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_res50_seg1_kinetics400_b8_g8_inflate311_f32s2_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_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/i3d/i3d_res50_seg1_kinetics400_b8_g8_inflate311_f32s2_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) ) (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) ) (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) ) (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) ) ) (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) ) (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) ) (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) ) (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) ) (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) ) (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) ) ) (3): HybridSequential( (0): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (2): Activation(relu) (3): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (5): Activation(relu) (6): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) (conv1): Conv3D(1024 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (conv3): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu): Activation(relu) (downsample): HybridSequential( (0): Conv3D(1024 -> 2048, kernel_size=(1, 1, 1), stride=(1, 2, 2), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) ) (1): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(2048 -> 512, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (2): Activation(relu) (3): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (5): Activation(relu) (6): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) (conv1): Conv3D(2048 -> 512, kernel_size=(3, 1, 1), stride=(1, 1, 1), padding=(1, 0, 0), bias=False) (conv2): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (conv3): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu): Activation(relu) ) (2): Bottleneck( (bottleneck): HybridSequential( (0): Conv3D(2048 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (2): Activation(relu) (3): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (5): Activation(relu) (6): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (7): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) ) (conv1): Conv3D(2048 -> 512, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (conv2): Conv3D(512 -> 512, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1), bias=False) (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (bn2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) (conv3): Conv3D(512 -> 2048, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False) (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) (relu): Activation(relu) ) ) ) (st_avg): GlobalAvgPool3D(size=(1, 1, 1), stride=(1, 1, 1), padding=(0, 0, 0), ceil_mode=True, global_pool=True, pool_type=avg, layout=NCDHW) (head): HybridSequential( (0): Dropout(p = 0.5, axes=()) (1): Dense(2048 -> 400, linear) ) (fc): Dense(2048 -> 400, linear) ) Load 240618 training samples and 19404 validation samples. 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accuracy=21.348881 loss=3.806251 lr=0.010000 Epoch[000] Batch [3399]/[3759] Speed: 76.584939 samples/sec accuracy=21.465993 loss=3.797142 lr=0.010000 Epoch[000] Batch [3449]/[3759] Speed: 67.175840 samples/sec accuracy=21.600996 loss=3.787765 lr=0.010000 Epoch[000] Batch [3499]/[3759] Speed: 77.544354 samples/sec accuracy=21.727679 loss=3.778579 lr=0.010000 Epoch[000] Batch [3549]/[3759] Speed: 68.175477 samples/sec accuracy=21.863996 loss=3.769415 lr=0.010000 Epoch[000] Batch [3599]/[3759] Speed: 75.448387 samples/sec accuracy=21.982639 loss=3.760035 lr=0.010000 Epoch[000] Batch [3649]/[3759] Speed: 70.788278 samples/sec accuracy=22.095890 loss=3.751868 lr=0.010000 Epoch[000] Batch [3699]/[3759] Speed: 70.704447 samples/sec accuracy=22.214527 loss=3.743519 lr=0.010000 Epoch[000] Batch [3749]/[3759] Speed: 84.262083 samples/sec accuracy=22.333750 loss=3.735159 lr=0.010000 Batch [0049]/[0303]: acc-top1=34.781250 acc-top5=60.937500 Batch [0099]/[0303]: acc-top1=34.312500 acc-top5=61.734375 Batch [0149]/[0303]: acc-top1=34.187500 acc-top5=61.739583 Batch [0199]/[0303]: acc-top1=34.539062 acc-top5=61.843750 Batch [0249]/[0303]: acc-top1=34.506250 acc-top5=61.731250 Batch [0299]/[0303]: acc-top1=34.322917 acc-top5=61.432292 [Epoch 000] training: accuracy=22.359254 loss=3.733582 [Epoch 000] speed: 71 samples/sec time cost: 3658.780173 [Epoch 000] validation: acc-top1=34.282178 acc-top5=61.422236 loss=2.986673 Epoch[001] Batch [0049]/[3760] Speed: 51.060767 samples/sec accuracy=34.375000 loss=2.974193 lr=0.010000 Epoch[001] Batch [0099]/[3760] Speed: 68.332607 samples/sec accuracy=32.671875 loss=3.042529 lr=0.010000 Epoch[001] Batch [0149]/[3760] Speed: 78.249499 samples/sec accuracy=33.447917 loss=3.001212 lr=0.010000 Epoch[001] Batch [0199]/[3760] Speed: 70.388313 samples/sec accuracy=33.132812 loss=3.019644 lr=0.010000 Epoch[001] Batch [0249]/[3760] Speed: 72.642783 samples/sec accuracy=32.956250 loss=3.026654 lr=0.010000 Epoch[001] Batch [0299]/[3760] 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accuracy=36.045139 loss=2.851653 lr=0.010000 Epoch[001] Batch [3649]/[3760] Speed: 75.360772 samples/sec accuracy=36.081764 loss=2.849069 lr=0.010000 Epoch[001] Batch [3699]/[3760] Speed: 71.985571 samples/sec accuracy=36.121199 loss=2.847255 lr=0.010000 Epoch[001] Batch [3749]/[3760] Speed: 78.037975 samples/sec accuracy=36.151667 loss=2.844456 lr=0.010000 Batch [0049]/[0303]: acc-top1=41.531250 acc-top5=69.156250 Batch [0099]/[0303]: acc-top1=42.375000 acc-top5=69.000000 Batch [0149]/[0303]: acc-top1=42.270833 acc-top5=68.666667 Batch [0199]/[0303]: acc-top1=42.390625 acc-top5=69.078125 Batch [0249]/[0303]: acc-top1=42.406250 acc-top5=69.156250 Batch [0299]/[0303]: acc-top1=42.104167 acc-top5=68.979167 [Epoch 001] training: accuracy=36.156499 loss=2.844042 [Epoch 001] speed: 72 samples/sec time cost: 3614.069513 [Epoch 001] validation: acc-top1=42.063738 acc-top5=68.982054 loss=2.648927 Epoch[002] Batch [0049]/[3759] Speed: 51.969683 samples/sec accuracy=39.593750 loss=2.666573 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69.451135 samples/sec accuracy=41.323070 loss=2.564064 lr=0.010000 Epoch[002] Batch [3449]/[3759] Speed: 75.012637 samples/sec accuracy=41.317482 loss=2.563584 lr=0.010000 Epoch[002] Batch [3499]/[3759] Speed: 72.734017 samples/sec accuracy=41.323214 loss=2.562984 lr=0.010000 Epoch[002] Batch [3549]/[3759] Speed: 73.335649 samples/sec accuracy=41.337148 loss=2.562397 lr=0.010000 Epoch[002] Batch [3599]/[3759] Speed: 74.722209 samples/sec accuracy=41.336806 loss=2.561951 lr=0.010000 Epoch[002] Batch [3649]/[3759] Speed: 68.230326 samples/sec accuracy=41.354024 loss=2.560950 lr=0.010000 Epoch[002] Batch [3699]/[3759] Speed: 75.366806 samples/sec accuracy=41.372044 loss=2.560256 lr=0.010000 Epoch[002] Batch [3749]/[3759] Speed: 84.100358 samples/sec accuracy=41.396667 loss=2.559248 lr=0.010000 Batch [0049]/[0303]: acc-top1=45.500000 acc-top5=71.968750 Batch [0099]/[0303]: acc-top1=45.937500 acc-top5=72.171875 Batch [0149]/[0303]: acc-top1=45.333333 acc-top5=72.010417 Batch [0199]/[0303]: acc-top1=45.421875 acc-top5=72.164062 Batch [0249]/[0303]: acc-top1=45.425000 acc-top5=72.150000 Batch [0299]/[0303]: acc-top1=45.343750 acc-top5=71.906250 [Epoch 002] training: accuracy=41.404379 loss=2.558959 [Epoch 002] speed: 72 samples/sec time cost: 3600.302289 [Epoch 002] validation: acc-top1=45.291873 acc-top5=71.936881 loss=2.461291 Epoch[003] Batch [0049]/[3760] Speed: 51.982199 samples/sec accuracy=43.531250 loss=2.424398 lr=0.010000 Epoch[003] Batch [0099]/[3760] Speed: 69.252191 samples/sec accuracy=44.156250 loss=2.410044 lr=0.010000 Epoch[003] Batch [0149]/[3760] Speed: 76.875364 samples/sec accuracy=44.031250 loss=2.415421 lr=0.010000 Epoch[003] Batch [0199]/[3760] Speed: 70.861866 samples/sec accuracy=44.375000 loss=2.394217 lr=0.010000 Epoch[003] Batch [0249]/[3760] Speed: 74.917967 samples/sec accuracy=43.937500 loss=2.413822 lr=0.010000 Epoch[003] Batch [0299]/[3760] Speed: 70.287783 samples/sec accuracy=44.052083 loss=2.410802 lr=0.010000 Epoch[003] Batch 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accuracy=44.573630 loss=2.389771 lr=0.010000 Epoch[003] Batch [3699]/[3760] Speed: 72.919025 samples/sec accuracy=44.587838 loss=2.388987 lr=0.010000 Epoch[003] Batch [3749]/[3760] Speed: 79.269152 samples/sec accuracy=44.607500 loss=2.388158 lr=0.010000 Batch [0049]/[0303]: acc-top1=47.906250 acc-top5=72.781250 Batch [0099]/[0303]: acc-top1=48.203125 acc-top5=73.421875 Batch [0149]/[0303]: acc-top1=47.677083 acc-top5=73.458333 Batch [0199]/[0303]: acc-top1=47.867188 acc-top5=73.562500 Batch [0249]/[0303]: acc-top1=47.987500 acc-top5=73.643750 Batch [0299]/[0303]: acc-top1=47.859375 acc-top5=73.442708 [Epoch 003] training: accuracy=44.613531 loss=2.387754 [Epoch 003] speed: 72 samples/sec time cost: 3597.799758 [Epoch 003] validation: acc-top1=47.870256 acc-top5=73.483911 loss=2.360510 Epoch[004] Batch [0049]/[3760] Speed: 52.436494 samples/sec accuracy=48.750000 loss=2.232428 lr=0.010000 Epoch[004] Batch [0099]/[3760] Speed: 67.056361 samples/sec accuracy=47.531250 loss=2.253325 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[0299]/[0303]: acc-top1=50.223958 acc-top5=75.723958 [Epoch 004] training: accuracy=47.078624 loss=2.269089 [Epoch 004] speed: 72 samples/sec time cost: 3604.106355 [Epoch 004] validation: acc-top1=50.185644 acc-top5=75.716790 loss=2.211379 Epoch[005] Batch [0049]/[3759] Speed: 52.518891 samples/sec accuracy=49.156250 loss=2.157857 lr=0.010000 Epoch[005] Batch [0099]/[3759] Speed: 69.915493 samples/sec accuracy=49.000000 loss=2.160056 lr=0.010000 Epoch[005] Batch [0149]/[3759] Speed: 73.629627 samples/sec accuracy=49.052083 loss=2.164077 lr=0.010000 Epoch[005] Batch [0199]/[3759] Speed: 74.236720 samples/sec accuracy=49.039062 loss=2.170457 lr=0.010000 Epoch[005] Batch [0249]/[3759] Speed: 71.979688 samples/sec accuracy=49.087500 loss=2.166974 lr=0.010000 Epoch[005] Batch [0299]/[3759] Speed: 74.903939 samples/sec accuracy=48.947917 loss=2.177925 lr=0.010000 Epoch[005] Batch [0349]/[3759] Speed: 70.973238 samples/sec accuracy=48.785714 loss=2.179208 lr=0.010000 Epoch[005] Batch 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accuracy=48.490451 loss=2.188106 lr=0.010000 Epoch[005] Batch [1849]/[3759] Speed: 75.298947 samples/sec accuracy=48.488176 loss=2.188608 lr=0.010000 Epoch[005] Batch [1899]/[3759] Speed: 73.201822 samples/sec accuracy=48.490954 loss=2.188399 lr=0.010000 Epoch[005] Batch [1949]/[3759] Speed: 73.402207 samples/sec accuracy=48.491987 loss=2.187663 lr=0.010000 Epoch[005] Batch [1999]/[3759] Speed: 71.107210 samples/sec accuracy=48.467969 loss=2.188503 lr=0.010000 Epoch[005] Batch [2049]/[3759] Speed: 74.892213 samples/sec accuracy=48.465701 loss=2.188684 lr=0.010000 Epoch[005] Batch [2099]/[3759] Speed: 72.007221 samples/sec accuracy=48.491071 loss=2.188693 lr=0.010000 Epoch[005] Batch [2149]/[3759] Speed: 74.265630 samples/sec accuracy=48.506541 loss=2.187424 lr=0.010000 Epoch[005] Batch [2199]/[3759] Speed: 70.976480 samples/sec accuracy=48.507812 loss=2.187460 lr=0.010000 Epoch[005] Batch [2249]/[3759] Speed: 75.204769 samples/sec accuracy=48.526389 loss=2.186494 lr=0.010000 Epoch[005] 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accuracy=48.575000 loss=2.183718 lr=0.010000 Epoch[005] Batch [2799]/[3759] Speed: 71.570032 samples/sec accuracy=48.575893 loss=2.183680 lr=0.010000 Epoch[005] Batch [2849]/[3759] Speed: 74.968164 samples/sec accuracy=48.576206 loss=2.183366 lr=0.010000 Epoch[005] Batch [2899]/[3759] Speed: 74.615710 samples/sec accuracy=48.573815 loss=2.183286 lr=0.010000 Epoch[005] Batch [2949]/[3759] Speed: 70.104608 samples/sec accuracy=48.578390 loss=2.183261 lr=0.010000 Epoch[005] Batch [2999]/[3759] Speed: 75.355107 samples/sec accuracy=48.603125 loss=2.181922 lr=0.010000 Epoch[005] Batch [3049]/[3759] Speed: 71.822405 samples/sec accuracy=48.615266 loss=2.181855 lr=0.010000 Epoch[005] Batch [3099]/[3759] Speed: 76.259669 samples/sec accuracy=48.602823 loss=2.182344 lr=0.010000 Epoch[005] Batch [3149]/[3759] Speed: 68.684081 samples/sec accuracy=48.586310 loss=2.183139 lr=0.010000 Epoch[005] Batch [3199]/[3759] Speed: 75.445540 samples/sec accuracy=48.614258 loss=2.182679 lr=0.010000 Epoch[005] 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accuracy=48.737331 loss=2.179223 lr=0.010000 Epoch[005] Batch [3749]/[3759] Speed: 82.635855 samples/sec accuracy=48.738333 loss=2.179683 lr=0.010000 Batch [0049]/[0303]: acc-top1=51.000000 acc-top5=76.187500 Batch [0099]/[0303]: acc-top1=51.000000 acc-top5=76.343750 Batch [0149]/[0303]: acc-top1=50.864583 acc-top5=76.072917 Batch [0199]/[0303]: acc-top1=50.968750 acc-top5=76.265625 Batch [0249]/[0303]: acc-top1=50.887500 acc-top5=76.343750 Batch [0299]/[0303]: acc-top1=50.807292 acc-top5=76.187500 [Epoch 005] training: accuracy=48.733041 loss=2.180114 [Epoch 005] speed: 72 samples/sec time cost: 3586.733464 [Epoch 005] validation: acc-top1=50.809612 acc-top5=76.227310 loss=2.177549 Epoch[006] Batch [0049]/[3760] Speed: 51.999717 samples/sec accuracy=50.187500 loss=2.105858 lr=0.010000 Epoch[006] Batch [0099]/[3760] Speed: 71.010049 samples/sec accuracy=50.750000 loss=2.081169 lr=0.010000 Epoch[006] Batch [0149]/[3760] Speed: 76.117632 samples/sec accuracy=50.979167 loss=2.077861 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lr=0.010000 Epoch[006] Batch [2099]/[3760] Speed: 70.675987 samples/sec accuracy=50.466518 loss=2.105739 lr=0.010000 Epoch[006] Batch [2149]/[3760] Speed: 75.643423 samples/sec accuracy=50.467297 loss=2.106723 lr=0.010000 Epoch[006] Batch [2199]/[3760] Speed: 71.925128 samples/sec accuracy=50.490767 loss=2.106700 lr=0.010000 Epoch[006] Batch [2249]/[3760] Speed: 72.752891 samples/sec accuracy=50.462500 loss=2.107576 lr=0.010000 Epoch[006] Batch [2299]/[3760] Speed: 74.928042 samples/sec accuracy=50.463995 loss=2.107562 lr=0.010000 Epoch[006] Batch [2349]/[3760] Speed: 71.244094 samples/sec accuracy=50.444814 loss=2.108855 lr=0.010000 Epoch[006] Batch [2399]/[3760] Speed: 75.471338 samples/sec accuracy=50.449219 loss=2.109148 lr=0.010000 Epoch[006] Batch [2449]/[3760] Speed: 68.954985 samples/sec accuracy=50.457270 loss=2.108066 lr=0.010000 Epoch[006] Batch [2499]/[3760] Speed: 75.404992 samples/sec accuracy=50.463750 loss=2.106587 lr=0.010000 Epoch[006] Batch [2549]/[3760] Speed: 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lr=0.010000 Epoch[006] Batch [3049]/[3760] Speed: 77.688310 samples/sec accuracy=50.416496 loss=2.107772 lr=0.010000 Epoch[006] Batch [3099]/[3760] Speed: 68.855006 samples/sec accuracy=50.399194 loss=2.108322 lr=0.010000 Epoch[006] Batch [3149]/[3760] Speed: 76.286240 samples/sec accuracy=50.375496 loss=2.109354 lr=0.010000 Epoch[006] Batch [3199]/[3760] Speed: 74.611120 samples/sec accuracy=50.371094 loss=2.109401 lr=0.010000 Epoch[006] Batch [3249]/[3760] Speed: 70.777526 samples/sec accuracy=50.353365 loss=2.110101 lr=0.010000 Epoch[006] Batch [3299]/[3760] Speed: 74.726370 samples/sec accuracy=50.379735 loss=2.109109 lr=0.010000 Epoch[006] Batch [3349]/[3760] Speed: 69.766384 samples/sec accuracy=50.393190 loss=2.109374 lr=0.010000 Epoch[006] Batch [3399]/[3760] Speed: 77.062828 samples/sec accuracy=50.385110 loss=2.109246 lr=0.010000 Epoch[006] Batch [3449]/[3760] Speed: 75.793722 samples/sec accuracy=50.411685 loss=2.108105 lr=0.010000 Epoch[006] Batch [3499]/[3760] Speed: 71.485561 samples/sec accuracy=50.405804 loss=2.108154 lr=0.010000 Epoch[006] Batch [3549]/[3760] Speed: 73.797565 samples/sec accuracy=50.410211 loss=2.107663 lr=0.010000 Epoch[006] Batch [3599]/[3760] Speed: 69.542400 samples/sec accuracy=50.414497 loss=2.107513 lr=0.010000 Epoch[006] Batch [3649]/[3760] Speed: 78.575797 samples/sec accuracy=50.422945 loss=2.107867 lr=0.010000 Epoch[006] Batch [3699]/[3760] Speed: 71.789343 samples/sec accuracy=50.436233 loss=2.107214 lr=0.010000 Epoch[006] Batch [3749]/[3760] Speed: 83.572269 samples/sec accuracy=50.430000 loss=2.106942 lr=0.010000 Batch [0049]/[0303]: acc-top1=52.093750 acc-top5=77.062500 Batch [0099]/[0303]: acc-top1=52.187500 acc-top5=77.171875 Batch [0149]/[0303]: acc-top1=51.843750 acc-top5=77.218750 Batch [0199]/[0303]: acc-top1=52.140625 acc-top5=77.414062 Batch [0249]/[0303]: acc-top1=52.137500 acc-top5=77.393750 Batch [0299]/[0303]: acc-top1=52.031250 acc-top5=77.348958 [Epoch 006] training: accuracy=50.428856 loss=2.106747 [Epoch 006] speed: 72 samples/sec time cost: 3586.370916 [Epoch 006] validation: acc-top1=51.969884 acc-top5=77.361799 loss=2.149965 Epoch[007] Batch [0049]/[3760] Speed: 52.047182 samples/sec accuracy=50.531250 loss=2.057396 lr=0.010000 Epoch[007] Batch [0099]/[3760] Speed: 71.050931 samples/sec accuracy=51.437500 loss=2.050423 lr=0.010000 Epoch[007] Batch [0149]/[3760] Speed: 76.480676 samples/sec accuracy=52.250000 loss=2.022396 lr=0.010000 Epoch[007] Batch [0199]/[3760] Speed: 72.291999 samples/sec accuracy=51.875000 loss=2.041147 lr=0.010000 Epoch[007] Batch [0249]/[3760] Speed: 71.607388 samples/sec accuracy=51.887500 loss=2.036753 lr=0.010000 Epoch[007] Batch [0299]/[3760] Speed: 76.126837 samples/sec accuracy=51.744792 loss=2.037488 lr=0.010000 Epoch[007] Batch [0349]/[3760] Speed: 70.006607 samples/sec accuracy=51.508929 loss=2.041752 lr=0.010000 Epoch[007] Batch [0399]/[3760] Speed: 76.862553 samples/sec accuracy=51.363281 loss=2.042436 lr=0.010000 Epoch[007] Batch 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accuracy=51.460000 loss=2.054953 lr=0.010000 Batch [0049]/[0303]: acc-top1=52.406250 acc-top5=77.062500 Batch [0099]/[0303]: acc-top1=52.625000 acc-top5=77.328125 Batch [0149]/[0303]: acc-top1=52.364583 acc-top5=77.500000 Batch [0199]/[0303]: acc-top1=52.414062 acc-top5=77.507812 Batch [0249]/[0303]: acc-top1=52.556250 acc-top5=77.506250 Batch [0299]/[0303]: acc-top1=52.619792 acc-top5=77.385417 [Epoch 007] training: accuracy=51.456533 loss=2.055027 [Epoch 007] speed: 73 samples/sec time cost: 3557.477523 [Epoch 007] validation: acc-top1=52.614480 acc-top5=77.439150 loss=2.113284 Epoch[008] Batch [0049]/[3759] Speed: 52.556379 samples/sec accuracy=54.093750 loss=1.916782 lr=0.010000 Epoch[008] Batch [0099]/[3759] Speed: 70.272024 samples/sec accuracy=53.890625 loss=1.949815 lr=0.010000 Epoch[008] Batch [0149]/[3759] Speed: 75.235300 samples/sec accuracy=53.770833 loss=1.964329 lr=0.010000 Epoch[008] Batch [0199]/[3759] Speed: 72.518904 samples/sec accuracy=53.640625 loss=1.967056 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lr=0.010000 Epoch[008] Batch [3099]/[3759] Speed: 77.432058 samples/sec accuracy=52.570565 loss=2.000449 lr=0.010000 Epoch[008] Batch [3149]/[3759] Speed: 75.083800 samples/sec accuracy=52.553571 loss=2.000883 lr=0.010000 Epoch[008] Batch [3199]/[3759] Speed: 71.223860 samples/sec accuracy=52.533203 loss=2.002076 lr=0.010000 Epoch[008] Batch [3249]/[3759] Speed: 77.875484 samples/sec accuracy=52.538462 loss=2.001388 lr=0.010000 Epoch[008] Batch [3299]/[3759] Speed: 70.439975 samples/sec accuracy=52.514678 loss=2.002900 lr=0.010000 Epoch[008] Batch [3349]/[3759] Speed: 75.576650 samples/sec accuracy=52.522854 loss=2.002815 lr=0.010000 Epoch[008] Batch [3399]/[3759] Speed: 72.650218 samples/sec accuracy=52.526654 loss=2.003113 lr=0.010000 Epoch[008] Batch [3449]/[3759] Speed: 75.466410 samples/sec accuracy=52.519475 loss=2.002691 lr=0.010000 Epoch[008] Batch [3499]/[3759] Speed: 76.781091 samples/sec accuracy=52.506250 loss=2.003346 lr=0.010000 Epoch[008] Batch [3549]/[3759] Speed: 68.586265 samples/sec accuracy=52.514085 loss=2.002758 lr=0.010000 Epoch[008] Batch [3599]/[3759] Speed: 76.619384 samples/sec accuracy=52.512153 loss=2.002933 lr=0.010000 Epoch[008] Batch [3649]/[3759] Speed: 75.602762 samples/sec accuracy=52.540668 loss=2.002152 lr=0.010000 Epoch[008] Batch [3699]/[3759] Speed: 75.323165 samples/sec accuracy=52.517736 loss=2.002603 lr=0.010000 Epoch[008] Batch [3749]/[3759] Speed: 83.704472 samples/sec accuracy=52.505833 loss=2.002829 lr=0.010000 Batch [0049]/[0303]: acc-top1=53.093750 acc-top5=77.500000 Batch [0099]/[0303]: acc-top1=53.671875 acc-top5=77.953125 Batch [0149]/[0303]: acc-top1=53.343750 acc-top5=77.656250 Batch [0199]/[0303]: acc-top1=53.617188 acc-top5=77.851562 Batch [0249]/[0303]: acc-top1=53.618750 acc-top5=77.887500 Batch [0299]/[0303]: acc-top1=53.567708 acc-top5=77.755208 [Epoch 008] training: accuracy=52.508563 loss=2.002608 [Epoch 008] speed: 73 samples/sec time cost: 3542.078644 [Epoch 008] validation: acc-top1=53.553012 acc-top5=77.764026 loss=2.060677 Epoch[009] Batch [0049]/[3760] Speed: 53.191773 samples/sec accuracy=53.843750 loss=1.978947 lr=0.010000 Epoch[009] Batch [0099]/[3760] Speed: 68.865553 samples/sec accuracy=54.109375 loss=1.955352 lr=0.010000 Epoch[009] Batch [0149]/[3760] Speed: 76.007719 samples/sec accuracy=53.958333 loss=1.949621 lr=0.010000 Epoch[009] Batch [0199]/[3760] Speed: 76.503255 samples/sec accuracy=54.132813 loss=1.937954 lr=0.010000 Epoch[009] Batch [0249]/[3760] Speed: 74.023774 samples/sec accuracy=54.156250 loss=1.932332 lr=0.010000 Epoch[009] Batch [0299]/[3760] Speed: 75.930759 samples/sec accuracy=54.208333 loss=1.924082 lr=0.010000 Epoch[009] Batch [0349]/[3760] Speed: 70.585506 samples/sec accuracy=54.191964 loss=1.928258 lr=0.010000 Epoch[009] Batch [0399]/[3760] Speed: 76.979377 samples/sec accuracy=54.148438 loss=1.928882 lr=0.010000 Epoch[009] Batch [0449]/[3760] Speed: 71.580807 samples/sec accuracy=54.267361 loss=1.930487 lr=0.010000 Epoch[009] Batch 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[0099]/[0303]: acc-top1=53.593750 acc-top5=78.328125 Batch [0149]/[0303]: acc-top1=53.395833 acc-top5=78.458333 Batch [0199]/[0303]: acc-top1=53.570312 acc-top5=78.562500 Batch [0249]/[0303]: acc-top1=53.637500 acc-top5=78.325000 Batch [0299]/[0303]: acc-top1=53.609375 acc-top5=78.218750 [Epoch 009] training: accuracy=53.400100 loss=1.963302 [Epoch 009] speed: 73 samples/sec time cost: 3532.050825 [Epoch 009] validation: acc-top1=53.583952 acc-top5=78.233292 loss=2.099376 Epoch[010] Batch [0049]/[3760] Speed: 54.281148 samples/sec accuracy=54.375000 loss=1.896150 lr=0.010000 Epoch[010] Batch [0099]/[3760] Speed: 68.695814 samples/sec accuracy=53.718750 loss=1.901797 lr=0.010000 Epoch[010] Batch [0149]/[3760] Speed: 77.995185 samples/sec accuracy=54.770833 loss=1.877906 lr=0.010000 Epoch[010] Batch [0199]/[3760] Speed: 75.799020 samples/sec accuracy=54.429688 loss=1.896305 lr=0.010000 Epoch[010] Batch [0249]/[3760] Speed: 73.147616 samples/sec accuracy=54.225000 loss=1.906987 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lr=0.010000 Epoch[010] Batch [3149]/[3760] Speed: 77.211478 samples/sec accuracy=53.979167 loss=1.927232 lr=0.010000 Epoch[010] Batch [3199]/[3760] Speed: 74.726756 samples/sec accuracy=53.986328 loss=1.927693 lr=0.010000 Epoch[010] Batch [3249]/[3760] Speed: 75.583181 samples/sec accuracy=53.980288 loss=1.927802 lr=0.010000 Epoch[010] Batch [3299]/[3760] Speed: 75.345240 samples/sec accuracy=53.985322 loss=1.928555 lr=0.010000 Epoch[010] Batch [3349]/[3760] Speed: 74.430089 samples/sec accuracy=53.992537 loss=1.928247 lr=0.010000 Epoch[010] Batch [3399]/[3760] Speed: 76.077411 samples/sec accuracy=53.983456 loss=1.928539 lr=0.010000 Epoch[010] Batch [3449]/[3760] Speed: 73.133495 samples/sec accuracy=53.971014 loss=1.928956 lr=0.010000 Epoch[010] Batch [3499]/[3760] Speed: 70.541588 samples/sec accuracy=53.978125 loss=1.928883 lr=0.010000 Epoch[010] Batch [3549]/[3760] Speed: 78.787791 samples/sec accuracy=53.990757 loss=1.928752 lr=0.010000 Epoch[010] Batch [3599]/[3760] Speed: 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acc-top5=79.427083 Batch [0199]/[0303]: acc-top1=55.125000 acc-top5=79.695312 Batch [0249]/[0303]: acc-top1=55.187500 acc-top5=79.737500 Batch [0299]/[0303]: acc-top1=55.213542 acc-top5=79.494792 [Epoch 011] training: accuracy=54.850027 loss=1.891341 [Epoch 011] speed: 74 samples/sec time cost: 3497.207829 [Epoch 011] validation: acc-top1=55.146452 acc-top5=79.512170 loss=1.987532 Epoch[012] Batch [0049]/[3760] Speed: 53.711336 samples/sec accuracy=57.218750 loss=1.806616 lr=0.010000 Epoch[012] Batch [0099]/[3760] Speed: 72.283093 samples/sec accuracy=56.640625 loss=1.854363 lr=0.010000 Epoch[012] Batch [0149]/[3760] Speed: 77.593276 samples/sec accuracy=56.343750 loss=1.849183 lr=0.010000 Epoch[012] Batch [0199]/[3760] Speed: 74.071083 samples/sec accuracy=56.390625 loss=1.845406 lr=0.010000 Epoch[012] Batch [0249]/[3760] Speed: 75.505731 samples/sec accuracy=56.237500 loss=1.846888 lr=0.010000 Epoch[012] Batch [0299]/[3760] Speed: 75.404943 samples/sec accuracy=56.125000 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accuracy=55.501420 loss=1.862685 lr=0.010000 Epoch[012] Batch [2249]/[3760] Speed: 76.653624 samples/sec accuracy=55.504861 loss=1.861882 lr=0.010000 Epoch[012] Batch [2299]/[3760] Speed: 74.242428 samples/sec accuracy=55.506114 loss=1.862194 lr=0.010000 Epoch[012] Batch [2349]/[3760] Speed: 75.491722 samples/sec accuracy=55.486037 loss=1.862248 lr=0.010000 Epoch[012] Batch [2399]/[3760] Speed: 72.961542 samples/sec accuracy=55.509766 loss=1.862265 lr=0.010000 Epoch[012] Batch [2449]/[3760] Speed: 77.234242 samples/sec accuracy=55.484056 loss=1.863613 lr=0.010000 Epoch[012] Batch [2499]/[3760] Speed: 72.881244 samples/sec accuracy=55.485625 loss=1.863727 lr=0.010000 Epoch[012] Batch [2549]/[3760] Speed: 76.159845 samples/sec accuracy=55.476716 loss=1.863592 lr=0.010000 Epoch[012] Batch [2599]/[3760] Speed: 74.534744 samples/sec accuracy=55.460337 loss=1.864315 lr=0.010000 Epoch[012] Batch [2649]/[3760] Speed: 75.299651 samples/sec accuracy=55.454599 loss=1.864748 lr=0.010000 Epoch[012] 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accuracy=55.440476 loss=1.864254 lr=0.010000 Epoch[012] Batch [3199]/[3760] Speed: 75.614096 samples/sec accuracy=55.461426 loss=1.863530 lr=0.010000 Epoch[012] Batch [3249]/[3760] Speed: 71.101849 samples/sec accuracy=55.446635 loss=1.864646 lr=0.010000 Epoch[012] Batch [3299]/[3760] Speed: 81.180795 samples/sec accuracy=55.453125 loss=1.863746 lr=0.010000 Epoch[012] Batch [3349]/[3760] Speed: 77.638687 samples/sec accuracy=55.443563 loss=1.864386 lr=0.010000 Epoch[012] Batch [3399]/[3760] Speed: 72.943428 samples/sec accuracy=55.434283 loss=1.864992 lr=0.010000 Epoch[012] Batch [3449]/[3760] Speed: 76.751497 samples/sec accuracy=55.431612 loss=1.865944 lr=0.010000 Epoch[012] Batch [3499]/[3760] Speed: 71.292594 samples/sec accuracy=55.424554 loss=1.865920 lr=0.010000 Epoch[012] Batch [3549]/[3760] Speed: 79.082882 samples/sec accuracy=55.427817 loss=1.866282 lr=0.010000 Epoch[012] Batch [3599]/[3760] Speed: 73.091763 samples/sec accuracy=55.443142 loss=1.865776 lr=0.010000 Epoch[012] 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[0249]/[0303]: acc-top1=56.868750 acc-top5=80.037500 Batch [0299]/[0303]: acc-top1=56.765625 acc-top5=79.968750 [Epoch 013] training: accuracy=55.707696 loss=1.846928 [Epoch 013] speed: 75 samples/sec time cost: 3480.402298 [Epoch 013] validation: acc-top1=56.714109 acc-top5=79.971122 loss=1.940537 Epoch[014] Batch [0049]/[3759] Speed: 53.991444 samples/sec accuracy=57.062500 loss=1.814165 lr=0.010000 Epoch[014] Batch [0099]/[3759] Speed: 70.860166 samples/sec accuracy=56.343750 loss=1.819300 lr=0.010000 Epoch[014] Batch [0149]/[3759] Speed: 77.204974 samples/sec accuracy=56.375000 loss=1.824608 lr=0.010000 Epoch[014] Batch [0199]/[3759] Speed: 77.366299 samples/sec accuracy=56.328125 loss=1.822285 lr=0.010000 Epoch[014] Batch [0249]/[3759] Speed: 72.252239 samples/sec accuracy=56.375000 loss=1.811135 lr=0.010000 Epoch[014] Batch [0299]/[3759] Speed: 77.334090 samples/sec accuracy=56.359375 loss=1.804056 lr=0.010000 Epoch[014] Batch [0349]/[3759] Speed: 73.875287 samples/sec 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lr=0.010000 Epoch[015] Batch [3499]/[3760] Speed: 74.046895 samples/sec accuracy=56.858482 loss=1.794904 lr=0.010000 Epoch[015] Batch [3549]/[3760] Speed: 76.897847 samples/sec accuracy=56.818662 loss=1.796444 lr=0.010000 Epoch[015] Batch [3599]/[3760] Speed: 76.118043 samples/sec accuracy=56.831597 loss=1.797001 lr=0.010000 Epoch[015] Batch [3649]/[3760] Speed: 72.207079 samples/sec accuracy=56.818493 loss=1.797335 lr=0.010000 Epoch[015] Batch [3699]/[3760] Speed: 77.156690 samples/sec accuracy=56.815878 loss=1.797488 lr=0.010000 Epoch[015] Batch [3749]/[3760] Speed: 83.408651 samples/sec accuracy=56.830417 loss=1.797389 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.125000 acc-top5=79.875000 Batch [0099]/[0303]: acc-top1=56.921875 acc-top5=80.062500 Batch [0149]/[0303]: acc-top1=56.531250 acc-top5=80.489583 Batch [0199]/[0303]: acc-top1=56.437500 acc-top5=80.500000 Batch [0249]/[0303]: acc-top1=56.331250 acc-top5=80.406250 Batch [0299]/[0303]: acc-top1=56.218750 acc-top5=80.276042 [Epoch 015] training: accuracy=56.829704 loss=1.797378 [Epoch 015] speed: 75 samples/sec time cost: 3486.824827 [Epoch 015] validation: acc-top1=56.177805 acc-top5=80.306312 loss=1.997360 Epoch[016] Batch [0049]/[3760] Speed: 54.754061 samples/sec accuracy=56.906250 loss=1.758133 lr=0.010000 Epoch[016] Batch [0099]/[3760] Speed: 70.699766 samples/sec accuracy=56.937500 loss=1.777242 lr=0.010000 Epoch[016] Batch [0149]/[3760] Speed: 78.531758 samples/sec accuracy=56.822917 loss=1.784368 lr=0.010000 Epoch[016] Batch [0199]/[3760] Speed: 74.532187 samples/sec accuracy=57.031250 loss=1.775842 lr=0.010000 Epoch[016] Batch [0249]/[3760] Speed: 75.140159 samples/sec accuracy=56.800000 loss=1.788401 lr=0.010000 Epoch[016] Batch [0299]/[3760] Speed: 77.324058 samples/sec accuracy=56.859375 loss=1.791499 lr=0.010000 Epoch[016] Batch [0349]/[3760] Speed: 73.780978 samples/sec accuracy=56.973214 loss=1.782292 lr=0.010000 Epoch[016] Batch [0399]/[3760] Speed: 76.939938 samples/sec accuracy=57.101562 loss=1.777896 lr=0.010000 Epoch[016] Batch [0449]/[3760] Speed: 75.443514 samples/sec accuracy=57.128472 loss=1.774217 lr=0.010000 Epoch[016] Batch [0499]/[3760] Speed: 73.937896 samples/sec accuracy=57.162500 loss=1.776641 lr=0.010000 Epoch[016] Batch [0549]/[3760] Speed: 77.048106 samples/sec accuracy=57.184659 loss=1.775259 lr=0.010000 Epoch[016] Batch [0599]/[3760] Speed: 74.718538 samples/sec accuracy=57.093750 loss=1.778641 lr=0.010000 Epoch[016] Batch [0649]/[3760] Speed: 76.445773 samples/sec accuracy=57.112981 loss=1.776860 lr=0.010000 Epoch[016] Batch [0699]/[3760] Speed: 75.855431 samples/sec accuracy=57.149554 loss=1.775956 lr=0.010000 Epoch[016] Batch [0749]/[3760] Speed: 76.034130 samples/sec accuracy=57.114583 loss=1.778127 lr=0.010000 Epoch[016] Batch [0799]/[3760] Speed: 76.261745 samples/sec accuracy=57.087891 loss=1.779370 lr=0.010000 Epoch[016] Batch [0849]/[3760] Speed: 73.681174 samples/sec accuracy=57.056985 loss=1.781847 lr=0.010000 Epoch[016] 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accuracy=56.994213 loss=1.784618 lr=0.010000 Epoch[016] Batch [1399]/[3760] Speed: 76.411238 samples/sec accuracy=56.945312 loss=1.786016 lr=0.010000 Epoch[016] Batch [1449]/[3760] Speed: 74.279575 samples/sec accuracy=56.949353 loss=1.784409 lr=0.010000 Epoch[016] Batch [1499]/[3760] Speed: 75.131055 samples/sec accuracy=56.923958 loss=1.785228 lr=0.010000 Epoch[016] Batch [1549]/[3760] Speed: 77.254138 samples/sec accuracy=56.918347 loss=1.784814 lr=0.010000 Epoch[016] Batch [1599]/[3760] Speed: 74.687130 samples/sec accuracy=56.919922 loss=1.785387 lr=0.010000 Epoch[016] Batch [1649]/[3760] Speed: 74.814217 samples/sec accuracy=56.890152 loss=1.786812 lr=0.010000 Epoch[016] Batch [1699]/[3760] Speed: 77.858850 samples/sec accuracy=56.902574 loss=1.786393 lr=0.010000 Epoch[016] Batch [1749]/[3760] Speed: 73.645522 samples/sec accuracy=56.914286 loss=1.786084 lr=0.010000 Epoch[016] Batch [1799]/[3760] Speed: 77.549662 samples/sec accuracy=56.907118 loss=1.787348 lr=0.010000 Epoch[016] 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accuracy=57.040082 loss=1.782685 lr=0.010000 Epoch[016] Batch [2349]/[3760] Speed: 76.068843 samples/sec accuracy=57.061170 loss=1.781968 lr=0.010000 Epoch[016] Batch [2399]/[3760] Speed: 76.623597 samples/sec accuracy=57.066406 loss=1.782015 lr=0.010000 Epoch[016] Batch [2449]/[3760] Speed: 73.976411 samples/sec accuracy=57.047832 loss=1.782031 lr=0.010000 Epoch[016] Batch [2499]/[3760] Speed: 75.616477 samples/sec accuracy=57.028125 loss=1.782753 lr=0.010000 Epoch[016] Batch [2549]/[3760] Speed: 76.770732 samples/sec accuracy=57.019608 loss=1.783533 lr=0.010000 Epoch[016] Batch [2599]/[3760] Speed: 76.573384 samples/sec accuracy=57.022236 loss=1.783735 lr=0.010000 Epoch[016] Batch [2649]/[3760] Speed: 73.014721 samples/sec accuracy=56.984670 loss=1.785506 lr=0.010000 Epoch[016] Batch [2699]/[3760] Speed: 77.353488 samples/sec accuracy=56.993634 loss=1.784922 lr=0.010000 Epoch[016] Batch [2749]/[3760] Speed: 75.741388 samples/sec accuracy=56.992045 loss=1.785014 lr=0.010000 Epoch[016] 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accuracy=56.994231 loss=1.786667 lr=0.010000 Epoch[016] Batch [3299]/[3760] Speed: 77.087142 samples/sec accuracy=57.010890 loss=1.786294 lr=0.010000 Epoch[016] Batch [3349]/[3760] Speed: 74.926611 samples/sec accuracy=57.025653 loss=1.785885 lr=0.010000 Epoch[016] Batch [3399]/[3760] Speed: 74.792566 samples/sec accuracy=57.042739 loss=1.786207 lr=0.010000 Epoch[016] Batch [3449]/[3760] Speed: 76.572001 samples/sec accuracy=57.043025 loss=1.786037 lr=0.010000 Epoch[016] Batch [3499]/[3760] Speed: 76.270971 samples/sec accuracy=57.023661 loss=1.786546 lr=0.010000 Epoch[016] Batch [3549]/[3760] Speed: 74.073694 samples/sec accuracy=57.029930 loss=1.786475 lr=0.010000 Epoch[016] Batch [3599]/[3760] Speed: 76.583287 samples/sec accuracy=57.037326 loss=1.786491 lr=0.010000 Epoch[016] Batch [3649]/[3760] Speed: 74.112159 samples/sec accuracy=57.035959 loss=1.786505 lr=0.010000 Epoch[016] Batch [3699]/[3760] Speed: 76.872607 samples/sec accuracy=57.033784 loss=1.786108 lr=0.010000 Epoch[016] Batch [3749]/[3760] Speed: 83.949447 samples/sec accuracy=57.000417 loss=1.787133 lr=0.010000 Batch [0049]/[0303]: acc-top1=55.812500 acc-top5=79.343750 Batch [0099]/[0303]: acc-top1=55.828125 acc-top5=79.484375 Batch [0149]/[0303]: acc-top1=56.083333 acc-top5=79.697917 Batch [0199]/[0303]: acc-top1=56.304687 acc-top5=79.929688 Batch [0249]/[0303]: acc-top1=56.437500 acc-top5=79.956250 Batch [0299]/[0303]: acc-top1=56.239583 acc-top5=79.822917 [Epoch 016] training: accuracy=57.001745 loss=1.787227 [Epoch 016] speed: 75 samples/sec time cost: 3473.329180 [Epoch 016] validation: acc-top1=56.250000 acc-top5=79.847360 loss=1.963980 Epoch[017] Batch [0049]/[3759] Speed: 53.782862 samples/sec accuracy=57.781250 loss=1.730486 lr=0.010000 Epoch[017] Batch [0099]/[3759] Speed: 73.533382 samples/sec accuracy=57.390625 loss=1.723902 lr=0.010000 Epoch[017] Batch [0149]/[3759] Speed: 75.132814 samples/sec accuracy=57.614583 loss=1.734147 lr=0.010000 Epoch[017] Batch [0199]/[3759] Speed: 75.855182 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lr=0.010000 Epoch[017] Batch [3549]/[3759] Speed: 75.560556 samples/sec accuracy=57.506162 loss=1.767121 lr=0.010000 Epoch[017] Batch [3599]/[3759] Speed: 76.257445 samples/sec accuracy=57.505208 loss=1.766992 lr=0.010000 Epoch[017] Batch [3649]/[3759] Speed: 73.679054 samples/sec accuracy=57.481164 loss=1.768048 lr=0.010000 Epoch[017] Batch [3699]/[3759] Speed: 76.415237 samples/sec accuracy=57.461149 loss=1.768469 lr=0.010000 Epoch[017] Batch [3749]/[3759] Speed: 85.913066 samples/sec accuracy=57.452917 loss=1.768791 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.312500 acc-top5=80.187500 Batch [0099]/[0303]: acc-top1=57.546875 acc-top5=80.250000 Batch [0149]/[0303]: acc-top1=57.031250 acc-top5=80.385417 Batch [0199]/[0303]: acc-top1=57.171875 acc-top5=80.578125 Batch [0249]/[0303]: acc-top1=57.300000 acc-top5=80.718750 Batch [0299]/[0303]: acc-top1=57.046875 acc-top5=80.375000 [Epoch 017] training: accuracy=57.454193 loss=1.768804 [Epoch 017] speed: 75 samples/sec time cost: 3473.803860 [Epoch 017] validation: acc-top1=57.018358 acc-top5=80.419761 loss=1.921809 Epoch[018] Batch [0049]/[3760] Speed: 53.963980 samples/sec accuracy=57.906250 loss=1.756255 lr=0.010000 Epoch[018] Batch [0099]/[3760] Speed: 68.681314 samples/sec accuracy=58.187500 loss=1.722515 lr=0.010000 Epoch[018] Batch [0149]/[3760] Speed: 79.097173 samples/sec accuracy=58.739583 loss=1.699953 lr=0.010000 Epoch[018] Batch [0199]/[3760] Speed: 70.910727 samples/sec accuracy=58.812500 loss=1.697819 lr=0.010000 Epoch[018] Batch [0249]/[3760] Speed: 79.690893 samples/sec accuracy=58.912500 loss=1.695372 lr=0.010000 Epoch[018] Batch [0299]/[3760] Speed: 76.348184 samples/sec accuracy=58.776042 loss=1.698417 lr=0.010000 Epoch[018] Batch [0349]/[3760] Speed: 75.806790 samples/sec accuracy=58.647321 loss=1.704419 lr=0.010000 Epoch[018] Batch [0399]/[3760] Speed: 74.345222 samples/sec accuracy=58.750000 loss=1.703552 lr=0.010000 Epoch[018] Batch [0449]/[3760] Speed: 75.199924 samples/sec 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accuracy=57.907670 loss=1.749079 lr=0.010000 Epoch[018] Batch [3349]/[3760] Speed: 75.528022 samples/sec accuracy=57.886194 loss=1.750246 lr=0.010000 Epoch[018] Batch [3399]/[3760] Speed: 76.934040 samples/sec accuracy=57.865349 loss=1.750895 lr=0.010000 Epoch[018] Batch [3449]/[3760] Speed: 73.480177 samples/sec accuracy=57.875906 loss=1.750690 lr=0.010000 Epoch[018] Batch [3499]/[3760] Speed: 75.700353 samples/sec accuracy=57.853125 loss=1.751631 lr=0.010000 Epoch[018] Batch [3549]/[3760] Speed: 76.740390 samples/sec accuracy=57.855194 loss=1.752103 lr=0.010000 Epoch[018] Batch [3599]/[3760] Speed: 74.797664 samples/sec accuracy=57.860677 loss=1.751249 lr=0.010000 Epoch[018] Batch [3649]/[3760] Speed: 75.944784 samples/sec accuracy=57.853168 loss=1.751141 lr=0.010000 Epoch[018] Batch [3699]/[3760] Speed: 75.174398 samples/sec accuracy=57.850929 loss=1.750775 lr=0.010000 Epoch[018] Batch [3749]/[3760] Speed: 83.446928 samples/sec accuracy=57.840833 loss=1.750482 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.843750 acc-top5=80.187500 Batch [0099]/[0303]: acc-top1=57.234375 acc-top5=80.609375 Batch [0149]/[0303]: acc-top1=56.802083 acc-top5=80.708333 Batch [0199]/[0303]: acc-top1=57.203125 acc-top5=80.898438 Batch [0249]/[0303]: acc-top1=57.237500 acc-top5=80.856250 Batch [0299]/[0303]: acc-top1=57.166667 acc-top5=80.791667 [Epoch 018] training: accuracy=57.840342 loss=1.750611 [Epoch 018] speed: 75 samples/sec time cost: 3475.952386 [Epoch 018] validation: acc-top1=57.147277 acc-top5=80.816832 loss=1.929434 Epoch[019] Batch [0049]/[3760] Speed: 53.623336 samples/sec accuracy=58.656250 loss=1.693104 lr=0.010000 Epoch[019] Batch [0099]/[3760] Speed: 72.107116 samples/sec accuracy=58.828125 loss=1.694077 lr=0.010000 Epoch[019] Batch [0149]/[3760] Speed: 76.024494 samples/sec accuracy=59.645833 loss=1.671129 lr=0.010000 Epoch[019] Batch [0199]/[3760] Speed: 78.297186 samples/sec accuracy=59.265625 loss=1.682402 lr=0.010000 Epoch[019] Batch [0249]/[3760] Speed: 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lr=0.010000 Epoch[019] Batch [3599]/[3760] Speed: 75.245748 samples/sec accuracy=58.110677 loss=1.739006 lr=0.010000 Epoch[019] Batch [3649]/[3760] Speed: 76.020743 samples/sec accuracy=58.086045 loss=1.740120 lr=0.010000 Epoch[019] Batch [3699]/[3760] Speed: 73.509769 samples/sec accuracy=58.068834 loss=1.740757 lr=0.010000 Epoch[019] Batch [3749]/[3760] Speed: 86.712818 samples/sec accuracy=58.071667 loss=1.740946 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.031250 acc-top5=80.625000 Batch [0099]/[0303]: acc-top1=56.312500 acc-top5=80.281250 Batch [0149]/[0303]: acc-top1=56.458333 acc-top5=80.406250 Batch [0199]/[0303]: acc-top1=56.703125 acc-top5=80.546875 Batch [0249]/[0303]: acc-top1=56.700000 acc-top5=80.462500 Batch [0299]/[0303]: acc-top1=56.859375 acc-top5=80.270833 [Epoch 019] training: accuracy=58.076795 loss=1.740757 [Epoch 019] speed: 75 samples/sec time cost: 3463.443555 [Epoch 019] validation: acc-top1=56.827558 acc-top5=80.270215 loss=1.966585 Epoch[020] Batch 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accuracy=58.634766 loss=1.716663 lr=0.010000 Epoch[020] Batch [2449]/[3759] Speed: 75.049049 samples/sec accuracy=58.606505 loss=1.717714 lr=0.010000 Epoch[020] Batch [2499]/[3759] Speed: 76.591892 samples/sec accuracy=58.617500 loss=1.718127 lr=0.010000 Epoch[020] Batch [2549]/[3759] Speed: 77.185863 samples/sec accuracy=58.625613 loss=1.718340 lr=0.010000 Epoch[020] Batch [2599]/[3759] Speed: 75.890895 samples/sec accuracy=58.586538 loss=1.720355 lr=0.010000 Epoch[020] Batch [2649]/[3759] Speed: 74.002970 samples/sec accuracy=58.600236 loss=1.719692 lr=0.010000 Epoch[020] Batch [2699]/[3759] Speed: 76.141782 samples/sec accuracy=58.567708 loss=1.720510 lr=0.010000 Epoch[020] Batch [2749]/[3759] Speed: 76.778389 samples/sec accuracy=58.594318 loss=1.720656 lr=0.010000 Epoch[020] Batch [2799]/[3759] Speed: 74.241882 samples/sec accuracy=58.577009 loss=1.720773 lr=0.010000 Epoch[020] Batch [2849]/[3759] Speed: 72.362380 samples/sec accuracy=58.564145 loss=1.721082 lr=0.010000 Epoch[020] 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accuracy=58.538713 loss=1.721828 lr=0.010000 Epoch[020] Batch [3399]/[3759] Speed: 73.510525 samples/sec accuracy=58.538603 loss=1.722412 lr=0.010000 Epoch[020] Batch [3449]/[3759] Speed: 77.344359 samples/sec accuracy=58.536232 loss=1.723102 lr=0.010000 Epoch[020] Batch [3499]/[3759] Speed: 74.512737 samples/sec accuracy=58.522768 loss=1.723927 lr=0.010000 Epoch[020] Batch [3549]/[3759] Speed: 74.562090 samples/sec accuracy=58.502201 loss=1.725030 lr=0.010000 Epoch[020] Batch [3599]/[3759] Speed: 75.020280 samples/sec accuracy=58.489149 loss=1.725072 lr=0.010000 Epoch[020] Batch [3649]/[3759] Speed: 78.465286 samples/sec accuracy=58.483305 loss=1.725393 lr=0.010000 Epoch[020] Batch [3699]/[3759] Speed: 73.847229 samples/sec accuracy=58.484797 loss=1.725101 lr=0.010000 Epoch[020] Batch [3749]/[3759] Speed: 83.921232 samples/sec accuracy=58.481667 loss=1.725054 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.343750 acc-top5=79.687500 Batch [0099]/[0303]: acc-top1=57.093750 acc-top5=80.078125 Batch [0149]/[0303]: acc-top1=56.458333 acc-top5=80.062500 Batch [0199]/[0303]: acc-top1=56.664062 acc-top5=80.179688 Batch [0249]/[0303]: acc-top1=56.575000 acc-top5=80.150000 Batch [0299]/[0303]: acc-top1=56.505208 acc-top5=80.098958 [Epoch 020] training: accuracy=58.485053 loss=1.724853 [Epoch 020] speed: 75 samples/sec time cost: 3473.304425 [Epoch 020] validation: acc-top1=56.482054 acc-top5=80.115512 loss=2.051231 Epoch[021] Batch [0049]/[3760] Speed: 52.745753 samples/sec accuracy=60.125000 loss=1.683971 lr=0.010000 Epoch[021] Batch [0099]/[3760] Speed: 72.848202 samples/sec accuracy=59.546875 loss=1.690676 lr=0.010000 Epoch[021] Batch [0149]/[3760] Speed: 78.115037 samples/sec accuracy=59.270833 loss=1.699215 lr=0.010000 Epoch[021] Batch [0199]/[3760] Speed: 74.446453 samples/sec accuracy=59.406250 loss=1.685147 lr=0.010000 Epoch[021] Batch [0249]/[3760] Speed: 75.707570 samples/sec accuracy=59.331250 loss=1.688135 lr=0.010000 Epoch[021] Batch [0299]/[3760] 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accuracy=58.513021 loss=1.720504 lr=0.010000 Epoch[021] Batch [3649]/[3760] Speed: 75.420412 samples/sec accuracy=58.504281 loss=1.721198 lr=0.010000 Epoch[021] Batch [3699]/[3760] Speed: 76.714240 samples/sec accuracy=58.514780 loss=1.721109 lr=0.010000 Epoch[021] Batch [3749]/[3760] Speed: 85.223511 samples/sec accuracy=58.514167 loss=1.720784 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.750000 acc-top5=80.031250 Batch [0099]/[0303]: acc-top1=57.234375 acc-top5=80.343750 Batch [0149]/[0303]: acc-top1=56.906250 acc-top5=80.500000 Batch [0199]/[0303]: acc-top1=56.976563 acc-top5=80.812500 Batch [0249]/[0303]: acc-top1=57.025000 acc-top5=80.843750 Batch [0299]/[0303]: acc-top1=57.062500 acc-top5=80.614583 [Epoch 021] training: accuracy=58.509392 loss=1.721050 [Epoch 021] speed: 75 samples/sec time cost: 3472.749113 [Epoch 021] validation: acc-top1=57.038985 acc-top5=80.631188 loss=1.967986 Epoch[022] Batch [0049]/[3760] Speed: 52.752494 samples/sec accuracy=61.500000 loss=1.604420 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acc-top1=57.531250 acc-top5=81.101562 Batch [0249]/[0303]: acc-top1=57.525000 acc-top5=81.187500 Batch [0299]/[0303]: acc-top1=57.619792 acc-top5=81.026042 [Epoch 022] training: accuracy=58.796127 loss=1.706880 [Epoch 022] speed: 75 samples/sec time cost: 3462.945509 [Epoch 022] validation: acc-top1=57.570132 acc-top5=81.059200 loss=1.932112 Epoch[023] Batch [0049]/[3759] Speed: 53.264627 samples/sec accuracy=59.687500 loss=1.626299 lr=0.010000 Epoch[023] Batch [0099]/[3759] Speed: 70.779165 samples/sec accuracy=60.593750 loss=1.611283 lr=0.010000 Epoch[023] Batch [0149]/[3759] Speed: 76.013758 samples/sec accuracy=60.500000 loss=1.627095 lr=0.010000 Epoch[023] Batch [0199]/[3759] Speed: 77.511874 samples/sec accuracy=60.312500 loss=1.650073 lr=0.010000 Epoch[023] Batch [0249]/[3759] Speed: 76.297232 samples/sec accuracy=60.062500 loss=1.649504 lr=0.010000 Epoch[023] Batch [0299]/[3759] Speed: 74.891418 samples/sec accuracy=60.015625 loss=1.652685 lr=0.010000 Epoch[023] Batch 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accuracy=58.943493 loss=1.697330 lr=0.010000 Epoch[023] Batch [3699]/[3759] Speed: 74.548200 samples/sec accuracy=58.943834 loss=1.697738 lr=0.010000 Epoch[023] Batch [3749]/[3759] Speed: 86.635169 samples/sec accuracy=58.934583 loss=1.697561 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.937500 acc-top5=80.562500 Batch [0099]/[0303]: acc-top1=58.265625 acc-top5=80.859375 Batch [0149]/[0303]: acc-top1=57.666667 acc-top5=81.114583 Batch [0199]/[0303]: acc-top1=58.203125 acc-top5=81.265625 Batch [0249]/[0303]: acc-top1=58.250000 acc-top5=81.406250 Batch [0299]/[0303]: acc-top1=58.083333 acc-top5=81.234375 [Epoch 023] training: accuracy=58.928987 loss=1.697745 [Epoch 023] speed: 75 samples/sec time cost: 3473.168813 [Epoch 023] validation: acc-top1=58.039398 acc-top5=81.260314 loss=1.921678 Epoch[024] Batch [0049]/[3760] Speed: 54.242046 samples/sec accuracy=59.843750 loss=1.685139 lr=0.010000 Epoch[024] Batch [0099]/[3760] Speed: 70.569967 samples/sec accuracy=59.562500 loss=1.667714 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lr=0.010000 Epoch[024] Batch [2999]/[3760] Speed: 75.168459 samples/sec accuracy=59.392188 loss=1.685507 lr=0.010000 Epoch[024] Batch [3049]/[3760] Speed: 77.405836 samples/sec accuracy=59.398566 loss=1.685776 lr=0.010000 Epoch[024] Batch [3099]/[3760] Speed: 76.987201 samples/sec accuracy=59.394657 loss=1.685943 lr=0.010000 Epoch[024] Batch [3149]/[3760] Speed: 74.466058 samples/sec accuracy=59.383929 loss=1.686803 lr=0.010000 Epoch[024] Batch [3199]/[3760] Speed: 75.874027 samples/sec accuracy=59.365723 loss=1.687730 lr=0.010000 Epoch[024] Batch [3249]/[3760] Speed: 75.284768 samples/sec accuracy=59.349519 loss=1.688029 lr=0.010000 Epoch[024] Batch [3299]/[3760] Speed: 75.230751 samples/sec accuracy=59.330966 loss=1.688503 lr=0.010000 Epoch[024] Batch [3349]/[3760] Speed: 77.319464 samples/sec accuracy=59.321362 loss=1.688884 lr=0.010000 Epoch[024] Batch [3399]/[3760] Speed: 77.130435 samples/sec accuracy=59.321691 loss=1.688471 lr=0.010000 Epoch[024] Batch [3449]/[3760] Speed: 74.250366 samples/sec accuracy=59.315670 loss=1.688477 lr=0.010000 Epoch[024] Batch [3499]/[3760] Speed: 76.554089 samples/sec accuracy=59.325446 loss=1.688302 lr=0.010000 Epoch[024] Batch [3549]/[3760] Speed: 77.532689 samples/sec accuracy=59.312940 loss=1.688237 lr=0.010000 Epoch[024] Batch [3599]/[3760] Speed: 75.248622 samples/sec accuracy=59.305990 loss=1.688707 lr=0.010000 Epoch[024] Batch [3649]/[3760] Speed: 76.710276 samples/sec accuracy=59.289384 loss=1.689638 lr=0.010000 Epoch[024] Batch [3699]/[3760] Speed: 75.573247 samples/sec accuracy=59.292230 loss=1.689707 lr=0.010000 Epoch[024] Batch [3749]/[3760] Speed: 83.174855 samples/sec accuracy=59.284583 loss=1.690035 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.656250 acc-top5=80.406250 Batch [0099]/[0303]: acc-top1=57.750000 acc-top5=80.843750 Batch [0149]/[0303]: acc-top1=57.395833 acc-top5=81.010417 Batch [0199]/[0303]: acc-top1=57.882812 acc-top5=81.250000 Batch [0249]/[0303]: acc-top1=57.825000 acc-top5=81.287500 Batch [0299]/[0303]: acc-top1=57.713542 acc-top5=81.182292 [Epoch 024] training: accuracy=59.276513 loss=1.690323 [Epoch 024] speed: 75 samples/sec time cost: 3460.041303 [Epoch 024] validation: acc-top1=57.683581 acc-top5=81.198432 loss=1.940002 Epoch[025] Batch [0049]/[3760] Speed: 54.319960 samples/sec accuracy=60.281250 loss=1.654011 lr=0.010000 Epoch[025] Batch [0099]/[3760] Speed: 72.009250 samples/sec accuracy=60.421875 loss=1.643581 lr=0.010000 Epoch[025] Batch [0149]/[3760] Speed: 77.812613 samples/sec accuracy=60.395833 loss=1.639696 lr=0.010000 Epoch[025] Batch [0199]/[3760] Speed: 77.861521 samples/sec accuracy=60.187500 loss=1.651975 lr=0.010000 Epoch[025] Batch [0249]/[3760] Speed: 73.095973 samples/sec accuracy=59.787500 loss=1.666758 lr=0.010000 Epoch[025] Batch [0299]/[3760] Speed: 76.556987 samples/sec accuracy=59.786458 loss=1.668273 lr=0.010000 Epoch[025] Batch [0349]/[3760] Speed: 76.720635 samples/sec accuracy=59.651786 loss=1.673879 lr=0.010000 Epoch[025] Batch 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accuracy=59.893382 loss=1.654398 lr=0.010000 Epoch[025] Batch [0899]/[3760] Speed: 77.460632 samples/sec accuracy=59.815972 loss=1.656940 lr=0.010000 Epoch[025] Batch [0949]/[3760] Speed: 75.692547 samples/sec accuracy=59.769737 loss=1.657475 lr=0.010000 Epoch[025] Batch [0999]/[3760] Speed: 74.186861 samples/sec accuracy=59.745313 loss=1.659771 lr=0.010000 Epoch[025] Batch [1049]/[3760] Speed: 76.260357 samples/sec accuracy=59.727679 loss=1.660153 lr=0.010000 Epoch[025] Batch [1099]/[3760] Speed: 77.412872 samples/sec accuracy=59.752841 loss=1.662289 lr=0.010000 Epoch[025] Batch [1149]/[3760] Speed: 74.926441 samples/sec accuracy=59.770380 loss=1.661317 lr=0.010000 Epoch[025] Batch [1199]/[3760] Speed: 75.784642 samples/sec accuracy=59.748698 loss=1.663745 lr=0.010000 Epoch[025] Batch [1249]/[3760] Speed: 77.002783 samples/sec accuracy=59.728750 loss=1.664822 lr=0.010000 Epoch[025] Batch [1299]/[3760] Speed: 74.466061 samples/sec accuracy=59.688702 loss=1.666293 lr=0.010000 Epoch[025] 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accuracy=59.480114 loss=1.675675 lr=0.010000 Epoch[025] Batch [2799]/[3760] Speed: 75.209609 samples/sec accuracy=59.461496 loss=1.676774 lr=0.010000 Epoch[025] Batch [2849]/[3760] Speed: 75.008320 samples/sec accuracy=59.454496 loss=1.677747 lr=0.010000 Epoch[025] Batch [2899]/[3760] Speed: 76.834955 samples/sec accuracy=59.433728 loss=1.679198 lr=0.010000 Epoch[025] Batch [2949]/[3760] Speed: 74.735998 samples/sec accuracy=59.440678 loss=1.678978 lr=0.010000 Epoch[025] Batch [2999]/[3760] Speed: 76.634337 samples/sec accuracy=59.438021 loss=1.679457 lr=0.010000 Epoch[025] Batch [3049]/[3760] Speed: 76.669797 samples/sec accuracy=59.423156 loss=1.679755 lr=0.010000 Epoch[025] Batch [3099]/[3760] Speed: 73.679096 samples/sec accuracy=59.415323 loss=1.680444 lr=0.010000 Epoch[025] Batch [3149]/[3760] Speed: 77.077538 samples/sec accuracy=59.414683 loss=1.680486 lr=0.010000 Epoch[025] Batch [3199]/[3760] Speed: 74.590636 samples/sec accuracy=59.394531 loss=1.680457 lr=0.010000 Epoch[025] 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accuracy=59.278716 loss=1.684613 lr=0.010000 Epoch[025] Batch [3749]/[3760] Speed: 81.634100 samples/sec accuracy=59.288750 loss=1.684366 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.906250 acc-top5=79.500000 Batch [0099]/[0303]: acc-top1=56.953125 acc-top5=79.953125 Batch [0149]/[0303]: acc-top1=56.718750 acc-top5=80.104167 Batch [0199]/[0303]: acc-top1=56.921875 acc-top5=80.265625 Batch [0249]/[0303]: acc-top1=56.718750 acc-top5=80.406250 Batch [0299]/[0303]: acc-top1=56.598958 acc-top5=80.255208 [Epoch 025] training: accuracy=59.281915 loss=1.684562 [Epoch 025] speed: 75 samples/sec time cost: 3464.083751 [Epoch 025] validation: acc-top1=56.569719 acc-top5=80.265058 loss=1.964102 Epoch[026] Batch [0049]/[3759] Speed: 53.262596 samples/sec accuracy=59.531250 loss=1.666010 lr=0.010000 Epoch[026] Batch [0099]/[3759] Speed: 71.075775 samples/sec accuracy=60.312500 loss=1.630792 lr=0.010000 Epoch[026] Batch [0149]/[3759] Speed: 77.442968 samples/sec accuracy=59.552083 loss=1.665670 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lr=0.010000 Epoch[026] Batch [2099]/[3759] Speed: 73.321254 samples/sec accuracy=59.651042 loss=1.667088 lr=0.010000 Epoch[026] Batch [2149]/[3759] Speed: 76.367027 samples/sec accuracy=59.664971 loss=1.666610 lr=0.010000 Epoch[026] Batch [2199]/[3759] Speed: 76.569093 samples/sec accuracy=59.688920 loss=1.665680 lr=0.010000 Epoch[026] Batch [2249]/[3759] Speed: 74.070666 samples/sec accuracy=59.658333 loss=1.666785 lr=0.010000 Epoch[026] Batch [2299]/[3759] Speed: 77.230645 samples/sec accuracy=59.648098 loss=1.667230 lr=0.010000 Epoch[026] Batch [2349]/[3759] Speed: 77.016729 samples/sec accuracy=59.665559 loss=1.666258 lr=0.010000 Epoch[026] Batch [2399]/[3759] Speed: 74.127551 samples/sec accuracy=59.673828 loss=1.666471 lr=0.010000 Epoch[026] Batch [2449]/[3759] Speed: 75.789272 samples/sec accuracy=59.669005 loss=1.666575 lr=0.010000 Epoch[026] Batch [2499]/[3759] Speed: 75.668422 samples/sec accuracy=59.678125 loss=1.666615 lr=0.010000 Epoch[026] Batch [2549]/[3759] Speed: 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lr=0.010000 Epoch[026] Batch [3049]/[3759] Speed: 76.245204 samples/sec accuracy=59.523053 loss=1.673088 lr=0.010000 Epoch[026] Batch [3099]/[3759] Speed: 73.766452 samples/sec accuracy=59.535786 loss=1.672755 lr=0.010000 Epoch[026] Batch [3149]/[3759] Speed: 77.020647 samples/sec accuracy=59.511905 loss=1.673417 lr=0.010000 Epoch[026] Batch [3199]/[3759] Speed: 76.806892 samples/sec accuracy=59.525879 loss=1.673476 lr=0.010000 Epoch[026] Batch [3249]/[3759] Speed: 75.041622 samples/sec accuracy=59.505769 loss=1.674868 lr=0.010000 Epoch[026] Batch [3299]/[3759] Speed: 74.039323 samples/sec accuracy=59.502367 loss=1.675028 lr=0.010000 Epoch[026] Batch [3349]/[3759] Speed: 77.670638 samples/sec accuracy=59.517257 loss=1.674806 lr=0.010000 Epoch[026] Batch [3399]/[3759] Speed: 75.191122 samples/sec accuracy=59.496324 loss=1.675596 lr=0.010000 Epoch[026] Batch [3449]/[3759] Speed: 77.261346 samples/sec accuracy=59.486866 loss=1.675595 lr=0.010000 Epoch[026] Batch [3499]/[3759] Speed: 75.212543 samples/sec accuracy=59.497768 loss=1.675135 lr=0.010000 Epoch[026] Batch [3549]/[3759] Speed: 76.373261 samples/sec accuracy=59.500000 loss=1.674570 lr=0.010000 Epoch[026] Batch [3599]/[3759] Speed: 77.154624 samples/sec accuracy=59.484809 loss=1.674891 lr=0.010000 Epoch[026] Batch [3649]/[3759] Speed: 75.869853 samples/sec accuracy=59.503853 loss=1.674164 lr=0.010000 Epoch[026] Batch [3699]/[3759] Speed: 76.736155 samples/sec accuracy=59.499155 loss=1.674437 lr=0.010000 Epoch[026] Batch [3749]/[3759] Speed: 82.529927 samples/sec accuracy=59.489583 loss=1.675138 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.156250 acc-top5=80.500000 Batch [0099]/[0303]: acc-top1=57.703125 acc-top5=80.468750 Batch [0149]/[0303]: acc-top1=57.281250 acc-top5=80.656250 Batch [0199]/[0303]: acc-top1=57.679688 acc-top5=80.953125 Batch [0249]/[0303]: acc-top1=57.775000 acc-top5=80.862500 Batch [0299]/[0303]: acc-top1=57.744792 acc-top5=80.718750 [Epoch 026] training: accuracy=59.482658 loss=1.675362 [Epoch 026] speed: 75 samples/sec time cost: 3468.539749 [Epoch 026] validation: acc-top1=57.693894 acc-top5=80.703383 loss=1.938440 Epoch[027] Batch [0049]/[3760] Speed: 53.829465 samples/sec accuracy=60.875000 loss=1.615715 lr=0.010000 Epoch[027] Batch [0099]/[3760] Speed: 73.589405 samples/sec accuracy=60.968750 loss=1.612277 lr=0.010000 Epoch[027] Batch [0149]/[3760] Speed: 77.524271 samples/sec accuracy=61.322917 loss=1.596153 lr=0.010000 Epoch[027] Batch [0199]/[3760] Speed: 75.801300 samples/sec accuracy=61.093750 loss=1.599364 lr=0.010000 Epoch[027] Batch [0249]/[3760] Speed: 75.616668 samples/sec accuracy=61.093750 loss=1.604117 lr=0.010000 Epoch[027] Batch [0299]/[3760] Speed: 77.295249 samples/sec accuracy=60.921875 loss=1.621560 lr=0.010000 Epoch[027] Batch [0349]/[3760] Speed: 74.702879 samples/sec accuracy=60.955357 loss=1.620411 lr=0.010000 Epoch[027] Batch [0399]/[3760] Speed: 76.663758 samples/sec accuracy=60.832031 loss=1.622777 lr=0.010000 Epoch[027] Batch 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accuracy=59.612500 loss=1.671809 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.468750 acc-top5=81.468750 Batch [0099]/[0303]: acc-top1=59.171875 acc-top5=81.343750 Batch [0149]/[0303]: acc-top1=58.604167 acc-top5=81.302083 Batch [0199]/[0303]: acc-top1=58.687500 acc-top5=81.453125 Batch [0249]/[0303]: acc-top1=58.456250 acc-top5=81.556250 Batch [0299]/[0303]: acc-top1=58.421875 acc-top5=81.510417 [Epoch 027] training: accuracy=59.605219 loss=1.671844 [Epoch 027] speed: 75 samples/sec time cost: 3454.872159 [Epoch 027] validation: acc-top1=58.415842 acc-top5=81.549092 loss=1.931340 Epoch[028] Batch [0049]/[3760] Speed: 53.734152 samples/sec accuracy=60.625000 loss=1.656375 lr=0.010000 Epoch[028] Batch [0099]/[3760] Speed: 72.627176 samples/sec accuracy=60.218750 loss=1.641109 lr=0.010000 Epoch[028] Batch [0149]/[3760] Speed: 77.389710 samples/sec accuracy=59.802083 loss=1.650948 lr=0.010000 Epoch[028] Batch [0199]/[3760] Speed: 77.193351 samples/sec accuracy=60.187500 loss=1.642496 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lr=0.010000 Epoch[028] Batch [3099]/[3760] Speed: 75.121699 samples/sec accuracy=59.847782 loss=1.655842 lr=0.010000 Epoch[028] Batch [3149]/[3760] Speed: 74.680064 samples/sec accuracy=59.856151 loss=1.656245 lr=0.010000 Epoch[028] Batch [3199]/[3760] Speed: 77.606129 samples/sec accuracy=59.845215 loss=1.656162 lr=0.010000 Epoch[028] Batch [3249]/[3760] Speed: 71.465689 samples/sec accuracy=59.843750 loss=1.656520 lr=0.010000 Epoch[028] Batch [3299]/[3760] Speed: 77.978073 samples/sec accuracy=59.850852 loss=1.655662 lr=0.010000 Epoch[028] Batch [3349]/[3760] Speed: 76.579845 samples/sec accuracy=59.838153 loss=1.655992 lr=0.010000 Epoch[028] Batch [3399]/[3760] Speed: 76.955123 samples/sec accuracy=59.827665 loss=1.656366 lr=0.010000 Epoch[028] Batch [3449]/[3760] Speed: 75.131924 samples/sec accuracy=59.831975 loss=1.656735 lr=0.010000 Epoch[028] Batch [3499]/[3760] Speed: 74.935798 samples/sec accuracy=59.816964 loss=1.657287 lr=0.010000 Epoch[028] Batch [3549]/[3760] Speed: 76.615105 samples/sec accuracy=59.797095 loss=1.658065 lr=0.010000 Epoch[028] Batch [3599]/[3760] Speed: 75.767076 samples/sec accuracy=59.788628 loss=1.658605 lr=0.010000 Epoch[028] Batch [3649]/[3760] Speed: 75.712340 samples/sec accuracy=59.797945 loss=1.658739 lr=0.010000 Epoch[028] Batch [3699]/[3760] Speed: 73.647279 samples/sec accuracy=59.770693 loss=1.660073 lr=0.010000 Epoch[028] Batch [3749]/[3760] Speed: 85.545800 samples/sec accuracy=59.768333 loss=1.660794 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.781250 acc-top5=81.312500 Batch [0099]/[0303]: acc-top1=58.203125 acc-top5=81.109375 Batch [0149]/[0303]: acc-top1=57.906250 acc-top5=81.250000 Batch [0199]/[0303]: acc-top1=58.054688 acc-top5=81.148438 Batch [0249]/[0303]: acc-top1=58.150000 acc-top5=81.106250 Batch [0299]/[0303]: acc-top1=57.932292 acc-top5=81.010417 [Epoch 028] training: accuracy=59.766456 loss=1.661179 [Epoch 028] speed: 75 samples/sec time cost: 3464.878999 [Epoch 028] validation: acc-top1=57.900165 acc-top5=81.012789 loss=1.966595 Epoch[029] Batch [0049]/[3759] Speed: 53.866061 samples/sec accuracy=60.500000 loss=1.627935 lr=0.010000 Epoch[029] Batch [0099]/[3759] Speed: 72.096549 samples/sec accuracy=60.718750 loss=1.603309 lr=0.010000 Epoch[029] Batch [0149]/[3759] Speed: 75.745465 samples/sec accuracy=60.895833 loss=1.597538 lr=0.010000 Epoch[029] Batch [0199]/[3759] Speed: 76.643979 samples/sec accuracy=60.648438 loss=1.615152 lr=0.010000 Epoch[029] Batch [0249]/[3759] Speed: 73.656780 samples/sec accuracy=60.812500 loss=1.611770 lr=0.010000 Epoch[029] Batch [0299]/[3759] Speed: 75.819280 samples/sec accuracy=60.770833 loss=1.617117 lr=0.010000 Epoch[029] Batch [0349]/[3759] Speed: 76.396494 samples/sec accuracy=60.950893 loss=1.612213 lr=0.010000 Epoch[029] Batch [0399]/[3759] Speed: 76.014681 samples/sec accuracy=60.988281 loss=1.612110 lr=0.010000 Epoch[029] Batch [0449]/[3759] Speed: 75.413783 samples/sec accuracy=60.850694 loss=1.613091 lr=0.010000 Epoch[029] Batch 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accuracy=60.076754 loss=1.650801 lr=0.010000 Epoch[029] Batch [2899]/[3759] Speed: 75.307945 samples/sec accuracy=60.097522 loss=1.650102 lr=0.010000 Epoch[029] Batch [2949]/[3759] Speed: 75.822179 samples/sec accuracy=60.077860 loss=1.651096 lr=0.010000 Epoch[029] Batch [2999]/[3759] Speed: 77.189747 samples/sec accuracy=60.067708 loss=1.651678 lr=0.010000 Epoch[029] Batch [3049]/[3759] Speed: 76.222301 samples/sec accuracy=60.072746 loss=1.651675 lr=0.010000 Epoch[029] Batch [3099]/[3759] Speed: 74.428466 samples/sec accuracy=60.066532 loss=1.652190 lr=0.010000 Epoch[029] Batch [3149]/[3759] Speed: 75.994332 samples/sec accuracy=60.071925 loss=1.651978 lr=0.010000 Epoch[029] Batch [3199]/[3759] Speed: 75.319179 samples/sec accuracy=60.054688 loss=1.652409 lr=0.010000 Epoch[029] Batch [3249]/[3759] Speed: 76.431422 samples/sec accuracy=60.030769 loss=1.652945 lr=0.010000 Epoch[029] Batch [3299]/[3759] Speed: 77.236877 samples/sec accuracy=60.024148 loss=1.653382 lr=0.010000 Epoch[029] 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[0099]/[0303]: acc-top1=57.640625 acc-top5=80.734375 Batch [0149]/[0303]: acc-top1=57.239583 acc-top5=80.979167 Batch [0199]/[0303]: acc-top1=57.507812 acc-top5=81.078125 Batch [0249]/[0303]: acc-top1=57.662500 acc-top5=81.112500 Batch [0299]/[0303]: acc-top1=57.635417 acc-top5=80.968750 [Epoch 029] training: accuracy=59.991437 loss=1.655169 [Epoch 029] speed: 75 samples/sec time cost: 3461.993841 [Epoch 029] validation: acc-top1=57.585602 acc-top5=80.940594 loss=1.937939 Epoch[030] Batch [0049]/[3760] Speed: 53.316741 samples/sec accuracy=60.437500 loss=1.606881 lr=0.010000 Epoch[030] Batch [0099]/[3760] Speed: 72.075792 samples/sec accuracy=61.171875 loss=1.592164 lr=0.010000 Epoch[030] Batch [0149]/[3760] Speed: 77.749883 samples/sec accuracy=60.906250 loss=1.600671 lr=0.010000 Epoch[030] Batch [0199]/[3760] Speed: 74.970735 samples/sec accuracy=60.710937 loss=1.614228 lr=0.010000 Epoch[030] Batch [0249]/[3760] Speed: 76.595783 samples/sec accuracy=60.781250 loss=1.609739 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lr=0.010000 Epoch[030] Batch [2199]/[3760] Speed: 75.442830 samples/sec accuracy=60.242898 loss=1.644518 lr=0.010000 Epoch[030] Batch [2249]/[3760] Speed: 76.980993 samples/sec accuracy=60.250694 loss=1.644539 lr=0.010000 Epoch[030] Batch [2299]/[3760] Speed: 75.976922 samples/sec accuracy=60.262908 loss=1.644844 lr=0.010000 Epoch[030] Batch [2349]/[3760] Speed: 75.224070 samples/sec accuracy=60.250665 loss=1.645095 lr=0.010000 Epoch[030] Batch [2399]/[3760] Speed: 76.064285 samples/sec accuracy=60.231771 loss=1.645434 lr=0.010000 Epoch[030] Batch [2449]/[3760] Speed: 77.144214 samples/sec accuracy=60.230867 loss=1.644728 lr=0.010000 Epoch[030] Batch [2499]/[3760] Speed: 75.835894 samples/sec accuracy=60.230625 loss=1.645270 lr=0.010000 Epoch[030] Batch [2549]/[3760] Speed: 76.127507 samples/sec accuracy=60.225490 loss=1.646186 lr=0.010000 Epoch[030] Batch [2599]/[3760] Speed: 76.088331 samples/sec accuracy=60.210337 loss=1.647169 lr=0.010000 Epoch[030] Batch [2649]/[3760] Speed: 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lr=0.010000 Epoch[030] Batch [3149]/[3760] Speed: 77.396148 samples/sec accuracy=60.093254 loss=1.650519 lr=0.010000 Epoch[030] Batch [3199]/[3760] Speed: 74.151964 samples/sec accuracy=60.080078 loss=1.650648 lr=0.010000 Epoch[030] Batch [3249]/[3760] Speed: 76.514204 samples/sec accuracy=60.071635 loss=1.651391 lr=0.010000 Epoch[030] Batch [3299]/[3760] Speed: 76.214093 samples/sec accuracy=60.053977 loss=1.652038 lr=0.010000 Epoch[030] Batch [3349]/[3760] Speed: 73.549564 samples/sec accuracy=60.058302 loss=1.652555 lr=0.010000 Epoch[030] Batch [3399]/[3760] Speed: 79.675022 samples/sec accuracy=60.062500 loss=1.652890 lr=0.010000 Epoch[030] Batch [3449]/[3760] Speed: 75.508369 samples/sec accuracy=60.065217 loss=1.653055 lr=0.010000 Epoch[030] Batch [3499]/[3760] Speed: 75.378123 samples/sec accuracy=60.061161 loss=1.653124 lr=0.010000 Epoch[030] Batch [3549]/[3760] Speed: 75.352004 samples/sec accuracy=60.041813 loss=1.653682 lr=0.010000 Epoch[030] Batch [3599]/[3760] Speed: 77.496202 samples/sec accuracy=60.051215 loss=1.653514 lr=0.010000 Epoch[030] Batch [3649]/[3760] Speed: 73.987736 samples/sec accuracy=60.041096 loss=1.654039 lr=0.010000 Epoch[030] Batch [3699]/[3760] Speed: 76.971203 samples/sec accuracy=60.024493 loss=1.654802 lr=0.010000 Epoch[030] Batch [3749]/[3760] Speed: 84.445211 samples/sec accuracy=60.023750 loss=1.654812 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.093750 acc-top5=80.156250 Batch [0099]/[0303]: acc-top1=57.671875 acc-top5=80.625000 Batch [0149]/[0303]: acc-top1=57.677083 acc-top5=80.656250 Batch [0199]/[0303]: acc-top1=57.906250 acc-top5=80.921875 Batch [0249]/[0303]: acc-top1=58.075000 acc-top5=81.068750 Batch [0299]/[0303]: acc-top1=57.937500 acc-top5=80.947917 [Epoch 030] training: accuracy=60.029505 loss=1.654710 [Epoch 030] speed: 75 samples/sec time cost: 3460.938205 [Epoch 030] validation: acc-top1=57.910479 acc-top5=80.976691 loss=1.949307 Epoch[031] Batch [0049]/[3760] Speed: 52.628992 samples/sec accuracy=60.906250 loss=1.602113 lr=0.010000 Epoch[031] Batch [0099]/[3760] Speed: 72.290155 samples/sec accuracy=60.781250 loss=1.604395 lr=0.010000 Epoch[031] Batch [0149]/[3760] Speed: 78.526400 samples/sec accuracy=60.812500 loss=1.611433 lr=0.010000 Epoch[031] Batch [0199]/[3760] Speed: 76.663994 samples/sec accuracy=60.296875 loss=1.634505 lr=0.010000 Epoch[031] Batch [0249]/[3760] Speed: 73.992552 samples/sec accuracy=60.375000 loss=1.633914 lr=0.010000 Epoch[031] Batch [0299]/[3760] Speed: 76.835842 samples/sec accuracy=60.572917 loss=1.620801 lr=0.010000 Epoch[031] Batch [0349]/[3760] Speed: 74.331328 samples/sec accuracy=60.575893 loss=1.622515 lr=0.010000 Epoch[031] Batch [0399]/[3760] Speed: 76.367554 samples/sec accuracy=60.511719 loss=1.626775 lr=0.010000 Epoch[031] Batch [0449]/[3760] Speed: 76.577826 samples/sec accuracy=60.531250 loss=1.626574 lr=0.010000 Epoch[031] Batch [0499]/[3760] Speed: 74.128523 samples/sec accuracy=60.453125 loss=1.627517 lr=0.010000 Epoch[031] 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acc-top5=81.052083 