Namespace(accumulate=1, batch_norm=False, batch_size=8, clip_grad=0, crop_ratio=0.875, data_dir='/home/ubuntu/yizhu/data/kinetics400/kinetics400/train_256', dataset='kinetics400', dtype='float32', eval=False, fast_temporal_stride=2, hard_weight=0.5, hashtag='', input_5d=False, input_size=224, kvstore=None, label_smoothing=False, last_gamma=False, log_interval=50, logging_file='i3d_nl10_res50_seg1_kinetics400_b8_g8_inflate311_f32s2_step_epoch100_video_cleanv3.txt', lr=0.01, lr_decay=0.1, lr_decay_epoch='40,80,100', lr_decay_period=0, lr_mode='step', mixup=False, mixup_alpha=0.2, mixup_off_epoch=0, mode='hybrid', model='i3d_nl10_resnet50_v1_kinetics400', momentum=0.9, new_height=256, new_length=32, new_step=2, new_width=340, no_wd=False, num_classes=400, num_crop=1, num_epochs=100, num_gpus=8, num_segments=1, num_workers=32, partial_bn=False, prefetch_ratio=1.0, resume_epoch=0, resume_params='', resume_states='', save_dir='/home/ubuntu/yizhu/logs/mxnet/kinetics400/nonlocal/i3d_nl10_res50_seg1_kinetics400_b8_g8_inflate311_f32s2_step_epoch100_video_cleanv3', save_frequency=20, scale_ratios='1.0,0.8', slow_temporal_stride=16, slowfast=False, teacher=None, temperature=20, train_list='/home/ubuntu/yizhu/data/kinetics400/kinetics400/k400_train_240618.txt', use_amp=False, use_decord=True, use_gn=False, use_pretrained=False, use_se=False, use_tsn=False, val_data_dir='/home/ubuntu/yizhu/data/kinetics400/kinetics400/val_256', val_list='/home/ubuntu/yizhu/code/gluon-cv/extra/kinetics400/k400_val_19761_cleanv3.txt', video_loader=True, warmup_epochs=0, warmup_lr=0.0, wd=0.0001) Total batch size is set to 64 on 8 GPUs I3D_ResNetV1( (first_stage): HybridSequential( (0): Conv3D(3 -> 64, kernel_size=(5, 7, 7), stride=(2, 2, 2), padding=(2, 3, 3), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (2): Activation(relu) (3): MaxPool3D(size=(1, 3, 3), stride=(2, 2, 2), padding=(0, 1, 1), ceil_mode=False, global_pool=False, pool_type=max, layout=NCDHW) ) (pool2): MaxPool3D(size=(2, 1, 1), stride=(2, 1, 1), padding=(0, 0, 0), ceil_mode=False, global_pool=False, pool_type=max, layout=NCDHW) (res_layers): HybridSequential( (0): HybridSequential( (0): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(64 -> 64, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (2): Activation(relu) (3): Conv3D(64 -> 64, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (5): Activation(relu) (6): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) ) (conv1): Conv3D(64 -> 64, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(64 -> 64, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (conv3): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu): Activation(relu) (downsample): HybridSequential( (0): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) ) ) (1): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(256 -> 64, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (2): Activation(relu) (3): Conv3D(64 -> 64, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (5): Activation(relu) (6): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) ) (conv1): Conv3D(256 -> 64, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(64 -> 64, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (conv3): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu): Activation(relu) ) (2): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(256 -> 64, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (2): Activation(relu) (3): Conv3D(64 -> 64, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (5): Activation(relu) (6): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) ) (conv1): Conv3D(256 -> 64, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(64 -> 64, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) (conv3): Conv3D(64 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (relu): Activation(relu) ) ) (1): HybridSequential( (0): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(256 -> 128, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (2): Activation(relu) (3): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (5): Activation(relu) (6): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (8): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (conv1): Conv3D(256 -> 128, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (conv3): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu): Activation(relu) (downsample): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 2, 2), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) (nonlocal_block): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (1): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(512 -> 128, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (2): Activation(relu) (3): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (5): Activation(relu) (6): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (8): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (conv1): Conv3D(512 -> 128, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (conv3): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (2): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(512 -> 128, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (2): Activation(relu) (3): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (5): Activation(relu) (6): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (8): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (conv1): Conv3D(512 -> 128, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (conv3): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (3): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(512 -> 128, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (2): Activation(relu) (3): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (5): Activation(relu) (6): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (8): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) (conv1): Conv3D(512 -> 128, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(128 -> 128, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) (conv3): Conv3D(128 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(512 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (W_bn): HybridSequential( (0): Conv3D(256 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) ) ) ) ) (2): HybridSequential( (0): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(512 -> 256, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (2): Activation(relu) (3): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (5): Activation(relu) (6): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (8): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (conv1): Conv3D(512 -> 256, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (conv3): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu): Activation(relu) (downsample): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 2, 2), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) (nonlocal_block): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (1): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (2): Activation(relu) (3): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (5): Activation(relu) (6): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (8): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (conv1): Conv3D(1024 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (conv3): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (2): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 256, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (2): Activation(relu) (3): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (5): Activation(relu) (6): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (8): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (conv1): Conv3D(1024 -> 256, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (conv3): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (3): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (2): Activation(relu) (3): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (5): Activation(relu) (6): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (8): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (conv1): Conv3D(1024 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (conv3): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (4): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 256, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (2): Activation(relu) (3): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (5): Activation(relu) (6): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (8): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (conv1): Conv3D(1024 -> 256, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (conv3): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (5): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (2): Activation(relu) (3): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (5): Activation(relu) (6): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (8): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) (conv1): Conv3D(1024 -> 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(256 -> 256, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) (conv3): Conv3D(256 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (relu): Activation(relu) (nonlocal_block): NonLocal( (theta): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (phi): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (g): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (W): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) (W_bn): HybridSequential( (0): Conv3D(512 -> 1024, kernel_size=(1, 1, 1), stride=(1, 1, 1)) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) ) ) ) ) (3): HybridSequential( (0): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (2): Activation(relu) (3): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (5): Activation(relu) (6): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) (conv1): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (conv3): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu): Activation(relu) (downsample): HybridSequential( (0): Conv3D(1024 -> 2048, kernel_size=(1, 1, 1), stride=(1, 2, 2), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) ) (1): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(2048 -> 512, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (2): Activation(relu) (3): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (5): Activation(relu) (6): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) (conv1): Conv3D(2048 -> 512, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (conv3): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu): Activation(relu) ) (2): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(2048 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (2): Activation(relu) (3): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (5): Activation(relu) (6): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) (conv1): Conv3D(2048 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (conv3): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu): Activation(relu) ) ) ) (st_avg): GlobalAvgPool3D(size=(1, 1, 1), stride=(1, 1, 1), padding=(0, 0, 0), ceil_mode=True, global_pool=True, pool_type=avg, layout=NCDHW) (head): HybridSequential( (0): Dropout(p = 0.5, axes=()) (1): Dense(2048 -> 400, linear) ) (fc): Dense(2048 -> 400, linear) ) Load 240618 training samples and 19404 validation samples. 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accuracy=21.724347 loss=3.776523 lr=0.010000 Epoch[000] Batch [3399]/[3759] Speed: 65.650208 samples/sec accuracy=21.870864 loss=3.766951 lr=0.010000 Epoch[000] Batch [3449]/[3759] Speed: 65.912272 samples/sec accuracy=22.009511 loss=3.757233 lr=0.010000 Epoch[000] Batch [3499]/[3759] Speed: 65.702701 samples/sec accuracy=22.139286 loss=3.747620 lr=0.010000 Epoch[000] Batch [3549]/[3759] Speed: 65.344471 samples/sec accuracy=22.278609 loss=3.738399 lr=0.010000 Epoch[000] Batch [3599]/[3759] Speed: 65.755600 samples/sec accuracy=22.409722 loss=3.730064 lr=0.010000 Epoch[000] Batch [3649]/[3759] Speed: 65.635647 samples/sec accuracy=22.529966 loss=3.721340 lr=0.010000 Epoch[000] Batch [3699]/[3759] Speed: 64.818873 samples/sec accuracy=22.640203 loss=3.713848 lr=0.010000 Epoch[000] Batch [3749]/[3759] Speed: 72.765360 samples/sec accuracy=22.779167 loss=3.704666 lr=0.010000 Batch [0049]/[0303]: acc-top1=33.312500 acc-top5=59.562500 Batch [0099]/[0303]: acc-top1=33.250000 acc-top5=59.890625 Batch [0149]/[0303]: acc-top1=33.177083 acc-top5=60.156250 Batch [0199]/[0303]: acc-top1=33.554688 acc-top5=60.406250 Batch [0249]/[0303]: acc-top1=33.593750 acc-top5=60.250000 Batch [0299]/[0303]: acc-top1=33.385417 acc-top5=60.171875 [Epoch 000] training: accuracy=22.799864 loss=3.703060 [Epoch 000] speed: 64 samples/sec time cost: 4022.711087 [Epoch 000] validation: acc-top1=33.400371 acc-top5=60.225866 loss=3.070485 Epoch[001] Batch [0049]/[3760] Speed: 45.061387 samples/sec accuracy=32.718750 loss=2.990017 lr=0.010000 Epoch[001] Batch [0099]/[3760] Speed: 65.570468 samples/sec accuracy=33.453125 loss=2.974998 lr=0.010000 Epoch[001] Batch [0149]/[3760] Speed: 66.704636 samples/sec accuracy=33.572917 loss=2.972489 lr=0.010000 Epoch[001] Batch [0199]/[3760] Speed: 66.426076 samples/sec accuracy=33.992188 loss=2.958024 lr=0.010000 Epoch[001] Batch [0249]/[3760] Speed: 65.725380 samples/sec accuracy=34.037500 loss=2.956764 lr=0.010000 Epoch[001] Batch [0299]/[3760] 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accuracy=36.858941 loss=2.799250 lr=0.010000 Epoch[001] Batch [3649]/[3760] Speed: 66.265375 samples/sec accuracy=36.887414 loss=2.797265 lr=0.010000 Epoch[001] Batch [3699]/[3760] Speed: 65.911658 samples/sec accuracy=36.930743 loss=2.795348 lr=0.010000 Epoch[001] Batch [3749]/[3760] Speed: 72.913384 samples/sec accuracy=36.973333 loss=2.793089 lr=0.010000 Batch [0049]/[0303]: acc-top1=44.343750 acc-top5=69.906250 Batch [0099]/[0303]: acc-top1=43.609375 acc-top5=69.421875 Batch [0149]/[0303]: acc-top1=43.510417 acc-top5=69.833333 Batch [0199]/[0303]: acc-top1=43.382812 acc-top5=70.039062 Batch [0249]/[0303]: acc-top1=43.568750 acc-top5=69.993750 Batch [0299]/[0303]: acc-top1=43.114583 acc-top5=70.083333 [Epoch 001] training: accuracy=36.992603 loss=2.792127 [Epoch 001] speed: 65 samples/sec time cost: 3958.035381 [Epoch 001] validation: acc-top1=43.141502 acc-top5=70.132013 loss=2.549732 Epoch[002] Batch [0049]/[3759] Speed: 45.387813 samples/sec accuracy=41.875000 loss=2.565977 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acc-top1=47.257812 acc-top5=72.929688 Batch [0249]/[0303]: acc-top1=47.312500 acc-top5=72.806250 Batch [0299]/[0303]: acc-top1=47.197917 acc-top5=72.963542 [Epoch 002] training: accuracy=42.733689 loss=2.485091 [Epoch 002] speed: 65 samples/sec time cost: 3952.653082 [Epoch 002] validation: acc-top1=47.251444 acc-top5=73.024959 loss=2.310221 Epoch[003] Batch [0049]/[3760] Speed: 45.060396 samples/sec accuracy=44.281250 loss=2.330793 lr=0.010000 Epoch[003] Batch [0099]/[3760] Speed: 66.120361 samples/sec accuracy=44.734375 loss=2.347545 lr=0.010000 Epoch[003] Batch [0149]/[3760] Speed: 66.433394 samples/sec accuracy=44.989583 loss=2.342646 lr=0.010000 Epoch[003] Batch [0199]/[3760] Speed: 65.836197 samples/sec accuracy=45.476562 loss=2.327009 lr=0.010000 Epoch[003] Batch [0249]/[3760] Speed: 66.378690 samples/sec accuracy=45.543750 loss=2.316140 lr=0.010000 Epoch[003] Batch [0299]/[3760] Speed: 66.505922 samples/sec accuracy=45.635417 loss=2.320454 lr=0.010000 Epoch[003] Batch 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accuracy=46.004709 loss=2.314203 lr=0.010000 Epoch[003] Batch [3699]/[3760] Speed: 66.762795 samples/sec accuracy=46.024916 loss=2.313173 lr=0.010000 Epoch[003] Batch [3749]/[3760] Speed: 72.943853 samples/sec accuracy=46.041250 loss=2.312150 lr=0.010000 Batch [0049]/[0303]: acc-top1=49.218750 acc-top5=75.343750 Batch [0099]/[0303]: acc-top1=48.781250 acc-top5=74.890625 Batch [0149]/[0303]: acc-top1=48.989583 acc-top5=74.812500 Batch [0199]/[0303]: acc-top1=49.242188 acc-top5=75.156250 Batch [0249]/[0303]: acc-top1=49.437500 acc-top5=74.950000 Batch [0299]/[0303]: acc-top1=49.359375 acc-top5=75.020833 [Epoch 003] training: accuracy=46.045545 loss=2.311885 [Epoch 003] speed: 65 samples/sec time cost: 3945.668601 [Epoch 003] validation: acc-top1=49.406972 acc-top5=75.056724 loss=2.250499 Epoch[004] Batch [0049]/[3760] Speed: 44.810917 samples/sec accuracy=49.218750 loss=2.173974 lr=0.010000 Epoch[004] Batch [0099]/[3760] Speed: 65.223305 samples/sec accuracy=48.328125 loss=2.201874 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lr=0.010000 Epoch[004] Batch [2999]/[3760] Speed: 66.636282 samples/sec accuracy=48.517187 loss=2.189434 lr=0.010000 Epoch[004] Batch [3049]/[3760] Speed: 66.569397 samples/sec accuracy=48.523053 loss=2.189525 lr=0.010000 Epoch[004] Batch [3099]/[3760] Speed: 66.126393 samples/sec accuracy=48.540323 loss=2.188234 lr=0.010000 Epoch[004] Batch [3149]/[3760] Speed: 66.403300 samples/sec accuracy=48.536706 loss=2.187809 lr=0.010000 Epoch[004] Batch [3199]/[3760] Speed: 66.667565 samples/sec accuracy=48.564453 loss=2.186301 lr=0.010000 Epoch[004] Batch [3249]/[3760] Speed: 66.453044 samples/sec accuracy=48.581250 loss=2.186103 lr=0.010000 Epoch[004] Batch [3299]/[3760] Speed: 66.071657 samples/sec accuracy=48.602273 loss=2.185516 lr=0.010000 Epoch[004] Batch [3349]/[3760] Speed: 67.381244 samples/sec accuracy=48.628265 loss=2.184269 lr=0.010000 Epoch[004] Batch [3399]/[3760] Speed: 66.172812 samples/sec accuracy=48.636029 loss=2.183587 lr=0.010000 Epoch[004] Batch [3449]/[3760] Speed: 65.949064 samples/sec accuracy=48.640851 loss=2.183715 lr=0.010000 Epoch[004] Batch [3499]/[3760] Speed: 67.129824 samples/sec accuracy=48.639732 loss=2.184283 lr=0.010000 Epoch[004] Batch [3549]/[3760] Speed: 66.156306 samples/sec accuracy=48.649648 loss=2.183544 lr=0.010000 Epoch[004] Batch [3599]/[3760] Speed: 66.730829 samples/sec accuracy=48.654514 loss=2.183220 lr=0.010000 Epoch[004] Batch [3649]/[3760] Speed: 66.287851 samples/sec accuracy=48.652825 loss=2.183168 lr=0.010000 Epoch[004] Batch [3699]/[3760] Speed: 66.761459 samples/sec accuracy=48.656250 loss=2.183787 lr=0.010000 Epoch[004] Batch [3749]/[3760] Speed: 72.681479 samples/sec accuracy=48.675417 loss=2.183665 lr=0.010000 Batch [0049]/[0303]: acc-top1=51.000000 acc-top5=76.218750 Batch [0099]/[0303]: acc-top1=51.109375 acc-top5=76.406250 Batch [0149]/[0303]: acc-top1=50.937500 acc-top5=76.614583 Batch [0199]/[0303]: acc-top1=51.265625 acc-top5=76.968750 Batch [0249]/[0303]: acc-top1=51.393750 acc-top5=76.768750 Batch [0299]/[0303]: acc-top1=51.291667 acc-top5=76.953125 [Epoch 004] training: accuracy=48.681433 loss=2.183463 [Epoch 004] speed: 66 samples/sec time cost: 3938.129095 [Epoch 004] validation: acc-top1=51.304662 acc-top5=76.949257 loss=2.133864 Epoch[005] Batch [0049]/[3759] Speed: 45.059850 samples/sec accuracy=50.062500 loss=2.134347 lr=0.010000 Epoch[005] Batch [0099]/[3759] Speed: 65.627289 samples/sec accuracy=50.171875 loss=2.124809 lr=0.010000 Epoch[005] Batch [0149]/[3759] Speed: 66.820818 samples/sec accuracy=50.395833 loss=2.099400 lr=0.010000 Epoch[005] Batch [0199]/[3759] Speed: 66.532989 samples/sec accuracy=50.476562 loss=2.086395 lr=0.010000 Epoch[005] Batch [0249]/[3759] Speed: 66.538977 samples/sec accuracy=50.587500 loss=2.080281 lr=0.010000 Epoch[005] Batch [0299]/[3759] Speed: 66.801285 samples/sec accuracy=50.593750 loss=2.076762 lr=0.010000 Epoch[005] Batch [0349]/[3759] Speed: 66.130309 samples/sec accuracy=50.696429 loss=2.071951 lr=0.010000 Epoch[005] Batch 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accuracy=50.430147 loss=2.078646 lr=0.010000 Epoch[005] Batch [0899]/[3759] Speed: 65.579379 samples/sec accuracy=50.461806 loss=2.077428 lr=0.010000 Epoch[005] Batch [0949]/[3759] Speed: 66.726879 samples/sec accuracy=50.493421 loss=2.075481 lr=0.010000 Epoch[005] Batch [0999]/[3759] Speed: 67.088457 samples/sec accuracy=50.568750 loss=2.073226 lr=0.010000 Epoch[005] Batch [1049]/[3759] Speed: 66.836566 samples/sec accuracy=50.508929 loss=2.075457 lr=0.010000 Epoch[005] Batch [1099]/[3759] Speed: 66.483334 samples/sec accuracy=50.507102 loss=2.076275 lr=0.010000 Epoch[005] Batch [1149]/[3759] Speed: 66.697441 samples/sec accuracy=50.508152 loss=2.077268 lr=0.010000 Epoch[005] Batch [1199]/[3759] Speed: 67.088719 samples/sec accuracy=50.569010 loss=2.075238 lr=0.010000 Epoch[005] Batch [1249]/[3759] Speed: 66.926175 samples/sec accuracy=50.571250 loss=2.075496 lr=0.010000 Epoch[005] Batch [1299]/[3759] Speed: 67.239877 samples/sec accuracy=50.526442 loss=2.078195 lr=0.010000 Epoch[005] 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accuracy=50.441840 loss=2.084105 lr=0.010000 Epoch[005] Batch [1849]/[3759] Speed: 66.479114 samples/sec accuracy=50.389358 loss=2.085934 lr=0.010000 Epoch[005] Batch [1899]/[3759] Speed: 66.818375 samples/sec accuracy=50.365132 loss=2.086912 lr=0.010000 Epoch[005] Batch [1949]/[3759] Speed: 67.398515 samples/sec accuracy=50.316506 loss=2.089354 lr=0.010000 Epoch[005] Batch [1999]/[3759] Speed: 66.378996 samples/sec accuracy=50.307031 loss=2.090303 lr=0.010000 Epoch[005] Batch [2049]/[3759] Speed: 66.916441 samples/sec accuracy=50.303354 loss=2.091633 lr=0.010000 Epoch[005] Batch [2099]/[3759] Speed: 66.526759 samples/sec accuracy=50.293899 loss=2.092099 lr=0.010000 Epoch[005] Batch [2149]/[3759] Speed: 66.361080 samples/sec accuracy=50.293605 loss=2.092170 lr=0.010000 Epoch[005] Batch [2199]/[3759] Speed: 66.661592 samples/sec accuracy=50.316051 loss=2.092629 lr=0.010000 Epoch[005] Batch [2249]/[3759] Speed: 67.193306 samples/sec accuracy=50.334028 loss=2.093379 lr=0.010000 Epoch[005] 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accuracy=50.371591 loss=2.094177 lr=0.010000 Epoch[005] Batch [2799]/[3759] Speed: 66.651571 samples/sec accuracy=50.392299 loss=2.093198 lr=0.010000 Epoch[005] Batch [2849]/[3759] Speed: 66.880375 samples/sec accuracy=50.397478 loss=2.092872 lr=0.010000 Epoch[005] Batch [2899]/[3759] Speed: 66.526066 samples/sec accuracy=50.420797 loss=2.092333 lr=0.010000 Epoch[005] Batch [2949]/[3759] Speed: 66.365167 samples/sec accuracy=50.426907 loss=2.092375 lr=0.010000 Epoch[005] Batch [2999]/[3759] Speed: 66.359976 samples/sec accuracy=50.435417 loss=2.091085 lr=0.010000 Epoch[005] Batch [3049]/[3759] Speed: 67.067473 samples/sec accuracy=50.439549 loss=2.091458 lr=0.010000 Epoch[005] Batch [3099]/[3759] Speed: 66.536377 samples/sec accuracy=50.430444 loss=2.091144 lr=0.010000 Epoch[005] Batch [3149]/[3759] Speed: 66.990866 samples/sec accuracy=50.446925 loss=2.090037 lr=0.010000 Epoch[005] Batch [3199]/[3759] Speed: 66.512113 samples/sec accuracy=50.443359 loss=2.090792 lr=0.010000 Epoch[005] Batch [3249]/[3759] Speed: 66.693921 samples/sec accuracy=50.466346 loss=2.090076 lr=0.010000 Epoch[005] Batch [3299]/[3759] Speed: 67.443706 samples/sec accuracy=50.485322 loss=2.090197 lr=0.010000 Epoch[005] Batch [3349]/[3759] Speed: 66.697031 samples/sec accuracy=50.501399 loss=2.089245 lr=0.010000 Epoch[005] Batch [3399]/[3759] Speed: 66.172905 samples/sec accuracy=50.487132 loss=2.089164 lr=0.010000 Epoch[005] Batch [3449]/[3759] Speed: 66.732898 samples/sec accuracy=50.501359 loss=2.087924 lr=0.010000 Epoch[005] Batch [3499]/[3759] Speed: 66.751209 samples/sec accuracy=50.526786 loss=2.087298 lr=0.010000 Epoch[005] Batch [3549]/[3759] Speed: 66.808603 samples/sec accuracy=50.534771 loss=2.086947 lr=0.010000 Epoch[005] Batch [3599]/[3759] Speed: 67.421703 samples/sec accuracy=50.535156 loss=2.087117 lr=0.010000 Epoch[005] Batch [3649]/[3759] Speed: 66.780583 samples/sec accuracy=50.542808 loss=2.086823 lr=0.010000 Epoch[005] Batch [3699]/[3759] Speed: 66.459752 samples/sec accuracy=50.525760 loss=2.087149 lr=0.010000 Epoch[005] Batch [3749]/[3759] Speed: 73.371454 samples/sec accuracy=50.533750 loss=2.086778 lr=0.010000 Batch [0049]/[0303]: acc-top1=53.000000 acc-top5=76.750000 Batch [0099]/[0303]: acc-top1=52.531250 acc-top5=76.593750 Batch [0149]/[0303]: acc-top1=52.281250 acc-top5=76.708333 Batch [0199]/[0303]: acc-top1=52.468750 acc-top5=77.226562 Batch [0249]/[0303]: acc-top1=52.587500 acc-top5=77.212500 Batch [0299]/[0303]: acc-top1=52.609375 acc-top5=77.390625 [Epoch 005] training: accuracy=50.540370 loss=2.086569 [Epoch 005] speed: 66 samples/sec time cost: 3924.128258 [Epoch 005] validation: acc-top1=52.640264 acc-top5=77.397896 loss=2.101635 Epoch[006] Batch [0049]/[3760] Speed: 45.855582 samples/sec accuracy=53.343750 loss=1.977458 lr=0.010000 Epoch[006] Batch [0099]/[3760] Speed: 65.870906 samples/sec accuracy=53.312500 loss=1.985866 lr=0.010000 Epoch[006] Batch [0149]/[3760] Speed: 67.576608 samples/sec accuracy=53.354167 loss=1.985308 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lr=0.010000 Epoch[006] Batch [2099]/[3760] Speed: 66.079507 samples/sec accuracy=52.151042 loss=2.013941 lr=0.010000 Epoch[006] Batch [2149]/[3760] Speed: 66.879351 samples/sec accuracy=52.167151 loss=2.013462 lr=0.010000 Epoch[006] Batch [2199]/[3760] Speed: 66.478727 samples/sec accuracy=52.157670 loss=2.013828 lr=0.010000 Epoch[006] Batch [2249]/[3760] Speed: 66.755214 samples/sec accuracy=52.143056 loss=2.013837 lr=0.010000 Epoch[006] Batch [2299]/[3760] Speed: 66.835713 samples/sec accuracy=52.138587 loss=2.014439 lr=0.010000 Epoch[006] Batch [2349]/[3760] Speed: 66.679324 samples/sec accuracy=52.139628 loss=2.014054 lr=0.010000 Epoch[006] Batch [2399]/[3760] Speed: 67.021322 samples/sec accuracy=52.113932 loss=2.014438 lr=0.010000 Epoch[006] Batch [2449]/[3760] Speed: 66.727473 samples/sec accuracy=52.093750 loss=2.014829 lr=0.010000 Epoch[006] Batch [2499]/[3760] Speed: 67.316148 samples/sec accuracy=52.093125 loss=2.015268 lr=0.010000 Epoch[006] Batch [2549]/[3760] Speed: 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lr=0.010000 Epoch[006] Batch [3049]/[3760] Speed: 67.313471 samples/sec accuracy=52.106045 loss=2.017681 lr=0.010000 Epoch[006] Batch [3099]/[3760] Speed: 66.922769 samples/sec accuracy=52.129032 loss=2.016822 lr=0.010000 Epoch[006] Batch [3149]/[3760] Speed: 67.139983 samples/sec accuracy=52.098214 loss=2.017678 lr=0.010000 Epoch[006] Batch [3199]/[3760] Speed: 66.029606 samples/sec accuracy=52.088379 loss=2.017743 lr=0.010000 Epoch[006] Batch [3249]/[3760] Speed: 66.035215 samples/sec accuracy=52.074038 loss=2.018217 lr=0.010000 Epoch[006] Batch [3299]/[3760] Speed: 66.787398 samples/sec accuracy=52.110322 loss=2.016808 lr=0.010000 Epoch[006] Batch [3349]/[3760] Speed: 66.453270 samples/sec accuracy=52.123134 loss=2.016359 lr=0.010000 Epoch[006] Batch [3399]/[3760] Speed: 66.055563 samples/sec accuracy=52.134651 loss=2.015746 lr=0.010000 Epoch[006] Batch [3449]/[3760] Speed: 67.002399 samples/sec accuracy=52.138587 loss=2.014624 lr=0.010000 Epoch[006] Batch [3499]/[3760] Speed: 67.180181 samples/sec accuracy=52.141964 loss=2.014698 lr=0.010000 Epoch[006] Batch [3549]/[3760] Speed: 66.286412 samples/sec accuracy=52.141725 loss=2.014692 lr=0.010000 Epoch[006] Batch [3599]/[3760] Speed: 66.922793 samples/sec accuracy=52.142361 loss=2.014594 lr=0.010000 Epoch[006] Batch [3649]/[3760] Speed: 66.321368 samples/sec accuracy=52.150685 loss=2.014616 lr=0.010000 Epoch[006] Batch [3699]/[3760] Speed: 67.164546 samples/sec accuracy=52.144848 loss=2.015235 lr=0.010000 Epoch[006] Batch [3749]/[3760] Speed: 73.621406 samples/sec accuracy=52.137500 loss=2.016208 lr=0.010000 Batch [0049]/[0303]: acc-top1=53.750000 acc-top5=78.031250 Batch [0099]/[0303]: acc-top1=52.703125 acc-top5=77.500000 Batch [0149]/[0303]: acc-top1=53.000000 acc-top5=77.666667 Batch [0199]/[0303]: acc-top1=53.156250 acc-top5=77.851562 Batch [0249]/[0303]: acc-top1=53.187500 acc-top5=77.806250 Batch [0299]/[0303]: acc-top1=53.104167 acc-top5=77.958333 [Epoch 006] training: accuracy=52.137633 loss=2.016154 [Epoch 006] speed: 66 samples/sec time cost: 3921.192166 [Epoch 006] validation: acc-top1=53.109530 acc-top5=77.965140 loss=2.076497 Epoch[007] Batch [0049]/[3760] Speed: 44.934705 samples/sec accuracy=54.625000 loss=1.904903 lr=0.010000 Epoch[007] Batch [0099]/[3760] Speed: 66.317908 samples/sec accuracy=53.984375 loss=1.914634 lr=0.010000 Epoch[007] Batch [0149]/[3760] Speed: 67.278514 samples/sec accuracy=54.302083 loss=1.920242 lr=0.010000 Epoch[007] Batch [0199]/[3760] Speed: 66.745494 samples/sec accuracy=54.031250 loss=1.913177 lr=0.010000 Epoch[007] Batch [0249]/[3760] Speed: 67.194599 samples/sec accuracy=54.243750 loss=1.908883 lr=0.010000 Epoch[007] Batch [0299]/[3760] Speed: 66.811863 samples/sec accuracy=54.046875 loss=1.915028 lr=0.010000 Epoch[007] Batch [0349]/[3760] Speed: 66.363960 samples/sec accuracy=54.075893 loss=1.920427 lr=0.010000 Epoch[007] Batch [0399]/[3760] Speed: 66.962105 samples/sec accuracy=53.996094 loss=1.927639 lr=0.010000 Epoch[007] Batch 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accuracy=53.713542 loss=1.936248 lr=0.010000 Epoch[007] Batch [0949]/[3760] Speed: 66.409389 samples/sec accuracy=53.674342 loss=1.937878 lr=0.010000 Epoch[007] Batch [0999]/[3760] Speed: 67.298067 samples/sec accuracy=53.648438 loss=1.937769 lr=0.010000 Epoch[007] Batch [1049]/[3760] Speed: 67.200690 samples/sec accuracy=53.669643 loss=1.938556 lr=0.010000 Epoch[007] Batch [1099]/[3760] Speed: 66.304994 samples/sec accuracy=53.637784 loss=1.938399 lr=0.010000 Epoch[007] Batch [1149]/[3760] Speed: 67.018014 samples/sec accuracy=53.626359 loss=1.939389 lr=0.010000 Epoch[007] Batch [1199]/[3760] Speed: 66.672224 samples/sec accuracy=53.644531 loss=1.938469 lr=0.010000 Epoch[007] Batch [1249]/[3760] Speed: 66.928905 samples/sec accuracy=53.682500 loss=1.937739 lr=0.010000 Epoch[007] Batch [1299]/[3760] Speed: 67.726717 samples/sec accuracy=53.673077 loss=1.938109 lr=0.010000 Epoch[007] Batch [1349]/[3760] Speed: 66.602487 samples/sec accuracy=53.665509 loss=1.938947 lr=0.010000 Epoch[007] 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accuracy=53.684122 loss=1.944582 lr=0.010000 Epoch[007] Batch [1899]/[3760] Speed: 67.059512 samples/sec accuracy=53.704770 loss=1.943437 lr=0.010000 Epoch[007] Batch [1949]/[3760] Speed: 66.872605 samples/sec accuracy=53.710737 loss=1.942892 lr=0.010000 Epoch[007] Batch [1999]/[3760] Speed: 66.554087 samples/sec accuracy=53.675781 loss=1.944525 lr=0.010000 Epoch[007] Batch [2049]/[3760] Speed: 66.588352 samples/sec accuracy=53.672256 loss=1.945568 lr=0.010000 Epoch[007] Batch [2099]/[3760] Speed: 66.731043 samples/sec accuracy=53.631696 loss=1.946204 lr=0.010000 Epoch[007] Batch [2149]/[3760] Speed: 66.949945 samples/sec accuracy=53.628634 loss=1.946776 lr=0.010000 Epoch[007] Batch [2199]/[3760] Speed: 66.454903 samples/sec accuracy=53.628551 loss=1.946110 lr=0.010000 Epoch[007] Batch [2249]/[3760] Speed: 67.752602 samples/sec accuracy=53.622917 loss=1.945921 lr=0.010000 Epoch[007] Batch [2299]/[3760] Speed: 66.503209 samples/sec accuracy=53.600543 loss=1.947112 lr=0.010000 Epoch[007] 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accuracy=53.487165 loss=1.949055 lr=0.010000 Epoch[007] Batch [2849]/[3760] Speed: 66.926385 samples/sec accuracy=53.483004 loss=1.949206 lr=0.010000 Epoch[007] Batch [2899]/[3760] Speed: 67.314257 samples/sec accuracy=53.505388 loss=1.949080 lr=0.010000 Epoch[007] Batch [2949]/[3760] Speed: 67.352176 samples/sec accuracy=53.508475 loss=1.948644 lr=0.010000 Epoch[007] Batch [2999]/[3760] Speed: 66.743760 samples/sec accuracy=53.486979 loss=1.950082 lr=0.010000 Epoch[007] Batch [3049]/[3760] Speed: 67.121107 samples/sec accuracy=53.489242 loss=1.950513 lr=0.010000 Epoch[007] Batch [3099]/[3760] Speed: 66.942495 samples/sec accuracy=53.490927 loss=1.950491 lr=0.010000 Epoch[007] Batch [3149]/[3760] Speed: 66.628503 samples/sec accuracy=53.513889 loss=1.949798 lr=0.010000 Epoch[007] Batch [3199]/[3760] Speed: 67.035448 samples/sec accuracy=53.500000 loss=1.950904 lr=0.010000 Epoch[007] Batch [3249]/[3760] Speed: 67.429215 samples/sec accuracy=53.491827 loss=1.951177 lr=0.010000 Epoch[007] 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accuracy=53.471667 loss=1.951691 lr=0.010000 Batch [0049]/[0303]: acc-top1=52.375000 acc-top5=78.250000 Batch [0099]/[0303]: acc-top1=52.140625 acc-top5=77.656250 Batch [0149]/[0303]: acc-top1=52.729167 acc-top5=78.052083 Batch [0199]/[0303]: acc-top1=53.289062 acc-top5=78.343750 Batch [0249]/[0303]: acc-top1=53.512500 acc-top5=78.300000 Batch [0299]/[0303]: acc-top1=53.593750 acc-top5=78.416667 [Epoch 007] training: accuracy=53.474900 loss=1.951726 [Epoch 007] speed: 66 samples/sec time cost: 3915.413808 [Epoch 007] validation: acc-top1=53.656147 acc-top5=78.449876 loss=2.015979 Epoch[008] Batch [0049]/[3759] Speed: 45.087735 samples/sec accuracy=54.281250 loss=1.915004 lr=0.010000 Epoch[008] Batch [0099]/[3759] Speed: 66.541093 samples/sec accuracy=54.484375 loss=1.866700 lr=0.010000 Epoch[008] Batch [0149]/[3759] Speed: 67.557614 samples/sec accuracy=54.593750 loss=1.865271 lr=0.010000 Epoch[008] Batch [0199]/[3759] Speed: 67.533685 samples/sec accuracy=54.523438 loss=1.868935 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lr=0.010000 Epoch[008] Batch [3099]/[3759] Speed: 67.112254 samples/sec accuracy=54.347278 loss=1.905189 lr=0.010000 Epoch[008] Batch [3149]/[3759] Speed: 67.392234 samples/sec accuracy=54.355655 loss=1.904969 lr=0.010000 Epoch[008] Batch [3199]/[3759] Speed: 67.071260 samples/sec accuracy=54.345703 loss=1.906013 lr=0.010000 Epoch[008] Batch [3249]/[3759] Speed: 66.926484 samples/sec accuracy=54.338462 loss=1.906291 lr=0.010000 Epoch[008] Batch [3299]/[3759] Speed: 67.058337 samples/sec accuracy=54.348011 loss=1.906598 lr=0.010000 Epoch[008] Batch [3349]/[3759] Speed: 66.999917 samples/sec accuracy=54.339552 loss=1.906812 lr=0.010000 Epoch[008] Batch [3399]/[3759] Speed: 67.174661 samples/sec accuracy=54.345129 loss=1.906711 lr=0.010000 Epoch[008] Batch [3449]/[3759] Speed: 66.988024 samples/sec accuracy=54.352808 loss=1.906222 lr=0.010000 Epoch[008] Batch [3499]/[3759] Speed: 66.970206 samples/sec accuracy=54.384821 loss=1.904908 lr=0.010000 Epoch[008] Batch [3549]/[3759] Speed: 67.761577 samples/sec accuracy=54.374120 loss=1.905213 lr=0.010000 Epoch[008] Batch [3599]/[3759] Speed: 67.159908 samples/sec accuracy=54.390625 loss=1.904883 lr=0.010000 Epoch[008] Batch [3649]/[3759] Speed: 66.736597 samples/sec accuracy=54.387842 loss=1.905139 lr=0.010000 Epoch[008] Batch [3699]/[3759] Speed: 66.914887 samples/sec accuracy=54.379645 loss=1.905203 lr=0.010000 Epoch[008] Batch [3749]/[3759] Speed: 73.813422 samples/sec accuracy=54.370417 loss=1.905900 lr=0.010000 Batch [0049]/[0303]: acc-top1=55.187500 acc-top5=78.750000 Batch [0099]/[0303]: acc-top1=54.734375 acc-top5=78.890625 Batch [0149]/[0303]: acc-top1=54.864583 acc-top5=79.010417 Batch [0199]/[0303]: acc-top1=54.812500 acc-top5=79.273438 Batch [0249]/[0303]: acc-top1=54.856250 acc-top5=79.343750 Batch [0299]/[0303]: acc-top1=54.869792 acc-top5=79.447917 [Epoch 008] training: accuracy=54.372007 loss=1.905764 [Epoch 008] speed: 66 samples/sec time cost: 3897.376425 [Epoch 008] validation: acc-top1=54.862830 acc-top5=79.465759 loss=2.011843 Epoch[009] Batch [0049]/[3760] Speed: 44.810458 samples/sec accuracy=56.156250 loss=1.827995 lr=0.010000 Epoch[009] Batch [0099]/[3760] Speed: 66.570942 samples/sec accuracy=55.843750 loss=1.824193 lr=0.010000 Epoch[009] Batch [0149]/[3760] Speed: 67.298524 samples/sec accuracy=55.958333 loss=1.815101 lr=0.010000 Epoch[009] Batch [0199]/[3760] Speed: 66.982079 samples/sec accuracy=55.921875 loss=1.822150 lr=0.010000 Epoch[009] Batch [0249]/[3760] Speed: 67.431292 samples/sec accuracy=55.950000 loss=1.814594 lr=0.010000 Epoch[009] Batch [0299]/[3760] Speed: 67.169580 samples/sec accuracy=56.020833 loss=1.814094 lr=0.010000 Epoch[009] Batch [0349]/[3760] Speed: 67.596123 samples/sec accuracy=56.165179 loss=1.810312 lr=0.010000 Epoch[009] Batch [0399]/[3760] Speed: 67.595529 samples/sec accuracy=56.082031 loss=1.817021 lr=0.010000 Epoch[009] Batch [0449]/[3760] Speed: 67.389111 samples/sec accuracy=55.913194 loss=1.821668 lr=0.010000 Epoch[009] Batch 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accuracy=55.542763 loss=1.853822 lr=0.010000 Epoch[009] Batch [2899]/[3760] Speed: 68.114561 samples/sec accuracy=55.536638 loss=1.854042 lr=0.010000 Epoch[009] Batch [2949]/[3760] Speed: 66.309936 samples/sec accuracy=55.542903 loss=1.853926 lr=0.010000 Epoch[009] Batch [2999]/[3760] Speed: 67.592613 samples/sec accuracy=55.533854 loss=1.854345 lr=0.010000 Epoch[009] Batch [3049]/[3760] Speed: 67.579204 samples/sec accuracy=55.509221 loss=1.855576 lr=0.010000 Epoch[009] Batch [3099]/[3760] Speed: 67.296647 samples/sec accuracy=55.485383 loss=1.856183 lr=0.010000 Epoch[009] Batch [3149]/[3760] Speed: 66.863634 samples/sec accuracy=55.472222 loss=1.856567 lr=0.010000 Epoch[009] Batch [3199]/[3760] Speed: 67.635669 samples/sec accuracy=55.477051 loss=1.856339 lr=0.010000 Epoch[009] Batch [3249]/[3760] Speed: 66.924489 samples/sec accuracy=55.463942 loss=1.856836 lr=0.010000 Epoch[009] Batch [3299]/[3760] Speed: 67.244386 samples/sec accuracy=55.461648 loss=1.857560 lr=0.010000 Epoch[009] 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[0099]/[0303]: acc-top1=55.250000 acc-top5=79.265625 Batch [0149]/[0303]: acc-top1=55.385417 acc-top5=79.520833 Batch [0199]/[0303]: acc-top1=55.570312 acc-top5=79.937500 Batch [0249]/[0303]: acc-top1=55.662500 acc-top5=79.812500 Batch [0299]/[0303]: acc-top1=55.661458 acc-top5=79.958333 [Epoch 009] training: accuracy=55.498670 loss=1.856155 [Epoch 009] speed: 66 samples/sec time cost: 3894.891801 [Epoch 009] validation: acc-top1=55.682756 acc-top5=79.976279 loss=1.977344 Epoch[010] Batch [0049]/[3760] Speed: 45.017453 samples/sec accuracy=58.437500 loss=1.726932 lr=0.010000 Epoch[010] Batch [0099]/[3760] Speed: 66.755696 samples/sec accuracy=57.593750 loss=1.751661 lr=0.010000 Epoch[010] Batch [0149]/[3760] Speed: 67.691077 samples/sec accuracy=56.906250 loss=1.781635 lr=0.010000 Epoch[010] Batch [0199]/[3760] Speed: 67.488856 samples/sec accuracy=56.281250 loss=1.803115 lr=0.010000 Epoch[010] Batch [0249]/[3760] Speed: 67.514387 samples/sec accuracy=56.325000 loss=1.800220 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lr=0.010000 Epoch[010] Batch [2199]/[3760] Speed: 67.331469 samples/sec accuracy=56.231534 loss=1.814450 lr=0.010000 Epoch[010] Batch [2249]/[3760] Speed: 66.897982 samples/sec accuracy=56.243750 loss=1.814651 lr=0.010000 Epoch[010] Batch [2299]/[3760] Speed: 67.256718 samples/sec accuracy=56.260190 loss=1.813371 lr=0.010000 Epoch[010] Batch [2349]/[3760] Speed: 67.507900 samples/sec accuracy=56.249335 loss=1.813694 lr=0.010000 Epoch[010] Batch [2399]/[3760] Speed: 67.490184 samples/sec accuracy=56.245443 loss=1.813934 lr=0.010000 Epoch[010] Batch [2449]/[3760] Speed: 66.852396 samples/sec accuracy=56.229592 loss=1.813926 lr=0.010000 Epoch[010] Batch [2499]/[3760] Speed: 67.851073 samples/sec accuracy=56.205625 loss=1.814263 lr=0.010000 Epoch[010] Batch [2549]/[3760] Speed: 67.164314 samples/sec accuracy=56.189951 loss=1.813901 lr=0.010000 Epoch[010] Batch [2599]/[3760] Speed: 66.890942 samples/sec accuracy=56.164062 loss=1.814489 lr=0.010000 Epoch[010] Batch [2649]/[3760] Speed: 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lr=0.010000 Epoch[010] Batch [3149]/[3760] Speed: 67.349407 samples/sec accuracy=56.126984 loss=1.817874 lr=0.010000 Epoch[010] Batch [3199]/[3760] Speed: 67.157739 samples/sec accuracy=56.143066 loss=1.817371 lr=0.010000 Epoch[010] Batch [3249]/[3760] Speed: 66.749244 samples/sec accuracy=56.149519 loss=1.817413 lr=0.010000 Epoch[010] Batch [3299]/[3760] Speed: 67.524925 samples/sec accuracy=56.156723 loss=1.817273 lr=0.010000 Epoch[010] Batch [3349]/[3760] Speed: 66.814931 samples/sec accuracy=56.173974 loss=1.816598 lr=0.010000 Epoch[010] Batch [3399]/[3760] Speed: 67.074795 samples/sec accuracy=56.163603 loss=1.817345 lr=0.010000 Epoch[010] Batch [3449]/[3760] Speed: 67.662425 samples/sec accuracy=56.150362 loss=1.817884 lr=0.010000 Epoch[010] Batch [3499]/[3760] Speed: 67.031929 samples/sec accuracy=56.162500 loss=1.817932 lr=0.010000 Epoch[010] Batch [3549]/[3760] Speed: 67.131714 samples/sec accuracy=56.164173 loss=1.817883 lr=0.010000 Epoch[010] Batch [3599]/[3760] Speed: 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accuracy=57.718750 loss=1.750421 lr=0.010000 Epoch[011] Batch [0099]/[3759] Speed: 66.704000 samples/sec accuracy=57.125000 loss=1.765264 lr=0.010000 Epoch[011] Batch [0149]/[3759] Speed: 66.776656 samples/sec accuracy=57.520833 loss=1.753896 lr=0.010000 Epoch[011] Batch [0199]/[3759] Speed: 66.911236 samples/sec accuracy=57.609375 loss=1.757810 lr=0.010000 Epoch[011] Batch [0249]/[3759] Speed: 66.984229 samples/sec accuracy=57.400000 loss=1.764940 lr=0.010000 Epoch[011] Batch [0299]/[3759] Speed: 67.886427 samples/sec accuracy=57.494792 loss=1.752581 lr=0.010000 Epoch[011] Batch [0349]/[3759] Speed: 66.988798 samples/sec accuracy=57.459821 loss=1.752247 lr=0.010000 Epoch[011] Batch [0399]/[3759] Speed: 66.777860 samples/sec accuracy=57.351562 loss=1.756113 lr=0.010000 Epoch[011] Batch [0449]/[3759] Speed: 67.977820 samples/sec accuracy=57.118056 loss=1.764976 lr=0.010000 Epoch[011] Batch [0499]/[3759] Speed: 67.025957 samples/sec accuracy=57.096875 loss=1.769963 lr=0.010000 Epoch[011] 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accuracy=56.852371 loss=1.782372 lr=0.010000 Epoch[011] Batch [2949]/[3759] Speed: 67.593970 samples/sec accuracy=56.816208 loss=1.784064 lr=0.010000 Epoch[011] Batch [2999]/[3759] Speed: 67.173568 samples/sec accuracy=56.835417 loss=1.783087 lr=0.010000 Epoch[011] Batch [3049]/[3759] Speed: 66.948768 samples/sec accuracy=56.809939 loss=1.784207 lr=0.010000 Epoch[011] Batch [3099]/[3759] Speed: 67.061615 samples/sec accuracy=56.813508 loss=1.783992 lr=0.010000 Epoch[011] Batch [3149]/[3759] Speed: 67.465365 samples/sec accuracy=56.831349 loss=1.783641 lr=0.010000 Epoch[011] Batch [3199]/[3759] Speed: 66.932762 samples/sec accuracy=56.825684 loss=1.783768 lr=0.010000 Epoch[011] Batch [3249]/[3759] Speed: 67.146783 samples/sec accuracy=56.832692 loss=1.783220 lr=0.010000 Epoch[011] Batch [3299]/[3759] Speed: 66.754684 samples/sec accuracy=56.816761 loss=1.784474 lr=0.010000 Epoch[011] Batch [3349]/[3759] Speed: 67.553076 samples/sec accuracy=56.822295 loss=1.784971 lr=0.010000 Epoch[011] Batch [3399]/[3759] Speed: 66.772446 samples/sec accuracy=56.817096 loss=1.785366 lr=0.010000 Epoch[011] Batch [3449]/[3759] Speed: 67.313461 samples/sec accuracy=56.816576 loss=1.785620 lr=0.010000 Epoch[011] Batch [3499]/[3759] Speed: 67.146957 samples/sec accuracy=56.817411 loss=1.786229 lr=0.010000 Epoch[011] Batch [3549]/[3759] Speed: 67.795096 samples/sec accuracy=56.819542 loss=1.786137 lr=0.010000 Epoch[011] Batch [3599]/[3759] Speed: 66.725356 samples/sec accuracy=56.822049 loss=1.785815 lr=0.010000 Epoch[011] Batch [3649]/[3759] Speed: 67.169417 samples/sec accuracy=56.812500 loss=1.786099 lr=0.010000 Epoch[011] Batch [3699]/[3759] Speed: 67.302573 samples/sec accuracy=56.797720 loss=1.786337 lr=0.010000 Epoch[011] Batch [3749]/[3759] Speed: 74.194526 samples/sec accuracy=56.797083 loss=1.786253 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.375000 acc-top5=80.562500 Batch [0099]/[0303]: acc-top1=56.515625 acc-top5=80.406250 Batch [0149]/[0303]: acc-top1=56.708333 acc-top5=80.531250 Batch [0199]/[0303]: acc-top1=56.929688 acc-top5=80.843750 Batch [0249]/[0303]: acc-top1=57.131250 acc-top5=80.856250 Batch [0299]/[0303]: acc-top1=57.244792 acc-top5=80.916667 [Epoch 011] training: accuracy=56.804918 loss=1.785963 [Epoch 011] speed: 66 samples/sec time cost: 3893.269943 [Epoch 011] validation: acc-top1=57.291667 acc-top5=80.935437 loss=1.902600 Epoch[012] Batch [0049]/[3760] Speed: 45.149590 samples/sec accuracy=58.468750 loss=1.692392 lr=0.010000 Epoch[012] Batch [0099]/[3760] Speed: 66.333958 samples/sec accuracy=58.468750 loss=1.694744 lr=0.010000 Epoch[012] Batch [0149]/[3760] Speed: 67.568945 samples/sec accuracy=58.645833 loss=1.694637 lr=0.010000 Epoch[012] Batch [0199]/[3760] Speed: 67.122397 samples/sec accuracy=58.734375 loss=1.699437 lr=0.010000 Epoch[012] Batch [0249]/[3760] Speed: 65.864383 samples/sec accuracy=58.737500 loss=1.698443 lr=0.010000 Epoch[012] Batch [0299]/[3760] Speed: 66.831688 samples/sec accuracy=58.520833 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lr=0.010000 Epoch[013] Batch [3449]/[3760] Speed: 67.223222 samples/sec accuracy=58.210598 loss=1.724358 lr=0.010000 Epoch[013] Batch [3499]/[3760] Speed: 67.817608 samples/sec accuracy=58.192857 loss=1.725072 lr=0.010000 Epoch[013] Batch [3549]/[3760] Speed: 66.688415 samples/sec accuracy=58.206866 loss=1.724859 lr=0.010000 Epoch[013] Batch [3599]/[3760] Speed: 67.185214 samples/sec accuracy=58.210938 loss=1.724909 lr=0.010000 Epoch[013] Batch [3649]/[3760] Speed: 66.514806 samples/sec accuracy=58.214041 loss=1.724916 lr=0.010000 Epoch[013] Batch [3699]/[3760] Speed: 67.362194 samples/sec accuracy=58.216216 loss=1.724868 lr=0.010000 Epoch[013] Batch [3749]/[3760] Speed: 74.147761 samples/sec accuracy=58.185417 loss=1.726111 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.687500 acc-top5=80.187500 Batch [0099]/[0303]: acc-top1=56.796875 acc-top5=79.984375 Batch [0149]/[0303]: acc-top1=56.885417 acc-top5=80.500000 Batch [0199]/[0303]: acc-top1=57.242188 acc-top5=80.835938 Batch [0249]/[0303]: acc-top1=57.150000 acc-top5=80.743750 Batch [0299]/[0303]: acc-top1=57.239583 acc-top5=81.026042 [Epoch 013] training: accuracy=58.183594 loss=1.726130 [Epoch 013] speed: 66 samples/sec time cost: 3898.706147 [Epoch 013] validation: acc-top1=57.327764 acc-top5=81.038573 loss=1.897861 Epoch[014] Batch [0049]/[3759] Speed: 45.085097 samples/sec accuracy=60.125000 loss=1.677962 lr=0.010000 Epoch[014] Batch [0099]/[3759] Speed: 66.266896 samples/sec accuracy=60.187500 loss=1.659626 lr=0.010000 Epoch[014] Batch [0149]/[3759] Speed: 67.525836 samples/sec accuracy=60.437500 loss=1.654411 lr=0.010000 Epoch[014] Batch [0199]/[3759] Speed: 67.351574 samples/sec accuracy=60.382813 loss=1.647098 lr=0.010000 Epoch[014] Batch [0249]/[3759] Speed: 66.867864 samples/sec accuracy=59.937500 loss=1.652637 lr=0.010000 Epoch[014] Batch [0299]/[3759] Speed: 66.977689 samples/sec accuracy=59.791667 loss=1.657578 lr=0.010000 Epoch[014] Batch [0349]/[3759] Speed: 67.568457 samples/sec 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accuracy=58.938702 loss=1.684679 lr=0.010000 Epoch[014] Batch [1349]/[3759] Speed: 67.180201 samples/sec accuracy=58.998843 loss=1.682227 lr=0.010000 Epoch[014] Batch [1399]/[3759] Speed: 66.853383 samples/sec accuracy=58.985491 loss=1.683481 lr=0.010000 Epoch[014] Batch [1449]/[3759] Speed: 67.799072 samples/sec accuracy=59.005388 loss=1.683588 lr=0.010000 Epoch[014] Batch [1499]/[3759] Speed: 66.706040 samples/sec accuracy=59.036458 loss=1.682646 lr=0.010000 Epoch[014] Batch [1549]/[3759] Speed: 67.089469 samples/sec accuracy=59.040323 loss=1.682520 lr=0.010000 Epoch[014] Batch [1599]/[3759] Speed: 67.492650 samples/sec accuracy=59.006836 loss=1.684050 lr=0.010000 Epoch[014] Batch [1649]/[3759] Speed: 66.554452 samples/sec accuracy=58.995265 loss=1.684359 lr=0.010000 Epoch[014] Batch [1699]/[3759] Speed: 67.123544 samples/sec accuracy=58.957721 loss=1.685692 lr=0.010000 Epoch[014] Batch [1749]/[3759] Speed: 67.015274 samples/sec accuracy=58.933929 loss=1.687497 lr=0.010000 Epoch[014] 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accuracy=58.795833 loss=1.692511 lr=0.010000 Epoch[014] Batch [2299]/[3759] Speed: 67.584628 samples/sec accuracy=58.764266 loss=1.694045 lr=0.010000 Epoch[014] Batch [2349]/[3759] Speed: 67.249481 samples/sec accuracy=58.735372 loss=1.694833 lr=0.010000 Epoch[014] Batch [2399]/[3759] Speed: 66.547793 samples/sec accuracy=58.734375 loss=1.694739 lr=0.010000 Epoch[014] Batch [2449]/[3759] Speed: 67.586215 samples/sec accuracy=58.693240 loss=1.696247 lr=0.010000 Epoch[014] Batch [2499]/[3759] Speed: 67.047560 samples/sec accuracy=58.665625 loss=1.697501 lr=0.010000 Epoch[014] Batch [2549]/[3759] Speed: 67.224378 samples/sec accuracy=58.680760 loss=1.697362 lr=0.010000 Epoch[014] Batch [2599]/[3759] Speed: 67.158766 samples/sec accuracy=58.689904 loss=1.696924 lr=0.010000 Epoch[014] Batch [2649]/[3759] Speed: 66.854429 samples/sec accuracy=58.696344 loss=1.696767 lr=0.010000 Epoch[014] Batch [2699]/[3759] Speed: 67.182861 samples/sec accuracy=58.660301 loss=1.698763 lr=0.010000 Epoch[014] 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accuracy=58.631348 loss=1.702577 lr=0.010000 Epoch[014] Batch [3249]/[3759] Speed: 67.241701 samples/sec accuracy=58.613462 loss=1.703534 lr=0.010000 Epoch[014] Batch [3299]/[3759] Speed: 66.422406 samples/sec accuracy=58.598958 loss=1.704349 lr=0.010000 Epoch[014] Batch [3349]/[3759] Speed: 67.479436 samples/sec accuracy=58.592351 loss=1.704794 lr=0.010000 Epoch[014] Batch [3399]/[3759] Speed: 67.388249 samples/sec accuracy=58.603401 loss=1.704297 lr=0.010000 Epoch[014] Batch [3449]/[3759] Speed: 67.538855 samples/sec accuracy=58.603261 loss=1.703958 lr=0.010000 Epoch[014] Batch [3499]/[3759] Speed: 67.228696 samples/sec accuracy=58.595089 loss=1.704560 lr=0.010000 Epoch[014] Batch [3549]/[3759] Speed: 67.490313 samples/sec accuracy=58.588468 loss=1.705180 lr=0.010000 Epoch[014] Batch [3599]/[3759] Speed: 67.135002 samples/sec accuracy=58.567274 loss=1.706057 lr=0.010000 Epoch[014] Batch [3649]/[3759] Speed: 67.013765 samples/sec accuracy=58.574486 loss=1.705830 lr=0.010000 Epoch[014] Batch [3699]/[3759] Speed: 67.363344 samples/sec accuracy=58.584037 loss=1.705781 lr=0.010000 Epoch[014] Batch [3749]/[3759] Speed: 74.336512 samples/sec accuracy=58.580417 loss=1.706061 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.687500 acc-top5=80.312500 Batch [0099]/[0303]: acc-top1=57.421875 acc-top5=80.234375 Batch [0149]/[0303]: acc-top1=57.656250 acc-top5=80.729167 Batch [0199]/[0303]: acc-top1=57.875000 acc-top5=81.093750 Batch [0249]/[0303]: acc-top1=57.981250 acc-top5=81.137500 Batch [0299]/[0303]: acc-top1=57.953125 acc-top5=81.265625 [Epoch 014] training: accuracy=58.568602 loss=1.706420 [Epoch 014] speed: 66 samples/sec time cost: 3896.607518 [Epoch 014] validation: acc-top1=57.982673 acc-top5=81.280941 loss=1.882802 Epoch[015] Batch [0049]/[3760] Speed: 44.585632 samples/sec accuracy=60.093750 loss=1.657528 lr=0.010000 Epoch[015] Batch [0099]/[3760] Speed: 66.122463 samples/sec accuracy=60.046875 loss=1.661817 lr=0.010000 Epoch[015] Batch [0149]/[3760] Speed: 68.585039 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lr=0.010000 Epoch[015] Batch [2549]/[3760] Speed: 68.163090 samples/sec accuracy=59.213235 loss=1.677678 lr=0.010000 Epoch[015] Batch [2599]/[3760] Speed: 67.641679 samples/sec accuracy=59.204327 loss=1.678487 lr=0.010000 Epoch[015] Batch [2649]/[3760] Speed: 68.087597 samples/sec accuracy=59.195165 loss=1.679373 lr=0.010000 Epoch[015] Batch [2699]/[3760] Speed: 67.563929 samples/sec accuracy=59.201389 loss=1.679796 lr=0.010000 Epoch[015] Batch [2749]/[3760] Speed: 67.909285 samples/sec accuracy=59.181250 loss=1.680290 lr=0.010000 Epoch[015] Batch [2799]/[3760] Speed: 68.205107 samples/sec accuracy=59.178571 loss=1.680652 lr=0.010000 Epoch[015] Batch [2849]/[3760] Speed: 67.679878 samples/sec accuracy=59.174342 loss=1.680896 lr=0.010000 Epoch[015] Batch [2899]/[3760] Speed: 68.019281 samples/sec accuracy=59.169720 loss=1.680994 lr=0.010000 Epoch[015] Batch [2949]/[3760] Speed: 67.668860 samples/sec accuracy=59.183792 loss=1.680104 lr=0.010000 Epoch[015] Batch [2999]/[3760] Speed: 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lr=0.010000 Epoch[015] Batch [3499]/[3760] Speed: 67.506388 samples/sec accuracy=59.145089 loss=1.681798 lr=0.010000 Epoch[015] Batch [3549]/[3760] Speed: 67.760994 samples/sec accuracy=59.143046 loss=1.681599 lr=0.010000 Epoch[015] Batch [3599]/[3760] Speed: 67.848185 samples/sec accuracy=59.170139 loss=1.680720 lr=0.010000 Epoch[015] Batch [3649]/[3760] Speed: 67.543152 samples/sec accuracy=59.183647 loss=1.680208 lr=0.010000 Epoch[015] Batch [3699]/[3760] Speed: 67.519164 samples/sec accuracy=59.180743 loss=1.680714 lr=0.010000 Epoch[015] Batch [3749]/[3760] Speed: 73.766425 samples/sec accuracy=59.173333 loss=1.680883 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.781250 acc-top5=81.593750 Batch [0099]/[0303]: acc-top1=57.796875 acc-top5=81.265625 Batch [0149]/[0303]: acc-top1=57.968750 acc-top5=81.500000 Batch [0199]/[0303]: acc-top1=58.296875 acc-top5=81.828125 Batch [0249]/[0303]: acc-top1=58.381250 acc-top5=81.662500 Batch [0299]/[0303]: acc-top1=58.307292 acc-top5=81.765625 [Epoch 015] training: accuracy=59.172623 loss=1.680871 [Epoch 015] speed: 67 samples/sec time cost: 3862.322408 [Epoch 015] validation: acc-top1=58.317863 acc-top5=81.775990 loss=1.870446 Epoch[016] Batch [0049]/[3760] Speed: 45.733831 samples/sec accuracy=59.968750 loss=1.641103 lr=0.010000 Epoch[016] Batch [0099]/[3760] Speed: 66.101068 samples/sec accuracy=60.203125 loss=1.620375 lr=0.010000 Epoch[016] Batch [0149]/[3760] Speed: 68.016643 samples/sec accuracy=59.979167 loss=1.618115 lr=0.010000 Epoch[016] Batch [0199]/[3760] Speed: 67.659698 samples/sec accuracy=60.187500 loss=1.622953 lr=0.010000 Epoch[016] Batch [0249]/[3760] Speed: 67.587722 samples/sec accuracy=60.043750 loss=1.631665 lr=0.010000 Epoch[016] Batch [0299]/[3760] Speed: 68.559133 samples/sec accuracy=59.984375 loss=1.634293 lr=0.010000 Epoch[016] Batch [0349]/[3760] Speed: 67.636718 samples/sec accuracy=59.977679 loss=1.638299 lr=0.010000 Epoch[016] Batch [0399]/[3760] Speed: 68.136678 samples/sec accuracy=59.972656 loss=1.636555 lr=0.010000 Epoch[016] Batch [0449]/[3760] Speed: 67.937842 samples/sec accuracy=59.906250 loss=1.643129 lr=0.010000 Epoch[016] Batch [0499]/[3760] Speed: 67.933558 samples/sec accuracy=59.781250 loss=1.644592 lr=0.010000 Epoch[016] Batch [0549]/[3760] Speed: 67.663589 samples/sec accuracy=59.764205 loss=1.642305 lr=0.010000 Epoch[016] Batch [0599]/[3760] Speed: 68.156803 samples/sec accuracy=59.838542 loss=1.639185 lr=0.010000 Epoch[016] Batch [0649]/[3760] Speed: 68.052344 samples/sec accuracy=59.802885 loss=1.638782 lr=0.010000 Epoch[016] Batch [0699]/[3760] Speed: 68.048560 samples/sec accuracy=59.796875 loss=1.637827 lr=0.010000 Epoch[016] Batch [0749]/[3760] Speed: 67.629436 samples/sec accuracy=59.729167 loss=1.641353 lr=0.010000 Epoch[016] Batch [0799]/[3760] Speed: 67.772234 samples/sec accuracy=59.626953 loss=1.644224 lr=0.010000 Epoch[016] Batch [0849]/[3760] Speed: 68.118750 samples/sec accuracy=59.534926 loss=1.647695 lr=0.010000 Epoch[016] 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accuracy=59.616898 loss=1.655924 lr=0.010000 Epoch[016] Batch [1399]/[3760] Speed: 68.122375 samples/sec accuracy=59.638393 loss=1.656118 lr=0.010000 Epoch[016] Batch [1449]/[3760] Speed: 66.826140 samples/sec accuracy=59.662716 loss=1.655753 lr=0.010000 Epoch[016] Batch [1499]/[3760] Speed: 67.957116 samples/sec accuracy=59.675000 loss=1.655974 lr=0.010000 Epoch[016] Batch [1549]/[3760] Speed: 68.009622 samples/sec accuracy=59.733871 loss=1.655109 lr=0.010000 Epoch[016] Batch [1599]/[3760] Speed: 68.199841 samples/sec accuracy=59.727539 loss=1.654486 lr=0.010000 Epoch[016] Batch [1649]/[3760] Speed: 67.970253 samples/sec accuracy=59.687500 loss=1.654382 lr=0.010000 Epoch[016] Batch [1699]/[3760] Speed: 67.735863 samples/sec accuracy=59.698529 loss=1.654008 lr=0.010000 Epoch[016] Batch [1749]/[3760] Speed: 68.061710 samples/sec accuracy=59.650000 loss=1.653888 lr=0.010000 Epoch[016] Batch [1799]/[3760] Speed: 68.075587 samples/sec accuracy=59.623264 loss=1.655364 lr=0.010000 Epoch[016] 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accuracy=59.652174 loss=1.656813 lr=0.010000 Epoch[016] Batch [2349]/[3760] Speed: 68.180209 samples/sec accuracy=59.645612 loss=1.657105 lr=0.010000 Epoch[016] Batch [2399]/[3760] Speed: 67.524886 samples/sec accuracy=59.644531 loss=1.656719 lr=0.010000 Epoch[016] Batch [2449]/[3760] Speed: 67.630285 samples/sec accuracy=59.640306 loss=1.656543 lr=0.010000 Epoch[016] Batch [2499]/[3760] Speed: 68.119284 samples/sec accuracy=59.653750 loss=1.656068 lr=0.010000 Epoch[016] Batch [2549]/[3760] Speed: 68.111065 samples/sec accuracy=59.651348 loss=1.656633 lr=0.010000 Epoch[016] Batch [2599]/[3760] Speed: 68.180184 samples/sec accuracy=59.629808 loss=1.657137 lr=0.010000 Epoch[016] Batch [2649]/[3760] Speed: 68.512728 samples/sec accuracy=59.620873 loss=1.657782 lr=0.010000 Epoch[016] Batch [2699]/[3760] Speed: 68.012163 samples/sec accuracy=59.606481 loss=1.658015 lr=0.010000 Epoch[016] Batch [2749]/[3760] Speed: 68.204539 samples/sec accuracy=59.589205 loss=1.658865 lr=0.010000 Epoch[016] 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accuracy=59.575481 loss=1.661118 lr=0.010000 Epoch[016] Batch [3299]/[3760] Speed: 68.347972 samples/sec accuracy=59.570076 loss=1.661096 lr=0.010000 Epoch[016] Batch [3349]/[3760] Speed: 67.682475 samples/sec accuracy=59.559235 loss=1.661822 lr=0.010000 Epoch[016] Batch [3399]/[3760] Speed: 67.759684 samples/sec accuracy=59.546415 loss=1.662607 lr=0.010000 Epoch[016] Batch [3449]/[3760] Speed: 67.392424 samples/sec accuracy=59.533062 loss=1.662743 lr=0.010000 Epoch[016] Batch [3499]/[3760] Speed: 67.994142 samples/sec accuracy=59.529464 loss=1.663062 lr=0.010000 Epoch[016] Batch [3549]/[3760] Speed: 68.032551 samples/sec accuracy=59.525088 loss=1.663106 lr=0.010000 Epoch[016] Batch [3599]/[3760] Speed: 67.904690 samples/sec accuracy=59.534288 loss=1.663435 lr=0.010000 Epoch[016] Batch [3649]/[3760] Speed: 68.058294 samples/sec accuracy=59.543236 loss=1.663227 lr=0.010000 Epoch[016] Batch [3699]/[3760] Speed: 67.814373 samples/sec accuracy=59.524916 loss=1.663961 lr=0.010000 Epoch[016] Batch [3749]/[3760] Speed: 74.227451 samples/sec accuracy=59.505417 loss=1.664224 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.750000 acc-top5=81.093750 Batch [0099]/[0303]: acc-top1=57.781250 acc-top5=80.734375 Batch [0149]/[0303]: acc-top1=57.864583 acc-top5=81.093750 Batch [0199]/[0303]: acc-top1=58.093750 acc-top5=81.351562 Batch [0249]/[0303]: acc-top1=58.118750 acc-top5=81.343750 Batch [0299]/[0303]: acc-top1=58.197917 acc-top5=81.453125 [Epoch 016] training: accuracy=59.502992 loss=1.664367 [Epoch 016] speed: 67 samples/sec time cost: 3854.627930 [Epoch 016] validation: acc-top1=58.214728 acc-top5=81.471741 loss=1.861569 Epoch[017] Batch [0049]/[3759] Speed: 45.446069 samples/sec accuracy=61.125000 loss=1.621735 lr=0.010000 Epoch[017] Batch [0099]/[3759] Speed: 67.108051 samples/sec accuracy=61.031250 loss=1.611920 lr=0.010000 Epoch[017] Batch [0149]/[3759] Speed: 68.447478 samples/sec accuracy=61.104167 loss=1.613191 lr=0.010000 Epoch[017] Batch [0199]/[3759] Speed: 68.167530 samples/sec accuracy=60.867188 loss=1.613153 lr=0.010000 Epoch[017] Batch [0249]/[3759] Speed: 67.863794 samples/sec accuracy=60.893750 loss=1.612187 lr=0.010000 Epoch[017] Batch [0299]/[3759] Speed: 67.808160 samples/sec accuracy=60.989583 loss=1.604727 lr=0.010000 Epoch[017] Batch [0349]/[3759] Speed: 67.185738 samples/sec accuracy=60.870536 loss=1.608464 lr=0.010000 Epoch[017] Batch [0399]/[3759] Speed: 68.503447 samples/sec accuracy=60.929687 loss=1.609191 lr=0.010000 Epoch[017] Batch [0449]/[3759] Speed: 67.769662 samples/sec accuracy=60.631944 loss=1.621113 lr=0.010000 Epoch[017] Batch [0499]/[3759] Speed: 67.760162 samples/sec accuracy=60.540625 loss=1.624261 lr=0.010000 Epoch[017] Batch [0549]/[3759] Speed: 67.733063 samples/sec accuracy=60.582386 loss=1.624489 lr=0.010000 Epoch[017] Batch [0599]/[3759] Speed: 67.799235 samples/sec accuracy=60.591146 loss=1.623862 lr=0.010000 Epoch[017] Batch [0649]/[3759] Speed: 67.999280 samples/sec accuracy=60.521635 loss=1.626070 lr=0.010000 Epoch[017] Batch [0699]/[3759] Speed: 67.741822 samples/sec accuracy=60.549107 loss=1.624950 lr=0.010000 Epoch[017] Batch [0749]/[3759] Speed: 68.114320 samples/sec accuracy=60.552083 loss=1.625541 lr=0.010000 Epoch[017] Batch [0799]/[3759] Speed: 67.716277 samples/sec accuracy=60.550781 loss=1.624378 lr=0.010000 Epoch[017] Batch [0849]/[3759] Speed: 68.117639 samples/sec accuracy=60.523897 loss=1.624388 lr=0.010000 Epoch[017] Batch [0899]/[3759] Speed: 67.866633 samples/sec accuracy=60.510417 loss=1.623533 lr=0.010000 Epoch[017] Batch [0949]/[3759] Speed: 68.070820 samples/sec accuracy=60.565789 loss=1.621045 lr=0.010000 Epoch[017] Batch [0999]/[3759] Speed: 67.465465 samples/sec accuracy=60.546875 loss=1.622737 lr=0.010000 Epoch[017] Batch [1049]/[3759] Speed: 68.333588 samples/sec accuracy=60.561012 loss=1.624284 lr=0.010000 Epoch[017] Batch [1099]/[3759] Speed: 68.331428 samples/sec accuracy=60.529830 loss=1.626358 lr=0.010000 Epoch[017] Batch [1149]/[3759] Speed: 67.911952 samples/sec accuracy=60.504076 loss=1.627837 lr=0.010000 Epoch[017] Batch [1199]/[3759] Speed: 67.676659 samples/sec accuracy=60.518229 loss=1.625340 lr=0.010000 Epoch[017] Batch [1249]/[3759] Speed: 67.225707 samples/sec accuracy=60.486250 loss=1.626051 lr=0.010000 Epoch[017] Batch [1299]/[3759] Speed: 68.961166 samples/sec accuracy=60.442308 loss=1.626154 lr=0.010000 Epoch[017] Batch [1349]/[3759] Speed: 67.471484 samples/sec accuracy=60.449074 loss=1.626756 lr=0.010000 Epoch[017] Batch [1399]/[3759] Speed: 68.023688 samples/sec accuracy=60.434152 loss=1.627173 lr=0.010000 Epoch[017] Batch [1449]/[3759] Speed: 68.431605 samples/sec accuracy=60.450431 loss=1.626268 lr=0.010000 Epoch[017] Batch [1499]/[3759] Speed: 67.884958 samples/sec accuracy=60.381250 loss=1.629021 lr=0.010000 Epoch[017] Batch [1549]/[3759] Speed: 67.667826 samples/sec accuracy=60.345766 loss=1.630402 lr=0.010000 Epoch[017] Batch [1599]/[3759] Speed: 68.216948 samples/sec accuracy=60.282227 loss=1.631540 lr=0.010000 Epoch[017] Batch [1649]/[3759] Speed: 68.036580 samples/sec accuracy=60.276515 loss=1.631876 lr=0.010000 Epoch[017] Batch [1699]/[3759] Speed: 67.841438 samples/sec accuracy=60.261029 loss=1.632285 lr=0.010000 Epoch[017] Batch [1749]/[3759] Speed: 68.130471 samples/sec accuracy=60.292857 loss=1.630890 lr=0.010000 Epoch[017] Batch [1799]/[3759] Speed: 67.748577 samples/sec accuracy=60.280382 loss=1.631362 lr=0.010000 Epoch[017] Batch [1849]/[3759] Speed: 68.110938 samples/sec accuracy=60.267736 loss=1.632849 lr=0.010000 Epoch[017] Batch [1899]/[3759] Speed: 68.093923 samples/sec accuracy=60.273849 loss=1.632808 lr=0.010000 Epoch[017] Batch [1949]/[3759] Speed: 68.218774 samples/sec accuracy=60.252404 loss=1.634149 lr=0.010000 Epoch[017] Batch [1999]/[3759] Speed: 68.120628 samples/sec accuracy=60.214062 loss=1.635125 lr=0.010000 Epoch[017] Batch [2049]/[3759] Speed: 67.934062 samples/sec accuracy=60.187500 loss=1.635554 lr=0.010000 Epoch[017] Batch [2099]/[3759] Speed: 68.262249 samples/sec accuracy=60.165179 loss=1.636451 lr=0.010000 Epoch[017] Batch [2149]/[3759] Speed: 68.060066 samples/sec accuracy=60.159157 loss=1.636252 lr=0.010000 Epoch[017] Batch [2199]/[3759] Speed: 67.709295 samples/sec accuracy=60.133523 loss=1.638414 lr=0.010000 Epoch[017] Batch [2249]/[3759] Speed: 67.689869 samples/sec accuracy=60.147917 loss=1.638727 lr=0.010000 Epoch[017] Batch [2299]/[3759] Speed: 67.714368 samples/sec accuracy=60.099864 loss=1.639869 lr=0.010000 Epoch[017] Batch [2349]/[3759] Speed: 67.774247 samples/sec accuracy=60.088431 loss=1.640192 lr=0.010000 Epoch[017] Batch [2399]/[3759] Speed: 68.373713 samples/sec accuracy=60.073568 loss=1.641492 lr=0.010000 Epoch[017] Batch [2449]/[3759] Speed: 68.080107 samples/sec accuracy=60.087372 loss=1.640986 lr=0.010000 Epoch[017] Batch [2499]/[3759] Speed: 67.665657 samples/sec accuracy=60.081875 loss=1.641088 lr=0.010000 Epoch[017] Batch [2549]/[3759] Speed: 67.625425 samples/sec accuracy=60.063725 loss=1.642586 lr=0.010000 Epoch[017] Batch [2599]/[3759] Speed: 68.030491 samples/sec accuracy=60.049880 loss=1.642710 lr=0.010000 Epoch[017] Batch [2649]/[3759] Speed: 67.833728 samples/sec accuracy=60.051297 loss=1.643290 lr=0.010000 Epoch[017] Batch [2699]/[3759] Speed: 67.876092 samples/sec accuracy=60.038773 loss=1.643868 lr=0.010000 Epoch[017] Batch [2749]/[3759] Speed: 68.134981 samples/sec accuracy=60.006250 loss=1.644827 lr=0.010000 Epoch[017] Batch [2799]/[3759] Speed: 67.820709 samples/sec accuracy=60.011719 loss=1.644487 lr=0.010000 Epoch[017] Batch [2849]/[3759] Speed: 68.366177 samples/sec accuracy=59.986294 loss=1.645861 lr=0.010000 Epoch[017] Batch [2899]/[3759] Speed: 67.406608 samples/sec accuracy=60.016164 loss=1.644895 lr=0.010000 Epoch[017] Batch [2949]/[3759] Speed: 68.137845 samples/sec accuracy=59.975636 loss=1.645998 lr=0.010000 Epoch[017] Batch [2999]/[3759] Speed: 67.966350 samples/sec accuracy=59.986458 loss=1.645407 lr=0.010000 Epoch[017] Batch [3049]/[3759] Speed: 67.745982 samples/sec accuracy=59.977971 loss=1.646013 lr=0.010000 Epoch[017] Batch [3099]/[3759] Speed: 67.770631 samples/sec accuracy=59.981351 loss=1.646103 lr=0.010000 Epoch[017] Batch [3149]/[3759] Speed: 68.512916 samples/sec accuracy=59.974702 loss=1.645945 lr=0.010000 Epoch[017] Batch [3199]/[3759] Speed: 68.060173 samples/sec accuracy=59.993652 loss=1.645368 lr=0.010000 Epoch[017] Batch [3249]/[3759] Speed: 67.931040 samples/sec accuracy=59.996154 loss=1.645949 lr=0.010000 Epoch[017] Batch [3299]/[3759] Speed: 68.772325 samples/sec accuracy=59.982955 loss=1.646265 lr=0.010000 Epoch[017] Batch [3349]/[3759] Speed: 68.071022 samples/sec accuracy=59.983675 loss=1.646368 lr=0.010000 Epoch[017] Batch [3399]/[3759] Speed: 68.034742 samples/sec accuracy=59.969210 loss=1.646962 lr=0.010000 Epoch[017] Batch [3449]/[3759] Speed: 67.901025 samples/sec accuracy=59.952446 loss=1.648090 lr=0.010000 Epoch[017] Batch [3499]/[3759] Speed: 68.578083 samples/sec accuracy=59.951339 loss=1.647936 lr=0.010000 Epoch[017] Batch [3549]/[3759] Speed: 68.073791 samples/sec accuracy=59.975352 loss=1.646770 lr=0.010000 Epoch[017] Batch [3599]/[3759] Speed: 68.143765 samples/sec accuracy=59.987413 loss=1.647257 lr=0.010000 Epoch[017] Batch [3649]/[3759] Speed: 67.834502 samples/sec accuracy=59.990582 loss=1.647235 lr=0.010000 Epoch[017] Batch [3699]/[3759] Speed: 68.154248 samples/sec accuracy=59.984375 loss=1.647454 lr=0.010000 Epoch[017] Batch [3749]/[3759] Speed: 74.587266 samples/sec accuracy=59.982500 loss=1.647734 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.093750 acc-top5=81.343750 Batch [0099]/[0303]: acc-top1=57.437500 acc-top5=80.968750 Batch [0149]/[0303]: acc-top1=57.520833 acc-top5=81.052083 Batch [0199]/[0303]: acc-top1=57.960938 acc-top5=81.367188 Batch [0249]/[0303]: acc-top1=57.950000 acc-top5=81.256250 Batch [0299]/[0303]: acc-top1=57.854167 acc-top5=81.437500 [Epoch 017] training: accuracy=59.978136 loss=1.647898 [Epoch 017] speed: 67 samples/sec time cost: 3851.125021 [Epoch 017] validation: acc-top1=57.874381 acc-top5=81.456271 loss=1.875445 Epoch[018] Batch [0049]/[3760] Speed: 45.697374 samples/sec accuracy=61.250000 loss=1.598347 lr=0.010000 Epoch[018] Batch [0099]/[3760] Speed: 66.915302 samples/sec accuracy=61.234375 loss=1.606455 lr=0.010000 Epoch[018] Batch [0149]/[3760] Speed: 68.157865 samples/sec accuracy=60.885417 loss=1.596433 lr=0.010000 Epoch[018] Batch [0199]/[3760] Speed: 67.760929 samples/sec accuracy=60.687500 loss=1.596137 lr=0.010000 Epoch[018] Batch [0249]/[3760] Speed: 67.474850 samples/sec accuracy=60.887500 loss=1.592573 lr=0.010000 Epoch[018] Batch [0299]/[3760] Speed: 68.221106 samples/sec accuracy=61.093750 loss=1.585265 lr=0.010000 Epoch[018] Batch [0349]/[3760] Speed: 67.523310 samples/sec accuracy=61.035714 loss=1.590851 lr=0.010000 Epoch[018] Batch [0399]/[3760] Speed: 67.663004 samples/sec accuracy=60.929687 loss=1.599694 lr=0.010000 Epoch[018] Batch [0449]/[3760] Speed: 68.053057 samples/sec 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accuracy=60.621652 loss=1.616081 lr=0.010000 Epoch[018] Batch [1449]/[3760] Speed: 67.711421 samples/sec accuracy=60.565733 loss=1.617287 lr=0.010000 Epoch[018] Batch [1499]/[3760] Speed: 67.447490 samples/sec accuracy=60.567708 loss=1.615842 lr=0.010000 Epoch[018] Batch [1549]/[3760] Speed: 68.396326 samples/sec accuracy=60.535282 loss=1.616455 lr=0.010000 Epoch[018] Batch [1599]/[3760] Speed: 68.315088 samples/sec accuracy=60.515625 loss=1.617603 lr=0.010000 Epoch[018] Batch [1649]/[3760] Speed: 68.034475 samples/sec accuracy=60.480114 loss=1.619796 lr=0.010000 Epoch[018] Batch [1699]/[3760] Speed: 67.715060 samples/sec accuracy=60.485294 loss=1.619530 lr=0.010000 Epoch[018] Batch [1749]/[3760] Speed: 67.681941 samples/sec accuracy=60.497321 loss=1.619712 lr=0.010000 Epoch[018] Batch [1799]/[3760] Speed: 67.941002 samples/sec accuracy=60.476562 loss=1.620156 lr=0.010000 Epoch[018] Batch [1849]/[3760] Speed: 68.385603 samples/sec accuracy=60.480574 loss=1.620444 lr=0.010000 Epoch[018] 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accuracy=60.430186 loss=1.623854 lr=0.010000 Epoch[018] Batch [2399]/[3760] Speed: 67.538793 samples/sec accuracy=60.415365 loss=1.623768 lr=0.010000 Epoch[018] Batch [2449]/[3760] Speed: 68.234480 samples/sec accuracy=60.397321 loss=1.624563 lr=0.010000 Epoch[018] Batch [2499]/[3760] Speed: 68.057580 samples/sec accuracy=60.363125 loss=1.624864 lr=0.010000 Epoch[018] Batch [2549]/[3760] Speed: 67.890975 samples/sec accuracy=60.330270 loss=1.625533 lr=0.010000 Epoch[018] Batch [2599]/[3760] Speed: 68.588075 samples/sec accuracy=60.317909 loss=1.626487 lr=0.010000 Epoch[018] Batch [2649]/[3760] Speed: 68.212084 samples/sec accuracy=60.323113 loss=1.626762 lr=0.010000 Epoch[018] Batch [2699]/[3760] Speed: 67.898360 samples/sec accuracy=60.317708 loss=1.627859 lr=0.010000 Epoch[018] Batch [2749]/[3760] Speed: 67.822390 samples/sec accuracy=60.321591 loss=1.628060 lr=0.010000 Epoch[018] Batch [2799]/[3760] Speed: 68.665245 samples/sec accuracy=60.323103 loss=1.627935 lr=0.010000 Epoch[018] 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accuracy=60.302083 loss=1.628952 lr=0.010000 Epoch[018] Batch [3349]/[3760] Speed: 67.979207 samples/sec accuracy=60.302239 loss=1.629427 lr=0.010000 Epoch[018] Batch [3399]/[3760] Speed: 68.109695 samples/sec accuracy=60.299632 loss=1.629173 lr=0.010000 Epoch[018] Batch [3449]/[3760] Speed: 67.376496 samples/sec accuracy=60.288949 loss=1.629112 lr=0.010000 Epoch[018] Batch [3499]/[3760] Speed: 67.972263 samples/sec accuracy=60.288393 loss=1.629447 lr=0.010000 Epoch[018] Batch [3549]/[3760] Speed: 68.472994 samples/sec accuracy=60.266725 loss=1.630210 lr=0.010000 Epoch[018] Batch [3599]/[3760] Speed: 67.875987 samples/sec accuracy=60.264323 loss=1.630191 lr=0.010000 Epoch[018] Batch [3649]/[3760] Speed: 67.829774 samples/sec accuracy=60.246147 loss=1.630857 lr=0.010000 Epoch[018] Batch [3699]/[3760] Speed: 67.832339 samples/sec accuracy=60.239443 loss=1.631119 lr=0.010000 Epoch[018] Batch [3749]/[3760] Speed: 74.276945 samples/sec accuracy=60.241250 loss=1.631216 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.156250 acc-top5=81.156250 Batch [0099]/[0303]: acc-top1=58.843750 acc-top5=80.500000 Batch [0149]/[0303]: acc-top1=58.822917 acc-top5=81.125000 Batch [0199]/[0303]: acc-top1=59.000000 acc-top5=81.648438 Batch [0249]/[0303]: acc-top1=58.968750 acc-top5=81.493750 Batch [0299]/[0303]: acc-top1=59.171875 acc-top5=81.765625 [Epoch 018] training: accuracy=60.241024 loss=1.631029 [Epoch 018] speed: 67 samples/sec time cost: 3854.344190 [Epoch 018] validation: acc-top1=59.158416 acc-top5=81.775990 loss=1.851041 Epoch[019] Batch [0049]/[3760] Speed: 46.067186 samples/sec accuracy=62.000000 loss=1.544066 lr=0.010000 Epoch[019] Batch [0099]/[3760] Speed: 66.454116 samples/sec accuracy=62.375000 loss=1.538971 lr=0.010000 Epoch[019] Batch [0149]/[3760] Speed: 68.768364 samples/sec accuracy=62.666667 loss=1.531559 lr=0.010000 Epoch[019] Batch [0199]/[3760] Speed: 66.485821 samples/sec accuracy=62.062500 loss=1.555854 lr=0.010000 Epoch[019] Batch [0249]/[3760] Speed: 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68.531513 samples/sec accuracy=60.792339 loss=1.607814 lr=0.010000 Epoch[019] Batch [3149]/[3760] Speed: 68.222073 samples/sec accuracy=60.762401 loss=1.609093 lr=0.010000 Epoch[019] Batch [3199]/[3760] Speed: 68.019929 samples/sec accuracy=60.774902 loss=1.608152 lr=0.010000 Epoch[019] Batch [3249]/[3760] Speed: 68.823223 samples/sec accuracy=60.769712 loss=1.608808 lr=0.010000 Epoch[019] Batch [3299]/[3760] Speed: 68.171617 samples/sec accuracy=60.766098 loss=1.608933 lr=0.010000 Epoch[019] Batch [3349]/[3760] Speed: 68.514821 samples/sec accuracy=60.755597 loss=1.609495 lr=0.010000 Epoch[019] Batch [3399]/[3760] Speed: 67.615491 samples/sec accuracy=60.732996 loss=1.610336 lr=0.010000 Epoch[019] Batch [3449]/[3760] Speed: 67.931448 samples/sec accuracy=60.740489 loss=1.609726 lr=0.010000 Epoch[019] Batch [3499]/[3760] Speed: 68.043524 samples/sec accuracy=60.730357 loss=1.610413 lr=0.010000 Epoch[019] Batch [3549]/[3760] Speed: 68.554186 samples/sec accuracy=60.689701 loss=1.612020 lr=0.010000 Epoch[019] Batch [3599]/[3760] Speed: 68.429786 samples/sec accuracy=60.675347 loss=1.612444 lr=0.010000 Epoch[019] Batch [3649]/[3760] Speed: 68.287727 samples/sec accuracy=60.666096 loss=1.613207 lr=0.010000 Epoch[019] Batch [3699]/[3760] Speed: 67.987985 samples/sec accuracy=60.654983 loss=1.613661 lr=0.010000 Epoch[019] Batch [3749]/[3760] Speed: 74.335354 samples/sec accuracy=60.657083 loss=1.613821 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.906250 acc-top5=81.375000 Batch [0099]/[0303]: acc-top1=58.765625 acc-top5=80.859375 Batch [0149]/[0303]: acc-top1=58.927083 acc-top5=81.437500 Batch [0199]/[0303]: acc-top1=59.226562 acc-top5=81.859375 Batch [0249]/[0303]: acc-top1=59.150000 acc-top5=81.862500 Batch [0299]/[0303]: acc-top1=59.260417 acc-top5=82.182292 [Epoch 019] training: accuracy=60.669049 loss=1.613400 [Epoch 019] speed: 67 samples/sec time cost: 3850.123026 [Epoch 019] validation: acc-top1=59.261551 acc-top5=82.183375 loss=1.868707 Epoch[020] Batch 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accuracy=61.244612 loss=1.579970 lr=0.010000 Epoch[020] Batch [1499]/[3759] Speed: 68.330552 samples/sec accuracy=61.196875 loss=1.581587 lr=0.010000 Epoch[020] Batch [1549]/[3759] Speed: 68.383990 samples/sec accuracy=61.152218 loss=1.583995 lr=0.010000 Epoch[020] Batch [1599]/[3759] Speed: 67.959123 samples/sec accuracy=61.102539 loss=1.586863 lr=0.010000 Epoch[020] Batch [1649]/[3759] Speed: 67.730089 samples/sec accuracy=61.116477 loss=1.587565 lr=0.010000 Epoch[020] Batch [1699]/[3759] Speed: 68.352962 samples/sec accuracy=61.112132 loss=1.587890 lr=0.010000 Epoch[020] Batch [1749]/[3759] Speed: 68.240294 samples/sec accuracy=61.097321 loss=1.589248 lr=0.010000 Epoch[020] Batch [1799]/[3759] Speed: 68.367025 samples/sec accuracy=61.102431 loss=1.589031 lr=0.010000 Epoch[020] Batch [1849]/[3759] Speed: 68.224713 samples/sec accuracy=61.062500 loss=1.590956 lr=0.010000 Epoch[020] Batch [1899]/[3759] Speed: 67.967552 samples/sec accuracy=61.050164 loss=1.591359 lr=0.010000 Epoch[020] 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accuracy=60.988281 loss=1.594577 lr=0.010000 Epoch[020] Batch [2449]/[3759] Speed: 67.652696 samples/sec accuracy=60.979592 loss=1.595998 lr=0.010000 Epoch[020] Batch [2499]/[3759] Speed: 67.516609 samples/sec accuracy=60.971250 loss=1.596851 lr=0.010000 Epoch[020] Batch [2549]/[3759] Speed: 67.666462 samples/sec accuracy=60.946691 loss=1.597285 lr=0.010000 Epoch[020] Batch [2599]/[3759] Speed: 67.891354 samples/sec accuracy=60.968750 loss=1.597055 lr=0.010000 Epoch[020] Batch [2649]/[3759] Speed: 68.068943 samples/sec accuracy=60.963443 loss=1.596930 lr=0.010000 Epoch[020] Batch [2699]/[3759] Speed: 68.328466 samples/sec accuracy=60.975116 loss=1.596350 lr=0.010000 Epoch[020] Batch [2749]/[3759] Speed: 67.682449 samples/sec accuracy=60.955114 loss=1.596598 lr=0.010000 Epoch[020] Batch [2799]/[3759] Speed: 67.904201 samples/sec accuracy=60.947545 loss=1.597017 lr=0.010000 Epoch[020] Batch [2849]/[3759] Speed: 68.776101 samples/sec accuracy=60.936952 loss=1.597294 lr=0.010000 Epoch[020] 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accuracy=60.898321 loss=1.600531 lr=0.010000 Epoch[020] Batch [3399]/[3759] Speed: 67.650241 samples/sec accuracy=60.907169 loss=1.600425 lr=0.010000 Epoch[020] Batch [3449]/[3759] Speed: 68.147337 samples/sec accuracy=60.896739 loss=1.601226 lr=0.010000 Epoch[020] Batch [3499]/[3759] Speed: 68.228097 samples/sec accuracy=60.885268 loss=1.601839 lr=0.010000 Epoch[020] Batch [3549]/[3759] Speed: 67.562002 samples/sec accuracy=60.885123 loss=1.602027 lr=0.010000 Epoch[020] Batch [3599]/[3759] Speed: 68.117810 samples/sec accuracy=60.904948 loss=1.602032 lr=0.010000 Epoch[020] Batch [3649]/[3759] Speed: 67.710078 samples/sec accuracy=60.889127 loss=1.602828 lr=0.010000 Epoch[020] Batch [3699]/[3759] Speed: 68.394406 samples/sec accuracy=60.895270 loss=1.602678 lr=0.010000 Epoch[020] Batch [3749]/[3759] Speed: 74.701674 samples/sec accuracy=60.873333 loss=1.603572 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.968750 acc-top5=81.625000 Batch [0099]/[0303]: acc-top1=57.953125 acc-top5=81.156250 Batch [0149]/[0303]: acc-top1=58.208333 acc-top5=81.406250 Batch [0199]/[0303]: acc-top1=58.257812 acc-top5=81.789062 Batch [0249]/[0303]: acc-top1=58.300000 acc-top5=81.662500 Batch [0299]/[0303]: acc-top1=58.276042 acc-top5=81.796875 [Epoch 020] training: accuracy=60.877644 loss=1.603608 [Epoch 020] speed: 67 samples/sec time cost: 3846.560401 [Epoch 020] validation: acc-top1=58.328177 acc-top5=81.791460 loss=1.873524 Epoch[021] Batch [0049]/[3760] Speed: 45.377989 samples/sec accuracy=62.125000 loss=1.586701 lr=0.010000 Epoch[021] Batch [0099]/[3760] Speed: 66.715105 samples/sec accuracy=62.781250 loss=1.536282 lr=0.010000 Epoch[021] Batch [0149]/[3760] Speed: 68.171775 samples/sec accuracy=62.312500 loss=1.541699 lr=0.010000 Epoch[021] Batch [0199]/[3760] Speed: 67.808334 samples/sec accuracy=61.867188 loss=1.551143 lr=0.010000 Epoch[021] Batch [0249]/[3760] Speed: 67.616267 samples/sec accuracy=61.950000 loss=1.548083 lr=0.010000 Epoch[021] Batch [0299]/[3760] 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accuracy=61.295956 loss=1.578171 lr=0.010000 Epoch[021] Batch [1749]/[3760] Speed: 68.052884 samples/sec accuracy=61.287500 loss=1.578383 lr=0.010000 Epoch[021] Batch [1799]/[3760] Speed: 68.059019 samples/sec accuracy=61.263889 loss=1.580249 lr=0.010000 Epoch[021] Batch [1849]/[3760] Speed: 68.100219 samples/sec accuracy=61.266047 loss=1.580962 lr=0.010000 Epoch[021] Batch [1899]/[3760] Speed: 68.544556 samples/sec accuracy=61.234375 loss=1.581802 lr=0.010000 Epoch[021] Batch [1949]/[3760] Speed: 67.940916 samples/sec accuracy=61.190705 loss=1.582400 lr=0.010000 Epoch[021] Batch [1999]/[3760] Speed: 68.173032 samples/sec accuracy=61.146875 loss=1.584884 lr=0.010000 Epoch[021] Batch [2049]/[3760] Speed: 68.171852 samples/sec accuracy=61.157012 loss=1.584780 lr=0.010000 Epoch[021] Batch [2099]/[3760] Speed: 68.269338 samples/sec accuracy=61.183780 loss=1.584310 lr=0.010000 Epoch[021] Batch [2149]/[3760] Speed: 67.932062 samples/sec accuracy=61.211483 loss=1.583846 lr=0.010000 Epoch[021] 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accuracy=61.232901 loss=1.585063 lr=0.010000 Epoch[021] Batch [2699]/[3760] Speed: 67.990675 samples/sec accuracy=61.210069 loss=1.586452 lr=0.010000 Epoch[021] Batch [2749]/[3760] Speed: 68.057495 samples/sec accuracy=61.222727 loss=1.586300 lr=0.010000 Epoch[021] Batch [2799]/[3760] Speed: 67.645658 samples/sec accuracy=61.184710 loss=1.587669 lr=0.010000 Epoch[021] Batch [2849]/[3760] Speed: 68.396672 samples/sec accuracy=61.157346 loss=1.588781 lr=0.010000 Epoch[021] Batch [2899]/[3760] Speed: 67.722029 samples/sec accuracy=61.158405 loss=1.589046 lr=0.010000 Epoch[021] Batch [2949]/[3760] Speed: 68.517398 samples/sec accuracy=61.158898 loss=1.588673 lr=0.010000 Epoch[021] Batch [2999]/[3760] Speed: 67.616735 samples/sec accuracy=61.171354 loss=1.587899 lr=0.010000 Epoch[021] Batch [3049]/[3760] Speed: 68.271615 samples/sec accuracy=61.158811 loss=1.588546 lr=0.010000 Epoch[021] Batch [3099]/[3760] Speed: 67.940222 samples/sec accuracy=61.153226 loss=1.588618 lr=0.010000 Epoch[021] Batch [3149]/[3760] Speed: 68.179910 samples/sec accuracy=61.125496 loss=1.590061 lr=0.010000 Epoch[021] Batch [3199]/[3760] Speed: 67.543648 samples/sec accuracy=61.115723 loss=1.590423 lr=0.010000 Epoch[021] Batch [3249]/[3760] Speed: 68.530840 samples/sec accuracy=61.129808 loss=1.590575 lr=0.010000 Epoch[021] Batch [3299]/[3760] Speed: 67.864675 samples/sec accuracy=61.146780 loss=1.589656 lr=0.010000 Epoch[021] Batch [3349]/[3760] Speed: 67.837967 samples/sec accuracy=61.141791 loss=1.589810 lr=0.010000 Epoch[021] Batch [3399]/[3760] Speed: 68.359877 samples/sec accuracy=61.145680 loss=1.589671 lr=0.010000 Epoch[021] Batch [3449]/[3760] Speed: 67.319433 samples/sec accuracy=61.148098 loss=1.589168 lr=0.010000 Epoch[021] Batch [3499]/[3760] Speed: 68.213348 samples/sec accuracy=61.127679 loss=1.590454 lr=0.010000 Epoch[021] Batch [3549]/[3760] Speed: 67.336901 samples/sec accuracy=61.136444 loss=1.590411 lr=0.010000 Epoch[021] Batch [3599]/[3760] Speed: 68.828604 samples/sec accuracy=61.126736 loss=1.590543 lr=0.010000 Epoch[021] Batch [3649]/[3760] Speed: 67.646981 samples/sec accuracy=61.107021 loss=1.591598 lr=0.010000 Epoch[021] Batch [3699]/[3760] Speed: 67.853200 samples/sec accuracy=61.098818 loss=1.592032 lr=0.010000 Epoch[021] Batch [3749]/[3760] Speed: 74.463905 samples/sec accuracy=61.112083 loss=1.592208 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.156250 acc-top5=82.656250 Batch [0099]/[0303]: acc-top1=59.171875 acc-top5=82.140625 Batch [0149]/[0303]: acc-top1=59.385417 acc-top5=82.406250 Batch [0199]/[0303]: acc-top1=59.632812 acc-top5=82.812500 Batch [0249]/[0303]: acc-top1=59.568750 acc-top5=82.687500 Batch [0299]/[0303]: acc-top1=59.598958 acc-top5=82.755208 [Epoch 021] training: accuracy=61.113281 loss=1.591968 [Epoch 021] speed: 67 samples/sec time cost: 3850.799171 [Epoch 021] validation: acc-top1=59.637995 acc-top5=82.781559 loss=1.835154 Epoch[022] Batch [0049]/[3760] Speed: 45.204345 samples/sec accuracy=62.125000 loss=1.549286 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lr=0.010000 Epoch[022] Batch [2949]/[3760] Speed: 68.363768 samples/sec accuracy=61.444915 loss=1.576858 lr=0.010000 Epoch[022] Batch [2999]/[3760] Speed: 68.223166 samples/sec accuracy=61.442708 loss=1.576535 lr=0.010000 Epoch[022] Batch [3049]/[3760] Speed: 68.258219 samples/sec accuracy=61.426230 loss=1.576934 lr=0.010000 Epoch[022] Batch [3099]/[3760] Speed: 68.793546 samples/sec accuracy=61.417339 loss=1.577201 lr=0.010000 Epoch[022] Batch [3149]/[3760] Speed: 68.051486 samples/sec accuracy=61.428571 loss=1.577325 lr=0.010000 Epoch[022] Batch [3199]/[3760] Speed: 67.580501 samples/sec accuracy=61.435547 loss=1.577591 lr=0.010000 Epoch[022] Batch [3249]/[3760] Speed: 67.926727 samples/sec accuracy=61.465865 loss=1.577171 lr=0.010000 Epoch[022] Batch [3299]/[3760] Speed: 68.688084 samples/sec accuracy=61.445076 loss=1.577909 lr=0.010000 Epoch[022] Batch [3349]/[3760] Speed: 67.905332 samples/sec accuracy=61.448228 loss=1.577786 lr=0.010000 Epoch[022] Batch [3399]/[3760] Speed: 67.882041 samples/sec accuracy=61.468750 loss=1.577009 lr=0.010000 Epoch[022] Batch [3449]/[3760] Speed: 68.283225 samples/sec accuracy=61.472826 loss=1.576757 lr=0.010000 Epoch[022] Batch [3499]/[3760] Speed: 67.738946 samples/sec accuracy=61.489732 loss=1.576096 lr=0.010000 Epoch[022] Batch [3549]/[3760] Speed: 67.905514 samples/sec accuracy=61.480194 loss=1.576318 lr=0.010000 Epoch[022] Batch [3599]/[3760] Speed: 68.248824 samples/sec accuracy=61.462240 loss=1.576973 lr=0.010000 Epoch[022] Batch [3649]/[3760] Speed: 67.952208 samples/sec accuracy=61.457620 loss=1.577562 lr=0.010000 Epoch[022] Batch [3699]/[3760] Speed: 68.268192 samples/sec accuracy=61.439611 loss=1.578606 lr=0.010000 Epoch[022] Batch [3749]/[3760] Speed: 74.832133 samples/sec accuracy=61.450000 loss=1.578462 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.812500 acc-top5=81.718750 Batch [0099]/[0303]: acc-top1=59.031250 acc-top5=81.234375 Batch [0149]/[0303]: acc-top1=58.802083 acc-top5=81.541667 Batch [0199]/[0303]: acc-top1=58.968750 acc-top5=81.859375 Batch [0249]/[0303]: acc-top1=58.850000 acc-top5=81.912500 Batch [0299]/[0303]: acc-top1=58.968750 acc-top5=81.937500 [Epoch 022] training: accuracy=61.451961 loss=1.578460 [Epoch 022] speed: 67 samples/sec time cost: 3852.877202 [Epoch 022] validation: acc-top1=58.952145 acc-top5=81.966790 loss=1.854250 Epoch[023] Batch [0049]/[3759] Speed: 45.646084 samples/sec accuracy=63.656250 loss=1.538804 lr=0.010000 Epoch[023] Batch [0099]/[3759] Speed: 66.262636 samples/sec accuracy=63.078125 loss=1.544860 lr=0.010000 Epoch[023] Batch [0149]/[3759] Speed: 68.776314 samples/sec accuracy=62.697917 loss=1.542039 lr=0.010000 Epoch[023] Batch [0199]/[3759] Speed: 67.635643 samples/sec accuracy=62.835938 loss=1.524436 lr=0.010000 Epoch[023] Batch [0249]/[3759] Speed: 68.243828 samples/sec accuracy=62.781250 loss=1.522844 lr=0.010000 Epoch[023] Batch [0299]/[3759] Speed: 67.975971 samples/sec accuracy=62.848958 loss=1.513554 lr=0.010000 Epoch[023] Batch 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accuracy=61.966797 loss=1.550390 lr=0.010000 Epoch[023] Batch [0849]/[3759] Speed: 68.248741 samples/sec accuracy=61.981618 loss=1.549747 lr=0.010000 Epoch[023] Batch [0899]/[3759] Speed: 67.893547 samples/sec accuracy=61.888889 loss=1.553169 lr=0.010000 Epoch[023] Batch [0949]/[3759] Speed: 68.040926 samples/sec accuracy=61.824013 loss=1.553443 lr=0.010000 Epoch[023] Batch [0999]/[3759] Speed: 67.910235 samples/sec accuracy=61.835938 loss=1.553090 lr=0.010000 Epoch[023] Batch [1049]/[3759] Speed: 67.673594 samples/sec accuracy=61.815476 loss=1.554073 lr=0.010000 Epoch[023] Batch [1099]/[3759] Speed: 68.374813 samples/sec accuracy=61.894886 loss=1.551671 lr=0.010000 Epoch[023] Batch [1149]/[3759] Speed: 67.538114 samples/sec accuracy=61.894022 loss=1.553287 lr=0.010000 Epoch[023] Batch [1199]/[3759] Speed: 67.960780 samples/sec accuracy=61.928385 loss=1.553123 lr=0.010000 Epoch[023] Batch [1249]/[3759] Speed: 68.293997 samples/sec accuracy=61.916250 loss=1.552648 lr=0.010000 Epoch[023] 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accuracy=61.707755 loss=1.562617 lr=0.010000 Epoch[023] Batch [2749]/[3759] Speed: 67.966316 samples/sec accuracy=61.727841 loss=1.561812 lr=0.010000 Epoch[023] Batch [2799]/[3759] Speed: 68.186223 samples/sec accuracy=61.728795 loss=1.561480 lr=0.010000 Epoch[023] Batch [2849]/[3759] Speed: 67.828321 samples/sec accuracy=61.728618 loss=1.561523 lr=0.010000 Epoch[023] Batch [2899]/[3759] Speed: 68.593965 samples/sec accuracy=61.713362 loss=1.562122 lr=0.010000 Epoch[023] Batch [2949]/[3759] Speed: 67.685939 samples/sec accuracy=61.707627 loss=1.562963 lr=0.010000 Epoch[023] Batch [2999]/[3759] Speed: 68.285673 samples/sec accuracy=61.703125 loss=1.563992 lr=0.010000 Epoch[023] Batch [3049]/[3759] Speed: 68.454812 samples/sec accuracy=61.693648 loss=1.563973 lr=0.010000 Epoch[023] Batch [3099]/[3759] Speed: 67.793247 samples/sec accuracy=61.669355 loss=1.564981 lr=0.010000 Epoch[023] Batch [3149]/[3759] Speed: 68.683773 samples/sec accuracy=61.654266 loss=1.566069 lr=0.010000 Epoch[023] 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accuracy=61.595034 loss=1.570399 lr=0.010000 Epoch[023] Batch [3699]/[3759] Speed: 68.138658 samples/sec accuracy=61.597973 loss=1.570246 lr=0.010000 Epoch[023] Batch [3749]/[3759] Speed: 74.674320 samples/sec accuracy=61.600417 loss=1.569961 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.156250 acc-top5=81.718750 Batch [0099]/[0303]: acc-top1=58.359375 acc-top5=81.359375 Batch [0149]/[0303]: acc-top1=58.802083 acc-top5=81.885417 Batch [0199]/[0303]: acc-top1=58.992188 acc-top5=82.218750 Batch [0249]/[0303]: acc-top1=58.956250 acc-top5=82.037500 Batch [0299]/[0303]: acc-top1=58.953125 acc-top5=82.145833 [Epoch 023] training: accuracy=61.603402 loss=1.569983 [Epoch 023] speed: 67 samples/sec time cost: 3847.406427 [Epoch 023] validation: acc-top1=58.967616 acc-top5=82.167904 loss=1.884146 Epoch[024] Batch [0049]/[3760] Speed: 46.332138 samples/sec accuracy=63.125000 loss=1.494819 lr=0.010000 Epoch[024] Batch [0099]/[3760] Speed: 66.922890 samples/sec accuracy=63.062500 loss=1.506243 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lr=0.010000 Epoch[024] Batch [2999]/[3760] Speed: 67.901497 samples/sec accuracy=61.995312 loss=1.557061 lr=0.010000 Epoch[024] Batch [3049]/[3760] Speed: 68.236604 samples/sec accuracy=61.995389 loss=1.557512 lr=0.010000 Epoch[024] Batch [3099]/[3760] Speed: 68.073765 samples/sec accuracy=61.965726 loss=1.557987 lr=0.010000 Epoch[024] Batch [3149]/[3760] Speed: 67.778540 samples/sec accuracy=61.964286 loss=1.557787 lr=0.010000 Epoch[024] Batch [3199]/[3760] Speed: 68.293970 samples/sec accuracy=61.943359 loss=1.558881 lr=0.010000 Epoch[024] Batch [3249]/[3760] Speed: 67.970331 samples/sec accuracy=61.921635 loss=1.559163 lr=0.010000 Epoch[024] Batch [3299]/[3760] Speed: 67.589658 samples/sec accuracy=61.912405 loss=1.559405 lr=0.010000 Epoch[024] Batch [3349]/[3760] Speed: 67.773837 samples/sec accuracy=61.924907 loss=1.559080 lr=0.010000 Epoch[024] Batch [3399]/[3760] Speed: 67.982994 samples/sec accuracy=61.911305 loss=1.559589 lr=0.010000 Epoch[024] Batch [3449]/[3760] Speed: 68.114780 samples/sec accuracy=61.910326 loss=1.560279 lr=0.010000 Epoch[024] Batch [3499]/[3760] Speed: 67.478670 samples/sec accuracy=61.909375 loss=1.560233 lr=0.010000 Epoch[024] Batch [3549]/[3760] Speed: 68.103070 samples/sec accuracy=61.900968 loss=1.560839 lr=0.010000 Epoch[024] Batch [3599]/[3760] Speed: 68.285763 samples/sec accuracy=61.898438 loss=1.560887 lr=0.010000 Epoch[024] Batch [3649]/[3760] Speed: 67.780464 samples/sec accuracy=61.900685 loss=1.561113 lr=0.010000 Epoch[024] Batch [3699]/[3760] Speed: 67.958615 samples/sec accuracy=61.888091 loss=1.561951 lr=0.010000 Epoch[024] Batch [3749]/[3760] Speed: 74.810032 samples/sec accuracy=61.880417 loss=1.562091 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.343750 acc-top5=81.500000 Batch [0099]/[0303]: acc-top1=59.453125 acc-top5=81.500000 Batch [0149]/[0303]: acc-top1=59.583333 acc-top5=82.093750 Batch [0199]/[0303]: acc-top1=59.546875 acc-top5=82.335938 Batch [0249]/[0303]: acc-top1=59.487500 acc-top5=82.312500 Batch [0299]/[0303]: acc-top1=59.463542 acc-top5=82.593750 [Epoch 024] training: accuracy=61.894531 loss=1.561761 [Epoch 024] speed: 67 samples/sec time cost: 3849.244598 [Epoch 024] validation: acc-top1=59.488449 acc-top5=82.590759 loss=1.862602 Epoch[025] Batch [0049]/[3760] Speed: 45.383867 samples/sec accuracy=62.875000 loss=1.480887 lr=0.010000 Epoch[025] Batch [0099]/[3760] Speed: 66.985258 samples/sec accuracy=62.781250 loss=1.518290 lr=0.010000 Epoch[025] Batch [0149]/[3760] Speed: 68.816857 samples/sec accuracy=63.166667 loss=1.513677 lr=0.010000 Epoch[025] Batch [0199]/[3760] Speed: 67.921226 samples/sec accuracy=63.445312 loss=1.505539 lr=0.010000 Epoch[025] Batch [0249]/[3760] Speed: 68.495211 samples/sec accuracy=63.268750 loss=1.510938 lr=0.010000 Epoch[025] Batch [0299]/[3760] Speed: 68.097228 samples/sec accuracy=63.182292 loss=1.511079 lr=0.010000 Epoch[025] Batch [0349]/[3760] Speed: 67.483773 samples/sec accuracy=63.205357 loss=1.505925 lr=0.010000 Epoch[025] Batch 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accuracy=62.681985 loss=1.522330 lr=0.010000 Epoch[025] Batch [0899]/[3760] Speed: 67.975928 samples/sec accuracy=62.631944 loss=1.524496 lr=0.010000 Epoch[025] Batch [0949]/[3760] Speed: 67.875654 samples/sec accuracy=62.615132 loss=1.524484 lr=0.010000 Epoch[025] Batch [0999]/[3760] Speed: 68.425951 samples/sec accuracy=62.653125 loss=1.523663 lr=0.010000 Epoch[025] Batch [1049]/[3760] Speed: 67.529917 samples/sec accuracy=62.645833 loss=1.524992 lr=0.010000 Epoch[025] Batch [1099]/[3760] Speed: 67.927285 samples/sec accuracy=62.620739 loss=1.525388 lr=0.010000 Epoch[025] Batch [1149]/[3760] Speed: 68.076526 samples/sec accuracy=62.536685 loss=1.528301 lr=0.010000 Epoch[025] Batch [1199]/[3760] Speed: 68.322680 samples/sec accuracy=62.541667 loss=1.528049 lr=0.010000 Epoch[025] Batch [1249]/[3760] Speed: 68.260295 samples/sec accuracy=62.520000 loss=1.529492 lr=0.010000 Epoch[025] Batch [1299]/[3760] Speed: 68.144203 samples/sec accuracy=62.445913 loss=1.532278 lr=0.010000 Epoch[025] 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accuracy=62.378472 loss=1.533579 lr=0.010000 Epoch[025] Batch [1849]/[3760] Speed: 68.359865 samples/sec accuracy=62.405405 loss=1.533704 lr=0.010000 Epoch[025] Batch [1899]/[3760] Speed: 67.658042 samples/sec accuracy=62.401316 loss=1.534701 lr=0.010000 Epoch[025] Batch [1949]/[3760] Speed: 67.693460 samples/sec accuracy=62.411058 loss=1.534061 lr=0.010000 Epoch[025] Batch [1999]/[3760] Speed: 68.187794 samples/sec accuracy=62.382031 loss=1.535426 lr=0.010000 Epoch[025] Batch [2049]/[3760] Speed: 68.038468 samples/sec accuracy=62.360518 loss=1.536636 lr=0.010000 Epoch[025] Batch [2099]/[3760] Speed: 67.618117 samples/sec accuracy=62.354911 loss=1.537213 lr=0.010000 Epoch[025] Batch [2149]/[3760] Speed: 68.466408 samples/sec accuracy=62.332122 loss=1.538311 lr=0.010000 Epoch[025] Batch [2199]/[3760] Speed: 67.794242 samples/sec accuracy=62.286222 loss=1.540459 lr=0.010000 Epoch[025] Batch [2249]/[3760] Speed: 68.033416 samples/sec accuracy=62.270139 loss=1.541447 lr=0.010000 Epoch[025] 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accuracy=62.214773 loss=1.542704 lr=0.010000 Epoch[025] Batch [2799]/[3760] Speed: 67.722613 samples/sec accuracy=62.221540 loss=1.542305 lr=0.010000 Epoch[025] Batch [2849]/[3760] Speed: 68.203173 samples/sec accuracy=62.197917 loss=1.543338 lr=0.010000 Epoch[025] Batch [2899]/[3760] Speed: 68.090212 samples/sec accuracy=62.189655 loss=1.543848 lr=0.010000 Epoch[025] Batch [2949]/[3760] Speed: 68.337052 samples/sec accuracy=62.157309 loss=1.545422 lr=0.010000 Epoch[025] Batch [2999]/[3760] Speed: 67.943734 samples/sec accuracy=62.155729 loss=1.545422 lr=0.010000 Epoch[025] Batch [3049]/[3760] Speed: 68.086583 samples/sec accuracy=62.167008 loss=1.545212 lr=0.010000 Epoch[025] Batch [3099]/[3760] Speed: 68.473042 samples/sec accuracy=62.153226 loss=1.546669 lr=0.010000 Epoch[025] Batch [3149]/[3760] Speed: 68.511296 samples/sec accuracy=62.165179 loss=1.547087 lr=0.010000 Epoch[025] Batch [3199]/[3760] Speed: 68.027333 samples/sec accuracy=62.163574 loss=1.547528 lr=0.010000 Epoch[025] 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accuracy=62.078547 loss=1.550766 lr=0.010000 Epoch[025] Batch [3749]/[3760] Speed: 74.727411 samples/sec accuracy=62.068333 loss=1.551405 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.062500 acc-top5=82.062500 Batch [0099]/[0303]: acc-top1=58.609375 acc-top5=81.718750 Batch [0149]/[0303]: acc-top1=59.020833 acc-top5=82.020833 Batch [0199]/[0303]: acc-top1=59.437500 acc-top5=82.414062 Batch [0249]/[0303]: acc-top1=59.606250 acc-top5=82.393750 Batch [0299]/[0303]: acc-top1=59.562500 acc-top5=82.552083 [Epoch 025] training: accuracy=62.062832 loss=1.551744 [Epoch 025] speed: 67 samples/sec time cost: 3843.786358 [Epoch 025] validation: acc-top1=59.581271 acc-top5=82.559818 loss=1.822449 Epoch[026] Batch [0049]/[3759] Speed: 45.567802 samples/sec accuracy=63.937500 loss=1.486715 lr=0.010000 Epoch[026] Batch [0099]/[3759] Speed: 66.722654 samples/sec accuracy=64.000000 loss=1.477642 lr=0.010000 Epoch[026] Batch [0149]/[3759] Speed: 68.767835 samples/sec accuracy=63.322917 loss=1.496989 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lr=0.010000 Epoch[026] Batch [1149]/[3759] Speed: 67.552189 samples/sec accuracy=62.445652 loss=1.524975 lr=0.010000 Epoch[026] Batch [1199]/[3759] Speed: 67.879780 samples/sec accuracy=62.365885 loss=1.528147 lr=0.010000 Epoch[026] Batch [1249]/[3759] Speed: 68.077803 samples/sec accuracy=62.353750 loss=1.528868 lr=0.010000 Epoch[026] Batch [1299]/[3759] Speed: 67.511894 samples/sec accuracy=62.343750 loss=1.528764 lr=0.010000 Epoch[026] Batch [1349]/[3759] Speed: 68.122083 samples/sec accuracy=62.332176 loss=1.528945 lr=0.010000 Epoch[026] Batch [1399]/[3759] Speed: 67.909687 samples/sec accuracy=62.318080 loss=1.530400 lr=0.010000 Epoch[026] Batch [1449]/[3759] Speed: 68.326180 samples/sec accuracy=62.273707 loss=1.531453 lr=0.010000 Epoch[026] Batch [1499]/[3759] Speed: 68.215437 samples/sec accuracy=62.278125 loss=1.531812 lr=0.010000 Epoch[026] Batch [1549]/[3759] Speed: 67.682709 samples/sec accuracy=62.278226 loss=1.530688 lr=0.010000 Epoch[026] Batch [1599]/[3759] Speed: 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lr=0.010000 Epoch[026] Batch [2099]/[3759] Speed: 67.468383 samples/sec accuracy=62.202381 loss=1.535447 lr=0.010000 Epoch[026] Batch [2149]/[3759] Speed: 68.176732 samples/sec accuracy=62.206395 loss=1.535810 lr=0.010000 Epoch[026] Batch [2199]/[3759] Speed: 68.189242 samples/sec accuracy=62.188210 loss=1.535917 lr=0.010000 Epoch[026] Batch [2249]/[3759] Speed: 68.232849 samples/sec accuracy=62.195833 loss=1.536204 lr=0.010000 Epoch[026] Batch [2299]/[3759] Speed: 68.009055 samples/sec accuracy=62.190897 loss=1.537260 lr=0.010000 Epoch[026] Batch [2349]/[3759] Speed: 68.212056 samples/sec accuracy=62.174202 loss=1.538150 lr=0.010000 Epoch[026] Batch [2399]/[3759] Speed: 67.737685 samples/sec accuracy=62.169271 loss=1.537912 lr=0.010000 Epoch[026] Batch [2449]/[3759] Speed: 68.849299 samples/sec accuracy=62.200255 loss=1.537602 lr=0.010000 Epoch[026] Batch [2499]/[3759] Speed: 67.754138 samples/sec accuracy=62.215000 loss=1.537590 lr=0.010000 Epoch[026] Batch [2549]/[3759] Speed: 68.041826 samples/sec accuracy=62.207721 loss=1.537782 lr=0.010000 Epoch[026] Batch [2599]/[3759] Speed: 68.265944 samples/sec accuracy=62.205529 loss=1.538538 lr=0.010000 Epoch[026] Batch [2649]/[3759] Speed: 68.621290 samples/sec accuracy=62.200472 loss=1.538084 lr=0.010000 Epoch[026] Batch [2699]/[3759] Speed: 67.626871 samples/sec accuracy=62.202546 loss=1.537899 lr=0.010000 Epoch[026] Batch [2749]/[3759] Speed: 68.002533 samples/sec accuracy=62.175000 loss=1.539251 lr=0.010000 Epoch[026] Batch [2799]/[3759] Speed: 67.669586 samples/sec accuracy=62.176339 loss=1.539698 lr=0.010000 Epoch[026] Batch [2849]/[3759] Speed: 68.043866 samples/sec accuracy=62.167763 loss=1.539825 lr=0.010000 Epoch[026] Batch [2899]/[3759] Speed: 68.086581 samples/sec accuracy=62.168103 loss=1.539886 lr=0.010000 Epoch[026] Batch [2949]/[3759] Speed: 67.976217 samples/sec accuracy=62.153072 loss=1.540952 lr=0.010000 Epoch[026] Batch [2999]/[3759] Speed: 68.427297 samples/sec accuracy=62.137500 loss=1.541528 lr=0.010000 Epoch[026] Batch [3049]/[3759] Speed: 67.474686 samples/sec accuracy=62.116291 loss=1.541789 lr=0.010000 Epoch[026] Batch [3099]/[3759] Speed: 68.027295 samples/sec accuracy=62.093750 loss=1.542707 lr=0.010000 Epoch[026] Batch [3149]/[3759] Speed: 67.928268 samples/sec accuracy=62.074901 loss=1.543558 lr=0.010000 Epoch[026] Batch [3199]/[3759] Speed: 67.123522 samples/sec accuracy=62.080078 loss=1.543576 lr=0.010000 Epoch[026] Batch [3249]/[3759] Speed: 67.503117 samples/sec accuracy=62.074519 loss=1.543810 lr=0.010000 Epoch[026] Batch [3299]/[3759] Speed: 67.885991 samples/sec accuracy=62.089015 loss=1.543726 lr=0.010000 Epoch[026] Batch [3349]/[3759] Speed: 68.712907 samples/sec accuracy=62.078825 loss=1.544130 lr=0.010000 Epoch[026] Batch [3399]/[3759] Speed: 67.840501 samples/sec accuracy=62.068934 loss=1.544045 lr=0.010000 Epoch[026] Batch [3449]/[3759] Speed: 68.062577 samples/sec accuracy=62.049366 loss=1.544673 lr=0.010000 Epoch[026] Batch [3499]/[3759] Speed: 67.878140 samples/sec accuracy=62.025893 loss=1.545486 lr=0.010000 Epoch[026] Batch [3549]/[3759] Speed: 67.996773 samples/sec accuracy=62.024208 loss=1.545140 lr=0.010000 Epoch[026] Batch [3599]/[3759] Speed: 67.545721 samples/sec accuracy=62.024740 loss=1.545527 lr=0.010000 Epoch[026] Batch [3649]/[3759] Speed: 67.944514 samples/sec accuracy=62.030394 loss=1.545711 lr=0.010000 Epoch[026] Batch [3699]/[3759] Speed: 68.292519 samples/sec accuracy=62.021115 loss=1.546315 lr=0.010000 Epoch[026] Batch [3749]/[3759] Speed: 74.707482 samples/sec accuracy=62.027083 loss=1.546211 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.500000 acc-top5=81.343750 Batch [0099]/[0303]: acc-top1=59.218750 acc-top5=81.109375 Batch [0149]/[0303]: acc-top1=59.479167 acc-top5=81.739583 Batch [0199]/[0303]: acc-top1=59.679688 acc-top5=82.078125 Batch [0249]/[0303]: acc-top1=59.618750 acc-top5=82.131250 Batch [0299]/[0303]: acc-top1=59.583333 acc-top5=82.276042 [Epoch 026] training: accuracy=62.031957 loss=1.546271 [Epoch 026] speed: 67 samples/sec time cost: 3852.247506 [Epoch 026] validation: acc-top1=59.612211 acc-top5=82.301980 loss=1.815655 Epoch[027] Batch [0049]/[3760] Speed: 45.815818 samples/sec accuracy=62.343750 loss=1.528956 lr=0.010000 Epoch[027] Batch [0099]/[3760] Speed: 67.134766 samples/sec accuracy=62.468750 loss=1.536466 lr=0.010000 Epoch[027] Batch [0149]/[3760] Speed: 67.942262 samples/sec accuracy=63.072917 loss=1.513714 lr=0.010000 Epoch[027] Batch [0199]/[3760] Speed: 67.551942 samples/sec accuracy=62.992188 loss=1.520240 lr=0.010000 Epoch[027] Batch [0249]/[3760] Speed: 68.196253 samples/sec accuracy=63.175000 loss=1.513601 lr=0.010000 Epoch[027] Batch [0299]/[3760] Speed: 68.387879 samples/sec accuracy=63.041667 loss=1.518031 lr=0.010000 Epoch[027] Batch [0349]/[3760] Speed: 68.255579 samples/sec accuracy=62.839286 loss=1.519426 lr=0.010000 Epoch[027] Batch [0399]/[3760] Speed: 68.145831 samples/sec accuracy=62.953125 loss=1.519760 lr=0.010000 Epoch[027] Batch 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accuracy=62.803819 loss=1.525119 lr=0.010000 Epoch[027] Batch [0949]/[3760] Speed: 67.957466 samples/sec accuracy=62.802632 loss=1.524272 lr=0.010000 Epoch[027] Batch [0999]/[3760] Speed: 67.525603 samples/sec accuracy=62.784375 loss=1.525964 lr=0.010000 Epoch[027] Batch [1049]/[3760] Speed: 68.063814 samples/sec accuracy=62.828869 loss=1.525060 lr=0.010000 Epoch[027] Batch [1099]/[3760] Speed: 67.857148 samples/sec accuracy=62.846591 loss=1.523051 lr=0.010000 Epoch[027] Batch [1149]/[3760] Speed: 67.822240 samples/sec accuracy=62.849185 loss=1.523303 lr=0.010000 Epoch[027] Batch [1199]/[3760] Speed: 68.224082 samples/sec accuracy=62.751302 loss=1.527873 lr=0.010000 Epoch[027] Batch [1249]/[3760] Speed: 67.462416 samples/sec accuracy=62.762500 loss=1.528613 lr=0.010000 Epoch[027] Batch [1299]/[3760] Speed: 67.725151 samples/sec accuracy=62.757212 loss=1.528564 lr=0.010000 Epoch[027] Batch [1349]/[3760] Speed: 67.711447 samples/sec accuracy=62.787037 loss=1.527664 lr=0.010000 Epoch[027] 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accuracy=62.688345 loss=1.527880 lr=0.010000 Epoch[027] Batch [1899]/[3760] Speed: 67.793332 samples/sec accuracy=62.652961 loss=1.529587 lr=0.010000 Epoch[027] Batch [1949]/[3760] Speed: 68.075298 samples/sec accuracy=62.657853 loss=1.529352 lr=0.010000 Epoch[027] Batch [1999]/[3760] Speed: 67.534671 samples/sec accuracy=62.650000 loss=1.529818 lr=0.010000 Epoch[027] Batch [2049]/[3760] Speed: 68.317342 samples/sec accuracy=62.603659 loss=1.530054 lr=0.010000 Epoch[027] Batch [2099]/[3760] Speed: 68.266451 samples/sec accuracy=62.577381 loss=1.531622 lr=0.010000 Epoch[027] Batch [2149]/[3760] Speed: 68.142655 samples/sec accuracy=62.572674 loss=1.531857 lr=0.010000 Epoch[027] Batch [2199]/[3760] Speed: 67.558710 samples/sec accuracy=62.560369 loss=1.532285 lr=0.010000 Epoch[027] Batch [2249]/[3760] Speed: 68.193321 samples/sec accuracy=62.564583 loss=1.531822 lr=0.010000 Epoch[027] Batch [2299]/[3760] Speed: 68.098589 samples/sec accuracy=62.550951 loss=1.531420 lr=0.010000 Epoch[027] 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accuracy=62.498326 loss=1.535323 lr=0.010000 Epoch[027] Batch [2849]/[3760] Speed: 67.932981 samples/sec accuracy=62.496162 loss=1.535243 lr=0.010000 Epoch[027] Batch [2899]/[3760] Speed: 68.628871 samples/sec accuracy=62.455280 loss=1.536813 lr=0.010000 Epoch[027] Batch [2949]/[3760] Speed: 67.950651 samples/sec accuracy=62.435381 loss=1.537842 lr=0.010000 Epoch[027] Batch [2999]/[3760] Speed: 67.997612 samples/sec accuracy=62.453646 loss=1.537531 lr=0.010000 Epoch[027] Batch [3049]/[3760] Speed: 67.724007 samples/sec accuracy=62.447746 loss=1.538025 lr=0.010000 Epoch[027] Batch [3099]/[3760] Speed: 68.170867 samples/sec accuracy=62.435988 loss=1.538171 lr=0.010000 Epoch[027] Batch [3149]/[3760] Speed: 67.832941 samples/sec accuracy=62.445933 loss=1.537885 lr=0.010000 Epoch[027] Batch [3199]/[3760] Speed: 67.970117 samples/sec accuracy=62.402344 loss=1.539392 lr=0.010000 Epoch[027] Batch [3249]/[3760] Speed: 68.210033 samples/sec accuracy=62.381250 loss=1.539678 lr=0.010000 Epoch[027] Batch [3299]/[3760] Speed: 67.997646 samples/sec accuracy=62.379261 loss=1.539741 lr=0.010000 Epoch[027] Batch [3349]/[3760] Speed: 67.713235 samples/sec accuracy=62.386660 loss=1.539505 lr=0.010000 Epoch[027] Batch [3399]/[3760] Speed: 67.988018 samples/sec accuracy=62.349724 loss=1.540560 lr=0.010000 Epoch[027] Batch [3449]/[3760] Speed: 67.835533 samples/sec accuracy=62.336051 loss=1.540449 lr=0.010000 Epoch[027] Batch [3499]/[3760] Speed: 67.527628 samples/sec accuracy=62.326339 loss=1.540650 lr=0.010000 Epoch[027] Batch [3549]/[3760] Speed: 68.527981 samples/sec accuracy=62.311180 loss=1.541096 lr=0.010000 Epoch[027] Batch [3599]/[3760] Speed: 68.001865 samples/sec accuracy=62.332899 loss=1.540041 lr=0.010000 Epoch[027] Batch [3649]/[3760] Speed: 67.477244 samples/sec accuracy=62.354880 loss=1.539488 lr=0.010000 Epoch[027] Batch [3699]/[3760] Speed: 68.660254 samples/sec accuracy=62.340794 loss=1.539808 lr=0.010000 Epoch[027] Batch [3749]/[3760] Speed: 74.284810 samples/sec accuracy=62.343750 loss=1.539782 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.500000 acc-top5=82.218750 Batch [0099]/[0303]: acc-top1=59.000000 acc-top5=81.390625 Batch [0149]/[0303]: acc-top1=59.239583 acc-top5=81.843750 Batch [0199]/[0303]: acc-top1=59.664062 acc-top5=82.296875 Batch [0249]/[0303]: acc-top1=59.606250 acc-top5=82.293750 Batch [0299]/[0303]: acc-top1=59.552083 acc-top5=82.468750 [Epoch 027] training: accuracy=62.349152 loss=1.539751 [Epoch 027] speed: 67 samples/sec time cost: 3852.681216 [Epoch 027] validation: acc-top1=59.529703 acc-top5=82.477310 loss=1.887817 Epoch[028] Batch [0049]/[3760] Speed: 45.750123 samples/sec accuracy=63.437500 loss=1.517350 lr=0.010000 Epoch[028] Batch [0099]/[3760] Speed: 66.444278 samples/sec accuracy=63.359375 loss=1.475654 lr=0.010000 Epoch[028] Batch [0149]/[3760] Speed: 68.531606 samples/sec accuracy=62.968750 loss=1.495016 lr=0.010000 Epoch[028] Batch [0199]/[3760] Speed: 67.580428 samples/sec accuracy=62.937500 loss=1.497735 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lr=0.010000 Epoch[028] Batch [3099]/[3760] Speed: 68.407594 samples/sec accuracy=62.561492 loss=1.529473 lr=0.010000 Epoch[028] Batch [3149]/[3760] Speed: 68.261095 samples/sec accuracy=62.558532 loss=1.529636 lr=0.010000 Epoch[028] Batch [3199]/[3760] Speed: 68.080426 samples/sec accuracy=62.544922 loss=1.530648 lr=0.010000 Epoch[028] Batch [3249]/[3760] Speed: 67.771624 samples/sec accuracy=62.533173 loss=1.531233 lr=0.010000 Epoch[028] Batch [3299]/[3760] Speed: 67.907485 samples/sec accuracy=62.524148 loss=1.530996 lr=0.010000 Epoch[028] Batch [3349]/[3760] Speed: 68.196140 samples/sec accuracy=62.501399 loss=1.531427 lr=0.010000 Epoch[028] Batch [3399]/[3760] Speed: 68.433376 samples/sec accuracy=62.515165 loss=1.531754 lr=0.010000 Epoch[028] Batch [3449]/[3760] Speed: 67.340325 samples/sec accuracy=62.513587 loss=1.531854 lr=0.010000 Epoch[028] Batch [3499]/[3760] Speed: 68.670052 samples/sec accuracy=62.489732 loss=1.532709 lr=0.010000 Epoch[028] Batch [3549]/[3760] Speed: 67.990678 samples/sec accuracy=62.488556 loss=1.532733 lr=0.010000 Epoch[028] Batch [3599]/[3760] Speed: 67.988687 samples/sec accuracy=62.492187 loss=1.532736 lr=0.010000 Epoch[028] Batch [3649]/[3760] Speed: 68.027762 samples/sec accuracy=62.486729 loss=1.532910 lr=0.010000 Epoch[028] Batch [3699]/[3760] Speed: 68.075412 samples/sec accuracy=62.472128 loss=1.533357 lr=0.010000 Epoch[028] Batch [3749]/[3760] Speed: 74.904253 samples/sec accuracy=62.444167 loss=1.534179 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.531250 acc-top5=82.218750 Batch [0099]/[0303]: acc-top1=59.609375 acc-top5=81.765625 Batch [0149]/[0303]: acc-top1=60.020833 acc-top5=82.197917 Batch [0199]/[0303]: acc-top1=60.109375 acc-top5=82.414062 Batch [0249]/[0303]: acc-top1=59.956250 acc-top5=82.375000 Batch [0299]/[0303]: acc-top1=59.932292 acc-top5=82.588542 [Epoch 028] training: accuracy=62.437666 loss=1.534556 [Epoch 028] speed: 67 samples/sec time cost: 3849.937530 [Epoch 028] validation: acc-top1=59.968028 acc-top5=82.601073 loss=1.776769 Epoch[029] Batch [0049]/[3759] Speed: 45.756357 samples/sec accuracy=64.593750 loss=1.489382 lr=0.010000 Epoch[029] Batch [0099]/[3759] Speed: 66.888880 samples/sec accuracy=63.828125 loss=1.488329 lr=0.010000 Epoch[029] Batch [0149]/[3759] Speed: 67.962366 samples/sec accuracy=63.770833 loss=1.476766 lr=0.010000 Epoch[029] Batch [0199]/[3759] Speed: 68.462670 samples/sec accuracy=63.679688 loss=1.479671 lr=0.010000 Epoch[029] Batch [0249]/[3759] Speed: 67.905044 samples/sec accuracy=63.612500 loss=1.478912 lr=0.010000 Epoch[029] Batch [0299]/[3759] Speed: 68.352932 samples/sec accuracy=63.489583 loss=1.485204 lr=0.010000 Epoch[029] Batch [0349]/[3759] Speed: 68.262077 samples/sec accuracy=63.441964 loss=1.485369 lr=0.010000 Epoch[029] Batch [0399]/[3759] Speed: 67.470312 samples/sec accuracy=63.484375 loss=1.483791 lr=0.010000 Epoch[029] Batch [0449]/[3759] Speed: 67.894195 samples/sec accuracy=63.392361 loss=1.486794 lr=0.010000 Epoch[029] Batch 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accuracy=62.926809 loss=1.509830 lr=0.010000 Epoch[029] Batch [1949]/[3759] Speed: 68.448039 samples/sec accuracy=62.883814 loss=1.511191 lr=0.010000 Epoch[029] Batch [1999]/[3759] Speed: 68.120578 samples/sec accuracy=62.905469 loss=1.510334 lr=0.010000 Epoch[029] Batch [2049]/[3759] Speed: 68.087215 samples/sec accuracy=62.914634 loss=1.510411 lr=0.010000 Epoch[029] Batch [2099]/[3759] Speed: 67.191283 samples/sec accuracy=62.901786 loss=1.510664 lr=0.010000 Epoch[029] Batch [2149]/[3759] Speed: 68.097486 samples/sec accuracy=62.872093 loss=1.513078 lr=0.010000 Epoch[029] Batch [2199]/[3759] Speed: 67.732175 samples/sec accuracy=62.909091 loss=1.512165 lr=0.010000 Epoch[029] Batch [2249]/[3759] Speed: 68.113459 samples/sec accuracy=62.911806 loss=1.511390 lr=0.010000 Epoch[029] Batch [2299]/[3759] Speed: 68.285164 samples/sec accuracy=62.955163 loss=1.510911 lr=0.010000 Epoch[029] Batch [2349]/[3759] Speed: 67.629750 samples/sec accuracy=62.949468 loss=1.511332 lr=0.010000 Epoch[029] 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accuracy=62.813048 loss=1.515251 lr=0.010000 Epoch[029] Batch [2899]/[3759] Speed: 68.687139 samples/sec accuracy=62.798491 loss=1.516115 lr=0.010000 Epoch[029] Batch [2949]/[3759] Speed: 67.474518 samples/sec accuracy=62.744703 loss=1.518389 lr=0.010000 Epoch[029] Batch [2999]/[3759] Speed: 68.082515 samples/sec accuracy=62.741667 loss=1.518580 lr=0.010000 Epoch[029] Batch [3049]/[3759] Speed: 67.609505 samples/sec accuracy=62.725922 loss=1.518994 lr=0.010000 Epoch[029] Batch [3099]/[3759] Speed: 68.326453 samples/sec accuracy=62.706653 loss=1.519263 lr=0.010000 Epoch[029] Batch [3149]/[3759] Speed: 67.923952 samples/sec accuracy=62.698909 loss=1.519932 lr=0.010000 Epoch[029] Batch [3199]/[3759] Speed: 67.932925 samples/sec accuracy=62.697754 loss=1.519927 lr=0.010000 Epoch[029] Batch [3249]/[3759] Speed: 67.780363 samples/sec accuracy=62.699519 loss=1.520129 lr=0.010000 Epoch[029] Batch [3299]/[3759] Speed: 68.368528 samples/sec accuracy=62.691288 loss=1.520302 lr=0.010000 Epoch[029] 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[0099]/[0303]: acc-top1=59.500000 acc-top5=82.078125 Batch [0149]/[0303]: acc-top1=59.770833 acc-top5=82.312500 Batch [0199]/[0303]: acc-top1=59.945312 acc-top5=82.570312 Batch [0249]/[0303]: acc-top1=60.000000 acc-top5=82.500000 Batch [0299]/[0303]: acc-top1=59.833333 acc-top5=82.640625 [Epoch 029] training: accuracy=62.594773 loss=1.523035 [Epoch 029] speed: 67 samples/sec time cost: 3852.616601 [Epoch 029] validation: acc-top1=59.828795 acc-top5=82.662954 loss=1.841019 Epoch[030] Batch [0049]/[3760] Speed: 45.632015 samples/sec accuracy=64.531250 loss=1.428025 lr=0.010000 Epoch[030] Batch [0099]/[3760] Speed: 66.420269 samples/sec accuracy=64.015625 loss=1.443445 lr=0.010000 Epoch[030] Batch [0149]/[3760] Speed: 68.299910 samples/sec accuracy=64.041667 loss=1.446579 lr=0.010000 Epoch[030] Batch [0199]/[3760] Speed: 67.841148 samples/sec accuracy=63.671875 loss=1.465972 lr=0.010000 Epoch[030] Batch [0249]/[3760] Speed: 68.000233 samples/sec accuracy=63.331250 loss=1.476797 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lr=0.010000 Epoch[030] Batch [1249]/[3760] Speed: 68.108758 samples/sec accuracy=63.335000 loss=1.487956 lr=0.010000 Epoch[030] Batch [1299]/[3760] Speed: 68.185787 samples/sec accuracy=63.420673 loss=1.485524 lr=0.010000 Epoch[030] Batch [1349]/[3760] Speed: 67.817625 samples/sec accuracy=63.402778 loss=1.487286 lr=0.010000 Epoch[030] Batch [1399]/[3760] Speed: 68.154245 samples/sec accuracy=63.364955 loss=1.488523 lr=0.010000 Epoch[030] Batch [1449]/[3760] Speed: 68.547256 samples/sec accuracy=63.371767 loss=1.488723 lr=0.010000 Epoch[030] Batch [1499]/[3760] Speed: 67.992178 samples/sec accuracy=63.407292 loss=1.487731 lr=0.010000 Epoch[030] Batch [1549]/[3760] Speed: 67.820904 samples/sec accuracy=63.341734 loss=1.490529 lr=0.010000 Epoch[030] Batch [1599]/[3760] Speed: 67.847248 samples/sec accuracy=63.313477 loss=1.490678 lr=0.010000 Epoch[030] Batch [1649]/[3760] Speed: 67.970820 samples/sec accuracy=63.319129 loss=1.490796 lr=0.010000 Epoch[030] Batch [1699]/[3760] Speed: 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lr=0.010000 Epoch[030] Batch [2199]/[3760] Speed: 67.903664 samples/sec accuracy=63.137074 loss=1.498171 lr=0.010000 Epoch[030] Batch [2249]/[3760] Speed: 67.870570 samples/sec accuracy=63.152778 loss=1.497965 lr=0.010000 Epoch[030] Batch [2299]/[3760] Speed: 67.851364 samples/sec accuracy=63.136549 loss=1.499229 lr=0.010000 Epoch[030] Batch [2349]/[3760] Speed: 68.263741 samples/sec accuracy=63.103059 loss=1.500103 lr=0.010000 Epoch[030] Batch [2399]/[3760] Speed: 67.902435 samples/sec accuracy=63.069010 loss=1.501088 lr=0.010000 Epoch[030] Batch [2449]/[3760] Speed: 68.139370 samples/sec accuracy=63.070153 loss=1.500293 lr=0.010000 Epoch[030] Batch [2499]/[3760] Speed: 68.205324 samples/sec accuracy=63.086875 loss=1.499702 lr=0.010000 Epoch[030] Batch [2549]/[3760] Speed: 68.618784 samples/sec accuracy=63.098652 loss=1.499304 lr=0.010000 Epoch[030] Batch [2599]/[3760] Speed: 67.980235 samples/sec accuracy=63.039062 loss=1.501020 lr=0.010000 Epoch[030] Batch [2649]/[3760] Speed: 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lr=0.010000 Epoch[030] Batch [3149]/[3760] Speed: 67.615253 samples/sec accuracy=62.969246 loss=1.505415 lr=0.010000 Epoch[030] Batch [3199]/[3760] Speed: 67.890319 samples/sec accuracy=62.909668 loss=1.507278 lr=0.010000 Epoch[030] Batch [3249]/[3760] Speed: 68.013204 samples/sec accuracy=62.911538 loss=1.507558 lr=0.010000 Epoch[030] Batch [3299]/[3760] Speed: 68.243522 samples/sec accuracy=62.917140 loss=1.507863 lr=0.010000 Epoch[030] Batch [3349]/[3760] Speed: 68.077521 samples/sec accuracy=62.912313 loss=1.507988 lr=0.010000 Epoch[030] Batch [3399]/[3760] Speed: 67.479996 samples/sec accuracy=62.880974 loss=1.508946 lr=0.010000 Epoch[030] Batch [3449]/[3760] Speed: 67.505280 samples/sec accuracy=62.887681 loss=1.508995 lr=0.010000 Epoch[030] Batch [3499]/[3760] Speed: 68.528091 samples/sec accuracy=62.879018 loss=1.509582 lr=0.010000 Epoch[030] Batch [3549]/[3760] Speed: 68.089923 samples/sec accuracy=62.885123 loss=1.509073 lr=0.010000 Epoch[030] Batch [3599]/[3760] Speed: 68.202818 samples/sec accuracy=62.869792 loss=1.509989 lr=0.010000 Epoch[030] Batch [3649]/[3760] Speed: 67.482182 samples/sec accuracy=62.854024 loss=1.510353 lr=0.010000 Epoch[030] Batch [3699]/[3760] Speed: 68.261971 samples/sec accuracy=62.834882 loss=1.511511 lr=0.010000 Epoch[030] Batch [3749]/[3760] Speed: 74.076740 samples/sec accuracy=62.842500 loss=1.511507 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.625000 acc-top5=82.031250 Batch [0099]/[0303]: acc-top1=59.484375 acc-top5=81.718750 Batch [0149]/[0303]: acc-top1=59.614583 acc-top5=82.197917 Batch [0199]/[0303]: acc-top1=59.554688 acc-top5=82.476562 Batch [0249]/[0303]: acc-top1=59.718750 acc-top5=82.425000 Batch [0299]/[0303]: acc-top1=59.776042 acc-top5=82.484375 [Epoch 030] training: accuracy=62.846576 loss=1.511638 [Epoch 030] speed: 67 samples/sec time cost: 3853.979892 [Epoch 030] validation: acc-top1=59.803012 acc-top5=82.534035 loss=1.833875 Epoch[031] Batch [0049]/[3760] Speed: 45.239775 samples/sec accuracy=64.468750 loss=1.450327 lr=0.010000 Epoch[031] Batch [0099]/[3760] Speed: 66.511907 samples/sec accuracy=63.906250 loss=1.487122 lr=0.010000 Epoch[031] Batch [0149]/[3760] Speed: 68.370358 samples/sec accuracy=62.822917 loss=1.503193 lr=0.010000 Epoch[031] Batch [0199]/[3760] Speed: 67.631478 samples/sec accuracy=62.984375 loss=1.491254 lr=0.010000 Epoch[031] Batch [0249]/[3760] Speed: 67.954397 samples/sec accuracy=63.075000 loss=1.487914 lr=0.010000 Epoch[031] Batch [0299]/[3760] Speed: 68.269757 samples/sec accuracy=63.260417 loss=1.482116 lr=0.010000 Epoch[031] Batch [0349]/[3760] Speed: 67.712522 samples/sec accuracy=63.500000 loss=1.478048 lr=0.010000 Epoch[031] Batch [0399]/[3760] Speed: 68.013589 samples/sec accuracy=63.562500 loss=1.474637 lr=0.010000 Epoch[031] Batch [0449]/[3760] Speed: 67.777579 samples/sec accuracy=63.569444 loss=1.475897 lr=0.010000 Epoch[031] Batch [0499]/[3760] Speed: 68.295064 samples/sec accuracy=63.518750 loss=1.477549 lr=0.010000 Epoch[031] 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accuracy=63.459375 loss=1.482190 lr=0.010000 Epoch[031] Batch [1049]/[3760] Speed: 68.242639 samples/sec accuracy=63.430060 loss=1.483676 lr=0.010000 Epoch[031] Batch [1099]/[3760] Speed: 68.084331 samples/sec accuracy=63.524148 loss=1.482428 lr=0.010000 Epoch[031] Batch [1149]/[3760] Speed: 68.152689 samples/sec accuracy=63.485054 loss=1.483845 lr=0.010000 Epoch[031] Batch [1199]/[3760] Speed: 68.329465 samples/sec accuracy=63.472656 loss=1.484717 lr=0.010000 Epoch[031] Batch [1249]/[3760] Speed: 67.706756 samples/sec accuracy=63.451250 loss=1.486052 lr=0.010000 Epoch[031] Batch [1299]/[3760] Speed: 68.153020 samples/sec accuracy=63.409856 loss=1.488179 lr=0.010000 Epoch[031] Batch [1349]/[3760] Speed: 67.848168 samples/sec accuracy=63.361111 loss=1.490371 lr=0.010000 Epoch[031] Batch [1399]/[3760] Speed: 67.956346 samples/sec accuracy=63.297991 loss=1.493625 lr=0.010000 Epoch[031] Batch [1449]/[3760] Speed: 67.605477 samples/sec accuracy=63.242457 loss=1.496755 lr=0.010000 Epoch[031] 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accuracy=63.096955 loss=1.499420 lr=0.010000 Epoch[031] Batch [1999]/[3760] Speed: 68.244209 samples/sec accuracy=63.078906 loss=1.499491 lr=0.010000 Epoch[031] Batch [2049]/[3760] Speed: 67.657626 samples/sec accuracy=63.062500 loss=1.500383 lr=0.010000 Epoch[031] Batch [2099]/[3760] Speed: 67.639737 samples/sec accuracy=63.045387 loss=1.500599 lr=0.010000 Epoch[031] Batch [2149]/[3760] Speed: 68.179224 samples/sec accuracy=63.058140 loss=1.500376 lr=0.010000 Epoch[031] Batch [2199]/[3760] Speed: 68.147381 samples/sec accuracy=63.053977 loss=1.500335 lr=0.010000 Epoch[031] Batch [2249]/[3760] Speed: 68.087344 samples/sec accuracy=63.034028 loss=1.501373 lr=0.010000 Epoch[031] Batch [2299]/[3760] Speed: 67.703622 samples/sec accuracy=63.010870 loss=1.502648 lr=0.010000 Epoch[031] Batch [2349]/[3760] Speed: 68.093135 samples/sec accuracy=63.025931 loss=1.503037 lr=0.010000 Epoch[031] Batch [2399]/[3760] Speed: 68.045727 samples/sec accuracy=63.014323 loss=1.503456 lr=0.010000 Epoch[031] Batch [2449]/[3760] Speed: 68.212546 samples/sec accuracy=63.016582 loss=1.503486 lr=0.010000 Epoch[031] Batch [2499]/[3760] Speed: 68.073744 samples/sec accuracy=63.019375 loss=1.503793 lr=0.010000 Epoch[031] Batch [2549]/[3760] Speed: 68.091546 samples/sec accuracy=62.989583 loss=1.504841 lr=0.010000 Epoch[031] Batch [2599]/[3760] Speed: 67.443378 samples/sec accuracy=62.966947 loss=1.505739 lr=0.010000 Epoch[031] Batch [2649]/[3760] Speed: 68.358185 samples/sec accuracy=62.938679 loss=1.507552 lr=0.010000 Epoch[031] Batch [2699]/[3760] Speed: 67.215974 samples/sec accuracy=62.938079 loss=1.508095 lr=0.010000 Epoch[031] Batch [2749]/[3760] Speed: 67.904810 samples/sec accuracy=62.929545 loss=1.508187 lr=0.010000 Epoch[031] Batch [2799]/[3760] Speed: 68.160467 samples/sec accuracy=62.908482 loss=1.508856 lr=0.010000 Epoch[031] Batch [2849]/[3760] Speed: 67.634919 samples/sec accuracy=62.881579 loss=1.509797 lr=0.010000 Epoch[031] Batch [2899]/[3760] Speed: 67.910773 samples/sec accuracy=62.897091 loss=1.509417 lr=0.010000 Epoch[031] Batch [2949]/[3760] Speed: 68.088884 samples/sec accuracy=62.884534 loss=1.509665 lr=0.010000 Epoch[031] Batch [2999]/[3760] Speed: 67.322046 samples/sec accuracy=62.869271 loss=1.510451 lr=0.010000 Epoch[031] Batch [3049]/[3760] Speed: 67.684978 samples/sec accuracy=62.858607 loss=1.510583 lr=0.010000 Epoch[031] Batch [3099]/[3760] Speed: 67.679870 samples/sec accuracy=62.876008 loss=1.510212 lr=0.010000 Epoch[031] Batch [3149]/[3760] Speed: 67.477866 samples/sec accuracy=62.891865 loss=1.509887 lr=0.010000 Epoch[031] Batch [3199]/[3760] Speed: 68.045487 samples/sec accuracy=62.910156 loss=1.508640 lr=0.010000 Epoch[031] Batch [3249]/[3760] Speed: 68.418093 samples/sec accuracy=62.915385 loss=1.508687 lr=0.010000 Epoch[031] Batch [3299]/[3760] Speed: 68.144543 samples/sec accuracy=62.919508 loss=1.509096 lr=0.010000 Epoch[031] Batch [3349]/[3760] Speed: 67.790326 samples/sec accuracy=62.926306 loss=1.509164 lr=0.010000 Epoch[031] Batch [3399]/[3760] Speed: 68.150677 samples/sec accuracy=62.911765 loss=1.509078 lr=0.010000 Epoch[031] Batch [3449]/[3760] Speed: 67.601275 samples/sec accuracy=62.923007 loss=1.509180 lr=0.010000 Epoch[031] Batch [3499]/[3760] Speed: 68.316629 samples/sec accuracy=62.918304 loss=1.510297 lr=0.010000 Epoch[031] Batch [3549]/[3760] Speed: 68.097514 samples/sec accuracy=62.915933 loss=1.510469 lr=0.010000 Epoch[031] Batch [3599]/[3760] Speed: 67.530961 samples/sec accuracy=62.900608 loss=1.510563 lr=0.010000 Epoch[031] Batch [3649]/[3760] Speed: 68.312688 samples/sec accuracy=62.890411 loss=1.511421 lr=0.010000 Epoch[031] Batch [3699]/[3760] Speed: 67.742987 samples/sec accuracy=62.877111 loss=1.512099 lr=0.010000 Epoch[031] Batch [3749]/[3760] Speed: 74.504640 samples/sec accuracy=62.876667 loss=1.511950 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.343750 acc-top5=82.187500 Batch [0099]/[0303]: acc-top1=60.125000 acc-top5=81.875000 Batch [0149]/[0303]: acc-top1=60.041667 acc-top5=82.187500 Batch [0199]/[0303]: acc-top1=60.117188 acc-top5=82.578125 Batch [0249]/[0303]: acc-top1=60.087500 acc-top5=82.568750 Batch [0299]/[0303]: acc-top1=60.026042 acc-top5=82.708333 [Epoch 031] training: accuracy=62.878989 loss=1.512046 [Epoch 031] speed: 67 samples/sec time cost: 3851.885962 [Epoch 031] validation: acc-top1=60.029909 acc-top5=82.735149 loss=1.859123 Epoch[032] Batch [0049]/[3759] Speed: 44.999654 samples/sec accuracy=63.625000 loss=1.440447 lr=0.010000 Epoch[032] Batch [0099]/[3759] Speed: 67.162506 samples/sec accuracy=63.750000 loss=1.468266 lr=0.010000 Epoch[032] Batch [0149]/[3759] Speed: 67.877864 samples/sec accuracy=64.000000 loss=1.461670 lr=0.010000 Epoch[032] Batch [0199]/[3759] Speed: 68.073049 samples/sec accuracy=63.750000 loss=1.470613 lr=0.010000 Epoch[032] Batch [0249]/[3759] Speed: 67.677919 samples/sec accuracy=63.650000 loss=1.471228 lr=0.010000 Epoch[032] Batch [0299]/[3759] Speed: 68.298718 samples/sec accuracy=63.463542 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accuracy=63.285000 loss=1.490174 lr=0.010000 Epoch[032] Batch [1299]/[3759] Speed: 67.923348 samples/sec accuracy=63.268029 loss=1.491105 lr=0.010000 Epoch[032] Batch [1349]/[3759] Speed: 68.043254 samples/sec accuracy=63.273148 loss=1.491221 lr=0.010000 Epoch[032] Batch [1399]/[3759] Speed: 68.013465 samples/sec accuracy=63.262277 loss=1.491317 lr=0.010000 Epoch[032] Batch [1449]/[3759] Speed: 67.598377 samples/sec accuracy=63.295259 loss=1.490208 lr=0.010000 Epoch[032] Batch [1499]/[3759] Speed: 67.782774 samples/sec accuracy=63.248958 loss=1.493025 lr=0.010000 Epoch[032] Batch [1549]/[3759] Speed: 67.839316 samples/sec accuracy=63.279234 loss=1.492044 lr=0.010000 Epoch[032] Batch [1599]/[3759] Speed: 67.410059 samples/sec accuracy=63.262695 loss=1.492716 lr=0.010000 Epoch[032] Batch [1649]/[3759] Speed: 67.950041 samples/sec accuracy=63.278409 loss=1.492886 lr=0.010000 Epoch[032] Batch [1699]/[3759] Speed: 68.004334 samples/sec accuracy=63.284007 loss=1.493081 lr=0.010000 Epoch[032] 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accuracy=63.129972 loss=1.499142 lr=0.010000 Epoch[032] Batch [2249]/[3759] Speed: 67.442949 samples/sec accuracy=63.108333 loss=1.499611 lr=0.010000 Epoch[032] Batch [2299]/[3759] Speed: 68.143449 samples/sec accuracy=63.108016 loss=1.499554 lr=0.010000 Epoch[032] Batch [2349]/[3759] Speed: 68.323933 samples/sec accuracy=63.087766 loss=1.500443 lr=0.010000 Epoch[032] Batch [2399]/[3759] Speed: 67.711397 samples/sec accuracy=63.093750 loss=1.500271 lr=0.010000 Epoch[032] Batch [2449]/[3759] Speed: 67.958967 samples/sec accuracy=63.052296 loss=1.501192 lr=0.010000 Epoch[032] Batch [2499]/[3759] Speed: 67.252804 samples/sec accuracy=63.058750 loss=1.500948 lr=0.010000 Epoch[032] Batch [2549]/[3759] Speed: 67.917227 samples/sec accuracy=63.042279 loss=1.502139 lr=0.010000 Epoch[032] Batch [2599]/[3759] Speed: 67.536834 samples/sec accuracy=63.025240 loss=1.502877 lr=0.010000 Epoch[032] Batch [2649]/[3759] Speed: 67.686325 samples/sec accuracy=63.011203 loss=1.502997 lr=0.010000 Epoch[032] 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accuracy=62.967758 loss=1.506771 lr=0.010000 Epoch[032] Batch [3199]/[3759] Speed: 67.545825 samples/sec accuracy=62.968750 loss=1.506657 lr=0.010000 Epoch[032] Batch [3249]/[3759] Speed: 68.309903 samples/sec accuracy=62.949038 loss=1.507536 lr=0.010000 Epoch[032] Batch [3299]/[3759] Speed: 67.882391 samples/sec accuracy=62.950758 loss=1.507248 lr=0.010000 Epoch[032] Batch [3349]/[3759] Speed: 68.220103 samples/sec accuracy=62.948228 loss=1.507761 lr=0.010000 Epoch[032] Batch [3399]/[3759] Speed: 67.674468 samples/sec accuracy=62.967831 loss=1.507481 lr=0.010000 Epoch[032] Batch [3449]/[3759] Speed: 68.132277 samples/sec accuracy=62.977355 loss=1.507140 lr=0.010000 Epoch[032] Batch [3499]/[3759] Speed: 67.977267 samples/sec accuracy=62.977232 loss=1.506969 lr=0.010000 Epoch[032] Batch [3549]/[3759] Speed: 67.866118 samples/sec accuracy=62.986796 loss=1.506698 lr=0.010000 Epoch[032] Batch [3599]/[3759] Speed: 68.108062 samples/sec accuracy=62.988715 loss=1.507108 lr=0.010000 Epoch[032] Batch [3649]/[3759] Speed: 68.106953 samples/sec accuracy=62.986729 loss=1.506968 lr=0.010000 Epoch[032] Batch [3699]/[3759] Speed: 67.942738 samples/sec accuracy=62.961993 loss=1.507772 lr=0.010000 Epoch[032] Batch [3749]/[3759] Speed: 75.275054 samples/sec accuracy=62.953333 loss=1.508417 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.406250 acc-top5=81.562500 Batch [0099]/[0303]: acc-top1=59.062500 acc-top5=81.281250 Batch [0149]/[0303]: acc-top1=59.437500 acc-top5=81.614583 Batch [0199]/[0303]: acc-top1=59.875000 acc-top5=82.117188 Batch [0249]/[0303]: acc-top1=59.593750 acc-top5=82.125000 Batch [0299]/[0303]: acc-top1=59.619792 acc-top5=82.307292 [Epoch 032] training: accuracy=62.960561 loss=1.507987 [Epoch 032] speed: 67 samples/sec time cost: 3849.900461 [Epoch 032] validation: acc-top1=59.622525 acc-top5=82.317450 loss=1.900609 Epoch[033] Batch [0049]/[3760] Speed: 45.129754 samples/sec accuracy=63.281250 loss=1.445113 lr=0.010000 Epoch[033] Batch [0099]/[3760] Speed: 66.664804 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68.264059 samples/sec accuracy=63.711310 loss=1.474423 lr=0.010000 Epoch[033] Batch [1099]/[3760] Speed: 67.443614 samples/sec accuracy=63.714489 loss=1.477134 lr=0.010000 Epoch[033] Batch [1149]/[3760] Speed: 68.244873 samples/sec accuracy=63.698370 loss=1.476738 lr=0.010000 Epoch[033] Batch [1199]/[3760] Speed: 67.505469 samples/sec accuracy=63.709635 loss=1.477485 lr=0.010000 Epoch[033] Batch [1249]/[3760] Speed: 68.381332 samples/sec accuracy=63.711250 loss=1.476942 lr=0.010000 Epoch[033] Batch [1299]/[3760] Speed: 67.908244 samples/sec accuracy=63.677885 loss=1.478044 lr=0.010000 Epoch[033] Batch [1349]/[3760] Speed: 67.939396 samples/sec accuracy=63.649306 loss=1.480443 lr=0.010000 Epoch[033] Batch [1399]/[3760] Speed: 67.817346 samples/sec accuracy=63.630580 loss=1.480990 lr=0.010000 Epoch[033] Batch [1449]/[3760] Speed: 67.764133 samples/sec accuracy=63.616379 loss=1.481864 lr=0.010000 Epoch[033] Batch [1499]/[3760] Speed: 67.522196 samples/sec accuracy=63.646875 loss=1.480953 lr=0.010000 Epoch[033] Batch [1549]/[3760] Speed: 68.124508 samples/sec accuracy=63.627016 loss=1.482796 lr=0.010000 Epoch[033] Batch [1599]/[3760] Speed: 68.137901 samples/sec accuracy=63.594727 loss=1.483074 lr=0.010000 Epoch[033] Batch [1649]/[3760] Speed: 68.029280 samples/sec accuracy=63.549242 loss=1.484893 lr=0.010000 Epoch[033] Batch [1699]/[3760] Speed: 67.939716 samples/sec accuracy=63.536765 loss=1.485127 lr=0.010000 Epoch[033] Batch [1749]/[3760] Speed: 68.300972 samples/sec accuracy=63.532143 loss=1.485264 lr=0.010000 Epoch[033] Batch [1799]/[3760] Speed: 68.244905 samples/sec accuracy=63.532986 loss=1.484414 lr=0.010000 Epoch[033] Batch [1849]/[3760] Speed: 68.184890 samples/sec accuracy=63.526182 loss=1.484721 lr=0.010000 Epoch[033] Batch [1899]/[3760] Speed: 67.807310 samples/sec accuracy=63.498355 loss=1.486296 lr=0.010000 Epoch[033] Batch [1949]/[3760] Speed: 68.248390 samples/sec accuracy=63.510417 loss=1.486432 lr=0.010000 Epoch[033] Batch [1999]/[3760] Speed: 68.188730 samples/sec accuracy=63.489844 loss=1.487351 lr=0.010000 Epoch[033] Batch [2049]/[3760] Speed: 67.888281 samples/sec accuracy=63.422256 loss=1.490070 lr=0.010000 Epoch[033] Batch [2099]/[3760] Speed: 68.195581 samples/sec accuracy=63.395833 loss=1.490928 lr=0.010000 Epoch[033] Batch [2149]/[3760] Speed: 67.899385 samples/sec accuracy=63.390988 loss=1.490817 lr=0.010000 Epoch[033] Batch [2199]/[3760] Speed: 68.172965 samples/sec accuracy=63.370739 loss=1.490993 lr=0.010000 Epoch[033] Batch [2249]/[3760] Speed: 68.245774 samples/sec accuracy=63.339583 loss=1.491836 lr=0.010000 Epoch[033] Batch [2299]/[3760] Speed: 67.930639 samples/sec accuracy=63.360734 loss=1.491027 lr=0.010000 Epoch[033] Batch [2349]/[3760] Speed: 68.176027 samples/sec accuracy=63.388963 loss=1.490241 lr=0.010000 Epoch[033] Batch [2399]/[3760] Speed: 68.063044 samples/sec accuracy=63.368490 loss=1.491232 lr=0.010000 Epoch[033] Batch [2449]/[3760] Speed: 67.612973 samples/sec accuracy=63.325893 loss=1.493187 lr=0.010000 Epoch[033] Batch [2499]/[3760] Speed: 68.087894 samples/sec accuracy=63.304375 loss=1.493964 lr=0.010000 Epoch[033] Batch [2549]/[3760] Speed: 68.515590 samples/sec accuracy=63.303309 loss=1.494561 lr=0.010000 Epoch[033] Batch [2599]/[3760] Speed: 67.806372 samples/sec accuracy=63.314904 loss=1.494402 lr=0.010000 Epoch[033] Batch [2649]/[3760] Speed: 67.843304 samples/sec accuracy=63.313679 loss=1.494456 lr=0.010000 Epoch[033] Batch [2699]/[3760] Speed: 67.852483 samples/sec accuracy=63.289931 loss=1.495077 lr=0.010000 Epoch[033] Batch [2749]/[3760] Speed: 67.465756 samples/sec accuracy=63.293182 loss=1.494928 lr=0.010000 Epoch[033] Batch [2799]/[3760] Speed: 68.567277 samples/sec accuracy=63.281250 loss=1.495678 lr=0.010000 Epoch[033] Batch [2849]/[3760] Speed: 68.049187 samples/sec accuracy=63.276316 loss=1.496478 lr=0.010000 Epoch[033] Batch [2899]/[3760] Speed: 68.212790 samples/sec accuracy=63.257004 loss=1.497265 lr=0.010000 Epoch[033] Batch [2949]/[3760] Speed: 68.014166 samples/sec accuracy=63.226695 loss=1.498397 lr=0.010000 Epoch[033] Batch [2999]/[3760] Speed: 67.379524 samples/sec accuracy=63.226042 loss=1.498695 lr=0.010000 Epoch[033] Batch [3049]/[3760] Speed: 67.616761 samples/sec accuracy=63.228996 loss=1.499006 lr=0.010000 Epoch[033] Batch [3099]/[3760] Speed: 68.046457 samples/sec accuracy=63.225806 loss=1.498982 lr=0.010000 Epoch[033] Batch [3149]/[3760] Speed: 67.705718 samples/sec accuracy=63.235119 loss=1.498062 lr=0.010000 Epoch[033] Batch [3199]/[3760] Speed: 67.850874 samples/sec accuracy=63.224121 loss=1.498357 lr=0.010000 Epoch[033] Batch [3249]/[3760] Speed: 67.806746 samples/sec accuracy=63.187981 loss=1.500039 lr=0.010000 Epoch[033] Batch [3299]/[3760] Speed: 67.896528 samples/sec accuracy=63.167614 loss=1.500650 lr=0.010000 Epoch[033] Batch [3349]/[3760] Speed: 68.177700 samples/sec accuracy=63.149720 loss=1.501109 lr=0.010000 Epoch[033] Batch [3399]/[3760] Speed: 67.250763 samples/sec accuracy=63.134191 loss=1.501899 lr=0.010000 Epoch[033] Batch [3449]/[3760] Speed: 68.088093 samples/sec accuracy=63.121377 loss=1.502535 lr=0.010000 Epoch[033] Batch [3499]/[3760] Speed: 68.009625 samples/sec accuracy=63.107589 loss=1.503484 lr=0.010000 Epoch[033] Batch [3549]/[3760] Speed: 68.101787 samples/sec accuracy=63.092870 loss=1.504163 lr=0.010000 Epoch[033] Batch [3599]/[3760] Speed: 68.046184 samples/sec accuracy=63.083767 loss=1.504225 lr=0.010000 Epoch[033] Batch [3649]/[3760] Speed: 68.223109 samples/sec accuracy=63.076199 loss=1.504691 lr=0.010000 Epoch[033] Batch [3699]/[3760] Speed: 68.246547 samples/sec accuracy=63.077280 loss=1.504586 lr=0.010000 Epoch[033] Batch [3749]/[3760] Speed: 73.824630 samples/sec accuracy=63.091250 loss=1.504627 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.156250 acc-top5=82.406250 Batch [0099]/[0303]: acc-top1=59.796875 acc-top5=82.046875 Batch [0149]/[0303]: acc-top1=59.979167 acc-top5=82.479167 Batch [0199]/[0303]: acc-top1=59.992188 acc-top5=82.828125 Batch [0249]/[0303]: acc-top1=60.043750 acc-top5=82.700000 Batch [0299]/[0303]: acc-top1=60.255208 acc-top5=82.921875 [Epoch 033] training: accuracy=63.083029 loss=1.504717 [Epoch 033] speed: 67 samples/sec time cost: 3849.325147 [Epoch 033] validation: acc-top1=60.282591 acc-top5=82.967203 loss=1.829661 Epoch[034] Batch [0049]/[3759] Speed: 45.679443 samples/sec accuracy=65.125000 loss=1.425027 lr=0.010000 Epoch[034] Batch [0099]/[3759] Speed: 66.725587 samples/sec accuracy=64.546875 loss=1.446336 lr=0.010000 Epoch[034] Batch [0149]/[3759] Speed: 68.029986 samples/sec accuracy=64.312500 loss=1.452026 lr=0.010000 Epoch[034] Batch [0199]/[3759] Speed: 67.358682 samples/sec accuracy=64.437500 loss=1.446158 lr=0.010000 Epoch[034] Batch [0249]/[3759] Speed: 67.779040 samples/sec accuracy=64.462500 loss=1.450456 lr=0.010000 Epoch[034] Batch [0299]/[3759] Speed: 68.149801 samples/sec accuracy=64.406250 loss=1.455726 lr=0.010000 Epoch[034] Batch [0349]/[3759] Speed: 67.578963 samples/sec accuracy=64.522321 loss=1.454886 lr=0.010000 Epoch[034] Batch [0399]/[3759] Speed: 68.308497 samples/sec accuracy=64.503906 loss=1.453246 lr=0.010000 Epoch[034] Batch [0449]/[3759] Speed: 67.958519 samples/sec accuracy=64.541667 loss=1.452352 lr=0.010000 Epoch[034] Batch [0499]/[3759] Speed: 67.616641 samples/sec accuracy=64.521875 loss=1.455331 lr=0.010000 Epoch[034] Batch [0549]/[3759] Speed: 68.384930 samples/sec accuracy=64.463068 loss=1.460248 lr=0.010000 Epoch[034] Batch [0599]/[3759] Speed: 67.966016 samples/sec accuracy=64.364583 loss=1.464405 lr=0.010000 Epoch[034] Batch [0649]/[3759] Speed: 67.956854 samples/sec accuracy=64.314904 loss=1.466100 lr=0.010000 Epoch[034] Batch [0699]/[3759] Speed: 67.928314 samples/sec accuracy=64.370536 loss=1.459154 lr=0.010000 Epoch[034] Batch [0749]/[3759] Speed: 67.684212 samples/sec accuracy=64.441667 loss=1.456513 lr=0.010000 Epoch[034] Batch [0799]/[3759] Speed: 68.229460 samples/sec accuracy=64.447266 loss=1.457561 lr=0.010000 Epoch[034] 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accuracy=63.915865 loss=1.469467 lr=0.010000 Epoch[034] Batch [1349]/[3759] Speed: 68.237337 samples/sec accuracy=63.910880 loss=1.468846 lr=0.010000 Epoch[034] Batch [1399]/[3759] Speed: 68.532155 samples/sec accuracy=63.904018 loss=1.469278 lr=0.010000 Epoch[034] Batch [1449]/[3759] Speed: 68.286100 samples/sec accuracy=63.829741 loss=1.471560 lr=0.010000 Epoch[034] Batch [1499]/[3759] Speed: 67.393212 samples/sec accuracy=63.807292 loss=1.472133 lr=0.010000 Epoch[034] Batch [1549]/[3759] Speed: 68.393727 samples/sec accuracy=63.801411 loss=1.471778 lr=0.010000 Epoch[034] Batch [1599]/[3759] Speed: 68.491971 samples/sec accuracy=63.721680 loss=1.475161 lr=0.010000 Epoch[034] Batch [1649]/[3759] Speed: 67.763097 samples/sec accuracy=63.688447 loss=1.476167 lr=0.010000 Epoch[034] Batch [1699]/[3759] Speed: 68.169013 samples/sec accuracy=63.667279 loss=1.477998 lr=0.010000 Epoch[034] Batch [1749]/[3759] Speed: 67.707345 samples/sec accuracy=63.668750 loss=1.478315 lr=0.010000 Epoch[034] Batch [1799]/[3759] Speed: 68.182370 samples/sec accuracy=63.669271 loss=1.477925 lr=0.010000 Epoch[034] Batch [1849]/[3759] Speed: 67.845373 samples/sec accuracy=63.646115 loss=1.479008 lr=0.010000 Epoch[034] Batch [1899]/[3759] Speed: 67.905742 samples/sec accuracy=63.604441 loss=1.479713 lr=0.010000 Epoch[034] Batch [1949]/[3759] Speed: 68.157042 samples/sec accuracy=63.562500 loss=1.481363 lr=0.010000 Epoch[034] Batch [1999]/[3759] Speed: 68.603658 samples/sec accuracy=63.561719 loss=1.481384 lr=0.010000 Epoch[034] Batch [2049]/[3759] Speed: 67.380790 samples/sec accuracy=63.564787 loss=1.481540 lr=0.010000 Epoch[034] Batch [2099]/[3759] Speed: 67.751595 samples/sec accuracy=63.503720 loss=1.483656 lr=0.010000 Epoch[034] Batch [2149]/[3759] Speed: 68.309452 samples/sec accuracy=63.504360 loss=1.484221 lr=0.010000 Epoch[034] Batch [2199]/[3759] Speed: 67.727473 samples/sec accuracy=63.516335 loss=1.484200 lr=0.010000 Epoch[034] Batch [2249]/[3759] Speed: 68.081691 samples/sec accuracy=63.488194 loss=1.484541 lr=0.010000 Epoch[034] Batch [2299]/[3759] Speed: 67.628674 samples/sec accuracy=63.471467 loss=1.484280 lr=0.010000 Epoch[034] Batch [2349]/[3759] Speed: 68.021203 samples/sec accuracy=63.454122 loss=1.484637 lr=0.010000 Epoch[034] Batch [2399]/[3759] Speed: 67.799885 samples/sec accuracy=63.442057 loss=1.485572 lr=0.010000 Epoch[034] Batch [2449]/[3759] Speed: 67.938508 samples/sec accuracy=63.452806 loss=1.485895 lr=0.010000 Epoch[034] Batch [2499]/[3759] Speed: 68.259001 samples/sec accuracy=63.435625 loss=1.486842 lr=0.010000 Epoch[034] Batch [2549]/[3759] Speed: 67.182696 samples/sec accuracy=63.419118 loss=1.487251 lr=0.010000 Epoch[034] Batch [2599]/[3759] Speed: 68.137560 samples/sec accuracy=63.407452 loss=1.487734 lr=0.010000 Epoch[034] Batch [2649]/[3759] Speed: 68.388486 samples/sec accuracy=63.372642 loss=1.488760 lr=0.010000 Epoch[034] Batch [2699]/[3759] Speed: 67.713955 samples/sec accuracy=63.396412 loss=1.488450 lr=0.010000 Epoch[034] Batch [2749]/[3759] Speed: 67.624185 samples/sec accuracy=63.393182 loss=1.488478 lr=0.010000 Epoch[034] Batch [2799]/[3759] Speed: 67.749593 samples/sec accuracy=63.368304 loss=1.489273 lr=0.010000 Epoch[034] Batch [2849]/[3759] Speed: 68.031146 samples/sec accuracy=63.384320 loss=1.488658 lr=0.010000 Epoch[034] Batch [2899]/[3759] Speed: 68.036602 samples/sec accuracy=63.402478 loss=1.488630 lr=0.010000 Epoch[034] Batch [2949]/[3759] Speed: 67.670951 samples/sec accuracy=63.384534 loss=1.488999 lr=0.010000 Epoch[034] Batch [2999]/[3759] Speed: 67.587687 samples/sec accuracy=63.353125 loss=1.490058 lr=0.010000 Epoch[034] Batch [3049]/[3759] Speed: 67.435160 samples/sec accuracy=63.345799 loss=1.490279 lr=0.010000 Epoch[034] Batch [3099]/[3759] Speed: 67.728991 samples/sec accuracy=63.362399 loss=1.489461 lr=0.010000 Epoch[034] Batch [3149]/[3759] Speed: 68.441286 samples/sec accuracy=63.348214 loss=1.489421 lr=0.010000 Epoch[034] Batch [3199]/[3759] Speed: 67.976702 samples/sec accuracy=63.336426 loss=1.489901 lr=0.010000 Epoch[034] Batch [3249]/[3759] Speed: 67.157237 samples/sec accuracy=63.325962 loss=1.490336 lr=0.010000 Epoch[034] Batch [3299]/[3759] Speed: 67.387422 samples/sec accuracy=63.319602 loss=1.490639 lr=0.010000 Epoch[034] Batch [3349]/[3759] Speed: 67.728209 samples/sec accuracy=63.296642 loss=1.491661 lr=0.010000 Epoch[034] Batch [3399]/[3759] Speed: 68.283482 samples/sec accuracy=63.277574 loss=1.493030 lr=0.010000 Epoch[034] Batch [3449]/[3759] Speed: 67.779474 samples/sec accuracy=63.273098 loss=1.493639 lr=0.010000 Epoch[034] Batch [3499]/[3759] Speed: 67.733486 samples/sec accuracy=63.258036 loss=1.494484 lr=0.010000 Epoch[034] Batch [3549]/[3759] Speed: 67.918506 samples/sec accuracy=63.248239 loss=1.495403 lr=0.010000 Epoch[034] Batch [3599]/[3759] Speed: 68.721189 samples/sec accuracy=63.238281 loss=1.495950 lr=0.010000 Epoch[034] Batch [3649]/[3759] Speed: 67.452092 samples/sec accuracy=63.227740 loss=1.496536 lr=0.010000 Epoch[034] Batch [3699]/[3759] Speed: 67.409299 samples/sec accuracy=63.239865 loss=1.496131 lr=0.010000 Epoch[034] Batch [3749]/[3759] Speed: 75.049742 samples/sec accuracy=63.226250 loss=1.496949 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.375000 acc-top5=81.937500 Batch [0099]/[0303]: acc-top1=59.875000 acc-top5=81.937500 Batch [0149]/[0303]: acc-top1=59.802083 acc-top5=82.062500 Batch [0199]/[0303]: acc-top1=59.960938 acc-top5=82.500000 Batch [0249]/[0303]: acc-top1=59.937500 acc-top5=82.362500 Batch [0299]/[0303]: acc-top1=60.062500 acc-top5=82.630208 [Epoch 034] training: accuracy=63.220770 loss=1.497152 [Epoch 034] speed: 67 samples/sec time cost: 3849.864048 [Epoch 034] validation: acc-top1=60.096947 acc-top5=82.642327 loss=1.852523 Epoch[035] Batch [0049]/[3760] Speed: 45.257710 samples/sec accuracy=62.468750 loss=1.504501 lr=0.010000 Epoch[035] Batch [0099]/[3760] Speed: 67.052852 samples/sec accuracy=63.640625 loss=1.482758 lr=0.010000 Epoch[035] Batch [0149]/[3760] Speed: 67.832363 samples/sec accuracy=63.729167 loss=1.471855 lr=0.010000 Epoch[035] Batch [0199]/[3760] Speed: 67.273378 samples/sec accuracy=63.976562 loss=1.467028 lr=0.010000 Epoch[035] Batch [0249]/[3760] Speed: 67.578194 samples/sec accuracy=64.143750 loss=1.459496 lr=0.010000 Epoch[035] Batch [0299]/[3760] Speed: 68.276293 samples/sec accuracy=64.203125 loss=1.456901 lr=0.010000 Epoch[035] Batch [0349]/[3760] Speed: 67.793199 samples/sec accuracy=64.254464 loss=1.457684 lr=0.010000 Epoch[035] Batch [0399]/[3760] Speed: 67.985002 samples/sec accuracy=64.187500 loss=1.457436 lr=0.010000 Epoch[035] Batch [0449]/[3760] Speed: 67.396414 samples/sec accuracy=64.166667 loss=1.456951 lr=0.010000 Epoch[035] Batch [0499]/[3760] Speed: 68.083315 samples/sec accuracy=64.293750 loss=1.454320 lr=0.010000 Epoch[035] Batch [0549]/[3760] Speed: 68.139506 samples/sec accuracy=64.406250 loss=1.452565 lr=0.010000 Epoch[035] Batch [0599]/[3760] Speed: 68.032599 samples/sec accuracy=64.343750 loss=1.451830 lr=0.010000 Epoch[035] Batch [0649]/[3760] Speed: 67.446007 samples/sec accuracy=64.180288 loss=1.460405 lr=0.010000 Epoch[035] Batch [0699]/[3760] Speed: 67.814869 samples/sec accuracy=64.212054 loss=1.461255 lr=0.010000 Epoch[035] Batch [0749]/[3760] Speed: 68.371240 samples/sec accuracy=64.195833 loss=1.461518 lr=0.010000 Epoch[035] Batch [0799]/[3760] Speed: 67.824900 samples/sec accuracy=64.175781 loss=1.459805 lr=0.010000 Epoch[035] Batch [0849]/[3760] Speed: 68.482137 samples/sec accuracy=64.084559 loss=1.460721 lr=0.010000 Epoch[035] Batch [0899]/[3760] Speed: 67.962654 samples/sec accuracy=64.078125 loss=1.463208 lr=0.010000 Epoch[035] Batch [0949]/[3760] Speed: 67.988702 samples/sec accuracy=64.090461 loss=1.463546 lr=0.010000 Epoch[035] Batch [0999]/[3760] Speed: 67.757451 samples/sec accuracy=64.025000 loss=1.465988 lr=0.010000 Epoch[035] Batch [1049]/[3760] Speed: 68.093565 samples/sec accuracy=63.998512 loss=1.467170 lr=0.010000 Epoch[035] Batch [1099]/[3760] Speed: 67.744754 samples/sec accuracy=64.046875 loss=1.465242 lr=0.010000 Epoch[035] Batch [1149]/[3760] Speed: 68.293756 samples/sec accuracy=64.046196 loss=1.466647 lr=0.010000 Epoch[035] Batch [1199]/[3760] Speed: 67.519310 samples/sec accuracy=64.005208 loss=1.468625 lr=0.010000 Epoch[035] Batch [1249]/[3760] Speed: 68.165636 samples/sec accuracy=63.976250 loss=1.470630 lr=0.010000 Epoch[035] Batch [1299]/[3760] Speed: 68.010001 samples/sec accuracy=63.944712 loss=1.470839 lr=0.010000 Epoch[035] Batch [1349]/[3760] Speed: 68.320613 samples/sec accuracy=63.956019 loss=1.471365 lr=0.010000 Epoch[035] Batch [1399]/[3760] Speed: 68.185672 samples/sec accuracy=63.953125 loss=1.470705 lr=0.010000 Epoch[035] Batch [1449]/[3760] Speed: 67.991654 samples/sec accuracy=63.949353 loss=1.470750 lr=0.010000 Epoch[035] Batch [1499]/[3760] Speed: 67.835151 samples/sec accuracy=63.939583 loss=1.472070 lr=0.010000 Epoch[035] Batch [1549]/[3760] Speed: 67.933056 samples/sec accuracy=63.910282 loss=1.472574 lr=0.010000 Epoch[035] Batch [1599]/[3760] Speed: 67.596404 samples/sec accuracy=63.898438 loss=1.472892 lr=0.010000 Epoch[035] Batch [1649]/[3760] Speed: 68.477335 samples/sec accuracy=63.898674 loss=1.473276 lr=0.010000 Epoch[035] Batch [1699]/[3760] Speed: 67.449899 samples/sec accuracy=63.844669 loss=1.475876 lr=0.010000 Epoch[035] Batch [1749]/[3760] Speed: 67.877426 samples/sec accuracy=63.869643 loss=1.474921 lr=0.010000 Epoch[035] Batch [1799]/[3760] Speed: 68.386104 samples/sec accuracy=63.864583 loss=1.476065 lr=0.010000 Epoch[035] Batch [1849]/[3760] Speed: 67.901390 samples/sec accuracy=63.855574 loss=1.476543 lr=0.010000 Epoch[035] Batch [1899]/[3760] Speed: 68.139119 samples/sec accuracy=63.885691 loss=1.475736 lr=0.010000 Epoch[035] Batch [1949]/[3760] Speed: 68.086975 samples/sec accuracy=63.897436 loss=1.475469 lr=0.010000 Epoch[035] Batch [1999]/[3760] Speed: 67.798804 samples/sec accuracy=63.892187 loss=1.474546 lr=0.010000 Epoch[035] Batch [2049]/[3760] Speed: 67.858448 samples/sec accuracy=63.863567 loss=1.475696 lr=0.010000 Epoch[035] Batch [2099]/[3760] Speed: 68.133266 samples/sec accuracy=63.825893 loss=1.476960 lr=0.010000 Epoch[035] Batch [2149]/[3760] Speed: 67.914883 samples/sec accuracy=63.782703 loss=1.478614 lr=0.010000 Epoch[035] Batch [2199]/[3760] Speed: 68.257034 samples/sec accuracy=63.795455 loss=1.478049 lr=0.010000 Epoch[035] Batch [2249]/[3760] Speed: 67.805870 samples/sec accuracy=63.797917 loss=1.478152 lr=0.010000 Epoch[035] Batch [2299]/[3760] Speed: 68.031703 samples/sec accuracy=63.785326 loss=1.478479 lr=0.010000 Epoch[035] Batch [2349]/[3760] Speed: 67.913465 samples/sec accuracy=63.778590 loss=1.478400 lr=0.010000 Epoch[035] Batch [2399]/[3760] Speed: 68.411348 samples/sec accuracy=63.750000 loss=1.478637 lr=0.010000 Epoch[035] Batch [2449]/[3760] Speed: 68.145006 samples/sec accuracy=63.739158 loss=1.478959 lr=0.010000 Epoch[035] Batch [2499]/[3760] Speed: 67.526944 samples/sec accuracy=63.751250 loss=1.478991 lr=0.010000 Epoch[035] Batch [2549]/[3760] Speed: 68.073446 samples/sec accuracy=63.764093 loss=1.478732 lr=0.010000 Epoch[035] Batch [2599]/[3760] Speed: 67.726004 samples/sec accuracy=63.740385 loss=1.479734 lr=0.010000 Epoch[035] Batch [2649]/[3760] Speed: 68.322754 samples/sec accuracy=63.701651 loss=1.481371 lr=0.010000 Epoch[035] Batch [2699]/[3760] Speed: 68.535399 samples/sec accuracy=63.672454 loss=1.482707 lr=0.010000 Epoch[035] Batch [2749]/[3760] Speed: 68.458918 samples/sec accuracy=63.645455 loss=1.483455 lr=0.010000 Epoch[035] Batch [2799]/[3760] Speed: 67.386541 samples/sec accuracy=63.626674 loss=1.483551 lr=0.010000 Epoch[035] Batch [2849]/[3760] Speed: 68.645772 samples/sec accuracy=63.620614 loss=1.484105 lr=0.010000 Epoch[035] Batch [2899]/[3760] Speed: 67.915525 samples/sec accuracy=63.630927 loss=1.484533 lr=0.010000 Epoch[035] Batch [2949]/[3760] Speed: 68.436022 samples/sec accuracy=63.611229 loss=1.485198 lr=0.010000 Epoch[035] Batch [2999]/[3760] Speed: 67.750095 samples/sec accuracy=63.598438 loss=1.486263 lr=0.010000 Epoch[035] Batch [3049]/[3760] Speed: 68.321680 samples/sec accuracy=63.600410 loss=1.486568 lr=0.010000 Epoch[035] Batch [3099]/[3760] Speed: 68.063444 samples/sec accuracy=63.573589 loss=1.487962 lr=0.010000 Epoch[035] Batch [3149]/[3760] Speed: 68.158755 samples/sec accuracy=63.564484 loss=1.488912 lr=0.010000 Epoch[035] Batch [3199]/[3760] Speed: 67.767837 samples/sec accuracy=63.543945 loss=1.489281 lr=0.010000 Epoch[035] Batch [3249]/[3760] Speed: 68.026268 samples/sec accuracy=63.529808 loss=1.490083 lr=0.010000 Epoch[035] Batch [3299]/[3760] Speed: 67.706852 samples/sec accuracy=63.512311 loss=1.490734 lr=0.010000 Epoch[035] Batch [3349]/[3760] Speed: 68.181220 samples/sec accuracy=63.514925 loss=1.491267 lr=0.010000 Epoch[035] Batch [3399]/[3760] Speed: 68.204609 samples/sec accuracy=63.528493 loss=1.490390 lr=0.010000 Epoch[035] Batch [3449]/[3760] Speed: 67.773993 samples/sec accuracy=63.515399 loss=1.490446 lr=0.010000 Epoch[035] Batch [3499]/[3760] Speed: 68.264605 samples/sec accuracy=63.495536 loss=1.491275 lr=0.010000 Epoch[035] Batch [3549]/[3760] Speed: 68.145953 samples/sec accuracy=63.480194 loss=1.492188 lr=0.010000 Epoch[035] Batch [3599]/[3760] Speed: 67.835788 samples/sec accuracy=63.465278 loss=1.492527 lr=0.010000 Epoch[035] Batch [3649]/[3760] Speed: 68.191387 samples/sec accuracy=63.452911 loss=1.493101 lr=0.010000 Epoch[035] Batch [3699]/[3760] Speed: 67.623265 samples/sec accuracy=63.448480 loss=1.492844 lr=0.010000 Epoch[035] Batch [3749]/[3760] Speed: 74.099940 samples/sec accuracy=63.452917 loss=1.492787 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.531250 acc-top5=81.312500 Batch [0099]/[0303]: acc-top1=59.656250 acc-top5=81.687500 Batch [0149]/[0303]: acc-top1=59.739583 acc-top5=81.864583 Batch [0199]/[0303]: acc-top1=60.015625 acc-top5=82.351562 Batch [0249]/[0303]: acc-top1=60.106250 acc-top5=82.431250 Batch [0299]/[0303]: acc-top1=60.078125 acc-top5=82.536458 [Epoch 035] training: accuracy=63.451213 loss=1.492646 [Epoch 035] speed: 67 samples/sec time cost: 3847.594541 [Epoch 035] validation: acc-top1=60.117574 acc-top5=82.544348 loss=1.839600 Epoch[036] Batch [0049]/[3760] Speed: 45.271098 samples/sec accuracy=63.500000 loss=1.457198 lr=0.010000 Epoch[036] Batch [0099]/[3760] Speed: 67.361802 samples/sec accuracy=64.015625 loss=1.453791 lr=0.010000 Epoch[036] Batch [0149]/[3760] Speed: 68.339160 samples/sec accuracy=64.052083 loss=1.460185 lr=0.010000 Epoch[036] Batch [0199]/[3760] Speed: 67.511766 samples/sec accuracy=64.203125 loss=1.466593 lr=0.010000 Epoch[036] Batch [0249]/[3760] Speed: 67.462588 samples/sec accuracy=64.168750 loss=1.472812 lr=0.010000 Epoch[036] Batch [0299]/[3760] Speed: 68.000202 samples/sec accuracy=64.255208 loss=1.467935 lr=0.010000 Epoch[036] Batch [0349]/[3760] Speed: 67.882692 samples/sec accuracy=64.339286 loss=1.460821 lr=0.010000 Epoch[036] Batch [0399]/[3760] Speed: 67.439508 samples/sec accuracy=64.433594 loss=1.459818 lr=0.010000 Epoch[036] Batch [0449]/[3760] Speed: 68.632838 samples/sec accuracy=64.541667 loss=1.458468 lr=0.010000 Epoch[036] Batch [0499]/[3760] Speed: 67.981322 samples/sec accuracy=64.421875 loss=1.459641 lr=0.010000 Epoch[036] Batch [0549]/[3760] Speed: 68.127986 samples/sec accuracy=64.488636 loss=1.456471 lr=0.010000 Epoch[036] Batch [0599]/[3760] Speed: 67.669619 samples/sec accuracy=64.528646 loss=1.452033 lr=0.010000 Epoch[036] Batch [0649]/[3760] Speed: 68.214863 samples/sec accuracy=64.461538 loss=1.452272 lr=0.010000 Epoch[036] Batch [0699]/[3760] Speed: 67.719458 samples/sec accuracy=64.464286 loss=1.452343 lr=0.010000 Epoch[036] Batch [0749]/[3760] Speed: 68.100806 samples/sec accuracy=64.410417 loss=1.453634 lr=0.010000 Epoch[036] Batch [0799]/[3760] Speed: 68.435413 samples/sec accuracy=64.339844 loss=1.454661 lr=0.010000 Epoch[036] Batch [0849]/[3760] Speed: 67.885229 samples/sec accuracy=64.321691 loss=1.457026 lr=0.010000 Epoch[036] Batch [0899]/[3760] Speed: 68.206268 samples/sec accuracy=64.335069 loss=1.457312 lr=0.010000 Epoch[036] Batch [0949]/[3760] Speed: 68.324676 samples/sec accuracy=64.297697 loss=1.459510 lr=0.010000 Epoch[036] Batch [0999]/[3760] Speed: 67.794149 samples/sec accuracy=64.234375 loss=1.460623 lr=0.010000 Epoch[036] Batch [1049]/[3760] Speed: 67.929405 samples/sec accuracy=64.177083 loss=1.462373 lr=0.010000 Epoch[036] Batch [1099]/[3760] Speed: 68.608649 samples/sec accuracy=64.180398 loss=1.462506 lr=0.010000 Epoch[036] Batch [1149]/[3760] Speed: 68.118285 samples/sec accuracy=64.176630 loss=1.464212 lr=0.010000 Epoch[036] Batch [1199]/[3760] Speed: 67.847882 samples/sec accuracy=64.153646 loss=1.464678 lr=0.010000 Epoch[036] Batch [1249]/[3760] Speed: 68.072426 samples/sec accuracy=64.161250 loss=1.466376 lr=0.010000 Epoch[036] Batch [1299]/[3760] Speed: 68.213221 samples/sec accuracy=64.129808 loss=1.467421 lr=0.010000 Epoch[036] Batch [1349]/[3760] Speed: 68.727139 samples/sec accuracy=64.162037 loss=1.465723 lr=0.010000 Epoch[036] Batch [1399]/[3760] Speed: 68.100535 samples/sec accuracy=64.079241 loss=1.468025 lr=0.010000 Epoch[036] Batch [1449]/[3760] Speed: 67.913016 samples/sec accuracy=64.084052 loss=1.467718 lr=0.010000 Epoch[036] Batch [1499]/[3760] Speed: 67.710945 samples/sec accuracy=64.093750 loss=1.466808 lr=0.010000 Epoch[036] Batch [1549]/[3760] Speed: 67.750616 samples/sec accuracy=64.079637 loss=1.468383 lr=0.010000 Epoch[036] Batch [1599]/[3760] Speed: 68.961711 samples/sec accuracy=64.046875 loss=1.468828 lr=0.010000 Epoch[036] Batch [1649]/[3760] Speed: 67.916815 samples/sec accuracy=64.037879 loss=1.468801 lr=0.010000 Epoch[036] Batch [1699]/[3760] Speed: 67.604153 samples/sec accuracy=64.000000 loss=1.470016 lr=0.010000 Epoch[036] Batch [1749]/[3760] Speed: 68.021767 samples/sec accuracy=63.958036 loss=1.471612 lr=0.010000 Epoch[036] Batch [1799]/[3760] Speed: 67.864031 samples/sec accuracy=63.935764 loss=1.471840 lr=0.010000 Epoch[036] Batch [1849]/[3760] Speed: 68.210686 samples/sec accuracy=63.899493 loss=1.472507 lr=0.010000 Epoch[036] Batch [1899]/[3760] Speed: 68.170020 samples/sec accuracy=63.900493 loss=1.472689 lr=0.010000 Epoch[036] Batch [1949]/[3760] Speed: 67.793374 samples/sec accuracy=63.895032 loss=1.473233 lr=0.010000 Epoch[036] Batch [1999]/[3760] Speed: 67.841426 samples/sec accuracy=63.895313 loss=1.473542 lr=0.010000 Epoch[036] Batch [2049]/[3760] Speed: 67.548179 samples/sec accuracy=63.888720 loss=1.473847 lr=0.010000 Epoch[036] Batch [2099]/[3760] Speed: 68.139077 samples/sec accuracy=63.840030 loss=1.475478 lr=0.010000 Epoch[036] Batch [2149]/[3760] Speed: 68.610900 samples/sec accuracy=63.783430 loss=1.477827 lr=0.010000 Epoch[036] Batch [2199]/[3760] Speed: 66.750794 samples/sec accuracy=63.772727 loss=1.477652 lr=0.010000 Epoch[036] Batch [2249]/[3760] Speed: 68.148172 samples/sec accuracy=63.754167 loss=1.478899 lr=0.010000 Epoch[036] Batch [2299]/[3760] Speed: 68.310530 samples/sec accuracy=63.707880 loss=1.480767 lr=0.010000 Epoch[036] Batch [2349]/[3760] Speed: 67.625000 samples/sec accuracy=63.696809 loss=1.481727 lr=0.010000 Epoch[036] Batch [2399]/[3760] Speed: 68.423807 samples/sec accuracy=63.703125 loss=1.480980 lr=0.010000 Epoch[036] Batch [2449]/[3760] Speed: 67.860933 samples/sec accuracy=63.688776 loss=1.480919 lr=0.010000 Epoch[036] Batch [2499]/[3760] Speed: 67.900385 samples/sec accuracy=63.651250 loss=1.482157 lr=0.010000 Epoch[036] Batch [2549]/[3760] Speed: 67.673029 samples/sec accuracy=63.621936 loss=1.483000 lr=0.010000 Epoch[036] Batch [2599]/[3760] Speed: 67.602957 samples/sec accuracy=63.616587 loss=1.483103 lr=0.010000 Epoch[036] Batch [2649]/[3760] Speed: 68.219534 samples/sec accuracy=63.633255 loss=1.483680 lr=0.010000 Epoch[036] Batch [2699]/[3760] Speed: 67.759283 samples/sec accuracy=63.634838 loss=1.483738 lr=0.010000 Epoch[036] Batch [2749]/[3760] Speed: 68.076860 samples/sec accuracy=63.630682 loss=1.483630 lr=0.010000 Epoch[036] Batch [2799]/[3760] Speed: 67.836069 samples/sec accuracy=63.611607 loss=1.484262 lr=0.010000 Epoch[036] Batch [2849]/[3760] Speed: 67.370557 samples/sec accuracy=63.605263 loss=1.484943 lr=0.010000 Epoch[036] Batch [2899]/[3760] Speed: 68.450253 samples/sec accuracy=63.586746 loss=1.486006 lr=0.010000 Epoch[036] Batch [2949]/[3760] Speed: 68.172288 samples/sec accuracy=63.563559 loss=1.486635 lr=0.010000 Epoch[036] Batch [2999]/[3760] Speed: 67.512885 samples/sec accuracy=63.522917 loss=1.488114 lr=0.010000 Epoch[036] Batch [3049]/[3760] Speed: 68.468048 samples/sec accuracy=63.522029 loss=1.488221 lr=0.010000 Epoch[036] Batch [3099]/[3760] Speed: 68.210784 samples/sec accuracy=63.522177 loss=1.488155 lr=0.010000 Epoch[036] Batch [3149]/[3760] Speed: 67.924174 samples/sec accuracy=63.528770 loss=1.488282 lr=0.010000 Epoch[036] Batch [3199]/[3760] Speed: 68.125005 samples/sec accuracy=63.523926 loss=1.487523 lr=0.010000 Epoch[036] Batch [3249]/[3760] Speed: 67.173929 samples/sec accuracy=63.503846 loss=1.488546 lr=0.010000 Epoch[036] Batch [3299]/[3760] Speed: 67.314459 samples/sec accuracy=63.490057 loss=1.488782 lr=0.010000 Epoch[036] Batch [3349]/[3760] Speed: 67.976648 samples/sec