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_nl5_res50_seg1_kinetics400_b8_g8_inflate311_f32s2_step_nosample_norm_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_nl5_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_nl5_res50_seg1_kinetics400_b8_g8_inflate311_f32s2_step_nosample_norm_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) ) (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) ) ) (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) ) (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) ) (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) ) (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) ) ) (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) ) (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) ) (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) ) (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) ) (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. Epoch[000] Batch [0049]/[3759] Speed: 35.564150 samples/sec accuracy=1.031250 loss=5.915680 lr=0.010000 Epoch[000] Batch [0099]/[3759] Speed: 68.181889 samples/sec accuracy=1.953125 loss=5.782330 lr=0.010000 Epoch[000] Batch [0149]/[3759] Speed: 69.850875 samples/sec accuracy=2.854167 loss=5.640296 lr=0.010000 Epoch[000] Batch [0199]/[3759] Speed: 68.917797 samples/sec accuracy=3.539062 loss=5.513441 lr=0.010000 Epoch[000] Batch [0249]/[3759] Speed: 70.566089 samples/sec accuracy=4.131250 loss=5.399374 lr=0.010000 Epoch[000] Batch [0299]/[3759] Speed: 68.066076 samples/sec accuracy=4.911458 loss=5.290510 lr=0.010000 Epoch[000] Batch [0349]/[3759] Speed: 68.711207 samples/sec accuracy=5.517857 loss=5.199256 lr=0.010000 Epoch[000] Batch [0399]/[3759] Speed: 69.475298 samples/sec accuracy=6.214844 loss=5.115594 lr=0.010000 Epoch[000] Batch [0449]/[3759] Speed: 68.910249 samples/sec accuracy=6.753472 loss=5.051429 lr=0.010000 Epoch[000] Batch [0499]/[3759] Speed: 70.332147 samples/sec 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accuracy=18.567057 loss=3.999321 lr=0.010000 Epoch[000] Batch [2449]/[3759] Speed: 69.898493 samples/sec accuracy=18.738520 loss=3.986058 lr=0.010000 Epoch[000] Batch [2499]/[3759] Speed: 68.727560 samples/sec accuracy=18.942500 loss=3.972516 lr=0.010000 Epoch[000] Batch [2549]/[3759] Speed: 69.015966 samples/sec accuracy=19.095588 loss=3.960071 lr=0.010000 Epoch[000] Batch [2599]/[3759] Speed: 68.916756 samples/sec accuracy=19.262019 loss=3.948112 lr=0.010000 Epoch[000] Batch [2649]/[3759] Speed: 68.560652 samples/sec accuracy=19.441038 loss=3.935976 lr=0.010000 Epoch[000] Batch [2699]/[3759] Speed: 69.413577 samples/sec accuracy=19.606481 loss=3.923664 lr=0.010000 Epoch[000] Batch [2749]/[3759] Speed: 68.839745 samples/sec accuracy=19.766477 loss=3.912233 lr=0.010000 Epoch[000] Batch [2799]/[3759] Speed: 68.855163 samples/sec accuracy=19.925781 loss=3.899897 lr=0.010000 Epoch[000] Batch [2849]/[3759] Speed: 69.403948 samples/sec accuracy=20.074013 loss=3.888592 lr=0.010000 Epoch[000] 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accuracy=21.611940 loss=3.782442 lr=0.010000 Epoch[000] Batch [3399]/[3759] Speed: 69.019368 samples/sec accuracy=21.740349 loss=3.772980 lr=0.010000 Epoch[000] Batch [3449]/[3759] Speed: 69.193519 samples/sec accuracy=21.883605 loss=3.763867 lr=0.010000 Epoch[000] Batch [3499]/[3759] Speed: 70.466512 samples/sec accuracy=22.016071 loss=3.755170 lr=0.010000 Epoch[000] Batch [3549]/[3759] Speed: 68.529842 samples/sec accuracy=22.148327 loss=3.745868 lr=0.010000 Epoch[000] Batch [3599]/[3759] Speed: 70.139047 samples/sec accuracy=22.274306 loss=3.736893 lr=0.010000 Epoch[000] Batch [3649]/[3759] Speed: 69.072001 samples/sec accuracy=22.379709 loss=3.727967 lr=0.010000 Epoch[000] Batch [3699]/[3759] Speed: 69.016664 samples/sec accuracy=22.510557 loss=3.719682 lr=0.010000 Epoch[000] Batch [3749]/[3759] Speed: 77.620485 samples/sec accuracy=22.631250 loss=3.710903 lr=0.010000 Batch [0049]/[0303]: acc-top1=33.875000 acc-top5=63.500000 Batch [0099]/[0303]: acc-top1=34.265625 acc-top5=62.734375 Batch [0149]/[0303]: acc-top1=34.395833 acc-top5=62.322917 Batch [0199]/[0303]: acc-top1=34.312500 acc-top5=62.281250 Batch [0249]/[0303]: acc-top1=34.225000 acc-top5=62.118750 Batch [0299]/[0303]: acc-top1=34.343750 acc-top5=61.953125 [Epoch 000] training: accuracy=22.663524 loss=3.708944 [Epoch 000] speed: 68 samples/sec time cost: 3818.279520 [Epoch 000] validation: acc-top1=34.405941 acc-top5=61.994637 loss=3.005398 Epoch[001] Batch [0049]/[3760] Speed: 48.264535 samples/sec accuracy=32.250000 loss=3.018234 lr=0.010000 Epoch[001] Batch [0099]/[3760] Speed: 68.562870 samples/sec accuracy=32.265625 loss=3.035879 lr=0.010000 Epoch[001] Batch [0149]/[3760] Speed: 68.613637 samples/sec accuracy=32.822917 loss=3.015355 lr=0.010000 Epoch[001] Batch [0199]/[3760] Speed: 69.091317 samples/sec accuracy=33.101562 loss=2.995791 lr=0.010000 Epoch[001] Batch [0249]/[3760] Speed: 69.338648 samples/sec accuracy=33.062500 loss=2.994127 lr=0.010000 Epoch[001] Batch [0299]/[3760] 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loss=2.956252 lr=0.010000 Epoch[001] Batch [0799]/[3760] Speed: 69.413684 samples/sec accuracy=33.914062 loss=2.956058 lr=0.010000 Epoch[001] Batch [0849]/[3760] Speed: 69.070017 samples/sec accuracy=34.038603 loss=2.952926 lr=0.010000 Epoch[001] Batch [0899]/[3760] Speed: 68.900331 samples/sec accuracy=34.239583 loss=2.946002 lr=0.010000 Epoch[001] Batch [0949]/[3760] Speed: 69.116824 samples/sec accuracy=34.292763 loss=2.944333 lr=0.010000 Epoch[001] Batch [0999]/[3760] Speed: 69.030692 samples/sec accuracy=34.285938 loss=2.942643 lr=0.010000 Epoch[001] Batch [1049]/[3760] Speed: 68.745788 samples/sec accuracy=34.331845 loss=2.937133 lr=0.010000 Epoch[001] Batch [1099]/[3760] Speed: 69.189472 samples/sec accuracy=34.424716 loss=2.931325 lr=0.010000 Epoch[001] Batch [1149]/[3760] Speed: 67.773381 samples/sec accuracy=34.498641 loss=2.926064 lr=0.010000 Epoch[001] Batch [1199]/[3760] Speed: 68.634500 samples/sec accuracy=34.514323 loss=2.925867 lr=0.010000 Epoch[001] Batch 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accuracy=35.218750 loss=2.893818 lr=0.010000 Epoch[001] Batch [1749]/[3760] Speed: 68.579968 samples/sec accuracy=35.273214 loss=2.890032 lr=0.010000 Epoch[001] Batch [1799]/[3760] Speed: 68.808602 samples/sec accuracy=35.308160 loss=2.886703 lr=0.010000 Epoch[001] Batch [1849]/[3760] Speed: 68.594285 samples/sec accuracy=35.354730 loss=2.883694 lr=0.010000 Epoch[001] Batch [1899]/[3760] Speed: 68.868973 samples/sec accuracy=35.395559 loss=2.880116 lr=0.010000 Epoch[001] Batch [1949]/[3760] Speed: 68.790543 samples/sec accuracy=35.437500 loss=2.878083 lr=0.010000 Epoch[001] Batch [1999]/[3760] Speed: 69.205491 samples/sec accuracy=35.496875 loss=2.876171 lr=0.010000 Epoch[001] Batch [2049]/[3760] Speed: 69.624131 samples/sec accuracy=35.549543 loss=2.873907 lr=0.010000 Epoch[001] Batch [2099]/[3760] Speed: 68.693131 samples/sec accuracy=35.584821 loss=2.871240 lr=0.010000 Epoch[001] Batch [2149]/[3760] Speed: 68.829479 samples/sec accuracy=35.652616 loss=2.867563 lr=0.010000 Epoch[001] 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accuracy=35.981722 loss=2.846071 lr=0.010000 Epoch[001] Batch [2699]/[3760] Speed: 68.658922 samples/sec accuracy=36.035301 loss=2.843304 lr=0.010000 Epoch[001] Batch [2749]/[3760] Speed: 68.613843 samples/sec accuracy=36.040909 loss=2.841249 lr=0.010000 Epoch[001] Batch [2799]/[3760] Speed: 68.373919 samples/sec accuracy=36.079241 loss=2.839190 lr=0.010000 Epoch[001] Batch [2849]/[3760] Speed: 69.200176 samples/sec accuracy=36.126645 loss=2.836150 lr=0.010000 Epoch[001] Batch [2899]/[3760] Speed: 68.465926 samples/sec accuracy=36.171336 loss=2.833907 lr=0.010000 Epoch[001] Batch [2949]/[3760] Speed: 69.117081 samples/sec accuracy=36.225106 loss=2.831898 lr=0.010000 Epoch[001] Batch [2999]/[3760] Speed: 68.433941 samples/sec accuracy=36.260938 loss=2.829809 lr=0.010000 Epoch[001] Batch [3049]/[3760] Speed: 68.748586 samples/sec accuracy=36.294570 loss=2.828829 lr=0.010000 Epoch[001] Batch [3099]/[3760] Speed: 67.549816 samples/sec accuracy=36.345766 loss=2.826319 lr=0.010000 Epoch[001] Batch [3149]/[3760] Speed: 68.758344 samples/sec accuracy=36.376984 loss=2.824704 lr=0.010000 Epoch[001] Batch [3199]/[3760] Speed: 68.033451 samples/sec accuracy=36.416016 loss=2.822483 lr=0.010000 Epoch[001] Batch [3249]/[3760] Speed: 68.498995 samples/sec accuracy=36.452885 loss=2.820651 lr=0.010000 Epoch[001] Batch [3299]/[3760] Speed: 69.495921 samples/sec accuracy=36.464489 loss=2.818638 lr=0.010000 Epoch[001] Batch [3349]/[3760] Speed: 67.666177 samples/sec accuracy=36.520989 loss=2.815979 lr=0.010000 Epoch[001] Batch [3399]/[3760] Speed: 68.817560 samples/sec accuracy=36.576746 loss=2.813238 lr=0.010000 Epoch[001] Batch [3449]/[3760] Speed: 67.751687 samples/sec accuracy=36.638587 loss=2.810937 lr=0.010000 Epoch[001] Batch [3499]/[3760] Speed: 69.208223 samples/sec accuracy=36.682589 loss=2.808025 lr=0.010000 Epoch[001] Batch [3549]/[3760] Speed: 68.637571 samples/sec accuracy=36.731074 loss=2.805352 lr=0.010000 Epoch[001] Batch [3599]/[3760] Speed: 68.671324 samples/sec accuracy=36.783420 loss=2.802803 lr=0.010000 Epoch[001] Batch [3649]/[3760] Speed: 68.649353 samples/sec accuracy=36.821490 loss=2.800690 lr=0.010000 Epoch[001] Batch [3699]/[3760] Speed: 68.960622 samples/sec accuracy=36.859375 loss=2.798764 lr=0.010000 Epoch[001] Batch [3749]/[3760] Speed: 76.891420 samples/sec accuracy=36.895417 loss=2.797261 lr=0.010000 Batch [0049]/[0303]: acc-top1=44.375000 acc-top5=70.593750 Batch [0099]/[0303]: acc-top1=43.828125 acc-top5=70.640625 Batch [0149]/[0303]: acc-top1=43.520833 acc-top5=70.416667 Batch [0199]/[0303]: acc-top1=43.507812 acc-top5=70.320312 Batch [0249]/[0303]: acc-top1=43.318750 acc-top5=70.362500 Batch [0299]/[0303]: acc-top1=43.380208 acc-top5=70.281250 [Epoch 001] training: accuracy=36.899934 loss=2.796918 [Epoch 001] speed: 68 samples/sec time cost: 3815.436538 [Epoch 001] validation: acc-top1=43.425124 acc-top5=70.338284 loss=2.529805 Epoch[002] Batch [0049]/[3759] Speed: 47.786530 samples/sec accuracy=41.156250 loss=2.590063 lr=0.010000 Epoch[002] Batch [0099]/[3759] Speed: 68.727560 samples/sec accuracy=41.500000 loss=2.540938 lr=0.010000 Epoch[002] Batch [0149]/[3759] Speed: 68.430533 samples/sec accuracy=41.052083 loss=2.561126 lr=0.010000 Epoch[002] Batch [0199]/[3759] Speed: 68.480493 samples/sec accuracy=41.234375 loss=2.552599 lr=0.010000 Epoch[002] Batch [0249]/[3759] Speed: 69.464284 samples/sec accuracy=41.387500 loss=2.552875 lr=0.010000 Epoch[002] Batch [0299]/[3759] Speed: 68.684559 samples/sec accuracy=41.473958 loss=2.555574 lr=0.010000 Epoch[002] Batch [0349]/[3759] Speed: 68.669831 samples/sec accuracy=41.508929 loss=2.552481 lr=0.010000 Epoch[002] Batch [0399]/[3759] Speed: 69.159198 samples/sec accuracy=41.597656 loss=2.549858 lr=0.010000 Epoch[002] Batch [0449]/[3759] Speed: 69.138952 samples/sec accuracy=41.583333 loss=2.545563 lr=0.010000 Epoch[002] Batch [0499]/[3759] Speed: 68.216429 samples/sec accuracy=41.493750 loss=2.549937 lr=0.010000 Epoch[002] Batch [0549]/[3759] Speed: 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acc-top1=47.484375 acc-top5=73.960938 Batch [0249]/[0303]: acc-top1=47.406250 acc-top5=73.800000 Batch [0299]/[0303]: acc-top1=47.406250 acc-top5=73.682292 [Epoch 002] training: accuracy=42.634760 loss=2.488094 [Epoch 002] speed: 68 samples/sec time cost: 3809.656870 [Epoch 002] validation: acc-top1=47.426774 acc-top5=73.659241 loss=2.318383 Epoch[003] Batch [0049]/[3760] Speed: 47.590988 samples/sec accuracy=44.843750 loss=2.343050 lr=0.010000 Epoch[003] Batch [0099]/[3760] Speed: 68.778075 samples/sec accuracy=44.796875 loss=2.348568 lr=0.010000 Epoch[003] Batch [0149]/[3760] Speed: 68.819370 samples/sec accuracy=45.031250 loss=2.350907 lr=0.010000 Epoch[003] Batch [0199]/[3760] Speed: 68.216353 samples/sec accuracy=45.148438 loss=2.348838 lr=0.010000 Epoch[003] Batch [0249]/[3760] Speed: 68.508866 samples/sec accuracy=45.037500 loss=2.359843 lr=0.010000 Epoch[003] Batch [0299]/[3760] Speed: 68.406133 samples/sec accuracy=45.015625 loss=2.358148 lr=0.010000 Epoch[003] Batch 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accuracy=46.052226 loss=2.312113 lr=0.010000 Epoch[003] Batch [3699]/[3760] Speed: 68.400469 samples/sec accuracy=46.081503 loss=2.311180 lr=0.010000 Epoch[003] Batch [3749]/[3760] Speed: 78.252529 samples/sec accuracy=46.092917 loss=2.310604 lr=0.010000 Batch [0049]/[0303]: acc-top1=49.468750 acc-top5=76.687500 Batch [0099]/[0303]: acc-top1=49.656250 acc-top5=76.578125 Batch [0149]/[0303]: acc-top1=49.322917 acc-top5=76.010417 Batch [0199]/[0303]: acc-top1=49.304688 acc-top5=75.703125 Batch [0249]/[0303]: acc-top1=49.393750 acc-top5=75.568750 Batch [0299]/[0303]: acc-top1=49.489583 acc-top5=75.390625 [Epoch 003] training: accuracy=46.103308 loss=2.310261 [Epoch 003] speed: 68 samples/sec time cost: 3800.693044 [Epoch 003] validation: acc-top1=49.504950 acc-top5=75.428012 loss=2.250026 Epoch[004] Batch [0049]/[3760] Speed: 48.028263 samples/sec accuracy=49.625000 loss=2.134778 lr=0.010000 Epoch[004] Batch [0099]/[3760] Speed: 68.966358 samples/sec accuracy=48.546875 loss=2.184548 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[0299]/[0303]: acc-top1=50.333333 acc-top5=75.828125 [Epoch 004] training: accuracy=48.774102 loss=2.183927 [Epoch 004] speed: 68 samples/sec time cost: 3795.216446 [Epoch 004] validation: acc-top1=50.366130 acc-top5=75.850866 loss=2.212009 Epoch[005] Batch [0049]/[3759] Speed: 47.148229 samples/sec accuracy=52.906250 loss=2.037963 lr=0.010000 Epoch[005] Batch [0099]/[3759] Speed: 68.711239 samples/sec accuracy=51.015625 loss=2.065233 lr=0.010000 Epoch[005] Batch [0149]/[3759] Speed: 69.052116 samples/sec accuracy=50.718750 loss=2.076056 lr=0.010000 Epoch[005] Batch [0199]/[3759] Speed: 68.603957 samples/sec accuracy=50.929688 loss=2.075846 lr=0.010000 Epoch[005] Batch [0249]/[3759] Speed: 69.015618 samples/sec accuracy=50.856250 loss=2.069265 lr=0.010000 Epoch[005] Batch [0299]/[3759] Speed: 68.669331 samples/sec accuracy=50.546875 loss=2.077255 lr=0.010000 Epoch[005] Batch [0349]/[3759] Speed: 68.729098 samples/sec accuracy=50.656250 loss=2.081725 lr=0.010000 Epoch[005] Batch 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accuracy=50.361064 loss=2.094140 lr=0.010000 Epoch[005] Batch [3749]/[3759] Speed: 78.001585 samples/sec accuracy=50.350417 loss=2.094176 lr=0.010000 Batch [0049]/[0303]: acc-top1=52.906250 acc-top5=78.968750 Batch [0099]/[0303]: acc-top1=51.921875 acc-top5=79.062500 Batch [0149]/[0303]: acc-top1=52.125000 acc-top5=78.343750 Batch [0199]/[0303]: acc-top1=52.210938 acc-top5=77.882812 Batch [0249]/[0303]: acc-top1=52.081250 acc-top5=77.906250 Batch [0299]/[0303]: acc-top1=52.161458 acc-top5=77.755208 [Epoch 005] training: accuracy=50.363295 loss=2.093752 [Epoch 005] speed: 68 samples/sec time cost: 3788.688291 [Epoch 005] validation: acc-top1=52.238036 acc-top5=77.815594 loss=2.094707 Epoch[006] Batch [0049]/[3760] Speed: 48.383070 samples/sec accuracy=54.093750 loss=1.925302 lr=0.010000 Epoch[006] Batch [0099]/[3760] Speed: 69.014431 samples/sec accuracy=54.125000 loss=1.942802 lr=0.010000 Epoch[006] Batch [0149]/[3760] Speed: 69.080005 samples/sec accuracy=53.000000 loss=1.990248 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lr=0.010000 Epoch[006] Batch [3049]/[3760] Speed: 69.309853 samples/sec accuracy=52.098361 loss=2.015052 lr=0.010000 Epoch[006] Batch [3099]/[3760] Speed: 68.527276 samples/sec accuracy=52.087702 loss=2.014817 lr=0.010000 Epoch[006] Batch [3149]/[3760] Speed: 69.945809 samples/sec accuracy=52.095734 loss=2.014583 lr=0.010000 Epoch[006] Batch [3199]/[3760] Speed: 69.891279 samples/sec accuracy=52.085938 loss=2.015239 lr=0.010000 Epoch[006] Batch [3249]/[3760] Speed: 68.996514 samples/sec accuracy=52.070192 loss=2.016108 lr=0.010000 Epoch[006] Batch [3299]/[3760] Speed: 69.280861 samples/sec accuracy=52.077178 loss=2.015916 lr=0.010000 Epoch[006] Batch [3349]/[3760] Speed: 69.078744 samples/sec accuracy=52.075560 loss=2.017007 lr=0.010000 Epoch[006] Batch [3399]/[3760] Speed: 69.159130 samples/sec accuracy=52.084099 loss=2.016195 lr=0.010000 Epoch[006] Batch [3449]/[3760] Speed: 68.693251 samples/sec accuracy=52.098279 loss=2.015826 lr=0.010000 Epoch[006] Batch [3499]/[3760] Speed: 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[Epoch 006] speed: 68 samples/sec time cost: 3778.351511 [Epoch 006] validation: acc-top1=53.465347 acc-top5=78.645833 loss=2.058814 Epoch[007] Batch [0049]/[3760] Speed: 47.619881 samples/sec accuracy=54.281250 loss=1.880963 lr=0.010000 Epoch[007] Batch [0099]/[3760] Speed: 68.070032 samples/sec accuracy=54.406250 loss=1.880850 lr=0.010000 Epoch[007] Batch [0149]/[3760] Speed: 69.350424 samples/sec accuracy=53.687500 loss=1.909355 lr=0.010000 Epoch[007] Batch [0199]/[3760] Speed: 69.668033 samples/sec accuracy=53.601562 loss=1.924572 lr=0.010000 Epoch[007] Batch [0249]/[3760] Speed: 69.552254 samples/sec accuracy=53.450000 loss=1.938072 lr=0.010000 Epoch[007] Batch [0299]/[3760] Speed: 69.309275 samples/sec accuracy=53.468750 loss=1.943848 lr=0.010000 Epoch[007] Batch [0349]/[3760] Speed: 69.480702 samples/sec accuracy=53.598214 loss=1.942756 lr=0.010000 Epoch[007] Batch [0399]/[3760] Speed: 69.282419 samples/sec accuracy=53.632813 loss=1.942808 lr=0.010000 Epoch[007] Batch 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accuracy=53.682292 loss=1.935473 lr=0.010000 Epoch[007] Batch [0949]/[3760] Speed: 68.611101 samples/sec accuracy=53.605263 loss=1.937692 lr=0.010000 Epoch[007] Batch [0999]/[3760] Speed: 68.918091 samples/sec accuracy=53.528125 loss=1.940677 lr=0.010000 Epoch[007] Batch [1049]/[3760] Speed: 69.650994 samples/sec accuracy=53.522321 loss=1.941318 lr=0.010000 Epoch[007] Batch [1099]/[3760] Speed: 69.729042 samples/sec accuracy=53.494318 loss=1.942906 lr=0.010000 Epoch[007] Batch [1149]/[3760] Speed: 68.899394 samples/sec accuracy=53.442935 loss=1.945133 lr=0.010000 Epoch[007] Batch [1199]/[3760] Speed: 69.491030 samples/sec accuracy=53.489583 loss=1.944145 lr=0.010000 Epoch[007] Batch [1249]/[3760] Speed: 68.982183 samples/sec accuracy=53.521250 loss=1.944678 lr=0.010000 Epoch[007] Batch [1299]/[3760] Speed: 69.167468 samples/sec accuracy=53.524038 loss=1.946599 lr=0.010000 Epoch[007] Batch [1349]/[3760] Speed: 68.976127 samples/sec accuracy=53.475694 loss=1.949214 lr=0.010000 Epoch[007] 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accuracy=53.470439 loss=1.956571 lr=0.010000 Epoch[007] Batch [1899]/[3760] Speed: 69.457036 samples/sec accuracy=53.491776 loss=1.956040 lr=0.010000 Epoch[007] Batch [1949]/[3760] Speed: 69.047717 samples/sec accuracy=53.478365 loss=1.955694 lr=0.010000 Epoch[007] Batch [1999]/[3760] Speed: 69.813146 samples/sec accuracy=53.491406 loss=1.954538 lr=0.010000 Epoch[007] Batch [2049]/[3760] Speed: 68.826694 samples/sec accuracy=53.516006 loss=1.954563 lr=0.010000 Epoch[007] Batch [2099]/[3760] Speed: 68.894842 samples/sec accuracy=53.501488 loss=1.955068 lr=0.010000 Epoch[007] Batch [2149]/[3760] Speed: 69.433132 samples/sec accuracy=53.484012 loss=1.955659 lr=0.010000 Epoch[007] Batch [2199]/[3760] Speed: 69.407217 samples/sec accuracy=53.495739 loss=1.955616 lr=0.010000 Epoch[007] Batch [2249]/[3760] Speed: 68.798284 samples/sec accuracy=53.467361 loss=1.956763 lr=0.010000 Epoch[007] Batch [2299]/[3760] Speed: 69.622367 samples/sec accuracy=53.472147 loss=1.956507 lr=0.010000 Epoch[007] 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accuracy=53.430246 loss=1.957075 lr=0.010000 Epoch[007] Batch [2849]/[3760] Speed: 69.394722 samples/sec accuracy=53.430921 loss=1.956805 lr=0.010000 Epoch[007] Batch [2899]/[3760] Speed: 70.036895 samples/sec accuracy=53.425108 loss=1.956885 lr=0.010000 Epoch[007] Batch [2949]/[3760] Speed: 69.613172 samples/sec accuracy=53.424788 loss=1.956949 lr=0.010000 Epoch[007] Batch [2999]/[3760] Speed: 69.696780 samples/sec accuracy=53.428646 loss=1.956949 lr=0.010000 Epoch[007] Batch [3049]/[3760] Speed: 69.458233 samples/sec accuracy=53.411373 loss=1.957452 lr=0.010000 Epoch[007] Batch [3099]/[3760] Speed: 69.769602 samples/sec accuracy=53.408770 loss=1.957739 lr=0.010000 Epoch[007] Batch [3149]/[3760] Speed: 68.790418 samples/sec accuracy=53.405258 loss=1.957687 lr=0.010000 Epoch[007] Batch [3199]/[3760] Speed: 68.939590 samples/sec accuracy=53.398926 loss=1.958653 lr=0.010000 Epoch[007] Batch [3249]/[3760] Speed: 69.911858 samples/sec accuracy=53.425962 loss=1.957703 lr=0.010000 Epoch[007] Batch [3299]/[3760] Speed: 69.969033 samples/sec accuracy=53.417614 loss=1.957939 lr=0.010000 Epoch[007] Batch [3349]/[3760] Speed: 69.867063 samples/sec accuracy=53.400187 loss=1.958387 lr=0.010000 Epoch[007] Batch [3399]/[3760] Speed: 69.552185 samples/sec accuracy=53.381434 loss=1.958456 lr=0.010000 Epoch[007] Batch [3449]/[3760] Speed: 69.369482 samples/sec accuracy=53.367301 loss=1.957791 lr=0.010000 Epoch[007] Batch [3499]/[3760] Speed: 69.252529 samples/sec accuracy=53.354464 loss=1.958348 lr=0.010000 Epoch[007] Batch [3549]/[3760] Speed: 70.095163 samples/sec accuracy=53.354313 loss=1.958301 lr=0.010000 Epoch[007] Batch [3599]/[3760] Speed: 69.647129 samples/sec accuracy=53.336806 loss=1.958964 lr=0.010000 Epoch[007] Batch [3649]/[3760] Speed: 69.147035 samples/sec accuracy=53.352740 loss=1.958211 lr=0.010000 Epoch[007] Batch [3699]/[3760] Speed: 69.381841 samples/sec accuracy=53.371199 loss=1.957288 lr=0.010000 Epoch[007] Batch [3749]/[3760] Speed: 77.806803 samples/sec accuracy=53.369583 loss=1.957214 lr=0.010000 Batch [0049]/[0303]: acc-top1=55.468750 acc-top5=79.562500 Batch [0099]/[0303]: acc-top1=55.140625 acc-top5=79.484375 Batch [0149]/[0303]: acc-top1=54.822917 acc-top5=78.843750 Batch [0199]/[0303]: acc-top1=54.625000 acc-top5=78.734375 Batch [0249]/[0303]: acc-top1=54.662500 acc-top5=78.837500 Batch [0299]/[0303]: acc-top1=54.546875 acc-top5=78.708333 [Epoch 007] training: accuracy=53.371426 loss=1.957152 [Epoch 007] speed: 69 samples/sec time cost: 3774.016011 [Epoch 007] validation: acc-top1=54.589521 acc-top5=78.723185 loss=2.003014 Epoch[008] Batch [0049]/[3759] Speed: 47.713563 samples/sec accuracy=55.125000 loss=1.837699 lr=0.010000 Epoch[008] Batch [0099]/[3759] Speed: 69.504276 samples/sec accuracy=54.750000 loss=1.874392 lr=0.010000 Epoch[008] Batch [0149]/[3759] Speed: 69.712714 samples/sec accuracy=54.802083 loss=1.875126 lr=0.010000 Epoch[008] Batch [0199]/[3759] Speed: 68.969703 samples/sec accuracy=54.539062 loss=1.891985 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acc-top5=79.620462 loss=1.979015 Epoch[009] Batch [0049]/[3760] Speed: 47.412642 samples/sec accuracy=56.343750 loss=1.793837 lr=0.010000 Epoch[009] Batch [0099]/[3760] Speed: 69.613495 samples/sec accuracy=56.203125 loss=1.801306 lr=0.010000 Epoch[009] Batch [0149]/[3760] Speed: 70.551117 samples/sec accuracy=56.166667 loss=1.807176 lr=0.010000 Epoch[009] Batch [0199]/[3760] Speed: 70.490496 samples/sec accuracy=55.968750 loss=1.812437 lr=0.010000 Epoch[009] Batch [0249]/[3760] Speed: 70.607548 samples/sec accuracy=56.050000 loss=1.815958 lr=0.010000 Epoch[009] Batch [0299]/[3760] Speed: 70.482487 samples/sec accuracy=55.968750 loss=1.829029 lr=0.010000 Epoch[009] Batch [0349]/[3760] Speed: 70.922983 samples/sec accuracy=55.959821 loss=1.833611 lr=0.010000 Epoch[009] Batch [0399]/[3760] Speed: 69.644547 samples/sec accuracy=55.828125 loss=1.838044 lr=0.010000 Epoch[009] Batch [0449]/[3760] Speed: 70.727187 samples/sec accuracy=55.670139 loss=1.843100 lr=0.010000 Epoch[009] Batch 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accuracy=55.242599 loss=1.866415 lr=0.010000 Epoch[009] Batch [1949]/[3760] Speed: 70.577725 samples/sec accuracy=55.261218 loss=1.866171 lr=0.010000 Epoch[009] Batch [1999]/[3760] Speed: 71.281504 samples/sec accuracy=55.267969 loss=1.865995 lr=0.010000 Epoch[009] Batch [2049]/[3760] Speed: 70.581964 samples/sec accuracy=55.264482 loss=1.865301 lr=0.010000 Epoch[009] Batch [2099]/[3760] Speed: 69.567904 samples/sec accuracy=55.278274 loss=1.866198 lr=0.010000 Epoch[009] Batch [2149]/[3760] Speed: 70.042351 samples/sec accuracy=55.271802 loss=1.866776 lr=0.010000 Epoch[009] Batch [2199]/[3760] Speed: 70.605900 samples/sec accuracy=55.275568 loss=1.866154 lr=0.010000 Epoch[009] Batch [2249]/[3760] Speed: 70.220781 samples/sec accuracy=55.275694 loss=1.865923 lr=0.010000 Epoch[009] Batch [2299]/[3760] Speed: 71.019796 samples/sec accuracy=55.296196 loss=1.865338 lr=0.010000 Epoch[009] Batch [2349]/[3760] Speed: 70.882312 samples/sec accuracy=55.281915 loss=1.865131 lr=0.010000 Epoch[009] 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accuracy=55.239583 loss=1.865943 lr=0.010000 Epoch[009] Batch [2899]/[3760] Speed: 69.797363 samples/sec accuracy=55.213901 loss=1.866098 lr=0.010000 Epoch[009] Batch [2949]/[3760] Speed: 70.844914 samples/sec accuracy=55.210805 loss=1.866644 lr=0.010000 Epoch[009] Batch [2999]/[3760] Speed: 70.449757 samples/sec accuracy=55.201563 loss=1.868032 lr=0.010000 Epoch[009] Batch [3049]/[3760] Speed: 70.729513 samples/sec accuracy=55.197746 loss=1.868420 lr=0.010000 Epoch[009] Batch [3099]/[3760] Speed: 70.082186 samples/sec accuracy=55.193044 loss=1.868269 lr=0.010000 Epoch[009] Batch [3149]/[3760] Speed: 69.446886 samples/sec accuracy=55.183532 loss=1.869000 lr=0.010000 Epoch[009] Batch [3199]/[3760] Speed: 70.579396 samples/sec accuracy=55.147949 loss=1.869834 lr=0.010000 Epoch[009] Batch [3249]/[3760] Speed: 70.190195 samples/sec accuracy=55.131731 loss=1.870359 lr=0.010000 Epoch[009] Batch [3299]/[3760] Speed: 70.734933 samples/sec accuracy=55.143939 loss=1.869724 lr=0.010000 Epoch[009] 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[0099]/[0303]: acc-top1=55.875000 acc-top5=80.640625 Batch [0149]/[0303]: acc-top1=56.260417 acc-top5=80.062500 Batch [0199]/[0303]: acc-top1=56.179688 acc-top5=79.796875 Batch [0249]/[0303]: acc-top1=56.250000 acc-top5=80.000000 Batch [0299]/[0303]: acc-top1=56.203125 acc-top5=79.885417 [Epoch 009] training: accuracy=55.130485 loss=1.869816 [Epoch 009] speed: 70 samples/sec time cost: 3719.790329 [Epoch 009] validation: acc-top1=56.244843 acc-top5=79.929868 loss=1.912294 Epoch[010] Batch [0049]/[3760] Speed: 48.403541 samples/sec accuracy=54.750000 loss=1.886233 lr=0.010000 Epoch[010] Batch [0099]/[3760] Speed: 69.630532 samples/sec accuracy=55.328125 loss=1.852195 lr=0.010000 Epoch[010] Batch [0149]/[3760] Speed: 70.859733 samples/sec accuracy=55.572917 loss=1.833255 lr=0.010000 Epoch[010] Batch [0199]/[3760] Speed: 70.898237 samples/sec accuracy=56.007812 loss=1.818636 lr=0.010000 Epoch[010] Batch [0249]/[3760] Speed: 70.549040 samples/sec accuracy=56.368750 loss=1.801733 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accuracy=58.593750 loss=1.744974 lr=0.010000 Epoch[011] Batch [0099]/[3759] Speed: 69.446408 samples/sec accuracy=58.296875 loss=1.758918 lr=0.010000 Epoch[011] Batch [0149]/[3759] Speed: 70.880215 samples/sec accuracy=57.947917 loss=1.759825 lr=0.010000 Epoch[011] Batch [0199]/[3759] Speed: 70.912291 samples/sec accuracy=57.734375 loss=1.763223 lr=0.010000 Epoch[011] Batch [0249]/[3759] Speed: 70.303798 samples/sec accuracy=57.562500 loss=1.768223 lr=0.010000 Epoch[011] Batch [0299]/[3759] Speed: 69.884449 samples/sec accuracy=57.604167 loss=1.762918 lr=0.010000 Epoch[011] Batch [0349]/[3759] Speed: 70.348151 samples/sec accuracy=57.450893 loss=1.765301 lr=0.010000 Epoch[011] Batch [0399]/[3759] Speed: 70.883721 samples/sec accuracy=57.457031 loss=1.765408 lr=0.010000 Epoch[011] Batch [0449]/[3759] Speed: 70.849245 samples/sec accuracy=57.336806 loss=1.768851 lr=0.010000 Epoch[011] Batch [0499]/[3759] Speed: 69.698563 samples/sec accuracy=57.340625 loss=1.775069 lr=0.010000 Epoch[011] 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accuracy=57.056250 loss=1.782511 lr=0.010000 Epoch[011] Batch [1049]/[3759] Speed: 70.086376 samples/sec accuracy=56.973214 loss=1.784643 lr=0.010000 Epoch[011] Batch [1099]/[3759] Speed: 70.377227 samples/sec accuracy=56.971591 loss=1.783056 lr=0.010000 Epoch[011] Batch [1149]/[3759] Speed: 69.348943 samples/sec accuracy=56.985054 loss=1.781113 lr=0.010000 Epoch[011] Batch [1199]/[3759] Speed: 70.437231 samples/sec accuracy=56.986979 loss=1.781635 lr=0.010000 Epoch[011] Batch [1249]/[3759] Speed: 70.748240 samples/sec accuracy=57.010000 loss=1.782184 lr=0.010000 Epoch[011] Batch [1299]/[3759] Speed: 70.350218 samples/sec accuracy=56.960337 loss=1.783807 lr=0.010000 Epoch[011] Batch [1349]/[3759] Speed: 70.124636 samples/sec accuracy=56.947917 loss=1.784381 lr=0.010000 Epoch[011] Batch [1399]/[3759] Speed: 71.125383 samples/sec accuracy=56.995536 loss=1.782531 lr=0.010000 Epoch[011] Batch [1449]/[3759] Speed: 70.495033 samples/sec accuracy=56.971983 loss=1.782574 lr=0.010000 Epoch[011] 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accuracy=56.951923 loss=1.783992 lr=0.010000 Epoch[011] Batch [1999]/[3759] Speed: 69.563885 samples/sec accuracy=56.955469 loss=1.784798 lr=0.010000 Epoch[011] Batch [2049]/[3759] Speed: 70.864301 samples/sec accuracy=56.923018 loss=1.786478 lr=0.010000 Epoch[011] Batch [2099]/[3759] Speed: 70.355570 samples/sec accuracy=56.919643 loss=1.786962 lr=0.010000 Epoch[011] Batch [2149]/[3759] Speed: 70.474538 samples/sec accuracy=56.901890 loss=1.787963 lr=0.010000 Epoch[011] Batch [2199]/[3759] Speed: 70.911599 samples/sec accuracy=56.926847 loss=1.787689 lr=0.010000 Epoch[011] Batch [2249]/[3759] Speed: 70.782209 samples/sec accuracy=56.924306 loss=1.787592 lr=0.010000 Epoch[011] Batch [2299]/[3759] Speed: 70.530376 samples/sec accuracy=56.921196 loss=1.787865 lr=0.010000 Epoch[011] Batch [2349]/[3759] Speed: 70.101611 samples/sec accuracy=56.912899 loss=1.788220 lr=0.010000 Epoch[011] Batch [2399]/[3759] Speed: 70.473450 samples/sec accuracy=56.927083 loss=1.787602 lr=0.010000 Epoch[011] 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accuracy=56.845905 loss=1.791288 lr=0.010000 Epoch[011] Batch [2949]/[3759] Speed: 69.986729 samples/sec accuracy=56.854343 loss=1.790560 lr=0.010000 Epoch[011] Batch [2999]/[3759] Speed: 70.840509 samples/sec accuracy=56.857813 loss=1.790544 lr=0.010000 Epoch[011] Batch [3049]/[3759] Speed: 70.159059 samples/sec accuracy=56.879611 loss=1.790135 lr=0.010000 Epoch[011] Batch [3099]/[3759] Speed: 71.096300 samples/sec accuracy=56.877016 loss=1.790406 lr=0.010000 Epoch[011] Batch [3149]/[3759] Speed: 70.517922 samples/sec accuracy=56.847718 loss=1.791639 lr=0.010000 Epoch[011] Batch [3199]/[3759] Speed: 70.314462 samples/sec accuracy=56.819336 loss=1.793561 lr=0.010000 Epoch[011] Batch [3249]/[3759] Speed: 70.583337 samples/sec accuracy=56.812019 loss=1.794137 lr=0.010000 Epoch[011] Batch [3299]/[3759] Speed: 70.941503 samples/sec accuracy=56.819602 loss=1.794169 lr=0.010000 Epoch[011] Batch [3349]/[3759] Speed: 70.295371 samples/sec accuracy=56.807369 loss=1.795184 lr=0.010000 Epoch[011] 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acc-top5=80.750000 Batch [0199]/[0303]: acc-top1=56.398438 acc-top5=80.500000 Batch [0249]/[0303]: acc-top1=56.343750 acc-top5=80.512500 Batch [0299]/[0303]: acc-top1=56.348958 acc-top5=80.447917 [Epoch 011] training: accuracy=56.771665 loss=1.795937 [Epoch 011] speed: 70 samples/sec time cost: 3714.451920 [Epoch 011] validation: acc-top1=56.373762 acc-top5=80.486799 loss=1.946648 Epoch[012] Batch [0049]/[3760] Speed: 48.232498 samples/sec accuracy=57.343750 loss=1.759347 lr=0.010000 Epoch[012] Batch [0099]/[3760] Speed: 69.390349 samples/sec accuracy=58.031250 loss=1.732564 lr=0.010000 Epoch[012] Batch [0149]/[3760] Speed: 70.613415 samples/sec accuracy=58.364583 loss=1.723231 lr=0.010000 Epoch[012] Batch [0199]/[3760] Speed: 70.667898 samples/sec accuracy=57.976562 loss=1.730990 lr=0.010000 Epoch[012] Batch [0249]/[3760] Speed: 70.683016 samples/sec accuracy=57.943750 loss=1.737935 lr=0.010000 Epoch[012] Batch [0299]/[3760] Speed: 70.244070 samples/sec accuracy=58.005208 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lr=0.010000 Epoch[013] Batch [3449]/[3760] Speed: 70.136604 samples/sec accuracy=57.904438 loss=1.736363 lr=0.010000 Epoch[013] Batch [3499]/[3760] Speed: 70.664815 samples/sec accuracy=57.909821 loss=1.736329 lr=0.010000 Epoch[013] Batch [3549]/[3760] Speed: 70.571214 samples/sec accuracy=57.907570 loss=1.736458 lr=0.010000 Epoch[013] Batch [3599]/[3760] Speed: 70.877727 samples/sec accuracy=57.927951 loss=1.736072 lr=0.010000 Epoch[013] Batch [3649]/[3760] Speed: 70.571755 samples/sec accuracy=57.934075 loss=1.736353 lr=0.010000 Epoch[013] Batch [3699]/[3760] Speed: 69.983430 samples/sec accuracy=57.951014 loss=1.736067 lr=0.010000 Epoch[013] Batch [3749]/[3760] Speed: 78.743171 samples/sec accuracy=57.950417 loss=1.735988 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.156250 acc-top5=82.687500 Batch [0099]/[0303]: acc-top1=57.890625 acc-top5=82.203125 Batch [0149]/[0303]: acc-top1=57.895833 acc-top5=81.479167 Batch [0199]/[0303]: acc-top1=57.890625 acc-top5=81.164062 Batch [0249]/[0303]: acc-top1=58.031250 acc-top5=81.500000 Batch [0299]/[0303]: acc-top1=57.963542 acc-top5=81.427083 [Epoch 013] training: accuracy=57.945894 loss=1.736045 [Epoch 013] speed: 70 samples/sec time cost: 3712.898408 [Epoch 013] validation: acc-top1=57.972360 acc-top5=81.440800 loss=1.859558 Epoch[014] Batch [0049]/[3759] Speed: 48.344614 samples/sec accuracy=58.656250 loss=1.695715 lr=0.010000 Epoch[014] Batch [0099]/[3759] Speed: 69.988250 samples/sec accuracy=58.937500 loss=1.691595 lr=0.010000 Epoch[014] Batch [0149]/[3759] Speed: 70.634281 samples/sec accuracy=58.479167 loss=1.702225 lr=0.010000 Epoch[014] Batch [0199]/[3759] Speed: 70.500925 samples/sec accuracy=58.539063 loss=1.710135 lr=0.010000 Epoch[014] Batch [0249]/[3759] Speed: 70.928214 samples/sec accuracy=58.700000 loss=1.694772 lr=0.010000 Epoch[014] Batch [0299]/[3759] Speed: 70.486354 samples/sec accuracy=58.692708 loss=1.699105 lr=0.010000 Epoch[014] Batch [0349]/[3759] Speed: 70.489689 samples/sec 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accuracy=58.537598 loss=1.707125 lr=0.010000 Epoch[014] Batch [3249]/[3759] Speed: 70.021511 samples/sec accuracy=58.519231 loss=1.708229 lr=0.010000 Epoch[014] Batch [3299]/[3759] Speed: 71.211450 samples/sec accuracy=58.511364 loss=1.708925 lr=0.010000 Epoch[014] Batch [3349]/[3759] Speed: 70.982359 samples/sec accuracy=58.485541 loss=1.709528 lr=0.010000 Epoch[014] Batch [3399]/[3759] Speed: 70.551066 samples/sec accuracy=58.477941 loss=1.709787 lr=0.010000 Epoch[014] Batch [3449]/[3759] Speed: 71.131158 samples/sec accuracy=58.481431 loss=1.709465 lr=0.010000 Epoch[014] Batch [3499]/[3759] Speed: 70.353986 samples/sec accuracy=58.484821 loss=1.710589 lr=0.010000 Epoch[014] Batch [3549]/[3759] Speed: 70.948818 samples/sec accuracy=58.495158 loss=1.710474 lr=0.010000 Epoch[014] Batch [3599]/[3759] Speed: 71.340804 samples/sec accuracy=58.516493 loss=1.709995 lr=0.010000 Epoch[014] Batch [3649]/[3759] Speed: 71.089507 samples/sec accuracy=58.521832 loss=1.710399 lr=0.010000 Epoch[014] Batch [3699]/[3759] Speed: 70.483419 samples/sec accuracy=58.536318 loss=1.710313 lr=0.010000 Epoch[014] Batch [3749]/[3759] Speed: 79.241993 samples/sec accuracy=58.515000 loss=1.710741 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.937500 acc-top5=82.656250 Batch [0099]/[0303]: acc-top1=58.203125 acc-top5=82.375000 Batch [0149]/[0303]: acc-top1=58.270833 acc-top5=81.552083 Batch [0199]/[0303]: acc-top1=58.093750 acc-top5=81.156250 Batch [0249]/[0303]: acc-top1=57.868750 acc-top5=81.262500 Batch [0299]/[0303]: acc-top1=57.984375 acc-top5=81.260417 [Epoch 014] training: accuracy=58.509161 loss=1.711127 [Epoch 014] speed: 70 samples/sec time cost: 3704.542144 [Epoch 014] validation: acc-top1=58.003300 acc-top5=81.275784 loss=1.851215 Epoch[015] Batch [0049]/[3760] Speed: 48.171638 samples/sec accuracy=61.125000 loss=1.607824 lr=0.010000 Epoch[015] Batch [0099]/[3760] Speed: 69.505572 samples/sec accuracy=60.000000 loss=1.616658 lr=0.010000 Epoch[015] Batch [0149]/[3760] Speed: 70.667320 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lr=0.010000 Epoch[015] Batch [3499]/[3760] Speed: 71.324817 samples/sec accuracy=59.083036 loss=1.688371 lr=0.010000 Epoch[015] Batch [3549]/[3760] Speed: 70.300287 samples/sec accuracy=59.077465 loss=1.688919 lr=0.010000 Epoch[015] Batch [3599]/[3760] Speed: 71.119293 samples/sec accuracy=59.065538 loss=1.689413 lr=0.010000 Epoch[015] Batch [3649]/[3760] Speed: 70.386592 samples/sec accuracy=59.047089 loss=1.690450 lr=0.010000 Epoch[015] Batch [3699]/[3760] Speed: 70.044122 samples/sec accuracy=59.062500 loss=1.690447 lr=0.010000 Epoch[015] Batch [3749]/[3760] Speed: 78.907067 samples/sec accuracy=59.036250 loss=1.691374 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.593750 acc-top5=82.812500 Batch [0099]/[0303]: acc-top1=58.468750 acc-top5=82.671875 Batch [0149]/[0303]: acc-top1=58.375000 acc-top5=82.000000 Batch [0199]/[0303]: acc-top1=58.125000 acc-top5=81.882812 Batch [0249]/[0303]: acc-top1=58.106250 acc-top5=81.987500 Batch [0299]/[0303]: acc-top1=58.114583 acc-top5=81.875000 [Epoch 015] training: accuracy=59.029671 loss=1.691417 [Epoch 015] speed: 70 samples/sec time cost: 3708.799671 [Epoch 015] validation: acc-top1=58.142533 acc-top5=81.889439 loss=1.890857 Epoch[016] Batch [0049]/[3760] Speed: 47.588991 samples/sec accuracy=60.593750 loss=1.594737 lr=0.010000 Epoch[016] Batch [0099]/[3760] Speed: 70.301973 samples/sec accuracy=60.953125 loss=1.602038 lr=0.010000 Epoch[016] Batch [0149]/[3760] Speed: 70.337820 samples/sec accuracy=60.708333 loss=1.619569 lr=0.010000 Epoch[016] Batch [0199]/[3760] Speed: 70.604229 samples/sec accuracy=60.093750 loss=1.633029 lr=0.010000 Epoch[016] Batch [0249]/[3760] Speed: 70.677397 samples/sec accuracy=59.975000 loss=1.636511 lr=0.010000 Epoch[016] Batch [0299]/[3760] Speed: 70.455660 samples/sec accuracy=59.916667 loss=1.642920 lr=0.010000 Epoch[016] Batch [0349]/[3760] Speed: 70.738097 samples/sec accuracy=59.973214 loss=1.637756 lr=0.010000 Epoch[016] Batch [0399]/[3760] Speed: 69.846189 samples/sec accuracy=59.882813 loss=1.642962 lr=0.010000 Epoch[016] Batch [0449]/[3760] Speed: 71.119561 samples/sec accuracy=59.736111 loss=1.649014 lr=0.010000 Epoch[016] Batch [0499]/[3760] Speed: 70.662343 samples/sec accuracy=59.628125 loss=1.650173 lr=0.010000 Epoch[016] Batch [0549]/[3760] Speed: 70.467774 samples/sec accuracy=59.534091 loss=1.651568 lr=0.010000 Epoch[016] Batch [0599]/[3760] Speed: 70.237810 samples/sec accuracy=59.518229 loss=1.654216 lr=0.010000 Epoch[016] Batch [0649]/[3760] Speed: 70.973792 samples/sec accuracy=59.521635 loss=1.653653 lr=0.010000 Epoch[016] Batch [0699]/[3760] Speed: 70.812606 samples/sec accuracy=59.535714 loss=1.653729 lr=0.010000 Epoch[016] Batch [0749]/[3760] Speed: 70.521032 samples/sec accuracy=59.562500 loss=1.653618 lr=0.010000 Epoch[016] Batch [0799]/[3760] Speed: 69.972216 samples/sec accuracy=59.544922 loss=1.653422 lr=0.010000 Epoch[016] Batch [0849]/[3760] Speed: 70.805567 samples/sec accuracy=59.654412 loss=1.649117 lr=0.010000 Epoch[016] 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Batch [3749]/[3760] Speed: 79.347394 samples/sec accuracy=59.280417 loss=1.672640 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.968750 acc-top5=81.812500 Batch [0099]/[0303]: acc-top1=57.734375 acc-top5=81.390625 Batch [0149]/[0303]: acc-top1=57.645833 acc-top5=80.916667 Batch [0199]/[0303]: acc-top1=57.265625 acc-top5=80.640625 Batch [0249]/[0303]: acc-top1=57.393750 acc-top5=80.750000 Batch [0299]/[0303]: acc-top1=57.343750 acc-top5=80.718750 [Epoch 016] training: accuracy=59.272357 loss=1.672899 [Epoch 016] speed: 70 samples/sec time cost: 3709.294292 [Epoch 016] validation: acc-top1=57.348391 acc-top5=80.760107 loss=1.949003 Epoch[017] Batch [0049]/[3759] Speed: 48.151612 samples/sec accuracy=59.406250 loss=1.618381 lr=0.010000 Epoch[017] Batch [0099]/[3759] Speed: 69.464460 samples/sec accuracy=59.171875 loss=1.640840 lr=0.010000 Epoch[017] Batch [0149]/[3759] Speed: 71.164216 samples/sec accuracy=59.208333 loss=1.654209 lr=0.010000 Epoch[017] Batch [0199]/[3759] Speed: 70.765667 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lr=0.010000 Epoch[017] Batch [2599]/[3759] Speed: 70.929677 samples/sec accuracy=59.896034 loss=1.647077 lr=0.010000 Epoch[017] Batch [2649]/[3759] Speed: 70.538647 samples/sec accuracy=59.886203 loss=1.646207 lr=0.010000 Epoch[017] Batch [2699]/[3759] Speed: 70.349121 samples/sec accuracy=59.853588 loss=1.647433 lr=0.010000 Epoch[017] Batch [2749]/[3759] Speed: 70.578011 samples/sec accuracy=59.887500 loss=1.646862 lr=0.010000 Epoch[017] Batch [2799]/[3759] Speed: 70.714023 samples/sec accuracy=59.873884 loss=1.648001 lr=0.010000 Epoch[017] Batch [2849]/[3759] Speed: 71.328047 samples/sec accuracy=59.859649 loss=1.648374 lr=0.010000 Epoch[017] Batch [2899]/[3759] Speed: 70.308735 samples/sec accuracy=59.860991 loss=1.648657 lr=0.010000 Epoch[017] Batch [2949]/[3759] Speed: 70.353395 samples/sec accuracy=59.867055 loss=1.648177 lr=0.010000 Epoch[017] Batch [2999]/[3759] Speed: 70.764938 samples/sec accuracy=59.882813 loss=1.647448 lr=0.010000 Epoch[017] Batch [3049]/[3759] Speed: 71.067573 samples/sec accuracy=59.877561 loss=1.647826 lr=0.010000 Epoch[017] Batch [3099]/[3759] Speed: 70.625683 samples/sec accuracy=59.868952 loss=1.648030 lr=0.010000 Epoch[017] Batch [3149]/[3759] Speed: 70.306048 samples/sec accuracy=59.854167 loss=1.648660 lr=0.010000 Epoch[017] Batch [3199]/[3759] Speed: 69.870394 samples/sec accuracy=59.822754 loss=1.649571 lr=0.010000 Epoch[017] Batch [3249]/[3759] Speed: 70.684646 samples/sec accuracy=59.808173 loss=1.650479 lr=0.010000 Epoch[017] Batch [3299]/[3759] Speed: 71.330355 samples/sec accuracy=59.830492 loss=1.649791 lr=0.010000 Epoch[017] Batch [3349]/[3759] Speed: 71.149366 samples/sec accuracy=59.795709 loss=1.650988 lr=0.010000 Epoch[017] Batch [3399]/[3759] Speed: 70.052128 samples/sec accuracy=59.794577 loss=1.651485 lr=0.010000 Epoch[017] Batch [3449]/[3759] Speed: 69.794679 samples/sec accuracy=59.795290 loss=1.651005 lr=0.010000 Epoch[017] Batch [3499]/[3759] Speed: 70.322239 samples/sec accuracy=59.777232 loss=1.651758 lr=0.010000 Epoch[017] Batch [3549]/[3759] Speed: 70.422265 samples/sec accuracy=59.791813 loss=1.651169 lr=0.010000 Epoch[017] Batch [3599]/[3759] Speed: 70.963388 samples/sec accuracy=59.781684 loss=1.652009 lr=0.010000 Epoch[017] Batch [3649]/[3759] Speed: 70.575825 samples/sec accuracy=59.769692 loss=1.653106 lr=0.010000 Epoch[017] Batch [3699]/[3759] Speed: 70.033020 samples/sec accuracy=59.751689 loss=1.653491 