iter [38500/160000] lr: 7.500e-05, eta: 10:15:30, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6452, loss: 0.0844 2023-03-04 00:06:24,559 - mmseg - INFO - Iter [38550/160000] lr: 7.500e-05, eta: 10:15:13, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.5724, loss: 0.0859 2023-03-04 00:06:36,627 - mmseg - INFO - Iter [38600/160000] lr: 7.500e-05, eta: 10:14:48, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8479, loss: 0.0798 2023-03-04 00:06:48,874 - mmseg - INFO - Iter [38650/160000] lr: 7.500e-05, eta: 10:14:23, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6424, loss: 0.0851 2023-03-04 00:07:03,460 - mmseg - INFO - Iter [38700/160000] lr: 7.500e-05, eta: 10:14:06, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6755, loss: 0.0843 2023-03-04 00:07:15,585 - mmseg - INFO - Iter [38750/160000] lr: 7.500e-05, eta: 10:13:41, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6257, loss: 0.0852 2023-03-04 00:07:28,006 - mmseg - INFO - Iter [38800/160000] lr: 7.500e-05, eta: 10:13:17, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7206, loss: 0.0823 2023-03-04 00:07:40,169 - mmseg - INFO - Iter [38850/160000] lr: 7.500e-05, eta: 10:12:53, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7510, loss: 0.0820 2023-03-04 00:07:54,737 - mmseg - INFO - Iter [38900/160000] lr: 7.500e-05, eta: 10:12:36, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7864, loss: 0.0813 2023-03-04 00:08:06,986 - mmseg - INFO - Iter [38950/160000] lr: 7.500e-05, eta: 10:12:12, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8558, loss: 0.0799 2023-03-04 00:08:19,280 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:08:19,280 - mmseg - INFO - Iter [39000/160000] lr: 7.500e-05, eta: 10:11:47, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8841, loss: 0.0791 2023-03-04 00:08:31,621 - mmseg - INFO - Iter [39050/160000] lr: 7.500e-05, eta: 10:11:23, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6387, loss: 0.0848 2023-03-04 00:08:46,028 - mmseg - INFO - Iter [39100/160000] lr: 7.500e-05, eta: 10:11:06, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6640, loss: 0.0841 2023-03-04 00:08:58,244 - mmseg - INFO - Iter [39150/160000] lr: 7.500e-05, eta: 10:10:42, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6844, loss: 0.0835 2023-03-04 00:09:10,501 - mmseg - INFO - Iter [39200/160000] lr: 7.500e-05, eta: 10:10:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8235, loss: 0.0798 2023-03-04 00:09:25,064 - mmseg - INFO - Iter [39250/160000] lr: 7.500e-05, eta: 10:10:01, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7988, loss: 0.0815 2023-03-04 00:09:37,217 - mmseg - INFO - Iter [39300/160000] lr: 7.500e-05, eta: 10:09:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7996, loss: 0.0806 2023-03-04 00:09:49,374 - mmseg - INFO - Iter [39350/160000] lr: 7.500e-05, eta: 10:09:12, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6169, loss: 0.0858 2023-03-04 00:10:01,544 - mmseg - INFO - Iter [39400/160000] lr: 7.500e-05, eta: 10:08:48, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.6266, loss: 0.0855 2023-03-04 00:10:16,014 - mmseg - INFO - Iter [39450/160000] lr: 7.500e-05, eta: 10:08:30, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6212, loss: 0.0858 2023-03-04 00:10:28,296 - mmseg - INFO - Iter [39500/160000] lr: 7.500e-05, eta: 10:08:07, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6919, loss: 0.0836 2023-03-04 00:10:40,559 - mmseg - INFO - Iter [39550/160000] lr: 7.500e-05, eta: 10:07:43, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.6254, loss: 0.0860 2023-03-04 00:10:52,774 - mmseg - INFO - Iter [39600/160000] lr: 7.500e-05, eta: 10:07:19, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6912, loss: 0.0835 2023-03-04 00:11:07,214 - mmseg - INFO - Iter [39650/160000] lr: 7.500e-05, eta: 10:07:01, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.6903, loss: 0.0834 2023-03-04 00:11:19,554 - mmseg - INFO - Iter [39700/160000] lr: 7.500e-05, eta: 10:06:38, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.6949, loss: 0.0829 2023-03-04 00:11:31,660 - mmseg - INFO - Iter [39750/160000] lr: 7.500e-05, eta: 10:06:14, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6890, loss: 0.0837 2023-03-04 00:11:43,953 - mmseg - INFO - Iter [39800/160000] lr: 7.500e-05, eta: 10:05:50, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7510, loss: 0.0836 2023-03-04 00:11:58,564 - mmseg - INFO - Iter [39850/160000] lr: 7.500e-05, eta: 10:05:33, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5880, loss: 0.0863 2023-03-04 00:12:10,781 - mmseg - INFO - Iter [39900/160000] lr: 7.500e-05, eta: 10:05:09, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7942, loss: 0.0814 2023-03-04 00:12:23,045 - mmseg - INFO - Iter [39950/160000] lr: 7.500e-05, eta: 10:04:46, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7026, loss: 0.0827 2023-03-04 00:12:37,665 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:12:37,666 - mmseg - INFO - Iter [40000/160000] lr: 7.500e-05, eta: 10:04:29, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7170, loss: 0.0835 2023-03-04 00:12:49,860 - mmseg - INFO - Iter [40050/160000] lr: 3.750e-05, eta: 10:04:05, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7698, loss: 0.0830 2023-03-04 00:13:02,024 - mmseg - INFO - Iter [40100/160000] lr: 3.750e-05, eta: 10:03:41, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7453, loss: 0.0830 2023-03-04 00:13:14,060 - mmseg - INFO - Iter [40150/160000] lr: 3.750e-05, eta: 10:03:17, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6767, loss: 0.0835 2023-03-04 00:13:28,491 - mmseg - INFO - Iter [40200/160000] lr: 3.750e-05, eta: 10:03:00, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8876, loss: 0.0788 2023-03-04 00:13:40,759 - mmseg - INFO - Iter [40250/160000] lr: 3.750e-05, eta: 10:02:36, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7728, loss: 0.0826 2023-03-04 00:13:52,836 - mmseg - INFO - Iter [40300/160000] lr: 3.750e-05, eta: 10:02:12, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7099, loss: 0.0828 2023-03-04 00:14:05,021 - mmseg - INFO - Iter [40350/160000] lr: 3.750e-05, eta: 10:01:49, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7487, loss: 0.0815 2023-03-04 00:14:19,587 - mmseg - INFO - Iter [40400/160000] lr: 3.750e-05, eta: 10:01:32, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6764, loss: 0.0848 2023-03-04 00:14:31,794 - mmseg - INFO - Iter [40450/160000] lr: 3.750e-05, eta: 10:01:08, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.6550, loss: 0.0833 2023-03-04 00:14:43,954 - mmseg - INFO - Iter [40500/160000] lr: 3.750e-05, eta: 10:00:45, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6661, loss: 0.0840 2023-03-04 00:14:58,470 - mmseg - INFO - Iter [40550/160000] lr: 3.750e-05, eta: 10:00:28, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5686, loss: 0.0875 2023-03-04 00:15:10,602 - mmseg - INFO - Iter [40600/160000] lr: 3.750e-05, eta: 10:00:04, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7572, loss: 0.0828 2023-03-04 00:15:22,723 - mmseg - INFO - Iter [40650/160000] lr: 3.750e-05, eta: 9:59:40, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6865, loss: 0.0840 2023-03-04 00:15:34,884 - mmseg - INFO - Iter [40700/160000] lr: 3.750e-05, eta: 9:59:17, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8206, loss: 0.0794 2023-03-04 00:15:49,369 - mmseg - INFO - Iter [40750/160000] lr: 3.750e-05, eta: 9:59:00, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6599, loss: 0.0850 2023-03-04 00:16:01,582 - mmseg - INFO - Iter [40800/160000] lr: 3.750e-05, eta: 9:58:37, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.8423, loss: 0.0827 2023-03-04 00:16:13,802 - mmseg - INFO - Iter [40850/160000] lr: 3.750e-05, eta: 9:58:13, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8311, loss: 0.0805 2023-03-04 00:16:25,890 - mmseg - INFO - Iter [40900/160000] lr: 3.750e-05, eta: 9:57:49, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7258, loss: 0.0826 2023-03-04 00:16:40,438 - mmseg - INFO - Iter [40950/160000] lr: 3.750e-05, eta: 9:57:33, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6928, loss: 0.0841 2023-03-04 00:16:52,704 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:16:52,704 - mmseg - INFO - Iter [41000/160000] lr: 3.750e-05, eta: 9:57:10, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7163, loss: 0.0833 2023-03-04 00:17:05,073 - mmseg - INFO - Iter [41050/160000] lr: 3.750e-05, eta: 9:56:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7562, loss: 0.0824 2023-03-04 00:17:17,205 - mmseg - INFO - Iter [41100/160000] lr: 3.750e-05, eta: 9:56:23, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7106, loss: 0.0827 2023-03-04 00:17:31,837 - mmseg - INFO - Iter [41150/160000] lr: 3.750e-05, eta: 9:56:07, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0873, decode.acc_seg: 96.6076, loss: 0.0873 2023-03-04 00:17:43,915 - mmseg - INFO - Iter [41200/160000] lr: 3.750e-05, eta: 9:55:44, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8957, loss: 0.0782 2023-03-04 00:17:55,970 - mmseg - INFO - Iter [41250/160000] lr: 3.750e-05, eta: 9:55:20, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8139, loss: 0.0800 2023-03-04 00:18:10,522 - mmseg - INFO - Iter [41300/160000] lr: 3.750e-05, eta: 9:55:03, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8103, loss: 0.0805 2023-03-04 00:18:22,694 - mmseg - INFO - Iter [41350/160000] lr: 3.750e-05, eta: 9:54:40, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7312, loss: 0.0824 2023-03-04 00:18:34,832 - mmseg - INFO - Iter [41400/160000] lr: 3.750e-05, eta: 9:54:17, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7457, loss: 0.0836 2023-03-04 00:18:47,048 - mmseg - INFO - Iter [41450/160000] lr: 3.750e-05, eta: 9:53:54, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7711, loss: 0.0806 2023-03-04 00:19:01,527 - mmseg - INFO - Iter [41500/160000] lr: 3.750e-05, eta: 9:53:37, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7492, loss: 0.0827 2023-03-04 00:19:13,701 - mmseg - INFO - Iter [41550/160000] lr: 3.750e-05, eta: 9:53:14, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7632, loss: 0.0818 2023-03-04 00:19:25,813 - mmseg - INFO - Iter [41600/160000] lr: 3.750e-05, eta: 9:52:51, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7122, loss: 0.0827 2023-03-04 00:19:37,882 - mmseg - INFO - Iter [41650/160000] lr: 3.750e-05, eta: 9:52:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6305, loss: 0.0854 2023-03-04 00:19:52,381 - mmseg - INFO - Iter [41700/160000] lr: 3.750e-05, eta: 9:52:11, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7233, loss: 0.0827 2023-03-04 00:20:04,557 - mmseg - INFO - Iter [41750/160000] lr: 3.750e-05, eta: 9:51:48, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7729, loss: 0.0815 2023-03-04 00:20:16,650 - mmseg - INFO - Iter [41800/160000] lr: 3.750e-05, eta: 9:51:24, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6959, loss: 0.0837 2023-03-04 00:20:28,734 - mmseg - INFO - Iter [41850/160000] lr: 3.750e-05, eta: 9:51:01, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.6178, loss: 0.0860 2023-03-04 00:20:43,341 - mmseg - INFO - Iter [41900/160000] lr: 3.750e-05, eta: 9:50:45, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.6785, loss: 0.0843 2023-03-04 00:20:55,456 - mmseg - INFO - Iter [41950/160000] lr: 3.750e-05, eta: 9:50:22, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.5648, loss: 0.0866 2023-03-04 00:21:07,544 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:21:07,544 - mmseg - INFO - Iter [42000/160000] lr: 3.750e-05, eta: 9:49:59, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8096, loss: 0.0797 2023-03-04 00:21:22,114 - mmseg - INFO - Iter [42050/160000] lr: 3.750e-05, eta: 9:49:43, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7486, loss: 0.0830 2023-03-04 00:21:34,364 - mmseg - INFO - Iter [42100/160000] lr: 3.750e-05, eta: 9:49:20, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8583, loss: 0.0795 2023-03-04 00:21:46,728 - mmseg - INFO - Iter [42150/160000] lr: 3.750e-05, eta: 9:48:57, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7585, loss: 0.0819 2023-03-04 00:21:58,879 - mmseg - INFO - Iter [42200/160000] lr: 3.750e-05, eta: 9:48:35, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8218, loss: 0.0810 2023-03-04 00:22:13,413 - mmseg - INFO - Iter [42250/160000] lr: 3.750e-05, eta: 9:48:18, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8066, loss: 0.0814 2023-03-04 00:22:25,686 - mmseg - INFO - Iter [42300/160000] lr: 3.750e-05, eta: 9:47:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6562, loss: 0.0852 2023-03-04 00:22:37,865 - mmseg - INFO - Iter [42350/160000] lr: 3.750e-05, eta: 9:47:33, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9001, loss: 0.0784 2023-03-04 00:22:50,045 - mmseg - INFO - Iter [42400/160000] lr: 3.750e-05, eta: 9:47:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7897, loss: 0.0817 2023-03-04 00:23:04,646 - mmseg - INFO - Iter [42450/160000] lr: 3.750e-05, eta: 9:46:54, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6387, loss: 0.0857 2023-03-04 00:23:16,730 - mmseg - INFO - Iter [42500/160000] lr: 3.750e-05, eta: 9:46:31, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8059, loss: 0.0805 2023-03-04 00:23:28,839 - mmseg - INFO - Iter [42550/160000] lr: 3.750e-05, eta: 9:46:08, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8252, loss: 0.0794 2023-03-04 00:23:43,522 - mmseg - INFO - Iter [42600/160000] lr: 3.750e-05, eta: 9:45:53, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6816, loss: 0.0842 2023-03-04 00:23:55,814 - mmseg - INFO - Iter [42650/160000] lr: 3.750e-05, eta: 9:45:30, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7602, loss: 0.0831 2023-03-04 00:24:07,920 - mmseg - INFO - Iter [42700/160000] lr: 3.750e-05, eta: 9:45:07, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7871, loss: 0.0811 2023-03-04 00:24:20,178 - mmseg - INFO - Iter [42750/160000] lr: 3.750e-05, eta: 9:44:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8414, loss: 0.0792 2023-03-04 00:24:34,566 - mmseg - INFO - Iter [42800/160000] lr: 3.750e-05, eta: 9:44:28, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7132, loss: 0.0820 2023-03-04 00:24:46,684 - mmseg - INFO - Iter [42850/160000] lr: 3.750e-05, eta: 9:44:06, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8336, loss: 0.0804 2023-03-04 00:24:58,871 - mmseg - INFO - Iter [42900/160000] lr: 3.750e-05, eta: 9:43:43, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7493, loss: 0.0818 2023-03-04 00:25:11,034 - mmseg - INFO - Iter [42950/160000] lr: 3.750e-05, eta: 9:43:21, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7112, loss: 0.0829 2023-03-04 00:25:25,512 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:25:25,512 - mmseg - INFO - Iter [43000/160000] lr: 3.750e-05, eta: 9:43:04, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7567, loss: 0.0818 2023-03-04 00:25:37,623 - mmseg - INFO - Iter [43050/160000] lr: 3.750e-05, eta: 9:42:42, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6389, loss: 0.0859 2023-03-04 00:25:49,814 - mmseg - INFO - Iter [43100/160000] lr: 3.750e-05, eta: 9:42:19, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7817, loss: 0.0815 2023-03-04 00:26:02,012 - mmseg - INFO - Iter [43150/160000] lr: 3.750e-05, eta: 9:41:57, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8071, loss: 0.0807 2023-03-04 00:26:16,580 - mmseg - INFO - Iter [43200/160000] lr: 3.750e-05, eta: 9:41:41, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.6140, loss: 0.0859 2023-03-04 00:26:28,859 - mmseg - INFO - Iter [43250/160000] lr: 3.750e-05, eta: 9:41:19, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6820, loss: 0.0847 2023-03-04 00:26:41,065 - mmseg - INFO - Iter [43300/160000] lr: 3.750e-05, eta: 9:40:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7718, loss: 0.0812 2023-03-04 00:26:55,637 - mmseg - INFO - Iter [43350/160000] lr: 3.750e-05, eta: 9:40:41, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7669, loss: 0.0817 2023-03-04 00:27:07,747 - mmseg - INFO - Iter [43400/160000] lr: 3.750e-05, eta: 9:40:18, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7831, loss: 0.0808 2023-03-04 00:27:19,919 - mmseg - INFO - Iter [43450/160000] lr: 3.750e-05, eta: 9:39:56, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7368, loss: 0.0817 2023-03-04 00:27:32,044 - mmseg - INFO - Iter [43500/160000] lr: 3.750e-05, eta: 9:39:33, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8004, loss: 0.0815 2023-03-04 00:27:46,551 - mmseg - INFO - Iter [43550/160000] lr: 3.750e-05, eta: 9:39:17, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7610, loss: 0.0831 2023-03-04 00:27:58,745 - mmseg - INFO - Iter [43600/160000] lr: 3.750e-05, eta: 9:38:55, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6552, loss: 0.0854 2023-03-04 00:28:10,918 - mmseg - INFO - Iter [43650/160000] lr: 3.750e-05, eta: 9:38:33, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.7988, loss: 0.0802 2023-03-04 00:28:23,145 - mmseg - INFO - Iter [43700/160000] lr: 3.750e-05, eta: 9:38:11, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7176, loss: 0.0834 2023-03-04 00:28:37,585 - mmseg - INFO - Iter [43750/160000] lr: 3.750e-05, eta: 9:37:55, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7545, loss: 0.0821 2023-03-04 00:28:49,666 - mmseg - INFO - Iter [43800/160000] lr: 3.750e-05, eta: 9:37:32, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8415, loss: 0.0802 2023-03-04 00:29:01,845 - mmseg - INFO - Iter [43850/160000] lr: 3.750e-05, eta: 9:37:10, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7738, loss: 0.0823 2023-03-04 00:29:16,621 - mmseg - INFO - Iter [43900/160000] lr: 3.750e-05, eta: 9:36:55, time: 0.296, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.6769, loss: 0.0826 2023-03-04 00:29:28,800 - mmseg - INFO - Iter [43950/160000] lr: 3.750e-05, eta: 9:36:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7817, loss: 0.0823 2023-03-04 00:29:40,997 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:29:40,997 - mmseg - INFO - Iter [44000/160000] lr: 3.750e-05, eta: 9:36:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7632, loss: 0.0824 2023-03-04 00:29:53,138 - mmseg - INFO - Iter [44050/160000] lr: 3.750e-05, eta: 9:35:48, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7670, loss: 0.0820 2023-03-04 00:30:07,668 - mmseg - INFO - Iter [44100/160000] lr: 3.750e-05, eta: 9:35:32, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.5659, loss: 0.0860 2023-03-04 00:30:19,913 - mmseg - INFO - Iter [44150/160000] lr: 3.750e-05, eta: 9:35:11, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8695, loss: 0.0784 2023-03-04 00:30:32,087 - mmseg - INFO - Iter [44200/160000] lr: 3.750e-05, eta: 9:34:49, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8991, loss: 0.0790 2023-03-04 00:30:44,321 - mmseg - INFO - Iter [44250/160000] lr: 3.750e-05, eta: 9:34:27, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7140, loss: 0.0830 2023-03-04 00:30:58,837 - mmseg - INFO - Iter [44300/160000] lr: 3.750e-05, eta: 9:34:11, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7817, loss: 0.0815 2023-03-04 00:31:10,960 - mmseg - INFO - Iter [44350/160000] lr: 3.750e-05, eta: 9:33:49, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8961, loss: 0.0778 2023-03-04 00:31:23,065 - mmseg - INFO - Iter [44400/160000] lr: 3.750e-05, eta: 9:33:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7115, loss: 0.0830 2023-03-04 00:31:35,159 - mmseg - INFO - Iter [44450/160000] lr: 3.750e-05, eta: 9:33:05, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6076, loss: 0.0857 2023-03-04 00:31:49,682 - mmseg - INFO - Iter [44500/160000] lr: 3.750e-05, eta: 9:32:49, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7552, loss: 0.0808 2023-03-04 00:32:01,916 - mmseg - INFO - Iter [44550/160000] lr: 3.750e-05, eta: 9:32:27, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7269, loss: 0.0823 2023-03-04 00:32:14,287 - mmseg - INFO - Iter [44600/160000] lr: 3.750e-05, eta: 9:32:06, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6557, loss: 0.0840 2023-03-04 00:32:28,975 - mmseg - INFO - Iter [44650/160000] lr: 3.750e-05, eta: 9:31:50, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7480, loss: 0.0813 2023-03-04 00:32:41,071 - mmseg - INFO - Iter [44700/160000] lr: 3.750e-05, eta: 9:31:28, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.6499, loss: 0.0833 2023-03-04 00:32:53,280 - mmseg - INFO - Iter [44750/160000] lr: 3.750e-05, eta: 9:31:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8133, loss: 0.0816 2023-03-04 00:33:05,457 - mmseg - INFO - Iter [44800/160000] lr: 3.750e-05, eta: 9:30:45, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.7102, loss: 0.0844 2023-03-04 00:33:20,084 - mmseg - INFO - Iter [44850/160000] lr: 3.750e-05, eta: 9:30:29, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8215, loss: 0.0811 2023-03-04 00:33:32,119 - mmseg - INFO - Iter [44900/160000] lr: 3.750e-05, eta: 9:30:07, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7651, loss: 0.0822 2023-03-04 00:33:44,310 - mmseg - INFO - Iter [44950/160000] lr: 3.750e-05, eta: 9:29:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9123, loss: 0.0784 2023-03-04 00:33:56,541 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:33:56,542 - mmseg - INFO - Iter [45000/160000] lr: 3.750e-05, eta: 9:29:24, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7909, loss: 0.0823 2023-03-04 00:34:11,034 - mmseg - INFO - Iter [45050/160000] lr: 3.750e-05, eta: 9:29:08, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6462, loss: 0.0848 2023-03-04 00:34:23,288 - mmseg - INFO - Iter [45100/160000] lr: 3.750e-05, eta: 9:28:47, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7107, loss: 0.0835 2023-03-04 00:34:35,385 - mmseg - INFO - Iter [45150/160000] lr: 3.750e-05, eta: 9:28:25, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7207, loss: 0.0827 2023-03-04 00:34:49,795 - mmseg - INFO - Iter [45200/160000] lr: 3.750e-05, eta: 9:28:09, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7630, loss: 0.0824 2023-03-04 00:35:02,068 - mmseg - INFO - Iter [45250/160000] lr: 3.750e-05, eta: 9:27:47, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8165, loss: 0.0813 2023-03-04 00:35:14,299 - mmseg - INFO - Iter [45300/160000] lr: 3.750e-05, eta: 9:27:26, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7433, loss: 0.0832 2023-03-04 00:35:26,531 - mmseg - INFO - Iter [45350/160000] lr: 3.750e-05, eta: 9:27:05, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7081, loss: 0.0836 2023-03-04 00:35:41,175 - mmseg - INFO - Iter [45400/160000] lr: 3.750e-05, eta: 9:26:49, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8437, loss: 0.0803 2023-03-04 00:35:53,331 - mmseg - INFO - Iter [45450/160000] lr: 3.750e-05, eta: 9:26:28, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6945, loss: 0.0847 2023-03-04 00:36:05,561 - mmseg - INFO - Iter [45500/160000] lr: 3.750e-05, eta: 9:26:06, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.5997, loss: 0.0860 2023-03-04 00:36:17,803 - mmseg - INFO - Iter [45550/160000] lr: 3.750e-05, eta: 9:25:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8016, loss: 0.0803 2023-03-04 00:36:32,418 - mmseg - INFO - Iter [45600/160000] lr: 3.750e-05, eta: 9:25:30, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8232, loss: 0.0798 2023-03-04 00:36:44,572 - mmseg - INFO - Iter [45650/160000] lr: 3.750e-05, eta: 9:25:08, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8434, loss: 0.0793 2023-03-04 00:36:56,902 - mmseg - INFO - Iter [45700/160000] lr: 3.750e-05, eta: 9:24:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7564, loss: 0.0818 2023-03-04 00:37:09,201 - mmseg - INFO - Iter [45750/160000] lr: 3.750e-05, eta: 9:24:26, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7088, loss: 0.0832 2023-03-04 00:37:23,704 - mmseg - INFO - Iter [45800/160000] lr: 3.750e-05, eta: 9:24:10, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6958, loss: 0.0835 2023-03-04 00:37:35,855 - mmseg - INFO - Iter [45850/160000] lr: 3.750e-05, eta: 9:23:49, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7726, loss: 0.0812 2023-03-04 00:37:47,985 - mmseg - INFO - Iter [45900/160000] lr: 3.750e-05, eta: 9:23:27, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7511, loss: 0.0815 2023-03-04 00:38:02,846 - mmseg - INFO - Iter [45950/160000] lr: 3.750e-05, eta: 9:23:12, time: 0.297, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0875, decode.acc_seg: 96.5680, loss: 0.0875 2023-03-04 00:38:15,145 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:38:15,146 - mmseg - INFO - Iter [46000/160000] lr: 3.750e-05, eta: 9:22:51, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8577, loss: 0.0794 2023-03-04 00:38:27,326 - mmseg - INFO - Iter [46050/160000] lr: 3.750e-05, eta: 9:22:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7808, loss: 0.0818 2023-03-04 00:38:39,780 - mmseg - INFO - Iter [46100/160000] lr: 3.750e-05, eta: 9:22:10, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7426, loss: 0.0826 2023-03-04 00:38:54,352 - mmseg - INFO - Iter [46150/160000] lr: 3.750e-05, eta: 9:21:54, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8002, loss: 0.0803 2023-03-04 00:39:06,546 - mmseg - INFO - Iter [46200/160000] lr: 3.750e-05, eta: 9:21:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.6935, loss: 0.0838 2023-03-04 00:39:18,851 - mmseg - INFO - Iter [46250/160000] lr: 3.750e-05, eta: 9:21:12, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7972, loss: 0.0814 2023-03-04 00:39:31,006 - mmseg - INFO - Iter [46300/160000] lr: 3.750e-05, eta: 9:20:51, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.6929, loss: 0.0830 2023-03-04 00:39:45,515 - mmseg - INFO - Iter [46350/160000] lr: 3.750e-05, eta: 9:20:35, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7096, loss: 0.0833 2023-03-04 00:39:57,592 - mmseg - INFO - Iter [46400/160000] lr: 3.750e-05, eta: 9:20:14, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7511, loss: 0.0814 2023-03-04 00:40:09,802 - mmseg - INFO - Iter [46450/160000] lr: 3.750e-05, eta: 9:19:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7257, loss: 0.0828 2023-03-04 00:40:21,869 - mmseg - INFO - Iter [46500/160000] lr: 3.750e-05, eta: 9:19:31, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9439, loss: 0.0767 2023-03-04 00:40:36,469 - mmseg - INFO - Iter [46550/160000] lr: 3.750e-05, eta: 9:19:16, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8147, loss: 0.0804 2023-03-04 00:40:48,619 - mmseg - INFO - Iter [46600/160000] lr: 3.750e-05, eta: 9:18:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.6815, loss: 0.0845 2023-03-04 00:41:00,868 - mmseg - INFO - Iter [46650/160000] lr: 3.750e-05, eta: 9:18:34, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7236, loss: 0.0828 2023-03-04 00:41:15,345 - mmseg - INFO - Iter [46700/160000] lr: 3.750e-05, eta: 9:18:18, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6367, loss: 0.0850 2023-03-04 00:41:27,463 - mmseg - INFO - Iter [46750/160000] lr: 3.750e-05, eta: 9:17:57, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6829, loss: 0.0858 2023-03-04 00:41:39,690 - mmseg - INFO - Iter [46800/160000] lr: 3.750e-05, eta: 9:17:36, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8156, loss: 0.0805 2023-03-04 00:41:51,953 - mmseg - INFO - Iter [46850/160000] lr: 3.750e-05, eta: 9:17:15, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7410, loss: 0.0836 2023-03-04 00:42:06,559 - mmseg - INFO - Iter [46900/160000] lr: 3.750e-05, eta: 9:17:00, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.8164, loss: 0.0818 2023-03-04 00:42:18,893 - mmseg - INFO - Iter [46950/160000] lr: 3.750e-05, eta: 9:16:39, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6346, loss: 0.0858 2023-03-04 00:42:31,010 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:42:31,010 - mmseg - INFO - Iter [47000/160000] lr: 3.750e-05, eta: 9:16:18, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7499, loss: 0.0821 2023-03-04 00:42:43,080 - mmseg - INFO - Iter [47050/160000] lr: 3.750e-05, eta: 9:15:57, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8283, loss: 0.0802 2023-03-04 00:42:57,668 - mmseg - INFO - Iter [47100/160000] lr: 3.750e-05, eta: 9:15:42, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.5943, loss: 0.0857 2023-03-04 00:43:09,855 - mmseg - INFO - Iter [47150/160000] lr: 3.750e-05, eta: 9:15:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.5788, loss: 0.0863 2023-03-04 00:43:22,276 - mmseg - INFO - Iter [47200/160000] lr: 3.750e-05, eta: 9:15:00, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8746, loss: 0.0798 2023-03-04 00:43:36,679 - mmseg - INFO - Iter [47250/160000] lr: 3.750e-05, eta: 9:14:45, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.8137, loss: 0.0819 2023-03-04 00:43:48,845 - mmseg - INFO - Iter [47300/160000] lr: 3.750e-05, eta: 9:14:24, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7796, loss: 0.0819 2023-03-04 00:44:01,034 - mmseg - INFO - Iter [47350/160000] lr: 3.750e-05, eta: 9:14:03, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8401, loss: 0.0805 2023-03-04 00:44:13,204 - mmseg - INFO - Iter [47400/160000] lr: 3.750e-05, eta: 9:13:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7986, loss: 0.0809 2023-03-04 00:44:27,636 - mmseg - INFO - Iter [47450/160000] lr: 3.750e-05, eta: 9:13:27, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7814, loss: 0.0814 2023-03-04 00:44:39,665 - mmseg - INFO - Iter [47500/160000] lr: 3.750e-05, eta: 9:13:05, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7560, loss: 0.0823 2023-03-04 00:44:51,774 - mmseg - INFO - Iter [47550/160000] lr: 3.750e-05, eta: 9:12:44, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8443, loss: 0.0797 2023-03-04 00:45:03,924 - mmseg - INFO - Iter [47600/160000] lr: 3.750e-05, eta: 9:12:23, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6440, loss: 0.0852 2023-03-04 00:45:18,493 - mmseg - INFO - Iter [47650/160000] lr: 3.750e-05, eta: 9:12:08, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0857, decode.acc_seg: 96.6094, loss: 0.0857 2023-03-04 00:45:30,785 - mmseg - INFO - Iter [47700/160000] lr: 3.750e-05, eta: 9:11:48, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7487, loss: 0.0831 2023-03-04 00:45:42,886 - mmseg - INFO - Iter [47750/160000] lr: 3.750e-05, eta: 9:11:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7452, loss: 0.0835 2023-03-04 00:45:55,055 - mmseg - INFO - Iter [47800/160000] lr: 3.750e-05, eta: 9:11:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7542, loss: 0.0828 2023-03-04 00:46:09,504 - mmseg - INFO - Iter [47850/160000] lr: 3.750e-05, eta: 9:10:51, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7939, loss: 0.0812 2023-03-04 00:46:21,653 - mmseg - INFO - Iter [47900/160000] lr: 3.750e-05, eta: 9:10:30, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6870, loss: 0.0844 2023-03-04 00:46:33,885 - mmseg - INFO - Iter [47950/160000] lr: 3.750e-05, eta: 9:10:09, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7502, loss: 0.0814 2023-03-04 00:46:48,432 - mmseg - INFO - Swap parameters (after train) after iter [48000] 2023-03-04 00:46:48,447 - mmseg - INFO - Saving checkpoint at 48000 iterations 2023-03-04 00:46:49,720 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 00:46:49,720 - mmseg - INFO - Iter [48000/160000] lr: 3.750e-05, eta: 9:09:57, time: 0.317, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8271, loss: 0.0811 2023-03-04 01:01:44,622 - mmseg - INFO - per class results: 2023-03-04 01:01:44,624 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.56,98.56,98.56,98.56,98.56,98.56,98.56,98.56,98.57,98.57,98.56 | | sidewalk | 87.65,87.64,87.66,87.67,87.67,87.68,87.67,87.69,87.7,87.72,87.67 | | building | 93.33,93.33,93.33,93.33,93.33,93.34,93.34,93.33,93.33,93.33,93.34 | | wall | 53.98,53.96,53.96,54.08,54.08,54.13,54.08,54.06,54.08,54.08,54.26 | | fence | 63.8,63.83,63.85,63.86,63.88,63.92,63.96,63.91,63.93,63.92,64.0 | | pole | 70.96,70.97,70.97,70.97,70.99,71.0,71.01,71.0,71.01,71.02,71.02 | | traffic light | 75.5,75.5,75.51,75.51,75.48,75.49,75.49,75.48,75.48,75.48,75.45 | | traffic sign | 83.28,83.3,83.3,83.31,83.32,83.3,83.32,83.32,83.33,83.32,83.34 | | vegetation | 92.95,92.96,92.96,92.96,92.96,92.96,92.96,92.96,92.96,92.96,92.96 | | terrain | 65.8,65.81,65.85,65.82,65.84,65.9,65.86,65.84,65.86,65.88,65.79 | | sky | 95.21,95.22,95.22,95.21,95.22,95.23,95.23,95.22,95.22,95.23,95.23 | | person | 84.74,84.74,84.74,84.73,84.74,84.75,84.74,84.73,84.74,84.73,84.75 | | rider | 66.7,66.7,66.72,66.68,66.69,66.71,66.71,66.68,66.71,66.71,66.77 | | car | 95.96,95.97,95.99,96.0,96.0,96.0,96.0,96.0,96.0,96.0,96.01 | | truck | 84.47,84.76,84.92,85.18,85.09,85.2,85.05,85.03,85.07,85.07,85.21 | | bus | 92.41,92.41,92.43,92.45,92.45,92.45,92.44,92.45,92.47,92.46,92.44 | | train | 86.35,86.43,86.36,86.43,86.43,86.4,86.46,86.48,86.48,86.55,86.52 | | motorcycle | 69.2,69.24,69.24,69.21,69.26,69.27,69.27,69.27,69.31,69.32,69.35 | | bicycle | 79.85,79.86,79.85,79.85,79.85,79.85,79.86,79.85,79.86,79.86,79.86 | +---------------+-------------------------------------------------------------------+ 2023-03-04 01:01:44,624 - mmseg - INFO - Summary: 2023-03-04 01:01:44,624 - mmseg - INFO - +-------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +-------------------------------------------------------------------+ | 81.09,81.12,81.13,81.15,81.15,81.16,81.16,81.15,81.16,81.17,81.19 | +-------------------------------------------------------------------+ 2023-03-04 01:01:44,671 - mmseg - INFO - The previous best checkpoint /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune/best_mIoU_iter_32000.pth was removed 2023-03-04 01:01:45,995 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_48000.pth. 2023-03-04 01:01:45,995 - mmseg - INFO - Best mIoU is 0.8119 at 48000 iter. 2023-03-04 01:01:45,996 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:01:45,996 - mmseg - INFO - Iter(val) [63] mIoU: [0.8109, 0.8112, 0.8113, 0.8115, 0.8115, 0.8116, 0.8116, 0.8115, 0.8116, 0.8117, 0.8119], copy_paste: 81.09,81.12,81.13,81.15,81.15,81.16,81.16,81.15,81.16,81.17,81.19 2023-03-04 01:01:46,002 - mmseg - INFO - Swap parameters (before train) before iter [48001] 2023-03-04 01:01:58,484 - mmseg - INFO - Iter [48050/160000] lr: 3.750e-05, eta: 9:44:25, time: 18.175, data_time: 17.934, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7636, loss: 0.0816 2023-03-04 01:02:10,856 - mmseg - INFO - Iter [48100/160000] lr: 3.750e-05, eta: 9:44:02, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7393, loss: 0.0828 2023-03-04 01:02:23,231 - mmseg - INFO - Iter [48150/160000] lr: 3.750e-05, eta: 9:43:39, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9136, loss: 0.0777 2023-03-04 01:02:37,982 - mmseg - INFO - Iter [48200/160000] lr: 3.750e-05, eta: 9:43:21, time: 0.295, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7146, loss: 0.0834 2023-03-04 01:02:50,324 - mmseg - INFO - Iter [48250/160000] lr: 3.750e-05, eta: 9:42:58, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8059, loss: 0.0808 2023-03-04 01:03:02,636 - mmseg - INFO - Iter [48300/160000] lr: 3.750e-05, eta: 9:42:34, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7266, loss: 0.0825 2023-03-04 01:03:14,910 - mmseg - INFO - Iter [48350/160000] lr: 3.750e-05, eta: 9:42:11, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8448, loss: 0.0797 2023-03-04 01:03:29,592 - mmseg - INFO - Iter [48400/160000] lr: 3.750e-05, eta: 9:41:53, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8446, loss: 0.0804 2023-03-04 01:03:41,955 - mmseg - INFO - Iter [48450/160000] lr: 3.750e-05, eta: 9:41:30, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7645, loss: 0.0822 2023-03-04 01:03:54,154 - mmseg - INFO - Iter [48500/160000] lr: 3.750e-05, eta: 9:41:06, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8138, loss: 0.0802 2023-03-04 01:04:08,780 - mmseg - INFO - Iter [48550/160000] lr: 3.750e-05, eta: 9:40:48, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8087, loss: 0.0799 2023-03-04 01:04:21,019 - mmseg - INFO - Iter [48600/160000] lr: 3.750e-05, eta: 9:40:25, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8559, loss: 0.0803 2023-03-04 01:04:33,209 - mmseg - INFO - Iter [48650/160000] lr: 3.750e-05, eta: 9:40:01, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7771, loss: 0.0811 2023-03-04 01:04:45,415 - mmseg - INFO - Iter [48700/160000] lr: 3.750e-05, eta: 9:39:38, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5900, loss: 0.0869 2023-03-04 01:05:00,044 - mmseg - INFO - Iter [48750/160000] lr: 3.750e-05, eta: 9:39:20, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7007, loss: 0.0834 2023-03-04 01:05:12,321 - mmseg - INFO - Iter [48800/160000] lr: 3.750e-05, eta: 9:38:57, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7509, loss: 0.0828 2023-03-04 01:05:24,503 - mmseg - INFO - Iter [48850/160000] lr: 3.750e-05, eta: 9:38:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7501, loss: 0.0818 2023-03-04 01:05:36,738 - mmseg - INFO - Iter [48900/160000] lr: 3.750e-05, eta: 9:38:10, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7957, loss: 0.0811 2023-03-04 01:05:51,160 - mmseg - INFO - Iter [48950/160000] lr: 3.750e-05, eta: 9:37:52, time: 0.288, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7827, loss: 0.0819 2023-03-04 01:06:03,444 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:06:03,444 - mmseg - INFO - Iter [49000/160000] lr: 3.750e-05, eta: 9:37:29, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7366, loss: 0.0830 2023-03-04 01:06:15,527 - mmseg - INFO - Iter [49050/160000] lr: 3.750e-05, eta: 9:37:05, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7685, loss: 0.0816 2023-03-04 01:06:27,629 - mmseg - INFO - Iter [49100/160000] lr: 3.750e-05, eta: 9:36:42, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6443, loss: 0.0854 2023-03-04 01:06:42,278 - mmseg - INFO - Iter [49150/160000] lr: 3.750e-05, eta: 9:36:24, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6471, loss: 0.0858 2023-03-04 01:06:54,393 - mmseg - INFO - Iter [49200/160000] lr: 3.750e-05, eta: 9:36:00, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8108, loss: 0.0803 2023-03-04 01:07:06,560 - mmseg - INFO - Iter [49250/160000] lr: 3.750e-05, eta: 9:35:37, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7950, loss: 0.0819 2023-03-04 01:07:21,242 - mmseg - INFO - Iter [49300/160000] lr: 3.750e-05, eta: 9:35:19, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8343, loss: 0.0792 2023-03-04 01:07:33,306 - mmseg - INFO - Iter [49350/160000] lr: 3.750e-05, eta: 9:34:56, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0890, decode.acc_seg: 96.6385, loss: 0.0890 2023-03-04 01:07:45,607 - mmseg - INFO - Iter [49400/160000] lr: 3.750e-05, eta: 9:34:33, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9426, loss: 0.0769 2023-03-04 01:07:57,816 - mmseg - INFO - Iter [49450/160000] lr: 3.750e-05, eta: 9:34:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7275, loss: 0.0827 2023-03-04 01:08:12,235 - mmseg - INFO - Iter [49500/160000] lr: 3.750e-05, eta: 9:33:52, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7305, loss: 0.0819 2023-03-04 01:08:24,612 - mmseg - INFO - Iter [49550/160000] lr: 3.750e-05, eta: 9:33:29, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7844, loss: 0.0822 2023-03-04 01:08:36,826 - mmseg - INFO - Iter [49600/160000] lr: 3.750e-05, eta: 9:33:06, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7340, loss: 0.0831 2023-03-04 01:08:49,005 - mmseg - INFO - Iter [49650/160000] lr: 3.750e-05, eta: 9:32:43, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6963, loss: 0.0840 2023-03-04 01:09:03,543 - mmseg - INFO - Iter [49700/160000] lr: 3.750e-05, eta: 9:32:25, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0865, decode.acc_seg: 96.5985, loss: 0.0865 2023-03-04 01:09:15,723 - mmseg - INFO - Iter [49750/160000] lr: 3.750e-05, eta: 9:32:02, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7058, loss: 0.0839 2023-03-04 01:09:27,864 - mmseg - INFO - Iter [49800/160000] lr: 3.750e-05, eta: 9:31:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6919, loss: 0.0835 2023-03-04 01:09:42,343 - mmseg - INFO - Iter [49850/160000] lr: 3.750e-05, eta: 9:31:21, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7482, loss: 0.0819 2023-03-04 01:09:54,556 - mmseg - INFO - Iter [49900/160000] lr: 3.750e-05, eta: 9:30:58, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7425, loss: 0.0814 2023-03-04 01:10:06,806 - mmseg - INFO - Iter [49950/160000] lr: 3.750e-05, eta: 9:30:35, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7366, loss: 0.0817 2023-03-04 01:10:19,083 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:10:19,083 - mmseg - INFO - Iter [50000/160000] lr: 3.750e-05, eta: 9:30:12, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7490, loss: 0.0823 2023-03-04 01:10:33,652 - mmseg - INFO - Iter [50050/160000] lr: 3.750e-05, eta: 9:29:54, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7609, loss: 0.0822 2023-03-04 01:10:45,820 - mmseg - INFO - Iter [50100/160000] lr: 3.750e-05, eta: 9:29:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6686, loss: 0.0850 2023-03-04 01:10:58,003 - mmseg - INFO - Iter [50150/160000] lr: 3.750e-05, eta: 9:29:09, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.6916, loss: 0.0827 2023-03-04 01:11:10,130 - mmseg - INFO - Iter [50200/160000] lr: 3.750e-05, eta: 9:28:46, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7996, loss: 0.0813 2023-03-04 01:11:24,624 - mmseg - INFO - Iter [50250/160000] lr: 3.750e-05, eta: 9:28:28, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.7221, loss: 0.0853 2023-03-04 01:11:36,823 - mmseg - INFO - Iter [50300/160000] lr: 3.750e-05, eta: 9:28:05, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7816, loss: 0.0811 2023-03-04 01:11:49,186 - mmseg - INFO - Iter [50350/160000] lr: 3.750e-05, eta: 9:27:42, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8210, loss: 0.0802 2023-03-04 01:12:01,226 - mmseg - INFO - Iter [50400/160000] lr: 3.750e-05, eta: 9:27:19, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7545, loss: 0.0825 2023-03-04 01:12:15,717 - mmseg - INFO - Iter [50450/160000] lr: 3.750e-05, eta: 9:27:02, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7795, loss: 0.0821 2023-03-04 01:12:27,859 - mmseg - INFO - Iter [50500/160000] lr: 3.750e-05, eta: 9:26:39, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7439, loss: 0.0817 2023-03-04 01:12:40,325 - mmseg - INFO - Iter [50550/160000] lr: 3.750e-05, eta: 9:26:16, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7862, loss: 0.0812 2023-03-04 01:12:54,760 - mmseg - INFO - Iter [50600/160000] lr: 3.750e-05, eta: 9:25:59, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7319, loss: 0.0821 2023-03-04 01:13:07,008 - mmseg - INFO - Iter [50650/160000] lr: 3.750e-05, eta: 9:25:36, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7528, loss: 0.0815 2023-03-04 01:13:19,193 - mmseg - INFO - Iter [50700/160000] lr: 3.750e-05, eta: 9:25:13, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7809, loss: 0.0819 2023-03-04 01:13:31,410 - mmseg - INFO - Iter [50750/160000] lr: 3.750e-05, eta: 9:24:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7956, loss: 0.0807 2023-03-04 01:13:45,827 - mmseg - INFO - Iter [50800/160000] lr: 3.750e-05, eta: 9:24:33, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6755, loss: 0.0849 2023-03-04 01:13:58,066 - mmseg - INFO - Iter [50850/160000] lr: 3.750e-05, eta: 9:24:10, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7915, loss: 0.0819 2023-03-04 01:14:10,203 - mmseg - INFO - Iter [50900/160000] lr: 3.750e-05, eta: 9:23:48, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7576, loss: 0.0822 2023-03-04 01:14:22,318 - mmseg - INFO - Iter [50950/160000] lr: 3.750e-05, eta: 9:23:25, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.8042, loss: 0.0817 2023-03-04 01:14:36,863 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:14:36,863 - mmseg - INFO - Iter [51000/160000] lr: 3.750e-05, eta: 9:23:07, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8038, loss: 0.0811 2023-03-04 01:14:49,166 - mmseg - INFO - Iter [51050/160000] lr: 3.750e-05, eta: 9:22:45, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6368, loss: 0.0851 2023-03-04 01:15:01,355 - mmseg - INFO - Iter [51100/160000] lr: 3.750e-05, eta: 9:22:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8521, loss: 0.0789 2023-03-04 01:15:13,519 - mmseg - INFO - Iter [51150/160000] lr: 3.750e-05, eta: 9:22:00, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7881, loss: 0.0824 2023-03-04 01:15:28,257 - mmseg - INFO - Iter [51200/160000] lr: 3.750e-05, eta: 9:21:43, time: 0.295, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9015, loss: 0.0785 2023-03-04 01:15:40,345 - mmseg - INFO - Iter [51250/160000] lr: 3.750e-05, eta: 9:21:20, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.5982, loss: 0.0853 2023-03-04 01:15:52,470 - mmseg - INFO - Iter [51300/160000] lr: 3.750e-05, eta: 9:20:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7235, loss: 0.0832 2023-03-04 01:16:06,943 - mmseg - INFO - Iter [51350/160000] lr: 3.750e-05, eta: 9:20:40, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7984, loss: 0.0813 2023-03-04 01:16:19,205 - mmseg - INFO - Iter [51400/160000] lr: 3.750e-05, eta: 9:20:18, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.7948, loss: 0.0802 2023-03-04 01:16:31,497 - mmseg - INFO - Iter [51450/160000] lr: 3.750e-05, eta: 9:19:55, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8397, loss: 0.0799 2023-03-04 01:16:43,721 - mmseg - INFO - Iter [51500/160000] lr: 3.750e-05, eta: 9:19:33, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7599, loss: 0.0818 2023-03-04 01:16:58,164 - mmseg - INFO - Iter [51550/160000] lr: 3.750e-05, eta: 9:19:15, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8731, loss: 0.0789 2023-03-04 01:17:10,362 - mmseg - INFO - Iter [51600/160000] lr: 3.750e-05, eta: 9:18:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6755, loss: 0.0847 2023-03-04 01:17:22,491 - mmseg - INFO - Iter [51650/160000] lr: 3.750e-05, eta: 9:18:31, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8211, loss: 0.0808 2023-03-04 01:17:34,575 - mmseg - INFO - Iter [51700/160000] lr: 3.750e-05, eta: 9:18:08, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7171, loss: 0.0832 2023-03-04 01:17:49,159 - mmseg - INFO - Iter [51750/160000] lr: 3.750e-05, eta: 9:17:51, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7926, loss: 0.0815 2023-03-04 01:18:01,395 - mmseg - INFO - Iter [51800/160000] lr: 3.750e-05, eta: 9:17:29, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8797, loss: 0.0793 2023-03-04 01:18:13,447 - mmseg - INFO - Iter [51850/160000] lr: 3.750e-05, eta: 9:17:06, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8208, loss: 0.0803 2023-03-04 01:18:28,007 - mmseg - INFO - Iter [51900/160000] lr: 3.750e-05, eta: 9:16:49, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.6802, loss: 0.0838 2023-03-04 01:18:40,186 - mmseg - INFO - Iter [51950/160000] lr: 3.750e-05, eta: 9:16:26, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7844, loss: 0.0816 2023-03-04 01:18:52,376 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:18:52,377 - mmseg - INFO - Iter [52000/160000] lr: 3.750e-05, eta: 9:16:04, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7890, loss: 0.0814 2023-03-04 01:19:04,574 - mmseg - INFO - Iter [52050/160000] lr: 3.750e-05, eta: 9:15:42, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8522, loss: 0.0793 2023-03-04 01:19:19,078 - mmseg - INFO - Iter [52100/160000] lr: 3.750e-05, eta: 9:15:25, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8683, loss: 0.0793 2023-03-04 01:19:31,285 - mmseg - INFO - Iter [52150/160000] lr: 3.750e-05, eta: 9:15:02, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7657, loss: 0.0814 2023-03-04 01:19:43,542 - mmseg - INFO - Iter [52200/160000] lr: 3.750e-05, eta: 9:14:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.8024, loss: 0.0822 2023-03-04 01:19:55,802 - mmseg - INFO - Iter [52250/160000] lr: 3.750e-05, eta: 9:14:18, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7036, loss: 0.0833 2023-03-04 01:20:10,323 - mmseg - INFO - Iter [52300/160000] lr: 3.750e-05, eta: 9:14:01, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7831, loss: 0.0819 2023-03-04 01:20:22,497 - mmseg - INFO - Iter [52350/160000] lr: 3.750e-05, eta: 9:13:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7366, loss: 0.0828 2023-03-04 01:20:34,692 - mmseg - INFO - Iter [52400/160000] lr: 3.750e-05, eta: 9:13:17, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7154, loss: 0.0834 2023-03-04 01:20:46,854 - mmseg - INFO - Iter [52450/160000] lr: 3.750e-05, eta: 9:12:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7578, loss: 0.0831 2023-03-04 01:21:01,355 - mmseg - INFO - Iter [52500/160000] lr: 3.750e-05, eta: 9:12:38, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6409, loss: 0.0850 2023-03-04 01:21:13,533 - mmseg - INFO - Iter [52550/160000] lr: 3.750e-05, eta: 9:12:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.7035, loss: 0.0846 2023-03-04 01:21:25,680 - mmseg - INFO - Iter [52600/160000] lr: 3.750e-05, eta: 9:11:53, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7835, loss: 0.0815 2023-03-04 01:21:40,122 - mmseg - INFO - Iter [52650/160000] lr: 3.750e-05, eta: 9:11:36, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8297, loss: 0.0802 2023-03-04 01:21:52,320 - mmseg - INFO - Iter [52700/160000] lr: 3.750e-05, eta: 9:11:14, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7993, loss: 0.0815 2023-03-04 01:22:04,566 - mmseg - INFO - Iter [52750/160000] lr: 3.750e-05, eta: 9:10:52, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6250, loss: 0.0852 2023-03-04 01:22:16,787 - mmseg - INFO - Iter [52800/160000] lr: 3.750e-05, eta: 9:10:30, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7385, loss: 0.0819 2023-03-04 01:22:31,324 - mmseg - INFO - Iter [52850/160000] lr: 3.750e-05, eta: 9:10:13, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8721, loss: 0.0786 2023-03-04 01:22:43,703 - mmseg - INFO - Iter [52900/160000] lr: 3.750e-05, eta: 9:09:52, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8631, loss: 0.0787 2023-03-04 01:22:55,780 - mmseg - INFO - Iter [52950/160000] lr: 3.750e-05, eta: 9:09:29, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7331, loss: 0.0831 2023-03-04 01:23:07,956 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:23:07,956 - mmseg - INFO - Iter [53000/160000] lr: 3.750e-05, eta: 9:09:08, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.6841, loss: 0.0861 2023-03-04 01:23:22,495 - mmseg - INFO - Iter [53050/160000] lr: 3.750e-05, eta: 9:08:50, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7647, loss: 0.0818 2023-03-04 01:23:34,616 - mmseg - INFO - Iter [53100/160000] lr: 3.750e-05, eta: 9:08:28, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8063, loss: 0.0801 2023-03-04 01:23:46,915 - mmseg - INFO - Iter [53150/160000] lr: 3.750e-05, eta: 9:08:07, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.5745, loss: 0.0860 2023-03-04 01:24:01,382 - mmseg - INFO - Iter [53200/160000] lr: 3.750e-05, eta: 9:07:50, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8703, loss: 0.0794 2023-03-04 01:24:13,581 - mmseg - INFO - Iter [53250/160000] lr: 3.750e-05, eta: 9:07:28, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7660, loss: 0.0825 2023-03-04 01:24:25,785 - mmseg - INFO - Iter [53300/160000] lr: 3.750e-05, eta: 9:07:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7451, loss: 0.0821 2023-03-04 01:24:37,922 - mmseg - INFO - Iter [53350/160000] lr: 3.750e-05, eta: 9:06:44, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7815, loss: 0.0811 2023-03-04 01:24:52,613 - mmseg - INFO - Iter [53400/160000] lr: 3.750e-05, eta: 9:06:27, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6619, loss: 0.0839 2023-03-04 01:25:04,738 - mmseg - INFO - Iter [53450/160000] lr: 3.750e-05, eta: 9:06:06, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8549, loss: 0.0791 2023-03-04 01:25:16,854 - mmseg - INFO - Iter [53500/160000] lr: 3.750e-05, eta: 9:05:44, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7562, loss: 0.0826 2023-03-04 01:25:29,143 - mmseg - INFO - Iter [53550/160000] lr: 3.750e-05, eta: 9:05:22, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7507, loss: 0.0821 2023-03-04 01:25:43,713 - mmseg - INFO - Iter [53600/160000] lr: 3.750e-05, eta: 9:05:05, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.7611, loss: 0.0840 2023-03-04 01:25:55,986 - mmseg - INFO - Iter [53650/160000] lr: 3.750e-05, eta: 9:04:44, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8757, loss: 0.0786 2023-03-04 01:26:08,260 - mmseg - INFO - Iter [53700/160000] lr: 3.750e-05, eta: 9:04:22, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0876, decode.acc_seg: 96.6167, loss: 0.0876 2023-03-04 01:26:20,494 - mmseg - INFO - Iter [53750/160000] lr: 3.750e-05, eta: 9:04:01, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.6936, loss: 0.0828 2023-03-04 01:26:35,029 - mmseg - INFO - Iter [53800/160000] lr: 3.750e-05, eta: 