accuracy=63.478545 loss=1.489288 lr=0.010000 Epoch[036] Batch [3399]/[3760] Speed: 67.611257 samples/sec accuracy=63.460478 loss=1.489926 lr=0.010000 Epoch[036] Batch [3449]/[3760] Speed: 67.226454 samples/sec accuracy=63.436141 loss=1.490488 lr=0.010000 Epoch[036] Batch [3499]/[3760] Speed: 68.158146 samples/sec accuracy=63.454464 loss=1.489907 lr=0.010000 Epoch[036] Batch [3549]/[3760] Speed: 68.046276 samples/sec accuracy=63.473151 loss=1.489181 lr=0.010000 Epoch[036] Batch [3599]/[3760] Speed: 67.636147 samples/sec accuracy=63.462674 loss=1.489475 lr=0.010000 Epoch[036] Batch [3649]/[3760] Speed: 67.746260 samples/sec accuracy=63.460616 loss=1.489775 lr=0.010000 Epoch[036] Batch [3699]/[3760] Speed: 68.310159 samples/sec accuracy=63.437922 loss=1.490845 lr=0.010000 Epoch[036] Batch [3749]/[3760] Speed: 74.445329 samples/sec accuracy=63.419167 loss=1.492013 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.937500 acc-top5=81.062500 Batch [0099]/[0303]: acc-top1=59.031250 acc-top5=81.328125 Batch [0149]/[0303]: acc-top1=58.989583 acc-top5=81.770833 Batch [0199]/[0303]: acc-top1=59.421875 acc-top5=82.023438 Batch [0249]/[0303]: acc-top1=59.487500 acc-top5=81.993750 Batch [0299]/[0303]: acc-top1=59.520833 acc-top5=82.140625 [Epoch 036] training: accuracy=63.417553 loss=1.492040 [Epoch 036] speed: 67 samples/sec time cost: 3849.268867 [Epoch 036] validation: acc-top1=59.560644 acc-top5=82.183375 loss=1.907331 Epoch[037] Batch [0049]/[3759] Speed: 45.442972 samples/sec accuracy=65.250000 loss=1.411563 lr=0.010000 Epoch[037] Batch [0099]/[3759] Speed: 67.160973 samples/sec accuracy=64.593750 loss=1.437779 lr=0.010000 Epoch[037] Batch [0149]/[3759] Speed: 68.161055 samples/sec accuracy=64.364583 loss=1.452387 lr=0.010000 Epoch[037] Batch [0199]/[3759] Speed: 68.163656 samples/sec accuracy=64.406250 loss=1.457861 lr=0.010000 Epoch[037] Batch [0249]/[3759] Speed: 67.595592 samples/sec accuracy=64.218750 loss=1.465751 lr=0.010000 Epoch[037] Batch [0299]/[3759] Speed: 68.184760 samples/sec accuracy=64.088542 loss=1.468307 lr=0.010000 Epoch[037] Batch [0349]/[3759] Speed: 68.465229 samples/sec accuracy=64.035714 loss=1.468772 lr=0.010000 Epoch[037] Batch [0399]/[3759] Speed: 67.851559 samples/sec accuracy=64.015625 loss=1.472014 lr=0.010000 Epoch[037] Batch [0449]/[3759] Speed: 68.416036 samples/sec accuracy=64.090278 loss=1.467226 lr=0.010000 Epoch[037] Batch [0499]/[3759] Speed: 67.999547 samples/sec accuracy=64.143750 loss=1.466039 lr=0.010000 Epoch[037] Batch [0549]/[3759] Speed: 68.487938 samples/sec accuracy=64.125000 loss=1.464471 lr=0.010000 Epoch[037] Batch [0599]/[3759] Speed: 68.072557 samples/sec accuracy=63.979167 loss=1.468011 lr=0.010000 Epoch[037] Batch [0649]/[3759] Speed: 66.812892 samples/sec accuracy=64.026442 loss=1.467483 lr=0.010000 Epoch[037] Batch [0699]/[3759] Speed: 68.652130 samples/sec accuracy=64.029018 loss=1.465298 lr=0.010000 Epoch[037] Batch [0749]/[3759] Speed: 68.142779 samples/sec accuracy=63.950000 loss=1.470209 lr=0.010000 Epoch[037] Batch [0799]/[3759] Speed: 68.446710 samples/sec accuracy=63.937500 loss=1.471373 lr=0.010000 Epoch[037] Batch [0849]/[3759] Speed: 67.857747 samples/sec accuracy=63.860294 loss=1.474368 lr=0.010000 Epoch[037] Batch [0899]/[3759] Speed: 68.302699 samples/sec accuracy=63.916667 loss=1.472895 lr=0.010000 Epoch[037] Batch [0949]/[3759] Speed: 67.898941 samples/sec accuracy=63.942434 loss=1.471677 lr=0.010000 Epoch[037] Batch [0999]/[3759] Speed: 68.161907 samples/sec accuracy=63.904688 loss=1.471948 lr=0.010000 Epoch[037] Batch [1049]/[3759] Speed: 68.216225 samples/sec accuracy=63.882440 loss=1.471652 lr=0.010000 Epoch[037] Batch [1099]/[3759] Speed: 67.262695 samples/sec accuracy=63.916193 loss=1.469252 lr=0.010000 Epoch[037] Batch [1149]/[3759] Speed: 68.320680 samples/sec accuracy=63.826087 loss=1.470264 lr=0.010000 Epoch[037] Batch [1199]/[3759] Speed: 67.601079 samples/sec accuracy=63.845052 loss=1.468852 lr=0.010000 Epoch[037] Batch [1249]/[3759] Speed: 68.734623 samples/sec accuracy=63.798750 loss=1.470030 lr=0.010000 Epoch[037] Batch [1299]/[3759] Speed: 67.842030 samples/sec accuracy=63.800481 loss=1.471287 lr=0.010000 Epoch[037] Batch [1349]/[3759] Speed: 68.156476 samples/sec accuracy=63.774306 loss=1.471840 lr=0.010000 Epoch[037] Batch [1399]/[3759] Speed: 68.188733 samples/sec accuracy=63.770089 loss=1.472416 lr=0.010000 Epoch[037] Batch [1449]/[3759] Speed: 68.171982 samples/sec accuracy=63.796336 loss=1.473041 lr=0.010000 Epoch[037] Batch [1499]/[3759] Speed: 67.999004 samples/sec accuracy=63.791667 loss=1.472191 lr=0.010000 Epoch[037] Batch [1549]/[3759] Speed: 68.123250 samples/sec accuracy=63.744960 loss=1.472781 lr=0.010000 Epoch[037] Batch [1599]/[3759] Speed: 67.759849 samples/sec accuracy=63.721680 loss=1.473714 lr=0.010000 Epoch[037] Batch [1649]/[3759] Speed: 67.506429 samples/sec accuracy=63.675189 loss=1.475124 lr=0.010000 Epoch[037] Batch [1699]/[3759] Speed: 67.942834 samples/sec accuracy=63.711397 loss=1.474621 lr=0.010000 Epoch[037] Batch [1749]/[3759] Speed: 68.384679 samples/sec accuracy=63.724107 loss=1.473749 lr=0.010000 Epoch[037] Batch [1799]/[3759] Speed: 67.386153 samples/sec accuracy=63.693576 loss=1.475323 lr=0.010000 Epoch[037] Batch [1849]/[3759] Speed: 68.303467 samples/sec accuracy=63.711993 loss=1.475015 lr=0.010000 Epoch[037] Batch [1899]/[3759] Speed: 67.864209 samples/sec accuracy=63.703947 loss=1.475377 lr=0.010000 Epoch[037] Batch [1949]/[3759] Speed: 68.142357 samples/sec accuracy=63.711538 loss=1.476099 lr=0.010000 Epoch[037] Batch [1999]/[3759] Speed: 68.063922 samples/sec accuracy=63.677344 loss=1.478546 lr=0.010000 Epoch[037] Batch [2049]/[3759] Speed: 68.262555 samples/sec accuracy=63.673018 loss=1.478206 lr=0.010000 Epoch[037] Batch [2099]/[3759] Speed: 68.274654 samples/sec accuracy=63.674107 loss=1.479502 lr=0.010000 Epoch[037] Batch [2149]/[3759] Speed: 67.444301 samples/sec accuracy=63.692587 loss=1.479030 lr=0.010000 Epoch[037] Batch [2199]/[3759] Speed: 68.467952 samples/sec accuracy=63.681108 loss=1.479899 lr=0.010000 Epoch[037] Batch [2249]/[3759] Speed: 68.007434 samples/sec accuracy=63.678472 loss=1.480398 lr=0.010000 Epoch[037] Batch [2299]/[3759] Speed: 67.495991 samples/sec accuracy=63.684103 loss=1.479874 lr=0.010000 Epoch[037] Batch [2349]/[3759] Speed: 67.909748 samples/sec accuracy=63.686170 loss=1.479533 lr=0.010000 Epoch[037] Batch [2399]/[3759] Speed: 67.557876 samples/sec accuracy=63.662760 loss=1.480379 lr=0.010000 Epoch[037] Batch [2449]/[3759] Speed: 68.145377 samples/sec accuracy=63.667730 loss=1.480242 lr=0.010000 Epoch[037] Batch [2499]/[3759] Speed: 67.820583 samples/sec accuracy=63.685000 loss=1.479745 lr=0.010000 Epoch[037] Batch [2549]/[3759] Speed: 68.245773 samples/sec accuracy=63.690564 loss=1.479530 lr=0.010000 Epoch[037] Batch [2599]/[3759] Speed: 67.788484 samples/sec accuracy=63.689904 loss=1.479841 lr=0.010000 Epoch[037] Batch [2649]/[3759] Speed: 67.975919 samples/sec accuracy=63.685142 loss=1.480866 lr=0.010000 Epoch[037] Batch [2699]/[3759] Speed: 68.331002 samples/sec accuracy=63.682292 loss=1.480681 lr=0.010000 Epoch[037] Batch [2749]/[3759] Speed: 68.806657 samples/sec accuracy=63.666477 loss=1.481604 lr=0.010000 Epoch[037] Batch [2799]/[3759] Speed: 67.696694 samples/sec accuracy=63.667411 loss=1.482029 lr=0.010000 Epoch[037] Batch [2849]/[3759] Speed: 68.380420 samples/sec accuracy=63.641996 loss=1.483058 lr=0.010000 Epoch[037] Batch [2899]/[3759] Speed: 67.780981 samples/sec accuracy=63.637931 loss=1.483531 lr=0.010000 Epoch[037] Batch [2949]/[3759] Speed: 68.192611 samples/sec accuracy=63.643008 loss=1.483392 lr=0.010000 Epoch[037] Batch [2999]/[3759] Speed: 68.030255 samples/sec accuracy=63.618750 loss=1.484881 lr=0.010000 Epoch[037] Batch [3049]/[3759] Speed: 67.969489 samples/sec accuracy=63.596311 loss=1.485957 lr=0.010000 Epoch[037] Batch [3099]/[3759] Speed: 68.114710 samples/sec accuracy=63.603327 loss=1.485678 lr=0.010000 Epoch[037] Batch [3149]/[3759] Speed: 68.408387 samples/sec accuracy=63.575893 loss=1.486424 lr=0.010000 Epoch[037] Batch [3199]/[3759] Speed: 67.982081 samples/sec accuracy=63.567383 loss=1.487090 lr=0.010000 Epoch[037] Batch [3249]/[3759] Speed: 68.215674 samples/sec accuracy=63.559615 loss=1.487440 lr=0.010000 Epoch[037] Batch [3299]/[3759] Speed: 68.469571 samples/sec accuracy=63.553977 loss=1.487388 lr=0.010000 Epoch[037] Batch [3349]/[3759] Speed: 67.773994 samples/sec accuracy=63.531250 loss=1.488060 lr=0.010000 Epoch[037] Batch [3399]/[3759] Speed: 67.633009 samples/sec accuracy=63.500460 loss=1.489052 lr=0.010000 Epoch[037] Batch [3449]/[3759] Speed: 68.359509 samples/sec accuracy=63.472373 loss=1.489831 lr=0.010000 Epoch[037] Batch [3499]/[3759] Speed: 67.611135 samples/sec accuracy=63.465625 loss=1.490146 lr=0.010000 Epoch[037] Batch [3549]/[3759] Speed: 67.924606 samples/sec accuracy=63.456426 loss=1.491101 lr=0.010000 Epoch[037] Batch [3599]/[3759] Speed: 68.178402 samples/sec accuracy=63.450087 loss=1.491216 lr=0.010000 Epoch[037] Batch [3649]/[3759] Speed: 68.874438 samples/sec accuracy=63.434503 loss=1.492244 lr=0.010000 Epoch[037] Batch [3699]/[3759] Speed: 67.976341 samples/sec accuracy=63.438345 loss=1.492274 lr=0.010000 Epoch[037] Batch [3749]/[3759] Speed: 74.989153 samples/sec accuracy=63.429167 loss=1.492657 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.906250 acc-top5=81.562500 Batch [0099]/[0303]: acc-top1=59.609375 acc-top5=81.359375 Batch [0149]/[0303]: acc-top1=59.666667 acc-top5=81.781250 Batch [0199]/[0303]: acc-top1=59.921875 acc-top5=82.171875 Batch [0249]/[0303]: acc-top1=59.818750 acc-top5=82.187500 Batch [0299]/[0303]: acc-top1=59.822917 acc-top5=82.484375 [Epoch 037] training: accuracy=63.431099 loss=1.492770 [Epoch 037] speed: 67 samples/sec time cost: 3843.126574 [Epoch 037] validation: acc-top1=59.849422 acc-top5=82.492781 loss=1.915967 Epoch[038] Batch [0049]/[3760] Speed: 45.521437 samples/sec accuracy=63.500000 loss=1.493214 lr=0.010000 Epoch[038] Batch [0099]/[3760] Speed: 67.341100 samples/sec accuracy=63.437500 loss=1.474394 lr=0.010000 Epoch[038] Batch [0149]/[3760] Speed: 68.003497 samples/sec accuracy=63.802083 loss=1.456882 lr=0.010000 Epoch[038] Batch [0199]/[3760] Speed: 67.033009 samples/sec accuracy=63.898438 loss=1.454988 lr=0.010000 Epoch[038] Batch [0249]/[3760] Speed: 68.057136 samples/sec accuracy=64.250000 loss=1.446811 lr=0.010000 Epoch[038] Batch [0299]/[3760] Speed: 68.137079 samples/sec accuracy=64.317708 loss=1.449317 lr=0.010000 Epoch[038] Batch [0349]/[3760] Speed: 67.994305 samples/sec accuracy=64.343750 loss=1.451250 lr=0.010000 Epoch[038] Batch [0399]/[3760] Speed: 68.538285 samples/sec accuracy=64.386719 loss=1.451447 lr=0.010000 Epoch[038] Batch [0449]/[3760] Speed: 67.989928 samples/sec accuracy=64.329861 loss=1.454703 lr=0.010000 Epoch[038] Batch [0499]/[3760] Speed: 67.923467 samples/sec accuracy=64.187500 loss=1.460871 lr=0.010000 Epoch[038] Batch [0549]/[3760] Speed: 67.603446 samples/sec accuracy=64.096591 loss=1.463157 lr=0.010000 Epoch[038] Batch [0599]/[3760] Speed: 67.728146 samples/sec accuracy=64.169271 loss=1.457722 lr=0.010000 Epoch[038] Batch [0649]/[3760] Speed: 67.908466 samples/sec accuracy=64.225962 loss=1.456216 lr=0.010000 Epoch[038] Batch [0699]/[3760] Speed: 67.717138 samples/sec accuracy=64.162946 loss=1.457013 lr=0.010000 Epoch[038] Batch [0749]/[3760] Speed: 68.130476 samples/sec accuracy=64.214583 loss=1.457080 lr=0.010000 Epoch[038] Batch [0799]/[3760] Speed: 68.019420 samples/sec accuracy=64.166016 loss=1.461796 lr=0.010000 Epoch[038] Batch [0849]/[3760] Speed: 68.448842 samples/sec accuracy=64.193015 loss=1.461635 lr=0.010000 Epoch[038] Batch [0899]/[3760] Speed: 67.471463 samples/sec accuracy=64.123264 loss=1.463178 lr=0.010000 Epoch[038] 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accuracy=64.071429 loss=1.462575 lr=0.010000 Epoch[038] Batch [1449]/[3760] Speed: 67.806454 samples/sec accuracy=64.053879 loss=1.462967 lr=0.010000 Epoch[038] Batch [1499]/[3760] Speed: 67.973067 samples/sec accuracy=64.082292 loss=1.462479 lr=0.010000 Epoch[038] Batch [1549]/[3760] Speed: 67.863641 samples/sec accuracy=64.079637 loss=1.462241 lr=0.010000 Epoch[038] Batch [1599]/[3760] Speed: 67.679244 samples/sec accuracy=64.082031 loss=1.462542 lr=0.010000 Epoch[038] Batch [1649]/[3760] Speed: 68.309955 samples/sec accuracy=64.112689 loss=1.460718 lr=0.010000 Epoch[038] Batch [1699]/[3760] Speed: 68.215164 samples/sec accuracy=64.125000 loss=1.461112 lr=0.010000 Epoch[038] Batch [1749]/[3760] Speed: 68.101283 samples/sec accuracy=64.107143 loss=1.461281 lr=0.010000 Epoch[038] Batch [1799]/[3760] Speed: 67.853549 samples/sec accuracy=64.079861 loss=1.462015 lr=0.010000 Epoch[038] Batch [1849]/[3760] Speed: 67.802519 samples/sec accuracy=64.058277 loss=1.463063 lr=0.010000 Epoch[038] Batch [1899]/[3760] Speed: 68.374132 samples/sec accuracy=64.027961 loss=1.464476 lr=0.010000 Epoch[038] Batch [1949]/[3760] Speed: 67.311283 samples/sec accuracy=63.993590 loss=1.465917 lr=0.010000 Epoch[038] Batch [1999]/[3760] Speed: 67.799961 samples/sec accuracy=63.932031 loss=1.467238 lr=0.010000 Epoch[038] Batch [2049]/[3760] Speed: 68.216688 samples/sec accuracy=63.932165 loss=1.466531 lr=0.010000 Epoch[038] Batch [2099]/[3760] Speed: 68.568922 samples/sec accuracy=63.939732 loss=1.466872 lr=0.010000 Epoch[038] Batch [2149]/[3760] Speed: 67.886302 samples/sec accuracy=63.925872 loss=1.467835 lr=0.010000 Epoch[038] Batch [2199]/[3760] Speed: 67.953842 samples/sec accuracy=63.898438 loss=1.469668 lr=0.010000 Epoch[038] Batch [2249]/[3760] Speed: 67.551082 samples/sec accuracy=63.909722 loss=1.470420 lr=0.010000 Epoch[038] Batch [2299]/[3760] Speed: 68.146210 samples/sec accuracy=63.890625 loss=1.471193 lr=0.010000 Epoch[038] Batch [2349]/[3760] Speed: 68.113698 samples/sec accuracy=63.853059 loss=1.471439 lr=0.010000 Epoch[038] Batch [2399]/[3760] Speed: 68.575197 samples/sec accuracy=63.805990 loss=1.472715 lr=0.010000 Epoch[038] Batch [2449]/[3760] Speed: 68.337986 samples/sec accuracy=63.829082 loss=1.472490 lr=0.010000 Epoch[038] Batch [2499]/[3760] Speed: 67.864105 samples/sec accuracy=63.807500 loss=1.472782 lr=0.010000 Epoch[038] Batch [2549]/[3760] Speed: 68.105654 samples/sec accuracy=63.795343 loss=1.473547 lr=0.010000 Epoch[038] Batch [2599]/[3760] Speed: 67.704095 samples/sec accuracy=63.799880 loss=1.473413 lr=0.010000 Epoch[038] Batch [2649]/[3760] Speed: 67.864233 samples/sec accuracy=63.762382 loss=1.474781 lr=0.010000 Epoch[038] Batch [2699]/[3760] Speed: 67.776067 samples/sec accuracy=63.763310 loss=1.475347 lr=0.010000 Epoch[038] Batch [2749]/[3760] Speed: 67.309226 samples/sec accuracy=63.749432 loss=1.476539 lr=0.010000 Epoch[038] Batch [2799]/[3760] Speed: 68.251046 samples/sec accuracy=63.742188 loss=1.476955 lr=0.010000 Epoch[038] Batch [2849]/[3760] Speed: 67.989491 samples/sec accuracy=63.716557 loss=1.477473 lr=0.010000 Epoch[038] Batch [2899]/[3760] Speed: 68.579108 samples/sec accuracy=63.692888 loss=1.478758 lr=0.010000 Epoch[038] Batch [2949]/[3760] Speed: 67.712129 samples/sec accuracy=63.700742 loss=1.478645 lr=0.010000 Epoch[038] Batch [2999]/[3760] Speed: 68.106005 samples/sec accuracy=63.688021 loss=1.479108 lr=0.010000 Epoch[038] Batch [3049]/[3760] Speed: 68.060938 samples/sec accuracy=63.680840 loss=1.479201 lr=0.010000 Epoch[038] Batch [3099]/[3760] Speed: 68.220290 samples/sec accuracy=63.690524 loss=1.478629 lr=0.010000 Epoch[038] Batch [3149]/[3760] Speed: 67.706004 samples/sec accuracy=63.703373 loss=1.478591 lr=0.010000 Epoch[038] Batch [3199]/[3760] Speed: 67.959467 samples/sec accuracy=63.693848 loss=1.479077 lr=0.010000 Epoch[038] Batch [3249]/[3760] Speed: 67.480191 samples/sec accuracy=63.693750 loss=1.479249 lr=0.010000 Epoch[038] Batch [3299]/[3760] Speed: 68.179050 samples/sec accuracy=63.692708 loss=1.479802 lr=0.010000 Epoch[038] Batch [3349]/[3760] Speed: 67.915820 samples/sec accuracy=63.716884 loss=1.479154 lr=0.010000 Epoch[038] Batch [3399]/[3760] Speed: 67.184271 samples/sec accuracy=63.719210 loss=1.478931 lr=0.010000 Epoch[038] Batch [3449]/[3760] Speed: 68.602266 samples/sec accuracy=63.698822 loss=1.479614 lr=0.010000 Epoch[038] Batch [3499]/[3760] Speed: 68.110706 samples/sec accuracy=63.680804 loss=1.479998 lr=0.010000 Epoch[038] Batch [3549]/[3760] Speed: 68.163036 samples/sec accuracy=63.669014 loss=1.480635 lr=0.010000 Epoch[038] Batch [3599]/[3760] Speed: 67.818718 samples/sec accuracy=63.645399 loss=1.481232 lr=0.010000 Epoch[038] Batch [3649]/[3760] Speed: 68.753460 samples/sec accuracy=63.650685 loss=1.481449 lr=0.010000 Epoch[038] Batch [3699]/[3760] Speed: 67.943461 samples/sec accuracy=63.645693 loss=1.481788 lr=0.010000 Epoch[038] Batch [3749]/[3760] Speed: 74.834193 samples/sec accuracy=63.622917 loss=1.482567 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.031250 acc-top5=82.781250 Batch [0099]/[0303]: acc-top1=59.343750 acc-top5=82.343750 Batch [0149]/[0303]: acc-top1=59.666667 acc-top5=82.625000 Batch [0199]/[0303]: acc-top1=59.812500 acc-top5=82.789062 Batch [0249]/[0303]: acc-top1=59.937500 acc-top5=82.850000 Batch [0299]/[0303]: acc-top1=60.187500 acc-top5=82.885417 [Epoch 038] training: accuracy=63.619515 loss=1.482929 [Epoch 038] speed: 67 samples/sec time cost: 3847.318799 [Epoch 038] validation: acc-top1=60.163985 acc-top5=82.895008 loss=1.862987 Epoch[039] Batch [0049]/[3760] Speed: 44.965972 samples/sec accuracy=63.562500 loss=1.450389 lr=0.010000 Epoch[039] Batch [0099]/[3760] Speed: 67.383672 samples/sec accuracy=63.546875 loss=1.446281 lr=0.010000 Epoch[039] Batch [0149]/[3760] Speed: 68.254261 samples/sec accuracy=64.000000 loss=1.433552 lr=0.010000 Epoch[039] Batch [0199]/[3760] Speed: 67.653235 samples/sec accuracy=63.960938 loss=1.435712 lr=0.010000 Epoch[039] Batch [0249]/[3760] Speed: 68.097593 samples/sec accuracy=64.075000 loss=1.433406 lr=0.010000 Epoch[039] Batch [0299]/[3760] Speed: 68.307981 samples/sec accuracy=64.213542 loss=1.429285 lr=0.010000 Epoch[039] Batch [0349]/[3760] Speed: 67.568030 samples/sec accuracy=64.232143 loss=1.435307 lr=0.010000 Epoch[039] Batch [0399]/[3760] Speed: 67.740582 samples/sec accuracy=64.261719 loss=1.436247 lr=0.010000 Epoch[039] Batch [0449]/[3760] Speed: 67.831513 samples/sec accuracy=64.152778 loss=1.442567 lr=0.010000 Epoch[039] Batch [0499]/[3760] Speed: 68.096096 samples/sec accuracy=64.231250 loss=1.440004 lr=0.010000 Epoch[039] Batch [0549]/[3760] Speed: 68.251649 samples/sec accuracy=64.309659 loss=1.440595 lr=0.010000 Epoch[039] Batch [0599]/[3760] Speed: 68.279324 samples/sec accuracy=64.184896 loss=1.445555 lr=0.010000 Epoch[039] Batch [0649]/[3760] Speed: 67.841690 samples/sec accuracy=64.170673 loss=1.447389 lr=0.010000 Epoch[039] Batch [0699]/[3760] Speed: 68.536281 samples/sec accuracy=64.220982 loss=1.448022 lr=0.010000 Epoch[039] Batch [0749]/[3760] Speed: 67.714150 samples/sec accuracy=64.310417 loss=1.447310 lr=0.010000 Epoch[039] Batch [0799]/[3760] Speed: 68.285246 samples/sec accuracy=64.359375 loss=1.445611 lr=0.010000 Epoch[039] Batch [0849]/[3760] Speed: 68.137693 samples/sec accuracy=64.351103 loss=1.447104 lr=0.010000 Epoch[039] Batch [0899]/[3760] Speed: 67.896959 samples/sec accuracy=64.225694 loss=1.451058 lr=0.010000 Epoch[039] Batch [0949]/[3760] Speed: 68.103284 samples/sec accuracy=64.194079 loss=1.452597 lr=0.010000 Epoch[039] Batch [0999]/[3760] Speed: 67.633765 samples/sec accuracy=64.223438 loss=1.453254 lr=0.010000 Epoch[039] Batch [1049]/[3760] Speed: 67.896633 samples/sec accuracy=64.181548 loss=1.455810 lr=0.010000 Epoch[039] Batch [1099]/[3760] Speed: 67.887175 samples/sec accuracy=64.255682 loss=1.453299 lr=0.010000 Epoch[039] Batch [1149]/[3760] Speed: 67.862394 samples/sec accuracy=64.286685 loss=1.453409 lr=0.010000 Epoch[039] Batch [1199]/[3760] Speed: 68.297371 samples/sec accuracy=64.281250 loss=1.454100 lr=0.010000 Epoch[039] Batch [1249]/[3760] Speed: 67.808814 samples/sec accuracy=64.270000 loss=1.456037 lr=0.010000 Epoch[039] Batch [1299]/[3760] Speed: 68.518580 samples/sec accuracy=64.225962 loss=1.457534 lr=0.010000 Epoch[039] Batch [1349]/[3760] Speed: 67.717439 samples/sec accuracy=64.152778 loss=1.459233 lr=0.010000 Epoch[039] Batch [1399]/[3760] Speed: 68.127730 samples/sec accuracy=64.120536 loss=1.459877 lr=0.010000 Epoch[039] Batch [1449]/[3760] Speed: 68.251204 samples/sec accuracy=64.060345 loss=1.462088 lr=0.010000 Epoch[039] Batch [1499]/[3760] Speed: 67.475828 samples/sec accuracy=64.012500 loss=1.463965 lr=0.010000 Epoch[039] Batch [1549]/[3760] Speed: 67.898227 samples/sec accuracy=64.017137 loss=1.463577 lr=0.010000 Epoch[039] Batch [1599]/[3760] Speed: 67.844581 samples/sec accuracy=63.995117 loss=1.464580 lr=0.010000 Epoch[039] Batch [1649]/[3760] Speed: 67.743643 samples/sec accuracy=63.984848 loss=1.464917 lr=0.010000 Epoch[039] Batch [1699]/[3760] Speed: 67.784150 samples/sec accuracy=63.930147 loss=1.467252 lr=0.010000 Epoch[039] Batch [1749]/[3760] Speed: 68.192808 samples/sec accuracy=63.938393 loss=1.467533 lr=0.010000 Epoch[039] Batch [1799]/[3760] Speed: 67.859842 samples/sec accuracy=63.954861 loss=1.466453 lr=0.010000 Epoch[039] Batch [1849]/[3760] Speed: 68.121355 samples/sec accuracy=63.917230 loss=1.467915 lr=0.010000 Epoch[039] Batch [1899]/[3760] Speed: 67.933201 samples/sec accuracy=63.951480 loss=1.466952 lr=0.010000 Epoch[039] Batch [1949]/[3760] Speed: 67.860727 samples/sec accuracy=63.947917 loss=1.466802 lr=0.010000 Epoch[039] Batch [1999]/[3760] Speed: 67.923960 samples/sec accuracy=63.961719 loss=1.466604 lr=0.010000 Epoch[039] Batch [2049]/[3760] Speed: 67.756384 samples/sec accuracy=63.961128 loss=1.466670 lr=0.010000 Epoch[039] Batch [2099]/[3760] Speed: 67.983815 samples/sec accuracy=63.941964 loss=1.467144 lr=0.010000 Epoch[039] Batch [2149]/[3760] Speed: 67.868809 samples/sec accuracy=63.882267 loss=1.469256 lr=0.010000 Epoch[039] Batch [2199]/[3760] Speed: 67.820724 samples/sec accuracy=63.890625 loss=1.468602 lr=0.010000 Epoch[039] Batch [2249]/[3760] Speed: 68.079462 samples/sec accuracy=63.852083 loss=1.470115 lr=0.010000 Epoch[039] Batch [2299]/[3760] Speed: 67.448086 samples/sec accuracy=63.854620 loss=1.470264 lr=0.010000 Epoch[039] Batch [2349]/[3760] Speed: 68.107603 samples/sec accuracy=63.851064 loss=1.469813 lr=0.010000 Epoch[039] Batch [2399]/[3760] Speed: 68.353110 samples/sec accuracy=63.853516 loss=1.469971 lr=0.010000 Epoch[039] Batch [2449]/[3760] Speed: 67.826743 samples/sec accuracy=63.877551 loss=1.469780 lr=0.010000 Epoch[039] Batch [2499]/[3760] Speed: 68.153735 samples/sec accuracy=63.860625 loss=1.470501 lr=0.010000 Epoch[039] Batch [2549]/[3760] Speed: 67.812121 samples/sec accuracy=63.873162 loss=1.469964 lr=0.010000 Epoch[039] Batch [2599]/[3760] Speed: 67.856756 samples/sec accuracy=63.875000 loss=1.470279 lr=0.010000 Epoch[039] Batch [2649]/[3760] Speed: 67.746629 samples/sec accuracy=63.887972 loss=1.469789 lr=0.010000 Epoch[039] Batch [2699]/[3760] Speed: 68.543911 samples/sec accuracy=63.875579 loss=1.469759 lr=0.010000 Epoch[039] Batch [2749]/[3760] Speed: 68.176535 samples/sec accuracy=63.852273 loss=1.470318 lr=0.010000 Epoch[039] Batch [2799]/[3760] Speed: 68.435742 samples/sec accuracy=63.848214 loss=1.470533 lr=0.010000 Epoch[039] Batch [2849]/[3760] Speed: 67.969679 samples/sec accuracy=63.844298 loss=1.470841 lr=0.010000 Epoch[039] Batch [2899]/[3760] Speed: 67.640769 samples/sec accuracy=63.836207 loss=1.470914 lr=0.010000 Epoch[039] Batch [2949]/[3760] Speed: 67.552690 samples/sec accuracy=63.835805 loss=1.471240 lr=0.010000 Epoch[039] Batch [2999]/[3760] Speed: 68.563023 samples/sec accuracy=63.819792 loss=1.472272 lr=0.010000 Epoch[039] Batch [3049]/[3760] Speed: 68.010861 samples/sec accuracy=63.789959 loss=1.473261 lr=0.010000 Epoch[039] Batch [3099]/[3760] Speed: 67.875042 samples/sec accuracy=63.779234 loss=1.473828 lr=0.010000 Epoch[039] Batch [3149]/[3760] Speed: 68.022112 samples/sec accuracy=63.765873 loss=1.474225 lr=0.010000 Epoch[039] Batch [3199]/[3760] Speed: 68.160098 samples/sec accuracy=63.757812 loss=1.475207 lr=0.010000 Epoch[039] Batch [3249]/[3760] Speed: 67.660390 samples/sec accuracy=63.750481 loss=1.475898 lr=0.010000 Epoch[039] Batch [3299]/[3760] Speed: 68.302555 samples/sec accuracy=63.742424 loss=1.475636 lr=0.010000 Epoch[039] Batch [3349]/[3760] Speed: 67.719910 samples/sec accuracy=63.734142 loss=1.476119 lr=0.010000 Epoch[039] Batch [3399]/[3760] Speed: 68.945556 samples/sec accuracy=63.724724 loss=1.476340 lr=0.010000 Epoch[039] Batch [3449]/[3760] Speed: 67.579820 samples/sec accuracy=63.726902 loss=1.476217 lr=0.010000 Epoch[039] Batch [3499]/[3760] Speed: 68.423829 samples/sec accuracy=63.727232 loss=1.477114 lr=0.010000 Epoch[039] Batch [3549]/[3760] Speed: 68.434109 samples/sec accuracy=63.735475 loss=1.476949 lr=0.010000 Epoch[039] Batch [3599]/[3760] Speed: 68.624184 samples/sec accuracy=63.730035 loss=1.477178 lr=0.010000 Epoch[039] Batch [3649]/[3760] Speed: 67.986851 samples/sec accuracy=63.731592 loss=1.476950 lr=0.010000 Epoch[039] Batch [3699]/[3760] Speed: 67.745504 samples/sec accuracy=63.745777 loss=1.476928 lr=0.010000 Epoch[039] Batch [3749]/[3760] Speed: 74.972550 samples/sec accuracy=63.713333 loss=1.477875 lr=0.001000 Batch [0049]/[0303]: acc-top1=59.437500 acc-top5=82.781250 Batch [0099]/[0303]: acc-top1=59.875000 acc-top5=82.859375 Batch [0149]/[0303]: acc-top1=60.270833 acc-top5=82.989583 Batch [0199]/[0303]: acc-top1=60.343750 acc-top5=82.953125 Batch [0249]/[0303]: acc-top1=60.525000 acc-top5=82.800000 Batch [0299]/[0303]: acc-top1=60.635417 acc-top5=82.947917 [Epoch 039] training: accuracy=63.709691 loss=1.478110 [Epoch 039] speed: 67 samples/sec time cost: 3848.946330 [Epoch 039] validation: acc-top1=60.612624 acc-top5=82.972360 loss=1.843642 Epoch[040] Batch 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accuracy=67.640625 loss=1.319085 lr=0.001000 Epoch[040] Batch [0549]/[3759] Speed: 67.977688 samples/sec accuracy=67.829545 loss=1.309256 lr=0.001000 Epoch[040] Batch [0599]/[3759] Speed: 68.106778 samples/sec accuracy=68.018229 loss=1.301357 lr=0.001000 Epoch[040] Batch [0649]/[3759] Speed: 68.331925 samples/sec accuracy=68.163462 loss=1.295521 lr=0.001000 Epoch[040] Batch [0699]/[3759] Speed: 68.629922 samples/sec accuracy=68.330357 loss=1.290126 lr=0.001000 Epoch[040] Batch [0749]/[3759] Speed: 68.020337 samples/sec accuracy=68.383333 loss=1.284614 lr=0.001000 Epoch[040] Batch [0799]/[3759] Speed: 67.733566 samples/sec accuracy=68.519531 loss=1.277730 lr=0.001000 Epoch[040] Batch [0849]/[3759] Speed: 68.533070 samples/sec accuracy=68.586397 loss=1.273953 lr=0.001000 Epoch[040] Batch [0899]/[3759] Speed: 68.297150 samples/sec accuracy=68.579861 loss=1.273939 lr=0.001000 Epoch[040] Batch [0949]/[3759] Speed: 67.864568 samples/sec accuracy=68.641447 loss=1.270545 lr=0.001000 Epoch[040] 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accuracy=70.058302 loss=1.202356 lr=0.001000 Epoch[040] Batch [3399]/[3759] Speed: 68.111212 samples/sec accuracy=70.065717 loss=1.202036 lr=0.001000 Epoch[040] Batch [3449]/[3759] Speed: 68.462008 samples/sec accuracy=70.098732 loss=1.200827 lr=0.001000 Epoch[040] Batch [3499]/[3759] Speed: 67.858622 samples/sec accuracy=70.124554 loss=1.200017 lr=0.001000 Epoch[040] Batch [3549]/[3759] Speed: 68.183665 samples/sec accuracy=70.138644 loss=1.199300 lr=0.001000 Epoch[040] Batch [3599]/[3759] Speed: 68.193650 samples/sec accuracy=70.157552 loss=1.198516 lr=0.001000 Epoch[040] Batch [3649]/[3759] Speed: 68.195122 samples/sec accuracy=70.196062 loss=1.197285 lr=0.001000 Epoch[040] Batch [3699]/[3759] Speed: 68.205588 samples/sec accuracy=70.209882 loss=1.196579 lr=0.001000 Epoch[040] Batch [3749]/[3759] Speed: 74.576910 samples/sec accuracy=70.222083 loss=1.196026 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.125000 acc-top5=85.406250 Batch [0099]/[0303]: acc-top1=65.218750 acc-top5=85.296875 Batch [0149]/[0303]: acc-top1=65.312500 acc-top5=85.604167 Batch [0199]/[0303]: acc-top1=65.476562 acc-top5=85.812500 Batch [0249]/[0303]: acc-top1=65.487500 acc-top5=85.881250 Batch [0299]/[0303]: acc-top1=65.572917 acc-top5=86.062500 [Epoch 040] training: accuracy=70.218143 loss=1.196238 [Epoch 040] speed: 67 samples/sec time cost: 3837.488269 [Epoch 040] validation: acc-top1=65.573432 acc-top5=86.066419 loss=1.604703 Epoch[041] Batch [0049]/[3760] Speed: 45.918137 samples/sec accuracy=72.437500 loss=1.112871 lr=0.001000 Epoch[041] Batch [0099]/[3760] Speed: 66.575947 samples/sec accuracy=71.421875 loss=1.158500 lr=0.001000 Epoch[041] Batch [0149]/[3760] Speed: 68.383447 samples/sec accuracy=71.531250 loss=1.140246 lr=0.001000 Epoch[041] Batch [0199]/[3760] Speed: 68.017650 samples/sec accuracy=71.554688 loss=1.131267 lr=0.001000 Epoch[041] Batch [0249]/[3760] Speed: 68.028430 samples/sec accuracy=71.687500 loss=1.126048 lr=0.001000 Epoch[041] Batch [0299]/[3760] 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accuracy=71.978860 loss=1.121144 lr=0.001000 Epoch[041] Batch [1749]/[3760] Speed: 67.804910 samples/sec accuracy=71.965179 loss=1.121850 lr=0.001000 Epoch[041] Batch [1799]/[3760] Speed: 68.276597 samples/sec accuracy=71.988715 loss=1.121181 lr=0.001000 Epoch[041] Batch [1849]/[3760] Speed: 67.699692 samples/sec accuracy=71.971284 loss=1.121475 lr=0.001000 Epoch[041] Batch [1899]/[3760] Speed: 68.032737 samples/sec accuracy=71.950658 loss=1.122184 lr=0.001000 Epoch[041] Batch [1949]/[3760] Speed: 68.087711 samples/sec accuracy=71.927885 loss=1.123302 lr=0.001000 Epoch[041] Batch [1999]/[3760] Speed: 67.965150 samples/sec accuracy=71.942969 loss=1.123173 lr=0.001000 Epoch[041] Batch [2049]/[3760] Speed: 68.076373 samples/sec accuracy=71.960366 loss=1.122169 lr=0.001000 Epoch[041] Batch [2099]/[3760] Speed: 67.943238 samples/sec accuracy=71.945685 loss=1.123425 lr=0.001000 Epoch[041] Batch [2149]/[3760] Speed: 67.658224 samples/sec accuracy=71.957122 loss=1.123174 lr=0.001000 Epoch[041] 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accuracy=72.007075 loss=1.119891 lr=0.001000 Epoch[041] Batch [2699]/[3760] Speed: 67.845526 samples/sec accuracy=71.984375 loss=1.119931 lr=0.001000 Epoch[041] Batch [2749]/[3760] Speed: 67.748919 samples/sec accuracy=71.993182 loss=1.119742 lr=0.001000 Epoch[041] Batch [2799]/[3760] Speed: 67.942024 samples/sec accuracy=72.007812 loss=1.119171 lr=0.001000 Epoch[041] Batch [2849]/[3760] Speed: 68.351301 samples/sec accuracy=72.009868 loss=1.118596 lr=0.001000 Epoch[041] Batch [2899]/[3760] Speed: 68.128246 samples/sec accuracy=72.003772 loss=1.118765 lr=0.001000 Epoch[041] Batch [2949]/[3760] Speed: 67.563485 samples/sec accuracy=72.017479 loss=1.117858 lr=0.001000 Epoch[041] Batch [2999]/[3760] Speed: 68.055803 samples/sec accuracy=72.041146 loss=1.117196 lr=0.001000 Epoch[041] Batch [3049]/[3760] Speed: 67.635067 samples/sec accuracy=72.051742 loss=1.116437 lr=0.001000 Epoch[041] Batch [3099]/[3760] Speed: 67.878673 samples/sec accuracy=72.025202 loss=1.117048 lr=0.001000 Epoch[041] 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accuracy=72.067274 loss=1.114989 lr=0.001000 Epoch[041] Batch [3649]/[3760] Speed: 68.575944 samples/sec accuracy=72.084760 loss=1.114459 lr=0.001000 Epoch[041] Batch [3699]/[3760] Speed: 67.576094 samples/sec accuracy=72.083615 loss=1.114863 lr=0.001000 Epoch[041] Batch [3749]/[3760] Speed: 74.687160 samples/sec accuracy=72.096667 loss=1.114186 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.218750 acc-top5=85.500000 Batch [0099]/[0303]: acc-top1=66.140625 acc-top5=85.500000 Batch [0149]/[0303]: acc-top1=66.250000 acc-top5=85.885417 Batch [0199]/[0303]: acc-top1=66.382812 acc-top5=86.156250 Batch [0249]/[0303]: acc-top1=66.268750 acc-top5=86.231250 Batch [0299]/[0303]: acc-top1=66.338542 acc-top5=86.401042 [Epoch 041] training: accuracy=72.103973 loss=1.113920 [Epoch 041] speed: 67 samples/sec time cost: 3848.842862 [Epoch 041] validation: acc-top1=66.346947 acc-top5=86.422236 loss=1.575349 Epoch[042] Batch [0049]/[3760] Speed: 45.915991 samples/sec accuracy=73.156250 loss=1.086945 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acc-top1=66.460938 acc-top5=86.546875 Batch [0249]/[0303]: acc-top1=66.481250 acc-top5=86.518750 Batch [0299]/[0303]: acc-top1=66.593750 acc-top5=86.666667 [Epoch 042] training: accuracy=72.957114 loss=1.078624 [Epoch 042] speed: 67 samples/sec time cost: 3845.107358 [Epoch 042] validation: acc-top1=66.579002 acc-top5=86.680074 loss=1.578995 Epoch[043] Batch [0049]/[3759] Speed: 45.987243 samples/sec accuracy=74.062500 loss=1.037055 lr=0.001000 Epoch[043] Batch [0099]/[3759] Speed: 66.659554 samples/sec accuracy=73.328125 loss=1.076476 lr=0.001000 Epoch[043] Batch [0149]/[3759] Speed: 68.799747 samples/sec accuracy=73.625000 loss=1.053529 lr=0.001000 Epoch[043] Batch [0199]/[3759] Speed: 67.966902 samples/sec accuracy=73.750000 loss=1.043847 lr=0.001000 Epoch[043] Batch [0249]/[3759] Speed: 68.091780 samples/sec accuracy=73.837500 loss=1.038331 lr=0.001000 Epoch[043] Batch [0299]/[3759] Speed: 67.732293 samples/sec accuracy=74.046875 loss=1.032719 lr=0.001000 Epoch[043] Batch 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accuracy=73.595034 loss=1.053918 lr=0.001000 Epoch[043] Batch [3699]/[3759] Speed: 67.981837 samples/sec accuracy=73.566301 loss=1.054298 lr=0.001000 Epoch[043] Batch [3749]/[3759] Speed: 74.590706 samples/sec accuracy=73.574583 loss=1.054124 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.937500 acc-top5=86.562500 Batch [0099]/[0303]: acc-top1=66.609375 acc-top5=86.031250 Batch [0149]/[0303]: acc-top1=66.802083 acc-top5=86.302083 Batch [0199]/[0303]: acc-top1=66.726562 acc-top5=86.429688 Batch [0249]/[0303]: acc-top1=66.731250 acc-top5=86.443750 Batch [0299]/[0303]: acc-top1=66.927083 acc-top5=86.619792 [Epoch 043] training: accuracy=73.580490 loss=1.053868 [Epoch 043] speed: 67 samples/sec time cost: 3843.874663 [Epoch 043] validation: acc-top1=66.919348 acc-top5=86.633663 loss=1.543611 Epoch[044] Batch [0049]/[3760] Speed: 45.358587 samples/sec accuracy=72.968750 loss=1.080748 lr=0.001000 Epoch[044] Batch [0099]/[3760] Speed: 66.709760 samples/sec accuracy=73.921875 loss=1.045825 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[0299]/[0303]: acc-top1=66.588542 acc-top5=86.578125 [Epoch 044] training: accuracy=73.860954 loss=1.041994 [Epoch 044] speed: 67 samples/sec time cost: 3850.406390 [Epoch 044] validation: acc-top1=66.584158 acc-top5=86.602723 loss=1.572348 Epoch[045] Batch [0049]/[3760] Speed: 45.916911 samples/sec accuracy=74.718750 loss=1.008559 lr=0.001000 Epoch[045] Batch [0099]/[3760] Speed: 66.751368 samples/sec accuracy=74.406250 loss=1.010493 lr=0.001000 Epoch[045] Batch [0149]/[3760] Speed: 67.746987 samples/sec accuracy=73.989583 loss=1.021389 lr=0.001000 Epoch[045] Batch [0199]/[3760] Speed: 67.772782 samples/sec accuracy=74.250000 loss=1.019053 lr=0.001000 Epoch[045] Batch [0249]/[3760] Speed: 68.184235 samples/sec accuracy=74.268750 loss=1.021214 lr=0.001000 Epoch[045] Batch [0299]/[3760] Speed: 67.779894 samples/sec accuracy=74.255208 loss=1.022951 lr=0.001000 Epoch[045] Batch [0349]/[3760] Speed: 67.751246 samples/sec accuracy=74.419643 loss=1.018455 lr=0.001000 Epoch[045] Batch 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accuracy=74.310227 loss=1.021015 lr=0.001000 Epoch[045] Batch [2799]/[3760] Speed: 68.323067 samples/sec accuracy=74.315848 loss=1.021104 lr=0.001000 Epoch[045] Batch [2849]/[3760] Speed: 67.798993 samples/sec accuracy=74.319627 loss=1.021226 lr=0.001000 Epoch[045] Batch [2899]/[3760] Speed: 67.890514 samples/sec accuracy=74.308190 loss=1.021701 lr=0.001000 Epoch[045] Batch [2949]/[3760] Speed: 68.173777 samples/sec accuracy=74.316737 loss=1.021542 lr=0.001000 Epoch[045] Batch [2999]/[3760] Speed: 68.102443 samples/sec accuracy=74.314583 loss=1.021831 lr=0.001000 Epoch[045] Batch [3049]/[3760] Speed: 67.734353 samples/sec accuracy=74.316598 loss=1.021853 lr=0.001000 Epoch[045] Batch [3099]/[3760] Speed: 68.500198 samples/sec accuracy=74.317036 loss=1.021513 lr=0.001000 Epoch[045] Batch [3149]/[3760] Speed: 67.711790 samples/sec accuracy=74.324901 loss=1.021918 lr=0.001000 Epoch[045] Batch [3199]/[3760] Speed: 67.941556 samples/sec accuracy=74.320312 loss=1.021783 lr=0.001000 Epoch[045] 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accuracy=74.308277 loss=1.021926 lr=0.001000 Epoch[045] Batch [3749]/[3760] Speed: 74.707066 samples/sec accuracy=74.315417 loss=1.022039 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.406250 acc-top5=86.218750 Batch [0099]/[0303]: acc-top1=66.390625 acc-top5=85.875000 Batch [0149]/[0303]: acc-top1=66.375000 acc-top5=86.250000 Batch [0199]/[0303]: acc-top1=66.515625 acc-top5=86.500000 Batch [0249]/[0303]: acc-top1=66.606250 acc-top5=86.500000 Batch [0299]/[0303]: acc-top1=66.692708 acc-top5=86.687500 [Epoch 045] training: accuracy=74.308926 loss=1.022135 [Epoch 045] speed: 67 samples/sec time cost: 3846.733279 [Epoch 045] validation: acc-top1=66.661510 acc-top5=86.700701 loss=1.555690 Epoch[046] Batch [0049]/[3759] Speed: 45.407732 samples/sec accuracy=74.687500 loss=0.984987 lr=0.001000 Epoch[046] Batch [0099]/[3759] Speed: 67.251834 samples/sec accuracy=74.609375 loss=0.983455 lr=0.001000 Epoch[046] Batch [0149]/[3759] Speed: 68.188380 samples/sec accuracy=74.760417 loss=0.985768 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lr=0.001000 Epoch[046] Batch [3049]/[3759] Speed: 67.560559 samples/sec accuracy=74.544570 loss=1.004516 lr=0.001000 Epoch[046] Batch [3099]/[3759] Speed: 68.377869 samples/sec accuracy=74.534274 loss=1.004735 lr=0.001000 Epoch[046] Batch [3149]/[3759] Speed: 67.878198 samples/sec accuracy=74.534722 loss=1.004379 lr=0.001000 Epoch[046] Batch [3199]/[3759] Speed: 67.877918 samples/sec accuracy=74.534668 loss=1.004826 lr=0.001000 Epoch[046] Batch [3249]/[3759] Speed: 68.124000 samples/sec accuracy=74.523077 loss=1.005353 lr=0.001000 Epoch[046] Batch [3299]/[3759] Speed: 67.799144 samples/sec accuracy=74.535985 loss=1.005386 lr=0.001000 Epoch[046] Batch [3349]/[3759] Speed: 68.562143 samples/sec accuracy=74.542910 loss=1.005484 lr=0.001000 Epoch[046] Batch [3399]/[3759] Speed: 67.454647 samples/sec accuracy=74.558824 loss=1.005241 lr=0.001000 Epoch[046] Batch [3449]/[3759] Speed: 67.606218 samples/sec accuracy=74.560236 loss=1.004809 lr=0.001000 Epoch[046] Batch [3499]/[3759] Speed: 67.450923 samples/sec accuracy=74.558482 loss=1.005218 lr=0.001000 Epoch[046] Batch [3549]/[3759] Speed: 67.606436 samples/sec accuracy=74.563820 loss=1.005376 lr=0.001000 Epoch[046] Batch [3599]/[3759] Speed: 68.289827 samples/sec accuracy=74.551215 loss=1.005818 lr=0.001000 Epoch[046] Batch [3649]/[3759] Speed: 68.007710 samples/sec accuracy=74.546661 loss=1.005927 lr=0.001000 Epoch[046] Batch [3699]/[3759] Speed: 67.720462 samples/sec accuracy=74.573902 loss=1.005355 lr=0.001000 Epoch[046] Batch [3749]/[3759] Speed: 74.115642 samples/sec accuracy=74.553333 loss=1.006239 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.250000 acc-top5=85.750000 Batch [0099]/[0303]: acc-top1=66.500000 acc-top5=85.937500 Batch [0149]/[0303]: acc-top1=66.791667 acc-top5=86.260417 Batch [0199]/[0303]: acc-top1=67.140625 acc-top5=86.398438 Batch [0249]/[0303]: acc-top1=66.912500 acc-top5=86.368750 Batch [0299]/[0303]: acc-top1=67.010417 acc-top5=86.598958 [Epoch 046] training: accuracy=74.552740 loss=1.006259 [Epoch 046] speed: 67 samples/sec time cost: 3846.904477 [Epoch 046] validation: acc-top1=67.017327 acc-top5=86.618193 loss=1.555711 Epoch[047] Batch [0049]/[3760] Speed: 46.022786 samples/sec accuracy=75.468750 loss=0.964513 lr=0.001000 Epoch[047] Batch [0099]/[3760] Speed: 66.875428 samples/sec accuracy=75.156250 loss=0.973478 lr=0.001000 Epoch[047] Batch [0149]/[3760] Speed: 68.183811 samples/sec accuracy=75.531250 loss=0.962092 lr=0.001000 Epoch[047] Batch [0199]/[3760] Speed: 67.609772 samples/sec accuracy=75.531250 loss=0.960680 lr=0.001000 Epoch[047] Batch [0249]/[3760] Speed: 67.691668 samples/sec accuracy=75.481250 loss=0.965631 lr=0.001000 Epoch[047] Batch [0299]/[3760] Speed: 68.144040 samples/sec accuracy=75.296875 loss=0.976293 lr=0.001000 Epoch[047] Batch [0349]/[3760] Speed: 67.788493 samples/sec accuracy=75.156250 loss=0.978868 lr=0.001000 Epoch[047] Batch [0399]/[3760] Speed: 67.918505 samples/sec accuracy=75.246094 loss=0.975787 lr=0.001000 Epoch[047] Batch 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accuracy=74.963542 loss=0.984799 lr=0.001000 Epoch[047] Batch [0949]/[3760] Speed: 67.912272 samples/sec accuracy=74.963816 loss=0.985341 lr=0.001000 Epoch[047] Batch [0999]/[3760] Speed: 67.393577 samples/sec accuracy=74.960938 loss=0.985566 lr=0.001000 Epoch[047] Batch [1049]/[3760] Speed: 67.802561 samples/sec accuracy=75.010417 loss=0.983717 lr=0.001000 Epoch[047] Batch [1099]/[3760] Speed: 67.894790 samples/sec accuracy=75.065341 loss=0.983677 lr=0.001000 Epoch[047] Batch [1149]/[3760] Speed: 68.063806 samples/sec accuracy=75.051630 loss=0.983316 lr=0.001000 Epoch[047] Batch [1199]/[3760] Speed: 67.658383 samples/sec accuracy=75.006510 loss=0.984834 lr=0.001000 Epoch[047] Batch [1249]/[3760] Speed: 67.739303 samples/sec accuracy=75.010000 loss=0.985459 lr=0.001000 Epoch[047] Batch [1299]/[3760] Speed: 67.993861 samples/sec accuracy=75.003606 loss=0.984374 lr=0.001000 Epoch[047] Batch [1349]/[3760] Speed: 68.108796 samples/sec accuracy=74.989583 loss=0.984293 lr=0.001000 Epoch[047] 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accuracy=74.939189 loss=0.990417 lr=0.001000 Epoch[047] Batch [1899]/[3760] Speed: 68.080006 samples/sec accuracy=74.925164 loss=0.991343 lr=0.001000 Epoch[047] Batch [1949]/[3760] Speed: 68.202687 samples/sec accuracy=74.936699 loss=0.990249 lr=0.001000 Epoch[047] Batch [1999]/[3760] Speed: 67.578425 samples/sec accuracy=74.929688 loss=0.990104 lr=0.001000 Epoch[047] Batch [2049]/[3760] Speed: 67.971634 samples/sec accuracy=74.912348 loss=0.990545 lr=0.001000 Epoch[047] Batch [2099]/[3760] Speed: 66.972026 samples/sec accuracy=74.921131 loss=0.989524 lr=0.001000 Epoch[047] Batch [2149]/[3760] Speed: 68.036104 samples/sec accuracy=74.923692 loss=0.989144 lr=0.001000 Epoch[047] Batch [2199]/[3760] Speed: 68.789709 samples/sec accuracy=74.909091 loss=0.990177 lr=0.001000 Epoch[047] Batch [2249]/[3760] Speed: 67.469251 samples/sec accuracy=74.934028 loss=0.990250 lr=0.001000 Epoch[047] Batch [2299]/[3760] Speed: 68.136329 samples/sec accuracy=74.922554 loss=0.990681 lr=0.001000 Epoch[047] 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accuracy=74.926897 loss=0.989889 lr=0.001000 Epoch[047] Batch [2849]/[3760] Speed: 68.363553 samples/sec accuracy=74.933114 loss=0.989736 lr=0.001000 Epoch[047] Batch [2899]/[3760] Speed: 67.804146 samples/sec accuracy=74.929957 loss=0.990286 lr=0.001000 Epoch[047] Batch [2949]/[3760] Speed: 67.261337 samples/sec accuracy=74.939089 loss=0.990828 lr=0.001000 Epoch[047] Batch [2999]/[3760] Speed: 68.348937 samples/sec accuracy=74.920312 loss=0.991583 lr=0.001000 Epoch[047] Batch [3049]/[3760] Speed: 67.742718 samples/sec accuracy=74.909836 loss=0.992102 lr=0.001000 Epoch[047] Batch [3099]/[3760] Speed: 67.887702 samples/sec accuracy=74.932964 loss=0.990870 lr=0.001000 Epoch[047] Batch [3149]/[3760] Speed: 67.776659 samples/sec accuracy=74.935020 loss=0.990718 lr=0.001000 Epoch[047] Batch [3199]/[3760] Speed: 67.994612 samples/sec accuracy=74.916992 loss=0.991319 lr=0.001000 Epoch[047] Batch [3249]/[3760] Speed: 67.564770 samples/sec accuracy=74.912981 loss=0.991603 lr=0.001000 Epoch[047] 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accuracy=74.865000 loss=0.992552 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.750000 acc-top5=86.156250 Batch [0099]/[0303]: acc-top1=66.359375 acc-top5=86.046875 Batch [0149]/[0303]: acc-top1=66.625000 acc-top5=86.447917 Batch [0199]/[0303]: acc-top1=66.867188 acc-top5=86.617188 Batch [0249]/[0303]: acc-top1=66.856250 acc-top5=86.587500 Batch [0299]/[0303]: acc-top1=66.973958 acc-top5=86.786458 [Epoch 047] training: accuracy=74.859541 loss=0.992626 [Epoch 047] speed: 67 samples/sec time cost: 3852.232367 [Epoch 047] validation: acc-top1=66.981229 acc-top5=86.783210 loss=1.553616 Epoch[048] Batch [0049]/[3760] Speed: 45.013800 samples/sec accuracy=74.750000 loss=0.986108 lr=0.001000 Epoch[048] Batch [0099]/[3760] Speed: 67.156354 samples/sec accuracy=75.250000 loss=0.972502 lr=0.001000 Epoch[048] Batch [0149]/[3760] Speed: 67.733223 samples/sec accuracy=75.302083 loss=0.974420 lr=0.001000 Epoch[048] Batch [0199]/[3760] Speed: 67.609752 samples/sec accuracy=75.421875 loss=0.972077 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68.450137 samples/sec accuracy=75.189701 loss=0.981618 lr=0.001000 Epoch[048] Batch [3599]/[3760] Speed: 67.961147 samples/sec accuracy=75.181424 loss=0.981714 lr=0.001000 Epoch[048] Batch [3649]/[3760] Speed: 67.350795 samples/sec accuracy=75.194349 loss=0.981152 lr=0.001000 Epoch[048] Batch [3699]/[3760] Speed: 67.836920 samples/sec accuracy=75.203125 loss=0.981030 lr=0.001000 Epoch[048] Batch [3749]/[3760] Speed: 73.952334 samples/sec accuracy=75.215833 loss=0.980668 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.843750 acc-top5=85.937500 Batch [0099]/[0303]: acc-top1=66.406250 acc-top5=85.937500 Batch [0149]/[0303]: acc-top1=66.489583 acc-top5=86.385417 Batch [0199]/[0303]: acc-top1=66.851562 acc-top5=86.578125 Batch [0249]/[0303]: acc-top1=66.912500 acc-top5=86.531250 Batch [0299]/[0303]: acc-top1=66.968750 acc-top5=86.734375 [Epoch 048] training: accuracy=75.214428 loss=0.980655 [Epoch 048] speed: 67 samples/sec time cost: 3851.795316 [Epoch 048] validation: acc-top1=66.960602 acc-top5=86.752269 loss=1.558931 Epoch[049] Batch [0049]/[3759] Speed: 45.535772 samples/sec accuracy=76.312500 loss=0.972706 lr=0.001000 Epoch[049] Batch [0099]/[3759] Speed: 67.366224 samples/sec accuracy=76.765625 loss=0.941414 lr=0.001000 Epoch[049] Batch [0149]/[3759] Speed: 68.096361 samples/sec accuracy=76.437500 loss=0.943521 lr=0.001000 Epoch[049] Batch [0199]/[3759] Speed: 67.851538 samples/sec accuracy=76.125000 loss=0.951242 lr=0.001000 Epoch[049] Batch [0249]/[3759] Speed: 67.598599 samples/sec accuracy=75.981250 loss=0.953822 lr=0.001000 Epoch[049] Batch [0299]/[3759] Speed: 68.014945 samples/sec accuracy=76.000000 loss=0.948625 lr=0.001000 Epoch[049] Batch [0349]/[3759] Speed: 67.670976 samples/sec accuracy=76.183036 loss=0.942171 lr=0.001000 Epoch[049] Batch [0399]/[3759] Speed: 67.959374 samples/sec accuracy=76.144531 loss=0.944130 lr=0.001000 Epoch[049] Batch [0449]/[3759] Speed: 67.199779 samples/sec accuracy=75.989583 loss=0.947197 lr=0.001000 Epoch[049] Batch 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accuracy=75.547697 loss=0.969068 lr=0.001000 Epoch[049] Batch [2899]/[3759] Speed: 67.910827 samples/sec accuracy=75.558728 loss=0.968663 lr=0.001000 Epoch[049] Batch [2949]/[3759] Speed: 67.804559 samples/sec accuracy=75.568326 loss=0.968567 lr=0.001000 Epoch[049] Batch [2999]/[3759] Speed: 67.173568 samples/sec accuracy=75.566667 loss=0.968435 lr=0.001000 Epoch[049] Batch [3049]/[3759] Speed: 68.332824 samples/sec accuracy=75.545594 loss=0.968772 lr=0.001000 Epoch[049] Batch [3099]/[3759] Speed: 67.231594 samples/sec accuracy=75.539819 loss=0.969136 lr=0.001000 Epoch[049] Batch [3149]/[3759] Speed: 68.265380 samples/sec accuracy=75.510417 loss=0.970294 lr=0.001000 Epoch[049] Batch [3199]/[3759] Speed: 67.731784 samples/sec accuracy=75.521973 loss=0.969826 lr=0.001000 Epoch[049] Batch [3249]/[3759] Speed: 68.001646 samples/sec accuracy=75.521635 loss=0.969644 lr=0.001000 Epoch[049] Batch [3299]/[3759] Speed: 68.055897 samples/sec accuracy=75.544034 loss=0.969146 lr=0.001000 Epoch[049] 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[0099]/[0303]: acc-top1=66.578125 acc-top5=85.984375 Batch [0149]/[0303]: acc-top1=66.739583 acc-top5=86.385417 Batch [0199]/[0303]: acc-top1=66.968750 acc-top5=86.585938 Batch [0249]/[0303]: acc-top1=67.025000 acc-top5=86.506250 Batch [0299]/[0303]: acc-top1=67.093750 acc-top5=86.708333 [Epoch 049] training: accuracy=75.458483 loss=0.970968 [Epoch 049] speed: 67 samples/sec time cost: 3850.708733 [Epoch 049] validation: acc-top1=67.079208 acc-top5=86.726485 loss=1.555312 Epoch[050] Batch [0049]/[3760] Speed: 45.300608 samples/sec accuracy=76.406250 loss=0.930433 lr=0.001000 Epoch[050] Batch [0099]/[3760] Speed: 67.105318 samples/sec accuracy=76.328125 loss=0.946608 lr=0.001000 Epoch[050] Batch [0149]/[3760] Speed: 67.589384 samples/sec accuracy=76.177083 loss=0.954368 lr=0.001000 Epoch[050] Batch [0199]/[3760] Speed: 67.577110 samples/sec accuracy=76.085938 loss=0.958300 lr=0.001000 Epoch[050] Batch [0249]/[3760] Speed: 67.676251 samples/sec accuracy=76.056250 loss=0.962665 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68.046932 samples/sec accuracy=75.599826 loss=0.961907 lr=0.001000 Epoch[050] Batch [3649]/[3760] Speed: 68.000125 samples/sec accuracy=75.619435 loss=0.961420 lr=0.001000 Epoch[050] Batch [3699]/[3760] Speed: 67.852900 samples/sec accuracy=75.622044 loss=0.961315 lr=0.001000 Epoch[050] Batch [3749]/[3760] Speed: 74.204729 samples/sec accuracy=75.633750 loss=0.960969 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.125000 acc-top5=86.218750 Batch [0099]/[0303]: acc-top1=66.828125 acc-top5=85.890625 Batch [0149]/[0303]: acc-top1=66.895833 acc-top5=86.447917 Batch [0199]/[0303]: acc-top1=66.976562 acc-top5=86.664062 Batch [0249]/[0303]: acc-top1=67.006250 acc-top5=86.643750 Batch [0299]/[0303]: acc-top1=67.036458 acc-top5=86.828125 [Epoch 050] training: accuracy=75.633727 loss=0.961138 [Epoch 050] speed: 67 samples/sec time cost: 3848.687116 [Epoch 050] validation: acc-top1=67.043111 acc-top5=86.855404 loss=1.566225 Epoch[051] Batch [0049]/[3760] Speed: 45.729937 samples/sec 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accuracy=75.993534 loss=0.946849 lr=0.001000 Epoch[051] Batch [2949]/[3760] Speed: 67.618040 samples/sec accuracy=75.980403 loss=0.947408 lr=0.001000 Epoch[051] Batch [2999]/[3760] Speed: 68.127016 samples/sec accuracy=75.963542 loss=0.947960 lr=0.001000 Epoch[051] Batch [3049]/[3760] Speed: 67.911323 samples/sec accuracy=75.967725 loss=0.947830 lr=0.001000 Epoch[051] Batch [3099]/[3760] Speed: 68.016636 samples/sec accuracy=75.962198 loss=0.947296 lr=0.001000 Epoch[051] Batch [3149]/[3760] Speed: 68.367027 samples/sec accuracy=75.960813 loss=0.947445 lr=0.001000 Epoch[051] Batch [3199]/[3760] Speed: 67.712036 samples/sec accuracy=75.950195 loss=0.947995 lr=0.001000 Epoch[051] Batch [3249]/[3760] Speed: 67.702468 samples/sec accuracy=75.964904 loss=0.947677 lr=0.001000 Epoch[051] Batch [3299]/[3760] Speed: 67.683932 samples/sec accuracy=75.962121 loss=0.947675 lr=0.001000 Epoch[051] Batch [3349]/[3760] Speed: 67.602040 samples/sec accuracy=75.974813 loss=0.946952 lr=0.001000 Epoch[051] 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acc-top5=86.322917 Batch [0199]/[0303]: acc-top1=67.203125 acc-top5=86.476562 Batch [0249]/[0303]: acc-top1=67.231250 acc-top5=86.462500 Batch [0299]/[0303]: acc-top1=67.234375 acc-top5=86.661458 [Epoch 051] training: accuracy=75.913813 loss=0.948877 [Epoch 051] speed: 67 samples/sec time cost: 3849.303102 [Epoch 051] validation: acc-top1=67.244224 acc-top5=86.690388 loss=1.565254 Epoch[052] Batch [0049]/[3759] Speed: 45.486895 samples/sec accuracy=76.468750 loss=0.916186 lr=0.001000 Epoch[052] Batch [0099]/[3759] Speed: 66.970077 samples/sec accuracy=75.796875 loss=0.948329 lr=0.001000 Epoch[052] Batch [0149]/[3759] Speed: 67.940334 samples/sec accuracy=76.218750 loss=0.930190 lr=0.001000 Epoch[052] Batch [0199]/[3759] Speed: 67.535478 samples/sec accuracy=76.031250 loss=0.941862 lr=0.001000 Epoch[052] Batch [0249]/[3759] Speed: 67.747279 samples/sec accuracy=76.212500 loss=0.940930 lr=0.001000 Epoch[052] Batch [0299]/[3759] Speed: 68.609805 samples/sec accuracy=76.276042 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accuracy=76.106250 loss=0.942587 lr=0.001000 Epoch[052] Batch [1299]/[3759] Speed: 67.860055 samples/sec accuracy=76.143029 loss=0.941231 lr=0.001000 Epoch[052] Batch [1349]/[3759] Speed: 67.699005 samples/sec accuracy=76.140046 loss=0.941824 lr=0.001000 Epoch[052] Batch [1399]/[3759] Speed: 67.971375 samples/sec accuracy=76.112723 loss=0.942998 lr=0.001000 Epoch[052] Batch [1449]/[3759] Speed: 67.489580 samples/sec accuracy=76.080819 loss=0.943838 lr=0.001000 Epoch[052] Batch [1499]/[3759] Speed: 68.102445 samples/sec accuracy=76.041667 loss=0.944078 lr=0.001000 Epoch[052] Batch [1549]/[3759] Speed: 68.112475 samples/sec accuracy=76.040323 loss=0.944784 lr=0.001000 Epoch[052] Batch [1599]/[3759] Speed: 