lr=0.010000 Epoch[017] Batch [3749]/[3759] Speed: 79.718910 samples/sec accuracy=59.764583 loss=1.653293 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.218750 acc-top5=82.781250 Batch [0099]/[0303]: acc-top1=58.640625 acc-top5=82.640625 Batch [0149]/[0303]: acc-top1=58.322917 acc-top5=81.822917 Batch [0199]/[0303]: acc-top1=58.187500 acc-top5=81.671875 Batch [0249]/[0303]: acc-top1=58.262500 acc-top5=81.806250 Batch [0299]/[0303]: acc-top1=58.343750 acc-top5=81.666667 [Epoch 017] training: accuracy=59.769470 loss=1.653154 [Epoch 017] speed: 70 samples/sec time cost: 3702.914989 [Epoch 017] validation: acc-top1=58.359117 acc-top5=81.672855 loss=1.851038 Epoch[018] Batch [0049]/[3760] Speed: 48.283611 samples/sec accuracy=62.000000 loss=1.569321 lr=0.010000 Epoch[018] Batch [0099]/[3760] Speed: 69.778627 samples/sec accuracy=61.796875 loss=1.588990 lr=0.010000 Epoch[018] Batch [0149]/[3760] Speed: 70.736960 samples/sec accuracy=60.947917 loss=1.623268 lr=0.010000 Epoch[018] Batch [0199]/[3760] Speed: 70.704960 samples/sec accuracy=60.937500 loss=1.614006 lr=0.010000 Epoch[018] Batch [0249]/[3760] Speed: 70.685553 samples/sec accuracy=60.818750 loss=1.616971 lr=0.010000 Epoch[018] Batch [0299]/[3760] Speed: 70.590454 samples/sec accuracy=60.687500 loss=1.614907 lr=0.010000 Epoch[018] Batch [0349]/[3760] Speed: 71.372665 samples/sec accuracy=60.584821 loss=1.614340 lr=0.010000 Epoch[018] Batch [0399]/[3760] Speed: 69.949517 samples/sec accuracy=60.710937 loss=1.617672 lr=0.010000 Epoch[018] Batch [0449]/[3760] Speed: 70.692067 samples/sec 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[0049]/[0303]: acc-top1=59.031250 acc-top5=83.625000 Batch [0099]/[0303]: acc-top1=58.750000 acc-top5=82.953125 Batch [0149]/[0303]: acc-top1=58.687500 acc-top5=82.281250 Batch [0199]/[0303]: acc-top1=58.546875 acc-top5=81.945312 Batch [0249]/[0303]: acc-top1=58.481250 acc-top5=82.000000 Batch [0299]/[0303]: acc-top1=58.500000 acc-top5=81.901042 [Epoch 018] training: accuracy=59.980053 loss=1.641814 [Epoch 018] speed: 70 samples/sec time cost: 3700.782226 [Epoch 018] validation: acc-top1=58.518977 acc-top5=81.935850 loss=1.895034 Epoch[019] Batch [0049]/[3760] Speed: 47.723743 samples/sec accuracy=62.687500 loss=1.545751 lr=0.010000 Epoch[019] Batch [0099]/[3760] Speed: 69.771995 samples/sec accuracy=62.687500 loss=1.528923 lr=0.010000 Epoch[019] Batch [0149]/[3760] Speed: 71.188736 samples/sec accuracy=62.145833 loss=1.552785 lr=0.010000 Epoch[019] Batch [0199]/[3760] Speed: 71.135243 samples/sec accuracy=61.921875 loss=1.561360 lr=0.010000 Epoch[019] Batch [0249]/[3760] Speed: 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lr=0.010000 Epoch[019] Batch [3599]/[3760] Speed: 71.607120 samples/sec accuracy=60.390191 loss=1.627193 lr=0.010000 Epoch[019] Batch [3649]/[3760] Speed: 70.673448 samples/sec accuracy=60.409675 loss=1.626915 lr=0.010000 Epoch[019] Batch [3699]/[3760] Speed: 70.808646 samples/sec accuracy=60.399916 loss=1.627827 lr=0.010000 Epoch[019] Batch [3749]/[3760] Speed: 79.010418 samples/sec accuracy=60.389583 loss=1.628332 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.437500 acc-top5=83.531250 Batch [0099]/[0303]: acc-top1=59.468750 acc-top5=83.000000 Batch [0149]/[0303]: acc-top1=59.177083 acc-top5=82.437500 Batch [0199]/[0303]: acc-top1=59.234375 acc-top5=82.429688 Batch [0249]/[0303]: acc-top1=59.112500 acc-top5=82.431250 Batch [0299]/[0303]: acc-top1=58.979167 acc-top5=82.270833 [Epoch 019] training: accuracy=60.394781 loss=1.628325 [Epoch 019] speed: 70 samples/sec time cost: 3695.334949 [Epoch 019] validation: acc-top1=59.024340 acc-top5=82.307137 loss=1.888466 Epoch[020] Batch 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accuracy=60.667444 loss=1.617852 lr=0.010000 Epoch[020] Batch [3399]/[3759] Speed: 71.645489 samples/sec accuracy=60.647518 loss=1.618111 lr=0.010000 Epoch[020] Batch [3449]/[3759] Speed: 71.012671 samples/sec accuracy=60.654891 loss=1.617324 lr=0.010000 Epoch[020] Batch [3499]/[3759] Speed: 70.739764 samples/sec accuracy=60.668304 loss=1.616963 lr=0.010000 Epoch[020] Batch [3549]/[3759] Speed: 70.230992 samples/sec accuracy=60.658891 loss=1.617413 lr=0.010000 Epoch[020] Batch [3599]/[3759] Speed: 70.579968 samples/sec accuracy=60.649740 loss=1.617526 lr=0.010000 Epoch[020] Batch [3649]/[3759] Speed: 70.825537 samples/sec accuracy=60.625428 loss=1.618718 lr=0.010000 Epoch[020] Batch [3699]/[3759] Speed: 70.833942 samples/sec accuracy=60.604730 loss=1.619760 lr=0.010000 Epoch[020] Batch [3749]/[3759] Speed: 80.346415 samples/sec accuracy=60.591667 loss=1.620251 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.937500 acc-top5=82.812500 Batch [0099]/[0303]: acc-top1=59.015625 acc-top5=82.406250 Batch [0149]/[0303]: acc-top1=58.802083 acc-top5=81.843750 Batch [0199]/[0303]: acc-top1=58.476562 acc-top5=81.562500 Batch [0249]/[0303]: acc-top1=58.568750 acc-top5=81.725000 Batch [0299]/[0303]: acc-top1=58.677083 acc-top5=81.697917 [Epoch 020] training: accuracy=60.595820 loss=1.620026 [Epoch 020] speed: 70 samples/sec time cost: 3696.940200 [Epoch 020] validation: acc-top1=58.683993 acc-top5=81.729579 loss=1.887758 Epoch[021] Batch [0049]/[3760] Speed: 48.611907 samples/sec accuracy=62.437500 loss=1.502359 lr=0.010000 Epoch[021] Batch [0099]/[3760] Speed: 70.210376 samples/sec accuracy=61.890625 loss=1.535687 lr=0.010000 Epoch[021] Batch [0149]/[3760] Speed: 70.605262 samples/sec accuracy=61.906250 loss=1.549420 lr=0.010000 Epoch[021] Batch [0199]/[3760] Speed: 71.163064 samples/sec accuracy=62.226563 loss=1.537687 lr=0.010000 Epoch[021] Batch [0249]/[3760] Speed: 70.509825 samples/sec accuracy=62.175000 loss=1.536014 lr=0.010000 Epoch[021] Batch [0299]/[3760] 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accuracy=61.070772 loss=1.590881 lr=0.010000 Epoch[021] Batch [1749]/[3760] Speed: 70.479373 samples/sec accuracy=61.057143 loss=1.591792 lr=0.010000 Epoch[021] Batch [1799]/[3760] Speed: 70.563710 samples/sec accuracy=61.094618 loss=1.591240 lr=0.010000 Epoch[021] Batch [1849]/[3760] Speed: 70.620640 samples/sec accuracy=61.071791 loss=1.591787 lr=0.010000 Epoch[021] Batch [1899]/[3760] Speed: 71.135576 samples/sec accuracy=61.091283 loss=1.590468 lr=0.010000 Epoch[021] Batch [1949]/[3760] Speed: 70.665495 samples/sec accuracy=61.070513 loss=1.590678 lr=0.010000 Epoch[021] Batch [1999]/[3760] Speed: 70.578962 samples/sec accuracy=61.043750 loss=1.591436 lr=0.010000 Epoch[021] Batch [2049]/[3760] Speed: 70.615051 samples/sec accuracy=61.019055 loss=1.592289 lr=0.010000 Epoch[021] Batch [2099]/[3760] Speed: 71.924806 samples/sec accuracy=61.028274 loss=1.591756 lr=0.010000 Epoch[021] Batch [2149]/[3760] Speed: 70.907808 samples/sec accuracy=61.035610 loss=1.591397 lr=0.010000 Epoch[021] 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accuracy=61.046580 loss=1.594732 lr=0.010000 Epoch[021] Batch [2699]/[3760] Speed: 70.732724 samples/sec accuracy=61.026620 loss=1.595272 lr=0.010000 Epoch[021] Batch [2749]/[3760] Speed: 70.894449 samples/sec accuracy=61.026136 loss=1.595863 lr=0.010000 Epoch[021] Batch [2799]/[3760] Speed: 70.715009 samples/sec accuracy=61.010045 loss=1.596398 lr=0.010000 Epoch[021] Batch [2849]/[3760] Speed: 70.715410 samples/sec accuracy=61.007675 loss=1.596251 lr=0.010000 Epoch[021] Batch [2899]/[3760] Speed: 71.475411 samples/sec accuracy=61.010776 loss=1.596308 lr=0.010000 Epoch[021] Batch [2949]/[3760] Speed: 70.412161 samples/sec accuracy=61.032839 loss=1.595527 lr=0.010000 Epoch[021] Batch [2999]/[3760] Speed: 70.863668 samples/sec accuracy=61.035938 loss=1.595496 lr=0.010000 Epoch[021] Batch [3049]/[3760] Speed: 70.740943 samples/sec accuracy=61.044570 loss=1.595452 lr=0.010000 Epoch[021] Batch [3099]/[3760] Speed: 71.335243 samples/sec accuracy=61.049395 loss=1.594884 lr=0.010000 Epoch[021] Batch [3149]/[3760] Speed: 71.012989 samples/sec accuracy=61.056548 loss=1.594687 lr=0.010000 Epoch[021] Batch [3199]/[3760] Speed: 70.817345 samples/sec accuracy=61.059082 loss=1.594555 lr=0.010000 Epoch[021] Batch [3249]/[3760] Speed: 71.303474 samples/sec accuracy=61.056250 loss=1.594331 lr=0.010000 Epoch[021] Batch [3299]/[3760] Speed: 71.103867 samples/sec accuracy=61.067708 loss=1.594094 lr=0.010000 Epoch[021] Batch [3349]/[3760] Speed: 70.486275 samples/sec accuracy=61.046642 loss=1.595222 lr=0.010000 Epoch[021] Batch [3399]/[3760] Speed: 70.633081 samples/sec accuracy=61.048254 loss=1.595605 lr=0.010000 Epoch[021] Batch [3449]/[3760] Speed: 71.000544 samples/sec accuracy=61.034420 loss=1.596298 lr=0.010000 Epoch[021] Batch [3499]/[3760] Speed: 70.799313 samples/sec accuracy=61.016964 loss=1.596891 lr=0.010000 Epoch[021] Batch [3549]/[3760] Speed: 70.961080 samples/sec accuracy=60.993398 loss=1.598056 lr=0.010000 Epoch[021] Batch [3599]/[3760] Speed: 70.416082 samples/sec accuracy=60.957899 loss=1.599656 lr=0.010000 Epoch[021] Batch [3649]/[3760] Speed: 71.056928 samples/sec accuracy=60.948202 loss=1.599409 lr=0.010000 Epoch[021] Batch [3699]/[3760] Speed: 70.821252 samples/sec accuracy=60.941301 loss=1.599474 lr=0.010000 Epoch[021] Batch [3749]/[3760] Speed: 79.385703 samples/sec accuracy=60.941667 loss=1.599960 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.437500 acc-top5=83.218750 Batch [0099]/[0303]: acc-top1=58.906250 acc-top5=82.703125 Batch [0149]/[0303]: acc-top1=58.968750 acc-top5=82.083333 Batch [0199]/[0303]: acc-top1=58.765625 acc-top5=81.929688 Batch [0249]/[0303]: acc-top1=58.618750 acc-top5=82.050000 Batch [0299]/[0303]: acc-top1=58.546875 acc-top5=81.947917 [Epoch 021] training: accuracy=60.936669 loss=1.600363 [Epoch 021] speed: 70 samples/sec time cost: 3696.089030 [Epoch 021] validation: acc-top1=58.549917 acc-top5=81.956477 loss=1.874724 Epoch[022] Batch [0049]/[3760] Speed: 47.713169 samples/sec accuracy=62.500000 loss=1.551003 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acc-top1=59.710938 acc-top5=82.812500 Batch [0249]/[0303]: acc-top1=59.568750 acc-top5=82.987500 Batch [0299]/[0303]: acc-top1=59.510417 acc-top5=82.906250 [Epoch 022] training: accuracy=61.035156 loss=1.592830 [Epoch 022] speed: 70 samples/sec time cost: 3699.505055 [Epoch 022] validation: acc-top1=59.509076 acc-top5=82.910479 loss=1.809880 Epoch[023] Batch [0049]/[3759] Speed: 48.653149 samples/sec accuracy=62.218750 loss=1.521463 lr=0.010000 Epoch[023] Batch [0099]/[3759] Speed: 70.718740 samples/sec accuracy=62.343750 loss=1.525131 lr=0.010000 Epoch[023] Batch [0149]/[3759] Speed: 70.054765 samples/sec accuracy=62.093750 loss=1.537150 lr=0.010000 Epoch[023] Batch [0199]/[3759] Speed: 71.359793 samples/sec accuracy=61.851562 loss=1.563432 lr=0.010000 Epoch[023] Batch [0249]/[3759] Speed: 71.250653 samples/sec accuracy=61.850000 loss=1.561352 lr=0.010000 Epoch[023] Batch [0299]/[3759] Speed: 70.837884 samples/sec accuracy=61.911458 loss=1.564088 lr=0.010000 Epoch[023] Batch 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accuracy=61.513672 loss=1.578087 lr=0.010000 Epoch[023] Batch [0849]/[3759] Speed: 70.822736 samples/sec accuracy=61.643382 loss=1.575523 lr=0.010000 Epoch[023] Batch [0899]/[3759] Speed: 70.746848 samples/sec accuracy=61.671875 loss=1.573325 lr=0.010000 Epoch[023] Batch [0949]/[3759] Speed: 70.660565 samples/sec accuracy=61.588816 loss=1.576609 lr=0.010000 Epoch[023] Batch [0999]/[3759] Speed: 71.439119 samples/sec accuracy=61.590625 loss=1.576583 lr=0.010000 Epoch[023] Batch [1049]/[3759] Speed: 70.640954 samples/sec accuracy=61.504464 loss=1.579530 lr=0.010000 Epoch[023] Batch [1099]/[3759] Speed: 71.318842 samples/sec accuracy=61.473011 loss=1.579586 lr=0.010000 Epoch[023] Batch [1149]/[3759] Speed: 70.549628 samples/sec accuracy=61.452446 loss=1.578878 lr=0.010000 Epoch[023] Batch [1199]/[3759] Speed: 70.636269 samples/sec accuracy=61.496094 loss=1.578336 lr=0.010000 Epoch[023] Batch [1249]/[3759] Speed: 71.299897 samples/sec accuracy=61.552500 loss=1.575293 lr=0.010000 Epoch[023] 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accuracy=61.417824 loss=1.578876 lr=0.010000 Epoch[023] Batch [2749]/[3759] Speed: 71.384984 samples/sec accuracy=61.407955 loss=1.579952 lr=0.010000 Epoch[023] Batch [2799]/[3759] Speed: 70.683912 samples/sec accuracy=61.421875 loss=1.579455 lr=0.010000 Epoch[023] Batch [2849]/[3759] Speed: 71.330286 samples/sec accuracy=61.408443 loss=1.579551 lr=0.010000 Epoch[023] Batch [2899]/[3759] Speed: 71.685402 samples/sec accuracy=61.394935 loss=1.580016 lr=0.010000 Epoch[023] Batch [2949]/[3759] Speed: 71.801274 samples/sec accuracy=61.392479 loss=1.580653 lr=0.010000 Epoch[023] Batch [2999]/[3759] Speed: 71.956030 samples/sec accuracy=61.368229 loss=1.581136 lr=0.010000 Epoch[023] Batch [3049]/[3759] Speed: 71.789061 samples/sec accuracy=61.364754 loss=1.581370 lr=0.010000 Epoch[023] Batch [3099]/[3759] Speed: 71.750360 samples/sec accuracy=61.345766 loss=1.581194 lr=0.010000 Epoch[023] Batch [3149]/[3759] Speed: 72.194122 samples/sec accuracy=61.334325 loss=1.581391 lr=0.010000 Epoch[023] 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accuracy=61.249572 loss=1.586493 lr=0.010000 Epoch[023] Batch [3699]/[3759] Speed: 71.543318 samples/sec accuracy=61.237753 loss=1.586628 lr=0.010000 Epoch[023] Batch [3749]/[3759] Speed: 80.061086 samples/sec accuracy=61.237917 loss=1.587048 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.812500 acc-top5=83.593750 Batch [0099]/[0303]: acc-top1=60.046875 acc-top5=83.250000 Batch [0149]/[0303]: acc-top1=59.854167 acc-top5=82.406250 Batch [0199]/[0303]: acc-top1=59.750000 acc-top5=82.375000 Batch [0249]/[0303]: acc-top1=59.712500 acc-top5=82.525000 Batch [0299]/[0303]: acc-top1=59.776042 acc-top5=82.458333 [Epoch 023] training: accuracy=61.238029 loss=1.587170 [Epoch 023] speed: 70 samples/sec time cost: 3682.196672 [Epoch 023] validation: acc-top1=59.823639 acc-top5=82.482467 loss=1.838939 Epoch[024] Batch [0049]/[3760] Speed: 49.068846 samples/sec accuracy=63.312500 loss=1.495253 lr=0.010000 Epoch[024] Batch [0099]/[3760] Speed: 70.541056 samples/sec accuracy=62.671875 loss=1.511229 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lr=0.010000 Epoch[024] Batch [2999]/[3760] Speed: 71.189567 samples/sec accuracy=61.553125 loss=1.572536 lr=0.010000 Epoch[024] Batch [3049]/[3760] Speed: 72.230565 samples/sec accuracy=61.539959 loss=1.573182 lr=0.010000 Epoch[024] Batch [3099]/[3760] Speed: 70.874396 samples/sec accuracy=61.534778 loss=1.573715 lr=0.010000 Epoch[024] Batch [3149]/[3760] Speed: 71.655445 samples/sec accuracy=61.515377 loss=1.574347 lr=0.010000 Epoch[024] Batch [3199]/[3760] Speed: 71.369351 samples/sec accuracy=61.505371 loss=1.574896 lr=0.010000 Epoch[024] Batch [3249]/[3760] Speed: 72.039717 samples/sec accuracy=61.517308 loss=1.574620 lr=0.010000 Epoch[024] Batch [3299]/[3760] Speed: 71.680048 samples/sec accuracy=61.508049 loss=1.574490 lr=0.010000 Epoch[024] Batch [3349]/[3760] Speed: 71.398487 samples/sec accuracy=61.492537 loss=1.575366 lr=0.010000 Epoch[024] Batch [3399]/[3760] Speed: 72.420375 samples/sec accuracy=61.476562 loss=1.576204 lr=0.010000 Epoch[024] Batch [3449]/[3760] Speed: 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[0299]/[0303]: acc-top1=59.234375 acc-top5=82.307292 [Epoch 024] training: accuracy=61.478973 loss=1.575960 [Epoch 024] speed: 71 samples/sec time cost: 3650.018474 [Epoch 024] validation: acc-top1=59.292492 acc-top5=82.327764 loss=1.909006 Epoch[025] Batch [0049]/[3760] Speed: 49.375336 samples/sec accuracy=62.781250 loss=1.484766 lr=0.010000 Epoch[025] Batch [0099]/[3760] Speed: 70.535481 samples/sec accuracy=62.625000 loss=1.477887 lr=0.010000 Epoch[025] Batch [0149]/[3760] Speed: 71.300064 samples/sec accuracy=63.125000 loss=1.480535 lr=0.010000 Epoch[025] Batch [0199]/[3760] Speed: 71.350988 samples/sec accuracy=62.664062 loss=1.499605 lr=0.010000 Epoch[025] Batch [0249]/[3760] Speed: 72.279274 samples/sec accuracy=62.468750 loss=1.508957 lr=0.010000 Epoch[025] Batch [0299]/[3760] Speed: 71.377701 samples/sec accuracy=62.307292 loss=1.518774 lr=0.010000 Epoch[025] Batch [0349]/[3760] Speed: 71.776668 samples/sec accuracy=62.299107 loss=1.519158 lr=0.010000 Epoch[025] Batch 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accuracy=62.126838 loss=1.531407 lr=0.010000 Epoch[025] Batch [0899]/[3760] Speed: 71.783809 samples/sec accuracy=62.215278 loss=1.527976 lr=0.010000 Epoch[025] Batch [0949]/[3760] Speed: 71.628816 samples/sec accuracy=62.212171 loss=1.530167 lr=0.010000 Epoch[025] Batch [0999]/[3760] Speed: 71.566150 samples/sec accuracy=62.185938 loss=1.531646 lr=0.010000 Epoch[025] Batch [1049]/[3760] Speed: 71.814567 samples/sec accuracy=62.141369 loss=1.533703 lr=0.010000 Epoch[025] Batch [1099]/[3760] Speed: 72.215150 samples/sec accuracy=62.169034 loss=1.532279 lr=0.010000 Epoch[025] Batch [1149]/[3760] Speed: 71.523237 samples/sec accuracy=62.226902 loss=1.531772 lr=0.010000 Epoch[025] Batch [1199]/[3760] Speed: 71.717388 samples/sec accuracy=62.233073 loss=1.531828 lr=0.010000 Epoch[025] Batch [1249]/[3760] Speed: 71.993883 samples/sec accuracy=62.173750 loss=1.534649 lr=0.010000 Epoch[025] Batch [1299]/[3760] Speed: 72.008547 samples/sec accuracy=62.157452 loss=1.535972 lr=0.010000 Epoch[025] 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accuracy=61.976562 loss=1.546381 lr=0.010000 Epoch[025] Batch [1849]/[3760] Speed: 71.824703 samples/sec accuracy=61.953547 loss=1.547854 lr=0.010000 Epoch[025] Batch [1899]/[3760] Speed: 72.215522 samples/sec accuracy=61.941612 loss=1.548319 lr=0.010000 Epoch[025] Batch [1949]/[3760] Speed: 72.336574 samples/sec accuracy=61.940705 loss=1.549313 lr=0.010000 Epoch[025] Batch [1999]/[3760] Speed: 71.824048 samples/sec accuracy=61.929688 loss=1.549014 lr=0.010000 Epoch[025] Batch [2049]/[3760] Speed: 72.612389 samples/sec accuracy=61.926829 loss=1.550052 lr=0.010000 Epoch[025] Batch [2099]/[3760] Speed: 72.116204 samples/sec accuracy=61.944940 loss=1.549641 lr=0.010000 Epoch[025] Batch [2149]/[3760] Speed: 71.610048 samples/sec accuracy=61.942587 loss=1.549702 lr=0.010000 Epoch[025] Batch [2199]/[3760] Speed: 71.779819 samples/sec accuracy=61.964489 loss=1.548565 lr=0.010000 Epoch[025] Batch [2249]/[3760] Speed: 72.189066 samples/sec accuracy=61.945139 loss=1.549232 lr=0.010000 Epoch[025] 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accuracy=61.909091 loss=1.552499 lr=0.010000 Epoch[025] Batch [2799]/[3760] Speed: 72.290798 samples/sec accuracy=61.869978 loss=1.553799 lr=0.010000 Epoch[025] Batch [2849]/[3760] Speed: 72.036779 samples/sec accuracy=61.865680 loss=1.554749 lr=0.010000 Epoch[025] Batch [2899]/[3760] Speed: 71.718017 samples/sec accuracy=61.864763 loss=1.555326 lr=0.010000 Epoch[025] Batch [2949]/[3760] Speed: 71.499799 samples/sec accuracy=61.850636 loss=1.556049 lr=0.010000 Epoch[025] Batch [2999]/[3760] Speed: 72.003052 samples/sec accuracy=61.843750 loss=1.556156 lr=0.010000 Epoch[025] Batch [3049]/[3760] Speed: 71.406291 samples/sec accuracy=61.837090 loss=1.556429 lr=0.010000 Epoch[025] Batch [3099]/[3760] Speed: 71.352940 samples/sec accuracy=61.841734 loss=1.556528 lr=0.010000 Epoch[025] Batch [3149]/[3760] Speed: 72.027808 samples/sec accuracy=61.819940 loss=1.557884 lr=0.010000 Epoch[025] Batch [3199]/[3760] Speed: 71.569232 samples/sec accuracy=61.813477 loss=1.558242 lr=0.010000 Epoch[025] 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accuracy=61.701014 loss=1.563574 lr=0.010000 Epoch[025] Batch [3749]/[3760] Speed: 80.285425 samples/sec accuracy=61.697083 loss=1.563852 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.593750 acc-top5=83.687500 Batch [0099]/[0303]: acc-top1=59.484375 acc-top5=83.343750 Batch [0149]/[0303]: acc-top1=59.520833 acc-top5=82.687500 Batch [0199]/[0303]: acc-top1=59.421875 acc-top5=82.398438 Batch [0249]/[0303]: acc-top1=59.450000 acc-top5=82.518750 Batch [0299]/[0303]: acc-top1=59.500000 acc-top5=82.494792 [Epoch 025] training: accuracy=61.695894 loss=1.563887 [Epoch 025] speed: 71 samples/sec time cost: 3648.898267 [Epoch 025] validation: acc-top1=59.524546 acc-top5=82.523721 loss=1.877018 Epoch[026] Batch [0049]/[3759] Speed: 48.290371 samples/sec accuracy=62.968750 loss=1.516310 lr=0.010000 Epoch[026] Batch [0099]/[3759] Speed: 71.033094 samples/sec accuracy=63.171875 loss=1.489444 lr=0.010000 Epoch[026] Batch [0149]/[3759] Speed: 72.110270 samples/sec accuracy=62.322917 loss=1.504553 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lr=0.010000 Epoch[026] Batch [3049]/[3759] Speed: 71.624033 samples/sec accuracy=62.073770 loss=1.552068 lr=0.010000 Epoch[026] Batch [3099]/[3759] Speed: 71.642895 samples/sec accuracy=62.068044 loss=1.552236 lr=0.010000 Epoch[026] Batch [3149]/[3759] Speed: 71.773242 samples/sec accuracy=62.077877 loss=1.551685 lr=0.010000 Epoch[026] Batch [3199]/[3759] Speed: 72.065602 samples/sec accuracy=62.056641 loss=1.552469 lr=0.010000 Epoch[026] Batch [3249]/[3759] Speed: 71.391835 samples/sec accuracy=62.045673 loss=1.552988 lr=0.010000 Epoch[026] Batch [3299]/[3759] Speed: 71.828582 samples/sec accuracy=62.044508 loss=1.553146 lr=0.010000 Epoch[026] Batch [3349]/[3759] Speed: 71.916453 samples/sec accuracy=62.031250 loss=1.553594 lr=0.010000 Epoch[026] Batch [3399]/[3759] Speed: 71.549215 samples/sec accuracy=62.030331 loss=1.553956 lr=0.010000 Epoch[026] Batch [3449]/[3759] Speed: 71.912213 samples/sec accuracy=62.019022 loss=1.554398 lr=0.010000 Epoch[026] Batch [3499]/[3759] Speed: 72.799710 samples/sec accuracy=62.007589 loss=1.555113 lr=0.010000 Epoch[026] Batch [3549]/[3759] Speed: 71.244970 samples/sec accuracy=61.988996 loss=1.555612 lr=0.010000 Epoch[026] Batch [3599]/[3759] Speed: 72.710259 samples/sec accuracy=61.969184 loss=1.555971 lr=0.010000 Epoch[026] Batch [3649]/[3759] Speed: 70.091543 samples/sec accuracy=61.935360 loss=1.557766 lr=0.010000 Epoch[026] Batch [3699]/[3759] Speed: 72.442066 samples/sec accuracy=61.933277 loss=1.557933 lr=0.010000 Epoch[026] Batch [3749]/[3759] Speed: 80.292316 samples/sec accuracy=61.919167 loss=1.558266 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.875000 acc-top5=82.812500 Batch [0099]/[0303]: acc-top1=60.093750 acc-top5=82.453125 Batch [0149]/[0303]: acc-top1=59.562500 acc-top5=82.125000 Batch [0199]/[0303]: acc-top1=59.156250 acc-top5=82.015625 Batch [0249]/[0303]: acc-top1=59.106250 acc-top5=82.031250 Batch [0299]/[0303]: acc-top1=59.302083 acc-top5=82.036458 [Epoch 026] training: accuracy=61.918063 loss=1.558244 [Epoch 026] speed: 71 samples/sec time cost: 3652.656112 [Epoch 026] validation: acc-top1=59.313119 acc-top5=82.064769 loss=1.885115 Epoch[027] Batch [0049]/[3760] Speed: 48.585782 samples/sec accuracy=63.531250 loss=1.488462 lr=0.010000 Epoch[027] Batch [0099]/[3760] Speed: 70.974861 samples/sec accuracy=63.156250 loss=1.496766 lr=0.010000 Epoch[027] Batch [0149]/[3760] Speed: 71.728661 samples/sec accuracy=63.166667 loss=1.498230 lr=0.010000 Epoch[027] Batch [0199]/[3760] Speed: 71.604696 samples/sec accuracy=62.953125 loss=1.502205 lr=0.010000 Epoch[027] Batch [0249]/[3760] Speed: 71.443801 samples/sec accuracy=62.687500 loss=1.516819 lr=0.010000 Epoch[027] Batch [0299]/[3760] Speed: 71.775545 samples/sec accuracy=62.515625 loss=1.527176 lr=0.010000 Epoch[027] Batch [0349]/[3760] Speed: 71.490891 samples/sec accuracy=62.486607 loss=1.528162 lr=0.010000 Epoch[027] Batch [0399]/[3760] Speed: 72.320365 samples/sec accuracy=62.277344 loss=1.534491 lr=0.010000 Epoch[027] Batch 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accuracy=62.666667 loss=1.520219 lr=0.010000 Epoch[027] Batch [0949]/[3760] Speed: 71.819626 samples/sec accuracy=62.618421 loss=1.519039 lr=0.010000 Epoch[027] Batch [0999]/[3760] Speed: 71.389092 samples/sec accuracy=62.568750 loss=1.521702 lr=0.010000 Epoch[027] Batch [1049]/[3760] Speed: 71.716791 samples/sec accuracy=62.501488 loss=1.524371 lr=0.010000 Epoch[027] Batch [1099]/[3760] Speed: 71.829595 samples/sec accuracy=62.484375 loss=1.524946 lr=0.010000 Epoch[027] Batch [1149]/[3760] Speed: 72.060651 samples/sec accuracy=62.476902 loss=1.525660 lr=0.010000 Epoch[027] Batch [1199]/[3760] Speed: 71.371953 samples/sec accuracy=62.424479 loss=1.527417 lr=0.010000 Epoch[027] Batch [1249]/[3760] Speed: 71.443175 samples/sec accuracy=62.412500 loss=1.527850 lr=0.010000 Epoch[027] Batch [1299]/[3760] Speed: 71.609107 samples/sec accuracy=62.385817 loss=1.528127 lr=0.010000 Epoch[027] Batch [1349]/[3760] Speed: 71.997287 samples/sec accuracy=62.314815 loss=1.531258 lr=0.010000 Epoch[027] 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accuracy=62.135135 loss=1.540499 lr=0.010000 Epoch[027] Batch [1899]/[3760] Speed: 71.723321 samples/sec accuracy=62.133224 loss=1.541171 lr=0.010000 Epoch[027] Batch [1949]/[3760] Speed: 71.573571 samples/sec accuracy=62.121795 loss=1.541633 lr=0.010000 Epoch[027] Batch [1999]/[3760] Speed: 71.928487 samples/sec accuracy=62.122656 loss=1.542003 lr=0.010000 Epoch[027] Batch [2049]/[3760] Speed: 72.622950 samples/sec accuracy=62.089939 loss=1.543606 lr=0.010000 Epoch[027] Batch [2099]/[3760] Speed: 71.678605 samples/sec accuracy=62.075893 loss=1.544292 lr=0.010000 Epoch[027] Batch [2149]/[3760] Speed: 71.976070 samples/sec accuracy=62.097384 loss=1.543844 lr=0.010000 Epoch[027] Batch [2199]/[3760] Speed: 71.771802 samples/sec accuracy=62.068892 loss=1.544677 lr=0.010000 Epoch[027] Batch [2249]/[3760] Speed: 71.375039 samples/sec accuracy=62.070139 loss=1.544750 lr=0.010000 Epoch[027] Batch [2299]/[3760] Speed: 71.569946 samples/sec accuracy=62.044158 loss=1.545461 lr=0.010000 Epoch[027] 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accuracy=61.934710 loss=1.550377 lr=0.010000 Epoch[027] Batch [2849]/[3760] Speed: 71.714673 samples/sec accuracy=61.952303 loss=1.549752 lr=0.010000 Epoch[027] Batch [2899]/[3760] Speed: 71.670751 samples/sec accuracy=61.954741 loss=1.550028 lr=0.010000 Epoch[027] Batch [2949]/[3760] Speed: 71.462272 samples/sec accuracy=61.932733 loss=1.551472 lr=0.010000 Epoch[027] Batch [2999]/[3760] Speed: 71.336484 samples/sec accuracy=61.906771 loss=1.552426 lr=0.010000 Epoch[027] Batch [3049]/[3760] Speed: 71.641600 samples/sec accuracy=61.912398 loss=1.552663 lr=0.010000 Epoch[027] Batch [3099]/[3760] Speed: 71.891003 samples/sec accuracy=61.929435 loss=1.552105 lr=0.010000 Epoch[027] Batch [3149]/[3760] Speed: 71.506421 samples/sec accuracy=61.922619 loss=1.551836 lr=0.010000 Epoch[027] Batch [3199]/[3760] Speed: 71.505031 samples/sec accuracy=61.914062 loss=1.551926 lr=0.010000 Epoch[027] Batch [3249]/[3760] Speed: 71.850771 samples/sec accuracy=61.890865 loss=1.552107 lr=0.010000 Epoch[027] Batch [3299]/[3760] Speed: 71.232684 samples/sec accuracy=61.883523 loss=1.552981 lr=0.010000 Epoch[027] Batch [3349]/[3760] Speed: 72.236267 samples/sec accuracy=61.879664 loss=1.553106 lr=0.010000 Epoch[027] Batch [3399]/[3760] Speed: 70.579265 samples/sec accuracy=61.865809 loss=1.553666 lr=0.010000 Epoch[027] Batch [3449]/[3760] Speed: 72.482400 samples/sec accuracy=61.869112 loss=1.553701 lr=0.010000 Epoch[027] Batch [3499]/[3760] Speed: 70.963295 samples/sec accuracy=61.877679 loss=1.553870 lr=0.010000 Epoch[027] Batch [3549]/[3760] Speed: 71.862428 samples/sec accuracy=61.887764 loss=1.554026 lr=0.010000 Epoch[027] Batch [3599]/[3760] Speed: 71.209796 samples/sec accuracy=61.876302 loss=1.554358 lr=0.010000 Epoch[027] Batch [3649]/[3760] Speed: 71.604313 samples/sec accuracy=61.872432 loss=1.554663 lr=0.010000 Epoch[027] Batch [3699]/[3760] Speed: 71.613859 samples/sec accuracy=61.864865 loss=1.554543 lr=0.010000 Epoch[027] Batch [3749]/[3760] Speed: 80.222911 samples/sec accuracy=61.868333 loss=1.554579 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.718750 acc-top5=83.218750 Batch [0099]/[0303]: acc-top1=60.250000 acc-top5=82.890625 Batch [0149]/[0303]: acc-top1=60.062500 acc-top5=82.135417 Batch [0199]/[0303]: acc-top1=59.914062 acc-top5=82.250000 Batch [0249]/[0303]: acc-top1=59.912500 acc-top5=82.268750 Batch [0299]/[0303]: acc-top1=59.979167 acc-top5=82.234375 [Epoch 027] training: accuracy=61.861287 loss=1.554916 [Epoch 027] speed: 71 samples/sec time cost: 3658.116512 [Epoch 027] validation: acc-top1=59.993812 acc-top5=82.250413 loss=1.856482 Epoch[028] Batch [0049]/[3760] Speed: 48.198909 samples/sec accuracy=63.937500 loss=1.483724 lr=0.010000 Epoch[028] Batch [0099]/[3760] Speed: 70.680921 samples/sec accuracy=64.796875 loss=1.454924 lr=0.010000 Epoch[028] Batch [0149]/[3760] Speed: 71.595519 samples/sec accuracy=64.562500 loss=1.467696 lr=0.010000 Epoch[028] Batch [0199]/[3760] Speed: 71.879780 samples/sec accuracy=64.406250 loss=1.470013 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acc-top5=82.090553 loss=1.875616 Epoch[029] Batch [0049]/[3759] Speed: 48.612203 samples/sec accuracy=63.750000 loss=1.486275 lr=0.010000 Epoch[029] Batch [0099]/[3759] Speed: 70.601978 samples/sec accuracy=62.953125 loss=1.497508 lr=0.010000 Epoch[029] Batch [0149]/[3759] Speed: 71.683392 samples/sec accuracy=63.031250 loss=1.495095 lr=0.010000 Epoch[029] Batch [0199]/[3759] Speed: 71.550768 samples/sec accuracy=63.296875 loss=1.484130 lr=0.010000 Epoch[029] Batch [0249]/[3759] Speed: 71.752014 samples/sec accuracy=63.381250 loss=1.481818 lr=0.010000 Epoch[029] Batch [0299]/[3759] Speed: 71.561126 samples/sec accuracy=63.088542 loss=1.492190 lr=0.010000 Epoch[029] Batch [0349]/[3759] Speed: 72.023310 samples/sec accuracy=63.174107 loss=1.492455 lr=0.010000 Epoch[029] Batch [0399]/[3759] Speed: 71.082825 samples/sec accuracy=62.992188 loss=1.499805 lr=0.010000 Epoch[029] Batch [0449]/[3759] Speed: 72.325223 samples/sec accuracy=62.951389 loss=1.504772 lr=0.010000 Epoch[029] Batch 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accuracy=62.689967 loss=1.520741 lr=0.010000 Epoch[029] Batch [1949]/[3759] Speed: 71.123274 samples/sec accuracy=62.691506 loss=1.521509 lr=0.010000 Epoch[029] Batch [1999]/[3759] Speed: 71.741021 samples/sec accuracy=62.684375 loss=1.521830 lr=0.010000 Epoch[029] Batch [2049]/[3759] Speed: 72.040908 samples/sec accuracy=62.663872 loss=1.523210 lr=0.010000 Epoch[029] Batch [2099]/[3759] Speed: 71.745489 samples/sec accuracy=62.639137 loss=1.523948 lr=0.010000 Epoch[029] Batch [2149]/[3759] Speed: 71.281773 samples/sec accuracy=62.599564 loss=1.524719 lr=0.010000 Epoch[029] Batch [2199]/[3759] Speed: 71.622899 samples/sec accuracy=62.617188 loss=1.525181 lr=0.010000 Epoch[029] Batch [2249]/[3759] Speed: 71.546131 samples/sec accuracy=62.600694 loss=1.526145 lr=0.010000 Epoch[029] Batch [2299]/[3759] Speed: 71.476027 samples/sec accuracy=62.620924 loss=1.526369 lr=0.010000 Epoch[029] Batch [2349]/[3759] Speed: 71.952172 samples/sec accuracy=62.590426 loss=1.527821 lr=0.010000 Epoch[029] 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accuracy=62.516447 loss=1.530968 lr=0.010000 Epoch[029] Batch [2899]/[3759] Speed: 71.160747 samples/sec accuracy=62.529095 loss=1.530423 lr=0.010000 Epoch[029] Batch [2949]/[3759] Speed: 71.879071 samples/sec accuracy=62.514831 loss=1.531268 lr=0.010000 Epoch[029] Batch [2999]/[3759] Speed: 71.100516 samples/sec accuracy=62.465625 loss=1.533272 lr=0.010000 Epoch[029] Batch [3049]/[3759] Speed: 72.096786 samples/sec accuracy=62.476434 loss=1.533287 lr=0.010000 Epoch[029] Batch [3099]/[3759] Speed: 71.706272 samples/sec accuracy=62.463206 loss=1.534170 lr=0.010000 Epoch[029] Batch [3149]/[3759] Speed: 71.702012 samples/sec accuracy=62.456845 loss=1.534591 lr=0.010000 Epoch[029] Batch [3199]/[3759] Speed: 71.716298 samples/sec accuracy=62.422852 loss=1.536115 lr=0.010000 Epoch[029] Batch [3249]/[3759] Speed: 71.433304 samples/sec accuracy=62.425962 loss=1.536018 lr=0.010000 Epoch[029] Batch [3299]/[3759] Speed: 71.821068 samples/sec accuracy=62.444602 loss=1.535763 lr=0.010000 Epoch[029] 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[0099]/[0303]: acc-top1=60.218750 acc-top5=83.546875 Batch [0149]/[0303]: acc-top1=60.052083 acc-top5=82.770833 Batch [0199]/[0303]: acc-top1=59.929687 acc-top5=82.593750 Batch [0249]/[0303]: acc-top1=59.837500 acc-top5=82.468750 Batch [0299]/[0303]: acc-top1=60.005208 acc-top5=82.468750 [Epoch 029] training: accuracy=62.344124 loss=1.539770 [Epoch 029] speed: 71 samples/sec time cost: 3652.496770 [Epoch 029] validation: acc-top1=59.988655 acc-top5=82.503094 loss=1.857837 Epoch[030] Batch [0049]/[3760] Speed: 48.204671 samples/sec accuracy=63.031250 loss=1.527510 lr=0.010000 Epoch[030] Batch [0099]/[3760] Speed: 71.296190 samples/sec accuracy=63.109375 loss=1.505092 lr=0.010000 Epoch[030] Batch [0149]/[3760] Speed: 71.530585 samples/sec accuracy=63.520833 loss=1.495566 lr=0.010000 Epoch[030] Batch [0199]/[3760] Speed: 71.738708 samples/sec accuracy=63.406250 loss=1.496491 lr=0.010000 Epoch[030] Batch [0249]/[3760] Speed: 71.127353 samples/sec accuracy=63.331250 loss=1.499920 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71.902119 samples/sec accuracy=62.522569 loss=1.534383 lr=0.010000 Epoch[030] Batch [3649]/[3760] Speed: 72.054569 samples/sec accuracy=62.511986 loss=1.534893 lr=0.010000 Epoch[030] Batch [3699]/[3760] Speed: 70.743718 samples/sec accuracy=62.493243 loss=1.535677 lr=0.010000 Epoch[030] Batch [3749]/[3760] Speed: 80.253292 samples/sec accuracy=62.502917 loss=1.535949 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.406250 acc-top5=83.281250 Batch [0099]/[0303]: acc-top1=59.265625 acc-top5=82.750000 Batch [0149]/[0303]: acc-top1=59.187500 acc-top5=82.020833 Batch [0199]/[0303]: acc-top1=59.195312 acc-top5=81.921875 Batch [0249]/[0303]: acc-top1=59.337500 acc-top5=82.050000 Batch [0299]/[0303]: acc-top1=59.343750 acc-top5=82.026042 [Epoch 030] training: accuracy=62.495429 loss=1.536189 [Epoch 030] speed: 71 samples/sec time cost: 3646.098906 [Epoch 030] validation: acc-top1=59.328589 acc-top5=82.033828 loss=1.909287 Epoch[031] Batch [0049]/[3760] Speed: 48.730924 samples/sec accuracy=63.468750 loss=1.483198 lr=0.010000 Epoch[031] Batch [0099]/[3760] Speed: 71.549248 samples/sec accuracy=62.796875 loss=1.495265 lr=0.010000 Epoch[031] Batch [0149]/[3760] Speed: 71.124515 samples/sec accuracy=63.447917 loss=1.478970 lr=0.010000 Epoch[031] Batch [0199]/[3760] Speed: 72.085786 samples/sec accuracy=63.625000 loss=1.472514 lr=0.010000 Epoch[031] Batch [0249]/[3760] Speed: 71.180239 samples/sec accuracy=63.450000 loss=1.478211 lr=0.010000 Epoch[031] Batch [0299]/[3760] Speed: 72.100030 samples/sec accuracy=63.130208 loss=1.492007 lr=0.010000 Epoch[031] Batch [0349]/[3760] Speed: 71.174337 samples/sec accuracy=63.089286 loss=1.496564 lr=0.010000 Epoch[031] Batch [0399]/[3760] Speed: 71.724857 samples/sec accuracy=63.074219 loss=1.494280 lr=0.010000 Epoch[031] Batch [0449]/[3760] Speed: 71.610986 samples/sec accuracy=62.968750 loss=1.496219 lr=0.010000 Epoch[031] Batch [0499]/[3760] Speed: 72.170812 samples/sec accuracy=62.906250 loss=1.498285 lr=0.010000 Epoch[031] 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accuracy=63.035938 loss=1.505710 lr=0.010000 Epoch[031] Batch [1049]/[3760] Speed: 71.715421 samples/sec accuracy=63.007440 loss=1.506879 lr=0.010000 Epoch[031] Batch [1099]/[3760] Speed: 72.137572 samples/sec accuracy=62.980114 loss=1.507244 lr=0.010000 Epoch[031] Batch [1149]/[3760] Speed: 71.800242 samples/sec accuracy=63.031250 loss=1.506542 lr=0.010000 Epoch[031] Batch [1199]/[3760] Speed: 71.773601 samples/sec accuracy=63.011719 loss=1.509274 lr=0.010000 Epoch[031] Batch [1249]/[3760] Speed: 71.994584 samples/sec accuracy=63.027500 loss=1.508562 lr=0.010000 Epoch[031] Batch [1299]/[3760] Speed: 71.584495 samples/sec accuracy=62.973558 loss=1.510685 lr=0.010000 Epoch[031] Batch [1349]/[3760] Speed: 71.988045 samples/sec accuracy=62.953704 loss=1.511235 lr=0.010000 Epoch[031] Batch [1399]/[3760] Speed: 71.910836 samples/sec accuracy=62.972098 loss=1.509592 lr=0.010000 Epoch[031] Batch [1449]/[3760] Speed: 71.376943 samples/sec accuracy=62.963362 loss=1.510463 lr=0.010000 Epoch[031] 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accuracy=62.861378 loss=1.513871 lr=0.010000 Epoch[031] Batch [1999]/[3760] Speed: 71.621901 samples/sec accuracy=62.862500 loss=1.513466 lr=0.010000 Epoch[031] Batch [2049]/[3760] Speed: 71.573024 samples/sec accuracy=62.844512 loss=1.515008 lr=0.010000 Epoch[031] Batch [2099]/[3760] Speed: 71.990900 samples/sec accuracy=62.845238 loss=1.514623 lr=0.010000 Epoch[031] Batch [2149]/[3760] Speed: 71.471688 samples/sec accuracy=62.829215 loss=1.515404 lr=0.010000 Epoch[031] Batch [2199]/[3760] Speed: 72.234734 samples/sec accuracy=62.821023 loss=1.515737 lr=0.010000 Epoch[031] Batch [2249]/[3760] Speed: 71.471216 samples/sec accuracy=62.850694 loss=1.514973 lr=0.010000 Epoch[031] Batch [2299]/[3760] Speed: 71.737472 samples/sec accuracy=62.804348 loss=1.516335 lr=0.010000 Epoch[031] Batch [2349]/[3760] Speed: 71.704251 samples/sec accuracy=62.816489 loss=1.515904 lr=0.010000 Epoch[031] Batch [2399]/[3760] Speed: 72.712034 samples/sec accuracy=62.804036 loss=1.516406 lr=0.010000 Epoch[031] 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accuracy=62.689655 loss=1.522438 lr=0.010000 Epoch[031] Batch [2949]/[3760] Speed: 71.663567 samples/sec accuracy=62.682733 loss=1.522826 lr=0.010000 Epoch[031] Batch [2999]/[3760] Speed: 71.661398 samples/sec accuracy=62.670313 loss=1.523273 lr=0.010000 Epoch[031] Batch [3049]/[3760] Speed: 71.254748 samples/sec accuracy=62.668545 loss=1.523295 lr=0.010000 Epoch[031] Batch [3099]/[3760] Speed: 71.675828 samples/sec accuracy=62.656250 loss=1.523935 lr=0.010000 Epoch[031] Batch [3149]/[3760] Speed: 72.296831 samples/sec accuracy=62.635417 loss=1.524782 lr=0.010000 Epoch[031] Batch [3199]/[3760] Speed: 71.283089 samples/sec accuracy=62.631348 loss=1.525387 lr=0.010000 Epoch[031] Batch [3249]/[3760] Speed: 72.425177 samples/sec accuracy=62.637981 loss=1.526178 lr=0.010000 Epoch[031] Batch [3299]/[3760] Speed: 71.695962 samples/sec accuracy=62.643466 loss=1.525653 lr=0.010000 Epoch[031] Batch [3349]/[3760] Speed: 71.528701 samples/sec accuracy=62.645522 loss=1.526090 lr=0.010000 Epoch[031] Batch [3399]/[3760] Speed: 72.180925 samples/sec accuracy=62.634191 loss=1.526276 lr=0.010000 Epoch[031] Batch [3449]/[3760] Speed: 71.839225 samples/sec accuracy=62.621377 loss=1.527022 lr=0.010000 Epoch[031] Batch [3499]/[3760] Speed: 71.545212 samples/sec accuracy=62.612054 loss=1.527387 lr=0.010000 Epoch[031] Batch [3549]/[3760] Speed: 72.118540 samples/sec accuracy=62.599912 loss=1.528200 lr=0.010000 Epoch[031] Batch [3599]/[3760] Speed: 71.787680 samples/sec accuracy=62.600694 loss=1.527997 lr=0.010000 Epoch[031] Batch [3649]/[3760] Speed: 71.513107 samples/sec accuracy=62.599743 loss=1.527809 lr=0.010000 Epoch[031] Batch [3699]/[3760] Speed: 71.726700 samples/sec accuracy=62.587416 loss=1.528194 lr=0.010000 Epoch[031] Batch [3749]/[3760] Speed: 80.441148 samples/sec accuracy=62.576250 loss=1.528342 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.187500 acc-top5=83.500000 Batch [0099]/[0303]: acc-top1=59.625000 acc-top5=83.296875 Batch [0149]/[0303]: acc-top1=59.302083 acc-top5=82.395833 Batch [0199]/[0303]: acc-top1=59.078125 acc-top5=82.296875 Batch [0249]/[0303]: acc-top1=59.093750 acc-top5=82.262500 Batch [0299]/[0303]: acc-top1=59.161458 acc-top5=82.312500 [Epoch 031] training: accuracy=62.568983 loss=1.528452 [Epoch 031] speed: 71 samples/sec time cost: 3647.127089 [Epoch 031] validation: acc-top1=59.158416 acc-top5=82.312294 loss=1.877202 Epoch[032] Batch [0049]/[3759] Speed: 49.158994 samples/sec accuracy=64.062500 loss=1.484194 lr=0.010000 Epoch[032] Batch [0099]/[3759] Speed: 70.797921 samples/sec accuracy=64.140625 loss=1.468165 lr=0.010000 Epoch[032] Batch [0149]/[3759] Speed: 71.813662 samples/sec accuracy=63.572917 loss=1.488186 lr=0.010000 Epoch[032] Batch [0199]/[3759] Speed: 71.994864 samples/sec accuracy=63.523438 loss=1.490908 lr=0.010000 Epoch[032] Batch [0249]/[3759] Speed: 72.713431 samples/sec accuracy=63.406250 loss=1.501181 lr=0.010000 Epoch[032] Batch [0299]/[3759] Speed: 71.526438 samples/sec accuracy=63.109375 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accuracy=62.665675 loss=1.519993 lr=0.010000 Epoch[032] Batch [3199]/[3759] Speed: 71.941724 samples/sec accuracy=62.658203 loss=1.520336 lr=0.010000 Epoch[032] Batch [3249]/[3759] Speed: 71.191457 samples/sec accuracy=62.655769 loss=1.520577 lr=0.010000 Epoch[032] Batch [3299]/[3759] Speed: 72.207987 samples/sec accuracy=62.648674 loss=1.521051 lr=0.010000 Epoch[032] Batch [3349]/[3759] Speed: 72.143057 samples/sec accuracy=62.645056 loss=1.521000 lr=0.010000 Epoch[032] Batch [3399]/[3759] Speed: 71.441674 samples/sec accuracy=62.648438 loss=1.521438 lr=0.010000 Epoch[032] Batch [3449]/[3759] Speed: 71.465912 samples/sec accuracy=62.641757 loss=1.522335 lr=0.010000 Epoch[032] Batch [3499]/[3759] Speed: 71.995326 samples/sec accuracy=62.638393 loss=1.522548 lr=0.010000 Epoch[032] Batch [3549]/[3759] Speed: 71.962289 samples/sec accuracy=62.648327 loss=1.522290 lr=0.010000 Epoch[032] Batch [3599]/[3759] Speed: 71.004566 samples/sec accuracy=62.643663 loss=1.522503 lr=0.010000 Epoch[032] Batch [3649]/[3759] Speed: 71.511184 samples/sec accuracy=62.628853 loss=1.522693 lr=0.010000 Epoch[032] Batch [3699]/[3759] Speed: 71.596518 samples/sec accuracy=62.619932 loss=1.522829 lr=0.010000 Epoch[032] Batch [3749]/[3759] Speed: 80.802403 samples/sec accuracy=62.627083 loss=1.523025 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.906250 acc-top5=83.031250 Batch [0099]/[0303]: acc-top1=59.687500 acc-top5=82.968750 Batch [0149]/[0303]: acc-top1=59.677083 acc-top5=82.385417 Batch [0199]/[0303]: acc-top1=59.445312 acc-top5=82.070312 Batch [0249]/[0303]: acc-top1=59.425000 acc-top5=82.200000 Batch [0299]/[0303]: acc-top1=59.442708 acc-top5=82.187500 [Epoch 032] training: accuracy=62.623038 loss=1.523092 [Epoch 032] speed: 71 samples/sec time cost: 3649.654637 [Epoch 032] validation: acc-top1=59.447195 acc-top5=82.193688 loss=1.888961 Epoch[033] Batch [0049]/[3760] Speed: 49.118270 samples/sec accuracy=63.093750 loss=1.513991 lr=0.010000 Epoch[033] Batch [0099]/[3760] Speed: 71.184427 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lr=0.010000 Epoch[033] Batch [2499]/[3760] Speed: 72.015691 samples/sec accuracy=62.870625 loss=1.517006 lr=0.010000 Epoch[033] Batch [2549]/[3760] Speed: 71.918007 samples/sec accuracy=62.851103 loss=1.517112 lr=0.010000 Epoch[033] Batch [2599]/[3760] Speed: 70.927038 samples/sec accuracy=62.825721 loss=1.517388 lr=0.010000 Epoch[033] Batch [2649]/[3760] Speed: 71.291599 samples/sec accuracy=62.824882 loss=1.517790 lr=0.010000 Epoch[033] Batch [2699]/[3760] Speed: 72.112713 samples/sec accuracy=62.817708 loss=1.518090 lr=0.010000 Epoch[033] Batch [2749]/[3760] Speed: 71.296555 samples/sec accuracy=62.809091 loss=1.518707 lr=0.010000 Epoch[033] Batch [2799]/[3760] Speed: 71.775238 samples/sec accuracy=62.805804 loss=1.519438 lr=0.010000 Epoch[033] Batch [2849]/[3760] Speed: 71.823304 samples/sec accuracy=62.791118 loss=1.519869 lr=0.010000 Epoch[033] Batch [2899]/[3760] Speed: 71.838937 samples/sec accuracy=62.820582 loss=1.519331 lr=0.010000 Epoch[033] Batch [2949]/[3760] Speed: 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lr=0.010000 Epoch[033] Batch [3449]/[3760] Speed: 71.213700 samples/sec accuracy=62.686594 loss=1.523475 lr=0.010000 Epoch[033] Batch [3499]/[3760] Speed: 71.505503 samples/sec accuracy=62.674554 loss=1.523924 lr=0.010000 Epoch[033] Batch [3549]/[3760] Speed: 71.051414 samples/sec accuracy=62.637764 loss=1.525312 lr=0.010000 Epoch[033] Batch [3599]/[3760] Speed: 72.092127 samples/sec accuracy=62.634115 loss=1.525115 lr=0.010000 Epoch[033] Batch [3649]/[3760] Speed: 71.719980 samples/sec accuracy=62.632705 loss=1.525604 lr=0.010000 Epoch[033] Batch [3699]/[3760] Speed: 71.975996 samples/sec accuracy=62.624578 loss=1.525552 lr=0.010000 Epoch[033] Batch [3749]/[3760] Speed: 79.081822 samples/sec accuracy=62.627500 loss=1.525731 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.031250 acc-top5=83.093750 Batch [0099]/[0303]: acc-top1=59.656250 acc-top5=82.765625 Batch [0149]/[0303]: acc-top1=59.312500 acc-top5=82.145833 Batch [0199]/[0303]: acc-top1=59.250000 acc-top5=82.078125 Batch [0249]/[0303]: acc-top1=59.293750 acc-top5=82.087500 Batch [0299]/[0303]: acc-top1=59.265625 acc-top5=82.041667 [Epoch 033] training: accuracy=62.629654 loss=1.525592 [Epoch 033] speed: 71 samples/sec time cost: 3654.118676 [Epoch 033] validation: acc-top1=59.297649 acc-top5=82.075083 loss=1.897163 Epoch[034] Batch [0049]/[3759] Speed: 49.038231 samples/sec accuracy=64.218750 loss=1.440111 lr=0.010000 Epoch[034] Batch [0099]/[3759] Speed: 70.673165 samples/sec accuracy=63.578125 loss=1.464918 lr=0.010000 Epoch[034] Batch [0149]/[3759] Speed: 71.592071 samples/sec accuracy=63.885417 loss=1.450987 lr=0.010000 Epoch[034] Batch [0199]/[3759] Speed: 71.524597 samples/sec accuracy=64.312500 loss=1.456425 lr=0.010000 Epoch[034] Batch [0249]/[3759] Speed: 71.691575 samples/sec accuracy=64.168750 loss=1.468505 lr=0.010000 Epoch[034] Batch [0299]/[3759] Speed: 71.531567 samples/sec accuracy=64.088542 loss=1.467130 lr=0.010000 Epoch[034] Batch [0349]/[3759] Speed: 71.887951 samples/sec 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accuracy=63.652644 loss=1.487247 lr=0.010000 Epoch[034] Batch [1349]/[3759] Speed: 71.590470 samples/sec accuracy=63.685185 loss=1.485818 lr=0.010000 Epoch[034] Batch [1399]/[3759] Speed: 71.688096 samples/sec accuracy=63.659598 loss=1.486509 lr=0.010000 Epoch[034] Batch [1449]/[3759] Speed: 71.324505 samples/sec accuracy=63.559267 loss=1.489319 lr=0.010000 Epoch[034] Batch [1499]/[3759] Speed: 71.814700 samples/sec accuracy=63.553125 loss=1.488911 lr=0.010000 Epoch[034] Batch [1549]/[3759] Speed: 71.576459 samples/sec accuracy=63.538306 loss=1.489685 lr=0.010000 Epoch[034] Batch [1599]/[3759] Speed: 72.551594 samples/sec accuracy=63.511719 loss=1.490667 lr=0.010000 Epoch[034] Batch [1649]/[3759] Speed: 72.168457 samples/sec accuracy=63.477273 loss=1.492795 lr=0.010000 Epoch[034] Batch [1699]/[3759] Speed: 72.042413 samples/sec accuracy=63.446691 loss=1.494295 lr=0.010000 Epoch[034] Batch [1749]/[3759] Speed: 71.066379 samples/sec accuracy=63.427679 loss=1.495060 lr=0.010000 Epoch[034] 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accuracy=63.154167 loss=1.502971 lr=0.010000 Epoch[034] Batch [2299]/[3759] Speed: 72.147601 samples/sec accuracy=63.142663 loss=1.503435 lr=0.010000 Epoch[034] Batch [2349]/[3759] Speed: 71.598699 samples/sec accuracy=63.102394 loss=1.505300 lr=0.010000 Epoch[034] Batch [2399]/[3759] Speed: 71.408716 samples/sec accuracy=63.085938 loss=1.505883 lr=0.010000 Epoch[034] Batch [2449]/[3759] Speed: 71.210118 samples/sec accuracy=63.075893 loss=1.506473 lr=0.010000 Epoch[034] Batch [2499]/[3759] Speed: 71.603855 samples/sec accuracy=63.082500 loss=1.506335 lr=0.010000 Epoch[034] Batch [2549]/[3759] Speed: 71.755303 samples/sec accuracy=63.087623 loss=1.506773 lr=0.010000 Epoch[034] Batch [2599]/[3759] Speed: 71.290070 samples/sec accuracy=63.078726 loss=1.507906 lr=0.010000 Epoch[034] Batch [2649]/[3759] Speed: 71.988844 samples/sec accuracy=63.068396 loss=1.507586 lr=0.010000 Epoch[034] Batch [2699]/[3759] Speed: 72.029838 samples/sec accuracy=63.042824 loss=1.508543 lr=0.010000 Epoch[034] 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accuracy=62.971680 loss=1.511768 lr=0.010000 Epoch[034] Batch [3249]/[3759] Speed: 72.047844 samples/sec accuracy=62.972115 loss=1.511603 lr=0.010000 Epoch[034] Batch [3299]/[3759] Speed: 71.928935 samples/sec accuracy=62.944602 loss=1.512896 lr=0.010000 Epoch[034] Batch [3349]/[3759] Speed: 71.597317 samples/sec accuracy=62.937500 loss=1.513272 lr=0.010000 Epoch[034] Batch [3399]/[3759] Speed: 71.496615 samples/sec accuracy=62.928768 loss=1.513500 lr=0.010000 Epoch[034] Batch [3449]/[3759] Speed: 71.327721 samples/sec accuracy=62.934330 loss=1.513410 lr=0.010000 Epoch[034] Batch [3499]/[3759] Speed: 71.781663 samples/sec accuracy=62.930357 loss=1.513898 lr=0.010000 Epoch[034] Batch [3549]/[3759] Speed: 71.716185 samples/sec accuracy=62.909771 loss=1.514122 lr=0.010000 Epoch[034] Batch [3599]/[3759] Speed: 71.518739 samples/sec accuracy=62.906250 loss=1.514251 lr=0.010000 Epoch[034] Batch [3649]/[3759] Speed: 72.276702 samples/sec accuracy=62.904538 loss=1.514030 lr=0.010000 Epoch[034] Batch [3699]/[3759] Speed: 71.175765 samples/sec accuracy=62.895693 loss=1.514271 lr=0.010000 Epoch[034] Batch [3749]/[3759] Speed: 80.228484 samples/sec accuracy=62.906250 loss=1.514097 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.781250 acc-top5=83.687500 Batch [0099]/[0303]: acc-top1=59.500000 acc-top5=83.046875 Batch [0149]/[0303]: acc-top1=59.656250 acc-top5=82.343750 Batch [0199]/[0303]: acc-top1=59.343750 acc-top5=82.203125 Batch [0249]/[0303]: acc-top1=59.443750 acc-top5=82.262500 Batch [0299]/[0303]: acc-top1=59.390625 acc-top5=82.177083 [Epoch 034] training: accuracy=62.903199 loss=1.514063 [Epoch 034] speed: 71 samples/sec time cost: 3653.007350 [Epoch 034] validation: acc-top1=59.405941 acc-top5=82.198845 loss=1.932332 Epoch[035] Batch [0049]/[3760] Speed: 48.905647 samples/sec accuracy=64.843750 loss=1.435876 lr=0.010000 Epoch[035] Batch [0099]/[3760] Speed: 70.572799 samples/sec accuracy=64.031250 loss=1.470036 lr=0.010000 Epoch[035] Batch [0149]/[3760] Speed: 71.503777 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lr=0.010000 Epoch[035] Batch [1599]/[3760] Speed: 71.114535 samples/sec accuracy=63.240234 loss=1.496467 lr=0.010000 Epoch[035] Batch [1649]/[3760] Speed: 71.862647 samples/sec accuracy=63.225379 loss=1.497067 lr=0.010000 Epoch[035] Batch [1699]/[3760] Speed: 71.597884 samples/sec accuracy=63.203125 loss=1.497243 lr=0.010000 Epoch[035] Batch [1749]/[3760] Speed: 71.754070 samples/sec accuracy=63.261607 loss=1.495657 lr=0.010000 Epoch[035] Batch [1799]/[3760] Speed: 71.807082 samples/sec accuracy=63.258681 loss=1.496066 lr=0.010000 Epoch[035] Batch [1849]/[3760] Speed: 71.122634 samples/sec accuracy=63.280405 loss=1.494780 lr=0.010000 Epoch[035] Batch [1899]/[3760] Speed: 72.338222 samples/sec accuracy=63.220395 loss=1.497487 lr=0.010000 Epoch[035] Batch [1949]/[3760] Speed: 71.098734 samples/sec accuracy=63.199519 loss=1.498824 lr=0.010000 Epoch[035] Batch [1999]/[3760] Speed: 71.711520 samples/sec accuracy=63.202344 loss=1.499458 lr=0.010000 Epoch[035] Batch [2049]/[3760] Speed: 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lr=0.010000 Epoch[035] Batch [2549]/[3760] Speed: 71.227728 samples/sec accuracy=62.961397 loss=1.511460 lr=0.010000 Epoch[035] Batch [2599]/[3760] Speed: 71.885354 samples/sec accuracy=62.933293 loss=1.512507 lr=0.010000 Epoch[035] Batch [2649]/[3760] Speed: 71.520771 samples/sec accuracy=62.932783 loss=1.512835 lr=0.010000 Epoch[035] Batch [2699]/[3760] Speed: 72.018434 samples/sec accuracy=62.905671 loss=1.513720 lr=0.010000 Epoch[035] Batch [2749]/[3760] Speed: 71.327496 samples/sec accuracy=62.914773 loss=1.513780 lr=0.010000 Epoch[035] Batch [2799]/[3760] Speed: 72.398170 samples/sec accuracy=62.911830 loss=1.513776 lr=0.010000 Epoch[035] Batch [2849]/[3760] Speed: 71.462209 samples/sec accuracy=62.922697 loss=1.513484 lr=0.010000 Epoch[035] Batch [2899]/[3760] Speed: 72.121897 samples/sec accuracy=62.914332 loss=1.514297 lr=0.010000 Epoch[035] Batch [2949]/[3760] Speed: 71.709609 samples/sec accuracy=62.902013 loss=1.514218 lr=0.010000 Epoch[035] Batch [2999]/[3760] Speed: 72.008373 samples/sec accuracy=62.896875 loss=1.514128 lr=0.010000 Epoch[035] Batch [3049]/[3760] Speed: 71.657914 samples/sec accuracy=62.910861 loss=1.513407 lr=0.010000 Epoch[035] Batch [3099]/[3760] Speed: 71.037625 samples/sec accuracy=62.923387 loss=1.513374 lr=0.010000 Epoch[035] Batch [3149]/[3760] Speed: 71.896168 samples/sec accuracy=62.962302 loss=1.512058 lr=0.010000 Epoch[035] Batch [3199]/[3760] Speed: 71.318125 samples/sec accuracy=62.962891 loss=1.512405 lr=0.010000 Epoch[035] Batch [3249]/[3760] Speed: 72.065127 samples/sec accuracy=62.942308 loss=1.513709 lr=0.010000 Epoch[035] Batch [3299]/[3760] Speed: 72.165809 samples/sec accuracy=62.945549 loss=1.513362 lr=0.010000 Epoch[035] Batch [3349]/[3760] Speed: 71.621847 samples/sec accuracy=62.912780 loss=1.514944 lr=0.010000 Epoch[035] Batch [3399]/[3760] Speed: 71.243655 samples/sec accuracy=62.907629 loss=1.515078 lr=0.010000 Epoch[035] Batch [3449]/[3760] Speed: 71.388278 samples/sec accuracy=62.913043 loss=1.515246 lr=0.010000 Epoch[035] Batch [3499]/[3760] Speed: 71.307226 samples/sec accuracy=62.900893 loss=1.516132 lr=0.010000 Epoch[035] Batch [3549]/[3760] Speed: 71.710370 samples/sec accuracy=62.890845 loss=1.516049 lr=0.010000 Epoch[035] Batch [3599]/[3760] Speed: 71.873853 samples/sec accuracy=62.879340 loss=1.516294 lr=0.010000 Epoch[035] Batch [3649]/[3760] Speed: 72.120612 samples/sec accuracy=62.885702 loss=1.516423 lr=0.010000 Epoch[035] Batch [3699]/[3760] Speed: 71.402138 samples/sec accuracy=62.872889 loss=1.516437 lr=0.010000 Epoch[035] Batch [3749]/[3760] Speed: 79.225133 samples/sec accuracy=62.858333 loss=1.517015 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.781250 acc-top5=84.250000 Batch [0099]/[0303]: acc-top1=60.250000 acc-top5=83.609375 Batch [0149]/[0303]: acc-top1=59.979167 acc-top5=82.583333 Batch [0199]/[0303]: acc-top1=59.835938 acc-top5=82.562500 Batch [0249]/[0303]: acc-top1=59.762500 acc-top5=82.587500 Batch [0299]/[0303]: acc-top1=59.765625 acc-top5=82.401042 [Epoch 035] training: accuracy=62.859458 loss=1.517079 [Epoch 035] speed: 71 samples/sec time cost: 3653.623687 [Epoch 035] validation: acc-top1=59.772071 acc-top5=82.425743 loss=1.883282 Epoch[036] Batch [0049]/[3760] Speed: 49.789695 samples/sec accuracy=64.000000 loss=1.445881 lr=0.010000 Epoch[036] Batch [0099]/[3760] Speed: 71.143095 samples/sec accuracy=63.906250 loss=1.449083 lr=0.010000 Epoch[036] Batch [0149]/[3760] Speed: 71.386797 samples/sec accuracy=63.822917 loss=1.461011 lr=0.010000 Epoch[036] Batch [0199]/[3760] Speed: 71.196314 samples/sec accuracy=64.101562 loss=1.454907 lr=0.010000 Epoch[036] Batch [0249]/[3760] Speed: 71.812011 samples/sec accuracy=63.906250 loss=1.459182 lr=0.010000 Epoch[036] Batch [0299]/[3760] Speed: 72.335758 samples/sec accuracy=63.791667 loss=1.463797 lr=0.010000 Epoch[036] Batch [0349]/[3760] Speed: 72.234744 samples/sec accuracy=63.928571 loss=1.463486 lr=0.010000 Epoch[036] Batch [0399]/[3760] Speed: 71.323197 samples/sec accuracy=63.750000 loss=1.468968 lr=0.010000 Epoch[036] Batch [0449]/[3760] Speed: 71.890269 samples/sec accuracy=63.829861 loss=1.466374 lr=0.010000 Epoch[036] Batch [0499]/[3760] Speed: 71.695299 samples/sec accuracy=63.846875 loss=1.467476 lr=0.010000 Epoch[036] Batch [0549]/[3760] Speed: 72.177462 samples/sec accuracy=63.803977 loss=1.464731 lr=0.010000 Epoch[036] Batch [0599]/[3760] Speed: 71.718409 samples/sec accuracy=63.765625 loss=1.468262 lr=0.010000 Epoch[036] Batch [0649]/[3760] Speed: 71.693312 samples/sec accuracy=63.819712 loss=1.466870 lr=0.010000 Epoch[036] Batch [0699]/[3760] Speed: 73.005048 samples/sec accuracy=63.866071 loss=1.465476 lr=0.010000 Epoch[036] Batch [0749]/[3760] Speed: 71.506848 samples/sec accuracy=63.870833 loss=1.466246 lr=0.010000 Epoch[036] Batch [0799]/[3760] Speed: 71.598435 samples/sec accuracy=63.830078 loss=1.468530 lr=0.010000 Epoch[036] Batch [0849]/[3760] Speed: 71.541491 samples/sec accuracy=63.812500 loss=1.468475 lr=0.010000 Epoch[036] 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accuracy=63.545139 loss=1.483094 lr=0.010000 Epoch[036] Batch [1399]/[3760] Speed: 71.006628 samples/sec accuracy=63.537946 loss=1.483756 lr=0.010000 Epoch[036] Batch [1449]/[3760] Speed: 71.920686 samples/sec accuracy=63.546336 loss=1.483836 lr=0.010000 Epoch[036] Batch [1499]/[3760] Speed: 71.519951 samples/sec accuracy=63.560417 loss=1.482636 lr=0.010000 Epoch[036] Batch [1549]/[3760] Speed: 71.576663 samples/sec accuracy=63.569556 loss=1.483025 lr=0.010000 Epoch[036] Batch [1599]/[3760] Speed: 71.812984 samples/sec accuracy=63.582031 loss=1.482551 lr=0.010000 Epoch[036] Batch [1649]/[3760] Speed: 71.589625 samples/sec accuracy=63.553030 loss=1.483075 lr=0.010000 Epoch[036] Batch [1699]/[3760] Speed: 71.665898 samples/sec accuracy=63.506434 loss=1.484540 lr=0.010000 Epoch[036] Batch [1749]/[3760] Speed: 71.762145 samples/sec accuracy=63.524107 loss=1.484206 lr=0.010000 Epoch[036] Batch [1799]/[3760] Speed: 71.373129 samples/sec accuracy=63.512153 loss=1.484484 lr=0.010000 Epoch[036] 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accuracy=63.430707 loss=1.489609 lr=0.010000 Epoch[036] Batch [2349]/[3760] Speed: 71.764279 samples/sec accuracy=63.416888 loss=1.490482 lr=0.010000 Epoch[036] Batch [2399]/[3760] Speed: 71.925927 samples/sec accuracy=63.387370 loss=1.491544 lr=0.010000 Epoch[036] Batch [2449]/[3760] Speed: 71.855301 samples/sec accuracy=63.360332 loss=1.492310 lr=0.010000 Epoch[036] Batch [2499]/[3760] Speed: 71.558591 samples/sec accuracy=63.350625 loss=1.493397 lr=0.010000 Epoch[036] Batch [2549]/[3760] Speed: 72.438209 samples/sec accuracy=63.320466 loss=1.494734 lr=0.010000 Epoch[036] Batch [2599]/[3760] Speed: 71.352742 samples/sec accuracy=63.311298 loss=1.495323 lr=0.010000 Epoch[036] Batch [2649]/[3760] Speed: 71.748143 samples/sec accuracy=63.314269 loss=1.495109 lr=0.010000 Epoch[036] Batch [2699]/[3760] Speed: 72.099900 samples/sec accuracy=63.316551 loss=1.494670 lr=0.010000 Epoch[036] Batch [2749]/[3760] Speed: 71.439055 samples/sec accuracy=63.297727 loss=1.495228 lr=0.010000 Epoch[036] 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accuracy=63.134135 loss=1.501312 lr=0.010000 Epoch[036] Batch [3299]/[3760] Speed: 71.632752 samples/sec accuracy=63.112216 loss=1.502618 lr=0.010000 Epoch[036] Batch [3349]/[3760] Speed: 71.887707 samples/sec accuracy=63.097948 loss=1.503734 lr=0.010000 Epoch[036] Batch [3399]/[3760] Speed: 71.941208 samples/sec accuracy=63.079504 loss=1.504023 lr=0.010000 Epoch[036] Batch [3449]/[3760] Speed: 71.972813 samples/sec accuracy=63.083786 loss=1.504424 lr=0.010000 Epoch[036] Batch [3499]/[3760] Speed: 71.559609 samples/sec accuracy=63.072768 loss=1.504807 lr=0.010000 Epoch[036] Batch [3549]/[3760] Speed: 72.239089 samples/sec accuracy=63.064261 loss=1.505036 lr=0.010000 Epoch[036] Batch [3599]/[3760] Speed: 71.413265 samples/sec accuracy=63.050347 loss=1.505454 lr=0.010000 Epoch[036] Batch [3649]/[3760] Speed: 71.746197 samples/sec accuracy=63.059075 loss=1.505239 lr=0.010000 Epoch[036] Batch [3699]/[3760] Speed: 70.931301 samples/sec accuracy=63.041385 loss=1.505715 lr=0.010000 Epoch[036] Batch [3749]/[3760] Speed: 80.061485 samples/sec accuracy=63.013333 loss=1.507231 lr=0.010000 Batch [0049]/[0303]: acc-top1=59.843750 acc-top5=84.156250 Batch [0099]/[0303]: acc-top1=60.062500 acc-top5=83.515625 Batch [0149]/[0303]: acc-top1=60.114583 acc-top5=82.854167 Batch [0199]/[0303]: acc-top1=59.960938 acc-top5=82.781250 Batch [0249]/[0303]: acc-top1=60.037500 acc-top5=82.812500 Batch [0299]/[0303]: acc-top1=60.041667 acc-top5=82.765625 [Epoch 036] training: accuracy=63.016124 loss=1.507151 [Epoch 036] speed: 71 samples/sec time cost: 3647.597415 [Epoch 036] validation: acc-top1=60.035066 acc-top5=82.791873 loss=1.848731 Epoch[037] Batch [0049]/[3759] Speed: 48.369095 samples/sec accuracy=65.500000 loss=1.434658 lr=0.010000 Epoch[037] Batch [0099]/[3759] Speed: 71.401420 samples/sec accuracy=64.937500 loss=1.444847 lr=0.010000 Epoch[037] Batch [0149]/[3759] Speed: 71.053573 samples/sec accuracy=64.750000 loss=1.440609 lr=0.010000 Epoch[037] Batch [0199]/[3759] Speed: 71.367767 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lr=0.010000 Epoch[037] Batch [0699]/[3759] Speed: 71.874793 samples/sec accuracy=64.281250 loss=1.469441 lr=0.010000 Epoch[037] Batch [0749]/[3759] Speed: 71.564077 samples/sec accuracy=64.210417 loss=1.472986 lr=0.010000 Epoch[037] Batch [0799]/[3759] Speed: 71.661303 samples/sec accuracy=64.193359 loss=1.472514 lr=0.010000 Epoch[037] Batch [0849]/[3759] Speed: 72.120002 samples/sec accuracy=64.077206 loss=1.475428 lr=0.010000 Epoch[037] Batch [0899]/[3759] Speed: 72.330160 samples/sec accuracy=64.060764 loss=1.475554 lr=0.010000 Epoch[037] Batch [0949]/[3759] Speed: 71.346770 samples/sec accuracy=63.978618 loss=1.476630 lr=0.010000 Epoch[037] Batch [0999]/[3759] Speed: 71.878770 samples/sec accuracy=63.939062 loss=1.477014 lr=0.010000 Epoch[037] Batch [1049]/[3759] Speed: 71.610428 samples/sec accuracy=63.901786 loss=1.478876 lr=0.010000 Epoch[037] Batch [1099]/[3759] Speed: 71.400414 samples/sec accuracy=63.839489 loss=1.479418 lr=0.010000 Epoch[037] Batch [1149]/[3759] Speed: 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lr=0.010000 Epoch[037] Batch [1649]/[3759] Speed: 72.257878 samples/sec accuracy=63.715909 loss=1.480699 lr=0.010000 Epoch[037] Batch [1699]/[3759] Speed: 71.010082 samples/sec accuracy=63.636949 loss=1.483261 lr=0.010000 Epoch[037] Batch [1749]/[3759] Speed: 71.869213 samples/sec accuracy=63.598214 loss=1.483835 lr=0.010000 Epoch[037] Batch [1799]/[3759] Speed: 71.730906 samples/sec accuracy=63.599826 loss=1.483100 lr=0.010000 Epoch[037] Batch [1849]/[3759] Speed: 72.108601 samples/sec accuracy=63.553209 loss=1.485303 lr=0.010000 Epoch[037] Batch [1899]/[3759] Speed: 71.334001 samples/sec accuracy=63.533717 loss=1.485852 lr=0.010000 Epoch[037] Batch [1949]/[3759] Speed: 72.356859 samples/sec accuracy=63.528045 loss=1.485428 lr=0.010000 Epoch[037] Batch [1999]/[3759] Speed: 72.020032 samples/sec accuracy=63.489844 loss=1.486712 lr=0.010000 Epoch[037] Batch [2049]/[3759] Speed: 71.472194 samples/sec accuracy=63.467226 loss=1.487792 lr=0.010000 Epoch[037] Batch [2099]/[3759] Speed: 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lr=0.010000 Epoch[037] Batch [2599]/[3759] Speed: 72.060671 samples/sec accuracy=63.305889 loss=1.495439 lr=0.010000 Epoch[037] Batch [2649]/[3759] Speed: 71.713541 samples/sec accuracy=63.301887 loss=1.495672 lr=0.010000 Epoch[037] Batch [2699]/[3759] Speed: 71.316124 samples/sec accuracy=63.300926 loss=1.495942 lr=0.010000 Epoch[037] Batch [2749]/[3759] Speed: 72.409346 samples/sec accuracy=63.256250 loss=1.497763 lr=0.010000 Epoch[037] Batch [2799]/[3759] Speed: 71.864787 samples/sec accuracy=63.236607 loss=1.497971 lr=0.010000 Epoch[037] Batch [2849]/[3759] Speed: 71.523678 samples/sec accuracy=63.227522 loss=1.498679 lr=0.010000 Epoch[037] Batch [2899]/[3759] Speed: 71.383396 samples/sec accuracy=63.219289 loss=1.499301 lr=0.010000 Epoch[037] Batch [2949]/[3759] Speed: 71.966568 samples/sec accuracy=63.200742 loss=1.500486 lr=0.010000 Epoch[037] Batch [2999]/[3759] Speed: 71.193826 samples/sec accuracy=63.183854 loss=1.501536 lr=0.010000 Epoch[037] Batch [3049]/[3759] Speed: 71.633124 samples/sec accuracy=63.188525 loss=1.501221 lr=0.010000 Epoch[037] Batch [3099]/[3759] Speed: 71.519030 samples/sec accuracy=63.201109 loss=1.501294 lr=0.010000 Epoch[037] Batch [3149]/[3759] Speed: 72.139694 samples/sec accuracy=63.202381 loss=1.501731 lr=0.010000 Epoch[037] Batch [3199]/[3759] Speed: 71.784434 samples/sec accuracy=63.186035 loss=1.503155 lr=0.010000 Epoch[037] Batch [3249]/[3759] Speed: 71.004991 samples/sec accuracy=63.166827 loss=1.504040 lr=0.010000 Epoch[037] Batch [3299]/[3759] Speed: 72.254108 samples/sec accuracy=63.154830 loss=1.504423 lr=0.010000 Epoch[037] Batch [3349]/[3759] Speed: 71.532200 samples/sec accuracy=63.147854 loss=1.504650 lr=0.010000 Epoch[037] Batch [3399]/[3759] Speed: 72.161423 samples/sec accuracy=63.148897 loss=1.504864 lr=0.010000 Epoch[037] Batch [3449]/[3759] Speed: 71.898165 samples/sec accuracy=63.143569 loss=1.504764 lr=0.010000 Epoch[037] Batch [3499]/[3759] Speed: 71.199682 samples/sec accuracy=63.140625 loss=1.505411 lr=0.010000 Epoch[037] Batch [3549]/[3759] Speed: 71.503163 samples/sec accuracy=63.139085 loss=1.505622 lr=0.010000 Epoch[037] Batch [3599]/[3759] Speed: 72.284085 samples/sec accuracy=63.114583 loss=1.506366 lr=0.010000 Epoch[037] Batch [3649]/[3759] Speed: 71.426896 samples/sec accuracy=63.091182 loss=1.507370 lr=0.010000 Epoch[037] Batch [3699]/[3759] Speed: 72.555627 samples/sec accuracy=63.089105 loss=1.507025 lr=0.010000 Epoch[037] Batch [3749]/[3759] Speed: 79.751851 samples/sec accuracy=63.099583 loss=1.506618 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.093750 acc-top5=83.562500 Batch [0099]/[0303]: acc-top1=59.984375 acc-top5=83.296875 Batch [0149]/[0303]: acc-top1=59.770833 acc-top5=82.750000 Batch [0199]/[0303]: acc-top1=59.703125 acc-top5=82.515625 Batch [0249]/[0303]: acc-top1=59.862500 acc-top5=82.575000 Batch [0299]/[0303]: acc-top1=59.963542 acc-top5=82.515625 [Epoch 037] training: accuracy=63.103551 loss=1.506529 [Epoch 037] speed: 71 samples/sec time cost: 3651.353851 [Epoch 037] validation: acc-top1=59.957715 acc-top5=82.539191 loss=1.891405 Epoch[038] Batch [0049]/[3760] Speed: 48.376900 samples/sec accuracy=62.343750 loss=1.503762 lr=0.010000 Epoch[038] Batch [0099]/[3760] Speed: 72.140846 samples/sec accuracy=63.671875 loss=1.473408 lr=0.010000 Epoch[038] Batch [0149]/[3760] Speed: 72.083405 samples/sec accuracy=63.750000 loss=1.470601 lr=0.010000 Epoch[038] Batch [0199]/[3760] Speed: 71.237275 samples/sec accuracy=63.648438 loss=1.472611 lr=0.010000 Epoch[038] Batch [0249]/[3760] Speed: 71.746800 samples/sec accuracy=63.631250 loss=1.475360 lr=0.010000 Epoch[038] Batch [0299]/[3760] Speed: 71.596776 samples/sec accuracy=63.682292 loss=1.476176 lr=0.010000 Epoch[038] Batch [0349]/[3760] Speed: 71.375613 samples/sec accuracy=63.464286 loss=1.483130 lr=0.010000 Epoch[038] Batch [0399]/[3760] Speed: 71.810098 samples/sec accuracy=63.398438 loss=1.486272 lr=0.010000 Epoch[038] Batch [0449]/[3760] Speed: 71.435826 samples/sec accuracy=63.447917 loss=1.488538 lr=0.010000 Epoch[038] Batch [0499]/[3760] Speed: 72.243216 samples/sec accuracy=63.515625 loss=1.483253 lr=0.010000 Epoch[038] Batch [0549]/[3760] Speed: 72.016866 samples/sec accuracy=63.596591 loss=1.476596 lr=0.010000 Epoch[038] Batch [0599]/[3760] Speed: 71.752579 samples/sec accuracy=63.656250 loss=1.473928 lr=0.010000 Epoch[038] Batch [0649]/[3760] Speed: 71.557088 samples/sec accuracy=63.620192 loss=1.476995 lr=0.010000 Epoch[038] Batch [0699]/[3760] Speed: 71.813156 samples/sec accuracy=63.631696 loss=1.475211 lr=0.010000 Epoch[038] Batch [0749]/[3760] Speed: 71.618712 samples/sec accuracy=63.566667 loss=1.476968 lr=0.010000 Epoch[038] Batch [0799]/[3760] Speed: 71.864235 samples/sec accuracy=63.582031 loss=1.475358 lr=0.010000 Epoch[038] Batch [0849]/[3760] Speed: 71.785026 samples/sec accuracy=63.626838 loss=1.474145 lr=0.010000 Epoch[038] Batch [0899]/[3760] Speed: 71.372566 samples/sec accuracy=63.628472 loss=1.476364 lr=0.010000 Epoch[038] 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accuracy=63.585938 loss=1.482542 lr=0.010000 Epoch[038] Batch [1449]/[3760] Speed: 72.088221 samples/sec accuracy=63.557112 loss=1.482972 lr=0.010000 Epoch[038] Batch [1499]/[3760] Speed: 71.455346 samples/sec accuracy=63.511458 loss=1.484378 lr=0.010000 Epoch[038] Batch [1549]/[3760] Speed: 72.093041 samples/sec accuracy=63.522177 loss=1.484322 lr=0.010000 Epoch[038] Batch [1599]/[3760] Speed: 71.374839 samples/sec accuracy=63.512695 loss=1.484382 lr=0.010000 Epoch[038] Batch [1649]/[3760] Speed: 72.646544 samples/sec accuracy=63.516098 loss=1.484867 lr=0.010000 Epoch[038] Batch [1699]/[3760] Speed: 71.536766 samples/sec accuracy=63.491728 loss=1.486059 lr=0.010000 Epoch[038] Batch [1749]/[3760] Speed: 72.459138 samples/sec accuracy=63.474107 loss=1.486736 lr=0.010000 Epoch[038] Batch [1799]/[3760] Speed: 71.892233 samples/sec accuracy=63.416667 loss=1.488159 lr=0.010000 Epoch[038] Batch [1849]/[3760] Speed: 71.503792 samples/sec accuracy=63.414696 loss=1.488440 lr=0.010000 Epoch[038] 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accuracy=63.281915 loss=1.494444 lr=0.010000 Epoch[038] Batch [2399]/[3760] Speed: 70.953216 samples/sec accuracy=63.277995 loss=1.494547 lr=0.010000 Epoch[038] Batch [2449]/[3760] Speed: 71.588353 samples/sec accuracy=63.262117 loss=1.494609 lr=0.010000 Epoch[038] Batch [2499]/[3760] Speed: 71.874589 samples/sec accuracy=63.248125 loss=1.495634 lr=0.010000 Epoch[038] Batch [2549]/[3760] Speed: 71.677176 samples/sec accuracy=63.287990 loss=1.495211 lr=0.010000 Epoch[038] Batch [2599]/[3760] Speed: 71.979542 samples/sec accuracy=63.273437 loss=1.495486 lr=0.010000 Epoch[038] Batch [2649]/[3760] Speed: 70.961445 samples/sec accuracy=63.286557 loss=1.495013 lr=0.010000 Epoch[038] Batch [2699]/[3760] Speed: 72.627205 samples/sec accuracy=63.284722 loss=1.495642 lr=0.010000 Epoch[038] Batch [2749]/[3760] Speed: 72.247734 samples/sec accuracy=63.250568 loss=1.497203 lr=0.010000 Epoch[038] Batch [2799]/[3760] Speed: 71.127300 samples/sec accuracy=63.228237 loss=1.498345 lr=0.010000 Epoch[038] 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accuracy=63.190341 loss=1.502336 lr=0.010000 Epoch[038] Batch [3349]/[3760] Speed: 71.021184 samples/sec accuracy=63.160914 loss=1.503382 lr=0.010000 Epoch[038] Batch [3399]/[3760] Speed: 71.547798 samples/sec accuracy=63.181066 loss=1.502493 lr=0.010000 Epoch[038] Batch [3449]/[3760] Speed: 71.905698 samples/sec accuracy=63.177083 loss=1.502681 lr=0.010000 Epoch[038] Batch [3499]/[3760] Speed: 71.784851 samples/sec accuracy=63.173661 loss=1.502878 lr=0.010000 Epoch[038] Batch [3549]/[3760] Speed: 71.952119 samples/sec accuracy=63.169454 loss=1.504084 lr=0.010000 Epoch[038] Batch [3599]/[3760] Speed: 72.105787 samples/sec accuracy=63.179253 loss=1.503488 lr=0.010000 Epoch[038] Batch [3649]/[3760] Speed: 71.783769 samples/sec accuracy=63.174658 loss=1.503501 lr=0.010000 Epoch[038] Batch [3699]/[3760] Speed: 71.490447 samples/sec accuracy=63.185811 loss=1.502609 lr=0.010000 Epoch[038] Batch [3749]/[3760] Speed: 79.625135 samples/sec accuracy=63.174167 loss=1.503584 lr=0.010000 Batch [0049]/[0303]: acc-top1=60.031250 acc-top5=84.062500 Batch [0099]/[0303]: acc-top1=60.703125 acc-top5=83.390625 Batch [0149]/[0303]: acc-top1=60.020833 acc-top5=82.500000 Batch [0199]/[0303]: acc-top1=59.406250 acc-top5=82.218750 Batch [0249]/[0303]: acc-top1=59.475000 acc-top5=82.312500 Batch [0299]/[0303]: acc-top1=59.479167 acc-top5=82.286458 [Epoch 038] training: accuracy=63.174036 loss=1.503761 [Epoch 038] speed: 71 samples/sec time cost: 3648.777536 [Epoch 038] validation: acc-top1=59.524546 acc-top5=82.301980 loss=1.919180 Epoch[039] Batch [0049]/[3760] Speed: 48.524270 samples/sec accuracy=63.375000 loss=1.491685 lr=0.010000 Epoch[039] Batch [0099]/[3760] Speed: 71.606576 samples/sec accuracy=63.468750 loss=1.477500 lr=0.010000 Epoch[039] Batch [0149]/[3760] Speed: 71.950226 samples/sec accuracy=63.750000 loss=1.471747 lr=0.010000 Epoch[039] Batch [0199]/[3760] Speed: 71.248766 samples/sec accuracy=64.039062 loss=1.465311 lr=0.010000 Epoch[039] Batch [0249]/[3760] Speed: 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lr=0.010000 Epoch[039] Batch [1699]/[3760] Speed: 71.143835 samples/sec accuracy=63.432904 loss=1.490090 lr=0.010000 Epoch[039] Batch [1749]/[3760] Speed: 71.327876 samples/sec accuracy=63.433036 loss=1.489586 lr=0.010000 Epoch[039] Batch [1799]/[3760] Speed: 72.505781 samples/sec accuracy=63.445312 loss=1.490626 lr=0.010000 Epoch[039] Batch [1849]/[3760] Speed: 71.868585 samples/sec accuracy=63.449324 loss=1.490275 lr=0.010000 Epoch[039] Batch [1899]/[3760] Speed: 72.003659 samples/sec accuracy=63.438322 loss=1.490053 lr=0.010000 Epoch[039] Batch [1949]/[3760] Speed: 71.553716 samples/sec accuracy=63.467147 loss=1.489598 lr=0.010000 Epoch[039] Batch [1999]/[3760] Speed: 71.479687 samples/sec accuracy=63.471094 loss=1.490332 lr=0.010000 Epoch[039] Batch [2049]/[3760] Speed: 71.386568 samples/sec accuracy=63.488567 loss=1.490484 lr=0.010000 Epoch[039] Batch [2099]/[3760] Speed: 71.913511 samples/sec accuracy=63.476190 loss=1.490957 lr=0.010000 Epoch[039] Batch [2149]/[3760] Speed: 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lr=0.010000 Epoch[039] Batch [2649]/[3760] Speed: 72.271015 samples/sec accuracy=63.387382 loss=1.493218 lr=0.010000 Epoch[039] Batch [2699]/[3760] Speed: 71.941731 samples/sec accuracy=63.392361 loss=1.492801 lr=0.010000 Epoch[039] Batch [2749]/[3760] Speed: 71.474877 samples/sec accuracy=63.394318 loss=1.492707 lr=0.010000 Epoch[039] Batch [2799]/[3760] Speed: 72.268670 samples/sec accuracy=63.400112 loss=1.492377 lr=0.010000 Epoch[039] Batch [2849]/[3760] Speed: 71.688915 samples/sec accuracy=63.398575 loss=1.491897 lr=0.010000 Epoch[039] Batch [2899]/[3760] Speed: 71.719642 samples/sec accuracy=63.386853 loss=1.492677 lr=0.010000 Epoch[039] Batch [2949]/[3760] Speed: 72.110943 samples/sec accuracy=63.372352 loss=1.493044 lr=0.010000 Epoch[039] Batch [2999]/[3760] Speed: 72.426824 samples/sec accuracy=63.376042 loss=1.493112 lr=0.010000 Epoch[039] Batch [3049]/[3760] Speed: 71.188773 samples/sec accuracy=63.359119 loss=1.493859 lr=0.010000 Epoch[039] Batch [3099]/[3760] Speed: 72.197510 samples/sec accuracy=63.349798 loss=1.494614 lr=0.010000 Epoch[039] Batch [3149]/[3760] Speed: 70.904723 samples/sec accuracy=63.352679 loss=1.494306 lr=0.010000 Epoch[039] Batch [3199]/[3760] Speed: 71.870130 samples/sec accuracy=63.331543 loss=1.495096 lr=0.010000 Epoch[039] Batch [3249]/[3760] Speed: 71.522725 samples/sec accuracy=63.327404 loss=1.495213 lr=0.010000 Epoch[039] Batch [3299]/[3760] Speed: 72.019367 samples/sec accuracy=63.309659 loss=1.495993 lr=0.010000 Epoch[039] Batch [3349]/[3760] Speed: 71.671831 samples/sec accuracy=63.296175 loss=1.496665 lr=0.010000 Epoch[039] Batch [3399]/[3760] Speed: 72.170023 samples/sec accuracy=63.283548 loss=1.497460 lr=0.010000 Epoch[039] Batch [3449]/[3760] Speed: 70.926094 samples/sec accuracy=63.265399 loss=1.498533 lr=0.010000 Epoch[039] Batch [3499]/[3760] Speed: 71.504976 samples/sec accuracy=63.246875 loss=1.499948 lr=0.010000 Epoch[039] Batch [3549]/[3760] Speed: 71.798565 samples/sec accuracy=63.252201 loss=1.499997 lr=0.010000 Epoch[039] Batch [3599]/[3760] Speed: 71.983679 samples/sec accuracy=63.250868 loss=1.499938 lr=0.010000 Epoch[039] Batch [3649]/[3760] Speed: 72.248139 samples/sec accuracy=63.248288 loss=1.500161 lr=0.010000 Epoch[039] Batch [3699]/[3760] Speed: 70.467190 samples/sec accuracy=63.234375 loss=1.500882 lr=0.010000 Epoch[039] Batch [3749]/[3760] Speed: 79.919529 samples/sec accuracy=63.227500 loss=1.501379 lr=0.001000 Batch [0049]/[0303]: acc-top1=61.343750 acc-top5=84.468750 Batch [0099]/[0303]: acc-top1=60.953125 acc-top5=83.484375 Batch [0149]/[0303]: acc-top1=60.468750 acc-top5=82.750000 Batch [0199]/[0303]: acc-top1=60.335938 acc-top5=82.726562 Batch [0249]/[0303]: acc-top1=60.206250 acc-top5=82.737500 Batch [0299]/[0303]: acc-top1=60.119792 acc-top5=82.645833 [Epoch 039] training: accuracy=63.228474 loss=1.501307 [Epoch 039] speed: 71 samples/sec time cost: 3650.733803 [Epoch 039] validation: acc-top1=60.112417 acc-top5=82.678424 loss=1.908069 Epoch[040] Batch 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accuracy=67.571875 loss=1.326444 lr=0.001000 Epoch[040] Batch [0549]/[3759] Speed: 71.476576 samples/sec accuracy=67.673295 loss=1.321898 lr=0.001000 Epoch[040] Batch [0599]/[3759] Speed: 72.106713 samples/sec accuracy=67.838542 loss=1.316248 lr=0.001000 Epoch[040] Batch [0649]/[3759] Speed: 71.197423 samples/sec accuracy=67.915865 loss=1.310588 lr=0.001000 Epoch[040] Batch [0699]/[3759] Speed: 71.577768 samples/sec accuracy=68.006696 loss=1.305637 lr=0.001000 Epoch[040] Batch [0749]/[3759] Speed: 71.809218 samples/sec accuracy=68.037500 loss=1.301475 lr=0.001000 Epoch[040] Batch [0799]/[3759] Speed: 71.392808 samples/sec accuracy=68.138672 loss=1.297782 lr=0.001000 Epoch[040] Batch [0849]/[3759] Speed: 72.580746 samples/sec accuracy=68.211397 loss=1.293295 lr=0.001000 Epoch[040] Batch [0899]/[3759] Speed: 72.137560 samples/sec accuracy=68.293403 loss=1.288506 lr=0.001000 Epoch[040] Batch [0949]/[3759] Speed: 72.049993 samples/sec accuracy=68.358553 loss=1.285065 lr=0.001000 Epoch[040] 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accuracy=68.961207 loss=1.257785 lr=0.001000 Epoch[040] Batch [1499]/[3759] Speed: 71.325196 samples/sec accuracy=68.985417 loss=1.255439 lr=0.001000 Epoch[040] Batch [1549]/[3759] Speed: 72.739267 samples/sec accuracy=69.020161 loss=1.254294 lr=0.001000 Epoch[040] Batch [1599]/[3759] Speed: 71.551868 samples/sec accuracy=69.088867 loss=1.251407 lr=0.001000 Epoch[040] Batch [1649]/[3759] Speed: 72.196760 samples/sec accuracy=69.133523 loss=1.249553 lr=0.001000 Epoch[040] Batch [1699]/[3759] Speed: 72.006013 samples/sec accuracy=69.135110 loss=1.248000 lr=0.001000 Epoch[040] Batch [1749]/[3759] Speed: 71.598323 samples/sec accuracy=69.159821 loss=1.246362 lr=0.001000 Epoch[040] Batch [1799]/[3759] Speed: 71.749912 samples/sec accuracy=69.197049 loss=1.245823 lr=0.001000 Epoch[040] Batch [1849]/[3759] Speed: 71.855183 samples/sec accuracy=69.221284 loss=1.244917 lr=0.001000 Epoch[040] Batch [1899]/[3759] Speed: 71.951015 samples/sec accuracy=69.236842 loss=1.243670 lr=0.001000 Epoch[040] 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accuracy=69.837687 loss=1.216214 lr=0.001000 Epoch[040] Batch [3399]/[3759] Speed: 71.841331 samples/sec accuracy=69.832721 loss=1.215759 lr=0.001000 Epoch[040] Batch [3449]/[3759] Speed: 71.330568 samples/sec accuracy=69.860054 loss=1.214758 lr=0.001000 Epoch[040] Batch [3499]/[3759] Speed: 72.116572 samples/sec accuracy=69.876339 loss=1.213901 lr=0.001000 Epoch[040] Batch [3549]/[3759] Speed: 71.373187 samples/sec accuracy=69.877641 loss=1.213263 lr=0.001000 Epoch[040] Batch [3599]/[3759] Speed: 72.161117 samples/sec accuracy=69.894965 loss=1.212474 lr=0.001000 Epoch[040] Batch [3649]/[3759] Speed: 71.654215 samples/sec accuracy=69.886558 loss=1.212255 lr=0.001000 Epoch[040] Batch [3699]/[3759] Speed: 71.444816 samples/sec accuracy=69.902872 loss=1.211684 lr=0.001000 Epoch[040] Batch [3749]/[3759] Speed: 80.630412 samples/sec accuracy=69.937500 loss=1.210357 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.312500 acc-top5=87.375000 Batch [0099]/[0303]: acc-top1=66.265625 acc-top5=86.703125 Batch [0149]/[0303]: acc-top1=65.739583 acc-top5=86.000000 Batch [0199]/[0303]: acc-top1=65.570312 acc-top5=85.828125 Batch [0249]/[0303]: acc-top1=65.487500 acc-top5=85.793750 Batch [0299]/[0303]: acc-top1=65.598958 acc-top5=85.791667 [Epoch 040] training: accuracy=69.929253 loss=1.210536 [Epoch 040] speed: 71 samples/sec time cost: 3648.877946 [Epoch 040] validation: acc-top1=65.583746 acc-top5=85.824051 loss=1.619868 Epoch[041] Batch [0049]/[3760] Speed: 49.114910 samples/sec accuracy=71.906250 loss=1.112917 lr=0.001000 Epoch[041] Batch [0099]/[3760] Speed: 71.099627 samples/sec accuracy=71.968750 loss=1.130754 lr=0.001000 Epoch[041] Batch [0149]/[3760] Speed: 71.234714 samples/sec accuracy=71.989583 loss=1.137404 lr=0.001000 Epoch[041] Batch [0199]/[3760] Speed: 71.896466 samples/sec accuracy=71.937500 loss=1.140853 lr=0.001000 Epoch[041] Batch [0249]/[3760] Speed: 71.728577 samples/sec accuracy=71.943750 loss=1.141507 lr=0.001000 Epoch[041] Batch [0299]/[3760] 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accuracy=71.803819 loss=1.129217 lr=0.001000 Epoch[041] Batch [3649]/[3760] Speed: 71.861194 samples/sec accuracy=71.810788 loss=1.128739 lr=0.001000 Epoch[041] Batch [3699]/[3760] Speed: 71.509173 samples/sec accuracy=71.820946 loss=1.128165 lr=0.001000 Epoch[041] Batch [3749]/[3760] Speed: 79.535444 samples/sec accuracy=71.828750 loss=1.127657 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.750000 acc-top5=87.250000 Batch [0099]/[0303]: acc-top1=66.609375 acc-top5=86.937500 Batch [0149]/[0303]: acc-top1=66.166667 acc-top5=86.197917 Batch [0199]/[0303]: acc-top1=65.890625 acc-top5=86.109375 Batch [0249]/[0303]: acc-top1=65.818750 acc-top5=86.000000 Batch [0299]/[0303]: acc-top1=65.838542 acc-top5=86.078125 [Epoch 041] training: accuracy=71.821809 loss=1.127690 [Epoch 041] speed: 71 samples/sec time cost: 3651.051356 [Epoch 041] validation: acc-top1=65.857054 acc-top5=86.117987 loss=1.600478 Epoch[042] Batch [0049]/[3760] Speed: 48.830102 samples/sec accuracy=73.343750 loss=1.073749 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acc-top1=66.289062 acc-top5=86.375000 Batch [0249]/[0303]: acc-top1=66.168750 acc-top5=86.287500 Batch [0299]/[0303]: acc-top1=66.390625 acc-top5=86.317708 [Epoch 042] training: accuracy=72.501662 loss=1.095578 [Epoch 042] speed: 71 samples/sec time cost: 3653.622038 [Epoch 042] validation: acc-top1=66.408828 acc-top5=86.350041 loss=1.587181 Epoch[043] Batch [0049]/[3759] Speed: 48.595936 samples/sec accuracy=72.531250 loss=1.091715 lr=0.001000 Epoch[043] Batch [0099]/[3759] Speed: 71.506052 samples/sec accuracy=73.093750 loss=1.075857 lr=0.001000 Epoch[043] Batch [0149]/[3759] Speed: 72.334330 samples/sec accuracy=73.500000 loss=1.068078 lr=0.001000 Epoch[043] Batch [0199]/[3759] Speed: 71.625361 samples/sec accuracy=73.328125 loss=1.067031 lr=0.001000 Epoch[043] Batch [0249]/[3759] Speed: 71.817208 samples/sec accuracy=73.312500 loss=1.065508 lr=0.001000 Epoch[043] Batch [0299]/[3759] Speed: 71.110407 samples/sec accuracy=73.005208 loss=1.072231 lr=0.001000 Epoch[043] Batch 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accuracy=73.041524 loss=1.070678 lr=0.001000 Epoch[043] Batch [3699]/[3759] Speed: 71.248072 samples/sec accuracy=73.055743 loss=1.069879 lr=0.001000 Epoch[043] Batch [3749]/[3759] Speed: 81.362625 samples/sec accuracy=73.046250 loss=1.070371 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.062500 acc-top5=87.250000 Batch [0099]/[0303]: acc-top1=67.250000 acc-top5=87.281250 Batch [0149]/[0303]: acc-top1=66.906250 acc-top5=86.625000 Batch [0199]/[0303]: acc-top1=66.562500 acc-top5=86.500000 Batch [0249]/[0303]: acc-top1=66.506250 acc-top5=86.450000 Batch [0299]/[0303]: acc-top1=66.588542 acc-top5=86.442708 [Epoch 043] training: accuracy=73.050096 loss=1.070134 [Epoch 043] speed: 71 samples/sec time cost: 3646.653627 [Epoch 043] validation: acc-top1=66.625413 acc-top5=86.473804 loss=1.578362 Epoch[044] Batch [0049]/[3760] Speed: 48.649029 samples/sec accuracy=73.718750 loss=1.075571 lr=0.001000 Epoch[044] Batch [0099]/[3760] Speed: 70.658567 samples/sec accuracy=73.609375 loss=1.068183 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[0299]/[0303]: acc-top1=66.697917 acc-top5=86.312500 [Epoch 044] training: accuracy=73.500665 loss=1.053214 [Epoch 044] speed: 71 samples/sec time cost: 3653.046837 [Epoch 044] validation: acc-top1=66.728548 acc-top5=86.350041 loss=1.569667 Epoch[045] Batch [0049]/[3760] Speed: 48.922257 samples/sec accuracy=72.875000 loss=1.080527 lr=0.001000 Epoch[045] Batch [0099]/[3760] Speed: 71.849128 samples/sec accuracy=74.500000 loss=1.043727 lr=0.001000 Epoch[045] Batch [0149]/[3760] Speed: 71.605652 samples/sec accuracy=74.354167 loss=1.038937 lr=0.001000 Epoch[045] Batch [0199]/[3760] Speed: 71.200584 samples/sec accuracy=74.171875 loss=1.038063 lr=0.001000 Epoch[045] Batch [0249]/[3760] Speed: 71.288839 samples/sec accuracy=74.343750 loss=1.030524 lr=0.001000 Epoch[045] Batch [0299]/[3760] Speed: 71.996382 samples/sec accuracy=74.578125 loss=1.022314 lr=0.001000 Epoch[045] Batch [0349]/[3760] Speed: 71.412577 samples/sec accuracy=74.379464 loss=1.031382 lr=0.001000 Epoch[045] Batch 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accuracy=73.806250 loss=1.039368 lr=0.001000 Epoch[045] Batch [2799]/[3760] Speed: 71.424512 samples/sec accuracy=73.789062 loss=1.040012 lr=0.001000 Epoch[045] Batch [2849]/[3760] Speed: 71.354338 samples/sec accuracy=73.799342 loss=1.039685 lr=0.001000 Epoch[045] Batch [2899]/[3760] Speed: 71.466654 samples/sec accuracy=73.791487 loss=1.039496 lr=0.001000 Epoch[045] Batch [2949]/[3760] Speed: 71.584633 samples/sec accuracy=73.788136 loss=1.039525 lr=0.001000 Epoch[045] Batch [2999]/[3760] Speed: 71.471710 samples/sec accuracy=73.797917 loss=1.039334 lr=0.001000 Epoch[045] Batch [3049]/[3760] Speed: 71.740850 samples/sec accuracy=73.814037 loss=1.038613 lr=0.001000 Epoch[045] Batch [3099]/[3760] Speed: 71.424912 samples/sec accuracy=73.815020 loss=1.038252 lr=0.001000 Epoch[045] Batch [3149]/[3760] Speed: 71.422175 samples/sec accuracy=73.811508 loss=1.038753 lr=0.001000 Epoch[045] Batch [3199]/[3760] Speed: 71.902123 samples/sec accuracy=73.834961 loss=1.037750 lr=0.001000 Epoch[045] 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accuracy=73.807010 loss=1.039498 lr=0.001000 Epoch[045] Batch [3749]/[3760] Speed: 80.098795 samples/sec accuracy=73.805833 loss=1.039543 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.843750 acc-top5=87.406250 Batch [0099]/[0303]: acc-top1=68.093750 acc-top5=87.234375 Batch [0149]/[0303]: acc-top1=67.447917 acc-top5=86.489583 Batch [0199]/[0303]: acc-top1=66.960938 acc-top5=86.484375 Batch [0249]/[0303]: acc-top1=66.925000 acc-top5=86.487500 Batch [0299]/[0303]: acc-top1=67.005208 acc-top5=86.557292 [Epoch 045] training: accuracy=73.808594 loss=1.039560 [Epoch 045] speed: 71 samples/sec time cost: 3654.323419 [Epoch 045] validation: acc-top1=67.027640 acc-top5=86.597566 loss=1.542240 Epoch[046] Batch [0049]/[3759] Speed: 49.475892 samples/sec accuracy=74.125000 loss=1.027287 lr=0.001000 Epoch[046] Batch [0099]/[3759] Speed: 70.928384 samples/sec accuracy=74.375000 loss=1.016591 lr=0.001000 Epoch[046] Batch [0149]/[3759] Speed: 71.351117 samples/sec accuracy=74.718750 loss=1.003684 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71.441209 samples/sec