Batch [0199]/[0303]: acc-top1=57.765625 acc-top5=81.289062 Batch [0249]/[0303]: acc-top1=57.731250 acc-top5=81.237500 Batch [0299]/[0303]: acc-top1=57.916667 acc-top5=81.114583 [Epoch 031] training: accuracy=59.982962 loss=1.650378 [Epoch 031] speed: 75 samples/sec time cost: 3470.002281 [Epoch 031] validation: acc-top1=57.879538 acc-top5=81.141708 loss=1.894596 Epoch[032] Batch [0049]/[3759] Speed: 54.950312 samples/sec accuracy=61.031250 loss=1.608353 lr=0.010000 Epoch[032] Batch [0099]/[3759] Speed: 72.081373 samples/sec accuracy=61.156250 loss=1.597151 lr=0.010000 Epoch[032] Batch [0149]/[3759] Speed: 77.080103 samples/sec accuracy=61.145833 loss=1.610258 lr=0.010000 Epoch[032] Batch [0199]/[3759] Speed: 74.566883 samples/sec accuracy=61.273438 loss=1.601552 lr=0.010000 Epoch[032] Batch [0249]/[3759] Speed: 76.056329 samples/sec accuracy=61.400000 loss=1.598034 lr=0.010000 Epoch[032] Batch [0299]/[3759] Speed: 76.894193 samples/sec accuracy=60.958333 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accuracy=60.313920 loss=1.633764 lr=0.010000 Epoch[032] Batch [2249]/[3759] Speed: 74.463468 samples/sec accuracy=60.294444 loss=1.634336 lr=0.010000 Epoch[032] Batch [2299]/[3759] Speed: 77.194577 samples/sec accuracy=60.264266 loss=1.635457 lr=0.010000 Epoch[032] Batch [2349]/[3759] Speed: 75.017568 samples/sec accuracy=60.247340 loss=1.636092 lr=0.010000 Epoch[032] Batch [2399]/[3759] Speed: 76.492091 samples/sec accuracy=60.291016 loss=1.634851 lr=0.010000 Epoch[032] Batch [2449]/[3759] Speed: 75.966856 samples/sec accuracy=60.290179 loss=1.634654 lr=0.010000 Epoch[032] Batch [2499]/[3759] Speed: 74.191129 samples/sec accuracy=60.278125 loss=1.634912 lr=0.010000 Epoch[032] Batch [2549]/[3759] Speed: 76.817956 samples/sec accuracy=60.222426 loss=1.636743 lr=0.010000 Epoch[032] Batch [2599]/[3759] Speed: 73.485699 samples/sec accuracy=60.216947 loss=1.637180 lr=0.010000 Epoch[032] Batch [2649]/[3759] Speed: 76.198490 samples/sec accuracy=60.224646 loss=1.636913 lr=0.010000 Epoch[032] 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accuracy=60.165179 loss=1.641641 lr=0.010000 Epoch[032] Batch [3199]/[3759] Speed: 76.227264 samples/sec accuracy=60.162109 loss=1.642337 lr=0.010000 Epoch[032] Batch [3249]/[3759] Speed: 76.516208 samples/sec accuracy=60.166346 loss=1.642746 lr=0.010000 Epoch[032] Batch [3299]/[3759] Speed: 76.661344 samples/sec accuracy=60.165246 loss=1.642954 lr=0.010000 Epoch[032] Batch [3349]/[3759] Speed: 75.053214 samples/sec accuracy=60.174440 loss=1.642657 lr=0.010000 Epoch[032] Batch [3399]/[3759] Speed: 75.581053 samples/sec accuracy=60.160386 loss=1.643349 lr=0.010000 Epoch[032] Batch [3449]/[3759] Speed: 77.478581 samples/sec accuracy=60.159420 loss=1.644570 lr=0.010000 Epoch[032] Batch [3499]/[3759] Speed: 74.862851 samples/sec accuracy=60.184821 loss=1.644113 lr=0.010000 Epoch[032] Batch [3549]/[3759] Speed: 76.632583 samples/sec accuracy=60.180458 loss=1.644291 lr=0.010000 Epoch[032] Batch [3599]/[3759] Speed: 73.012132 samples/sec accuracy=60.164497 loss=1.644568 lr=0.010000 Epoch[032] Batch [3649]/[3759] Speed: 75.867845 samples/sec accuracy=60.171661 loss=1.644454 lr=0.010000 Epoch[032] Batch [3699]/[3759] Speed: 78.595423 samples/sec accuracy=60.177365 loss=1.644217 lr=0.010000 Epoch[032] Batch [3749]/[3759] Speed: 84.148884 samples/sec accuracy=60.167917 loss=1.644464 lr=0.010000 Batch [0049]/[0303]: acc-top1=56.875000 acc-top5=81.000000 Batch [0099]/[0303]: acc-top1=57.906250 acc-top5=81.109375 Batch [0149]/[0303]: acc-top1=57.520833 acc-top5=81.145833 Batch [0199]/[0303]: acc-top1=57.898438 acc-top5=81.398438 Batch [0249]/[0303]: acc-top1=57.900000 acc-top5=81.412500 Batch [0299]/[0303]: acc-top1=57.796875 acc-top5=81.166667 [Epoch 032] training: accuracy=60.166434 loss=1.644513 [Epoch 032] speed: 75 samples/sec time cost: 3464.720004 [Epoch 032] validation: acc-top1=57.709365 acc-top5=81.203589 loss=1.925272 Epoch[033] Batch [0049]/[3760] Speed: 52.699749 samples/sec accuracy=61.687500 loss=1.578822 lr=0.010000 Epoch[033] Batch [0099]/[3760] Speed: 72.678342 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[0249]/[0303]: acc-top1=58.331250 acc-top5=81.493750 Batch [0299]/[0303]: acc-top1=58.244792 acc-top5=81.343750 [Epoch 033] training: accuracy=60.372756 loss=1.636431 [Epoch 033] speed: 75 samples/sec time cost: 3464.224380 [Epoch 033] validation: acc-top1=58.194101 acc-top5=81.373762 loss=1.930493 Epoch[034] Batch [0049]/[3759] Speed: 53.845650 samples/sec accuracy=60.343750 loss=1.626112 lr=0.010000 Epoch[034] Batch [0099]/[3759] Speed: 71.883080 samples/sec accuracy=60.437500 loss=1.594701 lr=0.010000 Epoch[034] Batch [0149]/[3759] Speed: 78.466571 samples/sec accuracy=60.781250 loss=1.605726 lr=0.010000 Epoch[034] Batch [0199]/[3759] Speed: 75.729475 samples/sec accuracy=60.687500 loss=1.613381 lr=0.010000 Epoch[034] Batch [0249]/[3759] Speed: 74.676542 samples/sec accuracy=61.175000 loss=1.597910 lr=0.010000 Epoch[034] Batch [0299]/[3759] Speed: 76.406625 samples/sec accuracy=60.947917 loss=1.599778 lr=0.010000 Epoch[034] Batch [0349]/[3759] Speed: 72.264772 samples/sec 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accuracy=60.721154 loss=1.611471 lr=0.010000 Epoch[034] Batch [1349]/[3759] Speed: 76.504713 samples/sec accuracy=60.699074 loss=1.613941 lr=0.010000 Epoch[034] Batch [1399]/[3759] Speed: 74.546217 samples/sec accuracy=60.680804 loss=1.615670 lr=0.010000 Epoch[034] Batch [1449]/[3759] Speed: 76.895802 samples/sec accuracy=60.671336 loss=1.617075 lr=0.010000 Epoch[034] Batch [1499]/[3759] Speed: 75.577931 samples/sec accuracy=60.657292 loss=1.619083 lr=0.010000 Epoch[034] Batch [1549]/[3759] Speed: 71.266916 samples/sec accuracy=60.660282 loss=1.619198 lr=0.010000 Epoch[034] Batch [1599]/[3759] Speed: 79.943183 samples/sec accuracy=60.652344 loss=1.618989 lr=0.010000 Epoch[034] Batch [1649]/[3759] Speed: 73.965471 samples/sec accuracy=60.618371 loss=1.620426 lr=0.010000 Epoch[034] Batch [1699]/[3759] Speed: 74.606832 samples/sec accuracy=60.634191 loss=1.621648 lr=0.010000 Epoch[034] Batch [1749]/[3759] Speed: 78.307340 samples/sec accuracy=60.622321 loss=1.621088 lr=0.010000 Epoch[034] 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accuracy=60.575694 loss=1.627113 lr=0.010000 Epoch[034] Batch [2299]/[3759] Speed: 75.932743 samples/sec accuracy=60.569293 loss=1.627411 lr=0.010000 Epoch[034] Batch [2349]/[3759] Speed: 75.578132 samples/sec accuracy=60.568484 loss=1.628008 lr=0.010000 Epoch[034] Batch [2399]/[3759] Speed: 74.808699 samples/sec accuracy=60.571615 loss=1.627803 lr=0.010000 Epoch[034] Batch [2449]/[3759] Speed: 76.946611 samples/sec accuracy=60.551658 loss=1.629330 lr=0.010000 Epoch[034] Batch [2499]/[3759] Speed: 75.384252 samples/sec accuracy=60.543125 loss=1.629971 lr=0.010000 Epoch[034] Batch [2549]/[3759] Speed: 76.012559 samples/sec accuracy=60.537377 loss=1.629869 lr=0.010000 Epoch[034] Batch [2599]/[3759] Speed: 76.111849 samples/sec accuracy=60.528846 loss=1.629814 lr=0.010000 Epoch[034] Batch [2649]/[3759] Speed: 74.271553 samples/sec accuracy=60.500000 loss=1.631634 lr=0.010000 Epoch[034] Batch [2699]/[3759] Speed: 76.706854 samples/sec accuracy=60.484954 loss=1.632456 lr=0.010000 Epoch[034] 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accuracy=60.403809 loss=1.635047 lr=0.010000 Epoch[034] Batch [3249]/[3759] Speed: 76.552890 samples/sec accuracy=60.414423 loss=1.634901 lr=0.010000 Epoch[034] Batch [3299]/[3759] Speed: 74.201856 samples/sec accuracy=60.417614 loss=1.635126 lr=0.010000 Epoch[034] Batch [3349]/[3759] Speed: 76.431240 samples/sec accuracy=60.409049 loss=1.635806 lr=0.010000 Epoch[034] Batch [3399]/[3759] Speed: 74.651029 samples/sec accuracy=60.412224 loss=1.635504 lr=0.010000 Epoch[034] Batch [3449]/[3759] Speed: 76.918908 samples/sec accuracy=60.383605 loss=1.636202 lr=0.010000 Epoch[034] Batch [3499]/[3759] Speed: 73.954306 samples/sec accuracy=60.361607 loss=1.636757 lr=0.010000 Epoch[034] Batch [3549]/[3759] Speed: 76.797142 samples/sec accuracy=60.370599 loss=1.636765 lr=0.010000 Epoch[034] Batch [3599]/[3759] Speed: 73.983449 samples/sec accuracy=60.345052 loss=1.637911 lr=0.010000 Epoch[034] Batch [3649]/[3759] Speed: 76.720805 samples/sec accuracy=60.337757 loss=1.638241 lr=0.010000 Epoch[034] Batch [3699]/[3759] Speed: 74.726508 samples/sec accuracy=60.319679 loss=1.639123 lr=0.010000 Epoch[034] Batch [3749]/[3759] Speed: 85.343546 samples/sec accuracy=60.320000 loss=1.639619 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.312500 acc-top5=80.437500 Batch [0099]/[0303]: acc-top1=58.000000 acc-top5=80.718750 Batch [0149]/[0303]: acc-top1=57.552083 acc-top5=80.770833 Batch [0199]/[0303]: acc-top1=57.664062 acc-top5=80.859375 Batch [0249]/[0303]: acc-top1=57.500000 acc-top5=80.887500 Batch [0299]/[0303]: acc-top1=57.484375 acc-top5=80.765625 [Epoch 034] training: accuracy=60.320647 loss=1.639808 [Epoch 034] speed: 75 samples/sec time cost: 3469.725337 [Epoch 034] validation: acc-top1=57.456683 acc-top5=80.760107 loss=1.967258 Epoch[035] Batch [0049]/[3760] Speed: 53.406564 samples/sec accuracy=60.281250 loss=1.639405 lr=0.010000 Epoch[035] Batch [0099]/[3760] Speed: 73.079281 samples/sec accuracy=61.609375 loss=1.607813 lr=0.010000 Epoch[035] Batch [0149]/[3760] Speed: 75.402904 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lr=0.010000 Epoch[035] Batch [3499]/[3760] Speed: 73.380209 samples/sec accuracy=60.538839 loss=1.628261 lr=0.010000 Epoch[035] Batch [3549]/[3760] Speed: 76.856158 samples/sec accuracy=60.536532 loss=1.628274 lr=0.010000 Epoch[035] Batch [3599]/[3760] Speed: 75.521641 samples/sec accuracy=60.516493 loss=1.629290 lr=0.010000 Epoch[035] Batch [3649]/[3760] Speed: 75.679978 samples/sec accuracy=60.525257 loss=1.628822 lr=0.010000 Epoch[035] Batch [3699]/[3760] Speed: 75.197419 samples/sec accuracy=60.516470 loss=1.628828 lr=0.010000 Epoch[035] Batch [3749]/[3760] Speed: 83.647942 samples/sec accuracy=60.517917 loss=1.628845 lr=0.010000 Batch [0049]/[0303]: acc-top1=57.875000 acc-top5=81.906250 Batch [0099]/[0303]: acc-top1=58.921875 acc-top5=81.625000 Batch [0149]/[0303]: acc-top1=58.500000 acc-top5=81.833333 Batch [0199]/[0303]: acc-top1=58.523438 acc-top5=81.828125 Batch [0249]/[0303]: acc-top1=58.531250 acc-top5=81.762500 Batch [0299]/[0303]: acc-top1=58.546875 acc-top5=81.578125 [Epoch 035] training: accuracy=60.514046 loss=1.629083 [Epoch 035] speed: 75 samples/sec time cost: 3465.595838 [Epoch 035] validation: acc-top1=58.493193 acc-top5=81.605817 loss=1.923796 Epoch[036] Batch [0049]/[3760] Speed: 54.481775 samples/sec accuracy=60.187500 loss=1.637048 lr=0.010000 Epoch[036] Batch [0099]/[3760] Speed: 72.360919 samples/sec accuracy=61.656250 loss=1.583728 lr=0.010000 Epoch[036] Batch [0149]/[3760] Speed: 77.911248 samples/sec accuracy=61.697917 loss=1.571942 lr=0.010000 Epoch[036] Batch [0199]/[3760] Speed: 75.454127 samples/sec accuracy=61.273438 loss=1.584906 lr=0.010000 Epoch[036] Batch [0249]/[3760] Speed: 75.177650 samples/sec accuracy=61.475000 loss=1.578159 lr=0.010000 Epoch[036] Batch [0299]/[3760] Speed: 77.738391 samples/sec accuracy=61.473958 loss=1.583379 lr=0.010000 Epoch[036] Batch [0349]/[3760] Speed: 72.635817 samples/sec accuracy=61.584821 loss=1.576812 lr=0.010000 Epoch[036] Batch [0399]/[3760] Speed: 77.115460 samples/sec accuracy=61.390625 loss=1.583851 lr=0.010000 Epoch[036] Batch [0449]/[3760] Speed: 75.633901 samples/sec accuracy=61.402778 loss=1.587668 lr=0.010000 Epoch[036] Batch [0499]/[3760] Speed: 75.480432 samples/sec accuracy=61.431250 loss=1.586486 lr=0.010000 Epoch[036] Batch [0549]/[3760] Speed: 76.309449 samples/sec accuracy=61.392045 loss=1.590051 lr=0.010000 Epoch[036] Batch [0599]/[3760] Speed: 75.825132 samples/sec accuracy=61.403646 loss=1.588154 lr=0.010000 Epoch[036] Batch [0649]/[3760] Speed: 75.643424 samples/sec accuracy=61.396635 loss=1.587087 lr=0.010000 Epoch[036] Batch [0699]/[3760] Speed: 75.145579 samples/sec accuracy=61.270089 loss=1.591924 lr=0.010000 Epoch[036] Batch [0749]/[3760] Speed: 77.603506 samples/sec accuracy=61.116667 loss=1.599693 lr=0.010000 Epoch[036] Batch [0799]/[3760] Speed: 73.563365 samples/sec accuracy=61.130859 loss=1.598412 lr=0.010000 Epoch[036] Batch [0849]/[3760] Speed: 77.436142 samples/sec accuracy=61.079044 loss=1.598349 lr=0.010000 Epoch[036] 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accuracy=60.994213 loss=1.604712 lr=0.010000 Epoch[036] Batch [1399]/[3760] Speed: 73.042641 samples/sec accuracy=60.986607 loss=1.605946 lr=0.010000 Epoch[036] Batch [1449]/[3760] Speed: 76.880029 samples/sec accuracy=60.948276 loss=1.607027 lr=0.010000 Epoch[036] Batch [1499]/[3760] Speed: 74.404244 samples/sec accuracy=60.908333 loss=1.608270 lr=0.010000 Epoch[036] Batch [1549]/[3760] Speed: 77.374774 samples/sec accuracy=60.870968 loss=1.609899 lr=0.010000 Epoch[036] Batch [1599]/[3760] Speed: 77.372462 samples/sec accuracy=60.864258 loss=1.610285 lr=0.010000 Epoch[036] Batch [1649]/[3760] Speed: 73.143766 samples/sec accuracy=60.855114 loss=1.611041 lr=0.010000 Epoch[036] Batch [1699]/[3760] Speed: 77.415931 samples/sec accuracy=60.886949 loss=1.610328 lr=0.010000 Epoch[036] Batch [1749]/[3760] Speed: 75.468699 samples/sec accuracy=60.844643 loss=1.612120 lr=0.010000 Epoch[036] Batch [1799]/[3760] Speed: 76.784771 samples/sec accuracy=60.856771 loss=1.613266 lr=0.010000 Epoch[036] 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accuracy=60.855978 loss=1.615806 lr=0.010000 Epoch[036] Batch [2349]/[3760] Speed: 76.639054 samples/sec accuracy=60.884309 loss=1.615236 lr=0.010000 Epoch[036] Batch [2399]/[3760] Speed: 73.870151 samples/sec accuracy=60.895182 loss=1.615215 lr=0.010000 Epoch[036] Batch [2449]/[3760] Speed: 77.847338 samples/sec accuracy=60.850765 loss=1.616167 lr=0.010000 Epoch[036] Batch [2499]/[3760] Speed: 75.857265 samples/sec accuracy=60.840625 loss=1.616889 lr=0.010000 Epoch[036] Batch [2549]/[3760] Speed: 76.883691 samples/sec accuracy=60.841912 loss=1.616088 lr=0.010000 Epoch[036] Batch [2599]/[3760] Speed: 75.365042 samples/sec accuracy=60.822716 loss=1.617037 lr=0.010000 Epoch[036] Batch [2649]/[3760] Speed: 76.978259 samples/sec accuracy=60.808373 loss=1.617425 lr=0.010000 Epoch[036] Batch [2699]/[3760] Speed: 75.892260 samples/sec accuracy=60.815972 loss=1.617557 lr=0.010000 Epoch[036] Batch [2749]/[3760] Speed: 75.089655 samples/sec accuracy=60.778409 loss=1.619196 lr=0.010000 Epoch[036] 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accuracy=60.692788 loss=1.623618 lr=0.010000 Epoch[036] Batch [3299]/[3760] Speed: 74.328870 samples/sec accuracy=60.690814 loss=1.624075 lr=0.010000 Epoch[036] Batch [3349]/[3760] Speed: 77.516596 samples/sec accuracy=60.683302 loss=1.624530 lr=0.010000 Epoch[036] Batch [3399]/[3760] Speed: 76.157875 samples/sec accuracy=60.683824 loss=1.624236 lr=0.010000 Epoch[036] Batch [3449]/[3760] Speed: 75.432729 samples/sec accuracy=60.658967 loss=1.626126 lr=0.010000 Epoch[036] Batch [3499]/[3760] Speed: 76.319806 samples/sec accuracy=60.621429 loss=1.627478 lr=0.010000 Epoch[036] Batch [3549]/[3760] Speed: 74.988115 samples/sec accuracy=60.591549 loss=1.628482 lr=0.010000 Epoch[036] Batch [3599]/[3760] Speed: 74.303950 samples/sec accuracy=60.592448 loss=1.628174 lr=0.010000 Epoch[036] Batch [3649]/[3760] Speed: 75.750790 samples/sec accuracy=60.589041 loss=1.628566 lr=0.010000 Epoch[036] Batch [3699]/[3760] Speed: 76.525037 samples/sec accuracy=60.587416 loss=1.628364 lr=0.010000 Epoch[036] Batch [3749]/[3760] Speed: 84.295053 samples/sec accuracy=60.588333 loss=1.628342 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.593750 acc-top5=80.843750 Batch [0099]/[0303]: acc-top1=58.890625 acc-top5=80.625000 Batch [0149]/[0303]: acc-top1=58.229167 acc-top5=81.000000 Batch [0199]/[0303]: acc-top1=58.242188 acc-top5=81.289062 Batch [0249]/[0303]: acc-top1=58.268750 acc-top5=81.056250 Batch [0299]/[0303]: acc-top1=58.265625 acc-top5=80.838542 [Epoch 036] training: accuracy=60.579704 loss=1.628576 [Epoch 036] speed: 75 samples/sec time cost: 3459.413242 [Epoch 036] validation: acc-top1=58.204414 acc-top5=80.806518 loss=1.955117 Epoch[037] Batch [0049]/[3759] Speed: 50.596234 samples/sec accuracy=61.718750 loss=1.608035 lr=0.010000 Epoch[037] Batch [0099]/[3759] Speed: 76.129829 samples/sec accuracy=61.578125 loss=1.593278 lr=0.010000 Epoch[037] Batch [0149]/[3759] Speed: 78.116374 samples/sec accuracy=61.385417 loss=1.609733 lr=0.010000 Epoch[037] Batch [0199]/[3759] Speed: 72.242502 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lr=0.010000 Epoch[037] Batch [3549]/[3759] Speed: 71.931731 samples/sec accuracy=60.633803 loss=1.624568 lr=0.010000 Epoch[037] Batch [3599]/[3759] Speed: 78.566085 samples/sec accuracy=60.632378 loss=1.624241 lr=0.010000 Epoch[037] Batch [3649]/[3759] Speed: 74.630940 samples/sec accuracy=60.616866 loss=1.624998 lr=0.010000 Epoch[037] Batch [3699]/[3759] Speed: 76.596565 samples/sec accuracy=60.619510 loss=1.624995 lr=0.010000 Epoch[037] Batch [3749]/[3759] Speed: 86.067788 samples/sec accuracy=60.608333 loss=1.624939 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.312500 acc-top5=81.656250 Batch [0099]/[0303]: acc-top1=58.140625 acc-top5=81.281250 Batch [0149]/[0303]: acc-top1=57.854167 acc-top5=81.177083 Batch [0199]/[0303]: acc-top1=58.328125 acc-top5=81.367188 Batch [0249]/[0303]: acc-top1=58.431250 acc-top5=81.412500 Batch [0299]/[0303]: acc-top1=58.343750 acc-top5=81.203125 [Epoch 037] training: accuracy=60.609953 loss=1.624918 [Epoch 037] speed: 75 samples/sec time cost: 3470.189164 [Epoch 037] validation: acc-top1=58.333333 acc-top5=81.239686 loss=1.912936 Epoch[038] Batch [0049]/[3760] Speed: 53.477388 samples/sec accuracy=61.312500 loss=1.577292 lr=0.010000 Epoch[038] Batch [0099]/[3760] Speed: 70.984599 samples/sec accuracy=61.718750 loss=1.564744 lr=0.010000 Epoch[038] Batch [0149]/[3760] Speed: 77.979114 samples/sec accuracy=61.604167 loss=1.573263 lr=0.010000 Epoch[038] Batch [0199]/[3760] Speed: 75.932582 samples/sec accuracy=61.148438 loss=1.590396 lr=0.010000 Epoch[038] Batch [0249]/[3760] Speed: 74.561254 samples/sec accuracy=61.168750 loss=1.596031 lr=0.010000 Epoch[038] Batch [0299]/[3760] Speed: 77.381804 samples/sec accuracy=61.177083 loss=1.594578 lr=0.010000 Epoch[038] Batch [0349]/[3760] Speed: 76.786014 samples/sec accuracy=61.116071 loss=1.599612 lr=0.010000 Epoch[038] Batch [0399]/[3760] Speed: 73.366493 samples/sec accuracy=61.078125 loss=1.597115 lr=0.010000 Epoch[038] Batch [0449]/[3760] Speed: 75.399229 samples/sec accuracy=61.083333 loss=1.596649 lr=0.010000 Epoch[038] Batch [0499]/[3760] Speed: 72.117698 samples/sec accuracy=61.115625 loss=1.599179 lr=0.010000 Epoch[038] Batch [0549]/[3760] Speed: 79.246748 samples/sec accuracy=61.130682 loss=1.599834 lr=0.010000 Epoch[038] Batch [0599]/[3760] Speed: 75.132145 samples/sec accuracy=61.179688 loss=1.598462 lr=0.010000 Epoch[038] Batch [0649]/[3760] Speed: 75.698071 samples/sec accuracy=61.161058 loss=1.596858 lr=0.010000 Epoch[038] Batch [0699]/[3760] Speed: 75.832589 samples/sec accuracy=61.180804 loss=1.596310 lr=0.010000 Epoch[038] Batch [0749]/[3760] Speed: 76.340575 samples/sec accuracy=61.185417 loss=1.598705 lr=0.010000 Epoch[038] Batch [0799]/[3760] Speed: 75.192278 samples/sec accuracy=61.207031 loss=1.597255 lr=0.010000 Epoch[038] Batch [0849]/[3760] Speed: 74.375331 samples/sec accuracy=61.125000 loss=1.600915 lr=0.010000 Epoch[038] Batch [0899]/[3760] Speed: 76.873446 samples/sec accuracy=61.098958 loss=1.601800 lr=0.010000 Epoch[038] 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accuracy=60.993304 loss=1.608770 lr=0.010000 Epoch[038] Batch [1449]/[3760] Speed: 77.933287 samples/sec accuracy=60.975216 loss=1.609911 lr=0.010000 Epoch[038] Batch [1499]/[3760] Speed: 74.308402 samples/sec accuracy=60.930208 loss=1.612383 lr=0.010000 Epoch[038] Batch [1549]/[3760] Speed: 77.097851 samples/sec accuracy=60.940524 loss=1.612418 lr=0.010000 Epoch[038] Batch [1599]/[3760] Speed: 75.843754 samples/sec accuracy=60.910156 loss=1.613078 lr=0.010000 Epoch[038] Batch [1649]/[3760] Speed: 74.879212 samples/sec accuracy=60.896780 loss=1.612979 lr=0.010000 Epoch[038] Batch [1699]/[3760] Speed: 74.493617 samples/sec accuracy=60.909926 loss=1.612244 lr=0.010000 Epoch[038] Batch [1749]/[3760] Speed: 76.825809 samples/sec accuracy=60.866964 loss=1.612953 lr=0.010000 Epoch[038] Batch [1799]/[3760] Speed: 76.677459 samples/sec accuracy=60.873264 loss=1.614833 lr=0.010000 Epoch[038] Batch [1849]/[3760] Speed: 73.248957 samples/sec accuracy=60.891892 loss=1.614696 lr=0.010000 Epoch[038] 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accuracy=60.756649 loss=1.619630 lr=0.010000 Epoch[038] Batch [2399]/[3760] Speed: 76.029792 samples/sec accuracy=60.748698 loss=1.620258 lr=0.010000 Epoch[038] Batch [2449]/[3760] Speed: 74.896963 samples/sec accuracy=60.764031 loss=1.619974 lr=0.010000 Epoch[038] Batch [2499]/[3760] Speed: 76.028792 samples/sec accuracy=60.781875 loss=1.619089 lr=0.010000 Epoch[038] Batch [2549]/[3760] Speed: 76.265012 samples/sec accuracy=60.765931 loss=1.619812 lr=0.010000 Epoch[038] Batch [2599]/[3760] Speed: 74.384818 samples/sec accuracy=60.763822 loss=1.620374 lr=0.010000 Epoch[038] Batch [2649]/[3760] Speed: 76.683010 samples/sec accuracy=60.795991 loss=1.619705 lr=0.010000 Epoch[038] Batch [2699]/[3760] Speed: 74.915556 samples/sec accuracy=60.817708 loss=1.619407 lr=0.010000 Epoch[038] Batch [2749]/[3760] Speed: 75.363181 samples/sec accuracy=60.825568 loss=1.618972 lr=0.010000 Epoch[038] Batch [2799]/[3760] Speed: 77.189337 samples/sec accuracy=60.838728 loss=1.618504 lr=0.010000 Epoch[038] 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accuracy=60.773674 loss=1.620180 lr=0.010000 Epoch[038] Batch [3349]/[3760] Speed: 78.016836 samples/sec accuracy=60.763993 loss=1.620908 lr=0.010000 Epoch[038] Batch [3399]/[3760] Speed: 77.065008 samples/sec accuracy=60.738051 loss=1.621926 lr=0.010000 Epoch[038] Batch [3449]/[3760] Speed: 75.020720 samples/sec accuracy=60.721920 loss=1.622023 lr=0.010000 Epoch[038] Batch [3499]/[3760] Speed: 77.208981 samples/sec accuracy=60.723214 loss=1.622159 lr=0.010000 Epoch[038] Batch [3549]/[3760] Speed: 74.741278 samples/sec accuracy=60.716549 loss=1.622456 lr=0.010000 Epoch[038] Batch [3599]/[3760] Speed: 76.697468 samples/sec accuracy=60.710937 loss=1.622305 lr=0.010000 Epoch[038] Batch [3649]/[3760] Speed: 74.784291 samples/sec accuracy=60.728168 loss=1.621367 lr=0.010000 Epoch[038] Batch [3699]/[3760] Speed: 76.994841 samples/sec accuracy=60.736909 loss=1.621560 lr=0.010000 Epoch[038] Batch [3749]/[3760] Speed: 84.289645 samples/sec accuracy=60.730417 loss=1.621844 lr=0.010000 Batch [0049]/[0303]: acc-top1=58.000000 acc-top5=80.812500 Batch [0099]/[0303]: acc-top1=58.328125 acc-top5=80.781250 Batch [0149]/[0303]: acc-top1=57.989583 acc-top5=80.895833 Batch [0199]/[0303]: acc-top1=58.070312 acc-top5=81.101562 Batch [0249]/[0303]: acc-top1=57.956250 acc-top5=81.025000 Batch [0299]/[0303]: acc-top1=57.942708 acc-top5=80.963542 [Epoch 038] training: accuracy=60.726812 loss=1.621931 [Epoch 038] speed: 75 samples/sec time cost: 3465.992348 [Epoch 038] validation: acc-top1=57.915635 acc-top5=80.966378 loss=1.968914 Epoch[039] Batch [0049]/[3760] Speed: 54.633113 samples/sec accuracy=61.906250 loss=1.565100 lr=0.010000 Epoch[039] Batch [0099]/[3760] Speed: 70.526507 samples/sec accuracy=62.265625 loss=1.565655 lr=0.010000 Epoch[039] Batch [0149]/[3760] Speed: 77.760001 samples/sec accuracy=62.145833 loss=1.565623 lr=0.010000 Epoch[039] Batch [0199]/[3760] Speed: 77.827998 samples/sec accuracy=62.226563 loss=1.559139 lr=0.010000 Epoch[039] Batch [0249]/[3760] Speed: 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lr=0.010000 Epoch[039] Batch [3599]/[3760] Speed: 76.073060 samples/sec accuracy=60.688368 loss=1.621850 lr=0.010000 Epoch[039] Batch [3649]/[3760] Speed: 74.601240 samples/sec accuracy=60.695205 loss=1.622301 lr=0.010000 Epoch[039] Batch [3699]/[3760] Speed: 75.790901 samples/sec accuracy=60.692145 loss=1.622931 lr=0.010000 Epoch[039] Batch [3749]/[3760] Speed: 84.464946 samples/sec accuracy=60.677083 loss=1.623470 lr=0.001000 Batch [0049]/[0303]: acc-top1=58.562500 acc-top5=80.843750 Batch [0099]/[0303]: acc-top1=58.953125 acc-top5=80.875000 Batch [0149]/[0303]: acc-top1=58.322917 acc-top5=80.739583 Batch [0199]/[0303]: acc-top1=58.382812 acc-top5=80.953125 Batch [0249]/[0303]: acc-top1=58.237500 acc-top5=80.950000 Batch [0299]/[0303]: acc-top1=58.145833 acc-top5=80.906250 [Epoch 039] training: accuracy=60.665725 loss=1.624026 [Epoch 039] speed: 75 samples/sec time cost: 3461.418318 [Epoch 039] validation: acc-top1=58.060025 acc-top5=80.909653 loss=1.969129 Epoch[040] Batch 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accuracy=65.758621 loss=1.398147 lr=0.001000 Epoch[040] Batch [1499]/[3759] Speed: 77.323145 samples/sec accuracy=65.758333 loss=1.396747 lr=0.001000 Epoch[040] Batch [1549]/[3759] Speed: 74.314896 samples/sec accuracy=65.831653 loss=1.392743 lr=0.001000 Epoch[040] Batch [1599]/[3759] Speed: 76.861637 samples/sec accuracy=65.880859 loss=1.389527 lr=0.001000 Epoch[040] Batch [1649]/[3759] Speed: 74.449916 samples/sec accuracy=65.952652 loss=1.387325 lr=0.001000 Epoch[040] Batch [1699]/[3759] Speed: 75.127483 samples/sec accuracy=65.997243 loss=1.386083 lr=0.001000 Epoch[040] Batch [1749]/[3759] Speed: 74.660536 samples/sec accuracy=66.027679 loss=1.385119 lr=0.001000 Epoch[040] Batch [1799]/[3759] Speed: 76.226975 samples/sec accuracy=66.034722 loss=1.384889 lr=0.001000 Epoch[040] Batch [1849]/[3759] Speed: 76.884404 samples/sec accuracy=66.061655 loss=1.383241 lr=0.001000 Epoch[040] Batch [1899]/[3759] Speed: 73.783674 samples/sec accuracy=66.060033 loss=1.382935 lr=0.001000 Epoch[040] 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accuracy=66.425130 loss=1.366113 lr=0.001000 Epoch[040] Batch [2449]/[3759] Speed: 76.821752 samples/sec accuracy=66.440051 loss=1.365302 lr=0.001000 Epoch[040] Batch [2499]/[3759] Speed: 75.832493 samples/sec accuracy=66.470000 loss=1.364500 lr=0.001000 Epoch[040] Batch [2549]/[3759] Speed: 76.288222 samples/sec accuracy=66.510417 loss=1.362964 lr=0.001000 Epoch[040] Batch [2599]/[3759] Speed: 74.973258 samples/sec accuracy=66.555288 loss=1.361643 lr=0.001000 Epoch[040] Batch [2649]/[3759] Speed: 77.554410 samples/sec accuracy=66.586675 loss=1.360344 lr=0.001000 Epoch[040] Batch [2699]/[3759] Speed: 76.076457 samples/sec accuracy=66.613426 loss=1.359682 lr=0.001000 Epoch[040] Batch [2749]/[3759] Speed: 73.732707 samples/sec accuracy=66.632955 loss=1.358278 lr=0.001000 Epoch[040] Batch [2799]/[3759] Speed: 77.218981 samples/sec accuracy=66.643415 loss=1.357826 lr=0.001000 Epoch[040] Batch [2849]/[3759] Speed: 76.506070 samples/sec accuracy=66.690789 loss=1.356301 lr=0.001000 Epoch[040] Batch [2899]/[3759] Speed: 72.318823 samples/sec accuracy=66.714978 loss=1.354860 lr=0.001000 Epoch[040] Batch [2949]/[3759] Speed: 78.212962 samples/sec accuracy=66.726695 loss=1.354494 lr=0.001000 Epoch[040] Batch [2999]/[3759] Speed: 74.815667 samples/sec accuracy=66.737500 loss=1.353975 lr=0.001000 Epoch[040] Batch [3049]/[3759] Speed: 76.847354 samples/sec accuracy=66.762295 loss=1.352939 lr=0.001000 Epoch[040] Batch [3099]/[3759] Speed: 74.388893 samples/sec accuracy=66.774698 loss=1.351997 lr=0.001000 Epoch[040] Batch [3149]/[3759] Speed: 73.898875 samples/sec accuracy=66.796627 loss=1.350973 lr=0.001000 Epoch[040] Batch [3199]/[3759] Speed: 77.750675 samples/sec accuracy=66.831543 loss=1.349386 lr=0.001000 Epoch[040] Batch [3249]/[3759] Speed: 75.274989 samples/sec accuracy=66.826923 loss=1.349529 lr=0.001000 Epoch[040] Batch [3299]/[3759] Speed: 76.320282 samples/sec accuracy=66.851326 loss=1.349032 lr=0.001000 Epoch[040] Batch [3349]/[3759] Speed: 73.543283 samples/sec accuracy=66.855877 loss=1.348397 lr=0.001000 Epoch[040] Batch [3399]/[3759] Speed: 77.011902 samples/sec accuracy=66.860294 loss=1.348164 lr=0.001000 Epoch[040] Batch [3449]/[3759] Speed: 74.058103 samples/sec accuracy=66.884058 loss=1.347633 lr=0.001000 Epoch[040] Batch [3499]/[3759] Speed: 78.026160 samples/sec accuracy=66.895536 loss=1.346721 lr=0.001000 Epoch[040] Batch [3549]/[3759] Speed: 74.698491 samples/sec accuracy=66.897887 loss=1.346312 lr=0.001000 Epoch[040] Batch [3599]/[3759] Speed: 77.199570 samples/sec accuracy=66.921875 loss=1.345084 lr=0.001000 Epoch[040] Batch [3649]/[3759] Speed: 75.266590 samples/sec accuracy=66.941353 loss=1.343851 lr=0.001000 Epoch[040] Batch [3699]/[3759] Speed: 75.165881 samples/sec accuracy=66.958193 loss=1.343233 lr=0.001000 Epoch[040] Batch [3749]/[3759] Speed: 85.714169 samples/sec accuracy=66.963750 loss=1.343102 lr=0.001000 Batch [0049]/[0303]: acc-top1=63.750000 acc-top5=84.718750 Batch [0099]/[0303]: acc-top1=64.093750 acc-top5=84.765625 Batch [0149]/[0303]: acc-top1=63.791667 acc-top5=84.937500 Batch [0199]/[0303]: acc-top1=63.859375 acc-top5=84.984375 Batch [0249]/[0303]: acc-top1=63.856250 acc-top5=84.956250 Batch [0299]/[0303]: acc-top1=63.791667 acc-top5=84.802083 [Epoch 040] training: accuracy=66.956388 loss=1.343271 [Epoch 040] speed: 75 samples/sec time cost: 3471.546967 [Epoch 040] validation: acc-top1=63.753094 acc-top5=84.818482 loss=1.659968 Epoch[041] Batch [0049]/[3760] Speed: 53.224398 samples/sec accuracy=68.062500 loss=1.283723 lr=0.001000 Epoch[041] Batch [0099]/[3760] Speed: 72.791285 samples/sec accuracy=68.546875 loss=1.281198 lr=0.001000 Epoch[041] Batch [0149]/[3760] Speed: 78.016226 samples/sec accuracy=68.927083 loss=1.260479 lr=0.001000 Epoch[041] Batch [0199]/[3760] Speed: 74.504194 samples/sec accuracy=69.062500 loss=1.252218 lr=0.001000 Epoch[041] Batch [0249]/[3760] Speed: 75.988232 samples/sec accuracy=68.787500 loss=1.261488 lr=0.001000 Epoch[041] Batch [0299]/[3760] 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accuracy=68.886285 loss=1.261467 lr=0.001000 Epoch[041] Batch [3649]/[3760] Speed: 74.212031 samples/sec accuracy=68.901113 loss=1.260988 lr=0.001000 Epoch[041] Batch [3699]/[3760] Speed: 76.456901 samples/sec accuracy=68.904561 loss=1.260730 lr=0.001000 Epoch[041] Batch [3749]/[3760] Speed: 85.293460 samples/sec accuracy=68.917917 loss=1.260177 lr=0.001000 Batch [0049]/[0303]: acc-top1=64.218750 acc-top5=85.250000 Batch [0099]/[0303]: acc-top1=64.984375 acc-top5=85.093750 Batch [0149]/[0303]: acc-top1=64.645833 acc-top5=85.260417 Batch [0199]/[0303]: acc-top1=64.578125 acc-top5=85.335938 Batch [0249]/[0303]: acc-top1=64.525000 acc-top5=85.262500 Batch [0299]/[0303]: acc-top1=64.416667 acc-top5=85.083333 [Epoch 041] training: accuracy=68.923703 loss=1.260218 [Epoch 041] speed: 75 samples/sec time cost: 3461.061288 [Epoch 041] validation: acc-top1=64.382219 acc-top5=85.102104 loss=1.631879 Epoch[042] Batch [0049]/[3760] Speed: 54.098852 samples/sec accuracy=69.187500 loss=1.229145 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acc-top1=64.507812 acc-top5=85.640625 Batch [0249]/[0303]: acc-top1=64.437500 acc-top5=85.581250 Batch [0299]/[0303]: acc-top1=64.411458 acc-top5=85.473958 [Epoch 042] training: accuracy=69.692487 loss=1.222402 [Epoch 042] speed: 75 samples/sec time cost: 3460.674620 [Epoch 042] validation: acc-top1=64.387376 acc-top5=85.488861 loss=1.620717 Epoch[043] Batch [0049]/[3759] Speed: 54.598951 samples/sec accuracy=70.687500 loss=1.191228 lr=0.001000 Epoch[043] Batch [0099]/[3759] Speed: 72.407875 samples/sec accuracy=71.312500 loss=1.171380 lr=0.001000 Epoch[043] Batch [0149]/[3759] Speed: 76.317764 samples/sec accuracy=70.666667 loss=1.187915 lr=0.001000 Epoch[043] Batch [0199]/[3759] Speed: 75.040438 samples/sec accuracy=70.539062 loss=1.202400 lr=0.001000 Epoch[043] Batch [0249]/[3759] Speed: 76.222271 samples/sec accuracy=70.250000 loss=1.208521 lr=0.001000 Epoch[043] Batch [0299]/[3759] Speed: 75.853342 samples/sec accuracy=70.104167 loss=1.214680 lr=0.001000 Epoch[043] Batch 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accuracy=70.133562 loss=1.205064 lr=0.001000 Epoch[043] Batch [3699]/[3759] Speed: 77.033100 samples/sec accuracy=70.148226 loss=1.204915 lr=0.001000 Epoch[043] Batch [3749]/[3759] Speed: 84.675017 samples/sec accuracy=70.155000 loss=1.204660 lr=0.001000 Batch [0049]/[0303]: acc-top1=64.406250 acc-top5=85.031250 Batch [0099]/[0303]: acc-top1=65.296875 acc-top5=85.062500 Batch [0149]/[0303]: acc-top1=64.916667 acc-top5=85.364583 Batch [0199]/[0303]: acc-top1=64.750000 acc-top5=85.421875 Batch [0249]/[0303]: acc-top1=64.581250 acc-top5=85.393750 Batch [0299]/[0303]: acc-top1=64.510417 acc-top5=85.281250 [Epoch 043] training: accuracy=70.156624 loss=1.204655 [Epoch 043] speed: 75 samples/sec time cost: 3466.152713 [Epoch 043] validation: acc-top1=64.480198 acc-top5=85.292904 loss=1.619461 Epoch[044] Batch [0049]/[3760] Speed: 53.084071 samples/sec accuracy=71.093750 loss=1.144160 lr=0.001000 Epoch[044] Batch [0099]/[3760] Speed: 72.754263 samples/sec accuracy=70.734375 loss=1.169927 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lr=0.001000 Epoch[044] Batch [2999]/[3760] Speed: 74.914661 samples/sec accuracy=70.753646 loss=1.181911 lr=0.001000 Epoch[044] Batch [3049]/[3760] Speed: 77.286562 samples/sec accuracy=70.765881 loss=1.181219 lr=0.001000 Epoch[044] Batch [3099]/[3760] Speed: 75.288128 samples/sec accuracy=70.762601 loss=1.181559 lr=0.001000 Epoch[044] Batch [3149]/[3760] Speed: 76.865902 samples/sec accuracy=70.744544 loss=1.181750 lr=0.001000 Epoch[044] Batch [3199]/[3760] Speed: 74.483220 samples/sec accuracy=70.770020 loss=1.181283 lr=0.001000 