68.284659 samples/sec accuracy=76.005859 loss=0.945511 lr=0.001000 Epoch[052] Batch [1649]/[3759] Speed: 67.788955 samples/sec accuracy=76.006629 loss=0.945304 lr=0.001000 Epoch[052] Batch [1699]/[3759] Speed: 67.759261 samples/sec accuracy=76.013787 loss=0.945267 lr=0.001000 Epoch[052] 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accuracy=76.001420 loss=0.945876 lr=0.001000 Epoch[052] Batch [2249]/[3759] Speed: 68.197787 samples/sec accuracy=76.006250 loss=0.945421 lr=0.001000 Epoch[052] Batch [2299]/[3759] Speed: 67.930464 samples/sec accuracy=76.038723 loss=0.944404 lr=0.001000 Epoch[052] Batch [2349]/[3759] Speed: 68.763335 samples/sec accuracy=76.049867 loss=0.943459 lr=0.001000 Epoch[052] Batch [2399]/[3759] Speed: 67.719734 samples/sec accuracy=76.029297 loss=0.944030 lr=0.001000 Epoch[052] Batch [2449]/[3759] Speed: 67.336557 samples/sec accuracy=76.012117 loss=0.944577 lr=0.001000 Epoch[052] Batch [2499]/[3759] Speed: 68.644264 samples/sec accuracy=76.015000 loss=0.944321 lr=0.001000 Epoch[052] Batch [2549]/[3759] Speed: 67.881005 samples/sec accuracy=76.037377 loss=0.943785 lr=0.001000 Epoch[052] Batch [2599]/[3759] Speed: 67.337695 samples/sec accuracy=76.042067 loss=0.943660 lr=0.001000 Epoch[052] Batch [2649]/[3759] Speed: 68.249788 samples/sec accuracy=76.052476 loss=0.943192 lr=0.001000 Epoch[052] Batch [2699]/[3759] Speed: 66.703594 samples/sec accuracy=76.047454 loss=0.943201 lr=0.001000 Epoch[052] Batch [2749]/[3759] Speed: 68.437061 samples/sec accuracy=76.059659 loss=0.942932 lr=0.001000 Epoch[052] Batch [2799]/[3759] Speed: 67.994141 samples/sec accuracy=76.056920 loss=0.942986 lr=0.001000 Epoch[052] Batch [2849]/[3759] Speed: 67.574528 samples/sec accuracy=76.036732 loss=0.943060 lr=0.001000 Epoch[052] Batch [2899]/[3759] Speed: 68.369318 samples/sec accuracy=76.051185 loss=0.943038 lr=0.001000 Epoch[052] Batch [2949]/[3759] Speed: 67.502697 samples/sec accuracy=76.053496 loss=0.943583 lr=0.001000 Epoch[052] Batch [2999]/[3759] Speed: 68.015311 samples/sec accuracy=76.041146 loss=0.944261 lr=0.001000 Epoch[052] Batch [3049]/[3759] Speed: 67.659930 samples/sec accuracy=76.049180 loss=0.944398 lr=0.001000 Epoch[052] Batch [3099]/[3759] Speed: 67.481451 samples/sec accuracy=76.056956 loss=0.944016 lr=0.001000 Epoch[052] Batch [3149]/[3759] Speed: 67.938476 samples/sec accuracy=76.060516 loss=0.943953 lr=0.001000 Epoch[052] Batch [3199]/[3759] Speed: 68.208976 samples/sec accuracy=76.059570 loss=0.944040 lr=0.001000 Epoch[052] Batch [3249]/[3759] Speed: 68.137788 samples/sec accuracy=76.075000 loss=0.943697 lr=0.001000 Epoch[052] Batch [3299]/[3759] Speed: 68.168252 samples/sec accuracy=76.085701 loss=0.943338 lr=0.001000 Epoch[052] Batch [3349]/[3759] Speed: 67.970326 samples/sec accuracy=76.075560 loss=0.943310 lr=0.001000 Epoch[052] Batch [3399]/[3759] Speed: 67.885197 samples/sec accuracy=76.101103 loss=0.942783 lr=0.001000 Epoch[052] Batch [3449]/[3759] Speed: 67.373873 samples/sec accuracy=76.099185 loss=0.943082 lr=0.001000 Epoch[052] Batch [3499]/[3759] Speed: 68.380461 samples/sec accuracy=76.125000 loss=0.942291 lr=0.001000 Epoch[052] Batch [3549]/[3759] Speed: 67.980233 samples/sec accuracy=76.121919 loss=0.942553 lr=0.001000 Epoch[052] Batch [3599]/[3759] Speed: 67.576316 samples/sec accuracy=76.120226 loss=0.943040 lr=0.001000 Epoch[052] Batch [3649]/[3759] Speed: 68.248521 samples/sec accuracy=76.113442 loss=0.943356 lr=0.001000 Epoch[052] Batch [3699]/[3759] Speed: 67.620049 samples/sec accuracy=76.105997 loss=0.943404 lr=0.001000 Epoch[052] Batch [3749]/[3759] Speed: 75.061227 samples/sec accuracy=76.104583 loss=0.943501 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.187500 acc-top5=86.062500 Batch [0099]/[0303]: acc-top1=66.859375 acc-top5=85.968750 Batch [0149]/[0303]: acc-top1=66.791667 acc-top5=86.354167 Batch [0199]/[0303]: acc-top1=67.007812 acc-top5=86.484375 Batch [0249]/[0303]: acc-top1=67.087500 acc-top5=86.487500 Batch [0299]/[0303]: acc-top1=67.119792 acc-top5=86.687500 [Epoch 052] training: accuracy=76.101939 loss=0.943608 [Epoch 052] speed: 67 samples/sec time cost: 3847.070634 [Epoch 052] validation: acc-top1=67.151403 acc-top5=86.705858 loss=1.552539 Epoch[053] Batch [0049]/[3760] Speed: 45.218853 samples/sec accuracy=77.562500 loss=0.896647 lr=0.001000 Epoch[053] Batch [0099]/[3760] Speed: 67.446426 samples/sec accuracy=77.000000 loss=0.904751 lr=0.001000 Epoch[053] Batch [0149]/[3760] Speed: 68.189777 samples/sec accuracy=77.166667 loss=0.905410 lr=0.001000 Epoch[053] Batch [0199]/[3760] Speed: 67.603911 samples/sec accuracy=76.937500 loss=0.906488 lr=0.001000 Epoch[053] Batch [0249]/[3760] Speed: 67.648855 samples/sec accuracy=76.987500 loss=0.903241 lr=0.001000 Epoch[053] Batch [0299]/[3760] Speed: 68.353266 samples/sec accuracy=76.932292 loss=0.911815 lr=0.001000 Epoch[053] Batch [0349]/[3760] Speed: 67.411032 samples/sec accuracy=76.950893 loss=0.913654 lr=0.001000 Epoch[053] Batch [0399]/[3760] Speed: 68.053681 samples/sec accuracy=76.867188 loss=0.918711 lr=0.001000 Epoch[053] Batch [0449]/[3760] Speed: 68.165424 samples/sec accuracy=76.989583 loss=0.911504 lr=0.001000 Epoch[053] Batch [0499]/[3760] Speed: 68.036659 samples/sec accuracy=76.975000 loss=0.910405 lr=0.001000 Epoch[053] Batch [0549]/[3760] Speed: 68.075746 samples/sec accuracy=76.906250 loss=0.912395 lr=0.001000 Epoch[053] Batch [0599]/[3760] Speed: 67.793426 samples/sec accuracy=76.820312 loss=0.916207 lr=0.001000 Epoch[053] Batch [0649]/[3760] Speed: 68.371390 samples/sec accuracy=76.875000 loss=0.912939 lr=0.001000 Epoch[053] Batch [0699]/[3760] Speed: 67.606753 samples/sec accuracy=76.899554 loss=0.913101 lr=0.001000 Epoch[053] Batch [0749]/[3760] Speed: 67.907188 samples/sec accuracy=76.827083 loss=0.914176 lr=0.001000 Epoch[053] Batch [0799]/[3760] Speed: 67.969653 samples/sec accuracy=76.789062 loss=0.914667 lr=0.001000 Epoch[053] Batch [0849]/[3760] Speed: 67.960120 samples/sec accuracy=76.681985 loss=0.917840 lr=0.001000 Epoch[053] Batch [0899]/[3760] Speed: 68.248394 samples/sec accuracy=76.656250 loss=0.919328 lr=0.001000 Epoch[053] Batch [0949]/[3760] Speed: 67.548036 samples/sec accuracy=76.646382 loss=0.920114 lr=0.001000 Epoch[053] Batch [0999]/[3760] Speed: 68.160267 samples/sec accuracy=76.632812 loss=0.919624 lr=0.001000 Epoch[053] Batch [1049]/[3760] Speed: 67.379336 samples/sec accuracy=76.654762 loss=0.919604 lr=0.001000 Epoch[053] Batch [1099]/[3760] Speed: 68.823574 samples/sec accuracy=76.644886 loss=0.919083 lr=0.001000 Epoch[053] Batch [1149]/[3760] Speed: 67.864993 samples/sec accuracy=76.638587 loss=0.919796 lr=0.001000 Epoch[053] Batch [1199]/[3760] Speed: 68.766860 samples/sec accuracy=76.666667 loss=0.919107 lr=0.001000 Epoch[053] Batch [1249]/[3760] Speed: 67.870027 samples/sec accuracy=76.628750 loss=0.920140 lr=0.001000 Epoch[053] Batch [1299]/[3760] Speed: 67.681324 samples/sec accuracy=76.574519 loss=0.921975 lr=0.001000 Epoch[053] Batch [1349]/[3760] Speed: 67.747581 samples/sec accuracy=76.575231 loss=0.922244 lr=0.001000 Epoch[053] Batch [1399]/[3760] Speed: 68.376314 samples/sec accuracy=76.572545 loss=0.922933 lr=0.001000 Epoch[053] Batch [1449]/[3760] Speed: 67.613083 samples/sec accuracy=76.618534 loss=0.921370 lr=0.001000 Epoch[053] Batch [1499]/[3760] Speed: 68.240686 samples/sec accuracy=76.576042 loss=0.922659 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68.449890 samples/sec accuracy=76.565625 loss=0.923706 lr=0.001000 Epoch[053] Batch [2049]/[3760] Speed: 67.415719 samples/sec accuracy=76.569360 loss=0.923838 lr=0.001000 Epoch[053] Batch [2099]/[3760] Speed: 68.248583 samples/sec accuracy=76.574405 loss=0.923762 lr=0.001000 Epoch[053] Batch [2149]/[3760] Speed: 68.292731 samples/sec accuracy=76.557413 loss=0.923302 lr=0.001000 Epoch[053] Batch [2199]/[3760] Speed: 68.131328 samples/sec accuracy=76.555398 loss=0.923469 lr=0.001000 Epoch[053] Batch [2249]/[3760] Speed: 68.064517 samples/sec accuracy=76.533333 loss=0.924560 lr=0.001000 Epoch[053] Batch [2299]/[3760] Speed: 67.799453 samples/sec accuracy=76.516984 loss=0.925474 lr=0.001000 Epoch[053] Batch [2349]/[3760] Speed: 67.993506 samples/sec accuracy=76.523271 loss=0.925230 lr=0.001000 Epoch[053] Batch [2399]/[3760] Speed: 68.185159 samples/sec accuracy=76.516927 loss=0.925110 lr=0.001000 Epoch[053] Batch [2449]/[3760] Speed: 67.565710 samples/sec accuracy=76.526786 loss=0.924554 lr=0.001000 Epoch[053] Batch [2499]/[3760] Speed: 68.463094 samples/sec accuracy=76.507500 loss=0.924748 lr=0.001000 Epoch[053] Batch [2549]/[3760] Speed: 67.903700 samples/sec accuracy=76.484681 loss=0.925628 lr=0.001000 Epoch[053] Batch [2599]/[3760] Speed: 67.821235 samples/sec accuracy=76.465745 loss=0.926204 lr=0.001000 Epoch[053] Batch [2649]/[3760] Speed: 68.044274 samples/sec accuracy=76.458726 loss=0.926500 lr=0.001000 Epoch[053] Batch [2699]/[3760] Speed: 67.804600 samples/sec accuracy=76.448495 loss=0.926893 lr=0.001000 Epoch[053] Batch [2749]/[3760] Speed: 67.939585 samples/sec accuracy=76.403977 loss=0.928729 lr=0.001000 Epoch[053] Batch [2799]/[3760] Speed: 68.443616 samples/sec accuracy=76.399554 loss=0.929124 lr=0.001000 Epoch[053] Batch [2849]/[3760] Speed: 67.492340 samples/sec accuracy=76.396930 loss=0.928876 lr=0.001000 Epoch[053] Batch [2899]/[3760] Speed: 67.989262 samples/sec accuracy=76.373922 loss=0.929989 lr=0.001000 Epoch[053] Batch [2949]/[3760] Speed: 67.327199 samples/sec accuracy=76.355932 loss=0.930791 lr=0.001000 Epoch[053] Batch [2999]/[3760] Speed: 69.045184 samples/sec accuracy=76.375000 loss=0.930654 lr=0.001000 Epoch[053] Batch [3049]/[3760] Speed: 67.518410 samples/sec accuracy=76.363217 loss=0.931076 lr=0.001000 Epoch[053] Batch [3099]/[3760] Speed: 68.638944 samples/sec accuracy=76.335685 loss=0.932353 lr=0.001000 Epoch[053] Batch [3149]/[3760] Speed: 67.586610 samples/sec accuracy=76.318948 loss=0.933167 lr=0.001000 Epoch[053] Batch [3199]/[3760] Speed: 68.015288 samples/sec accuracy=76.322754 loss=0.933104 lr=0.001000 Epoch[053] Batch [3249]/[3760] Speed: 68.597955 samples/sec accuracy=76.325962 loss=0.933003 lr=0.001000 Epoch[053] Batch [3299]/[3760] Speed: 67.679904 samples/sec accuracy=76.319602 loss=0.933223 lr=0.001000 Epoch[053] Batch [3349]/[3760] Speed: 67.610866 samples/sec accuracy=76.324627 loss=0.933186 lr=0.001000 Epoch[053] Batch [3399]/[3760] Speed: 67.895525 samples/sec accuracy=76.315257 loss=0.933051 lr=0.001000 Epoch[053] Batch [3449]/[3760] Speed: 68.531599 samples/sec accuracy=76.309783 loss=0.933134 lr=0.001000 Epoch[053] Batch [3499]/[3760] Speed: 67.735068 samples/sec accuracy=76.312946 loss=0.933232 lr=0.001000 Epoch[053] Batch [3549]/[3760] Speed: 68.199842 samples/sec accuracy=76.317342 loss=0.932738 lr=0.001000 Epoch[053] Batch [3599]/[3760] Speed: 67.668390 samples/sec accuracy=76.323785 loss=0.932797 lr=0.001000 Epoch[053] Batch [3649]/[3760] Speed: 67.980853 samples/sec accuracy=76.341182 loss=0.932365 lr=0.001000 Epoch[053] Batch [3699]/[3760] Speed: 67.496393 samples/sec accuracy=76.342483 loss=0.932163 lr=0.001000 Epoch[053] Batch [3749]/[3760] Speed: 74.250702 samples/sec accuracy=76.342083 loss=0.932811 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.093750 acc-top5=86.281250 Batch [0099]/[0303]: acc-top1=66.890625 acc-top5=86.171875 Batch [0149]/[0303]: acc-top1=66.979167 acc-top5=86.614583 Batch [0199]/[0303]: acc-top1=67.132812 acc-top5=86.703125 Batch [0249]/[0303]: acc-top1=67.156250 acc-top5=86.668750 Batch [0299]/[0303]: acc-top1=67.291667 acc-top5=86.864583 [Epoch 053] training: accuracy=76.336852 loss=0.932751 [Epoch 053] speed: 67 samples/sec time cost: 3847.458127 [Epoch 053] validation: acc-top1=67.300949 acc-top5=86.876031 loss=1.549051 Epoch[054] Batch [0049]/[3760] Speed: 45.685474 samples/sec accuracy=77.531250 loss=0.931458 lr=0.001000 Epoch[054] Batch [0099]/[3760] Speed: 67.499379 samples/sec accuracy=76.656250 loss=0.939437 lr=0.001000 Epoch[054] Batch [0149]/[3760] Speed: 68.326761 samples/sec accuracy=76.739583 loss=0.925626 lr=0.001000 Epoch[054] Batch [0199]/[3760] Speed: 67.177003 samples/sec accuracy=76.828125 loss=0.913555 lr=0.001000 Epoch[054] Batch [0249]/[3760] Speed: 68.445485 samples/sec accuracy=76.837500 loss=0.915358 lr=0.001000 Epoch[054] Batch [0299]/[3760] Speed: 68.061412 samples/sec accuracy=76.744792 loss=0.915716 lr=0.001000 Epoch[054] Batch [0349]/[3760] Speed: 68.072654 samples/sec 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accuracy=76.632212 loss=0.920546 lr=0.001000 Epoch[054] Batch [1349]/[3760] Speed: 67.961554 samples/sec accuracy=76.653935 loss=0.919760 lr=0.001000 Epoch[054] Batch [1399]/[3760] Speed: 67.796145 samples/sec accuracy=76.629464 loss=0.920137 lr=0.001000 Epoch[054] Batch [1449]/[3760] Speed: 67.929015 samples/sec accuracy=76.563578 loss=0.923124 lr=0.001000 Epoch[054] Batch [1499]/[3760] Speed: 67.619200 samples/sec accuracy=76.538542 loss=0.924842 lr=0.001000 Epoch[054] Batch [1549]/[3760] Speed: 68.197207 samples/sec accuracy=76.545363 loss=0.924531 lr=0.001000 Epoch[054] Batch [1599]/[3760] Speed: 67.983133 samples/sec accuracy=76.558594 loss=0.923627 lr=0.001000 Epoch[054] Batch [1649]/[3760] Speed: 67.965035 samples/sec accuracy=76.567235 loss=0.923461 lr=0.001000 Epoch[054] Batch [1699]/[3760] Speed: 67.811274 samples/sec accuracy=76.558824 loss=0.924655 lr=0.001000 Epoch[054] Batch [1749]/[3760] Speed: 67.953271 samples/sec accuracy=76.541071 loss=0.925231 lr=0.001000 Epoch[054] 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accuracy=76.584028 loss=0.925224 lr=0.001000 Epoch[054] Batch [2299]/[3760] Speed: 68.577438 samples/sec accuracy=76.604620 loss=0.924419 lr=0.001000 Epoch[054] Batch [2349]/[3760] Speed: 67.291066 samples/sec accuracy=76.614362 loss=0.924422 lr=0.001000 Epoch[054] Batch [2399]/[3760] Speed: 68.190447 samples/sec accuracy=76.632812 loss=0.924102 lr=0.001000 Epoch[054] Batch [2449]/[3760] Speed: 67.774473 samples/sec accuracy=76.653061 loss=0.923404 lr=0.001000 Epoch[054] Batch [2499]/[3760] Speed: 68.290660 samples/sec accuracy=76.641875 loss=0.923933 lr=0.001000 Epoch[054] Batch [2549]/[3760] Speed: 68.035411 samples/sec accuracy=76.653186 loss=0.923505 lr=0.001000 Epoch[054] Batch [2599]/[3760] Speed: 68.298962 samples/sec accuracy=76.674279 loss=0.922618 lr=0.001000 Epoch[054] Batch [2649]/[3760] Speed: 67.362186 samples/sec accuracy=76.671580 loss=0.922809 lr=0.001000 Epoch[054] Batch [2699]/[3760] Speed: 68.016025 samples/sec accuracy=76.654514 loss=0.922939 lr=0.001000 Epoch[054] 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accuracy=76.640137 loss=0.923450 lr=0.001000 Epoch[054] Batch [3249]/[3760] Speed: 68.253429 samples/sec accuracy=76.624038 loss=0.924107 lr=0.001000 Epoch[054] Batch [3299]/[3760] Speed: 67.723886 samples/sec accuracy=76.629261 loss=0.924330 lr=0.001000 Epoch[054] Batch [3349]/[3760] Speed: 68.283764 samples/sec accuracy=76.628265 loss=0.924829 lr=0.001000 Epoch[054] Batch [3399]/[3760] Speed: 67.523858 samples/sec accuracy=76.624081 loss=0.924989 lr=0.001000 Epoch[054] Batch [3449]/[3760] Speed: 68.033250 samples/sec accuracy=76.631793 loss=0.924657 lr=0.001000 Epoch[054] Batch [3499]/[3760] Speed: 68.336481 samples/sec accuracy=76.623661 loss=0.925348 lr=0.001000 Epoch[054] Batch [3549]/[3760] Speed: 68.674914 samples/sec accuracy=76.628521 loss=0.925487 lr=0.001000 Epoch[054] Batch [3599]/[3760] Speed: 67.345403 samples/sec accuracy=76.631944 loss=0.925536 lr=0.001000 Epoch[054] Batch [3649]/[3760] Speed: 67.489615 samples/sec accuracy=76.635702 loss=0.925752 lr=0.001000 Epoch[054] 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67.763021 samples/sec accuracy=76.651042 loss=0.922309 lr=0.001000 Epoch[055] Batch [3049]/[3759] Speed: 68.206304 samples/sec accuracy=76.644980 loss=0.922570 lr=0.001000 Epoch[055] Batch [3099]/[3759] Speed: 67.712773 samples/sec accuracy=76.631552 loss=0.923628 lr=0.001000 Epoch[055] Batch [3149]/[3759] Speed: 68.622446 samples/sec accuracy=76.634425 loss=0.923585 lr=0.001000 Epoch[055] Batch [3199]/[3759] Speed: 67.440206 samples/sec accuracy=76.635254 loss=0.923337 lr=0.001000 Epoch[055] Batch [3249]/[3759] Speed: 67.987519 samples/sec accuracy=76.648077 loss=0.923765 lr=0.001000 Epoch[055] Batch [3299]/[3759] Speed: 67.815869 samples/sec accuracy=76.674716 loss=0.922806 lr=0.001000 Epoch[055] Batch [3349]/[3759] Speed: 68.188721 samples/sec accuracy=76.665112 loss=0.922638 lr=0.001000 Epoch[055] Batch [3399]/[3759] Speed: 67.888480 samples/sec accuracy=76.673254 loss=0.922245 lr=0.001000 Epoch[055] Batch [3449]/[3759] Speed: 68.253379 samples/sec accuracy=76.674366 loss=0.922376 lr=0.001000 Epoch[055] Batch [3499]/[3759] Speed: 68.022391 samples/sec accuracy=76.692411 loss=0.921951 lr=0.001000 Epoch[055] Batch [3549]/[3759] Speed: 67.802397 samples/sec accuracy=76.698944 loss=0.921765 lr=0.001000 Epoch[055] Batch [3599]/[3759] Speed: 67.413572 samples/sec accuracy=76.703993 loss=0.922129 lr=0.001000 Epoch[055] Batch [3649]/[3759] Speed: 68.065502 samples/sec accuracy=76.708476 loss=0.921954 lr=0.001000 Epoch[055] Batch [3699]/[3759] Speed: 68.077441 samples/sec accuracy=76.702703 loss=0.921980 lr=0.001000 Epoch[055] Batch [3749]/[3759] Speed: 75.365281 samples/sec accuracy=76.709583 loss=0.921742 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.906250 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.593750 acc-top5=85.968750 Batch [0149]/[0303]: acc-top1=66.833333 acc-top5=86.562500 Batch [0199]/[0303]: acc-top1=67.031250 acc-top5=86.640625 Batch [0249]/[0303]: acc-top1=67.200000 acc-top5=86.681250 Batch [0299]/[0303]: acc-top1=67.317708 acc-top5=86.802083 [Epoch 055] training: accuracy=76.709647 loss=0.921799 [Epoch 055] speed: 67 samples/sec time cost: 3843.741717 [Epoch 055] validation: acc-top1=67.311262 acc-top5=86.819307 loss=1.572116 Epoch[056] Batch [0049]/[3760] Speed: 45.235150 samples/sec accuracy=76.812500 loss=0.913787 lr=0.001000 Epoch[056] Batch [0099]/[3760] Speed: 67.139660 samples/sec accuracy=77.515625 loss=0.880795 lr=0.001000 Epoch[056] Batch [0149]/[3760] Speed: 68.163825 samples/sec accuracy=77.968750 loss=0.867905 lr=0.001000 Epoch[056] Batch [0199]/[3760] Speed: 67.955365 samples/sec accuracy=77.671875 loss=0.885945 lr=0.001000 Epoch[056] Batch [0249]/[3760] Speed: 67.989326 samples/sec accuracy=77.456250 loss=0.892268 lr=0.001000 Epoch[056] Batch [0299]/[3760] Speed: 68.750098 samples/sec accuracy=77.395833 loss=0.889761 lr=0.001000 Epoch[056] Batch [0349]/[3760] Speed: 67.854463 samples/sec accuracy=77.245536 loss=0.892562 lr=0.001000 Epoch[056] Batch [0399]/[3760] Speed: 68.063997 samples/sec accuracy=77.304688 loss=0.893824 lr=0.001000 Epoch[056] Batch [0449]/[3760] Speed: 68.182601 samples/sec accuracy=77.246528 loss=0.896470 lr=0.001000 Epoch[056] Batch [0499]/[3760] Speed: 68.368374 samples/sec accuracy=77.221875 loss=0.900292 lr=0.001000 Epoch[056] Batch [0549]/[3760] Speed: 67.591811 samples/sec accuracy=77.215909 loss=0.900852 lr=0.001000 Epoch[056] Batch [0599]/[3760] Speed: 67.455886 samples/sec accuracy=77.190104 loss=0.901395 lr=0.001000 Epoch[056] Batch [0649]/[3760] Speed: 68.248580 samples/sec accuracy=77.233173 loss=0.899975 lr=0.001000 Epoch[056] Batch [0699]/[3760] Speed: 67.680838 samples/sec accuracy=77.205357 loss=0.902973 lr=0.001000 Epoch[056] Batch [0749]/[3760] Speed: 67.659966 samples/sec accuracy=77.175000 loss=0.902680 lr=0.001000 Epoch[056] Batch [0799]/[3760] Speed: 67.891466 samples/sec accuracy=77.158203 loss=0.903540 lr=0.001000 Epoch[056] Batch [0849]/[3760] Speed: 68.155514 samples/sec accuracy=77.139706 loss=0.903226 lr=0.001000 Epoch[056] 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accuracy=77.133102 loss=0.902064 lr=0.001000 Epoch[056] Batch [1399]/[3760] Speed: 67.271784 samples/sec accuracy=77.108259 loss=0.903206 lr=0.001000 Epoch[056] Batch [1449]/[3760] Speed: 68.430664 samples/sec accuracy=77.115302 loss=0.902307 lr=0.001000 Epoch[056] Batch [1499]/[3760] Speed: 68.044484 samples/sec accuracy=77.122917 loss=0.900763 lr=0.001000 Epoch[056] Batch [1549]/[3760] Speed: 67.454267 samples/sec accuracy=77.143145 loss=0.900176 lr=0.001000 Epoch[056] Batch [1599]/[3760] Speed: 67.321183 samples/sec accuracy=77.099609 loss=0.901801 lr=0.001000 Epoch[056] Batch [1649]/[3760] Speed: 67.701905 samples/sec accuracy=77.108902 loss=0.901661 lr=0.001000 Epoch[056] Batch [1699]/[3760] Speed: 68.365387 samples/sec accuracy=77.080882 loss=0.902694 lr=0.001000 Epoch[056] Batch [1749]/[3760] Speed: 68.215544 samples/sec accuracy=77.060714 loss=0.903085 lr=0.001000 Epoch[056] Batch [1799]/[3760] Speed: 67.923682 samples/sec accuracy=77.054688 loss=0.903130 lr=0.001000 Epoch[056] Batch [1849]/[3760] Speed: 67.873108 samples/sec accuracy=77.053209 loss=0.903079 lr=0.001000 Epoch[056] Batch [1899]/[3760] Speed: 68.565056 samples/sec accuracy=77.056743 loss=0.902772 lr=0.001000 Epoch[056] Batch [1949]/[3760] Speed: 68.201881 samples/sec accuracy=77.064103 loss=0.902735 lr=0.001000 Epoch[056] Batch [1999]/[3760] Speed: 68.003206 samples/sec accuracy=77.028125 loss=0.904753 lr=0.001000 Epoch[056] Batch [2049]/[3760] Speed: 68.029159 samples/sec accuracy=77.035823 loss=0.904436 lr=0.001000 Epoch[056] Batch [2099]/[3760] Speed: 68.064975 samples/sec accuracy=76.999256 loss=0.905822 lr=0.001000 Epoch[056] Batch [2149]/[3760] Speed: 68.430092 samples/sec accuracy=76.982558 loss=0.906403 lr=0.001000 Epoch[056] Batch [2199]/[3760] Speed: 68.048491 samples/sec accuracy=76.973011 loss=0.906753 lr=0.001000 Epoch[056] Batch [2249]/[3760] Speed: 68.637831 samples/sec accuracy=76.969444 loss=0.907091 lr=0.001000 Epoch[056] Batch [2299]/[3760] Speed: 68.070137 samples/sec accuracy=76.967391 loss=0.907289 lr=0.001000 Epoch[056] Batch [2349]/[3760] Speed: 68.101666 samples/sec accuracy=76.917553 loss=0.909016 lr=0.001000 Epoch[056] Batch [2399]/[3760] Speed: 67.491372 samples/sec accuracy=76.921224 loss=0.909328 lr=0.001000 Epoch[056] Batch [2449]/[3760] Speed: 68.452903 samples/sec accuracy=76.920281 loss=0.909114 lr=0.001000 Epoch[056] Batch [2499]/[3760] Speed: 67.624442 samples/sec accuracy=76.909375 loss=0.909666 lr=0.001000 Epoch[056] Batch [2549]/[3760] Speed: 67.655249 samples/sec accuracy=76.930760 loss=0.909130 lr=0.001000 Epoch[056] Batch [2599]/[3760] Speed: 68.191746 samples/sec accuracy=76.934495 loss=0.908541 lr=0.001000 Epoch[056] Batch [2649]/[3760] Speed: 68.378263 samples/sec accuracy=76.930425 loss=0.909416 lr=0.001000 Epoch[056] Batch [2699]/[3760] Speed: 67.764994 samples/sec accuracy=76.912037 loss=0.909378 lr=0.001000 Epoch[056] Batch [2749]/[3760] Speed: 67.965739 samples/sec accuracy=76.928977 loss=0.909078 lr=0.001000 Epoch[056] Batch [2799]/[3760] Speed: 67.472431 samples/sec accuracy=76.926897 loss=0.909370 lr=0.001000 Epoch[056] Batch [2849]/[3760] Speed: 68.665006 samples/sec accuracy=76.930921 loss=0.909347 lr=0.001000 Epoch[056] Batch [2899]/[3760] Speed: 67.605395 samples/sec accuracy=76.935884 loss=0.909289 lr=0.001000 Epoch[056] Batch [2949]/[3760] Speed: 67.577827 samples/sec accuracy=76.949153 loss=0.908735 lr=0.001000 Epoch[056] Batch [2999]/[3760] Speed: 68.649689 samples/sec accuracy=76.944271 loss=0.909322 lr=0.001000 Epoch[056] Batch [3049]/[3760] Speed: 68.305578 samples/sec accuracy=76.940574 loss=0.909719 lr=0.001000 Epoch[056] Batch [3099]/[3760] Speed: 67.142025 samples/sec accuracy=76.947581 loss=0.909002 lr=0.001000 Epoch[056] Batch [3149]/[3760] Speed: 68.552680 samples/sec accuracy=76.932540 loss=0.909601 lr=0.001000 Epoch[056] Batch [3199]/[3760] Speed: 67.889770 samples/sec accuracy=76.937988 loss=0.909205 lr=0.001000 Epoch[056] Batch [3249]/[3760] Speed: 68.163115 samples/sec accuracy=76.907692 loss=0.909712 lr=0.001000 Epoch[056] Batch [3299]/[3760] Speed: 67.905889 samples/sec accuracy=76.926136 loss=0.909452 lr=0.001000 Epoch[056] Batch [3349]/[3760] Speed: 67.993330 samples/sec accuracy=76.916511 loss=0.910077 lr=0.001000 Epoch[056] Batch [3399]/[3760] Speed: 68.328971 samples/sec accuracy=76.908088 loss=0.910403 lr=0.001000 Epoch[056] Batch [3449]/[3760] Speed: 67.742318 samples/sec accuracy=76.889946 loss=0.911155 lr=0.001000 Epoch[056] Batch [3499]/[3760] Speed: 68.327742 samples/sec accuracy=76.886161 loss=0.911026 lr=0.001000 Epoch[056] Batch [3549]/[3760] Speed: 67.357197 samples/sec accuracy=76.882923 loss=0.910752 lr=0.001000 Epoch[056] Batch [3599]/[3760] Speed: 68.214000 samples/sec accuracy=76.904080 loss=0.909971 lr=0.001000 Epoch[056] Batch [3649]/[3760] Speed: 68.125809 samples/sec accuracy=76.920805 loss=0.909524 lr=0.001000 Epoch[056] Batch [3699]/[3760] Speed: 68.429979 samples/sec accuracy=76.915963 loss=0.909771 lr=0.001000 Epoch[056] Batch [3749]/[3760] Speed: 74.561066 samples/sec accuracy=76.925833 loss=0.909341 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.562500 acc-top5=86.250000 Batch [0099]/[0303]: acc-top1=66.343750 acc-top5=85.968750 Batch [0149]/[0303]: acc-top1=66.562500 acc-top5=86.489583 Batch [0199]/[0303]: acc-top1=66.960938 acc-top5=86.562500 Batch [0249]/[0303]: acc-top1=67.056250 acc-top5=86.581250 Batch [0299]/[0303]: acc-top1=67.255208 acc-top5=86.770833 [Epoch 056] training: accuracy=76.928607 loss=0.909296 [Epoch 056] speed: 67 samples/sec time cost: 3848.831485 [Epoch 056] validation: acc-top1=67.233911 acc-top5=86.783210 loss=1.562357 Epoch[057] Batch [0049]/[3760] Speed: 45.275957 samples/sec accuracy=78.031250 loss=0.900509 lr=0.001000 Epoch[057] Batch [0099]/[3760] Speed: 66.433978 samples/sec accuracy=77.578125 loss=0.891754 lr=0.001000 Epoch[057] Batch [0149]/[3760] Speed: 68.320508 samples/sec accuracy=77.875000 loss=0.879502 lr=0.001000 Epoch[057] Batch [0199]/[3760] Speed: 67.619186 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lr=0.001000 Epoch[057] Batch [0699]/[3760] Speed: 67.774702 samples/sec accuracy=77.254464 loss=0.894204 lr=0.001000 Epoch[057] Batch [0749]/[3760] Speed: 67.619034 samples/sec accuracy=77.162500 loss=0.898297 lr=0.001000 Epoch[057] Batch [0799]/[3760] Speed: 67.853120 samples/sec accuracy=77.126953 loss=0.900759 lr=0.001000 Epoch[057] Batch [0849]/[3760] Speed: 68.195700 samples/sec accuracy=77.165441 loss=0.900020 lr=0.001000 Epoch[057] Batch [0899]/[3760] Speed: 67.762940 samples/sec accuracy=77.156250 loss=0.898050 lr=0.001000 Epoch[057] Batch [0949]/[3760] Speed: 67.663201 samples/sec accuracy=77.179276 loss=0.897350 lr=0.001000 Epoch[057] Batch [0999]/[3760] Speed: 67.618879 samples/sec accuracy=77.151562 loss=0.897939 lr=0.001000 Epoch[057] Batch [1049]/[3760] Speed: 68.042365 samples/sec accuracy=77.114583 loss=0.898621 lr=0.001000 Epoch[057] Batch [1099]/[3760] Speed: 67.223429 samples/sec accuracy=77.105114 loss=0.900156 lr=0.001000 Epoch[057] Batch [1149]/[3760] Speed: 68.378644 samples/sec accuracy=77.076087 loss=0.901568 lr=0.001000 Epoch[057] Batch [1199]/[3760] Speed: 68.185386 samples/sec accuracy=77.108073 loss=0.899917 lr=0.001000 Epoch[057] Batch [1249]/[3760] Speed: 67.553198 samples/sec accuracy=77.151250 loss=0.899328 lr=0.001000 Epoch[057] Batch [1299]/[3760] Speed: 67.637389 samples/sec accuracy=77.177885 loss=0.899035 lr=0.001000 Epoch[057] Batch [1349]/[3760] Speed: 68.455251 samples/sec accuracy=77.152778 loss=0.899768 lr=0.001000 Epoch[057] Batch [1399]/[3760] Speed: 68.075034 samples/sec accuracy=77.149554 loss=0.900421 lr=0.001000 Epoch[057] Batch [1449]/[3760] Speed: 67.880461 samples/sec accuracy=77.147629 loss=0.899763 lr=0.001000 Epoch[057] Batch [1499]/[3760] Speed: 68.581774 samples/sec accuracy=77.108333 loss=0.900610 lr=0.001000 Epoch[057] Batch [1549]/[3760] Speed: 68.017869 samples/sec accuracy=77.141129 loss=0.899860 lr=0.001000 Epoch[057] Batch [1599]/[3760] Speed: 67.742241 samples/sec accuracy=77.157227 loss=0.899233 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68.328669 samples/sec accuracy=77.132440 loss=0.899084 lr=0.001000 Epoch[057] Batch [2149]/[3760] Speed: 67.311910 samples/sec accuracy=77.135174 loss=0.899466 lr=0.001000 Epoch[057] Batch [2199]/[3760] Speed: 67.644331 samples/sec accuracy=77.124290 loss=0.900353 lr=0.001000 Epoch[057] Batch [2249]/[3760] Speed: 68.248413 samples/sec accuracy=77.111806 loss=0.900237 lr=0.001000 Epoch[057] Batch [2299]/[3760] Speed: 67.656199 samples/sec accuracy=77.093750 loss=0.900535 lr=0.001000 Epoch[057] Batch [2349]/[3760] Speed: 68.046145 samples/sec accuracy=77.116356 loss=0.899960 lr=0.001000 Epoch[057] Batch [2399]/[3760] Speed: 67.531467 samples/sec accuracy=77.097656 loss=0.900254 lr=0.001000 Epoch[057] Batch [2449]/[3760] Speed: 68.223220 samples/sec accuracy=77.112883 loss=0.899937 lr=0.001000 Epoch[057] Batch [2499]/[3760] Speed: 67.503325 samples/sec accuracy=77.104375 loss=0.899781 lr=0.001000 Epoch[057] Batch [2549]/[3760] Speed: 68.010758 samples/sec accuracy=77.090074 loss=0.900483 lr=0.001000 Epoch[057] Batch [2599]/[3760] Speed: 67.714683 samples/sec accuracy=77.058894 loss=0.901204 lr=0.001000 Epoch[057] Batch [2649]/[3760] Speed: 67.597837 samples/sec accuracy=77.054835 loss=0.901344 lr=0.001000 Epoch[057] Batch [2699]/[3760] Speed: 67.873399 samples/sec accuracy=77.056134 loss=0.901535 lr=0.001000 Epoch[057] Batch [2749]/[3760] Speed: 67.810572 samples/sec accuracy=77.036364 loss=0.901720 lr=0.001000 Epoch[057] Batch [2799]/[3760] Speed: 68.177807 samples/sec accuracy=77.022321 loss=0.902034 lr=0.001000 Epoch[057] Batch [2849]/[3760] Speed: 67.947374 samples/sec accuracy=77.014803 loss=0.902922 lr=0.001000 Epoch[057] Batch [2899]/[3760] Speed: 68.032812 samples/sec accuracy=77.009159 loss=0.903971 lr=0.001000 Epoch[057] Batch [2949]/[3760] Speed: 67.500029 samples/sec accuracy=77.001059 loss=0.904014 lr=0.001000 Epoch[057] Batch [2999]/[3760] Speed: 68.358724 samples/sec accuracy=77.006250 loss=0.904185 lr=0.001000 Epoch[057] Batch [3049]/[3760] Speed: 68.071982 samples/sec accuracy=77.007172 loss=0.904519 lr=0.001000 Epoch[057] Batch [3099]/[3760] Speed: 67.669397 samples/sec accuracy=77.016129 loss=0.904193 lr=0.001000 Epoch[057] Batch [3149]/[3760] Speed: 68.267431 samples/sec accuracy=77.019841 loss=0.903857 lr=0.001000 Epoch[057] Batch [3199]/[3760] Speed: 67.901421 samples/sec accuracy=77.038086 loss=0.903543 lr=0.001000 Epoch[057] Batch [3249]/[3760] Speed: 67.550725 samples/sec accuracy=77.042308 loss=0.903094 lr=0.001000 Epoch[057] Batch [3299]/[3760] Speed: 68.402543 samples/sec accuracy=77.042614 loss=0.903308 lr=0.001000 Epoch[057] Batch [3349]/[3760] Speed: 67.908158 samples/sec accuracy=77.026586 loss=0.904278 lr=0.001000 Epoch[057] Batch [3399]/[3760] Speed: 67.631928 samples/sec accuracy=77.032169 loss=0.903823 lr=0.001000 Epoch[057] Batch [3449]/[3760] Speed: 67.824595 samples/sec accuracy=77.026268 loss=0.903889 lr=0.001000 Epoch[057] Batch [3499]/[3760] Speed: 68.238438 samples/sec accuracy=77.017411 loss=0.904095 lr=0.001000 Epoch[057] Batch [3549]/[3760] Speed: 68.065495 samples/sec accuracy=77.009243 loss=0.904305 lr=0.001000 Epoch[057] Batch [3599]/[3760] Speed: 67.449963 samples/sec accuracy=77.016927 loss=0.904524 lr=0.001000 Epoch[057] Batch [3649]/[3760] Speed: 67.949880 samples/sec accuracy=77.008134 loss=0.904602 lr=0.001000 Epoch[057] Batch [3699]/[3760] Speed: 68.372356 samples/sec accuracy=77.000422 loss=0.904669 lr=0.001000 Epoch[057] Batch [3749]/[3760] Speed: 74.893761 samples/sec accuracy=77.010833 loss=0.904326 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.656250 acc-top5=86.187500 Batch [0099]/[0303]: acc-top1=66.750000 acc-top5=85.812500 Batch [0149]/[0303]: acc-top1=66.916667 acc-top5=86.333333 Batch [0199]/[0303]: acc-top1=67.210938 acc-top5=86.546875 Batch [0249]/[0303]: acc-top1=67.293750 acc-top5=86.518750 Batch [0299]/[0303]: acc-top1=67.296875 acc-top5=86.765625 [Epoch 057] training: accuracy=77.008394 loss=0.904576 [Epoch 057] speed: 67 samples/sec time cost: 3841.274710 [Epoch 057] validation: acc-top1=67.300949 acc-top5=86.788366 loss=1.594833 Epoch[058] Batch [0049]/[3759] Speed: 45.477640 samples/sec accuracy=78.062500 loss=0.874188 lr=0.001000 Epoch[058] Batch [0099]/[3759] Speed: 66.274615 samples/sec accuracy=77.687500 loss=0.870122 lr=0.001000 Epoch[058] Batch [0149]/[3759] Speed: 68.448775 samples/sec accuracy=77.458333 loss=0.877851 lr=0.001000 Epoch[058] Batch [0199]/[3759] Speed: 67.532051 samples/sec accuracy=77.523438 loss=0.880282 lr=0.001000 Epoch[058] Batch [0249]/[3759] Speed: 67.780331 samples/sec accuracy=77.543750 loss=0.880716 lr=0.001000 Epoch[058] Batch [0299]/[3759] Speed: 68.626250 samples/sec accuracy=77.609375 loss=0.877651 lr=0.001000 Epoch[058] Batch [0349]/[3759] Speed: 67.670856 samples/sec accuracy=77.500000 loss=0.883621 lr=0.001000 Epoch[058] Batch [0399]/[3759] Speed: 68.385587 samples/sec accuracy=77.355469 loss=0.886531 lr=0.001000 Epoch[058] Batch [0449]/[3759] Speed: 67.711140 samples/sec 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accuracy=77.551339 loss=0.883133 lr=0.001000 Epoch[058] Batch [1449]/[3759] Speed: 68.200464 samples/sec accuracy=77.592672 loss=0.882587 lr=0.001000 Epoch[058] Batch [1499]/[3759] Speed: 67.859251 samples/sec accuracy=77.571875 loss=0.883147 lr=0.001000 Epoch[058] Batch [1549]/[3759] Speed: 68.170423 samples/sec accuracy=77.538306 loss=0.883330 lr=0.001000 Epoch[058] Batch [1599]/[3759] Speed: 68.149033 samples/sec accuracy=77.506836 loss=0.884709 lr=0.001000 Epoch[058] Batch [1649]/[3759] Speed: 68.238965 samples/sec accuracy=77.453598 loss=0.886067 lr=0.001000 Epoch[058] Batch [1699]/[3759] Speed: 68.312037 samples/sec accuracy=77.420037 loss=0.886268 lr=0.001000 Epoch[058] Batch [1749]/[3759] Speed: 67.885732 samples/sec accuracy=77.413393 loss=0.886975 lr=0.001000 Epoch[058] Batch [1799]/[3759] Speed: 68.627102 samples/sec accuracy=77.441840 loss=0.886057 lr=0.001000 Epoch[058] Batch [1849]/[3759] Speed: 68.123857 samples/sec accuracy=77.412162 loss=0.886873 lr=0.001000 Epoch[058] 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accuracy=77.404920 loss=0.887726 lr=0.001000 Epoch[058] Batch [2399]/[3759] Speed: 68.076547 samples/sec accuracy=77.421224 loss=0.887663 lr=0.001000 Epoch[058] Batch [2449]/[3759] Speed: 67.503741 samples/sec accuracy=77.403699 loss=0.888196 lr=0.001000 Epoch[058] Batch [2499]/[3759] Speed: 67.799140 samples/sec accuracy=77.378125 loss=0.889340 lr=0.001000 Epoch[058] Batch [2549]/[3759] Speed: 68.349880 samples/sec accuracy=77.373775 loss=0.889402 lr=0.001000 Epoch[058] Batch [2599]/[3759] Speed: 67.636833 samples/sec accuracy=77.382212 loss=0.888633 lr=0.001000 Epoch[058] Batch [2649]/[3759] Speed: 69.044305 samples/sec accuracy=77.355542 loss=0.889859 lr=0.001000 Epoch[058] Batch [2699]/[3759] Speed: 67.829479 samples/sec accuracy=77.388310 loss=0.888564 lr=0.001000 Epoch[058] Batch [2749]/[3759] Speed: 67.483053 samples/sec accuracy=77.373295 loss=0.889182 lr=0.001000 Epoch[058] Batch [2799]/[3759] Speed: 68.165489 samples/sec accuracy=77.370536 loss=0.888723 lr=0.001000 Epoch[058] 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accuracy=77.284091 loss=0.891656 lr=0.001000 Epoch[058] Batch [3349]/[3759] Speed: 68.095761 samples/sec accuracy=77.276119 loss=0.891750 lr=0.001000 Epoch[058] Batch [3399]/[3759] Speed: 67.629347 samples/sec accuracy=77.277114 loss=0.891695 lr=0.001000 Epoch[058] Batch [3449]/[3759] Speed: 67.640187 samples/sec accuracy=77.280797 loss=0.891753 lr=0.001000 Epoch[058] Batch [3499]/[3759] Speed: 68.029468 samples/sec accuracy=77.280804 loss=0.891817 lr=0.001000 Epoch[058] Batch [3549]/[3759] Speed: 68.428294 samples/sec accuracy=77.283011 loss=0.891783 lr=0.001000 Epoch[058] Batch [3599]/[3759] Speed: 67.589082 samples/sec accuracy=77.286458 loss=0.891577 lr=0.001000 Epoch[058] Batch [3649]/[3759] Speed: 68.137222 samples/sec accuracy=77.292380 loss=0.891295 lr=0.001000 Epoch[058] Batch [3699]/[3759] Speed: 67.791889 samples/sec accuracy=77.288429 loss=0.891407 lr=0.001000 Epoch[058] Batch [3749]/[3759] Speed: 74.682116 samples/sec accuracy=77.300417 loss=0.891107 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.468750 acc-top5=86.656250 Batch [0099]/[0303]: acc-top1=67.046875 acc-top5=86.390625 Batch [0149]/[0303]: acc-top1=67.260417 acc-top5=86.750000 Batch [0199]/[0303]: acc-top1=67.562500 acc-top5=86.882812 Batch [0249]/[0303]: acc-top1=67.381250 acc-top5=86.837500 Batch [0299]/[0303]: acc-top1=67.447917 acc-top5=86.984375 [Epoch 058] training: accuracy=77.294909 loss=0.891323 [Epoch 058] speed: 67 samples/sec time cost: 3833.944037 [Epoch 058] validation: acc-top1=67.445338 acc-top5=86.994637 loss=1.562988 Epoch[059] Batch [0049]/[3760] Speed: 45.094289 samples/sec accuracy=76.312500 loss=0.904626 lr=0.001000 Epoch[059] Batch [0099]/[3760] Speed: 66.476964 samples/sec accuracy=76.968750 loss=0.897532 lr=0.001000 Epoch[059] Batch [0149]/[3760] Speed: 67.374240 samples/sec accuracy=76.947917 loss=0.906548 lr=0.001000 Epoch[059] Batch [0199]/[3760] Speed: 67.803778 samples/sec accuracy=76.960938 loss=0.908452 lr=0.001000 Epoch[059] Batch [0249]/[3760] Speed: 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lr=0.001000 Epoch[059] Batch [2649]/[3760] Speed: 67.799394 samples/sec accuracy=77.625000 loss=0.880742 lr=0.001000 Epoch[059] Batch [2699]/[3760] Speed: 68.287522 samples/sec accuracy=77.629630 loss=0.880737 lr=0.001000 Epoch[059] Batch [2749]/[3760] Speed: 68.118348 samples/sec accuracy=77.641477 loss=0.880552 lr=0.001000 Epoch[059] Batch [2799]/[3760] Speed: 67.921665 samples/sec accuracy=77.636161 loss=0.881056 lr=0.001000 Epoch[059] Batch [2849]/[3760] Speed: 67.924148 samples/sec accuracy=77.614583 loss=0.881948 lr=0.001000 Epoch[059] Batch [2899]/[3760] Speed: 68.223471 samples/sec accuracy=77.612069 loss=0.882635 lr=0.001000 Epoch[059] Batch [2949]/[3760] Speed: 67.972417 samples/sec accuracy=77.594280 loss=0.883083 lr=0.001000 Epoch[059] Batch [2999]/[3760] Speed: 67.389854 samples/sec accuracy=77.595833 loss=0.883116 lr=0.001000 Epoch[059] Batch [3049]/[3760] Speed: 68.313489 samples/sec accuracy=77.587602 loss=0.883478 lr=0.001000 Epoch[059] Batch [3099]/[3760] Speed: 68.058252 samples/sec accuracy=77.584677 loss=0.883587 lr=0.001000 Epoch[059] Batch [3149]/[3760] Speed: 67.844177 samples/sec accuracy=77.594246 loss=0.883400 lr=0.001000 Epoch[059] Batch [3199]/[3760] Speed: 68.507041 samples/sec accuracy=77.603516 loss=0.883374 lr=0.001000 Epoch[059] Batch [3249]/[3760] Speed: 68.179947 samples/sec accuracy=77.591346 loss=0.883396 lr=0.001000 Epoch[059] Batch [3299]/[3760] Speed: 68.088057 samples/sec accuracy=77.565341 loss=0.883783 lr=0.001000 Epoch[059] Batch [3349]/[3760] Speed: 67.851811 samples/sec accuracy=77.554571 loss=0.884793 lr=0.001000 Epoch[059] Batch [3399]/[3760] Speed: 67.391489 samples/sec accuracy=77.547335 loss=0.885427 lr=0.001000 Epoch[059] Batch [3449]/[3760] Speed: 67.649460 samples/sec accuracy=77.532156 loss=0.886065 lr=0.001000 Epoch[059] Batch [3499]/[3760] Speed: 68.975856 samples/sec accuracy=77.532589 loss=0.886254 lr=0.001000 Epoch[059] Batch [3549]/[3760] Speed: 68.017697 samples/sec accuracy=77.511004 loss=0.887428 lr=0.001000 Epoch[059] Batch [3599]/[3760] Speed: 68.409428 samples/sec accuracy=77.504774 loss=0.887021 lr=0.001000 Epoch[059] Batch [3649]/[3760] Speed: 67.489775 samples/sec accuracy=77.505993 loss=0.887558 lr=0.001000 Epoch[059] Batch [3699]/[3760] Speed: 67.773407 samples/sec accuracy=77.511402 loss=0.887139 lr=0.001000 Epoch[059] Batch [3749]/[3760] Speed: 74.332533 samples/sec accuracy=77.520000 loss=0.886765 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.718750 acc-top5=86.406250 Batch [0099]/[0303]: acc-top1=67.281250 acc-top5=86.328125 Batch [0149]/[0303]: acc-top1=67.166667 acc-top5=86.645833 Batch [0199]/[0303]: acc-top1=67.281250 acc-top5=86.726562 Batch [0249]/[0303]: acc-top1=67.181250 acc-top5=86.825000 Batch [0299]/[0303]: acc-top1=67.302083 acc-top5=86.994792 [Epoch 059] training: accuracy=77.518700 loss=0.886930 [Epoch 059] speed: 67 samples/sec time cost: 3839.121555 [Epoch 059] validation: acc-top1=67.290635 acc-top5=87.025578 loss=1.574903 Epoch[060] Batch 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accuracy=77.896875 loss=0.870550 lr=0.001000 Epoch[060] Batch [0549]/[3760] Speed: 67.691121 samples/sec accuracy=77.923295 loss=0.869755 lr=0.001000 Epoch[060] Batch [0599]/[3760] Speed: 68.411352 samples/sec accuracy=77.966146 loss=0.867156 lr=0.001000 Epoch[060] Batch [0649]/[3760] Speed: 67.659489 samples/sec accuracy=77.896635 loss=0.869440 lr=0.001000 Epoch[060] Batch [0699]/[3760] Speed: 67.894556 samples/sec accuracy=77.953125 loss=0.866524 lr=0.001000 Epoch[060] Batch [0749]/[3760] Speed: 67.695579 samples/sec accuracy=77.970833 loss=0.865414 lr=0.001000 Epoch[060] Batch [0799]/[3760] Speed: 68.369908 samples/sec accuracy=77.892578 loss=0.866968 lr=0.001000 Epoch[060] Batch [0849]/[3760] Speed: 67.859122 samples/sec accuracy=77.849265 loss=0.867833 lr=0.001000 Epoch[060] Batch [0899]/[3760] Speed: 67.307314 samples/sec accuracy=77.803819 loss=0.868267 lr=0.001000 Epoch[060] Batch [0949]/[3760] Speed: 68.017346 samples/sec accuracy=77.791118 loss=0.868524 lr=0.001000 Epoch[060] 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accuracy=77.728448 loss=0.870171 lr=0.001000 Epoch[060] Batch [1499]/[3760] Speed: 67.170579 samples/sec accuracy=77.731250 loss=0.871090 lr=0.001000 Epoch[060] Batch [1549]/[3760] Speed: 68.396677 samples/sec accuracy=77.730847 loss=0.870375 lr=0.001000 Epoch[060] Batch [1599]/[3760] Speed: 67.615094 samples/sec accuracy=77.711914 loss=0.870081 lr=0.001000 Epoch[060] Batch [1649]/[3760] Speed: 68.432403 samples/sec accuracy=77.704545 loss=0.870121 lr=0.001000 Epoch[060] Batch [1699]/[3760] Speed: 68.103243 samples/sec accuracy=77.661765 loss=0.871254 lr=0.001000 Epoch[060] Batch [1749]/[3760] Speed: 67.636817 samples/sec accuracy=77.663393 loss=0.871628 lr=0.001000 Epoch[060] Batch [1799]/[3760] Speed: 68.469934 samples/sec accuracy=77.645833 loss=0.873347 lr=0.001000 Epoch[060] Batch [1849]/[3760] Speed: 67.224327 samples/sec accuracy=77.610642 loss=0.874660 lr=0.001000 Epoch[060] Batch [1899]/[3760] Speed: 68.191420 samples/sec accuracy=77.610197 loss=0.875088 lr=0.001000 Epoch[060] 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accuracy=77.553385 loss=0.879094 lr=0.001000 Epoch[060] Batch [2449]/[3760] Speed: 67.817562 samples/sec accuracy=77.524235 loss=0.880173 lr=0.001000 Epoch[060] Batch [2499]/[3760] Speed: 68.141544 samples/sec accuracy=77.520625 loss=0.880009 lr=0.001000 Epoch[060] Batch [2549]/[3760] Speed: 67.623484 samples/sec accuracy=77.532475 loss=0.879369 lr=0.001000 Epoch[060] Batch [2599]/[3760] Speed: 67.381536 samples/sec accuracy=77.542668 loss=0.879593 lr=0.001000 Epoch[060] Batch [2649]/[3760] Speed: 68.359673 samples/sec accuracy=77.548349 loss=0.879632 lr=0.001000 Epoch[060] Batch [2699]/[3760] Speed: 67.673538 samples/sec accuracy=77.534722 loss=0.880009 lr=0.001000 Epoch[060] Batch [2749]/[3760] Speed: 68.584387 samples/sec accuracy=77.558523 loss=0.879171 lr=0.001000 Epoch[060] Batch [2799]/[3760] Speed: 68.249491 samples/sec accuracy=77.541853 loss=0.879762 lr=0.001000 Epoch[060] Batch [2849]/[3760] Speed: 67.846513 samples/sec accuracy=77.560855 loss=0.878915 lr=0.001000 Epoch[060] Batch [2899]/[3760] Speed: 68.346217 samples/sec accuracy=77.596444 loss=0.877982 lr=0.001000 Epoch[060] Batch [2949]/[3760] Speed: 67.300643 samples/sec accuracy=77.598517 loss=0.878433 lr=0.001000 Epoch[060] Batch [2999]/[3760] Speed: 67.971771 samples/sec accuracy=77.593229 loss=0.878819 lr=0.001000 Epoch[060] Batch [3049]/[3760] Speed: 67.612797 samples/sec accuracy=77.576332 loss=0.879304 lr=0.001000 Epoch[060] Batch [3099]/[3760] Speed: 67.773716 samples/sec accuracy=77.575605 loss=0.879242 lr=0.001000 Epoch[060] Batch [3149]/[3760] Speed: 68.043288 samples/sec accuracy=77.570437 loss=0.879297 lr=0.001000 Epoch[060] Batch [3199]/[3760] Speed: 67.923065 samples/sec accuracy=77.544922 loss=0.879859 lr=0.001000 Epoch[060] Batch [3249]/[3760] Speed: 67.801780 samples/sec accuracy=77.539423 loss=0.880135 lr=0.001000 Epoch[060] Batch [3299]/[3760] Speed: 68.628820 samples/sec accuracy=77.534564 loss=0.880008 lr=0.001000 Epoch[060] Batch [3349]/[3760] Speed: 67.488852 samples/sec accuracy=77.537313 loss=0.880087 lr=0.001000 Epoch[060] Batch [3399]/[3760] Speed: 68.005736 samples/sec accuracy=77.531250 loss=0.880320 lr=0.001000 Epoch[060] Batch [3449]/[3760] Speed: 67.795364 samples/sec accuracy=77.523551 loss=0.880633 lr=0.001000 Epoch[060] Batch [3499]/[3760] Speed: 68.305160 samples/sec accuracy=77.508036 loss=0.881503 lr=0.001000 Epoch[060] Batch [3549]/[3760] Speed: 68.221828 samples/sec accuracy=77.507042 loss=0.881412 lr=0.001000 Epoch[060] Batch [3599]/[3760] Speed: 67.659574 samples/sec accuracy=77.482205 loss=0.882036 lr=0.001000 Epoch[060] Batch [3649]/[3760] Speed: 68.212640 samples/sec accuracy=77.478168 loss=0.882285 lr=0.001000 Epoch[060] Batch [3699]/[3760] Speed: 68.241140 samples/sec accuracy=77.468328 loss=0.882927 lr=0.001000 Epoch[060] Batch [3749]/[3760] Speed: 74.267563 samples/sec accuracy=77.465417 loss=0.882989 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.812500 acc-top5=85.906250 Batch [0099]/[0303]: acc-top1=66.843750 acc-top5=85.750000 Batch [0149]/[0303]: acc-top1=67.052083 acc-top5=86.416667 Batch [0199]/[0303]: acc-top1=67.281250 acc-top5=86.523438 Batch [0249]/[0303]: acc-top1=67.268750 acc-top5=86.525000 Batch [0299]/[0303]: acc-top1=67.401042 acc-top5=86.822917 [Epoch 060] training: accuracy=77.475066 loss=0.882617 [Epoch 060] speed: 67 samples/sec time cost: 3838.564431 [Epoch 060] validation: acc-top1=67.383457 acc-top5=86.834777 loss=1.576420 Epoch[061] Batch [0049]/[3759] Speed: 45.619774 samples/sec accuracy=79.281250 loss=0.818397 lr=0.001000 Epoch[061] Batch [0099]/[3759] Speed: 66.663243 samples/sec accuracy=78.734375 loss=0.836434 lr=0.001000 Epoch[061] Batch [0149]/[3759] Speed: 68.156096 samples/sec accuracy=78.468750 loss=0.844250 lr=0.001000 Epoch[061] Batch [0199]/[3759] Speed: 67.838099 samples/sec accuracy=78.328125 loss=0.847108 lr=0.001000 Epoch[061] Batch [0249]/[3759] Speed: 68.243314 samples/sec accuracy=78.200000 loss=0.851722 lr=0.001000 Epoch[061] Batch [0299]/[3759] 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accuracy=77.770833 loss=0.874739 lr=0.001000 Epoch[061] Batch [3649]/[3759] Speed: 67.838613 samples/sec accuracy=77.775257 loss=0.874777 lr=0.001000 Epoch[061] Batch [3699]/[3759] Speed: 68.283903 samples/sec accuracy=77.774493 loss=0.874843 lr=0.001000 Epoch[061] Batch [3749]/[3759] Speed: 74.830043 samples/sec accuracy=77.779583 loss=0.874913 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.687500 acc-top5=86.218750 Batch [0099]/[0303]: acc-top1=66.453125 acc-top5=85.750000 Batch [0149]/[0303]: acc-top1=66.760417 acc-top5=86.270833 Batch [0199]/[0303]: acc-top1=67.054688 acc-top5=86.468750 Batch [0249]/[0303]: acc-top1=67.093750 acc-top5=86.400000 Batch [0299]/[0303]: acc-top1=67.088542 acc-top5=86.588542 [Epoch 061] training: accuracy=77.774175 loss=0.875092 [Epoch 061] speed: 67 samples/sec time cost: 3838.645219 [Epoch 061] validation: acc-top1=67.094678 acc-top5=86.602723 loss=1.591088 Epoch[062] Batch [0049]/[3760] Speed: 46.094784 samples/sec accuracy=78.593750 loss=0.873536 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lr=0.001000 Epoch[062] Batch [2949]/[3760] Speed: 67.872542 samples/sec accuracy=77.883475 loss=0.870530 lr=0.001000 Epoch[062] Batch [2999]/[3760] Speed: 67.956494 samples/sec accuracy=77.868750 loss=0.870904 lr=0.001000 Epoch[062] Batch [3049]/[3760] Speed: 67.627949 samples/sec accuracy=77.885246 loss=0.870146 lr=0.001000 Epoch[062] Batch [3099]/[3760] Speed: 68.330830 samples/sec accuracy=77.885585 loss=0.869902 lr=0.001000 Epoch[062] Batch [3149]/[3760] Speed: 67.540861 samples/sec accuracy=77.904266 loss=0.869630 lr=0.001000 Epoch[062] Batch [3199]/[3760] Speed: 68.154534 samples/sec accuracy=77.918945 loss=0.868779 lr=0.001000 Epoch[062] Batch [3249]/[3760] Speed: 67.844389 samples/sec accuracy=77.916827 loss=0.868956 lr=0.001000 Epoch[062] Batch [3299]/[3760] Speed: 67.300804 samples/sec accuracy=77.912879 loss=0.868902 lr=0.001000 Epoch[062] Batch [3349]/[3760] Speed: 68.156815 samples/sec accuracy=77.908116 loss=0.868931 lr=0.001000 Epoch[062] Batch [3399]/[3760] Speed: 67.962707 samples/sec accuracy=77.897518 loss=0.869257 lr=0.001000 Epoch[062] Batch [3449]/[3760] Speed: 67.790482 samples/sec accuracy=77.897645 loss=0.869254 lr=0.001000 Epoch[062] Batch [3499]/[3760] Speed: 68.035862 samples/sec accuracy=77.892857 loss=0.869414 lr=0.001000 Epoch[062] Batch [3549]/[3760] Speed: 67.263890 samples/sec accuracy=77.878961 loss=0.869855 lr=0.001000 Epoch[062] Batch [3599]/[3760] Speed: 67.724578 samples/sec accuracy=77.856771 loss=0.870647 lr=0.001000 Epoch[062] Batch [3649]/[3760] Speed: 67.854332 samples/sec accuracy=77.858305 loss=0.870668 lr=0.001000 Epoch[062] Batch [3699]/[3760] Speed: 68.418225 samples/sec accuracy=77.859797 loss=0.870536 lr=0.001000 Epoch[062] Batch [3749]/[3760] Speed: 73.975312 samples/sec accuracy=77.869167 loss=0.870234 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.343750 acc-top5=86.625000 Batch [0099]/[0303]: acc-top1=66.406250 acc-top5=85.984375 Batch [0149]/[0303]: acc-top1=66.520833 acc-top5=86.302083 Batch [0199]/[0303]: acc-top1=66.750000 acc-top5=86.414062 Batch [0249]/[0303]: acc-top1=66.781250 acc-top5=86.518750 Batch [0299]/[0303]: acc-top1=66.859375 acc-top5=86.645833 [Epoch 062] training: accuracy=77.874834 loss=0.870167 [Epoch 062] speed: 67 samples/sec time cost: 3840.343941 [Epoch 062] validation: acc-top1=66.831683 acc-top5=86.659447 loss=1.602638 Epoch[063] Batch [0049]/[3760] Speed: 45.945437 samples/sec accuracy=76.906250 loss=0.879528 lr=0.001000 Epoch[063] Batch [0099]/[3760] Speed: 66.689476 samples/sec accuracy=77.750000 loss=0.863032 lr=0.001000 Epoch[063] Batch [0149]/[3760] Speed: 68.204729 samples/sec accuracy=77.822917 loss=0.859235 lr=0.001000 Epoch[063] Batch [0199]/[3760] Speed: 67.032345 samples/sec accuracy=77.890625 loss=0.856648 lr=0.001000 Epoch[063] Batch [0249]/[3760] Speed: 68.139660 samples/sec accuracy=77.925000 loss=0.860152 lr=0.001000 Epoch[063] Batch [0299]/[3760] Speed: 68.090392 samples/sec accuracy=77.958333 loss=0.856591 lr=0.001000 Epoch[063] Batch 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accuracy=78.072774 loss=0.860911 lr=0.001000 Epoch[063] Batch [3699]/[3760] Speed: 67.711397 samples/sec accuracy=78.068412 loss=0.860866 lr=0.001000 Epoch[063] Batch [3749]/[3760] Speed: 73.676748 samples/sec accuracy=78.075833 loss=0.860668 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.093750 acc-top5=86.406250 Batch [0099]/[0303]: acc-top1=66.093750 acc-top5=85.828125 Batch [0149]/[0303]: acc-top1=66.406250 acc-top5=86.218750 Batch [0199]/[0303]: acc-top1=66.812500 acc-top5=86.312500 Batch [0249]/[0303]: acc-top1=66.912500 acc-top5=86.337500 Batch [0299]/[0303]: acc-top1=67.062500 acc-top5=86.505208 [Epoch 063] training: accuracy=78.063913 loss=0.860981 [Epoch 063] speed: 67 samples/sec time cost: 3842.488705 [Epoch 063] validation: acc-top1=67.053424 acc-top5=86.535685 loss=1.603468 Epoch[064] Batch [0049]/[3759] Speed: 45.851116 samples/sec accuracy=79.281250 loss=0.815134 lr=0.001000 Epoch[064] Batch [0099]/[3759] Speed: 66.706174 samples/sec accuracy=78.828125 loss=0.819664 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67.880828 samples/sec accuracy=78.338768 loss=0.849437 lr=0.001000 Epoch[064] Batch [3499]/[3759] Speed: 67.730283 samples/sec accuracy=78.331696 loss=0.849786 lr=0.001000 Epoch[064] Batch [3549]/[3759] Speed: 68.421344 samples/sec accuracy=78.318222 loss=0.850488 lr=0.001000 Epoch[064] Batch [3599]/[3759] Speed: 67.829070 samples/sec accuracy=78.287326 loss=0.851044 lr=0.001000 Epoch[064] Batch [3649]/[3759] Speed: 67.918653 samples/sec accuracy=78.273116 loss=0.851501 lr=0.001000 Epoch[064] Batch [3699]/[3759] Speed: 68.143854 samples/sec accuracy=78.286318 loss=0.851038 lr=0.001000 Epoch[064] Batch [3749]/[3759] Speed: 75.086944 samples/sec accuracy=78.261250 loss=0.852040 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.781250 acc-top5=86.125000 Batch [0099]/[0303]: acc-top1=66.062500 acc-top5=85.765625 Batch [0149]/[0303]: acc-top1=66.427083 acc-top5=86.041667 Batch [0199]/[0303]: acc-top1=66.773438 acc-top5=86.187500 Batch [0249]/[0303]: acc-top1=66.750000 acc-top5=86.275000 Batch [0299]/[0303]: acc-top1=66.963542 acc-top5=86.572917 [Epoch 064] training: accuracy=78.258014 loss=0.852198 [Epoch 064] speed: 67 samples/sec time cost: 3841.210926 [Epoch 064] validation: acc-top1=66.965759 acc-top5=86.582096 loss=1.600446 Epoch[065] Batch [0049]/[3760] Speed: 45.048885 samples/sec accuracy=79.531250 loss=0.803414 