accuracy=74.141071 loss=1.025756 lr=0.001000 Epoch[046] Batch [3549]/[3759] Speed: 71.654397 samples/sec accuracy=74.148768 loss=1.025618 lr=0.001000 Epoch[046] Batch [3599]/[3759] Speed: 71.456749 samples/sec accuracy=74.147569 loss=1.025807 lr=0.001000 Epoch[046] Batch [3649]/[3759] Speed: 72.254215 samples/sec accuracy=74.154110 loss=1.025579 lr=0.001000 Epoch[046] Batch [3699]/[3759] Speed: 71.085927 samples/sec accuracy=74.154561 loss=1.025713 lr=0.001000 Epoch[046] Batch [3749]/[3759] Speed: 80.627179 samples/sec accuracy=74.151667 loss=1.025987 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.218750 acc-top5=87.593750 Batch [0099]/[0303]: acc-top1=67.984375 acc-top5=87.296875 Batch [0149]/[0303]: acc-top1=67.083333 acc-top5=86.447917 Batch [0199]/[0303]: acc-top1=66.781250 acc-top5=86.492188 Batch [0249]/[0303]: acc-top1=66.712500 acc-top5=86.487500 Batch [0299]/[0303]: acc-top1=66.687500 acc-top5=86.442708 [Epoch 046] training: accuracy=74.152451 loss=1.025955 [Epoch 046] speed: 71 samples/sec time cost: 3650.388239 [Epoch 046] validation: acc-top1=66.687294 acc-top5=86.489274 loss=1.564963 Epoch[047] Batch [0049]/[3760] Speed: 48.368847 samples/sec accuracy=75.187500 loss=0.970559 lr=0.001000 Epoch[047] Batch [0099]/[3760] Speed: 71.242612 samples/sec accuracy=74.546875 loss=1.008023 lr=0.001000 Epoch[047] Batch [0149]/[3760] Speed: 71.488387 samples/sec accuracy=74.645833 loss=0.998240 lr=0.001000 Epoch[047] Batch [0199]/[3760] Speed: 71.211065 samples/sec accuracy=74.179688 loss=1.013067 lr=0.001000 Epoch[047] Batch [0249]/[3760] Speed: 71.640613 samples/sec accuracy=74.412500 loss=1.011185 lr=0.001000 Epoch[047] Batch [0299]/[3760] Speed: 71.335028 samples/sec accuracy=74.255208 loss=1.016549 lr=0.001000 Epoch[047] Batch [0349]/[3760] Speed: 72.279556 samples/sec accuracy=74.276786 loss=1.015941 lr=0.001000 Epoch[047] Batch [0399]/[3760] Speed: 71.382631 samples/sec accuracy=74.308594 loss=1.011910 lr=0.001000 Epoch[047] Batch 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accuracy=74.256944 loss=1.010354 lr=0.001000 Epoch[047] Batch [0949]/[3760] Speed: 71.236446 samples/sec accuracy=74.192434 loss=1.011349 lr=0.001000 Epoch[047] Batch [0999]/[3760] Speed: 71.538414 samples/sec accuracy=74.231250 loss=1.011768 lr=0.001000 Epoch[047] Batch [1049]/[3760] Speed: 71.821379 samples/sec accuracy=74.184524 loss=1.013074 lr=0.001000 Epoch[047] Batch [1099]/[3760] Speed: 71.990493 samples/sec accuracy=74.238636 loss=1.012094 lr=0.001000 Epoch[047] Batch [1149]/[3760] Speed: 71.469271 samples/sec accuracy=74.201087 loss=1.014275 lr=0.001000 Epoch[047] Batch [1199]/[3760] Speed: 71.338196 samples/sec accuracy=74.200521 loss=1.015129 lr=0.001000 Epoch[047] Batch [1249]/[3760] Speed: 71.583707 samples/sec accuracy=74.241250 loss=1.014057 lr=0.001000 Epoch[047] Batch [1299]/[3760] Speed: 72.186071 samples/sec accuracy=74.316106 loss=1.012566 lr=0.001000 Epoch[047] Batch [1349]/[3760] Speed: 71.793447 samples/sec accuracy=74.327546 loss=1.012135 lr=0.001000 Epoch[047] 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accuracy=74.281250 loss=1.015973 lr=0.001000 Epoch[047] Batch [1899]/[3760] Speed: 70.969290 samples/sec accuracy=74.282895 loss=1.015171 lr=0.001000 Epoch[047] Batch [1949]/[3760] Speed: 71.336517 samples/sec accuracy=74.290865 loss=1.014900 lr=0.001000 Epoch[047] Batch [1999]/[3760] Speed: 72.141795 samples/sec accuracy=74.282031 loss=1.014643 lr=0.001000 Epoch[047] Batch [2049]/[3760] Speed: 71.297163 samples/sec accuracy=74.297256 loss=1.013855 lr=0.001000 Epoch[047] Batch [2099]/[3760] Speed: 71.422409 samples/sec accuracy=74.270089 loss=1.015374 lr=0.001000 Epoch[047] Batch [2149]/[3760] Speed: 71.829550 samples/sec accuracy=74.254360 loss=1.016300 lr=0.001000 Epoch[047] Batch [2199]/[3760] Speed: 72.139240 samples/sec accuracy=74.262074 loss=1.015726 lr=0.001000 Epoch[047] Batch [2249]/[3760] Speed: 71.495765 samples/sec accuracy=74.281944 loss=1.015379 lr=0.001000 Epoch[047] Batch [2299]/[3760] Speed: 71.865382 samples/sec accuracy=74.269701 loss=1.015650 lr=0.001000 Epoch[047] 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accuracy=74.255580 loss=1.016778 lr=0.001000 Epoch[047] Batch [2849]/[3760] Speed: 71.779012 samples/sec accuracy=74.262061 loss=1.016005 lr=0.001000 Epoch[047] Batch [2899]/[3760] Speed: 71.578829 samples/sec accuracy=74.257004 loss=1.016331 lr=0.001000 Epoch[047] Batch [2949]/[3760] Speed: 72.418355 samples/sec accuracy=74.279661 loss=1.016229 lr=0.001000 Epoch[047] Batch [2999]/[3760] Speed: 71.199145 samples/sec accuracy=74.307812 loss=1.015659 lr=0.001000 Epoch[047] Batch [3049]/[3760] Speed: 71.590076 samples/sec accuracy=74.309939 loss=1.015601 lr=0.001000 Epoch[047] Batch [3099]/[3760] Speed: 71.963391 samples/sec accuracy=74.294355 loss=1.015685 lr=0.001000 Epoch[047] Batch [3149]/[3760] Speed: 71.723336 samples/sec accuracy=74.274802 loss=1.016334 lr=0.001000 Epoch[047] Batch [3199]/[3760] Speed: 71.640085 samples/sec accuracy=74.282227 loss=1.016240 lr=0.001000 Epoch[047] Batch [3249]/[3760] Speed: 70.276620 samples/sec accuracy=74.268269 loss=1.016929 lr=0.001000 Epoch[047] Batch [3299]/[3760] Speed: 72.676711 samples/sec accuracy=74.276515 loss=1.016447 lr=0.001000 Epoch[047] Batch [3349]/[3760] Speed: 71.829456 samples/sec accuracy=74.269590 loss=1.016874 lr=0.001000 Epoch[047] Batch [3399]/[3760] Speed: 71.245027 samples/sec accuracy=74.287684 loss=1.016234 lr=0.001000 Epoch[047] Batch [3449]/[3760] Speed: 71.410616 samples/sec accuracy=74.269928 loss=1.016495 lr=0.001000 Epoch[047] Batch [3499]/[3760] Speed: 72.610902 samples/sec accuracy=74.282589 loss=1.016380 lr=0.001000 Epoch[047] Batch [3549]/[3760] Speed: 71.630657 samples/sec accuracy=74.286972 loss=1.016000 lr=0.001000 Epoch[047] Batch [3599]/[3760] Speed: 71.529653 samples/sec accuracy=74.271701 loss=1.016495 lr=0.001000 Epoch[047] Batch [3649]/[3760] Speed: 71.794948 samples/sec accuracy=74.288099 loss=1.015886 lr=0.001000 Epoch[047] Batch [3699]/[3760] Speed: 70.685970 samples/sec accuracy=74.298986 loss=1.015317 lr=0.001000 Epoch[047] Batch [3749]/[3760] Speed: 79.644798 samples/sec accuracy=74.314167 loss=1.014761 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.406250 acc-top5=87.593750 Batch [0099]/[0303]: acc-top1=67.640625 acc-top5=87.281250 Batch [0149]/[0303]: acc-top1=66.927083 acc-top5=86.458333 Batch [0199]/[0303]: acc-top1=66.796875 acc-top5=86.492188 Batch [0249]/[0303]: acc-top1=66.581250 acc-top5=86.462500 Batch [0299]/[0303]: acc-top1=66.656250 acc-top5=86.458333 [Epoch 047] training: accuracy=74.316822 loss=1.014611 [Epoch 047] speed: 71 samples/sec time cost: 3652.767882 [Epoch 047] validation: acc-top1=66.687294 acc-top5=86.494431 loss=1.566332 Epoch[048] Batch [0049]/[3760] Speed: 48.459252 samples/sec accuracy=75.625000 loss=0.938996 lr=0.001000 Epoch[048] Batch [0099]/[3760] Speed: 71.203735 samples/sec accuracy=74.609375 loss=0.978699 lr=0.001000 Epoch[048] Batch [0149]/[3760] Speed: 71.241928 samples/sec accuracy=74.614583 loss=0.991839 lr=0.001000 Epoch[048] Batch [0199]/[3760] Speed: 71.359602 samples/sec accuracy=74.984375 loss=0.980309 lr=0.001000 Epoch[048] Batch [0249]/[3760] Speed: 72.092574 samples/sec accuracy=75.037500 loss=0.980609 lr=0.001000 Epoch[048] Batch [0299]/[3760] Speed: 71.356416 samples/sec accuracy=74.984375 loss=0.985941 lr=0.001000 Epoch[048] Batch [0349]/[3760] Speed: 71.678308 samples/sec accuracy=74.843750 loss=0.995287 lr=0.001000 Epoch[048] Batch [0399]/[3760] Speed: 71.826390 samples/sec accuracy=74.890625 loss=0.993348 lr=0.001000 Epoch[048] Batch [0449]/[3760] Speed: 71.945655 samples/sec accuracy=74.718750 loss=0.994687 lr=0.001000 Epoch[048] Batch [0499]/[3760] Speed: 71.333611 samples/sec accuracy=74.721875 loss=0.994730 lr=0.001000 Epoch[048] Batch [0549]/[3760] Speed: 70.829939 samples/sec accuracy=74.661932 loss=0.995591 lr=0.001000 Epoch[048] Batch [0599]/[3760] Speed: 71.867635 samples/sec accuracy=74.585938 loss=0.999380 lr=0.001000 Epoch[048] Batch [0649]/[3760] Speed: 71.586836 samples/sec accuracy=74.687500 loss=0.997418 lr=0.001000 Epoch[048] Batch [0699]/[3760] Speed: 72.117972 samples/sec accuracy=74.685268 loss=0.995995 lr=0.001000 Epoch[048] Batch [0749]/[3760] Speed: 71.581315 samples/sec accuracy=74.731250 loss=0.994369 lr=0.001000 Epoch[048] Batch [0799]/[3760] Speed: 71.531906 samples/sec accuracy=74.638672 loss=0.995200 lr=0.001000 Epoch[048] Batch [0849]/[3760] Speed: 71.296474 samples/sec accuracy=74.582721 loss=0.996900 lr=0.001000 Epoch[048] Batch [0899]/[3760] Speed: 71.692066 samples/sec accuracy=74.625000 loss=0.996040 lr=0.001000 Epoch[048] Batch [0949]/[3760] Speed: 72.009219 samples/sec accuracy=74.646382 loss=0.995357 lr=0.001000 Epoch[048] Batch [0999]/[3760] Speed: 71.710477 samples/sec accuracy=74.631250 loss=0.996301 lr=0.001000 Epoch[048] Batch [1049]/[3760] Speed: 72.023188 samples/sec accuracy=74.629464 loss=0.996135 lr=0.001000 Epoch[048] Batch [1099]/[3760] Speed: 71.262250 samples/sec accuracy=74.627841 loss=0.996666 lr=0.001000 Epoch[048] Batch [1149]/[3760] Speed: 71.884673 samples/sec accuracy=74.622283 loss=0.996481 lr=0.001000 Epoch[048] Batch [1199]/[3760] Speed: 72.195465 samples/sec accuracy=74.592448 loss=0.998222 lr=0.001000 Epoch[048] Batch [1249]/[3760] Speed: 71.691255 samples/sec accuracy=74.582500 loss=0.998384 lr=0.001000 Epoch[048] Batch [1299]/[3760] Speed: 71.585421 samples/sec accuracy=74.555288 loss=0.999894 lr=0.001000 Epoch[048] Batch [1349]/[3760] Speed: 71.074579 samples/sec accuracy=74.543981 loss=1.000350 lr=0.001000 Epoch[048] Batch [1399]/[3760] Speed: 71.694954 samples/sec accuracy=74.563616 loss=1.001934 lr=0.001000 Epoch[048] Batch [1449]/[3760] Speed: 71.725580 samples/sec accuracy=74.574353 loss=1.002360 lr=0.001000 Epoch[048] Batch [1499]/[3760] Speed: 71.683595 samples/sec accuracy=74.579167 loss=1.001431 lr=0.001000 Epoch[048] Batch [1549]/[3760] Speed: 71.118805 samples/sec accuracy=74.609879 loss=1.000603 lr=0.001000 Epoch[048] Batch [1599]/[3760] Speed: 71.192688 samples/sec accuracy=74.612305 loss=0.999708 lr=0.001000 Epoch[048] Batch [1649]/[3760] Speed: 72.132678 samples/sec accuracy=74.628788 loss=0.999088 lr=0.001000 Epoch[048] Batch [1699]/[3760] Speed: 71.045255 samples/sec accuracy=74.648897 loss=0.998478 lr=0.001000 Epoch[048] Batch [1749]/[3760] Speed: 72.004273 samples/sec accuracy=74.639286 loss=0.998183 lr=0.001000 Epoch[048] Batch [1799]/[3760] Speed: 71.042509 samples/sec accuracy=74.637153 loss=0.999196 lr=0.001000 Epoch[048] Batch [1849]/[3760] Speed: 71.342538 samples/sec accuracy=74.652027 loss=0.999457 lr=0.001000 Epoch[048] Batch [1899]/[3760] Speed: 71.706637 samples/sec accuracy=74.633224 loss=0.999723 lr=0.001000 Epoch[048] Batch [1949]/[3760] Speed: 71.668525 samples/sec accuracy=74.653045 loss=0.999757 lr=0.001000 Epoch[048] Batch [1999]/[3760] Speed: 72.545563 samples/sec accuracy=74.671875 loss=0.999318 lr=0.001000 Epoch[048] Batch [2049]/[3760] Speed: 71.365338 samples/sec accuracy=74.703506 loss=0.998408 lr=0.001000 Epoch[048] Batch [2099]/[3760] Speed: 72.302114 samples/sec accuracy=74.681548 loss=0.999757 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71.488346 samples/sec accuracy=74.697183 loss=0.999753 lr=0.001000 Epoch[048] Batch [3599]/[3760] Speed: 71.708096 samples/sec accuracy=74.699219 loss=0.999697 lr=0.001000 Epoch[048] Batch [3649]/[3760] Speed: 71.288525 samples/sec accuracy=74.685788 loss=1.000371 lr=0.001000 Epoch[048] Batch [3699]/[3760] Speed: 71.527935 samples/sec accuracy=74.680321 loss=1.000540 lr=0.001000 Epoch[048] Batch [3749]/[3760] Speed: 80.186066 samples/sec accuracy=74.697917 loss=1.000017 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.593750 acc-top5=87.437500 Batch [0099]/[0303]: acc-top1=68.078125 acc-top5=87.296875 Batch [0149]/[0303]: acc-top1=67.500000 acc-top5=86.614583 Batch [0199]/[0303]: acc-top1=67.187500 acc-top5=86.632812 Batch [0249]/[0303]: acc-top1=67.068750 acc-top5=86.543750 Batch [0299]/[0303]: acc-top1=67.088542 acc-top5=86.546875 [Epoch 048] training: accuracy=74.702045 loss=0.999674 [Epoch 048] speed: 71 samples/sec time cost: 3654.510993 [Epoch 048] validation: acc-top1=67.104992 acc-top5=86.582096 loss=1.568425 Epoch[049] Batch [0049]/[3759] Speed: 48.748261 samples/sec accuracy=75.500000 loss=0.974708 lr=0.001000 Epoch[049] Batch [0099]/[3759] Speed: 70.374274 samples/sec accuracy=75.515625 loss=0.969556 lr=0.001000 Epoch[049] Batch [0149]/[3759] Speed: 71.740614 samples/sec accuracy=75.281250 loss=0.981495 lr=0.001000 Epoch[049] Batch [0199]/[3759] Speed: 71.003915 samples/sec accuracy=75.187500 loss=0.980184 lr=0.001000 Epoch[049] Batch [0249]/[3759] Speed: 71.730159 samples/sec accuracy=75.387500 loss=0.976220 lr=0.001000 Epoch[049] Batch [0299]/[3759] Speed: 71.591426 samples/sec accuracy=75.453125 loss=0.974667 lr=0.001000 Epoch[049] Batch [0349]/[3759] Speed: 71.499245 samples/sec accuracy=75.071429 loss=0.986544 lr=0.001000 Epoch[049] Batch [0399]/[3759] Speed: 71.400759 samples/sec accuracy=74.949219 loss=0.991204 lr=0.001000 Epoch[049] Batch [0449]/[3759] Speed: 71.860245 samples/sec accuracy=74.840278 loss=0.994080 lr=0.001000 Epoch[049] Batch 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accuracy=74.981908 loss=0.985778 lr=0.001000 Epoch[049] Batch [0999]/[3759] Speed: 71.514385 samples/sec accuracy=75.009375 loss=0.985261 lr=0.001000 Epoch[049] Batch [1049]/[3759] Speed: 71.424759 samples/sec accuracy=74.958333 loss=0.986907 lr=0.001000 Epoch[049] Batch [1099]/[3759] Speed: 71.837190 samples/sec accuracy=74.936080 loss=0.988173 lr=0.001000 Epoch[049] Batch [1149]/[3759] Speed: 71.445457 samples/sec accuracy=74.938859 loss=0.987929 lr=0.001000 Epoch[049] Batch [1199]/[3759] Speed: 71.921863 samples/sec accuracy=74.980469 loss=0.987108 lr=0.001000 Epoch[049] Batch [1249]/[3759] Speed: 71.705164 samples/sec accuracy=74.991250 loss=0.987380 lr=0.001000 Epoch[049] Batch [1299]/[3759] Speed: 70.569801 samples/sec accuracy=74.991587 loss=0.987660 lr=0.001000 Epoch[049] Batch [1349]/[3759] Speed: 72.132767 samples/sec accuracy=75.032407 loss=0.987080 lr=0.001000 Epoch[049] Batch [1399]/[3759] Speed: 71.258842 samples/sec accuracy=74.992188 loss=0.988169 lr=0.001000 Epoch[049] 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accuracy=74.943257 loss=0.990005 lr=0.001000 Epoch[049] Batch [1949]/[3759] Speed: 71.460569 samples/sec accuracy=74.968750 loss=0.988881 lr=0.001000 Epoch[049] Batch [1999]/[3759] Speed: 71.517041 samples/sec accuracy=74.953125 loss=0.989747 lr=0.001000 Epoch[049] Batch [2049]/[3759] Speed: 72.046295 samples/sec accuracy=74.954268 loss=0.990077 lr=0.001000 Epoch[049] Batch [2099]/[3759] Speed: 71.408228 samples/sec accuracy=74.951637 loss=0.990482 lr=0.001000 Epoch[049] Batch [2149]/[3759] Speed: 71.181657 samples/sec accuracy=74.949128 loss=0.990777 lr=0.001000 Epoch[049] Batch [2199]/[3759] Speed: 71.589840 samples/sec accuracy=74.950284 loss=0.990538 lr=0.001000 Epoch[049] Batch [2249]/[3759] Speed: 70.989359 samples/sec accuracy=74.971528 loss=0.990100 lr=0.001000 Epoch[049] Batch [2299]/[3759] Speed: 72.159351 samples/sec accuracy=74.972147 loss=0.989991 lr=0.001000 Epoch[049] Batch [2349]/[3759] Speed: 71.547319 samples/sec accuracy=74.961436 loss=0.990589 lr=0.001000 Epoch[049] 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accuracy=74.921053 loss=0.990896 lr=0.001000 Epoch[049] Batch [2899]/[3759] Speed: 71.634319 samples/sec accuracy=74.914871 loss=0.991063 lr=0.001000 Epoch[049] Batch [2949]/[3759] Speed: 71.264072 samples/sec accuracy=74.929555 loss=0.990364 lr=0.001000 Epoch[049] Batch [2999]/[3759] Speed: 71.367772 samples/sec accuracy=74.956771 loss=0.989556 lr=0.001000 Epoch[049] Batch [3049]/[3759] Speed: 71.891537 samples/sec accuracy=74.958504 loss=0.990020 lr=0.001000 Epoch[049] Batch [3099]/[3759] Speed: 72.147922 samples/sec accuracy=74.957661 loss=0.990238 lr=0.001000 Epoch[049] Batch [3149]/[3759] Speed: 71.868488 samples/sec accuracy=74.963790 loss=0.990207 lr=0.001000 Epoch[049] Batch [3199]/[3759] Speed: 71.056548 samples/sec accuracy=74.972168 loss=0.990037 lr=0.001000 Epoch[049] Batch [3249]/[3759] Speed: 72.375892 samples/sec accuracy=74.975000 loss=0.989631 lr=0.001000 Epoch[049] Batch [3299]/[3759] Speed: 71.626146 samples/sec accuracy=74.979167 loss=0.989970 lr=0.001000 Epoch[049] Batch [3349]/[3759] Speed: 71.286827 samples/sec accuracy=74.971549 loss=0.990360 lr=0.001000 Epoch[049] Batch [3399]/[3759] Speed: 71.648816 samples/sec accuracy=74.971048 loss=0.990516 lr=0.001000 Epoch[049] Batch [3449]/[3759] Speed: 71.472994 samples/sec accuracy=74.971467 loss=0.990146 lr=0.001000 Epoch[049] Batch [3499]/[3759] Speed: 71.569092 samples/sec accuracy=74.942411 loss=0.991173 lr=0.001000 Epoch[049] Batch [3549]/[3759] Speed: 71.717015 samples/sec accuracy=74.951585 loss=0.991168 lr=0.001000 Epoch[049] Batch [3599]/[3759] Speed: 71.842396 samples/sec accuracy=74.945747 loss=0.991333 lr=0.001000 Epoch[049] Batch [3649]/[3759] Speed: 71.775585 samples/sec accuracy=74.956764 loss=0.990969 lr=0.001000 Epoch[049] Batch [3699]/[3759] Speed: 71.574938 samples/sec accuracy=74.950169 loss=0.991002 lr=0.001000 Epoch[049] Batch [3749]/[3759] Speed: 80.689602 samples/sec accuracy=74.952500 loss=0.990953 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.937500 acc-top5=87.750000 Batch [0099]/[0303]: acc-top1=67.750000 acc-top5=87.421875 Batch [0149]/[0303]: acc-top1=67.302083 acc-top5=86.697917 Batch [0199]/[0303]: acc-top1=67.046875 acc-top5=86.593750 Batch [0249]/[0303]: acc-top1=66.912500 acc-top5=86.612500 Batch [0299]/[0303]: acc-top1=66.968750 acc-top5=86.578125 [Epoch 049] training: accuracy=74.955523 loss=0.990793 [Epoch 049] speed: 71 samples/sec time cost: 3652.011536 [Epoch 049] validation: acc-top1=66.981229 acc-top5=86.602723 loss=1.565072 Epoch[050] Batch [0049]/[3760] Speed: 48.646706 samples/sec accuracy=76.437500 loss=0.972815 lr=0.001000 Epoch[050] Batch [0099]/[3760] Speed: 70.882779 samples/sec accuracy=76.578125 loss=0.950192 lr=0.001000 Epoch[050] Batch [0149]/[3760] Speed: 71.785462 samples/sec accuracy=75.958333 loss=0.962284 lr=0.001000 Epoch[050] Batch [0199]/[3760] Speed: 71.088104 samples/sec accuracy=75.992188 loss=0.959705 lr=0.001000 Epoch[050] Batch [0249]/[3760] Speed: 72.263416 samples/sec accuracy=75.950000 loss=0.961561 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71.910573 samples/sec accuracy=75.335938 loss=0.979058 lr=0.001000 Epoch[050] Batch [3649]/[3760] Speed: 71.201040 samples/sec accuracy=75.334332 loss=0.979101 lr=0.001000 Epoch[050] Batch [3699]/[3760] Speed: 71.402156 samples/sec accuracy=75.322213 loss=0.979553 lr=0.001000 Epoch[050] Batch [3749]/[3760] Speed: 80.025635 samples/sec accuracy=75.305000 loss=0.980331 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.281250 acc-top5=87.750000 Batch [0099]/[0303]: acc-top1=67.734375 acc-top5=87.421875 Batch [0149]/[0303]: acc-top1=67.104167 acc-top5=86.604167 Batch [0199]/[0303]: acc-top1=66.773438 acc-top5=86.570312 Batch [0249]/[0303]: acc-top1=66.687500 acc-top5=86.631250 Batch [0299]/[0303]: acc-top1=66.796875 acc-top5=86.697917 [Epoch 050] training: accuracy=75.297955 loss=0.980607 [Epoch 050] speed: 71 samples/sec time cost: 3649.912805 [Epoch 050] validation: acc-top1=66.821370 acc-top5=86.747112 loss=1.553895 Epoch[051] Batch [0049]/[3760] Speed: 48.726562 samples/sec accuracy=76.718750 loss=0.965425 lr=0.001000 Epoch[051] Batch [0099]/[3760] Speed: 70.914292 samples/sec accuracy=76.140625 loss=0.958515 lr=0.001000 Epoch[051] Batch [0149]/[3760] Speed: 71.482037 samples/sec accuracy=75.885417 loss=0.953454 lr=0.001000 Epoch[051] Batch [0199]/[3760] Speed: 71.436776 samples/sec accuracy=75.968750 loss=0.949573 lr=0.001000 Epoch[051] Batch [0249]/[3760] Speed: 71.919909 samples/sec accuracy=75.812500 loss=0.954566 lr=0.001000 Epoch[051] Batch [0299]/[3760] Speed: 71.439340 samples/sec accuracy=75.687500 loss=0.958976 lr=0.001000 Epoch[051] Batch [0349]/[3760] Speed: 72.064420 samples/sec accuracy=75.705357 loss=0.955386 lr=0.001000 Epoch[051] Batch [0399]/[3760] Speed: 71.486476 samples/sec accuracy=75.781250 loss=0.954764 lr=0.001000 Epoch[051] Batch [0449]/[3760] Speed: 71.658371 samples/sec accuracy=75.722222 loss=0.957617 lr=0.001000 Epoch[051] Batch [0499]/[3760] Speed: 71.275461 samples/sec accuracy=75.759375 loss=0.957011 lr=0.001000 Epoch[051] 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accuracy=75.815625 loss=0.955836 lr=0.001000 Epoch[051] Batch [1049]/[3760] Speed: 72.290409 samples/sec accuracy=75.800595 loss=0.954784 lr=0.001000 Epoch[051] Batch [1099]/[3760] Speed: 71.577630 samples/sec accuracy=75.772727 loss=0.955539 lr=0.001000 Epoch[051] Batch [1149]/[3760] Speed: 71.586732 samples/sec accuracy=75.771739 loss=0.955079 lr=0.001000 Epoch[051] Batch [1199]/[3760] Speed: 71.317305 samples/sec accuracy=75.766927 loss=0.954519 lr=0.001000 Epoch[051] Batch [1249]/[3760] Speed: 71.560214 samples/sec accuracy=75.758750 loss=0.955060 lr=0.001000 Epoch[051] Batch [1299]/[3760] Speed: 71.586072 samples/sec accuracy=75.721154 loss=0.955499 lr=0.001000 Epoch[051] Batch [1349]/[3760] Speed: 71.694520 samples/sec accuracy=75.740741 loss=0.955572 lr=0.001000 Epoch[051] Batch [1399]/[3760] Speed: 70.962821 samples/sec accuracy=75.746652 loss=0.956927 lr=0.001000 Epoch[051] Batch [1449]/[3760] Speed: 71.626134 samples/sec accuracy=75.746767 loss=0.956747 lr=0.001000 Epoch[051] 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accuracy=75.679487 loss=0.961750 lr=0.001000 Epoch[051] Batch [1999]/[3760] Speed: 71.815675 samples/sec accuracy=75.662500 loss=0.962398 lr=0.001000 Epoch[051] Batch [2049]/[3760] Speed: 71.268744 samples/sec accuracy=75.630335 loss=0.963094 lr=0.001000 Epoch[051] Batch [2099]/[3760] Speed: 71.956059 samples/sec accuracy=75.627976 loss=0.962239 lr=0.001000 Epoch[051] Batch [2149]/[3760] Speed: 71.186690 samples/sec accuracy=75.617733 loss=0.963309 lr=0.001000 Epoch[051] Batch [2199]/[3760] Speed: 71.330737 samples/sec accuracy=75.619318 loss=0.963214 lr=0.001000 Epoch[051] Batch [2249]/[3760] Speed: 71.772972 samples/sec accuracy=75.609722 loss=0.963352 lr=0.001000 Epoch[051] Batch [2299]/[3760] Speed: 71.717648 samples/sec accuracy=75.614810 loss=0.963238 lr=0.001000 Epoch[051] Batch [2349]/[3760] Speed: 71.684781 samples/sec accuracy=75.587101 loss=0.964423 lr=0.001000 Epoch[051] Batch [2399]/[3760] Speed: 71.308300 samples/sec accuracy=75.583984 loss=0.964850 lr=0.001000 Epoch[051] 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accuracy=75.526401 loss=0.966292 lr=0.001000 Epoch[051] Batch [2949]/[3760] Speed: 72.196000 samples/sec accuracy=75.520657 loss=0.966196 lr=0.001000 Epoch[051] Batch [2999]/[3760] Speed: 72.583104 samples/sec accuracy=75.514062 loss=0.966192 lr=0.001000 Epoch[051] Batch [3049]/[3760] Speed: 71.019782 samples/sec accuracy=75.528176 loss=0.966067 lr=0.001000 Epoch[051] Batch [3099]/[3760] Speed: 71.513150 samples/sec accuracy=75.515121 loss=0.966232 lr=0.001000 Epoch[051] Batch [3149]/[3760] Speed: 71.615696 samples/sec accuracy=75.511905 loss=0.966305 lr=0.001000 Epoch[051] Batch [3199]/[3760] Speed: 71.517543 samples/sec accuracy=75.539551 loss=0.965675 lr=0.001000 Epoch[051] Batch [3249]/[3760] Speed: 71.814507 samples/sec accuracy=75.533173 loss=0.966014 lr=0.001000 Epoch[051] Batch [3299]/[3760] Speed: 71.415250 samples/sec accuracy=75.532670 loss=0.966114 lr=0.001000 Epoch[051] Batch [3349]/[3760] Speed: 71.898690 samples/sec accuracy=75.540578 loss=0.965889 lr=0.001000 Epoch[051] Batch [3399]/[3760] Speed: 70.407306 samples/sec accuracy=75.524816 loss=0.966292 lr=0.001000 Epoch[051] Batch [3449]/[3760] Speed: 71.762458 samples/sec accuracy=75.528080 loss=0.966365 lr=0.001000 Epoch[051] Batch [3499]/[3760] Speed: 71.866379 samples/sec accuracy=75.542411 loss=0.965943 lr=0.001000 Epoch[051] Batch [3549]/[3760] Speed: 71.231311 samples/sec accuracy=75.536972 loss=0.966651 lr=0.001000 Epoch[051] Batch [3599]/[3760] Speed: 72.092237 samples/sec accuracy=75.538628 loss=0.967385 lr=0.001000 Epoch[051] Batch [3649]/[3760] Speed: 71.756652 samples/sec accuracy=75.534247 loss=0.967512 lr=0.001000 Epoch[051] Batch [3699]/[3760] Speed: 71.041545 samples/sec accuracy=75.539274 loss=0.967473 lr=0.001000 Epoch[051] Batch [3749]/[3760] Speed: 79.113895 samples/sec accuracy=75.556250 loss=0.966829 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.281250 acc-top5=87.468750 Batch [0099]/[0303]: acc-top1=67.906250 acc-top5=87.281250 Batch [0149]/[0303]: acc-top1=67.291667 acc-top5=86.500000 Batch [0199]/[0303]: acc-top1=66.984375 acc-top5=86.500000 Batch [0249]/[0303]: acc-top1=66.856250 acc-top5=86.437500 Batch [0299]/[0303]: acc-top1=66.937500 acc-top5=86.401042 [Epoch 051] training: accuracy=75.553939 loss=0.966952 [Epoch 051] speed: 71 samples/sec time cost: 3652.753710 [Epoch 051] validation: acc-top1=66.929662 acc-top5=86.448020 loss=1.582205 Epoch[052] Batch [0049]/[3759] Speed: 48.691948 samples/sec accuracy=76.000000 loss=0.966103 lr=0.001000 Epoch[052] Batch [0099]/[3759] Speed: 71.254472 samples/sec accuracy=76.062500 loss=0.943832 lr=0.001000 Epoch[052] Batch [0149]/[3759] Speed: 71.090087 samples/sec accuracy=75.958333 loss=0.943901 lr=0.001000 Epoch[052] Batch [0199]/[3759] Speed: 71.221063 samples/sec accuracy=76.351562 loss=0.937831 lr=0.001000 Epoch[052] Batch [0249]/[3759] Speed: 71.475984 samples/sec accuracy=76.381250 loss=0.942400 lr=0.001000 Epoch[052] Batch [0299]/[3759] Speed: 72.179826 samples/sec accuracy=76.250000 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accuracy=76.052500 loss=0.947115 lr=0.001000 Epoch[052] Batch [1299]/[3759] Speed: 72.182957 samples/sec accuracy=76.034856 loss=0.948383 lr=0.001000 Epoch[052] Batch [1349]/[3759] Speed: 71.960711 samples/sec accuracy=76.035880 loss=0.948524 lr=0.001000 Epoch[052] Batch [1399]/[3759] Speed: 71.595760 samples/sec accuracy=76.014509 loss=0.949069 lr=0.001000 Epoch[052] Batch [1449]/[3759] Speed: 72.223478 samples/sec accuracy=75.980603 loss=0.949983 lr=0.001000 Epoch[052] Batch [1499]/[3759] Speed: 72.098685 samples/sec accuracy=75.966667 loss=0.950475 lr=0.001000 Epoch[052] Batch [1549]/[3759] Speed: 71.610938 samples/sec accuracy=75.960685 loss=0.949965 lr=0.001000 Epoch[052] Batch [1599]/[3759] Speed: 71.802014 samples/sec accuracy=75.980469 loss=0.950460 lr=0.001000 Epoch[052] Batch [1649]/[3759] Speed: 72.128278 samples/sec accuracy=75.976326 loss=0.950895 lr=0.001000 Epoch[052] Batch [1699]/[3759] Speed: 71.385702 samples/sec accuracy=75.971507 loss=0.951106 lr=0.001000 Epoch[052] 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Batch [3649]/[3759] Speed: 71.421991 samples/sec accuracy=75.750000 loss=0.958268 lr=0.001000 Epoch[052] Batch [3699]/[3759] Speed: 71.855937 samples/sec accuracy=75.745355 loss=0.958099 lr=0.001000 Epoch[052] Batch [3749]/[3759] Speed: 80.815037 samples/sec accuracy=75.748333 loss=0.958441 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.375000 acc-top5=87.656250 Batch [0099]/[0303]: acc-top1=68.171875 acc-top5=87.531250 Batch [0149]/[0303]: acc-top1=67.593750 acc-top5=86.729167 Batch [0199]/[0303]: acc-top1=67.390625 acc-top5=86.664062 Batch [0249]/[0303]: acc-top1=67.343750 acc-top5=86.675000 Batch [0299]/[0303]: acc-top1=67.333333 acc-top5=86.661458 [Epoch 052] training: accuracy=75.744463 loss=0.958550 [Epoch 052] speed: 71 samples/sec time cost: 3648.521301 [Epoch 052] validation: acc-top1=67.362830 acc-top5=86.705858 loss=1.553845 Epoch[053] Batch [0049]/[3760] Speed: 48.525852 samples/sec accuracy=77.250000 loss=0.927101 lr=0.001000 Epoch[053] Batch [0099]/[3760] Speed: 70.727305 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lr=0.001000 Epoch[053] Batch [3449]/[3760] Speed: 72.995362 samples/sec accuracy=75.935688 loss=0.952547 lr=0.001000 Epoch[053] Batch [3499]/[3760] Speed: 71.823647 samples/sec accuracy=75.916518 loss=0.953123 lr=0.001000 Epoch[053] Batch [3549]/[3760] Speed: 71.649985 samples/sec accuracy=75.920775 loss=0.953120 lr=0.001000 Epoch[053] Batch [3599]/[3760] Speed: 71.202848 samples/sec accuracy=75.922743 loss=0.952849 lr=0.001000 Epoch[053] Batch [3649]/[3760] Speed: 71.855279 samples/sec accuracy=75.916524 loss=0.952989 lr=0.001000 Epoch[053] Batch [3699]/[3760] Speed: 71.434060 samples/sec accuracy=75.911740 loss=0.953525 lr=0.001000 Epoch[053] Batch [3749]/[3760] Speed: 79.727502 samples/sec accuracy=75.910000 loss=0.953611 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.812500 acc-top5=88.125000 Batch [0099]/[0303]: acc-top1=67.640625 acc-top5=87.671875 Batch [0149]/[0303]: acc-top1=67.020833 acc-top5=86.729167 Batch [0199]/[0303]: acc-top1=66.898438 acc-top5=86.750000 Batch [0249]/[0303]: acc-top1=66.706250 acc-top5=86.762500 Batch [0299]/[0303]: acc-top1=66.890625 acc-top5=86.718750 [Epoch 053] training: accuracy=75.905086 loss=0.953871 [Epoch 053] speed: 71 samples/sec time cost: 3648.024833 [Epoch 053] validation: acc-top1=66.919348 acc-top5=86.747112 loss=1.573928 Epoch[054] Batch [0049]/[3760] Speed: 48.208934 samples/sec accuracy=75.937500 loss=0.963641 lr=0.001000 Epoch[054] Batch [0099]/[3760] Speed: 69.731864 samples/sec accuracy=76.171875 loss=0.942437 lr=0.001000 Epoch[054] Batch [0149]/[3760] Speed: 72.534214 samples/sec accuracy=76.145833 loss=0.947993 lr=0.001000 Epoch[054] Batch [0199]/[3760] Speed: 71.144903 samples/sec accuracy=76.117188 loss=0.950180 lr=0.001000 Epoch[054] Batch [0249]/[3760] Speed: 71.961700 samples/sec accuracy=76.037500 loss=0.953900 lr=0.001000 Epoch[054] Batch [0299]/[3760] Speed: 71.558996 samples/sec accuracy=76.010417 loss=0.951392 lr=0.001000 Epoch[054] Batch [0349]/[3760] Speed: 72.116498 samples/sec 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accuracy=76.059082 loss=0.945451 lr=0.001000 Epoch[054] Batch [3249]/[3760] Speed: 71.646335 samples/sec accuracy=76.085577 loss=0.944770 lr=0.001000 Epoch[054] Batch [3299]/[3760] Speed: 71.577190 samples/sec accuracy=76.066288 loss=0.945569 lr=0.001000 Epoch[054] Batch [3349]/[3760] Speed: 72.197715 samples/sec accuracy=76.089552 loss=0.944723 lr=0.001000 Epoch[054] Batch [3399]/[3760] Speed: 71.292068 samples/sec accuracy=76.089154 loss=0.944883 lr=0.001000 Epoch[054] Batch [3449]/[3760] Speed: 71.409567 samples/sec accuracy=76.096920 loss=0.944468 lr=0.001000 Epoch[054] Batch [3499]/[3760] Speed: 72.243071 samples/sec accuracy=76.103571 loss=0.944581 lr=0.001000 Epoch[054] Batch [3549]/[3760] Speed: 72.213436 samples/sec accuracy=76.088908 loss=0.944473 lr=0.001000 Epoch[054] Batch [3599]/[3760] Speed: 70.843855 samples/sec accuracy=76.080295 loss=0.944485 lr=0.001000 Epoch[054] Batch [3649]/[3760] Speed: 71.642272 samples/sec accuracy=76.085616 loss=0.944611 lr=0.001000 Epoch[054] Batch [3699]/[3760] Speed: 71.441614 samples/sec accuracy=76.087838 loss=0.944388 lr=0.001000 Epoch[054] Batch [3749]/[3760] Speed: 79.204348 samples/sec accuracy=76.074583 loss=0.944855 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.156250 acc-top5=87.625000 Batch [0099]/[0303]: acc-top1=67.937500 acc-top5=87.203125 Batch [0149]/[0303]: acc-top1=67.218750 acc-top5=86.604167 Batch [0199]/[0303]: acc-top1=67.039062 acc-top5=86.578125 Batch [0249]/[0303]: acc-top1=66.931250 acc-top5=86.593750 Batch [0299]/[0303]: acc-top1=67.062500 acc-top5=86.604167 [Epoch 054] training: accuracy=76.069648 loss=0.944989 [Epoch 054] speed: 71 samples/sec time cost: 3648.349080 [Epoch 054] validation: acc-top1=67.063738 acc-top5=86.654290 loss=1.571509 Epoch[055] Batch [0049]/[3759] Speed: 48.345841 samples/sec accuracy=76.218750 loss=0.945731 lr=0.001000 Epoch[055] Batch [0099]/[3759] Speed: 70.563328 samples/sec accuracy=77.125000 loss=0.906575 lr=0.001000 Epoch[055] Batch [0149]/[3759] Speed: 72.146775 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lr=0.001000 Epoch[055] Batch [2549]/[3759] Speed: 71.484156 samples/sec accuracy=76.235907 loss=0.938182 lr=0.001000 Epoch[055] Batch [2599]/[3759] Speed: 72.723182 samples/sec accuracy=76.232572 loss=0.937795 lr=0.001000 Epoch[055] Batch [2649]/[3759] Speed: 71.751347 samples/sec accuracy=76.241156 loss=0.937207 lr=0.001000 Epoch[055] Batch [2699]/[3759] Speed: 71.034832 samples/sec accuracy=76.244792 loss=0.936954 lr=0.001000 Epoch[055] Batch [2749]/[3759] Speed: 71.697370 samples/sec accuracy=76.241477 loss=0.937169 lr=0.001000 Epoch[055] Batch [2799]/[3759] Speed: 70.977383 samples/sec accuracy=76.262277 loss=0.936501 lr=0.001000 Epoch[055] Batch [2849]/[3759] Speed: 71.846217 samples/sec accuracy=76.265351 loss=0.936617 lr=0.001000 Epoch[055] Batch [2899]/[3759] Speed: 72.301923 samples/sec accuracy=76.276401 loss=0.936650 lr=0.001000 Epoch[055] Batch [2949]/[3759] Speed: 72.344602 samples/sec accuracy=76.259534 loss=0.937195 lr=0.001000 Epoch[055] Batch [2999]/[3759] Speed: 71.668893 samples/sec accuracy=76.248437 loss=0.937462 lr=0.001000 Epoch[055] Batch [3049]/[3759] Speed: 71.678632 samples/sec accuracy=76.252561 loss=0.937336 lr=0.001000 Epoch[055] Batch [3099]/[3759] Speed: 71.832220 samples/sec accuracy=76.268649 loss=0.936816 lr=0.001000 Epoch[055] Batch [3149]/[3759] Speed: 71.545649 samples/sec accuracy=76.284226 loss=0.936289 lr=0.001000 Epoch[055] Batch [3199]/[3759] Speed: 72.031629 samples/sec accuracy=76.295410 loss=0.935990 lr=0.001000 Epoch[055] Batch [3249]/[3759] Speed: 71.415458 samples/sec accuracy=76.295673 loss=0.936062 lr=0.001000 Epoch[055] Batch [3299]/[3759] Speed: 71.547072 samples/sec accuracy=76.281250 loss=0.936858 lr=0.001000 Epoch[055] Batch [3349]/[3759] Speed: 72.097806 samples/sec accuracy=76.273321 loss=0.936837 lr=0.001000 Epoch[055] Batch [3399]/[3759] Speed: 71.914538 samples/sec accuracy=76.278952 loss=0.936965 lr=0.001000 Epoch[055] Batch [3449]/[3759] Speed: 72.047591 samples/sec accuracy=76.276721 loss=0.936925 lr=0.001000 Epoch[055] Batch [3499]/[3759] Speed: 71.376195 samples/sec accuracy=76.274107 loss=0.936819 lr=0.001000 Epoch[055] Batch [3549]/[3759] Speed: 71.989902 samples/sec accuracy=76.272447 loss=0.937230 lr=0.001000 Epoch[055] Batch [3599]/[3759] Speed: 71.093489 samples/sec accuracy=76.268663 loss=0.937302 lr=0.001000 Epoch[055] Batch [3649]/[3759] Speed: 72.995334 samples/sec accuracy=76.273116 loss=0.937222 lr=0.001000 Epoch[055] Batch [3699]/[3759] Speed: 71.044593 samples/sec accuracy=76.278294 loss=0.937190 lr=0.001000 Epoch[055] Batch [3749]/[3759] Speed: 80.248890 samples/sec accuracy=76.272500 loss=0.937522 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.625000 acc-top5=88.093750 Batch [0099]/[0303]: acc-top1=68.406250 acc-top5=87.734375 Batch [0149]/[0303]: acc-top1=67.916667 acc-top5=86.864583 Batch [0199]/[0303]: acc-top1=67.703125 acc-top5=86.828125 Batch [0249]/[0303]: acc-top1=67.456250 acc-top5=86.800000 Batch [0299]/[0303]: acc-top1=67.500000 acc-top5=86.833333 [Epoch 055] training: accuracy=76.274857 loss=0.937361 [Epoch 055] speed: 71 samples/sec time cost: 3651.263492 [Epoch 055] validation: acc-top1=67.533003 acc-top5=86.845091 loss=1.567472 Epoch[056] Batch [0049]/[3760] Speed: 48.701366 samples/sec accuracy=76.406250 loss=0.927278 lr=0.001000 Epoch[056] Batch [0099]/[3760] Speed: 70.395302 samples/sec accuracy=76.484375 loss=0.930402 lr=0.001000 Epoch[056] Batch [0149]/[3760] Speed: 71.775551 samples/sec accuracy=76.354167 loss=0.944435 lr=0.001000 Epoch[056] Batch [0199]/[3760] Speed: 71.658762 samples/sec accuracy=76.492188 loss=0.941851 lr=0.001000 Epoch[056] Batch [0249]/[3760] Speed: 71.904243 samples/sec accuracy=76.287500 loss=0.942293 lr=0.001000 Epoch[056] Batch [0299]/[3760] Speed: 71.185398 samples/sec accuracy=76.244792 loss=0.942679 lr=0.001000 Epoch[056] Batch [0349]/[3760] Speed: 71.470366 samples/sec accuracy=76.410714 loss=0.937061 lr=0.001000 Epoch[056] Batch [0399]/[3760] Speed: 72.993868 samples/sec accuracy=76.449219 loss=0.936058 lr=0.001000 Epoch[056] Batch [0449]/[3760] Speed: 70.840835 samples/sec accuracy=76.590278 loss=0.931508 lr=0.001000 Epoch[056] Batch [0499]/[3760] Speed: 72.549349 samples/sec accuracy=76.606250 loss=0.930789 lr=0.001000 Epoch[056] Batch [0549]/[3760] Speed: 71.269250 samples/sec accuracy=76.656250 loss=0.927576 lr=0.001000 Epoch[056] Batch [0599]/[3760] Speed: 71.420220 samples/sec accuracy=76.671875 loss=0.927202 lr=0.001000 Epoch[056] Batch [0649]/[3760] Speed: 71.473208 samples/sec accuracy=76.704327 loss=0.925923 lr=0.001000 Epoch[056] Batch [0699]/[3760] Speed: 71.628976 samples/sec accuracy=76.718750 loss=0.923852 lr=0.001000 Epoch[056] Batch [0749]/[3760] Speed: 72.279654 samples/sec accuracy=76.783333 loss=0.922742 lr=0.001000 Epoch[056] Batch [0799]/[3760] Speed: 71.726930 samples/sec accuracy=76.787109 loss=0.921874 lr=0.001000 Epoch[056] Batch [0849]/[3760] Speed: 71.932977 samples/sec accuracy=76.814338 loss=0.921626 lr=0.001000 Epoch[056] 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accuracy=76.766204 loss=0.923112 lr=0.001000 Epoch[056] Batch [1399]/[3760] Speed: 71.681059 samples/sec accuracy=76.753348 loss=0.922163 lr=0.001000 Epoch[056] Batch [1449]/[3760] Speed: 71.407112 samples/sec accuracy=76.724138 loss=0.922588 lr=0.001000 Epoch[056] Batch [1499]/[3760] Speed: 72.221795 samples/sec accuracy=76.708333 loss=0.922997 lr=0.001000 Epoch[056] Batch [1549]/[3760] Speed: 71.415389 samples/sec accuracy=76.711694 loss=0.923045 lr=0.001000 Epoch[056] Batch [1599]/[3760] Speed: 71.862592 samples/sec accuracy=76.704102 loss=0.923260 lr=0.001000 Epoch[056] Batch [1649]/[3760] Speed: 72.618281 samples/sec accuracy=76.684659 loss=0.924835 lr=0.001000 Epoch[056] Batch [1699]/[3760] Speed: 71.451887 samples/sec accuracy=76.685662 loss=0.924263 lr=0.001000 Epoch[056] Batch [1749]/[3760] Speed: 71.619571 samples/sec accuracy=76.677679 loss=0.924249 lr=0.001000 Epoch[056] Batch [1799]/[3760] Speed: 72.240056 samples/sec accuracy=76.671007 loss=0.923688 lr=0.001000 Epoch[056] 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accuracy=76.597826 loss=0.925581 lr=0.001000 Epoch[056] Batch [2349]/[3760] Speed: 71.149052 samples/sec accuracy=76.567154 loss=0.926480 lr=0.001000 Epoch[056] Batch [2399]/[3760] Speed: 71.936381 samples/sec accuracy=76.552083 loss=0.927168 lr=0.001000 Epoch[056] Batch [2449]/[3760] Speed: 72.165251 samples/sec accuracy=76.563138 loss=0.926750 lr=0.001000 Epoch[056] Batch [2499]/[3760] Speed: 70.836265 samples/sec accuracy=76.565000 loss=0.927303 lr=0.001000 Epoch[056] Batch [2549]/[3760] Speed: 71.814300 samples/sec accuracy=76.591299 loss=0.926358 lr=0.001000 Epoch[056] Batch [2599]/[3760] Speed: 72.790348 samples/sec accuracy=76.596154 loss=0.926623 lr=0.001000 Epoch[056] Batch [2649]/[3760] Speed: 71.421762 samples/sec accuracy=76.579009 loss=0.926932 lr=0.001000 Epoch[056] Batch [2699]/[3760] Speed: 72.257731 samples/sec accuracy=76.555556 loss=0.927847 lr=0.001000 Epoch[056] Batch [2749]/[3760] Speed: 71.613076 samples/sec accuracy=76.538636 loss=0.928352 lr=0.001000 Epoch[056] 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accuracy=76.485577 loss=0.929383 lr=0.001000 Epoch[056] Batch [3299]/[3760] Speed: 71.275362 samples/sec accuracy=76.468277 loss=0.930292 lr=0.001000 Epoch[056] Batch [3349]/[3760] Speed: 71.929669 samples/sec accuracy=76.453358 loss=0.930634 lr=0.001000 Epoch[056] Batch [3399]/[3760] Speed: 71.385716 samples/sec accuracy=76.457261 loss=0.930348 lr=0.001000 Epoch[056] Batch [3449]/[3760] Speed: 72.540084 samples/sec accuracy=76.446558 loss=0.930960 lr=0.001000 Epoch[056] Batch [3499]/[3760] Speed: 72.386303 samples/sec accuracy=76.444643 loss=0.931541 lr=0.001000 Epoch[056] Batch [3549]/[3760] Speed: 71.515591 samples/sec accuracy=76.430898 loss=0.932122 lr=0.001000 Epoch[056] Batch [3599]/[3760] Speed: 71.753641 samples/sec accuracy=76.433594 loss=0.931985 lr=0.001000 Epoch[056] Batch [3649]/[3760] Speed: 71.964913 samples/sec accuracy=76.437072 loss=0.931809 lr=0.001000 Epoch[056] Batch [3699]/[3760] Speed: 71.490121 samples/sec accuracy=76.430743 loss=0.932007 lr=0.001000 Epoch[056] Batch [3749]/[3760] Speed: 79.891578 samples/sec accuracy=76.441250 loss=0.931426 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.593750 acc-top5=88.406250 Batch [0099]/[0303]: acc-top1=68.625000 acc-top5=87.796875 Batch [0149]/[0303]: acc-top1=67.520833 acc-top5=86.958333 Batch [0199]/[0303]: acc-top1=67.242188 acc-top5=86.828125 Batch [0249]/[0303]: acc-top1=67.093750 acc-top5=86.768750 Batch [0299]/[0303]: acc-top1=67.286458 acc-top5=86.776042 [Epoch 056] training: accuracy=76.446144 loss=0.931305 [Epoch 056] speed: 71 samples/sec time cost: 3647.698826 [Epoch 056] validation: acc-top1=67.326733 acc-top5=86.803837 loss=1.574267 Epoch[057] Batch [0049]/[3760] Speed: 48.627665 samples/sec accuracy=76.468750 loss=0.940392 lr=0.001000 Epoch[057] Batch [0099]/[3760] Speed: 70.481124 samples/sec accuracy=76.250000 loss=0.930255 lr=0.001000 Epoch[057] Batch [0149]/[3760] Speed: 71.530968 samples/sec accuracy=76.968750 loss=0.906287 lr=0.001000 Epoch[057] Batch [0199]/[3760] Speed: 71.429135 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lr=0.001000 Epoch[057] Batch [2599]/[3760] Speed: 71.519957 samples/sec accuracy=76.772236 loss=0.918189 lr=0.001000 Epoch[057] Batch [2649]/[3760] Speed: 71.752246 samples/sec accuracy=76.747052 loss=0.918372 lr=0.001000 Epoch[057] Batch [2699]/[3760] Speed: 71.612427 samples/sec accuracy=76.736111 loss=0.918416 lr=0.001000 Epoch[057] Batch [2749]/[3760] Speed: 72.833362 samples/sec accuracy=76.751136 loss=0.917234 lr=0.001000 Epoch[057] Batch [2799]/[3760] Speed: 71.473073 samples/sec accuracy=76.750000 loss=0.917220 lr=0.001000 Epoch[057] Batch [2849]/[3760] Speed: 71.937383 samples/sec accuracy=76.744518 loss=0.916959 lr=0.001000 Epoch[057] Batch [2899]/[3760] Speed: 71.222396 samples/sec accuracy=76.718211 loss=0.917898 lr=0.001000 Epoch[057] Batch [2949]/[3760] Speed: 72.009589 samples/sec accuracy=76.698093 loss=0.918754 lr=0.001000 Epoch[057] Batch [2999]/[3760] Speed: 71.808049 samples/sec accuracy=76.679688 loss=0.918912 lr=0.001000 Epoch[057] Batch [3049]/[3760] Speed: 71.313635 samples/sec accuracy=76.681865 loss=0.919045 lr=0.001000 Epoch[057] Batch [3099]/[3760] Speed: 71.980557 samples/sec accuracy=76.692540 loss=0.918721 lr=0.001000 Epoch[057] Batch [3149]/[3760] Speed: 71.981127 samples/sec accuracy=76.677083 loss=0.919190 lr=0.001000 Epoch[057] Batch [3199]/[3760] Speed: 72.456865 samples/sec accuracy=76.674316 loss=0.919014 lr=0.001000 Epoch[057] Batch [3249]/[3760] Speed: 71.488114 samples/sec accuracy=76.660096 loss=0.919473 lr=0.001000 Epoch[057] Batch [3299]/[3760] Speed: 72.135745 samples/sec accuracy=76.658144 loss=0.919930 lr=0.001000 Epoch[057] Batch [3349]/[3760] Speed: 71.931755 samples/sec accuracy=76.665578 loss=0.919746 lr=0.001000 Epoch[057] Batch [3399]/[3760] Speed: 72.070183 samples/sec accuracy=76.663143 loss=0.919860 lr=0.001000 Epoch[057] Batch [3449]/[3760] Speed: 71.600326 samples/sec accuracy=76.650362 loss=0.920095 lr=0.001000 Epoch[057] Batch [3499]/[3760] Speed: 71.296084 samples/sec accuracy=76.656696 loss=0.920007 lr=0.001000 Epoch[057] Batch [3549]/[3760] Speed: 70.630445 samples/sec accuracy=76.653609 loss=0.920580 lr=0.001000 Epoch[057] Batch [3599]/[3760] Speed: 72.547594 samples/sec accuracy=76.649306 loss=0.920717 lr=0.001000 Epoch[057] Batch [3649]/[3760] Speed: 71.978119 samples/sec accuracy=76.627997 loss=0.921315 lr=0.001000 Epoch[057] Batch [3699]/[3760] Speed: 72.141405 samples/sec accuracy=76.627956 loss=0.921089 lr=0.001000 Epoch[057] Batch [3749]/[3760] Speed: 79.298790 samples/sec accuracy=76.637083 loss=0.920646 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.250000 acc-top5=87.937500 Batch [0099]/[0303]: acc-top1=68.171875 acc-top5=87.484375 Batch [0149]/[0303]: acc-top1=67.406250 acc-top5=86.593750 Batch [0199]/[0303]: acc-top1=67.234375 acc-top5=86.593750 Batch [0249]/[0303]: acc-top1=67.012500 acc-top5=86.587500 Batch [0299]/[0303]: acc-top1=67.083333 acc-top5=86.567708 [Epoch 057] training: accuracy=76.641872 loss=0.920486 [Epoch 057] speed: 71 samples/sec time cost: 3644.797227 [Epoch 057] validation: acc-top1=67.099835 acc-top5=86.597566 loss=1.584221 Epoch[058] Batch [0049]/[3759] Speed: 48.752237 samples/sec accuracy=78.281250 loss=0.835908 lr=0.001000 Epoch[058] Batch [0099]/[3759] Speed: 70.562317 samples/sec accuracy=77.640625 loss=0.861816 lr=0.001000 Epoch[058] Batch [0149]/[3759] Speed: 71.972915 samples/sec accuracy=77.166667 loss=0.895904 lr=0.001000 Epoch[058] Batch [0199]/[3759] Speed: 71.419299 samples/sec accuracy=77.554688 loss=0.891817 lr=0.001000 Epoch[058] Batch [0249]/[3759] Speed: 71.410005 samples/sec accuracy=77.375000 loss=0.894708 lr=0.001000 Epoch[058] Batch [0299]/[3759] Speed: 72.052872 samples/sec accuracy=77.182292 loss=0.904868 lr=0.001000 Epoch[058] Batch [0349]/[3759] Speed: 71.845312 samples/sec accuracy=77.133929 loss=0.904612 lr=0.001000 Epoch[058] Batch [0399]/[3759] Speed: 71.151214 samples/sec accuracy=77.191406 loss=0.901753 lr=0.001000 Epoch[058] Batch [0449]/[3759] Speed: 71.969349 samples/sec 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accuracy=76.755208 loss=0.913024 lr=0.001000 Epoch[058] Batch [3349]/[3759] Speed: 71.853490 samples/sec accuracy=76.743004 loss=0.913295 lr=0.001000 Epoch[058] Batch [3399]/[3759] Speed: 71.848375 samples/sec accuracy=76.742647 loss=0.913545 lr=0.001000 Epoch[058] Batch [3449]/[3759] Speed: 71.785863 samples/sec accuracy=76.740942 loss=0.913250 lr=0.001000 Epoch[058] Batch [3499]/[3759] Speed: 72.236736 samples/sec accuracy=76.741071 loss=0.913043 lr=0.001000 Epoch[058] Batch [3549]/[3759] Speed: 71.679789 samples/sec accuracy=76.725792 loss=0.913524 lr=0.001000 Epoch[058] Batch [3599]/[3759] Speed: 71.834328 samples/sec accuracy=76.712674 loss=0.913997 lr=0.001000 Epoch[058] Batch [3649]/[3759] Speed: 71.093669 samples/sec accuracy=76.706336 loss=0.913909 lr=0.001000 Epoch[058] Batch [3699]/[3759] Speed: 72.217033 samples/sec accuracy=76.700169 loss=0.914401 lr=0.001000 Epoch[058] Batch [3749]/[3759] Speed: 80.261575 samples/sec accuracy=76.696667 loss=0.914530 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.031250 acc-top5=87.718750 Batch [0099]/[0303]: acc-top1=68.265625 acc-top5=87.281250 Batch [0149]/[0303]: acc-top1=67.625000 acc-top5=86.635417 Batch [0199]/[0303]: acc-top1=67.398438 acc-top5=86.500000 Batch [0249]/[0303]: acc-top1=67.387500 acc-top5=86.493750 Batch [0299]/[0303]: acc-top1=67.494792 acc-top5=86.541667 [Epoch 058] training: accuracy=76.694267 loss=0.914664 [Epoch 058] speed: 71 samples/sec time cost: 3643.975015 [Epoch 058] validation: acc-top1=67.517533 acc-top5=86.566625 loss=1.562351 Epoch[059] Batch [0049]/[3760] Speed: 48.533091 samples/sec accuracy=78.093750 loss=0.858419 lr=0.001000 Epoch[059] Batch [0099]/[3760] Speed: 71.727107 samples/sec accuracy=77.921875 loss=0.866533 lr=0.001000 Epoch[059] Batch [0149]/[3760] Speed: 71.321977 samples/sec accuracy=77.687500 loss=0.876856 lr=0.001000 Epoch[059] Batch [0199]/[3760] Speed: 71.428141 samples/sec accuracy=77.539062 loss=0.889857 lr=0.001000 Epoch[059] Batch [0249]/[3760] Speed: 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71.452529 samples/sec accuracy=76.881048 loss=0.913644 lr=0.001000 Epoch[059] Batch [3149]/[3760] Speed: 71.262169 samples/sec accuracy=76.902778 loss=0.913119 lr=0.001000 Epoch[059] Batch [3199]/[3760] Speed: 71.613038 samples/sec accuracy=76.915527 loss=0.912720 lr=0.001000 Epoch[059] Batch [3249]/[3760] Speed: 71.673714 samples/sec accuracy=76.908654 loss=0.912878 lr=0.001000 Epoch[059] Batch [3299]/[3760] Speed: 72.092679 samples/sec accuracy=76.896780 loss=0.913038 lr=0.001000 Epoch[059] Batch [3349]/[3760] Speed: 71.910532 samples/sec accuracy=76.875933 loss=0.913612 lr=0.001000 Epoch[059] Batch [3399]/[3760] Speed: 71.449138 samples/sec accuracy=76.884191 loss=0.913341 lr=0.001000 Epoch[059] Batch [3449]/[3760] Speed: 71.480365 samples/sec accuracy=76.877264 loss=0.913766 lr=0.001000 Epoch[059] Batch [3499]/[3760] Speed: 72.059938 samples/sec accuracy=76.881250 loss=0.913517 lr=0.001000 Epoch[059] Batch [3549]/[3760] Speed: 71.952489 samples/sec accuracy=76.879842 loss=0.913564 lr=0.001000 Epoch[059] Batch [3599]/[3760] Speed: 71.735529 samples/sec accuracy=76.879340 loss=0.913739 lr=0.001000 Epoch[059] Batch [3649]/[3760] Speed: 71.413565 samples/sec accuracy=76.890411 loss=0.912822 lr=0.001000 Epoch[059] Batch [3699]/[3760] Speed: 71.769603 samples/sec accuracy=76.892736 loss=0.912709 lr=0.001000 Epoch[059] Batch [3749]/[3760] Speed: 79.465590 samples/sec accuracy=76.885000 loss=0.912950 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.406250 acc-top5=87.625000 Batch [0099]/[0303]: acc-top1=67.703125 acc-top5=87.468750 Batch [0149]/[0303]: acc-top1=67.281250 acc-top5=86.760417 Batch [0199]/[0303]: acc-top1=66.968750 acc-top5=86.742188 Batch [0249]/[0303]: acc-top1=66.862500 acc-top5=86.793750 Batch [0299]/[0303]: acc-top1=67.104167 acc-top5=86.770833 [Epoch 059] training: accuracy=76.884973 loss=0.912985 [Epoch 059] speed: 71 samples/sec time cost: 3648.125392 [Epoch 059] validation: acc-top1=67.146246 acc-top5=86.798680 loss=1.578243 Epoch[060] Batch 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accuracy=77.062966 loss=0.903924 lr=0.001000 Epoch[060] Batch [3399]/[3760] Speed: 72.897221 samples/sec accuracy=77.064338 loss=0.903668 lr=0.001000 Epoch[060] Batch [3449]/[3760] Speed: 72.571389 samples/sec accuracy=77.081069 loss=0.903260 lr=0.001000 Epoch[060] Batch [3499]/[3760] Speed: 72.178899 samples/sec accuracy=77.071875 loss=0.903890 lr=0.001000 Epoch[060] Batch [3549]/[3760] Speed: 71.132318 samples/sec accuracy=77.073504 loss=0.904073 lr=0.001000 Epoch[060] Batch [3599]/[3760] Speed: 71.632470 samples/sec accuracy=77.063802 loss=0.904245 lr=0.001000 Epoch[060] Batch [3649]/[3760] Speed: 71.904629 samples/sec accuracy=77.074058 loss=0.903778 lr=0.001000 Epoch[060] Batch [3699]/[3760] Speed: 72.411597 samples/sec accuracy=77.057855 loss=0.904500 lr=0.001000 Epoch[060] Batch [3749]/[3760] Speed: 78.762875 samples/sec accuracy=77.042500 loss=0.904950 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.343750 acc-top5=87.562500 Batch [0099]/[0303]: acc-top1=68.546875 acc-top5=87.562500 Batch [0149]/[0303]: acc-top1=67.833333 acc-top5=86.781250 Batch [0199]/[0303]: acc-top1=67.765625 acc-top5=86.804688 Batch [0249]/[0303]: acc-top1=67.512500 acc-top5=86.843750 Batch [0299]/[0303]: acc-top1=67.526042 acc-top5=86.916667 [Epoch 060] training: accuracy=77.033328 loss=0.905202 [Epoch 060] speed: 71 samples/sec time cost: 3646.963289 [Epoch 060] validation: acc-top1=67.527847 acc-top5=86.953383 loss=1.576958 Epoch[061] Batch [0049]/[3759] Speed: 49.143314 samples/sec accuracy=78.250000 loss=0.851200 lr=0.001000 Epoch[061] Batch [0099]/[3759] Speed: 70.808734 samples/sec accuracy=78.125000 loss=0.852313 lr=0.001000 Epoch[061] Batch [0149]/[3759] Speed: 71.577916 samples/sec accuracy=78.197917 loss=0.862211 lr=0.001000 Epoch[061] Batch [0199]/[3759] Speed: 72.027935 samples/sec accuracy=77.945312 loss=0.867508 lr=0.001000 Epoch[061] Batch [0249]/[3759] Speed: 72.136901 samples/sec accuracy=77.831250 loss=0.876986 lr=0.001000 Epoch[061] Batch [0299]/[3759] 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accuracy=77.388787 loss=0.892180 lr=0.001000 Epoch[061] Batch [1749]/[3759] Speed: 71.348145 samples/sec accuracy=77.382143 loss=0.892002 lr=0.001000 Epoch[061] Batch [1799]/[3759] Speed: 72.160813 samples/sec accuracy=77.390625 loss=0.891634 lr=0.001000 Epoch[061] Batch [1849]/[3759] Speed: 71.524307 samples/sec accuracy=77.405405 loss=0.891532 lr=0.001000 Epoch[061] Batch [1899]/[3759] Speed: 71.835595 samples/sec accuracy=77.407895 loss=0.891390 lr=0.001000 Epoch[061] Batch [1949]/[3759] Speed: 72.039921 samples/sec accuracy=77.411058 loss=0.891165 lr=0.001000 Epoch[061] Batch [1999]/[3759] Speed: 71.161379 samples/sec accuracy=77.390625 loss=0.891831 lr=0.001000 Epoch[061] Batch [2049]/[3759] Speed: 71.844303 samples/sec accuracy=77.406250 loss=0.891441 lr=0.001000 Epoch[061] Batch [2099]/[3759] Speed: 71.793841 samples/sec accuracy=77.387649 loss=0.892720 lr=0.001000 Epoch[061] Batch [2149]/[3759] Speed: 72.279395 samples/sec accuracy=77.379360 loss=0.893673 lr=0.001000 Epoch[061] 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accuracy=77.349057 loss=0.893736 lr=0.001000 Epoch[061] Batch [2699]/[3759] Speed: 71.966363 samples/sec accuracy=77.366319 loss=0.893511 lr=0.001000 Epoch[061] Batch [2749]/[3759] Speed: 72.031972 samples/sec accuracy=77.373295 loss=0.893159 lr=0.001000 Epoch[061] Batch [2799]/[3759] Speed: 71.100623 samples/sec accuracy=77.378906 loss=0.893215 lr=0.001000 Epoch[061] Batch [2849]/[3759] Speed: 71.427286 samples/sec accuracy=77.361294 loss=0.893678 lr=0.001000 Epoch[061] Batch [2899]/[3759] Speed: 70.993803 samples/sec accuracy=77.375539 loss=0.893634 lr=0.001000 Epoch[061] Batch [2949]/[3759] Speed: 71.906769 samples/sec accuracy=77.370763 loss=0.893862 lr=0.001000 Epoch[061] Batch [2999]/[3759] Speed: 71.496283 samples/sec accuracy=77.378646 loss=0.893155 lr=0.001000 Epoch[061] Batch [3049]/[3759] Speed: 71.925919 samples/sec accuracy=77.384734 loss=0.893039 lr=0.001000 Epoch[061] Batch [3099]/[3759] Speed: 72.339885 samples/sec accuracy=77.374496 loss=0.893573 lr=0.001000 Epoch[061] Batch [3149]/[3759] Speed: 70.464185 samples/sec accuracy=77.364087 loss=0.893788 lr=0.001000 Epoch[061] Batch [3199]/[3759] Speed: 71.712031 samples/sec accuracy=77.373535 loss=0.893462 lr=0.001000 Epoch[061] Batch [3249]/[3759] Speed: 72.657881 samples/sec accuracy=77.350000 loss=0.893937 lr=0.001000 Epoch[061] Batch [3299]/[3759] Speed: 71.489270 samples/sec accuracy=77.328125 loss=0.894244 lr=0.001000 Epoch[061] Batch [3349]/[3759] Speed: 71.945896 samples/sec accuracy=77.340485 loss=0.893919 lr=0.001000 Epoch[061] Batch [3399]/[3759] Speed: 71.339956 samples/sec accuracy=77.334099 loss=0.894420 lr=0.001000 Epoch[061] Batch [3449]/[3759] Speed: 71.668896 samples/sec accuracy=77.334692 loss=0.894510 lr=0.001000 Epoch[061] Batch [3499]/[3759] Speed: 71.267616 samples/sec accuracy=77.341964 loss=0.894363 lr=0.001000 Epoch[061] Batch [3549]/[3759] Speed: 70.782972 samples/sec accuracy=77.326585 loss=0.894864 lr=0.001000 Epoch[061] Batch [3599]/[3759] Speed: 72.931828 samples/sec accuracy=77.311632 loss=0.895265 lr=0.001000 Epoch[061] Batch [3649]/[3759] Speed: 71.484768 samples/sec accuracy=77.321062 loss=0.894795 lr=0.001000 Epoch[061] Batch [3699]/[3759] Speed: 71.536852 samples/sec accuracy=77.316723 loss=0.894762 lr=0.001000 Epoch[061] Batch [3749]/[3759] Speed: 80.063410 samples/sec accuracy=77.318333 loss=0.894526 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.031250 acc-top5=88.031250 Batch [0099]/[0303]: acc-top1=68.093750 acc-top5=87.484375 Batch [0149]/[0303]: acc-top1=67.406250 acc-top5=86.708333 Batch [0199]/[0303]: acc-top1=67.304688 acc-top5=86.640625 Batch [0249]/[0303]: acc-top1=67.137500 acc-top5=86.625000 Batch [0299]/[0303]: acc-top1=67.223958 acc-top5=86.583333 [Epoch 061] training: accuracy=77.311951 loss=0.894824 [Epoch 061] speed: 71 samples/sec time cost: 3645.320545 [Epoch 061] validation: acc-top1=67.239068 acc-top5=86.602723 loss=1.610136 Epoch[062] Batch [0049]/[3760] Speed: 48.934391 samples/sec accuracy=78.593750 loss=0.857302 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acc-top1=66.914062 acc-top5=86.710938 Batch [0249]/[0303]: acc-top1=66.856250 acc-top5=86.712500 Batch [0299]/[0303]: acc-top1=66.927083 acc-top5=86.744792 [Epoch 062] training: accuracy=77.397357 loss=0.886947 [Epoch 062] speed: 71 samples/sec time cost: 3652.942504 [Epoch 062] validation: acc-top1=66.945132 acc-top5=86.772896 loss=1.615710 Epoch[063] Batch [0049]/[3760] Speed: 48.975060 samples/sec accuracy=77.125000 loss=0.874842 lr=0.001000 Epoch[063] Batch [0099]/[3760] Speed: 70.550162 samples/sec accuracy=76.562500 loss=0.913675 lr=0.001000 Epoch[063] Batch [0149]/[3760] Speed: 72.167397 samples/sec accuracy=77.239583 loss=0.888465 lr=0.001000 Epoch[063] Batch [0199]/[3760] Speed: 71.131945 samples/sec accuracy=77.328125 loss=0.884489 lr=0.001000 Epoch[063] Batch [0249]/[3760] Speed: 71.426442 samples/sec accuracy=77.543750 loss=0.879314 lr=0.001000 Epoch[063] Batch [0299]/[3760] Speed: 71.136590 samples/sec accuracy=77.677083 loss=0.874596 lr=0.001000 Epoch[063] Batch 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accuracy=77.583048 loss=0.881426 lr=0.001000 Epoch[063] Batch [3699]/[3760] Speed: 71.780110 samples/sec accuracy=77.590794 loss=0.881346 lr=0.001000 Epoch[063] Batch [3749]/[3760] Speed: 79.627221 samples/sec accuracy=77.585000 loss=0.881585 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.750000 acc-top5=87.937500 Batch [0099]/[0303]: acc-top1=67.609375 acc-top5=87.453125 Batch [0149]/[0303]: acc-top1=67.177083 acc-top5=86.645833 Batch [0199]/[0303]: acc-top1=67.148438 acc-top5=86.554688 Batch [0249]/[0303]: acc-top1=67.031250 acc-top5=86.512500 Batch [0299]/[0303]: acc-top1=67.119792 acc-top5=86.552083 [Epoch 063] training: accuracy=77.585189 loss=0.881676 [Epoch 063] speed: 71 samples/sec time cost: 3651.573705 [Epoch 063] validation: acc-top1=67.135932 acc-top5=86.582096 loss=1.602877 Epoch[064] Batch [0049]/[3759] Speed: 48.786001 samples/sec accuracy=78.968750 loss=0.851230 lr=0.001000 Epoch[064] Batch [0099]/[3759] Speed: 70.577745 samples/sec accuracy=77.765625 loss=0.875667 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71.086611 samples/sec accuracy=77.716486 loss=0.873833 lr=0.001000 Epoch[064] Batch [3499]/[3759] Speed: 71.119940 samples/sec accuracy=77.708929 loss=0.874039 lr=0.001000 Epoch[064] Batch [3549]/[3759] Speed: 72.096503 samples/sec accuracy=77.712148 loss=0.873828 lr=0.001000 Epoch[064] Batch [3599]/[3759] Speed: 71.753254 samples/sec accuracy=77.719618 loss=0.873670 lr=0.001000 Epoch[064] Batch [3649]/[3759] Speed: 72.128387 samples/sec accuracy=77.703339 loss=0.874130 lr=0.001000 Epoch[064] Batch [3699]/[3759] Speed: 71.598455 samples/sec accuracy=77.680743 loss=0.875097 lr=0.001000 Epoch[064] Batch [3749]/[3759] Speed: 79.850655 samples/sec accuracy=77.668333 loss=0.875600 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.218750 acc-top5=88.281250 Batch [0099]/[0303]: acc-top1=68.015625 acc-top5=87.609375 Batch [0149]/[0303]: acc-top1=67.416667 acc-top5=86.729167 Batch [0199]/[0303]: acc-top1=67.132812 acc-top5=86.632812 Batch [0249]/[0303]: acc-top1=67.025000 acc-top5=86.637500 Batch [0299]/[0303]: acc-top1=67.067708 acc-top5=86.703125 [Epoch 064] training: accuracy=77.663607 loss=0.875679 [Epoch 064] speed: 71 samples/sec time cost: 3651.815747 [Epoch 064] validation: acc-top1=67.099835 acc-top5=86.741955 loss=1.608045 Epoch[065] Batch [0049]/[3760] Speed: 48.931363 samples/sec accuracy=78.218750 loss=0.864029 lr=0.001000 Epoch[065] Batch [0099]/[3760] Speed: 71.070279 samples/sec accuracy=78.328125 loss=0.858702 lr=0.001000 Epoch[065] Batch [0149]/[3760] Speed: 72.049829 samples/sec accuracy=77.947917 loss=0.871305 lr=0.001000 Epoch[065] Batch [0199]/[3760] Speed: 70.508244 samples/sec accuracy=77.937500 loss=0.866788 lr=0.001000 Epoch[065] Batch [0249]/[3760] Speed: 71.483641 samples/sec accuracy=78.131250 loss=0.859868 lr=0.001000 Epoch[065] Batch [0299]/[3760] Speed: 71.587610 samples/sec accuracy=78.000000 loss=0.864589 lr=0.001000 Epoch[065] Batch [0349]/[3760] Speed: 71.708651 samples/sec accuracy=77.977679 loss=0.863978 lr=0.001000 Epoch[065] Batch 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accuracy=78.090074 loss=0.861048 lr=0.001000 Epoch[065] Batch [0899]/[3760] Speed: 72.372263 samples/sec accuracy=78.085069 loss=0.858851 lr=0.001000 Epoch[065] Batch [0949]/[3760] Speed: 72.199632 samples/sec accuracy=78.108553 loss=0.856472 lr=0.001000 Epoch[065] Batch [0999]/[3760] Speed: 71.262908 samples/sec accuracy=78.150000 loss=0.854201 lr=0.001000 Epoch[065] Batch [1049]/[3760] Speed: 72.251293 samples/sec accuracy=78.138393 loss=0.855108 lr=0.001000 Epoch[065] Batch [1099]/[3760] Speed: 71.288225 samples/sec accuracy=78.102273 loss=0.856867 lr=0.001000 Epoch[065] Batch [1149]/[3760] Speed: 72.354809 samples/sec accuracy=78.099185 loss=0.856678 lr=0.001000 Epoch[065] Batch [1199]/[3760] Speed: 70.998276 samples/sec accuracy=78.070312 loss=0.857501 lr=0.001000 Epoch[065] Batch [1249]/[3760] Speed: 72.175788 samples/sec accuracy=78.122500 loss=0.856145 lr=0.001000 Epoch[065] Batch [1299]/[3760] Speed: 71.617317 samples/sec accuracy=78.155048 loss=0.855932 lr=0.001000 Epoch[065] 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accuracy=78.140625 loss=0.859646 lr=0.001000 Epoch[065] Batch [1849]/[3760] Speed: 72.051811 samples/sec accuracy=78.126689 loss=0.860253 lr=0.001000 Epoch[065] Batch [1899]/[3760] Speed: 71.265603 samples/sec accuracy=78.121711 loss=0.860894 lr=0.001000 Epoch[065] Batch [1949]/[3760] Speed: 71.874238 samples/sec accuracy=78.112981 loss=0.861238 lr=0.001000 Epoch[065] Batch [1999]/[3760] Speed: 71.613848 samples/sec accuracy=78.117969 loss=0.861629 lr=0.001000 Epoch[065] Batch [2049]/[3760] Speed: 71.453990 samples/sec accuracy=78.143293 loss=0.860812 lr=0.001000 Epoch[065] Batch [2099]/[3760] Speed: 71.242351 samples/sec accuracy=78.116071 loss=0.861160 lr=0.001000 Epoch[065] Batch [2149]/[3760] Speed: 72.197989 samples/sec accuracy=78.095930 loss=0.862423 lr=0.001000 Epoch[065] Batch [2199]/[3760] Speed: 71.646733 samples/sec accuracy=78.109375 loss=0.861903 lr=0.001000 Epoch[065] Batch [2249]/[3760] Speed: 71.507672 samples/sec accuracy=78.111111 loss=0.861578 lr=0.001000 Epoch[065] 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accuracy=78.055682 loss=0.863333 lr=0.001000 Epoch[065] Batch [2799]/[3760] Speed: 72.226037 samples/sec accuracy=78.020089 loss=0.864192 lr=0.001000 Epoch[065] Batch [2849]/[3760] Speed: 71.219834 samples/sec accuracy=77.999452 loss=0.865136 lr=0.001000 Epoch[065] Batch [2899]/[3760] Speed: 72.114431 samples/sec accuracy=77.996767 loss=0.865106 lr=0.001000 Epoch[065] Batch [2949]/[3760] Speed: 72.171232 samples/sec accuracy=77.973517 loss=0.865965 lr=0.001000 Epoch[065] Batch [2999]/[3760] Speed: 71.175423 samples/sec accuracy=77.960938 loss=0.866495 lr=0.001000 Epoch[065] Batch [3049]/[3760] Speed: 71.387858 samples/sec accuracy=77.914959 loss=0.868075 lr=0.001000 Epoch[065] Batch [3099]/[3760] Speed: 71.746691 samples/sec accuracy=77.934980 loss=0.867794 lr=0.001000 Epoch[065] Batch [3149]/[3760] Speed: 71.341208 samples/sec accuracy=77.934028 loss=0.867603 lr=0.001000 Epoch[065] Batch [3199]/[3760] Speed: 71.812096 samples/sec accuracy=77.915039 loss=0.868214 lr=0.001000 Epoch[065] 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accuracy=77.838682 loss=0.870854 lr=0.001000 Epoch[065] Batch [3749]/[3760] Speed: 79.467945 samples/sec accuracy=77.820000 loss=0.871758 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.656250 acc-top5=87.437500 Batch [0099]/[0303]: acc-top1=68.234375 acc-top5=87.312500 Batch [0149]/[0303]: acc-top1=67.333333 acc-top5=86.562500 Batch [0199]/[0303]: acc-top1=67.109375 acc-top5=86.484375 Batch [0249]/[0303]: acc-top1=67.143750 acc-top5=86.475000 Batch [0299]/[0303]: acc-top1=67.213542 acc-top5=86.500000 [Epoch 065] training: accuracy=77.831200 loss=0.871485 [Epoch 065] speed: 71 samples/sec time cost: 3652.320562 [Epoch 065] validation: acc-top1=67.270008 acc-top5=86.545998 loss=1.595563 Epoch[066] Batch [0049]/[3759] Speed: 48.733455 samples/sec accuracy=78.406250 loss=0.845492 lr=0.001000 Epoch[066] Batch [0099]/[3759] Speed: 70.397367 samples/sec accuracy=78.859375 loss=0.833985 lr=0.001000 Epoch[066] Batch [0149]/[3759] Speed: 70.572005 samples/sec accuracy=78.760417 loss=0.839341 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lr=0.001000 Epoch[066] Batch [3049]/[3759] Speed: 71.383634 samples/sec accuracy=78.122951 loss=0.861677 lr=0.001000 Epoch[066] Batch [3099]/[3759] Speed: 71.488408 samples/sec accuracy=78.129032 loss=0.861631 lr=0.001000 Epoch[066] Batch [3149]/[3759] Speed: 71.255583 samples/sec accuracy=78.131944 loss=0.861832 lr=0.001000 Epoch[066] Batch [3199]/[3759] Speed: 71.389882 samples/sec accuracy=78.144531 loss=0.860856 lr=0.001000 Epoch[066] Batch [3249]/[3759] Speed: 71.444919 samples/sec accuracy=78.156731 loss=0.860508 lr=0.001000 Epoch[066] Batch [3299]/[3759] Speed: 72.019438 samples/sec accuracy=78.146307 loss=0.860547 lr=0.001000 Epoch[066] Batch [3349]/[3759] Speed: 71.817027 samples/sec accuracy=78.130597 loss=0.860892 lr=0.001000 Epoch[066] Batch [3399]/[3759] Speed: 71.720090 samples/sec accuracy=78.133732 loss=0.860868 lr=0.001000 Epoch[066] Batch [3449]/[3759] Speed: 71.790035 samples/sec accuracy=78.121377 loss=0.860940 lr=0.001000 Epoch[066] Batch [3499]/[3759] Speed: 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[Epoch 066] speed: 71 samples/sec time cost: 3654.280709 [Epoch 066] validation: acc-top1=67.115305 acc-top5=86.654290 loss=1.596267 Epoch[067] Batch [0049]/[3760] Speed: 48.773587 samples/sec accuracy=78.750000 loss=0.860581 lr=0.001000 Epoch[067] Batch [0099]/[3760] Speed: 70.918058 samples/sec accuracy=78.609375 loss=0.849988 lr=0.001000 Epoch[067] Batch [0149]/[3760] Speed: 71.235962 samples/sec accuracy=78.677083 loss=0.839535 lr=0.001000 Epoch[067] Batch [0199]/[3760] Speed: 71.539837 samples/sec accuracy=78.625000 loss=0.837248 lr=0.001000 Epoch[067] Batch [0249]/[3760] Speed: 72.269566 samples/sec accuracy=78.543750 loss=0.835002 lr=0.001000 Epoch[067] Batch [0299]/[3760] Speed: 70.928320 samples/sec accuracy=78.614583 loss=0.831850 lr=0.001000 Epoch[067] Batch [0349]/[3760] Speed: 72.264837 samples/sec accuracy=78.508929 loss=0.837042 lr=0.001000 Epoch[067] Batch [0399]/[3760] Speed: 71.459701 samples/sec accuracy=78.519531 loss=0.837968 lr=0.001000 Epoch[067] Batch 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accuracy=78.345486 loss=0.849718 lr=0.001000 Epoch[067] Batch [0949]/[3760] Speed: 71.518975 samples/sec accuracy=78.291118 loss=0.850493 lr=0.001000 Epoch[067] Batch [0999]/[3760] Speed: 71.761900 samples/sec accuracy=78.312500 loss=0.849796 lr=0.001000 Epoch[067] Batch [1049]/[3760] Speed: 72.188517 samples/sec accuracy=78.315476 loss=0.847847 lr=0.001000 Epoch[067] Batch [1099]/[3760] Speed: 71.521553 samples/sec accuracy=78.346591 loss=0.847595 lr=0.001000 Epoch[067] Batch [1149]/[3760] Speed: 72.063836 samples/sec accuracy=78.330163 loss=0.847614 lr=0.001000 Epoch[067] Batch [1199]/[3760] Speed: 72.182761 samples/sec accuracy=78.324219 loss=0.848516 lr=0.001000 Epoch[067] Batch [1249]/[3760] Speed: 71.658576 samples/sec accuracy=78.338750 loss=0.848795 lr=0.001000 Epoch[067] Batch [1299]/[3760] Speed: 72.043851 samples/sec accuracy=78.368990 loss=0.847613 lr=0.001000 Epoch[067] Batch [1349]/[3760] Speed: 71.292240 samples/sec accuracy=78.325231 loss=0.848652 lr=0.001000 Epoch[067] 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accuracy=78.226351 loss=0.854690 lr=0.001000 Epoch[067] Batch [1899]/[3760] Speed: 72.541362 samples/sec accuracy=78.230263 loss=0.854614 lr=0.001000 Epoch[067] Batch [1949]/[3760] Speed: 71.708966 samples/sec accuracy=78.244391 loss=0.854244 lr=0.001000 Epoch[067] Batch [1999]/[3760] Speed: 71.842904 samples/sec accuracy=78.272656 loss=0.853304 lr=0.001000 Epoch[067] Batch [2049]/[3760] Speed: 71.936810 samples/sec accuracy=78.294207 loss=0.851929 lr=0.001000 Epoch[067] Batch [2099]/[3760] Speed: 72.240300 samples/sec accuracy=78.273810 loss=0.853058 lr=0.001000 Epoch[067] Batch [2149]/[3760] Speed: 71.757876 samples/sec accuracy=78.303779 loss=0.852533 lr=0.001000 Epoch[067] Batch [2199]/[3760] Speed: 71.853836 samples/sec accuracy=78.306818 loss=0.852022 lr=0.001000 Epoch[067] Batch [2249]/[3760] Speed: 70.972743 samples/sec accuracy=78.288889 loss=0.852280 lr=0.001000 Epoch[067] Batch [2299]/[3760] Speed: 71.462801 samples/sec accuracy=78.273777 loss=0.852149 lr=0.001000 Epoch[067] 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accuracy=78.245536 loss=0.853963 lr=0.001000 Epoch[067] Batch [2849]/[3760] Speed: 71.340888 samples/sec accuracy=78.243421 loss=0.854174 lr=0.001000 Epoch[067] Batch [2899]/[3760] Speed: 71.071704 samples/sec accuracy=78.240302 loss=0.853948 lr=0.001000 Epoch[067] Batch [2949]/[3760] Speed: 71.840393 samples/sec accuracy=78.220339 loss=0.854713 lr=0.001000 Epoch[067] Batch [2999]/[3760] Speed: 71.314253 samples/sec accuracy=78.226562 loss=0.854453 lr=0.001000 Epoch[067] Batch [3049]/[3760] Speed: 71.537536 samples/sec accuracy=78.231045 loss=0.854404 lr=0.001000 Epoch[067] Batch [3099]/[3760] Speed: 71.533213 samples/sec accuracy=78.252016 loss=0.854076 lr=0.001000 Epoch[067] Batch [3149]/[3760] Speed: 72.298033 samples/sec accuracy=78.250992 loss=0.854347 lr=0.001000 Epoch[067] Batch [3199]/[3760] Speed: 71.098265 samples/sec accuracy=78.244141 loss=0.854261 lr=0.001000 Epoch[067] Batch [3249]/[3760] Speed: 72.309474 samples/sec accuracy=78.225962 loss=0.854898 lr=0.001000 Epoch[067] 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accuracy=78.171667 loss=0.856733 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.312500 acc-top5=88.406250 Batch [0099]/[0303]: acc-top1=68.140625 acc-top5=87.625000 Batch [0149]/[0303]: acc-top1=67.500000 acc-top5=86.729167 Batch [0199]/[0303]: acc-top1=67.171875 acc-top5=86.648438 Batch [0249]/[0303]: acc-top1=66.993750 acc-top5=86.706250 Batch [0299]/[0303]: acc-top1=67.109375 acc-top5=86.703125 [Epoch 067] training: accuracy=78.166971 loss=0.857022 [Epoch 067] speed: 71 samples/sec time cost: 3646.721180 [Epoch 067] validation: acc-top1=67.161716 acc-top5=86.736799 loss=1.586063 Epoch[068] Batch [0049]/[3760] Speed: 48.721404 samples/sec accuracy=79.187500 loss=0.837574 lr=0.001000 Epoch[068] Batch [0099]/[3760] Speed: 70.840589 samples/sec accuracy=78.500000 loss=0.852837 lr=0.001000 Epoch[068] Batch [0149]/[3760] Speed: 71.856906 samples/sec accuracy=78.750000 loss=0.833039 lr=0.001000 Epoch[068] Batch [0199]/[3760] Speed: 72.008641 samples/sec accuracy=78.640625 loss=0.833869 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acc-top5=86.685231 loss=1.605441 Epoch[069] Batch [0049]/[3759] Speed: 48.645546 samples/sec accuracy=78.937500 loss=0.848244 lr=0.001000 Epoch[069] Batch [0099]/[3759] Speed: 70.503269 samples/sec accuracy=78.906250 loss=0.842508 lr=0.001000 Epoch[069] Batch [0149]/[3759] Speed: 71.394060 samples/sec accuracy=78.833333 loss=0.835236 lr=0.001000 Epoch[069] Batch [0199]/[3759] Speed: 71.085016 samples/sec accuracy=79.015625 loss=0.833916 lr=0.001000 Epoch[069] Batch [0249]/[3759] Speed: 72.511740 samples/sec accuracy=79.106250 loss=0.830069 lr=0.001000 Epoch[069] Batch [0299]/[3759] Speed: 71.208938 samples/sec accuracy=79.177083 loss=0.825719 lr=0.001000 Epoch[069] Batch [0349]/[3759] Speed: 71.135779 samples/sec accuracy=79.267857 loss=0.819301 lr=0.001000 Epoch[069] Batch [0399]/[3759] Speed: 71.301147 samples/sec accuracy=79.238281 loss=0.820746 lr=0.001000 Epoch[069] Batch [0449]/[3759] Speed: 71.835705 samples/sec accuracy=79.065972 loss=0.825402 lr=0.001000 Epoch[069] Batch 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accuracy=78.682566 loss=0.838446 lr=0.001000 Epoch[069] Batch [1949]/[3759] Speed: 72.535079 samples/sec accuracy=78.661058 loss=0.839510 lr=0.001000 Epoch[069] Batch [1999]/[3759] Speed: 71.391640 samples/sec accuracy=78.643750 loss=0.839292 lr=0.001000 Epoch[069] Batch [2049]/[3759] Speed: 72.135789 samples/sec accuracy=78.627287 loss=0.839182 lr=0.001000 Epoch[069] Batch [2099]/[3759] Speed: 71.001135 samples/sec accuracy=78.615327 loss=0.839514 lr=0.001000 Epoch[069] Batch [2149]/[3759] Speed: 71.069607 samples/sec accuracy=78.601744 loss=0.840323 lr=0.001000 Epoch[069] Batch [2199]/[3759] Speed: 71.240174 samples/sec accuracy=78.583097 loss=0.840162 lr=0.001000 Epoch[069] Batch [2249]/[3759] Speed: 71.683897 samples/sec accuracy=78.565972 loss=0.840204 lr=0.001000 Epoch[069] Batch [2299]/[3759] Speed: 71.880652 samples/sec accuracy=78.557065 loss=0.840863 lr=0.001000 Epoch[069] Batch [2349]/[3759] Speed: 72.048460 samples/sec accuracy=78.571144 loss=0.839857 lr=0.001000 Epoch[069] 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accuracy=78.557566 loss=0.841677 lr=0.001000 Epoch[069] Batch [2899]/[3759] Speed: 71.490937 samples/sec accuracy=78.551185 loss=0.841956 lr=0.001000 Epoch[069] Batch [2949]/[3759] Speed: 71.745613 samples/sec accuracy=78.539725 loss=0.842667 lr=0.001000 Epoch[069] Batch [2999]/[3759] Speed: 71.987360 samples/sec accuracy=78.531771 loss=0.843494 lr=0.001000 Epoch[069] Batch [3049]/[3759] Speed: 72.184064 samples/sec accuracy=78.522541 loss=0.843903 lr=0.001000 Epoch[069] Batch [3099]/[3759] Speed: 71.175844 samples/sec accuracy=78.524698 loss=0.843667 lr=0.001000 Epoch[069] Batch [3149]/[3759] Speed: 71.418081 samples/sec accuracy=78.519345 loss=0.843504 lr=0.001000 Epoch[069] Batch [3199]/[3759] Speed: 71.226606 samples/sec accuracy=78.520020 loss=0.843476 lr=0.001000 Epoch[069] Batch [3249]/[3759] Speed: 72.086505 samples/sec accuracy=78.500962 loss=0.843872 lr=0.001000 Epoch[069] Batch [3299]/[3759] Speed: 72.584361 samples/sec accuracy=78.524621 loss=0.842804 lr=0.001000 Epoch[069] 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[0099]/[0303]: acc-top1=68.031250 acc-top5=87.015625 Batch [0149]/[0303]: acc-top1=67.395833 acc-top5=86.250000 Batch [0199]/[0303]: acc-top1=67.109375 acc-top5=86.226562 Batch [0249]/[0303]: acc-top1=66.943750 acc-top5=86.350000 Batch [0299]/[0303]: acc-top1=66.958333 acc-top5=86.432292 [Epoch 069] training: accuracy=78.506169 loss=0.843635 [Epoch 069] speed: 71 samples/sec time cost: 3646.893502 [Epoch 069] validation: acc-top1=67.012170 acc-top5=86.463490 loss=1.638583 Epoch[070] Batch [0049]/[3760] Speed: 48.734402 samples/sec accuracy=77.906250 loss=0.871319 lr=0.001000 Epoch[070] Batch [0099]/[3760] Speed: 70.210111 samples/sec accuracy=78.328125 loss=0.854618 lr=0.001000 Epoch[070] Batch [0149]/[3760] Speed: 72.278147 samples/sec accuracy=78.406250 loss=0.860426 lr=0.001000 Epoch[070] Batch [0199]/[3760] Speed: 71.234216 samples/sec accuracy=78.570312 loss=0.849438 lr=0.001000 Epoch[070] Batch [0249]/[3760] Speed: 71.490598 samples/sec accuracy=78.487500 loss=0.847522 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acc-top5=86.458333 Batch [0199]/[0303]: acc-top1=66.875000 acc-top5=86.375000 Batch [0249]/[0303]: acc-top1=66.768750 acc-top5=86.387500 Batch [0299]/[0303]: acc-top1=66.885417 acc-top5=86.463542 [Epoch 071] training: accuracy=78.642786 loss=0.837789 [Epoch 071] speed: 71 samples/sec time cost: 3644.863738 [Epoch 071] validation: acc-top1=66.909035 acc-top5=86.504744 loss=1.631381 Epoch[072] Batch [0049]/[3759] Speed: 48.710227 samples/sec accuracy=77.718750 loss=0.847266 lr=0.001000 Epoch[072] Batch [0099]/[3759] Speed: 71.078152 samples/sec accuracy=78.406250 loss=0.828118 lr=0.001000 Epoch[072] Batch [0149]/[3759] Speed: 72.090786 samples/sec accuracy=78.562500 loss=0.818909 lr=0.001000 Epoch[072] Batch [0199]/[3759] Speed: 71.237595 samples/sec accuracy=78.843750 loss=0.817115 lr=0.001000 Epoch[072] Batch [0249]/[3759] Speed: 70.762404 samples/sec accuracy=79.143750 loss=0.809195 lr=0.001000 Epoch[072] Batch [0299]/[3759] Speed: 72.509179 samples/sec accuracy=79.078125 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accuracy=78.825397 loss=0.831183 lr=0.001000 Epoch[072] Batch [3199]/[3759] Speed: 71.686154 samples/sec accuracy=78.815918 loss=0.831675 lr=0.001000 Epoch[072] Batch [3249]/[3759] Speed: 72.493562 samples/sec accuracy=78.821635 loss=0.831698 lr=0.001000 Epoch[072] Batch [3299]/[3759] Speed: 71.366988 samples/sec accuracy=78.828125 loss=0.831518 lr=0.001000 Epoch[072] Batch [3349]/[3759] Speed: 71.814758 samples/sec accuracy=78.843750 loss=0.831180 lr=0.001000 Epoch[072] Batch [3399]/[3759] Speed: 72.145492 samples/sec accuracy=78.859375 loss=0.830667 lr=0.001000 Epoch[072] Batch [3449]/[3759] Speed: 71.863539 samples/sec accuracy=78.846920 loss=0.831013 lr=0.001000 Epoch[072] Batch [3499]/[3759] Speed: 71.477345 samples/sec accuracy=78.842411 loss=0.830926 lr=0.001000 Epoch[072] Batch [3549]/[3759] Speed: 71.681785 samples/sec accuracy=78.858275 loss=0.830629 lr=0.001000 Epoch[072] Batch [3599]/[3759] Speed: 71.568969 samples/sec accuracy=78.862413 loss=0.830606 lr=0.001000 Epoch[072] Batch [3649]/[3759] Speed: 71.466418 samples/sec accuracy=78.856164 loss=0.830671 lr=0.001000 Epoch[072] Batch [3699]/[3759] Speed: 71.772443 samples/sec accuracy=78.856419 loss=0.830948 lr=0.001000 Epoch[072] Batch [3749]/[3759] Speed: 80.550697 samples/sec accuracy=78.851250 loss=0.831396 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.250000 acc-top5=87.687500 Batch [0099]/[0303]: acc-top1=67.812500 acc-top5=87.390625 Batch [0149]/[0303]: acc-top1=67.385417 acc-top5=86.666667 Batch [0199]/[0303]: acc-top1=67.023438 acc-top5=86.617188 Batch [0249]/[0303]: acc-top1=66.837500 acc-top5=86.587500 Batch [0299]/[0303]: acc-top1=66.869792 acc-top5=86.677083 [Epoch 072] training: accuracy=78.852421 loss=0.831367 [Epoch 072] speed: 71 samples/sec time cost: 3639.344402 [Epoch 072] validation: acc-top1=66.898721 acc-top5=86.685231 loss=1.625448 Epoch[073] Batch [0049]/[3760] Speed: 48.722597 samples/sec accuracy=79.937500 loss=0.812734 lr=0.001000 Epoch[073] Batch [0099]/[3760] Speed: 70.393870 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lr=0.001000 Epoch[073] Batch [3449]/[3760] Speed: 72.424046 samples/sec accuracy=78.919837 loss=0.827236 lr=0.001000 Epoch[073] Batch [3499]/[3760] Speed: 71.277975 samples/sec accuracy=78.918750 loss=0.827479 lr=0.001000 Epoch[073] Batch [3549]/[3760] Speed: 71.515473 samples/sec accuracy=78.913732 loss=0.827287 lr=0.001000 Epoch[073] Batch [3599]/[3760] Speed: 71.758800 samples/sec accuracy=78.896701 loss=0.827913 lr=0.001000 Epoch[073] Batch [3649]/[3760] Speed: 71.806808 samples/sec accuracy=78.896832 loss=0.827744 lr=0.001000 Epoch[073] Batch [3699]/[3760] Speed: 71.984776 samples/sec accuracy=78.880912 loss=0.828401 lr=0.001000 Epoch[073] Batch [3749]/[3760] Speed: 79.916860 samples/sec accuracy=78.874167 loss=0.828542 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.875000 acc-top5=88.062500 Batch [0099]/[0303]: acc-top1=67.593750 acc-top5=87.453125 Batch [0149]/[0303]: acc-top1=67.239583 acc-top5=86.625000 Batch [0199]/[0303]: acc-top1=66.921875 acc-top5=86.500000 Batch [0249]/[0303]: acc-top1=66.806250 acc-top5=86.475000 Batch [0299]/[0303]: acc-top1=66.796875 acc-top5=86.557292 [Epoch 073] training: accuracy=78.864694 loss=0.828858 [Epoch 073] speed: 71 samples/sec time cost: 3640.079884 [Epoch 073] validation: acc-top1=66.841997 acc-top5=86.597566 loss=1.636993 Epoch[074] Batch [0049]/[3760] Speed: 48.571491 samples/sec accuracy=79.218750 loss=0.813391 lr=0.001000 Epoch[074] Batch [0099]/[3760] Speed: 71.143820 samples/sec accuracy=79.625000 loss=0.814157 lr=0.001000 Epoch[074] Batch [0149]/[3760] Speed: 71.871165 samples/sec accuracy=79.968750 loss=0.796243 lr=0.001000 Epoch[074] Batch [0199]/[3760] Speed: 71.627559 samples/sec accuracy=79.757812 loss=0.798064 lr=0.001000 Epoch[074] Batch [0249]/[3760] Speed: 71.577230 samples/sec accuracy=79.706250 loss=0.797721 lr=0.001000 Epoch[074] Batch [0299]/[3760] Speed: 71.770787 samples/sec accuracy=79.708333 loss=0.797961 lr=0.001000 Epoch[074] Batch [0349]/[3760] Speed: 72.520326 samples/sec 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accuracy=79.202148 loss=0.818853 lr=0.001000 Epoch[074] Batch [3249]/[3760] Speed: 72.139810 samples/sec accuracy=79.213462 loss=0.818294 lr=0.001000 Epoch[074] Batch [3299]/[3760] Speed: 71.418205 samples/sec accuracy=79.222064 loss=0.817828 lr=0.001000 Epoch[074] Batch [3349]/[3760] Speed: 71.727638 samples/sec accuracy=79.207090 loss=0.817729 lr=0.001000 Epoch[074] Batch [3399]/[3760] Speed: 71.819813 samples/sec accuracy=79.198989 loss=0.818008 lr=0.001000 Epoch[074] Batch [3449]/[3760] Speed: 71.072243 samples/sec accuracy=79.171649 loss=0.819182 lr=0.001000 Epoch[074] Batch [3499]/[3760] Speed: 72.525144 samples/sec accuracy=79.151339 loss=0.819887 lr=0.001000 Epoch[074] Batch [3549]/[3760] Speed: 71.138820 samples/sec accuracy=79.140845 loss=0.820158 lr=0.001000 Epoch[074] Batch [3599]/[3760] Speed: 71.772928 samples/sec accuracy=79.130208 loss=0.820081 lr=0.001000 Epoch[074] Batch [3649]/[3760] Speed: 72.003780 samples/sec accuracy=79.121575 loss=0.820407 lr=0.001000 Epoch[074] Batch [3699]/[3760] Speed: 72.256707 samples/sec accuracy=79.124155 loss=0.820373 lr=0.001000 Epoch[074] Batch [3749]/[3760] Speed: 79.275198 samples/sec accuracy=79.120417 loss=0.820542 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.781250 acc-top5=87.593750 Batch [0099]/[0303]: acc-top1=67.984375 acc-top5=87.218750 Batch [0149]/[0303]: acc-top1=67.270833 acc-top5=86.385417 Batch [0199]/[0303]: acc-top1=67.101562 acc-top5=86.359375 Batch [0249]/[0303]: acc-top1=66.887500 acc-top5=86.356250 Batch [0299]/[0303]: acc-top1=66.953125 acc-top5=86.406250 [Epoch 074] training: accuracy=79.123172 loss=0.820537 [Epoch 074] speed: 71 samples/sec time cost: 3639.558565 [Epoch 074] validation: acc-top1=66.965759 acc-top5=86.432550 loss=1.637526 Epoch[075] Batch [0049]/[3759] Speed: 49.012233 samples/sec accuracy=79.093750 loss=0.823411 lr=0.001000 Epoch[075] Batch [0099]/[3759] Speed: 70.932889 samples/sec accuracy=79.281250 loss=0.820197 lr=0.001000 Epoch[075] Batch [0149]/[3759] Speed: 71.699217 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lr=0.001000 Epoch[075] Batch [0649]/[3759] Speed: 71.528912 samples/sec accuracy=79.343750 loss=0.811982 lr=0.001000 Epoch[075] Batch [0699]/[3759] Speed: 71.883394 samples/sec accuracy=79.352679 loss=0.811308 lr=0.001000 Epoch[075] Batch [0749]/[3759] Speed: 72.379487 samples/sec accuracy=79.297917 loss=0.813250 lr=0.001000 Epoch[075] Batch [0799]/[3759] Speed: 71.275044 samples/sec accuracy=79.316406 loss=0.813889 lr=0.001000 Epoch[075] Batch [0849]/[3759] Speed: 71.164870 samples/sec accuracy=79.283088 loss=0.813540 lr=0.001000 Epoch[075] Batch [0899]/[3759] Speed: 72.309514 samples/sec accuracy=79.274306 loss=0.813784 lr=0.001000 Epoch[075] Batch [0949]/[3759] Speed: 72.142313 samples/sec accuracy=79.254934 loss=0.813313 lr=0.001000 Epoch[075] Batch [0999]/[3759] Speed: 71.461087 samples/sec accuracy=79.345312 loss=0.810501 lr=0.001000 Epoch[075] Batch [1049]/[3759] Speed: 71.878248 samples/sec accuracy=79.334821 loss=0.809636 lr=0.001000 Epoch[075] Batch [1099]/[3759] Speed: 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lr=0.001000 Epoch[075] Batch [1599]/[3759] Speed: 72.116301 samples/sec accuracy=79.319336 loss=0.809819 lr=0.001000 Epoch[075] Batch [1649]/[3759] Speed: 71.666457 samples/sec accuracy=79.296402 loss=0.810336 lr=0.001000 Epoch[075] Batch [1699]/[3759] Speed: 71.662447 samples/sec accuracy=79.287684 loss=0.811298 lr=0.001000 Epoch[075] Batch [1749]/[3759] Speed: 71.765838 samples/sec accuracy=79.300000 loss=0.810590 lr=0.001000 Epoch[075] Batch [1799]/[3759] Speed: 71.649205 samples/sec accuracy=79.270833 loss=0.811254 lr=0.001000 Epoch[075] Batch [1849]/[3759] Speed: 71.884217 samples/sec accuracy=79.259291 loss=0.811791 lr=0.001000 Epoch[075] Batch [1899]/[3759] Speed: 71.263083 samples/sec accuracy=79.244243 loss=0.812345 lr=0.001000 Epoch[075] Batch [1949]/[3759] Speed: 72.237097 samples/sec accuracy=79.235577 loss=0.812795 lr=0.001000 Epoch[075] Batch [1999]/[3759] Speed: 71.403066 samples/sec accuracy=79.242188 loss=0.812172 lr=0.001000 Epoch[075] Batch [2049]/[3759] Speed: 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lr=0.001000 Epoch[075] Batch [2549]/[3759] Speed: 70.711319 samples/sec accuracy=79.252451 loss=0.813014 lr=0.001000 Epoch[075] Batch [2599]/[3759] Speed: 71.268272 samples/sec accuracy=79.263822 loss=0.812500 lr=0.001000 Epoch[075] Batch [2649]/[3759] Speed: 72.353724 samples/sec accuracy=79.255307 loss=0.813334 lr=0.001000 Epoch[075] Batch [2699]/[3759] Speed: 71.610219 samples/sec accuracy=79.246528 loss=0.814118 lr=0.001000 Epoch[075] Batch [2749]/[3759] Speed: 71.744478 samples/sec accuracy=79.230114 loss=0.814188 lr=0.001000 Epoch[075] Batch [2799]/[3759] Speed: 72.227640 samples/sec accuracy=79.236607 loss=0.814088 lr=0.001000 Epoch[075] Batch [2849]/[3759] Speed: 72.147327 samples/sec accuracy=79.229167 loss=0.814400 lr=0.001000 Epoch[075] Batch [2899]/[3759] Speed: 72.142385 samples/sec accuracy=79.212823 loss=0.814850 lr=0.001000 Epoch[075] Batch [2949]/[3759] Speed: 70.995581 samples/sec accuracy=79.223517 loss=0.814740 lr=0.001000 Epoch[075] Batch [2999]/[3759] Speed: 72.224759 samples/sec accuracy=79.231250 loss=0.814490 lr=0.001000 Epoch[075] Batch [3049]/[3759] Speed: 71.794245 samples/sec accuracy=79.233607 loss=0.814400 lr=0.001000 Epoch[075] Batch [3099]/[3759] Speed: 71.561163 samples/sec accuracy=79.232863 loss=0.814549 lr=0.001000 Epoch[075] Batch [3149]/[3759] Speed: 71.734675 samples/sec accuracy=79.212798 loss=0.815127 lr=0.001000 Epoch[075] Batch [3199]/[3759] Speed: 72.120061 samples/sec accuracy=79.206543 loss=0.815061 lr=0.001000 Epoch[075] Batch [3249]/[3759] Speed: 71.524472 samples/sec accuracy=79.205288 loss=0.814822 lr=0.001000 Epoch[075] Batch [3299]/[3759] Speed: 71.842710 samples/sec accuracy=79.195076 loss=0.815290 lr=0.001000 Epoch[075] Batch [3349]/[3759] Speed: 72.250325 samples/sec accuracy=79.176306 loss=0.815989 lr=0.001000 Epoch[075] Batch [3399]/[3759] Speed: 71.556785 samples/sec accuracy=79.188879 loss=0.815786 lr=0.001000 Epoch[075] Batch [3449]/[3759] Speed: 