9:03:44, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8085, loss: 0.0816 2023-03-04 01:26:47,161 - mmseg - INFO - Iter [53850/160000] lr: 3.750e-05, eta: 9:03:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.7818, loss: 0.0804 2023-03-04 01:26:59,296 - mmseg - INFO - Iter [53900/160000] lr: 3.750e-05, eta: 9:03:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7293, loss: 0.0832 2023-03-04 01:27:13,998 - mmseg - INFO - Iter [53950/160000] lr: 3.750e-05, eta: 9:02:44, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8646, loss: 0.0793 2023-03-04 01:27:26,304 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:27:26,304 - mmseg - INFO - Iter [54000/160000] lr: 3.750e-05, eta: 9:02:22, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7520, loss: 0.0822 2023-03-04 01:27:38,526 - mmseg - INFO - Iter [54050/160000] lr: 3.750e-05, eta: 9:02:01, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8963, loss: 0.0788 2023-03-04 01:27:50,605 - mmseg - INFO - Iter [54100/160000] lr: 3.750e-05, eta: 9:01:39, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7160, loss: 0.0834 2023-03-04 01:28:05,131 - mmseg - INFO - Iter [54150/160000] lr: 3.750e-05, eta: 9:01:22, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7713, loss: 0.0815 2023-03-04 01:28:17,312 - mmseg - INFO - Iter [54200/160000] lr: 3.750e-05, eta: 9:01:01, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7695, loss: 0.0817 2023-03-04 01:28:29,490 - mmseg - INFO - Iter [54250/160000] lr: 3.750e-05, eta: 9:00:39, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8128, loss: 0.0813 2023-03-04 01:28:41,875 - mmseg - INFO - Iter [54300/160000] lr: 3.750e-05, eta: 9:00:18, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.6169, loss: 0.0856 2023-03-04 01:28:56,556 - mmseg - INFO - Iter [54350/160000] lr: 3.750e-05, eta: 9:00:01, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7089, loss: 0.0824 2023-03-04 01:29:08,694 - mmseg - INFO - Iter [54400/160000] lr: 3.750e-05, eta: 8:59:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7520, loss: 0.0829 2023-03-04 01:29:20,940 - mmseg - INFO - Iter [54450/160000] lr: 3.750e-05, eta: 8:59:19, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8922, loss: 0.0778 2023-03-04 01:29:35,524 - mmseg - INFO - Iter [54500/160000] lr: 3.750e-05, eta: 8:59:02, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7740, loss: 0.0811 2023-03-04 01:29:47,711 - mmseg - INFO - Iter [54550/160000] lr: 3.750e-05, eta: 8:58:40, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.7146, loss: 0.0843 2023-03-04 01:29:59,856 - mmseg - INFO - Iter [54600/160000] lr: 3.750e-05, eta: 8:58:19, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.9296, loss: 0.0791 2023-03-04 01:30:11,940 - mmseg - INFO - Iter [54650/160000] lr: 3.750e-05, eta: 8:57:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7655, loss: 0.0823 2023-03-04 01:30:26,346 - mmseg - INFO - Iter [54700/160000] lr: 3.750e-05, eta: 8:57:40, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.6621, loss: 0.0839 2023-03-04 01:30:38,664 - mmseg - INFO - Iter [54750/160000] lr: 3.750e-05, eta: 8:57:19, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7239, loss: 0.0827 2023-03-04 01:30:50,865 - mmseg - INFO - Iter [54800/160000] lr: 3.750e-05, eta: 8:56:58, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8534, loss: 0.0788 2023-03-04 01:31:03,021 - mmseg - INFO - Iter [54850/160000] lr: 3.750e-05, eta: 8:56:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7037, loss: 0.0828 2023-03-04 01:31:17,526 - mmseg - INFO - Iter [54900/160000] lr: 3.750e-05, eta: 8:56:20, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8079, loss: 0.0810 2023-03-04 01:31:29,896 - mmseg - INFO - Iter [54950/160000] lr: 3.750e-05, eta: 8:55:59, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7894, loss: 0.0810 2023-03-04 01:31:41,981 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:31:41,981 - mmseg - INFO - Iter [55000/160000] lr: 3.750e-05, eta: 8:55:37, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8788, loss: 0.0792 2023-03-04 01:31:54,150 - mmseg - INFO - Iter [55050/160000] lr: 3.750e-05, eta: 8:55:16, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7902, loss: 0.0813 2023-03-04 01:32:08,735 - mmseg - INFO - Iter [55100/160000] lr: 3.750e-05, eta: 8:54:59, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7650, loss: 0.0824 2023-03-04 01:32:20,939 - mmseg - INFO - Iter [55150/160000] lr: 3.750e-05, eta: 8:54:38, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7103, loss: 0.0818 2023-03-04 01:32:33,306 - mmseg - INFO - Iter [55200/160000] lr: 3.750e-05, eta: 8:54:17, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8365, loss: 0.0808 2023-03-04 01:32:47,899 - mmseg - INFO - Iter [55250/160000] lr: 3.750e-05, eta: 8:54:01, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.8467, loss: 0.0825 2023-03-04 01:33:00,005 - mmseg - INFO - Iter [55300/160000] lr: 3.750e-05, eta: 8:53:39, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9393, loss: 0.0785 2023-03-04 01:33:12,195 - mmseg - INFO - Iter [55350/160000] lr: 3.750e-05, eta: 8:53:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7350, loss: 0.0823 2023-03-04 01:33:24,527 - mmseg - INFO - Iter [55400/160000] lr: 3.750e-05, eta: 8:52:57, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9044, loss: 0.0782 2023-03-04 01:33:39,053 - mmseg - INFO - Iter [55450/160000] lr: 3.750e-05, eta: 8:52:41, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8293, loss: 0.0806 2023-03-04 01:33:51,326 - mmseg - INFO - Iter [55500/160000] lr: 3.750e-05, eta: 8:52:20, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.6935, loss: 0.0831 2023-03-04 01:34:03,652 - mmseg - INFO - Iter [55550/160000] lr: 3.750e-05, eta: 8:51:59, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.6993, loss: 0.0826 2023-03-04 01:34:15,954 - mmseg - INFO - Iter [55600/160000] lr: 3.750e-05, eta: 8:51:38, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9398, loss: 0.0769 2023-03-04 01:34:30,399 - mmseg - INFO - Iter [55650/160000] lr: 3.750e-05, eta: 8:51:21, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7752, loss: 0.0832 2023-03-04 01:34:42,690 - mmseg - INFO - Iter [55700/160000] lr: 3.750e-05, eta: 8:51:00, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7991, loss: 0.0818 2023-03-04 01:34:54,963 - mmseg - INFO - Iter [55750/160000] lr: 3.750e-05, eta: 8:50:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7177, loss: 0.0824 2023-03-04 01:35:07,114 - mmseg - INFO - Iter [55800/160000] lr: 3.750e-05, eta: 8:50:18, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7087, loss: 0.0830 2023-03-04 01:35:21,575 - mmseg - INFO - Iter [55850/160000] lr: 3.750e-05, eta: 8:50:01, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.7967, loss: 0.0802 2023-03-04 01:35:33,948 - mmseg - INFO - Iter [55900/160000] lr: 3.750e-05, eta: 8:49:41, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8232, loss: 0.0804 2023-03-04 01:35:46,291 - mmseg - INFO - Iter [55950/160000] lr: 3.750e-05, eta: 8:49:20, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7166, loss: 0.0839 2023-03-04 01:36:00,840 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:36:00,840 - mmseg - INFO - Iter [56000/160000] lr: 3.750e-05, eta: 8:49:03, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6395, loss: 0.0852 2023-03-04 01:36:13,000 - mmseg - INFO - Iter [56050/160000] lr: 3.750e-05, eta: 8:48:42, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6603, loss: 0.0840 2023-03-04 01:36:25,300 - mmseg - INFO - Iter [56100/160000] lr: 3.750e-05, eta: 8:48:22, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6451, loss: 0.0852 2023-03-04 01:36:37,440 - mmseg - INFO - Iter [56150/160000] lr: 3.750e-05, eta: 8:48:01, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7747, loss: 0.0817 2023-03-04 01:36:51,947 - mmseg - INFO - Iter [56200/160000] lr: 3.750e-05, eta: 8:47:44, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6616, loss: 0.0841 2023-03-04 01:37:04,177 - mmseg - INFO - Iter [56250/160000] lr: 3.750e-05, eta: 8:47:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7081, loss: 0.0839 2023-03-04 01:37:16,556 - mmseg - INFO - Iter [56300/160000] lr: 3.750e-05, eta: 8:47:03, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8955, loss: 0.0782 2023-03-04 01:37:28,878 - mmseg - INFO - Iter [56350/160000] lr: 3.750e-05, eta: 8:46:42, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8126, loss: 0.0807 2023-03-04 01:37:43,362 - mmseg - INFO - Iter [56400/160000] lr: 3.750e-05, eta: 8:46:25, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8175, loss: 0.0811 2023-03-04 01:37:55,551 - mmseg - INFO - Iter [56450/160000] lr: 3.750e-05, eta: 8:46:05, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6331, loss: 0.0866 2023-03-04 01:38:07,896 - mmseg - INFO - Iter [56500/160000] lr: 3.750e-05, eta: 8:45:44, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7529, loss: 0.0823 2023-03-04 01:38:22,470 - mmseg - INFO - Iter [56550/160000] lr: 3.750e-05, eta: 8:45:28, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7926, loss: 0.0814 2023-03-04 01:38:34,689 - mmseg - INFO - Iter [56600/160000] lr: 3.750e-05, eta: 8:45:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8418, loss: 0.0802 2023-03-04 01:38:46,957 - mmseg - INFO - Iter [56650/160000] lr: 3.750e-05, eta: 8:44:46, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8581, loss: 0.0799 2023-03-04 01:38:59,245 - mmseg - INFO - Iter [56700/160000] lr: 3.750e-05, eta: 8:44:26, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7385, loss: 0.0834 2023-03-04 01:39:13,667 - mmseg - INFO - Iter [56750/160000] lr: 3.750e-05, eta: 8:44:09, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7597, loss: 0.0816 2023-03-04 01:39:25,949 - mmseg - INFO - Iter [56800/160000] lr: 3.750e-05, eta: 8:43:48, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8154, loss: 0.0806 2023-03-04 01:39:38,082 - mmseg - INFO - Iter [56850/160000] lr: 3.750e-05, eta: 8:43:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7607, loss: 0.0820 2023-03-04 01:39:50,254 - mmseg - INFO - Iter [56900/160000] lr: 3.750e-05, eta: 8:43:07, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7467, loss: 0.0825 2023-03-04 01:40:04,814 - mmseg - INFO - Iter [56950/160000] lr: 3.750e-05, eta: 8:42:50, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.6637, loss: 0.0838 2023-03-04 01:40:16,929 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:40:16,930 - mmseg - INFO - Iter [57000/160000] lr: 3.750e-05, eta: 8:42:29, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8895, loss: 0.0780 2023-03-04 01:40:29,154 - mmseg - INFO - Iter [57050/160000] lr: 3.750e-05, eta: 8:42:09, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7857, loss: 0.0825 2023-03-04 01:40:41,415 - mmseg - INFO - Iter [57100/160000] lr: 3.750e-05, eta: 8:41:48, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6741, loss: 0.0853 2023-03-04 01:40:55,930 - mmseg - INFO - Iter [57150/160000] lr: 3.750e-05, eta: 8:41:32, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7969, loss: 0.0816 2023-03-04 01:41:08,210 - mmseg - INFO - Iter [57200/160000] lr: 3.750e-05, eta: 8:41:11, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8024, loss: 0.0802 2023-03-04 01:41:20,362 - mmseg - INFO - Iter [57250/160000] lr: 3.750e-05, eta: 8:40:51, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8577, loss: 0.0801 2023-03-04 01:41:34,861 - mmseg - INFO - Iter [57300/160000] lr: 3.750e-05, eta: 8:40:34, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7624, loss: 0.0821 2023-03-04 01:41:47,096 - mmseg - INFO - Iter [57350/160000] lr: 3.750e-05, eta: 8:40:14, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7675, loss: 0.0811 2023-03-04 01:41:59,274 - mmseg - INFO - Iter [57400/160000] lr: 3.750e-05, eta: 8:39:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8764, loss: 0.0784 2023-03-04 01:42:11,399 - mmseg - INFO - Iter [57450/160000] lr: 3.750e-05, eta: 8:39:32, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7963, loss: 0.0826 2023-03-04 01:42:25,860 - mmseg - INFO - Iter [57500/160000] lr: 3.750e-05, eta: 8:39:16, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8083, loss: 0.0813 2023-03-04 01:42:38,091 - mmseg - INFO - Iter [57550/160000] lr: 3.750e-05, eta: 8:38:55, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7120, loss: 0.0830 2023-03-04 01:42:50,267 - mmseg - INFO - Iter [57600/160000] lr: 3.750e-05, eta: 8:38:35, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7677, loss: 0.0820 2023-03-04 01:43:02,414 - mmseg - INFO - Iter [57650/160000] lr: 3.750e-05, eta: 8:38:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7436, loss: 0.0821 2023-03-04 01:43:16,939 - mmseg - INFO - Iter [57700/160000] lr: 3.750e-05, eta: 8:37:58, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8518, loss: 0.0791 2023-03-04 01:43:29,129 - mmseg - INFO - Iter [57750/160000] lr: 3.750e-05, eta: 8:37:37, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7501, loss: 0.0815 2023-03-04 01:43:41,369 - mmseg - INFO - Iter [57800/160000] lr: 3.750e-05, eta: 8:37:17, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7317, loss: 0.0829 2023-03-04 01:43:55,895 - mmseg - INFO - Iter [57850/160000] lr: 3.750e-05, eta: 8:37:01, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7720, loss: 0.0811 2023-03-04 01:44:08,162 - mmseg - INFO - Iter [57900/160000] lr: 3.750e-05, eta: 8:36:40, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6546, loss: 0.0850 2023-03-04 01:44:20,349 - mmseg - INFO - Iter [57950/160000] lr: 3.750e-05, eta: 8:36:20, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.6945, loss: 0.0829 2023-03-04 01:44:32,420 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:44:32,420 - mmseg - INFO - Iter [58000/160000] lr: 3.750e-05, eta: 8:35:59, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7914, loss: 0.0816 2023-03-04 01:44:46,979 - mmseg - INFO - Iter [58050/160000] lr: 3.750e-05, eta: 8:35:43, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8958, loss: 0.0782 2023-03-04 01:44:59,283 - mmseg - INFO - Iter [58100/160000] lr: 3.750e-05, eta: 8:35:23, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8392, loss: 0.0801 2023-03-04 01:45:11,601 - mmseg - INFO - Iter [58150/160000] lr: 3.750e-05, eta: 8:35:02, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8851, loss: 0.0793 2023-03-04 01:45:23,749 - mmseg - INFO - Iter [58200/160000] lr: 3.750e-05, eta: 8:34:42, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7933, loss: 0.0813 2023-03-04 01:45:38,366 - mmseg - INFO - Iter [58250/160000] lr: 3.750e-05, eta: 8:34:26, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8336, loss: 0.0808 2023-03-04 01:45:50,584 - mmseg - INFO - Iter [58300/160000] lr: 3.750e-05, eta: 8:34:06, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8185, loss: 0.0803 2023-03-04 01:46:02,942 - mmseg - INFO - Iter [58350/160000] lr: 3.750e-05, eta: 8:33:45, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9462, loss: 0.0776 2023-03-04 01:46:15,202 - mmseg - INFO - Iter [58400/160000] lr: 3.750e-05, eta: 8:33:25, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7502, loss: 0.0819 2023-03-04 01:46:29,706 - mmseg - INFO - Iter [58450/160000] lr: 3.750e-05, eta: 8:33:09, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7630, loss: 0.0820 2023-03-04 01:46:41,893 - mmseg - INFO - Iter [58500/160000] lr: 3.750e-05, eta: 8:32:49, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7354, loss: 0.0825 2023-03-04 01:46:54,034 - mmseg - INFO - Iter [58550/160000] lr: 3.750e-05, eta: 8:32:28, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7982, loss: 0.0807 2023-03-04 01:47:08,473 - mmseg - INFO - Iter [58600/160000] lr: 3.750e-05, eta: 8:32:12, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8657, loss: 0.0794 2023-03-04 01:47:20,606 - mmseg - INFO - Iter [58650/160000] lr: 3.750e-05, eta: 8:31:52, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8045, loss: 0.0815 2023-03-04 01:47:32,770 - mmseg - INFO - Iter [58700/160000] lr: 3.750e-05, eta: 8:31:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8029, loss: 0.0810 2023-03-04 01:47:44,988 - mmseg - INFO - Iter [58750/160000] lr: 3.750e-05, eta: 8:31:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7447, loss: 0.0818 2023-03-04 01:47:59,492 - mmseg - INFO - Iter [58800/160000] lr: 3.750e-05, eta: 8:30:55, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8271, loss: 0.0797 2023-03-04 01:48:11,641 - mmseg - INFO - Iter [58850/160000] lr: 3.750e-05, eta: 8:30:34, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8102, loss: 0.0804 2023-03-04 01:48:23,871 - mmseg - INFO - Iter [58900/160000] lr: 3.750e-05, eta: 8:30:14, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7593, loss: 0.0822 2023-03-04 01:48:36,147 - mmseg - INFO - Iter [58950/160000] lr: 3.750e-05, eta: 8:29:54, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8075, loss: 0.0801 2023-03-04 01:48:50,640 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:48:50,640 - mmseg - INFO - Iter [59000/160000] lr: 3.750e-05, eta: 8:29:38, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6488, loss: 0.0846 2023-03-04 01:49:02,907 - mmseg - INFO - Iter [59050/160000] lr: 3.750e-05, eta: 8:29:18, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7255, loss: 0.0831 2023-03-04 01:49:15,307 - mmseg - INFO - Iter [59100/160000] lr: 3.750e-05, eta: 8:28:58, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7824, loss: 0.0825 2023-03-04 01:49:29,863 - mmseg - INFO - Iter [59150/160000] lr: 3.750e-05, eta: 8:28:42, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7853, loss: 0.0811 2023-03-04 01:49:42,012 - mmseg - INFO - Iter [59200/160000] lr: 3.750e-05, eta: 8:28:22, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7965, loss: 0.0810 2023-03-04 01:49:54,225 - mmseg - INFO - Iter [59250/160000] lr: 3.750e-05, eta: 8:28:02, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9053, loss: 0.0780 2023-03-04 01:50:06,336 - mmseg - INFO - Iter [59300/160000] lr: 3.750e-05, eta: 8:27:41, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7454, loss: 0.0822 2023-03-04 01:50:20,922 - mmseg - INFO - Iter [59350/160000] lr: 3.750e-05, eta: 8:27:25, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8123, loss: 0.0805 2023-03-04 01:50:33,101 - mmseg - INFO - Iter [59400/160000] lr: 3.750e-05, eta: 8:27:05, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8699, loss: 0.0793 2023-03-04 01:50:45,299 - mmseg - INFO - Iter [59450/160000] lr: 3.750e-05, eta: 8:26:45, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6275, loss: 0.0847 2023-03-04 01:50:57,674 - mmseg - INFO - Iter [59500/160000] lr: 3.750e-05, eta: 8:26:25, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6973, loss: 0.0836 2023-03-04 01:51:12,189 - mmseg - INFO - Iter [59550/160000] lr: 3.750e-05, eta: 8:26:09, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7613, loss: 0.0827 2023-03-04 01:51:24,371 - mmseg - INFO - Iter [59600/160000] lr: 3.750e-05, eta: 8:25:49, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8407, loss: 0.0807 2023-03-04 01:51:36,525 - mmseg - INFO - Iter [59650/160000] lr: 3.750e-05, eta: 8:25:29, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.6932, loss: 0.0832 2023-03-04 01:51:48,619 - mmseg - INFO - Iter [59700/160000] lr: 3.750e-05, eta: 8:25:09, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8428, loss: 0.0802 2023-03-04 01:52:03,214 - mmseg - INFO - Iter [59750/160000] lr: 3.750e-05, eta: 8:24:53, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7386, loss: 0.0838 2023-03-04 01:52:15,335 - mmseg - INFO - Iter [59800/160000] lr: 3.750e-05, eta: 8:24:33, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7472, loss: 0.0823 2023-03-04 01:52:27,762 - mmseg - INFO - Iter [59850/160000] lr: 3.750e-05, eta: 8:24:13, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7558, loss: 0.0810 2023-03-04 01:52:42,343 - mmseg - INFO - Iter [59900/160000] lr: 3.750e-05, eta: 8:23:57, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8624, loss: 0.0784 2023-03-04 01:52:54,545 - mmseg - INFO - Iter [59950/160000] lr: 3.750e-05, eta: 8:23:37, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8285, loss: 0.0811 2023-03-04 01:53:06,719 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:53:06,719 - mmseg - INFO - Iter [60000/160000] lr: 3.750e-05, eta: 8:23:17, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0854, decode.acc_seg: 96.6215, loss: 0.0854 2023-03-04 01:53:18,998 - mmseg - INFO - Iter [60050/160000] lr: 1.875e-05, eta: 8:22:58, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8657, loss: 0.0796 2023-03-04 01:53:33,603 - mmseg - INFO - Iter [60100/160000] lr: 1.875e-05, eta: 8:22:42, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7341, loss: 0.0824 2023-03-04 01:53:45,907 - mmseg - INFO - Iter [60150/160000] lr: 1.875e-05, eta: 8:22:22, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8829, loss: 0.0798 2023-03-04 01:53:58,125 - mmseg - INFO - Iter [60200/160000] lr: 1.875e-05, eta: 8:22:02, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8622, loss: 0.0781 2023-03-04 01:54:10,286 - mmseg - INFO - Iter [60250/160000] lr: 1.875e-05, eta: 8:21:42, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7429, loss: 0.0827 2023-03-04 01:54:24,822 - mmseg - INFO - Iter [60300/160000] lr: 1.875e-05, eta: 8:21:26, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8661, loss: 0.0808 2023-03-04 01:54:37,144 - mmseg - INFO - Iter [60350/160000] lr: 1.875e-05, eta: 8:21:07, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8441, loss: 0.0792 2023-03-04 01:54:49,333 - mmseg - INFO - Iter [60400/160000] lr: 1.875e-05, eta: 8:20:47, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8287, loss: 0.0797 2023-03-04 01:55:01,515 - mmseg - INFO - Iter [60450/160000] lr: 1.875e-05, eta: 8:20:27, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8212, loss: 0.0803 2023-03-04 01:55:16,079 - mmseg - INFO - Iter [60500/160000] lr: 1.875e-05, eta: 8:20:11, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8022, loss: 0.0804 2023-03-04 01:55:28,279 - mmseg - INFO - Iter [60550/160000] lr: 1.875e-05, eta: 8:19:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7210, loss: 0.0825 2023-03-04 01:55:40,338 - mmseg - INFO - Iter [60600/160000] lr: 1.875e-05, eta: 8:19:31, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8600, loss: 0.0802 2023-03-04 01:55:54,806 - mmseg - INFO - Iter [60650/160000] lr: 1.875e-05, eta: 8:19:15, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8652, loss: 0.0806 2023-03-04 01:56:06,972 - mmseg - INFO - Iter [60700/160000] lr: 1.875e-05, eta: 8:18:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.7920, loss: 0.0801 2023-03-04 01:56:19,171 - mmseg - INFO - Iter [60750/160000] lr: 1.875e-05, eta: 8:18:35, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6722, loss: 0.0846 2023-03-04 01:56:31,462 - mmseg - INFO - Iter [60800/160000] lr: 1.875e-05, eta: 8:18:16, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9097, loss: 0.0782 2023-03-04 01:56:46,037 - mmseg - INFO - Iter [60850/160000] lr: 1.875e-05, eta: 8:18:00, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8894, loss: 0.0791 2023-03-04 01:56:58,303 - mmseg - INFO - Iter [60900/160000] lr: 1.875e-05, eta: 8:17:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7787, loss: 0.0823 2023-03-04 01:57:10,654 - mmseg - INFO - Iter [60950/160000] lr: 1.875e-05, eta: 8:17:21, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8204, loss: 0.0796 2023-03-04 01:57:22,934 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 01:57:22,934 - mmseg - INFO - Iter [61000/160000] lr: 1.875e-05, eta: 8:17:01, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8434, loss: 0.0803 2023-03-04 01:57:37,376 - mmseg - INFO - Iter [61050/160000] lr: 1.875e-05, eta: 8:16:45, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8381, loss: 0.0807 2023-03-04 01:57:49,613 - mmseg - INFO - Iter [61100/160000] lr: 1.875e-05, eta: 8:16:25, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8861, loss: 0.0787 2023-03-04 01:58:01,928 - mmseg - INFO - Iter [61150/160000] lr: 1.875e-05, eta: 8:16:06, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8002, loss: 0.0812 2023-03-04 01:58:16,395 - mmseg - INFO - Iter [61200/160000] lr: 1.875e-05, eta: 8:15:50, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7777, loss: 0.0814 2023-03-04 01:58:28,626 - mmseg - INFO - Iter [61250/160000] lr: 1.875e-05, eta: 8:15:30, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7546, loss: 0.0826 2023-03-04 01:58:40,805 - mmseg - INFO - Iter [61300/160000] lr: 1.875e-05, eta: 8:15:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8233, loss: 0.0815 2023-03-04 01:58:53,028 - mmseg - INFO - Iter [61350/160000] lr: 1.875e-05, eta: 8:14:51, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7117, loss: 0.0831 2023-03-04 01:59:07,497 - mmseg - INFO - Iter [61400/160000] lr: 1.875e-05, eta: 8:14:35, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7572, loss: 0.0826 2023-03-04 01:59:19,712 - mmseg - INFO - Iter [61450/160000] lr: 1.875e-05, eta: 8:14:16, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7490, loss: 0.0821 2023-03-04 01:59:31,961 - mmseg - INFO - Iter [61500/160000] lr: 1.875e-05, eta: 8:13:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7794, loss: 0.0818 2023-03-04 01:59:44,061 - mmseg - INFO - Iter [61550/160000] lr: 1.875e-05, eta: 8:13:36, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0861, decode.acc_seg: 96.5729, loss: 0.0861 2023-03-04 01:59:58,460 - mmseg - INFO - Iter [61600/160000] lr: 1.875e-05, eta: 8:13:20, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.7990, loss: 0.0804 2023-03-04 02:00:10,544 - mmseg - INFO - Iter [61650/160000] lr: 1.875e-05, eta: 8:13:00, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7185, loss: 0.0835 2023-03-04 02:00:22,662 - mmseg - INFO - Iter [61700/160000] lr: 1.875e-05, eta: 8:12:41, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6149, loss: 0.0858 2023-03-04 02:00:34,769 - mmseg - INFO - Iter [61750/160000] lr: 1.875e-05, eta: 8:12:21, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8667, loss: 0.0791 2023-03-04 02:00:49,356 - mmseg - INFO - Iter [61800/160000] lr: 1.875e-05, eta: 8:12:05, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7897, loss: 0.0808 2023-03-04 02:01:01,713 - mmseg - INFO - Iter [61850/160000] lr: 1.875e-05, eta: 8:11:46, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7771, loss: 0.0820 2023-03-04 02:01:14,103 - mmseg - INFO - Iter [61900/160000] lr: 1.875e-05, eta: 8:11:27, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.7957, loss: 0.0800 2023-03-04 02:01:28,704 - mmseg - INFO - Iter [61950/160000] lr: 1.875e-05, eta: 8:11:11, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6508, loss: 0.0841 2023-03-04 02:01:40,977 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:01:40,977 - mmseg - INFO - Iter [62000/160000] lr: 1.875e-05, eta: 8:10:52, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9108, loss: 0.0783 2023-03-04 02:01:53,099 - mmseg - INFO - Iter [62050/160000] lr: 1.875e-05, eta: 8:10:32, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7609, loss: 0.0817 2023-03-04 02:02:05,347 - mmseg - INFO - Iter [62100/160000] lr: 1.875e-05, eta: 8:10:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7625, loss: 0.0808 2023-03-04 02:02:19,900 - mmseg - INFO - Iter [62150/160000] lr: 1.875e-05, eta: 8:09:57, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9006, loss: 0.0788 2023-03-04 02:02:32,060 - mmseg - INFO - Iter [62200/160000] lr: 1.875e-05, eta: 8:09:37, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8534, loss: 0.0791 2023-03-04 02:02:44,241 - mmseg - INFO - Iter [62250/160000] lr: 1.875e-05, eta: 8:09:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8096, loss: 0.0814 2023-03-04 02:02:56,397 - mmseg - INFO - Iter [62300/160000] lr: 1.875e-05, eta: 8:08:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8108, loss: 0.0807 2023-03-04 02:03:10,885 - mmseg - INFO - Iter [62350/160000] lr: 1.875e-05, eta: 8:08:43, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.7006, loss: 0.0840 2023-03-04 02:03:23,111 - mmseg - INFO - Iter [62400/160000] lr: 1.875e-05, eta: 8:08:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7632, loss: 0.0809 2023-03-04 02:03:35,375 - mmseg - INFO - Iter [62450/160000] lr: 1.875e-05, eta: 8:08:04, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8669, loss: 0.0792 2023-03-04 02:03:49,907 - mmseg - INFO - Iter [62500/160000] lr: 1.875e-05, eta: 8:07:48, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7678, loss: 0.0816 2023-03-04 02:04:02,016 - mmseg - INFO - Iter [62550/160000] lr: 1.875e-05, eta: 8:07:29, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7388, loss: 0.0831 2023-03-04 02:04:14,232 - mmseg - INFO - Iter [62600/160000] lr: 1.875e-05, eta: 8:07:09, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8616, loss: 0.0784 2023-03-04 02:04:26,449 - mmseg - INFO - Iter [62650/160000] lr: 1.875e-05, eta: 8:06:50, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8184, loss: 0.0808 2023-03-04 02:04:41,180 - mmseg - INFO - Iter [62700/160000] lr: 1.875e-05, eta: 8:06:34, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8339, loss: 0.0815 2023-03-04 02:04:53,378 - mmseg - INFO - Iter [62750/160000] lr: 1.875e-05, eta: 8:06:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8382, loss: 0.0798 2023-03-04 02:05:05,657 - mmseg - INFO - Iter [62800/160000] lr: 1.875e-05, eta: 8:05:56, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8452, loss: 0.0793 2023-03-04 02:05:17,895 - mmseg - INFO - Iter [62850/160000] lr: 1.875e-05, eta: 8:05:37, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.6980, loss: 0.0831 2023-03-04 02:05:32,474 - mmseg - INFO - Iter [62900/160000] lr: 1.875e-05, eta: 8:05:21, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8501, loss: 0.0789 2023-03-04 02:05:44,617 - mmseg - INFO - Iter [62950/160000] lr: 1.875e-05, eta: 8:05:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8761, loss: 0.0790 2023-03-04 02:05:56,756 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:05:56,756 - mmseg - INFO - Iter [63000/160000] lr: 1.875e-05, eta: 8:04:42, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8170, loss: 0.0798 2023-03-04 02:06:08,838 - mmseg - INFO - Iter [63050/160000] lr: 1.875e-05, eta: 8:04:23, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7346, loss: 0.0834 2023-03-04 02:06:23,425 - mmseg - INFO - Iter [63100/160000] lr: 1.875e-05, eta: 8:04:07, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7858, loss: 0.0814 2023-03-04 02:06:35,622 - mmseg - INFO - Iter [63150/160000] lr: 1.875e-05, eta: 8:03:48, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8205, loss: 0.0803 2023-03-04 02:06:47,871 - mmseg - INFO - Iter [63200/160000] lr: 1.875e-05, eta: 8:03:29, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6935, loss: 0.0848 2023-03-04 02:07:02,406 - mmseg - INFO - Iter [63250/160000] lr: 1.875e-05, eta: 8:03:13, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8292, loss: 0.0810 2023-03-04 02:07:14,544 - mmseg - INFO - Iter [63300/160000] lr: 1.875e-05, eta: 8:02:54, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8424, loss: 0.0811 2023-03-04 02:07:26,747 - mmseg - INFO - Iter [63350/160000] lr: 1.875e-05, eta: 8:02:34, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7921, loss: 0.0812 2023-03-04 02:07:39,001 - mmseg - INFO - Iter [63400/160000] lr: 1.875e-05, eta: 8:02:15, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7769, loss: 0.0809 2023-03-04 02:07:53,518 - mmseg - INFO - Iter [63450/160000] lr: 1.875e-05, eta: 8:02:00, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8445, loss: 0.0800 2023-03-04 02:08:05,754 - mmseg - INFO - Iter [63500/160000] lr: 1.875e-05, eta: 8:01:41, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8027, loss: 0.0801 2023-03-04 02:08:17,954 - mmseg - INFO - Iter [63550/160000] lr: 1.875e-05, eta: 8:01:21, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8224, loss: 0.0805 2023-03-04 02:08:30,103 - mmseg - INFO - Iter [63600/160000] lr: 1.875e-05, eta: 8:01:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8528, loss: 0.0796 2023-03-04 02:08:44,695 - mmseg - INFO - Iter [63650/160000] lr: 1.875e-05, eta: 8:00:47, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8475, loss: 0.0798 2023-03-04 02:08:57,045 - mmseg - INFO - Iter [63700/160000] lr: 1.875e-05, eta: 8:00:28, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9085, loss: 0.0783 2023-03-04 02:09:09,102 - mmseg - INFO - Iter [63750/160000] lr: 1.875e-05, eta: 8:00:08, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7420, loss: 0.0820 2023-03-04 02:09:23,530 - mmseg - INFO - Iter [63800/160000] lr: 1.875e-05, eta: 7:59:52, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6485, loss: 0.0852 2023-03-04 02:09:35,750 - mmseg - INFO - Iter [63850/160000] lr: 1.875e-05, eta: 7:59:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9148, loss: 0.0784 2023-03-04 02:09:48,038 - mmseg - INFO - Iter [63900/160000] lr: 1.875e-05, eta: 7:59:14, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7673, loss: 0.0809 2023-03-04 02:10:00,162 - mmseg - INFO - Iter [63950/160000] lr: 1.875e-05, eta: 7:58:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8030, loss: 0.0808 2023-03-04 02:10:14,619 - mmseg - INFO - Swap parameters (after train) after iter [64000] 2023-03-04 02:10:14,635 - mmseg - INFO - Saving checkpoint at 64000 iterations 2023-03-04 02:10:16,105 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:10:16,106 - mmseg - INFO - Iter [64000/160000] lr: 1.875e-05, eta: 7:58:42, time: 0.319, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9165, loss: 0.0771 2023-03-04 02:25:07,300 - mmseg - INFO - per class results: 2023-03-04 02:25:07,302 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.56,98.56,98.56,98.56,98.56,98.56,98.57,98.57,98.56,98.57,98.56 | | sidewalk | 87.64,87.65,87.66,87.66,87.69,87.71,87.72,87.72,87.7,87.72,87.71 | | building | 93.35,93.36,93.36,93.36,93.36,93.36,93.36,93.35,93.36,93.36,93.36 | | wall | 54.48,54.54,54.55,54.65,54.59,54.76,54.62,54.66,54.67,54.69,54.79 | | fence | 63.9,63.9,63.95,63.94,64.0,64.04,64.01,64.01,64.07,64.02,64.05 | | pole | 71.07,71.08,71.1,71.08,71.09,71.09,71.1,71.09,71.09,71.1,71.11 | | traffic light | 75.54,75.54,75.54,75.52,75.53,75.52,75.53,75.51,75.53,75.52,75.52 | | traffic sign | 83.31,83.33,83.34,83.35,83.35,83.35,83.37,83.36,83.37,83.38,83.38 | | vegetation | 92.96,92.96,92.97,92.97,92.96,92.96,92.96,92.97,92.96,92.97,92.96 | | terrain | 65.85,65.84,65.88,65.92,65.91,65.9,65.88,65.91,65.93,65.94,65.9 | | sky | 95.22,95.22,95.22,95.22,95.23,95.23,95.23,95.23,95.22,95.24,95.23 | | person | 84.77,84.77,84.78,84.77,84.78,84.78,84.77,84.79,84.77,84.78,84.77 | | rider | 66.97,66.94,66.97,66.94,66.95,67.0,66.93,66.98,66.94,66.96,66.92 | | car | 95.97,95.98,96.0,96.01,96.01,96.02,96.02,96.02,96.03,96.03,96.05 | | truck | 84.17,84.6,84.92,85.22,85.24,85.31,85.37,85.43,85.57,85.49,85.87 | | bus | 92.16,92.18,92.21,92.21,92.23,92.26,92.25,92.24,92.24,92.21,92.27 | | train | 85.97,85.99,85.99,85.95,85.98,86.06,86.06,85.95,85.99,85.98,86.22 | | motorcycle | 69.47,69.5,69.49,69.5,69.51,69.49,69.53,69.51,69.54,69.53,69.53 | | bicycle | 79.86,79.86,79.87,79.87,79.88,79.88,79.88,79.88,79.89,79.89,79.89 | +---------------+-------------------------------------------------------------------+ 2023-03-04 02:25:07,302 - mmseg - INFO - Summary: 2023-03-04 02:25:07,302 - mmseg - INFO - +------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +------------------------------------------------------------------+ | 81.12,81.15,81.18,81.19,81.2,81.23,81.22,81.22,81.23,81.23,81.27 | +------------------------------------------------------------------+ 2023-03-04 02:25:07,351 - mmseg - INFO - The previous best checkpoint /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune/best_mIoU_iter_48000.pth was removed 2023-03-04 02:25:08,714 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_64000.pth. 2023-03-04 02:25:08,715 - mmseg - INFO - Best mIoU is 0.8127 at 64000 iter. 2023-03-04 02:25:08,715 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:25:08,715 - mmseg - INFO - Iter(val) [63] mIoU: [0.8112, 0.8115, 0.8118, 0.8119, 0.812, 0.8123, 0.8122, 0.8122, 0.8123, 0.8123, 0.8127], copy_paste: 81.12,81.15,81.18,81.19,81.2,81.23,81.22,81.22,81.23,81.23,81.27 2023-03-04 02:25:08,723 - mmseg - INFO - Swap parameters (before train) before iter [64001] 2023-03-04 02:25:21,160 - mmseg - INFO - Iter [64050/160000] lr: 1.875e-05, eta: 8:20:40, time: 18.101, data_time: 17.861, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8832, loss: 0.0799 2023-03-04 02:25:33,572 - mmseg - INFO - Iter [64100/160000] lr: 1.875e-05, eta: 8:20:20, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0869, decode.acc_seg: 96.5952, loss: 0.0869 2023-03-04 02:25:45,935 - mmseg - INFO - Iter [64150/160000] lr: 1.875e-05, eta: 8:19:59, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.7028, loss: 0.0852 2023-03-04 02:26:00,567 - mmseg - INFO - Iter [64200/160000] lr: 1.875e-05, eta: 8:19:42, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8470, loss: 0.0800 2023-03-04 02:26:12,871 - mmseg - INFO - Iter [64250/160000] lr: 1.875e-05, eta: 8:19:21, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.7967, loss: 0.0800 2023-03-04 02:26:25,184 - mmseg - INFO - Iter [64300/160000] lr: 1.875e-05, eta: 8:19:01, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8318, loss: 0.0807 2023-03-04 02:26:37,578 - mmseg - INFO - Iter [64350/160000] lr: 1.875e-05, eta: 8:18:40, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0866, decode.acc_seg: 96.6593, loss: 0.0866 2023-03-04 02:26:52,177 - mmseg - INFO - Iter [64400/160000] lr: 1.875e-05, eta: 8:18:23, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7648, loss: 0.0837 2023-03-04 02:27:04,438 - mmseg - INFO - Iter [64450/160000] lr: 1.875e-05, eta: 8:18:02, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8423, loss: 0.0812 2023-03-04 02:27:16,713 - mmseg - INFO - Iter [64500/160000] lr: 1.875e-05, eta: 8:17:42, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8384, loss: 0.0786 2023-03-04 02:27:31,160 - mmseg - INFO - Iter [64550/160000] lr: 1.875e-05, eta: 8:17:24, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7568, loss: 0.0821 2023-03-04 02:27:43,455 - mmseg - INFO - Iter [64600/160000] lr: 1.875e-05, eta: 8:17:04, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7498, loss: 0.0827 2023-03-04 02:27:55,690 - mmseg - INFO - Iter [64650/160000] lr: 1.875e-05, eta: 8:16:43, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8226, loss: 0.0809 2023-03-04 02:28:07,960 - mmseg - INFO - Iter [64700/160000] lr: 1.875e-05, eta: 8:16:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.9182, loss: 0.0791 2023-03-04 02:28:22,511 - mmseg - INFO - Iter [64750/160000] lr: 1.875e-05, eta: 8:16:05, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7571, loss: 0.0816 2023-03-04 02:28:34,690 - mmseg - INFO - Iter [64800/160000] lr: 1.875e-05, eta: 8:15:45, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7925, loss: 0.0824 2023-03-04 02:28:46,992 - mmseg - INFO - Iter [64850/160000] lr: 1.875e-05, eta: 8:15:24, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8008, loss: 0.0805 2023-03-04 02:28:59,149 - mmseg - INFO - Iter [64900/160000] lr: 1.875e-05, eta: 8:15:03, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7368, loss: 0.0836 2023-03-04 02:29:13,572 - mmseg - INFO - Iter [64950/160000] lr: 1.875e-05, eta: 8:14:46, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7685, loss: 0.0820 2023-03-04 02:29:26,004 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:29:26,004 - mmseg - INFO - Iter [65000/160000] lr: 1.875e-05, eta: 8:14:26, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7560, loss: 0.0809 2023-03-04 02:29:38,383 - mmseg - INFO - Iter [65050/160000] lr: 1.875e-05, eta: 8:14:05, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8398, loss: 0.0804 2023-03-04 02:29:50,613 - mmseg - INFO - Iter [65100/160000] lr: 1.875e-05, eta: 8:13:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7551, loss: 0.0822 2023-03-04 02:30:05,171 - mmseg - INFO - Iter [65150/160000] lr: 1.875e-05, eta: 8:13:28, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7343, loss: 0.0829 2023-03-04 02:30:17,302 - mmseg - INFO - Iter [65200/160000] lr: 1.875e-05, eta: 8:13:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7823, loss: 0.0810 2023-03-04 02:30:29,483 - mmseg - INFO - Iter [65250/160000] lr: 1.875e-05, eta: 8:12:47, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8917, loss: 0.0784 2023-03-04 02:30:44,020 - mmseg - INFO - Iter [65300/160000] lr: 1.875e-05, eta: 8:12:29, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7192, loss: 0.0832 2023-03-04 02:30:56,250 - mmseg - INFO - Iter [65350/160000] lr: 1.875e-05, eta: 8:12:09, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8018, loss: 0.0814 2023-03-04 02:31:08,516 - mmseg - INFO - Iter [65400/160000] lr: 1.875e-05, eta: 8:11:49, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7265, loss: 0.0824 2023-03-04 02:31:20,628 - mmseg - INFO - Iter [65450/160000] lr: 1.875e-05, eta: 8:11:28, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8703, loss: 0.0793 2023-03-04 02:31:35,173 - mmseg - INFO - Iter [65500/160000] lr: 1.875e-05, eta: 8:11:11, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7126, loss: 0.0831 2023-03-04 02:31:47,346 - mmseg - INFO - Iter [65550/160000] lr: 1.875e-05, eta: 8:10:50, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7264, loss: 0.0837 2023-03-04 02:31:59,575 - mmseg - INFO - Iter [65600/160000] lr: 1.875e-05, eta: 8:10:30, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8715, loss: 0.0788 2023-03-04 02:32:11,805 - mmseg - INFO - Iter [65650/160000] lr: 1.875e-05, eta: 8:10:09, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7181, loss: 0.0834 2023-03-04 02:32:26,337 - mmseg - INFO - Iter [65700/160000] lr: 1.875e-05, eta: 8:09:52, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9456, loss: 0.0782 2023-03-04 02:32:38,527 - mmseg - INFO - Iter [65750/160000] lr: 1.875e-05, eta: 8:09:32, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8173, loss: 0.0804 2023-03-04 02:32:50,637 - mmseg - INFO - Iter [65800/160000] lr: 1.875e-05, eta: 8:09:11, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8553, loss: 0.0789 2023-03-04 02:33:05,176 - mmseg - INFO - Iter [65850/160000] lr: 1.875e-05, eta: 8:08:54, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7409, loss: 0.0827 2023-03-04 02:33:17,390 - mmseg - INFO - Iter [65900/160000] lr: 1.875e-05, eta: 8:08:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8085, loss: 0.0803 2023-03-04 02:33:29,485 - mmseg - INFO - Iter [65950/160000] lr: 1.875e-05, eta: 8:08:13, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7807, loss: 0.0813 2023-03-04 02:33:41,700 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:33:41,700 - mmseg - INFO - Iter [66000/160000] lr: 1.875e-05, eta: 8:07:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7772, loss: 0.0808 2023-03-04 02:33:56,201 - mmseg - INFO - Iter [66050/160000] lr: 1.875e-05, eta: 8:07:36, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7593, loss: 0.0812 2023-03-04 02:34:08,483 - mmseg - INFO - Iter [66100/160000] lr: 1.875e-05, eta: 8:07:16, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7331, loss: 0.0830 2023-03-04 02:34:20,637 - mmseg - INFO - Iter [66150/160000] lr: 1.875e-05, eta: 8:06:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7953, loss: 0.0825 2023-03-04 02:34:32,855 - mmseg - INFO - Iter [66200/160000] lr: 1.875e-05, eta: 8:06:35, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.6858, loss: 0.0830 2023-03-04 02:34:47,428 - mmseg - INFO - Iter [66250/160000] lr: 1.875e-05, eta: 8:06:18, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9032, loss: 0.0786 2023-03-04 02:34:59,765 - mmseg - INFO - Iter [66300/160000] lr: 1.875e-05, eta: 8:05:58, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7510, loss: 0.0818 2023-03-04 02:35:11,917 - mmseg - INFO - Iter [66350/160000] lr: 1.875e-05, eta: 8:05:37, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7871, loss: 0.0817 2023-03-04 02:35:24,155 - mmseg - INFO - Iter [66400/160000] lr: 1.875e-05, eta: 8:05:17, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7721, loss: 0.0816 2023-03-04 02:35:38,733 - mmseg - INFO - Iter [66450/160000] lr: 1.875e-05, eta: 8:05:00, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8437, loss: 0.0794 2023-03-04 02:35:51,116 - mmseg - INFO - Iter [66500/160000] lr: 1.875e-05, eta: 8:04:40, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7388, loss: 0.0824 2023-03-04 02:36:03,357 - mmseg - INFO - Iter [66550/160000] lr: 1.875e-05, eta: 8:04:20, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.8030, loss: 0.0820 2023-03-04 02:36:17,797 - mmseg - INFO - Iter [66600/160000] lr: 1.875e-05, eta: 8:04:03, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7048, loss: 0.0841 2023-03-04 02:36:29,988 - mmseg - INFO - Iter [66650/160000] lr: 1.875e-05, eta: 8:03:43, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9415, loss: 0.0767 2023-03-04 02:36:42,323 - mmseg - INFO - Iter [66700/160000] lr: 1.875e-05, eta: 8:03:23, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8491, loss: 0.0802 2023-03-04 02:36:54,598 - mmseg - INFO - Iter [66750/160000] lr: 1.875e-05, eta: 8:03:03, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.6420, loss: 0.0841 2023-03-04 02:37:09,134 - mmseg - INFO - Iter [66800/160000] lr: 1.875e-05, eta: 8:02:46, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8939, loss: 0.0790 2023-03-04 02:37:21,417 - mmseg - INFO - Iter [66850/160000] lr: 1.875e-05, eta: 8:02:26, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.7855, loss: 0.0800 2023-03-04 02:37:33,589 - mmseg - INFO - Iter [66900/160000] lr: 1.875e-05, eta: 8:02:05, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7407, loss: 0.0822 2023-03-04 02:37:45,825 - mmseg - INFO - Iter [66950/160000] lr: 1.875e-05, eta: 8:01:45, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8318, loss: 0.0803 2023-03-04 02:38:00,351 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:38:00,351 - mmseg - INFO - Iter [67000/160000] lr: 1.875e-05, eta: 8:01:28, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7586, loss: 0.0822 2023-03-04 02:38:12,589 - mmseg - INFO - Iter [67050/160000] lr: 1.875e-05, eta: 8:01:08, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7802, loss: 0.0810 2023-03-04 02:38:24,811 - mmseg - INFO - Iter [67100/160000] lr: 1.875e-05, eta: 8:00:48, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8544, loss: 0.0797 2023-03-04 02:38:39,247 - mmseg - INFO - Iter [67150/160000] lr: 1.875e-05, eta: 8:00:31, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7544, loss: 0.0823 2023-03-04 02:38:51,362 - mmseg - INFO - Iter [67200/160000] lr: 1.875e-05, eta: 8:00:11, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8075, loss: 0.0808 2023-03-04 02:39:03,467 - mmseg - INFO - Iter [67250/160000] lr: 1.875e-05, eta: 7:59:51, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.7642, loss: 0.0802 2023-03-04 02:39:15,541 - mmseg - INFO - Iter [67300/160000] lr: 1.875e-05, eta: 7:59:30, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8242, loss: 0.0796 2023-03-04 02:39:30,198 - mmseg - INFO - Iter [67350/160000] lr: 1.875e-05, eta: 7:59:14, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8457, loss: 0.0793 2023-03-04 02:39:42,331 - mmseg - INFO - Iter [67400/160000] lr: 1.875e-05, eta: 7:58:53, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8386, loss: 0.0791 2023-03-04 02:39:54,496 - mmseg - INFO - Iter [67450/160000] lr: 1.875e-05, eta: 7:58:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.6891, loss: 0.0830 2023-03-04 02:40:06,707 - mmseg - INFO - Iter [67500/160000] lr: 1.875e-05, eta: 7:58:13, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8119, loss: 0.0800 2023-03-04 02:40:21,306 - mmseg - INFO - Iter [67550/160000] lr: 1.875e-05, eta: 7:57:57, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8296, loss: 0.0795 2023-03-04 02:40:33,685 - mmseg - INFO - Iter [67600/160000] lr: 1.875e-05, eta: 7:57:37, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8194, loss: 0.0807 2023-03-04 02:40:45,876 - mmseg - INFO - Iter [67650/160000] lr: 1.875e-05, eta: 7:57:17, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.6664, loss: 0.0858 2023-03-04 02:40:57,990 - mmseg - INFO - Iter [67700/160000] lr: 1.875e-05, eta: 7:56:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8920, loss: 0.0784 2023-03-04 02:41:12,636 - mmseg - INFO - Iter [67750/160000] lr: 1.875e-05, eta: 7:56:40, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8405, loss: 0.0813 2023-03-04 02:41:24,865 - mmseg - INFO - Iter [67800/160000] lr: 1.875e-05, eta: 7:56:20, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7838, loss: 0.0824 2023-03-04 02:41:37,089 - mmseg - INFO - Iter [67850/160000] lr: 1.875e-05, eta: 7:56:00, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8306, loss: 0.0795 2023-03-04 02:41:51,600 - mmseg - INFO - Iter [67900/160000] lr: 1.875e-05, eta: 7:55:43, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9616, loss: 0.0765 2023-03-04 02:42:03,776 - mmseg - INFO - Iter [67950/160000] lr: 1.875e-05, eta: 7:55:23, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7641, loss: 0.0809 2023-03-04 02:42:16,104 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:42:16,104 - mmseg - INFO - Iter [68000/160000] lr: 1.875e-05, eta: 7:55:03, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7973, loss: 0.0816 2023-03-04 02:42:28,230 - mmseg - INFO - Iter [68050/160000] lr: 1.875e-05, eta: 7:54:43, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8215, loss: 0.0803 2023-03-04 02:42:42,755 - mmseg - INFO - Iter [68100/160000] lr: 1.875e-05, eta: 7:54:27, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7481, loss: 0.0812 2023-03-04 02:42:55,011 - mmseg - INFO - Iter [68150/160000] lr: 1.875e-05, eta: 7:54:07, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7690, loss: 0.0818 2023-03-04 02:43:07,338 - mmseg - INFO - Iter [68200/160000] lr: 1.875e-05, eta: 7:53:47, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7675, loss: 0.0827 2023-03-04 02:43:19,650 - mmseg - INFO - Iter [68250/160000] lr: 1.875e-05, eta: 7:53:27, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8754, loss: 0.0785 2023-03-04 02:43:34,192 - mmseg - INFO - Iter [68300/160000] lr: 1.875e-05, eta: 7:53:10, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7520, loss: 0.0829 2023-03-04 02:43:46,420 - mmseg - INFO - Iter [68350/160000] lr: 1.875e-05, eta: 7:52:51, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8646, loss: 0.0786 2023-03-04 02:43:58,554 - mmseg - INFO - Iter [68400/160000] lr: 1.875e-05, eta: 7:52:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7796, loss: 0.0821 2023-03-04 02:44:13,072 - mmseg - INFO - Iter [68450/160000] lr: 1.875e-05, eta: 7:52:14, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6342, loss: 0.0846 2023-03-04 02:44:25,223 - mmseg - INFO - Iter [68500/160000] lr: 1.875e-05, eta: 7:51:54, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.7091, loss: 0.0850 2023-03-04 02:44:37,474 - mmseg - INFO - Iter [68550/160000] lr: 1.875e-05, eta: 7:51:34, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8559, loss: 0.0800 2023-03-04 02:44:49,561 - mmseg - INFO - Iter [68600/160000] lr: 1.875e-05, eta: 7:51:14, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7983, loss: 0.0811 2023-03-04 02:45:04,172 - mmseg - INFO - Iter [68650/160000] lr: 1.875e-05, eta: 7:50:58, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8121, loss: 0.0808 2023-03-04 02:45:16,364 - mmseg - INFO - Iter [68700/160000] lr: 1.875e-05, eta: 7:50:38, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7634, loss: 0.0817 2023-03-04 02:45:28,471 - mmseg - INFO - Iter [68750/160000] lr: 1.875e-05, eta: 7:50:18, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7094, loss: 0.0832 2023-03-04 02:45:40,755 - mmseg - INFO - Iter [68800/160000] lr: 1.875e-05, eta: 7:49:58, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7196, loss: 0.0828 2023-03-04 02:45:55,386 - mmseg - INFO - Iter [68850/160000] lr: 1.875e-05, eta: 7:49:42, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8364, loss: 0.0801 2023-03-04 02:46:07,662 - mmseg - INFO - Iter [68900/160000] lr: 1.875e-05, eta: 7:49:22, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8127, loss: 0.0803 2023-03-04 02:46:19,776 - mmseg - INFO - Iter [68950/160000] lr: 1.875e-05, eta: 7:49:02, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7095, loss: 0.0834 2023-03-04 02:46:31,900 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:46:31,900 - mmseg - INFO - Iter [69000/160000] lr: 1.875e-05, eta: 7:48:42, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.6682, loss: 0.0860 2023-03-04 02:46:46,529 - mmseg - INFO - Iter [69050/160000] lr: 1.875e-05, eta: 7:48:26, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8775, loss: 0.0790 2023-03-04 02:46:58,799 - mmseg - INFO - Iter [69100/160000] lr: 1.875e-05, eta: 7:48:06, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7775, loss: 0.0814 2023-03-04 02:47:10,968 - mmseg - INFO - Iter [69150/160000] lr: 