Epoch[044] Batch [3249]/[3760] Speed: 77.410022 samples/sec accuracy=70.754808 loss=1.181655 lr=0.001000 Epoch[044] Batch [3299]/[3760] Speed: 75.024992 samples/sec accuracy=70.761364 loss=1.181275 lr=0.001000 Epoch[044] Batch [3349]/[3760] Speed: 76.770244 samples/sec accuracy=70.776119 loss=1.180665 lr=0.001000 Epoch[044] Batch [3399]/[3760] Speed: 75.423896 samples/sec accuracy=70.753217 loss=1.181176 lr=0.001000 Epoch[044] Batch [3449]/[3760] Speed: 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[0299]/[0303]: acc-top1=64.984375 acc-top5=85.421875 [Epoch 044] training: accuracy=70.703125 loss=1.182472 [Epoch 044] speed: 75 samples/sec time cost: 3459.309158 [Epoch 044] validation: acc-top1=64.954620 acc-top5=85.432137 loss=1.609055 Epoch[045] Batch [0049]/[3760] Speed: 53.791741 samples/sec accuracy=71.843750 loss=1.158380 lr=0.001000 Epoch[045] Batch [0099]/[3760] Speed: 73.425672 samples/sec accuracy=71.203125 loss=1.182824 lr=0.001000 Epoch[045] Batch [0149]/[3760] Speed: 77.129571 samples/sec accuracy=71.135417 loss=1.169837 lr=0.001000 Epoch[045] Batch [0199]/[3760] Speed: 76.802180 samples/sec accuracy=71.132812 loss=1.167149 lr=0.001000 Epoch[045] Batch [0249]/[3760] Speed: 74.168308 samples/sec accuracy=71.356250 loss=1.161496 lr=0.001000 Epoch[045] Batch [0299]/[3760] Speed: 76.754776 samples/sec accuracy=71.411458 loss=1.157806 lr=0.001000 Epoch[045] Batch [0349]/[3760] Speed: 75.554151 samples/sec accuracy=71.419643 loss=1.157268 lr=0.001000 Epoch[045] Batch 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accuracy=71.011364 loss=1.167580 lr=0.001000 Epoch[045] Batch [2799]/[3760] Speed: 75.201036 samples/sec accuracy=70.985491 loss=1.168190 lr=0.001000 Epoch[045] Batch [2849]/[3760] Speed: 75.012647 samples/sec accuracy=70.974781 loss=1.168361 lr=0.001000 Epoch[045] Batch [2899]/[3760] Speed: 76.655535 samples/sec accuracy=70.982759 loss=1.168566 lr=0.001000 Epoch[045] Batch [2949]/[3760] Speed: 76.102065 samples/sec accuracy=70.984640 loss=1.169103 lr=0.001000 Epoch[045] Batch [2999]/[3760] Speed: 73.355612 samples/sec accuracy=70.984896 loss=1.169391 lr=0.001000 Epoch[045] Batch [3049]/[3760] Speed: 77.707033 samples/sec accuracy=71.002561 loss=1.168782 lr=0.001000 Epoch[045] Batch [3099]/[3760] Speed: 74.089544 samples/sec accuracy=71.004032 loss=1.168967 lr=0.001000 Epoch[045] Batch [3149]/[3760] Speed: 76.727788 samples/sec accuracy=70.993552 loss=1.169236 lr=0.001000 Epoch[045] Batch [3199]/[3760] Speed: 74.551521 samples/sec accuracy=70.984863 loss=1.169041 lr=0.001000 Epoch[045] 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accuracy=70.945101 loss=1.169015 lr=0.001000 Epoch[045] Batch [3749]/[3760] Speed: 86.122339 samples/sec accuracy=70.923750 loss=1.169528 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.562500 acc-top5=85.562500 Batch [0099]/[0303]: acc-top1=66.078125 acc-top5=85.609375 Batch [0149]/[0303]: acc-top1=65.437500 acc-top5=85.729167 Batch [0199]/[0303]: acc-top1=65.390625 acc-top5=85.773438 Batch [0249]/[0303]: acc-top1=65.250000 acc-top5=85.731250 Batch [0299]/[0303]: acc-top1=65.145833 acc-top5=85.619792 [Epoch 045] training: accuracy=70.923787 loss=1.169425 [Epoch 045] speed: 75 samples/sec time cost: 3466.450114 [Epoch 045] validation: acc-top1=65.140264 acc-top5=85.628094 loss=1.619224 Epoch[046] Batch [0049]/[3759] Speed: 53.756401 samples/sec accuracy=71.906250 loss=1.113564 lr=0.001000 Epoch[046] Batch [0099]/[3759] Speed: 72.392045 samples/sec accuracy=72.406250 loss=1.120327 lr=0.001000 Epoch[046] Batch [0149]/[3759] Speed: 76.447434 samples/sec accuracy=72.541667 loss=1.109240 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lr=0.001000 Epoch[046] Batch [1149]/[3759] Speed: 77.026923 samples/sec accuracy=71.501359 loss=1.147187 lr=0.001000 Epoch[046] Batch [1199]/[3759] Speed: 75.879605 samples/sec accuracy=71.505208 loss=1.146705 lr=0.001000 Epoch[046] Batch [1249]/[3759] Speed: 75.365994 samples/sec accuracy=71.523750 loss=1.146988 lr=0.001000 Epoch[046] Batch [1299]/[3759] Speed: 77.023799 samples/sec accuracy=71.501202 loss=1.148141 lr=0.001000 Epoch[046] Batch [1349]/[3759] Speed: 73.791305 samples/sec accuracy=71.469907 loss=1.148827 lr=0.001000 Epoch[046] Batch [1399]/[3759] Speed: 75.523781 samples/sec accuracy=71.433036 loss=1.149277 lr=0.001000 Epoch[046] Batch [1449]/[3759] Speed: 78.220518 samples/sec accuracy=71.409483 loss=1.149418 lr=0.001000 Epoch[046] Batch [1499]/[3759] Speed: 74.612171 samples/sec accuracy=71.375000 loss=1.149780 lr=0.001000 Epoch[046] Batch [1549]/[3759] Speed: 76.754679 samples/sec accuracy=71.351815 loss=1.150079 lr=0.001000 Epoch[046] Batch [1599]/[3759] Speed: 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lr=0.001000 Epoch[046] Batch [2099]/[3759] Speed: 77.515209 samples/sec accuracy=71.268601 loss=1.154260 lr=0.001000 Epoch[046] Batch [2149]/[3759] Speed: 74.588820 samples/sec accuracy=71.248547 loss=1.154340 lr=0.001000 Epoch[046] Batch [2199]/[3759] Speed: 73.625446 samples/sec accuracy=71.254972 loss=1.154031 lr=0.001000 Epoch[046] Batch [2249]/[3759] Speed: 78.664396 samples/sec accuracy=71.234028 loss=1.154971 lr=0.001000 Epoch[046] Batch [2299]/[3759] Speed: 75.355506 samples/sec accuracy=71.241168 loss=1.154434 lr=0.001000 Epoch[046] Batch [2349]/[3759] Speed: 75.764989 samples/sec accuracy=71.233378 loss=1.154440 lr=0.001000 Epoch[046] Batch [2399]/[3759] Speed: 77.076209 samples/sec accuracy=71.213542 loss=1.155063 lr=0.001000 Epoch[046] Batch [2449]/[3759] Speed: 75.512431 samples/sec accuracy=71.194515 loss=1.155585 lr=0.001000 Epoch[046] Batch [2499]/[3759] Speed: 74.510594 samples/sec accuracy=71.227500 loss=1.154715 lr=0.001000 Epoch[046] Batch [2549]/[3759] Speed: 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lr=0.001000 Epoch[046] Batch [3049]/[3759] Speed: 74.672051 samples/sec accuracy=71.264344 loss=1.152686 lr=0.001000 Epoch[046] Batch [3099]/[3759] Speed: 76.127607 samples/sec accuracy=71.250504 loss=1.152952 lr=0.001000 Epoch[046] Batch [3149]/[3759] Speed: 76.027714 samples/sec accuracy=71.272817 loss=1.152060 lr=0.001000 Epoch[046] Batch [3199]/[3759] Speed: 76.718363 samples/sec accuracy=71.265625 loss=1.152304 lr=0.001000 Epoch[046] Batch [3249]/[3759] Speed: 75.624307 samples/sec accuracy=71.267788 loss=1.152504 lr=0.001000 Epoch[046] Batch [3299]/[3759] Speed: 75.989464 samples/sec accuracy=71.260890 loss=1.152713 lr=0.001000 Epoch[046] Batch [3349]/[3759] Speed: 75.997714 samples/sec accuracy=71.294310 loss=1.151462 lr=0.001000 Epoch[046] Batch [3399]/[3759] Speed: 76.619420 samples/sec accuracy=71.295037 loss=1.151705 lr=0.001000 Epoch[046] Batch [3449]/[3759] Speed: 74.065482 samples/sec accuracy=71.290761 loss=1.151866 lr=0.001000 Epoch[046] Batch [3499]/[3759] Speed: 77.259455 samples/sec accuracy=71.287500 loss=1.152366 lr=0.001000 Epoch[046] Batch [3549]/[3759] Speed: 77.439891 samples/sec accuracy=71.299736 loss=1.152600 lr=0.001000 Epoch[046] Batch [3599]/[3759] Speed: 74.526193 samples/sec accuracy=71.304253 loss=1.152544 lr=0.001000 Epoch[046] Batch [3649]/[3759] Speed: 75.919832 samples/sec accuracy=71.311216 loss=1.152217 lr=0.001000 Epoch[046] Batch [3699]/[3759] Speed: 76.737329 samples/sec accuracy=71.314611 loss=1.152292 lr=0.001000 Epoch[046] Batch [3749]/[3759] Speed: 85.819432 samples/sec accuracy=71.300417 loss=1.153166 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.843750 acc-top5=86.093750 Batch [0099]/[0303]: acc-top1=65.968750 acc-top5=85.828125 Batch [0149]/[0303]: acc-top1=65.541667 acc-top5=85.854167 Batch [0199]/[0303]: acc-top1=65.468750 acc-top5=85.859375 Batch [0249]/[0303]: acc-top1=65.318750 acc-top5=85.787500 Batch [0299]/[0303]: acc-top1=65.223958 acc-top5=85.630208 [Epoch 046] training: accuracy=71.295557 loss=1.153230 [Epoch 046] speed: 75 samples/sec time cost: 3460.402819 [Epoch 046] validation: acc-top1=65.181518 acc-top5=85.648721 loss=1.600036 Epoch[047] Batch [0049]/[3760] Speed: 53.643855 samples/sec accuracy=71.250000 loss=1.161868 lr=0.001000 Epoch[047] Batch [0099]/[3760] Speed: 72.383351 samples/sec accuracy=71.390625 loss=1.159197 lr=0.001000 Epoch[047] Batch [0149]/[3760] Speed: 77.690463 samples/sec accuracy=71.218750 loss=1.162534 lr=0.001000 Epoch[047] Batch [0199]/[3760] Speed: 74.407336 samples/sec accuracy=71.156250 loss=1.155461 lr=0.001000 Epoch[047] Batch [0249]/[3760] Speed: 76.471999 samples/sec accuracy=71.112500 loss=1.156475 lr=0.001000 Epoch[047] Batch [0299]/[3760] Speed: 75.942583 samples/sec accuracy=71.244792 loss=1.148537 lr=0.001000 Epoch[047] Batch [0349]/[3760] Speed: 75.992064 samples/sec accuracy=71.151786 loss=1.147283 lr=0.001000 Epoch[047] Batch [0399]/[3760] Speed: 75.935417 samples/sec accuracy=71.253906 loss=1.142432 lr=0.001000 Epoch[047] Batch 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accuracy=71.557917 loss=1.140542 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.625000 acc-top5=86.031250 Batch [0099]/[0303]: acc-top1=65.984375 acc-top5=85.812500 Batch [0149]/[0303]: acc-top1=65.531250 acc-top5=85.875000 Batch [0199]/[0303]: acc-top1=65.515625 acc-top5=85.929688 Batch [0249]/[0303]: acc-top1=65.337500 acc-top5=85.881250 Batch [0299]/[0303]: acc-top1=65.390625 acc-top5=85.718750 [Epoch 047] training: accuracy=71.548371 loss=1.140777 [Epoch 047] speed: 75 samples/sec time cost: 3460.294008 [Epoch 047] validation: acc-top1=65.387789 acc-top5=85.731229 loss=1.590989 Epoch[048] Batch [0049]/[3760] Speed: 54.064776 samples/sec accuracy=71.750000 loss=1.124221 lr=0.001000 Epoch[048] Batch [0099]/[3760] Speed: 71.057462 samples/sec accuracy=72.156250 loss=1.122575 lr=0.001000 Epoch[048] Batch [0149]/[3760] Speed: 76.532555 samples/sec accuracy=71.812500 loss=1.130508 lr=0.001000 Epoch[048] Batch [0199]/[3760] Speed: 74.711143 samples/sec accuracy=71.789062 loss=1.120370 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lr=0.001000 Epoch[048] Batch [3099]/[3760] Speed: 77.025432 samples/sec accuracy=71.867440 loss=1.128361 lr=0.001000 Epoch[048] Batch [3149]/[3760] Speed: 75.498972 samples/sec accuracy=71.897321 loss=1.127519 lr=0.001000 Epoch[048] Batch [3199]/[3760] Speed: 75.091095 samples/sec accuracy=71.891113 loss=1.128110 lr=0.001000 Epoch[048] Batch [3249]/[3760] Speed: 75.251991 samples/sec accuracy=71.891827 loss=1.128321 lr=0.001000 Epoch[048] Batch [3299]/[3760] Speed: 75.032678 samples/sec accuracy=71.906250 loss=1.127983 lr=0.001000 Epoch[048] Batch [3349]/[3760] Speed: 77.121210 samples/sec accuracy=71.901586 loss=1.128420 lr=0.001000 Epoch[048] Batch [3399]/[3760] Speed: 74.303919 samples/sec accuracy=71.898438 loss=1.128870 lr=0.001000 Epoch[048] Batch [3449]/[3760] Speed: 76.517660 samples/sec accuracy=71.909873 loss=1.128382 lr=0.001000 Epoch[048] Batch [3499]/[3760] Speed: 77.093124 samples/sec accuracy=71.908036 loss=1.128492 lr=0.001000 Epoch[048] Batch [3549]/[3760] Speed: 76.514556 samples/sec accuracy=71.889965 loss=1.129312 lr=0.001000 Epoch[048] Batch [3599]/[3760] Speed: 72.758278 samples/sec accuracy=71.885417 loss=1.129358 lr=0.001000 Epoch[048] Batch [3649]/[3760] Speed: 77.821713 samples/sec accuracy=71.883990 loss=1.129460 lr=0.001000 Epoch[048] Batch [3699]/[3760] Speed: 74.467692 samples/sec accuracy=71.873311 loss=1.129755 lr=0.001000 Epoch[048] Batch [3749]/[3760] Speed: 86.118378 samples/sec accuracy=71.867500 loss=1.129857 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.812500 acc-top5=85.656250 Batch [0099]/[0303]: acc-top1=66.109375 acc-top5=85.671875 Batch [0149]/[0303]: acc-top1=65.718750 acc-top5=85.875000 Batch [0199]/[0303]: acc-top1=65.625000 acc-top5=85.875000 Batch [0249]/[0303]: acc-top1=65.518750 acc-top5=85.825000 Batch [0299]/[0303]: acc-top1=65.515625 acc-top5=85.734375 [Epoch 048] training: accuracy=71.864195 loss=1.129889 [Epoch 048] speed: 75 samples/sec time cost: 3467.985308 [Epoch 048] validation: acc-top1=65.490924 acc-top5=85.757013 loss=1.611398 Epoch[049] Batch [0049]/[3759] Speed: 53.151142 samples/sec accuracy=73.843750 loss=1.049773 lr=0.001000 Epoch[049] Batch [0099]/[3759] Speed: 72.691162 samples/sec accuracy=72.593750 loss=1.104199 lr=0.001000 Epoch[049] Batch [0149]/[3759] Speed: 76.715400 samples/sec accuracy=72.718750 loss=1.085049 lr=0.001000 Epoch[049] Batch [0199]/[3759] Speed: 73.106978 samples/sec accuracy=73.125000 loss=1.077010 lr=0.001000 Epoch[049] Batch [0249]/[3759] Speed: 77.266932 samples/sec accuracy=72.768750 loss=1.084725 lr=0.001000 Epoch[049] Batch [0299]/[3759] Speed: 77.399910 samples/sec accuracy=72.708333 loss=1.087360 lr=0.001000 Epoch[049] Batch [0349]/[3759] Speed: 74.836780 samples/sec accuracy=72.656250 loss=1.088584 lr=0.001000 Epoch[049] Batch [0399]/[3759] Speed: 76.389077 samples/sec accuracy=72.484375 loss=1.093508 lr=0.001000 Epoch[049] Batch [0449]/[3759] Speed: 75.582996 samples/sec accuracy=72.583333 loss=1.091038 lr=0.001000 Epoch[049] Batch 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[0099]/[0303]: acc-top1=66.453125 acc-top5=85.656250 Batch [0149]/[0303]: acc-top1=65.927083 acc-top5=85.750000 Batch [0199]/[0303]: acc-top1=65.718750 acc-top5=85.796875 Batch [0249]/[0303]: acc-top1=65.493750 acc-top5=85.831250 Batch [0299]/[0303]: acc-top1=65.557292 acc-top5=85.755208 [Epoch 049] training: accuracy=72.096552 loss=1.119983 [Epoch 049] speed: 75 samples/sec time cost: 3464.745875 [Epoch 049] validation: acc-top1=65.547649 acc-top5=85.787954 loss=1.610281 Epoch[050] Batch [0049]/[3760] Speed: 53.210009 samples/sec accuracy=71.843750 loss=1.135195 lr=0.001000 Epoch[050] Batch [0099]/[3760] Speed: 74.837308 samples/sec accuracy=72.609375 loss=1.111515 lr=0.001000 Epoch[050] Batch [0149]/[3760] Speed: 76.396872 samples/sec accuracy=72.739583 loss=1.111296 lr=0.001000 Epoch[050] Batch [0199]/[3760] Speed: 75.502453 samples/sec accuracy=72.382812 loss=1.121872 lr=0.001000 Epoch[050] Batch [0249]/[3760] Speed: 74.947330 samples/sec accuracy=72.618750 loss=1.105016 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lr=0.001000 Epoch[050] Batch [2199]/[3760] Speed: 75.634736 samples/sec accuracy=72.178977 loss=1.113170 lr=0.001000 Epoch[050] Batch [2249]/[3760] Speed: 73.903991 samples/sec accuracy=72.147917 loss=1.114332 lr=0.001000 Epoch[050] Batch [2299]/[3760] Speed: 77.721617 samples/sec accuracy=72.149457 loss=1.113911 lr=0.001000 Epoch[050] Batch [2349]/[3760] Speed: 75.608508 samples/sec accuracy=72.156915 loss=1.113895 lr=0.001000 Epoch[050] Batch [2399]/[3760] Speed: 75.510769 samples/sec accuracy=72.146484 loss=1.113767 lr=0.001000 Epoch[050] Batch [2449]/[3760] Speed: 75.418952 samples/sec accuracy=72.156250 loss=1.113201 lr=0.001000 Epoch[050] Batch [2499]/[3760] Speed: 76.799515 samples/sec accuracy=72.139375 loss=1.113473 lr=0.001000 Epoch[050] Batch [2549]/[3760] Speed: 76.194035 samples/sec accuracy=72.152574 loss=1.112658 lr=0.001000 Epoch[050] Batch [2599]/[3760] Speed: 73.544218 samples/sec accuracy=72.145433 loss=1.112743 lr=0.001000 Epoch[050] Batch [2649]/[3760] Speed: 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lr=0.001000 Epoch[050] Batch [3149]/[3760] Speed: 75.136992 samples/sec accuracy=72.177579 loss=1.111633 lr=0.001000 Epoch[050] Batch [3199]/[3760] Speed: 70.996344 samples/sec accuracy=72.166504 loss=1.112010 lr=0.001000 Epoch[050] Batch [3249]/[3760] Speed: 80.673956 samples/sec accuracy=72.177885 loss=1.111877 lr=0.001000 Epoch[050] Batch [3299]/[3760] Speed: 74.200578 samples/sec accuracy=72.161458 loss=1.112258 lr=0.001000 Epoch[050] Batch [3349]/[3760] Speed: 76.027668 samples/sec accuracy=72.174907 loss=1.111789 lr=0.001000 Epoch[050] Batch [3399]/[3760] Speed: 75.373243 samples/sec accuracy=72.177390 loss=1.112083 lr=0.001000 Epoch[050] Batch [3449]/[3760] Speed: 75.056375 samples/sec accuracy=72.185236 loss=1.111778 lr=0.001000 Epoch[050] Batch [3499]/[3760] Speed: 76.906510 samples/sec accuracy=72.205804 loss=1.110578 lr=0.001000 Epoch[050] Batch [3549]/[3760] Speed: 75.289158 samples/sec accuracy=72.194542 loss=1.110664 lr=0.001000 Epoch[050] Batch [3599]/[3760] Speed: 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accuracy=72.625000 loss=1.083718 lr=0.001000 Epoch[051] Batch [0099]/[3760] Speed: 72.916715 samples/sec accuracy=72.890625 loss=1.073171 lr=0.001000 Epoch[051] Batch [0149]/[3760] Speed: 76.633636 samples/sec accuracy=73.041667 loss=1.075487 lr=0.001000 Epoch[051] Batch [0199]/[3760] Speed: 75.830854 samples/sec accuracy=73.117188 loss=1.077762 lr=0.001000 Epoch[051] Batch [0249]/[3760] Speed: 76.255201 samples/sec accuracy=73.281250 loss=1.069636 lr=0.001000 Epoch[051] Batch [0299]/[3760] Speed: 75.019982 samples/sec accuracy=73.348958 loss=1.070407 lr=0.001000 Epoch[051] Batch [0349]/[3760] Speed: 75.414684 samples/sec accuracy=73.366071 loss=1.071179 lr=0.001000 Epoch[051] Batch [0399]/[3760] Speed: 74.646695 samples/sec accuracy=73.246094 loss=1.075112 lr=0.001000 Epoch[051] Batch [0449]/[3760] Speed: 76.689983 samples/sec accuracy=73.149306 loss=1.076781 lr=0.001000 Epoch[051] Batch [0499]/[3760] Speed: 74.591147 samples/sec accuracy=73.100000 loss=1.079631 lr=0.001000 Epoch[051] 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acc-top5=85.812500 Batch [0199]/[0303]: acc-top1=65.656250 acc-top5=85.820312 Batch [0249]/[0303]: acc-top1=65.581250 acc-top5=85.812500 Batch [0299]/[0303]: acc-top1=65.619792 acc-top5=85.755208 [Epoch 051] training: accuracy=72.556100 loss=1.097530 [Epoch 051] speed: 75 samples/sec time cost: 3471.018060 [Epoch 051] validation: acc-top1=65.568276 acc-top5=85.777640 loss=1.601154 Epoch[052] Batch [0049]/[3759] Speed: 53.346282 samples/sec accuracy=71.750000 loss=1.131189 lr=0.001000 Epoch[052] Batch [0099]/[3759] Speed: 72.484842 samples/sec accuracy=72.937500 loss=1.086921 lr=0.001000 Epoch[052] Batch [0149]/[3759] Speed: 77.813292 samples/sec accuracy=73.406250 loss=1.072308 lr=0.001000 Epoch[052] Batch [0199]/[3759] Speed: 74.977379 samples/sec accuracy=73.320312 loss=1.069320 lr=0.001000 Epoch[052] Batch [0249]/[3759] Speed: 75.654816 samples/sec accuracy=73.350000 loss=1.068380 lr=0.001000 Epoch[052] Batch [0299]/[3759] Speed: 76.432152 samples/sec accuracy=73.135417 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accuracy=72.901786 loss=1.086036 lr=0.001000 Epoch[052] Batch [3199]/[3759] Speed: 73.610365 samples/sec accuracy=72.877441 loss=1.086255 lr=0.001000 Epoch[052] Batch [3249]/[3759] Speed: 77.253321 samples/sec accuracy=72.876923 loss=1.085978 lr=0.001000 Epoch[052] Batch [3299]/[3759] Speed: 75.090658 samples/sec accuracy=72.860322 loss=1.087105 lr=0.001000 Epoch[052] Batch [3349]/[3759] Speed: 77.151343 samples/sec accuracy=72.848414 loss=1.087814 lr=0.001000 Epoch[052] Batch [3399]/[3759] Speed: 75.821805 samples/sec accuracy=72.838695 loss=1.088112 lr=0.001000 Epoch[052] Batch [3449]/[3759] Speed: 75.038639 samples/sec accuracy=72.834239 loss=1.088486 lr=0.001000 Epoch[052] Batch [3499]/[3759] Speed: 77.036986 samples/sec accuracy=72.804911 loss=1.089483 lr=0.001000 Epoch[052] Batch [3549]/[3759] Speed: 74.450672 samples/sec accuracy=72.815141 loss=1.089312 lr=0.001000 Epoch[052] Batch [3599]/[3759] Speed: 76.266586 samples/sec accuracy=72.796441 loss=1.089872 lr=0.001000 Epoch[052] 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[0249]/[0303]: acc-top1=65.450000 acc-top5=85.793750 Batch [0299]/[0303]: acc-top1=65.489583 acc-top5=85.697917 [Epoch 053] training: accuracy=72.941323 loss=1.080493 [Epoch 053] speed: 75 samples/sec time cost: 3462.048538 [Epoch 053] validation: acc-top1=65.459983 acc-top5=85.731229 loss=1.593461 Epoch[054] Batch [0049]/[3760] Speed: 53.605772 samples/sec accuracy=72.687500 loss=1.093990 lr=0.001000 Epoch[054] Batch [0099]/[3760] Speed: 71.917287 samples/sec accuracy=73.218750 loss=1.071150 lr=0.001000 Epoch[054] Batch [0149]/[3760] Speed: 76.833439 samples/sec accuracy=73.395833 loss=1.071811 lr=0.001000 Epoch[054] Batch [0199]/[3760] Speed: 77.611677 samples/sec accuracy=73.539062 loss=1.063892 lr=0.001000 Epoch[054] Batch [0249]/[3760] Speed: 72.724926 samples/sec accuracy=73.437500 loss=1.067300 lr=0.001000 Epoch[054] Batch [0299]/[3760] Speed: 78.462747 samples/sec accuracy=73.395833 loss=1.069271 lr=0.001000 Epoch[054] Batch [0349]/[3760] Speed: 75.701142 samples/sec 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lr=0.001000 Epoch[055] Batch [3499]/[3759] Speed: 75.756615 samples/sec accuracy=73.276786 loss=1.069740 lr=0.001000 Epoch[055] Batch [3549]/[3759] Speed: 76.875169 samples/sec accuracy=73.290933 loss=1.069133 lr=0.001000 Epoch[055] Batch [3599]/[3759] Speed: 74.920574 samples/sec accuracy=73.307292 loss=1.068640 lr=0.001000 Epoch[055] Batch [3649]/[3759] Speed: 74.830350 samples/sec accuracy=73.309932 loss=1.068475 lr=0.001000 Epoch[055] Batch [3699]/[3759] Speed: 76.965539 samples/sec accuracy=73.323902 loss=1.068103 lr=0.001000 Epoch[055] Batch [3749]/[3759] Speed: 84.246151 samples/sec accuracy=73.325000 loss=1.068309 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.656250 acc-top5=85.937500 Batch [0099]/[0303]: acc-top1=65.875000 acc-top5=85.750000 Batch [0149]/[0303]: acc-top1=65.885417 acc-top5=85.895833 Batch [0199]/[0303]: acc-top1=65.804688 acc-top5=85.929688 Batch [0249]/[0303]: acc-top1=65.643750 acc-top5=85.937500 Batch [0299]/[0303]: acc-top1=65.723958 acc-top5=85.869792 [Epoch 055] training: accuracy=73.331089 loss=1.068249 [Epoch 055] speed: 75 samples/sec time cost: 3461.324205 [Epoch 055] validation: acc-top1=65.681724 acc-top5=85.891089 loss=1.595457 Epoch[056] Batch [0049]/[3760] Speed: 53.969745 samples/sec accuracy=72.312500 loss=1.115379 lr=0.001000 Epoch[056] Batch [0099]/[3760] Speed: 71.005958 samples/sec accuracy=73.578125 loss=1.057747 lr=0.001000 Epoch[056] Batch [0149]/[3760] Speed: 77.901394 samples/sec accuracy=73.395833 loss=1.067474 lr=0.001000 Epoch[056] Batch [0199]/[3760] Speed: 75.161544 samples/sec accuracy=73.257812 loss=1.069360 lr=0.001000 Epoch[056] Batch [0249]/[3760] Speed: 76.945293 samples/sec accuracy=73.406250 loss=1.069180 lr=0.001000 Epoch[056] Batch [0299]/[3760] Speed: 76.355899 samples/sec accuracy=73.338542 loss=1.069001 lr=0.001000 Epoch[056] Batch [0349]/[3760] Speed: 74.914926 samples/sec accuracy=73.205357 loss=1.076723 lr=0.001000 Epoch[056] Batch [0399]/[3760] Speed: 75.548623 samples/sec accuracy=73.285156 loss=1.072118 lr=0.001000 Epoch[056] Batch [0449]/[3760] Speed: 77.356156 samples/sec accuracy=73.274306 loss=1.068487 lr=0.001000 Epoch[056] Batch [0499]/[3760] Speed: 76.673378 samples/sec accuracy=73.315625 loss=1.064787 lr=0.001000 Epoch[056] Batch [0549]/[3760] Speed: 75.819213 samples/sec accuracy=73.250000 loss=1.065357 lr=0.001000 Epoch[056] Batch [0599]/[3760] Speed: 75.909767 samples/sec accuracy=73.179688 loss=1.066103 lr=0.001000 Epoch[056] Batch [0649]/[3760] Speed: 75.582241 samples/sec accuracy=73.257212 loss=1.062443 lr=0.001000 Epoch[056] Batch [0699]/[3760] Speed: 76.800497 samples/sec accuracy=73.252232 loss=1.063069 lr=0.001000 Epoch[056] Batch [0749]/[3760] Speed: 74.881279 samples/sec accuracy=73.283333 loss=1.060743 lr=0.001000 Epoch[056] Batch [0799]/[3760] Speed: 76.137250 samples/sec accuracy=73.226562 loss=1.063336 lr=0.001000 Epoch[056] Batch [0849]/[3760] Speed: 75.104433 samples/sec accuracy=73.242647 loss=1.062933 lr=0.001000 Epoch[056] 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accuracy=73.334491 loss=1.064250 lr=0.001000 Epoch[056] Batch [1399]/[3760] Speed: 78.246646 samples/sec accuracy=73.343750 loss=1.064478 lr=0.001000 Epoch[056] Batch [1449]/[3760] Speed: 75.959354 samples/sec accuracy=73.354526 loss=1.063952 lr=0.001000 Epoch[056] Batch [1499]/[3760] Speed: 76.918336 samples/sec accuracy=73.394792 loss=1.062711 lr=0.001000 Epoch[056] Batch [1549]/[3760] Speed: 74.907718 samples/sec accuracy=73.395161 loss=1.062940 lr=0.001000 Epoch[056] Batch [1599]/[3760] Speed: 75.368782 samples/sec accuracy=73.416016 loss=1.062619 lr=0.001000 Epoch[056] Batch [1649]/[3760] Speed: 76.185634 samples/sec accuracy=73.386364 loss=1.063706 lr=0.001000 Epoch[056] Batch [1699]/[3760] Speed: 76.511250 samples/sec accuracy=73.393382 loss=1.062744 lr=0.001000 Epoch[056] Batch [1749]/[3760] Speed: 75.261056 samples/sec accuracy=73.415179 loss=1.062184 lr=0.001000 Epoch[056] Batch [1799]/[3760] Speed: 75.780945 samples/sec accuracy=73.408854 loss=1.062653 lr=0.001000 Epoch[056] 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accuracy=73.449728 loss=1.061428 lr=0.001000 Epoch[056] Batch [2349]/[3760] Speed: 76.081487 samples/sec accuracy=73.428191 loss=1.061691 lr=0.001000 Epoch[056] Batch [2399]/[3760] Speed: 75.203510 samples/sec accuracy=73.420573 loss=1.061652 lr=0.001000 Epoch[056] Batch [2449]/[3760] Speed: 77.377570 samples/sec accuracy=73.422832 loss=1.061355 lr=0.001000 Epoch[056] Batch [2499]/[3760] Speed: 74.843061 samples/sec accuracy=73.394375 loss=1.062232 lr=0.001000 Epoch[056] Batch [2549]/[3760] Speed: 76.813487 samples/sec accuracy=73.408701 loss=1.062180 lr=0.001000 Epoch[056] Batch [2599]/[3760] Speed: 73.763034 samples/sec accuracy=73.402644 loss=1.061838 lr=0.001000 Epoch[056] Batch [2649]/[3760] Speed: 78.053078 samples/sec accuracy=73.405660 loss=1.061423 lr=0.001000 Epoch[056] Batch [2699]/[3760] Speed: 74.271339 samples/sec accuracy=73.390625 loss=1.061670 lr=0.001000 Epoch[056] Batch [2749]/[3760] Speed: 76.531673 samples/sec accuracy=73.394318 loss=1.061370 lr=0.001000 Epoch[056] 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accuracy=73.472596 loss=1.058249 lr=0.001000 Epoch[056] Batch [3299]/[3760] Speed: 74.386702 samples/sec accuracy=73.477273 loss=1.058259 lr=0.001000 Epoch[056] Batch [3349]/[3760] Speed: 77.259807 samples/sec accuracy=73.488340 loss=1.057726 lr=0.001000 Epoch[056] Batch [3399]/[3760] Speed: 72.982731 samples/sec accuracy=73.477022 loss=1.058366 lr=0.001000 Epoch[056] Batch [3449]/[3760] Speed: 79.060781 samples/sec accuracy=73.484601 loss=1.058295 lr=0.001000 Epoch[056] Batch [3499]/[3760] Speed: 71.099028 samples/sec accuracy=73.473661 loss=1.058626 lr=0.001000 Epoch[056] Batch [3549]/[3760] Speed: 78.002672 samples/sec accuracy=73.461708 loss=1.058940 lr=0.001000 Epoch[056] Batch [3599]/[3760] Speed: 71.245040 samples/sec accuracy=73.449219 loss=1.059207 lr=0.001000 Epoch[056] Batch [3649]/[3760] Speed: 77.029216 samples/sec accuracy=73.460616 loss=1.058454 lr=0.001000 Epoch[056] Batch [3699]/[3760] Speed: 77.757637 samples/sec accuracy=73.463682 loss=1.058629 lr=0.001000 Epoch[056] Batch [3749]/[3760] Speed: 85.660353 samples/sec accuracy=73.472083 loss=1.058135 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.937500 acc-top5=85.562500 Batch [0099]/[0303]: acc-top1=66.234375 acc-top5=85.625000 Batch [0149]/[0303]: acc-top1=65.791667 acc-top5=85.750000 Batch [0199]/[0303]: acc-top1=65.804688 acc-top5=85.851562 Batch [0249]/[0303]: acc-top1=65.693750 acc-top5=85.887500 Batch [0299]/[0303]: acc-top1=65.770833 acc-top5=85.739583 [Epoch 056] training: accuracy=73.476562 loss=1.057888 [Epoch 056] speed: 75 samples/sec time cost: 3467.306057 [Epoch 056] validation: acc-top1=65.733292 acc-top5=85.751856 loss=1.623392 Epoch[057] Batch [0049]/[3760] Speed: 52.382449 samples/sec accuracy=74.375000 loss=1.019529 lr=0.001000 Epoch[057] Batch [0099]/[3760] Speed: 72.729726 samples/sec accuracy=74.296875 loss=1.014756 lr=0.001000 Epoch[057] Batch [0149]/[3760] Speed: 76.604673 samples/sec accuracy=73.906250 loss=1.029618 lr=0.001000 Epoch[057] Batch [0199]/[3760] Speed: 76.407053 samples/sec accuracy=73.640625 loss=1.032741 lr=0.001000 Epoch[057] Batch [0249]/[3760] Speed: 72.984313 samples/sec accuracy=73.706250 loss=1.034917 lr=0.001000 Epoch[057] Batch [0299]/[3760] Speed: 77.800476 samples/sec accuracy=73.645833 loss=1.038721 lr=0.001000 Epoch[057] Batch [0349]/[3760] Speed: 71.834935 samples/sec accuracy=73.696429 loss=1.037787 lr=0.001000 Epoch[057] Batch [0399]/[3760] Speed: 77.543484 samples/sec accuracy=73.796875 loss=1.039491 lr=0.001000 Epoch[057] Batch [0449]/[3760] Speed: 76.948304 samples/sec accuracy=73.840278 loss=1.037658 lr=0.001000 Epoch[057] Batch [0499]/[3760] Speed: 75.380306 samples/sec accuracy=73.709375 loss=1.043928 lr=0.001000 Epoch[057] Batch [0549]/[3760] Speed: 72.153731 samples/sec accuracy=73.809659 loss=1.040300 lr=0.001000 Epoch[057] Batch [0599]/[3760] Speed: 77.748975 samples/sec accuracy=73.705729 loss=1.045469 lr=0.001000 Epoch[057] Batch [0649]/[3760] Speed: 75.656878 samples/sec accuracy=73.709135 loss=1.044753 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3465.058368 [Epoch 057] validation: acc-top1=65.578589 acc-top5=85.689975 loss=1.615652 Epoch[058] Batch [0049]/[3759] Speed: 52.840562 samples/sec accuracy=73.906250 loss=1.044105 lr=0.001000 Epoch[058] Batch [0099]/[3759] Speed: 74.918448 samples/sec accuracy=74.031250 loss=1.050972 lr=0.001000 Epoch[058] Batch [0149]/[3759] Speed: 75.521428 samples/sec accuracy=74.135417 loss=1.040295 lr=0.001000 Epoch[058] Batch [0199]/[3759] Speed: 76.624952 samples/sec accuracy=74.140625 loss=1.037703 lr=0.001000 Epoch[058] Batch [0249]/[3759] Speed: 75.962449 samples/sec accuracy=74.312500 loss=1.035466 lr=0.001000 Epoch[058] Batch [0299]/[3759] Speed: 76.199223 samples/sec accuracy=74.328125 loss=1.036691 lr=0.001000 Epoch[058] Batch [0349]/[3759] Speed: 74.786335 samples/sec accuracy=74.339286 loss=1.035575 lr=0.001000 Epoch[058] Batch [0399]/[3759] Speed: 77.180668 samples/sec accuracy=74.046875 loss=1.043134 lr=0.001000 Epoch[058] Batch [0449]/[3759] Speed: 75.573877 samples/sec 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[0049]/[0303]: acc-top1=64.968750 acc-top5=85.906250 Batch [0099]/[0303]: acc-top1=65.734375 acc-top5=85.859375 Batch [0149]/[0303]: acc-top1=65.697917 acc-top5=86.041667 Batch [0199]/[0303]: acc-top1=65.835938 acc-top5=86.070312 Batch [0249]/[0303]: acc-top1=65.593750 acc-top5=86.068750 Batch [0299]/[0303]: acc-top1=65.489583 acc-top5=85.942708 [Epoch 058] training: accuracy=73.767541 loss=1.045930 [Epoch 058] speed: 75 samples/sec time cost: 3454.643742 [Epoch 058] validation: acc-top1=65.454827 acc-top5=85.963284 loss=1.605537 Epoch[059] Batch [0049]/[3760] Speed: 53.048285 samples/sec accuracy=74.437500 loss=1.049767 lr=0.001000 Epoch[059] Batch [0099]/[3760] Speed: 74.430804 samples/sec accuracy=73.765625 loss=1.039079 lr=0.001000 Epoch[059] Batch [0149]/[3760] Speed: 76.501567 samples/sec accuracy=74.114583 loss=1.035387 lr=0.001000 Epoch[059] Batch [0199]/[3760] Speed: 73.087059 samples/sec accuracy=73.945312 loss=1.043107 lr=0.001000 Epoch[059] Batch [0249]/[3760] Speed: 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lr=0.001000 Epoch[059] Batch [3599]/[3760] Speed: 75.189214 samples/sec accuracy=74.003472 loss=1.039257 lr=0.001000 Epoch[059] Batch [3649]/[3760] Speed: 74.659780 samples/sec accuracy=73.958476 loss=1.040485 lr=0.001000 Epoch[059] Batch [3699]/[3760] Speed: 74.100434 samples/sec accuracy=73.958193 loss=1.040452 lr=0.001000 Epoch[059] Batch [3749]/[3760] Speed: 87.383681 samples/sec accuracy=73.955417 loss=1.040286 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.593750 acc-top5=85.531250 Batch [0099]/[0303]: acc-top1=65.953125 acc-top5=85.640625 Batch [0149]/[0303]: acc-top1=65.750000 acc-top5=85.718750 Batch [0199]/[0303]: acc-top1=65.828125 acc-top5=85.804688 Batch [0249]/[0303]: acc-top1=65.587500 acc-top5=85.831250 Batch [0299]/[0303]: acc-top1=65.598958 acc-top5=85.739583 [Epoch 059] training: accuracy=73.954870 loss=1.040239 [Epoch 059] speed: 75 samples/sec time cost: 3461.271306 [Epoch 059] validation: acc-top1=65.563119 acc-top5=85.762170 loss=1.631814 Epoch[060] Batch 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accuracy=74.102146 loss=1.030834 lr=0.001000 Epoch[060] Batch [3399]/[3760] Speed: 74.921680 samples/sec accuracy=74.104779 loss=1.030653 lr=0.001000 Epoch[060] Batch [3449]/[3760] Speed: 75.783005 samples/sec accuracy=74.115489 loss=1.029750 lr=0.001000 Epoch[060] Batch [3499]/[3760] Speed: 76.503426 samples/sec accuracy=74.130804 loss=1.029542 lr=0.001000 Epoch[060] Batch [3549]/[3760] Speed: 75.655827 samples/sec accuracy=74.136004 loss=1.029686 lr=0.001000 Epoch[060] Batch [3599]/[3760] Speed: 73.655922 samples/sec accuracy=74.140625 loss=1.029442 lr=0.001000 Epoch[060] Batch [3649]/[3760] Speed: 78.195291 samples/sec accuracy=74.125428 loss=1.030013 lr=0.001000 Epoch[060] Batch [3699]/[3760] Speed: 76.651708 samples/sec accuracy=74.130912 loss=1.029554 lr=0.001000 Epoch[060] Batch [3749]/[3760] Speed: 83.031865 samples/sec accuracy=74.133333 loss=1.029340 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.593750 acc-top5=85.812500 Batch [0099]/[0303]: acc-top1=66.125000 acc-top5=85.796875 Batch [0149]/[0303]: acc-top1=65.843750 acc-top5=85.937500 Batch [0199]/[0303]: acc-top1=66.023438 acc-top5=85.992188 Batch [0249]/[0303]: acc-top1=65.862500 acc-top5=85.956250 Batch [0299]/[0303]: acc-top1=65.890625 acc-top5=85.786458 [Epoch 060] training: accuracy=74.124418 loss=1.029618 [Epoch 060] speed: 75 samples/sec time cost: 3465.947453 [Epoch 060] validation: acc-top1=65.851898 acc-top5=85.808581 loss=1.603924 Epoch[061] Batch [0049]/[3759] Speed: 53.484243 samples/sec accuracy=75.093750 loss=0.982663 lr=0.001000 Epoch[061] Batch [0099]/[3759] Speed: 72.005898 samples/sec accuracy=74.281250 loss=1.006063 lr=0.001000 Epoch[061] Batch [0149]/[3759] Speed: 78.053699 samples/sec accuracy=74.239583 loss=1.010683 lr=0.001000 Epoch[061] Batch [0199]/[3759] Speed: 75.288888 samples/sec accuracy=74.742188 loss=1.001407 lr=0.001000 Epoch[061] Batch [0249]/[3759] Speed: 75.825051 samples/sec accuracy=74.468750 loss=1.006556 lr=0.001000 Epoch[061] Batch [0299]/[3759] 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accuracy=74.330729 loss=1.018888 lr=0.001000 Epoch[061] Batch [3649]/[3759] Speed: 76.803668 samples/sec accuracy=74.314212 loss=1.019139 lr=0.001000 Epoch[061] Batch [3699]/[3759] Speed: 77.192918 samples/sec accuracy=74.317990 loss=1.019264 lr=0.001000 Epoch[061] Batch [3749]/[3759] Speed: 84.093069 samples/sec accuracy=74.323750 loss=1.019365 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.937500 acc-top5=85.562500 Batch [0099]/[0303]: acc-top1=66.078125 acc-top5=85.421875 Batch [0149]/[0303]: acc-top1=65.927083 acc-top5=85.645833 Batch [0199]/[0303]: acc-top1=66.070312 acc-top5=85.710938 Batch [0249]/[0303]: acc-top1=65.918750 acc-top5=85.781250 Batch [0299]/[0303]: acc-top1=65.947917 acc-top5=85.604167 [Epoch 061] training: accuracy=74.326616 loss=1.019430 [Epoch 061] speed: 75 samples/sec time cost: 3459.623936 [Epoch 061] validation: acc-top1=65.918936 acc-top5=85.617781 loss=1.622056 Epoch[062] Batch [0049]/[3760] Speed: 53.673576 samples/sec accuracy=74.718750 loss=0.975227 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acc-top1=66.164062 acc-top5=85.789062 Batch [0249]/[0303]: acc-top1=65.918750 acc-top5=85.818750 Batch [0299]/[0303]: acc-top1=65.932292 acc-top5=85.645833 [Epoch 062] training: accuracy=74.446892 loss=1.016429 [Epoch 062] speed: 75 samples/sec time cost: 3466.855315 [Epoch 062] validation: acc-top1=65.908622 acc-top5=85.648721 loss=1.617767 Epoch[063] Batch [0049]/[3760] Speed: 54.509928 samples/sec accuracy=74.687500 loss=0.973260 lr=0.001000 Epoch[063] Batch [0099]/[3760] Speed: 71.451217 samples/sec accuracy=74.890625 loss=0.979752 lr=0.001000 Epoch[063] Batch [0149]/[3760] Speed: 74.698138 samples/sec accuracy=74.750000 loss=0.997180 lr=0.001000 Epoch[063] Batch [0199]/[3760] Speed: 78.367688 samples/sec accuracy=74.820312 loss=0.987833 lr=0.001000 Epoch[063] Batch [0249]/[3760] Speed: 73.301516 samples/sec accuracy=74.712500 loss=0.993930 lr=0.001000 Epoch[063] Batch [0299]/[3760] Speed: 78.560718 samples/sec accuracy=74.546875 loss=1.003323 lr=0.001000 Epoch[063] Batch 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accuracy=74.540668 loss=1.011552 lr=0.001000 Epoch[063] Batch [3699]/[3760] Speed: 77.315088 samples/sec accuracy=74.514780 loss=1.012473 lr=0.001000 Epoch[063] Batch [3749]/[3760] Speed: 84.042686 samples/sec accuracy=74.523750 loss=1.012389 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.343750 acc-top5=85.468750 Batch [0099]/[0303]: acc-top1=66.750000 acc-top5=85.546875 Batch [0149]/[0303]: acc-top1=66.333333 acc-top5=85.625000 Batch [0199]/[0303]: acc-top1=66.093750 acc-top5=85.750000 Batch [0249]/[0303]: acc-top1=65.800000 acc-top5=85.837500 Batch [0299]/[0303]: acc-top1=65.812500 acc-top5=85.682292 [Epoch 063] training: accuracy=74.525432 loss=1.012252 [Epoch 063] speed: 75 samples/sec time cost: 3460.417353 [Epoch 063] validation: acc-top1=65.790017 acc-top5=85.705446 loss=1.625226 Epoch[064] Batch [0049]/[3759] Speed: 53.740018 samples/sec accuracy=74.187500 loss=1.046708 lr=0.001000 Epoch[064] Batch [0099]/[3759] Speed: 71.675661 samples/sec accuracy=74.640625 loss=1.015736 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lr=0.001000 Epoch[064] Batch [2999]/[3759] Speed: 78.360746 samples/sec accuracy=74.806250 loss=1.002872 lr=0.001000 Epoch[064] Batch [3049]/[3759] Speed: 74.843168 samples/sec accuracy=74.793033 loss=1.003551 lr=0.001000 Epoch[064] Batch [3099]/[3759] Speed: 74.496314 samples/sec accuracy=74.798891 loss=1.003406 lr=0.001000 Epoch[064] Batch [3149]/[3759] Speed: 76.931352 samples/sec accuracy=74.782242 loss=1.003815 lr=0.001000 Epoch[064] Batch [3199]/[3759] Speed: 74.992834 samples/sec accuracy=74.780273 loss=1.004334 lr=0.001000 Epoch[064] Batch [3249]/[3759] Speed: 77.106470 samples/sec accuracy=74.775000 loss=1.004677 lr=0.001000 Epoch[064] Batch [3299]/[3759] Speed: 75.306321 samples/sec accuracy=74.783617 loss=1.004383 lr=0.001000 Epoch[064] Batch [3349]/[3759] Speed: 76.408668 samples/sec accuracy=74.773787 loss=1.004600 lr=0.001000 Epoch[064] Batch [3399]/[3759] Speed: 74.055658 samples/sec accuracy=74.760110 loss=1.005079 lr=0.001000 Epoch[064] Batch [3449]/[3759] Speed: 78.228190 samples/sec accuracy=74.750453 loss=1.005680 lr=0.001000 Epoch[064] Batch [3499]/[3759] Speed: 71.441722 samples/sec accuracy=74.732589 loss=1.006052 lr=0.001000 Epoch[064] Batch [3549]/[3759] Speed: 79.441100 samples/sec accuracy=74.747799 loss=1.005738 lr=0.001000 Epoch[064] Batch [3599]/[3759] Speed: 76.986003 samples/sec accuracy=74.759549 loss=1.005339 lr=0.001000 Epoch[064] Batch [3649]/[3759] Speed: 75.904696 samples/sec accuracy=74.763271 loss=1.005208 lr=0.001000 Epoch[064] Batch [3699]/[3759] Speed: 75.290023 samples/sec accuracy=74.773649 loss=1.004908 lr=0.001000 Epoch[064] Batch [3749]/[3759] Speed: 86.489649 samples/sec accuracy=74.764167 loss=1.004813 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.656250 acc-top5=85.812500 Batch [0099]/[0303]: acc-top1=65.859375 acc-top5=85.703125 Batch [0149]/[0303]: acc-top1=65.593750 acc-top5=85.885417 Batch [0199]/[0303]: acc-top1=65.679688 acc-top5=85.859375 Batch [0249]/[0303]: acc-top1=65.387500 acc-top5=85.806250 Batch [0299]/[0303]: acc-top1=65.505208 acc-top5=85.666667 [Epoch 064] training: accuracy=74.763069 loss=1.004649 [Epoch 064] speed: 75 samples/sec time cost: 3457.897444 [Epoch 064] validation: acc-top1=65.459983 acc-top5=85.684818 loss=1.623084 Epoch[065] Batch [0049]/[3760] Speed: 53.712357 samples/sec accuracy=74.437500 loss=0.988421 lr=0.001000 Epoch[065] Batch [0099]/[3760] Speed: 72.139661 samples/sec accuracy=75.109375 loss=0.975508 lr=0.001000 Epoch[065] Batch [0149]/[3760] Speed: 76.775890 samples/sec accuracy=75.645833 loss=0.968701 lr=0.001000 Epoch[065] Batch [0199]/[3760] Speed: 75.993083 samples/sec accuracy=75.625000 loss=0.967367 lr=0.001000 Epoch[065] Batch [0249]/[3760] Speed: 75.495977 samples/sec accuracy=75.356250 loss=0.978389 lr=0.001000 Epoch[065] Batch [0299]/[3760] Speed: 75.040026 samples/sec accuracy=75.135417 loss=0.985449 lr=0.001000 Epoch[065] Batch [0349]/[3760] Speed: 75.858625 samples/sec accuracy=75.022321 loss=0.987174 lr=0.001000 Epoch[065] Batch 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accuracy=74.901705 loss=0.994214 lr=0.001000 Epoch[065] Batch [2799]/[3760] Speed: 76.297615 samples/sec accuracy=74.913504 loss=0.993738 lr=0.001000 Epoch[065] Batch [2849]/[3760] Speed: 73.578668 samples/sec accuracy=74.895833 loss=0.994209 lr=0.001000 Epoch[065] Batch [2899]/[3760] Speed: 76.800466 samples/sec accuracy=74.894935 loss=0.994655 lr=0.001000 Epoch[065] Batch [2949]/[3760] Speed: 76.544137 samples/sec accuracy=74.896186 loss=0.994688 lr=0.001000 Epoch[065] Batch [2999]/[3760] Speed: 74.927486 samples/sec accuracy=74.908333 loss=0.994502 lr=0.001000 Epoch[065] Batch [3049]/[3760] Speed: 77.741688 samples/sec accuracy=74.907787 loss=0.994150 lr=0.001000 Epoch[065] Batch [3099]/[3760] Speed: 74.393416 samples/sec accuracy=74.909274 loss=0.994408 lr=0.001000 Epoch[065] Batch [3149]/[3760] Speed: 77.524071 samples/sec accuracy=74.888889 loss=0.995346 lr=0.001000 Epoch[065] Batch [3199]/[3760] Speed: 74.828689 samples/sec accuracy=74.887207 loss=0.995560 lr=0.001000 Epoch[065] 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accuracy=74.820946 loss=0.998967 lr=0.001000 Epoch[065] Batch [3749]/[3760] Speed: 85.624747 samples/sec accuracy=74.824167 loss=0.998869 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.093750 acc-top5=85.531250 Batch [0099]/[0303]: acc-top1=65.921875 acc-top5=85.312500 Batch [0149]/[0303]: acc-top1=65.760417 acc-top5=85.468750 Batch [0199]/[0303]: acc-top1=65.960938 acc-top5=85.531250 Batch [0249]/[0303]: acc-top1=65.662500 acc-top5=85.568750 Batch [0299]/[0303]: acc-top1=65.630208 acc-top5=85.468750 [Epoch 065] training: accuracy=74.828374 loss=0.998860 [Epoch 065] speed: 75 samples/sec time cost: 3469.968396 [Epoch 065] validation: acc-top1=65.578589 acc-top5=85.478548 loss=1.632343 Epoch[066] Batch [0049]/[3759] Speed: 53.733756 samples/sec accuracy=76.375000 loss=0.981109 lr=0.001000 Epoch[066] Batch [0099]/[3759] Speed: 72.039227 samples/sec accuracy=75.281250 loss=0.996256 lr=0.001000 Epoch[066] Batch [0149]/[3759] Speed: 78.313694 samples/sec accuracy=75.364583 loss=0.989655 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lr=0.001000 Epoch[066] Batch [2099]/[3759] Speed: 74.710022 samples/sec accuracy=75.235863 loss=0.989537 lr=0.001000 Epoch[066] Batch [2149]/[3759] Speed: 76.517776 samples/sec accuracy=75.214390 loss=0.989604 lr=0.001000 Epoch[066] Batch [2199]/[3759] Speed: 76.458990 samples/sec accuracy=75.213068 loss=0.988945 lr=0.001000 Epoch[066] Batch [2249]/[3759] Speed: 76.907979 samples/sec accuracy=75.230556 loss=0.988335 lr=0.001000 Epoch[066] Batch [2299]/[3759] Speed: 75.949885 samples/sec accuracy=75.222826 loss=0.989189 lr=0.001000 Epoch[066] Batch [2349]/[3759] Speed: 74.615281 samples/sec accuracy=75.235372 loss=0.988847 lr=0.001000 Epoch[066] Batch [2399]/[3759] Speed: 76.587521 samples/sec accuracy=75.231120 loss=0.988611 lr=0.001000 Epoch[066] Batch [2449]/[3759] Speed: 76.026363 samples/sec accuracy=75.250000 loss=0.988040 lr=0.001000 Epoch[066] Batch [2499]/[3759] Speed: 76.272132 samples/sec accuracy=75.228750 loss=0.989046 lr=0.001000 Epoch[066] Batch [2549]/[3759] Speed: 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lr=0.001000 Epoch[066] Batch [3049]/[3759] Speed: 77.595444 samples/sec accuracy=75.160861 loss=0.990850 lr=0.001000 Epoch[066] Batch [3099]/[3759] Speed: 75.865275 samples/sec accuracy=75.152722 loss=0.990968 lr=0.001000 Epoch[066] Batch [3149]/[3759] Speed: 76.456746 samples/sec accuracy=75.139881 loss=0.991277 lr=0.001000 Epoch[066] Batch [3199]/[3759] Speed: 76.156460 samples/sec accuracy=75.132324 loss=0.991827 lr=0.001000 Epoch[066] Batch [3249]/[3759] Speed: 75.672689 samples/sec accuracy=75.137981 loss=0.991471 lr=0.001000 Epoch[066] Batch [3299]/[3759] Speed: 76.780266 samples/sec accuracy=75.124527 loss=0.991644 lr=0.001000 Epoch[066] Batch [3349]/[3759] Speed: 74.780776 samples/sec accuracy=75.133396 loss=0.991548 lr=0.001000 Epoch[066] Batch [3399]/[3759] Speed: 76.709445 samples/sec accuracy=75.122702 loss=0.991528 lr=0.001000 Epoch[066] Batch [3449]/[3759] Speed: 75.394329 samples/sec accuracy=75.134511 loss=0.991240 lr=0.001000 Epoch[066] Batch [3499]/[3759] Speed: 76.648095 samples/sec accuracy=75.098214 loss=0.992201 lr=0.001000 Epoch[066] Batch [3549]/[3759] Speed: 76.670113 samples/sec accuracy=75.089349 loss=0.991951 lr=0.001000 Epoch[066] Batch [3599]/[3759] Speed: 73.307773 samples/sec accuracy=75.074653 loss=0.992526 lr=0.001000 Epoch[066] Batch [3649]/[3759] Speed: 76.664375 samples/sec accuracy=75.052226 loss=0.993292 lr=0.001000 Epoch[066] Batch [3699]/[3759] Speed: 77.313854 samples/sec accuracy=75.044764 loss=0.993050 lr=0.001000 Epoch[066] Batch [3749]/[3759] Speed: 83.411245 samples/sec accuracy=75.035417 loss=0.993423 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.218750 acc-top5=85.250000 Batch [0099]/[0303]: acc-top1=66.406250 acc-top5=85.500000 Batch [0149]/[0303]: acc-top1=66.177083 acc-top5=85.750000 Batch [0199]/[0303]: acc-top1=66.054688 acc-top5=85.820312 Batch [0249]/[0303]: acc-top1=65.718750 acc-top5=85.756250 Batch [0299]/[0303]: acc-top1=65.739583 acc-top5=85.635417 [Epoch 066] training: accuracy=75.029928 loss=0.993547 [Epoch 066] speed: 75 samples/sec time cost: 3460.806910 [Epoch 066] validation: acc-top1=65.686881 acc-top5=85.633251 loss=1.633109 Epoch[067] Batch [0049]/[3760] Speed: 53.964444 samples/sec accuracy=74.312500 loss=1.035161 lr=0.001000 Epoch[067] Batch [0099]/[3760] Speed: 72.579804 samples/sec accuracy=74.562500 loss=1.009678 lr=0.001000 Epoch[067] Batch [0149]/[3760] Speed: 76.944114 samples/sec accuracy=74.739583 loss=1.004378 lr=0.001000 Epoch[067] Batch [0199]/[3760] Speed: 78.646934 samples/sec accuracy=75.226562 loss=0.983003 lr=0.001000 Epoch[067] Batch [0249]/[3760] Speed: 73.924574 samples/sec accuracy=75.212500 loss=0.984297 lr=0.001000 Epoch[067] Batch [0299]/[3760] Speed: 76.404459 samples/sec accuracy=75.171875 loss=0.987554 lr=0.001000 Epoch[067] Batch [0349]/[3760] Speed: 75.431486 samples/sec accuracy=75.209821 loss=0.990229 lr=0.001000 Epoch[067] Batch [0399]/[3760] Speed: 74.556011 samples/sec accuracy=75.148438 loss=0.989561 lr=0.001000 Epoch[067] Batch 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accuracy=75.267361 loss=0.981212 lr=0.001000 Epoch[067] Batch [0949]/[3760] Speed: 73.401931 samples/sec accuracy=75.297697 loss=0.979464 lr=0.001000 Epoch[067] Batch [0999]/[3760] Speed: 78.004519 samples/sec accuracy=75.254687 loss=0.981736 lr=0.001000 Epoch[067] Batch [1049]/[3760] Speed: 76.569105 samples/sec accuracy=75.266369 loss=0.981702 lr=0.001000 Epoch[067] Batch [1099]/[3760] Speed: 75.406274 samples/sec accuracy=75.205966 loss=0.983538 lr=0.001000 Epoch[067] Batch [1149]/[3760] Speed: 76.322307 samples/sec accuracy=75.222826 loss=0.982777 lr=0.001000 Epoch[067] Batch [1199]/[3760] Speed: 76.412470 samples/sec accuracy=75.230469 loss=0.982299 lr=0.001000 Epoch[067] Batch [1249]/[3760] Speed: 76.350588 samples/sec accuracy=75.230000 loss=0.981993 lr=0.001000 Epoch[067] Batch [1299]/[3760] Speed: 74.562394 samples/sec accuracy=75.191106 loss=0.983598 lr=0.001000 Epoch[067] Batch [1349]/[3760] Speed: 77.203745 samples/sec accuracy=75.173611 loss=0.983684 lr=0.001000 Epoch[067] 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accuracy=75.084167 loss=0.989344 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.781250 acc-top5=86.062500 Batch [0099]/[0303]: acc-top1=65.953125 acc-top5=85.906250 Batch [0149]/[0303]: acc-top1=65.833333 acc-top5=85.833333 Batch [0199]/[0303]: acc-top1=65.828125 acc-top5=85.859375 Batch [0249]/[0303]: acc-top1=65.693750 acc-top5=85.781250 Batch [0299]/[0303]: acc-top1=65.734375 acc-top5=85.640625 [Epoch 067] training: accuracy=75.081449 loss=0.989574 [Epoch 067] speed: 75 samples/sec time cost: 3461.962349 [Epoch 067] validation: acc-top1=65.692038 acc-top5=85.664191 loss=1.639880 Epoch[068] Batch [0049]/[3760] Speed: 54.332218 samples/sec accuracy=74.656250 loss=0.992071 lr=0.001000 Epoch[068] Batch [0099]/[3760] Speed: 68.549391 samples/sec accuracy=75.218750 loss=0.984258 lr=0.001000 Epoch[068] Batch [0149]/[3760] Speed: 75.062529 samples/sec accuracy=75.208333 loss=0.978747 lr=0.001000 Epoch[068] Batch [0199]/[3760] Speed: 80.027042 samples/sec accuracy=74.843750 loss=0.999236 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lr=0.001000 Epoch[068] Batch [3099]/[3760] Speed: 76.177614 samples/sec accuracy=75.177419 loss=0.982559 lr=0.001000 Epoch[068] Batch [3149]/[3760] Speed: 74.934777 samples/sec accuracy=75.180060 loss=0.982593 lr=0.001000 Epoch[068] Batch [3199]/[3760] Speed: 75.187914 samples/sec accuracy=75.187012 loss=0.982574 lr=0.001000 Epoch[068] Batch [3249]/[3760] Speed: 77.456695 samples/sec accuracy=75.172115 loss=0.982940 lr=0.001000 Epoch[068] Batch [3299]/[3760] Speed: 71.946442 samples/sec accuracy=75.161458 loss=0.983249 lr=0.001000 Epoch[068] Batch [3349]/[3760] Speed: 79.914047 samples/sec accuracy=75.157183 loss=0.983613 lr=0.001000 Epoch[068] Batch [3399]/[3760] Speed: 73.685812 samples/sec accuracy=75.128217 loss=0.984558 lr=0.001000 Epoch[068] Batch [3449]/[3760] Speed: 77.942983 samples/sec accuracy=75.153533 loss=0.984022 lr=0.001000 Epoch[068] Batch [3499]/[3760] Speed: 76.162094 samples/sec accuracy=75.163393 loss=0.983779 lr=0.001000 Epoch[068] Batch [3549]/[3760] Speed: 74.770572 samples/sec accuracy=75.171655 loss=0.983941 lr=0.001000 Epoch[068] Batch [3599]/[3760] Speed: 76.402258 samples/sec accuracy=75.151042 loss=0.984295 lr=0.001000 Epoch[068] Batch [3649]/[3760] Speed: 77.239655 samples/sec accuracy=75.144264 loss=0.984669 lr=0.001000 Epoch[068] Batch [3699]/[3760] Speed: 73.648874 samples/sec accuracy=75.157939 loss=0.984291 lr=0.001000 Epoch[068] Batch [3749]/[3760] Speed: 85.307089 samples/sec accuracy=75.158333 loss=0.984165 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.750000 acc-top5=85.000000 Batch [0099]/[0303]: acc-top1=66.109375 acc-top5=85.296875 Batch [0149]/[0303]: acc-top1=66.145833 acc-top5=85.625000 Batch [0199]/[0303]: acc-top1=65.945312 acc-top5=85.835938 Batch [0249]/[0303]: acc-top1=65.731250 acc-top5=85.768750 Batch [0299]/[0303]: acc-top1=65.723958 acc-top5=85.625000 [Epoch 068] training: accuracy=75.148354 loss=0.984251 [Epoch 068] speed: 75 samples/sec time cost: 3463.944646 [Epoch 068] validation: acc-top1=65.702351 acc-top5=85.643564 loss=1.622094 Epoch[069] Batch [0049]/[3759] Speed: 53.969414 samples/sec accuracy=76.937500 loss=0.917332 lr=0.001000 Epoch[069] Batch [0099]/[3759] Speed: 71.630644 samples/sec accuracy=76.734375 loss=0.935181 lr=0.001000 Epoch[069] Batch [0149]/[3759] Speed: 77.280051 samples/sec accuracy=76.218750 loss=0.941321 lr=0.001000 Epoch[069] Batch [0199]/[3759] Speed: 78.052885 samples/sec accuracy=76.335938 loss=0.936334 lr=0.001000 Epoch[069] Batch [0249]/[3759] Speed: 73.766650 samples/sec accuracy=76.012500 loss=0.946900 lr=0.001000 Epoch[069] Batch [0299]/[3759] Speed: 75.760607 samples/sec accuracy=75.859375 loss=0.944150 lr=0.001000 Epoch[069] Batch [0349]/[3759] Speed: 76.201423 samples/sec accuracy=75.866071 loss=0.944590 lr=0.001000 Epoch[069] Batch [0399]/[3759] Speed: 75.165242 samples/sec accuracy=75.750000 loss=0.952813 lr=0.001000 Epoch[069] Batch [0449]/[3759] Speed: 77.576095 samples/sec accuracy=75.732639 loss=0.958303 lr=0.001000 Epoch[069] Batch 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[0099]/[0303]: acc-top1=66.359375 acc-top5=85.656250 Batch [0149]/[0303]: acc-top1=66.270833 acc-top5=85.635417 Batch [0199]/[0303]: acc-top1=66.203125 acc-top5=85.703125 Batch [0249]/[0303]: acc-top1=65.931250 acc-top5=85.693750 Batch [0299]/[0303]: acc-top1=65.906250 acc-top5=85.541667 [Epoch 069] training: accuracy=75.483839 loss=0.974646 [Epoch 069] speed: 75 samples/sec time cost: 3459.261780 [Epoch 069] validation: acc-top1=65.857054 acc-top5=85.545586 loss=1.657992 Epoch[070] Batch [0049]/[3760] Speed: 52.729272 samples/sec accuracy=75.406250 loss=0.945534 lr=0.001000 Epoch[070] Batch [0099]/[3760] Speed: 74.508808 samples/sec accuracy=75.593750 loss=0.957847 lr=0.001000 Epoch[070] Batch [0149]/[3760] Speed: 76.938389 samples/sec accuracy=75.510417 loss=0.965859 lr=0.001000 Epoch[070] Batch [0199]/[3760] Speed: 75.104306 samples/sec accuracy=75.601562 loss=0.961512 lr=0.001000 Epoch[070] Batch [0249]/[3760] Speed: 74.882427 samples/sec accuracy=75.712500 loss=0.958725 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lr=0.001000 Epoch[070] Batch [3149]/[3760] Speed: 76.641179 samples/sec accuracy=75.572421 loss=0.970122 lr=0.001000 Epoch[070] Batch [3199]/[3760] Speed: 75.127977 samples/sec accuracy=75.584961 loss=0.969793 lr=0.001000 Epoch[070] Batch [3249]/[3760] Speed: 74.829656 samples/sec accuracy=75.599519 loss=0.969577 lr=0.001000 Epoch[070] Batch [3299]/[3760] Speed: 76.822001 samples/sec accuracy=75.589015 loss=0.969884 lr=0.001000 Epoch[070] Batch [3349]/[3760] Speed: 74.368886 samples/sec accuracy=75.584422 loss=0.970329 lr=0.001000 Epoch[070] Batch [3399]/[3760] Speed: 75.964248 samples/sec accuracy=75.579044 loss=0.970508 lr=0.001000 Epoch[070] Batch [3449]/[3760] Speed: 75.054089 samples/sec accuracy=75.586051 loss=0.970441 lr=0.001000 Epoch[070] Batch [3499]/[3760] Speed: 76.847896 samples/sec accuracy=75.568750 loss=0.971051 lr=0.001000 Epoch[070] Batch [3549]/[3760] Speed: 74.277261 samples/sec accuracy=75.546215 loss=0.971674 lr=0.001000 Epoch[070] Batch [3599]/[3760] Speed: 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accuracy=76.218750 loss=0.923140 lr=0.001000 Epoch[071] Batch [0099]/[3760] Speed: 70.814171 samples/sec accuracy=75.687500 loss=0.943624 lr=0.001000 Epoch[071] Batch [0149]/[3760] Speed: 76.204125 samples/sec accuracy=75.635417 loss=0.950726 lr=0.001000 Epoch[071] Batch [0199]/[3760] Speed: 77.174488 samples/sec accuracy=75.914062 loss=0.944218 lr=0.001000 Epoch[071] Batch [0249]/[3760] Speed: 74.524213 samples/sec accuracy=76.162500 loss=0.938189 lr=0.001000 Epoch[071] Batch [0299]/[3760] Speed: 76.006490 samples/sec accuracy=76.010417 loss=0.941949 lr=0.001000 Epoch[071] Batch [0349]/[3760] Speed: 72.893493 samples/sec accuracy=75.991071 loss=0.943983 lr=0.001000 Epoch[071] Batch [0399]/[3760] Speed: 77.203506 samples/sec accuracy=76.027344 loss=0.944981 lr=0.001000 Epoch[071] Batch [0449]/[3760] Speed: 76.090566 samples/sec accuracy=76.027778 loss=0.948251 lr=0.001000 Epoch[071] Batch [0499]/[3760] Speed: 75.110474 samples/sec accuracy=76.031250 loss=0.948338 lr=0.001000 Epoch[071] 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acc-top5=85.510417 Batch [0199]/[0303]: acc-top1=65.726562 acc-top5=85.601562 Batch [0249]/[0303]: acc-top1=65.493750 acc-top5=85.600000 Batch [0299]/[0303]: acc-top1=65.510417 acc-top5=85.500000 [Epoch 071] training: accuracy=75.764212 loss=0.962276 [Epoch 071] speed: 75 samples/sec time cost: 3463.437766 [Epoch 071] validation: acc-top1=65.496081 acc-top5=85.504332 loss=1.656881 Epoch[072] Batch [0049]/[3759] Speed: 52.378300 samples/sec accuracy=76.593750 loss=0.917570 lr=0.001000 Epoch[072] Batch [0099]/[3759] Speed: 74.446901 samples/sec accuracy=75.734375 loss=0.952353 lr=0.001000 Epoch[072] Batch [0149]/[3759] Speed: 77.057506 samples/sec accuracy=75.875000 loss=0.954520 lr=0.001000 Epoch[072] Batch [0199]/[3759] Speed: 77.110288 samples/sec accuracy=76.101562 loss=0.947722 lr=0.001000 Epoch[072] Batch [0249]/[3759] Speed: 75.985238 samples/sec accuracy=76.218750 loss=0.941456 lr=0.001000 Epoch[072] Batch [0299]/[3759] Speed: 75.751935 samples/sec accuracy=76.317708 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[0249]/[0303]: acc-top1=65.606250 acc-top5=85.531250 Batch [0299]/[0303]: acc-top1=65.536458 acc-top5=85.322917 [Epoch 073] training: accuracy=75.840259 loss=0.957950 [Epoch 073] speed: 75 samples/sec time cost: 3460.748361 [Epoch 073] validation: acc-top1=65.501238 acc-top5=85.323845 loss=1.657085 Epoch[074] Batch [0049]/[3760] Speed: 54.420691 samples/sec accuracy=76.843750 loss=0.905405 lr=0.001000 Epoch[074] Batch [0099]/[3760] Speed: 70.326436 samples/sec accuracy=76.843750 loss=0.913172 lr=0.001000 Epoch[074] Batch [0149]/[3760] Speed: 78.202660 samples/sec accuracy=76.666667 loss=0.932436 lr=0.001000 Epoch[074] Batch [0199]/[3760] Speed: 75.707114 samples/sec accuracy=76.531250 loss=0.935751 lr=0.001000 Epoch[074] Batch [0249]/[3760] Speed: 74.016255 samples/sec accuracy=76.693750 loss=0.930894 lr=0.001000 Epoch[074] Batch [0299]/[3760] Speed: 77.179409 samples/sec accuracy=76.703125 loss=0.932471 lr=0.001000 Epoch[074] Batch [0349]/[3760] Speed: 74.963982 samples/sec 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accuracy=76.261806 loss=0.940645 lr=0.001000 Epoch[074] Batch [2299]/[3760] Speed: 74.316452 samples/sec accuracy=76.232337 loss=0.942028 lr=0.001000 Epoch[074] Batch [2349]/[3760] Speed: 75.098241 samples/sec accuracy=76.227394 loss=0.942619 lr=0.001000 Epoch[074] Batch [2399]/[3760] Speed: 77.015876 samples/sec accuracy=76.235026 loss=0.942796 lr=0.001000 Epoch[074] Batch [2449]/[3760] Speed: 75.630708 samples/sec accuracy=76.213010 loss=0.943626 lr=0.001000 Epoch[074] Batch [2499]/[3760] Speed: 76.629749 samples/sec accuracy=76.196250 loss=0.944178 lr=0.001000 Epoch[074] Batch [2549]/[3760] Speed: 74.745448 samples/sec accuracy=76.169730 loss=0.944972 lr=0.001000 Epoch[074] Batch [2599]/[3760] Speed: 77.264521 samples/sec accuracy=76.179688 loss=0.944592 lr=0.001000 Epoch[074] Batch [2649]/[3760] Speed: 74.598205 samples/sec accuracy=76.163325 loss=0.945385 lr=0.001000 Epoch[074] Batch [2699]/[3760] Speed: 75.469173 samples/sec accuracy=76.170139 loss=0.945029 lr=0.001000 Epoch[074] 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accuracy=76.119141 loss=0.946723 lr=0.001000 Epoch[074] Batch [3249]/[3760] Speed: 76.732894 samples/sec accuracy=76.136538 loss=0.945997 lr=0.001000 Epoch[074] Batch [3299]/[3760] Speed: 73.854103 samples/sec accuracy=76.117424 loss=0.946546 lr=0.001000 Epoch[074] Batch [3349]/[3760] Speed: 76.347780 samples/sec accuracy=76.109142 loss=0.946636 lr=0.001000 Epoch[074] Batch [3399]/[3760] Speed: 77.213645 samples/sec accuracy=76.101562 loss=0.946682 lr=0.001000 Epoch[074] Batch [3449]/[3760] Speed: 74.334874 samples/sec accuracy=76.099638 loss=0.946996 lr=0.001000 Epoch[074] Batch [3499]/[3760] Speed: 78.161972 samples/sec accuracy=76.091518 loss=0.947271 lr=0.001000 Epoch[074] Batch [3549]/[3760] Speed: 76.492406 samples/sec accuracy=76.098151 loss=0.947041 lr=0.001000 Epoch[074] Batch [3599]/[3760] Speed: 74.083731 samples/sec accuracy=76.110677 loss=0.946740 lr=0.001000 Epoch[074] Batch [3649]/[3760] Speed: 77.851614 samples/sec accuracy=76.094606 loss=0.947143 lr=0.001000 Epoch[074] 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lr=0.001000 Epoch[075] Batch [3499]/[3759] Speed: 72.679826 samples/sec accuracy=76.239732 loss=0.944017 lr=0.001000 Epoch[075] Batch [3549]/[3759] Speed: 77.551481 samples/sec accuracy=76.265405 loss=0.943662 lr=0.001000 Epoch[075] Batch [3599]/[3759] Speed: 77.169631 samples/sec accuracy=76.279080 loss=0.943267 lr=0.001000 Epoch[075] Batch [3649]/[3759] Speed: 77.057948 samples/sec accuracy=76.287243 loss=0.942747 lr=0.001000 Epoch[075] Batch [3699]/[3759] Speed: 73.563510 samples/sec accuracy=76.292652 loss=0.942774 lr=0.001000 Epoch[075] Batch [3749]/[3759] Speed: 86.585791 samples/sec accuracy=76.280000 loss=0.943159 lr=0.001000 Batch [0049]/[0303]: acc-top1=64.781250 acc-top5=85.437500 Batch [0099]/[0303]: acc-top1=65.265625 acc-top5=85.531250 Batch [0149]/[0303]: acc-top1=65.166667 acc-top5=85.666667 Batch [0199]/[0303]: acc-top1=65.234375 acc-top5=85.546875 Batch [0249]/[0303]: acc-top1=65.062500 acc-top5=85.500000 Batch [0299]/[0303]: acc-top1=65.192708 acc-top5=85.401042 [Epoch 075] training: accuracy=76.266544 loss=0.943612 [Epoch 075] speed: 75 samples/sec time cost: 3461.184038 [Epoch 075] validation: acc-top1=65.181518 acc-top5=85.411510 loss=1.684895 Epoch[076] Batch [0049]/[3760] Speed: 53.960870 samples/sec accuracy=75.687500 loss=0.946488 lr=0.001000 Epoch[076] Batch [0099]/[3760] Speed: 73.312049 samples/sec accuracy=76.187500 loss=0.932038 lr=0.001000 Epoch[076] Batch [0149]/[3760] Speed: 76.328599 samples/sec accuracy=76.385417 loss=0.927478 lr=0.001000 Epoch[076] Batch [0199]/[3760] Speed: 75.317975 samples/sec accuracy=76.226562 loss=0.929285 lr=0.001000 Epoch[076] Batch [0249]/[3760] Speed: 75.498154 samples/sec accuracy=76.393750 loss=0.922813 lr=0.001000 Epoch[076] Batch [0299]/[3760] Speed: 74.465067 samples/sec accuracy=76.411458 loss=0.924423 lr=0.001000 Epoch[076] Batch [0349]/[3760] Speed: 76.848363 samples/sec accuracy=76.540179 loss=0.922569 lr=0.001000 Epoch[076] Batch [0399]/[3760] Speed: 75.783438 samples/sec accuracy=76.539062 loss=0.921674 lr=0.001000 Epoch[076] Batch [0449]/[3760] Speed: 75.959122 samples/sec accuracy=76.447917 loss=0.922607 lr=0.001000 Epoch[076] Batch [0499]/[3760] Speed: 75.229425 samples/sec accuracy=76.609375 loss=0.920156 lr=0.001000 Epoch[076] Batch [0549]/[3760] Speed: 77.229560 samples/sec accuracy=76.545455 loss=0.922982 lr=0.001000 Epoch[076] Batch [0599]/[3760] Speed: 75.522009 samples/sec accuracy=76.500000 loss=0.925077 lr=0.001000 Epoch[076] Batch [0649]/[3760] Speed: 75.469538 samples/sec accuracy=76.435096 loss=0.926694 lr=0.001000 Epoch[076] Batch [0699]/[3760] Speed: 76.828900 samples/sec accuracy=76.468750 loss=0.924587 lr=0.001000 Epoch[076] Batch [0749]/[3760] Speed: 74.400054 samples/sec accuracy=76.545833 loss=0.925136 lr=0.001000 Epoch[076] Batch [0799]/[3760] Speed: 76.815337 samples/sec accuracy=76.580078 loss=0.925766 lr=0.001000 Epoch[076] Batch [0849]/[3760] Speed: 75.125128 samples/sec accuracy=76.573529 loss=0.925351 lr=0.001000 Epoch[076] 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accuracy=76.501157 loss=0.932054 lr=0.001000 Epoch[076] Batch [1399]/[3760] Speed: 75.308685 samples/sec accuracy=76.477679 loss=0.932790 lr=0.001000 Epoch[076] Batch [1449]/[3760] Speed: 74.941337 samples/sec accuracy=76.471983 loss=0.933086 lr=0.001000 Epoch[076] Batch [1499]/[3760] Speed: 76.791148 samples/sec accuracy=76.492708 loss=0.932278 lr=0.001000 Epoch[076] Batch [1549]/[3760] Speed: 76.519448 samples/sec accuracy=76.546371 loss=0.930192 lr=0.001000 Epoch[076] Batch [1599]/[3760] Speed: 74.605838 samples/sec accuracy=76.552734 loss=0.930143 lr=0.001000 Epoch[076] Batch [1649]/[3760] Speed: 76.570904 samples/sec accuracy=76.504735 loss=0.931526 lr=0.001000 Epoch[076] Batch [1699]/[3760] Speed: 74.527022 samples/sec accuracy=76.503676 loss=0.931114 lr=0.001000 Epoch[076] Batch [1749]/[3760] Speed: 76.913339 samples/sec accuracy=76.505357 loss=0.931655 lr=0.001000 Epoch[076] Batch [1799]/[3760] Speed: 74.205440 samples/sec accuracy=76.541667 loss=0.930408 lr=0.001000 Epoch[076] 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accuracy=76.411685 loss=0.935807 lr=0.001000 Epoch[076] Batch [2349]/[3760] Speed: 76.855547 samples/sec accuracy=76.384973 loss=0.937026 lr=0.001000 Epoch[076] Batch [2399]/[3760] Speed: 74.264813 samples/sec accuracy=76.357422 loss=0.938291 lr=0.001000 Epoch[076] Batch [2449]/[3760] Speed: 74.468887 samples/sec accuracy=76.355867 loss=0.938410 lr=0.001000 Epoch[076] Batch [2499]/[3760] Speed: 77.468395 samples/sec accuracy=76.386875 loss=0.937465 lr=0.001000 Epoch[076] Batch [2549]/[3760] Speed: 74.373223 samples/sec accuracy=76.390931 loss=0.937320 lr=0.001000 Epoch[076] Batch [2599]/[3760] Speed: 77.118427 samples/sec accuracy=76.384615 loss=0.937307 lr=0.001000 Epoch[076] Batch [2649]/[3760] Speed: 76.857765 samples/sec accuracy=76.377948 loss=0.937212 lr=0.001000 Epoch[076] Batch [2699]/[3760] Speed: 75.746405 samples/sec accuracy=76.380787 loss=0.937371 lr=0.001000 Epoch[076] Batch [2749]/[3760] Speed: 75.817625 samples/sec accuracy=76.402841 loss=0.936517 lr=0.001000 Epoch[076] 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accuracy=76.377404 loss=0.936752 lr=0.001000 Epoch[076] Batch [3299]/[3760] Speed: 77.167596 samples/sec accuracy=76.383523 loss=0.937111 lr=0.001000 Epoch[076] Batch [3349]/[3760] Speed: 73.709737 samples/sec accuracy=76.379198 loss=0.937461 lr=0.001000 Epoch[076] Batch [3399]/[3760] Speed: 77.135217 samples/sec accuracy=76.388787 loss=0.937072 lr=0.001000 Epoch[076] Batch [3449]/[3760] Speed: 73.594106 samples/sec accuracy=76.388587 loss=0.937603 lr=0.001000 Epoch[076] Batch [3499]/[3760] Speed: 78.742844 samples/sec accuracy=76.396429 loss=0.937827 lr=0.001000 Epoch[076] Batch [3549]/[3760] Speed: 75.842529 samples/sec accuracy=76.388204 loss=0.938067 lr=0.001000 Epoch[076] Batch [3599]/[3760] Speed: 75.727956 samples/sec accuracy=76.371528 loss=0.939021 lr=0.001000 Epoch[076] Batch [3649]/[3760] Speed: 76.013841 samples/sec accuracy=76.365154 loss=0.938796 lr=0.001000 Epoch[076] Batch [3699]/[3760] Speed: 77.445626 samples/sec accuracy=76.360220 loss=0.938553 lr=0.001000 Epoch[076] Batch [3749]/[3760] Speed: 82.173281 samples/sec accuracy=76.345000 loss=0.938830 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.875000 acc-top5=85.406250 Batch [0099]/[0303]: acc-top1=65.656250 acc-top5=85.359375 Batch [0149]/[0303]: acc-top1=65.677083 acc-top5=85.531250 Batch [0199]/[0303]: acc-top1=65.734375 acc-top5=85.664062 Batch [0249]/[0303]: acc-top1=65.612500 acc-top5=85.668750 Batch [0299]/[0303]: acc-top1=65.588542 acc-top5=85.562500 [Epoch 076] training: accuracy=76.342670 loss=0.938936 [Epoch 076] speed: 75 samples/sec time cost: 3465.431296 [Epoch 076] validation: acc-top1=65.557962 acc-top5=85.581683 loss=1.659222 Epoch[077] Batch [0049]/[3760] Speed: 53.770005 samples/sec accuracy=75.937500 loss=0.967142 lr=0.001000 Epoch[077] Batch [0099]/[3760] Speed: 74.167150 samples/sec accuracy=75.906250 loss=0.951826 lr=0.001000 Epoch[077] Batch [0149]/[3760] Speed: 77.208233 samples/sec accuracy=76.604167 loss=0.923789 lr=0.001000 Epoch[077] Batch [0199]/[3760] Speed: 76.176968 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lr=0.001000 Epoch[077] Batch [3549]/[3760] Speed: 75.595807 samples/sec accuracy=76.411972 loss=0.937596 lr=0.001000 Epoch[077] Batch [3599]/[3760] Speed: 74.675181 samples/sec accuracy=76.425781 loss=0.937331 lr=0.001000 Epoch[077] Batch [3649]/[3760] Speed: 75.268150 samples/sec accuracy=76.413955 loss=0.938115 lr=0.001000 Epoch[077] Batch [3699]/[3760] Speed: 77.018871 samples/sec accuracy=76.429899 loss=0.937525 lr=0.001000 Epoch[077] Batch [3749]/[3760] Speed: 84.864886 samples/sec accuracy=76.420417 loss=0.937760 lr=0.001000 Batch [0049]/[0303]: acc-top1=66.062500 acc-top5=85.781250 Batch [0099]/[0303]: acc-top1=65.937500 acc-top5=85.578125 Batch [0149]/[0303]: acc-top1=65.781250 acc-top5=85.562500 Batch [0199]/[0303]: acc-top1=65.859375 acc-top5=85.679688 Batch [0249]/[0303]: acc-top1=65.468750 acc-top5=85.593750 Batch [0299]/[0303]: acc-top1=65.500000 acc-top5=85.421875 [Epoch 077] training: accuracy=76.419132 loss=0.937685 [Epoch 077] speed: 75 samples/sec time cost: 3459.217709 [Epoch 077] validation: acc-top1=65.454827 acc-top5=85.457921 loss=1.659262 Epoch[078] Batch [0049]/[3759] Speed: 53.510682 samples/sec accuracy=77.718750 loss=0.883260 lr=0.001000 Epoch[078] Batch [0099]/[3759] Speed: 72.451999 samples/sec accuracy=76.921875 loss=0.900313 lr=0.001000 Epoch[078] Batch [0149]/[3759] Speed: 76.664652 samples/sec accuracy=76.625000 loss=0.919276 lr=0.001000 