72.189220 samples/sec accuracy=79.197917 loss=0.815460 lr=0.001000 Epoch[075] Batch [3499]/[3759] Speed: 71.340822 samples/sec accuracy=79.192411 loss=0.815881 lr=0.001000 Epoch[075] Batch [3549]/[3759] Speed: 71.671693 samples/sec accuracy=79.183099 loss=0.816070 lr=0.001000 Epoch[075] Batch [3599]/[3759] Speed: 71.582407 samples/sec accuracy=79.193142 loss=0.815931 lr=0.001000 Epoch[075] Batch [3649]/[3759] Speed: 72.422447 samples/sec accuracy=79.190068 loss=0.816033 lr=0.001000 Epoch[075] Batch [3699]/[3759] Speed: 71.555052 samples/sec accuracy=79.187078 loss=0.816176 lr=0.001000 Epoch[075] Batch [3749]/[3759] Speed: 80.435690 samples/sec accuracy=79.173333 loss=0.816510 lr=0.001000 Batch [0049]/[0303]: acc-top1=67.406250 acc-top5=87.187500 Batch [0099]/[0303]: acc-top1=67.375000 acc-top5=86.828125 Batch [0149]/[0303]: acc-top1=66.906250 acc-top5=85.927083 Batch [0199]/[0303]: acc-top1=66.757812 acc-top5=85.906250 Batch [0249]/[0303]: acc-top1=66.637500 acc-top5=85.993750 Batch [0299]/[0303]: acc-top1=66.651042 acc-top5=86.031250 [Epoch 075] training: accuracy=79.172070 loss=0.816571 [Epoch 075] speed: 71 samples/sec time cost: 3637.900357 [Epoch 075] validation: acc-top1=66.682137 acc-top5=86.097360 loss=1.677040 Epoch[076] Batch [0049]/[3760] Speed: 48.772130 samples/sec accuracy=80.375000 loss=0.757271 lr=0.001000 Epoch[076] Batch [0099]/[3760] Speed: 70.131836 samples/sec accuracy=79.703125 loss=0.793563 lr=0.001000 Epoch[076] Batch [0149]/[3760] Speed: 71.749757 samples/sec accuracy=80.187500 loss=0.779117 lr=0.001000 Epoch[076] Batch [0199]/[3760] Speed: 72.039245 samples/sec accuracy=79.828125 loss=0.788956 lr=0.001000 Epoch[076] Batch [0249]/[3760] Speed: 70.905121 samples/sec accuracy=79.843750 loss=0.790701 lr=0.001000 Epoch[076] Batch [0299]/[3760] Speed: 72.219605 samples/sec accuracy=79.750000 loss=0.790978 lr=0.001000 Epoch[076] Batch [0349]/[3760] Speed: 71.568937 samples/sec accuracy=79.687500 loss=0.791320 lr=0.001000 Epoch[076] Batch [0399]/[3760] Speed: 71.613824 samples/sec accuracy=79.621094 loss=0.792689 lr=0.001000 Epoch[076] Batch [0449]/[3760] Speed: 71.645786 samples/sec accuracy=79.611111 loss=0.793553 lr=0.001000 Epoch[076] Batch [0499]/[3760] Speed: 71.502427 samples/sec accuracy=79.484375 loss=0.798287 lr=0.001000 Epoch[076] Batch [0549]/[3760] Speed: 71.478117 samples/sec accuracy=79.491477 loss=0.799744 lr=0.001000 Epoch[076] Batch [0599]/[3760] Speed: 72.016231 samples/sec accuracy=79.552083 loss=0.798781 lr=0.001000 Epoch[076] Batch [0649]/[3760] Speed: 71.850305 samples/sec accuracy=79.600962 loss=0.796332 lr=0.001000 Epoch[076] Batch [0699]/[3760] Speed: 71.622539 samples/sec accuracy=79.578125 loss=0.797333 lr=0.001000 Epoch[076] Batch [0749]/[3760] Speed: 72.109587 samples/sec accuracy=79.497917 loss=0.799159 lr=0.001000 Epoch[076] Batch [0799]/[3760] Speed: 71.750864 samples/sec accuracy=79.500000 loss=0.798163 lr=0.001000 Epoch[076] Batch [0849]/[3760] Speed: 70.808751 samples/sec accuracy=79.463235 loss=0.799193 lr=0.001000 Epoch[076] 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accuracy=79.397596 loss=0.806971 lr=0.001000 Epoch[076] Batch [3299]/[3760] Speed: 71.518506 samples/sec accuracy=79.388258 loss=0.807111 lr=0.001000 Epoch[076] Batch [3349]/[3760] Speed: 71.788083 samples/sec accuracy=79.378731 loss=0.807349 lr=0.001000 Epoch[076] Batch [3399]/[3760] Speed: 71.428711 samples/sec accuracy=79.365349 loss=0.807989 lr=0.001000 Epoch[076] Batch [3449]/[3760] Speed: 72.257242 samples/sec accuracy=79.366848 loss=0.807957 lr=0.001000 Epoch[076] Batch [3499]/[3760] Speed: 71.141815 samples/sec accuracy=79.344643 loss=0.808773 lr=0.001000 Epoch[076] Batch [3549]/[3760] Speed: 71.977937 samples/sec accuracy=79.343750 loss=0.809135 lr=0.001000 Epoch[076] Batch [3599]/[3760] Speed: 71.637595 samples/sec accuracy=79.322049 loss=0.809880 lr=0.001000 Epoch[076] Batch [3649]/[3760] Speed: 72.152173 samples/sec accuracy=79.328339 loss=0.809634 lr=0.001000 Epoch[076] Batch [3699]/[3760] Speed: 72.348809 samples/sec accuracy=79.314189 loss=0.809837 lr=0.001000 Epoch[076] Batch [3749]/[3760] Speed: 79.425151 samples/sec accuracy=79.310417 loss=0.809982 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.062500 acc-top5=87.625000 Batch [0099]/[0303]: acc-top1=67.968750 acc-top5=87.125000 Batch [0149]/[0303]: acc-top1=67.312500 acc-top5=86.385417 Batch [0199]/[0303]: acc-top1=67.015625 acc-top5=86.343750 Batch [0249]/[0303]: acc-top1=66.806250 acc-top5=86.312500 Batch [0299]/[0303]: acc-top1=66.739583 acc-top5=86.312500 [Epoch 076] training: accuracy=79.318484 loss=0.809717 [Epoch 076] speed: 71 samples/sec time cost: 3637.071455 [Epoch 076] validation: acc-top1=66.785272 acc-top5=86.360355 loss=1.670530 Epoch[077] Batch [0049]/[3760] Speed: 48.158517 samples/sec accuracy=78.843750 loss=0.820245 lr=0.001000 Epoch[077] Batch [0099]/[3760] Speed: 70.786353 samples/sec accuracy=79.468750 loss=0.806309 lr=0.001000 Epoch[077] Batch [0149]/[3760] Speed: 71.637515 samples/sec accuracy=79.656250 loss=0.794182 lr=0.001000 Epoch[077] Batch [0199]/[3760] Speed: 71.089818 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lr=0.001000 Epoch[077] Batch [2599]/[3760] Speed: 71.368122 samples/sec accuracy=79.519832 loss=0.804754 lr=0.001000 Epoch[077] Batch [2649]/[3760] Speed: 71.162057 samples/sec accuracy=79.531250 loss=0.804824 lr=0.001000 Epoch[077] Batch [2699]/[3760] Speed: 71.566444 samples/sec accuracy=79.531829 loss=0.804149 lr=0.001000 Epoch[077] Batch [2749]/[3760] Speed: 71.949833 samples/sec accuracy=79.515341 loss=0.804768 lr=0.001000 Epoch[077] Batch [2799]/[3760] Speed: 71.461426 samples/sec accuracy=79.525112 loss=0.804070 lr=0.001000 Epoch[077] Batch [2849]/[3760] Speed: 71.203549 samples/sec accuracy=79.516447 loss=0.804140 lr=0.001000 Epoch[077] Batch [2899]/[3760] Speed: 71.655970 samples/sec accuracy=79.522629 loss=0.804102 lr=0.001000 Epoch[077] Batch [2949]/[3760] Speed: 72.603618 samples/sec accuracy=79.524364 loss=0.804549 lr=0.001000 Epoch[077] Batch [2999]/[3760] Speed: 71.311901 samples/sec accuracy=79.528125 loss=0.804401 lr=0.001000 Epoch[077] Batch [3049]/[3760] Speed: 71.719375 samples/sec accuracy=79.497951 loss=0.805286 lr=0.001000 Epoch[077] Batch [3099]/[3760] Speed: 71.375973 samples/sec accuracy=79.488911 loss=0.805759 lr=0.001000 Epoch[077] Batch [3149]/[3760] Speed: 71.846324 samples/sec accuracy=79.482639 loss=0.806405 lr=0.001000 Epoch[077] Batch [3199]/[3760] Speed: 70.511960 samples/sec accuracy=79.461426 loss=0.807467 lr=0.001000 Epoch[077] Batch [3249]/[3760] Speed: 72.866514 samples/sec accuracy=79.463942 loss=0.807422 lr=0.001000 Epoch[077] Batch [3299]/[3760] Speed: 71.754984 samples/sec accuracy=79.474905 loss=0.806813 lr=0.001000 Epoch[077] Batch [3349]/[3760] Speed: 71.753348 samples/sec accuracy=79.463619 loss=0.806933 lr=0.001000 Epoch[077] Batch [3399]/[3760] Speed: 71.479271 samples/sec accuracy=79.455423 loss=0.807107 lr=0.001000 Epoch[077] Batch [3449]/[3760] Speed: 71.936004 samples/sec accuracy=79.440670 loss=0.807616 lr=0.001000 Epoch[077] Batch [3499]/[3760] Speed: 72.094407 samples/sec accuracy=79.445536 loss=0.807674 lr=0.001000 Epoch[077] Batch [3549]/[3760] Speed: 71.757468 samples/sec accuracy=79.440141 loss=0.807713 lr=0.001000 Epoch[077] Batch [3599]/[3760] Speed: 70.869535 samples/sec accuracy=79.418837 loss=0.808266 lr=0.001000 Epoch[077] Batch [3649]/[3760] Speed: 71.527710 samples/sec accuracy=79.420377 loss=0.808348 lr=0.001000 Epoch[077] Batch [3699]/[3760] Speed: 71.721941 samples/sec accuracy=79.411318 loss=0.808322 lr=0.001000 Epoch[077] Batch [3749]/[3760] Speed: 79.560844 samples/sec accuracy=79.391250 loss=0.808542 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.312500 acc-top5=87.406250 Batch [0099]/[0303]: acc-top1=68.109375 acc-top5=87.078125 Batch [0149]/[0303]: acc-top1=67.489583 acc-top5=86.197917 Batch [0199]/[0303]: acc-top1=67.046875 acc-top5=86.148438 Batch [0249]/[0303]: acc-top1=66.887500 acc-top5=86.225000 Batch [0299]/[0303]: acc-top1=66.838542 acc-top5=86.281250 [Epoch 077] training: accuracy=79.392869 loss=0.808445 [Epoch 077] speed: 71 samples/sec time cost: 3643.291483 [Epoch 077] validation: acc-top1=66.883251 acc-top5=86.324257 loss=1.679073 Epoch[078] Batch [0049]/[3759] Speed: 48.764303 samples/sec accuracy=80.250000 loss=0.784291 lr=0.001000 Epoch[078] Batch [0099]/[3759] Speed: 70.549921 samples/sec accuracy=80.406250 loss=0.771164 lr=0.001000 Epoch[078] Batch [0149]/[3759] Speed: 71.683387 samples/sec accuracy=80.229167 loss=0.772795 lr=0.001000 Epoch[078] Batch [0199]/[3759] Speed: 71.644840 samples/sec accuracy=79.960938 loss=0.779343 lr=0.001000 Epoch[078] Batch [0249]/[3759] Speed: 71.449737 samples/sec accuracy=80.031250 loss=0.775099 lr=0.001000 Epoch[078] Batch [0299]/[3759] Speed: 72.570674 samples/sec accuracy=79.864583 loss=0.779903 lr=0.001000 Epoch[078] Batch [0349]/[3759] Speed: 71.462090 samples/sec accuracy=79.910714 loss=0.779893 lr=0.001000 Epoch[078] Batch [0399]/[3759] Speed: 71.692282 samples/sec accuracy=79.945312 loss=0.780519 lr=0.001000 Epoch[078] Batch [0449]/[3759] Speed: 71.055021 samples/sec accuracy=80.017361 loss=0.776016 lr=0.001000 Epoch[078] Batch [0499]/[3759] Speed: 72.197916 samples/sec accuracy=79.937500 loss=0.777280 lr=0.001000 Epoch[078] Batch [0549]/[3759] Speed: 71.910554 samples/sec accuracy=79.764205 loss=0.782519 lr=0.001000 Epoch[078] Batch [0599]/[3759] Speed: 71.754939 samples/sec accuracy=79.796875 loss=0.782150 lr=0.001000 Epoch[078] Batch [0649]/[3759] Speed: 71.386037 samples/sec accuracy=79.766827 loss=0.783746 lr=0.001000 Epoch[078] Batch [0699]/[3759] Speed: 71.450831 samples/sec accuracy=79.727679 loss=0.784971 lr=0.001000 Epoch[078] Batch [0749]/[3759] Speed: 72.728857 samples/sec accuracy=79.704167 loss=0.787086 lr=0.001000 Epoch[078] Batch [0799]/[3759] Speed: 72.384117 samples/sec accuracy=79.623047 loss=0.791254 lr=0.001000 Epoch[078] Batch [0849]/[3759] Speed: 70.422398 samples/sec accuracy=79.681985 loss=0.791047 lr=0.001000 Epoch[078] Batch [0899]/[3759] Speed: 73.348219 samples/sec accuracy=79.720486 loss=0.790958 lr=0.001000 Epoch[078] 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accuracy=79.449811 loss=0.805226 lr=0.001000 Epoch[078] Batch [3349]/[3759] Speed: 71.710477 samples/sec accuracy=79.444030 loss=0.805465 lr=0.001000 Epoch[078] Batch [3399]/[3759] Speed: 71.723975 samples/sec accuracy=79.444853 loss=0.805057 lr=0.001000 Epoch[078] Batch [3449]/[3759] Speed: 72.399715 samples/sec accuracy=79.456975 loss=0.804825 lr=0.001000 Epoch[078] Batch [3499]/[3759] Speed: 72.373427 samples/sec accuracy=79.454018 loss=0.805233 lr=0.001000 Epoch[078] Batch [3549]/[3759] Speed: 71.964978 samples/sec accuracy=79.457306 loss=0.804867 lr=0.001000 Epoch[078] Batch [3599]/[3759] Speed: 71.747908 samples/sec accuracy=79.448351 loss=0.805366 lr=0.001000 Epoch[078] Batch [3649]/[3759] Speed: 71.104995 samples/sec accuracy=79.458904 loss=0.804990 lr=0.001000 Epoch[078] Batch [3699]/[3759] Speed: 71.430436 samples/sec accuracy=79.467061 loss=0.805149 lr=0.001000 Epoch[078] Batch [3749]/[3759] Speed: 80.043800 samples/sec accuracy=79.466667 loss=0.805267 lr=0.001000 Batch [0049]/[0303]: acc-top1=68.187500 acc-top5=87.531250 Batch [0099]/[0303]: acc-top1=67.828125 acc-top5=87.296875 Batch [0149]/[0303]: acc-top1=67.156250 acc-top5=86.437500 Batch [0199]/[0303]: acc-top1=67.085938 acc-top5=86.453125 Batch [0249]/[0303]: acc-top1=66.850000 acc-top5=86.331250 Batch [0299]/[0303]: acc-top1=66.843750 acc-top5=86.286458 [Epoch 078] training: accuracy=79.473015 loss=0.805083 [Epoch 078] speed: 71 samples/sec time cost: 3639.399458 [Epoch 078] validation: acc-top1=66.888408 acc-top5=86.313944 loss=1.656230 Epoch[079] Batch [0049]/[3760] Speed: 48.952730 samples/sec accuracy=80.687500 loss=0.778487 lr=0.001000 Epoch[079] Batch [0099]/[3760] Speed: 70.364137 samples/sec accuracy=80.500000 loss=0.771681 lr=0.001000 Epoch[079] Batch [0149]/[3760] Speed: 71.971312 samples/sec accuracy=80.416667 loss=0.778576 lr=0.001000 Epoch[079] Batch [0199]/[3760] Speed: 70.528088 samples/sec accuracy=80.156250 loss=0.782329 lr=0.001000 Epoch[079] Batch [0249]/[3760] Speed: 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lr=0.001000 Epoch[079] Batch [2649]/[3760] Speed: 71.733895 samples/sec accuracy=79.746462 loss=0.794668 lr=0.001000 Epoch[079] Batch [2699]/[3760] Speed: 71.406147 samples/sec accuracy=79.734375 loss=0.794894 lr=0.001000 Epoch[079] Batch [2749]/[3760] Speed: 72.080274 samples/sec accuracy=79.717614 loss=0.795413 lr=0.001000 Epoch[079] Batch [2799]/[3760] Speed: 70.731405 samples/sec accuracy=79.732701 loss=0.794710 lr=0.001000 Epoch[079] Batch [2849]/[3760] Speed: 71.684238 samples/sec accuracy=79.737939 loss=0.794530 lr=0.001000 Epoch[079] Batch [2899]/[3760] Speed: 71.796200 samples/sec accuracy=79.731142 loss=0.795560 lr=0.001000 Epoch[079] Batch [2949]/[3760] Speed: 71.955215 samples/sec accuracy=79.740996 loss=0.795257 lr=0.001000 Epoch[079] Batch [2999]/[3760] Speed: 71.476126 samples/sec accuracy=79.742188 loss=0.795032 lr=0.001000 Epoch[079] Batch [3049]/[3760] Speed: 71.683699 samples/sec accuracy=79.722848 loss=0.795652 lr=0.001000 Epoch[079] Batch [3099]/[3760] Speed: 71.784905 samples/sec accuracy=79.714718 loss=0.796306 lr=0.001000 Epoch[079] Batch [3149]/[3760] Speed: 71.858840 samples/sec accuracy=79.718254 loss=0.796195 lr=0.001000 Epoch[079] Batch [3199]/[3760] Speed: 71.922867 samples/sec accuracy=79.706055 loss=0.796976 lr=0.001000 Epoch[079] Batch [3249]/[3760] Speed: 71.260883 samples/sec accuracy=79.697115 loss=0.796602 lr=0.001000 Epoch[079] Batch [3299]/[3760] Speed: 72.038540 samples/sec accuracy=79.673295 loss=0.797492 lr=0.001000 Epoch[079] Batch [3349]/[3760] Speed: 71.317222 samples/sec accuracy=79.670243 loss=0.797661 lr=0.001000 Epoch[079] Batch [3399]/[3760] Speed: 71.404377 samples/sec accuracy=79.657629 loss=0.797812 lr=0.001000 Epoch[079] Batch [3449]/[3760] Speed: 71.882240 samples/sec accuracy=79.662591 loss=0.797204 lr=0.001000 Epoch[079] Batch [3499]/[3760] Speed: 71.426816 samples/sec accuracy=79.665625 loss=0.797098 lr=0.001000 Epoch[079] Batch [3549]/[3760] Speed: 71.841713 samples/sec accuracy=79.670775 loss=0.797147 lr=0.001000 Epoch[079] Batch [3599]/[3760] Speed: 72.311236 samples/sec accuracy=79.665365 loss=0.797301 lr=0.001000 Epoch[079] Batch [3649]/[3760] Speed: 71.484133 samples/sec accuracy=79.658390 loss=0.797476 lr=0.001000 Epoch[079] Batch [3699]/[3760] Speed: 71.234310 samples/sec accuracy=79.640203 loss=0.797720 lr=0.001000 Epoch[079] Batch [3749]/[3760] Speed: 79.459275 samples/sec accuracy=79.647917 loss=0.797233 lr=0.000100 Batch [0049]/[0303]: acc-top1=67.937500 acc-top5=87.750000 Batch [0099]/[0303]: acc-top1=67.593750 acc-top5=87.375000 Batch [0149]/[0303]: acc-top1=66.947917 acc-top5=86.395833 Batch [0199]/[0303]: acc-top1=66.867188 acc-top5=86.328125 Batch [0249]/[0303]: acc-top1=66.575000 acc-top5=86.300000 Batch [0299]/[0303]: acc-top1=66.625000 acc-top5=86.338542 [Epoch 079] training: accuracy=79.650100 loss=0.797320 [Epoch 079] speed: 71 samples/sec time cost: 3640.966609 [Epoch 079] validation: acc-top1=66.651196 acc-top5=86.365512 loss=1.680638 Epoch[080] Batch 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accuracy=81.100911 loss=0.743310 lr=0.000100 Epoch[080] Batch [2449]/[3760] Speed: 71.785120 samples/sec accuracy=81.115434 loss=0.742813 lr=0.000100 Epoch[080] Batch [2499]/[3760] Speed: 71.886184 samples/sec accuracy=81.103125 loss=0.743104 lr=0.000100 Epoch[080] Batch [2549]/[3760] Speed: 71.726025 samples/sec accuracy=81.099877 loss=0.743337 lr=0.000100 Epoch[080] Batch [2599]/[3760] Speed: 72.016269 samples/sec accuracy=81.125601 loss=0.742823 lr=0.000100 Epoch[080] Batch [2649]/[3760] Speed: 70.199090 samples/sec accuracy=81.133255 loss=0.741941 lr=0.000100 Epoch[080] Batch [2699]/[3760] Speed: 72.498327 samples/sec accuracy=81.140625 loss=0.741603 lr=0.000100 Epoch[080] Batch [2749]/[3760] Speed: 71.586409 samples/sec accuracy=81.147159 loss=0.741201 lr=0.000100 Epoch[080] Batch [2799]/[3760] Speed: 71.885133 samples/sec accuracy=81.165737 loss=0.740748 lr=0.000100 Epoch[080] Batch [2849]/[3760] Speed: 71.929091 samples/sec accuracy=81.173794 loss=0.740681 lr=0.000100 Epoch[080] 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accuracy=81.275653 loss=0.737619 lr=0.000100 Epoch[080] Batch [3399]/[3760] Speed: 71.653796 samples/sec accuracy=81.279412 loss=0.737627 lr=0.000100 Epoch[080] Batch [3449]/[3760] Speed: 71.832433 samples/sec accuracy=81.302083 loss=0.736941 lr=0.000100 Epoch[080] Batch [3499]/[3760] Speed: 71.370556 samples/sec accuracy=81.300893 loss=0.737270 lr=0.000100 Epoch[080] Batch [3549]/[3760] Speed: 71.722169 samples/sec accuracy=81.305898 loss=0.737070 lr=0.000100 Epoch[080] Batch [3599]/[3760] Speed: 70.962288 samples/sec accuracy=81.319010 loss=0.736410 lr=0.000100 Epoch[080] Batch [3649]/[3760] Speed: 71.325707 samples/sec accuracy=81.320634 loss=0.736315 lr=0.000100 Epoch[080] Batch [3699]/[3760] Speed: 71.533226 samples/sec accuracy=81.316301 loss=0.736634 lr=0.000100 Epoch[080] Batch [3749]/[3760] Speed: 79.993605 samples/sec accuracy=81.322500 loss=0.736461 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.656250 acc-top5=88.000000 Batch [0099]/[0303]: acc-top1=68.703125 acc-top5=87.578125 Batch [0149]/[0303]: acc-top1=68.062500 acc-top5=86.656250 Batch [0199]/[0303]: acc-top1=67.890625 acc-top5=86.539062 Batch [0249]/[0303]: acc-top1=67.681250 acc-top5=86.468750 Batch [0299]/[0303]: acc-top1=67.723958 acc-top5=86.484375 [Epoch 080] training: accuracy=81.321476 loss=0.736518 [Epoch 080] speed: 71 samples/sec time cost: 3643.787362 [Epoch 080] validation: acc-top1=67.749587 acc-top5=86.509901 loss=1.626607 Epoch[081] Batch [0049]/[3759] Speed: 48.874961 samples/sec accuracy=81.468750 loss=0.731460 lr=0.000100 Epoch[081] Batch [0099]/[3759] Speed: 70.405778 samples/sec accuracy=81.734375 loss=0.724627 lr=0.000100 Epoch[081] Batch [0149]/[3759] Speed: 71.730737 samples/sec accuracy=81.927083 loss=0.715621 lr=0.000100 Epoch[081] Batch [0199]/[3759] Speed: 71.372784 samples/sec accuracy=81.953125 loss=0.715061 lr=0.000100 Epoch[081] Batch [0249]/[3759] Speed: 71.767492 samples/sec accuracy=81.981250 loss=0.716969 lr=0.000100 Epoch[081] Batch [0299]/[3759] 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accuracy=81.681985 loss=0.719870 lr=0.000100 Epoch[081] Batch [1749]/[3759] Speed: 72.063403 samples/sec accuracy=81.669643 loss=0.719652 lr=0.000100 Epoch[081] Batch [1799]/[3759] Speed: 70.421646 samples/sec accuracy=81.706597 loss=0.718449 lr=0.000100 Epoch[081] Batch [1849]/[3759] Speed: 72.311743 samples/sec accuracy=81.691723 loss=0.718838 lr=0.000100 Epoch[081] Batch [1899]/[3759] Speed: 71.364506 samples/sec accuracy=81.679276 loss=0.719507 lr=0.000100 Epoch[081] Batch [1949]/[3759] Speed: 71.518047 samples/sec accuracy=81.689103 loss=0.719735 lr=0.000100 Epoch[081] Batch [1999]/[3759] Speed: 71.984369 samples/sec accuracy=81.712500 loss=0.718804 lr=0.000100 Epoch[081] Batch [2049]/[3759] Speed: 71.135969 samples/sec accuracy=81.750000 loss=0.717701 lr=0.000100 Epoch[081] Batch [2099]/[3759] Speed: 72.344311 samples/sec accuracy=81.749256 loss=0.718170 lr=0.000100 Epoch[081] Batch [2149]/[3759] Speed: 71.868127 samples/sec accuracy=81.754360 loss=0.717807 lr=0.000100 Epoch[081] 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accuracy=81.737028 loss=0.718998 lr=0.000100 Epoch[081] Batch [2699]/[3759] Speed: 71.745592 samples/sec accuracy=81.730903 loss=0.719356 lr=0.000100 Epoch[081] Batch [2749]/[3759] Speed: 72.134435 samples/sec accuracy=81.742045 loss=0.719062 lr=0.000100 Epoch[081] Batch [2799]/[3759] Speed: 71.670517 samples/sec accuracy=81.747768 loss=0.718410 lr=0.000100 Epoch[081] Batch [2849]/[3759] Speed: 71.662266 samples/sec accuracy=81.748355 loss=0.718552 lr=0.000100 Epoch[081] Batch [2899]/[3759] Speed: 70.674357 samples/sec accuracy=81.741379 loss=0.718493 lr=0.000100 Epoch[081] Batch [2949]/[3759] Speed: 71.809846 samples/sec accuracy=81.734110 loss=0.718887 lr=0.000100 Epoch[081] Batch [2999]/[3759] Speed: 71.267209 samples/sec accuracy=81.747917 loss=0.718728 lr=0.000100 Epoch[081] Batch [3049]/[3759] Speed: 72.346074 samples/sec accuracy=81.744877 loss=0.718774 lr=0.000100 Epoch[081] Batch [3099]/[3759] Speed: 71.863157 samples/sec accuracy=81.746976 loss=0.718675 lr=0.000100 Epoch[081] Batch [3149]/[3759] Speed: 71.194395 samples/sec accuracy=81.746528 loss=0.718550 lr=0.000100 Epoch[081] Batch [3199]/[3759] Speed: 71.962393 samples/sec accuracy=81.753906 loss=0.718379 lr=0.000100 Epoch[081] Batch [3249]/[3759] Speed: 71.398385 samples/sec accuracy=81.752885 loss=0.718289 lr=0.000100 Epoch[081] Batch [3299]/[3759] Speed: 71.877848 samples/sec accuracy=81.752367 loss=0.718469 lr=0.000100 Epoch[081] Batch [3349]/[3759] Speed: 71.558857 samples/sec accuracy=81.753265 loss=0.718362 lr=0.000100 Epoch[081] Batch [3399]/[3759] Speed: 71.767379 samples/sec accuracy=81.761949 loss=0.718179 lr=0.000100 Epoch[081] Batch [3449]/[3759] Speed: 71.502600 samples/sec accuracy=81.776721 loss=0.717657 lr=0.000100 Epoch[081] Batch [3499]/[3759] Speed: 72.525294 samples/sec accuracy=81.773214 loss=0.717618 lr=0.000100 Epoch[081] Batch [3549]/[3759] Speed: 71.593724 samples/sec accuracy=81.788292 loss=0.717478 lr=0.000100 Epoch[081] Batch [3599]/[3759] Speed: 71.840827 samples/sec accuracy=81.787326 loss=0.718039 lr=0.000100 Epoch[081] Batch [3649]/[3759] Speed: 71.843946 samples/sec accuracy=81.793236 loss=0.717578 lr=0.000100 Epoch[081] Batch [3699]/[3759] Speed: 71.570203 samples/sec accuracy=81.809966 loss=0.716619 lr=0.000100 Epoch[081] Batch [3749]/[3759] Speed: 80.271071 samples/sec accuracy=81.815417 loss=0.716569 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.031250 acc-top5=88.375000 Batch [0099]/[0303]: acc-top1=68.796875 acc-top5=87.703125 Batch [0149]/[0303]: acc-top1=68.010417 acc-top5=86.875000 Batch [0199]/[0303]: acc-top1=67.937500 acc-top5=86.773438 Batch [0249]/[0303]: acc-top1=67.643750 acc-top5=86.750000 Batch [0299]/[0303]: acc-top1=67.635417 acc-top5=86.791667 [Epoch 081] training: accuracy=81.818220 loss=0.716536 [Epoch 081] speed: 71 samples/sec time cost: 3641.739219 [Epoch 081] validation: acc-top1=67.682550 acc-top5=86.819307 loss=1.636093 Epoch[082] Batch [0049]/[3760] Speed: 48.909181 samples/sec accuracy=82.781250 loss=0.699455 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lr=0.000100 Epoch[082] Batch [2949]/[3760] Speed: 71.767216 samples/sec accuracy=81.905720 loss=0.707926 lr=0.000100 Epoch[082] Batch [2999]/[3760] Speed: 70.950173 samples/sec accuracy=81.901562 loss=0.708102 lr=0.000100 Epoch[082] Batch [3049]/[3760] Speed: 71.463830 samples/sec accuracy=81.892930 loss=0.708187 lr=0.000100 Epoch[082] Batch [3099]/[3760] Speed: 72.028982 samples/sec accuracy=81.890121 loss=0.708567 lr=0.000100 Epoch[082] Batch [3149]/[3760] Speed: 71.395807 samples/sec accuracy=81.892857 loss=0.708462 lr=0.000100 Epoch[082] Batch [3199]/[3760] Speed: 71.499578 samples/sec accuracy=81.889160 loss=0.708492 lr=0.000100 Epoch[082] Batch [3249]/[3760] Speed: 71.520712 samples/sec accuracy=81.883173 loss=0.708528 lr=0.000100 Epoch[082] Batch [3299]/[3760] Speed: 71.791708 samples/sec accuracy=81.868371 loss=0.709596 lr=0.000100 Epoch[082] Batch [3349]/[3760] Speed: 71.751289 samples/sec accuracy=81.880597 loss=0.709192 lr=0.000100 Epoch[082] Batch [3399]/[3760] Speed: 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acc-top1=67.906250 acc-top5=86.531250 Batch [0249]/[0303]: acc-top1=67.706250 acc-top5=86.568750 Batch [0299]/[0303]: acc-top1=67.760417 acc-top5=86.588542 [Epoch 082] training: accuracy=81.914062 loss=0.709645 [Epoch 082] speed: 71 samples/sec time cost: 3640.983543 [Epoch 082] validation: acc-top1=67.795998 acc-top5=86.613036 loss=1.625843 Epoch[083] Batch [0049]/[3760] Speed: 49.260209 samples/sec accuracy=82.375000 loss=0.674497 lr=0.000100 Epoch[083] Batch [0099]/[3760] Speed: 70.544464 samples/sec accuracy=82.593750 loss=0.673129 lr=0.000100 Epoch[083] Batch [0149]/[3760] Speed: 71.474433 samples/sec accuracy=82.687500 loss=0.672375 lr=0.000100 Epoch[083] Batch [0199]/[3760] Speed: 70.708894 samples/sec accuracy=82.203125 loss=0.699672 lr=0.000100 Epoch[083] Batch [0249]/[3760] Speed: 72.884384 samples/sec accuracy=81.918750 loss=0.707045 lr=0.000100 Epoch[083] Batch [0299]/[3760] Speed: 71.243839 samples/sec accuracy=81.760417 loss=0.716178 lr=0.000100 Epoch[083] Batch 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accuracy=82.064453 loss=0.706876 lr=0.000100 Epoch[083] Batch [0849]/[3760] Speed: 71.357462 samples/sec accuracy=82.104779 loss=0.706172 lr=0.000100 Epoch[083] Batch [0899]/[3760] Speed: 71.688318 samples/sec accuracy=82.137153 loss=0.705498 lr=0.000100 Epoch[083] Batch [0949]/[3760] Speed: 70.517125 samples/sec accuracy=82.139803 loss=0.706356 lr=0.000100 Epoch[083] Batch [0999]/[3760] Speed: 72.541176 samples/sec accuracy=82.104687 loss=0.707247 lr=0.000100 Epoch[083] Batch [1049]/[3760] Speed: 72.180780 samples/sec accuracy=82.105655 loss=0.709288 lr=0.000100 Epoch[083] Batch [1099]/[3760] Speed: 72.184349 samples/sec accuracy=82.035511 loss=0.710912 lr=0.000100 Epoch[083] Batch [1149]/[3760] Speed: 70.922921 samples/sec accuracy=82.043478 loss=0.709702 lr=0.000100 Epoch[083] Batch [1199]/[3760] Speed: 72.236758 samples/sec accuracy=82.058594 loss=0.709057 lr=0.000100 Epoch[083] Batch [1249]/[3760] Speed: 71.504678 samples/sec accuracy=82.047500 loss=0.709079 lr=0.000100 Epoch[083] 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accuracy=82.080357 loss=0.708237 lr=0.000100 Epoch[083] Batch [1799]/[3760] Speed: 71.711304 samples/sec accuracy=82.088542 loss=0.707577 lr=0.000100 Epoch[083] Batch [1849]/[3760] Speed: 72.015099 samples/sec accuracy=82.086993 loss=0.707858 lr=0.000100 Epoch[083] Batch [1899]/[3760] Speed: 71.525940 samples/sec accuracy=82.060033 loss=0.708449 lr=0.000100 Epoch[083] Batch [1949]/[3760] Speed: 71.363490 samples/sec accuracy=82.037660 loss=0.708893 lr=0.000100 Epoch[083] Batch [1999]/[3760] Speed: 71.737889 samples/sec accuracy=82.011719 loss=0.709845 lr=0.000100 Epoch[083] Batch [2049]/[3760] Speed: 71.347536 samples/sec accuracy=82.012957 loss=0.709997 lr=0.000100 Epoch[083] Batch [2099]/[3760] Speed: 72.343832 samples/sec accuracy=81.999256 loss=0.710538 lr=0.000100 Epoch[083] Batch [2149]/[3760] Speed: 72.063004 samples/sec accuracy=81.978198 loss=0.710717 lr=0.000100 Epoch[083] Batch [2199]/[3760] Speed: 71.101830 samples/sec accuracy=81.985795 loss=0.710054 lr=0.000100 Epoch[083] 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accuracy=82.002315 loss=0.709621 lr=0.000100 Epoch[083] Batch [2749]/[3760] Speed: 71.853777 samples/sec accuracy=82.001136 loss=0.709522 lr=0.000100 Epoch[083] Batch [2799]/[3760] Speed: 71.738393 samples/sec accuracy=81.985491 loss=0.709883 lr=0.000100 Epoch[083] Batch [2849]/[3760] Speed: 71.307221 samples/sec accuracy=81.993969 loss=0.709233 lr=0.000100 Epoch[083] Batch [2899]/[3760] Speed: 71.715340 samples/sec accuracy=82.012392 loss=0.708288 lr=0.000100 Epoch[083] Batch [2949]/[3760] Speed: 71.797185 samples/sec accuracy=82.006886 loss=0.708131 lr=0.000100 Epoch[083] Batch [2999]/[3760] Speed: 71.887816 samples/sec accuracy=82.021875 loss=0.707511 lr=0.000100 Epoch[083] Batch [3049]/[3760] Speed: 71.796885 samples/sec accuracy=82.030738 loss=0.707118 lr=0.000100 Epoch[083] Batch [3099]/[3760] Speed: 71.386186 samples/sec accuracy=82.031754 loss=0.707231 lr=0.000100 Epoch[083] Batch [3149]/[3760] Speed: 71.369168 samples/sec accuracy=82.012401 loss=0.708343 lr=0.000100 Epoch[083] Batch [3199]/[3760] Speed: 71.304928 samples/sec accuracy=82.019043 loss=0.708101 lr=0.000100 Epoch[083] Batch [3249]/[3760] Speed: 71.340258 samples/sec accuracy=82.025481 loss=0.707458 lr=0.000100 Epoch[083] Batch [3299]/[3760] Speed: 72.017774 samples/sec accuracy=82.026042 loss=0.707563 lr=0.000100 Epoch[083] Batch [3349]/[3760] Speed: 71.169528 samples/sec accuracy=82.031250 loss=0.707464 lr=0.000100 Epoch[083] Batch [3399]/[3760] Speed: 71.612980 samples/sec accuracy=82.034926 loss=0.707437 lr=0.000100 Epoch[083] Batch [3449]/[3760] Speed: 72.218527 samples/sec accuracy=82.013587 loss=0.707992 lr=0.000100 Epoch[083] Batch [3499]/[3760] Speed: 71.696184 samples/sec accuracy=82.020536 loss=0.707646 lr=0.000100 Epoch[083] Batch [3549]/[3760] Speed: 71.615212 samples/sec accuracy=82.027729 loss=0.707454 lr=0.000100 Epoch[083] Batch [3599]/[3760] Speed: 70.861816 samples/sec accuracy=82.019097 loss=0.707881 lr=0.000100 Epoch[083] Batch [3649]/[3760] Speed: 72.428179 samples/sec accuracy=82.025685 loss=0.707779 lr=0.000100 Epoch[083] Batch [3699]/[3760] Speed: 71.109874 samples/sec accuracy=82.024916 loss=0.708119 lr=0.000100 Epoch[083] Batch [3749]/[3760] Speed: 79.658788 samples/sec accuracy=82.037083 loss=0.707854 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.562500 acc-top5=87.906250 Batch [0099]/[0303]: acc-top1=69.171875 acc-top5=87.546875 Batch [0149]/[0303]: acc-top1=68.197917 acc-top5=86.697917 Batch [0199]/[0303]: acc-top1=67.937500 acc-top5=86.578125 Batch [0249]/[0303]: acc-top1=67.706250 acc-top5=86.612500 Batch [0299]/[0303]: acc-top1=67.760417 acc-top5=86.671875 [Epoch 083] training: accuracy=82.037068 loss=0.707731 [Epoch 083] speed: 71 samples/sec time cost: 3642.177727 [Epoch 083] validation: acc-top1=67.790842 acc-top5=86.711015 loss=1.640981 Epoch[084] Batch [0049]/[3759] Speed: 48.370430 samples/sec accuracy=82.906250 loss=0.658391 lr=0.000100 Epoch[084] Batch [0099]/[3759] Speed: 71.113353 samples/sec accuracy=83.031250 loss=0.658301 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lr=0.000100 Epoch[084] Batch [1099]/[3759] Speed: 71.678018 samples/sec accuracy=82.231534 loss=0.696442 lr=0.000100 Epoch[084] Batch [1149]/[3759] Speed: 71.934647 samples/sec accuracy=82.266304 loss=0.695400 lr=0.000100 Epoch[084] Batch [1199]/[3759] Speed: 71.450748 samples/sec accuracy=82.266927 loss=0.694663 lr=0.000100 Epoch[084] Batch [1249]/[3759] Speed: 71.909889 samples/sec accuracy=82.277500 loss=0.694333 lr=0.000100 Epoch[084] Batch [1299]/[3759] Speed: 71.040886 samples/sec accuracy=82.284856 loss=0.693900 lr=0.000100 Epoch[084] Batch [1349]/[3759] Speed: 71.208959 samples/sec accuracy=82.332176 loss=0.692662 lr=0.000100 Epoch[084] Batch [1399]/[3759] Speed: 71.617109 samples/sec accuracy=82.366071 loss=0.691861 lr=0.000100 Epoch[084] Batch [1449]/[3759] Speed: 71.539297 samples/sec accuracy=82.407328 loss=0.691799 lr=0.000100 Epoch[084] Batch [1499]/[3759] Speed: 71.720857 samples/sec accuracy=82.412500 loss=0.691294 lr=0.000100 Epoch[084] Batch [1549]/[3759] Speed: 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lr=0.000100 Epoch[084] Batch [2049]/[3759] Speed: 71.419554 samples/sec accuracy=82.355183 loss=0.694197 lr=0.000100 Epoch[084] Batch [2099]/[3759] Speed: 71.861227 samples/sec accuracy=82.354911 loss=0.693997 lr=0.000100 Epoch[084] Batch [2149]/[3759] Speed: 71.804279 samples/sec accuracy=82.351744 loss=0.694256 lr=0.000100 Epoch[084] Batch [2199]/[3759] Speed: 72.030431 samples/sec accuracy=82.328835 loss=0.695060 lr=0.000100 Epoch[084] Batch [2249]/[3759] Speed: 71.284938 samples/sec accuracy=82.327083 loss=0.695070 lr=0.000100 Epoch[084] Batch [2299]/[3759] Speed: 72.034319 samples/sec accuracy=82.333560 loss=0.694938 lr=0.000100 Epoch[084] Batch [2349]/[3759] Speed: 71.106278 samples/sec accuracy=82.355718 loss=0.694366 lr=0.000100 Epoch[084] Batch [2399]/[3759] Speed: 71.779760 samples/sec accuracy=82.370443 loss=0.694080 lr=0.000100 Epoch[084] Batch [2449]/[3759] Speed: 71.655527 samples/sec accuracy=82.376913 loss=0.693830 lr=0.000100 Epoch[084] Batch [2499]/[3759] Speed: 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lr=0.000100 Epoch[084] Batch [2999]/[3759] Speed: 71.598986 samples/sec accuracy=82.320312 loss=0.695412 lr=0.000100 Epoch[084] Batch [3049]/[3759] Speed: 71.688992 samples/sec accuracy=82.309426 loss=0.695730 lr=0.000100 Epoch[084] Batch [3099]/[3759] Speed: 71.422634 samples/sec accuracy=82.304940 loss=0.695915 lr=0.000100 Epoch[084] Batch [3149]/[3759] Speed: 72.244124 samples/sec accuracy=82.317460 loss=0.695733 lr=0.000100 Epoch[084] Batch [3199]/[3759] Speed: 71.156483 samples/sec accuracy=82.324707 loss=0.695413 lr=0.000100 Epoch[084] Batch [3249]/[3759] Speed: 71.211441 samples/sec accuracy=82.328365 loss=0.695278 lr=0.000100 Epoch[084] Batch [3299]/[3759] Speed: 72.049058 samples/sec accuracy=82.321496 loss=0.695255 lr=0.000100 Epoch[084] Batch [3349]/[3759] Speed: 71.808043 samples/sec accuracy=82.336754 loss=0.694630 lr=0.000100 Epoch[084] Batch [3399]/[3759] Speed: 71.605414 samples/sec accuracy=82.353401 loss=0.693855 lr=0.000100 Epoch[084] Batch [3449]/[3759] Speed: 71.808958 samples/sec accuracy=82.358243 loss=0.693857 lr=0.000100 Epoch[084] Batch [3499]/[3759] Speed: 71.617380 samples/sec accuracy=82.350893 loss=0.694065 lr=0.000100 Epoch[084] Batch [3549]/[3759] Speed: 71.982747 samples/sec accuracy=82.357835 loss=0.693572 lr=0.000100 Epoch[084] Batch [3599]/[3759] Speed: 71.549423 samples/sec accuracy=82.370226 loss=0.693555 lr=0.000100 Epoch[084] Batch [3649]/[3759] Speed: 71.321213 samples/sec accuracy=82.356164 loss=0.694019 lr=0.000100 Epoch[084] Batch [3699]/[3759] Speed: 71.867929 samples/sec accuracy=82.356841 loss=0.694040 lr=0.000100 Epoch[084] Batch [3749]/[3759] Speed: 80.541437 samples/sec accuracy=82.365000 loss=0.693840 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.281250 acc-top5=87.687500 Batch [0099]/[0303]: acc-top1=69.093750 acc-top5=87.359375 Batch [0149]/[0303]: acc-top1=68.302083 acc-top5=86.468750 Batch [0199]/[0303]: acc-top1=68.015625 acc-top5=86.445312 Batch [0249]/[0303]: acc-top1=67.687500 acc-top5=86.462500 Batch [0299]/[0303]: acc-top1=67.651042 acc-top5=86.546875 [Epoch 084] training: accuracy=82.364824 loss=0.693689 [Epoch 084] speed: 71 samples/sec time cost: 3641.248622 [Epoch 084] validation: acc-top1=67.682550 acc-top5=86.566625 loss=1.647517 Epoch[085] Batch [0049]/[3760] Speed: 48.468286 samples/sec accuracy=82.312500 loss=0.711698 lr=0.000100 Epoch[085] Batch [0099]/[3760] Speed: 70.687873 samples/sec accuracy=82.562500 loss=0.699015 lr=0.000100 Epoch[085] Batch [0149]/[3760] Speed: 72.132373 samples/sec accuracy=82.656250 loss=0.692730 lr=0.000100 Epoch[085] Batch [0199]/[3760] Speed: 70.636063 samples/sec accuracy=82.546875 loss=0.695648 lr=0.000100 Epoch[085] Batch [0249]/[3760] Speed: 71.481229 samples/sec accuracy=82.387500 loss=0.700696 lr=0.000100 Epoch[085] Batch [0299]/[3760] Speed: 71.770143 samples/sec accuracy=82.432292 loss=0.696892 lr=0.000100 Epoch[085] Batch [0349]/[3760] Speed: 71.807958 samples/sec accuracy=82.526786 loss=0.692604 lr=0.000100 Epoch[085] Batch 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accuracy=82.277574 loss=0.696602 lr=0.000100 Epoch[085] Batch [0899]/[3760] Speed: 71.994502 samples/sec accuracy=82.281250 loss=0.696717 lr=0.000100 Epoch[085] Batch [0949]/[3760] Speed: 72.051608 samples/sec accuracy=82.223684 loss=0.698416 lr=0.000100 Epoch[085] Batch [0999]/[3760] Speed: 70.984602 samples/sec accuracy=82.257812 loss=0.697022 lr=0.000100 Epoch[085] Batch [1049]/[3760] Speed: 71.428437 samples/sec accuracy=82.272321 loss=0.695457 lr=0.000100 Epoch[085] Batch [1099]/[3760] Speed: 71.356293 samples/sec accuracy=82.315341 loss=0.694626 lr=0.000100 Epoch[085] Batch [1149]/[3760] Speed: 71.859666 samples/sec accuracy=82.300272 loss=0.694094 lr=0.000100 Epoch[085] Batch [1199]/[3760] Speed: 71.801325 samples/sec accuracy=82.316406 loss=0.694237 lr=0.000100 Epoch[085] Batch [1249]/[3760] Speed: 71.313449 samples/sec accuracy=82.317500 loss=0.694436 lr=0.000100 Epoch[085] Batch [1299]/[3760] Speed: 71.983276 samples/sec accuracy=82.317308 loss=0.694662 lr=0.000100 Epoch[085] Batch [1349]/[3760] Speed: 71.995613 samples/sec accuracy=82.274306 loss=0.695509 lr=0.000100 Epoch[085] Batch [1399]/[3760] Speed: 71.574890 samples/sec accuracy=82.321429 loss=0.694303 lr=0.000100 Epoch[085] Batch [1449]/[3760] Speed: 71.546324 samples/sec accuracy=82.370690 loss=0.692751 lr=0.000100 Epoch[085] Batch [1499]/[3760] Speed: 71.576827 samples/sec accuracy=82.352083 loss=0.692828 lr=0.000100 Epoch[085] Batch [1549]/[3760] Speed: 71.511868 samples/sec accuracy=82.363911 loss=0.692895 lr=0.000100 Epoch[085] Batch [1599]/[3760] Speed: 72.145611 samples/sec accuracy=82.352539 loss=0.693056 lr=0.000100 Epoch[085] Batch [1649]/[3760] Speed: 70.708280 samples/sec accuracy=82.297348 loss=0.694837 lr=0.000100 Epoch[085] Batch [1699]/[3760] Speed: 72.006189 samples/sec accuracy=82.268382 loss=0.695328 lr=0.000100 Epoch[085] Batch [1749]/[3760] Speed: 70.743802 samples/sec accuracy=82.275893 loss=0.695000 lr=0.000100 Epoch[085] Batch [1799]/[3760] Speed: 72.447349 samples/sec accuracy=82.286458 loss=0.694798 lr=0.000100 Epoch[085] Batch [1849]/[3760] Speed: 71.784052 samples/sec accuracy=82.311655 loss=0.694061 lr=0.000100 Epoch[085] Batch [1899]/[3760] Speed: 71.656194 samples/sec accuracy=82.332237 loss=0.693070 lr=0.000100 Epoch[085] Batch [1949]/[3760] Speed: 71.527360 samples/sec accuracy=82.352564 loss=0.691970 lr=0.000100 Epoch[085] Batch [1999]/[3760] Speed: 71.641951 samples/sec accuracy=82.360937 loss=0.691061 lr=0.000100 Epoch[085] Batch [2049]/[3760] Speed: 71.709885 samples/sec accuracy=82.356707 loss=0.690645 lr=0.000100 Epoch[085] Batch [2099]/[3760] Speed: 72.131474 samples/sec accuracy=82.348214 loss=0.690464 lr=0.000100 Epoch[085] Batch [2149]/[3760] Speed: 71.629029 samples/sec accuracy=82.339390 loss=0.690895 lr=0.000100 Epoch[085] Batch [2199]/[3760] Speed: 70.996068 samples/sec accuracy=82.348011 loss=0.690371 lr=0.000100 Epoch[085] Batch [2249]/[3760] Speed: 71.225740 samples/sec accuracy=82.343056 loss=0.690434 lr=0.000100 Epoch[085] Batch [2299]/[3760] Speed: 71.897997 samples/sec accuracy=82.357337 loss=0.690301 lr=0.000100 Epoch[085] Batch [2349]/[3760] Speed: 71.742083 samples/sec accuracy=82.380984 loss=0.689575 lr=0.000100 Epoch[085] Batch [2399]/[3760] Speed: 72.157744 samples/sec accuracy=82.358073 loss=0.690570 lr=0.000100 Epoch[085] Batch [2449]/[3760] Speed: 71.733885 samples/sec accuracy=82.348214 loss=0.690948 lr=0.000100 Epoch[085] Batch [2499]/[3760] Speed: 70.669855 samples/sec accuracy=82.327500 loss=0.691823 lr=0.000100 Epoch[085] Batch [2549]/[3760] Speed: 72.325732 samples/sec accuracy=82.321691 loss=0.692551 lr=0.000100 Epoch[085] Batch [2599]/[3760] Speed: 71.732422 samples/sec accuracy=82.319111 loss=0.692516 lr=0.000100 Epoch[085] Batch [2649]/[3760] Speed: 71.927615 samples/sec accuracy=82.329599 loss=0.692368 lr=0.000100 Epoch[085] Batch [2699]/[3760] Speed: 72.436152 samples/sec accuracy=82.320602 loss=0.692754 lr=0.000100 Epoch[085] Batch [2749]/[3760] Speed: 71.970955 samples/sec accuracy=82.321591 loss=0.692626 lr=0.000100 Epoch[085] Batch [2799]/[3760] Speed: 71.467173 samples/sec accuracy=82.314174 loss=0.693292 lr=0.000100 Epoch[085] Batch [2849]/[3760] Speed: 71.362263 samples/sec accuracy=82.321820 loss=0.693296 lr=0.000100 Epoch[085] Batch [2899]/[3760] Speed: 71.201444 samples/sec accuracy=82.303879 loss=0.693846 lr=0.000100 Epoch[085] Batch [2949]/[3760] Speed: 72.237813 samples/sec accuracy=82.314619 loss=0.693371 lr=0.000100 Epoch[085] Batch [2999]/[3760] Speed: 71.249377 samples/sec accuracy=82.317188 loss=0.693165 lr=0.000100 Epoch[085] Batch [3049]/[3760] Speed: 71.708803 samples/sec accuracy=82.333504 loss=0.692550 lr=0.000100 Epoch[085] Batch [3099]/[3760] Speed: 71.390785 samples/sec accuracy=82.345262 loss=0.691939 lr=0.000100 Epoch[085] Batch [3149]/[3760] Speed: 71.281220 samples/sec accuracy=82.361111 loss=0.691370 lr=0.000100 Epoch[085] Batch [3199]/[3760] Speed: 72.095749 samples/sec accuracy=82.350098 loss=0.691751 lr=0.000100 Epoch[085] Batch [3249]/[3760] Speed: 72.154307 samples/sec accuracy=82.350481 loss=0.692068 lr=0.000100 Epoch[085] Batch [3299]/[3760] Speed: 71.486164 samples/sec accuracy=82.344223 loss=0.692720 lr=0.000100 Epoch[085] Batch [3349]/[3760] Speed: 71.843557 samples/sec accuracy=82.336287 loss=0.693087 lr=0.000100 Epoch[085] Batch [3399]/[3760] Speed: 71.845413 samples/sec accuracy=82.344210 loss=0.693056 lr=0.000100 Epoch[085] Batch [3449]/[3760] Speed: 72.004172 samples/sec accuracy=82.338315 loss=0.693244 lr=0.000100 Epoch[085] Batch [3499]/[3760] Speed: 71.694613 samples/sec accuracy=82.347768 loss=0.692979 lr=0.000100 Epoch[085] Batch [3549]/[3760] Speed: 71.582313 samples/sec accuracy=82.361356 loss=0.692843 lr=0.000100 Epoch[085] Batch [3599]/[3760] Speed: 71.411260 samples/sec accuracy=82.362413 loss=0.692854 lr=0.000100 Epoch[085] Batch [3649]/[3760] Speed: 71.897952 samples/sec accuracy=82.353596 loss=0.693244 lr=0.000100 Epoch[085] Batch [3699]/[3760] Speed: 71.988070 samples/sec accuracy=82.354730 loss=0.693138 lr=0.000100 Epoch[085] Batch [3749]/[3760] Speed: 79.326664 samples/sec accuracy=82.335417 loss=0.693726 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.906250 acc-top5=87.937500 Batch [0099]/[0303]: acc-top1=68.937500 acc-top5=87.453125 Batch [0149]/[0303]: acc-top1=68.156250 acc-top5=86.520833 Batch [0199]/[0303]: acc-top1=67.859375 acc-top5=86.507812 Batch [0249]/[0303]: acc-top1=67.612500 acc-top5=86.525000 Batch [0299]/[0303]: acc-top1=67.640625 acc-top5=86.557292 [Epoch 085] training: accuracy=82.331699 loss=0.693826 [Epoch 085] speed: 71 samples/sec time cost: 3640.767110 [Epoch 085] validation: acc-top1=67.692863 acc-top5=86.592409 loss=1.629963 Epoch[086] Batch [0049]/[3760] Speed: 48.927982 samples/sec accuracy=81.406250 loss=0.712904 lr=0.000100 Epoch[086] Batch [0099]/[3760] Speed: 70.151163 samples/sec accuracy=82.406250 loss=0.693056 lr=0.000100 Epoch[086] Batch [0149]/[3760] Speed: 71.465647 samples/sec accuracy=82.614583 loss=0.686581 lr=0.000100 Epoch[086] Batch [0199]/[3760] Speed: 71.323308 samples/sec accuracy=82.421875 loss=0.690755 lr=0.000100 Epoch[086] Batch [0249]/[3760] Speed: 71.666407 samples/sec accuracy=82.243750 loss=0.697020 lr=0.000100 Epoch[086] Batch [0299]/[3760] Speed: 71.190119 samples/sec accuracy=82.276042 loss=0.693453 lr=0.000100 Epoch[086] Batch [0349]/[3760] Speed: 71.638652 samples/sec accuracy=82.558036 loss=0.690305 lr=0.000100 Epoch[086] Batch [0399]/[3760] Speed: 71.618429 samples/sec accuracy=82.515625 loss=0.689717 lr=0.000100 Epoch[086] Batch [0449]/[3760] Speed: 71.768529 samples/sec accuracy=82.524306 loss=0.690385 lr=0.000100 Epoch[086] Batch [0499]/[3760] Speed: 72.062627 samples/sec accuracy=82.537500 loss=0.689145 lr=0.000100 Epoch[086] Batch [0549]/[3760] Speed: 72.022546 samples/sec accuracy=82.585227 loss=0.689916 lr=0.000100 