1.875e-05, eta: 7:47:46, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6332, loss: 0.0844 2023-03-04 02:47:25,524 - mmseg - INFO - Iter [69200/160000] lr: 1.875e-05, eta: 7:47:30, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.7984, loss: 0.0800 2023-03-04 02:47:37,757 - mmseg - INFO - Iter [69250/160000] lr: 1.875e-05, eta: 7:47:10, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7653, loss: 0.0827 2023-03-04 02:47:49,890 - mmseg - INFO - Iter [69300/160000] lr: 1.875e-05, eta: 7:46:50, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7770, loss: 0.0821 2023-03-04 02:48:02,091 - mmseg - INFO - Iter [69350/160000] lr: 1.875e-05, eta: 7:46:31, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8752, loss: 0.0790 2023-03-04 02:48:16,725 - mmseg - INFO - Iter [69400/160000] lr: 1.875e-05, eta: 7:46:14, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7530, loss: 0.0820 2023-03-04 02:48:29,069 - mmseg - INFO - Iter [69450/160000] lr: 1.875e-05, eta: 7:45:55, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8680, loss: 0.0798 2023-03-04 02:48:41,317 - mmseg - INFO - Iter [69500/160000] lr: 1.875e-05, eta: 7:45:35, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.7996, loss: 0.0804 2023-03-04 02:48:53,584 - mmseg - INFO - Iter [69550/160000] lr: 1.875e-05, eta: 7:45:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7963, loss: 0.0821 2023-03-04 02:49:08,178 - mmseg - INFO - Iter [69600/160000] lr: 1.875e-05, eta: 7:44:59, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7280, loss: 0.0827 2023-03-04 02:49:20,445 - mmseg - INFO - Iter [69650/160000] lr: 1.875e-05, eta: 7:44:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8103, loss: 0.0793 2023-03-04 02:49:32,639 - mmseg - INFO - Iter [69700/160000] lr: 1.875e-05, eta: 7:44:20, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9133, loss: 0.0774 2023-03-04 02:49:44,835 - mmseg - INFO - Iter [69750/160000] lr: 1.875e-05, eta: 7:44:00, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7602, loss: 0.0813 2023-03-04 02:49:59,371 - mmseg - INFO - Iter [69800/160000] lr: 1.875e-05, eta: 7:43:44, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8449, loss: 0.0799 2023-03-04 02:50:11,596 - mmseg - INFO - Iter [69850/160000] lr: 1.875e-05, eta: 7:43:24, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.6949, loss: 0.0830 2023-03-04 02:50:23,814 - mmseg - INFO - Iter [69900/160000] lr: 1.875e-05, eta: 7:43:05, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7885, loss: 0.0826 2023-03-04 02:50:38,218 - mmseg - INFO - Iter [69950/160000] lr: 1.875e-05, eta: 7:42:48, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8917, loss: 0.0796 2023-03-04 02:50:50,475 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:50:50,475 - mmseg - INFO - Iter [70000/160000] lr: 1.875e-05, eta: 7:42:28, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8586, loss: 0.0794 2023-03-04 02:51:02,857 - mmseg - INFO - Iter [70050/160000] lr: 1.875e-05, eta: 7:42:09, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8306, loss: 0.0795 2023-03-04 02:51:15,119 - mmseg - INFO - Iter [70100/160000] lr: 1.875e-05, eta: 7:41:50, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8608, loss: 0.0798 2023-03-04 02:51:29,612 - mmseg - INFO - Iter [70150/160000] lr: 1.875e-05, eta: 7:41:33, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8800, loss: 0.0800 2023-03-04 02:51:41,785 - mmseg - INFO - Iter [70200/160000] lr: 1.875e-05, eta: 7:41:13, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8262, loss: 0.0801 2023-03-04 02:51:53,951 - mmseg - INFO - Iter [70250/160000] lr: 1.875e-05, eta: 7:40:54, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 97.0105, loss: 0.0756 2023-03-04 02:52:06,049 - mmseg - INFO - Iter [70300/160000] lr: 1.875e-05, eta: 7:40:34, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8338, loss: 0.0798 2023-03-04 02:52:20,637 - mmseg - INFO - Iter [70350/160000] lr: 1.875e-05, eta: 7:40:18, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9228, loss: 0.0773 2023-03-04 02:52:32,913 - mmseg - INFO - Iter [70400/160000] lr: 1.875e-05, eta: 7:39:58, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8934, loss: 0.0788 2023-03-04 02:52:45,013 - mmseg - INFO - Iter [70450/160000] lr: 1.875e-05, eta: 7:39:39, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6279, loss: 0.0836 2023-03-04 02:52:59,467 - mmseg - INFO - Iter [70500/160000] lr: 1.875e-05, eta: 7:39:22, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8111, loss: 0.0811 2023-03-04 02:53:11,676 - mmseg - INFO - Iter [70550/160000] lr: 1.875e-05, eta: 7:39:03, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8348, loss: 0.0806 2023-03-04 02:53:24,050 - mmseg - INFO - Iter [70600/160000] lr: 1.875e-05, eta: 7:38:44, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7875, loss: 0.0813 2023-03-04 02:53:36,209 - mmseg - INFO - Iter [70650/160000] lr: 1.875e-05, eta: 7:38:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8585, loss: 0.0797 2023-03-04 02:53:50,674 - mmseg - INFO - Iter [70700/160000] lr: 1.875e-05, eta: 7:38:08, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8845, loss: 0.0786 2023-03-04 02:54:02,915 - mmseg - INFO - Iter [70750/160000] lr: 1.875e-05, eta: 7:37:48, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7944, loss: 0.0816 2023-03-04 02:54:15,112 - mmseg - INFO - Iter [70800/160000] lr: 1.875e-05, eta: 7:37:29, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9351, loss: 0.0780 2023-03-04 02:54:27,344 - mmseg - INFO - Iter [70850/160000] lr: 1.875e-05, eta: 7:37:09, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7046, loss: 0.0832 2023-03-04 02:54:41,790 - mmseg - INFO - Iter [70900/160000] lr: 1.875e-05, eta: 7:36:53, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8939, loss: 0.0793 2023-03-04 02:54:54,067 - mmseg - INFO - Iter [70950/160000] lr: 1.875e-05, eta: 7:36:34, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8437, loss: 0.0794 2023-03-04 02:55:06,251 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:55:06,251 - mmseg - INFO - Iter [71000/160000] lr: 1.875e-05, eta: 7:36:14, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8936, loss: 0.0784 2023-03-04 02:55:18,510 - mmseg - INFO - Iter [71050/160000] lr: 1.875e-05, eta: 7:35:55, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7461, loss: 0.0811 2023-03-04 02:55:33,106 - mmseg - INFO - Iter [71100/160000] lr: 1.875e-05, eta: 7:35:39, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8407, loss: 0.0798 2023-03-04 02:55:45,416 - mmseg - INFO - Iter [71150/160000] lr: 1.875e-05, eta: 7:35:19, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.9058, loss: 0.0789 2023-03-04 02:55:57,524 - mmseg - INFO - Iter [71200/160000] lr: 1.875e-05, eta: 7:35:00, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8022, loss: 0.0806 2023-03-04 02:56:12,026 - mmseg - INFO - Iter [71250/160000] lr: 1.875e-05, eta: 7:34:43, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7154, loss: 0.0833 2023-03-04 02:56:24,179 - mmseg - INFO - Iter [71300/160000] lr: 1.875e-05, eta: 7:34:24, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8245, loss: 0.0798 2023-03-04 02:56:36,363 - mmseg - INFO - Iter [71350/160000] lr: 1.875e-05, eta: 7:34:05, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.6833, loss: 0.0849 2023-03-04 02:56:48,561 - mmseg - INFO - Iter [71400/160000] lr: 1.875e-05, eta: 7:33:45, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8195, loss: 0.0800 2023-03-04 02:57:03,074 - mmseg - INFO - Iter [71450/160000] lr: 1.875e-05, eta: 7:33:29, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7856, loss: 0.0808 2023-03-04 02:57:15,190 - mmseg - INFO - Iter [71500/160000] lr: 1.875e-05, eta: 7:33:10, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.5982, loss: 0.0856 2023-03-04 02:57:27,527 - mmseg - INFO - Iter [71550/160000] lr: 1.875e-05, eta: 7:32:51, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9515, loss: 0.0773 2023-03-04 02:57:39,625 - mmseg - INFO - Iter [71600/160000] lr: 1.875e-05, eta: 7:32:31, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8349, loss: 0.0793 2023-03-04 02:57:54,118 - mmseg - INFO - Iter [71650/160000] lr: 1.875e-05, eta: 7:32:15, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9104, loss: 0.0778 2023-03-04 02:58:06,253 - mmseg - INFO - Iter [71700/160000] lr: 1.875e-05, eta: 7:31:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7722, loss: 0.0823 2023-03-04 02:58:18,474 - mmseg - INFO - Iter [71750/160000] lr: 1.875e-05, eta: 7:31:36, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7912, loss: 0.0803 2023-03-04 02:58:33,231 - mmseg - INFO - Iter [71800/160000] lr: 1.875e-05, eta: 7:31:20, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7917, loss: 0.0821 2023-03-04 02:58:45,656 - mmseg - INFO - Iter [71850/160000] lr: 1.875e-05, eta: 7:31:01, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9380, loss: 0.0771 2023-03-04 02:58:57,789 - mmseg - INFO - Iter [71900/160000] lr: 1.875e-05, eta: 7:30:42, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7336, loss: 0.0822 2023-03-04 02:59:10,047 - mmseg - INFO - Iter [71950/160000] lr: 1.875e-05, eta: 7:30:23, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8324, loss: 0.0803 2023-03-04 02:59:24,674 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 02:59:24,674 - mmseg - INFO - Iter [72000/160000] lr: 1.875e-05, eta: 7:30:06, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8785, loss: 0.0807 2023-03-04 02:59:36,835 - mmseg - INFO - Iter [72050/160000] lr: 1.875e-05, eta: 7:29:47, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0880, decode.acc_seg: 96.5584, loss: 0.0880 2023-03-04 02:59:48,969 - mmseg - INFO - Iter [72100/160000] lr: 1.875e-05, eta: 7:29:28, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7674, loss: 0.0818 2023-03-04 03:00:01,206 - mmseg - INFO - Iter [72150/160000] lr: 1.875e-05, eta: 7:29:09, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8700, loss: 0.0785 2023-03-04 03:00:15,690 - mmseg - INFO - Iter [72200/160000] lr: 1.875e-05, eta: 7:28:53, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8943, loss: 0.0783 2023-03-04 03:00:27,910 - mmseg - INFO - Iter [72250/160000] lr: 1.875e-05, eta: 7:28:33, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9263, loss: 0.0774 2023-03-04 03:00:40,166 - mmseg - INFO - Iter [72300/160000] lr: 1.875e-05, eta: 7:28:14, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7858, loss: 0.0816 2023-03-04 03:00:52,321 - mmseg - INFO - Iter [72350/160000] lr: 1.875e-05, eta: 7:27:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7360, loss: 0.0837 2023-03-04 03:01:06,812 - mmseg - INFO - Iter [72400/160000] lr: 1.875e-05, eta: 7:27:39, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7928, loss: 0.0808 2023-03-04 03:01:19,111 - mmseg - INFO - Iter [72450/160000] lr: 1.875e-05, eta: 7:27:20, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7986, loss: 0.0803 2023-03-04 03:01:31,373 - mmseg - INFO - Iter [72500/160000] lr: 1.875e-05, eta: 7:27:01, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7990, loss: 0.0815 2023-03-04 03:01:45,922 - mmseg - INFO - Iter [72550/160000] lr: 1.875e-05, eta: 7:26:44, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9073, loss: 0.0784 2023-03-04 03:01:58,147 - mmseg - INFO - Iter [72600/160000] lr: 1.875e-05, eta: 7:26:25, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8490, loss: 0.0801 2023-03-04 03:02:10,353 - mmseg - INFO - Iter [72650/160000] lr: 1.875e-05, eta: 7:26:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6707, loss: 0.0851 2023-03-04 03:02:22,559 - mmseg - INFO - Iter [72700/160000] lr: 1.875e-05, eta: 7:25:47, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7601, loss: 0.0819 2023-03-04 03:02:37,150 - mmseg - INFO - Iter [72750/160000] lr: 1.875e-05, eta: 7:25:31, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0742, decode.acc_seg: 97.0503, loss: 0.0742 2023-03-04 03:02:49,305 - mmseg - INFO - Iter [72800/160000] lr: 1.875e-05, eta: 7:25:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8848, loss: 0.0790 2023-03-04 03:03:01,532 - mmseg - INFO - Iter [72850/160000] lr: 1.875e-05, eta: 7:24:53, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7359, loss: 0.0825 2023-03-04 03:03:13,805 - mmseg - INFO - Iter [72900/160000] lr: 1.875e-05, eta: 7:24:34, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7074, loss: 0.0821 2023-03-04 03:03:28,307 - mmseg - INFO - Iter [72950/160000] lr: 1.875e-05, eta: 7:24:18, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8460, loss: 0.0788 2023-03-04 03:03:40,457 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:03:40,458 - mmseg - INFO - Iter [73000/160000] lr: 1.875e-05, eta: 7:23:59, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8396, loss: 0.0808 2023-03-04 03:03:52,676 - mmseg - INFO - Iter [73050/160000] lr: 1.875e-05, eta: 7:23:40, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8300, loss: 0.0804 2023-03-04 03:04:07,146 - mmseg - INFO - Iter [73100/160000] lr: 1.875e-05, eta: 7:23:23, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8374, loss: 0.0800 2023-03-04 03:04:19,431 - mmseg - INFO - Iter [73150/160000] lr: 1.875e-05, eta: 7:23:04, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 97.0030, loss: 0.0762 2023-03-04 03:04:31,593 - mmseg - INFO - Iter [73200/160000] lr: 1.875e-05, eta: 7:22:45, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.7999, loss: 0.0800 2023-03-04 03:04:43,882 - mmseg - INFO - Iter [73250/160000] lr: 1.875e-05, eta: 7:22:27, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7629, loss: 0.0829 2023-03-04 03:04:58,392 - mmseg - INFO - Iter [73300/160000] lr: 1.875e-05, eta: 7:22:10, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7368, loss: 0.0814 2023-03-04 03:05:10,543 - mmseg - INFO - Iter [73350/160000] lr: 1.875e-05, eta: 7:21:51, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8068, loss: 0.0808 2023-03-04 03:05:22,946 - mmseg - INFO - Iter [73400/160000] lr: 1.875e-05, eta: 7:21:33, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8098, loss: 0.0808 2023-03-04 03:05:35,227 - mmseg - INFO - Iter [73450/160000] lr: 1.875e-05, eta: 7:21:14, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7763, loss: 0.0832 2023-03-04 03:05:49,678 - mmseg - INFO - Iter [73500/160000] lr: 1.875e-05, eta: 7:20:57, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9583, loss: 0.0775 2023-03-04 03:06:01,849 - mmseg - INFO - Iter [73550/160000] lr: 1.875e-05, eta: 7:20:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8428, loss: 0.0788 2023-03-04 03:06:14,062 - mmseg - INFO - Iter [73600/160000] lr: 1.875e-05, eta: 7:20:20, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7915, loss: 0.0810 2023-03-04 03:06:26,212 - mmseg - INFO - Iter [73650/160000] lr: 1.875e-05, eta: 7:20:01, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.9224, loss: 0.0790 2023-03-04 03:06:40,920 - mmseg - INFO - Iter [73700/160000] lr: 1.875e-05, eta: 7:19:45, time: 0.294, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8984, loss: 0.0786 2023-03-04 03:06:53,092 - mmseg - INFO - Iter [73750/160000] lr: 1.875e-05, eta: 7:19:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8894, loss: 0.0791 2023-03-04 03:07:05,305 - mmseg - INFO - Iter [73800/160000] lr: 1.875e-05, eta: 7:19:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7973, loss: 0.0810 2023-03-04 03:07:19,949 - mmseg - INFO - Iter [73850/160000] lr: 1.875e-05, eta: 7:18:51, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7741, loss: 0.0810 2023-03-04 03:07:32,106 - mmseg - INFO - Iter [73900/160000] lr: 1.875e-05, eta: 7:18:32, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8577, loss: 0.0788 2023-03-04 03:07:44,349 - mmseg - INFO - Iter [73950/160000] lr: 1.875e-05, eta: 7:18:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8285, loss: 0.0800 2023-03-04 03:07:56,564 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:07:56,564 - mmseg - INFO - Iter [74000/160000] lr: 1.875e-05, eta: 7:17:54, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8009, loss: 0.0816 2023-03-04 03:08:11,046 - mmseg - INFO - Iter [74050/160000] lr: 1.875e-05, eta: 7:17:38, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8577, loss: 0.0797 2023-03-04 03:08:23,285 - mmseg - INFO - Iter [74100/160000] lr: 1.875e-05, eta: 7:17:19, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8380, loss: 0.0793 2023-03-04 03:08:35,563 - mmseg - INFO - Iter [74150/160000] lr: 1.875e-05, eta: 7:17:01, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8034, loss: 0.0811 2023-03-04 03:08:47,833 - mmseg - INFO - Iter [74200/160000] lr: 1.875e-05, eta: 7:16:42, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9341, loss: 0.0766 2023-03-04 03:09:02,348 - mmseg - INFO - Iter [74250/160000] lr: 1.875e-05, eta: 7:16:26, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8024, loss: 0.0814 2023-03-04 03:09:14,557 - mmseg - INFO - Iter [74300/160000] lr: 1.875e-05, eta: 7:16:07, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8976, loss: 0.0778 2023-03-04 03:09:26,772 - mmseg - INFO - Iter [74350/160000] lr: 1.875e-05, eta: 7:15:48, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7850, loss: 0.0807 2023-03-04 03:09:39,097 - mmseg - INFO - Iter [74400/160000] lr: 1.875e-05, eta: 7:15:29, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8297, loss: 0.0805 2023-03-04 03:09:53,677 - mmseg - INFO - Iter [74450/160000] lr: 1.875e-05, eta: 7:15:13, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7107, loss: 0.0823 2023-03-04 03:10:05,841 - mmseg - INFO - Iter [74500/160000] lr: 1.875e-05, eta: 7:14:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8354, loss: 0.0806 2023-03-04 03:10:18,036 - mmseg - INFO - Iter [74550/160000] lr: 1.875e-05, eta: 7:14:36, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8907, loss: 0.0784 2023-03-04 03:10:32,476 - mmseg - INFO - Iter [74600/160000] lr: 1.875e-05, eta: 7:14:20, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8031, loss: 0.0806 2023-03-04 03:10:44,792 - mmseg - INFO - Iter [74650/160000] lr: 1.875e-05, eta: 7:14:01, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8424, loss: 0.0796 2023-03-04 03:10:56,927 - mmseg - INFO - Iter [74700/160000] lr: 1.875e-05, eta: 7:13:42, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7965, loss: 0.0811 2023-03-04 03:11:09,267 - mmseg - INFO - Iter [74750/160000] lr: 1.875e-05, eta: 7:13:24, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9010, loss: 0.0785 2023-03-04 03:11:23,878 - mmseg - INFO - Iter [74800/160000] lr: 1.875e-05, eta: 7:13:08, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7746, loss: 0.0820 2023-03-04 03:11:36,184 - mmseg - INFO - Iter [74850/160000] lr: 1.875e-05, eta: 7:12:49, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8565, loss: 0.0787 2023-03-04 03:11:48,573 - mmseg - INFO - Iter [74900/160000] lr: 1.875e-05, eta: 7:12:30, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7664, loss: 0.0826 2023-03-04 03:12:00,742 - mmseg - INFO - Iter [74950/160000] lr: 1.875e-05, eta: 7:12:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7153, loss: 0.0829 2023-03-04 03:12:15,279 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:12:15,279 - mmseg - INFO - Iter [75000/160000] lr: 1.875e-05, eta: 7:11:56, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7934, loss: 0.0808 2023-03-04 03:12:27,526 - mmseg - INFO - Iter [75050/160000] lr: 1.875e-05, eta: 7:11:37, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7831, loss: 0.0809 2023-03-04 03:12:39,660 - mmseg - INFO - Iter [75100/160000] lr: 1.875e-05, eta: 7:11:18, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8484, loss: 0.0795 2023-03-04 03:12:54,435 - mmseg - INFO - Iter [75150/160000] lr: 1.875e-05, eta: 7:11:03, time: 0.295, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8930, loss: 0.0781 2023-03-04 03:13:06,776 - mmseg - INFO - Iter [75200/160000] lr: 1.875e-05, eta: 7:10:44, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7898, loss: 0.0814 2023-03-04 03:13:18,911 - mmseg - INFO - Iter [75250/160000] lr: 1.875e-05, eta: 7:10:25, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8918, loss: 0.0783 2023-03-04 03:13:31,078 - mmseg - INFO - Iter [75300/160000] lr: 1.875e-05, eta: 7:10:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7358, loss: 0.0832 2023-03-04 03:13:45,698 - mmseg - INFO - Iter [75350/160000] lr: 1.875e-05, eta: 7:09:51, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8441, loss: 0.0790 2023-03-04 03:13:57,815 - mmseg - INFO - Iter [75400/160000] lr: 1.875e-05, eta: 7:09:32, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8952, loss: 0.0780 2023-03-04 03:14:10,076 - mmseg - INFO - Iter [75450/160000] lr: 1.875e-05, eta: 7:09:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7858, loss: 0.0808 2023-03-04 03:14:22,203 - mmseg - INFO - Iter [75500/160000] lr: 1.875e-05, eta: 7:08:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7496, loss: 0.0822 2023-03-04 03:14:36,731 - mmseg - INFO - Iter [75550/160000] lr: 1.875e-05, eta: 7:08:39, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7472, loss: 0.0825 2023-03-04 03:14:48,942 - mmseg - INFO - Iter [75600/160000] lr: 1.875e-05, eta: 7:08:20, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6339, loss: 0.0853 2023-03-04 03:15:01,141 - mmseg - INFO - Iter [75650/160000] lr: 1.875e-05, eta: 7:08:01, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7207, loss: 0.0821 2023-03-04 03:15:13,333 - mmseg - INFO - Iter [75700/160000] lr: 1.875e-05, eta: 7:07:43, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.9170, loss: 0.0791 2023-03-04 03:15:27,892 - mmseg - INFO - Iter [75750/160000] lr: 1.875e-05, eta: 7:07:27, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7994, loss: 0.0810 2023-03-04 03:15:40,129 - mmseg - INFO - Iter [75800/160000] lr: 1.875e-05, eta: 7:07:08, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7042, loss: 0.0837 2023-03-04 03:15:52,316 - mmseg - INFO - Iter [75850/160000] lr: 1.875e-05, eta: 7:06:50, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9228, loss: 0.0771 2023-03-04 03:16:06,826 - mmseg - INFO - Iter [75900/160000] lr: 1.875e-05, eta: 7:06:34, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7266, loss: 0.0820 2023-03-04 03:16:19,160 - mmseg - INFO - Iter [75950/160000] lr: 1.875e-05, eta: 7:06:15, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8702, loss: 0.0791 2023-03-04 03:16:31,332 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:16:31,332 - mmseg - INFO - Iter [76000/160000] lr: 1.875e-05, eta: 7:05:57, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8038, loss: 0.0806 2023-03-04 03:16:43,580 - mmseg - INFO - Iter [76050/160000] lr: 1.875e-05, eta: 7:05:38, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7179, loss: 0.0831 2023-03-04 03:16:58,138 - mmseg - INFO - Iter [76100/160000] lr: 1.875e-05, eta: 7:05:22, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8060, loss: 0.0804 2023-03-04 03:17:10,219 - mmseg - INFO - Iter [76150/160000] lr: 1.875e-05, eta: 7:05:04, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8910, loss: 0.0790 2023-03-04 03:17:22,476 - mmseg - INFO - Iter [76200/160000] lr: 1.875e-05, eta: 7:04:45, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7981, loss: 0.0811 2023-03-04 03:17:34,582 - mmseg - INFO - Iter [76250/160000] lr: 1.875e-05, eta: 7:04:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6313, loss: 0.0850 2023-03-04 03:17:49,168 - mmseg - INFO - Iter [76300/160000] lr: 1.875e-05, eta: 7:04:11, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9449, loss: 0.0772 2023-03-04 03:18:01,418 - mmseg - INFO - Iter [76350/160000] lr: 1.875e-05, eta: 7:03:52, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.7960, loss: 0.0801 2023-03-04 03:18:13,627 - mmseg - INFO - Iter [76400/160000] lr: 1.875e-05, eta: 7:03:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7587, loss: 0.0822 2023-03-04 03:18:28,028 - mmseg - INFO - Iter [76450/160000] lr: 1.875e-05, eta: 7:03:18, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7431, loss: 0.0818 2023-03-04 03:18:40,363 - mmseg - INFO - Iter [76500/160000] lr: 1.875e-05, eta: 7:02:59, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7869, loss: 0.0809 2023-03-04 03:18:52,496 - mmseg - INFO - Iter [76550/160000] lr: 1.875e-05, eta: 7:02:41, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9254, loss: 0.0774 2023-03-04 03:19:04,849 - mmseg - INFO - Iter [76600/160000] lr: 1.875e-05, eta: 7:02:23, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7866, loss: 0.0812 2023-03-04 03:19:19,289 - mmseg - INFO - Iter [76650/160000] lr: 1.875e-05, eta: 7:02:07, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8894, loss: 0.0788 2023-03-04 03:19:31,424 - mmseg - INFO - Iter [76700/160000] lr: 1.875e-05, eta: 7:01:48, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8314, loss: 0.0798 2023-03-04 03:19:43,630 - mmseg - INFO - Iter [76750/160000] lr: 1.875e-05, eta: 7:01:30, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7243, loss: 0.0823 2023-03-04 03:19:55,881 - mmseg - INFO - Iter [76800/160000] lr: 1.875e-05, eta: 7:01:11, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7626, loss: 0.0815 2023-03-04 03:20:10,429 - mmseg - INFO - Iter [76850/160000] lr: 1.875e-05, eta: 7:00:55, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7457, loss: 0.0827 2023-03-04 03:20:22,534 - mmseg - INFO - Iter [76900/160000] lr: 1.875e-05, eta: 7:00:37, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8254, loss: 0.0809 2023-03-04 03:20:34,966 - mmseg - INFO - Iter [76950/160000] lr: 1.875e-05, eta: 7:00:19, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8290, loss: 0.0788 2023-03-04 03:20:47,138 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:20:47,138 - mmseg - INFO - Iter [77000/160000] lr: 1.875e-05, eta: 7:00:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7488, loss: 0.0825 2023-03-04 03:21:01,772 - mmseg - INFO - Iter [77050/160000] lr: 1.875e-05, eta: 6:59:45, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8238, loss: 0.0796 2023-03-04 03:21:13,949 - mmseg - INFO - Iter [77100/160000] lr: 1.875e-05, eta: 6:59:26, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8246, loss: 0.0806 2023-03-04 03:21:26,063 - mmseg - INFO - Iter [77150/160000] lr: 1.875e-05, eta: 6:59:08, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7714, loss: 0.0814 2023-03-04 03:21:40,519 - mmseg - INFO - Iter [77200/160000] lr: 1.875e-05, eta: 6:58:52, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7751, loss: 0.0819 2023-03-04 03:21:52,671 - mmseg - INFO - Iter [77250/160000] lr: 1.875e-05, eta: 6:58:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8699, loss: 0.0793 2023-03-04 03:22:04,870 - mmseg - INFO - Iter [77300/160000] lr: 1.875e-05, eta: 6:58:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.8257, loss: 0.0821 2023-03-04 03:22:17,064 - mmseg - INFO - Iter [77350/160000] lr: 1.875e-05, eta: 6:57:57, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8898, loss: 0.0785 2023-03-04 03:22:31,781 - mmseg - INFO - Iter [77400/160000] lr: 1.875e-05, eta: 6:57:41, time: 0.294, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8822, loss: 0.0794 2023-03-04 03:22:43,996 - mmseg - INFO - Iter [77450/160000] lr: 1.875e-05, eta: 6:57:23, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8799, loss: 0.0788 2023-03-04 03:22:56,111 - mmseg - INFO - Iter [77500/160000] lr: 1.875e-05, eta: 6:57:04, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8680, loss: 0.0796 2023-03-04 03:23:08,206 - mmseg - INFO - Iter [77550/160000] lr: 1.875e-05, eta: 6:56:46, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8848, loss: 0.0783 2023-03-04 03:23:22,783 - mmseg - INFO - Iter [77600/160000] lr: 1.875e-05, eta: 6:56:30, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9229, loss: 0.0774 2023-03-04 03:23:34,902 - mmseg - INFO - Iter [77650/160000] lr: 1.875e-05, eta: 6:56:12, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8324, loss: 0.0809 2023-03-04 03:23:47,098 - mmseg - INFO - Iter [77700/160000] lr: 1.875e-05, eta: 6:55:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7679, loss: 0.0815 2023-03-04 03:24:01,770 - mmseg - INFO - Iter [77750/160000] lr: 1.875e-05, eta: 6:55:38, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8308, loss: 0.0800 2023-03-04 03:24:14,233 - mmseg - INFO - Iter [77800/160000] lr: 1.875e-05, eta: 6:55:20, time: 0.250, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7910, loss: 0.0816 2023-03-04 03:24:26,598 - mmseg - INFO - Iter [77850/160000] lr: 1.875e-05, eta: 6:55:01, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.6759, loss: 0.0837 2023-03-04 03:24:38,824 - mmseg - INFO - Iter [77900/160000] lr: 1.875e-05, eta: 6:54:43, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8450, loss: 0.0794 2023-03-04 03:24:53,463 - mmseg - INFO - Iter [77950/160000] lr: 1.875e-05, eta: 6:54:28, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8793, loss: 0.0779 2023-03-04 03:25:05,675 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:25:05,675 - mmseg - INFO - Iter [78000/160000] lr: 1.875e-05, eta: 6:54:09, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8283, loss: 0.0799 2023-03-04 03:25:17,781 - mmseg - INFO - Iter [78050/160000] lr: 1.875e-05, eta: 6:53:51, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9115, loss: 0.0788 2023-03-04 03:25:30,037 - mmseg - INFO - Iter [78100/160000] lr: 1.875e-05, eta: 6:53:33, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8264, loss: 0.0802 2023-03-04 03:25:44,585 - mmseg - INFO - Iter [78150/160000] lr: 1.875e-05, eta: 6:53:17, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8416, loss: 0.0806 2023-03-04 03:25:56,822 - mmseg - INFO - Iter [78200/160000] lr: 1.875e-05, eta: 6:52:59, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7279, loss: 0.0838 2023-03-04 03:26:09,002 - mmseg - INFO - Iter [78250/160000] lr: 1.875e-05, eta: 6:52:41, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7878, loss: 0.0814 2023-03-04 03:26:21,162 - mmseg - INFO - Iter [78300/160000] lr: 1.875e-05, eta: 6:52:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.9063, loss: 0.0789 2023-03-04 03:26:35,741 - mmseg - INFO - Iter [78350/160000] lr: 1.875e-05, eta: 6:52:07, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8095, loss: 0.0807 2023-03-04 03:26:47,962 - mmseg - INFO - Iter [78400/160000] lr: 1.875e-05, eta: 6:51:48, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8983, loss: 0.0783 2023-03-04 03:27:00,130 - mmseg - INFO - Iter [78450/160000] lr: 1.875e-05, eta: 6:51:30, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8364, loss: 0.0791 2023-03-04 03:27:14,611 - mmseg - INFO - Iter [78500/160000] lr: 1.875e-05, eta: 6:51:14, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7587, loss: 0.0818 2023-03-04 03:27:26,893 - mmseg - INFO - Iter [78550/160000] lr: 1.875e-05, eta: 6:50:56, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8769, loss: 0.0783 2023-03-04 03:27:39,007 - mmseg - INFO - Iter [78600/160000] lr: 1.875e-05, eta: 6:50:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8601, loss: 0.0807 2023-03-04 03:27:51,329 - mmseg - INFO - Iter [78650/160000] lr: 1.875e-05, eta: 6:50:20, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8296, loss: 0.0794 2023-03-04 03:28:05,917 - mmseg - INFO - Iter [78700/160000] lr: 1.875e-05, eta: 6:50:04, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7934, loss: 0.0814 2023-03-04 03:28:18,159 - mmseg - INFO - Iter [78750/160000] lr: 1.875e-05, eta: 6:49:46, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7452, loss: 0.0822 2023-03-04 03:28:30,345 - mmseg - INFO - Iter [78800/160000] lr: 1.875e-05, eta: 6:49:28, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9845, loss: 0.0771 2023-03-04 03:28:42,515 - mmseg - INFO - Iter [78850/160000] lr: 1.875e-05, eta: 6:49:10, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6879, loss: 0.0846 2023-03-04 03:28:57,139 - mmseg - INFO - Iter [78900/160000] lr: 1.875e-05, eta: 6:48:54, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7301, loss: 0.0828 2023-03-04 03:29:09,395 - mmseg - INFO - Iter [78950/160000] lr: 1.875e-05, eta: 6:48:36, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8384, loss: 0.0800 2023-03-04 03:29:21,753 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:29:21,753 - mmseg - INFO - Iter [79000/160000] lr: 1.875e-05, eta: 6:48:18, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7383, loss: 0.0821 2023-03-04 03:29:33,929 - mmseg - INFO - Iter [79050/160000] lr: 1.875e-05, eta: 6:48:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.9272, loss: 0.0793 2023-03-04 03:29:48,401 - mmseg - INFO - Iter [79100/160000] lr: 1.875e-05, eta: 6:47:44, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8991, loss: 0.0779 2023-03-04 03:30:00,533 - mmseg - INFO - Iter [79150/160000] lr: 1.875e-05, eta: 6:47:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7816, loss: 0.0807 2023-03-04 03:30:12,794 - mmseg - INFO - Iter [79200/160000] lr: 1.875e-05, eta: 6:47:08, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8540, loss: 0.0798 2023-03-04 03:30:27,296 - mmseg - INFO - Iter [79250/160000] lr: 1.875e-05, eta: 6:46:52, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.6969, loss: 0.0835 2023-03-04 03:30:39,472 - mmseg - INFO - Iter [79300/160000] lr: 1.875e-05, eta: 6:46:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.8910, loss: 0.0776 2023-03-04 03:30:51,730 - mmseg - INFO - Iter [79350/160000] lr: 1.875e-05, eta: 6:46:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8477, loss: 0.0804 2023-03-04 03:31:03,841 - mmseg - INFO - Iter [79400/160000] lr: 1.875e-05, eta: 6:45:58, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7642, loss: 0.0826 2023-03-04 03:31:18,412 - mmseg - INFO - Iter [79450/160000] lr: 1.875e-05, eta: 6:45:42, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8010, loss: 0.0802 2023-03-04 03:31:30,623 - mmseg - INFO - Iter [79500/160000] lr: 1.875e-05, eta: 6:45:24, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8137, loss: 0.0807 2023-03-04 03:31:42,918 - mmseg - INFO - Iter [79550/160000] lr: 1.875e-05, eta: 6:45:06, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7645, loss: 0.0821 2023-03-04 03:31:55,143 - mmseg - INFO - Iter [79600/160000] lr: 1.875e-05, eta: 6:44:48, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9263, loss: 0.0780 2023-03-04 03:32:09,660 - mmseg - INFO - Iter [79650/160000] lr: 1.875e-05, eta: 6:44:33, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7598, loss: 0.0822 2023-03-04 03:32:21,762 - mmseg - INFO - Iter [79700/160000] lr: 1.875e-05, eta: 6:44:14, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9579, loss: 0.0773 2023-03-04 03:32:33,922 - mmseg - INFO - Iter [79750/160000] lr: 1.875e-05, eta: 6:43:56, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9093, loss: 0.0787 2023-03-04 03:32:48,428 - mmseg - INFO - Iter [79800/160000] lr: 1.875e-05, eta: 6:43:41, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0842, decode.acc_seg: 96.6565, loss: 0.0842 2023-03-04 03:33:00,689 - mmseg - INFO - Iter [79850/160000] lr: 1.875e-05, eta: 6:43:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8067, loss: 0.0797 2023-03-04 03:33:12,971 - mmseg - INFO - Iter [79900/160000] lr: 1.875e-05, eta: 6:43:05, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9319, loss: 0.0775 2023-03-04 03:33:25,147 - mmseg - INFO - Iter [79950/160000] lr: 1.875e-05, eta: 6:42:47, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7880, loss: 0.0816 2023-03-04 03:33:39,843 - mmseg - INFO - Swap parameters (after train) after iter [80000] 2023-03-04 03:33:39,859 - mmseg - INFO - Saving checkpoint at 80000 iterations 2023-03-04 03:33:41,315 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:33:41,315 - mmseg - INFO - Iter [80000/160000] lr: 1.875e-05, eta: 6:42:33, time: 0.323, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6681, loss: 0.0844 2023-03-04 03:48:32,843 - mmseg - INFO - per class results: 2023-03-04 03:48:32,844 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.57,98.57,98.58,98.58,98.58,98.58,98.58,98.59,98.59,98.59,98.59 | | sidewalk | 87.74,87.75,87.8,87.81,87.83,87.84,87.86,87.89,87.91,87.9,87.92 | | building | 93.32,93.32,93.32,93.33,93.32,93.32,93.33,93.33,93.33,93.33,93.34 | | wall | 54.07,54.11,54.17,54.26,54.22,54.34,54.4,54.43,54.52,54.57,54.53 | | fence | 63.6,63.63,63.65,63.64,63.62,63.67,63.71,63.71,63.75,63.71,63.79 | | pole | 71.09,71.1,71.1,71.1,71.1,71.11,71.1,71.1,71.11,71.14,71.13 | | traffic light | 75.58,75.57,75.57,75.56,75.57,75.53,75.56,75.54,75.54,75.57,75.54 | | traffic sign | 83.33,83.33,83.35,83.35,83.35,83.36,83.37,83.36,83.37,83.39,83.39 | | vegetation | 92.94,92.94,92.95,92.95,92.95,92.96,92.96,92.95,92.96,92.97,92.97 | | terrain | 65.72,65.76,65.79,65.85,65.9,65.89,65.98,65.98,66.05,66.17,66.18 | | sky | 95.23,95.23,95.23,95.23,95.22,95.23,95.22,95.22,95.21,95.22,95.22 | | person | 84.84,84.85,84.85,84.85,84.84,84.84,84.83,84.84,84.83,84.83,84.83 | | rider | 67.49,67.49,67.5,67.49,67.45,67.43,67.4,67.44,67.43,67.38,67.39 | | car | 95.91,95.93,95.96,95.97,95.97,95.98,95.98,95.99,95.99,96.0,96.0 | | truck | 83.83,84.21,84.87,85.26,85.32,85.58,85.66,85.75,85.73,86.03,85.89 | | bus | 92.26,92.27,92.29,92.29,92.28,92.33,92.32,92.32,92.33,92.32,92.33 | | train | 86.02,85.98,85.98,85.99,86.03,86.02,86.0,86.0,86.12,86.21,86.04 | | motorcycle | 69.6,69.62,69.63,69.62,69.59,69.61,69.64,69.6,69.59,69.59,69.61 | | bicycle | 79.9,79.91,79.93,79.92,79.92,79.93,79.93,79.93,79.93,79.94,79.94 | +---------------+-------------------------------------------------------------------+ 2023-03-04 03:48:32,844 - mmseg - INFO - Summary: 2023-03-04 03:48:32,844 - mmseg - INFO - +------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +------------------------------------------------------------------+ | 81.11,81.13,81.19,81.21,81.21,81.24,81.25,81.26,81.28,81.31,81.3 | +------------------------------------------------------------------+ 2023-03-04 03:48:32,885 - mmseg - INFO - The previous best checkpoint /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune/best_mIoU_iter_64000.pth was removed 2023-03-04 03:48:34,245 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_80000.pth. 2023-03-04 03:48:34,246 - mmseg - INFO - Best mIoU is 0.8130 at 80000 iter. 2023-03-04 03:48:34,246 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:48:34,246 - mmseg - INFO - Iter(val) [63] mIoU: [0.8111, 0.8113, 0.8119, 0.8121, 0.8121, 0.8124, 0.8125, 0.8126, 0.8128, 0.8131, 0.813], copy_paste: 81.11,81.13,81.19,81.21,81.21,81.24,81.25,81.26,81.28,81.31,81.3 2023-03-04 03:48:34,253 - mmseg - INFO - Swap parameters (before train) before iter [80001] 2023-03-04 03:48:46,710 - mmseg - INFO - Iter [80050/160000] lr: 9.375e-06, eta: 6:57:07, time: 18.108, data_time: 17.868, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8036, loss: 0.0810 2023-03-04 03:48:59,023 - mmseg - INFO - Iter [80100/160000] lr: 9.375e-06, eta: 6:56:48, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8456, loss: 0.0803 2023-03-04 03:49:11,390 - mmseg - INFO - Iter [80150/160000] lr: 9.375e-06, eta: 6:56:29, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8601, loss: 0.0795 2023-03-04 03:49:26,123 - mmseg - INFO - Iter [80200/160000] lr: 9.375e-06, eta: 6:56:12, time: 0.295, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8544, loss: 0.0791 2023-03-04 03:49:38,503 - mmseg - INFO - Iter [80250/160000] lr: 9.375e-06, eta: 6:55:53, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8137, loss: 0.0802 2023-03-04 03:49:50,792 - mmseg - INFO - Iter [80300/160000] lr: 9.375e-06, eta: 6:55:34, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8503, loss: 0.0798 2023-03-04 03:50:03,056 - mmseg - INFO - Iter [80350/160000] lr: 9.375e-06, eta: 6:55:15, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9295, loss: 0.0773 2023-03-04 03:50:17,626 - mmseg - INFO - Iter [80400/160000] lr: 9.375e-06, eta: 6:54:59, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7221, loss: 0.0833 2023-03-04 03:50:29,843 - mmseg - INFO - Iter [80450/160000] lr: 9.375e-06, eta: 6:54:40, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8319, loss: 0.0799 2023-03-04 03:50:42,124 - mmseg - INFO - Iter [80500/160000] lr: 9.375e-06, eta: 6:54:21, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8706, loss: 0.0791 2023-03-04 03:50:56,790 - mmseg - INFO - Iter [80550/160000] lr: 9.375e-06, eta: 6:54:04, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7640, loss: 0.0814 2023-03-04 03:51:09,026 - mmseg - INFO - Iter [80600/160000] lr: 9.375e-06, eta: 6:53:45, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7723, loss: 0.0812 2023-03-04 03:51:21,380 - mmseg - INFO - Iter [80650/160000] lr: 9.375e-06, eta: 6:53:26, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8698, loss: 0.0786 2023-03-04 03:51:33,686 - mmseg - INFO - Iter [80700/160000] lr: 9.375e-06, eta: 6:53:07, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8872, loss: 0.0783 2023-03-04 03:51:48,383 - mmseg - INFO - Iter [80750/160000] lr: 9.375e-06, eta: 6:52:51, time: 0.294, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9546, loss: 0.0771 2023-03-04 03:52:00,515 - mmseg - INFO - Iter [80800/160000] lr: 9.375e-06, eta: 6:52:32, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8639, loss: 0.0791 2023-03-04 03:52:12,772 - mmseg - INFO - Iter [80850/160000] lr: 9.375e-06, eta: 6:52:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7864, loss: 0.0808 2023-03-04 03:52:24,878 - mmseg - INFO - Iter [80900/160000] lr: 9.375e-06, eta: 6:51:54, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7864, loss: 0.0803 2023-03-04 03:52:39,392 - mmseg - INFO - Iter [80950/160000] lr: 9.375e-06, eta: 6:51:37, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.7471, loss: 0.0801 2023-03-04 03:52:51,664 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:52:51,664 - mmseg - INFO - Iter [81000/160000] lr: 9.375e-06, eta: 6:51:18, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.8961, loss: 0.0776 2023-03-04 03:53:03,868 - mmseg - INFO - Iter [81050/160000] lr: 9.375e-06, eta: 6:50:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8141, loss: 0.0814 2023-03-04 03:53:18,379 - mmseg - INFO - Iter [81100/160000] lr: 9.375e-06, eta: 6:50:43, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7870, loss: 0.0808 2023-03-04 03:53:30,518 - mmseg - INFO - Iter [81150/160000] lr: 9.375e-06, eta: 6:50:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8588, loss: 0.0785 2023-03-04 03:53:42,703 - mmseg - INFO - Iter [81200/160000] lr: 9.375e-06, eta: 6:50:05, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9702, loss: 0.0761 2023-03-04 03:53:54,868 - mmseg - INFO - Iter [81250/160000] lr: 9.375e-06, eta: 6:49:46, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8625, loss: 0.0791 2023-03-04 03:54:09,540 - mmseg - INFO - Iter [81300/160000] lr: 9.375e-06, eta: 6:49:29, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8788, loss: 0.0791 2023-03-04 03:54:21,616 - mmseg - INFO - Iter [81350/160000] lr: 9.375e-06, eta: 6:49:10, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8102, loss: 0.0805 2023-03-04 03:54:34,040 - mmseg - INFO - Iter [81400/160000] lr: 9.375e-06, eta: 6:48:52, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7530, loss: 0.0810 2023-03-04 03:54:46,348 - mmseg - INFO - Iter [81450/160000] lr: 9.375e-06, eta: 6:48:33, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8346, loss: 0.0800 2023-03-04 03:55:00,929 - mmseg - INFO - Iter [81500/160000] lr: 9.375e-06, eta: 6:48:16, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8495, loss: 0.0796 2023-03-04 03:55:13,190 - mmseg - INFO - Iter [81550/160000] lr: 9.375e-06, eta: 6:47:57, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8043, loss: 0.0816 2023-03-04 03:55:25,500 - mmseg - INFO - Iter [81600/160000] lr: 9.375e-06, eta: 6:47:39, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7764, loss: 0.0811 2023-03-04 03:55:37,648 - mmseg - INFO - Iter [81650/160000] lr: 9.375e-06, eta: 6:47:20, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8780, loss: 0.0790 2023-03-04 03:55:52,100 - mmseg - INFO - Iter [81700/160000] lr: 9.375e-06, eta: 6:47:03, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7363, loss: 0.0831 2023-03-04 03:56:04,346 - mmseg - INFO - Iter [81750/160000] lr: 9.375e-06, eta: 6:46:44, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8904, loss: 0.0790 2023-03-04 03:56:16,528 - mmseg - INFO - Iter [81800/160000] lr: 9.375e-06, eta: 6:46:25, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8603, loss: 0.0794 2023-03-04 03:56:31,006 - mmseg - INFO - Iter [81850/160000] lr: 9.375e-06, eta: 6:46:09, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 96.9845, loss: 0.0754 2023-03-04 03:56:43,089 - mmseg - INFO - Iter [81900/160000] lr: 9.375e-06, eta: 6:45:50, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9391, loss: 0.0765 2023-03-04 03:56:55,238 - mmseg - INFO - Iter [81950/160000] lr: 9.375e-06, eta: 6:45:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8828, loss: 0.0789 2023-03-04 03:57:07,486 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 03:57:07,487 - mmseg - INFO - Iter [82000/160000] lr: 9.375e-06, eta: 6:45:12, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7761, loss: 0.0818 2023-03-04 03:57:22,216 - mmseg - INFO - Iter [82050/160000] lr: 9.375e-06, eta: 6:44:56, time: 0.294, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8410, loss: 0.0791 2023-03-04 03:57:34,606 - mmseg - INFO - Iter [82100/160000] lr: 9.375e-06, eta: 6:44:37, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8239, loss: 0.0802 2023-03-04 03:57:46,823 - mmseg - INFO - Iter [82150/160000] lr: 9.375e-06, eta: 6:44:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8391, loss: 0.0805 2023-03-04 03:57:59,140 - mmseg - INFO - Iter [82200/160000] lr: 9.375e-06, eta: 6:44:00, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7208, loss: 0.0814 2023-03-04 03:58:13,739 - mmseg - INFO - Iter [82250/160000] lr: 9.375e-06, eta: 6:43:43, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8378, loss: 0.0790 2023-03-04 03:58:25,916 - mmseg - INFO - Iter [82300/160000] lr: 9.375e-06, eta: 6:43:24, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7954, loss: 0.0819 2023-03-04 03:58:37,996 - mmseg - INFO - Iter [82350/160000] lr: 9.375e-06, eta: 6:43:05, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9279, loss: 0.0774 2023-03-04 03:58:52,560 - mmseg - INFO - Iter [82400/160000] lr: 9.375e-06, eta: 6:42:49, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8275, loss: 0.0804 2023-03-04 03:59:04,831 - mmseg - INFO - Iter [82450/160000] lr: 9.375e-06, eta: 6:42:30, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0748, decode.acc_seg: 97.0298, loss: 0.0748 2023-03-04 03:59:17,020 - mmseg - INFO - Iter [82500/160000] lr: 9.375e-06, eta: 6:42:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8033, loss: 0.0809 2023-03-04 03:59:29,169 - mmseg - INFO - Iter [82550/160000] lr: 9.375e-06, eta: 6:41:53, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8441, loss: 0.0799 2023-03-04 03:59:43,663 - mmseg - INFO - Iter [82600/160000] lr: 9.375e-06, eta: 6:41:36, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8289, loss: 0.0802 2023-03-04 03:59:55,801 - mmseg - INFO - Iter [82650/160000] lr: 9.375e-06, eta: 6:41:17, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7632, loss: 0.0811 2023-03-04 04:00:07,994 - mmseg - INFO - Iter [82700/160000] lr: 9.375e-06, eta: 6:40:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7866, loss: 0.0809 2023-03-04 04:00:20,279 - mmseg - INFO - Iter [82750/160000] lr: 9.375e-06, eta: 6:40:40, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.7936, loss: 0.0796 2023-03-04 04:00:34,923 - mmseg - INFO - Iter [82800/160000] lr: 9.375e-06, eta: 6:40:24, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8010, loss: 0.0801 2023-03-04 04:00:47,120 - mmseg - INFO - Iter [82850/160000] lr: 9.375e-06, eta: 6:40:05, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9195, loss: 0.0776 2023-03-04 04:00:59,488 - mmseg - INFO - Iter [82900/160000] lr: 9.375e-06, eta: 6:39:46, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8137, loss: 0.0816 2023-03-04 04:01:11,957 - mmseg - INFO - Iter [82950/160000] lr: 9.375e-06, eta: 6:39:28, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8540, loss: 0.0797 2023-03-04 04:01:26,524 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:01:26,525 - mmseg - INFO - Iter [83000/160000] lr: 9.375e-06, eta: 6:39:12, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8013, loss: 0.0813 2023-03-04 04:01:38,745 - mmseg - INFO - Iter [83050/160000] lr: 9.375e-06, eta: 6:38:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9025, loss: 0.0788 2023-03-04 04:01:50,935 - mmseg - INFO - Iter [83100/160000] lr: 9.375e-06, eta: 6:38:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7294, loss: 0.0834 2023-03-04 04:02:05,406 - mmseg - INFO - Iter [83150/160000] lr: 9.375e-06, eta: 6:38:18, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8784, loss: 0.0794 2023-03-04 04:02:17,605 - mmseg - INFO - Iter [83200/160000] lr: 9.375e-06, eta: 6:37:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8248, loss: 0.0802 2023-03-04 04:02:29,920 - mmseg - INFO - Iter [83250/160000] lr: 9.375e-06, eta: 6:37:40, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8348, loss: 0.0787 2023-03-04 04:02:42,154 - mmseg - INFO - Iter [83300/160000] lr: 9.375e-06, eta: 6:37:22, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8895, loss: 0.0791 2023-03-04 04:02:56,793 - mmseg - INFO - Iter [83350/160000] lr: 9.375e-06, eta: 6:37:06, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8991, loss: 0.0786 2023-03-04 04:03:09,000 - mmseg - INFO - Iter [83400/160000] lr: 9.375e-06, eta: 6:36:47, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8463, loss: 0.0786 2023-03-04 04:03:21,382 - mmseg - INFO - Iter [83450/160000] lr: 9.375e-06, eta: 6:36:28, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8545, loss: 0.0796 2023-03-04 04:03:33,644 - mmseg - INFO - Iter [83500/160000] lr: 9.375e-06, eta: 6:36:10, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8073, loss: 0.0813 2023-03-04 04:03:48,254 - mmseg - INFO - Iter [83550/160000] lr: 9.375e-06, eta: 6:35:54, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8588, loss: 0.0794 2023-03-04 04:04:00,378 - mmseg - INFO - Iter [83600/160000] lr: 9.375e-06, eta: 6:35:35, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8550, loss: 0.0792 2023-03-04 04:04:12,569 - mmseg - INFO - Iter [83650/160000] lr: 9.375e-06, eta: 6:35:16, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8255, loss: 0.0802 2023-03-04 04:04:24,731 - mmseg - INFO - Iter [83700/160000] lr: 9.375e-06, eta: 6:34:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9095, loss: 0.0780 2023-03-04 04:04:39,389 - mmseg - INFO - Iter [83750/160000] lr: 9.375e-06, eta: 6:34:41, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8679, loss: 0.0789 2023-03-04 04:04:51,615 - mmseg - INFO - Iter [83800/160000] lr: 9.375e-06, eta: 6:34:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8766, loss: 0.0786 2023-03-04 04:05:03,953 - mmseg - INFO - Iter [83850/160000] lr: 9.375e-06, eta: 6:34:04, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8163, loss: 0.0801 2023-03-04 04:05:18,479 - mmseg - INFO - Iter [83900/160000] lr: 9.375e-06, eta: 6:33:48, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7809, loss: 0.0809 2023-03-04 04:05:30,760 - mmseg - INFO - Iter [83950/160000] lr: 9.375e-06, eta: 6:33:30, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.8257, loss: 0.0822 2023-03-04 04:05:43,070 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:05:43,071 - mmseg - INFO - Iter [84000/160000] lr: 9.375e-06, eta: 6:33:11, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7965, loss: 0.0811 2023-03-04 04:05:55,362 - mmseg - INFO - Iter [84050/160000] lr: 9.375e-06, eta: 6:32:53, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8129, loss: 0.0796 2023-03-04 04:06:09,955 - mmseg - INFO - Iter [84100/160000] lr: 9.375e-06, eta: 6:32:36, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8836, loss: 0.0793 2023-03-04 04:06:22,097 - mmseg - INFO - Iter [84150/160000] lr: 9.375e-06, eta: 6:32:18, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7807, loss: 0.0805 2023-03-04 04:06:34,274 - mmseg - INFO - Iter [84200/160000] lr: 9.375e-06, eta: 6:31:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7176, loss: 0.0832 2023-03-04 04:06:46,534 - mmseg - INFO - Iter [84250/160000] lr: 9.375e-06, eta: 6:31:41, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7827, loss: 0.0808 2023-03-04 04:07:01,119 - mmseg - INFO - Iter [84300/160000] lr: 9.375e-06, eta: 6:31:24, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7894, loss: 0.0809 2023-03-04 04:07:13,314 - mmseg - INFO - Iter [84350/160000] lr: 9.375e-06, eta: 6:31:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8033, loss: 0.0803 2023-03-04 04:07:25,383 - mmseg - INFO - Iter [84400/160000] lr: 9.375e-06, eta: 6:30:47, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8677, loss: 0.0788 2023-03-04 04:07:39,978 - mmseg - INFO - Iter [84450/160000] lr: 9.375e-06, eta: 6:30:31, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.8944, loss: 0.0774 2023-03-04 04:07:52,363 - mmseg - INFO - Iter [84500/160000] lr: 9.375e-06, eta: 6:30:13, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9207, loss: 0.0777 2023-03-04 04:08:04,606 - mmseg - INFO - Iter [84550/160000] lr: 9.375e-06, eta: 6:29:54, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8060, loss: 0.0806 2023-03-04 04:08:16,825 - mmseg - INFO - Iter [84600/160000] lr: 9.375e-06, eta: 6:29:36, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9492, loss: 0.0762 2023-03-04 04:08:31,382 - mmseg - INFO - Iter [84650/160000] lr: 9.375e-06, eta: 6:29:20, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8791, loss: 0.0791 2023-03-04 04:08:43,559 - mmseg - INFO - Iter [84700/160000] lr: 9.375e-06, eta: 6:29:01, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7342, loss: 0.0819 2023-03-04 04:08:55,800 - mmseg - INFO - Iter [84750/160000] lr: 9.375e-06, eta: 6:28:43, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.8935, loss: 0.0775 2023-03-04 04:09:07,973 - mmseg - INFO - Iter [84800/160000] lr: 9.375e-06, eta: 6:28:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7434, loss: 0.0819 2023-03-04 04:09:22,731 - mmseg - INFO - Iter [84850/160000] lr: 9.375e-06, eta: 6:28:08, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8820, loss: 0.0787 2023-03-04 04:09:34,842 - mmseg - INFO - Iter [84900/160000] lr: 9.375e-06, eta: 6:27:50, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7509, loss: 0.0833 2023-03-04 04:09:47,023 - mmseg - INFO - Iter [84950/160000] lr: 9.375e-06, eta: 6:27:31, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7980, loss: 0.0818 2023-03-04 04:09:59,130 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:09:59,130 - mmseg - INFO - Iter [85000/160000] lr: 9.375e-06, eta: 6:27:13, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.7940, loss: 0.0797 2023-03-04 04:10:13,620 - mmseg - INFO - Iter [85050/160000] lr: 9.375e-06, eta: 6:26:56, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7164, loss: 0.0821 2023-03-04 04:10:25,944 - mmseg - INFO - Iter [85100/160000] lr: 9.375e-06, eta: 6:26:38, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9167, loss: 0.0778 2023-03-04 04:10:38,116 - mmseg - INFO - Iter [85150/160000] lr: 9.375e-06, eta: 6:26:20, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9159, loss: 0.0776 2023-03-04 04:10:52,582 - mmseg - INFO - Iter [85200/160000] lr: 9.375e-06, eta: 6:26:03, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9045, loss: 0.0786 2023-03-04 04:11:04,758 - mmseg - INFO - Iter [85250/160000] lr: 9.375e-06, eta: 6:25:45, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8273, loss: 0.0809 2023-03-04 04:11:17,040 - mmseg - INFO - Iter [85300/160000] lr: 9.375e-06, eta: 6:25:27, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8703, loss: 0.0791 2023-03-04 04:11:29,198 - mmseg - INFO - Iter [85350/160000] lr: 9.375e-06, eta: 6:25:08, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7954, loss: 0.0811 2023-03-04 04:11:43,671 - mmseg - INFO - Iter [85400/160000] lr: 9.375e-06, eta: 6:24:52, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8538, loss: 0.0806 2023-03-04 04:11:55,892 - mmseg - INFO - Iter [85450/160000] lr: 9.375e-06, eta: 6:24:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7876, loss: 0.0822 2023-03-04 04:12:08,082 - mmseg - INFO - Iter [85500/160000] lr: 9.375e-06, eta: 6:24:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8767, loss: 0.0782 2023-03-04 04:12:20,286 - mmseg - INFO - Iter [85550/160000] lr: 9.375e-06, eta: 6:23:57, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8597, loss: 0.0785 2023-03-04 04:12:34,763 - mmseg - INFO - Iter [85600/160000] lr: 9.375e-06, eta: 6:23:41, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7968, loss: 0.0805 2023-03-04 04:12:46,956 - mmseg - INFO - Iter [85650/160000] lr: 9.375e-06, eta: 6:23:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7405, loss: 0.0826 2023-03-04 04:12:59,038 - mmseg - INFO - Iter [85700/160000] lr: 9.375e-06, eta: 6:23:04, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8083, loss: 0.0808 2023-03-04 04:13:13,718 - mmseg - INFO - Iter [85750/160000] lr: 9.375e-06, eta: 6:22:48, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7379, loss: 0.0821 2023-03-04 04:13:26,058 - mmseg - INFO - Iter [85800/160000] lr: 9.375e-06, eta: 6:22:30, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8693, loss: 0.0787 2023-03-04 04:13:38,240 - mmseg - INFO - Iter [85850/160000] lr: 9.375e-06, eta: 6:22:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9351, loss: 0.0786 2023-03-04 04:13:50,417 - mmseg - INFO - Iter [85900/160000] lr: 9.375e-06, eta: 6:21:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9613, loss: 0.0767 2023-03-04 04:14:04,948 - mmseg - INFO - Iter [85950/160000] lr: 9.375e-06, eta: 6:21:37, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0760, decode.acc_seg: 96.9721, loss: 0.0760 2023-03-04 04:14:17,111 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:14:17,111 - mmseg - INFO - Iter [86000/160000] lr: 9.375e-06, eta: 6:21:18, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7251, loss: 0.0824 2023-03-04 04:14:29,210 - mmseg - INFO - Iter [86050/160000] lr: 9.375e-06, eta: 6:21:00, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9178, loss: 0.0779 2023-03-04 04:14:41,303 - mmseg - INFO - Iter [86100/160000] lr: 9.375e-06, eta: 6:20:42, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8449, loss: 0.0787 2023-03-04 04:14:55,867 - mmseg - INFO - Iter [86150/160000] lr: 9.375e-06, eta: 6:20:25, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8725, loss: 0.0794 2023-03-04 04:15:08,068 - mmseg - INFO - Iter [86200/160000] lr: 9.375e-06, eta: 6:20:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7871, loss: 0.0805 2023-03-04 04:15:20,206 - mmseg - INFO - Iter [86250/160000] lr: 9.375e-06, eta: 6:19:49, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9598, loss: 0.0766 2023-03-04 04:15:32,363 - mmseg - INFO - Iter [86300/160000] lr: 9.375e-06, eta: 6:19:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7656, loss: 0.0813 2023-03-04 04:15:46,827 - mmseg - INFO - Iter [86350/160000] lr: 9.375e-06, eta: 6:19:14, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9694, loss: 0.0765 2023-03-04 04:15:58,965 - mmseg - INFO - Iter [86400/160000] lr: 9.375e-06, eta: 6:18:56, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7486, loss: 0.0808 2023-03-04 04:16:11,272 - mmseg - INFO - Iter [86450/160000] lr: 9.375e-06, eta: 6:18:38, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.6948, loss: 0.0833 2023-03-04 04:16:25,752 - mmseg - INFO - Iter [86500/160000] lr: 9.375e-06, eta: 6:18:22, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9085, loss: 0.0787 2023-03-04 04:16:38,043 - mmseg - INFO - Iter [86550/160000] lr: 9.375e-06, eta: 6:18:04, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8972, loss: 0.0791 2023-03-04 04:16:50,281 - mmseg - INFO - Iter [86600/160000] lr: 9.375e-06, eta: 6:17:45, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8387, loss: 0.0791 2023-03-04 04:17:02,480 - mmseg - INFO - Iter [86650/160000] lr: 9.375e-06, eta: 6:17:27, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8530, loss: 0.0799 2023-03-04 04:17:16,951 - mmseg - INFO - Iter [86700/160000] lr: 9.375e-06, eta: 6:17:11, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0835, decode.acc_seg: 96.7765, loss: 0.0835 2023-03-04 04:17:29,411 - mmseg - INFO - Iter [86750/160000] lr: 9.375e-06, eta: 6:16:53, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.8831, loss: 0.0775 2023-03-04 04:17:41,810 - mmseg - INFO - Iter [86800/160000] lr: 9.375e-06, eta: 6:16:35, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8072, loss: 0.0812 2023-03-04 04:17:54,155 - mmseg - INFO - Iter [86850/160000] lr: 9.375e-06, eta: 6:16:17, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9225, loss: 0.0783 2023-03-04 04:18:08,701 - mmseg - INFO - Iter [86900/160000] lr: 9.375e-06, eta: 6:16:01, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7158, loss: 0.0841 2023-03-04 04:18:21,068 - mmseg - INFO - Iter [86950/160000] lr: 9.375e-06, eta: 6:15:43, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8201, loss: 0.0801 2023-03-04 04:18:33,232 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:18:33,232 - mmseg - INFO - Iter [87000/160000] lr: 9.375e-06, eta: 6:15:25, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8529, loss: 0.0798 2023-03-04 04:18:47,747 - mmseg - INFO - Iter [87050/160000] lr: 9.375e-06, eta: 6:15:08, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8304, loss: 0.0807 2023-03-04 04:18:59,981 - mmseg - INFO - Iter [87100/160000] lr: 9.375e-06, eta: 6:14:50, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8817, loss: 0.0782 2023-03-04 04:19:12,243 - mmseg - INFO - Iter [87150/160000] lr: 9.375e-06, eta: 6:14:32, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9192, loss: 0.0780 2023-03-04 04:19:24,529 - mmseg - INFO - Iter [87200/160000] lr: 9.375e-06, eta: 6:14:14, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9764, loss: 0.0768 2023-03-04 04:19:39,088 - mmseg - INFO - Iter [87250/160000] lr: 9.375e-06, eta: 6:13:58, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9008, loss: 0.0786 2023-03-04 04:19:51,306 - mmseg - INFO - Iter [87300/160000] lr: 9.375e-06, eta: 6:13:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9301, loss: 0.0777 2023-03-04 04:20:03,559 - mmseg - INFO - Iter [87350/160000] lr: 9.375e-06, eta: 6:13:22, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0840, decode.acc_seg: 96.6814, loss: 0.0840 2023-03-04 04:20:15,827 - mmseg - INFO - Iter [87400/160000] lr: 9.375e-06, eta: 6:13:04, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8709, loss: 0.0783 2023-03-04 04:20:30,404 - mmseg - INFO - Iter [87450/160000] lr: 9.375e-06, eta: 6:12:48, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9082, loss: 0.0776 2023-03-04 04:20:42,694 - mmseg - INFO - Iter [87500/160000] lr: 9.375e-06, eta: 6:12:30, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7622, loss: 0.0821 2023-03-04 04:20:54,969 - mmseg - INFO - Iter [87550/160000] lr: 9.375e-06, eta: 6:12:12, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9869, loss: 0.0763 2023-03-04 04:21:07,029 - mmseg - INFO - Iter [87600/160000] lr: 9.375e-06, eta: 6:11:54, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8794, loss: 0.0789 2023-03-04 04:21:21,514 - mmseg - INFO - Iter [87650/160000] lr: 9.375e-06, eta: 6:11:37, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7975, loss: 0.0821 2023-03-04 04:21:33,700 - mmseg - INFO - Iter [87700/160000] lr: 9.375e-06, eta: 6:11:19, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7776, loss: 0.0817 2023-03-04 04:21:46,001 - mmseg - INFO - Iter [87750/160000] lr: 9.375e-06, eta: 6:11:01, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9039, loss: 0.0788 2023-03-04 04:22:00,526 - mmseg - INFO - Iter [87800/160000] lr: 9.375e-06, eta: 6:10:45, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7675, loss: 0.0821 2023-03-04 04:22:12,688 - mmseg - INFO - Iter [87850/160000] lr: 9.375e-06, eta: 6:10:27, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.8955, loss: 0.0773 2023-03-04 04:22:24,909 - mmseg - INFO - Iter [87900/160000] lr: 9.375e-06, eta: 6:10:09, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8629, loss: 0.0786 2023-03-04 04:22:37,071 - mmseg - INFO - Iter [87950/160000] lr: 9.375e-06, eta: 6:09:51, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8037, loss: 0.0814 2023-03-04 04:22:51,646 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:22:51,646 - mmseg - INFO - Iter [88000/160000] lr: 9.375e-06, eta: 6:09:35, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8034, loss: 0.0806 2023-03-04 04:23:03,767 - mmseg - INFO - Iter [88050/160000] lr: 9.375e-06, eta: 6:09:17, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9076, loss: 0.0780 2023-03-04 04:23:16,066 - mmseg - INFO - Iter [88100/160000] lr: 9.375e-06, eta: 6:08:59, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8006, loss: 0.0811 2023-03-04 04:23:28,415 - mmseg - INFO - Iter [88150/160000] lr: 9.375e-06, eta: 6:08:41, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7963, loss: 0.0807 2023-03-04 04:23:43,113 - mmseg - INFO - Iter [88200/160000] lr: 9.375e-06, eta: 6:08:25, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9154, loss: 0.0787 2023-03-04 04:23:55,355 - mmseg - INFO - Iter [88250/160000] lr: 9.375e-06, eta: 6:08:07, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9189, loss: 0.0783 2023-03-04 04:24:07,517 - mmseg - INFO - Iter [88300/160000] lr: 9.375e-06, eta: 6:07:49, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7179, loss: 0.0841 2023-03-04 04:24:19,808 - mmseg - INFO - Iter [88350/160000] lr: 9.375e-06, eta: 6:07:31, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8368, loss: 0.0793 2023-03-04 04:24:34,386 - mmseg - INFO - Iter [88400/160000] lr: 9.375e-06, eta: 6:07:15, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7416, loss: 0.0811 2023-03-04 04:24:46,509 - mmseg - INFO - Iter [88450/160000] lr: 9.375e-06, eta: 6:06:57, time: 0.242, data_time: 0.010, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8571, loss: 0.0801 2023-03-04 04:24:58,717 - mmseg - INFO - Iter [88500/160000] lr: 9.375e-06, eta: 6:06:39, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8830, loss: 0.0784 2023-03-04 04:25:13,350 - mmseg - INFO - Iter [88550/160000] lr: 9.375e-06, eta: 6:06:23, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8499, loss: 0.0797 2023-03-04 04:25:25,489 - mmseg - INFO - Iter [88600/160000] lr: 9.375e-06, eta: 6:06:05, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9137, loss: 0.0778 2023-03-04 04:25:37,781 - mmseg - INFO - Iter [88650/160000] lr: 9.375e-06, eta: 6:05:47, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7432, loss: 0.0833 2023-03-04 04:25:50,019 - mmseg - INFO - Iter [88700/160000] lr: 9.375e-06, eta: 6:05:30, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7656, loss: 0.0813 2023-03-04 04:26:04,441 - mmseg - INFO - Iter [88750/160000] lr: 9.375e-06, eta: 6:05:13, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8929, loss: 0.0788 2023-03-04 04:26:16,566 - mmseg - INFO - Iter [88800/160000] lr: 9.375e-06, eta: 6:04:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.8133, loss: 0.0826 2023-03-04 04:26:28,723 - mmseg - INFO - Iter [88850/160000] lr: 9.375e-06, eta: 6:04:37, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9041, loss: 0.0784 2023-03-04 04:26:40,953 - mmseg - INFO - Iter [88900/160000] lr: 9.375e-06, eta: 6:04:20, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7062, loss: 0.0830 2023-03-04 04:26:55,598 - mmseg - INFO - Iter [88950/160000] lr: 9.375e-06, eta: 6:04:04, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8134, loss: 0.0809 2023-03-04 04:27:07,759 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:27:07,759 - mmseg - INFO - Iter [89000/160000] lr: 9.375e-06, eta: 6:03:46, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7081, loss: 0.0825 2023-03-04 04:27:19,904 - mmseg - INFO - Iter [89050/160000] lr: 9.375e-06, eta: 6:03:28, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9044, loss: 0.0787 2023-03-04 04:27:34,370 - mmseg - INFO - Iter [89100/160000] lr: 9.375e-06, eta: 6:03:12, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8129, loss: 0.0805 2023-03-04 04:27:46,631 - mmseg - INFO - Iter [89150/160000] lr: 9.375e-06, eta: 6:02:54, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8782, loss: 0.0784 2023-03-04 04:27:58,828 - mmseg - INFO - Iter [89200/160000] lr: 9.375e-06, eta: 6:02:36, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9258, loss: 0.0783 2023-03-04 04:28:11,076 - mmseg - INFO - Iter [89250/160000] lr: 9.375e-06, eta: 6:02:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7515, loss: 0.0820 2023-03-04 04:28:25,534 - mmseg - INFO - Iter [89300/160000] lr: 9.375e-06, eta: 6:02:02, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7617, loss: 0.0821 2023-03-04 04:28:37,865 - mmseg - INFO - Iter [89350/160000] lr: 9.375e-06, eta: 6:01:44, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7914, loss: 0.0815 2023-03-04 04:28:50,287 - mmseg - INFO - Iter [89400/160000] lr: 9.375e-06, eta: 6:01:27, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9908, loss: 0.0756 2023-03-04 04:29:02,440 - mmseg - INFO - Iter [89450/160000] lr: 9.375e-06, eta: 6:01:09, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8648, loss: 0.0786 2023-03-04 04:29:16,946 - mmseg - INFO - Iter [89500/160000] lr: 9.375e-06, eta: 6:00:53, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7973, loss: 0.0813 2023-03-04 04:29:29,229 - mmseg - INFO - Iter [89550/160000] lr: 9.375e-06, eta: 6:00:35, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8695, loss: 0.0787 2023-03-04 04:29:41,319 - mmseg - INFO - Iter [89600/160000] lr: 9.375e-06, eta: 6:00:17, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8106, loss: 0.0813 2023-03-04 04:29:53,645 - mmseg - INFO - Iter [89650/160000] lr: 9.375e-06, eta: 5:59:59, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9070, loss: 0.0784 2023-03-04 04:30:08,275 - mmseg - INFO - Iter [89700/160000] lr: 9.375e-06, eta: 5:59:43, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8316, loss: 0.0794 2023-03-04 04:30:20,421 - mmseg - INFO - Iter [89750/160000] lr: 9.375e-06, eta: 5:59:25, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8686, loss: 0.0798 2023-03-04 04:30:32,710 - mmseg - INFO - Iter [89800/160000] lr: 9.375e-06, eta: 5:59:08, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8671, loss: 0.0788 2023-03-04 04:30:47,192 - mmseg - INFO - Iter [89850/160000] lr: 9.375e-06, eta: 5:58:52, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.8830, loss: 0.0774 2023-03-04 04:30:59,384 - mmseg - INFO - Iter [89900/160000] lr: 9.375e-06, eta: 5:58:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8255, loss: 0.0802 2023-03-04 04:31:11,596 - mmseg - INFO - Iter [89950/160000] lr: 9.375e-06, eta: 5:58:16, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7440, loss: 0.0815 2023-03-04 04:31:23,691 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:31:23,691 - mmseg - INFO - Iter [90000/160000] lr: 9.375e-06, eta: 5:57:58, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8621, loss: 0.0794 2023-03-04 04:31:38,284 - mmseg - INFO - Iter [90050/160000] lr: 9.375e-06, eta: 5:57:42, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0860, decode.acc_seg: 96.6225, loss: 0.0860 2023-03-04 04:31:50,675 - mmseg - INFO - Iter [90100/160000] lr: 9.375e-06, eta: 5:57:25, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8800, loss: 0.0784 2023-03-04 04:32:02,846 - mmseg - INFO - Iter [90150/160000] lr: 9.375e-06, eta: 5:57:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9643, loss: 0.0771 2023-03-04 04:32:15,160 - mmseg - INFO - Iter [90200/160000] lr: 9.375e-06, eta: 5:56:49, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9071, loss: 0.0778 2023-03-04 04:32:29,632 - mmseg - INFO - Iter [90250/160000] lr: 9.375e-06, eta: 5:56:33, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8077, loss: 0.0809 2023-03-04 04:32:41,841 - mmseg - INFO - Iter [90300/160000] lr: 9.375e-06, eta: 5:56:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8657, loss: 0.0792 2023-03-04 04:32:54,092 - mmseg - INFO - Iter [90350/160000] lr: 9.375e-06, eta: 5:55:58, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8718, loss: 0.0793 2023-03-04 04:33:08,571 - mmseg - INFO - Iter [90400/160000] lr: 9.375e-06, eta: 5:55:42, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8473, loss: 0.0798 2023-03-04 04:33:20,780 - mmseg - INFO - Iter [90450/160000] lr: 9.375e-06, eta: 5:55:24, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8825, loss: 0.0786 2023-03-04 04:33:32,872 - mmseg - INFO - Iter [90500/160000] lr: 9.375e-06, eta: 5:55:06, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.8097, loss: 0.0816 2023-03-04 04:33:44,986 - mmseg - INFO - Iter [90550/160000] lr: 9.375e-06, eta: 5:54:48, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8457, loss: 0.0790 2023-03-04 04:33:59,522 - mmseg - INFO - Iter [90600/160000] lr: 9.375e-06, eta: 5:54:32, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8601, loss: 0.0796 2023-03-04 04:34:11,645 - mmseg - INFO - Iter [90650/160000] lr: 9.375e-06, eta: 5:54:15, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8479, loss: 0.0798 2023-03-04 04:34:23,782 - mmseg - INFO - Iter [90700/160000] lr: 9.375e-06, eta: 5:53:57, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9489, loss: 0.0771 2023-03-04 04:34:35,889 - mmseg - INFO - Iter [90750/160000] lr: 9.375e-06, eta: 5:53:39, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7746, loss: 0.0809 2023-03-04 04:34:50,414 - mmseg - INFO - Iter [90800/160000] lr: 9.375e-06, eta: 5:53:23, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7835, loss: 0.0808 2023-03-04 04:35:02,647 - mmseg - INFO - Iter [90850/160000] lr: 9.375e-06, eta: 5:53:06, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9515, loss: 0.0768 2023-03-04 04:35:14,831 - mmseg - INFO - Iter [90900/160000] lr: 9.375e-06, eta: 5:52:48, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7551, loss: 0.0822 2023-03-04 04:35:27,136 - mmseg - INFO - Iter [90950/160000] lr: 9.375e-06, eta: 5:52:30, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8387, loss: 0.0798 2023-03-04 04:35:41,723 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:35:41,723 - mmseg - INFO - Iter [91000/160000] lr: 9.375e-06, eta: 5:52:14, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8154, loss: 0.0805 2023-03-04 04:35:53,828 - mmseg - INFO - Iter [91050/160000] lr: 9.375e-06, eta: 5:51:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8577, loss: 0.0791 2023-03-04 04:36:06,124 - mmseg - INFO - Iter [91100/160000] lr: 9.375e-06, eta: 5:51:39, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8437, loss: 0.0800 2023-03-04 04:36:20,684 - mmseg - INFO - Iter [91150/160000] lr: 9.375e-06, eta: 5:51:23, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7688, loss: 0.0818 2023-03-04 04:36:32,785 - mmseg - INFO - Iter [91200/160000] lr: 9.375e-06, eta: 5:51:05, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8493, loss: 0.0794 2023-03-04 04:36:45,025 - mmseg - INFO - Iter [91250/160000] lr: 9.375e-06, eta: 5:50:48, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8017, loss: 0.0806 2023-03-04 04:36:57,184 - mmseg - INFO - Iter [91300/160000] lr: 9.375e-06, eta: 5:50:30, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9033, loss: 0.0781 2023-03-04 04:37:11,707 - mmseg - INFO - Iter [91350/160000] lr: 9.375e-06, eta: 5:50:14, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8382, loss: 0.0795 2023-03-04 04:37:23,871 - mmseg - INFO - Iter [91400/160000] lr: 9.375e-06, eta: 5:49:57, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7806, loss: 0.0809 2023-03-04 04:37:36,116 - mmseg - INFO - Iter [91450/160000] lr: 9.375e-06, eta: 5:49:39, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9147, loss: 0.0784 2023-03-04 04:37:48,399 - mmseg - INFO - Iter [91500/160000] lr: 9.375e-06, eta: 5:49:21, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8189, loss: 0.0804 2023-03-04 04:38:02,947 - mmseg - INFO - Iter [91550/160000] lr: 9.375e-06, eta: 5:49:06, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8379, loss: 0.0796 2023-03-04 04:38:15,082 - mmseg - INFO - Iter [91600/160000] lr: 9.375e-06, eta: 5:48:48, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8437, loss: 0.0796 2023-03-04 04:38:27,168 - mmseg - INFO - Iter [91650/160000] lr: 9.375e-06, eta: 5:48:30, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9247, loss: 0.0775 2023-03-04 04:38:41,734 - mmseg - INFO - Iter [91700/160000] lr: 9.375e-06, eta: 5:48:14, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8198, loss: 0.0806 2023-03-04 04:38:54,111 - mmseg - INFO - Iter [91750/160000] lr: 9.375e-06, eta: 5:47:57, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7826, loss: 0.0820 2023-03-04 04:39:06,280 - mmseg - INFO - Iter [91800/160000] lr: 9.375e-06, eta: 5:47:39, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8936, loss: 0.0788 2023-03-04 04:39:18,535 - mmseg - INFO - Iter [91850/160000] lr: 9.375e-06, eta: 5:47:22, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6581, loss: 0.0848 2023-03-04 04:39:33,015 - mmseg - INFO - Iter [91900/160000] lr: 9.375e-06, eta: 5:47:06, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9537, loss: 0.0776 2023-03-04 04:39:45,263 - mmseg - INFO - Iter [91950/160000] lr: 9.375e-06, eta: 5:46:48, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9107, loss: 0.0775 2023-03-04 04:39:57,463 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:39:57,463 - mmseg - INFO - Iter [92000/160000] lr: 9.375e-06, eta: 5:46:31, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8925, loss: 0.0796 2023-03-04 04:40:09,695 - mmseg - INFO - Iter [92050/160000] lr: 9.375e-06, eta: 5:46:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8134, loss: 0.0803 2023-03-04 04:40:24,155 - mmseg - INFO - Iter [92100/160000] lr: 9.375e-06, eta: 5:45:57, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8474, loss: 0.0789 2023-03-04 04:40:36,318 - mmseg - INFO - Iter [92150/160000] lr: 9.375e-06, eta: 5:45:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8467, loss: 0.0809 2023-03-04 04:40:48,546 - mmseg - INFO - Iter [92200/160000] lr: 9.375e-06, eta: 5:45:22, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8166, loss: 0.0810 2023-03-04 04:41:00,680 - mmseg - INFO - Iter [92250/160000] lr: 9.375e-06, eta: 5:45:05, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7718, loss: 0.0809 2023-03-04 04:41:15,222 - mmseg - INFO - Iter [92300/160000] lr: 9.375e-06, eta: 5:44:49, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8337, loss: 0.0801 2023-03-04 04:41:27,316 - mmseg - INFO - Iter [92350/160000] lr: 9.375e-06, eta: 5:44:31, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9020, loss: 0.0781 2023-03-04 04:41:39,441 - mmseg - INFO - Iter [92400/160000] lr: 9.375e-06, eta: 5:44:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8199, loss: 0.0795 2023-03-04 04:41:54,040 - mmseg - INFO - Iter [92450/160000] lr: 9.375e-06, eta: 5:43:58, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8720, loss: 0.0803 2023-03-04 04:42:06,348 - mmseg - INFO - Iter [92500/160000] lr: 9.375e-06, eta: 5:43:40, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9168, loss: 0.0787 2023-03-04 04:42:18,599 - mmseg - INFO - Iter [92550/160000] lr: 9.375e-06, eta: 5:43:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8457, loss: 0.0800 2023-03-04 04:42:30,949 - mmseg - INFO - Iter [92600/160000] lr: 9.375e-06, eta: 5:43:05, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8774, loss: 0.0783 2023-03-04 04:42:45,500 - mmseg - INFO - Iter [92650/160000] lr: 9.375e-06, eta: 5:42:50, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8394, loss: 0.0801 2023-03-04 04:42:57,698 - mmseg - INFO - Iter [92700/160000] lr: 9.375e-06, eta: 5:42:32, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7777, loss: 0.0817 2023-03-04 04:43:09,859 - mmseg - INFO - Iter [92750/160000] lr: 9.375e-06, eta: 5:42:15, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7259, loss: 0.0822 2023-03-04 04:43:22,114 - mmseg - INFO - Iter [92800/160000] lr: 9.375e-06, eta: 5:41:57, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9125, loss: 0.0779 2023-03-04 04:43:36,652 - mmseg - INFO - Iter [92850/160000] lr: 9.375e-06, eta: 5:41:41, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7757, loss: 0.0817 2023-03-04 04:43:48,931 - mmseg - INFO - Iter [92900/160000] lr: 9.375e-06, eta: 5:41:24, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8763, loss: 0.0792 2023-03-04 04:44:01,135 - mmseg - INFO - Iter [92950/160000] lr: 9.375e-06, eta: 5:41:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.6977, loss: 0.0832 2023-03-04 04:44:13,374 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:44:13,374 - mmseg - INFO - Iter [93000/160000] lr: 9.375e-06, eta: 5:40:49, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8992, loss: 0.0787 2023-03-04 04:44:27,844 - mmseg - INFO - Iter [93050/160000] lr: 9.375e-06, eta: 5:40:33, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8459, loss: 0.0788 2023-03-04 04:44:39,978 - mmseg - INFO - Iter [93100/160000] lr: 9.375e-06, eta: 5:40:16, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8443, loss: 0.0799 2023-03-04 04:44:52,244 - mmseg - INFO - Iter [93150/160000] lr: 9.375e-06, eta: 5:39:58, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7890, loss: 0.0808 2023-03-04 04:45:06,843 - mmseg - INFO - Iter [93200/160000] lr: 9.375e-06, eta: 5:39:43, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8877, loss: 0.0791 2023-03-04 04:45:19,014 - mmseg - INFO - Iter [93250/160000] lr: 9.375e-06, eta: 5:39:25, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7291, loss: 0.0827 2023-03-04 04:45:31,364 - mmseg - INFO - Iter [93300/160000] lr: 9.375e-06, eta: 5:39:08, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9244, loss: 0.0776 2023-03-04 04:45:43,580 - mmseg - INFO - Iter [93350/160000] lr: 9.375e-06, eta: 5:38:50, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8500, loss: 0.0798 2023-03-04 04:45:58,206 - mmseg - INFO - Iter [93400/160000] lr: 9.375e-06, eta: 5:38:35, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.7847, loss: 0.0804 2023-03-04 04:46:10,435 - mmseg - INFO - Iter [93450/160000] lr: 9.375e-06, eta: 5:38:17, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9147, loss: 0.0778 2023-03-04 04:46:22,615 - mmseg - INFO - Iter [93500/160000] lr: 9.375e-06, eta: 5:38:00, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7820, loss: 0.0809 2023-03-04 04:46:34,840 - mmseg - INFO - Iter [93550/160000] lr: 9.375e-06, eta: 5:37:42, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8947, loss: 0.0784 2023-03-04 04:46:49,434 - mmseg - INFO - Iter [93600/160000] lr: 9.375e-06, eta: 5:37:27, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9288, loss: 0.0775 2023-03-04 04:47:01,531 - mmseg - INFO - Iter [93650/160000] lr: 9.375e-06, eta: 5:37:09, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8374, loss: 0.0798 2023-03-04 04:47:13,764 - mmseg - INFO - Iter [93700/160000] lr: 9.375e-06, eta: 5:36:52, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8743, loss: 0.0790 2023-03-04 04:47:28,335 - mmseg - INFO - Iter [93750/160000] lr: 9.375e-06, eta: 5:36:36, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9218, loss: 0.0777 2023-03-04 04:47:40,745 - mmseg - INFO - Iter [93800/160000] lr: 9.375e-06, eta: 5:36:19, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.9177, loss: 0.0789 2023-03-04 04:47:52,933 - mmseg - INFO - Iter [93850/160000] lr: 9.375e-06, eta: 5:36:01, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8314, loss: 0.0799 2023-03-04 04:48:05,125 - mmseg - INFO - Iter [93900/160000] lr: 9.375e-06, eta: 5:35:44, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8290, loss: 0.0801 2023-03-04 04:48:19,611 - mmseg - INFO - Iter [93950/160000] lr: 9.375e-06, eta: 5:35:28, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7607, loss: 0.0817 2023-03-04 04:48:31,894 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:48:31,894 - mmseg - INFO - Iter [94000/160000] lr: 9.375e-06, eta: 5:35:11, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7581, loss: 0.0815 2023-03-04 04:48:44,151 - mmseg - INFO - Iter [94050/160000] lr: 9.375e-06, eta: 5:34:54, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9326, loss: 0.0782 2023-03-04 04:48:56,321 - mmseg - INFO - Iter [94100/160000] lr: 9.375e-06, eta: 5:34:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9180, loss: 0.0771 2023-03-04 04:49:11,012 - mmseg - INFO - Iter [94150/160000] lr: 9.375e-06, eta: 5:34:21, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8663, loss: 0.0794 2023-03-04 04:49:23,147 - mmseg - INFO - Iter [94200/160000] lr: 9.375e-06, eta: 5:34:03, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9744, loss: 0.0767 2023-03-04 04:49:35,432 - mmseg - INFO - Iter [94250/160000] lr: 9.375e-06, eta: 5:33:46, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7602, loss: 0.0805 2023-03-04 04:49:47,639 - mmseg - INFO - Iter [94300/160000] lr: 9.375e-06, eta: 5:33:29, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9196, loss: 0.0775 2023-03-04 04:50:02,324 - mmseg - INFO - Iter [94350/160000] lr: 9.375e-06, eta: 5:33:13, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8255, loss: 0.0801 2023-03-04 04:50:14,577 - mmseg - INFO - Iter [94400/160000] lr: 9.375e-06, eta: 5:32:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9033, loss: 0.0777 2023-03-04 04:50:26,716 - mmseg - INFO - Iter [94450/160000] lr: 9.375e-06, eta: 5:32:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8374, loss: 0.0811 2023-03-04 04:50:41,171 - mmseg - INFO - Iter [94500/160000] lr: 9.375e-06, eta: 5:32:23, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8102, loss: 0.0804 2023-03-04 04:50:53,403 - mmseg - INFO - Iter [94550/160000] lr: 9.375e-06, eta: 5:32:05, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8768, loss: 0.0790 2023-03-04 04:51:05,541 - mmseg - INFO - Iter [94600/160000] lr: 9.375e-06, eta: 5:31:48, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8747, loss: 0.0788 2023-03-04 04:51:17,765 - mmseg - INFO - Iter [94650/160000] lr: 9.375e-06, eta: 5:31:31, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0745, decode.acc_seg: 97.0603, loss: 0.0745 2023-03-04 04:51:32,361 - mmseg - INFO - Iter [94700/160000] lr: 9.375e-06, eta: 5:31:15, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9387, loss: 0.0776 2023-03-04 04:51:44,470 - mmseg - INFO - Iter [94750/160000] lr: 9.375e-06, eta: 5:30:58, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9517, loss: 0.0774 2023-03-04 04:51:56,536 - mmseg - INFO - Iter [94800/160000] lr: 9.375e-06, eta: 5:30:40, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9221, loss: 0.0773 2023-03-04 04:52:08,727 - mmseg - INFO - Iter [94850/160000] lr: 9.375e-06, eta: 5:30:23, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7926, loss: 0.0813 2023-03-04 04:52:23,357 - mmseg - INFO - Iter [94900/160000] lr: 9.375e-06, eta: 5:30:07, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9371, loss: 0.0773 2023-03-04 04:52:35,423 - mmseg - INFO - Iter [94950/160000] lr: 9.375e-06, eta: 5:29:50, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.7937, loss: 0.0800 2023-03-04 04:52:47,782 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:52:47,783 - mmseg - INFO - Iter [95000/160000] lr: 9.375e-06, eta: 5:29:33, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9259, loss: 0.0770 2023-03-04 04:53:02,209 - mmseg - INFO - Iter [95050/160000] lr: 9.375e-06, eta: 5:29:17, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9351, loss: 0.0778 2023-03-04 04:53:14,368 - mmseg - INFO - Iter [95100/160000] lr: 9.375e-06, eta: 5:29:00, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8181, loss: 0.0815 2023-03-04 04:53:26,518 - mmseg - INFO - Iter [95150/160000] lr: 9.375e-06, eta: 5:28:43, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0846, decode.acc_seg: 96.6810, loss: 0.0846 2023-03-04 04:53:38,673 - mmseg - INFO - Iter [95200/160000] lr: 9.375e-06, eta: 5:28:25, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.8144, loss: 0.0817 2023-03-04 04:53:53,248 - mmseg - INFO - Iter [95250/160000] lr: 9.375e-06, eta: 5:28:10, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7260, loss: 0.0822 2023-03-04 04:54:05,656 - mmseg - INFO - Iter [95300/160000] lr: 9.375e-06, eta: 5:27:53, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8868, loss: 0.0787 2023-03-04 04:54:17,902 - mmseg - INFO - Iter [95350/160000] lr: 9.375e-06, eta: 5:27:35, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7892, loss: 0.0824 2023-03-04 04:54:30,085 - mmseg - INFO - Iter [95400/160000] lr: 9.375e-06, eta: 5:27:18, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.6877, loss: 0.0844 2023-03-04 04:54:44,747 - mmseg - INFO - Iter [95450/160000] lr: 9.375e-06, eta: 5:27:03, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8685, loss: 0.0794 2023-03-04 04:54:56,883 - mmseg - INFO - Iter [95500/160000] lr: 9.375e-06, eta: 5:26:45, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8624, loss: 0.0789 2023-03-04 04:55:08,945 - mmseg - INFO - Iter [95550/160000] lr: 9.375e-06, eta: 5:26:28, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8640, loss: 0.0780 2023-03-04 04:55:21,296 - mmseg - INFO - Iter [95600/160000] lr: 9.375e-06, eta: 5:26:11, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8144, loss: 0.0805 2023-03-04 04:55:35,790 - mmseg - INFO - Iter [95650/160000] lr: 9.375e-06, eta: 5:25:55, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7998, loss: 0.0824 2023-03-04 04:55:48,052 - mmseg - INFO - Iter [95700/160000] lr: 9.375e-06, eta: 5:25:38, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9839, loss: 0.0756 2023-03-04 04:56:00,296 - mmseg - INFO - Iter [95750/160000] lr: 9.375e-06, eta: 5:25:21, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7944, loss: 0.0815 2023-03-04 04:56:14,837 - mmseg - INFO - Iter [95800/160000] lr: 9.375e-06, eta: 5:25:05, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9377, loss: 0.0774 2023-03-04 04:56:27,226 - mmseg - INFO - Iter [95850/160000] lr: 9.375e-06, eta: 5:24:48, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8707, loss: 0.0797 2023-03-04 04:56:39,428 - mmseg - INFO - Iter [95900/160000] lr: 9.375e-06, eta: 5:24:31, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.7254, loss: 0.0839 2023-03-04 04:56:51,660 - mmseg - INFO - Iter [95950/160000] lr: 9.375e-06, eta: 5:24:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8437, loss: 0.0806 2023-03-04 04:57:06,224 - mmseg - INFO - Swap parameters (after train) after iter [96000] 2023-03-04 04:57:06,239 - mmseg - INFO - Saving checkpoint at 96000 iterations 2023-03-04 04:57:07,619 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 04:57:07,619 - mmseg - INFO - Iter [96000/160000] lr: 9.375e-06, eta: 5:23:59, time: 0.319, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8454, loss: 0.0785 2023-03-04 05:11:59,955 - mmseg - INFO - per class results: 2023-03-04 05:11:59,957 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.58,98.58,98.58,98.59,98.59,98.6,98.59,98.61,98.61,98.6,98.6 | | sidewalk | 87.76,87.79,87.82,87.86,87.89,87.91,87.9,87.98,88.0,87.98,87.98 | | building | 93.33,93.33,93.33,93.34,93.34,93.34,93.34,93.35,93.35,93.35,93.35 | | wall | 54.22,54.29,54.35,54.59,54.69,54.8,54.89,55.06,55.13,55.24,55.18 | | fence | 63.73,63.75,63.74,63.81,63.82,63.81,63.8,63.84,63.84,63.79,63.87 | | pole | 71.05,71.04,71.08,71.08,71.06,71.06,71.07,71.05,71.05,71.06,71.05 | | traffic light | 75.53,75.51,75.52,75.52,75.5,75.5,75.51,75.49,75.51,75.5,75.5 | | traffic sign | 83.28,83.29,83.3,83.31,83.31,83.32,83.34,83.33,83.34,83.35,83.35 | | vegetation | 92.95,92.95,92.95,92.96,92.96,92.96,92.96,92.96,92.96,92.96,92.97 | | terrain | 65.72,65.82,65.78,65.9,66.02,66.01,66.07,66.13,66.15,66.24,66.34 | | sky | 95.25,95.25,95.25,95.25,95.25,95.26,95.25,95.24,95.25,95.25,95.24 | | person | 84.86,84.86,84.87,84.88,84.87,84.87,84.88,84.87,84.86,84.88,84.87 | | rider | 67.71,67.72,67.72,67.73,67.74,67.72,67.75,67.77,67.72,67.73,67.7 | | car | 95.97,95.99,96.0,96.01,96.01,96.02,96.03,96.03,96.04,96.04,96.03 | | truck | 85.18,85.56,85.86,86.19,86.16,86.52,86.64,86.66,86.63,86.66,86.74 | | bus | 92.21,92.25,92.25,92.24,92.25,92.29,92.3,92.3,92.32,92.32,92.28 | | train | 85.83,85.84,85.84,85.85,85.88,85.84,85.86,85.81,85.86,85.92,85.82 | | motorcycle | 69.67,69.65,69.66,69.63,69.68,69.66,69.64,69.67,69.69,69.67,69.68 | | bicycle | 79.89,79.89,79.9,79.9,79.92,79.91,79.92,79.92,79.94,79.94,79.94 | +---------------+-------------------------------------------------------------------+ 2023-03-04 05:11:59,957 - mmseg - INFO - Summary: 2023-03-04 05:11:59,957 - mmseg - INFO - +-----------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +-----------------------------------------------------------------+ | 81.2,81.23,81.25,81.3,81.31,81.34,81.36,81.37,81.38,81.39,81.39 | +-----------------------------------------------------------------+ 2023-03-04 05:12:00,002 - mmseg - INFO - The previous best checkpoint /mnt/petrelfs/laizeqiang/mmseg-baseline/work_dirs2/deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune/best_mIoU_iter_80000.pth was removed 2023-03-04 05:12:01,421 - mmseg - INFO - Now best checkpoint is saved as best_mIoU_iter_96000.pth. 2023-03-04 05:12:01,422 - mmseg - INFO - Best mIoU is 0.8139 at 96000 iter. 2023-03-04 05:12:01,422 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:12:01,422 - mmseg - INFO - Iter(val) [63] mIoU: [0.812, 0.8123, 0.8125, 0.813, 0.8131, 0.8134, 0.8136, 0.8137, 0.8138, 0.8139, 0.8139], copy_paste: 81.2,81.23,81.25,81.3,81.31,81.34,81.36,81.37,81.38,81.39,81.39 2023-03-04 05:12:01,428 - mmseg - INFO - Swap parameters (before train) before iter [96001] 2023-03-04 05:12:13,848 - mmseg - INFO - Iter [96050/160000] lr: 9.375e-06, eta: 5:33:37, time: 18.125, data_time: 17.885, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8689, loss: 0.0793 2023-03-04 05:12:26,177 - mmseg - INFO - Iter [96100/160000] lr: 9.375e-06, eta: 5:33:19, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7810, loss: 0.0819 2023-03-04 05:12:38,455 - mmseg - INFO - Iter [96150/160000] lr: 9.375e-06, eta: 5:33:01, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8303, loss: 0.0803 2023-03-04 05:12:53,145 - mmseg - INFO - Iter [96200/160000] lr: 9.375e-06, eta: 5:32:45, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7554, loss: 0.0816 2023-03-04 05:13:05,535 - mmseg - INFO - Iter [96250/160000] lr: 9.375e-06, eta: 5:32:27, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8930, loss: 0.0778 2023-03-04 05:13:17,952 - mmseg - INFO - Iter [96300/160000] lr: 9.375e-06, eta: 5:32:10, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8214, loss: 0.0802 2023-03-04 05:13:32,573 - mmseg - INFO - Iter [96350/160000] lr: 9.375e-06, eta: 5:31:53, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8305, loss: 0.0795 2023-03-04 05:13:44,867 - mmseg - INFO - Iter [96400/160000] lr: 9.375e-06, eta: 5:31:35, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7445, loss: 0.0817 2023-03-04 05:13:57,155 - mmseg - INFO - Iter [96450/160000] lr: 9.375e-06, eta: 5:31:18, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9008, loss: 0.0786 2023-03-04 05:14:09,505 - mmseg - INFO - Iter [96500/160000] lr: 9.375e-06, eta: 5:31:00, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8789, loss: 0.0789 2023-03-04 05:14:24,174 - mmseg - INFO - Iter [96550/160000] lr: 9.375e-06, eta: 5:30:43, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8894, loss: 0.0779 2023-03-04 05:14:36,409 - mmseg - INFO - Iter [96600/160000] lr: 9.375e-06, eta: 5:30:26, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7704, loss: 0.0828 2023-03-04 05:14:48,817 - mmseg - INFO - Iter [96650/160000] lr: 9.375e-06, eta: 5:30:08, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9106, loss: 0.0783 2023-03-04 05:15:01,111 - mmseg - INFO - Iter [96700/160000] lr: 9.375e-06, eta: 5:29:50, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8885, loss: 0.0783 2023-03-04 05:15:15,730 - mmseg - INFO - Iter [96750/160000] lr: 9.375e-06, eta: 5:29:34, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8994, loss: 0.0795 2023-03-04 05:15:27,900 - mmseg - INFO - Iter [96800/160000] lr: 9.375e-06, eta: 5:29:16, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7732, loss: 0.0817 2023-03-04 05:15:40,067 - mmseg - INFO - Iter [96850/160000] lr: 9.375e-06, eta: 5:28:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9214, loss: 0.0778 2023-03-04 05:15:52,323 - mmseg - INFO - Iter [96900/160000] lr: 9.375e-06, eta: 5:28:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8860, loss: 0.0781 2023-03-04 05:16:06,914 - mmseg - INFO - Iter [96950/160000] lr: 9.375e-06, eta: 5:28:24, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8990, loss: 0.0787 2023-03-04 05:16:19,103 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:16:19,104 - mmseg - INFO - Iter [97000/160000] lr: 9.375e-06, eta: 5:28:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8287, loss: 0.0801 2023-03-04 05:16:31,291 - mmseg - INFO - Iter [97050/160000] lr: 9.375e-06, eta: 5:27:48, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8811, loss: 0.0785 2023-03-04 05:16:46,008 - mmseg - INFO - Iter [97100/160000] lr: 9.375e-06, eta: 5:27:32, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9019, loss: 0.0784 2023-03-04 05:16:58,225 - mmseg - INFO - Iter [97150/160000] lr: 9.375e-06, eta: 5:27:14, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8609, loss: 0.0798 2023-03-04 05:17:10,496 - mmseg - INFO - Iter [97200/160000] lr: 9.375e-06, eta: 5:26:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8278, loss: 0.0802 2023-03-04 05:17:22,642 - mmseg - INFO - Iter [97250/160000] lr: 9.375e-06, eta: 5:26:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8002, loss: 0.0811 2023-03-04 05:17:37,114 - mmseg - INFO - Iter [97300/160000] lr: 9.375e-06, eta: 5:26:22, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8613, loss: 0.0799 2023-03-04 05:17:49,232 - mmseg - INFO - Iter [97350/160000] lr: 9.375e-06, eta: 5:26:04, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8685, loss: 0.0802 2023-03-04 05:18:01,410 - mmseg - INFO - Iter [97400/160000] lr: 9.375e-06, eta: 5:25:46, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8220, loss: 0.0806 2023-03-04 05:18:13,716 - mmseg - INFO - Iter [97450/160000] lr: 9.375e-06, eta: 5:25:29, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7512, loss: 0.0814 2023-03-04 05:18:28,257 - mmseg - INFO - Iter [97500/160000] lr: 9.375e-06, eta: 5:25:12, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8432, loss: 0.0801 2023-03-04 05:18:40,628 - mmseg - INFO - Iter [97550/160000] lr: 9.375e-06, eta: 5:24:55, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7879, loss: 0.0816 2023-03-04 05:18:52,821 - mmseg - INFO - Iter [97600/160000] lr: 9.375e-06, eta: 5:24:37, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9035, loss: 0.0780 2023-03-04 05:19:05,054 - mmseg - INFO - Iter [97650/160000] lr: 9.375e-06, eta: 5:24:19, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.8179, loss: 0.0818 2023-03-04 05:19:19,733 - mmseg - INFO - Iter [97700/160000] lr: 9.375e-06, eta: 5:24:03, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9366, loss: 0.0777 2023-03-04 05:19:32,095 - mmseg - INFO - Iter [97750/160000] lr: 9.375e-06, eta: 5:23:45, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8509, loss: 0.0792 2023-03-04 05:19:44,261 - mmseg - INFO - Iter [97800/160000] lr: 9.375e-06, eta: 5:23:27, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8159, loss: 0.0805 2023-03-04 05:19:58,757 - mmseg - INFO - Iter [97850/160000] lr: 9.375e-06, eta: 5:23:11, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8638, loss: 0.0792 2023-03-04 05:20:11,052 - mmseg - INFO - Iter [97900/160000] lr: 9.375e-06, eta: 5:22:53, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8389, loss: 0.0796 2023-03-04 05:20:23,359 - mmseg - INFO - Iter [97950/160000] lr: 9.375e-06, eta: 5:22:36, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8399, loss: 0.0807 2023-03-04 05:20:35,663 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:20:35,663 - mmseg - INFO - Iter [98000/160000] lr: 9.375e-06, eta: 5:22:18, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8800, loss: 0.0783 2023-03-04 05:20:50,223 - mmseg - INFO - Iter [98050/160000] lr: 9.375e-06, eta: 5:22:02, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8033, loss: 0.0810 2023-03-04 05:21:02,451 - mmseg - INFO - Iter [98100/160000] lr: 9.375e-06, eta: 5:21:44, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9110, loss: 0.0771 2023-03-04 05:21:14,698 - mmseg - INFO - Iter [98150/160000] lr: 9.375e-06, eta: 5:21:26, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.9060, loss: 0.0790 2023-03-04 05:21:26,788 - mmseg - INFO - Iter [98200/160000] lr: 9.375e-06, eta: 5:21:09, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9094, loss: 0.0783 2023-03-04 05:21:41,403 - mmseg - INFO - Iter [98250/160000] lr: 9.375e-06, eta: 5:20:52, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8419, loss: 0.0800 2023-03-04 05:21:53,565 - mmseg - INFO - Iter [98300/160000] lr: 9.375e-06, eta: 5:20:35, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8518, loss: 0.0793 2023-03-04 05:22:05,681 - mmseg - INFO - Iter [98350/160000] lr: 9.375e-06, eta: 5:20:17, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8148, loss: 0.0802 2023-03-04 05:22:20,186 - mmseg - INFO - Iter [98400/160000] lr: 9.375e-06, eta: 5:20:01, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8778, loss: 0.0787 2023-03-04 05:22:32,356 - mmseg - INFO - Iter [98450/160000] lr: 9.375e-06, eta: 5:19:43, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7521, loss: 0.0824 2023-03-04 05:22:44,475 - mmseg - INFO - Iter [98500/160000] lr: 9.375e-06, eta: 5:19:25, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.7210, loss: 0.0844 2023-03-04 05:22:56,742 - mmseg - INFO - Iter [98550/160000] lr: 9.375e-06, eta: 5:19:08, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9629, loss: 0.0761 2023-03-04 05:23:11,286 - mmseg - INFO - Iter [98600/160000] lr: 9.375e-06, eta: 5:18:51, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9417, loss: 0.0771 2023-03-04 05:23:23,410 - mmseg - INFO - Iter [98650/160000] lr: 9.375e-06, eta: 5:18:34, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8190, loss: 0.0804 2023-03-04 05:23:35,611 - mmseg - INFO - Iter [98700/160000] lr: 9.375e-06, eta: 5:18:16, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8937, loss: 0.0784 2023-03-04 05:23:47,778 - mmseg - INFO - Iter [98750/160000] lr: 9.375e-06, eta: 5:17:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8065, loss: 0.0803 2023-03-04 05:24:02,194 - mmseg - INFO - Iter [98800/160000] lr: 9.375e-06, eta: 5:17:42, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8578, loss: 0.0785 2023-03-04 05:24:14,361 - mmseg - INFO - Iter [98850/160000] lr: 9.375e-06, eta: 5:17:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7795, loss: 0.0814 2023-03-04 05:24:26,609 - mmseg - INFO - Iter [98900/160000] lr: 9.375e-06, eta: 5:17:07, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7927, loss: 0.0818 2023-03-04 05:24:38,788 - mmseg - INFO - Iter [98950/160000] lr: 9.375e-06, eta: 5:16:49, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8850, loss: 0.0782 2023-03-04 05:24:53,388 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:24:53,389 - mmseg - INFO - Iter [99000/160000] lr: 9.375e-06, eta: 5:16:33, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9387, loss: 0.0772 2023-03-04 05:25:05,597 - mmseg - INFO - Iter [99050/160000] lr: 9.375e-06, eta: 5:16:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9311, loss: 0.0762 2023-03-04 05:25:17,794 - mmseg - INFO - Iter [99100/160000] lr: 9.375e-06, eta: 5:15:57, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9319, loss: 0.0773 2023-03-04 05:25:32,381 - mmseg - INFO - Iter [99150/160000] lr: 9.375e-06, eta: 5:15:41, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8511, loss: 0.0794 2023-03-04 05:25:44,540 - mmseg - INFO - Iter [99200/160000] lr: 9.375e-06, eta: 5:15:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8798, loss: 0.0796 2023-03-04 05:25:56,747 - mmseg - INFO - Iter [99250/160000] lr: 9.375e-06, eta: 5:15:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9055, loss: 0.0777 2023-03-04 05:26:08,884 - mmseg - INFO - Iter [99300/160000] lr: 9.375e-06, eta: 5:14:48, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8749, loss: 0.0792 2023-03-04 05:26:23,409 - mmseg - INFO - Iter [99350/160000] lr: 9.375e-06, eta: 5:14:32, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9068, loss: 0.0782 2023-03-04 05:26:35,573 - mmseg - INFO - Iter [99400/160000] lr: 9.375e-06, eta: 5:14:15, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8331, loss: 0.0805 2023-03-04 05:26:47,675 - mmseg - INFO - Iter [99450/160000] lr: 9.375e-06, eta: 5:13:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8345, loss: 0.0795 2023-03-04 05:26:59,927 - mmseg - INFO - Iter [99500/160000] lr: 9.375e-06, eta: 5:13:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7727, loss: 0.0806 2023-03-04 05:27:14,464 - mmseg - INFO - Iter [99550/160000] lr: 9.375e-06, eta: 5:13:23, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0748, decode.acc_seg: 97.0445, loss: 0.0748 2023-03-04 05:27:26,724 - mmseg - INFO - Iter [99600/160000] lr: 9.375e-06, eta: 5:13:06, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9236, loss: 0.0775 2023-03-04 05:27:38,853 - mmseg - INFO - Iter [99650/160000] lr: 9.375e-06, eta: 5:12:48, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9118, loss: 0.0780 2023-03-04 05:27:53,360 - mmseg - INFO - Iter [99700/160000] lr: 9.375e-06, eta: 5:12:32, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7858, loss: 0.0812 2023-03-04 05:28:05,675 - mmseg - INFO - Iter [99750/160000] lr: 9.375e-06, eta: 5:12:14, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9267, loss: 0.0783 2023-03-04 05:28:18,087 - mmseg - INFO - Iter [99800/160000] lr: 9.375e-06, eta: 