lr=0.001000 Epoch[065] Batch [0099]/[3760] Speed: 66.554180 samples/sec accuracy=79.296875 loss=0.816557 lr=0.001000 Epoch[065] Batch [0149]/[3760] Speed: 68.220820 samples/sec accuracy=79.229167 loss=0.822453 lr=0.001000 Epoch[065] Batch [0199]/[3760] Speed: 66.735515 samples/sec accuracy=78.984375 loss=0.829366 lr=0.001000 Epoch[065] Batch [0249]/[3760] Speed: 67.376963 samples/sec accuracy=78.956250 loss=0.830943 lr=0.001000 Epoch[065] Batch [0299]/[3760] Speed: 68.164168 samples/sec accuracy=79.046875 loss=0.828094 lr=0.001000 Epoch[065] Batch [0349]/[3760] Speed: 67.574562 samples/sec accuracy=78.741071 loss=0.838524 lr=0.001000 Epoch[065] Batch 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accuracy=78.354730 loss=0.849257 lr=0.001000 Epoch[065] Batch [3749]/[3760] Speed: 74.297182 samples/sec accuracy=78.354583 loss=0.849465 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.281250 acc-top5=85.968750 Batch [0099]/[0303]: acc-top1=66.437500 acc-top5=85.718750 Batch [0149]/[0303]: acc-top1=66.593750 acc-top5=86.229167 Batch [0199]/[0303]: acc-top1=66.851562 acc-top5=86.335938 Batch [0249]/[0303]: acc-top1=66.931250 acc-top5=86.287500 Batch [0299]/[0303]: acc-top1=67.010417 acc-top5=86.510417 [Epoch 065] training: accuracy=78.348986 loss=0.849608 [Epoch 065] speed: 67 samples/sec time cost: 3844.110496 [Epoch 065] validation: acc-top1=67.022483 acc-top5=86.535685 loss=1.619888 Epoch[066] Batch [0049]/[3759] Speed: 45.925609 samples/sec accuracy=78.625000 loss=0.836568 lr=0.001000 Epoch[066] Batch [0099]/[3759] Speed: 67.196173 samples/sec accuracy=79.250000 loss=0.809745 lr=0.001000 Epoch[066] Batch [0149]/[3759] Speed: 68.577779 samples/sec accuracy=79.447917 loss=0.804811 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lr=0.001000 Epoch[066] Batch [3049]/[3759] Speed: 67.510514 samples/sec accuracy=78.575307 loss=0.843349 lr=0.001000 Epoch[066] Batch [3099]/[3759] Speed: 67.335873 samples/sec accuracy=78.563508 loss=0.843993 lr=0.001000 Epoch[066] Batch [3149]/[3759] Speed: 67.423792 samples/sec accuracy=78.563492 loss=0.844061 lr=0.001000 Epoch[066] Batch [3199]/[3759] Speed: 69.044565 samples/sec accuracy=78.555176 loss=0.843820 lr=0.001000 Epoch[066] Batch [3249]/[3759] Speed: 67.755330 samples/sec accuracy=78.543750 loss=0.844543 lr=0.001000 Epoch[066] Batch [3299]/[3759] Speed: 68.017760 samples/sec accuracy=78.550189 loss=0.844513 lr=0.001000 Epoch[066] Batch [3349]/[3759] Speed: 68.192745 samples/sec accuracy=78.542444 loss=0.844520 lr=0.001000 Epoch[066] Batch [3399]/[3759] Speed: 68.113869 samples/sec accuracy=78.535846 loss=0.844729 lr=0.001000 Epoch[066] Batch [3449]/[3759] Speed: 67.477575 samples/sec accuracy=78.548913 loss=0.843878 lr=0.001000 Epoch[066] Batch [3499]/[3759] Speed: 68.493770 samples/sec accuracy=78.535268 loss=0.844654 lr=0.001000 Epoch[066] Batch [3549]/[3759] Speed: 66.935434 samples/sec accuracy=78.521567 loss=0.845142 lr=0.001000 Epoch[066] Batch [3599]/[3759] Speed: 68.515225 samples/sec accuracy=78.504774 loss=0.845835 lr=0.001000 Epoch[066] Batch [3649]/[3759] Speed: 67.761920 samples/sec accuracy=78.511558 loss=0.845370 lr=0.001000 Epoch[066] Batch [3699]/[3759] Speed: 68.245886 samples/sec accuracy=78.513936 loss=0.845100 lr=0.001000 Epoch[066] Batch [3749]/[3759] Speed: 74.658478 samples/sec accuracy=78.532917 loss=0.844362 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.187500 acc-top5=86.125000 Batch [0099]/[0303]: acc-top1=66.062500 acc-top5=86.015625 Batch [0149]/[0303]: acc-top1=66.375000 acc-top5=86.437500 Batch [0199]/[0303]: acc-top1=66.585938 acc-top5=86.515625 Batch [0249]/[0303]: acc-top1=66.656250 acc-top5=86.487500 Batch [0299]/[0303]: acc-top1=66.822917 acc-top5=86.687500 [Epoch 066] training: accuracy=78.541085 loss=0.844283 [Epoch 066] speed: 67 samples/sec time cost: 3837.920581 [Epoch 066] validation: acc-top1=66.862624 acc-top5=86.705858 loss=1.632833 Epoch[067] Batch [0049]/[3760] Speed: 45.510835 samples/sec accuracy=79.156250 loss=0.824770 lr=0.001000 Epoch[067] Batch [0099]/[3760] Speed: 66.924375 samples/sec accuracy=78.796875 loss=0.826575 lr=0.001000 Epoch[067] Batch [0149]/[3760] Speed: 68.276718 samples/sec accuracy=78.791667 loss=0.828638 lr=0.001000 Epoch[067] Batch [0199]/[3760] Speed: 67.053351 samples/sec accuracy=78.960938 loss=0.822721 lr=0.001000 Epoch[067] Batch [0249]/[3760] Speed: 67.973440 samples/sec accuracy=79.025000 loss=0.823946 lr=0.001000 Epoch[067] Batch [0299]/[3760] Speed: 68.159684 samples/sec accuracy=79.031250 loss=0.823859 lr=0.001000 Epoch[067] Batch [0349]/[3760] Speed: 67.909426 samples/sec accuracy=78.892857 loss=0.832937 lr=0.001000 Epoch[067] Batch [0399]/[3760] Speed: 67.966555 samples/sec accuracy=78.871094 loss=0.831918 lr=0.001000 Epoch[067] Batch 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accuracy=78.687917 loss=0.837112 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.531250 acc-top5=86.343750 Batch [0099]/[0303]: acc-top1=66.312500 acc-top5=85.890625 Batch [0149]/[0303]: acc-top1=66.500000 acc-top5=86.229167 Batch [0199]/[0303]: acc-top1=66.898438 acc-top5=86.312500 Batch [0249]/[0303]: acc-top1=66.862500 acc-top5=86.331250 Batch [0299]/[0303]: acc-top1=66.906250 acc-top5=86.583333 [Epoch 067] training: accuracy=78.681848 loss=0.837046 [Epoch 067] speed: 67 samples/sec time cost: 3844.088103 [Epoch 067] validation: acc-top1=66.924505 acc-top5=86.602723 loss=1.626143 Epoch[068] Batch [0049]/[3760] Speed: 45.823461 samples/sec accuracy=78.156250 loss=0.837842 lr=0.001000 Epoch[068] Batch [0099]/[3760] Speed: 66.991047 samples/sec accuracy=78.640625 loss=0.830107 lr=0.001000 Epoch[068] Batch [0149]/[3760] Speed: 68.213626 samples/sec accuracy=78.687500 loss=0.823245 lr=0.001000 Epoch[068] Batch [0199]/[3760] Speed: 67.238715 samples/sec accuracy=79.007812 loss=0.812548 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68.799056 samples/sec accuracy=78.901408 loss=0.830184 lr=0.001000 Epoch[068] Batch [3599]/[3760] Speed: 67.754138 samples/sec accuracy=78.907118 loss=0.829817 lr=0.001000 Epoch[068] Batch [3649]/[3760] Speed: 68.036947 samples/sec accuracy=78.888699 loss=0.830508 lr=0.001000 Epoch[068] Batch [3699]/[3760] Speed: 67.939136 samples/sec accuracy=78.875000 loss=0.830699 lr=0.001000 Epoch[068] Batch [3749]/[3760] Speed: 74.347489 samples/sec accuracy=78.879167 loss=0.830397 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.500000 acc-top5=86.343750 Batch [0099]/[0303]: acc-top1=66.750000 acc-top5=86.031250 Batch [0149]/[0303]: acc-top1=66.687500 acc-top5=86.270833 Batch [0199]/[0303]: acc-top1=66.804688 acc-top5=86.476562 Batch [0249]/[0303]: acc-top1=66.831250 acc-top5=86.468750 Batch [0299]/[0303]: acc-top1=66.953125 acc-top5=86.697917 [Epoch 068] training: accuracy=78.882148 loss=0.830503 [Epoch 068] speed: 67 samples/sec time cost: 3838.963717 [Epoch 068] validation: acc-top1=66.986386 acc-top5=86.700701 loss=1.623172 Epoch[069] Batch [0049]/[3759] Speed: 45.352012 samples/sec accuracy=80.187500 loss=0.784140 lr=0.001000 Epoch[069] Batch [0099]/[3759] Speed: 66.680056 samples/sec accuracy=79.750000 loss=0.796273 lr=0.001000 Epoch[069] Batch [0149]/[3759] Speed: 68.020650 samples/sec accuracy=79.541667 loss=0.798745 lr=0.001000 Epoch[069] Batch [0199]/[3759] Speed: 67.573834 samples/sec accuracy=79.335938 loss=0.802508 lr=0.001000 Epoch[069] Batch [0249]/[3759] Speed: 67.847682 samples/sec accuracy=79.306250 loss=0.812815 lr=0.001000 Epoch[069] Batch [0299]/[3759] Speed: 67.448010 samples/sec accuracy=79.427083 loss=0.809245 lr=0.001000 Epoch[069] Batch [0349]/[3759] Speed: 68.290515 samples/sec accuracy=79.491071 loss=0.808501 lr=0.001000 Epoch[069] Batch [0399]/[3759] Speed: 68.030849 samples/sec accuracy=79.597656 loss=0.803078 lr=0.001000 Epoch[069] Batch [0449]/[3759] Speed: 67.985749 samples/sec accuracy=79.729167 loss=0.799710 lr=0.001000 Epoch[069] Batch 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[0099]/[0303]: acc-top1=66.781250 acc-top5=86.125000 Batch [0149]/[0303]: acc-top1=66.802083 acc-top5=86.427083 Batch [0199]/[0303]: acc-top1=67.070312 acc-top5=86.531250 Batch [0249]/[0303]: acc-top1=67.031250 acc-top5=86.506250 Batch [0299]/[0303]: acc-top1=67.072917 acc-top5=86.734375 [Epoch 069] training: accuracy=78.958001 loss=0.828004 [Epoch 069] speed: 67 samples/sec time cost: 3833.453699 [Epoch 069] validation: acc-top1=67.089521 acc-top5=86.736799 loss=1.631756 Epoch[070] Batch [0049]/[3760] Speed: 45.464343 samples/sec accuracy=79.750000 loss=0.783950 lr=0.001000 Epoch[070] Batch [0099]/[3760] Speed: 66.609722 samples/sec accuracy=79.515625 loss=0.798327 lr=0.001000 Epoch[070] Batch [0149]/[3760] Speed: 68.854053 samples/sec accuracy=79.562500 loss=0.792375 lr=0.001000 Epoch[070] Batch [0199]/[3760] Speed: 67.868044 samples/sec accuracy=79.585938 loss=0.802696 lr=0.001000 Epoch[070] Batch [0249]/[3760] Speed: 67.714484 samples/sec accuracy=79.512500 loss=0.805576 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lr=0.001000 Epoch[070] Batch [3149]/[3760] Speed: 67.403524 samples/sec accuracy=79.102183 loss=0.820301 lr=0.001000 Epoch[070] Batch [3199]/[3760] Speed: 67.901270 samples/sec accuracy=79.089355 loss=0.821069 lr=0.001000 Epoch[070] Batch [3249]/[3760] Speed: 68.604209 samples/sec accuracy=79.096635 loss=0.821292 lr=0.001000 Epoch[070] Batch [3299]/[3760] Speed: 67.548277 samples/sec accuracy=79.083333 loss=0.821925 lr=0.001000 Epoch[070] Batch [3349]/[3760] Speed: 67.677539 samples/sec accuracy=79.084888 loss=0.821814 lr=0.001000 Epoch[070] Batch [3399]/[3760] Speed: 68.381420 samples/sec accuracy=79.088695 loss=0.821706 lr=0.001000 Epoch[070] Batch [3449]/[3760] Speed: 67.910766 samples/sec accuracy=79.094656 loss=0.821353 lr=0.001000 Epoch[070] Batch [3499]/[3760] Speed: 68.329480 samples/sec accuracy=79.096875 loss=0.821030 lr=0.001000 Epoch[070] Batch [3549]/[3760] Speed: 68.344954 samples/sec accuracy=79.086268 loss=0.821513 lr=0.001000 Epoch[070] Batch [3599]/[3760] Speed: 67.215672 samples/sec accuracy=79.079427 loss=0.821834 lr=0.001000 Epoch[070] Batch [3649]/[3760] Speed: 68.417450 samples/sec accuracy=79.072346 loss=0.821760 lr=0.001000 Epoch[070] Batch [3699]/[3760] Speed: 68.228746 samples/sec accuracy=79.060389 loss=0.822102 lr=0.001000 Epoch[070] Batch [3749]/[3760] Speed: 74.044256 samples/sec accuracy=79.079167 loss=0.821413 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.468750 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.281250 acc-top5=85.875000 Batch [0149]/[0303]: acc-top1=66.520833 acc-top5=86.197917 Batch [0199]/[0303]: acc-top1=66.890625 acc-top5=86.414062 Batch [0249]/[0303]: acc-top1=66.881250 acc-top5=86.375000 Batch [0299]/[0303]: acc-top1=67.015625 acc-top5=86.625000 [Epoch 070] training: accuracy=79.077876 loss=0.821568 [Epoch 070] speed: 67 samples/sec time cost: 3833.340492 [Epoch 070] validation: acc-top1=67.037954 acc-top5=86.643977 loss=1.660368 Epoch[071] Batch [0049]/[3760] Speed: 45.167216 samples/sec accuracy=80.093750 loss=0.787521 lr=0.001000 Epoch[071] Batch [0099]/[3760] Speed: 66.493598 samples/sec accuracy=80.281250 loss=0.780989 lr=0.001000 Epoch[071] Batch [0149]/[3760] Speed: 68.547622 samples/sec accuracy=79.989583 loss=0.793550 lr=0.001000 Epoch[071] Batch [0199]/[3760] Speed: 67.466389 samples/sec accuracy=79.945312 loss=0.795289 lr=0.001000 Epoch[071] Batch [0249]/[3760] Speed: 67.729204 samples/sec accuracy=79.800000 loss=0.798969 lr=0.001000 Epoch[071] Batch [0299]/[3760] Speed: 67.714633 samples/sec accuracy=79.802083 loss=0.797624 lr=0.001000 Epoch[071] Batch [0349]/[3760] Speed: 67.974505 samples/sec accuracy=79.816964 loss=0.797528 lr=0.001000 Epoch[071] Batch [0399]/[3760] Speed: 68.118257 samples/sec accuracy=79.777344 loss=0.801870 lr=0.001000 Epoch[071] Batch [0449]/[3760] Speed: 67.915127 samples/sec accuracy=79.711806 loss=0.801617 lr=0.001000 Epoch[071] Batch [0499]/[3760] Speed: 67.816252 samples/sec accuracy=79.684375 loss=0.801046 lr=0.001000 Epoch[071] 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acc-top5=86.531250 Batch [0199]/[0303]: acc-top1=66.781250 acc-top5=86.554688 Batch [0249]/[0303]: acc-top1=66.743750 acc-top5=86.543750 Batch [0299]/[0303]: acc-top1=66.859375 acc-top5=86.723958 [Epoch 071] training: accuracy=79.312666 loss=0.813468 [Epoch 071] speed: 67 samples/sec time cost: 3840.765175 [Epoch 071] validation: acc-top1=66.862624 acc-top5=86.731642 loss=1.629150 Epoch[072] Batch [0049]/[3759] Speed: 45.707457 samples/sec accuracy=79.968750 loss=0.787177 lr=0.001000 Epoch[072] Batch [0099]/[3759] Speed: 66.783248 samples/sec accuracy=79.937500 loss=0.781264 lr=0.001000 Epoch[072] Batch [0149]/[3759] Speed: 67.866420 samples/sec accuracy=79.520833 loss=0.790679 lr=0.001000 Epoch[072] Batch [0199]/[3759] Speed: 68.020215 samples/sec accuracy=79.539062 loss=0.797937 lr=0.001000 Epoch[072] Batch [0249]/[3759] Speed: 68.431683 samples/sec accuracy=79.706250 loss=0.795548 lr=0.001000 Epoch[072] Batch [0299]/[3759] Speed: 67.899600 samples/sec accuracy=79.822917 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accuracy=79.666250 loss=0.800454 lr=0.001000 Epoch[072] Batch [1299]/[3759] Speed: 68.157816 samples/sec accuracy=79.674279 loss=0.800011 lr=0.001000 Epoch[072] Batch [1349]/[3759] Speed: 67.846397 samples/sec accuracy=79.626157 loss=0.802574 lr=0.001000 Epoch[072] Batch [1399]/[3759] Speed: 68.090886 samples/sec accuracy=79.655134 loss=0.801717 lr=0.001000 Epoch[072] Batch [1449]/[3759] Speed: 68.124581 samples/sec accuracy=79.659483 loss=0.801451 lr=0.001000 Epoch[072] Batch [1499]/[3759] Speed: 67.945630 samples/sec accuracy=79.648958 loss=0.800904 lr=0.001000 Epoch[072] Batch [1549]/[3759] Speed: 68.149873 samples/sec accuracy=79.611895 loss=0.801839 lr=0.001000 Epoch[072] Batch [1599]/[3759] Speed: 68.449767 samples/sec accuracy=79.575195 loss=0.803250 lr=0.001000 Epoch[072] Batch [1649]/[3759] Speed: 67.630693 samples/sec accuracy=79.589015 loss=0.803298 lr=0.001000 Epoch[072] Batch [1699]/[3759] Speed: 68.270057 samples/sec accuracy=79.604779 loss=0.802855 lr=0.001000 Epoch[072] 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accuracy=79.521307 loss=0.806089 lr=0.001000 Epoch[072] Batch [2249]/[3759] Speed: 67.576277 samples/sec accuracy=79.523611 loss=0.806152 lr=0.001000 Epoch[072] Batch [2299]/[3759] Speed: 68.479003 samples/sec accuracy=79.510870 loss=0.806425 lr=0.001000 Epoch[072] Batch [2349]/[3759] Speed: 68.040972 samples/sec accuracy=79.535904 loss=0.806009 lr=0.001000 Epoch[072] Batch [2399]/[3759] Speed: 68.829523 samples/sec accuracy=79.555990 loss=0.805187 lr=0.001000 Epoch[072] Batch [2449]/[3759] Speed: 67.534662 samples/sec accuracy=79.550383 loss=0.805152 lr=0.001000 Epoch[072] Batch [2499]/[3759] Speed: 68.002384 samples/sec accuracy=79.549375 loss=0.805001 lr=0.001000 Epoch[072] Batch [2549]/[3759] Speed: 67.770365 samples/sec accuracy=79.543505 loss=0.804909 lr=0.001000 Epoch[072] Batch [2599]/[3759] Speed: 67.301888 samples/sec accuracy=79.534255 loss=0.804717 lr=0.001000 Epoch[072] Batch [2649]/[3759] Speed: 68.587859 samples/sec accuracy=79.536557 loss=0.804368 lr=0.001000 Epoch[072] 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accuracy=79.526786 loss=0.804307 lr=0.001000 Epoch[072] Batch [3199]/[3759] Speed: 68.086707 samples/sec accuracy=79.528809 loss=0.804518 lr=0.001000 Epoch[072] Batch [3249]/[3759] Speed: 68.114400 samples/sec accuracy=79.525000 loss=0.804745 lr=0.001000 Epoch[072] Batch [3299]/[3759] Speed: 68.557014 samples/sec accuracy=79.509470 loss=0.805524 lr=0.001000 Epoch[072] Batch [3349]/[3759] Speed: 67.652272 samples/sec accuracy=79.497668 loss=0.805640 lr=0.001000 Epoch[072] Batch [3399]/[3759] Speed: 68.042472 samples/sec accuracy=79.482537 loss=0.806000 lr=0.001000 Epoch[072] Batch [3449]/[3759] Speed: 67.932901 samples/sec accuracy=79.490036 loss=0.805775 lr=0.001000 Epoch[072] Batch [3499]/[3759] Speed: 67.750444 samples/sec accuracy=79.476786 loss=0.805799 lr=0.001000 Epoch[072] Batch [3549]/[3759] Speed: 68.133973 samples/sec accuracy=79.461268 loss=0.806422 lr=0.001000 Epoch[072] Batch [3599]/[3759] Speed: 68.086115 samples/sec accuracy=79.458767 loss=0.806772 lr=0.001000 Epoch[072] Batch [3649]/[3759] Speed: 68.076187 samples/sec accuracy=79.452055 loss=0.806828 lr=0.001000 Epoch[072] Batch [3699]/[3759] Speed: 68.086577 samples/sec accuracy=79.452703 loss=0.806515 lr=0.001000 Epoch[072] Batch [3749]/[3759] Speed: 74.449048 samples/sec accuracy=79.440833 loss=0.806841 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.562500 acc-top5=86.375000 Batch [0099]/[0303]: acc-top1=66.453125 acc-top5=85.796875 Batch [0149]/[0303]: acc-top1=66.562500 acc-top5=86.135417 Batch [0199]/[0303]: acc-top1=66.656250 acc-top5=86.203125 Batch [0249]/[0303]: acc-top1=66.487500 acc-top5=86.137500 Batch [0299]/[0303]: acc-top1=66.614583 acc-top5=86.281250 [Epoch 072] training: accuracy=79.443502 loss=0.806826 [Epoch 072] speed: 67 samples/sec time cost: 3833.835537 [Epoch 072] validation: acc-top1=66.615099 acc-top5=86.308787 loss=1.668395 Epoch[073] Batch [0049]/[3760] Speed: 46.271798 samples/sec accuracy=79.937500 loss=0.803029 lr=0.001000 Epoch[073] Batch [0099]/[3760] Speed: 67.170853 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lr=0.001000 Epoch[073] Batch [3449]/[3760] Speed: 68.179941 samples/sec accuracy=79.435236 loss=0.803779 lr=0.001000 Epoch[073] Batch [3499]/[3760] Speed: 67.578094 samples/sec accuracy=79.435268 loss=0.803682 lr=0.001000 Epoch[073] Batch [3549]/[3760] Speed: 68.690104 samples/sec accuracy=79.434419 loss=0.804019 lr=0.001000 Epoch[073] Batch [3599]/[3760] Speed: 68.129151 samples/sec accuracy=79.420139 loss=0.804665 lr=0.001000 Epoch[073] Batch [3649]/[3760] Speed: 68.255224 samples/sec accuracy=79.429366 loss=0.804634 lr=0.001000 Epoch[073] Batch [3699]/[3760] Speed: 68.216198 samples/sec accuracy=79.397804 loss=0.805656 lr=0.001000 Epoch[073] Batch [3749]/[3760] Speed: 73.212772 samples/sec accuracy=79.386250 loss=0.806332 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.500000 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.140625 acc-top5=86.015625 Batch [0149]/[0303]: acc-top1=66.333333 acc-top5=86.197917 Batch [0199]/[0303]: acc-top1=66.640625 acc-top5=86.359375 Batch [0249]/[0303]: acc-top1=66.650000 acc-top5=86.418750 Batch [0299]/[0303]: acc-top1=66.723958 acc-top5=86.651042 [Epoch 073] training: accuracy=79.386636 loss=0.806305 [Epoch 073] speed: 67 samples/sec time cost: 3833.385377 [Epoch 073] validation: acc-top1=66.738861 acc-top5=86.664604 loss=1.634371 Epoch[074] Batch [0049]/[3760] Speed: 45.757156 samples/sec accuracy=79.906250 loss=0.778044 lr=0.001000 Epoch[074] Batch [0099]/[3760] Speed: 67.320166 samples/sec accuracy=79.546875 loss=0.786524 lr=0.001000 Epoch[074] Batch [0149]/[3760] Speed: 68.344997 samples/sec accuracy=79.708333 loss=0.783799 lr=0.001000 Epoch[074] Batch [0199]/[3760] Speed: 67.632810 samples/sec accuracy=79.539062 loss=0.791410 lr=0.001000 Epoch[074] Batch [0249]/[3760] Speed: 68.401992 samples/sec accuracy=79.643750 loss=0.791006 lr=0.001000 Epoch[074] Batch [0299]/[3760] Speed: 67.798304 samples/sec accuracy=79.557292 loss=0.795352 lr=0.001000 Epoch[074] Batch [0349]/[3760] Speed: 67.820381 samples/sec 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accuracy=79.824519 loss=0.790821 lr=0.001000 Epoch[074] Batch [1349]/[3760] Speed: 68.650093 samples/sec accuracy=79.798611 loss=0.791486 lr=0.001000 Epoch[074] Batch [1399]/[3760] Speed: 68.631589 samples/sec accuracy=79.784598 loss=0.792349 lr=0.001000 Epoch[074] Batch [1449]/[3760] Speed: 68.090142 samples/sec accuracy=79.753233 loss=0.793437 lr=0.001000 Epoch[074] Batch [1499]/[3760] Speed: 67.955889 samples/sec accuracy=79.707292 loss=0.794659 lr=0.001000 Epoch[074] Batch [1549]/[3760] Speed: 68.341226 samples/sec accuracy=79.714718 loss=0.794530 lr=0.001000 Epoch[074] Batch [1599]/[3760] Speed: 68.071032 samples/sec accuracy=79.698242 loss=0.794500 lr=0.001000 Epoch[074] Batch [1649]/[3760] Speed: 67.660976 samples/sec accuracy=79.708333 loss=0.793791 lr=0.001000 Epoch[074] Batch [1699]/[3760] Speed: 67.622352 samples/sec accuracy=79.655331 loss=0.795862 lr=0.001000 Epoch[074] Batch [1749]/[3760] Speed: 68.208831 samples/sec accuracy=79.643750 loss=0.796935 lr=0.001000 Epoch[074] 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accuracy=79.630556 loss=0.798205 lr=0.001000 Epoch[074] Batch [2299]/[3760] Speed: 67.754233 samples/sec accuracy=79.637228 loss=0.798406 lr=0.001000 Epoch[074] Batch [2349]/[3760] Speed: 67.844467 samples/sec accuracy=79.618351 loss=0.799006 lr=0.001000 Epoch[074] Batch [2399]/[3760] Speed: 68.611544 samples/sec accuracy=79.625651 loss=0.798420 lr=0.001000 Epoch[074] Batch [2449]/[3760] Speed: 67.701265 samples/sec accuracy=79.595663 loss=0.799494 lr=0.001000 Epoch[074] Batch [2499]/[3760] Speed: 68.484075 samples/sec accuracy=79.586875 loss=0.799718 lr=0.001000 Epoch[074] Batch [2549]/[3760] Speed: 68.114721 samples/sec accuracy=79.575980 loss=0.799696 lr=0.001000 Epoch[074] Batch [2599]/[3760] Speed: 67.837063 samples/sec accuracy=79.584135 loss=0.799319 lr=0.001000 Epoch[074] Batch [2649]/[3760] Speed: 68.342490 samples/sec accuracy=79.584906 loss=0.799077 lr=0.001000 Epoch[074] Batch [2699]/[3760] Speed: 67.923308 samples/sec accuracy=79.571181 loss=0.799308 lr=0.001000 Epoch[074] 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accuracy=79.538086 loss=0.800658 lr=0.001000 Epoch[074] Batch [3249]/[3760] Speed: 68.057190 samples/sec accuracy=79.536058 loss=0.800770 lr=0.001000 Epoch[074] Batch [3299]/[3760] Speed: 68.339455 samples/sec accuracy=79.536458 loss=0.800880 lr=0.001000 Epoch[074] Batch [3349]/[3760] Speed: 68.217222 samples/sec accuracy=79.538713 loss=0.800746 lr=0.001000 Epoch[074] Batch [3399]/[3760] Speed: 68.377312 samples/sec accuracy=79.534467 loss=0.801250 lr=0.001000 Epoch[074] Batch [3449]/[3760] Speed: 67.849721 samples/sec accuracy=79.532156 loss=0.801428 lr=0.001000 Epoch[074] Batch [3499]/[3760] Speed: 67.968486 samples/sec accuracy=79.531250 loss=0.801464 lr=0.001000 Epoch[074] Batch [3549]/[3760] Speed: 68.333839 samples/sec accuracy=79.543134 loss=0.801103 lr=0.001000 Epoch[074] Batch [3599]/[3760] Speed: 67.487535 samples/sec accuracy=79.532986 loss=0.801738 lr=0.001000 Epoch[074] Batch [3649]/[3760] Speed: 68.047902 samples/sec accuracy=79.523545 loss=0.801926 lr=0.001000 Epoch[074] Batch [3699]/[3760] Speed: 67.847499 samples/sec accuracy=79.503801 loss=0.802604 lr=0.001000 Epoch[074] Batch [3749]/[3760] Speed: 75.060244 samples/sec accuracy=79.509583 loss=0.802618 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.343750 acc-top5=86.187500 Batch [0099]/[0303]: acc-top1=66.109375 acc-top5=85.656250 Batch [0149]/[0303]: acc-top1=66.343750 acc-top5=85.864583 Batch [0199]/[0303]: acc-top1=66.679688 acc-top5=86.046875 Batch [0249]/[0303]: acc-top1=66.575000 acc-top5=86.168750 Batch [0299]/[0303]: acc-top1=66.635417 acc-top5=86.437500 [Epoch 074] training: accuracy=79.515459 loss=0.802465 [Epoch 074] speed: 67 samples/sec time cost: 3832.681668 [Epoch 074] validation: acc-top1=66.671823 acc-top5=86.499587 loss=1.652996 Epoch[075] Batch [0049]/[3759] Speed: 45.129210 samples/sec accuracy=79.562500 loss=0.811449 lr=0.001000 Epoch[075] Batch [0099]/[3759] Speed: 66.522335 samples/sec accuracy=79.703125 loss=0.791893 lr=0.001000 Epoch[075] Batch [0149]/[3759] Speed: 68.530058 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lr=0.001000 Epoch[075] Batch [2549]/[3759] Speed: 67.590004 samples/sec accuracy=79.832108 loss=0.790755 lr=0.001000 Epoch[075] Batch [2599]/[3759] Speed: 68.054646 samples/sec accuracy=79.826923 loss=0.790876 lr=0.001000 Epoch[075] Batch [2649]/[3759] Speed: 67.830839 samples/sec accuracy=79.810142 loss=0.791282 lr=0.001000 Epoch[075] Batch [2699]/[3759] Speed: 68.107451 samples/sec accuracy=79.810764 loss=0.791108 lr=0.001000 Epoch[075] Batch [2749]/[3759] Speed: 67.501717 samples/sec accuracy=79.801705 loss=0.791996 lr=0.001000 Epoch[075] Batch [2799]/[3759] Speed: 68.270258 samples/sec accuracy=79.807478 loss=0.791376 lr=0.001000 Epoch[075] Batch [2849]/[3759] Speed: 67.816818 samples/sec accuracy=79.799890 loss=0.791602 lr=0.001000 Epoch[075] Batch [2899]/[3759] Speed: 68.199531 samples/sec accuracy=79.776940 loss=0.792898 lr=0.001000 Epoch[075] Batch [2949]/[3759] Speed: 67.928658 samples/sec accuracy=79.772775 loss=0.793100 lr=0.001000 Epoch[075] Batch [2999]/[3759] Speed: 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lr=0.001000 Epoch[075] Batch [3499]/[3759] Speed: 68.387337 samples/sec accuracy=79.720089 loss=0.794848 lr=0.001000 Epoch[075] Batch [3549]/[3759] Speed: 68.066098 samples/sec accuracy=79.717430 loss=0.795288 lr=0.001000 Epoch[075] Batch [3599]/[3759] Speed: 68.145047 samples/sec accuracy=79.703559 loss=0.795797 lr=0.001000 Epoch[075] Batch [3649]/[3759] Speed: 68.185971 samples/sec accuracy=79.705908 loss=0.795671 lr=0.001000 Epoch[075] Batch [3699]/[3759] Speed: 67.806352 samples/sec accuracy=79.706926 loss=0.795794 lr=0.001000 Epoch[075] Batch [3749]/[3759] Speed: 74.715216 samples/sec accuracy=79.718750 loss=0.795245 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.468750 acc-top5=86.218750 Batch [0099]/[0303]: acc-top1=66.578125 acc-top5=85.875000 Batch [0149]/[0303]: acc-top1=66.562500 acc-top5=86.197917 Batch [0199]/[0303]: acc-top1=66.789062 acc-top5=86.304688 Batch [0249]/[0303]: acc-top1=66.687500 acc-top5=86.293750 Batch [0299]/[0303]: acc-top1=66.812500 acc-top5=86.484375 [Epoch 075] training: accuracy=79.714518 loss=0.795367 [Epoch 075] speed: 67 samples/sec time cost: 3832.427606 [Epoch 075] validation: acc-top1=66.847153 acc-top5=86.484117 loss=1.637839 Epoch[076] Batch [0049]/[3760] Speed: 45.126770 samples/sec accuracy=80.656250 loss=0.768853 lr=0.001000 Epoch[076] Batch [0099]/[3760] Speed: 67.040516 samples/sec accuracy=80.468750 loss=0.779959 lr=0.001000 Epoch[076] Batch [0149]/[3760] Speed: 68.397712 samples/sec accuracy=80.364583 loss=0.778648 lr=0.001000 Epoch[076] Batch [0199]/[3760] Speed: 67.927137 samples/sec accuracy=80.453125 loss=0.770982 lr=0.001000 Epoch[076] Batch [0249]/[3760] Speed: 67.699689 samples/sec accuracy=80.375000 loss=0.779148 lr=0.001000 Epoch[076] Batch [0299]/[3760] Speed: 68.012119 samples/sec accuracy=80.296875 loss=0.775041 lr=0.001000 Epoch[076] Batch [0349]/[3760] Speed: 67.678722 samples/sec accuracy=80.491071 loss=0.767335 lr=0.001000 Epoch[076] Batch [0399]/[3760] Speed: 68.016612 samples/sec accuracy=80.593750 loss=0.765871 lr=0.001000 Epoch[076] Batch [0449]/[3760] Speed: 68.379060 samples/sec accuracy=80.486111 loss=0.770649 lr=0.001000 Epoch[076] Batch [0499]/[3760] Speed: 67.768358 samples/sec accuracy=80.515625 loss=0.772041 lr=0.001000 Epoch[076] Batch [0549]/[3760] Speed: 68.413005 samples/sec accuracy=80.508523 loss=0.772660 lr=0.001000 Epoch[076] Batch [0599]/[3760] Speed: 67.545256 samples/sec accuracy=80.466146 loss=0.772811 lr=0.001000 Epoch[076] Batch [0649]/[3760] Speed: 67.828226 samples/sec accuracy=80.471154 loss=0.772946 lr=0.001000 Epoch[076] Batch [0699]/[3760] Speed: 68.117567 samples/sec accuracy=80.417411 loss=0.775901 lr=0.001000 Epoch[076] Batch [0749]/[3760] Speed: 68.026736 samples/sec accuracy=80.458333 loss=0.774438 lr=0.001000 Epoch[076] Batch [0799]/[3760] Speed: 67.956366 samples/sec accuracy=80.451172 loss=0.776077 lr=0.001000 Epoch[076] Batch [0849]/[3760] Speed: 68.552260 samples/sec accuracy=80.415441 loss=0.776249 lr=0.001000 Epoch[076] 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accuracy=80.350694 loss=0.778949 lr=0.001000 Epoch[076] Batch [1399]/[3760] Speed: 68.030965 samples/sec accuracy=80.330357 loss=0.779458 lr=0.001000 Epoch[076] Batch [1449]/[3760] Speed: 68.244335 samples/sec accuracy=80.362069 loss=0.777420 lr=0.001000 Epoch[076] Batch [1499]/[3760] Speed: 67.856089 samples/sec accuracy=80.346875 loss=0.777314 lr=0.001000 Epoch[076] Batch [1549]/[3760] Speed: 67.878753 samples/sec accuracy=80.305444 loss=0.778160 lr=0.001000 Epoch[076] Batch [1599]/[3760] Speed: 68.824604 samples/sec accuracy=80.296875 loss=0.778219 lr=0.001000 Epoch[076] Batch [1649]/[3760] Speed: 68.161976 samples/sec accuracy=80.336174 loss=0.777285 lr=0.001000 Epoch[076] Batch [1699]/[3760] Speed: 67.875793 samples/sec accuracy=80.345588 loss=0.777024 lr=0.001000 Epoch[076] Batch [1749]/[3760] Speed: 68.759289 samples/sec accuracy=80.320536 loss=0.777486 lr=0.001000 Epoch[076] Batch [1799]/[3760] Speed: 68.340091 samples/sec accuracy=80.295139 loss=0.778501 lr=0.001000 Epoch[076] Batch [1849]/[3760] Speed: 67.694949 samples/sec accuracy=80.293074 loss=0.777972 lr=0.001000 Epoch[076] Batch [1899]/[3760] Speed: 68.923028 samples/sec accuracy=80.294408 loss=0.777797 lr=0.001000 Epoch[076] Batch [1949]/[3760] Speed: 67.877747 samples/sec accuracy=80.306090 loss=0.776849 lr=0.001000 Epoch[076] Batch [1999]/[3760] Speed: 67.918150 samples/sec accuracy=80.298437 loss=0.776810 lr=0.001000 Epoch[076] Batch [2049]/[3760] Speed: 67.893413 samples/sec accuracy=80.276677 loss=0.776784 lr=0.001000 Epoch[076] Batch [2099]/[3760] Speed: 67.925007 samples/sec accuracy=80.289435 loss=0.776173 lr=0.001000 Epoch[076] Batch [2149]/[3760] Speed: 68.321607 samples/sec accuracy=80.276890 loss=0.776922 lr=0.001000 Epoch[076] Batch [2199]/[3760] Speed: 68.517844 samples/sec accuracy=80.267045 loss=0.777240 lr=0.001000 Epoch[076] Batch [2249]/[3760] Speed: 68.647485 samples/sec accuracy=80.253472 loss=0.777568 lr=0.001000 Epoch[076] Batch [2299]/[3760] Speed: 68.058813 samples/sec accuracy=80.260190 loss=0.777817 lr=0.001000 Epoch[076] Batch [2349]/[3760] Speed: 68.164238 samples/sec accuracy=80.267952 loss=0.777057 lr=0.001000 Epoch[076] Batch [2399]/[3760] Speed: 68.366018 samples/sec accuracy=80.257812 loss=0.777568 lr=0.001000 Epoch[076] Batch [2449]/[3760] Speed: 68.299644 samples/sec accuracy=80.237883 loss=0.777952 lr=0.001000 Epoch[076] Batch [2499]/[3760] Speed: 67.742157 samples/sec accuracy=80.242500 loss=0.778337 lr=0.001000 Epoch[076] Batch [2549]/[3760] Speed: 68.224585 samples/sec accuracy=80.234681 loss=0.779069 lr=0.001000 Epoch[076] Batch [2599]/[3760] Speed: 68.235713 samples/sec accuracy=80.258413 loss=0.778366 lr=0.001000 Epoch[076] Batch [2649]/[3760] Speed: 67.892546 samples/sec accuracy=80.235849 loss=0.779070 lr=0.001000 Epoch[076] Batch [2699]/[3760] Speed: 68.383139 samples/sec accuracy=80.214120 loss=0.779498 lr=0.001000 Epoch[076] Batch [2749]/[3760] Speed: 68.228720 samples/sec accuracy=80.207955 loss=0.779979 lr=0.001000 Epoch[076] Batch [2799]/[3760] Speed: 68.631250 samples/sec accuracy=80.184710 loss=0.780707 lr=0.001000 Epoch[076] Batch [2849]/[3760] Speed: 67.945565 samples/sec accuracy=80.157346 loss=0.781394 lr=0.001000 Epoch[076] Batch [2899]/[3760] Speed: 67.644136 samples/sec accuracy=80.146013 loss=0.781516 lr=0.001000 Epoch[076] Batch [2949]/[3760] Speed: 68.111306 samples/sec accuracy=80.137712 loss=0.782262 lr=0.001000 Epoch[076] Batch [2999]/[3760] Speed: 68.181319 samples/sec accuracy=80.095313 loss=0.783317 lr=0.001000 Epoch[076] Batch [3049]/[3760] Speed: 68.314885 samples/sec accuracy=80.082480 loss=0.783743 lr=0.001000 Epoch[076] Batch [3099]/[3760] Speed: 68.002940 samples/sec accuracy=80.068548 loss=0.784332 lr=0.001000 Epoch[076] Batch [3149]/[3760] Speed: 68.228789 samples/sec accuracy=80.066964 loss=0.784688 lr=0.001000 Epoch[076] Batch [3199]/[3760] Speed: 67.876623 samples/sec accuracy=80.072266 loss=0.784194 lr=0.001000 Epoch[076] Batch [3249]/[3760] Speed: 67.380864 samples/sec accuracy=80.069231 loss=0.784520 lr=0.001000 Epoch[076] Batch [3299]/[3760] Speed: 67.862288 samples/sec accuracy=80.071496 loss=0.784065 lr=0.001000 Epoch[076] Batch [3349]/[3760] Speed: 67.575344 samples/sec accuracy=80.086754 loss=0.783306 lr=0.001000 Epoch[076] Batch [3399]/[3760] Speed: 67.738463 samples/sec accuracy=80.064798 loss=0.783886 lr=0.001000 Epoch[076] Batch [3449]/[3760] Speed: 68.262192 samples/sec accuracy=80.056159 loss=0.784089 lr=0.001000 Epoch[076] Batch [3499]/[3760] Speed: 68.310867 samples/sec accuracy=80.044196 loss=0.784163 lr=0.001000 Epoch[076] Batch [3549]/[3760] Speed: 67.729398 samples/sec accuracy=80.041813 loss=0.784358 lr=0.001000 Epoch[076] Batch [3599]/[3760] Speed: 68.476165 samples/sec accuracy=80.022135 loss=0.784459 lr=0.001000 Epoch[076] Batch [3649]/[3760] Speed: 67.867084 samples/sec accuracy=80.027825 loss=0.784022 lr=0.001000 Epoch[076] Batch [3699]/[3760] Speed: 67.765302 samples/sec accuracy=80.013936 loss=0.784503 lr=0.001000 Epoch[076] Batch [3749]/[3760] Speed: 74.916470 samples/sec accuracy=80.000000 loss=0.784769 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.875000 acc-top5=85.968750 Batch [0099]/[0303]: acc-top1=65.953125 acc-top5=85.718750 Batch [0149]/[0303]: acc-top1=66.166667 acc-top5=86.062500 Batch [0199]/[0303]: acc-top1=66.554688 acc-top5=86.101562 Batch [0249]/[0303]: acc-top1=66.450000 acc-top5=86.062500 Batch [0299]/[0303]: acc-top1=66.515625 acc-top5=86.296875 [Epoch 076] training: accuracy=80.009142 loss=0.784506 [Epoch 076] speed: 67 samples/sec time cost: 3831.049323 [Epoch 076] validation: acc-top1=66.558375 acc-top5=86.324257 loss=1.687712 Epoch[077] Batch [0049]/[3760] Speed: 45.765758 samples/sec accuracy=80.562500 loss=0.750250 lr=0.001000 Epoch[077] Batch [0099]/[3760] Speed: 67.297981 samples/sec accuracy=80.796875 loss=0.748754 lr=0.001000 Epoch[077] Batch [0149]/[3760] Speed: 68.767376 samples/sec accuracy=80.083333 loss=0.768706 lr=0.001000 Epoch[077] Batch [0199]/[3760] Speed: 67.947400 samples/sec accuracy=80.250000 loss=0.761799 lr=0.001000 Epoch[077] Batch [0249]/[3760] Speed: 67.953174 samples/sec accuracy=80.268750 loss=0.766722 lr=0.001000 Epoch[077] Batch [0299]/[3760] Speed: 67.919783 samples/sec accuracy=80.213542 loss=0.768102 lr=0.001000 Epoch[077] Batch [0349]/[3760] Speed: 67.776885 samples/sec accuracy=80.147321 loss=0.774331 lr=0.001000 Epoch[077] Batch [0399]/[3760] Speed: 68.258913 samples/sec accuracy=80.187500 loss=0.769904 lr=0.001000 Epoch[077] Batch [0449]/[3760] Speed: 67.634462 samples/sec accuracy=80.159722 loss=0.773555 lr=0.001000 Epoch[077] Batch [0499]/[3760] Speed: 68.297569 samples/sec accuracy=80.131250 loss=0.770605 lr=0.001000 Epoch[077] Batch [0549]/[3760] Speed: 67.280797 samples/sec accuracy=80.164773 loss=0.768686 lr=0.001000 Epoch[077] Batch [0599]/[3760] Speed: 68.234743 samples/sec accuracy=80.239583 loss=0.767743 lr=0.001000 Epoch[077] Batch [0649]/[3760] Speed: 68.014936 samples/sec accuracy=80.206731 loss=0.768398 lr=0.001000 Epoch[077] Batch [0699]/[3760] Speed: 68.315650 samples/sec accuracy=80.185268 loss=0.769320 lr=0.001000 Epoch[077] Batch [0749]/[3760] Speed: 68.572165 samples/sec accuracy=80.129167 loss=0.772540 lr=0.001000 Epoch[077] Batch [0799]/[3760] Speed: 68.393331 samples/sec accuracy=80.185547 loss=0.771144 lr=0.001000 Epoch[077] Batch [0849]/[3760] Speed: 67.283829 samples/sec accuracy=80.176471 loss=0.772427 lr=0.001000 Epoch[077] Batch [0899]/[3760] Speed: 68.335467 samples/sec accuracy=80.171875 loss=0.772427 lr=0.001000 Epoch[077] Batch [0949]/[3760] Speed: 67.768926 samples/sec accuracy=80.236842 loss=0.770237 lr=0.001000 Epoch[077] Batch [0999]/[3760] Speed: 68.003137 samples/sec accuracy=80.243750 loss=0.771566 lr=0.001000 Epoch[077] Batch [1049]/[3760] Speed: 67.756696 samples/sec accuracy=80.288690 loss=0.770593 lr=0.001000 Epoch[077] Batch [1099]/[3760] Speed: 67.968869 samples/sec accuracy=80.313920 loss=0.770686 lr=0.001000 Epoch[077] Batch [1149]/[3760] Speed: 67.599292 samples/sec accuracy=80.216033 loss=0.773186 lr=0.001000 Epoch[077] Batch [1199]/[3760] Speed: 68.449018 samples/sec accuracy=80.239583 loss=0.772759 lr=0.001000 Epoch[077] Batch [1249]/[3760] Speed: 68.176657 samples/sec accuracy=80.266250 loss=0.772362 lr=0.001000 Epoch[077] Batch [1299]/[3760] Speed: 68.104593 samples/sec accuracy=80.248798 loss=0.772236 lr=0.001000 Epoch[077] Batch [1349]/[3760] Speed: 67.795792 samples/sec accuracy=80.201389 loss=0.773007 lr=0.001000 Epoch[077] Batch [1399]/[3760] Speed: 68.132638 samples/sec accuracy=80.232143 loss=0.772488 lr=0.001000 Epoch[077] Batch [1449]/[3760] Speed: 67.084106 samples/sec accuracy=80.205819 loss=0.773297 lr=0.001000 Epoch[077] Batch [1499]/[3760] Speed: 68.849029 samples/sec accuracy=80.196875 loss=0.773446 lr=0.001000 Epoch[077] Batch [1549]/[3760] Speed: 67.988838 samples/sec accuracy=80.187500 loss=0.772980 lr=0.001000 Epoch[077] Batch [1599]/[3760] Speed: 67.838338 samples/sec accuracy=80.190430 loss=0.772751 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67.501615 samples/sec accuracy=80.145833 loss=0.776838 lr=0.001000 Epoch[077] Batch [2149]/[3760] Speed: 67.746032 samples/sec accuracy=80.118459 loss=0.777949 lr=0.001000 Epoch[077] Batch [2199]/[3760] Speed: 68.058729 samples/sec accuracy=80.102273 loss=0.777871 lr=0.001000 Epoch[077] Batch [2249]/[3760] Speed: 67.869069 samples/sec accuracy=80.102083 loss=0.778212 lr=0.001000 Epoch[077] Batch [2299]/[3760] Speed: 67.578983 samples/sec accuracy=80.101902 loss=0.778319 lr=0.001000 Epoch[077] Batch [2349]/[3760] Speed: 68.798337 samples/sec accuracy=80.084441 loss=0.779297 lr=0.001000 Epoch[077] Batch [2399]/[3760] Speed: 67.842713 samples/sec accuracy=80.075521 loss=0.779854 lr=0.001000 Epoch[077] Batch [2449]/[3760] Speed: 67.922069 samples/sec accuracy=80.068240 loss=0.780566 lr=0.001000 Epoch[077] Batch [2499]/[3760] Speed: 67.863375 samples/sec accuracy=80.041250 loss=0.781584 lr=0.001000 Epoch[077] Batch [2549]/[3760] Speed: 68.009558 samples/sec accuracy=80.037990 loss=0.781698 lr=0.001000 Epoch[077] Batch [2599]/[3760] Speed: 68.096866 samples/sec accuracy=80.024038 loss=0.781781 lr=0.001000 Epoch[077] Batch [2649]/[3760] Speed: 67.857029 samples/sec accuracy=80.042453 loss=0.781744 lr=0.001000 Epoch[077] Batch [2699]/[3760] Speed: 68.127684 samples/sec accuracy=80.061921 loss=0.781179 lr=0.001000 Epoch[077] Batch [2749]/[3760] Speed: 68.011491 samples/sec accuracy=80.053409 loss=0.781165 lr=0.001000 Epoch[077] Batch [2799]/[3760] Speed: 68.023483 samples/sec accuracy=80.041295 loss=0.781516 lr=0.001000 Epoch[077] Batch [2849]/[3760] Speed: 67.486007 samples/sec accuracy=80.051535 loss=0.781335 lr=0.001000 Epoch[077] Batch [2899]/[3760] Speed: 68.848901 samples/sec accuracy=80.023707 loss=0.782281 lr=0.001000 Epoch[077] Batch [2949]/[3760] Speed: 68.090477 samples/sec accuracy=80.016949 loss=0.782236 lr=0.001000 Epoch[077] Batch [2999]/[3760] Speed: 67.905487 samples/sec accuracy=80.015104 loss=0.782845 lr=0.001000 Epoch[077] Batch [3049]/[3760] Speed: 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lr=0.001000 Epoch[077] Batch [3549]/[3760] Speed: 68.422617 samples/sec accuracy=80.014525 loss=0.782140 lr=0.001000 Epoch[077] Batch [3599]/[3760] Speed: 67.739402 samples/sec accuracy=80.016493 loss=0.782220 lr=0.001000 Epoch[077] Batch [3649]/[3760] Speed: 68.006168 samples/sec accuracy=80.012842 loss=0.782169 lr=0.001000 Epoch[077] Batch [3699]/[3760] Speed: 68.254844 samples/sec accuracy=80.013936 loss=0.782045 lr=0.001000 Epoch[077] Batch [3749]/[3760] Speed: 75.112285 samples/sec accuracy=79.999583 loss=0.782316 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.843750 acc-top5=86.093750 Batch [0099]/[0303]: acc-top1=65.906250 acc-top5=85.750000 Batch [0149]/[0303]: acc-top1=66.354167 acc-top5=86.270833 Batch [0199]/[0303]: acc-top1=66.640625 acc-top5=86.367188 Batch [0249]/[0303]: acc-top1=66.468750 acc-top5=86.375000 Batch [0299]/[0303]: acc-top1=66.697917 acc-top5=86.536458 [Epoch 077] training: accuracy=79.999584 loss=0.782517 [Epoch 077] speed: 67 samples/sec time cost: 3832.264043 [Epoch 077] validation: acc-top1=66.744018 acc-top5=86.561469 loss=1.668259 Epoch[078] Batch [0049]/[3759] Speed: 45.518598 samples/sec accuracy=80.000000 loss=0.791560 lr=0.001000 Epoch[078] Batch [0099]/[3759] Speed: 66.529557 samples/sec accuracy=80.109375 loss=0.774389 lr=0.001000 Epoch[078] Batch [0149]/[3759] Speed: 68.130078 samples/sec accuracy=80.458333 loss=0.762989 lr=0.001000 Epoch[078] Batch [0199]/[3759] Speed: 67.546133 samples/sec accuracy=80.265625 loss=0.775248 lr=0.001000 Epoch[078] Batch [0249]/[3759] Speed: 68.002153 samples/sec accuracy=80.431250 loss=0.768429 lr=0.001000 Epoch[078] Batch [0299]/[3759] Speed: 67.849559 samples/sec accuracy=80.755208 loss=0.759062 lr=0.001000 Epoch[078] Batch [0349]/[3759] Speed: 67.792098 samples/sec accuracy=80.602679 loss=0.763435 lr=0.001000 Epoch[078] Batch [0399]/[3759] Speed: 67.874906 samples/sec accuracy=80.535156 loss=0.768704 lr=0.001000 Epoch[078] Batch [0449]/[3759] Speed: 68.581330 samples/sec 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accuracy=80.404018 loss=0.772750 lr=0.001000 Epoch[078] Batch [1449]/[3759] Speed: 67.897384 samples/sec accuracy=80.350216 loss=0.773240 lr=0.001000 Epoch[078] Batch [1499]/[3759] Speed: 68.095088 samples/sec accuracy=80.328125 loss=0.772967 lr=0.001000 Epoch[078] Batch [1549]/[3759] Speed: 68.009670 samples/sec accuracy=80.325605 loss=0.773732 lr=0.001000 Epoch[078] Batch [1599]/[3759] Speed: 67.596777 samples/sec accuracy=80.286133 loss=0.774767 lr=0.001000 Epoch[078] Batch [1649]/[3759] Speed: 67.972220 samples/sec accuracy=80.273674 loss=0.775870 lr=0.001000 Epoch[078] Batch [1699]/[3759] Speed: 68.494839 samples/sec accuracy=80.266544 loss=0.777267 lr=0.001000 Epoch[078] Batch [1749]/[3759] Speed: 67.950721 samples/sec accuracy=80.233036 loss=0.778168 lr=0.001000 Epoch[078] Batch [1799]/[3759] Speed: 68.547526 samples/sec accuracy=80.212674 loss=0.778707 lr=0.001000 Epoch[078] Batch [1849]/[3759] Speed: 67.598489 samples/sec accuracy=80.251689 loss=0.777961 lr=0.001000 Epoch[078] 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accuracy=80.277926 loss=0.776919 lr=0.001000 Epoch[078] Batch [2399]/[3759] Speed: 67.411833 samples/sec accuracy=80.276042 loss=0.776846 lr=0.001000 Epoch[078] Batch [2449]/[3759] Speed: 68.103079 samples/sec accuracy=80.245536 loss=0.777784 lr=0.001000 Epoch[078] Batch [2499]/[3759] Speed: 67.905281 samples/sec accuracy=80.246250 loss=0.777142 lr=0.001000 Epoch[078] Batch [2549]/[3759] Speed: 68.423695 samples/sec accuracy=80.234681 loss=0.777500 lr=0.001000 Epoch[078] Batch [2599]/[3759] Speed: 68.137037 samples/sec accuracy=80.243389 loss=0.776984 lr=0.001000 Epoch[078] Batch [2649]/[3759] Speed: 67.964931 samples/sec accuracy=80.242925 loss=0.777026 lr=0.001000 Epoch[078] Batch [2699]/[3759] Speed: 68.385941 samples/sec accuracy=80.214120 loss=0.777569 lr=0.001000 Epoch[078] Batch [2749]/[3759] Speed: 68.082626 samples/sec accuracy=80.208523 loss=0.777407 lr=0.001000 Epoch[078] Batch [2799]/[3759] Speed: 67.764197 samples/sec accuracy=80.205357 loss=0.777311 lr=0.001000 Epoch[078] 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accuracy=80.172348 loss=0.778821 lr=0.001000 Epoch[078] Batch [3349]/[3759] Speed: 67.577926 samples/sec accuracy=80.158116 loss=0.779020 lr=0.001000 Epoch[078] Batch [3399]/[3759] Speed: 67.720147 samples/sec accuracy=80.160386 loss=0.779744 lr=0.001000 Epoch[078] Batch [3449]/[3759] Speed: 68.116189 samples/sec accuracy=80.149909 loss=0.780403 lr=0.001000 Epoch[078] Batch [3499]/[3759] Speed: 68.624249 samples/sec accuracy=80.130804 loss=0.781262 lr=0.001000 Epoch[078] Batch [3549]/[3759] Speed: 68.006677 samples/sec accuracy=80.117958 loss=0.781771 lr=0.001000 Epoch[078] Batch [3599]/[3759] Speed: 67.959757 samples/sec accuracy=80.115017 loss=0.781692 lr=0.001000 Epoch[078] Batch [3649]/[3759] Speed: 68.187555 samples/sec accuracy=80.116866 loss=0.781409 lr=0.001000 Epoch[078] Batch [3699]/[3759] Speed: 67.989845 samples/sec accuracy=80.113176 loss=0.781752 lr=0.001000 Epoch[078] Batch [3749]/[3759] Speed: 74.764538 samples/sec accuracy=80.110833 loss=0.781923 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.250000 acc-top5=85.687500 Batch [0099]/[0303]: acc-top1=66.312500 acc-top5=85.421875 Batch [0149]/[0303]: acc-top1=66.479167 acc-top5=85.802083 Batch [0199]/[0303]: acc-top1=66.679688 acc-top5=85.835938 Batch [0249]/[0303]: acc-top1=66.650000 acc-top5=85.906250 Batch [0299]/[0303]: acc-top1=66.697917 acc-top5=86.072917 [Epoch 078] training: accuracy=80.109404 loss=0.782064 [Epoch 078] speed: 67 samples/sec time cost: 3833.713017 [Epoch 078] validation: acc-top1=66.718234 acc-top5=86.102517 loss=1.671076 Epoch[079] Batch [0049]/[3760] Speed: 45.712085 samples/sec accuracy=80.687500 loss=0.758584 lr=0.001000 Epoch[079] Batch [0099]/[3760] Speed: 66.870233 samples/sec accuracy=81.296875 loss=0.737887 lr=0.001000 Epoch[079] Batch [0149]/[3760] Speed: 68.404231 samples/sec accuracy=80.854167 loss=0.750909 lr=0.001000 Epoch[079] Batch [0199]/[3760] Speed: 67.321474 samples/sec accuracy=80.679688 loss=0.749410 lr=0.001000 Epoch[079] Batch [0249]/[3760] Speed: 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lr=0.001000 Epoch[079] Batch [2649]/[3760] Speed: 67.788657 samples/sec accuracy=80.431604 loss=0.766397 lr=0.001000 Epoch[079] Batch [2699]/[3760] Speed: 68.578241 samples/sec accuracy=80.428819 loss=0.766088 lr=0.001000 Epoch[079] Batch [2749]/[3760] Speed: 67.840990 samples/sec accuracy=80.421591 loss=0.766230 lr=0.001000 Epoch[079] Batch [2799]/[3760] Speed: 67.940851 samples/sec accuracy=80.417411 loss=0.766457 lr=0.001000 Epoch[079] Batch [2849]/[3760] Speed: 67.893894 samples/sec accuracy=80.412281 loss=0.766741 lr=0.001000 Epoch[079] Batch [2899]/[3760] Speed: 67.505309 samples/sec accuracy=80.394935 loss=0.767756 lr=0.001000 Epoch[079] Batch [2949]/[3760] Speed: 68.005639 samples/sec accuracy=80.400953 loss=0.767658 lr=0.001000 Epoch[079] Batch [2999]/[3760] Speed: 68.655619 samples/sec accuracy=80.365625 loss=0.768538 lr=0.001000 Epoch[079] Batch [3049]/[3760] Speed: 67.508984 samples/sec accuracy=80.344775 loss=0.769424 lr=0.001000 Epoch[079] Batch [3099]/[3760] Speed: 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lr=0.001000 Epoch[079] Batch [3599]/[3760] Speed: 67.792370 samples/sec accuracy=80.317708 loss=0.771613 lr=0.001000 Epoch[079] Batch [3649]/[3760] Speed: 68.666730 samples/sec accuracy=80.290668 loss=0.772813 lr=0.001000 Epoch[079] Batch [3699]/[3760] Speed: 67.936984 samples/sec accuracy=80.291385 loss=0.773091 lr=0.001000 Epoch[079] Batch [3749]/[3760] Speed: 74.664644 samples/sec accuracy=80.267917 loss=0.773773 lr=0.000100 Batch [0049]/[0303]: acc-top1=65.593750 acc-top5=85.750000 Batch [0099]/[0303]: acc-top1=65.750000 acc-top5=85.562500 Batch [0149]/[0303]: acc-top1=66.239583 acc-top5=86.041667 Batch [0199]/[0303]: acc-top1=66.484375 acc-top5=86.164062 Batch [0249]/[0303]: acc-top1=66.468750 acc-top5=86.256250 Batch [0299]/[0303]: acc-top1=66.572917 acc-top5=86.307292 [Epoch 079] training: accuracy=80.270944 loss=0.773592 [Epoch 079] speed: 67 samples/sec time cost: 3833.432008 [Epoch 079] validation: acc-top1=66.599629 acc-top5=86.339728 loss=1.684037 Epoch[080] Batch 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accuracy=81.462500 loss=0.730004 lr=0.000100 Epoch[080] Batch [0549]/[3760] Speed: 68.434721 samples/sec accuracy=81.494318 loss=0.729160 lr=0.000100 Epoch[080] Batch [0599]/[3760] Speed: 67.723089 samples/sec accuracy=81.458333 loss=0.730463 lr=0.000100 Epoch[080] Batch [0649]/[3760] Speed: 67.789700 samples/sec accuracy=81.512019 loss=0.728114 lr=0.000100 Epoch[080] Batch [0699]/[3760] Speed: 68.014375 samples/sec accuracy=81.511161 loss=0.729053 lr=0.000100 Epoch[080] Batch [0749]/[3760] Speed: 67.776150 samples/sec accuracy=81.489583 loss=0.728422 lr=0.000100 Epoch[080] Batch [0799]/[3760] Speed: 67.720066 samples/sec accuracy=81.437500 loss=0.731159 lr=0.000100 Epoch[080] Batch [0849]/[3760] Speed: 68.670134 samples/sec accuracy=81.450368 loss=0.730555 lr=0.000100 Epoch[080] Batch [0899]/[3760] Speed: 67.804278 samples/sec accuracy=81.503472 loss=0.728938 lr=0.000100 Epoch[080] Batch [0949]/[3760] Speed: 67.975122 samples/sec accuracy=81.503289 loss=0.729728 lr=0.000100 Epoch[080] 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accuracy=81.550647 loss=0.726787 lr=0.000100 Epoch[080] Batch [1499]/[3760] Speed: 68.037690 samples/sec accuracy=81.553125 loss=0.726567 lr=0.000100 Epoch[080] Batch [1549]/[3760] Speed: 67.772984 samples/sec accuracy=81.587702 loss=0.725128 lr=0.000100 Epoch[080] Batch [1599]/[3760] Speed: 68.095379 samples/sec accuracy=81.577148 loss=0.724882 lr=0.000100 Epoch[080] Batch [1649]/[3760] Speed: 67.482750 samples/sec accuracy=81.600379 loss=0.724505 lr=0.000100 Epoch[080] Batch [1699]/[3760] Speed: 68.024750 samples/sec accuracy=81.591912 loss=0.724083 lr=0.000100 Epoch[080] Batch [1749]/[3760] Speed: 67.880735 samples/sec accuracy=81.604464 loss=0.723799 lr=0.000100 Epoch[080] Batch [1799]/[3760] Speed: 68.232637 samples/sec accuracy=81.625868 loss=0.722579 lr=0.000100 Epoch[080] Batch [1849]/[3760] Speed: 68.180014 samples/sec accuracy=81.652872 loss=0.721870 lr=0.000100 Epoch[080] Batch [1899]/[3760] Speed: 68.327498 samples/sec accuracy=81.689145 loss=0.721152 lr=0.000100 Epoch[080] Batch [1949]/[3760] Speed: 67.376820 samples/sec accuracy=81.681891 loss=0.721008 lr=0.000100 Epoch[080] Batch [1999]/[3760] Speed: 67.117892 samples/sec accuracy=81.678906 loss=0.720890 lr=0.000100 Epoch[080] Batch [2049]/[3760] Speed: 68.863381 samples/sec accuracy=81.702744 loss=0.720014 lr=0.000100 Epoch[080] Batch [2099]/[3760] Speed: 68.019648 samples/sec accuracy=81.692708 loss=0.720131 lr=0.000100 Epoch[080] Batch [2149]/[3760] Speed: 68.468343 samples/sec accuracy=81.659884 loss=0.720970 lr=0.000100 Epoch[080] Batch [2199]/[3760] Speed: 68.179421 samples/sec accuracy=81.685369 loss=0.719758 lr=0.000100 Epoch[080] Batch [2249]/[3760] Speed: 68.221065 samples/sec accuracy=81.684722 loss=0.720331 lr=0.000100 Epoch[080] Batch [2299]/[3760] Speed: 67.652899 samples/sec accuracy=81.723505 loss=0.719366 lr=0.000100 Epoch[080] Batch [2349]/[3760] Speed: 67.276063 samples/sec accuracy=81.734043 loss=0.719416 lr=0.000100 Epoch[080] Batch [2399]/[3760] Speed: 68.566997 samples/sec accuracy=81.750651 loss=0.718694 lr=0.000100 Epoch[080] Batch [2449]/[3760] Speed: 67.671820 samples/sec accuracy=81.759566 loss=0.718315 lr=0.000100 Epoch[080] Batch [2499]/[3760] Speed: 67.214672 samples/sec accuracy=81.768125 loss=0.718392 lr=0.000100 Epoch[080] Batch [2549]/[3760] Speed: 68.093393 samples/sec accuracy=81.756127 loss=0.718716 lr=0.000100 Epoch[080] Batch [2599]/[3760] Speed: 67.749800 samples/sec accuracy=81.760817 loss=0.718619 lr=0.000100 Epoch[080] Batch [2649]/[3760] Speed: 67.262809 samples/sec accuracy=81.764741 loss=0.718706 lr=0.000100 Epoch[080] Batch [2699]/[3760] Speed: 68.132986 samples/sec accuracy=81.776042 loss=0.717954 lr=0.000100 Epoch[080] Batch [2749]/[3760] Speed: 66.610553 samples/sec accuracy=81.800568 loss=0.717261 lr=0.000100 Epoch[080] Batch [2799]/[3760] Speed: 68.431890 samples/sec accuracy=81.811942 loss=0.717017 lr=0.000100 Epoch[080] Batch [2849]/[3760] Speed: 67.452669 samples/sec accuracy=81.809211 loss=0.716761 lr=0.000100 Epoch[080] Batch [2899]/[3760] Speed: 68.291461 samples/sec accuracy=81.825431 loss=0.715687 lr=0.000100 Epoch[080] Batch [2949]/[3760] Speed: 67.793768 samples/sec accuracy=81.825212 loss=0.715379 lr=0.000100 Epoch[080] Batch [2999]/[3760] Speed: 67.593023 samples/sec accuracy=81.823437 loss=0.715739 lr=0.000100 Epoch[080] Batch [3049]/[3760] Speed: 67.977302 samples/sec accuracy=81.838115 loss=0.715312 lr=0.000100 Epoch[080] Batch [3099]/[3760] Speed: 67.429816 samples/sec accuracy=81.851815 loss=0.714817 lr=0.000100 Epoch[080] Batch [3149]/[3760] Speed: 68.453891 samples/sec accuracy=81.851687 loss=0.715302 lr=0.000100 Epoch[080] Batch [3199]/[3760] Speed: 68.071476 samples/sec accuracy=81.838379 loss=0.715507 lr=0.000100 Epoch[080] Batch [3249]/[3760] Speed: 68.247780 samples/sec accuracy=81.839904 loss=0.715399 lr=0.000100 Epoch[080] Batch [3299]/[3760] Speed: 67.608724 samples/sec accuracy=81.861269 loss=0.714631 lr=0.000100 Epoch[080] Batch [3349]/[3760] Speed: 67.850837 samples/sec accuracy=81.854944 loss=0.714759 lr=0.000100 Epoch[080] Batch [3399]/[3760] Speed: 67.816583 samples/sec accuracy=81.878676 loss=0.714146 lr=0.000100 Epoch[080] Batch [3449]/[3760] Speed: 68.230367 samples/sec accuracy=81.877717 loss=0.714015 lr=0.000100 Epoch[080] Batch [3499]/[3760] Speed: 67.709642 samples/sec accuracy=81.878125 loss=0.713532 lr=0.000100 Epoch[080] Batch [3549]/[3760] Speed: 67.736874 samples/sec accuracy=81.881162 loss=0.713290 lr=0.000100 Epoch[080] Batch [3599]/[3760] Speed: 67.318916 samples/sec accuracy=81.869358 loss=0.713433 lr=0.000100 Epoch[080] Batch [3649]/[3760] Speed: 68.063061 samples/sec accuracy=81.859589 loss=0.713737 lr=0.000100 