Epoch[086] Batch [0599]/[3760] Speed: 71.873903 samples/sec accuracy=82.617188 loss=0.689861 lr=0.000100 Epoch[086] Batch [0649]/[3760] Speed: 71.320182 samples/sec accuracy=82.637019 loss=0.689374 lr=0.000100 Epoch[086] Batch [0699]/[3760] Speed: 72.565858 samples/sec accuracy=82.683036 loss=0.686649 lr=0.000100 Epoch[086] Batch [0749]/[3760] Speed: 70.795767 samples/sec accuracy=82.691667 loss=0.684206 lr=0.000100 Epoch[086] Batch [0799]/[3760] Speed: 71.312203 samples/sec accuracy=82.685547 loss=0.682904 lr=0.000100 Epoch[086] Batch [0849]/[3760] Speed: 71.644471 samples/sec accuracy=82.678309 loss=0.682346 lr=0.000100 Epoch[086] Batch [0899]/[3760] Speed: 71.394341 samples/sec accuracy=82.668403 loss=0.683623 lr=0.000100 Epoch[086] Batch [0949]/[3760] Speed: 71.652376 samples/sec accuracy=82.618421 loss=0.684446 lr=0.000100 Epoch[086] Batch [0999]/[3760] Speed: 71.274656 samples/sec accuracy=82.642187 loss=0.683163 lr=0.000100 Epoch[086] Batch [1049]/[3760] Speed: 71.064944 samples/sec accuracy=82.636905 loss=0.683461 lr=0.000100 Epoch[086] Batch [1099]/[3760] Speed: 71.877411 samples/sec accuracy=82.595170 loss=0.685860 lr=0.000100 Epoch[086] Batch [1149]/[3760] Speed: 72.453182 samples/sec accuracy=82.566576 loss=0.686755 lr=0.000100 Epoch[086] Batch [1199]/[3760] Speed: 71.148101 samples/sec accuracy=82.597656 loss=0.685562 lr=0.000100 Epoch[086] Batch [1249]/[3760] Speed: 71.824148 samples/sec accuracy=82.593750 loss=0.684507 lr=0.000100 Epoch[086] Batch [1299]/[3760] Speed: 71.642010 samples/sec accuracy=82.634615 loss=0.683488 lr=0.000100 Epoch[086] Batch [1349]/[3760] Speed: 71.752920 samples/sec accuracy=82.613426 loss=0.683649 lr=0.000100 Epoch[086] Batch [1399]/[3760] Speed: 71.390578 samples/sec accuracy=82.600446 loss=0.683381 lr=0.000100 Epoch[086] Batch [1449]/[3760] Speed: 71.723244 samples/sec accuracy=82.590517 loss=0.684013 lr=0.000100 Epoch[086] Batch [1499]/[3760] Speed: 72.129768 samples/sec accuracy=82.567708 loss=0.684457 lr=0.000100 Epoch[086] Batch [1549]/[3760] Speed: 71.646376 samples/sec accuracy=82.558468 loss=0.684868 lr=0.000100 Epoch[086] Batch [1599]/[3760] Speed: 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lr=0.000100 Epoch[086] Batch [2099]/[3760] Speed: 71.723427 samples/sec accuracy=82.640625 loss=0.685240 lr=0.000100 Epoch[086] Batch [2149]/[3760] Speed: 71.451767 samples/sec accuracy=82.604651 loss=0.686204 lr=0.000100 Epoch[086] Batch [2199]/[3760] Speed: 72.155274 samples/sec accuracy=82.606534 loss=0.685907 lr=0.000100 Epoch[086] Batch [2249]/[3760] Speed: 71.207033 samples/sec accuracy=82.627083 loss=0.684558 lr=0.000100 Epoch[086] Batch [2299]/[3760] Speed: 70.939321 samples/sec accuracy=82.612772 loss=0.684752 lr=0.000100 Epoch[086] Batch [2349]/[3760] Speed: 71.840547 samples/sec accuracy=82.598404 loss=0.685037 lr=0.000100 Epoch[086] Batch [2399]/[3760] Speed: 72.534841 samples/sec accuracy=82.593750 loss=0.685264 lr=0.000100 Epoch[086] Batch [2449]/[3760] Speed: 71.767991 samples/sec accuracy=82.563776 loss=0.686631 lr=0.000100 Epoch[086] Batch [2499]/[3760] Speed: 71.571228 samples/sec accuracy=82.548750 loss=0.686824 lr=0.000100 Epoch[086] Batch [2549]/[3760] Speed: 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lr=0.000100 Epoch[086] Batch [3049]/[3760] Speed: 71.178928 samples/sec accuracy=82.491803 loss=0.688211 lr=0.000100 Epoch[086] Batch [3099]/[3760] Speed: 71.684854 samples/sec accuracy=82.503024 loss=0.688401 lr=0.000100 Epoch[086] Batch [3149]/[3760] Speed: 72.071122 samples/sec accuracy=82.505456 loss=0.688150 lr=0.000100 Epoch[086] Batch [3199]/[3760] Speed: 71.714719 samples/sec accuracy=82.508789 loss=0.688198 lr=0.000100 Epoch[086] Batch [3249]/[3760] Speed: 71.454706 samples/sec accuracy=82.514904 loss=0.687719 lr=0.000100 Epoch[086] Batch [3299]/[3760] Speed: 71.645255 samples/sec accuracy=82.493371 loss=0.688402 lr=0.000100 Epoch[086] Batch [3349]/[3760] Speed: 71.927886 samples/sec accuracy=82.473881 loss=0.688785 lr=0.000100 Epoch[086] Batch [3399]/[3760] Speed: 71.036289 samples/sec accuracy=82.477482 loss=0.688619 lr=0.000100 Epoch[086] Batch [3449]/[3760] Speed: 72.546291 samples/sec accuracy=82.477808 loss=0.688910 lr=0.000100 Epoch[086] Batch [3499]/[3760] Speed: 71.845959 samples/sec accuracy=82.475446 loss=0.689097 lr=0.000100 Epoch[086] Batch [3549]/[3760] Speed: 71.943138 samples/sec accuracy=82.471391 loss=0.689163 lr=0.000100 Epoch[086] Batch [3599]/[3760] Speed: 71.398416 samples/sec accuracy=82.467014 loss=0.689466 lr=0.000100 Epoch[086] Batch [3649]/[3760] Speed: 71.729660 samples/sec accuracy=82.472603 loss=0.689530 lr=0.000100 Epoch[086] Batch [3699]/[3760] Speed: 71.466299 samples/sec accuracy=82.470439 loss=0.689574 lr=0.000100 Epoch[086] Batch [3749]/[3760] Speed: 78.717500 samples/sec accuracy=82.465833 loss=0.689517 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.312500 acc-top5=87.937500 Batch [0099]/[0303]: acc-top1=69.046875 acc-top5=87.421875 Batch [0149]/[0303]: acc-top1=68.302083 acc-top5=86.552083 Batch [0199]/[0303]: acc-top1=68.117188 acc-top5=86.492188 Batch [0249]/[0303]: acc-top1=67.768750 acc-top5=86.587500 Batch [0299]/[0303]: acc-top1=67.796875 acc-top5=86.645833 [Epoch 086] training: accuracy=82.464262 loss=0.689531 [Epoch 086] speed: 71 samples/sec time cost: 3642.884447 [Epoch 086] validation: acc-top1=67.826939 acc-top5=86.680074 loss=1.634769 Epoch[087] Batch [0049]/[3759] Speed: 48.283272 samples/sec accuracy=82.968750 loss=0.689603 lr=0.000100 Epoch[087] Batch [0099]/[3759] Speed: 69.776722 samples/sec accuracy=82.515625 loss=0.692552 lr=0.000100 Epoch[087] Batch [0149]/[3759] Speed: 72.045852 samples/sec accuracy=82.812500 loss=0.690240 lr=0.000100 Epoch[087] Batch [0199]/[3759] Speed: 71.974085 samples/sec accuracy=82.476562 loss=0.701284 lr=0.000100 Epoch[087] Batch [0249]/[3759] Speed: 71.692168 samples/sec accuracy=82.318750 loss=0.697527 lr=0.000100 Epoch[087] Batch [0299]/[3759] Speed: 70.463244 samples/sec accuracy=82.401042 loss=0.691397 lr=0.000100 Epoch[087] Batch [0349]/[3759] Speed: 71.612817 samples/sec accuracy=82.397321 loss=0.688569 lr=0.000100 Epoch[087] Batch [0399]/[3759] Speed: 70.755383 samples/sec accuracy=82.417969 loss=0.691157 lr=0.000100 Epoch[087] Batch 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accuracy=82.527778 loss=0.688468 lr=0.000100 Epoch[087] Batch [0949]/[3759] Speed: 70.962960 samples/sec accuracy=82.597039 loss=0.685660 lr=0.000100 Epoch[087] Batch [0999]/[3759] Speed: 72.311458 samples/sec accuracy=82.595312 loss=0.684897 lr=0.000100 Epoch[087] Batch [1049]/[3759] Speed: 71.509381 samples/sec accuracy=82.636905 loss=0.683681 lr=0.000100 Epoch[087] Batch [1099]/[3759] Speed: 71.316741 samples/sec accuracy=82.642045 loss=0.684178 lr=0.000100 Epoch[087] Batch [1149]/[3759] Speed: 70.810145 samples/sec accuracy=82.595109 loss=0.685205 lr=0.000100 Epoch[087] Batch [1199]/[3759] Speed: 70.860618 samples/sec accuracy=82.572917 loss=0.685208 lr=0.000100 Epoch[087] Batch [1249]/[3759] Speed: 71.655764 samples/sec accuracy=82.543750 loss=0.685757 lr=0.000100 Epoch[087] Batch [1299]/[3759] Speed: 71.282552 samples/sec accuracy=82.515625 loss=0.686693 lr=0.000100 Epoch[087] Batch [1349]/[3759] Speed: 71.515453 samples/sec accuracy=82.484954 loss=0.687299 lr=0.000100 Epoch[087] Batch [1399]/[3759] Speed: 71.841334 samples/sec accuracy=82.496652 loss=0.687127 lr=0.000100 Epoch[087] Batch [1449]/[3759] Speed: 71.569536 samples/sec accuracy=82.505388 loss=0.686689 lr=0.000100 Epoch[087] Batch [1499]/[3759] Speed: 71.954018 samples/sec accuracy=82.485417 loss=0.687817 lr=0.000100 Epoch[087] Batch [1549]/[3759] Speed: 72.007429 samples/sec accuracy=82.459677 loss=0.687881 lr=0.000100 Epoch[087] Batch [1599]/[3759] Speed: 70.672125 samples/sec accuracy=82.487305 loss=0.687157 lr=0.000100 Epoch[087] Batch [1649]/[3759] Speed: 71.755179 samples/sec accuracy=82.507576 loss=0.686738 lr=0.000100 Epoch[087] Batch [1699]/[3759] Speed: 71.593886 samples/sec accuracy=82.516544 loss=0.686669 lr=0.000100 Epoch[087] Batch [1749]/[3759] Speed: 72.008417 samples/sec accuracy=82.516071 loss=0.686144 lr=0.000100 Epoch[087] Batch [1799]/[3759] Speed: 71.446765 samples/sec accuracy=82.533854 loss=0.685026 lr=0.000100 Epoch[087] Batch [1849]/[3759] Speed: 72.058887 samples/sec accuracy=82.510980 loss=0.685552 lr=0.000100 Epoch[087] Batch [1899]/[3759] Speed: 71.311610 samples/sec accuracy=82.514803 loss=0.685947 lr=0.000100 Epoch[087] Batch [1949]/[3759] Speed: 70.669757 samples/sec accuracy=82.529647 loss=0.684761 lr=0.000100 Epoch[087] Batch [1999]/[3759] Speed: 73.002718 samples/sec accuracy=82.533594 loss=0.684329 lr=0.000100 Epoch[087] Batch [2049]/[3759] Speed: 71.493338 samples/sec accuracy=82.522104 loss=0.684893 lr=0.000100 Epoch[087] Batch [2099]/[3759] Speed: 71.218067 samples/sec accuracy=82.518601 loss=0.685116 lr=0.000100 Epoch[087] Batch [2149]/[3759] Speed: 72.058607 samples/sec accuracy=82.530523 loss=0.684596 lr=0.000100 Epoch[087] Batch [2199]/[3759] Speed: 71.512720 samples/sec accuracy=82.529830 loss=0.684490 lr=0.000100 Epoch[087] Batch [2249]/[3759] Speed: 71.434946 samples/sec accuracy=82.513194 loss=0.684594 lr=0.000100 Epoch[087] Batch [2299]/[3759] Speed: 71.926378 samples/sec accuracy=82.519701 loss=0.684761 lr=0.000100 Epoch[087] Batch [2349]/[3759] Speed: 71.349070 samples/sec accuracy=82.541223 loss=0.684295 lr=0.000100 Epoch[087] Batch [2399]/[3759] Speed: 71.761327 samples/sec accuracy=82.527344 loss=0.685015 lr=0.000100 Epoch[087] Batch [2449]/[3759] Speed: 72.108830 samples/sec accuracy=82.518495 loss=0.685465 lr=0.000100 Epoch[087] Batch [2499]/[3759] Speed: 71.462092 samples/sec accuracy=82.490625 loss=0.686489 lr=0.000100 Epoch[087] Batch [2549]/[3759] Speed: 71.751202 samples/sec accuracy=82.487745 loss=0.686613 lr=0.000100 Epoch[087] Batch [2599]/[3759] Speed: 71.468626 samples/sec accuracy=82.487380 loss=0.686375 lr=0.000100 Epoch[087] Batch [2649]/[3759] Speed: 71.711697 samples/sec accuracy=82.477005 loss=0.686927 lr=0.000100 Epoch[087] Batch [2699]/[3759] Speed: 72.632436 samples/sec accuracy=82.484954 loss=0.686504 lr=0.000100 Epoch[087] Batch [2749]/[3759] Speed: 70.794709 samples/sec accuracy=82.497159 loss=0.686393 lr=0.000100 Epoch[087] Batch [2799]/[3759] Speed: 71.582691 samples/sec accuracy=82.506696 loss=0.685841 lr=0.000100 Epoch[087] Batch [2849]/[3759] Speed: 72.044646 samples/sec accuracy=82.503838 loss=0.685770 lr=0.000100 Epoch[087] Batch [2899]/[3759] Speed: 71.628635 samples/sec accuracy=82.493534 loss=0.685687 lr=0.000100 Epoch[087] Batch [2949]/[3759] Speed: 71.580422 samples/sec accuracy=82.486229 loss=0.685963 lr=0.000100 Epoch[087] Batch [2999]/[3759] Speed: 72.409361 samples/sec accuracy=82.496875 loss=0.685953 lr=0.000100 Epoch[087] Batch [3049]/[3759] Speed: 71.564256 samples/sec accuracy=82.486168 loss=0.686092 lr=0.000100 Epoch[087] Batch [3099]/[3759] Speed: 72.000835 samples/sec accuracy=82.473790 loss=0.686519 lr=0.000100 Epoch[087] Batch [3149]/[3759] Speed: 71.712980 samples/sec accuracy=82.480159 loss=0.686218 lr=0.000100 Epoch[087] Batch [3199]/[3759] Speed: 71.013589 samples/sec accuracy=82.486328 loss=0.685975 lr=0.000100 Epoch[087] Batch [3249]/[3759] Speed: 71.617557 samples/sec accuracy=82.467788 loss=0.686578 lr=0.000100 Epoch[087] Batch [3299]/[3759] Speed: 72.171891 samples/sec accuracy=82.446023 loss=0.687183 lr=0.000100 Epoch[087] Batch [3349]/[3759] Speed: 71.861890 samples/sec accuracy=82.452892 loss=0.687081 lr=0.000100 Epoch[087] Batch [3399]/[3759] Speed: 71.606635 samples/sec accuracy=82.458640 loss=0.687041 lr=0.000100 Epoch[087] Batch [3449]/[3759] Speed: 71.032431 samples/sec accuracy=82.462862 loss=0.686771 lr=0.000100 Epoch[087] Batch [3499]/[3759] Speed: 72.177119 samples/sec accuracy=82.481250 loss=0.686004 lr=0.000100 Epoch[087] Batch [3549]/[3759] Speed: 70.943202 samples/sec accuracy=82.494718 loss=0.685707 lr=0.000100 Epoch[087] Batch [3599]/[3759] Speed: 72.635261 samples/sec accuracy=82.499566 loss=0.685495 lr=0.000100 Epoch[087] Batch [3649]/[3759] Speed: 71.581906 samples/sec accuracy=82.508134 loss=0.685135 lr=0.000100 Epoch[087] Batch [3699]/[3759] Speed: 71.386871 samples/sec accuracy=82.498733 loss=0.685324 lr=0.000100 Epoch[087] Batch [3749]/[3759] Speed: 80.776943 samples/sec accuracy=82.496667 loss=0.685432 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.750000 acc-top5=88.062500 Batch [0099]/[0303]: acc-top1=68.828125 acc-top5=87.609375 Batch [0149]/[0303]: acc-top1=68.156250 acc-top5=86.739583 Batch [0199]/[0303]: acc-top1=67.968750 acc-top5=86.679688 Batch [0249]/[0303]: acc-top1=67.625000 acc-top5=86.650000 Batch [0299]/[0303]: acc-top1=67.765625 acc-top5=86.656250 [Epoch 087] training: accuracy=82.490772 loss=0.685617 [Epoch 087] speed: 71 samples/sec time cost: 3642.853071 [Epoch 087] validation: acc-top1=67.816625 acc-top5=86.685231 loss=1.649299 Epoch[088] Batch [0049]/[3760] Speed: 48.809405 samples/sec accuracy=82.343750 loss=0.684892 lr=0.000100 Epoch[088] Batch [0099]/[3760] Speed: 70.750480 samples/sec accuracy=83.250000 loss=0.661874 lr=0.000100 Epoch[088] Batch [0149]/[3760] Speed: 71.391269 samples/sec accuracy=82.718750 loss=0.679057 lr=0.000100 Epoch[088] Batch [0199]/[3760] Speed: 71.263711 samples/sec accuracy=82.648438 loss=0.687739 lr=0.000100 Epoch[088] Batch [0249]/[3760] Speed: 71.922234 samples/sec accuracy=82.775000 loss=0.686049 lr=0.000100 Epoch[088] Batch [0299]/[3760] Speed: 72.218492 samples/sec accuracy=82.739583 loss=0.684064 lr=0.000100 Epoch[088] Batch [0349]/[3760] Speed: 71.672016 samples/sec accuracy=82.964286 loss=0.677347 lr=0.000100 Epoch[088] Batch [0399]/[3760] Speed: 71.741985 samples/sec accuracy=83.066406 loss=0.672301 lr=0.000100 Epoch[088] Batch [0449]/[3760] Speed: 71.241920 samples/sec accuracy=83.118056 loss=0.670420 lr=0.000100 Epoch[088] Batch [0499]/[3760] Speed: 72.114267 samples/sec accuracy=83.021875 loss=0.673203 lr=0.000100 Epoch[088] Batch [0549]/[3760] Speed: 71.290965 samples/sec accuracy=83.019886 loss=0.673419 lr=0.000100 Epoch[088] Batch [0599]/[3760] Speed: 71.150845 samples/sec accuracy=83.130208 loss=0.669505 lr=0.000100 Epoch[088] Batch [0649]/[3760] Speed: 71.551070 samples/sec accuracy=83.141827 loss=0.667701 lr=0.000100 Epoch[088] Batch [0699]/[3760] Speed: 71.787678 samples/sec accuracy=83.140625 loss=0.667921 lr=0.000100 Epoch[088] Batch [0749]/[3760] Speed: 71.456264 samples/sec accuracy=83.106250 loss=0.670219 lr=0.000100 Epoch[088] Batch [0799]/[3760] Speed: 71.601823 samples/sec accuracy=83.146484 loss=0.669794 lr=0.000100 Epoch[088] Batch [0849]/[3760] Speed: 72.152236 samples/sec accuracy=83.058824 loss=0.673061 lr=0.000100 Epoch[088] Batch [0899]/[3760] Speed: 71.449882 samples/sec accuracy=83.031250 loss=0.673850 lr=0.000100 Epoch[088] Batch [0949]/[3760] Speed: 71.402654 samples/sec accuracy=82.972039 loss=0.676056 lr=0.000100 Epoch[088] Batch [0999]/[3760] Speed: 72.039409 samples/sec accuracy=82.878125 loss=0.678213 lr=0.000100 Epoch[088] Batch [1049]/[3760] Speed: 70.964311 samples/sec accuracy=82.903274 loss=0.677286 lr=0.000100 Epoch[088] Batch [1099]/[3760] Speed: 72.524790 samples/sec accuracy=82.867898 loss=0.677342 lr=0.000100 Epoch[088] Batch [1149]/[3760] Speed: 71.434250 samples/sec accuracy=82.811141 loss=0.677695 lr=0.000100 Epoch[088] Batch [1199]/[3760] Speed: 71.187758 samples/sec accuracy=82.811198 loss=0.678637 lr=0.000100 Epoch[088] Batch [1249]/[3760] Speed: 71.838137 samples/sec accuracy=82.827500 loss=0.678450 lr=0.000100 Epoch[088] Batch [1299]/[3760] Speed: 71.772743 samples/sec accuracy=82.826923 loss=0.678937 lr=0.000100 Epoch[088] Batch [1349]/[3760] Speed: 71.387682 samples/sec accuracy=82.829861 loss=0.679290 lr=0.000100 Epoch[088] Batch [1399]/[3760] Speed: 72.235156 samples/sec accuracy=82.803571 loss=0.680002 lr=0.000100 Epoch[088] Batch [1449]/[3760] Speed: 71.593751 samples/sec accuracy=82.789871 loss=0.681304 lr=0.000100 Epoch[088] Batch [1499]/[3760] Speed: 71.898011 samples/sec accuracy=82.822917 loss=0.680357 lr=0.000100 Epoch[088] Batch [1549]/[3760] Speed: 71.809594 samples/sec accuracy=82.806452 loss=0.680804 lr=0.000100 Epoch[088] Batch [1599]/[3760] Speed: 70.803504 samples/sec accuracy=82.769531 loss=0.681682 lr=0.000100 Epoch[088] Batch [1649]/[3760] Speed: 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lr=0.000100 Epoch[088] Batch [3099]/[3760] Speed: 71.930435 samples/sec accuracy=82.694052 loss=0.681378 lr=0.000100 Epoch[088] Batch [3149]/[3760] Speed: 72.247915 samples/sec accuracy=82.685516 loss=0.681938 lr=0.000100 Epoch[088] Batch [3199]/[3760] Speed: 70.785279 samples/sec accuracy=82.670898 loss=0.682578 lr=0.000100 Epoch[088] Batch [3249]/[3760] Speed: 71.864958 samples/sec accuracy=82.665385 loss=0.682717 lr=0.000100 Epoch[088] Batch [3299]/[3760] Speed: 72.098003 samples/sec accuracy=82.663826 loss=0.683201 lr=0.000100 Epoch[088] Batch [3349]/[3760] Speed: 71.178425 samples/sec accuracy=82.663713 loss=0.683067 lr=0.000100 Epoch[088] Batch [3399]/[3760] Speed: 72.016833 samples/sec accuracy=82.671415 loss=0.682716 lr=0.000100 Epoch[088] Batch [3449]/[3760] Speed: 71.550110 samples/sec accuracy=82.674366 loss=0.682279 lr=0.000100 Epoch[088] Batch [3499]/[3760] Speed: 71.044750 samples/sec accuracy=82.675893 loss=0.682237 lr=0.000100 Epoch[088] Batch [3549]/[3760] Speed: 71.666280 samples/sec accuracy=82.687060 loss=0.681855 lr=0.000100 Epoch[088] Batch [3599]/[3760] Speed: 71.914119 samples/sec accuracy=82.679253 loss=0.681746 lr=0.000100 Epoch[088] Batch [3649]/[3760] Speed: 71.592923 samples/sec accuracy=82.687500 loss=0.681648 lr=0.000100 Epoch[088] Batch [3699]/[3760] Speed: 72.719175 samples/sec accuracy=82.690878 loss=0.681589 lr=0.000100 Epoch[088] Batch [3749]/[3760] Speed: 78.057773 samples/sec accuracy=82.678750 loss=0.681809 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.125000 acc-top5=87.718750 Batch [0099]/[0303]: acc-top1=69.000000 acc-top5=87.453125 Batch [0149]/[0303]: acc-top1=68.250000 acc-top5=86.729167 Batch [0199]/[0303]: acc-top1=67.953125 acc-top5=86.671875 Batch [0249]/[0303]: acc-top1=67.525000 acc-top5=86.725000 Batch [0299]/[0303]: acc-top1=67.614583 acc-top5=86.750000 [Epoch 088] training: accuracy=82.676197 loss=0.681979 [Epoch 088] speed: 71 samples/sec time cost: 3641.007096 [Epoch 088] validation: acc-top1=67.672236 acc-top5=86.788366 loss=1.638958 Epoch[089] Batch [0049]/[3760] Speed: 48.676787 samples/sec accuracy=81.656250 loss=0.715033 lr=0.000100 Epoch[089] Batch [0099]/[3760] Speed: 71.297631 samples/sec accuracy=82.500000 loss=0.693283 lr=0.000100 Epoch[089] Batch [0149]/[3760] Speed: 71.653498 samples/sec accuracy=82.854167 loss=0.687791 lr=0.000100 Epoch[089] Batch [0199]/[3760] Speed: 71.002369 samples/sec accuracy=82.906250 loss=0.681547 lr=0.000100 Epoch[089] Batch [0249]/[3760] Speed: 71.395079 samples/sec accuracy=82.906250 loss=0.681119 lr=0.000100 Epoch[089] Batch [0299]/[3760] Speed: 71.991770 samples/sec accuracy=82.947917 loss=0.683331 lr=0.000100 Epoch[089] Batch [0349]/[3760] Speed: 71.585905 samples/sec accuracy=82.875000 loss=0.682793 lr=0.000100 Epoch[089] Batch [0399]/[3760] Speed: 71.898394 samples/sec accuracy=82.925781 loss=0.677704 lr=0.000100 Epoch[089] Batch [0449]/[3760] Speed: 71.684699 samples/sec accuracy=82.993056 loss=0.676077 lr=0.000100 Epoch[089] Batch 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accuracy=82.730263 loss=0.674213 lr=0.000100 Epoch[089] Batch [0999]/[3760] Speed: 71.626208 samples/sec accuracy=82.710938 loss=0.674624 lr=0.000100 Epoch[089] Batch [1049]/[3760] Speed: 71.458396 samples/sec accuracy=82.693452 loss=0.674711 lr=0.000100 Epoch[089] Batch [1099]/[3760] Speed: 71.753971 samples/sec accuracy=82.680398 loss=0.674796 lr=0.000100 Epoch[089] Batch [1149]/[3760] Speed: 71.740869 samples/sec accuracy=82.672554 loss=0.675083 lr=0.000100 Epoch[089] Batch [1199]/[3760] Speed: 72.013607 samples/sec accuracy=82.723958 loss=0.672874 lr=0.000100 Epoch[089] Batch [1249]/[3760] Speed: 70.762543 samples/sec accuracy=82.690000 loss=0.674186 lr=0.000100 Epoch[089] Batch [1299]/[3760] Speed: 72.440215 samples/sec accuracy=82.659856 loss=0.674838 lr=0.000100 Epoch[089] Batch [1349]/[3760] Speed: 71.364253 samples/sec accuracy=82.653935 loss=0.675746 lr=0.000100 Epoch[089] Batch [1399]/[3760] Speed: 72.005010 samples/sec accuracy=82.638393 loss=0.677059 lr=0.000100 Epoch[089] 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accuracy=82.621711 loss=0.679540 lr=0.000100 Epoch[089] Batch [1949]/[3760] Speed: 71.362236 samples/sec accuracy=82.600962 loss=0.680112 lr=0.000100 Epoch[089] Batch [1999]/[3760] Speed: 71.847642 samples/sec accuracy=82.624219 loss=0.679323 lr=0.000100 Epoch[089] Batch [2049]/[3760] Speed: 72.104128 samples/sec accuracy=82.631098 loss=0.679522 lr=0.000100 Epoch[089] Batch [2099]/[3760] Speed: 71.055205 samples/sec accuracy=82.598214 loss=0.680687 lr=0.000100 Epoch[089] Batch [2149]/[3760] Speed: 71.569800 samples/sec accuracy=82.618459 loss=0.679920 lr=0.000100 Epoch[089] Batch [2199]/[3760] Speed: 71.399094 samples/sec accuracy=82.605114 loss=0.680244 lr=0.000100 Epoch[089] Batch [2249]/[3760] Speed: 71.566509 samples/sec accuracy=82.605556 loss=0.680412 lr=0.000100 Epoch[089] Batch [2299]/[3760] Speed: 72.327563 samples/sec accuracy=82.573370 loss=0.681369 lr=0.000100 Epoch[089] Batch [2349]/[3760] Speed: 71.275366 samples/sec accuracy=82.585106 loss=0.681477 lr=0.000100 Epoch[089] 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accuracy=82.593202 loss=0.682225 lr=0.000100 Epoch[089] Batch [2899]/[3760] Speed: 71.626837 samples/sec accuracy=82.615841 loss=0.681554 lr=0.000100 Epoch[089] Batch [2949]/[3760] Speed: 71.650715 samples/sec accuracy=82.611758 loss=0.681816 lr=0.000100 Epoch[089] Batch [2999]/[3760] Speed: 72.578841 samples/sec accuracy=82.602604 loss=0.681916 lr=0.000100 Epoch[089] Batch [3049]/[3760] Speed: 71.546422 samples/sec accuracy=82.606557 loss=0.681469 lr=0.000100 Epoch[089] Batch [3099]/[3760] Speed: 71.992029 samples/sec accuracy=82.615423 loss=0.681456 lr=0.000100 Epoch[089] Batch [3149]/[3760] Speed: 70.702045 samples/sec accuracy=82.616071 loss=0.681729 lr=0.000100 Epoch[089] Batch [3199]/[3760] Speed: 72.036580 samples/sec accuracy=82.618652 loss=0.681667 lr=0.000100 Epoch[089] Batch [3249]/[3760] Speed: 71.870942 samples/sec accuracy=82.626442 loss=0.681620 lr=0.000100 Epoch[089] Batch [3299]/[3760] Speed: 72.012978 samples/sec accuracy=82.629735 loss=0.681515 lr=0.000100 Epoch[089] Batch [3349]/[3760] Speed: 71.425702 samples/sec accuracy=82.621735 loss=0.681550 lr=0.000100 Epoch[089] Batch [3399]/[3760] Speed: 72.149500 samples/sec accuracy=82.624081 loss=0.681277 lr=0.000100 Epoch[089] Batch [3449]/[3760] Speed: 71.003006 samples/sec accuracy=82.639946 loss=0.681006 lr=0.000100 Epoch[089] Batch [3499]/[3760] Speed: 71.655049 samples/sec accuracy=82.640625 loss=0.681005 lr=0.000100 Epoch[089] Batch [3549]/[3760] Speed: 72.444559 samples/sec accuracy=82.643926 loss=0.681011 lr=0.000100 Epoch[089] Batch [3599]/[3760] Speed: 71.486760 samples/sec accuracy=82.632812 loss=0.681172 lr=0.000100 Epoch[089] Batch [3649]/[3760] Speed: 72.196856 samples/sec accuracy=82.622860 loss=0.681469 lr=0.000100 Epoch[089] Batch [3699]/[3760] Speed: 70.749844 samples/sec accuracy=82.625000 loss=0.681215 lr=0.000100 Epoch[089] Batch [3749]/[3760] Speed: 80.148876 samples/sec accuracy=82.626667 loss=0.681526 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.875000 acc-top5=88.093750 Batch [0099]/[0303]: acc-top1=69.125000 acc-top5=87.625000 Batch [0149]/[0303]: acc-top1=68.406250 acc-top5=86.687500 Batch [0199]/[0303]: acc-top1=68.109375 acc-top5=86.726562 Batch [0249]/[0303]: acc-top1=67.800000 acc-top5=86.675000 Batch [0299]/[0303]: acc-top1=67.796875 acc-top5=86.697917 [Epoch 089] training: accuracy=82.628408 loss=0.681408 [Epoch 089] speed: 71 samples/sec time cost: 3641.155981 [Epoch 089] validation: acc-top1=67.842409 acc-top5=86.731642 loss=1.660875 Epoch[090] Batch [0049]/[3759] Speed: 48.501423 samples/sec accuracy=82.531250 loss=0.671410 lr=0.000100 Epoch[090] Batch [0099]/[3759] Speed: 71.073410 samples/sec accuracy=82.734375 loss=0.671720 lr=0.000100 Epoch[090] Batch [0149]/[3759] Speed: 71.602332 samples/sec accuracy=83.229167 loss=0.654781 lr=0.000100 Epoch[090] Batch [0199]/[3759] Speed: 71.860850 samples/sec accuracy=82.906250 loss=0.665958 lr=0.000100 Epoch[090] Batch [0249]/[3759] Speed: 71.092189 samples/sec accuracy=83.000000 loss=0.668039 lr=0.000100 Epoch[090] Batch [0299]/[3759] Speed: 71.817623 samples/sec accuracy=83.015625 loss=0.666534 lr=0.000100 Epoch[090] Batch [0349]/[3759] Speed: 71.591395 samples/sec accuracy=82.919643 loss=0.670012 lr=0.000100 Epoch[090] Batch [0399]/[3759] Speed: 71.905975 samples/sec accuracy=82.820312 loss=0.671124 lr=0.000100 Epoch[090] Batch [0449]/[3759] Speed: 71.808181 samples/sec accuracy=82.760417 loss=0.674292 lr=0.000100 Epoch[090] Batch [0499]/[3759] Speed: 71.235671 samples/sec accuracy=82.753125 loss=0.676356 lr=0.000100 Epoch[090] Batch [0549]/[3759] Speed: 71.843024 samples/sec accuracy=82.750000 loss=0.674692 lr=0.000100 Epoch[090] Batch [0599]/[3759] Speed: 72.101830 samples/sec accuracy=82.677083 loss=0.678501 lr=0.000100 Epoch[090] Batch [0649]/[3759] Speed: 72.445439 samples/sec accuracy=82.697115 loss=0.679622 lr=0.000100 Epoch[090] Batch [0699]/[3759] Speed: 71.989283 samples/sec accuracy=82.720982 loss=0.678418 lr=0.000100 Epoch[090] Batch [0749]/[3759] Speed: 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lr=0.000100 Epoch[090] Batch [1249]/[3759] Speed: 71.686567 samples/sec accuracy=82.713750 loss=0.681149 lr=0.000100 Epoch[090] Batch [1299]/[3759] Speed: 71.985464 samples/sec accuracy=82.768029 loss=0.679019 lr=0.000100 Epoch[090] Batch [1349]/[3759] Speed: 72.377170 samples/sec accuracy=82.799769 loss=0.678169 lr=0.000100 Epoch[090] Batch [1399]/[3759] Speed: 71.651657 samples/sec accuracy=82.808036 loss=0.678332 lr=0.000100 Epoch[090] Batch [1449]/[3759] Speed: 71.419098 samples/sec accuracy=82.790948 loss=0.678157 lr=0.000100 Epoch[090] Batch [1499]/[3759] Speed: 72.659743 samples/sec accuracy=82.807292 loss=0.677822 lr=0.000100 Epoch[090] Batch [1549]/[3759] Speed: 71.488647 samples/sec accuracy=82.791331 loss=0.678104 lr=0.000100 Epoch[090] Batch [1599]/[3759] Speed: 71.632718 samples/sec accuracy=82.774414 loss=0.678843 lr=0.000100 Epoch[090] Batch [1649]/[3759] Speed: 72.313794 samples/sec accuracy=82.790720 loss=0.678264 lr=0.000100 Epoch[090] Batch [1699]/[3759] Speed: 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lr=0.000100 Epoch[090] Batch [3149]/[3759] Speed: 71.727716 samples/sec accuracy=82.772817 loss=0.678882 lr=0.000100 Epoch[090] Batch [3199]/[3759] Speed: 72.246347 samples/sec accuracy=82.761230 loss=0.679400 lr=0.000100 Epoch[090] Batch [3249]/[3759] Speed: 71.844526 samples/sec accuracy=82.746154 loss=0.680348 lr=0.000100 Epoch[090] Batch [3299]/[3759] Speed: 71.577053 samples/sec accuracy=82.762311 loss=0.680261 lr=0.000100 Epoch[090] Batch [3349]/[3759] Speed: 71.288700 samples/sec accuracy=82.773787 loss=0.680171 lr=0.000100 Epoch[090] Batch [3399]/[3759] Speed: 72.329927 samples/sec accuracy=82.776654 loss=0.679803 lr=0.000100 Epoch[090] Batch [3449]/[3759] Speed: 71.113119 samples/sec accuracy=82.768116 loss=0.680032 lr=0.000100 Epoch[090] Batch [3499]/[3759] Speed: 72.201081 samples/sec accuracy=82.764286 loss=0.679973 lr=0.000100 Epoch[090] Batch [3549]/[3759] Speed: 72.036177 samples/sec accuracy=82.762764 loss=0.680100 lr=0.000100 Epoch[090] Batch [3599]/[3759] Speed: 71.746110 samples/sec accuracy=82.782118 loss=0.679536 lr=0.000100 Epoch[090] Batch [3649]/[3759] Speed: 71.644568 samples/sec accuracy=82.776541 loss=0.679826 lr=0.000100 Epoch[090] Batch [3699]/[3759] Speed: 71.415151 samples/sec accuracy=82.783784 loss=0.679891 lr=0.000100 Epoch[090] Batch [3749]/[3759] Speed: 80.970055 samples/sec accuracy=82.782917 loss=0.680120 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.250000 acc-top5=88.031250 Batch [0099]/[0303]: acc-top1=69.109375 acc-top5=87.515625 Batch [0149]/[0303]: acc-top1=68.385417 acc-top5=86.812500 Batch [0199]/[0303]: acc-top1=68.101562 acc-top5=86.773438 Batch [0249]/[0303]: acc-top1=67.875000 acc-top5=86.712500 Batch [0299]/[0303]: acc-top1=67.906250 acc-top5=86.744792 [Epoch 090] training: accuracy=82.780909 loss=0.680044 [Epoch 090] speed: 71 samples/sec time cost: 3631.361845 [Epoch 090] validation: acc-top1=67.950701 acc-top5=86.772896 loss=1.625860 Epoch[091] Batch [0049]/[3760] Speed: 48.956318 samples/sec accuracy=84.125000 loss=0.636738 lr=0.000100 Epoch[091] Batch [0099]/[3760] Speed: 71.055042 samples/sec accuracy=83.046875 loss=0.659554 lr=0.000100 Epoch[091] Batch [0149]/[3760] Speed: 71.970189 samples/sec accuracy=82.968750 loss=0.668626 lr=0.000100 Epoch[091] Batch [0199]/[3760] Speed: 71.840150 samples/sec accuracy=82.781250 loss=0.670190 lr=0.000100 Epoch[091] Batch [0249]/[3760] Speed: 70.707554 samples/sec accuracy=82.781250 loss=0.668502 lr=0.000100 Epoch[091] Batch [0299]/[3760] Speed: 71.969981 samples/sec accuracy=82.937500 loss=0.663721 lr=0.000100 Epoch[091] Batch [0349]/[3760] Speed: 72.238408 samples/sec accuracy=82.816964 loss=0.671003 lr=0.000100 Epoch[091] Batch [0399]/[3760] Speed: 71.686033 samples/sec accuracy=82.988281 loss=0.666108 lr=0.000100 Epoch[091] Batch [0449]/[3760] Speed: 71.760042 samples/sec accuracy=82.968750 loss=0.668622 lr=0.000100 Epoch[091] Batch [0499]/[3760] Speed: 71.947144 samples/sec accuracy=83.053125 loss=0.665553 lr=0.000100 Epoch[091] 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accuracy=82.862500 loss=0.671088 lr=0.000100 Epoch[091] Batch [1049]/[3760] Speed: 72.122939 samples/sec accuracy=82.790179 loss=0.673515 lr=0.000100 Epoch[091] Batch [1099]/[3760] Speed: 72.342441 samples/sec accuracy=82.769886 loss=0.673739 lr=0.000100 Epoch[091] Batch [1149]/[3760] Speed: 72.709615 samples/sec accuracy=82.764946 loss=0.674587 lr=0.000100 Epoch[091] Batch [1199]/[3760] Speed: 71.662754 samples/sec accuracy=82.777344 loss=0.674745 lr=0.000100 Epoch[091] Batch [1249]/[3760] Speed: 71.201196 samples/sec accuracy=82.767500 loss=0.674540 lr=0.000100 Epoch[091] Batch [1299]/[3760] Speed: 72.213134 samples/sec accuracy=82.800481 loss=0.674233 lr=0.000100 Epoch[091] Batch [1349]/[3760] Speed: 71.988731 samples/sec accuracy=82.813657 loss=0.674013 lr=0.000100 Epoch[091] Batch [1399]/[3760] Speed: 71.915950 samples/sec accuracy=82.797991 loss=0.673903 lr=0.000100 Epoch[091] Batch [1449]/[3760] Speed: 71.032643 samples/sec accuracy=82.760776 loss=0.674582 lr=0.000100 Epoch[091] 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accuracy=82.711538 loss=0.678058 lr=0.000100 Epoch[091] Batch [1999]/[3760] Speed: 71.533065 samples/sec accuracy=82.702344 loss=0.678245 lr=0.000100 Epoch[091] Batch [2049]/[3760] Speed: 71.867793 samples/sec accuracy=82.698933 loss=0.678574 lr=0.000100 Epoch[091] Batch [2099]/[3760] Speed: 71.118982 samples/sec accuracy=82.700149 loss=0.677892 lr=0.000100 Epoch[091] Batch [2149]/[3760] Speed: 71.801431 samples/sec accuracy=82.696948 loss=0.677513 lr=0.000100 Epoch[091] Batch [2199]/[3760] Speed: 71.404980 samples/sec accuracy=82.688210 loss=0.677871 lr=0.000100 Epoch[091] Batch [2249]/[3760] Speed: 71.720847 samples/sec accuracy=82.668750 loss=0.678944 lr=0.000100 Epoch[091] Batch [2299]/[3760] Speed: 72.204587 samples/sec accuracy=82.678668 loss=0.678751 lr=0.000100 Epoch[091] Batch [2349]/[3760] Speed: 71.446843 samples/sec accuracy=82.669548 loss=0.679024 lr=0.000100 Epoch[091] Batch [2399]/[3760] Speed: 72.011230 samples/sec accuracy=82.646484 loss=0.680108 lr=0.000100 Epoch[091] Batch [2449]/[3760] Speed: 71.775617 samples/sec accuracy=82.671556 loss=0.679642 lr=0.000100 Epoch[091] Batch [2499]/[3760] Speed: 72.013320 samples/sec accuracy=82.668750 loss=0.680097 lr=0.000100 Epoch[091] Batch [2549]/[3760] Speed: 72.102170 samples/sec accuracy=82.667892 loss=0.679680 lr=0.000100 Epoch[091] Batch [2599]/[3760] Speed: 71.906020 samples/sec accuracy=82.664663 loss=0.679650 lr=0.000100 Epoch[091] Batch [2649]/[3760] Speed: 72.025546 samples/sec accuracy=82.680425 loss=0.678713 lr=0.000100 Epoch[091] Batch [2699]/[3760] Speed: 71.315458 samples/sec accuracy=82.680556 loss=0.678544 lr=0.000100 Epoch[091] Batch [2749]/[3760] Speed: 71.921527 samples/sec accuracy=82.698295 loss=0.678377 lr=0.000100 Epoch[091] Batch [2799]/[3760] Speed: 71.505810 samples/sec accuracy=82.707589 loss=0.677885 lr=0.000100 Epoch[091] Batch [2849]/[3760] Speed: 71.729399 samples/sec accuracy=82.708882 loss=0.677799 lr=0.000100 Epoch[091] Batch [2899]/[3760] Speed: 70.628339 samples/sec accuracy=82.716056 loss=0.677675 lr=0.000100 Epoch[091] Batch [2949]/[3760] Speed: 72.672768 samples/sec accuracy=82.705508 loss=0.677969 lr=0.000100 Epoch[091] Batch [2999]/[3760] Speed: 71.504159 samples/sec accuracy=82.705208 loss=0.678234 lr=0.000100 Epoch[091] Batch [3049]/[3760] Speed: 72.147030 samples/sec accuracy=82.705430 loss=0.678351 lr=0.000100 Epoch[091] Batch [3099]/[3760] Speed: 71.547728 samples/sec accuracy=82.712702 loss=0.678008 lr=0.000100 Epoch[091] Batch [3149]/[3760] Speed: 72.067395 samples/sec accuracy=82.730655 loss=0.677137 lr=0.000100 Epoch[091] Batch [3199]/[3760] Speed: 71.120512 samples/sec accuracy=82.729980 loss=0.677261 lr=0.000100 Epoch[091] Batch [3249]/[3760] Speed: 72.000107 samples/sec accuracy=82.726442 loss=0.677299 lr=0.000100 Epoch[091] Batch [3299]/[3760] Speed: 72.035471 samples/sec accuracy=82.721591 loss=0.677502 lr=0.000100 Epoch[091] Batch [3349]/[3760] Speed: 71.470149 samples/sec accuracy=82.699160 loss=0.677727 lr=0.000100 Epoch[091] Batch [3399]/[3760] Speed: 71.603461 samples/sec accuracy=82.703585 loss=0.677333 lr=0.000100 Epoch[091] Batch [3449]/[3760] Speed: 71.681583 samples/sec accuracy=82.718750 loss=0.676807 lr=0.000100 Epoch[091] Batch [3499]/[3760] Speed: 71.939406 samples/sec accuracy=82.737500 loss=0.675919 lr=0.000100 Epoch[091] Batch [3549]/[3760] Speed: 71.281640 samples/sec accuracy=82.730634 loss=0.676255 lr=0.000100 Epoch[091] Batch [3599]/[3760] Speed: 71.436792 samples/sec accuracy=82.726128 loss=0.676785 lr=0.000100 Epoch[091] Batch [3649]/[3760] Speed: 71.256038 samples/sec accuracy=82.708904 loss=0.677393 lr=0.000100 Epoch[091] Batch [3699]/[3760] Speed: 72.436248 samples/sec accuracy=82.711571 loss=0.676827 lr=0.000100 Epoch[091] Batch [3749]/[3760] Speed: 79.050384 samples/sec accuracy=82.701667 loss=0.676716 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.875000 acc-top5=87.843750 Batch [0099]/[0303]: acc-top1=68.875000 acc-top5=87.484375 Batch [0149]/[0303]: acc-top1=68.197917 acc-top5=86.697917 Batch [0199]/[0303]: acc-top1=67.882812 acc-top5=86.718750 Batch [0249]/[0303]: acc-top1=67.575000 acc-top5=86.712500 Batch [0299]/[0303]: acc-top1=67.619792 acc-top5=86.739583 [Epoch 091] training: accuracy=82.701546 loss=0.676754 [Epoch 091] speed: 71 samples/sec time cost: 3637.494797 [Epoch 091] validation: acc-top1=67.646452 acc-top5=86.778053 loss=1.658407 Epoch[092] Batch [0049]/[3760] Speed: 48.390373 samples/sec accuracy=81.812500 loss=0.691132 lr=0.000100 Epoch[092] Batch [0099]/[3760] Speed: 70.118566 samples/sec accuracy=82.687500 loss=0.671375 lr=0.000100 Epoch[092] Batch [0149]/[3760] Speed: 71.902485 samples/sec accuracy=83.062500 loss=0.665031 lr=0.000100 Epoch[092] Batch [0199]/[3760] Speed: 71.587229 samples/sec accuracy=83.296875 loss=0.662115 lr=0.000100 Epoch[092] Batch [0249]/[3760] Speed: 71.999868 samples/sec accuracy=82.918750 loss=0.674252 lr=0.000100 Epoch[092] Batch [0299]/[3760] Speed: 72.193192 samples/sec accuracy=83.000000 loss=0.674547 lr=0.000100 Epoch[092] Batch [0349]/[3760] Speed: 71.115576 samples/sec accuracy=82.924107 loss=0.676915 lr=0.000100 Epoch[092] Batch [0399]/[3760] Speed: 71.862922 samples/sec accuracy=82.800781 loss=0.678773 lr=0.000100 Epoch[092] Batch [0449]/[3760] Speed: 71.868513 samples/sec accuracy=82.871528 loss=0.678216 lr=0.000100 Epoch[092] Batch [0499]/[3760] Speed: 71.731979 samples/sec accuracy=82.940625 loss=0.674377 lr=0.000100 Epoch[092] Batch [0549]/[3760] Speed: 71.871641 samples/sec accuracy=82.886364 loss=0.677597 lr=0.000100 Epoch[092] Batch [0599]/[3760] Speed: 71.322874 samples/sec accuracy=82.955729 loss=0.676792 lr=0.000100 Epoch[092] Batch [0649]/[3760] Speed: 71.596395 samples/sec accuracy=82.930288 loss=0.676851 lr=0.000100 Epoch[092] Batch [0699]/[3760] Speed: 72.351011 samples/sec accuracy=82.848214 loss=0.679290 lr=0.000100 Epoch[092] Batch [0749]/[3760] Speed: 71.712116 samples/sec accuracy=82.872917 loss=0.677835 lr=0.000100 Epoch[092] Batch 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accuracy=82.875000 loss=0.675743 lr=0.000100 Epoch[092] Batch [1299]/[3760] Speed: 71.996469 samples/sec accuracy=82.837740 loss=0.676010 lr=0.000100 Epoch[092] Batch [1349]/[3760] Speed: 71.695110 samples/sec accuracy=82.802083 loss=0.676748 lr=0.000100 Epoch[092] Batch [1399]/[3760] Speed: 71.436264 samples/sec accuracy=82.786830 loss=0.676730 lr=0.000100 Epoch[092] Batch [1449]/[3760] Speed: 71.291437 samples/sec accuracy=82.803879 loss=0.676147 lr=0.000100 Epoch[092] Batch [1499]/[3760] Speed: 72.240840 samples/sec accuracy=82.798958 loss=0.676567 lr=0.000100 Epoch[092] Batch [1549]/[3760] Speed: 71.193051 samples/sec accuracy=82.788306 loss=0.677534 lr=0.000100 Epoch[092] Batch [1599]/[3760] Speed: 71.784964 samples/sec accuracy=82.807617 loss=0.676583 lr=0.000100 Epoch[092] Batch [1649]/[3760] Speed: 72.502492 samples/sec accuracy=82.804924 loss=0.677463 lr=0.000100 Epoch[092] Batch [1699]/[3760] Speed: 71.739388 samples/sec accuracy=82.793199 loss=0.677541 lr=0.000100 Epoch[092] 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accuracy=82.813210 loss=0.677007 lr=0.000100 Epoch[092] Batch [2249]/[3760] Speed: 71.973465 samples/sec accuracy=82.811806 loss=0.676737 lr=0.000100 Epoch[092] Batch [2299]/[3760] Speed: 71.514089 samples/sec accuracy=82.808424 loss=0.677166 lr=0.000100 Epoch[092] Batch [2349]/[3760] Speed: 71.174402 samples/sec accuracy=82.796543 loss=0.677269 lr=0.000100 Epoch[092] Batch [2399]/[3760] Speed: 72.060036 samples/sec accuracy=82.781901 loss=0.677671 lr=0.000100 Epoch[092] Batch [2449]/[3760] Speed: 71.287064 samples/sec accuracy=82.769133 loss=0.677868 lr=0.000100 Epoch[092] Batch [2499]/[3760] Speed: 72.214675 samples/sec accuracy=82.750000 loss=0.678461 lr=0.000100 Epoch[092] Batch [2549]/[3760] Speed: 71.901466 samples/sec accuracy=82.763480 loss=0.678230 lr=0.000100 Epoch[092] Batch [2599]/[3760] Speed: 71.175859 samples/sec accuracy=82.745192 loss=0.678384 lr=0.000100 Epoch[092] Batch [2649]/[3760] Speed: 72.179123 samples/sec accuracy=82.749410 loss=0.678171 lr=0.000100 Epoch[092] 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accuracy=82.721726 loss=0.678098 lr=0.000100 Epoch[092] Batch [3199]/[3760] Speed: 71.527757 samples/sec accuracy=82.719238 loss=0.678089 lr=0.000100 Epoch[092] Batch [3249]/[3760] Speed: 71.443496 samples/sec accuracy=82.725000 loss=0.677979 lr=0.000100 Epoch[092] Batch [3299]/[3760] Speed: 72.090290 samples/sec accuracy=82.714962 loss=0.678281 lr=0.000100 Epoch[092] Batch [3349]/[3760] Speed: 71.329613 samples/sec accuracy=82.717817 loss=0.678144 lr=0.000100 Epoch[092] Batch [3399]/[3760] Speed: 71.348778 samples/sec accuracy=82.725184 loss=0.677798 lr=0.000100 Epoch[092] Batch [3449]/[3760] Speed: 72.152795 samples/sec accuracy=82.744565 loss=0.676997 lr=0.000100 Epoch[092] Batch [3499]/[3760] Speed: 71.322284 samples/sec accuracy=82.741071 loss=0.676775 lr=0.000100 Epoch[092] Batch [3549]/[3760] Speed: 72.482654 samples/sec accuracy=82.732835 loss=0.677044 lr=0.000100 Epoch[092] Batch [3599]/[3760] Speed: 71.783397 samples/sec accuracy=82.739583 loss=0.676850 lr=0.000100 Epoch[092] Batch [3649]/[3760] Speed: 72.031252 samples/sec accuracy=82.746147 loss=0.676637 lr=0.000100 Epoch[092] Batch [3699]/[3760] Speed: 71.497144 samples/sec accuracy=82.765625 loss=0.675767 lr=0.000100 Epoch[092] Batch [3749]/[3760] Speed: 80.051426 samples/sec accuracy=82.770000 loss=0.675564 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.062500 acc-top5=88.000000 Batch [0099]/[0303]: acc-top1=68.890625 acc-top5=87.562500 Batch [0149]/[0303]: acc-top1=68.156250 acc-top5=86.770833 Batch [0199]/[0303]: acc-top1=67.937500 acc-top5=86.757812 Batch [0249]/[0303]: acc-top1=67.606250 acc-top5=86.750000 Batch [0299]/[0303]: acc-top1=67.656250 acc-top5=86.812500 [Epoch 092] training: accuracy=82.773438 loss=0.675398 [Epoch 092] speed: 71 samples/sec time cost: 3637.486332 [Epoch 092] validation: acc-top1=67.713490 acc-top5=86.839934 loss=1.638891 Epoch[093] Batch [0049]/[3759] Speed: 48.554131 samples/sec accuracy=83.281250 loss=0.648167 lr=0.000100 Epoch[093] Batch [0099]/[3759] Speed: 70.032260 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lr=0.000100 Epoch[093] Batch [0599]/[3759] Speed: 71.637380 samples/sec accuracy=82.643229 loss=0.675450 lr=0.000100 Epoch[093] Batch [0649]/[3759] Speed: 71.203150 samples/sec accuracy=82.687500 loss=0.674161 lr=0.000100 Epoch[093] Batch [0699]/[3759] Speed: 71.531024 samples/sec accuracy=82.678571 loss=0.675599 lr=0.000100 Epoch[093] Batch [0749]/[3759] Speed: 71.744265 samples/sec accuracy=82.681250 loss=0.675305 lr=0.000100 Epoch[093] Batch [0799]/[3759] Speed: 71.614373 samples/sec accuracy=82.662109 loss=0.675564 lr=0.000100 Epoch[093] Batch [0849]/[3759] Speed: 71.783034 samples/sec accuracy=82.713235 loss=0.674574 lr=0.000100 Epoch[093] Batch [0899]/[3759] Speed: 72.210608 samples/sec accuracy=82.727431 loss=0.674157 lr=0.000100 Epoch[093] Batch [0949]/[3759] Speed: 71.590275 samples/sec accuracy=82.750000 loss=0.673556 lr=0.000100 Epoch[093] Batch [0999]/[3759] Speed: 72.393353 samples/sec accuracy=82.773438 loss=0.672396 lr=0.000100 Epoch[093] Batch [1049]/[3759] Speed: 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lr=0.000100 Epoch[093] Batch [1549]/[3759] Speed: 71.170000 samples/sec accuracy=82.889113 loss=0.671723 lr=0.000100 Epoch[093] Batch [1599]/[3759] Speed: 71.618081 samples/sec accuracy=82.895508 loss=0.671338 lr=0.000100 Epoch[093] Batch [1649]/[3759] Speed: 71.403139 samples/sec accuracy=82.881629 loss=0.671373 lr=0.000100 Epoch[093] Batch [1699]/[3759] Speed: 72.351056 samples/sec accuracy=82.868566 loss=0.672134 lr=0.000100 Epoch[093] Batch [1749]/[3759] Speed: 71.610227 samples/sec accuracy=82.846429 loss=0.672527 lr=0.000100 Epoch[093] Batch [1799]/[3759] Speed: 72.166612 samples/sec accuracy=82.902778 loss=0.670454 lr=0.000100 Epoch[093] Batch [1849]/[3759] Speed: 71.477955 samples/sec accuracy=82.918074 loss=0.669702 lr=0.000100 Epoch[093] Batch [1899]/[3759] Speed: 71.867152 samples/sec