20221104_101802.log

2022-11-04 10:18:02,170 - mmseg - INFO - Multi-processing start method is `None`
2022-11-04 10:18:02,170 - mmseg - INFO - OpenCV num_threads is `184
2022-11-04 10:18:02,170 - mmseg - INFO - OMP num threads is 1
2022-11-04 10:18:02,211 - mmseg - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.9.5 (default, Jun  4 2021, 12:28:51) [GCC 7.5.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: A100-SXM4-40GB
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.0, V11.0.221
GCC: gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5)
PyTorch: 1.10.1+cu113
PyTorch compiling details: PyTorch built with:
  - GCC 7.3
  - C++ Version: 201402
  - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 11.3
  - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
  - CuDNN 8.2
  - Magma 2.5.2
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.1, 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, 

TorchVision: 0.11.2+cu113
OpenCV: 4.5.4
MMCV: 1.6.2
MMCV Compiler: GCC 9.3
MMCV CUDA Compiler: 11.3
MMSegmentation: 0.28.0+
------------------------------------------------------------

2022-11-04 10:18:02,212 - mmseg - INFO - Distributed training: True
2022-11-04 10:18:02,503 - mmseg - INFO - Config:
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
    type='EncoderDecoder',
    backbone=dict(
        type='MetaMobile',
        depths=[3, 3, 9, 3],
        stem_dim=24,
        embed_dims=[32, 48, 120, 200],
        exp_ratios=[2.0, 2.5, 3.0, 3.5],
        norm_layers=['bn_2d', 'bn_2d', 'ln_2d', 'ln_2d'],
        act_layers=['silu', 'silu', 'gelu', 'gelu'],
        dw_kss=[3, 3, 5, 5],
        group_size=1,
        se_ratios=[0.0, 0.0, 0.0, 0.0],
        dim_heads=[16, 16, 20, 20],
        window_sizes=[7, 7, 7, 7],
        attn_ss=[False, False, True, True],
        attn_s_skips=[False, False, False, False],
        qkv_bias=True,
        attn_drop=0.0,
        drop=0.0,
        drop_path=0.05,
        v_group=False,
        attn_pre=True,
        conv_l=True,
        skip_l=True,
        pre_dim=0,
        sync_bn=True,
        out_indices=(1, 2, 3, 4),
        pretrained='../../ckpt_models/MetaMobile_2M/net_E.pth',
        frozen_stages=-1,
        norm_eval=False),
    decode_head=dict(
        type='PSPHead',
        in_channels=200,
        in_index=3,
        channels=256,
        pool_scales=(1, 2, 3, 6),
        dropout_ratio=0.1,
        num_classes=150,
        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=dict(
        type='FCNHead',
        in_channels=120,
        in_index=2,
        channels=256,
        num_convs=1,
        concat_input=False,
        dropout_ratio=0.1,
        num_classes=150,
        norm_cfg=dict(type='SyncBN', requires_grad=True),
        align_corners=False,
        loss_decode=dict(
            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
    train_cfg=dict(),
    test_cfg=dict(mode='whole'))
dataset_type = 'ADE20KDataset'
data_root = 'data/ade/ADEChallengeData2016'
img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
crop_size = (512, 512)
train_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(type='LoadAnnotations', reduce_zero_label=True),
    dict(type='Resize', img_scale=(2048, 512), ratio_range=(0.5, 2.0)),
    dict(type='RandomCrop', crop_size=(512, 512), 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, 512), pad_val=0, seg_pad_val=255),
    dict(type='DefaultFormatBundle'),
    dict(type='Collect', keys=['img', 'gt_semantic_seg'])
]
test_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(
        type='MultiScaleFlipAug',
        img_scale=(2048, 512),
        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=4,
    workers_per_gpu=4,
    train=dict(
        type='ADE20KDataset',
        data_root='data/ade/ADEChallengeData2016',
        img_dir='images/training',
        ann_dir='annotations/training',
        pipeline=[
            dict(type='LoadImageFromFile'),
            dict(type='LoadAnnotations', reduce_zero_label=True),
            dict(type='Resize', img_scale=(2048, 512), ratio_range=(0.5, 2.0)),
            dict(type='RandomCrop', crop_size=(512, 512), 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, 512), pad_val=0, seg_pad_val=255),
            dict(type='DefaultFormatBundle'),
            dict(type='Collect', keys=['img', 'gt_semantic_seg'])
        ]),
    val=dict(
        type='ADE20KDataset',
        data_root='data/ade/ADEChallengeData2016',
        img_dir='images/validation',
        ann_dir='annotations/validation',
        pipeline=[
            dict(type='LoadImageFromFile'),
            dict(
                type='MultiScaleFlipAug',
                img_scale=(2048, 512),
                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='ADE20KDataset',
        data_root='data/ade/ADEChallengeData2016',
        img_dir='images/validation',
        ann_dir='annotations/validation',
        pipeline=[
            dict(type='LoadImageFromFile'),
            dict(
                type='MultiScaleFlipAug',
                img_scale=(2048, 512),
                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_config = dict()
runner = dict(type='IterBasedRunner', max_iters=80000)
checkpoint_config = dict(by_epoch=False, interval=8000)
evaluation = dict(interval=8000, metric='mIoU', pre_eval=True)
bs_ratio = 1
optimizer = dict(
    type='AdamW',
    lr=0.00012,
    betas=(0.9, 0.999),
    weight_decay=0.01,
    paramwise_cfg=dict(
        custom_keys=dict(
            absolute_pos_embed=dict(decay_mult=0.0),
            relative_position_bias_table=dict(decay_mult=0.0),
            norm=dict(decay_mult=0.0))))
lr_config = dict(policy='poly', power=0.9, min_lr=0.0, by_epoch=False)
work_dir = './work_dirs/pspnet_metamobile2M_512x512_80k_ade20k_256'
gpu_ids = range(0, 8)
auto_resume = False

2022-11-04 10:18:11,513 - mmseg - INFO - Set random seed to 539768611, deterministic: False
2022-11-04 10:18:11,732 - mmseg - INFO - initialize PSPHead with init_cfg {'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}}
2022-11-04 10:18:11,763 - mmseg - INFO - initialize FCNHead with init_cfg {'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}}
Name of parameter - Initialization information

backbone.stage0.0.convs.0.0.weight - torch.Size([24, 3, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.0.convs.0.0.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.0.convs.0.1.weight - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.0.convs.0.1.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.conv_local.conv.weight - torch.Size([24, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.conv_local.norm.weight - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.conv_local.norm.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.se.conv_reduce.weight - torch.Size([24, 24, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.se.conv_reduce.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.se.conv_expand.weight - torch.Size([24, 24, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.se.conv_expand.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage0.1.proj.conv.weight - torch.Size([24, 24, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.norm.weight - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.norm.bias - torch.Size([24]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.v.conv.weight - torch.Size([96, 24, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.v.conv.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.conv_local.conv.weight - torch.Size([96, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.conv_local.norm.weight - torch.Size([96]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.conv_local.norm.bias - torch.Size([96]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.0.proj.conv.weight - torch.Size([32, 96, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.norm.weight - torch.Size([32]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.norm.bias - torch.Size([32]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.v.conv.weight - torch.Size([64, 32, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.v.conv.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.conv_local.conv.weight - torch.Size([64, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.conv_local.norm.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.conv_local.norm.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.1.proj.conv.weight - torch.Size([32, 64, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.norm.weight - torch.Size([32]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.norm.bias - torch.Size([32]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.v.conv.weight - torch.Size([64, 32, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.v.conv.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.conv_local.conv.weight - torch.Size([64, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.conv_local.norm.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.conv_local.norm.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage1.2.proj.conv.weight - torch.Size([32, 64, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.norm.weight - torch.Size([32]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.norm.bias - torch.Size([32]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.v.conv.weight - torch.Size([160, 32, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.v.conv.bias - torch.Size([160]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.conv_local.conv.weight - torch.Size([160, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.conv_local.norm.weight - torch.Size([160]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.conv_local.norm.bias - torch.Size([160]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.0.proj.conv.weight - torch.Size([48, 160, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.norm.weight - torch.Size([48]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.norm.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.v.conv.weight - torch.Size([120, 48, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.v.conv.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.conv_local.conv.weight - torch.Size([120, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.conv_local.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.conv_local.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.1.proj.conv.weight - torch.Size([48, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.norm.weight - torch.Size([48]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.norm.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.v.conv.weight - torch.Size([120, 48, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.v.conv.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.conv_local.conv.weight - torch.Size([120, 1, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.conv_local.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.conv_local.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage2.2.proj.conv.weight - torch.Size([48, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.norm.norm.weight - torch.Size([48]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.norm.norm.bias - torch.Size([48]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.v.conv.weight - torch.Size([288, 48, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.v.conv.bias - torch.Size([288]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.conv_local.conv.weight - torch.Size([288, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.conv_local.norm.weight - torch.Size([288]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.conv_local.norm.bias - torch.Size([288]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.0.proj.conv.weight - torch.Size([120, 288, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.1.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.2.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.3.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.4.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.5.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.6.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.7.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.qk.conv.weight - torch.Size([240, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.qk.conv.bias - torch.Size([240]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.v.conv.weight - torch.Size([360, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.v.conv.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.conv_local.conv.weight - torch.Size([360, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.conv_local.norm.weight - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.conv_local.norm.bias - torch.Size([360]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage3.8.proj.conv.weight - torch.Size([120, 360, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.norm.norm.weight - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.norm.norm.bias - torch.Size([120]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.v.conv.weight - torch.Size([840, 120, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.v.conv.bias - torch.Size([840]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.conv_local.conv.weight - torch.Size([840, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.conv_local.norm.weight - torch.Size([840]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.conv_local.norm.bias - torch.Size([840]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.0.proj.conv.weight - torch.Size([200, 840, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.norm.norm.weight - torch.Size([200]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.norm.norm.bias - torch.Size([200]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.qk.conv.weight - torch.Size([400, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.qk.conv.bias - torch.Size([400]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.v.conv.weight - torch.Size([700, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.v.conv.bias - torch.Size([700]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.conv_local.conv.weight - torch.Size([700, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.conv_local.norm.weight - torch.Size([700]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.conv_local.norm.bias - torch.Size([700]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.1.proj.conv.weight - torch.Size([200, 700, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.norm.norm.weight - torch.Size([200]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.norm.norm.bias - torch.Size([200]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.qk.conv.weight - torch.Size([400, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.qk.conv.bias - torch.Size([400]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.v.conv.weight - torch.Size([700, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.v.conv.bias - torch.Size([700]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.conv_local.conv.weight - torch.Size([700, 1, 5, 5]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.conv_local.norm.weight - torch.Size([700]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.conv_local.norm.bias - torch.Size([700]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

backbone.stage4.2.proj.conv.weight - torch.Size([200, 700, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.conv_seg.weight - torch.Size([150, 256, 1, 1]): 
NormalInit: mean=0, std=0.01, bias=0 

decode_head.conv_seg.bias - torch.Size([150]): 
NormalInit: mean=0, std=0.01, bias=0 

decode_head.psp_modules.0.1.conv.weight - torch.Size([256, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.0.1.bn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.0.1.bn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.1.1.conv.weight - torch.Size([256, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.1.1.bn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.1.1.bn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.2.1.conv.weight - torch.Size([256, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.2.1.bn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.2.1.bn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.3.1.conv.weight - torch.Size([256, 200, 1, 1]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.3.1.bn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.psp_modules.3.1.bn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.bottleneck.conv.weight - torch.Size([256, 1224, 3, 3]): 
Initialized by user-defined `init_weights` in ConvModule  

decode_head.bottleneck.bn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

decode_head.bottleneck.bn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

auxiliary_head.conv_seg.weight - torch.Size([150, 256, 1, 1]): 
NormalInit: mean=0, std=0.01, bias=0 

auxiliary_head.conv_seg.bias - torch.Size([150]): 
NormalInit: mean=0, std=0.01, bias=0 

auxiliary_head.convs.0.conv.weight - torch.Size([256, 120, 3, 3]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