Epoch[080] Batch [3699]/[3760] Speed: 68.386691 samples/sec accuracy=81.858953 loss=0.713471 lr=0.000100 Epoch[080] Batch [3749]/[3760] Speed: 74.232702 samples/sec accuracy=81.865417 loss=0.713551 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.343750 acc-top5=85.968750 Batch [0099]/[0303]: acc-top1=67.281250 acc-top5=85.671875 Batch [0149]/[0303]: acc-top1=67.302083 acc-top5=86.145833 Batch [0199]/[0303]: acc-top1=67.476562 acc-top5=86.273438 Batch [0249]/[0303]: acc-top1=67.412500 acc-top5=86.293750 Batch [0299]/[0303]: acc-top1=67.562500 acc-top5=86.458333 [Epoch 080] training: accuracy=81.862949 loss=0.713642 [Epoch 080] speed: 67 samples/sec time cost: 3834.449348 [Epoch 080] validation: acc-top1=67.600041 acc-top5=86.494431 loss=1.642020 Epoch[081] Batch [0049]/[3759] Speed: 46.265316 samples/sec accuracy=81.156250 loss=0.737476 lr=0.000100 Epoch[081] Batch [0099]/[3759] Speed: 66.317686 samples/sec accuracy=81.796875 loss=0.713826 lr=0.000100 Epoch[081] Batch [0149]/[3759] Speed: 68.267505 samples/sec accuracy=82.104167 loss=0.710149 lr=0.000100 Epoch[081] Batch [0199]/[3759] Speed: 67.597051 samples/sec accuracy=82.187500 loss=0.709514 lr=0.000100 Epoch[081] Batch [0249]/[3759] Speed: 68.070591 samples/sec accuracy=82.131250 loss=0.710892 lr=0.000100 Epoch[081] Batch [0299]/[3759] 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loss=0.696966 lr=0.000100 Epoch[081] Batch [0799]/[3759] Speed: 67.907268 samples/sec accuracy=82.283203 loss=0.698529 lr=0.000100 Epoch[081] Batch [0849]/[3759] Speed: 68.101084 samples/sec accuracy=82.321691 loss=0.696941 lr=0.000100 Epoch[081] Batch [0899]/[3759] Speed: 68.189625 samples/sec accuracy=82.375000 loss=0.696189 lr=0.000100 Epoch[081] Batch [0949]/[3759] Speed: 67.569481 samples/sec accuracy=82.412829 loss=0.694242 lr=0.000100 Epoch[081] Batch [0999]/[3759] Speed: 68.088864 samples/sec accuracy=82.467188 loss=0.691926 lr=0.000100 Epoch[081] Batch [1049]/[3759] Speed: 68.193806 samples/sec accuracy=82.495536 loss=0.690051 lr=0.000100 Epoch[081] Batch [1099]/[3759] Speed: 67.172226 samples/sec accuracy=82.549716 loss=0.688650 lr=0.000100 Epoch[081] Batch [1149]/[3759] Speed: 67.611706 samples/sec accuracy=82.542120 loss=0.688487 lr=0.000100 Epoch[081] Batch [1199]/[3759] Speed: 67.952252 samples/sec accuracy=82.545573 loss=0.687960 lr=0.000100 Epoch[081] Batch 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accuracy=82.432904 loss=0.693309 lr=0.000100 Epoch[081] Batch [1749]/[3759] Speed: 67.920902 samples/sec accuracy=82.422321 loss=0.692335 lr=0.000100 Epoch[081] Batch [1799]/[3759] Speed: 68.227237 samples/sec accuracy=82.418403 loss=0.692217 lr=0.000100 Epoch[081] Batch [1849]/[3759] Speed: 67.637665 samples/sec accuracy=82.445101 loss=0.691070 lr=0.000100 Epoch[081] Batch [1899]/[3759] Speed: 67.674543 samples/sec accuracy=82.436678 loss=0.691086 lr=0.000100 Epoch[081] Batch [1949]/[3759] Speed: 68.173975 samples/sec accuracy=82.419872 loss=0.691611 lr=0.000100 Epoch[081] Batch [1999]/[3759] Speed: 68.120529 samples/sec accuracy=82.446094 loss=0.690373 lr=0.000100 Epoch[081] Batch [2049]/[3759] Speed: 68.184997 samples/sec accuracy=82.442073 loss=0.690894 lr=0.000100 Epoch[081] Batch [2099]/[3759] Speed: 67.802684 samples/sec accuracy=82.427083 loss=0.691638 lr=0.000100 Epoch[081] Batch [2149]/[3759] Speed: 67.664116 samples/sec accuracy=82.426599 loss=0.691241 lr=0.000100 Epoch[081] 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accuracy=82.390920 loss=0.691739 lr=0.000100 Epoch[081] Batch [2699]/[3759] Speed: 67.905236 samples/sec accuracy=82.407407 loss=0.690956 lr=0.000100 Epoch[081] Batch [2749]/[3759] Speed: 67.838452 samples/sec accuracy=82.404545 loss=0.691434 lr=0.000100 Epoch[081] Batch [2799]/[3759] Speed: 67.697154 samples/sec accuracy=82.410156 loss=0.691668 lr=0.000100 Epoch[081] Batch [2849]/[3759] Speed: 68.362108 samples/sec accuracy=82.402412 loss=0.691932 lr=0.000100 Epoch[081] Batch [2899]/[3759] Speed: 67.724715 samples/sec accuracy=82.386853 loss=0.692190 lr=0.000100 Epoch[081] Batch [2949]/[3759] Speed: 67.936233 samples/sec accuracy=82.391419 loss=0.692018 lr=0.000100 Epoch[081] Batch [2999]/[3759] Speed: 67.770342 samples/sec accuracy=82.379688 loss=0.692352 lr=0.000100 Epoch[081] Batch [3049]/[3759] Speed: 67.749624 samples/sec accuracy=82.385246 loss=0.692015 lr=0.000100 Epoch[081] Batch [3099]/[3759] Speed: 66.996111 samples/sec accuracy=82.393145 loss=0.691795 lr=0.000100 Epoch[081] 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accuracy=82.383247 loss=0.692103 lr=0.000100 Epoch[081] Batch [3649]/[3759] Speed: 68.805283 samples/sec accuracy=82.373288 loss=0.692221 lr=0.000100 Epoch[081] Batch [3699]/[3759] Speed: 67.920191 samples/sec accuracy=82.385135 loss=0.691602 lr=0.000100 Epoch[081] Batch [3749]/[3759] Speed: 74.824702 samples/sec accuracy=82.382083 loss=0.691833 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.031250 acc-top5=86.093750 Batch [0099]/[0303]: acc-top1=67.140625 acc-top5=85.781250 Batch [0149]/[0303]: acc-top1=67.291667 acc-top5=86.312500 Batch [0199]/[0303]: acc-top1=67.445312 acc-top5=86.429688 Batch [0249]/[0303]: acc-top1=67.443750 acc-top5=86.518750 Batch [0299]/[0303]: acc-top1=67.536458 acc-top5=86.651042 [Epoch 081] training: accuracy=82.380620 loss=0.691964 [Epoch 081] speed: 67 samples/sec time cost: 3832.485095 [Epoch 081] validation: acc-top1=67.553630 acc-top5=86.680074 loss=1.652702 Epoch[082] Batch [0049]/[3760] Speed: 45.389716 samples/sec accuracy=82.750000 loss=0.692426 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lr=0.000100 Epoch[082] Batch [1999]/[3760] Speed: 68.151234 samples/sec accuracy=82.406250 loss=0.692841 lr=0.000100 Epoch[082] Batch [2049]/[3760] Speed: 67.993183 samples/sec accuracy=82.398628 loss=0.693114 lr=0.000100 Epoch[082] Batch [2099]/[3760] Speed: 67.816965 samples/sec accuracy=82.380952 loss=0.693679 lr=0.000100 Epoch[082] Batch [2149]/[3760] Speed: 68.090339 samples/sec accuracy=82.396802 loss=0.693642 lr=0.000100 Epoch[082] Batch [2199]/[3760] Speed: 67.826624 samples/sec accuracy=82.380682 loss=0.694178 lr=0.000100 Epoch[082] Batch [2249]/[3760] Speed: 67.533295 samples/sec accuracy=82.388889 loss=0.693506 lr=0.000100 Epoch[082] Batch [2299]/[3760] Speed: 68.458542 samples/sec accuracy=82.396060 loss=0.693854 lr=0.000100 Epoch[082] Batch [2349]/[3760] Speed: 67.878888 samples/sec accuracy=82.412899 loss=0.692865 lr=0.000100 Epoch[082] Batch [2399]/[3760] Speed: 67.172470 samples/sec accuracy=82.453776 loss=0.691161 lr=0.000100 Epoch[082] Batch [2449]/[3760] Speed: 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lr=0.000100 Epoch[082] Batch [2949]/[3760] Speed: 68.425231 samples/sec accuracy=82.469280 loss=0.690551 lr=0.000100 Epoch[082] Batch [2999]/[3760] Speed: 68.189435 samples/sec accuracy=82.473958 loss=0.690552 lr=0.000100 Epoch[082] Batch [3049]/[3760] Speed: 67.504413 samples/sec accuracy=82.470799 loss=0.690489 lr=0.000100 Epoch[082] Batch [3099]/[3760] Speed: 68.054594 samples/sec accuracy=82.488407 loss=0.689883 lr=0.000100 Epoch[082] Batch [3149]/[3760] Speed: 67.100212 samples/sec accuracy=82.505952 loss=0.689567 lr=0.000100 Epoch[082] Batch [3199]/[3760] Speed: 68.116611 samples/sec accuracy=82.514160 loss=0.689378 lr=0.000100 Epoch[082] Batch [3249]/[3760] Speed: 67.889786 samples/sec accuracy=82.519231 loss=0.689562 lr=0.000100 Epoch[082] Batch [3299]/[3760] Speed: 67.583383 samples/sec accuracy=82.526989 loss=0.689492 lr=0.000100 Epoch[082] Batch [3349]/[3760] Speed: 68.161151 samples/sec accuracy=82.528451 loss=0.689382 lr=0.000100 Epoch[082] Batch [3399]/[3760] Speed: 68.583833 samples/sec accuracy=82.531250 loss=0.689000 lr=0.000100 Epoch[082] Batch [3449]/[3760] Speed: 67.037566 samples/sec accuracy=82.536685 loss=0.689156 lr=0.000100 Epoch[082] Batch [3499]/[3760] Speed: 67.820397 samples/sec accuracy=82.528571 loss=0.689439 lr=0.000100 Epoch[082] Batch [3549]/[3760] Speed: 68.255805 samples/sec accuracy=82.552377 loss=0.688676 lr=0.000100 Epoch[082] Batch [3599]/[3760] Speed: 67.942015 samples/sec accuracy=82.556424 loss=0.688445 lr=0.000100 Epoch[082] Batch [3649]/[3760] Speed: 67.897781 samples/sec accuracy=82.565497 loss=0.688219 lr=0.000100 Epoch[082] Batch [3699]/[3760] Speed: 67.779002 samples/sec accuracy=82.564189 loss=0.688170 lr=0.000100 Epoch[082] Batch [3749]/[3760] Speed: 74.220345 samples/sec accuracy=82.571667 loss=0.687703 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.687500 acc-top5=86.406250 Batch [0099]/[0303]: acc-top1=66.843750 acc-top5=85.984375 Batch [0149]/[0303]: acc-top1=67.052083 acc-top5=86.416667 Batch [0199]/[0303]: acc-top1=67.304688 acc-top5=86.445312 Batch [0249]/[0303]: acc-top1=67.281250 acc-top5=86.425000 Batch [0299]/[0303]: acc-top1=67.395833 acc-top5=86.666667 [Epoch 082] training: accuracy=82.568152 loss=0.687721 [Epoch 082] speed: 67 samples/sec time cost: 3835.079030 [Epoch 082] validation: acc-top1=67.440182 acc-top5=86.680074 loss=1.644888 Epoch[083] Batch [0049]/[3760] Speed: 45.893510 samples/sec accuracy=81.968750 loss=0.703898 lr=0.000100 Epoch[083] Batch [0099]/[3760] Speed: 66.889377 samples/sec accuracy=82.218750 loss=0.688184 lr=0.000100 Epoch[083] Batch [0149]/[3760] Speed: 68.786462 samples/sec accuracy=82.145833 loss=0.693816 lr=0.000100 Epoch[083] Batch [0199]/[3760] Speed: 67.620255 samples/sec accuracy=82.781250 loss=0.673468 lr=0.000100 Epoch[083] Batch [0249]/[3760] Speed: 67.398243 samples/sec accuracy=82.881250 loss=0.670901 lr=0.000100 Epoch[083] Batch [0299]/[3760] Speed: 68.148962 samples/sec accuracy=82.703125 loss=0.676232 lr=0.000100 Epoch[083] Batch 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accuracy=82.806641 loss=0.667706 lr=0.000100 Epoch[083] Batch [0849]/[3760] Speed: 67.532550 samples/sec accuracy=82.783088 loss=0.669515 lr=0.000100 Epoch[083] Batch [0899]/[3760] Speed: 67.301089 samples/sec accuracy=82.782986 loss=0.670182 lr=0.000100 Epoch[083] Batch [0949]/[3760] Speed: 68.073543 samples/sec accuracy=82.792763 loss=0.669934 lr=0.000100 Epoch[083] Batch [0999]/[3760] Speed: 67.523105 samples/sec accuracy=82.785937 loss=0.669255 lr=0.000100 Epoch[083] Batch [1049]/[3760] Speed: 68.383642 samples/sec accuracy=82.785714 loss=0.670409 lr=0.000100 Epoch[083] Batch [1099]/[3760] Speed: 67.800404 samples/sec accuracy=82.795455 loss=0.670723 lr=0.000100 Epoch[083] Batch [1149]/[3760] Speed: 68.250394 samples/sec accuracy=82.745924 loss=0.672666 lr=0.000100 Epoch[083] Batch [1199]/[3760] Speed: 67.934299 samples/sec accuracy=82.716146 loss=0.674270 lr=0.000100 Epoch[083] Batch [1249]/[3760] Speed: 67.824072 samples/sec accuracy=82.673750 loss=0.675882 lr=0.000100 Epoch[083] 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accuracy=82.626157 loss=0.681189 lr=0.000100 Epoch[083] Batch [2749]/[3760] Speed: 67.985133 samples/sec accuracy=82.622159 loss=0.681421 lr=0.000100 Epoch[083] Batch [2799]/[3760] Speed: 67.642799 samples/sec accuracy=82.621094 loss=0.681730 lr=0.000100 Epoch[083] Batch [2849]/[3760] Speed: 67.743611 samples/sec accuracy=82.640351 loss=0.681459 lr=0.000100 Epoch[083] Batch [2899]/[3760] Speed: 67.831108 samples/sec accuracy=82.656250 loss=0.681348 lr=0.000100 Epoch[083] Batch [2949]/[3760] Speed: 67.602385 samples/sec accuracy=82.665784 loss=0.681257 lr=0.000100 Epoch[083] Batch [2999]/[3760] Speed: 67.711183 samples/sec accuracy=82.675521 loss=0.681230 lr=0.000100 Epoch[083] Batch [3049]/[3760] Speed: 67.551428 samples/sec accuracy=82.677766 loss=0.680962 lr=0.000100 Epoch[083] Batch [3099]/[3760] Speed: 67.885244 samples/sec accuracy=82.675403 loss=0.681133 lr=0.000100 Epoch[083] Batch [3149]/[3760] Speed: 68.442098 samples/sec accuracy=82.669147 loss=0.681353 lr=0.000100 Epoch[083] 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accuracy=82.676370 loss=0.680854 lr=0.000100 Epoch[083] Batch [3699]/[3760] Speed: 68.002861 samples/sec accuracy=82.667652 loss=0.681016 lr=0.000100 Epoch[083] Batch [3749]/[3760] Speed: 74.498885 samples/sec accuracy=82.663750 loss=0.681120 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.125000 acc-top5=86.656250 Batch [0099]/[0303]: acc-top1=67.343750 acc-top5=86.125000 Batch [0149]/[0303]: acc-top1=67.510417 acc-top5=86.635417 Batch [0199]/[0303]: acc-top1=67.539062 acc-top5=86.671875 Batch [0249]/[0303]: acc-top1=67.525000 acc-top5=86.600000 Batch [0299]/[0303]: acc-top1=67.671875 acc-top5=86.786458 [Epoch 083] training: accuracy=82.662483 loss=0.681021 [Epoch 083] speed: 67 samples/sec time cost: 3834.065642 [Epoch 083] validation: acc-top1=67.698020 acc-top5=86.808993 loss=1.632543 Epoch[084] Batch [0049]/[3759] Speed: 45.937216 samples/sec accuracy=81.937500 loss=0.697608 lr=0.000100 Epoch[084] Batch [0099]/[3759] Speed: 66.681218 samples/sec accuracy=82.781250 loss=0.673310 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lr=0.000100 Epoch[084] Batch [1099]/[3759] Speed: 67.800154 samples/sec accuracy=82.829545 loss=0.678427 lr=0.000100 Epoch[084] Batch [1149]/[3759] Speed: 67.750117 samples/sec accuracy=82.807065 loss=0.678546 lr=0.000100 Epoch[084] Batch [1199]/[3759] Speed: 68.220518 samples/sec accuracy=82.864583 loss=0.676006 lr=0.000100 Epoch[084] Batch [1249]/[3759] Speed: 67.676421 samples/sec accuracy=82.892500 loss=0.674432 lr=0.000100 Epoch[084] Batch [1299]/[3759] Speed: 68.107256 samples/sec accuracy=82.872596 loss=0.674984 lr=0.000100 Epoch[084] Batch [1349]/[3759] Speed: 67.808523 samples/sec accuracy=82.905093 loss=0.674392 lr=0.000100 Epoch[084] Batch [1399]/[3759] Speed: 68.117784 samples/sec accuracy=82.925223 loss=0.674569 lr=0.000100 Epoch[084] Batch [1449]/[3759] Speed: 67.952572 samples/sec accuracy=82.942888 loss=0.674037 lr=0.000100 Epoch[084] Batch [1499]/[3759] Speed: 68.156919 samples/sec accuracy=82.940625 loss=0.674240 lr=0.000100 Epoch[084] Batch [1549]/[3759] Speed: 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lr=0.000100 Epoch[084] Batch [2049]/[3759] Speed: 68.069706 samples/sec accuracy=82.904726 loss=0.674549 lr=0.000100 Epoch[084] Batch [2099]/[3759] Speed: 68.363500 samples/sec accuracy=82.913690 loss=0.674802 lr=0.000100 Epoch[084] Batch [2149]/[3759] Speed: 67.993217 samples/sec accuracy=82.924419 loss=0.674166 lr=0.000100 Epoch[084] Batch [2199]/[3759] Speed: 67.488826 samples/sec accuracy=82.901278 loss=0.674655 lr=0.000100 Epoch[084] Batch [2249]/[3759] Speed: 68.192099 samples/sec accuracy=82.906944 loss=0.674950 lr=0.000100 Epoch[084] Batch [2299]/[3759] Speed: 67.961025 samples/sec accuracy=82.901495 loss=0.675131 lr=0.000100 Epoch[084] Batch [2349]/[3759] Speed: 67.719681 samples/sec accuracy=82.878989 loss=0.675789 lr=0.000100 Epoch[084] Batch [2399]/[3759] Speed: 68.451809 samples/sec accuracy=82.896484 loss=0.675571 lr=0.000100 Epoch[084] Batch [2449]/[3759] Speed: 68.233077 samples/sec accuracy=82.916454 loss=0.675045 lr=0.000100 Epoch[084] Batch [2499]/[3759] Speed: 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lr=0.000100 Epoch[084] Batch [2999]/[3759] Speed: 67.718935 samples/sec accuracy=82.897396 loss=0.675269 lr=0.000100 Epoch[084] Batch [3049]/[3759] Speed: 68.203826 samples/sec accuracy=82.906250 loss=0.674771 lr=0.000100 Epoch[084] Batch [3099]/[3759] Speed: 68.069501 samples/sec accuracy=82.890121 loss=0.674883 lr=0.000100 Epoch[084] Batch [3149]/[3759] Speed: 67.820739 samples/sec accuracy=82.900794 loss=0.674330 lr=0.000100 Epoch[084] Batch [3199]/[3759] Speed: 67.627438 samples/sec accuracy=82.903320 loss=0.674376 lr=0.000100 Epoch[084] Batch [3249]/[3759] Speed: 67.299977 samples/sec accuracy=82.902885 loss=0.674346 lr=0.000100 Epoch[084] Batch [3299]/[3759] Speed: 67.622817 samples/sec accuracy=82.892045 loss=0.674303 lr=0.000100 Epoch[084] Batch [3349]/[3759] Speed: 67.696368 samples/sec accuracy=82.899720 loss=0.674245 lr=0.000100 Epoch[084] Batch [3399]/[3759] Speed: 68.188812 samples/sec accuracy=82.896599 loss=0.674421 lr=0.000100 Epoch[084] Batch [3449]/[3759] Speed: 68.056516 samples/sec accuracy=82.894475 loss=0.674248 lr=0.000100 Epoch[084] Batch [3499]/[3759] Speed: 67.885443 samples/sec accuracy=82.902679 loss=0.673736 lr=0.000100 Epoch[084] Batch [3549]/[3759] Speed: 67.717171 samples/sec accuracy=82.912412 loss=0.673517 lr=0.000100 Epoch[084] Batch [3599]/[3759] Speed: 68.195388 samples/sec accuracy=82.903646 loss=0.673637 lr=0.000100 Epoch[084] Batch [3649]/[3759] Speed: 67.755419 samples/sec accuracy=82.905822 loss=0.673213 lr=0.000100 Epoch[084] Batch [3699]/[3759] Speed: 68.170290 samples/sec accuracy=82.896537 loss=0.673353 lr=0.000100 Epoch[084] Batch [3749]/[3759] Speed: 74.149916 samples/sec accuracy=82.900417 loss=0.673382 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.218750 acc-top5=86.218750 Batch [0099]/[0303]: acc-top1=67.281250 acc-top5=85.828125 Batch [0149]/[0303]: acc-top1=67.479167 acc-top5=86.302083 Batch [0199]/[0303]: acc-top1=67.656250 acc-top5=86.398438 Batch [0249]/[0303]: acc-top1=67.475000 acc-top5=86.425000 Batch [0299]/[0303]: acc-top1=67.541667 acc-top5=86.604167 [Epoch 084] training: accuracy=82.895218 loss=0.673495 [Epoch 084] speed: 67 samples/sec time cost: 3834.309705 [Epoch 084] validation: acc-top1=67.569101 acc-top5=86.638820 loss=1.645105 Epoch[085] Batch [0049]/[3760] Speed: 45.318912 samples/sec accuracy=81.531250 loss=0.705522 lr=0.000100 Epoch[085] Batch [0099]/[3760] Speed: 67.359935 samples/sec accuracy=82.796875 loss=0.681636 lr=0.000100 Epoch[085] Batch [0149]/[3760] Speed: 68.081490 samples/sec accuracy=82.604167 loss=0.681121 lr=0.000100 Epoch[085] Batch [0199]/[3760] Speed: 67.855767 samples/sec accuracy=82.757812 loss=0.679218 lr=0.000100 Epoch[085] Batch [0249]/[3760] Speed: 68.071072 samples/sec accuracy=82.793750 loss=0.672043 lr=0.000100 Epoch[085] Batch [0299]/[3760] Speed: 67.331712 samples/sec accuracy=82.838542 loss=0.669685 lr=0.000100 Epoch[085] Batch [0349]/[3760] Speed: 68.093285 samples/sec accuracy=82.781250 loss=0.672565 lr=0.000100 Epoch[085] Batch 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accuracy=82.847426 loss=0.672922 lr=0.000100 Epoch[085] Batch [0899]/[3760] Speed: 67.972302 samples/sec accuracy=82.795139 loss=0.675671 lr=0.000100 Epoch[085] Batch [0949]/[3760] Speed: 67.649781 samples/sec accuracy=82.843750 loss=0.674524 lr=0.000100 Epoch[085] Batch [0999]/[3760] Speed: 67.980930 samples/sec accuracy=82.853125 loss=0.674712 lr=0.000100 Epoch[085] Batch [1049]/[3760] Speed: 67.897939 samples/sec accuracy=82.894345 loss=0.673140 lr=0.000100 Epoch[085] Batch [1099]/[3760] Speed: 67.813350 samples/sec accuracy=82.855114 loss=0.674592 lr=0.000100 Epoch[085] Batch [1149]/[3760] Speed: 67.969404 samples/sec accuracy=82.853261 loss=0.675470 lr=0.000100 Epoch[085] Batch [1199]/[3760] Speed: 68.498843 samples/sec accuracy=82.847656 loss=0.676286 lr=0.000100 Epoch[085] Batch [1249]/[3760] Speed: 67.747507 samples/sec accuracy=82.798750 loss=0.678979 lr=0.000100 Epoch[085] Batch [1299]/[3760] Speed: 68.395075 samples/sec accuracy=82.844952 loss=0.677198 lr=0.000100 Epoch[085] 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accuracy=82.954861 loss=0.674225 lr=0.000100 Epoch[085] Batch [1849]/[3760] Speed: 68.081479 samples/sec accuracy=82.942568 loss=0.674660 lr=0.000100 Epoch[085] Batch [1899]/[3760] Speed: 68.038689 samples/sec accuracy=82.924342 loss=0.674825 lr=0.000100 Epoch[085] Batch [1949]/[3760] Speed: 68.213980 samples/sec accuracy=82.930288 loss=0.675270 lr=0.000100 Epoch[085] Batch [1999]/[3760] Speed: 67.132316 samples/sec accuracy=82.915625 loss=0.676159 lr=0.000100 Epoch[085] Batch [2049]/[3760] Speed: 68.671260 samples/sec accuracy=82.923780 loss=0.676342 lr=0.000100 Epoch[085] Batch [2099]/[3760] Speed: 67.547957 samples/sec accuracy=82.912946 loss=0.677082 lr=0.000100 Epoch[085] Batch [2149]/[3760] Speed: 68.073015 samples/sec accuracy=82.922965 loss=0.676378 lr=0.000100 Epoch[085] Batch [2199]/[3760] Speed: 67.512413 samples/sec accuracy=82.940341 loss=0.675472 lr=0.000100 Epoch[085] Batch [2249]/[3760] Speed: 68.162061 samples/sec accuracy=82.947917 loss=0.675587 lr=0.000100 Epoch[085] 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accuracy=82.943182 loss=0.673309 lr=0.000100 Epoch[085] Batch [2799]/[3760] Speed: 66.907335 samples/sec accuracy=82.941406 loss=0.673669 lr=0.000100 Epoch[085] Batch [2849]/[3760] Speed: 67.533097 samples/sec accuracy=82.945724 loss=0.673504 lr=0.000100 Epoch[085] Batch [2899]/[3760] Speed: 67.987822 samples/sec accuracy=82.946659 loss=0.673189 lr=0.000100 Epoch[085] Batch [2949]/[3760] Speed: 67.593466 samples/sec accuracy=82.933792 loss=0.674015 lr=0.000100 Epoch[085] Batch [2999]/[3760] Speed: 67.673523 samples/sec accuracy=82.943229 loss=0.673904 lr=0.000100 Epoch[085] Batch [3049]/[3760] Speed: 68.434873 samples/sec accuracy=82.932889 loss=0.674528 lr=0.000100 Epoch[085] Batch [3099]/[3760] Speed: 67.954472 samples/sec accuracy=82.931956 loss=0.674508 lr=0.000100 Epoch[085] Batch [3149]/[3760] Speed: 68.216451 samples/sec accuracy=82.948909 loss=0.673885 lr=0.000100 Epoch[085] Batch [3199]/[3760] Speed: 67.349892 samples/sec accuracy=82.931152 loss=0.673925 lr=0.000100 Epoch[085] 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accuracy=82.959459 loss=0.672177 lr=0.000100 Epoch[085] Batch [3749]/[3760] Speed: 74.825953 samples/sec accuracy=82.955833 loss=0.672280 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.156250 acc-top5=86.343750 Batch [0099]/[0303]: acc-top1=67.218750 acc-top5=86.125000 Batch [0149]/[0303]: acc-top1=67.437500 acc-top5=86.552083 Batch [0199]/[0303]: acc-top1=67.593750 acc-top5=86.578125 Batch [0249]/[0303]: acc-top1=67.556250 acc-top5=86.593750 Batch [0299]/[0303]: acc-top1=67.609375 acc-top5=86.760417 [Epoch 085] training: accuracy=82.958361 loss=0.672085 [Epoch 085] speed: 67 samples/sec time cost: 3834.719441 [Epoch 085] validation: acc-top1=67.625825 acc-top5=86.788366 loss=1.644930 Epoch[086] Batch [0049]/[3760] Speed: 45.607286 samples/sec accuracy=83.531250 loss=0.637631 lr=0.000100 Epoch[086] Batch [0099]/[3760] Speed: 66.753067 samples/sec accuracy=83.468750 loss=0.656149 lr=0.000100 Epoch[086] Batch [0149]/[3760] Speed: 68.410456 samples/sec accuracy=83.208333 loss=0.668094 lr=0.000100 Epoch[086] Batch [0199]/[3760] Speed: 66.989142 samples/sec accuracy=83.281250 loss=0.663749 lr=0.000100 Epoch[086] Batch [0249]/[3760] Speed: 68.457016 samples/sec accuracy=83.225000 loss=0.665707 lr=0.000100 Epoch[086] Batch [0299]/[3760] Speed: 67.690775 samples/sec accuracy=83.052083 loss=0.670564 lr=0.000100 Epoch[086] Batch [0349]/[3760] Speed: 67.795829 samples/sec accuracy=83.187500 loss=0.663732 lr=0.000100 Epoch[086] Batch [0399]/[3760] Speed: 67.949033 samples/sec accuracy=83.179688 loss=0.663091 lr=0.000100 Epoch[086] Batch [0449]/[3760] Speed: 67.372760 samples/sec accuracy=83.256944 loss=0.659362 lr=0.000100 Epoch[086] Batch [0499]/[3760] Speed: 68.202943 samples/sec accuracy=83.184375 loss=0.663573 lr=0.000100 Epoch[086] Batch [0549]/[3760] Speed: 68.479197 samples/sec accuracy=83.093750 loss=0.666193 lr=0.000100 Epoch[086] Batch [0599]/[3760] Speed: 67.470849 samples/sec accuracy=83.007812 loss=0.668089 lr=0.000100 Epoch[086] Batch [0649]/[3760] Speed: 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lr=0.000100 Epoch[086] Batch [1149]/[3760] Speed: 67.884951 samples/sec accuracy=82.953804 loss=0.669606 lr=0.000100 Epoch[086] Batch [1199]/[3760] Speed: 67.421162 samples/sec accuracy=82.953125 loss=0.670418 lr=0.000100 Epoch[086] Batch [1249]/[3760] Speed: 67.457377 samples/sec accuracy=82.970000 loss=0.669623 lr=0.000100 Epoch[086] Batch [1299]/[3760] Speed: 66.870885 samples/sec accuracy=83.012019 loss=0.667638 lr=0.000100 Epoch[086] Batch [1349]/[3760] Speed: 68.400712 samples/sec accuracy=83.013889 loss=0.666959 lr=0.000100 Epoch[086] Batch [1399]/[3760] Speed: 67.196961 samples/sec accuracy=83.020089 loss=0.666878 lr=0.000100 Epoch[086] Batch [1449]/[3760] Speed: 68.110214 samples/sec accuracy=82.993534 loss=0.667479 lr=0.000100 Epoch[086] Batch [1499]/[3760] Speed: 68.245694 samples/sec accuracy=83.022917 loss=0.666697 lr=0.000100 Epoch[086] Batch [1549]/[3760] Speed: 67.547391 samples/sec accuracy=82.974798 loss=0.668223 lr=0.000100 Epoch[086] Batch [1599]/[3760] Speed: 68.247538 samples/sec accuracy=82.955078 loss=0.668475 lr=0.000100 Epoch[086] Batch [1649]/[3760] Speed: 67.608405 samples/sec accuracy=82.960227 loss=0.668244 lr=0.000100 Epoch[086] Batch [1699]/[3760] Speed: 68.488966 samples/sec accuracy=82.926471 loss=0.669037 lr=0.000100 Epoch[086] Batch [1749]/[3760] Speed: 68.507267 samples/sec accuracy=82.928571 loss=0.668564 lr=0.000100 Epoch[086] Batch [1799]/[3760] Speed: 67.337281 samples/sec accuracy=82.933160 loss=0.668015 lr=0.000100 Epoch[086] Batch [1849]/[3760] Speed: 67.400847 samples/sec accuracy=82.950169 loss=0.667076 lr=0.000100 Epoch[086] Batch [1899]/[3760] Speed: 67.476432 samples/sec accuracy=82.939967 loss=0.667294 lr=0.000100 Epoch[086] Batch [1949]/[3760] Speed: 68.323657 samples/sec accuracy=82.944712 loss=0.667604 lr=0.000100 Epoch[086] Batch [1999]/[3760] Speed: 68.121627 samples/sec accuracy=82.949219 loss=0.667204 lr=0.000100 Epoch[086] Batch [2049]/[3760] Speed: 68.280962 samples/sec accuracy=82.939024 loss=0.667000 lr=0.000100 Epoch[086] Batch [2099]/[3760] Speed: 68.123553 samples/sec accuracy=82.963542 loss=0.665995 lr=0.000100 Epoch[086] Batch [2149]/[3760] Speed: 68.475194 samples/sec accuracy=82.982558 loss=0.665827 lr=0.000100 Epoch[086] Batch [2199]/[3760] Speed: 67.558185 samples/sec accuracy=82.966619 loss=0.666994 lr=0.000100 Epoch[086] Batch [2249]/[3760] Speed: 67.744994 samples/sec accuracy=82.961806 loss=0.667454 lr=0.000100 Epoch[086] Batch [2299]/[3760] Speed: 68.394886 samples/sec accuracy=82.966033 loss=0.667655 lr=0.000100 Epoch[086] Batch [2349]/[3760] Speed: 67.474021 samples/sec accuracy=82.964096 loss=0.667173 lr=0.000100 Epoch[086] Batch [2399]/[3760] Speed: 68.183177 samples/sec accuracy=82.947917 loss=0.667364 lr=0.000100 Epoch[086] Batch [2449]/[3760] Speed: 67.559396 samples/sec accuracy=82.935587 loss=0.667876 lr=0.000100 Epoch[086] Batch [2499]/[3760] Speed: 68.074249 samples/sec accuracy=82.961250 loss=0.667878 lr=0.000100 Epoch[086] Batch [2549]/[3760] Speed: 67.203239 samples/sec accuracy=82.979167 loss=0.666917 lr=0.000100 Epoch[086] Batch [2599]/[3760] Speed: 68.410181 samples/sec accuracy=82.980168 loss=0.667097 lr=0.000100 Epoch[086] Batch [2649]/[3760] Speed: 68.152013 samples/sec accuracy=82.977594 loss=0.667368 lr=0.000100 Epoch[086] Batch [2699]/[3760] Speed: 68.544789 samples/sec accuracy=82.973380 loss=0.667257 lr=0.000100 Epoch[086] Batch [2749]/[3760] Speed: 67.511157 samples/sec accuracy=82.982955 loss=0.667222 lr=0.000100 Epoch[086] Batch [2799]/[3760] Speed: 68.287026 samples/sec accuracy=82.973772 loss=0.667775 lr=0.000100 Epoch[086] Batch [2849]/[3760] Speed: 67.208863 samples/sec accuracy=82.975329 loss=0.668111 lr=0.000100 Epoch[086] Batch [2899]/[3760] Speed: 68.541282 samples/sec accuracy=82.975754 loss=0.667886 lr=0.000100 Epoch[086] Batch [2949]/[3760] Speed: 67.892711 samples/sec accuracy=82.959216 loss=0.668606 lr=0.000100 Epoch[086] Batch [2999]/[3760] Speed: 67.802166 samples/sec accuracy=82.950000 loss=0.668688 lr=0.000100 Epoch[086] Batch [3049]/[3760] Speed: 67.420316 samples/sec accuracy=82.935963 loss=0.669255 lr=0.000100 Epoch[086] Batch [3099]/[3760] Speed: 67.843720 samples/sec accuracy=82.930444 loss=0.669161 lr=0.000100 Epoch[086] Batch [3149]/[3760] Speed: 67.617056 samples/sec accuracy=82.927579 loss=0.669345 lr=0.000100 Epoch[086] Batch [3199]/[3760] Speed: 67.869087 samples/sec accuracy=82.915527 loss=0.670009 lr=0.000100 Epoch[086] Batch [3249]/[3760] Speed: 68.024930 samples/sec accuracy=82.916346 loss=0.669819 lr=0.000100 Epoch[086] Batch [3299]/[3760] Speed: 68.332729 samples/sec accuracy=82.928030 loss=0.669462 lr=0.000100 Epoch[086] Batch [3349]/[3760] Speed: 67.992864 samples/sec accuracy=82.934235 loss=0.669687 lr=0.000100 Epoch[086] Batch [3399]/[3760] Speed: 67.187522 samples/sec accuracy=82.940257 loss=0.669953 lr=0.000100 Epoch[086] Batch [3449]/[3760] Speed: 68.183192 samples/sec accuracy=82.947011 loss=0.669910 lr=0.000100 Epoch[086] Batch [3499]/[3760] Speed: 67.939812 samples/sec accuracy=82.941071 loss=0.669848 lr=0.000100 Epoch[086] Batch [3549]/[3760] Speed: 67.174303 samples/sec accuracy=82.958627 loss=0.669531 lr=0.000100 Epoch[086] Batch [3599]/[3760] Speed: 68.087636 samples/sec accuracy=82.953125 loss=0.669541 lr=0.000100 Epoch[086] Batch [3649]/[3760] Speed: 68.140139 samples/sec accuracy=82.963185 loss=0.669151 lr=0.000100 Epoch[086] Batch [3699]/[3760] Speed: 67.714485 samples/sec accuracy=82.959882 loss=0.669421 lr=0.000100 Epoch[086] Batch [3749]/[3760] Speed: 74.678118 samples/sec accuracy=82.977083 loss=0.668827 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.062500 acc-top5=86.500000 Batch [0099]/[0303]: acc-top1=67.187500 acc-top5=86.156250 Batch [0149]/[0303]: acc-top1=67.187500 acc-top5=86.500000 Batch [0199]/[0303]: acc-top1=67.312500 acc-top5=86.531250 Batch [0249]/[0303]: acc-top1=67.300000 acc-top5=86.537500 Batch [0299]/[0303]: acc-top1=67.442708 acc-top5=86.640625 [Epoch 086] training: accuracy=82.967088 loss=0.669148 [Epoch 086] speed: 67 samples/sec time cost: 3836.747562 [Epoch 086] validation: acc-top1=67.476279 acc-top5=86.674917 loss=1.662787 Epoch[087] Batch [0049]/[3759] Speed: 45.848215 samples/sec accuracy=83.625000 loss=0.652084 lr=0.000100 Epoch[087] Batch [0099]/[3759] Speed: 67.096873 samples/sec accuracy=83.453125 loss=0.667162 lr=0.000100 Epoch[087] Batch [0149]/[3759] Speed: 68.377848 samples/sec accuracy=83.645833 loss=0.664500 lr=0.000100 Epoch[087] Batch [0199]/[3759] Speed: 67.295363 samples/sec accuracy=83.632812 loss=0.657372 lr=0.000100 Epoch[087] Batch [0249]/[3759] Speed: 68.076634 samples/sec accuracy=83.712500 loss=0.652601 lr=0.000100 Epoch[087] Batch [0299]/[3759] Speed: 67.834654 samples/sec accuracy=83.895833 loss=0.645030 lr=0.000100 Epoch[087] Batch [0349]/[3759] Speed: 68.035687 samples/sec accuracy=83.656250 loss=0.648182 lr=0.000100 Epoch[087] Batch [0399]/[3759] Speed: 67.827079 samples/sec accuracy=83.636719 loss=0.648293 lr=0.000100 Epoch[087] Batch 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accuracy=83.286458 loss=0.660260 lr=0.000100 Epoch[087] Batch [0949]/[3759] Speed: 68.210255 samples/sec accuracy=83.312500 loss=0.659237 lr=0.000100 Epoch[087] Batch [0999]/[3759] Speed: 67.358242 samples/sec accuracy=83.317188 loss=0.658574 lr=0.000100 Epoch[087] Batch [1049]/[3759] Speed: 67.859411 samples/sec accuracy=83.327381 loss=0.658449 lr=0.000100 Epoch[087] Batch [1099]/[3759] Speed: 68.704442 samples/sec accuracy=83.335227 loss=0.657736 lr=0.000100 Epoch[087] Batch [1149]/[3759] Speed: 66.737089 samples/sec accuracy=83.309783 loss=0.658722 lr=0.000100 Epoch[087] Batch [1199]/[3759] Speed: 68.706467 samples/sec accuracy=83.324219 loss=0.657658 lr=0.000100 Epoch[087] Batch [1249]/[3759] Speed: 67.762540 samples/sec accuracy=83.292500 loss=0.657670 lr=0.000100 Epoch[087] Batch [1299]/[3759] Speed: 68.569379 samples/sec accuracy=83.302885 loss=0.658192 lr=0.000100 Epoch[087] Batch [1349]/[3759] Speed: 67.397487 samples/sec accuracy=83.288194 loss=0.658985 lr=0.000100 Epoch[087] 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accuracy=83.250000 loss=0.660343 lr=0.000100 Epoch[087] Batch [1899]/[3759] Speed: 68.402993 samples/sec accuracy=83.222862 loss=0.660891 lr=0.000100 Epoch[087] Batch [1949]/[3759] Speed: 67.967829 samples/sec accuracy=83.209135 loss=0.661566 lr=0.000100 Epoch[087] Batch [1999]/[3759] Speed: 68.394690 samples/sec accuracy=83.203906 loss=0.661719 lr=0.000100 Epoch[087] Batch [2049]/[3759] Speed: 68.136609 samples/sec accuracy=83.205030 loss=0.661465 lr=0.000100 Epoch[087] Batch [2099]/[3759] Speed: 68.006718 samples/sec accuracy=83.234375 loss=0.661088 lr=0.000100 Epoch[087] Batch [2149]/[3759] Speed: 68.139755 samples/sec accuracy=83.246366 loss=0.661108 lr=0.000100 Epoch[087] Batch [2199]/[3759] Speed: 67.825626 samples/sec accuracy=83.241477 loss=0.661468 lr=0.000100 Epoch[087] Batch [2249]/[3759] Speed: 68.377853 samples/sec accuracy=83.231250 loss=0.661541 lr=0.000100 Epoch[087] Batch [2299]/[3759] Speed: 67.719679 samples/sec accuracy=83.233696 loss=0.661681 lr=0.000100 Epoch[087] 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accuracy=83.206473 loss=0.662749 lr=0.000100 Epoch[087] Batch [2849]/[3759] Speed: 68.294974 samples/sec accuracy=83.222039 loss=0.662315 lr=0.000100 Epoch[087] Batch [2899]/[3759] Speed: 67.712506 samples/sec accuracy=83.227371 loss=0.661792 lr=0.000100 Epoch[087] Batch [2949]/[3759] Speed: 67.956236 samples/sec accuracy=83.200742 loss=0.662906 lr=0.000100 Epoch[087] Batch [2999]/[3759] Speed: 67.921334 samples/sec accuracy=83.202083 loss=0.662931 lr=0.000100 Epoch[087] Batch [3049]/[3759] Speed: 67.658978 samples/sec accuracy=83.209529 loss=0.663003 lr=0.000100 Epoch[087] Batch [3099]/[3759] Speed: 67.954026 samples/sec accuracy=83.222278 loss=0.662536 lr=0.000100 Epoch[087] Batch [3149]/[3759] Speed: 67.751457 samples/sec accuracy=83.237103 loss=0.661994 lr=0.000100 Epoch[087] Batch [3199]/[3759] Speed: 67.706468 samples/sec accuracy=83.235352 loss=0.661842 lr=0.000100 Epoch[087] Batch [3249]/[3759] Speed: 67.607258 samples/sec accuracy=83.222596 loss=0.662401 lr=0.000100 Epoch[087] 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accuracy=83.207083 loss=0.663657 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.406250 acc-top5=86.406250 Batch [0099]/[0303]: acc-top1=67.296875 acc-top5=85.890625 Batch [0149]/[0303]: acc-top1=67.395833 acc-top5=86.364583 Batch [0199]/[0303]: acc-top1=67.492188 acc-top5=86.359375 Batch [0249]/[0303]: acc-top1=67.412500 acc-top5=86.356250 Batch [0299]/[0303]: acc-top1=67.494792 acc-top5=86.510417 [Epoch 087] training: accuracy=83.209048 loss=0.663585 [Epoch 087] speed: 67 samples/sec time cost: 3829.646300 [Epoch 087] validation: acc-top1=67.527847 acc-top5=86.530528 loss=1.657099 Epoch[088] Batch [0049]/[3760] Speed: 45.717001 samples/sec accuracy=81.812500 loss=0.711916 lr=0.000100 Epoch[088] Batch [0099]/[3760] Speed: 66.152120 samples/sec accuracy=83.140625 loss=0.678452 lr=0.000100 Epoch[088] Batch [0149]/[3760] Speed: 68.068780 samples/sec accuracy=83.041667 loss=0.674405 lr=0.000100 Epoch[088] Batch [0199]/[3760] Speed: 67.844495 samples/sec accuracy=83.148438 loss=0.665754 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lr=0.000100 Epoch[088] Batch [2149]/[3760] Speed: 67.938446 samples/sec accuracy=83.239099 loss=0.662256 lr=0.000100 Epoch[088] Batch [2199]/[3760] Speed: 68.249475 samples/sec accuracy=83.241477 loss=0.661908 lr=0.000100 Epoch[088] Batch [2249]/[3760] Speed: 67.684827 samples/sec accuracy=83.259722 loss=0.661255 lr=0.000100 Epoch[088] Batch [2299]/[3760] Speed: 68.108689 samples/sec accuracy=83.224185 loss=0.662105 lr=0.000100 Epoch[088] Batch [2349]/[3760] Speed: 67.674607 samples/sec accuracy=83.232713 loss=0.661748 lr=0.000100 Epoch[088] Batch [2399]/[3760] Speed: 68.069596 samples/sec accuracy=83.208333 loss=0.663195 lr=0.000100 Epoch[088] Batch [2449]/[3760] Speed: 67.816959 samples/sec accuracy=83.227679 loss=0.662232 lr=0.000100 Epoch[088] Batch [2499]/[3760] Speed: 68.119122 samples/sec accuracy=83.221875 loss=0.662585 lr=0.000100 Epoch[088] Batch [2549]/[3760] Speed: 67.496211 samples/sec accuracy=83.245098 loss=0.661751 lr=0.000100 Epoch[088] Batch [2599]/[3760] Speed: 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lr=0.000100 Epoch[088] Batch [3099]/[3760] Speed: 67.935899 samples/sec accuracy=83.235887 loss=0.661973 lr=0.000100 Epoch[088] Batch [3149]/[3760] Speed: 67.226670 samples/sec accuracy=83.243552 loss=0.661822 lr=0.000100 Epoch[088] Batch [3199]/[3760] Speed: 68.502921 samples/sec accuracy=83.256836 loss=0.661210 lr=0.000100 Epoch[088] Batch [3249]/[3760] Speed: 68.547209 samples/sec accuracy=83.262500 loss=0.661200 lr=0.000100 Epoch[088] Batch [3299]/[3760] Speed: 67.703390 samples/sec accuracy=83.255208 loss=0.661118 lr=0.000100 Epoch[088] Batch [3349]/[3760] Speed: 68.062514 samples/sec accuracy=83.271455 loss=0.660871 lr=0.000100 Epoch[088] Batch [3399]/[3760] Speed: 67.353337 samples/sec accuracy=83.265165 loss=0.660702 lr=0.000100 Epoch[088] Batch [3449]/[3760] Speed: 68.459123 samples/sec accuracy=83.256341 loss=0.660939 lr=0.000100 Epoch[088] Batch [3499]/[3760] Speed: 67.962335 samples/sec accuracy=83.266071 loss=0.660531 lr=0.000100 Epoch[088] Batch [3549]/[3760] Speed: 67.725276 samples/sec accuracy=83.252201 loss=0.660885 lr=0.000100 Epoch[088] Batch [3599]/[3760] Speed: 68.691711 samples/sec accuracy=83.269097 loss=0.660383 lr=0.000100 Epoch[088] Batch [3649]/[3760] Speed: 67.724165 samples/sec accuracy=83.250428 loss=0.661013 lr=0.000100 Epoch[088] Batch [3699]/[3760] Speed: 67.341254 samples/sec accuracy=83.257601 loss=0.660858 lr=0.000100 Epoch[088] Batch [3749]/[3760] Speed: 74.344704 samples/sec accuracy=83.245000 loss=0.661401 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.031250 acc-top5=86.156250 Batch [0099]/[0303]: acc-top1=67.156250 acc-top5=85.937500 Batch [0149]/[0303]: acc-top1=67.312500 acc-top5=86.395833 Batch [0199]/[0303]: acc-top1=67.531250 acc-top5=86.328125 Batch [0249]/[0303]: acc-top1=67.543750 acc-top5=86.425000 Batch [0299]/[0303]: acc-top1=67.661458 acc-top5=86.609375 [Epoch 088] training: accuracy=83.249252 loss=0.661249 [Epoch 088] speed: 67 samples/sec time cost: 3833.908590 [Epoch 088] validation: acc-top1=67.703177 acc-top5=86.643977 loss=1.657210 Epoch[089] Batch [0049]/[3760] Speed: 46.297320 samples/sec accuracy=83.500000 loss=0.662261 lr=0.000100 Epoch[089] Batch [0099]/[3760] Speed: 66.621341 samples/sec accuracy=83.531250 loss=0.656060 lr=0.000100 Epoch[089] Batch [0149]/[3760] Speed: 68.795192 samples/sec accuracy=83.552083 loss=0.648044 lr=0.000100 Epoch[089] Batch [0199]/[3760] Speed: 67.709455 samples/sec accuracy=83.570312 loss=0.648704 lr=0.000100 Epoch[089] Batch [0249]/[3760] Speed: 68.136336 samples/sec accuracy=83.487500 loss=0.651343 lr=0.000100 Epoch[089] Batch [0299]/[3760] Speed: 67.644823 samples/sec accuracy=83.578125 loss=0.649382 lr=0.000100 Epoch[089] Batch [0349]/[3760] Speed: 68.184852 samples/sec accuracy=83.575893 loss=0.646300 lr=0.000100 Epoch[089] Batch [0399]/[3760] Speed: 68.078946 samples/sec accuracy=83.554688 loss=0.645184 lr=0.000100 Epoch[089] Batch [0449]/[3760] Speed: 67.553001 samples/sec accuracy=83.503472 loss=0.648118 lr=0.000100 Epoch[089] Batch 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accuracy=83.225329 loss=0.654192 lr=0.000100 Epoch[089] Batch [0999]/[3760] Speed: 67.516615 samples/sec accuracy=83.225000 loss=0.654790 lr=0.000100 Epoch[089] Batch [1049]/[3760] Speed: 67.615647 samples/sec accuracy=83.184524 loss=0.655675 lr=0.000100 Epoch[089] Batch [1099]/[3760] Speed: 67.728806 samples/sec accuracy=83.232955 loss=0.653308 lr=0.000100 Epoch[089] Batch [1149]/[3760] Speed: 68.165706 samples/sec accuracy=83.264946 loss=0.652391 lr=0.000100 Epoch[089] Batch [1199]/[3760] Speed: 68.244664 samples/sec accuracy=83.268229 loss=0.652399 lr=0.000100 Epoch[089] Batch [1249]/[3760] Speed: 68.221185 samples/sec accuracy=83.271250 loss=0.651721 lr=0.000100 Epoch[089] Batch [1299]/[3760] Speed: 67.897513 samples/sec accuracy=83.274038 loss=0.652076 lr=0.000100 Epoch[089] Batch [1349]/[3760] Speed: 68.383696 samples/sec accuracy=83.271991 loss=0.651747 lr=0.000100 Epoch[089] Batch [1399]/[3760] Speed: 68.261962 samples/sec accuracy=83.228795 loss=0.653237 lr=0.000100 Epoch[089] 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accuracy=83.263706 loss=0.657437 lr=0.000100 Epoch[089] Batch [2899]/[3760] Speed: 67.985270 samples/sec accuracy=83.251616 loss=0.657717 lr=0.000100 Epoch[089] Batch [2949]/[3760] Speed: 68.221998 samples/sec accuracy=83.243114 loss=0.657667 lr=0.000100 Epoch[089] Batch [2999]/[3760] Speed: 68.384774 samples/sec accuracy=83.229688 loss=0.658205 lr=0.000100 Epoch[089] Batch [3049]/[3760] Speed: 67.413831 samples/sec accuracy=83.230533 loss=0.657795 lr=0.000100 Epoch[089] Batch [3099]/[3760] Speed: 67.527347 samples/sec accuracy=83.247984 loss=0.657534 lr=0.000100 Epoch[089] Batch [3149]/[3760] Speed: 67.958328 samples/sec accuracy=83.250496 loss=0.657891 lr=0.000100 Epoch[089] Batch [3199]/[3760] Speed: 67.845132 samples/sec accuracy=83.234863 loss=0.658506 lr=0.000100 Epoch[089] Batch [3249]/[3760] Speed: 68.007488 samples/sec accuracy=83.231250 loss=0.658870 lr=0.000100 Epoch[089] Batch [3299]/[3760] Speed: 67.832913 samples/sec accuracy=83.214015 loss=0.659566 lr=0.000100 Epoch[089] 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[0099]/[0303]: acc-top1=66.984375 acc-top5=85.937500 Batch [0149]/[0303]: acc-top1=67.125000 acc-top5=86.364583 Batch [0199]/[0303]: acc-top1=67.421875 acc-top5=86.335938 Batch [0249]/[0303]: acc-top1=67.425000 acc-top5=86.400000 Batch [0299]/[0303]: acc-top1=67.494792 acc-top5=86.515625 [Epoch 089] training: accuracy=83.216423 loss=0.659714 [Epoch 089] speed: 67 samples/sec time cost: 3830.481584 [Epoch 089] validation: acc-top1=67.548474 acc-top5=86.545998 loss=1.663466 Epoch[090] Batch [0049]/[3759] Speed: 45.622767 samples/sec accuracy=84.437500 loss=0.617822 lr=0.000100 Epoch[090] Batch [0099]/[3759] Speed: 66.877743 samples/sec accuracy=83.718750 loss=0.630353 lr=0.000100 Epoch[090] Batch [0149]/[3759] Speed: 68.254485 samples/sec accuracy=83.625000 loss=0.642232 lr=0.000100 Epoch[090] Batch [0199]/[3759] Speed: 67.941945 samples/sec accuracy=83.867188 loss=0.640347 lr=0.000100 Epoch[090] Batch [0249]/[3759] Speed: 67.733882 samples/sec accuracy=83.800000 loss=0.640050 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lr=0.000100 Epoch[090] Batch [1249]/[3759] Speed: 68.785337 samples/sec accuracy=83.360000 loss=0.655367 lr=0.000100 Epoch[090] Batch [1299]/[3759] Speed: 68.267348 samples/sec accuracy=83.288462 loss=0.657674 lr=0.000100 Epoch[090] Batch [1349]/[3759] Speed: 67.874000 samples/sec accuracy=83.310185 loss=0.657088 lr=0.000100 Epoch[090] Batch [1399]/[3759] Speed: 68.216876 samples/sec accuracy=83.344866 loss=0.656347 lr=0.000100 Epoch[090] Batch [1449]/[3759] Speed: 68.000180 samples/sec accuracy=83.363147 loss=0.656187 lr=0.000100 Epoch[090] Batch [1499]/[3759] Speed: 67.381732 samples/sec accuracy=83.397917 loss=0.654490 lr=0.000100 Epoch[090] Batch [1549]/[3759] Speed: 68.277390 samples/sec accuracy=83.406250 loss=0.654256 lr=0.000100 Epoch[090] Batch [1599]/[3759] Speed: 67.680293 samples/sec accuracy=83.451172 loss=0.652766 lr=0.000100 Epoch[090] Batch [1649]/[3759] Speed: 67.663976 samples/sec accuracy=83.433712 loss=0.654157 lr=0.000100 Epoch[090] Batch [1699]/[3759] Speed: 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lr=0.000100 Epoch[090] Batch [2199]/[3759] Speed: 67.738748 samples/sec accuracy=83.409801 loss=0.655487 lr=0.000100 Epoch[090] Batch [2249]/[3759] Speed: 67.960179 samples/sec accuracy=83.409722 loss=0.655256 lr=0.000100 Epoch[090] Batch [2299]/[3759] Speed: 68.141944 samples/sec accuracy=83.406929 loss=0.654243 lr=0.000100 Epoch[090] Batch [2349]/[3759] Speed: 68.403708 samples/sec accuracy=83.409574 loss=0.654341 lr=0.000100 Epoch[090] Batch [2399]/[3759] Speed: 67.637518 samples/sec accuracy=83.408203 loss=0.654252 lr=0.000100 Epoch[090] Batch [2449]/[3759] Speed: 68.175750 samples/sec accuracy=83.394770 loss=0.654642 lr=0.000100 Epoch[090] Batch [2499]/[3759] Speed: 67.552662 samples/sec accuracy=83.391875 loss=0.654627 lr=0.000100 Epoch[090] Batch [2549]/[3759] Speed: 67.492599 samples/sec accuracy=83.401961 loss=0.654615 lr=0.000100 Epoch[090] Batch [2599]/[3759] Speed: 68.227841 samples/sec accuracy=83.397837 loss=0.654474 lr=0.000100 Epoch[090] Batch [2649]/[3759] Speed: 67.831980 samples/sec accuracy=83.390330 loss=0.654841 lr=0.000100 Epoch[090] Batch [2699]/[3759] Speed: 67.647788 samples/sec accuracy=83.403935 loss=0.654644 lr=0.000100 Epoch[090] Batch [2749]/[3759] Speed: 68.258693 samples/sec accuracy=83.394318 loss=0.654905 lr=0.000100 Epoch[090] Batch [2799]/[3759] Speed: 67.920335 samples/sec accuracy=83.405692 loss=0.654555 lr=0.000100 Epoch[090] Batch [2849]/[3759] Speed: 67.831991 samples/sec accuracy=83.397478 loss=0.654300 lr=0.000100 Epoch[090] Batch [2899]/[3759] Speed: 68.322578 samples/sec accuracy=83.397091 loss=0.654558 lr=0.000100 Epoch[090] Batch [2949]/[3759] Speed: 68.045085 samples/sec accuracy=83.393538 loss=0.654532 lr=0.000100 Epoch[090] Batch [2999]/[3759] Speed: 68.220880 samples/sec accuracy=83.404687 loss=0.654032 lr=0.000100 Epoch[090] Batch [3049]/[3759] Speed: 67.660469 samples/sec accuracy=83.402664 loss=0.654090 lr=0.000100 Epoch[090] Batch [3099]/[3759] Speed: 67.667335 samples/sec accuracy=83.373992 loss=0.655180 lr=0.000100 Epoch[090] Batch [3149]/[3759] Speed: 68.154680 samples/sec accuracy=83.372520 loss=0.654999 lr=0.000100 Epoch[090] Batch [3199]/[3759] Speed: 68.171962 samples/sec accuracy=83.362793 loss=0.654878 lr=0.000100 Epoch[090] Batch [3249]/[3759] Speed: 68.321143 samples/sec accuracy=83.363462 loss=0.654736 lr=0.000100 Epoch[090] Batch [3299]/[3759] Speed: 67.700013 samples/sec accuracy=83.349432 loss=0.654906 lr=0.000100 Epoch[090] Batch [3349]/[3759] Speed: 68.370813 samples/sec accuracy=83.342817 loss=0.655101 lr=0.000100 Epoch[090] Batch [3399]/[3759] Speed: 68.643196 samples/sec accuracy=83.342831 loss=0.655350 lr=0.000100 Epoch[090] Batch [3449]/[3759] Speed: 67.876674 samples/sec accuracy=83.352355 loss=0.655073 lr=0.000100 Epoch[090] Batch [3499]/[3759] Speed: 68.510770 samples/sec accuracy=83.335714 loss=0.655220 lr=0.000100 Epoch[090] Batch [3549]/[3759] Speed: 67.394131 samples/sec accuracy=83.348592 loss=0.654624 lr=0.000100 Epoch[090] Batch [3599]/[3759] Speed: 68.052834 samples/sec accuracy=83.343750 loss=0.654532 lr=0.000100 Epoch[090] Batch [3649]/[3759] Speed: 67.409001 samples/sec accuracy=83.348459 loss=0.654433 lr=0.000100 Epoch[090] Batch [3699]/[3759] Speed: 68.349775 samples/sec accuracy=83.356841 loss=0.654224 lr=0.000100 Epoch[090] Batch [3749]/[3759] Speed: 75.019307 samples/sec accuracy=83.349167 loss=0.654516 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.250000 acc-top5=86.468750 Batch [0099]/[0303]: acc-top1=67.500000 acc-top5=86.000000 Batch [0149]/[0303]: acc-top1=67.500000 acc-top5=86.479167 Batch [0199]/[0303]: acc-top1=67.664062 acc-top5=86.453125 Batch [0249]/[0303]: acc-top1=67.512500 acc-top5=86.487500 Batch [0299]/[0303]: acc-top1=67.661458 acc-top5=86.625000 [Epoch 090] training: accuracy=83.346635 loss=0.654506 [Epoch 090] speed: 67 samples/sec time cost: 3828.200874 [Epoch 090] validation: acc-top1=67.687706 acc-top5=86.649134 loss=1.648968 Epoch[091] Batch [0049]/[3760] Speed: 45.887190 samples/sec accuracy=83.156250 loss=0.646026 lr=0.000100 Epoch[091] Batch [0099]/[3760] Speed: 66.695668 samples/sec accuracy=83.390625 loss=0.647675 lr=0.000100 Epoch[091] Batch [0149]/[3760] Speed: 68.504166 samples/sec accuracy=83.645833 loss=0.646769 lr=0.000100 Epoch[091] Batch [0199]/[3760] Speed: 68.502693 samples/sec accuracy=83.765625 loss=0.645131 lr=0.000100 Epoch[091] Batch [0249]/[3760] Speed: 67.190685 samples/sec accuracy=83.781250 loss=0.644620 lr=0.000100 Epoch[091] Batch [0299]/[3760] Speed: 68.441377 samples/sec accuracy=83.671875 loss=0.648517 lr=0.000100 Epoch[091] Batch [0349]/[3760] Speed: 67.743678 samples/sec accuracy=83.691964 loss=0.648402 lr=0.000100 Epoch[091] Batch [0399]/[3760] Speed: 67.762350 samples/sec accuracy=83.675781 loss=0.648987 lr=0.000100 Epoch[091] Batch [0449]/[3760] Speed: 68.071587 samples/sec accuracy=83.642361 loss=0.650748 lr=0.000100 Epoch[091] Batch [0499]/[3760] Speed: 67.737600 samples/sec accuracy=83.550000 loss=0.651982 lr=0.000100 Epoch[091] 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accuracy=83.162500 loss=0.660019 lr=0.000100 Epoch[091] Batch [1049]/[3760] Speed: 68.078013 samples/sec accuracy=83.181548 loss=0.659217 lr=0.000100 Epoch[091] Batch [1099]/[3760] Speed: 67.771129 samples/sec accuracy=83.193182 loss=0.660048 lr=0.000100 Epoch[091] Batch [1149]/[3760] Speed: 68.118636 samples/sec accuracy=83.254076 loss=0.658052 lr=0.000100 Epoch[091] Batch [1199]/[3760] Speed: 67.604519 samples/sec accuracy=83.240885 loss=0.658477 lr=0.000100 Epoch[091] Batch [1249]/[3760] Speed: 68.956951 samples/sec accuracy=83.252500 loss=0.657927 lr=0.000100 Epoch[091] Batch [1299]/[3760] Speed: 67.994492 samples/sec accuracy=83.322115 loss=0.656619 lr=0.000100 Epoch[091] Batch [1349]/[3760] Speed: 68.012992 samples/sec accuracy=83.321759 loss=0.657536 lr=0.000100 Epoch[091] Batch [1399]/[3760] Speed: 67.084665 samples/sec accuracy=83.340402 loss=0.656822 lr=0.000100 Epoch[091] Batch [1449]/[3760] Speed: 68.341454 samples/sec accuracy=83.329741 loss=0.656879 lr=0.000100 Epoch[091] 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accuracy=83.325321 loss=0.654659 lr=0.000100 Epoch[091] Batch [1999]/[3760] Speed: 66.900938 samples/sec accuracy=83.352344 loss=0.653916 lr=0.000100 Epoch[091] Batch [2049]/[3760] Speed: 68.666827 samples/sec accuracy=83.317835 loss=0.655036 lr=0.000100 Epoch[091] Batch [2099]/[3760] Speed: 67.990681 samples/sec accuracy=83.308036 loss=0.655350 lr=0.000100 Epoch[091] Batch [2149]/[3760] Speed: 68.239762 samples/sec accuracy=83.300145 loss=0.655254 lr=0.000100 Epoch[091] Batch [2199]/[3760] Speed: 67.789339 samples/sec accuracy=83.301847 loss=0.655243 lr=0.000100 Epoch[091] Batch [2249]/[3760] Speed: 67.648655 samples/sec accuracy=83.320833 loss=0.655105 lr=0.000100 Epoch[091] Batch [2299]/[3760] Speed: 67.776958 samples/sec accuracy=83.326766 loss=0.654575 lr=0.000100 Epoch[091] Batch [2349]/[3760] Speed: 67.976342 samples/sec accuracy=83.336436 loss=0.654134 lr=0.000100 Epoch[091] Batch [2399]/[3760] Speed: 68.359159 samples/sec accuracy=83.339844 loss=0.654228 lr=0.000100 Epoch[091] 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accuracy=83.326509 loss=0.654185 lr=0.000100 Epoch[091] Batch [2949]/[3760] Speed: 67.990464 samples/sec accuracy=83.310381 loss=0.654668 lr=0.000100 Epoch[091] Batch [2999]/[3760] Speed: 67.789936 samples/sec accuracy=83.315625 loss=0.654751 lr=0.000100 Epoch[091] Batch [3049]/[3760] Speed: 68.291835 samples/sec accuracy=83.313012 loss=0.654827 lr=0.000100 Epoch[091] Batch [3099]/[3760] Speed: 67.195652 samples/sec accuracy=83.330141 loss=0.654109 lr=0.000100 Epoch[091] Batch [3149]/[3760] Speed: 68.094614 samples/sec accuracy=83.328869 loss=0.653830 lr=0.000100 Epoch[091] Batch [3199]/[3760] Speed: 68.087035 samples/sec accuracy=83.339355 loss=0.653362 lr=0.000100 Epoch[091] Batch [3249]/[3760] Speed: 68.504921 samples/sec accuracy=83.338462 loss=0.653177 lr=0.000100 Epoch[091] Batch [3299]/[3760] Speed: 68.014727 samples/sec accuracy=83.316761 loss=0.653863 lr=0.000100 Epoch[091] Batch [3349]/[3760] Speed: 67.874386 samples/sec accuracy=83.321362 loss=0.654225 lr=0.000100 Epoch[091] Batch [3399]/[3760] Speed: 68.637432 samples/sec accuracy=83.324908 loss=0.654142 lr=0.000100 Epoch[091] Batch [3449]/[3760] Speed: 68.288565 samples/sec accuracy=83.322011 loss=0.654547 lr=0.000100 Epoch[091] Batch [3499]/[3760] Speed: 68.210972 samples/sec accuracy=83.318750 loss=0.654552 lr=0.000100 Epoch[091] Batch [3549]/[3760] Speed: 67.850120 samples/sec accuracy=83.332306 loss=0.654354 lr=0.000100 Epoch[091] Batch [3599]/[3760] Speed: 67.713254 samples/sec accuracy=83.353299 loss=0.653703 lr=0.000100 Epoch[091] Batch [3649]/[3760] Speed: 67.467931 samples/sec accuracy=83.349315 loss=0.653374 lr=0.000100 Epoch[091] Batch [3699]/[3760] Speed: 67.883794 samples/sec accuracy=83.336993 loss=0.653943 lr=0.000100 Epoch[091] Batch [3749]/[3760] Speed: 74.314657 samples/sec accuracy=83.337917 loss=0.654057 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.843750 acc-top5=86.437500 Batch [0099]/[0303]: acc-top1=66.984375 acc-top5=85.953125 Batch [0149]/[0303]: acc-top1=67.197917 acc-top5=86.229167 Batch [0199]/[0303]: acc-top1=67.320312 acc-top5=86.320312 Batch [0249]/[0303]: acc-top1=67.287500 acc-top5=86.343750 Batch [0299]/[0303]: acc-top1=67.395833 acc-top5=86.515625 [Epoch 091] training: accuracy=83.336519 loss=0.654041 [Epoch 091] speed: 67 samples/sec time cost: 3829.249993 [Epoch 091] validation: acc-top1=67.440182 acc-top5=86.535685 loss=1.660405 Epoch[092] Batch [0049]/[3760] Speed: 45.073634 samples/sec accuracy=82.343750 loss=0.671542 lr=0.000100 Epoch[092] Batch [0099]/[3760] Speed: 66.510512 samples/sec accuracy=82.781250 loss=0.652247 lr=0.000100 Epoch[092] Batch [0149]/[3760] Speed: 68.480244 samples/sec accuracy=83.135417 loss=0.642288 lr=0.000100 Epoch[092] Batch [0199]/[3760] Speed: 