accuracy=82.921053 loss=0.669457 lr=0.000100 Epoch[093] Batch [1949]/[3759] Speed: 71.856588 samples/sec accuracy=82.900641 loss=0.669798 lr=0.000100 Epoch[093] Batch [1999]/[3759] Speed: 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lr=0.000100 Epoch[093] Batch [2499]/[3759] Speed: 71.905849 samples/sec accuracy=82.883125 loss=0.671411 lr=0.000100 Epoch[093] Batch [2549]/[3759] Speed: 71.599699 samples/sec accuracy=82.889093 loss=0.671248 lr=0.000100 Epoch[093] Batch [2599]/[3759] Speed: 71.737807 samples/sec accuracy=82.864784 loss=0.671876 lr=0.000100 Epoch[093] Batch [2649]/[3759] Speed: 71.664749 samples/sec accuracy=82.870283 loss=0.672059 lr=0.000100 Epoch[093] Batch [2699]/[3759] Speed: 71.880266 samples/sec accuracy=82.854745 loss=0.672494 lr=0.000100 Epoch[093] Batch [2749]/[3759] Speed: 72.322852 samples/sec accuracy=82.832386 loss=0.673234 lr=0.000100 Epoch[093] Batch [2799]/[3759] Speed: 70.234875 samples/sec accuracy=82.851562 loss=0.672530 lr=0.000100 Epoch[093] Batch [2849]/[3759] Speed: 71.784467 samples/sec accuracy=82.847588 loss=0.673296 lr=0.000100 Epoch[093] Batch [2899]/[3759] Speed: 71.722543 samples/sec accuracy=82.869073 loss=0.672652 lr=0.000100 Epoch[093] Batch [2949]/[3759] Speed: 72.321573 samples/sec accuracy=82.867585 loss=0.672533 lr=0.000100 Epoch[093] Batch [2999]/[3759] Speed: 71.555306 samples/sec accuracy=82.848958 loss=0.673137 lr=0.000100 Epoch[093] Batch [3049]/[3759] Speed: 71.266886 samples/sec accuracy=82.837090 loss=0.673463 lr=0.000100 Epoch[093] Batch [3099]/[3759] Speed: 71.522198 samples/sec accuracy=82.854839 loss=0.672798 lr=0.000100 Epoch[093] Batch [3149]/[3759] Speed: 71.748375 samples/sec accuracy=82.852183 loss=0.673035 lr=0.000100 Epoch[093] Batch [3199]/[3759] Speed: 71.665242 samples/sec accuracy=82.852051 loss=0.672967 lr=0.000100 Epoch[093] Batch [3249]/[3759] Speed: 72.308473 samples/sec accuracy=82.849038 loss=0.672882 lr=0.000100 Epoch[093] Batch [3299]/[3759] Speed: 71.762607 samples/sec accuracy=82.850379 loss=0.673035 lr=0.000100 Epoch[093] Batch [3349]/[3759] Speed: 71.567878 samples/sec accuracy=82.852612 loss=0.673445 lr=0.000100 Epoch[093] Batch [3399]/[3759] Speed: 71.612804 samples/sec accuracy=82.850184 loss=0.673697 lr=0.000100 Epoch[093] Batch [3449]/[3759] Speed: 71.323607 samples/sec accuracy=82.852808 loss=0.673538 lr=0.000100 Epoch[093] Batch [3499]/[3759] Speed: 72.125066 samples/sec accuracy=82.862054 loss=0.673435 lr=0.000100 Epoch[093] Batch [3549]/[3759] Speed: 71.358219 samples/sec accuracy=82.874560 loss=0.673134 lr=0.000100 Epoch[093] Batch [3599]/[3759] Speed: 72.092026 samples/sec accuracy=82.871094 loss=0.673452 lr=0.000100 Epoch[093] Batch [3649]/[3759] Speed: 71.537414 samples/sec accuracy=82.854452 loss=0.674232 lr=0.000100 Epoch[093] Batch [3699]/[3759] Speed: 72.001113 samples/sec accuracy=82.860642 loss=0.673759 lr=0.000100 Epoch[093] Batch [3749]/[3759] Speed: 80.315153 samples/sec accuracy=82.847083 loss=0.674165 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.062500 acc-top5=88.093750 Batch [0099]/[0303]: acc-top1=68.937500 acc-top5=87.406250 Batch [0149]/[0303]: acc-top1=68.156250 acc-top5=86.677083 Batch [0199]/[0303]: acc-top1=67.875000 acc-top5=86.632812 Batch [0249]/[0303]: acc-top1=67.493750 acc-top5=86.562500 Batch [0299]/[0303]: acc-top1=67.494792 acc-top5=86.567708 [Epoch 093] training: accuracy=82.847001 loss=0.674143 [Epoch 093] speed: 71 samples/sec time cost: 3639.531826 [Epoch 093] validation: acc-top1=67.538160 acc-top5=86.592409 loss=1.658839 Epoch[094] Batch [0049]/[3760] Speed: 48.355551 samples/sec accuracy=82.718750 loss=0.664628 lr=0.000100 Epoch[094] Batch [0099]/[3760] Speed: 70.746286 samples/sec accuracy=82.468750 loss=0.688441 lr=0.000100 Epoch[094] Batch [0149]/[3760] Speed: 71.560496 samples/sec accuracy=82.718750 loss=0.672411 lr=0.000100 Epoch[094] Batch [0199]/[3760] Speed: 71.777801 samples/sec accuracy=82.695312 loss=0.672395 lr=0.000100 Epoch[094] Batch [0249]/[3760] Speed: 71.764288 samples/sec accuracy=82.693750 loss=0.676244 lr=0.000100 Epoch[094] Batch [0299]/[3760] Speed: 71.718423 samples/sec accuracy=82.828125 loss=0.673682 lr=0.000100 Epoch[094] Batch [0349]/[3760] Speed: 71.626659 samples/sec accuracy=82.665179 loss=0.680568 lr=0.000100 Epoch[094] Batch [0399]/[3760] Speed: 72.100197 samples/sec accuracy=82.957031 loss=0.670338 lr=0.000100 Epoch[094] Batch [0449]/[3760] Speed: 71.316915 samples/sec accuracy=83.045139 loss=0.666500 lr=0.000100 Epoch[094] Batch [0499]/[3760] Speed: 71.599460 samples/sec accuracy=82.896875 loss=0.669695 lr=0.000100 Epoch[094] Batch [0549]/[3760] Speed: 71.519943 samples/sec accuracy=82.914773 loss=0.671875 lr=0.000100 Epoch[094] Batch [0599]/[3760] Speed: 72.059626 samples/sec accuracy=82.942708 loss=0.669692 lr=0.000100 Epoch[094] Batch [0649]/[3760] Speed: 71.665304 samples/sec accuracy=82.903846 loss=0.671695 lr=0.000100 Epoch[094] Batch [0699]/[3760] Speed: 71.199984 samples/sec accuracy=82.883929 loss=0.672250 lr=0.000100 Epoch[094] Batch [0749]/[3760] Speed: 71.880047 samples/sec accuracy=82.870833 loss=0.673067 lr=0.000100 Epoch[094] Batch [0799]/[3760] Speed: 71.956010 samples/sec accuracy=82.851562 loss=0.674621 lr=0.000100 Epoch[094] 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accuracy=82.929087 loss=0.669649 lr=0.000100 Epoch[094] Batch [1349]/[3760] Speed: 71.955371 samples/sec accuracy=82.949074 loss=0.669122 lr=0.000100 Epoch[094] Batch [1399]/[3760] Speed: 71.939139 samples/sec accuracy=82.957589 loss=0.669536 lr=0.000100 Epoch[094] Batch [1449]/[3760] Speed: 71.313746 samples/sec accuracy=82.966595 loss=0.668367 lr=0.000100 Epoch[094] Batch [1499]/[3760] Speed: 71.633117 samples/sec accuracy=82.914583 loss=0.670474 lr=0.000100 Epoch[094] Batch [1549]/[3760] Speed: 70.801246 samples/sec accuracy=82.905242 loss=0.671227 lr=0.000100 Epoch[094] Batch [1599]/[3760] Speed: 72.187443 samples/sec accuracy=82.862305 loss=0.672098 lr=0.000100 Epoch[094] Batch [1649]/[3760] Speed: 72.358443 samples/sec accuracy=82.878788 loss=0.672422 lr=0.000100 Epoch[094] Batch [1699]/[3760] Speed: 72.287841 samples/sec accuracy=82.896140 loss=0.672356 lr=0.000100 Epoch[094] Batch [1749]/[3760] Speed: 71.294917 samples/sec accuracy=82.880357 loss=0.673194 lr=0.000100 Epoch[094] 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accuracy=82.865278 loss=0.674262 lr=0.000100 Epoch[094] Batch [2299]/[3760] Speed: 71.969954 samples/sec accuracy=82.877717 loss=0.673802 lr=0.000100 Epoch[094] Batch [2349]/[3760] Speed: 71.677627 samples/sec accuracy=82.857713 loss=0.674335 lr=0.000100 Epoch[094] Batch [2399]/[3760] Speed: 70.706264 samples/sec accuracy=82.859375 loss=0.673706 lr=0.000100 Epoch[094] Batch [2449]/[3760] Speed: 72.233699 samples/sec accuracy=82.855867 loss=0.673758 lr=0.000100 Epoch[094] Batch [2499]/[3760] Speed: 72.217740 samples/sec accuracy=82.868125 loss=0.673218 lr=0.000100 Epoch[094] Batch [2549]/[3760] Speed: 71.490618 samples/sec accuracy=82.886642 loss=0.672693 lr=0.000100 Epoch[094] Batch [2599]/[3760] Speed: 71.655041 samples/sec accuracy=82.912861 loss=0.671620 lr=0.000100 Epoch[094] Batch [2649]/[3760] Speed: 72.359195 samples/sec accuracy=82.916863 loss=0.671408 lr=0.000100 Epoch[094] Batch [2699]/[3760] Speed: 71.966667 samples/sec accuracy=82.907407 loss=0.671637 lr=0.000100 Epoch[094] Batch [2749]/[3760] Speed: 71.330878 samples/sec accuracy=82.889205 loss=0.672447 lr=0.000100 Epoch[094] Batch [2799]/[3760] Speed: 70.740446 samples/sec accuracy=82.876674 loss=0.673296 lr=0.000100 Epoch[094] Batch [2849]/[3760] Speed: 72.310507 samples/sec accuracy=82.876645 loss=0.672945 lr=0.000100 Epoch[094] Batch [2899]/[3760] Speed: 71.742996 samples/sec accuracy=82.878233 loss=0.672844 lr=0.000100 Epoch[094] Batch [2949]/[3760] Speed: 72.343266 samples/sec accuracy=82.886653 loss=0.672681 lr=0.000100 Epoch[094] Batch [2999]/[3760] Speed: 71.532949 samples/sec accuracy=82.908854 loss=0.671892 lr=0.000100 Epoch[094] Batch [3049]/[3760] Speed: 71.296332 samples/sec accuracy=82.903689 loss=0.672385 lr=0.000100 Epoch[094] Batch [3099]/[3760] Speed: 71.307321 samples/sec accuracy=82.922379 loss=0.671831 lr=0.000100 Epoch[094] Batch [3149]/[3760] Speed: 72.301573 samples/sec accuracy=82.924603 loss=0.671773 lr=0.000100 Epoch[094] Batch [3199]/[3760] Speed: 71.245268 samples/sec accuracy=82.939941 loss=0.671371 lr=0.000100 Epoch[094] Batch [3249]/[3760] Speed: 71.199201 samples/sec accuracy=82.938942 loss=0.671378 lr=0.000100 Epoch[094] Batch [3299]/[3760] Speed: 72.172091 samples/sec accuracy=82.944602 loss=0.671158 lr=0.000100 Epoch[094] Batch [3349]/[3760] Speed: 71.544921 samples/sec accuracy=82.948694 loss=0.670901 lr=0.000100 Epoch[094] Batch [3399]/[3760] Speed: 72.201456 samples/sec accuracy=82.927390 loss=0.670933 lr=0.000100 Epoch[094] Batch [3449]/[3760] Speed: 70.900091 samples/sec accuracy=82.932065 loss=0.670829 lr=0.000100 Epoch[094] Batch [3499]/[3760] Speed: 72.527428 samples/sec accuracy=82.934375 loss=0.670661 lr=0.000100 Epoch[094] Batch [3549]/[3760] Speed: 72.341357 samples/sec accuracy=82.941461 loss=0.670301 lr=0.000100 Epoch[094] Batch [3599]/[3760] Speed: 72.009024 samples/sec accuracy=82.941406 loss=0.670038 lr=0.000100 Epoch[094] Batch [3649]/[3760] Speed: 71.542958 samples/sec accuracy=82.941781 loss=0.670204 lr=0.000100 Epoch[094] Batch [3699]/[3760] Speed: 71.513139 samples/sec accuracy=82.948480 loss=0.670043 lr=0.000100 Epoch[094] Batch [3749]/[3760] Speed: 79.606542 samples/sec accuracy=82.956667 loss=0.669896 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.937500 acc-top5=87.781250 Batch [0099]/[0303]: acc-top1=68.828125 acc-top5=87.484375 Batch [0149]/[0303]: acc-top1=68.104167 acc-top5=86.822917 Batch [0199]/[0303]: acc-top1=67.914062 acc-top5=86.781250 Batch [0249]/[0303]: acc-top1=67.656250 acc-top5=86.806250 Batch [0299]/[0303]: acc-top1=67.718750 acc-top5=86.843750 [Epoch 094] training: accuracy=82.953374 loss=0.669869 [Epoch 094] speed: 71 samples/sec time cost: 3637.177504 [Epoch 094] validation: acc-top1=67.744431 acc-top5=86.865718 loss=1.646764 Epoch[095] Batch [0049]/[3760] Speed: 47.877766 samples/sec accuracy=82.468750 loss=0.680730 lr=0.000100 Epoch[095] Batch [0099]/[3760] Speed: 71.247717 samples/sec accuracy=82.890625 loss=0.663693 lr=0.000100 Epoch[095] Batch [0149]/[3760] Speed: 70.943244 samples/sec accuracy=82.937500 loss=0.663333 lr=0.000100 Epoch[095] Batch [0199]/[3760] Speed: 71.644578 samples/sec accuracy=83.046875 loss=0.665311 lr=0.000100 Epoch[095] Batch [0249]/[3760] Speed: 71.792097 samples/sec accuracy=82.793750 loss=0.672696 lr=0.000100 Epoch[095] Batch [0299]/[3760] Speed: 70.407090 samples/sec accuracy=82.911458 loss=0.667434 lr=0.000100 Epoch[095] Batch [0349]/[3760] Speed: 72.344167 samples/sec accuracy=82.941964 loss=0.667291 lr=0.000100 Epoch[095] Batch [0399]/[3760] Speed: 72.186267 samples/sec accuracy=82.960938 loss=0.664597 lr=0.000100 Epoch[095] Batch [0449]/[3760] Speed: 71.715935 samples/sec accuracy=83.055556 loss=0.660619 lr=0.000100 Epoch[095] Batch [0499]/[3760] Speed: 71.885303 samples/sec accuracy=82.996875 loss=0.663870 lr=0.000100 Epoch[095] Batch [0549]/[3760] Speed: 71.964215 samples/sec accuracy=82.954545 loss=0.669002 lr=0.000100 Epoch[095] Batch [0599]/[3760] Speed: 72.087381 samples/sec accuracy=82.908854 loss=0.670782 lr=0.000100 Epoch[095] Batch [0649]/[3760] Speed: 71.444550 samples/sec accuracy=82.855769 loss=0.672028 lr=0.000100 Epoch[095] Batch [0699]/[3760] Speed: 72.037941 samples/sec accuracy=82.872768 loss=0.671919 lr=0.000100 Epoch[095] Batch [0749]/[3760] Speed: 71.876409 samples/sec accuracy=82.872917 loss=0.673601 lr=0.000100 Epoch[095] Batch [0799]/[3760] Speed: 71.269591 samples/sec accuracy=82.890625 loss=0.672845 lr=0.000100 Epoch[095] Batch [0849]/[3760] Speed: 71.628850 samples/sec accuracy=82.950368 loss=0.670573 lr=0.000100 Epoch[095] Batch [0899]/[3760] Speed: 71.348327 samples/sec accuracy=82.972222 loss=0.670171 lr=0.000100 Epoch[095] Batch [0949]/[3760] Speed: 71.634890 samples/sec accuracy=82.973684 loss=0.670729 lr=0.000100 Epoch[095] Batch [0999]/[3760] Speed: 71.229512 samples/sec accuracy=83.015625 loss=0.669260 lr=0.000100 Epoch[095] Batch [1049]/[3760] Speed: 72.048758 samples/sec accuracy=83.037202 loss=0.667523 lr=0.000100 Epoch[095] Batch [1099]/[3760] Speed: 72.149095 samples/sec accuracy=83.045455 loss=0.667169 lr=0.000100 Epoch[095] Batch [1149]/[3760] Speed: 71.681087 samples/sec accuracy=83.069293 loss=0.666920 lr=0.000100 Epoch[095] Batch [1199]/[3760] Speed: 71.676746 samples/sec accuracy=83.119792 loss=0.665280 lr=0.000100 Epoch[095] Batch [1249]/[3760] Speed: 71.360533 samples/sec accuracy=83.126250 loss=0.665212 lr=0.000100 Epoch[095] Batch [1299]/[3760] Speed: 71.294768 samples/sec accuracy=83.093750 loss=0.666474 lr=0.000100 Epoch[095] Batch [1349]/[3760] Speed: 71.923337 samples/sec accuracy=83.086806 loss=0.666656 lr=0.000100 Epoch[095] Batch [1399]/[3760] Speed: 71.656426 samples/sec accuracy=83.073661 loss=0.666622 lr=0.000100 Epoch[095] Batch [1449]/[3760] Speed: 71.693732 samples/sec accuracy=83.078664 loss=0.666410 lr=0.000100 Epoch[095] Batch [1499]/[3760] Speed: 71.993465 samples/sec accuracy=83.115625 loss=0.666376 lr=0.000100 Epoch[095] Batch [1549]/[3760] Speed: 71.451987 samples/sec accuracy=83.115927 loss=0.667126 lr=0.000100 Epoch[095] Batch [1599]/[3760] Speed: 71.849527 samples/sec accuracy=83.119141 loss=0.667324 lr=0.000100 Epoch[095] Batch [1649]/[3760] Speed: 72.211502 samples/sec accuracy=83.107955 loss=0.667315 lr=0.000100 Epoch[095] Batch [1699]/[3760] Speed: 71.652599 samples/sec accuracy=83.123162 loss=0.667064 lr=0.000100 Epoch[095] Batch [1749]/[3760] Speed: 71.984274 samples/sec accuracy=83.116071 loss=0.667594 lr=0.000100 Epoch[095] Batch [1799]/[3760] Speed: 71.482206 samples/sec accuracy=83.070312 loss=0.668508 lr=0.000100 Epoch[095] Batch [1849]/[3760] Speed: 71.419553 samples/sec accuracy=83.097128 loss=0.666802 lr=0.000100 Epoch[095] Batch [1899]/[3760] Speed: 71.821124 samples/sec accuracy=83.113487 loss=0.666424 lr=0.000100 Epoch[095] Batch [1949]/[3760] Speed: 71.843491 samples/sec accuracy=83.113782 loss=0.666670 lr=0.000100 Epoch[095] Batch [1999]/[3760] Speed: 71.709915 samples/sec accuracy=83.118750 loss=0.666435 lr=0.000100 Epoch[095] Batch [2049]/[3760] Speed: 71.389036 samples/sec accuracy=83.086890 loss=0.666928 lr=0.000100 Epoch[095] Batch [2099]/[3760] Speed: 72.265742 samples/sec accuracy=83.062500 loss=0.667446 lr=0.000100 Epoch[095] Batch [2149]/[3760] Speed: 71.130680 samples/sec accuracy=83.041424 loss=0.667547 lr=0.000100 Epoch[095] Batch [2199]/[3760] Speed: 70.997974 samples/sec accuracy=83.049716 loss=0.667278 lr=0.000100 Epoch[095] Batch [2249]/[3760] Speed: 71.923488 samples/sec accuracy=83.025000 loss=0.668210 lr=0.000100 Epoch[095] Batch [2299]/[3760] Speed: 71.842185 samples/sec accuracy=83.008832 loss=0.668950 lr=0.000100 Epoch[095] Batch [2349]/[3760] Speed: 71.226715 samples/sec accuracy=82.985372 loss=0.669478 lr=0.000100 Epoch[095] Batch [2399]/[3760] Speed: 72.331892 samples/sec accuracy=82.989583 loss=0.669362 lr=0.000100 Epoch[095] Batch [2449]/[3760] Speed: 71.991112 samples/sec accuracy=82.991071 loss=0.669559 lr=0.000100 Epoch[095] Batch [2499]/[3760] Speed: 71.527980 samples/sec accuracy=83.016250 loss=0.668704 lr=0.000100 Epoch[095] Batch [2549]/[3760] Speed: 71.275959 samples/sec accuracy=83.007966 loss=0.669015 lr=0.000100 Epoch[095] Batch [2599]/[3760] Speed: 71.877965 samples/sec accuracy=83.004808 loss=0.669179 lr=0.000100 Epoch[095] Batch [2649]/[3760] Speed: 72.283435 samples/sec accuracy=83.003538 loss=0.669087 lr=0.000100 Epoch[095] Batch [2699]/[3760] Speed: 71.139216 samples/sec accuracy=83.004630 loss=0.669165 lr=0.000100 Epoch[095] Batch [2749]/[3760] Speed: 72.189901 samples/sec accuracy=83.003409 loss=0.669219 lr=0.000100 Epoch[095] Batch [2799]/[3760] Speed: 71.807685 samples/sec accuracy=82.999442 loss=0.669947 lr=0.000100 Epoch[095] Batch [2849]/[3760] Speed: 70.775840 samples/sec accuracy=83.010417 loss=0.669359 lr=0.000100 Epoch[095] Batch [2899]/[3760] Speed: 72.397659 samples/sec accuracy=83.010776 loss=0.669246 lr=0.000100 Epoch[095] Batch [2949]/[3760] Speed: 71.773711 samples/sec accuracy=82.992055 loss=0.670157 lr=0.000100 Epoch[095] Batch [2999]/[3760] Speed: 71.553547 samples/sec accuracy=82.989583 loss=0.670374 lr=0.000100 Epoch[095] Batch [3049]/[3760] Speed: 71.564935 samples/sec accuracy=82.974898 loss=0.670353 lr=0.000100 Epoch[095] Batch [3099]/[3760] Speed: 71.453830 samples/sec accuracy=82.961190 loss=0.670921 lr=0.000100 Epoch[095] Batch [3149]/[3760] Speed: 72.202075 samples/sec accuracy=82.953869 loss=0.671256 lr=0.000100 Epoch[095] Batch [3199]/[3760] Speed: 71.434367 samples/sec accuracy=82.952637 loss=0.670914 lr=0.000100 Epoch[095] Batch [3249]/[3760] Speed: 72.343870 samples/sec accuracy=82.945192 loss=0.670701 lr=0.000100 Epoch[095] Batch [3299]/[3760] Speed: 71.786615 samples/sec accuracy=82.934659 loss=0.670961 lr=0.000100 Epoch[095] Batch [3349]/[3760] Speed: 72.098025 samples/sec accuracy=82.925840 loss=0.671088 lr=0.000100 Epoch[095] Batch [3399]/[3760] Speed: 72.036430 samples/sec accuracy=82.926930 loss=0.671092 lr=0.000100 Epoch[095] Batch [3449]/[3760] Speed: 71.967845 samples/sec accuracy=82.924819 loss=0.671108 lr=0.000100 Epoch[095] Batch [3499]/[3760] Speed: 71.914353 samples/sec accuracy=82.923214 loss=0.671524 lr=0.000100 Epoch[095] Batch [3549]/[3760] Speed: 72.447663 samples/sec accuracy=82.922535 loss=0.671562 lr=0.000100 Epoch[095] Batch [3599]/[3760] Speed: 71.799702 samples/sec accuracy=82.904948 loss=0.672124 lr=0.000100 Epoch[095] Batch [3649]/[3760] Speed: 71.505486 samples/sec accuracy=82.921233 loss=0.672177 lr=0.000100 Epoch[095] Batch [3699]/[3760] Speed: 71.308853 samples/sec accuracy=82.919341 loss=0.672210 lr=0.000100 Epoch[095] Batch [3749]/[3760] Speed: 79.715630 samples/sec accuracy=82.910417 loss=0.672717 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.781250 acc-top5=88.156250 Batch [0099]/[0303]: acc-top1=68.625000 acc-top5=87.578125 Batch [0149]/[0303]: acc-top1=68.041667 acc-top5=86.781250 Batch [0199]/[0303]: acc-top1=67.781250 acc-top5=86.718750 Batch [0249]/[0303]: acc-top1=67.606250 acc-top5=86.712500 Batch [0299]/[0303]: acc-top1=67.640625 acc-top5=86.776042 [Epoch 095] training: accuracy=82.914312 loss=0.672514 [Epoch 095] speed: 71 samples/sec time cost: 3640.815484 [Epoch 095] validation: acc-top1=67.682550 acc-top5=86.808993 loss=1.654046 Epoch[096] Batch [0049]/[3759] Speed: 47.792376 samples/sec accuracy=83.781250 loss=0.656170 lr=0.000100 Epoch[096] Batch [0099]/[3759] Speed: 71.145702 samples/sec accuracy=83.359375 loss=0.654405 lr=0.000100 Epoch[096] Batch [0149]/[3759] Speed: 71.964947 samples/sec accuracy=83.541667 loss=0.652075 lr=0.000100 Epoch[096] Batch [0199]/[3759] Speed: 72.462983 samples/sec accuracy=83.460938 loss=0.650833 lr=0.000100 Epoch[096] Batch [0249]/[3759] Speed: 71.351350 samples/sec accuracy=83.506250 loss=0.652533 lr=0.000100 Epoch[096] Batch [0299]/[3759] Speed: 72.227054 samples/sec accuracy=83.260417 loss=0.660005 lr=0.000100 Epoch[096] Batch [0349]/[3759] Speed: 72.108218 samples/sec accuracy=83.236607 loss=0.664000 lr=0.000100 Epoch[096] Batch [0399]/[3759] Speed: 72.141656 samples/sec accuracy=83.156250 loss=0.666794 lr=0.000100 Epoch[096] Batch [0449]/[3759] Speed: 71.375727 samples/sec accuracy=83.250000 loss=0.662544 lr=0.000100 Epoch[096] Batch [0499]/[3759] Speed: 71.751931 samples/sec accuracy=83.315625 loss=0.660880 lr=0.000100 Epoch[096] Batch [0549]/[3759] Speed: 71.693763 samples/sec accuracy=83.309659 loss=0.661795 lr=0.000100 Epoch[096] Batch [0599]/[3759] Speed: 71.990742 samples/sec accuracy=83.312500 loss=0.661271 lr=0.000100 Epoch[096] Batch [0649]/[3759] Speed: 72.343459 samples/sec accuracy=83.250000 loss=0.662603 lr=0.000100 Epoch[096] Batch [0699]/[3759] Speed: 71.226292 samples/sec accuracy=83.200893 loss=0.664504 lr=0.000100 Epoch[096] Batch [0749]/[3759] Speed: 70.348413 samples/sec accuracy=83.100000 loss=0.666228 lr=0.000100 Epoch[096] Batch [0799]/[3759] Speed: 72.906742 samples/sec accuracy=83.083984 loss=0.667302 lr=0.000100 Epoch[096] Batch [0849]/[3759] Speed: 71.356395 samples/sec accuracy=83.128676 loss=0.665885 lr=0.000100 Epoch[096] 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accuracy=83.184028 loss=0.665007 lr=0.000100 Epoch[096] Batch [1399]/[3759] Speed: 71.784003 samples/sec accuracy=83.149554 loss=0.665642 lr=0.000100 Epoch[096] Batch [1449]/[3759] Speed: 71.894368 samples/sec accuracy=83.135776 loss=0.665946 lr=0.000100 Epoch[096] Batch [1499]/[3759] Speed: 71.417349 samples/sec accuracy=83.141667 loss=0.665955 lr=0.000100 Epoch[096] Batch [1549]/[3759] Speed: 71.908915 samples/sec accuracy=83.131048 loss=0.666705 lr=0.000100 Epoch[096] Batch [1599]/[3759] Speed: 71.897892 samples/sec accuracy=83.083008 loss=0.668429 lr=0.000100 Epoch[096] Batch [1649]/[3759] Speed: 71.985260 samples/sec accuracy=83.069129 loss=0.668977 lr=0.000100 Epoch[096] Batch [1699]/[3759] Speed: 71.736161 samples/sec accuracy=83.121324 loss=0.667483 lr=0.000100 Epoch[096] Batch [1749]/[3759] Speed: 71.270346 samples/sec accuracy=83.077679 loss=0.668835 lr=0.000100 Epoch[096] Batch [1799]/[3759] Speed: 72.160690 samples/sec accuracy=83.078993 loss=0.669278 lr=0.000100 Epoch[096] 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accuracy=83.007473 loss=0.670182 lr=0.000100 Epoch[096] Batch [2349]/[3759] Speed: 71.443731 samples/sec accuracy=83.015957 loss=0.669733 lr=0.000100 Epoch[096] Batch [2399]/[3759] Speed: 72.086183 samples/sec accuracy=83.036458 loss=0.669073 lr=0.000100 Epoch[096] Batch [2449]/[3759] Speed: 71.734667 samples/sec accuracy=83.058673 loss=0.668298 lr=0.000100 Epoch[096] Batch [2499]/[3759] Speed: 71.157477 samples/sec accuracy=83.066875 loss=0.667651 lr=0.000100 Epoch[096] Batch [2549]/[3759] Speed: 71.893491 samples/sec accuracy=83.064951 loss=0.668236 lr=0.000100 Epoch[096] Batch [2599]/[3759] Speed: 71.770666 samples/sec accuracy=83.055288 loss=0.668590 lr=0.000100 Epoch[096] Batch [2649]/[3759] Speed: 71.741645 samples/sec accuracy=83.044811 loss=0.669077 lr=0.000100 Epoch[096] Batch [2699]/[3759] Speed: 71.600913 samples/sec accuracy=83.055556 loss=0.668531 lr=0.000100 Epoch[096] Batch [2749]/[3759] Speed: 71.578920 samples/sec accuracy=83.060227 loss=0.668481 lr=0.000100 Epoch[096] 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accuracy=83.004327 loss=0.668503 lr=0.000100 Epoch[096] Batch [3299]/[3759] Speed: 71.894338 samples/sec accuracy=82.993371 loss=0.669048 lr=0.000100 Epoch[096] Batch [3349]/[3759] Speed: 71.903327 samples/sec accuracy=82.999534 loss=0.668613 lr=0.000100 Epoch[096] Batch [3399]/[3759] Speed: 71.252040 samples/sec accuracy=83.000919 loss=0.668613 lr=0.000100 Epoch[096] Batch [3449]/[3759] Speed: 71.563473 samples/sec accuracy=83.009511 loss=0.668429 lr=0.000100 Epoch[096] Batch [3499]/[3759] Speed: 71.724217 samples/sec accuracy=82.995536 loss=0.668691 lr=0.000100 Epoch[096] Batch [3549]/[3759] Speed: 72.200657 samples/sec accuracy=83.004842 loss=0.668087 lr=0.000100 Epoch[096] Batch [3599]/[3759] Speed: 71.535669 samples/sec accuracy=82.990885 loss=0.668932 lr=0.000100 Epoch[096] Batch [3649]/[3759] Speed: 71.262243 samples/sec accuracy=82.970034 loss=0.669199 lr=0.000100 Epoch[096] Batch [3699]/[3759] Speed: 71.750311 samples/sec accuracy=82.969595 loss=0.669158 lr=0.000100 Epoch[096] Batch [3749]/[3759] Speed: 80.348979 samples/sec accuracy=82.968333 loss=0.669245 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.000000 acc-top5=88.093750 Batch [0099]/[0303]: acc-top1=68.984375 acc-top5=87.546875 Batch [0149]/[0303]: acc-top1=68.229167 acc-top5=86.708333 Batch [0199]/[0303]: acc-top1=67.960938 acc-top5=86.664062 Batch [0249]/[0303]: acc-top1=67.650000 acc-top5=86.675000 Batch [0299]/[0303]: acc-top1=67.671875 acc-top5=86.739583 [Epoch 096] training: accuracy=82.967960 loss=0.669203 [Epoch 096] speed: 71 samples/sec time cost: 3635.772709 [Epoch 096] validation: acc-top1=67.713490 acc-top5=86.778053 loss=1.649048 Epoch[097] Batch [0049]/[3760] Speed: 49.338925 samples/sec accuracy=82.937500 loss=0.698652 lr=0.000100 Epoch[097] Batch [0099]/[3760] Speed: 70.320228 samples/sec accuracy=82.937500 loss=0.685659 lr=0.000100 Epoch[097] Batch [0149]/[3760] Speed: 71.810785 samples/sec accuracy=82.791667 loss=0.683492 lr=0.000100 Epoch[097] Batch [0199]/[3760] Speed: 71.566909 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72.133316 samples/sec accuracy=83.244565 loss=0.660972 lr=0.000100 Epoch[097] Batch [1199]/[3760] Speed: 71.612683 samples/sec accuracy=83.260417 loss=0.659907 lr=0.000100 Epoch[097] Batch [1249]/[3760] Speed: 72.294535 samples/sec accuracy=83.280000 loss=0.659971 lr=0.000100 Epoch[097] Batch [1299]/[3760] Speed: 70.335186 samples/sec accuracy=83.263221 loss=0.659223 lr=0.000100 Epoch[097] Batch [1349]/[3760] Speed: 72.500801 samples/sec accuracy=83.261574 loss=0.659862 lr=0.000100 Epoch[097] Batch [1399]/[3760] Speed: 71.667724 samples/sec accuracy=83.231027 loss=0.660778 lr=0.000100 Epoch[097] Batch [1449]/[3760] Speed: 71.898199 samples/sec accuracy=83.220905 loss=0.661641 lr=0.000100 Epoch[097] Batch [1499]/[3760] Speed: 72.188134 samples/sec accuracy=83.214583 loss=0.662417 lr=0.000100 Epoch[097] Batch [1549]/[3760] Speed: 71.875623 samples/sec accuracy=83.188508 loss=0.662765 lr=0.000100 Epoch[097] Batch [1599]/[3760] Speed: 72.229503 samples/sec accuracy=83.175781 loss=0.662348 lr=0.000100 Epoch[097] Batch [1649]/[3760] Speed: 71.643269 samples/sec accuracy=83.179924 loss=0.662215 lr=0.000100 Epoch[097] Batch [1699]/[3760] Speed: 70.791960 samples/sec accuracy=83.200368 loss=0.661757 lr=0.000100 Epoch[097] Batch [1749]/[3760] Speed: 72.216970 samples/sec accuracy=83.225893 loss=0.661291 lr=0.000100 Epoch[097] Batch [1799]/[3760] Speed: 71.353514 samples/sec accuracy=83.197917 loss=0.662436 lr=0.000100 Epoch[097] Batch [1849]/[3760] Speed: 71.614135 samples/sec accuracy=83.154561 loss=0.663299 lr=0.000100 Epoch[097] Batch [1899]/[3760] Speed: 71.669734 samples/sec accuracy=83.166941 loss=0.663227 lr=0.000100 Epoch[097] Batch [1949]/[3760] Speed: 71.484654 samples/sec accuracy=83.150641 loss=0.663288 lr=0.000100 Epoch[097] Batch [1999]/[3760] Speed: 71.228583 samples/sec accuracy=83.160156 loss=0.664050 lr=0.000100 Epoch[097] Batch [2049]/[3760] Speed: 71.583017 samples/sec accuracy=83.165396 loss=0.663854 lr=0.000100 Epoch[097] Batch [2099]/[3760] Speed: 72.119269 samples/sec accuracy=83.186012 loss=0.662912 lr=0.000100 Epoch[097] Batch [2149]/[3760] Speed: 71.873787 samples/sec accuracy=83.184593 loss=0.662777 lr=0.000100 Epoch[097] Batch [2199]/[3760] Speed: 71.129938 samples/sec accuracy=83.196023 loss=0.662905 lr=0.000100 Epoch[097] Batch [2249]/[3760] Speed: 72.489448 samples/sec accuracy=83.161806 loss=0.664296 lr=0.000100 Epoch[097] Batch [2299]/[3760] Speed: 71.099030 samples/sec accuracy=83.165761 loss=0.664509 lr=0.000100 Epoch[097] Batch [2349]/[3760] Speed: 71.147935 samples/sec accuracy=83.167553 loss=0.664288 lr=0.000100 Epoch[097] Batch [2399]/[3760] Speed: 71.907481 samples/sec accuracy=83.166667 loss=0.663728 lr=0.000100 Epoch[097] Batch [2449]/[3760] Speed: 71.638877 samples/sec accuracy=83.169005 loss=0.663450 lr=0.000100 Epoch[097] Batch [2499]/[3760] Speed: 71.109435 samples/sec accuracy=83.167500 loss=0.663614 lr=0.000100 Epoch[097] Batch [2549]/[3760] Speed: 72.000438 samples/sec accuracy=83.162990 loss=0.663496 lr=0.000100 Epoch[097] Batch [2599]/[3760] Speed: 70.939472 samples/sec accuracy=83.171875 loss=0.663456 lr=0.000100 Epoch[097] Batch [2649]/[3760] Speed: 71.974199 samples/sec accuracy=83.194575 loss=0.663349 lr=0.000100 Epoch[097] Batch [2699]/[3760] Speed: 71.423836 samples/sec accuracy=83.200231 loss=0.663050 lr=0.000100 Epoch[097] Batch [2749]/[3760] Speed: 71.337656 samples/sec accuracy=83.185795 loss=0.663382 lr=0.000100 Epoch[097] Batch [2799]/[3760] Speed: 72.428254 samples/sec accuracy=83.172433 loss=0.663548 lr=0.000100 Epoch[097] Batch [2849]/[3760] Speed: 72.025302 samples/sec accuracy=83.172697 loss=0.663415 lr=0.000100 Epoch[097] Batch [2899]/[3760] Speed: 71.699782 samples/sec accuracy=83.172953 loss=0.662984 lr=0.000100 Epoch[097] Batch [2949]/[3760] Speed: 72.112263 samples/sec accuracy=83.173199 loss=0.662736 lr=0.000100 Epoch[097] Batch [2999]/[3760] Speed: 70.768172 samples/sec accuracy=83.175521 loss=0.662589 lr=0.000100 Epoch[097] Batch [3049]/[3760] Speed: 71.401697 samples/sec accuracy=83.175205 loss=0.662245 lr=0.000100 Epoch[097] Batch [3099]/[3760] Speed: 71.457829 samples/sec accuracy=83.185988 loss=0.661909 lr=0.000100 Epoch[097] Batch [3149]/[3760] Speed: 71.742016 samples/sec accuracy=83.190476 loss=0.661906 lr=0.000100 Epoch[097] Batch [3199]/[3760] Speed: 71.900916 samples/sec accuracy=83.182617 loss=0.662068 lr=0.000100 Epoch[097] Batch [3249]/[3760] Speed: 71.429754 samples/sec accuracy=83.182212 loss=0.661861 lr=0.000100 Epoch[097] Batch [3299]/[3760] Speed: 71.919642 samples/sec accuracy=83.179451 loss=0.662322 lr=0.000100 Epoch[097] Batch [3349]/[3760] Speed: 71.610533 samples/sec accuracy=83.155784 loss=0.662760 lr=0.000100 Epoch[097] Batch [3399]/[3760] Speed: 71.483497 samples/sec accuracy=83.144761 loss=0.663052 lr=0.000100 Epoch[097] Batch [3449]/[3760] Speed: 71.486462 samples/sec accuracy=83.147192 loss=0.663596 lr=0.000100 Epoch[097] Batch [3499]/[3760] Speed: 72.209554 samples/sec accuracy=83.129911 loss=0.664135 lr=0.000100 Epoch[097] Batch [3549]/[3760] Speed: 71.307557 samples/sec accuracy=83.128521 loss=0.664302 lr=0.000100 Epoch[097] Batch [3599]/[3760] Speed: 71.204609 samples/sec accuracy=83.118924 loss=0.664750 lr=0.000100 Epoch[097] Batch [3649]/[3760] Speed: 71.494122 samples/sec accuracy=83.112158 loss=0.665177 lr=0.000100 Epoch[097] Batch [3699]/[3760] Speed: 71.788535 samples/sec accuracy=83.116132 loss=0.665055 lr=0.000100 Epoch[097] Batch [3749]/[3760] Speed: 80.240875 samples/sec accuracy=83.112500 loss=0.665297 lr=0.000100 Batch [0049]/[0303]: acc-top1=69.500000 acc-top5=87.906250 Batch [0099]/[0303]: acc-top1=69.218750 acc-top5=87.468750 Batch [0149]/[0303]: acc-top1=68.385417 acc-top5=86.729167 Batch [0199]/[0303]: acc-top1=68.070312 acc-top5=86.671875 Batch [0249]/[0303]: acc-top1=67.762500 acc-top5=86.743750 Batch [0299]/[0303]: acc-top1=67.739583 acc-top5=86.807292 [Epoch 097] training: accuracy=83.111702 loss=0.665312 [Epoch 097] speed: 71 samples/sec time cost: 3639.080076 [Epoch 097] validation: acc-top1=67.780528 acc-top5=86.850248 loss=1.648752 Epoch[098] Batch [0049]/[3759] Speed: 48.217658 samples/sec accuracy=82.656250 loss=0.665623 lr=0.000100 Epoch[098] Batch [0099]/[3759] Speed: 69.655561 samples/sec accuracy=82.953125 loss=0.663794 lr=0.000100 Epoch[098] Batch [0149]/[3759] Speed: 72.831756 samples/sec accuracy=82.968750 loss=0.663008 lr=0.000100 Epoch[098] Batch [0199]/[3759] Speed: 71.712574 samples/sec accuracy=82.859375 loss=0.668115 lr=0.000100 Epoch[098] Batch [0249]/[3759] Speed: 71.736301 samples/sec accuracy=83.050000 loss=0.660485 lr=0.000100 Epoch[098] Batch [0299]/[3759] Speed: 72.264801 samples/sec accuracy=82.864583 loss=0.667323 lr=0.000100 Epoch[098] Batch [0349]/[3759] Speed: 71.509296 samples/sec accuracy=82.928571 loss=0.667322 lr=0.000100 Epoch[098] Batch [0399]/[3759] Speed: 72.313148 samples/sec accuracy=82.921875 loss=0.667374 lr=0.000100 Epoch[098] Batch [0449]/[3759] Speed: 71.886752 samples/sec accuracy=82.916667 loss=0.668104 lr=0.000100 Epoch[098] Batch [0499]/[3759] Speed: 71.060938 samples/sec accuracy=83.006250 loss=0.664262 lr=0.000100 Epoch[098] Batch [0549]/[3759] Speed: 71.496693 samples/sec accuracy=82.991477 loss=0.665641 lr=0.000100 Epoch[098] Batch [0599]/[3759] Speed: 71.539599 samples/sec accuracy=83.010417 loss=0.665508 lr=0.000100 Epoch[098] Batch [0649]/[3759] Speed: 72.121232 samples/sec accuracy=82.995192 loss=0.665736 lr=0.000100 Epoch[098] Batch [0699]/[3759] Speed: 71.766379 samples/sec accuracy=82.950893 loss=0.667041 lr=0.000100 Epoch[098] Batch [0749]/[3759] Speed: 71.524337 samples/sec accuracy=82.981250 loss=0.667507 lr=0.000100 Epoch[098] Batch [0799]/[3759] Speed: 72.057698 samples/sec accuracy=82.958984 loss=0.668643 lr=0.000100 Epoch[098] Batch [0849]/[3759] Speed: 71.703549 samples/sec accuracy=82.981618 loss=0.669218 lr=0.000100 Epoch[098] Batch [0899]/[3759] Speed: 71.382164 samples/sec accuracy=83.020833 loss=0.668292 lr=0.000100 Epoch[098] 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accuracy=83.099330 loss=0.663857 lr=0.000100 Epoch[098] Batch [1449]/[3759] Speed: 71.434181 samples/sec accuracy=83.100216 loss=0.663702 lr=0.000100 Epoch[098] Batch [1499]/[3759] Speed: 71.350473 samples/sec accuracy=83.122917 loss=0.662138 lr=0.000100 Epoch[098] Batch [1549]/[3759] Speed: 71.659781 samples/sec accuracy=83.093750 loss=0.663396 lr=0.000100 Epoch[098] Batch [1599]/[3759] Speed: 72.061205 samples/sec accuracy=83.068359 loss=0.663901 lr=0.000100 Epoch[098] Batch [1649]/[3759] Speed: 70.893294 samples/sec accuracy=83.071970 loss=0.663735 lr=0.000100 Epoch[098] Batch [1699]/[3759] Speed: 71.939615 samples/sec accuracy=83.060662 loss=0.665051 lr=0.000100 Epoch[098] Batch [1749]/[3759] Speed: 71.692083 samples/sec accuracy=83.050000 loss=0.665080 lr=0.000100 Epoch[098] Batch [1799]/[3759] Speed: 71.645035 samples/sec accuracy=83.046007 loss=0.665633 lr=0.000100 Epoch[098] Batch [1849]/[3759] Speed: 71.329236 samples/sec accuracy=83.023649 loss=0.665875 lr=0.000100 Epoch[098] 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accuracy=83.035904 loss=0.666008 lr=0.000100 Epoch[098] Batch [2399]/[3759] Speed: 72.001848 samples/sec accuracy=83.057292 loss=0.665318 lr=0.000100 Epoch[098] Batch [2449]/[3759] Speed: 71.371001 samples/sec accuracy=83.040816 loss=0.666436 lr=0.000100 Epoch[098] Batch [2499]/[3759] Speed: 71.501642 samples/sec accuracy=83.018750 loss=0.667097 lr=0.000100 Epoch[098] Batch [2549]/[3759] Speed: 71.564027 samples/sec accuracy=83.033088 loss=0.667148 lr=0.000100 Epoch[098] Batch [2599]/[3759] Speed: 71.881842 samples/sec accuracy=83.016226 loss=0.667617 lr=0.000100 Epoch[098] Batch [2649]/[3759] Speed: 70.715406 samples/sec accuracy=83.027712 loss=0.667405 lr=0.000100 Epoch[098] Batch [2699]/[3759] Speed: 72.402251 samples/sec accuracy=83.015625 loss=0.667931 lr=0.000100 Epoch[098] Batch [2749]/[3759] Speed: 70.063852 samples/sec accuracy=83.000568 loss=0.668399 lr=0.000100 Epoch[098] Batch [2799]/[3759] Speed: 72.631699 samples/sec accuracy=83.000558 loss=0.667774 lr=0.000100 Epoch[098] 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accuracy=82.989583 loss=0.666790 lr=0.000100 Epoch[098] Batch [3349]/[3759] Speed: 71.849193 samples/sec accuracy=82.999067 loss=0.666834 lr=0.000100 Epoch[098] Batch [3399]/[3759] Speed: 70.146507 samples/sec accuracy=83.007353 loss=0.666537 lr=0.000100 Epoch[098] Batch [3449]/[3759] Speed: 72.326221 samples/sec accuracy=82.997283 loss=0.666770 lr=0.000100 Epoch[098] Batch [3499]/[3759] Speed: 71.346607 samples/sec accuracy=82.999107 loss=0.666815 lr=0.000100 Epoch[098] Batch [3549]/[3759] Speed: 70.899875 samples/sec accuracy=82.998680 loss=0.666994 lr=0.000100 Epoch[098] Batch [3599]/[3759] Speed: 72.015723 samples/sec accuracy=83.014757 loss=0.666697 lr=0.000100 Epoch[098] Batch [3649]/[3759] Speed: 71.202318 samples/sec accuracy=83.016267 loss=0.666371 lr=0.000100 Epoch[098] Batch [3699]/[3759] Speed: 72.070211 samples/sec accuracy=83.014780 loss=0.666728 lr=0.000100 Epoch[098] Batch [3749]/[3759] Speed: 80.038766 samples/sec accuracy=83.015417 loss=0.666620 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.781250 acc-top5=87.875000 Batch [0099]/[0303]: acc-top1=68.765625 acc-top5=87.421875 Batch [0149]/[0303]: acc-top1=67.843750 acc-top5=86.562500 Batch [0199]/[0303]: acc-top1=67.726562 acc-top5=86.578125 Batch [0249]/[0303]: acc-top1=67.487500 acc-top5=86.606250 Batch [0299]/[0303]: acc-top1=67.567708 acc-top5=86.651042 [Epoch 098] training: accuracy=83.015347 loss=0.666554 [Epoch 098] speed: 71 samples/sec time cost: 3639.869564 [Epoch 098] validation: acc-top1=67.620668 acc-top5=86.680074 loss=1.656463 Epoch[099] Batch [0049]/[3760] Speed: 48.700466 samples/sec accuracy=84.000000 loss=0.655244 lr=0.000100 Epoch[099] Batch [0099]/[3760] Speed: 70.528406 samples/sec accuracy=83.578125 loss=0.663806 lr=0.000100 Epoch[099] Batch [0149]/[3760] Speed: 71.828324 samples/sec accuracy=83.437500 loss=0.658648 lr=0.000100 Epoch[099] Batch [0199]/[3760] Speed: 71.615522 samples/sec accuracy=83.476562 loss=0.649803 lr=0.000100 Epoch[099] Batch [0249]/[3760] Speed: 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lr=0.000100 Epoch[099] Batch [0749]/[3760] Speed: 70.868973 samples/sec accuracy=83.362500 loss=0.654704 lr=0.000100 Epoch[099] Batch [0799]/[3760] Speed: 71.986499 samples/sec accuracy=83.363281 loss=0.654861 lr=0.000100 Epoch[099] Batch [0849]/[3760] Speed: 71.696914 samples/sec accuracy=83.303309 loss=0.656049 lr=0.000100 Epoch[099] Batch [0899]/[3760] Speed: 71.749568 samples/sec accuracy=83.302083 loss=0.655515 lr=0.000100 Epoch[099] Batch [0949]/[3760] Speed: 71.822101 samples/sec accuracy=83.320724 loss=0.655891 lr=0.000100 Epoch[099] Batch [0999]/[3760] Speed: 70.957439 samples/sec accuracy=83.332813 loss=0.655967 lr=0.000100 Epoch[099] Batch [1049]/[3760] Speed: 71.373926 samples/sec accuracy=83.346726 loss=0.656254 lr=0.000100 Epoch[099] Batch [1099]/[3760] Speed: 71.866363 samples/sec accuracy=83.350852 loss=0.656060 lr=0.000100 Epoch[099] Batch [1149]/[3760] Speed: 71.452481 samples/sec accuracy=83.349185 loss=0.655555 lr=0.000100 Epoch[099] Batch [1199]/[3760] Speed: 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lr=0.000100 Epoch[099] Batch [1699]/[3760] Speed: 71.194784 samples/sec accuracy=83.279412 loss=0.656349 lr=0.000100 Epoch[099] Batch [1749]/[3760] Speed: 71.212277 samples/sec accuracy=83.264286 loss=0.657264 lr=0.000100 Epoch[099] Batch [1799]/[3760] Speed: 71.936109 samples/sec accuracy=83.234375 loss=0.658528 lr=0.000100 Epoch[099] Batch [1849]/[3760] Speed: 71.622690 samples/sec accuracy=83.251689 loss=0.658147 lr=0.000100 Epoch[099] Batch [1899]/[3760] Speed: 71.395318 samples/sec accuracy=83.245066 loss=0.658905 lr=0.000100 Epoch[099] Batch [1949]/[3760] Speed: 71.788291 samples/sec accuracy=83.260417 loss=0.658183 lr=0.000100 Epoch[099] Batch [1999]/[3760] Speed: 71.511946 samples/sec accuracy=83.267969 loss=0.657837 lr=0.000100 Epoch[099] Batch [2049]/[3760] Speed: 71.623714 samples/sec accuracy=83.272866 loss=0.658043 lr=0.000100 Epoch[099] Batch [2099]/[3760] Speed: 72.003485 samples/sec accuracy=83.252232 loss=0.658397 lr=0.000100 Epoch[099] Batch [2149]/[3760] Speed: 71.641273 samples/sec accuracy=83.259448 loss=0.658316 lr=0.000100 Epoch[099] Batch [2199]/[3760] Speed: 71.914049 samples/sec accuracy=83.258523 loss=0.657722 lr=0.000100 Epoch[099] Batch [2249]/[3760] Speed: 71.582456 samples/sec accuracy=83.256944 loss=0.657486 lr=0.000100 Epoch[099] Batch [2299]/[3760] Speed: 72.263743 samples/sec accuracy=83.252038 loss=0.657933 lr=0.000100 Epoch[099] Batch [2349]/[3760] Speed: 71.474282 samples/sec accuracy=83.267287 loss=0.657390 lr=0.000100 Epoch[099] Batch [2399]/[3760] Speed: 71.476653 samples/sec accuracy=83.291016 loss=0.656899 lr=0.000100 Epoch[099] Batch [2449]/[3760] Speed: 70.909901 samples/sec accuracy=83.301658 loss=0.656584 lr=0.000100 Epoch[099] Batch [2499]/[3760] Speed: 71.715464 samples/sec accuracy=83.296875 loss=0.656408 lr=0.000100 Epoch[099] Batch [2549]/[3760] Speed: 72.172439 samples/sec accuracy=83.297794 loss=0.656293 lr=0.000100 Epoch[099] Batch [2599]/[3760] Speed: 72.074389 samples/sec accuracy=83.298077 loss=0.656532 lr=0.000100 Epoch[099] Batch [2649]/[3760] Speed: 71.119302 samples/sec accuracy=83.306014 loss=0.656859 lr=0.000100 Epoch[099] Batch [2699]/[3760] Speed: 72.117120 samples/sec accuracy=83.302662 loss=0.656920 lr=0.000100 Epoch[099] Batch [2749]/[3760] Speed: 71.557115 samples/sec accuracy=83.278977 loss=0.657829 lr=0.000100 Epoch[099] Batch [2799]/[3760] Speed: 71.422093 samples/sec accuracy=83.254464 loss=0.658224 lr=0.000100 Epoch[099] Batch [2849]/[3760] Speed: 72.545124 samples/sec accuracy=83.243421 loss=0.658713 lr=0.000100 Epoch[099] Batch [2899]/[3760] Speed: 70.940421 samples/sec accuracy=83.264547 loss=0.657792 lr=0.000100 Epoch[099] Batch [2949]/[3760] Speed: 72.208573 samples/sec accuracy=83.262712 loss=0.657680 lr=0.000100 Epoch[099] Batch [2999]/[3760] Speed: 71.858331 samples/sec accuracy=83.257292 loss=0.657415 lr=0.000100 Epoch[099] Batch [3049]/[3760] Speed: 71.771583 samples/sec accuracy=83.248463 loss=0.657599 lr=0.000100 Epoch[099] Batch [3099]/[3760] Speed: 71.271071 samples/sec accuracy=83.256552 loss=0.657591 lr=0.000100 Epoch[099] Batch [3149]/[3760] Speed: 72.244705 samples/sec accuracy=83.255952 loss=0.657652 lr=0.000100 Epoch[099] Batch [3199]/[3760] Speed: 72.516050 samples/sec accuracy=83.262207 loss=0.657868 lr=0.000100 Epoch[099] Batch [3249]/[3760] Speed: 72.531084 samples/sec accuracy=83.264423 loss=0.657634 lr=0.000100 Epoch[099] Batch [3299]/[3760] Speed: 71.118003 samples/sec accuracy=83.266098 loss=0.657812 lr=0.000100 Epoch[099] Batch [3349]/[3760] Speed: 72.075952 samples/sec accuracy=83.277985 loss=0.657629 lr=0.000100 Epoch[099] Batch [3399]/[3760] Speed: 71.741663 samples/sec accuracy=83.275276 loss=0.657967 lr=0.000100 Epoch[099] Batch [3449]/[3760] Speed: 71.290974 samples/sec accuracy=83.251359 loss=0.658809 lr=0.000100 Epoch[099] Batch [3499]/[3760] Speed: 72.262830 samples/sec accuracy=83.253125 loss=0.658432 lr=0.000100 Epoch[099] Batch [3549]/[3760] Speed: 71.393229 samples/sec accuracy=83.249120 loss=0.658831 lr=0.000100 Epoch[099] Batch [3599]/[3760] Speed: 71.222489 samples/sec accuracy=83.224392 loss=0.659960 lr=0.000100 Epoch[099] Batch [3649]/[3760] Speed: 71.151379 samples/sec accuracy=83.221747 loss=0.660003 lr=0.000100 Epoch[099] Batch [3699]/[3760] Speed: 72.046526 samples/sec accuracy=83.217061 loss=0.660052 lr=0.000100 Epoch[099] Batch [3749]/[3760] Speed: 79.546284 samples/sec accuracy=83.223750 loss=0.659880 lr=0.000100 Batch [0049]/[0303]: acc-top1=68.625000 acc-top5=88.250000 Batch [0099]/[0303]: acc-top1=68.796875 acc-top5=87.468750 Batch [0149]/[0303]: acc-top1=68.260417 acc-top5=86.614583 Batch [0199]/[0303]: acc-top1=68.007812 acc-top5=86.562500 Batch [0249]/[0303]: acc-top1=67.737500 acc-top5=86.612500 Batch [0299]/[0303]: acc-top1=67.750000 acc-top5=86.703125 [Epoch 099] training: accuracy=83.226812 loss=0.659775 [Epoch 099] speed: 71 samples/sec time cost: 3638.497486 [Epoch 099] validation: acc-top1=67.806312 acc-top5=86.731642 loss=1.657089