auxiliary_head.convs.0.bn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  

auxiliary_head.convs.0.bn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of EncoderDecoder  
2022-11-04 10:18:11,767 - mmseg - INFO - EncoderDecoder(
  (backbone): MetaMobile(
    (stage0): ModuleList(
      (0): MSPatchEmb(
        (convs): ModuleList(
          (0): Sequential(
            (0): Conv2d(3, 24, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
            (1): SyncBatchNorm(24, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
            (2): Identity()
          )
        )
      )
      (1): MetaMobileModule(
        (norm): Identity()
        (v): Identity()
        (conv_local): ConvNormAct(
          (conv): Conv2d(24, 24, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=24, bias=False)
          (norm): SyncBatchNorm(24, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): SqueezeExcite(
          (conv_reduce): Conv2d(24, 24, kernel_size=(1, 1), stride=(1, 1))
          (act1): SiLU(inplace=True)
          (conv_expand): Conv2d(24, 24, kernel_size=(1, 1), stride=(1, 1))
          (gate): Sigmoid()
        )
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(24, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): Identity()
      )
    )
    (stage1): ModuleList(
      (0): MetaMobileModule(
        (norm): SyncBatchNorm(24, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
        (v): ConvNormAct(
          (conv): Conv2d(24, 96, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=96, bias=False)
          (norm): SyncBatchNorm(96, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(96, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): Identity()
      )
      (1): MetaMobileModule(
        (norm): SyncBatchNorm(32, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
        (v): ConvNormAct(
          (conv): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64, bias=False)
          (norm): SyncBatchNorm(64, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.003)
      )
      (2): MetaMobileModule(
        (norm): SyncBatchNorm(32, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
        (v): ConvNormAct(
          (conv): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=64, bias=False)
          (norm): SyncBatchNorm(64, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.006)
      )
    )
    (stage2): ModuleList(
      (0): MetaMobileModule(
        (norm): SyncBatchNorm(32, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
        (v): ConvNormAct(
          (conv): Conv2d(32, 160, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(160, 160, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=160, bias=False)
          (norm): SyncBatchNorm(160, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(160, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.009)
      )
      (1): MetaMobileModule(
        (norm): SyncBatchNorm(48, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
        (v): ConvNormAct(
          (conv): Conv2d(48, 120, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(120, 120, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=120, bias=False)
          (norm): SyncBatchNorm(120, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(120, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.012)
      )
      (2): MetaMobileModule(
        (norm): SyncBatchNorm(48, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
        (v): ConvNormAct(
          (conv): Conv2d(48, 120, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(120, 120, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=120, bias=False)
          (norm): SyncBatchNorm(120, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(120, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.015)
      )
    )
    (stage3): ModuleList(
      (0): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((48,), eps=1e-06, elementwise_affine=True)
        )
        (v): ConvNormAct(
          (conv): Conv2d(48, 288, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(288, 288, kernel_size=(5, 5), stride=(2, 2), padding=(2, 2), groups=288, bias=False)
          (norm): SyncBatchNorm(288, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(288, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.018)
      )
      (1): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.021)
      )
      (2): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.024)
      )
      (3): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.026)
      )
      (4): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.029)
      )
      (5): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.032)
      )
      (6): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.035)
      )
      (7): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.038)
      )
      (8): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(120, 240, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 360, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(360, 360, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=360, bias=False)
          (norm): SyncBatchNorm(360, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(360, 120, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.041)
      )
    )
    (stage4): ModuleList(
      (0): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((120,), eps=1e-06, elementwise_affine=True)
        )
        (v): ConvNormAct(
          (conv): Conv2d(120, 840, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (conv_local): ConvNormAct(
          (conv): Conv2d(840, 840, kernel_size=(5, 5), stride=(2, 2), padding=(2, 2), groups=840, bias=False)
          (norm): SyncBatchNorm(840, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(840, 200, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.044)
      )
      (1): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((200,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(200, 400, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(200, 700, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(700, 700, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=700, bias=False)
          (norm): SyncBatchNorm(700, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(700, 200, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.047)
      )
      (2): MetaMobileModule(
        (norm): LayerNorm2d(
          (norm): LayerNorm((200,), eps=1e-06, elementwise_affine=True)
        )
        (qk): ConvNormAct(
          (conv): Conv2d(200, 400, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (v): ConvNormAct(
          (conv): Conv2d(200, 700, kernel_size=(1, 1), stride=(1, 1))
          (norm): Identity()
          (act): GELU()
          (drop_path): Identity()
        )
        (attn_drop): Dropout(p=0.0, inplace=False)
        (conv_local): ConvNormAct(
          (conv): Conv2d(700, 700, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=700, bias=False)
          (norm): SyncBatchNorm(700, eps=1e-06, momentum=0.1, affine=True, track_running_stats=True)
          (act): SiLU(inplace=True)
          (drop_path): Identity()
        )
        (se): Identity()
        (proj_drop): Dropout(p=0.0, inplace=False)
        (proj): ConvNormAct(
          (conv): Conv2d(700, 200, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (norm): Identity()
          (act): Identity()
          (drop_path): Identity()
        )
        (ls): Identity()
        (drop_path): DropPath(drop_prob=0.050)
      )
    )
  )
  (decode_head): PSPHead(
    input_transform=None, ignore_index=255, align_corners=False
    (loss_decode): CrossEntropyLoss(avg_non_ignore=False)
    (conv_seg): Conv2d(256, 150, kernel_size=(1, 1), stride=(1, 1))
    (dropout): Dropout2d(p=0.1, inplace=False)
    (psp_modules): PPM(
      (0): Sequential(
        (0): AdaptiveAvgPool2d(output_size=1)
        (1): ConvModule(
          (conv): Conv2d(200, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (activate): ReLU(inplace=True)
        )
      )
      (1): Sequential(
        (0): AdaptiveAvgPool2d(output_size=2)
        (1): ConvModule(
          (conv): Conv2d(200, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (activate): ReLU(inplace=True)
        )
      )
      (2): Sequential(
        (0): AdaptiveAvgPool2d(output_size=3)
        (1): ConvModule(
          (conv): Conv2d(200, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (activate): ReLU(inplace=True)
        )
      )
      (3): Sequential(
        (0): AdaptiveAvgPool2d(output_size=6)
        (1): ConvModule(
          (conv): Conv2d(200, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
          (bn): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
          (activate): ReLU(inplace=True)
        )
      )
    )
    (bottleneck): ConvModule(
      (conv): Conv2d(1224, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
      (bn): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (activate): ReLU(inplace=True)
    )
  )
  init_cfg={'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}}
  (auxiliary_head): FCNHead(
    input_transform=None, ignore_index=255, align_corners=False
    (loss_decode): CrossEntropyLoss(avg_non_ignore=False)
    (conv_seg): Conv2d(256, 150, kernel_size=(1, 1), stride=(1, 1))
    (dropout): Dropout2d(p=0.1, inplace=False)
    (convs): Sequential(
      (0): ConvModule(
        (conv): Conv2d(120, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn): SyncBatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (activate): ReLU(inplace=True)
      )
    )
  )
  init_cfg={'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}}
)
2022-11-04 10:18:12,174 - mmseg - INFO - Loaded 20210 images
2022-11-04 10:18:12,662 - mmseg - INFO - Loaded 2000 images
2022-11-04 10:18:12,662 - mmseg - INFO - Start running, host: root@ts-416329afce9447a898dd59bdf425a7a4-launcher, work_dir: /youtu_fuxi_team1_ceph/vtzhang/codes/pts_cls/down-stream-tasks/mmsegmentation/work_dirs/pspnet_metamobile2M_512x512_80k_ade20k_256
2022-11-04 10:18:12,663 - mmseg - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH   ) PolyLrUpdaterHook                  
(NORMAL      ) CheckpointHook                     
(LOW         ) DistEvalHook                       
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
before_train_epoch:
(VERY_HIGH   ) PolyLrUpdaterHook                  
(LOW         ) IterTimerHook                      
(LOW         ) DistEvalHook                       
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
before_train_iter:
(VERY_HIGH   ) PolyLrUpdaterHook                  
(LOW         ) IterTimerHook                      
(LOW         ) DistEvalHook                       
 -------------------- 
after_train_iter:
(ABOVE_NORMAL) OptimizerHook                      
(NORMAL      ) CheckpointHook                     
(LOW         ) IterTimerHook                      
(LOW         ) DistEvalHook                       
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
after_train_epoch:
(NORMAL      ) CheckpointHook                     
(LOW         ) DistEvalHook                       
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
before_val_epoch:
(LOW         ) IterTimerHook                      
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
before_val_iter:
(LOW         ) IterTimerHook                      
 -------------------- 
after_val_iter:
(LOW         ) IterTimerHook                      
 -------------------- 
after_val_epoch:
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
after_run:
(VERY_LOW    ) TextLoggerHook                     
 -------------------- 
2022-11-04 10:18:12,663 - mmseg - INFO - workflow: [('train', 1)], max: 80000 iters
2022-11-04 10:18:12,663 - mmseg - INFO - Checkpoints will be saved to /youtu_fuxi_team1_ceph/vtzhang/codes/pts_cls/down-stream-tasks/mmsegmentation/work_dirs/pspnet_metamobile2M_512x512_80k_ade20k_256 by HardDiskBackend.
2022-11-04 10:18:47,741 - mmseg - INFO - Iter [50/80000]	lr: 1.199e-04, eta: 10:37:40, time: 0.479, data_time: 0.012, memory: 5208, decode.loss_ce: 3.5313, decode.acc_seg: 32.3596, aux.loss_ce: 1.4475, aux.acc_seg: 26.8651, loss: 4.9788
2022-11-04 10:19:05,087 - mmseg - INFO - Iter [100/80000]	lr: 1.199e-04, eta: 9:09:37, time: 0.347, data_time: 0.008, memory: 5208, decode.loss_ce: 2.7949, decode.acc_seg: 44.4678, aux.loss_ce: 1.1589, aux.acc_seg: 40.1274, loss: 3.9539
2022-11-04 10:19:23,097 - mmseg - INFO - Iter [150/80000]	lr: 1.198e-04, eta: 8:45:58, time: 0.360, data_time: 0.008, memory: 5208, decode.loss_ce: 2.3798, decode.acc_seg: 45.4125, aux.loss_ce: 0.9829, aux.acc_seg: 42.0578, loss: 3.3627
2022-11-04 10:19:41,575 - mmseg - INFO - Iter [200/80000]	lr: 1.197e-04, eta: 8:37:06, time: 0.370, data_time: 0.007, memory: 5208, decode.loss_ce: 2.1072, decode.acc_seg: 48.5178, aux.loss_ce: 0.8867, aux.acc_seg: 44.3015, loss: 2.9939
2022-11-04 10:19:59,759 - mmseg - INFO - Iter [250/80000]	lr: 1.197e-04, eta: 8:30:06, time: 0.364, data_time: 0.009, memory: 5208, decode.loss_ce: 1.9269, decode.acc_seg: 49.9363, aux.loss_ce: 0.8152, aux.acc_seg: 46.2863, loss: 2.7421
2022-11-04 10:20:16,769 - mmseg - INFO - Iter [300/80000]	lr: 1.196e-04, eta: 8:20:07, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 1.8321, decode.acc_seg: 51.7282, aux.loss_ce: 0.7806, aux.acc_seg: 48.4338, loss: 2.6127
2022-11-04 10:20:33,733 - mmseg - INFO - Iter [350/80000]	lr: 1.195e-04, eta: 8:12:45, time: 0.339, data_time: 0.008, memory: 5208, decode.loss_ce: 1.7509, decode.acc_seg: 52.8459, aux.loss_ce: 0.7447, aux.acc_seg: 50.2244, loss: 2.4956
2022-11-04 10:20:50,653 - mmseg - INFO - Iter [400/80000]	lr: 1.195e-04, eta: 8:07:00, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 1.6753, decode.acc_seg: 53.7994, aux.loss_ce: 0.7147, aux.acc_seg: 51.3515, loss: 2.3900
2022-11-04 10:21:07,292 - mmseg - INFO - Iter [450/80000]	lr: 1.194e-04, eta: 8:01:38, time: 0.333, data_time: 0.008, memory: 5208, decode.loss_ce: 1.6367, decode.acc_seg: 54.5243, aux.loss_ce: 0.7020, aux.acc_seg: 52.2354, loss: 2.3387
2022-11-04 10:21:24,237 - mmseg - INFO - Iter [500/80000]	lr: 1.193e-04, eta: 7:58:06, time: 0.339, data_time: 0.008, memory: 5208, decode.loss_ce: 1.5726, decode.acc_seg: 55.7173, aux.loss_ce: 0.6727, aux.acc_seg: 53.6888, loss: 2.2453
2022-11-04 10:21:40,959 - mmseg - INFO - Iter [550/80000]	lr: 1.193e-04, eta: 7:54:37, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 1.6005, decode.acc_seg: 55.5452, aux.loss_ce: 0.6846, aux.acc_seg: 53.6373, loss: 2.2851
2022-11-04 10:21:57,793 - mmseg - INFO - Iter [600/80000]	lr: 1.192e-04, eta: 7:51:55, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 1.5110, decode.acc_seg: 57.1807, aux.loss_ce: 0.6446, aux.acc_seg: 55.1930, loss: 2.1556
2022-11-04 10:22:17,838 - mmseg - INFO - Iter [650/80000]	lr: 1.191e-04, eta: 7:56:08, time: 0.401, data_time: 0.067, memory: 5208, decode.loss_ce: 1.4777, decode.acc_seg: 57.2821, aux.loss_ce: 0.6312, aux.acc_seg: 55.6958, loss: 2.1089
2022-11-04 10:22:34,783 - mmseg - INFO - Iter [700/80000]	lr: 1.191e-04, eta: 7:53:50, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 1.4286, decode.acc_seg: 58.2392, aux.loss_ce: 0.6152, aux.acc_seg: 56.2223, loss: 2.0439
2022-11-04 10:22:51,516 - mmseg - INFO - Iter [750/80000]	lr: 1.190e-04, eta: 7:51:26, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 1.4294, decode.acc_seg: 58.0825, aux.loss_ce: 0.6133, aux.acc_seg: 56.5797, loss: 2.0427
2022-11-04 10:23:08,344 - mmseg - INFO - Iter [800/80000]	lr: 1.189e-04, eta: 7:49:27, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 1.4248, decode.acc_seg: 58.4896, aux.loss_ce: 0.6134, aux.acc_seg: 56.1763, loss: 2.0381
2022-11-04 10:23:25,171 - mmseg - INFO - Iter [850/80000]	lr: 1.189e-04, eta: 7:47:41, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 1.3423, decode.acc_seg: 59.9798, aux.loss_ce: 0.5862, aux.acc_seg: 57.5526, loss: 1.9285
2022-11-04 10:23:42,112 - mmseg - INFO - Iter [900/80000]	lr: 1.188e-04, eta: 7:46:14, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 1.3291, decode.acc_seg: 60.4125, aux.loss_ce: 0.5725, aux.acc_seg: 58.6722, loss: 1.9016
2022-11-04 10:23:59,086 - mmseg - INFO - Iter [950/80000]	lr: 1.187e-04, eta: 7:44:57, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 1.3227, decode.acc_seg: 60.5926, aux.loss_ce: 0.5813, aux.acc_seg: 58.4020, loss: 1.9040
2022-11-04 10:24:15,921 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:24:15,922 - mmseg - INFO - Iter [1000/80000]	lr: 1.187e-04, eta: 7:43:35, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 1.3105, decode.acc_seg: 60.5568, aux.loss_ce: 0.5733, aux.acc_seg: 58.1531, loss: 1.8838
2022-11-04 10:24:32,681 - mmseg - INFO - Iter [1050/80000]	lr: 1.186e-04, eta: 7:42:14, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 1.3041, decode.acc_seg: 60.2658, aux.loss_ce: 0.5673, aux.acc_seg: 58.3601, loss: 1.8713
2022-11-04 10:24:49,692 - mmseg - INFO - Iter [1100/80000]	lr: 1.185e-04, eta: 7:41:17, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 1.3129, decode.acc_seg: 60.5223, aux.loss_ce: 0.5768, aux.acc_seg: 57.9818, loss: 1.8898
2022-11-04 10:25:06,470 - mmseg - INFO - Iter [1150/80000]	lr: 1.184e-04, eta: 7:40:07, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 1.2680, decode.acc_seg: 61.4752, aux.loss_ce: 0.5546, aux.acc_seg: 59.3663, loss: 1.8225
2022-11-04 10:25:23,267 - mmseg - INFO - Iter [1200/80000]	lr: 1.184e-04, eta: 7:39:03, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 1.2492, decode.acc_seg: 61.9813, aux.loss_ce: 0.5454, aux.acc_seg: 60.0148, loss: 1.7946
2022-11-04 10:25:40,211 - mmseg - INFO - Iter [1250/80000]	lr: 1.183e-04, eta: 7:38:12, time: 0.339, data_time: 0.008, memory: 5208, decode.loss_ce: 1.2645, decode.acc_seg: 60.9707, aux.loss_ce: 0.5553, aux.acc_seg: 58.5694, loss: 1.8198
2022-11-04 10:26:00,118 - mmseg - INFO - Iter [1300/80000]	lr: 1.182e-04, eta: 7:40:23, time: 0.398, data_time: 0.066, memory: 5208, decode.loss_ce: 1.2238, decode.acc_seg: 62.3946, aux.loss_ce: 0.5446, aux.acc_seg: 59.6982, loss: 1.7684
2022-11-04 10:26:17,137 - mmseg - INFO - Iter [1350/80000]	lr: 1.182e-04, eta: 7:39:34, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 1.1851, decode.acc_seg: 63.6117, aux.loss_ce: 0.5327, aux.acc_seg: 60.5664, loss: 1.7178
2022-11-04 10:26:34,170 - mmseg - INFO - Iter [1400/80000]	lr: 1.181e-04, eta: 7:38:49, time: 0.341, data_time: 0.008, memory: 5208, decode.loss_ce: 1.1901, decode.acc_seg: 63.2389, aux.loss_ce: 0.5284, aux.acc_seg: 61.0763, loss: 1.7185
2022-11-04 10:26:51,287 - mmseg - INFO - Iter [1450/80000]	lr: 1.180e-04, eta: 7:38:10, time: 0.342, data_time: 0.011, memory: 5208, decode.loss_ce: 1.2054, decode.acc_seg: 62.1870, aux.loss_ce: 0.5376, aux.acc_seg: 59.8579, loss: 1.7430
2022-11-04 10:27:08,240 - mmseg - INFO - Iter [1500/80000]	lr: 1.180e-04, eta: 7:37:24, time: 0.339, data_time: 0.008, memory: 5208, decode.loss_ce: 1.1624, decode.acc_seg: 63.5226, aux.loss_ce: 0.5182, aux.acc_seg: 60.9129, loss: 1.6806
2022-11-04 10:27:24,945 - mmseg - INFO - Iter [1550/80000]	lr: 1.179e-04, eta: 7:36:27, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 1.1870, decode.acc_seg: 62.5210, aux.loss_ce: 0.5329, aux.acc_seg: 59.7465, loss: 1.7199
2022-11-04 10:27:41,850 - mmseg - INFO - Iter [1600/80000]	lr: 1.178e-04, eta: 7:35:43, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 1.1124, decode.acc_seg: 64.5678, aux.loss_ce: 0.5003, aux.acc_seg: 61.4755, loss: 1.6127
2022-11-04 10:27:58,714 - mmseg - INFO - Iter [1650/80000]	lr: 1.178e-04, eta: 7:34:58, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 1.1382, decode.acc_seg: 64.6573, aux.loss_ce: 0.5121, aux.acc_seg: 61.8101, loss: 1.6504
2022-11-04 10:28:15,531 - mmseg - INFO - Iter [1700/80000]	lr: 1.177e-04, eta: 7:34:13, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 1.1432, decode.acc_seg: 63.3582, aux.loss_ce: 0.5089, aux.acc_seg: 60.6974, loss: 1.6521
2022-11-04 10:28:32,316 - mmseg - INFO - Iter [1750/80000]	lr: 1.176e-04, eta: 7:33:28, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 1.1576, decode.acc_seg: 62.5037, aux.loss_ce: 0.5205, aux.acc_seg: 59.8622, loss: 1.6781
2022-11-04 10:28:49,112 - mmseg - INFO - Iter [1800/80000]	lr: 1.176e-04, eta: 7:32:45, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 1.1543, decode.acc_seg: 63.3025, aux.loss_ce: 0.5181, aux.acc_seg: 60.8669, loss: 1.6724
2022-11-04 10:29:06,011 - mmseg - INFO - Iter [1850/80000]	lr: 1.175e-04, eta: 7:32:07, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 1.1267, decode.acc_seg: 63.7123, aux.loss_ce: 0.5060, aux.acc_seg: 61.2519, loss: 1.6327
2022-11-04 10:29:25,855 - mmseg - INFO - Iter [1900/80000]	lr: 1.174e-04, eta: 7:33:32, time: 0.397, data_time: 0.061, memory: 5208, decode.loss_ce: 1.1130, decode.acc_seg: 64.5429, aux.loss_ce: 0.5078, aux.acc_seg: 61.6057, loss: 1.6208
2022-11-04 10:29:42,763 - mmseg - INFO - Iter [1950/80000]	lr: 1.174e-04, eta: 7:32:54, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0553, decode.acc_seg: 65.6275, aux.loss_ce: 0.4812, aux.acc_seg: 62.6279, loss: 1.5365
2022-11-04 10:29:59,683 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:29:59,683 - mmseg - INFO - Iter [2000/80000]	lr: 1.173e-04, eta: 7:32:18, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0720, decode.acc_seg: 64.1436, aux.loss_ce: 0.4908, aux.acc_seg: 61.1947, loss: 1.5627
2022-11-04 10:30:16,570 - mmseg - INFO - Iter [2050/80000]	lr: 1.172e-04, eta: 7:31:41, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0953, decode.acc_seg: 64.3938, aux.loss_ce: 0.4969, aux.acc_seg: 61.8892, loss: 1.5922
2022-11-04 10:30:33,501 - mmseg - INFO - Iter [2100/80000]	lr: 1.172e-04, eta: 7:31:07, time: 0.339, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0463, decode.acc_seg: 65.5806, aux.loss_ce: 0.4774, aux.acc_seg: 62.7374, loss: 1.5238
2022-11-04 10:30:50,176 - mmseg - INFO - Iter [2150/80000]	lr: 1.171e-04, eta: 7:30:24, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0794, decode.acc_seg: 65.3454, aux.loss_ce: 0.4891, aux.acc_seg: 62.4342, loss: 1.5685
2022-11-04 10:31:07,049 - mmseg - INFO - Iter [2200/80000]	lr: 1.170e-04, eta: 7:29:50, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0693, decode.acc_seg: 64.9720, aux.loss_ce: 0.4883, aux.acc_seg: 62.0742, loss: 1.5577
2022-11-04 10:31:23,847 - mmseg - INFO - Iter [2250/80000]	lr: 1.170e-04, eta: 7:29:13, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0695, decode.acc_seg: 65.1590, aux.loss_ce: 0.4869, aux.acc_seg: 62.5334, loss: 1.5564
2022-11-04 10:31:40,676 - mmseg - INFO - Iter [2300/80000]	lr: 1.169e-04, eta: 7:28:39, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0269, decode.acc_seg: 65.4272, aux.loss_ce: 0.4708, aux.acc_seg: 62.8931, loss: 1.4976
2022-11-04 10:31:57,563 - mmseg - INFO - Iter [2350/80000]	lr: 1.168e-04, eta: 7:28:07, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 1.0706, decode.acc_seg: 64.9533, aux.loss_ce: 0.4893, aux.acc_seg: 62.1368, loss: 1.5598
2022-11-04 10:32:14,374 - mmseg - INFO - Iter [2400/80000]	lr: 1.168e-04, eta: 7:27:34, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 1.0302, decode.acc_seg: 65.3204, aux.loss_ce: 0.4743, aux.acc_seg: 62.5088, loss: 1.5045
2022-11-04 10:32:31,196 - mmseg - INFO - Iter [2450/80000]	lr: 1.167e-04, eta: 7:27:01, time: 0.336, data_time: 0.011, memory: 5208, decode.loss_ce: 1.0631, decode.acc_seg: 65.2352, aux.loss_ce: 0.4856, aux.acc_seg: 62.4486, loss: 1.5487
2022-11-04 10:32:47,947 - mmseg - INFO - Iter [2500/80000]	lr: 1.166e-04, eta: 7:26:27, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0112, decode.acc_seg: 66.0013, aux.loss_ce: 0.4640, aux.acc_seg: 63.5610, loss: 1.4752
2022-11-04 10:33:07,883 - mmseg - INFO - Iter [2550/80000]	lr: 1.166e-04, eta: 7:27:30, time: 0.399, data_time: 0.066, memory: 5208, decode.loss_ce: 1.0105, decode.acc_seg: 67.1461, aux.loss_ce: 0.4728, aux.acc_seg: 63.5068, loss: 1.4833
2022-11-04 10:33:24,524 - mmseg - INFO - Iter [2600/80000]	lr: 1.165e-04, eta: 7:26:52, time: 0.333, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0026, decode.acc_seg: 66.2723, aux.loss_ce: 0.4643, aux.acc_seg: 63.1078, loss: 1.4669
2022-11-04 10:33:41,460 - mmseg - INFO - Iter [2650/80000]	lr: 1.164e-04, eta: 7:26:24, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9972, decode.acc_seg: 66.2561, aux.loss_ce: 0.4642, aux.acc_seg: 62.8060, loss: 1.4613
2022-11-04 10:33:58,158 - mmseg - INFO - Iter [2700/80000]	lr: 1.164e-04, eta: 7:25:49, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 1.0012, decode.acc_seg: 66.3946, aux.loss_ce: 0.4702, aux.acc_seg: 62.9199, loss: 1.4715
2022-11-04 10:34:14,843 - mmseg - INFO - Iter [2750/80000]	lr: 1.163e-04, eta: 7:25:14, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9845, decode.acc_seg: 66.7708, aux.loss_ce: 0.4551, aux.acc_seg: 63.6546, loss: 1.4395
2022-11-04 10:34:31,716 - mmseg - INFO - Iter [2800/80000]	lr: 1.162e-04, eta: 7:24:45, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9920, decode.acc_seg: 66.7680, aux.loss_ce: 0.4647, aux.acc_seg: 63.2107, loss: 1.4567
2022-11-04 10:34:48,743 - mmseg - INFO - Iter [2850/80000]	lr: 1.161e-04, eta: 7:24:21, time: 0.341, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9747, decode.acc_seg: 66.9913, aux.loss_ce: 0.4515, aux.acc_seg: 64.1497, loss: 1.4262
2022-11-04 10:35:05,598 - mmseg - INFO - Iter [2900/80000]	lr: 1.161e-04, eta: 7:23:53, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9914, decode.acc_seg: 67.0873, aux.loss_ce: 0.4575, aux.acc_seg: 63.5725, loss: 1.4489
2022-11-04 10:35:22,412 - mmseg - INFO - Iter [2950/80000]	lr: 1.160e-04, eta: 7:23:23, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 1.0057, decode.acc_seg: 66.1017, aux.loss_ce: 0.4636, aux.acc_seg: 63.2142, loss: 1.4692
2022-11-04 10:35:39,153 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:35:39,153 - mmseg - INFO - Iter [3000/80000]	lr: 1.159e-04, eta: 7:22:53, time: 0.335, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9714, decode.acc_seg: 66.6830, aux.loss_ce: 0.4514, aux.acc_seg: 63.7503, loss: 1.4229
2022-11-04 10:35:55,865 - mmseg - INFO - Iter [3050/80000]	lr: 1.159e-04, eta: 7:22:22, time: 0.334, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9721, decode.acc_seg: 67.0854, aux.loss_ce: 0.4512, aux.acc_seg: 63.5550, loss: 1.4233
2022-11-04 10:36:12,627 - mmseg - INFO - Iter [3100/80000]	lr: 1.158e-04, eta: 7:21:52, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9698, decode.acc_seg: 67.2665, aux.loss_ce: 0.4525, aux.acc_seg: 63.7555, loss: 1.4223
2022-11-04 10:36:29,304 - mmseg - INFO - Iter [3150/80000]	lr: 1.157e-04, eta: 7:21:21, time: 0.334, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9961, decode.acc_seg: 66.1661, aux.loss_ce: 0.4617, aux.acc_seg: 62.9210, loss: 1.4578
2022-11-04 10:36:49,117 - mmseg - INFO - Iter [3200/80000]	lr: 1.157e-04, eta: 7:22:06, time: 0.396, data_time: 0.059, memory: 5208, decode.loss_ce: 0.9790, decode.acc_seg: 66.6994, aux.loss_ce: 0.4584, aux.acc_seg: 63.7438, loss: 1.4373
2022-11-04 10:37:06,710 - mmseg - INFO - Iter [3250/80000]	lr: 1.156e-04, eta: 7:21:57, time: 0.352, data_time: 0.023, memory: 5208, decode.loss_ce: 0.9323, decode.acc_seg: 68.1779, aux.loss_ce: 0.4397, aux.acc_seg: 64.7613, loss: 1.3719
2022-11-04 10:37:23,663 - mmseg - INFO - Iter [3300/80000]	lr: 1.155e-04, eta: 7:21:32, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9492, decode.acc_seg: 67.6973, aux.loss_ce: 0.4492, aux.acc_seg: 64.4843, loss: 1.3983
2022-11-04 10:37:40,311 - mmseg - INFO - Iter [3350/80000]	lr: 1.155e-04, eta: 7:21:00, time: 0.333, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9569, decode.acc_seg: 67.6680, aux.loss_ce: 0.4454, aux.acc_seg: 64.3553, loss: 1.4023
2022-11-04 10:37:57,230 - mmseg - INFO - Iter [3400/80000]	lr: 1.154e-04, eta: 7:20:35, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9309, decode.acc_seg: 68.0460, aux.loss_ce: 0.4354, aux.acc_seg: 64.7909, loss: 1.3663
2022-11-04 10:38:14,226 - mmseg - INFO - Iter [3450/80000]	lr: 1.153e-04, eta: 7:20:12, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9220, decode.acc_seg: 68.5102, aux.loss_ce: 0.4334, aux.acc_seg: 64.8340, loss: 1.3554
2022-11-04 10:38:31,239 - mmseg - INFO - Iter [3500/80000]	lr: 1.153e-04, eta: 7:19:50, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9158, decode.acc_seg: 68.6084, aux.loss_ce: 0.4338, aux.acc_seg: 64.8818, loss: 1.3496
2022-11-04 10:38:48,151 - mmseg - INFO - Iter [3550/80000]	lr: 1.152e-04, eta: 7:19:25, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9324, decode.acc_seg: 68.1734, aux.loss_ce: 0.4403, aux.acc_seg: 64.2673, loss: 1.3728
2022-11-04 10:39:05,102 - mmseg - INFO - Iter [3600/80000]	lr: 1.151e-04, eta: 7:19:02, time: 0.339, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9201, decode.acc_seg: 68.5384, aux.loss_ce: 0.4372, aux.acc_seg: 64.1666, loss: 1.3573
2022-11-04 10:39:22,015 - mmseg - INFO - Iter [3650/80000]	lr: 1.151e-04, eta: 7:18:38, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9364, decode.acc_seg: 67.3261, aux.loss_ce: 0.4418, aux.acc_seg: 63.6722, loss: 1.3782
2022-11-04 10:39:39,000 - mmseg - INFO - Iter [3700/80000]	lr: 1.150e-04, eta: 7:18:15, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9135, decode.acc_seg: 68.9254, aux.loss_ce: 0.4268, aux.acc_seg: 65.3286, loss: 1.3403
2022-11-04 10:39:55,967 - mmseg - INFO - Iter [3750/80000]	lr: 1.149e-04, eta: 7:17:53, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9359, decode.acc_seg: 67.2066, aux.loss_ce: 0.4364, aux.acc_seg: 64.2148, loss: 1.3723
2022-11-04 10:40:15,768 - mmseg - INFO - Iter [3800/80000]	lr: 1.149e-04, eta: 7:18:27, time: 0.396, data_time: 0.066, memory: 5208, decode.loss_ce: 0.9385, decode.acc_seg: 67.4539, aux.loss_ce: 0.4358, aux.acc_seg: 64.4696, loss: 1.3744
2022-11-04 10:40:32,561 - mmseg - INFO - Iter [3850/80000]	lr: 1.148e-04, eta: 7:18:00, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9222, decode.acc_seg: 68.2884, aux.loss_ce: 0.4397, aux.acc_seg: 64.6706, loss: 1.3618
2022-11-04 10:40:49,368 - mmseg - INFO - Iter [3900/80000]	lr: 1.147e-04, eta: 7:17:34, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9128, decode.acc_seg: 69.3902, aux.loss_ce: 0.4321, aux.acc_seg: 65.3501, loss: 1.3450
2022-11-04 10:41:06,147 - mmseg - INFO - Iter [3950/80000]	lr: 1.147e-04, eta: 7:17:08, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8933, decode.acc_seg: 69.0139, aux.loss_ce: 0.4201, aux.acc_seg: 65.5769, loss: 1.3134
2022-11-04 10:41:23,030 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:41:23,031 - mmseg - INFO - Iter [4000/80000]	lr: 1.146e-04, eta: 7:16:44, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9059, decode.acc_seg: 68.8744, aux.loss_ce: 0.4303, aux.acc_seg: 65.3698, loss: 1.3362
2022-11-04 10:41:39,839 - mmseg - INFO - Iter [4050/80000]	lr: 1.145e-04, eta: 7:16:19, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9173, decode.acc_seg: 68.3594, aux.loss_ce: 0.4374, aux.acc_seg: 64.4370, loss: 1.3547
2022-11-04 10:41:56,631 - mmseg - INFO - Iter [4100/80000]	lr: 1.145e-04, eta: 7:15:53, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8681, decode.acc_seg: 69.7236, aux.loss_ce: 0.4172, aux.acc_seg: 65.9273, loss: 1.2853
2022-11-04 10:42:13,517 - mmseg - INFO - Iter [4150/80000]	lr: 1.144e-04, eta: 7:15:30, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 0.9079, decode.acc_seg: 68.7868, aux.loss_ce: 0.4298, aux.acc_seg: 64.7758, loss: 1.3377
2022-11-04 10:42:30,256 - mmseg - INFO - Iter [4200/80000]	lr: 1.143e-04, eta: 7:15:04, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8733, decode.acc_seg: 69.6785, aux.loss_ce: 0.4114, aux.acc_seg: 66.1025, loss: 1.2847
2022-11-04 10:42:46,844 - mmseg - INFO - Iter [4250/80000]	lr: 1.142e-04, eta: 7:14:35, time: 0.332, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8934, decode.acc_seg: 68.9203, aux.loss_ce: 0.4248, aux.acc_seg: 64.9519, loss: 1.3182
2022-11-04 10:43:03,669 - mmseg - INFO - Iter [4300/80000]	lr: 1.142e-04, eta: 7:14:11, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8851, decode.acc_seg: 69.4001, aux.loss_ce: 0.4229, aux.acc_seg: 65.3435, loss: 1.3080
2022-11-04 10:43:20,677 - mmseg - INFO - Iter [4350/80000]	lr: 1.141e-04, eta: 7:13:51, time: 0.340, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8763, decode.acc_seg: 69.7110, aux.loss_ce: 0.4147, aux.acc_seg: 66.0954, loss: 1.2909
2022-11-04 10:43:37,560 - mmseg - INFO - Iter [4400/80000]	lr: 1.140e-04, eta: 7:13:28, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 0.9125, decode.acc_seg: 68.4552, aux.loss_ce: 0.4351, aux.acc_seg: 64.4816, loss: 1.3476
2022-11-04 10:43:57,158 - mmseg - INFO - Iter [4450/80000]	lr: 1.140e-04, eta: 7:13:51, time: 0.392, data_time: 0.062, memory: 5208, decode.loss_ce: 0.8967, decode.acc_seg: 69.3513, aux.loss_ce: 0.4293, aux.acc_seg: 65.4759, loss: 1.3260
2022-11-04 10:44:13,876 - mmseg - INFO - Iter [4500/80000]	lr: 1.139e-04, eta: 7:13:26, time: 0.334, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8817, decode.acc_seg: 68.6758, aux.loss_ce: 0.4251, aux.acc_seg: 64.6494, loss: 1.3068
2022-11-04 10:44:30,665 - mmseg - INFO - Iter [4550/80000]	lr: 1.138e-04, eta: 7:13:01, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8653, decode.acc_seg: 69.5986, aux.loss_ce: 0.4165, aux.acc_seg: 65.8082, loss: 1.2819
2022-11-04 10:44:47,224 - mmseg - INFO - Iter [4600/80000]	lr: 1.138e-04, eta: 7:12:33, time: 0.331, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8727, decode.acc_seg: 69.8926, aux.loss_ce: 0.4128, aux.acc_seg: 66.2466, loss: 1.2856
2022-11-04 10:45:04,172 - mmseg - INFO - Iter [4650/80000]	lr: 1.137e-04, eta: 7:12:12, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8682, decode.acc_seg: 70.0024, aux.loss_ce: 0.4138, aux.acc_seg: 65.8543, loss: 1.2821
2022-11-04 10:45:20,930 - mmseg - INFO - Iter [4700/80000]	lr: 1.136e-04, eta: 7:11:47, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8748, decode.acc_seg: 70.0521, aux.loss_ce: 0.4163, aux.acc_seg: 66.0362, loss: 1.2911
2022-11-04 10:45:37,614 - mmseg - INFO - Iter [4750/80000]	lr: 1.136e-04, eta: 7:11:22, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8551, decode.acc_seg: 69.4403, aux.loss_ce: 0.4169, aux.acc_seg: 65.6020, loss: 1.2720
2022-11-04 10:45:54,333 - mmseg - INFO - Iter [4800/80000]	lr: 1.135e-04, eta: 7:10:57, time: 0.334, data_time: 0.007, memory: 5208, decode.loss_ce: 0.8469, decode.acc_seg: 70.3403, aux.loss_ce: 0.4078, aux.acc_seg: 66.1991, loss: 1.2547
2022-11-04 10:46:11,016 - mmseg - INFO - Iter [4850/80000]	lr: 1.134e-04, eta: 7:10:32, time: 0.334, data_time: 0.007, memory: 5208, decode.loss_ce: 0.8609, decode.acc_seg: 69.6656, aux.loss_ce: 0.4109, aux.acc_seg: 66.1931, loss: 1.2718
2022-11-04 10:46:27,914 - mmseg - INFO - Iter [4900/80000]	lr: 1.134e-04, eta: 7:10:10, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8698, decode.acc_seg: 69.0542, aux.loss_ce: 0.4139, aux.acc_seg: 65.3311, loss: 1.2837
2022-11-04 10:46:44,574 - mmseg - INFO - Iter [4950/80000]	lr: 1.133e-04, eta: 7:09:45, time: 0.333, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8034, decode.acc_seg: 71.1940, aux.loss_ce: 0.3866, aux.acc_seg: 67.7411, loss: 1.1900
2022-11-04 10:47:01,303 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:47:01,304 - mmseg - INFO - Iter [5000/80000]	lr: 1.132e-04, eta: 7:09:21, time: 0.335, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8572, decode.acc_seg: 70.0710, aux.loss_ce: 0.4119, aux.acc_seg: 66.0071, loss: 1.2691
2022-11-04 10:47:20,856 - mmseg - INFO - Iter [5050/80000]	lr: 1.132e-04, eta: 7:09:39, time: 0.391, data_time: 0.062, memory: 5208, decode.loss_ce: 0.8481, decode.acc_seg: 70.0345, aux.loss_ce: 0.4101, aux.acc_seg: 66.1588, loss: 1.2582
2022-11-04 10:47:37,612 - mmseg - INFO - Iter [5100/80000]	lr: 1.131e-04, eta: 7:09:16, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8430, decode.acc_seg: 70.5456, aux.loss_ce: 0.4050, aux.acc_seg: 66.6496, loss: 1.2480
2022-11-04 10:47:54,315 - mmseg - INFO - Iter [5150/80000]	lr: 1.130e-04, eta: 7:08:51, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8193, decode.acc_seg: 70.9635, aux.loss_ce: 0.3987, aux.acc_seg: 66.8461, loss: 1.2179
2022-11-04 10:48:11,100 - mmseg - INFO - Iter [5200/80000]	lr: 1.130e-04, eta: 7:08:28, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8285, decode.acc_seg: 70.6651, aux.loss_ce: 0.3963, aux.acc_seg: 66.8267, loss: 1.2248
2022-11-04 10:48:27,955 - mmseg - INFO - Iter [5250/80000]	lr: 1.129e-04, eta: 7:08:06, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8279, decode.acc_seg: 70.2033, aux.loss_ce: 0.3977, aux.acc_seg: 66.3666, loss: 1.2256
2022-11-04 10:48:44,754 - mmseg - INFO - Iter [5300/80000]	lr: 1.128e-04, eta: 7:07:44, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8519, decode.acc_seg: 70.0733, aux.loss_ce: 0.4085, aux.acc_seg: 65.8125, loss: 1.2603
2022-11-04 10:49:01,436 - mmseg - INFO - Iter [5350/80000]	lr: 1.128e-04, eta: 7:07:20, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8355, decode.acc_seg: 70.3336, aux.loss_ce: 0.3968, aux.acc_seg: 66.8882, loss: 1.2324
2022-11-04 10:49:18,231 - mmseg - INFO - Iter [5400/80000]	lr: 1.127e-04, eta: 7:06:57, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8133, decode.acc_seg: 70.9742, aux.loss_ce: 0.3955, aux.acc_seg: 66.9916, loss: 1.2088
2022-11-04 10:49:35,097 - mmseg - INFO - Iter [5450/80000]	lr: 1.126e-04, eta: 7:06:36, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8332, decode.acc_seg: 70.1889, aux.loss_ce: 0.4037, aux.acc_seg: 66.2327, loss: 1.2369
2022-11-04 10:49:51,931 - mmseg - INFO - Iter [5500/80000]	lr: 1.126e-04, eta: 7:06:14, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8352, decode.acc_seg: 70.0780, aux.loss_ce: 0.4004, aux.acc_seg: 66.5814, loss: 1.2356
2022-11-04 10:50:08,865 - mmseg - INFO - Iter [5550/80000]	lr: 1.125e-04, eta: 7:05:54, time: 0.339, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8447, decode.acc_seg: 70.2972, aux.loss_ce: 0.4016, aux.acc_seg: 66.8322, loss: 1.2462
2022-11-04 10:50:25,718 - mmseg - INFO - Iter [5600/80000]	lr: 1.124e-04, eta: 7:05:33, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8296, decode.acc_seg: 70.4380, aux.loss_ce: 0.3991, aux.acc_seg: 66.6780, loss: 1.2287
2022-11-04 10:50:42,403 - mmseg - INFO - Iter [5650/80000]	lr: 1.123e-04, eta: 7:05:09, time: 0.334, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8415, decode.acc_seg: 70.2711, aux.loss_ce: 0.4027, aux.acc_seg: 66.5846, loss: 1.2442
2022-11-04 10:51:02,229 - mmseg - INFO - Iter [5700/80000]	lr: 1.123e-04, eta: 7:05:27, time: 0.397, data_time: 0.063, memory: 5208, decode.loss_ce: 0.8162, decode.acc_seg: 70.4908, aux.loss_ce: 0.3909, aux.acc_seg: 66.8561, loss: 1.2071
2022-11-04 10:51:19,016 - mmseg - INFO - Iter [5750/80000]	lr: 1.122e-04, eta: 7:05:05, time: 0.336, data_time: 0.007, memory: 5208, decode.loss_ce: 0.8230, decode.acc_seg: 70.3586, aux.loss_ce: 0.4010, aux.acc_seg: 66.3558, loss: 1.2241
2022-11-04 10:51:36,303 - mmseg - INFO - Iter [5800/80000]	lr: 1.121e-04, eta: 7:04:49, time: 0.346, data_time: 0.016, memory: 5208, decode.loss_ce: 0.8150, decode.acc_seg: 71.4604, aux.loss_ce: 0.3949, aux.acc_seg: 67.4927, loss: 1.2099
2022-11-04 10:51:53,072 - mmseg - INFO - Iter [5850/80000]	lr: 1.121e-04, eta: 7:04:27, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8275, decode.acc_seg: 70.6645, aux.loss_ce: 0.4030, aux.acc_seg: 66.4716, loss: 1.2305
2022-11-04 10:52:10,055 - mmseg - INFO - Iter [5900/80000]	lr: 1.120e-04, eta: 7:04:07, time: 0.340, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7939, decode.acc_seg: 71.2529, aux.loss_ce: 0.3835, aux.acc_seg: 67.2474, loss: 1.1774
2022-11-04 10:52:26,830 - mmseg - INFO - Iter [5950/80000]	lr: 1.119e-04, eta: 7:03:45, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8369, decode.acc_seg: 70.5508, aux.loss_ce: 0.4054, aux.acc_seg: 66.5891, loss: 1.2423
2022-11-04 10:52:43,419 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:52:43,419 - mmseg - INFO - Iter [6000/80000]	lr: 1.119e-04, eta: 7:03:21, time: 0.332, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8241, decode.acc_seg: 70.9001, aux.loss_ce: 0.3999, aux.acc_seg: 66.8968, loss: 1.2240
2022-11-04 10:53:00,078 - mmseg - INFO - Iter [6050/80000]	lr: 1.118e-04, eta: 7:02:57, time: 0.333, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8103, decode.acc_seg: 70.7164, aux.loss_ce: 0.3874, aux.acc_seg: 67.0502, loss: 1.1977
2022-11-04 10:53:16,930 - mmseg - INFO - Iter [6100/80000]	lr: 1.117e-04, eta: 7:02:37, time: 0.337, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8174, decode.acc_seg: 71.2262, aux.loss_ce: 0.3912, aux.acc_seg: 67.4716, loss: 1.2086
2022-11-04 10:53:33,787 - mmseg - INFO - Iter [6150/80000]	lr: 1.117e-04, eta: 7:02:16, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8315, decode.acc_seg: 70.5002, aux.loss_ce: 0.3898, aux.acc_seg: 67.1492, loss: 1.2213
2022-11-04 10:53:50,537 - mmseg - INFO - Iter [6200/80000]	lr: 1.116e-04, eta: 7:01:54, time: 0.335, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8072, decode.acc_seg: 70.9496, aux.loss_ce: 0.3914, aux.acc_seg: 66.9668, loss: 1.1986
2022-11-04 10:54:07,198 - mmseg - INFO - Iter [6250/80000]	lr: 1.115e-04, eta: 7:01:31, time: 0.333, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8276, decode.acc_seg: 71.0208, aux.loss_ce: 0.3968, aux.acc_seg: 67.0551, loss: 1.2244
2022-11-04 10:54:24,233 - mmseg - INFO - Iter [6300/80000]	lr: 1.115e-04, eta: 7:01:12, time: 0.341, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8114, decode.acc_seg: 71.3496, aux.loss_ce: 0.3903, aux.acc_seg: 67.3990, loss: 1.2017
2022-11-04 10:54:43,829 - mmseg - INFO - Iter [6350/80000]	lr: 1.114e-04, eta: 7:01:24, time: 0.392, data_time: 0.070, memory: 5208, decode.loss_ce: 0.7725, decode.acc_seg: 71.8776, aux.loss_ce: 0.3739, aux.acc_seg: 68.0264, loss: 1.1464
2022-11-04 10:55:00,706 - mmseg - INFO - Iter [6400/80000]	lr: 1.113e-04, eta: 7:01:03, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7781, decode.acc_seg: 71.8630, aux.loss_ce: 0.3818, aux.acc_seg: 67.8202, loss: 1.1599
2022-11-04 10:55:17,604 - mmseg - INFO - Iter [6450/80000]	lr: 1.113e-04, eta: 7:00:43, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7966, decode.acc_seg: 71.6107, aux.loss_ce: 0.3821, aux.acc_seg: 68.1628, loss: 1.1787
2022-11-04 10:55:34,357 - mmseg - INFO - Iter [6500/80000]	lr: 1.112e-04, eta: 7:00:21, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7969, decode.acc_seg: 71.6838, aux.loss_ce: 0.3917, aux.acc_seg: 67.0296, loss: 1.1886
2022-11-04 10:55:51,338 - mmseg - INFO - Iter [6550/80000]	lr: 1.111e-04, eta: 7:00:02, time: 0.340, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8027, decode.acc_seg: 72.0126, aux.loss_ce: 0.3847, aux.acc_seg: 68.9189, loss: 1.1874
2022-11-04 10:56:08,119 - mmseg - INFO - Iter [6600/80000]	lr: 1.111e-04, eta: 6:59:41, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8070, decode.acc_seg: 71.0013, aux.loss_ce: 0.3917, aux.acc_seg: 66.7508, loss: 1.1987
2022-11-04 10:56:24,853 - mmseg - INFO - Iter [6650/80000]	lr: 1.110e-04, eta: 6:59:19, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7623, decode.acc_seg: 72.3351, aux.loss_ce: 0.3701, aux.acc_seg: 68.2395, loss: 1.1324
2022-11-04 10:56:41,470 - mmseg - INFO - Iter [6700/80000]	lr: 1.109e-04, eta: 6:58:56, time: 0.332, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7829, decode.acc_seg: 71.6713, aux.loss_ce: 0.3879, aux.acc_seg: 67.2119, loss: 1.1709
2022-11-04 10:56:58,285 - mmseg - INFO - Iter [6750/80000]	lr: 1.108e-04, eta: 6:58:35, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7997, decode.acc_seg: 71.4198, aux.loss_ce: 0.3861, aux.acc_seg: 67.9119, loss: 1.1858
2022-11-04 10:57:15,018 - mmseg - INFO - Iter [6800/80000]	lr: 1.108e-04, eta: 6:58:14, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7959, decode.acc_seg: 71.4485, aux.loss_ce: 0.3826, aux.acc_seg: 67.7184, loss: 1.1785
2022-11-04 10:57:31,805 - mmseg - INFO - Iter [6850/80000]	lr: 1.107e-04, eta: 6:57:53, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8052, decode.acc_seg: 71.0459, aux.loss_ce: 0.3873, aux.acc_seg: 67.1571, loss: 1.1925
2022-11-04 10:57:48,561 - mmseg - INFO - Iter [6900/80000]	lr: 1.106e-04, eta: 6:57:32, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7668, decode.acc_seg: 71.7804, aux.loss_ce: 0.3708, aux.acc_seg: 68.1414, loss: 1.1376
2022-11-04 10:58:07,928 - mmseg - INFO - Iter [6950/80000]	lr: 1.106e-04, eta: 6:57:38, time: 0.387, data_time: 0.063, memory: 5208, decode.loss_ce: 0.7848, decode.acc_seg: 72.1982, aux.loss_ce: 0.3823, aux.acc_seg: 67.6705, loss: 1.1671
2022-11-04 10:58:24,400 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 10:58:24,401 - mmseg - INFO - Iter [7000/80000]	lr: 1.105e-04, eta: 6:57:14, time: 0.329, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7642, decode.acc_seg: 72.8544, aux.loss_ce: 0.3774, aux.acc_seg: 68.1155, loss: 1.1415
2022-11-04 10:58:41,078 - mmseg - INFO - Iter [7050/80000]	lr: 1.104e-04, eta: 6:56:52, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7782, decode.acc_seg: 72.3276, aux.loss_ce: 0.3790, aux.acc_seg: 68.1749, loss: 1.1572
2022-11-04 10:58:57,758 - mmseg - INFO - Iter [7100/80000]	lr: 1.104e-04, eta: 6:56:30, time: 0.334, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7556, decode.acc_seg: 72.4577, aux.loss_ce: 0.3697, aux.acc_seg: 68.5047, loss: 1.1253
2022-11-04 10:59:14,558 - mmseg - INFO - Iter [7150/80000]	lr: 1.103e-04, eta: 6:56:09, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7656, decode.acc_seg: 72.0130, aux.loss_ce: 0.3693, aux.acc_seg: 68.1441, loss: 1.1350
2022-11-04 10:59:31,335 - mmseg - INFO - Iter [7200/80000]	lr: 1.102e-04, eta: 6:55:48, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7581, decode.acc_seg: 73.1623, aux.loss_ce: 0.3706, aux.acc_seg: 68.7460, loss: 1.1287
2022-11-04 10:59:48,088 - mmseg - INFO - Iter [7250/80000]	lr: 1.102e-04, eta: 6:55:27, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7857, decode.acc_seg: 71.6174, aux.loss_ce: 0.3854, aux.acc_seg: 67.5057, loss: 1.1711
2022-11-04 11:00:04,861 - mmseg - INFO - Iter [7300/80000]	lr: 1.101e-04, eta: 6:55:07, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7991, decode.acc_seg: 71.7305, aux.loss_ce: 0.3921, aux.acc_seg: 66.9631, loss: 1.1912
2022-11-04 11:00:21,677 - mmseg - INFO - Iter [7350/80000]	lr: 1.100e-04, eta: 6:54:46, time: 0.336, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7870, decode.acc_seg: 71.8296, aux.loss_ce: 0.3759, aux.acc_seg: 68.2681, loss: 1.1629
2022-11-04 11:00:38,400 - mmseg - INFO - Iter [7400/80000]	lr: 1.100e-04, eta: 6:54:25, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7774, decode.acc_seg: 72.1061, aux.loss_ce: 0.3770, aux.acc_seg: 67.9948, loss: 1.1544
2022-11-04 11:00:55,076 - mmseg - INFO - Iter [7450/80000]	lr: 1.099e-04, eta: 6:54:04, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.8061, decode.acc_seg: 71.6237, aux.loss_ce: 0.3863, aux.acc_seg: 67.5792, loss: 1.1923
2022-11-04 11:01:11,694 - mmseg - INFO - Iter [7500/80000]	lr: 1.098e-04, eta: 6:53:42, time: 0.332, data_time: 0.009, memory: 5208, decode.loss_ce: 0.8410, decode.acc_seg: 70.3915, aux.loss_ce: 0.4086, aux.acc_seg: 66.1938, loss: 1.2496
2022-11-04 11:01:28,395 - mmseg - INFO - Iter [7550/80000]	lr: 1.098e-04, eta: 6:53:21, time: 0.334, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7836, decode.acc_seg: 71.6745, aux.loss_ce: 0.3758, aux.acc_seg: 68.0199, loss: 1.1594
2022-11-04 11:01:48,194 - mmseg - INFO - Iter [7600/80000]	lr: 1.097e-04, eta: 6:53:29, time: 0.396, data_time: 0.071, memory: 5208, decode.loss_ce: 0.7790, decode.acc_seg: 71.4565, aux.loss_ce: 0.3761, aux.acc_seg: 67.7654, loss: 1.1551
2022-11-04 11:02:04,924 - mmseg - INFO - Iter [7650/80000]	lr: 1.096e-04, eta: 6:53:08, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7484, decode.acc_seg: 72.9798, aux.loss_ce: 0.3731, aux.acc_seg: 68.2251, loss: 1.1215
2022-11-04 11:02:22,989 - mmseg - INFO - Iter [7700/80000]	lr: 1.096e-04, eta: 6:53:00, time: 0.361, data_time: 0.037, memory: 5208, decode.loss_ce: 0.7628, decode.acc_seg: 72.4146, aux.loss_ce: 0.3777, aux.acc_seg: 68.2992, loss: 1.1405
2022-11-04 11:02:39,815 - mmseg - INFO - Iter [7750/80000]	lr: 1.095e-04, eta: 6:52:40, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7915, decode.acc_seg: 71.5908, aux.loss_ce: 0.3899, aux.acc_seg: 67.2575, loss: 1.1814
2022-11-04 11:02:56,575 - mmseg - INFO - Iter [7800/80000]	lr: 1.094e-04, eta: 6:52:19, time: 0.335, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7448, decode.acc_seg: 72.5227, aux.loss_ce: 0.3659, aux.acc_seg: 68.4482, loss: 1.1107
2022-11-04 11:03:13,479 - mmseg - INFO - Iter [7850/80000]	lr: 1.093e-04, eta: 6:52:00, time: 0.338, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7548, decode.acc_seg: 72.5376, aux.loss_ce: 0.3688, aux.acc_seg: 68.4983, loss: 1.1236
2022-11-04 11:03:30,364 - mmseg - INFO - Iter [7900/80000]	lr: 1.093e-04, eta: 6:51:41, time: 0.338, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7646, decode.acc_seg: 72.5401, aux.loss_ce: 0.3779, aux.acc_seg: 68.1362, loss: 1.1424
2022-11-04 11:03:47,198 - mmseg - INFO - Iter [7950/80000]	lr: 1.092e-04, eta: 6:51:21, time: 0.337, data_time: 0.009, memory: 5208, decode.loss_ce: 0.7369, decode.acc_seg: 72.9953, aux.loss_ce: 0.3619, aux.acc_seg: 68.8848, loss: 1.0988
2022-11-04 11:04:03,825 - mmseg - INFO - Saving checkpoint at 8000 iterations
2022-11-04 11:04:04,020 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:04:04,020 - mmseg - INFO - Iter [8000/80000]	lr: 1.091e-04, eta: 6:51:01, time: 0.336, data_time: 0.008, memory: 5208, decode.loss_ce: 0.7758, decode.acc_seg: 72.1605, aux.loss_ce: 0.3760, aux.acc_seg: 68.4170, loss: 1.1519
2022-11-04 11:04:39,717 - mmseg - INFO - per class results:
2022-11-04 11:04:39,724 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        |  63.3 | 83.02 |
|       building      | 74.67 | 88.61 |
|         sky         | 88.24 | 93.56 |
|        floor        | 69.03 | 83.19 |
|         tree        | 63.37 | 85.06 |
|       ceiling       | 72.74 | 82.63 |
|         road        | 72.72 | 88.49 |
|         bed         | 69.23 | 90.27 |
|      windowpane     | 46.65 | 63.61 |
|        grass        | 63.17 | 79.03 |
|       cabinet       | 43.94 | 60.58 |
|       sidewalk      | 45.69 | 60.61 |
|        person       |  61.6 |  77.7 |
|        earth        | 25.62 | 33.55 |
|         door        | 20.67 | 29.69 |
|        table        | 34.11 | 48.35 |
|       mountain      | 53.92 | 74.65 |
|        plant        | 35.19 | 43.35 |
|       curtain       | 52.55 | 70.57 |
|        chair        | 34.13 |  48.8 |
|         car         |  67.1 | 82.68 |
|        water        | 42.66 | 57.48 |
|       painting      | 49.68 | 67.39 |
|         sofa        | 44.85 |  68.8 |
|        shelf        | 29.83 | 44.35 |
|        house        | 37.19 | 49.52 |
|         sea         | 45.99 | 86.21 |
|        mirror       | 26.89 | 31.46 |
|         rug         | 34.31 | 39.97 |
|        field        | 30.04 | 47.31 |
|       armchair      |  20.2 | 29.58 |
|         seat        | 43.27 | 62.29 |
|        fence        |  18.6 | 31.96 |
|         desk        | 22.08 | 40.61 |
|         rock        | 44.51 | 68.62 |
|       wardrobe      | 34.99 | 56.89 |
|         lamp        | 31.68 | 41.37 |
|       bathtub       | 45.14 | 74.09 |
|       railing       | 29.14 | 36.03 |
|       cushion       | 22.59 | 29.43 |
|         base        |  11.9 | 20.51 |
|         box         |  7.81 |  9.65 |
|        column       |  23.3 | 27.01 |
|      signboard      | 19.97 | 27.03 |
|   chest of drawers  | 27.67 | 49.01 |
|       counter       | 14.27 | 19.97 |
|         sand        | 27.38 | 41.93 |
|         sink        | 31.56 | 42.48 |
|      skyscraper     | 54.41 | 68.78 |
|      fireplace      | 45.07 | 67.73 |
|     refrigerator    | 32.65 |  38.8 |
|      grandstand     | 46.75 | 62.62 |
|         path        |  6.14 |  7.3  |
|        stairs       | 23.15 | 26.72 |
|        runway       | 69.09 | 84.67 |
|         case        | 37.43 | 59.42 |
|      pool table     | 71.15 | 92.96 |
|        pillow       | 29.07 | 39.07 |
|     screen door     | 31.98 | 36.65 |
|       stairway      | 18.88 | 24.48 |
|        river        | 10.92 | 17.91 |
|        bridge       | 36.73 | 59.86 |
|       bookcase      | 26.03 | 56.85 |
|        blind        |  4.1  |  4.23 |
|     coffee table    | 32.98 | 59.73 |
|        toilet       | 54.69 | 70.96 |
|        flower       | 21.99 | 36.11 |
|         book        | 30.58 |  41.7 |
|         hill        |  2.12 |  2.27 |
|        bench        |  30.8 | 43.53 |
|      countertop     | 25.79 |  31.6 |
|        stove        | 38.42 | 69.65 |
|         palm        | 28.62 | 34.52 |
|    kitchen island   | 16.39 | 32.28 |
|       computer      | 38.49 |  50.4 |
|     swivel chair    | 23.47 | 39.12 |
|         boat        | 39.59 | 64.02 |
|         bar         | 11.83 | 13.61 |
|    arcade machine   | 28.28 | 48.33 |
|        hovel        | 31.79 | 35.92 |
|         bus         | 65.25 | 81.86 |
|        towel        | 27.19 | 32.99 |
|        light        |  2.5  |  2.57 |
|        truck        |  4.22 |  6.28 |
|        tower        | 31.59 | 35.35 |
|      chandelier     | 39.48 | 52.92 |
|        awning       |  2.45 |  2.63 |
|     streetlight     |  1.96 |  2.08 |
|        booth        | 21.93 | 22.03 |
| television receiver | 38.05 | 58.24 |
|       airplane      | 35.68 | 52.83 |
|      dirt track     |  0.0  |  0.0  |
|       apparel       |  5.25 |  6.45 |
|         pole        |  5.36 |  6.1  |
|         land        |  0.0  |  0.0  |
|      bannister      |  0.19 |  0.22 |
|      escalator      | 19.64 |  22.1 |
|       ottoman       |  0.0  |  0.0  |
|        bottle       |  0.32 |  0.33 |
|        buffet       |  8.93 | 10.55 |
|        poster       |  0.25 |  0.27 |
|        stage        |  4.17 | 12.12 |
|         van         |  0.68 |  0.7  |
|         ship        | 14.72 | 16.44 |
|       fountain      |  2.56 |  2.65 |
|    conveyer belt    | 37.82 | 56.21 |
|        canopy       |  3.94 |  4.2  |
|        washer       | 44.32 | 57.78 |
|      plaything      |  0.52 |  0.61 |
|    swimming pool    | 21.64 | 44.68 |
|        stool        |  0.07 |  0.07 |
|        barrel       | 10.37 | 62.31 |
|        basket       |  1.32 |  1.35 |
|      waterfall      | 53.58 | 72.54 |
|         tent        | 71.61 | 99.49 |
|         bag         |  0.0  |  0.0  |
|       minibike      | 22.06 | 28.13 |
|        cradle       | 47.21 | 86.84 |
|         oven        |  0.17 |  0.18 |
|         ball        | 15.84 | 19.91 |
|         food        | 48.92 | 60.18 |
|         step        |  0.0  |  0.0  |
|         tank        |  0.0  |  0.0  |
|      trade name     |  8.65 |  8.9  |
|      microwave      | 18.94 | 23.43 |
|         pot         | 17.96 |  19.7 |
|        animal       | 42.06 | 45.17 |
|       bicycle       | 25.77 | 40.06 |
|         lake        |  0.0  |  0.0  |
|      dishwasher     |  2.67 |  2.68 |
|        screen       | 51.36 | 58.91 |
|       blanket       |  0.0  |  0.0  |
|      sculpture      |  0.97 |  0.98 |
|         hood        |  5.33 |  5.61 |
|        sconce       |  1.47 |  1.49 |
|         vase        |  6.71 |  7.8  |
|    traffic light    |  0.33 |  0.33 |
|         tray        |  0.27 |  0.28 |
|        ashcan       | 11.12 | 13.69 |
|         fan         |  13.2 | 14.43 |
|         pier        | 19.24 | 20.99 |
|      crt screen     |  0.0  |  0.0  |
|        plate        | 19.14 | 19.78 |
|       monitor       | 17.51 | 18.46 |
|    bulletin board   | 15.02 | 17.29 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 12.31 | 12.46 |
|        glass        |  0.0  |  0.0  |
|        clock        |  1.13 |  1.13 |
|         flag        |  0.19 |  0.19 |
+---------------------+-------+-------+
2022-11-04 11:04:39,724 - mmseg - INFO - Summary:
2022-11-04 11:04:39,725 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 72.86 | 26.52 | 36.31 |
+-------+-------+-------+
2022-11-04 11:04:39,726 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:04:39,726 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7286, mIoU: 0.2652, mAcc: 0.3631, IoU.wall: 0.6330, IoU.building: 0.7467, IoU.sky: 0.8824, IoU.floor: 0.6903, IoU.tree: 0.6337, IoU.ceiling: 0.7274, IoU.road: 0.7272, IoU.bed : 0.6923, IoU.windowpane: 0.4665, IoU.grass: 0.6317, IoU.cabinet: 0.4394, IoU.sidewalk: 0.4569, IoU.person: 0.6160, IoU.earth: 0.2562, IoU.door: 0.2067, IoU.table: 0.3411, IoU.mountain: 0.5392, IoU.plant: 0.3519, IoU.curtain: 0.5255, IoU.chair: 0.3413, IoU.car: 0.6710, IoU.water: 0.4266, IoU.painting: 0.4968, IoU.sofa: 0.4485, IoU.shelf: 0.2983, IoU.house: 0.3719, IoU.sea: 0.4599, IoU.mirror: 0.2689, IoU.rug: 0.3431, IoU.field: 0.3004, IoU.armchair: 0.2020, IoU.seat: 0.4327, IoU.fence: 0.1860, IoU.desk: 0.2208, IoU.rock: 0.4451, IoU.wardrobe: 0.3499, IoU.lamp: 0.3168, IoU.bathtub: 0.4514, IoU.railing: 0.2914, IoU.cushion: 0.2259, IoU.base: 0.1190, IoU.box: 0.0781, IoU.column: 0.2330, IoU.signboard: 0.1997, IoU.chest of drawers: 0.2767, IoU.counter: 0.1427, IoU.sand: 0.2738, IoU.sink: 0.3156, IoU.skyscraper: 0.5441, IoU.fireplace: 0.4507, IoU.refrigerator: 0.3265, IoU.grandstand: 0.4675, IoU.path: 0.0614, IoU.stairs: 0.2315, IoU.runway: 0.6909, IoU.case: 0.3743, IoU.pool table: 0.7115, IoU.pillow: 0.2907, IoU.screen door: 0.3198, IoU.stairway: 0.1888, IoU.river: 0.1092, IoU.bridge: 0.3673, IoU.bookcase: 0.2603, IoU.blind: 0.0410, IoU.coffee table: 0.3298, IoU.toilet: 0.5469, IoU.flower: 0.2199, IoU.book: 0.3058, IoU.hill: 0.0212, IoU.bench: 0.3080, IoU.countertop: 0.2579, IoU.stove: 0.3842, IoU.palm: 0.2862, IoU.kitchen island: 0.1639, IoU.computer: 0.3849, IoU.swivel chair: 0.2347, IoU.boat: 0.3959, IoU.bar: 0.1183, IoU.arcade machine: 0.2828, IoU.hovel: 0.3179, IoU.bus: 0.6525, IoU.towel: 0.2719, IoU.light: 0.0250, IoU.truck: 0.0422, IoU.tower: 0.3159, IoU.chandelier: 0.3948, IoU.awning: 0.0245, IoU.streetlight: 0.0196, IoU.booth: 0.2193, IoU.television receiver: 0.3805, IoU.airplane: 0.3568, IoU.dirt track: 0.0000, IoU.apparel: 0.0525, IoU.pole: 0.0536, IoU.land: 0.0000, IoU.bannister: 0.0019, IoU.escalator: 0.1964, IoU.ottoman: 0.0000, IoU.bottle: 0.0032, IoU.buffet: 0.0893, IoU.poster: 0.0025, IoU.stage: 0.0417, IoU.van: 0.0068, IoU.ship: 0.1472, IoU.fountain: 0.0256, IoU.conveyer belt: 0.3782, IoU.canopy: 0.0394, IoU.washer: 0.4432, IoU.plaything: 0.0052, IoU.swimming pool: 0.2164, IoU.stool: 0.0007, IoU.barrel: 0.1037, IoU.basket: 0.0132, IoU.waterfall: 0.5358, IoU.tent: 0.7161, IoU.bag: 0.0000, IoU.minibike: 0.2206, IoU.cradle: 0.4721, IoU.oven: 0.0017, IoU.ball: 0.1584, IoU.food: 0.4892, IoU.step: 0.0000, IoU.tank: 0.0000, IoU.trade name: 0.0865, IoU.microwave: 0.1894, IoU.pot: 0.1796, IoU.animal: 0.4206, IoU.bicycle: 0.2577, IoU.lake: 0.0000, IoU.dishwasher: 0.0267, IoU.screen: 0.5136, IoU.blanket: 0.0000, IoU.sculpture: 0.0097, IoU.hood: 0.0533, IoU.sconce: 0.0147, IoU.vase: 0.0671, IoU.traffic light: 0.0033, IoU.tray: 0.0027, IoU.ashcan: 0.1112, IoU.fan: 0.1320, IoU.pier: 0.1924, IoU.crt screen: 0.0000, IoU.plate: 0.1914, IoU.monitor: 0.1751, IoU.bulletin board: 0.1502, IoU.shower: 0.0000, IoU.radiator: 0.1231, IoU.glass: 0.0000, IoU.clock: 0.0113, IoU.flag: 0.0019, Acc.wall: 0.8302, Acc.building: 0.8861, Acc.sky: 0.9356, Acc.floor: 0.8319, Acc.tree: 0.8506, Acc.ceiling: 0.8263, Acc.road: 0.8849, Acc.bed : 0.9027, Acc.windowpane: 0.6361, Acc.grass: 0.7903, Acc.cabinet: 0.6058, Acc.sidewalk: 0.6061, Acc.person: 0.7770, Acc.earth: 0.3355, Acc.door: 0.2969, Acc.table: 0.4835, Acc.mountain: 0.7465, Acc.plant: 0.4335, Acc.curtain: 0.7057, Acc.chair: 0.4880, Acc.car: 0.8268, Acc.water: 0.5748, Acc.painting: 0.6739, Acc.sofa: 0.6880, Acc.shelf: 0.4435, Acc.house: 0.4952, Acc.sea: 0.8621, Acc.mirror: 0.3146, Acc.rug: 0.3997, Acc.field: 0.4731, Acc.armchair: 0.2958, Acc.seat: 0.6229, Acc.fence: 0.3196, Acc.desk: 0.4061, Acc.rock: 0.6862, Acc.wardrobe: 0.5689, Acc.lamp: 0.4137, Acc.bathtub: 0.7409, Acc.railing: 0.3603, Acc.cushion: 0.2943, Acc.base: 0.2051, Acc.box: 0.0965, Acc.column: 0.2701, Acc.signboard: 0.2703, Acc.chest of drawers: 0.4901, Acc.counter: 0.1997, Acc.sand: 0.4193, Acc.sink: 0.4248, Acc.skyscraper: 0.6878, Acc.fireplace: 0.6773, Acc.refrigerator: 0.3880, Acc.grandstand: 0.6262, Acc.path: 0.0730, Acc.stairs: 0.2672, Acc.runway: 0.8467, Acc.case: 0.5942, Acc.pool table: 0.9296, Acc.pillow: 0.3907, Acc.screen door: 0.3665, Acc.stairway: 0.2448, Acc.river: 0.1791, Acc.bridge: 0.5986, Acc.bookcase: 0.5685, Acc.blind: 0.0423, Acc.coffee table: 0.5973, Acc.toilet: 0.7096, Acc.flower: 0.3611, Acc.book: 0.4170, Acc.hill: 0.0227, Acc.bench: 0.4353, Acc.countertop: 0.3160, Acc.stove: 0.6965, Acc.palm: 0.3452, Acc.kitchen island: 0.3228, Acc.computer: 0.5040, Acc.swivel chair: 0.3912, Acc.boat: 0.6402, Acc.bar: 0.1361, Acc.arcade machine: 0.4833, Acc.hovel: 0.3592, Acc.bus: 0.8186, Acc.towel: 0.3299, Acc.light: 0.0257, Acc.truck: 0.0628, Acc.tower: 0.3535, Acc.chandelier: 0.5292, Acc.awning: 0.0263, Acc.streetlight: 0.0208, Acc.booth: 0.2203, Acc.television receiver: 0.5824, Acc.airplane: 0.5283, Acc.dirt track: 0.0000, Acc.apparel: 0.0645, Acc.pole: 0.0610, Acc.land: 0.0000, Acc.bannister: 0.0022, Acc.escalator: 0.2210, Acc.ottoman: 0.0000, Acc.bottle: 0.0033, Acc.buffet: 0.1055, Acc.poster: 0.0027, Acc.stage: 0.1212, Acc.van: 0.0070, Acc.ship: 0.1644, Acc.fountain: 0.0265, Acc.conveyer belt: 0.5621, Acc.canopy: 0.0420, Acc.washer: 0.5778, Acc.plaything: 0.0061, Acc.swimming pool: 0.4468, Acc.stool: 0.0007, Acc.barrel: 0.6231, Acc.basket: 0.0135, Acc.waterfall: 0.7254, Acc.tent: 0.9949, Acc.bag: 0.0000, Acc.minibike: 0.2813, Acc.cradle: 0.8684, Acc.oven: 0.0018, Acc.ball: 0.1991, Acc.food: 0.6018, Acc.step: 0.0000, Acc.tank: 0.0000, Acc.trade name: 0.0890, Acc.microwave: 0.2343, Acc.pot: 0.1970, Acc.animal: 0.4517, Acc.bicycle: 0.4006, Acc.lake: 0.0000, Acc.dishwasher: 0.0268, Acc.screen: 0.5891, Acc.blanket: 0.0000, Acc.sculpture: 0.0098, Acc.hood: 0.0561, Acc.sconce: 0.0149, Acc.vase: 0.0780, Acc.traffic light: 0.0033, Acc.tray: 0.0028, Acc.ashcan: 0.1369, Acc.fan: 0.1443, Acc.pier: 0.2099, Acc.crt screen: 0.0000, Acc.plate: 0.1978, Acc.monitor: 0.1846, Acc.bulletin board: 0.1729, Acc.shower: 0.0000, Acc.radiator: 0.1246, Acc.glass: 0.0000, Acc.clock: 0.0113, Acc.flag: 0.0019
2022-11-04 11:04:56,423 - mmseg - INFO - Iter [8050/80000]	lr: 1.091e-04, eta: 6:55:59, time: 1.048, data_time: 0.722, memory: 12960, decode.loss_ce: 0.7601, decode.acc_seg: 72.4217, aux.loss_ce: 0.3763, aux.acc_seg: 67.9656, loss: 1.1364
2022-11-04 11:05:13,221 - mmseg - INFO - Iter [8100/80000]	lr: 1.090e-04, eta: 6:55:37, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7537, decode.acc_seg: 72.6323, aux.loss_ce: 0.3645, aux.acc_seg: 68.9570, loss: 1.1182
2022-11-04 11:05:29,940 - mmseg - INFO - Iter [8150/80000]	lr: 1.089e-04, eta: 6:55:14, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7598, decode.acc_seg: 72.4209, aux.loss_ce: 0.3738, aux.acc_seg: 68.0697, loss: 1.1336
2022-11-04 11:05:46,591 - mmseg - INFO - Iter [8200/80000]	lr: 1.089e-04, eta: 6:54:51, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7642, decode.acc_seg: 72.6231, aux.loss_ce: 0.3782, aux.acc_seg: 68.1485, loss: 1.1424
2022-11-04 11:06:06,484 - mmseg - INFO - Iter [8250/80000]	lr: 1.088e-04, eta: 6:54:56, time: 0.398, data_time: 0.061, memory: 12960, decode.loss_ce: 0.7736, decode.acc_seg: 72.2643, aux.loss_ce: 0.3893, aux.acc_seg: 67.1431, loss: 1.1628
2022-11-04 11:06:23,142 - mmseg - INFO - Iter [8300/80000]	lr: 1.087e-04, eta: 6:54:32, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7311, decode.acc_seg: 73.1880, aux.loss_ce: 0.3626, aux.acc_seg: 69.0982, loss: 1.0937
2022-11-04 11:06:40,012 - mmseg - INFO - Iter [8350/80000]	lr: 1.087e-04, eta: 6:54:11, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7525, decode.acc_seg: 72.5699, aux.loss_ce: 0.3682, aux.acc_seg: 68.4712, loss: 1.1207
2022-11-04 11:06:56,754 - mmseg - INFO - Iter [8400/80000]	lr: 1.086e-04, eta: 6:53:48, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7377, decode.acc_seg: 73.6125, aux.loss_ce: 0.3608, aux.acc_seg: 69.6238, loss: 1.0985
2022-11-04 11:07:13,467 - mmseg - INFO - Iter [8450/80000]	lr: 1.085e-04, eta: 6:53:26, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7521, decode.acc_seg: 72.6477, aux.loss_ce: 0.3691, aux.acc_seg: 68.5094, loss: 1.1213
2022-11-04 11:07:30,412 - mmseg - INFO - Iter [8500/80000]	lr: 1.085e-04, eta: 6:53:05, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7221, decode.acc_seg: 73.8528, aux.loss_ce: 0.3537, aux.acc_seg: 69.9696, loss: 1.0758
2022-11-04 11:07:47,363 - mmseg - INFO - Iter [8550/80000]	lr: 1.084e-04, eta: 6:52:45, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7565, decode.acc_seg: 72.5087, aux.loss_ce: 0.3669, aux.acc_seg: 68.6039, loss: 1.1235
2022-11-04 11:08:04,327 - mmseg - INFO - Iter [8600/80000]	lr: 1.083e-04, eta: 6:52:24, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7217, decode.acc_seg: 73.7470, aux.loss_ce: 0.3569, aux.acc_seg: 69.3790, loss: 1.0786
2022-11-04 11:08:21,061 - mmseg - INFO - Iter [8650/80000]	lr: 1.083e-04, eta: 6:52:02, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7339, decode.acc_seg: 73.3970, aux.loss_ce: 0.3652, aux.acc_seg: 68.8730, loss: 1.0991
2022-11-04 11:08:38,023 - mmseg - INFO - Iter [8700/80000]	lr: 1.082e-04, eta: 6:51:42, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7648, decode.acc_seg: 72.1244, aux.loss_ce: 0.3835, aux.acc_seg: 67.1685, loss: 1.1483
2022-11-04 11:08:54,741 - mmseg - INFO - Iter [8750/80000]	lr: 1.081e-04, eta: 6:51:19, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7330, decode.acc_seg: 73.5102, aux.loss_ce: 0.3631, aux.acc_seg: 69.1816, loss: 1.0961
2022-11-04 11:09:11,609 - mmseg - INFO - Iter [8800/80000]	lr: 1.081e-04, eta: 6:50:58, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7504, decode.acc_seg: 72.9105, aux.loss_ce: 0.3629, aux.acc_seg: 68.8339, loss: 1.1133
2022-11-04 11:09:31,370 - mmseg - INFO - Iter [8850/80000]	lr: 1.080e-04, eta: 6:51:01, time: 0.395, data_time: 0.061, memory: 12960, decode.loss_ce: 0.7437, decode.acc_seg: 73.4341, aux.loss_ce: 0.3704, aux.acc_seg: 68.6165, loss: 1.1141
2022-11-04 11:09:48,061 - mmseg - INFO - Iter [8900/80000]	lr: 1.079e-04, eta: 6:50:38, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7066, decode.acc_seg: 74.1644, aux.loss_ce: 0.3527, aux.acc_seg: 69.7694, loss: 1.0592
2022-11-04 11:10:04,760 - mmseg - INFO - Iter [8950/80000]	lr: 1.078e-04, eta: 6:50:16, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7326, decode.acc_seg: 73.2988, aux.loss_ce: 0.3600, aux.acc_seg: 69.4138, loss: 1.0926
2022-11-04 11:10:21,406 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:10:21,407 - mmseg - INFO - Iter [9000/80000]	lr: 1.078e-04, eta: 6:49:53, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7427, decode.acc_seg: 73.2994, aux.loss_ce: 0.3681, aux.acc_seg: 68.7821, loss: 1.1108
2022-11-04 11:10:38,247 - mmseg - INFO - Iter [9050/80000]	lr: 1.077e-04, eta: 6:49:32, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7050, decode.acc_seg: 74.6327, aux.loss_ce: 0.3521, aux.acc_seg: 70.2721, loss: 1.0571
2022-11-04 11:10:55,123 - mmseg - INFO - Iter [9100/80000]	lr: 1.076e-04, eta: 6:49:11, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7401, decode.acc_seg: 73.4258, aux.loss_ce: 0.3650, aux.acc_seg: 68.7277, loss: 1.1051
2022-11-04 11:11:11,879 - mmseg - INFO - Iter [9150/80000]	lr: 1.076e-04, eta: 6:48:50, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7365, decode.acc_seg: 72.9376, aux.loss_ce: 0.3658, aux.acc_seg: 68.6846, loss: 1.1022
2022-11-04 11:11:28,787 - mmseg - INFO - Iter [9200/80000]	lr: 1.075e-04, eta: 6:48:29, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7273, decode.acc_seg: 73.2558, aux.loss_ce: 0.3581, aux.acc_seg: 68.9431, loss: 1.0853
2022-11-04 11:11:45,439 - mmseg - INFO - Iter [9250/80000]	lr: 1.074e-04, eta: 6:48:07, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7562, decode.acc_seg: 72.4314, aux.loss_ce: 0.3738, aux.acc_seg: 68.3414, loss: 1.1301
2022-11-04 11:12:02,330 - mmseg - INFO - Iter [9300/80000]	lr: 1.074e-04, eta: 6:47:47, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7100, decode.acc_seg: 73.6442, aux.loss_ce: 0.3527, aux.acc_seg: 69.5710, loss: 1.0627
2022-11-04 11:12:19,191 - mmseg - INFO - Iter [9350/80000]	lr: 1.073e-04, eta: 6:47:26, time: 0.337, data_time: 0.010, memory: 12960, decode.loss_ce: 0.7555, decode.acc_seg: 72.0331, aux.loss_ce: 0.3648, aux.acc_seg: 68.3075, loss: 1.1203
2022-11-04 11:12:35,960 - mmseg - INFO - Iter [9400/80000]	lr: 1.072e-04, eta: 6:47:05, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7435, decode.acc_seg: 73.3056, aux.loss_ce: 0.3650, aux.acc_seg: 69.3334, loss: 1.1085
2022-11-04 11:12:52,862 - mmseg - INFO - Iter [9450/80000]	lr: 1.072e-04, eta: 6:46:44, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7109, decode.acc_seg: 73.6875, aux.loss_ce: 0.3488, aux.acc_seg: 69.5694, loss: 1.0597
2022-11-04 11:13:12,567 - mmseg - INFO - Iter [9500/80000]	lr: 1.071e-04, eta: 6:46:45, time: 0.394, data_time: 0.064, memory: 12960, decode.loss_ce: 0.7183, decode.acc_seg: 74.0793, aux.loss_ce: 0.3539, aux.acc_seg: 69.4503, loss: 1.0722
2022-11-04 11:13:29,323 - mmseg - INFO - Iter [9550/80000]	lr: 1.070e-04, eta: 6:46:24, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7469, decode.acc_seg: 72.9871, aux.loss_ce: 0.3736, aux.acc_seg: 68.6938, loss: 1.1206
2022-11-04 11:13:46,062 - mmseg - INFO - Iter [9600/80000]	lr: 1.070e-04, eta: 6:46:02, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7103, decode.acc_seg: 74.1039, aux.loss_ce: 0.3501, aux.acc_seg: 69.9063, loss: 1.0604
2022-11-04 11:14:02,850 - mmseg - INFO - Iter [9650/80000]	lr: 1.069e-04, eta: 6:45:41, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7273, decode.acc_seg: 73.6608, aux.loss_ce: 0.3652, aux.acc_seg: 69.3026, loss: 1.0925
2022-11-04 11:14:19,883 - mmseg - INFO - Iter [9700/80000]	lr: 1.068e-04, eta: 6:45:22, time: 0.341, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7268, decode.acc_seg: 73.4946, aux.loss_ce: 0.3558, aux.acc_seg: 69.4589, loss: 1.0826
2022-11-04 11:14:36,548 - mmseg - INFO - Iter [9750/80000]	lr: 1.068e-04, eta: 6:45:00, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7094, decode.acc_seg: 74.2885, aux.loss_ce: 0.3576, aux.acc_seg: 69.8041, loss: 1.0670
2022-11-04 11:14:53,472 - mmseg - INFO - Iter [9800/80000]	lr: 1.067e-04, eta: 6:44:40, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7200, decode.acc_seg: 74.0646, aux.loss_ce: 0.3574, aux.acc_seg: 69.8132, loss: 1.0774
2022-11-04 11:15:10,299 - mmseg - INFO - Iter [9850/80000]	lr: 1.066e-04, eta: 6:44:19, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7307, decode.acc_seg: 73.3086, aux.loss_ce: 0.3621, aux.acc_seg: 69.1767, loss: 1.0928
2022-11-04 11:15:26,925 - mmseg - INFO - Iter [9900/80000]	lr: 1.065e-04, eta: 6:43:57, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7348, decode.acc_seg: 73.4812, aux.loss_ce: 0.3632, aux.acc_seg: 69.2407, loss: 1.0980
2022-11-04 11:15:43,610 - mmseg - INFO - Iter [9950/80000]	lr: 1.065e-04, eta: 6:43:36, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7094, decode.acc_seg: 74.0700, aux.loss_ce: 0.3506, aux.acc_seg: 69.8301, loss: 1.0600
2022-11-04 11:16:00,409 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:16:00,409 - mmseg - INFO - Iter [10000/80000]	lr: 1.064e-04, eta: 6:43:15, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7613, decode.acc_seg: 72.2630, aux.loss_ce: 0.3792, aux.acc_seg: 67.5570, loss: 1.1405
2022-11-04 11:16:17,139 - mmseg - INFO - Iter [10050/80000]	lr: 1.063e-04, eta: 6:42:54, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7012, decode.acc_seg: 74.2420, aux.loss_ce: 0.3500, aux.acc_seg: 69.7617, loss: 1.0512
2022-11-04 11:16:36,477 - mmseg - INFO - Iter [10100/80000]	lr: 1.063e-04, eta: 6:42:51, time: 0.387, data_time: 0.062, memory: 12960, decode.loss_ce: 0.7166, decode.acc_seg: 73.8523, aux.loss_ce: 0.3553, aux.acc_seg: 69.2696, loss: 1.0719
2022-11-04 11:16:53,209 - mmseg - INFO - Iter [10150/80000]	lr: 1.062e-04, eta: 6:42:30, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7229, decode.acc_seg: 73.6082, aux.loss_ce: 0.3653, aux.acc_seg: 68.8742, loss: 1.0882
2022-11-04 11:17:10,128 - mmseg - INFO - Iter [10200/80000]	lr: 1.061e-04, eta: 6:42:10, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6895, decode.acc_seg: 75.1887, aux.loss_ce: 0.3505, aux.acc_seg: 70.0319, loss: 1.0399
2022-11-04 11:17:26,690 - mmseg - INFO - Iter [10250/80000]	lr: 1.061e-04, eta: 6:41:48, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7214, decode.acc_seg: 74.1035, aux.loss_ce: 0.3567, aux.acc_seg: 69.9367, loss: 1.0781
2022-11-04 11:17:43,460 - mmseg - INFO - Iter [10300/80000]	lr: 1.060e-04, eta: 6:41:27, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7116, decode.acc_seg: 73.8966, aux.loss_ce: 0.3564, aux.acc_seg: 69.3035, loss: 1.0680
2022-11-04 11:18:00,044 - mmseg - INFO - Iter [10350/80000]	lr: 1.059e-04, eta: 6:41:05, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7075, decode.acc_seg: 74.0589, aux.loss_ce: 0.3515, aux.acc_seg: 69.7433, loss: 1.0590