5:11:57, time: 0.248, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9561, loss: 0.0766 2023-03-04 05:28:30,270 - mmseg - INFO - Iter [99850/160000] lr: 9.375e-06, eta: 5:11:39, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7771, loss: 0.0816 2023-03-04 05:28:44,739 - mmseg - INFO - Iter [99900/160000] lr: 9.375e-06, eta: 5:11:23, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8870, loss: 0.0788 2023-03-04 05:28:56,928 - mmseg - INFO - Iter [99950/160000] lr: 9.375e-06, eta: 5:11:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7850, loss: 0.0813 2023-03-04 05:29:09,039 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:29:09,039 - mmseg - INFO - Iter [100000/160000] lr: 9.375e-06, eta: 5:10:48, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9197, loss: 0.0777 2023-03-04 05:29:21,229 - mmseg - INFO - Iter [100050/160000] lr: 4.687e-06, eta: 5:10:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9448, loss: 0.0771 2023-03-04 05:29:35,788 - mmseg - INFO - Iter [100100/160000] lr: 4.687e-06, eta: 5:10:14, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7686, loss: 0.0822 2023-03-04 05:29:48,011 - mmseg - INFO - Iter [100150/160000] lr: 4.687e-06, eta: 5:09:57, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8817, loss: 0.0789 2023-03-04 05:30:00,245 - mmseg - INFO - Iter [100200/160000] lr: 4.687e-06, eta: 5:09:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8752, loss: 0.0792 2023-03-04 05:30:12,366 - mmseg - INFO - Iter [100250/160000] lr: 4.687e-06, eta: 5:09:22, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8335, loss: 0.0802 2023-03-04 05:30:26,927 - mmseg - INFO - Iter [100300/160000] lr: 4.687e-06, eta: 5:09:06, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.6758, loss: 0.0838 2023-03-04 05:30:39,185 - mmseg - INFO - Iter [100350/160000] lr: 4.687e-06, eta: 5:08:48, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8654, loss: 0.0779 2023-03-04 05:30:51,345 - mmseg - INFO - Iter [100400/160000] lr: 4.687e-06, eta: 5:08:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7925, loss: 0.0806 2023-03-04 05:31:05,943 - mmseg - INFO - Iter [100450/160000] lr: 4.687e-06, eta: 5:08:14, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.9000, loss: 0.0790 2023-03-04 05:31:18,152 - mmseg - INFO - Iter [100500/160000] lr: 4.687e-06, eta: 5:07:57, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9920, loss: 0.0766 2023-03-04 05:31:30,383 - mmseg - INFO - Iter [100550/160000] lr: 4.687e-06, eta: 5:07:40, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0740, decode.acc_seg: 97.0713, loss: 0.0740 2023-03-04 05:31:42,785 - mmseg - INFO - Iter [100600/160000] lr: 4.687e-06, eta: 5:07:22, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7799, loss: 0.0815 2023-03-04 05:31:57,253 - mmseg - INFO - Iter [100650/160000] lr: 4.687e-06, eta: 5:07:06, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7553, loss: 0.0815 2023-03-04 05:32:09,550 - mmseg - INFO - Iter [100700/160000] lr: 4.687e-06, eta: 5:06:49, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9085, loss: 0.0783 2023-03-04 05:32:21,704 - mmseg - INFO - Iter [100750/160000] lr: 4.687e-06, eta: 5:06:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8088, loss: 0.0815 2023-03-04 05:32:34,171 - mmseg - INFO - Iter [100800/160000] lr: 4.687e-06, eta: 5:06:14, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9127, loss: 0.0773 2023-03-04 05:32:48,824 - mmseg - INFO - Iter [100850/160000] lr: 4.687e-06, eta: 5:05:58, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7849, loss: 0.0831 2023-03-04 05:33:01,104 - mmseg - INFO - Iter [100900/160000] lr: 4.687e-06, eta: 5:05:40, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8936, loss: 0.0784 2023-03-04 05:33:13,387 - mmseg - INFO - Iter [100950/160000] lr: 4.687e-06, eta: 5:05:23, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 97.0148, loss: 0.0766 2023-03-04 05:33:27,829 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:33:27,829 - mmseg - INFO - Iter [101000/160000] lr: 4.687e-06, eta: 5:05:07, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8120, loss: 0.0813 2023-03-04 05:33:40,051 - mmseg - INFO - Iter [101050/160000] lr: 4.687e-06, eta: 5:04:49, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8204, loss: 0.0809 2023-03-04 05:33:52,375 - mmseg - INFO - Iter [101100/160000] lr: 4.687e-06, eta: 5:04:32, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8957, loss: 0.0784 2023-03-04 05:34:04,796 - mmseg - INFO - Iter [101150/160000] lr: 4.687e-06, eta: 5:04:15, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8414, loss: 0.0796 2023-03-04 05:34:19,361 - mmseg - INFO - Iter [101200/160000] lr: 4.687e-06, eta: 5:03:59, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9049, loss: 0.0777 2023-03-04 05:34:31,602 - mmseg - INFO - Iter [101250/160000] lr: 4.687e-06, eta: 5:03:41, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7066, loss: 0.0833 2023-03-04 05:34:43,763 - mmseg - INFO - Iter [101300/160000] lr: 4.687e-06, eta: 5:03:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8071, loss: 0.0800 2023-03-04 05:34:56,044 - mmseg - INFO - Iter [101350/160000] lr: 4.687e-06, eta: 5:03:06, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6829, loss: 0.0847 2023-03-04 05:35:10,708 - mmseg - INFO - Iter [101400/160000] lr: 4.687e-06, eta: 5:02:50, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7412, loss: 0.0813 2023-03-04 05:35:22,895 - mmseg - INFO - Iter [101450/160000] lr: 4.687e-06, eta: 5:02:33, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8298, loss: 0.0807 2023-03-04 05:35:35,099 - mmseg - INFO - Iter [101500/160000] lr: 4.687e-06, eta: 5:02:16, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7965, loss: 0.0812 2023-03-04 05:35:47,386 - mmseg - INFO - Iter [101550/160000] lr: 4.687e-06, eta: 5:01:58, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8565, loss: 0.0802 2023-03-04 05:36:01,945 - mmseg - INFO - Iter [101600/160000] lr: 4.687e-06, eta: 5:01:42, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8414, loss: 0.0798 2023-03-04 05:36:14,284 - mmseg - INFO - Iter [101650/160000] lr: 4.687e-06, eta: 5:01:25, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8769, loss: 0.0806 2023-03-04 05:36:26,500 - mmseg - INFO - Iter [101700/160000] lr: 4.687e-06, eta: 5:01:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9349, loss: 0.0763 2023-03-04 05:36:41,113 - mmseg - INFO - Iter [101750/160000] lr: 4.687e-06, eta: 5:00:51, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8689, loss: 0.0791 2023-03-04 05:36:53,374 - mmseg - INFO - Iter [101800/160000] lr: 4.687e-06, eta: 5:00:34, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8647, loss: 0.0797 2023-03-04 05:37:05,650 - mmseg - INFO - Iter [101850/160000] lr: 4.687e-06, eta: 5:00:17, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8027, loss: 0.0810 2023-03-04 05:37:18,128 - mmseg - INFO - Iter [101900/160000] lr: 4.687e-06, eta: 5:00:00, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9801, loss: 0.0768 2023-03-04 05:37:32,677 - mmseg - INFO - Iter [101950/160000] lr: 4.687e-06, eta: 4:59:44, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7697, loss: 0.0821 2023-03-04 05:37:44,872 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:37:44,873 - mmseg - INFO - Iter [102000/160000] lr: 4.687e-06, eta: 4:59:26, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8447, loss: 0.0793 2023-03-04 05:37:57,186 - mmseg - INFO - Iter [102050/160000] lr: 4.687e-06, eta: 4:59:09, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7915, loss: 0.0811 2023-03-04 05:38:09,358 - mmseg - INFO - Iter [102100/160000] lr: 4.687e-06, eta: 4:58:52, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0753, decode.acc_seg: 97.0023, loss: 0.0753 2023-03-04 05:38:23,946 - mmseg - INFO - Iter [102150/160000] lr: 4.687e-06, eta: 4:58:36, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8837, loss: 0.0784 2023-03-04 05:38:36,134 - mmseg - INFO - Iter [102200/160000] lr: 4.687e-06, eta: 4:58:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8115, loss: 0.0805 2023-03-04 05:38:48,377 - mmseg - INFO - Iter [102250/160000] lr: 4.687e-06, eta: 4:58:01, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7515, loss: 0.0821 2023-03-04 05:39:00,531 - mmseg - INFO - Iter [102300/160000] lr: 4.687e-06, eta: 4:57:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9047, loss: 0.0784 2023-03-04 05:39:15,151 - mmseg - INFO - Iter [102350/160000] lr: 4.687e-06, eta: 4:57:28, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8236, loss: 0.0799 2023-03-04 05:39:27,343 - mmseg - INFO - Iter [102400/160000] lr: 4.687e-06, eta: 4:57:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9378, loss: 0.0776 2023-03-04 05:39:39,474 - mmseg - INFO - Iter [102450/160000] lr: 4.687e-06, eta: 4:56:53, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8714, loss: 0.0797 2023-03-04 05:39:54,020 - mmseg - INFO - Iter [102500/160000] lr: 4.687e-06, eta: 4:56:37, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7434, loss: 0.0813 2023-03-04 05:40:06,189 - mmseg - INFO - Iter [102550/160000] lr: 4.687e-06, eta: 4:56:20, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7556, loss: 0.0809 2023-03-04 05:40:18,345 - mmseg - INFO - Iter [102600/160000] lr: 4.687e-06, eta: 4:56:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9209, loss: 0.0773 2023-03-04 05:40:30,533 - mmseg - INFO - Iter [102650/160000] lr: 4.687e-06, eta: 4:55:45, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8479, loss: 0.0803 2023-03-04 05:40:45,109 - mmseg - INFO - Iter [102700/160000] lr: 4.687e-06, eta: 4:55:29, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8516, loss: 0.0794 2023-03-04 05:40:57,296 - mmseg - INFO - Iter [102750/160000] lr: 4.687e-06, eta: 4:55:12, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8259, loss: 0.0799 2023-03-04 05:41:09,525 - mmseg - INFO - Iter [102800/160000] lr: 4.687e-06, eta: 4:54:54, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8329, loss: 0.0792 2023-03-04 05:41:21,658 - mmseg - INFO - Iter [102850/160000] lr: 4.687e-06, eta: 4:54:37, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8699, loss: 0.0790 2023-03-04 05:41:36,382 - mmseg - INFO - Iter [102900/160000] lr: 4.687e-06, eta: 4:54:21, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7621, loss: 0.0817 2023-03-04 05:41:48,691 - mmseg - INFO - Iter [102950/160000] lr: 4.687e-06, eta: 4:54:04, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9156, loss: 0.0782 2023-03-04 05:42:01,031 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:42:01,031 - mmseg - INFO - Iter [103000/160000] lr: 4.687e-06, eta: 4:53:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7842, loss: 0.0810 2023-03-04 05:42:15,627 - mmseg - INFO - Iter [103050/160000] lr: 4.687e-06, eta: 4:53:31, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8157, loss: 0.0803 2023-03-04 05:42:27,823 - mmseg - INFO - Iter [103100/160000] lr: 4.687e-06, eta: 4:53:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8720, loss: 0.0786 2023-03-04 05:42:40,072 - mmseg - INFO - Iter [103150/160000] lr: 4.687e-06, eta: 4:52:56, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8169, loss: 0.0799 2023-03-04 05:42:52,268 - mmseg - INFO - Iter [103200/160000] lr: 4.687e-06, eta: 4:52:39, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9816, loss: 0.0762 2023-03-04 05:43:06,861 - mmseg - INFO - Iter [103250/160000] lr: 4.687e-06, eta: 4:52:23, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.7435, loss: 0.0829 2023-03-04 05:43:18,980 - mmseg - INFO - Iter [103300/160000] lr: 4.687e-06, eta: 4:52:06, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8988, loss: 0.0790 2023-03-04 05:43:31,205 - mmseg - INFO - Iter [103350/160000] lr: 4.687e-06, eta: 4:51:49, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7489, loss: 0.0808 2023-03-04 05:43:43,338 - mmseg - INFO - Iter [103400/160000] lr: 4.687e-06, eta: 4:51:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9449, loss: 0.0774 2023-03-04 05:43:57,797 - mmseg - INFO - Iter [103450/160000] lr: 4.687e-06, eta: 4:51:15, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8723, loss: 0.0786 2023-03-04 05:44:10,134 - mmseg - INFO - Iter [103500/160000] lr: 4.687e-06, eta: 4:50:58, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8677, loss: 0.0789 2023-03-04 05:44:22,477 - mmseg - INFO - Iter [103550/160000] lr: 4.687e-06, eta: 4:50:41, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.9046, loss: 0.0802 2023-03-04 05:44:34,556 - mmseg - INFO - Iter [103600/160000] lr: 4.687e-06, eta: 4:50:24, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8875, loss: 0.0790 2023-03-04 05:44:49,132 - mmseg - INFO - Iter [103650/160000] lr: 4.687e-06, eta: 4:50:08, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8975, loss: 0.0785 2023-03-04 05:45:01,407 - mmseg - INFO - Iter [103700/160000] lr: 4.687e-06, eta: 4:49:51, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8150, loss: 0.0795 2023-03-04 05:45:13,666 - mmseg - INFO - Iter [103750/160000] lr: 4.687e-06, eta: 4:49:34, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9507, loss: 0.0766 2023-03-04 05:45:28,098 - mmseg - INFO - Iter [103800/160000] lr: 4.687e-06, eta: 4:49:18, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.7981, loss: 0.0799 2023-03-04 05:45:40,251 - mmseg - INFO - Iter [103850/160000] lr: 4.687e-06, eta: 4:49:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7670, loss: 0.0815 2023-03-04 05:45:52,605 - mmseg - INFO - Iter [103900/160000] lr: 4.687e-06, eta: 4:48:43, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.7797, loss: 0.0802 2023-03-04 05:46:04,757 - mmseg - INFO - Iter [103950/160000] lr: 4.687e-06, eta: 4:48:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9122, loss: 0.0780 2023-03-04 05:46:19,169 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:46:19,170 - mmseg - INFO - Iter [104000/160000] lr: 4.687e-06, eta: 4:48:10, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7381, loss: 0.0822 2023-03-04 05:46:31,421 - mmseg - INFO - Iter [104050/160000] lr: 4.687e-06, eta: 4:47:53, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9416, loss: 0.0777 2023-03-04 05:46:43,629 - mmseg - INFO - Iter [104100/160000] lr: 4.687e-06, eta: 4:47:36, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7701, loss: 0.0825 2023-03-04 05:46:55,748 - mmseg - INFO - Iter [104150/160000] lr: 4.687e-06, eta: 4:47:18, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9431, loss: 0.0778 2023-03-04 05:47:10,187 - mmseg - INFO - Iter [104200/160000] lr: 4.687e-06, eta: 4:47:02, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0759, decode.acc_seg: 96.9820, loss: 0.0759 2023-03-04 05:47:22,293 - mmseg - INFO - Iter [104250/160000] lr: 4.687e-06, eta: 4:46:45, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8342, loss: 0.0803 2023-03-04 05:47:34,534 - mmseg - INFO - Iter [104300/160000] lr: 4.687e-06, eta: 4:46:28, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7134, loss: 0.0832 2023-03-04 05:47:49,073 - mmseg - INFO - Iter [104350/160000] lr: 4.687e-06, eta: 4:46:12, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9190, loss: 0.0781 2023-03-04 05:48:01,251 - mmseg - INFO - Iter [104400/160000] lr: 4.687e-06, eta: 4:45:55, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7941, loss: 0.0810 2023-03-04 05:48:13,498 - mmseg - INFO - Iter [104450/160000] lr: 4.687e-06, eta: 4:45:38, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8185, loss: 0.0793 2023-03-04 05:48:25,615 - mmseg - INFO - Iter [104500/160000] lr: 4.687e-06, eta: 4:45:21, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8698, loss: 0.0795 2023-03-04 05:48:40,159 - mmseg - INFO - Iter [104550/160000] lr: 4.687e-06, eta: 4:45:05, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9683, loss: 0.0772 2023-03-04 05:48:52,397 - mmseg - INFO - Iter [104600/160000] lr: 4.687e-06, eta: 4:44:48, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8630, loss: 0.0801 2023-03-04 05:49:04,600 - mmseg - INFO - Iter [104650/160000] lr: 4.687e-06, eta: 4:44:31, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8490, loss: 0.0795 2023-03-04 05:49:16,730 - mmseg - INFO - Iter [104700/160000] lr: 4.687e-06, eta: 4:44:13, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8261, loss: 0.0799 2023-03-04 05:49:31,250 - mmseg - INFO - Iter [104750/160000] lr: 4.687e-06, eta: 4:43:58, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9275, loss: 0.0773 2023-03-04 05:49:43,568 - mmseg - INFO - Iter [104800/160000] lr: 4.687e-06, eta: 4:43:41, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7871, loss: 0.0810 2023-03-04 05:49:55,718 - mmseg - INFO - Iter [104850/160000] lr: 4.687e-06, eta: 4:43:23, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8756, loss: 0.0791 2023-03-04 05:50:07,965 - mmseg - INFO - Iter [104900/160000] lr: 4.687e-06, eta: 4:43:06, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8295, loss: 0.0801 2023-03-04 05:50:22,432 - mmseg - INFO - Iter [104950/160000] lr: 4.687e-06, eta: 4:42:50, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8127, loss: 0.0805 2023-03-04 05:50:34,655 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:50:34,655 - mmseg - INFO - Iter [105000/160000] lr: 4.687e-06, eta: 4:42:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8442, loss: 0.0789 2023-03-04 05:50:46,815 - mmseg - INFO - Iter [105050/160000] lr: 4.687e-06, eta: 4:42:16, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8179, loss: 0.0799 2023-03-04 05:51:01,466 - mmseg - INFO - Iter [105100/160000] lr: 4.687e-06, eta: 4:42:00, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9041, loss: 0.0787 2023-03-04 05:51:13,790 - mmseg - INFO - Iter [105150/160000] lr: 4.687e-06, eta: 4:41:43, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8081, loss: 0.0807 2023-03-04 05:51:26,019 - mmseg - INFO - Iter [105200/160000] lr: 4.687e-06, eta: 4:41:26, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9409, loss: 0.0768 2023-03-04 05:51:38,223 - mmseg - INFO - Iter [105250/160000] lr: 4.687e-06, eta: 4:41:09, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9415, loss: 0.0774 2023-03-04 05:51:52,774 - mmseg - INFO - Iter [105300/160000] lr: 4.687e-06, eta: 4:40:53, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0757, decode.acc_seg: 97.0047, loss: 0.0757 2023-03-04 05:52:04,939 - mmseg - INFO - Iter [105350/160000] lr: 4.687e-06, eta: 4:40:36, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8886, loss: 0.0782 2023-03-04 05:52:17,334 - mmseg - INFO - Iter [105400/160000] lr: 4.687e-06, eta: 4:40:19, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9356, loss: 0.0779 2023-03-04 05:52:29,677 - mmseg - INFO - Iter [105450/160000] lr: 4.687e-06, eta: 4:40:02, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8070, loss: 0.0797 2023-03-04 05:52:44,340 - mmseg - INFO - Iter [105500/160000] lr: 4.687e-06, eta: 4:39:47, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9501, loss: 0.0768 2023-03-04 05:52:56,767 - mmseg - INFO - Iter [105550/160000] lr: 4.687e-06, eta: 4:39:30, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7795, loss: 0.0815 2023-03-04 05:53:09,003 - mmseg - INFO - Iter [105600/160000] lr: 4.687e-06, eta: 4:39:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9371, loss: 0.0779 2023-03-04 05:53:23,506 - mmseg - INFO - Iter [105650/160000] lr: 4.687e-06, eta: 4:38:57, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8586, loss: 0.0786 2023-03-04 05:53:35,665 - mmseg - INFO - Iter [105700/160000] lr: 4.687e-06, eta: 4:38:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9586, loss: 0.0769 2023-03-04 05:53:48,040 - mmseg - INFO - Iter [105750/160000] lr: 4.687e-06, eta: 4:38:23, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7739, loss: 0.0803 2023-03-04 05:54:00,276 - mmseg - INFO - Iter [105800/160000] lr: 4.687e-06, eta: 4:38:06, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7700, loss: 0.0819 2023-03-04 05:54:14,800 - mmseg - INFO - Iter [105850/160000] lr: 4.687e-06, eta: 4:37:50, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8357, loss: 0.0792 2023-03-04 05:54:26,988 - mmseg - INFO - Iter [105900/160000] lr: 4.687e-06, eta: 4:37:33, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9395, loss: 0.0772 2023-03-04 05:54:39,266 - mmseg - INFO - Iter [105950/160000] lr: 4.687e-06, eta: 4:37:16, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9037, loss: 0.0783 2023-03-04 05:54:51,391 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:54:51,391 - mmseg - INFO - Iter [106000/160000] lr: 4.687e-06, eta: 4:36:59, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8287, loss: 0.0797 2023-03-04 05:55:05,904 - mmseg - INFO - Iter [106050/160000] lr: 4.687e-06, eta: 4:36:43, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8813, loss: 0.0779 2023-03-04 05:55:18,054 - mmseg - INFO - Iter [106100/160000] lr: 4.687e-06, eta: 4:36:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8445, loss: 0.0800 2023-03-04 05:55:30,199 - mmseg - INFO - Iter [106150/160000] lr: 4.687e-06, eta: 4:36:09, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8521, loss: 0.0799 2023-03-04 05:55:42,460 - mmseg - INFO - Iter [106200/160000] lr: 4.687e-06, eta: 4:35:52, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9284, loss: 0.0777 2023-03-04 05:55:57,072 - mmseg - INFO - Iter [106250/160000] lr: 4.687e-06, eta: 4:35:36, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8938, loss: 0.0794 2023-03-04 05:56:09,255 - mmseg - INFO - Iter [106300/160000] lr: 4.687e-06, eta: 4:35:19, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8134, loss: 0.0800 2023-03-04 05:56:21,588 - mmseg - INFO - Iter [106350/160000] lr: 4.687e-06, eta: 4:35:02, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9620, loss: 0.0766 2023-03-04 05:56:36,209 - mmseg - INFO - Iter [106400/160000] lr: 4.687e-06, eta: 4:34:46, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8305, loss: 0.0803 2023-03-04 05:56:48,435 - mmseg - INFO - Iter [106450/160000] lr: 4.687e-06, eta: 4:34:30, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8820, loss: 0.0793 2023-03-04 05:57:00,662 - mmseg - INFO - Iter [106500/160000] lr: 4.687e-06, eta: 4:34:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0850, decode.acc_seg: 96.6604, loss: 0.0850 2023-03-04 05:57:12,894 - mmseg - INFO - Iter [106550/160000] lr: 4.687e-06, eta: 4:33:56, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9165, loss: 0.0782 2023-03-04 05:57:27,375 - mmseg - INFO - Iter [106600/160000] lr: 4.687e-06, eta: 4:33:40, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8338, loss: 0.0794 2023-03-04 05:57:39,538 - mmseg - INFO - Iter [106650/160000] lr: 4.687e-06, eta: 4:33:23, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8295, loss: 0.0791 2023-03-04 05:57:51,741 - mmseg - INFO - Iter [106700/160000] lr: 4.687e-06, eta: 4:33:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.8117, loss: 0.0817 2023-03-04 05:58:04,035 - mmseg - INFO - Iter [106750/160000] lr: 4.687e-06, eta: 4:32:49, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8626, loss: 0.0794 2023-03-04 05:58:18,501 - mmseg - INFO - Iter [106800/160000] lr: 4.687e-06, eta: 4:32:33, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9257, loss: 0.0774 2023-03-04 05:58:30,744 - mmseg - INFO - Iter [106850/160000] lr: 4.687e-06, eta: 4:32:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7522, loss: 0.0823 2023-03-04 05:58:42,834 - mmseg - INFO - Iter [106900/160000] lr: 4.687e-06, eta: 4:31:59, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8663, loss: 0.0792 2023-03-04 05:58:54,948 - mmseg - INFO - Iter [106950/160000] lr: 4.687e-06, eta: 4:31:42, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9127, loss: 0.0772 2023-03-04 05:59:09,583 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 05:59:09,583 - mmseg - INFO - Iter [107000/160000] lr: 4.687e-06, eta: 4:31:26, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0755, decode.acc_seg: 96.9538, loss: 0.0755 2023-03-04 05:59:21,825 - mmseg - INFO - Iter [107050/160000] lr: 4.687e-06, eta: 4:31:10, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8700, loss: 0.0793 2023-03-04 05:59:34,010 - mmseg - INFO - Iter [107100/160000] lr: 4.687e-06, eta: 4:30:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8485, loss: 0.0783 2023-03-04 05:59:48,598 - mmseg - INFO - Iter [107150/160000] lr: 4.687e-06, eta: 4:30:37, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7804, loss: 0.0814 2023-03-04 06:00:00,884 - mmseg - INFO - Iter [107200/160000] lr: 4.687e-06, eta: 4:30:20, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8941, loss: 0.0785 2023-03-04 06:00:13,162 - mmseg - INFO - Iter [107250/160000] lr: 4.687e-06, eta: 4:30:03, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8931, loss: 0.0778 2023-03-04 06:00:25,380 - mmseg - INFO - Iter [107300/160000] lr: 4.687e-06, eta: 4:29:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7929, loss: 0.0805 2023-03-04 06:00:39,822 - mmseg - INFO - Iter [107350/160000] lr: 4.687e-06, eta: 4:29:30, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8828, loss: 0.0784 2023-03-04 06:00:52,019 - mmseg - INFO - Iter [107400/160000] lr: 4.687e-06, eta: 4:29:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9795, loss: 0.0761 2023-03-04 06:01:04,175 - mmseg - INFO - Iter [107450/160000] lr: 4.687e-06, eta: 4:28:57, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9801, loss: 0.0764 2023-03-04 06:01:16,401 - mmseg - INFO - Iter [107500/160000] lr: 4.687e-06, eta: 4:28:40, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8403, loss: 0.0800 2023-03-04 06:01:30,959 - mmseg - INFO - Iter [107550/160000] lr: 4.687e-06, eta: 4:28:24, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8120, loss: 0.0799 2023-03-04 06:01:43,341 - mmseg - INFO - Iter [107600/160000] lr: 4.687e-06, eta: 4:28:07, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8343, loss: 0.0804 2023-03-04 06:01:55,568 - mmseg - INFO - Iter [107650/160000] lr: 4.687e-06, eta: 4:27:50, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9357, loss: 0.0776 2023-03-04 06:02:10,037 - mmseg - INFO - Iter [107700/160000] lr: 4.687e-06, eta: 4:27:35, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8173, loss: 0.0804 2023-03-04 06:02:22,275 - mmseg - INFO - Iter [107750/160000] lr: 4.687e-06, eta: 4:27:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7822, loss: 0.0837 2023-03-04 06:02:34,532 - mmseg - INFO - Iter [107800/160000] lr: 4.687e-06, eta: 4:27:01, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8923, loss: 0.0790 2023-03-04 06:02:46,781 - mmseg - INFO - Iter [107850/160000] lr: 4.687e-06, eta: 4:26:44, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8506, loss: 0.0802 2023-03-04 06:03:01,337 - mmseg - INFO - Iter [107900/160000] lr: 4.687e-06, eta: 4:26:28, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7940, loss: 0.0817 2023-03-04 06:03:13,617 - mmseg - INFO - Iter [107950/160000] lr: 4.687e-06, eta: 4:26:11, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9677, loss: 0.0771 2023-03-04 06:03:25,717 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:03:25,718 - mmseg - INFO - Iter [108000/160000] lr: 4.687e-06, eta: 4:25:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7712, loss: 0.0819 2023-03-04 06:03:37,969 - mmseg - INFO - Iter [108050/160000] lr: 4.687e-06, eta: 4:25:38, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9073, loss: 0.0778 2023-03-04 06:03:52,414 - mmseg - INFO - Iter [108100/160000] lr: 4.687e-06, eta: 4:25:22, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7817, loss: 0.0811 2023-03-04 06:04:04,586 - mmseg - INFO - Iter [108150/160000] lr: 4.687e-06, eta: 4:25:05, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8222, loss: 0.0802 2023-03-04 06:04:16,873 - mmseg - INFO - Iter [108200/160000] lr: 4.687e-06, eta: 4:24:48, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0758, decode.acc_seg: 96.9636, loss: 0.0758 2023-03-04 06:04:29,062 - mmseg - INFO - Iter [108250/160000] lr: 4.687e-06, eta: 4:24:31, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9109, loss: 0.0784 2023-03-04 06:04:43,708 - mmseg - INFO - Iter [108300/160000] lr: 4.687e-06, eta: 4:24:16, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9053, loss: 0.0774 2023-03-04 06:04:55,896 - mmseg - INFO - Iter [108350/160000] lr: 4.687e-06, eta: 4:23:59, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8903, loss: 0.0785 2023-03-04 06:05:08,129 - mmseg - INFO - Iter [108400/160000] lr: 4.687e-06, eta: 4:23:42, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7150, loss: 0.0841 2023-03-04 06:05:22,604 - mmseg - INFO - Iter [108450/160000] lr: 4.687e-06, eta: 4:23:26, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8996, loss: 0.0779 2023-03-04 06:05:34,819 - mmseg - INFO - Iter [108500/160000] lr: 4.687e-06, eta: 4:23:10, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8670, loss: 0.0789 2023-03-04 06:05:47,024 - mmseg - INFO - Iter [108550/160000] lr: 4.687e-06, eta: 4:22:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8482, loss: 0.0796 2023-03-04 06:05:59,216 - mmseg - INFO - Iter [108600/160000] lr: 4.687e-06, eta: 4:22:36, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8899, loss: 0.0790 2023-03-04 06:06:13,692 - mmseg - INFO - Iter [108650/160000] lr: 4.687e-06, eta: 4:22:20, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9080, loss: 0.0780 2023-03-04 06:06:25,881 - mmseg - INFO - Iter [108700/160000] lr: 4.687e-06, eta: 4:22:03, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7866, loss: 0.0812 2023-03-04 06:06:38,142 - mmseg - INFO - Iter [108750/160000] lr: 4.687e-06, eta: 4:21:47, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8328, loss: 0.0801 2023-03-04 06:06:50,246 - mmseg - INFO - Iter [108800/160000] lr: 4.687e-06, eta: 4:21:30, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8250, loss: 0.0800 2023-03-04 06:07:04,864 - mmseg - INFO - Iter [108850/160000] lr: 4.687e-06, eta: 4:21:14, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7984, loss: 0.0806 2023-03-04 06:07:17,065 - mmseg - INFO - Iter [108900/160000] lr: 4.687e-06, eta: 4:20:57, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9000, loss: 0.0784 2023-03-04 06:07:29,196 - mmseg - INFO - Iter [108950/160000] lr: 4.687e-06, eta: 4:20:41, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8924, loss: 0.0783 2023-03-04 06:07:43,695 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:07:43,695 - mmseg - INFO - Iter [109000/160000] lr: 4.687e-06, eta: 4:20:25, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9371, loss: 0.0778 2023-03-04 06:07:55,851 - mmseg - INFO - Iter [109050/160000] lr: 4.687e-06, eta: 4:20:08, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8687, loss: 0.0793 2023-03-04 06:08:08,142 - mmseg - INFO - Iter [109100/160000] lr: 4.687e-06, eta: 4:19:51, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8516, loss: 0.0795 2023-03-04 06:08:20,413 - mmseg - INFO - Iter [109150/160000] lr: 4.687e-06, eta: 4:19:35, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8812, loss: 0.0778 2023-03-04 06:08:35,067 - mmseg - INFO - Iter [109200/160000] lr: 4.687e-06, eta: 4:19:19, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7214, loss: 0.0826 2023-03-04 06:08:47,349 - mmseg - INFO - Iter [109250/160000] lr: 4.687e-06, eta: 4:19:02, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9656, loss: 0.0765 2023-03-04 06:08:59,437 - mmseg - INFO - Iter [109300/160000] lr: 4.687e-06, eta: 4:18:45, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8644, loss: 0.0796 2023-03-04 06:09:11,561 - mmseg - INFO - Iter [109350/160000] lr: 4.687e-06, eta: 4:18:29, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8592, loss: 0.0801 2023-03-04 06:09:26,094 - mmseg - INFO - Iter [109400/160000] lr: 4.687e-06, eta: 4:18:13, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8586, loss: 0.0779 2023-03-04 06:09:38,290 - mmseg - INFO - Iter [109450/160000] lr: 4.687e-06, eta: 4:17:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8881, loss: 0.0789 2023-03-04 06:09:50,541 - mmseg - INFO - Iter [109500/160000] lr: 4.687e-06, eta: 4:17:40, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7667, loss: 0.0806 2023-03-04 06:10:02,664 - mmseg - INFO - Iter [109550/160000] lr: 4.687e-06, eta: 4:17:23, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9418, loss: 0.0773 2023-03-04 06:10:17,218 - mmseg - INFO - Iter [109600/160000] lr: 4.687e-06, eta: 4:17:07, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9359, loss: 0.0774 2023-03-04 06:10:29,492 - mmseg - INFO - Iter [109650/160000] lr: 4.687e-06, eta: 4:16:50, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8791, loss: 0.0789 2023-03-04 06:10:41,613 - mmseg - INFO - Iter [109700/160000] lr: 4.687e-06, eta: 4:16:34, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8884, loss: 0.0781 2023-03-04 06:10:56,333 - mmseg - INFO - Iter [109750/160000] lr: 4.687e-06, eta: 4:16:18, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8357, loss: 0.0801 2023-03-04 06:11:08,571 - mmseg - INFO - Iter [109800/160000] lr: 4.687e-06, eta: 4:16:01, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9018, loss: 0.0776 2023-03-04 06:11:20,796 - mmseg - INFO - Iter [109850/160000] lr: 4.687e-06, eta: 4:15:45, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9144, loss: 0.0787 2023-03-04 06:11:33,015 - mmseg - INFO - Iter [109900/160000] lr: 4.687e-06, eta: 4:15:28, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8750, loss: 0.0792 2023-03-04 06:11:47,516 - mmseg - INFO - Iter [109950/160000] lr: 4.687e-06, eta: 4:15:12, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0758, decode.acc_seg: 96.9983, loss: 0.0758 2023-03-04 06:11:59,772 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:11:59,772 - mmseg - INFO - Iter [110000/160000] lr: 4.687e-06, eta: 4:14:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8364, loss: 0.0802 2023-03-04 06:12:11,928 - mmseg - INFO - Iter [110050/160000] lr: 4.687e-06, eta: 4:14:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8022, loss: 0.0812 2023-03-04 06:12:24,059 - mmseg - INFO - Iter [110100/160000] lr: 4.687e-06, eta: 4:14:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9662, loss: 0.0772 2023-03-04 06:12:38,487 - mmseg - INFO - Iter [110150/160000] lr: 4.687e-06, eta: 4:14:06, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7712, loss: 0.0812 2023-03-04 06:12:50,685 - mmseg - INFO - Iter [110200/160000] lr: 4.687e-06, eta: 4:13:50, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 97.0033, loss: 0.0763 2023-03-04 06:13:02,817 - mmseg - INFO - Iter [110250/160000] lr: 4.687e-06, eta: 4:13:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8661, loss: 0.0789 2023-03-04 06:13:17,337 - mmseg - INFO - Iter [110300/160000] lr: 4.687e-06, eta: 4:13:17, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8329, loss: 0.0798 2023-03-04 06:13:29,538 - mmseg - INFO - Iter [110350/160000] lr: 4.687e-06, eta: 4:13:01, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8625, loss: 0.0791 2023-03-04 06:13:41,842 - mmseg - INFO - Iter [110400/160000] lr: 4.687e-06, eta: 4:12:44, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7357, loss: 0.0823 2023-03-04 06:13:54,139 - mmseg - INFO - Iter [110450/160000] lr: 4.687e-06, eta: 4:12:27, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7740, loss: 0.0812 2023-03-04 06:14:08,710 - mmseg - INFO - Iter [110500/160000] lr: 4.687e-06, eta: 4:12:12, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0758, decode.acc_seg: 96.9620, loss: 0.0758 2023-03-04 06:14:21,120 - mmseg - INFO - Iter [110550/160000] lr: 4.687e-06, eta: 4:11:55, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8368, loss: 0.0797 2023-03-04 06:14:33,470 - mmseg - INFO - Iter [110600/160000] lr: 4.687e-06, eta: 4:11:39, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7722, loss: 0.0811 2023-03-04 06:14:45,648 - mmseg - INFO - Iter [110650/160000] lr: 4.687e-06, eta: 4:11:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8277, loss: 0.0800 2023-03-04 06:15:00,128 - mmseg - INFO - Iter [110700/160000] lr: 4.687e-06, eta: 4:11:06, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7602, loss: 0.0823 2023-03-04 06:15:12,302 - mmseg - INFO - Iter [110750/160000] lr: 4.687e-06, eta: 4:10:50, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8320, loss: 0.0799 2023-03-04 06:15:24,425 - mmseg - INFO - Iter [110800/160000] lr: 4.687e-06, eta: 4:10:33, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8080, loss: 0.0811 2023-03-04 06:15:36,696 - mmseg - INFO - Iter [110850/160000] lr: 4.687e-06, eta: 4:10:16, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9823, loss: 0.0756 2023-03-04 06:15:51,383 - mmseg - INFO - Iter [110900/160000] lr: 4.687e-06, eta: 4:10:01, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9414, loss: 0.0773 2023-03-04 06:16:03,530 - mmseg - INFO - Iter [110950/160000] lr: 4.687e-06, eta: 4:09:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7484, loss: 0.0828 2023-03-04 06:16:15,752 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:16:15,752 - mmseg - INFO - Iter [111000/160000] lr: 4.687e-06, eta: 4:09:28, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7111, loss: 0.0841 2023-03-04 06:16:30,247 - mmseg - INFO - Iter [111050/160000] lr: 4.687e-06, eta: 4:09:12, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.8053, loss: 0.0821 2023-03-04 06:16:42,385 - mmseg - INFO - Iter [111100/160000] lr: 4.687e-06, eta: 4:08:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8570, loss: 0.0795 2023-03-04 06:16:54,574 - mmseg - INFO - Iter [111150/160000] lr: 4.687e-06, eta: 4:08:39, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8718, loss: 0.0781 2023-03-04 06:17:06,707 - mmseg - INFO - Iter [111200/160000] lr: 4.687e-06, eta: 4:08:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8291, loss: 0.0799 2023-03-04 06:17:21,178 - mmseg - INFO - Iter [111250/160000] lr: 4.687e-06, eta: 4:08:06, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8460, loss: 0.0803 2023-03-04 06:17:33,301 - mmseg - INFO - Iter [111300/160000] lr: 4.687e-06, eta: 4:07:50, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.8965, loss: 0.0775 2023-03-04 06:17:45,493 - mmseg - INFO - Iter [111350/160000] lr: 4.687e-06, eta: 4:07:33, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9693, loss: 0.0768 2023-03-04 06:17:57,754 - mmseg - INFO - Iter [111400/160000] lr: 4.687e-06, eta: 4:07:17, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7800, loss: 0.0825 2023-03-04 06:18:12,222 - mmseg - INFO - Iter [111450/160000] lr: 4.687e-06, eta: 4:07:01, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8694, loss: 0.0793 2023-03-04 06:18:24,409 - mmseg - INFO - Iter [111500/160000] lr: 4.687e-06, eta: 4:06:44, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8458, loss: 0.0799 2023-03-04 06:18:36,611 - mmseg - INFO - Iter [111550/160000] lr: 4.687e-06, eta: 4:06:28, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9323, loss: 0.0782 2023-03-04 06:18:48,762 - mmseg - INFO - Iter [111600/160000] lr: 4.687e-06, eta: 4:06:11, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8955, loss: 0.0779 2023-03-04 06:19:03,441 - mmseg - INFO - Iter [111650/160000] lr: 4.687e-06, eta: 4:05:56, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8839, loss: 0.0796 2023-03-04 06:19:15,551 - mmseg - INFO - Iter [111700/160000] lr: 4.687e-06, eta: 4:05:39, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8218, loss: 0.0789 2023-03-04 06:19:27,812 - mmseg - INFO - Iter [111750/160000] lr: 4.687e-06, eta: 4:05:23, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8970, loss: 0.0787 2023-03-04 06:19:42,422 - mmseg - INFO - Iter [111800/160000] lr: 4.687e-06, eta: 4:05:07, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0759, decode.acc_seg: 96.9896, loss: 0.0759 2023-03-04 06:19:54,658 - mmseg - INFO - Iter [111850/160000] lr: 4.687e-06, eta: 4:04:50, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9535, loss: 0.0772 2023-03-04 06:20:06,979 - mmseg - INFO - Iter [111900/160000] lr: 4.687e-06, eta: 4:04:34, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9776, loss: 0.0771 2023-03-04 06:20:19,090 - mmseg - INFO - Iter [111950/160000] lr: 4.687e-06, eta: 4:04:17, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7611, loss: 0.0817 2023-03-04 06:20:33,856 - mmseg - INFO - Swap parameters (after train) after iter [112000] 2023-03-04 06:20:33,871 - mmseg - INFO - Saving checkpoint at 112000 iterations 2023-03-04 06:20:35,216 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:20:35,217 - mmseg - INFO - Iter [112000/160000] lr: 4.687e-06, eta: 4:04:02, time: 0.323, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8489, loss: 0.0796 2023-03-04 06:35:29,540 - mmseg - INFO - per class results: 2023-03-04 06:35:29,542 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.57,98.57,98.58,98.58,98.58,98.58,98.58,98.58,98.58,98.58,98.58 | | sidewalk | 87.78,87.8,87.86,87.87,87.88,87.87,87.9,87.89,87.89,87.89,87.87 | | building | 93.33,93.33,93.34,93.34,93.34,93.35,93.34,93.35,93.35,93.35,93.34 | | wall | 54.43,54.47,54.54,54.66,54.77,54.98,54.93,55.22,55.35,55.51,55.19 | | fence | 63.61,63.61,63.61,63.64,63.62,63.64,63.55,63.58,63.63,63.58,63.6 | | pole | 71.02,71.01,71.05,71.05,71.04,71.05,71.05,71.04,71.05,71.05,71.04 | | traffic light | 75.51,75.49,75.51,75.5,75.5,75.5,75.5,75.5,75.5,75.5,75.49 | | traffic sign | 83.27,83.26,83.28,83.29,83.28,83.3,83.3,83.31,83.32,83.32,83.33 | | vegetation | 92.93,92.93,92.94,92.95,92.94,92.94,92.94,92.94,92.95,92.94,92.94 | | terrain | 65.68,65.75,65.87,66.02,66.05,66.03,66.12,66.14,66.2,66.11,65.99 | | sky | 95.25,95.26,95.26,95.26,95.26,95.26,95.26,95.26,95.26,95.26,95.26 | | person | 84.8,84.81,84.82,84.83,84.83,84.83,84.82,84.83,84.84,84.84,84.84 | | rider | 67.42,67.45,67.44,67.53,67.51,67.48,67.5,67.51,67.54,67.54,67.54 | | car | 95.95,95.97,95.99,96.0,96.02,96.03,96.03,96.03,96.04,96.04,96.03 | | truck | 84.81,85.4,85.81,86.18,86.32,86.64,86.73,86.62,86.79,86.71,86.73 | | bus | 92.18,92.18,92.22,92.2,92.22,92.25,92.26,92.25,92.31,92.29,92.27 | | train | 85.77,85.77,85.81,85.89,85.85,85.93,85.92,85.92,85.94,85.9,85.91 | | motorcycle | 69.72,69.7,69.69,69.66,69.71,69.69,69.64,69.66,69.65,69.65,69.64 | | bicycle | 79.91,79.9,79.9,79.9,79.91,79.91,79.93,79.93,79.95,79.94,79.95 | +---------------+-------------------------------------------------------------------+ 2023-03-04 06:35:29,542 - mmseg - INFO - Summary: 2023-03-04 06:35:29,542 - mmseg - INFO - +------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +------------------------------------------------------------------+ | 81.15,81.19,81.24,81.28,81.3,81.33,81.33,81.35,81.38,81.37,81.34 | +------------------------------------------------------------------+ 2023-03-04 06:35:29,542 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:35:29,542 - mmseg - INFO - Iter(val) [63] mIoU: [0.8115, 0.8119, 0.8124, 0.8128, 0.813, 0.8133, 0.8133, 0.8135, 0.8138, 0.8137, 0.8134], copy_paste: 81.15,81.19,81.24,81.28,81.3,81.33,81.33,81.35,81.38,81.37,81.34 2023-03-04 06:35:29,550 - mmseg - INFO - Swap parameters (before train) before iter [112001] 2023-03-04 06:35:41,938 - mmseg - INFO - Iter [112050/160000] lr: 4.687e-06, eta: 4:10:09, time: 18.134, data_time: 17.895, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8320, loss: 0.0811 2023-03-04 06:35:54,362 - mmseg - INFO - Iter [112100/160000] lr: 4.687e-06, eta: 4:09:52, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8259, loss: 0.0801 2023-03-04 06:36:06,697 - mmseg - INFO - Iter [112150/160000] lr: 4.687e-06, eta: 4:09:35, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8185, loss: 0.0797 2023-03-04 06:36:21,301 - mmseg - INFO - Iter [112200/160000] lr: 4.687e-06, eta: 4:09:18, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8548, loss: 0.0787 2023-03-04 06:36:33,777 - mmseg - INFO - Iter [112250/160000] lr: 4.687e-06, eta: 4:09:01, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8307, loss: 0.0801 2023-03-04 06:36:45,965 - mmseg - INFO - Iter [112300/160000] lr: 4.687e-06, eta: 4:08:44, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9379, loss: 0.0771 2023-03-04 06:37:00,617 - mmseg - INFO - Iter [112350/160000] lr: 4.687e-06, eta: 4:08:28, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.9349, loss: 0.0793 2023-03-04 06:37:12,815 - mmseg - INFO - Iter [112400/160000] lr: 4.687e-06, eta: 4:08:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8386, loss: 0.0794 2023-03-04 06:37:25,070 - mmseg - INFO - Iter [112450/160000] lr: 4.687e-06, eta: 4:07:54, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8162, loss: 0.0813 2023-03-04 06:37:37,250 - mmseg - INFO - Iter [112500/160000] lr: 4.687e-06, eta: 4:07:37, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.8776, loss: 0.0775 2023-03-04 06:37:51,772 - mmseg - INFO - Iter [112550/160000] lr: 4.687e-06, eta: 4:07:21, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8867, loss: 0.0790 2023-03-04 06:38:04,089 - mmseg - INFO - Iter [112600/160000] lr: 4.687e-06, eta: 4:07:04, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8067, loss: 0.0810 2023-03-04 06:38:16,305 - mmseg - INFO - Iter [112650/160000] lr: 4.687e-06, eta: 4:06:47, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9315, loss: 0.0766 2023-03-04 06:38:28,730 - mmseg - INFO - Iter [112700/160000] lr: 4.687e-06, eta: 4:06:30, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8334, loss: 0.0802 2023-03-04 06:38:43,245 - mmseg - INFO - Iter [112750/160000] lr: 4.687e-06, eta: 4:06:14, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8997, loss: 0.0786 2023-03-04 06:38:55,402 - mmseg - INFO - Iter [112800/160000] lr: 4.687e-06, eta: 4:05:57, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9398, loss: 0.0782 2023-03-04 06:39:07,663 - mmseg - INFO - Iter [112850/160000] lr: 4.687e-06, eta: 4:05:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8202, loss: 0.0805 2023-03-04 06:39:19,911 - mmseg - INFO - Iter [112900/160000] lr: 4.687e-06, eta: 4:05:23, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8583, loss: 0.0789 2023-03-04 06:39:34,455 - mmseg - INFO - Iter [112950/160000] lr: 4.687e-06, eta: 4:05:06, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9618, loss: 0.0773 2023-03-04 06:39:46,704 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:39:46,704 - mmseg - INFO - Iter [113000/160000] lr: 4.687e-06, eta: 4:04:49, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7236, loss: 0.0837 2023-03-04 06:39:58,962 - mmseg - INFO - Iter [113050/160000] lr: 4.687e-06, eta: 4:04:32, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8536, loss: 0.0790 2023-03-04 06:40:13,558 - mmseg - INFO - Iter [113100/160000] lr: 4.687e-06, eta: 4:04:16, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.8017, loss: 0.0818 2023-03-04 06:40:25,690 - mmseg - INFO - Iter [113150/160000] lr: 4.687e-06, eta: 4:03:59, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9127, loss: 0.0770 2023-03-04 06:40:37,849 - mmseg - INFO - Iter [113200/160000] lr: 4.687e-06, eta: 4:03:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9267, loss: 0.0778 2023-03-04 06:40:49,923 - mmseg - INFO - Iter [113250/160000] lr: 4.687e-06, eta: 4:03:25, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8686, loss: 0.0789 2023-03-04 06:41:04,431 - mmseg - INFO - Iter [113300/160000] lr: 4.687e-06, eta: 4:03:09, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7675, loss: 0.0823 2023-03-04 06:41:16,583 - mmseg - INFO - Iter [113350/160000] lr: 4.687e-06, eta: 4:02:52, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8410, loss: 0.0804 2023-03-04 06:41:28,719 - mmseg - INFO - Iter [113400/160000] lr: 4.687e-06, eta: 4:02:35, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8520, loss: 0.0793 2023-03-04 06:41:41,141 - mmseg - INFO - Iter [113450/160000] lr: 4.687e-06, eta: 4:02:18, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8144, loss: 0.0804 2023-03-04 06:41:55,764 - mmseg - INFO - Iter [113500/160000] lr: 4.687e-06, eta: 4:02:02, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8113, loss: 0.0801 2023-03-04 06:42:07,948 - mmseg - INFO - Iter [113550/160000] lr: 4.687e-06, eta: 4:01:45, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0844, decode.acc_seg: 96.7903, loss: 0.0844 2023-03-04 06:42:20,149 - mmseg - INFO - Iter [113600/160000] lr: 4.687e-06, eta: 4:01:28, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9180, loss: 0.0785 2023-03-04 06:42:34,673 - mmseg - INFO - Iter [113650/160000] lr: 4.687e-06, eta: 4:01:12, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 97.0109, loss: 0.0764 2023-03-04 06:42:46,891 - mmseg - INFO - Iter [113700/160000] lr: 4.687e-06, eta: 4:00:55, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8877, loss: 0.0787 2023-03-04 06:42:59,132 - mmseg - INFO - Iter [113750/160000] lr: 4.687e-06, eta: 4:00:38, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7469, loss: 0.0821 2023-03-04 06:43:11,295 - mmseg - INFO - Iter [113800/160000] lr: 4.687e-06, eta: 4:00:21, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7885, loss: 0.0815 2023-03-04 06:43:25,806 - mmseg - INFO - Iter [113850/160000] lr: 4.687e-06, eta: 4:00:05, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8382, loss: 0.0812 2023-03-04 06:43:38,032 - mmseg - INFO - Iter [113900/160000] lr: 4.687e-06, eta: 3:59:48, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8080, loss: 0.0809 2023-03-04 06:43:50,194 - mmseg - INFO - Iter [113950/160000] lr: 4.687e-06, eta: 3:59:31, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8635, loss: 0.0795 2023-03-04 06:44:02,340 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:44:02,340 - mmseg - INFO - Iter [114000/160000] lr: 4.687e-06, eta: 3:59:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9293, loss: 0.0779 2023-03-04 06:44:16,967 - mmseg - INFO - Iter [114050/160000] lr: 4.687e-06, eta: 3:58:58, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8751, loss: 0.0784 2023-03-04 06:44:29,213 - mmseg - INFO - Iter [114100/160000] lr: 4.687e-06, eta: 3:58:41, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9311, loss: 0.0780 2023-03-04 06:44:41,487 - mmseg - INFO - Iter [114150/160000] lr: 4.687e-06, eta: 3:58:24, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8759, loss: 0.0781 2023-03-04 06:44:53,581 - mmseg - INFO - Iter [114200/160000] lr: 4.687e-06, eta: 3:58:07, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8393, loss: 0.0796 2023-03-04 06:45:08,067 - mmseg - INFO - Iter [114250/160000] lr: 4.687e-06, eta: 3:57:51, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.6721, loss: 0.0833 2023-03-04 06:45:20,359 - mmseg - INFO - Iter [114300/160000] lr: 4.687e-06, eta: 3:57:34, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9159, loss: 0.0785 2023-03-04 06:45:32,455 - mmseg - INFO - Iter [114350/160000] lr: 4.687e-06, eta: 3:57:17, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9735, loss: 0.0766 2023-03-04 06:45:46,912 - mmseg - INFO - Iter [114400/160000] lr: 4.687e-06, eta: 3:57:01, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8747, loss: 0.0788 2023-03-04 06:45:59,074 - mmseg - INFO - Iter [114450/160000] lr: 4.687e-06, eta: 3:56:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9678, loss: 0.0764 2023-03-04 06:46:11,296 - mmseg - INFO - Iter [114500/160000] lr: 4.687e-06, eta: 3:56:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9177, loss: 0.0776 2023-03-04 06:46:23,535 - mmseg - INFO - Iter [114550/160000] lr: 4.687e-06, eta: 3:56:10, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8854, loss: 0.0789 2023-03-04 06:46:38,093 - mmseg - INFO - Iter [114600/160000] lr: 4.687e-06, eta: 3:55:54, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7036, loss: 0.0834 2023-03-04 06:46:50,181 - mmseg - INFO - Iter [114650/160000] lr: 4.687e-06, eta: 3:55:37, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8519, loss: 0.0787 2023-03-04 06:47:02,331 - mmseg - INFO - Iter [114700/160000] lr: 4.687e-06, eta: 3:55:20, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8574, loss: 0.0813 2023-03-04 06:47:14,503 - mmseg - INFO - Iter [114750/160000] lr: 4.687e-06, eta: 3:55:03, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9257, loss: 0.0779 2023-03-04 06:47:29,097 - mmseg - INFO - Iter [114800/160000] lr: 4.687e-06, eta: 3:54:47, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8429, loss: 0.0798 2023-03-04 06:47:41,251 - mmseg - INFO - Iter [114850/160000] lr: 4.687e-06, eta: 3:54:30, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8122, loss: 0.0796 2023-03-04 06:47:53,364 - mmseg - INFO - Iter [114900/160000] lr: 4.687e-06, eta: 3:54:14, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8861, loss: 0.0783 2023-03-04 06:48:07,942 - mmseg - INFO - Iter [114950/160000] lr: 4.687e-06, eta: 3:53:58, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8523, loss: 0.0800 2023-03-04 06:48:20,163 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:48:20,163 - mmseg - INFO - Iter [115000/160000] lr: 4.687e-06, eta: 3:53:41, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9040, loss: 0.0787 2023-03-04 06:48:32,416 - mmseg - INFO - Iter [115050/160000] lr: 4.687e-06, eta: 3:53:24, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8619, loss: 0.0793 2023-03-04 06:48:44,600 - mmseg - INFO - Iter [115100/160000] lr: 4.687e-06, eta: 