67.370141 samples/sec accuracy=82.992188 loss=0.646981 lr=0.000100 Epoch[092] Batch [0249]/[3760] Speed: 67.574565 samples/sec accuracy=82.887500 loss=0.656489 lr=0.000100 Epoch[092] Batch [0299]/[3760] Speed: 67.803397 samples/sec accuracy=83.026042 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accuracy=83.416250 loss=0.655594 lr=0.000100 Epoch[092] Batch [1299]/[3760] Speed: 68.194422 samples/sec accuracy=83.442308 loss=0.654747 lr=0.000100 Epoch[092] Batch [1349]/[3760] Speed: 68.039295 samples/sec accuracy=83.364583 loss=0.656398 lr=0.000100 Epoch[092] Batch [1399]/[3760] Speed: 67.307888 samples/sec accuracy=83.393973 loss=0.655867 lr=0.000100 Epoch[092] Batch [1449]/[3760] Speed: 68.575418 samples/sec accuracy=83.363147 loss=0.656768 lr=0.000100 Epoch[092] Batch [1499]/[3760] Speed: 67.003289 samples/sec accuracy=83.354167 loss=0.656883 lr=0.000100 Epoch[092] Batch [1549]/[3760] Speed: 68.575240 samples/sec accuracy=83.324597 loss=0.657380 lr=0.000100 Epoch[092] Batch [1599]/[3760] Speed: 67.482411 samples/sec accuracy=83.300781 loss=0.657920 lr=0.000100 Epoch[092] Batch [1649]/[3760] Speed: 67.823149 samples/sec accuracy=83.265152 loss=0.659035 lr=0.000100 Epoch[092] Batch [1699]/[3760] Speed: 68.008601 samples/sec accuracy=83.262868 loss=0.658494 lr=0.000100 Epoch[092] 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accuracy=83.330256 loss=0.656297 lr=0.000100 Epoch[092] Batch [2249]/[3760] Speed: 68.091335 samples/sec accuracy=83.311806 loss=0.656796 lr=0.000100 Epoch[092] Batch [2299]/[3760] Speed: 67.920455 samples/sec accuracy=83.340353 loss=0.656181 lr=0.000100 Epoch[092] Batch [2349]/[3760] Speed: 67.959321 samples/sec accuracy=83.366356 loss=0.655644 lr=0.000100 Epoch[092] Batch [2399]/[3760] Speed: 67.944591 samples/sec accuracy=83.389323 loss=0.655143 lr=0.000100 Epoch[092] Batch [2449]/[3760] Speed: 67.760128 samples/sec accuracy=83.379464 loss=0.655498 lr=0.000100 Epoch[092] Batch [2499]/[3760] Speed: 68.072583 samples/sec accuracy=83.362500 loss=0.656219 lr=0.000100 Epoch[092] Batch [2549]/[3760] Speed: 67.964235 samples/sec accuracy=83.333946 loss=0.657088 lr=0.000100 Epoch[092] Batch [2599]/[3760] Speed: 67.633417 samples/sec accuracy=83.349760 loss=0.656293 lr=0.000100 Epoch[092] Batch [2649]/[3760] Speed: 68.293048 samples/sec accuracy=83.352005 loss=0.655782 lr=0.000100 Epoch[092] 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accuracy=83.337302 loss=0.656248 lr=0.000100 Epoch[092] Batch [3199]/[3760] Speed: 68.564888 samples/sec accuracy=83.326172 loss=0.656317 lr=0.000100 Epoch[092] Batch [3249]/[3760] Speed: 67.502255 samples/sec accuracy=83.339423 loss=0.655970 lr=0.000100 Epoch[092] Batch [3299]/[3760] Speed: 68.563159 samples/sec accuracy=83.330019 loss=0.656505 lr=0.000100 Epoch[092] Batch [3349]/[3760] Speed: 67.268030 samples/sec accuracy=83.341884 loss=0.655884 lr=0.000100 Epoch[092] Batch [3399]/[3760] Speed: 68.424772 samples/sec accuracy=83.324449 loss=0.656168 lr=0.000100 Epoch[092] Batch [3449]/[3760] Speed: 68.103605 samples/sec accuracy=83.326993 loss=0.655974 lr=0.000100 Epoch[092] Batch [3499]/[3760] Speed: 68.388316 samples/sec accuracy=83.328125 loss=0.656031 lr=0.000100 Epoch[092] Batch [3549]/[3760] Speed: 68.150598 samples/sec accuracy=83.327025 loss=0.656031 lr=0.000100 Epoch[092] Batch [3599]/[3760] Speed: 68.289170 samples/sec accuracy=83.346788 loss=0.655070 lr=0.000100 Epoch[092] Batch [3649]/[3760] Speed: 68.257063 samples/sec accuracy=83.349315 loss=0.654920 lr=0.000100 Epoch[092] Batch [3699]/[3760] Speed: 66.637106 samples/sec accuracy=83.352618 loss=0.654690 lr=0.000100 Epoch[092] Batch [3749]/[3760] Speed: 75.076921 samples/sec accuracy=83.342083 loss=0.654878 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.375000 acc-top5=86.437500 Batch [0099]/[0303]: acc-top1=67.281250 acc-top5=86.046875 Batch [0149]/[0303]: acc-top1=67.322917 acc-top5=86.447917 Batch [0199]/[0303]: acc-top1=67.593750 acc-top5=86.453125 Batch [0249]/[0303]: acc-top1=67.500000 acc-top5=86.568750 Batch [0299]/[0303]: acc-top1=67.567708 acc-top5=86.750000 [Epoch 092] training: accuracy=83.336104 loss=0.655092 [Epoch 092] speed: 67 samples/sec time cost: 3832.432863 [Epoch 092] validation: acc-top1=67.600041 acc-top5=86.772896 loss=1.660276 Epoch[093] Batch [0049]/[3759] Speed: 46.575754 samples/sec accuracy=83.125000 loss=0.681892 lr=0.000100 Epoch[093] Batch [0099]/[3759] Speed: 66.193963 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68.256730 samples/sec accuracy=83.419492 loss=0.654426 lr=0.000100 Epoch[093] Batch [2999]/[3759] Speed: 68.040828 samples/sec accuracy=83.431771 loss=0.653738 lr=0.000100 Epoch[093] Batch [3049]/[3759] Speed: 67.937073 samples/sec accuracy=83.428279 loss=0.653789 lr=0.000100 Epoch[093] Batch [3099]/[3759] Speed: 67.665845 samples/sec accuracy=83.422883 loss=0.653854 lr=0.000100 Epoch[093] Batch [3149]/[3759] Speed: 68.026465 samples/sec accuracy=83.407242 loss=0.654262 lr=0.000100 Epoch[093] Batch [3199]/[3759] Speed: 68.481008 samples/sec accuracy=83.416504 loss=0.654128 lr=0.000100 Epoch[093] Batch [3249]/[3759] Speed: 67.235539 samples/sec accuracy=83.410577 loss=0.654353 lr=0.000100 Epoch[093] Batch [3299]/[3759] Speed: 68.739235 samples/sec accuracy=83.397254 loss=0.654990 lr=0.000100 Epoch[093] Batch [3349]/[3759] Speed: 68.255054 samples/sec accuracy=83.407649 loss=0.654871 lr=0.000100 Epoch[093] Batch [3399]/[3759] Speed: 68.551413 samples/sec accuracy=83.394761 loss=0.655595 lr=0.000100 Epoch[093] Batch [3449]/[3759] Speed: 67.662618 samples/sec accuracy=83.399909 loss=0.655117 lr=0.000100 Epoch[093] Batch [3499]/[3759] Speed: 68.365355 samples/sec accuracy=83.400893 loss=0.655177 lr=0.000100 Epoch[093] Batch [3549]/[3759] Speed: 67.691969 samples/sec accuracy=83.397007 loss=0.655085 lr=0.000100 Epoch[093] Batch [3599]/[3759] Speed: 68.347604 samples/sec accuracy=83.413194 loss=0.654538 lr=0.000100 Epoch[093] Batch [3649]/[3759] Speed: 67.873575 samples/sec accuracy=83.410959 loss=0.654244 lr=0.000100 Epoch[093] Batch [3699]/[3759] Speed: 68.209835 samples/sec accuracy=83.408784 loss=0.654113 lr=0.000100 Epoch[093] Batch [3749]/[3759] Speed: 74.638457 samples/sec accuracy=83.417083 loss=0.653831 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.250000 acc-top5=86.156250 Batch [0099]/[0303]: acc-top1=67.328125 acc-top5=85.593750 Batch [0149]/[0303]: acc-top1=67.354167 acc-top5=86.187500 Batch [0199]/[0303]: acc-top1=67.484375 acc-top5=86.179688 Batch [0249]/[0303]: acc-top1=67.293750 acc-top5=86.212500 Batch [0299]/[0303]: acc-top1=67.328125 acc-top5=86.432292 [Epoch 093] training: accuracy=83.425196 loss=0.653455 [Epoch 093] speed: 67 samples/sec time cost: 3824.343102 [Epoch 093] validation: acc-top1=67.367987 acc-top5=86.468647 loss=1.673052 Epoch[094] Batch [0049]/[3760] Speed: 45.260142 samples/sec accuracy=83.687500 loss=0.634677 lr=0.000100 Epoch[094] Batch [0099]/[3760] Speed: 66.606121 samples/sec accuracy=83.234375 loss=0.643570 lr=0.000100 Epoch[094] Batch [0149]/[3760] Speed: 68.822904 samples/sec accuracy=83.104167 loss=0.642873 lr=0.000100 Epoch[094] Batch [0199]/[3760] Speed: 68.206091 samples/sec accuracy=83.390625 loss=0.636815 lr=0.000100 Epoch[094] Batch [0249]/[3760] Speed: 68.345412 samples/sec accuracy=83.400000 loss=0.637571 lr=0.000100 Epoch[094] Batch [0299]/[3760] Speed: 68.286932 samples/sec accuracy=83.520833 loss=0.637021 lr=0.000100 Epoch[094] Batch [0349]/[3760] Speed: 67.790131 samples/sec accuracy=83.593750 loss=0.634303 lr=0.000100 Epoch[094] Batch [0399]/[3760] Speed: 68.099052 samples/sec accuracy=83.601562 loss=0.636454 lr=0.000100 Epoch[094] Batch [0449]/[3760] Speed: 68.290310 samples/sec accuracy=83.541667 loss=0.639736 lr=0.000100 Epoch[094] Batch [0499]/[3760] Speed: 68.199404 samples/sec accuracy=83.468750 loss=0.641708 lr=0.000100 Epoch[094] Batch [0549]/[3760] Speed: 68.251492 samples/sec accuracy=83.482955 loss=0.641835 lr=0.000100 Epoch[094] Batch [0599]/[3760] Speed: 67.207356 samples/sec accuracy=83.463542 loss=0.641903 lr=0.000100 Epoch[094] Batch [0649]/[3760] Speed: 68.430274 samples/sec accuracy=83.463942 loss=0.641139 lr=0.000100 Epoch[094] Batch [0699]/[3760] Speed: 67.634855 samples/sec accuracy=83.457589 loss=0.642483 lr=0.000100 Epoch[094] Batch [0749]/[3760] Speed: 68.573385 samples/sec accuracy=83.441667 loss=0.641767 lr=0.000100 Epoch[094] Batch [0799]/[3760] Speed: 67.593915 samples/sec accuracy=83.431641 loss=0.643118 lr=0.000100 Epoch[094] 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accuracy=83.484375 loss=0.644745 lr=0.000100 Epoch[094] Batch [1349]/[3760] Speed: 68.384521 samples/sec accuracy=83.488426 loss=0.644303 lr=0.000100 Epoch[094] Batch [1399]/[3760] Speed: 68.403438 samples/sec accuracy=83.529018 loss=0.643225 lr=0.000100 Epoch[094] Batch [1449]/[3760] Speed: 67.551488 samples/sec accuracy=83.531250 loss=0.643718 lr=0.000100 Epoch[094] Batch [1499]/[3760] Speed: 67.635668 samples/sec accuracy=83.548958 loss=0.642805 lr=0.000100 Epoch[094] Batch [1549]/[3760] Speed: 67.756200 samples/sec accuracy=83.554435 loss=0.643092 lr=0.000100 Epoch[094] Batch [1599]/[3760] Speed: 68.428851 samples/sec accuracy=83.565430 loss=0.643053 lr=0.000100 Epoch[094] Batch [1649]/[3760] Speed: 67.611362 samples/sec accuracy=83.578598 loss=0.642714 lr=0.000100 Epoch[094] Batch [1699]/[3760] Speed: 66.936738 samples/sec accuracy=83.592831 loss=0.642273 lr=0.000100 Epoch[094] Batch [1749]/[3760] Speed: 69.068630 samples/sec accuracy=83.609821 loss=0.642148 lr=0.000100 Epoch[094] Batch [1799]/[3760] Speed: 67.626538 samples/sec accuracy=83.593750 loss=0.642067 lr=0.000100 Epoch[094] Batch [1849]/[3760] Speed: 67.403807 samples/sec accuracy=83.585304 loss=0.641688 lr=0.000100 Epoch[094] Batch [1899]/[3760] Speed: 68.336345 samples/sec accuracy=83.558388 loss=0.642722 lr=0.000100 Epoch[094] Batch [1949]/[3760] Speed: 67.937000 samples/sec accuracy=83.557692 loss=0.642961 lr=0.000100 Epoch[094] Batch [1999]/[3760] Speed: 67.924372 samples/sec accuracy=83.574219 loss=0.642077 lr=0.000100 Epoch[094] Batch [2049]/[3760] Speed: 67.799210 samples/sec accuracy=83.580793 loss=0.641578 lr=0.000100 Epoch[094] Batch [2099]/[3760] Speed: 67.958876 samples/sec accuracy=83.569940 loss=0.641849 lr=0.000100 Epoch[094] Batch [2149]/[3760] Speed: 67.918962 samples/sec accuracy=83.554506 loss=0.642493 lr=0.000100 Epoch[094] Batch [2199]/[3760] Speed: 68.359468 samples/sec accuracy=83.539062 loss=0.643136 lr=0.000100 Epoch[094] Batch [2249]/[3760] Speed: 67.854755 samples/sec accuracy=83.527083 loss=0.643057 lr=0.000100 Epoch[094] Batch [2299]/[3760] Speed: 67.452716 samples/sec accuracy=83.543478 loss=0.642595 lr=0.000100 Epoch[094] Batch [2349]/[3760] Speed: 67.586636 samples/sec accuracy=83.544548 loss=0.642053 lr=0.000100 Epoch[094] Batch [2399]/[3760] Speed: 68.092698 samples/sec accuracy=83.516927 loss=0.642451 lr=0.000100 Epoch[094] Batch [2449]/[3760] Speed: 67.789144 samples/sec accuracy=83.528061 loss=0.641993 lr=0.000100 Epoch[094] Batch [2499]/[3760] Speed: 68.289369 samples/sec accuracy=83.543750 loss=0.641772 lr=0.000100 Epoch[094] Batch [2549]/[3760] Speed: 68.265855 samples/sec accuracy=83.528799 loss=0.642155 lr=0.000100 Epoch[094] Batch [2599]/[3760] Speed: 68.148963 samples/sec accuracy=83.518630 loss=0.642377 lr=0.000100 Epoch[094] Batch [2649]/[3760] Speed: 67.901903 samples/sec accuracy=83.529481 loss=0.642160 lr=0.000100 Epoch[094] Batch [2699]/[3760] Speed: 68.499246 samples/sec accuracy=83.516204 loss=0.642585 lr=0.000100 Epoch[094] Batch [2749]/[3760] Speed: 68.284329 samples/sec accuracy=83.518182 loss=0.642781 lr=0.000100 Epoch[094] Batch [2799]/[3760] Speed: 67.497438 samples/sec accuracy=83.491071 loss=0.643944 lr=0.000100 Epoch[094] Batch [2849]/[3760] Speed: 67.090591 samples/sec accuracy=83.473684 loss=0.644334 lr=0.000100 Epoch[094] Batch [2899]/[3760] Speed: 68.084439 samples/sec accuracy=83.459052 loss=0.644687 lr=0.000100 Epoch[094] Batch [2949]/[3760] Speed: 68.654979 samples/sec accuracy=83.445445 loss=0.645386 lr=0.000100 Epoch[094] Batch [2999]/[3760] Speed: 67.856176 samples/sec accuracy=83.444271 loss=0.645804 lr=0.000100 Epoch[094] Batch [3049]/[3760] Speed: 68.075980 samples/sec accuracy=83.441598 loss=0.645808 lr=0.000100 Epoch[094] Batch [3099]/[3760] Speed: 68.051650 samples/sec accuracy=83.445565 loss=0.645614 lr=0.000100 Epoch[094] Batch [3149]/[3760] Speed: 67.757491 samples/sec accuracy=83.417163 loss=0.646615 lr=0.000100 Epoch[094] Batch [3199]/[3760] Speed: 68.183022 samples/sec accuracy=83.428711 loss=0.646256 lr=0.000100 Epoch[094] Batch [3249]/[3760] Speed: 67.893378 samples/sec accuracy=83.423077 loss=0.646518 lr=0.000100 Epoch[094] Batch [3299]/[3760] Speed: 68.164120 samples/sec accuracy=83.432765 loss=0.646260 lr=0.000100 Epoch[094] Batch [3349]/[3760] Speed: 67.306339 samples/sec accuracy=83.438433 loss=0.645929 lr=0.000100 Epoch[094] Batch [3399]/[3760] Speed: 67.760904 samples/sec accuracy=83.462776 loss=0.645171 lr=0.000100 Epoch[094] Batch [3449]/[3760] Speed: 68.155165 samples/sec accuracy=83.458333 loss=0.645089 lr=0.000100 Epoch[094] Batch [3499]/[3760] Speed: 68.218914 samples/sec accuracy=83.453125 loss=0.645553 lr=0.000100 Epoch[094] Batch [3549]/[3760] Speed: 68.066394 samples/sec accuracy=83.459067 loss=0.645368 lr=0.000100 Epoch[094] Batch [3599]/[3760] Speed: 67.404291 samples/sec accuracy=83.452691 loss=0.645858 lr=0.000100 Epoch[094] Batch [3649]/[3760] Speed: 68.242660 samples/sec accuracy=83.441781 loss=0.646359 lr=0.000100 Epoch[094] Batch [3699]/[3760] Speed: 68.216357 samples/sec accuracy=83.445946 loss=0.646018 lr=0.000100 Epoch[094] Batch [3749]/[3760] Speed: 74.646543 samples/sec accuracy=83.441667 loss=0.646306 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.093750 acc-top5=86.375000 Batch [0099]/[0303]: acc-top1=67.171875 acc-top5=85.937500 Batch [0149]/[0303]: acc-top1=67.218750 acc-top5=86.437500 Batch [0199]/[0303]: acc-top1=67.507812 acc-top5=86.406250 Batch [0249]/[0303]: acc-top1=67.437500 acc-top5=86.443750 Batch [0299]/[0303]: acc-top1=67.473958 acc-top5=86.635417 [Epoch 094] training: accuracy=83.432513 loss=0.646679 [Epoch 094] speed: 67 samples/sec time cost: 3828.864865 [Epoch 094] validation: acc-top1=67.496906 acc-top5=86.669761 loss=1.671399 Epoch[095] Batch [0049]/[3760] Speed: 45.685475 samples/sec accuracy=83.687500 loss=0.637433 lr=0.000100 Epoch[095] Batch [0099]/[3760] Speed: 66.853521 samples/sec accuracy=83.750000 loss=0.642144 lr=0.000100 Epoch[095] Batch [0149]/[3760] Speed: 68.157341 samples/sec accuracy=83.802083 loss=0.631029 lr=0.000100 Epoch[095] Batch [0199]/[3760] Speed: 67.513523 samples/sec accuracy=83.640625 loss=0.639438 lr=0.000100 Epoch[095] Batch [0249]/[3760] Speed: 67.984146 samples/sec accuracy=83.862500 loss=0.634047 lr=0.000100 Epoch[095] Batch [0299]/[3760] Speed: 68.123485 samples/sec accuracy=84.088542 loss=0.625253 lr=0.000100 Epoch[095] Batch [0349]/[3760] Speed: 68.333356 samples/sec accuracy=84.000000 loss=0.630403 lr=0.000100 Epoch[095] Batch [0399]/[3760] Speed: 67.964894 samples/sec accuracy=83.921875 loss=0.633357 lr=0.000100 Epoch[095] Batch [0449]/[3760] Speed: 67.827614 samples/sec accuracy=83.871528 loss=0.634819 lr=0.000100 Epoch[095] Batch [0499]/[3760] Speed: 68.397479 samples/sec accuracy=83.862500 loss=0.635936 lr=0.000100 Epoch[095] Batch [0549]/[3760] Speed: 68.312969 samples/sec accuracy=83.792614 loss=0.636904 lr=0.000100 Epoch[095] Batch [0599]/[3760] Speed: 67.937084 samples/sec accuracy=83.903646 loss=0.634842 lr=0.000100 Epoch[095] Batch [0649]/[3760] Speed: 68.272729 samples/sec accuracy=83.918269 loss=0.634875 lr=0.000100 Epoch[095] Batch [0699]/[3760] Speed: 68.522592 samples/sec accuracy=83.921875 loss=0.636339 lr=0.000100 Epoch[095] Batch [0749]/[3760] Speed: 67.331326 samples/sec accuracy=83.854167 loss=0.637861 lr=0.000100 Epoch[095] Batch [0799]/[3760] Speed: 68.372706 samples/sec accuracy=83.878906 loss=0.637798 lr=0.000100 Epoch[095] Batch [0849]/[3760] Speed: 68.269221 samples/sec accuracy=83.895221 loss=0.636694 lr=0.000100 Epoch[095] Batch [0899]/[3760] Speed: 67.870311 samples/sec accuracy=83.861111 loss=0.638306 lr=0.000100 Epoch[095] Batch [0949]/[3760] Speed: 68.316828 samples/sec accuracy=83.794408 loss=0.640863 lr=0.000100 Epoch[095] Batch [0999]/[3760] Speed: 67.873787 samples/sec accuracy=83.798438 loss=0.640738 lr=0.000100 Epoch[095] Batch [1049]/[3760] Speed: 68.076033 samples/sec accuracy=83.816964 loss=0.639752 lr=0.000100 Epoch[095] Batch [1099]/[3760] Speed: 67.601302 samples/sec accuracy=83.813920 loss=0.639640 lr=0.000100 Epoch[095] Batch [1149]/[3760] Speed: 67.770199 samples/sec accuracy=83.802989 loss=0.639467 lr=0.000100 Epoch[095] Batch [1199]/[3760] Speed: 68.049413 samples/sec accuracy=83.777344 loss=0.640998 lr=0.000100 Epoch[095] Batch [1249]/[3760] Speed: 68.466210 samples/sec accuracy=83.773750 loss=0.641268 lr=0.000100 Epoch[095] Batch [1299]/[3760] Speed: 66.753273 samples/sec accuracy=83.723558 loss=0.643062 lr=0.000100 Epoch[095] Batch [1349]/[3760] Speed: 68.726967 samples/sec accuracy=83.697917 loss=0.644107 lr=0.000100 Epoch[095] Batch [1399]/[3760] Speed: 68.420701 samples/sec accuracy=83.681920 loss=0.645467 lr=0.000100 Epoch[095] Batch [1449]/[3760] Speed: 68.261061 samples/sec accuracy=83.684267 loss=0.644955 lr=0.000100 Epoch[095] Batch [1499]/[3760] Speed: 67.901677 samples/sec accuracy=83.693750 loss=0.644428 lr=0.000100 Epoch[095] Batch [1549]/[3760] Speed: 67.982986 samples/sec accuracy=83.684476 loss=0.643703 lr=0.000100 Epoch[095] Batch [1599]/[3760] Speed: 68.790789 samples/sec accuracy=83.688477 loss=0.643908 lr=0.000100 Epoch[095] Batch [1649]/[3760] Speed: 68.033693 samples/sec accuracy=83.680871 loss=0.644266 lr=0.000100 Epoch[095] Batch [1699]/[3760] Speed: 68.282697 samples/sec accuracy=83.635110 loss=0.645126 lr=0.000100 Epoch[095] Batch [1749]/[3760] Speed: 68.438612 samples/sec accuracy=83.602679 loss=0.646372 lr=0.000100 Epoch[095] Batch [1799]/[3760] Speed: 67.871927 samples/sec accuracy=83.608507 loss=0.645778 lr=0.000100 Epoch[095] Batch [1849]/[3760] Speed: 67.595578 samples/sec accuracy=83.603885 loss=0.646436 lr=0.000100 Epoch[095] Batch [1899]/[3760] Speed: 67.779727 samples/sec accuracy=83.615132 loss=0.646102 lr=0.000100 Epoch[095] Batch [1949]/[3760] Speed: 67.813107 samples/sec accuracy=83.621795 loss=0.645593 lr=0.000100 Epoch[095] Batch [1999]/[3760] Speed: 67.858317 samples/sec accuracy=83.619531 loss=0.645409 lr=0.000100 Epoch[095] Batch [2049]/[3760] Speed: 68.544357 samples/sec accuracy=83.633384 loss=0.645385 lr=0.000100 Epoch[095] Batch [2099]/[3760] Speed: 67.904670 samples/sec accuracy=83.627232 loss=0.645834 lr=0.000100 Epoch[095] Batch [2149]/[3760] Speed: 68.404063 samples/sec accuracy=83.627907 loss=0.646233 lr=0.000100 Epoch[095] Batch [2199]/[3760] Speed: 67.960377 samples/sec accuracy=83.612216 loss=0.646835 lr=0.000100 Epoch[095] Batch [2249]/[3760] Speed: 68.052799 samples/sec accuracy=83.627083 loss=0.646688 lr=0.000100 Epoch[095] Batch [2299]/[3760] Speed: 68.166431 samples/sec accuracy=83.639266 loss=0.646346 lr=0.000100 Epoch[095] Batch [2349]/[3760] Speed: 68.668956 samples/sec accuracy=83.632314 loss=0.646352 lr=0.000100 Epoch[095] Batch [2399]/[3760] Speed: 68.212090 samples/sec accuracy=83.621745 loss=0.646887 lr=0.000100 Epoch[095] Batch [2449]/[3760] Speed: 67.213545 samples/sec accuracy=83.631378 loss=0.646785 lr=0.000100 Epoch[095] Batch [2499]/[3760] Speed: 68.420928 samples/sec accuracy=83.633125 loss=0.646238 lr=0.000100 Epoch[095] Batch [2549]/[3760] Speed: 68.034277 samples/sec accuracy=83.640319 loss=0.645982 lr=0.000100 Epoch[095] Batch [2599]/[3760] Speed: 68.032381 samples/sec accuracy=83.650240 loss=0.645527 lr=0.000100 Epoch[095] Batch [2649]/[3760] Speed: 67.580970 samples/sec accuracy=83.666863 loss=0.644970 lr=0.000100 Epoch[095] Batch [2699]/[3760] Speed: 67.583609 samples/sec accuracy=83.657986 loss=0.645433 lr=0.000100 Epoch[095] Batch [2749]/[3760] Speed: 68.162776 samples/sec accuracy=83.636932 loss=0.645659 lr=0.000100 Epoch[095] Batch [2799]/[3760] Speed: 67.749109 samples/sec accuracy=83.631138 loss=0.646032 lr=0.000100 Epoch[095] Batch [2849]/[3760] Speed: 67.968486 samples/sec accuracy=83.642544 loss=0.646119 lr=0.000100 Epoch[095] Batch [2899]/[3760] Speed: 67.823127 samples/sec accuracy=83.632543 loss=0.646970 lr=0.000100 Epoch[095] Batch [2949]/[3760] Speed: 67.958940 samples/sec accuracy=83.644068 loss=0.646830 lr=0.000100 Epoch[095] Batch [2999]/[3760] Speed: 66.745990 samples/sec accuracy=83.635937 loss=0.646610 lr=0.000100 Epoch[095] Batch [3049]/[3760] Speed: 69.130657 samples/sec accuracy=83.649078 loss=0.646136 lr=0.000100 Epoch[095] Batch [3099]/[3760] Speed: 67.652983 samples/sec accuracy=83.641129 loss=0.646200 lr=0.000100 Epoch[095] Batch [3149]/[3760] Speed: 67.730568 samples/sec accuracy=83.647817 loss=0.646247 lr=0.000100 Epoch[095] Batch [3199]/[3760] Speed: 68.104176 samples/sec accuracy=83.633789 loss=0.646487 lr=0.000100 Epoch[095] Batch [3249]/[3760] Speed: 67.461870 samples/sec accuracy=83.635577 loss=0.646738 lr=0.000100 Epoch[095] Batch [3299]/[3760] Speed: 67.974147 samples/sec accuracy=83.622633 loss=0.647017 lr=0.000100 Epoch[095] Batch [3349]/[3760] Speed: 67.604424 samples/sec accuracy=83.628731 loss=0.646737 lr=0.000100 Epoch[095] Batch [3399]/[3760] Speed: 67.628884 samples/sec accuracy=83.630515 loss=0.646387 lr=0.000100 Epoch[095] Batch [3449]/[3760] Speed: 68.328707 samples/sec accuracy=83.629982 loss=0.646727 lr=0.000100 Epoch[095] Batch [3499]/[3760] Speed: 67.719998 samples/sec accuracy=83.633036 loss=0.646433 lr=0.000100 Epoch[095] Batch [3549]/[3760] Speed: 67.986865 samples/sec accuracy=83.628081 loss=0.646756 lr=0.000100 Epoch[095] Batch [3599]/[3760] Speed: 67.869554 samples/sec accuracy=83.609809 loss=0.647254 lr=0.000100 Epoch[095] Batch [3649]/[3760] Speed: 67.777194 samples/sec accuracy=83.605308 loss=0.647094 lr=0.000100 Epoch[095] Batch [3699]/[3760] Speed: 68.360970 samples/sec accuracy=83.597551 loss=0.647178 lr=0.000100 Epoch[095] Batch [3749]/[3760] Speed: 74.174716 samples/sec accuracy=83.600000 loss=0.646724 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.843750 acc-top5=86.187500 Batch [0099]/[0303]: acc-top1=67.015625 acc-top5=85.843750 Batch [0149]/[0303]: acc-top1=67.187500 acc-top5=86.322917 Batch [0199]/[0303]: acc-top1=67.406250 acc-top5=86.273438 Batch [0249]/[0303]: acc-top1=67.337500 acc-top5=86.343750 Batch [0299]/[0303]: acc-top1=67.369792 acc-top5=86.515625 [Epoch 095] training: accuracy=83.601230 loss=0.646655 [Epoch 095] speed: 67 samples/sec time cost: 3828.434386 [Epoch 095] validation: acc-top1=67.398927 acc-top5=86.551155 loss=1.670058 Epoch[096] Batch [0049]/[3759] Speed: 45.833637 samples/sec accuracy=83.906250 loss=0.645740 lr=0.000100 Epoch[096] Batch [0099]/[3759] Speed: 66.991350 samples/sec accuracy=83.859375 loss=0.638459 lr=0.000100 Epoch[096] Batch [0149]/[3759] Speed: 67.789051 samples/sec accuracy=83.812500 loss=0.644469 lr=0.000100 Epoch[096] Batch [0199]/[3759] Speed: 68.117525 samples/sec accuracy=84.164062 loss=0.626956 lr=0.000100 Epoch[096] Batch [0249]/[3759] Speed: 68.018080 samples/sec accuracy=84.175000 loss=0.628264 lr=0.000100 Epoch[096] Batch [0299]/[3759] Speed: 67.893593 samples/sec accuracy=84.145833 loss=0.629759 lr=0.000100 Epoch[096] Batch [0349]/[3759] Speed: 67.421363 samples/sec accuracy=84.004464 loss=0.634725 lr=0.000100 Epoch[096] Batch [0399]/[3759] Speed: 67.631173 samples/sec accuracy=83.789062 loss=0.643317 lr=0.000100 Epoch[096] Batch [0449]/[3759] Speed: 67.596261 samples/sec accuracy=83.843750 loss=0.641627 lr=0.000100 Epoch[096] Batch [0499]/[3759] Speed: 68.423287 samples/sec accuracy=83.800000 loss=0.643987 lr=0.000100 Epoch[096] Batch [0549]/[3759] Speed: 68.323201 samples/sec accuracy=83.761364 loss=0.644652 lr=0.000100 Epoch[096] Batch [0599]/[3759] Speed: 68.426010 samples/sec accuracy=83.747396 loss=0.643715 lr=0.000100 Epoch[096] Batch [0649]/[3759] Speed: 67.696646 samples/sec accuracy=83.776442 loss=0.642101 lr=0.000100 Epoch[096] Batch [0699]/[3759] Speed: 67.552508 samples/sec accuracy=83.720982 loss=0.644888 lr=0.000100 Epoch[096] Batch [0749]/[3759] Speed: 68.324173 samples/sec accuracy=83.662500 loss=0.646188 lr=0.000100 Epoch[096] Batch [0799]/[3759] Speed: 67.747276 samples/sec accuracy=83.660156 loss=0.646788 lr=0.000100 Epoch[096] Batch [0849]/[3759] Speed: 67.974982 samples/sec accuracy=83.588235 loss=0.648992 lr=0.000100 Epoch[096] Batch [0899]/[3759] Speed: 68.412002 samples/sec accuracy=83.539931 loss=0.649678 lr=0.000100 Epoch[096] Batch [0949]/[3759] Speed: 68.134059 samples/sec accuracy=83.500000 loss=0.650523 lr=0.000100 Epoch[096] Batch [0999]/[3759] Speed: 67.640237 samples/sec accuracy=83.545313 loss=0.648534 lr=0.000100 Epoch[096] Batch [1049]/[3759] Speed: 68.342333 samples/sec accuracy=83.494048 loss=0.650188 lr=0.000100 Epoch[096] Batch [1099]/[3759] Speed: 67.639259 samples/sec accuracy=83.492898 loss=0.650843 lr=0.000100 Epoch[096] Batch [1149]/[3759] Speed: 67.850664 samples/sec accuracy=83.516304 loss=0.649705 lr=0.000100 Epoch[096] Batch [1199]/[3759] Speed: 68.110881 samples/sec accuracy=83.488281 loss=0.651171 lr=0.000100 Epoch[096] Batch [1249]/[3759] Speed: 68.351899 samples/sec accuracy=83.478750 loss=0.652230 lr=0.000100 Epoch[096] Batch [1299]/[3759] Speed: 67.664669 samples/sec accuracy=83.508413 loss=0.651014 lr=0.000100 Epoch[096] Batch [1349]/[3759] Speed: 68.105509 samples/sec accuracy=83.474537 loss=0.653550 lr=0.000100 Epoch[096] Batch [1399]/[3759] Speed: 67.932356 samples/sec accuracy=83.450893 loss=0.653565 lr=0.000100 Epoch[096] Batch [1449]/[3759] Speed: 67.774432 samples/sec accuracy=83.440733 loss=0.653632 lr=0.000100 Epoch[096] Batch [1499]/[3759] Speed: 67.654644 samples/sec accuracy=83.455208 loss=0.652632 lr=0.000100 Epoch[096] Batch [1549]/[3759] Speed: 68.346046 samples/sec accuracy=83.448589 loss=0.651767 lr=0.000100 Epoch[096] Batch [1599]/[3759] Speed: 67.830937 samples/sec accuracy=83.459961 loss=0.651428 lr=0.000100 Epoch[096] Batch [1649]/[3759] Speed: 68.069704 samples/sec accuracy=83.483902 loss=0.650533 lr=0.000100 Epoch[096] Batch [1699]/[3759] Speed: 68.243232 samples/sec accuracy=83.488051 loss=0.649905 lr=0.000100 Epoch[096] Batch [1749]/[3759] Speed: 68.002554 samples/sec accuracy=83.458036 loss=0.650082 lr=0.000100 Epoch[096] Batch [1799]/[3759] Speed: 68.193756 samples/sec accuracy=83.473958 loss=0.650161 lr=0.000100 Epoch[096] Batch [1849]/[3759] Speed: 67.999376 samples/sec accuracy=83.500000 loss=0.649800 lr=0.000100 Epoch[096] Batch [1899]/[3759] Speed: 67.445003 samples/sec accuracy=83.521382 loss=0.649131 lr=0.000100 Epoch[096] Batch [1949]/[3759] Speed: 68.783474 samples/sec accuracy=83.499199 loss=0.649416 lr=0.000100 Epoch[096] Batch [1999]/[3759] Speed: 68.004031 samples/sec accuracy=83.494531 loss=0.649319 lr=0.000100 Epoch[096] Batch [2049]/[3759] Speed: 68.133825 samples/sec accuracy=83.490091 loss=0.649115 lr=0.000100 Epoch[096] Batch [2099]/[3759] Speed: 67.615799 samples/sec accuracy=83.517857 loss=0.648610 lr=0.000100 Epoch[096] Batch [2149]/[3759] Speed: 68.109319 samples/sec accuracy=83.507267 loss=0.648752 lr=0.000100 Epoch[096] Batch [2199]/[3759] Speed: 67.869782 samples/sec accuracy=83.527699 loss=0.648294 lr=0.000100 Epoch[096] Batch [2249]/[3759] Speed: 67.856119 samples/sec accuracy=83.548611 loss=0.648076 lr=0.000100 Epoch[096] Batch [2299]/[3759] Speed: 68.170684 samples/sec accuracy=83.565217 loss=0.647881 lr=0.000100 Epoch[096] Batch [2349]/[3759] Speed: 68.304289 samples/sec accuracy=83.550532 loss=0.648051 lr=0.000100 Epoch[096] Batch [2399]/[3759] Speed: 67.929165 samples/sec accuracy=83.552083 loss=0.648182 lr=0.000100 Epoch[096] Batch [2449]/[3759] Speed: 68.169179 samples/sec accuracy=83.547832 loss=0.648229 lr=0.000100 Epoch[096] Batch [2499]/[3759] Speed: 67.908631 samples/sec accuracy=83.553125 loss=0.648092 lr=0.000100 Epoch[096] Batch [2549]/[3759] Speed: 68.111384 samples/sec accuracy=83.554534 loss=0.647390 lr=0.000100 Epoch[096] Batch [2599]/[3759] Speed: 68.312408 samples/sec accuracy=83.547476 loss=0.647386 lr=0.000100 Epoch[096] Batch [2649]/[3759] Speed: 67.469098 samples/sec accuracy=83.551887 loss=0.647206 lr=0.000100 Epoch[096] Batch [2699]/[3759] Speed: 67.851561 samples/sec accuracy=83.561921 loss=0.646978 lr=0.000100 Epoch[096] Batch [2749]/[3759] Speed: 67.925246 samples/sec accuracy=83.556250 loss=0.647085 lr=0.000100 Epoch[096] Batch [2799]/[3759] Speed: 68.488197 samples/sec accuracy=83.569196 loss=0.646677 lr=0.000100 Epoch[096] Batch [2849]/[3759] Speed: 68.006673 samples/sec accuracy=83.558662 loss=0.647046 lr=0.000100 Epoch[096] Batch [2899]/[3759] Speed: 67.731472 samples/sec accuracy=83.555496 loss=0.647284 lr=0.000100 Epoch[096] Batch [2949]/[3759] Speed: 68.437048 samples/sec accuracy=83.569915 loss=0.646885 lr=0.000100 Epoch[096] Batch [2999]/[3759] Speed: 68.494639 samples/sec accuracy=83.576042 loss=0.646880 lr=0.000100 Epoch[096] Batch [3049]/[3759] Speed: 67.612086 samples/sec accuracy=83.583504 loss=0.646286 lr=0.000100 Epoch[096] Batch [3099]/[3759] Speed: 68.321832 samples/sec accuracy=83.584173 loss=0.646414 lr=0.000100 Epoch[096] Batch [3149]/[3759] Speed: 67.422906 samples/sec accuracy=83.582341 loss=0.646033 lr=0.000100 Epoch[096] Batch [3199]/[3759] Speed: 67.827867 samples/sec accuracy=83.586426 loss=0.646000 lr=0.000100 Epoch[096] Batch [3249]/[3759] Speed: 67.257465 samples/sec accuracy=83.597115 loss=0.645553 lr=0.000100 Epoch[096] Batch [3299]/[3759] Speed: 68.231323 samples/sec accuracy=83.570076 loss=0.646146 lr=0.000100 Epoch[096] Batch [3349]/[3759] Speed: 68.373567 samples/sec accuracy=83.581157 loss=0.645907 lr=0.000100 Epoch[096] Batch [3399]/[3759] Speed: 67.976143 samples/sec accuracy=83.590074 loss=0.645237 lr=0.000100 Epoch[096] Batch [3449]/[3759] Speed: 67.483800 samples/sec accuracy=83.587862 loss=0.645477 lr=0.000100 Epoch[096] Batch [3499]/[3759] Speed: 67.952026 samples/sec accuracy=83.571875 loss=0.645965 lr=0.000100 Epoch[096] Batch [3549]/[3759] Speed: 67.827392 samples/sec accuracy=83.574824 loss=0.646230 lr=0.000100 Epoch[096] Batch [3599]/[3759] Speed: 68.500840 samples/sec accuracy=83.573785 loss=0.646486 lr=0.000100 Epoch[096] Batch [3649]/[3759] Speed: 67.994250 samples/sec accuracy=83.576199 loss=0.646540 lr=0.000100 Epoch[096] Batch [3699]/[3759] Speed: 68.265543 samples/sec accuracy=83.588682 loss=0.646047 lr=0.000100 Epoch[096] Batch [3749]/[3759] Speed: 75.493541 samples/sec accuracy=83.587917 loss=0.645984 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.625000 acc-top5=86.312500 Batch [0099]/[0303]: acc-top1=66.781250 acc-top5=85.796875 Batch [0149]/[0303]: acc-top1=66.947917 acc-top5=86.343750 Batch [0199]/[0303]: acc-top1=67.257812 acc-top5=86.335938 Batch [0249]/[0303]: acc-top1=67.281250 acc-top5=86.400000 Batch [0299]/[0303]: acc-top1=67.317708 acc-top5=86.541667 [Epoch 096] training: accuracy=83.596868 loss=0.645749 [Epoch 096] speed: 67 samples/sec time cost: 3828.896826 [Epoch 096] validation: acc-top1=67.352517 acc-top5=86.582096 loss=1.670758 Epoch[097] Batch [0049]/[3760] Speed: 45.201768 samples/sec accuracy=83.687500 loss=0.654063 lr=0.000100 Epoch[097] Batch [0099]/[3760] Speed: 65.638773 samples/sec accuracy=83.937500 loss=0.648477 lr=0.000100 Epoch[097] Batch [0149]/[3760] Speed: 68.178174 samples/sec accuracy=83.718750 loss=0.648405 lr=0.000100 Epoch[097] Batch [0199]/[3760] Speed: 68.052845 samples/sec accuracy=83.742188 loss=0.644988 lr=0.000100 Epoch[097] Batch [0249]/[3760] Speed: 67.729271 samples/sec accuracy=83.768750 loss=0.644141 lr=0.000100 Epoch[097] Batch [0299]/[3760] Speed: 67.881534 samples/sec accuracy=83.927083 loss=0.641202 lr=0.000100 Epoch[097] Batch [0349]/[3760] Speed: 67.174709 samples/sec accuracy=83.901786 loss=0.642031 lr=0.000100 Epoch[097] Batch [0399]/[3760] Speed: 68.764427 samples/sec accuracy=83.734375 loss=0.646848 lr=0.000100 Epoch[097] Batch [0449]/[3760] Speed: 67.734710 samples/sec accuracy=83.687500 loss=0.646961 lr=0.000100 Epoch[097] Batch [0499]/[3760] Speed: 67.616439 samples/sec accuracy=83.715625 loss=0.644440 lr=0.000100 Epoch[097] Batch [0549]/[3760] Speed: 67.982010 samples/sec accuracy=83.738636 loss=0.643884 lr=0.000100 Epoch[097] Batch [0599]/[3760] Speed: 67.011972 samples/sec accuracy=83.817708 loss=0.643109 lr=0.000100 Epoch[097] Batch [0649]/[3760] Speed: 68.253955 samples/sec accuracy=83.786058 loss=0.645343 lr=0.000100 Epoch[097] Batch [0699]/[3760] Speed: 67.832714 samples/sec accuracy=83.752232 loss=0.645681 lr=0.000100 Epoch[097] Batch [0749]/[3760] Speed: 67.740860 samples/sec accuracy=83.716667 loss=0.646108 lr=0.000100 Epoch[097] Batch [0799]/[3760] Speed: 68.013279 samples/sec accuracy=83.710938 loss=0.645184 lr=0.000100 Epoch[097] Batch [0849]/[3760] Speed: 67.649858 samples/sec accuracy=83.617647 loss=0.647520 lr=0.000100 Epoch[097] Batch [0899]/[3760] Speed: 67.153837 samples/sec accuracy=83.618056 loss=0.647496 lr=0.000100 Epoch[097] Batch [0949]/[3760] Speed: 68.859947 samples/sec accuracy=83.646382 loss=0.647408 lr=0.000100 Epoch[097] Batch [0999]/[3760] Speed: 68.003850 samples/sec accuracy=83.640625 loss=0.646466 lr=0.000100 Epoch[097] Batch [1049]/[3760] Speed: 68.380365 samples/sec accuracy=83.660714 loss=0.645332 lr=0.000100 Epoch[097] Batch [1099]/[3760] Speed: 67.706679 samples/sec accuracy=83.661932 loss=0.644959 lr=0.000100 Epoch[097] Batch [1149]/[3760] Speed: 67.907921 samples/sec accuracy=83.658967 loss=0.644012 lr=0.000100 Epoch[097] Batch [1199]/[3760] Speed: 67.692385 samples/sec accuracy=83.682292 loss=0.643263 lr=0.000100 Epoch[097] Batch [1249]/[3760] Speed: 68.334499 samples/sec accuracy=83.690000 loss=0.643501 lr=0.000100 Epoch[097] Batch [1299]/[3760] Speed: 67.718807 samples/sec accuracy=83.723558 loss=0.641994 lr=0.000100 Epoch[097] Batch [1349]/[3760] Speed: 67.818303 samples/sec accuracy=83.703704 loss=0.641911 lr=0.000100 Epoch[097] Batch [1399]/[3760] Speed: 67.911245 samples/sec accuracy=83.727679 loss=0.641069 lr=0.000100 Epoch[097] Batch [1449]/[3760] Speed: 67.906445 samples/sec accuracy=83.717672 loss=0.641242 lr=0.000100 Epoch[097] Batch [1499]/[3760] Speed: 68.233768 samples/sec accuracy=83.692708 loss=0.641623 lr=0.000100 Epoch[097] Batch [1549]/[3760] Speed: 67.929167 samples/sec accuracy=83.680444 loss=0.642531 lr=0.000100 Epoch[097] Batch [1599]/[3760] Speed: 67.866542 samples/sec accuracy=83.689453 loss=0.641908 lr=0.000100 Epoch[097] Batch [1649]/[3760] Speed: 68.454392 samples/sec accuracy=83.668561 loss=0.642421 lr=0.000100 Epoch[097] Batch [1699]/[3760] Speed: 67.634641 samples/sec accuracy=83.664522 loss=0.642370 lr=0.000100 Epoch[097] Batch [1749]/[3760] Speed: 68.007134 samples/sec accuracy=83.669643 loss=0.642245 lr=0.000100 Epoch[097] Batch [1799]/[3760] Speed: 67.996301 samples/sec accuracy=83.670139 loss=0.642161 lr=0.000100 Epoch[097] Batch [1849]/[3760] Speed: 67.119557 samples/sec accuracy=83.663851 loss=0.642014 lr=0.000100 Epoch[097] Batch [1899]/[3760] Speed: 68.128170 samples/sec accuracy=83.692434 loss=0.641244 lr=0.000100 Epoch[097] Batch [1949]/[3760] Speed: 68.085092 samples/sec accuracy=83.681891 loss=0.641290 lr=0.000100 Epoch[097] Batch [1999]/[3760] Speed: 68.165531 samples/sec accuracy=83.669531 loss=0.641659 lr=0.000100 Epoch[097] Batch [2049]/[3760] Speed: 67.750201 samples/sec accuracy=83.658537 loss=0.641799 lr=0.000100 Epoch[097] Batch [2099]/[3760] Speed: 67.759112 samples/sec accuracy=83.655506 loss=0.642262 lr=0.000100 Epoch[097] Batch [2149]/[3760] Speed: 67.864919 samples/sec accuracy=83.648983 loss=0.642362 lr=0.000100 Epoch[097] Batch [2199]/[3760] Speed: 68.129942 samples/sec accuracy=83.633523 loss=0.642518 lr=0.000100 Epoch[097] Batch [2249]/[3760] Speed: 68.474602 samples/sec accuracy=83.636806 loss=0.641776 lr=0.000100 Epoch[097] Batch [2299]/[3760] Speed: 68.163140 samples/sec accuracy=83.639266 loss=0.641897 lr=0.000100 Epoch[097] Batch [2349]/[3760] Speed: 68.174664 samples/sec accuracy=83.630984 loss=0.641996 lr=0.000100 Epoch[097] Batch [2399]/[3760] Speed: 67.791480 samples/sec accuracy=83.613932 loss=0.642496 lr=0.000100 Epoch[097] Batch [2449]/[3760] Speed: 67.663525 samples/sec accuracy=83.616071 loss=0.642432 lr=0.000100 Epoch[097] Batch [2499]/[3760] Speed: 68.181189 samples/sec accuracy=83.611250 loss=0.642457 lr=0.000100 Epoch[097] Batch [2549]/[3760] Speed: 68.692371 samples/sec accuracy=83.615809 loss=0.642784 lr=0.000100 Epoch[097] Batch [2599]/[3760] Speed: 67.563092 samples/sec accuracy=83.620793 loss=0.642348 lr=0.000100 Epoch[097] Batch [2649]/[3760] Speed: 68.217397 samples/sec accuracy=83.609080 loss=0.642814 lr=0.000100 Epoch[097] Batch [2699]/[3760] Speed: 67.724736 samples/sec accuracy=83.624421 loss=0.642720 lr=0.000100 Epoch[097] Batch [2749]/[3760] Speed: 68.400019 samples/sec accuracy=83.626705 loss=0.642729 lr=0.000100 Epoch[097] Batch [2799]/[3760] Speed: 68.053304 samples/sec accuracy=83.622210 loss=0.642460 lr=0.000100 Epoch[097] Batch [2849]/[3760] Speed: 68.124027 samples/sec accuracy=83.626096 loss=0.642416 lr=0.000100 Epoch[097] Batch [2899]/[3760] Speed: 67.578496 samples/sec accuracy=83.615841 loss=0.642932 lr=0.000100 Epoch[097] Batch [2949]/[3760] Speed: 68.584596 samples/sec accuracy=83.610699 loss=0.643176 lr=0.000100 Epoch[097] Batch [2999]/[3760] Speed: 67.916432 samples/sec accuracy=83.615625 loss=0.642810 lr=0.000100 Epoch[097] Batch [3049]/[3760] Speed: 68.118332 samples/sec accuracy=83.607582 loss=0.643559 lr=0.000100 Epoch[097] Batch [3099]/[3760] Speed: 67.577510 samples/sec accuracy=83.604839 loss=0.643811 lr=0.000100 Epoch[097] Batch [3149]/[3760] Speed: 68.041254 samples/sec accuracy=83.625496 loss=0.643214 lr=0.000100 Epoch[097] Batch [3199]/[3760] Speed: 67.415123 samples/sec accuracy=83.613770 loss=0.643210 lr=0.000100 Epoch[097] Batch [3249]/[3760] Speed: 67.929857 samples/sec accuracy=83.609135 loss=0.643824 lr=0.000100 Epoch[097] Batch [3299]/[3760] Speed: 67.992103 samples/sec accuracy=83.597064 loss=0.644273 lr=0.000100 Epoch[097] Batch [3349]/[3760] Speed: 68.133729 samples/sec accuracy=83.602146 loss=0.643911 lr=0.000100 Epoch[097] Batch [3399]/[3760] Speed: 67.579966 samples/sec accuracy=83.613051 loss=0.643640 lr=0.000100 Epoch[097] Batch [3449]/[3760] Speed: 68.031920 samples/sec accuracy=83.605072 loss=0.644134 lr=0.000100 Epoch[097] Batch [3499]/[3760] Speed: 67.441557 samples/sec accuracy=83.610268 loss=0.643869 lr=0.000100 Epoch[097] Batch [3549]/[3760] Speed: 68.213202 samples/sec accuracy=83.611356 loss=0.643821 lr=0.000100 Epoch[097] Batch [3599]/[3760] Speed: 68.212910 samples/sec accuracy=83.607639 loss=0.644154 lr=0.000100 Epoch[097] Batch [3649]/[3760] Speed: 68.031598 samples/sec accuracy=83.591182 loss=0.644525 lr=0.000100 Epoch[097] Batch [3699]/[3760] Speed: 68.090940 samples/sec accuracy=83.597973 loss=0.644295 lr=0.000100 Epoch[097] Batch [3749]/[3760] Speed: 74.248019 samples/sec accuracy=83.599583 loss=0.644471 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.906250 acc-top5=86.375000 Batch [0099]/[0303]: acc-top1=66.906250 acc-top5=86.031250 Batch [0149]/[0303]: acc-top1=67.031250 acc-top5=86.343750 Batch [0199]/[0303]: acc-top1=67.320312 acc-top5=86.203125 Batch [0249]/[0303]: acc-top1=67.268750 acc-top5=86.312500 Batch [0299]/[0303]: acc-top1=67.359375 acc-top5=86.510417 [Epoch 097] training: accuracy=83.600814 loss=0.644591 [Epoch 097] speed: 67 samples/sec time cost: 3831.552038 [Epoch 097] validation: acc-top1=67.393771 acc-top5=86.545998 loss=1.677016 Epoch[098] Batch [0049]/[3759] Speed: 45.329427 samples/sec accuracy=82.312500 loss=0.668160 lr=0.000100 Epoch[098] Batch [0099]/[3759] Speed: 66.877970 samples/sec accuracy=82.921875 loss=0.644593 lr=0.000100 Epoch[098] Batch [0149]/[3759] Speed: 68.318242 samples/sec accuracy=83.104167 loss=0.643687 lr=0.000100 Epoch[098] Batch [0199]/[3759] Speed: 67.722478 samples/sec accuracy=83.640625 loss=0.628931 lr=0.000100 Epoch[098] Batch [0249]/[3759] Speed: 68.307935 samples/sec accuracy=83.806250 loss=0.626289 lr=0.000100 Epoch[098] Batch [0299]/[3759] Speed: 67.382867 samples/sec accuracy=83.984375 loss=0.624023 lr=0.000100 Epoch[098] Batch [0349]/[3759] Speed: 67.968885 samples/sec accuracy=84.125000 loss=0.619376 lr=0.000100 Epoch[098] Batch [0399]/[3759] Speed: 68.362299 samples/sec accuracy=84.082031 loss=0.623322 lr=0.000100 Epoch[098] Batch [0449]/[3759] Speed: 68.120005 samples/sec accuracy=83.961806 loss=0.626870 lr=0.000100 Epoch[098] Batch [0499]/[3759] Speed: 68.010849 samples/sec accuracy=83.971875 loss=0.627139 lr=0.000100 Epoch[098] Batch [0549]/[3759] Speed: 67.924465 samples/sec accuracy=83.917614 loss=0.630855 lr=0.000100 Epoch[098] Batch [0599]/[3759] Speed: 67.935860 samples/sec accuracy=83.875000 loss=0.633508 lr=0.000100 Epoch[098] Batch [0649]/[3759] Speed: 67.905390 samples/sec accuracy=83.822115 loss=0.635458 lr=0.000100 Epoch[098] Batch [0699]/[3759] Speed: 67.559930 samples/sec accuracy=83.754464 loss=0.637719 lr=0.000100 Epoch[098] Batch [0749]/[3759] Speed: 67.847816 samples/sec accuracy=83.783333 loss=0.636647 lr=0.000100 Epoch[098] Batch [0799]/[3759] Speed: 68.132839 samples/sec accuracy=83.761719 loss=0.638505 lr=0.000100 Epoch[098] Batch [0849]/[3759] Speed: 67.144687 samples/sec accuracy=83.724265 loss=0.639160 lr=0.000100 Epoch[098] Batch [0899]/[3759] Speed: 68.499150 samples/sec accuracy=83.779514 loss=0.638682 lr=0.000100 Epoch[098] 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accuracy=83.823661 loss=0.638602 lr=0.000100 Epoch[098] Batch [1449]/[3759] Speed: 67.820046 samples/sec accuracy=83.778017 loss=0.639527 lr=0.000100 Epoch[098] Batch [1499]/[3759] Speed: 67.896282 samples/sec accuracy=83.760417 loss=0.639891 lr=0.000100 Epoch[098] Batch [1549]/[3759] Speed: 68.284812 samples/sec accuracy=83.747984 loss=0.639402 lr=0.000100 Epoch[098] Batch [1599]/[3759] Speed: 67.658214 samples/sec accuracy=83.715820 loss=0.640393 lr=0.000100 Epoch[098] Batch [1649]/[3759] Speed: 67.809527 samples/sec accuracy=83.728220 loss=0.639583 lr=0.000100 Epoch[098] Batch [1699]/[3759] Speed: 67.909596 samples/sec accuracy=83.719669 loss=0.639535 lr=0.000100 Epoch[098] Batch [1749]/[3759] Speed: 67.820620 samples/sec accuracy=83.740179 loss=0.638917 lr=0.000100 Epoch[098] Batch [1799]/[3759] Speed: 67.665518 samples/sec accuracy=83.724826 loss=0.639489 lr=0.000100 Epoch[098] Batch [1849]/[3759] Speed: 68.391908 samples/sec accuracy=83.731419 loss=0.639761 lr=0.000100 Epoch[098] 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accuracy=83.680851 loss=0.640714 lr=0.000100 Epoch[098] Batch [2399]/[3759] Speed: 67.970633 samples/sec accuracy=83.679688 loss=0.640973 lr=0.000100 Epoch[098] Batch [2449]/[3759] Speed: 67.571283 samples/sec accuracy=83.686224 loss=0.640874 lr=0.000100 Epoch[098] Batch [2499]/[3759] Speed: 67.229459 samples/sec accuracy=83.679375 loss=0.641201 lr=0.000100 Epoch[098] Batch [2549]/[3759] Speed: 67.825442 samples/sec accuracy=83.661152 loss=0.641755 lr=0.000100 Epoch[098] Batch [2599]/[3759] Speed: 67.512384 samples/sec accuracy=83.635817 loss=0.643035 lr=0.000100 Epoch[098] Batch [2649]/[3759] Speed: 67.567185 samples/sec accuracy=83.628538 loss=0.643411 lr=0.000100 Epoch[098] Batch [2699]/[3759] Speed: 68.472790 samples/sec accuracy=83.648727 loss=0.642712 lr=0.000100 Epoch[098] Batch [2749]/[3759] Speed: 68.562797 samples/sec accuracy=83.642045 loss=0.642752 lr=0.000100 Epoch[098] Batch [2799]/[3759] Speed: 67.944700 samples/sec accuracy=83.645089 loss=0.642728 lr=0.000100 Epoch[098] 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accuracy=83.679924 loss=0.641302 lr=0.000100 Epoch[098] Batch [3349]/[3759] Speed: 68.033807 samples/sec accuracy=83.690299 loss=0.640765 lr=0.000100 Epoch[098] Batch [3399]/[3759] Speed: 68.345791 samples/sec accuracy=83.692555 loss=0.640857 lr=0.000100 Epoch[098] Batch [3449]/[3759] Speed: 67.590370 samples/sec accuracy=83.696105 loss=0.640878 lr=0.000100 Epoch[098] Batch [3499]/[3759] Speed: 68.563681 samples/sec accuracy=83.681250 loss=0.641467 lr=0.000100 Epoch[098] Batch [3549]/[3759] Speed: 68.095689 samples/sec accuracy=83.682658 loss=0.641648 lr=0.000100 Epoch[098] Batch [3599]/[3759] Speed: 67.665029 samples/sec accuracy=83.672309 loss=0.641950 lr=0.000100 Epoch[098] Batch [3649]/[3759] Speed: 67.396558 samples/sec accuracy=83.664384 loss=0.642097 lr=0.000100 Epoch[098] Batch [3699]/[3759] Speed: 68.565548 samples/sec accuracy=83.665541 loss=0.641875 lr=0.000100 Epoch[098] Batch [3749]/[3759] Speed: 73.364816 samples/sec accuracy=83.673333 loss=0.641821 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.218750 acc-top5=86.187500 Batch [0099]/[0303]: acc-top1=67.296875 acc-top5=85.953125 Batch [0149]/[0303]: acc-top1=67.197917 acc-top5=86.312500 Batch [0199]/[0303]: acc-top1=67.351562 acc-top5=86.250000 Batch [0249]/[0303]: acc-top1=67.268750 acc-top5=86.262500 Batch [0299]/[0303]: acc-top1=67.281250 acc-top5=86.442708 [Epoch 098] training: accuracy=83.674598 loss=0.641754 [Epoch 098] speed: 67 samples/sec time cost: 3831.937515 [Epoch 098] validation: acc-top1=67.316419 acc-top5=86.478960 loss=1.672725 Epoch[099] Batch [0049]/[3760] Speed: 45.426963 samples/sec accuracy=83.718750 loss=0.645039 lr=0.000100 Epoch[099] Batch [0099]/[3760] Speed: 66.746226 samples/sec accuracy=83.515625 loss=0.644509 lr=0.000100 Epoch[099] Batch [0149]/[3760] Speed: 68.048493 samples/sec accuracy=83.489583 loss=0.654372 lr=0.000100 Epoch[099] Batch [0199]/[3760] Speed: 67.770025 samples/sec accuracy=83.609375 loss=0.654960 lr=0.000100 Epoch[099] Batch [0249]/[3760] Speed: 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lr=0.000100 Epoch[099] Batch [0749]/[3760] Speed: 68.277797 samples/sec accuracy=83.570833 loss=0.647079 lr=0.000100 Epoch[099] Batch [0799]/[3760] Speed: 68.079462 samples/sec accuracy=83.541016 loss=0.648563 lr=0.000100 Epoch[099] Batch [0849]/[3760] Speed: 68.177795 samples/sec accuracy=83.522059 loss=0.649697 lr=0.000100 Epoch[099] Batch [0899]/[3760] Speed: 68.177639 samples/sec accuracy=83.546875 loss=0.648603 lr=0.000100 Epoch[099] Batch [0949]/[3760] Speed: 68.229310 samples/sec accuracy=83.569079 loss=0.648135 lr=0.000100 Epoch[099] Batch [0999]/[3760] Speed: 68.030511 samples/sec accuracy=83.573437 loss=0.647830 lr=0.000100 Epoch[099] Batch [1049]/[3760] Speed: 68.017339 samples/sec accuracy=83.532738 loss=0.649663 lr=0.000100 Epoch[099] Batch [1099]/[3760] Speed: 67.789427 samples/sec accuracy=83.544034 loss=0.648926 lr=0.000100 Epoch[099] Batch [1149]/[3760] Speed: 66.974337 samples/sec accuracy=83.570652 loss=0.647627 lr=0.000100 Epoch[099] Batch [1199]/[3760] Speed: 68.794014 samples/sec accuracy=83.598958 loss=0.646910 lr=0.000100 Epoch[099] Batch [1249]/[3760] Speed: 68.076150 samples/sec accuracy=83.585000 loss=0.647149 lr=0.000100 Epoch[099] Batch [1299]/[3760] Speed: 67.801944 samples/sec accuracy=83.562500 loss=0.648708 lr=0.000100 Epoch[099] Batch [1349]/[3760] Speed: 68.487946 samples/sec accuracy=83.568287 loss=0.648004 lr=0.000100 Epoch[099] Batch [1399]/[3760] Speed: 68.567890 samples/sec accuracy=83.577009 loss=0.647158 lr=0.000100 Epoch[099] Batch [1449]/[3760] Speed: 67.934056 samples/sec accuracy=83.572198 loss=0.646340 lr=0.000100 Epoch[099] Batch [1499]/[3760] Speed: 68.050431 samples/sec accuracy=83.567708 loss=0.646230 lr=0.000100 Epoch[099] Batch [1549]/[3760] Speed: 68.116014 samples/sec accuracy=83.565524 loss=0.646209 lr=0.000100 Epoch[099] Batch [1599]/[3760] Speed: 68.203070 samples/sec accuracy=83.580078 loss=0.644951 lr=0.000100 Epoch[099] Batch [1649]/[3760] Speed: 68.404116 samples/sec accuracy=83.626894 loss=0.643075 lr=0.000100 Epoch[099] Batch [1699]/[3760] Speed: 67.884721 samples/sec accuracy=83.651654 loss=0.642679 lr=0.000100 Epoch[099] Batch [1749]/[3760] Speed: 67.380869 samples/sec accuracy=83.641964 loss=0.643298 lr=0.000100 Epoch[099] Batch [1799]/[3760] Speed: 68.173574 samples/sec accuracy=83.644097 loss=0.642645 lr=0.000100 Epoch[099] Batch [1849]/[3760] Speed: 68.206664 samples/sec accuracy=83.641047 loss=0.643081 lr=0.000100 Epoch[099] Batch [1899]/[3760] Speed: 67.925770 samples/sec accuracy=83.625822 loss=0.643148 lr=0.000100 Epoch[099] Batch [1949]/[3760] Speed: 68.001593 samples/sec accuracy=83.627404 loss=0.643163 lr=0.000100 Epoch[099] Batch [1999]/[3760] Speed: 68.052738 samples/sec accuracy=83.623437 loss=0.643234 lr=0.000100 Epoch[099] Batch [2049]/[3760] Speed: 68.089071 samples/sec accuracy=83.626524 loss=0.643236 lr=0.000100 Epoch[099] Batch [2099]/[3760] Speed: 68.165773 samples/sec accuracy=83.610863 loss=0.643518 lr=0.000100 Epoch[099] Batch [2149]/[3760] Speed: 67.749656 samples/sec accuracy=83.626453 loss=0.643136 lr=0.000100 Epoch[099] Batch [2199]/[3760] Speed: 67.822397 samples/sec accuracy=83.629972 loss=0.642529 lr=0.000100 Epoch[099] Batch [2249]/[3760] Speed: 67.950276 samples/sec accuracy=83.650694 loss=0.642262 lr=0.000100 Epoch[099] Batch [2299]/[3760] Speed: 68.022139 samples/sec accuracy=83.647418 loss=0.642031 lr=0.000100 Epoch[099] Batch [2349]/[3760] Speed: 68.076809 samples/sec accuracy=83.650931 loss=0.641763 lr=0.000100 Epoch[099] Batch [2399]/[3760] Speed: 68.123048 samples/sec accuracy=83.634115 loss=0.642534 lr=0.000100 Epoch[099] Batch [2449]/[3760] Speed: 67.822684 samples/sec accuracy=83.644770 loss=0.642499 lr=0.000100 Epoch[099] Batch [2499]/[3760] Speed: 68.078851 samples/sec accuracy=83.644375 loss=0.642118 lr=0.000100 Epoch[099] Batch [2549]/[3760] Speed: 67.817565 samples/sec accuracy=83.636642 loss=0.642267 lr=0.000100 Epoch[099] Batch [2599]/[3760] Speed: 68.531758 samples/sec accuracy=83.626202 loss=0.642217 lr=0.000100 Epoch[099] Batch [2649]/[3760] Speed: 67.988827 samples/sec accuracy=83.622052 loss=0.641872 lr=0.000100 Epoch[099] Batch [2699]/[3760] Speed: 67.811535 samples/sec accuracy=83.636574 loss=0.642043 lr=0.000100 Epoch[099] Batch [2749]/[3760] Speed: 68.528862 samples/sec accuracy=83.625568 loss=0.642273 lr=0.000100 Epoch[099] Batch [2799]/[3760] Speed: 67.833253 samples/sec accuracy=83.652902 loss=0.641437 lr=0.000100 Epoch[099] Batch [2849]/[3760] Speed: 68.173691 samples/sec accuracy=83.647478 loss=0.641243 lr=0.000100 Epoch[099] Batch [2899]/[3760] Speed: 66.984534 samples/sec accuracy=83.645474 loss=0.641618 lr=0.000100 Epoch[099] Batch [2949]/[3760] Speed: 68.915664 samples/sec accuracy=83.661547 loss=0.641429 lr=0.000100 Epoch[099] Batch [2999]/[3760] Speed: 68.615392 samples/sec accuracy=83.657812 loss=0.641455 lr=0.000100 Epoch[099] Batch [3049]/[3760] Speed: 67.849110 samples/sec accuracy=83.661373 loss=0.641138 lr=0.000100 Epoch[099] Batch [3099]/[3760] Speed: 67.837238 samples/sec accuracy=83.692540 loss=0.640256 lr=0.000100 Epoch[099] Batch [3149]/[3760] Speed: 68.282886 samples/sec accuracy=83.666171 loss=0.641241 lr=0.000100 Epoch[099] Batch [3199]/[3760] Speed: 68.268314 samples/sec accuracy=83.685059 loss=0.640699 lr=0.000100 Epoch[099] Batch [3249]/[3760] Speed: 68.350422 samples/sec accuracy=83.679327 loss=0.641051 lr=0.000100 Epoch[099] Batch [3299]/[3760] Speed: 67.756499 samples/sec accuracy=83.682292 loss=0.641223 lr=0.000100 Epoch[099] Batch [3349]/[3760] Speed: 68.225066 samples/sec accuracy=83.675373 loss=0.641392 lr=0.000100 Epoch[099] Batch [3399]/[3760] Speed: 68.067931 samples/sec accuracy=83.672794 loss=0.641518 lr=0.000100 Epoch[099] Batch [3449]/[3760] Speed: 67.606999 samples/sec accuracy=83.665308 loss=0.641722 lr=0.000100 Epoch[099] Batch [3499]/[3760] Speed: 67.784365 samples/sec accuracy=83.674554 loss=0.641539 lr=0.000100 Epoch[099] Batch [3549]/[3760] Speed: 67.879870 samples/sec accuracy=83.672095 loss=0.641740 lr=0.000100 Epoch[099] Batch [3599]/[3760] Speed: 68.334603 samples/sec accuracy=83.651476 loss=0.642054 lr=0.000100 Epoch[099] Batch [3649]/[3760] Speed: 68.411507 samples/sec accuracy=83.657106 loss=0.641896 lr=0.000100 Epoch[099] Batch [3699]/[3760] Speed: 68.132536 samples/sec accuracy=83.662162 loss=0.641845 lr=0.000100 Epoch[099] Batch [3749]/[3760] Speed: 74.403818 samples/sec accuracy=83.664583 loss=0.641875 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.093750 acc-top5=86.125000 Batch [0099]/[0303]: acc-top1=67.218750 acc-top5=85.781250 Batch [0149]/[0303]: acc-top1=67.229167 acc-top5=86.302083 Batch [0199]/[0303]: acc-top1=67.437500 acc-top5=86.335938 Batch [0249]/[0303]: acc-top1=67.250000 acc-top5=86.443750 Batch [0299]/[0303]: acc-top1=67.380208 acc-top5=86.593750 [Epoch 099] training: accuracy=83.661486 loss=0.641915 [Epoch 099] speed: 67 samples/sec time cost: 3826.612679 [Epoch 099] validation: acc-top1=67.409241 acc-top5=86.618193 loss=1.670871