2022-11-04 11:18:16,983 - mmseg - INFO - Iter [10400/80000]	lr: 1.059e-04, eta: 6:40:46, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7027, decode.acc_seg: 74.4286, aux.loss_ce: 0.3526, aux.acc_seg: 69.7436, loss: 1.0553
2022-11-04 11:18:33,772 - mmseg - INFO - Iter [10450/80000]	lr: 1.058e-04, eta: 6:40:25, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7486, decode.acc_seg: 72.7669, aux.loss_ce: 0.3675, aux.acc_seg: 68.7405, loss: 1.1161
2022-11-04 11:18:50,555 - mmseg - INFO - Iter [10500/80000]	lr: 1.057e-04, eta: 6:40:05, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6875, decode.acc_seg: 74.4755, aux.loss_ce: 0.3403, aux.acc_seg: 70.3628, loss: 1.0278
2022-11-04 11:19:07,239 - mmseg - INFO - Iter [10550/80000]	lr: 1.057e-04, eta: 6:39:43, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7123, decode.acc_seg: 73.6845, aux.loss_ce: 0.3551, aux.acc_seg: 69.4141, loss: 1.0674
2022-11-04 11:19:23,873 - mmseg - INFO - Iter [10600/80000]	lr: 1.056e-04, eta: 6:39:22, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7002, decode.acc_seg: 74.3732, aux.loss_ce: 0.3486, aux.acc_seg: 70.0356, loss: 1.0488
2022-11-04 11:19:40,611 - mmseg - INFO - Iter [10650/80000]	lr: 1.055e-04, eta: 6:39:01, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7203, decode.acc_seg: 73.3071, aux.loss_ce: 0.3529, aux.acc_seg: 69.2473, loss: 1.0732
2022-11-04 11:19:57,248 - mmseg - INFO - Iter [10700/80000]	lr: 1.055e-04, eta: 6:38:40, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7273, decode.acc_seg: 73.7086, aux.loss_ce: 0.3583, aux.acc_seg: 69.4682, loss: 1.0856
2022-11-04 11:20:16,883 - mmseg - INFO - Iter [10750/80000]	lr: 1.054e-04, eta: 6:38:38, time: 0.393, data_time: 0.060, memory: 12960, decode.loss_ce: 0.7193, decode.acc_seg: 73.2284, aux.loss_ce: 0.3561, aux.acc_seg: 68.9367, loss: 1.0754
2022-11-04 11:20:33,976 - mmseg - INFO - Iter [10800/80000]	lr: 1.053e-04, eta: 6:38:20, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6770, decode.acc_seg: 75.1615, aux.loss_ce: 0.3385, aux.acc_seg: 70.6355, loss: 1.0154
2022-11-04 11:20:50,556 - mmseg - INFO - Iter [10850/80000]	lr: 1.052e-04, eta: 6:37:58, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6925, decode.acc_seg: 74.7034, aux.loss_ce: 0.3450, aux.acc_seg: 70.3465, loss: 1.0374
2022-11-04 11:21:07,383 - mmseg - INFO - Iter [10900/80000]	lr: 1.052e-04, eta: 6:37:38, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7223, decode.acc_seg: 73.7342, aux.loss_ce: 0.3642, aux.acc_seg: 69.0199, loss: 1.0865
2022-11-04 11:21:24,247 - mmseg - INFO - Iter [10950/80000]	lr: 1.051e-04, eta: 6:37:18, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6709, decode.acc_seg: 75.4051, aux.loss_ce: 0.3384, aux.acc_seg: 70.8098, loss: 1.0093
2022-11-04 11:21:41,028 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:21:41,029 - mmseg - INFO - Iter [11000/80000]	lr: 1.050e-04, eta: 6:36:58, time: 0.336, data_time: 0.010, memory: 12960, decode.loss_ce: 0.7074, decode.acc_seg: 74.1576, aux.loss_ce: 0.3557, aux.acc_seg: 69.6675, loss: 1.0631
2022-11-04 11:21:57,769 - mmseg - INFO - Iter [11050/80000]	lr: 1.050e-04, eta: 6:36:37, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6833, decode.acc_seg: 75.0016, aux.loss_ce: 0.3401, aux.acc_seg: 70.6092, loss: 1.0235
2022-11-04 11:22:14,587 - mmseg - INFO - Iter [11100/80000]	lr: 1.049e-04, eta: 6:36:17, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7138, decode.acc_seg: 73.7733, aux.loss_ce: 0.3598, aux.acc_seg: 69.2723, loss: 1.0736
2022-11-04 11:22:31,289 - mmseg - INFO - Iter [11150/80000]	lr: 1.048e-04, eta: 6:35:57, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6883, decode.acc_seg: 75.0564, aux.loss_ce: 0.3485, aux.acc_seg: 70.2169, loss: 1.0367
2022-11-04 11:22:48,229 - mmseg - INFO - Iter [11200/80000]	lr: 1.048e-04, eta: 6:35:38, time: 0.339, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6886, decode.acc_seg: 74.3749, aux.loss_ce: 0.3442, aux.acc_seg: 69.7821, loss: 1.0328
2022-11-04 11:23:05,194 - mmseg - INFO - Iter [11250/80000]	lr: 1.047e-04, eta: 6:35:18, time: 0.339, data_time: 0.008, memory: 12960, decode.loss_ce: 0.7046, decode.acc_seg: 73.5957, aux.loss_ce: 0.3488, aux.acc_seg: 69.4387, loss: 1.0534
2022-11-04 11:23:22,111 - mmseg - INFO - Iter [11300/80000]	lr: 1.046e-04, eta: 6:34:59, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7144, decode.acc_seg: 73.8775, aux.loss_ce: 0.3565, aux.acc_seg: 69.5059, loss: 1.0709
2022-11-04 11:23:38,854 - mmseg - INFO - Iter [11350/80000]	lr: 1.046e-04, eta: 6:34:39, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7233, decode.acc_seg: 73.8331, aux.loss_ce: 0.3593, aux.acc_seg: 69.5578, loss: 1.0826
2022-11-04 11:23:58,416 - mmseg - INFO - Iter [11400/80000]	lr: 1.045e-04, eta: 6:34:36, time: 0.391, data_time: 0.054, memory: 12960, decode.loss_ce: 0.6819, decode.acc_seg: 74.4126, aux.loss_ce: 0.3425, aux.acc_seg: 69.8810, loss: 1.0244
2022-11-04 11:24:15,241 - mmseg - INFO - Iter [11450/80000]	lr: 1.044e-04, eta: 6:34:16, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6935, decode.acc_seg: 74.4591, aux.loss_ce: 0.3495, aux.acc_seg: 69.5228, loss: 1.0429
2022-11-04 11:24:32,052 - mmseg - INFO - Iter [11500/80000]	lr: 1.044e-04, eta: 6:33:56, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6851, decode.acc_seg: 74.6403, aux.loss_ce: 0.3485, aux.acc_seg: 69.7618, loss: 1.0337
2022-11-04 11:24:48,608 - mmseg - INFO - Iter [11550/80000]	lr: 1.043e-04, eta: 6:33:34, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6952, decode.acc_seg: 74.2746, aux.loss_ce: 0.3522, aux.acc_seg: 69.6990, loss: 1.0474
2022-11-04 11:25:05,336 - mmseg - INFO - Iter [11600/80000]	lr: 1.042e-04, eta: 6:33:14, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7000, decode.acc_seg: 74.3434, aux.loss_ce: 0.3498, aux.acc_seg: 70.1897, loss: 1.0498
2022-11-04 11:25:22,327 - mmseg - INFO - Iter [11650/80000]	lr: 1.042e-04, eta: 6:32:55, time: 0.340, data_time: 0.010, memory: 12960, decode.loss_ce: 0.7058, decode.acc_seg: 74.6502, aux.loss_ce: 0.3538, aux.acc_seg: 70.0706, loss: 1.0595
2022-11-04 11:25:39,013 - mmseg - INFO - Iter [11700/80000]	lr: 1.041e-04, eta: 6:32:35, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6910, decode.acc_seg: 74.6663, aux.loss_ce: 0.3461, aux.acc_seg: 69.8832, loss: 1.0371
2022-11-04 11:25:55,864 - mmseg - INFO - Iter [11750/80000]	lr: 1.040e-04, eta: 6:32:15, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7003, decode.acc_seg: 74.0739, aux.loss_ce: 0.3431, aux.acc_seg: 70.1701, loss: 1.0434
2022-11-04 11:26:12,568 - mmseg - INFO - Iter [11800/80000]	lr: 1.039e-04, eta: 6:31:55, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6944, decode.acc_seg: 74.5003, aux.loss_ce: 0.3483, aux.acc_seg: 70.2115, loss: 1.0427
2022-11-04 11:26:29,442 - mmseg - INFO - Iter [11850/80000]	lr: 1.039e-04, eta: 6:31:36, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6995, decode.acc_seg: 74.4181, aux.loss_ce: 0.3498, aux.acc_seg: 69.7255, loss: 1.0493
2022-11-04 11:26:46,273 - mmseg - INFO - Iter [11900/80000]	lr: 1.038e-04, eta: 6:31:16, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6844, decode.acc_seg: 74.8505, aux.loss_ce: 0.3346, aux.acc_seg: 70.9719, loss: 1.0190
2022-11-04 11:27:02,763 - mmseg - INFO - Iter [11950/80000]	lr: 1.037e-04, eta: 6:30:55, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6847, decode.acc_seg: 75.0053, aux.loss_ce: 0.3419, aux.acc_seg: 70.4889, loss: 1.0267
2022-11-04 11:27:22,724 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:27:22,725 - mmseg - INFO - Iter [12000/80000]	lr: 1.037e-04, eta: 6:30:53, time: 0.399, data_time: 0.058, memory: 12960, decode.loss_ce: 0.6802, decode.acc_seg: 74.3703, aux.loss_ce: 0.3441, aux.acc_seg: 69.8030, loss: 1.0244
2022-11-04 11:27:39,430 - mmseg - INFO - Iter [12050/80000]	lr: 1.036e-04, eta: 6:30:32, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6534, decode.acc_seg: 75.5934, aux.loss_ce: 0.3316, aux.acc_seg: 70.8373, loss: 0.9850
2022-11-04 11:27:55,954 - mmseg - INFO - Iter [12100/80000]	lr: 1.035e-04, eta: 6:30:11, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6652, decode.acc_seg: 75.1046, aux.loss_ce: 0.3381, aux.acc_seg: 70.4533, loss: 1.0033
2022-11-04 11:28:12,756 - mmseg - INFO - Iter [12150/80000]	lr: 1.035e-04, eta: 6:29:52, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6652, decode.acc_seg: 75.5102, aux.loss_ce: 0.3372, aux.acc_seg: 71.2351, loss: 1.0024
2022-11-04 11:28:29,576 - mmseg - INFO - Iter [12200/80000]	lr: 1.034e-04, eta: 6:29:32, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6708, decode.acc_seg: 75.1766, aux.loss_ce: 0.3374, aux.acc_seg: 70.7603, loss: 1.0082
2022-11-04 11:28:46,438 - mmseg - INFO - Iter [12250/80000]	lr: 1.033e-04, eta: 6:29:13, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6889, decode.acc_seg: 74.9539, aux.loss_ce: 0.3461, aux.acc_seg: 70.0865, loss: 1.0349
2022-11-04 11:29:03,079 - mmseg - INFO - Iter [12300/80000]	lr: 1.033e-04, eta: 6:28:52, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6859, decode.acc_seg: 75.0783, aux.loss_ce: 0.3466, aux.acc_seg: 70.4058, loss: 1.0325
2022-11-04 11:29:19,784 - mmseg - INFO - Iter [12350/80000]	lr: 1.032e-04, eta: 6:28:32, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6822, decode.acc_seg: 74.8919, aux.loss_ce: 0.3441, aux.acc_seg: 70.2727, loss: 1.0263
2022-11-04 11:29:36,416 - mmseg - INFO - Iter [12400/80000]	lr: 1.031e-04, eta: 6:28:12, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6607, decode.acc_seg: 75.4752, aux.loss_ce: 0.3342, aux.acc_seg: 70.9951, loss: 0.9949
2022-11-04 11:29:53,239 - mmseg - INFO - Iter [12450/80000]	lr: 1.031e-04, eta: 6:27:52, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7073, decode.acc_seg: 73.9701, aux.loss_ce: 0.3520, aux.acc_seg: 69.6578, loss: 1.0593
2022-11-04 11:30:10,063 - mmseg - INFO - Iter [12500/80000]	lr: 1.030e-04, eta: 6:27:33, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.7088, decode.acc_seg: 74.3025, aux.loss_ce: 0.3571, aux.acc_seg: 69.4186, loss: 1.0660
2022-11-04 11:30:26,951 - mmseg - INFO - Iter [12550/80000]	lr: 1.029e-04, eta: 6:27:14, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6765, decode.acc_seg: 75.0632, aux.loss_ce: 0.3405, aux.acc_seg: 70.4189, loss: 1.0170
2022-11-04 11:30:43,542 - mmseg - INFO - Iter [12600/80000]	lr: 1.028e-04, eta: 6:26:53, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6770, decode.acc_seg: 74.7901, aux.loss_ce: 0.3417, aux.acc_seg: 70.1427, loss: 1.0187
2022-11-04 11:31:03,213 - mmseg - INFO - Iter [12650/80000]	lr: 1.028e-04, eta: 6:26:49, time: 0.393, data_time: 0.063, memory: 12960, decode.loss_ce: 0.6857, decode.acc_seg: 74.9738, aux.loss_ce: 0.3507, aux.acc_seg: 70.0959, loss: 1.0365
2022-11-04 11:31:19,879 - mmseg - INFO - Iter [12700/80000]	lr: 1.027e-04, eta: 6:26:29, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6854, decode.acc_seg: 74.9739, aux.loss_ce: 0.3464, aux.acc_seg: 70.3880, loss: 1.0318
2022-11-04 11:31:36,572 - mmseg - INFO - Iter [12750/80000]	lr: 1.026e-04, eta: 6:26:09, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6797, decode.acc_seg: 74.7485, aux.loss_ce: 0.3382, aux.acc_seg: 70.4576, loss: 1.0179
2022-11-04 11:31:53,202 - mmseg - INFO - Iter [12800/80000]	lr: 1.026e-04, eta: 6:25:48, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6612, decode.acc_seg: 75.0975, aux.loss_ce: 0.3344, aux.acc_seg: 70.5359, loss: 0.9956
2022-11-04 11:32:09,893 - mmseg - INFO - Iter [12850/80000]	lr: 1.025e-04, eta: 6:25:28, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6537, decode.acc_seg: 75.2394, aux.loss_ce: 0.3306, aux.acc_seg: 70.8436, loss: 0.9843
2022-11-04 11:32:26,885 - mmseg - INFO - Iter [12900/80000]	lr: 1.024e-04, eta: 6:25:10, time: 0.340, data_time: 0.010, memory: 12960, decode.loss_ce: 0.6738, decode.acc_seg: 75.3159, aux.loss_ce: 0.3410, aux.acc_seg: 70.8079, loss: 1.0149
2022-11-04 11:32:43,848 - mmseg - INFO - Iter [12950/80000]	lr: 1.024e-04, eta: 6:24:51, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6812, decode.acc_seg: 75.0370, aux.loss_ce: 0.3364, aux.acc_seg: 71.0354, loss: 1.0176
2022-11-04 11:33:00,460 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:33:00,461 - mmseg - INFO - Iter [13000/80000]	lr: 1.023e-04, eta: 6:24:31, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6899, decode.acc_seg: 74.7237, aux.loss_ce: 0.3444, aux.acc_seg: 70.1558, loss: 1.0344
2022-11-04 11:33:17,154 - mmseg - INFO - Iter [13050/80000]	lr: 1.022e-04, eta: 6:24:11, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6887, decode.acc_seg: 74.2631, aux.loss_ce: 0.3469, aux.acc_seg: 69.8023, loss: 1.0356
2022-11-04 11:33:33,929 - mmseg - INFO - Iter [13100/80000]	lr: 1.022e-04, eta: 6:23:52, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6801, decode.acc_seg: 74.8458, aux.loss_ce: 0.3404, aux.acc_seg: 70.5461, loss: 1.0205
2022-11-04 11:33:51,533 - mmseg - INFO - Iter [13150/80000]	lr: 1.021e-04, eta: 6:23:36, time: 0.352, data_time: 0.026, memory: 12960, decode.loss_ce: 0.6913, decode.acc_seg: 74.6824, aux.loss_ce: 0.3464, aux.acc_seg: 70.3946, loss: 1.0377
2022-11-04 11:34:08,309 - mmseg - INFO - Iter [13200/80000]	lr: 1.020e-04, eta: 6:23:17, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6902, decode.acc_seg: 74.2207, aux.loss_ce: 0.3462, aux.acc_seg: 69.6223, loss: 1.0364
2022-11-04 11:34:24,811 - mmseg - INFO - Iter [13250/80000]	lr: 1.020e-04, eta: 6:22:56, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6690, decode.acc_seg: 75.1732, aux.loss_ce: 0.3346, aux.acc_seg: 70.8762, loss: 1.0037
2022-11-04 11:34:44,950 - mmseg - INFO - Iter [13300/80000]	lr: 1.019e-04, eta: 6:22:54, time: 0.403, data_time: 0.062, memory: 12960, decode.loss_ce: 0.6684, decode.acc_seg: 74.9730, aux.loss_ce: 0.3401, aux.acc_seg: 70.5655, loss: 1.0085
2022-11-04 11:35:01,654 - mmseg - INFO - Iter [13350/80000]	lr: 1.018e-04, eta: 6:22:34, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6473, decode.acc_seg: 76.2183, aux.loss_ce: 0.3285, aux.acc_seg: 71.5754, loss: 0.9758
2022-11-04 11:35:18,279 - mmseg - INFO - Iter [13400/80000]	lr: 1.017e-04, eta: 6:22:14, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6749, decode.acc_seg: 75.4301, aux.loss_ce: 0.3438, aux.acc_seg: 70.6723, loss: 1.0188
2022-11-04 11:35:34,973 - mmseg - INFO - Iter [13450/80000]	lr: 1.017e-04, eta: 6:21:54, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6386, decode.acc_seg: 76.2364, aux.loss_ce: 0.3260, aux.acc_seg: 71.5250, loss: 0.9646
2022-11-04 11:35:51,613 - mmseg - INFO - Iter [13500/80000]	lr: 1.016e-04, eta: 6:21:34, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6681, decode.acc_seg: 75.2066, aux.loss_ce: 0.3376, aux.acc_seg: 70.5809, loss: 1.0057
2022-11-04 11:36:08,486 - mmseg - INFO - Iter [13550/80000]	lr: 1.015e-04, eta: 6:21:15, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6594, decode.acc_seg: 75.6105, aux.loss_ce: 0.3306, aux.acc_seg: 71.5691, loss: 0.9900
2022-11-04 11:36:24,958 - mmseg - INFO - Iter [13600/80000]	lr: 1.015e-04, eta: 6:20:54, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6667, decode.acc_seg: 75.3636, aux.loss_ce: 0.3384, aux.acc_seg: 71.2173, loss: 1.0051
2022-11-04 11:36:41,606 - mmseg - INFO - Iter [13650/80000]	lr: 1.014e-04, eta: 6:20:34, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6524, decode.acc_seg: 75.5936, aux.loss_ce: 0.3312, aux.acc_seg: 70.9761, loss: 0.9836
2022-11-04 11:36:58,252 - mmseg - INFO - Iter [13700/80000]	lr: 1.013e-04, eta: 6:20:14, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6617, decode.acc_seg: 75.6889, aux.loss_ce: 0.3321, aux.acc_seg: 71.1060, loss: 0.9938
2022-11-04 11:37:14,942 - mmseg - INFO - Iter [13750/80000]	lr: 1.013e-04, eta: 6:19:54, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6748, decode.acc_seg: 75.2188, aux.loss_ce: 0.3503, aux.acc_seg: 69.7090, loss: 1.0251
2022-11-04 11:37:31,653 - mmseg - INFO - Iter [13800/80000]	lr: 1.012e-04, eta: 6:19:35, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6555, decode.acc_seg: 75.3173, aux.loss_ce: 0.3267, aux.acc_seg: 71.1834, loss: 0.9822
2022-11-04 11:37:48,340 - mmseg - INFO - Iter [13850/80000]	lr: 1.011e-04, eta: 6:19:15, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6741, decode.acc_seg: 74.6626, aux.loss_ce: 0.3392, aux.acc_seg: 69.7654, loss: 1.0133
2022-11-04 11:38:07,763 - mmseg - INFO - Iter [13900/80000]	lr: 1.011e-04, eta: 6:19:09, time: 0.388, data_time: 0.065, memory: 12960, decode.loss_ce: 0.6495, decode.acc_seg: 75.9806, aux.loss_ce: 0.3359, aux.acc_seg: 70.7708, loss: 0.9854
2022-11-04 11:38:24,223 - mmseg - INFO - Iter [13950/80000]	lr: 1.010e-04, eta: 6:18:48, time: 0.329, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6647, decode.acc_seg: 75.2318, aux.loss_ce: 0.3449, aux.acc_seg: 70.1441, loss: 1.0095
2022-11-04 11:38:41,400 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:38:41,401 - mmseg - INFO - Iter [14000/80000]	lr: 1.009e-04, eta: 6:18:30, time: 0.343, data_time: 0.018, memory: 12960, decode.loss_ce: 0.6620, decode.acc_seg: 75.6150, aux.loss_ce: 0.3357, aux.acc_seg: 70.8551, loss: 0.9977
2022-11-04 11:38:58,176 - mmseg - INFO - Iter [14050/80000]	lr: 1.009e-04, eta: 6:18:11, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6284, decode.acc_seg: 76.6543, aux.loss_ce: 0.3217, aux.acc_seg: 71.7495, loss: 0.9501
2022-11-04 11:39:14,894 - mmseg - INFO - Iter [14100/80000]	lr: 1.008e-04, eta: 6:17:52, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6765, decode.acc_seg: 75.0924, aux.loss_ce: 0.3371, aux.acc_seg: 70.6258, loss: 1.0136
2022-11-04 11:39:31,517 - mmseg - INFO - Iter [14150/80000]	lr: 1.007e-04, eta: 6:17:32, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6434, decode.acc_seg: 76.1303, aux.loss_ce: 0.3284, aux.acc_seg: 71.3130, loss: 0.9718
2022-11-04 11:39:48,276 - mmseg - INFO - Iter [14200/80000]	lr: 1.006e-04, eta: 6:17:13, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6636, decode.acc_seg: 75.4400, aux.loss_ce: 0.3365, aux.acc_seg: 70.4850, loss: 1.0001
2022-11-04 11:40:04,931 - mmseg - INFO - Iter [14250/80000]	lr: 1.006e-04, eta: 6:16:53, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6639, decode.acc_seg: 75.3210, aux.loss_ce: 0.3386, aux.acc_seg: 70.3094, loss: 1.0025
2022-11-04 11:40:21,601 - mmseg - INFO - Iter [14300/80000]	lr: 1.005e-04, eta: 6:16:33, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6508, decode.acc_seg: 75.4751, aux.loss_ce: 0.3282, aux.acc_seg: 70.8696, loss: 0.9789
2022-11-04 11:40:38,319 - mmseg - INFO - Iter [14350/80000]	lr: 1.004e-04, eta: 6:16:14, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6423, decode.acc_seg: 76.1882, aux.loss_ce: 0.3278, aux.acc_seg: 71.1367, loss: 0.9702
2022-11-04 11:40:55,112 - mmseg - INFO - Iter [14400/80000]	lr: 1.004e-04, eta: 6:15:55, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6840, decode.acc_seg: 74.8263, aux.loss_ce: 0.3436, aux.acc_seg: 70.2487, loss: 1.0276
2022-11-04 11:41:11,787 - mmseg - INFO - Iter [14450/80000]	lr: 1.003e-04, eta: 6:15:35, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6676, decode.acc_seg: 75.2086, aux.loss_ce: 0.3395, aux.acc_seg: 70.4966, loss: 1.0070
2022-11-04 11:41:28,500 - mmseg - INFO - Iter [14500/80000]	lr: 1.002e-04, eta: 6:15:16, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6744, decode.acc_seg: 75.1524, aux.loss_ce: 0.3399, aux.acc_seg: 70.2439, loss: 1.0143
2022-11-04 11:41:48,181 - mmseg - INFO - Iter [14550/80000]	lr: 1.002e-04, eta: 6:15:10, time: 0.394, data_time: 0.062, memory: 12960, decode.loss_ce: 0.6834, decode.acc_seg: 74.8680, aux.loss_ce: 0.3467, aux.acc_seg: 69.8942, loss: 1.0301
2022-11-04 11:42:04,878 - mmseg - INFO - Iter [14600/80000]	lr: 1.001e-04, eta: 6:14:51, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6481, decode.acc_seg: 75.7498, aux.loss_ce: 0.3348, aux.acc_seg: 70.6590, loss: 0.9830
2022-11-04 11:42:21,583 - mmseg - INFO - Iter [14650/80000]	lr: 1.000e-04, eta: 6:14:31, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6558, decode.acc_seg: 75.3816, aux.loss_ce: 0.3403, aux.acc_seg: 70.2434, loss: 0.9961
2022-11-04 11:42:37,956 - mmseg - INFO - Iter [14700/80000]	lr: 9.996e-05, eta: 6:14:10, time: 0.327, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6496, decode.acc_seg: 76.1960, aux.loss_ce: 0.3287, aux.acc_seg: 71.5170, loss: 0.9783
2022-11-04 11:42:54,446 - mmseg - INFO - Iter [14750/80000]	lr: 9.989e-05, eta: 6:13:50, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6381, decode.acc_seg: 76.1586, aux.loss_ce: 0.3255, aux.acc_seg: 71.2938, loss: 0.9636
2022-11-04 11:43:11,301 - mmseg - INFO - Iter [14800/80000]	lr: 9.982e-05, eta: 6:13:31, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6459, decode.acc_seg: 76.3840, aux.loss_ce: 0.3326, aux.acc_seg: 71.6435, loss: 0.9785
2022-11-04 11:43:27,955 - mmseg - INFO - Iter [14850/80000]	lr: 9.975e-05, eta: 6:13:12, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6421, decode.acc_seg: 75.9410, aux.loss_ce: 0.3286, aux.acc_seg: 71.0030, loss: 0.9707
2022-11-04 11:43:44,604 - mmseg - INFO - Iter [14900/80000]	lr: 9.968e-05, eta: 6:12:52, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6355, decode.acc_seg: 76.0161, aux.loss_ce: 0.3228, aux.acc_seg: 71.4296, loss: 0.9583
2022-11-04 11:44:01,334 - mmseg - INFO - Iter [14950/80000]	lr: 9.962e-05, eta: 6:12:33, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6308, decode.acc_seg: 76.7439, aux.loss_ce: 0.3253, aux.acc_seg: 71.6569, loss: 0.9561
2022-11-04 11:44:17,812 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:44:17,812 - mmseg - INFO - Iter [15000/80000]	lr: 9.955e-05, eta: 6:12:13, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6704, decode.acc_seg: 75.1293, aux.loss_ce: 0.3389, aux.acc_seg: 70.7121, loss: 1.0093
2022-11-04 11:44:34,308 - mmseg - INFO - Iter [15050/80000]	lr: 9.948e-05, eta: 6:11:53, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6369, decode.acc_seg: 76.3859, aux.loss_ce: 0.3278, aux.acc_seg: 71.3601, loss: 0.9647
2022-11-04 11:44:51,192 - mmseg - INFO - Iter [15100/80000]	lr: 9.941e-05, eta: 6:11:34, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6631, decode.acc_seg: 75.4633, aux.loss_ce: 0.3337, aux.acc_seg: 70.6228, loss: 0.9968
2022-11-04 11:45:10,992 - mmseg - INFO - Iter [15150/80000]	lr: 9.934e-05, eta: 6:11:28, time: 0.396, data_time: 0.061, memory: 12960, decode.loss_ce: 0.6558, decode.acc_seg: 76.0604, aux.loss_ce: 0.3397, aux.acc_seg: 71.0205, loss: 0.9955
2022-11-04 11:45:27,694 - mmseg - INFO - Iter [15200/80000]	lr: 9.927e-05, eta: 6:11:09, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6359, decode.acc_seg: 76.3343, aux.loss_ce: 0.3275, aux.acc_seg: 71.5941, loss: 0.9634
2022-11-04 11:45:44,357 - mmseg - INFO - Iter [15250/80000]	lr: 9.920e-05, eta: 6:10:50, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6410, decode.acc_seg: 76.4234, aux.loss_ce: 0.3243, aux.acc_seg: 72.2086, loss: 0.9653
2022-11-04 11:46:01,144 - mmseg - INFO - Iter [15300/80000]	lr: 9.913e-05, eta: 6:10:31, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6622, decode.acc_seg: 75.2324, aux.loss_ce: 0.3361, aux.acc_seg: 70.6717, loss: 0.9984
2022-11-04 11:46:17,752 - mmseg - INFO - Iter [15350/80000]	lr: 9.906e-05, eta: 6:10:11, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6316, decode.acc_seg: 76.3566, aux.loss_ce: 0.3223, aux.acc_seg: 71.8906, loss: 0.9538
2022-11-04 11:46:34,569 - mmseg - INFO - Iter [15400/80000]	lr: 9.900e-05, eta: 6:09:53, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6293, decode.acc_seg: 76.3557, aux.loss_ce: 0.3202, aux.acc_seg: 71.5494, loss: 0.9494
2022-11-04 11:46:50,989 - mmseg - INFO - Iter [15450/80000]	lr: 9.893e-05, eta: 6:09:32, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6418, decode.acc_seg: 75.9974, aux.loss_ce: 0.3318, aux.acc_seg: 71.0126, loss: 0.9736
2022-11-04 11:47:07,550 - mmseg - INFO - Iter [15500/80000]	lr: 9.886e-05, eta: 6:09:13, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6371, decode.acc_seg: 76.3339, aux.loss_ce: 0.3310, aux.acc_seg: 71.3392, loss: 0.9680
2022-11-04 11:47:24,374 - mmseg - INFO - Iter [15550/80000]	lr: 9.879e-05, eta: 6:08:54, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6418, decode.acc_seg: 76.1689, aux.loss_ce: 0.3288, aux.acc_seg: 71.3254, loss: 0.9706
2022-11-04 11:47:41,331 - mmseg - INFO - Iter [15600/80000]	lr: 9.872e-05, eta: 6:08:36, time: 0.339, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6368, decode.acc_seg: 75.9689, aux.loss_ce: 0.3228, aux.acc_seg: 71.1297, loss: 0.9596
2022-11-04 11:47:58,132 - mmseg - INFO - Iter [15650/80000]	lr: 9.865e-05, eta: 6:08:17, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6636, decode.acc_seg: 75.2083, aux.loss_ce: 0.3414, aux.acc_seg: 70.2553, loss: 1.0051
2022-11-04 11:48:14,848 - mmseg - INFO - Iter [15700/80000]	lr: 9.858e-05, eta: 6:07:58, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6367, decode.acc_seg: 76.0649, aux.loss_ce: 0.3236, aux.acc_seg: 71.6139, loss: 0.9603
2022-11-04 11:48:31,521 - mmseg - INFO - Iter [15750/80000]	lr: 9.851e-05, eta: 6:07:39, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6621, decode.acc_seg: 75.7398, aux.loss_ce: 0.3306, aux.acc_seg: 71.1028, loss: 0.9926
2022-11-04 11:48:51,131 - mmseg - INFO - Iter [15800/80000]	lr: 9.844e-05, eta: 6:07:32, time: 0.392, data_time: 0.068, memory: 12960, decode.loss_ce: 0.6373, decode.acc_seg: 76.2204, aux.loss_ce: 0.3299, aux.acc_seg: 71.3964, loss: 0.9672
2022-11-04 11:49:08,265 - mmseg - INFO - Iter [15850/80000]	lr: 9.837e-05, eta: 6:07:14, time: 0.343, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6392, decode.acc_seg: 75.9726, aux.loss_ce: 0.3263, aux.acc_seg: 71.2281, loss: 0.9654
2022-11-04 11:49:24,858 - mmseg - INFO - Iter [15900/80000]	lr: 9.831e-05, eta: 6:06:55, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6543, decode.acc_seg: 75.6311, aux.loss_ce: 0.3326, aux.acc_seg: 71.0978, loss: 0.9869
2022-11-04 11:49:41,733 - mmseg - INFO - Iter [15950/80000]	lr: 9.824e-05, eta: 6:06:37, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6297, decode.acc_seg: 76.4009, aux.loss_ce: 0.3234, aux.acc_seg: 71.1961, loss: 0.9531
2022-11-04 11:49:58,261 - mmseg - INFO - Saving checkpoint at 16000 iterations
2022-11-04 11:49:58,539 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:49:58,539 - mmseg - INFO - Iter [16000/80000]	lr: 9.817e-05, eta: 6:06:18, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6488, decode.acc_seg: 76.1287, aux.loss_ce: 0.3342, aux.acc_seg: 71.2101, loss: 0.9830
2022-11-04 11:50:07,441 - mmseg - INFO - per class results:
2022-11-04 11:50:07,448 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 64.49 | 80.09 |
|       building      | 74.24 | 88.23 |
|         sky         | 88.24 | 93.06 |
|        floor        | 69.71 | 83.01 |
|         tree        | 65.23 | 82.74 |
|       ceiling       | 74.69 | 85.77 |
|         road        | 72.52 | 87.28 |
|         bed         | 72.29 | 88.59 |
|      windowpane     | 48.92 |  69.4 |
|        grass        | 60.69 |  77.0 |
|       cabinet       | 44.95 | 63.33 |
|       sidewalk      | 47.27 | 60.06 |
|        person       | 63.57 | 81.46 |
|        earth        | 25.77 | 32.39 |
|         door        | 22.17 | 34.43 |
|        table        | 38.69 | 57.31 |
|       mountain      | 55.37 | 76.89 |
|        plant        | 41.13 | 52.07 |
|       curtain       | 53.55 | 74.13 |
|        chair        | 35.55 | 53.54 |
|         car         |  65.7 | 85.42 |
|        water        | 40.35 | 57.91 |
|       painting      | 53.38 | 71.07 |
|         sofa        | 47.19 | 70.67 |
|        shelf        | 32.93 | 50.74 |
|        house        | 45.73 | 65.41 |
|         sea         | 38.55 | 70.62 |
|        mirror       | 36.31 | 45.94 |
|         rug         | 42.62 | 52.14 |
|        field        | 24.07 |  42.0 |
|       armchair      | 23.62 |  33.0 |
|         seat        | 45.12 | 71.67 |
|        fence        | 23.82 | 40.25 |
|         desk        | 29.16 | 52.71 |
|         rock        | 39.08 | 69.24 |
|       wardrobe      | 34.77 |  56.4 |
|         lamp        | 33.55 | 45.68 |
|       bathtub       | 49.31 | 65.37 |
|       railing       | 27.33 | 34.56 |
|       cushion       | 29.41 | 43.36 |
|         base        | 14.71 | 23.56 |
|         box         | 13.25 | 19.31 |
|        column       | 26.43 | 34.85 |
|      signboard      | 22.13 | 27.84 |
|   chest of drawers  | 23.07 | 37.64 |
|       counter       | 18.14 | 21.68 |
|         sand        | 17.07 | 24.21 |
|         sink        | 40.11 | 51.59 |
|      skyscraper     | 52.84 | 83.57 |
|      fireplace      | 52.85 | 68.87 |
|     refrigerator    | 42.23 | 55.02 |
|      grandstand     | 34.23 | 64.26 |
|         path        |  7.27 |  9.85 |
|        stairs       | 25.36 | 29.34 |
|        runway       | 70.72 | 88.45 |
|         case        | 46.52 | 63.87 |
|      pool table     | 77.97 | 89.46 |
|        pillow       | 30.21 | 35.07 |
|     screen door     | 46.35 | 52.67 |
|       stairway      | 24.84 | 30.57 |
|        river        | 13.16 | 23.23 |
|        bridge       | 44.28 | 58.97 |
|       bookcase      |  24.2 | 38.78 |
|        blind        | 19.98 | 24.04 |
|     coffee table    | 37.67 | 69.23 |
|        toilet       | 60.25 | 75.82 |
|        flower       | 22.27 | 38.31 |
|         book        | 36.43 | 54.32 |
|         hill        |  3.09 |  3.28 |
|        bench        | 27.14 | 38.18 |
|      countertop     | 42.53 |  55.6 |
|        stove        | 43.96 | 61.97 |
|         palm        | 32.14 | 44.54 |
|    kitchen island   | 15.85 |  31.5 |
|       computer      | 40.07 | 59.22 |
|     swivel chair    | 28.73 | 41.37 |
|         boat        | 48.35 | 70.85 |
|         bar         | 29.22 | 33.15 |
|    arcade machine   | 56.47 | 63.31 |
|        hovel        | 42.07 |  54.9 |
|         bus         |  64.4 | 78.22 |
|        towel        | 32.55 | 44.97 |
|        light        |  6.63 |  6.93 |
|        truck        |  7.33 |  9.04 |
|        tower        |  32.3 | 38.31 |
|      chandelier     | 42.22 | 63.97 |
|        awning       |  9.88 | 10.79 |
|     streetlight     |  3.44 |  3.98 |
|        booth        | 22.94 | 27.48 |
| television receiver | 34.86 | 63.72 |
|       airplane      | 29.56 | 59.05 |
|      dirt track     |  8.59 | 13.77 |
|       apparel       | 11.02 | 14.72 |
|         pole        |  5.6  |  7.8  |
|         land        |  5.83 | 11.99 |
|      bannister      |  0.19 |  0.22 |
|      escalator      | 35.58 | 44.06 |
|       ottoman       | 12.99 | 15.01 |
|        bottle       |  3.83 |  4.14 |
|        buffet       | 19.05 | 20.29 |
|        poster       |  6.79 |  7.01 |
|        stage        |  8.42 | 13.68 |
|         van         |  8.32 | 10.08 |
|         ship        | 35.71 | 39.42 |
|       fountain      |  3.13 |  3.24 |
|    conveyer belt    | 42.05 |  66.5 |
|        canopy       | 35.46 |  48.3 |
|        washer       | 33.96 |  39.0 |
|      plaything      |  4.41 |  6.22 |
|    swimming pool    | 35.34 | 65.98 |
|        stool        |  5.11 |  6.29 |
|        barrel       | 18.22 | 63.34 |
|        basket       |  7.72 |  9.18 |
|      waterfall      | 47.75 | 72.99 |
|         tent        | 86.73 | 95.37 |
|         bag         |  1.08 |  1.1  |
|       minibike      | 29.84 | 35.42 |
|        cradle       | 51.57 | 78.88 |
|         oven        | 12.07 | 14.18 |
|         ball        |  0.0  |  0.0  |
|         food        | 47.32 | 58.39 |
|         step        |  0.01 |  0.01 |
|         tank        | 23.88 | 26.07 |
|      trade name     | 13.04 | 13.57 |
|      microwave      | 21.34 | 25.81 |
|         pot         | 14.24 |  16.0 |
|        animal       | 41.36 | 45.21 |
|       bicycle       | 34.17 | 52.66 |
|         lake        |  0.0  |  0.0  |
|      dishwasher     |  3.78 |  3.79 |
|        screen       | 47.98 |  70.6 |
|       blanket       |  0.0  |  0.0  |
|      sculpture      | 23.24 | 32.99 |
|         hood        | 23.51 | 30.16 |
|        sconce       |  6.22 |  6.4  |
|         vase        | 13.54 | 19.86 |
|    traffic light    |  7.35 |  8.6  |
|         tray        |  0.55 |  0.63 |
|        ashcan       | 15.92 | 17.37 |
|         fan         | 17.48 | 19.74 |
|         pier        | 26.25 | 31.62 |
|      crt screen     |  0.0  |  0.0  |
|        plate        | 26.92 | 33.04 |
|       monitor       |  49.6 | 71.46 |
|    bulletin board   |  28.2 | 31.99 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 22.73 | 24.84 |
|        glass        |  0.0  |  0.0  |
|        clock        |  3.43 |  3.6  |
|         flag        |  6.92 |  7.0  |
+---------------------+-------+-------+
2022-11-04 11:50:07,449 - mmseg - INFO - Summary:
2022-11-04 11:50:07,449 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 73.73 | 30.78 | 41.75 |
+-------+-------+-------+
2022-11-04 11:50:07,450 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:50:07,450 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7373, mIoU: 0.3078, mAcc: 0.4175, IoU.wall: 0.6449, IoU.building: 0.7424, IoU.sky: 0.8824, IoU.floor: 0.6971, IoU.tree: 0.6523, IoU.ceiling: 0.7469, IoU.road: 0.7252, IoU.bed : 0.7229, IoU.windowpane: 0.4892, IoU.grass: 0.6069, IoU.cabinet: 0.4495, IoU.sidewalk: 0.4727, IoU.person: 0.6357, IoU.earth: 0.2577, IoU.door: 0.2217, IoU.table: 0.3869, IoU.mountain: 0.5537, IoU.plant: 0.4113, IoU.curtain: 0.5355, IoU.chair: 0.3555, IoU.car: 0.6570, IoU.water: 0.4035, IoU.painting: 0.5338, IoU.sofa: 0.4719, IoU.shelf: 0.3293, IoU.house: 0.4573, IoU.sea: 0.3855, IoU.mirror: 0.3631, IoU.rug: 0.4262, IoU.field: 0.2407, IoU.armchair: 0.2362, IoU.seat: 0.4512, IoU.fence: 0.2382, IoU.desk: 0.2916, IoU.rock: 0.3908, IoU.wardrobe: 0.3477, IoU.lamp: 0.3355, IoU.bathtub: 0.4931, IoU.railing: 0.2733, IoU.cushion: 0.2941, IoU.base: 0.1471, IoU.box: 0.1325, IoU.column: 0.2643, IoU.signboard: 0.2213, IoU.chest of drawers: 0.2307, IoU.counter: 0.1814, IoU.sand: 0.1707, IoU.sink: 0.4011, IoU.skyscraper: 0.5284, IoU.fireplace: 0.5285, IoU.refrigerator: 0.4223, IoU.grandstand: 0.3423, IoU.path: 0.0727, IoU.stairs: 0.2536, IoU.runway: 0.7072, IoU.case: 0.4652, IoU.pool table: 0.7797, IoU.pillow: 0.3021, IoU.screen door: 0.4635, IoU.stairway: 0.2484, IoU.river: 0.1316, IoU.bridge: 0.4428, IoU.bookcase: 0.2420, IoU.blind: 0.1998, IoU.coffee table: 0.3767, IoU.toilet: 0.6025, IoU.flower: 0.2227, IoU.book: 0.3643, IoU.hill: 0.0309, IoU.bench: 0.2714, IoU.countertop: 0.4253, IoU.stove: 0.4396, IoU.palm: 0.3214, IoU.kitchen island: 0.1585, IoU.computer: 0.4007, IoU.swivel chair: 0.2873, IoU.boat: 0.4835, IoU.bar: 0.2922, IoU.arcade machine: 0.5647, IoU.hovel: 0.4207, IoU.bus: 0.6440, IoU.towel: 0.3255, IoU.light: 0.0663, IoU.truck: 0.0733, IoU.tower: 0.3230, IoU.chandelier: 0.4222, IoU.awning: 0.0988, IoU.streetlight: 0.0344, IoU.booth: 0.2294, IoU.television receiver: 0.3486, IoU.airplane: 0.2956, IoU.dirt track: 0.0859, IoU.apparel: 0.1102, IoU.pole: 0.0560, IoU.land: 0.0583, IoU.bannister: 0.0019, IoU.escalator: 0.3558, IoU.ottoman: 0.1299, IoU.bottle: 0.0383, IoU.buffet: 0.1905, IoU.poster: 0.0679, IoU.stage: 0.0842, IoU.van: 0.0832, IoU.ship: 0.3571, IoU.fountain: 0.0313, IoU.conveyer belt: 0.4205, IoU.canopy: 0.3546, IoU.washer: 0.3396, IoU.plaything: 0.0441, IoU.swimming pool: 0.3534, IoU.stool: 0.0511, IoU.barrel: 0.1822, IoU.basket: 0.0772, IoU.waterfall: 0.4775, IoU.tent: 0.8673, IoU.bag: 0.0108, IoU.minibike: 0.2984, IoU.cradle: 0.5157, IoU.oven: 0.1207, IoU.ball: 0.0000, IoU.food: 0.4732, IoU.step: 0.0001, IoU.tank: 0.2388, IoU.trade name: 0.1304, IoU.microwave: 0.2134, IoU.pot: 0.1424, IoU.animal: 0.4136, IoU.bicycle: 0.3417, IoU.lake: 0.0000, IoU.dishwasher: 0.0378, IoU.screen: 0.4798, IoU.blanket: 0.0000, IoU.sculpture: 0.2324, IoU.hood: 0.2351, IoU.sconce: 0.0622, IoU.vase: 0.1354, IoU.traffic light: 0.0735, IoU.tray: 0.0055, IoU.ashcan: 0.1592, IoU.fan: 0.1748, IoU.pier: 0.2625, IoU.crt screen: 0.0000, IoU.plate: 0.2692, IoU.monitor: 0.4960, IoU.bulletin board: 0.2820, IoU.shower: 0.0000, IoU.radiator: 0.2273, IoU.glass: 0.0000, IoU.clock: 0.0343, IoU.flag: 0.0692, Acc.wall: 0.8009, Acc.building: 0.8823, Acc.sky: 0.9306, Acc.floor: 0.8301, Acc.tree: 0.8274, Acc.ceiling: 0.8577, Acc.road: 0.8728, Acc.bed : 0.8859, Acc.windowpane: 0.6940, Acc.grass: 0.7700, Acc.cabinet: 0.6333, Acc.sidewalk: 0.6006, Acc.person: 0.8146, Acc.earth: 0.3239, Acc.door: 0.3443, Acc.table: 0.5731, Acc.mountain: 0.7689, Acc.plant: 0.5207, Acc.curtain: 0.7413, Acc.chair: 0.5354, Acc.car: 0.8542, Acc.water: 0.5791, Acc.painting: 0.7107, Acc.sofa: 0.7067, Acc.shelf: 0.5074, Acc.house: 0.6541, Acc.sea: 0.7062, Acc.mirror: 0.4594, Acc.rug: 0.5214, Acc.field: 0.4200, Acc.armchair: 0.3300, Acc.seat: 0.7167, Acc.fence: 0.4025, Acc.desk: 0.5271, Acc.rock: 0.6924, Acc.wardrobe: 0.5640, Acc.lamp: 0.4568, Acc.bathtub: 0.6537, Acc.railing: 0.3456, Acc.cushion: 0.4336, Acc.base: 0.2356, Acc.box: 0.1931, Acc.column: 0.3485, Acc.signboard: 0.2784, Acc.chest of drawers: 0.3764, Acc.counter: 0.2168, Acc.sand: 0.2421, Acc.sink: 0.5159, Acc.skyscraper: 0.8357, Acc.fireplace: 0.6887, Acc.refrigerator: 0.5502, Acc.grandstand: 0.6426, Acc.path: 0.0985, Acc.stairs: 0.2934, Acc.runway: 0.8845, Acc.case: 0.6387, Acc.pool table: 0.8946, Acc.pillow: 0.3507, Acc.screen door: 0.5267, Acc.stairway: 0.3057, Acc.river: 0.2323, Acc.bridge: 0.5897, Acc.bookcase: 0.3878, Acc.blind: 0.2404, Acc.coffee table: 0.6923, Acc.toilet: 0.7582, Acc.flower: 0.3831, Acc.book: 0.5432, Acc.hill: 0.0328, Acc.bench: 0.3818, Acc.countertop: 0.5560, Acc.stove: 0.6197, Acc.palm: 0.4454, Acc.kitchen island: 0.3150, Acc.computer: 0.5922, Acc.swivel chair: 0.4137, Acc.boat: 0.7085, Acc.bar: 0.3315, Acc.arcade machine: 0.6331, Acc.hovel: 0.5490, Acc.bus: 0.7822, Acc.towel: 0.4497, Acc.light: 0.0693, Acc.truck: 0.0904, Acc.tower: 0.3831, Acc.chandelier: 0.6397, Acc.awning: 0.1079, Acc.streetlight: 0.0398, Acc.booth: 0.2748, Acc.television receiver: 0.6372, Acc.airplane: 0.5905, Acc.dirt track: 0.1377, Acc.apparel: 0.1472, Acc.pole: 0.0780, Acc.land: 0.1199, Acc.bannister: 0.0022, Acc.escalator: 0.4406, Acc.ottoman: 0.1501, Acc.bottle: 0.0414, Acc.buffet: 0.2029, Acc.poster: 0.0701, Acc.stage: 0.1368, Acc.van: 0.1008, Acc.ship: 0.3942, Acc.fountain: 0.0324, Acc.conveyer belt: 0.6650, Acc.canopy: 0.4830, Acc.washer: 0.3900, Acc.plaything: 0.0622, Acc.swimming pool: 0.6598, Acc.stool: 0.0629, Acc.barrel: 0.6334, Acc.basket: 0.0918, Acc.waterfall: 0.7299, Acc.tent: 0.9537, Acc.bag: 0.0110, Acc.minibike: 0.3542, Acc.cradle: 0.7888, Acc.oven: 0.1418, Acc.ball: 0.0000, Acc.food: 0.5839, Acc.step: 0.0001, Acc.tank: 0.2607, Acc.trade name: 0.1357, Acc.microwave: 0.2581, Acc.pot: 0.1600, Acc.animal: 0.4521, Acc.bicycle: 0.5266, Acc.lake: 0.0000, Acc.dishwasher: 0.0379, Acc.screen: 0.7060, Acc.blanket: 0.0000, Acc.sculpture: 0.3299, Acc.hood: 0.3016, Acc.sconce: 0.0640, Acc.vase: 0.1986, Acc.traffic light: 0.0860, Acc.tray: 0.0063, Acc.ashcan: 0.1737, Acc.fan: 0.1974, Acc.pier: 0.3162, Acc.crt screen: 0.0000, Acc.plate: 0.3304, Acc.monitor: 0.7146, Acc.bulletin board: 0.3199, Acc.shower: 0.0000, Acc.radiator: 0.2484, Acc.glass: 0.0000, Acc.clock: 0.0360, Acc.flag: 0.0700
2022-11-04 11:50:24,212 - mmseg - INFO - Iter [16050/80000]	lr: 9.810e-05, eta: 6:06:35, time: 0.513, data_time: 0.187, memory: 12960, decode.loss_ce: 0.6308, decode.acc_seg: 76.5664, aux.loss_ce: 0.3276, aux.acc_seg: 71.3790, loss: 0.9584
2022-11-04 11:50:40,949 - mmseg - INFO - Iter [16100/80000]	lr: 9.803e-05, eta: 6:06:16, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6237, decode.acc_seg: 76.5566, aux.loss_ce: 0.3203, aux.acc_seg: 72.2423, loss: 0.9440
2022-11-04 11:50:57,565 - mmseg - INFO - Iter [16150/80000]	lr: 9.796e-05, eta: 6:05:56, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6375, decode.acc_seg: 76.3438, aux.loss_ce: 0.3206, aux.acc_seg: 71.3883, loss: 0.9581
2022-11-04 11:51:14,308 - mmseg - INFO - Iter [16200/80000]	lr: 9.789e-05, eta: 6:05:37, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6435, decode.acc_seg: 76.0926, aux.loss_ce: 0.3324, aux.acc_seg: 70.9563, loss: 0.9758
2022-11-04 11:51:31,335 - mmseg - INFO - Iter [16250/80000]	lr: 9.782e-05, eta: 6:05:19, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6146, decode.acc_seg: 76.9354, aux.loss_ce: 0.3191, aux.acc_seg: 71.8613, loss: 0.9336
2022-11-04 11:51:48,079 - mmseg - INFO - Iter [16300/80000]	lr: 9.775e-05, eta: 6:05:00, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6237, decode.acc_seg: 76.7141, aux.loss_ce: 0.3218, aux.acc_seg: 71.9340, loss: 0.9455
2022-11-04 11:52:04,848 - mmseg - INFO - Iter [16350/80000]	lr: 9.768e-05, eta: 6:04:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6268, decode.acc_seg: 76.4040, aux.loss_ce: 0.3236, aux.acc_seg: 71.3011, loss: 0.9505
2022-11-04 11:52:21,506 - mmseg - INFO - Iter [16400/80000]	lr: 9.762e-05, eta: 6:04:22, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6258, decode.acc_seg: 76.0741, aux.loss_ce: 0.3247, aux.acc_seg: 71.3816, loss: 0.9506
2022-11-04 11:52:41,289 - mmseg - INFO - Iter [16450/80000]	lr: 9.755e-05, eta: 6:04:15, time: 0.396, data_time: 0.072, memory: 12960, decode.loss_ce: 0.6121, decode.acc_seg: 76.7340, aux.loss_ce: 0.3136, aux.acc_seg: 72.1720, loss: 0.9256
2022-11-04 11:52:58,135 - mmseg - INFO - Iter [16500/80000]	lr: 9.748e-05, eta: 6:03:57, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6196, decode.acc_seg: 76.9858, aux.loss_ce: 0.3162, aux.acc_seg: 72.5431, loss: 0.9358
2022-11-04 11:53:14,845 - mmseg - INFO - Iter [16550/80000]	lr: 9.741e-05, eta: 6:03:37, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6185, decode.acc_seg: 76.7501, aux.loss_ce: 0.3233, aux.acc_seg: 71.6009, loss: 0.9417
2022-11-04 11:53:31,644 - mmseg - INFO - Iter [16600/80000]	lr: 9.734e-05, eta: 6:03:19, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6241, decode.acc_seg: 76.6149, aux.loss_ce: 0.3228, aux.acc_seg: 71.4386, loss: 0.9469
2022-11-04 11:53:48,431 - mmseg - INFO - Iter [16650/80000]	lr: 9.727e-05, eta: 6:03:00, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6433, decode.acc_seg: 76.2128, aux.loss_ce: 0.3285, aux.acc_seg: 71.1660, loss: 0.9718
2022-11-04 11:54:05,202 - mmseg - INFO - Iter [16700/80000]	lr: 9.720e-05, eta: 6:02:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6275, decode.acc_seg: 76.4323, aux.loss_ce: 0.3183, aux.acc_seg: 71.9090, loss: 0.9459
2022-11-04 11:54:21,941 - mmseg - INFO - Iter [16750/80000]	lr: 9.713e-05, eta: 6:02:22, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6293, decode.acc_seg: 76.5168, aux.loss_ce: 0.3266, aux.acc_seg: 71.4280, loss: 0.9558
2022-11-04 11:54:38,501 - mmseg - INFO - Iter [16800/80000]	lr: 9.706e-05, eta: 6:02:03, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6278, decode.acc_seg: 76.6203, aux.loss_ce: 0.3230, aux.acc_seg: 71.8651, loss: 0.9508
2022-11-04 11:54:55,135 - mmseg - INFO - Iter [16850/80000]	lr: 9.699e-05, eta: 6:01:44, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6428, decode.acc_seg: 76.0216, aux.loss_ce: 0.3289, aux.acc_seg: 71.4785, loss: 0.9717
2022-11-04 11:55:11,828 - mmseg - INFO - Iter [16900/80000]	lr: 9.692e-05, eta: 6:01:25, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6180, decode.acc_seg: 76.9725, aux.loss_ce: 0.3180, aux.acc_seg: 72.1461, loss: 0.9360
2022-11-04 11:55:28,684 - mmseg - INFO - Iter [16950/80000]	lr: 9.686e-05, eta: 6:01:06, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6472, decode.acc_seg: 76.1090, aux.loss_ce: 0.3366, aux.acc_seg: 71.0640, loss: 0.9838
2022-11-04 11:55:45,147 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 11:55:45,147 - mmseg - INFO - Iter [17000/80000]	lr: 9.679e-05, eta: 6:00:46, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6237, decode.acc_seg: 76.6217, aux.loss_ce: 0.3243, aux.acc_seg: 71.5514, loss: 0.9479
2022-11-04 11:56:04,852 - mmseg - INFO - Iter [17050/80000]	lr: 9.672e-05, eta: 6:00:38, time: 0.394, data_time: 0.057, memory: 12960, decode.loss_ce: 0.6461, decode.acc_seg: 75.6817, aux.loss_ce: 0.3247, aux.acc_seg: 71.6449, loss: 0.9708
2022-11-04 11:56:21,827 - mmseg - INFO - Iter [17100/80000]	lr: 9.665e-05, eta: 6:00:20, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6032, decode.acc_seg: 77.2776, aux.loss_ce: 0.3167, aux.acc_seg: 72.2093, loss: 0.9199
2022-11-04 11:56:38,576 - mmseg - INFO - Iter [17150/80000]	lr: 9.658e-05, eta: 6:00:02, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6295, decode.acc_seg: 76.3715, aux.loss_ce: 0.3273, aux.acc_seg: 71.5964, loss: 0.9568
2022-11-04 11:56:55,024 - mmseg - INFO - Iter [17200/80000]	lr: 9.651e-05, eta: 5:59:42, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6129, decode.acc_seg: 76.5927, aux.loss_ce: 0.3142, aux.acc_seg: 71.6975, loss: 0.9271
2022-11-04 11:57:11,923 - mmseg - INFO - Iter [17250/80000]	lr: 9.644e-05, eta: 5:59:24, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6292, decode.acc_seg: 76.9044, aux.loss_ce: 0.3227, aux.acc_seg: 72.2742, loss: 0.9519
2022-11-04 11:57:28,477 - mmseg - INFO - Iter [17300/80000]	lr: 9.637e-05, eta: 5:59:04, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6344, decode.acc_seg: 76.0635, aux.loss_ce: 0.3302, aux.acc_seg: 71.0865, loss: 0.9646
2022-11-04 11:57:45,097 - mmseg - INFO - Iter [17350/80000]	lr: 9.630e-05, eta: 5:58:45, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6263, decode.acc_seg: 76.3674, aux.loss_ce: 0.3250, aux.acc_seg: 71.5883, loss: 0.9513
2022-11-04 11:58:01,906 - mmseg - INFO - Iter [17400/80000]	lr: 9.623e-05, eta: 5:58:26, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6102, decode.acc_seg: 77.0934, aux.loss_ce: 0.3104, aux.acc_seg: 72.8858, loss: 0.9206
2022-11-04 11:58:18,498 - mmseg - INFO - Iter [17450/80000]	lr: 9.616e-05, eta: 5:58:07, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6001, decode.acc_seg: 77.1738, aux.loss_ce: 0.3069, aux.acc_seg: 72.5430, loss: 0.9070
2022-11-04 11:58:35,224 - mmseg - INFO - Iter [17500/80000]	lr: 9.609e-05, eta: 5:57:48, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6102, decode.acc_seg: 77.3937, aux.loss_ce: 0.3156, aux.acc_seg: 72.5570, loss: 0.9258
2022-11-04 11:58:51,942 - mmseg - INFO - Iter [17550/80000]	lr: 9.603e-05, eta: 5:57:29, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6255, decode.acc_seg: 76.5238, aux.loss_ce: 0.3232, aux.acc_seg: 71.2717, loss: 0.9486
2022-11-04 11:59:08,667 - mmseg - INFO - Iter [17600/80000]	lr: 9.596e-05, eta: 5:57:11, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6370, decode.acc_seg: 76.0570, aux.loss_ce: 0.3248, aux.acc_seg: 71.8646, loss: 0.9618
2022-11-04 11:59:25,462 - mmseg - INFO - Iter [17650/80000]	lr: 9.589e-05, eta: 5:56:52, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6405, decode.acc_seg: 76.5091, aux.loss_ce: 0.3295, aux.acc_seg: 71.3330, loss: 0.9699
2022-11-04 11:59:45,014 - mmseg - INFO - Iter [17700/80000]	lr: 9.582e-05, eta: 5:56:43, time: 0.391, data_time: 0.066, memory: 12960, decode.loss_ce: 0.6001, decode.acc_seg: 77.0307, aux.loss_ce: 0.3150, aux.acc_seg: 72.0588, loss: 0.9151
2022-11-04 12:00:01,911 - mmseg - INFO - Iter [17750/80000]	lr: 9.575e-05, eta: 5:56:25, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6078, decode.acc_seg: 77.4516, aux.loss_ce: 0.3125, aux.acc_seg: 72.8590, loss: 0.9203
2022-11-04 12:00:18,752 - mmseg - INFO - Iter [17800/80000]	lr: 9.568e-05, eta: 5:56:07, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6281, decode.acc_seg: 76.5806, aux.loss_ce: 0.3248, aux.acc_seg: 71.5801, loss: 0.9528
2022-11-04 12:00:36,292 - mmseg - INFO - Iter [17850/80000]	lr: 9.561e-05, eta: 5:55:51, time: 0.351, data_time: 0.024, memory: 12960, decode.loss_ce: 0.6195, decode.acc_seg: 76.9930, aux.loss_ce: 0.3172, aux.acc_seg: 72.6007, loss: 0.9367
2022-11-04 12:00:53,082 - mmseg - INFO - Iter [17900/80000]	lr: 9.554e-05, eta: 5:55:32, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5937, decode.acc_seg: 77.4171, aux.loss_ce: 0.3094, aux.acc_seg: 72.7810, loss: 0.9031
2022-11-04 12:01:09,670 - mmseg - INFO - Iter [17950/80000]	lr: 9.547e-05, eta: 5:55:13, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6203, decode.acc_seg: 76.8564, aux.loss_ce: 0.3176, aux.acc_seg: 72.0940, loss: 0.9378
2022-11-04 12:01:26,319 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:01:26,319 - mmseg - INFO - Iter [18000/80000]	lr: 9.540e-05, eta: 5:54:54, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6190, decode.acc_seg: 76.5912, aux.loss_ce: 0.3242, aux.acc_seg: 71.6667, loss: 0.9431
2022-11-04 12:01:42,865 - mmseg - INFO - Iter [18050/80000]	lr: 9.533e-05, eta: 5:54:35, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6061, decode.acc_seg: 77.2359, aux.loss_ce: 0.3103, aux.acc_seg: 72.6176, loss: 0.9164
2022-11-04 12:01:59,630 - mmseg - INFO - Iter [18100/80000]	lr: 9.526e-05, eta: 5:54:16, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6013, decode.acc_seg: 77.1942, aux.loss_ce: 0.3136, aux.acc_seg: 72.2856, loss: 0.9149
2022-11-04 12:02:16,165 - mmseg - INFO - Iter [18150/80000]	lr: 9.519e-05, eta: 5:53:57, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6214, decode.acc_seg: 76.8188, aux.loss_ce: 0.3252, aux.acc_seg: 71.6594, loss: 0.9467
2022-11-04 12:02:32,751 - mmseg - INFO - Iter [18200/80000]	lr: 9.513e-05, eta: 5:53:38, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6216, decode.acc_seg: 76.6671, aux.loss_ce: 0.3182, aux.acc_seg: 71.9050, loss: 0.9398
2022-11-04 12:02:49,824 - mmseg - INFO - Iter [18250/80000]	lr: 9.506e-05, eta: 5:53:20, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5991, decode.acc_seg: 77.2676, aux.loss_ce: 0.3113, aux.acc_seg: 72.4272, loss: 0.9104
2022-11-04 12:03:09,604 - mmseg - INFO - Iter [18300/80000]	lr: 9.499e-05, eta: 5:53:12, time: 0.395, data_time: 0.062, memory: 12960, decode.loss_ce: 0.6378, decode.acc_seg: 76.3408, aux.loss_ce: 0.3316, aux.acc_seg: 71.1285, loss: 0.9693
2022-11-04 12:03:26,101 - mmseg - INFO - Iter [18350/80000]	lr: 9.492e-05, eta: 5:52:53, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6086, decode.acc_seg: 77.1303, aux.loss_ce: 0.3150, aux.acc_seg: 72.2431, loss: 0.9236
2022-11-04 12:03:42,660 - mmseg - INFO - Iter [18400/80000]	lr: 9.485e-05, eta: 5:52:33, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5858, decode.acc_seg: 77.5897, aux.loss_ce: 0.2992, aux.acc_seg: 73.1526, loss: 0.8850
2022-11-04 12:03:59,121 - mmseg - INFO - Iter [18450/80000]	lr: 9.478e-05, eta: 5:52:14, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6147, decode.acc_seg: 77.0823, aux.loss_ce: 0.3204, aux.acc_seg: 72.0297, loss: 0.9351
2022-11-04 12:04:16,026 - mmseg - INFO - Iter [18500/80000]	lr: 9.471e-05, eta: 5:51:56, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6150, decode.acc_seg: 77.5201, aux.loss_ce: 0.3243, aux.acc_seg: 72.3603, loss: 0.9392
2022-11-04 12:04:33,062 - mmseg - INFO - Iter [18550/80000]	lr: 9.464e-05, eta: 5:51:38, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5908, decode.acc_seg: 77.7969, aux.loss_ce: 0.3066, aux.acc_seg: 72.9838, loss: 0.8974
2022-11-04 12:04:49,865 - mmseg - INFO - Iter [18600/80000]	lr: 9.457e-05, eta: 5:51:20, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.6234, decode.acc_seg: 76.3188, aux.loss_ce: 0.3190, aux.acc_seg: 71.5801, loss: 0.9424
2022-11-04 12:05:06,647 - mmseg - INFO - Iter [18650/80000]	lr: 9.450e-05, eta: 5:51:01, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6037, decode.acc_seg: 76.8958, aux.loss_ce: 0.3123, aux.acc_seg: 71.9383, loss: 0.9160
2022-11-04 12:05:23,369 - mmseg - INFO - Iter [18700/80000]	lr: 9.443e-05, eta: 5:50:43, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6049, decode.acc_seg: 77.0489, aux.loss_ce: 0.3133, aux.acc_seg: 72.1329, loss: 0.9182
2022-11-04 12:05:39,904 - mmseg - INFO - Iter [18750/80000]	lr: 9.436e-05, eta: 5:50:24, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5929, decode.acc_seg: 77.5026, aux.loss_ce: 0.3034, aux.acc_seg: 72.8118, loss: 0.8963
2022-11-04 12:05:56,765 - mmseg - INFO - Iter [18800/80000]	lr: 9.429e-05, eta: 5:50:05, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5932, decode.acc_seg: 77.8794, aux.loss_ce: 0.3031, aux.acc_seg: 73.1511, loss: 0.8963
2022-11-04 12:06:13,283 - mmseg - INFO - Iter [18850/80000]	lr: 9.422e-05, eta: 5:49:46, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6078, decode.acc_seg: 77.0550, aux.loss_ce: 0.3122, aux.acc_seg: 72.6085, loss: 0.9200
2022-11-04 12:06:30,436 - mmseg - INFO - Iter [18900/80000]	lr: 9.416e-05, eta: 5:49:29, time: 0.343, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6302, decode.acc_seg: 76.5158, aux.loss_ce: 0.3250, aux.acc_seg: 71.4783, loss: 0.9552
2022-11-04 12:06:50,184 - mmseg - INFO - Iter [18950/80000]	lr: 9.409e-05, eta: 5:49:20, time: 0.395, data_time: 0.064, memory: 12960, decode.loss_ce: 0.6191, decode.acc_seg: 76.7495, aux.loss_ce: 0.3230, aux.acc_seg: 71.7299, loss: 0.9421
2022-11-04 12:07:07,032 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:07:07,032 - mmseg - INFO - Iter [19000/80000]	lr: 9.402e-05, eta: 5:49:02, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5992, decode.acc_seg: 76.9871, aux.loss_ce: 0.3136, aux.acc_seg: 71.9842, loss: 0.9128
2022-11-04 12:07:23,847 - mmseg - INFO - Iter [19050/80000]	lr: 9.395e-05, eta: 5:48:44, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6030, decode.acc_seg: 77.6362, aux.loss_ce: 0.3159, aux.acc_seg: 72.1800, loss: 0.9189
2022-11-04 12:07:40,483 - mmseg - INFO - Iter [19100/80000]	lr: 9.388e-05, eta: 5:48:25, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5922, decode.acc_seg: 78.0273, aux.loss_ce: 0.3065, aux.acc_seg: 73.0087, loss: 0.8987
2022-11-04 12:07:57,009 - mmseg - INFO - Iter [19150/80000]	lr: 9.381e-05, eta: 5:48:06, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5906, decode.acc_seg: 77.6318, aux.loss_ce: 0.3041, aux.acc_seg: 73.0170, loss: 0.8947
2022-11-04 12:08:13,696 - mmseg - INFO - Iter [19200/80000]	lr: 9.374e-05, eta: 5:47:47, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5979, decode.acc_seg: 77.2619, aux.loss_ce: 0.3103, aux.acc_seg: 72.4865, loss: 0.9082
2022-11-04 12:08:30,549 - mmseg - INFO - Iter [19250/80000]	lr: 9.367e-05, eta: 5:47:29, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5851, decode.acc_seg: 78.0507, aux.loss_ce: 0.3083, aux.acc_seg: 72.8658, loss: 0.8934
2022-11-04 12:08:47,232 - mmseg - INFO - Iter [19300/80000]	lr: 9.360e-05, eta: 5:47:10, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6215, decode.acc_seg: 76.8422, aux.loss_ce: 0.3253, aux.acc_seg: 71.5127, loss: 0.9469
2022-11-04 12:09:04,062 - mmseg - INFO - Iter [19350/80000]	lr: 9.353e-05, eta: 5:46:52, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6250, decode.acc_seg: 76.7872, aux.loss_ce: 0.3252, aux.acc_seg: 71.9377, loss: 0.9502
2022-11-04 12:09:20,883 - mmseg - INFO - Iter [19400/80000]	lr: 9.346e-05, eta: 5:46:34, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6058, decode.acc_seg: 76.7469, aux.loss_ce: 0.3120, aux.acc_seg: 72.2212, loss: 0.9178
2022-11-04 12:09:37,680 - mmseg - INFO - Iter [19450/80000]	lr: 9.339e-05, eta: 5:46:15, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6124, decode.acc_seg: 76.7299, aux.loss_ce: 0.3163, aux.acc_seg: 72.2357, loss: 0.9287
2022-11-04 12:09:54,485 - mmseg - INFO - Iter [19500/80000]	lr: 9.332e-05, eta: 5:45:57, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5972, decode.acc_seg: 77.2574, aux.loss_ce: 0.3062, aux.acc_seg: 72.6069, loss: 0.9034
2022-11-04 12:10:11,101 - mmseg - INFO - Iter [19550/80000]	lr: 9.325e-05, eta: 5:45:38, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6167, decode.acc_seg: 76.9682, aux.loss_ce: 0.3162, aux.acc_seg: 72.2285, loss: 0.9330
2022-11-04 12:10:30,718 - mmseg - INFO - Iter [19600/80000]	lr: 9.318e-05, eta: 5:45:29, time: 0.392, data_time: 0.053, memory: 12960, decode.loss_ce: 0.6030, decode.acc_seg: 77.4832, aux.loss_ce: 0.3092, aux.acc_seg: 72.6028, loss: 0.9122
2022-11-04 12:10:47,570 - mmseg - INFO - Iter [19650/80000]	lr: 9.311e-05, eta: 5:45:11, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5810, decode.acc_seg: 77.4809, aux.loss_ce: 0.3078, aux.acc_seg: 72.4087, loss: 0.8888
2022-11-04 12:11:04,109 - mmseg - INFO - Iter [19700/80000]	lr: 9.304e-05, eta: 5:44:52, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6049, decode.acc_seg: 77.3198, aux.loss_ce: 0.3134, aux.acc_seg: 72.1669, loss: 0.9183
2022-11-04 12:11:20,695 - mmseg - INFO - Iter [19750/80000]	lr: 9.298e-05, eta: 5:44:33, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6026, decode.acc_seg: 77.5218, aux.loss_ce: 0.3159, aux.acc_seg: 72.2511, loss: 0.9185
2022-11-04 12:11:37,346 - mmseg - INFO - Iter [19800/80000]	lr: 9.291e-05, eta: 5:44:14, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5923, decode.acc_seg: 77.3926, aux.loss_ce: 0.3052, aux.acc_seg: 72.7839, loss: 0.8975
2022-11-04 12:11:54,221 - mmseg - INFO - Iter [19850/80000]	lr: 9.284e-05, eta: 5:43:56, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5994, decode.acc_seg: 77.2454, aux.loss_ce: 0.3145, aux.acc_seg: 71.9442, loss: 0.9139
2022-11-04 12:12:10,936 - mmseg - INFO - Iter [19900/80000]	lr: 9.277e-05, eta: 5:43:38, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6122, decode.acc_seg: 77.3050, aux.loss_ce: 0.3135, aux.acc_seg: 72.8607, loss: 0.9257
2022-11-04 12:12:27,638 - mmseg - INFO - Iter [19950/80000]	lr: 9.270e-05, eta: 5:43:19, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6189, decode.acc_seg: 76.8149, aux.loss_ce: 0.3221, aux.acc_seg: 71.9455, loss: 0.9410
2022-11-04 12:12:44,541 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:12:44,542 - mmseg - INFO - Iter [20000/80000]	lr: 9.263e-05, eta: 5:43:01, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.6064, decode.acc_seg: 76.8818, aux.loss_ce: 0.3128, aux.acc_seg: 72.2599, loss: 0.9191
2022-11-04 12:13:01,348 - mmseg - INFO - Iter [20050/80000]	lr: 9.256e-05, eta: 5:42:43, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6189, decode.acc_seg: 76.9435, aux.loss_ce: 0.3181, aux.acc_seg: 72.2393, loss: 0.9369
2022-11-04 12:13:18,220 - mmseg - INFO - Iter [20100/80000]	lr: 9.249e-05, eta: 5:42:25, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6058, decode.acc_seg: 77.1902, aux.loss_ce: 0.3130, aux.acc_seg: 72.4344, loss: 0.9188
2022-11-04 12:13:34,739 - mmseg - INFO - Iter [20150/80000]	lr: 9.242e-05, eta: 5:42:06, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6069, decode.acc_seg: 77.1688, aux.loss_ce: 0.3173, aux.acc_seg: 72.1575, loss: 0.9241
2022-11-04 12:13:54,258 - mmseg - INFO - Iter [20200/80000]	lr: 9.235e-05, eta: 5:41:56, time: 0.390, data_time: 0.055, memory: 12960, decode.loss_ce: 0.6076, decode.acc_seg: 77.4551, aux.loss_ce: 0.3176, aux.acc_seg: 72.4399, loss: 0.9252
2022-11-04 12:14:11,290 - mmseg - INFO - Iter [20250/80000]	lr: 9.228e-05, eta: 5:41:38, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5788, decode.acc_seg: 77.8373, aux.loss_ce: 0.3030, aux.acc_seg: 72.9208, loss: 0.8819
2022-11-04 12:14:27,953 - mmseg - INFO - Iter [20300/80000]	lr: 9.221e-05, eta: 5:41:20, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5942, decode.acc_seg: 77.4651, aux.loss_ce: 0.3054, aux.acc_seg: 72.7143, loss: 0.8996
2022-11-04 12:14:44,685 - mmseg - INFO - Iter [20350/80000]	lr: 9.214e-05, eta: 5:41:01, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5834, decode.acc_seg: 78.1102, aux.loss_ce: 0.3042, aux.acc_seg: 72.8584, loss: 0.8876
2022-11-04 12:15:01,309 - mmseg - INFO - Iter [20400/80000]	lr: 9.207e-05, eta: 5:40:43, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6098, decode.acc_seg: 77.1244, aux.loss_ce: 0.3187, aux.acc_seg: 71.8616, loss: 0.9285
2022-11-04 12:15:18,262 - mmseg - INFO - Iter [20450/80000]	lr: 9.200e-05, eta: 5:40:25, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5935, decode.acc_seg: 77.5547, aux.loss_ce: 0.3109, aux.acc_seg: 72.3858, loss: 0.9044
2022-11-04 12:15:34,965 - mmseg - INFO - Iter [20500/80000]	lr: 9.193e-05, eta: 5:40:06, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6018, decode.acc_seg: 77.4115, aux.loss_ce: 0.3157, aux.acc_seg: 72.2613, loss: 0.9175
2022-11-04 12:15:51,811 - mmseg - INFO - Iter [20550/80000]	lr: 9.186e-05, eta: 5:39:48, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5795, decode.acc_seg: 78.2007, aux.loss_ce: 0.2998, aux.acc_seg: 73.6672, loss: 0.8793
2022-11-04 12:16:08,598 - mmseg - INFO - Iter [20600/80000]	lr: 9.179e-05, eta: 5:39:30, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5975, decode.acc_seg: 77.6369, aux.loss_ce: 0.3151, aux.acc_seg: 72.2145, loss: 0.9127
2022-11-04 12:16:25,405 - mmseg - INFO - Iter [20650/80000]	lr: 9.172e-05, eta: 5:39:12, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6067, decode.acc_seg: 77.1111, aux.loss_ce: 0.3133, aux.acc_seg: 72.0926, loss: 0.9200
2022-11-04 12:16:41,965 - mmseg - INFO - Iter [20700/80000]	lr: 9.165e-05, eta: 5:38:53, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5989, decode.acc_seg: 77.2080, aux.loss_ce: 0.3088, aux.acc_seg: 72.7894, loss: 0.9077
2022-11-04 12:16:58,741 - mmseg - INFO - Iter [20750/80000]	lr: 9.159e-05, eta: 5:38:35, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6182, decode.acc_seg: 76.7653, aux.loss_ce: 0.3243, aux.acc_seg: 71.8794, loss: 0.9424
2022-11-04 12:17:15,464 - mmseg - INFO - Iter [20800/80000]	lr: 9.152e-05, eta: 5:38:17, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6053, decode.acc_seg: 77.0195, aux.loss_ce: 0.3193, aux.acc_seg: 71.6848, loss: 0.9245
2022-11-04 12:17:35,015 - mmseg - INFO - Iter [20850/80000]	lr: 9.145e-05, eta: 5:38:06, time: 0.391, data_time: 0.062, memory: 12960, decode.loss_ce: 0.5877, decode.acc_seg: 77.8626, aux.loss_ce: 0.3067, aux.acc_seg: 72.7444, loss: 0.8943
2022-11-04 12:17:51,563 - mmseg - INFO - Iter [20900/80000]	lr: 9.138e-05, eta: 5:37:48, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5924, decode.acc_seg: 77.5777, aux.loss_ce: 0.3140, aux.acc_seg: 72.4561, loss: 0.9065
2022-11-04 12:18:08,264 - mmseg - INFO - Iter [20950/80000]	lr: 9.131e-05, eta: 5:37:29, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5877, decode.acc_seg: 77.5165, aux.loss_ce: 0.3087, aux.acc_seg: 72.5151, loss: 0.8963
2022-11-04 12:18:24,958 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:18:24,958 - mmseg - INFO - Iter [21000/80000]	lr: 9.124e-05, eta: 5:37:11, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5886, decode.acc_seg: 77.4868, aux.loss_ce: 0.3064, aux.acc_seg: 72.5030, loss: 0.8950
2022-11-04 12:18:41,641 - mmseg - INFO - Iter [21050/80000]	lr: 9.117e-05, eta: 5:36:52, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5966, decode.acc_seg: 77.2221, aux.loss_ce: 0.3180, aux.acc_seg: 71.9141, loss: 0.9146
2022-11-04 12:18:58,406 - mmseg - INFO - Iter [21100/80000]	lr: 9.110e-05, eta: 5:36:34, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6207, decode.acc_seg: 76.7155, aux.loss_ce: 0.3249, aux.acc_seg: 71.7694, loss: 0.9455
2022-11-04 12:19:15,432 - mmseg - INFO - Iter [21150/80000]	lr: 9.103e-05, eta: 5:36:17, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.6061, decode.acc_seg: 77.1074, aux.loss_ce: 0.3184, aux.acc_seg: 72.2536, loss: 0.9244
2022-11-04 12:19:32,108 - mmseg - INFO - Iter [21200/80000]	lr: 9.096e-05, eta: 5:35:58, time: 0.334, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5869, decode.acc_seg: 77.8351, aux.loss_ce: 0.3069, aux.acc_seg: 72.9381, loss: 0.8938
2022-11-04 12:19:49,098 - mmseg - INFO - Iter [21250/80000]	lr: 9.089e-05, eta: 5:35:41, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5884, decode.acc_seg: 77.9035, aux.loss_ce: 0.3066, aux.acc_seg: 73.3267, loss: 0.8950
2022-11-04 12:20:05,843 - mmseg - INFO - Iter [21300/80000]	lr: 9.082e-05, eta: 5:35:22, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5961, decode.acc_seg: 77.8027, aux.loss_ce: 0.3162, aux.acc_seg: 72.5035, loss: 0.9123
2022-11-04 12:20:22,675 - mmseg - INFO - Iter [21350/80000]	lr: 9.075e-05, eta: 5:35:04, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5948, decode.acc_seg: 77.5721, aux.loss_ce: 0.3128, aux.acc_seg: 72.4657, loss: 0.9077
2022-11-04 12:20:39,267 - mmseg - INFO - Iter [21400/80000]	lr: 9.068e-05, eta: 5:34:46, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5660, decode.acc_seg: 78.4646, aux.loss_ce: 0.2995, aux.acc_seg: 73.3109, loss: 0.8656
2022-11-04 12:20:55,922 - mmseg - INFO - Iter [21450/80000]	lr: 9.061e-05, eta: 5:34:27, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5705, decode.acc_seg: 78.3689, aux.loss_ce: 0.2956, aux.acc_seg: 73.5702, loss: 0.8661
2022-11-04 12:21:15,822 - mmseg - INFO - Iter [21500/80000]	lr: 9.054e-05, eta: 5:34:18, time: 0.398, data_time: 0.066, memory: 12960, decode.loss_ce: 0.5656, decode.acc_seg: 78.2764, aux.loss_ce: 0.2977, aux.acc_seg: 73.3344, loss: 0.8633
2022-11-04 12:21:32,682 - mmseg - INFO - Iter [21550/80000]	lr: 9.047e-05, eta: 5:34:00, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5829, decode.acc_seg: 78.0770, aux.loss_ce: 0.3083, aux.acc_seg: 73.0038, loss: 0.8912
2022-11-04 12:21:49,423 - mmseg - INFO - Iter [21600/80000]	lr: 9.040e-05, eta: 5:33:42, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5862, decode.acc_seg: 77.5381, aux.loss_ce: 0.3045, aux.acc_seg: 72.8005, loss: 0.8907
2022-11-04 12:22:06,219 - mmseg - INFO - Iter [21650/80000]	lr: 9.033e-05, eta: 5:33:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5829, decode.acc_seg: 77.9081, aux.loss_ce: 0.3112, aux.acc_seg: 72.3775, loss: 0.8942
2022-11-04 12:22:22,995 - mmseg - INFO - Iter [21700/80000]	lr: 9.026e-05, eta: 5:33:05, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5973, decode.acc_seg: 77.8323, aux.loss_ce: 0.3160, aux.acc_seg: 72.3382, loss: 0.9133
2022-11-04 12:22:39,884 - mmseg - INFO - Iter [21750/80000]	lr: 9.019e-05, eta: 5:32:48, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5746, decode.acc_seg: 78.0784, aux.loss_ce: 0.3012, aux.acc_seg: 73.2077, loss: 0.8758
2022-11-04 12:22:56,624 - mmseg - INFO - Iter [21800/80000]	lr: 9.012e-05, eta: 5:32:29, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5906, decode.acc_seg: 77.5081, aux.loss_ce: 0.3116, aux.acc_seg: 71.9686, loss: 0.9022
2022-11-04 12:23:13,755 - mmseg - INFO - Iter [21850/80000]	lr: 9.005e-05, eta: 5:32:12, time: 0.343, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5924, decode.acc_seg: 77.9322, aux.loss_ce: 0.3123, aux.acc_seg: 72.3484, loss: 0.9047
2022-11-04 12:23:30,647 - mmseg - INFO - Iter [21900/80000]	lr: 8.998e-05, eta: 5:31:54, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5957, decode.acc_seg: 77.3971, aux.loss_ce: 0.3108, aux.acc_seg: 72.4579, loss: 0.9065
2022-11-04 12:23:47,436 - mmseg - INFO - Iter [21950/80000]	lr: 8.991e-05, eta: 5:31:36, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5816, decode.acc_seg: 78.1191, aux.loss_ce: 0.3041, aux.acc_seg: 72.8105, loss: 0.8857
2022-11-04 12:24:04,271 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:24:04,271 - mmseg - INFO - Iter [22000/80000]	lr: 8.984e-05, eta: 5:31:18, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5715, decode.acc_seg: 78.0532, aux.loss_ce: 0.2974, aux.acc_seg: 73.2467, loss: 0.8689
2022-11-04 12:24:20,914 - mmseg - INFO - Iter [22050/80000]	lr: 8.977e-05, eta: 5:31:00, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5875, decode.acc_seg: 78.3444, aux.loss_ce: 0.3068, aux.acc_seg: 73.1215, loss: 0.8943
2022-11-04 12:24:40,526 - mmseg - INFO - Iter [22100/80000]	lr: 8.971e-05, eta: 5:30:49, time: 0.392, data_time: 0.060, memory: 12960, decode.loss_ce: 0.5632, decode.acc_seg: 78.9326, aux.loss_ce: 0.3018, aux.acc_seg: 73.5581, loss: 0.8650
2022-11-04 12:24:57,459 - mmseg - INFO - Iter [22150/80000]	lr: 8.964e-05, eta: 5:30:32, time: 0.339, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5802, decode.acc_seg: 77.8882, aux.loss_ce: 0.3145, aux.acc_seg: 72.0553, loss: 0.8947
2022-11-04 12:25:14,174 - mmseg - INFO - Iter [22200/80000]	lr: 8.957e-05, eta: 5:30:13, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5635, decode.acc_seg: 78.4069, aux.loss_ce: 0.3032, aux.acc_seg: 72.7986, loss: 0.8667
2022-11-04 12:25:30,711 - mmseg - INFO - Iter [22250/80000]	lr: 8.950e-05, eta: 5:29:55, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5555, decode.acc_seg: 79.1588, aux.loss_ce: 0.2941, aux.acc_seg: 74.0803, loss: 0.8497
2022-11-04 12:25:47,533 - mmseg - INFO - Iter [22300/80000]	lr: 8.943e-05, eta: 5:29:37, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5616, decode.acc_seg: 78.7647, aux.loss_ce: 0.2962, aux.acc_seg: 74.1264, loss: 0.8577
2022-11-04 12:26:04,286 - mmseg - INFO - Iter [22350/80000]	lr: 8.936e-05, eta: 5:29:19, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5725, decode.acc_seg: 78.1901, aux.loss_ce: 0.2995, aux.acc_seg: 73.1555, loss: 0.8720
2022-11-04 12:26:20,940 - mmseg - INFO - Iter [22400/80000]	lr: 8.929e-05, eta: 5:29:00, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5904, decode.acc_seg: 77.2901, aux.loss_ce: 0.3043, aux.acc_seg: 72.7816, loss: 0.8947
2022-11-04 12:26:37,758 - mmseg - INFO - Iter [22450/80000]	lr: 8.922e-05, eta: 5:28:42, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5813, decode.acc_seg: 78.0879, aux.loss_ce: 0.3056, aux.acc_seg: 72.9676, loss: 0.8869
2022-11-04 12:26:54,601 - mmseg - INFO - Iter [22500/80000]	lr: 8.915e-05, eta: 5:28:24, time: 0.337, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5895, decode.acc_seg: 77.9244, aux.loss_ce: 0.3134, aux.acc_seg: 72.5831, loss: 0.9029
2022-11-04 12:27:11,178 - mmseg - INFO - Iter [22550/80000]	lr: 8.908e-05, eta: 5:28:06, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5720, decode.acc_seg: 78.3503, aux.loss_ce: 0.2993, aux.acc_seg: 73.5560, loss: 0.8712
2022-11-04 12:27:27,772 - mmseg - INFO - Iter [22600/80000]	lr: 8.901e-05, eta: 5:27:47, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5841, decode.acc_seg: 77.5833, aux.loss_ce: 0.3047, aux.acc_seg: 72.4572, loss: 0.8888
2022-11-04 12:27:44,563 - mmseg - INFO - Iter [22650/80000]	lr: 8.894e-05, eta: 5:27:29, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5980, decode.acc_seg: 77.3364, aux.loss_ce: 0.3152, aux.acc_seg: 72.2626, loss: 0.9133
2022-11-04 12:28:01,241 - mmseg - INFO - Iter [22700/80000]	lr: 8.887e-05, eta: 5:27:11, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5837, decode.acc_seg: 78.3110, aux.loss_ce: 0.3057, aux.acc_seg: 73.6707, loss: 0.8894
2022-11-04 12:28:20,722 - mmseg - INFO - Iter [22750/80000]	lr: 8.880e-05, eta: 5:27:00, time: 0.390, data_time: 0.065, memory: 12960, decode.loss_ce: 0.5735, decode.acc_seg: 78.5100, aux.loss_ce: 0.3028, aux.acc_seg: 73.3983, loss: 0.8762
2022-11-04 12:28:37,291 - mmseg - INFO - Iter [22800/80000]	lr: 8.873e-05, eta: 5:26:41, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5808, decode.acc_seg: 78.0661, aux.loss_ce: 0.3064, aux.acc_seg: 73.2314, loss: 0.8872
2022-11-04 12:28:53,977 - mmseg - INFO - Iter [22850/80000]	lr: 8.866e-05, eta: 5:26:23, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5678, decode.acc_seg: 78.4038, aux.loss_ce: 0.3031, aux.acc_seg: 73.0752, loss: 0.8709
2022-11-04 12:29:10,709 - mmseg - INFO - Iter [22900/80000]	lr: 8.859e-05, eta: 5:26:05, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5594, decode.acc_seg: 79.0186, aux.loss_ce: 0.3025, aux.acc_seg: 73.4443, loss: 0.8619
2022-11-04 12:29:27,545 - mmseg - INFO - Iter [22950/80000]	lr: 8.852e-05, eta: 5:25:47, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5646, decode.acc_seg: 78.6140, aux.loss_ce: 0.2971, aux.acc_seg: 73.3995, loss: 0.8618
2022-11-04 12:29:44,180 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:29:44,181 - mmseg - INFO - Iter [23000/80000]	lr: 8.845e-05, eta: 5:25:29, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5562, decode.acc_seg: 78.6970, aux.loss_ce: 0.2894, aux.acc_seg: 73.8730, loss: 0.8455
2022-11-04 12:30:00,794 - mmseg - INFO - Iter [23050/80000]	lr: 8.838e-05, eta: 5:25:10, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5721, decode.acc_seg: 78.0992, aux.loss_ce: 0.2998, aux.acc_seg: 72.9497, loss: 0.8719
2022-11-04 12:30:17,307 - mmseg - INFO - Iter [23100/80000]	lr: 8.831e-05, eta: 5:24:52, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5906, decode.acc_seg: 77.6936, aux.loss_ce: 0.3056, aux.acc_seg: 72.9882, loss: 0.8961
2022-11-04 12:30:33,906 - mmseg - INFO - Iter [23150/80000]	lr: 8.824e-05, eta: 5:24:33, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5927, decode.acc_seg: 77.6424, aux.loss_ce: 0.3112, aux.acc_seg: 72.3191, loss: 0.9039
2022-11-04 12:30:50,616 - mmseg - INFO - Iter [23200/80000]	lr: 8.817e-05, eta: 5:24:15, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5724, decode.acc_seg: 78.3729, aux.loss_ce: 0.3006, aux.acc_seg: 73.1426, loss: 0.8730
2022-11-04 12:31:07,510 - mmseg - INFO - Iter [23250/80000]	lr: 8.810e-05, eta: 5:23:57, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5750, decode.acc_seg: 78.2131, aux.loss_ce: 0.3018, aux.acc_seg: 73.3511, loss: 0.8768
2022-11-04 12:31:24,415 - mmseg - INFO - Iter [23300/80000]	lr: 8.803e-05, eta: 5:23:40, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5870, decode.acc_seg: 77.4195, aux.loss_ce: 0.3076, aux.acc_seg: 72.3224, loss: 0.8945
2022-11-04 12:31:44,000 - mmseg - INFO - Iter [23350/80000]	lr: 8.796e-05, eta: 5:23:28, time: 0.392, data_time: 0.059, memory: 12960, decode.loss_ce: 0.5764, decode.acc_seg: 78.3191, aux.loss_ce: 0.3018, aux.acc_seg: 72.8839, loss: 0.8782