Epoch[078] Batch [0199]/[3759] Speed: 77.193606 samples/sec accuracy=76.742188 loss=0.921092 lr=0.001000 Epoch[078] Batch [0249]/[3759] Speed: 73.460526 samples/sec accuracy=76.693750 loss=0.921151 lr=0.001000 Epoch[078] Batch [0299]/[3759] Speed: 77.348845 samples/sec accuracy=76.619792 loss=0.924059 lr=0.001000 Epoch[078] Batch [0349]/[3759] Speed: 72.153284 samples/sec accuracy=76.723214 loss=0.919019 lr=0.001000 Epoch[078] Batch [0399]/[3759] Speed: 78.207076 samples/sec accuracy=76.730469 loss=0.918519 lr=0.001000 Epoch[078] Batch [0449]/[3759] Speed: 75.624829 samples/sec 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accuracy=76.748884 loss=0.918721 lr=0.001000 Epoch[078] Batch [1449]/[3759] Speed: 77.210599 samples/sec accuracy=76.742457 loss=0.917858 lr=0.001000 Epoch[078] Batch [1499]/[3759] Speed: 76.324787 samples/sec accuracy=76.722917 loss=0.918066 lr=0.001000 Epoch[078] Batch [1549]/[3759] Speed: 73.312614 samples/sec accuracy=76.699597 loss=0.918965 lr=0.001000 Epoch[078] Batch [1599]/[3759] Speed: 76.978815 samples/sec accuracy=76.709961 loss=0.919636 lr=0.001000 Epoch[078] Batch [1649]/[3759] Speed: 74.314372 samples/sec accuracy=76.714962 loss=0.919158 lr=0.001000 Epoch[078] Batch [1699]/[3759] Speed: 76.582138 samples/sec accuracy=76.783088 loss=0.917422 lr=0.001000 Epoch[078] Batch [1749]/[3759] Speed: 77.090646 samples/sec accuracy=76.841071 loss=0.915990 lr=0.001000 Epoch[078] Batch [1799]/[3759] Speed: 75.990148 samples/sec accuracy=76.811632 loss=0.916726 lr=0.001000 Epoch[078] Batch [1849]/[3759] Speed: 74.262882 samples/sec accuracy=76.807432 loss=0.917201 lr=0.001000 Epoch[078] 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accuracy=76.710771 loss=0.920814 lr=0.001000 Epoch[078] Batch [2399]/[3759] Speed: 77.340089 samples/sec accuracy=76.704427 loss=0.920655 lr=0.001000 Epoch[078] Batch [2449]/[3759] Speed: 76.427383 samples/sec accuracy=76.698980 loss=0.920572 lr=0.001000 Epoch[078] Batch [2499]/[3759] Speed: 76.163550 samples/sec accuracy=76.701250 loss=0.920953 lr=0.001000 Epoch[078] Batch [2549]/[3759] Speed: 74.567541 samples/sec accuracy=76.705882 loss=0.920681 lr=0.001000 Epoch[078] Batch [2599]/[3759] Speed: 74.532626 samples/sec accuracy=76.707332 loss=0.920678 lr=0.001000 Epoch[078] Batch [2649]/[3759] Speed: 77.831482 samples/sec accuracy=76.696344 loss=0.920868 lr=0.001000 Epoch[078] Batch [2699]/[3759] Speed: 77.049502 samples/sec accuracy=76.715856 loss=0.920429 lr=0.001000 Epoch[078] Batch [2749]/[3759] Speed: 73.959762 samples/sec accuracy=76.721591 loss=0.920496 lr=0.001000 Epoch[078] Batch [2799]/[3759] Speed: 75.744215 samples/sec accuracy=76.724888 loss=0.920920 lr=0.001000 Epoch[078] 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accuracy=76.642992 loss=0.923462 lr=0.001000 Epoch[078] Batch [3349]/[3759] Speed: 78.480156 samples/sec accuracy=76.634795 loss=0.923684 lr=0.001000 Epoch[078] Batch [3399]/[3759] Speed: 74.329004 samples/sec accuracy=76.597886 loss=0.925054 lr=0.001000 Epoch[078] Batch [3449]/[3759] Speed: 77.785650 samples/sec accuracy=76.601902 loss=0.924782 lr=0.001000 Epoch[078] Batch [3499]/[3759] Speed: 76.337645 samples/sec accuracy=76.603571 loss=0.925130 lr=0.001000 Epoch[078] Batch [3549]/[3759] Speed: 74.594646 samples/sec accuracy=76.599472 loss=0.925518 lr=0.001000 Epoch[078] Batch [3599]/[3759] Speed: 75.355551 samples/sec accuracy=76.602431 loss=0.925647 lr=0.001000 Epoch[078] Batch [3649]/[3759] Speed: 76.812482 samples/sec accuracy=76.588185 loss=0.926116 lr=0.001000 Epoch[078] Batch [3699]/[3759] Speed: 76.400317 samples/sec accuracy=76.589949 loss=0.926174 lr=0.001000 Epoch[078] Batch [3749]/[3759] Speed: 85.241676 samples/sec accuracy=76.586667 loss=0.926271 lr=0.001000 Batch [0049]/[0303]: acc-top1=65.625000 acc-top5=85.437500 Batch [0099]/[0303]: acc-top1=65.828125 acc-top5=85.265625 Batch [0149]/[0303]: acc-top1=65.666667 acc-top5=85.322917 Batch [0199]/[0303]: acc-top1=65.796875 acc-top5=85.546875 Batch [0249]/[0303]: acc-top1=65.525000 acc-top5=85.593750 Batch [0299]/[0303]: acc-top1=65.562500 acc-top5=85.468750 [Epoch 078] training: accuracy=76.585777 loss=0.926560 [Epoch 078] speed: 75 samples/sec time cost: 3458.245276 [Epoch 078] validation: acc-top1=65.532178 acc-top5=85.473391 loss=1.672577 Epoch[079] Batch [0049]/[3760] Speed: 52.923781 samples/sec accuracy=76.750000 loss=0.920936 lr=0.001000 Epoch[079] Batch [0099]/[3760] Speed: 74.524771 samples/sec accuracy=76.515625 loss=0.925668 lr=0.001000 Epoch[079] Batch [0149]/[3760] Speed: 76.799618 samples/sec accuracy=77.322917 loss=0.902265 lr=0.001000 Epoch[079] Batch [0199]/[3760] Speed: 75.317675 samples/sec accuracy=77.117188 loss=0.908740 lr=0.001000 Epoch[079] Batch [0249]/[3760] Speed: 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lr=0.001000 Epoch[079] Batch [3599]/[3760] Speed: 77.772575 samples/sec accuracy=76.623264 loss=0.927106 lr=0.001000 Epoch[079] Batch [3649]/[3760] Speed: 75.968077 samples/sec accuracy=76.616010 loss=0.927352 lr=0.001000 Epoch[079] Batch [3699]/[3760] Speed: 75.135771 samples/sec accuracy=76.597128 loss=0.928009 lr=0.001000 Epoch[079] Batch [3749]/[3760] Speed: 83.702862 samples/sec accuracy=76.585417 loss=0.928740 lr=0.000100 Batch [0049]/[0303]: acc-top1=65.125000 acc-top5=85.406250 Batch [0099]/[0303]: acc-top1=65.609375 acc-top5=85.406250 Batch [0149]/[0303]: acc-top1=65.541667 acc-top5=85.468750 Batch [0199]/[0303]: acc-top1=65.734375 acc-top5=85.687500 Batch [0249]/[0303]: acc-top1=65.556250 acc-top5=85.687500 Batch [0299]/[0303]: acc-top1=65.572917 acc-top5=85.562500 [Epoch 079] training: accuracy=76.588265 loss=0.928635 [Epoch 079] speed: 75 samples/sec time cost: 3470.137511 [Epoch 079] validation: acc-top1=65.527021 acc-top5=85.576526 loss=1.659204 Epoch[080] Batch 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accuracy=77.500000 loss=0.886745 lr=0.000100 Epoch[080] Batch [0549]/[3760] Speed: 76.263817 samples/sec accuracy=77.463068 loss=0.886982 lr=0.000100 Epoch[080] Batch [0599]/[3760] Speed: 74.590061 samples/sec accuracy=77.536458 loss=0.885905 lr=0.000100 Epoch[080] Batch [0649]/[3760] Speed: 77.050567 samples/sec accuracy=77.615385 loss=0.882193 lr=0.000100 Epoch[080] Batch [0699]/[3760] Speed: 74.156578 samples/sec accuracy=77.636161 loss=0.882308 lr=0.000100 Epoch[080] Batch [0749]/[3760] Speed: 76.342368 samples/sec accuracy=77.662500 loss=0.882306 lr=0.000100 Epoch[080] Batch [0799]/[3760] Speed: 75.908450 samples/sec accuracy=77.695312 loss=0.882094 lr=0.000100 Epoch[080] Batch [0849]/[3760] Speed: 73.669461 samples/sec accuracy=77.691176 loss=0.882447 lr=0.000100 Epoch[080] Batch [0899]/[3760] Speed: 77.295228 samples/sec accuracy=77.807292 loss=0.879067 lr=0.000100 Epoch[080] Batch [0949]/[3760] Speed: 76.934629 samples/sec accuracy=77.832237 loss=0.877804 lr=0.000100 Epoch[080] 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accuracy=77.982759 loss=0.873886 lr=0.000100 Epoch[080] Batch [1499]/[3760] Speed: 74.355185 samples/sec accuracy=77.966667 loss=0.874176 lr=0.000100 Epoch[080] Batch [1549]/[3760] Speed: 77.223086 samples/sec accuracy=77.985887 loss=0.872891 lr=0.000100 Epoch[080] Batch [1599]/[3760] Speed: 74.472924 samples/sec accuracy=78.023438 loss=0.872231 lr=0.000100 Epoch[080] Batch [1649]/[3760] Speed: 75.448418 samples/sec accuracy=78.020833 loss=0.873253 lr=0.000100 Epoch[080] Batch [1699]/[3760] Speed: 77.230721 samples/sec accuracy=78.043199 loss=0.871747 lr=0.000100 Epoch[080] Batch [1749]/[3760] Speed: 74.896201 samples/sec accuracy=78.058929 loss=0.871802 lr=0.000100 Epoch[080] Batch [1799]/[3760] Speed: 75.836981 samples/sec accuracy=78.023438 loss=0.873250 lr=0.000100 Epoch[080] Batch [1849]/[3760] Speed: 75.353992 samples/sec accuracy=77.995777 loss=0.873675 lr=0.000100 Epoch[080] Batch [1899]/[3760] Speed: 78.535440 samples/sec accuracy=78.010691 loss=0.873020 lr=0.000100 Epoch[080] 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accuracy=78.078776 loss=0.870937 lr=0.000100 Epoch[080] Batch [2449]/[3760] Speed: 73.544001 samples/sec accuracy=78.081633 loss=0.870412 lr=0.000100 Epoch[080] Batch [2499]/[3760] Speed: 78.096593 samples/sec accuracy=78.094375 loss=0.869973 lr=0.000100 Epoch[080] Batch [2549]/[3760] Speed: 74.091813 samples/sec accuracy=78.115809 loss=0.869116 lr=0.000100 Epoch[080] Batch [2599]/[3760] Speed: 76.695135 samples/sec accuracy=78.103966 loss=0.869154 lr=0.000100 Epoch[080] Batch [2649]/[3760] Speed: 75.796289 samples/sec accuracy=78.125590 loss=0.868598 lr=0.000100 Epoch[080] Batch [2699]/[3760] Speed: 76.852583 samples/sec accuracy=78.130208 loss=0.868714 lr=0.000100 Epoch[080] Batch [2749]/[3760] Speed: 74.103386 samples/sec accuracy=78.128409 loss=0.868306 lr=0.000100 Epoch[080] Batch [2799]/[3760] Speed: 76.282131 samples/sec accuracy=78.128348 loss=0.868433 lr=0.000100 Epoch[080] Batch [2849]/[3760] Speed: 76.971422 samples/sec accuracy=78.135417 loss=0.868256 lr=0.000100 Epoch[080] Batch [2899]/[3760] Speed: 75.210203 samples/sec accuracy=78.132004 loss=0.868293 lr=0.000100 Epoch[080] Batch [2949]/[3760] Speed: 75.857110 samples/sec accuracy=78.146186 loss=0.867548 lr=0.000100 Epoch[080] Batch [2999]/[3760] Speed: 75.804998 samples/sec accuracy=78.166667 loss=0.867161 lr=0.000100 Epoch[080] Batch [3049]/[3760] Speed: 76.848043 samples/sec accuracy=78.167008 loss=0.866991 lr=0.000100 Epoch[080] Batch [3099]/[3760] Speed: 74.301057 samples/sec accuracy=78.157258 loss=0.867015 lr=0.000100 Epoch[080] Batch [3149]/[3760] Speed: 77.425921 samples/sec accuracy=78.170139 loss=0.866430 lr=0.000100 Epoch[080] Batch [3199]/[3760] Speed: 73.374957 samples/sec accuracy=78.166992 loss=0.866469 lr=0.000100 Epoch[080] Batch [3249]/[3760] Speed: 77.467557 samples/sec accuracy=78.175000 loss=0.866189 lr=0.000100 Epoch[080] Batch [3299]/[3760] Speed: 76.539981 samples/sec accuracy=78.165246 loss=0.866372 lr=0.000100 Epoch[080] Batch [3349]/[3760] Speed: 75.041690 samples/sec accuracy=78.180037 loss=0.865766 lr=0.000100 Epoch[080] Batch [3399]/[3760] Speed: 76.342729 samples/sec accuracy=78.179228 loss=0.866357 lr=0.000100 Epoch[080] Batch [3449]/[3760] Speed: 76.879710 samples/sec accuracy=78.177989 loss=0.865891 lr=0.000100 Epoch[080] Batch [3499]/[3760] Speed: 74.401686 samples/sec accuracy=78.176786 loss=0.866160 lr=0.000100 Epoch[080] Batch [3549]/[3760] Speed: 76.747686 samples/sec accuracy=78.176496 loss=0.865837 lr=0.000100 Epoch[080] Batch [3599]/[3760] Speed: 77.245357 samples/sec accuracy=78.190538 loss=0.865486 lr=0.000100 Epoch[080] Batch [3649]/[3760] Speed: 75.106311 samples/sec accuracy=78.187072 loss=0.865556 lr=0.000100 Epoch[080] Batch [3699]/[3760] Speed: 75.403263 samples/sec accuracy=78.185389 loss=0.865532 lr=0.000100 Epoch[080] Batch [3749]/[3760] Speed: 82.775868 samples/sec accuracy=78.173333 loss=0.865555 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.312500 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.468750 acc-top5=85.890625 Batch [0149]/[0303]: acc-top1=66.375000 acc-top5=86.031250 Batch [0199]/[0303]: acc-top1=66.554688 acc-top5=86.140625 Batch [0249]/[0303]: acc-top1=66.343750 acc-top5=86.175000 Batch [0299]/[0303]: acc-top1=66.380208 acc-top5=86.046875 [Epoch 080] training: accuracy=78.164478 loss=0.865728 [Epoch 080] speed: 75 samples/sec time cost: 3465.685356 [Epoch 080] validation: acc-top1=66.362417 acc-top5=86.056106 loss=1.623930 Epoch[081] Batch [0049]/[3759] Speed: 53.605090 samples/sec accuracy=77.687500 loss=0.871397 lr=0.000100 Epoch[081] Batch [0099]/[3759] Speed: 71.239225 samples/sec accuracy=78.593750 loss=0.853238 lr=0.000100 Epoch[081] Batch [0149]/[3759] Speed: 78.518280 samples/sec accuracy=78.718750 loss=0.844271 lr=0.000100 Epoch[081] Batch [0199]/[3759] Speed: 77.645801 samples/sec accuracy=78.468750 loss=0.852436 lr=0.000100 Epoch[081] Batch [0249]/[3759] Speed: 72.348438 samples/sec accuracy=78.268750 loss=0.857214 lr=0.000100 Epoch[081] Batch [0299]/[3759] 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accuracy=78.539931 loss=0.849748 lr=0.000100 Epoch[081] Batch [3649]/[3759] Speed: 73.807158 samples/sec accuracy=78.552654 loss=0.849801 lr=0.000100 Epoch[081] Batch [3699]/[3759] Speed: 77.811995 samples/sec accuracy=78.562922 loss=0.849451 lr=0.000100 Epoch[081] Batch [3749]/[3759] Speed: 84.418732 samples/sec accuracy=78.563750 loss=0.849548 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.875000 acc-top5=86.281250 Batch [0099]/[0303]: acc-top1=66.781250 acc-top5=85.953125 Batch [0149]/[0303]: acc-top1=66.677083 acc-top5=86.083333 Batch [0199]/[0303]: acc-top1=66.781250 acc-top5=86.179688 Batch [0249]/[0303]: acc-top1=66.481250 acc-top5=86.181250 Batch [0299]/[0303]: acc-top1=66.437500 acc-top5=86.015625 [Epoch 081] training: accuracy=78.561037 loss=0.849583 [Epoch 081] speed: 75 samples/sec time cost: 3460.274433 [Epoch 081] validation: acc-top1=66.403672 acc-top5=86.030322 loss=1.633392 Epoch[082] Batch [0049]/[3760] Speed: 54.199460 samples/sec accuracy=78.437500 loss=0.861596 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lr=0.000100 Epoch[082] Batch [2949]/[3760] Speed: 76.598811 samples/sec accuracy=78.764831 loss=0.842968 lr=0.000100 Epoch[082] Batch [2999]/[3760] Speed: 73.274872 samples/sec accuracy=78.784896 loss=0.842781 lr=0.000100 Epoch[082] Batch [3049]/[3760] Speed: 76.428809 samples/sec accuracy=78.779201 loss=0.842849 lr=0.000100 Epoch[082] Batch [3099]/[3760] Speed: 76.128286 samples/sec accuracy=78.787802 loss=0.842530 lr=0.000100 Epoch[082] Batch [3149]/[3760] Speed: 74.509614 samples/sec accuracy=78.807044 loss=0.841608 lr=0.000100 Epoch[082] Batch [3199]/[3760] Speed: 77.214725 samples/sec accuracy=78.809082 loss=0.841369 lr=0.000100 Epoch[082] Batch [3249]/[3760] Speed: 76.756428 samples/sec accuracy=78.796635 loss=0.841664 lr=0.000100 Epoch[082] Batch [3299]/[3760] Speed: 75.724100 samples/sec accuracy=78.802557 loss=0.841122 lr=0.000100 Epoch[082] Batch [3349]/[3760] Speed: 75.840139 samples/sec accuracy=78.798974 loss=0.841363 lr=0.000100 Epoch[082] Batch [3399]/[3760] Speed: 75.210642 samples/sec accuracy=78.802390 loss=0.841857 lr=0.000100 Epoch[082] Batch [3449]/[3760] Speed: 77.356132 samples/sec accuracy=78.804801 loss=0.842050 lr=0.000100 Epoch[082] Batch [3499]/[3760] Speed: 74.543610 samples/sec accuracy=78.818304 loss=0.841597 lr=0.000100 Epoch[082] Batch [3549]/[3760] Speed: 76.035091 samples/sec accuracy=78.828785 loss=0.841283 lr=0.000100 Epoch[082] Batch [3599]/[3760] Speed: 75.062527 samples/sec accuracy=78.848958 loss=0.840563 lr=0.000100 Epoch[082] Batch [3649]/[3760] Speed: 76.317525 samples/sec accuracy=78.842038 loss=0.840549 lr=0.000100 Epoch[082] Batch [3699]/[3760] Speed: 74.801838 samples/sec accuracy=78.851351 loss=0.840104 lr=0.000100 Epoch[082] Batch [3749]/[3760] Speed: 84.795878 samples/sec accuracy=78.855417 loss=0.839924 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.125000 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.296875 acc-top5=85.734375 Batch [0149]/[0303]: acc-top1=66.406250 acc-top5=85.864583 Batch [0199]/[0303]: acc-top1=66.476562 acc-top5=86.062500 Batch [0249]/[0303]: acc-top1=66.262500 acc-top5=86.018750 Batch [0299]/[0303]: acc-top1=66.291667 acc-top5=85.901042 [Epoch 082] training: accuracy=78.850150 loss=0.840204 [Epoch 082] speed: 75 samples/sec time cost: 3463.435266 [Epoch 082] validation: acc-top1=66.274752 acc-top5=85.922030 loss=1.630912 Epoch[083] Batch [0049]/[3760] Speed: 53.508942 samples/sec accuracy=79.562500 loss=0.815623 lr=0.000100 Epoch[083] Batch [0099]/[3760] Speed: 71.275486 samples/sec accuracy=79.890625 loss=0.805276 lr=0.000100 Epoch[083] Batch [0149]/[3760] Speed: 78.511821 samples/sec accuracy=79.645833 loss=0.816264 lr=0.000100 Epoch[083] Batch [0199]/[3760] Speed: 77.253085 samples/sec accuracy=79.640625 loss=0.813040 lr=0.000100 Epoch[083] Batch [0249]/[3760] Speed: 73.186362 samples/sec accuracy=79.631250 loss=0.814766 lr=0.000100 Epoch[083] Batch [0299]/[3760] Speed: 78.255148 samples/sec accuracy=79.213542 loss=0.828371 lr=0.000100 Epoch[083] Batch 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accuracy=78.894676 loss=0.836909 lr=0.000100 Epoch[083] Batch [2749]/[3760] Speed: 74.689383 samples/sec accuracy=78.890341 loss=0.837077 lr=0.000100 Epoch[083] Batch [2799]/[3760] Speed: 75.885320 samples/sec accuracy=78.898438 loss=0.836750 lr=0.000100 Epoch[083] Batch [2849]/[3760] Speed: 76.873312 samples/sec accuracy=78.886513 loss=0.837698 lr=0.000100 Epoch[083] Batch [2899]/[3760] Speed: 75.873230 samples/sec accuracy=78.877694 loss=0.837969 lr=0.000100 Epoch[083] Batch [2949]/[3760] Speed: 76.050689 samples/sec accuracy=78.876059 loss=0.838243 lr=0.000100 Epoch[083] Batch [2999]/[3760] Speed: 73.409585 samples/sec accuracy=78.886458 loss=0.838101 lr=0.000100 Epoch[083] Batch [3049]/[3760] Speed: 78.190861 samples/sec accuracy=78.871414 loss=0.838313 lr=0.000100 Epoch[083] Batch [3099]/[3760] Speed: 76.664582 samples/sec accuracy=78.892137 loss=0.837962 lr=0.000100 Epoch[083] Batch [3149]/[3760] Speed: 75.578104 samples/sec accuracy=78.878472 loss=0.838172 lr=0.000100 Epoch[083] 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accuracy=78.890839 loss=0.838902 lr=0.000100 Epoch[083] Batch [3699]/[3760] Speed: 75.234564 samples/sec accuracy=78.885980 loss=0.839112 lr=0.000100 Epoch[083] Batch [3749]/[3760] Speed: 84.610387 samples/sec accuracy=78.867917 loss=0.839702 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.750000 acc-top5=86.125000 Batch [0099]/[0303]: acc-top1=66.843750 acc-top5=85.875000 Batch [0149]/[0303]: acc-top1=66.708333 acc-top5=85.916667 Batch [0199]/[0303]: acc-top1=66.804688 acc-top5=86.078125 Batch [0249]/[0303]: acc-top1=66.612500 acc-top5=86.093750 Batch [0299]/[0303]: acc-top1=66.531250 acc-top5=85.932292 [Epoch 083] training: accuracy=78.865941 loss=0.839595 [Epoch 083] speed: 75 samples/sec time cost: 3461.742572 [Epoch 083] validation: acc-top1=66.522277 acc-top5=85.963284 loss=1.625171 Epoch[084] Batch [0049]/[3759] Speed: 52.882898 samples/sec accuracy=79.656250 loss=0.834720 lr=0.000100 Epoch[084] Batch [0099]/[3759] Speed: 72.391887 samples/sec accuracy=79.187500 loss=0.835555 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lr=0.000100 Epoch[084] Batch [2999]/[3759] Speed: 76.733295 samples/sec accuracy=78.916667 loss=0.838060 lr=0.000100 Epoch[084] Batch [3049]/[3759] Speed: 74.398171 samples/sec accuracy=78.943648 loss=0.836872 lr=0.000100 Epoch[084] Batch [3099]/[3759] Speed: 76.495911 samples/sec accuracy=78.955645 loss=0.836198 lr=0.000100 Epoch[084] Batch [3149]/[3759] Speed: 77.382222 samples/sec accuracy=78.946429 loss=0.836946 lr=0.000100 Epoch[084] Batch [3199]/[3759] Speed: 74.795592 samples/sec accuracy=78.967285 loss=0.836343 lr=0.000100 Epoch[084] Batch [3249]/[3759] Speed: 76.217873 samples/sec accuracy=78.971154 loss=0.836079 lr=0.000100 Epoch[084] Batch [3299]/[3759] Speed: 75.123866 samples/sec accuracy=78.980587 loss=0.835875 lr=0.000100 Epoch[084] Batch [3349]/[3759] Speed: 76.091580 samples/sec accuracy=78.990672 loss=0.835627 lr=0.000100 Epoch[084] Batch [3399]/[3759] Speed: 74.603654 samples/sec accuracy=79.000919 loss=0.835266 lr=0.000100 Epoch[084] Batch [3449]/[3759] Speed: 77.180786 samples/sec accuracy=79.002717 loss=0.835130 lr=0.000100 Epoch[084] Batch [3499]/[3759] Speed: 74.087187 samples/sec accuracy=79.005357 loss=0.835015 lr=0.000100 Epoch[084] Batch [3549]/[3759] Speed: 75.755478 samples/sec accuracy=79.005282 loss=0.835145 lr=0.000100 Epoch[084] Batch [3599]/[3759] Speed: 74.936333 samples/sec accuracy=79.013021 loss=0.834727 lr=0.000100 Epoch[084] Batch [3649]/[3759] Speed: 74.807875 samples/sec accuracy=79.017123 loss=0.833962 lr=0.000100 Epoch[084] Batch [3699]/[3759] Speed: 73.765230 samples/sec accuracy=79.014780 loss=0.833853 lr=0.000100 Epoch[084] Batch [3749]/[3759] Speed: 85.812481 samples/sec accuracy=79.020833 loss=0.833438 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.812500 acc-top5=86.062500 Batch [0099]/[0303]: acc-top1=66.890625 acc-top5=85.875000 Batch [0149]/[0303]: acc-top1=66.781250 acc-top5=85.843750 Batch [0199]/[0303]: acc-top1=66.921875 acc-top5=86.070312 Batch [0249]/[0303]: acc-top1=66.656250 acc-top5=86.112500 Batch [0299]/[0303]: acc-top1=66.552083 acc-top5=85.942708 [Epoch 084] training: accuracy=79.024508 loss=0.833366 [Epoch 084] speed: 75 samples/sec time cost: 3463.449368 [Epoch 084] validation: acc-top1=66.527434 acc-top5=85.978754 loss=1.618248 Epoch[085] Batch [0049]/[3760] Speed: 53.587126 samples/sec accuracy=80.000000 loss=0.801046 lr=0.000100 Epoch[085] Batch [0099]/[3760] Speed: 71.530692 samples/sec accuracy=79.421875 loss=0.819329 lr=0.000100 Epoch[085] Batch [0149]/[3760] Speed: 76.273415 samples/sec accuracy=79.385417 loss=0.821240 lr=0.000100 Epoch[085] Batch [0199]/[3760] Speed: 75.655364 samples/sec accuracy=79.210938 loss=0.828700 lr=0.000100 Epoch[085] Batch [0249]/[3760] Speed: 76.920052 samples/sec accuracy=79.200000 loss=0.829846 lr=0.000100 Epoch[085] Batch [0299]/[3760] Speed: 75.280660 samples/sec accuracy=79.302083 loss=0.828203 lr=0.000100 Epoch[085] Batch [0349]/[3760] Speed: 74.494489 samples/sec accuracy=79.303571 loss=0.827123 lr=0.000100 Epoch[085] Batch 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accuracy=79.106618 loss=0.827820 lr=0.000100 Epoch[085] Batch [0899]/[3760] Speed: 76.466804 samples/sec accuracy=79.157986 loss=0.826967 lr=0.000100 Epoch[085] Batch [0949]/[3760] Speed: 75.744170 samples/sec accuracy=79.202303 loss=0.826453 lr=0.000100 Epoch[085] Batch [0999]/[3760] Speed: 75.702167 samples/sec accuracy=79.121875 loss=0.829589 lr=0.000100 Epoch[085] Batch [1049]/[3760] Speed: 76.104992 samples/sec accuracy=79.110119 loss=0.830748 lr=0.000100 Epoch[085] Batch [1099]/[3760] Speed: 75.397583 samples/sec accuracy=79.073864 loss=0.831181 lr=0.000100 Epoch[085] Batch [1149]/[3760] Speed: 74.158150 samples/sec accuracy=79.057065 loss=0.830508 lr=0.000100 Epoch[085] Batch [1199]/[3760] Speed: 78.375247 samples/sec accuracy=79.054688 loss=0.831400 lr=0.000100 Epoch[085] Batch [1249]/[3760] Speed: 74.465666 samples/sec accuracy=79.048750 loss=0.831200 lr=0.000100 Epoch[085] Batch [1299]/[3760] Speed: 78.036277 samples/sec accuracy=79.046875 loss=0.830701 lr=0.000100 Epoch[085] 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accuracy=79.166667 loss=0.825024 lr=0.000100 Epoch[085] Batch [1849]/[3760] Speed: 74.435994 samples/sec accuracy=79.169764 loss=0.825060 lr=0.000100 Epoch[085] Batch [1899]/[3760] Speed: 75.311870 samples/sec accuracy=79.181743 loss=0.825139 lr=0.000100 Epoch[085] Batch [1949]/[3760] Speed: 75.552818 samples/sec accuracy=79.195513 loss=0.824514 lr=0.000100 Epoch[085] Batch [1999]/[3760] Speed: 76.052581 samples/sec accuracy=79.202344 loss=0.824706 lr=0.000100 Epoch[085] Batch [2049]/[3760] Speed: 74.186861 samples/sec accuracy=79.186738 loss=0.825024 lr=0.000100 Epoch[085] Batch [2099]/[3760] Speed: 76.798954 samples/sec accuracy=79.186012 loss=0.825245 lr=0.000100 Epoch[085] Batch [2149]/[3760] Speed: 77.758833 samples/sec accuracy=79.199855 loss=0.824784 lr=0.000100 Epoch[085] Batch [2199]/[3760] Speed: 73.059554 samples/sec accuracy=79.205966 loss=0.824929 lr=0.000100 Epoch[085] Batch [2249]/[3760] Speed: 77.362540 samples/sec accuracy=79.191667 loss=0.825211 lr=0.000100 Epoch[085] 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accuracy=79.182386 loss=0.826071 lr=0.000100 Epoch[085] Batch [2799]/[3760] Speed: 75.640614 samples/sec accuracy=79.155692 loss=0.826624 lr=0.000100 Epoch[085] Batch [2849]/[3760] Speed: 76.214958 samples/sec accuracy=79.151316 loss=0.827281 lr=0.000100 Epoch[085] Batch [2899]/[3760] Speed: 74.216027 samples/sec accuracy=79.142780 loss=0.827279 lr=0.000100 Epoch[085] Batch [2949]/[3760] Speed: 76.516260 samples/sec accuracy=79.134004 loss=0.827450 lr=0.000100 Epoch[085] Batch [2999]/[3760] Speed: 76.234341 samples/sec accuracy=79.127083 loss=0.827408 lr=0.000100 Epoch[085] Batch [3049]/[3760] Speed: 74.556113 samples/sec accuracy=79.120902 loss=0.827320 lr=0.000100 Epoch[085] Batch [3099]/[3760] Speed: 76.528692 samples/sec accuracy=79.089214 loss=0.828125 lr=0.000100 Epoch[085] Batch [3149]/[3760] Speed: 75.822364 samples/sec accuracy=79.064484 loss=0.828837 lr=0.000100 Epoch[085] Batch [3199]/[3760] Speed: 75.712483 samples/sec accuracy=79.067871 loss=0.828688 lr=0.000100 Epoch[085] Batch [3249]/[3760] Speed: 74.187327 samples/sec accuracy=79.051923 loss=0.829523 lr=0.000100 Epoch[085] Batch [3299]/[3760] Speed: 78.019537 samples/sec accuracy=79.050663 loss=0.829799 lr=0.000100 Epoch[085] Batch [3349]/[3760] Speed: 74.769821 samples/sec accuracy=79.029851 loss=0.830445 lr=0.000100 Epoch[085] Batch [3399]/[3760] Speed: 77.048383 samples/sec accuracy=79.026195 loss=0.830681 lr=0.000100 Epoch[085] Batch [3449]/[3760] Speed: 74.105801 samples/sec accuracy=79.031250 loss=0.830723 lr=0.000100 Epoch[085] Batch [3499]/[3760] Speed: 77.512057 samples/sec accuracy=79.038393 loss=0.830636 lr=0.000100 Epoch[085] Batch [3549]/[3760] Speed: 74.980911 samples/sec accuracy=79.060739 loss=0.829911 lr=0.000100 Epoch[085] Batch [3599]/[3760] Speed: 76.853694 samples/sec accuracy=79.066406 loss=0.829631 lr=0.000100 Epoch[085] Batch [3649]/[3760] Speed: 75.810000 samples/sec accuracy=79.076199 loss=0.829701 lr=0.000100 Epoch[085] Batch [3699]/[3760] Speed: 74.749106 samples/sec accuracy=79.077280 loss=0.829412 lr=0.000100 Epoch[085] Batch [3749]/[3760] Speed: 85.480099 samples/sec accuracy=79.089167 loss=0.829169 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.437500 acc-top5=85.750000 Batch [0099]/[0303]: acc-top1=66.625000 acc-top5=85.703125 Batch [0149]/[0303]: acc-top1=66.520833 acc-top5=85.927083 Batch [0199]/[0303]: acc-top1=66.601562 acc-top5=86.125000 Batch [0249]/[0303]: acc-top1=66.356250 acc-top5=86.056250 Batch [0299]/[0303]: acc-top1=66.411458 acc-top5=85.906250 [Epoch 085] training: accuracy=79.089927 loss=0.829208 [Epoch 085] speed: 75 samples/sec time cost: 3466.472577 [Epoch 085] validation: acc-top1=66.393358 acc-top5=85.922030 loss=1.631194 Epoch[086] Batch [0049]/[3760] Speed: 52.071685 samples/sec accuracy=79.937500 loss=0.786446 lr=0.000100 Epoch[086] Batch [0099]/[3760] Speed: 74.120768 samples/sec accuracy=80.156250 loss=0.795133 lr=0.000100 Epoch[086] Batch [0149]/[3760] Speed: 74.962465 samples/sec accuracy=79.802083 loss=0.799335 lr=0.000100 Epoch[086] Batch [0199]/[3760] Speed: 74.797785 samples/sec accuracy=79.695312 loss=0.805287 lr=0.000100 Epoch[086] Batch [0249]/[3760] Speed: 76.777241 samples/sec accuracy=79.493750 loss=0.816441 lr=0.000100 Epoch[086] Batch [0299]/[3760] Speed: 75.692470 samples/sec accuracy=79.401042 loss=0.821618 lr=0.000100 Epoch[086] Batch [0349]/[3760] Speed: 74.283702 samples/sec accuracy=79.183036 loss=0.830488 lr=0.000100 Epoch[086] Batch [0399]/[3760] Speed: 77.484575 samples/sec accuracy=79.214844 loss=0.829346 lr=0.000100 Epoch[086] Batch [0449]/[3760] Speed: 75.104136 samples/sec accuracy=79.246528 loss=0.827141 lr=0.000100 Epoch[086] Batch [0499]/[3760] Speed: 75.744653 samples/sec accuracy=79.196875 loss=0.827819 lr=0.000100 Epoch[086] Batch [0549]/[3760] Speed: 76.989436 samples/sec accuracy=79.227273 loss=0.825715 lr=0.000100 Epoch[086] Batch [0599]/[3760] Speed: 76.700153 samples/sec accuracy=79.195312 loss=0.828375 lr=0.000100 Epoch[086] Batch [0649]/[3760] Speed: 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lr=0.000100 Epoch[086] Batch [1149]/[3760] Speed: 76.764493 samples/sec accuracy=79.199728 loss=0.828483 lr=0.000100 Epoch[086] Batch [1199]/[3760] Speed: 75.978061 samples/sec accuracy=79.174479 loss=0.829171 lr=0.000100 Epoch[086] Batch [1249]/[3760] Speed: 74.916488 samples/sec accuracy=79.195000 loss=0.828014 lr=0.000100 Epoch[086] Batch [1299]/[3760] Speed: 77.527125 samples/sec accuracy=79.209135 loss=0.827166 lr=0.000100 Epoch[086] Batch [1349]/[3760] Speed: 74.665151 samples/sec accuracy=79.224537 loss=0.826655 lr=0.000100 Epoch[086] Batch [1399]/[3760] Speed: 77.968207 samples/sec accuracy=79.275670 loss=0.825386 lr=0.000100 Epoch[086] Batch [1449]/[3760] Speed: 74.584898 samples/sec accuracy=79.271552 loss=0.826116 lr=0.000100 Epoch[086] Batch [1499]/[3760] Speed: 76.185753 samples/sec accuracy=79.293750 loss=0.825402 lr=0.000100 Epoch[086] Batch [1549]/[3760] Speed: 75.928896 samples/sec accuracy=79.284274 loss=0.825009 lr=0.000100 Epoch[086] Batch [1599]/[3760] Speed: 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lr=0.000100 Epoch[086] Batch [2099]/[3760] Speed: 77.242342 samples/sec accuracy=79.203869 loss=0.825817 lr=0.000100 Epoch[086] Batch [2149]/[3760] Speed: 77.700002 samples/sec accuracy=79.210029 loss=0.826001 lr=0.000100 Epoch[086] Batch [2199]/[3760] Speed: 75.702362 samples/sec accuracy=79.193182 loss=0.826862 lr=0.000100 Epoch[086] Batch [2249]/[3760] Speed: 75.853958 samples/sec accuracy=79.163889 loss=0.827510 lr=0.000100 Epoch[086] Batch [2299]/[3760] Speed: 74.727001 samples/sec accuracy=79.162364 loss=0.827569 lr=0.000100 Epoch[086] Batch [2349]/[3760] Speed: 76.349338 samples/sec accuracy=79.182846 loss=0.826806 lr=0.000100 Epoch[086] Batch [2399]/[3760] Speed: 74.462905 samples/sec accuracy=79.162109 loss=0.828017 lr=0.000100 Epoch[086] Batch [2449]/[3760] Speed: 78.503197 samples/sec accuracy=79.142857 loss=0.828358 lr=0.000100 Epoch[086] Batch [2499]/[3760] Speed: 72.778777 samples/sec accuracy=79.129375 loss=0.828936 lr=0.000100 Epoch[086] Batch [2549]/[3760] Speed: 76.677620 samples/sec accuracy=79.129902 loss=0.828323 lr=0.000100 Epoch[086] Batch [2599]/[3760] Speed: 77.960638 samples/sec accuracy=79.137019 loss=0.828475 lr=0.000100 Epoch[086] Batch [2649]/[3760] Speed: 72.442225 samples/sec accuracy=79.148585 loss=0.828329 lr=0.000100 Epoch[086] Batch [2699]/[3760] Speed: 77.533270 samples/sec accuracy=79.156250 loss=0.827649 lr=0.000100 Epoch[086] Batch [2749]/[3760] Speed: 77.123286 samples/sec accuracy=79.172727 loss=0.827020 lr=0.000100 Epoch[086] Batch [2799]/[3760] Speed: 73.885178 samples/sec accuracy=79.190848 loss=0.825940 lr=0.000100 Epoch[086] Batch [2849]/[3760] Speed: 77.073399 samples/sec accuracy=79.163377 loss=0.826453 lr=0.000100 Epoch[086] Batch [2899]/[3760] Speed: 77.511307 samples/sec accuracy=79.136315 loss=0.827241 lr=0.000100 Epoch[086] Batch [2949]/[3760] Speed: 73.769587 samples/sec accuracy=79.134004 loss=0.827343 lr=0.000100 Epoch[086] Batch [2999]/[3760] Speed: 76.343369 samples/sec accuracy=79.121354 loss=0.828090 lr=0.000100 Epoch[086] Batch [3049]/[3760] Speed: 76.130786 samples/sec accuracy=79.121926 loss=0.827525 lr=0.000100 Epoch[086] Batch [3099]/[3760] Speed: 76.576546 samples/sec accuracy=79.127016 loss=0.827305 lr=0.000100 Epoch[086] Batch [3149]/[3760] Speed: 76.369272 samples/sec accuracy=79.136409 loss=0.827569 lr=0.000100 Epoch[086] Batch [3199]/[3760] Speed: 75.669474 samples/sec accuracy=79.119141 loss=0.828380 lr=0.000100 Epoch[086] Batch [3249]/[3760] Speed: 74.930746 samples/sec accuracy=79.124519 loss=0.828049 lr=0.000100 Epoch[086] Batch [3299]/[3760] Speed: 76.859807 samples/sec accuracy=79.116951 loss=0.828768 lr=0.000100 Epoch[086] Batch [3349]/[3760] Speed: 76.398589 samples/sec accuracy=79.115205 loss=0.828618 lr=0.000100 Epoch[086] Batch [3399]/[3760] Speed: 76.669257 samples/sec accuracy=79.128676 loss=0.827921 lr=0.000100 Epoch[086] Batch [3449]/[3760] Speed: 75.504588 samples/sec accuracy=79.119112 loss=0.827963 lr=0.000100 Epoch[086] Batch [3499]/[3760] Speed: 73.992631 samples/sec accuracy=79.121875 loss=0.827462 lr=0.000100 Epoch[086] Batch [3549]/[3760] Speed: 76.164095 samples/sec accuracy=79.129842 loss=0.826944 lr=0.000100 Epoch[086] Batch [3599]/[3760] Speed: 78.007654 samples/sec accuracy=79.140191 loss=0.826974 lr=0.000100 Epoch[086] Batch [3649]/[3760] Speed: 73.221235 samples/sec accuracy=79.150257 loss=0.826693 lr=0.000100 Epoch[086] Batch [3699]/[3760] Speed: 76.985754 samples/sec accuracy=79.140625 loss=0.826923 lr=0.000100 Epoch[086] Batch [3749]/[3760] Speed: 84.673126 samples/sec accuracy=79.149583 loss=0.826731 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.687500 acc-top5=85.812500 Batch [0099]/[0303]: acc-top1=66.812500 acc-top5=85.781250 Batch [0149]/[0303]: acc-top1=66.770833 acc-top5=85.947917 Batch [0199]/[0303]: acc-top1=66.882812 acc-top5=86.085938 Batch [0249]/[0303]: acc-top1=66.656250 acc-top5=86.037500 Batch [0299]/[0303]: acc-top1=66.552083 acc-top5=85.911458 [Epoch 086] training: accuracy=79.144365 loss=0.826918 [Epoch 086] speed: 75 samples/sec time cost: 3463.643864 [Epoch 086] validation: acc-top1=66.517120 acc-top5=85.937500 loss=1.624385 Epoch[087] Batch [0049]/[3759] Speed: 53.576809 samples/sec accuracy=79.968750 loss=0.769821 lr=0.000100 Epoch[087] Batch [0099]/[3759] Speed: 70.080894 samples/sec accuracy=79.281250 loss=0.811982 lr=0.000100 Epoch[087] Batch [0149]/[3759] Speed: 78.591478 samples/sec accuracy=79.072917 loss=0.826855 lr=0.000100 Epoch[087] Batch [0199]/[3759] Speed: 76.321847 samples/sec accuracy=79.140625 loss=0.819456 lr=0.000100 Epoch[087] Batch [0249]/[3759] Speed: 76.234311 samples/sec accuracy=79.350000 loss=0.816796 lr=0.000100 Epoch[087] Batch [0299]/[3759] Speed: 75.912014 samples/sec accuracy=79.432292 loss=0.808434 lr=0.000100 Epoch[087] Batch [0349]/[3759] Speed: 74.940800 samples/sec accuracy=79.334821 loss=0.810335 lr=0.000100 Epoch[087] Batch [0399]/[3759] Speed: 76.811319 samples/sec accuracy=79.277344 loss=0.816334 lr=0.000100 Epoch[087] Batch 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accuracy=79.335069 loss=0.818406 lr=0.000100 Epoch[087] Batch [0949]/[3759] Speed: 