3:53:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7185, loss: 0.0817 2023-03-04 06:48:59,316 - mmseg - INFO - Iter [115150/160000] lr: 4.687e-06, eta: 3:52:51, time: 0.294, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9746, loss: 0.0767 2023-03-04 06:49:11,508 - mmseg - INFO - Iter [115200/160000] lr: 4.687e-06, eta: 3:52:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9350, loss: 0.0779 2023-03-04 06:49:23,817 - mmseg - INFO - Iter [115250/160000] lr: 4.687e-06, eta: 3:52:17, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0858, decode.acc_seg: 96.7672, loss: 0.0858 2023-03-04 06:49:36,018 - mmseg - INFO - Iter [115300/160000] lr: 4.687e-06, eta: 3:52:00, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0751, decode.acc_seg: 97.0089, loss: 0.0751 2023-03-04 06:49:50,464 - mmseg - INFO - Iter [115350/160000] lr: 4.687e-06, eta: 3:51:44, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 96.9811, loss: 0.0754 2023-03-04 06:50:02,685 - mmseg - INFO - Iter [115400/160000] lr: 4.687e-06, eta: 3:51:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9057, loss: 0.0780 2023-03-04 06:50:14,889 - mmseg - INFO - Iter [115450/160000] lr: 4.687e-06, eta: 3:51:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8784, loss: 0.0787 2023-03-04 06:50:27,146 - mmseg - INFO - Iter [115500/160000] lr: 4.687e-06, eta: 3:50:54, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8839, loss: 0.0792 2023-03-04 06:50:41,593 - mmseg - INFO - Iter [115550/160000] lr: 4.687e-06, eta: 3:50:38, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.6666, loss: 0.0852 2023-03-04 06:50:53,879 - mmseg - INFO - Iter [115600/160000] lr: 4.687e-06, eta: 3:50:21, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7102, loss: 0.0815 2023-03-04 06:51:06,022 - mmseg - INFO - Iter [115650/160000] lr: 4.687e-06, eta: 3:50:04, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7654, loss: 0.0811 2023-03-04 06:51:20,727 - mmseg - INFO - Iter [115700/160000] lr: 4.687e-06, eta: 3:49:48, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 97.0451, loss: 0.0754 2023-03-04 06:51:32,814 - mmseg - INFO - Iter [115750/160000] lr: 4.687e-06, eta: 3:49:31, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8206, loss: 0.0814 2023-03-04 06:51:44,939 - mmseg - INFO - Iter [115800/160000] lr: 4.687e-06, eta: 3:49:14, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8982, loss: 0.0786 2023-03-04 06:51:57,276 - mmseg - INFO - Iter [115850/160000] lr: 4.687e-06, eta: 3:48:58, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8284, loss: 0.0803 2023-03-04 06:52:11,847 - mmseg - INFO - Iter [115900/160000] lr: 4.687e-06, eta: 3:48:42, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.9047, loss: 0.0793 2023-03-04 06:52:24,057 - mmseg - INFO - Iter [115950/160000] lr: 4.687e-06, eta: 3:48:25, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9031, loss: 0.0776 2023-03-04 06:52:36,187 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:52:36,187 - mmseg - INFO - Iter [116000/160000] lr: 4.687e-06, eta: 3:48:08, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8489, loss: 0.0795 2023-03-04 06:52:48,505 - mmseg - INFO - Iter [116050/160000] lr: 4.687e-06, eta: 3:47:51, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9181, loss: 0.0775 2023-03-04 06:53:02,989 - mmseg - INFO - Iter [116100/160000] lr: 4.687e-06, eta: 3:47:35, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8782, loss: 0.0805 2023-03-04 06:53:15,099 - mmseg - INFO - Iter [116150/160000] lr: 4.687e-06, eta: 3:47:18, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9045, loss: 0.0783 2023-03-04 06:53:27,309 - mmseg - INFO - Iter [116200/160000] lr: 4.687e-06, eta: 3:47:02, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8288, loss: 0.0795 2023-03-04 06:53:39,476 - mmseg - INFO - Iter [116250/160000] lr: 4.687e-06, eta: 3:46:45, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8438, loss: 0.0798 2023-03-04 06:53:53,961 - mmseg - INFO - Iter [116300/160000] lr: 4.687e-06, eta: 3:46:29, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7767, loss: 0.0815 2023-03-04 06:54:06,102 - mmseg - INFO - Iter [116350/160000] lr: 4.687e-06, eta: 3:46:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0757, decode.acc_seg: 96.9957, loss: 0.0757 2023-03-04 06:54:18,276 - mmseg - INFO - Iter [116400/160000] lr: 4.687e-06, eta: 3:45:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9365, loss: 0.0768 2023-03-04 06:54:32,828 - mmseg - INFO - Iter [116450/160000] lr: 4.687e-06, eta: 3:45:39, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8549, loss: 0.0789 2023-03-04 06:54:44,982 - mmseg - INFO - Iter [116500/160000] lr: 4.687e-06, eta: 3:45:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9260, loss: 0.0787 2023-03-04 06:54:57,050 - mmseg - INFO - Iter [116550/160000] lr: 4.687e-06, eta: 3:45:06, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8339, loss: 0.0797 2023-03-04 06:55:09,312 - mmseg - INFO - Iter [116600/160000] lr: 4.687e-06, eta: 3:44:49, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9287, loss: 0.0766 2023-03-04 06:55:23,943 - mmseg - INFO - Iter [116650/160000] lr: 4.687e-06, eta: 3:44:33, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7304, loss: 0.0827 2023-03-04 06:55:36,153 - mmseg - INFO - Iter [116700/160000] lr: 4.687e-06, eta: 3:44:16, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8138, loss: 0.0803 2023-03-04 06:55:48,282 - mmseg - INFO - Iter [116750/160000] lr: 4.687e-06, eta: 3:43:59, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7936, loss: 0.0814 2023-03-04 06:56:00,525 - mmseg - INFO - Iter [116800/160000] lr: 4.687e-06, eta: 3:43:43, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7699, loss: 0.0827 2023-03-04 06:56:15,226 - mmseg - INFO - Iter [116850/160000] lr: 4.687e-06, eta: 3:43:27, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8884, loss: 0.0779 2023-03-04 06:56:27,509 - mmseg - INFO - Iter [116900/160000] lr: 4.687e-06, eta: 3:43:10, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8102, loss: 0.0808 2023-03-04 06:56:39,702 - mmseg - INFO - Iter [116950/160000] lr: 4.687e-06, eta: 3:42:53, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0845, decode.acc_seg: 96.7219, loss: 0.0845 2023-03-04 06:56:54,308 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 06:56:54,308 - mmseg - INFO - Iter [117000/160000] lr: 4.687e-06, eta: 3:42:37, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8839, loss: 0.0778 2023-03-04 06:57:06,529 - mmseg - INFO - Iter [117050/160000] lr: 4.687e-06, eta: 3:42:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9707, loss: 0.0762 2023-03-04 06:57:18,694 - mmseg - INFO - Iter [117100/160000] lr: 4.687e-06, eta: 3:42:04, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9363, loss: 0.0770 2023-03-04 06:57:30,798 - mmseg - INFO - Iter [117150/160000] lr: 4.687e-06, eta: 3:41:47, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8744, loss: 0.0794 2023-03-04 06:57:45,404 - mmseg - INFO - Iter [117200/160000] lr: 4.687e-06, eta: 3:41:31, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8689, loss: 0.0797 2023-03-04 06:57:57,573 - mmseg - INFO - Iter [117250/160000] lr: 4.687e-06, eta: 3:41:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9241, loss: 0.0762 2023-03-04 06:58:09,749 - mmseg - INFO - Iter [117300/160000] lr: 4.687e-06, eta: 3:40:58, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0863, decode.acc_seg: 96.6764, loss: 0.0863 2023-03-04 06:58:22,001 - mmseg - INFO - Iter [117350/160000] lr: 4.687e-06, eta: 3:40:41, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.8075, loss: 0.0826 2023-03-04 06:58:36,548 - mmseg - INFO - Iter [117400/160000] lr: 4.687e-06, eta: 3:40:25, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8179, loss: 0.0808 2023-03-04 06:58:48,817 - mmseg - INFO - Iter [117450/160000] lr: 4.687e-06, eta: 3:40:08, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8207, loss: 0.0794 2023-03-04 06:59:00,964 - mmseg - INFO - Iter [117500/160000] lr: 4.687e-06, eta: 3:39:52, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7974, loss: 0.0819 2023-03-04 06:59:13,169 - mmseg - INFO - Iter [117550/160000] lr: 4.687e-06, eta: 3:39:35, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9607, loss: 0.0768 2023-03-04 06:59:27,636 - mmseg - INFO - Iter [117600/160000] lr: 4.687e-06, eta: 3:39:19, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8669, loss: 0.0788 2023-03-04 06:59:39,769 - mmseg - INFO - Iter [117650/160000] lr: 4.687e-06, eta: 3:39:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9200, loss: 0.0775 2023-03-04 06:59:51,960 - mmseg - INFO - Iter [117700/160000] lr: 4.687e-06, eta: 3:38:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8049, loss: 0.0800 2023-03-04 07:00:06,483 - mmseg - INFO - Iter [117750/160000] lr: 4.687e-06, eta: 3:38:30, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8791, loss: 0.0788 2023-03-04 07:00:18,610 - mmseg - INFO - Iter [117800/160000] lr: 4.687e-06, eta: 3:38:13, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0753, decode.acc_seg: 97.0173, loss: 0.0753 2023-03-04 07:00:30,910 - mmseg - INFO - Iter [117850/160000] lr: 4.687e-06, eta: 3:37:56, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8577, loss: 0.0789 2023-03-04 07:00:43,114 - mmseg - INFO - Iter [117900/160000] lr: 4.687e-06, eta: 3:37:40, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8267, loss: 0.0796 2023-03-04 07:00:57,676 - mmseg - INFO - Iter [117950/160000] lr: 4.687e-06, eta: 3:37:24, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7768, loss: 0.0814 2023-03-04 07:01:09,955 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:01:09,956 - mmseg - INFO - Iter [118000/160000] lr: 4.687e-06, eta: 3:37:07, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8971, loss: 0.0787 2023-03-04 07:01:22,059 - mmseg - INFO - Iter [118050/160000] lr: 4.687e-06, eta: 3:36:50, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7373, loss: 0.0833 2023-03-04 07:01:34,167 - mmseg - INFO - Iter [118100/160000] lr: 4.687e-06, eta: 3:36:34, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8804, loss: 0.0786 2023-03-04 07:01:48,737 - mmseg - INFO - Iter [118150/160000] lr: 4.687e-06, eta: 3:36:18, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9219, loss: 0.0778 2023-03-04 07:02:01,163 - mmseg - INFO - Iter [118200/160000] lr: 4.687e-06, eta: 3:36:01, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7764, loss: 0.0811 2023-03-04 07:02:13,339 - mmseg - INFO - Iter [118250/160000] lr: 4.687e-06, eta: 3:35:45, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8821, loss: 0.0808 2023-03-04 07:02:27,781 - mmseg - INFO - Iter [118300/160000] lr: 4.687e-06, eta: 3:35:29, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8655, loss: 0.0786 2023-03-04 07:02:39,976 - mmseg - INFO - Iter [118350/160000] lr: 4.687e-06, eta: 3:35:12, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8569, loss: 0.0786 2023-03-04 07:02:52,318 - mmseg - INFO - Iter [118400/160000] lr: 4.687e-06, eta: 3:34:55, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9255, loss: 0.0775 2023-03-04 07:03:04,627 - mmseg - INFO - Iter [118450/160000] lr: 4.687e-06, eta: 3:34:39, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9633, loss: 0.0762 2023-03-04 07:03:19,109 - mmseg - INFO - Iter [118500/160000] lr: 4.687e-06, eta: 3:34:23, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9219, loss: 0.0783 2023-03-04 07:03:31,283 - mmseg - INFO - Iter [118550/160000] lr: 4.687e-06, eta: 3:34:06, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8743, loss: 0.0786 2023-03-04 07:03:43,500 - mmseg - INFO - Iter [118600/160000] lr: 4.687e-06, eta: 3:33:50, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9153, loss: 0.0788 2023-03-04 07:03:55,814 - mmseg - INFO - Iter [118650/160000] lr: 4.687e-06, eta: 3:33:33, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9653, loss: 0.0768 2023-03-04 07:04:10,410 - mmseg - INFO - Iter [118700/160000] lr: 4.687e-06, eta: 3:33:17, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8731, loss: 0.0789 2023-03-04 07:04:22,633 - mmseg - INFO - Iter [118750/160000] lr: 4.687e-06, eta: 3:33:01, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8074, loss: 0.0813 2023-03-04 07:04:34,796 - mmseg - INFO - Iter [118800/160000] lr: 4.687e-06, eta: 3:32:44, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9243, loss: 0.0782 2023-03-04 07:04:47,082 - mmseg - INFO - Iter [118850/160000] lr: 4.687e-06, eta: 3:32:27, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8634, loss: 0.0787 2023-03-04 07:05:01,772 - mmseg - INFO - Iter [118900/160000] lr: 4.687e-06, eta: 3:32:12, time: 0.294, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8631, loss: 0.0796 2023-03-04 07:05:13,929 - mmseg - INFO - Iter [118950/160000] lr: 4.687e-06, eta: 3:31:55, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9169, loss: 0.0774 2023-03-04 07:05:25,977 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:05:25,977 - mmseg - INFO - Iter [119000/160000] lr: 4.687e-06, eta: 3:31:38, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8415, loss: 0.0795 2023-03-04 07:05:40,449 - mmseg - INFO - Iter [119050/160000] lr: 4.687e-06, eta: 3:31:22, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8380, loss: 0.0799 2023-03-04 07:05:52,600 - mmseg - INFO - Iter [119100/160000] lr: 4.687e-06, eta: 3:31:06, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7935, loss: 0.0808 2023-03-04 07:06:04,794 - mmseg - INFO - Iter [119150/160000] lr: 4.687e-06, eta: 3:30:49, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8331, loss: 0.0805 2023-03-04 07:06:16,998 - mmseg - INFO - Iter [119200/160000] lr: 4.687e-06, eta: 3:30:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8716, loss: 0.0791 2023-03-04 07:06:31,664 - mmseg - INFO - Iter [119250/160000] lr: 4.687e-06, eta: 3:30:17, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8381, loss: 0.0809 2023-03-04 07:06:43,821 - mmseg - INFO - Iter [119300/160000] lr: 4.687e-06, eta: 3:30:00, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9192, loss: 0.0781 2023-03-04 07:06:55,873 - mmseg - INFO - Iter [119350/160000] lr: 4.687e-06, eta: 3:29:44, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8642, loss: 0.0789 2023-03-04 07:07:07,991 - mmseg - INFO - Iter [119400/160000] lr: 4.687e-06, eta: 3:29:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8965, loss: 0.0780 2023-03-04 07:07:22,647 - mmseg - INFO - Iter [119450/160000] lr: 4.687e-06, eta: 3:29:11, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9922, loss: 0.0761 2023-03-04 07:07:34,772 - mmseg - INFO - Iter [119500/160000] lr: 4.687e-06, eta: 3:28:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9447, loss: 0.0771 2023-03-04 07:07:46,960 - mmseg - INFO - Iter [119550/160000] lr: 4.687e-06, eta: 3:28:38, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8247, loss: 0.0811 2023-03-04 07:08:01,481 - mmseg - INFO - Iter [119600/160000] lr: 4.687e-06, eta: 3:28:22, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8540, loss: 0.0795 2023-03-04 07:08:13,603 - mmseg - INFO - Iter [119650/160000] lr: 4.687e-06, eta: 3:28:06, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9113, loss: 0.0782 2023-03-04 07:08:25,874 - mmseg - INFO - Iter [119700/160000] lr: 4.687e-06, eta: 3:27:49, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8163, loss: 0.0806 2023-03-04 07:08:38,128 - mmseg - INFO - Iter [119750/160000] lr: 4.687e-06, eta: 3:27:33, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8866, loss: 0.0786 2023-03-04 07:08:52,694 - mmseg - INFO - Iter [119800/160000] lr: 4.687e-06, eta: 3:27:17, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8386, loss: 0.0803 2023-03-04 07:09:05,012 - mmseg - INFO - Iter [119850/160000] lr: 4.687e-06, eta: 3:27:00, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7174, loss: 0.0820 2023-03-04 07:09:17,251 - mmseg - INFO - Iter [119900/160000] lr: 4.687e-06, eta: 3:26:44, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8897, loss: 0.0786 2023-03-04 07:09:29,332 - mmseg - INFO - Iter [119950/160000] lr: 4.687e-06, eta: 3:26:27, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8341, loss: 0.0801 2023-03-04 07:09:43,742 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:09:43,742 - mmseg - INFO - Iter [120000/160000] lr: 4.687e-06, eta: 3:26:11, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7520, loss: 0.0826 2023-03-04 07:09:56,045 - mmseg - INFO - Iter [120050/160000] lr: 2.344e-06, eta: 3:25:55, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8907, loss: 0.0784 2023-03-04 07:10:08,351 - mmseg - INFO - Iter [120100/160000] lr: 2.344e-06, eta: 3:25:38, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9259, loss: 0.0773 2023-03-04 07:10:20,453 - mmseg - INFO - Iter [120150/160000] lr: 2.344e-06, eta: 3:25:22, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9075, loss: 0.0783 2023-03-04 07:10:35,053 - mmseg - INFO - Iter [120200/160000] lr: 2.344e-06, eta: 3:25:06, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0755, decode.acc_seg: 96.9985, loss: 0.0755 2023-03-04 07:10:47,111 - mmseg - INFO - Iter [120250/160000] lr: 2.344e-06, eta: 3:24:49, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8577, loss: 0.0793 2023-03-04 07:10:59,297 - mmseg - INFO - Iter [120300/160000] lr: 2.344e-06, eta: 3:24:33, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7511, loss: 0.0822 2023-03-04 07:11:13,958 - mmseg - INFO - Iter [120350/160000] lr: 2.344e-06, eta: 3:24:17, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8928, loss: 0.0789 2023-03-04 07:11:26,080 - mmseg - INFO - Iter [120400/160000] lr: 2.344e-06, eta: 3:24:01, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8403, loss: 0.0799 2023-03-04 07:11:38,290 - mmseg - INFO - Iter [120450/160000] lr: 2.344e-06, eta: 3:23:44, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8264, loss: 0.0814 2023-03-04 07:11:50,420 - mmseg - INFO - Iter [120500/160000] lr: 2.344e-06, eta: 3:23:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8663, loss: 0.0802 2023-03-04 07:12:04,944 - mmseg - INFO - Iter [120550/160000] lr: 2.344e-06, eta: 3:23:12, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8580, loss: 0.0801 2023-03-04 07:12:17,134 - mmseg - INFO - Iter [120600/160000] lr: 2.344e-06, eta: 3:22:55, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8399, loss: 0.0800 2023-03-04 07:12:29,403 - mmseg - INFO - Iter [120650/160000] lr: 2.344e-06, eta: 3:22:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9471, loss: 0.0770 2023-03-04 07:12:41,581 - mmseg - INFO - Iter [120700/160000] lr: 2.344e-06, eta: 3:22:22, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0751, decode.acc_seg: 96.9988, loss: 0.0751 2023-03-04 07:12:56,111 - mmseg - INFO - Iter [120750/160000] lr: 2.344e-06, eta: 3:22:06, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8279, loss: 0.0804 2023-03-04 07:13:08,479 - mmseg - INFO - Iter [120800/160000] lr: 2.344e-06, eta: 3:21:50, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9011, loss: 0.0777 2023-03-04 07:13:20,877 - mmseg - INFO - Iter [120850/160000] lr: 2.344e-06, eta: 3:21:34, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9829, loss: 0.0763 2023-03-04 07:13:33,005 - mmseg - INFO - Iter [120900/160000] lr: 2.344e-06, eta: 3:21:17, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9076, loss: 0.0774 2023-03-04 07:13:47,586 - mmseg - INFO - Iter [120950/160000] lr: 2.344e-06, eta: 3:21:01, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8461, loss: 0.0796 2023-03-04 07:13:59,696 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:13:59,696 - mmseg - INFO - Iter [121000/160000] lr: 2.344e-06, eta: 3:20:45, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0758, decode.acc_seg: 96.9894, loss: 0.0758 2023-03-04 07:14:11,837 - mmseg - INFO - Iter [121050/160000] lr: 2.344e-06, eta: 3:20:28, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9469, loss: 0.0775 2023-03-04 07:14:26,436 - mmseg - INFO - Iter [121100/160000] lr: 2.344e-06, eta: 3:20:13, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9145, loss: 0.0788 2023-03-04 07:14:38,620 - mmseg - INFO - Iter [121150/160000] lr: 2.344e-06, eta: 3:19:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7928, loss: 0.0810 2023-03-04 07:14:50,799 - mmseg - INFO - Iter [121200/160000] lr: 2.344e-06, eta: 3:19:40, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8462, loss: 0.0800 2023-03-04 07:15:02,852 - mmseg - INFO - Iter [121250/160000] lr: 2.344e-06, eta: 3:19:23, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7579, loss: 0.0841 2023-03-04 07:15:17,552 - mmseg - INFO - Iter [121300/160000] lr: 2.344e-06, eta: 3:19:07, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8590, loss: 0.0808 2023-03-04 07:15:29,855 - mmseg - INFO - Iter [121350/160000] lr: 2.344e-06, eta: 3:18:51, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.8988, loss: 0.0777 2023-03-04 07:15:41,998 - mmseg - INFO - Iter [121400/160000] lr: 2.344e-06, eta: 3:18:34, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9399, loss: 0.0761 2023-03-04 07:15:54,184 - mmseg - INFO - Iter [121450/160000] lr: 2.344e-06, eta: 3:18:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9466, loss: 0.0773 2023-03-04 07:16:08,749 - mmseg - INFO - Iter [121500/160000] lr: 2.344e-06, eta: 3:18:02, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8977, loss: 0.0786 2023-03-04 07:16:20,884 - mmseg - INFO - Iter [121550/160000] lr: 2.344e-06, eta: 3:17:46, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8165, loss: 0.0804 2023-03-04 07:16:33,155 - mmseg - INFO - Iter [121600/160000] lr: 2.344e-06, eta: 3:17:29, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9656, loss: 0.0772 2023-03-04 07:16:47,652 - mmseg - INFO - Iter [121650/160000] lr: 2.344e-06, eta: 3:17:14, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8510, loss: 0.0794 2023-03-04 07:17:00,052 - mmseg - INFO - Iter [121700/160000] lr: 2.344e-06, eta: 3:16:57, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7946, loss: 0.0805 2023-03-04 07:17:12,404 - mmseg - INFO - Iter [121750/160000] lr: 2.344e-06, eta: 3:16:41, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7980, loss: 0.0809 2023-03-04 07:17:24,639 - mmseg - INFO - Iter [121800/160000] lr: 2.344e-06, eta: 3:16:24, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9279, loss: 0.0767 2023-03-04 07:17:39,061 - mmseg - INFO - Iter [121850/160000] lr: 2.344e-06, eta: 3:16:09, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8661, loss: 0.0788 2023-03-04 07:17:51,291 - mmseg - INFO - Iter [121900/160000] lr: 2.344e-06, eta: 3:15:52, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9376, loss: 0.0772 2023-03-04 07:18:03,470 - mmseg - INFO - Iter [121950/160000] lr: 2.344e-06, eta: 3:15:36, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8090, loss: 0.0792 2023-03-04 07:18:15,613 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:18:15,613 - mmseg - INFO - Iter [122000/160000] lr: 2.344e-06, eta: 3:15:19, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8945, loss: 0.0779 2023-03-04 07:18:30,167 - mmseg - INFO - Iter [122050/160000] lr: 2.344e-06, eta: 3:15:04, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7873, loss: 0.0825 2023-03-04 07:18:42,640 - mmseg - INFO - Iter [122100/160000] lr: 2.344e-06, eta: 3:14:47, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8407, loss: 0.0795 2023-03-04 07:18:54,911 - mmseg - INFO - Iter [122150/160000] lr: 2.344e-06, eta: 3:14:31, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.9018, loss: 0.0801 2023-03-04 07:19:07,197 - mmseg - INFO - Iter [122200/160000] lr: 2.344e-06, eta: 3:14:15, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8180, loss: 0.0804 2023-03-04 07:19:21,797 - mmseg - INFO - Iter [122250/160000] lr: 2.344e-06, eta: 3:13:59, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0755, decode.acc_seg: 97.0043, loss: 0.0755 2023-03-04 07:19:34,177 - mmseg - INFO - Iter [122300/160000] lr: 2.344e-06, eta: 3:13:43, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8350, loss: 0.0809 2023-03-04 07:19:46,376 - mmseg - INFO - Iter [122350/160000] lr: 2.344e-06, eta: 3:13:26, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9198, loss: 0.0774 2023-03-04 07:20:00,875 - mmseg - INFO - Iter [122400/160000] lr: 2.344e-06, eta: 3:13:11, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8839, loss: 0.0792 2023-03-04 07:20:13,090 - mmseg - INFO - Iter [122450/160000] lr: 2.344e-06, eta: 3:12:54, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8498, loss: 0.0798 2023-03-04 07:20:25,227 - mmseg - INFO - Iter [122500/160000] lr: 2.344e-06, eta: 3:12:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7990, loss: 0.0812 2023-03-04 07:20:37,438 - mmseg - INFO - Iter [122550/160000] lr: 2.344e-06, eta: 3:12:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8019, loss: 0.0797 2023-03-04 07:20:52,061 - mmseg - INFO - Iter [122600/160000] lr: 2.344e-06, eta: 3:12:06, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7512, loss: 0.0823 2023-03-04 07:21:04,210 - mmseg - INFO - Iter [122650/160000] lr: 2.344e-06, eta: 3:11:49, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7835, loss: 0.0822 2023-03-04 07:21:16,287 - mmseg - INFO - Iter [122700/160000] lr: 2.344e-06, eta: 3:11:33, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8524, loss: 0.0794 2023-03-04 07:21:28,491 - mmseg - INFO - Iter [122750/160000] lr: 2.344e-06, eta: 3:11:16, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8514, loss: 0.0796 2023-03-04 07:21:43,084 - mmseg - INFO - Iter [122800/160000] lr: 2.344e-06, eta: 3:11:01, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9487, loss: 0.0766 2023-03-04 07:21:55,207 - mmseg - INFO - Iter [122850/160000] lr: 2.344e-06, eta: 3:10:44, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0839, decode.acc_seg: 96.8257, loss: 0.0839 2023-03-04 07:22:07,350 - mmseg - INFO - Iter [122900/160000] lr: 2.344e-06, eta: 3:10:28, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7380, loss: 0.0810 2023-03-04 07:22:21,802 - mmseg - INFO - Iter [122950/160000] lr: 2.344e-06, eta: 3:10:12, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0848, decode.acc_seg: 96.6768, loss: 0.0848 2023-03-04 07:22:34,022 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:22:34,022 - mmseg - INFO - Iter [123000/160000] lr: 2.344e-06, eta: 3:09:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8435, loss: 0.0800 2023-03-04 07:22:46,241 - mmseg - INFO - Iter [123050/160000] lr: 2.344e-06, eta: 3:09:40, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7957, loss: 0.0805 2023-03-04 07:22:58,358 - mmseg - INFO - Iter [123100/160000] lr: 2.344e-06, eta: 3:09:23, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9090, loss: 0.0774 2023-03-04 07:23:12,735 - mmseg - INFO - Iter [123150/160000] lr: 2.344e-06, eta: 3:09:08, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8422, loss: 0.0798 2023-03-04 07:23:24,787 - mmseg - INFO - Iter [123200/160000] lr: 2.344e-06, eta: 3:08:51, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9393, loss: 0.0769 2023-03-04 07:23:36,908 - mmseg - INFO - Iter [123250/160000] lr: 2.344e-06, eta: 3:08:35, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.6954, loss: 0.0831 2023-03-04 07:23:48,954 - mmseg - INFO - Iter [123300/160000] lr: 2.344e-06, eta: 3:08:18, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9025, loss: 0.0778 2023-03-04 07:24:03,428 - mmseg - INFO - Iter [123350/160000] lr: 2.344e-06, eta: 3:08:03, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8563, loss: 0.0801 2023-03-04 07:24:15,588 - mmseg - INFO - Iter [123400/160000] lr: 2.344e-06, eta: 3:07:46, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8397, loss: 0.0785 2023-03-04 07:24:27,657 - mmseg - INFO - Iter [123450/160000] lr: 2.344e-06, eta: 3:07:30, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9075, loss: 0.0775 2023-03-04 07:24:39,937 - mmseg - INFO - Iter [123500/160000] lr: 2.344e-06, eta: 3:07:14, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 97.0393, loss: 0.0762 2023-03-04 07:24:54,431 - mmseg - INFO - Iter [123550/160000] lr: 2.344e-06, eta: 3:06:58, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.6970, loss: 0.0853 2023-03-04 07:25:06,791 - mmseg - INFO - Iter [123600/160000] lr: 2.344e-06, eta: 3:06:42, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8537, loss: 0.0791 2023-03-04 07:25:18,891 - mmseg - INFO - Iter [123650/160000] lr: 2.344e-06, eta: 3:06:25, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9184, loss: 0.0783 2023-03-04 07:25:33,611 - mmseg - INFO - Iter [123700/160000] lr: 2.344e-06, eta: 3:06:10, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8399, loss: 0.0805 2023-03-04 07:25:45,896 - mmseg - INFO - Iter [123750/160000] lr: 2.344e-06, eta: 3:05:54, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0838, decode.acc_seg: 96.7757, loss: 0.0838 2023-03-04 07:25:58,027 - mmseg - INFO - Iter [123800/160000] lr: 2.344e-06, eta: 3:05:37, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0856, decode.acc_seg: 96.8458, loss: 0.0856 2023-03-04 07:26:10,270 - mmseg - INFO - Iter [123850/160000] lr: 2.344e-06, eta: 3:05:21, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8596, loss: 0.0796 2023-03-04 07:26:24,809 - mmseg - INFO - Iter [123900/160000] lr: 2.344e-06, eta: 3:05:05, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7482, loss: 0.0830 2023-03-04 07:26:36,875 - mmseg - INFO - Iter [123950/160000] lr: 2.344e-06, eta: 3:04:49, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8669, loss: 0.0800 2023-03-04 07:26:49,050 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:26:49,050 - mmseg - INFO - Iter [124000/160000] lr: 2.344e-06, eta: 3:04:33, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9160, loss: 0.0784 2023-03-04 07:27:01,137 - mmseg - INFO - Iter [124050/160000] lr: 2.344e-06, eta: 3:04:16, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9334, loss: 0.0772 2023-03-04 07:27:15,651 - mmseg - INFO - Iter [124100/160000] lr: 2.344e-06, eta: 3:04:01, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9372, loss: 0.0761 2023-03-04 07:27:27,804 - mmseg - INFO - Iter [124150/160000] lr: 2.344e-06, eta: 3:03:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8224, loss: 0.0815 2023-03-04 07:27:39,912 - mmseg - INFO - Iter [124200/160000] lr: 2.344e-06, eta: 3:03:28, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8664, loss: 0.0792 2023-03-04 07:27:54,377 - mmseg - INFO - Iter [124250/160000] lr: 2.344e-06, eta: 3:03:12, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7712, loss: 0.0805 2023-03-04 07:28:06,610 - mmseg - INFO - Iter [124300/160000] lr: 2.344e-06, eta: 3:02:56, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7968, loss: 0.0805 2023-03-04 07:28:18,741 - mmseg - INFO - Iter [124350/160000] lr: 2.344e-06, eta: 3:02:40, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8522, loss: 0.0795 2023-03-04 07:28:30,988 - mmseg - INFO - Iter [124400/160000] lr: 2.344e-06, eta: 3:02:24, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8165, loss: 0.0806 2023-03-04 07:28:45,565 - mmseg - INFO - Iter [124450/160000] lr: 2.344e-06, eta: 3:02:08, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9129, loss: 0.0782 2023-03-04 07:28:57,671 - mmseg - INFO - Iter [124500/160000] lr: 2.344e-06, eta: 3:01:52, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8576, loss: 0.0792 2023-03-04 07:29:09,929 - mmseg - INFO - Iter [124550/160000] lr: 2.344e-06, eta: 3:01:35, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8606, loss: 0.0793 2023-03-04 07:29:22,096 - mmseg - INFO - Iter [124600/160000] lr: 2.344e-06, eta: 3:01:19, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8433, loss: 0.0791 2023-03-04 07:29:36,642 - mmseg - INFO - Iter [124650/160000] lr: 2.344e-06, eta: 3:01:03, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8984, loss: 0.0779 2023-03-04 07:29:48,888 - mmseg - INFO - Iter [124700/160000] lr: 2.344e-06, eta: 3:00:47, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9066, loss: 0.0775 2023-03-04 07:30:01,050 - mmseg - INFO - Iter [124750/160000] lr: 2.344e-06, eta: 3:00:31, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8727, loss: 0.0814 2023-03-04 07:30:13,267 - mmseg - INFO - Iter [124800/160000] lr: 2.344e-06, eta: 3:00:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7813, loss: 0.0823 2023-03-04 07:30:27,844 - mmseg - INFO - Iter [124850/160000] lr: 2.344e-06, eta: 2:59:59, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8019, loss: 0.0809 2023-03-04 07:30:39,942 - mmseg - INFO - Iter [124900/160000] lr: 2.344e-06, eta: 2:59:43, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8733, loss: 0.0789 2023-03-04 07:30:52,191 - mmseg - INFO - Iter [124950/160000] lr: 2.344e-06, eta: 2:59:27, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9290, loss: 0.0778 2023-03-04 07:31:06,682 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:31:06,682 - mmseg - INFO - Iter [125000/160000] lr: 2.344e-06, eta: 2:59:11, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8308, loss: 0.0801 2023-03-04 07:31:18,851 - mmseg - INFO - Iter [125050/160000] lr: 2.344e-06, eta: 2:58:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8791, loss: 0.0783 2023-03-04 07:31:31,150 - mmseg - INFO - Iter [125100/160000] lr: 2.344e-06, eta: 2:58:39, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8888, loss: 0.0782 2023-03-04 07:31:43,274 - mmseg - INFO - Iter [125150/160000] lr: 2.344e-06, eta: 2:58:22, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9597, loss: 0.0770 2023-03-04 07:31:57,866 - mmseg - INFO - Iter [125200/160000] lr: 2.344e-06, eta: 2:58:07, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8103, loss: 0.0805 2023-03-04 07:32:10,145 - mmseg - INFO - Iter [125250/160000] lr: 2.344e-06, eta: 2:57:51, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8409, loss: 0.0804 2023-03-04 07:32:22,351 - mmseg - INFO - Iter [125300/160000] lr: 2.344e-06, eta: 2:57:34, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8955, loss: 0.0784 2023-03-04 07:32:34,526 - mmseg - INFO - Iter [125350/160000] lr: 2.344e-06, eta: 2:57:18, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9154, loss: 0.0778 2023-03-04 07:32:49,044 - mmseg - INFO - Iter [125400/160000] lr: 2.344e-06, eta: 2:57:02, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7921, loss: 0.0807 2023-03-04 07:33:01,189 - mmseg - INFO - Iter [125450/160000] lr: 2.344e-06, eta: 2:56:46, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8315, loss: 0.0800 2023-03-04 07:33:13,519 - mmseg - INFO - Iter [125500/160000] lr: 2.344e-06, eta: 2:56:30, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9334, loss: 0.0778 2023-03-04 07:33:25,661 - mmseg - INFO - Iter [125550/160000] lr: 2.344e-06, eta: 2:56:14, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8481, loss: 0.0799 2023-03-04 07:33:40,245 - mmseg - INFO - Iter [125600/160000] lr: 2.344e-06, eta: 2:55:58, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7302, loss: 0.0818 2023-03-04 07:33:52,423 - mmseg - INFO - Iter [125650/160000] lr: 2.344e-06, eta: 2:55:42, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8876, loss: 0.0788 2023-03-04 07:34:04,600 - mmseg - INFO - Iter [125700/160000] lr: 2.344e-06, eta: 2:55:26, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9639, loss: 0.0765 2023-03-04 07:34:19,158 - mmseg - INFO - Iter [125750/160000] lr: 2.344e-06, eta: 2:55:10, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8690, loss: 0.0787 2023-03-04 07:34:31,333 - mmseg - INFO - Iter [125800/160000] lr: 2.344e-06, eta: 2:54:54, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.7888, loss: 0.0804 2023-03-04 07:34:43,562 - mmseg - INFO - Iter [125850/160000] lr: 2.344e-06, eta: 2:54:38, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8021, loss: 0.0795 2023-03-04 07:34:55,758 - mmseg - INFO - Iter [125900/160000] lr: 2.344e-06, eta: 2:54:22, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9600, loss: 0.0769 2023-03-04 07:35:10,286 - mmseg - INFO - Iter [125950/160000] lr: 2.344e-06, eta: 2:54:06, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7562, loss: 0.0815 2023-03-04 07:35:22,452 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:35:22,453 - mmseg - INFO - Iter [126000/160000] lr: 2.344e-06, eta: 2:53:50, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 96.9895, loss: 0.0754 2023-03-04 07:35:34,592 - mmseg - INFO - Iter [126050/160000] lr: 2.344e-06, eta: 2:53:34, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8214, loss: 0.0799 2023-03-04 07:35:46,771 - mmseg - INFO - Iter [126100/160000] lr: 2.344e-06, eta: 2:53:18, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8977, loss: 0.0785 2023-03-04 07:36:01,220 - mmseg - INFO - Iter [126150/160000] lr: 2.344e-06, eta: 2:53:02, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9231, loss: 0.0766 2023-03-04 07:36:13,402 - mmseg - INFO - Iter [126200/160000] lr: 2.344e-06, eta: 2:52:46, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9384, loss: 0.0777 2023-03-04 07:36:25,714 - mmseg - INFO - Iter [126250/160000] lr: 2.344e-06, eta: 2:52:30, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8263, loss: 0.0797 2023-03-04 07:36:40,133 - mmseg - INFO - Iter [126300/160000] lr: 2.344e-06, eta: 2:52:14, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8670, loss: 0.0794 2023-03-04 07:36:52,367 - mmseg - INFO - Iter [126350/160000] lr: 2.344e-06, eta: 2:51:58, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0737, decode.acc_seg: 97.0518, loss: 0.0737 2023-03-04 07:37:04,523 - mmseg - INFO - Iter [126400/160000] lr: 2.344e-06, eta: 2:51:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8209, loss: 0.0795 2023-03-04 07:37:16,628 - mmseg - INFO - Iter [126450/160000] lr: 2.344e-06, eta: 2:51:26, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9229, loss: 0.0777 2023-03-04 07:37:31,137 - mmseg - INFO - Iter [126500/160000] lr: 2.344e-06, eta: 2:51:10, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7505, loss: 0.0830 2023-03-04 07:37:43,434 - mmseg - INFO - Iter [126550/160000] lr: 2.344e-06, eta: 2:50:54, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8194, loss: 0.0805 2023-03-04 07:37:55,527 - mmseg - INFO - Iter [126600/160000] lr: 2.344e-06, eta: 2:50:38, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9142, loss: 0.0788 2023-03-04 07:38:07,711 - mmseg - INFO - Iter [126650/160000] lr: 2.344e-06, eta: 2:50:22, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8845, loss: 0.0781 2023-03-04 07:38:22,228 - mmseg - INFO - Iter [126700/160000] lr: 2.344e-06, eta: 2:50:06, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9492, loss: 0.0776 2023-03-04 07:38:34,406 - mmseg - INFO - Iter [126750/160000] lr: 2.344e-06, eta: 2:49:50, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9243, loss: 0.0773 2023-03-04 07:38:46,560 - mmseg - INFO - Iter [126800/160000] lr: 2.344e-06, eta: 2:49:34, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8337, loss: 0.0796 2023-03-04 07:38:58,688 - mmseg - INFO - Iter [126850/160000] lr: 2.344e-06, eta: 2:49:18, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9101, loss: 0.0780 2023-03-04 07:39:13,220 - mmseg - INFO - Iter [126900/160000] lr: 2.344e-06, eta: 2:49:02, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.7461, loss: 0.0818 2023-03-04 07:39:25,450 - mmseg - INFO - Iter [126950/160000] lr: 2.344e-06, eta: 2:48:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0760, decode.acc_seg: 96.9613, loss: 0.0760 2023-03-04 07:39:37,741 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:39:37,741 - mmseg - INFO - Iter [127000/160000] lr: 2.344e-06, eta: 2:48:30, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7566, loss: 0.0812 2023-03-04 07:39:52,276 - mmseg - INFO - Iter [127050/160000] lr: 2.344e-06, eta: 2:48:14, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9119, loss: 0.0785 2023-03-04 07:40:04,459 - mmseg - INFO - Iter [127100/160000] lr: 2.344e-06, eta: 2:47:58, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7412, loss: 0.0834 2023-03-04 07:40:16,601 - mmseg - INFO - Iter [127150/160000] lr: 2.344e-06, eta: 2:47:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7903, loss: 0.0817 2023-03-04 07:40:28,883 - mmseg - INFO - Iter [127200/160000] lr: 2.344e-06, eta: 2:47:26, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9393, loss: 0.0775 2023-03-04 07:40:43,365 - mmseg - INFO - Iter [127250/160000] lr: 2.344e-06, eta: 2:47:10, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9309, loss: 0.0768 2023-03-04 07:40:55,600 - mmseg - INFO - Iter [127300/160000] lr: 2.344e-06, eta: 2:46:54, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8385, loss: 0.0798 2023-03-04 07:41:07,899 - mmseg - INFO - Iter [127350/160000] lr: 2.344e-06, eta: 2:46:38, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8618, loss: 0.0787 2023-03-04 07:41:19,931 - mmseg - INFO - Iter [127400/160000] lr: 2.344e-06, eta: 2:46:22, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8005, loss: 0.0801 2023-03-04 07:41:34,566 - mmseg - INFO - Iter [127450/160000] lr: 2.344e-06, eta: 2:46:07, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8252, loss: 0.0795 2023-03-04 07:41:46,845 - mmseg - INFO - Iter [127500/160000] lr: 2.344e-06, eta: 2:45:50, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8868, loss: 0.0790 2023-03-04 07:41:59,058 - mmseg - INFO - Iter [127550/160000] lr: 2.344e-06, eta: 2:45:34, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0855, decode.acc_seg: 96.7109, loss: 0.0855 2023-03-04 07:42:13,662 - mmseg - INFO - Iter [127600/160000] lr: 2.344e-06, eta: 2:45:19, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9062, loss: 0.0781 2023-03-04 07:42:25,849 - mmseg - INFO - Iter [127650/160000] lr: 2.344e-06, eta: 2:45:03, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9708, loss: 0.0776 2023-03-04 07:42:38,126 - mmseg - INFO - Iter [127700/160000] lr: 2.344e-06, eta: 2:44:47, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9408, loss: 0.0780 2023-03-04 07:42:50,249 - mmseg - INFO - Iter [127750/160000] lr: 2.344e-06, eta: 2:44:31, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8649, loss: 0.0787 2023-03-04 07:43:04,715 - mmseg - INFO - Iter [127800/160000] lr: 2.344e-06, eta: 2:44:15, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8296, loss: 0.0811 2023-03-04 07:43:16,925 - mmseg - INFO - Iter [127850/160000] lr: 2.344e-06, eta: 2:43:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7801, loss: 0.0822 2023-03-04 07:43:29,073 - mmseg - INFO - Iter [127900/160000] lr: 2.344e-06, eta: 2:43:43, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8508, loss: 0.0801 2023-03-04 07:43:41,166 - mmseg - INFO - Iter [127950/160000] lr: 2.344e-06, eta: 2:43:27, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8008, loss: 0.0804 2023-03-04 07:43:55,752 - mmseg - INFO - Swap parameters (after train) after iter [128000] 2023-03-04 07:43:55,767 - mmseg - INFO - Saving checkpoint at 128000 iterations 2023-03-04 07:43:57,314 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:43:57,314 - mmseg - INFO - Iter [128000/160000] lr: 2.344e-06, eta: 2:43:12, time: 0.323, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9493, loss: 0.0776 2023-03-04 07:58:51,200 - mmseg - INFO - per class results: 2023-03-04 07:58:51,201 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.58,98.58,98.58,98.59,98.58,98.59,98.59,98.59,98.59,98.59,98.59 | | sidewalk | 87.81,87.83,87.85,87.88,87.86,87.89,87.92,87.92,87.93,87.96,87.93 | | building | 93.34,93.33,93.34,93.34,93.34,93.35,93.34,93.35,93.34,93.34,93.35 | | wall | 54.38,54.47,54.64,54.75,54.86,55.0,54.9,55.04,55.08,55.07,55.11 | | fence | 63.41,63.42,63.45,63.47,63.37,63.45,63.28,63.3,63.29,63.32,63.22 | | pole | 70.98,70.98,70.99,71.01,70.99,71.01,71.01,71.01,71.0,71.01,71.01 | | traffic light | 75.51,75.5,75.53,75.52,75.52,75.52,75.52,75.51,75.51,75.52,75.5 | | traffic sign | 83.29,83.28,83.31,83.32,83.31,83.33,83.34,83.35,83.36,83.37,83.37 | | vegetation | 92.92,92.92,92.93,92.93,92.94,92.94,92.95,92.95,92.95,92.95,92.94 | | terrain | 65.66,65.8,65.9,66.04,66.13,66.2,66.36,66.44,66.49,66.46,66.47 | | sky | 95.24,95.25,95.25,95.25,95.25,95.25,95.25,95.25,95.25,95.25,95.26 | | person | 84.75,84.75,84.77,84.78,84.77,84.79,84.78,84.8,84.79,84.79,84.81 | | rider | 67.09,67.1,67.18,67.2,67.21,67.25,67.24,67.32,67.3,67.29,67.34 | | car | 95.91,95.94,95.97,95.98,95.99,96.0,96.0,96.0,96.0,96.0,96.0 | | truck | 84.37,84.97,85.49,85.86,86.09,86.1,86.2,86.2,86.17,86.1,86.04 | | bus | 92.26,92.28,92.3,92.31,92.33,92.34,92.37,92.39,92.39,92.42,92.36 | | train | 85.87,85.9,85.91,85.93,86.01,85.94,86.05,86.0,86.02,86.0,86.0 | | motorcycle | 69.64,69.66,69.64,69.62,69.65,69.58,69.63,69.63,69.6,69.6,69.6 | | bicycle | 79.84,79.86,79.86,79.86,79.89,79.89,79.9,79.9,79.91,79.91,79.91 | +---------------+-------------------------------------------------------------------+ 2023-03-04 07:58:51,201 - mmseg - INFO - Summary: 2023-03-04 07:58:51,201 - mmseg - INFO - +----------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +----------------------------------------------------------------+ | 81.1,81.15,81.2,81.24,81.27,81.28,81.3,81.31,81.31,81.31,81.31 | +----------------------------------------------------------------+ 2023-03-04 07:58:51,201 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 07:58:51,201 - mmseg - INFO - Iter(val) [63] mIoU: [0.811, 0.8115, 0.812, 0.8124, 0.8127, 0.8128, 0.813, 0.8131, 0.8131, 0.8131, 0.8131], copy_paste: 81.1,81.15,81.2,81.24,81.27,81.28,81.3,81.31,81.31,81.31,81.31 2023-03-04 07:58:51,209 - mmseg - INFO - Swap parameters (before train) before iter [128001] 2023-03-04 07:59:03,756 - mmseg - INFO - Iter [128050/160000] lr: 2.344e-06, eta: 2:46:39, time: 18.129, data_time: 17.886, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8821, loss: 0.0789 2023-03-04 07:59:16,200 - mmseg - INFO - Iter [128100/160000] lr: 2.344e-06, eta: 2:46:22, time: 0.249, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9853, loss: 0.0765 2023-03-04 07:59:28,561 - mmseg - INFO - Iter [128150/160000] lr: 2.344e-06, eta: 2:46:06, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7771, loss: 0.0807 2023-03-04 07:59:43,148 - mmseg - INFO - Iter [128200/160000] lr: 2.344e-06, eta: 2:45:50, time: 0.292, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.7969, loss: 0.0799 2023-03-04 07:59:55,409 - mmseg - INFO - Iter [128250/160000] lr: 2.344e-06, eta: 2:45:33, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7607, loss: 0.0816 2023-03-04 08:00:07,763 - mmseg - INFO - Iter [128300/160000] lr: 2.344e-06, eta: 2:45:17, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9434, loss: 0.0762 2023-03-04 08:00:22,364 - mmseg - INFO - Iter [128350/160000] lr: 2.344e-06, eta: 2:45:01, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0752, decode.acc_seg: 97.0182, loss: 0.0752 2023-03-04 08:00:34,730 - mmseg - INFO - Iter [128400/160000] lr: 2.344e-06, eta: 2:44:45, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8790, loss: 0.0787 2023-03-04 08:00:46,988 - mmseg - INFO - Iter [128450/160000] lr: 2.344e-06, eta: 2:44:28, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 97.0072, loss: 0.0754 2023-03-04 08:00:59,182 - mmseg - INFO - Iter [128500/160000] lr: 2.344e-06, eta: 2:44:12, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9577, loss: 0.0768 2023-03-04 08:01:13,779 - mmseg - INFO - Iter [128550/160000] lr: 2.344e-06, eta: 2:43:56, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8748, loss: 0.0793 2023-03-04 08:01:26,024 - mmseg - INFO - Iter [128600/160000] lr: 2.344e-06, eta: 2:43:39, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9555, loss: 0.0763 2023-03-04 08:01:38,280 - mmseg - INFO - Iter [128650/160000] lr: 2.344e-06, eta: 2:43:23, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8441, loss: 0.0796 2023-03-04 08:01:50,476 - mmseg - INFO - Iter [128700/160000] lr: 2.344e-06, eta: 2:43:06, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.7465, loss: 0.0813 2023-03-04 08:02:05,020 - mmseg - INFO - Iter [128750/160000] lr: 2.344e-06, eta: 2:42:51, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.7393, loss: 0.0843 2023-03-04 08:02:17,153 - mmseg - INFO - Iter [128800/160000] lr: 2.344e-06, eta: 2:42:34, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8880, loss: 0.0790 2023-03-04 08:02:29,489 - mmseg - INFO - Iter [128850/160000] lr: 2.344e-06, eta: 2:42:18, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9085, loss: 0.0784 2023-03-04 08:02:44,054 - mmseg - INFO - Iter [128900/160000] lr: 2.344e-06, eta: 2:42:02, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7806, loss: 0.0822 2023-03-04 08:02:56,323 - mmseg - INFO - Iter [128950/160000] lr: 2.344e-06, eta: 2:41:45, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.9063, loss: 0.0797 2023-03-04 08:03:08,423 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:03:08,423 - mmseg - INFO - Iter [129000/160000] lr: 2.344e-06, eta: 2:41:29, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8780, loss: 0.0787 2023-03-04 08:03:20,677 - mmseg - INFO - Iter [129050/160000] lr: 2.344e-06, eta: 2:41:12, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8654, loss: 0.0793 2023-03-04 08:03:35,225 - mmseg - INFO - Iter [129100/160000] lr: 2.344e-06, eta: 2:40:56, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9548, loss: 0.0771 2023-03-04 08:03:47,373 - mmseg - INFO - Iter [129150/160000] lr: 2.344e-06, eta: 2:40:40, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8155, loss: 0.0808 2023-03-04 08:03:59,609 - mmseg - INFO - Iter [129200/160000] lr: 2.344e-06, eta: 2:40:24, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8638, loss: 0.0791 2023-03-04 08:04:11,826 - mmseg - INFO - Iter [129250/160000] lr: 2.344e-06, eta: 2:40:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8241, loss: 0.0795 2023-03-04 08:04:26,401 - mmseg - INFO - Iter [129300/160000] lr: 2.344e-06, eta: 2:39:51, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8558, loss: 0.0809 2023-03-04 08:04:38,592 - mmseg - INFO - Iter [129350/160000] lr: 2.344e-06, eta: 2:39:35, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8693, loss: 0.0789 2023-03-04 08:04:50,742 - mmseg - INFO - Iter [129400/160000] lr: 2.344e-06, eta: 2:39:18, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8340, loss: 0.0796 2023-03-04 08:05:03,005 - mmseg - INFO - Iter [129450/160000] lr: 2.344e-06, eta: 2:39:02, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8343, loss: 0.0799 2023-03-04 08:05:17,557 - mmseg - INFO - Iter [129500/160000] lr: 2.344e-06, eta: 2:38:46, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8168, loss: 0.0810 2023-03-04 08:05:29,767 - mmseg - INFO - Iter [129550/160000] lr: 2.344e-06, eta: 2:38:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9270, loss: 0.0771 2023-03-04 08:05:41,949 - mmseg - INFO - Iter [129600/160000] lr: 2.344e-06, eta: 2:38:13, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8612, loss: 0.0790 2023-03-04 08:05:56,464 - mmseg - INFO - Iter [129650/160000] lr: 2.344e-06, eta: 2:37:57, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8399, loss: 0.0797 2023-03-04 08:06:08,808 - mmseg - INFO - Iter [129700/160000] lr: 2.344e-06, eta: 2:37:41, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9247, loss: 0.0777 2023-03-04 08:06:21,216 - mmseg - INFO - Iter [129750/160000] lr: 2.344e-06, eta: 2:37:25, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7881, loss: 0.0809 2023-03-04 08:06:33,339 - mmseg - INFO - Iter [129800/160000] lr: 2.344e-06, eta: 2:37:08, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9072, loss: 0.0782 2023-03-04 08:06:47,862 - mmseg - INFO - Iter [129850/160000] lr: 2.344e-06, eta: 2:36:52, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8452, loss: 0.0798 2023-03-04 08:07:00,130 - mmseg - INFO - Iter [129900/160000] lr: 2.344e-06, eta: 2:36:36, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7386, loss: 0.0814 2023-03-04 08:07:12,343 - mmseg - INFO - Iter [129950/160000] lr: 2.344e-06, eta: 2:36:20, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9221, loss: 0.0772 2023-03-04 08:07:24,462 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:07:24,462 - mmseg - INFO - Iter [130000/160000] lr: 2.344e-06, eta: 2:36:03, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8267, loss: 0.0808 2023-03-04 08:07:39,025 - mmseg - INFO - Iter [130050/160000] lr: 2.344e-06, eta: 2:35:47, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0847, decode.acc_seg: 96.6739, loss: 0.0847 2023-03-04 08:07:51,123 - mmseg - INFO - Iter [130100/160000] lr: 2.344e-06, eta: 2:35:31, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9777, loss: 0.0765 2023-03-04 08:08:03,262 - mmseg - INFO - Iter [130150/160000] lr: 2.344e-06, eta: 2:35:15, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8682, loss: 0.0779 2023-03-04 08:08:15,421 - mmseg - INFO - Iter [130200/160000] lr: 2.344e-06, eta: 2:34:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8725, loss: 0.0790 2023-03-04 08:08:30,125 - mmseg - INFO - Iter [130250/160000] lr: 2.344e-06, eta: 2:34:42, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9222, loss: 0.0774 2023-03-04 08:08:42,333 - mmseg - INFO - Iter [130300/160000] lr: 2.344e-06, eta: 2:34:26, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8335, loss: 0.0805 2023-03-04 08:08:54,532 - mmseg - INFO - Iter [130350/160000] lr: 2.344e-06, eta: 2:34:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9283, loss: 0.0773 2023-03-04 08:09:09,041 - mmseg - INFO - Iter [130400/160000] lr: 2.344e-06, eta: 2:33:54, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8786, loss: 0.0801 2023-03-04 08:09:21,228 - mmseg - INFO - Iter [130450/160000] lr: 2.344e-06, eta: 2:33:37, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9235, loss: 0.0771 2023-03-04 08:09:33,384 - mmseg - INFO - Iter [130500/160000] lr: 2.344e-06, eta: 2:33:21, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7607, loss: 0.0822 2023-03-04 08:09:45,556 - mmseg - INFO - Iter [130550/160000] lr: 2.344e-06, eta: 2:33:05, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8692, loss: 0.0781 2023-03-04 08:09:59,993 - mmseg - INFO - Iter [130600/160000] lr: 2.344e-06, eta: 2:32:49, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9074, loss: 0.0772 2023-03-04 08:10:12,301 - mmseg - INFO - Iter [130650/160000] lr: 2.344e-06, eta: 2:32:32, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0853, decode.acc_seg: 96.7039, loss: 0.0853 2023-03-04 08:10:24,606 - mmseg - INFO - Iter [130700/160000] lr: 2.344e-06, eta: 2:32:16, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8269, loss: 0.0813 2023-03-04 08:10:36,707 - mmseg - INFO - Iter [130750/160000] lr: 2.344e-06, eta: 2:32:00, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9615, loss: 0.0762 2023-03-04 08:10:51,265 - mmseg - INFO - Iter [130800/160000] lr: 2.344e-06, eta: 2:31:44, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8557, loss: 0.0788 2023-03-04 08:11:03,379 - mmseg - INFO - Iter [130850/160000] lr: 2.344e-06, eta: 2:31:28, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8809, loss: 0.0787 2023-03-04 08:11:15,568 - mmseg - INFO - Iter [130900/160000] lr: 2.344e-06, eta: 2:31:11, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9189, loss: 0.0781 2023-03-04 08:11:29,994 - mmseg - INFO - Iter [130950/160000] lr: 2.344e-06, eta: 2:30:55, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9730, loss: 0.0765 2023-03-04 08:11:42,144 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:11:42,145 - mmseg - INFO - Iter [131000/160000] lr: 2.344e-06, eta: 2:30:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8586, loss: 0.0787 2023-03-04 08:11:54,343 - mmseg - INFO - Iter [131050/160000] lr: 2.344e-06, eta: 2:30:23, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8256, loss: 0.0802 2023-03-04 08:12:06,478 - mmseg - INFO - Iter [131100/160000] lr: 2.344e-06, eta: 2:30:06, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.8216, loss: 0.0812 2023-03-04 08:12:21,018 - mmseg - INFO - Iter [131150/160000] lr: 2.344e-06, eta: 2:29:51, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9372, loss: 0.0771 2023-03-04 08:12:33,265 - mmseg - INFO - Iter [131200/160000] lr: 2.344e-06, eta: 2:29:34, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9733, loss: 0.0761 2023-03-04 08:12:45,499 - mmseg - INFO - Iter [131250/160000] lr: 2.344e-06, eta: 2:29:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8592, loss: 0.0793 2023-03-04 08:12:57,679 - mmseg - INFO - Iter [131300/160000] lr: 2.344e-06, eta: 2:29:02, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8299, loss: 0.0795 2023-03-04 08:13:12,227 - mmseg - INFO - Iter [131350/160000] lr: 2.344e-06, eta: 2:28:46, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.9019, loss: 0.0789 2023-03-04 08:13:24,411 - mmseg - INFO - Iter [131400/160000] lr: 2.344e-06, eta: 2:28:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7628, loss: 0.0806 2023-03-04 08:13:36,602 - mmseg - INFO - Iter [131450/160000] lr: 2.344e-06, eta: 2:28:13, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7687, loss: 0.0806 2023-03-04 08:13:48,707 - mmseg - INFO - Iter [131500/160000] lr: 2.344e-06, eta: 2:27:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9096, loss: 0.0778 2023-03-04 08:14:03,207 - mmseg - INFO - Iter [131550/160000] lr: 2.344e-06, eta: 2:27:41, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9020, loss: 0.0774 2023-03-04 08:14:15,379 - mmseg - INFO - Iter [131600/160000] lr: 2.344e-06, eta: 2:27:25, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9284, loss: 0.0765 2023-03-04 08:14:27,519 - mmseg - INFO - Iter [131650/160000] lr: 2.344e-06, eta: 2:27:08, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8767, loss: 0.0795 2023-03-04 08:14:41,982 - mmseg - INFO - Iter [131700/160000] lr: 2.344e-06, eta: 2:26:53, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8859, loss: 0.0786 2023-03-04 08:14:54,140 - mmseg - INFO - Iter [131750/160000] lr: 2.344e-06, eta: 2:26:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9701, loss: 0.0763 2023-03-04 08:15:06,263 - mmseg - INFO - Iter [131800/160000] lr: 2.344e-06, eta: 2:26:20, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8591, loss: 0.0805 2023-03-04 08:15:18,490 - mmseg - INFO - Iter [131850/160000] lr: 2.344e-06, eta: 2:26:04, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8762, loss: 0.0790 2023-03-04 08:15:33,038 - mmseg - INFO - Iter [131900/160000] lr: 2.344e-06, eta: 2:25:48, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8668, loss: 0.0787 2023-03-04 08:15:45,198 - mmseg - INFO - Iter [131950/160000] lr: 2.344e-06, eta: 2:25:32, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.8909, loss: 0.0777 2023-03-04 08:15:57,404 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:15:57,404 - mmseg - INFO - Iter [132000/160000] lr: 2.344e-06, eta: 2:25:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8331, loss: 0.0804 2023-03-04 08:16:09,647 - mmseg - INFO - Iter [132050/160000] lr: 2.344e-06, eta: 2:24:59, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0837, decode.acc_seg: 96.7071, loss: 0.0837 2023-03-04 08:16:24,162 - mmseg - INFO - Iter [132100/160000] lr: 2.344e-06, eta: 2:24:43, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9012, loss: 0.0787 2023-03-04 08:16:36,365 - mmseg - INFO - Iter [132150/160000] lr: 2.344e-06, eta: 2:24:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0818, decode.acc_seg: 96.8167, loss: 0.0818 2023-03-04 08:16:48,575 - mmseg - INFO - Iter [132200/160000] lr: 2.344e-06, eta: 2:24:11, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8481, loss: 0.0791 2023-03-04 08:17:03,110 - mmseg - INFO - Iter [132250/160000] lr: 2.344e-06, eta: 2:23:55, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.9087, loss: 0.0794 2023-03-04 08:17:15,463 - mmseg - INFO - Iter [132300/160000] lr: 2.344e-06, eta: 2:23:39, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9430, loss: 0.0777 2023-03-04 08:17:27,588 - mmseg - INFO - Iter [132350/160000] lr: 2.344e-06, eta: 2:23:22, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8157, loss: 0.0801 2023-03-04 08:17:39,707 - mmseg - INFO - Iter [132400/160000] lr: 2.344e-06, eta: 2:23:06, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9010, loss: 0.0783 2023-03-04 08:17:54,158 - mmseg - INFO - Iter [132450/160000] lr: 2.344e-06, eta: 2:22:50, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0759, decode.acc_seg: 96.9916, loss: 0.0759 2023-03-04 08:18:06,223 - mmseg - INFO - Iter [132500/160000] lr: 2.344e-06, eta: 2:22:34, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0852, decode.acc_seg: 96.7757, loss: 0.0852 2023-03-04 08:18:18,488 - mmseg - INFO - Iter [132550/160000] lr: 2.344e-06, eta: 2:22:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8851, loss: 0.0798 2023-03-04 08:18:30,607 - mmseg - INFO - Iter [132600/160000] lr: 2.344e-06, eta: 2:22:02, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8473, loss: 0.0789 2023-03-04 08:18:45,344 - mmseg - INFO - Iter [132650/160000] lr: 2.344e-06, eta: 2:21:46, time: 0.295, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8291, loss: 0.0795 2023-03-04 08:18:57,635 - mmseg - INFO - Iter [132700/160000] lr: 2.344e-06, eta: 2:21:30, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8807, loss: 0.0782 2023-03-04 08:19:09,764 - mmseg - INFO - Iter [132750/160000] lr: 2.344e-06, eta: 2:21:13, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9600, loss: 0.0765 2023-03-04 08:19:21,940 - mmseg - INFO - Iter [132800/160000] lr: 2.344e-06, eta: 2:20:57, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7416, loss: 0.0825 2023-03-04 08:19:36,602 - mmseg - INFO - Iter [132850/160000] lr: 2.344e-06, eta: 2:20:41, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8670, loss: 0.0783 2023-03-04 08:19:48,754 - mmseg - INFO - Iter [132900/160000] lr: 2.344e-06, eta: 2:20:25, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0813, decode.acc_seg: 96.8575, loss: 0.0813 2023-03-04 08:20:01,068 - mmseg - INFO - Iter [132950/160000] lr: 2.344e-06, eta: 2:20:09, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8406, loss: 0.0809 2023-03-04 08:20:15,646 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:20:15,646 - mmseg - INFO - Iter [133000/160000] lr: 2.344e-06, eta: 2:19:53, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8120, loss: 0.0811 2023-03-04 08:20:28,005 - mmseg - INFO - Iter [133050/160000] lr: 2.344e-06, eta: 2:19:37, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9545, loss: 0.0775 2023-03-04 08:20:40,339 - mmseg - INFO - Iter [133100/160000] lr: 2.344e-06, eta: 2:19:21, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7565, loss: 0.0822 2023-03-04 08:20:52,821 - mmseg - INFO - Iter [133150/160000] lr: 2.344e-06, eta: 2:19:05, time: 0.250, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0751, decode.acc_seg: 96.9871, loss: 0.0751 2023-03-04 08:21:07,403 - mmseg - INFO - Iter [133200/160000] lr: 2.344e-06, eta: 2:18:49, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9358, loss: 0.0777 2023-03-04 08:21:19,631 - mmseg - INFO - Iter [133250/160000] lr: 2.344e-06, eta: 2:18:33, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7513, loss: 0.0811 2023-03-04 08:21:31,857 - mmseg - INFO - Iter [133300/160000] lr: 2.344e-06, eta: 2:18:17, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8810, loss: 0.0788 2023-03-04 08:21:43,995 - mmseg - INFO - Iter [133350/160000] lr: 2.344e-06, eta: 2:18:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8107, loss: 0.0806 2023-03-04 08:21:58,456 - mmseg - INFO - Iter [133400/160000] lr: 2.344e-06, eta: 2:17:45, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8411, loss: 0.0792 2023-03-04 08:22:10,573 - mmseg - INFO - Iter [133450/160000] lr: 2.344e-06, eta: 2:17:28, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8413, loss: 0.0785 2023-03-04 08:22:22,930 - mmseg - INFO - Iter [133500/160000] lr: 2.344e-06, eta: 2:17:12, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.6976, loss: 0.0836 2023-03-04 08:22:37,349 - mmseg - INFO - Iter [133550/160000] lr: 2.344e-06, eta: 2:16:56, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8768, loss: 0.0786 2023-03-04 08:22:49,457 - mmseg - INFO - Iter [133600/160000] lr: 2.344e-06, eta: 2:16:40, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9047, loss: 0.0780 2023-03-04 08:23:01,612 - mmseg - INFO - Iter [133650/160000] lr: 2.344e-06, eta: 2:16:24, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8756, loss: 0.0793 2023-03-04 08:23:13,792 - mmseg - INFO - Iter [133700/160000] lr: 2.344e-06, eta: 2:16:08, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8739, loss: 0.0789 2023-03-04 08:23:28,403 - mmseg - INFO - Iter [133750/160000] lr: 2.344e-06, eta: 2:15:52, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8745, loss: 0.0791 2023-03-04 08:23:40,639 - mmseg - INFO - Iter [133800/160000] lr: 2.344e-06, eta: 2:15:36, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9811, loss: 0.0769 2023-03-04 08:23:52,741 - mmseg - INFO - Iter [133850/160000] lr: 2.344e-06, eta: 2:15:20, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8744, loss: 0.0791 2023-03-04 08:24:05,039 - mmseg - INFO - Iter [133900/160000] lr: 2.344e-06, eta: 2:15:04, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7961, loss: 0.0809 2023-03-04 08:24:19,586 - mmseg - INFO - Iter [133950/160000] lr: 2.344e-06, eta: 2:14:48, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9004, loss: 0.0774 2023-03-04 08:24:31,708 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:24:31,709 - mmseg - INFO - Iter [134000/160000] lr: 2.344e-06, eta: 2:14:32, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8037, loss: 0.0801 2023-03-04 08:24:43,755 - mmseg - INFO - Iter [134050/160000] lr: 2.344e-06, eta: 2:14:16, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 97.0271, loss: 0.0756 2023-03-04 08:24:55,833 - mmseg - INFO - Iter [134100/160000] lr: 2.344e-06, eta: 2:13:59, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9015, loss: 0.0781 2023-03-04 08:25:10,502 - mmseg - INFO - Iter [134150/160000] lr: 2.344e-06, eta: 2:13:44, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7755, loss: 0.0815 2023-03-04 08:25:22,842 - mmseg - INFO - Iter [134200/160000] lr: 2.344e-06, eta: 2:13:28, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9480, loss: 0.0772 2023-03-04 08:25:35,110 - mmseg - INFO - Iter [134250/160000] lr: 2.344e-06, eta: 2:13:11, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9477, loss: 0.0763 2023-03-04 08:25:49,554 - mmseg - INFO - Iter [134300/160000] lr: 2.344e-06, eta: 2:12:56, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7423, loss: 0.0825 2023-03-04 08:26:01,643 - mmseg - INFO - Iter [134350/160000] lr: 2.344e-06, eta: 2:12:40, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8205, loss: 0.0797 2023-03-04 08:26:13,731 - mmseg - INFO - Iter [134400/160000] lr: 2.344e-06, eta: 2:12:23, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8302, loss: 0.0803 2023-03-04 08:26:26,020 - mmseg - INFO - Iter [134450/160000] lr: 2.344e-06, eta: 2:12:07, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 97.0022, loss: 0.0754 2023-03-04 08:26:40,601 - mmseg - INFO - Iter [134500/160000] lr: 2.344e-06, eta: 2:11:52, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0829, decode.acc_seg: 96.6876, loss: 0.0829 2023-03-04 08:26:52,862 - mmseg - INFO - Iter [134550/160000] lr: 2.344e-06, eta: 2:11:35, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7460, loss: 0.0811 2023-03-04 08:27:05,134 - mmseg - INFO - Iter [134600/160000] lr: 2.344e-06, eta: 2:11:19, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8115, loss: 0.0795 2023-03-04 08:27:17,188 - mmseg - INFO - Iter [134650/160000] lr: 2.344e-06, eta: 2:11:03, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8998, loss: 0.0781 2023-03-04 08:27:31,875 - mmseg - INFO - Iter [134700/160000] lr: 2.344e-06, eta: 2:10:47, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8659, loss: 0.0790 2023-03-04 08:27:44,063 - mmseg - INFO - Iter [134750/160000] lr: 2.344e-06, eta: 2:10:31, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8643, loss: 0.0794 2023-03-04 08:27:56,309 - mmseg - INFO - Iter [134800/160000] lr: 2.344e-06, eta: 2:10:15, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9135, loss: 0.0778 2023-03-04 08:28:08,440 - mmseg - INFO - Iter [134850/160000] lr: 2.344e-06, eta: 2:09:59, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8164, loss: 0.0806 2023-03-04 08:28:23,011 - mmseg - INFO - Iter [134900/160000] lr: 2.344e-06, eta: 2:09:43, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8749, loss: 0.0814 2023-03-04 08:28:35,223 - mmseg - INFO - Iter [134950/160000] lr: 2.344e-06, eta: 2:09:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8965, loss: 0.0778 2023-03-04 08:28:47,367 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:28:47,367 - mmseg - INFO - Iter [135000/160000] lr: 2.344e-06, eta: 2:09:11, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9176, loss: 0.0779 2023-03-04 08:29:01,757 - mmseg - INFO - Iter [135050/160000] lr: 2.344e-06, eta: 2:08:55, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8284, loss: 0.0791 2023-03-04 08:29:13,909 - mmseg - INFO - Iter [135100/160000] lr: 2.344e-06, eta: 2:08:39, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8575, loss: 0.0795 2023-03-04 08:29:26,077 - mmseg - INFO - Iter [135150/160000] lr: 2.344e-06, eta: 2:08:23, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9373, loss: 0.0774 2023-03-04 08:29:38,297 - mmseg - INFO - Iter [135200/160000] lr: 2.344e-06, eta: 2:08:07, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9855, loss: 0.0756 2023-03-04 08:29:52,750 - mmseg - INFO - Iter [135250/160000] lr: 2.344e-06, eta: 2:07:51, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9805, loss: 0.0767 2023-03-04 08:30:04,997 - mmseg - INFO - Iter [135300/160000] lr: 2.344e-06, eta: 2:07:35, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8373, loss: 0.0799 2023-03-04 08:30:17,035 - mmseg - INFO - Iter [135350/160000] lr: 2.344e-06, eta: 2:07:19, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8839, loss: 0.0783 2023-03-04 08:30:29,153 - mmseg - INFO - Iter [135400/160000] lr: 2.344e-06, eta: 2:07:03, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8986, loss: 0.0786 2023-03-04 08:30:43,646 - mmseg - INFO - Iter [135450/160000] lr: 2.344e-06, eta: 2:06:47, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8009, loss: 0.0802 2023-03-04 08:30:55,965 - mmseg - INFO - Iter [135500/160000] lr: 2.344e-06, eta: 2:06:31, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9401, loss: 0.0763 2023-03-04 08:31:08,122 - mmseg - INFO - Iter [135550/160000] lr: 2.344e-06, eta: 2:06:15, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0760, decode.acc_seg: 97.0025, loss: 0.0760 2023-03-04 08:31:22,572 - mmseg - INFO - Iter [135600/160000] lr: 2.344e-06, eta: 2:06:00, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.7913, loss: 0.0820 2023-03-04 08:31:34,802 - mmseg - INFO - Iter [135650/160000] lr: 2.344e-06, eta: 2:05:43, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9102, loss: 0.0773 2023-03-04 08:31:47,102 - mmseg - INFO - Iter [135700/160000] lr: 2.344e-06, eta: 2:05:27, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8559, loss: 0.0781 2023-03-04 08:31:59,291 - mmseg - INFO - Iter [135750/160000] lr: 2.344e-06, eta: 2:05:11, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9440, loss: 0.0774 2023-03-04 08:32:13,790 - mmseg - INFO - Iter [135800/160000] lr: 2.344e-06, eta: 2:04:56, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8584, loss: 0.0790 2023-03-04 08:32:25,948 - mmseg - INFO - Iter [135850/160000] lr: 2.344e-06, eta: 2:04:40, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8317, loss: 0.0801 2023-03-04 08:32:38,095 - mmseg - INFO - Iter [135900/160000] lr: 2.344e-06, eta: 2:04:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8956, loss: 0.0785 2023-03-04 08:32:50,232 - mmseg - INFO - Iter [135950/160000] lr: 2.344e-06, eta: 2:04:07, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9325, loss: 0.0780 2023-03-04 08:33:04,705 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:33:04,705 - mmseg - INFO - Iter [136000/160000] lr: 2.344e-06, eta: 2:03:52, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8301, loss: 0.0797 2023-03-04 08:33:16,856 - mmseg - INFO - Iter [136050/160000] lr: 2.344e-06, eta: 2:03:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8098, loss: 0.0803 2023-03-04 08:33:29,150 - mmseg - INFO - Iter [136100/160000] lr: 2.344e-06, eta: 2:03:20, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8384, loss: 0.0796 2023-03-04 08:33:41,282 - mmseg - INFO - Iter [136150/160000] lr: 2.344e-06, eta: 2:03:04, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0752, decode.acc_seg: 97.0156, loss: 0.0752 2023-03-04 08:33:55,818 - mmseg - INFO - Iter [136200/160000] lr: 2.344e-06, eta: 2:02:48, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8760, loss: 0.0791 2023-03-04 08:34:08,000 - mmseg - INFO - Iter [136250/160000] lr: 2.344e-06, eta: 2:02:32, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8548, loss: 0.0795 2023-03-04 08:34:20,097 - mmseg - INFO - Iter [136300/160000] lr: 2.344e-06, eta: 2:02:16, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8682, loss: 0.0793 2023-03-04 08:34:34,674 - mmseg - INFO - Iter [136350/160000] lr: 2.344e-06, eta: 2:02:00, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8291, loss: 0.0799 2023-03-04 08:34:46,803 - mmseg - INFO - Iter [136400/160000] lr: 2.344e-06, eta: 2:01:44, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9637, loss: 0.0761 2023-03-04 08:34:58,982 - mmseg - INFO - Iter [136450/160000] lr: 2.344e-06, eta: 2:01:28, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9002, loss: 0.0787 2023-03-04 08:35:11,120 - mmseg - INFO - Iter [136500/160000] lr: 2.344e-06, eta: 2:01:12, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8670, loss: 0.0785 2023-03-04 08:35:25,626 - mmseg - INFO - Iter [136550/160000] lr: 2.344e-06, eta: 2:00:56, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9185, loss: 0.0776 2023-03-04 08:35:37,816 - mmseg - INFO - Iter [136600/160000] lr: 2.344e-06, eta: 2:00:40, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.8086, loss: 0.0828 2023-03-04 08:35:50,054 - mmseg - INFO - Iter [136650/160000] lr: 2.344e-06, eta: 2:00:24, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9147, loss: 0.0776 2023-03-04 08:36:02,203 - mmseg - INFO - Iter [136700/160000] lr: 2.344e-06, eta: 2:00:08, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8813, loss: 0.0798 2023-03-04 08:36:16,609 - mmseg - INFO - Iter [136750/160000] lr: 2.344e-06, eta: 1:59:53, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9170, loss: 0.0776 2023-03-04 08:36:28,893 - mmseg - INFO - Iter [136800/160000] lr: 2.344e-06, eta: 1:59:37, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9421, loss: 0.0769 2023-03-04 08:36:40,949 - mmseg - INFO - Iter [136850/160000] lr: 2.344e-06, eta: 1:59:21, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7640, loss: 0.0822 2023-03-04 08:36:55,770 - mmseg - INFO - Iter [136900/160000] lr: 2.344e-06, eta: 1:59:05, time: 0.296, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7902, loss: 0.0805 2023-03-04 08:37:08,069 - mmseg - INFO - Iter [136950/160000] lr: 2.344e-06, eta: 1:58:49, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7558, loss: 0.0822 2023-03-04 08:37:20,198 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:37:20,198 - mmseg - INFO - Iter [137000/160000] lr: 2.344e-06, eta: 1:58:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9400, loss: 0.0764 2023-03-04 08:37:32,274 - mmseg - INFO - Iter [137050/160000] lr: 2.344e-06, eta: 1:58:17, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8526, loss: 0.0795 2023-03-04 08:37:46,864 - mmseg - INFO - Iter [137100/160000] lr: 2.344e-06, eta: 1:58:01, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9162, loss: 0.0770 2023-03-04 08:37:59,094 - mmseg - INFO - Iter [137150/160000] lr: 2.344e-06, eta: 1:57:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9400, loss: 0.0769 2023-03-04 08:38:11,314 - mmseg - INFO - Iter [137200/160000] lr: 2.344e-06, eta: 1:57:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9170, loss: 0.0779 2023-03-04 08:38:23,528 - mmseg - INFO - Iter [137250/160000] lr: 2.344e-06, eta: 1:57:13, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9152, loss: 0.0785 2023-03-04 08:38:38,086 - mmseg - INFO - Iter [137300/160000] lr: 2.344e-06, eta: 1:56:58, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9138, loss: 0.0786 2023-03-04 08:38:50,188 - mmseg - INFO - Iter [137350/160000] lr: 2.344e-06, eta: 1:56:42, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8062, loss: 0.0807 2023-03-04 08:39:02,296 - mmseg - INFO - Iter [137400/160000] lr: 2.344e-06, eta: 1:56:26, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8989, loss: 0.0779 2023-03-04 08:39:14,400 - mmseg - INFO - Iter [137450/160000] lr: 2.344e-06, eta: 1:56:10, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9099, loss: 0.0780 2023-03-04 08:39:28,989 - mmseg - INFO - Iter [137500/160000] lr: 2.344e-06, eta: 1:55:54, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9058, loss: 0.0783 2023-03-04 08:39:41,054 - mmseg - INFO - Iter [137550/160000] lr: 2.344e-06, eta: 1:55:38, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8780, loss: 0.0794 2023-03-04 08:39:53,367 - mmseg - INFO - Iter [137600/160000] lr: 2.344e-06, eta: 1:55:22, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8296, loss: 0.0805 2023-03-04 08:40:07,912 - mmseg - INFO - Iter [137650/160000] lr: 2.344e-06, eta: 1:55:07, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0755, decode.acc_seg: 97.0007, loss: 0.0755 2023-03-04 08:40:20,276 - mmseg - INFO - Iter [137700/160000] lr: 2.344e-06, eta: 1:54:51, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9752, loss: 0.0777 2023-03-04 08:40:32,498 - mmseg - INFO - Iter [137750/160000] lr: 2.344e-06, eta: 1:54:35, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8385, loss: 0.0793 2023-03-04 08:40:44,719 - mmseg - INFO - Iter [137800/160000] lr: 2.344e-06, eta: 1:54:19, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9250, loss: 0.0779 2023-03-04 08:40:59,141 - mmseg - INFO - Iter [137850/160000] lr: 2.344e-06, eta: 1:54:03, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8931, loss: 0.0794 2023-03-04 08:41:11,377 - mmseg - INFO - Iter [137900/160000] lr: 2.344e-06, eta: 1:53:47, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9311, loss: 0.0768 2023-03-04 08:41:23,781 - mmseg - INFO - Iter [137950/160000] lr: 2.344e-06, eta: 1:53:31, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9209, loss: 0.0777 2023-03-04 08:41:36,014 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:41:36,015 - mmseg - INFO - Iter [138000/160000] lr: 2.344e-06, eta: 1:53:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8363, loss: 0.0799 2023-03-04 08:41:50,670 - mmseg - INFO - Iter [138050/160000] lr: 2.344e-06, eta: 1:53:00, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9014, loss: 0.0783 2023-03-04 08:42:02,890 - mmseg - INFO - Iter [138100/160000] lr: 2.344e-06, eta: 1:52:44, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8137, loss: 0.0804 2023-03-04 08:42:15,112 - mmseg - INFO - Iter [138150/160000] lr: 2.344e-06, eta: 1:52:28, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8167, loss: 0.0802 2023-03-04 08:42:29,607 - mmseg - INFO - Iter [138200/160000] lr: 2.344e-06, eta: 1:52:12, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7564, loss: 0.0816 2023-03-04 08:42:41,698 - mmseg - INFO - Iter [138250/160000] lr: 2.344e-06, eta: 1:51:56, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8826, loss: 0.0788 2023-03-04 08:42:53,867 - mmseg - INFO - Iter [138300/160000] lr: 2.344e-06, eta: 1:51:40, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8635, loss: 0.0785 2023-03-04 08:43:06,139 - mmseg - INFO - Iter [138350/160000] lr: 2.344e-06, eta: 1:51:24, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7491, loss: 0.0819 2023-03-04 08:43:20,572 - mmseg - INFO - Iter [138400/160000] lr: 2.344e-06, eta: 1:51:09, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8275, loss: 0.0801 2023-03-04 08:43:32,836 - mmseg - INFO - Iter [138450/160000] lr: 2.344e-06, eta: 1:50:53, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7369, loss: 0.0826 2023-03-04 08:43:45,065 - mmseg - INFO - Iter [138500/160000] lr: 2.344e-06, eta: 1:50:37, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8998, loss: 0.0788 2023-03-04 08:43:57,256 - mmseg - INFO - Iter [138550/160000] lr: 2.344e-06, eta: 1:50:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8979, loss: 0.0780 2023-03-04 08:44:11,661 - mmseg - INFO - Iter [138600/160000] lr: 2.344e-06, eta: 1:50:05, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8483, loss: 0.0784 2023-03-04 08:44:23,927 - mmseg - INFO - Iter [138650/160000] lr: 2.344e-06, eta: 1:49:49, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8701, loss: 0.0798 2023-03-04 08:44:36,206 - mmseg - INFO - Iter [138700/160000] lr: 2.344e-06, eta: 1:49:33, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8660, loss: 0.0786 2023-03-04 08:44:48,398 - mmseg - INFO - Iter [138750/160000] lr: 2.344e-06, eta: 1:49:17, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.8620, loss: 0.0822 2023-03-04 08:45:02,846 - mmseg - INFO - Iter [138800/160000] lr: 2.344e-06, eta: 1:49:02, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9085, loss: 0.0785 2023-03-04 08:45:15,068 - mmseg - INFO - Iter [138850/160000] lr: 2.344e-06, eta: 1:48:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7507, loss: 0.0822 2023-03-04 08:45:27,304 - mmseg - INFO - Iter [138900/160000] lr: 2.344e-06, eta: 1:48:30, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0765, decode.acc_seg: 96.9247, loss: 0.0765 2023-03-04 08:45:41,768 - mmseg - INFO - Iter [138950/160000] lr: 2.344e-06, eta: 1:48:15, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8581, loss: 0.0791 2023-03-04 08:45:53,962 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:45:53,962 - mmseg - INFO - Iter [139000/160000] lr: 2.344e-06, eta: 1:47:59, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8958, loss: 0.0795 2023-03-04 08:46:06,122 - mmseg - INFO - Iter [139050/160000] lr: 2.344e-06, eta: 1:47:43, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8893, loss: 0.0780 2023-03-04 08:46:18,369 - mmseg - INFO - Iter [139100/160000] lr: 2.344e-06, eta: 1:47:27, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9257, loss: 0.0775 2023-03-04 08:46:32,783 - mmseg - INFO - Iter [139150/160000] lr: 2.344e-06, eta: 1:47:11, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8831, loss: 0.0782 2023-03-04 08:46:45,140 - mmseg - INFO - Iter [139200/160000] lr: 2.344e-06, eta: 1:46:55, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9243, loss: 0.0778 2023-03-04 08:46:57,355 - mmseg - INFO - Iter [139250/160000] lr: 2.344e-06, eta: 1:46:39, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0828, decode.acc_seg: 96.7461, loss: 0.0828 2023-03-04 08:47:09,614 - mmseg - INFO - Iter [139300/160000] lr: 2.344e-06, eta: 1:46:24, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0746, decode.acc_seg: 97.0141, loss: 0.0746 2023-03-04 08:47:24,064 - mmseg - INFO - Iter [139350/160000] lr: 2.344e-06, eta: 1:46:08, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8276, loss: 0.0802 2023-03-04 08:47:36,252 - mmseg - INFO - Iter [139400/160000] lr: 2.344e-06, eta: 1:45:52, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8245, loss: 0.0801 2023-03-04 08:47:48,413 - mmseg - INFO - Iter [139450/160000] lr: 2.344e-06, eta: 1:45:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7929, loss: 0.0811 2023-03-04 08:48:00,629 - mmseg - INFO - Iter [139500/160000] lr: 2.344e-06, eta: 1:45:20, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8144, loss: 0.0805 2023-03-04 08:48:15,202 - mmseg - INFO - Iter [139550/160000] lr: 2.344e-06, eta: 1:45:05, time: 0.291, data_time: 0.052, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9505, loss: 0.0764 2023-03-04 08:48:27,272 - mmseg - INFO - Iter [139600/160000] lr: 2.344e-06, eta: 1:44:49, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7710, loss: 0.0812 2023-03-04 08:48:39,465 - mmseg - INFO - Iter [139650/160000] lr: 2.344e-06, eta: 1:44:33, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9768, loss: 0.0764 2023-03-04 08:48:53,973 - mmseg - INFO - Iter [139700/160000] lr: 2.344e-06, eta: 1:44:17, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0758, decode.acc_seg: 96.9750, loss: 0.0758 2023-03-04 08:49:06,080 - mmseg - INFO - Iter [139750/160000] lr: 2.344e-06, eta: 1:44:02, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8747, loss: 0.0797 2023-03-04 08:49:18,150 - mmseg - INFO - Iter [139800/160000] lr: 2.344e-06, eta: 1:43:46, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 97.0021, loss: 0.0754 2023-03-04 08:49:30,409 - mmseg - INFO - Iter [139850/160000] lr: 2.344e-06, eta: 1:43:30, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8405, loss: 0.0801 2023-03-04 08:49:44,971 - mmseg - INFO - Iter [139900/160000] lr: 2.344e-06, eta: 1:43:14, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9170, loss: 0.0780 2023-03-04 08:49:57,091 - mmseg - INFO - Iter [139950/160000] lr: 2.344e-06, eta: 1:42:58, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8988, loss: 0.0792 2023-03-04 08:50:09,260 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:50:09,261 - mmseg - INFO - Iter [140000/160000] lr: 2.344e-06, eta: 1:42:42, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 97.0115, loss: 0.0754 2023-03-04 08:50:21,475 - mmseg - INFO - Iter [140050/160000] lr: 1.172e-06, eta: 1:42:27, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8391, loss: 0.0793 2023-03-04 08:50:35,991 - mmseg - INFO - Iter [140100/160000] lr: 1.172e-06, eta: 1:42:11, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8701, loss: 0.0790 2023-03-04 08:50:48,307 - mmseg - INFO - Iter [140150/160000] lr: 1.172e-06, eta: 1:41:55, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8730, loss: 0.0792 2023-03-04 08:51:00,474 - mmseg - INFO - Iter [140200/160000] lr: 1.172e-06, eta: 1:41:39, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9500, loss: 0.0767 2023-03-04 08:51:14,924 - mmseg - INFO - Iter [140250/160000] lr: 1.172e-06, eta: 1:41:24, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7976, loss: 0.0811 2023-03-04 08:51:27,011 - mmseg - INFO - Iter [140300/160000] lr: 1.172e-06, eta: 1:41:08, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.7987, loss: 0.0807 2023-03-04 08:51:39,074 - mmseg - INFO - Iter [140350/160000] lr: 1.172e-06, eta: 1:40:52, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8935, loss: 0.0792 2023-03-04 08:51:51,175 - mmseg - INFO - Iter [140400/160000] lr: 1.172e-06, eta: 1:40:36, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7391, loss: 0.0841 2023-03-04 08:52:05,709 - mmseg - INFO - Iter [140450/160000] lr: 1.172e-06, eta: 1:40:21, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8913, loss: 0.0786 2023-03-04 08:52:18,142 - mmseg - INFO - Iter [140500/160000] lr: 1.172e-06, eta: 1:40:05, time: 0.249, data_time: 0.007, memory: 67501, decode.loss_ce: 0.0761, decode.acc_seg: 96.9813, loss: 0.0761 2023-03-04 08:52:30,246 - mmseg - INFO - Iter [140550/160000] lr: 1.172e-06, eta: 1:39:49, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9116, loss: 0.0773 2023-03-04 08:52:42,491 - mmseg - INFO - Iter [140600/160000] lr: 1.172e-06, eta: 1:39:33, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9859, loss: 0.0764 2023-03-04 08:52:57,112 - mmseg - INFO - Iter [140650/160000] lr: 1.172e-06, eta: 1:39:18, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8408, loss: 0.0794 2023-03-04 08:53:09,249 - mmseg - INFO - Iter [140700/160000] lr: 1.172e-06, eta: 1:39:02, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9445, loss: 0.0768 2023-03-04 08:53:21,530 - mmseg - INFO - Iter [140750/160000] lr: 1.172e-06, eta: 1:38:46, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9385, loss: 0.0769 2023-03-04 08:53:33,730 - mmseg - INFO - Iter [140800/160000] lr: 1.172e-06, eta: 1:38:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7815, loss: 0.0819 2023-03-04 08:53:48,180 - mmseg - INFO - Iter [140850/160000] lr: 1.172e-06, eta: 1:38:15, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8028, loss: 0.0807 2023-03-04 08:54:00,414 - mmseg - INFO - Iter [140900/160000] lr: 1.172e-06, eta: 1:37:59, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8917, loss: 0.0785 2023-03-04 08:54:12,684 - mmseg - INFO - Iter [140950/160000] lr: 1.172e-06, eta: 1:37:43, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0757, decode.acc_seg: 97.0059, loss: 0.0757 2023-03-04 08:54:27,371 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:54:27,371 - mmseg - INFO - Iter [141000/160000] lr: 1.172e-06, eta: 1:37:28, time: 0.294, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8440, loss: 0.0795 2023-03-04 08:54:39,657 - mmseg - INFO - Iter [141050/160000] lr: 1.172e-06, eta: 1:37:12, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8719, loss: 0.0792 2023-03-04 08:54:51,888 - mmseg - INFO - Iter [141100/160000] lr: 1.172e-06, eta: 1:36:56, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8803, loss: 0.0799 2023-03-04 08:55:04,035 - mmseg - INFO - Iter [141150/160000] lr: 1.172e-06, eta: 1:36:40, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8988, loss: 0.0779 2023-03-04 08:55:18,641 - mmseg - INFO - Iter [141200/160000] lr: 1.172e-06, eta: 1:36:25, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9032, loss: 0.0784 2023-03-04 08:55:30,749 - mmseg - INFO - Iter [141250/160000] lr: 1.172e-06, eta: 1:36:09, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8777, loss: 0.0787 2023-03-04 08:55:42,933 - mmseg - INFO - Iter [141300/160000] lr: 1.172e-06, eta: 1:35:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0843, decode.acc_seg: 96.8075, loss: 0.0843 2023-03-04 08:55:55,087 - mmseg - INFO - Iter [141350/160000] lr: 1.172e-06, eta: 1:35:37, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9578, loss: 0.0770 2023-03-04 08:56:09,674 - mmseg - INFO - Iter [141400/160000] lr: 1.172e-06, eta: 1:35:22, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0742, decode.acc_seg: 97.0291, loss: 0.0742 2023-03-04 08:56:21,803 - mmseg - INFO - Iter [141450/160000] lr: 1.172e-06, eta: 1:35:06, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9122, loss: 0.0788 2023-03-04 08:56:34,094 - mmseg - INFO - Iter [141500/160000] lr: 1.172e-06, eta: 1:34:50, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8457, loss: 0.0797 2023-03-04 08:56:48,639 - mmseg - INFO - Iter [141550/160000] lr: 1.172e-06, eta: 1:34:35, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8729, loss: 0.0793 2023-03-04 08:57:00,797 - mmseg - INFO - Iter [141600/160000] lr: 1.172e-06, eta: 1:34:19, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8913, loss: 0.0794 2023-03-04 08:57:12,842 - mmseg - INFO - Iter [141650/160000] lr: 1.172e-06, eta: 1:34:03, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9338, loss: 0.0770 2023-03-04 08:57:24,965 - mmseg - INFO - Iter [141700/160000] lr: 1.172e-06, eta: 1:33:47, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8841, loss: 0.0784 2023-03-04 08:57:39,620 - mmseg - INFO - Iter [141750/160000] lr: 1.172e-06, eta: 1:33:32, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9401, loss: 0.0769 2023-03-04 08:57:51,827 - mmseg - INFO - Iter [141800/160000] lr: 1.172e-06, eta: 1:33:16, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8673, loss: 0.0809 2023-03-04 08:58:03,968 - mmseg - INFO - Iter [141850/160000] lr: 1.172e-06, eta: 1:33:00, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8400, loss: 0.0797 2023-03-04 08:58:16,019 - mmseg - INFO - Iter [141900/160000] lr: 1.172e-06, eta: 1:32:44, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8592, loss: 0.0792 2023-03-04 08:58:30,542 - mmseg - INFO - Iter [141950/160000] lr: 1.172e-06, eta: 1:32:29, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9420, loss: 0.0779 2023-03-04 08:58:42,722 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 08:58:42,723 - mmseg - INFO - Iter [142000/160000] lr: 1.172e-06, eta: 1:32:13, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8460, loss: 0.0788 2023-03-04 08:58:55,075 - mmseg - INFO - Iter [142050/160000] lr: 1.172e-06, eta: 1:31:57, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8301, loss: 0.0810 2023-03-04 08:59:07,224 - mmseg - INFO - Iter [142100/160000] lr: 1.172e-06, eta: 1:31:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8685, loss: 0.0792 2023-03-04 08:59:21,878 - mmseg - INFO - Iter [142150/160000] lr: 1.172e-06, eta: 1:31:26, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9339, loss: 0.0776 2023-03-04 08:59:34,081 - mmseg - INFO - Iter [142200/160000] lr: 1.172e-06, eta: 1:31:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9220, loss: 0.0772 2023-03-04 08:59:46,225 - mmseg - INFO - Iter [142250/160000] lr: 1.172e-06, eta: 1:30:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8781, loss: 0.0784 2023-03-04 09:00:00,881 - mmseg - INFO - Iter [142300/160000] lr: 1.172e-06, eta: 1:30:39, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7947, loss: 0.0806 2023-03-04 09:00:13,054 - mmseg - INFO - Iter [142350/160000] lr: 1.172e-06, eta: 1:30:23, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7566, loss: 0.0821 2023-03-04 09:00:25,119 - mmseg - INFO - Iter [142400/160000] lr: 1.172e-06, eta: 1:30:08, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7863, loss: 0.0822 2023-03-04 09:00:37,388 - mmseg - INFO - Iter [142450/160000] lr: 1.172e-06, eta: 1:29:52, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7919, loss: 0.0806 2023-03-04 09:00:52,050 - mmseg - INFO - Iter [142500/160000] lr: 1.172e-06, eta: 1:29:36, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9241, loss: 0.0780 2023-03-04 09:01:04,271 - mmseg - INFO - Iter [142550/160000] lr: 1.172e-06, eta: 1:29:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9282, loss: 0.0778 2023-03-04 09:01:16,569 - mmseg - INFO - Iter [142600/160000] lr: 1.172e-06, eta: 1:29:05, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9600, loss: 0.0773 2023-03-04 09:01:28,696 - mmseg - INFO - Iter [142650/160000] lr: 1.172e-06, eta: 1:28:49, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.9115, loss: 0.0796 2023-03-04 09:01:43,107 - mmseg - INFO - Iter [142700/160000] lr: 1.172e-06, eta: 1:28:34, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7561, loss: 0.0803 2023-03-04 09:01:55,316 - mmseg - INFO - Iter [142750/160000] lr: 1.172e-06, eta: 1:28:18, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8768, loss: 0.0790 2023-03-04 09:02:07,475 - mmseg - INFO - Iter [142800/160000] lr: 1.172e-06, eta: 1:28:02, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9308, loss: 0.0776 2023-03-04 09:02:22,013 - mmseg - INFO - Iter [142850/160000] lr: 1.172e-06, eta: 1:27:47, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8253, loss: 0.0805 2023-03-04 09:02:34,262 - mmseg - INFO - Iter [142900/160000] lr: 1.172e-06, eta: 1:27:31, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9493, loss: 0.0769 2023-03-04 09:02:46,335 - mmseg - INFO - Iter [142950/160000] lr: 1.172e-06, eta: 1:27:15, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0826, decode.acc_seg: 96.7997, loss: 0.0826 2023-03-04 09:02:58,559 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:02:58,559 - mmseg - INFO - Iter [143000/160000] lr: 1.172e-06, eta: 1:27:00, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8010, loss: 0.0794 2023-03-04 09:03:13,069 - mmseg - INFO - Iter [143050/160000] lr: 1.172e-06, eta: 1:26:44, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9092, loss: 0.0777 2023-03-04 09:03:25,216 - mmseg - INFO - Iter [143100/160000] lr: 1.172e-06, eta: 1:26:28, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.7930, loss: 0.0792 2023-03-04 09:03:37,308 - mmseg - INFO - Iter [143150/160000] lr: 1.172e-06, eta: 1:26:13, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7727, loss: 0.0817 2023-03-04 09:03:49,399 - mmseg - INFO - Iter [143200/160000] lr: 1.172e-06, eta: 1:25:57, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8239, loss: 0.0803 2023-03-04 09:04:03,860 - mmseg - INFO - Iter [143250/160000] lr: 1.172e-06, eta: 1:25:41, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0758, decode.acc_seg: 96.9854, loss: 0.0758 2023-03-04 09:04:16,167 - mmseg - INFO - Iter [143300/160000] lr: 1.172e-06, eta: 1:25:26, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8900, loss: 0.0789 2023-03-04 09:04:28,351 - mmseg - INFO - Iter [143350/160000] lr: 1.172e-06, eta: 1:25:10, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9047, loss: 0.0781 2023-03-04 09:04:40,534 - mmseg - INFO - Iter [143400/160000] lr: 1.172e-06, eta: 1:24:54, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8393, loss: 0.0799 2023-03-04 09:04:55,181 - mmseg - INFO - Iter [143450/160000] lr: 1.172e-06, eta: 1:24:39, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7228, loss: 0.0836 2023-03-04 09:05:07,364 - mmseg - INFO - Iter [143500/160000] lr: 1.172e-06, eta: 1:24:23, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0757, decode.acc_seg: 96.9884, loss: 0.0757 2023-03-04 09:05:19,527 - mmseg - INFO - Iter [143550/160000] lr: 1.172e-06, eta: 1:24:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8307, loss: 0.0804 2023-03-04 09:05:34,212 - mmseg - INFO - Iter [143600/160000] lr: 1.172e-06, eta: 1:23:52, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9100, loss: 0.0775 2023-03-04 09:05:46,275 - mmseg - INFO - Iter [143650/160000] lr: 1.172e-06, eta: 1:23:36, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8485, loss: 0.0800 2023-03-04 09:05:58,405 - mmseg - INFO - Iter [143700/160000] lr: 1.172e-06, eta: 1:23:21, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8037, loss: 0.0814 2023-03-04 09:06:10,558 - mmseg - INFO - Iter [143750/160000] lr: 1.172e-06, eta: 1:23:05, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9414, loss: 0.0778 2023-03-04 09:06:25,157 - mmseg - INFO - Iter [143800/160000] lr: 1.172e-06, eta: 1:22:50, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8095, loss: 0.0801 2023-03-04 09:06:37,458 - mmseg - INFO - Iter [143850/160000] lr: 1.172e-06, eta: 1:22:34, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8732, loss: 0.0783 2023-03-04 09:06:49,647 - mmseg - INFO - Iter [143900/160000] lr: 1.172e-06, eta: 1:22:18, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7730, loss: 0.0808 2023-03-04 09:07:01,857 - mmseg - INFO - Iter [143950/160000] lr: 1.172e-06, eta: 1:22:02, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8891, loss: 0.0780 2023-03-04 09:07:16,343 - mmseg - INFO - Swap parameters (after train) after iter [144000] 2023-03-04 09:07:16,358 - mmseg - INFO - Saving checkpoint at 144000 iterations 2023-03-04 09:07:17,825 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:07:17,825 - mmseg - INFO - Iter [144000/160000] lr: 1.172e-06, eta: 1:21:47, time: 0.319, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9373, loss: 0.0775 2023-03-04 09:22:09,275 - mmseg - INFO - per class results: 2023-03-04 09:22:09,277 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.58,98.58,98.59,98.59,98.6,98.59,98.59,98.59,98.59,98.6,98.6 | | sidewalk | 87.88,87.88,87.93,87.96,87.98,87.96,87.98,87.98,87.98,88.03,88.03 | | building | 93.32,93.32,93.32,93.33,93.32,93.33,93.32,93.33,93.33,93.33,93.33 | | wall | 54.19,54.26,54.41,54.52,54.59,54.61,54.42,54.67,54.73,54.76,54.93 | | fence | 63.36,63.35,63.38,63.41,63.38,63.42,63.25,63.35,63.32,63.36,63.39 | | pole | 71.03,71.03,71.06,71.05,71.05,71.06,71.06,71.05,71.06,71.06,71.06 | | traffic light | 75.54,75.54,75.55,75.55,75.52,75.54,75.55,75.54,75.52,75.53,75.52 | | traffic sign | 83.26,83.27,83.29,83.3,83.29,83.31,83.32,83.32,83.34,83.35,83.35 | | vegetation | 92.9,92.91,92.92,92.92,92.92,92.93,92.92,92.91,92.92,92.92,92.92 | | terrain | 65.66,65.79,65.96,66.0,66.03,66.16,66.14,66.06,66.08,66.18,66.27 | | sky | 95.26,95.26,95.26,95.27,95.27,95.27,95.27,95.27,95.27,95.28,95.27 | | person | 84.73,84.75,84.76,84.75,84.76,84.77,84.78,84.78,84.8,84.78,84.79 | | rider | 67.14,67.21,67.25,67.24,67.3,67.32,67.37,67.34,67.48,67.37,67.42 | | car | 95.95,95.98,96.01,96.02,96.03,96.03,96.04,96.04,96.05,96.06,96.05 | | truck | 85.32,85.9,86.48,86.75,86.9,86.91,87.09,87.16,87.15,87.28,87.23 | | bus | 92.2,92.25,92.23,92.27,92.28,92.29,92.3,92.34,92.36,92.37,92.39 | | train | 86.07,86.06,86.07,86.07,86.12,86.09,86.13,86.1,86.13,86.07,86.08 | | motorcycle | 69.77,69.76,69.72,69.73,69.72,69.7,69.7,69.67,69.72,69.69,69.68 | | bicycle | 79.85,79.87,79.87,79.88,79.89,79.88,79.89,79.9,79.91,79.91,79.92 | +---------------+-------------------------------------------------------------------+ 2023-03-04 09:22:09,277 - mmseg - INFO - Summary: 2023-03-04 09:22:09,277 - mmseg - INFO - +------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +------------------------------------------------------------------+ | 81.16,81.21,81.27,81.3,81.31,81.32,81.32,81.34,81.35,81.36,81.38 | +------------------------------------------------------------------+ 2023-03-04 09:22:09,277 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:22:09,277 - mmseg - INFO - Iter(val) [63] mIoU: [0.8116, 0.8121, 0.8127, 0.813, 0.8131, 0.8132, 0.8132, 0.8134, 0.8135, 0.8136, 0.8138], copy_paste: 81.16,81.21,81.27,81.3,81.31,81.32,81.32,81.34,81.35,81.36,81.38 2023-03-04 09:22:09,285 - mmseg - INFO - Swap parameters (before train) before iter [144001] 2023-03-04 09:22:21,717 - mmseg - INFO - Iter [144050/160000] lr: 1.172e-06, eta: 1:23:10, time: 18.078, data_time: 17.838, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8732, loss: 0.0783 2023-03-04 09:22:34,027 - mmseg - INFO - Iter [144100/160000] lr: 1.172e-06, eta: 1:22:54, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7875, loss: 0.0808 2023-03-04 09:22:46,302 - mmseg - INFO - Iter [144150/160000] lr: 1.172e-06, eta: 1:22:38, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9339, loss: 0.0780 2023-03-04 09:23:00,924 - mmseg - INFO - Iter [144200/160000] lr: 1.172e-06, eta: 1:22:22, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8351, loss: 0.0798 2023-03-04 09:23:13,227 - mmseg - INFO - Iter [144250/160000] lr: 1.172e-06, eta: 1:22:06, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9486, loss: 0.0779 2023-03-04 09:23:25,479 - mmseg - INFO - Iter [144300/160000] lr: 1.172e-06, eta: 1:21:50, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0748, decode.acc_seg: 97.0353, loss: 0.0748 2023-03-04 09:23:40,252 - mmseg - INFO - Iter [144350/160000] lr: 1.172e-06, eta: 1:21:35, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9316, loss: 0.0773 2023-03-04 09:23:52,517 - mmseg - INFO - Iter [144400/160000] lr: 1.172e-06, eta: 1:21:19, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0750, decode.acc_seg: 97.0233, loss: 0.0750 2023-03-04 09:24:04,699 - mmseg - INFO - Iter [144450/160000] lr: 1.172e-06, eta: 1:21:03, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8188, loss: 0.0803 2023-03-04 09:24:17,034 - mmseg - INFO - Iter [144500/160000] lr: 1.172e-06, eta: 1:20:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7992, loss: 0.0803 2023-03-04 09:24:31,490 - mmseg - INFO - Iter [144550/160000] lr: 1.172e-06, eta: 1:20:31, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8941, loss: 0.0781 2023-03-04 09:24:43,702 - mmseg - INFO - Iter [144600/160000] lr: 1.172e-06, eta: 1:20:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8344, loss: 0.0795 2023-03-04 09:24:55,934 - mmseg - INFO - Iter [144650/160000] lr: 1.172e-06, eta: 1:19:59, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8208, loss: 0.0811 2023-03-04 09:25:08,214 - mmseg - INFO - Iter [144700/160000] lr: 1.172e-06, eta: 1:19:43, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8949, loss: 0.0801 2023-03-04 09:25:22,903 - mmseg - INFO - Iter [144750/160000] lr: 1.172e-06, eta: 1:19:27, time: 0.294, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0760, decode.acc_seg: 96.9727, loss: 0.0760 2023-03-04 09:25:35,147 - mmseg - INFO - Iter [144800/160000] lr: 1.172e-06, eta: 1:19:11, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8477, loss: 0.0801 2023-03-04 09:25:47,442 - mmseg - INFO - Iter [144850/160000] lr: 1.172e-06, eta: 1:18:55, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.8035, loss: 0.0815 2023-03-04 09:26:01,922 - mmseg - INFO - Iter [144900/160000] lr: 1.172e-06, eta: 1:18:40, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9092, loss: 0.0773 2023-03-04 09:26:14,135 - mmseg - INFO - Iter [144950/160000] lr: 1.172e-06, eta: 1:18:24, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8946, loss: 0.0780 2023-03-04 09:26:26,320 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:26:26,320 - mmseg - INFO - Iter [145000/160000] lr: 1.172e-06, eta: 1:18:08, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7067, loss: 0.0833 2023-03-04 09:26:38,527 - mmseg - INFO - Iter [145050/160000] lr: 1.172e-06, eta: 1:17:52, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8249, loss: 0.0799 2023-03-04 09:26:52,964 - mmseg - INFO - Iter [145100/160000] lr: 1.172e-06, eta: 1:17:36, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8338, loss: 0.0794 2023-03-04 09:27:05,298 - mmseg - INFO - Iter [145150/160000] lr: 1.172e-06, eta: 1:17:20, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0831, decode.acc_seg: 96.7446, loss: 0.0831 2023-03-04 09:27:17,549 - mmseg - INFO - Iter [145200/160000] lr: 1.172e-06, eta: 1:17:04, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8958, loss: 0.0781 2023-03-04 09:27:29,757 - mmseg - INFO - Iter [145250/160000] lr: 1.172e-06, eta: 1:16:48, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8615, loss: 0.0796 2023-03-04 09:27:44,327 - mmseg - INFO - Iter [145300/160000] lr: 1.172e-06, eta: 1:16:32, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7486, loss: 0.0815 2023-03-04 09:27:56,652 - mmseg - INFO - Iter [145350/160000] lr: 1.172e-06, eta: 1:16:16, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8726, loss: 0.0793 2023-03-04 09:28:08,870 - mmseg - INFO - Iter [145400/160000] lr: 1.172e-06, eta: 1:16:00, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8614, loss: 0.0808 2023-03-04 09:28:20,956 - mmseg - INFO - Iter [145450/160000] lr: 1.172e-06, eta: 1:15:44, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8356, loss: 0.0789 2023-03-04 09:28:35,622 - mmseg - INFO - Iter [145500/160000] lr: 1.172e-06, eta: 