2022-11-04 12:32:00,818 - mmseg - INFO - Iter [23400/80000]	lr: 8.789e-05, eta: 5:23:11, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5560, decode.acc_seg: 78.7692, aux.loss_ce: 0.3000, aux.acc_seg: 73.2722, loss: 0.8560
2022-11-04 12:32:17,523 - mmseg - INFO - Iter [23450/80000]	lr: 8.782e-05, eta: 5:22:52, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5868, decode.acc_seg: 78.1695, aux.loss_ce: 0.3047, aux.acc_seg: 73.5388, loss: 0.8914
2022-11-04 12:32:34,384 - mmseg - INFO - Iter [23500/80000]	lr: 8.775e-05, eta: 5:22:35, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5740, decode.acc_seg: 78.7088, aux.loss_ce: 0.2991, aux.acc_seg: 73.9410, loss: 0.8731
2022-11-04 12:32:50,990 - mmseg - INFO - Iter [23550/80000]	lr: 8.768e-05, eta: 5:22:16, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5544, decode.acc_seg: 78.6647, aux.loss_ce: 0.2930, aux.acc_seg: 73.4021, loss: 0.8474
2022-11-04 12:33:07,661 - mmseg - INFO - Iter [23600/80000]	lr: 8.761e-05, eta: 5:21:58, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5908, decode.acc_seg: 77.8234, aux.loss_ce: 0.3133, aux.acc_seg: 72.4110, loss: 0.9042
2022-11-04 12:33:24,295 - mmseg - INFO - Iter [23650/80000]	lr: 8.754e-05, eta: 5:21:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5849, decode.acc_seg: 77.9700, aux.loss_ce: 0.3125, aux.acc_seg: 72.4756, loss: 0.8974
2022-11-04 12:33:41,020 - mmseg - INFO - Iter [23700/80000]	lr: 8.747e-05, eta: 5:21:22, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5833, decode.acc_seg: 78.3454, aux.loss_ce: 0.3046, aux.acc_seg: 73.3941, loss: 0.8880
2022-11-04 12:33:57,487 - mmseg - INFO - Iter [23750/80000]	lr: 8.740e-05, eta: 5:21:03, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5725, decode.acc_seg: 78.1545, aux.loss_ce: 0.3021, aux.acc_seg: 73.2158, loss: 0.8746
2022-11-04 12:34:14,217 - mmseg - INFO - Iter [23800/80000]	lr: 8.733e-05, eta: 5:20:45, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5716, decode.acc_seg: 78.5740, aux.loss_ce: 0.2943, aux.acc_seg: 74.0805, loss: 0.8658
2022-11-04 12:34:31,001 - mmseg - INFO - Iter [23850/80000]	lr: 8.726e-05, eta: 5:20:27, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5742, decode.acc_seg: 78.0396, aux.loss_ce: 0.3025, aux.acc_seg: 73.0917, loss: 0.8767
2022-11-04 12:34:47,450 - mmseg - INFO - Iter [23900/80000]	lr: 8.719e-05, eta: 5:20:08, time: 0.329, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5715, decode.acc_seg: 78.4216, aux.loss_ce: 0.3012, aux.acc_seg: 73.3396, loss: 0.8727
2022-11-04 12:35:03,993 - mmseg - INFO - Iter [23950/80000]	lr: 8.712e-05, eta: 5:19:50, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5571, decode.acc_seg: 78.7875, aux.loss_ce: 0.2984, aux.acc_seg: 73.4512, loss: 0.8554
2022-11-04 12:35:23,774 - mmseg - INFO - Saving checkpoint at 24000 iterations
2022-11-04 12:35:23,990 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:35:23,991 - mmseg - INFO - Iter [24000/80000]	lr: 8.705e-05, eta: 5:19:39, time: 0.400, data_time: 0.058, memory: 12960, decode.loss_ce: 0.5591, decode.acc_seg: 78.7776, aux.loss_ce: 0.3004, aux.acc_seg: 72.9814, loss: 0.8595
2022-11-04 12:35:32,898 - mmseg - INFO - per class results:
2022-11-04 12:35:32,905 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 65.57 | 82.57 |
|       building      | 75.67 | 90.72 |
|         sky         | 88.48 | 92.79 |
|        floor        | 70.17 | 84.22 |
|         tree        | 66.43 | 82.17 |
|       ceiling       | 74.74 | 84.25 |
|         road        |  73.6 |  84.9 |
|         bed         | 71.89 | 90.93 |
|      windowpane     | 48.64 | 67.09 |
|        grass        | 62.58 | 81.09 |
|       cabinet       | 44.16 |  56.6 |
|       sidewalk      | 49.81 | 67.18 |
|        person       | 62.78 | 84.38 |
|        earth        | 24.83 | 33.49 |
|         door        | 23.81 | 34.67 |
|        table        | 38.57 | 53.43 |
|       mountain      | 56.35 | 72.14 |
|        plant        | 42.79 | 59.12 |
|       curtain       | 54.13 | 69.77 |
|        chair        | 35.45 | 49.26 |
|         car         | 69.23 | 83.68 |
|        water        | 41.68 | 59.66 |
|       painting      | 52.67 | 71.92 |
|         sofa        | 48.51 |  73.2 |
|        shelf        | 30.56 | 41.45 |
|        house        | 42.09 | 57.32 |
|         sea         | 35.69 | 56.68 |
|        mirror       | 34.19 | 38.39 |
|         rug         | 47.65 | 58.08 |
|        field        | 23.32 | 36.86 |
|       armchair      | 21.45 | 27.18 |
|         seat        | 51.47 | 67.02 |
|        fence        | 21.74 | 37.73 |
|         desk        | 30.56 | 51.22 |
|         rock        | 41.38 | 67.79 |
|       wardrobe      | 36.48 | 52.92 |
|         lamp        |  33.7 |  44.2 |
|       bathtub       | 47.44 | 68.77 |
|       railing       | 27.12 | 37.22 |
|       cushion       | 30.49 | 40.26 |
|         base        | 21.98 | 30.72 |
|         box         | 17.08 | 23.46 |
|        column       | 29.41 | 37.24 |
|      signboard      | 21.25 | 29.87 |
|   chest of drawers  | 25.35 | 43.27 |
|       counter       | 27.47 | 34.28 |
|         sand        | 27.98 | 42.42 |
|         sink        | 40.05 | 47.46 |
|      skyscraper     | 58.61 | 82.01 |
|      fireplace      | 56.11 | 72.18 |
|     refrigerator    | 49.22 |  66.1 |
|      grandstand     | 44.74 | 63.57 |
|         path        |  7.4  | 10.02 |
|        stairs       | 23.38 | 29.49 |
|        runway       | 72.25 | 89.49 |
|         case        | 39.66 | 63.97 |
|      pool table     |  76.6 | 88.59 |
|        pillow       | 30.72 | 36.46 |
|     screen door     | 48.72 | 71.66 |
|       stairway      | 23.49 | 28.04 |
|        river        | 12.42 | 24.51 |
|        bridge       | 40.89 | 61.06 |
|       bookcase      | 23.33 | 42.36 |
|        blind        |  18.7 | 21.01 |
|     coffee table    | 38.61 | 68.55 |
|        toilet       | 62.16 | 75.31 |
|        flower       | 20.03 | 33.01 |
|         book        | 27.65 | 37.96 |
|         hill        |  5.74 |  7.83 |
|        bench        | 28.57 | 39.91 |
|      countertop     | 37.94 | 47.62 |
|        stove        | 44.82 | 57.82 |
|         palm        | 32.77 | 52.64 |
|    kitchen island   | 19.43 | 60.05 |
|       computer      | 41.46 | 61.69 |
|     swivel chair    | 30.85 | 45.56 |
|         boat        | 41.07 | 52.49 |
|         bar         |  25.1 | 29.53 |
|    arcade machine   | 33.45 | 38.94 |
|        hovel        | 31.55 | 39.16 |
|         bus         | 58.33 | 80.25 |
|        towel        | 28.98 | 39.46 |
|        light        | 10.11 | 10.72 |
|        truck        |  4.17 |  5.89 |
|        tower        | 40.07 | 61.31 |
|      chandelier     |  44.4 | 57.56 |
|        awning       |  13.7 | 15.75 |
|     streetlight     |  3.4  |  3.91 |
|        booth        | 26.06 | 37.95 |
| television receiver | 33.55 | 64.79 |
|       airplane      | 41.56 | 48.28 |
|      dirt track     |  3.24 | 17.96 |
|       apparel       | 20.87 | 29.87 |
|         pole        |  7.3  | 11.22 |
|         land        |  0.46 |  0.81 |
|      bannister      |  0.47 |  0.63 |
|      escalator      |  40.5 | 69.69 |
|       ottoman       |  24.7 | 28.86 |
|        bottle       | 17.32 | 22.46 |
|        buffet       | 30.75 |  35.5 |
|        poster       | 16.32 | 20.87 |
|        stage        |  12.7 | 15.47 |
|         van         |  6.92 |  8.23 |
|         ship        |  0.32 |  0.38 |
|       fountain      |  8.73 |  8.96 |
|    conveyer belt    | 50.39 | 59.47 |
|        canopy       | 21.79 |  28.9 |
|        washer       |  46.8 | 63.61 |
|      plaything      |  4.67 |  7.08 |
|    swimming pool    | 37.09 | 68.05 |
|        stool        |  11.6 |  13.0 |
|        barrel       |  17.3 |  62.2 |
|        basket       | 14.74 | 19.68 |
|      waterfall      |  56.7 | 76.09 |
|         tent        |  86.3 | 96.28 |
|         bag         |  1.65 |  1.69 |
|       minibike      | 38.01 | 44.72 |
|        cradle       | 55.02 | 77.24 |
|         oven        |  15.5 | 20.33 |
|         ball        | 16.71 | 20.08 |
|         food        | 46.07 | 60.77 |
|         step        |  0.72 |  0.73 |
|         tank        | 38.83 | 44.43 |
|      trade name     | 20.04 | 22.62 |
|      microwave      | 21.76 | 26.68 |
|         pot         | 15.41 | 17.63 |
|        animal       | 39.45 | 44.19 |
|       bicycle       | 31.72 | 50.86 |
|         lake        |  0.02 |  0.02 |
|      dishwasher     | 26.08 | 39.13 |
|        screen       | 49.99 | 75.37 |
|       blanket       |  0.0  |  0.0  |
|      sculpture      | 31.03 | 44.84 |
|         hood        |  23.9 | 26.11 |
|        sconce       |  6.94 |  7.11 |
|         vase        | 14.16 | 18.48 |
|    traffic light    |  5.72 |  6.36 |
|         tray        |  0.82 |  0.95 |
|        ashcan       | 17.59 | 19.98 |
|         fan         | 19.87 | 22.37 |
|         pier        |  4.35 |  9.15 |
|      crt screen     |  0.0  |  0.0  |
|        plate        | 27.57 |  32.2 |
|       monitor       | 23.42 | 32.01 |
|    bulletin board   | 26.23 | 30.84 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 25.98 | 28.04 |
|        glass        |  0.0  |  0.0  |
|        clock        |  4.25 |  4.67 |
|         flag        | 11.01 | 11.28 |
+---------------------+-------+-------+
2022-11-04 12:35:32,905 - mmseg - INFO - Summary:
2022-11-04 12:35:32,906 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 74.36 | 31.72 | 42.74 |
+-------+-------+-------+
2022-11-04 12:35:32,907 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:35:32,907 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7436, mIoU: 0.3172, mAcc: 0.4274, IoU.wall: 0.6557, IoU.building: 0.7567, IoU.sky: 0.8848, IoU.floor: 0.7017, IoU.tree: 0.6643, IoU.ceiling: 0.7474, IoU.road: 0.7360, IoU.bed : 0.7189, IoU.windowpane: 0.4864, IoU.grass: 0.6258, IoU.cabinet: 0.4416, IoU.sidewalk: 0.4981, IoU.person: 0.6278, IoU.earth: 0.2483, IoU.door: 0.2381, IoU.table: 0.3857, IoU.mountain: 0.5635, IoU.plant: 0.4279, IoU.curtain: 0.5413, IoU.chair: 0.3545, IoU.car: 0.6923, IoU.water: 0.4168, IoU.painting: 0.5267, IoU.sofa: 0.4851, IoU.shelf: 0.3056, IoU.house: 0.4209, IoU.sea: 0.3569, IoU.mirror: 0.3419, IoU.rug: 0.4765, IoU.field: 0.2332, IoU.armchair: 0.2145, IoU.seat: 0.5147, IoU.fence: 0.2174, IoU.desk: 0.3056, IoU.rock: 0.4138, IoU.wardrobe: 0.3648, IoU.lamp: 0.3370, IoU.bathtub: 0.4744, IoU.railing: 0.2712, IoU.cushion: 0.3049, IoU.base: 0.2198, IoU.box: 0.1708, IoU.column: 0.2941, IoU.signboard: 0.2125, IoU.chest of drawers: 0.2535, IoU.counter: 0.2747, IoU.sand: 0.2798, IoU.sink: 0.4005, IoU.skyscraper: 0.5861, IoU.fireplace: 0.5611, IoU.refrigerator: 0.4922, IoU.grandstand: 0.4474, IoU.path: 0.0740, IoU.stairs: 0.2338, IoU.runway: 0.7225, IoU.case: 0.3966, IoU.pool table: 0.7660, IoU.pillow: 0.3072, IoU.screen door: 0.4872, IoU.stairway: 0.2349, IoU.river: 0.1242, IoU.bridge: 0.4089, IoU.bookcase: 0.2333, IoU.blind: 0.1870, IoU.coffee table: 0.3861, IoU.toilet: 0.6216, IoU.flower: 0.2003, IoU.book: 0.2765, IoU.hill: 0.0574, IoU.bench: 0.2857, IoU.countertop: 0.3794, IoU.stove: 0.4482, IoU.palm: 0.3277, IoU.kitchen island: 0.1943, IoU.computer: 0.4146, IoU.swivel chair: 0.3085, IoU.boat: 0.4107, IoU.bar: 0.2510, IoU.arcade machine: 0.3345, IoU.hovel: 0.3155, IoU.bus: 0.5833, IoU.towel: 0.2898, IoU.light: 0.1011, IoU.truck: 0.0417, IoU.tower: 0.4007, IoU.chandelier: 0.4440, IoU.awning: 0.1370, IoU.streetlight: 0.0340, IoU.booth: 0.2606, IoU.television receiver: 0.3355, IoU.airplane: 0.4156, IoU.dirt track: 0.0324, IoU.apparel: 0.2087, IoU.pole: 0.0730, IoU.land: 0.0046, IoU.bannister: 0.0047, IoU.escalator: 0.4050, IoU.ottoman: 0.2470, IoU.bottle: 0.1732, IoU.buffet: 0.3075, IoU.poster: 0.1632, IoU.stage: 0.1270, IoU.van: 0.0692, IoU.ship: 0.0032, IoU.fountain: 0.0873, IoU.conveyer belt: 0.5039, IoU.canopy: 0.2179, IoU.washer: 0.4680, IoU.plaything: 0.0467, IoU.swimming pool: 0.3709, IoU.stool: 0.1160, IoU.barrel: 0.1730, IoU.basket: 0.1474, IoU.waterfall: 0.5670, IoU.tent: 0.8630, IoU.bag: 0.0165, IoU.minibike: 0.3801, IoU.cradle: 0.5502, IoU.oven: 0.1550, IoU.ball: 0.1671, IoU.food: 0.4607, IoU.step: 0.0072, IoU.tank: 0.3883, IoU.trade name: 0.2004, IoU.microwave: 0.2176, IoU.pot: 0.1541, IoU.animal: 0.3945, IoU.bicycle: 0.3172, IoU.lake: 0.0002, IoU.dishwasher: 0.2608, IoU.screen: 0.4999, IoU.blanket: 0.0000, IoU.sculpture: 0.3103, IoU.hood: 0.2390, IoU.sconce: 0.0694, IoU.vase: 0.1416, IoU.traffic light: 0.0572, IoU.tray: 0.0082, IoU.ashcan: 0.1759, IoU.fan: 0.1987, IoU.pier: 0.0435, IoU.crt screen: 0.0000, IoU.plate: 0.2757, IoU.monitor: 0.2342, IoU.bulletin board: 0.2623, IoU.shower: 0.0000, IoU.radiator: 0.2598, IoU.glass: 0.0000, IoU.clock: 0.0425, IoU.flag: 0.1101, Acc.wall: 0.8257, Acc.building: 0.9072, Acc.sky: 0.9279, Acc.floor: 0.8422, Acc.tree: 0.8217, Acc.ceiling: 0.8425, Acc.road: 0.8490, Acc.bed : 0.9093, Acc.windowpane: 0.6709, Acc.grass: 0.8109, Acc.cabinet: 0.5660, Acc.sidewalk: 0.6718, Acc.person: 0.8438, Acc.earth: 0.3349, Acc.door: 0.3467, Acc.table: 0.5343, Acc.mountain: 0.7214, Acc.plant: 0.5912, Acc.curtain: 0.6977, Acc.chair: 0.4926, Acc.car: 0.8368, Acc.water: 0.5966, Acc.painting: 0.7192, Acc.sofa: 0.7320, Acc.shelf: 0.4145, Acc.house: 0.5732, Acc.sea: 0.5668, Acc.mirror: 0.3839, Acc.rug: 0.5808, Acc.field: 0.3686, Acc.armchair: 0.2718, Acc.seat: 0.6702, Acc.fence: 0.3773, Acc.desk: 0.5122, Acc.rock: 0.6779, Acc.wardrobe: 0.5292, Acc.lamp: 0.4420, Acc.bathtub: 0.6877, Acc.railing: 0.3722, Acc.cushion: 0.4026, Acc.base: 0.3072, Acc.box: 0.2346, Acc.column: 0.3724, Acc.signboard: 0.2987, Acc.chest of drawers: 0.4327, Acc.counter: 0.3428, Acc.sand: 0.4242, Acc.sink: 0.4746, Acc.skyscraper: 0.8201, Acc.fireplace: 0.7218, Acc.refrigerator: 0.6610, Acc.grandstand: 0.6357, Acc.path: 0.1002, Acc.stairs: 0.2949, Acc.runway: 0.8949, Acc.case: 0.6397, Acc.pool table: 0.8859, Acc.pillow: 0.3646, Acc.screen door: 0.7166, Acc.stairway: 0.2804, Acc.river: 0.2451, Acc.bridge: 0.6106, Acc.bookcase: 0.4236, Acc.blind: 0.2101, Acc.coffee table: 0.6855, Acc.toilet: 0.7531, Acc.flower: 0.3301, Acc.book: 0.3796, Acc.hill: 0.0783, Acc.bench: 0.3991, Acc.countertop: 0.4762, Acc.stove: 0.5782, Acc.palm: 0.5264, Acc.kitchen island: 0.6005, Acc.computer: 0.6169, Acc.swivel chair: 0.4556, Acc.boat: 0.5249, Acc.bar: 0.2953, Acc.arcade machine: 0.3894, Acc.hovel: 0.3916, Acc.bus: 0.8025, Acc.towel: 0.3946, Acc.light: 0.1072, Acc.truck: 0.0589, Acc.tower: 0.6131, Acc.chandelier: 0.5756, Acc.awning: 0.1575, Acc.streetlight: 0.0391, Acc.booth: 0.3795, Acc.television receiver: 0.6479, Acc.airplane: 0.4828, Acc.dirt track: 0.1796, Acc.apparel: 0.2987, Acc.pole: 0.1122, Acc.land: 0.0081, Acc.bannister: 0.0063, Acc.escalator: 0.6969, Acc.ottoman: 0.2886, Acc.bottle: 0.2246, Acc.buffet: 0.3550, Acc.poster: 0.2087, Acc.stage: 0.1547, Acc.van: 0.0823, Acc.ship: 0.0038, Acc.fountain: 0.0896, Acc.conveyer belt: 0.5947, Acc.canopy: 0.2890, Acc.washer: 0.6361, Acc.plaything: 0.0708, Acc.swimming pool: 0.6805, Acc.stool: 0.1300, Acc.barrel: 0.6220, Acc.basket: 0.1968, Acc.waterfall: 0.7609, Acc.tent: 0.9628, Acc.bag: 0.0169, Acc.minibike: 0.4472, Acc.cradle: 0.7724, Acc.oven: 0.2033, Acc.ball: 0.2008, Acc.food: 0.6077, Acc.step: 0.0073, Acc.tank: 0.4443, Acc.trade name: 0.2262, Acc.microwave: 0.2668, Acc.pot: 0.1763, Acc.animal: 0.4419, Acc.bicycle: 0.5086, Acc.lake: 0.0002, Acc.dishwasher: 0.3913, Acc.screen: 0.7537, Acc.blanket: 0.0000, Acc.sculpture: 0.4484, Acc.hood: 0.2611, Acc.sconce: 0.0711, Acc.vase: 0.1848, Acc.traffic light: 0.0636, Acc.tray: 0.0095, Acc.ashcan: 0.1998, Acc.fan: 0.2237, Acc.pier: 0.0915, Acc.crt screen: 0.0000, Acc.plate: 0.3220, Acc.monitor: 0.3201, Acc.bulletin board: 0.3084, Acc.shower: 0.0000, Acc.radiator: 0.2804, Acc.glass: 0.0000, Acc.clock: 0.0467, Acc.flag: 0.1128
2022-11-04 12:35:49,759 - mmseg - INFO - Iter [24050/80000]	lr: 8.698e-05, eta: 5:19:42, time: 0.515, data_time: 0.187, memory: 12960, decode.loss_ce: 0.5644, decode.acc_seg: 78.9740, aux.loss_ce: 0.3005, aux.acc_seg: 73.8974, loss: 0.8649
2022-11-04 12:36:06,456 - mmseg - INFO - Iter [24100/80000]	lr: 8.691e-05, eta: 5:19:24, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5545, decode.acc_seg: 78.8469, aux.loss_ce: 0.2965, aux.acc_seg: 73.6575, loss: 0.8510
2022-11-04 12:36:23,104 - mmseg - INFO - Iter [24150/80000]	lr: 8.684e-05, eta: 5:19:06, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5663, decode.acc_seg: 78.6614, aux.loss_ce: 0.3045, aux.acc_seg: 73.2706, loss: 0.8708
2022-11-04 12:36:39,835 - mmseg - INFO - Iter [24200/80000]	lr: 8.677e-05, eta: 5:18:48, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5631, decode.acc_seg: 78.6512, aux.loss_ce: 0.2997, aux.acc_seg: 73.3250, loss: 0.8628
2022-11-04 12:36:56,661 - mmseg - INFO - Iter [24250/80000]	lr: 8.670e-05, eta: 5:18:30, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5329, decode.acc_seg: 79.7242, aux.loss_ce: 0.2892, aux.acc_seg: 74.1116, loss: 0.8221
2022-11-04 12:37:13,511 - mmseg - INFO - Iter [24300/80000]	lr: 8.663e-05, eta: 5:18:12, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5719, decode.acc_seg: 78.1662, aux.loss_ce: 0.3052, aux.acc_seg: 73.2157, loss: 0.8771
2022-11-04 12:37:30,069 - mmseg - INFO - Iter [24350/80000]	lr: 8.656e-05, eta: 5:17:54, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5508, decode.acc_seg: 78.8303, aux.loss_ce: 0.2926, aux.acc_seg: 73.7549, loss: 0.8434
2022-11-04 12:37:46,580 - mmseg - INFO - Iter [24400/80000]	lr: 8.649e-05, eta: 5:17:35, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5592, decode.acc_seg: 78.3547, aux.loss_ce: 0.2913, aux.acc_seg: 73.7637, loss: 0.8505
2022-11-04 12:38:03,338 - mmseg - INFO - Iter [24450/80000]	lr: 8.642e-05, eta: 5:17:17, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5794, decode.acc_seg: 77.8790, aux.loss_ce: 0.2987, aux.acc_seg: 73.1285, loss: 0.8781
2022-11-04 12:38:20,047 - mmseg - INFO - Iter [24500/80000]	lr: 8.635e-05, eta: 5:16:59, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5836, decode.acc_seg: 78.2290, aux.loss_ce: 0.3136, aux.acc_seg: 72.5156, loss: 0.8972
2022-11-04 12:38:36,811 - mmseg - INFO - Iter [24550/80000]	lr: 8.628e-05, eta: 5:16:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5834, decode.acc_seg: 77.9561, aux.loss_ce: 0.3014, aux.acc_seg: 73.2762, loss: 0.8848
2022-11-04 12:38:53,598 - mmseg - INFO - Iter [24600/80000]	lr: 8.621e-05, eta: 5:16:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5824, decode.acc_seg: 78.2667, aux.loss_ce: 0.3124, aux.acc_seg: 72.3756, loss: 0.8948
2022-11-04 12:39:13,377 - mmseg - INFO - Iter [24650/80000]	lr: 8.614e-05, eta: 5:16:12, time: 0.396, data_time: 0.061, memory: 12960, decode.loss_ce: 0.5713, decode.acc_seg: 78.3108, aux.loss_ce: 0.3008, aux.acc_seg: 73.2332, loss: 0.8720
2022-11-04 12:39:29,978 - mmseg - INFO - Iter [24700/80000]	lr: 8.607e-05, eta: 5:15:54, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5659, decode.acc_seg: 78.1194, aux.loss_ce: 0.3020, aux.acc_seg: 72.9101, loss: 0.8679
2022-11-04 12:39:46,721 - mmseg - INFO - Iter [24750/80000]	lr: 8.600e-05, eta: 5:15:36, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5496, decode.acc_seg: 79.4617, aux.loss_ce: 0.2939, aux.acc_seg: 74.0802, loss: 0.8434
2022-11-04 12:40:03,325 - mmseg - INFO - Iter [24800/80000]	lr: 8.593e-05, eta: 5:15:17, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5465, decode.acc_seg: 78.9671, aux.loss_ce: 0.2911, aux.acc_seg: 73.7160, loss: 0.8376
2022-11-04 12:40:20,055 - mmseg - INFO - Iter [24850/80000]	lr: 8.586e-05, eta: 5:14:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5515, decode.acc_seg: 79.1663, aux.loss_ce: 0.2945, aux.acc_seg: 74.0149, loss: 0.8460
2022-11-04 12:40:36,745 - mmseg - INFO - Iter [24900/80000]	lr: 8.579e-05, eta: 5:14:41, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5497, decode.acc_seg: 79.0285, aux.loss_ce: 0.2956, aux.acc_seg: 73.4667, loss: 0.8452
2022-11-04 12:40:53,288 - mmseg - INFO - Iter [24950/80000]	lr: 8.572e-05, eta: 5:14:23, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5751, decode.acc_seg: 78.3948, aux.loss_ce: 0.3054, aux.acc_seg: 73.1410, loss: 0.8804
2022-11-04 12:41:10,067 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:41:10,067 - mmseg - INFO - Iter [25000/80000]	lr: 8.565e-05, eta: 5:14:05, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5718, decode.acc_seg: 78.7088, aux.loss_ce: 0.3080, aux.acc_seg: 72.9304, loss: 0.8799
2022-11-04 12:41:26,902 - mmseg - INFO - Iter [25050/80000]	lr: 8.558e-05, eta: 5:13:47, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5827, decode.acc_seg: 77.9990, aux.loss_ce: 0.3060, aux.acc_seg: 72.7217, loss: 0.8886
2022-11-04 12:41:43,616 - mmseg - INFO - Iter [25100/80000]	lr: 8.551e-05, eta: 5:13:29, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5528, decode.acc_seg: 79.0968, aux.loss_ce: 0.2910, aux.acc_seg: 73.7977, loss: 0.8438
2022-11-04 12:42:00,454 - mmseg - INFO - Iter [25150/80000]	lr: 8.544e-05, eta: 5:13:11, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5454, decode.acc_seg: 79.3387, aux.loss_ce: 0.2930, aux.acc_seg: 73.8811, loss: 0.8385
2022-11-04 12:42:17,141 - mmseg - INFO - Iter [25200/80000]	lr: 8.537e-05, eta: 5:12:53, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5578, decode.acc_seg: 78.6309, aux.loss_ce: 0.2988, aux.acc_seg: 73.3386, loss: 0.8567
2022-11-04 12:42:36,519 - mmseg - INFO - Iter [25250/80000]	lr: 8.530e-05, eta: 5:12:41, time: 0.388, data_time: 0.066, memory: 12960, decode.loss_ce: 0.5758, decode.acc_seg: 77.9180, aux.loss_ce: 0.3051, aux.acc_seg: 72.7547, loss: 0.8809
2022-11-04 12:42:53,342 - mmseg - INFO - Iter [25300/80000]	lr: 8.523e-05, eta: 5:12:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5695, decode.acc_seg: 78.6635, aux.loss_ce: 0.3026, aux.acc_seg: 73.3627, loss: 0.8721
2022-11-04 12:43:10,132 - mmseg - INFO - Iter [25350/80000]	lr: 8.516e-05, eta: 5:12:05, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5630, decode.acc_seg: 78.5363, aux.loss_ce: 0.3007, aux.acc_seg: 73.2769, loss: 0.8637
2022-11-04 12:43:26,842 - mmseg - INFO - Iter [25400/80000]	lr: 8.509e-05, eta: 5:11:47, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5472, decode.acc_seg: 79.3547, aux.loss_ce: 0.2962, aux.acc_seg: 73.8903, loss: 0.8435
2022-11-04 12:43:43,495 - mmseg - INFO - Iter [25450/80000]	lr: 8.502e-05, eta: 5:11:29, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5567, decode.acc_seg: 78.9874, aux.loss_ce: 0.2954, aux.acc_seg: 73.4942, loss: 0.8520
2022-11-04 12:44:00,072 - mmseg - INFO - Iter [25500/80000]	lr: 8.495e-05, eta: 5:11:11, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5505, decode.acc_seg: 79.5126, aux.loss_ce: 0.2962, aux.acc_seg: 74.1336, loss: 0.8467
2022-11-04 12:44:16,639 - mmseg - INFO - Iter [25550/80000]	lr: 8.488e-05, eta: 5:10:52, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5641, decode.acc_seg: 78.7917, aux.loss_ce: 0.2974, aux.acc_seg: 74.0637, loss: 0.8615
2022-11-04 12:44:33,347 - mmseg - INFO - Iter [25600/80000]	lr: 8.481e-05, eta: 5:10:34, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5485, decode.acc_seg: 78.8268, aux.loss_ce: 0.2895, aux.acc_seg: 73.8751, loss: 0.8380
2022-11-04 12:44:50,161 - mmseg - INFO - Iter [25650/80000]	lr: 8.474e-05, eta: 5:10:16, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5640, decode.acc_seg: 78.4439, aux.loss_ce: 0.3006, aux.acc_seg: 73.3943, loss: 0.8646
2022-11-04 12:45:06,787 - mmseg - INFO - Iter [25700/80000]	lr: 8.467e-05, eta: 5:09:58, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5605, decode.acc_seg: 78.8198, aux.loss_ce: 0.2922, aux.acc_seg: 73.9472, loss: 0.8526
2022-11-04 12:45:23,655 - mmseg - INFO - Iter [25750/80000]	lr: 8.460e-05, eta: 5:09:41, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5585, decode.acc_seg: 78.7972, aux.loss_ce: 0.2942, aux.acc_seg: 73.8932, loss: 0.8527
2022-11-04 12:45:40,314 - mmseg - INFO - Iter [25800/80000]	lr: 8.453e-05, eta: 5:09:23, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5593, decode.acc_seg: 78.5211, aux.loss_ce: 0.3066, aux.acc_seg: 72.8637, loss: 0.8659
2022-11-04 12:45:56,909 - mmseg - INFO - Iter [25850/80000]	lr: 8.446e-05, eta: 5:09:04, time: 0.332, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5488, decode.acc_seg: 79.5021, aux.loss_ce: 0.2942, aux.acc_seg: 74.3557, loss: 0.8430
2022-11-04 12:46:16,321 - mmseg - INFO - Iter [25900/80000]	lr: 8.439e-05, eta: 5:08:52, time: 0.388, data_time: 0.063, memory: 12960, decode.loss_ce: 0.5491, decode.acc_seg: 79.1539, aux.loss_ce: 0.3032, aux.acc_seg: 73.1167, loss: 0.8523
2022-11-04 12:46:33,202 - mmseg - INFO - Iter [25950/80000]	lr: 8.432e-05, eta: 5:08:34, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5291, decode.acc_seg: 79.8390, aux.loss_ce: 0.2851, aux.acc_seg: 74.8107, loss: 0.8142
2022-11-04 12:46:49,909 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:46:49,910 - mmseg - INFO - Iter [26000/80000]	lr: 8.425e-05, eta: 5:08:16, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5544, decode.acc_seg: 79.1682, aux.loss_ce: 0.2956, aux.acc_seg: 73.7787, loss: 0.8500
2022-11-04 12:47:06,700 - mmseg - INFO - Iter [26050/80000]	lr: 8.418e-05, eta: 5:07:58, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5350, decode.acc_seg: 79.3420, aux.loss_ce: 0.2844, aux.acc_seg: 74.4464, loss: 0.8194
2022-11-04 12:47:23,447 - mmseg - INFO - Iter [26100/80000]	lr: 8.411e-05, eta: 5:07:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5516, decode.acc_seg: 78.8335, aux.loss_ce: 0.2891, aux.acc_seg: 73.9578, loss: 0.8407
2022-11-04 12:47:40,291 - mmseg - INFO - Iter [26150/80000]	lr: 8.404e-05, eta: 5:07:23, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5513, decode.acc_seg: 79.0603, aux.loss_ce: 0.2965, aux.acc_seg: 73.5287, loss: 0.8478
2022-11-04 12:47:57,096 - mmseg - INFO - Iter [26200/80000]	lr: 8.397e-05, eta: 5:07:05, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5592, decode.acc_seg: 78.7666, aux.loss_ce: 0.2960, aux.acc_seg: 73.7114, loss: 0.8551
2022-11-04 12:48:13,803 - mmseg - INFO - Iter [26250/80000]	lr: 8.390e-05, eta: 5:06:47, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5533, decode.acc_seg: 78.6430, aux.loss_ce: 0.2964, aux.acc_seg: 73.6763, loss: 0.8497
2022-11-04 12:48:30,618 - mmseg - INFO - Iter [26300/80000]	lr: 8.383e-05, eta: 5:06:29, time: 0.336, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5427, decode.acc_seg: 79.2578, aux.loss_ce: 0.2872, aux.acc_seg: 74.5650, loss: 0.8300
2022-11-04 12:48:47,323 - mmseg - INFO - Iter [26350/80000]	lr: 8.376e-05, eta: 5:06:11, time: 0.334, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5580, decode.acc_seg: 78.7127, aux.loss_ce: 0.3012, aux.acc_seg: 73.1089, loss: 0.8592
2022-11-04 12:49:03,853 - mmseg - INFO - Iter [26400/80000]	lr: 8.369e-05, eta: 5:05:53, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5427, decode.acc_seg: 79.0317, aux.loss_ce: 0.2865, aux.acc_seg: 74.1196, loss: 0.8292
2022-11-04 12:49:20,437 - mmseg - INFO - Iter [26450/80000]	lr: 8.362e-05, eta: 5:05:35, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5532, decode.acc_seg: 78.8532, aux.loss_ce: 0.2927, aux.acc_seg: 74.1282, loss: 0.8459
2022-11-04 12:49:37,266 - mmseg - INFO - Iter [26500/80000]	lr: 8.355e-05, eta: 5:05:17, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5995, decode.acc_seg: 77.5329, aux.loss_ce: 0.3150, aux.acc_seg: 71.8787, loss: 0.9145
2022-11-04 12:49:56,925 - mmseg - INFO - Iter [26550/80000]	lr: 8.348e-05, eta: 5:05:05, time: 0.393, data_time: 0.063, memory: 12960, decode.loss_ce: 0.5330, decode.acc_seg: 79.8932, aux.loss_ce: 0.2886, aux.acc_seg: 74.4287, loss: 0.8216
2022-11-04 12:50:13,575 - mmseg - INFO - Iter [26600/80000]	lr: 8.341e-05, eta: 5:04:47, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5737, decode.acc_seg: 78.4042, aux.loss_ce: 0.3026, aux.acc_seg: 73.1676, loss: 0.8764
2022-11-04 12:50:29,978 - mmseg - INFO - Iter [26650/80000]	lr: 8.334e-05, eta: 5:04:28, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5342, decode.acc_seg: 79.6940, aux.loss_ce: 0.2891, aux.acc_seg: 74.5110, loss: 0.8233
2022-11-04 12:50:46,631 - mmseg - INFO - Iter [26700/80000]	lr: 8.326e-05, eta: 5:04:10, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5339, decode.acc_seg: 79.8481, aux.loss_ce: 0.2877, aux.acc_seg: 74.4232, loss: 0.8216
2022-11-04 12:51:03,366 - mmseg - INFO - Iter [26750/80000]	lr: 8.319e-05, eta: 5:03:53, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5543, decode.acc_seg: 78.9907, aux.loss_ce: 0.2930, aux.acc_seg: 73.7333, loss: 0.8473
2022-11-04 12:51:20,016 - mmseg - INFO - Iter [26800/80000]	lr: 8.312e-05, eta: 5:03:34, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5549, decode.acc_seg: 78.7074, aux.loss_ce: 0.3016, aux.acc_seg: 72.8685, loss: 0.8565
2022-11-04 12:51:36,560 - mmseg - INFO - Iter [26850/80000]	lr: 8.305e-05, eta: 5:03:16, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5518, decode.acc_seg: 78.7776, aux.loss_ce: 0.2922, aux.acc_seg: 73.7373, loss: 0.8440
2022-11-04 12:51:53,318 - mmseg - INFO - Iter [26900/80000]	lr: 8.298e-05, eta: 5:02:58, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5505, decode.acc_seg: 78.9555, aux.loss_ce: 0.2911, aux.acc_seg: 73.8609, loss: 0.8416
2022-11-04 12:52:09,951 - mmseg - INFO - Iter [26950/80000]	lr: 8.291e-05, eta: 5:02:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5481, decode.acc_seg: 79.1736, aux.loss_ce: 0.2907, aux.acc_seg: 73.9208, loss: 0.8389
2022-11-04 12:52:26,735 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:52:26,735 - mmseg - INFO - Iter [27000/80000]	lr: 8.284e-05, eta: 5:02:23, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5496, decode.acc_seg: 79.1786, aux.loss_ce: 0.2948, aux.acc_seg: 74.3221, loss: 0.8444
2022-11-04 12:52:43,526 - mmseg - INFO - Iter [27050/80000]	lr: 8.277e-05, eta: 5:02:05, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5488, decode.acc_seg: 79.1946, aux.loss_ce: 0.2905, aux.acc_seg: 74.3486, loss: 0.8393
2022-11-04 12:53:00,293 - mmseg - INFO - Iter [27100/80000]	lr: 8.270e-05, eta: 5:01:47, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5731, decode.acc_seg: 78.2276, aux.loss_ce: 0.3024, aux.acc_seg: 73.1302, loss: 0.8754
2022-11-04 12:53:19,928 - mmseg - INFO - Iter [27150/80000]	lr: 8.263e-05, eta: 5:01:35, time: 0.393, data_time: 0.063, memory: 12960, decode.loss_ce: 0.5487, decode.acc_seg: 79.2176, aux.loss_ce: 0.2940, aux.acc_seg: 74.1157, loss: 0.8428
2022-11-04 12:53:36,570 - mmseg - INFO - Iter [27200/80000]	lr: 8.256e-05, eta: 5:01:17, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5482, decode.acc_seg: 79.3615, aux.loss_ce: 0.2964, aux.acc_seg: 73.8637, loss: 0.8446
2022-11-04 12:53:53,298 - mmseg - INFO - Iter [27250/80000]	lr: 8.249e-05, eta: 5:00:59, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5373, decode.acc_seg: 79.3402, aux.loss_ce: 0.2933, aux.acc_seg: 73.8555, loss: 0.8306
2022-11-04 12:54:10,009 - mmseg - INFO - Iter [27300/80000]	lr: 8.242e-05, eta: 5:00:41, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5402, decode.acc_seg: 79.2495, aux.loss_ce: 0.2895, aux.acc_seg: 73.9041, loss: 0.8298
2022-11-04 12:54:26,816 - mmseg - INFO - Iter [27350/80000]	lr: 8.235e-05, eta: 5:00:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5481, decode.acc_seg: 79.0771, aux.loss_ce: 0.2969, aux.acc_seg: 73.8214, loss: 0.8449
2022-11-04 12:54:43,588 - mmseg - INFO - Iter [27400/80000]	lr: 8.228e-05, eta: 5:00:05, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5382, decode.acc_seg: 79.5929, aux.loss_ce: 0.2849, aux.acc_seg: 74.5928, loss: 0.8231
2022-11-04 12:55:00,516 - mmseg - INFO - Iter [27450/80000]	lr: 8.221e-05, eta: 4:59:48, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5487, decode.acc_seg: 79.0727, aux.loss_ce: 0.2901, aux.acc_seg: 74.1589, loss: 0.8388
2022-11-04 12:55:17,294 - mmseg - INFO - Iter [27500/80000]	lr: 8.214e-05, eta: 4:59:30, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5474, decode.acc_seg: 78.8235, aux.loss_ce: 0.2939, aux.acc_seg: 73.5615, loss: 0.8413
2022-11-04 12:55:33,993 - mmseg - INFO - Iter [27550/80000]	lr: 8.207e-05, eta: 4:59:12, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5544, decode.acc_seg: 79.2193, aux.loss_ce: 0.2971, aux.acc_seg: 74.0349, loss: 0.8515
2022-11-04 12:55:50,639 - mmseg - INFO - Iter [27600/80000]	lr: 8.200e-05, eta: 4:58:54, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5512, decode.acc_seg: 79.2463, aux.loss_ce: 0.2980, aux.acc_seg: 73.6367, loss: 0.8491
2022-11-04 12:56:07,340 - mmseg - INFO - Iter [27650/80000]	lr: 8.193e-05, eta: 4:58:36, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5325, decode.acc_seg: 79.4112, aux.loss_ce: 0.2848, aux.acc_seg: 74.2636, loss: 0.8173
2022-11-04 12:56:23,919 - mmseg - INFO - Iter [27700/80000]	lr: 8.186e-05, eta: 4:58:18, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5400, decode.acc_seg: 79.4889, aux.loss_ce: 0.2860, aux.acc_seg: 74.9238, loss: 0.8259
2022-11-04 12:56:40,439 - mmseg - INFO - Iter [27750/80000]	lr: 8.179e-05, eta: 4:58:00, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5557, decode.acc_seg: 78.8641, aux.loss_ce: 0.2913, aux.acc_seg: 73.7681, loss: 0.8470
2022-11-04 12:57:00,092 - mmseg - INFO - Iter [27800/80000]	lr: 8.172e-05, eta: 4:57:48, time: 0.393, data_time: 0.061, memory: 12960, decode.loss_ce: 0.5409, decode.acc_seg: 79.4291, aux.loss_ce: 0.2983, aux.acc_seg: 73.3894, loss: 0.8392
2022-11-04 12:57:16,618 - mmseg - INFO - Iter [27850/80000]	lr: 8.165e-05, eta: 4:57:30, time: 0.331, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5538, decode.acc_seg: 79.0012, aux.loss_ce: 0.2963, aux.acc_seg: 73.6556, loss: 0.8501
2022-11-04 12:57:33,432 - mmseg - INFO - Iter [27900/80000]	lr: 8.158e-05, eta: 4:57:12, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5414, decode.acc_seg: 79.0963, aux.loss_ce: 0.2905, aux.acc_seg: 73.8273, loss: 0.8319
2022-11-04 12:57:50,033 - mmseg - INFO - Iter [27950/80000]	lr: 8.151e-05, eta: 4:56:54, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5403, decode.acc_seg: 79.2519, aux.loss_ce: 0.2874, aux.acc_seg: 74.2726, loss: 0.8277
2022-11-04 12:58:07,218 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 12:58:07,218 - mmseg - INFO - Iter [28000/80000]	lr: 8.143e-05, eta: 4:56:37, time: 0.344, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5643, decode.acc_seg: 78.7022, aux.loss_ce: 0.3049, aux.acc_seg: 73.1669, loss: 0.8692
2022-11-04 12:58:23,739 - mmseg - INFO - Iter [28050/80000]	lr: 8.136e-05, eta: 4:56:19, time: 0.330, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5610, decode.acc_seg: 78.8208, aux.loss_ce: 0.2993, aux.acc_seg: 73.3518, loss: 0.8603
2022-11-04 12:58:40,407 - mmseg - INFO - Iter [28100/80000]	lr: 8.129e-05, eta: 4:56:01, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5517, decode.acc_seg: 79.3339, aux.loss_ce: 0.2961, aux.acc_seg: 74.1659, loss: 0.8479
2022-11-04 12:58:57,145 - mmseg - INFO - Iter [28150/80000]	lr: 8.122e-05, eta: 4:55:43, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5485, decode.acc_seg: 78.9931, aux.loss_ce: 0.2879, aux.acc_seg: 74.0799, loss: 0.8364
2022-11-04 12:59:13,702 - mmseg - INFO - Iter [28200/80000]	lr: 8.115e-05, eta: 4:55:25, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5450, decode.acc_seg: 79.4194, aux.loss_ce: 0.2852, aux.acc_seg: 74.7841, loss: 0.8302
2022-11-04 12:59:30,458 - mmseg - INFO - Iter [28250/80000]	lr: 8.108e-05, eta: 4:55:07, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5397, decode.acc_seg: 79.3161, aux.loss_ce: 0.2895, aux.acc_seg: 74.1598, loss: 0.8292
2022-11-04 12:59:47,116 - mmseg - INFO - Iter [28300/80000]	lr: 8.101e-05, eta: 4:54:49, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5377, decode.acc_seg: 79.4395, aux.loss_ce: 0.2866, aux.acc_seg: 74.3964, loss: 0.8242
2022-11-04 13:00:03,699 - mmseg - INFO - Iter [28350/80000]	lr: 8.094e-05, eta: 4:54:31, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5529, decode.acc_seg: 78.8577, aux.loss_ce: 0.2934, aux.acc_seg: 73.4112, loss: 0.8463
2022-11-04 13:00:23,417 - mmseg - INFO - Iter [28400/80000]	lr: 8.087e-05, eta: 4:54:19, time: 0.394, data_time: 0.070, memory: 12960, decode.loss_ce: 0.5440, decode.acc_seg: 78.9337, aux.loss_ce: 0.2923, aux.acc_seg: 73.5772, loss: 0.8363
2022-11-04 13:00:40,254 - mmseg - INFO - Iter [28450/80000]	lr: 8.080e-05, eta: 4:54:01, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5266, decode.acc_seg: 79.5312, aux.loss_ce: 0.2825, aux.acc_seg: 74.2218, loss: 0.8091
2022-11-04 13:00:56,770 - mmseg - INFO - Iter [28500/80000]	lr: 8.073e-05, eta: 4:53:43, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5181, decode.acc_seg: 80.0309, aux.loss_ce: 0.2792, aux.acc_seg: 75.1639, loss: 0.7973
2022-11-04 13:01:13,476 - mmseg - INFO - Iter [28550/80000]	lr: 8.066e-05, eta: 4:53:25, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5377, decode.acc_seg: 79.1144, aux.loss_ce: 0.2927, aux.acc_seg: 73.5124, loss: 0.8304
2022-11-04 13:01:30,217 - mmseg - INFO - Iter [28600/80000]	lr: 8.059e-05, eta: 4:53:07, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5420, decode.acc_seg: 79.3493, aux.loss_ce: 0.2891, aux.acc_seg: 74.2841, loss: 0.8312
2022-11-04 13:01:46,706 - mmseg - INFO - Iter [28650/80000]	lr: 8.052e-05, eta: 4:52:49, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5339, decode.acc_seg: 79.6135, aux.loss_ce: 0.2909, aux.acc_seg: 73.9171, loss: 0.8248
2022-11-04 13:02:03,257 - mmseg - INFO - Iter [28700/80000]	lr: 8.045e-05, eta: 4:52:31, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5318, decode.acc_seg: 79.3423, aux.loss_ce: 0.2883, aux.acc_seg: 73.7618, loss: 0.8201
2022-11-04 13:02:20,036 - mmseg - INFO - Iter [28750/80000]	lr: 8.038e-05, eta: 4:52:13, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5274, decode.acc_seg: 80.0483, aux.loss_ce: 0.2858, aux.acc_seg: 74.4494, loss: 0.8132
2022-11-04 13:02:36,788 - mmseg - INFO - Iter [28800/80000]	lr: 8.031e-05, eta: 4:51:55, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5378, decode.acc_seg: 79.7006, aux.loss_ce: 0.2875, aux.acc_seg: 74.4157, loss: 0.8253
2022-11-04 13:02:53,497 - mmseg - INFO - Iter [28850/80000]	lr: 8.024e-05, eta: 4:51:38, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5449, decode.acc_seg: 79.2333, aux.loss_ce: 0.2933, aux.acc_seg: 74.2431, loss: 0.8382
2022-11-04 13:03:10,109 - mmseg - INFO - Iter [28900/80000]	lr: 8.017e-05, eta: 4:51:20, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5464, decode.acc_seg: 78.8218, aux.loss_ce: 0.2877, aux.acc_seg: 73.7843, loss: 0.8341
2022-11-04 13:03:26,778 - mmseg - INFO - Iter [28950/80000]	lr: 8.009e-05, eta: 4:51:02, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5251, decode.acc_seg: 79.9968, aux.loss_ce: 0.2840, aux.acc_seg: 74.7799, loss: 0.8091
2022-11-04 13:03:43,491 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:03:43,491 - mmseg - INFO - Iter [29000/80000]	lr: 8.002e-05, eta: 4:50:44, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5388, decode.acc_seg: 79.2680, aux.loss_ce: 0.2908, aux.acc_seg: 73.9557, loss: 0.8297
2022-11-04 13:04:03,030 - mmseg - INFO - Iter [29050/80000]	lr: 7.995e-05, eta: 4:50:31, time: 0.391, data_time: 0.062, memory: 12960, decode.loss_ce: 0.5420, decode.acc_seg: 79.4427, aux.loss_ce: 0.2920, aux.acc_seg: 73.8426, loss: 0.8340
2022-11-04 13:04:20,018 - mmseg - INFO - Iter [29100/80000]	lr: 7.988e-05, eta: 4:50:14, time: 0.340, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5247, decode.acc_seg: 79.6640, aux.loss_ce: 0.2815, aux.acc_seg: 74.4155, loss: 0.8062
2022-11-04 13:04:36,569 - mmseg - INFO - Iter [29150/80000]	lr: 7.981e-05, eta: 4:49:56, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5293, decode.acc_seg: 79.8043, aux.loss_ce: 0.2837, aux.acc_seg: 74.5560, loss: 0.8130
2022-11-04 13:04:53,356 - mmseg - INFO - Iter [29200/80000]	lr: 7.974e-05, eta: 4:49:38, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5099, decode.acc_seg: 80.1794, aux.loss_ce: 0.2778, aux.acc_seg: 74.9428, loss: 0.7877
2022-11-04 13:05:10,084 - mmseg - INFO - Iter [29250/80000]	lr: 7.967e-05, eta: 4:49:20, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5412, decode.acc_seg: 79.4103, aux.loss_ce: 0.2874, aux.acc_seg: 74.4292, loss: 0.8286
2022-11-04 13:05:26,888 - mmseg - INFO - Iter [29300/80000]	lr: 7.960e-05, eta: 4:49:03, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5500, decode.acc_seg: 78.8609, aux.loss_ce: 0.2974, aux.acc_seg: 73.0530, loss: 0.8474
2022-11-04 13:05:43,607 - mmseg - INFO - Iter [29350/80000]	lr: 7.953e-05, eta: 4:48:45, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5168, decode.acc_seg: 80.3750, aux.loss_ce: 0.2762, aux.acc_seg: 75.4539, loss: 0.7930
2022-11-04 13:06:00,423 - mmseg - INFO - Iter [29400/80000]	lr: 7.946e-05, eta: 4:48:27, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5197, decode.acc_seg: 80.5765, aux.loss_ce: 0.2863, aux.acc_seg: 74.7996, loss: 0.8060
2022-11-04 13:06:17,075 - mmseg - INFO - Iter [29450/80000]	lr: 7.939e-05, eta: 4:48:09, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5256, decode.acc_seg: 79.8132, aux.loss_ce: 0.2872, aux.acc_seg: 74.0450, loss: 0.8128
2022-11-04 13:06:33,769 - mmseg - INFO - Iter [29500/80000]	lr: 7.932e-05, eta: 4:47:52, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5361, decode.acc_seg: 79.3890, aux.loss_ce: 0.2888, aux.acc_seg: 74.1426, loss: 0.8248
2022-11-04 13:06:50,310 - mmseg - INFO - Iter [29550/80000]	lr: 7.925e-05, eta: 4:47:34, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5549, decode.acc_seg: 78.7578, aux.loss_ce: 0.2942, aux.acc_seg: 73.6333, loss: 0.8491
2022-11-04 13:07:07,063 - mmseg - INFO - Iter [29600/80000]	lr: 7.918e-05, eta: 4:47:16, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5360, decode.acc_seg: 79.3081, aux.loss_ce: 0.2867, aux.acc_seg: 73.8604, loss: 0.8227
2022-11-04 13:07:24,157 - mmseg - INFO - Iter [29650/80000]	lr: 7.911e-05, eta: 4:46:59, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5427, decode.acc_seg: 79.2500, aux.loss_ce: 0.2884, aux.acc_seg: 74.2530, loss: 0.8312
2022-11-04 13:07:43,715 - mmseg - INFO - Iter [29700/80000]	lr: 7.903e-05, eta: 4:46:46, time: 0.391, data_time: 0.068, memory: 12960, decode.loss_ce: 0.5369, decode.acc_seg: 79.4091, aux.loss_ce: 0.2925, aux.acc_seg: 73.8510, loss: 0.8294
2022-11-04 13:08:00,522 - mmseg - INFO - Iter [29750/80000]	lr: 7.896e-05, eta: 4:46:28, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5099, decode.acc_seg: 80.6802, aux.loss_ce: 0.2782, aux.acc_seg: 75.0266, loss: 0.7881
2022-11-04 13:08:17,356 - mmseg - INFO - Iter [29800/80000]	lr: 7.889e-05, eta: 4:46:11, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5273, decode.acc_seg: 79.7583, aux.loss_ce: 0.2855, aux.acc_seg: 74.0507, loss: 0.8128
2022-11-04 13:08:34,098 - mmseg - INFO - Iter [29850/80000]	lr: 7.882e-05, eta: 4:45:53, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5298, decode.acc_seg: 79.5457, aux.loss_ce: 0.2864, aux.acc_seg: 73.9690, loss: 0.8162
2022-11-04 13:08:50,747 - mmseg - INFO - Iter [29900/80000]	lr: 7.875e-05, eta: 4:45:35, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5289, decode.acc_seg: 80.1550, aux.loss_ce: 0.2862, aux.acc_seg: 74.8918, loss: 0.8151
2022-11-04 13:09:07,235 - mmseg - INFO - Iter [29950/80000]	lr: 7.868e-05, eta: 4:45:17, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5404, decode.acc_seg: 79.5101, aux.loss_ce: 0.2882, aux.acc_seg: 74.2916, loss: 0.8286
2022-11-04 13:09:23,993 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:09:23,993 - mmseg - INFO - Iter [30000/80000]	lr: 7.861e-05, eta: 4:44:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5291, decode.acc_seg: 79.6131, aux.loss_ce: 0.2854, aux.acc_seg: 74.0512, loss: 0.8144
2022-11-04 13:09:40,429 - mmseg - INFO - Iter [30050/80000]	lr: 7.854e-05, eta: 4:44:41, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5363, decode.acc_seg: 79.4968, aux.loss_ce: 0.2943, aux.acc_seg: 73.5289, loss: 0.8306
2022-11-04 13:09:57,260 - mmseg - INFO - Iter [30100/80000]	lr: 7.847e-05, eta: 4:44:24, time: 0.337, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5368, decode.acc_seg: 79.2213, aux.loss_ce: 0.2853, aux.acc_seg: 73.8790, loss: 0.8221
2022-11-04 13:10:13,793 - mmseg - INFO - Iter [30150/80000]	lr: 7.840e-05, eta: 4:44:06, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5368, decode.acc_seg: 79.3262, aux.loss_ce: 0.2978, aux.acc_seg: 73.2568, loss: 0.8346
2022-11-04 13:10:30,466 - mmseg - INFO - Iter [30200/80000]	lr: 7.833e-05, eta: 4:43:48, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5378, decode.acc_seg: 79.6101, aux.loss_ce: 0.2910, aux.acc_seg: 74.0143, loss: 0.8288
2022-11-04 13:10:47,175 - mmseg - INFO - Iter [30250/80000]	lr: 7.826e-05, eta: 4:43:30, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5322, decode.acc_seg: 79.9824, aux.loss_ce: 0.2870, aux.acc_seg: 74.6536, loss: 0.8192
2022-11-04 13:11:07,016 - mmseg - INFO - Iter [30300/80000]	lr: 7.819e-05, eta: 4:43:17, time: 0.397, data_time: 0.065, memory: 12960, decode.loss_ce: 0.5351, decode.acc_seg: 79.4130, aux.loss_ce: 0.2890, aux.acc_seg: 73.7570, loss: 0.8241
2022-11-04 13:11:23,659 - mmseg - INFO - Iter [30350/80000]	lr: 7.812e-05, eta: 4:43:00, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5286, decode.acc_seg: 80.1822, aux.loss_ce: 0.2890, aux.acc_seg: 74.5276, loss: 0.8177
2022-11-04 13:11:40,723 - mmseg - INFO - Iter [30400/80000]	lr: 7.804e-05, eta: 4:42:42, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5138, decode.acc_seg: 80.0547, aux.loss_ce: 0.2750, aux.acc_seg: 75.1230, loss: 0.7888
2022-11-04 13:11:57,479 - mmseg - INFO - Iter [30450/80000]	lr: 7.797e-05, eta: 4:42:25, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5136, decode.acc_seg: 80.1806, aux.loss_ce: 0.2782, aux.acc_seg: 75.0061, loss: 0.7918
2022-11-04 13:12:14,286 - mmseg - INFO - Iter [30500/80000]	lr: 7.790e-05, eta: 4:42:07, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5269, decode.acc_seg: 79.7960, aux.loss_ce: 0.2789, aux.acc_seg: 74.8716, loss: 0.8058
2022-11-04 13:12:30,908 - mmseg - INFO - Iter [30550/80000]	lr: 7.783e-05, eta: 4:41:49, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5360, decode.acc_seg: 79.3757, aux.loss_ce: 0.2899, aux.acc_seg: 74.0013, loss: 0.8259
2022-11-04 13:12:47,592 - mmseg - INFO - Iter [30600/80000]	lr: 7.776e-05, eta: 4:41:32, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5228, decode.acc_seg: 79.8885, aux.loss_ce: 0.2825, aux.acc_seg: 74.6302, loss: 0.8053
2022-11-04 13:13:04,305 - mmseg - INFO - Iter [30650/80000]	lr: 7.769e-05, eta: 4:41:14, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5240, decode.acc_seg: 80.1109, aux.loss_ce: 0.2884, aux.acc_seg: 74.4628, loss: 0.8124
2022-11-04 13:13:21,015 - mmseg - INFO - Iter [30700/80000]	lr: 7.762e-05, eta: 4:40:56, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5415, decode.acc_seg: 79.1746, aux.loss_ce: 0.2915, aux.acc_seg: 74.1528, loss: 0.8330
2022-11-04 13:13:37,535 - mmseg - INFO - Iter [30750/80000]	lr: 7.755e-05, eta: 4:40:38, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5231, decode.acc_seg: 79.8787, aux.loss_ce: 0.2826, aux.acc_seg: 74.6286, loss: 0.8057
2022-11-04 13:13:53,912 - mmseg - INFO - Iter [30800/80000]	lr: 7.748e-05, eta: 4:40:20, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5267, decode.acc_seg: 79.9053, aux.loss_ce: 0.2837, aux.acc_seg: 74.6591, loss: 0.8104
2022-11-04 13:14:10,521 - mmseg - INFO - Iter [30850/80000]	lr: 7.741e-05, eta: 4:40:02, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5278, decode.acc_seg: 79.6309, aux.loss_ce: 0.2913, aux.acc_seg: 73.8605, loss: 0.8191
2022-11-04 13:14:27,294 - mmseg - INFO - Iter [30900/80000]	lr: 7.734e-05, eta: 4:39:44, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5346, decode.acc_seg: 80.2140, aux.loss_ce: 0.2863, aux.acc_seg: 75.0723, loss: 0.8209
2022-11-04 13:14:46,892 - mmseg - INFO - Iter [30950/80000]	lr: 7.727e-05, eta: 4:39:31, time: 0.392, data_time: 0.069, memory: 12960, decode.loss_ce: 0.5235, decode.acc_seg: 79.8517, aux.loss_ce: 0.2886, aux.acc_seg: 74.3984, loss: 0.8121
2022-11-04 13:15:03,439 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:15:03,440 - mmseg - INFO - Iter [31000/80000]	lr: 7.719e-05, eta: 4:39:13, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5055, decode.acc_seg: 80.5515, aux.loss_ce: 0.2746, aux.acc_seg: 75.3169, loss: 0.7801
2022-11-04 13:15:20,241 - mmseg - INFO - Iter [31050/80000]	lr: 7.712e-05, eta: 4:38:56, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5338, decode.acc_seg: 79.5698, aux.loss_ce: 0.2859, aux.acc_seg: 74.3834, loss: 0.8197
2022-11-04 13:15:36,887 - mmseg - INFO - Iter [31100/80000]	lr: 7.705e-05, eta: 4:38:38, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5265, decode.acc_seg: 79.4332, aux.loss_ce: 0.2833, aux.acc_seg: 74.5280, loss: 0.8098
2022-11-04 13:15:53,694 - mmseg - INFO - Iter [31150/80000]	lr: 7.698e-05, eta: 4:38:20, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5189, decode.acc_seg: 80.2939, aux.loss_ce: 0.2791, aux.acc_seg: 75.0160, loss: 0.7980
2022-11-04 13:16:10,249 - mmseg - INFO - Iter [31200/80000]	lr: 7.691e-05, eta: 4:38:02, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5175, decode.acc_seg: 79.8269, aux.loss_ce: 0.2815, aux.acc_seg: 74.3567, loss: 0.7990
2022-11-04 13:16:26,917 - mmseg - INFO - Iter [31250/80000]	lr: 7.684e-05, eta: 4:37:45, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5451, decode.acc_seg: 79.2918, aux.loss_ce: 0.2980, aux.acc_seg: 73.8374, loss: 0.8431
2022-11-04 13:16:43,458 - mmseg - INFO - Iter [31300/80000]	lr: 7.677e-05, eta: 4:37:27, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5200, decode.acc_seg: 79.8154, aux.loss_ce: 0.2792, aux.acc_seg: 74.3706, loss: 0.7992
2022-11-04 13:17:00,298 - mmseg - INFO - Iter [31350/80000]	lr: 7.670e-05, eta: 4:37:09, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5389, decode.acc_seg: 79.4922, aux.loss_ce: 0.2944, aux.acc_seg: 73.9163, loss: 0.8333
2022-11-04 13:17:17,282 - mmseg - INFO - Iter [31400/80000]	lr: 7.663e-05, eta: 4:36:52, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5323, decode.acc_seg: 79.6153, aux.loss_ce: 0.2885, aux.acc_seg: 74.1153, loss: 0.8208
2022-11-04 13:17:34,159 - mmseg - INFO - Iter [31450/80000]	lr: 7.656e-05, eta: 4:36:35, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5293, decode.acc_seg: 79.7121, aux.loss_ce: 0.2845, aux.acc_seg: 74.5303, loss: 0.8138
2022-11-04 13:17:50,850 - mmseg - INFO - Iter [31500/80000]	lr: 7.648e-05, eta: 4:36:17, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5105, decode.acc_seg: 80.2686, aux.loss_ce: 0.2768, aux.acc_seg: 75.0580, loss: 0.7873
2022-11-04 13:18:07,251 - mmseg - INFO - Iter [31550/80000]	lr: 7.641e-05, eta: 4:35:59, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5166, decode.acc_seg: 80.3291, aux.loss_ce: 0.2855, aux.acc_seg: 74.6972, loss: 0.8021
2022-11-04 13:18:27,193 - mmseg - INFO - Iter [31600/80000]	lr: 7.634e-05, eta: 4:35:46, time: 0.399, data_time: 0.066, memory: 12960, decode.loss_ce: 0.5128, decode.acc_seg: 80.4088, aux.loss_ce: 0.2783, aux.acc_seg: 75.0730, loss: 0.7911
2022-11-04 13:18:44,119 - mmseg - INFO - Iter [31650/80000]	lr: 7.627e-05, eta: 4:35:29, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5265, decode.acc_seg: 79.9941, aux.loss_ce: 0.2866, aux.acc_seg: 74.4264, loss: 0.8131
2022-11-04 13:19:00,845 - mmseg - INFO - Iter [31700/80000]	lr: 7.620e-05, eta: 4:35:11, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5236, decode.acc_seg: 80.0998, aux.loss_ce: 0.2826, aux.acc_seg: 74.7602, loss: 0.8062
2022-11-04 13:19:17,481 - mmseg - INFO - Iter [31750/80000]	lr: 7.613e-05, eta: 4:34:53, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5096, decode.acc_seg: 80.5803, aux.loss_ce: 0.2793, aux.acc_seg: 74.6738, loss: 0.7889
2022-11-04 13:19:34,050 - mmseg - INFO - Iter [31800/80000]	lr: 7.606e-05, eta: 4:34:35, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5127, decode.acc_seg: 80.3958, aux.loss_ce: 0.2773, aux.acc_seg: 75.0293, loss: 0.7900
2022-11-04 13:19:50,741 - mmseg - INFO - Iter [31850/80000]	lr: 7.599e-05, eta: 4:34:18, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5214, decode.acc_seg: 80.1632, aux.loss_ce: 0.2800, aux.acc_seg: 74.4543, loss: 0.8013
2022-11-04 13:20:07,411 - mmseg - INFO - Iter [31900/80000]	lr: 7.592e-05, eta: 4:34:00, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5350, decode.acc_seg: 79.5964, aux.loss_ce: 0.2856, aux.acc_seg: 74.5940, loss: 0.8205
2022-11-04 13:20:24,118 - mmseg - INFO - Iter [31950/80000]	lr: 7.585e-05, eta: 4:33:42, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5193, decode.acc_seg: 80.2724, aux.loss_ce: 0.2811, aux.acc_seg: 75.0672, loss: 0.8004
2022-11-04 13:20:40,645 - mmseg - INFO - Saving checkpoint at 32000 iterations
2022-11-04 13:20:40,875 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:20:40,876 - mmseg - INFO - Iter [32000/80000]	lr: 7.577e-05, eta: 4:33:25, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5187, decode.acc_seg: 80.2954, aux.loss_ce: 0.2807, aux.acc_seg: 75.1897, loss: 0.7994
2022-11-04 13:20:49,807 - mmseg - INFO - per class results:
2022-11-04 13:20:49,814 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 65.87 | 81.82 |
|       building      | 75.33 | 90.05 |
|         sky         | 89.08 | 93.16 |
|        floor        | 70.66 |  84.6 |
|         tree        | 67.12 | 82.51 |
|       ceiling       | 75.41 | 85.58 |
|         road        | 75.29 | 84.87 |
|         bed         | 74.18 | 91.03 |
|      windowpane     | 49.27 | 65.71 |
|        grass        | 65.15 | 84.13 |
|       cabinet       | 46.65 |  63.2 |
|       sidewalk      | 51.16 |  68.9 |
|        person       | 63.92 | 83.46 |
|        earth        | 29.35 | 42.08 |
|         door        |  24.7 | 38.09 |
|        table        | 39.52 | 56.96 |
|       mountain      |  54.6 | 74.04 |
|        plant        | 44.97 | 56.81 |
|       curtain       | 54.96 | 70.73 |
|        chair        | 36.39 | 51.98 |
|         car         | 69.59 | 85.01 |
|        water        | 41.83 | 55.88 |
|       painting      | 55.01 | 71.58 |
|         sofa        | 49.57 | 71.96 |
|        shelf        | 29.45 | 42.56 |
|        house        | 42.28 | 58.92 |
|         sea         | 36.76 | 64.24 |
|        mirror       | 35.21 | 39.87 |
|         rug         | 44.08 | 51.62 |
|        field        | 33.64 | 46.31 |
|       armchair      |  27.1 |  39.5 |
|         seat        | 50.68 | 68.11 |
|        fence        | 23.05 |  42.2 |
|         desk        | 33.21 | 52.59 |
|         rock        | 37.78 | 62.34 |
|       wardrobe      | 33.18 | 49.19 |
|         lamp        | 34.69 | 45.83 |
|       bathtub       |  53.2 | 69.83 |
|       railing       | 25.23 | 34.38 |
|       cushion       | 29.58 |  38.6 |
|         base        |  24.7 |  39.2 |
|         box         | 14.67 | 22.65 |
|        column       | 30.98 | 40.97 |
|      signboard      | 24.59 | 34.58 |
|   chest of drawers  | 25.15 | 36.56 |
|       counter       | 25.28 | 29.52 |
|         sand        | 22.86 | 34.18 |
|         sink        | 44.47 | 54.19 |
|      skyscraper     | 58.99 | 74.99 |
|      fireplace      | 50.04 | 72.56 |
|     refrigerator    | 49.26 | 68.38 |
|      grandstand     | 45.67 | 66.17 |
|         path        |  8.63 | 11.42 |
|        stairs       | 24.17 | 32.78 |
|        runway       |  74.5 | 92.86 |
|         case        | 39.82 | 59.71 |
|      pool table     | 78.44 | 87.47 |
|        pillow       | 38.08 | 48.87 |
|     screen door     |  40.1 | 53.22 |
|       stairway      | 23.89 | 28.94 |
|        river        | 19.74 |  39.8 |
|        bridge       | 41.51 | 62.49 |
|       bookcase      | 26.44 | 43.85 |
|        blind        |  24.2 | 27.96 |
|     coffee table    |  38.8 | 71.11 |
|        toilet       | 63.82 | 73.81 |
|        flower       | 22.15 | 36.53 |
|         book        | 35.15 | 48.98 |
|         hill        |  2.89 |  3.88 |
|        bench        |  34.0 | 45.67 |
|      countertop     | 43.92 | 55.44 |
|        stove        | 33.21 | 37.26 |
|         palm        | 36.92 | 49.25 |
|    kitchen island   |  16.9 | 40.62 |
|       computer      | 42.28 | 57.42 |
|     swivel chair    | 28.05 | 37.94 |
|         boat        | 48.51 | 67.38 |
|         bar         | 23.66 | 30.73 |
|    arcade machine   | 38.13 | 42.23 |
|        hovel        | 28.46 | 48.25 |
|         bus         |  69.9 | 81.33 |
|        towel        | 33.01 | 46.07 |
|        light        | 11.79 | 12.67 |
|        truck        |  4.06 |  5.42 |
|        tower        | 40.67 | 48.83 |
|      chandelier     | 44.71 | 57.35 |
|        awning       | 15.24 | 17.88 |
|     streetlight     |  4.58 |  5.5  |
|        booth        | 29.95 | 37.53 |
| television receiver | 35.91 | 62.55 |
|       airplane      | 42.68 | 52.29 |
|      dirt track     |  3.61 | 15.53 |
|       apparel       | 14.19 | 22.47 |
|         pole        |  5.37 |  7.97 |
|         land        |  0.81 |  1.33 |
|      bannister      |  1.17 |  1.79 |
|      escalator      | 33.08 | 34.41 |
|       ottoman       | 22.13 | 25.67 |
|        bottle       |  7.5  |  8.61 |
|        buffet       | 30.84 | 35.25 |
|        poster       | 13.67 | 16.06 |
|        stage        | 10.82 | 14.43 |
|         van         | 11.14 | 12.61 |
|         ship        |  20.8 | 21.48 |
|       fountain      | 17.44 | 17.89 |
|    conveyer belt    | 56.35 | 70.12 |
|        canopy       | 26.83 | 41.34 |
|        washer       |  48.7 | 56.79 |
|      plaything      |  5.68 | 10.62 |
|    swimming pool    | 40.01 | 67.51 |
|        stool        | 10.02 | 11.16 |
|        barrel       |  8.85 | 63.45 |
|        basket       |  16.0 | 22.84 |
|      waterfall      |  44.7 | 63.98 |
|         tent        | 82.67 | 97.11 |
|         bag         |  1.68 |  1.89 |
|       minibike      | 37.77 | 47.07 |
|        cradle       | 55.13 | 79.17 |
|         oven        | 13.11 | 30.46 |
|         ball        | 10.73 | 12.88 |
|         food        | 42.51 | 62.05 |
|         step        |  2.99 |  3.13 |
|         tank        | 27.07 | 28.69 |
|      trade name     | 16.69 | 18.76 |
|      microwave      |  23.4 | 26.75 |
|         pot         | 11.72 | 13.52 |
|        animal       | 40.17 | 44.92 |
|       bicycle       | 32.03 | 55.05 |
|         lake        |  0.0  |  0.0  |
|      dishwasher     | 26.48 | 37.36 |
|        screen       | 52.78 | 72.92 |
|       blanket       |  0.75 |  0.85 |
|      sculpture      | 32.58 | 51.48 |
|         hood        | 24.63 | 27.83 |
|        sconce       |  8.57 |  8.95 |
|         vase        | 14.81 | 21.36 |
|    traffic light    |  6.9  |  8.39 |
|         tray        |  3.78 |  5.03 |
|        ashcan       | 17.79 |  23.9 |
|         fan         | 24.11 | 30.23 |
|         pier        | 19.03 |  29.6 |
|      crt screen     |  0.0  |  0.0  |
|        plate        | 32.34 | 44.23 |
|       monitor       | 49.19 | 66.65 |
|    bulletin board   | 35.06 | 43.68 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 33.04 | 37.49 |
|        glass        |  0.04 |  0.04 |
|        clock        |  5.63 |  6.15 |
|         flag        | 13.28 | 14.13 |
+---------------------+-------+-------+
2022-11-04 13:20:49,815 - mmseg - INFO - Summary:
2022-11-04 13:20:49,815 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 74.86 | 32.75 | 43.82 |
+-------+-------+-------+
2022-11-04 13:20:49,816 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:20:49,817 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7486, mIoU: 0.3275, mAcc: 0.4382, IoU.wall: 0.6587, IoU.building: 0.7533, IoU.sky: 0.8908, IoU.floor: 0.7066, IoU.tree: 0.6712, IoU.ceiling: 0.7541, IoU.road: 0.7529, IoU.bed : 0.7418, IoU.windowpane: 0.4927, IoU.grass: 0.6515, IoU.cabinet: 0.4665, IoU.sidewalk: 0.5116, IoU.person: 0.6392, IoU.earth: 0.2935, IoU.door: 0.2470, IoU.table: 0.3952, IoU.mountain: 0.5460, IoU.plant: 0.4497, IoU.curtain: 0.5496, IoU.chair: 0.3639, IoU.car: 0.6959, IoU.water: 0.4183, IoU.painting: 0.5501, IoU.sofa: 0.4957, IoU.shelf: 0.2945, IoU.house: 0.4228, IoU.sea: 0.3676, IoU.mirror: 0.3521, IoU.rug: 0.4408, IoU.field: 0.3364, IoU.armchair: 0.2710, IoU.seat: 0.5068, IoU.fence: 0.2305, IoU.desk: 0.3321, IoU.rock: 0.3778, IoU.wardrobe: 0.3318, IoU.lamp: 0.3469, IoU.bathtub: 0.5320, IoU.railing: 0.2523, IoU.cushion: 0.2958, IoU.base: 0.2470, IoU.box: 0.1467, IoU.column: 0.3098, IoU.signboard: 0.2459, IoU.chest of drawers: 0.2515, IoU.counter: 0.2528, IoU.sand: 0.2286, IoU.sink: 0.4447, IoU.skyscraper: 0.5899, IoU.fireplace: 0.5004, IoU.refrigerator: 0.4926, IoU.grandstand: 0.4567, IoU.path: 0.0863, IoU.stairs: 0.2417, IoU.runway: 0.7450, IoU.case: 0.3982, IoU.pool table: 0.7844, IoU.pillow: 0.3808, IoU.screen door: 0.4010, IoU.stairway: 0.2389, IoU.river: 0.1974, IoU.bridge: 0.4151, IoU.bookcase: 0.2644, IoU.blind: 0.2420, IoU.coffee table: 0.3880, IoU.toilet: 0.6382, IoU.flower: 0.2215, IoU.book: 0.3515, IoU.hill: 0.0289, IoU.bench: 0.3400, IoU.countertop: 0.4392, IoU.stove: 0.3321, IoU.palm: 0.3692, IoU.kitchen island: 0.1690, IoU.computer: 0.4228, IoU.swivel chair: 0.2805, IoU.boat: 0.4851, IoU.bar: 0.2366, IoU.arcade machine: 0.3813, IoU.hovel: 0.2846, IoU.bus: 0.6990, IoU.towel: 0.3301, IoU.light: 0.1179, IoU.truck: 0.0406, IoU.tower: 0.4067, IoU.chandelier: 0.4471, IoU.awning: 0.1524, IoU.streetlight: 0.0458, IoU.booth: 0.2995, IoU.television receiver: 0.3591, IoU.airplane: 0.4268, IoU.dirt track: 0.0361, IoU.apparel: 0.1419, IoU.pole: 0.0537, IoU.land: 0.0081, IoU.bannister: 0.0117, IoU.escalator: 0.3308, IoU.ottoman: 0.2213, IoU.bottle: 0.0750, IoU.buffet: 0.3084, IoU.poster: 0.1367, IoU.stage: 0.1082, IoU.van: 0.1114, IoU.ship: 0.2080, IoU.fountain: 0.1744, IoU.conveyer belt: 0.5635, IoU.canopy: 0.2683, IoU.washer: 0.4870, IoU.plaything: 0.0568, IoU.swimming pool: 0.4001, IoU.stool: 0.1002, IoU.barrel: 0.0885, IoU.basket: 0.1600, IoU.waterfall: 0.4470, IoU.tent: 0.8267, IoU.bag: 0.0168, IoU.minibike: 0.3777, IoU.cradle: 0.5513, IoU.oven: 0.1311, IoU.ball: 0.1073, IoU.food: 0.4251, IoU.step: 0.0299, IoU.tank: 0.2707, IoU.trade name: 0.1669, IoU.microwave: 0.2340, IoU.pot: 0.1172, IoU.animal: 0.4017, IoU.bicycle: 0.3203, IoU.lake: 0.0000, IoU.dishwasher: 0.2648, IoU.screen: 0.5278, IoU.blanket: 0.0075, IoU.sculpture: 0.3258, IoU.hood: 0.2463, IoU.sconce: 0.0857, IoU.vase: 0.1481, IoU.traffic light: 0.0690, IoU.tray: 0.0378, IoU.ashcan: 0.1779, IoU.fan: 0.2411, IoU.pier: 0.1903, IoU.crt screen: 0.0000, IoU.plate: 0.3234, IoU.monitor: 0.4919, IoU.bulletin board: 0.3506, IoU.shower: 0.0000, IoU.radiator: 0.3304, IoU.glass: 0.0004, IoU.clock: 0.0563, IoU.flag: 0.1328, Acc.wall: 0.8182, Acc.building: 0.9005, Acc.sky: 0.9316, Acc.floor: 0.8460, Acc.tree: 0.8251, Acc.ceiling: 0.8558, Acc.road: 0.8487, Acc.bed : 0.9103, Acc.windowpane: 0.6571, Acc.grass: 0.8413, Acc.cabinet: 0.6320, Acc.sidewalk: 0.6890, Acc.person: 0.8346, Acc.earth: 0.4208, Acc.door: 0.3809, Acc.table: 0.5696, Acc.mountain: 0.7404, Acc.plant: 0.5681, Acc.curtain: 0.7073, Acc.chair: 0.5198, Acc.car: 0.8501, Acc.water: 0.5588, Acc.painting: 0.7158, Acc.sofa: 0.7196, Acc.shelf: 0.4256, Acc.house: 0.5892, Acc.sea: 0.6424, Acc.mirror: 0.3987, Acc.rug: 0.5162, Acc.field: 0.4631, Acc.armchair: 0.3950, Acc.seat: 0.6811, Acc.fence: 0.4220, Acc.desk: 0.5259, Acc.rock: 0.6234, Acc.wardrobe: 0.4919, Acc.lamp: 0.4583, Acc.bathtub: 0.6983, Acc.railing: 0.3438, Acc.cushion: 0.3860, Acc.base: 0.3920, Acc.box: 0.2265, Acc.column: 0.4097, Acc.signboard: 0.3458, Acc.chest of drawers: 0.3656, Acc.counter: 0.2952, Acc.sand: 0.3418, Acc.sink: 0.5419, Acc.skyscraper: 0.7499, Acc.fireplace: 0.7256, Acc.refrigerator: 0.6838, Acc.grandstand: 0.6617, Acc.path: 0.1142, Acc.stairs: 0.3278, Acc.runway: 0.9286, Acc.case: 0.5971, Acc.pool table: 0.8747, Acc.pillow: 0.4887, Acc.screen door: 0.5322, Acc.stairway: 0.2894, Acc.river: 0.3980, Acc.bridge: 0.6249, Acc.bookcase: 0.4385, Acc.blind: 0.2796, Acc.coffee table: 0.7111, Acc.toilet: 0.7381, Acc.flower: 0.3653, Acc.book: 0.4898, Acc.hill: 0.0388, Acc.bench: 0.4567, Acc.countertop: 0.5544, Acc.stove: 0.3726, Acc.palm: 0.4925, Acc.kitchen island: 0.4062, Acc.computer: 0.5742, Acc.swivel chair: 0.3794, Acc.boat: 0.6738, Acc.bar: 0.3073, Acc.arcade machine: 0.4223, Acc.hovel: 0.4825, Acc.bus: 0.8133, Acc.towel: 0.4607, Acc.light: 0.1267, Acc.truck: 0.0542, Acc.tower: 0.4883, Acc.chandelier: 0.5735, Acc.awning: 0.1788, Acc.streetlight: 0.0550, Acc.booth: 0.3753, Acc.television receiver: 0.6255, Acc.airplane: 0.5229, Acc.dirt track: 0.1553, Acc.apparel: 0.2247, Acc.pole: 0.0797, Acc.land: 0.0133, Acc.bannister: 0.0179, Acc.escalator: 0.3441, Acc.ottoman: 0.2567, Acc.bottle: 0.0861, Acc.buffet: 0.3525, Acc.poster: 0.1606, Acc.stage: 0.1443, Acc.van: 0.1261, Acc.ship: 0.2148, Acc.fountain: 0.1789, Acc.conveyer belt: 0.7012, Acc.canopy: 0.4134, Acc.washer: 0.5679, Acc.plaything: 0.1062, Acc.swimming pool: 0.6751, Acc.stool: 0.1116, Acc.barrel: 0.6345, Acc.basket: 0.2284, Acc.waterfall: 0.6398, Acc.tent: 0.9711, Acc.bag: 0.0189, Acc.minibike: 0.4707, Acc.cradle: 0.7917, Acc.oven: 0.3046, Acc.ball: 0.1288, Acc.food: 0.6205, Acc.step: 0.0313, Acc.tank: 0.2869, Acc.trade name: 0.1876, Acc.microwave: 0.2675, Acc.pot: 0.1352, Acc.animal: 0.4492, Acc.bicycle: 0.5505, Acc.lake: 0.0000, Acc.dishwasher: 0.3736, Acc.screen: 0.7292, Acc.blanket: 0.0085, Acc.sculpture: 0.5148, Acc.hood: 0.2783, Acc.sconce: 0.0895, Acc.vase: 0.2136, Acc.traffic light: 0.0839, Acc.tray: 0.0503, Acc.ashcan: 0.2390, Acc.fan: 0.3023, Acc.pier: 0.2960, Acc.crt screen: 0.0000, Acc.plate: 0.4423, Acc.monitor: 0.6665, Acc.bulletin board: 0.4368, Acc.shower: 0.0000, Acc.radiator: 0.3749, Acc.glass: 0.0004, Acc.clock: 0.0615, Acc.flag: 0.1413
2022-11-04 13:21:06,552 - mmseg - INFO - Iter [32050/80000]	lr: 7.570e-05, eta: 4:33:20, time: 0.514, data_time: 0.187, memory: 12960, decode.loss_ce: 0.5261, decode.acc_seg: 80.1953, aux.loss_ce: 0.2783, aux.acc_seg: 75.4059, loss: 0.8044
2022-11-04 13:21:23,410 - mmseg - INFO - Iter [32100/80000]	lr: 7.563e-05, eta: 4:33:03, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5277, decode.acc_seg: 79.8924, aux.loss_ce: 0.2869, aux.acc_seg: 74.3381, loss: 0.8146
2022-11-04 13:21:40,079 - mmseg - INFO - Iter [32150/80000]	lr: 7.556e-05, eta: 4:32:45, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5499, decode.acc_seg: 79.0240, aux.loss_ce: 0.3017, aux.acc_seg: 73.3160, loss: 0.8516
2022-11-04 13:21:59,705 - mmseg - INFO - Iter [32200/80000]	lr: 7.549e-05, eta: 4:32:32, time: 0.393, data_time: 0.054, memory: 12960, decode.loss_ce: 0.5217, decode.acc_seg: 79.9032, aux.loss_ce: 0.2836, aux.acc_seg: 74.1459, loss: 0.8053
2022-11-04 13:22:16,249 - mmseg - INFO - Iter [32250/80000]	lr: 7.542e-05, eta: 4:32:14, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5167, decode.acc_seg: 80.1766, aux.loss_ce: 0.2761, aux.acc_seg: 75.2440, loss: 0.7929
2022-11-04 13:22:32,945 - mmseg - INFO - Iter [32300/80000]	lr: 7.535e-05, eta: 4:31:56, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5245, decode.acc_seg: 79.6860, aux.loss_ce: 0.2838, aux.acc_seg: 74.3534, loss: 0.8083
2022-11-04 13:22:49,804 - mmseg - INFO - Iter [32350/80000]	lr: 7.528e-05, eta: 4:31:39, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5274, decode.acc_seg: 79.7620, aux.loss_ce: 0.2916, aux.acc_seg: 73.9897, loss: 0.8190
2022-11-04 13:23:06,409 - mmseg - INFO - Iter [32400/80000]	lr: 7.521e-05, eta: 4:31:21, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5214, decode.acc_seg: 80.2280, aux.loss_ce: 0.2780, aux.acc_seg: 75.1298, loss: 0.7994
2022-11-04 13:23:22,981 - mmseg - INFO - Iter [32450/80000]	lr: 7.514e-05, eta: 4:31:03, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5213, decode.acc_seg: 80.0766, aux.loss_ce: 0.2812, aux.acc_seg: 74.7216, loss: 0.8025
2022-11-04 13:23:39,649 - mmseg - INFO - Iter [32500/80000]	lr: 7.506e-05, eta: 4:30:45, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5285, decode.acc_seg: 79.6457, aux.loss_ce: 0.2901, aux.acc_seg: 73.9798, loss: 0.8186
2022-11-04 13:23:56,498 - mmseg - INFO - Iter [32550/80000]	lr: 7.499e-05, eta: 4:30:28, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5217, decode.acc_seg: 80.0525, aux.loss_ce: 0.2811, aux.acc_seg: 74.9475, loss: 0.8029
2022-11-04 13:24:13,151 - mmseg - INFO - Iter [32600/80000]	lr: 7.492e-05, eta: 4:30:10, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5067, decode.acc_seg: 80.5346, aux.loss_ce: 0.2775, aux.acc_seg: 74.8621, loss: 0.7842
2022-11-04 13:24:29,920 - mmseg - INFO - Iter [32650/80000]	lr: 7.485e-05, eta: 4:29:52, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5088, decode.acc_seg: 80.4379, aux.loss_ce: 0.2755, aux.acc_seg: 75.3234, loss: 0.7844
2022-11-04 13:24:46,811 - mmseg - INFO - Iter [32700/80000]	lr: 7.478e-05, eta: 4:29:35, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5304, decode.acc_seg: 79.4706, aux.loss_ce: 0.2825, aux.acc_seg: 74.5927, loss: 0.8129
2022-11-04 13:25:03,667 - mmseg - INFO - Iter [32750/80000]	lr: 7.471e-05, eta: 4:29:18, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5365, decode.acc_seg: 79.1887, aux.loss_ce: 0.2886, aux.acc_seg: 73.7519, loss: 0.8251
2022-11-04 13:25:20,169 - mmseg - INFO - Iter [32800/80000]	lr: 7.464e-05, eta: 4:29:00, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5373, decode.acc_seg: 79.4966, aux.loss_ce: 0.2894, aux.acc_seg: 74.1730, loss: 0.8267
2022-11-04 13:25:39,724 - mmseg - INFO - Iter [32850/80000]	lr: 7.457e-05, eta: 4:28:46, time: 0.391, data_time: 0.067, memory: 12960, decode.loss_ce: 0.5117, decode.acc_seg: 80.3367, aux.loss_ce: 0.2731, aux.acc_seg: 75.4554, loss: 0.7848
2022-11-04 13:25:56,424 - mmseg - INFO - Iter [32900/80000]	lr: 7.450e-05, eta: 4:28:28, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5248, decode.acc_seg: 80.0189, aux.loss_ce: 0.2869, aux.acc_seg: 74.0959, loss: 0.8117
2022-11-04 13:26:12,916 - mmseg - INFO - Iter [32950/80000]	lr: 7.442e-05, eta: 4:28:10, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5129, decode.acc_seg: 80.0112, aux.loss_ce: 0.2783, aux.acc_seg: 74.6861, loss: 0.7912
2022-11-04 13:26:29,622 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:26:29,622 - mmseg - INFO - Iter [33000/80000]	lr: 7.435e-05, eta: 4:27:53, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5196, decode.acc_seg: 79.7703, aux.loss_ce: 0.2794, aux.acc_seg: 74.7690, loss: 0.7990
2022-11-04 13:26:46,351 - mmseg - INFO - Iter [33050/80000]	lr: 7.428e-05, eta: 4:27:35, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5039, decode.acc_seg: 80.3589, aux.loss_ce: 0.2765, aux.acc_seg: 74.8609, loss: 0.7803
2022-11-04 13:27:02,982 - mmseg - INFO - Iter [33100/80000]	lr: 7.421e-05, eta: 4:27:17, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4934, decode.acc_seg: 80.9835, aux.loss_ce: 0.2688, aux.acc_seg: 75.8140, loss: 0.7623
2022-11-04 13:27:19,630 - mmseg - INFO - Iter [33150/80000]	lr: 7.414e-05, eta: 4:27:00, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5262, decode.acc_seg: 79.6695, aux.loss_ce: 0.2852, aux.acc_seg: 74.3187, loss: 0.8114
2022-11-04 13:27:36,351 - mmseg - INFO - Iter [33200/80000]	lr: 7.407e-05, eta: 4:26:42, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5321, decode.acc_seg: 79.5429, aux.loss_ce: 0.2866, aux.acc_seg: 74.4092, loss: 0.8187
2022-11-04 13:27:53,137 - mmseg - INFO - Iter [33250/80000]	lr: 7.400e-05, eta: 4:26:25, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5355, decode.acc_seg: 79.6886, aux.loss_ce: 0.2896, aux.acc_seg: 74.2089, loss: 0.8251
2022-11-04 13:28:10,111 - mmseg - INFO - Iter [33300/80000]	lr: 7.393e-05, eta: 4:26:07, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5272, decode.acc_seg: 80.0052, aux.loss_ce: 0.2899, aux.acc_seg: 74.1341, loss: 0.8171
2022-11-04 13:28:26,559 - mmseg - INFO - Iter [33350/80000]	lr: 7.385e-05, eta: 4:25:49, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5262, decode.acc_seg: 79.5951, aux.loss_ce: 0.2811, aux.acc_seg: 74.5157, loss: 0.8073
2022-11-04 13:28:43,289 - mmseg - INFO - Iter [33400/80000]	lr: 7.378e-05, eta: 4:25:32, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5049, decode.acc_seg: 80.5231, aux.loss_ce: 0.2794, aux.acc_seg: 74.8124, loss: 0.7843
2022-11-04 13:29:02,877 - mmseg - INFO - Iter [33450/80000]	lr: 7.371e-05, eta: 4:25:18, time: 0.392, data_time: 0.063, memory: 12960, decode.loss_ce: 0.5286, decode.acc_seg: 80.1521, aux.loss_ce: 0.2817, aux.acc_seg: 75.0082, loss: 0.8104
2022-11-04 13:29:19,806 - mmseg - INFO - Iter [33500/80000]	lr: 7.364e-05, eta: 4:25:01, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5124, decode.acc_seg: 80.3107, aux.loss_ce: 0.2767, aux.acc_seg: 75.3470, loss: 0.7891
2022-11-04 13:29:36,376 - mmseg - INFO - Iter [33550/80000]	lr: 7.357e-05, eta: 4:24:43, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4973, decode.acc_seg: 80.6831, aux.loss_ce: 0.2728, aux.acc_seg: 75.3553, loss: 0.7702
2022-11-04 13:29:53,185 - mmseg - INFO - Iter [33600/80000]	lr: 7.350e-05, eta: 4:24:25, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5016, decode.acc_seg: 80.7889, aux.loss_ce: 0.2755, aux.acc_seg: 75.1137, loss: 0.7770