76.426684 samples/sec accuracy=79.271382 loss=0.819869 lr=0.000100 Epoch[087] Batch [0999]/[3759] Speed: 75.522067 samples/sec accuracy=79.285938 loss=0.820380 lr=0.000100 Epoch[087] Batch [1049]/[3759] Speed: 76.696379 samples/sec accuracy=79.312500 loss=0.819050 lr=0.000100 Epoch[087] Batch [1099]/[3759] Speed: 76.322608 samples/sec accuracy=79.313920 loss=0.818421 lr=0.000100 Epoch[087] Batch [1149]/[3759] Speed: 74.978106 samples/sec accuracy=79.338315 loss=0.818485 lr=0.000100 Epoch[087] Batch [1199]/[3759] Speed: 76.669578 samples/sec accuracy=79.385417 loss=0.816480 lr=0.000100 Epoch[087] Batch [1249]/[3759] Speed: 75.119055 samples/sec accuracy=79.382500 loss=0.817083 lr=0.000100 Epoch[087] Batch [1299]/[3759] Speed: 74.130900 samples/sec accuracy=79.350962 loss=0.818123 lr=0.000100 Epoch[087] Batch [1349]/[3759] Speed: 76.813615 samples/sec accuracy=79.336806 loss=0.818216 lr=0.000100 Epoch[087] 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accuracy=79.273649 loss=0.819635 lr=0.000100 Epoch[087] Batch [1899]/[3759] Speed: 71.329539 samples/sec accuracy=79.286184 loss=0.819140 lr=0.000100 Epoch[087] Batch [1949]/[3759] Speed: 79.183074 samples/sec accuracy=79.334135 loss=0.816977 lr=0.000100 Epoch[087] Batch [1999]/[3759] Speed: 74.992604 samples/sec accuracy=79.345312 loss=0.816442 lr=0.000100 Epoch[087] Batch [2049]/[3759] Speed: 77.071933 samples/sec accuracy=79.339177 loss=0.816872 lr=0.000100 Epoch[087] Batch [2099]/[3759] Speed: 74.703449 samples/sec accuracy=79.343750 loss=0.816476 lr=0.000100 Epoch[087] Batch [2149]/[3759] Speed: 76.595141 samples/sec accuracy=79.349564 loss=0.816322 lr=0.000100 Epoch[087] Batch [2199]/[3759] Speed: 74.794035 samples/sec accuracy=79.344460 loss=0.816356 lr=0.000100 Epoch[087] Batch [2249]/[3759] Speed: 74.620240 samples/sec accuracy=79.347222 loss=0.817023 lr=0.000100 Epoch[087] Batch [2299]/[3759] Speed: 76.501883 samples/sec accuracy=79.353261 loss=0.816761 lr=0.000100 Epoch[087] 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accuracy=79.383929 loss=0.814938 lr=0.000100 Epoch[087] Batch [2849]/[3759] Speed: 77.926057 samples/sec accuracy=79.358004 loss=0.815700 lr=0.000100 Epoch[087] Batch [2899]/[3759] Speed: 76.583749 samples/sec accuracy=79.356681 loss=0.815839 lr=0.000100 Epoch[087] Batch [2949]/[3759] Speed: 74.995191 samples/sec accuracy=79.354873 loss=0.815723 lr=0.000100 Epoch[087] Batch [2999]/[3759] Speed: 75.782512 samples/sec accuracy=79.355208 loss=0.815491 lr=0.000100 Epoch[087] Batch [3049]/[3759] Speed: 76.596725 samples/sec accuracy=79.356045 loss=0.815398 lr=0.000100 Epoch[087] Batch [3099]/[3759] Speed: 73.795016 samples/sec accuracy=79.346774 loss=0.815859 lr=0.000100 Epoch[087] Batch [3149]/[3759] Speed: 76.293202 samples/sec accuracy=79.345238 loss=0.816216 lr=0.000100 Epoch[087] Batch [3199]/[3759] Speed: 75.695548 samples/sec accuracy=79.336426 loss=0.816531 lr=0.000100 Epoch[087] Batch [3249]/[3759] Speed: 75.159875 samples/sec accuracy=79.325962 loss=0.817076 lr=0.000100 Epoch[087] 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accuracy=79.337500 loss=0.816743 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.875000 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.578125 acc-top5=85.718750 Batch [0149]/[0303]: acc-top1=66.604167 acc-top5=85.822917 Batch [0199]/[0303]: acc-top1=66.867188 acc-top5=85.992188 Batch [0249]/[0303]: acc-top1=66.612500 acc-top5=85.987500 Batch [0299]/[0303]: acc-top1=66.578125 acc-top5=85.885417 [Epoch 087] training: accuracy=79.336260 loss=0.816853 [Epoch 087] speed: 75 samples/sec time cost: 3465.406507 [Epoch 087] validation: acc-top1=66.537748 acc-top5=85.906559 loss=1.626684 Epoch[088] Batch [0049]/[3760] Speed: 52.164953 samples/sec accuracy=79.843750 loss=0.790490 lr=0.000100 Epoch[088] Batch [0099]/[3760] Speed: 74.142969 samples/sec accuracy=79.718750 loss=0.798812 lr=0.000100 Epoch[088] Batch [0149]/[3760] Speed: 75.360174 samples/sec accuracy=79.718750 loss=0.802324 lr=0.000100 Epoch[088] Batch [0199]/[3760] Speed: 77.482340 samples/sec accuracy=79.789062 loss=0.801547 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lr=0.000100 Epoch[088] Batch [1199]/[3760] Speed: 76.636015 samples/sec accuracy=79.407552 loss=0.818570 lr=0.000100 Epoch[088] Batch [1249]/[3760] Speed: 75.473423 samples/sec accuracy=79.412500 loss=0.818721 lr=0.000100 Epoch[088] Batch [1299]/[3760] Speed: 76.556157 samples/sec accuracy=79.411058 loss=0.818381 lr=0.000100 Epoch[088] Batch [1349]/[3760] Speed: 75.548676 samples/sec accuracy=79.346065 loss=0.820399 lr=0.000100 Epoch[088] Batch [1399]/[3760] Speed: 74.663882 samples/sec accuracy=79.370536 loss=0.819668 lr=0.000100 Epoch[088] Batch [1449]/[3760] Speed: 76.479916 samples/sec accuracy=79.396552 loss=0.819067 lr=0.000100 Epoch[088] Batch [1499]/[3760] Speed: 75.489346 samples/sec accuracy=79.380208 loss=0.819370 lr=0.000100 Epoch[088] Batch [1549]/[3760] Speed: 77.395275 samples/sec accuracy=79.367944 loss=0.819469 lr=0.000100 Epoch[088] Batch [1599]/[3760] Speed: 73.628892 samples/sec accuracy=79.378906 loss=0.818882 lr=0.000100 Epoch[088] Batch [1649]/[3760] Speed: 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lr=0.000100 Epoch[088] Batch [2149]/[3760] Speed: 72.882901 samples/sec accuracy=79.276890 loss=0.820144 lr=0.000100 Epoch[088] Batch [2199]/[3760] Speed: 77.055973 samples/sec accuracy=79.277699 loss=0.820871 lr=0.000100 Epoch[088] Batch [2249]/[3760] Speed: 76.513473 samples/sec accuracy=79.265972 loss=0.821084 lr=0.000100 Epoch[088] Batch [2299]/[3760] Speed: 74.498368 samples/sec accuracy=79.275136 loss=0.820796 lr=0.000100 Epoch[088] Batch [2349]/[3760] Speed: 76.589141 samples/sec accuracy=79.246011 loss=0.821306 lr=0.000100 Epoch[088] Batch [2399]/[3760] Speed: 74.902707 samples/sec accuracy=79.239583 loss=0.821958 lr=0.000100 Epoch[088] Batch [2449]/[3760] Speed: 78.051612 samples/sec accuracy=79.258929 loss=0.821505 lr=0.000100 Epoch[088] Batch [2499]/[3760] Speed: 75.241887 samples/sec accuracy=79.258750 loss=0.821257 lr=0.000100 Epoch[088] Batch [2549]/[3760] Speed: 74.139712 samples/sec accuracy=79.268382 loss=0.820873 lr=0.000100 Epoch[088] Batch [2599]/[3760] Speed: 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lr=0.000100 Epoch[088] Batch [3099]/[3760] Speed: 76.906829 samples/sec accuracy=79.239415 loss=0.820773 lr=0.000100 Epoch[088] Batch [3149]/[3760] Speed: 75.937594 samples/sec accuracy=79.251984 loss=0.820574 lr=0.000100 Epoch[088] Batch [3199]/[3760] Speed: 74.882285 samples/sec accuracy=79.258301 loss=0.820402 lr=0.000100 Epoch[088] Batch [3249]/[3760] Speed: 76.749273 samples/sec accuracy=79.226442 loss=0.821190 lr=0.000100 Epoch[088] Batch [3299]/[3760] Speed: 75.852740 samples/sec accuracy=79.234848 loss=0.821147 lr=0.000100 Epoch[088] Batch [3349]/[3760] Speed: 73.193220 samples/sec accuracy=79.222481 loss=0.821353 lr=0.000100 Epoch[088] Batch [3399]/[3760] Speed: 77.523331 samples/sec accuracy=79.217831 loss=0.821473 lr=0.000100 Epoch[088] Batch [3449]/[3760] Speed: 75.934076 samples/sec accuracy=79.213315 loss=0.821635 lr=0.000100 Epoch[088] Batch [3499]/[3760] Speed: 76.233341 samples/sec accuracy=79.217411 loss=0.821603 lr=0.000100 Epoch[088] Batch [3549]/[3760] Speed: 74.198038 samples/sec accuracy=79.201585 loss=0.821897 lr=0.000100 Epoch[088] Batch [3599]/[3760] Speed: 77.486146 samples/sec accuracy=79.214410 loss=0.821591 lr=0.000100 Epoch[088] Batch [3649]/[3760] Speed: 75.227332 samples/sec accuracy=79.219606 loss=0.821703 lr=0.000100 Epoch[088] Batch [3699]/[3760] Speed: 75.404546 samples/sec accuracy=79.221706 loss=0.821373 lr=0.000100 Epoch[088] Batch [3749]/[3760] Speed: 85.697960 samples/sec accuracy=79.219167 loss=0.821231 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.437500 acc-top5=85.968750 Batch [0099]/[0303]: acc-top1=66.625000 acc-top5=85.796875 Batch [0149]/[0303]: acc-top1=66.583333 acc-top5=85.885417 Batch [0199]/[0303]: acc-top1=66.703125 acc-top5=86.132812 Batch [0249]/[0303]: acc-top1=66.575000 acc-top5=86.175000 Batch [0299]/[0303]: acc-top1=66.557292 acc-top5=86.010417 [Epoch 088] training: accuracy=79.221243 loss=0.821301 [Epoch 088] speed: 75 samples/sec time cost: 3464.577296 [Epoch 088] validation: acc-top1=66.548061 acc-top5=86.020008 loss=1.626329 Epoch[089] Batch [0049]/[3760] Speed: 52.854729 samples/sec accuracy=80.218750 loss=0.775668 lr=0.000100 Epoch[089] Batch [0099]/[3760] Speed: 72.612730 samples/sec accuracy=79.718750 loss=0.791394 lr=0.000100 Epoch[089] Batch [0149]/[3760] Speed: 77.265320 samples/sec accuracy=79.989583 loss=0.795897 lr=0.000100 Epoch[089] Batch [0199]/[3760] Speed: 75.552908 samples/sec accuracy=79.835938 loss=0.800407 lr=0.000100 Epoch[089] Batch [0249]/[3760] Speed: 74.337503 samples/sec accuracy=79.612500 loss=0.805590 lr=0.000100 Epoch[089] Batch [0299]/[3760] Speed: 77.165306 samples/sec accuracy=79.583333 loss=0.808431 lr=0.000100 Epoch[089] Batch [0349]/[3760] Speed: 75.099096 samples/sec accuracy=79.504464 loss=0.809068 lr=0.000100 Epoch[089] Batch [0399]/[3760] Speed: 75.506013 samples/sec accuracy=79.546875 loss=0.805735 lr=0.000100 Epoch[089] Batch [0449]/[3760] Speed: 76.726446 samples/sec accuracy=79.631944 loss=0.805364 lr=0.000100 Epoch[089] Batch 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accuracy=79.593750 loss=0.805600 lr=0.000100 Epoch[089] Batch [0999]/[3760] Speed: 76.127726 samples/sec accuracy=79.584375 loss=0.805882 lr=0.000100 Epoch[089] Batch [1049]/[3760] Speed: 76.855974 samples/sec accuracy=79.574405 loss=0.806500 lr=0.000100 Epoch[089] Batch [1099]/[3760] Speed: 75.544242 samples/sec accuracy=79.544034 loss=0.808220 lr=0.000100 Epoch[089] Batch [1149]/[3760] Speed: 76.562618 samples/sec accuracy=79.603261 loss=0.805699 lr=0.000100 Epoch[089] Batch [1199]/[3760] Speed: 76.859353 samples/sec accuracy=79.544271 loss=0.807284 lr=0.000100 Epoch[089] Batch [1249]/[3760] Speed: 74.858900 samples/sec accuracy=79.541250 loss=0.806897 lr=0.000100 Epoch[089] Batch [1299]/[3760] Speed: 75.807901 samples/sec accuracy=79.536058 loss=0.807263 lr=0.000100 Epoch[089] Batch [1349]/[3760] Speed: 76.489915 samples/sec accuracy=79.552083 loss=0.807694 lr=0.000100 Epoch[089] Batch [1399]/[3760] Speed: 76.244877 samples/sec accuracy=79.526786 loss=0.808566 lr=0.000100 Epoch[089] 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accuracy=79.444079 loss=0.812986 lr=0.000100 Epoch[089] Batch [1949]/[3760] Speed: 76.110435 samples/sec accuracy=79.425481 loss=0.813356 lr=0.000100 Epoch[089] Batch [1999]/[3760] Speed: 76.831853 samples/sec accuracy=79.417187 loss=0.813363 lr=0.000100 Epoch[089] Batch [2049]/[3760] Speed: 75.924356 samples/sec accuracy=79.406250 loss=0.814553 lr=0.000100 Epoch[089] Batch [2099]/[3760] Speed: 76.737800 samples/sec accuracy=79.404762 loss=0.814882 lr=0.000100 Epoch[089] Batch [2149]/[3760] Speed: 73.973297 samples/sec accuracy=79.395349 loss=0.815642 lr=0.000100 Epoch[089] Batch [2199]/[3760] Speed: 76.283756 samples/sec accuracy=79.394886 loss=0.816124 lr=0.000100 Epoch[089] Batch [2249]/[3760] Speed: 76.410735 samples/sec accuracy=79.395139 loss=0.816354 lr=0.000100 Epoch[089] Batch [2299]/[3760] Speed: 76.866633 samples/sec accuracy=79.404891 loss=0.815686 lr=0.000100 Epoch[089] Batch [2349]/[3760] Speed: 74.411516 samples/sec accuracy=79.416223 loss=0.815341 lr=0.000100 Epoch[089] 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accuracy=79.343750 loss=0.817643 lr=0.000100 Epoch[089] Batch [2899]/[3760] Speed: 75.418964 samples/sec accuracy=79.363147 loss=0.816875 lr=0.000100 Epoch[089] Batch [2949]/[3760] Speed: 75.549235 samples/sec accuracy=79.364936 loss=0.816768 lr=0.000100 Epoch[089] Batch [2999]/[3760] Speed: 75.916389 samples/sec accuracy=79.368750 loss=0.816453 lr=0.000100 Epoch[089] Batch [3049]/[3760] Speed: 77.189378 samples/sec accuracy=79.354508 loss=0.816580 lr=0.000100 Epoch[089] Batch [3099]/[3760] Speed: 74.355798 samples/sec accuracy=79.351815 loss=0.816501 lr=0.000100 Epoch[089] Batch [3149]/[3760] Speed: 76.699808 samples/sec accuracy=79.350198 loss=0.816646 lr=0.000100 Epoch[089] Batch [3199]/[3760] Speed: 75.610849 samples/sec accuracy=79.353516 loss=0.816362 lr=0.000100 Epoch[089] Batch [3249]/[3760] Speed: 76.412172 samples/sec accuracy=79.357212 loss=0.815953 lr=0.000100 Epoch[089] Batch [3299]/[3760] Speed: 74.808998 samples/sec accuracy=79.355587 loss=0.815992 lr=0.000100 Epoch[089] 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[0099]/[0303]: acc-top1=66.687500 acc-top5=85.703125 Batch [0149]/[0303]: acc-top1=66.697917 acc-top5=85.843750 Batch [0199]/[0303]: acc-top1=66.851562 acc-top5=86.085938 Batch [0249]/[0303]: acc-top1=66.600000 acc-top5=86.025000 Batch [0299]/[0303]: acc-top1=66.536458 acc-top5=85.895833 [Epoch 089] training: accuracy=79.297291 loss=0.817683 [Epoch 089] speed: 75 samples/sec time cost: 3459.621768 [Epoch 089] validation: acc-top1=66.506807 acc-top5=85.922030 loss=1.628613 Epoch[090] Batch [0049]/[3759] Speed: 53.641579 samples/sec accuracy=78.781250 loss=0.842207 lr=0.000100 Epoch[090] Batch [0099]/[3759] Speed: 72.150911 samples/sec accuracy=78.546875 loss=0.844563 lr=0.000100 Epoch[090] Batch [0149]/[3759] Speed: 77.441704 samples/sec accuracy=78.833333 loss=0.842846 lr=0.000100 Epoch[090] Batch [0199]/[3759] Speed: 75.843797 samples/sec accuracy=78.906250 loss=0.836325 lr=0.000100 Epoch[090] Batch [0249]/[3759] Speed: 76.830633 samples/sec accuracy=78.893750 loss=0.840076 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lr=0.000100 Epoch[090] Batch [1249]/[3759] Speed: 79.421887 samples/sec accuracy=79.421250 loss=0.812162 lr=0.000100 Epoch[090] Batch [1299]/[3759] Speed: 75.522546 samples/sec accuracy=79.463942 loss=0.811187 lr=0.000100 Epoch[090] Batch [1349]/[3759] Speed: 76.886666 samples/sec accuracy=79.486111 loss=0.810488 lr=0.000100 Epoch[090] Batch [1399]/[3759] Speed: 75.295638 samples/sec accuracy=79.496652 loss=0.811034 lr=0.000100 Epoch[090] Batch [1449]/[3759] Speed: 74.673970 samples/sec accuracy=79.476293 loss=0.811268 lr=0.000100 Epoch[090] Batch [1499]/[3759] Speed: 74.556905 samples/sec accuracy=79.463542 loss=0.811758 lr=0.000100 Epoch[090] Batch [1549]/[3759] Speed: 73.384747 samples/sec accuracy=79.487903 loss=0.810613 lr=0.000100 Epoch[090] Batch [1599]/[3759] Speed: 78.736964 samples/sec accuracy=79.473633 loss=0.810916 lr=0.000100 Epoch[090] Batch [1649]/[3759] Speed: 75.387196 samples/sec accuracy=79.514205 loss=0.810864 lr=0.000100 Epoch[090] Batch [1699]/[3759] Speed: 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lr=0.000100 Epoch[090] Batch [2199]/[3759] Speed: 73.142284 samples/sec accuracy=79.409801 loss=0.816430 lr=0.000100 Epoch[090] Batch [2249]/[3759] Speed: 75.741733 samples/sec accuracy=79.416667 loss=0.815742 lr=0.000100 Epoch[090] Batch [2299]/[3759] Speed: 77.117025 samples/sec accuracy=79.420516 loss=0.815712 lr=0.000100 Epoch[090] Batch [2349]/[3759] Speed: 74.755665 samples/sec accuracy=79.428191 loss=0.815487 lr=0.000100 Epoch[090] Batch [2399]/[3759] Speed: 77.857905 samples/sec accuracy=79.410156 loss=0.816261 lr=0.000100 Epoch[090] Batch [2449]/[3759] Speed: 74.104809 samples/sec accuracy=79.418367 loss=0.816229 lr=0.000100 Epoch[090] Batch [2499]/[3759] Speed: 77.946344 samples/sec accuracy=79.415000 loss=0.815792 lr=0.000100 Epoch[090] Batch [2549]/[3759] Speed: 72.777015 samples/sec accuracy=79.425858 loss=0.815836 lr=0.000100 Epoch[090] Batch [2599]/[3759] Speed: 78.571762 samples/sec accuracy=79.394231 loss=0.816393 lr=0.000100 Epoch[090] Batch [2649]/[3759] Speed: 73.642223 samples/sec accuracy=79.395047 loss=0.816311 lr=0.000100 Epoch[090] Batch [2699]/[3759] Speed: 73.638631 samples/sec accuracy=79.398727 loss=0.816224 lr=0.000100 Epoch[090] Batch [2749]/[3759] Speed: 76.554732 samples/sec accuracy=79.400568 loss=0.815954 lr=0.000100 Epoch[090] Batch [2799]/[3759] Speed: 75.484069 samples/sec accuracy=79.403460 loss=0.815886 lr=0.000100 Epoch[090] Batch [2849]/[3759] Speed: 75.145023 samples/sec accuracy=79.393092 loss=0.815892 lr=0.000100 Epoch[090] Batch [2899]/[3759] Speed: 78.163290 samples/sec accuracy=79.391703 loss=0.816040 lr=0.000100 Epoch[090] Batch [2949]/[3759] Speed: 74.557533 samples/sec accuracy=79.388242 loss=0.816731 lr=0.000100 Epoch[090] Batch [2999]/[3759] Speed: 75.431878 samples/sec accuracy=79.395833 loss=0.816613 lr=0.000100 Epoch[090] Batch [3049]/[3759] Speed: 74.556820 samples/sec accuracy=79.407787 loss=0.816413 lr=0.000100 Epoch[090] Batch [3099]/[3759] Speed: 76.222304 samples/sec accuracy=79.404738 loss=0.816528 lr=0.000100 Epoch[090] Batch [3149]/[3759] Speed: 74.544323 samples/sec accuracy=79.403274 loss=0.816725 lr=0.000100 Epoch[090] Batch [3199]/[3759] Speed: 74.528704 samples/sec accuracy=79.408203 loss=0.816832 lr=0.000100 Epoch[090] Batch [3249]/[3759] Speed: 77.976150 samples/sec accuracy=79.394231 loss=0.817332 lr=0.000100 Epoch[090] Batch [3299]/[3759] Speed: 72.246847 samples/sec accuracy=79.414299 loss=0.816562 lr=0.000100 Epoch[090] Batch [3349]/[3759] Speed: 78.332241 samples/sec accuracy=79.411847 loss=0.816820 lr=0.000100 Epoch[090] Batch [3399]/[3759] Speed: 76.023390 samples/sec accuracy=79.400276 loss=0.817152 lr=0.000100 Epoch[090] Batch [3449]/[3759] Speed: 73.376043 samples/sec accuracy=79.391757 loss=0.817193 lr=0.000100 Epoch[090] Batch [3499]/[3759] Speed: 77.888956 samples/sec accuracy=79.401786 loss=0.816747 lr=0.000100 Epoch[090] Batch [3549]/[3759] Speed: 75.402228 samples/sec accuracy=79.385123 loss=0.817589 lr=0.000100 Epoch[090] Batch [3599]/[3759] Speed: 75.179438 samples/sec accuracy=79.373698 loss=0.817862 lr=0.000100 Epoch[090] Batch [3649]/[3759] Speed: 75.761980 samples/sec accuracy=79.397688 loss=0.817137 lr=0.000100 Epoch[090] Batch [3699]/[3759] Speed: 74.929375 samples/sec accuracy=79.395693 loss=0.816707 lr=0.000100 Epoch[090] Batch [3749]/[3759] Speed: 84.069602 samples/sec accuracy=79.410000 loss=0.816157 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.250000 acc-top5=85.906250 Batch [0099]/[0303]: acc-top1=66.312500 acc-top5=85.687500 Batch [0149]/[0303]: acc-top1=66.333333 acc-top5=85.916667 Batch [0199]/[0303]: acc-top1=66.460938 acc-top5=86.125000 Batch [0249]/[0303]: acc-top1=66.337500 acc-top5=86.068750 Batch [0299]/[0303]: acc-top1=66.375000 acc-top5=85.947917 [Epoch 090] training: accuracy=79.408586 loss=0.816157 [Epoch 090] speed: 75 samples/sec time cost: 3471.601812 [Epoch 090] validation: acc-top1=66.372731 acc-top5=85.968441 loss=1.628342 Epoch[091] Batch [0049]/[3760] Speed: 54.743602 samples/sec accuracy=79.781250 loss=0.810142 lr=0.000100 Epoch[091] Batch [0099]/[3760] Speed: 71.694741 samples/sec accuracy=79.781250 loss=0.816583 lr=0.000100 Epoch[091] Batch [0149]/[3760] Speed: 76.670122 samples/sec accuracy=80.072917 loss=0.806447 lr=0.000100 Epoch[091] Batch [0199]/[3760] Speed: 76.132931 samples/sec accuracy=79.937500 loss=0.814083 lr=0.000100 Epoch[091] Batch [0249]/[3760] Speed: 75.797943 samples/sec accuracy=79.918750 loss=0.815600 lr=0.000100 Epoch[091] Batch [0299]/[3760] Speed: 76.547519 samples/sec accuracy=79.713542 loss=0.818351 lr=0.000100 Epoch[091] Batch [0349]/[3760] Speed: 75.764989 samples/sec accuracy=79.625000 loss=0.819496 lr=0.000100 Epoch[091] Batch [0399]/[3760] Speed: 74.842229 samples/sec accuracy=79.429688 loss=0.821414 lr=0.000100 Epoch[091] Batch [0449]/[3760] Speed: 76.480309 samples/sec accuracy=79.572917 loss=0.817162 lr=0.000100 Epoch[091] Batch [0499]/[3760] Speed: 75.811222 samples/sec accuracy=79.468750 loss=0.821265 lr=0.000100 Epoch[091] 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accuracy=79.634375 loss=0.815540 lr=0.000100 Epoch[091] Batch [1049]/[3760] Speed: 75.880911 samples/sec accuracy=79.596726 loss=0.815963 lr=0.000100 Epoch[091] Batch [1099]/[3760] Speed: 77.023359 samples/sec accuracy=79.580966 loss=0.815598 lr=0.000100 Epoch[091] Batch [1149]/[3760] Speed: 75.397043 samples/sec accuracy=79.615489 loss=0.814329 lr=0.000100 Epoch[091] Batch [1199]/[3760] Speed: 76.690090 samples/sec accuracy=79.625000 loss=0.813999 lr=0.000100 Epoch[091] Batch [1249]/[3760] Speed: 74.118811 samples/sec accuracy=79.610000 loss=0.814674 lr=0.000100 Epoch[091] Batch [1299]/[3760] Speed: 77.601504 samples/sec accuracy=79.618990 loss=0.814035 lr=0.000100 Epoch[091] Batch [1349]/[3760] Speed: 75.498467 samples/sec accuracy=79.628472 loss=0.814303 lr=0.000100 Epoch[091] Batch [1399]/[3760] Speed: 75.885211 samples/sec accuracy=79.636161 loss=0.813734 lr=0.000100 Epoch[091] Batch [1449]/[3760] Speed: 74.186475 samples/sec accuracy=79.599138 loss=0.814810 lr=0.000100 Epoch[091] 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accuracy=79.633013 loss=0.812028 lr=0.000100 Epoch[091] Batch [1999]/[3760] Speed: 76.031380 samples/sec accuracy=79.619531 loss=0.812797 lr=0.000100 Epoch[091] Batch [2049]/[3760] Speed: 75.679704 samples/sec accuracy=79.615854 loss=0.812921 lr=0.000100 Epoch[091] Batch [2099]/[3760] Speed: 77.591779 samples/sec accuracy=79.619792 loss=0.812456 lr=0.000100 Epoch[091] Batch [2149]/[3760] Speed: 74.998790 samples/sec accuracy=79.599564 loss=0.813299 lr=0.000100 Epoch[091] Batch [2199]/[3760] Speed: 77.116561 samples/sec accuracy=79.609375 loss=0.812930 lr=0.000100 Epoch[091] Batch [2249]/[3760] Speed: 75.441237 samples/sec accuracy=79.649306 loss=0.812643 lr=0.000100 Epoch[091] Batch [2299]/[3760] Speed: 75.709982 samples/sec accuracy=79.669837 loss=0.811852 lr=0.000100 Epoch[091] Batch [2349]/[3760] Speed: 76.201019 samples/sec accuracy=79.694814 loss=0.811077 lr=0.000100 Epoch[091] Batch [2399]/[3760] Speed: 75.227038 samples/sec accuracy=79.708984 loss=0.810758 lr=0.000100 Epoch[091] 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accuracy=79.618534 loss=0.813327 lr=0.000100 Epoch[091] Batch [2949]/[3760] Speed: 75.610181 samples/sec accuracy=79.619174 loss=0.813223 lr=0.000100 Epoch[091] Batch [2999]/[3760] Speed: 76.392159 samples/sec accuracy=79.628125 loss=0.812590 lr=0.000100 Epoch[091] Batch [3049]/[3760] Speed: 77.739623 samples/sec accuracy=79.622951 loss=0.812798 lr=0.000100 Epoch[091] Batch [3099]/[3760] Speed: 74.077516 samples/sec accuracy=79.638609 loss=0.812307 lr=0.000100 Epoch[091] Batch [3149]/[3760] Speed: 74.783396 samples/sec accuracy=79.646825 loss=0.811803 lr=0.000100 Epoch[091] Batch [3199]/[3760] Speed: 77.332848 samples/sec accuracy=79.636719 loss=0.812092 lr=0.000100 Epoch[091] Batch [3249]/[3760] Speed: 75.591044 samples/sec accuracy=79.639904 loss=0.811863 lr=0.000100 Epoch[091] Batch [3299]/[3760] Speed: 77.699187 samples/sec accuracy=79.625473 loss=0.812271 lr=0.000100 Epoch[091] Batch [3349]/[3760] Speed: 76.279986 samples/sec accuracy=79.618937 loss=0.812490 lr=0.000100 Epoch[091] Batch [3399]/[3760] Speed: 74.240923 samples/sec accuracy=79.608456 loss=0.812894 lr=0.000100 Epoch[091] Batch [3449]/[3760] Speed: 76.130837 samples/sec accuracy=79.601449 loss=0.813117 lr=0.000100 Epoch[091] Batch [3499]/[3760] Speed: 77.235726 samples/sec accuracy=79.587500 loss=0.813671 lr=0.000100 Epoch[091] Batch [3549]/[3760] Speed: 75.002794 samples/sec accuracy=79.586268 loss=0.813420 lr=0.000100 Epoch[091] Batch [3599]/[3760] Speed: 74.151862 samples/sec accuracy=79.572483 loss=0.813768 lr=0.000100 Epoch[091] Batch [3649]/[3760] Speed: 76.399338 samples/sec accuracy=79.577055 loss=0.813408 lr=0.000100 Epoch[091] Batch [3699]/[3760] Speed: 75.962627 samples/sec accuracy=79.568834 loss=0.813242 lr=0.000100 Epoch[091] Batch [3749]/[3760] Speed: 84.259517 samples/sec accuracy=79.568333 loss=0.812838 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.343750 acc-top5=85.875000 Batch [0099]/[0303]: acc-top1=66.593750 acc-top5=85.718750 Batch [0149]/[0303]: acc-top1=66.520833 acc-top5=85.812500 Batch [0199]/[0303]: acc-top1=66.679688 acc-top5=86.054688 Batch [0249]/[0303]: acc-top1=66.550000 acc-top5=85.993750 Batch [0299]/[0303]: acc-top1=66.567708 acc-top5=85.864583 [Epoch 091] training: accuracy=79.569481 loss=0.812632 [Epoch 091] speed: 75 samples/sec time cost: 3460.575294 [Epoch 091] validation: acc-top1=66.553218 acc-top5=85.875619 loss=1.626936 Epoch[092] Batch [0049]/[3760] Speed: 52.354432 samples/sec accuracy=78.468750 loss=0.846245 lr=0.000100 Epoch[092] Batch [0099]/[3760] Speed: 74.003205 samples/sec accuracy=78.593750 loss=0.845357 lr=0.000100 Epoch[092] Batch [0149]/[3760] Speed: 78.674796 samples/sec accuracy=79.250000 loss=0.826625 lr=0.000100 Epoch[092] Batch [0199]/[3760] Speed: 75.130674 samples/sec accuracy=79.484375 loss=0.821348 lr=0.000100 Epoch[092] Batch [0249]/[3760] Speed: 74.807303 samples/sec accuracy=79.556250 loss=0.815039 lr=0.000100 Epoch[092] Batch [0299]/[3760] Speed: 76.057549 samples/sec accuracy=79.598958 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accuracy=79.486250 loss=0.809071 lr=0.000100 Epoch[092] Batch [1299]/[3760] Speed: 75.709957 samples/sec accuracy=79.525240 loss=0.807514 lr=0.000100 Epoch[092] Batch [1349]/[3760] Speed: 75.621198 samples/sec accuracy=79.516204 loss=0.808184 lr=0.000100 Epoch[092] Batch [1399]/[3760] Speed: 76.156197 samples/sec accuracy=79.497768 loss=0.809646 lr=0.000100 Epoch[092] Batch [1449]/[3760] Speed: 75.975873 samples/sec accuracy=79.549569 loss=0.807493 lr=0.000100 Epoch[092] Batch [1499]/[3760] Speed: 75.369279 samples/sec accuracy=79.533333 loss=0.808747 lr=0.000100 Epoch[092] Batch [1549]/[3760] Speed: 75.801643 samples/sec accuracy=79.500000 loss=0.811007 lr=0.000100 Epoch[092] Batch [1599]/[3760] Speed: 76.132952 samples/sec accuracy=79.504883 loss=0.810737 lr=0.000100 Epoch[092] Batch [1649]/[3760] Speed: 76.957066 samples/sec accuracy=79.515152 loss=0.810611 lr=0.000100 Epoch[092] Batch [1699]/[3760] Speed: 75.320070 samples/sec accuracy=79.537684 loss=0.809707 lr=0.000100 Epoch[092] 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accuracy=79.498580 loss=0.812638 lr=0.000100 Epoch[092] Batch [2249]/[3760] Speed: 74.166552 samples/sec accuracy=79.495139 loss=0.812860 lr=0.000100 Epoch[092] Batch [2299]/[3760] Speed: 76.157930 samples/sec accuracy=79.514266 loss=0.812031 lr=0.000100 Epoch[092] Batch [2349]/[3760] Speed: 75.194325 samples/sec accuracy=79.509973 loss=0.811763 lr=0.000100 Epoch[092] Batch [2399]/[3760] Speed: 75.836715 samples/sec accuracy=79.507161 loss=0.812132 lr=0.000100 Epoch[092] Batch [2449]/[3760] Speed: 76.435961 samples/sec accuracy=79.498087 loss=0.812748 lr=0.000100 Epoch[092] Batch [2499]/[3760] Speed: 76.410948 samples/sec accuracy=79.518750 loss=0.812007 lr=0.000100 Epoch[092] Batch [2549]/[3760] Speed: 74.322226 samples/sec accuracy=79.523284 loss=0.812518 lr=0.000100 Epoch[092] Batch [2599]/[3760] Speed: 76.447727 samples/sec accuracy=79.513221 loss=0.812521 lr=0.000100 Epoch[092] Batch [2649]/[3760] Speed: 76.796352 samples/sec accuracy=79.510613 loss=0.812750 lr=0.000100 Epoch[092] 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accuracy=79.528274 loss=0.811691 lr=0.000100 Epoch[092] Batch [3199]/[3760] Speed: 74.779611 samples/sec accuracy=79.536133 loss=0.811254 lr=0.000100 Epoch[092] Batch [3249]/[3760] Speed: 76.078449 samples/sec accuracy=79.537981 loss=0.811786 lr=0.000100 Epoch[092] Batch [3299]/[3760] Speed: 75.575308 samples/sec accuracy=79.544981 loss=0.811545 lr=0.000100 Epoch[092] Batch [3349]/[3760] Speed: 76.271959 samples/sec accuracy=79.537780 loss=0.811897 lr=0.000100 Epoch[092] Batch [3399]/[3760] Speed: 74.679449 samples/sec accuracy=79.527114 loss=0.812043 lr=0.000100 Epoch[092] Batch [3449]/[3760] Speed: 76.494059 samples/sec accuracy=79.515851 loss=0.812217 lr=0.000100 Epoch[092] Batch [3499]/[3760] Speed: 76.093856 samples/sec accuracy=79.521429 loss=0.812064 lr=0.000100 Epoch[092] Batch [3549]/[3760] Speed: 74.934998 samples/sec accuracy=79.528609 loss=0.811489 lr=0.000100 Epoch[092] Batch [3599]/[3760] Speed: 77.676442 samples/sec accuracy=79.503472 loss=0.811771 lr=0.000100 Epoch[092] Batch [3649]/[3760] Speed: 76.052874 samples/sec accuracy=79.511558 loss=0.811135 lr=0.000100 Epoch[092] Batch [3699]/[3760] Speed: 75.421903 samples/sec accuracy=79.503378 loss=0.811272 lr=0.000100 Epoch[092] Batch [3749]/[3760] Speed: 84.773160 samples/sec accuracy=79.508750 loss=0.811225 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.593750 acc-top5=85.781250 Batch [0099]/[0303]: acc-top1=66.640625 acc-top5=85.656250 Batch [0149]/[0303]: acc-top1=66.625000 acc-top5=85.781250 Batch [0199]/[0303]: acc-top1=66.742188 acc-top5=86.015625 Batch [0249]/[0303]: acc-top1=66.556250 acc-top5=85.968750 Batch [0299]/[0303]: acc-top1=66.536458 acc-top5=85.890625 [Epoch 092] training: accuracy=79.503408 loss=0.811329 [Epoch 092] speed: 75 samples/sec time cost: 3461.665686 [Epoch 092] validation: acc-top1=66.511964 acc-top5=85.896246 loss=1.624581 Epoch[093] Batch [0049]/[3759] Speed: 53.111552 samples/sec accuracy=80.218750 loss=0.792444 lr=0.000100 Epoch[093] Batch [0099]/[3759] Speed: 71.621650 samples/sec accuracy=79.468750 loss=0.812424 lr=0.000100 Epoch[093] Batch [0149]/[3759] Speed: 77.592267 samples/sec accuracy=79.437500 loss=0.808774 lr=0.000100 Epoch[093] Batch [0199]/[3759] Speed: 76.201739 samples/sec accuracy=79.476562 loss=0.807053 lr=0.000100 Epoch[093] Batch [0249]/[3759] Speed: 76.324046 samples/sec accuracy=79.468750 loss=0.801233 lr=0.000100 Epoch[093] Batch [0299]/[3759] Speed: 76.148157 samples/sec accuracy=79.447917 loss=0.802676 lr=0.000100 Epoch[093] Batch [0349]/[3759] Speed: 73.635366 samples/sec accuracy=79.343750 loss=0.812639 lr=0.000100 Epoch[093] Batch [0399]/[3759] Speed: 76.611610 samples/sec accuracy=79.398438 loss=0.810548 lr=0.000100 Epoch[093] Batch [0449]/[3759] Speed: 76.458528 samples/sec accuracy=79.416667 loss=0.807913 lr=0.000100 Epoch[093] Batch [0499]/[3759] Speed: 74.954620 samples/sec accuracy=79.375000 loss=0.812373 lr=0.000100 Epoch[093] Batch [0549]/[3759] Speed: 77.074878 samples/sec accuracy=79.301136 loss=0.812824 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lr=0.000100 Epoch[093] Batch [3449]/[3759] Speed: 77.182145 samples/sec accuracy=79.595109 loss=0.808051 lr=0.000100 Epoch[093] Batch [3499]/[3759] Speed: 75.551525 samples/sec accuracy=79.608929 loss=0.807599 lr=0.000100 Epoch[093] Batch [3549]/[3759] Speed: 75.843556 samples/sec accuracy=79.599472 loss=0.808102 lr=0.000100 Epoch[093] Batch [3599]/[3759] Speed: 74.674452 samples/sec accuracy=79.598090 loss=0.808095 lr=0.000100 Epoch[093] Batch [3649]/[3759] Speed: 77.648277 samples/sec accuracy=79.601455 loss=0.808170 lr=0.000100 Epoch[093] Batch [3699]/[3759] Speed: 74.047797 samples/sec accuracy=79.603041 loss=0.808202 lr=0.000100 Epoch[093] Batch [3749]/[3759] Speed: 84.975260 samples/sec accuracy=79.612500 loss=0.807794 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.375000 acc-top5=85.937500 Batch [0099]/[0303]: acc-top1=66.546875 acc-top5=85.984375 Batch [0149]/[0303]: acc-top1=66.416667 acc-top5=85.968750 Batch [0199]/[0303]: acc-top1=66.742188 acc-top5=86.218750 Batch [0249]/[0303]: acc-top1=66.493750 acc-top5=86.143750 Batch [0299]/[0303]: acc-top1=66.484375 acc-top5=85.989583 [Epoch 093] training: accuracy=79.614342 loss=0.807850 [Epoch 093] speed: 75 samples/sec time cost: 3464.906030 [Epoch 093] validation: acc-top1=66.439769 acc-top5=85.994224 loss=1.643019 Epoch[094] Batch [0049]/[3760] Speed: 55.037028 samples/sec accuracy=80.718750 loss=0.779920 lr=0.000100 Epoch[094] Batch [0099]/[3760] Speed: 71.088216 samples/sec accuracy=80.531250 loss=0.777362 lr=0.000100 Epoch[094] Batch [0149]/[3760] Speed: 78.047925 samples/sec accuracy=80.416667 loss=0.786764 lr=0.000100 Epoch[094] Batch [0199]/[3760] Speed: 74.958109 samples/sec accuracy=79.921875 loss=0.790581 lr=0.000100 Epoch[094] Batch [0249]/[3760] Speed: 75.768949 samples/sec accuracy=79.987500 loss=0.792549 lr=0.000100 Epoch[094] Batch [0299]/[3760] Speed: 78.125135 samples/sec accuracy=79.979167 loss=0.794168 lr=0.000100 Epoch[094] Batch [0349]/[3760] Speed: 74.456900 samples/sec accuracy=79.803571 loss=0.798797 lr=0.000100 Epoch[094] Batch [0399]/[3760] Speed: 76.166637 samples/sec accuracy=79.925781 loss=0.796103 lr=0.000100 Epoch[094] Batch [0449]/[3760] Speed: 74.984194 samples/sec accuracy=79.961806 loss=0.796946 lr=0.000100 Epoch[094] Batch [0499]/[3760] Speed: 75.245231 samples/sec accuracy=79.740625 loss=0.801214 lr=0.000100 Epoch[094] Batch [0549]/[3760] Speed: 78.219183 samples/sec accuracy=79.718750 loss=0.800411 lr=0.000100 Epoch[094] Batch [0599]/[3760] Speed: 73.652189 samples/sec accuracy=79.703125 loss=0.799250 lr=0.000100 Epoch[094] Batch [0649]/[3760] Speed: 77.355348 samples/sec accuracy=79.670673 loss=0.801341 lr=0.000100 Epoch[094] Batch [0699]/[3760] Speed: 77.145664 samples/sec accuracy=79.660714 loss=0.801714 lr=0.000100 Epoch[094] Batch [0749]/[3760] Speed: 75.519152 samples/sec accuracy=79.645833 loss=0.803096 lr=0.000100 Epoch[094] Batch [0799]/[3760] Speed: 76.634142 samples/sec accuracy=79.615234 loss=0.804723 lr=0.000100 Epoch[094] Batch [0849]/[3760] Speed: 76.669136 samples/sec accuracy=79.670956 loss=0.804234 lr=0.000100 Epoch[094] Batch [0899]/[3760] Speed: 72.734904 samples/sec accuracy=79.618056 loss=0.805861 lr=0.000100 Epoch[094] Batch [0949]/[3760] Speed: 77.580515 samples/sec accuracy=79.562500 loss=0.808355 lr=0.000100 Epoch[094] Batch [0999]/[3760] Speed: 77.359378 samples/sec accuracy=79.595313 loss=0.807491 lr=0.000100 Epoch[094] Batch [1049]/[3760] Speed: 75.126808 samples/sec accuracy=79.632440 loss=0.805375 lr=0.000100 Epoch[094] Batch [1099]/[3760] Speed: 76.241723 samples/sec accuracy=79.630682 loss=0.806290 lr=0.000100 Epoch[094] Batch [1149]/[3760] Speed: 74.258209 samples/sec accuracy=79.644022 