1:15:29, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9227, loss: 0.0778 2023-03-04 09:28:47,856 - mmseg - INFO - Iter [145550/160000] lr: 1.172e-06, eta: 1:15:13, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7826, loss: 0.0814 2023-03-04 09:29:00,192 - mmseg - INFO - Iter [145600/160000] lr: 1.172e-06, eta: 1:14:57, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8244, loss: 0.0794 2023-03-04 09:29:14,625 - mmseg - INFO - Iter [145650/160000] lr: 1.172e-06, eta: 1:14:41, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9461, loss: 0.0768 2023-03-04 09:29:26,805 - mmseg - INFO - Iter [145700/160000] lr: 1.172e-06, eta: 1:14:25, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8780, loss: 0.0793 2023-03-04 09:29:39,168 - mmseg - INFO - Iter [145750/160000] lr: 1.172e-06, eta: 1:14:09, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9752, loss: 0.0774 2023-03-04 09:29:51,361 - mmseg - INFO - Iter [145800/160000] lr: 1.172e-06, eta: 1:13:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7659, loss: 0.0817 2023-03-04 09:30:05,863 - mmseg - INFO - Iter [145850/160000] lr: 1.172e-06, eta: 1:13:37, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9328, loss: 0.0770 2023-03-04 09:30:18,087 - mmseg - INFO - Iter [145900/160000] lr: 1.172e-06, eta: 1:13:21, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7749, loss: 0.0812 2023-03-04 09:30:30,272 - mmseg - INFO - Iter [145950/160000] lr: 1.172e-06, eta: 1:13:06, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8011, loss: 0.0811 2023-03-04 09:30:42,507 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:30:42,507 - mmseg - INFO - Iter [146000/160000] lr: 1.172e-06, eta: 1:12:50, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7925, loss: 0.0811 2023-03-04 09:30:57,039 - mmseg - INFO - Iter [146050/160000] lr: 1.172e-06, eta: 1:12:34, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9305, loss: 0.0773 2023-03-04 09:31:09,334 - mmseg - INFO - Iter [146100/160000] lr: 1.172e-06, eta: 1:12:18, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.7749, loss: 0.0822 2023-03-04 09:31:21,424 - mmseg - INFO - Iter [146150/160000] lr: 1.172e-06, eta: 1:12:02, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 96.9712, loss: 0.0766 2023-03-04 09:31:36,050 - mmseg - INFO - Iter [146200/160000] lr: 1.172e-06, eta: 1:11:46, time: 0.293, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8820, loss: 0.0784 2023-03-04 09:31:48,269 - mmseg - INFO - Iter [146250/160000] lr: 1.172e-06, eta: 1:11:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 96.9834, loss: 0.0754 2023-03-04 09:32:00,464 - mmseg - INFO - Iter [146300/160000] lr: 1.172e-06, eta: 1:11:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9368, loss: 0.0777 2023-03-04 09:32:12,644 - mmseg - INFO - Iter [146350/160000] lr: 1.172e-06, eta: 1:10:59, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7068, loss: 0.0832 2023-03-04 09:32:27,075 - mmseg - INFO - Iter [146400/160000] lr: 1.172e-06, eta: 1:10:43, time: 0.289, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8858, loss: 0.0795 2023-03-04 09:32:39,257 - mmseg - INFO - Iter [146450/160000] lr: 1.172e-06, eta: 1:10:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9242, loss: 0.0777 2023-03-04 09:32:51,293 - mmseg - INFO - Iter [146500/160000] lr: 1.172e-06, eta: 1:10:11, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7812, loss: 0.0817 2023-03-04 09:33:03,397 - mmseg - INFO - Iter [146550/160000] lr: 1.172e-06, eta: 1:09:55, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9321, loss: 0.0769 2023-03-04 09:33:17,876 - mmseg - INFO - Iter [146600/160000] lr: 1.172e-06, eta: 1:09:39, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8275, loss: 0.0802 2023-03-04 09:33:30,088 - mmseg - INFO - Iter [146650/160000] lr: 1.172e-06, eta: 1:09:23, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7758, loss: 0.0817 2023-03-04 09:33:42,226 - mmseg - INFO - Iter [146700/160000] lr: 1.172e-06, eta: 1:09:08, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9600, loss: 0.0770 2023-03-04 09:33:54,306 - mmseg - INFO - Iter [146750/160000] lr: 1.172e-06, eta: 1:08:52, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8517, loss: 0.0794 2023-03-04 09:34:08,802 - mmseg - INFO - Iter [146800/160000] lr: 1.172e-06, eta: 1:08:36, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0834, decode.acc_seg: 96.7407, loss: 0.0834 2023-03-04 09:34:20,989 - mmseg - INFO - Iter [146850/160000] lr: 1.172e-06, eta: 1:08:20, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8457, loss: 0.0801 2023-03-04 09:34:33,153 - mmseg - INFO - Iter [146900/160000] lr: 1.172e-06, eta: 1:08:04, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8993, loss: 0.0788 2023-03-04 09:34:47,617 - mmseg - INFO - Iter [146950/160000] lr: 1.172e-06, eta: 1:07:48, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8678, loss: 0.0795 2023-03-04 09:34:59,862 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:34:59,863 - mmseg - INFO - Iter [147000/160000] lr: 1.172e-06, eta: 1:07:33, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.9076, loss: 0.0797 2023-03-04 09:35:12,055 - mmseg - INFO - Iter [147050/160000] lr: 1.172e-06, eta: 1:07:17, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8728, loss: 0.0785 2023-03-04 09:35:24,367 - mmseg - INFO - Iter [147100/160000] lr: 1.172e-06, eta: 1:07:01, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8716, loss: 0.0792 2023-03-04 09:35:38,808 - mmseg - INFO - Iter [147150/160000] lr: 1.172e-06, eta: 1:06:45, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8394, loss: 0.0798 2023-03-04 09:35:50,971 - mmseg - INFO - Iter [147200/160000] lr: 1.172e-06, eta: 1:06:29, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8951, loss: 0.0780 2023-03-04 09:36:03,083 - mmseg - INFO - Iter [147250/160000] lr: 1.172e-06, eta: 1:06:13, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0752, decode.acc_seg: 96.9848, loss: 0.0752 2023-03-04 09:36:15,269 - mmseg - INFO - Iter [147300/160000] lr: 1.172e-06, eta: 1:05:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8353, loss: 0.0803 2023-03-04 09:36:29,798 - mmseg - INFO - Iter [147350/160000] lr: 1.172e-06, eta: 1:05:42, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9246, loss: 0.0768 2023-03-04 09:36:41,960 - mmseg - INFO - Iter [147400/160000] lr: 1.172e-06, eta: 1:05:26, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8494, loss: 0.0795 2023-03-04 09:36:54,138 - mmseg - INFO - Iter [147450/160000] lr: 1.172e-06, eta: 1:05:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9177, loss: 0.0780 2023-03-04 09:37:08,671 - mmseg - INFO - Iter [147500/160000] lr: 1.172e-06, eta: 1:04:54, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9042, loss: 0.0786 2023-03-04 09:37:20,806 - mmseg - INFO - Iter [147550/160000] lr: 1.172e-06, eta: 1:04:39, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9230, loss: 0.0779 2023-03-04 09:37:32,902 - mmseg - INFO - Iter [147600/160000] lr: 1.172e-06, eta: 1:04:23, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8735, loss: 0.0790 2023-03-04 09:37:45,203 - mmseg - INFO - Iter [147650/160000] lr: 1.172e-06, eta: 1:04:07, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8599, loss: 0.0795 2023-03-04 09:37:59,684 - mmseg - INFO - Iter [147700/160000] lr: 1.172e-06, eta: 1:03:51, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9054, loss: 0.0779 2023-03-04 09:38:11,832 - mmseg - INFO - Iter [147750/160000] lr: 1.172e-06, eta: 1:03:35, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7790, loss: 0.0821 2023-03-04 09:38:24,107 - mmseg - INFO - Iter [147800/160000] lr: 1.172e-06, eta: 1:03:19, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7858, loss: 0.0809 2023-03-04 09:38:36,256 - mmseg - INFO - Iter [147850/160000] lr: 1.172e-06, eta: 1:03:04, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9036, loss: 0.0786 2023-03-04 09:38:50,914 - mmseg - INFO - Iter [147900/160000] lr: 1.172e-06, eta: 1:02:48, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9137, loss: 0.0769 2023-03-04 09:39:03,000 - mmseg - INFO - Iter [147950/160000] lr: 1.172e-06, eta: 1:02:32, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9437, loss: 0.0778 2023-03-04 09:39:15,098 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:39:15,098 - mmseg - INFO - Iter [148000/160000] lr: 1.172e-06, eta: 1:02:16, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9347, loss: 0.0780 2023-03-04 09:39:27,367 - mmseg - INFO - Iter [148050/160000] lr: 1.172e-06, eta: 1:02:00, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7856, loss: 0.0809 2023-03-04 09:39:41,867 - mmseg - INFO - Iter [148100/160000] lr: 1.172e-06, eta: 1:01:45, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0859, decode.acc_seg: 96.7561, loss: 0.0859 2023-03-04 09:39:53,964 - mmseg - INFO - Iter [148150/160000] lr: 1.172e-06, eta: 1:01:29, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.7920, loss: 0.0803 2023-03-04 09:40:06,068 - mmseg - INFO - Iter [148200/160000] lr: 1.172e-06, eta: 1:01:13, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8803, loss: 0.0783 2023-03-04 09:40:20,554 - mmseg - INFO - Iter [148250/160000] lr: 1.172e-06, eta: 1:00:57, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0754, decode.acc_seg: 97.0000, loss: 0.0754 2023-03-04 09:40:32,747 - mmseg - INFO - Iter [148300/160000] lr: 1.172e-06, eta: 1:00:42, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8697, loss: 0.0792 2023-03-04 09:40:44,877 - mmseg - INFO - Iter [148350/160000] lr: 1.172e-06, eta: 1:00:26, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9087, loss: 0.0779 2023-03-04 09:40:57,069 - mmseg - INFO - Iter [148400/160000] lr: 1.172e-06, eta: 1:00:10, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9041, loss: 0.0788 2023-03-04 09:41:11,611 - mmseg - INFO - Iter [148450/160000] lr: 1.172e-06, eta: 0:59:54, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7937, loss: 0.0812 2023-03-04 09:41:23,751 - mmseg - INFO - Iter [148500/160000] lr: 1.172e-06, eta: 0:59:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0824, decode.acc_seg: 96.7683, loss: 0.0824 2023-03-04 09:41:35,877 - mmseg - INFO - Iter [148550/160000] lr: 1.172e-06, eta: 0:59:23, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7995, loss: 0.0805 2023-03-04 09:41:48,116 - mmseg - INFO - Iter [148600/160000] lr: 1.172e-06, eta: 0:59:07, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9485, loss: 0.0774 2023-03-04 09:42:02,542 - mmseg - INFO - Iter [148650/160000] lr: 1.172e-06, eta: 0:58:51, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8446, loss: 0.0797 2023-03-04 09:42:14,881 - mmseg - INFO - Iter [148700/160000] lr: 1.172e-06, eta: 0:58:35, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9286, loss: 0.0785 2023-03-04 09:42:27,061 - mmseg - INFO - Iter [148750/160000] lr: 1.172e-06, eta: 0:58:20, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8624, loss: 0.0792 2023-03-04 09:42:39,178 - mmseg - INFO - Iter [148800/160000] lr: 1.172e-06, eta: 0:58:04, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8556, loss: 0.0793 2023-03-04 09:42:53,671 - mmseg - INFO - Iter [148850/160000] lr: 1.172e-06, eta: 0:57:48, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8656, loss: 0.0781 2023-03-04 09:43:05,785 - mmseg - INFO - Iter [148900/160000] lr: 1.172e-06, eta: 0:57:32, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8906, loss: 0.0790 2023-03-04 09:43:17,972 - mmseg - INFO - Iter [148950/160000] lr: 1.172e-06, eta: 0:57:16, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8730, loss: 0.0788 2023-03-04 09:43:32,512 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:43:32,513 - mmseg - INFO - Iter [149000/160000] lr: 1.172e-06, eta: 0:57:01, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8362, loss: 0.0798 2023-03-04 09:43:44,791 - mmseg - INFO - Iter [149050/160000] lr: 1.172e-06, eta: 0:56:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8661, loss: 0.0786 2023-03-04 09:43:56,957 - mmseg - INFO - Iter [149100/160000] lr: 1.172e-06, eta: 0:56:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0802, decode.acc_seg: 96.8197, loss: 0.0802 2023-03-04 09:44:09,190 - mmseg - INFO - Iter [149150/160000] lr: 1.172e-06, eta: 0:56:13, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8676, loss: 0.0792 2023-03-04 09:44:23,742 - mmseg - INFO - Iter [149200/160000] lr: 1.172e-06, eta: 0:55:58, time: 0.291, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8577, loss: 0.0784 2023-03-04 09:44:35,891 - mmseg - INFO - Iter [149250/160000] lr: 1.172e-06, eta: 0:55:42, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9034, loss: 0.0785 2023-03-04 09:44:48,195 - mmseg - INFO - Iter [149300/160000] lr: 1.172e-06, eta: 0:55:26, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0851, decode.acc_seg: 96.6137, loss: 0.0851 2023-03-04 09:45:00,447 - mmseg - INFO - Iter [149350/160000] lr: 1.172e-06, eta: 0:55:11, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0757, decode.acc_seg: 96.9817, loss: 0.0757 2023-03-04 09:45:15,024 - mmseg - INFO - Iter [149400/160000] lr: 1.172e-06, eta: 0:54:55, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8624, loss: 0.0793 2023-03-04 09:45:27,172 - mmseg - INFO - Iter [149450/160000] lr: 1.172e-06, eta: 0:54:39, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0766, decode.acc_seg: 97.0303, loss: 0.0766 2023-03-04 09:45:39,402 - mmseg - INFO - Iter [149500/160000] lr: 1.172e-06, eta: 0:54:23, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9818, loss: 0.0756 2023-03-04 09:45:53,897 - mmseg - INFO - Iter [149550/160000] lr: 1.172e-06, eta: 0:54:08, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8484, loss: 0.0793 2023-03-04 09:46:06,099 - mmseg - INFO - Iter [149600/160000] lr: 1.172e-06, eta: 0:53:52, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9237, loss: 0.0784 2023-03-04 09:46:18,227 - mmseg - INFO - Iter [149650/160000] lr: 1.172e-06, eta: 0:53:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9359, loss: 0.0781 2023-03-04 09:46:30,408 - mmseg - INFO - Iter [149700/160000] lr: 1.172e-06, eta: 0:53:20, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9868, loss: 0.0767 2023-03-04 09:46:44,904 - mmseg - INFO - Iter [149750/160000] lr: 1.172e-06, eta: 0:53:05, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0798, decode.acc_seg: 96.8580, loss: 0.0798 2023-03-04 09:46:57,175 - mmseg - INFO - Iter [149800/160000] lr: 1.172e-06, eta: 0:52:49, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.8790, loss: 0.0777 2023-03-04 09:47:09,335 - mmseg - INFO - Iter [149850/160000] lr: 1.172e-06, eta: 0:52:33, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7922, loss: 0.0808 2023-03-04 09:47:21,576 - mmseg - INFO - Iter [149900/160000] lr: 1.172e-06, eta: 0:52:18, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9059, loss: 0.0775 2023-03-04 09:47:36,229 - mmseg - INFO - Iter [149950/160000] lr: 1.172e-06, eta: 0:52:02, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8704, loss: 0.0788 2023-03-04 09:47:48,411 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:47:48,411 - mmseg - INFO - Iter [150000/160000] lr: 1.172e-06, eta: 0:51:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9271, loss: 0.0777 2023-03-04 09:48:00,635 - mmseg - INFO - Iter [150050/160000] lr: 1.172e-06, eta: 0:51:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9195, loss: 0.0781 2023-03-04 09:48:12,860 - mmseg - INFO - Iter [150100/160000] lr: 1.172e-06, eta: 0:51:15, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8031, loss: 0.0803 2023-03-04 09:48:27,606 - mmseg - INFO - Iter [150150/160000] lr: 1.172e-06, eta: 0:50:59, time: 0.295, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8774, loss: 0.0779 2023-03-04 09:48:39,816 - mmseg - INFO - Iter [150200/160000] lr: 1.172e-06, eta: 0:50:43, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9057, loss: 0.0782 2023-03-04 09:48:52,219 - mmseg - INFO - Iter [150250/160000] lr: 1.172e-06, eta: 0:50:28, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8499, loss: 0.0801 2023-03-04 09:49:06,745 - mmseg - INFO - Iter [150300/160000] lr: 1.172e-06, eta: 0:50:12, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8320, loss: 0.0794 2023-03-04 09:49:18,927 - mmseg - INFO - Iter [150350/160000] lr: 1.172e-06, eta: 0:49:56, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8761, loss: 0.0786 2023-03-04 09:49:31,115 - mmseg - INFO - Iter [150400/160000] lr: 1.172e-06, eta: 0:49:41, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8817, loss: 0.0792 2023-03-04 09:49:43,376 - mmseg - INFO - Iter [150450/160000] lr: 1.172e-06, eta: 0:49:25, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0750, decode.acc_seg: 97.0450, loss: 0.0750 2023-03-04 09:49:57,883 - mmseg - INFO - Iter [150500/160000] lr: 1.172e-06, eta: 0:49:09, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0849, decode.acc_seg: 96.7128, loss: 0.0849 2023-03-04 09:50:10,077 - mmseg - INFO - Iter [150550/160000] lr: 1.172e-06, eta: 0:48:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9026, loss: 0.0784 2023-03-04 09:50:22,317 - mmseg - INFO - Iter [150600/160000] lr: 1.172e-06, eta: 0:48:38, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9115, loss: 0.0778 2023-03-04 09:50:34,650 - mmseg - INFO - Iter [150650/160000] lr: 1.172e-06, eta: 0:48:22, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7455, loss: 0.0819 2023-03-04 09:50:49,101 - mmseg - INFO - Iter [150700/160000] lr: 1.172e-06, eta: 0:48:06, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8799, loss: 0.0785 2023-03-04 09:51:01,303 - mmseg - INFO - Iter [150750/160000] lr: 1.172e-06, eta: 0:47:51, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8681, loss: 0.0787 2023-03-04 09:51:13,463 - mmseg - INFO - Iter [150800/160000] lr: 1.172e-06, eta: 0:47:35, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8479, loss: 0.0803 2023-03-04 09:51:28,118 - mmseg - INFO - Iter [150850/160000] lr: 1.172e-06, eta: 0:47:19, time: 0.293, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9800, loss: 0.0764 2023-03-04 09:51:40,347 - mmseg - INFO - Iter [150900/160000] lr: 1.172e-06, eta: 0:47:04, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0819, decode.acc_seg: 96.7542, loss: 0.0819 2023-03-04 09:51:52,450 - mmseg - INFO - Iter [150950/160000] lr: 1.172e-06, eta: 0:46:48, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9229, loss: 0.0775 2023-03-04 09:52:04,635 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:52:04,636 - mmseg - INFO - Iter [151000/160000] lr: 1.172e-06, eta: 0:46:32, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7976, loss: 0.0811 2023-03-04 09:52:19,225 - mmseg - INFO - Iter [151050/160000] lr: 1.172e-06, eta: 0:46:17, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9148, loss: 0.0782 2023-03-04 09:52:31,434 - mmseg - INFO - Iter [151100/160000] lr: 1.172e-06, eta: 0:46:01, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0764, decode.acc_seg: 96.9654, loss: 0.0764 2023-03-04 09:52:43,648 - mmseg - INFO - Iter [151150/160000] lr: 1.172e-06, eta: 0:45:45, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8497, loss: 0.0805 2023-03-04 09:52:55,914 - mmseg - INFO - Iter [151200/160000] lr: 1.172e-06, eta: 0:45:30, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.7643, loss: 0.0814 2023-03-04 09:53:10,337 - mmseg - INFO - Iter [151250/160000] lr: 1.172e-06, eta: 0:45:14, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8690, loss: 0.0791 2023-03-04 09:53:22,756 - mmseg - INFO - Iter [151300/160000] lr: 1.172e-06, eta: 0:44:58, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9514, loss: 0.0773 2023-03-04 09:53:35,036 - mmseg - INFO - Iter [151350/160000] lr: 1.172e-06, eta: 0:44:43, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9492, loss: 0.0772 2023-03-04 09:53:47,197 - mmseg - INFO - Iter [151400/160000] lr: 1.172e-06, eta: 0:44:27, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8778, loss: 0.0785 2023-03-04 09:54:01,851 - mmseg - INFO - Iter [151450/160000] lr: 1.172e-06, eta: 0:44:11, time: 0.293, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8343, loss: 0.0797 2023-03-04 09:54:14,018 - mmseg - INFO - Iter [151500/160000] lr: 1.172e-06, eta: 0:43:56, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0823, decode.acc_seg: 96.7686, loss: 0.0823 2023-03-04 09:54:26,219 - mmseg - INFO - Iter [151550/160000] lr: 1.172e-06, eta: 0:43:40, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8444, loss: 0.0786 2023-03-04 09:54:40,818 - mmseg - INFO - Iter [151600/160000] lr: 1.172e-06, eta: 0:43:24, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9930, loss: 0.0770 2023-03-04 09:54:53,273 - mmseg - INFO - Iter [151650/160000] lr: 1.172e-06, eta: 0:43:09, time: 0.249, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9153, loss: 0.0785 2023-03-04 09:55:05,515 - mmseg - INFO - Iter [151700/160000] lr: 1.172e-06, eta: 0:42:53, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9604, loss: 0.0770 2023-03-04 09:55:17,587 - mmseg - INFO - Iter [151750/160000] lr: 1.172e-06, eta: 0:42:37, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0822, decode.acc_seg: 96.8285, loss: 0.0822 2023-03-04 09:55:32,010 - mmseg - INFO - Iter [151800/160000] lr: 1.172e-06, eta: 0:42:22, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8207, loss: 0.0789 2023-03-04 09:55:44,161 - mmseg - INFO - Iter [151850/160000] lr: 1.172e-06, eta: 0:42:06, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9005, loss: 0.0777 2023-03-04 09:55:56,257 - mmseg - INFO - Iter [151900/160000] lr: 1.172e-06, eta: 0:41:50, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9275, loss: 0.0768 2023-03-04 09:56:08,402 - mmseg - INFO - Iter [151950/160000] lr: 1.172e-06, eta: 0:41:35, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9039, loss: 0.0784 2023-03-04 09:56:22,946 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 09:56:22,946 - mmseg - INFO - Iter [152000/160000] lr: 1.172e-06, eta: 0:41:19, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0830, decode.acc_seg: 96.7576, loss: 0.0830 2023-03-04 09:56:35,165 - mmseg - INFO - Iter [152050/160000] lr: 1.172e-06, eta: 0:41:04, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0814, decode.acc_seg: 96.8203, loss: 0.0814 2023-03-04 09:56:47,506 - mmseg - INFO - Iter [152100/160000] lr: 1.172e-06, eta: 0:40:48, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0796, decode.acc_seg: 96.8316, loss: 0.0796 2023-03-04 09:57:02,045 - mmseg - INFO - Iter [152150/160000] lr: 1.172e-06, eta: 0:40:32, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9039, loss: 0.0782 2023-03-04 09:57:14,282 - mmseg - INFO - Iter [152200/160000] lr: 1.172e-06, eta: 0:40:17, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7889, loss: 0.0817 2023-03-04 09:57:26,340 - mmseg - INFO - Iter [152250/160000] lr: 1.172e-06, eta: 0:40:01, time: 0.241, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.9193, loss: 0.0780 2023-03-04 09:57:38,569 - mmseg - INFO - Iter [152300/160000] lr: 1.172e-06, eta: 0:39:45, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9637, loss: 0.0769 2023-03-04 09:57:53,168 - mmseg - INFO - Iter [152350/160000] lr: 1.172e-06, eta: 0:39:30, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0803, decode.acc_seg: 96.8051, loss: 0.0803 2023-03-04 09:58:05,358 - mmseg - INFO - Iter [152400/160000] lr: 1.172e-06, eta: 0:39:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0755, decode.acc_seg: 96.9979, loss: 0.0755 2023-03-04 09:58:17,489 - mmseg - INFO - Iter [152450/160000] lr: 1.172e-06, eta: 0:38:58, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.8583, loss: 0.0809 2023-03-04 09:58:29,625 - mmseg - INFO - Iter [152500/160000] lr: 1.172e-06, eta: 0:38:43, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7380, loss: 0.0825 2023-03-04 09:58:44,309 - mmseg - INFO - Iter [152550/160000] lr: 1.172e-06, eta: 0:38:27, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8488, loss: 0.0800 2023-03-04 09:58:56,382 - mmseg - INFO - Iter [152600/160000] lr: 1.172e-06, eta: 0:38:12, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8743, loss: 0.0782 2023-03-04 09:59:08,548 - mmseg - INFO - Iter [152650/160000] lr: 1.172e-06, eta: 0:37:56, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8551, loss: 0.0788 2023-03-04 09:59:20,830 - mmseg - INFO - Iter [152700/160000] lr: 1.172e-06, eta: 0:37:40, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8388, loss: 0.0794 2023-03-04 09:59:35,426 - mmseg - INFO - Iter [152750/160000] lr: 1.172e-06, eta: 0:37:25, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8826, loss: 0.0780 2023-03-04 09:59:47,565 - mmseg - INFO - Iter [152800/160000] lr: 1.172e-06, eta: 0:37:09, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8383, loss: 0.0791 2023-03-04 09:59:59,828 - mmseg - INFO - Iter [152850/160000] lr: 1.172e-06, eta: 0:36:54, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8425, loss: 0.0799 2023-03-04 10:00:14,373 - mmseg - INFO - Iter [152900/160000] lr: 1.172e-06, eta: 0:36:38, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9237, loss: 0.0770 2023-03-04 10:00:26,492 - mmseg - INFO - Iter [152950/160000] lr: 1.172e-06, eta: 0:36:22, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.8792, loss: 0.0779 2023-03-04 10:00:38,728 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:00:38,728 - mmseg - INFO - Iter [153000/160000] lr: 1.172e-06, eta: 0:36:07, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8383, loss: 0.0801 2023-03-04 10:00:51,114 - mmseg - INFO - Iter [153050/160000] lr: 1.172e-06, eta: 0:35:51, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8484, loss: 0.0785 2023-03-04 10:01:05,670 - mmseg - INFO - Iter [153100/160000] lr: 1.172e-06, eta: 0:35:36, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9834, loss: 0.0772 2023-03-04 10:01:17,893 - mmseg - INFO - Iter [153150/160000] lr: 1.172e-06, eta: 0:35:20, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0759, decode.acc_seg: 97.0134, loss: 0.0759 2023-03-04 10:01:30,153 - mmseg - INFO - Iter [153200/160000] lr: 1.172e-06, eta: 0:35:04, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9106, loss: 0.0778 2023-03-04 10:01:42,429 - mmseg - INFO - Iter [153250/160000] lr: 1.172e-06, eta: 0:34:49, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7549, loss: 0.0817 2023-03-04 10:01:56,994 - mmseg - INFO - Iter [153300/160000] lr: 1.172e-06, eta: 0:34:33, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8381, loss: 0.0804 2023-03-04 10:02:09,169 - mmseg - INFO - Iter [153350/160000] lr: 1.172e-06, eta: 0:34:18, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.8877, loss: 0.0790 2023-03-04 10:02:21,330 - mmseg - INFO - Iter [153400/160000] lr: 1.172e-06, eta: 0:34:02, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0763, decode.acc_seg: 96.9884, loss: 0.0763 2023-03-04 10:02:33,523 - mmseg - INFO - Iter [153450/160000] lr: 1.172e-06, eta: 0:33:46, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8267, loss: 0.0795 2023-03-04 10:02:47,964 - mmseg - INFO - Iter [153500/160000] lr: 1.172e-06, eta: 0:33:31, time: 0.289, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.7946, loss: 0.0806 2023-03-04 10:03:00,271 - mmseg - INFO - Iter [153550/160000] lr: 1.172e-06, eta: 0:33:15, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0755, decode.acc_seg: 96.9933, loss: 0.0755 2023-03-04 10:03:12,485 - mmseg - INFO - Iter [153600/160000] lr: 1.172e-06, eta: 0:33:00, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8917, loss: 0.0782 2023-03-04 10:03:27,034 - mmseg - INFO - Iter [153650/160000] lr: 1.172e-06, eta: 0:32:44, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8585, loss: 0.0797 2023-03-04 10:03:39,150 - mmseg - INFO - Iter [153700/160000] lr: 1.172e-06, eta: 0:32:29, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0790, decode.acc_seg: 96.9214, loss: 0.0790 2023-03-04 10:03:51,262 - mmseg - INFO - Iter [153750/160000] lr: 1.172e-06, eta: 0:32:13, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.9261, loss: 0.0776 2023-03-04 10:04:03,404 - mmseg - INFO - Iter [153800/160000] lr: 1.172e-06, eta: 0:31:57, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7748, loss: 0.0825 2023-03-04 10:04:18,013 - mmseg - INFO - Iter [153850/160000] lr: 1.172e-06, eta: 0:31:42, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8533, loss: 0.0787 2023-03-04 10:04:30,277 - mmseg - INFO - Iter [153900/160000] lr: 1.172e-06, eta: 0:31:26, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8485, loss: 0.0792 2023-03-04 10:04:42,453 - mmseg - INFO - Iter [153950/160000] lr: 1.172e-06, eta: 0:31:11, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0809, decode.acc_seg: 96.7814, loss: 0.0809 2023-03-04 10:04:54,649 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:04:54,649 - mmseg - INFO - Iter [154000/160000] lr: 1.172e-06, eta: 0:30:55, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9552, loss: 0.0767 2023-03-04 10:05:09,276 - mmseg - INFO - Iter [154050/160000] lr: 1.172e-06, eta: 0:30:40, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9438, loss: 0.0775 2023-03-04 10:05:21,402 - mmseg - INFO - Iter [154100/160000] lr: 1.172e-06, eta: 0:30:24, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8619, loss: 0.0789 2023-03-04 10:05:33,668 - mmseg - INFO - Iter [154150/160000] lr: 1.172e-06, eta: 0:30:08, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9832, loss: 0.0756 2023-03-04 10:05:48,185 - mmseg - INFO - Iter [154200/160000] lr: 1.172e-06, eta: 0:29:53, time: 0.290, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.8055, loss: 0.0832 2023-03-04 10:06:00,569 - mmseg - INFO - Iter [154250/160000] lr: 1.172e-06, eta: 0:29:37, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7727, loss: 0.0816 2023-03-04 10:06:12,750 - mmseg - INFO - Iter [154300/160000] lr: 1.172e-06, eta: 0:29:22, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9724, loss: 0.0756 2023-03-04 10:06:24,875 - mmseg - INFO - Iter [154350/160000] lr: 1.172e-06, eta: 0:29:06, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8848, loss: 0.0785 2023-03-04 10:06:39,357 - mmseg - INFO - Iter [154400/160000] lr: 1.172e-06, eta: 0:28:51, time: 0.290, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9222, loss: 0.0779 2023-03-04 10:06:51,538 - mmseg - INFO - Iter [154450/160000] lr: 1.172e-06, eta: 0:28:35, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.7867, loss: 0.0810 2023-03-04 10:07:03,676 - mmseg - INFO - Iter [154500/160000] lr: 1.172e-06, eta: 0:28:20, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9064, loss: 0.0781 2023-03-04 10:07:15,928 - mmseg - INFO - Iter [154550/160000] lr: 1.172e-06, eta: 0:28:04, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8798, loss: 0.0783 2023-03-04 10:07:30,402 - mmseg - INFO - Iter [154600/160000] lr: 1.172e-06, eta: 0:27:48, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8588, loss: 0.0789 2023-03-04 10:07:42,675 - mmseg - INFO - Iter [154650/160000] lr: 1.172e-06, eta: 0:27:33, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9259, loss: 0.0769 2023-03-04 10:07:54,797 - mmseg - INFO - Iter [154700/160000] lr: 1.172e-06, eta: 0:27:17, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9188, loss: 0.0774 2023-03-04 10:08:07,057 - mmseg - INFO - Iter [154750/160000] lr: 1.172e-06, eta: 0:27:02, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0771, decode.acc_seg: 96.9673, loss: 0.0771 2023-03-04 10:08:21,587 - mmseg - INFO - Iter [154800/160000] lr: 1.172e-06, eta: 0:26:46, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9479, loss: 0.0770 2023-03-04 10:08:33,705 - mmseg - INFO - Iter [154850/160000] lr: 1.172e-06, eta: 0:26:31, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8359, loss: 0.0804 2023-03-04 10:08:46,059 - mmseg - INFO - Iter [154900/160000] lr: 1.172e-06, eta: 0:26:15, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8360, loss: 0.0800 2023-03-04 10:09:00,664 - mmseg - INFO - Iter [154950/160000] lr: 1.172e-06, eta: 0:26:00, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.8982, loss: 0.0778 2023-03-04 10:09:12,771 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:09:12,772 - mmseg - INFO - Iter [155000/160000] lr: 1.172e-06, eta: 0:25:44, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9112, loss: 0.0782 2023-03-04 10:09:24,992 - mmseg - INFO - Iter [155050/160000] lr: 1.172e-06, eta: 0:25:29, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0745, decode.acc_seg: 97.0143, loss: 0.0745 2023-03-04 10:09:37,159 - mmseg - INFO - Iter [155100/160000] lr: 1.172e-06, eta: 0:25:13, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8323, loss: 0.0792 2023-03-04 10:09:51,629 - mmseg - INFO - Iter [155150/160000] lr: 1.172e-06, eta: 0:24:58, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.7833, loss: 0.0805 2023-03-04 10:10:04,000 - mmseg - INFO - Iter [155200/160000] lr: 1.172e-06, eta: 0:24:42, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8190, loss: 0.0805 2023-03-04 10:10:16,185 - mmseg - INFO - Iter [155250/160000] lr: 1.172e-06, eta: 0:24:26, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.9240, loss: 0.0787 2023-03-04 10:10:28,332 - mmseg - INFO - Iter [155300/160000] lr: 1.172e-06, eta: 0:24:11, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0825, decode.acc_seg: 96.7206, loss: 0.0825 2023-03-04 10:10:42,806 - mmseg - INFO - Iter [155350/160000] lr: 1.172e-06, eta: 0:23:55, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0812, decode.acc_seg: 96.7938, loss: 0.0812 2023-03-04 10:10:55,054 - mmseg - INFO - Iter [155400/160000] lr: 1.172e-06, eta: 0:23:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9573, loss: 0.0775 2023-03-04 10:11:07,122 - mmseg - INFO - Iter [155450/160000] lr: 1.172e-06, eta: 0:23:24, time: 0.241, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9004, loss: 0.0782 2023-03-04 10:11:21,505 - mmseg - INFO - Iter [155500/160000] lr: 1.172e-06, eta: 0:23:09, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0772, decode.acc_seg: 96.9093, loss: 0.0772 2023-03-04 10:11:33,598 - mmseg - INFO - Iter [155550/160000] lr: 1.172e-06, eta: 0:22:53, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0795, decode.acc_seg: 96.8536, loss: 0.0795 2023-03-04 10:11:45,735 - mmseg - INFO - Iter [155600/160000] lr: 1.172e-06, eta: 0:22:38, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0841, decode.acc_seg: 96.7112, loss: 0.0841 2023-03-04 10:11:57,858 - mmseg - INFO - Iter [155650/160000] lr: 1.172e-06, eta: 0:22:22, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8653, loss: 0.0799 2023-03-04 10:12:12,282 - mmseg - INFO - Iter [155700/160000] lr: 1.172e-06, eta: 0:22:07, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.7685, loss: 0.0808 2023-03-04 10:12:24,558 - mmseg - INFO - Iter [155750/160000] lr: 1.172e-06, eta: 0:21:51, time: 0.246, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8515, loss: 0.0789 2023-03-04 10:12:36,729 - mmseg - INFO - Iter [155800/160000] lr: 1.172e-06, eta: 0:21:36, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8744, loss: 0.0791 2023-03-04 10:12:48,857 - mmseg - INFO - Iter [155850/160000] lr: 1.172e-06, eta: 0:21:20, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8818, loss: 0.0794 2023-03-04 10:13:03,428 - mmseg - INFO - Iter [155900/160000] lr: 1.172e-06, eta: 0:21:05, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9475, loss: 0.0769 2023-03-04 10:13:15,826 - mmseg - INFO - Iter [155950/160000] lr: 1.172e-06, eta: 0:20:49, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.9433, loss: 0.0788 2023-03-04 10:13:28,050 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:13:28,050 - mmseg - INFO - Iter [156000/160000] lr: 1.172e-06, eta: 0:20:34, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8739, loss: 0.0785 2023-03-04 10:13:40,333 - mmseg - INFO - Iter [156050/160000] lr: 1.172e-06, eta: 0:20:18, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0780, decode.acc_seg: 96.8827, loss: 0.0780 2023-03-04 10:13:54,935 - mmseg - INFO - Iter [156100/160000] lr: 1.172e-06, eta: 0:20:03, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.9057, loss: 0.0785 2023-03-04 10:14:07,164 - mmseg - INFO - Iter [156150/160000] lr: 1.172e-06, eta: 0:19:47, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8195, loss: 0.0801 2023-03-04 10:14:19,343 - mmseg - INFO - Iter [156200/160000] lr: 1.172e-06, eta: 0:19:32, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 97.0143, loss: 0.0756 2023-03-04 10:14:34,085 - mmseg - INFO - Iter [156250/160000] lr: 1.172e-06, eta: 0:19:16, time: 0.295, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.8891, loss: 0.0769 2023-03-04 10:14:46,258 - mmseg - INFO - Iter [156300/160000] lr: 1.172e-06, eta: 0:19:01, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8697, loss: 0.0786 2023-03-04 10:14:58,405 - mmseg - INFO - Iter [156350/160000] lr: 1.172e-06, eta: 0:18:45, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 97.0000, loss: 0.0762 2023-03-04 10:15:10,685 - mmseg - INFO - Iter [156400/160000] lr: 1.172e-06, eta: 0:18:30, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.8935, loss: 0.0781 2023-03-04 10:15:25,242 - mmseg - INFO - Iter [156450/160000] lr: 1.172e-06, eta: 0:18:14, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9017, loss: 0.0767 2023-03-04 10:15:37,441 - mmseg - INFO - Iter [156500/160000] lr: 1.172e-06, eta: 0:17:59, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8344, loss: 0.0804 2023-03-04 10:15:49,544 - mmseg - INFO - Iter [156550/160000] lr: 1.172e-06, eta: 0:17:43, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8711, loss: 0.0793 2023-03-04 10:16:01,834 - mmseg - INFO - Iter [156600/160000] lr: 1.172e-06, eta: 0:17:28, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0778, decode.acc_seg: 96.9006, loss: 0.0778 2023-03-04 10:16:16,452 - mmseg - INFO - Iter [156650/160000] lr: 1.172e-06, eta: 0:17:13, time: 0.292, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8027, loss: 0.0806 2023-03-04 10:16:28,822 - mmseg - INFO - Iter [156700/160000] lr: 1.172e-06, eta: 0:16:57, time: 0.248, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9431, loss: 0.0768 2023-03-04 10:16:41,089 - mmseg - INFO - Iter [156750/160000] lr: 1.172e-06, eta: 0:16:42, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.8916, loss: 0.0784 2023-03-04 10:16:55,492 - mmseg - INFO - Iter [156800/160000] lr: 1.172e-06, eta: 0:16:26, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8190, loss: 0.0805 2023-03-04 10:17:07,618 - mmseg - INFO - Iter [156850/160000] lr: 1.172e-06, eta: 0:16:11, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9044, loss: 0.0786 2023-03-04 10:17:19,923 - mmseg - INFO - Iter [156900/160000] lr: 1.172e-06, eta: 0:15:55, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8773, loss: 0.0785 2023-03-04 10:17:32,157 - mmseg - INFO - Iter [156950/160000] lr: 1.172e-06, eta: 0:15:40, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0789, decode.acc_seg: 96.8613, loss: 0.0789 2023-03-04 10:17:46,694 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:17:46,694 - mmseg - INFO - Iter [157000/160000] lr: 1.172e-06, eta: 0:15:24, time: 0.291, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8673, loss: 0.0783 2023-03-04 10:17:58,792 - mmseg - INFO - Iter [157050/160000] lr: 1.172e-06, eta: 0:15:09, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8827, loss: 0.0785 2023-03-04 10:18:10,984 - mmseg - INFO - Iter [157100/160000] lr: 1.172e-06, eta: 0:14:53, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.8981, loss: 0.0782 2023-03-04 10:18:23,214 - mmseg - INFO - Iter [157150/160000] lr: 1.172e-06, eta: 0:14:38, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.7651, loss: 0.0811 2023-03-04 10:18:37,759 - mmseg - INFO - Iter [157200/160000] lr: 1.172e-06, eta: 0:14:22, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0815, decode.acc_seg: 96.7914, loss: 0.0815 2023-03-04 10:18:49,919 - mmseg - INFO - Iter [157250/160000] lr: 1.172e-06, eta: 0:14:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0808, decode.acc_seg: 96.8473, loss: 0.0808 2023-03-04 10:19:02,097 - mmseg - INFO - Iter [157300/160000] lr: 1.172e-06, eta: 0:13:52, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8282, loss: 0.0801 2023-03-04 10:19:14,217 - mmseg - INFO - Iter [157350/160000] lr: 1.172e-06, eta: 0:13:36, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8384, loss: 0.0800 2023-03-04 10:19:28,648 - mmseg - INFO - Iter [157400/160000] lr: 1.172e-06, eta: 0:13:21, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8491, loss: 0.0791 2023-03-04 10:19:40,758 - mmseg - INFO - Iter [157450/160000] lr: 1.172e-06, eta: 0:13:05, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0770, decode.acc_seg: 96.9577, loss: 0.0770 2023-03-04 10:19:52,992 - mmseg - INFO - Iter [157500/160000] lr: 1.172e-06, eta: 0:12:50, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8790, loss: 0.0783 2023-03-04 10:20:07,578 - mmseg - INFO - Iter [157550/160000] lr: 1.172e-06, eta: 0:12:34, time: 0.292, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0774, decode.acc_seg: 96.9468, loss: 0.0774 2023-03-04 10:20:19,710 - mmseg - INFO - Iter [157600/160000] lr: 1.172e-06, eta: 0:12:19, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0777, decode.acc_seg: 96.9174, loss: 0.0777 2023-03-04 10:20:31,814 - mmseg - INFO - Iter [157650/160000] lr: 1.172e-06, eta: 0:12:03, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0784, decode.acc_seg: 96.9292, loss: 0.0784 2023-03-04 10:20:44,002 - mmseg - INFO - Iter [157700/160000] lr: 1.172e-06, eta: 0:11:48, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8884, loss: 0.0793 2023-03-04 10:20:58,537 - mmseg - INFO - Iter [157750/160000] lr: 1.172e-06, eta: 0:11:33, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0794, decode.acc_seg: 96.8347, loss: 0.0794 2023-03-04 10:21:10,624 - mmseg - INFO - Iter [157800/160000] lr: 1.172e-06, eta: 0:11:17, time: 0.242, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8562, loss: 0.0800 2023-03-04 10:21:22,803 - mmseg - INFO - Iter [157850/160000] lr: 1.172e-06, eta: 0:11:02, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0762, decode.acc_seg: 96.9847, loss: 0.0762 2023-03-04 10:21:34,934 - mmseg - INFO - Iter [157900/160000] lr: 1.172e-06, eta: 0:10:46, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0785, decode.acc_seg: 96.8385, loss: 0.0785 2023-03-04 10:21:49,642 - mmseg - INFO - Iter [157950/160000] lr: 1.172e-06, eta: 0:10:31, time: 0.294, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0816, decode.acc_seg: 96.7604, loss: 0.0816 2023-03-04 10:22:01,821 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:22:01,821 - mmseg - INFO - Iter [158000/160000] lr: 1.172e-06, eta: 0:10:15, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0817, decode.acc_seg: 96.7660, loss: 0.0817 2023-03-04 10:22:14,066 - mmseg - INFO - Iter [158050/160000] lr: 1.172e-06, eta: 0:10:00, time: 0.245, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0797, decode.acc_seg: 96.8290, loss: 0.0797 2023-03-04 10:22:26,421 - mmseg - INFO - Iter [158100/160000] lr: 1.172e-06, eta: 0:09:44, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0800, decode.acc_seg: 96.8316, loss: 0.0800 2023-03-04 10:22:41,305 - mmseg - INFO - Iter [158150/160000] lr: 1.172e-06, eta: 0:09:29, time: 0.297, data_time: 0.053, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8512, loss: 0.0799 2023-03-04 10:22:53,507 - mmseg - INFO - Iter [158200/160000] lr: 1.172e-06, eta: 0:09:14, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.8087, loss: 0.0801 2023-03-04 10:23:05,829 - mmseg - INFO - Iter [158250/160000] lr: 1.172e-06, eta: 0:08:58, time: 0.247, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0787, decode.acc_seg: 96.8730, loss: 0.0787 2023-03-04 10:23:20,309 - mmseg - INFO - Iter [158300/160000] lr: 1.172e-06, eta: 0:08:43, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.9022, loss: 0.0783 2023-03-04 10:23:32,508 - mmseg - INFO - Iter [158350/160000] lr: 1.172e-06, eta: 0:08:27, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0811, decode.acc_seg: 96.8071, loss: 0.0811 2023-03-04 10:23:44,618 - mmseg - INFO - Iter [158400/160000] lr: 1.172e-06, eta: 0:08:12, time: 0.242, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0781, decode.acc_seg: 96.9054, loss: 0.0781 2023-03-04 10:23:56,780 - mmseg - INFO - Iter [158450/160000] lr: 1.172e-06, eta: 0:07:57, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0836, decode.acc_seg: 96.7514, loss: 0.0836 2023-03-04 10:24:11,176 - mmseg - INFO - Iter [158500/160000] lr: 1.172e-06, eta: 0:07:41, time: 0.288, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0788, decode.acc_seg: 96.8562, loss: 0.0788 2023-03-04 10:24:23,310 - mmseg - INFO - Iter [158550/160000] lr: 1.172e-06, eta: 0:07:26, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0821, decode.acc_seg: 96.7466, loss: 0.0821 2023-03-04 10:24:35,595 - mmseg - INFO - Iter [158600/160000] lr: 1.172e-06, eta: 0:07:10, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0783, decode.acc_seg: 96.8789, loss: 0.0783 2023-03-04 10:24:47,721 - mmseg - INFO - Iter [158650/160000] lr: 1.172e-06, eta: 0:06:55, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0799, decode.acc_seg: 96.8557, loss: 0.0799 2023-03-04 10:25:02,273 - mmseg - INFO - Iter [158700/160000] lr: 1.172e-06, eta: 0:06:40, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0756, decode.acc_seg: 96.9472, loss: 0.0756 2023-03-04 10:25:14,575 - mmseg - INFO - Iter [158750/160000] lr: 1.172e-06, eta: 0:06:24, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0806, decode.acc_seg: 96.8085, loss: 0.0806 2023-03-04 10:25:26,847 - mmseg - INFO - Iter [158800/160000] lr: 1.172e-06, eta: 0:06:09, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0767, decode.acc_seg: 96.9245, loss: 0.0767 2023-03-04 10:25:41,278 - mmseg - INFO - Iter [158850/160000] lr: 1.172e-06, eta: 0:05:53, time: 0.289, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0833, decode.acc_seg: 96.7458, loss: 0.0833 2023-03-04 10:25:53,505 - mmseg - INFO - Iter [158900/160000] lr: 1.172e-06, eta: 0:05:38, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8799, loss: 0.0804 2023-03-04 10:26:05,699 - mmseg - INFO - Iter [158950/160000] lr: 1.172e-06, eta: 0:05:23, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0782, decode.acc_seg: 96.9346, loss: 0.0782 2023-03-04 10:26:17,836 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:26:17,837 - mmseg - INFO - Iter [159000/160000] lr: 1.172e-06, eta: 0:05:07, time: 0.243, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0827, decode.acc_seg: 96.7409, loss: 0.0827 2023-03-04 10:26:32,338 - mmseg - INFO - Iter [159050/160000] lr: 1.172e-06, eta: 0:04:52, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0801, decode.acc_seg: 96.7915, loss: 0.0801 2023-03-04 10:26:44,665 - mmseg - INFO - Iter [159100/160000] lr: 1.172e-06, eta: 0:04:36, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0805, decode.acc_seg: 96.8360, loss: 0.0805 2023-03-04 10:26:56,900 - mmseg - INFO - Iter [159150/160000] lr: 1.172e-06, eta: 0:04:21, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0807, decode.acc_seg: 96.8171, loss: 0.0807 2023-03-04 10:27:09,033 - mmseg - INFO - Iter [159200/160000] lr: 1.172e-06, eta: 0:04:06, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0768, decode.acc_seg: 96.9818, loss: 0.0768 2023-03-04 10:27:23,549 - mmseg - INFO - Iter [159250/160000] lr: 1.172e-06, eta: 0:03:50, time: 0.290, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8558, loss: 0.0792 2023-03-04 10:27:35,722 - mmseg - INFO - Iter [159300/160000] lr: 1.172e-06, eta: 0:03:35, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0792, decode.acc_seg: 96.8644, loss: 0.0792 2023-03-04 10:27:47,872 - mmseg - INFO - Iter [159350/160000] lr: 1.172e-06, eta: 0:03:19, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.9133, loss: 0.0786 2023-03-04 10:28:00,106 - mmseg - INFO - Iter [159400/160000] lr: 1.172e-06, eta: 0:03:04, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0810, decode.acc_seg: 96.8274, loss: 0.0810 2023-03-04 10:28:14,668 - mmseg - INFO - Iter [159450/160000] lr: 1.172e-06, eta: 0:02:49, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0832, decode.acc_seg: 96.7569, loss: 0.0832 2023-03-04 10:28:26,834 - mmseg - INFO - Iter [159500/160000] lr: 1.172e-06, eta: 0:02:33, time: 0.243, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8789, loss: 0.0786 2023-03-04 10:28:39,127 - mmseg - INFO - Iter [159550/160000] lr: 1.172e-06, eta: 0:02:18, time: 0.246, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0773, decode.acc_seg: 96.9111, loss: 0.0773 2023-03-04 10:28:53,656 - mmseg - INFO - Iter [159600/160000] lr: 1.172e-06, eta: 0:02:02, time: 0.291, data_time: 0.054, memory: 67501, decode.loss_ce: 0.0820, decode.acc_seg: 96.8258, loss: 0.0820 2023-03-04 10:29:05,983 - mmseg - INFO - Iter [159650/160000] lr: 1.172e-06, eta: 0:01:47, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0779, decode.acc_seg: 96.9372, loss: 0.0779 2023-03-04 10:29:18,211 - mmseg - INFO - Iter [159700/160000] lr: 1.172e-06, eta: 0:01:32, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0791, decode.acc_seg: 96.8373, loss: 0.0791 2023-03-04 10:29:30,397 - mmseg - INFO - Iter [159750/160000] lr: 1.172e-06, eta: 0:01:16, time: 0.244, data_time: 0.009, memory: 67501, decode.loss_ce: 0.0786, decode.acc_seg: 96.8839, loss: 0.0786 2023-03-04 10:29:44,775 - mmseg - INFO - Iter [159800/160000] lr: 1.172e-06, eta: 0:01:01, time: 0.288, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0769, decode.acc_seg: 96.9500, loss: 0.0769 2023-03-04 10:29:57,003 - mmseg - INFO - Iter [159850/160000] lr: 1.172e-06, eta: 0:00:46, time: 0.245, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0804, decode.acc_seg: 96.8211, loss: 0.0804 2023-03-04 10:30:09,237 - mmseg - INFO - Iter [159900/160000] lr: 1.172e-06, eta: 0:00:30, time: 0.244, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0793, decode.acc_seg: 96.8559, loss: 0.0793 2023-03-04 10:30:21,587 - mmseg - INFO - Iter [159950/160000] lr: 1.172e-06, eta: 0:00:15, time: 0.247, data_time: 0.008, memory: 67501, decode.loss_ce: 0.0775, decode.acc_seg: 96.9187, loss: 0.0775 2023-03-04 10:30:36,055 - mmseg - INFO - Swap parameters (after train) after iter [160000] 2023-03-04 10:30:36,071 - mmseg - INFO - Saving checkpoint at 160000 iterations 2023-03-04 10:30:37,553 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:30:37,554 - mmseg - INFO - Iter [160000/160000] lr: 1.172e-06, eta: 0:00:00, time: 0.320, data_time: 0.055, memory: 67501, decode.loss_ce: 0.0776, decode.acc_seg: 96.8883, loss: 0.0776 2023-03-04 10:45:30,066 - mmseg - INFO - per class results: 2023-03-04 10:45:30,068 - mmseg - INFO - +---------------+-------------------------------------------------------------------+ | Class | IoU 0,10,20,30,40,50,60,70,80,90,99 | +---------------+-------------------------------------------------------------------+ | background | nan,nan,nan,nan,nan,nan,nan,nan,nan,nan,nan | | road | 98.57,98.58,98.59,98.59,98.59,98.58,98.58,98.58,98.58,98.58,98.57 | | sidewalk | 87.79,87.85,87.88,87.89,87.9,87.86,87.86,87.87,87.88,87.88,87.84 | | building | 93.32,93.31,93.32,93.33,93.32,93.33,93.32,93.33,93.33,93.33,93.33 | | wall | 54.26,54.26,54.45,54.64,54.67,54.8,54.71,54.97,55.02,54.94,54.85 | | fence | 63.24,63.17,63.22,63.2,63.12,63.18,63.18,63.14,63.16,63.16,63.18 | | pole | 71.0,71.0,71.01,71.02,71.01,71.01,71.02,71.01,71.02,71.02,71.0 | | traffic light | 75.53,75.53,75.51,75.54,75.5,75.52,75.51,75.51,75.51,75.51,75.5 | | traffic sign | 83.27,83.27,83.29,83.3,83.31,83.31,83.32,83.32,83.34,83.35,83.35 | | vegetation | 92.9,92.91,92.91,92.92,92.92,92.93,92.92,92.91,92.91,92.91,92.91 | | terrain | 65.52,65.64,65.79,65.85,65.97,66.02,65.96,65.89,65.97,65.97,66.05 | | sky | 95.25,95.25,95.26,95.25,95.26,95.26,95.26,95.26,95.26,95.26,95.26 | | person | 84.75,84.75,84.77,84.78,84.78,84.78,84.78,84.78,84.79,84.79,84.79 | | rider | 67.17,67.21,67.23,67.29,67.34,67.33,67.35,67.37,67.37,67.35,67.35 | | car | 95.96,95.98,96.01,96.02,96.01,96.02,96.02,96.03,96.04,96.05,96.05 | | truck | 85.33,85.88,86.37,86.57,86.56,86.72,86.58,86.78,87.01,87.22,87.03 | | bus | 92.15,92.15,92.23,92.24,92.23,92.26,92.28,92.29,92.33,92.36,92.29 | | train | 85.96,85.98,85.91,85.92,86.0,86.01,86.04,85.95,85.98,85.93,85.96 | | motorcycle | 69.71,69.69,69.71,69.65,69.65,69.68,69.69,69.63,69.63,69.64,69.63 | | bicycle | 79.87,79.87,79.88,79.89,79.89,79.9,79.92,79.91,79.92,79.93,79.93 | +---------------+-------------------------------------------------------------------+ 2023-03-04 10:45:30,068 - mmseg - INFO - Summary: 2023-03-04 10:45:30,068 - mmseg - INFO - +-------------------------------------------------------------------+ | mIoU 0,10,20,30,40,50,60,70,80,90,99 | +-------------------------------------------------------------------+ | 81.13,81.17,81.23,81.26,81.27,81.29,81.28,81.29,81.32,81.33,81.31 | +-------------------------------------------------------------------+ 2023-03-04 10:45:30,068 - mmseg - INFO - Exp name: deeplabv3plus_r50-d8_aspp_head_unet_fc_multi_step_ade_pretrained_freeze_embed_160k_cityscapes20_finetune.py 2023-03-04 10:45:30,068 - mmseg - INFO - Iter(val) [63] mIoU: [0.8113, 0.8117, 0.8123, 0.8126, 0.8127, 0.8129, 0.8128, 0.8129, 0.8132, 0.8133, 0.8131], copy_paste: 81.13,81.17,81.23,81.26,81.27,81.29,81.28,81.29,81.32,81.33,81.31