2022-11-04 13:30:09,874 - mmseg - INFO - Iter [33650/80000]	lr: 7.343e-05, eta: 4:24:08, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4971, decode.acc_seg: 80.9452, aux.loss_ce: 0.2771, aux.acc_seg: 75.4700, loss: 0.7742
2022-11-04 13:30:26,618 - mmseg - INFO - Iter [33700/80000]	lr: 7.336e-05, eta: 4:23:50, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5163, decode.acc_seg: 80.0888, aux.loss_ce: 0.2830, aux.acc_seg: 74.2332, loss: 0.7993
2022-11-04 13:30:43,037 - mmseg - INFO - Iter [33750/80000]	lr: 7.328e-05, eta: 4:23:32, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5313, decode.acc_seg: 79.7883, aux.loss_ce: 0.2899, aux.acc_seg: 73.9950, loss: 0.8212
2022-11-04 13:30:59,697 - mmseg - INFO - Iter [33800/80000]	lr: 7.321e-05, eta: 4:23:14, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5119, decode.acc_seg: 80.1500, aux.loss_ce: 0.2777, aux.acc_seg: 74.8697, loss: 0.7896
2022-11-04 13:31:16,409 - mmseg - INFO - Iter [33850/80000]	lr: 7.314e-05, eta: 4:22:57, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5270, decode.acc_seg: 79.8377, aux.loss_ce: 0.2868, aux.acc_seg: 74.5843, loss: 0.8138
2022-11-04 13:31:33,131 - mmseg - INFO - Iter [33900/80000]	lr: 7.307e-05, eta: 4:22:39, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5199, decode.acc_seg: 80.0846, aux.loss_ce: 0.2833, aux.acc_seg: 75.0376, loss: 0.8032
2022-11-04 13:31:49,890 - mmseg - INFO - Iter [33950/80000]	lr: 7.300e-05, eta: 4:22:22, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5120, decode.acc_seg: 80.1903, aux.loss_ce: 0.2797, aux.acc_seg: 74.9283, loss: 0.7917
2022-11-04 13:32:06,484 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:32:06,484 - mmseg - INFO - Iter [34000/80000]	lr: 7.293e-05, eta: 4:22:04, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5191, decode.acc_seg: 80.1950, aux.loss_ce: 0.2800, aux.acc_seg: 75.0910, loss: 0.7991
2022-11-04 13:32:23,277 - mmseg - INFO - Iter [34050/80000]	lr: 7.286e-05, eta: 4:21:46, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5230, decode.acc_seg: 80.1497, aux.loss_ce: 0.2852, aux.acc_seg: 74.4053, loss: 0.8083
2022-11-04 13:32:42,950 - mmseg - INFO - Iter [34100/80000]	lr: 7.278e-05, eta: 4:21:33, time: 0.393, data_time: 0.067, memory: 12960, decode.loss_ce: 0.5171, decode.acc_seg: 80.0399, aux.loss_ce: 0.2825, aux.acc_seg: 74.5808, loss: 0.7997
2022-11-04 13:32:59,605 - mmseg - INFO - Iter [34150/80000]	lr: 7.271e-05, eta: 4:21:15, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5145, decode.acc_seg: 80.2602, aux.loss_ce: 0.2824, aux.acc_seg: 74.6423, loss: 0.7969
2022-11-04 13:33:16,443 - mmseg - INFO - Iter [34200/80000]	lr: 7.264e-05, eta: 4:20:58, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4928, decode.acc_seg: 81.0451, aux.loss_ce: 0.2736, aux.acc_seg: 75.3798, loss: 0.7664
2022-11-04 13:33:32,860 - mmseg - INFO - Iter [34250/80000]	lr: 7.257e-05, eta: 4:20:40, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5235, decode.acc_seg: 79.6876, aux.loss_ce: 0.2842, aux.acc_seg: 74.0787, loss: 0.8077
2022-11-04 13:33:49,571 - mmseg - INFO - Iter [34300/80000]	lr: 7.250e-05, eta: 4:20:22, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5100, decode.acc_seg: 80.4454, aux.loss_ce: 0.2763, aux.acc_seg: 75.1927, loss: 0.7863
2022-11-04 13:34:06,206 - mmseg - INFO - Iter [34350/80000]	lr: 7.243e-05, eta: 4:20:04, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5115, decode.acc_seg: 80.4896, aux.loss_ce: 0.2843, aux.acc_seg: 74.7593, loss: 0.7957
2022-11-04 13:34:22,741 - mmseg - INFO - Iter [34400/80000]	lr: 7.236e-05, eta: 4:19:46, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5153, decode.acc_seg: 80.5712, aux.loss_ce: 0.2747, aux.acc_seg: 75.7899, loss: 0.7900
2022-11-04 13:34:39,349 - mmseg - INFO - Iter [34450/80000]	lr: 7.229e-05, eta: 4:19:29, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5117, decode.acc_seg: 80.5177, aux.loss_ce: 0.2782, aux.acc_seg: 75.3560, loss: 0.7900
2022-11-04 13:34:56,151 - mmseg - INFO - Iter [34500/80000]	lr: 7.221e-05, eta: 4:19:11, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4902, decode.acc_seg: 81.0884, aux.loss_ce: 0.2688, aux.acc_seg: 75.4462, loss: 0.7589
2022-11-04 13:35:12,958 - mmseg - INFO - Iter [34550/80000]	lr: 7.214e-05, eta: 4:18:54, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5026, decode.acc_seg: 80.7368, aux.loss_ce: 0.2741, aux.acc_seg: 75.2606, loss: 0.7767
2022-11-04 13:35:30,069 - mmseg - INFO - Iter [34600/80000]	lr: 7.207e-05, eta: 4:18:37, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4993, decode.acc_seg: 80.6610, aux.loss_ce: 0.2759, aux.acc_seg: 75.0309, loss: 0.7753
2022-11-04 13:35:46,965 - mmseg - INFO - Iter [34650/80000]	lr: 7.200e-05, eta: 4:18:19, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5213, decode.acc_seg: 79.9075, aux.loss_ce: 0.2853, aux.acc_seg: 74.4604, loss: 0.8066
2022-11-04 13:36:03,725 - mmseg - INFO - Iter [34700/80000]	lr: 7.193e-05, eta: 4:18:02, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5104, decode.acc_seg: 80.5918, aux.loss_ce: 0.2751, aux.acc_seg: 75.6048, loss: 0.7855
2022-11-04 13:36:23,446 - mmseg - INFO - Iter [34750/80000]	lr: 7.186e-05, eta: 4:17:48, time: 0.394, data_time: 0.058, memory: 12960, decode.loss_ce: 0.4973, decode.acc_seg: 81.0613, aux.loss_ce: 0.2781, aux.acc_seg: 75.2060, loss: 0.7754
2022-11-04 13:36:40,053 - mmseg - INFO - Iter [34800/80000]	lr: 7.178e-05, eta: 4:17:31, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4961, decode.acc_seg: 80.5782, aux.loss_ce: 0.2701, aux.acc_seg: 75.2918, loss: 0.7662
2022-11-04 13:36:56,955 - mmseg - INFO - Iter [34850/80000]	lr: 7.171e-05, eta: 4:17:13, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5078, decode.acc_seg: 80.2527, aux.loss_ce: 0.2759, aux.acc_seg: 74.9535, loss: 0.7838
2022-11-04 13:37:13,419 - mmseg - INFO - Iter [34900/80000]	lr: 7.164e-05, eta: 4:16:55, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5081, decode.acc_seg: 80.1401, aux.loss_ce: 0.2809, aux.acc_seg: 74.5150, loss: 0.7890
2022-11-04 13:37:30,113 - mmseg - INFO - Iter [34950/80000]	lr: 7.157e-05, eta: 4:16:38, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5111, decode.acc_seg: 80.3351, aux.loss_ce: 0.2796, aux.acc_seg: 74.6256, loss: 0.7908
2022-11-04 13:37:46,837 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:37:46,837 - mmseg - INFO - Iter [35000/80000]	lr: 7.150e-05, eta: 4:16:20, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5232, decode.acc_seg: 80.1883, aux.loss_ce: 0.2849, aux.acc_seg: 74.3148, loss: 0.8082
2022-11-04 13:38:03,787 - mmseg - INFO - Iter [35050/80000]	lr: 7.143e-05, eta: 4:16:03, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5108, decode.acc_seg: 80.3638, aux.loss_ce: 0.2764, aux.acc_seg: 75.1912, loss: 0.7872
2022-11-04 13:38:20,149 - mmseg - INFO - Iter [35100/80000]	lr: 7.136e-05, eta: 4:15:45, time: 0.327, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5104, decode.acc_seg: 80.6413, aux.loss_ce: 0.2777, aux.acc_seg: 75.2951, loss: 0.7881
2022-11-04 13:38:37,138 - mmseg - INFO - Iter [35150/80000]	lr: 7.128e-05, eta: 4:15:28, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5020, decode.acc_seg: 80.8009, aux.loss_ce: 0.2660, aux.acc_seg: 76.0530, loss: 0.7680
2022-11-04 13:38:53,631 - mmseg - INFO - Iter [35200/80000]	lr: 7.121e-05, eta: 4:15:10, time: 0.330, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5002, decode.acc_seg: 80.5114, aux.loss_ce: 0.2796, aux.acc_seg: 74.3506, loss: 0.7798
2022-11-04 13:39:10,236 - mmseg - INFO - Iter [35250/80000]	lr: 7.114e-05, eta: 4:14:52, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5250, decode.acc_seg: 79.9477, aux.loss_ce: 0.2851, aux.acc_seg: 74.5756, loss: 0.8101
2022-11-04 13:39:26,860 - mmseg - INFO - Iter [35300/80000]	lr: 7.107e-05, eta: 4:14:34, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5123, decode.acc_seg: 80.0405, aux.loss_ce: 0.2840, aux.acc_seg: 74.7204, loss: 0.7963
2022-11-04 13:39:46,502 - mmseg - INFO - Iter [35350/80000]	lr: 7.100e-05, eta: 4:14:21, time: 0.393, data_time: 0.064, memory: 12960, decode.loss_ce: 0.5091, decode.acc_seg: 80.4956, aux.loss_ce: 0.2786, aux.acc_seg: 75.0923, loss: 0.7877
2022-11-04 13:40:02,969 - mmseg - INFO - Iter [35400/80000]	lr: 7.093e-05, eta: 4:14:03, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4974, decode.acc_seg: 80.6297, aux.loss_ce: 0.2718, aux.acc_seg: 74.9009, loss: 0.7692
2022-11-04 13:40:19,828 - mmseg - INFO - Iter [35450/80000]	lr: 7.086e-05, eta: 4:13:45, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4866, decode.acc_seg: 81.4780, aux.loss_ce: 0.2709, aux.acc_seg: 75.8310, loss: 0.7574
2022-11-04 13:40:36,642 - mmseg - INFO - Iter [35500/80000]	lr: 7.078e-05, eta: 4:13:28, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5026, decode.acc_seg: 80.4829, aux.loss_ce: 0.2728, aux.acc_seg: 75.1415, loss: 0.7754
2022-11-04 13:40:53,414 - mmseg - INFO - Iter [35550/80000]	lr: 7.071e-05, eta: 4:13:10, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5021, decode.acc_seg: 80.6544, aux.loss_ce: 0.2723, aux.acc_seg: 75.5469, loss: 0.7745
2022-11-04 13:41:10,207 - mmseg - INFO - Iter [35600/80000]	lr: 7.064e-05, eta: 4:12:53, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4927, decode.acc_seg: 81.1472, aux.loss_ce: 0.2690, aux.acc_seg: 75.8505, loss: 0.7617
2022-11-04 13:41:26,983 - mmseg - INFO - Iter [35650/80000]	lr: 7.057e-05, eta: 4:12:35, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5052, decode.acc_seg: 80.3137, aux.loss_ce: 0.2743, aux.acc_seg: 75.0575, loss: 0.7795
2022-11-04 13:41:43,852 - mmseg - INFO - Iter [35700/80000]	lr: 7.050e-05, eta: 4:12:18, time: 0.337, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5015, decode.acc_seg: 80.9331, aux.loss_ce: 0.2777, aux.acc_seg: 75.4401, loss: 0.7792
2022-11-04 13:42:00,502 - mmseg - INFO - Iter [35750/80000]	lr: 7.043e-05, eta: 4:12:00, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4823, decode.acc_seg: 81.2592, aux.loss_ce: 0.2682, aux.acc_seg: 75.7105, loss: 0.7505
2022-11-04 13:42:17,448 - mmseg - INFO - Iter [35800/80000]	lr: 7.035e-05, eta: 4:11:43, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5102, decode.acc_seg: 80.0640, aux.loss_ce: 0.2774, aux.acc_seg: 74.8217, loss: 0.7876
2022-11-04 13:42:34,016 - mmseg - INFO - Iter [35850/80000]	lr: 7.028e-05, eta: 4:11:25, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5091, decode.acc_seg: 80.7384, aux.loss_ce: 0.2832, aux.acc_seg: 75.2258, loss: 0.7922
2022-11-04 13:42:50,733 - mmseg - INFO - Iter [35900/80000]	lr: 7.021e-05, eta: 4:11:08, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5303, decode.acc_seg: 79.4350, aux.loss_ce: 0.2872, aux.acc_seg: 74.0832, loss: 0.8175
2022-11-04 13:43:07,612 - mmseg - INFO - Iter [35950/80000]	lr: 7.014e-05, eta: 4:10:51, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5013, decode.acc_seg: 80.2831, aux.loss_ce: 0.2759, aux.acc_seg: 74.7654, loss: 0.7772
2022-11-04 13:43:27,430 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:43:27,431 - mmseg - INFO - Iter [36000/80000]	lr: 7.007e-05, eta: 4:10:37, time: 0.396, data_time: 0.062, memory: 12960, decode.loss_ce: 0.5086, decode.acc_seg: 80.3250, aux.loss_ce: 0.2764, aux.acc_seg: 75.1758, loss: 0.7850
2022-11-04 13:43:44,206 - mmseg - INFO - Iter [36050/80000]	lr: 7.000e-05, eta: 4:10:19, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5032, decode.acc_seg: 80.8237, aux.loss_ce: 0.2740, aux.acc_seg: 75.4886, loss: 0.7772
2022-11-04 13:44:01,064 - mmseg - INFO - Iter [36100/80000]	lr: 6.992e-05, eta: 4:10:02, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5004, decode.acc_seg: 80.6346, aux.loss_ce: 0.2716, aux.acc_seg: 75.6437, loss: 0.7719
2022-11-04 13:44:17,756 - mmseg - INFO - Iter [36150/80000]	lr: 6.985e-05, eta: 4:09:44, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4911, decode.acc_seg: 81.2110, aux.loss_ce: 0.2701, aux.acc_seg: 75.8374, loss: 0.7612
2022-11-04 13:44:34,373 - mmseg - INFO - Iter [36200/80000]	lr: 6.978e-05, eta: 4:09:27, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5103, decode.acc_seg: 80.3305, aux.loss_ce: 0.2849, aux.acc_seg: 74.3742, loss: 0.7952
2022-11-04 13:44:50,961 - mmseg - INFO - Iter [36250/80000]	lr: 6.971e-05, eta: 4:09:09, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4955, decode.acc_seg: 80.9830, aux.loss_ce: 0.2720, aux.acc_seg: 75.6003, loss: 0.7675
2022-11-04 13:45:07,741 - mmseg - INFO - Iter [36300/80000]	lr: 6.964e-05, eta: 4:08:52, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5013, decode.acc_seg: 80.2373, aux.loss_ce: 0.2738, aux.acc_seg: 74.9839, loss: 0.7752
2022-11-04 13:45:24,557 - mmseg - INFO - Iter [36350/80000]	lr: 6.957e-05, eta: 4:08:34, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5160, decode.acc_seg: 80.1775, aux.loss_ce: 0.2790, aux.acc_seg: 75.0305, loss: 0.7950
2022-11-04 13:45:41,228 - mmseg - INFO - Iter [36400/80000]	lr: 6.949e-05, eta: 4:08:17, time: 0.333, data_time: 0.011, memory: 12960, decode.loss_ce: 0.5023, decode.acc_seg: 80.5064, aux.loss_ce: 0.2827, aux.acc_seg: 74.2727, loss: 0.7850
2022-11-04 13:45:57,981 - mmseg - INFO - Iter [36450/80000]	lr: 6.942e-05, eta: 4:07:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4967, decode.acc_seg: 80.6291, aux.loss_ce: 0.2720, aux.acc_seg: 75.2807, loss: 0.7687
2022-11-04 13:46:14,562 - mmseg - INFO - Iter [36500/80000]	lr: 6.935e-05, eta: 4:07:41, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5009, decode.acc_seg: 80.8336, aux.loss_ce: 0.2793, aux.acc_seg: 75.2538, loss: 0.7802
2022-11-04 13:46:31,256 - mmseg - INFO - Iter [36550/80000]	lr: 6.928e-05, eta: 4:07:24, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5134, decode.acc_seg: 80.5226, aux.loss_ce: 0.2865, aux.acc_seg: 74.4412, loss: 0.7999
2022-11-04 13:46:50,817 - mmseg - INFO - Iter [36600/80000]	lr: 6.921e-05, eta: 4:07:10, time: 0.391, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4999, decode.acc_seg: 80.8365, aux.loss_ce: 0.2698, aux.acc_seg: 75.6504, loss: 0.7697
2022-11-04 13:47:07,492 - mmseg - INFO - Iter [36650/80000]	lr: 6.914e-05, eta: 4:06:52, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5031, decode.acc_seg: 80.4119, aux.loss_ce: 0.2786, aux.acc_seg: 75.0373, loss: 0.7817
2022-11-04 13:47:24,247 - mmseg - INFO - Iter [36700/80000]	lr: 6.906e-05, eta: 4:06:35, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4888, decode.acc_seg: 80.9486, aux.loss_ce: 0.2671, aux.acc_seg: 75.6367, loss: 0.7558
2022-11-04 13:47:40,840 - mmseg - INFO - Iter [36750/80000]	lr: 6.899e-05, eta: 4:06:17, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5090, decode.acc_seg: 80.4147, aux.loss_ce: 0.2871, aux.acc_seg: 74.3196, loss: 0.7961
2022-11-04 13:47:57,608 - mmseg - INFO - Iter [36800/80000]	lr: 6.892e-05, eta: 4:06:00, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4999, decode.acc_seg: 80.5731, aux.loss_ce: 0.2760, aux.acc_seg: 74.9080, loss: 0.7758
2022-11-04 13:48:14,095 - mmseg - INFO - Iter [36850/80000]	lr: 6.885e-05, eta: 4:05:42, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4973, decode.acc_seg: 80.7568, aux.loss_ce: 0.2752, aux.acc_seg: 75.3402, loss: 0.7724
2022-11-04 13:48:30,922 - mmseg - INFO - Iter [36900/80000]	lr: 6.878e-05, eta: 4:05:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4921, decode.acc_seg: 81.0377, aux.loss_ce: 0.2719, aux.acc_seg: 75.4697, loss: 0.7640
2022-11-04 13:48:47,683 - mmseg - INFO - Iter [36950/80000]	lr: 6.870e-05, eta: 4:05:07, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5027, decode.acc_seg: 80.6514, aux.loss_ce: 0.2742, aux.acc_seg: 75.2890, loss: 0.7769
2022-11-04 13:49:04,413 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:49:04,414 - mmseg - INFO - Iter [37000/80000]	lr: 6.863e-05, eta: 4:04:50, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5129, decode.acc_seg: 80.4452, aux.loss_ce: 0.2774, aux.acc_seg: 75.1035, loss: 0.7903
2022-11-04 13:49:21,234 - mmseg - INFO - Iter [37050/80000]	lr: 6.856e-05, eta: 4:04:32, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4951, decode.acc_seg: 81.0751, aux.loss_ce: 0.2700, aux.acc_seg: 75.8274, loss: 0.7651
2022-11-04 13:49:37,945 - mmseg - INFO - Iter [37100/80000]	lr: 6.849e-05, eta: 4:04:15, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5045, decode.acc_seg: 80.7043, aux.loss_ce: 0.2736, aux.acc_seg: 75.5519, loss: 0.7781
2022-11-04 13:49:54,803 - mmseg - INFO - Iter [37150/80000]	lr: 6.842e-05, eta: 4:03:57, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5006, decode.acc_seg: 80.8612, aux.loss_ce: 0.2759, aux.acc_seg: 75.3874, loss: 0.7765
2022-11-04 13:50:11,661 - mmseg - INFO - Iter [37200/80000]	lr: 6.835e-05, eta: 4:03:40, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4920, decode.acc_seg: 81.0773, aux.loss_ce: 0.2664, aux.acc_seg: 76.1027, loss: 0.7583
2022-11-04 13:50:31,441 - mmseg - INFO - Iter [37250/80000]	lr: 6.827e-05, eta: 4:03:26, time: 0.396, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4940, decode.acc_seg: 81.1373, aux.loss_ce: 0.2710, aux.acc_seg: 75.6362, loss: 0.7650
2022-11-04 13:50:48,253 - mmseg - INFO - Iter [37300/80000]	lr: 6.820e-05, eta: 4:03:09, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4847, decode.acc_seg: 81.2591, aux.loss_ce: 0.2688, aux.acc_seg: 75.8403, loss: 0.7535
2022-11-04 13:51:04,914 - mmseg - INFO - Iter [37350/80000]	lr: 6.813e-05, eta: 4:02:51, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4851, decode.acc_seg: 81.2609, aux.loss_ce: 0.2660, aux.acc_seg: 75.8913, loss: 0.7512
2022-11-04 13:51:21,388 - mmseg - INFO - Iter [37400/80000]	lr: 6.806e-05, eta: 4:02:33, time: 0.329, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4992, decode.acc_seg: 80.6614, aux.loss_ce: 0.2775, aux.acc_seg: 75.0744, loss: 0.7766
2022-11-04 13:51:38,195 - mmseg - INFO - Iter [37450/80000]	lr: 6.799e-05, eta: 4:02:16, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4888, decode.acc_seg: 81.3356, aux.loss_ce: 0.2689, aux.acc_seg: 76.1199, loss: 0.7577
2022-11-04 13:51:55,067 - mmseg - INFO - Iter [37500/80000]	lr: 6.791e-05, eta: 4:01:59, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5084, decode.acc_seg: 80.7853, aux.loss_ce: 0.2816, aux.acc_seg: 74.8808, loss: 0.7901
2022-11-04 13:52:11,657 - mmseg - INFO - Iter [37550/80000]	lr: 6.784e-05, eta: 4:01:41, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4757, decode.acc_seg: 81.4579, aux.loss_ce: 0.2636, aux.acc_seg: 76.0158, loss: 0.7394
2022-11-04 13:52:28,325 - mmseg - INFO - Iter [37600/80000]	lr: 6.777e-05, eta: 4:01:23, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5149, decode.acc_seg: 79.8275, aux.loss_ce: 0.2811, aux.acc_seg: 74.5607, loss: 0.7960
2022-11-04 13:52:44,990 - mmseg - INFO - Iter [37650/80000]	lr: 6.770e-05, eta: 4:01:06, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5196, decode.acc_seg: 80.1129, aux.loss_ce: 0.2844, aux.acc_seg: 74.3733, loss: 0.8040
2022-11-04 13:53:01,669 - mmseg - INFO - Iter [37700/80000]	lr: 6.763e-05, eta: 4:00:48, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5020, decode.acc_seg: 81.1178, aux.loss_ce: 0.2706, aux.acc_seg: 76.1436, loss: 0.7726
2022-11-04 13:53:18,394 - mmseg - INFO - Iter [37750/80000]	lr: 6.755e-05, eta: 4:00:31, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5125, decode.acc_seg: 80.3733, aux.loss_ce: 0.2781, aux.acc_seg: 75.0423, loss: 0.7907
2022-11-04 13:53:35,117 - mmseg - INFO - Iter [37800/80000]	lr: 6.748e-05, eta: 4:00:13, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4929, decode.acc_seg: 81.2131, aux.loss_ce: 0.2698, aux.acc_seg: 75.9056, loss: 0.7627
2022-11-04 13:53:51,871 - mmseg - INFO - Iter [37850/80000]	lr: 6.741e-05, eta: 3:59:56, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5035, decode.acc_seg: 80.3240, aux.loss_ce: 0.2735, aux.acc_seg: 75.3981, loss: 0.7770
2022-11-04 13:54:11,277 - mmseg - INFO - Iter [37900/80000]	lr: 6.734e-05, eta: 3:59:41, time: 0.388, data_time: 0.062, memory: 12960, decode.loss_ce: 0.5036, decode.acc_seg: 80.2981, aux.loss_ce: 0.2813, aux.acc_seg: 74.4717, loss: 0.7849
2022-11-04 13:54:27,900 - mmseg - INFO - Iter [37950/80000]	lr: 6.727e-05, eta: 3:59:24, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4838, decode.acc_seg: 80.8644, aux.loss_ce: 0.2670, aux.acc_seg: 75.4414, loss: 0.7507
2022-11-04 13:54:44,591 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 13:54:44,591 - mmseg - INFO - Iter [38000/80000]	lr: 6.719e-05, eta: 3:59:06, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4989, decode.acc_seg: 80.7740, aux.loss_ce: 0.2760, aux.acc_seg: 75.0207, loss: 0.7750
2022-11-04 13:55:01,240 - mmseg - INFO - Iter [38050/80000]	lr: 6.712e-05, eta: 3:58:49, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4931, decode.acc_seg: 81.0466, aux.loss_ce: 0.2762, aux.acc_seg: 74.9079, loss: 0.7693
2022-11-04 13:55:18,015 - mmseg - INFO - Iter [38100/80000]	lr: 6.705e-05, eta: 3:58:31, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4966, decode.acc_seg: 81.2151, aux.loss_ce: 0.2708, aux.acc_seg: 76.0430, loss: 0.7674
2022-11-04 13:55:34,777 - mmseg - INFO - Iter [38150/80000]	lr: 6.698e-05, eta: 3:58:14, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5087, decode.acc_seg: 80.5423, aux.loss_ce: 0.2748, aux.acc_seg: 75.5185, loss: 0.7836
2022-11-04 13:55:51,359 - mmseg - INFO - Iter [38200/80000]	lr: 6.691e-05, eta: 3:57:56, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5004, decode.acc_seg: 80.7499, aux.loss_ce: 0.2798, aux.acc_seg: 75.1553, loss: 0.7802
2022-11-04 13:56:07,897 - mmseg - INFO - Iter [38250/80000]	lr: 6.683e-05, eta: 3:57:39, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4956, decode.acc_seg: 80.9233, aux.loss_ce: 0.2750, aux.acc_seg: 75.6868, loss: 0.7706
2022-11-04 13:56:24,658 - mmseg - INFO - Iter [38300/80000]	lr: 6.676e-05, eta: 3:57:21, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4942, decode.acc_seg: 80.9351, aux.loss_ce: 0.2741, aux.acc_seg: 74.9483, loss: 0.7683
2022-11-04 13:56:41,213 - mmseg - INFO - Iter [38350/80000]	lr: 6.669e-05, eta: 3:57:04, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4985, decode.acc_seg: 80.8622, aux.loss_ce: 0.2727, aux.acc_seg: 75.4063, loss: 0.7712
2022-11-04 13:56:57,936 - mmseg - INFO - Iter [38400/80000]	lr: 6.662e-05, eta: 3:56:46, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4964, decode.acc_seg: 80.7736, aux.loss_ce: 0.2727, aux.acc_seg: 75.2432, loss: 0.7690
2022-11-04 13:57:14,964 - mmseg - INFO - Iter [38450/80000]	lr: 6.655e-05, eta: 3:56:29, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5076, decode.acc_seg: 80.3847, aux.loss_ce: 0.2756, aux.acc_seg: 75.2356, loss: 0.7833
2022-11-04 13:57:34,986 - mmseg - INFO - Iter [38500/80000]	lr: 6.647e-05, eta: 3:56:15, time: 0.400, data_time: 0.058, memory: 12960, decode.loss_ce: 0.5150, decode.acc_seg: 80.2691, aux.loss_ce: 0.2761, aux.acc_seg: 75.1569, loss: 0.7911
2022-11-04 13:57:51,606 - mmseg - INFO - Iter [38550/80000]	lr: 6.640e-05, eta: 3:55:57, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4913, decode.acc_seg: 80.8695, aux.loss_ce: 0.2711, aux.acc_seg: 75.3806, loss: 0.7624
2022-11-04 13:58:08,141 - mmseg - INFO - Iter [38600/80000]	lr: 6.633e-05, eta: 3:55:40, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4727, decode.acc_seg: 81.8310, aux.loss_ce: 0.2588, aux.acc_seg: 76.6823, loss: 0.7315
2022-11-04 13:58:24,761 - mmseg - INFO - Iter [38650/80000]	lr: 6.626e-05, eta: 3:55:22, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4985, decode.acc_seg: 80.8901, aux.loss_ce: 0.2755, aux.acc_seg: 74.9110, loss: 0.7740
2022-11-04 13:58:41,179 - mmseg - INFO - Iter [38700/80000]	lr: 6.619e-05, eta: 3:55:04, time: 0.328, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4969, decode.acc_seg: 81.0401, aux.loss_ce: 0.2775, aux.acc_seg: 75.0963, loss: 0.7744
2022-11-04 13:58:57,921 - mmseg - INFO - Iter [38750/80000]	lr: 6.611e-05, eta: 3:54:47, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4856, decode.acc_seg: 81.3484, aux.loss_ce: 0.2603, aux.acc_seg: 76.2848, loss: 0.7459
2022-11-04 13:59:14,493 - mmseg - INFO - Iter [38800/80000]	lr: 6.604e-05, eta: 3:54:29, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4889, decode.acc_seg: 81.2032, aux.loss_ce: 0.2729, aux.acc_seg: 75.4663, loss: 0.7618
2022-11-04 13:59:31,248 - mmseg - INFO - Iter [38850/80000]	lr: 6.597e-05, eta: 3:54:12, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4755, decode.acc_seg: 81.4185, aux.loss_ce: 0.2628, aux.acc_seg: 76.0308, loss: 0.7383
2022-11-04 13:59:48,233 - mmseg - INFO - Iter [38900/80000]	lr: 6.590e-05, eta: 3:53:55, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4864, decode.acc_seg: 81.2356, aux.loss_ce: 0.2721, aux.acc_seg: 75.6487, loss: 0.7586
2022-11-04 14:00:04,751 - mmseg - INFO - Iter [38950/80000]	lr: 6.583e-05, eta: 3:53:37, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4813, decode.acc_seg: 81.1432, aux.loss_ce: 0.2693, aux.acc_seg: 75.5535, loss: 0.7506
2022-11-04 14:00:21,343 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:00:21,343 - mmseg - INFO - Iter [39000/80000]	lr: 6.575e-05, eta: 3:53:20, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.5037, decode.acc_seg: 80.6916, aux.loss_ce: 0.2833, aux.acc_seg: 74.7739, loss: 0.7870
2022-11-04 14:00:38,069 - mmseg - INFO - Iter [39050/80000]	lr: 6.568e-05, eta: 3:53:02, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5084, decode.acc_seg: 80.4963, aux.loss_ce: 0.2823, aux.acc_seg: 74.6400, loss: 0.7907
2022-11-04 14:00:54,832 - mmseg - INFO - Iter [39100/80000]	lr: 6.561e-05, eta: 3:52:45, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4874, decode.acc_seg: 81.2514, aux.loss_ce: 0.2720, aux.acc_seg: 75.5228, loss: 0.7594
2022-11-04 14:01:14,657 - mmseg - INFO - Iter [39150/80000]	lr: 6.554e-05, eta: 3:52:31, time: 0.396, data_time: 0.071, memory: 12960, decode.loss_ce: 0.4891, decode.acc_seg: 81.2173, aux.loss_ce: 0.2706, aux.acc_seg: 75.6918, loss: 0.7597
2022-11-04 14:01:31,261 - mmseg - INFO - Iter [39200/80000]	lr: 6.546e-05, eta: 3:52:13, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4614, decode.acc_seg: 82.1018, aux.loss_ce: 0.2535, aux.acc_seg: 77.1905, loss: 0.7150
2022-11-04 14:01:48,033 - mmseg - INFO - Iter [39250/80000]	lr: 6.539e-05, eta: 3:51:56, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4733, decode.acc_seg: 81.7692, aux.loss_ce: 0.2632, aux.acc_seg: 76.3454, loss: 0.7365
2022-11-04 14:02:04,826 - mmseg - INFO - Iter [39300/80000]	lr: 6.532e-05, eta: 3:51:38, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4833, decode.acc_seg: 81.4924, aux.loss_ce: 0.2652, aux.acc_seg: 76.2801, loss: 0.7485
2022-11-04 14:02:21,624 - mmseg - INFO - Iter [39350/80000]	lr: 6.525e-05, eta: 3:51:21, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5002, decode.acc_seg: 80.5690, aux.loss_ce: 0.2759, aux.acc_seg: 75.1557, loss: 0.7760
2022-11-04 14:02:38,232 - mmseg - INFO - Iter [39400/80000]	lr: 6.518e-05, eta: 3:51:03, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4951, decode.acc_seg: 80.7750, aux.loss_ce: 0.2761, aux.acc_seg: 75.0150, loss: 0.7712
2022-11-04 14:02:54,880 - mmseg - INFO - Iter [39450/80000]	lr: 6.510e-05, eta: 3:50:46, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4869, decode.acc_seg: 81.1300, aux.loss_ce: 0.2697, aux.acc_seg: 75.7981, loss: 0.7566
2022-11-04 14:03:11,520 - mmseg - INFO - Iter [39500/80000]	lr: 6.503e-05, eta: 3:50:28, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.5015, decode.acc_seg: 80.7659, aux.loss_ce: 0.2744, aux.acc_seg: 75.5752, loss: 0.7759
2022-11-04 14:03:28,289 - mmseg - INFO - Iter [39550/80000]	lr: 6.496e-05, eta: 3:50:11, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5001, decode.acc_seg: 80.4879, aux.loss_ce: 0.2740, aux.acc_seg: 75.0586, loss: 0.7741
2022-11-04 14:03:44,899 - mmseg - INFO - Iter [39600/80000]	lr: 6.489e-05, eta: 3:49:53, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4845, decode.acc_seg: 81.2725, aux.loss_ce: 0.2732, aux.acc_seg: 75.1148, loss: 0.7577
2022-11-04 14:04:01,672 - mmseg - INFO - Iter [39650/80000]	lr: 6.481e-05, eta: 3:49:36, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5079, decode.acc_seg: 80.4738, aux.loss_ce: 0.2782, aux.acc_seg: 75.3188, loss: 0.7861
2022-11-04 14:04:18,266 - mmseg - INFO - Iter [39700/80000]	lr: 6.474e-05, eta: 3:49:18, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4901, decode.acc_seg: 80.8047, aux.loss_ce: 0.2729, aux.acc_seg: 75.1805, loss: 0.7629
2022-11-04 14:04:34,639 - mmseg - INFO - Iter [39750/80000]	lr: 6.467e-05, eta: 3:49:01, time: 0.327, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4971, decode.acc_seg: 80.7155, aux.loss_ce: 0.2753, aux.acc_seg: 75.3321, loss: 0.7723
2022-11-04 14:04:54,240 - mmseg - INFO - Iter [39800/80000]	lr: 6.460e-05, eta: 3:48:46, time: 0.392, data_time: 0.068, memory: 12960, decode.loss_ce: 0.4616, decode.acc_seg: 82.0175, aux.loss_ce: 0.2515, aux.acc_seg: 77.0127, loss: 0.7131
2022-11-04 14:05:10,980 - mmseg - INFO - Iter [39850/80000]	lr: 6.452e-05, eta: 3:48:29, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4878, decode.acc_seg: 81.3485, aux.loss_ce: 0.2679, aux.acc_seg: 75.7970, loss: 0.7558
2022-11-04 14:05:27,611 - mmseg - INFO - Iter [39900/80000]	lr: 6.445e-05, eta: 3:48:11, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4826, decode.acc_seg: 81.5180, aux.loss_ce: 0.2743, aux.acc_seg: 75.1043, loss: 0.7568
2022-11-04 14:05:44,428 - mmseg - INFO - Iter [39950/80000]	lr: 6.438e-05, eta: 3:47:54, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4811, decode.acc_seg: 81.2869, aux.loss_ce: 0.2676, aux.acc_seg: 75.6250, loss: 0.7487
2022-11-04 14:06:01,201 - mmseg - INFO - Saving checkpoint at 40000 iterations
2022-11-04 14:06:01,453 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:06:01,453 - mmseg - INFO - Iter [40000/80000]	lr: 6.431e-05, eta: 3:47:37, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4990, decode.acc_seg: 80.6517, aux.loss_ce: 0.2668, aux.acc_seg: 75.9390, loss: 0.7658
2022-11-04 14:06:10,198 - mmseg - INFO - per class results:
2022-11-04 14:06:10,205 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 66.37 | 83.07 |
|       building      | 74.77 | 88.85 |
|         sky         | 88.58 | 92.94 |
|        floor        | 70.61 | 84.51 |
|         tree        | 66.75 |  82.6 |
|       ceiling       | 75.91 | 85.85 |
|         road        | 74.93 | 83.77 |
|         bed         | 74.47 | 89.48 |
|      windowpane     | 49.41 | 65.67 |
|        grass        | 62.27 | 78.59 |
|       cabinet       | 46.54 | 61.13 |
|       sidewalk      | 52.35 | 69.65 |
|        person       | 64.14 | 81.71 |
|        earth        | 30.27 | 45.48 |
|         door        | 25.89 | 41.39 |
|        table        | 39.69 | 56.88 |
|       mountain      | 53.23 | 69.48 |
|        plant        | 44.78 | 56.27 |
|       curtain       | 54.82 | 70.02 |
|        chair        | 35.16 | 46.96 |
|         car         | 69.92 | 85.58 |
|        water        | 41.62 | 57.97 |
|       painting      | 55.25 | 72.03 |
|         sofa        |  46.2 | 68.04 |
|        shelf        | 33.17 | 47.47 |
|        house        | 39.59 | 59.34 |
|         sea         | 33.31 | 57.48 |
|        mirror       | 38.03 | 48.44 |
|         rug         |  47.3 | 56.65 |
|        field        | 27.54 | 40.91 |
|       armchair      | 24.47 | 39.41 |
|         seat        | 47.35 | 63.76 |
|        fence        | 23.36 |  39.4 |
|         desk        | 31.85 | 55.39 |
|         rock        | 36.66 | 62.77 |
|       wardrobe      |  36.7 | 59.77 |
|         lamp        | 36.19 | 51.05 |
|       bathtub       | 51.56 |  60.6 |
|       railing       | 26.18 | 34.56 |
|       cushion       | 31.49 | 44.89 |
|         base        | 20.27 | 27.05 |
|         box         | 17.05 | 29.19 |
|        column       | 31.26 | 38.79 |
|      signboard      | 23.96 | 32.59 |
|   chest of drawers  | 23.29 |  43.2 |
|       counter       | 27.71 | 31.11 |
|         sand        | 31.82 | 46.04 |
|         sink        | 44.55 | 55.43 |
|      skyscraper     | 61.18 | 86.68 |
|      fireplace      | 57.75 |  69.1 |
|     refrigerator    | 49.05 | 61.97 |
|      grandstand     | 41.82 | 69.38 |
|         path        | 19.66 | 28.89 |
|        stairs       | 22.85 | 31.21 |
|        runway       | 73.09 | 90.55 |
|         case        | 39.76 | 60.06 |
|      pool table     | 79.32 | 90.22 |
|        pillow       | 36.83 | 45.91 |
|     screen door     | 46.92 | 67.42 |
|       stairway      | 21.35 | 24.24 |
|        river        | 19.79 | 29.88 |
|        bridge       | 37.72 | 57.09 |
|       bookcase      | 25.75 | 39.11 |
|        blind        |  24.6 | 29.34 |
|     coffee table    | 40.32 | 65.38 |
|        toilet       | 65.07 | 77.58 |
|        flower       | 26.09 | 39.78 |
|         book        | 34.81 | 47.08 |
|         hill        |  9.14 | 13.14 |
|        bench        | 29.26 | 38.81 |
|      countertop     | 44.82 | 59.66 |
|        stove        | 49.46 |  60.9 |
|         palm        | 39.35 | 59.25 |
|    kitchen island   | 16.28 | 35.85 |
|       computer      | 43.15 | 58.53 |
|     swivel chair    | 30.55 | 41.56 |
|         boat        | 51.08 | 64.53 |
|         bar         | 23.02 | 27.43 |
|    arcade machine   | 36.61 | 41.76 |
|        hovel        | 29.36 | 39.78 |
|         bus         | 61.85 | 80.21 |
|        towel        |  34.8 | 44.77 |
|        light        |  12.1 | 12.88 |
|        truck        |  2.96 |  4.02 |
|        tower        | 33.86 | 40.27 |
|      chandelier     | 43.92 | 56.13 |
|        awning       | 17.08 |  19.8 |
|     streetlight     |  5.62 |  6.72 |
|        booth        | 30.52 | 34.74 |
| television receiver | 38.66 | 62.32 |
|       airplane      | 41.98 | 52.57 |
|      dirt track     |  8.39 | 15.84 |
|       apparel       | 15.27 | 21.89 |
|         pole        |  6.07 | 11.95 |
|         land        |  1.15 |  2.11 |
|      bannister      |  1.3  |  1.86 |
|      escalator      | 30.57 | 32.55 |
|       ottoman       | 30.03 | 37.42 |
|        bottle       | 13.04 |  20.7 |
|        buffet       | 34.89 | 44.25 |
|        poster       |  12.2 | 14.18 |
|        stage        | 10.42 | 15.67 |
|         van         | 10.75 | 12.85 |
|         ship        | 27.01 | 29.61 |
|       fountain      | 17.49 | 18.08 |
|    conveyer belt    | 61.64 | 68.47 |
|        canopy       | 35.59 | 46.54 |
|        washer       | 50.76 |  59.6 |
|      plaything      |  6.07 |  8.71 |
|    swimming pool    | 30.55 | 49.86 |
|        stool        | 11.39 | 13.48 |
|        barrel       | 36.05 | 53.12 |
|        basket       | 13.12 | 18.43 |
|      waterfall      | 53.89 | 73.55 |
|         tent        | 86.12 | 97.07 |
|         bag         |  2.64 |  3.07 |
|       minibike      | 36.04 | 44.16 |
|        cradle       | 57.92 | 78.56 |
|         oven        | 13.43 | 25.29 |
|         ball        | 30.35 | 42.84 |
|         food        | 39.17 |  47.8 |
|         step        |  1.8  |  1.84 |
|         tank        | 32.31 | 38.17 |
|      trade name     | 18.87 | 20.71 |
|      microwave      | 25.82 | 29.33 |
|         pot         | 19.17 | 22.64 |
|        animal       | 45.02 | 51.45 |
|       bicycle       | 33.41 | 59.25 |
|         lake        |  0.0  |  0.0  |
|      dishwasher     | 21.26 | 24.22 |
|        screen       |  48.9 | 72.29 |
|       blanket       |  1.31 |  1.5  |
|      sculpture      | 31.83 | 49.14 |
|         hood        | 32.93 |  36.6 |
|        sconce       |  8.08 |  8.62 |
|         vase        | 12.26 |  16.1 |
|    traffic light    |  9.17 |  11.5 |
|         tray        |  2.63 |  3.79 |
|        ashcan       |  21.1 |  26.4 |
|         fan         | 24.81 | 30.01 |
|         pier        | 34.92 | 45.84 |
|      crt screen     |  0.15 |  0.31 |
|        plate        | 34.95 | 43.41 |
|       monitor       | 29.15 | 31.89 |
|    bulletin board   | 25.74 | 28.65 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 32.24 | 36.08 |
|        glass        |  0.0  |  0.0  |
|        clock        |  9.17 |  9.98 |
|         flag        | 13.22 | 15.51 |
+---------------------+-------+-------+
2022-11-04 14:06:10,205 - mmseg - INFO - Summary:
2022-11-04 14:06:10,206 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 74.82 | 33.68 | 44.23 |
+-------+-------+-------+
2022-11-04 14:06:10,207 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:06:10,207 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7482, mIoU: 0.3368, mAcc: 0.4423, IoU.wall: 0.6637, IoU.building: 0.7477, IoU.sky: 0.8858, IoU.floor: 0.7061, IoU.tree: 0.6675, IoU.ceiling: 0.7591, IoU.road: 0.7493, IoU.bed : 0.7447, IoU.windowpane: 0.4941, IoU.grass: 0.6227, IoU.cabinet: 0.4654, IoU.sidewalk: 0.5235, IoU.person: 0.6414, IoU.earth: 0.3027, IoU.door: 0.2589, IoU.table: 0.3969, IoU.mountain: 0.5323, IoU.plant: 0.4478, IoU.curtain: 0.5482, IoU.chair: 0.3516, IoU.car: 0.6992, IoU.water: 0.4162, IoU.painting: 0.5525, IoU.sofa: 0.4620, IoU.shelf: 0.3317, IoU.house: 0.3959, IoU.sea: 0.3331, IoU.mirror: 0.3803, IoU.rug: 0.4730, IoU.field: 0.2754, IoU.armchair: 0.2447, IoU.seat: 0.4735, IoU.fence: 0.2336, IoU.desk: 0.3185, IoU.rock: 0.3666, IoU.wardrobe: 0.3670, IoU.lamp: 0.3619, IoU.bathtub: 0.5156, IoU.railing: 0.2618, IoU.cushion: 0.3149, IoU.base: 0.2027, IoU.box: 0.1705, IoU.column: 0.3126, IoU.signboard: 0.2396, IoU.chest of drawers: 0.2329, IoU.counter: 0.2771, IoU.sand: 0.3182, IoU.sink: 0.4455, IoU.skyscraper: 0.6118, IoU.fireplace: 0.5775, IoU.refrigerator: 0.4905, IoU.grandstand: 0.4182, IoU.path: 0.1966, IoU.stairs: 0.2285, IoU.runway: 0.7309, IoU.case: 0.3976, IoU.pool table: 0.7932, IoU.pillow: 0.3683, IoU.screen door: 0.4692, IoU.stairway: 0.2135, IoU.river: 0.1979, IoU.bridge: 0.3772, IoU.bookcase: 0.2575, IoU.blind: 0.2460, IoU.coffee table: 0.4032, IoU.toilet: 0.6507, IoU.flower: 0.2609, IoU.book: 0.3481, IoU.hill: 0.0914, IoU.bench: 0.2926, IoU.countertop: 0.4482, IoU.stove: 0.4946, IoU.palm: 0.3935, IoU.kitchen island: 0.1628, IoU.computer: 0.4315, IoU.swivel chair: 0.3055, IoU.boat: 0.5108, IoU.bar: 0.2302, IoU.arcade machine: 0.3661, IoU.hovel: 0.2936, IoU.bus: 0.6185, IoU.towel: 0.3480, IoU.light: 0.1210, IoU.truck: 0.0296, IoU.tower: 0.3386, IoU.chandelier: 0.4392, IoU.awning: 0.1708, IoU.streetlight: 0.0562, IoU.booth: 0.3052, IoU.television receiver: 0.3866, IoU.airplane: 0.4198, IoU.dirt track: 0.0839, IoU.apparel: 0.1527, IoU.pole: 0.0607, IoU.land: 0.0115, IoU.bannister: 0.0130, IoU.escalator: 0.3057, IoU.ottoman: 0.3003, IoU.bottle: 0.1304, IoU.buffet: 0.3489, IoU.poster: 0.1220, IoU.stage: 0.1042, IoU.van: 0.1075, IoU.ship: 0.2701, IoU.fountain: 0.1749, IoU.conveyer belt: 0.6164, IoU.canopy: 0.3559, IoU.washer: 0.5076, IoU.plaything: 0.0607, IoU.swimming pool: 0.3055, IoU.stool: 0.1139, IoU.barrel: 0.3605, IoU.basket: 0.1312, IoU.waterfall: 0.5389, IoU.tent: 0.8612, IoU.bag: 0.0264, IoU.minibike: 0.3604, IoU.cradle: 0.5792, IoU.oven: 0.1343, IoU.ball: 0.3035, IoU.food: 0.3917, IoU.step: 0.0180, IoU.tank: 0.3231, IoU.trade name: 0.1887, IoU.microwave: 0.2582, IoU.pot: 0.1917, IoU.animal: 0.4502, IoU.bicycle: 0.3341, IoU.lake: 0.0000, IoU.dishwasher: 0.2126, IoU.screen: 0.4890, IoU.blanket: 0.0131, IoU.sculpture: 0.3183, IoU.hood: 0.3293, IoU.sconce: 0.0808, IoU.vase: 0.1226, IoU.traffic light: 0.0917, IoU.tray: 0.0263, IoU.ashcan: 0.2110, IoU.fan: 0.2481, IoU.pier: 0.3492, IoU.crt screen: 0.0015, IoU.plate: 0.3495, IoU.monitor: 0.2915, IoU.bulletin board: 0.2574, IoU.shower: 0.0000, IoU.radiator: 0.3224, IoU.glass: 0.0000, IoU.clock: 0.0917, IoU.flag: 0.1322, Acc.wall: 0.8307, Acc.building: 0.8885, Acc.sky: 0.9294, Acc.floor: 0.8451, Acc.tree: 0.8260, Acc.ceiling: 0.8585, Acc.road: 0.8377, Acc.bed : 0.8948, Acc.windowpane: 0.6567, Acc.grass: 0.7859, Acc.cabinet: 0.6113, Acc.sidewalk: 0.6965, Acc.person: 0.8171, Acc.earth: 0.4548, Acc.door: 0.4139, Acc.table: 0.5688, Acc.mountain: 0.6948, Acc.plant: 0.5627, Acc.curtain: 0.7002, Acc.chair: 0.4696, Acc.car: 0.8558, Acc.water: 0.5797, Acc.painting: 0.7203, Acc.sofa: 0.6804, Acc.shelf: 0.4747, Acc.house: 0.5934, Acc.sea: 0.5748, Acc.mirror: 0.4844, Acc.rug: 0.5665, Acc.field: 0.4091, Acc.armchair: 0.3941, Acc.seat: 0.6376, Acc.fence: 0.3940, Acc.desk: 0.5539, Acc.rock: 0.6277, Acc.wardrobe: 0.5977, Acc.lamp: 0.5105, Acc.bathtub: 0.6060, Acc.railing: 0.3456, Acc.cushion: 0.4489, Acc.base: 0.2705, Acc.box: 0.2919, Acc.column: 0.3879, Acc.signboard: 0.3259, Acc.chest of drawers: 0.4320, Acc.counter: 0.3111, Acc.sand: 0.4604, Acc.sink: 0.5543, Acc.skyscraper: 0.8668, Acc.fireplace: 0.6910, Acc.refrigerator: 0.6197, Acc.grandstand: 0.6938, Acc.path: 0.2889, Acc.stairs: 0.3121, Acc.runway: 0.9055, Acc.case: 0.6006, Acc.pool table: 0.9022, Acc.pillow: 0.4591, Acc.screen door: 0.6742, Acc.stairway: 0.2424, Acc.river: 0.2988, Acc.bridge: 0.5709, Acc.bookcase: 0.3911, Acc.blind: 0.2934, Acc.coffee table: 0.6538, Acc.toilet: 0.7758, Acc.flower: 0.3978, Acc.book: 0.4708, Acc.hill: 0.1314, Acc.bench: 0.3881, Acc.countertop: 0.5966, Acc.stove: 0.6090, Acc.palm: 0.5925, Acc.kitchen island: 0.3585, Acc.computer: 0.5853, Acc.swivel chair: 0.4156, Acc.boat: 0.6453, Acc.bar: 0.2743, Acc.arcade machine: 0.4176, Acc.hovel: 0.3978, Acc.bus: 0.8021, Acc.towel: 0.4477, Acc.light: 0.1288, Acc.truck: 0.0402, Acc.tower: 0.4027, Acc.chandelier: 0.5613, Acc.awning: 0.1980, Acc.streetlight: 0.0672, Acc.booth: 0.3474, Acc.television receiver: 0.6232, Acc.airplane: 0.5257, Acc.dirt track: 0.1584, Acc.apparel: 0.2189, Acc.pole: 0.1195, Acc.land: 0.0211, Acc.bannister: 0.0186, Acc.escalator: 0.3255, Acc.ottoman: 0.3742, Acc.bottle: 0.2070, Acc.buffet: 0.4425, Acc.poster: 0.1418, Acc.stage: 0.1567, Acc.van: 0.1285, Acc.ship: 0.2961, Acc.fountain: 0.1808, Acc.conveyer belt: 0.6847, Acc.canopy: 0.4654, Acc.washer: 0.5960, Acc.plaything: 0.0871, Acc.swimming pool: 0.4986, Acc.stool: 0.1348, Acc.barrel: 0.5312, Acc.basket: 0.1843, Acc.waterfall: 0.7355, Acc.tent: 0.9707, Acc.bag: 0.0307, Acc.minibike: 0.4416, Acc.cradle: 0.7856, Acc.oven: 0.2529, Acc.ball: 0.4284, Acc.food: 0.4780, Acc.step: 0.0184, Acc.tank: 0.3817, Acc.trade name: 0.2071, Acc.microwave: 0.2933, Acc.pot: 0.2264, Acc.animal: 0.5145, Acc.bicycle: 0.5925, Acc.lake: 0.0000, Acc.dishwasher: 0.2422, Acc.screen: 0.7229, Acc.blanket: 0.0150, Acc.sculpture: 0.4914, Acc.hood: 0.3660, Acc.sconce: 0.0862, Acc.vase: 0.1610, Acc.traffic light: 0.1150, Acc.tray: 0.0379, Acc.ashcan: 0.2640, Acc.fan: 0.3001, Acc.pier: 0.4584, Acc.crt screen: 0.0031, Acc.plate: 0.4341, Acc.monitor: 0.3189, Acc.bulletin board: 0.2865, Acc.shower: 0.0000, Acc.radiator: 0.3608, Acc.glass: 0.0000, Acc.clock: 0.0998, Acc.flag: 0.1551
2022-11-04 14:06:26,934 - mmseg - INFO - Iter [40050/80000]	lr: 6.424e-05, eta: 3:47:28, time: 0.510, data_time: 0.184, memory: 12960, decode.loss_ce: 0.5122, decode.acc_seg: 80.3126, aux.loss_ce: 0.2828, aux.acc_seg: 74.4927, loss: 0.7951
2022-11-04 14:06:43,525 - mmseg - INFO - Iter [40100/80000]	lr: 6.416e-05, eta: 3:47:11, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4960, decode.acc_seg: 80.5330, aux.loss_ce: 0.2683, aux.acc_seg: 75.3776, loss: 0.7643
2022-11-04 14:07:00,399 - mmseg - INFO - Iter [40150/80000]	lr: 6.409e-05, eta: 3:46:53, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5035, decode.acc_seg: 80.8277, aux.loss_ce: 0.2807, aux.acc_seg: 75.1445, loss: 0.7842
2022-11-04 14:07:16,909 - mmseg - INFO - Iter [40200/80000]	lr: 6.402e-05, eta: 3:46:36, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4783, decode.acc_seg: 81.4186, aux.loss_ce: 0.2650, aux.acc_seg: 75.5367, loss: 0.7434
2022-11-04 14:07:33,697 - mmseg - INFO - Iter [40250/80000]	lr: 6.395e-05, eta: 3:46:18, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4942, decode.acc_seg: 80.9244, aux.loss_ce: 0.2716, aux.acc_seg: 75.7610, loss: 0.7658
2022-11-04 14:07:50,503 - mmseg - INFO - Iter [40300/80000]	lr: 6.387e-05, eta: 3:46:01, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4716, decode.acc_seg: 81.4955, aux.loss_ce: 0.2615, aux.acc_seg: 76.1137, loss: 0.7331
2022-11-04 14:08:07,365 - mmseg - INFO - Iter [40350/80000]	lr: 6.380e-05, eta: 3:45:44, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4892, decode.acc_seg: 81.2597, aux.loss_ce: 0.2674, aux.acc_seg: 75.8537, loss: 0.7565
2022-11-04 14:08:26,833 - mmseg - INFO - Iter [40400/80000]	lr: 6.373e-05, eta: 3:45:29, time: 0.389, data_time: 0.073, memory: 12960, decode.loss_ce: 0.4989, decode.acc_seg: 81.0914, aux.loss_ce: 0.2733, aux.acc_seg: 75.5709, loss: 0.7721
2022-11-04 14:08:43,525 - mmseg - INFO - Iter [40450/80000]	lr: 6.366e-05, eta: 3:45:11, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4848, decode.acc_seg: 81.4577, aux.loss_ce: 0.2717, aux.acc_seg: 75.5833, loss: 0.7565
2022-11-04 14:09:00,184 - mmseg - INFO - Iter [40500/80000]	lr: 6.358e-05, eta: 3:44:54, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4738, decode.acc_seg: 81.7184, aux.loss_ce: 0.2627, aux.acc_seg: 75.8210, loss: 0.7365
2022-11-04 14:09:16,951 - mmseg - INFO - Iter [40550/80000]	lr: 6.351e-05, eta: 3:44:36, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4959, decode.acc_seg: 80.8053, aux.loss_ce: 0.2717, aux.acc_seg: 75.3041, loss: 0.7676
2022-11-04 14:09:33,650 - mmseg - INFO - Iter [40600/80000]	lr: 6.344e-05, eta: 3:44:19, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5024, decode.acc_seg: 80.9441, aux.loss_ce: 0.2755, aux.acc_seg: 75.8767, loss: 0.7779
2022-11-04 14:09:50,409 - mmseg - INFO - Iter [40650/80000]	lr: 6.337e-05, eta: 3:44:02, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4969, decode.acc_seg: 81.0036, aux.loss_ce: 0.2767, aux.acc_seg: 75.1624, loss: 0.7736
2022-11-04 14:10:07,171 - mmseg - INFO - Iter [40700/80000]	lr: 6.329e-05, eta: 3:43:44, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4918, decode.acc_seg: 81.0093, aux.loss_ce: 0.2684, aux.acc_seg: 75.5437, loss: 0.7602
2022-11-04 14:10:23,835 - mmseg - INFO - Iter [40750/80000]	lr: 6.322e-05, eta: 3:43:27, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4915, decode.acc_seg: 81.5123, aux.loss_ce: 0.2678, aux.acc_seg: 76.3803, loss: 0.7594
2022-11-04 14:10:40,719 - mmseg - INFO - Iter [40800/80000]	lr: 6.315e-05, eta: 3:43:09, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4826, decode.acc_seg: 81.0240, aux.loss_ce: 0.2651, aux.acc_seg: 75.7233, loss: 0.7477
2022-11-04 14:10:57,463 - mmseg - INFO - Iter [40850/80000]	lr: 6.308e-05, eta: 3:42:52, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4868, decode.acc_seg: 81.2445, aux.loss_ce: 0.2775, aux.acc_seg: 75.1728, loss: 0.7643
2022-11-04 14:11:14,175 - mmseg - INFO - Iter [40900/80000]	lr: 6.300e-05, eta: 3:42:35, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5111, decode.acc_seg: 80.4621, aux.loss_ce: 0.2841, aux.acc_seg: 74.6660, loss: 0.7952
2022-11-04 14:11:31,144 - mmseg - INFO - Iter [40950/80000]	lr: 6.293e-05, eta: 3:42:17, time: 0.339, data_time: 0.015, memory: 12960, decode.loss_ce: 0.5009, decode.acc_seg: 80.7982, aux.loss_ce: 0.2755, aux.acc_seg: 75.4786, loss: 0.7764
2022-11-04 14:11:47,685 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:11:47,686 - mmseg - INFO - Iter [41000/80000]	lr: 6.286e-05, eta: 3:42:00, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4819, decode.acc_seg: 81.3473, aux.loss_ce: 0.2642, aux.acc_seg: 75.8740, loss: 0.7461
2022-11-04 14:12:07,454 - mmseg - INFO - Iter [41050/80000]	lr: 6.279e-05, eta: 3:41:45, time: 0.395, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4830, decode.acc_seg: 81.3772, aux.loss_ce: 0.2664, aux.acc_seg: 75.8200, loss: 0.7494
2022-11-04 14:12:24,514 - mmseg - INFO - Iter [41100/80000]	lr: 6.271e-05, eta: 3:41:28, time: 0.341, data_time: 0.014, memory: 12960, decode.loss_ce: 0.4743, decode.acc_seg: 81.3473, aux.loss_ce: 0.2667, aux.acc_seg: 75.7414, loss: 0.7410
2022-11-04 14:12:41,179 - mmseg - INFO - Iter [41150/80000]	lr: 6.264e-05, eta: 3:41:11, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4802, decode.acc_seg: 81.2969, aux.loss_ce: 0.2663, aux.acc_seg: 75.9904, loss: 0.7464
2022-11-04 14:12:57,726 - mmseg - INFO - Iter [41200/80000]	lr: 6.257e-05, eta: 3:40:53, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4777, decode.acc_seg: 81.2866, aux.loss_ce: 0.2696, aux.acc_seg: 75.1984, loss: 0.7472
2022-11-04 14:13:14,262 - mmseg - INFO - Iter [41250/80000]	lr: 6.250e-05, eta: 3:40:36, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4945, decode.acc_seg: 80.6099, aux.loss_ce: 0.2726, aux.acc_seg: 74.8240, loss: 0.7672
2022-11-04 14:13:30,945 - mmseg - INFO - Iter [41300/80000]	lr: 6.242e-05, eta: 3:40:18, time: 0.334, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4752, decode.acc_seg: 81.9117, aux.loss_ce: 0.2695, aux.acc_seg: 76.3513, loss: 0.7447
2022-11-04 14:13:47,739 - mmseg - INFO - Iter [41350/80000]	lr: 6.235e-05, eta: 3:40:01, time: 0.336, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4879, decode.acc_seg: 81.2867, aux.loss_ce: 0.2718, aux.acc_seg: 75.9634, loss: 0.7597
2022-11-04 14:14:04,740 - mmseg - INFO - Iter [41400/80000]	lr: 6.228e-05, eta: 3:39:44, time: 0.340, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4719, decode.acc_seg: 81.5649, aux.loss_ce: 0.2626, aux.acc_seg: 76.2697, loss: 0.7345
2022-11-04 14:14:21,452 - mmseg - INFO - Iter [41450/80000]	lr: 6.221e-05, eta: 3:39:26, time: 0.334, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4780, decode.acc_seg: 81.1207, aux.loss_ce: 0.2685, aux.acc_seg: 75.5466, loss: 0.7465
2022-11-04 14:14:37,950 - mmseg - INFO - Iter [41500/80000]	lr: 6.213e-05, eta: 3:39:09, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4808, decode.acc_seg: 81.2446, aux.loss_ce: 0.2640, aux.acc_seg: 76.1508, loss: 0.7448
2022-11-04 14:14:54,691 - mmseg - INFO - Iter [41550/80000]	lr: 6.206e-05, eta: 3:38:51, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4956, decode.acc_seg: 80.7485, aux.loss_ce: 0.2750, aux.acc_seg: 75.0567, loss: 0.7706
2022-11-04 14:15:11,264 - mmseg - INFO - Iter [41600/80000]	lr: 6.199e-05, eta: 3:38:34, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4748, decode.acc_seg: 81.3223, aux.loss_ce: 0.2624, aux.acc_seg: 76.0420, loss: 0.7372
2022-11-04 14:15:30,665 - mmseg - INFO - Iter [41650/80000]	lr: 6.192e-05, eta: 3:38:19, time: 0.388, data_time: 0.059, memory: 12960, decode.loss_ce: 0.4968, decode.acc_seg: 80.9808, aux.loss_ce: 0.2738, aux.acc_seg: 75.3138, loss: 0.7706
2022-11-04 14:15:47,169 - mmseg - INFO - Iter [41700/80000]	lr: 6.184e-05, eta: 3:38:01, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4890, decode.acc_seg: 80.9479, aux.loss_ce: 0.2726, aux.acc_seg: 75.4265, loss: 0.7616
2022-11-04 14:16:03,781 - mmseg - INFO - Iter [41750/80000]	lr: 6.177e-05, eta: 3:37:44, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4757, decode.acc_seg: 81.6269, aux.loss_ce: 0.2664, aux.acc_seg: 75.9635, loss: 0.7422
2022-11-04 14:16:20,279 - mmseg - INFO - Iter [41800/80000]	lr: 6.170e-05, eta: 3:37:26, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4723, decode.acc_seg: 81.6373, aux.loss_ce: 0.2632, aux.acc_seg: 76.1550, loss: 0.7354
2022-11-04 14:16:36,785 - mmseg - INFO - Iter [41850/80000]	lr: 6.162e-05, eta: 3:37:08, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4606, decode.acc_seg: 82.0202, aux.loss_ce: 0.2517, aux.acc_seg: 77.0390, loss: 0.7123
2022-11-04 14:16:53,586 - mmseg - INFO - Iter [41900/80000]	lr: 6.155e-05, eta: 3:36:51, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4993, decode.acc_seg: 80.7134, aux.loss_ce: 0.2796, aux.acc_seg: 74.4460, loss: 0.7789
2022-11-04 14:17:10,222 - mmseg - INFO - Iter [41950/80000]	lr: 6.148e-05, eta: 3:36:34, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4611, decode.acc_seg: 82.1579, aux.loss_ce: 0.2578, aux.acc_seg: 76.9287, loss: 0.7189
2022-11-04 14:17:27,156 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:17:27,157 - mmseg - INFO - Iter [42000/80000]	lr: 6.141e-05, eta: 3:36:16, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4860, decode.acc_seg: 81.0905, aux.loss_ce: 0.2632, aux.acc_seg: 76.1579, loss: 0.7492
2022-11-04 14:17:44,003 - mmseg - INFO - Iter [42050/80000]	lr: 6.133e-05, eta: 3:35:59, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4996, decode.acc_seg: 81.0689, aux.loss_ce: 0.2761, aux.acc_seg: 75.6116, loss: 0.7756
2022-11-04 14:18:00,743 - mmseg - INFO - Iter [42100/80000]	lr: 6.126e-05, eta: 3:35:42, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4811, decode.acc_seg: 81.2216, aux.loss_ce: 0.2724, aux.acc_seg: 75.2681, loss: 0.7535
2022-11-04 14:18:17,376 - mmseg - INFO - Iter [42150/80000]	lr: 6.119e-05, eta: 3:35:24, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4809, decode.acc_seg: 81.2916, aux.loss_ce: 0.2624, aux.acc_seg: 76.0601, loss: 0.7432
2022-11-04 14:18:33,889 - mmseg - INFO - Iter [42200/80000]	lr: 6.112e-05, eta: 3:35:07, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4906, decode.acc_seg: 80.9057, aux.loss_ce: 0.2698, aux.acc_seg: 75.3607, loss: 0.7604
2022-11-04 14:18:50,691 - mmseg - INFO - Iter [42250/80000]	lr: 6.104e-05, eta: 3:34:49, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4811, decode.acc_seg: 81.5042, aux.loss_ce: 0.2665, aux.acc_seg: 75.9062, loss: 0.7476
2022-11-04 14:19:10,255 - mmseg - INFO - Iter [42300/80000]	lr: 6.097e-05, eta: 3:34:35, time: 0.391, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4828, decode.acc_seg: 81.3030, aux.loss_ce: 0.2682, aux.acc_seg: 75.4805, loss: 0.7510
2022-11-04 14:19:26,863 - mmseg - INFO - Iter [42350/80000]	lr: 6.090e-05, eta: 3:34:17, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4816, decode.acc_seg: 81.2643, aux.loss_ce: 0.2663, aux.acc_seg: 75.6280, loss: 0.7479
2022-11-04 14:19:43,562 - mmseg - INFO - Iter [42400/80000]	lr: 6.082e-05, eta: 3:34:00, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4910, decode.acc_seg: 80.9170, aux.loss_ce: 0.2688, aux.acc_seg: 75.5178, loss: 0.7597
2022-11-04 14:20:00,591 - mmseg - INFO - Iter [42450/80000]	lr: 6.075e-05, eta: 3:33:43, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4806, decode.acc_seg: 81.7298, aux.loss_ce: 0.2693, aux.acc_seg: 75.9938, loss: 0.7499
2022-11-04 14:20:17,425 - mmseg - INFO - Iter [42500/80000]	lr: 6.068e-05, eta: 3:33:25, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4982, decode.acc_seg: 80.8669, aux.loss_ce: 0.2733, aux.acc_seg: 75.2872, loss: 0.7715
2022-11-04 14:20:34,098 - mmseg - INFO - Iter [42550/80000]	lr: 6.061e-05, eta: 3:33:08, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4758, decode.acc_seg: 81.3697, aux.loss_ce: 0.2601, aux.acc_seg: 76.2687, loss: 0.7359
2022-11-04 14:20:51,011 - mmseg - INFO - Iter [42600/80000]	lr: 6.053e-05, eta: 3:32:51, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4898, decode.acc_seg: 80.9109, aux.loss_ce: 0.2733, aux.acc_seg: 75.1060, loss: 0.7631
2022-11-04 14:21:07,665 - mmseg - INFO - Iter [42650/80000]	lr: 6.046e-05, eta: 3:32:33, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4703, decode.acc_seg: 82.0292, aux.loss_ce: 0.2603, aux.acc_seg: 76.7839, loss: 0.7307
2022-11-04 14:21:24,429 - mmseg - INFO - Iter [42700/80000]	lr: 6.039e-05, eta: 3:32:16, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5069, decode.acc_seg: 80.5770, aux.loss_ce: 0.2787, aux.acc_seg: 75.2575, loss: 0.7855
2022-11-04 14:21:41,177 - mmseg - INFO - Iter [42750/80000]	lr: 6.031e-05, eta: 3:31:58, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4782, decode.acc_seg: 81.2558, aux.loss_ce: 0.2548, aux.acc_seg: 76.6537, loss: 0.7331
2022-11-04 14:21:57,708 - mmseg - INFO - Iter [42800/80000]	lr: 6.024e-05, eta: 3:31:41, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4713, decode.acc_seg: 81.6173, aux.loss_ce: 0.2568, aux.acc_seg: 76.8601, loss: 0.7280
2022-11-04 14:22:14,367 - mmseg - INFO - Iter [42850/80000]	lr: 6.017e-05, eta: 3:31:24, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4932, decode.acc_seg: 81.0701, aux.loss_ce: 0.2734, aux.acc_seg: 75.5273, loss: 0.7666
2022-11-04 14:22:31,144 - mmseg - INFO - Iter [42900/80000]	lr: 6.010e-05, eta: 3:31:06, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4836, decode.acc_seg: 81.1438, aux.loss_ce: 0.2687, aux.acc_seg: 75.8118, loss: 0.7522
2022-11-04 14:22:50,739 - mmseg - INFO - Iter [42950/80000]	lr: 6.002e-05, eta: 3:30:51, time: 0.392, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4691, decode.acc_seg: 81.7018, aux.loss_ce: 0.2636, aux.acc_seg: 76.2005, loss: 0.7326
2022-11-04 14:23:07,512 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:23:07,512 - mmseg - INFO - Iter [43000/80000]	lr: 5.995e-05, eta: 3:30:34, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4919, decode.acc_seg: 81.2276, aux.loss_ce: 0.2735, aux.acc_seg: 75.4174, loss: 0.7654
2022-11-04 14:23:24,334 - mmseg - INFO - Iter [43050/80000]	lr: 5.988e-05, eta: 3:30:17, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4797, decode.acc_seg: 81.6211, aux.loss_ce: 0.2684, aux.acc_seg: 75.9882, loss: 0.7481
2022-11-04 14:23:40,774 - mmseg - INFO - Iter [43100/80000]	lr: 5.980e-05, eta: 3:29:59, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4775, decode.acc_seg: 81.3792, aux.loss_ce: 0.2610, aux.acc_seg: 76.1370, loss: 0.7384
2022-11-04 14:23:57,454 - mmseg - INFO - Iter [43150/80000]	lr: 5.973e-05, eta: 3:29:42, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4853, decode.acc_seg: 81.0672, aux.loss_ce: 0.2663, aux.acc_seg: 75.8889, loss: 0.7515
2022-11-04 14:24:14,147 - mmseg - INFO - Iter [43200/80000]	lr: 5.966e-05, eta: 3:29:24, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4780, decode.acc_seg: 81.3254, aux.loss_ce: 0.2644, aux.acc_seg: 75.8894, loss: 0.7424
2022-11-04 14:24:30,612 - mmseg - INFO - Iter [43250/80000]	lr: 5.959e-05, eta: 3:29:07, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4831, decode.acc_seg: 81.0886, aux.loss_ce: 0.2676, aux.acc_seg: 75.6903, loss: 0.7507
2022-11-04 14:24:47,205 - mmseg - INFO - Iter [43300/80000]	lr: 5.951e-05, eta: 3:28:49, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4721, decode.acc_seg: 81.7643, aux.loss_ce: 0.2629, aux.acc_seg: 76.1650, loss: 0.7351
2022-11-04 14:25:03,867 - mmseg - INFO - Iter [43350/80000]	lr: 5.944e-05, eta: 3:28:32, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.5072, decode.acc_seg: 80.7337, aux.loss_ce: 0.2826, aux.acc_seg: 75.1532, loss: 0.7898
2022-11-04 14:25:20,586 - mmseg - INFO - Iter [43400/80000]	lr: 5.937e-05, eta: 3:28:14, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4757, decode.acc_seg: 81.6151, aux.loss_ce: 0.2692, aux.acc_seg: 75.7299, loss: 0.7449
2022-11-04 14:25:37,511 - mmseg - INFO - Iter [43450/80000]	lr: 5.929e-05, eta: 3:27:57, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4689, decode.acc_seg: 81.8332, aux.loss_ce: 0.2639, aux.acc_seg: 76.0753, loss: 0.7328
2022-11-04 14:25:54,145 - mmseg - INFO - Iter [43500/80000]	lr: 5.922e-05, eta: 3:27:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4675, decode.acc_seg: 81.8769, aux.loss_ce: 0.2637, aux.acc_seg: 76.2249, loss: 0.7313
2022-11-04 14:26:13,811 - mmseg - INFO - Iter [43550/80000]	lr: 5.915e-05, eta: 3:27:25, time: 0.393, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4852, decode.acc_seg: 81.3163, aux.loss_ce: 0.2655, aux.acc_seg: 75.8430, loss: 0.7507
2022-11-04 14:26:30,343 - mmseg - INFO - Iter [43600/80000]	lr: 5.907e-05, eta: 3:27:07, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4764, decode.acc_seg: 81.6807, aux.loss_ce: 0.2619, aux.acc_seg: 76.3303, loss: 0.7383
2022-11-04 14:26:47,253 - mmseg - INFO - Iter [43650/80000]	lr: 5.900e-05, eta: 3:26:50, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4720, decode.acc_seg: 81.6210, aux.loss_ce: 0.2605, aux.acc_seg: 76.1070, loss: 0.7324
2022-11-04 14:27:04,224 - mmseg - INFO - Iter [43700/80000]	lr: 5.893e-05, eta: 3:26:33, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4913, decode.acc_seg: 81.2692, aux.loss_ce: 0.2803, aux.acc_seg: 75.2886, loss: 0.7716
2022-11-04 14:27:20,830 - mmseg - INFO - Iter [43750/80000]	lr: 5.886e-05, eta: 3:26:16, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4785, decode.acc_seg: 81.4818, aux.loss_ce: 0.2629, aux.acc_seg: 75.9834, loss: 0.7414
2022-11-04 14:27:37,654 - mmseg - INFO - Iter [43800/80000]	lr: 5.878e-05, eta: 3:25:58, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4836, decode.acc_seg: 81.3877, aux.loss_ce: 0.2698, aux.acc_seg: 75.8592, loss: 0.7534
2022-11-04 14:27:54,544 - mmseg - INFO - Iter [43850/80000]	lr: 5.871e-05, eta: 3:25:41, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4827, decode.acc_seg: 81.4541, aux.loss_ce: 0.2704, aux.acc_seg: 75.8837, loss: 0.7531
2022-11-04 14:28:11,247 - mmseg - INFO - Iter [43900/80000]	lr: 5.864e-05, eta: 3:25:24, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4827, decode.acc_seg: 81.3842, aux.loss_ce: 0.2642, aux.acc_seg: 76.1023, loss: 0.7469
2022-11-04 14:28:27,859 - mmseg - INFO - Iter [43950/80000]	lr: 5.856e-05, eta: 3:25:06, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4692, decode.acc_seg: 81.9502, aux.loss_ce: 0.2619, aux.acc_seg: 76.5688, loss: 0.7311
2022-11-04 14:28:44,750 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:28:44,751 - mmseg - INFO - Iter [44000/80000]	lr: 5.849e-05, eta: 3:24:49, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4891, decode.acc_seg: 81.0099, aux.loss_ce: 0.2699, aux.acc_seg: 75.4901, loss: 0.7590
2022-11-04 14:29:01,362 - mmseg - INFO - Iter [44050/80000]	lr: 5.842e-05, eta: 3:24:32, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4606, decode.acc_seg: 82.1424, aux.loss_ce: 0.2520, aux.acc_seg: 77.0715, loss: 0.7125
2022-11-04 14:29:18,095 - mmseg - INFO - Iter [44100/80000]	lr: 5.834e-05, eta: 3:24:14, time: 0.335, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4668, decode.acc_seg: 81.7760, aux.loss_ce: 0.2676, aux.acc_seg: 75.7860, loss: 0.7345
2022-11-04 14:29:34,788 - mmseg - INFO - Iter [44150/80000]	lr: 5.827e-05, eta: 3:23:57, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4742, decode.acc_seg: 81.7586, aux.loss_ce: 0.2674, aux.acc_seg: 76.0725, loss: 0.7415
2022-11-04 14:29:54,325 - mmseg - INFO - Iter [44200/80000]	lr: 5.820e-05, eta: 3:23:42, time: 0.391, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4725, decode.acc_seg: 81.5454, aux.loss_ce: 0.2637, aux.acc_seg: 76.2213, loss: 0.7362
2022-11-04 14:30:11,157 - mmseg - INFO - Iter [44250/80000]	lr: 5.812e-05, eta: 3:23:25, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4795, decode.acc_seg: 81.3539, aux.loss_ce: 0.2658, aux.acc_seg: 75.9842, loss: 0.7453
2022-11-04 14:30:27,852 - mmseg - INFO - Iter [44300/80000]	lr: 5.805e-05, eta: 3:23:07, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4775, decode.acc_seg: 81.8137, aux.loss_ce: 0.2702, aux.acc_seg: 75.6505, loss: 0.7477
2022-11-04 14:30:44,327 - mmseg - INFO - Iter [44350/80000]	lr: 5.798e-05, eta: 3:22:50, time: 0.329, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4818, decode.acc_seg: 81.3928, aux.loss_ce: 0.2689, aux.acc_seg: 75.9061, loss: 0.7507
2022-11-04 14:31:01,191 - mmseg - INFO - Iter [44400/80000]	lr: 5.791e-05, eta: 3:22:32, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4771, decode.acc_seg: 81.6192, aux.loss_ce: 0.2633, aux.acc_seg: 76.5987, loss: 0.7403
2022-11-04 14:31:17,971 - mmseg - INFO - Iter [44450/80000]	lr: 5.783e-05, eta: 3:22:15, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4630, decode.acc_seg: 81.8429, aux.loss_ce: 0.2619, aux.acc_seg: 76.0012, loss: 0.7249
2022-11-04 14:31:34,722 - mmseg - INFO - Iter [44500/80000]	lr: 5.776e-05, eta: 3:21:58, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4654, decode.acc_seg: 81.9842, aux.loss_ce: 0.2547, aux.acc_seg: 76.6447, loss: 0.7200
2022-11-04 14:31:51,472 - mmseg - INFO - Iter [44550/80000]	lr: 5.769e-05, eta: 3:21:40, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4691, decode.acc_seg: 81.9127, aux.loss_ce: 0.2572, aux.acc_seg: 76.3694, loss: 0.7263
2022-11-04 14:32:08,249 - mmseg - INFO - Iter [44600/80000]	lr: 5.761e-05, eta: 3:21:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4798, decode.acc_seg: 81.4470, aux.loss_ce: 0.2673, aux.acc_seg: 75.8410, loss: 0.7471
2022-11-04 14:32:24,868 - mmseg - INFO - Iter [44650/80000]	lr: 5.754e-05, eta: 3:21:06, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4807, decode.acc_seg: 81.5457, aux.loss_ce: 0.2707, aux.acc_seg: 75.8477, loss: 0.7514
2022-11-04 14:32:41,690 - mmseg - INFO - Iter [44700/80000]	lr: 5.747e-05, eta: 3:20:48, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4792, decode.acc_seg: 81.3718, aux.loss_ce: 0.2645, aux.acc_seg: 76.2397, loss: 0.7436
2022-11-04 14:32:58,552 - mmseg - INFO - Iter [44750/80000]	lr: 5.739e-05, eta: 3:20:31, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4741, decode.acc_seg: 81.4931, aux.loss_ce: 0.2666, aux.acc_seg: 75.8593, loss: 0.7407
2022-11-04 14:33:15,029 - mmseg - INFO - Iter [44800/80000]	lr: 5.732e-05, eta: 3:20:14, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4698, decode.acc_seg: 81.2879, aux.loss_ce: 0.2583, aux.acc_seg: 75.8269, loss: 0.7281
2022-11-04 14:33:34,814 - mmseg - INFO - Iter [44850/80000]	lr: 5.725e-05, eta: 3:19:59, time: 0.396, data_time: 0.068, memory: 12960, decode.loss_ce: 0.4763, decode.acc_seg: 81.6822, aux.loss_ce: 0.2668, aux.acc_seg: 75.9715, loss: 0.7430
2022-11-04 14:33:51,947 - mmseg - INFO - Iter [44900/80000]	lr: 5.717e-05, eta: 3:19:42, time: 0.343, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4592, decode.acc_seg: 82.3630, aux.loss_ce: 0.2585, aux.acc_seg: 76.5806, loss: 0.7177
2022-11-04 14:34:08,756 - mmseg - INFO - Iter [44950/80000]	lr: 5.710e-05, eta: 3:19:24, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4640, decode.acc_seg: 82.1086, aux.loss_ce: 0.2587, aux.acc_seg: 76.5865, loss: 0.7227
2022-11-04 14:34:25,550 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:34:25,550 - mmseg - INFO - Iter [45000/80000]	lr: 5.703e-05, eta: 3:19:07, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4716, decode.acc_seg: 81.4229, aux.loss_ce: 0.2651, aux.acc_seg: 75.9194, loss: 0.7367
2022-11-04 14:34:42,437 - mmseg - INFO - Iter [45050/80000]	lr: 5.695e-05, eta: 3:18:50, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4776, decode.acc_seg: 81.4445, aux.loss_ce: 0.2657, aux.acc_seg: 75.8303, loss: 0.7433
2022-11-04 14:34:59,237 - mmseg - INFO - Iter [45100/80000]	lr: 5.688e-05, eta: 3:18:33, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4796, decode.acc_seg: 81.6757, aux.loss_ce: 0.2640, aux.acc_seg: 76.0732, loss: 0.7436
2022-11-04 14:35:16,289 - mmseg - INFO - Iter [45150/80000]	lr: 5.681e-05, eta: 3:18:16, time: 0.341, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4675, decode.acc_seg: 81.5846, aux.loss_ce: 0.2554, aux.acc_seg: 76.3487, loss: 0.7229
2022-11-04 14:35:32,976 - mmseg - INFO - Iter [45200/80000]	lr: 5.673e-05, eta: 3:17:58, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4745, decode.acc_seg: 81.6014, aux.loss_ce: 0.2652, aux.acc_seg: 75.8561, loss: 0.7397
2022-11-04 14:35:49,746 - mmseg - INFO - Iter [45250/80000]	lr: 5.666e-05, eta: 3:17:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4683, decode.acc_seg: 81.8848, aux.loss_ce: 0.2633, aux.acc_seg: 76.4620, loss: 0.7316
2022-11-04 14:36:06,595 - mmseg - INFO - Iter [45300/80000]	lr: 5.659e-05, eta: 3:17:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4782, decode.acc_seg: 81.4327, aux.loss_ce: 0.2681, aux.acc_seg: 75.6307, loss: 0.7463
2022-11-04 14:36:23,529 - mmseg - INFO - Iter [45350/80000]	lr: 5.651e-05, eta: 3:17:07, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4599, decode.acc_seg: 81.7992, aux.loss_ce: 0.2586, aux.acc_seg: 76.2585, loss: 0.7185
2022-11-04 14:36:40,169 - mmseg - INFO - Iter [45400/80000]	lr: 5.644e-05, eta: 3:16:49, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4769, decode.acc_seg: 81.3773, aux.loss_ce: 0.2621, aux.acc_seg: 76.0448, loss: 0.7391
2022-11-04 14:36:59,778 - mmseg - INFO - Iter [45450/80000]	lr: 5.637e-05, eta: 3:16:34, time: 0.392, data_time: 0.065, memory: 12960, decode.loss_ce: 0.4743, decode.acc_seg: 81.6439, aux.loss_ce: 0.2683, aux.acc_seg: 75.9664, loss: 0.7426
2022-11-04 14:37:16,558 - mmseg - INFO - Iter [45500/80000]	lr: 5.629e-05, eta: 3:16:17, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4667, decode.acc_seg: 81.4770, aux.loss_ce: 0.2642, aux.acc_seg: 76.0097, loss: 0.7309
2022-11-04 14:37:33,124 - mmseg - INFO - Iter [45550/80000]	lr: 5.622e-05, eta: 3:15:59, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4727, decode.acc_seg: 81.6829, aux.loss_ce: 0.2650, aux.acc_seg: 75.8556, loss: 0.7377
2022-11-04 14:37:49,717 - mmseg - INFO - Iter [45600/80000]	lr: 5.615e-05, eta: 3:15:42, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4523, decode.acc_seg: 82.3128, aux.loss_ce: 0.2524, aux.acc_seg: 76.7502, loss: 0.7047
2022-11-04 14:38:06,231 - mmseg - INFO - Iter [45650/80000]	lr: 5.607e-05, eta: 3:15:24, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4653, decode.acc_seg: 81.6887, aux.loss_ce: 0.2587, aux.acc_seg: 76.2551, loss: 0.7240
2022-11-04 14:38:22,850 - mmseg - INFO - Iter [45700/80000]	lr: 5.600e-05, eta: 3:15:07, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4637, decode.acc_seg: 82.1987, aux.loss_ce: 0.2620, aux.acc_seg: 76.4274, loss: 0.7257
2022-11-04 14:38:39,671 - mmseg - INFO - Iter [45750/80000]	lr: 5.593e-05, eta: 3:14:50, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4730, decode.acc_seg: 81.3940, aux.loss_ce: 0.2670, aux.acc_seg: 75.9698, loss: 0.7400
2022-11-04 14:38:56,437 - mmseg - INFO - Iter [45800/80000]	lr: 5.585e-05, eta: 3:14:32, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4783, decode.acc_seg: 81.4984, aux.loss_ce: 0.2668, aux.acc_seg: 75.9206, loss: 0.7451
2022-11-04 14:39:13,208 - mmseg - INFO - Iter [45850/80000]	lr: 5.578e-05, eta: 3:14:15, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4589, decode.acc_seg: 82.2500, aux.loss_ce: 0.2511, aux.acc_seg: 77.4306, loss: 0.7099
2022-11-04 14:39:29,914 - mmseg - INFO - Iter [45900/80000]	lr: 5.570e-05, eta: 3:13:58, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4754, decode.acc_seg: 81.5639, aux.loss_ce: 0.2653, aux.acc_seg: 75.9895, loss: 0.7407
2022-11-04 14:39:46,661 - mmseg - INFO - Iter [45950/80000]	lr: 5.563e-05, eta: 3:13:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4750, decode.acc_seg: 81.5074, aux.loss_ce: 0.2634, aux.acc_seg: 76.3329, loss: 0.7385
2022-11-04 14:40:03,427 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:40:03,428 - mmseg - INFO - Iter [46000/80000]	lr: 5.556e-05, eta: 3:13:23, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4809, decode.acc_seg: 81.0558, aux.loss_ce: 0.2705, aux.acc_seg: 75.0909, loss: 0.7514
2022-11-04 14:40:20,158 - mmseg - INFO - Iter [46050/80000]	lr: 5.548e-05, eta: 3:13:06, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4753, decode.acc_seg: 81.4235, aux.loss_ce: 0.2667, aux.acc_seg: 75.7198, loss: 0.7420
2022-11-04 14:40:39,604 - mmseg - INFO - Iter [46100/80000]	lr: 5.541e-05, eta: 3:12:51, time: 0.389, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4857, decode.acc_seg: 81.3139, aux.loss_ce: 0.2677, aux.acc_seg: 76.0346, loss: 0.7534
2022-11-04 14:40:56,609 - mmseg - INFO - Iter [46150/80000]	lr: 5.534e-05, eta: 3:12:34, time: 0.340, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4628, decode.acc_seg: 82.1816, aux.loss_ce: 0.2633, aux.acc_seg: 76.3657, loss: 0.7260
2022-11-04 14:41:13,685 - mmseg - INFO - Iter [46200/80000]	lr: 5.526e-05, eta: 3:12:16, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4599, decode.acc_seg: 82.2301, aux.loss_ce: 0.2628, aux.acc_seg: 76.4324, loss: 0.7228
2022-11-04 14:41:30,603 - mmseg - INFO - Iter [46250/80000]	lr: 5.519e-05, eta: 3:11:59, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4647, decode.acc_seg: 81.8170, aux.loss_ce: 0.2623, aux.acc_seg: 76.2419, loss: 0.7270
2022-11-04 14:41:47,263 - mmseg - INFO - Iter [46300/80000]	lr: 5.512e-05, eta: 3:11:42, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4804, decode.acc_seg: 81.3708, aux.loss_ce: 0.2715, aux.acc_seg: 75.3485, loss: 0.7519
2022-11-04 14:42:04,122 - mmseg - INFO - Iter [46350/80000]	lr: 5.504e-05, eta: 3:11:25, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4704, decode.acc_seg: 81.8231, aux.loss_ce: 0.2562, aux.acc_seg: 76.6241, loss: 0.7266
2022-11-04 14:42:20,770 - mmseg - INFO - Iter [46400/80000]	lr: 5.497e-05, eta: 3:11:07, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4653, decode.acc_seg: 81.9727, aux.loss_ce: 0.2615, aux.acc_seg: 76.1752, loss: 0.7268
2022-11-04 14:42:37,465 - mmseg - INFO - Iter [46450/80000]	lr: 5.490e-05, eta: 3:10:50, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4521, decode.acc_seg: 81.9719, aux.loss_ce: 0.2536, aux.acc_seg: 76.3377, loss: 0.7057
2022-11-04 14:42:54,478 - mmseg - INFO - Iter [46500/80000]	lr: 5.482e-05, eta: 3:10:33, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4750, decode.acc_seg: 82.0105, aux.loss_ce: 0.2604, aux.acc_seg: 76.4434, loss: 0.7354
2022-11-04 14:43:11,274 - mmseg - INFO - Iter [46550/80000]	lr: 5.475e-05, eta: 3:10:16, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4567, decode.acc_seg: 81.9927, aux.loss_ce: 0.2585, aux.acc_seg: 76.2881, loss: 0.7152
2022-11-04 14:43:28,039 - mmseg - INFO - Iter [46600/80000]	lr: 5.467e-05, eta: 3:09:58, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4888, decode.acc_seg: 81.1337, aux.loss_ce: 0.2696, aux.acc_seg: 75.6822, loss: 0.7584