loss=0.805679 lr=0.000100 Epoch[094] Batch [1199]/[3760] Speed: 77.378717 samples/sec accuracy=79.649740 loss=0.806497 lr=0.000100 Epoch[094] Batch [1249]/[3760] Speed: 75.925771 samples/sec accuracy=79.665000 loss=0.806540 lr=0.000100 Epoch[094] Batch [1299]/[3760] Speed: 76.830330 samples/sec accuracy=79.685096 loss=0.806960 lr=0.000100 Epoch[094] Batch [1349]/[3760] Speed: 75.671815 samples/sec accuracy=79.688657 loss=0.805794 lr=0.000100 Epoch[094] Batch [1399]/[3760] Speed: 75.678554 samples/sec accuracy=79.691964 loss=0.806089 lr=0.000100 Epoch[094] Batch [1449]/[3760] Speed: 77.093457 samples/sec accuracy=79.717672 loss=0.805768 lr=0.000100 Epoch[094] Batch [1499]/[3760] Speed: 76.209094 samples/sec accuracy=79.756250 loss=0.805212 lr=0.000100 Epoch[094] Batch [1549]/[3760] Speed: 73.648469 samples/sec accuracy=79.731855 loss=0.806280 lr=0.000100 Epoch[094] Batch [1599]/[3760] Speed: 77.966150 samples/sec accuracy=79.735352 loss=0.806730 lr=0.000100 Epoch[094] Batch [1649]/[3760] Speed: 75.056919 samples/sec accuracy=79.762311 loss=0.805655 lr=0.000100 Epoch[094] Batch [1699]/[3760] Speed: 77.150005 samples/sec accuracy=79.749081 loss=0.805083 lr=0.000100 Epoch[094] Batch [1749]/[3760] Speed: 75.065968 samples/sec accuracy=79.774107 loss=0.804747 lr=0.000100 Epoch[094] 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accuracy=79.728472 loss=0.805755 lr=0.000100 Epoch[094] Batch [2299]/[3760] Speed: 76.670413 samples/sec accuracy=79.748641 loss=0.805203 lr=0.000100 Epoch[094] Batch [2349]/[3760] Speed: 74.218475 samples/sec accuracy=79.705452 loss=0.806306 lr=0.000100 Epoch[094] Batch [2399]/[3760] Speed: 78.415269 samples/sec accuracy=79.701823 loss=0.806878 lr=0.000100 Epoch[094] Batch [2449]/[3760] Speed: 73.570298 samples/sec accuracy=79.698980 loss=0.807314 lr=0.000100 Epoch[094] Batch [2499]/[3760] Speed: 77.395128 samples/sec accuracy=79.696250 loss=0.807665 lr=0.000100 Epoch[094] Batch [2549]/[3760] Speed: 77.350091 samples/sec accuracy=79.695466 loss=0.807831 lr=0.000100 Epoch[094] Batch [2599]/[3760] Speed: 75.665050 samples/sec accuracy=79.705529 loss=0.807122 lr=0.000100 Epoch[094] Batch [2649]/[3760] Speed: 76.022052 samples/sec accuracy=79.717571 loss=0.806184 lr=0.000100 Epoch[094] Batch [2699]/[3760] Speed: 74.001570 samples/sec accuracy=79.719907 loss=0.806197 lr=0.000100 Epoch[094] Batch [2749]/[3760] Speed: 76.820554 samples/sec accuracy=79.708523 loss=0.806401 lr=0.000100 Epoch[094] Batch [2799]/[3760] Speed: 73.760310 samples/sec accuracy=79.706473 loss=0.806546 lr=0.000100 Epoch[094] Batch [2849]/[3760] Speed: 78.899717 samples/sec accuracy=79.722039 loss=0.805895 lr=0.000100 Epoch[094] Batch [2899]/[3760] Speed: 75.520155 samples/sec accuracy=79.708513 loss=0.806425 lr=0.000100 Epoch[094] Batch [2949]/[3760] Speed: 75.003380 samples/sec accuracy=79.693326 loss=0.806826 lr=0.000100 Epoch[094] Batch [2999]/[3760] Speed: 78.709572 samples/sec accuracy=79.684896 loss=0.806833 lr=0.000100 Epoch[094] Batch [3049]/[3760] Speed: 74.238971 samples/sec accuracy=79.694160 loss=0.806733 lr=0.000100 Epoch[094] Batch [3099]/[3760] Speed: 76.285224 samples/sec accuracy=79.693044 loss=0.806464 lr=0.000100 Epoch[094] Batch [3149]/[3760] Speed: 76.092237 samples/sec accuracy=79.682044 loss=0.806760 lr=0.000100 Epoch[094] Batch [3199]/[3760] Speed: 73.638147 samples/sec accuracy=79.693359 loss=0.806148 lr=0.000100 Epoch[094] Batch [3249]/[3760] Speed: 76.895957 samples/sec accuracy=79.697115 loss=0.805941 lr=0.000100 Epoch[094] Batch [3299]/[3760] Speed: 77.373065 samples/sec accuracy=79.688920 loss=0.805965 lr=0.000100 Epoch[094] Batch [3349]/[3760] Speed: 74.466680 samples/sec accuracy=79.710354 loss=0.805451 lr=0.000100 Epoch[094] Batch [3399]/[3760] Speed: 75.240293 samples/sec accuracy=79.698989 loss=0.805352 lr=0.000100 Epoch[094] Batch [3449]/[3760] Speed: 75.248221 samples/sec accuracy=79.690217 loss=0.805814 lr=0.000100 Epoch[094] Batch [3499]/[3760] Speed: 77.865395 samples/sec accuracy=79.693304 loss=0.805507 lr=0.000100 Epoch[094] Batch [3549]/[3760] Speed: 74.726003 samples/sec accuracy=79.704665 loss=0.804703 lr=0.000100 Epoch[094] Batch [3599]/[3760] Speed: 76.124526 samples/sec accuracy=79.683594 loss=0.805242 lr=0.000100 Epoch[094] Batch [3649]/[3760] Speed: 75.253053 samples/sec accuracy=79.666524 loss=0.805669 lr=0.000100 Epoch[094] Batch [3699]/[3760] Speed: 77.406751 samples/sec accuracy=79.661318 loss=0.806046 lr=0.000100 Epoch[094] Batch [3749]/[3760] Speed: 83.492128 samples/sec accuracy=79.658333 loss=0.806353 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.875000 acc-top5=86.281250 Batch [0099]/[0303]: acc-top1=66.968750 acc-top5=86.062500 Batch [0149]/[0303]: acc-top1=66.822917 acc-top5=86.072917 Batch [0199]/[0303]: acc-top1=67.007812 acc-top5=86.234375 Batch [0249]/[0303]: acc-top1=66.700000 acc-top5=86.168750 Batch [0299]/[0303]: acc-top1=66.682292 acc-top5=86.057292 [Epoch 094] training: accuracy=79.662566 loss=0.806222 [Epoch 094] speed: 75 samples/sec time cost: 3455.355310 [Epoch 094] validation: acc-top1=66.656353 acc-top5=86.076733 loss=1.623792 Epoch[095] Batch [0049]/[3760] Speed: 54.434196 samples/sec accuracy=79.437500 loss=0.818422 lr=0.000100 Epoch[095] Batch [0099]/[3760] Speed: 70.841865 samples/sec accuracy=80.000000 loss=0.800303 lr=0.000100 Epoch[095] Batch [0149]/[3760] Speed: 77.220281 samples/sec accuracy=79.937500 loss=0.797275 lr=0.000100 Epoch[095] Batch [0199]/[3760] Speed: 74.732954 samples/sec accuracy=79.929688 loss=0.803931 lr=0.000100 Epoch[095] Batch [0249]/[3760] Speed: 77.638206 samples/sec accuracy=79.993750 loss=0.800864 lr=0.000100 Epoch[095] Batch [0299]/[3760] Speed: 76.580651 samples/sec accuracy=80.005208 loss=0.800663 lr=0.000100 Epoch[095] Batch [0349]/[3760] Speed: 74.614536 samples/sec accuracy=79.991071 loss=0.802728 lr=0.000100 Epoch[095] Batch [0399]/[3760] Speed: 73.826775 samples/sec accuracy=79.917969 loss=0.803307 lr=0.000100 Epoch[095] Batch [0449]/[3760] Speed: 78.215473 samples/sec accuracy=79.788194 loss=0.806037 lr=0.000100 Epoch[095] Batch [0499]/[3760] Speed: 73.720163 samples/sec accuracy=79.903125 loss=0.801261 lr=0.000100 Epoch[095] Batch [0549]/[3760] Speed: 78.715047 samples/sec accuracy=79.951705 loss=0.800267 lr=0.000100 Epoch[095] Batch [0599]/[3760] Speed: 75.497120 samples/sec accuracy=79.940104 loss=0.800609 lr=0.000100 Epoch[095] Batch [0649]/[3760] Speed: 74.246670 samples/sec accuracy=79.947115 loss=0.802009 lr=0.000100 Epoch[095] Batch [0699]/[3760] Speed: 76.799997 samples/sec accuracy=79.821429 loss=0.803345 lr=0.000100 Epoch[095] Batch [0749]/[3760] Speed: 76.853537 samples/sec accuracy=79.877083 loss=0.801713 lr=0.000100 Epoch[095] Batch [0799]/[3760] Speed: 77.689308 samples/sec accuracy=79.871094 loss=0.801541 lr=0.000100 Epoch[095] Batch [0849]/[3760] Speed: 74.291208 samples/sec accuracy=79.867647 loss=0.801087 lr=0.000100 Epoch[095] Batch [0899]/[3760] Speed: 76.070458 samples/sec accuracy=79.888889 loss=0.800238 lr=0.000100 Epoch[095] Batch [0949]/[3760] Speed: 76.585994 samples/sec accuracy=79.850329 loss=0.801086 lr=0.000100 Epoch[095] Batch [0999]/[3760] Speed: 74.435562 samples/sec accuracy=79.846875 loss=0.800987 lr=0.000100 Epoch[095] Batch [1049]/[3760] Speed: 78.355611 samples/sec accuracy=79.842262 loss=0.800487 lr=0.000100 Epoch[095] Batch [1099]/[3760] Speed: 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lr=0.000100 Epoch[095] Batch [2549]/[3760] Speed: 75.172001 samples/sec accuracy=79.804534 loss=0.799976 lr=0.000100 Epoch[095] Batch [2599]/[3760] Speed: 76.790627 samples/sec accuracy=79.806490 loss=0.800004 lr=0.000100 Epoch[095] Batch [2649]/[3760] Speed: 75.402649 samples/sec accuracy=79.804835 loss=0.800229 lr=0.000100 Epoch[095] Batch [2699]/[3760] Speed: 74.062107 samples/sec accuracy=79.825810 loss=0.799499 lr=0.000100 Epoch[095] Batch [2749]/[3760] Speed: 78.124533 samples/sec accuracy=79.819886 loss=0.799389 lr=0.000100 Epoch[095] Batch [2799]/[3760] Speed: 73.959158 samples/sec accuracy=79.803571 loss=0.799700 lr=0.000100 Epoch[095] Batch [2849]/[3760] Speed: 76.244800 samples/sec accuracy=79.801535 loss=0.799533 lr=0.000100 Epoch[095] Batch [2899]/[3760] Speed: 76.550784 samples/sec accuracy=79.775862 loss=0.800705 lr=0.000100 Epoch[095] Batch [2949]/[3760] Speed: 74.695127 samples/sec accuracy=79.772246 loss=0.800722 lr=0.000100 Epoch[095] Batch [2999]/[3760] Speed: 76.690483 samples/sec accuracy=79.778125 loss=0.800547 lr=0.000100 Epoch[095] Batch [3049]/[3760] Speed: 75.848095 samples/sec accuracy=79.759221 loss=0.801103 lr=0.000100 Epoch[095] Batch [3099]/[3760] Speed: 77.029663 samples/sec accuracy=79.747480 loss=0.801541 lr=0.000100 Epoch[095] Batch [3149]/[3760] Speed: 73.271728 samples/sec accuracy=79.748512 loss=0.801586 lr=0.000100 Epoch[095] Batch [3199]/[3760] Speed: 76.681205 samples/sec accuracy=79.736328 loss=0.802049 lr=0.000100 Epoch[095] Batch [3249]/[3760] Speed: 77.330268 samples/sec accuracy=79.762500 loss=0.801570 lr=0.000100 Epoch[095] Batch [3299]/[3760] Speed: 75.727596 samples/sec accuracy=79.770833 loss=0.801363 lr=0.000100 Epoch[095] Batch [3349]/[3760] Speed: 75.343951 samples/sec accuracy=79.773321 loss=0.801540 lr=0.000100 Epoch[095] Batch [3399]/[3760] Speed: 76.101026 samples/sec accuracy=79.787224 loss=0.801330 lr=0.000100 Epoch[095] Batch [3449]/[3760] Speed: 76.795685 samples/sec accuracy=79.778533 loss=0.801513 lr=0.000100 Epoch[095] Batch [3499]/[3760] Speed: 74.753368 samples/sec accuracy=79.796429 loss=0.801086 lr=0.000100 Epoch[095] Batch [3549]/[3760] Speed: 75.782640 samples/sec accuracy=79.780370 loss=0.801603 lr=0.000100 Epoch[095] Batch [3599]/[3760] Speed: 76.474518 samples/sec accuracy=79.763455 loss=0.802047 lr=0.000100 Epoch[095] Batch [3649]/[3760] Speed: 76.101958 samples/sec accuracy=79.762414 loss=0.802245 lr=0.000100 Epoch[095] Batch [3699]/[3760] Speed: 75.058371 samples/sec accuracy=79.750845 loss=0.802469 lr=0.000100 Epoch[095] Batch [3749]/[3760] Speed: 83.545191 samples/sec accuracy=79.740833 loss=0.802973 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.093750 acc-top5=86.156250 Batch [0099]/[0303]: acc-top1=66.406250 acc-top5=85.875000 Batch [0149]/[0303]: acc-top1=66.354167 acc-top5=85.989583 Batch [0199]/[0303]: acc-top1=66.562500 acc-top5=86.195312 Batch [0249]/[0303]: acc-top1=66.412500 acc-top5=86.093750 Batch [0299]/[0303]: acc-top1=66.421875 acc-top5=85.963542 [Epoch 095] training: accuracy=79.747340 loss=0.802834 [Epoch 095] speed: 75 samples/sec time cost: 3462.019993 [Epoch 095] validation: acc-top1=66.398515 acc-top5=85.989068 loss=1.630974 Epoch[096] Batch [0049]/[3759] Speed: 53.351826 samples/sec accuracy=79.812500 loss=0.775365 lr=0.000100 Epoch[096] Batch [0099]/[3759] Speed: 71.929720 samples/sec accuracy=79.796875 loss=0.792111 lr=0.000100 Epoch[096] Batch [0149]/[3759] Speed: 78.501240 samples/sec accuracy=79.395833 loss=0.806374 lr=0.000100 Epoch[096] Batch [0199]/[3759] Speed: 75.593228 samples/sec accuracy=79.835938 loss=0.798710 lr=0.000100 Epoch[096] Batch [0249]/[3759] Speed: 70.381194 samples/sec accuracy=79.850000 loss=0.793744 lr=0.000100 Epoch[096] Batch [0299]/[3759] Speed: 79.042237 samples/sec accuracy=79.744792 loss=0.798188 lr=0.000100 Epoch[096] Batch [0349]/[3759] Speed: 76.942287 samples/sec accuracy=79.642857 loss=0.802441 lr=0.000100 Epoch[096] Batch [0399]/[3759] Speed: 73.205244 samples/sec accuracy=79.878906 loss=0.795572 lr=0.000100 Epoch[096] Batch [0449]/[3759] Speed: 76.377228 samples/sec accuracy=80.076389 loss=0.793422 lr=0.000100 Epoch[096] Batch [0499]/[3759] Speed: 77.101240 samples/sec accuracy=80.034375 loss=0.794943 lr=0.000100 Epoch[096] Batch [0549]/[3759] Speed: 76.372830 samples/sec accuracy=79.982955 loss=0.796479 lr=0.000100 Epoch[096] Batch [0599]/[3759] Speed: 76.079959 samples/sec accuracy=79.848958 loss=0.799649 lr=0.000100 Epoch[096] Batch [0649]/[3759] Speed: 73.257209 samples/sec accuracy=79.947115 loss=0.799119 lr=0.000100 Epoch[096] Batch [0699]/[3759] Speed: 76.043938 samples/sec accuracy=79.984375 loss=0.797934 lr=0.000100 Epoch[096] Batch [0749]/[3759] Speed: 76.989580 samples/sec accuracy=79.927083 loss=0.798240 lr=0.000100 Epoch[096] Batch [0799]/[3759] Speed: 77.297587 samples/sec accuracy=79.902344 loss=0.799407 lr=0.000100 Epoch[096] Batch [0849]/[3759] Speed: 74.779312 samples/sec accuracy=79.913603 loss=0.798553 lr=0.000100 Epoch[096] Batch [0899]/[3759] Speed: 74.097910 samples/sec accuracy=79.935764 loss=0.798179 lr=0.000100 Epoch[096] Batch [0949]/[3759] Speed: 76.916088 samples/sec accuracy=79.921053 loss=0.798879 lr=0.000100 Epoch[096] Batch [0999]/[3759] Speed: 75.220110 samples/sec accuracy=79.903125 loss=0.798640 lr=0.000100 Epoch[096] Batch [1049]/[3759] Speed: 76.077607 samples/sec accuracy=79.886905 loss=0.797915 lr=0.000100 Epoch[096] Batch [1099]/[3759] Speed: 76.639755 samples/sec accuracy=79.893466 loss=0.797619 lr=0.000100 Epoch[096] Batch [1149]/[3759] Speed: 77.902282 samples/sec accuracy=79.849185 loss=0.799374 lr=0.000100 Epoch[096] Batch [1199]/[3759] Speed: 74.266377 samples/sec accuracy=79.826823 loss=0.799450 lr=0.000100 Epoch[096] Batch [1249]/[3759] Speed: 76.013575 samples/sec accuracy=79.821250 loss=0.798494 lr=0.000100 Epoch[096] Batch [1299]/[3759] Speed: 76.153927 samples/sec accuracy=79.862981 loss=0.797111 lr=0.000100 Epoch[096] Batch [1349]/[3759] Speed: 75.409399 samples/sec accuracy=79.839120 loss=0.797097 lr=0.000100 Epoch[096] Batch [1399]/[3759] Speed: 75.497838 samples/sec accuracy=79.799107 loss=0.797280 lr=0.000100 Epoch[096] Batch [1449]/[3759] Speed: 76.462613 samples/sec accuracy=79.750000 loss=0.798929 lr=0.000100 Epoch[096] Batch [1499]/[3759] Speed: 74.659092 samples/sec accuracy=79.793750 loss=0.797904 lr=0.000100 Epoch[096] Batch [1549]/[3759] Speed: 77.118436 samples/sec accuracy=79.777218 loss=0.798149 lr=0.000100 Epoch[096] Batch [1599]/[3759] Speed: 76.155735 samples/sec accuracy=79.785156 loss=0.797923 lr=0.000100 Epoch[096] Batch [1649]/[3759] Speed: 75.669973 samples/sec accuracy=79.830492 loss=0.796322 lr=0.000100 Epoch[096] Batch [1699]/[3759] Speed: 74.281813 samples/sec accuracy=79.819853 loss=0.796629 lr=0.000100 Epoch[096] Batch [1749]/[3759] Speed: 77.735653 samples/sec accuracy=79.775000 loss=0.798733 lr=0.000100 Epoch[096] Batch [1799]/[3759] Speed: 71.283154 samples/sec accuracy=79.763889 loss=0.798884 lr=0.000100 Epoch[096] Batch [1849]/[3759] Speed: 79.249743 samples/sec accuracy=79.788851 loss=0.798537 lr=0.000100 Epoch[096] Batch [1899]/[3759] Speed: 77.650401 samples/sec accuracy=79.816612 loss=0.797637 lr=0.000100 Epoch[096] Batch [1949]/[3759] Speed: 75.472411 samples/sec accuracy=79.814103 loss=0.798223 lr=0.000100 Epoch[096] Batch [1999]/[3759] Speed: 75.659247 samples/sec accuracy=79.775000 loss=0.799040 lr=0.000100 Epoch[096] Batch [2049]/[3759] Speed: 74.864983 samples/sec accuracy=79.804878 loss=0.798578 lr=0.000100 Epoch[096] Batch [2099]/[3759] Speed: 78.134608 samples/sec accuracy=79.802083 loss=0.798646 lr=0.000100 Epoch[096] Batch [2149]/[3759] Speed: 74.577367 samples/sec accuracy=79.811773 loss=0.798232 lr=0.000100 Epoch[096] Batch [2199]/[3759] Speed: 76.141934 samples/sec accuracy=79.796165 loss=0.799304 lr=0.000100 Epoch[096] Batch [2249]/[3759] Speed: 75.879848 samples/sec accuracy=79.800000 loss=0.799354 lr=0.000100 Epoch[096] Batch [2299]/[3759] Speed: 74.792493 samples/sec accuracy=79.800272 loss=0.799096 lr=0.000100 Epoch[096] Batch [2349]/[3759] Speed: 77.210573 samples/sec accuracy=79.801862 loss=0.799535 lr=0.000100 Epoch[096] Batch [2399]/[3759] Speed: 74.608268 samples/sec accuracy=79.773438 loss=0.800275 lr=0.000100 Epoch[096] Batch [2449]/[3759] Speed: 77.472561 samples/sec accuracy=79.782526 loss=0.800543 lr=0.000100 Epoch[096] Batch [2499]/[3759] Speed: 76.055006 samples/sec accuracy=79.783750 loss=0.800551 lr=0.000100 Epoch[096] Batch [2549]/[3759] Speed: 75.230397 samples/sec accuracy=79.780025 loss=0.800512 lr=0.000100 Epoch[096] Batch [2599]/[3759] Speed: 75.090460 samples/sec accuracy=79.792668 loss=0.799826 lr=0.000100 Epoch[096] Batch [2649]/[3759] Speed: 77.685400 samples/sec accuracy=79.791274 loss=0.799534 lr=0.000100 Epoch[096] Batch [2699]/[3759] Speed: 77.015626 samples/sec accuracy=79.800926 loss=0.799489 lr=0.000100 Epoch[096] Batch [2749]/[3759] Speed: 74.782286 samples/sec accuracy=79.800000 loss=0.799164 lr=0.000100 Epoch[096] Batch [2799]/[3759] Speed: 76.172841 samples/sec accuracy=79.794643 loss=0.799532 lr=0.000100 Epoch[096] Batch [2849]/[3759] Speed: 75.791122 samples/sec accuracy=79.779057 loss=0.799963 lr=0.000100 Epoch[096] Batch [2899]/[3759] Speed: 75.003990 samples/sec accuracy=79.784483 loss=0.799527 lr=0.000100 Epoch[096] Batch [2949]/[3759] Speed: 75.593818 samples/sec accuracy=79.777542 loss=0.799628 lr=0.000100 Epoch[096] Batch [2999]/[3759] Speed: 76.429310 samples/sec accuracy=79.778646 loss=0.799773 lr=0.000100 Epoch[096] Batch [3049]/[3759] Speed: 76.351562 samples/sec accuracy=79.777152 loss=0.800133 lr=0.000100 Epoch[096] Batch [3099]/[3759] Speed: 74.208161 samples/sec accuracy=79.777218 loss=0.799956 lr=0.000100 Epoch[096] Batch [3149]/[3759] Speed: 77.160368 samples/sec accuracy=79.771329 loss=0.799888 lr=0.000100 Epoch[096] Batch [3199]/[3759] Speed: 77.123485 samples/sec accuracy=79.778809 loss=0.799818 lr=0.000100 Epoch[096] Batch [3249]/[3759] Speed: 75.030806 samples/sec accuracy=79.778846 loss=0.799868 lr=0.000100 Epoch[096] Batch [3299]/[3759] Speed: 75.493061 samples/sec accuracy=79.777462 loss=0.800648 lr=0.000100 Epoch[096] Batch [3349]/[3759] Speed: 75.935112 samples/sec accuracy=79.764925 loss=0.800885 lr=0.000100 Epoch[096] Batch [3399]/[3759] Speed: 74.968007 samples/sec accuracy=79.757353 loss=0.801527 lr=0.000100 Epoch[096] Batch [3449]/[3759] Speed: 76.560246 samples/sec accuracy=79.750453 loss=0.802145 lr=0.000100 Epoch[096] Batch [3499]/[3759] Speed: 75.061045 samples/sec accuracy=79.740179 loss=0.802600 lr=0.000100 Epoch[096] Batch [3549]/[3759] Speed: 77.242123 samples/sec accuracy=79.729313 loss=0.803321 lr=0.000100 Epoch[096] Batch [3599]/[3759] Speed: 76.450886 samples/sec accuracy=79.728733 loss=0.803510 lr=0.000100 Epoch[096] Batch [3649]/[3759] Speed: 73.576419 samples/sec accuracy=79.729452 loss=0.803588 lr=0.000100 Epoch[096] Batch [3699]/[3759] Speed: 77.267857 samples/sec accuracy=79.730152 loss=0.803555 lr=0.000100 Epoch[096] Batch [3749]/[3759] Speed: 85.690644 samples/sec accuracy=79.727917 loss=0.803591 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.500000 acc-top5=86.187500 Batch [0099]/[0303]: acc-top1=66.562500 acc-top5=85.968750 Batch [0149]/[0303]: acc-top1=66.437500 acc-top5=85.937500 Batch [0199]/[0303]: acc-top1=66.585938 acc-top5=86.093750 Batch [0249]/[0303]: acc-top1=66.362500 acc-top5=86.068750 Batch [0299]/[0303]: acc-top1=66.416667 acc-top5=85.973958 [Epoch 096] training: accuracy=79.734055 loss=0.803425 [Epoch 096] speed: 75 samples/sec time cost: 3459.707170 [Epoch 096] validation: acc-top1=66.408828 acc-top5=85.994224 loss=1.632166 Epoch[097] Batch [0049]/[3760] Speed: 53.624088 samples/sec accuracy=79.468750 loss=0.803061 lr=0.000100 Epoch[097] Batch [0099]/[3760] Speed: 71.065161 samples/sec accuracy=79.328125 loss=0.816020 lr=0.000100 Epoch[097] Batch [0149]/[3760] Speed: 77.558024 samples/sec accuracy=79.541667 loss=0.815668 lr=0.000100 Epoch[097] Batch [0199]/[3760] Speed: 77.382320 samples/sec accuracy=79.601562 loss=0.816977 lr=0.000100 Epoch[097] Batch [0249]/[3760] Speed: 74.448386 samples/sec accuracy=79.637500 loss=0.810367 lr=0.000100 Epoch[097] Batch [0299]/[3760] Speed: 77.868278 samples/sec accuracy=79.708333 loss=0.804155 lr=0.000100 Epoch[097] Batch [0349]/[3760] Speed: 75.011864 samples/sec accuracy=79.834821 loss=0.800233 lr=0.000100 Epoch[097] Batch [0399]/[3760] Speed: 74.816272 samples/sec accuracy=79.832031 loss=0.797820 lr=0.000100 Epoch[097] Batch [0449]/[3760] Speed: 74.111331 samples/sec accuracy=79.854167 loss=0.798010 lr=0.000100 Epoch[097] Batch [0499]/[3760] Speed: 79.126249 samples/sec accuracy=79.843750 loss=0.798066 lr=0.000100 Epoch[097] Batch [0549]/[3760] Speed: 73.858057 samples/sec accuracy=79.744318 loss=0.801641 lr=0.000100 Epoch[097] Batch [0599]/[3760] Speed: 77.392854 samples/sec accuracy=79.765625 loss=0.800568 lr=0.000100 Epoch[097] Batch [0649]/[3760] Speed: 75.914653 samples/sec accuracy=79.706731 loss=0.803304 lr=0.000100 Epoch[097] Batch [0699]/[3760] Speed: 74.810095 samples/sec accuracy=79.716518 loss=0.802832 lr=0.000100 Epoch[097] Batch [0749]/[3760] Speed: 75.388579 samples/sec accuracy=79.756250 loss=0.800368 lr=0.000100 Epoch[097] Batch [0799]/[3760] Speed: 77.396540 samples/sec accuracy=79.708984 loss=0.801658 lr=0.000100 Epoch[097] Batch [0849]/[3760] Speed: 74.015120 samples/sec accuracy=79.735294 loss=0.799948 lr=0.000100 Epoch[097] Batch [0899]/[3760] Speed: 74.125511 samples/sec accuracy=79.751736 loss=0.797541 lr=0.000100 Epoch[097] Batch [0949]/[3760] Speed: 76.927306 samples/sec accuracy=79.784539 loss=0.795402 lr=0.000100 Epoch[097] Batch [0999]/[3760] Speed: 78.526048 samples/sec accuracy=79.787500 loss=0.796125 lr=0.000100 Epoch[097] Batch [1049]/[3760] Speed: 74.778330 samples/sec accuracy=79.819940 loss=0.795374 lr=0.000100 Epoch[097] Batch [1099]/[3760] Speed: 77.586385 samples/sec accuracy=79.806818 loss=0.796233 lr=0.000100 Epoch[097] Batch [1149]/[3760] Speed: 73.855836 samples/sec accuracy=79.790761 loss=0.796488 lr=0.000100 Epoch[097] Batch [1199]/[3760] Speed: 76.765667 samples/sec accuracy=79.809896 loss=0.796716 lr=0.000100 Epoch[097] Batch [1249]/[3760] Speed: 75.408883 samples/sec accuracy=79.823750 loss=0.796195 lr=0.000100 Epoch[097] Batch [1299]/[3760] Speed: 74.729668 samples/sec accuracy=79.812500 loss=0.796879 lr=0.000100 Epoch[097] Batch [1349]/[3760] Speed: 77.174750 samples/sec accuracy=79.841435 loss=0.796211 lr=0.000100 Epoch[097] Batch [1399]/[3760] Speed: 76.750456 samples/sec accuracy=79.852679 loss=0.794742 lr=0.000100 Epoch[097] Batch [1449]/[3760] Speed: 75.276553 samples/sec accuracy=79.899784 loss=0.793487 lr=0.000100 Epoch[097] Batch [1499]/[3760] Speed: 77.117311 samples/sec accuracy=79.922917 loss=0.792690 lr=0.000100 Epoch[097] Batch [1549]/[3760] Speed: 73.543980 samples/sec accuracy=79.954637 loss=0.792316 lr=0.000100 Epoch[097] Batch [1599]/[3760] Speed: 77.625528 samples/sec accuracy=79.889648 loss=0.793768 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lr=0.000100 Epoch[097] Batch [3549]/[3760] Speed: 77.710846 samples/sec accuracy=79.690581 loss=0.801022 lr=0.000100 Epoch[097] Batch [3599]/[3760] Speed: 72.711896 samples/sec accuracy=79.703125 loss=0.800791 lr=0.000100 Epoch[097] Batch [3649]/[3760] Speed: 76.744761 samples/sec accuracy=79.699058 loss=0.800726 lr=0.000100 Epoch[097] Batch [3699]/[3760] Speed: 77.083420 samples/sec accuracy=79.703970 loss=0.800464 lr=0.000100 Epoch[097] Batch [3749]/[3760] Speed: 83.399775 samples/sec accuracy=79.703333 loss=0.800342 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.718750 acc-top5=86.375000 Batch [0099]/[0303]: acc-top1=66.687500 acc-top5=85.921875 Batch [0149]/[0303]: acc-top1=66.593750 acc-top5=85.968750 Batch [0199]/[0303]: acc-top1=66.757812 acc-top5=86.140625 Batch [0249]/[0303]: acc-top1=66.562500 acc-top5=86.100000 Batch [0299]/[0303]: acc-top1=66.588542 acc-top5=85.989583 [Epoch 097] training: accuracy=79.701213 loss=0.800435 [Epoch 097] speed: 75 samples/sec time cost: 3461.550852 [Epoch 097] validation: acc-top1=66.579002 acc-top5=86.009695 loss=1.626888 Epoch[098] Batch [0049]/[3759] Speed: 54.102074 samples/sec accuracy=78.937500 loss=0.819909 lr=0.000100 Epoch[098] Batch [0099]/[3759] Speed: 70.318930 samples/sec accuracy=79.718750 loss=0.797743 lr=0.000100 Epoch[098] Batch [0149]/[3759] Speed: 76.558295 samples/sec accuracy=79.427083 loss=0.810099 lr=0.000100 Epoch[098] Batch [0199]/[3759] Speed: 77.675071 samples/sec accuracy=79.757812 loss=0.803194 lr=0.000100 Epoch[098] Batch [0249]/[3759] Speed: 75.973051 samples/sec accuracy=79.868750 loss=0.802079 lr=0.000100 Epoch[098] Batch [0299]/[3759] Speed: 73.450814 samples/sec accuracy=79.963542 loss=0.798333 lr=0.000100 Epoch[098] Batch [0349]/[3759] Speed: 75.216297 samples/sec accuracy=79.991071 loss=0.794025 lr=0.000100 Epoch[098] Batch [0399]/[3759] Speed: 78.133073 samples/sec accuracy=80.003906 loss=0.793577 lr=0.000100 Epoch[098] Batch [0449]/[3759] Speed: 76.801776 samples/sec accuracy=79.871528 loss=0.793057 lr=0.000100 Epoch[098] Batch [0499]/[3759] Speed: 74.522013 samples/sec accuracy=79.693750 loss=0.799188 lr=0.000100 Epoch[098] Batch [0549]/[3759] Speed: 76.065032 samples/sec accuracy=79.775568 loss=0.797199 lr=0.000100 Epoch[098] Batch [0599]/[3759] Speed: 76.044727 samples/sec accuracy=79.809896 loss=0.798146 lr=0.000100 Epoch[098] Batch [0649]/[3759] Speed: 74.891888 samples/sec accuracy=79.899038 loss=0.795432 lr=0.000100 Epoch[098] Batch [0699]/[3759] Speed: 77.432053 samples/sec accuracy=79.910714 loss=0.793863 lr=0.000100 Epoch[098] Batch [0749]/[3759] Speed: 75.538294 samples/sec accuracy=79.922917 loss=0.792104 lr=0.000100 Epoch[098] Batch [0799]/[3759] Speed: 72.720707 samples/sec accuracy=79.941406 loss=0.793716 lr=0.000100 Epoch[098] Batch [0849]/[3759] Speed: 77.826032 samples/sec accuracy=79.898897 loss=0.796368 lr=0.000100 Epoch[098] Batch [0899]/[3759] Speed: 77.685868 samples/sec accuracy=79.883681 loss=0.797273 lr=0.000100 Epoch[098] 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accuracy=79.841518 loss=0.799727 lr=0.000100 Epoch[098] Batch [1449]/[3759] Speed: 73.931860 samples/sec accuracy=79.814655 loss=0.801019 lr=0.000100 Epoch[098] Batch [1499]/[3759] Speed: 75.196304 samples/sec accuracy=79.860417 loss=0.800130 lr=0.000100 Epoch[098] Batch [1549]/[3759] Speed: 77.124620 samples/sec accuracy=79.831653 loss=0.801366 lr=0.000100 Epoch[098] Batch [1599]/[3759] Speed: 77.191631 samples/sec accuracy=79.845703 loss=0.800731 lr=0.000100 Epoch[098] Batch [1649]/[3759] Speed: 74.562499 samples/sec accuracy=79.841856 loss=0.799636 lr=0.000100 Epoch[098] Batch [1699]/[3759] Speed: 76.858195 samples/sec accuracy=79.791360 loss=0.801484 lr=0.000100 Epoch[098] Batch [1749]/[3759] Speed: 74.813302 samples/sec accuracy=79.816964 loss=0.800616 lr=0.000100 Epoch[098] Batch [1799]/[3759] Speed: 76.650570 samples/sec accuracy=79.803819 loss=0.801574 lr=0.000100 Epoch[098] Batch [1849]/[3759] Speed: 76.037152 samples/sec accuracy=79.781250 loss=0.802222 lr=0.000100 Epoch[098] 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accuracy=79.783245 loss=0.801111 lr=0.000100 Epoch[098] Batch [2399]/[3759] Speed: 75.178936 samples/sec accuracy=79.799479 loss=0.800701 lr=0.000100 Epoch[098] Batch [2449]/[3759] Speed: 75.029591 samples/sec accuracy=79.808036 loss=0.800636 lr=0.000100 Epoch[098] Batch [2499]/[3759] Speed: 75.973256 samples/sec accuracy=79.800000 loss=0.800931 lr=0.000100 Epoch[098] Batch [2549]/[3759] Speed: 73.588796 samples/sec accuracy=79.808824 loss=0.800619 lr=0.000100 Epoch[098] Batch [2599]/[3759] Speed: 79.318940 samples/sec accuracy=79.806490 loss=0.800768 lr=0.000100 Epoch[098] Batch [2649]/[3759] Speed: 76.183463 samples/sec accuracy=79.799528 loss=0.801512 lr=0.000100 Epoch[098] Batch [2699]/[3759] Speed: 74.867869 samples/sec accuracy=79.787616 loss=0.801734 lr=0.000100 Epoch[098] Batch [2749]/[3759] Speed: 77.748875 samples/sec accuracy=79.776136 loss=0.801851 lr=0.000100 Epoch[098] Batch [2799]/[3759] Speed: 73.106983 samples/sec accuracy=79.801339 loss=0.801343 lr=0.000100 Epoch[098] 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accuracy=79.770833 loss=0.802190 lr=0.000100 Epoch[098] Batch [3349]/[3759] Speed: 75.555471 samples/sec accuracy=79.765392 loss=0.802528 lr=0.000100 Epoch[098] Batch [3399]/[3759] Speed: 76.333608 samples/sec accuracy=79.786305 loss=0.801742 lr=0.000100 Epoch[098] Batch [3449]/[3759] Speed: 76.577945 samples/sec accuracy=79.786232 loss=0.801539 lr=0.000100 Epoch[098] Batch [3499]/[3759] Speed: 71.719043 samples/sec accuracy=79.789732 loss=0.801127 lr=0.000100 Epoch[098] Batch [3549]/[3759] Speed: 79.231328 samples/sec accuracy=79.784771 loss=0.801374 lr=0.000100 Epoch[098] Batch [3599]/[3759] Speed: 71.794729 samples/sec accuracy=79.780816 loss=0.801603 lr=0.000100 Epoch[098] Batch [3649]/[3759] Speed: 79.181191 samples/sec accuracy=79.783390 loss=0.801313 lr=0.000100 Epoch[098] Batch [3699]/[3759] Speed: 77.175779 samples/sec accuracy=79.778716 loss=0.801480 lr=0.000100 Epoch[098] Batch [3749]/[3759] Speed: 84.136416 samples/sec accuracy=79.788333 loss=0.801150 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.750000 acc-top5=85.843750 Batch [0099]/[0303]: acc-top1=66.796875 acc-top5=85.734375 Batch [0149]/[0303]: acc-top1=66.750000 acc-top5=85.750000 Batch [0199]/[0303]: acc-top1=66.773438 acc-top5=85.992188 Batch [0249]/[0303]: acc-top1=66.618750 acc-top5=85.937500 Batch [0299]/[0303]: acc-top1=66.656250 acc-top5=85.828125 [Epoch 098] training: accuracy=79.787676 loss=0.801168 [Epoch 098] speed: 75 samples/sec time cost: 3462.891107 [Epoch 098] validation: acc-top1=66.661510 acc-top5=85.844678 loss=1.626292 Epoch[099] Batch [0049]/[3760] Speed: 53.365069 samples/sec accuracy=79.093750 loss=0.847898 lr=0.000100 Epoch[099] Batch [0099]/[3760] Speed: 72.816105 samples/sec accuracy=78.828125 loss=0.859573 lr=0.000100 Epoch[099] Batch [0149]/[3760] Speed: 76.276760 samples/sec accuracy=78.854167 loss=0.858727 lr=0.000100 Epoch[099] Batch [0199]/[3760] Speed: 77.186837 samples/sec accuracy=79.148438 loss=0.844359 lr=0.000100 Epoch[099] Batch [0249]/[3760] Speed: 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75.056438 samples/sec accuracy=79.849564 loss=0.796209 lr=0.000100 Epoch[099] Batch [2199]/[3760] Speed: 76.742077 samples/sec accuracy=79.869318 loss=0.795104 lr=0.000100 Epoch[099] Batch [2249]/[3760] Speed: 77.410605 samples/sec accuracy=79.891667 loss=0.794117 lr=0.000100 Epoch[099] Batch [2299]/[3760] Speed: 73.347462 samples/sec accuracy=79.901495 loss=0.793759 lr=0.000100 Epoch[099] Batch [2349]/[3760] Speed: 76.225447 samples/sec accuracy=79.918218 loss=0.793288 lr=0.000100 Epoch[099] Batch [2399]/[3760] Speed: 76.342722 samples/sec accuracy=79.935547 loss=0.792562 lr=0.000100 Epoch[099] Batch [2449]/[3760] Speed: 75.863995 samples/sec accuracy=79.950255 loss=0.792375 lr=0.000100 Epoch[099] Batch [2499]/[3760] Speed: 75.184066 samples/sec accuracy=79.955625 loss=0.792389 lr=0.000100 Epoch[099] Batch [2549]/[3760] Speed: 76.555065 samples/sec accuracy=79.937500 loss=0.793148 lr=0.000100 Epoch[099] Batch [2599]/[3760] Speed: 75.033223 samples/sec accuracy=79.942909 loss=0.793068 lr=0.000100 Epoch[099] Batch [2649]/[3760] Speed: 77.738855 samples/sec accuracy=79.932193 loss=0.793980 lr=0.000100 Epoch[099] Batch [2699]/[3760] Speed: 75.368652 samples/sec accuracy=79.951968 loss=0.793429 lr=0.000100 Epoch[099] Batch [2749]/[3760] Speed: 76.335862 samples/sec accuracy=79.960227 loss=0.792853 lr=0.000100 Epoch[099] Batch [2799]/[3760] Speed: 75.611338 samples/sec accuracy=79.965960 loss=0.792421 lr=0.000100 Epoch[099] Batch [2849]/[3760] Speed: 75.152367 samples/sec accuracy=79.939693 loss=0.793229 lr=0.000100 Epoch[099] Batch [2899]/[3760] Speed: 77.134388 samples/sec accuracy=79.928341 loss=0.793489 lr=0.000100 Epoch[099] Batch [2949]/[3760] Speed: 73.293155 samples/sec accuracy=79.923199 loss=0.794061 lr=0.000100 Epoch[099] Batch [2999]/[3760] Speed: 77.459656 samples/sec accuracy=79.931771 loss=0.793974 lr=0.000100 Epoch[099] Batch [3049]/[3760] Speed: 71.444534 samples/sec accuracy=79.924693 loss=0.794131 lr=0.000100 Epoch[099] Batch [3099]/[3760] Speed: 79.031721 samples/sec accuracy=79.918851 loss=0.794602 lr=0.000100 Epoch[099] Batch [3149]/[3760] Speed: 76.730205 samples/sec accuracy=79.904762 loss=0.794979 lr=0.000100 Epoch[099] Batch [3199]/[3760] Speed: 75.276891 samples/sec accuracy=79.896484 loss=0.794992 lr=0.000100 Epoch[099] Batch [3249]/[3760] Speed: 75.995112 samples/sec accuracy=79.925481 loss=0.794152 lr=0.000100 Epoch[099] Batch [3299]/[3760] Speed: 75.568624 samples/sec accuracy=79.936553 loss=0.794085 lr=0.000100 Epoch[099] Batch [3349]/[3760] Speed: 76.970893 samples/sec accuracy=79.952892 loss=0.793863 lr=0.000100 Epoch[099] Batch [3399]/[3760] Speed: 77.216071 samples/sec accuracy=79.977482 loss=0.792952 lr=0.000100 Epoch[099] Batch [3449]/[3760] Speed: 75.516335 samples/sec accuracy=79.969656 loss=0.793094 lr=0.000100 Epoch[099] Batch [3499]/[3760] Speed: 74.305737 samples/sec accuracy=79.973214 loss=0.792791 lr=0.000100 Epoch[099] Batch [3549]/[3760] Speed: 75.872915 samples/sec accuracy=79.975352 loss=0.792771 lr=0.000100 Epoch[099] Batch [3599]/[3760] Speed: 74.340867 samples/sec accuracy=79.967448 loss=0.793269 lr=0.000100 Epoch[099] Batch [3649]/[3760] Speed: 78.593372 samples/sec accuracy=79.968750 loss=0.793426 lr=0.000100 Epoch[099] Batch [3699]/[3760] Speed: 75.849990 samples/sec accuracy=79.950169 loss=0.794175 lr=0.000100 Epoch[099] Batch [3749]/[3760] Speed: 82.952630 samples/sec accuracy=79.960417 loss=0.794049 lr=0.000100 Batch [0049]/[0303]: acc-top1=66.625000 acc-top5=86.000000 Batch [0099]/[0303]: acc-top1=66.812500 acc-top5=85.812500 Batch [0149]/[0303]: acc-top1=66.750000 acc-top5=85.895833 Batch [0199]/[0303]: acc-top1=66.867188 acc-top5=86.109375 Batch [0249]/[0303]: acc-top1=66.568750 acc-top5=86.100000 Batch [0299]/[0303]: acc-top1=66.609375 acc-top5=85.968750 [Epoch 099] training: accuracy=79.960106 loss=0.794099 [Epoch 099] speed: 75 samples/sec time cost: 3461.229136 [Epoch 099] validation: acc-top1=66.589315 acc-top5=85.983911 loss=1.625288