2022-11-04 14:43:44,820 - mmseg - INFO - Iter [46650/80000]	lr: 5.460e-05, eta: 3:09:41, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4604, decode.acc_seg: 82.0434, aux.loss_ce: 0.2639, aux.acc_seg: 76.1230, loss: 0.7244
2022-11-04 14:44:04,573 - mmseg - INFO - Iter [46700/80000]	lr: 5.453e-05, eta: 3:09:26, time: 0.395, data_time: 0.058, memory: 12960, decode.loss_ce: 0.4487, decode.acc_seg: 82.5866, aux.loss_ce: 0.2564, aux.acc_seg: 76.5635, loss: 0.7051
2022-11-04 14:44:21,142 - mmseg - INFO - Iter [46750/80000]	lr: 5.445e-05, eta: 3:09:09, time: 0.331, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4450, decode.acc_seg: 82.1480, aux.loss_ce: 0.2498, aux.acc_seg: 76.4231, loss: 0.6948
2022-11-04 14:44:37,808 - mmseg - INFO - Iter [46800/80000]	lr: 5.438e-05, eta: 3:08:51, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4643, decode.acc_seg: 81.7787, aux.loss_ce: 0.2576, aux.acc_seg: 76.4257, loss: 0.7218
2022-11-04 14:44:54,688 - mmseg - INFO - Iter [46850/80000]	lr: 5.431e-05, eta: 3:08:34, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4701, decode.acc_seg: 82.0510, aux.loss_ce: 0.2634, aux.acc_seg: 76.3263, loss: 0.7336
2022-11-04 14:45:11,344 - mmseg - INFO - Iter [46900/80000]	lr: 5.423e-05, eta: 3:08:17, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4766, decode.acc_seg: 81.6474, aux.loss_ce: 0.2710, aux.acc_seg: 75.7603, loss: 0.7475
2022-11-04 14:45:28,050 - mmseg - INFO - Iter [46950/80000]	lr: 5.416e-05, eta: 3:07:59, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4656, decode.acc_seg: 81.7968, aux.loss_ce: 0.2627, aux.acc_seg: 76.3128, loss: 0.7283
2022-11-04 14:45:44,584 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:45:44,584 - mmseg - INFO - Iter [47000/80000]	lr: 5.408e-05, eta: 3:07:42, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4699, decode.acc_seg: 81.6680, aux.loss_ce: 0.2639, aux.acc_seg: 76.1635, loss: 0.7339
2022-11-04 14:46:01,290 - mmseg - INFO - Iter [47050/80000]	lr: 5.401e-05, eta: 3:07:25, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4742, decode.acc_seg: 81.5200, aux.loss_ce: 0.2646, aux.acc_seg: 75.9766, loss: 0.7387
2022-11-04 14:46:17,938 - mmseg - INFO - Iter [47100/80000]	lr: 5.394e-05, eta: 3:07:07, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4619, decode.acc_seg: 82.0194, aux.loss_ce: 0.2622, aux.acc_seg: 76.4179, loss: 0.7241
2022-11-04 14:46:34,673 - mmseg - INFO - Iter [47150/80000]	lr: 5.386e-05, eta: 3:06:50, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4560, decode.acc_seg: 82.4607, aux.loss_ce: 0.2568, aux.acc_seg: 76.7604, loss: 0.7129
2022-11-04 14:46:51,386 - mmseg - INFO - Iter [47200/80000]	lr: 5.379e-05, eta: 3:06:33, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4813, decode.acc_seg: 81.4987, aux.loss_ce: 0.2679, aux.acc_seg: 76.1894, loss: 0.7492
2022-11-04 14:47:08,105 - mmseg - INFO - Iter [47250/80000]	lr: 5.372e-05, eta: 3:06:15, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4759, decode.acc_seg: 81.6239, aux.loss_ce: 0.2687, aux.acc_seg: 75.7028, loss: 0.7446
2022-11-04 14:47:24,954 - mmseg - INFO - Iter [47300/80000]	lr: 5.364e-05, eta: 3:05:58, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4697, decode.acc_seg: 81.7134, aux.loss_ce: 0.2622, aux.acc_seg: 75.7869, loss: 0.7319
2022-11-04 14:47:44,772 - mmseg - INFO - Iter [47350/80000]	lr: 5.357e-05, eta: 3:05:43, time: 0.396, data_time: 0.073, memory: 12960, decode.loss_ce: 0.4837, decode.acc_seg: 81.2318, aux.loss_ce: 0.2731, aux.acc_seg: 75.4782, loss: 0.7568
2022-11-04 14:48:01,455 - mmseg - INFO - Iter [47400/80000]	lr: 5.349e-05, eta: 3:05:26, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4448, decode.acc_seg: 82.7732, aux.loss_ce: 0.2486, aux.acc_seg: 77.4915, loss: 0.6934
2022-11-04 14:48:18,165 - mmseg - INFO - Iter [47450/80000]	lr: 5.342e-05, eta: 3:05:08, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4777, decode.acc_seg: 81.5750, aux.loss_ce: 0.2636, aux.acc_seg: 76.0132, loss: 0.7412
2022-11-04 14:48:35,138 - mmseg - INFO - Iter [47500/80000]	lr: 5.335e-05, eta: 3:04:51, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4593, decode.acc_seg: 81.9633, aux.loss_ce: 0.2546, aux.acc_seg: 76.7812, loss: 0.7139
2022-11-04 14:48:51,881 - mmseg - INFO - Iter [47550/80000]	lr: 5.327e-05, eta: 3:04:34, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4559, decode.acc_seg: 82.3973, aux.loss_ce: 0.2576, aux.acc_seg: 76.7687, loss: 0.7134
2022-11-04 14:49:08,656 - mmseg - INFO - Iter [47600/80000]	lr: 5.320e-05, eta: 3:04:17, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4672, decode.acc_seg: 81.7869, aux.loss_ce: 0.2638, aux.acc_seg: 76.1304, loss: 0.7310
2022-11-04 14:49:25,424 - mmseg - INFO - Iter [47650/80000]	lr: 5.313e-05, eta: 3:03:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4678, decode.acc_seg: 82.0247, aux.loss_ce: 0.2586, aux.acc_seg: 76.6289, loss: 0.7264
2022-11-04 14:49:42,283 - mmseg - INFO - Iter [47700/80000]	lr: 5.305e-05, eta: 3:03:42, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4604, decode.acc_seg: 82.4524, aux.loss_ce: 0.2589, aux.acc_seg: 76.6003, loss: 0.7193
2022-11-04 14:49:58,995 - mmseg - INFO - Iter [47750/80000]	lr: 5.298e-05, eta: 3:03:25, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4794, decode.acc_seg: 81.4942, aux.loss_ce: 0.2638, aux.acc_seg: 76.2425, loss: 0.7432
2022-11-04 14:50:15,895 - mmseg - INFO - Iter [47800/80000]	lr: 5.290e-05, eta: 3:03:08, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4630, decode.acc_seg: 81.9897, aux.loss_ce: 0.2583, aux.acc_seg: 76.6546, loss: 0.7213
2022-11-04 14:50:32,650 - mmseg - INFO - Iter [47850/80000]	lr: 5.283e-05, eta: 3:02:50, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4764, decode.acc_seg: 81.5995, aux.loss_ce: 0.2648, aux.acc_seg: 76.5066, loss: 0.7412
2022-11-04 14:50:49,491 - mmseg - INFO - Iter [47900/80000]	lr: 5.276e-05, eta: 3:02:33, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4650, decode.acc_seg: 81.8538, aux.loss_ce: 0.2633, aux.acc_seg: 76.2979, loss: 0.7283
2022-11-04 14:51:06,142 - mmseg - INFO - Iter [47950/80000]	lr: 5.268e-05, eta: 3:02:16, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4621, decode.acc_seg: 82.2149, aux.loss_ce: 0.2558, aux.acc_seg: 76.8294, loss: 0.7179
2022-11-04 14:51:25,741 - mmseg - INFO - Saving checkpoint at 48000 iterations
2022-11-04 14:51:25,994 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:51:25,995 - mmseg - INFO - Iter [48000/80000]	lr: 5.261e-05, eta: 3:02:01, time: 0.397, data_time: 0.065, memory: 12960, decode.loss_ce: 0.4608, decode.acc_seg: 82.2392, aux.loss_ce: 0.2608, aux.acc_seg: 76.4187, loss: 0.7216
2022-11-04 14:51:34,871 - mmseg - INFO - per class results:
2022-11-04 14:51:34,878 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 66.47 | 83.38 |
|       building      | 75.53 | 89.49 |
|         sky         | 88.54 | 92.61 |
|        floor        | 70.87 | 84.35 |
|         tree        | 67.41 |  84.1 |
|       ceiling       | 76.18 | 85.78 |
|         road        | 74.84 | 87.29 |
|         bed         | 75.48 | 89.88 |
|      windowpane     | 50.28 | 68.98 |
|        grass        | 64.82 | 84.15 |
|       cabinet       | 48.48 | 65.57 |
|       sidewalk      | 51.78 | 65.78 |
|        person       | 64.56 | 81.81 |
|        earth        | 29.74 | 41.57 |
|         door        |  24.1 | 37.11 |
|        table        |  39.3 | 55.08 |
|       mountain      |  53.0 | 71.25 |
|        plant        | 45.12 | 58.59 |
|       curtain       | 55.55 | 71.07 |
|        chair        | 37.33 | 51.88 |
|         car         | 70.98 | 84.58 |
|        water        | 45.48 | 64.58 |
|       painting      | 55.18 | 72.98 |
|         sofa        | 48.22 | 70.48 |
|        shelf        | 29.17 | 41.98 |
|        house        | 41.55 | 62.73 |
|         sea         | 34.46 | 54.58 |
|        mirror       | 39.39 | 49.81 |
|         rug         | 46.95 | 57.92 |
|        field        | 35.24 | 47.91 |
|       armchair      | 26.12 | 39.33 |
|         seat        |  50.0 | 68.94 |
|        fence        | 25.52 | 43.42 |
|         desk        | 31.16 | 55.51 |
|         rock        | 37.57 | 58.37 |
|       wardrobe      | 34.73 | 54.04 |
|         lamp        | 37.26 | 49.09 |
|       bathtub       | 53.64 | 63.54 |
|       railing       | 25.12 | 38.14 |
|       cushion       | 31.29 | 42.74 |
|         base        | 16.11 | 19.51 |
|         box         |  16.2 | 24.46 |
|        column       | 29.34 | 34.38 |
|      signboard      | 23.62 | 31.95 |
|   chest of drawers  | 27.18 | 41.44 |
|       counter       | 28.48 |  34.4 |
|         sand        | 25.89 |  39.1 |
|         sink        | 45.37 | 57.24 |
|      skyscraper     | 65.58 | 86.67 |
|      fireplace      | 59.87 | 71.89 |
|     refrigerator    | 48.86 | 64.75 |
|      grandstand     | 40.69 | 62.91 |
|         path        |  15.6 | 21.64 |
|        stairs       | 20.79 | 23.64 |
|        runway       | 71.27 | 85.71 |
|         case        | 32.06 | 42.45 |
|      pool table     | 80.05 | 90.97 |
|        pillow       | 36.93 | 46.45 |
|     screen door     | 42.38 | 56.89 |
|       stairway      | 26.96 | 31.35 |
|        river        |  7.39 | 10.54 |
|        bridge       | 45.76 | 65.64 |
|       bookcase      | 29.09 |  45.9 |
|        blind        | 26.28 | 32.54 |
|     coffee table    | 39.28 | 65.14 |
|        toilet       | 66.12 | 76.77 |
|        flower       | 29.02 | 39.95 |
|         book        | 34.34 | 46.46 |
|         hill        |  4.46 |  5.7  |
|        bench        | 28.95 | 37.05 |
|      countertop     | 41.02 | 50.52 |
|        stove        | 43.37 | 49.97 |
|         palm        | 36.73 | 50.88 |
|    kitchen island   | 18.59 | 47.84 |
|       computer      | 44.01 | 57.74 |
|     swivel chair    | 26.57 | 32.06 |
|         boat        | 41.98 | 52.65 |
|         bar         |  23.7 | 28.43 |
|    arcade machine   | 26.05 | 34.15 |
|        hovel        | 30.56 | 37.85 |
|         bus         | 72.99 |  85.4 |
|        towel        | 35.01 | 45.78 |
|        light        | 16.23 | 17.95 |
|        truck        |  3.65 |  4.6  |
|        tower        | 26.77 | 31.01 |
|      chandelier     | 46.75 | 62.39 |
|        awning       | 15.76 | 18.56 |
|     streetlight     |  5.29 |  6.11 |
|        booth        |  26.5 | 31.62 |
| television receiver | 39.25 | 63.24 |
|       airplane      | 43.35 | 50.91 |
|      dirt track     |  5.71 | 15.78 |
|       apparel       | 17.73 | 24.53 |
|         pole        |  6.56 | 10.06 |
|         land        |  2.46 |  3.29 |
|      bannister      |  0.47 |  0.63 |
|      escalator      | 31.35 | 32.96 |
|       ottoman       | 25.28 | 29.88 |
|        bottle       | 15.73 | 31.59 |
|        buffet       | 33.18 | 43.73 |
|        poster       | 16.61 |  19.8 |
|        stage        | 11.43 |  15.4 |
|         van         |  17.8 | 20.85 |
|         ship        |  3.22 |  3.87 |
|       fountain      | 15.64 |  16.0 |
|    conveyer belt    | 55.56 | 60.43 |
|        canopy       | 20.07 | 24.59 |
|        washer       | 54.41 | 57.72 |
|      plaything      |  6.7  |  9.94 |
|    swimming pool    | 28.38 | 45.49 |
|        stool        |  13.6 | 16.91 |
|        barrel       | 26.81 | 62.49 |
|        basket       | 12.49 | 17.46 |
|      waterfall      | 45.04 | 55.46 |
|         tent        | 77.69 | 96.32 |
|         bag         |  2.34 |  2.61 |
|       minibike      | 46.33 | 55.86 |
|        cradle       | 55.71 | 79.85 |
|         oven        | 15.27 | 27.24 |
|         ball        | 22.99 | 26.37 |
|         food        | 41.51 | 53.42 |
|         step        |  1.44 |  1.46 |
|         tank        | 25.12 | 29.85 |
|      trade name     | 17.63 | 19.25 |
|      microwave      | 25.33 | 28.61 |
|         pot         | 17.74 | 20.39 |
|        animal       | 42.34 | 49.51 |
|       bicycle       | 36.55 | 55.13 |
|         lake        |  0.0  |  0.0  |
|      dishwasher     | 27.91 |  36.8 |
|        screen       | 55.77 | 75.94 |
|       blanket       |  2.17 |  2.42 |
|      sculpture      | 32.13 | 46.05 |
|         hood        | 29.34 | 33.72 |
|        sconce       | 11.98 | 12.89 |
|         vase        | 15.42 | 20.92 |
|    traffic light    |  9.64 | 12.82 |
|         tray        |  2.23 |  4.9  |
|        ashcan       | 19.46 | 23.48 |
|         fan         | 30.09 | 39.45 |
|         pier        | 29.62 | 39.73 |
|      crt screen     |  0.0  |  0.0  |
|        plate        | 32.68 | 42.03 |
|       monitor       |  47.6 | 52.34 |
|    bulletin board   | 26.74 | 30.49 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 37.25 | 43.05 |
|        glass        |  0.01 |  0.01 |
|        clock        |  9.67 | 10.36 |
|         flag        |  14.1 | 15.05 |
+---------------------+-------+-------+
2022-11-04 14:51:34,879 - mmseg - INFO - Summary:
2022-11-04 14:51:34,879 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 75.23 | 33.43 | 43.54 |
+-------+-------+-------+
2022-11-04 14:51:34,880 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:51:34,881 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7523, mIoU: 0.3343, mAcc: 0.4354, IoU.wall: 0.6647, IoU.building: 0.7553, IoU.sky: 0.8854, IoU.floor: 0.7087, IoU.tree: 0.6741, IoU.ceiling: 0.7618, IoU.road: 0.7484, IoU.bed : 0.7548, IoU.windowpane: 0.5028, IoU.grass: 0.6482, IoU.cabinet: 0.4848, IoU.sidewalk: 0.5178, IoU.person: 0.6456, IoU.earth: 0.2974, IoU.door: 0.2410, IoU.table: 0.3930, IoU.mountain: 0.5300, IoU.plant: 0.4512, IoU.curtain: 0.5555, IoU.chair: 0.3733, IoU.car: 0.7098, IoU.water: 0.4548, IoU.painting: 0.5518, IoU.sofa: 0.4822, IoU.shelf: 0.2917, IoU.house: 0.4155, IoU.sea: 0.3446, IoU.mirror: 0.3939, IoU.rug: 0.4695, IoU.field: 0.3524, IoU.armchair: 0.2612, IoU.seat: 0.5000, IoU.fence: 0.2552, IoU.desk: 0.3116, IoU.rock: 0.3757, IoU.wardrobe: 0.3473, IoU.lamp: 0.3726, IoU.bathtub: 0.5364, IoU.railing: 0.2512, IoU.cushion: 0.3129, IoU.base: 0.1611, IoU.box: 0.1620, IoU.column: 0.2934, IoU.signboard: 0.2362, IoU.chest of drawers: 0.2718, IoU.counter: 0.2848, IoU.sand: 0.2589, IoU.sink: 0.4537, IoU.skyscraper: 0.6558, IoU.fireplace: 0.5987, IoU.refrigerator: 0.4886, IoU.grandstand: 0.4069, IoU.path: 0.1560, IoU.stairs: 0.2079, IoU.runway: 0.7127, IoU.case: 0.3206, IoU.pool table: 0.8005, IoU.pillow: 0.3693, IoU.screen door: 0.4238, IoU.stairway: 0.2696, IoU.river: 0.0739, IoU.bridge: 0.4576, IoU.bookcase: 0.2909, IoU.blind: 0.2628, IoU.coffee table: 0.3928, IoU.toilet: 0.6612, IoU.flower: 0.2902, IoU.book: 0.3434, IoU.hill: 0.0446, IoU.bench: 0.2895, IoU.countertop: 0.4102, IoU.stove: 0.4337, IoU.palm: 0.3673, IoU.kitchen island: 0.1859, IoU.computer: 0.4401, IoU.swivel chair: 0.2657, IoU.boat: 0.4198, IoU.bar: 0.2370, IoU.arcade machine: 0.2605, IoU.hovel: 0.3056, IoU.bus: 0.7299, IoU.towel: 0.3501, IoU.light: 0.1623, IoU.truck: 0.0365, IoU.tower: 0.2677, IoU.chandelier: 0.4675, IoU.awning: 0.1576, IoU.streetlight: 0.0529, IoU.booth: 0.2650, IoU.television receiver: 0.3925, IoU.airplane: 0.4335, IoU.dirt track: 0.0571, IoU.apparel: 0.1773, IoU.pole: 0.0656, IoU.land: 0.0246, IoU.bannister: 0.0047, IoU.escalator: 0.3135, IoU.ottoman: 0.2528, IoU.bottle: 0.1573, IoU.buffet: 0.3318, IoU.poster: 0.1661, IoU.stage: 0.1143, IoU.van: 0.1780, IoU.ship: 0.0322, IoU.fountain: 0.1564, IoU.conveyer belt: 0.5556, IoU.canopy: 0.2007, IoU.washer: 0.5441, IoU.plaything: 0.0670, IoU.swimming pool: 0.2838, IoU.stool: 0.1360, IoU.barrel: 0.2681, IoU.basket: 0.1249, IoU.waterfall: 0.4504, IoU.tent: 0.7769, IoU.bag: 0.0234, IoU.minibike: 0.4633, IoU.cradle: 0.5571, IoU.oven: 0.1527, IoU.ball: 0.2299, IoU.food: 0.4151, IoU.step: 0.0144, IoU.tank: 0.2512, IoU.trade name: 0.1763, IoU.microwave: 0.2533, IoU.pot: 0.1774, IoU.animal: 0.4234, IoU.bicycle: 0.3655, IoU.lake: 0.0000, IoU.dishwasher: 0.2791, IoU.screen: 0.5577, IoU.blanket: 0.0217, IoU.sculpture: 0.3213, IoU.hood: 0.2934, IoU.sconce: 0.1198, IoU.vase: 0.1542, IoU.traffic light: 0.0964, IoU.tray: 0.0223, IoU.ashcan: 0.1946, IoU.fan: 0.3009, IoU.pier: 0.2962, IoU.crt screen: 0.0000, IoU.plate: 0.3268, IoU.monitor: 0.4760, IoU.bulletin board: 0.2674, IoU.shower: 0.0000, IoU.radiator: 0.3725, IoU.glass: 0.0001, IoU.clock: 0.0967, IoU.flag: 0.1410, Acc.wall: 0.8338, Acc.building: 0.8949, Acc.sky: 0.9261, Acc.floor: 0.8435, Acc.tree: 0.8410, Acc.ceiling: 0.8578, Acc.road: 0.8729, Acc.bed : 0.8988, Acc.windowpane: 0.6898, Acc.grass: 0.8415, Acc.cabinet: 0.6557, Acc.sidewalk: 0.6578, Acc.person: 0.8181, Acc.earth: 0.4157, Acc.door: 0.3711, Acc.table: 0.5508, Acc.mountain: 0.7125, Acc.plant: 0.5859, Acc.curtain: 0.7107, Acc.chair: 0.5188, Acc.car: 0.8458, Acc.water: 0.6458, Acc.painting: 0.7298, Acc.sofa: 0.7048, Acc.shelf: 0.4198, Acc.house: 0.6273, Acc.sea: 0.5458, Acc.mirror: 0.4981, Acc.rug: 0.5792, Acc.field: 0.4791, Acc.armchair: 0.3933, Acc.seat: 0.6894, Acc.fence: 0.4342, Acc.desk: 0.5551, Acc.rock: 0.5837, Acc.wardrobe: 0.5404, Acc.lamp: 0.4909, Acc.bathtub: 0.6354, Acc.railing: 0.3814, Acc.cushion: 0.4274, Acc.base: 0.1951, Acc.box: 0.2446, Acc.column: 0.3438, Acc.signboard: 0.3195, Acc.chest of drawers: 0.4144, Acc.counter: 0.3440, Acc.sand: 0.3910, Acc.sink: 0.5724, Acc.skyscraper: 0.8667, Acc.fireplace: 0.7189, Acc.refrigerator: 0.6475, Acc.grandstand: 0.6291, Acc.path: 0.2164, Acc.stairs: 0.2364, Acc.runway: 0.8571, Acc.case: 0.4245, Acc.pool table: 0.9097, Acc.pillow: 0.4645, Acc.screen door: 0.5689, Acc.stairway: 0.3135, Acc.river: 0.1054, Acc.bridge: 0.6564, Acc.bookcase: 0.4590, Acc.blind: 0.3254, Acc.coffee table: 0.6514, Acc.toilet: 0.7677, Acc.flower: 0.3995, Acc.book: 0.4646, Acc.hill: 0.0570, Acc.bench: 0.3705, Acc.countertop: 0.5052, Acc.stove: 0.4997, Acc.palm: 0.5088, Acc.kitchen island: 0.4784, Acc.computer: 0.5774, Acc.swivel chair: 0.3206, Acc.boat: 0.5265, Acc.bar: 0.2843, Acc.arcade machine: 0.3415, Acc.hovel: 0.3785, Acc.bus: 0.8540, Acc.towel: 0.4578, Acc.light: 0.1795, Acc.truck: 0.0460, Acc.tower: 0.3101, Acc.chandelier: 0.6239, Acc.awning: 0.1856, Acc.streetlight: 0.0611, Acc.booth: 0.3162, Acc.television receiver: 0.6324, Acc.airplane: 0.5091, Acc.dirt track: 0.1578, Acc.apparel: 0.2453, Acc.pole: 0.1006, Acc.land: 0.0329, Acc.bannister: 0.0063, Acc.escalator: 0.3296, Acc.ottoman: 0.2988, Acc.bottle: 0.3159, Acc.buffet: 0.4373, Acc.poster: 0.1980, Acc.stage: 0.1540, Acc.van: 0.2085, Acc.ship: 0.0387, Acc.fountain: 0.1600, Acc.conveyer belt: 0.6043, Acc.canopy: 0.2459, Acc.washer: 0.5772, Acc.plaything: 0.0994, Acc.swimming pool: 0.4549, Acc.stool: 0.1691, Acc.barrel: 0.6249, Acc.basket: 0.1746, Acc.waterfall: 0.5546, Acc.tent: 0.9632, Acc.bag: 0.0261, Acc.minibike: 0.5586, Acc.cradle: 0.7985, Acc.oven: 0.2724, Acc.ball: 0.2637, Acc.food: 0.5342, Acc.step: 0.0146, Acc.tank: 0.2985, Acc.trade name: 0.1925, Acc.microwave: 0.2861, Acc.pot: 0.2039, Acc.animal: 0.4951, Acc.bicycle: 0.5513, Acc.lake: 0.0000, Acc.dishwasher: 0.3680, Acc.screen: 0.7594, Acc.blanket: 0.0242, Acc.sculpture: 0.4605, Acc.hood: 0.3372, Acc.sconce: 0.1289, Acc.vase: 0.2092, Acc.traffic light: 0.1282, Acc.tray: 0.0490, Acc.ashcan: 0.2348, Acc.fan: 0.3945, Acc.pier: 0.3973, Acc.crt screen: 0.0000, Acc.plate: 0.4203, Acc.monitor: 0.5234, Acc.bulletin board: 0.3049, Acc.shower: 0.0000, Acc.radiator: 0.4305, Acc.glass: 0.0001, Acc.clock: 0.1036, Acc.flag: 0.1505
2022-11-04 14:51:51,553 - mmseg - INFO - Iter [48050/80000]	lr: 5.253e-05, eta: 3:01:49, time: 0.511, data_time: 0.186, memory: 12960, decode.loss_ce: 0.4512, decode.acc_seg: 82.3845, aux.loss_ce: 0.2537, aux.acc_seg: 77.0070, loss: 0.7050
2022-11-04 14:52:08,121 - mmseg - INFO - Iter [48100/80000]	lr: 5.246e-05, eta: 3:01:32, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4503, decode.acc_seg: 82.3334, aux.loss_ce: 0.2580, aux.acc_seg: 76.2963, loss: 0.7083
2022-11-04 14:52:24,798 - mmseg - INFO - Iter [48150/80000]	lr: 5.239e-05, eta: 3:01:14, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4848, decode.acc_seg: 81.4453, aux.loss_ce: 0.2694, aux.acc_seg: 75.9335, loss: 0.7542
2022-11-04 14:52:41,666 - mmseg - INFO - Iter [48200/80000]	lr: 5.231e-05, eta: 3:00:57, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4537, decode.acc_seg: 82.1743, aux.loss_ce: 0.2525, aux.acc_seg: 76.9452, loss: 0.7062
2022-11-04 14:52:58,218 - mmseg - INFO - Iter [48250/80000]	lr: 5.224e-05, eta: 3:00:40, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4415, decode.acc_seg: 82.9238, aux.loss_ce: 0.2516, aux.acc_seg: 77.3085, loss: 0.6931
2022-11-04 14:53:14,911 - mmseg - INFO - Iter [48300/80000]	lr: 5.216e-05, eta: 3:00:23, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4676, decode.acc_seg: 82.2140, aux.loss_ce: 0.2585, aux.acc_seg: 76.9988, loss: 0.7261
2022-11-04 14:53:31,288 - mmseg - INFO - Iter [48350/80000]	lr: 5.209e-05, eta: 3:00:05, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4737, decode.acc_seg: 81.6868, aux.loss_ce: 0.2646, aux.acc_seg: 76.0366, loss: 0.7384
2022-11-04 14:53:47,898 - mmseg - INFO - Iter [48400/80000]	lr: 5.202e-05, eta: 2:59:48, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4745, decode.acc_seg: 81.6697, aux.loss_ce: 0.2697, aux.acc_seg: 75.7701, loss: 0.7442
2022-11-04 14:54:04,489 - mmseg - INFO - Iter [48450/80000]	lr: 5.194e-05, eta: 2:59:30, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4507, decode.acc_seg: 82.2167, aux.loss_ce: 0.2505, aux.acc_seg: 77.0966, loss: 0.7013
2022-11-04 14:54:21,074 - mmseg - INFO - Iter [48500/80000]	lr: 5.187e-05, eta: 2:59:13, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4422, decode.acc_seg: 82.6420, aux.loss_ce: 0.2542, aux.acc_seg: 76.6008, loss: 0.6963
2022-11-04 14:54:37,796 - mmseg - INFO - Iter [48550/80000]	lr: 5.179e-05, eta: 2:58:56, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4755, decode.acc_seg: 81.4512, aux.loss_ce: 0.2661, aux.acc_seg: 75.7905, loss: 0.7415
2022-11-04 14:54:57,524 - mmseg - INFO - Iter [48600/80000]	lr: 5.172e-05, eta: 2:58:40, time: 0.395, data_time: 0.073, memory: 12960, decode.loss_ce: 0.4623, decode.acc_seg: 82.1333, aux.loss_ce: 0.2559, aux.acc_seg: 76.6432, loss: 0.7182
2022-11-04 14:55:14,367 - mmseg - INFO - Iter [48650/80000]	lr: 5.164e-05, eta: 2:58:23, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4642, decode.acc_seg: 81.7700, aux.loss_ce: 0.2595, aux.acc_seg: 76.1147, loss: 0.7238
2022-11-04 14:55:31,323 - mmseg - INFO - Iter [48700/80000]	lr: 5.157e-05, eta: 2:58:06, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4627, decode.acc_seg: 82.2770, aux.loss_ce: 0.2616, aux.acc_seg: 76.4789, loss: 0.7243
2022-11-04 14:55:47,997 - mmseg - INFO - Iter [48750/80000]	lr: 5.150e-05, eta: 2:57:49, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4710, decode.acc_seg: 81.8296, aux.loss_ce: 0.2641, aux.acc_seg: 76.0706, loss: 0.7351
2022-11-04 14:56:04,681 - mmseg - INFO - Iter [48800/80000]	lr: 5.142e-05, eta: 2:57:31, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4627, decode.acc_seg: 82.1939, aux.loss_ce: 0.2655, aux.acc_seg: 76.1793, loss: 0.7282
2022-11-04 14:56:21,539 - mmseg - INFO - Iter [48850/80000]	lr: 5.135e-05, eta: 2:57:14, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4572, decode.acc_seg: 82.1312, aux.loss_ce: 0.2550, aux.acc_seg: 76.4601, loss: 0.7123
2022-11-04 14:56:38,145 - mmseg - INFO - Iter [48900/80000]	lr: 5.127e-05, eta: 2:56:57, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4562, decode.acc_seg: 82.0972, aux.loss_ce: 0.2586, aux.acc_seg: 76.6029, loss: 0.7148
2022-11-04 14:56:54,769 - mmseg - INFO - Iter [48950/80000]	lr: 5.120e-05, eta: 2:56:39, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4575, decode.acc_seg: 82.0719, aux.loss_ce: 0.2562, aux.acc_seg: 76.4816, loss: 0.7138
2022-11-04 14:57:11,589 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 14:57:11,589 - mmseg - INFO - Iter [49000/80000]	lr: 5.113e-05, eta: 2:56:22, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4709, decode.acc_seg: 81.8030, aux.loss_ce: 0.2641, aux.acc_seg: 76.3834, loss: 0.7349
2022-11-04 14:57:28,172 - mmseg - INFO - Iter [49050/80000]	lr: 5.105e-05, eta: 2:56:05, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4547, decode.acc_seg: 82.1185, aux.loss_ce: 0.2574, aux.acc_seg: 76.5232, loss: 0.7121
2022-11-04 14:57:44,742 - mmseg - INFO - Iter [49100/80000]	lr: 5.098e-05, eta: 2:55:47, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4607, decode.acc_seg: 82.1503, aux.loss_ce: 0.2624, aux.acc_seg: 76.3182, loss: 0.7231
2022-11-04 14:58:01,361 - mmseg - INFO - Iter [49150/80000]	lr: 5.090e-05, eta: 2:55:30, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4740, decode.acc_seg: 81.6550, aux.loss_ce: 0.2684, aux.acc_seg: 75.6128, loss: 0.7424
2022-11-04 14:58:18,197 - mmseg - INFO - Iter [49200/80000]	lr: 5.083e-05, eta: 2:55:13, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4704, decode.acc_seg: 81.8831, aux.loss_ce: 0.2659, aux.acc_seg: 76.1988, loss: 0.7363
2022-11-04 14:58:38,131 - mmseg - INFO - Iter [49250/80000]	lr: 5.075e-05, eta: 2:54:57, time: 0.399, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4605, decode.acc_seg: 82.1563, aux.loss_ce: 0.2566, aux.acc_seg: 76.7349, loss: 0.7171
2022-11-04 14:58:54,777 - mmseg - INFO - Iter [49300/80000]	lr: 5.068e-05, eta: 2:54:40, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4690, decode.acc_seg: 82.0098, aux.loss_ce: 0.2695, aux.acc_seg: 75.6005, loss: 0.7385
2022-11-04 14:59:11,619 - mmseg - INFO - Iter [49350/80000]	lr: 5.061e-05, eta: 2:54:23, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4552, decode.acc_seg: 82.2384, aux.loss_ce: 0.2560, aux.acc_seg: 76.7451, loss: 0.7112
2022-11-04 14:59:28,368 - mmseg - INFO - Iter [49400/80000]	lr: 5.053e-05, eta: 2:54:06, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4733, decode.acc_seg: 81.5098, aux.loss_ce: 0.2622, aux.acc_seg: 76.1293, loss: 0.7355
2022-11-04 14:59:45,004 - mmseg - INFO - Iter [49450/80000]	lr: 5.046e-05, eta: 2:53:48, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4577, decode.acc_seg: 81.7844, aux.loss_ce: 0.2606, aux.acc_seg: 76.4442, loss: 0.7183
2022-11-04 15:00:01,652 - mmseg - INFO - Iter [49500/80000]	lr: 5.038e-05, eta: 2:53:31, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4514, decode.acc_seg: 82.2168, aux.loss_ce: 0.2616, aux.acc_seg: 76.0414, loss: 0.7131
2022-11-04 15:00:18,638 - mmseg - INFO - Iter [49550/80000]	lr: 5.031e-05, eta: 2:53:14, time: 0.340, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4470, decode.acc_seg: 82.7630, aux.loss_ce: 0.2501, aux.acc_seg: 77.2477, loss: 0.6971
2022-11-04 15:00:35,374 - mmseg - INFO - Iter [49600/80000]	lr: 5.023e-05, eta: 2:52:57, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4509, decode.acc_seg: 82.5243, aux.loss_ce: 0.2574, aux.acc_seg: 76.5911, loss: 0.7083
2022-11-04 15:00:52,010 - mmseg - INFO - Iter [49650/80000]	lr: 5.016e-05, eta: 2:52:39, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4639, decode.acc_seg: 82.0668, aux.loss_ce: 0.2633, aux.acc_seg: 76.5070, loss: 0.7272
2022-11-04 15:01:08,611 - mmseg - INFO - Iter [49700/80000]	lr: 5.009e-05, eta: 2:52:22, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4467, decode.acc_seg: 82.4719, aux.loss_ce: 0.2493, aux.acc_seg: 77.1649, loss: 0.6960
2022-11-04 15:01:25,373 - mmseg - INFO - Iter [49750/80000]	lr: 5.001e-05, eta: 2:52:05, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4613, decode.acc_seg: 81.9637, aux.loss_ce: 0.2600, aux.acc_seg: 76.3896, loss: 0.7212
2022-11-04 15:01:42,137 - mmseg - INFO - Iter [49800/80000]	lr: 4.994e-05, eta: 2:51:47, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4536, decode.acc_seg: 82.3141, aux.loss_ce: 0.2548, aux.acc_seg: 76.5753, loss: 0.7084
2022-11-04 15:02:01,926 - mmseg - INFO - Iter [49850/80000]	lr: 4.986e-05, eta: 2:51:32, time: 0.396, data_time: 0.073, memory: 12960, decode.loss_ce: 0.4599, decode.acc_seg: 82.2103, aux.loss_ce: 0.2537, aux.acc_seg: 76.9407, loss: 0.7136
2022-11-04 15:02:18,710 - mmseg - INFO - Iter [49900/80000]	lr: 4.979e-05, eta: 2:51:15, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4756, decode.acc_seg: 81.6318, aux.loss_ce: 0.2667, aux.acc_seg: 75.9974, loss: 0.7423
2022-11-04 15:02:35,351 - mmseg - INFO - Iter [49950/80000]	lr: 4.971e-05, eta: 2:50:57, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4454, decode.acc_seg: 82.6030, aux.loss_ce: 0.2520, aux.acc_seg: 77.1898, loss: 0.6974
2022-11-04 15:02:52,298 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:02:52,299 - mmseg - INFO - Iter [50000/80000]	lr: 4.964e-05, eta: 2:50:40, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4627, decode.acc_seg: 81.8076, aux.loss_ce: 0.2580, aux.acc_seg: 76.5600, loss: 0.7207
2022-11-04 15:03:09,169 - mmseg - INFO - Iter [50050/80000]	lr: 4.956e-05, eta: 2:50:23, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4576, decode.acc_seg: 82.0873, aux.loss_ce: 0.2590, aux.acc_seg: 76.3843, loss: 0.7166
2022-11-04 15:03:25,835 - mmseg - INFO - Iter [50100/80000]	lr: 4.949e-05, eta: 2:50:06, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4597, decode.acc_seg: 82.2833, aux.loss_ce: 0.2635, aux.acc_seg: 76.1200, loss: 0.7231
2022-11-04 15:03:42,612 - mmseg - INFO - Iter [50150/80000]	lr: 4.942e-05, eta: 2:49:49, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4570, decode.acc_seg: 82.1532, aux.loss_ce: 0.2530, aux.acc_seg: 77.0174, loss: 0.7100
2022-11-04 15:03:59,525 - mmseg - INFO - Iter [50200/80000]	lr: 4.934e-05, eta: 2:49:31, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4579, decode.acc_seg: 81.8342, aux.loss_ce: 0.2583, aux.acc_seg: 75.9324, loss: 0.7162
2022-11-04 15:04:16,284 - mmseg - INFO - Iter [50250/80000]	lr: 4.927e-05, eta: 2:49:14, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4627, decode.acc_seg: 82.1642, aux.loss_ce: 0.2625, aux.acc_seg: 76.5403, loss: 0.7252
2022-11-04 15:04:33,096 - mmseg - INFO - Iter [50300/80000]	lr: 4.919e-05, eta: 2:48:57, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4685, decode.acc_seg: 82.2021, aux.loss_ce: 0.2680, aux.acc_seg: 76.1009, loss: 0.7364
2022-11-04 15:04:49,826 - mmseg - INFO - Iter [50350/80000]	lr: 4.912e-05, eta: 2:48:40, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4674, decode.acc_seg: 82.1102, aux.loss_ce: 0.2591, aux.acc_seg: 76.6295, loss: 0.7265
2022-11-04 15:05:06,721 - mmseg - INFO - Iter [50400/80000]	lr: 4.904e-05, eta: 2:48:23, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4665, decode.acc_seg: 81.6918, aux.loss_ce: 0.2547, aux.acc_seg: 76.6456, loss: 0.7212
2022-11-04 15:05:23,493 - mmseg - INFO - Iter [50450/80000]	lr: 4.897e-05, eta: 2:48:05, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4719, decode.acc_seg: 81.7678, aux.loss_ce: 0.2624, aux.acc_seg: 76.6309, loss: 0.7343
2022-11-04 15:05:43,199 - mmseg - INFO - Iter [50500/80000]	lr: 4.889e-05, eta: 2:47:50, time: 0.394, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4595, decode.acc_seg: 82.2868, aux.loss_ce: 0.2574, aux.acc_seg: 76.6874, loss: 0.7169
2022-11-04 15:05:59,831 - mmseg - INFO - Iter [50550/80000]	lr: 4.882e-05, eta: 2:47:32, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4412, decode.acc_seg: 82.5560, aux.loss_ce: 0.2488, aux.acc_seg: 76.9868, loss: 0.6900
2022-11-04 15:06:16,663 - mmseg - INFO - Iter [50600/80000]	lr: 4.874e-05, eta: 2:47:15, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4398, decode.acc_seg: 83.0239, aux.loss_ce: 0.2410, aux.acc_seg: 78.1106, loss: 0.6808
2022-11-04 15:06:33,501 - mmseg - INFO - Iter [50650/80000]	lr: 4.867e-05, eta: 2:46:58, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4479, decode.acc_seg: 82.6036, aux.loss_ce: 0.2532, aux.acc_seg: 76.9876, loss: 0.7011
2022-11-04 15:06:50,300 - mmseg - INFO - Iter [50700/80000]	lr: 4.860e-05, eta: 2:46:41, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4608, decode.acc_seg: 81.9415, aux.loss_ce: 0.2585, aux.acc_seg: 76.6342, loss: 0.7193
2022-11-04 15:07:07,152 - mmseg - INFO - Iter [50750/80000]	lr: 4.852e-05, eta: 2:46:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4546, decode.acc_seg: 82.3919, aux.loss_ce: 0.2575, aux.acc_seg: 76.7575, loss: 0.7120
2022-11-04 15:07:23,771 - mmseg - INFO - Iter [50800/80000]	lr: 4.845e-05, eta: 2:46:06, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4659, decode.acc_seg: 81.7639, aux.loss_ce: 0.2641, aux.acc_seg: 76.2384, loss: 0.7300
2022-11-04 15:07:40,290 - mmseg - INFO - Iter [50850/80000]	lr: 4.837e-05, eta: 2:45:49, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4515, decode.acc_seg: 82.4022, aux.loss_ce: 0.2541, aux.acc_seg: 77.0309, loss: 0.7056
2022-11-04 15:07:56,807 - mmseg - INFO - Iter [50900/80000]	lr: 4.830e-05, eta: 2:45:32, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4524, decode.acc_seg: 82.4162, aux.loss_ce: 0.2585, aux.acc_seg: 76.7208, loss: 0.7109
2022-11-04 15:08:13,339 - mmseg - INFO - Iter [50950/80000]	lr: 4.822e-05, eta: 2:45:14, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4608, decode.acc_seg: 81.6318, aux.loss_ce: 0.2629, aux.acc_seg: 75.9924, loss: 0.7237
2022-11-04 15:08:29,896 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:08:29,897 - mmseg - INFO - Iter [51000/80000]	lr: 4.815e-05, eta: 2:44:57, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4722, decode.acc_seg: 81.8297, aux.loss_ce: 0.2639, aux.acc_seg: 76.2986, loss: 0.7361
2022-11-04 15:08:46,558 - mmseg - INFO - Iter [51050/80000]	lr: 4.807e-05, eta: 2:44:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4598, decode.acc_seg: 82.0908, aux.loss_ce: 0.2519, aux.acc_seg: 76.8123, loss: 0.7117
2022-11-04 15:09:03,363 - mmseg - INFO - Iter [51100/80000]	lr: 4.800e-05, eta: 2:44:22, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4623, decode.acc_seg: 82.1965, aux.loss_ce: 0.2575, aux.acc_seg: 76.9193, loss: 0.7198
2022-11-04 15:09:23,097 - mmseg - INFO - Iter [51150/80000]	lr: 4.792e-05, eta: 2:44:07, time: 0.395, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4657, decode.acc_seg: 82.0263, aux.loss_ce: 0.2595, aux.acc_seg: 76.6967, loss: 0.7252
2022-11-04 15:09:39,784 - mmseg - INFO - Iter [51200/80000]	lr: 4.785e-05, eta: 2:43:49, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4414, decode.acc_seg: 82.8918, aux.loss_ce: 0.2501, aux.acc_seg: 77.3431, loss: 0.6914
2022-11-04 15:09:56,625 - mmseg - INFO - Iter [51250/80000]	lr: 4.777e-05, eta: 2:43:32, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4576, decode.acc_seg: 82.0664, aux.loss_ce: 0.2606, aux.acc_seg: 76.5361, loss: 0.7182
2022-11-04 15:10:13,095 - mmseg - INFO - Iter [51300/80000]	lr: 4.770e-05, eta: 2:43:15, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4516, decode.acc_seg: 82.2231, aux.loss_ce: 0.2524, aux.acc_seg: 76.9695, loss: 0.7040
2022-11-04 15:10:29,817 - mmseg - INFO - Iter [51350/80000]	lr: 4.762e-05, eta: 2:42:58, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4275, decode.acc_seg: 83.2190, aux.loss_ce: 0.2458, aux.acc_seg: 77.3878, loss: 0.6733
2022-11-04 15:10:46,488 - mmseg - INFO - Iter [51400/80000]	lr: 4.755e-05, eta: 2:42:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4750, decode.acc_seg: 81.6100, aux.loss_ce: 0.2671, aux.acc_seg: 76.2284, loss: 0.7421
2022-11-04 15:11:02,938 - mmseg - INFO - Iter [51450/80000]	lr: 4.747e-05, eta: 2:42:23, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4493, decode.acc_seg: 82.6167, aux.loss_ce: 0.2499, aux.acc_seg: 77.0361, loss: 0.6991
2022-11-04 15:11:19,680 - mmseg - INFO - Iter [51500/80000]	lr: 4.740e-05, eta: 2:42:06, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4517, decode.acc_seg: 82.0526, aux.loss_ce: 0.2531, aux.acc_seg: 76.8249, loss: 0.7048
2022-11-04 15:11:36,393 - mmseg - INFO - Iter [51550/80000]	lr: 4.732e-05, eta: 2:41:48, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4627, decode.acc_seg: 81.8765, aux.loss_ce: 0.2580, aux.acc_seg: 76.6769, loss: 0.7206
2022-11-04 15:11:53,231 - mmseg - INFO - Iter [51600/80000]	lr: 4.725e-05, eta: 2:41:31, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4620, decode.acc_seg: 82.0498, aux.loss_ce: 0.2594, aux.acc_seg: 76.7487, loss: 0.7214
2022-11-04 15:12:09,816 - mmseg - INFO - Iter [51650/80000]	lr: 4.717e-05, eta: 2:41:14, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4530, decode.acc_seg: 82.4573, aux.loss_ce: 0.2576, aux.acc_seg: 76.6083, loss: 0.7106
2022-11-04 15:12:26,372 - mmseg - INFO - Iter [51700/80000]	lr: 4.710e-05, eta: 2:40:57, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4591, decode.acc_seg: 82.0965, aux.loss_ce: 0.2626, aux.acc_seg: 76.2482, loss: 0.7217
2022-11-04 15:12:45,802 - mmseg - INFO - Iter [51750/80000]	lr: 4.703e-05, eta: 2:40:41, time: 0.389, data_time: 0.061, memory: 12960, decode.loss_ce: 0.4686, decode.acc_seg: 81.8011, aux.loss_ce: 0.2660, aux.acc_seg: 76.0159, loss: 0.7346
2022-11-04 15:13:02,511 - mmseg - INFO - Iter [51800/80000]	lr: 4.695e-05, eta: 2:40:24, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4503, decode.acc_seg: 82.3723, aux.loss_ce: 0.2570, aux.acc_seg: 76.4555, loss: 0.7073
2022-11-04 15:13:19,179 - mmseg - INFO - Iter [51850/80000]	lr: 4.688e-05, eta: 2:40:06, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4532, decode.acc_seg: 82.3135, aux.loss_ce: 0.2535, aux.acc_seg: 77.0885, loss: 0.7067
2022-11-04 15:13:36,001 - mmseg - INFO - Iter [51900/80000]	lr: 4.680e-05, eta: 2:39:49, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4714, decode.acc_seg: 81.7121, aux.loss_ce: 0.2638, aux.acc_seg: 76.3000, loss: 0.7353
2022-11-04 15:13:52,623 - mmseg - INFO - Iter [51950/80000]	lr: 4.673e-05, eta: 2:39:32, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4554, decode.acc_seg: 82.3522, aux.loss_ce: 0.2590, aux.acc_seg: 76.5412, loss: 0.7144
2022-11-04 15:14:09,378 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:14:09,378 - mmseg - INFO - Iter [52000/80000]	lr: 4.665e-05, eta: 2:39:15, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4428, decode.acc_seg: 82.5114, aux.loss_ce: 0.2538, aux.acc_seg: 77.1063, loss: 0.6965
2022-11-04 15:14:26,707 - mmseg - INFO - Iter [52050/80000]	lr: 4.658e-05, eta: 2:38:58, time: 0.347, data_time: 0.020, memory: 12960, decode.loss_ce: 0.4643, decode.acc_seg: 82.1324, aux.loss_ce: 0.2630, aux.acc_seg: 76.4190, loss: 0.7273
2022-11-04 15:14:43,098 - mmseg - INFO - Iter [52100/80000]	lr: 4.650e-05, eta: 2:38:40, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4510, decode.acc_seg: 82.1431, aux.loss_ce: 0.2531, aux.acc_seg: 76.7678, loss: 0.7041
2022-11-04 15:14:59,750 - mmseg - INFO - Iter [52150/80000]	lr: 4.643e-05, eta: 2:38:23, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4649, decode.acc_seg: 82.0971, aux.loss_ce: 0.2605, aux.acc_seg: 76.5490, loss: 0.7254
2022-11-04 15:15:16,501 - mmseg - INFO - Iter [52200/80000]	lr: 4.635e-05, eta: 2:38:06, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4538, decode.acc_seg: 82.3618, aux.loss_ce: 0.2500, aux.acc_seg: 76.9181, loss: 0.7038
2022-11-04 15:15:33,046 - mmseg - INFO - Iter [52250/80000]	lr: 4.628e-05, eta: 2:37:48, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4462, decode.acc_seg: 82.5460, aux.loss_ce: 0.2524, aux.acc_seg: 77.0862, loss: 0.6986
2022-11-04 15:15:49,688 - mmseg - INFO - Iter [52300/80000]	lr: 4.620e-05, eta: 2:37:31, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4315, decode.acc_seg: 83.0731, aux.loss_ce: 0.2446, aux.acc_seg: 77.5600, loss: 0.6761
2022-11-04 15:16:06,504 - mmseg - INFO - Iter [52350/80000]	lr: 4.613e-05, eta: 2:37:14, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4377, decode.acc_seg: 83.0390, aux.loss_ce: 0.2511, aux.acc_seg: 77.1412, loss: 0.6887
2022-11-04 15:16:25,993 - mmseg - INFO - Iter [52400/80000]	lr: 4.605e-05, eta: 2:36:58, time: 0.390, data_time: 0.058, memory: 12960, decode.loss_ce: 0.4529, decode.acc_seg: 82.4227, aux.loss_ce: 0.2586, aux.acc_seg: 76.7288, loss: 0.7116
2022-11-04 15:16:42,687 - mmseg - INFO - Iter [52450/80000]	lr: 4.598e-05, eta: 2:36:41, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4382, decode.acc_seg: 82.6698, aux.loss_ce: 0.2510, aux.acc_seg: 76.8841, loss: 0.6892
2022-11-04 15:16:59,481 - mmseg - INFO - Iter [52500/80000]	lr: 4.590e-05, eta: 2:36:24, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4624, decode.acc_seg: 82.3715, aux.loss_ce: 0.2606, aux.acc_seg: 76.8248, loss: 0.7230
2022-11-04 15:17:16,110 - mmseg - INFO - Iter [52550/80000]	lr: 4.583e-05, eta: 2:36:06, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4456, decode.acc_seg: 82.4842, aux.loss_ce: 0.2541, aux.acc_seg: 76.6422, loss: 0.6997
2022-11-04 15:17:33,034 - mmseg - INFO - Iter [52600/80000]	lr: 4.575e-05, eta: 2:35:49, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4384, decode.acc_seg: 83.0937, aux.loss_ce: 0.2500, aux.acc_seg: 77.0648, loss: 0.6885
2022-11-04 15:17:49,824 - mmseg - INFO - Iter [52650/80000]	lr: 4.567e-05, eta: 2:35:32, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4420, decode.acc_seg: 82.6107, aux.loss_ce: 0.2512, aux.acc_seg: 77.0540, loss: 0.6932
2022-11-04 15:18:06,477 - mmseg - INFO - Iter [52700/80000]	lr: 4.560e-05, eta: 2:35:15, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4462, decode.acc_seg: 82.7796, aux.loss_ce: 0.2597, aux.acc_seg: 76.7920, loss: 0.7059
2022-11-04 15:18:23,096 - mmseg - INFO - Iter [52750/80000]	lr: 4.552e-05, eta: 2:34:57, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4635, decode.acc_seg: 81.4864, aux.loss_ce: 0.2620, aux.acc_seg: 75.9476, loss: 0.7256
2022-11-04 15:18:39,790 - mmseg - INFO - Iter [52800/80000]	lr: 4.545e-05, eta: 2:34:40, time: 0.334, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4444, decode.acc_seg: 82.6927, aux.loss_ce: 0.2518, aux.acc_seg: 77.3945, loss: 0.6961
2022-11-04 15:18:56,508 - mmseg - INFO - Iter [52850/80000]	lr: 4.537e-05, eta: 2:34:23, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4410, decode.acc_seg: 82.7603, aux.loss_ce: 0.2532, aux.acc_seg: 77.0099, loss: 0.6942
2022-11-04 15:19:13,175 - mmseg - INFO - Iter [52900/80000]	lr: 4.530e-05, eta: 2:34:06, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4415, decode.acc_seg: 82.9232, aux.loss_ce: 0.2502, aux.acc_seg: 77.3433, loss: 0.6917
2022-11-04 15:19:29,889 - mmseg - INFO - Iter [52950/80000]	lr: 4.522e-05, eta: 2:33:48, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4730, decode.acc_seg: 82.0904, aux.loss_ce: 0.2628, aux.acc_seg: 76.5322, loss: 0.7358
2022-11-04 15:19:46,747 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:19:46,747 - mmseg - INFO - Iter [53000/80000]	lr: 4.515e-05, eta: 2:33:31, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4480, decode.acc_seg: 82.4875, aux.loss_ce: 0.2514, aux.acc_seg: 76.8443, loss: 0.6995
2022-11-04 15:20:06,454 - mmseg - INFO - Iter [53050/80000]	lr: 4.507e-05, eta: 2:33:16, time: 0.394, data_time: 0.061, memory: 12960, decode.loss_ce: 0.4439, decode.acc_seg: 82.3945, aux.loss_ce: 0.2489, aux.acc_seg: 77.0133, loss: 0.6928
2022-11-04 15:20:23,200 - mmseg - INFO - Iter [53100/80000]	lr: 4.500e-05, eta: 2:32:58, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4596, decode.acc_seg: 82.1314, aux.loss_ce: 0.2619, aux.acc_seg: 76.4092, loss: 0.7215
2022-11-04 15:20:39,973 - mmseg - INFO - Iter [53150/80000]	lr: 4.492e-05, eta: 2:32:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4336, decode.acc_seg: 82.8614, aux.loss_ce: 0.2438, aux.acc_seg: 77.3767, loss: 0.6774
2022-11-04 15:20:56,675 - mmseg - INFO - Iter [53200/80000]	lr: 4.485e-05, eta: 2:32:24, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4462, decode.acc_seg: 82.1158, aux.loss_ce: 0.2591, aux.acc_seg: 76.3923, loss: 0.7053
2022-11-04 15:21:13,165 - mmseg - INFO - Iter [53250/80000]	lr: 4.477e-05, eta: 2:32:07, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4477, decode.acc_seg: 82.4534, aux.loss_ce: 0.2495, aux.acc_seg: 77.1131, loss: 0.6972
2022-11-04 15:21:29,744 - mmseg - INFO - Iter [53300/80000]	lr: 4.470e-05, eta: 2:31:49, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4520, decode.acc_seg: 82.5645, aux.loss_ce: 0.2551, aux.acc_seg: 77.1931, loss: 0.7071
2022-11-04 15:21:46,363 - mmseg - INFO - Iter [53350/80000]	lr: 4.462e-05, eta: 2:31:32, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4465, decode.acc_seg: 82.7859, aux.loss_ce: 0.2548, aux.acc_seg: 77.0721, loss: 0.7013
2022-11-04 15:22:03,110 - mmseg - INFO - Iter [53400/80000]	lr: 4.455e-05, eta: 2:31:15, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4555, decode.acc_seg: 82.1967, aux.loss_ce: 0.2585, aux.acc_seg: 76.4803, loss: 0.7140
2022-11-04 15:22:19,758 - mmseg - INFO - Iter [53450/80000]	lr: 4.447e-05, eta: 2:30:58, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4433, decode.acc_seg: 82.7656, aux.loss_ce: 0.2481, aux.acc_seg: 77.4635, loss: 0.6914
2022-11-04 15:22:36,510 - mmseg - INFO - Iter [53500/80000]	lr: 4.440e-05, eta: 2:30:40, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4659, decode.acc_seg: 82.0725, aux.loss_ce: 0.2590, aux.acc_seg: 76.6559, loss: 0.7249
2022-11-04 15:22:53,474 - mmseg - INFO - Iter [53550/80000]	lr: 4.432e-05, eta: 2:30:23, time: 0.339, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4585, decode.acc_seg: 82.2681, aux.loss_ce: 0.2586, aux.acc_seg: 76.4252, loss: 0.7171
2022-11-04 15:23:10,152 - mmseg - INFO - Iter [53600/80000]	lr: 4.424e-05, eta: 2:30:06, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4374, decode.acc_seg: 82.8068, aux.loss_ce: 0.2484, aux.acc_seg: 77.0522, loss: 0.6859
2022-11-04 15:23:29,534 - mmseg - INFO - Iter [53650/80000]	lr: 4.417e-05, eta: 2:29:50, time: 0.388, data_time: 0.065, memory: 12960, decode.loss_ce: 0.4528, decode.acc_seg: 82.6431, aux.loss_ce: 0.2529, aux.acc_seg: 77.1139, loss: 0.7058
2022-11-04 15:23:46,574 - mmseg - INFO - Iter [53700/80000]	lr: 4.409e-05, eta: 2:29:33, time: 0.341, data_time: 0.016, memory: 12960, decode.loss_ce: 0.4495, decode.acc_seg: 82.4438, aux.loss_ce: 0.2575, aux.acc_seg: 76.4612, loss: 0.7071
2022-11-04 15:24:03,283 - mmseg - INFO - Iter [53750/80000]	lr: 4.402e-05, eta: 2:29:16, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4401, decode.acc_seg: 82.6610, aux.loss_ce: 0.2460, aux.acc_seg: 77.3653, loss: 0.6860
2022-11-04 15:24:19,908 - mmseg - INFO - Iter [53800/80000]	lr: 4.394e-05, eta: 2:28:58, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4387, decode.acc_seg: 82.8661, aux.loss_ce: 0.2496, aux.acc_seg: 77.1569, loss: 0.6883
2022-11-04 15:24:36,390 - mmseg - INFO - Iter [53850/80000]	lr: 4.387e-05, eta: 2:28:41, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4389, decode.acc_seg: 83.2224, aux.loss_ce: 0.2560, aux.acc_seg: 77.0115, loss: 0.6950
2022-11-04 15:24:53,251 - mmseg - INFO - Iter [53900/80000]	lr: 4.379e-05, eta: 2:28:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4413, decode.acc_seg: 82.8238, aux.loss_ce: 0.2553, aux.acc_seg: 77.0386, loss: 0.6966
2022-11-04 15:25:09,876 - mmseg - INFO - Iter [53950/80000]	lr: 4.372e-05, eta: 2:28:07, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4355, decode.acc_seg: 82.9033, aux.loss_ce: 0.2463, aux.acc_seg: 77.3929, loss: 0.6818
2022-11-04 15:25:26,430 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:25:26,431 - mmseg - INFO - Iter [54000/80000]	lr: 4.364e-05, eta: 2:27:49, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4398, decode.acc_seg: 82.8223, aux.loss_ce: 0.2550, aux.acc_seg: 76.9710, loss: 0.6948
2022-11-04 15:25:43,013 - mmseg - INFO - Iter [54050/80000]	lr: 4.357e-05, eta: 2:27:32, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4326, decode.acc_seg: 83.0863, aux.loss_ce: 0.2486, aux.acc_seg: 76.9429, loss: 0.6812
2022-11-04 15:25:59,755 - mmseg - INFO - Iter [54100/80000]	lr: 4.349e-05, eta: 2:27:15, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4512, decode.acc_seg: 82.3653, aux.loss_ce: 0.2569, aux.acc_seg: 76.8368, loss: 0.7081
2022-11-04 15:26:16,465 - mmseg - INFO - Iter [54150/80000]	lr: 4.341e-05, eta: 2:26:58, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4538, decode.acc_seg: 82.1929, aux.loss_ce: 0.2523, aux.acc_seg: 76.9134, loss: 0.7061
2022-11-04 15:26:33,177 - mmseg - INFO - Iter [54200/80000]	lr: 4.334e-05, eta: 2:26:40, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4522, decode.acc_seg: 82.4695, aux.loss_ce: 0.2598, aux.acc_seg: 76.6977, loss: 0.7121
2022-11-04 15:26:49,804 - mmseg - INFO - Iter [54250/80000]	lr: 4.326e-05, eta: 2:26:23, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4700, decode.acc_seg: 81.7628, aux.loss_ce: 0.2636, aux.acc_seg: 76.1650, loss: 0.7336
2022-11-04 15:27:09,664 - mmseg - INFO - Iter [54300/80000]	lr: 4.319e-05, eta: 2:26:07, time: 0.397, data_time: 0.061, memory: 12960, decode.loss_ce: 0.4369, decode.acc_seg: 82.7442, aux.loss_ce: 0.2480, aux.acc_seg: 77.1018, loss: 0.6849
2022-11-04 15:27:26,246 - mmseg - INFO - Iter [54350/80000]	lr: 4.311e-05, eta: 2:25:50, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4526, decode.acc_seg: 82.1945, aux.loss_ce: 0.2558, aux.acc_seg: 76.2879, loss: 0.7084
2022-11-04 15:27:43,072 - mmseg - INFO - Iter [54400/80000]	lr: 4.304e-05, eta: 2:25:33, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4484, decode.acc_seg: 82.4159, aux.loss_ce: 0.2540, aux.acc_seg: 76.7185, loss: 0.7025
2022-11-04 15:27:59,746 - mmseg - INFO - Iter [54450/80000]	lr: 4.296e-05, eta: 2:25:16, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4417, decode.acc_seg: 82.7230, aux.loss_ce: 0.2444, aux.acc_seg: 77.8014, loss: 0.6861
2022-11-04 15:28:16,649 - mmseg - INFO - Iter [54500/80000]	lr: 4.288e-05, eta: 2:24:59, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4451, decode.acc_seg: 82.4911, aux.loss_ce: 0.2517, aux.acc_seg: 77.0901, loss: 0.6968
2022-11-04 15:28:33,209 - mmseg - INFO - Iter [54550/80000]	lr: 4.281e-05, eta: 2:24:41, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4552, decode.acc_seg: 81.9954, aux.loss_ce: 0.2555, aux.acc_seg: 76.3642, loss: 0.7107
2022-11-04 15:28:50,000 - mmseg - INFO - Iter [54600/80000]	lr: 4.273e-05, eta: 2:24:24, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4466, decode.acc_seg: 82.4985, aux.loss_ce: 0.2495, aux.acc_seg: 77.1080, loss: 0.6961
2022-11-04 15:29:06,651 - mmseg - INFO - Iter [54650/80000]	lr: 4.266e-05, eta: 2:24:07, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4354, decode.acc_seg: 83.0961, aux.loss_ce: 0.2448, aux.acc_seg: 77.5069, loss: 0.6802
2022-11-04 15:29:23,554 - mmseg - INFO - Iter [54700/80000]	lr: 4.258e-05, eta: 2:23:50, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4518, decode.acc_seg: 82.4504, aux.loss_ce: 0.2533, aux.acc_seg: 77.1171, loss: 0.7051
2022-11-04 15:29:40,504 - mmseg - INFO - Iter [54750/80000]	lr: 4.251e-05, eta: 2:23:33, time: 0.339, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4503, decode.acc_seg: 82.5599, aux.loss_ce: 0.2567, aux.acc_seg: 76.6797, loss: 0.7071
2022-11-04 15:29:57,094 - mmseg - INFO - Iter [54800/80000]	lr: 4.243e-05, eta: 2:23:15, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4574, decode.acc_seg: 82.2153, aux.loss_ce: 0.2587, aux.acc_seg: 76.5662, loss: 0.7161
2022-11-04 15:30:13,478 - mmseg - INFO - Iter [54850/80000]	lr: 4.235e-05, eta: 2:22:58, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4522, decode.acc_seg: 82.1380, aux.loss_ce: 0.2599, aux.acc_seg: 76.1228, loss: 0.7121
2022-11-04 15:30:33,449 - mmseg - INFO - Iter [54900/80000]	lr: 4.228e-05, eta: 2:22:42, time: 0.399, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4516, decode.acc_seg: 82.4409, aux.loss_ce: 0.2571, aux.acc_seg: 76.7106, loss: 0.7087
2022-11-04 15:30:50,188 - mmseg - INFO - Iter [54950/80000]	lr: 4.220e-05, eta: 2:22:25, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4492, decode.acc_seg: 82.3217, aux.loss_ce: 0.2552, aux.acc_seg: 76.6597, loss: 0.7045
2022-11-04 15:31:06,893 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:31:06,893 - mmseg - INFO - Iter [55000/80000]	lr: 4.213e-05, eta: 2:22:08, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4504, decode.acc_seg: 82.5584, aux.loss_ce: 0.2604, aux.acc_seg: 76.5083, loss: 0.7107
2022-11-04 15:31:23,763 - mmseg - INFO - Iter [55050/80000]	lr: 4.205e-05, eta: 2:21:51, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4393, decode.acc_seg: 82.9784, aux.loss_ce: 0.2511, aux.acc_seg: 77.2626, loss: 0.6905
2022-11-04 15:31:40,546 - mmseg - INFO - Iter [55100/80000]	lr: 4.198e-05, eta: 2:21:34, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4336, decode.acc_seg: 83.1575, aux.loss_ce: 0.2503, aux.acc_seg: 77.4460, loss: 0.6839
2022-11-04 15:31:57,368 - mmseg - INFO - Iter [55150/80000]	lr: 4.190e-05, eta: 2:21:16, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4447, decode.acc_seg: 82.6054, aux.loss_ce: 0.2511, aux.acc_seg: 77.3049, loss: 0.6958
2022-11-04 15:32:14,125 - mmseg - INFO - Iter [55200/80000]	lr: 4.182e-05, eta: 2:20:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4405, decode.acc_seg: 82.8883, aux.loss_ce: 0.2541, aux.acc_seg: 77.2712, loss: 0.6946
2022-11-04 15:32:31,392 - mmseg - INFO - Iter [55250/80000]	lr: 4.175e-05, eta: 2:20:42, time: 0.345, data_time: 0.022, memory: 12960, decode.loss_ce: 0.4510, decode.acc_seg: 82.4106, aux.loss_ce: 0.2554, aux.acc_seg: 77.1019, loss: 0.7064
2022-11-04 15:32:48,190 - mmseg - INFO - Iter [55300/80000]	lr: 4.167e-05, eta: 2:20:25, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4470, decode.acc_seg: 82.4792, aux.loss_ce: 0.2542, aux.acc_seg: 76.8627, loss: 0.7012
2022-11-04 15:33:04,957 - mmseg - INFO - Iter [55350/80000]	lr: 4.160e-05, eta: 2:20:08, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4366, decode.acc_seg: 82.8252, aux.loss_ce: 0.2474, aux.acc_seg: 77.3959, loss: 0.6841
2022-11-04 15:33:21,684 - mmseg - INFO - Iter [55400/80000]	lr: 4.152e-05, eta: 2:19:51, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4420, decode.acc_seg: 82.2425, aux.loss_ce: 0.2491, aux.acc_seg: 76.9612, loss: 0.6911
2022-11-04 15:33:38,353 - mmseg - INFO - Iter [55450/80000]	lr: 4.144e-05, eta: 2:19:34, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4470, decode.acc_seg: 82.5408, aux.loss_ce: 0.2533, aux.acc_seg: 77.1281, loss: 0.7003
2022-11-04 15:33:55,174 - mmseg - INFO - Iter [55500/80000]	lr: 4.137e-05, eta: 2:19:16, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4351, decode.acc_seg: 82.9595, aux.loss_ce: 0.2495, aux.acc_seg: 76.9442, loss: 0.6846
2022-11-04 15:34:14,800 - mmseg - INFO - Iter [55550/80000]	lr: 4.129e-05, eta: 2:19:00, time: 0.393, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4516, decode.acc_seg: 82.2354, aux.loss_ce: 0.2587, aux.acc_seg: 76.5459, loss: 0.7104
2022-11-04 15:34:31,567 - mmseg - INFO - Iter [55600/80000]	lr: 4.122e-05, eta: 2:18:43, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4524, decode.acc_seg: 82.1734, aux.loss_ce: 0.2581, aux.acc_seg: 76.5022, loss: 0.7105
2022-11-04 15:34:48,500 - mmseg - INFO - Iter [55650/80000]	lr: 4.114e-05, eta: 2:18:26, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4453, decode.acc_seg: 82.5228, aux.loss_ce: 0.2569, aux.acc_seg: 76.3363, loss: 0.7022
2022-11-04 15:35:05,248 - mmseg - INFO - Iter [55700/80000]	lr: 4.106e-05, eta: 2:18:09, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4491, decode.acc_seg: 82.5671, aux.loss_ce: 0.2525, aux.acc_seg: 77.6045, loss: 0.7016
2022-11-04 15:35:22,063 - mmseg - INFO - Iter [55750/80000]	lr: 4.099e-05, eta: 2:17:52, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4452, decode.acc_seg: 82.9011, aux.loss_ce: 0.2509, aux.acc_seg: 77.3471, loss: 0.6961
2022-11-04 15:35:39,004 - mmseg - INFO - Iter [55800/80000]	lr: 4.091e-05, eta: 2:17:35, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4514, decode.acc_seg: 82.5775, aux.loss_ce: 0.2554, aux.acc_seg: 77.1923, loss: 0.7067
2022-11-04 15:35:55,877 - mmseg - INFO - Iter [55850/80000]	lr: 4.084e-05, eta: 2:17:18, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4322, decode.acc_seg: 82.8982, aux.loss_ce: 0.2472, aux.acc_seg: 77.1085, loss: 0.6794
2022-11-04 15:36:12,684 - mmseg - INFO - Iter [55900/80000]	lr: 4.076e-05, eta: 2:17:00, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4360, decode.acc_seg: 82.8792, aux.loss_ce: 0.2516, aux.acc_seg: 77.1080, loss: 0.6877
2022-11-04 15:36:29,536 - mmseg - INFO - Iter [55950/80000]	lr: 4.068e-05, eta: 2:16:43, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4340, decode.acc_seg: 82.9246, aux.loss_ce: 0.2477, aux.acc_seg: 77.5463, loss: 0.6817
2022-11-04 15:36:46,413 - mmseg - INFO - Saving checkpoint at 56000 iterations
2022-11-04 15:36:46,758 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:36:46,759 - mmseg - INFO - Iter [56000/80000]	lr: 4.061e-05, eta: 2:16:26, time: 0.345, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4472, decode.acc_seg: 82.3794, aux.loss_ce: 0.2532, aux.acc_seg: 76.7220, loss: 0.7004
2022-11-04 15:36:55,649 - mmseg - INFO - per class results:
2022-11-04 15:36:55,655 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 66.36 | 82.29 |
|       building      | 75.57 | 88.96 |
|         sky         | 88.73 | 93.03 |
|        floor        | 70.91 | 84.58 |
|         tree        | 67.86 | 83.57 |
|       ceiling       |  76.3 | 86.84 |
|         road        | 75.17 | 86.74 |
|         bed         | 76.28 | 89.95 |
|      windowpane     | 50.13 | 67.57 |
|        grass        | 63.03 | 81.75 |
|       cabinet       | 47.42 | 61.99 |
|       sidewalk      | 50.41 | 64.81 |
|        person       | 63.71 | 83.39 |
|        earth        | 27.06 | 37.07 |
|         door        | 26.28 | 42.69 |
|        table        | 40.32 | 55.33 |
|       mountain      | 54.11 | 73.27 |
|        plant        | 44.31 | 54.55 |
|       curtain       | 54.91 | 72.72 |
|        chair        | 35.76 | 47.79 |
|         car         | 71.11 | 84.78 |
|        water        |  43.8 | 61.29 |
|       painting      |  55.3 | 72.08 |
|         sofa        | 46.44 | 65.01 |
|        shelf        | 32.55 |  50.4 |
|        house        | 43.24 | 67.21 |
|         sea         | 38.36 |  63.3 |
|        mirror       | 40.44 | 48.86 |
|         rug         | 45.54 | 56.88 |
|        field        | 34.64 | 53.35 |
|       armchair      | 28.79 | 48.15 |
|         seat        | 51.05 | 70.78 |
|        fence        | 27.34 | 44.94 |
|         desk        | 30.82 | 56.06 |
|         rock        | 36.92 | 60.66 |
|       wardrobe      | 33.93 |  53.2 |
|         lamp        | 37.53 | 51.57 |
|       bathtub       | 53.71 |  65.1 |
|       railing       |  24.2 |  33.7 |
|       cushion       | 31.54 | 41.61 |
|         base        | 18.72 | 23.37 |
|         box         |  17.9 | 26.94 |
|        column       | 30.32 | 40.52 |
|      signboard      | 23.36 | 33.49 |
|   chest of drawers  | 29.09 | 45.07 |
|       counter       |  25.1 |  28.2 |
|         sand        |  24.3 | 38.04 |
|         sink        | 44.91 | 61.77 |
|      skyscraper     | 63.99 | 87.06 |
|      fireplace      | 60.31 | 76.38 |
|     refrigerator    | 48.16 | 65.95 |
|      grandstand     | 40.12 |  65.1 |
|         path        |  18.4 | 26.95 |
|        stairs       | 24.13 | 29.26 |
|        runway       | 70.71 | 85.21 |
|         case        | 31.71 | 41.38 |
|      pool table     | 80.02 |  91.3 |
|        pillow       |  37.0 | 46.71 |
|     screen door     | 49.45 | 62.92 |
|       stairway      | 26.45 | 34.08 |
|        river        | 12.67 | 17.52 |
|        bridge       | 47.56 | 68.08 |
|       bookcase      | 27.79 | 45.56 |
|        blind        | 24.26 | 28.14 |
|     coffee table    | 38.41 | 71.43 |
|        toilet       | 65.37 | 80.97 |
|        flower       |  23.9 | 40.62 |
|         book        | 34.56 | 48.33 |
|         hill        |  3.52 |  5.06 |
|        bench        | 31.59 | 44.24 |
|      countertop     | 41.33 | 52.57 |
|        stove        | 47.94 | 57.57 |
|         palm        | 38.31 | 52.55 |
|    kitchen island   | 19.62 | 56.54 |
|       computer      | 42.98 | 55.63 |
|     swivel chair    | 31.22 | 40.06 |
|         boat        | 45.79 | 63.76 |
|         bar         | 23.77 | 31.76 |
|    arcade machine   | 34.38 | 36.86 |
|        hovel        | 30.76 | 38.38 |
|         bus         | 71.32 | 86.76 |
|        towel        | 37.67 | 51.87 |
|        light        | 15.01 | 16.44 |
|        truck        |  4.56 |  5.83 |
|        tower        |  33.3 | 39.64 |
|      chandelier     | 45.57 | 60.76 |
|        awning       | 15.78 | 17.51 |
|     streetlight     |  6.6  |  7.79 |
|        booth        | 29.05 | 31.73 |
| television receiver | 34.89 | 64.18 |
|       airplane      | 42.17 | 53.62 |
|      dirt track     | 11.89 | 15.76 |
|       apparel       | 20.67 | 29.99 |
|         pole        |  7.17 | 13.07 |
|         land        |  0.29 |  0.39 |
|      bannister      |  0.88 |  1.11 |
|      escalator      | 29.82 | 30.74 |
|       ottoman       | 25.91 | 30.89 |
|        bottle       | 18.02 |  42.3 |
|        buffet       |  36.2 | 46.93 |
|        poster       | 23.57 | 28.73 |
|        stage        | 11.39 |  14.6 |
|         van         | 12.94 | 14.69 |
|         ship        |  2.82 |  2.92 |
|       fountain      |  4.2  |  4.33 |
|    conveyer belt    | 52.37 | 60.08 |
|        canopy       |  25.7 | 33.43 |
|        washer       | 54.24 | 58.18 |
|      plaything      |  4.65 |  6.29 |
|    swimming pool    |  35.8 | 58.49 |
|        stool        | 12.79 | 15.23 |
|        barrel       | 31.62 | 62.12 |
|        basket       | 12.95 |  17.4 |
|      waterfall      | 37.92 | 42.83 |
|         tent        | 77.86 | 93.57 |
|         bag         |  4.18 |  4.94 |
|       minibike      | 43.77 | 54.31 |
|        cradle       | 58.03 | 78.67 |
|         oven        | 17.53 | 29.91 |
|         ball        | 15.02 | 16.55 |
|         food        | 42.24 | 52.28 |
|         step        |  2.35 |  2.46 |
|         tank        | 36.09 | 45.05 |
|      trade name     | 17.14 | 19.23 |
|      microwave      |  25.4 | 29.51 |
|         pot         | 17.58 | 20.54 |
|        animal       | 45.98 | 51.62 |
|       bicycle       | 35.31 | 55.97 |
|         lake        | 36.92 | 52.14 |
|      dishwasher     | 28.24 | 36.43 |
|        screen       | 57.33 | 72.78 |
|       blanket       |  1.09 |  1.24 |
|      sculpture      |  33.3 | 50.58 |
|         hood        | 34.78 | 42.29 |
|        sconce       | 14.43 | 15.71 |
|         vase        | 13.48 | 21.11 |
|    traffic light    |  9.16 | 11.97 |
|         tray        |  1.65 |  2.81 |
|        ashcan       | 19.94 | 25.58 |
|         fan         | 26.76 | 32.75 |
|         pier        | 32.67 | 44.92 |
|      crt screen     |  0.11 |  0.15 |
|        plate        | 30.25 | 36.76 |
|       monitor       | 50.73 | 64.52 |
|    bulletin board   | 28.61 | 42.73 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 33.98 | 38.92 |
|        glass        |  0.79 |  0.81 |
|        clock        |  8.66 |  9.3  |
|         flag        | 14.35 | 16.21 |
+---------------------+-------+-------+
2022-11-04 15:36:55,656 - mmseg - INFO - Summary:
2022-11-04 15:36:55,656 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 75.17 | 34.12 | 45.16 |
+-------+-------+-------+
2022-11-04 15:36:55,657 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:36:55,657 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7517, mIoU: 0.3412, mAcc: 0.4516, IoU.wall: 0.6636, IoU.building: 0.7557, IoU.sky: 0.8873, IoU.floor: 0.7091, IoU.tree: 0.6786, IoU.ceiling: 0.7630, IoU.road: 0.7517, IoU.bed : 0.7628, IoU.windowpane: 0.5013, IoU.grass: 0.6303, IoU.cabinet: 0.4742, IoU.sidewalk: 0.5041, IoU.person: 0.6371, IoU.earth: 0.2706, IoU.door: 0.2628, IoU.table: 0.4032, IoU.mountain: 0.5411, IoU.plant: 0.4431, IoU.curtain: 0.5491, IoU.chair: 0.3576, IoU.car: 0.7111, IoU.water: 0.4380, IoU.painting: 0.5530, IoU.sofa: 0.4644, IoU.shelf: 0.3255, IoU.house: 0.4324, IoU.sea: 0.3836, IoU.mirror: 0.4044, IoU.rug: 0.4554, IoU.field: 0.3464, IoU.armchair: 0.2879, IoU.seat: 0.5105, IoU.fence: 0.2734, IoU.desk: 0.3082, IoU.rock: 0.3692, IoU.wardrobe: 0.3393, IoU.lamp: 0.3753, IoU.bathtub: 0.5371, IoU.railing: 0.2420, IoU.cushion: 0.3154, IoU.base: 0.1872, IoU.box: 0.1790, IoU.column: 0.3032, IoU.signboard: 0.2336, IoU.chest of drawers: 0.2909, IoU.counter: 0.2510, IoU.sand: 0.2430, IoU.sink: 0.4491, IoU.skyscraper: 0.6399, IoU.fireplace: 0.6031, IoU.refrigerator: 0.4816, IoU.grandstand: 0.4012, IoU.path: 0.1840, IoU.stairs: 0.2413, IoU.runway: 0.7071, IoU.case: 0.3171, IoU.pool table: 0.8002, IoU.pillow: 0.3700, IoU.screen door: 0.4945, IoU.stairway: 0.2645, IoU.river: 0.1267, IoU.bridge: 0.4756, IoU.bookcase: 0.2779, IoU.blind: 0.2426, IoU.coffee table: 0.3841, IoU.toilet: 0.6537, IoU.flower: 0.2390, IoU.book: 0.3456, IoU.hill: 0.0352, IoU.bench: 0.3159, IoU.countertop: 0.4133, IoU.stove: 0.4794, IoU.palm: 0.3831, IoU.kitchen island: 0.1962, IoU.computer: 0.4298, IoU.swivel chair: 0.3122, IoU.boat: 0.4579, IoU.bar: 0.2377, IoU.arcade machine: 0.3438, IoU.hovel: 0.3076, IoU.bus: 0.7132, IoU.towel: 0.3767, IoU.light: 0.1501, IoU.truck: 0.0456, IoU.tower: 0.3330, IoU.chandelier: 0.4557, IoU.awning: 0.1578, IoU.streetlight: 0.0660, IoU.booth: 0.2905, IoU.television receiver: 0.3489, IoU.airplane: 0.4217, IoU.dirt track: 0.1189, IoU.apparel: 0.2067, IoU.pole: 0.0717, IoU.land: 0.0029, IoU.bannister: 0.0088, IoU.escalator: 0.2982, IoU.ottoman: 0.2591, IoU.bottle: 0.1802, IoU.buffet: 0.3620, IoU.poster: 0.2357, IoU.stage: 0.1139, IoU.van: 0.1294, IoU.ship: 0.0282, IoU.fountain: 0.0420, IoU.conveyer belt: 0.5237, IoU.canopy: 0.2570, IoU.washer: 0.5424, IoU.plaything: 0.0465, IoU.swimming pool: 0.3580, IoU.stool: 0.1279, IoU.barrel: 0.3162, IoU.basket: 0.1295, IoU.waterfall: 0.3792, IoU.tent: 0.7786, IoU.bag: 0.0418, IoU.minibike: 0.4377, IoU.cradle: 0.5803, IoU.oven: 0.1753, IoU.ball: 0.1502, IoU.food: 0.4224, IoU.step: 0.0235, IoU.tank: 0.3609, IoU.trade name: 0.1714, IoU.microwave: 0.2540, IoU.pot: 0.1758, IoU.animal: 0.4598, IoU.bicycle: 0.3531, IoU.lake: 0.3692, IoU.dishwasher: 0.2824, IoU.screen: 0.5733, IoU.blanket: 0.0109, IoU.sculpture: 0.3330, IoU.hood: 0.3478, IoU.sconce: 0.1443, IoU.vase: 0.1348, IoU.traffic light: 0.0916, IoU.tray: 0.0165, IoU.ashcan: 0.1994, IoU.fan: 0.2676, IoU.pier: 0.3267, IoU.crt screen: 0.0011, IoU.plate: 0.3025, IoU.monitor: 0.5073, IoU.bulletin board: 0.2861, IoU.shower: 0.0000, IoU.radiator: 0.3398, IoU.glass: 0.0079, IoU.clock: 0.0866, IoU.flag: 0.1435, Acc.wall: 0.8229, Acc.building: 0.8896, Acc.sky: 0.9303, Acc.floor: 0.8458, Acc.tree: 0.8357, Acc.ceiling: 0.8684, Acc.road: 0.8674, Acc.bed : 0.8995, Acc.windowpane: 0.6757, Acc.grass: 0.8175, Acc.cabinet: 0.6199, Acc.sidewalk: 0.6481, Acc.person: 0.8339, Acc.earth: 0.3707, Acc.door: 0.4269, Acc.table: 0.5533, Acc.mountain: 0.7327, Acc.plant: 0.5455, Acc.curtain: 0.7272, Acc.chair: 0.4779, Acc.car: 0.8478, Acc.water: 0.6129, Acc.painting: 0.7208, Acc.sofa: 0.6501, Acc.shelf: 0.5040, Acc.house: 0.6721, Acc.sea: 0.6330, Acc.mirror: 0.4886, Acc.rug: 0.5688, Acc.field: 0.5335, Acc.armchair: 0.4815, Acc.seat: 0.7078, Acc.fence: 0.4494, Acc.desk: 0.5606, Acc.rock: 0.6066, Acc.wardrobe: 0.5320, Acc.lamp: 0.5157, Acc.bathtub: 0.6510, Acc.railing: 0.3370, Acc.cushion: 0.4161, Acc.base: 0.2337, Acc.box: 0.2694, Acc.column: 0.4052, Acc.signboard: 0.3349, Acc.chest of drawers: 0.4507, Acc.counter: 0.2820, Acc.sand: 0.3804, Acc.sink: 0.6177, Acc.skyscraper: 0.8706, Acc.fireplace: 0.7638, Acc.refrigerator: 0.6595, Acc.grandstand: 0.6510, Acc.path: 0.2695, Acc.stairs: 0.2926, Acc.runway: 0.8521, Acc.case: 0.4138, Acc.pool table: 0.9130, Acc.pillow: 0.4671, Acc.screen door: 0.6292, Acc.stairway: 0.3408, Acc.river: 0.1752, Acc.bridge: 0.6808, Acc.bookcase: 0.4556, Acc.blind: 0.2814, Acc.coffee table: 0.7143, Acc.toilet: 0.8097, Acc.flower: 0.4062, Acc.book: 0.4833, Acc.hill: 0.0506, Acc.bench: 0.4424, Acc.countertop: 0.5257, Acc.stove: 0.5757, Acc.palm: 0.5255, Acc.kitchen island: 0.5654, Acc.computer: 0.5563, Acc.swivel chair: 0.4006, Acc.boat: 0.6376, Acc.bar: 0.3176, Acc.arcade machine: 0.3686, Acc.hovel: 0.3838, Acc.bus: 0.8676, Acc.towel: 0.5187, Acc.light: 0.1644, Acc.truck: 0.0583, Acc.tower: 0.3964, Acc.chandelier: 0.6076, Acc.awning: 0.1751, Acc.streetlight: 0.0779, Acc.booth: 0.3173, Acc.television receiver: 0.6418, Acc.airplane: 0.5362, Acc.dirt track: 0.1576, Acc.apparel: 0.2999, Acc.pole: 0.1307, Acc.land: 0.0039, Acc.bannister: 0.0111, Acc.escalator: 0.3074, Acc.ottoman: 0.3089, Acc.bottle: 0.4230, Acc.buffet: 0.4693, Acc.poster: 0.2873, Acc.stage: 0.1460, Acc.van: 0.1469, Acc.ship: 0.0292, Acc.fountain: 0.0433, Acc.conveyer belt: 0.6008, Acc.canopy: 0.3343, Acc.washer: 0.5818, Acc.plaything: 0.0629, Acc.swimming pool: 0.5849, Acc.stool: 0.1523, Acc.barrel: 0.6212, Acc.basket: 0.1740, Acc.waterfall: 0.4283, Acc.tent: 0.9357, Acc.bag: 0.0494, Acc.minibike: 0.5431, Acc.cradle: 0.7867, Acc.oven: 0.2991, Acc.ball: 0.1655, Acc.food: 0.5228, Acc.step: 0.0246, Acc.tank: 0.4505, Acc.trade name: 0.1923, Acc.microwave: 0.2951, Acc.pot: 0.2054, Acc.animal: 0.5162, Acc.bicycle: 0.5597, Acc.lake: 0.5214, Acc.dishwasher: 0.3643, Acc.screen: 0.7278, Acc.blanket: 0.0124, Acc.sculpture: 0.5058, Acc.hood: 0.4229, Acc.sconce: 0.1571, Acc.vase: 0.2111, Acc.traffic light: 0.1197, Acc.tray: 0.0281, Acc.ashcan: 0.2558, Acc.fan: 0.3275, Acc.pier: 0.4492, Acc.crt screen: 0.0015, Acc.plate: 0.3676, Acc.monitor: 0.6452, Acc.bulletin board: 0.4273, Acc.shower: 0.0000, Acc.radiator: 0.3892, Acc.glass: 0.0081, Acc.clock: 0.0930, Acc.flag: 0.1621
2022-11-04 15:37:12,159 - mmseg - INFO - Iter [56050/80000]	lr: 4.053e-05, eta: 2:16:13, time: 0.508, data_time: 0.187, memory: 12960, decode.loss_ce: 0.4416, decode.acc_seg: 82.9464, aux.loss_ce: 0.2520, aux.acc_seg: 77.4096, loss: 0.6936
2022-11-04 15:37:28,888 - mmseg - INFO - Iter [56100/80000]	lr: 4.046e-05, eta: 2:15:56, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4481, decode.acc_seg: 82.4848, aux.loss_ce: 0.2566, aux.acc_seg: 76.9075, loss: 0.7046
2022-11-04 15:37:45,507 - mmseg - INFO - Iter [56150/80000]	lr: 4.038e-05, eta: 2:15:38, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4568, decode.acc_seg: 82.1673, aux.loss_ce: 0.2558, aux.acc_seg: 76.8460, loss: 0.7126
2022-11-04 15:38:05,244 - mmseg - INFO - Iter [56200/80000]	lr: 4.030e-05, eta: 2:15:22, time: 0.395, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4425, decode.acc_seg: 82.9069, aux.loss_ce: 0.2545, aux.acc_seg: 77.0508, loss: 0.6970
2022-11-04 15:38:22,045 - mmseg - INFO - Iter [56250/80000]	lr: 4.023e-05, eta: 2:15:05, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4456, decode.acc_seg: 82.5994, aux.loss_ce: 0.2558, aux.acc_seg: 77.0225, loss: 0.7014
2022-11-04 15:38:38,882 - mmseg - INFO - Iter [56300/80000]	lr: 4.015e-05, eta: 2:14:48, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4405, decode.acc_seg: 82.6839, aux.loss_ce: 0.2476, aux.acc_seg: 77.5237, loss: 0.6881
2022-11-04 15:38:55,586 - mmseg - INFO - Iter [56350/80000]	lr: 4.007e-05, eta: 2:14:31, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4467, decode.acc_seg: 82.3444, aux.loss_ce: 0.2583, aux.acc_seg: 76.3503, loss: 0.7050
2022-11-04 15:39:12,068 - mmseg - INFO - Iter [56400/80000]	lr: 4.000e-05, eta: 2:14:14, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4342, decode.acc_seg: 82.6564, aux.loss_ce: 0.2467, aux.acc_seg: 77.1997, loss: 0.6809
2022-11-04 15:39:28,868 - mmseg - INFO - Iter [56450/80000]	lr: 3.992e-05, eta: 2:13:56, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4397, decode.acc_seg: 82.6945, aux.loss_ce: 0.2442, aux.acc_seg: 77.5133, loss: 0.6838
2022-11-04 15:39:45,706 - mmseg - INFO - Iter [56500/80000]	lr: 3.985e-05, eta: 2:13:39, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4472, decode.acc_seg: 82.5094, aux.loss_ce: 0.2554, aux.acc_seg: 77.0039, loss: 0.7025
2022-11-04 15:40:02,239 - mmseg - INFO - Iter [56550/80000]	lr: 3.977e-05, eta: 2:13:22, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4403, decode.acc_seg: 82.8640, aux.loss_ce: 0.2528, aux.acc_seg: 77.2632, loss: 0.6931
2022-11-04 15:40:18,903 - mmseg - INFO - Iter [56600/80000]	lr: 3.969e-05, eta: 2:13:05, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4471, decode.acc_seg: 82.1604, aux.loss_ce: 0.2520, aux.acc_seg: 76.7202, loss: 0.6991
2022-11-04 15:40:35,684 - mmseg - INFO - Iter [56650/80000]	lr: 3.962e-05, eta: 2:12:47, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4366, decode.acc_seg: 83.1083, aux.loss_ce: 0.2525, aux.acc_seg: 77.5129, loss: 0.6890
2022-11-04 15:40:52,459 - mmseg - INFO - Iter [56700/80000]	lr: 3.954e-05, eta: 2:12:30, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4399, decode.acc_seg: 82.9877, aux.loss_ce: 0.2455, aux.acc_seg: 77.8980, loss: 0.6854
2022-11-04 15:41:09,539 - mmseg - INFO - Iter [56750/80000]	lr: 3.946e-05, eta: 2:12:13, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4507, decode.acc_seg: 82.4927, aux.loss_ce: 0.2556, aux.acc_seg: 77.1213, loss: 0.7063
2022-11-04 15:41:28,929 - mmseg - INFO - Iter [56800/80000]	lr: 3.939e-05, eta: 2:11:57, time: 0.388, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4391, decode.acc_seg: 82.4786, aux.loss_ce: 0.2464, aux.acc_seg: 77.2007, loss: 0.6855
2022-11-04 15:41:45,705 - mmseg - INFO - Iter [56850/80000]	lr: 3.931e-05, eta: 2:11:40, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4551, decode.acc_seg: 82.1885, aux.loss_ce: 0.2566, aux.acc_seg: 76.7763, loss: 0.7117
2022-11-04 15:42:02,416 - mmseg - INFO - Iter [56900/80000]	lr: 3.923e-05, eta: 2:11:23, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4423, decode.acc_seg: 82.6507, aux.loss_ce: 0.2536, aux.acc_seg: 76.8691, loss: 0.6959
2022-11-04 15:42:18,963 - mmseg - INFO - Iter [56950/80000]	lr: 3.916e-05, eta: 2:11:05, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4457, decode.acc_seg: 82.7142, aux.loss_ce: 0.2532, aux.acc_seg: 76.9713, loss: 0.6988
2022-11-04 15:42:35,873 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:42:35,873 - mmseg - INFO - Iter [57000/80000]	lr: 3.908e-05, eta: 2:10:48, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4436, decode.acc_seg: 82.5648, aux.loss_ce: 0.2467, aux.acc_seg: 77.1778, loss: 0.6902
2022-11-04 15:42:52,572 - mmseg - INFO - Iter [57050/80000]	lr: 3.901e-05, eta: 2:10:31, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4447, decode.acc_seg: 82.6687, aux.loss_ce: 0.2517, aux.acc_seg: 77.1770, loss: 0.6964
2022-11-04 15:43:09,298 - mmseg - INFO - Iter [57100/80000]	lr: 3.893e-05, eta: 2:10:14, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4240, decode.acc_seg: 83.1812, aux.loss_ce: 0.2423, aux.acc_seg: 77.7416, loss: 0.6664
2022-11-04 15:43:26,239 - mmseg - INFO - Iter [57150/80000]	lr: 3.885e-05, eta: 2:09:57, time: 0.339, data_time: 0.018, memory: 12960, decode.loss_ce: 0.4558, decode.acc_seg: 81.7072, aux.loss_ce: 0.2624, aux.acc_seg: 76.0165, loss: 0.7182
2022-11-04 15:43:42,869 - mmseg - INFO - Iter [57200/80000]	lr: 3.878e-05, eta: 2:09:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4385, decode.acc_seg: 82.9278, aux.loss_ce: 0.2480, aux.acc_seg: 77.3616, loss: 0.6865
2022-11-04 15:43:59,727 - mmseg - INFO - Iter [57250/80000]	lr: 3.870e-05, eta: 2:09:22, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4622, decode.acc_seg: 81.9686, aux.loss_ce: 0.2622, aux.acc_seg: 76.1772, loss: 0.7244
2022-11-04 15:44:16,274 - mmseg - INFO - Iter [57300/80000]	lr: 3.862e-05, eta: 2:09:05, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4247, decode.acc_seg: 83.2022, aux.loss_ce: 0.2397, aux.acc_seg: 77.9103, loss: 0.6645
2022-11-04 15:44:32,864 - mmseg - INFO - Iter [57350/80000]	lr: 3.855e-05, eta: 2:08:48, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4405, decode.acc_seg: 82.7762, aux.loss_ce: 0.2529, aux.acc_seg: 76.9486, loss: 0.6933
2022-11-04 15:44:49,530 - mmseg - INFO - Iter [57400/80000]	lr: 3.847e-05, eta: 2:08:31, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4376, decode.acc_seg: 82.6095, aux.loss_ce: 0.2502, aux.acc_seg: 76.8974, loss: 0.6877
2022-11-04 15:45:09,171 - mmseg - INFO - Iter [57450/80000]	lr: 3.839e-05, eta: 2:08:15, time: 0.393, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4365, decode.acc_seg: 82.6924, aux.loss_ce: 0.2442, aux.acc_seg: 77.3182, loss: 0.6807
2022-11-04 15:45:25,737 - mmseg - INFO - Iter [57500/80000]	lr: 3.832e-05, eta: 2:07:57, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4364, decode.acc_seg: 82.9905, aux.loss_ce: 0.2472, aux.acc_seg: 77.9092, loss: 0.6836
2022-11-04 15:45:42,930 - mmseg - INFO - Iter [57550/80000]	lr: 3.824e-05, eta: 2:07:40, time: 0.344, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4336, decode.acc_seg: 82.8551, aux.loss_ce: 0.2512, aux.acc_seg: 77.2126, loss: 0.6847
2022-11-04 15:45:59,671 - mmseg - INFO - Iter [57600/80000]	lr: 3.816e-05, eta: 2:07:23, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4349, decode.acc_seg: 82.9511, aux.loss_ce: 0.2489, aux.acc_seg: 77.0866, loss: 0.6838
2022-11-04 15:46:16,469 - mmseg - INFO - Iter [57650/80000]	lr: 3.809e-05, eta: 2:07:06, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4440, decode.acc_seg: 82.6100, aux.loss_ce: 0.2513, aux.acc_seg: 77.1540, loss: 0.6953
2022-11-04 15:46:33,166 - mmseg - INFO - Iter [57700/80000]	lr: 3.801e-05, eta: 2:06:49, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4510, decode.acc_seg: 82.4512, aux.loss_ce: 0.2563, aux.acc_seg: 76.9008, loss: 0.7073
2022-11-04 15:46:49,817 - mmseg - INFO - Iter [57750/80000]	lr: 3.793e-05, eta: 2:06:32, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4382, decode.acc_seg: 82.7233, aux.loss_ce: 0.2486, aux.acc_seg: 77.3129, loss: 0.6868
2022-11-04 15:47:06,353 - mmseg - INFO - Iter [57800/80000]	lr: 3.786e-05, eta: 2:06:14, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4224, decode.acc_seg: 83.4097, aux.loss_ce: 0.2424, aux.acc_seg: 77.8440, loss: 0.6648
2022-11-04 15:47:22,952 - mmseg - INFO - Iter [57850/80000]	lr: 3.778e-05, eta: 2:05:57, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4461, decode.acc_seg: 82.6313, aux.loss_ce: 0.2512, aux.acc_seg: 77.3097, loss: 0.6973
2022-11-04 15:47:39,736 - mmseg - INFO - Iter [57900/80000]	lr: 3.770e-05, eta: 2:05:40, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4466, decode.acc_seg: 82.4311, aux.loss_ce: 0.2558, aux.acc_seg: 76.4477, loss: 0.7023
2022-11-04 15:47:56,453 - mmseg - INFO - Iter [57950/80000]	lr: 3.763e-05, eta: 2:05:23, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4470, decode.acc_seg: 82.4159, aux.loss_ce: 0.2555, aux.acc_seg: 76.8314, loss: 0.7025
2022-11-04 15:48:13,161 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:48:13,162 - mmseg - INFO - Iter [58000/80000]	lr: 3.755e-05, eta: 2:05:06, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4387, decode.acc_seg: 82.7677, aux.loss_ce: 0.2475, aux.acc_seg: 77.4167, loss: 0.6862
2022-11-04 15:48:29,786 - mmseg - INFO - Iter [58050/80000]	lr: 3.747e-05, eta: 2:04:48, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4263, decode.acc_seg: 83.3518, aux.loss_ce: 0.2493, aux.acc_seg: 77.1419, loss: 0.6756
2022-11-04 15:48:49,587 - mmseg - INFO - Iter [58100/80000]	lr: 3.740e-05, eta: 2:04:32, time: 0.396, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4311, decode.acc_seg: 83.1484, aux.loss_ce: 0.2486, aux.acc_seg: 77.5385, loss: 0.6797
2022-11-04 15:49:06,281 - mmseg - INFO - Iter [58150/80000]	lr: 3.732e-05, eta: 2:04:15, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4252, decode.acc_seg: 83.2587, aux.loss_ce: 0.2420, aux.acc_seg: 77.6855, loss: 0.6672
2022-11-04 15:49:22,762 - mmseg - INFO - Iter [58200/80000]	lr: 3.724e-05, eta: 2:03:58, time: 0.330, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4336, decode.acc_seg: 83.0001, aux.loss_ce: 0.2486, aux.acc_seg: 77.4643, loss: 0.6822
2022-11-04 15:49:39,490 - mmseg - INFO - Iter [58250/80000]	lr: 3.716e-05, eta: 2:03:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4379, decode.acc_seg: 82.9631, aux.loss_ce: 0.2506, aux.acc_seg: 77.7543, loss: 0.6885
2022-11-04 15:49:56,127 - mmseg - INFO - Iter [58300/80000]	lr: 3.709e-05, eta: 2:03:23, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4362, decode.acc_seg: 82.6417, aux.loss_ce: 0.2471, aux.acc_seg: 77.1396, loss: 0.6833
2022-11-04 15:50:12,767 - mmseg - INFO - Iter [58350/80000]	lr: 3.701e-05, eta: 2:03:06, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4474, decode.acc_seg: 82.7441, aux.loss_ce: 0.2542, aux.acc_seg: 77.0945, loss: 0.7016
2022-11-04 15:50:29,178 - mmseg - INFO - Iter [58400/80000]	lr: 3.693e-05, eta: 2:02:49, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4461, decode.acc_seg: 82.7560, aux.loss_ce: 0.2545, aux.acc_seg: 77.1369, loss: 0.7006
2022-11-04 15:50:45,683 - mmseg - INFO - Iter [58450/80000]	lr: 3.686e-05, eta: 2:02:32, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4391, decode.acc_seg: 82.7455, aux.loss_ce: 0.2483, aux.acc_seg: 77.6214, loss: 0.6874
2022-11-04 15:51:02,514 - mmseg - INFO - Iter [58500/80000]	lr: 3.678e-05, eta: 2:02:15, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4366, decode.acc_seg: 82.8626, aux.loss_ce: 0.2463, aux.acc_seg: 77.4449, loss: 0.6829
2022-11-04 15:51:19,016 - mmseg - INFO - Iter [58550/80000]	lr: 3.670e-05, eta: 2:01:57, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4389, decode.acc_seg: 82.4864, aux.loss_ce: 0.2536, aux.acc_seg: 76.6971, loss: 0.6925
2022-11-04 15:51:35,436 - mmseg - INFO - Iter [58600/80000]	lr: 3.663e-05, eta: 2:01:40, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4288, decode.acc_seg: 83.3476, aux.loss_ce: 0.2464, aux.acc_seg: 77.5274, loss: 0.6752
2022-11-04 15:51:51,950 - mmseg - INFO - Iter [58650/80000]	lr: 3.655e-05, eta: 2:01:23, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4256, decode.acc_seg: 83.0651, aux.loss_ce: 0.2434, aux.acc_seg: 77.4299, loss: 0.6690
2022-11-04 15:52:11,632 - mmseg - INFO - Iter [58700/80000]	lr: 3.647e-05, eta: 2:01:07, time: 0.394, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4442, decode.acc_seg: 82.9466, aux.loss_ce: 0.2557, aux.acc_seg: 77.0693, loss: 0.6998
2022-11-04 15:52:28,157 - mmseg - INFO - Iter [58750/80000]	lr: 3.639e-05, eta: 2:00:49, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4370, decode.acc_seg: 83.1280, aux.loss_ce: 0.2490, aux.acc_seg: 77.7701, loss: 0.6860
2022-11-04 15:52:45,091 - mmseg - INFO - Iter [58800/80000]	lr: 3.632e-05, eta: 2:00:32, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4251, decode.acc_seg: 83.1781, aux.loss_ce: 0.2452, aux.acc_seg: 77.5125, loss: 0.6702
2022-11-04 15:53:01,880 - mmseg - INFO - Iter [58850/80000]	lr: 3.624e-05, eta: 2:00:15, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4319, decode.acc_seg: 83.1589, aux.loss_ce: 0.2503, aux.acc_seg: 77.0321, loss: 0.6821
2022-11-04 15:53:18,314 - mmseg - INFO - Iter [58900/80000]	lr: 3.616e-05, eta: 1:59:58, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4447, decode.acc_seg: 82.6282, aux.loss_ce: 0.2456, aux.acc_seg: 77.6177, loss: 0.6903
2022-11-04 15:53:34,960 - mmseg - INFO - Iter [58950/80000]	lr: 3.609e-05, eta: 1:59:41, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4319, decode.acc_seg: 83.0863, aux.loss_ce: 0.2459, aux.acc_seg: 77.5302, loss: 0.6779
2022-11-04 15:53:51,494 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:53:51,494 - mmseg - INFO - Iter [59000/80000]	lr: 3.601e-05, eta: 1:59:23, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4224, decode.acc_seg: 83.2046, aux.loss_ce: 0.2395, aux.acc_seg: 77.7400, loss: 0.6619
2022-11-04 15:54:08,302 - mmseg - INFO - Iter [59050/80000]	lr: 3.593e-05, eta: 1:59:06, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4430, decode.acc_seg: 82.4526, aux.loss_ce: 0.2485, aux.acc_seg: 77.3864, loss: 0.6915
2022-11-04 15:54:25,110 - mmseg - INFO - Iter [59100/80000]	lr: 3.586e-05, eta: 1:58:49, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4334, decode.acc_seg: 82.7738, aux.loss_ce: 0.2458, aux.acc_seg: 77.3860, loss: 0.6793
2022-11-04 15:54:41,624 - mmseg - INFO - Iter [59150/80000]	lr: 3.578e-05, eta: 1:58:32, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4347, decode.acc_seg: 82.7671, aux.loss_ce: 0.2458, aux.acc_seg: 77.0935, loss: 0.6805
2022-11-04 15:54:58,269 - mmseg - INFO - Iter [59200/80000]	lr: 3.570e-05, eta: 1:58:15, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4350, decode.acc_seg: 82.9950, aux.loss_ce: 0.2469, aux.acc_seg: 77.4484, loss: 0.6819
2022-11-04 15:55:15,049 - mmseg - INFO - Iter [59250/80000]	lr: 3.562e-05, eta: 1:57:58, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4414, decode.acc_seg: 82.9747, aux.loss_ce: 0.2542, aux.acc_seg: 77.0448, loss: 0.6956
2022-11-04 15:55:31,651 - mmseg - INFO - Iter [59300/80000]	lr: 3.555e-05, eta: 1:57:40, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4381, decode.acc_seg: 83.0424, aux.loss_ce: 0.2474, aux.acc_seg: 77.5268, loss: 0.6855
2022-11-04 15:55:51,181 - mmseg - INFO - Iter [59350/80000]	lr: 3.547e-05, eta: 1:57:24, time: 0.391, data_time: 0.057, memory: 12960, decode.loss_ce: 0.4202, decode.acc_seg: 83.5935, aux.loss_ce: 0.2415, aux.acc_seg: 78.2020, loss: 0.6617
2022-11-04 15:56:07,795 - mmseg - INFO - Iter [59400/80000]	lr: 3.539e-05, eta: 1:57:07, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4255, decode.acc_seg: 83.3540, aux.loss_ce: 0.2490, aux.acc_seg: 77.4711, loss: 0.6746
2022-11-04 15:56:24,435 - mmseg - INFO - Iter [59450/80000]	lr: 3.531e-05, eta: 1:56:50, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4427, decode.acc_seg: 82.6175, aux.loss_ce: 0.2520, aux.acc_seg: 76.8976, loss: 0.6947
2022-11-04 15:56:41,171 - mmseg - INFO - Iter [59500/80000]	lr: 3.524e-05, eta: 1:56:33, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4355, decode.acc_seg: 82.9280, aux.loss_ce: 0.2477, aux.acc_seg: 77.3603, loss: 0.6832
2022-11-04 15:56:57,709 - mmseg - INFO - Iter [59550/80000]	lr: 3.516e-05, eta: 1:56:15, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4227, decode.acc_seg: 83.4644, aux.loss_ce: 0.2403, aux.acc_seg: 78.0875, loss: 0.6630
2022-11-04 15:57:14,238 - mmseg - INFO - Iter [59600/80000]	lr: 3.508e-05, eta: 1:55:58, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4441, decode.acc_seg: 82.7274, aux.loss_ce: 0.2548, aux.acc_seg: 77.0005, loss: 0.6989
2022-11-04 15:57:31,092 - mmseg - INFO - Iter [59650/80000]	lr: 3.500e-05, eta: 1:55:41, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4263, decode.acc_seg: 83.1355, aux.loss_ce: 0.2465, aux.acc_seg: 77.6288, loss: 0.6727
2022-11-04 15:57:47,924 - mmseg - INFO - Iter [59700/80000]	lr: 3.493e-05, eta: 1:55:24, time: 0.337, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4205, decode.acc_seg: 83.4782, aux.loss_ce: 0.2408, aux.acc_seg: 77.7532, loss: 0.6613
2022-11-04 15:58:04,627 - mmseg - INFO - Iter [59750/80000]	lr: 3.485e-05, eta: 1:55:07, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4435, decode.acc_seg: 82.7942, aux.loss_ce: 0.2513, aux.acc_seg: 77.3255, loss: 0.6948
2022-11-04 15:58:21,129 - mmseg - INFO - Iter [59800/80000]	lr: 3.477e-05, eta: 1:54:49, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4424, decode.acc_seg: 82.6918, aux.loss_ce: 0.2502, aux.acc_seg: 77.2548, loss: 0.6925
2022-11-04 15:58:37,699 - mmseg - INFO - Iter [59850/80000]	lr: 3.470e-05, eta: 1:54:32, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4269, decode.acc_seg: 83.3246, aux.loss_ce: 0.2427, aux.acc_seg: 78.0522, loss: 0.6696
2022-11-04 15:58:54,441 - mmseg - INFO - Iter [59900/80000]	lr: 3.462e-05, eta: 1:54:15, time: 0.335, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4482, decode.acc_seg: 82.4350, aux.loss_ce: 0.2504, aux.acc_seg: 77.2891, loss: 0.6986
2022-11-04 15:59:14,186 - mmseg - INFO - Iter [59950/80000]	lr: 3.454e-05, eta: 1:53:59, time: 0.395, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4508, decode.acc_seg: 82.5583, aux.loss_ce: 0.2520, aux.acc_seg: 77.2311, loss: 0.7028
2022-11-04 15:59:30,992 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 15:59:30,992 - mmseg - INFO - Iter [60000/80000]	lr: 3.446e-05, eta: 1:53:42, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4590, decode.acc_seg: 82.0316, aux.loss_ce: 0.2597, aux.acc_seg: 76.1307, loss: 0.7187
2022-11-04 15:59:47,503 - mmseg - INFO - Iter [60050/80000]	lr: 3.438e-05, eta: 1:53:24, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4515, decode.acc_seg: 82.4083, aux.loss_ce: 0.2600, aux.acc_seg: 76.7314, loss: 0.7115
2022-11-04 16:00:04,073 - mmseg - INFO - Iter [60100/80000]	lr: 3.431e-05, eta: 1:53:07, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4442, decode.acc_seg: 82.6588, aux.loss_ce: 0.2570, aux.acc_seg: 76.8319, loss: 0.7011
2022-11-04 16:00:20,863 - mmseg - INFO - Iter [60150/80000]	lr: 3.423e-05, eta: 1:52:50, time: 0.336, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4209, decode.acc_seg: 83.2135, aux.loss_ce: 0.2429, aux.acc_seg: 77.4383, loss: 0.6638
2022-11-04 16:00:37,521 - mmseg - INFO - Iter [60200/80000]	lr: 3.415e-05, eta: 1:52:33, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4320, decode.acc_seg: 83.0427, aux.loss_ce: 0.2480, aux.acc_seg: 77.4117, loss: 0.6800
2022-11-04 16:00:54,160 - mmseg - INFO - Iter [60250/80000]	lr: 3.407e-05, eta: 1:52:16, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4494, decode.acc_seg: 82.8527, aux.loss_ce: 0.2501, aux.acc_seg: 77.2603, loss: 0.6995
2022-11-04 16:01:10,882 - mmseg - INFO - Iter [60300/80000]	lr: 3.400e-05, eta: 1:51:59, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4322, decode.acc_seg: 83.0935, aux.loss_ce: 0.2510, aux.acc_seg: 77.3418, loss: 0.6832
2022-11-04 16:01:27,418 - mmseg - INFO - Iter [60350/80000]	lr: 3.392e-05, eta: 1:51:41, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4375, decode.acc_seg: 83.0832, aux.loss_ce: 0.2490, aux.acc_seg: 77.5871, loss: 0.6866
2022-11-04 16:01:44,099 - mmseg - INFO - Iter [60400/80000]	lr: 3.384e-05, eta: 1:51:24, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4385, decode.acc_seg: 83.1198, aux.loss_ce: 0.2502, aux.acc_seg: 77.4061, loss: 0.6887
2022-11-04 16:02:00,652 - mmseg - INFO - Iter [60450/80000]	lr: 3.376e-05, eta: 1:51:07, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4366, decode.acc_seg: 82.7561, aux.loss_ce: 0.2487, aux.acc_seg: 77.0972, loss: 0.6853
2022-11-04 16:02:17,261 - mmseg - INFO - Iter [60500/80000]	lr: 3.369e-05, eta: 1:50:50, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4147, decode.acc_seg: 83.3940, aux.loss_ce: 0.2415, aux.acc_seg: 77.6644, loss: 0.6562
2022-11-04 16:02:34,079 - mmseg - INFO - Iter [60550/80000]	lr: 3.361e-05, eta: 1:50:33, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4314, decode.acc_seg: 82.9636, aux.loss_ce: 0.2446, aux.acc_seg: 77.3306, loss: 0.6761
2022-11-04 16:02:53,702 - mmseg - INFO - Iter [60600/80000]	lr: 3.353e-05, eta: 1:50:16, time: 0.392, data_time: 0.073, memory: 12960, decode.loss_ce: 0.4381, decode.acc_seg: 83.0969, aux.loss_ce: 0.2514, aux.acc_seg: 77.2443, loss: 0.6895
2022-11-04 16:03:10,186 - mmseg - INFO - Iter [60650/80000]	lr: 3.345e-05, eta: 1:49:59, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4217, decode.acc_seg: 83.3389, aux.loss_ce: 0.2459, aux.acc_seg: 77.6432, loss: 0.6676
2022-11-04 16:03:27,194 - mmseg - INFO - Iter [60700/80000]	lr: 3.338e-05, eta: 1:49:42, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4288, decode.acc_seg: 83.0773, aux.loss_ce: 0.2445, aux.acc_seg: 77.4142, loss: 0.6733
2022-11-04 16:03:43,666 - mmseg - INFO - Iter [60750/80000]	lr: 3.330e-05, eta: 1:49:25, time: 0.329, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4197, decode.acc_seg: 83.6091, aux.loss_ce: 0.2409, aux.acc_seg: 77.8806, loss: 0.6606
2022-11-04 16:04:00,514 - mmseg - INFO - Iter [60800/80000]	lr: 3.322e-05, eta: 1:49:08, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4219, decode.acc_seg: 83.2390, aux.loss_ce: 0.2443, aux.acc_seg: 77.5147, loss: 0.6662
2022-11-04 16:04:17,125 - mmseg - INFO - Iter [60850/80000]	lr: 3.314e-05, eta: 1:48:51, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4447, decode.acc_seg: 82.5347, aux.loss_ce: 0.2525, aux.acc_seg: 77.1289, loss: 0.6972
2022-11-04 16:04:33,976 - mmseg - INFO - Iter [60900/80000]	lr: 3.306e-05, eta: 1:48:33, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4214, decode.acc_seg: 83.4753, aux.loss_ce: 0.2410, aux.acc_seg: 77.7476, loss: 0.6624
2022-11-04 16:04:50,413 - mmseg - INFO - Iter [60950/80000]	lr: 3.299e-05, eta: 1:48:16, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4332, decode.acc_seg: 82.9396, aux.loss_ce: 0.2463, aux.acc_seg: 77.5996, loss: 0.6795
2022-11-04 16:05:07,046 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:05:07,047 - mmseg - INFO - Iter [61000/80000]	lr: 3.291e-05, eta: 1:47:59, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4348, decode.acc_seg: 82.9174, aux.loss_ce: 0.2538, aux.acc_seg: 76.7044, loss: 0.6886
2022-11-04 16:05:23,803 - mmseg - INFO - Iter [61050/80000]	lr: 3.283e-05, eta: 1:47:42, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4353, decode.acc_seg: 83.2175, aux.loss_ce: 0.2520, aux.acc_seg: 77.3604, loss: 0.6873
2022-11-04 16:05:40,619 - mmseg - INFO - Iter [61100/80000]	lr: 3.275e-05, eta: 1:47:25, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4391, decode.acc_seg: 82.3819, aux.loss_ce: 0.2485, aux.acc_seg: 76.9182, loss: 0.6876
2022-11-04 16:05:57,636 - mmseg - INFO - Iter [61150/80000]	lr: 3.267e-05, eta: 1:47:08, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4300, decode.acc_seg: 82.8434, aux.loss_ce: 0.2442, aux.acc_seg: 77.2487, loss: 0.6742
2022-11-04 16:06:14,182 - mmseg - INFO - Iter [61200/80000]	lr: 3.260e-05, eta: 1:46:50, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4354, decode.acc_seg: 83.0878, aux.loss_ce: 0.2431, aux.acc_seg: 77.7701, loss: 0.6785
2022-11-04 16:06:33,672 - mmseg - INFO - Iter [61250/80000]	lr: 3.252e-05, eta: 1:46:34, time: 0.390, data_time: 0.065, memory: 12960, decode.loss_ce: 0.4342, decode.acc_seg: 83.2354, aux.loss_ce: 0.2496, aux.acc_seg: 77.5690, loss: 0.6838
2022-11-04 16:06:50,168 - mmseg - INFO - Iter [61300/80000]	lr: 3.244e-05, eta: 1:46:17, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4309, decode.acc_seg: 82.7999, aux.loss_ce: 0.2514, aux.acc_seg: 76.9906, loss: 0.6823
2022-11-04 16:07:06,710 - mmseg - INFO - Iter [61350/80000]	lr: 3.236e-05, eta: 1:46:00, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4344, decode.acc_seg: 82.8618, aux.loss_ce: 0.2481, aux.acc_seg: 77.3341, loss: 0.6825
2022-11-04 16:07:23,307 - mmseg - INFO - Iter [61400/80000]	lr: 3.228e-05, eta: 1:45:43, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4264, decode.acc_seg: 83.1901, aux.loss_ce: 0.2454, aux.acc_seg: 77.6094, loss: 0.6718
2022-11-04 16:07:40,058 - mmseg - INFO - Iter [61450/80000]	lr: 3.221e-05, eta: 1:45:25, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4384, decode.acc_seg: 83.1910, aux.loss_ce: 0.2477, aux.acc_seg: 77.7502, loss: 0.6861
2022-11-04 16:07:56,535 - mmseg - INFO - Iter [61500/80000]	lr: 3.213e-05, eta: 1:45:08, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4387, decode.acc_seg: 82.9578, aux.loss_ce: 0.2511, aux.acc_seg: 77.4901, loss: 0.6899
2022-11-04 16:08:13,315 - mmseg - INFO - Iter [61550/80000]	lr: 3.205e-05, eta: 1:44:51, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4198, decode.acc_seg: 83.5358, aux.loss_ce: 0.2426, aux.acc_seg: 77.9832, loss: 0.6623
2022-11-04 16:08:30,090 - mmseg - INFO - Iter [61600/80000]	lr: 3.197e-05, eta: 1:44:34, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4258, decode.acc_seg: 83.3056, aux.loss_ce: 0.2500, aux.acc_seg: 77.4466, loss: 0.6757
2022-11-04 16:08:47,102 - mmseg - INFO - Iter [61650/80000]	lr: 3.189e-05, eta: 1:44:17, time: 0.340, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4341, decode.acc_seg: 82.9871, aux.loss_ce: 0.2471, aux.acc_seg: 77.3942, loss: 0.6813
2022-11-04 16:09:03,841 - mmseg - INFO - Iter [61700/80000]	lr: 3.181e-05, eta: 1:44:00, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4365, decode.acc_seg: 82.6427, aux.loss_ce: 0.2427, aux.acc_seg: 77.4519, loss: 0.6791
2022-11-04 16:09:20,565 - mmseg - INFO - Iter [61750/80000]	lr: 3.174e-05, eta: 1:43:43, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4398, decode.acc_seg: 83.0172, aux.loss_ce: 0.2542, aux.acc_seg: 76.8649, loss: 0.6940
2022-11-04 16:09:37,277 - mmseg - INFO - Iter [61800/80000]	lr: 3.166e-05, eta: 1:43:25, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4257, decode.acc_seg: 83.0837, aux.loss_ce: 0.2442, aux.acc_seg: 77.5595, loss: 0.6698
2022-11-04 16:09:57,088 - mmseg - INFO - Iter [61850/80000]	lr: 3.158e-05, eta: 1:43:09, time: 0.396, data_time: 0.065, memory: 12960, decode.loss_ce: 0.4278, decode.acc_seg: 83.1673, aux.loss_ce: 0.2396, aux.acc_seg: 77.8153, loss: 0.6674
2022-11-04 16:10:13,945 - mmseg - INFO - Iter [61900/80000]	lr: 3.150e-05, eta: 1:42:52, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4116, decode.acc_seg: 83.7555, aux.loss_ce: 0.2359, aux.acc_seg: 78.4719, loss: 0.6475
2022-11-04 16:10:30,585 - mmseg - INFO - Iter [61950/80000]	lr: 3.142e-05, eta: 1:42:35, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4247, decode.acc_seg: 83.2216, aux.loss_ce: 0.2419, aux.acc_seg: 77.7929, loss: 0.6666
2022-11-04 16:10:47,295 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:10:47,295 - mmseg - INFO - Iter [62000/80000]	lr: 3.134e-05, eta: 1:42:18, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4305, decode.acc_seg: 82.9370, aux.loss_ce: 0.2374, aux.acc_seg: 77.9412, loss: 0.6679
2022-11-04 16:11:03,881 - mmseg - INFO - Iter [62050/80000]	lr: 3.127e-05, eta: 1:42:01, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4343, decode.acc_seg: 83.0630, aux.loss_ce: 0.2506, aux.acc_seg: 77.4677, loss: 0.6849
2022-11-04 16:11:20,610 - mmseg - INFO - Iter [62100/80000]	lr: 3.119e-05, eta: 1:41:43, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4331, decode.acc_seg: 82.9660, aux.loss_ce: 0.2495, aux.acc_seg: 77.2003, loss: 0.6827
2022-11-04 16:11:37,526 - mmseg - INFO - Iter [62150/80000]	lr: 3.111e-05, eta: 1:41:26, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4315, decode.acc_seg: 83.1504, aux.loss_ce: 0.2476, aux.acc_seg: 77.2417, loss: 0.6791
2022-11-04 16:11:54,078 - mmseg - INFO - Iter [62200/80000]	lr: 3.103e-05, eta: 1:41:09, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4256, decode.acc_seg: 83.3103, aux.loss_ce: 0.2426, aux.acc_seg: 77.6196, loss: 0.6682
2022-11-04 16:12:10,922 - mmseg - INFO - Iter [62250/80000]	lr: 3.095e-05, eta: 1:40:52, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4274, decode.acc_seg: 83.0155, aux.loss_ce: 0.2463, aux.acc_seg: 77.6249, loss: 0.6737
2022-11-04 16:12:28,016 - mmseg - INFO - Iter [62300/80000]	lr: 3.087e-05, eta: 1:40:35, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4335, decode.acc_seg: 83.1285, aux.loss_ce: 0.2487, aux.acc_seg: 77.4233, loss: 0.6822
2022-11-04 16:12:44,810 - mmseg - INFO - Iter [62350/80000]	lr: 3.080e-05, eta: 1:40:18, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4358, decode.acc_seg: 82.8978, aux.loss_ce: 0.2523, aux.acc_seg: 76.9672, loss: 0.6882
2022-11-04 16:13:01,589 - mmseg - INFO - Iter [62400/80000]	lr: 3.072e-05, eta: 1:40:01, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4323, decode.acc_seg: 83.0955, aux.loss_ce: 0.2516, aux.acc_seg: 77.2882, loss: 0.6839
2022-11-04 16:13:18,490 - mmseg - INFO - Iter [62450/80000]	lr: 3.064e-05, eta: 1:39:44, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4183, decode.acc_seg: 83.4844, aux.loss_ce: 0.2369, aux.acc_seg: 78.2625, loss: 0.6552
2022-11-04 16:13:38,090 - mmseg - INFO - Iter [62500/80000]	lr: 3.056e-05, eta: 1:39:27, time: 0.392, data_time: 0.058, memory: 12960, decode.loss_ce: 0.4309, decode.acc_seg: 82.9687, aux.loss_ce: 0.2483, aux.acc_seg: 77.2824, loss: 0.6792
2022-11-04 16:13:54,864 - mmseg - INFO - Iter [62550/80000]	lr: 3.048e-05, eta: 1:39:10, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4300, decode.acc_seg: 83.2036, aux.loss_ce: 0.2499, aux.acc_seg: 77.1455, loss: 0.6799
2022-11-04 16:14:11,629 - mmseg - INFO - Iter [62600/80000]	lr: 3.040e-05, eta: 1:38:53, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4291, decode.acc_seg: 83.0861, aux.loss_ce: 0.2466, aux.acc_seg: 77.3104, loss: 0.6757
2022-11-04 16:14:28,366 - mmseg - INFO - Iter [62650/80000]	lr: 3.032e-05, eta: 1:38:36, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4348, decode.acc_seg: 82.8802, aux.loss_ce: 0.2479, aux.acc_seg: 77.2786, loss: 0.6827
2022-11-04 16:14:45,218 - mmseg - INFO - Iter [62700/80000]	lr: 3.025e-05, eta: 1:38:19, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4301, decode.acc_seg: 82.9070, aux.loss_ce: 0.2475, aux.acc_seg: 77.2232, loss: 0.6775
2022-11-04 16:15:01,845 - mmseg - INFO - Iter [62750/80000]	lr: 3.017e-05, eta: 1:38:02, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4237, decode.acc_seg: 83.2543, aux.loss_ce: 0.2395, aux.acc_seg: 78.0688, loss: 0.6632
2022-11-04 16:15:18,576 - mmseg - INFO - Iter [62800/80000]	lr: 3.009e-05, eta: 1:37:45, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4178, decode.acc_seg: 83.5057, aux.loss_ce: 0.2402, aux.acc_seg: 77.9835, loss: 0.6580
2022-11-04 16:15:35,425 - mmseg - INFO - Iter [62850/80000]	lr: 3.001e-05, eta: 1:37:27, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4207, decode.acc_seg: 83.5083, aux.loss_ce: 0.2492, aux.acc_seg: 77.2897, loss: 0.6699
2022-11-04 16:15:52,318 - mmseg - INFO - Iter [62900/80000]	lr: 2.993e-05, eta: 1:37:10, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4338, decode.acc_seg: 83.2123, aux.loss_ce: 0.2433, aux.acc_seg: 78.1821, loss: 0.6771
2022-11-04 16:16:09,044 - mmseg - INFO - Iter [62950/80000]	lr: 2.985e-05, eta: 1:36:53, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4328, decode.acc_seg: 83.1756, aux.loss_ce: 0.2500, aux.acc_seg: 77.3206, loss: 0.6828
2022-11-04 16:16:26,124 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:16:26,125 - mmseg - INFO - Iter [63000/80000]	lr: 2.977e-05, eta: 1:36:36, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4341, decode.acc_seg: 82.9844, aux.loss_ce: 0.2443, aux.acc_seg: 77.7136, loss: 0.6784
2022-11-04 16:16:42,736 - mmseg - INFO - Iter [63050/80000]	lr: 2.969e-05, eta: 1:36:19, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4349, decode.acc_seg: 82.7055, aux.loss_ce: 0.2465, aux.acc_seg: 77.5112, loss: 0.6814
2022-11-04 16:16:58,933 - mmseg - INFO - Iter [63100/80000]	lr: 2.962e-05, eta: 1:36:02, time: 0.324, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4341, decode.acc_seg: 82.9174, aux.loss_ce: 0.2496, aux.acc_seg: 77.0146, loss: 0.6836
2022-11-04 16:17:18,808 - mmseg - INFO - Iter [63150/80000]	lr: 2.954e-05, eta: 1:35:45, time: 0.398, data_time: 0.068, memory: 12960, decode.loss_ce: 0.4312, decode.acc_seg: 82.9772, aux.loss_ce: 0.2484, aux.acc_seg: 77.2133, loss: 0.6796
2022-11-04 16:17:35,582 - mmseg - INFO - Iter [63200/80000]	lr: 2.946e-05, eta: 1:35:28, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4248, decode.acc_seg: 83.5801, aux.loss_ce: 0.2430, aux.acc_seg: 78.0733, loss: 0.6678
2022-11-04 16:17:52,380 - mmseg - INFO - Iter [63250/80000]	lr: 2.938e-05, eta: 1:35:11, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4281, decode.acc_seg: 83.1843, aux.loss_ce: 0.2505, aux.acc_seg: 77.2218, loss: 0.6786
2022-11-04 16:18:09,013 - mmseg - INFO - Iter [63300/80000]	lr: 2.930e-05, eta: 1:34:54, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4289, decode.acc_seg: 83.2665, aux.loss_ce: 0.2408, aux.acc_seg: 78.2157, loss: 0.6697
2022-11-04 16:18:25,794 - mmseg - INFO - Iter [63350/80000]	lr: 2.922e-05, eta: 1:34:37, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4146, decode.acc_seg: 84.0171, aux.loss_ce: 0.2392, aux.acc_seg: 78.5175, loss: 0.6537
2022-11-04 16:18:42,617 - mmseg - INFO - Iter [63400/80000]	lr: 2.914e-05, eta: 1:34:20, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4434, decode.acc_seg: 82.6138, aux.loss_ce: 0.2550, aux.acc_seg: 76.7639, loss: 0.6984
2022-11-04 16:18:59,528 - mmseg - INFO - Iter [63450/80000]	lr: 2.906e-05, eta: 1:34:03, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4176, decode.acc_seg: 83.4588, aux.loss_ce: 0.2417, aux.acc_seg: 77.6560, loss: 0.6593
2022-11-04 16:19:16,031 - mmseg - INFO - Iter [63500/80000]	lr: 2.898e-05, eta: 1:33:46, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4347, decode.acc_seg: 82.6925, aux.loss_ce: 0.2496, aux.acc_seg: 76.9459, loss: 0.6843
2022-11-04 16:19:32,692 - mmseg - INFO - Iter [63550/80000]	lr: 2.891e-05, eta: 1:33:28, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4344, decode.acc_seg: 83.0015, aux.loss_ce: 0.2494, aux.acc_seg: 77.5847, loss: 0.6838
2022-11-04 16:19:49,615 - mmseg - INFO - Iter [63600/80000]	lr: 2.883e-05, eta: 1:33:11, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4493, decode.acc_seg: 82.3829, aux.loss_ce: 0.2494, aux.acc_seg: 77.3357, loss: 0.6987
2022-11-04 16:20:06,434 - mmseg - INFO - Iter [63650/80000]	lr: 2.875e-05, eta: 1:32:54, time: 0.336, data_time: 0.014, memory: 12960, decode.loss_ce: 0.4279, decode.acc_seg: 83.2353, aux.loss_ce: 0.2471, aux.acc_seg: 77.2850, loss: 0.6751
2022-11-04 16:20:23,243 - mmseg - INFO - Iter [63700/80000]	lr: 2.867e-05, eta: 1:32:37, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4240, decode.acc_seg: 83.3946, aux.loss_ce: 0.2433, aux.acc_seg: 77.7929, loss: 0.6673
2022-11-04 16:20:42,984 - mmseg - INFO - Iter [63750/80000]	lr: 2.859e-05, eta: 1:32:21, time: 0.395, data_time: 0.057, memory: 12960, decode.loss_ce: 0.4211, decode.acc_seg: 83.2512, aux.loss_ce: 0.2420, aux.acc_seg: 77.9926, loss: 0.6631
2022-11-04 16:20:59,339 - mmseg - INFO - Iter [63800/80000]	lr: 2.851e-05, eta: 1:32:03, time: 0.327, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4256, decode.acc_seg: 83.1952, aux.loss_ce: 0.2468, aux.acc_seg: 77.3654, loss: 0.6724
2022-11-04 16:21:16,040 - mmseg - INFO - Iter [63850/80000]	lr: 2.843e-05, eta: 1:31:46, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4166, decode.acc_seg: 83.5628, aux.loss_ce: 0.2438, aux.acc_seg: 77.3512, loss: 0.6603
2022-11-04 16:21:33,168 - mmseg - INFO - Iter [63900/80000]	lr: 2.835e-05, eta: 1:31:29, time: 0.343, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4147, decode.acc_seg: 83.6821, aux.loss_ce: 0.2405, aux.acc_seg: 77.9864, loss: 0.6552
2022-11-04 16:21:49,858 - mmseg - INFO - Iter [63950/80000]	lr: 2.827e-05, eta: 1:31:12, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4349, decode.acc_seg: 82.9464, aux.loss_ce: 0.2537, aux.acc_seg: 76.8123, loss: 0.6885
2022-11-04 16:22:07,031 - mmseg - INFO - Saving checkpoint at 64000 iterations
2022-11-04 16:22:07,261 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:22:07,262 - mmseg - INFO - Iter [64000/80000]	lr: 2.819e-05, eta: 1:30:55, time: 0.348, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4469, decode.acc_seg: 82.8169, aux.loss_ce: 0.2587, aux.acc_seg: 77.0996, loss: 0.7056
2022-11-04 16:22:16,112 - mmseg - INFO - per class results:
2022-11-04 16:22:16,119 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 66.74 | 82.07 |
|       building      | 75.63 | 89.51 |
|         sky         |  88.9 | 93.11 |
|        floor        | 70.71 | 85.05 |
|         tree        | 67.95 | 83.99 |
|       ceiling       |  75.8 | 84.59 |
|         road        | 75.19 | 83.71 |
|         bed         | 75.94 | 90.73 |
|      windowpane     | 49.59 | 69.03 |
|        grass        |  64.0 | 83.86 |
|       cabinet       | 48.26 | 64.79 |
|       sidewalk      | 53.13 | 73.08 |
|        person       | 63.98 | 83.18 |
|        earth        | 27.11 |  38.3 |
|         door        | 24.78 | 39.18 |
|        table        | 39.49 | 55.13 |
|       mountain      | 53.21 | 71.36 |
|        plant        | 45.75 | 59.84 |
|       curtain       | 55.13 | 72.45 |
|        chair        | 36.78 | 50.44 |
|         car         | 70.76 | 85.57 |
|        water        | 43.46 | 61.01 |
|       painting      | 55.27 |  73.1 |
|         sofa        | 47.52 | 69.01 |
|        shelf        | 32.57 | 47.88 |
|        house        | 43.82 | 67.11 |
|         sea         |  34.3 | 56.48 |
|        mirror       | 40.13 | 48.58 |
|         rug         | 47.07 | 58.81 |
|        field        | 35.74 | 45.69 |
|       armchair      | 25.93 | 37.81 |
|         seat        | 50.41 | 71.61 |
|        fence        |  25.8 | 45.33 |
|         desk        | 31.37 | 50.67 |
|         rock        | 38.36 | 63.88 |
|       wardrobe      | 34.41 | 50.97 |
|         lamp        | 38.14 |  52.4 |
|       bathtub       | 52.89 | 65.31 |
|       railing       | 25.22 | 36.52 |
|       cushion       | 33.01 | 44.23 |
|         base        | 20.39 | 25.21 |
|         box         | 15.45 | 21.97 |
|        column       | 34.17 | 43.08 |
|      signboard      | 23.77 | 33.31 |
|   chest of drawers  | 27.75 |  42.3 |
|       counter       | 27.04 | 29.73 |
|         sand        | 28.49 | 45.24 |
|         sink        | 45.46 | 61.83 |
|      skyscraper     | 64.93 | 86.05 |
|      fireplace      | 59.24 | 76.58 |
|     refrigerator    | 51.12 |  62.9 |
|      grandstand     | 40.01 | 67.31 |
|         path        | 21.23 | 31.94 |
|        stairs       | 24.76 | 31.43 |
|        runway       | 70.74 | 85.03 |
|         case        | 34.74 | 52.61 |
|      pool table     | 79.94 | 90.36 |
|        pillow       | 37.44 | 47.15 |
|     screen door     | 49.83 | 66.63 |
|       stairway      | 21.75 | 25.55 |
|        river        | 13.18 | 17.43 |
|        bridge       | 46.08 | 68.63 |
|       bookcase      | 28.33 | 45.77 |
|        blind        | 25.87 | 30.94 |
|     coffee table    | 37.92 | 71.55 |
|        toilet       | 66.36 | 77.44 |
|        flower       | 23.78 |  39.4 |
|         book        | 34.92 | 46.94 |
|         hill        |  4.67 |  5.67 |
|        bench        | 31.61 | 40.76 |
|      countertop     | 40.72 | 53.05 |
|        stove        | 50.36 | 63.15 |
|         palm        | 36.75 | 55.39 |
|    kitchen island   | 18.04 | 40.13 |
|       computer      | 42.27 | 57.03 |
|     swivel chair    | 25.93 | 31.39 |
|         boat        | 42.31 | 58.68 |
|         bar         | 24.35 | 29.18 |
|    arcade machine   | 38.58 | 43.55 |
|        hovel        | 31.21 |  38.3 |
|         bus         |  62.8 |  83.6 |
|        towel        | 36.58 |  48.6 |
|        light        | 16.83 |  18.7 |
|        truck        |  5.19 |  7.36 |
|        tower        | 34.05 | 41.25 |
|      chandelier     | 45.89 | 61.87 |
|        awning       |  16.2 | 19.36 |
|     streetlight     |  7.23 |  8.57 |
|        booth        | 24.96 | 27.14 |
| television receiver | 36.89 | 63.62 |
|       airplane      |  43.8 | 54.95 |
|      dirt track     | 11.61 | 16.25 |
|       apparel       | 18.09 | 30.71 |
|         pole        |  6.46 | 10.98 |
|         land        |  0.46 |  0.63 |
|      bannister      |  2.21 |  2.89 |
|      escalator      | 20.92 | 22.26 |
|       ottoman       | 25.69 | 30.18 |
|        bottle       | 17.72 | 43.77 |
|        buffet       | 37.87 | 49.63 |
|        poster       |  23.3 | 26.48 |
|        stage        | 10.33 |  14.2 |
|         van         | 13.65 | 15.43 |
|         ship        |  2.01 |  2.4  |
|       fountain      | 11.94 | 12.48 |
|    conveyer belt    | 53.63 | 56.31 |
|        canopy       | 17.97 | 24.51 |
|        washer       | 59.69 | 61.57 |
|      plaything      |  5.6  |  9.15 |
|    swimming pool    | 28.71 | 46.85 |
|        stool        | 15.32 | 18.35 |
|        barrel       |  34.8 | 61.93 |
|        basket       | 13.92 | 17.74 |
|      waterfall      | 49.01 |  62.9 |
|         tent        | 81.71 |  97.4 |
|         bag         |  3.22 |  3.59 |
|       minibike      | 41.76 | 49.44 |
|        cradle       | 55.69 | 79.82 |
|         oven        | 17.25 | 29.31 |
|         ball        | 17.99 | 19.28 |
|         food        | 36.73 | 47.09 |
|         step        |  3.03 |  3.27 |
|         tank        | 30.36 | 37.06 |
|      trade name     |  15.6 |  17.6 |
|      microwave      | 25.68 | 30.01 |
|         pot         | 22.23 | 26.56 |
|        animal       | 42.44 | 49.59 |
|       bicycle       | 33.37 | 53.76 |
|         lake        | 10.46 |  11.5 |
|      dishwasher     | 30.03 |  41.8 |
|        screen       | 53.15 | 76.36 |
|       blanket       |  1.03 |  1.19 |
|      sculpture      | 34.12 | 49.63 |
|         hood        | 34.92 | 42.83 |
|        sconce       | 13.02 | 14.34 |
|         vase        | 14.93 | 20.65 |
|    traffic light    |  9.93 | 13.61 |
|         tray        |  2.85 |  5.45 |
|        ashcan       | 21.88 | 27.37 |
|         fan         | 25.91 |  31.0 |
|         pier        |  37.8 | 50.84 |
|      crt screen     |  0.53 |  0.84 |
|        plate        | 29.44 | 37.58 |
|       monitor       |  29.4 | 32.92 |
|    bulletin board   | 32.06 | 36.79 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 34.39 | 39.48 |
|        glass        |  0.23 |  0.23 |
|        clock        |  7.76 |  8.45 |
|         flag        | 14.51 | 15.52 |
+---------------------+-------+-------+
2022-11-04 16:22:16,119 - mmseg - INFO - Summary:
2022-11-04 16:22:16,119 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 75.26 | 33.88 | 44.67 |
+-------+-------+-------+
2022-11-04 16:22:16,120 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:22:16,121 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7526, mIoU: 0.3388, mAcc: 0.4467, IoU.wall: 0.6674, IoU.building: 0.7563, IoU.sky: 0.8890, IoU.floor: 0.7071, IoU.tree: 0.6795, IoU.ceiling: 0.7580, IoU.road: 0.7519, IoU.bed : 0.7594, IoU.windowpane: 0.4959, IoU.grass: 0.6400, IoU.cabinet: 0.4826, IoU.sidewalk: 0.5313, IoU.person: 0.6398, IoU.earth: 0.2711, IoU.door: 0.2478, IoU.table: 0.3949, IoU.mountain: 0.5321, IoU.plant: 0.4575, IoU.curtain: 0.5513, IoU.chair: 0.3678, IoU.car: 0.7076, IoU.water: 0.4346, IoU.painting: 0.5527, IoU.sofa: 0.4752, IoU.shelf: 0.3257, IoU.house: 0.4382, IoU.sea: 0.3430, IoU.mirror: 0.4013, IoU.rug: 0.4707, IoU.field: 0.3574, IoU.armchair: 0.2593, IoU.seat: 0.5041, IoU.fence: 0.2580, IoU.desk: 0.3137, IoU.rock: 0.3836, IoU.wardrobe: 0.3441, IoU.lamp: 0.3814, IoU.bathtub: 0.5289, IoU.railing: 0.2522, IoU.cushion: 0.3301, IoU.base: 0.2039, IoU.box: 0.1545, IoU.column: 0.3417, IoU.signboard: 0.2377, IoU.chest of drawers: 0.2775, IoU.counter: 0.2704, IoU.sand: 0.2849, IoU.sink: 0.4546, IoU.skyscraper: 0.6493, IoU.fireplace: 0.5924, IoU.refrigerator: 0.5112, IoU.grandstand: 0.4001, IoU.path: 0.2123, IoU.stairs: 0.2476, IoU.runway: 0.7074, IoU.case: 0.3474, IoU.pool table: 0.7994, IoU.pillow: 0.3744, IoU.screen door: 0.4983, IoU.stairway: 0.2175, IoU.river: 0.1318, IoU.bridge: 0.4608, IoU.bookcase: 0.2833, IoU.blind: 0.2587, IoU.coffee table: 0.3792, IoU.toilet: 0.6636, IoU.flower: 0.2378, IoU.book: 0.3492, IoU.hill: 0.0467, IoU.bench: 0.3161, IoU.countertop: 0.4072, IoU.stove: 0.5036, IoU.palm: 0.3675, IoU.kitchen island: 0.1804, IoU.computer: 0.4227, IoU.swivel chair: 0.2593, IoU.boat: 0.4231, IoU.bar: 0.2435, IoU.arcade machine: 0.3858, IoU.hovel: 0.3121, IoU.bus: 0.6280, IoU.towel: 0.3658, IoU.light: 0.1683, IoU.truck: 0.0519, IoU.tower: 0.3405, IoU.chandelier: 0.4589, IoU.awning: 0.1620, IoU.streetlight: 0.0723, IoU.booth: 0.2496, IoU.television receiver: 0.3689, IoU.airplane: 0.4380, IoU.dirt track: 0.1161, IoU.apparel: 0.1809, IoU.pole: 0.0646, IoU.land: 0.0046, IoU.bannister: 0.0221, IoU.escalator: 0.2092, IoU.ottoman: 0.2569, IoU.bottle: 0.1772, IoU.buffet: 0.3787, IoU.poster: 0.2330, IoU.stage: 0.1033, IoU.van: 0.1365, IoU.ship: 0.0201, IoU.fountain: 0.1194, IoU.conveyer belt: 0.5363, IoU.canopy: 0.1797, IoU.washer: 0.5969, IoU.plaything: 0.0560, IoU.swimming pool: 0.2871, IoU.stool: 0.1532, IoU.barrel: 0.3480, IoU.basket: 0.1392, IoU.waterfall: 0.4901, IoU.tent: 0.8171, IoU.bag: 0.0322, IoU.minibike: 0.4176, IoU.cradle: 0.5569, IoU.oven: 0.1725, IoU.ball: 0.1799, IoU.food: 0.3673, IoU.step: 0.0303, IoU.tank: 0.3036, IoU.trade name: 0.1560, IoU.microwave: 0.2568, IoU.pot: 0.2223, IoU.animal: 0.4244, IoU.bicycle: 0.3337, IoU.lake: 0.1046, IoU.dishwasher: 0.3003, IoU.screen: 0.5315, IoU.blanket: 0.0103, IoU.sculpture: 0.3412, IoU.hood: 0.3492, IoU.sconce: 0.1302, IoU.vase: 0.1493, IoU.traffic light: 0.0993, IoU.tray: 0.0285, IoU.ashcan: 0.2188, IoU.fan: 0.2591, IoU.pier: 0.3780, IoU.crt screen: 0.0053, IoU.plate: 0.2944, IoU.monitor: 0.2940, IoU.bulletin board: 0.3206, IoU.shower: 0.0000, IoU.radiator: 0.3439, IoU.glass: 0.0023, IoU.clock: 0.0776, IoU.flag: 0.1451, Acc.wall: 0.8207, Acc.building: 0.8951, Acc.sky: 0.9311, Acc.floor: 0.8505, Acc.tree: 0.8399, Acc.ceiling: 0.8459, Acc.road: 0.8371, Acc.bed : 0.9073, Acc.windowpane: 0.6903, Acc.grass: 0.8386, Acc.cabinet: 0.6479, Acc.sidewalk: 0.7308, Acc.person: 0.8318, Acc.earth: 0.3830, Acc.door: 0.3918, Acc.table: 0.5513, Acc.mountain: 0.7136, Acc.plant: 0.5984, Acc.curtain: 0.7245, Acc.chair: 0.5044, Acc.car: 0.8557, Acc.water: 0.6101, Acc.painting: 0.7310, Acc.sofa: 0.6901, Acc.shelf: 0.4788, Acc.house: 0.6711, Acc.sea: 0.5648, Acc.mirror: 0.4858, Acc.rug: 0.5881, Acc.field: 0.4569, Acc.armchair: 0.3781, Acc.seat: 0.7161, Acc.fence: 0.4533, Acc.desk: 0.5067, Acc.rock: 0.6388, Acc.wardrobe: 0.5097, Acc.lamp: 0.5240, Acc.bathtub: 0.6531, Acc.railing: 0.3652, Acc.cushion: 0.4423, Acc.base: 0.2521, Acc.box: 0.2197, Acc.column: 0.4308, Acc.signboard: 0.3331, Acc.chest of drawers: 0.4230, Acc.counter: 0.2973, Acc.sand: 0.4524, Acc.sink: 0.6183, Acc.skyscraper: 0.8605, Acc.fireplace: 0.7658, Acc.refrigerator: 0.6290, Acc.grandstand: 0.6731, Acc.path: 0.3194, Acc.stairs: 0.3143, Acc.runway: 0.8503, Acc.case: 0.5261, Acc.pool table: 0.9036, Acc.pillow: 0.4715, Acc.screen door: 0.6663, Acc.stairway: 0.2555, Acc.river: 0.1743, Acc.bridge: 0.6863, Acc.bookcase: 0.4577, Acc.blind: 0.3094, Acc.coffee table: 0.7155, Acc.toilet: 0.7744, Acc.flower: 0.3940, Acc.book: 0.4694, Acc.hill: 0.0567, Acc.bench: 0.4076, Acc.countertop: 0.5305, Acc.stove: 0.6315, Acc.palm: 0.5539, Acc.kitchen island: 0.4013, Acc.computer: 0.5703, Acc.swivel chair: 0.3139, Acc.boat: 0.5868, Acc.bar: 0.2918, Acc.arcade machine: 0.4355, Acc.hovel: 0.3830, Acc.bus: 0.8360, Acc.towel: 0.4860, Acc.light: 0.1870, Acc.truck: 0.0736, Acc.tower: 0.4125, Acc.chandelier: 0.6187, Acc.awning: 0.1936, Acc.streetlight: 0.0857, Acc.booth: 0.2714, Acc.television receiver: 0.6362, Acc.airplane: 0.5495, Acc.dirt track: 0.1625, Acc.apparel: 0.3071, Acc.pole: 0.1098, Acc.land: 0.0063, Acc.bannister: 0.0289, Acc.escalator: 0.2226, Acc.ottoman: 0.3018, Acc.bottle: 0.4377, Acc.buffet: 0.4963, Acc.poster: 0.2648, Acc.stage: 0.1420, Acc.van: 0.1543, Acc.ship: 0.0240, Acc.fountain: 0.1248, Acc.conveyer belt: 0.5631, Acc.canopy: 0.2451, Acc.washer: 0.6157, Acc.plaything: 0.0915, Acc.swimming pool: 0.4685, Acc.stool: 0.1835, Acc.barrel: 0.6193, Acc.basket: 0.1774, Acc.waterfall: 0.6290, Acc.tent: 0.9740, Acc.bag: 0.0359, Acc.minibike: 0.4944, Acc.cradle: 0.7982, Acc.oven: 0.2931, Acc.ball: 0.1928, Acc.food: 0.4709, Acc.step: 0.0327, Acc.tank: 0.3706, Acc.trade name: 0.1760, Acc.microwave: 0.3001, Acc.pot: 0.2656, Acc.animal: 0.4959, Acc.bicycle: 0.5376, Acc.lake: 0.1150, Acc.dishwasher: 0.4180, Acc.screen: 0.7636, Acc.blanket: 0.0119, Acc.sculpture: 0.4963, Acc.hood: 0.4283, Acc.sconce: 0.1434, Acc.vase: 0.2065, Acc.traffic light: 0.1361, Acc.tray: 0.0545, Acc.ashcan: 0.2737, Acc.fan: 0.3100, Acc.pier: 0.5084, Acc.crt screen: 0.0084, Acc.plate: 0.3758, Acc.monitor: 0.3292, Acc.bulletin board: 0.3679, Acc.shower: 0.0000, Acc.radiator: 0.3948, Acc.glass: 0.0023, Acc.clock: 0.0845, Acc.flag: 0.1552
2022-11-04 16:22:32,635 - mmseg - INFO - Iter [64050/80000]	lr: 2.811e-05, eta: 1:30:40, time: 0.507, data_time: 0.186, memory: 12960, decode.loss_ce: 0.4154, decode.acc_seg: 83.5570, aux.loss_ce: 0.2358, aux.acc_seg: 78.5558, loss: 0.6512
2022-11-04 16:22:49,339 - mmseg - INFO - Iter [64100/80000]	lr: 2.803e-05, eta: 1:30:23, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4253, decode.acc_seg: 83.1211, aux.loss_ce: 0.2429, aux.acc_seg: 77.6749, loss: 0.6682
2022-11-04 16:23:06,087 - mmseg - INFO - Iter [64150/80000]	lr: 2.795e-05, eta: 1:30:06, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4301, decode.acc_seg: 83.1493, aux.loss_ce: 0.2480, aux.acc_seg: 77.2715, loss: 0.6781
2022-11-04 16:23:22,939 - mmseg - INFO - Iter [64200/80000]	lr: 2.788e-05, eta: 1:29:49, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4189, decode.acc_seg: 83.3921, aux.loss_ce: 0.2440, aux.acc_seg: 77.7134, loss: 0.6629
2022-11-04 16:23:39,663 - mmseg - INFO - Iter [64250/80000]	lr: 2.780e-05, eta: 1:29:32, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4242, decode.acc_seg: 83.3762, aux.loss_ce: 0.2416, aux.acc_seg: 78.2048, loss: 0.6658
2022-11-04 16:23:56,472 - mmseg - INFO - Iter [64300/80000]	lr: 2.772e-05, eta: 1:29:15, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4368, decode.acc_seg: 82.7438, aux.loss_ce: 0.2476, aux.acc_seg: 77.3430, loss: 0.6844
2022-11-04 16:24:13,387 - mmseg - INFO - Iter [64350/80000]	lr: 2.764e-05, eta: 1:28:58, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4299, decode.acc_seg: 83.4406, aux.loss_ce: 0.2460, aux.acc_seg: 77.8872, loss: 0.6759
2022-11-04 16:24:33,016 - mmseg - INFO - Iter [64400/80000]	lr: 2.756e-05, eta: 1:28:41, time: 0.393, data_time: 0.058, memory: 12960, decode.loss_ce: 0.4306, decode.acc_seg: 83.1660, aux.loss_ce: 0.2476, aux.acc_seg: 77.4147, loss: 0.6783
2022-11-04 16:24:49,847 - mmseg - INFO - Iter [64450/80000]	lr: 2.748e-05, eta: 1:28:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4057, decode.acc_seg: 83.6846, aux.loss_ce: 0.2360, aux.acc_seg: 77.8416, loss: 0.6417
2022-11-04 16:25:06,649 - mmseg - INFO - Iter [64500/80000]	lr: 2.740e-05, eta: 1:28:07, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4353, decode.acc_seg: 82.8130, aux.loss_ce: 0.2519, aux.acc_seg: 77.1161, loss: 0.6872
2022-11-04 16:25:23,469 - mmseg - INFO - Iter [64550/80000]	lr: 2.732e-05, eta: 1:27:50, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4234, decode.acc_seg: 83.1265, aux.loss_ce: 0.2448, aux.acc_seg: 77.4207, loss: 0.6681
2022-11-04 16:25:40,359 - mmseg - INFO - Iter [64600/80000]	lr: 2.724e-05, eta: 1:27:33, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4097, decode.acc_seg: 83.6420, aux.loss_ce: 0.2326, aux.acc_seg: 78.5897, loss: 0.6423
2022-11-04 16:25:56,999 - mmseg - INFO - Iter [64650/80000]	lr: 2.716e-05, eta: 1:27:15, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4167, decode.acc_seg: 83.5642, aux.loss_ce: 0.2390, aux.acc_seg: 78.1061, loss: 0.6557
2022-11-04 16:26:13,802 - mmseg - INFO - Iter [64700/80000]	lr: 2.708e-05, eta: 1:26:58, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4208, decode.acc_seg: 83.5060, aux.loss_ce: 0.2449, aux.acc_seg: 77.6457, loss: 0.6658
2022-11-04 16:26:30,572 - mmseg - INFO - Iter [64750/80000]	lr: 2.700e-05, eta: 1:26:41, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4283, decode.acc_seg: 83.1171, aux.loss_ce: 0.2446, aux.acc_seg: 77.7581, loss: 0.6729
2022-11-04 16:26:47,373 - mmseg - INFO - Iter [64800/80000]	lr: 2.692e-05, eta: 1:26:24, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4261, decode.acc_seg: 83.2203, aux.loss_ce: 0.2440, aux.acc_seg: 77.6453, loss: 0.6701
2022-11-04 16:27:04,089 - mmseg - INFO - Iter [64850/80000]	lr: 2.684e-05, eta: 1:26:07, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4296, decode.acc_seg: 83.2906, aux.loss_ce: 0.2495, aux.acc_seg: 77.0550, loss: 0.6791
2022-11-04 16:27:20,829 - mmseg - INFO - Iter [64900/80000]	lr: 2.676e-05, eta: 1:25:50, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4340, decode.acc_seg: 82.9533, aux.loss_ce: 0.2474, aux.acc_seg: 77.1726, loss: 0.6814
2022-11-04 16:27:37,610 - mmseg - INFO - Iter [64950/80000]	lr: 2.668e-05, eta: 1:25:33, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4316, decode.acc_seg: 83.1547, aux.loss_ce: 0.2487, aux.acc_seg: 77.4699, loss: 0.6803
2022-11-04 16:27:57,265 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:27:57,266 - mmseg - INFO - Iter [65000/80000]	lr: 2.660e-05, eta: 1:25:16, time: 0.393, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4212, decode.acc_seg: 83.6204, aux.loss_ce: 0.2398, aux.acc_seg: 78.1565, loss: 0.6610
2022-11-04 16:28:13,830 - mmseg - INFO - Iter [65050/80000]	lr: 2.652e-05, eta: 1:24:59, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4257, decode.acc_seg: 83.2267, aux.loss_ce: 0.2514, aux.acc_seg: 76.9908, loss: 0.6771
2022-11-04 16:28:30,649 - mmseg - INFO - Iter [65100/80000]	lr: 2.644e-05, eta: 1:24:42, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4295, decode.acc_seg: 83.0112, aux.loss_ce: 0.2516, aux.acc_seg: 77.2886, loss: 0.6811
2022-11-04 16:28:47,469 - mmseg - INFO - Iter [65150/80000]	lr: 2.636e-05, eta: 1:24:25, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4254, decode.acc_seg: 83.4461, aux.loss_ce: 0.2464, aux.acc_seg: 77.6318, loss: 0.6718
2022-11-04 16:29:04,441 - mmseg - INFO - Iter [65200/80000]	lr: 2.628e-05, eta: 1:24:08, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4216, decode.acc_seg: 83.3077, aux.loss_ce: 0.2466, aux.acc_seg: 77.4841, loss: 0.6683
2022-11-04 16:29:20,853 - mmseg - INFO - Iter [65250/80000]	lr: 2.620e-05, eta: 1:23:51, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4158, decode.acc_seg: 83.5326, aux.loss_ce: 0.2361, aux.acc_seg: 78.5110, loss: 0.6519
2022-11-04 16:29:37,535 - mmseg - INFO - Iter [65300/80000]	lr: 2.612e-05, eta: 1:23:34, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4242, decode.acc_seg: 83.3939, aux.loss_ce: 0.2431, aux.acc_seg: 77.7821, loss: 0.6673
2022-11-04 16:29:54,105 - mmseg - INFO - Iter [65350/80000]	lr: 2.604e-05, eta: 1:23:16, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4276, decode.acc_seg: 83.0068, aux.loss_ce: 0.2435, aux.acc_seg: 77.2748, loss: 0.6710
2022-11-04 16:30:10,857 - mmseg - INFO - Iter [65400/80000]	lr: 2.596e-05, eta: 1:22:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4184, decode.acc_seg: 83.4446, aux.loss_ce: 0.2458, aux.acc_seg: 77.2527, loss: 0.6642
2022-11-04 16:30:27,400 - mmseg - INFO - Iter [65450/80000]	lr: 2.588e-05, eta: 1:22:42, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4308, decode.acc_seg: 83.1732, aux.loss_ce: 0.2435, aux.acc_seg: 77.8707, loss: 0.6743
2022-11-04 16:30:44,271 - mmseg - INFO - Iter [65500/80000]	lr: 2.580e-05, eta: 1:22:25, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4265, decode.acc_seg: 83.4433, aux.loss_ce: 0.2489, aux.acc_seg: 77.5451, loss: 0.6754
2022-11-04 16:31:00,926 - mmseg - INFO - Iter [65550/80000]	lr: 2.572e-05, eta: 1:22:08, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4293, decode.acc_seg: 83.2168, aux.loss_ce: 0.2430, aux.acc_seg: 77.8347, loss: 0.6723
2022-11-04 16:31:17,610 - mmseg - INFO - Iter [65600/80000]	lr: 2.564e-05, eta: 1:21:51, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4152, decode.acc_seg: 83.7637, aux.loss_ce: 0.2350, aux.acc_seg: 78.4075, loss: 0.6502
2022-11-04 16:31:37,090 - mmseg - INFO - Iter [65650/80000]	lr: 2.556e-05, eta: 1:21:34, time: 0.390, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4253, decode.acc_seg: 83.2481, aux.loss_ce: 0.2459, aux.acc_seg: 77.3962, loss: 0.6712
2022-11-04 16:31:53,840 - mmseg - INFO - Iter [65700/80000]	lr: 2.548e-05, eta: 1:21:17, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4155, decode.acc_seg: 83.7243, aux.loss_ce: 0.2454, aux.acc_seg: 77.4862, loss: 0.6610
2022-11-04 16:32:10,753 - mmseg - INFO - Iter [65750/80000]	lr: 2.540e-05, eta: 1:21:00, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4350, decode.acc_seg: 82.8476, aux.loss_ce: 0.2536, aux.acc_seg: 76.6407, loss: 0.6885
2022-11-04 16:32:27,400 - mmseg - INFO - Iter [65800/80000]	lr: 2.532e-05, eta: 1:20:43, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4190, decode.acc_seg: 83.4805, aux.loss_ce: 0.2411, aux.acc_seg: 77.9514, loss: 0.6601
2022-11-04 16:32:44,026 - mmseg - INFO - Iter [65850/80000]	lr: 2.524e-05, eta: 1:20:26, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4407, decode.acc_seg: 82.8121, aux.loss_ce: 0.2528, aux.acc_seg: 77.1419, loss: 0.6935
2022-11-04 16:33:01,001 - mmseg - INFO - Iter [65900/80000]	lr: 2.516e-05, eta: 1:20:09, time: 0.340, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4265, decode.acc_seg: 83.5616, aux.loss_ce: 0.2466, aux.acc_seg: 77.5373, loss: 0.6730
2022-11-04 16:33:17,915 - mmseg - INFO - Iter [65950/80000]	lr: 2.508e-05, eta: 1:19:52, time: 0.338, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4223, decode.acc_seg: 83.4303, aux.loss_ce: 0.2440, aux.acc_seg: 77.6091, loss: 0.6663
2022-11-04 16:33:34,640 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:33:34,641 - mmseg - INFO - Iter [66000/80000]	lr: 2.500e-05, eta: 1:19:34, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4218, decode.acc_seg: 83.2291, aux.loss_ce: 0.2422, aux.acc_seg: 77.8784, loss: 0.6640
2022-11-04 16:33:51,589 - mmseg - INFO - Iter [66050/80000]	lr: 2.492e-05, eta: 1:19:17, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4062, decode.acc_seg: 83.9952, aux.loss_ce: 0.2412, aux.acc_seg: 77.9749, loss: 0.6474
2022-11-04 16:34:08,240 - mmseg - INFO - Iter [66100/80000]	lr: 2.484e-05, eta: 1:19:00, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4208, decode.acc_seg: 83.4508, aux.loss_ce: 0.2413, aux.acc_seg: 77.8649, loss: 0.6621
2022-11-04 16:34:24,920 - mmseg - INFO - Iter [66150/80000]	lr: 2.476e-05, eta: 1:18:43, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4367, decode.acc_seg: 82.8534, aux.loss_ce: 0.2539, aux.acc_seg: 76.9105, loss: 0.6906
2022-11-04 16:34:41,999 - mmseg - INFO - Iter [66200/80000]	lr: 2.468e-05, eta: 1:18:26, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4127, decode.acc_seg: 83.5837, aux.loss_ce: 0.2374, aux.acc_seg: 78.0704, loss: 0.6501
2022-11-04 16:34:58,680 - mmseg - INFO - Iter [66250/80000]	lr: 2.460e-05, eta: 1:18:09, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4359, decode.acc_seg: 82.8905, aux.loss_ce: 0.2530, aux.acc_seg: 77.1307, loss: 0.6889
2022-11-04 16:35:18,347 - mmseg - INFO - Iter [66300/80000]	lr: 2.452e-05, eta: 1:17:52, time: 0.393, data_time: 0.060, memory: 12960, decode.loss_ce: 0.4074, decode.acc_seg: 83.8250, aux.loss_ce: 0.2344, aux.acc_seg: 78.5550, loss: 0.6418
2022-11-04 16:35:34,827 - mmseg - INFO - Iter [66350/80000]	lr: 2.444e-05, eta: 1:17:35, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4098, decode.acc_seg: 83.8875, aux.loss_ce: 0.2357, aux.acc_seg: 78.4458, loss: 0.6455
2022-11-04 16:35:51,588 - mmseg - INFO - Iter [66400/80000]	lr: 2.436e-05, eta: 1:17:18, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4374, decode.acc_seg: 82.7772, aux.loss_ce: 0.2471, aux.acc_seg: 77.4761, loss: 0.6845
2022-11-04 16:36:08,142 - mmseg - INFO - Iter [66450/80000]	lr: 2.428e-05, eta: 1:17:01, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4204, decode.acc_seg: 83.3574, aux.loss_ce: 0.2391, aux.acc_seg: 77.8904, loss: 0.6595
2022-11-04 16:36:24,783 - mmseg - INFO - Iter [66500/80000]	lr: 2.420e-05, eta: 1:16:44, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4173, decode.acc_seg: 83.7221, aux.loss_ce: 0.2439, aux.acc_seg: 77.7930, loss: 0.6613
2022-11-04 16:36:41,417 - mmseg - INFO - Iter [66550/80000]	lr: 2.411e-05, eta: 1:16:27, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4115, decode.acc_seg: 83.8490, aux.loss_ce: 0.2337, aux.acc_seg: 78.8094, loss: 0.6452
2022-11-04 16:36:57,953 - mmseg - INFO - Iter [66600/80000]	lr: 2.403e-05, eta: 1:16:09, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4176, decode.acc_seg: 83.5243, aux.loss_ce: 0.2449, aux.acc_seg: 77.3637, loss: 0.6625
2022-11-04 16:37:14,660 - mmseg - INFO - Iter [66650/80000]	lr: 2.395e-05, eta: 1:15:52, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4181, decode.acc_seg: 83.6132, aux.loss_ce: 0.2409, aux.acc_seg: 78.1209, loss: 0.6591
2022-11-04 16:37:31,270 - mmseg - INFO - Iter [66700/80000]	lr: 2.387e-05, eta: 1:15:35, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4338, decode.acc_seg: 83.2165, aux.loss_ce: 0.2512, aux.acc_seg: 77.1695, loss: 0.6850
2022-11-04 16:37:47,933 - mmseg - INFO - Iter [66750/80000]	lr: 2.379e-05, eta: 1:15:18, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4335, decode.acc_seg: 82.8947, aux.loss_ce: 0.2492, aux.acc_seg: 77.1085, loss: 0.6827
2022-11-04 16:38:04,686 - mmseg - INFO - Iter [66800/80000]	lr: 2.371e-05, eta: 1:15:01, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4337, decode.acc_seg: 82.9652, aux.loss_ce: 0.2530, aux.acc_seg: 76.9789, loss: 0.6867
2022-11-04 16:38:21,551 - mmseg - INFO - Iter [66850/80000]	lr: 2.363e-05, eta: 1:14:44, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4063, decode.acc_seg: 84.1793, aux.loss_ce: 0.2335, aux.acc_seg: 78.8913, loss: 0.6398
2022-11-04 16:38:41,208 - mmseg - INFO - Iter [66900/80000]	lr: 2.355e-05, eta: 1:14:27, time: 0.393, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4216, decode.acc_seg: 83.4162, aux.loss_ce: 0.2474, aux.acc_seg: 77.2001, loss: 0.6690
2022-11-04 16:38:57,621 - mmseg - INFO - Iter [66950/80000]	lr: 2.347e-05, eta: 1:14:10, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4219, decode.acc_seg: 83.5304, aux.loss_ce: 0.2392, aux.acc_seg: 78.0519, loss: 0.6611
2022-11-04 16:39:14,325 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:39:14,325 - mmseg - INFO - Iter [67000/80000]	lr: 2.339e-05, eta: 1:13:53, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4362, decode.acc_seg: 82.6951, aux.loss_ce: 0.2472, aux.acc_seg: 77.0875, loss: 0.6833
2022-11-04 16:39:30,800 - mmseg - INFO - Iter [67050/80000]	lr: 2.331e-05, eta: 1:13:36, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4013, decode.acc_seg: 83.9520, aux.loss_ce: 0.2281, aux.acc_seg: 78.6784, loss: 0.6294
2022-11-04 16:39:47,390 - mmseg - INFO - Iter [67100/80000]	lr: 2.323e-05, eta: 1:13:19, time: 0.332, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4371, decode.acc_seg: 82.7705, aux.loss_ce: 0.2524, aux.acc_seg: 76.8804, loss: 0.6895
2022-11-04 16:40:04,004 - mmseg - INFO - Iter [67150/80000]	lr: 2.314e-05, eta: 1:13:02, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4095, decode.acc_seg: 83.5870, aux.loss_ce: 0.2378, aux.acc_seg: 78.1277, loss: 0.6473
2022-11-04 16:40:20,703 - mmseg - INFO - Iter [67200/80000]	lr: 2.306e-05, eta: 1:12:45, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4242, decode.acc_seg: 83.1071, aux.loss_ce: 0.2474, aux.acc_seg: 77.2829, loss: 0.6716
2022-11-04 16:40:37,464 - mmseg - INFO - Iter [67250/80000]	lr: 2.298e-05, eta: 1:12:27, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4347, decode.acc_seg: 83.0566, aux.loss_ce: 0.2515, aux.acc_seg: 77.2994, loss: 0.6862
2022-11-04 16:40:54,162 - mmseg - INFO - Iter [67300/80000]	lr: 2.290e-05, eta: 1:12:10, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4038, decode.acc_seg: 83.9922, aux.loss_ce: 0.2319, aux.acc_seg: 78.4894, loss: 0.6357
2022-11-04 16:41:10,729 - mmseg - INFO - Iter [67350/80000]	lr: 2.282e-05, eta: 1:11:53, time: 0.331, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4264, decode.acc_seg: 83.1728, aux.loss_ce: 0.2436, aux.acc_seg: 77.6261, loss: 0.6700
2022-11-04 16:41:27,550 - mmseg - INFO - Iter [67400/80000]	lr: 2.274e-05, eta: 1:11:36, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4106, decode.acc_seg: 83.9565, aux.loss_ce: 0.2403, aux.acc_seg: 78.1985, loss: 0.6509
2022-11-04 16:41:44,018 - mmseg - INFO - Iter [67450/80000]	lr: 2.266e-05, eta: 1:11:19, time: 0.329, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4160, decode.acc_seg: 83.5296, aux.loss_ce: 0.2384, aux.acc_seg: 78.0958, loss: 0.6544
2022-11-04 16:42:00,751 - mmseg - INFO - Iter [67500/80000]	lr: 2.258e-05, eta: 1:11:02, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4153, decode.acc_seg: 83.4858, aux.loss_ce: 0.2381, aux.acc_seg: 77.9434, loss: 0.6534
2022-11-04 16:42:20,739 - mmseg - INFO - Iter [67550/80000]	lr: 2.249e-05, eta: 1:10:45, time: 0.400, data_time: 0.065, memory: 12960, decode.loss_ce: 0.4001, decode.acc_seg: 84.2825, aux.loss_ce: 0.2337, aux.acc_seg: 78.8215, loss: 0.6338
2022-11-04 16:42:37,547 - mmseg - INFO - Iter [67600/80000]	lr: 2.241e-05, eta: 1:10:28, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4349, decode.acc_seg: 83.0278, aux.loss_ce: 0.2523, aux.acc_seg: 77.1465, loss: 0.6872
2022-11-04 16:42:54,504 - mmseg - INFO - Iter [67650/80000]	lr: 2.233e-05, eta: 1:10:11, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4131, decode.acc_seg: 83.9129, aux.loss_ce: 0.2404, aux.acc_seg: 78.1595, loss: 0.6535
2022-11-04 16:43:11,238 - mmseg - INFO - Iter [67700/80000]	lr: 2.225e-05, eta: 1:09:54, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4181, decode.acc_seg: 83.4409, aux.loss_ce: 0.2423, aux.acc_seg: 77.7062, loss: 0.6604
2022-11-04 16:43:28,168 - mmseg - INFO - Iter [67750/80000]	lr: 2.217e-05, eta: 1:09:37, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4288, decode.acc_seg: 83.0623, aux.loss_ce: 0.2471, aux.acc_seg: 77.4568, loss: 0.6759
2022-11-04 16:43:44,730 - mmseg - INFO - Iter [67800/80000]	lr: 2.209e-05, eta: 1:09:20, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4178, decode.acc_seg: 83.5880, aux.loss_ce: 0.2426, aux.acc_seg: 77.8170, loss: 0.6604
2022-11-04 16:44:01,400 - mmseg - INFO - Iter [67850/80000]	lr: 2.201e-05, eta: 1:09:03, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4308, decode.acc_seg: 83.2543, aux.loss_ce: 0.2512, aux.acc_seg: 77.5695, loss: 0.6819
2022-11-04 16:44:18,145 - mmseg - INFO - Iter [67900/80000]	lr: 2.192e-05, eta: 1:08:46, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4241, decode.acc_seg: 83.2287, aux.loss_ce: 0.2453, aux.acc_seg: 77.4628, loss: 0.6694
2022-11-04 16:44:35,045 - mmseg - INFO - Iter [67950/80000]	lr: 2.184e-05, eta: 1:08:28, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4172, decode.acc_seg: 83.5162, aux.loss_ce: 0.2411, aux.acc_seg: 77.7579, loss: 0.6582
2022-11-04 16:44:51,825 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:44:51,825 - mmseg - INFO - Iter [68000/80000]	lr: 2.176e-05, eta: 1:08:11, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4207, decode.acc_seg: 83.5583, aux.loss_ce: 0.2450, aux.acc_seg: 77.5619, loss: 0.6656
2022-11-04 16:45:08,465 - mmseg - INFO - Iter [68050/80000]	lr: 2.168e-05, eta: 1:07:54, time: 0.333, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4167, decode.acc_seg: 83.7076, aux.loss_ce: 0.2384, aux.acc_seg: 78.2583, loss: 0.6551
2022-11-04 16:45:25,211 - mmseg - INFO - Iter [68100/80000]	lr: 2.160e-05, eta: 1:07:37, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4192, decode.acc_seg: 83.2565, aux.loss_ce: 0.2416, aux.acc_seg: 77.8852, loss: 0.6609
2022-11-04 16:45:44,718 - mmseg - INFO - Iter [68150/80000]	lr: 2.152e-05, eta: 1:07:21, time: 0.389, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4176, decode.acc_seg: 83.6967, aux.loss_ce: 0.2433, aux.acc_seg: 77.7969, loss: 0.6609
2022-11-04 16:46:01,802 - mmseg - INFO - Iter [68200/80000]	lr: 2.144e-05, eta: 1:07:03, time: 0.343, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4202, decode.acc_seg: 83.7364, aux.loss_ce: 0.2413, aux.acc_seg: 78.0748, loss: 0.6615
2022-11-04 16:46:18,647 - mmseg - INFO - Iter [68250/80000]	lr: 2.135e-05, eta: 1:06:46, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4162, decode.acc_seg: 83.7250, aux.loss_ce: 0.2408, aux.acc_seg: 78.0556, loss: 0.6570
2022-11-04 16:46:35,188 - mmseg - INFO - Iter [68300/80000]	lr: 2.127e-05, eta: 1:06:29, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4317, decode.acc_seg: 83.1519, aux.loss_ce: 0.2453, aux.acc_seg: 77.6834, loss: 0.6770
2022-11-04 16:46:51,869 - mmseg - INFO - Iter [68350/80000]	lr: 2.119e-05, eta: 1:06:12, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4187, decode.acc_seg: 83.5805, aux.loss_ce: 0.2399, aux.acc_seg: 78.0475, loss: 0.6586
2022-11-04 16:47:08,595 - mmseg - INFO - Iter [68400/80000]	lr: 2.111e-05, eta: 1:05:55, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4236, decode.acc_seg: 83.5763, aux.loss_ce: 0.2445, aux.acc_seg: 78.0941, loss: 0.6680
2022-11-04 16:47:25,179 - mmseg - INFO - Iter [68450/80000]	lr: 2.103e-05, eta: 1:05:38, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4236, decode.acc_seg: 83.6321, aux.loss_ce: 0.2389, aux.acc_seg: 78.4463, loss: 0.6625
2022-11-04 16:47:41,726 - mmseg - INFO - Iter [68500/80000]	lr: 2.094e-05, eta: 1:05:21, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4221, decode.acc_seg: 83.4915, aux.loss_ce: 0.2426, aux.acc_seg: 77.9391, loss: 0.6647
2022-11-04 16:47:58,320 - mmseg - INFO - Iter [68550/80000]	lr: 2.086e-05, eta: 1:05:04, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4043, decode.acc_seg: 83.7691, aux.loss_ce: 0.2318, aux.acc_seg: 78.5613, loss: 0.6361
2022-11-04 16:48:14,972 - mmseg - INFO - Iter [68600/80000]	lr: 2.078e-05, eta: 1:04:47, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4258, decode.acc_seg: 83.2764, aux.loss_ce: 0.2489, aux.acc_seg: 77.1958, loss: 0.6747
2022-11-04 16:48:31,355 - mmseg - INFO - Iter [68650/80000]	lr: 2.070e-05, eta: 1:04:29, time: 0.328, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4220, decode.acc_seg: 83.4345, aux.loss_ce: 0.2457, aux.acc_seg: 77.5795, loss: 0.6677
2022-11-04 16:48:48,016 - mmseg - INFO - Iter [68700/80000]	lr: 2.062e-05, eta: 1:04:12, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4239, decode.acc_seg: 83.5175, aux.loss_ce: 0.2459, aux.acc_seg: 77.6142, loss: 0.6699
2022-11-04 16:49:04,751 - mmseg - INFO - Iter [68750/80000]	lr: 2.053e-05, eta: 1:03:55, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4161, decode.acc_seg: 83.5220, aux.loss_ce: 0.2435, aux.acc_seg: 77.6196, loss: 0.6596
2022-11-04 16:49:24,553 - mmseg - INFO - Iter [68800/80000]	lr: 2.045e-05, eta: 1:03:39, time: 0.396, data_time: 0.067, memory: 12960, decode.loss_ce: 0.4090, decode.acc_seg: 83.9490, aux.loss_ce: 0.2379, aux.acc_seg: 78.5258, loss: 0.6470
2022-11-04 16:49:41,306 - mmseg - INFO - Iter [68850/80000]	lr: 2.037e-05, eta: 1:03:21, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4188, decode.acc_seg: 83.6742, aux.loss_ce: 0.2423, aux.acc_seg: 78.1217, loss: 0.6611
2022-11-04 16:49:58,366 - mmseg - INFO - Iter [68900/80000]	lr: 2.029e-05, eta: 1:03:04, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4132, decode.acc_seg: 83.8371, aux.loss_ce: 0.2395, aux.acc_seg: 78.4442, loss: 0.6527
2022-11-04 16:50:15,131 - mmseg - INFO - Iter [68950/80000]	lr: 2.021e-05, eta: 1:02:47, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4190, decode.acc_seg: 83.4544, aux.loss_ce: 0.2407, aux.acc_seg: 77.9550, loss: 0.6597
2022-11-04 16:50:31,902 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:50:31,903 - mmseg - INFO - Iter [69000/80000]	lr: 2.012e-05, eta: 1:02:30, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4167, decode.acc_seg: 83.6134, aux.loss_ce: 0.2427, aux.acc_seg: 78.0116, loss: 0.6593
2022-11-04 16:50:49,087 - mmseg - INFO - Iter [69050/80000]	lr: 2.004e-05, eta: 1:02:13, time: 0.344, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4157, decode.acc_seg: 83.9065, aux.loss_ce: 0.2414, aux.acc_seg: 78.1085, loss: 0.6572
2022-11-04 16:51:05,937 - mmseg - INFO - Iter [69100/80000]	lr: 1.996e-05, eta: 1:01:56, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4358, decode.acc_seg: 82.9821, aux.loss_ce: 0.2484, aux.acc_seg: 77.5134, loss: 0.6841
2022-11-04 16:51:22,641 - mmseg - INFO - Iter [69150/80000]	lr: 1.988e-05, eta: 1:01:39, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4094, decode.acc_seg: 83.7719, aux.loss_ce: 0.2400, aux.acc_seg: 77.9114, loss: 0.6495
2022-11-04 16:51:39,292 - mmseg - INFO - Iter [69200/80000]	lr: 1.979e-05, eta: 1:01:22, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4075, decode.acc_seg: 83.7242, aux.loss_ce: 0.2410, aux.acc_seg: 77.8335, loss: 0.6485
2022-11-04 16:51:55,968 - mmseg - INFO - Iter [69250/80000]	lr: 1.971e-05, eta: 1:01:05, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4024, decode.acc_seg: 83.9023, aux.loss_ce: 0.2351, aux.acc_seg: 78.0791, loss: 0.6375
2022-11-04 16:52:12,634 - mmseg - INFO - Iter [69300/80000]	lr: 1.963e-05, eta: 1:00:48, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4096, decode.acc_seg: 83.6538, aux.loss_ce: 0.2382, aux.acc_seg: 77.9784, loss: 0.6478
2022-11-04 16:52:29,556 - mmseg - INFO - Iter [69350/80000]	lr: 1.955e-05, eta: 1:00:31, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4420, decode.acc_seg: 82.6459, aux.loss_ce: 0.2521, aux.acc_seg: 76.9360, loss: 0.6941
2022-11-04 16:52:46,073 - mmseg - INFO - Iter [69400/80000]	lr: 1.946e-05, eta: 1:00:14, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4100, decode.acc_seg: 83.8513, aux.loss_ce: 0.2378, aux.acc_seg: 78.0750, loss: 0.6478
2022-11-04 16:53:05,790 - mmseg - INFO - Iter [69450/80000]	lr: 1.938e-05, eta: 0:59:57, time: 0.394, data_time: 0.063, memory: 12960, decode.loss_ce: 0.4264, decode.acc_seg: 83.4260, aux.loss_ce: 0.2477, aux.acc_seg: 77.3737, loss: 0.6742
2022-11-04 16:53:22,410 - mmseg - INFO - Iter [69500/80000]	lr: 1.930e-05, eta: 0:59:40, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4088, decode.acc_seg: 83.8847, aux.loss_ce: 0.2382, aux.acc_seg: 78.3804, loss: 0.6469
2022-11-04 16:53:39,206 - mmseg - INFO - Iter [69550/80000]	lr: 1.922e-05, eta: 0:59:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4175, decode.acc_seg: 83.8742, aux.loss_ce: 0.2403, aux.acc_seg: 78.1643, loss: 0.6578
2022-11-04 16:53:55,875 - mmseg - INFO - Iter [69600/80000]	lr: 1.913e-05, eta: 0:59:06, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4188, decode.acc_seg: 83.3427, aux.loss_ce: 0.2439, aux.acc_seg: 77.5680, loss: 0.6627
2022-11-04 16:54:12,463 - mmseg - INFO - Iter [69650/80000]	lr: 1.905e-05, eta: 0:58:48, time: 0.332, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4115, decode.acc_seg: 83.6071, aux.loss_ce: 0.2383, aux.acc_seg: 77.6878, loss: 0.6499
2022-11-04 16:54:29,153 - mmseg - INFO - Iter [69700/80000]	lr: 1.897e-05, eta: 0:58:31, time: 0.334, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4286, decode.acc_seg: 83.3381, aux.loss_ce: 0.2488, aux.acc_seg: 77.6459, loss: 0.6774
2022-11-04 16:54:46,012 - mmseg - INFO - Iter [69750/80000]	lr: 1.888e-05, eta: 0:58:14, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4204, decode.acc_seg: 83.3235, aux.loss_ce: 0.2427, aux.acc_seg: 77.5571, loss: 0.6631
2022-11-04 16:55:02,794 - mmseg - INFO - Iter [69800/80000]	lr: 1.880e-05, eta: 0:57:57, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4256, decode.acc_seg: 83.1852, aux.loss_ce: 0.2534, aux.acc_seg: 76.7027, loss: 0.6789
2022-11-04 16:55:19,509 - mmseg - INFO - Iter [69850/80000]	lr: 1.872e-05, eta: 0:57:40, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4129, decode.acc_seg: 83.7652, aux.loss_ce: 0.2350, aux.acc_seg: 78.4322, loss: 0.6480
2022-11-04 16:55:36,251 - mmseg - INFO - Iter [69900/80000]	lr: 1.863e-05, eta: 0:57:23, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4154, decode.acc_seg: 83.6020, aux.loss_ce: 0.2390, aux.acc_seg: 78.1007, loss: 0.6543
2022-11-04 16:55:53,055 - mmseg - INFO - Iter [69950/80000]	lr: 1.855e-05, eta: 0:57:06, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4120, decode.acc_seg: 83.6576, aux.loss_ce: 0.2362, aux.acc_seg: 78.2428, loss: 0.6482
2022-11-04 16:56:09,886 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 16:56:09,886 - mmseg - INFO - Iter [70000/80000]	lr: 1.847e-05, eta: 0:56:49, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4196, decode.acc_seg: 83.6000, aux.loss_ce: 0.2399, aux.acc_seg: 78.3803, loss: 0.6595
2022-11-04 16:56:29,599 - mmseg - INFO - Iter [70050/80000]	lr: 1.839e-05, eta: 0:56:32, time: 0.394, data_time: 0.061, memory: 12960, decode.loss_ce: 0.4102, decode.acc_seg: 84.0368, aux.loss_ce: 0.2410, aux.acc_seg: 78.2223, loss: 0.6512
2022-11-04 16:56:46,265 - mmseg - INFO - Iter [70100/80000]	lr: 1.830e-05, eta: 0:56:15, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4084, decode.acc_seg: 83.7475, aux.loss_ce: 0.2351, aux.acc_seg: 78.5769, loss: 0.6435
2022-11-04 16:57:02,954 - mmseg - INFO - Iter [70150/80000]	lr: 1.822e-05, eta: 0:55:58, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4150, decode.acc_seg: 83.5283, aux.loss_ce: 0.2391, aux.acc_seg: 77.9683, loss: 0.6541
2022-11-04 16:57:19,745 - mmseg - INFO - Iter [70200/80000]	lr: 1.814e-05, eta: 0:55:41, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4217, decode.acc_seg: 83.3864, aux.loss_ce: 0.2452, aux.acc_seg: 77.6468, loss: 0.6669
2022-11-04 16:57:36,257 - mmseg - INFO - Iter [70250/80000]	lr: 1.805e-05, eta: 0:55:24, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4201, decode.acc_seg: 83.5229, aux.loss_ce: 0.2427, aux.acc_seg: 77.8737, loss: 0.6628
2022-11-04 16:57:52,796 - mmseg - INFO - Iter [70300/80000]	lr: 1.797e-05, eta: 0:55:07, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4301, decode.acc_seg: 82.9840, aux.loss_ce: 0.2516, aux.acc_seg: 77.1188, loss: 0.6816
2022-11-04 16:58:09,619 - mmseg - INFO - Iter [70350/80000]	lr: 1.789e-05, eta: 0:54:50, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4082, decode.acc_seg: 84.0129, aux.loss_ce: 0.2407, aux.acc_seg: 78.0011, loss: 0.6489
2022-11-04 16:58:26,371 - mmseg - INFO - Iter [70400/80000]	lr: 1.780e-05, eta: 0:54:32, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4092, decode.acc_seg: 83.8784, aux.loss_ce: 0.2367, aux.acc_seg: 78.6018, loss: 0.6458
2022-11-04 16:58:42,942 - mmseg - INFO - Iter [70450/80000]	lr: 1.772e-05, eta: 0:54:15, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4020, decode.acc_seg: 84.1167, aux.loss_ce: 0.2324, aux.acc_seg: 78.8538, loss: 0.6344
2022-11-04 16:58:59,819 - mmseg - INFO - Iter [70500/80000]	lr: 1.764e-05, eta: 0:53:58, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4124, decode.acc_seg: 83.8958, aux.loss_ce: 0.2396, aux.acc_seg: 78.2979, loss: 0.6520
2022-11-04 16:59:16,685 - mmseg - INFO - Iter [70550/80000]	lr: 1.755e-05, eta: 0:53:41, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4154, decode.acc_seg: 83.5833, aux.loss_ce: 0.2400, aux.acc_seg: 78.0791, loss: 0.6554
2022-11-04 16:59:33,508 - mmseg - INFO - Iter [70600/80000]	lr: 1.747e-05, eta: 0:53:24, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4132, decode.acc_seg: 83.8882, aux.loss_ce: 0.2401, aux.acc_seg: 77.9928, loss: 0.6533
2022-11-04 16:59:50,080 - mmseg - INFO - Iter [70650/80000]	lr: 1.738e-05, eta: 0:53:07, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4142, decode.acc_seg: 83.5000, aux.loss_ce: 0.2363, aux.acc_seg: 78.0793, loss: 0.6505
2022-11-04 17:00:09,603 - mmseg - INFO - Iter [70700/80000]	lr: 1.730e-05, eta: 0:52:50, time: 0.390, data_time: 0.057, memory: 12960, decode.loss_ce: 0.4111, decode.acc_seg: 83.7731, aux.loss_ce: 0.2407, aux.acc_seg: 78.1033, loss: 0.6518
2022-11-04 17:00:26,413 - mmseg - INFO - Iter [70750/80000]	lr: 1.722e-05, eta: 0:52:33, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4178, decode.acc_seg: 83.7407, aux.loss_ce: 0.2405, aux.acc_seg: 78.1463, loss: 0.6582
2022-11-04 17:00:42,995 - mmseg - INFO - Iter [70800/80000]	lr: 1.713e-05, eta: 0:52:16, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4060, decode.acc_seg: 84.0716, aux.loss_ce: 0.2392, aux.acc_seg: 77.9331, loss: 0.6453
2022-11-04 17:00:59,524 - mmseg - INFO - Iter [70850/80000]	lr: 1.705e-05, eta: 0:51:59, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4287, decode.acc_seg: 82.9391, aux.loss_ce: 0.2454, aux.acc_seg: 77.4402, loss: 0.6741
2022-11-04 17:01:16,235 - mmseg - INFO - Iter [70900/80000]	lr: 1.697e-05, eta: 0:51:42, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4051, decode.acc_seg: 83.7871, aux.loss_ce: 0.2319, aux.acc_seg: 78.5705, loss: 0.6370
2022-11-04 17:01:33,207 - mmseg - INFO - Iter [70950/80000]	lr: 1.688e-05, eta: 0:51:25, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4278, decode.acc_seg: 83.3378, aux.loss_ce: 0.2436, aux.acc_seg: 77.6479, loss: 0.6714
2022-11-04 17:01:49,896 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:01:49,896 - mmseg - INFO - Iter [71000/80000]	lr: 1.680e-05, eta: 0:51:08, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4232, decode.acc_seg: 83.4729, aux.loss_ce: 0.2437, aux.acc_seg: 77.8134, loss: 0.6670
2022-11-04 17:02:06,634 - mmseg - INFO - Iter [71050/80000]	lr: 1.671e-05, eta: 0:50:51, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4005, decode.acc_seg: 84.1021, aux.loss_ce: 0.2391, aux.acc_seg: 77.8409, loss: 0.6395
2022-11-04 17:02:23,347 - mmseg - INFO - Iter [71100/80000]	lr: 1.663e-05, eta: 0:50:34, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4128, decode.acc_seg: 83.7357, aux.loss_ce: 0.2402, aux.acc_seg: 77.8367, loss: 0.6531
2022-11-04 17:02:40,000 - mmseg - INFO - Iter [71150/80000]	lr: 1.655e-05, eta: 0:50:17, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4112, decode.acc_seg: 83.7843, aux.loss_ce: 0.2422, aux.acc_seg: 77.8495, loss: 0.6535
2022-11-04 17:02:56,770 - mmseg - INFO - Iter [71200/80000]	lr: 1.646e-05, eta: 0:49:59, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4208, decode.acc_seg: 83.5700, aux.loss_ce: 0.2434, aux.acc_seg: 77.7381, loss: 0.6641
2022-11-04 17:03:13,640 - mmseg - INFO - Iter [71250/80000]	lr: 1.638e-05, eta: 0:49:42, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4106, decode.acc_seg: 84.0862, aux.loss_ce: 0.2429, aux.acc_seg: 78.2680, loss: 0.6535
2022-11-04 17:03:30,436 - mmseg - INFO - Iter [71300/80000]	lr: 1.629e-05, eta: 0:49:25, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4222, decode.acc_seg: 83.0988, aux.loss_ce: 0.2379, aux.acc_seg: 77.9619, loss: 0.6600
2022-11-04 17:03:50,182 - mmseg - INFO - Iter [71350/80000]	lr: 1.621e-05, eta: 0:49:09, time: 0.395, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4110, decode.acc_seg: 83.6874, aux.loss_ce: 0.2441, aux.acc_seg: 77.6410, loss: 0.6551
2022-11-04 17:04:06,985 - mmseg - INFO - Iter [71400/80000]	lr: 1.612e-05, eta: 0:48:52, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4142, decode.acc_seg: 83.5564, aux.loss_ce: 0.2358, aux.acc_seg: 78.3444, loss: 0.6500
2022-11-04 17:04:23,731 - mmseg - INFO - Iter [71450/80000]	lr: 1.604e-05, eta: 0:48:34, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3954, decode.acc_seg: 84.0544, aux.loss_ce: 0.2323, aux.acc_seg: 78.3951, loss: 0.6277
2022-11-04 17:04:40,340 - mmseg - INFO - Iter [71500/80000]	lr: 1.596e-05, eta: 0:48:17, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4266, decode.acc_seg: 83.2100, aux.loss_ce: 0.2474, aux.acc_seg: 77.2890, loss: 0.6740
2022-11-04 17:04:57,250 - mmseg - INFO - Iter [71550/80000]	lr: 1.587e-05, eta: 0:48:00, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4203, decode.acc_seg: 83.6129, aux.loss_ce: 0.2429, aux.acc_seg: 77.9388, loss: 0.6632
2022-11-04 17:05:14,085 - mmseg - INFO - Iter [71600/80000]	lr: 1.579e-05, eta: 0:47:43, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4201, decode.acc_seg: 83.7204, aux.loss_ce: 0.2422, aux.acc_seg: 78.1291, loss: 0.6623
2022-11-04 17:05:30,886 - mmseg - INFO - Iter [71650/80000]	lr: 1.570e-05, eta: 0:47:26, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4274, decode.acc_seg: 83.2443, aux.loss_ce: 0.2503, aux.acc_seg: 77.5669, loss: 0.6778
2022-11-04 17:05:47,544 - mmseg - INFO - Iter [71700/80000]	lr: 1.562e-05, eta: 0:47:09, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4070, decode.acc_seg: 83.8805, aux.loss_ce: 0.2402, aux.acc_seg: 77.7159, loss: 0.6472
2022-11-04 17:06:04,250 - mmseg - INFO - Iter [71750/80000]	lr: 1.553e-05, eta: 0:46:52, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4235, decode.acc_seg: 83.4048, aux.loss_ce: 0.2497, aux.acc_seg: 77.5667, loss: 0.6731
2022-11-04 17:06:20,953 - mmseg - INFO - Iter [71800/80000]	lr: 1.545e-05, eta: 0:46:35, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4076, decode.acc_seg: 83.9067, aux.loss_ce: 0.2334, aux.acc_seg: 78.6503, loss: 0.6410
2022-11-04 17:06:37,839 - mmseg - INFO - Iter [71850/80000]	lr: 1.536e-05, eta: 0:46:18, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4056, decode.acc_seg: 83.8333, aux.loss_ce: 0.2340, aux.acc_seg: 78.6913, loss: 0.6396
2022-11-04 17:06:54,652 - mmseg - INFO - Iter [71900/80000]	lr: 1.528e-05, eta: 0:46:01, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4092, decode.acc_seg: 83.7997, aux.loss_ce: 0.2378, aux.acc_seg: 77.8546, loss: 0.6470
2022-11-04 17:07:14,142 - mmseg - INFO - Iter [71950/80000]	lr: 1.519e-05, eta: 0:45:44, time: 0.390, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4051, decode.acc_seg: 83.8843, aux.loss_ce: 0.2320, aux.acc_seg: 78.6041, loss: 0.6371
2022-11-04 17:07:30,969 - mmseg - INFO - Saving checkpoint at 72000 iterations
2022-11-04 17:07:31,207 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:07:31,207 - mmseg - INFO - Iter [72000/80000]	lr: 1.511e-05, eta: 0:45:27, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4174, decode.acc_seg: 83.7495, aux.loss_ce: 0.2455, aux.acc_seg: 77.9256, loss: 0.6629
2022-11-04 17:07:40,330 - mmseg - INFO - per class results:
2022-11-04 17:07:40,337 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 66.69 | 83.72 |
|       building      | 75.67 | 88.87 |
|         sky         | 88.83 | 93.16 |
|        floor        |  71.1 | 85.45 |
|         tree        | 68.24 | 84.69 |
|       ceiling       | 75.82 | 83.91 |
|         road        | 75.12 | 85.25 |
|         bed         | 76.48 | 90.68 |
|      windowpane     | 49.83 | 67.12 |
|        grass        | 64.13 |  81.5 |
|       cabinet       | 48.34 | 63.16 |
|       sidewalk      | 53.02 | 70.46 |
|        person       | 64.56 | 82.35 |
|        earth        | 28.06 | 39.84 |
|         door        | 26.95 | 40.65 |
|        table        | 40.31 | 56.01 |
|       mountain      | 51.43 | 69.11 |
|        plant        | 46.13 | 60.11 |
|       curtain       | 55.76 | 72.24 |
|        chair        | 37.37 | 51.92 |
|         car         | 71.38 | 85.79 |
|        water        | 46.55 | 67.25 |
|       painting      | 54.61 | 73.58 |
|         sofa        | 46.47 | 68.39 |
|        shelf        | 32.88 | 49.03 |
|        house        | 43.52 | 64.29 |
|         sea         | 35.77 | 53.08 |
|        mirror       | 40.71 | 48.32 |
|         rug         | 48.31 |  59.1 |
|        field        | 31.07 | 47.33 |
|       armchair      | 25.55 | 40.18 |
|         seat        | 50.96 | 70.65 |
|        fence        | 29.23 | 44.88 |
|         desk        | 31.08 | 50.42 |
|         rock        | 38.23 | 64.54 |
|       wardrobe      | 37.57 | 53.77 |
|         lamp        |  37.8 | 50.61 |
|       bathtub       | 55.05 | 67.89 |
|       railing       | 24.92 | 37.25 |
|       cushion       | 32.26 | 41.87 |
|         base        |  18.5 | 22.68 |
|         box         | 17.29 | 25.17 |
|        column       | 32.49 |  41.4 |
|      signboard      |  24.4 |  35.0 |
|   chest of drawers  | 27.17 | 45.13 |
|       counter       | 25.14 | 29.86 |
|         sand        | 26.63 | 40.13 |
|         sink        | 47.16 | 59.16 |
|      skyscraper     | 63.26 | 81.82 |
|      fireplace      | 60.63 | 81.43 |
|     refrigerator    |  51.8 | 65.73 |
|      grandstand     | 41.72 | 63.53 |
|         path        | 18.57 |  26.5 |
|        stairs       | 24.96 | 31.61 |
|        runway       | 70.09 | 84.35 |
|         case        | 33.81 |  49.3 |
|      pool table     | 80.58 | 89.36 |
|        pillow       | 37.67 | 48.22 |
|     screen door     | 43.82 | 52.81 |
|       stairway      |  25.5 | 32.78 |
|        river        | 13.03 |  18.7 |
|        bridge       | 47.34 | 68.34 |
|       bookcase      | 27.36 | 42.99 |
|        blind        | 26.04 | 30.99 |
|     coffee table    | 38.29 | 71.41 |
|        toilet       |  67.6 | 80.96 |
|        flower       | 25.26 | 37.74 |
|         book        | 36.11 | 52.72 |
|         hill        |  4.5  |  6.5  |
|        bench        | 31.99 | 41.69 |
|      countertop     | 39.54 | 52.38 |
|        stove        | 50.73 | 62.64 |
|         palm        | 37.36 | 54.34 |
|    kitchen island   | 17.63 | 44.95 |
|       computer      | 43.75 | 58.62 |
|     swivel chair    | 26.78 | 31.88 |
|         boat        | 45.61 | 57.82 |
|         bar         | 24.17 | 30.05 |
|    arcade machine   | 30.65 | 35.15 |
|        hovel        | 31.39 | 37.37 |
|         bus         | 71.35 | 87.75 |
|        towel        | 37.29 | 48.09 |
|        light        |  17.4 | 19.37 |
|        truck        |  5.69 |  7.73 |
|        tower        |  33.3 | 40.19 |
|      chandelier     | 46.77 | 60.98 |
|        awning       | 16.12 | 17.81 |
|     streetlight     |  5.97 |  6.81 |
|        booth        | 28.49 | 31.51 |
| television receiver | 38.61 | 63.15 |
|       airplane      | 43.23 | 52.68 |
|      dirt track     | 11.26 | 15.78 |
|       apparel       | 19.86 | 27.72 |
|         pole        |  7.27 |  10.8 |
|         land        |  0.07 |  0.09 |
|      bannister      |  1.71 |  2.16 |
|      escalator      | 25.56 |  26.3 |
|       ottoman       |  23.5 |  26.1 |
|        bottle       | 18.42 | 40.38 |
|        buffet       | 38.16 | 48.55 |
|        poster       | 24.41 | 28.71 |
|        stage        | 11.78 | 15.64 |
|         van         | 14.41 | 16.54 |
|         ship        |  3.81 |  4.17 |
|       fountain      |  12.9 |  13.3 |
|    conveyer belt    | 52.89 | 60.28 |
|        canopy       | 15.16 | 18.39 |
|        washer       | 59.27 |  61.5 |
|      plaything      |  5.66 |  8.73 |
|    swimming pool    | 32.43 | 52.09 |
|        stool        | 15.41 | 17.53 |
|        barrel       | 37.27 | 61.38 |
|        basket       | 12.74 |  16.0 |
|      waterfall      | 37.22 | 45.83 |
|         tent        | 86.05 | 96.87 |
|         bag         |  3.78 |  4.28 |
|       minibike      | 45.96 | 52.74 |
|        cradle       | 56.92 | 78.69 |
|         oven        | 17.75 | 29.76 |
|         ball        | 18.67 | 20.48 |
|         food        | 37.35 | 45.34 |
|         step        |  2.15 |  2.28 |
|         tank        | 33.45 | 41.41 |
|      trade name     | 15.75 | 17.48 |
|      microwave      | 26.18 | 30.21 |
|         pot         | 20.66 |  24.7 |
|        animal       |  42.8 | 48.99 |
|       bicycle       | 35.85 | 56.28 |
|         lake        |  0.0  |  0.0  |
|      dishwasher     | 29.87 | 42.07 |
|        screen       | 52.89 | 74.74 |
|       blanket       |  2.09 |  2.34 |
|      sculpture      | 35.76 |  50.6 |
|         hood        | 36.67 | 45.24 |
|        sconce       | 13.71 | 15.21 |
|         vase        | 14.78 |  20.0 |
|    traffic light    |  9.75 | 12.94 |
|         tray        |  2.71 |  4.89 |
|        ashcan       |  21.2 | 27.04 |
|         fan         | 26.45 | 32.15 |
|         pier        | 40.02 | 58.81 |
|      crt screen     |  0.48 |  0.81 |
|        plate        | 27.19 | 32.44 |
|       monitor       | 15.79 | 17.29 |
|    bulletin board   | 28.16 | 38.44 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 34.25 | 40.54 |
|        glass        |  0.58 |  0.59 |
|        clock        |  9.26 | 10.13 |
|         flag        | 15.15 | 16.76 |
+---------------------+-------+-------+
2022-11-04 17:07:40,337 - mmseg - INFO - Summary:
2022-11-04 17:07:40,337 - mmseg - INFO - 
+-------+------+-------+
|  aAcc | mIoU |  mAcc |
+-------+------+-------+
| 75.45 | 34.0 | 44.39 |
+-------+------+-------+
2022-11-04 17:07:40,339 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:07:40,339 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7545, mIoU: 0.3400, mAcc: 0.4439, IoU.wall: 0.6669, IoU.building: 0.7567, IoU.sky: 0.8883, IoU.floor: 0.7110, IoU.tree: 0.6824, IoU.ceiling: 0.7582, IoU.road: 0.7512, IoU.bed : 0.7648, IoU.windowpane: 0.4983, IoU.grass: 0.6413, IoU.cabinet: 0.4834, IoU.sidewalk: 0.5302, IoU.person: 0.6456, IoU.earth: 0.2806, IoU.door: 0.2695, IoU.table: 0.4031, IoU.mountain: 0.5143, IoU.plant: 0.4613, IoU.curtain: 0.5576, IoU.chair: 0.3737, IoU.car: 0.7138, IoU.water: 0.4655, IoU.painting: 0.5461, IoU.sofa: 0.4647, IoU.shelf: 0.3288, IoU.house: 0.4352, IoU.sea: 0.3577, IoU.mirror: 0.4071, IoU.rug: 0.4831, IoU.field: 0.3107, IoU.armchair: 0.2555, IoU.seat: 0.5096, IoU.fence: 0.2923, IoU.desk: 0.3108, IoU.rock: 0.3823, IoU.wardrobe: 0.3757, IoU.lamp: 0.3780, IoU.bathtub: 0.5505, IoU.railing: 0.2492, IoU.cushion: 0.3226, IoU.base: 0.1850, IoU.box: 0.1729, IoU.column: 0.3249, IoU.signboard: 0.2440, IoU.chest of drawers: 0.2717, IoU.counter: 0.2514, IoU.sand: 0.2663, IoU.sink: 0.4716, IoU.skyscraper: 0.6326, IoU.fireplace: 0.6063, IoU.refrigerator: 0.5180, IoU.grandstand: 0.4172, IoU.path: 0.1857, IoU.stairs: 0.2496, IoU.runway: 0.7009, IoU.case: 0.3381, IoU.pool table: 0.8058, IoU.pillow: 0.3767, IoU.screen door: 0.4382, IoU.stairway: 0.2550, IoU.river: 0.1303, IoU.bridge: 0.4734, IoU.bookcase: 0.2736, IoU.blind: 0.2604, IoU.coffee table: 0.3829, IoU.toilet: 0.6760, IoU.flower: 0.2526, IoU.book: 0.3611, IoU.hill: 0.0450, IoU.bench: 0.3199, IoU.countertop: 0.3954, IoU.stove: 0.5073, IoU.palm: 0.3736, IoU.kitchen island: 0.1763, IoU.computer: 0.4375, IoU.swivel chair: 0.2678, IoU.boat: 0.4561, IoU.bar: 0.2417, IoU.arcade machine: 0.3065, IoU.hovel: 0.3139, IoU.bus: 0.7135, IoU.towel: 0.3729, IoU.light: 0.1740, IoU.truck: 0.0569, IoU.tower: 0.3330, IoU.chandelier: 0.4677, IoU.awning: 0.1612, IoU.streetlight: 0.0597, IoU.booth: 0.2849, IoU.television receiver: 0.3861, IoU.airplane: 0.4323, IoU.dirt track: 0.1126, IoU.apparel: 0.1986, IoU.pole: 0.0727, IoU.land: 0.0007, IoU.bannister: 0.0171, IoU.escalator: 0.2556, IoU.ottoman: 0.2350, IoU.bottle: 0.1842, IoU.buffet: 0.3816, IoU.poster: 0.2441, IoU.stage: 0.1178, IoU.van: 0.1441, IoU.ship: 0.0381, IoU.fountain: 0.1290, IoU.conveyer belt: 0.5289, IoU.canopy: 0.1516, IoU.washer: 0.5927, IoU.plaything: 0.0566, IoU.swimming pool: 0.3243, IoU.stool: 0.1541, IoU.barrel: 0.3727, IoU.basket: 0.1274, IoU.waterfall: 0.3722, IoU.tent: 0.8605, IoU.bag: 0.0378, IoU.minibike: 0.4596, IoU.cradle: 0.5692, IoU.oven: 0.1775, IoU.ball: 0.1867, IoU.food: 0.3735, IoU.step: 0.0215, IoU.tank: 0.3345, IoU.trade name: 0.1575, IoU.microwave: 0.2618, IoU.pot: 0.2066, IoU.animal: 0.4280, IoU.bicycle: 0.3585, IoU.lake: 0.0000, IoU.dishwasher: 0.2987, IoU.screen: 0.5289, IoU.blanket: 0.0209, IoU.sculpture: 0.3576, IoU.hood: 0.3667, IoU.sconce: 0.1371, IoU.vase: 0.1478, IoU.traffic light: 0.0975, IoU.tray: 0.0271, IoU.ashcan: 0.2120, IoU.fan: 0.2645, IoU.pier: 0.4002, IoU.crt screen: 0.0048, IoU.plate: 0.2719, IoU.monitor: 0.1579, IoU.bulletin board: 0.2816, IoU.shower: 0.0000, IoU.radiator: 0.3425, IoU.glass: 0.0058, IoU.clock: 0.0926, IoU.flag: 0.1515, Acc.wall: 0.8372, Acc.building: 0.8887, Acc.sky: 0.9316, Acc.floor: 0.8545, Acc.tree: 0.8469, Acc.ceiling: 0.8391, Acc.road: 0.8525, Acc.bed : 0.9068, Acc.windowpane: 0.6712, Acc.grass: 0.8150, Acc.cabinet: 0.6316, Acc.sidewalk: 0.7046, Acc.person: 0.8235, Acc.earth: 0.3984, Acc.door: 0.4065, Acc.table: 0.5601, Acc.mountain: 0.6911, Acc.plant: 0.6011, Acc.curtain: 0.7224, Acc.chair: 0.5192, Acc.car: 0.8579, Acc.water: 0.6725, Acc.painting: 0.7358, Acc.sofa: 0.6839, Acc.shelf: 0.4903, Acc.house: 0.6429, Acc.sea: 0.5308, Acc.mirror: 0.4832, Acc.rug: 0.5910, Acc.field: 0.4733, Acc.armchair: 0.4018, Acc.seat: 0.7065, Acc.fence: 0.4488, Acc.desk: 0.5042, Acc.rock: 0.6454, Acc.wardrobe: 0.5377, Acc.lamp: 0.5061, Acc.bathtub: 0.6789, Acc.railing: 0.3725, Acc.cushion: 0.4187, Acc.base: 0.2268, Acc.box: 0.2517, Acc.column: 0.4140, Acc.signboard: 0.3500, Acc.chest of drawers: 0.4513, Acc.counter: 0.2986, Acc.sand: 0.4013, Acc.sink: 0.5916, Acc.skyscraper: 0.8182, Acc.fireplace: 0.8143, Acc.refrigerator: 0.6573, Acc.grandstand: 0.6353, Acc.path: 0.2650, Acc.stairs: 0.3161, Acc.runway: 0.8435, Acc.case: 0.4930, Acc.pool table: 0.8936, Acc.pillow: 0.4822, Acc.screen door: 0.5281, Acc.stairway: 0.3278, Acc.river: 0.1870, Acc.bridge: 0.6834, Acc.bookcase: 0.4299, Acc.blind: 0.3099, Acc.coffee table: 0.7141, Acc.toilet: 0.8096, Acc.flower: 0.3774, Acc.book: 0.5272, Acc.hill: 0.0650, Acc.bench: 0.4169, Acc.countertop: 0.5238, Acc.stove: 0.6264, Acc.palm: 0.5434, Acc.kitchen island: 0.4495, Acc.computer: 0.5862, Acc.swivel chair: 0.3188, Acc.boat: 0.5782, Acc.bar: 0.3005, Acc.arcade machine: 0.3515, Acc.hovel: 0.3737, Acc.bus: 0.8775, Acc.towel: 0.4809, Acc.light: 0.1937, Acc.truck: 0.0773, Acc.tower: 0.4019, Acc.chandelier: 0.6098, Acc.awning: 0.1781, Acc.streetlight: 0.0681, Acc.booth: 0.3151, Acc.television receiver: 0.6315, Acc.airplane: 0.5268, Acc.dirt track: 0.1578, Acc.apparel: 0.2772, Acc.pole: 0.1080, Acc.land: 0.0009, Acc.bannister: 0.0216, Acc.escalator: 0.2630, Acc.ottoman: 0.2610, Acc.bottle: 0.4038, Acc.buffet: 0.4855, Acc.poster: 0.2871, Acc.stage: 0.1564, Acc.van: 0.1654, Acc.ship: 0.0417, Acc.fountain: 0.1330, Acc.conveyer belt: 0.6028, Acc.canopy: 0.1839, Acc.washer: 0.6150, Acc.plaything: 0.0873, Acc.swimming pool: 0.5209, Acc.stool: 0.1753, Acc.barrel: 0.6138, Acc.basket: 0.1600, Acc.waterfall: 0.4583, Acc.tent: 0.9687, Acc.bag: 0.0428, Acc.minibike: 0.5274, Acc.cradle: 0.7869, Acc.oven: 0.2976, Acc.ball: 0.2048, Acc.food: 0.4534, Acc.step: 0.0228, Acc.tank: 0.4141, Acc.trade name: 0.1748, Acc.microwave: 0.3021, Acc.pot: 0.2470, Acc.animal: 0.4899, Acc.bicycle: 0.5628, Acc.lake: 0.0000, Acc.dishwasher: 0.4207, Acc.screen: 0.7474, Acc.blanket: 0.0234, Acc.sculpture: 0.5060, Acc.hood: 0.4524, Acc.sconce: 0.1521, Acc.vase: 0.2000, Acc.traffic light: 0.1294, Acc.tray: 0.0489, Acc.ashcan: 0.2704, Acc.fan: 0.3215, Acc.pier: 0.5881, Acc.crt screen: 0.0081, Acc.plate: 0.3244, Acc.monitor: 0.1729, Acc.bulletin board: 0.3844, Acc.shower: 0.0000, Acc.radiator: 0.4054, Acc.glass: 0.0059, Acc.clock: 0.1013, Acc.flag: 0.1676
2022-11-04 17:07:57,142 - mmseg - INFO - Iter [72050/80000]	lr: 1.502e-05, eta: 0:45:11, time: 0.519, data_time: 0.191, memory: 12960, decode.loss_ce: 0.4019, decode.acc_seg: 84.1288, aux.loss_ce: 0.2407, aux.acc_seg: 77.9983, loss: 0.6425
2022-11-04 17:08:13,877 - mmseg - INFO - Iter [72100/80000]	lr: 1.494e-05, eta: 0:44:54, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4339, decode.acc_seg: 83.0861, aux.loss_ce: 0.2508, aux.acc_seg: 77.2961, loss: 0.6848
2022-11-04 17:08:30,526 - mmseg - INFO - Iter [72150/80000]	lr: 1.485e-05, eta: 0:44:37, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4151, decode.acc_seg: 83.6035, aux.loss_ce: 0.2415, aux.acc_seg: 77.8728, loss: 0.6566
2022-11-04 17:08:47,473 - mmseg - INFO - Iter [72200/80000]	lr: 1.477e-05, eta: 0:44:20, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4250, decode.acc_seg: 83.2503, aux.loss_ce: 0.2457, aux.acc_seg: 77.7534, loss: 0.6707
2022-11-04 17:09:04,248 - mmseg - INFO - Iter [72250/80000]	lr: 1.468e-05, eta: 0:44:03, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4116, decode.acc_seg: 83.6745, aux.loss_ce: 0.2376, aux.acc_seg: 78.1825, loss: 0.6492
2022-11-04 17:09:21,029 - mmseg - INFO - Iter [72300/80000]	lr: 1.460e-05, eta: 0:43:45, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4265, decode.acc_seg: 83.1938, aux.loss_ce: 0.2485, aux.acc_seg: 77.4740, loss: 0.6751
2022-11-04 17:09:37,752 - mmseg - INFO - Iter [72350/80000]	lr: 1.451e-05, eta: 0:43:28, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4078, decode.acc_seg: 84.0320, aux.loss_ce: 0.2387, aux.acc_seg: 78.2916, loss: 0.6465
2022-11-04 17:09:54,361 - mmseg - INFO - Iter [72400/80000]	lr: 1.443e-05, eta: 0:43:11, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4181, decode.acc_seg: 83.8718, aux.loss_ce: 0.2469, aux.acc_seg: 77.5616, loss: 0.6651
2022-11-04 17:10:10,833 - mmseg - INFO - Iter [72450/80000]	lr: 1.434e-05, eta: 0:42:54, time: 0.329, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4088, decode.acc_seg: 83.7732, aux.loss_ce: 0.2376, aux.acc_seg: 78.3663, loss: 0.6464
2022-11-04 17:10:27,768 - mmseg - INFO - Iter [72500/80000]	lr: 1.426e-05, eta: 0:42:37, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4129, decode.acc_seg: 83.9775, aux.loss_ce: 0.2385, aux.acc_seg: 78.4082, loss: 0.6513
2022-11-04 17:10:44,540 - mmseg - INFO - Iter [72550/80000]	lr: 1.417e-05, eta: 0:42:20, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4077, decode.acc_seg: 83.8791, aux.loss_ce: 0.2362, aux.acc_seg: 78.1822, loss: 0.6439
2022-11-04 17:11:04,186 - mmseg - INFO - Iter [72600/80000]	lr: 1.409e-05, eta: 0:42:03, time: 0.393, data_time: 0.060, memory: 12960, decode.loss_ce: 0.4111, decode.acc_seg: 83.9485, aux.loss_ce: 0.2395, aux.acc_seg: 78.2613, loss: 0.6506
2022-11-04 17:11:21,138 - mmseg - INFO - Iter [72650/80000]	lr: 1.400e-05, eta: 0:41:46, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4069, decode.acc_seg: 83.8759, aux.loss_ce: 0.2350, aux.acc_seg: 78.3007, loss: 0.6419
2022-11-04 17:11:37,875 - mmseg - INFO - Iter [72700/80000]	lr: 1.391e-05, eta: 0:41:29, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4193, decode.acc_seg: 83.6626, aux.loss_ce: 0.2448, aux.acc_seg: 77.6767, loss: 0.6641
2022-11-04 17:11:54,649 - mmseg - INFO - Iter [72750/80000]	lr: 1.383e-05, eta: 0:41:12, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4053, decode.acc_seg: 84.1051, aux.loss_ce: 0.2392, aux.acc_seg: 78.2556, loss: 0.6445
2022-11-04 17:12:11,471 - mmseg - INFO - Iter [72800/80000]	lr: 1.374e-05, eta: 0:40:55, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4073, decode.acc_seg: 84.0846, aux.loss_ce: 0.2391, aux.acc_seg: 78.4401, loss: 0.6463
2022-11-04 17:12:28,259 - mmseg - INFO - Iter [72850/80000]	lr: 1.366e-05, eta: 0:40:38, time: 0.336, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4196, decode.acc_seg: 83.5736, aux.loss_ce: 0.2472, aux.acc_seg: 77.4221, loss: 0.6669
2022-11-04 17:12:45,052 - mmseg - INFO - Iter [72900/80000]	lr: 1.357e-05, eta: 0:40:21, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4126, decode.acc_seg: 83.8068, aux.loss_ce: 0.2377, aux.acc_seg: 78.1413, loss: 0.6503
2022-11-04 17:13:01,551 - mmseg - INFO - Iter [72950/80000]	lr: 1.348e-05, eta: 0:40:04, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4106, decode.acc_seg: 83.8484, aux.loss_ce: 0.2394, aux.acc_seg: 78.2436, loss: 0.6500
2022-11-04 17:13:18,320 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:13:18,321 - mmseg - INFO - Iter [73000/80000]	lr: 1.340e-05, eta: 0:39:47, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4254, decode.acc_seg: 83.2914, aux.loss_ce: 0.2407, aux.acc_seg: 77.6369, loss: 0.6661
2022-11-04 17:13:35,067 - mmseg - INFO - Iter [73050/80000]	lr: 1.331e-05, eta: 0:39:29, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4092, decode.acc_seg: 84.0032, aux.loss_ce: 0.2411, aux.acc_seg: 78.2893, loss: 0.6503
2022-11-04 17:13:51,714 - mmseg - INFO - Iter [73100/80000]	lr: 1.323e-05, eta: 0:39:12, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4187, decode.acc_seg: 83.7004, aux.loss_ce: 0.2382, aux.acc_seg: 78.4362, loss: 0.6569
2022-11-04 17:14:08,271 - mmseg - INFO - Iter [73150/80000]	lr: 1.314e-05, eta: 0:38:55, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4231, decode.acc_seg: 83.4252, aux.loss_ce: 0.2426, aux.acc_seg: 78.1895, loss: 0.6657
2022-11-04 17:14:27,651 - mmseg - INFO - Iter [73200/80000]	lr: 1.305e-05, eta: 0:38:38, time: 0.388, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4239, decode.acc_seg: 83.3914, aux.loss_ce: 0.2442, aux.acc_seg: 77.7227, loss: 0.6681
2022-11-04 17:14:44,738 - mmseg - INFO - Iter [73250/80000]	lr: 1.297e-05, eta: 0:38:21, time: 0.342, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4161, decode.acc_seg: 83.5967, aux.loss_ce: 0.2429, aux.acc_seg: 77.5864, loss: 0.6589
2022-11-04 17:15:01,298 - mmseg - INFO - Iter [73300/80000]	lr: 1.288e-05, eta: 0:38:04, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4199, decode.acc_seg: 83.2561, aux.loss_ce: 0.2383, aux.acc_seg: 77.8691, loss: 0.6582
2022-11-04 17:15:18,115 - mmseg - INFO - Iter [73350/80000]	lr: 1.279e-05, eta: 0:37:47, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4225, decode.acc_seg: 83.7164, aux.loss_ce: 0.2449, aux.acc_seg: 77.9828, loss: 0.6674
2022-11-04 17:15:34,879 - mmseg - INFO - Iter [73400/80000]	lr: 1.271e-05, eta: 0:37:30, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4069, decode.acc_seg: 83.8658, aux.loss_ce: 0.2426, aux.acc_seg: 78.0105, loss: 0.6496
2022-11-04 17:15:51,719 - mmseg - INFO - Iter [73450/80000]	lr: 1.262e-05, eta: 0:37:13, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4262, decode.acc_seg: 83.4527, aux.loss_ce: 0.2458, aux.acc_seg: 77.7500, loss: 0.6720
2022-11-04 17:16:08,207 - mmseg - INFO - Iter [73500/80000]	lr: 1.253e-05, eta: 0:36:56, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4249, decode.acc_seg: 83.2972, aux.loss_ce: 0.2441, aux.acc_seg: 77.5682, loss: 0.6690
2022-11-04 17:16:24,845 - mmseg - INFO - Iter [73550/80000]	lr: 1.245e-05, eta: 0:36:39, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4188, decode.acc_seg: 83.5635, aux.loss_ce: 0.2454, aux.acc_seg: 77.8051, loss: 0.6642
2022-11-04 17:16:41,716 - mmseg - INFO - Iter [73600/80000]	lr: 1.236e-05, eta: 0:36:22, time: 0.337, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4145, decode.acc_seg: 83.4392, aux.loss_ce: 0.2408, aux.acc_seg: 77.8838, loss: 0.6553
2022-11-04 17:16:58,427 - mmseg - INFO - Iter [73650/80000]	lr: 1.227e-05, eta: 0:36:05, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4077, decode.acc_seg: 83.9253, aux.loss_ce: 0.2405, aux.acc_seg: 77.9175, loss: 0.6481
2022-11-04 17:17:15,188 - mmseg - INFO - Iter [73700/80000]	lr: 1.219e-05, eta: 0:35:48, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3935, decode.acc_seg: 84.3944, aux.loss_ce: 0.2241, aux.acc_seg: 79.2948, loss: 0.6176
2022-11-04 17:17:32,052 - mmseg - INFO - Iter [73750/80000]	lr: 1.210e-05, eta: 0:35:31, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4075, decode.acc_seg: 83.5975, aux.loss_ce: 0.2332, aux.acc_seg: 78.2713, loss: 0.6407
2022-11-04 17:17:48,728 - mmseg - INFO - Iter [73800/80000]	lr: 1.201e-05, eta: 0:35:14, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4156, decode.acc_seg: 83.8123, aux.loss_ce: 0.2437, aux.acc_seg: 77.8688, loss: 0.6594
2022-11-04 17:18:08,362 - mmseg - INFO - Iter [73850/80000]	lr: 1.192e-05, eta: 0:34:57, time: 0.393, data_time: 0.061, memory: 12960, decode.loss_ce: 0.4104, decode.acc_seg: 83.8515, aux.loss_ce: 0.2333, aux.acc_seg: 78.7299, loss: 0.6437
2022-11-04 17:18:25,113 - mmseg - INFO - Iter [73900/80000]	lr: 1.184e-05, eta: 0:34:40, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4092, decode.acc_seg: 83.4361, aux.loss_ce: 0.2401, aux.acc_seg: 77.9500, loss: 0.6493
2022-11-04 17:18:41,881 - mmseg - INFO - Iter [73950/80000]	lr: 1.175e-05, eta: 0:34:23, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4357, decode.acc_seg: 83.1753, aux.loss_ce: 0.2539, aux.acc_seg: 77.1602, loss: 0.6897
2022-11-04 17:18:58,546 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:18:58,547 - mmseg - INFO - Iter [74000/80000]	lr: 1.166e-05, eta: 0:34:06, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4092, decode.acc_seg: 83.7582, aux.loss_ce: 0.2365, aux.acc_seg: 78.3846, loss: 0.6458
2022-11-04 17:19:15,166 - mmseg - INFO - Iter [74050/80000]	lr: 1.158e-05, eta: 0:33:48, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3997, decode.acc_seg: 84.0330, aux.loss_ce: 0.2266, aux.acc_seg: 78.9725, loss: 0.6263
2022-11-04 17:19:31,962 - mmseg - INFO - Iter [74100/80000]	lr: 1.149e-05, eta: 0:33:31, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4138, decode.acc_seg: 83.8133, aux.loss_ce: 0.2439, aux.acc_seg: 77.8389, loss: 0.6577
2022-11-04 17:19:48,870 - mmseg - INFO - Iter [74150/80000]	lr: 1.140e-05, eta: 0:33:14, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4089, decode.acc_seg: 83.8519, aux.loss_ce: 0.2419, aux.acc_seg: 77.9041, loss: 0.6508
2022-11-04 17:20:05,503 - mmseg - INFO - Iter [74200/80000]	lr: 1.131e-05, eta: 0:32:57, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4093, decode.acc_seg: 84.1906, aux.loss_ce: 0.2351, aux.acc_seg: 78.6224, loss: 0.6444
2022-11-04 17:20:22,240 - mmseg - INFO - Iter [74250/80000]	lr: 1.122e-05, eta: 0:32:40, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4350, decode.acc_seg: 82.7218, aux.loss_ce: 0.2496, aux.acc_seg: 76.8893, loss: 0.6846
2022-11-04 17:20:39,039 - mmseg - INFO - Iter [74300/80000]	lr: 1.114e-05, eta: 0:32:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4148, decode.acc_seg: 83.7288, aux.loss_ce: 0.2409, aux.acc_seg: 78.1055, loss: 0.6557
2022-11-04 17:20:55,930 - mmseg - INFO - Iter [74350/80000]	lr: 1.105e-05, eta: 0:32:06, time: 0.338, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4168, decode.acc_seg: 83.4947, aux.loss_ce: 0.2425, aux.acc_seg: 77.7771, loss: 0.6594
2022-11-04 17:21:12,640 - mmseg - INFO - Iter [74400/80000]	lr: 1.096e-05, eta: 0:31:49, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3973, decode.acc_seg: 84.3780, aux.loss_ce: 0.2320, aux.acc_seg: 78.7522, loss: 0.6293
2022-11-04 17:21:29,430 - mmseg - INFO - Iter [74450/80000]	lr: 1.087e-05, eta: 0:31:32, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4083, decode.acc_seg: 83.5971, aux.loss_ce: 0.2422, aux.acc_seg: 77.8477, loss: 0.6505
2022-11-04 17:21:49,032 - mmseg - INFO - Iter [74500/80000]	lr: 1.078e-05, eta: 0:31:15, time: 0.392, data_time: 0.068, memory: 12960, decode.loss_ce: 0.4051, decode.acc_seg: 83.9402, aux.loss_ce: 0.2320, aux.acc_seg: 78.4649, loss: 0.6371
2022-11-04 17:22:05,851 - mmseg - INFO - Iter [74550/80000]	lr: 1.070e-05, eta: 0:30:58, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4241, decode.acc_seg: 83.3590, aux.loss_ce: 0.2474, aux.acc_seg: 77.4975, loss: 0.6716
2022-11-04 17:22:22,390 - mmseg - INFO - Iter [74600/80000]	lr: 1.061e-05, eta: 0:30:41, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4045, decode.acc_seg: 83.9976, aux.loss_ce: 0.2374, aux.acc_seg: 78.2542, loss: 0.6419
2022-11-04 17:22:39,229 - mmseg - INFO - Iter [74650/80000]	lr: 1.052e-05, eta: 0:30:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4174, decode.acc_seg: 83.8597, aux.loss_ce: 0.2433, aux.acc_seg: 78.3902, loss: 0.6607
2022-11-04 17:22:55,997 - mmseg - INFO - Iter [74700/80000]	lr: 1.043e-05, eta: 0:30:07, time: 0.335, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4200, decode.acc_seg: 83.4551, aux.loss_ce: 0.2450, aux.acc_seg: 77.6069, loss: 0.6650
2022-11-04 17:23:12,655 - mmseg - INFO - Iter [74750/80000]	lr: 1.034e-05, eta: 0:29:50, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4139, decode.acc_seg: 83.5811, aux.loss_ce: 0.2405, aux.acc_seg: 77.6165, loss: 0.6544
2022-11-04 17:23:29,303 - mmseg - INFO - Iter [74800/80000]	lr: 1.025e-05, eta: 0:29:33, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4060, decode.acc_seg: 83.7710, aux.loss_ce: 0.2354, aux.acc_seg: 78.4510, loss: 0.6414
2022-11-04 17:23:46,087 - mmseg - INFO - Iter [74850/80000]	lr: 1.016e-05, eta: 0:29:15, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3995, decode.acc_seg: 84.1807, aux.loss_ce: 0.2317, aux.acc_seg: 78.5562, loss: 0.6312
2022-11-04 17:24:02,877 - mmseg - INFO - Iter [74900/80000]	lr: 1.008e-05, eta: 0:28:58, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4216, decode.acc_seg: 82.9573, aux.loss_ce: 0.2422, aux.acc_seg: 77.5166, loss: 0.6638
2022-11-04 17:24:19,836 - mmseg - INFO - Iter [74950/80000]	lr: 9.987e-06, eta: 0:28:41, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4121, decode.acc_seg: 83.8668, aux.loss_ce: 0.2399, aux.acc_seg: 78.4057, loss: 0.6521
2022-11-04 17:24:36,687 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:24:36,687 - mmseg - INFO - Iter [75000/80000]	lr: 9.898e-06, eta: 0:28:24, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3982, decode.acc_seg: 84.3022, aux.loss_ce: 0.2338, aux.acc_seg: 78.6291, loss: 0.6321
2022-11-04 17:24:53,639 - mmseg - INFO - Iter [75050/80000]	lr: 9.809e-06, eta: 0:28:07, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4133, decode.acc_seg: 83.4418, aux.loss_ce: 0.2395, aux.acc_seg: 77.7482, loss: 0.6528
2022-11-04 17:25:13,162 - mmseg - INFO - Iter [75100/80000]	lr: 9.720e-06, eta: 0:27:50, time: 0.390, data_time: 0.057, memory: 12960, decode.loss_ce: 0.4016, decode.acc_seg: 84.0746, aux.loss_ce: 0.2339, aux.acc_seg: 78.4381, loss: 0.6355
2022-11-04 17:25:29,810 - mmseg - INFO - Iter [75150/80000]	lr: 9.630e-06, eta: 0:27:33, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4151, decode.acc_seg: 83.5798, aux.loss_ce: 0.2420, aux.acc_seg: 77.9284, loss: 0.6572
2022-11-04 17:25:46,582 - mmseg - INFO - Iter [75200/80000]	lr: 9.541e-06, eta: 0:27:16, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4175, decode.acc_seg: 83.7510, aux.loss_ce: 0.2413, aux.acc_seg: 78.2320, loss: 0.6588
2022-11-04 17:26:03,127 - mmseg - INFO - Iter [75250/80000]	lr: 9.452e-06, eta: 0:26:59, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4108, decode.acc_seg: 83.6168, aux.loss_ce: 0.2402, aux.acc_seg: 77.6448, loss: 0.6510
2022-11-04 17:26:19,857 - mmseg - INFO - Iter [75300/80000]	lr: 9.362e-06, eta: 0:26:42, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4167, decode.acc_seg: 83.8306, aux.loss_ce: 0.2460, aux.acc_seg: 77.4745, loss: 0.6627
2022-11-04 17:26:36,472 - mmseg - INFO - Iter [75350/80000]	lr: 9.272e-06, eta: 0:26:25, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4220, decode.acc_seg: 83.5636, aux.loss_ce: 0.2414, aux.acc_seg: 77.9794, loss: 0.6634
2022-11-04 17:26:53,284 - mmseg - INFO - Iter [75400/80000]	lr: 9.183e-06, eta: 0:26:08, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4110, decode.acc_seg: 83.5100, aux.loss_ce: 0.2430, aux.acc_seg: 77.5320, loss: 0.6540
2022-11-04 17:27:09,899 - mmseg - INFO - Iter [75450/80000]	lr: 9.093e-06, eta: 0:25:51, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4047, decode.acc_seg: 83.6928, aux.loss_ce: 0.2338, aux.acc_seg: 78.0214, loss: 0.6385
2022-11-04 17:27:26,655 - mmseg - INFO - Iter [75500/80000]	lr: 9.003e-06, eta: 0:25:34, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4161, decode.acc_seg: 83.6734, aux.loss_ce: 0.2449, aux.acc_seg: 77.8080, loss: 0.6609
2022-11-04 17:27:43,405 - mmseg - INFO - Iter [75550/80000]	lr: 8.913e-06, eta: 0:25:17, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4073, decode.acc_seg: 83.8566, aux.loss_ce: 0.2375, aux.acc_seg: 78.1346, loss: 0.6448
2022-11-04 17:27:59,901 - mmseg - INFO - Iter [75600/80000]	lr: 8.823e-06, eta: 0:25:00, time: 0.330, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4245, decode.acc_seg: 83.2669, aux.loss_ce: 0.2504, aux.acc_seg: 77.3665, loss: 0.6749
2022-11-04 17:28:16,757 - mmseg - INFO - Iter [75650/80000]	lr: 8.732e-06, eta: 0:24:43, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4123, decode.acc_seg: 83.9276, aux.loss_ce: 0.2385, aux.acc_seg: 78.3375, loss: 0.6508
2022-11-04 17:28:33,498 - mmseg - INFO - Iter [75700/80000]	lr: 8.642e-06, eta: 0:24:26, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4031, decode.acc_seg: 84.1016, aux.loss_ce: 0.2322, aux.acc_seg: 78.6809, loss: 0.6353
2022-11-04 17:28:53,021 - mmseg - INFO - Iter [75750/80000]	lr: 8.551e-06, eta: 0:24:09, time: 0.390, data_time: 0.062, memory: 12960, decode.loss_ce: 0.3981, decode.acc_seg: 84.2372, aux.loss_ce: 0.2346, aux.acc_seg: 78.5772, loss: 0.6327
2022-11-04 17:29:09,636 - mmseg - INFO - Iter [75800/80000]	lr: 8.461e-06, eta: 0:23:52, time: 0.332, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4079, decode.acc_seg: 83.8931, aux.loss_ce: 0.2342, aux.acc_seg: 78.4248, loss: 0.6421
2022-11-04 17:29:26,494 - mmseg - INFO - Iter [75850/80000]	lr: 8.370e-06, eta: 0:23:34, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4126, decode.acc_seg: 83.9318, aux.loss_ce: 0.2380, aux.acc_seg: 78.4722, loss: 0.6505
2022-11-04 17:29:43,073 - mmseg - INFO - Iter [75900/80000]	lr: 8.279e-06, eta: 0:23:17, time: 0.332, data_time: 0.010, memory: 12960, decode.loss_ce: 0.4021, decode.acc_seg: 84.1439, aux.loss_ce: 0.2339, aux.acc_seg: 78.6172, loss: 0.6360
2022-11-04 17:29:59,805 - mmseg - INFO - Iter [75950/80000]	lr: 8.189e-06, eta: 0:23:00, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3935, decode.acc_seg: 84.2264, aux.loss_ce: 0.2312, aux.acc_seg: 78.6564, loss: 0.6247
2022-11-04 17:30:16,367 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:30:16,368 - mmseg - INFO - Iter [76000/80000]	lr: 8.098e-06, eta: 0:22:43, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4093, decode.acc_seg: 83.9555, aux.loss_ce: 0.2398, aux.acc_seg: 77.9969, loss: 0.6490
2022-11-04 17:30:33,087 - mmseg - INFO - Iter [76050/80000]	lr: 8.006e-06, eta: 0:22:26, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4022, decode.acc_seg: 84.3226, aux.loss_ce: 0.2341, aux.acc_seg: 78.8063, loss: 0.6363
2022-11-04 17:30:49,838 - mmseg - INFO - Iter [76100/80000]	lr: 7.915e-06, eta: 0:22:09, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4130, decode.acc_seg: 83.6852, aux.loss_ce: 0.2380, aux.acc_seg: 78.0967, loss: 0.6510
2022-11-04 17:31:06,685 - mmseg - INFO - Iter [76150/80000]	lr: 7.824e-06, eta: 0:21:52, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4141, decode.acc_seg: 83.5102, aux.loss_ce: 0.2415, aux.acc_seg: 77.9102, loss: 0.6556
2022-11-04 17:31:23,493 - mmseg - INFO - Iter [76200/80000]	lr: 7.732e-06, eta: 0:21:35, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4290, decode.acc_seg: 83.1925, aux.loss_ce: 0.2477, aux.acc_seg: 77.3228, loss: 0.6767
2022-11-04 17:31:39,979 - mmseg - INFO - Iter [76250/80000]	lr: 7.641e-06, eta: 0:21:18, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4138, decode.acc_seg: 83.7821, aux.loss_ce: 0.2444, aux.acc_seg: 77.6501, loss: 0.6582
2022-11-04 17:31:56,880 - mmseg - INFO - Iter [76300/80000]	lr: 7.549e-06, eta: 0:21:01, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4068, decode.acc_seg: 83.6072, aux.loss_ce: 0.2398, aux.acc_seg: 77.9970, loss: 0.6466
2022-11-04 17:32:13,477 - mmseg - INFO - Iter [76350/80000]	lr: 7.457e-06, eta: 0:20:44, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4042, decode.acc_seg: 84.2086, aux.loss_ce: 0.2356, aux.acc_seg: 78.6162, loss: 0.6399
2022-11-04 17:32:33,408 - mmseg - INFO - Iter [76400/80000]	lr: 7.365e-06, eta: 0:20:27, time: 0.399, data_time: 0.064, memory: 12960, decode.loss_ce: 0.4125, decode.acc_seg: 83.6007, aux.loss_ce: 0.2379, aux.acc_seg: 77.9165, loss: 0.6504
2022-11-04 17:32:50,313 - mmseg - INFO - Iter [76450/80000]	lr: 7.273e-06, eta: 0:20:10, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3963, decode.acc_seg: 84.2687, aux.loss_ce: 0.2305, aux.acc_seg: 78.7590, loss: 0.6268
2022-11-04 17:33:07,098 - mmseg - INFO - Iter [76500/80000]	lr: 7.181e-06, eta: 0:19:53, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3989, decode.acc_seg: 84.0691, aux.loss_ce: 0.2325, aux.acc_seg: 78.5350, loss: 0.6314
2022-11-04 17:33:24,052 - mmseg - INFO - Iter [76550/80000]	lr: 7.088e-06, eta: 0:19:36, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4075, decode.acc_seg: 84.0320, aux.loss_ce: 0.2378, aux.acc_seg: 78.7284, loss: 0.6452
2022-11-04 17:33:40,923 - mmseg - INFO - Iter [76600/80000]	lr: 6.996e-06, eta: 0:19:19, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4202, decode.acc_seg: 83.5978, aux.loss_ce: 0.2422, aux.acc_seg: 78.0149, loss: 0.6624
2022-11-04 17:33:57,449 - mmseg - INFO - Iter [76650/80000]	lr: 6.903e-06, eta: 0:19:02, time: 0.331, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4175, decode.acc_seg: 83.8030, aux.loss_ce: 0.2392, aux.acc_seg: 78.4205, loss: 0.6567
2022-11-04 17:34:14,134 - mmseg - INFO - Iter [76700/80000]	lr: 6.811e-06, eta: 0:18:45, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4070, decode.acc_seg: 84.0860, aux.loss_ce: 0.2397, aux.acc_seg: 78.0632, loss: 0.6467
2022-11-04 17:34:30,872 - mmseg - INFO - Iter [76750/80000]	lr: 6.718e-06, eta: 0:18:28, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4054, decode.acc_seg: 84.0943, aux.loss_ce: 0.2336, aux.acc_seg: 78.4974, loss: 0.6390
2022-11-04 17:34:47,711 - mmseg - INFO - Iter [76800/80000]	lr: 6.625e-06, eta: 0:18:10, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4069, decode.acc_seg: 83.8469, aux.loss_ce: 0.2347, aux.acc_seg: 78.3380, loss: 0.6416
2022-11-04 17:35:04,328 - mmseg - INFO - Iter [76850/80000]	lr: 6.531e-06, eta: 0:17:53, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4100, decode.acc_seg: 83.8927, aux.loss_ce: 0.2413, aux.acc_seg: 77.8532, loss: 0.6513
2022-11-04 17:35:21,108 - mmseg - INFO - Iter [76900/80000]	lr: 6.438e-06, eta: 0:17:36, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3956, decode.acc_seg: 84.1596, aux.loss_ce: 0.2303, aux.acc_seg: 78.6492, loss: 0.6259
2022-11-04 17:35:37,833 - mmseg - INFO - Iter [76950/80000]	lr: 6.345e-06, eta: 0:17:19, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4035, decode.acc_seg: 84.1559, aux.loss_ce: 0.2423, aux.acc_seg: 77.9369, loss: 0.6459
2022-11-04 17:35:57,762 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:35:57,762 - mmseg - INFO - Iter [77000/80000]	lr: 6.251e-06, eta: 0:17:02, time: 0.399, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4126, decode.acc_seg: 84.0827, aux.loss_ce: 0.2389, aux.acc_seg: 78.3499, loss: 0.6515
2022-11-04 17:36:14,489 - mmseg - INFO - Iter [77050/80000]	lr: 6.157e-06, eta: 0:16:45, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4144, decode.acc_seg: 83.7496, aux.loss_ce: 0.2432, aux.acc_seg: 77.9970, loss: 0.6576
2022-11-04 17:36:30,980 - mmseg - INFO - Iter [77100/80000]	lr: 6.063e-06, eta: 0:16:28, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3964, decode.acc_seg: 84.4144, aux.loss_ce: 0.2314, aux.acc_seg: 78.9671, loss: 0.6278
2022-11-04 17:36:47,700 - mmseg - INFO - Iter [77150/80000]	lr: 5.969e-06, eta: 0:16:11, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4113, decode.acc_seg: 83.8910, aux.loss_ce: 0.2436, aux.acc_seg: 78.0199, loss: 0.6548
2022-11-04 17:37:04,509 - mmseg - INFO - Iter [77200/80000]	lr: 5.875e-06, eta: 0:15:54, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4084, decode.acc_seg: 83.7721, aux.loss_ce: 0.2364, aux.acc_seg: 78.2404, loss: 0.6448
2022-11-04 17:37:21,450 - mmseg - INFO - Iter [77250/80000]	lr: 5.780e-06, eta: 0:15:37, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4043, decode.acc_seg: 83.6212, aux.loss_ce: 0.2360, aux.acc_seg: 78.2090, loss: 0.6403
2022-11-04 17:37:38,056 - mmseg - INFO - Iter [77300/80000]	lr: 5.686e-06, eta: 0:15:20, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4105, decode.acc_seg: 83.6282, aux.loss_ce: 0.2415, aux.acc_seg: 77.9095, loss: 0.6520
2022-11-04 17:37:54,743 - mmseg - INFO - Iter [77350/80000]	lr: 5.591e-06, eta: 0:15:03, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4118, decode.acc_seg: 84.0017, aux.loss_ce: 0.2393, aux.acc_seg: 78.5772, loss: 0.6511
2022-11-04 17:38:11,547 - mmseg - INFO - Iter [77400/80000]	lr: 5.496e-06, eta: 0:14:46, time: 0.336, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4191, decode.acc_seg: 83.6552, aux.loss_ce: 0.2396, aux.acc_seg: 78.3124, loss: 0.6587
2022-11-04 17:38:28,090 - mmseg - INFO - Iter [77450/80000]	lr: 5.401e-06, eta: 0:14:29, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4115, decode.acc_seg: 83.9129, aux.loss_ce: 0.2341, aux.acc_seg: 78.7205, loss: 0.6456
2022-11-04 17:38:44,852 - mmseg - INFO - Iter [77500/80000]	lr: 5.305e-06, eta: 0:14:12, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4051, decode.acc_seg: 83.9114, aux.loss_ce: 0.2397, aux.acc_seg: 78.0152, loss: 0.6447
2022-11-04 17:39:01,393 - mmseg - INFO - Iter [77550/80000]	lr: 5.210e-06, eta: 0:13:55, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3999, decode.acc_seg: 84.2943, aux.loss_ce: 0.2307, aux.acc_seg: 78.7394, loss: 0.6306
2022-11-04 17:39:17,958 - mmseg - INFO - Iter [77600/80000]	lr: 5.114e-06, eta: 0:13:38, time: 0.331, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3977, decode.acc_seg: 84.3267, aux.loss_ce: 0.2318, aux.acc_seg: 78.7664, loss: 0.6295
2022-11-04 17:39:37,558 - mmseg - INFO - Iter [77650/80000]	lr: 5.018e-06, eta: 0:13:21, time: 0.392, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4080, decode.acc_seg: 84.0445, aux.loss_ce: 0.2417, aux.acc_seg: 78.1514, loss: 0.6497
2022-11-04 17:39:54,406 - mmseg - INFO - Iter [77700/80000]	lr: 4.922e-06, eta: 0:13:04, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4098, decode.acc_seg: 84.0230, aux.loss_ce: 0.2363, aux.acc_seg: 78.7860, loss: 0.6461
2022-11-04 17:40:11,885 - mmseg - INFO - Iter [77750/80000]	lr: 4.825e-06, eta: 0:12:47, time: 0.350, data_time: 0.024, memory: 12960, decode.loss_ce: 0.4175, decode.acc_seg: 83.6917, aux.loss_ce: 0.2438, aux.acc_seg: 77.8577, loss: 0.6612
2022-11-04 17:40:28,591 - mmseg - INFO - Iter [77800/80000]	lr: 4.729e-06, eta: 0:12:30, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4041, decode.acc_seg: 84.2385, aux.loss_ce: 0.2332, aux.acc_seg: 78.9720, loss: 0.6373
2022-11-04 17:40:45,115 - mmseg - INFO - Iter [77850/80000]	lr: 4.632e-06, eta: 0:12:12, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3965, decode.acc_seg: 84.3460, aux.loss_ce: 0.2307, aux.acc_seg: 78.8288, loss: 0.6271
2022-11-04 17:41:01,541 - mmseg - INFO - Iter [77900/80000]	lr: 4.535e-06, eta: 0:11:55, time: 0.329, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4047, decode.acc_seg: 84.1271, aux.loss_ce: 0.2354, aux.acc_seg: 78.6334, loss: 0.6401
2022-11-04 17:41:18,377 - mmseg - INFO - Iter [77950/80000]	lr: 4.438e-06, eta: 0:11:38, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4090, decode.acc_seg: 83.6308, aux.loss_ce: 0.2371, aux.acc_seg: 78.1678, loss: 0.6461
2022-11-04 17:41:35,208 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:41:35,208 - mmseg - INFO - Iter [78000/80000]	lr: 4.340e-06, eta: 0:11:21, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4099, decode.acc_seg: 84.0157, aux.loss_ce: 0.2366, aux.acc_seg: 78.4424, loss: 0.6464
2022-11-04 17:41:52,126 - mmseg - INFO - Iter [78050/80000]	lr: 4.243e-06, eta: 0:11:04, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4063, decode.acc_seg: 83.7706, aux.loss_ce: 0.2334, aux.acc_seg: 78.3832, loss: 0.6397
2022-11-04 17:42:08,900 - mmseg - INFO - Iter [78100/80000]	lr: 4.145e-06, eta: 0:10:47, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4075, decode.acc_seg: 83.8808, aux.loss_ce: 0.2360, aux.acc_seg: 78.5510, loss: 0.6435
2022-11-04 17:42:25,517 - mmseg - INFO - Iter [78150/80000]	lr: 4.046e-06, eta: 0:10:30, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4159, decode.acc_seg: 83.6270, aux.loss_ce: 0.2405, aux.acc_seg: 78.1514, loss: 0.6564
2022-11-04 17:42:42,028 - mmseg - INFO - Iter [78200/80000]	lr: 3.948e-06, eta: 0:10:13, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4133, decode.acc_seg: 83.5991, aux.loss_ce: 0.2419, aux.acc_seg: 77.7637, loss: 0.6552
2022-11-04 17:43:01,651 - mmseg - INFO - Iter [78250/80000]	lr: 3.849e-06, eta: 0:09:56, time: 0.392, data_time: 0.066, memory: 12960, decode.loss_ce: 0.4026, decode.acc_seg: 84.0157, aux.loss_ce: 0.2352, aux.acc_seg: 78.5212, loss: 0.6378
2022-11-04 17:43:18,295 - mmseg - INFO - Iter [78300/80000]	lr: 3.750e-06, eta: 0:09:39, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4168, decode.acc_seg: 83.4755, aux.loss_ce: 0.2437, aux.acc_seg: 77.8785, loss: 0.6604
2022-11-04 17:43:34,961 - mmseg - INFO - Iter [78350/80000]	lr: 3.651e-06, eta: 0:09:22, time: 0.333, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4149, decode.acc_seg: 83.8543, aux.loss_ce: 0.2412, aux.acc_seg: 78.2144, loss: 0.6560
2022-11-04 17:43:52,032 - mmseg - INFO - Iter [78400/80000]	lr: 3.551e-06, eta: 0:09:05, time: 0.341, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4155, decode.acc_seg: 83.6313, aux.loss_ce: 0.2443, aux.acc_seg: 77.7154, loss: 0.6597
2022-11-04 17:44:08,717 - mmseg - INFO - Iter [78450/80000]	lr: 3.451e-06, eta: 0:08:48, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4102, decode.acc_seg: 83.5888, aux.loss_ce: 0.2383, aux.acc_seg: 77.8279, loss: 0.6485
2022-11-04 17:44:25,535 - mmseg - INFO - Iter [78500/80000]	lr: 3.351e-06, eta: 0:08:31, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4128, decode.acc_seg: 83.7502, aux.loss_ce: 0.2408, aux.acc_seg: 78.1834, loss: 0.6536
2022-11-04 17:44:42,032 - mmseg - INFO - Iter [78550/80000]	lr: 3.250e-06, eta: 0:08:14, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4089, decode.acc_seg: 84.0146, aux.loss_ce: 0.2390, aux.acc_seg: 78.0247, loss: 0.6479
2022-11-04 17:44:58,655 - mmseg - INFO - Iter [78600/80000]	lr: 3.149e-06, eta: 0:07:57, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4057, decode.acc_seg: 83.9054, aux.loss_ce: 0.2346, aux.acc_seg: 78.6292, loss: 0.6403
2022-11-04 17:45:15,162 - mmseg - INFO - Iter [78650/80000]	lr: 3.048e-06, eta: 0:07:40, time: 0.330, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3873, decode.acc_seg: 84.5381, aux.loss_ce: 0.2304, aux.acc_seg: 78.5866, loss: 0.6177
2022-11-04 17:45:31,971 - mmseg - INFO - Iter [78700/80000]	lr: 2.946e-06, eta: 0:07:23, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4045, decode.acc_seg: 84.0112, aux.loss_ce: 0.2304, aux.acc_seg: 78.8985, loss: 0.6349
2022-11-04 17:45:48,741 - mmseg - INFO - Iter [78750/80000]	lr: 2.844e-06, eta: 0:07:06, time: 0.335, data_time: 0.008, memory: 12960, decode.loss_ce: 0.4106, decode.acc_seg: 84.0388, aux.loss_ce: 0.2381, aux.acc_seg: 78.5321, loss: 0.6487
2022-11-04 17:46:05,333 - mmseg - INFO - Iter [78800/80000]	lr: 2.742e-06, eta: 0:06:49, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3987, decode.acc_seg: 83.9390, aux.loss_ce: 0.2343, aux.acc_seg: 78.1079, loss: 0.6330
2022-11-04 17:46:22,087 - mmseg - INFO - Iter [78850/80000]	lr: 2.639e-06, eta: 0:06:31, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4045, decode.acc_seg: 83.9037, aux.loss_ce: 0.2349, aux.acc_seg: 78.5224, loss: 0.6394
2022-11-04 17:46:41,506 - mmseg - INFO - Iter [78900/80000]	lr: 2.535e-06, eta: 0:06:14, time: 0.388, data_time: 0.056, memory: 12960, decode.loss_ce: 0.4122, decode.acc_seg: 83.7917, aux.loss_ce: 0.2407, aux.acc_seg: 78.1550, loss: 0.6529
2022-11-04 17:46:58,143 - mmseg - INFO - Iter [78950/80000]	lr: 2.431e-06, eta: 0:05:57, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4019, decode.acc_seg: 84.4488, aux.loss_ce: 0.2347, aux.acc_seg: 78.9190, loss: 0.6366
2022-11-04 17:47:14,806 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:47:14,807 - mmseg - INFO - Iter [79000/80000]	lr: 2.327e-06, eta: 0:05:40, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4081, decode.acc_seg: 83.9976, aux.loss_ce: 0.2398, aux.acc_seg: 78.2417, loss: 0.6478
2022-11-04 17:47:31,781 - mmseg - INFO - Iter [79050/80000]	lr: 2.222e-06, eta: 0:05:23, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4029, decode.acc_seg: 84.0523, aux.loss_ce: 0.2403, aux.acc_seg: 78.2606, loss: 0.6432
2022-11-04 17:47:48,578 - mmseg - INFO - Iter [79100/80000]	lr: 2.117e-06, eta: 0:05:06, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3836, decode.acc_seg: 84.6850, aux.loss_ce: 0.2255, aux.acc_seg: 79.0373, loss: 0.6090
2022-11-04 17:48:05,350 - mmseg - INFO - Iter [79150/80000]	lr: 2.011e-06, eta: 0:04:49, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4035, decode.acc_seg: 83.9695, aux.loss_ce: 0.2412, aux.acc_seg: 77.8812, loss: 0.6446
2022-11-04 17:48:22,095 - mmseg - INFO - Iter [79200/80000]	lr: 1.904e-06, eta: 0:04:32, time: 0.335, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4173, decode.acc_seg: 83.5541, aux.loss_ce: 0.2400, aux.acc_seg: 78.0522, loss: 0.6573
2022-11-04 17:48:38,722 - mmseg - INFO - Iter [79250/80000]	lr: 1.797e-06, eta: 0:04:15, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4196, decode.acc_seg: 83.4847, aux.loss_ce: 0.2415, aux.acc_seg: 77.8092, loss: 0.6611
2022-11-04 17:48:55,339 - mmseg - INFO - Iter [79300/80000]	lr: 1.689e-06, eta: 0:03:58, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4045, decode.acc_seg: 84.1490, aux.loss_ce: 0.2333, aux.acc_seg: 78.6027, loss: 0.6377
2022-11-04 17:49:12,048 - mmseg - INFO - Iter [79350/80000]	lr: 1.580e-06, eta: 0:03:41, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4062, decode.acc_seg: 84.0438, aux.loss_ce: 0.2437, aux.acc_seg: 77.7026, loss: 0.6499
2022-11-04 17:49:28,935 - mmseg - INFO - Iter [79400/80000]	lr: 1.470e-06, eta: 0:03:24, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4039, decode.acc_seg: 84.0206, aux.loss_ce: 0.2344, aux.acc_seg: 78.3128, loss: 0.6383
2022-11-04 17:49:45,519 - mmseg - INFO - Iter [79450/80000]	lr: 1.360e-06, eta: 0:03:07, time: 0.332, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4149, decode.acc_seg: 83.6172, aux.loss_ce: 0.2424, aux.acc_seg: 77.6955, loss: 0.6573
2022-11-04 17:50:02,158 - mmseg - INFO - Iter [79500/80000]	lr: 1.248e-06, eta: 0:02:50, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4072, decode.acc_seg: 83.7701, aux.loss_ce: 0.2338, aux.acc_seg: 78.3213, loss: 0.6409
2022-11-04 17:50:21,799 - mmseg - INFO - Iter [79550/80000]	lr: 1.135e-06, eta: 0:02:33, time: 0.393, data_time: 0.062, memory: 12960, decode.loss_ce: 0.4036, decode.acc_seg: 84.1091, aux.loss_ce: 0.2385, aux.acc_seg: 78.2074, loss: 0.6421
2022-11-04 17:50:38,692 - mmseg - INFO - Iter [79600/80000]	lr: 1.021e-06, eta: 0:02:16, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3888, decode.acc_seg: 84.5782, aux.loss_ce: 0.2264, aux.acc_seg: 79.3822, loss: 0.6152
2022-11-04 17:50:55,333 - mmseg - INFO - Iter [79650/80000]	lr: 9.061e-07, eta: 0:01:59, time: 0.333, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3927, decode.acc_seg: 84.4449, aux.loss_ce: 0.2342, aux.acc_seg: 78.3210, loss: 0.6269
2022-11-04 17:51:12,152 - mmseg - INFO - Iter [79700/80000]	lr: 7.891e-07, eta: 0:01:42, time: 0.336, data_time: 0.010, memory: 12960, decode.loss_ce: 0.3980, decode.acc_seg: 84.0868, aux.loss_ce: 0.2360, aux.acc_seg: 77.7898, loss: 0.6340
2022-11-04 17:51:28,858 - mmseg - INFO - Iter [79750/80000]	lr: 6.700e-07, eta: 0:01:25, time: 0.334, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4060, decode.acc_seg: 83.8546, aux.loss_ce: 0.2364, aux.acc_seg: 77.8669, loss: 0.6423
2022-11-04 17:51:45,738 - mmseg - INFO - Iter [79800/80000]	lr: 5.486e-07, eta: 0:01:08, time: 0.338, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4007, decode.acc_seg: 84.1764, aux.loss_ce: 0.2362, aux.acc_seg: 78.2766, loss: 0.6369
2022-11-04 17:52:02,572 - mmseg - INFO - Iter [79850/80000]	lr: 4.241e-07, eta: 0:00:51, time: 0.337, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3976, decode.acc_seg: 84.5933, aux.loss_ce: 0.2315, aux.acc_seg: 79.5693, loss: 0.6292
2022-11-04 17:52:19,361 - mmseg - INFO - Iter [79900/80000]	lr: 2.953e-07, eta: 0:00:34, time: 0.336, data_time: 0.009, memory: 12960, decode.loss_ce: 0.3944, decode.acc_seg: 84.3892, aux.loss_ce: 0.2330, aux.acc_seg: 78.6868, loss: 0.6274
2022-11-04 17:52:36,863 - mmseg - INFO - Iter [79950/80000]	lr: 1.597e-07, eta: 0:00:17, time: 0.350, data_time: 0.023, memory: 12960, decode.loss_ce: 0.4033, decode.acc_seg: 84.1871, aux.loss_ce: 0.2372, aux.acc_seg: 78.4024, loss: 0.6405
2022-11-04 17:52:53,549 - mmseg - INFO - Saving checkpoint at 80000 iterations
2022-11-04 17:52:53,834 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:52:53,834 - mmseg - INFO - Iter [80000/80000]	lr: 4.639e-09, eta: 0:00:00, time: 0.339, data_time: 0.009, memory: 12960, decode.loss_ce: 0.4093, decode.acc_seg: 83.8377, aux.loss_ce: 0.2398, aux.acc_seg: 78.1147, loss: 0.6491
2022-11-04 17:53:02,607 - mmseg - INFO - per class results:
2022-11-04 17:53:02,614 - mmseg - INFO - 
+---------------------+-------+-------+
|        Class        |  IoU  |  Acc  |
+---------------------+-------+-------+
|         wall        | 66.64 | 83.21 |
|       building      | 75.21 | 89.33 |
|         sky         | 88.75 | 92.98 |
|        floor        | 71.09 | 85.01 |
|         tree        | 67.77 |  84.3 |
|       ceiling       | 76.52 | 85.57 |
|         road        | 75.26 | 85.43 |
|         bed         | 75.94 | 90.68 |
|      windowpane     | 49.91 | 67.91 |
|        grass        | 63.55 |  81.2 |
|       cabinet       | 48.54 | 62.98 |
|       sidewalk      | 52.72 | 68.91 |
|        person       | 64.56 |  82.8 |
|        earth        |  29.6 | 41.93 |
|         door        | 27.19 | 42.22 |
|        table        | 40.71 | 56.63 |
|       mountain      | 52.36 |  72.1 |
|        plant        |  45.2 | 57.57 |
|       curtain       | 55.72 | 72.93 |
|        chair        | 37.97 | 53.46 |
|         car         | 71.55 | 85.49 |
|        water        | 43.98 | 60.35 |
|       painting      |  55.8 | 72.79 |
|         sofa        | 46.69 | 67.43 |
|        shelf        | 33.47 | 50.38 |
|        house        | 40.81 | 60.31 |
|         sea         | 33.77 | 56.65 |
|        mirror       | 40.72 | 49.29 |
|         rug         |  48.7 | 56.91 |
|        field        |  35.0 | 48.24 |
|       armchair      | 26.91 | 41.28 |
|         seat        | 51.97 | 68.78 |
|        fence        | 27.72 | 43.46 |
|         desk        | 31.43 | 51.45 |
|         rock        | 38.77 | 61.68 |
|       wardrobe      | 36.25 | 54.54 |
|         lamp        | 37.65 | 50.24 |
|       bathtub       | 55.19 | 65.96 |
|       railing       | 24.96 | 39.08 |
|       cushion       | 33.02 | 43.57 |
|         base        | 19.13 | 22.58 |
|         box         | 15.45 |  21.3 |
|        column       | 31.96 | 40.52 |
|      signboard      | 23.96 |  32.8 |
|   chest of drawers  | 26.53 | 43.52 |
|       counter       | 25.07 | 27.51 |
|         sand        | 27.98 | 42.55 |
|         sink        | 47.43 | 60.62 |
|      skyscraper     | 65.39 | 85.79 |
|      fireplace      | 60.98 | 79.21 |
|     refrigerator    | 52.48 | 64.99 |
|      grandstand     | 43.57 | 64.61 |
|         path        | 18.56 | 26.24 |
|        stairs       | 25.02 |  31.3 |
|        runway       | 70.65 | 84.97 |
|         case        | 34.35 | 49.36 |
|      pool table     | 80.47 |  90.3 |
|        pillow       | 38.06 |  49.3 |
|     screen door     | 46.85 | 60.44 |
|       stairway      | 26.93 | 33.81 |
|        river        | 14.06 | 18.65 |
|        bridge       | 45.06 | 64.87 |
|       bookcase      | 25.35 | 37.23 |
|        blind        | 26.19 | 31.71 |
|     coffee table    | 39.71 | 69.66 |
|        toilet       | 67.64 | 78.83 |
|        flower       |  24.8 |  41.3 |
|         book        | 36.29 | 51.77 |
|         hill        |  4.37 |  6.51 |
|        bench        | 31.31 | 40.18 |
|      countertop     | 39.95 | 51.98 |
|        stove        | 49.55 | 60.82 |
|         palm        | 37.59 | 57.16 |
|    kitchen island   |  17.7 |  40.3 |
|       computer      | 42.78 | 57.71 |
|     swivel chair    | 28.96 | 35.03 |
|         boat        | 44.55 | 56.68 |
|         bar         | 23.86 | 29.33 |
|    arcade machine   | 29.14 | 33.55 |
|        hovel        | 30.77 | 37.76 |
|         bus         | 69.71 |  85.3 |
|        towel        | 37.39 | 50.32 |
|        light        |  16.4 | 18.06 |
|        truck        |  5.24 |  7.41 |
|        tower        | 30.66 | 36.77 |
|      chandelier     | 46.53 | 59.93 |
|        awning       | 16.16 | 18.17 |
|     streetlight     |  6.88 |  8.1  |
|        booth        | 27.82 | 29.99 |
| television receiver | 38.86 | 62.97 |
|       airplane      | 43.26 | 53.02 |
|      dirt track     |  8.58 | 14.57 |
|       apparel       | 18.34 | 26.38 |
|         pole        |  7.33 | 12.29 |
|         land        |  1.62 |  2.31 |
|      bannister      |  2.86 |  3.6  |
|      escalator      | 35.38 | 37.42 |
|       ottoman       |  23.6 | 26.56 |
|        bottle       | 19.04 | 41.57 |
|        buffet       | 40.87 | 53.02 |
|        poster       | 24.37 | 29.19 |
|        stage        | 12.55 | 15.73 |
|         van         | 15.86 | 18.54 |
|         ship        |  3.86 |  4.13 |
|       fountain      |  12.0 | 12.39 |
|    conveyer belt    |  53.0 | 58.45 |
|        canopy       | 20.06 | 24.88 |
|        washer       | 59.09 | 62.53 |
|      plaything      |  6.05 |  8.89 |
|    swimming pool    | 29.03 | 47.53 |
|        stool        | 16.36 | 19.34 |
|        barrel       | 37.98 | 60.28 |
|        basket       | 14.81 | 19.37 |
|      waterfall      | 36.63 | 40.91 |
|         tent        | 84.06 |  96.9 |
|         bag         |  3.74 |  4.23 |
|       minibike      |  47.9 |  57.3 |
|        cradle       | 57.08 | 79.06 |
|         oven        | 15.87 | 29.31 |
|         ball        | 31.78 | 39.43 |
|         food        |  37.7 | 48.78 |
|         step        |  2.7  |  2.87 |
|         tank        | 36.49 | 42.25 |
|      trade name     | 15.82 | 17.52 |
|      microwave      |  26.6 | 30.12 |
|         pot         |  21.9 | 26.55 |
|        animal       | 43.91 | 50.88 |
|       bicycle       | 35.49 | 58.05 |
|         lake        | 43.62 | 50.17 |
|      dishwasher     | 29.05 | 39.72 |
|        screen       | 54.27 | 75.73 |
|       blanket       |  2.04 |  2.34 |
|      sculpture      | 34.37 | 50.47 |
|         hood        | 36.74 | 43.61 |
|        sconce       | 14.72 | 16.24 |
|         vase        | 14.39 | 20.69 |
|    traffic light    |  10.7 | 13.98 |
|         tray        |  2.26 |  4.87 |
|        ashcan       | 21.76 | 26.22 |
|         fan         | 25.23 | 30.13 |
|         pier        | 33.32 | 43.45 |
|      crt screen     |  0.14 |  0.2  |
|        plate        | 31.16 | 39.24 |
|       monitor       | 14.36 | 15.47 |
|    bulletin board   | 31.96 | 39.98 |
|        shower       |  0.0  |  0.0  |
|       radiator      | 34.35 | 40.61 |
|        glass        |  0.78 |  0.8  |
|        clock        |  9.77 | 10.64 |
|         flag        |  16.7 | 18.61 |
+---------------------+-------+-------+
2022-11-04 17:53:02,614 - mmseg - INFO - Summary:
2022-11-04 17:53:02,615 - mmseg - INFO - 
+-------+-------+-------+
|  aAcc |  mIoU |  mAcc |
+-------+-------+-------+
| 75.47 | 34.54 | 44.89 |
+-------+-------+-------+
2022-11-04 17:53:02,616 - mmseg - INFO - Exp name: pspnet_metamobile2M_512x512_80k_ade20k_256.py
2022-11-04 17:53:02,616 - mmseg - INFO - Iter(val) [250]	aAcc: 0.7547, mIoU: 0.3454, mAcc: 0.4489, IoU.wall: 0.6664, IoU.building: 0.7521, IoU.sky: 0.8875, IoU.floor: 0.7109, IoU.tree: 0.6777, IoU.ceiling: 0.7652, IoU.road: 0.7526, IoU.bed : 0.7594, IoU.windowpane: 0.4991, IoU.grass: 0.6355, IoU.cabinet: 0.4854, IoU.sidewalk: 0.5272, IoU.person: 0.6456, IoU.earth: 0.2960, IoU.door: 0.2719, IoU.table: 0.4071, IoU.mountain: 0.5236, IoU.plant: 0.4520, IoU.curtain: 0.5572, IoU.chair: 0.3797, IoU.car: 0.7155, IoU.water: 0.4398, IoU.painting: 0.5580, IoU.sofa: 0.4669, IoU.shelf: 0.3347, IoU.house: 0.4081, IoU.sea: 0.3377, IoU.mirror: 0.4072, IoU.rug: 0.4870, IoU.field: 0.3500, IoU.armchair: 0.2691, IoU.seat: 0.5197, IoU.fence: 0.2772, IoU.desk: 0.3143, IoU.rock: 0.3877, IoU.wardrobe: 0.3625, IoU.lamp: 0.3765, IoU.bathtub: 0.5519, IoU.railing: 0.2496, IoU.cushion: 0.3302, IoU.base: 0.1913, IoU.box: 0.1545, IoU.column: 0.3196, IoU.signboard: 0.2396, IoU.chest of drawers: 0.2653, IoU.counter: 0.2507, IoU.sand: 0.2798, IoU.sink: 0.4743, IoU.skyscraper: 0.6539, IoU.fireplace: 0.6098, IoU.refrigerator: 0.5248, IoU.grandstand: 0.4357, IoU.path: 0.1856, IoU.stairs: 0.2502, IoU.runway: 0.7065, IoU.case: 0.3435, IoU.pool table: 0.8047, IoU.pillow: 0.3806, IoU.screen door: 0.4685, IoU.stairway: 0.2693, IoU.river: 0.1406, IoU.bridge: 0.4506, IoU.bookcase: 0.2535, IoU.blind: 0.2619, IoU.coffee table: 0.3971, IoU.toilet: 0.6764, IoU.flower: 0.2480, IoU.book: 0.3629, IoU.hill: 0.0437, IoU.bench: 0.3131, IoU.countertop: 0.3995, IoU.stove: 0.4955, IoU.palm: 0.3759, IoU.kitchen island: 0.1770, IoU.computer: 0.4278, IoU.swivel chair: 0.2896, IoU.boat: 0.4455, IoU.bar: 0.2386, IoU.arcade machine: 0.2914, IoU.hovel: 0.3077, IoU.bus: 0.6971, IoU.towel: 0.3739, IoU.light: 0.1640, IoU.truck: 0.0524, IoU.tower: 0.3066, IoU.chandelier: 0.4653, IoU.awning: 0.1616, IoU.streetlight: 0.0688, IoU.booth: 0.2782, IoU.television receiver: 0.3886, IoU.airplane: 0.4326, IoU.dirt track: 0.0858, IoU.apparel: 0.1834, IoU.pole: 0.0733, IoU.land: 0.0162, IoU.bannister: 0.0286, IoU.escalator: 0.3538, IoU.ottoman: 0.2360, IoU.bottle: 0.1904, IoU.buffet: 0.4087, IoU.poster: 0.2437, IoU.stage: 0.1255, IoU.van: 0.1586, IoU.ship: 0.0386, IoU.fountain: 0.1200, IoU.conveyer belt: 0.5300, IoU.canopy: 0.2006, IoU.washer: 0.5909, IoU.plaything: 0.0605, IoU.swimming pool: 0.2903, IoU.stool: 0.1636, IoU.barrel: 0.3798, IoU.basket: 0.1481, IoU.waterfall: 0.3663, IoU.tent: 0.8406, IoU.bag: 0.0374, IoU.minibike: 0.4790, IoU.cradle: 0.5708, IoU.oven: 0.1587, IoU.ball: 0.3178, IoU.food: 0.3770, IoU.step: 0.0270, IoU.tank: 0.3649, IoU.trade name: 0.1582, IoU.microwave: 0.2660, IoU.pot: 0.2190, IoU.animal: 0.4391, IoU.bicycle: 0.3549, IoU.lake: 0.4362, IoU.dishwasher: 0.2905, IoU.screen: 0.5427, IoU.blanket: 0.0204, IoU.sculpture: 0.3437, IoU.hood: 0.3674, IoU.sconce: 0.1472, IoU.vase: 0.1439, IoU.traffic light: 0.1070, IoU.tray: 0.0226, IoU.ashcan: 0.2176, IoU.fan: 0.2523, IoU.pier: 0.3332, IoU.crt screen: 0.0014, IoU.plate: 0.3116, IoU.monitor: 0.1436, IoU.bulletin board: 0.3196, IoU.shower: 0.0000, IoU.radiator: 0.3435, IoU.glass: 0.0078, IoU.clock: 0.0977, IoU.flag: 0.1670, Acc.wall: 0.8321, Acc.building: 0.8933, Acc.sky: 0.9298, Acc.floor: 0.8501, Acc.tree: 0.8430, Acc.ceiling: 0.8557, Acc.road: 0.8543, Acc.bed : 0.9068, Acc.windowpane: 0.6791, Acc.grass: 0.8120, Acc.cabinet: 0.6298, Acc.sidewalk: 0.6891, Acc.person: 0.8280, Acc.earth: 0.4193, Acc.door: 0.4222, Acc.table: 0.5663, Acc.mountain: 0.7210, Acc.plant: 0.5757, Acc.curtain: 0.7293, Acc.chair: 0.5346, Acc.car: 0.8549, Acc.water: 0.6035, Acc.painting: 0.7279, Acc.sofa: 0.6743, Acc.shelf: 0.5038, Acc.house: 0.6031, Acc.sea: 0.5665, Acc.mirror: 0.4929, Acc.rug: 0.5691, Acc.field: 0.4824, Acc.armchair: 0.4128, Acc.seat: 0.6878, Acc.fence: 0.4346, Acc.desk: 0.5145, Acc.rock: 0.6168, Acc.wardrobe: 0.5454, Acc.lamp: 0.5024, Acc.bathtub: 0.6596, Acc.railing: 0.3908, Acc.cushion: 0.4357, Acc.base: 0.2258, Acc.box: 0.2130, Acc.column: 0.4052, Acc.signboard: 0.3280, Acc.chest of drawers: 0.4352, Acc.counter: 0.2751, Acc.sand: 0.4255, Acc.sink: 0.6062, Acc.skyscraper: 0.8579, Acc.fireplace: 0.7921, Acc.refrigerator: 0.6499, Acc.grandstand: 0.6461, Acc.path: 0.2624, Acc.stairs: 0.3130, Acc.runway: 0.8497, Acc.case: 0.4936, Acc.pool table: 0.9030, Acc.pillow: 0.4930, Acc.screen door: 0.6044, Acc.stairway: 0.3381, Acc.river: 0.1865, Acc.bridge: 0.6487, Acc.bookcase: 0.3723, Acc.blind: 0.3171, Acc.coffee table: 0.6966, Acc.toilet: 0.7883, Acc.flower: 0.4130, Acc.book: 0.5177, Acc.hill: 0.0651, Acc.bench: 0.4018, Acc.countertop: 0.5198, Acc.stove: 0.6082, Acc.palm: 0.5716, Acc.kitchen island: 0.4030, Acc.computer: 0.5771, Acc.swivel chair: 0.3503, Acc.boat: 0.5668, Acc.bar: 0.2933, Acc.arcade machine: 0.3355, Acc.hovel: 0.3776, Acc.bus: 0.8530, Acc.towel: 0.5032, Acc.light: 0.1806, Acc.truck: 0.0741, Acc.tower: 0.3677, Acc.chandelier: 0.5993, Acc.awning: 0.1817, Acc.streetlight: 0.0810, Acc.booth: 0.2999, Acc.television receiver: 0.6297, Acc.airplane: 0.5302, Acc.dirt track: 0.1457, Acc.apparel: 0.2638, Acc.pole: 0.1229, Acc.land: 0.0231, Acc.bannister: 0.0360, Acc.escalator: 0.3742, Acc.ottoman: 0.2656, Acc.bottle: 0.4157, Acc.buffet: 0.5302, Acc.poster: 0.2919, Acc.stage: 0.1573, Acc.van: 0.1854, Acc.ship: 0.0413, Acc.fountain: 0.1239, Acc.conveyer belt: 0.5845, Acc.canopy: 0.2488, Acc.washer: 0.6253, Acc.plaything: 0.0889, Acc.swimming pool: 0.4753, Acc.stool: 0.1934, Acc.barrel: 0.6028, Acc.basket: 0.1937, Acc.waterfall: 0.4091, Acc.tent: 0.9690, Acc.bag: 0.0423, Acc.minibike: 0.5730, Acc.cradle: 0.7906, Acc.oven: 0.2931, Acc.ball: 0.3943, Acc.food: 0.4878, Acc.step: 0.0287, Acc.tank: 0.4225, Acc.trade name: 0.1752, Acc.microwave: 0.3012, Acc.pot: 0.2655, Acc.animal: 0.5088, Acc.bicycle: 0.5805, Acc.lake: 0.5017, Acc.dishwasher: 0.3972, Acc.screen: 0.7573, Acc.blanket: 0.0234, Acc.sculpture: 0.5047, Acc.hood: 0.4361, Acc.sconce: 0.1624, Acc.vase: 0.2069, Acc.traffic light: 0.1398, Acc.tray: 0.0487, Acc.ashcan: 0.2622, Acc.fan: 0.3013, Acc.pier: 0.4345, Acc.crt screen: 0.0020, Acc.plate: 0.3924, Acc.monitor: 0.1547, Acc.bulletin board: 0.3998, Acc.shower: 0.0000, Acc.radiator: 0.4061, Acc.glass: 0.0080, Acc.clock: 0.1064, Acc.flag: 0.1861